bluuebunny/crossref_metadata_2025 huggingface dataset:
A Review of the Potential of Non-timber Forest Products to Alleviate Poverty
Authors: Asamoah Obed , Danquah Jones Abrefa , Bamwesigye Dastan , Verter Nahanga , Quartey Ebo Tawiah , Boateng Charles Mario , Kuittinen Suvi , Boakye Emmanuel A. , Appiah Mark , Pappinen Ari
Published: December 2023

Non-timber forest Products (NTFPs) are a broad category of natural resources harvested from forests that do not involve cutting down trees for their wood or timber. NTFPs play a vital role in the livelihoods and economies of many rural communities, particularly in forest-dependent regions. Despite the benefits obtained from NTFPS, little is known about its potential to alleviate poverty in the local communities. The objective of this review is to comprehensively assess the potential of NTFP's contribution to poverty reduction within forest fringe communities. The study employed the systematic review method to delve into the multifaceted relationship between NTFPs and poverty alleviation. We followed the preferred reporting items for systematic reviews and meta-analyses protocol (PRISM-P). In all, 58 research articles were reviewed. The results indicated that NTFPs hold significant promise as a tool for poverty alleviation. Globally, NTFPs have the potential to alleviate poverty and increase household incomes between 19% and 78% within forest fringe rural communities. In addition, the review indicated that countries in Africa and Asia depend highly on NTFPs and provide substantial amounts of income to the locals. However, the potential for NTFPs to reduce poverty is not uniform. It is highly contingent upon local ecological conditions, market accessibility, community involvement, and supporting policies and interventions. In conclusion, this systematic review demonstrates that NTFPs have a substantial role in poverty alleviation. This study underscores the need for continued research and targeted development initiatives to unlock the vast potential of NTFPs in addressing poverty challenges.
Different Mechanisms in Doxorubicin-induced Cardiomyopathy: Impact of BRCA1 and BRCA2 Mutations
Authors: Nguyen Hien C. , Frisbee Jefferson C. , Singh Krishna K.
Published: December 2023

Germline mutations in Breast cancer susceptibility gene 1 and 2 (BRCA1 and BRCA2) cause breast, ovarian and other cancers, and the chemotherapeutic drug doxorubicin (Dox) is widely used to treat these cancers. However, Dox use is limited by latent induction of severe cardiotoxicity known as Dox-induced cardiomyopathy, for which there are no specific treatments currently available. Dox is administered into the systemic circulation, where it readily translocates into sub-cellular compartments, and disrupts the integrity of DNA. Accumulating evidence indicates that oxidative stress, DNA damage, inflammation and apoptosis all play a central role in Dox-induced cardiomyopathy. The BRCA1 and BRCA2 proteins are distinct as they perform crucial yet separate roles in the homologous recombination repair of DNA double-strand breaks, thereby maintaining genomic integrity. Additionally, both BRCA1 and BRCA2 mitigate oxidative stress and apoptosis in both cardiomyocytes and endothelial cells. Accordingly, BRCA1 and BRCA2 are essential regulators of pathways that are central to the development of cardiomyopathy induced by Doxorubicin. Despite extensive investigations, there exists a gap in knowledge about the role of BRCA1 and BRCA2 in Doxorubicin-induced cardiomyopathy. Here, we review the previous findings and associations about the expected role and associated mechanisms of BRCA1 and 2 in Dox-induced cardiomyopathy and future perspectives.
Optimal Treatment Strategy for Oligo-Recurrence Lung Cancer Patients With Driver Mutations
Authors: Tachibana Taimei , Matsuura Yosuke , Ninomiya Hironori , Ichinose Junji , Nakao Masayuki , Okumura Sakae , Nishio Makoto , Ikeda Norihiko , Mun Mingyon
Published: December 2023

Background: The efficacy of local therapies for lung cancer patients with postoperative oligo-recurrence has been reported. However, whether local therapies should be chosen over molecular targeted therapies for oligo-recurrence patients with driver mutations remains controversial. We hence aimed to investigate the optimal initial treatment strategy for oligo-recurrence in lung cancer patients with driver mutations.
Methods: Among 2,152 patients with lung adenocarcinoma who underwent surgical resection at our institute between 2008 and 2020, 66 patients with driver mutations who experienced cancer oligo-recurrence after surgery, and were treated with local or molecularly targeted therapy as an initial therapy after recurrence were evaluated. Oligo-recurrence was characterized by the presence of 1 to 3 recurrent lesions. These patients were investigated focusing on their post-recurrence therapies and prognoses.
Results: The median follow-up period was 71 months. Local and molecular targeted therapies were administered to 41 and 25 patients, respectively. The number of recurrence lesions tended to be lower in the initial local therapy group than in the molecular targeted therapy group. In the initial local therapy group, 23 patients (56%) subsequently received molecular targeted therapies. The time from recurrence to the initiation of molecular targeted therapy was significantly longer in the local therapy group than in the molecular targeted therapy group (p < 0.001). There was no significant difference in post-recurrence overall survival (hazard ratio, 1.429; 95% confidence interval, 0.701–2.912; log-rank, p = 0.324), and post-recurrence progression-free survival (hazard ratio, 0.799; 95% confidence interval, 0.459–1.390; log-rank, p = 0.426) in the initial local ablative therapy group compared with the initial molecular targeted therapy group.
Conclusions: Local therapies as a first-line treatment did not show statistically significant differences in post-recurrence survival or progression-free survival compared with molecular targeted therapies. However, local therapies as an initial treatment should be considered preferably, as it can cure the recurrence and can delay the start of administration of molecular-targeted therapies.
Agriculture By -Products Wastes as Low-Cost Bio-Sorbents for Heavy Metals Removal from Industrial Waste Stream, Short Review
Authors: Habib Mohamed Ahmed , Mohamed Inas Elkhedr
Published: December 2023

ABSTRACT
Heavy metals have been classified as dangerous environmental pollutants. Interest in feasible ways to reduce heavy metals pollution is a noble goal. Adsorption is an effective method based on its effectiveness and low- cost. Nowadays, low-cost bio-sorbents have been utilized to replace costly expensive adsorbents. Rich cellulose materials are effective heavy metal adsorbents, and their performance can be enhanced via chemical modification. The present work reviews the steady progress in the utilization of agriculture by-product wastes as heavy metal bio-sorbent. The unique advantages of these by-products such as renewability, abundance, simple processing, and low cost, justifier this work. The results confirm that the chemically treated agro-wastes exhibit high- removal efficiency (reaches 95% in most cases). The adsorption isotherm studies indicate that the concentration of the metal ions has a significant effect on the adsorption process. The Freundlich model provides a physical adsorption model of the metal ions on the bio-sorbent surface. Langmuir isotherm offers an estimate of the effect of different factors on the efficiency of the process. The adsorption kinetics studies offer an idea of reaction pathways including the adsorption mechanism and the efficiency of the metal ion removal. Applying the pseudo-first-order and pseudo-second-order models describes the adsorption kinetics. This information can be utilized in developing effective strategies to remove heavy metal ions using chemically treated agro-waste. The data confirmed that chemical modification is a significant parameter in the efficiency of metal ion removal. The feasibility and effectiveness of using these cellulosic by-products as bio-sorbent should be given attention and encouraged.
Analysis of Underlapped Symmetrically Ported Valve Controlled Asymmetric Cylinder Drive
Authors: Wang Huankun , Xu Man , Cao Zijian
Published: December 2023

The valve controlled cylinder drive system is the most common type among hydraulic applications. The nonlinear behaviour in such system is inevitable when the valve spool around its null position [1] , Leaney [2] utilised component linking method to investigate the nonlinearities in a Moog valve controlled asymmetric cylinder drive system by simulation in Fortran, in which a generalised concept is introduced and validated by comparing to the experimental results. An factor is proposed in the generalised concepts to describe the asymmetric cylinder state, which is a constant when the cylinder in extending or retracting, but numerically calculated when the valve spool in the underlap region [2]. This paper utilises the component linking method to simulate the Moog valve controlled asymmetric cylinder drive system in Matlab Simulink, and proposed an analytical solution for factor when the valve spool in the underlap region.
Designing Advanced Drug Delivery Systems: Core-Shell Alginate Particles through Electro-Fluid Dynamic Atomization
Authors: Cruz-Maya Iriczalli , Schiavone Carmine , Ferraro Rosalia , Renkler Nergis Zeynep , Caserta Sergio , Guarino Vincenzo
Published: December 2023

Innovations in drug delivery systems are crucial for enhancing therapeutic efficiency. Our research presents a novel approach based on Electro-fluid dynamic atomization (EFDA) to fabricate core-shell monophasic particles (CSMp) from sodium alginate blends of varying molecular weights. This study explores the morphological characteristics of these particles in relation to material properties and process conditions, highlighting their potential in drug delivery applications. A key aspect of our work is the development of a mathematical model that simulates the release kinetics of small molecules, specifically sodium diclofenac. By assessing the diffusion properties of different molecules and gel formulations through transport and rheological models, we have created a predictive tool for evaluating the efficiency of these particles in drug delivery. Our findings underscore two critical independent parameters for optimizing drug release: the external shell thickness and the diffusivity ratios within the dual layers. This allows for precise control over the timing and intensity of the release profile. The study advances our understanding of EFDA in the fabrication of CSMp and offers promising avenues for enhancing drug delivery systems by tailoring release profiles through particle characteristic manipulation.
Testing for the Multifractality in Air Pollutants Time Series Dynamics and Application to Tabuk Region Case Study
Authors: Aljohani Abdulrahman F. , Ben Mabrouk Anouar Ben , Areshi Mounirah , Bouslimi Jamel , Laatar Ali H. , Shaltout Abdallah A.
Published: December 2023

Fractal analysis of time series aims to extract the hidden or complex structures issued from the associated real data, such as scaling laws, non-stationary, dynamics, and so on. In the present work, the air quality index and its components are considered as time series owing fractal structures. To understand their underlying dynamics, wavelet multifractal approach is applied starting with a wavelet multifractal spectrum test to confirm the multifractality of the underlying data. Next, a new model is introduced improving the classical minmax one, provided with a statistical measure for the adequacy of the new model. The theoretical findings are applied to the north west Tabuk region of Saudi Arabia for environmental and climate data related to pollutants and factors involved in the estimation of the air quality index.
The Future of AI in IoT: Emerging Trends in Intelligent Data Analysis and Privacy Protection
Authors: Marengo Agostino
Published: December 2023

This paper explores the dynamic intersection of Artificial Intelligence (AI) and the Internet of Things (IoT), focusing on emerging trends in intelligent data analysis and privacy protection. Employing a systematic literature review, we analyze recent advancements and challenges in AI-IoT integration. The paper highlights key developments in sensor data anomaly detection, AI-driven big-data analytics, and IoT-based communication techniques. It delves into the complexities of privacy protection in IoT, examining innovative solutions like federated learning and blockchain technologies. The study also addresses the challenges in AI for IoT, prioritizing the most pressing issues such as data security, ethical implementation, and compliance with regulations like GDPR. The research underscores the need for adaptable solutions that balance technological advancements with privacy and security considerations, setting a path for future exploration in AI-empowered IoT applications.
Anti-Bacterial and Antioxidant Potential of an Ostrich Oil Emulsion
Authors: Ponphaiboon Juthaporn , Limmatvapirat Sontaya , Limmatvapirat Chutima
Published: December 2023

This study explores the development of an oil-in-water (O/W) emulsion with a high concentration of ostrich oil, rich in omega-3, -6, and -9 fatty acids, for potential skincare applications. Utilizing Span and Tween emulsifiers, an optimized O/W emulsion containing 20% w/w ostrich oil and 15% w/w mixed emulsifiers was formulated through homogenization, demonstrating the smallest droplet size (5.01 ± 0.43 μm) and appropriate zeta potential (-32.22 mV). The emulsion exhibited antioxidant and antibacterial properties against Staphylococcus aureus, suggesting its suitability for skincare. Stability tests over 6 months at varying temperatures (4 °C, 25 °C, 45 °C) confirmed the emulsion's physical and microbial stability, emphasizing its potential for topical applications. Despite slight changes in acid values (AV) and peroxide values (PV), results remained within acceptable limits. Cytotoxicity assessments on human dermal fibroblasts indicated the emulsion's safety, supporting its suitability for skin application. The emulsion demonstrated antibacterial efficacy against S. aureus and enhanced antioxidant activity compared to ostrich oil alone. The study underscores the importance of emulsification in optimizing the efficacy and stability of ostrich oil in skincare formulations, offering valuable insights for practical applications where stability is critical.
A Comprehensive Review of the Cosmetic Application of Kojic Acid Dipalmitate: Kojic Acid Derivative with Improved Properties
Authors: Ayuhastuti Angreni , Syah Insan Sunan Kurniawan , Megantara Sandra , Chaerunisaa Anis Yohana
Published: December 2023

Kojic acid (KA) has emerged as a prominent tyrosinase inhibitor with considerable potential in cosmetic applications; however, its susceptibility to instability during storage poses a challenge to its widespread use. This review explores the advancements in addressing this limitation through the development of various KA derivatives, focusing on the modification of the C-7 hydroxyl group. Strategies such as esterification, hydroxy-phenyl ether formation, glycosylation, and incorporation into amino acid or tripeptide derivatives have been employed to enhance stability and efficacy. Among these derivatives, Kojic Acid Dipalmitate (KDP), a palmitic ester derivative of KA, stands out for its notable improvements in stability, permeability, and low toxicity. Recent developments indicate a growing utilization of KDP in cosmetic formulations, with over 132 available products on the market, encompassing various formulations. Additionally, three patents and seven advanced system deliveries of KDP further underscore its significance. Despite its increasing prevalence, the literature on KDP remains limited. This comprehensive review aims to bridge this gap by providing insights into the synthesis process, physicochemical properties, pharmaceutical preparation, diverse applications of KDP in cosmetic products, and recent nanotechnology formulations of KDP. This review paper seeks to explore the recent developments in the use of KDP in cosmetics. The goal is to enhance stability, permeability, and reduce the toxicity of KA, with the intention of promoting future research in this promising sector.
Calorie Restriction and Time-Restricted Feeding: Effective Interventions in Overweight or Obese Patients Undergoing Radiotherapy Treatment with Curative Intent for Cancer
Authors: Vega Carmen , Barnafi Esteban , Sánchez César , Acevedo Francisco , Walbaum Benjamin , Parada Alejandra , Rivas Nicolás , Merino Tomás
Published: December 2023

Breast and prostate cancer lead incidence rankings in Chile, with obesity and overweight as important risk factors involved in prognosis. Nutritional interventions have shown to be beneficial therapies in patients with cancer, improving anthropometric and biochemical measurements. This study investigates the feasibility and effectiveness of Calorie Restriction and Time-Restricted Feeding in overweight or obese patients undergoing curative radiotherapy for breast and prostate cancer. The research was conducted as a prospective, interventional, non-randomized clinical trial, involving 27 participants, of whom 23 completed the study. Findings indicate that both interventions are feasible and effective. Notably, Time-Restricted Feeding demonstrated superior adherence and more significant improvements in weight loss and metabolic parameters. A mean weight reduction of 3.6 kg and waist circumference decrease of 4.9 cm was observed across participants. Serum levels of glucose, insulin, LDL, HDL and TG showed an average reduction, indicating positive metabolic changes. Results suggest that Time-Restricted Feeding could be a superior beneficial dietary intervention for cancer patients undergoing radiotherapy, due to its ease of adherence and positive impact on metabolic health. This research contributes to the growing evidence on the role of nutritional interventions in cancer treatment and underscores the need for more extensive studies to validate these findings.
Detecting IoT Anomaly using Fuzzy Subspace Clustering Algorithm
Authors: Mazarbhuiya Fokrul Alom Alom , Shenify Mohamed A , Wungreiphi A S
Published: December 2023

There are many applications of anomaly detection in IoT domain. IoT technology consists of large number of interconnecting digital devices not only generating huge data continuously but also making real-time computations. Since IoT devices are highly exposed due to Internet, they frequently meet with the challenges of illegitimate accesses in the form of intrusions, anomaly, fraud, etc. Identifying these illegitimate accesses in IoT domain can be an exciting research problem. In numerous applications fuzzy clustering and rough set theory have been successfully employed. As the data generated in IoT domains are high-dimensional, the clustering methods used for lower dimensional data cannot be applied efficiently. In this article, mixed approaches consisting of nano topology and fuzzy clustering techniques are proposed for anomaly detection. First of all, the nano topology is generated to find lower dimensional apace and then a couple of well-known fuzzy clustering techniques are employed on it for the efficient anomaly detection. The effectiveness of the proposed approaches is evaluated using time-complexity analysis, experimental studies with a synthetic dataset and a real-life dataset along with comparative studies with traditional fuzzy clustering approaches namely fuzzy c-means clustering (FCM) algorithm, Gustafson-Kessel (GK) Algorithm, Gath-Geva (GG) Algorithm, Mahalanobis Distance based Fuzzy C-Means algorithm (M-FCM), and Common Mahalanobis Distance based Fuzzy C-Means algorithm (CM-FCM). Experimentally, it has been found that the proposed approaches outperform the aforesaid algorithms in terms of detection rates, accuracy rates, false alarm rates and computational times.
High-Stable Hybrid Pigments Prepared From Organic Chromophores and Fluorinated Hydrotalcites
Authors: Hernández Magali , Felipe Carlos , Guzmán-Vargas Ariel , Rivera José Luis , Lima Enrique
Published: December 2023

Structural hydroxide groups in layered magnesium-aluminum double hydroxides were partially replaced by fluoride ions. Fluorinated and fluorine-free materials were used as hosts for two dyes, carminic acid and hydroxyl naphthol blue, resulting in a hybrid pigment color palette. Additionally, the pigments were protected with a magnesium hydroxide phase to prevent the color from fading over time. The color properties of the pigments were significantly influenced by the host of dye, since the presence of fluorine directly influences the acid-base properties of the layered double hydroxides. Finally, the pigments were successfully applied to prepare colored creams.
Effects of Nonsteroid Anti-inflammatory Drugs on Pregnant Women and the Fetus: A Systematic Review of Literature
Authors: Guerrero Natalia , Ayala Nicolas , Duran Natalia , Cubides Munevar Angela Mayerly , Botero Carvajal Alejandro
Published: December 2023

Currently, the use of medications during pregnancy in Latin America is common; studies with Latin American samples find that nearly 90% of pregnant women use some medication at least once during pregnancy. Furthermore, approximately 21% of the respondents self-medicated. Worldwide, the prevalence of this disease is 32%. The most common medications are nonsteroidal anti-inflammatory drugs and analgesics. Many of these drugs are available over the counter without a prescription. For this reason, a systematic review of the literature on the adverse effects on the woman and the fetus was performed.

Objective: To determine the adverse effects associated with the use of nonsteroidal anti-inflammatory drugs (NSAIDs) on pregnant women and fetuses during pregnancy.

Methods: Systematic literature review. The following search strategy was used for the databases: Science Direct, PubMed, Scopus and Web of Science, through September 3, 2022. The population of pregnant women without previous comorbidities was defined. The intervention of interest was the use of NSAIDs during pregnancy. The outcomes of interest were adverse effects for the mother or fetus (weight of the newborn, congenital malformations present in the fetus, systemic effects in the pregnant woman during her gestation period). The types of studies included clinical trials, cohort studies and case‒control studies.
Results: 1 study included 2,985 pregnant women without previous comorbidities. The use of aspirin more frequently during pregnancy stands out. The adverse effects on the fetus were preterm birth <37 weeks, low birth weight < 2500 g and increased admission to the neonatal intensive care unit. No adverse effects were found for the mother.

Conclusions: There are not enough data indicating that the use of NSAIDs during pregnancy is safe. Some studies show that the use of NSAIDs during pregnancy could be related to problems in the development and growth of the fetus and health effects for the mother during pregnancy, so it is advisable to use these drugs under medical prescription and for the shortest possible time. in the gestation stage.
Efek Residu Biochar Sekam Padi terhadap Pertumbuhan dan Hasil Kedelai
Authors: Suswana Suli , Maulana Dick Dick
Published: December 2023

Biochar is a carbon-rich solid material derived from the pyrolysis of agricultural residue biomass, which takes longer to decompose than the raw material biomass. Biochar has been observed to have agronomic benefits. Because of its persistence in the soil, biochar has the potential to extend its agronomic benefits. The purpose of this study was to obtain evidence that biochar has a longer effect so that its residual effect can increase the growth and yield of soybean. A series of pot experiments which included 4 consecutive plantings were carried out. The treatments consisting of: control; rice husk biochar (RHB) 20 ton.ha-1; RHB 40 ton.ha-1; RHB 50 ton.ha-1; RHB 60 ton.ha-1; RHB 10 ton.ha-1 + chicken manure (CM) 10 ton.ha-1; RBH 20 ton.ha-1 + CM 20 ton.ha-1; RHB 30 ton.ha-1 + CM 30 ton.ha-1. The treatments were applied to the first planting of the series experiment (September-December 2018). To determine the residual effect of the treatments, the second experiment was carried out in February-June 2019 with planting aerobic rice plants, third experiment in March-June 2020 with soybeans plant, and fourth experiment in July-October 2020 with soybean plants. The results showed that the effect of residual rice husk biochar did not significantly increase growth and soybean yields in the 3rd and 4th planting.
ANALISIS PUSAT LISTRIK MINIHIRO (PLTM) STUDI KASUS : SALIDO KECIL PESISIR SELATAN SUMATERA BARAT
Authors: Indriani Rani , Alfith Alfith
Published: December 2023

Dalam penelitian ini, kami menggunakan berbagai metode yang dapat diterapkan pada PLTM Salido untuk mengatasi masalah tegangan terminal generator yang sangat rendah. Ini terutama berlaku dalam situasi di mana beban puncak terjadi, yang mengharuskan pembangkit ini dikeluarkan dari sistem. Analisis aliran daya dilakukan menggunakan program ETAP Power Station untuk simulasi pencarian skema operasi yang dapat memperbaiki keadaan tersebut. Hasil analisis menunjukkan bahwa melalui injeksi daya reaktif dari generator ke jaringan PLN dan optimasi seting governor, PLTM Salido dapat menghasilkan lebih banyak energi dengan menyuplai daya ke jaringan PLN, bahkan dalam kondisi beban puncak. Ini memungkinkan PLTM Salido untuk meningkatkan jumlah energi yang dikirim dari pembangkit ke jaringan distribusi Pesisir Selatan. Setelah optimalisasi, nilainya meningkat menjadi 14,06 MWh per hari dari 10,64 MWh sebelumnya Dengan menambah satu unit pembangkit lagi, suplai energi PLTM salido dapat meningkat sampai 22 MWh per hari.
Efectos de la alta velocidad ferroviaria en la demanda turística: una aproximación para el caso de Galicia
Authors: Martínez Roget Fidel , Pazos Otón Miguel , Rodríguez González Xose Antón , Varela Cornado Mateo
Published: December 2023

Desde la inauguración de la primera línea de alta velocidad en España, Madrid-Sevilla en 1992, la expansión de la red de alta velocidad ha modificado los hábitos de movilidad de residentes y turistas. Galicia se ha beneficiado de la llegada de la alta velocidad ferroviaria de forma tardía, pero las sucesivas mejoras en los tiempos de viaje desde Madrid han comenzado a animar al trasvase desde otros medios de transporte, fundamentalmente desde 2012. El propósito de este estudio es investigar sobre la relación que existe entre las mejoras de tiempos de viaje y la llegada de la alta velocidad ferroviaria a Galicia y un supuesto crecimiento de la demanda turística. Para ello se consideran ocho de los más importantes municipios turísticos gallegos y se aplica un modelo econométrico sencillo, con la finalidad de analizar, de una forma comparativa, los posibles efectos de la llegada de la alta velocidad ferroviaria a Galicia sobre su demanda turística. A falta de la publicación de datos recientes relativos al período post-pandémico, los resultados permiten extraer unas primeras conclusiones que confirman el importante papel que el tren de alta velocidad puede desempeñar en el futuro en relación con el turismo en Galicia.
Prospecção Tecnológica de Patentes Depositadas no Brasil para a Manufatura na Cadeia do Leite e seus Derivados
Authors: Wonspeher Ana Carolina Vavassori de Freitas , Teixeira Clarissa Stefani
Published: December 2023

A cadeia produtiva do leite é um dos principais setores do agronegócio brasileiro, e o terceiro em importância na indústria de alimentos. Estudos demonstram que os produtores buscam cada vez mais a utilização de tecnologias inovadoras para auxiliar na eficiência e aumento da produtividade de seus rebanhos. De igual forma, o setor industrial do laticínio almeja um aumento da procura por seus consumidores, seja por oferecer produtos novos ou até mesmo, por oferecer os mesmos produtos com um menor custo. Todas estas atividades somente são possíveis através da implementação de inovações tanto nos processos produtivos, quanto nos produtos e serviços. Assim, este trabalho busca levantar dados sobre patentes ligadas à manufatura do leite, traçando um cenário no Brasil contemporâneo. Por meio do Orbit Questel, observou-se que há uma predominância de tecnologias relacionadas a maquinários e equipamentos. Mesmo o Brasil sendo atualmente o terceiro maior produtor de leite no globo, apenas 10% das patentes são depositadas no país, demonstrando que o mercado brasileiro ainda é um celeiro de oportunidades.
Análise de Resultados do Grupo de Pesquisa Crítica Textual da Fundação Biblioteca Nacional
Authors: Saraiva Maria Olívia de Quadros
Published: December 2023

Atualmente contando com mais de 200 anos de história, a Biblioteca Nacional do Brasil é considerada a mais antiga instituição cultural brasileira, sendo também considerada pela UNESCO uma das dez maiores bibliotecas nacionais do mundo, e a maior biblioteca da América Latina. Voltada eminentemente à pesquisa, a Fundação Biblioteca Nacional mantém programas de pesquisa, incluindo-se o Programa Nacional de Apoio a Pesquisa (PNAP), o Programa de Residência em Pesquisa na Biblioteca Nacional, e o Programa de Apoio à Pesquisa - Iniciação Científica (PAP-IC); além da política de disseminação de resultados de pesquisa, que inclui as Jornadas de Pesquisadores da FBN, os Seminários do Centro de Pesquisa e Editoração, além da publicação dos Dossiês Temáticos, da Revista Científica da FBN, e da realização de palestras e debates; entre outras. A Crítica Textual estuda a produção, transmissão e recepção do texto em seus diversos suportes escritos atentando para as diferentes versões e edições de uma obra, ocupando-se da comparação entre manuscritos, impressos e outros documentos que mostrem como um texto se modifica ao longo da história. Este artigo descreve alguns dos principais resultados do Grupo de Pesquisa Crítica Textual da Fundação Biblioteca Nacional, criado em 2014 e contando atualmente com 13 doutores, e que se destina a aliar a discussão teórica da Crítica Textual, e a pesquisa de especialistas da área, ao trabalho prático de estudo do acervo da Biblioteca Nacional.
Substrate stiffness mediates osteogenic and adipogenic differentiation of osteosarcoma through the PIEZO1 / ITGB1 -YAP -EZH2 signaling pathway
Authors: Li Lisha , Gao Qingyuan , Wang Meijing , Qiu Xiaolei , Li Meiying
Published: December 2023

Most osteosarcoma (OS) are poorly differentiated histopathologically, when normal osteogenic differentiation is disrupted, growth factors stimulate uncontrolled proliferation of precursor cells, leading to osteosarcoma development. Differentiation therapy aims to slow disease progression by restoring the osteogenic differentiation process of OS cells and is considered a new approach to treating OS. However, there are currently too few studies on the mechanism of osteogenic and adipogenic differentiation of osteosarcoma, which puts the development of differentiation therapeutic drugs into a bottleneck. Previous studies have shown that matrix stiffness can regulate osteogenic and adipogenic differentiation in mesenchymal stem cells. In this study, we simulated different stiffnesses in vitro to investigate the mechanism of matrix stiffness affecting osteogenic and adipogenic differentiation of osteosarcoma. We demonstrate that PIEZO1 plays a critical regulatory role in sensing matrix stiffness in osteogenic and adipogenic differentiation of osteosarcoma. When OS are cultured on the stiff matrix, integrin beta 1 (ITGB1) increases and cooperates with PIEZO1 to promote YAP entering the nucleus. The YAP enters the nucleus to inhibit EZH2, thereby inhibiting the expression of H3K27me3 and increasing RUNX2 expression, and cells differentiate toward osteogenesis. Our results are new advances in research on differentiation treatment of osteosarcoma, can help understand the pathological changes in osteosarcoma, and are expected to become new targets for future drug design.
Modes competition of vortex-induced vibration of long-span bridges with closely-spaced multi-modes
Authors: Cui Wei , Zhang Liutian , Zhao Lin
Published: December 2023

In recent years, vortex-induced vibration (VIV) phenomena have been observed in various long-span bridges worldwide. The existing literature has presented several nonlinear mathematical models for VIV, predominantly founded on a single dynamic mode. However, long-span bridges inherently possess multiple modes, and with the expansion of bridge spans, the frequencies associated with these structural modes become closely spaced. The incongruity arises from the linear assumption inherent in dynamic mode decomposition and the nonlinear dynamics characterizing VIV, thereby impeding the extrapolation of single-mode VIV to scenarios involving multiple coupled modes. This research introduces a multimode VIV modeling approach to emulate the coupling effects among modes, predicated on the polynomial expansion of nonlinear aeroelastic forces. The equation governing the evolution of amplitudes in the multimode VIV is derived through averaging methods. In particular, the multi-mode VIV model can be reduced to a conventional single-mode VIV model, facilitating the identification of aeroelastic parameters during VIV through wind tunnel testing. The investigation reveals that coupled multimode VIV consistently converges towards a stable equilibrium point corresponding to a single mode after modes undergo competition. Finally, this article concludes with a discussion on the influence of structural damping on coupled multimode VIV.
Association between high birth weight and dental caries at 4-5 years of age: a birth-cohort study
Authors: Zhang Hao , Wang Huning , Zeng Xiaoli , Yu Jin , Jiang Yiwei , Huang Lisu , Zeng Xinxin , Chen Qian , Da Dongxin , Zhang Ying
Published: December 2023

Objective: Early childhood caries has become a globally crucial oral health problem over the decades. Most studies have discussed the association between low birth weight and early childhood caries; however, studies focusing on high birth weight have been relatively limited. This study aimed to assess the impact of high birth weight on the incidence and severity of dental caries in 4–5-year-old children.
Subjects and Methods: Study subjects included 491 children from a birth cohort study at 4–5 years of age. Data on dental caries, prenatal and perinatal factors, and socio-demographic determinants were recorded. Logistic regression models adjusted for potential confounders were performed to analyze the data. Two-sided P-value < 0.05 was considered statistically significant.
Results: Of the 491 children, the prevalence of dental caries was 48.7%. High birth weight (≥ 4,000 g) was significantly associated with increased incidence of dental caries (OR, 2.000; CI 95% 1.062–3.765), and the relatively enhanced risk OR was further increased in subjects experiencing caries (dmft ≥ 3) (OR, 2.437; CI 95% 1.306–4.549) compared with the normal birth weight (2,500–3,999 g).
Conclusions: High birth weight is a risk factor for early childhood caries. Particular attention should be paid to children with birth weight more than or equal to 4,000 grams.
The Leadership Puzzle: Unveiling the Impact of Leader Behaviors on Basketball Players Performance through Breakthrough EMG and EEG Measurements
Authors: AKSOY Yasin , SERBEST Kasım , DERESHGI Hamid ASADI , AKSOY Yağmur ÖZYER , SAVAŞ Derya Durusu Emek , GÖSE Ersin
Published: December 2023

The research design investigated the leader-player relationship that is universally relevant in all organizations, focusing on the behavior between a university basketball team and their coach, using pre-established models. The study examined the mechanical changes in players' elbow joint movements and biceps brachii muscles in response to different behavior models exhibited by the coach, using electromyography (EMG) and precise camera analysis. Electroencephalography (EEG) recordings were also utilized to detect brain responses to various stimuli. Additionally, players' responses to the Leader Behavior Scale questionnaire were analyzed, and their free-throw performance at different times was compared with the results obtained from the aforementioned analysis methods. Thus, the research aimed to investigate whether different leader behavior models had an impact on team members' performance or perceptions. Interdisciplinary analysis using these techniques supported the conclusion that when the leader exhibits momentary different behavior, it does not affect the players' instant performance. EMG, precise camera analyses, EEG recordings analysis, free-throw percentages, and survey responses revealed that the momentary changes in the leader's behavior do not have a significant impact on basketball players' performance. The most significant constraint of the research is that it was conducted on university basketball team players and leaders. This study could be expanded with new research that has a more extensive experimental design, where the performance of leaders and players can be observed using various measurement methods, both used and unused in this study. Lay Summary: The main objective of our study is to analyze the relationships between athletes and coaches from a leadership perspective using various in-depth measurement methods. This study was conducted on athletes and their leaders, the coaches, in order to determine the extent to which the performance and perceptions of the players change when the leader exhibits different behavioral patterns.
Cervical precancerous lesion and cancer detection on Pap smear image using machine learning algorithm
Authors: Getenet Agmas , Kassaw Amare
Published: December 2023

Cervical cancer is the second most common cancer in women globally, it is the leading cause of female death, next to breast cancer. Sexually transmitted virus, known as Human papillomavirus, causes this cancer. This preventable diseases cause female death because of lack of cervical screening in health institutes. Cervical screening used to detect the precancerous lesion before developing cancer cells. Pap smear is one of cervical cancer screening techniques that uses microscope to visualize the cervix lesion or cervix cancer. However, visual inspection suffers from false positive or false negative results due to human errors. This research aims to change the visual inspection to Computer-Assisted Screening using machine-learning algorithm. Machine learning algorithm currently used for the detection and diagnosis of cervical cancer. The ultimate objective of this research is to detect precancerous lesion before developing cancer cells using multi-class classification, on local Pap smear image data. In this research, 1224 Pap smear image collected from local health institute and annotated by pathologist. Preprocessing mainly focused on image denoising using bilateral filter to remove Poisson noise. Convolutional Neural Network (CNN) and Pre-trained VGG19 algorithms were developed using train, validation and test data split. From Classical machine learning, Support Vector Machine (SVM) and Random Forest (RF) algorithms were developed. The accuracy of CNN, VGG-19, SVM and RF are 99%, 100%, 96% and 100% registered, respectively. Pre-trained VGG19 and Random Forest models were outperformed. Hence, these developed algorithms can improve the diagnosis and detection of cervical lesion and cancer cells from Pap smear images, which are safe, simple, available and routine screening methods in cervical diagnosis to improve the quality of life of patients.
Advancing Bearing Fault Diagnosis under Variable Working Conditions: A CEEMDAN-SBS Approach with Vibro-Electric Signal Integration
Authors: LOURARI Abdel wahhab , SOUALHI Abdenour , BENKEDJOUH Tarak
Published: December 2023

Bearings represent crucial components within rotating machinery, and unexpected failures can lead to significant damage and unplanned breakdowns. This paper introduces a novel approach to diagnose bearing faults under variable working conditions, leveraging the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and Sequential Backward Selection (SBS). CEEMDAN automatically selects intrinsic mode functions (IMFs) from vibration and current signals to establish a comprehensive set of health indicators. Subsequently, the SBS algorithm identifies the most pertinent indicators for different bearing failure modes. The accuracy of the proposed method is evaluated on both vibration and electrical signals using data from a dedicated test bench at the Signal and Industrial Process Analysis Laboratory (LASPI). Results demonstrate the effectiveness of the proposed method in accurately identifying and classifying bearing faults across various working conditions, utilizing both types of signals. This approach holds promise for real-world industrial applications, offering a reliable method for condition monitoring and Diagnostics in bearing systems.
Perception System Architecture for Self-Driving Vehicles: A Cyber- Physical Systems Framework
Authors: Babaei Parinaz , Riahinia Nosrat , Ebadati Omid Mahdi , Azimi Ali
Published: December 2023

This research is seeking for design the autonomous vehicle's perception system from the perspective of cyber-physical system. The perception system is considered a cyber and physical component. This research takes a systemic approach. Unified Modeling Language (UML) has been applied to design perception systems. The perceptual system was created using the 3 common UML diagrams. The findings show that UML can be used as a powerful tool for modeling every type of complex system. The sensors utilized in the tasks of the perception layer are shown in use case diagrams. To recognize surrounding things and avoid obstacles, a variety of technologies including cameras, LiDAR, RADAR, ultrasonic sensors, GPS, and GNSS are utilized in 2/3-d object detection, speed and distance detection, localization, and mapping. The class diagram displays the perception system's structural elements. The perception system's task execution was shown in the sequence diagram. The engineers can improve the functionality and security of autonomous vehicles by using UML to create a precise and organized description of the perception system. The model in which designed in this paper can improve autonomous vehicles' perception system performance, driving safety, and self-confidence of vehicles. this model is an innovative model based on the cyber-physical systems approach and with the UML modeling method. other models in the literature are pipeline modular and/or see the perception layer tasks in isolation.
Alterations in vaginal and urinary microbiota among women of different ages based on a cross-sectional study from Health Examination Center
Authors: Li Ya , Jin Xi , Xiang Liyuan , Wen Jun , Li Puhan , Wei Jingwen , Huang Yan , Wang Kunjie
Published: December 2023

Background: Role of vaginal and urinary microbiomes have gaining increasing concern in many health aspects. The dynamic change of these bacterial communities of healthy females throughout their life remained poorly understood, and how vaginal and urinary microbiota interact with each other requires further exploration. Therefore, we conducted a cross-sectional study to examine vaginal and urinary microbiota of healthy female of different age based on 16S rRNA gene sequencing.
Results: A total of 348 vaginal swab samples and 209 urine samples were collected and 90 pairs of samples were matched. The average age of all participants was 44.76±0.55 years old. All the participants were further divided into 5 age groups: <=30 years old (G1), 31-40 years old (G2), 41-50 years old (G3), 51-60 years old (G4), >60 years old (G5). 16s rRNA analysis of vaginal and urinary microbiota identified 3458 OTUs and 1282 OTUs respectively. Lactobacillus was the most abundant genus in both vaginal and urinary microbiota of female under 40 years old, but the abundance decreased with age. The diversity of both vaginal and urinary microbiota increased with age. Moderate to high Pearson correlations were found in some genera presenting in both sites, including Lactobacillus (R2=0.7735, P≤0.001), Gardnerella (R2=0.6698, P≤0.001), Actinomyces (R2=0.6118, P≤0.001), while vaginal Anaerococcus was also positively associated with urine Peptoniphilus (R2=0.6352, P≤0.001). Urine Lactobacillus was negatively associated with Streptococcus (R2=-0.62275, P≤0.001), Peptoniphilus (R2=-0.6097, P≤0.001), and Finegoldia (R2=-0.60703, P≤0.001). Age and the status of menopause appeared to be the most dominant clinical factors impact both vaginal and urinary microbiota.
Conclusions: Significant variations of vaginal and urinary microbiota in different age groups were observed. Lactobacillus was the most dominant genus in both in female under 40 and correlated highly between different samples. The diversity increased, with the decrease of Lactobacillus dominance in both vaginal and urinary microbiota after 40 and the change was especially significant in the perimenopausal period. This change may be partially related to the susceptibility of some urogenital diseases of the postmenstrual women, but more studies on microbiota of patients are required to further explore it.
The Efficacy of Online Extensive Reading Among University Students: Focus on the Relationship Between Affective Variables and English Reading Comprehension
Authors: Anggia Helta , Habók Anita
Published: December 2023

Online extensive reading has been shown to improve English reading comprehension and related motivational factors. However, few studies have examined the structural relationship between affective variables and reading comprehension in this platform. Thus, this study designed an online extensive reading program to examine this relationship and the affective behavior of a sample of university students. Clustered random sampling was used to select two experimental groups (N = 120, N = 130) and a control group (N = 100), who were requested to take the Test of English as a Foreign Language reading comprehension pre-and post-tests and complete online surveys about self-beliefs, reading motivation, and English reading behavior. Based on the findings, the experimental groups significantly outperformed the control group in reading comprehension. Meanwhile, reading self-efficacy predicted intrinsic and extrinsic motivation, but self-concept only predicted extrinsic drive. Although there was no correlation between extrinsic or intrinsic motivation and English reading comprehension, only the latter mediated self-efficacy with English reading behavior. Surprisingly, reading behavior did not mediate intrinsic motivation and reading comprehension. The findings imply that internal motivation and reading behavior cannot guarantee students’ reading comprehension achievement.