bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on BP neural network model-based data mining technique in KOL identification
Authors: Hou Jiarui , Li Tianyu , Wu Yahui , Wang Pei
Published: November 2024

Abstract. Accompanied by the development of artificial intelligence industry, to play the data value of web crawler technology has been the focus of research in the field of computer network and data science, and the data mining technology based on artificial neural network intelligent algorithm is widely used. In view of this, this paper takes the BP neural network data mining technology, which has excellent nonlinear mapping capability, parallel processing capability and fault tolerance and is widely used, as the basis, and integrates the methods and ideas of data mining into the mining of data laws in the field of KOL identification of key opinion leaders, with a view to finding valuable intrinsic laws and relationships between the mining of web crawler technology and the identification of KOL features. The research content of this paper mainly includes two aspects of research work, the design of high-performance data mining technology and the actual work in the field of KOL recognition. On the one hand, this paper comprehensively describes the basic theory and methods of data mining, and focuses on the in-depth analysis and elaboration of BP neural network-based data mining technology on the basis of understanding and analyzing a variety of data mining technologies. On the other hand, this paper aims to solve the problem of bias in the prediction of traditional KOL model and design the experimental method of KOL recognition by BP neural network algorithm.
Exploring Spotify's Music Popularity Dynamics and Forecasting with Machine Learning
Authors: Shu Miaomiao
Published: November 2024

Abstract. Spotify, one of the largest music streaming service providers, boasts a vast user base and an extensive music catalog. To gain a deeper understanding of Spotify users' music preferences and behavioral patterns, this paper conducts a thorough analysis and explores the correlation between music features and user behavior. It collects Spotify users' music listening data and extracts various music features such as energy, danceability, valence, and beats per minute (BPM). These features not only reflect the musical style and rhythm but also potentially correlate with users' preferences and listening habits. Then we employ two machine learning models, Decision Trees and Random Forests, to model and analyze Spotify users' behavior data. Through these models, we can accurately identify potential relationships between music features and user behavior. The experimental results indicate that music features such as energy, danceability, valence, and BPM have a significant impact on users' music selection and preferences. By analyzing the most popular songs on Spotify over different time periods, we discover that songs with high energy, danceability, and valence tend to be more popular among users. This finding not only validates the correlation between music features and user behavior but also reveals the user preferences and market demands behind music trends. For music streaming service providers, understanding users' music preferences and behavioral patterns is crucial. By deeply analyzing user data, music streaming services can better satisfy users' needs, enhance user experience, and stand out in the fiercely competitive market. These findings have important practical implications for music streaming service providers and provide new insights and methodologies for the research and development of the music industry.
ATPAM: Adversarial Temporal Pattern Attention Mechanism
Authors: Huang Luyao
Published: November 2024

Abstract. Time series forecasting has a large number of applications in daily life, for instance the prediction of stock prices, electricity consumption, exchange rate changes etc. However, the existing time series prediction methods have limitations. The most significant one is that when all the prediction models get the predicted value, a new round of iteration starts after the loss function is calculated with the corresponding real data. This may cause the accumulation of errors, since there is only one loss function to measure the difference between the predicted value and the ground truth, it will make the connection weak and mainly depend on the accuracy of the prediction model. Unfortunately, there are few time series prediction models with high accuracy in reality. To solve the issue, in this paper, we propose a new time series forecasting model Adversarial Temporal Pattern Attention Mechanism (ATPAM), which based on Generative Adversarial Nets (GANs). ATPAM adopts a Temporal Pattern Attention model as the generator to learn time-invariant temporal patterns, and use a discriminator to improve the prediction performance and do auxiliary adversarial training. Extensive experiments on several real-world datasets show the effectiveness of our method.
How Seam Inclination Influences Cricket Ball Swing
Authors: Li Tianyu
Published: November 2024

Abstract. Cricket, a sport with origins in 16th century England, involves players attempting to manipulate the lateral motion of the ball to outwit the batsman. This is often achieved by adjusting the seam inclination or altering the ball's surface roughness. This paper specifically investigates how seam inclination affects cricket ball swing through computational fluid dynamics (CFD) simulations. The focus of the study is on conventional swing for both non-rotational and rotational cricket balls. The results indicate that seam inclination significantly influences swing, with an optimal angle between 58 to 60 degrees for the maximum lateral force of non-rotational cricket. This finding provides valuable insights into the mechanics of conventional swing and offers guidelines for bowlers to enhance their performance. The research explores the complex interplay between the ball's aerodynamics, seam inclination, and the resulting swing. By utilizing CFD simulations, the study delves into the underlying fluid dynamics that govern the ball's trajectory and the generation of lateral forces.
An evaluate of ORR catalysts in fuel cell: Current Advances and Applications
Authors: Hu Qingyuan
Published: November 2024

Abstract. This thesis presents a comprehensive review of fuel cell technology, with a specific emphasis at the latest trends and programs of oxygen reduction response (ORR) catalysts. The examine starts offevolved with the aid of using evaluating the benefits and drawbacks of hydrogen fuel cells with different alternative power sources, which include sun power and secondary batteries, highlighting the ability of fuel cells to update traditional inner combustion engines because of their high power density and environmental benefits. The thesis then explores the essential running ideas of fuel cells and examines their operational mechanisms in numerous chemical environments. In the context of ORR catalysts, the assessment evaluates quite a number catalysts, which include precious metal catalysts, non-precious metal catalysts, and single-atom catalysts, that specialize in techniques to decorate their activity and stability. Finally, the thesis discusses the demanding situations and destiny possibilities for the industrial application of ORR catalysts in hydrogen fuel cells.
Design and Construction of Experimental System for Validation of a New Image Reconstruction Technique with Limited-view-angle Projection Data for BNCT-SPECT
Authors: Lu Fan , Okuda Kouki , Tamaki Shingo , Kusaka Sachie , Murata Isao
Published: November 2024

Abstract. Boron Neutron Capture Therapy (BNCT) is expected to be a promising radiation therapy for cancer, and research on various issues associated with it is still in progress. One of the unsolved issues is the construction of a system for observing the effect of the treatment (local boron dose) in real time under high-background circumstances. Thus, we set out to establish a method for measuring gamma-rays emitted promptly from the body following the boron neutron capture reaction and reconstructing images in a SPECT-like manner. We call this method BNCT-SPECT. We have been developing a new image reconstruction method based on Bayesian estimation for the BNCT-SPECT method. In the present study, the aims were to design and construct an experimental system capable of validating BNCT-SPECT and its image reconstruction method and to confirm BNCT-SPECTs performance. The crucial takeaway from this study is that we should consider the use of extremely high background radiation during BNCT. For the validation of BNCT-SPECT, we attempted to reproduce these conditions, despite this being quite challenging. We first constructed an experimental system capable of reproducing such conditions. Theoretical investigation was carried out to facilitate the design of the system using the Monte Carlo transport calculation code MCNP. Finally, we performed experiments with some standard gamma-ray sources to complete the system.
Research on Data Feature Selection of Sharing Platform Based on Particle Swarm Optimization Algorithm
Authors: Zhang Baihan
Published: November 2024

Abstract. This paper is based on the optimization of machine learning models such as SVM (Support Vector Machine) and LightGBM through the application of PSO (Particle Swarm Optimization) and combines shared platform recovery data to provide training material for machine models. The goal is to accelerate the parameter configuration of machine learning models and enhance the rigor of feature selection through the application of algorithmic models. The experimental results show that PSO performs well in optimizing parameters for machine learning models like SVM and LightGBM, achieving high levels in evaluation metrics such as accuracy, recall, precision, and F1 score. Based on this, a framework is proposed for embedding the PSO algorithm into a shared platform architecture, including layers for data collection and preprocessing, algorithm integration and optimization, decision support and service, and feedback and optimization. This framework allows for precise predictions of user behavior, market demand, and other factors, achieving automated scheduling of machine model parameters.
Visualization of particulate matters in air using lensless microscopy
Authors: Huang Zhi
Published: November 2024

Abstract. Air quality is crucial for health, yet monitoring airborne particulate matter (PM), particularly PM2.5, remains challenging due to pollution and widespread distribution. PM2.5, with diameters less than 2.5 micrometers, are known to have significant health implications. Traditional methods of PMs detection and analysis are often time-consuming or require complex optical systems. This study explores the use of lensless microscopy as an innovative and cost-effective alternative for the visualization and measurement of PMs. Utilizing computational imaging techniques, lensless microscopy captures high-resolution images without the need for traditional lenses, facilitating rapid and accurate analysis of air quality. We describe the implementation of lensless imaging to detect and quantify PM2.5 particles in the air, highlighting the use of the single light wavelength and the computational reconstruction method. Our experiments demonstrated that this approach could effectively capture fine details of PMs, achieving resolutions comparable to traditional microscopy. This validates the potential of lensless microscopy as a practical tool for real-time air quality monitoring. By adopting lensless microscopy, we offer a more efficient and economical method for the continuous monitoring of PMs, which can significantly contribute to environmental health studies and pollution control efforts. According to specific needs, simply replacing the flow rate of the air pump can adapt to the PM measurement speed requirements in different environments. This research introduces a novel approach to air quality assessment, providing a promising solution for the rapid and detailed analysis of airborne particulate matter while at an affordable cost.
Riemann Zeta Function and Its Applications
Authors: Shi Yuxuan , Lin Zhanyu
Published: November 2024

Abstract. This paper focuses on the introduction and proof of the fundamental properties of (z), i.e. Riemann zeta function and explores its applications in algebra. We begin with a systematic derivation and proof of the basic characteristics of the zeta function. Following this, we examine its application in algebra, including the use of the Dirichlet L-function to prove Dirichlets theorem. Furthermore, we show the classical result for the subgroup growth rate of J-groups and the enumeration of n-dimensional irreducible representations of Heisenberg groups.
Variance reduction in Monte Carlo for Integrals
Authors: Yang Yuchen , Zhou Jun , Chen Xiaotong
Published: November 2024

Abstract. Nowadays, the extensive use of Monte Carlo methods in various fields has promoted the scientific decision-making, improved the efficiency of social operation, and enabled better management of many uncertain factors in daily life. However, in some cases, traditional Monte Carlo methods doesn't work so well because of the excessive variance. This paper aims to explore a new numerical integration method called splitting method to minimize intrinsic variance in Monte Carlo simulations. Through this innovative method, we found that the variance was reduced significantly. Despite some oscillating functions which are still difficult to estimate because they have too many turning points, this study provides new insights into variance reduction in Monte Carlo for integrals to optimize calculations in various fields when the modelling functions are not monotonic.
Modelling and Analysis of the Pisa Tower Based on ANSYS
Authors: Shang Deye , Qin Puxun , Huang Chenghao
Published: November 2024

Abstract. This study looks at why the Leaning Tower of Pisa leans by using historical information and computer simulations. Using the "Spaceclaim" function in ANSYS, we made a full-size model of the tower and the ground it sits on. We did two experiments: first, we simulated how the tower was built to understand why it started leaning, and second, we changed the soil's stiffness (Youngs Modulus) to see how this affects the tower's tilt and vibration. Our results show that softer soil makes the tower lean more, giving important information for preserving the tower and other similar structures around the world.
Analysis of the Correlation of Topic Feature Changes Based on the LDA Model
Authors: Si Yunhao , Jiang Chongrong , Wei Xiangmi , Fang Shuning , Li Yunchen , Hu Yunfeng
Published: November 2024

Abstract. As is well known, with the continuous development of artificial intelligence technology and the increasing accessibility of data, various social platforms are committed to using intelligent recommendation algorithms to cater to user preferences. Some platforms even exaggerate facts and push sensational, valueless information to users, leading to the "Screaming Effect" and the "Echo Chamber Effect." The prolonged existence of these effects may result in "Information Cocoon," which is detrimental to the healthy development of individuals and society. To address this issue, different topics can have varying trajectories as online comments ferment, potentially reaching a neutral consensus or resulting in polarization. As a mainstream social platform in China, Weibo users serve as nodes for the dissemination of public opinion information, and the characteristics of information release, reception, forwarding, and commenting all influence the effectiveness of communication. First, we selected the topics "COVID-19" and "IG Electronic Sports Club" as our research subjects, identifying a range of topic popularity through Baidu Index, followed by data collection. Second, we used perplexity and coherence to determine the optimal number of topics for LDA, analyzing the changes in topic feature characteristics over different time periods. Through correlation analysis, we reached the following conclusions: Higher Weibo levels correlate with better information dissemination effectiveness; the quantity of information published on Weibo negatively impacts the forwarding and commenting behaviors; and as events progress, the enthusiasm for information dissemination on Weibo declines, with daily dissemination gradually decreasing.
There is no algorithm to determine if the homotopy group is trivial or not for all compact spaces
Authors: Gao Dayou , Huang Jiaxi , Liu Tianchang , Liu Tiantian
Published: November 2024

Abstract. Constructive mathematics involves numbers and objects that can be constructed and computed through algorithmic methods. In this paper we prove that there is no algorithm to determine if the homotopy group _n is trivial or not for all constructive compact spaces. In the beginning we introduce constructive mathematics and topology theory. Then we introduce constructive compact spaces to describe the compact space in algorithmic way, and we calculate certain homotopy groups. Finally, we use an unextendible partially computable function to prove that there is no algorithm that can always determine the triviality of their homotopy groups by contradiction.
Expansion of Landau theory with Magnetic Susceptibility and Heat Capacity
Authors: Qi Xuran
Published: November 2024

Abstract. Landau theory employs free energy to depict the work potential of molecules and utilizes order parameters to signify the degree of molecular organization. By applying a Taylor expansion of the free energy with respect to the order parameter in the vicinity of a phase transition, the theory elucidates how molecular arrangements can influence the system's energy. The universality of Landau theory stems from the order parameter within the framework of free energy expansion. The application of critical exponents exemplifies the universality of Landau theory, showcasing the properties of materials that share the same dimensionality and similar correlation lengths. This article aims to derive formulas and discuss practical applications of Landau theory, such as analyzing the heat capacity and magnetic susceptibility of materials across a range of temperatures.
Comparative Analysis of Machine Learning Models for Music Recommendation
Authors: Cheng Xi , Liu Ke , Hu Xin , Liu Tong , Che Chang , Zhu Chen
Published: November 2024

Abstract. This study is inspired by the Kaggle competition WSDM - KKBoxs Music Recommendation Challenge. The study focuses on doing a comparative study on music recommendation models. Based on the requirements and the given dataset from the Kaggle competition, the problem can be transferred to a classification problem, and therefore, we chose three classification models for the comparative study. The three models are K Nearest Neighbors (KNN), Random Forest, and Light Gradient Boosting Machine (LightGBM). We also did data analysis and data preparation before applying the model and used the handout method and cross-validation method for the validation. For the evaluation, the AUC score is applied to the results and the empirical results show that LightGBM is the best model among these three.
Research on Predicting Survival in Heart Failure Patients of Logistic Regression Models
Authors: Man Huixin
Published: November 2024

Abstract. The purpose of this paper is to study a logistic regression model for predicting the survival of patients with heart failure. Heart failure is a serious clinical syndrome that usually develops from multiple heart diseases, and its inadequate pumping function of the heart poses a significant threat to the life and health of the patient and a significant economic burden on the healthcare system. Using medical record data from 299 patients with heart failure in the UCI database, this research utilized logistic regression models to identify the critical factors influencing the survival of heart failure patients and to forecast their survival outcomes. This paper found that age, ejection fraction, serum creatinine concentration and follow-up period are significant factors affecting survival in patients with heart failure. By adopting backward elimination method to optimize the model, the accuracy of prediction is further improved. The optimized logistic regression model yields an area under the Receiver Operating Characteristic (ROC) curve of 0.845, showing high prediction accuracy. The conclusions of this study provide a new perspective for the early diagnosis, risk assessment and personalized treatment of heart failure.
The aerodynamic load experienced by an igloo under varying wind angles
Authors: Wu Pengze
Published: November 2024

Abstract. In this project, I investigated the aerodynamic load acting on an igloo structure when it is subjected to different wind angles. By using Computational Fluid Dynamics (CFD) simulations on COMSOL Multiphysics, I first analyzed a simple 2D cylinder case as a way to learn the software. After that, I studied a sample CFD case of a NACA 0012 airfoil that is published under the COMSOL website. Finally, I moved on to create my own igloo CFD case to study its aerodynamic load under varying wind angles (0-30 degrees in 3-degree increments). Understanding the aerodynamic load of this sample igloo can be useful in learning how igloos behave in extreme weather conditions and fast wind velocities. It is also beneficial to know when will the igloo experience the least force when built under a non-level surface and the wind is hitting the structure at an angle.
Exploring particle interactions under different shielding conditions through Coincidence Analysis
Authors: Cui Yunlin , Dai Cankun
Published: November 2024

Abstract. When muon particles in the cosmic ray pass through different materials, they will interact with the materials, leading to variation in muon event rates, which is the munber of muon detected per unit time. This study investigates muon event rates under two shielding conditions. In this experiment, six Cosmic Watch detectors are set into three pairs, arranged vertically, to identify the muon particles passing through the shielding materials. Muon event rates under these conditions are determined through coincidence analysis between data collected by paired detectors, which allows the specific events to be separated from the background radiation. To calibrate the muon event rates, environmental factors and differences between detectors are considered. Specifically, atmospheric pressure variations and the difference in time measurement caused by built-in quartz are corrected. The analysis reveals that the detected muon events rate is higher under a thin absorber (1cm iron) and is lower under a thick one(5cm lead). These findings align with the results of previous experiments, which provide insights into particle interactions with materials.
Quantum Entanglement and Nonlocality: Challenging the Local Realism of Classical Physics
Authors: Liu Xiaoci
Published: November 2024

Abstract. This paper delves into the significance and impact of quantum entanglement across the fields of physics, information science, and philosophy. Utilizing a literature review approach, the paper first introduces the concept and historical background of quantum entanglement, emphasizing its challenge to the limitations of classical physics and its potential applications in quantum communication and quantum computing. This paper thoroughly explains the theoretical foundations of the Einstein-Podolsky-Rosen experiment and Bell's inequality, along with related experimental validations and key results. In particular, it elucidates how quantum entanglement reveals the nonlocality in quantum mechanics and the characteristics of nonlocal information transfer. The discussion then shifts to the challenge quantum entanglement poses to physical ontology, exploring the philosophical implications and the new perspectives it offers in information theory. Finally, this study concludes by summarizing the profound impact of quantum entanglement as one of the most challenging and inspiring research areas in contemporary physics on scientific theory and philosophical thought, as well as anticipating future research directions and potential applications.
Social Support and Expectancy as Predictors of Licensure Examination Success Among Professional Teachers
Authors: Guardario Larry B. , Bucio Carl Joseph M. , Garocho Louiely Kaye B. , Caballo John Harry S.
Published: November 2024

This study aimed to determine the Licensure Examination for Teachers (LET) profile, the Level of Social Support and Expectancy and their relationships and identify the dimensions that predict LET Success Rating. This quantitative study utilized descriptive-correlational design among LET Passers and Licensed Professional Teachers produced by the University of Mindanao from 2019–2023. 303 LPTs composed of 109 Elementary and 194 Secondary teachers selected via convenience and snowball sampling responded to the virtual survey. The collected data were analyzed using mean, standard deviation, spearman correlations, and multiple regressions. Results revealed that 87% of the LPTs were top-performing and had high social support and expectancy levels during their LET preparation. The correlation between social support and the LET Success Rating is positive but very weak. Likewise, the correlation between expectancy and LET Success Rating is positive but very weak. Moreover, social support predicts the LET Success Rating by 1.9%; expectancy predicts it by 0.4%. Furthermore, support from Friends and/or classmates has moderate and positive correlations and has a strong positive predictive power with LET Success Rating.
A UTILIZAÇÃO DO PROGRAMA OPERACIONAL PADRÃO NA MELHORIA CONTINUA DA PADRONIZAÇÃO DE PROCESSOS LOGISTICOS INDUSTRIAIS
Authors: Silva Leonardo Henrique da , Magalhães Laís Michele Leite , Doalto Camila da Silva , Anjos Alexander Pitta dos
Published: November 2024

Este estudo investigou a eficácia do Programa Operacional Padrão (POP) na promoção da melhoria contínua na padronização dos processos logísticos industriais. Em um cenário de constante evolução tecnológica e aumento das demandas do mercado, o POP é frequentemente adotado para garantir a consistência e a eficiência operacional. O objetivo principal foi analisar como o POP pode ser utilizado para estabelecer e manter padrões operacionais, integrar a filosofia de melhoria contínua e adaptar-se às mudanças tecnológicas. Para alcançar esses objetivos, o estudo empregou uma abordagem metodológica que incluiu a revisão da literatura existente sobre o POP. A revisão da literatura forneceu um panorama sobre as práticas de padronização e melhoria contínua. Os resultados indicam que o POP, quando implementado com clareza e apoiado por uma filosofia de melhoria contínua, pode efetivamente contribuir para a padronização dos processos logísticos. No entanto, a eficácia do POP está diretamente ligada à sua capacidade de adaptação às novas tecnologias e às mudanças no mercado. A resistência à mudança e a necessidade de treinamento contínuo foram identificados como desafios significativos para a sua adoção e sucesso a longo prazo.
THE ROLE OF NOVEL PROBIOTIC STRAINS IN ENHANCING IMMUNITY AND PREVENTING INFECTIONS IN LIVESTOCK: A COMPREHENSIVE REVIEW
Authors: Uzoka Ugonna Henry , Abimbola Olufemi Gabriel , Isiaka Amarachukwu Bernaldine , Bolawa Oluseun Peter , Ugwor Emmanuel Ifeanyichukwu , Ani Nneka Victoria , Anakwenze Vivian Nonyelum
Published: November 2024

The use of probiotics in animal production has become increasingly important due to growing concerns about antimicrobial resistance and the pursuit of sustainable farming practices. This study aimed to explore the role of novel probiotic strains in enhancing immunity and preventing infections in livestock. We conducted a systematic literature review following PRISMA guidelines and used the PICO model to formulate the research question. The results indicated that various probiotic strains, such as Lactobacillus fermentum, Enterococcus faecium, Lactobacillus rhamnosus, Lactobacillus gasseri, and Bacillus subtilis, showed significant antimicrobial and immunomodulatory activities. These strains improved nutrient digestibility, reduced disease incidence, and increased the production of immunoglobulins and anti-inflammatory cytokines. We conclude that probiotics have significant potential as an alternative to antibiotics in livestock production, promoting safer and more sustainable agricultural practices.
DETALHE E FRAGMENTO: ANÁLISE DOS CONCEITOS DE WALTER BENJAMIN SOBRE A FOTOGRAFIA
Authors: Lichacovski Racquel Vonsowski , Perius Cristiano
Published: November 2024

Esse estudo investiga os conceitos de detalhe e fragmento nas principais obras de Walter Benjamin, essencialmente no que se refere à fotografia e ao cinema, a partir de uma análise crítica, a busca do presente texto foi por entender como, e se se relacionam, adentrando pormenores históricos, bem como de que maneira tais conceitos eram e ainda são percebidos. Foi feita uma revisão bibliográfica, tendo como base principalmente o livro “Obras escolhidas I: Magia, técnica, arte e política”, o artigo “A fotografia e a pequena história de Walter Benjamin”, de Maurício Lissovsky, além de escritos de Omar Calabrese. Ademais, tentou-se compreender a ideia de aura, a partir da reprodutibilidade da obra de arte, e de que maneira a experiência artística foi transformada.
AS TECNOLOGIAS NO COTIDIANO ESCOLAR: UMA FERRAMENTA FACILITADORA NO PROCESSO DE ENSINO-APRENDIZAGEM
Authors: Fagundes Regiane Cantuario , Silva Gleicyane Sousa , Barros Flavia Cristina Magalhaes
Published: November 2024

A tecnologia é essencial para a educação, ou melhor, a educação e a tecnologia são indissociáveis. Ao fazer uso das Tecnologias educacionais o educador deve estar atento para os objetivos pedagógicos, pois as ferramentas tecnológicas não podem ser substituídas pelo processo de aprendizagem que por si só constrói o conhecimento. O educador pode fortalecer sua ação com o uso das tecnologias, sem fazer com que o aluno perca o foco na educação, onde o aluno deve sempre estar em busca do conhecimento. Nesse contexto, o uso de tecnologia em sala de aula pode contribuir com a ampliação da oferta de produção e de acesso a conteúdo que ajudam o aluno na construção do conhecimento. É importante destacar que toda ação educativa não se limita aos meios utilizados, mas está intrinsecamente ligada a decisões políticas, sociais e culturais que envolvem o coletivo, com suas limitações e possibilidades, ultrapassando a esfera de deliberação das escolas e seus agentes. O objetivo geral deste artigo é explorar de que maneira as tecnologias presentes no cotidiano escolar podem contribuir para facilitar o processo de ensino-aprendizagem. A alfabetização digital busca ensinar e avaliar os conhecimentos e habilidades fundamentais em informática, permitindo que as pessoas utilizem a tecnologia computacional em seu cotidiano. e desenvolver novas oportunidades sociais e econômicas para si mesmas, suas famílias e suas comunidades. É importante, pois é uma chave fundamental para a inclusão e o desenvolvimento de uma Sociedade da Informação e do Conhecimento (SIC) acessível a todos.
A pragmatic analysis of manipulative speech acts used by American and Arabic attorneys in selected criminal trials
Authors: Dahaam Ziyad Ahmed , Salih Ahmed Mohammed
Published: November 2024

The present study investigates the manipulative speech acts used by American and Arabic attorneys while defending their clients in criminal trials. It is hypothesized that they construct their arguments on the basis of such type of speech acts to mislead the members of the jury who expect to listen to concrete evidences of innocence. The study follows a qualitative analysis to achieve the aims in terms of the modal adopted. The model is applied to six selected arguments divided between American and Arabic attorneys. Each part is resembled by an attorney. The results show that they both use indirect speech acts of manipulation, with some notable differences. The conclusions are drawn on the basis of their manipulative speech acts and on the basis of the comparison between the two attorneys which prove that they resort to two different types of indirect speech acts to manipulate the members of the jury.
Comprehending geometry proofs: A study on prospective mathematics teachers' perceptions and preferences of proof formats
Authors: Anwar Lathiful , Sa’dijah Cholis , Listiawan Tomi , Utami Anita Dewi , Zulnaidi Hutkemri , Eu Leong Kwan
Published: November 2024

The explicative aim of this research is to investigate the optics of proof format preferences held by prospective mathematics teachers (PMTs), in an effort to assess the effect that such preferences may have on their understanding of geometric proofs. The researchers employed a qualitative case study approach, in which six PMTs participated in Focus Group Discussions (FGDs) on the three styles of proof: paragraph proof, two-column proof and flow-chart proof. The methodology employed also focused on the formatting models by exploring the participants’ suggestions regarding each format in order to determine their cognitive responses as well as their preferences. The study exposes different preferences among PMTs which are a result of their personal cognitive style and experience with proofs. Some of the PMTs preferred the two-column format due to its systematic and logical nature, other PMTs preferred the storytelling nature of the paragraph proof format sponsored also flow-chart representation. These preferences bring out the requirement for the development of pedagogical strategies that employ different proof formats in order to meet the needs of different types of learners for effective understanding. In summary, this research demonstrates the need for customizing proof instruction to different students’ needs which can hopefully enhance PMTs’ responses and interactions with the concept of mathematical proofs. The practical outcomes show that teachers should not be afraid to think in more flexible witnessing forms of proof in order to aid students learning while minimizing the cognitive load in line with the principles of constructivist learning. It would be worthwhile however to extend this research and examine what these preferences would mean for the future and how those would fit within the context of online education with the overall aim of creating a better mathematics curriculum that is more effective and has a wider reach.
Future Resilience of the European Technology Security Policy Paper
Authors:   European Center for Populism Studies (ECPS), Miguel De Vera Anton , Hamaiunova Viktoriia , Koleszár Réka , Pasquettaz Giada
Published: November 2024

This paper explores vulnerabilities in the European Union’s technological security, focusing on Huawei as a case study to illuminate broader security challenges. Amid intensifying US-China tensions, especially under former US President Donald Trump, the EU encountered new risks linked to the strategic positioning of Chinese tech firms within critical European infrastructure. Trump’s "America First" policy targeted China with tariffs and trade restrictions to address perceived unfair practices, triggering disruptions in global supply chains that reverberated through the EU economy. For Europe, heavily reliant on secure, stable trade flows, these events highlighted the urgency of reassessing technological dependencies and reinforcing digital security. The paper presents a series of strategic recommendations for the EU to mitigate such vulnerabilities, emphasizing the need for diversified supply chains, rigorous security standards for tech partnerships, and collaborative policies among EU members to strengthen resilience in the face of geopolitical shifts and technological competition. Keyword: Populism, EU, Framing, US, China, Technology
Multidimensional Growth: Conceptualizing Human Development across Various Indices Case Study: Sierra Leone
Authors: Kamara Sheku , Knox-Goba Terrence Laurel , Rhodrick Strasser-King Emmanuel Adeyemi
Published: November 2024

An individual's economic, social, emotional, and cognitive growth are only a few of the many facets that make up the complicated and multidimensional idea of development. The need to reframe human development as a multidimensional construct that captures the complex interactions among these multiple dimensions is evident, even in the face of the abundance of indices and frameworks that seek to quantify human progress. In light of the fact that Sierra Leone has recently experienced serious development obstacles, this qualitative case study seeks to investigate the idea of multidimensional growth and its implications for human development in that nation. With 30 participants from a range of backgrounds including policymakers, development practitioners, and community leaders this study uses a purely qualitative methodology to investigate their perspectives on human development in Sierra Leone through in-depth interviews and focus groups. The research uses a phenomenological method to better understand people's lived experiences and perspectives on human development in Sierra Leone. The results of this research demonstrate that human development in Sierra Leone is a multifaceted and intricate concept that defies easy summarization into a single framework or index. The individual accounts of the participants emphasize the significance of taking into account several aspects of human development, such as cognitive, social, emotional, and economic development, along with the connections and interplay among these aspects. A variety of issues, such as institutional and policy frameworks, societal norms and values, historical and cultural contexts, and human development in Sierra Leone are all revealed by the study. Policies and practices will be greatly impacted by the study's conclusions. The report emphasizes the necessity for legislators and development professionals to embrace a more comprehensive and integrated approach to development programming by stressing the significance of a multifaceted approach to human development. The study's findings highlight the need for more sophisticated and situation-specific theories of human development that take into consideration the diversity and complexity of human experiences in various social and cultural contexts. With its more in-depth and contextualized explanation of the idea in the Sierra Leonean context, this study adds to the body of knowledge already available on human development. The study's conclusions call attention to the need for more comprehensive and multifaceted approaches to development programs, which has ramifications for the field of development studies as a whole. In the end, the research shows how critical it is to prioritize the perspectives and experiences of people and communities in development law and policy.
Antioxidant Activity of Lotion From Sonneratia caseolaris Leaves and Trigona sp. Propolis Extract
Authors: Safitri Annisa Nurul , Kustiawan Paula Mariana
Published: November 2024

Daily activities can trigger free radicals due to air pollution and increase the decline in skin health. One of the prevention efforts by using a lotion that made from natural ingredients. Natural ingredients such as Sonneratia caseolaris leaves and Trigona sp. bee propolis are still limited used in the form of lotion combination preparations. The purpose of this study was to explore the antioxidant activity of a combination lotion of S. caseolaris leaves and Trigona sp. bee propolis. Antioxidant activity was detemine by used the DPPH technique with lotion formula combination of S. caseolaris leaves and Trigona sp. bee propolis. F1 (1:1), F2 (2:1) and F3 (1:2) accompanied by a physical stability test of the lotion. The results showed that preparations F1, F2, F3 had strong antioxidants in the concentration range of 60-100 ppm. The three formulas met the criteria for a stable lotion preparation. The combination lotion formula has potential in the development of cosmetic products from natural ingredients.
O Impacto da humanização da assistência de enfermagem no processo de cuidado assistencial
Authors: Vaz Aline de Souza Costa , Lima Joielly Félix , Barbosa João de Sousa Pinheiro
Published: November 2024

Objetivo: avaliar como a assistência de enfermagem humanizada influencia a qualidade da recuperação dos pacientes, investigando seus impactos nos desfechos clínicos e no bem-estar geral. Metodologia: Realizou-se uma revisão integrativa da literatura, abrangendo a análise de artigos científicos e dados epidemiológicos publicados no período de 2019 a 2024. As bases de dados consultadas foram Medline, SciELO e BVS. Resultados: foram elegidos 16 artigos científicos nas bases de dados sobre o impacto na humanização na assistência de enfermagem, os estudos foram unanimes quanto o impacto positivo dessa prática. Conclusão: a humanização não se limita a aspectos técnicos do atendimento, mas envolve uma abordagem integral que leva em conta as dimensões físicas, emocionais e sociais do paciente. a humanização no cuidado hospitalar fortalece a confiança entre o paciente e o profissional de enfermagem, assim os pacientes que se sentem acolhidos e compreendidos respondem melhor aos tratamentos, permitindo uma recuperação mais rápida e eficiente.
Cateter central de inserção periférica em neonatologia: estudo retrospectivo
Authors: Ferreira Carolina da Silva , Serafim Clarita Terra Rodrigues , Russo Natália Conteçote , Ferrari Anna Paula , Oliveira Priscila Braga de , Corrêa Ione
Published: November 2024

O cateter central de inserção periférica (PICC) se destaca como um dispositivo crucial, pois proporciona um acesso venoso central seguro e prolongado para a administração de medicamentos, nutrição parenteral e quimioterápicos, especialmente em situações que exigem terapia de longa duração. O objetivo deste estudo é analisar os dados de controle de inserção e retirada do cateter central de PICC em uma Unidade Neonatal do interior de São Paulo. Trata-se de um estudo retrospectivo com abordagem quantitativa, descritiva e de delineamento transversal. A coleta de dados foi realizada por meio da análise documental de 150 instrumentos de registro de controle de PICC em uma Unidade Neonatal. Resultados: A amostra do estudo caracteriza-se por pacientes prematuros e de baixo peso. Os registros demonstraram que a principal causa de retirada do PICC foi o término da terapia medicamentosa proposta (43,3%). No entanto, um número significativo de cateteres (37,7%) precisou ser retirado devido à ocorrência de eventos adversos, evidenciando a necessidade de treinamento e orientação adequados para as equipes de saúde. Os resultados deste estudo reforçam a importância do PICC no tratamento de recém-nascidos, principalmente em situações de gravidade. Além disso, destacam a necessidade de monitoramento cuidadoso e intervenção precoce para prevenir complicações associadas à inserção e retirada do PICC.
Desafios da medicina do estilo de vida na saúde pública
Authors: Martins Samuel Ribeiro , Malta Arlete do Monte Massela , Barcelos Cristiane de Castro , Lima Fabiano de , Bohórquez Karen de Fátima Figueroa
Published: November 2024

O sistema público de saúde busca o cuidado integral ao indivíduo, contudo, a cultura de tratar a doença quando já instaurada ainda é uma realidade latente no Brasil. Nesse sentido, é válido salientar uma preocupação, uma vez que, até 2025 estima-se que hajam 1,2 milhões de idosos com idade superior à 80 anos no mundo, sendo a maioria deles possuidora de fatores de risco desencadeadores de doenças graves, como as Doenças Crônicas Não Transmissíveis (DCNT), deste modo, a medicina do estilo de vida ganha destaque seja na prevenção de doenças, tratamento das mesmas ou reabilitação de pacientes já acometidos. Para essa discussão, realizou-se pesquisas nas bases de dados: PubMed, SciElo e Google Acadêmico, no período de 2015 a 2024. Nesse contexto, a medicina do estilo de vida pauta-se em seis pilares: atividade física regular, alimentação saudável, controle de estresse, cessação de tabagismo, qualidade do sono, controle de substâncias tóxicas e conexões sociais. Pode-se observar que existem vários desafios ainda na incrementação ampla da medicina do estilo de vida no sistema público de saúde, contudo, entende-se que essa instalação é fundamental para promoção de saúde, tendo em vistas os benefícios que esses pilares apresentam em várias doenças. Portanto, conclui-se que apesar dos empasses, instalar a medicina do estilo de vida é um ganho gigantesco ao sistema público de saúde, tendo em vista a prevenção de doenças e redução de gastos com as DCNT.
Caracterização in silico da familia gênica e proteica da ascorbato peroxidase de Ricinus communis L.
Authors: Filadelfo Crismeire Santana Santos , Silva Simone Alves , Oliveira Michelle dos Santos , Filadelfo Ciro Ribeiro
Published: November 2024

O presente estudo investigou a capacidade adaptativa da planta de mamona (Ricinus communis L.) sob condições ambientais adversas, com foco na caracterização das ascorbato peroxidases (RcApxs) e seus mecanismos de defesa contra espécies reativas de oxigênio (ROS). A partir de banco de dados genômicos, cinco genes de RcApxs foram identificados, e sua distribuição cromossômica sugere variabilidade funcional, essencial para a resistência ao estresse biótico e abiótico. A análise in silico revelou variações significativas em tamanho e peso molecular entre as isoformas, por conseguinte, estabilidade metabólica e solubilidade. Elementos cis-regulatórios associados à resposta à luz e hormônios de estresse foram identificados nas regiões promotoras dos genes. A análise filogenética mostrou uma relação próxima entre algumas isoformas da mamona e a Apx de Arabidopsis thaliana L., sugerindo conexões evolutivas. A modelagem estrutural das enzimas demonstrou boa qualidade e potencial para aplicações futuras in silico, como ancoragem molecular. Esses achados contribuem para a compreensão dos mecanismos de adaptação da mamona e destacam a relevância das RcApxs em contextos de estresse ambiental.
Sistema de gestão Lean: estudo de caso aplicado no setor florestal
Authors: Tonett Erasmo Luis , Navroski Marcio Carlos , Soares Philipe Ricardo Casemiro , Nocera Natasha Marcon , Pereira Mariane de Oliveira
Published: November 2024

Este estudo objetivou analisar a eficiência da implementação de um sistema de gestão com base na filosofia Lean no setor de pátio de madeiras de uma empresa de base florestal comparando diferentes períodos de implementação através dos indicadores-chave de performance. O projeto foi desenvolvido em uma empresa de base florestal, localizada na região dos Campos Gerais, no estado do Paraná/BR. A metodologia de implementação das práticas de gestão Lean foi feita em ciclos semanais de melhoria contínua, divididos em 12 semanas, contando com a capacitação dos gestores das áreas, construção das ferramentas e aplicação nas respectivas áreas. A eficiência do Sistema de Gestão Lean (SGL) foi definida pelos KPI’s - Key Performance Indicator (Indicador-Chave de Performance) que a área estabeleceu de acordo com a estratégia da mesma. A média geral do indicador Tempo de Pátio teve uma queda, saindo de 0,622 h no período de implementação, para uma média de 0,597 h após a segunda reavaliação. Juntamente com o indicador de produtividade, que no período de implementação atingiu uma média geral de 197,05 t.h-1, para uma média de 221,43 t.h-1 após a segunda reavaliação. A correta aplicação das práticas e ferramentas Lean tendem a refletir em aumentos de performance dos indicadores-chave.