bluuebunny/crossref_metadata_2025 huggingface dataset:
The VEGFB Gene Variants and the Effectiveness of Platelet-Rich Plasma Treatment of Lateral Elbow Tendinopathy: A Prospective Cohort Study with a Two-Year Follow-Up
Authors: Jarosz Alicja , Nowak Tomasz , Szyluk Karol , Balcerzyk-Matić Anna , Iwanicki Tomasz , Iwanicka Joanna , Kalita Marcin , Gawron Katarzyna , Kania Wojciech , Niemiec Paweł
Published: December 2024

Platelet-rich plasma (PRP) is an autologous preparation used to accelerate regeneration; however, this form of therapy is not always effective. Vascular endothelial growth factor B (VEGFB), which affects vessel survival, pathological angiogenesis, and muscle development may differentiate the risk and treatment of lateral elbow tendinopathy (LET). In this study, we analyzed the influence of VEGFB gene polymorphisms on the effectiveness of LET treatment with PRP. Therapeutic effectiveness was analyzed in 107 patients (132 elbows) using patient-reported outcome measures (PROMs), specifically the visual analog scale (VAS); quick version of disabilities of the arm, shoulder, and hand score (QDASH); and patient-rated tennis elbow evaluation (PRTEE), for two years (weeks 2, 4, 8, 12, 24, 52, and 104). The polymorphisms selected for the study were rs72922019, rs12366035, rs4930152, rs594942, and rs595880, being in strong linkage disequilibrium. Patients with TT (rs72922019), TT (rs12366035), AA (rs4930152), CC (rs594942), and GG (rs595880) genotypes showed better treatment effectiveness. Statistically important differences were shown for rs72922019 VAS (week 2), QDASH (weeks 0–4), and PRTEE (week 2); rs12366035 and rs4930152 VAS (week 2), QDASH (week 2), and PRTEE (weeks 2 and 4); and rs594942 and rs595880 VAS (weeks 2 and 4), QDASH (week 2), and PRTEE (weeks 2, 52, and 104). The studied polymorphisms also showed an association with blood morphological parameters, including mean platelet volume, platelet distribution width, and eosinophil levels, as well as some comorbidities (heart failure). Genotyping due to patient selection for therapy may be considered for any of the rs72922019, rs12366035, or rs4930152 polymorphisms.
Exploring Antimicrobial Compounds from Agri-Food Wastes for Sustainable Applications
Authors: Di Maro Mattia , Gargiulo Luca , Gomez d’Ayala Giovanna , Duraccio Donatella
Published: December 2024

Transforming agri-food wastes into valuable products is crucial due to their significant environmental impact, when discarded, including energy consumption, water use, and carbon emissions. This review aims to explore the current research on the recovery of bioactive molecules with antimicrobial properties from agri-food waste and by-products, and discusses future opportunities for promoting a circular economy in its production and processing. Mainly, antibacterial molecules extracted from agri-food wastes are phenolic compounds, essential oils, and saponins. Their extraction and antimicrobial activity against a wide spectrum of bacteria is analyzed in depth. Also, their possible mechanisms of activity are described and classified based on their effect on bacteria, such as the (i) alteration of the cell membrane, (ii) inhibition of energy metabolism and DNA synthesis, and iii) disruption of quorum sensing and biofilm formation. These bioactive molecules have a wide range of possible applications ranging from cosmetics to food packaging. However, despite their potential, the amount of wastes transformed into valuable compounds is very low, due to the high costs relating to their extraction, technical challenges in managing supply chain complexity, limited infrastructure, policy and regulatory barriers, and public perception. For these reasons, further research is needed to develop cost-effective, scalable technologies for biomass valorization.
Development of an rpS6-Based Ex Vivo Assay for the Analysis of Neuronal Activity in Mouse and Human Olfactory Systems
Authors: Broillet-Olivier Emma , Wenger Yaëlle , Gilliand Noah , Cadas Hugues , Sabatasso Sara , Broillet Marie-Christine , Brechbühl Julien
Published: December 2024

Olfactory sensitivity to odorant molecules is a complex biological function influenced by both endogenous factors, such as genetic background and physiological state, and exogenous factors, such as environmental conditions. In animals, this vital ability is mediated by olfactory sensory neurons (OSNs), which are distributed across several specialized olfactory subsystems depending on the species. Using the phosphorylation of the ribosomal protein S6 (rpS6) in OSNs following sensory stimulation, we developed an ex vivo assay allowing the simultaneous conditioning and odorant stimulation of different mouse olfactory subsystems, including the main olfactory epithelium, the vomeronasal organ, and the Grueneberg ganglion. This approach enabled us to observe odorant-induced neuronal activity within the different olfactory subsystems and to demonstrate the impact of environmental conditioning, such as temperature variations, on olfactory sensitivity, specifically in the Grueneberg ganglion. We further applied our rpS6-based assay to the human olfactory system and demonstrated its feasibility. Our findings show that analyzing rpS6 signal intensity is a robust and highly reproducible indicator of neuronal activity across various olfactory systems, while avoiding stress and some experimental limitations associated with in vivo exposure. The potential extension of this assay to other conditioning paradigms and olfactory systems, as well as its application to other animal species, including human olfactory diagnostics, is also discussed.
Dictamnus dasycarpus Turcz. Root Bark Improves Skin Barrier Function and Symptoms of Atopic Dermatitis in Mice
Authors: Park Sangjun , Yang Jinkyu , Sun Kyoungmin , Park Seonah , Lee Jimi , Kim Soyeon , Lyu Ji Hyo , Kim Hyungwoo
Published: December 2024

The root bark of Dictamus dasycarpus Turcz. has been traditionally used for the topical treatment of skin disorders like pruritus. This study was designed to investigate the inflammatory and skin barrier protective effects of D. dasycarpus in mice with calcipotriol (MC903)-induced atopic dermatitis (AD). Topical skin lesions on male Balb/c mice (8 weeks old) were treated topically with an ethanolic extract of D. dasycarpus (EEDD), and skin water content, water holding capacity (WHC), histopathological abnormalities, and inflammatory cytokine and chemokine levels were investigated. Topical application of EEDD effectively alleviated skin lesion severity, improved skin water content and WHC, and ameliorated histopathological abnormalities, including hyperkeratosis, blood vessel numbers near the epidermis, spongiotic changes, and immune cell infiltration in skin tissues. EEDD also suppressed inflammatory cytokines and chemokines, such as tumor necrosis factor (TNF)-α, thymic stromal lymphopoietin (TSLP), interleukin (IL)-1β, IL-4, IL-8, and monocyte chemotactic protein (MCP)-1. In RAW264.7 cells, EEDD reduced nuclear factor kappa-light-chain-enhancer of activated B cells (NF-kB) expression and suppressed the phosphorylations of extracellular signal-regulated kinase (ERK) and p38. These results suggest that the root bark of D. dasycarpus has therapeutic potential due to its anti-dermatitis and skin barrier protective effects in AD and that it could be used as an ingredient in skincare products.
Antimicrobial Mixture Based on Micronized Kaolinite and Ziziphora Essential Oil as a Promising Formulation for the Management of Infected Wounds
Authors: Karaubayeva Aigerim A. , Bekezhanova Tolkyn , Zhaparkulova Karlygash , Susniak Katarzyna , Sobczynski Jan , Kazimierczak Paulina , Przekora Agata , Skalicka-Wozniak Krystyna , Kulinowski Łukasz , Glowniak-Lipa Anna , Sakipova Zuryiadda B. , Korona-Głowniak Izabela
Published: December 2024

Kaolinite stands out as a promising natural geomaterial for developing new therapeutic systems aimed at addressing global health challenges, such as multidrug-resistant infections. In this study, we report on the formulation and biological activity of a therapeutic mixture composed of white micronized kaolinite (KAO) and Ziziphora essential oil (ZEO), intended for topical application on infected wounds. GC–MS analysis revealed that the primary component of ZEO is pulegone, constituting 72.98% of the oil. ZEO demonstrated good bioactivity against bacterial and fungal strains (MIC 1.25–5 mg/mL). Additionally, ZEO at a concentration of 0.0156% (0.156 mg/mL) was found to significantly stimulate collagen synthesis. The antimicrobial activity of the tested KAO–ZEO mixture formulation (30% KAO/0.25% ZEO in an excipient base) showed the highest effectiveness against Candida spp. (MIC 0.08–25 mg/mL) and Gram-positive bacteria (MIC 0.16–25 mg/mL), with lower activity against Gram-negative bacteria (MIC 25–50 mg/mL). Moreover, the KAO–ZEO mixture was nontoxic (cell viability near 100%) to human skin fibroblasts according to the ISO 10993-5 standard and promoted collagen synthesis by skin cells. This is the first documented formulation combining KAO and ZEO, demonstrating significant antimicrobial properties along with the ability to stimulate collagen production in fibroblasts. These properties highlight KAO–ZEO as a promising novel treatment, which may synergize with current care standards and improve wound healing outcomes.
StUBC13, a Ubiquitin-Conjugating Enzyme, Positively Regulates Salt and Osmotic Stresses in Potato
Authors: Fu Xue , Tang Xun , Zhang Ning , Si Huaijun
Published: December 2024

Protein ubiquitination is an important regulatory mechanism for biological growth and development against environmental influences, and can affect several biological processes, including the growth, development, and stress responses of plants. However, the function of potato-related ubiquitin-conjugating enzymes in abiotic stress tolerance is poorly understood. In this study, a StUBC13 with a UBC conserved structural domain was identified in potato and its function was investigated under osmotic stress and salt stress conditions. The observation of plant phenotypes under stress conditions revealed that overexpressed plants grew better than wild-type plants. In line with the above results, the determination of stress-related physiological indices revealed that the overexpression transgenic plants had better stress tolerance and stronger adaptation to environmental stress, and the transgenic plants were found to tolerate better drought and salt stress by decreasing their malondialdehyde (MDA) content and increasing their superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) contents under stress conditions. Based on these results, StUBC13 has an important regulatory role in the response of plants to abiotic stresses (osmotic stress and salt stress), and overexpression of this gene can improve the tolerance of potatoes to osmotic and salt stresses.
Biochip-Based Identification of Mycobacterial Species in Russia
Authors: Zimenkov Danila , Zhuravlev Vyacheslav , Ushtanit Anastasia , Filippova Marina , Semenova Uliana , Solovieva Natalia , Sviridenko Maria , Khakhalina Anastasia , Safonova Svetlana , Makarova Marina , Gordeeva Elizaveta , Guselnikova Elena , Schwartz Yakov , Stavitskaya Natalia , Yablonsky Peter
Published: December 2024

Infections caused by nontuberculous mycobacteria (NTM) are rising globally throughout the world. The number of species isolated from clinical samples is steadily growing, which demands the implementation of a robust diagnostic method with wide specificity. This study was carried out in in 2022–2024 in three clinical antituberculosis centers in the biggest cities of Russia: Moscow, Saint Petersburg, and Novosibirsk. We developed the DNA hybridization assay ‘Myco-biochip’ that allows the identification of 79 mycobacterial species and analyzed 3119 samples from 2221 patients. Sixty-eight mycobacterial species were identified in clinics, including the three novel species phylogenetically related to M. duvalii, M. lentiflavum, and M. talmoniae. The identification of a close relative of M. talmoniae adds to the existence of separate clade between M. terrae, M. triviale complexes and other slow-growing Mycobacteria, which supports the thesis against the splitting of Mycobacteria into five separate genera. Adding to the list of potentially pathogenic species, we identified M. adipatum and M. terramassiliense, which were previously described as natural habitats. The diversity of acid-fast bacilli identified in TB-suspected persons was not limited to the Mycobacteria genus and also includes species from genera Nocardia, Gordonia, Corynebacterium, Tsukamurella, and Rhodococcus of the order Mycobacteriales. The revealed bacterial diversity in patients with suspected NTM-diseases requires the implementation of relevant species identification assays as the first step in the laboratory diagnostic pipeline.
Valorization of Hom Thong Banana Peel (Musa sp., AAA Group) as an Anti-Melanogenic Agent Through Inhibition of Pigmentary Genes and Molecular Docking Study
Authors: Linsaenkart Pichchapa , Yooin Wipawadee , Jiranusornkul Supat , Sringarm Korawan , Arjin Chaiwat , Rachtanapun Pornchai , Jantanasakulwong Kittisak , Castagnini Juan M. , Ruksiriwanich Warintorn
Published: December 2024

Prolonged and unprotected exposure to the environment explicitly influences the development of hyperpigmented lesions. The enzyme tyrosinase (TYR) is a key target for regulating melanin synthesis. Several bioactive compounds derived from plant extracts have been found to possess potent anti-melanogenesis properties against TYR. In particular, the potential of banana peels from various varieties has garnered interest due to their application in skin hyperpigmentation treatment. A molecular docking study demonstrated interactions between rosmarinic acid, which is predominantly found in all Hom Thong peel extracts, and the active site of TYR (PDB ID: 2Y9X) at residues HIS263, VAL283, SER282, and MET280, with the lowest binding energy of −5.05 kcal/mol, showing the strongest interaction. Additionally, Hom Thong banana peels are rich in phenolic compounds that could inhibit melanin content and tyrosinase activity in both human and mouse melanoma cells. These effects may be attributed to the suppression of gene expression related to melanogenesis, including the regulator gene MITF and pigmentary genes TYR, TRP-1, and DCT, indicating effects comparable to those of the standard treatment groups with arbutin and kojic acid. Our findings indicated the potential of Hom Thong peel extracts as anti-melanogenic agents.
Microbiome-Based Therapeutics for Insomnia
Authors: Li Chenyu , Chen Sizhe , Wang Yun , Su Qi
Published: December 2024

Insomnia poses considerable risks to both physical and mental health, leading to cognitive impairment, weakened immune function, metabolic dysfunction, cardiovascular issues, and reduced quality of life. Given the significant global increase in insomnia and the growing scientific evidence connecting gut microbiota to this disorder, targeting gut microbiota as an intervention for insomnia has gained popularity. In this review, we summarize current microbiome-based therapeutics for insomnia, including dietary modifications; probiotic, prebiotic, postbiotic, and synbiotic interventions; and fecal microbiota transplantation. Moreover, we assess the capabilities and weaknesses of these technologies to offer valuable insights for future studies.
The Emerging Role of p21 in Diabetes and Related Metabolic Disorders
Authors: Elmitwalli Omar , Darwish Radwan , Al-Jabery Lana , Algahiny Ahmed , Roy Sornali , Butler Alexandra E. , Hasan Ammar S.
Published: December 2024

In the context of cell cycle inhibition, anti-proliferation, and the dysregulation observed in certain cancer pathologies, the protein p21 assumes a pivotal role. p21 links DNA damage responses to cellular processes such as apoptosis, senescence, and cell cycle arrest, primarily functioning as a regulator of the cell cycle. However, accumulating empirical evidence suggests that p21 is both directly and indirectly linked to a number of different metabolic processes. Intriguingly, recent investigations indicate that p21 significantly contributes to the pathogenesis of diabetes. In this review, we present a comprehensive evaluation of the scientific literature regarding the involvement of p21 in metabolic processes, diabetes etiology, pancreatic function, glucose homeostasis, and insulin resistance. Furthermore, we provide an encapsulated overview of therapies that target p21 to alleviate metabolic disorders. A deeper understanding of the complex interrelationship between p21 and diabetes holds promise for informing current and future therapeutic strategies to address this rapidly escalating health crisis.
Mitigation of Atherosclerotic Vascular Damage and Cognitive Improvement Through Mesenchymal Stem Cells in an Alzheimer’s Disease Mouse Model
Authors: Lee Woong Jin , Cho Kyoung Joo , Kim Gyung Whan
Published: December 2024

Alzheimer’s disease (AD) is a neurodegenerative condition characterized by progressive memory loss and other cognitive disturbances. Patients with AD can be vulnerable to vascular damage, and damaged vessels can lead to cognitive impairment. Mesenchymal stem cell (MSC) treatment has shown potential in ameliorating AD pathogenesis, but its effect on vascular function remains unclear. This study aimed to improve cognitive function by alleviating atherosclerosis-induced vessel damage using MSCs in mice with a genetic AD background. In this study, a 5xFAD mouse model of AD was used, and atherosclerotic vessel damage was induced by high-fat diets (HFDs). MSCs were injected into the tail vein along with mannitol in 5xFAD mice on an HFD. MSCs were detected in the brain, and vascular damage was improved following MSC treatment. Behavioral tests showed that MSCs enhanced cognitive function, as measured by the Y-maze and passive avoidance tests. Additionally, muscle strength measured by the rotarod test was also increased by MSCs in AD mice with vessel damage induced by HFDs. Overall, our results suggest that stem cells can alleviate vascular damage caused by metabolic diseases, including HFDs, and vascular disease in individuals carrying the AD gene. Consequently, this alleviates cognitive decline related to vascular dementia symptoms.
Modulating Amyloid-β Toxicity: In Vitro Analysis of Aβ42(G37V) Variant Impact on Aβ42 Aggregation and Cytotoxicity
Authors: Huang Shu-Hsiang , Fang Shang-Ting , Yang Chin-Hao , Liou Je-Wen , Chen Yi-Cheng
Published: December 2024

Alzheimer’s disease (AD) is primarily driven by the formation of toxic amyloid-β (Aβ) aggregates, with Aβ42 being a pivotal contributor to disease pathology. This study investigates a novel agent to mitigate Aβ42-induced toxicity by co-assembling Aβ42 with its G37V variant (Aβ42(G37V)), where Gly at position 37 is substituted with valine. Using a combination of Thioflavin-T (Th-T) fluorescence assays, Western blot analysis, atomic force microscopy (AFM)/transmission electron microscopy (TEM), and biochemical assays, we demonstrated that adding Aβ42(G37V) significantly accelerates Aβ42 aggregation rate and mass while altering the morphology of the resulting aggregates. Consequently, adding Aβ42(G37V) reduces the Aβ42 aggregates-induced cytotoxicity, as evidenced by improved cell viability assays. The possible mechanism for this effect is that adding Aβ42(G37V) reduces the production of reactive oxygen species (ROS) and lipid peroxidation, typically elevated in response to Aβ42, indicating its protective effects against oxidative stress. These findings suggest that Aβ42(G37V) could be a promising candidate for modulating Aβ42 aggregation dynamics and reducing its neurotoxic effects, providing a new avenue for potential therapeutic interventions in AD.
Fabrication of Porous MXene/Cellulose Nanofibers Composite Membrane for Maximum Osmotic Energy Harvesting
Authors: Wang Sha , Sun Zhe , Ahmad Mehraj , Miao Mengyu
Published: December 2024

Two-dimensional (2D) nanofluidic channels are emerging as potential candidates for harnessing osmotic energy from salinity gradients. However, conventional 2D nanofluidic membranes suffer from high transport resistance and low ion selectivity, leading to inefficient transport dynamics and limiting energy conversion performance. In this study, we present a novel composite membrane consisting of porous MXene (PMXene) nanosheets featuring etched nanopores, in conjunction with cellulose nanofibers (CNF), yielding enhancement in ion flux and ion selectivity. A mild H2O2 oxidant is employed to etch and perforate the MXene sheets to create a robust network of cation transportation nanochannels that effectively reduces the energy barrier for cation transport. Additionally, CNF with a unique nanosize and high charge density further enhances the charge density and mechanical stability of the nanofluidic system. Under neutral pH and room temperature, the PMXene/CNF membrane demonstrates a maximum output power density of 0.95 W·m−2 at a 50-fold KCl gradient. Notably, this represents a 43% improvement over the performance of the pristine MXene/CNF membrane. Moreover, 36 nanofluidic devices connected in series are demonstrated to achieve a stable voltage output of 5.27 V and power a calculator successfully. This work holds great promise for achieving sustainable energy harvesting with efficient osmotic energy conversion utilization.
The In Vitro Cytotoxic Potential of Biosynthesized Silver Nanoparticles in MIA PaCa-2 Cells Supported with an In Silico Study
Authors: González-Garibay Angélica Sofía , Vallejo-Cardona Alba Adriana , Villarreal-Amézquita Ariadna Abigail , Sánchez-Hernández Iván Moisés , Torres-González Omar Ricardo , Padilla-Camberos Eduardo
Published: December 2024

Pancreatic cancer affects many people and is quite aggressive. Metallic nanoparticles may be an alternative treatment for this disease. In this work, the antiproliferative activity of biosynthesized silver nanoparticles was evaluated. Stenocereus queretaroensis peel extract was used as a reducing agent for nanoparticle synthesis; the characterization was carried out using spectroscopic techniques, X-ray diffraction, and microscopy. The antiproliferative effect was evaluated in the MIA PaCa-2 pancreatic tumoral cell line, and a molecular docking test was run with the STAT3 protein. The results obtained show that it was possible to synthesize silver nanoparticles from the plant extract, which was confirmed through characterization studies. The average size of the nanoparticles was measured to be 48.8 nm, and they predominantly exhibited a spherical shape. The antiproliferative effect was demonstrated in the pancreatic cell line, with an IC50 value of 15.66 µg/mL. The molecular docking analysis predicted a strong interaction with the STAT3 protein, with a binding energy value of −6.47 obtained. With these results, it is concluded that biosynthesized silver nanoparticles inhibit pancreatic tumor cell growth and may represent an innovative cancer treatment.
Synthesis and Characterization of Thermosensitive Nanosupports with Core–Shell Structure (PSt-PNIPAM) and Their Application with Silver Nanoparticles
Authors: Palos Zúñiga Ana , Facundo Arzola Isabel , Rosales Sosa Ma. , Rangel Hernández Yadira , Reyes Guzmán Claudia , García Yregoi Manuel , Muñoz Ramirez Leonor , Saade Caballero Hened
Published: December 2024

The present study synthesized silver nanoparticles supported on a thermosensitive polymer with a core–shell structure, formed by a polystyrene (PS) core and a poly(N-isopropylacrylamide) (PNIPAM)/Poly(N, N-methylenebisacrylamide) (MBA) shell. The PS core was synthesized via semicontinuous heterophase polymerization at a flow of 0.073 g/min, enabling polystyrene nanoparticles with an average size (Dz) of 35.2 nm to be obtained. In the next stage, the conditions required for polymerization synthesis were established in seeded microemulsion using PS nanoparticles as seed and semicontinuously adding the thermosensitive shell monomer (PNIPAM/MBA) under monomer-flooded conditions to favor shell formation. The non-homopolymerization of PNIPAM/MBA was demonstrated by obtaining nanoparticles with a core–shell structure, with average particle sizes of 41 nm and extremely low and narrow polydispersity index (PDI) values (1.1). The thermosensitive behavior was analyzed by QLS, revealing an average shrinkage of 4.03 nm and a percentage of shrinkage of 23.7%. Finally, silver nanoparticles were synthesized on the core–shell heat-sensitive nanoparticles in a colloidal solution containing the latices, while silver nanoparticles were anchored onto the cross-linked heat-sensitive network via the formation of complexes between the Ag+ ions and the nitrogen contained in the PNIPAM/MBA network, favoring anchorage around the network and maintaining a size of 5 nm.
Impact of Moisture Absorption on Optical Fiber Sensors: New Bragg Law Formulation for Monitoring Composite Structures
Authors: Aceti Pietro , Sala Giuseppe
Published: December 2024

In recent decades, the aviation industry has increasingly adopted composite materials for various aircraft components, due to their high strength-to-weight ratio and durability. To ensure the safety and reliability of these structures, Health and Usage Monitoring Systems (HUMSs) based on fiber optics (FO), particularly Fiber Bragg Grating (FBG) sensors, have been developed. However, both composite materials and optical fibers are susceptible to environmental factors such as moisture, in addition to the well-known effects of mechanical stress and thermal loads. Moisture absorption can lead to the degradation of mechanical properties, posing a risk to the structural integrity of aircraft components. This research aims to quantify and monitor the impact of moisture on composite materials. A new formulation of the Bragg equation is introduced, incorporating mechanical strain, thermal expansion, and hygroscopic swelling to accurately measure Bragg wavelength variations. Experimental validation was performed using both uncoated and polyimide-coated optical fibers subjected to controlled hygrothermal conditions in a climate chamber. The results demonstrate that uncoated fibers are insensitive to humidity, whereas coated fibers exhibit measurable wavelength shifts due to moisture absorption. The proposed model effectively predicts these shifts, with errors consistently below 2.6%. This approach is crucial for improving the performance and reliability of HUMSs in monitoring composite structures, ensuring long-term safety in extreme environmental conditions.
A Minimal-Data Approach for Film Thickness Prediction in Tribological Contacts Using Venner’s Equation
Authors: Müller Felix , Wingertszahn Patrick , Koch Oliver , Sauer Bernd
Published: December 2024

The accurate design of tribological contacts, such as those in bearings and gearboxes, makes them highly efficient and helps reduce emission in all driven systems. Traditionally, this process requires more lubricant data than data sheets typically provide, mainly kinematic viscosity at 40 °C and 100 °C and density, which limits the design process. This study introduces a simplified methodology for determining lubricant film thickness, one of the main design critical parameters, using minimal viscosity measurements obtained with a high-pressure viscometer. The researchers demonstrate that essential lubricant parameters can be derived effectively from a few measurements. By combining state-of-the-art models for film thickness with practical measurements from an EHL tribometer, this study confirms that reliable film thickness predictions can be made from basic viscosity data. This approach streamlines the design process, making tribological simulations more accessible and cost-effective, and enhances the design of tribological contacts under extreme conditions.
Cryo-Rolled AA5052 Alloy: Insights into Mechanical Properties, Formability, and Microstructure
Authors: Achuthankutty Arun , Saravanan Rohith , Nagarajan Hariesh , Pasunuri Vidyanand , Gopal Nishanth Hari , Ramesh Ajith , Arangot Sumesh , Thekkuden Dinu Thomas
Published: December 2024

Industries operating in extreme conditions demand materials with exceptional strength, fatigue resistance, corrosion resistance, and formability. While AA5052 alloy is widely used in such industries due to its high fatigue strength and corrosion resistance, its strength frequently falls short of stringent standards. For AA5052 alloy, this study explores the combined use of solutionizing and cryo-rolling, followed by annealing, to improve strength. Although several alloys have been reported to undergo solution treatment before cryo-rolling, this study focuses on how post-processing via annealing can lessen the formability constraints usually connected to conventional cryo-rolling. The study sheds light on the ways that solutionizing, cryo-rolling, and annealing interact to affect the alloy’s mechanical characteristics. Microstructure analysis shows that solutionizing improves the grain structure by reducing dynamic recovery, promoting dislocation density, and facilitating precipitate formation. Sheets subjected to solutionizing + cryo-rolling and partially annealed at 250 °C produce optimal results. Interestingly, formability is decreased when cryo-rolling alone is used instead of cold rolling, whereas formability is successfully increased when solutionizing is used. Comparing solutionized + cryo-rolled sheets that are partially annealed at 250 °C to cold-rolled sheets that are annealed at the same temperature, the former show notable quantitative improvements: a notable 17% increase in ultimate strength, a 10% boost in yield strength, and a noteworthy 13% enhancement in microhardness. Formability has improved with the solutionized + cryo-rolled specimens by annealing. This proposed approach led to noticeable gains in formability, hardness, and strength, which would significantly improve material performance for industrial applications.
An Integrated Modeling Framework for Automated Product Design, Topology Optimization, and Mechanical Simulation
Authors: Charalampous Paschalis , Pelekoudas Athanasios , Kostavelis Ioannis , Ioannidis Dimosthenis , Tzovaras Dimitrios
Published: December 2024

The present study introduces an integrated software approach that provides an automated product design toolkit for customized products like knives, incorporating topology optimization (TO) and numerical simulations in order to streamline engineering workflows during the product development procedure. The modeling framework combines state-of-the-art technologies into a single platform, enabling the design and the optimization of mechanical structures with minimal human intervention. In particular, the proposed solution leverages artificial intelligence (AI), shape optimization methods, and computational tools in order to iteratively optimize material utilization as well as the design of products based on certain criteria. By embedding simulation within the design optimization loop, the developed software module ensures that performance constraints are respected throughout the design process. The case studies are concentrated in designing knives, demonstrating the platform’s ability to reduce design time, enhance product performance and provide rapid iterations of structurally optimized geometries. Finally, it should be noted that this research showcases the potential of integrated modeling technologies towards the transformation of traditional design paradigms, in this way contributing to faster, more reliable and efficient product development in various engineering industries through the training and deployment of AI models in these scientific fields.
Two-Dimensional Numerical Method for Predicting the Resistance of Ships in Pack Ice: Development and Validation
Authors: Huang Yan , Sun Ce , Sun Jianqiao
Published: December 2024

This study presents a 2D numerical simulation method for predicting the resistance of ships navigating in pack ice. The key contribution of this study lies in the derivation of analytical closed-form solutions for calculating the flexural deformation and stress distribution in an elastic plate using Symplectic Mechanics and Hooke’s laws. These solutions are used to determine the failure mode of ice floes. Linear Elastic Fracture Mechanics (LEFMs) and the weight function method are utilized to analyze crack initiation, propagation, and fracture. Ice is broken when a crack propagates to 14.5% of the ice length. The compressive strength of ice and the contact area are used to calculate the ice load. A collision method was developed based on the Sweep and Prune (SAP) and Gilbert–Johnson–Keerthi (GJK) algorithms. A program for predicting the resistance of ships navigating in pack ice was developed based on MATLAB and the aforementioned theories. The navigation resistance of RV Xuelong at different ice concentrations and speeds was simulated and compared with the model test results from an ice tank. The comparison shows that the simulation results are consistent with the test results, with an average error of 9.05%, indicating the effectiveness and reliability of this numerical method. This study lays a solid foundation for future research on autonomous ship navigation in pack ice.
Comparison of Collision Avoidance Algorithms for Unmanned Surface Vehicle Through Free-Running Test: Collision Risk Index, Artificial Potential Field, and Safety Zone
Authors: Kim Jung-Hyeon , Jo Hyun-Jae , Kim Su-Rim , Choi Si-Woong , Park Jong-Yong , Kim Nakwan
Published: December 2024

This paper details the development of a collision avoidance algorithm for unmanned surface vehicles (USVs) and its validation using free-running tests. The USV, designed as a catamaran, incorporates a variety of sensors for its guidance, navigation, and control system. It performs turning maneuvers using thrusters positioned on the port and starboard sides. The robot operating system is used to streamline communication, transmitting data such as position, orientation, and situational information from diverse sensors. Using the collision risk index (CRI) method, the algorithm calculates risk based on the distance to obstacles and the angle to the desired waypoint, directing the USV on a path with minimized risk. Noise within the data captured by the two-dimensional light detection and ranging system is filtered out using the k-dimensional tree and Euclidean distance methods, ensuring single obstacles are distinctly identified. To assess the efficacy of the CRI-based collision avoidance algorithm, it was benchmarked against other algorithms rooted in the artificial potential field and safety zone methods within an artificial tank setting. The results highlight the CRI method’s superior time efficiency and optimality in comparison to its counterparts.
Evaluation and Structural Optimisation of 0.6 m Impulse Turbine in Dolphin Wave Energy Conversion Device Through Computational Fluid Dynamics and Generative Design
Authors: Szatkowski Szymon , Gonzalez Delgado Daniel , Jaen-Sola Pablo , Oterkus Erkan
Published: December 2024

In this paper, the performance of an adapted design of a 0.6 m impulse turbine in a new wave energy conversion device—the Dolphin device—is evaluated. This study is focused on developing an optimised structure in order to maximise the potential of the device and provide a lightweight and robust novel design. For this purpose, initial studies on the system involved 2D CFD simulations combined with parametric optimisation, which validated the use of the turbine system with water as the working fluid. The obtained component geometries were then used for the creation of a 3D CFD model, which was tested in a set-up dynamic simulation environment. Subsequently, the performance of the system was evaluated through the use of referenced experimental analyses. By taking into account the loading conditions present at the blades, as well as the inherent typical loads caused by the rotational speed of the turbine, the system was then optimised using generative design processes. Through the applied methodology, the performance of the turbine was predicted to be 61.79%. Moreover, the generative design optimisation showed a reduction in mass of 60.226% for the blade structure and 69.523% for the rotor structure.
Effective Stress-Based Numerical Method for Predicting Large-Diameter Monopile Response to Various Lateral Cyclic Loadings
Authors: Lei Jichao , Leng Kehua , Xu Wei , Wang Lixian , Hu Yu , Liu Zhen
Published: December 2024

Extreme marine environmental cyclic loading significantly affects the serviceability of monopiles applied for the foundation of offshore wind turbines (OWTs). Existing research has primarily used p-y methods or total stress-based models to investigate the behavior of monopile–marine clay systems, overlooking the pore pressure development in subsea clay. Studies on the effective stress-based behavior of clay under various lateral cyclic loading conditions are limited. This paper presents an effective stress-based 3D finite element numerical method developed to predict key behaviors of pile–clay systems, including permanent pile rotation under cyclic loading, pile bending moment, and the evolution of pore pressure in subsea clay. The model is verified by contrasting the simulations results to centrifuge experimental results. Cyclic lateral loading is divided into average cyclic load and amplitude of cyclic load to investigate their impacts on the pile–clay system response. The research findings offer insights for the design of large-diameter monopiles under complex cyclic loading conditions.
Biocontrol Potential of Endophytic Bacillus velezensis LSR7 Against Rubber Red Root Rot Disease
Authors: Meng Xiangjia , Cai Haibin , Luo Youhong , Zhao Xinyang , Fu Yongwei , Zou Lifang , Zhou Yi , Tu Min
Published: December 2024

To obtain an effective bacterial biocontrol strain against the fungal pathogen Ganoderma pseudoferreum, causing rubber tree red root rot disease, healthy rubber tree tissue from Baisha County, Hainan Province, was selected as the isolation source, and bacterial strains with strong antifungal effects against G. pseudoferreum were screened. The strain was identified by molecular biology, in vitro root segment tests, pot growth promotion tests, and genome detection. The strain was further evaluated by biological function tests, genome annotation analysis, and plant defense-related enzyme activity detection. The results show that strain LSR7 had good antagonistic effects against G. pseudoferreum, and the inhibition rate reached 88.49%. The strain LSR7 was identified as Bacillus velezensis by genome sequencing. In a greenhouse environment, LSR7 prevents and treats red root rot disease in rubber trees and promotes the growth of rubber tree seedlings. LSR7 secreted cell wall hydrolases (protease, glucanase, and cellulase), amylases, and siderophores. LSR7 also formed biofilms, facilitating plant colonization. Genome prediction showed that LSR7 secreted multiple antifungal lipopeptides. LSR7 enhanced rubber tree resistance to G. pseudoferreum by increasing the activity of defense enzymes. Bacillus velezensis LSR7 has biocontrol potential and is a candidate strain for controlling red root rot disease in rubber trees.
Multi-Objective Urban Green Space Optimization of Wetland Cities Based on the Carbon Balance: A Case Study in Wuhan
Authors: Liu Xu , Zhou Zhixiang
Published: December 2024

Urban areas are significant centers of human activity and are recognized as major contributors to global carbon emissions. The establishment of urban green spaces plays a crucial role in enhancing carbon sinks and mitigating carbon emissions, thereby fostering a low-carbon cycle within cities. However, the existing literature on the carbon sequestration of green spaces in Chinese cities often overlooks the role of water bodies, which are a significant characteristic of wetland cities. Therefore, it is necessary to investigate the carbon sequestration potential of green spaces in wetland cities, taking into account the contribution of water bodies to carbon sinks. This study aims to analyze the quantitative structure of urban green spaces through the lens of carbon balance, which can effectively enhance a city’s overall carbon sequestration capacity. Utilizing carbon balance theory, this research first assesses the carbon offsetting capability (COC) of urban green spaces in Wuhan for the year 2019. It then forecasts future carbon emissions, sets improvement targets for COC, and calculates the required area of standard green space to achieve these targets by 2030. A multi-objective programming (MOP) model is developed to identify the optimal solution that aligns with urban development planning constraints while maximizing carbon sinks. Lastly, we analyzed the contribution rates of different types of urban green spaces to the total carbon sequestration capacity of green spaces to clarify the characteristics of carbon absorption in green spaces of Wuhan, a wetland city. The findings indicate the following: (1) In 2019, Wuhan’s carbon emissions from human activities reached approximately 38.20 Mt, with urban green spaces absorbing around 5.62 Mt of carbon, and a COC of about 14.71%. (2) Projections for 2030 suggest that carbon emissions in Wuhan will rise to approximately 42.64 Mt. Depending on the targeted COC improvement rates of 5%, 10%, 15%, 20%, and 25%, the required values of carbon sequestration will be 6.59 Mt, 6.90 Mt, 7.21 Mt, 7.53 Mt and 7.84 Mt, respectively. (3) The results of the MOP model indicate that the optimal COC for 2030 is projected to be 16.33%, which necessitates a carbon sequestration of 6.97 Mt. (4) Water bodies accounted for 56.23% of the total carbon absorption in green spaces in 2019 and are projected to represent 45.37% in 2030, highlighting the distinctive characteristics of Wuhan as a wetland city in terms of its green space carbon sequestrations. The management and enhancement of water body carbon sequestration capacity is crucial for the carbon sequestration potential of urban green space in Wuhan. The results of this study can provide evidence and recommendations for the low-carbon development patterns of wetland cities across China.
Landscape Composition and Crop Border Vegetation Diversity Effect on Pollinators, Auxiliary Fauna, and Phytophagous Arthropods of Leguminous Cropland in Araba (Basque Country)
Authors: Urkijo Ainhoa , Ametzaga-Arregi Ibone , Elkano Eneko , Albizu Isabel
Published: December 2024

Many strategies and directives are starting to address the importance of an appropriate landscape for agricultural biodiversity, such as pollinators and auxiliary fauna. Therefore, it is necessary to identify which landscape features are more important for agricultural biodiversity conservation and the ecosystem services they offer, like pollination and pest control. Thus, the main objective of this study was to assess the effect of landscape composition, configuration, connectivity, and crop border vegetation on arthropod diversity. The arthropod community was sampled in eight legume crops located across a gradient of landscape complexity. Additionally, the border vegetation of each plot was characterized, and the surrounding landscape was analyzed at a small and a large scale. For the statistical analysis, Generalized Linear Mix Models and redundancy analyses were applied. Pollinators were positively affected mainly by landscape connectivity. Pest control agents were less influenced by the landscape and only before harvest were they positively affected by riparian forests. Finally, phytophagous arthropod richness increased with border vegetation diversity and cropland in the surroundings. In conclusion, in the leguminous crops of Araba landscape connectivity together with cropland extension in the surroundings should be considered to promote ES-offering fauna diversity.
Performance and Emission Characteristics of a Small Gas Turbine Engine Using Hexanol as a Biomass-Derived Fuel
Authors: Suchocki Tomasz
Published: December 2024

The global transition to renewable energy has amplified the need for sustainable aviation fuels. This study investigates hexanol, a biomass-derived alcohol, as an alternative fuel for small-scale gas turbines. Experimental trials were conducted on a JETPOL GTM-160 turbine, assessing blends of 25% (He25) and 50% (He50) hexanol with kerosene (JET A) under rotational velocities ranging from 40,000 to 110,000 RPM. The parameters measured included thrust-specific fuel consumption (TSFC), turbine inlet and outlet velocities, and the emission indices of NOx and CO. The results demonstrated that the He25 and He50 blends achieved comparable thermal efficiency to pure JET A at high rotational velocities, despite requiring higher fuel flows due to hexanol’s lower heating value. CO emissions decreased significantly at higher velocities, reflecting improved combustion efficiency with hexanol blends, while NOx emissions exhibited a slight increase, attributed to the oxygen content of the fuel. This study contributes a novel analysis of hexanol-kerosene blends in gas turbines, offering insights into their operational and emission characteristics. These findings underscore hexanol’s potential as an environmentally friendly alternative fuel, aligning with global efforts to reduce fossil fuel dependency and carbon emissions.
Preparation of Alumina Oxo-Cluster/Cellulose Polymers and Dye Adsorption Application
Authors: Tang Henglong , Yao Simeng , Long Zhu , Yang Xuefei , Si Pengxiang , Sun Chang , Zhang Dan
Published: December 2024

Aluminum oxide clusters (AlOCs) possess high surface areas and customizable pore structures, making them applicable in the field of environmental remediation. However, their practical use is hindered by stability issues, aggregation tendencies, and recycling challenges. This study presents an in -situ synthesis of AlOCs on cellulose using a solvent thermal method. The resulting adsorbent’s structural and property profiles were thoroughly characterized using multiple analytical techniques. Batch adsorption experiments were performed to assess the adsorbent’s capacity and kinetics in removing selected dyes from aqueous solutions. Additionally, both real-environment simulation and regeneration experiments have been conducted to thoroughly assess the adsorbent’s reliability, stability, and practical applicability. The aim was to engineer an effective and recyclable adsorbent specifically tailored for dye-contaminated wastewater treatment.
A Hybrid Deep Learning Approach for Enhanced Sentiment Classification and Consistency Analysis in Customer Reviews
Authors: Sorour Shaymaa E. , Alojail Abdulrahman , El-Shora Amr , Amin Ahmed E. , Abohany Amr A.
Published: December 2024

Consumer reviews play a pivotal role in shaping purchasing decisions and influencing the reputation of businesses in today’s digital economy. This paper presents a novel hybrid deep learning model, WDE-CNN-LSTM, designed to enhance the sentiment classification of consumer reviews. The model leverages the strengths of Word Embeddings (WDE), Long Short-Term Memory (LSTM) networks, and Convolutional Neural Networks (CNNs) to capture temporal and local text data features. Extensive experiments were conducted across binary, three-class, and five-class classification tasks, with the proposed model achieving an accuracy of 98% for binary classification, 98% for three-class classification, and 95.21% for five-class classifications. The WDE-CNN-LSTM model consistently outperformed standalone CNN, LSTM, and WDE-LSTM models regarding precision, recall, and F1-score, achieving up to 98.26% in F1-score for three-class classification. The consistency analysis also revealed a high alignment between the predicted sentiment and customer ratings, with a consistency rate of 96.00%. These results demonstrate the efficacy of this hybrid architecture in handling complex sentiment classification tasks (SCTs), offering significant improvements in accuracy, classification metrics, and sentiment consistency. The findings have important implications for improving sentiment analysis in customer review systems, contributing to more reliable and accurate sentiment classification.