bluuebunny/crossref_metadata_2025_split huggingface dataset:
Recent Advancements in Fused Deposition Modeling
Authors: Raza Umer , Ahmed Arslan , Waheed Saad , Abid Muhammad , Tahir Mohammad , Zahid Ali , Ahmed Arham , Bilal Muhammed , Hussain Tussadq , Mustafa Ghulam 
Published: January 2025

ABSTRACTAdditive manufacturing (AM) is a continuously growing field composed of numerous part‐building approaches that involve the creation of products in a layer‐by‐layer fashion. Fused deposition modeling (FDM) is a three‐dimensional printing or AM technique that is being adopted on an industrial scale and is being utilized to make parts for commercial use mainly in the medical sector these days. It has become the need of the hour to study the printing parameters of FDM to understand the print behavior and optimize process parameters to make parts with better mechanical properties. This review paper provides an understanding of development in the optimization of process parameters for various print materials like Nylon, polylactic acid (PLA), acrylonitrile butadiene styrene (ABS), and polyether ether ketone (PEEK) by utilizing the different designs of optimization techniques like Taguchi and response surface methodology. Regarding relevant mechanical properties, the influence of process parameters like layer thickness, raster angle, build orientations, raster width, and infill density are underlined carefully. The paper also concludes the optimized parameters to obtain the best mechanical properties such as tensile and flexural strength of Nylon, PLA, PEEK, and ABS. It also provides literature with up‐to‐date references and highlights future recommendations to optimize the mechanical properties of FDM fabricated components.
Enhancing PLA/ABS Blends Compatibility: A Comparative Study With SAN‐Epoxy and SAN‐MA
Authors: dos Santos Filho Edson Antonio , Luna Carlos Bruno Barreto , da Silva Barbosa Ferreira Eduardo , Pinto Gabriel Matheus , Andrade Ricardo Jorge Espanhol , Fechine Guilhermino José Macêdo , Araújo Edcleide Maria 
Published: January 2025

ABSTRACTBlends of poly (lactic acid) (PLA) with acrylonitrile‐butadiene‐styrene (ABS) were prepared using styrene–acrylonitrile copolymers functionalized with maleic anhydride (SAN‐MA) and epoxy (SAN‐Epoxy) as compatibilizers. The blends were processed in an internal mixer and injection molded. Analyses included torque rheometry, dynamic oscillatory shear rheology, impact resistance, tensile strength, Shore D hardness, heat deflection temperature (HDT), differential scanning calorimetry (DSC), and scanning electron microscopy (SEM). Rheological tests showed increased torque and viscosity in PLA/ABS blends, particularly with SAN‐Epoxy, indicating better phase compatibility. The incorporation of 10 phr (parts per hundred resin) of SAN‐Epoxy into the PLA/ABS blend (70/30% by weight) increased impact resistance by approximately 200% compared to pure PLA. Additionally, it promoted better performance in tensile modulus and tensile strength compared to the system compatibilized with SAN‐MA. SEM analysis revealed that ABS particles in the PLA matrix had more stable size and distribution with SAN‐Epoxy, explaining the favorable mechanical results. The Shore D hardness and HDT of the PLA/ABS/SAN‐Epoxy blends remained unchanged compared to PLA, suggesting a balance of properties. Overall, SAN‐Epoxy proved to be the most effective compatibilizer, indicating greater interaction with the phases, thereby contributing to improved mechanical and thermal performance.
Genotypic diversity and biological characterization of Alphabaculovirus mabrassicae isolates from a wide host range
Authors: Yang Xiaoqin , Lei Chengfeng , Peng Xiaowei , Min Yuanqin , Hu Jia , Sun Xiulian 
Published: January 2025

AbstractBACKGROUNDBaculoviruses are ideal biological insecticides, providing long‐lasting pest control and environmental benefits. Alphabaculovirus mabrassicae stains, with their broad host range, have been effective in agricultural pest management. Various A. mabrassicae isolates (MbMNPV‐CHb1/CTa/K1/QD, MyseMNPV‐Hb, HearMNPV and MacoNPV‐B) have been identified in different hosts. Identifying more effective A. mabrassicae strains with detailed genetic information is crucial for commercial use.RESULTSLaboratory bioassays showed that the median lethal concentration (LC50) of MyseMNPV‐Hb against Mythimna separata was significantly lower than those against Helicoverpa armigera and Spodoptera exigua, but higher than the LC50 of MbMNPV‐CHb1, MbMNPV‐QD and HearMNPV against H. armigera or S. exigua. Comparative genomic analysis revealed significant differences in genomic composition and single‐nucleotide polymorphisms between MyseMNPV‐Hb and the other isolates. A piggyBac‐like element, likely to have been from Alcis repandata (Lepidoptera: Geometridae), was identified in the genomes of these isolates. Eight genes in the A. mabrassicae genomes were found to be under positive selection.CONCLUSIONAlphabaculovirus mabrassicae isolates exhibit different infectivity in various pests, indicating the need for selecting appropriate isolates specific target pests. This study elucidates the genetic factors contributing to the differential infectivity of A. mabrassicae isolates and extends knowledge on its population characteristics. © 2025 Society of Chemical Industry.
Covalent Organic Framework Nanofilm‐Assisted Laser Desorption Ionization Mass Spectrometry for Rapid Screening of Parabens in Personal Care Products
Authors: Zheng Wenjun , Yan Jingjing , Jin Yingxue , Lin Zian , Cai Zongwei 
Published: January 2025

ABSTRACTRationalPeople are widely exposed to parabens in their daily life, but parabens are endocrine disrupting chemicals that pose a threat to human health. Therefore, establishing a rapid screening method to enhance monitoring of parabens is necessary. Herein, a covalent organic framework (COF) nanofilm‐assisted laser desorption ionization mass spectrometry (LDI‐MS) method was established to screen parabens in personal care products (PCPs).MethodsTAPB‐TFPB‐COF nanofilm was synthesized on indium tin oxide (ITO) glass and used as LDI‐MS substrates. To observe the practicability of TAPB‐TFPB‐COF nanofilm‐assisted LDI‐MS, the results of this method for analyzing small molecules such as parabens, estrogens, and bisphenols were compared with those of the conventional organic matrix 9‐aminoacridine (9‐AA), and the reproducibility and detection limit were further verified. Finally, the method was applied to screen parabens in PCPs.ResultsTAPB‐TFPB‐COF nanofilm‐assisted LDI‐MS analyzed small molecules such as parabens, estrogens, and bisphenols with higher mass spectral signals and cleaner mass spectral backgrounds compared with 9‐AA. Meanwhile, the method analyzed methylparaben (MeP) with high reproducibility (RSD = 6.96%) and low detection limit (1.64 μM) and performed well for rapid screening of parabens in PCPs.ConclusionTAPB‐TFPB‐COF nanofilm‐assisted LDI‐MS for analyzing small molecules such as parabens, estrogens, and amino acids offered the advantages of rapid analysis, a clean background, and good reproducibility. The method was successfully applied to detecting parabens in PCPs, demonstrating the practical utility of LDI‐MS based on TAPB‐TFPB‐COF nanofilm for analyzing parabens in complex samples.
Allostatic Load as a Short‐Term Prognostic and Predictive Marker
Authors: García Ana M. Gómez , Arias Arias Angel Jesús , Muñoz Francisco López , García‐Rico E. 
Published: January 2025

ABSTRACTIt would be highly valuable to possess a tool for evaluating disease progression and identifying patients at risk of experiencing a more severe clinical course and potentially worse outcomes. The concept of allostatic load, which represents the overall strain on the body from repeated stress responses, has been recognized as a precursor to the development of chronic illnesses. It functions as a cumulative measure of the body's capacity to adapt to stress. Numerous studies have demonstrated that elevated allostatic load levels are associated with various negative health outcomes, both physical and mental, and are more predictive of mortality than individual biomarkers. Leveraging the unique circumstances presented by the COVID‐19 pandemic, we evaluated different clinical and laboratory parameters in hospitalised COVID‐19 patients to assess allostatic load. Our results indicated that allostatic load acts as a strong predictor of prolonged hospitalisation, increased ICU days, and mortality. This highlights its efficacy as a precise gauge of biological dysregulation linked to the response to COVID‐19 during disease progression. Allostatic load is easily obtainable and provides an early, cost‐effective indication of disease prognosis. Additionally, it has the potential to forecast the necessity for ICU admission. As a result, this parameter, indicative of the comprehensive physiological disruption in response to stress, emerges as a promising prognostic marker for hospitalised patients, extending beyond COVID‐19.
Commercial SiO Encapsulated in Hybrid Bilayer Conductive Skeleton as Stable Anode Coupling Chemical Prelithiation for Lithium‐Ion Batteries
Authors: Huang Haihang , Yin Xucai , Bai Xianhai , Long Xingzhi , Yuan Quanqiang , Shan Yaoxiang , Zou Yujie , Tong Zhangfa , Ren Yang 
Published: January 2025

AbstractAlthough Silicon monoxide (SiO) is regarded as the most promising next‐generation anode material, the large volume expansion, poor conductivity, and low initial Coulombic efficiency (ICE) severely hamper its commercialization application. Designing a multilayer conductive skeleton combined with advanced prelithiation technology is considered an effective approach to address these problems. Herein, a reliable strategy is proposed that utilizes MXene and carbon nanotube (CNT) as dual‐conductive skeletons to encapsulate SiO through simple electrostatic interaction for high‐performance anodes in LIBs, while also performing chemical prelithiation. Various characterizations and electrochemical measurements indicate that both MXene and CNT, as conductive networks and buffer interfaces, synergistically enhance the electron transport and lithium storage properties of the electrode. Moreover, the chemical prelithiation process effectively improves the ICE and cycling stability. Consequently, the prepared SiO@MXene@CNT anode delivers a high capacity of 1032 mAh g−1 after 200 cycles at 200 mA g−1 and an ultrahigh capacity retention rate of 89.5% beyond 1000 cycles at 1000 mA g−1. More importantly, the ICE of the SiO@MXene@CNT anode increases from 65.1% to 92.3% after chemical prelithiation. The work opens a new avenue for significantly improving the lithium storage performance of SiO‐based anodes and is expected to promote their commercialization progress.
Confined CVD Synthesis and Temperature‐Dependent Spectroscopic Properties of Bilayer Graphene Ribbon Arrays with Bifunctional Modulation of Adhesion Metal
Authors: Ning Congcong , Yang Qian , Jin Yan , Gong Xiangnan , Zhu Yifan , Mao Amin , Hu Baoshan 
Published: January 2025

AbstractBilayer graphene ribbons (GRs) hold great promise for the fabrication of next‐generation nanodevices, thanks to unparalleled electronic properties, especially the tunable bandgap in association with twist angle, ribbon width, edge structure, and interlayer coupling. A common challenge in manufacturing bilayer GRs via templated chemical vapor deposition (CVD) approach is uncontrollable dewetting of micro‐ and nano‐scaled patterned metal substrates. Herein, a confined CVD synthetic strategy of bilayer GR arrays is proposed, by utilizing the bifunctional Ni as a buffered adhesion layer to regulate the anisotropic dewetting of metal film in the V‐groove and as a carbon‐dissolution regulated metal to initiate the bilayer nucleation. Using C2H4 as direct donor of C dimer species, high‐quality bilayer GR arrays are synthesized on regular CuNi ribbons with twist angles at 900 °C, harnessing the non‐equilibrium jointly induced by confined V‐groove and C dimer species. The nucleation and growth mechanism of bilayer GR are investigated with density functional theory (DFT) calculations. The as‐grown bilayer GRs display distinctive variable temperature Raman and photoluminescence properties. Our results contribute to a highly controllable technique for fabricating twisted bilayer GR arrays and deep insights into the optical properties of bilayer GRs for potential optoelectronics applications.
Harnessing Banana Peel Waste: Development of Starch‐Based Bioplastics for Green Packaging
Authors: Seth Atul Kumar , Vellaparambil Hariharan Sangeetha , Jaideva Rajvardhan 
Published: January 2025

ABSTRACTThis study investigates the isolation and characterization of starch from green banana peels and preparation of biodegradable blend films thereof. Sodium metabisulfite was found more effective than sodium bisulfite in isolating starch, resulting in a higher yield. The extracted starch was verified through FTIR, XRD, SEM, and TGA analyses. Biodegradable blend film was prepared via solvent casting with the addition of 40 wt.% glycerol as plasticizer. FTIR analysis revealed good interactions between chitosan and green banana peel starch in the blend film. X‐ray diffraction, differential scanning calorimetry, and scanning electron microscopy confirmed that starch and chitosan in blend films displayed miscibility, interactions, and some microphase separation. Mechanical testing revealed that the film achieved an elongation at break of 76% when chitosan and starch were combined in equal proportions (50:50 by weight). Luminous transmittance decreased from 82% to 35% as starch content increased, while water absorption dropped from 89% to 61%. Soil burial tests demonstrated that the blend films exhibited greater biodegradability, as evidenced by higher weight loss and reduced tensile strength (0.53 MPa for CS4) compared to virgin chitosan film. Among the various formulations, the film containing 45% starch, 55% chitosan, and 40% glycerol (CS3) exhibited optimal performance, showcasing good mechanical strength, superior optical properties, effective water absorption, controlled swelling behavior, and improved biodegradability.
Machine Learning Approach to Energy Detection Based Spectrum Sensing for Cognitive Radio Networks
Authors: Ahmed Md. Tofail , Haque Mousumi , Sugiura Yosuke , Shimamura Tetsuya 
Published: January 2025

AbstractCognitive radio is an intelligent technology for wireless communication that optimizes the use of available frequency bands. Machine learning techniques can play an important role in spectrum sensing for cognitive radio networks to meet the rising traffic demand of wireless communication systems. The reliability of spectrum sensing methods depends on the prior knowledge of the noise to set a threshold. On the other hand, the success of a machine learning model relies on both the datasets and the accuracy of its learning algorithms. In this paper, we propose a spectrum sensing method for cognitive radio based on a machine learning algorithm in the conventional energy detection technique that removes the requirement to calculate the threshold. Initially, we introduce a method to build the dataset using the general concept of spectrum sensing based on the energy detection technique. The Naive Bayes supervised machine learning classification algorithm is implemented on the generated dataset for training, validation, and testing to sense the available spectrum. The proposed method is evaluated and tested using performance metrics such as confusion matrix, accuracy, precision, recall, F1 score, probability of detection, and probability of false alarm. In the simulation, the quadrature phase‐shift keying (QPSK) modulation scheme over the additive white Gaussian noise (AWGN) channel is considered. The experimental outcomes of the proposed method provide satisfactory and acceptable performance for spectrum sensing in cognitive radio networks. © 2025 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.
Multi‐Objective Sleeve Optimization of Solid High Speed Permanent Magnet Motor Based on Rotor Strength Failure Judgment Parameters
Authors: Yang Zihao , Ge Baojun , Dong Chuanyou , Tao Dajun , Yang Zhifei 
Published: January 2025

AbstractIt is necessary to consider the coupling effects of multiple physical fields in the rotor design of high speed permanent magnet motor. However, the calculation method ignoring axial constraints will lead to misjudgment of various strength failure modes of solid permanent magnet rotor. In this paper, the calculation methods of three kinds of judgment parameters of rotor strength failure modes under axial constraint are given by means of theoretical derivation. On this basis, a solid high speed permanent magnet motor of 38 000 rpm and 200 kW is taken as the research object to explore the rule of influence of sheath thickness on motor loss and temperature. Combining the rotor strength failure criterion and NSGAII algorithm, a new sleeve multi‐objective optimization design method for solid high speed permanent magnet motor is proposed by taking the multi‐physical properties such as strength, efficiency and temperature as objective functions. Finally, experiments and simulations are carried out to verify the effectiveness of the method. © 2025 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.
Exploring the Potential of Generative AI: Use Cases in Software Startups
Authors: Simaremare Mario , Triando  , Rico Sergio 
Published: January 2025

AbstractBackground and Related Work: Software startups face unique challenges in product development, including limited resources, the need for rapid innovation, and the constant pressure to adapt to market changes. Generative Artificial Intelligence (GenAI) has recently gained significant attention, offering capabilities to assist creative processes, generate content, and enhance decision-making through data analysis. However, how GenAI can be integrated into agile product development processes in software startups remains an open question. Objective: This study aims to identify potential use cases for GenAI in software startups and explore how GenAI can support innovation, overcome development challenges, and integrate with agile practices to improve product quality and development speed. Method: We identified a list of GenAI use cases from existing systematic literature reviews and mapped them to engineering process areas in software startups. Following that, we conducted workshops with experts to validate our results. Results: The results provide a descriptive overview of GenAI’s potential applications in software startup environments. Given the current state of the art, we identified areas that could benefit faster from integrating GenAI. Conclusions: The study delineates the prospective impact of GenAI on agile product development in software startups, showcasing areas of immediate applicability.
Social Capital in Software Product Management: A Case Study From a Large-Scale Agile Context
Authors: Barbala Astri , Moe Nils Brede , Berntzen Marthe 
Published: January 2025

AbstractAlthough large-scale agile software development increasingly is being organized in product areas, little research has to date looked into the skills needed for central roles to succeed with software product management (SPM) in a large-scale setting. Addressing this research gap, this paper provides insights into the skills and competencies deemed essential among Product Managers and Product Owners in ScanBank, a Scandinavian fintech organization counting over 10,000 employees. Our findings reveal that establishing and maintaining social networks are found to be paramount for successfully performing SPM-related tasks in a large-scale agile organizational context. We utilized a model for social capital consisting of three different dimensions to analyze our data material and highlight the value of social capabilities in enhancing collaboration and efficiency within large-scale agile SPM.
Selected Concepts of Leadership in Self-organizing Teams
Authors: Perlak Jakub 
Published: January 2025

AbstractSelf-organizing teams are a common way of organizing teamwork in sectors related to modern technologies, especially in programming teams. Agile methods often promote and advocate such teams. One of the problems in this form of team organization is the issue of leadership, and particularly the relationship between vertical leadership - one person, and horizontal leadership - team members. In the literature on the subject, we can find traces of many concepts in such a broad area as the issue of leadership. However, several selected concepts allow us to capture an emerging feature in self-organizing teams which is the taking over of leadership functions by team members. Shared leadership, where the leadership function comes from team members, not from one appointed leader. Distributed leadership is where leadership in the organization is taken over voluntarily by individuals. Balanced leadership, where the vertical leader enables team members to take over leadership functions depending on the situation. The selected concepts presented here allow for a better understanding and research of the nature and phenomenon of leadership in self-organizing teams.
Domestic Tax Regulation in the Face of the Crypto Economy: Challenges Going Forward
Authors: Cediel Ana 
Published: January 2025

AbstractOur tax system clings to a traditional economy linked to pre-digital criteria such as territoriality. It tries to update itself by introducing elements that attempt to deal with the new issues without resolving them head-on. The lack of tax regulation produces a sudden injustice barely resolved by soft law derived from binding administrative resolutions, such as the responses offered by the General Directorate of Taxes.MiCA demonstrates the tax system’s obsolescence in a broad and community sense. The lack of provisions for classifying new economic goods for tax purposes fragments their treatment, leads to tax conflicts, and creates legal uncertainty.This legal uncertainty contrasts with the enormous deployment of mechanisms to control compliance with tax obligations. These include the effective automatic exchange of tax information, joint inspection procedures, and the, at times, unscrupulous application of artificial intelligence to all types of available data, personal and non-personal, without time limitation.We understand that the rules applicable to the taxation of crypto assets must constantly be updated, and this is our purpose in an economy undergoing absolute digitalisation.
The European Digital Identity Wallet as Defined in the EIDAS 2 Regulation
Authors: Inza Julián 
Published: January 2025

AbstractSeveral legislative developments are taking place in Europe that make some regulations converge with others, and one of the most influential is the one that will govern the new digital identity model that arises from the modification of the European Regulation that defines digital identity and electronic trust services. Regulation 910/2014 is called eIDAS and has been essential in developing European-qualified trust services. Regulation (EU) 2024/1183, called eIDAS 2 because it modifies the eIDAS regulation and increases its scope, has been recently published in the Official Journal of the European Union.