bluuebunny/crossref_metadata_2025 huggingface dataset:
Building Traceable Redactable Blockchain with Time-Verifiable Chameleon Hash
Authors: Chen Mingliang , Xie Guoqiang , Pan Benren , Fang Jinyan , Xu Zaide , Zhao Zhen
Published: February 2025

Blockchain is a decentralized digital ledger that records transactions across a distributed network of computers, enabling secure and transparent operations without requiring trust in a central authority. While initially developed for Bitcoin, blockchain technology now underpins many cryptocurrencies and other applications. It serves as an open trust layer without central reliance and is widely used in cryptocurrencies such as Bitcoin and Ethereum. However, this public and permanent open storage has raised concerns about its potential misuse for illegal trades or the distribution of unwanted content. In EuroS&P 2017, Ateniese et al. introduced the concept of the redactable blockchain, which utilizes the trapdoor collision function provided by chameleon hash to rewrite block contents without causing hashing inconsistencies. Recent research has continued to propose solutions for redactable blockchains, leveraging cryptographic algorithms such as chameleon hash and attribute-based encryption (ABE). Current solutions often employ sophisticated cryptographic schemes, such as ABE, but lack sufficient focus on developing secure and scalable solution for practical use. In this work, we propose the time-verifiable policy-based chameleon hash (TPCH) as a candidate solution for practical redaction to rewrite blockchain contents. Our solution for redactable blockchains enables the verification of whether a redaction was executed at a specific time, thereby offering time-based traceability for dominant algorithms in TPCH. Additionally, it restricts misbehavior or abuse of redaction powers by introducing a new trapdoor finding algorithm, Update, in addition to the adapt algorithm Adapt. We formally introduce TPCH with both black-box and white-box constructions. Our experimental and theoretical analysis demonstrates the feasibility and practicality of the proposed solution.
ConBOOM: A Configurable CPU Microarchitecture for Speculative Covert Channel Mitigation
Authors: Zhang Zhewen , Liu Yao , She Yuhan , Sanka Abdurrashid Ibrahim , Hung Patrick S. Y. , Cheung Ray C. C.
Published: February 2025

Speculative execution attacks are serious security problems that cause information leakage in computer systems by building speculative covert channels. Hardware defenses mitigate speculative covert channels through microarchitectural changes. However, two main limitations become the major bottleneck in existing hardware defenses. High-security hardware defenses, such as eager delay, can effectively mitigate both known and unknown covert channels. However, these defenses incur high performance overhead due to the long-fixed delayed execution applied in all potential attack scenarios. In contrast, hardware defenses with low performance overhead are faster and can mitigate known covert channels, but lack sufficient security to mitigate unknown covert channels. The limitations indicate that it is difficult to achieve better security and performance of a processor against speculative execution attacks using a single defense method. In this paper, we propose ConBOOM, a configurable central processing unit (CPU) microarchitecture that provides optimized switchable hardware defensive modes, including the high-security eager delay mode and two proposed performance-optimized modes based on the anticipated attack scenarios. The defensive modes allow for flexibility in mitigating different speculative execution attacks with better performance, unlike the existing defenses having fixed performance overhead for all attack scenarios. The ConBOOM modes can be switched without modifying the hardware, and switching ConBOOM to the suitable mode for the anticipated attack scenario is achieved through the provided software configuration interface. We implemented ConBOOM on Berkeley’s RISC-V out-of-order processor core (SonicBOOM). Furthermore, we evaluated ConBOOM on the VCU118 FPGA platform. Compared to the existing representative work with the fixed performance overhead of 39.1%, ConBOOM has the lower performance overhead ranging between 15.1% and 39.1% to mitigate different attack scenarios. ConBOOM provides more defensive flexibility with negligible hardware resource overhead about 2.0% and good security.
A 12 dBm B1dB N-Path Notch Filter for Transmitter Leakage Suppression in Wideband Receiver
Authors: Luo Xujia , Qi Shihao , Xu Shang , Zhang Haotian , Xu Qinfen , Wu Guoan , Zhan Lamin
Published: February 2025

This paper proposes an N-path notch filter while offering high blocker power handling for co-address transmitter (TX) leakage suppression in a wideband receiver. The filter includes an impedance flip-flop over an adjustable transmission line in a block band, achieving a 12.3 to 13.6 dBm blocker 1 dB compression point (B1dB) and a 12.8 to 14 dBm 1 dB compression point (P1dB) in a 130 nm CMOS SOI process. This design effectively suppresses broadband interference in the receiving system and improves the dynamic range and linearity of the receiver (RX) channel. The filter consumes 186 to 242 mW in the 0.3 GHz to 0.6 GHz band and has an active chip area of 0.21 mm2, providing maximum rejection >25 dB, with a passband third-order input intercept point (IIP3) of 22 to 25.2 dBm. The design of the adjustable transmission line structure is analyzed to reduce the insertion loss in terms of impedance and to achieve a 1.7 to 2 dB insertion loss shortfall over the RF tuning range.
Human–Robot Interaction Using Dynamic Hand Gesture for Teleoperation of Quadruped Robots with a Robotic Arm
Authors: Xie Jianan , Xu Zhen , Zeng Jiayu , Gao Yuyang , Hashimoto Kenji
Published: February 2025

Human–Robot Interaction (HRI) using hand gesture recognition offers an effective and non-contact approach to enhancing operational intuitiveness and user convenience. However, most existing studies primarily focus on either static sign language recognition or the tracking of hand position and orientation in space. These approaches often prove inadequate for controlling complex robotic systems. This paper proposes an advanced HRI system leveraging dynamic hand gestures for controlling quadruped robots equipped with a robotic arm. The proposed system integrates both semantic and pose information from dynamic gestures to enable comprehensive control over the robot’s diverse functionalities. First, a Depth–MediaPipe framework is introduced to facilitate the precise three-dimensional (3D) coordinate extraction of 21 hand bone keypoints. Subsequently, a Semantic-Pose to Motion (SPM) model is developed to analyze and interpret both the pose and semantic aspects of hand gestures. This model translates the extracted 3D coordinate data into corresponding mechanical actions in real-time, encompassing quadruped robot locomotion, robotic arm end-effector tracking, and semantic-based command switching. Extensive real-world experiments demonstrate the proposed system’s effectiveness in achieving real-time interaction and precise control, underscoring its potential for enhancing the usability of complex robotic platforms.
Using Machine Learning Algorithms to Forecast Solar Energy Power Output
Authors: Lari Ali Jassim , Sanfilippo Antonio P. , Bachour Dunia , Perez-Astudillo Daniel
Published: February 2025

Solar energy is an inherently variable energy resource, and the ensuing uncertainty in matching energy demand presents a challenge in its operational use as an alternative energy source. The factors influencing solar energy power generation include geographic location, solar radiation, weather conditions, and solar panel performance. Solar energy forecasting is performed using machine learning for better accuracy and performance. Due to the variability of solar energy, the forecasting window is an important aspect of solar energy forecasting that must be integrated into any machine learning model. This study evaluates the suitability of selected machine learning (ML) models comprising Linear Regression, Decision Tree, Random Forest and XGBoost, which have been proven to be effective at forecasting. The data forecasting horizon used was a 24-h window in steps of 30 min. We focused on the first 30-min, 3-h, 6-h, 12-h, and 24-h windows to gain an appreciation of the impact of forecasting duration on the accuracy of prediction using the selected machine learning algorithms. The study results show that Random Forest outperformed all other tested algorithms. It recorded the best values in all evaluation metrics: an average mean absolute error of 0.13, mean absolute percentage error of 0.6, root-mean-square error of 0.28 and R-squared value of 0.89.
Generative AI and Large Language Models in Industry 5.0: Shaping Smarter Sustainable Cities
Authors: Salierno Giulio , Leonardi Letizia , Cabri Giacomo
Published: February 2025

This review paper examines how Generative AI (GAI) and Large Language Models (LLMs) can transform smart cities in the Industry 5.0 era. Through selected case studies and portions of the literature, we analyze these technologies’ impact on industrial processes and urban management. The paper targets GAI as an enabler for industrial optimization and predictive maintenance, underlining how domain experts can work with LLMs to improve municipal services and citizen communication, while addressing the practical and ethical challenges in deploying these technologies. We also highlight promising trends, as reflected in real-world case studies ranging from factories to city-wide test-beds and identify pitfalls to avoid. Widespread adoption of GAI still faces challenges that include infrastructure and lack of specialized knowledge as a limitation of proper implementation. While LLMs enable new services for citizens in smart cities, they also expose certain privacy issues, which we aim to investigate in this study. Finally, as a way forward, the paper suggests future research directions covering new ethical AI frameworks and long-term studies on societal impacts. Our paper is a starting point for industrial pioneers and urban developers to navigate the complexity of GAI and LLM integration, balancing the demands of technological innovation on one hand and ethical responsibility on the other.
Design and Experimental Validation of Wireless Electric Vehicle Charger Control Using Genetic Algorithms and Feedforward Artificial Neural Network
Authors: El Ancary Marouane , Lassioui Abdellah , El Fadil Hassan , El Asri Yassine , Hasni Anwar , Nady Soukaina
Published: February 2025

Integrating electric vehicles (EVs) into the transportation ecosystem is crucial for environmental protection. With the increasing demand for sustainable mobility solutions, wireless power transfer (WPT) systems present a promising method to facilitate the adoption of EVs while reducing carbon footprints. This paper presents a control strategy for the primary side of a WPT charger utilizing a genetic algorithm (GA) combined with a feedforward artificial neural network (ANN). The aim is to optimize charging in constant current (CC) mode and enhance energy transmission efficiency. The proposed approach employs a GA to control the WPT charger, enabling real-time adaptation of charging parameters. The ANN estimates the system’s efficiency, ensuring optimal performance during the charging process. The developed control strategy significantly improved energy transfer efficiency and system stability. Simulation results demonstrate the effectiveness of this new approach, achieving an efficiency of 89.32% in challenging situations of loss of communication with the vehicle. To validate the design procedure, an experimental prototype was constructed, operating at an operational frequency of 85 kHz. Experimental results confirm the proposed design methodology.
Mass Spectrometry-Based Method for Multiple Allergens Control: Application to Bakery Goods
Authors: Luparelli Anna , De Angelis Elisabetta , Pilolli Rosa , Lambertini Francesca , Suman Michele , Monaci Linda
Published: February 2025

In recent years, mass spectrometry has played a key role as a confirmatory method to unequivocally identify multiple allergens, increasing the level of protection of allergic consumers. Despite advances made in methods of development, food processing still represents a critical issue in terms of the detection and accurate quantification of allergens due to chemical/structural modifications that can occur on the protein moiety or interferences of matrix compounds that might impair their final detection. Based on the multi-allergen MS/MS method devised within the ThrAll project, in this paper, we investigated the applicability of the developed method for the detection of traces of allergenic ingredients including egg, milk, soy, almond, hazelnut, peanuts, and sesame in two different kind of food matrices, namely cookies and rusks. The products were produced at laboratory scale in a food pilot plant that underwent different technological and thermal treatments. The challenge was to validate, in these extensively processed foods, the selected proteotypic peptide-markers capable of tracing the culprit ingredients in baked goods despite the processing the foods had undergone for their production. To accomplish this goal, the multi-target method developed on a low-resolution MS platform was transferred to a high-resolution MS system, and the pre-identified markers were also checked and validated on the new platform in order to be considered robust markers able to be indistinctly used on both types of platforms. Finally, the sensitivity of the method in terms of the Limit of Detection (LOD) and Limit of Quantification (LOQ) was calculated and the effect of the processing conditions on allergens detection in both baked goods was also investigated.
Nanolipsome Modified with Inulin and Pea Protein Isolate Improve the Thermal Stability and Slow the Release of Anthocyanin at Simulated In Vitro Digestion and Hot Cocoa Beverage
Authors: Aniya  , Zhang Lianlian , Li Yan , Fu Xiaoji
Published: February 2025

Anthocyanin (ACN) is a natural pigment with various biological activities, but their stability is compromised by external environmental factors, which limits their practical application in food processing. To enhance the stability of anthocyanin, double-layer-modified anthocyanin nanoliposomes (ACN-NLs) were prepared in this study using pea protein isolate (PPI) and inulin (IN) through layer-by-layer assembly in this study. The preparation conditions of unmodified, single-modified, and double-layer-modified nanoliposomes (ACN-NLs, PPI-ACN-NLs, and IN-PPI-ACN-NLs) were optimized via analysis of their average particle size, zeta potential, and encapsulation efficiency (EE). In addition, the structure of the nanoliposomes was characterized via transmission electron microscopy (TEM) and a Fourier transform infrared (FTIR) spectrometer. Furthermore, the thermal stability of nanoliposomes in hot cocoa and their release behavior during in vitro simulated digestion were evaluated. The results indicated that the optimal formulation for IN-PPI-ACN-NLs was 6% PPI and 2% IN. Under these conditions, the IN-PPI-ACN-NLs had a particle size of 270.2 ± 0.66 nm, a zeta potential of −15.76 ± 0.81 mV, and a high EE of 88.6 ± 0.71%. TEM analysis revealed that IN-PPI-ACN-NLs exhibited a spherical core–shell structure, while FTIR confirmed the interaction between ACNs and the encapsulating materials (PPI and IN). Compared with unmodified or monolayer-modified nanoliposomes, IN-PPI-ACN-NLs exhibited thermal stability in beverage systems and enhanced DPPH radical scavenging activity. During in vitro digestion, IN-PPI-ACN-NLs demonstrated a sustained-release effect and improved the digestive stability of ACN. These properties make it a promising functional additive for applications in the food and pharmaceutical industry.
Comparative Analysis of Physics-Guided Bayesian Neural Networks for Uncertainty Quantification in Dynamic Systems
Authors: Xu Xinyue , Wang Julian
Published: February 2025

Uncertainty quantification (UQ) is critical for modeling complex dynamic systems, ensuring robustness and interpretability. This study extends Physics-Guided Bayesian Neural Networks (PG-BNNs) to enhance model robustness by integrating physical laws into Bayesian frameworks. Unlike Artificial Neural Networks (ANNs), which provide deterministic predictions, and Bayesian Neural Networks (BNNs), which handle uncertainty probabilistically but struggle with generalization under sparse and noisy data, PG-BNNs incorporate the laws of physics, such as governing equations and boundary conditions, to enforce physical consistency. This physics-guided approach improves generalization across different noise levels while reducing data dependency. The effectiveness of PG-BNNs is validated through a one-degree-of-freedom vibration system with multiple noise levels, serving as a representative case study to compare the performance of Monte Carlo (MC) dropout ANNs, BNNs, and PG-BNNs across interpolation and extrapolation domains. Model accuracy is assessed using Mean Squared Error (MSE), Mean Absolute Percentage Error (MAE), and Coefficient of Variation of Root Mean Square Error (CVRMSE), while UQ is evaluated through 95% Credible Intervals (CIs), Mean Prediction Interval Width (MPIW), the Quality of Confidence Intervals (QCI), and Coverage Width-based Criterion (CWC). Results demonstrate that PG-BNNs can achieve high accuracy and good adherence to physical laws simultaneously, compared to MC dropout ANNs and BNNs, which confirms the potential of PG-BNNs in engineering applications related to dynamic systems.
The Observed Luminosity Correlations of Gamma-Ray Bursts and Their Applications
Authors: Deng Chen , Huang Yong-Feng , Xu Fan , Kurban Abdusattar
Published: February 2025

Gamma-ray bursts (GRBs) are among the most luminous electromagnetic transients in the universe, providing unique insights into extreme astrophysical processes and serving as promising probes for cosmology. Unlike Type Ia supernovae, which have a unified explosion mechanism, GRBs cannot directly act as standard candles for tracing cosmic evolution at high redshifts due to significant uncertainties in their underlying physical origins. Empirical correlations derived from statistical analyses involving various GRB parameters provide valuable information regarding their intrinsic properties. In this brief review, we describe various correlations among GRB parameters involving the prompt and afterglow phases, discussing possible theoretical interpretations behind them. The scarcity of low-redshift GRBs poses a major obstacle to the application of GRB empirical correlations in cosmology, referred to as the circularity problem. We present various efforts aiming at calibrating GRBs to address this challenge and leveraging established empirical correlations to constrain cosmological parameters. The pivotal role of GRB sample quality in advancing cosmological research is underscored. Some correlations that could potentially be utilized as redshift indicators are also introduced.
Development of Dual-Crosslinking N-Isopropylacrylamide-Based Injectable Hydrogel for Transcatheter Embolization in Swine Model
Authors: Pal Amrita , Zdrale Gabriel , Loui Michelle , Blanzy Jeff , Bichard William , On Thomas J. , Xu Yuan , Alcantar-Garibay Oscar , Preul Mark C. , Vernon Brent L.
Published: February 2025

For decades, endovascular embolization (EE) has been a common technique for the treatment of several vascular abnormalities where the affected vessel is occluded using biocompatible embolic agents. In this work, we developed a NIPAAm-based temperature responsive, dual-crosslinking biocompatible and non-toxic injectable hydrogel system as a liquid embolic agent for EE. The swelling and mechanical properties of the hydrogel were tuned and optimized for its in vivo application. The in vivo study was carried out with nine swine models, including three animals for exploratory study and six animals for acute confirmatory study for the occlusion of surgically created aneurysm and rete mirabile. The polymer hydrogel was delivered into the vascular malformation sites using a catheter guided by angiography. After the injection, the liquid embolic agent was transformed into a solid implant in situ via cross-linking through chemical and thermal processes. During the exploratory study, it was observed that one of the three aneurysms and all the RMs were occluded. During the acute confirmatory study, all the aneurysms and the RMs of six animals were successfully occluded. Overall, our study presents the construction and characterization of a novel injectable hydrogel system capable of successfully occluding vascular malformation in large animals. In the future, after further modification and validation, this material may be used as a liquid embolic agent in clinical studies.
Digital Toxicology Teleconsultation for Adult Poisoning Cases in Saudi Hospitals: A Nationwide Study
Authors: Alharbi Abdullah A. , Muaddi Mohammed A. , Binhotan Meshary S. , Alqassim Ahmad Y. , Alsultan Ali K. , Arafat Mohammed S. , Aldhabib Abdulrahman , Alaska Yasser A. , Alwahbi Eid B. , Sayedahmed Ghali , Alharthi Mobarak , Khan M. Mahmud , Alabdulaali Mohammed K. , Aljerian Nawfal A.
Published: February 2025

Background/Objectives: Poisoning represents a significant global public health challenge, particularly with its complex manifestations in adult populations. Understanding regional epidemiology through digital health systems is crucial for developing evidence-based prevention and management strategies. This nationwide study analyzes hospital-based toxicology teleconsultation data from the Toxicology Consultation Service-Saudi Medical Appointments and Referrals Center (TCS-SMARC) platform to characterize the epidemiological patterns, clinical features, and outcomes of adult poisoning cases across Saudi regions. Methods: We conducted a retrospective cross-sectional analysis of 6427 adult poisoning cases where hospitals sought teleconsultation from the Saudi Toxicology Consultation Service (TCS) from January to December 2023. Descriptive statistics were used to analyze poisoning rates by demographic characteristics, agents responsible for the poisoning, clinical presentations, and management decisions. Population-adjusted rates were calculated using the national census data. Associations between variables were analyzed using cross-tabulations and chi-square tests. Results: Young adults aged 18–35 years constituted most cases (58.67%), with the highest population-adjusted rates observed among those aged 18–24 (5.15 per 10,000). Medicine-related poisonings were the most common across all regions (50.04%), followed by bites and stings (15.31%). Regional analysis indicated relatively uniform poisoning rates across Business Units (BUs) (2.02–2.74 per 10,000). Most cases (87.44%) were asymptomatic, with 91.71% exhibiting normal Glasgow Coma Scale scores, although substance abuse cases had higher rate of severe manifestations (24.34%). Significant seasonal variations were observed (p < 0.001), with peak incidents occurring in the summer (29.25%). Management decisions primarily involved hospital observation (40.27%) and admission (30.34%), with agent-specific variations in care requirements (p < 0.001). Conclusions: This comprehensive analysis demonstrates the effectiveness of Saudi Arabia’s digital health infrastructure in capturing and managing nationwide poisoning data. The integrated digital platform enables real-time surveillance, standardized triage, enhanced access to specialized toxicology services, and coordinated management across diverse geographical contexts. Our findings inform evidence-based recommendations for targeted prevention strategies, particularly for young adults and medicine-related poisonings, while establishing a scalable model for digital health-enabled poisoning management.
The Diagnostic Role of the Platelet-to-Lymphocyte Ratio in Ovarian Cancer: A Systematic Review and Meta-Analysis
Authors: Bizon Magdalena , Olszewski Maciej , Krason Boguslawa , Kochanowicz Elzbieta , Safiejko Kamil , Borowka Anna , Sekita-Krzak Joanna , Pruc Michal , Drozd Anna , Feduniw Stepan , Cander Basar , Szarpak Lukasz
Published: February 2025

Ovarian cancer is among the most lethal gynecologic malignancies, often diagnosed at advanced stages due to a lack of effective screening tools. Recent studies suggest that the platelet-to-lymphocyte ratio (PLR), an indicator of systemic inflammation, may serve as a potential biomarker for diagnosing and staging ovarian cancer. We conducted a systematic review and meta-analysis, adhering to PRISMA guidelines. We searched the PubMed/Medline, Scopus, Web of Science, and EMBASE databases. We pooled data using a random-effects model to assess the sensitivity, specificity, and diagnostic performance of PLR in ovarian cancer. The meta-analysis of 22 studies comprising 5740 participants showed significantly elevated platelet-to-lymphocyte ratio (PLR) values in ovarian cancer patients compared to healthy controls, with a mean difference of 46.84 (p < 0.001). Additionally, PLR demonstrated utility in distinguishing benign from malignant lesions and early-stage from advanced-stage ovarian cancer. While PLR shows potential as a cost-effective and accessible biomarker for ovarian cancer diagnosis and staging, its diagnostic accuracy remains moderate. Therefore, combining PLR with other diagnostic tools enhances clinical decision-making.
Advances in Melanoma and Skin Cancers
Authors: Mallardo Domenico , Basile Debora , Vitale Maria Grazia
Published: February 2025

Cutaneous melanoma, with a continuously rising incidence worldwide, represents one of the most aggressive forms of skin cancer [...]
C/EBP Homologous Protein Expression in Retinal Ganglion Cells Induces Neurodegeneration in Mice
Authors: Mayhew William C. , Kaipa Balasankara Reddy , Li Linya , Maddineni Prabhavathi , Sundaresan Yogapriya , Clark Abbot F. , Zode Gulab S.
Published: February 2025

The progressive loss of retinal ganglion cell (RGC) axons leading to irreversible loss of vision is the pathological hallmark of glaucoma. However, the pathological mechanisms of RGC degeneration are not completely understood. Here, we investigated the role of chronic endoplasmic reticulum (ER) stress in glaucomatous neurodegeneration. To evaluate whether chronic ER stress-induced transcriptional factors, activating transcription factor 4 (ATF4), and C/EBP homologous protein (CHOP) are induced in RGCs; we utilized human donor tissue and the microbead occlusion model of glaucoma. Additionally, we performed the intravitreal injection of adeno-associated virus (AAV) 2 to express CHOP selectively in RGCs in C57BL/6 mice and evaluated its effect on RGC function and structure by pattern electroretinogram (PERG) and whole-mount retina staining with the RBPMS antibody. Here, we report that the ATF4-CHOP pathway is activated in the retinas of human glaucoma donor eyes and a mouse model of ocular hypertension. Further, the expression of CHOP in RGCs led to a significant loss of function, as evidenced by reduced PERG. Notably, the expression of CHOP in the retina induced a significant structural loss of RGCs within 15 weeks of injection. Altogether, our studies indicate that the expression of CHOP in RGCs leads to neurodegeneration in mice.
Metabolome and Transcriptome Analyses Reveal the Correlation Between Fructan Changes and Phytohormone Regulation During Tuber Sprouting of Helianthus tuberosus L.
Authors: Wen Ya , Zhou Zhenjie , Guo Xiaozhu , Li Juan , Wang Gui , Sun Xuemei
Published: February 2025

Jerusalem artichoke (Helianthus tuberosus L.) reproduces asexually through tubers, which are rich in fructan-type carbohydrates and serve as the primary processing organ. Plant hormones may regulate the sprouting process of tubers, but the changes in fructans and their regulatory mechanisms in relation to hormones remain unclear. This study utilized two varieties of Jerusalem artichoke, “Qingyu No.1” and “Qingyu No.3”, to analyze the changes in the proportion of carbohydrates (especially fructans) in total sugars during the sprouting process. Metabolomic and transcriptomic analyses were conducted at three selected sprouting stages. The results indicated that during tuber sprouting, carbohydrates such as fructans play a regulatory role through conversion activities. Multi-omics analysis revealed that jasmonic acid and salicylic acid promote Jerusalem artichoke sprouting through metabolism and are involved in the plant hormone signal transduction process. Differentially expressed genes related to hormone signaling were screened and divided into three groups based on expression levels. It was found that the proportion of carbohydrates is highly correlated with the expression of hormone-related genes in the sprouts, suggesting that plant hormones may regulate carbohydrate metabolism during the sprouting of Jerusalem artichoke tubers. In conclusion, these results preliminarily elucidate the regulatory mechanisms of plant hormones in Jerusalem artichoke tuber sprouting, aiming to provide a theoretical basis for the production and processing of Jerusalem artichoke.
CYP4X1 Expression Is Associated with Metastasis and Poor Prognosis in Patients with Colorectal Cancer
Authors: Kim Sooyoun , Kim Hakchun , Hong Inpyo , Lee Minho , Kim Hyeongjoo , Kwak Hyoungjong , Kim Chang-Jin , Kang Donghyun , Ahn Taesung , Baek Moojun , Jeong Dongjun
Published: February 2025

Globally, the mortality rate of colorectal cancer (CRC) remains high. Despite the development of various treatments, such as targeted therapy and immunotherapy, colorectal cancer continues to be a serious health issue worldwide. Identifying new biomarkers is essential for improving prognosis and tailoring targeted therapies for CRC. This study aims to elucidate the role of CYP4X1 in CRC and its association with patient survival and clinicopathological parameters. Using TCGA databases like GENT2, UALCAN, and GEPIA, we analyzed CYP4X1 expression in CRC and normal tissues. Our analysis revealed a significant increase in CYP4X1 expression in CRC tissues compared to normal tissues. And CYP4X1 high expression was strongly associated with advanced TNM stage, poor tumor differentiation, deeper invasion, and lymph node metastasis. Kaplan–Meier analysis revealed that high CYP4X1 expression correlated with shorter survival times. To investigate the relationship between CYP4X1 expression and colon cancer, WST-1, Transwell, and colony formation assays were performed using colon cancer cells with siRNA-mediated CYP4X1 downregulation. CYP4X1 downregulation significantly inhibited cell proliferation, invasion, migration, and colony formation in vitro. Furthermore, the tumor-forming ability in mice injected with cell lines where CYP4X1 expression was suppressed decreased. In conclusion, CYP4X1 overexpression is closely linked to CRC progression as an independent prognostic marker and potential therapeutic target.
Identification of Thyroid Genes Whose Expression Is Altered by Neonatal Irradiation in Rats
Authors: Fujimoto Nariaki , Matsuu-Matsuyama Mutsumi , Nakashima Masahiro
Published: February 2025

Childhood radiation is a risk factor for thyroid cancer that became well known after the Chernobyl nuclear plant accident. Although these human cases have been extensively studied, the mechanisms underlying childhood susceptibility to radiation-induced thyroid cancer have yet to be explained. Our previous study showed that neonatal X-irradiation resulted in long-term alterations in the mRNA expression of thyroid cancer-related marker genes, which may be a critical mechanism for understanding the higher radiation sensitivity in young patients. In this study, RNA sequencing (RNA-Seq)-based gene expression analysis was employed to identify thyroid genes whose mRNA expression was changed by neonatal irradiation. Male Wistar rats aged 1 week and 4 months were subjected to cervical X-irradiation at 4 Gy. After 8 weeks, total RNA was extracted from the thyroid and subjected to RNA-Seq analysis to identify differentially expressed genes following irradiation. We identified five upregulated genes (i.e., Adm2, Vnn1, Snph, Gria3, and Cpa4) and one downregulated gene (i.e., Crtac1) explicitly altered by neonatal radiation exposure. Western blotting confirmed the corresponding changes in CPA4 and CRTAC1 expression. The gene expressions identified were also altered in thyroid tumors induced by an iodine-deficient diet. These long-term changes in thyroid gene expression caused by neonatal irradiation may be involved in the increased risk of thyroid carcinogenesis.
A Graduate Level Personalized Learning Environment in the Field of f-NIRS Signal Processing
Authors: Persano Adorno Dominique , Giaconia Giuseppe Costantino
Published: February 2025

Active student involvement and instruction through experience in everyday contexts are pedagogical approaches suitable to promote inquiry-based learning and improve learners’ cognitive skills. Nevertheless, many university and postgraduate courses offer lecture-based instructions of theoretical concepts to the students; little attention is still devoted to design hands-on activities, to improve practical/technical competencies and enhance students’ effective understanding of the concepts. The development of a personalized, student-centered learning environment that encourages teamwork and inquiry-based learning aligns with the contemporary push for interdisciplinary education in bioengineering fields. This is particularly relevant for fostering expertise in emerging technologies like functional Near-Infrared Spectroscopy (f-NIRS). In this framework, this paper reports a lab activity for bioelectronic engineering and/or biomedical science students focused on analyzing prefrontal cortex activation during a memory task, processing the f-NIRS signals. This pilot activity, conducted at the University of Palermo (Italy), involved Master’s and Ph.D. students working in teams to address challenges in experimental design. The study combines cutting-edge biosignal detection techniques with innovative educational strategies, offering substantial contributions to both bioengineering and educational research. The outcomes suggest that a hands-on and student-centered laboratory, experienced through a methodical sequence of self-directed learning activities, could considerably boost the student motivation to learn and the level of engagement in bioengineering and biosciences.
Digital Competences of Digital Natives: Measuring Skills in the Modern Technology Environment
Authors: Pongrac Danijela , Alić Marta , Cafuta Brigitta
Published: February 2025

The fourth industrial revolution has ushered in a new era in which technology is seamlessly integrated into daily life. The digital transformation has created new media formats that require the development of robust digital skills to navigate this landscape. By utilising the Youth Digital Skills Indicator (yDSI) and integrating it with the Digital Competence Framework for Citizens (DigComp 2.2), this research examines media habits and digital competences among Croatian youth aged 10–24, corresponding to Generations Alpha and Z. A sample of 231 participants across three competence domains—information literacy, security and communication—revealed statistically significant generational differences in the first two areas of digital skills. Furthermore, gender-based analyses, conducted using the Mann–Whitney U-test and Spearman correlations for Likert scale responses, showed no significant differences. These findings deepen our understanding of digital natives, how media habits evolve and influence their digital skills, highlighting the need for more tailored strategies to enhance their competences and bridge generational gaps.
Machine Learning Approaches for Fault Detection in Internal Combustion Engines: A Review and Experimental Investigation
Authors: Srinivaas A. , Sakthivel N. R. , Nair Binoy B.
Published: February 2025

Fault diagnostics in internal combustion engines (ICEs) is vital for optimal operation and avoiding costly breakdowns. This paper reviews methodologies for ICE fault detection, including model-based and data-driven approaches. The former uses physical models of engine components to diagnose defects, while the latter employs statistical analysis of sensor data to identify patterns indicating faults. Various methods for ICE fault identification, such as vibration analysis, thermography, acoustic analysis, and optical approaches, are reviewed. This paper also explores the latest approaches for detecting ICE faults. It highlights the challenges in the diagnostic process and ways to enhance result accuracy and reliability. This paper concludes with a review of the progress in fault identification in ICE components and prospects, highlighted by an experimental investigation using 16 machine learning algorithms with seven feature selection techniques under three load conditions to detect faults in a four-cylinder ICE. Additionally, this study incorporates advanced deep learning techniques, including a deep neural network (DNN), a one-dimensional convolutional neural network (1D-CNN), Transformer and a hybrid Transformer and DNN model which demonstrate superior performance in fault detection compared to traditional machine learning methods.
An Evaluation of the Predatory Function of Orius strigicollis (Poppius) (Hemiptera: Anthocoridae) on Megalurothrips usitatus (Bagnall) (Thysanoptera: Thripidae)
Authors: Fu Zuying , Cheng Yuanrun , Cui Yifan , Xiong Changyu , Cao Ziyu , Wang Ying , Zhang Rong , Liu Chang , Sun Wei , Ban Liping , Tan Yao , Wei Shuhua
Published: February 2025

Megalurothrips usitatus (Bagnall) is one of the most important pests harming alfalfa (Medicago sativa L.) in Ningxia. In the field, Orius strigicollis (Poppius) is abundant. It has a high search efficiency and consumption rate of prey on a wide range of thrips and is often used as a biological control agent for these insects. To understand the predatory function and biological control potential of O. strigicollis on M. usitatus, the predatory ability of adults of O. strigicollis on second-instar larvae and adults of M. usitatus was measured under indoor conditions, and the Holling II and Hassell–Varley models were fitted to calculate the predatory function response, search efficiency, intraspecific interference, and predation preference of O. strigicollis on second-instar larvae and adults of M. usitatus. Our results showed that the predatory ability of O. strigicollis on second-instar larvae of M. usitatus was 78.62, and the theoretical maximum daily predation was 76.92. The predatory ability of O. strigicollis on adults of M. usitatus was 52.79, and the theoretical maximum daily predation was 52.62. The daily predation of O. strigicollis was positively correlated with prey density and negatively correlated with search efficiency. The rate of predatory action on prey decreased with an increasing O. strigicollis density, while the intensity of apportioned competition increased with an increasing O. strigicollis density. The results of the prey preference experiment showed that the preference of O. strigicollis for second-instar larvae of M. usitatus was significantly higher than for adults of M. usitatus. In conclusion, the indoor experiment data can provide an effective reference for the use of O. strigicollis to control M. usitatus infestation, providing an important biological control agent for controlling M. sativa thrips.
Mechanisms and Efficacy of Contrast Therapy for Musculoskeletal Painful Disease: A Scoping Review
Authors: Leonardi Giulia , Portaro Simona , Milardi Demetrio , Bonanno Francesco , Sanzarello Ilaria , Bruschetta Daniele , Sconza Cristiano , Tisano Adriana , Fontana Jacopo Maria , Alito Angelo
Published: February 2025

Background: Contrast therapy (CT) is a non-pharmacological treatment that alternates between cryotherapy and thermotherapy. It helps reduce VAS pain, improve joint ROM, enhance function, alleviate muscle soreness, and manage swelling, while also improving blood circulation. This scoping review summarizes recent studies on its use for musculoskeletal injuries (e.g., exercise-induced muscle damage, ankle sprain), degenerative conditions (e.g., osteoarthritis), and painful disorders (e.g., complex regional pain syndrome), assessing its healing potential compared to other conservative therapies. Methods: PubMed, Scopus, and Cochrane Library were searched to identify relevant publications. Articles were selected using the following inclusion criteria: randomized controlled trials, written in English, published between 2004 and 2024, and addressing the use of CT in the management of musculoskeletal painful conditions. Results: Data from 7 articles and 303 patients with musculoskeletal painful conditions treated with CT were included. There was considerable heterogeneity in terms of treatment protocols, with significant differences in the application method, duration, sequence of individuals in each hot/cold cycle, total treatment time, and the pathologies studied. Nevertheless, all studies showed an improvement in the patients’ initial clinical conditions. Conclusions: This review highlights the lack of guidelines for the clinical use of CT in musculoskeletal painful conditions. The heterogeneity of the studies reviewed (different clinical scores, follow-up periods, data, and samples) makes the results imprecise. In addition, the modest quality of the trials does not allow the authors to draw clear conclusions about the effectiveness of CT compared with other therapies.
Unmasking Cardiovascular Risk in Patients with COPD at Primary Care Settings: The Critical Role of Age, Sex, and Smoking
Authors: Young Claire , Courtenay Aaron , Rajiah Kingston , Abuelhana Ahmed
Published: February 2025

Background: Chronic obstructive pulmonary disease (COPD) is a progressive respiratory condition frequently associated with cardiovascular comorbidities, including ischemic heart disease (IHD), heart failure (HF), and atrial fibrillation (AF). These conditions significantly impact patient outcomes, yet their prevalence and risk factors remain underexplored in primary care settings. This study investigates the role of age, sex, and smoking status in the prevalence of IHD, HF, and AF among patients with COPD managed in general practice settings. Methods: A retrospective analysis was conducted using de-identified electronic health records from eleven general practitioner (GP) practices in Northern Ireland. Patients with COPD were identified through the Quality and Outcomes Framework (QOF) register, and the presence of IHD, HF, and AF was recorded. Statistical analyses included chi-square tests and independent t-tests to examine associations between cardiovascular comorbidities and patient demographics, with significance set at p < 0.05. Results: Among the total registered population of 77,797, there were 1575 patients with COPD, of whom 335 had IHD, 211 had AF, and 116 had HF. Patients with COPD had a significantly higher prevalence of IHD, AF, and HF compared to those without COPD. Age was a strong determinant, with older age groups, particularly those over 75 years, showing a markedly higher prevalence of all three conditions. Sex analysis revealed that male patients with COPD were significantly more likely to have IHD, AF, and HF than females. However, the association between smoking status and the presence of HF, IHD, or AF was not significantly different between current/ex-smokers and non-smokers. Conclusions: The findings highlight the high burden of cardiovascular comorbidities among patients with COPD in primary care and emphasise the need for routine cardiovascular screening. Given the strong influence of age and sex, targeted risk assessment and management strategies should be prioritised for older and male patients with COPD. The lack of association between smoking and cardiovascular comorbidities suggests that additional risk factors should be considered in cardiovascular risk assessment. A more integrated approach to managing COPD and cardiovascular conditions within general practice settings is essential to improve patient outcomes. Future research should focus on evaluating interventions that enhance early detection and multidisciplinary management of cardiovascular comorbidities in patients with COPD.
Clinical Research on Positron Emission Tomography Imaging of the Neuro-Stimulation System in Patients with Cochleo-Vestibular Implants: Is There a Response Beyond the Peripheral Organ?
Authors: Lorente-Piera Joan , Prieto Elena , Ramos de Miguel Ángel , Manrique Manuel , Pérez-Fernández Nicolás , Ramos Macías Ángel , Monedero Afonso Jaime , Sanfiel Delgado Alina , Miranda Ramos Jorge , Alonso Alonso Paula , Arbizu Javier , Manrique-Huarte Raquel
Published: February 2025

Introduction: In patients refractory to vestibular rehabilitation in the management of bilateral vestibulopathy, the cochleo-vestibular implant has emerged as a viable alternative to enhance both audiovestibular function and quality of life. The main objective of this study is to pioneer the use of PET to assess cortical modifications in patients with cochleo-vestibular implants, aiming to evaluate the safety and functional improvements in individuals with bilateral vestibulopathy and severe to profound hearing loss. Methods: A phase I pilot clinical trial was conducted with participants who received a BIONIC-VEST CI24RE cochleo-vestibular implant, with pre- and post-implantation assessments conducted for twelve months. Audiovestibular testing and two PET studies with 18F-FDG under baseline conditions and with active stimulus to observe cortical-level differences were performed. Results: Five patients were included in the study, all of them treated with a cochleo-vestibular implant, none of whom presented postoperative adverse effects. Audiologically, the mean post-implant gain was 56.63 ± 14.53 dB and 50.40 ± 35.54% in terms of speech intelligibility. From a vestibular perspective, the most remarkable findings were observed at the graviceptive pathway level, where a mean posturographic improvement was observed, with a sensory organization test score of 24.20 ± 13.74 and a subjective visual vertical of 1.57° ± 0.79°, achieving, in most cases, results within the normal range (<2.3°) by the end of the follow-up. PET images confirmed that with the electrical stimulus active (implant ON), there was a supratentorial activation pattern, particularly in areas related to somatosensory integration, emotional regulation, and autonomic control. Conclusions: The BIONIC-VEST implant significantly improved the vestibular system, particularly the graviceptive pathway, enhancing balance and SVV and reducing fall risk. PET revealed distinct uptake patterns in baseline and activated conditions, highlighting a cortical-level response with the use of the cochleo-vestibular implant.