bluuebunny/crossref_metadata_2025 huggingface dataset:
Introdução ao Pensamento Computacional no Ensino Fundamental: Um Relato de Experiência em Escolas Distritais
Authors: Gorgônio Flavius L. , Vale Karliane M. O.
Published: October 2023

O ensino de conceitos de pensamento computacional nas escolas de ensino fundamental é um importante diferencial que contribui significativamente para ampliar a capacidade e a cognitividade do raciocínio computacional em crianças e adolescentes. Entretanto, a implantação destes conteúdos em escolas das redes estaduais e municipais brasileiras ainda enfrentar uma série de desafios e limitações. Este artigo descreve um relato de experiência de implantação de minicursos de pensamento computacional em escolas localizadas em pequenos distritos do interior do estado do Rio Grande do Norte a partir de projetos de extensão universitária.
An Approach in Brain Tumor Classification: The Development of a New Convolutional Neural Network Model
Authors: Felipe Caio dos Santos , Alva Thatiane Alves Pianoschi , Winck Ana Trindade , Becker Carla Diniz Lopes
Published: October 2023

Brain tumor diagnosis is a complex problem that requires specialized skills and knowledge. Manual analysis is often time-consuming, and there can be high subjectivity in interpreting results. Convolutional neural networks (CNNs) have emerged as a promising solution for automatically classifying brain tumors from magnetic resonance images (MRI). CNNs are a type of neural network that can automatically learn and extract relevant features from images, making them particularly suited to this task when applied in deep learning algorithms. The use of CNNs for brain tumor diagnosis has been widely explored in the literature, with many studies reporting promising results. By leveraging datasets of labeled MRI, CNNs can learn to accurately detect and classify different types of brain tumors, including gliomas, meningiomas, and pituitary adenomas. These models have been shown to outperform traditional machine-learning algorithms and even human experts in some cases. This article presents a CNN model designed to identify and classify brain tumors from MRI. The model was trained on a large dataset of MRI, and its performance was evaluated on an independent test set. The model achieved an accuracy of 99% considering all validation steps and outperformed state-of-the-art methods for brain tumor classification. When considering individual classes, the accuracy percentages were 100%, 98%, 99%, and 99% for glioma, meningioma, notumor, and pituitary, respectively. The development of accurate and efficient methods for brain tumor diagnosis is critical for improving patient outcomes and reducing healthcare costs. This article can advance our understanding of leveraging these powerful algorithms best to solve real-world healthcare problems by contributing to the growing literature on deep learning for medical image analysis.
Improving performance in small datasets via pre-trained architectures based on VGGFace and VGGFace2 datasets
Authors: Simões Rodolfo , Kemmer Bruno , Ivamoto Victor , Lima Clodoaldo
Published: October 2023

Face recognition algorithms have achieved outstanding results under controlled conditions, mainly through deep learning computational techniques. However, the performance under uncontrolled conditions still needs improvement. Facial recognition systems in real-world problems often deal with uncontrolled conditions such as occlusion and pose and lighting variations, which degrade recognition performance. Despite such limitations, with enough training samples, it is still possible to reach high performance via existing deep-learning architectures. Nevertheless, the lack of training samples often results in low recognition accuracy in this domain. In this study, it has been shown that utilizing pre-trained models for the facial recognition task can enhance performance significantly in scenarios with a low number of training images available.
Back to the Promotion - EvacSIM: a Serious Game to Practice Requirements Elicitation on an Agent-based Simulation
Authors: Debacher Nícolas M. , Kuster Luis F. , Santos Ana F. C. dos , Vahldick Adilson , Santos Fernando
Published: October 2023

Simulação baseada em agentes (SBA) é um paradigma de simulações computacionais cujo foco está nos indivíduos (agentes) e suas interações. Para desenvolver uma SBA é preciso identificar e descrever os agentes, as interações e o ambiente em estudo. Isto pode ser feito através da elicitação de requisitos, uma etapa da engenharia de requisitos na qual se entende e se coletam as necessidades dos stakeholders do software. O sucesso da elicitação de requisitos frequentemente depende da experiência prática do engenheiro de software. Contudo, a experiência prática vivenciada durante a formação do engenheiro de software é limitada e raramente contempla elicitar requisitos de SBAs. Neste artigo é proposto um jogo sério com realidade virtual para viabilizar uma forma de praticar a elicitação de requisitos de SBAs. O jogador assume o papel de engenheiro de software e interage com os stakeholders para identificar e coletar os requisitos de uma SBA de evacuação. O resultado obtido conjectura que um jogo sério pode ser uma alternativa viável para praticar a elicitação de requisitos de SBAs.
Surrogate-based constrained multi-objective optimization for the compression of CNNs
Authors: Ferreira Gabriel Bicalho , Barros Antônio de , Ibrahim Issah , Silva Rodrigo
Published: October 2023

A implantação de redes neurais profundas em dispositivos com recursos limitados apresenta desafios significativos. Para enfrentar esse problema, técnicas como poda e quantização são frequentemente utilizadas. No entanto, essas técnicas exigem ajustes cuidadosos para garantir que o modelo final seja computacionalmente eficiente sem sacrificar muita qualidade. Para automatizar o processo de compressão e melhorar sua robustez e acessibilidade, propomos um Algoritmo Evolucionário Multiobjetivo com Restrições Baseado em Surrogates para a compressão de redes neurais artificiais. Resultados experimentais obtidos para o conjunto de dados CIFAR10 utilizando as arquiteturas ResNet50 e VGG16 indicam que a abordagem proposta permite um ajuste mais eficiente em relação aos algoritmos de poda e quantização, resultando em conjuntos não dominados de maior qualidade em comparação com o método de otimização sem Surrogates. Além disso, nosso método produziu versões mais enxutas das arquiteturas testadas mantendo a precisão.
Detection of Big Five personality traits in Twitter user's profiles based on textual posts
Authors: de Almeida Laura Damaceno , Goya Denise
Published: October 2023

Personalidade descreve o comportamento das pessoas e pode influenciar suas escolhas e tomadas de decisão. Uma das métricas mais consolidadas para traços de personalidade é o Big Five. Poucos trabalhos foram produzidos para detecção dos mesmos a partir de textos em português compartilhados em redes sociais. O objetivo do presente trabalho consiste na construção de um conjunto de dados com tweets em português rotulados com o traço de personalidade dominante e verificar o seu potencial de uso em modelos de aprendizado de máquina clássicos. No experimento realizado, os algoritmos de aprendizado de máquina apresentaram desempenho superior com a inclusão da técnica SMOTE e o melhor resultado foi Regressão Logística com TF-IDF unigram.
BioPrediction: Democratizing Machine Learning in the Study of Molecular Interactions
Authors: Florentino Bruno Rafael , Sanches Natan Henrique , Bonidia Robson Parmezan , Carvalho André C. P. L. F. de
Published: October 2023

Given the increasing number of biological sequences stored in databases, there is a large source of information that can benefit several sectors such as agriculture and health. Machine Learning (ML) algorithms can extract useful and new information from these data, increasing social and economic benefits, in addition to productivity. However, the categorical and unstructured nature of biological sequences makes this process difficult, requiring ML expertise. In this paper, we propose and experimentally evaluate an end-to-end automated ML-based framework, named BioPrediction, able to identify implicit interactions between sequences, e.g., long non-coding RNA and protein pairs, without the need for end-to-end ML expertise. Our experimental results show that the proposed framework can induce ML models with high predictive accuracy, between 77% and 91%, which are competitive with state-of-the-art tools.
LUNCH: an Answer Set Programming System for Course Scheduling
Authors: Lima Ana Y. F. de , de Sousa Briza M. D. , Cardeal Daniel P. , Sato Jessica Y. N. , Salvador Lorenzo B. , Geh Renato L. , Bazaluk Bruna
Published: October 2023

Timetable scheduling is a known NP-hard problem; despite this, there have been many efforts to enable fast and efficient algorithms and heuristics for such a challenging task. Within the realm of timetable scheduling lies the particularly complex problem of Course Scheduling (CS). The goal in CS is to find an optimal timetable configuration of courses within the constraints set by faculty, course requirements and departmental functions. Answer Set Programming (ASP) is a declarative logic programming paradigm for solving combinatorial search tasks; instead of explicitly writing the solution to the problem, ASP programs define the problem’s constraints and knowledge in a high-level language, leaving the model search to a highly optimized solver. In this work, we construct and showcase LUNCH, an easily extensible, free and open-source system for course scheduling. Notably, we study the use of ASP for course scheduling within the specific context of the Computer Science Department at the University of São Paulo, showing how LUNCH fares against the manual scheduling done in previous years.
Eu, Tu, Ele, Ela, Elu, Nós, Vós, Eles, Elas, Elus por um Modelo de Linguagem Neutra
Authors: Lopes Washington Roberto , Zilberman Be , da Cruz Bruna Magrini , Cruz Leticia dos Santos Monte , Gomes Rafaella Alves Lucena , Wassermann Renata , Peres Sarajane Marques , Freire Valdinei
Published: October 2023

A linguagem neutra está no centro de discussões sobre inclusão e combate a vieses de gênero. Pautada na neutralização de gênero, ela é caracterizada pela adição de novos elementos de gênero neutro em uma língua, ou pela priorização da escrita em sintaxe neutra. Ambas as formas são processáveis automaticamente e podem ser tratadas no escopo do processamento de linguagem natural. Este artigo apresenta uma iniciativa para otimizar um modelo de linguagem para traduzir sentenças do português oficial para a linguagem neutra, considerando os novos elementos de gênero neutro. Um corpus bilíngue foi criado para o treinamento, contendo traduções manuais de parágrafos de notícias, palavras e frases de um guia oficial de linguagem neutra, além de sentenças geradas automaticamente. Os resultados com os modelos otimizados mostram que a geração de modelos de linguagem inclusivos são factíveis.
Hyperspectral Imaging: A comparative study of supervised learning algorithms
Authors: Guimarães Mailson R. M. , Canuto Anne M. P. , Kreutz Márcio Eduardo
Published: October 2023

O presente trabalho mostra um estudo em torno de uma base de dados de imagens hiperespectrais, realizando-se manipulações nesta para a derivação de novas bases de dados para que seja possível observar o comportamento dessas manipulações nos resultados. Além disso, é realizada a automatização do processo de classificação de pixels através da aplicação de algoritmos de aprendizado com diferentes razões de divisão entre as bases de teste e treinamento. Também foram implementados comitês de classificadores como forma de melhorar a acurácia. Os resultados mostram que a Multilayer Perceptron (MLP) é o método com maior acurácia dentre os implementados, atigindo valores superiores a 85% e fornecendo resultados semelhantes aos dos comitês. Dentre as bases analisadas, as que mostraram melhor resultado foi a base original (inalterada) e a que teve seus atributos reduzidos para 20 componentes principais através do algoritmo Principal Component Analysis (PCA). Além disso, devido à consideração dos pixels sem classe definida, obsevou-se uma limitação de acurácia para os algoritmos implementados.
AutoML Optimized by Genetic Algorithm and Item Response Theory
Authors: Cardoso Lucas F. F. , Santos Vitor C. A. , Kawasaki Francês Regiane S. , Alves Ronnie C. O.
Published: October 2023

Gerar modelos de aprendizado de máquina automaticamente segue sendo uma área de muita pesquisa recente e desafiadora. E ainda não há uma forma definitiva capaz de gerar resultados satisfatórios e que apresente uma complexidade baixa. Com isso, neste trabalho, são apresentados os resultados de uma metodologia proposta que utiliza os conceitos da Teoria de Resposta ao Item e Algoritmo Genético para criar um algoritmo de AutoML do tipo NAS que seja capaz de gerar uma Rede Neural competitiva com os modelos já conhecidos na literatura. Nos resultados obtidos, foi possível gerar um modelo competitivo se comparado ao AutoKeras, porém com complexidade inferior a 5.5% da complexidade total do modelo do próprio AutoKeras.
Leveraging Property Tax Collection Through an Unsupervised Model for Taxpayer Qualification
Authors: Alves Elioenai L. G. , Viana Luiz Zairo Bastos , Santos Fabio , Franco Wellington , Pinheiro Vládia
Published: October 2023

O Imposto Predial e Territorial Urbano (IPTU), tributo de competência municipal e importante suporte financeiro de serviços públicos, vem sofrendo diminuição na sua arrecadação nos últimos anos. Neste contexto, muitas prefeituras tem buscado medidas para melhorar a comunicação e o sistema de cobrança, e, conhecer o perfil de cada contribuinte/imóvel é fundamental para otimizar os recursos destinados à cobrança e diminuir a inadimplência. O presente trabalho propõe um modelo de Machine Learning não supervisionado para qualificar os contribuintes de impostos imobiliários como o IPTU, a partir do histórico de pagamentos e dos débitos do imposto. Os resultados do modelo treinado com dados da cidade de Fortaleza, comparados com o sistema baseline em uso hoje nessa cidade, indicaram desempenho promissor com F1-Score de 92,30%.
Caracterização de Estratégias de Futebol com base na Frequência, Importância e Efetividade de Jogadas
Authors: Valadao Gabriel , Gonçalves João L. L. , L. Megale João L. , Paula Vinicius M. , Rios-Neto Hugo , Pereira Adriano C. M. , Meira Jr. Wagner
Published: October 2023

Entender e prever resultados em futebol é um desafio pela complexidade do jogo em si, pelo número e diversidade dos jogadores envolvidos e mesmo por fatores externos que nem sempre são qualificáveis ou quantificáveis. Por outro lado, há todo um esforço no sentido de treinar os times e prepará-los para agir e reagir adequadamente a uma variedade de cenários, o que indica a existência de estratégias. Este artigo tem por objetivo caracterizar essas estratégias de futebol, com foco em como o time se comporta coletivamente. Estratégia de futebol é definida como um conjunto de jogadas que devem ser frequentes, importantes e efetivas, que são critérios normalmente conflitantes. É proposta uma metodologia para identificar essas estratégias, a qual é implementada e avaliada usando dados reais de temporadas de ligas. Os resultados mostram que a metodologia proposta permite caracterizar estratégias dos diferentes times.
Local Dampening: Differential Privacy for Non-numeric Queries via Local Sensitivity
Authors: de Farias Victor Aguiar Evangelista , Machado Javam de Castro
Published: October 2023

Differential privacy is the state-of-the-art formal definition for data release under strong privacy guarantees. We present the local dampening mechanism a differentially private mechanism for non-numeric queries. Our approach is the first to leverage the notion of local sensitivity to reduce noise injected to the output. We develop a theoretical accuracy analysis to show the conditions that our approach performs accurately and we conduct an experimental evaluation with competitors on diverse problems. Those contributions were published on VDLB conference and on the special issue of the VLDB journal. Non-related contributions were published in SBBD, SBRC, CLOSER and FGCS. This work was carried out in cooperation with AT&T Labs Research - USA.
Flower-PROV: Captura Distribuída de Dados de Proveniência em Experimentos de Aprendizado Federado
Authors: Lopes Camila , Nunes Alan L. , Boeres Cristina , Drummond Lúcia M. A. , de Oliveira Daniel
Published: October 2023

O Aprendizado Federado (AF) é uma técnica descentralizada que possibilita que vários usuários treinem modelos de Aprendizado de Máquina de forma colaborativa, sem precisar acessar dados privados ou sensíveis. O treinamento de um modelo pode exigir várias iterações, e a duração de cada iteração depende diretamente das configurações definidas, como os valores dos hiper-parâmetros. Analisar os hiperparâmetros durante o treinamento permite uma melhor compreensão do modelo treinado e abre oportunidades para melhorias. Este artigo apresenta o arcabouço Flower-PROV que tem como objetivo capturar dados de proveniência durante o treinamento para rastrear configurações e métricas de avaliação, possibilitando a análise dos hiperparâmetros em tempo real. O banco de dados de proveniência segue a recomendação W3C PROV, facilitando a comparação, explicação e reprodução desses experimentos.
STMotif Explorer: A Tool for Spatiotemporal Motif Analysis
Authors: Borges Heraldo , Castro Antonio , Coutinho Rafaelli , Porto Fabio , Pacitti Esther , Ogasawara Eduardo
Published: October 2023

Pattern discovery is an important task in time series mining. A pattern that occurs a significant number of times in a time series is called a motif. Several approaches have been developed to discover motifs in time series. However, we can observe a clear gap in exploring the spatial-time series data. It is challenging to understand and characterize the meaning of the motif obtained concerning the data domain, comparing different approaches and analyzing the quality of the results obtained. We propose STMotif Explorer, a spatial-time motif analysis system that aims to interactively discover and visualize spatial-time motifs in different domains, offering insight to users. STMotif Explorer enables users to use and implement novel spatiotemporal motif detection techniques and then run this across various domains. Besides, STMotif Explorer offers the users a set of interactive resources where it is possible to visualize and analyze the discovered motifs and compare the results from different techniques. We show the features of our system with different approaches using real data.
Repense, Recupere e Reranqueie: Um Pipeline de Recuperação e Reranqueamento para Classificação de Texto Multi-rótulo Extrema
Authors: França Celso , Ribeiro-Neto Berthier , Gonçalves Marcos André
Published: October 2023

A classificação de texto multi-rótulo extrema (XMTC) envolve a atribuição de rótulos relevantes a um texto a partir de um enorme espaço de rótulos. Abordando os desafios centrais da XMTC (volume, desbalanceamento e qualidade), propomos o xCoRetriev, um pipeline de dois estágios migrando de uma perspectiva de classificação para uma abordagem de recuperação de informações (IR). Tratamos o desafio de volume combinando de forma eficiente métodos de IR; enfrentamos o desafio do desbalanceamento capturando melhor a relação texto-rótulo e; aprimoramos a qualidade enriquecendo os nomes dos rótulos com pseudo-rótulos. Nossos resultados demonstram os pontos fortes do xCoRetriev quando comparado a linhas de base em termos de: (i) escalabilidade para grandes espaços de rótulos e quantidade de textos; (ii) eficácia diante do alto desbalanceamento, especialmente para predição de rótulos infrequentes – com ganhos de até 40% em MRR e NDCG –; e (iii) capacidade de lidar com textos e rótulos anotados de baixa qualidade.
Ensemble of Term Classification (ETC): Classifying Word Occurrences
Authors: Mangaravite Vítor , Gonçalves Marcos André
Published: October 2023

Automatic text classification in Natural Language Processing (NLP) and the task of predicting classes for textual documents. Traditionally, there have been two predominant approaches: bag-of-words-based models and more recent sequence-based models. While bag-of-words-based models represent documents considering only the occurrence of individual terms, sequence-based models take into account the order of terms within the text, up to an established maximum length. While deep learning-based sequence models have dominated the field, bag-of-words-based approaches continue to produce competitive results. However, existing methods generally require building a representation of the document and then predicting its class, without specifically classifying individual occurrences of terms within the wordset. This research gap serves as motivation for the proposed thesis, which presents a new perspective for automatic text classification. The main objective is to classify each term occurrence within the word bag and then estimate the class of the document, thus eliminating the need for a single hidden representation of the document. As demonstrated by the results obtained, the proposed approach offers greater interpretability and efficiency in text classification, by addressing the limitations of existing methods.
Diversidade de Dados Meteorológicos da Cidade do Rio de Janeiro: Uma Proposta de Arquitetura de Armazenamento e Fluxo de Dados para Modelos de Previsão
Authors: Freitas Bruno L. , da Fonseca Augusto J. M. , Bezerra Eduardo , Bernardini Flávia C. , Ferro Mariza
Published: October 2023

A precipitação nowcasting é um componente essencial dos sistemas de alerta precoce e das ações consecutivas no âmbito da gestão de crises para eventos climáticos extremos em áreas urbanas. Este artigo apresenta os trabalhos em andamento para a coleta, descrição de atributos, preparação e uso de múltiplas observações meteorológicas como fontes de dados disponíveis para a cidade do Rio de Janeiro. O desafio é reunir diferentes fontes, disponíveis abertamente ou sob restrições de acordos de cooperação, de diferentes portais e sites, sob a responsabilidade de diferentes proprietários em diferentes esferas (municipal, estadual e federal), com o objetivo de desenvolver um data lake que reúna todos e possa ser usado para o desenvolvimento de modelos de previsão.
Sistanism: An Attempt to Combine Shi’ism with Democracy in Post-2003 Iraq
Authors: Suzah Saleem
Published: October 2023

This chapter is a contribution to the literatures that debate about the relationship between religion and democracy, particularly between Shi’ism and democracy that has not adequately been addressed by scholars. The chapter attempts at highlighting the way religion (Shi’ism) is fused with democracy in post-2003 Iraq and the role of Ayatollah Sistani in sponsoring such a fusion and thus maintaining the political system from a distance. Sistani’s power in Iraq is not based on his religious status only, but also on a carefully constructed relationship between himself and the government of Iraq on the one hand and between himself and the people (the Shi’i population of Iraq) on the other. Through his ever-changing strategies and tactics, I argue that Sistani was able to combine Shi’ism with democracy, not in a strictly secular sense or in a wholly Islamist way, but through a practical compromise between the two. He has maintained the balance so well that neither the government nor Shi’is can now ignore his suggestions when disagreements occur. In doing so, Sistani will stay a key figure that sustains a pattern of democratic regime that is at ease with Shi’ism in Iraq.
Perspective Chapter: Foreign Residents Providing Eldercare in Japan – Government Data and Their Limitations
Authors: J. Milly Deborah
Published: October 2023

How many foreign residents in Japan are caring for Japanese senior citizens? What trends will likely characterize reliance on foreign residents for caregiving? Japan leads the world in its proportion of seniors, but many other countries are following a similar path. The visa system and the care industry in Japan are highly institutionalized and diverse, posing challenges for assessing the extent of foreign residents’ contribution to care. Scholars, policy professionals, and those advising potential migrants from other countries should recognize the pros and cons of the major government data sources and not rely on just one source. This chapter provides guidance on these sources and suggestions for using them effectively. It further highlights that, given recent access to new visa options, employers are opting for workers with more skills and the possibility of remaining in Japan for a longer period of time.
Fundamentals of a Safe and Effective Neonatal Building Design in a Tropical Low-Income Setting
Authors: O. Amadi Hippolite , B. Kawuwa Mohammed , L. Abubakar Amina , K. Obaro Stephen
Published: October 2023

A safe and effective neonatal building is an aspect of Neonatal Rescue Scheme (NRS) concept as described in the literature. Observable habitual practices leading to various neonatal outcomes at tropical LMIC settings point to adverse facility-based mortality contributions from poor nursery layouts. Sadly, the negative impacts of building deficiencies are not well-understood or empirically quantified as tailored to the limitations in resource-constrained tropical climate. Lack of helpful building features may exacerbate high morbidity owing to adverse issues such as poor infection control, evening fever syndrome (EFS), noise pollution, medication safety, intra-ward traffic, nursing fatigue, and parental services. A tropical LMIC setting has the disadvantages of relative poverty, infrastructural inadequacies, and adverse equatorial climatic conditions, necessitating design-specific requirements for safe neonatal care. This chapter is proposed to explore the constraints, concepts, and features as integrated in some NRS nurseries at different tropical regions of Nigeria, which function to mitigate the climate, poor infrastructure, and societal poverty against neonatal survival.
Sport Analytics: Graduating From Alchemy
Authors: Mountifield Charles
Published: October 2023

Sport analytics allows sport teams and organizations to improve performance and associated business decisions. There is an increasing demand for sport analytics, in part connected to the emergence of Big Data, resulting in a new discipline in the sport industry. Business models related to sport analytics offer the opportunity to analyze the performance of athletes, teams, clubs, and sport organizations. The burgeoning yet competitive objectives based on sport analytics explain, to a degree, why it is rare to find algorithms, predictive models, and other statistical methods and analyses being carried out in the public domain. This chapter first outlines topical views of the developing field of sport analytics that suggest that its application is based on organizational self-interest, resulting in a degree of obfuscation that may limit the pursuit of knowledge. Countering these opinions, however, is evidence pointing to sport analytics becoming more mainstream and a domain of shared knowledge. The chapter provides a non-exhaustive literature review, including sections addressing statistical elements, performance optimization, theoretical frameworks, and the application of sport analytics, followed by some overall observations. Within that context, recent developments in the sport industry demonstrate that sport analytics is more than alchemy.
Anti-war Stance in Contemporary Fiction: Kamran Pasha’s Shadow of the Swords and the War on Terror
Authors: T. Yousef Nisreen
Published: October 2023

The chapter considers literary depictions of the “War on Terror” in a contemporary novel written by a Muslim author. It examines Islam’s relationship with the West in Kamran Pasha’s Shadow of the Swords (2010). The chapter argues that the author articulates his understanding of the relationship between Islam and the West by means of revisiting the Third Crusade following the 9/11 attacks. The novel refutes the assumption that the Crusades were fought mainly for religious purposes; in consequence, it modifies Samuel Huntington’s thesis of the “Clash of Civilizations” by suggesting that the economic and political interests and the desires for expansion were dominant factors driving the Crusades. By presenting the Third Crusade and, by means of historical analogy, the ongoing “War on Terror” as an Imperialist project, Pasha supports Edward Said’s views in his book Orientalism (1978). By presenting the vicious and destructive outcomes of the Crusades on people, the land, cultural heritage and human relations, the novel denounces the consequences of using military force and calls for resorting to diplomacy. Ultimately, Pasha’s Shadow of the Swords reflects a solid anti-war stance and optimistic views on future Islam-West relationships.
Implications of Migration Dynamics for Aged Care in Australia
Authors: Robertson Hamish , Nicholas Nick
Published: October 2023

We examine immigration, population ageing and the aged care workforce, as well as making suggestions for their effects on health, aged and social care including more localised implications. While there is now a push to reopen borders, and while numbers are rising, it is as yet unclear if the ‘old order’ will resurge or if the situation has changed for the foreseeable future. We draw on data from a variety of official sources in a developmental discussion of the current and likely future effects of labour migration patterns, workforce supply and demand issues in Australia, and the lingering effects of the COVID-19 pandemic. For a variety of reasons, the data used here are emergent and the effects on current and future workforce requirements will be varied at several levels. Australia’s ageing population and associated health and social care needs are dynamic in themselves, but they are also situated within a broader international context. There is a need for ongoing monitoring and evaluation of how these factors intersect and likely future scenarios.
The Chilean Student Movement and the Bio-Politics of Existence: New Patterns of (re)Politicisation in a Post-Authoritarian Society
Authors: Hernandez Santibañez Ivette
Published: October 2023

This article analyses the specific forms of doing and building politics in the Chilean student movement, and through which, it becomes a key actor for mobilising (re)politicisation within a post-authoritarian democratic society. The bio-politics of existence – transforming life into political action – is central to understanding this role. The bio-politics of existence refers to the emergence of a new political subjectivity in the Chilean student movement engaging with new forms of (re)politicisation of everyday life and forms of egalitarian political relationships. The bio-politics of existence interweaves with self-transformation to constitute subjectivities that subvert neoliberal governmentalities. Learning through making mistakes is central for student activists in 2006 to (re)vision their political agency and animate, in 2011, a radical political imaginary of politics as being-in-common. The manifold forms of the bio-politics of existence in the Chilean student movement, from everyday activism to grassroots building network alliances – presupposing temporal contingencies to identity politics as marginal sites and spaces of resistance – unveil a rhizomatic growth of egalitarian, participatory politics through which the Chilean student movement transformed, from below, the character of politics and democracy in a society regarded as the first laboratory of neoliberalism.
Trends in maternal health care utilization in West Africa: Diffusion or modernization?
Authors: Cissé Siaka , Rherrad Imad
Published: October 2023

Maternal health care remains a major concern in developing countries, but many sub-Saharan countries have achieved substantial reduction in maternal and neonatal mortality rates. This chapter seeks to account for the sources of these reductions, focusing on the role of socioeconomic changes and the health system and using Mali, Burkina Faso, Niger, and Senegal as case studies. The results of our decomposition analysis suggest that, overall, changes in the use of maternal health care reflect behavioral changes associated with improvements in the performance of health systems in these countries. Exceptions were observed for pregnancy and delivery assistance in Mali between 2001 and 2006, and in Burkina Faso between 1999 and 2003. Despite this overall progress, inequalities between socioeconomic groups persist, particularly in Mali and Senegal.
Demographic data in the built environment and human health studies
Authors: Wang Huaqing , G. Tassinary Louis
Published: October 2023

Demographic data is widely used in both built environment and population health studies. Traditional data sources include national, state, and local surveys as well as archived data from longitudinal studies and newly emerging sources such as digitally accessible administrative data and real-time data from mobile devices. The value of these diverse data sets hinges on their accuracy, completeness, reliability, relevance, and timeliness. This chapter reviews the literature published in this field, provides a selective overview of the extant published research based on such data, and offers suggestions for the continuing access and use of such datasets.
Perspective Chapter: Exploring the Potential of Vagus Nerve Neuromodulation as a Personalized and Enhanced Therapeutic Experience for Type 2 Diabetics
Authors: Waataja Jonathan , Ikramuddin Sayeed , Gal Dov , Billington Charles
Published: October 2023

Glucagon-like peptide-1 (GLP-1) receptor agonists have become the gold standard for the treatment of type 2 diabetes mellitus (T2D). The therapeutic benefits of GLP-1 are marred by compliance, cost, and side effects. Vagus nerve modulation (VNM) holds great potential for current and future neuromodulation therapies in a range of medical conditions. Treatment for T2D using VNM is a potential new area of research. Most VNM studies investigating glycemic control utilize glucose tolerance tests. There are few long-term chronic studies examining both fasting plasma glucose and plasma glucose in the absorptive state. This chapter explores literature involving the use of VNM to enhance glycemic control. Also, results of a novel method of multi-site, multi-frequency sub-diaphragmatic vagal neuromodulation will be reviewed as well as a discussion of mechanisms associated with this VNM technique. This modality holds promise in enhancing glycemic control in the fasting and postprandial states. Multi-site multi-frequency neuromodulation offers a multitude of different therapy parameters for personalized medicine.
Limited Approaches for Genomic Studies in Rapid Postmortem Tissue Collection
Authors: Sandusky George , Yard Michael , Szymanski Megan , Emmert Lydia , Valadares Vivian
Published: October 2023

Rapid postmortem tissue collection has been shown to have increasing use for molecular and genetic profiling. Although research on human tissue has been conducted for many years, modern molecular assays have significantly higher sensitivity and specificity than those used in the past. Higher grade tissue specimens are now required for the extraction of macromolecules as a result of this. In fact, these studies have paved the way for multiple postmortem tissue collection studies such as COVID-19, brain, skin, and small cell lung cancer. Best practices for tissue collection have also been developed by a number of professional organizations, including the National Institutes of Health Office of Biorepositories and the International Society of Biological and Environmental Repositories (ISBER). These guidelines can be used to establish procedures for tissue collection.
Advanced Esophageal Cancer Palliative Surgical Therapy Using Isoperistaltic Gastric Tube
Authors: Luis Braga De Aquino Jose , Aparecida Leandro-Merhi Vania
Published: October 2023

Although malignant neoplasms of the esophagus remain a very common disease, their diagnosis might often come late, which explains why 50% of patients require palliative treatment. The ideal scenario would be the performance of procedures that provided an adequate quality of life and satisfactorily restored swallowing. This chapter aims to describe the results of palliative methods, discussed with emphasis on the technique of the isoperistaltic greater curvature gastric tube (IGCGT). About 143 patients with unresectable squamous cell carcinoma of the esophagus (T4b) were evaluated at this facility. In the early postoperative evaluation, 64 patients (44.7%) presented systemic complications, with pulmonary infection being the most frequent; 51 patients (35.6%) presented local complications, with cervical esophagogastric anastomosis leak being the most frequent. Thirteen patients (9.1%) died as a result of postoperative complications. Out of 112 patients who were adequately followed up, 91 (81.2%) achieved good palliation with this procedure, as they had adequate restoration of swallowing function, with a median survival of 3 years in 63 patients (69.2%). With these results, it is possible to conclude that despite showing non-negligible morbidity, IGCGT can be performed quickly and safely, offering adequate palliation and survival rate.
The Ethical and Religious Directives
Authors: Brehany John F. ,   The National Catholic Bioethics Center
Published: October 2023

The first edition of the Ethical Religious Directives for Catholic Health Care Services was published in 1948. Since then, it has undergone two major revisions and several smaller ones. The following essay explores the history of the ERDs and the important aspects of these revisions.
BÁO CÁO CA LÂM SÀNG ĐIỀU TRỊ XUẤT HUYẾT TIÊU HÓA TRÊN DO LOÉT TO HÀNH TÁ TRÀNG BIẾN CHỨNG VỠ TÚI GIẢ PHÌNH ĐỘNG MẠCH VỊ TÁ TRÀNG BẰNG THUYÊN TẮC NỘI MẠCH
Authors: Phan Văn Bạc , Võ Xuân Sang , Nguyễn Ngọc Huy , Phạm Ngọc Sơn
Published: October 2023

Vỡ giả phình động mạch vị tá tràng là một nguyên nhân xuất huyết tiêu hóa trên hiếm gặp, và bệnh có tỉ lệ tử vong đến 21%. Chỉ định can thiệp thuyên tắc nội mạch sau khi cầm máu qua nội soi thất bại mang lại hiệu quả cao. Chúng tôi báo cáo một trường hợp vào tháng 9/2022, bệnh nhân nữ, 72 tuổi xuất huyết tiêu hóa đe dọa tính mạng, có ổ loét lớn ở vị trí mặt trước hành tá tràng, tái xuất huyết sau nhiều lần nội soi cầm máu. Túi giả phình ở động mạch vị tá tràng liền kề vị trí ổ loét được phát hiện trên CT mạch máu, sau đó được can thiệp thuyên tắc nội mạch bằng coil kèm NCBA thành công.
NGHIÊN CỨU ĐẶC ĐIỂM HÌNH ẢNH HỌC VÀ GIÁ TRỊ CỦA CỘNG HƯỞNG TỪ MẠCH MÁU TOF 3D 3.0 TESLA TRONG PHÁT HIỆN PHÌNH ĐỘNG MẠCH NÃO TẠI BỆNH VIỆN ĐỘT QUỴ TIM MẠCH CẦN THƠ
Authors: Đinh Văn Tuyền , Trần Chí Cường
Published: October 2023

Đặt vấn đề: Phình mạch não một trong những nguyên nhân phổ biến gây xuất huyết dưới nhện không do chấn thương. Cộng hưởng từ mạch máu từ trường cao 3.0 Tesla đóng vai trò quan trọng trong chẩn đoán phình động mạch não. Mục tiêu nghien cứu: Mô tả đặc điểm lâm sàng, hình ảnh học của phình động mạch não và giá trị của chụp mạch cộng hưởng từ 3.0 Tesla trong phát hiện phình động mạch não tại Bệnh viện Đột quỵ tim mạch Cần Thơ. Đối tượng và phương pháp nghiên cứu: Nghiên cứu tiến cứu, mô tả cắt ngang trên 110 bệnh nhân xuất huyết dưới nhện, nghi ngờ phình mạch máu não được chụp cộng hưởng từ mạch máu não, sau đó được chụp mạch số hóa xóa nền. Kết quả: Tổng cộng có 128 phình mạch não trên 110 bệnh nhân. Độ tuổi trung bình có phình mạch não là 57,73±11,86. Cộng hưởng từ mạch máu 3D TOF MRA có độ nhạy, độ đặc hiệu, độ chính xác lần lượt là 95,6%, 100%, 96,36%. Đối với những phình có kích thước rất nhỏ <3mm, độ nhạy, độ đặc hiệu, độ chính xác lần lượt là 90,5%, 100%, 95%. Đối với những phình có kích thước ≥3mm, độ nhạy, độ đặc hiệu, độ chính xác lần lượt là 98,1%, 100%, 98,4%. Kết luận: Chụp cộng hưởng từ mạch máu 3D TOF 3.0 Tesla là một phương pháp không xâm lấn, giúp chẩn đoán chính xác phình mạch não.
ĐÁNH GIÁ ĐỘC TÍNH CẤP VÀ TÁC DỤNG KIỂM SOÁT LIPID HUYẾT CỦA CAO CHIẾT ETHANOL LÁ CÂY MẬT GẤU NAM TRÊN MÔ HÌNH CHUỘT NHẮT TRẮNG TĂNG LIPID HUYẾT BẰNG TYLOXAPOL
Authors: Nguyễn Thị Mỹ Hạnh , Cao Thị Tài Nguyên , Mai Huỳnh Như
Published: October 2023

Đặt vấn đề: Mật gấu nam (Vernonia amygdalina Asteraceae), là một loại cây được trồng phổ biến ở Việt Nam. Cây Mật gấu nam có tác dụng chống oxy hóa, hạ đường huyết, hạ lipid huyết,… Mục tiêu nghiên cứu: Nghiên cứu này nhằm mục đích đánh giá độc tính cấp và tác dụng giảm rối loạn lipid huyết của cao chiết lá Mật gấu nam trên mô hình chuột nhắt trắng gây tăng lipid huyết bằng tyloxapol. Đối tượng và phương pháp nghiên cứu: Cao chiết ethanol lá Mật gấu nam. Độc tính cấp được tiến hành dựa theo tài liệu: “Hướng dẫn thử nghiệm tiền lâm sàng và lâm sàng thuốc đông y, thuốc từ dược liệu, số 141/QĐ-K2ĐT ngày 27/10/2015 của Bộ Y Tế năm 2015”. Chuột được gây tăng lipid huyết bằng cách tiêm phúc mô một liều duy nhất tyloxapol (400 mg/kg). Kết quả: Với liều 15 g/kg trọng lượng chuột, cao chiết lá Mật gấu nam không thể hiện độc tính cấp đường uống. Thêm vào đó, những chuột được uống cao chiết lá cây Mật gấu nam với liều 500 mg/kg, 1500 mg/kg và atorvastatin liều 60 mg/kg thể trọng chuột cho thấy sự giảm đáng kể nồng độ triglycerid (p < 0,05) nhưng không giảm nồng độ cholesterol toàn phần (p > 0,05) trong huyết tương chuột khi so sánh với nhóm chứng. Kết luận: Cao chiết lá Mật gấu nam không gây độc tính cấp đường uống. Nghiên cứu này cho thấy, cao chiết lá Mật gấu nam có tác dụng hạ triglycerid ở liều 500 mg/kg và 1500 mg/kg so với nhóm chứng bệnh (p < 0,05). Trong khi đó, liều 250 mg/kg không có tác dụng hạ triglycerid ở mô hình chuột gây tăng lipid máu cấp bằng tyloxapol với liều 400 mg/kg.
The Role of PAI Teachers' Social Competence in the Learning Process
Authors: B.S Iman Asroa , Mastura Lidiya Fadhlah
Published: October 2023

This study examines the role of social competence possessed by PAI teachers on the PAI learning process at SMP IT Insan Kamil Batusangkar. The background of this research is the influence caused as a result of the social competence of PAI teachers at SMP IT Insan Kamil Batusangkar. Based on these problems, a research question arises in the form of what is the role of the social competence of PAI teachers in the PAI learning process at SMP IT Insan Kamil Batusangkar? The research was conducted with a qualitative approach using field research methods. Data were collected by conducting field observations and interviews with PAI teachers and teacher and student councils. The data obtained were processed using the Miles & Huberman data analysis method by collecting data, reducing the data that had been collected, analyzing and presenting the results of data analysis. From the results of the analysis, it is concluded that the social competence of PAI teachers plays a very important role in the PAI learning process at SMP IT Insan Kamil Batusangkar. This role can be seen in the ongoing learning process, student achievement, and student social intelligence.
John H. Walton: “The Lost World of Genesis One: Ancient Cosmology and the Origins Debate” and “The Lost World of Adam and Eve: Genesis 2–3 and the Human Origins Debate”
Authors: Sherlo Charles
Published: October 2023

Charles Sherlock reviews two books by John Walton: “The Lost World of Genesis One: Ancient Cosmology and the Origins Debate” and “The Lost World of Adam and Eve: Genesis 2–3 and the Human Origins Debate”
Nonlinear degenerate elliptic equations in weighted Sobolev spaces
Authors: Benali Aharrouch , Jaouad Bennouna
Published: October 2023

We study the existence of solutions for the nonlinear degenerated elliptic problem $$\displaylines{ -\operatorname{div} a(x,u,\nabla u)=f \quad\text{in } \Omega,\cr u=0 \quad\text{on }\partial\Omega, }$$ where \(\Omega\) is a bounded open set in \(\mathbb{R}^N\), \(N\geq2\), a is a Caratheodory function having degenerate coercivity \(a(x,u,\nabla u)\nabla u\geq \nu(x)b(|u|)|\nabla u|^p\), 1<p<N, \(\nu(\cdot)\) is the weight function, b is continuous and \(f\in L^r(\Omega)\).

For more information see https://ejde.math.txstate.edu/Volumes/2020/105/abstr.html
Local existence and blow-up criterion for the two and three dimensional ideal magnetic Benard problem
Authors: Manna Utpal , Ashirbad Panda Akash
Published: October 2023

In this article, we consider the ideal magnetic Benard problem in both two and three dimensions and prove the existence and uniqueness of strong local-in-time solutions, in Hs for s > (n/2)+1, n = 2,3. In addition, a necessary condition is derived for singularity development with respect to the BMO-norm of the vorticity and electrical current, generalizing the Beale-Kato-Majda condition for ideal hydrodynamics.
For more information see https://ejde.math.txstate.edu/Volumes/2020/91/abstr.html
Estymatory kalibracyjne w badaniach statystycznych
Authors: Szymkowiak Marcin
Published: October 2023

The literature proposes two basic statistical techniques: imputation and weighting. They mitigate the negative impact of non-response test results. One of the weighing methods, used by some foreign statistical offices, is calibration, which consists of correcting the output weights resulting from the sampling scheme using a variety of auxiliary variables. Calibration can also be used in the complete surveys, and the starting point in its practical application is to establish an appropriate baseline — artificial weights. This article presents an example of how to use the calibration approach. With it one can create contingency tables based on the data from complete surveys (censuses, administrative records).
Analiza potencjału kreatywności mieszkańców Warszawy
Authors: Podogrodzka Małgorzata
Published: October 2023

The observed transformations of Warsaw for years relate i.a. a creative potential of human resources. The article presents the socio-demographic population structure of the capital, a proposal to assess their creativity, through the fixing a synthetic variable based on the statistical characteristics such as gender, age and education as well as population density.
Działalność innowacyjna przedsiębiorstw przemysłowych
Authors: Baruk Jerzy
Published: October 2023

In this publication the author discusses selected measures of technological, organisational and marketing innovations in industrial enterprises in Poland. The level of these measures and their dynamics is compared with aims which have been received in the National strategy of cohesion. This methodical approach shows significant divergence between strategic aims of the Polish economy and reality. A small percentage of industrial enterprises fulfils criterion of innovation enterprise.
Dezaktywizacja zawodowa społecznym skutkiem transformacji
Authors: Ptaszyńska Barbara
Published: October 2023

The observed increase in the labor market deactivation is one of the most important effects of changes in Poland. While in the EU countries we can observe an increasing labor force participation rate, in Poland we note the continuing downward trend. One reason for this phenomenon is the deactivation of near retirement aged persons. It is related to the possibility to take advantage of early retirement or other benefits. One of the main reasons for this process is the employment policy in transition.
Działalność Komisji Matematycznej GUS w latach 1950–1993
Authors: Kordos Jan
Published: October 2023

Article relates to the author’s paper “The interaction between the development of the theory and practice of sample surveys in Poland”, delivered at the Congress. Consultation given to the Mathematical Commission by Professor Jerzy Neyman in the years 1950–1958 were especially widely discussed, as well as the activities of the body in the application of mathematical methods in CSO surveys. Conclusions of the Commission’s core activities and their impact for the development of official statistics are discussed, too.