bluuebunny/crossref_metadata_2025_split huggingface dataset:
Thermal behavior of polypropylene composites with segregated graphene nanoplatelet network
Authors: Jang Woo Seok , Kim Ki Hoon , Kang Jinhyeok , Nam Changwoo , Kim Seong Yun 
Published: June 2024

AbstractThree‐dimensional architecture of segregated network can significantly influence thermal behaviors of polymer composites, such as the melting temperature (Tm) and degradation temperature. However, there have been few systematic studies on the thermal behaviors of polypropylene (PP) composites with a segregated network that the fillers were selectively located in the polymeric particle interfaces. In this study, we found that introduction of the segregated graphene nanoplatelet (GNP) network induced the maximum Tm of 177.6°C, extending the operating temperature by 11.5°C compared to the Tm of composites with randomly dispersed GNPs. In contrast, the thermal degradation temperature of polymer composites varied insignificantly regardless of introduction of the segregated network because the thermal degradation of the polymer matrix occurred after the PP chains melted and the segregated GNP network collapsed at temperatures above the Tm. Therefore, the incorporation of a segregated network can be an effective option for enhancing the Tm and extending the operating temperature of the polymer composites.Highlights
Segregated network induced the remarkable increase in melting temperature.
Meanwhile, the segregated network had little effect on decomposition temperature.
Segregated composite was efficient strategy for expanding operating temperature.
Rapid and comprehensive quality evaluation of Huang‐qin from different origins by FT‐IR and NIR spectroscopy combined with chemometrics
Authors: Lv Kaidi , Yin Chunling , Li Fang , Chen Wenbo , Zhao Liuchuang , Liu Zhimin , Hu Leqian 
Published: June 2024

AbstractIntroductionQuality evaluation of Huang‐qin is significant to ensure its clinical efficacy.ObjectiveThis study aims to establish an accurate, rapid and comprehensive Huang‐qin quality evaluation method to overcome the time‐consuming and laborious shortcomings of traditional herbal medicine quality assessment methods.MethodsThe contents of baicalin, baicalein and scutellarin in Huang‐qin from five different origins were analyzed by FT‐IR and NIR spectra combined with multivariate data technology. The quality of Huang‐qin from different origins was evaluated by TOPSIS and consistency analysis based on the content of three active ingredients. The correlation between ecological factors and the accumulation of active ingredients was explored.ResultsSatisfactory prediction results of PLS models were obtained. Relatively, the model based on FT‐IR combined with the PLS regression method has higher R2 and smaller RMSE than the NIR combined with the PLS method. TOPSIS and consistency analysis results showed that the quality of Huang‐qin from different geographical origins was significantly different. The results showed that the quality of Huang‐qin produced in Shanxi Province was the best among the five origins studied. The results also found that the quality of Huang‐qin in different growing areas of the same origin was not completely consistent. The correlation study showed that altitude, sunshine duration and rainfall were the main factors that caused the quality difference of medicinal materials in different geographical origins.ConclusionThis study provides a reference for the rapid quantitative analysis of the active components of herbal medicine and the quality evaluation of them.
Regulatory roles of insulin growth factor binding protein family in neuroblastoma cell proliferation and differentiation: Potential prognostic biomarkers and therapeutic targets for neuroblastoma
Authors: Huang Kai , Yang LinYu , Ma Yue , Wang Shan 
Published: June 2024

AbstractNeuroblastoma (NB), as a representative of tumors of embryonic origin in children, has specific clinical features. On the one hand, a very small number of NBs may appear to regress on their own. On the other hand, highly malignant NBs can invade the surrounding blood vessels and organs and metastasize to distant bone, bone marrow, and lymph nodes in the early stages of the disease. Based on differential affinities to insulin growth factors (IGFs), insulin growth factor binding proteins (IGFBPs) are classified into two groups: IGF binding proteins (IGFBP1‐6) with high‐affinity and IGF low‐affinity binding proteins, such as IGFBP‐related proteins (IGFBP rP1‐10). IGFBP are crucial regulators of the bioavailability and function of IGF in metabolic signaling and as modulators of IGF signaling, and their role in NB is gaining increasing attention. In this study, we investigate the involvement of IGFBP family members in the growth and differentiation of NB cells, as well as the potential of IGFBPs as prognostic biomarkers and therapeutic targets for human NB.
Resting CD4 regulatory T cell and neuroblastoma: A Mendelian randomization study
Authors: Wang RuiZong , Wang Shan 
Published: June 2024

AbstractNeuroblastoma (NB) is a common extracranial solid tumor in children, and currently our understanding of the molecular mechanisms underlying tumor progression is not very thorough. In clinical practice, although the prognosis and survival rates of NB patients in the low‐risk and medium‐risk groups are still acceptable, the prognosis and survival rates of NB patients in the high‐risk group are extremely poor. Therefore, improving awareness of NB tumors is crucial for improving the treatment status of NB patients in clinical practice. So we collected common tumor exposure factors and performed multiple Mendelian randomization (MR) analysis on NB, and ultimately determined that the increase in Resting CD4 regulatory T cell was positively correlated with the occurrence and development of NB. In addition, we also used the network pharmacology algorithm proximity to screen the NB chemotherapy drug papain and reasonably speculated that there is an interaction between papain and CD4 regulatory T cell in the chemotherapy of NB patients.
Leishmaniinae: Evolutionary inferences based on protein expression profiles (PhyloQuant) congruent with phylogenetic relationships among Leishmania, Endotrypanum, Porcisia, Zelonia, Crithidia, and Leptomonas
Authors: Mule Simon Ngao , Alemán Evaristo Villalba , Rosa‐Fernandes Livia , Saad Joyce S. , de Oliveira Gilberto Santos , Martins Deivid , Angeli Claudia Blanes , Brandt‐Almeida Deborah , Cortez Mauro , Larsen Martin Røssel , Shaw Jeffrey J. , Teixeira Marta M. G. , Palmisano Giuseppe 
Published: June 2024

AbstractEvolutionary relationships among parasites of the subfamily Leishmaniinae, which comprises pathogen agents of leishmaniasis, were inferred based on differential protein expression profiles from mass spectrometry‐based quantitative data using the PhyloQuant method. Evolutionary distances following identification and quantification of protein and peptide abundances using Proteome Discoverer and MaxQuant software were estimated for 11 species from six Leishmaniinae genera. Results clustered all dixenous species of the genus Leishmania, subgenera L. (Leishmania), L. (Viannia), and L. (Mundinia), sister to the dixenous species of genera Endotrypanum and Porcisia. Placed basal to the assemblage formed by all these parasites were the species of genera Zelonia, Crithidia, and Leptomonas, so far described as monoxenous of insects although eventually reported from humans. Inferences based on protein expression profiles were congruent with currently established phylogeny using DNA sequences. Our results reinforce PhyloQuant as a valuable approach to infer evolutionary relationships within Leishmaniinae, which is comprised of very tightly related trypanosomatids that are just beginning to be phylogenetically unraveled. In addition to evolutionary history, mapping of species‐specific protein expression is paramount to understand differences in infection processes, tissue tropisms, potential to jump from insects to vertebrates including humans, and targets for species‐specific diagnostic and drug development.
Improved Dielectric, Magnetic, and Multiferroic Properties of (Bi0.5Na0.5)0.7La0.3(Ti0.7Fe0.3)O3Ceramics Synthesis by the Solid‐State Combustion Technique
Authors: Kornphom Chittakorn , Somsri Widchaya , Prasertpalichat Sasipohn , Thatawong Bhoowadol , Kruea‐In Chatchai , Udeye Thanya , Rittidech Aurawan , Menkun Chanagon , Vittayakorn Naratip , Pinitsoontorn Supree , Jantaratana Pongsakorn , Chanlek Narong , Bongkarn Theerachai 
Published: June 2024

Lead‐free (Bi0.5Na0.5)0.7La0.3(Ti0.7Fe0.3)O3ceramics (abbreviated as BNLTF) are synthesized by the solid‐state combustion technique using glycine as fuel. The effect of the firing temperature (calcined between 700 and 800 °C for 2 h and sintered between at 800 and 900 °C for 2 h) on the phase structure, microstructure, electrical, and magnetic properties is investigated. Pure BNLTF powders are obtained with a calcination temperature of 750 °C for 2 h and the crystal size increases from 47 to 62 nm when the calcination temperature increases from 700 to 800 °C. All sintered BNLTF ceramics show a pure perovskite structure with a rhombohedral phase. The average grain size increases with increasing sintering temperatures. A well‐packed microstructure with the highest density (5.98 g cm−3), good dielectric properties at room temperature (εr ≈ 589 and tanδ ≈ 0.572), soft ferroelectric behavior, and excellent magnetic properties (Ms ≈ 0.091 emu g−1,Mr ≈ 0.0026 emu g−1) is obtained from the ceramic sintered at 875 °C for 2 h. The multiferroic BNLTF ceramic sintered at 875 °C has a maximum magnetoelectric coupling coefficient (αE ≈ 2.08 mV cm−1 Oe−1) when the magnetic field is near 4500 Oe.
Adaptive EWMA control chart by using support vector regression
Authors: Kazmi Muhammad Waqas , Noor‐ul‐Amin Muhammad 
Published: June 2024

AbstractTraditional control charts depend on the process parameters that are used to monitor the shifts in the process. The adaptive control charts are used to adapt a process parameter during the online monitoring. This research introduces a support vector regression (SVR) based adaptive exponentially weighted moving average control chat to enhance the monitoring of the mean in industrial processes. The study systematically investigates the comparative efficiency of linear, radial basis function (RBF), and polynomial functions within the SVR framework. The proposed SVR‐based AEWMA control chart leverages the strengths of the RBF kernel, providing a robust mechanism for detecting shifts in the process mean by adapting the smoothing constant according to the size of the shift. To validate the efficacy of the proposed methodology, a practical application is presented by using real‐life data. The application showcases the adaptability and reliability of the SVR‐based adaptive EWMA control chart in effectively monitoring location shifts.
Azvudine versus Paxlovid in COVID‐19: A systematic review and meta‐analysis
Authors: Amani Behnam , Amani Bahman 
Published: June 2024

AbstractThis systematic review and meta‐analysis aimed to compare the effectiveness and safety of azvudine versus nirmatrelvir/ritonavir (Paxlovid) in treating coronavirus disease 2019 (COVID‐19). The researchers conducted searches on PubMed, Cochrane Library, Web of Science, medRxiv, and Google Scholar until January 2024. The Cochrane risk of bias tool was utilised to evaluate the quality of the included studies, and data analysis was performed using Comprehensive Meta‐Analysis software. Thirteen studies, including 4949 patients, were analysed. The meta‐analysis results showed no significant difference between the azvudine and Paxlovid groups in terms of mortality rate (odds rate [OR] = 0.84, 95% confidence interval [CI]: 0.59–1.21), negative polymerase chain reaction (PCR) conversion time (standard mean difference [SMD] = 1.52, 95% CI: −1.07–4.11), and hospital stay (SMD = −0.39, 95% CI: −1.12–0.33). However, a significant difference was observed between the two groups in terms of intensive care unit admission (OR = 0.42, 95% CI: 0.23–0.75) and the need for mechanical ventilation (OR = 0.61, 95% CI: 0.44–0.86) in favour of azvudine. The incidence of adverse events in the azvudine group was significantly lower (OR = 0.66, 95% CI: 0.43–0.99). The certainty of evidence was rated as low and moderate. Azvudine and Paxlovid demonstrated similar effectiveness in reducing mortality rates, negative PCR conversion time and hospital stay. However, azvudine showed better effectiveness in improving other outcomes. Regarding the level of certainty of evidence, further research is needed to validate or challenge these results.
Pose‐graph underwater simultaneous localization and mapping for autonomous monitoring and 3D reconstruction by means of optical and acoustic sensors
Authors: Bucci Alessandro , Ridolfi Alessandro , Allotta Benedetto 
Published: June 2024

AbstractModern mobile robots require precise and robust localization and navigation systems to achieve mission tasks correctly. In particular, in the underwater environment, where Global Navigation Satellite Systems cannot be exploited, the development of localization and navigation strategies becomes more challenging. Maximum A Posteriori (MAP) strategies have been analyzed and tested to increase navigation accuracy and take into account the entire history of the system state. In particular, a sensor fusion algorithm relying on a MAP technique for Simultaneous Localization and Mapping (SLAM) has been developed to fuse information coming from a monocular camera and a Doppler Velocity Log (DVL) and to consider the landmark points in the navigation framework. The proposed approach can guarantee to simultaneously locate the vehicle and map the surrounding environment with the information extracted from the images acquired by a bottom‐looking optical camera. Optical sensors can provide constraints between the vehicle poses and the landmarks belonging to the observed scene. The DVL measurements have been employed to solve the unknown scale factor and to guarantee the correct vehicle localization even in the absence of visual features. Furthermore, to evaluate the mapping capabilities of the SLAM algorithm, the obtained point cloud is elaborated with a Poisson reconstruction method to obtain a smooth seabed surface. After validating the proposed solution through realistic simulations, an experimental campaign at sea was conducted in Stromboli Island (Messina), Italy, where both the navigation and the mapping performance have been evaluated.
A selective harvesting robot for cherry tomatoes: Design, development, field evaluation analysis
Authors: Rong Jiacheng , Hu Lin , Zhou Hui , Dai Guanglin , Yuan Ting , Wang Pengbo 
Published: June 2024

AbstractWith the aging population and increasing labor costs, traditional manual harvesting methods have become less economically efficient. Consequently, research into fully automated harvesting using selective harvesting robots for cherry tomatoes has become a hot topic. However, most of the current research is focused on individual harvesting of large tomatoes, and there is less research on the development of complete systems for harvesting cherry tomatoes in clusters. The purpose of this study is to develop a harvesting robot system capable of picking tomato clusters by cutting their fruit‐bearing pedicels and to evaluate the robot prototype in real greenhouse environments. First, to enhance the grasping stability, a novel end‐effector was designed. This end‐effector utilizes a cam mechanism to achieve asynchronous actions of cutting and grasping with only one power source. Subsequently, a visual perception system was developed to locate the cutting points of the pedicels. This system is divided into two parts: rough positioning of the fruits in the far‐range view and accurate positioning of the cutting points of the pedicels in the close‐range view. Furthermore, it possesses the capability to adaptively infer the approaching pose of the end‐effector based on point cloud features extracted from fruit‐bearing pedicels and stems. Finally, a prototype of the tomato‐harvesting robot was assembled for field trials. The test results demonstrate that in tomato clusters with unobstructed pedicels, the localization success rates for the cutting points were 88.5% and 83.7% in the two greenhouses, respectively, while the harvesting success rates reached 57.7% and 55.4%, respectively. The average cycle time to harvest a tomato cluster was 24 s. The experimental results prove the potential for commercial application of the developed tomato‐harvesting robot and through the analysis of failure cases, discuss directions for future work.
Connecting forest soil properties with ecosystem services: Toward a better use of digital soil maps—A review
Authors: Paré David , Bognounou Fidèle , Emilson Erik J. S. , Laganière Jérôme , Leach Jason , Mansuy Nicolas , Martineau Christine , Norris Charlotte , Venier Lisa , Webster Kara 
Published: June 2024

AbstractThe soil supports many ecosystem services (ES) essential to human well‐being. Rapid developments in digital soil mapping (DSM) allow the mapping of soil types and soil properties with improved resolution and accuracy. However, the potential of DSM to improve the assessment and mapping of ES is not fully exploited. To better understand this potential, we synthesized the peer‐reviewed literature. We examined what empirical studies reveal about the role of soil properties in the assessment of four major ES provided by the forest: (I) timber production, (II) soil carbon storage, (III) regulation of water flow and provision of clean water, and (IV) the soil as a habitat for organisms. Results revealed that soil properties are strongly related to the provision of ES. Therefore, using DSM could greatly improve the assessment of the ES provided by forests. Several variables were related to specific ES regardless of region or ecosystem types, but others were found to be situation‐specific (climate and soil type) and need to be considered at the proper scale or within a proper land classification framework. DSM products have the potential to greatly improve the assessment of ES by turning qualitative relationships between soil and ES to quantitative ones. This could also lead to the discovery of new soil–ES relationships. For this potential to be realized, progress should be made in mapping the most crucial soil parameters with greater precision and in promoting the use of soil parameters in ES assessment.
Scrutinizing the nexus: Energy, economic growth, and environmental quality: An approach toward achieving the Sustainable Development Goals (7, 13, and 8)
Authors: Fahad Shah , Khan Aftab , Waqas Muhammad , Luqman Muhammad 
Published: June 2024

AbstractThis study investigates the intricate relationship between energy consumption, economic growth, and environmental quality in Pakistan from 1990 to 2022, highlighting the critical role of natural resources rent (NRR) and renewable energy consumption (REC) in shaping carbon dioxide emissions. The study aims to understand how these variables interact and influence each other, particularly focusing on the impact of NRR and REC on CO2 emissions within the context of Pakistan's economic growth and energy consumption patterns. Given the country's rapid economic growth and increasing energy demands, there is an imperative need to investigate how these factors influence environmental quality, particularly CO2 emissions employing the autoregressive distributed lag approach with structural breaks, we analyze the long‐term interactions and causality among NRR, REC, energy use (EU), gross domestic product (GDP), and CO2 emissions. Our findings demonstrate that while NRR and REC negatively correlate with CO2 emissions, a positive association exists between EU, GDP growth, and emissions. These results underscore the potential of strategic environmental policies, aligned with Sustainable Development Goals 7, 13, and 8, to foster sustainable development pathways in Pakistan. By comparing this study's approach with existing methodologies, we highlight our study's unique contribution to the literature, offering policymakers a robust foundation to formulate effective strategies for balancing economic growth with environmental sustainability.
Solving flood problems with deep learning technology: Research status, strategies, and future directions
Authors: Li Hongyang , Zhu Mingxin , Li Fangxin , Skitmore Martin 
Published: June 2024

AbstractAs a frequent and devastating natural disaster worldwide, floods are influenced by complex factors. Building flood models for simulating, monitoring, and forecasting floods is crucial to reduce the risk of disasters and minimize damage to people and property. With advancements in computing power and the impressive capabilities of deep learning in such areas as classification and prediction, there has been growing interest in using this technology in flood research. There is also a growing body of research into building flood data‐driven models with deep learning. Based on this, this study adopts a mixed‐method approach of bibliometric and qualitative analyses to provide an overview of the research. The research status is revealed in a bibliometric visualization, where the research objects are defined from the flood perspective, and the research strategies are explained from the deep learning perspective to provide a comprehensive and in‐depth understanding of the flood problem and how to apply deep learning to solve it. In addition, the study reflects on the future direction of improvement and innovation needed to promote the further development and exploration of deep learning in flood research.
Business digitalisation as a driver of environmental and economic sustainability in micro, small, and medium‐sized enterprises
Authors: Miranda Luis Francisco , Saunila Minna , Cruz‐Cázares Claudio , Ukko Juhani 
Published: June 2024

AbstractIn this study, we examine the direct relationship between business digitalisation and improvements in economic sustainability, as well as the potential mediating role of environmental sustainability. We also examine the potential role of company size as a moderating variable in these relationships. We gathered data from micro, small and medium‐sized enterprises (MSMEs) in Finland. Contrary to initial expectations, our findings reveal that there is no direct and significant relationship between business digitalisation and the economic sustainability of enterprises; this relationship is only possible through the mediating role of environmental sustainability. We also found that, although high levels of environmental sustainability may result in improved economic outcomes, the strength of this relationship is much weaker for microenterprises than for their larger counterparts. Altogether, these results underscore the complex interplay between digitalisation and sustainability outcomes within the context of small businesses.