bluuebunny/crossref_metadata_2025 huggingface dataset:
Liquidation of Shallow-Lying Post-Mining Excavations
Authors: Macuda Jan , Skrzypkowski Krzysztof , Złotkowski Albert
Published: January 2025

This article presents an example of the treatment of rock mass disturbed by shallow mining of hard coal in the Małopolska voivodeship, Poland. Considering various methods of rock mass recognition and ways of eliminating shallow voids, recipes for sealing slurries containing mainly liquefiers were developed and used in drilling and injection works in a 10 m-long hole. The course and intensity of rock layer deformation phenomena depend on both natural conditions and the mining method used. At a small depth of hard coal mining (up to 100 m below ground level), the fracture zone may reach the ground surface. In such conditions, sinkholes of various sizes may form on the ground surface. The proposed recipes for sealing slurries, as well as the presented technology for carrying out backfilling works, can be very useful at the stage of selecting the method for liquidation of shallow-lying voids in the carboniferous rock mass.
Application of Near-Far Field Conversion to Measurement of Scattering on Bessel Vortex Electromagnetic Wave
Authors: Wu Zhe , Yun Yu , Liu Nengwu , Wu Jiaji , Wu Zhensen , Ma Lingkun , Monorchio Agostino
Published: January 2025

The measurement and analysis of the interaction between Bessel vortex electromagnetic (EM) and several standard targets are presented in this paper. With the aid of the angular spectrum expansion (ASE) method and physics optics (PO) theorem, scattering results on the plates (metal and dielectric) and a sphere could be derived. Furthermore, plane near-field scanning and near-far field conversion methods were implemented to compare the theoretical radar cross section (RCS). In the experiment, the quasi Bessel vortex wave was generated by a holographic metasurface antenna, and the whole measurement was performed in an anechoic chamber. The results of both the theory and measurement show that the scattered fields of the plate and sphere still had characteristics of the vortex EM wave, and the scientificity and accuracy of the measured RCS were verified. Our work involved a vortex scattering experiment in the microwave frequency band, which provides strong support for the application of vortex waves in radar detection and target recognition.
FREDC: A Few-Shot Relation Extraction Dataset for Chinese
Authors: Yilahun Hankiz , Zhao Hangtian , Hamdulla Askar
Published: January 2025

Few-shot relation extraction (RE) is a critical task in natural language processing (NLP), yet benchmark datasets for non-English languages, particularly Chinese, remain scarce. Owing to their narrow focus and insufficient coverage of relation types, extant Chinese datasets typically exhibit limited applicability and it proves difficult to establish a standardized evaluation benchmark. To address this issue, we introduce FREDC, a few-shot RE dataset for Chinese (FREDC) featuring nearly 100 relation categories across general, medical, and financial domains, with over 100,000 annotated instances. FREDC supports diverse experimental setups, including cross-domain and “None-of-the-Above” (NOTA) tasks. To evaluate FREDC, we adapted the baseline RE model designed for English to Chinese and tested across multiple experimental configurations. FREDC has proven to be effective across multiple models. It also posed challenges to cross-domain and NOTA tasks, due to the linguistic complexity and domain-specific features of the dataset. Comparisons with English datasets showed a performance gap of 15–30% on the accuracy. FREDC fills a critical gap by providing a standardized, high-quality resource for Chinese few-shot RE. It offers a robust foundation for advancing multilingual RE research and improving the adaptability of RE models across languages and domains. We provide relevant code snippets to facilitate reproducibility and encourage further research in the field.
Improving the Efficiency of Multimedia Learning and the Quality of Experience by Reducing Cognitive Load
Authors: Ljubojević Miloš , Savić Mihajlo , Mijić Danijel , Vico Grujica
Published: January 2025

The design of multimedia teaching materials and the principles of their presentation to students strongly influence distance learning efficiency. The appropriate design of online educational multimedia content became especially important during the period of the COVID-19 crisis. This study presents a methodology for improving the efficiency of multimedia-based distance learning by reducing the cognitive load. Combining the segmentation principle with pauses and testing questions in the design of multimedia teaching materials has a positive influence on reducing the cognitive load in distance learning. Practice as an instructional element was more efficient if it was used between the multimedia educational segments than after the presentation of complete multimedia material. The obtained experimental results show an improvement in distance learning efficiency and an increase in the students’ quality of experience. The improvement of learning outcomes using the proposed methodology of multimedia segmentation combined with pauses and testing questions can be especially important for distance education in situations such as the COVID-19 pandemic.
Crude Oil Price Forecasting Model Based on Neural Networks and Error Correction
Authors: Zheng Guangji , Li Ye , Xia Yu
Published: January 2025

Crude oil price forecasting contributes to global economic development. This study proposes a hybrid deep learning model for crude oil price forecasting. First, empirical wavelet transform decomposes raw data into multiple. Then, three neural networks generate preliminary forecasts, which are subsequently refined by a reinforcement learning-based ensemble method. Finally, an error correction module handles residuals, further enhancing the forecasting outcomes. Three West Texas Intermediate datasets and additional emergency scenarios were used to validate the hybrid model. The findings indicate that the proposed model achieves superior predictive performance compared with sixteen benchmark methods and three advanced models.
Exploring the Anxiolytic, Antidepressant, and Immunomodulatory Effects of Cannabidiol in Acute Stress Rat Models
Authors: Zlatanova-Tenisheva Hristina , Georgieva-Kotetarova Maria , Vilmosh Natalia , Kandilarov Ilin , Delev Delyan , Dermendzhiev Tihomir , Kostadinov Ilia Dimitrov
Published: January 2025

Cannabidiol (CBD), a non-psychoactive compound derived from Cannabis sativa, is believed to have anxiety-reducing and antidepressant effects. However, existing data are inconsistent, likely due to variations in experimental designs, dosages, and stress models. This study sought to assess the impact of CBD on anxiety and depression-like behaviors in Wistar rats exposed to acute cold stress, as well as its impact on pro- and anti-inflammatory cytokines. Male rats were treated with CBD (2.5, 5, or 10 mg/kg) or vehicle for 14 days and subjected to behavioral tests, including the elevated plus maze, social interaction, and forced swim tests. Serum levels of cytokines (IL-6, TNF-α, IL-1β, and IL-10) were analyzed post-experiment using ELISA. Results demonstrated a dose-dependent anxiolytic effect of CBD, with significant improvements in social interaction and reductions in anxiety-like behaviors at 5 and 10 mg/kg. All doses of CBD decreased immobility in the forced swim test, suggesting antidepressant effects. Furthermore, CBD selectively lowered IL-6 levels, a key cytokine in acute stress and depression pathogenesis. These findings indicate that CBD has anxiety-reducing and antidepressant properties, partially mediated by modulation of inflammatory processes, particularly IL-6.
Oxyacetylene Flame Forming of Thick Steel Plates
Authors: Joudaki Jalal , Safari Mehdi , Fernandes Fábio A. O.
Published: January 2025

One of the most widely used processes in ship hull plate manufacturing is the flame forming process (FFP). In this work, the fabrication of saddle-shaped specimens with FFP using a spiral irradiating pattern is studied experimentally. The deformation of the deformed plates by FFP based on the spiral irradiating pattern is affected by process parameters such as the pitch of spiral passes (PSP), the radius of the starting circle (RSC), and the number of irradiation passes (NIP). However, in this work, the effects of process parameters on the deformation of SSS are statistically examined by the design of experiment (DOE) method based on response surface methodology (RSM). The experimental and statistical results show that the deformation of flame-formed SSS increases with the increase in RSC and NIP and the decrease in PSP. In addition, the results of the optimization procedure demonstrate that the maximum value of deformations of flame-formed saddle-shaped specimens is achieved by adjusting the process parameters as follows: PSP = 10 mm, RSC = 75 mm, and five NIPs.
Post-Fire Restoration of the Vegetation at the Cemetery of the Tatoi Estate Historical Site
Authors: Kanellou Electra , Doxiadis Thomas
Published: January 2025

The restoration of historical landscapes is crucial for preserving the cultural heritage. This study focuses on the cemetery of the former royal Tatoi estate, a historical site severely damaged by a wildfire in 2021. The fire almost completely eradicated the vegetation on Palaeokastro hill, necessitating a comprehensive vegetation restoration strategy. This research aims to restore the natural environment and historical landscape landmarks and improve future fire protection conditions. This study emphasizes creating a firebreak zone through thinning vegetation, aiding natural regeneration, and planting new seedlings, particularly Aleppo pines and cypresses. We recommend thinning interventions to reduce tree density, which improves the health of the remaining trees and lowers the fire risk. Additionally, the restoration of historical pathways, including cypress-lined routes, is proposed to preserve the cultural landscape. This study underscores the importance of maintaining the historical integrity and enhancing the resilience of the landscape against future fires.
Investigating Stress During a Virtual Reality Game Through Fractal and Multifractal Analysis of Heart Rate Variability
Authors: Lebamovski Penio , Gospodinova Evgeniya
Published: January 2025

This article presents the process of creating a virtual reality (VR) game designed to assess the impact of stress on heart rate variability (HRV). The game features dynamic and challenging scenarios to induce stress responses, incorporating advanced 3D modelling and 3D animation techniques. A study involving 20 volunteers was conducted, with electrocardiographic (ECG) data collected before and during game play. HRV analysis focused on fractal and multifractal characteristics, utilizing detrended fluctuation analysis (DFA) and multifractal detrended fluctuation analysis (MFDFA) methods. DFA results revealed decreased values of α1, α2, and αall, indicating alterations in short-term and long-term correlations under stress. MFDFA further analyzed changes in fluctuation function Fq(s), generalized Hurst exponent Hq, multifractal scaling exponent τ(q), and multifractal spectrum f(α), showing significant differences in these parameters under stress. These findings validate the game’s effectiveness in simulating stress and its impact on HRV. The present study not only demonstrates the relationship between stress and the fractal characteristics of HRV but also offers a new foundation for future applications in psychology, physiology, and the development of VR technologies for stress management.
Temperature-Dependent FTIRS Study of Manganese Oxide Spinel Obtained by Solution Combustion Synthesis (SCS) for Supercapacitor Applications
Authors: Karakoç Taylan , Sall Sécou , Pronkin Sergey N.
Published: January 2025

Solution combustion synthesis (SCS) is often utilized to prepare crystalline nanoparticles of transition metal oxides, in particular Mn oxides. The structure and composition of the final product depend on the conditions of the synthesis, in particular on the composition of metal precursors, its molar ratio to the fuel component, and the mode of heating. In the present work, the study of chemical phenomena that may occur in the SCS process has been studied for the conventional nitrate–glycine synthesis of Mn oxide, as well as for nitrate–citrate–glycine and nitrate–citrate–urea synthesis. In the case of nitrate–glycine synthesis at a 1:1 fuel-to-salt ratio, the formation of a weak complex of Mn(II) and glycine provides the conditions for an instantaneous SCS reaction upon heating, resulting in slight sintering of final oxide nanoparticles. Partial hydrolysis of the Mn precursor during slow solvent evaporation results in the formation of a mixture of oxides, namely MnO and Mn3O4. Formation of MnO is completely suppressed when ammonium citrate is added into the initial mixture. Pure Mn2O3 oxide is obtained from nitrate–citrate synthesis, while the pure Mn3O4 phase is obtained in the case of nitrate–citrate–glycine and nitrate–citrate–urea synthesis, due to the higher temperature generated in the presence of additional fuel. In the presence of citrate, the SCS reaction is slower, resulting in stronger sintering of the nanoparticles. The study of the electrochemical properties of synthesized oxides demonstrates that SCS with the nitrate–citrate–urea mixture provides the highest charge capacitance in 1 M NaOH: 130 F/g at 2 A/g. The impedance characterization of materials allows us to propose a tentative mechanism of degradation of electrode materials during galvanostatic cycling.
Manipulating Intracellular Oxidative Conditions to Enhance Porphyrin Production in Escherichia coli
Authors: Arab Bahareh , Moo-Young Murray , Liu Yilan , Chou C. Perry
Published: January 2025

Being essential intermediates for the biosynthesis of heme, chlorophyll, and several other biologically critical compounds, porphyrins have wide practical applications. However, up till now, their bio-based production remains challenging. In this study, we identified potential metabolic factors limiting the biosynthesis of type-III stereoisomeric porphyrins in Escherichia coli. To alleviate this limitation, we developed bioprocessing strategies by redirecting more dissimilated carbon flux toward the HemD-enzymatic pathway to enhance the production of type-III uroporphyrin (UP-III), which is a key precursor for heme biosynthesis. Our approaches included the use of antioxidant reagents and strain engineering. Supplementation with ascorbic acid (up to 1 g/L) increased the UP-III/UP-I ratio from 0.62 to 2.57. On the other hand, overexpression of ROS-scavenging genes such as sod- and kat-genes significantly enhanced UP production in E. coli. Notably, overexpression of sodA alone led to a 72.9% increase in total porphyrin production (1.56 g/L) while improving the UP-III/UP-I ratio to 1.94. Our findings highlight the potential of both antioxidant supplementation and strain engineering to mitigate ROS-induced oxidative stress and redirect more dissimilated carbon flux toward the biosynthesis of type-III porphyrins in E. coli. This work offers an effective platform to enhance the bio-based production of porphyrins.
TSF-MDD: A Deep Learning Approach for Electroencephalography-Based Diagnosis of Major Depressive Disorder with Temporal–Spatial–Frequency Feature Fusion
Authors: Gan Wei , Zhao Ruochen , Ma Yujie , Ning Xiaolin
Published: January 2025

Major depressive disorder (MDD) is a prevalent mental illness characterized by persistent sadness, loss of interest in activities, and significant functional impairment. It poses severe risks to individuals’ physical and psychological well-being. The development of automated diagnostic systems for MDD is essential to improve diagnostic accuracy and efficiency. Electroencephalography (EEG) has been extensively utilized in MDD diagnostic research. However, studies employing deep learning methods still face several challenges, such as difficulty in extracting effective information from EEG signals and risks of data leakage due to experimental designs. These issues result in limited generalization capabilities when models are tested on unseen individuals, thereby restricting their practical application. In this study, we propose a novel deep learning approach, termed TSF-MDD, which integrates temporal, spatial, and frequency-domain information. TSF-MDD first applies a data reconstruction scheme to obtain a four-dimensional temporal–spatial–frequency representation of EEG signals. These data are then processed by a model based on 3D-CNN and CapsNet, enabling comprehensive feature extraction across domains. Finally, a subject-independent data partitioning strategy is employed during training and testing to eliminate data leakage. The proposed approach achieves an accuracy of 92.1%, precision of 90.0%, recall of 94.9%, and F1-score of 92.4%, respectively, on the Mumtaz2016 public dataset. The results demonstrate that TSF-MDD exhibits excellent generalization performance.
The Secretome of the Inductive Tooth Germ Exhibits Signals Required for Tooth Development
Authors: Birjandi Anahid A , Sharpe Paul
Published: January 2025

Teeth develop from reciprocal signaling between inductive and receptive cells. The inductive signals for tooth development are initially in the epithelium of the developing branchial arch, but later shift to the underlying mesenchyme of a developing tooth germ. The inductive signals that are needed for tooth development have not yet been fully identified. Our lab previously provided a basis for bioengineering new teeth by separating the tooth germ’s epithelial and mesenchyme cells into a single cell population and recombing them. This approach, however, is not clinically applicable as the cells lose their inductive ability when expanded in vitro. In this study, we investigate whether the secretome and small extracellular vehicles (sEV) derived from inductive tooth germ mesenchyme can contribute to inductive signals required for tooth development. To address this, small extracellular vesicles and secretome were purified from inductive tooth germ mesenchyme and characterized. We investigated the proteome of sEV and proteome of inductive tooth germ mesenchyme and the impact of the culture condition and duration on the proteome. Additionally, we investigated the transcriptomic changes in tooth germ epithelium after treatment with sEV from inductive tooth germ mesenchyme. We show that culture duration of inductive tooth germ mesenchyme has an impact on the proteome of sEV purified from these cells. Similarly, culturing these cells in 2D and 3D environments results in different protein content. Proteome unique to sEV derived from inductive shows an association with multiple signaling pathways related to tooth development. Our RNASeq results show that treatment of tooth germ epithelial cells with small extracellular vesicles derived from inductive tooth germ mesenchyme results in an increased expression of some of the known odontogenic genes. Whilst further analysis is required to harvest the full potential of these sEV, our results suggests that extracellular vehicles contribute to signals required during tooth development, potentially through modulation of cellular metabolism and ECM organization.
Chia (Salvia hispanica) Seed Oil Modulates the Haemato-Immunological Response, Antioxidative Status and Cytokine Gene Expression of Tropical Freshwater Teleost, Labeo rohita
Authors: Gupta Sanjay Kumar , Gupta Rajan , Gupta Akruti , Foysal Md Javed , Krishnani Kishore Kumar
Published: January 2025

The present investigation attempts to evaluate the impact of the dietary inclusion of chia (Salvia hispanica) seed oil (CSO) on the indices of haemato-immunology, metabolic enzymes, and expression of immune-responsive cytokine genes in Labeo rohita (rohu) fingerlings. The responses were observed in a 60-day feeding trial, set up with a total of 180 rohu fingerlings (19.74 ± 0.33 g) randomly allocated to four treatment groups with three replicates each. The groups were fed with a basal diet incorporated with 0%, 1.0%, 2.0%, and 3.0% CSO, denoted as control, CSO (1), CSO (2), and CSO (3), respectively. Significant (p < 0.05) augmentation of hematological indices such as total protein and globulin levels was observed in the group fed a 1.0% CSO-supplemented diet. Serum glucose, cholesterol, triglycerides, and complement reactive protein levels declined, whereas marker anti-oxidative enzymes (SOD, CAT, and GST) and protein metabolic enzymes (ALT and AST) increased (p < 0.05) in the lowest CSO-supplemented group. A significant upregulation of inflammatory cytokine viz. IL-1β, IFN-γ, TNF-α, and TLR22 alongside downregulation of IL-10 was noted in various tissues. The results support the inclusion of 1.0% CSO as a prospective dietary vegan substitute to fish oil in rohu aquaculture.
A Genetic and Environmental Analysis of Inflammatory Factors in Chronic Widespread Pain Using the TwinsUK Cohort
Authors: Cherny Stacey S. , Livshits Gregory , Williams Frances M. K.
Published: January 2025

Chronic widespread musculoskeletal pain (CWP), a significant health issue affecting individuals and society, is often diagnosed as part of fibromyalgia but is not generally considered inflammatory. This study investigated the relationship between blood-based inflammatory factors and CWP in 904 individuals from the TwinsUK cohort. Participants, free of major inflammatory conditions, completed questionnaires to assess CWP. Plasma samples were analysed using the Olink panel, alongside assays for C-reactive protein (CRP) and Apolipoproteins A1 and B. No significant associations were observed between CWP and inflammatory factors after adjusting for multiple testing. Twin modelling revealed significant heritability for both CWP and inflammatory factors, with genetic covariance observed between CWP and several inflammatory factors. Additive Bayesian network modelling suggested that any association between CWP and inflammatory factors is mediated by body mass index (BMI). These findings emphasize the complexity of CWP and its potential reliance on factors beyond inflammation, such as BMI, which strongly correlates with CRP and other inflammatory markers. Future research should explore additional molecular, genetic, and environmental contributors to CWP variability and investigate clinical factors or covariates that may obscure relationships with inflammation, providing a more comprehensive understanding of this multifaceted condition.
Effects of the Chemical and Mechanical Pre-Treatment of Brown Seaweed on Biomethane Yields in a Batch Configuration
Authors: Marshall Ashleen , Oyekola Oluwaseun
Published: January 2025

Brown seaweed could be a viable option for biogas production, with the added advantage of not competing with land-based crops, which negates the food vs. fuel argument. To optimise the process, this research investigates using mechanical and chemical pre-treatment to increase the biomethane yield of seaweed. The biomethane potential, biodegradability index, and biomethane yields were determined as well as the kinetics based on the hydrolysis of the anaerobic digestion process. Mechanical pre-treatment showed the highest increase in methane yield for the smaller size (<1.7 mm), recording yields of 126.16 mL/g VS after 28 days when compared to 31.54 mL/g VS for the control (2–3 mm). Chemical pre-treatment yielded higher methane rates (34.59–60.33 mL/g VS) than the control, but not as high as the mechanical pre-treatment processes. First-order kinetics described the anaerobic digestion process, with k-values between 0.050 and 0.106. The biodegradability index was between 0.145 and 0.580. The research increased the knowledge base of the potential of the Ecklonia Maxima seaweed to produce biogas. Careful consideration of the impact on the overall process must be completed to determine the advantages or disadvantages of including a pre-treatment step in the process under consideration.
Clinical Electrophysiology and Mathematical Modeling for Precision Diagnosis of Infertility
Authors: Cavalari Fernanda Carvalho , Mendes Paola Sulis , Zaniboni Bruna Antunes , Royer Carine , Taques Bárbara Ogliari Martins , Cesca Karina , Aragón Marcela , Silva Fátima Regina Mena Barreto
Published: January 2025

How can cellular electrophysiology measurements and mathematical modeling of ionic channels help to identify pivotal targets in disease-related cell signaling? The purpose of this review is to highlight the advantages and disadvantages of using both of these complementary techniques to determine molecular targets that may be structurally or functionally altered in a specific disease. In addition, both electrophysiology measurements and mathematical modeling may improve coordinated drug development, accelerate the prediction of new drugs, and facilitate repositioning of pharmacological agents. This review focuses on the data obtained from electrophysiology and mathematical model approaches, including intracellular recording, cellular patch clamp measurements, and the Hodgkin and Huxley equation, as key precision methodologies. To this end, seminiferous tubules, the Sertoli cell line (TM4), and/or primary cultures of Sertoli cells were used to explore the role of follicle-stimulating hormone (FSH), thyroid hormones, retinol, testosterone, and 1,25(OH)2 vitamin D3 in the coordinated activation or inhibition of ionic channels essential for male fertility. Based on the discussed data, Sertoli cells precisely regulate their biological activity by coordinating channel activity according to the hormonal environment and the nutritional requirements required for germ cell development.
Development of a Pain Measurement Device Using 3D Printing and Electronic Air Pressure Control
Authors: Sierra José Manuel , Fernández Mª del Rocío , Cortizo José Luis , González Juan Díaz
Published: January 2025

This article describes the design of a wireless pain monitor system, also known as a pain meter, which can be used to diagnose people with fibromyalgia. Background/Objectives: As the test should be done while a simultaneous Magnetic Resonance Imaging (MRI) scan is being performed on the patient to observe their brain activity, the device must not have metallic components. Methods: Solid modelling and additive manufacturing were used for the manufacture of the device, an electropneumatic control has also been defined, and several prototypes were manufactured and tested. The work focuses on the validation of the designed pain meter, built by Material Extrusion (MEX) technology in different materials and with different printers. The surface finishes and manufacturing tolerances of the critical parts were tested, and their suitability for the necessary functions is verified. Conclusions: A proper mechanical pain meter device has been designed to be used in fibromyalgia diagnosis without metal components nor wires, which is therefore compatible with simultaneous MRI.
Assessment of Changes in Executive Functions and Attention of Cadets as a Result of Military Parachute Jumping
Authors: Jamro Dariusz , Kociuba Marek , Lachowicz Maciej , Korytko Pawel , Zurek Grzegorz
Published: January 2025

Objectives: This study analyzed the effects of parachute jump stress on the executive functions and attention of cadets. Executive functions, which includes processes such as attentional control and cognitive flexibility, are crucial for soldiers, especially in situations requiring rapid decision-making. Parachute jumping, as an intense stressor, mobilizes cognitive resources, which can lead to short-term improvements in executive functions. Methods: A total of 64 cadets divided into control (N = 32) and experimental (N = 32) groups participated in the study. The experimental group performed a parachute jump and then took the Color Trails Test, assessed both before and after the jump. Results: The results showed significant improvements in executive functions, in particular, sustained and alternating attention, sequential information processing, and monitoring one’s own behavior, suggesting a positive effect of stress on selected executive functions. Conclusions: The results indicate that intense, short-term stress can positively affect executive functions, although this effect may depend on the type of task and the participants’ experience of exposure to intense stressful stimuli. The study makes an important contribution to the design of future military training, considering the importance of mobilizing cognitive resources in response to short-term stress.
EEG-Based ADHD Classification Using Autoencoder Feature Extraction and ResNet with Double Augmented Attention Mechanism
Authors: Bansal Jayoti , Gangwar Gaurav , Aljaidi Mohammad , Alkoradees Ali , Singh Gagandeep
Published: January 2025

Background: Attention-Deficit/Hyperactivity Disorder (ADHD) represents a widely prevalent and heterogeneous neurodevelopmental condition in pediatric populations, often exhibiting a substantial propensity to persist into adulthood. ADHD is a multifaceted disorder that resists straightforward diagnostic tests. Clinicians must invest substantial time and effort to secure an accurate diagnosis and implement effective treatment. ADHD diagnosis is primarily based on psychiatric tests, as there is currently no clinically utilized objective diagnostic tool. Nonetheless, several studies in have documented endeavors to create objective instruments designed to assist in the diagnostic process of ADHD, aiming to enhance diagnostic accuracy and reduce subjectivity. Method: This research endeavor sought to establish an objective diagnostic modality for ADHD through the utilization of electroencephalography (EEG) signal analysis. With the use of innovative deep learning techniques, this research seeks to improve the diagnosis of ADHD using EEG data. To capture complex patterns in EEG data, this study proposes a double-augmented attention mechanism ResNet-based model. Using an autoencoder for feature extraction, the Reptile Search Algorithm for feature selection, and a modified ResNet architecture for model training comprise the technique. Results: AUC, F1-score, accuracy, precision, recall, and other standard classifiers like Random Forest and AdaBoost were utilized to compare the model’s performance. By a wide margin, the proposed ResNet model outperforms the traditional models with a 99.42% accuracy, 99.03% precision, 99.82% recall, and 99.42% F1-score. Conclusions: ROC AUC score of 0.99 for the model underscores its remarkable capability to differentiate between children with and without ADHD, thereby minimizing misclassification errors and improving diagnostic precision.
Exploring the Practice of Dual Vaping: Health Risks and Behavioral Patterns in Nicotine and Cannabis E-Cigarette Users
Authors: Vaccari Bongetta Giovanna Nelda , Ferreira França Raony , Pozzolo Pedro Maria Olivia , Leopoldo Kae , Florence Luiza Larrubia Alvares , Blaas Israel Kanaan , Koch Gimenes Gislaine , Torales Julio , Ventriglio Antonio , de Berardis Domenico , Castaldelli-Maia João Mauricio
Published: January 2025

Background: E-cigarettes, initially designed for nicotine consumption, are now increasingly being used to smoke cannabis, resulting in a growing trend known as “dual vaping”. This term describes individuals, referred to as “dual users”, who use e-cigarettes for both substances. This study aims to review and analyze existing research on dual vaping, with a focus on the associated health risks and behavioral patterns. Methods: A narrative review of the literature was conducted using PubMed. Studies focusing on individuals who use electronic cigarettes for vaping tobacco and cannabis, either chronically or episodically, were examined. Relevant articles were identified and thematically synthesized to provide a comprehensive overview of the topic. Results: Dual vaping was found to be prevalent among younger men, White and Hispanic populations, and individuals with higher economic status and educational level. The use of one substance was shown to predispose individuals to the use of the other, often leading to concurrent use of both substances. Peer influence and positive expectations regarding e-cigarettes were identified as significant predictors of dual use. Dual vapers exhibited a higher susceptibility to respiratory and systemic symptoms compared to those who exclusively vaped nicotine or cannabis. Moreover, a notable prevalence of psychiatric disorders, such as substance use disorders, anxiety, and depression, was observed in this group. Fruit-flavored e-cigarettes were the most preferred option among dual vapers when using both nicotine and cannabis. Conclusions: Current evidence is insufficient to fully elucidate the long-term impacts of dual vaping on physical and mental health, particularly when compared to individuals who have never vaped. Further studies are needed to gain a more comprehensive understanding of this behavior.
Adapting and Implementing a Blended Collaborative Care Intervention for Older Adults with Multimorbidity: Quantitative and Qualitative Results from the ESCAPE Pilot Study
Authors: Schulze Josefine , Lühmann Dagmar , Nagel Jonas , Regner Cornelia , Zelenak Christine , Bersch Kristina , Herrmann-Lingen Christoph , Burg Matthew M. , Herbeck-Belnap Birgit
Published: January 2025

Multimorbidity poses significant challenges for patients and healthcare systems, often exacerbated by fragmented care and insufficient collaboration across providers. Blended Collaborative Care (BCC) is a promising strategy to address care complexity by partnering care managers (CMs) with primary care providers (PCPs) and specialists. This study aimed to adapt and pilot a BCC intervention for patients aged 65+ with heart failure and physical–mental multimorbidity. Our objectives were to assess the feasibility of the study procedures, patient recruitment, participant satisfaction and acceptability, and to identify necessary adjustments for improving intervention delivery. We evaluated goal attainment and intervention fidelity through standardised electronic documentation by CMs, and patient acceptance and satisfaction through semi-structured interviews. A monocentric, one-arm pilot study involved nine patients with a mean of 6.7 contacts with their CM over three months. Patients’ health goals primarily focused on lifestyle changes and psychosocial support. The intervention was generally well-accepted, with no reported negative consequences. Difficulties in establishing working alliances with PCPs were a barrier to effective implementation. The analysis indicated the need for minor procedural adjustments. Next steps include launching the ESCAPE trial, a large randomised-controlled trial across different European healthcare systems and developing strategies to facilitate PCP involvement.
Exploring Logical Intuition in Base-Rate Problems Using the Instructional Manipulation Paradigm
Authors: Zhu Debiao , Lu Ping , Hu Zhujing , Yang Jianyong , Nie Dandan
Published: January 2025

The default–interventionist model of dual-process theories proposes that stereotype descriptions in base-rate problems are processed using Type 1 processing, while the evaluation of base rates depends on Type 2 processing. The logical intuition view posits that people can process base-rate information using Type 1 processing. This study examined the logical intuition view using the instructional manipulation paradigm. Participants judged the probability that a character in a base-rate problem belonged to a particular group based on either their beliefs or statistics and then rated their confidence in their responses. Results showed that a belief–statistics conflict affected both statistics- and belief-based judgments, resulting in lower probability estimates, longer response times, and lower confidence ratings for conflict items compared to no-conflict items, suggesting participants intuitively processed base rates such that they influenced rapid belief judgments. This intuitive logic effect was observed for extreme base rates, moderate base rates, and moderate base rates with small absolute values. These findings are inconsistent with the default–interventionist model but align with dual-process theories emphasizing logical intuition. The study provides additional evidence for human rationality.
The Mediating Roles of Resilience and Flow in Linking Basic Psychological Needs to Tertiary EFL Learners’ Engagement in the Informal Digital Learning of English: A Mixed-Methods Study
Authors: Gao Yang , Wang Xiaochen , Reynolds Barry Lee
Published: January 2025

Resilience and flow are crucial in language education, yet most research focuses on formal learning environments, with limited studies on their impact in informal settings. This study explores the relationship between basic psychological needs and engagement in the context of informal digital English learning (IDLE). Using a mixed-methods design, data were collected from 512 Chinese EFL learners. Structural equation modeling and NVivo analysis were applied to quantitative and qualitative data, respectively. The findings reveal that resilience fully mediates the relationship between basic psychological needs and engagement, serving as an adaptability enhancer, persistence promoter, stress buffer, self-efficacy builder, and emotional regulation facilitator. Conversely, flow partially mediates this relationship, though perceived competence does not significantly predict flow in this context. Building on this, flow contributes as an intrinsic motivation driver, positive cycle creator, external pressure mitigator, and efficiency enhancer. This research underscores the important role of resilience and flow in IDLE among Chinese university EFL students. By highlighting these mediating roles, the study provides valuable insights for enhancing the effectiveness of IDLE experiences, contributing to the broader discourse on language education in the digital age.
Digital Financial Literacy and Life Satisfaction: Evidence from South Korea
Authors: Choung Youngjoo , Pak Tae-Young , Chatterjee Swarn
Published: January 2025

Digital financial literacy is an emerging concept that refers to the ability to effectively use digital tools, platforms, and services to manage personal finances. While previous studies have explored the behavioral effects of digital financial literacy, less is known about its broader well-being implications for financial consumers. In this study, we aim to examine the association between digital financial literacy and life satisfaction in a developed country context. Digital financial literacy was measured using a multidimensional scale that encompasses financial knowledge, digital literacy, digital financial service awareness, practical know-how of digital financial services, and self-protection against digital financial fraud. Using data of 1615 Korean adults who currently use digital financial services, this study estimated a series of regressions linking life satisfaction to digital financial literacy and covariates. The results showed a significant association between digital financial literacy and life satisfaction, with self-protection against fraud being the most influential subdimension. Notably, financial knowledge was not associated with life satisfaction when other dimensions of digital financial literacy were independently included in the regression models. These findings highlight the importance of digital skills and knowledge in navigating digital financial services. They also emphasize the need for targeted policies, financial education initiatives, and consumer protection measures to address the lack of digital financial literacy among marginalized populations.
Impact of Ethical Leadership on Autonomy and Self-Efficacy in Virtual Work Environments: The Disintegrating Effect of an Egoistic Climate
Authors: Santiago-Torner Carlos , Corral-Marfil José-Antonio , Jiménez-Pérez Yirsa , Tarrats-Pons Elisenda
Published: January 2025

Ethical management is key to ensuring organizational sustainability, through resources such as autonomy or self-efficacy. However, economic and social uncertainty occasionally leads to adaptive responses that prioritize profit as the primary interest, blurring the integrating role of ethical leadership. There are a number of studies that support this reality in a virtual work environment. This sector-specific and cross-sectional research explores how ethical leadership influences self-efficacy among teleworkers, through active commitment to job autonomy, and how an egoistic climate hinders this influence. The analysis is quantitative and correlational, and the sample includes 448 teleworkers. A model of conditional indirect effects, including both a mediation process and a moderation process, is used. The results support that ethical leadership enhances followers’ self-efficacy through a redistribution of responsibilities, which increases the perception of autonomy. However, when ethical leadership coincides with a climate that has opposing interests, such as an egoistic climate, ethical leadership is unable to counteract it, and its effect on self-efficacy gradually diminishes. The benefits of this management style are widely known, but it is crucial to understand under what circumstances it loses efficacy. This research presents a new theoretical model that contributes to the existing literature on ethical leadership. Lastly, organizations that embrace ethical leadership can avoid the emergence of ethical climates disconnected from collective benefit, such as those characterized by selfishness, which hinder prosocial motivation. In this context, ethical leadership fosters the development of high-quality interpersonal relationships with followers, which are considered essential for creating an environment conducive to group learning. Consequently, change management in organizations necessitates the adoption of an ethical system that enhances self-efficacy through moral principles, rather than relying solely on individualistic aspects.
Tristetraprolin Family Members and Processing Bodies: A Complex Regulatory Network Involved in Fatty Liver Disease, Viral Hepatitis and Hepatocellular Carcinoma
Authors: Gellée Noémie , Legrand Noémie , Jouve Mickaël , Devaux Pierre-Jean , Dubuquoy Laurent , Sobolewski Cyril
Published: January 2025

Chronic liver diseases, such as those encountered with obesity, chronic/abusive alcohol consumption or viral infections, represent not only major public health concerns with limited therapeutic options but also important risk factors for the onset of hepatocellular carcinoma (HCC). Deciphering the molecular traits underlying these disorders is of high interest for designing new and effective treatments. The tristetraprolin (TTP) family members are of particular importance given their ability to control the expression of a wide range of genes involved in metabolism, inflammation and carcinogenesis at the post-transcriptional level. This regulation can occur within small cytoplasmic granules, namely, processing bodies (P-bodies), where the mRNA degradation occurs. Increasing evidence indicates that TTP family members and P-bodies are involved in the development of chronic liver diseases and cancers. In this review, we discuss the role of this regulatory mechanism in metabolic-dysfunction-associated steatotic liver disease (MASLD), alcohol-related liver disease (ALD), hepatic viral infections and HCC.
Biocatalysis for Lignin Conversion and Valorization: Driving Sustainability in the Circular Economy
Authors: Nargotra Parushi , Sharma Vishal , Wang Hui-Min David , Shieh Chwen-Jen , Liu Yung-Chuan , Kuo Chia-Hung
Published: January 2025

In recent years, lignin derived from lignocellulosic biomass has emerged as a critical component in modern biorefinery systems. The production yield and reactivity of lignin are critical factors for advancing the research and development of lignin-derived biochemicals. The recovery of high-purity lignin, along with carbohydrates, is accomplished through the application of various advanced pretreatment techniques. However, biological pretreatment using lignin-degrading enzymes to facilitate lignin depolymerization is an environmentally benign method for the sustainable production of valuable products that occurs under mild conditions with high substrate specificity. The current review presents the role of biocatalysis in lignin valorization, focusing on lignin-degrading enzymes that facilitate different bond cleavage in the lignocellulosic biomass. The review also highlights the recent advancements in enzyme engineering that have enabled the enhancement of enzyme stability and catalytic efficiency for improving lignin valorization processes. Furthermore, the integration of omics technologies that provide valuable insights into the microbial and enzymatic pathways involved in lignin degradation is presented. The challenges and future prospects in this emerging field of study for a biorefinery concept are also outlined for improving lignin depolymerization efficiency.
The Effect of Corn Stover Carbon-Based Bimetallic Catalysts on the Depolarization Electrolysis Reaction of Sulfur Dioxide for Hydrogen Production
Authors: Qi Tiantian , Li Yingxia , Liu Feng , Qu Yongshui , Wei Quanyuan
Published: January 2025

The hybrid sulfur cycle (HyS), as one of the most promising thermochemical cycles for hydrogen production, has received widespread attention in recent years. The HyS contains the sulfur dioxide depolarization electrolysis (SDE) reaction that produces hydrogen, and the anodic reaction process that determines the efficiency of the SDE reaction has become a research focus in this field. In this study, high-temperature pyrolysis technology was used to prepare biomass-based carbon materials from corn stover and analyze their catalytic performance when loaded with platinum–chromium bimetal as an anode catalyst in the SDE reaction. The system investigates the influence of the structure of various components of corn stover (cellulose, holocellulose, and lignin), carbonization conditions, etc., on the structure of the stover-based carbon carrier and then uses it to prepare platinum–chromium bimetallic catalysts for characterization and electrochemical analysis. The results show that the holocellulose-based porous carbon has excellent performance, with a specific surface area reaching 519.81 m2/g and a pore volume of 0.65 cm3/g, and the catalyst can achieve a current density of 780 mA/cm2 under a voltage of 1.2 V, showing excellent electrocatalytic performance in the SDE. Therefore, corn stover carbon as a carbon carrier has very high application prospects.
Inflammatory Pathways in Coronary Artery Disease: Which Ones to Target for Secondary Prevention?
Authors: Cheng Wan-Hei , Wang Ying
Published: January 2025

Coronary artery disease (CAD), the build-up of atherosclerotic plaques on the wall of blood vessels, causes adverse cardiovascular events. Secondary prevention focuses on treating patients with existing plaques to prevent disease progression. Recent studies have shown that inflammation is an independent risk factor that drives disease progression, and targeting inflammation could be an effective therapeutic strategy for secondary prevention. In this review, we highlighted the roles of several inflammatory pathways in rupture and erosion, two major processes through which established plaques lead to adverse cardiovascular events. In the past 15 years, numerous clinical trials have tested the therapeutic potential of targeting these pathways, including neutralizing inflammatory cytokines and blocking signaling transduction of the inflammatory pathways. Only colchicine was approved for clinical use in patients with CAD. This is primarily due to the multifaceted roles of inflammatory pathways in disease progression. Commonly used pre-clinical models provided robust information for the onset of early disease but limited understanding of the inflammatory network in established plaques. This review will summarize lessons learned from successful and failed clinical trials to advocate for assessing inflammation in established plaques before designing therapeutics for secondary prevention.