bluuebunny/crossref_metadata_2025 huggingface dataset:
Immune-Boosting and Antiviral Effects of Antioxidants in COVID-19 Pneumonia: A Therapeutic Perspective
Authors: Sanduzzi Zamparelli Stefano , Sanduzzi Zamparelli Alessandro , Bocchino Marialuisa
Published: January 2025

The COVID-19 pandemic caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has profoundly impacted global health, with pneumonia emerging as a major complication in severe cases. The pathogenesis of COVID-19 is marked by the overproduction of reactive oxygen species (ROS) and an excessive inflammatory response, resulting in oxidative stress and significant tissue damage, particularly in the respiratory system. Antioxidants have garnered considerable attention for their potential role in managing COVID-19 pneumonia by mitigating oxidative stress and modulating immune responses. This review provides a comprehensive overview of the literature on the use of antioxidants in hospitalized patients with mild-to-moderate COVID-19. Studies exploring antioxidants, including vitamins, trace elements, nitric oxide (NO), ozone (O3), glutathione (GSH), L-carnitine, melatonin, bromelain, N-acetylcysteine (NAC), and numerous polyphenols, have yielded promising outcomes. Through their ROS-scavenging properties, these molecules support endothelial function, reduce the thrombosis risk, and may help mitigate the effects of the cytokine storm, a key contributor to COVID-19 morbidity and mortality. Clinical evidence suggests that antioxidant supplementation may improve patient outcomes by decreasing inflammation, supporting immune cell function, and potentially shortening recovery times. Furthermore, these molecules may mitigate the symptoms of COVID-19 by exerting direct antiviral effects that inhibit the infection process and genomic replication of SARS-CoV-2 in host cells. Moreover, antioxidants may work synergistically with standard antiviral treatments to reduce viral-induced oxidative damage. By integrating findings from the literature with real-world data from our clinical experience, we gain a more profound understanding of the role of antioxidants in managing COVID-19 pneumonia. Further research combining comprehensive literature reviews with real-world data analysis is crucial to validate the efficacy of antioxidants and establish evidence-based guidelines for their use in clinical practice.
Picosecond Laser Direct Writing of Micro-Nano Structures on Flexible Thin Film for X-Band Transmittance Function
Authors: Feng Jiecai , Zhou Jin , Xu Cuilian , Yang Bingdong , Tian Ze , Liu Hongfei , Zhang Yilian , Sun Zhenghao , Peng Xiaohai , Tian Yingzhong
Published: January 2025

Recently, ultrafast laser direct writing has become an effective method for preparing flexible films with micro-nano structures. However, effective control of laser parameters to obtain acceptable micro-nano structures and the effect of micro-nano structure sizes on function of the film remain challenges. Additionally, flexible films with high X-band transmittance are urgently required in aerospace and other fields. In this work, we evaluate the feasibility of applying picosecond laser direct writing for fabricating micro-nano structures on the surface of flexible thin film and the relationship between the size of square columnar micro-nano structures and the transmittance of the flexible thin film. The results show that an array of square columnar micro-nano structures was achieved by picosecond laser direct writing on the surface of flexible thin film (Au-SiO2-PI) with a thickness of 50 µm. Additionally, excellent micro-nano structures morphology of the square columnar arrays without burning through or destroying were obtained by laser direct writing with a pulse power and frequency of 2 W and 100 KHz, respectively. The results also show that the X-band transmittance was effected by the characteristic of the square columnar array on the surface of the flexible thin film. The X-band transmittance was significantly increased by decreasing the length of the square column on the surface of the flexible thin film. The X-band transmittance was slightly increased by decreasing the width of the groove of the square column on the surface of the flexible thin film.
Comparison of the Performance of Nonlinear Time-Dependent Constitutive Models Calibrated with Minimal Test Data Applied to an Epoxy Resin
Authors: Guedes Rui Miranda , Morais José Lopes
Published: January 2025

Epoxy resins are extensively employed as adhesives and matrices in fibre-reinforced composites. As polymers, they possess a viscoelastic nature and are prone to creep and stress relaxation even at room temperature. This phenomenon is also responsible for time-dependent failure or creep fracture due to cumulative strain. Several constitutive equations have been used to describe the mechanical time-dependent response of polymers. These models have been proposed over the past six decades, with minimal direct and practical confrontation. Each model is associated with a specific application or research group. This work assesses the predictive performance of four distinct time-dependent constitutive models based on experimental data. The models were deemed sufficiently straightforward to be readily integrated into practical engineering analyses. A range of loading cases, encompassing constant strain rate, creep, and relaxation tests, were conducted on a commercial epoxy resin. Model parameter calibration was conducted with a minimum data set. The extrapolative predictive capacity of the models was evaluated for creep loading by extending the tests to five decades. The selected rheological models comprise two viscoelastic models based on Volterra-type integrals, as originally proposed by Schapery and Rabotnov; one viscoplastic model, as originally proposed by Norton and Bailey; and the Burger model, in which two springs and two dashpots are combined in a serial and parallel configuration. The number of model parameters does not correlate positively to superior performance, even if it is high. Overall, the models exhibited satisfactory predictive performance, displaying similar outcomes with some relevant differences during the unloading phases.
Optimizing Lightweight Material Selection in Automotive Engineering: A Hybrid Methodology Incorporating Ashby’s Method and VIKOR Analysis
Authors: Risaliti Edoardo , Del Pero Francesco , Arcidiacono Gabriele , Citti Paolo
Published: January 2025

The automotive industry is responsible for about 20% of greenhouse gas emissions in Europe, and it is under notable pressure to meet the reduction targets set by the European Union for the next decades. In this context, lightweighting is a very effective design strategy for which materials selection plays a key role. One of the main challenges of lightweighting is selecting materials with enhanced structural properties but a reduced weight in comparison with traditional solutions. The spectrum of available materials is very large, and the choice needs to be carefully evaluated based on multiple factors, such as mechanical behavior, raw materials cost, the availability of manufacturing processes, and environmental impact. This article presents an innovative methodology for materials selection in the lightweight automotive field based on the Ashby approach for mechanical performance coefficients as an initial filtering criterion. Following this preliminary screening, this study adopts the VIKOR (Vise Kriterijumska Optimizacija I Kompromisno Resenje) MCDA (Multi-Criteria Decision Analysis) technique to rank feasible design solutions based on case study boundary conditions. The evaluation criterion of different design options encompasses crucial factors, such as mechanical properties, cost considerations, and environmental impact measures. The method is finally validated by the application of a redesign case study, a motor bracket of an electric commercial car.
The Volume-Based Pollution-Routing Problem with Time Windows: A Case Study
Authors: Bencharif Bilal , Beghoura Mohamed Amine , Demir Emrah
Published: January 2025

Green logistics has gained significant attention in recent years due to increasing pollution levels and their negative effects. This area of research is crucial as governments and countries worldwide recognize the severity of pollution and its detrimental effects. Despite progress, significant gaps remain due to the lack of advanced models that consider additional factors and the influence of speed on their outcomes. This paper presents a case study on the Volume-based Pollution-Routing Problem with Time Windows (VPRPTW). The objective is to minimize CO⁢2 emissions and improve customer satisfaction using a fleet of delivery vehicles. We propose a mathematical model and a probabilistic Tabu Search (TS) algorithm to solve the studied VPRPTW. The study revealed a decrease in daily fleet size from 16 to 12, indicating improved operational efficiency. In our study, we evaluate the impact of vehicle speed on fuel consumption and compare the results with a constant route speed to those obtained at varying speeds. Computational experiments reveal a significant difference of over 20% between fixed and variable speed assumptions. Additionally, we confirm that distance alone does not always correlate with energy consumption and CO⁢2 emissions. This highlights the importance of considering variable speeds in routing problems to assist logistics companies, urban planners, and policymakers achieve more accurate and environmentally friendly transportation solutions.
Absorption Spectrum of Hydroperoxymethyl Thioformate: A Computational Chemistry Study
Authors: Catalán-Fenollosa David , Carmona-García Javier , Borrego-Sánchez Ana , Saiz-Lopez Alfonso , Roca-Sanjuán Daniel
Published: January 2025

Hydroperoxymethyl thioformate (or HPMTF) is a compound relevant to the chemistry of sulfur in the marine atmosphere. The chemical cycling of this molecule in the atmosphere is still uncertain due in part to the lack of accurate knowledge of its photolytic behavior. Only approximations based on the properties of its chromophores are used in previous studies. In this work, we calculated the absorption spectra of the molecule in gas and aqueous phases using the Nuclear Ensemble Approach (NEA) and the CASPT2 method. Furthermore, we used such information to obtain relative photolysis rates. We found that the chromophore approximation overestimates the photolysis rates in the gas phase by twice the value obtained with the NEA-CASPT2 protocol. Furthermore, for the aqueous phase, we predict a lower role of photolysis as compared to the gas phase.
Mechanism and Characterization of Bicomponent-Filler-Reinforced Natural Rubber Latex Composites: Experiment and Molecular Dynamics (MD)
Authors: Feng Zhipeng , Zhu Hongzhou , Hu Bo , Chen Huabin , Yan Yong
Published: January 2025

The incorporation of reinforcing fillers into natural rubber latex (NR) to achieve superior elasticity and mechanical properties has been widely applied across various fields. However, the tendency of reinforcing fillers to agglomerate within NR limits their potential applications. In this study, multi-walled carbon nanotube (MWCNT)–silica (SiO2)/NR composites were prepared using a solution blending method, aiming to enhance the performance of NR composites through the synergistic effects of dual-component fillers. The mechanical properties, dispersion behavior, and Payne effect of three types of composites—SiO2/NR (SNR), MWCNT/NR (MNR), and MWCNT-SiO2/NR (MSNR)—were investigated. In addition, the mean square displacement (MSD), fractional free volume (FFV), and binding energy of the three composites were simulated using molecular dynamics (MD) models. The results showed that the addition of a two-component filler increased the tensile strength, elongation at break, and Young’s modulus of NR composites by 56.4%, 72.41%, and 34.44%, respectively. The Payne effect of MSNR was reduced by 4.5% compared to MNR and SNR. In addition, the MD simulation results showed that the MSD and FFV of MSNR were reduced by 21% and 17.44%, respectively, and the binding energy was increased by 69 times, which was in agreement with the experimental results. The underlying mechanisms between the dual-component fillers were elucidated through dynamic mechanical analysis (DMA), a rubber process analyzer (RPA), and field emission scanning electron microscopy (SEM). This study provides an effective reference for broadening the application fields of NR.
Controlled Capture of Magnetic Nanoparticles from Microfluidic Flows by Ferromagnetic Antidot and Dot Nanostructures
Authors: Dowling Reyne , Kostylev Mikhail
Published: January 2025

The capture of magnetic nanoparticles (MNPs) is essential in the separation and detection of MNPs for applications such as magnetic biosensing. The sensitivity of magnetic biosensors inherently depends upon the distribution of captured MNPs within the sensing area. We previously demonstrated that the distribution of MNPs captured from evaporating droplets by ferromagnetic antidot nanostructures can be controlled via an external magnetic field. In this paper, we demonstrate the capture of magnetic nanoparticles from a microfluidic flow by four variants of antidot array nanostructures etched into 30 nm thick Permalloy films. The nanostructures were exposed to 130 nm MNP clusters passing through microfluidic channels with square cross-sections of 400 μm × 400 μm. In the presence of a parallel magnetic field, up to 83.1% of nanoparticles were captured inside the antidot holes. Significantly higher proportions of nanoparticles were captured within the antidots from the flow than when applying the nanoparticles via droplets. In the parallel field configuration, MNPs can be focused into the regularly spaced antidot indents in the nanostructure, which may be useful when detecting or observing MNPs and their conjugates. Conversely, up to 84% of MNPs were caught outside of antidots under a perpendicular magnetic field. Antidot nanostructures under this perpendicular configuration show potential for MNP filtration applications.
A Cross-Sectional Study Exploring the Role of Social Isolation in the Relationship Between Food Insecurity, Depressive Symptoms, and Resource Use Among Midwestern Rural Veterans in the U.S.
Authors: Uwashimimana Mwiza A. , MacDermid Wadsworth Shelley , Sneddon Douglas A. , Newton Jake , Eicher-Miller Heather A.
Published: January 2025

Background/Objectives: The study’s objective was to determine whether social isolation serves as a mediator in the cross-sectional relationship between food insecurity, both as a short-term and longer-term situation, with resource use and depressive symptoms as outcomes. Methods: This cross-sectional design study utilized secondary survey data, including 30-day and 12-month food security measured by the U.S. Household Food Security Survey Module. The Baron–Kenny mediation approach was used to determine whether social isolation mediated the relationship between food security, depressive symptoms, and resource use (p ≤ 0.05). Results: Social isolation mediates the association between both 30-day and 12-month food security with depressive symptoms but not resource use. Conclusions: Acknowledging and targeting social isolation, policies, and interventions that integrate peer support and community outreach to promote food security could support rural veterans food security and mental health.
Archival and Newly Isolated Historical Bacillus anthracis Strains Populate the Deeper Phylogeny of the A.Br.075(Sterne) Clade
Authors: Antwerpen Markus , Braun Peter , Beyer Wolfgang , Aldenkortt Dirk , Seidel Michael , Grass Gregor
Published: January 2025

The anthrax pathogen Bacillus anthracis can remain dormant as spores in soil for many years. This applies to both natural foci and to sites of anthropogenic activity such as tanneries, abattoirs, or wool factories. The A.Br.075 (A-branch) clade (also known as A.Br.Sterne) is prominent not only because it comprises several outbreak strains but even more so because spore preparations of its namesake, the Sterne strain, are counted among the most utilized anthrax animal vaccines. In this study, we genome-sequenced and analyzed 56 additional B. anthracis isolates of the A.Br.075 clade. Four of these we recently retrieved from soil samples taken from a decades-long abandoned tannery. The other 52 strains originated from our archival collection from the 20th century. Notably, the extended phylogeny of the A.Br.075 clade indicated that many of the newly added chromosomes represent basal members, some of which are among the most basal strains from this lineage. Twelve new strains populate a very deep-branching lineage we have named A.Br.Ortho-Sterne (also known as A.Br.076). A further 11 isolates amend the clade named A.Br.Para-Sterne (A.Br.078). Finally, some of the terminal clusters of the clade named A.Br.Eu-Sterne appear to be replete with (near) identical isolates, possibly a result of widespread use of the Sterne vaccine and of its re-isolation from vaccination-related animal anthrax outbreaks. From the accrued new phylogenetic information, we designed and tested a variety of new SNP-PCR assays for rapid and facile genotyping of unassigned B. anthracis genomes. Lastly, the successful isolation of live B. anthracis from a long-abandoned tannery reemphasizes the need for continued risk awareness of such sites.
Targeting Cytokine-Mediated Inflammation in Brain Disorders: Developing New Treatment Strategies
Authors: Mallick Rahul , Basak Sanjay , Chowdhury Premanjali , Bhowmik Prasenjit , Das Ranjit K. , Banerjee Antara , Paul Sujay , Pathak Surajit , Duttaroy Asim K.
Published: January 2025

Cytokine-mediated inflammation is increasingly recognized for playing a vital role in the pathophysiology of a wide range of brain disorders, including neurodegenerative, psychiatric, and neurodevelopmental problems. Pro-inflammatory cytokines such as interleukin-1 (IL-1), tumor necrosis factor-alpha (TNF-α), and interleukin-6 (IL-6) cause neuroinflammation, alter brain function, and accelerate disease development. Despite progress in understanding these pathways, effective medicines targeting brain inflammation are still limited. Traditional anti-inflammatory and immunomodulatory drugs are effective in peripheral inflammatory illnesses. Still, they face substantial hurdles when applied to the central nervous system (CNS), such as the blood–brain barrier (BBB) and unwanted systemic effects. This review highlights the developing treatment techniques for modifying cytokine-driven neuroinflammation, focusing on advances that selectively target critical cytokines involved in brain pathology. Novel approaches, including cytokine-specific inhibitors, antibody-based therapeutics, gene- and RNA-based interventions, and sophisticated drug delivery systems like nanoparticles, show promise with respect to lowering neuroinflammation with greater specificity and safety. Furthermore, developments in biomarker discoveries and neuroimaging techniques are improving our ability to monitor inflammatory responses, allowing for more accurate and personalized treatment regimens. Preclinical and clinical trial data demonstrate the therapeutic potential of these tailored techniques. However, significant challenges remain, such as improving delivery across the BBB and reducing off-target effects. As research advances, the creation of personalized, cytokine-centered therapeutics has the potential to alter the therapy landscape for brain illnesses, giving patients hope for better results and a higher quality of life.
Exploring Azithromycin’s Neuroprotective Role in Traumatic Brain Injury: Insights into Cognitive and Motor Recovery and Neuroinflammatory Modulation
Authors: Almikhlafi Mohannad A. , Abdallah Nehad A. , Kumar Aakash , Sharma Tarun , Khan Zuber , Fadil Haifa A. , Althagfan Sultan , Aljohani Ahmed K. B. , Almadani Sara A. , Miski Samar F. , Saeedi Tahani , Alharbi Rayan S. , Al-Harthe Abdulrahman M. , Alsubhi Mohammed H. , Wanas Hanaa , Aldhafiri Ahmed , Mehan Sidharth , Elbadawy Hossein M.
Published: January 2025

Background: Traumatic brain injury (TBI) is a leading cause of mortality worldwide and often results in substantial cognitive, motor, and psychological impairments, triggering oxidative stress, neuroinflammation, and neurodegeneration. This study examined the neuroprotective effects of azithromycin (AZI) in TBI. Methods: TBI was induced in rats using the weight-drop method. Subsequently, rats received a daily intraperitoneal (I.P.) dose of AZI (150 mg/kg) for 28 days. Behavioral tests (Morris water maze, rotarod, and open field tests) were performed to assess cognitive and motor functions. Neurochemical analyses included oxidative stress markers (GSH, SOD, MDA, catalase), inflammatory cytokines (TNF-α, IL-1β), apoptotic markers (caspase-3, Bax, Bcl-2), mitochondrial complexes (complex I, II, III, IV, and V), and the transforming growth factor- beta (TGF-β) as a neurofilament marker. Histological evaluations focused on neuronal integrity in the cortex, hippocampus, and striatum. Results: Treatment with AZI significantly facilitated motor and cognitive function recovery in TBI-affected rats. At the molecular level, AZI effectively reduced oxidative stress markers, ameliorated neuroinflammation by decreasing TNF-α, IL-1β, and neuronal apoptosis, and differentially modulated mitochondrial complexes. Histological assessments revealed enhanced neuronal integrity and fewer pathological changes in AZI-treated rats compared to untreated TBI controls. Conclusions: AZI was shown to interfere with several pathways involved in TBI’s pathophysiology. While preclinical results are promising, further studies are necessary to establish the long-term safety and efficacy of AZI in a clinical setting. This research supports the potential re-purposing of AZI as a novel treatment strategy for TBI and related neurodegenerative disorders.
InP/Si3N4 Hybrid Integrated Lasers for RF Local Oscillator Signal Generation in Satellite Payloads
Authors: César-Cuello Jessica , Zarzuelo Alberto , Guzmán Robinson C. , Mitsolidou Charoula , Visscher Ilka , Timens Roelof B. , Dijk Paulus W. L. Van , Roeloffzen Chris G. H. , González Luis , Delgado Mendinueta José Manuel , Carpintero Guillermo
Published: January 2025

This paper presents an integrated tunable hybrid multi-laser module designed to simultaneously generate multiple radiofrequency (RF) local oscillator (LO) signals through optical heterodyning. The device consists of five hybrid InP/Si3N4 integrated lasers, each incorporating an intracavity wavelength-selective optical filter formed by two micro-ring resonators. Through beating the wavelengths generated from three of these lasers, we demonstrate the simultaneous generation of two LO signals within bands crucial for satellite communications (SatCom): one in the Ka-band and the other in the V-band. The device provides an extensive wavelength tuning range across the entire C-band and exhibits exceptionally narrow optical linewidths, below 40 kHz in free-running mode. This results in ultra-wideband tunable RF signals with narrow electrical linewidths below 100 kHz. The system is compact and highly scalable, with the potential to generate up to 10 simultaneous LO signals, being a promising solution for advanced RF signal generation in high throughput satellite payloads.
Genome-Wide Identification and Expression Analysis of PkNRT Gene Family in Korean Pine (Pinus koraiensis)
Authors: Zhao Xinyu , Wu Haibo , Li Boyang , Wang Pengyang , Zhang Peng , Shen Hailong , Yang Jianfei
Published: January 2025

The utilization of nitrogen (N) is crucial for the optimal growth and development of plants. As the dominant form of nitrogen in temperate soil, nitrate (NO3−) is absorbed from the soil and redistributed to other organs through NO3− transporters (NRTs). Therefore, exploration of the role of NRTs in response to various NO3− conditions is crucial for improving N utilization efficiency (NUE). Here, we present a comprehensive genome-wide analysis and characterization of the NRT gene family in Korean pine, an invaluable tree species cultivated extensively in northeastern China. A total of 76 PkNRTs were identified in Korean pine and further divided into three subfamilies (NRT1/NPF, NRT2, and NRT3) based on phylogenetic analysis. All PkNRTs were distributed on 11 chromosomes, with multiple tandem duplications observed. The tissue-specific expression analysis indicated that most PkNRTs showed differential expression in six vegetative tissues. Furthermore, a significantly greater number of lateral roots was observed in seedlings under nitrogen-deficient conditions, accompanied by an increase in both total root biomass and root length. The temporal expression profiles of 16 PkNRTs in seedling roots revealed that four PkNRTs, PkNPF5.6, PkNPF5.13, PkNPF6.1, and PkNPF6.2, exhibited significantly upregulated expression under the NO3− deficiency condition, whereas robust induction was observed for PkNPF1.1, PkNRT2.6, and PkNRT3.3 upon the NO3− sufficiency condition. The expression patterns of the PkNRTs suggest their potential diverse roles as key participants in root NO3− uptake under varying NO3− conditions during root development. These findings would provide a theoretical foundation for further investigations into the functions of PkNRTs in Korean pine.
Biomimetic Silicone Surfaces for Antibacterial Applications
Authors: Barshutina Marie , Yakubovsky Dmitry , Arsenin Aleksey , Volkov Valentyn , Barshutin Sergey , Vladimirova Anastasiya , Baymiev Andrei
Published: January 2025

Biomimetic patterning emerges as a promising antibiotic-free approach to protect medical devices from bacterial adhesion and biofilm formation. The main advantage of this approach lies in its simplicity and scalability for industrial applications. In this study, we employ it to produce antibacterial coatings based on silicone materials, widely used in the healthcare industry. In doing so, we patterned silicone substrates with a topography of various flower petals (rose, chamomile, pansy, and magnolia) and studied the relationship between the antibacterial properties of the obtained biomimetic substrates and their surface topography. To study the surface topography of biomimetic surfaces, we used the fractal analysis of their SEM images. In particular, as a measure of surface complexity and heterogeneity, we used the values of the developed interfacial area ratio (Sdr) and lacunarity coefficient (β). In the result, we found that the bacterial area coverage of biomimetic substrates decreased exponentially with the increase in their surface complexity and heterogeneity, and prominent antibacterial properties were observed at β > 1.6 and Sdr > 50. The results of this study can be used to identify biomimetic materials with superior antibacterial properties and produce efficient antibacterial silicone coatings for biomedical and healthcare applications.
Antioxidant Particleboards Produced from Forest By-Products with Application in the Food Packaging Industry
Authors: Fernandes Raquel A. , Ferreira Nuno , Lopes Sandro , Freitas Beatriz , Santos Jorge , Martins Jorge M. , Carvalho Luisa H.
Published: January 2025

The food packaging industry is one of the fastest growing sectors of our economy, with a large contribution to environmental concerns due to the extensive use of fossil-derived materials. Combining wood-based materials, such as particleboards, with bio-adhesives may offer a great opportunity to develop sustainable packaging solutions with active antioxidant properties. In the present work, a phenolic extract of poplar bark was produced and bio-adhesives were formulated using citric acid as a cross-linker. The impact of citric acid content on the chemical and bonding properties of bio-adhesives was evaluated. Additionally, the impact of the temperature of curing on their antioxidant capacity was also accessed. The bio-adhesives were applied in the production of particleboards, using poplar veneer particles as raw material. The composite materials exhibit high mechanical resistance, fulfilling the requirement of PB type P1, with remarkable antioxidant activity, opening a possibility to be employed in an active packaging solution.
Fracture Toughness of Winding Carbon Plastics Based on Epoxy Matrices and Reinforced by Polysulfone Film
Authors: Dzhangurazov Eldar B. , Petrova Tuyara V. , Shapagin Aleksey V. , Tretyakov Ilya V. , Korokhin Roman A. , Kireynov Aleksey V. , Alexeeva Olga V. , Solodilov Vitaliy I. , Yurkov Gleb Yu. , Berlin Alexander Al.
Published: January 2025

In this work, the fracture mechanism of winding carbon-fiber-reinforced plastics (CFRPs) based on epoxy matrices reinforced by polysulfone film was investigated. Two types of polymer matrices were used: epoxy oligomer (EO) cured by iso-methyltetrahydrophthalic anhydride (iso-MTHPA), and EO-modified polysulfone (PSU) with active diluent furfuryl glycidyl ether (FGE) cured by iso-MTHPA. At the winding stage, the reinforcing film was placed in the middle layer of the CFRP. The fracture toughness GIR of the obtained CFRP was determined by the double-cantilever beam delamination method. Additionally, the effect of cyclic loading on the fracture toughness of CFRP reinforced with polysulfone film was investigated. It was shown that heterogeneous structures arising from the dissolution of the polysulfone film in the epoxy binder during the curing process increase the fracture toughness of CFRP from 0.5 kJ/m2 to 1.2 kJ/m2. Application of cyclic loads had little effect on the fracture toughness value. As a result of this study, it was revealed that the macrocrack propagates near the reinforcement layer along the diffusion zone, which has a phase organization of the type PSU matrix–EO dispersion.
Applications of Nanomaterial Coatings in Solid-Phase Microextraction (SPME)
Authors: Adeniji Taiwo Musa , Haroon Naila , Stine Keith J.
Published: January 2025

This review explores the advances in developing adsorbent materials for solid-phase microextraction (SPME), focusing on nanoparticles, nanocomposites, and nanoporous structures. Nanoparticles, including those of metals (e.g., gold, silver), metal oxides (e.g., TiO2, ZnO), and carbon-based materials (e.g., carbon nanotubes, graphene), offer enhanced surface area, improved extraction efficiency, and increased selectivity compared to traditional coatings. Nanocomposites, such as those combining metal oxides with polymers or carbon-based materials, exhibit synergistic properties, further improving extraction performance. Nanoporous materials, including metal–organic frameworks (MOFs) and ordered mesoporous carbons, provide high surface area and tunable pore structures, enabling selective adsorption of analytes. These advanced materials have been successfully applied to various analytes, including volatile organic compounds (VOCs), polycyclic aromatic hydrocarbons (PAHs), pesticides, and heavy metals, demonstrating improved sensitivity, selectivity, and reproducibility compared to conventional SPME fibers. The incorporation of nanomaterials has significantly expanded the scope and applicability of SPME, enabling the analysis of trace-level analytes in complex matrices. This review highlights the significant potential of nanomaterials in revolutionizing SPME technology, offering new possibilities for sensitive and selective analysis in environmental monitoring, food safety, and other critical applications.
Multi-Type Ship Target Detection in Complex Marine Background Based on YOLOv11
Authors: Wang Yao , Zeng Weigui , Xu Huiqi , Jiang Yi , Liu Minggang , Xiao Chuanliang , Zhao Ke
Published: January 2025

Realizing accurate control of ship target information in complex marine environments is of great significance for maintaining marine environment security and safeguarding maritime sovereignty. With the rapid development of material technology and manufacturing industry, the types and styles of ships are increasing, and the distribution of multi-type ships on the sea is widespread. How to realize the accurate detection and identification of dynamic multi-type ship targets in the complex marine environment is an important and difficult problem that needs to be solved urgently in current marine environment detection. In this paper, an improved YOLOv11 ship target detection algorithm is proposed, which firstly utilizes the improved EfficientNetv2 network to replace the original backbone network of YOLOv11 to improve the learning ability of ship features under complex sea conditions; in order to solve the problem of interference by moving objects at sea when detecting dense ship targets and reduce the problems of missing detection and false alarms, the algorithm borrows from ConvNext block idea in the process of a neck feature pyramid network fusion; the algorithm introduces the WIoU loss function, which compensates for the effect of the small number of pixels of the small target in the process of regression loss computation, so as to improve the network’s performance in detecting small targets. In order to test the network performance in actual application scenarios, the article builds a visible ship target dataset, including complex background, occlusion and overlap, small targets, and other factors. Through experimental verification, the detection accuracy of the improved algorithm is improved by 5.6% compared with the original algorithm, and compared with typical algorithms in terms of detection accuracy, speed, and number of parameters, ablation experiments are designed to comprehensively validate and analyze the algorithm’s performance.
Dynamic Interferometry for Freeform Surface Measurement Based on Machine Learning-Configured Deformable Mirror
Authors: Chang Xu , Hu Yao , Wang Jintao , Liu Xiang , Hao Qun
Published: January 2025

Optical freeform surfaces are widely used in imaging and non-imaging systems due to their high design freedom. In freeform surface manufacturing and assembly, dynamic freeform surface measurement that can guide the next operation remains a challenge. To meet this urgent need, we propose a dynamic interferometric method based on a machine learning-configured deformable mirror (DM). In this method, a dynamic interferometric system is developed. By using coaxial structure and polarization interference, transient measurement of the measured surface can be realized to meet dynamic requirements, and at the same time, DM transient monitoring can be realized to reduce the accuracy loss caused by DM surface changes and meet dynamic requirements. A transient phase modulation scheme using machine learning to configure the DM surface is proposed, which keeps the system in a measurable state. Compared with the traditional phase modulation scheme that relies on iteration, the scheme proposed in this paper is more efficient and is conducive to meeting dynamic requirements. The feasibility is verified by practical experiments. The research in this paper has significance for guiding the application of dynamic interferometry in the measurement of dynamic surfaces.
A Magnetoelectric Distance Estimation System for Relative Human Motion Tracking
Authors: Hoffmann Johannes , Wolframm Henrik , Engelhardt Erik , Boueke Moritz , Schmidt Tobias , Welzel Julius , Höft Michael , Maetzler Walter , Schmidt Gerhard
Published: January 2025

Clinical motion analysis plays an important role in the diagnosis and treatment of mobility-limiting diseases. Within this assessment, relative (point-to-point) tracking of extremities could benefit from increased accuracy. Given the limitations of current wearable sensor technology, supplementary spatial data such as distance estimates could provide added value. Therefore, we propose a distributed magnetic tracking system based on early-stage demonstrators of novel magnetoelectric (ME) sensors. The system consists of two body-worn magnetic actuators and four ME sensor arrays (body-worn and fixed). It is enabled by a comprehensive signal processing framework with sensor-specific signal enhancement and a gradient descent-based system calibration. As a pilot study, we evaluated the technical feasibility of the described system for motion tracking in general (Scenario A) and for operation during treadmill walking (Scenario B). At distances of up to 60 cm, we achieved a mean absolute distance error of 0.4 cm during gait experiments. Our results show that the modular system is capable of centimeter-level motion tracking of the lower extremities during treadmill walking and should therefore be investigated for clinical gait parameter assessment.
A Large-Scale Agricultural Land Classification Method Based on Synergistic Integration of Time Series Red-Edge Vegetation Index and Phenological Features
Authors: Zhao Huansan , Chang Chunyan , Wang Zhuoran , Zhao Gengxing
Published: January 2025

Agricultural land classification plays a pivotal role in food security and ecological sustainability, yet achieving accurate large-scale mapping remains challenging. This study presents methodological innovations through a multi-level feature enhancement framework that transcends traditional time series analysis. Using Shandong Province, northern China’s agricultural heartland, as a case study, we first established a foundation with time series red-edge vegetation indices (REVI) from Sentinel-2 imagery, uniquely combining the normalized difference red edge index (NDRE705) and plant senescence reflectance index (PSRI). Moving beyond conventional time series analysis, we innovatively amplified key temporal characteristics through newly designed spatial feature parameters (SFPs) and phenological feature parameters (PFPs). This strategic enhancement of critical temporal points significantly improved classification performance by capturing subtle spatial patterns and phenological transitions that are often overlooked in traditional approaches. The study yielded three significant findings: (1) The synergistic application of NDRE705 and PSRI significantly outperformed single-index approaches, demonstrating the effectiveness of our dual-index strategy; (2) The integration of SFPs and PFPs with time series REVI markedly enhanced feature discrimination at crucial growth stages, with PFPs showing superior capability in distinguishing agricultural land types through amplified phenological signatures; (3) Our optimal classification scheme (FC6), leveraging both enhanced spatial and phenological features, achieved remarkable accuracy (93.21%) with a Kappa coefficient of 0.9159, representing improvements of 4.83% and 0.0538, respectively, over the baseline approach. This comprehensive framework successfully mapped 120,996 km2 of agricultural land, differentiating winter wheat–summer maize rotation areas (39.44%), single-season crop fields (36.16%), orchards (14.49%), and facility vegetable fields (9.91%). Our approach advances the field by introducing a robust, scalable methodology that not only utilizes the full potential of time series data but also strategically enhances critical temporal features for improved classification accuracy, particularly valuable for regions with complex farming systems and diverse crop patterns.
The Role of Environmental Certification in the Hospitality Industry: Assessing Sustainability, Consumer Preferences, and the Economic Impact
Authors: Velaoras Konstantinos , Menegaki Angeliki N. , Polyzos Serafeim , Gotzamani Katerina
Published: January 2025

Hotel certifications have become increasingly vital in promoting sustainability within the hospitality industry, providing frameworks that guide hotels toward reducing their environmental footprint, enhancing operational efficiency, and gaining a competitive edge in the marketplace. This review explores the development, types, and impact of hotel certifications, with a focus on prominent schemes, such as LEED, Green Key, and EarthCheck. Through an analysis of case studies from globally recognized hotels, we highlight how certifications contribute to significant reductions in energy and water use, improved waste management, and enhanced biodiversity protection, while also delivering economic benefits through cost savings and increased guest loyalty. Our paper also examines consumer perceptions of certifications and their willingness to pay (WTP) for certified hotels. The findings suggest that eco-conscious travelers, particularly younger generations, are willing to pay a premium for hotels that demonstrate a commitment to sustainability; however, consumer awareness of certification schemes remains limited. The barriers to adopting certifications, such as high initial costs, resource limitations, and management resistance, are also discussed, along with the challenges posed by greenwashing and the proliferation of certification schemes. Looking to the future, this review identifies key trends that will shape the evolution of hotel certifications, including increased transparency, the integration of smart technologies, the expanding role of social responsibility, and their alignment with global sustainability goals, such as the United Nations Sustainable Development Goals (SDGs). Hotel certifications are not only crucial for environmental sustainability, but also serve as a powerful tool for enhancing the economic viability of hotels in an increasingly competitive and sustainability-driven market.
Individual Factors Influencing the Use of Home- and Community-Based Care Services by Disabled Elderly Individuals in Urban Areas: Evidence from Beijing, China
Authors: Gao Xiuwen , Tang Yong
Published: January 2025

China’s rapidly aging population necessitates a sustainable social care system. Although the majority of Chinese disabled older adults live in their communities, the utilization rate of home- and community-based care (HCBC) services has been low. Moreover, family members still take the main responsibility for the care of disabled older persons and generally suffer from the stress of caregiving. To increase the use of HCBC services by disabled elderly families, this study examined which individual characteristics of both elderly individuals and their primary family caregivers were related to HCBC service use among disabled urban elderly individuals in a regional sample from the 2018 to 2019 Beijing Precise Assistance Need Survey (n = 34,153). Logistic regression was used as the baseline model, and a simultaneous equation model was established to address the jointly dependent variables. The results show that the degree of disability of disabled older adults has no significant effect on their service use, whereas their worse health status played a significant role in predicting respite care service use. Working status, a longer period of caregiving, and poor health of caregivers all significantly predict a greater likelihood of service use by elderly individuals. Caregivers with burdened feelings predicted a decrease in the likelihood of elderly individuals using services. Our findings show that primary family caregivers have an important influence on disabled elderly people’s use of HCBC services, but service use is more likely to compensate for the lack of care and expertise provided by family caregivers than to reduce caregivers’ caregiving burden.
The Effect of Intelligent Development on Green Economy Efficiency: An Analysis Based on China’s Province-Level Data
Authors: Yao Yingyu , Pan Haiying
Published: January 2025

As the main driving force of the new technological revolution, intelligent development is the key to promoting high-quality economic development. This paper empirically examines the nonlinear influence of intelligent development on green economy efficiency and its action paths using provincial panel data of China from 2009 to 2021. The result provides significant evidence of a U-shaped relationship between intelligent development and green economy efficiency, indicating that intelligent development initially leads to green economy efficiency decreases before ultimately increasing. Additional analysis confirms that environmental regulation, green finance, and industrial agglomeration positively moderate the impact of intelligent development on green economy efficiency. Furthermore, heterogeneous tests reveal that in the eastern region and after the release of “Made in China 2025” in 2015, the nonlinear effect of intelligent development on green economy efficiency is more pronounced. The findings of this paper provide a beneficial reference for how to leverage intelligent technology to release new kinetic energy for green economic growth under the new development concept.
Sustainable Development in Africa: A Comprehensive Analysis of GDP, CO2 Emissions, and Socio-Economic Factors
Authors: Habimana Simbi Claudien , Yao Fengmei , Zhang Jiahua
Published: January 2025

The fight against climate change is gaining momentum, with a growing focus on reducing carbon dioxide (CO2) emissions and mitigating environmental impacts. Africa, the continent most vulnerable to global warming, faces unique challenges in this context. This study examines the long-term association among CO2 emissions, economic growth, and different socio-economic factors in 36 African countries from 1990 to 2020. Employing the Pooled Mean Group (PMG) estimator with Autoregressive Distributed Lag (ARDL) model, along with U-test and Dumitrescu and Hurlin causality analyses, our study reveals substantial long-term connections amongst CO2 emissions and factors such as economic growth, trade openness, renewable energy consumption, urbanization, and population dynamics. The findings support the Environmental Kuznets Curve (EKC) hypothesis, indicating that CO2 emissions initially increase with GDP per capita growth but begin to decline after a turning point at approximately 10,614.75 USD. However, the evidence for this turning point remains weak, suggesting that most African countries have not yet achieved decoupling. Renewable energy consumption and urbanization are negatively associated with CO2 emissions, while trade openness and GDP per capita show positive correlations. Causality analysis reveals bidirectional relationships among most variables, except for population growth and CO2 emissions, which may involve other moderating factors. The findings highlight the urgent need for integrated policies that advance sustainable development by focusing on renewable energy adoption, sustainable urbanization, and green growth strategies. Policymakers should prioritize initiatives that harmonize economic growth with environmental sustainability, ensuring a lasting balance between development and ecological preservation across Africa.
Water Reuse: Contribution of a Decision Support Model
Authors: Filho Edilson Holanda Costa , Stefanutti Ronaldo , Oliveira Ulisses Costa de , Matos José Saldanha
Published: January 2025

Sustainability seeks to strike a balance between preserving the environment and meeting human needs without compromising future generations. In this context, and considering the effects of climate change on water availability, water reuse is emerging as an alternative to conventional water sources for various purposes, contributing to sustainability. Water reuse projects are, in general, not simple to implement due to different technical, environmental, social and economic aspects. In this paper, a support decision model for water reuse projects is presented, identifying relevant indicators and parameters. Based on a literature review, four indicators or dimensions (technical, social, environmental and economic) and twelve parameters (e.g., WWTP safety, transport complexity, existence of legislation, risk to health and environment, energy consumption, degree of acceptance and required investment and operation and maintenance costs) are proposed. The Fuzzy Analytic Hierarchy Process (FAHP) method is used as a component of the model to determine the weights of the indicators and parameters in order to allow the calculation of a reuse feasibility index (RFI). The developed model was applied to the city of Aquiraz, Ceará, Brazil, and the RFI found was 82%, which means that the water reuse project had very high viability. The results underwent a sensitivity analysis, which confirms the consistency of the conclusions.