bluuebunny/crossref_metadata_2025_split huggingface dataset:
Aspectos Democráticos da Lei de Incentivo à Cultura e sua relação com a promoção do Pluralismo Cultural
Authors: Teixeira Lusvanio Carlos , Silva Xavier Wescley , Rodrigues de Faria Evandro 
Published: August 2023

Objetivo da Pesquisa: Verificar se a Lei de Incentivo à Cultura (LIC) contribui para a democratização do acesso e da difusão de diferentes manifestações culturais, promovendo o pluralismo cultural na distribuição de recursos entre produções e proponentes culturais.
Enquadramento Teórico: As relações entre Democracia e Cultura e elementos de funcionamento da LIC embasaram a análise da lei em termos de pluralismo cultural.
Metodologia: Partiu-se da abordagem qualitativa e quantitativa, para descrever a distribuição de recursos realizada pela LIC, utilizando-se instrumentos de análise documental e estatística descritiva.
Resultados: Desvelou-se a existência de uma concentração maciça de recursos em determinadas áreas e proponentes culturais, com destaque para as áreas de artes cênicas e música. Outro aspecto significativo refere-se à profissionalização que o mecanismo demanda, onde apesar de qualquer indivíduo – pessoa física ou jurídica – poder se tornar proponente cultural, a maior parte dos recursos é direcionada para pessoas jurídicas.Originalidade: Análise da LIC pela lente democrática, num levantamento inédito até o presente momento, com enfoque em compreender a capacidade do principal instrumento de financiamento à cultura no Brasil em termos de promoção do pluralismo cultural.
Contribuições Teóricas e Práticas: Realizou-se uma análise da LIC pela perspectiva democrática, analisando os resultados da lei e a promoção de pluralismo cultural. Além disso, o artigo dá transparência no direcionamento de recursos e revela concentrações de recursos em determinadas áreas e atores culturais.
PALAVRAS-CHAVE: Incentivo Fiscal à Cultura; Cultura; Políticas Culturais; Democracia; Financiamento à Cultura.
Interação e Autonomia entre Estado e Capital: Uma Análise Baseada nos Membros da Câmara Brasileira da Indústria 4.0
Authors: Paço Cunha Elcemir , Peterson Alves Mendes Giovani , Vieira Ferreira Rodrigo 
Published: August 2023

Objetivo da pesquisa: Analisar a interação e a autonomia dos aparatos administrativos do governo federal ligados ao desenvolvimento de política de inovação tecnológica a partir de respondentes vinculados ao poder público e à representação do setor econômico, ambos os grupos ligados/componentes da Câmara Brasileira da Indústria 4.0.
Enquadramento teórico: Autonomia estatal e interação entre capital e Estado fundamentadas no materialismo científico.
Metodologia: Realizou-se dois surveys. O primeiro junto aos burocratas dos ministérios componentes do Conselho Superior da Câmara Brasileira da Indústria 4.0, obtendo-se 117 questionários respondidos conforme Paço Cunha e Mendes (2022) e o segundo junto aos integrantes de entidades representantes do empresariado componentes da Câmara Brasileira da Indústria 4.0, obtendo-se 41 questionários respondidos. Os dados foram posteriormente compilados, expostos na forma de tabelas e analisados a partir de estatística descritiva.
Resultados: Os resultados sugerem haver uma alta interação e limitações quanto à autonomia dos aparelhos administrativos frente às interferências econômicas e políticas.
Originalidade: Discute a autonomia estatal e a interação entre capital e Estado a partir de surveys realizados com representantes de ambos os setores ligados (Governo e Empresas) à Câmara Brasileira da Indústria 4.0.
Contribuições teóricas e práticas: Retoma a discussão a respeito da autonomia e interação do aparato estatal brasileiro a partir de um prisma materialista e aponta para considerável frequência de interferências políticas e econômicas e para o possível questionamento da autonomia do quadro administrativo com vistas ao seu aperfeiçoamento futuro.
O Que se Espera do Ensino Fundamental: Famílias e Docentes Convergem em Termos de Expectativas?
Authors: Davel da Silva Fernanda , Magno Marchiori Danilo 
Published: August 2023

Objetivo de pesquisa: O objetivo deste estudo é identificar se as famílias e docentes convergem em termos de expectativas relacionadas ao ensino desenvolvido em escolas públicas de ensino fundamental. De forma complementar, busca-se identificar quais são os fatores que influenciam a expectativa dos familiares em relação à expectativa sobre o ensino da escola e sobre a escola de maneira geral.
Enquadramento teórico: O estudo discute o conceito do Modelo dos 5 Gaps, conceitos teóricos de gerenciamento de expectativas em organizações, a relação família – escola e o marketing educacional.
Metodologia: A pesquisa possui uma abordagem quantitativa, descritiva e com corte transversal, com dados obtidos por meio da aplicação de questionários estruturados para famílias (pais ou responsáveis) e docentes de escolas.
Resultados: O estudo identificou que existem de fato diferenças de expectativas entre familiares e corpo docente. Os quatro temas mais significativos para a família foram: boa estrutura física, grau de exigência do ensino, acesso às informações dos alunos e liberdade de pensamento e expressão, enquanto que para os docentes os cinco temas mais significativos foram: grau de exigência do ensino, processos burocráticos claros e definidos, ambiente agradável e propício ao aprendizado, expectativa geral sobre o ensino da escola e expectativa geral sobre a escola o que apontam para importantes linhas de ação a serem conduzidas pelos gestores da área educacional.
Originalidade: Discute-se o marketing escolar e a expectativa do cliente na educação básica pública.
Contribuições teóricas e práticas: A pesquisa contribui com discussões relacionadas às percepções de famílias e docentes em escolas de educação básica pública no Brasil bem como na melhoria de tomada de decisão nas escolas de ensino fundamental, visando ampliação da satisfação com os serviços prestados.
Efficient Continuous kNN Join over Dynamic High-dimensional Data
Authors: Ukey Nimish , Zhang Guangjian , Yang Zhengyi , Li Binghao , Li Wei , Zhang Wenjie 
Published: August 2023

Abstract

Given a user dataset U and an object dataset I, a kNN join query in high-dimensional space returns the k nearest neighbors of each object in dataset U from the object dataset I. The kNN join is a basic and necessary operation in many applications, such as databases, data mining, computer vision, multi-media, machine learning, recommendation systems, and many more. In the real world, datasets frequently update dynamically as objects are added or removed. In this paper, we propose novel methods of continuous kNN join over dynamic highdimensional data. We firstly propose the HDR+ Tree, which supports more efficient insertion, deletion, and batch update. Further observed that the existing methods rely on globally correlated datasets for effective dimensionality reduction, we then propose the HDR Forest. It clusters the dataset and constructs multiple HDR Trees to capture local correlations among the data. As a result, our HDR Forest is able to process non-globally correlated datasets efficiently. Two novel optimisations are applied to the proposed HDR Forest, including the precomputation of the PCA states of data items and pruning-based kNN recomputation during item deletion. For the completeness of the work, we also present the proof of computing distances in reduced dimensions of PCA in HDR Tree. Extensive experiments on realworld datasets show that the proposed methods and optimisations outperform the baseline algorithms of naive RkNN join and HDR Tree.
Soluble CD14 produced by bovine mammary epithelial cells modulates their response to full length LPS
Authors: Védrine Mégane , Gilbert Florence B. , Maman Sarah , Klopp Christophe , Gitton Christophe , Rainard Pascal , Germon Pierre 
Published: August 2023

Abstract

Bovine mastitis remains a major disease in cattle world-wide. In the mammary gland, epithelial cells are sentinels equipped with receptors allowing them to detect and respond to the invasion by bacterial pathogens, in particular Escherichia coli. Lipopolysaccharide (LPS) is the major E. coli motif recognized by MEC through its interaction with the TLR4 receptor and the CD14 co-receptor. Previous studies have highlighted the role of soluble CD14 in the efficient recognition of LPS molecules possessing a full-length O-antigen (LPSS). We demonstrate here that MEC are able to secrete CD14 and are likely to contribute to the presence of soluble CD14 in milk. We then investigated how CD14 modulates and is required for the response of MEC to LPSS. This study highlights the key role of soluble CD14 for the full activation of the Myd88-independent pathway by LPSS. We also identified several long non-coding RNA that are activated in MEC in response to LPS, including one lncRNA showing homologies with the mir-99a-let-7c gene (MIR99AHG). Altogether, our results provide detailed information on how milk soluble CD14 can contribute to an efficient recognition of LPS from coliform pathogens.
A combined landfarming-phytoremediation method to enhance remediation of mixed persistent contaminants
Authors: Tehrani Mohamad Reza Fadaei , Besalatpour Ali Asghar 
Published: August 2023

Abstract

Contamination of soil and water with petroleum hydrocarbons and metals can pose a significant threat to the environment and human health. This study aimed to investigate the establishment and growth of high fescue and agropyron in two petroleum-contaminated soils (soil S1 and soil S2) with previous landfarming treatments, and to assess the phytoremediation potential for heavy metal removal from these polluted soils. The results showed that the presence of petroleum hydrocarbons significantly (P < 0.05) reduced plant growth, but plant development was facilitated in soils with prior landfarming treatments. Urease activity in the rhizosphere of agropyron for soil S1 was about 47% higher than the unplanted control soil. The rhizosphere of agropyron and tall fescue eliminated more than 40% and 20% of total hydrocarbon amounts in soil S1, respectively, compared to the unplanted soil. Moreover, the plants grown in the landfarming treatment exhibited higher concentrations of metals (Fe, Zn, Mn, Cu, and Ni) than the control. Based on the findings, the combination of landfarming and phytoremediation techniques can provide an optimal solution for removing mixed pollutants, including petroleum hydrocarbons and metals, from the environment.
Research hotspots and thematic trends in the management of pre-eclampsia: a bibliometric analysis from 2000 to 2022
Authors: Shen Xiao , Tao Yuchen , Wang Yixiao , Obore Nathan , Yu Hong 
Published: August 2023

Abstract

Background
Pre-eclampsia (PE) is one of the serious complications of pregnancy, and the management of PE remains an important problem for obstetricians. This study aims to identify the characteristics and trends of published articles on PE management through bibliometric analysis.
Methods
We searched Web of Science database for articles related to PE management from 2000 to 2022. Metadata was obtained, including the titles, publication dates, authors, institutions, countries, and keywords of all articles, and then network visualization and burst keyword analysis were performed using Citespace and VOSviewer software.
Results
A total of 5190 articles were included in the analysis. The number of publications in the field of PE management has steadily increased over the years, and a visual analysis of collaborative networks of authors, institutions, and countries revealed that the United States, United Kingdom, Australia, and Canada have contributed the most to the field and formed extensive collaborations. The Journal of maternal-fetal & neonatal medicine has the most publications in this field, and the Journal of Obstetrics and gynecology has not only more publications but also 64.75 citations per article. The keywords mainly focused on prevention, diagnosis, risk factors, and outcome of PE. In addition, hypertensive disorders of pregnancy and fetal growth restriction have received a lot of attention in this field in recent years.
Conclusions
We analyzed the partnerships in PE management through bibliometrics and showed trends in the field. The available results suggest that PE management will continue to be a focus of attention.
A Performance Comparison of Deep Learning and Shallow Machine Learning in Acoustic Emission Monitoring of Aluminum Alloy Pulsed Laser Welding
Authors: Zeng Da , Wu Di , Luo Zhongyi , Dong Jinfang , Huang Hongxing , Yang Fangyi , Zhang Peilei , Xin Ye 
Published: August 2023

Abstract
The penetration depth is one of the important indicators in aluminum alloy laser welding, which is closely related to the welding quality. In-situ monitoring penetration depth can provide a judging basis for the process optimization, so as to reduce the occurrence of lack of penetration or burn-through defects. In this paper, the acoustic emission (AE) technique combing with various machine learning (ML) algorithms, including the shallow machine learning (SML) and deep learning (DL) algorithms, were proposed to predict the weld penetration. Furthermore, the class activation map (CAM) method was applied to visualize and explain the prediction mechanism of convolutional neural network (CNN). The comparison results demonstrated that the combination of ML and AE monitoring can achieve very accurate penetration prediction, and the classification performance of DL algorithm is stronger than that of SML algorithm. In addition, the CAM method can effectively reveal the important feature areas related to penetration in AE signal, which provides valuable information for the understanding and optimization of DL algorithm. In summary, our work proposes a new approach for in-situ penetration monitoring of aluminum alloy pulse laser welding, which can improve the welding quality and efficiency.
The Genetic Basis of Resilience: A Genome-Wide Association Study Meta-Analysis in the German Population
Authors: Herrera-Rivero Marisol , Garvert Linda , Horn Katrin , Löbner Margrit , Weitzel Elena , Stoll Monika , Lichtner Peter , Teismann Henning , Teumer Alexander , Auwera Sandra Van der , Völzke Henry , Völker Uwe , Andlauer Till , Meinert Susanne , Heilmann-Heimbach Stefanie , Forstner Andreas J. , Streit Fabian , Witt Stephanie , Kircher Tilo , Dannlowski Udo , Scholz Markus , Riedel-Heller Steffi , Grabe Hans , Baune Bernhard , Berger Klaus 
Published: August 2023

Abstract

Resilience is the capacity to adapt to stressful life events. As such, this trait is associated with physical and mental functions and conditions. Here, we aimed to identify the genetic factors contributing to shape resilience. We performed variant- and gene-based meta-analyses of genome-wide association studies from six German cohorts (N = 15822) using the 11-item version of the Resilience Scale (RS-11) as outcome measure. Variant- and gene-level results were combined to explore the biological context using network analysis. In addition, we conducted tests of correlation between RS-11 and the polygenic scores (PGSs) for 12 personality and mental health traits in one of these cohorts (PROCAM-2, N = 3879). Our analyses suggested five genomic loci (p < 1x10− 5) in the variant-based analysis and 33 potential candidates (p < 1x10− 4) in the gene-based analysis, including three genome-wide significant genes (ROBO1, CIB3 and LYPD4), associated with resilience. Network analysis revealed enrichment of biological pathways related to neuronal proliferation and differentiation, synaptic organization, immune responses and vascular homeostasis. We also found significant correlations (FDR < 0.05) between RS-11 and the PGSs for neuroticism and general happiness. These observations improve our understanding of the genetic architecture underlying resilience and of its relationship with other personality traits and mental health.
Effect of heat treatment on the properties of D and G lattice structures with different cell sizes fabricated by SLM
Authors: Tang Qian , Nie Yunfei 
Published: August 2023

Abstract

Triply periodical minimal surface (TPMS) structures fabricated by additive manufacturing (AM) technology has been widely used in aerospace and biomedical fields. In this study, the Diamond (D) and Gyriod (G) TPMS structures with the same volume fraction 20%, consistent overall size Φ12*18mm3(unit cell size of 2mm, 3mm and 6mm) were fabricated via selective laser melting (SLM). The effects of heat treatment on mechanical properties, deformation behavior and energy absorption properties of these structures have been systematically investigated. The results show that all as-built D structures exhibit 45° V-shaped fractures, while the fracture pattern of the G structure depends on the unit size. The D202 structure exhibits the highest resistance to compressive failure, and heat treatment can significantly enhance the deformation capability of lattice structures with small cell unit. The study also found that cell unit size has a greater influence on the energy absorption capacity than enhancement by heat treatment and cell structure type. These findings provide inspiration and guidance for the design and heat treatment of lattice structures with both load-bearing and energy-absorbing applications.
Usefulness of transbronchial lung cryobiopsy when choosing treatment for chronic fibrosing interstitial lung disease: Descriptive research
Authors: Takatsuka Makiko , Yamakawa Hideaki , Takemura Tamiko , Sato Shintaro , Ohta Hiroki , Kusano Kenji , Oba Tomohiro , Kawabe Rie , Akasaka Keiichi , Sasaki Hiroki , Amano Masako , Araya Jun , Matsushima Hidekazu 
Published: August 2023

Abstract
Background: Although transbronchial lung cryobiopsy (TBLC) is widely used in diagnostic algorithms for various interstitial lung diseases (ILD), its real-world utility in the therapeutic decision-making strategy for ILD patients remains unclear.
Methods: We analyzed medical records of 40 consecutive patients with idiopathic or fibrotic hypersensitivity pneumonitis who underwent TBLC. A TBLC-based usual interstitial pneumonia (UIP) score was used to assess three morphologic descriptors: i) patchy fibrosis, ⅱ) fibroblastic foci, and ⅲ) honeycombing.
Results: In our 40 patients with ILD, the most frequent radiological feature was indeterminate for UIP (45.0%). Final diagnosis included idiopathic pulmonary fibrosis (22.5%), fibrotic nonspecific interstitial pneumonia (5.0%), fibrotic hypersensitivity pneumonitis (35.0%), and unclassifiable ILD (37.5%). Linear mixed-effects analysis showed that declines in the slopes of %FVC and %DLCO in patients with TBLC-based UIP ‘Score ≥2’ were significantly steeper than those of patients with ‘Score ≤1’. During follow-up of patients with ‘Score ≥2’ (n = 24), more than half of them received combination therapy (i.e., anti-inflammatory and anti-fibrotic agents). Moreover, in the groups receiving an anti-fibrotic agent, many patients received anti-fibrotic agent administration within 6 months after the TBLC procedure. Among the groups with combination therapy, most patients received an anti-fibrotic agent within 6 months of the multi-disciplinary discussion-based diagnosis.
Conclusions: TBLC-based UIP score ≥2 indicated the increased possibility of a progressive fibrosis course that may prove helpful in predicting progressive pulmonary fibrosis/progressive fibrosing ILD even if disease is temporarily stabilized due to anti-inflammatory agents. Patients may benefit from early introduction of anti-fibrotic agents by treating clinicians.
Evaluating Hyperspectral Techniques Using Objective Metrics Research on Analog Narrowband Image
Authors: Yang Kai-Yao , Mukundan Arvind , Tsao Yu-Ming , Shi Xian-Hong , Huang Chien-Wei , Wang Hsiang-Chen 
Published: August 2023

Abstract
The evident signs of esophageal cancer (EC) typically do not become noticeable until the middle or late stages. The survival rate of EC is reduced to less than 20% if it is detected in the latter stages. This paper compares the performance of white light image (WLI), narrowband imaging (NBI), cycle-consistent adversarial network (CycleGAN) simulated narrowband image (CNBI), and hyperspectral imaging (HSI) simulated narrowband image (HNBI) to detect EC in its early stages. A total of 1000 EC images (500 WLI images and 500 NBI images) were used as dataset in collaboration with Kaohsiung Armed Forces General Hospital. The CycleGAN model was used to produce CNBI. An HSI imaging algorithm was also developed to produce HNBI images. The effectiveness of these four types of images in detecting EC at its early stages was evaluated based on three indicators, namely, CIEDE2000, entropy, and structural similarity index measure (SSIM). Results of CIEDE2000, entropy, and SSIM analysis suggest using CycleGAN to generate CNBI and HNBI images is superior in detecting EC compared with normal WLI and NBI.
Intelligent Energy Management with IoT Framework in Smart Cities Using Intelligent Analysis: An Application of Machine Learning Methods for Complex Networks and Systems
Authors: Nikpour Maryam , Yousefi Parisa Behvand , Jafarzadeh Hadi , Danesh Kasra , Ahmadi Mohsen 
Published: August 2023

Abstract
Smart buildings are increasingly using Internet of Things (IoT)-based wireless sensing systems to reduce their energy consumption and environmental impact. As a result of their compact size and ability to sense, measure, and compute all electrical properties, Internet of Things devices have become increasingly important in our society. A major contribution of this study is the development of a comprehensive IoT-based framework for smart city energy management, incorporating multiple components of IoT architecture and framework. An IoT framework for intelligent energy management applications that employ intelligent analysis is an essential system component that collects and stores information. Additionally, it serves as a platform for the development of applications by other companies. Furthermore, we have studied intelligent energy management solutions based on intelligent mechanisms. The depletion of energy resources and the increase in energy demand have led to an increase in energy consumption and building maintenance. The data collected is used to monitor, control, and enhance the efficiency of the system.
The Impact of Climate Change on Cognitive Performance among Workers: A Systematic Literature Review
Authors: Habibi Peymaneh , Razmjouei Jaleh , Moradi Gholamreza , Badzohreh Abdollah , Falla-Aliabadi Saeed , Heydari Ahad 
Published: August 2023

Abstract
Due to climate change and global warming, attention-demanding tasks, continuous performance tasks, choice reaction time and vigilance tasks have become less efficient, which can, directly and indirectly affect cognitive performance, specifically among workers exposed to hot-dry and hot-wet environments. This systematic study was done by reviewing research studies on the impact of climate change on cognitive performance and gathering physiological responses that can increase vulnerability to climate-related cognitive performance among workers. In this study, a total of 3487 articles from experienced worker population (men = 574; women = 94) in various real-world environmental and experimental climate conditions were searched. Climate change causes the most significant decrease in cognitive performance, especially in attention-demanding tasks. Decreasing vigilance performance in hot seasons is one of the outcomes of global warming. The effect of high temperature and heat stress on cognitive performance correlated with changes in physical parameters (air temperature, relative humidity (RH), etc.) and physiological parameters (core-body and skin temperature, heart, breathing, and sweating rate, etc.). It is required to develop more studies, especially in various real-world environments, and develop a framework to strengthen workers’ awareness for considering the impact of climate change on cognitive performance among workers. The present study results can be used to inform policy-makers with physiological parameters and upper limit values for occupational exposure to thermal stress.