bluuebunny/crossref_metadata_2025 huggingface dataset:
Suggestions and Applications for Evaluating Seismic Functionality for Railway Infrastructure Network Based on Fragility Curve
Authors: Yoo Mintaek , Jeon Jiyun , Kim Seokjung , Haam Sunnie
Published: January 2025

This study proposes a novel model to quantitatively evaluate functionality loss in railway network systems during earthquakes and assesses its applicability to a hypothetical railway network system. The model combines seismic fragility functions and restoration curves to assess functionality loss, deriving a time-dependent recovery function to propose a functionality loss model based on earthquake magnitude. The proposed model uses a hypothetical railway network to calculate the overall functionality loss of the network under various earthquake scenarios. The hypothetical railway network was designed with three lines, allowing different routes to remain operational depending on the damaged sections and increasing the diversity of network impact scenarios based on the functionality loss. This model provides a framework for analyzing the functionality loss and recovery processes of railway networks during seismic events and assessing the socioeconomic impacts of earthquakes.
Analysis of Volatile Compounds in a Value-Added Jerky by Incorporating Ajwain and Thyme Essential Oils
Authors: Anit Elaine , Hernández Helga , Banout Jan , Urbanová Klára
Published: January 2025

Ajwain essential oil and thyme essential oil naturally contain important bioactive compounds. Various researchers have discovered that these compounds contribute biological benefits for living things such as humans and animals. Bioactive compounds found in essential oils, such as terpenes and terpenoids, possess antibacterial and flavouring qualities, making them promising natural preservatives in the food business. This study investigates the effect of essential oil treatment methods on their incorporation into dehydrated beef and its subsequent sensory acceptability. The meat samples underwent hot air blanching and oil treatment with doses of 0.75 mL and 1.5 mL, respectively. Subsequently, the samples were dried at 55 °C for 6 h after each treatment. The identification and quantification of volatile chemicals were performed using headspace solid-phase microextraction and gas chromatography–mass spectrometry. Thymol, γ-terpinene, p-cymene, and β-pinene were the predominant compounds before and after the treatments. The findings revealed that the application of ajwain and thyme essential oil treatments resulted in significant differences in the final concentration of monoterpenes. However, the sensory evaluation indicated that the ajwain and thyme essential oil samples received similar overall ratings. Consequently, ajwain essential oil could be a suitable alternative to thyme in beef jerky.
Integration of Artificial Intelligence in Art Preservation and Exhibition Spaces
Authors: Huang Pin-Chia , Li I-Cheng , Wang Ching-Yi , Shih Cheng-Hsiung , Srinivaas Masimukku , Yang Wan-Ting , Kao Chin-Fang , Su Te-Jen
Published: January 2025

This study aims to explore the application of artificial intelligence (AI) technology in the preservation and exhibition of artworks, with the “Exhibition Environment Status Detection Device and System” and the “Automatic Exhibition Guide System”, developed by Cheng Shiu University, as case studies. In recent years, AI technology has made significant advancements in image recognition, machine learning, and data analysis, which provide new opportunities for art management. However, due to high costs and implementation challenges, as well as a lack of qualified personnel to use these tools and systems, small art galleries and museums have not yet had the opportunity to acquire such systems. Therefore, this study observes the practical application of the “Exhibition Environment Status Detection Device and System” and the “Automatic Exhibition Guide System” in the fields of art preservation and exhibition. The study employs case study and observation methods, with participatory observation as the primary data collection approach. The results indicate that AI technology significantly enhances the preservation conditions of artworks and the interactivity of exhibitions. The paper suggests that future efforts should focus on long-term planning relating to technology costs and professional talent development to fully realize the potential of AI in art management and exhibition. Additionally, the application of these technologies can be extended to other fields.
Lip-Reading Classification of Turkish Digits Using Ensemble Learning Architecture Based on 3DCNN
Authors: Erbey Ali , Barışçı Necaattin
Published: January 2025

Understanding others correctly is of great importance for maintaining effective communication. Factors such as hearing difficulties or environmental noise can disrupt this process. Lip reading offers an effective solution to these challenges. With the growing success of deep learning architectures, research on lip reading has gained momentum. The aim of this study is to create a lip reading dataset for Turkish digit recognition and to conduct predictive analyses. The dataset has divided into two subsets: the face region and the lip region. CNN, LSTM, and 3DCNN-based models, including C3D, I3D, and 3DCNN+BiLSTM, were used. While LSTM models are effective in processing temporal data, 3DCNN-based models, which can process both spatial and temporal information, achieved higher accuracy in this study. Experimental results showed that the dataset containing only the lip region performed better; accuracy rates for CNN, LSTM, C3D, and I3D on the lip region were 67.12%, 75.53%, 86.32%, and 93.24%, respectively. The 3DCNN-based models achieved higher accuracy due to their ability to process spatio-temporal data. Furthermore, an additional 1.23% improvement was achieved through ensemble learning, with the best result reaching 94.53% accuracy. Ensemble learning, by combining the strengths of different models, provided a meaningful improvement in overall performance. These results demonstrate that 3DCNN architectures and ensemble learning methods yield high success in addressing the problem of lip reading in the Turkish language. While our study focuses on Turkish digit recognition, the proposed methods have the potential to be successful in other languages or broader lip reading applications.
Tambaqui (Colossoma macropomum) in RAS Technology: Zootechnical, Hematological, Biochemical and Kn Profiles at Different Stocking Densities During the Initial Grow-Out Phase
Authors: Petillo Emilly Cordeiro , Ferreira Aline da Cunha , Oliveira Christiane Patrícia Feitosa de , Brandão Lian Valente , Marinho-Pereira Thiago , Cavero Bruno Adan Sagratzki
Published: January 2025

The tambaqui (Colossoma macropomum) is Brazil’s most farmed native species, playing a crucial role in aquaculture. This study aimed to evaluate growth, hematological, biochemical, and body condition (Kn) parameters of tambaqui under two stocking densities in a recirculating aquaculture system (RAS). A total of 240 tambaqui (12.2 ± 4.1 g; 6.63 ± 0.73 cm) were distributed across six experimental units in two treatments (SD1 = 140 fish m−3; SD2 = 180 fish m−3) with three replicates. After 45 days, no significant differences were observed in water quality or zootechnical performance (p > 0.05), with final productivities of 8.64 ± 1.85 kg m3 and 9.46 ± 1.95 kg m3 for SD1 and SD2, respectively. Elevated plasma glucose, cholesterol, and triglyceride levels indicated energy reserve mobilization, suggesting some physiological response to higher stocking densities. However, other hematological and body condition parameters, including condition factor (Kn), indicated no significant adverse effects. These findings suggest that tambaqui can tolerate these stocking densities in RAS without compromising body condition, supporting the species’ intensive farming potential in controlled systems. This study highlights the importance of balancing productivity and physiological conditions in aquaculture management.
A Millimeter-Resolution Operando Thermal Image of Prismatic Li-Ion Batteries Using a Distributed Optical Fiber Sensor
Authors: Guo Zhen , Varnosfaderani Mina Abedi , Briggs Calum , Guk Erdogan , Marco James
Published: January 2025

With the demand for energy gravimetric and volumetric density in electrical vehicles, lithium-ion batteries are undergoing a trend toward larger formats, along with maximized cell-to-pack efficiency. Current battery thermal management systems and battery modeling, relying on point measurement (thermocouples/thermistors), face challenges in providing comprehensive characterization for larger batteries and extensive monitoring across the pack. Here, we proposed a novel Rayleigh-scattering-based distributed optical fiber sensor to deliver thermal images of a large prismatic cell. Using an optical fiber of 1 mm diameter wrapped around the cell, the optical sensor delivered over 400 unique measurement locations at 3 mm spatial resolution. During a 1.0 C charge, the optical-measured maximum temperature difference was 8.2 °C, while point-like thermocouples, located at the cell front surface and rear surface center, only had a 0.8 °C maximum temperature difference. Moreover, the all-surface-covered optical sensor identified hotspot generation around the vicinity of the tabs, highlighting the essential role of tabs. The maximum temperature on the negative current tab reached 113.9 °C during a 1.5 C discharge, while the hottest spot on the cell surface was only 52.1 °C. This was further validated by the operando thermal image in both the time domain and the spatial domain, facilitating a detailed analysis of the thermal-behavior-like heat generation on the current tabs, transmission through the surface, and dissipation to the cell bottom.
Cell Architecture Design for Fast-Charging Lithium-Ion Batteries in Electric Vehicles
Authors: Yeganehdoust Firoozeh , Madikere Raghunatha Reddy Anil Kumar , Zaghib Karim
Published: January 2025

This paper reviews the growing demand for and importance of fast and ultra-fast charging in lithium-ion batteries (LIBs) for electric vehicles (EVs). Fast charging is critical to improving EV performance and is crucial in reducing range concerns to make EVs more attractive to consumers. We focused on the design aspects of fast- and ultra-fast-charging LIBs at different levels, from internal cell architecture, through cell design, to complete system integration within the vehicle chassis. This paper explores battery internal cell architecture, including how the design of electrodes, electrolytes, and other factors may impact battery performance. Then, we provide a detailed review of different cell format characteristics in cylindrical, prismatic, pouch, and blade shapes. Recent trends, technological advancements in tab design and placement, and shape factors are discussed with a focus on reducing ion transport resistance and enhancing energy density. In addition to cell-level modifications, pack and chassis design must be implemented across aspects such as safety, mechanical integrity, and thermal management. Considering the requirements and challenges of high-power charging systems, we examined how modules, packs, and the vehicle chassis should be adapted to provide fast and ultra-fast charging. In this way, we explored the potential of fast and ultra-fast charging by investigating the required modification of individual cells up to their integration into the EV system through pack and chassis design.
Precision Medicine Assessment of the Radiographic Defect Angle of the Intrabony Defect in Periodontal Lesions by Deep Learning of Bitewing Radiographs
Authors: Abu Patricia Angela R. , Mao Yi-Cheng , Lin Yuan-Jin , Chao Chien-Kai , Lin Yi-He , Wang Bo-Siang , Chen Chiung-An , Chen Shih-Lun , Chen Tsung-Yi , Li Kuo-Chen
Published: January 2025

In dental diagnosis, evaluating the severity of periodontal disease by analyzing the radiographic defect angle of the intrabony defect is essential for effective treatment planning. However, dentists often rely on clinical examinations and manual analysis, which can be time-consuming and labor-intensive. Due to the high recurrence rate of periodontal disease after treatment, accurately evaluating the radiographic defect angle of the intrabony defect is vital for implementing targeted interventions, which can improve treatment outcomes and reduce recurrence. This study aims to streamline clinical practices and enhance patient care in managing periodontal disease by determining its severity based on the analysis of the radiographic defect angle of the intrabony defect. In this approach, radiographic defect angles of the intrabony defect greater than 37 degrees are classified as severe, while those less than 37 degrees are considered mild. This study employed a series of novel image enhancement techniques to significantly improve diagnostic accuracy. Before enhancement, the maximum accuracy was 78.85%, which increased to 95.12% following enhancement. YOLOv8 detects the affected tooth, and its mAP can reach 95.5%, with a precision reach of 94.32%. This approach assists dentists in swiftly assessing the extent of periodontal erosion, enabling timely and appropriate treatment. These techniques reduce diagnostic time and improve healthcare quality.
Butyrate Supplementation Improves Intestinal Health and Growth Performance in Livestock: A Review
Authors: Chen Wenting , Ma Qingshan , Li Yan , Wei Lin , Zhang Zhenwei , Khan Adnan , Khan Muhammad Zahoor , Wang Changfa
Published: January 2025

Butyrate supplementation has gained considerable attention for its potential benefits in livestock, particularly concerning intestinal health and growth performance. This review synthesizes recent research on the diverse roles of butyrate, across various livestock species. As a short-chain fatty acid, butyrate is known for enhancing intestinal development, improving immune function, and modulating microbial diversity. Studies indicate that butyrate supports gut barrier integrity, reduces inflammation, and optimizes feed efficiency, especially during the critical weaning and post-weaning periods in calves, piglets, and lambs. Supplementation with butyrate in livestock has been shown to increase average daily gain (ADG), improve gut microbiota balance, promote growth, enhance gut health, boost antioxidant capacity, and reduce diarrhea. Additionally, butyrate plays a role in the epigenetic regulation of gene expression through histone acetylation, influencing tissue development and immune modulation. Its anti-inflammatory and antioxidant effects have been demonstrated across various species, positioning butyrate as a potential therapeutic agent in animal nutrition. This review suggests that optimizing butyrate supplementation strategies to meet the specific needs of each species may yield additional benefits, establishing butyrate as an important dietary additive for enhancing growth performance and health in livestock.
An Addendum to the Chemiosmotic Theory of Mitochondrial Activity: The Role of RNA as a Proton Sink
Authors: Farahani Ramin M.
Published: January 2025

Mitochondrial ATP synthesis is driven by harnessing the electrochemical gradient of protons (proton motive force) across the mitochondrial inner membrane via the process of chemiosmosis. While there is consensus that the proton gradient is generated by components of the electron transport chain, the mechanism by which protons are supplied to ATP synthase remains controversial. As opposed to a global coupling model whereby protons diffuse into the intermembrane space, a localised coupling model predicts that protons remain closely associated with the lipid membrane prior to interaction with ATP synthase. Herein, a revised version of the chemiosmotic theory is proposed by introducing an RNA-based proton sink which aligns the release of sequestered protons to availability of ADP and Pi thereby maximising the efficiency of oxidative phosphorylation.
A Narrative Review of Prognostic Gene Signatures in Oral Squamous Cell Carcinoma Using LASSO Cox Regression
Authors: Mohd Faizal Nur Fatinazwa , Shai Saptarsi , Savaliya Bansi P. , Karen-Ng Lee Peng , Kumari Rupa , Kumar Rahul , Vincent-Chong Vui King
Published: January 2025

Oral squamous cell carcinoma (OSCC) is one of the most common malignancies of the head and neck squamous cell carcinoma (HNSCC). HNSCC is recognized as the eighth most commonly occurring cancer globally in men. It is essential to distinguish between cancers arising in the head and neck regions due to significant differences in their etiologies, treatment approaches, and prognoses. As the Cancer Genome Atlas (TCGA) dataset is available in HNSCC, the survival analysis prognosis of OSCC patients based on the TCGA dataset for discovering gene expression-based prognostic biomarkers is limited. To address this paucity, we aimed to provide comprehensive evidence by recruiting studies that have reported new biomarkers/signatures to establish a prognostic model to predict the survival of OSCC patients. Using PubMed search, we have identified 34 studies that have been using the least absolute shrinkage and selection operator (LASSO)-based Cox regression analyses to establish signature prognosis that related to different pathways in OSCC from the past 4 years. Our review was focused on summarizing these signatures and implications for targeted therapy using FDA-approved drugs. Furthermore, we conducted an analysis of the LASSO Cox regression gene signatures. Our findings revealed 13 studies that correlated a greater number of regulatory T cells (Tregs) cells in protective gene signatures with increased recurrence-free and overall survival rates. Conversely, two studies displayed an opposing trend in cases of OSCC. We will also explore how the dysregulation of these signatures impacts immune status, promoting tumor immune evasion or, conversely, enhancing immune surveillance. Overall, this review will provide new insight for future anti-cancer therapies based on the potential gene that is associated with poor prognosis in OSCC.
An Investigation of the Capabilities of Resin Tire Carbon Black “N-330” as a Waste Binder in Asphalt Concrete Mixtures
Authors: A. Nada Amr. , Edris Walid Fouad , Al-Jabali Hebah Mohammad , D. Almutairi Ahmed , A. Al Sayed Abd Al-Kader , Khairy Shady
Published: January 2025

This study investigates the potential use of tire-derived carbon black “N-330” as a sustainable waste binder in asphalt concrete mixtures, combined with resin as an alternative to the usual binding material in asphalt mixtures, “bitumen”. With the increasing demand for environmentally friendly construction materials, this research aims to assess the feasibility of incorporating resin tire carbon black N-330 “RTCB N-330” into asphalt as a full replacement for conventional binders. A comprehensive experimental program has been designed to evaluate the mechanical and performance properties of asphalt mixtures containing varying proportions of RTCB N-330, ranging from 2% to 10% by weight of the binder. The impact of replacing bitumen with resin that contains TCB N-330 on the physical, rheological, and thermal characteristics of RTCB N-330 as a modified asphalt binder is assessed in this study. To assess the binders, a number of tests were carried out, including standard tests for ductility, the softening point, and penetration. DTG (Derivative Thermogravimetric Analysis) and testing the thermal susceptibility index were performed. A higher percentage of TCB N-330 reduced the penetration while increasing both the softening point and ductility. Resin with 8% of TCB N-330 was the optimum percentage, which was compared with bitumen as a new environmentally friendly binder. The testing program involved the preparation of asphalt concrete specimens using a Marshall mix design, followed by a Marshall Stability test to evaluate the deformation resistance of the modified mixtures. The results were anticipated to demonstrate that incorporating N-330 into asphalt mixtures can enhance stability. The Marshall test results indicated that samples with 6% resin tire carbon black as the binder percentage “AC-RTCB6” demonstrated the highest stability among all RTCB samples. Moreover, these samples outperformed asphalt mixtures using bitumen as the binder in terms of stability. Also, the AC-B mixes exhibited lower flow values compared to the AC-RTCB mixes. The higher flow observed in the AC-RTCB specimens suggests that the addition of 1.5% xylene as a solvent to the resin was effective and positively influenced the flow characteristics.
Axillary Overtreatment in Patients with Breast Cancer After Neoadjuvant Chemotherapy in the Current Era of Targeted Axillary Dissection
Authors: Zapletal Ondřej , Žatecký Jan , Gabrielová Lucie , Selingerová Iveta , Holánek Miloš , Burkoň Petr , Coufal Oldřich
Published: January 2025

Background: In the current era of targeted axillary dissection (TAD), there are still cases where axillary lymph node dissection (ALND) is indicated, but histopathological examination confirms the regression of nodal metastases (ypN0). In this situation, ALND may represent undesirable overtreatment. Methods: A retrospective study at the Comprehensive Cancer Centre was conducted based on a prospectively maintained database. Patients who underwent surgery after neoadjuvant chemotherapy (NAC) between 2020 and 2023 were selected, specifically those for whom ALND was directly indicated after NAC. Subsequently, clinical–pathological characteristics were compared between cases with ypN0 and those with persistent metastases (ypN+). The reasons for indicating ALND in ypN0 cases were extracted from the medical records. Results: ALND was indicated in 118 cases across 117 patients, of which ypN0 was observed in 44 cases (37%). There were significantly more ypN0 cases for inflammatory carcinomas (68%), the non-luminal HER2-positive phenotype (76%), and carcinomas with histopathological regression of the primary tumor (76%) or the persistence of only the non-invasive component of ypTis (67%). Typical reasons for ALND in ypN0 cases included inflammatory carcinoma (n = 13, 29.5%), locally advanced carcinoma (n = 5, 11.4%), occult carcinoma (n = 2, 4.5%), or persistent lymphadenopathy on ultrasound examination after NAC, especially in the tumor phenotypes HER2-positive and triple-negative breast cancer (TNBC) (n = 8, 18.2%). Conclusions: Through real-world evidence data analysis, subgroups of breast cancer patients treated with NAC were identified who may experience surgical overtreatment in the axilla. These include patients with inflammatory carcinoma, locally advanced carcinoma, occult carcinoma, or patients with persistent lymphadenopathy on US examination after NAC, particularly in the tumor phenotypes HER2-positive and TNBC.
Proximity Labeling: Precise Proteomics Technology for Mapping Receptor Protein Neighborhoods at the Cancer Cell Surface
Authors: Rahmati Saman , Emili Andrew
Published: January 2025

Cell surface receptors are pivotal to cancer cell transformation, disease progression, metastasis, early detection, targeted therapy, drug responses, and clinical outcomes. Since they coordinate complex signaling communication networks in the tumor microenvironment, mapping the physical interaction partners of cell surface receptors in vivo is vital for understanding their roles, functional states, and suitability as therapeutic targets. Yet traditional methods like immunoprecipitation and affinity purification–mass spectrometry often fail to detect key but weak or transient receptor–protein interactions. Proximity labeling, a cutting-edge proteomics technology, addresses these technical challenges by enabling precise mapping of protein neighborhoods around a receptor target on the cell surface of cancer cells. This technique has been successfully applied in vitro and in vivo for proteomic mapping across various model systems. This review explores the fundamental principles, technologies, advantages, limitations, and applications of proximity labeling in cancer biology, focusing on mapping receptor microenvironments. By advancing mechanistic insights into cancer cell receptor signaling mechanisms, proximity labeling is poised to transform cancer research, improve targeted therapies, and illuminate avenues to overcome drug resistance.
Prognostic Significance of S100A4 in Ovarian Clear Cell Carcinoma: Its Relation to Tumor Progression and Chemoresistance
Authors: Hayashi Misato , Yokoi Ako , Nakagawa Mayu , Hashimura Miki , Oguri Yasuko , Saegusa Makoto
Published: January 2025

Background/Objectives: S100A4, a small calcium-binding protein, promotes metastasis in a variety of human malignancies, but little is known about its involvement in ovarian clear cell carcinoma (OCCC). Herein, we characterized the functional role of S100A4 in this tumor type. Methods: We analyzed immunohistochemical sections from 120 OCCC patients. OCCC cell lines in which S100A4 was knocked out (KO) or overexpressed were also used to study the protein’s effects. Results: Stable overexpression of S100A4 decreased the proliferation of OCCC cell lines (concomitant with more cells in G1 and fewer in the G2/M phase of the cell cycle). S100A4 overexpression also reduced susceptibility to cisplatin-induced apoptosis (probably due to an increased BCL2: BAX ratio), accelerated epithelial–mesenchymal transition (EMT)-related cell mobility, and enhanced cancer stem cell (CSC) properties (including increases in both spheroid formation and in the aldehyde dehydrogenase 1 (ALDH1)high population). In contrast, S100A4 KO generally induced the opposite phenotypes, although it did not affect migration capability. In clinical OCCC samples, high S100A4 expression was associated with a low frequency of cleaved poly-(ADP-ribose) polymerase 1-positive apoptotic cells, a reduced proliferative rate, and expression of high ALDH1 and vimentin levels. In addition, a high S100A4 score was a significant (but not independent) prognostic factor in OCCC. Conclusions: Our findings suggest that S100A4 may be an unfavorable prognostic factor in OCCC, as it accelerates tumor progression and promotes chemoresistance through the modulation of proliferation, susceptibility to apoptosis, and EMT/CSC properties.
Silicone Fiducial Markers Improve Precision in Uveal Melanoma Radiation Therapy
Authors: Sonntag Svenja Rebecca , Wittenstein Olaf , Blanck Oliver , Dunst Jürgen , Huttenlocher Stefan , Grehn Melanie , Busch Maximilian , Rades Dirk , Tura Ayseguel , Grisanti Salvatore
Published: January 2025

Objectives: Accurate target definition, treatment planning and delivery increases local tumor control for radiotherapy by minimizing collateral damage. To achieve this goal for uveal melanoma (UM), tantalum fiducial markers (TFMs) were previously introduced in proton and photon beam radiotherapy. However, TFMs cause pronounced scattering effects in imaging that make the delineation of small tumors difficult. The aim of this study was to evaluate silicone fiducial markers (SFMs) for the guiding of stereotactic radiosurgery (SRS) for UM. Methods: In this retrospective interventional pilot case series, three patients with small UMs 3 mm or less in tumor thickness and ≤10 mm in largest basal diameter received silicone fiducial markers. The fiducial markers were punched out (3 mm) from conventional silicone encircling bands for buckle surgery. The markers were sutured onto the sclera at the tumor margins according to the use of TFMs. MRI and CT images were used for the localization of the tumor and the markers before robotic-guided SRS. Results: The silicone fiducial markers were punched out easily from the original band, better to handle than TFMs and easy to suture onto the sclera. They could be visualized in both MRI and CT, but were more visible in CT. In the absence of scattering effects, both the markers and thus the tumor boundaries could be clearly delineated. Conclusions: This is the first report that introduces fiducial markers intraoperatively shaped from conventional silicone encircling bands usually used for retinal detachment surgery. The SFMs allow more accurate tumor delineation, resulting in the more precise planning and administration of SRS when compared to TFMs. This simple modification has a major impact on a well-known treatment approach.
miR-1233-3p Inhibits Angiopoietin-1-Induced Endothelial Cell Survival, Migration, and Differentiation
Authors: Sanchez Veronica , Harel Sharon , Sa’ub Anas Khalid , Mayaki Dominique , Hussain Sabah N. A.
Published: January 2025

Angiopoietin-1 (Ang-1) and its receptor Tie-2 promote vascular integrity and angiogenesis. MicroRNAs (miRNAs) are involved in the regulation of many cellular functions, including endothelial cell (EC) survival, proliferation, and differentiation. Several reports indicate that these effects of miRNAs on EC functions are mediated through the modulation of angiogenesis factor signaling including that of vascular endothelial growth factor (VEGF). To date, very little is known about the roles played by miRNAs in the signaling and angiogenesis promoted by the Ang-1–Tie-2 receptor axis. Our high-throughput screening of miRNAs regulated by Ang-1 exposure in human umbilical vein endothelial cells (HUVECs) has identified miR-1233-3p as a mature miRNA whose cellular levels are significantly downregulated in response to Ang-1 exposure. The expression of miR-1233-3p in these cells is also downregulated by other angiogenesis factors including VEGF, fibroblast growth factor 2 (FGF-2), transforming growth factor β (TGFβ), and angiopoietin-2 (Ang-2). The overexpression of miR-1233-3p in HUVECs using specific mimics significantly attenuated cell survival, migration, and capillary-like tube formation, and promoted apoptosis. Moreover, miR-1233-3p overexpression resulted in reversal of the anti-apoptotic, pro-migration, and pro-differentiation effects of Ang-1. Biotinylated miRNA pull-down assays showed that p53 and DNA damage-regulated 1 (PDRG1) is a direct target of miR-1233-3p in HUVECs. The exposure of HUVECs to Ang-1, angiopoietin-2 (Ang-2), fibroblast growth factor 2 (FGF2), vascular endothelial growth factor (VEGF), or transforming growth factor β (TGFβ) triggers the regulation of PDRG1 expression. This study highlights that miR-1233-3p exerts inhibitory effects on Ang-1-induced survival, migration, and the differentiation of cultured ECs.
Effect of Alkyl Chain Length of Quaternary Ammonium Surfactant Corrosion Inhibitor on Fe (110) in Acetic Acid Media via Computer Simulation
Authors: Numin Mohd Sofi , Jumbri Khairulazhar , Eng Kee Kok , Hassan Almila , Borhan Noorazlenawati , Daud Nik M. Radi Nik M. , A Azmi M. Nor , Suhor Firdaus , Dzulkifli Nur Nadia
Published: January 2025

Density functional theory (DFT) and molecular dynamics (MD) simulations were employed to investigate the inhibition mechanism of cationic quaternary ammonium surfactant corrosion inhibitors (CIs) with varying chain lengths in 1.0 M HCl and 500 ppm acetic acid on Fe (110) surfaces. DFT calculations demonstrated that all surfactant CI molecules possess favorable inhibition properties, with the cationic quaternary ammonium groups (N+) and alpha carbon serving as electron-donating reactive centers, characterized by a low band-gap energy of 1.26 eV. MD simulations highlighted C12, with a 12-alkyl chain length, as the most promising CI molecule, exhibiting high adsorption and binding energies, a low diffusion coefficient, and a random distribution at low concentrations, thereby facilitating optimal adsorption onto the Fe (110) metal surface. The insights gained from computational modeling regarding the influence of alkyl chain length on inhibition efficiency, coupled with the comprehensive theoretical understanding of cationic quaternary ammonium surfactant CI molecules in acidic corrosion systems, can serve as a foundation for the future development of innovative surfactant CI molecules incorporating ammonium-based functional groups.
The Importance of Soil Seed Bank Function in Studies of Grassland Degradation
Authors: Chen Chao , He Wei , Scullion John , Wilkinson Mike
Published: January 2025

The world’s grasslands are under increasing threat of degradation. Given the potential for multiple drivers of decline, precise diagnosis of degradation is best achieved by comparison with a local, sustainable grassland community. Comparisons of this kind are becoming increasingly common for regional grassland plant communities, but these studies largely overlook interactions between soil responses to system degradation and the effective functioning of the soil seed bank. Surveys of grassland degradation studies have revealed that only around 5% include information on soil seed bank composition and no one aspect of community structure features across all studies. Furthermore, the majority of studies provide information only on ground coverage, sward biomass or species diversity in the plant subcommunity, with very few including information on the health of the soil seed bank or how changes in the soil environment could drive further deterioration in the plant community size, structure or effective functioning of the soil seed bank. We consider that soil responses to sward degradation are likely to exacerbate rather than mitigate impacts on soil seed bank function, leading to a spiral of system degradation in the absence of timely and targeted intervention. We propose improvements for future studies seeking to diagnose and quantify grassland degradation.
Forecasting Half-Hourly Electricity Prices Using a Mixed-Frequency Structural VAR Framework
Authors: Kapoor Gaurav , Wichitaksorn Nuttanan , Li Mengheng , Zhang Wenjun
Published: January 2025

Electricity price forecasting has been a topic of significant interest since the deregulation of electricity markets worldwide. The New Zealand electricity market is run primarily on renewable fuels, and so weather metrics have a significant impact on electricity price and volatility. In this paper, we employ a mixed-frequency vector autoregression (MF-VAR) framework where we propose a VAR specification to the reverse unrestricted mixed-data sampling (RU-MIDAS) model, called RU-MIDAS-VAR, to provide point forecasts of half-hourly electricity prices using several weather variables and electricity demand. A key focus of this study is the use of variational Bayes as an estimation technique and its comparison with other well-known Bayesian estimation methods. We separate forecasts for peak and off-peak periods in a day since we are primarily concerned with forecasts for peak periods. Our forecasts, which include peak and off-peak data, show that weather variables and demand as regressors can replicate some key characteristics of electricity prices. We also find the MF-VAR and RU-MIDAS-VAR models achieve similar forecast results. Using the LASSO, adaptive LASSO, and random subspace regression as dimension-reduction and variable selection methods helps to improve forecasts where random subspace methods perform well for large parameter sets while the LASSO significantly improves our forecasting results in all scenarios.
An Improved Binary Simulated Annealing Algorithm and TPE-FL-LightGBM for Fast Network Intrusion Detection
Authors: Luo Yafei , Chen Ruihan , Li Chuantao , Yang Derong , Tang Kun , Su Jing
Published: January 2025

With the rapid proliferation of the Internet, network security issues that threaten users have become increasingly severe, despite the widespread benefits of Internet access. Most existing intrusion detection systems (IDS) suffer from suboptimal performance due to data imbalance and feature redundancy, while also facing high computational complexity in areas such as feature selection and optimization. To address these challenges, this study proposes a novel network intrusion detection method based on an improved binary simulated annealing algorithm (IBSA) and TPE-FL-LightGBM. First, by integrating Focal Loss into the loss function of the LightGBM classifier, we introduce cost-sensitive learning, which effectively mitigates the impact of class imbalance on model performance and enhances the model’s ability to learn difficult-to-classify samples. Next, significant improvements are made to the simulated annealing algorithm, including adaptive adjustments of the initial temperature and Metropolis criterion, the incorporation of multi-neighborhood search strategies, and the integration of an S-shaped transfer function. These improvements enable the IBSA method to achieve efficient optimal feature selection with fewer iterations. Finally, the Tree-structured Parzen Estimator (TPE) algorithm is employed to optimize the structure of the FL-LightGBM classifier, further enhancing its performance. Through comprehensive visual analysis, ablation studies, and comparative experiments on the NSL-KDD and UNSW-NB15 datasets, the reliability of the proposed network intrusion detection method is validated.
Large Language Model-Based Tuning Assistant for Variable Speed PMSM Drive with Cascade Control Structure
Authors: Tarczewski Tomasz , Stojic Djordje , Dzielinski Andrzej
Published: January 2025

A cascade control structure (CCS) is still the most commonly used control scheme in variable speed control (VSC) electrical drives with alternating current (AC) motors. Several tuning methods are used to select the coefficients of controllers applied in CCS. These approaches can be divided into analytical, empirical, and heuristic ones. Regardless of the tuning method used, there is still a question of whether the CCS is tuned optimally in terms of considered performance indicators to provide high-performance behavior of the electrical drive. Recently, artificial intelligence-based methods, e.g., swarm-based metaheuristic algorithms (SBMAs), have been extensively examined in this field, giving promising results. Moreover, the intensive development of artificial intelligence (AI) assistants based on large language models (LLMs) supporting decision-making processes is observed. Therefore, it is worth examining the ability of LLMs to tune the CCS in the VSC electrical drive. This paper investigates tuning methods for the cascade control structure equipped with PI-type current and angular velocity controllers for PMSM drive. Sets of CCS parameters from electrical engineers with different experiences are compared with reference solutions obtained by using the SBMA approach and LLMs. The novel LLM-based Tuning Assistant (TA) is developed and trained to improve the quality of responses. Obtained results are assessed regarding the drive performance, number of attempts, and time required to accomplish the considered task. A quantitative analysis of LLM-based solutions is also presented. The results indicate that AI-based tuning methods and the properly trained Tuning Assistant can significantly improve the performance of VSC electrical drives, while state-of-the-art LLMs do not guarantee high-performance drive operation.
A New Koch and Hexagonal Fractal Combined Circular Structure Antenna for 4G/5G/WLAN Applications
Authors: Yu Zhen , Chang Yi , Niu Ruirong , Zhang Ruixin , Wang Feng , Sun Runzhi , Zhang Guodong , Ran Xiaoying
Published: January 2025

This paper presents a novel double-sided structure multi-band antenna that cleverly combines a Koch snowflake structure with a hexagonal fractal structure; the front of the antenna features a right semicircle minus a half-order Koch snowflake structure, while the back of the antenna showcases a left semicircle minus half of a hexagonal fractal snowflake structure, which are combined together to form a complete circle. The antenna can cover common communication bands such as fourth to fifth generation (5G) commercial bands, ISM, WLAN, and Bluetooth. The structure of the radiator portion of the antenna is designed by iteratively scaling a basic arc shape multiple times based on a certain scale factor, and after simulation and comparison, three iterations can achieve the best antenna performance, and the antenna uses a microstrip line transmission to broaden the antenna bandwidth. The antenna covers three effective frequency bands: 2.38–2.90 GHz (20.3%), 3.35–3.85 GHz (14.1%), and 5.06–5.80 GHz (13.5%). The antenna dielectric sheet is made of RF-35 from Taconic, which has the advantages of high strength, complete surface inertness, and a long service life, with a dielectric constant of 3.5 and actual dimensions of 50 mm × 54 mm × 0.76 mm. The antenna is fractal-iterated in small dimensions, and the approximation of the frequency bands is accomplished by comparing the ratios of each iteration with the current vector map. The antenna was simulated by HFSS software (Version 21). and measured in an electromagnetic anechoic chamber, and the test results were consistent with the simulation results.
Hierarchical Energy Management and Energy Saving Potential Analysis for Fuel Cell Hybrid Electric Tractors
Authors: Lei Shenghui , Li Yanying , Liu Mengnan , Li Wenshuo , Zhao Tenglong , Hou Shuailong , Xu Liyou
Published: January 2025

To address the challenges faced by fuel cell hybrid electric tractors (FCHETs) equipped with a battery and supercapacitor, including the complex coordination of multiple energy sources, low power allocation efficiency, and unclear optimal energy consumption, this paper proposes two energy management strategies (EMSs): one based on hierarchical instantaneous optimization (HIO) and the other based on multi-dimensional dynamic programming with final state constraints (MDDP-FSC). The proposed HIO-based EMS utilizes a low-pass filter and fuzzy logic correction in its upper-level strategy to manage high-frequency dynamic power using the supercapacitor. The lower-level strategy optimizes fuel cell efficiency by allocating low-frequency stable power based on the principle of minimizing equivalent consumption. Validation using a hardware-in-the-loop (HIL) simulation platform and comparative analysis demonstrate that the HIO-based EMS effectively improves the transient operating conditions of the battery and fuel cell, extending their lifespan and enhancing system efficiency. Furthermore, the HIO-based EMS achieves a 95.20% level of hydrogen consumption compared to the MDDP-FSC-based EMS, validating its superiority. The MDDP-FSC-based EMS effectively avoids the extensive debugging efforts required to achieve a final state equilibrium, while providing valuable insights into the global optimal energy consumption potential of multi-energy source FCHETs.
Innovative Role of Magnesium Oxide Nanoparticles and Surfactant in Optimizing Interfacial Tension for Enhanced Oil Recovery
Authors: Kandiel Youssef E. , Attia Gamal , Metwalli Farouk , Khalaf Rafik , Mahmoud Omar
Published: January 2025

Enhancing oil recovery efficiency is vital in the energy industry. This study investigates magnesium oxide (MgO) nanoparticles combined with sodium dodecyl sulfate (SDS) surfactants to reduce interfacial tension (IFT) and improve oil recovery. Pendant drop method measurements revealed a 70% IFT reduction, significantly improving nanoparticle dispersion stability due to SDS. Alterations in Zeta Potential and viscosity, indicating enhanced colloidal stability under reservoir conditions, were key findings. These results suggest that the MgO-SDS system offers a promising and sustainable alternative to conventional methods, although challenges such as scaling up and managing nanoparticle–surfactant dynamics remain. The preparation of MgO nanofluids involved magnetic stirring and ultrasonic homogenization to ensure thorough mixing. Characterization techniques included density, viscosity, pH, Zeta Potential, electric conductivity, and electrophoretic mobility assessments for the nanofluid and surfactant–nanofluid systems. Paraffin oil was used as the oil phase, with MgO nanoparticle concentrations ranging from 0.01 to 0.5 wt% and a constant SDS concentration of 0.5 wt%. IFT reduction was significant, from 47.9 to 26.9 mN/m with 0.1 wt% MgO nanofluid. Even 0.01 wt% MgO nanoparticles reduced the IFT to 41.8 mN/m. Combining MgO nanoparticles with SDS achieved up to 70% IFT reduction, enhancing oil mobility. Changes in Zeta Potential (from −2.54 to 3.45 mV) and pH (from 8.4 to 10.8) indicated improved MgO nanoparticle dispersion and stability, further boosting oil displacement efficiency under experimental conditions. The MgO-SDS system shows promise as a cleaner, cost-effective Enhanced Oil Recovery (EOR) method. However, challenges such as nanoparticle stability under diverse conditions, surfactant adsorption management, and scaling up require further research, emphasizing interdisciplinary approaches and rigorous field studies.
Genome-Wide Investigation and Expression Analysis of AP2 Gene Subfamily Reveals Its Evolution and Regulatory Role Under Salt Stress in Populus
Authors: Wang Zhengbo , Liang Xiaolin , Hao Ziyuan , Feng Qi , Li Hongying , Liu Yingli
Published: January 2025

The APETALA2/ethylene-responsive factor (AP2/ERF) is a well-researched superfamily of plant transcription factors. The APETALA2 (AP2) subfamily is essential for plant growth and development. However, a systematic analysis of the AP2 subfamily in poplar has yet to be conducted. This study identified 29 AP2 genes in the poplar genome, classifying them into three clades—euAP2, euANT, and basalANT based on evolutionary relationships. These genes are distributed across 12 chromosomes and one scaffold. Results from the syntenic analysis suggest that whole-genome duplication events are the primary factors driving the expansion of the AP2 subfamily in poplar. Cis-element analysis reveals that numerous PtAP2 genes possess hormone-related cis-elements. These genes also contain cis-elements linked to plant development and stress responses. PtAP2s from different clades exhibit significantly tissue-specific expression patterns in poplar. Gene expression levels in the euAP2 clade are significantly higher than in the euANT and basalANT clades across various tissues, with basalANT showing the lowest expression. Through RT-qPCR and recombinant Saccharomyces cerevisiae assays under salt stress, it was discovered that the majority of AP2 genes showed a negative response in salt stress regulation in poplar trees. In conclusion, this study offers valuable insights into salt tolerance in poplar trees and the role of AP2 genes under salt stress conditions.
RETRACTED: Fatunmbi et al. Irreversibility Analysis for Eyring–Powell Nanoliquid Flow Past Magnetized Riga Device with Nonlinear Thermal Radiation. Fluids 2021, 6, 416
Authors: Fatunmbi Ephesus Olusoji , Adeosun Adeshina Taofeeq , Salawu Sulyman Olakunle
Published: January 2025

The Fluids Editorial Office retracts the article “Irreversibility Analysis for Eyring–Powell Nanoliquid Flow Past Magnetized Riga Device with Nonlinear Thermal Radiation” [...]
Sheep Manure-Tail Vegetable-Corn Straw Co-Composting Improved the Yield and Quality of Mini Chinese Cabbage
Authors: Wang Xuehua , Qiao Yali , Tie Jianzhong , Zhang Wenbin , Wei Baihong , Liu Zeci , Yu Jihua , Hu Linli
Published: January 2025

In order to fully utilize the resources of agricultural waste in Gansu Province’s semi-arid area. Local commercial organic fertilizer (ST1) was selected as the control, and four kinds of planting and breeding waste composts (PBCs) were designed with sheep manure (SM), cow manure (CM), tail vegetable (TV), mushroom residue (MR), and corn straw (CS) to study the effects of the different PBC formulations on the yield and quality of mini Chinese cabbage. In contrast to local commercial organic fertilizer, the STS (SM:TV:CS = 6:3:1) treatment increased the economic yield by 5.56%. Additionally, STS also significantly increased the VC content of mini Chinese cabbage, increased the organic acid by 14.66%, increased the free amino acid by 38.98%, and the nitrate concentration was significantly reduced by 41.05%. Meanwhile, the STS formula also increased the concentrations of polyphenols and essential amino acids of mini Chinese cabbage and also had excellent performance in volatile compounds. As a result, the STS formula can make full use of local planting and breeding waste resources and produce high yield and high quality of local mini Chinese cabbage. The study provided a theoretical foundation and technical guidance for screening suitable local compost formulas, as well as for the achievement of high-yield and high-quality mini Chinese cabbage production in the semi-arid areas of central Gansu province.