bluuebunny/crossref_metadata_2025 huggingface dataset:
Fidex and FidexGlo: From Local Explanations to Global Explanations of Deep Models
Authors: Bologna Guido , Boutay Jean-Marc , Boquete Damian , Leblanc Quentin , Köprülü Deniz , Pfeiffer Ludovic
Published: February 2025

Deep connectionist models are characterized by many neurons grouped together in many successive layers. As a result, their data classifications are difficult to understand. We present two novel algorithms which explain the responses of several black-box machine learning models. The first is Fidex, which is local and thus applied to a single sample. The second, called FidexGlo, is global and uses Fidex. Both algorithms generate explanations by means of propositional rules. In our framework, the discriminative boundaries are parallel to the input variables and their location is precisely determined. Fidex is a heuristic algorithm that, at each step, establishes where the best hyperplane is that has increased fidelity the most. The algorithmic complexity of Fidex is proportional to the maximum number of steps, the number of possible hyperplanes, which is finite, and the number of samples. We first used FidexGlo with ensembles and support vector machines (SVMs) to show that its performance on three benchmark problems is competitive in terms of complexity, fidelity and accuracy. The most challenging part was then to apply it to convolutional neural networks. We achieved this with three classification problems based on images. We obtained accurate results and described the characteristics of the rules generated, as well as several examples of explanations illustrated with their corresponding images. To the best of our knowledge, this is one of the few works showing a global rule extraction technique applied to both ensembles, SVMs and deep neural networks.
Evaluation and Early Detection of Downy Mildew of Lettuce Using Hyperspectral Imagery
Authors: Ban Songtao , Tian Minglu , Hu Dong , Xu Mengyuan , Yuan Tao , Zheng Xiuguo , Li Linyi , Wei Shiwei
Published: February 2025

This study combines hyperspectral imaging technology with biochemical parameter analysis to facilitate the disease severity evaluation and early detection of lettuce downy mildew. The results reveal a significant negative correlation between the disease index (DI) and the levels of flavonoids (r = −0.523) and anthocyanins (r = −0.746), indicating the role of these secondary metabolites in enhancing plant resistance. Analysis of hyperspectral data identified that spectral regions (410–503 nm, 510–615 nm, and 630–690 nm) and vegetation indices like PRI and ARI2 were highly correlated with DI, flavonoids, and anthocyanins, providing potential spectral indicators for disease assessment and early detection. Moreover, regression models developed using Partial Least Squares (PLS), Random Forest (RF), and Convolutional Neural Network (CNN) algorithms demonstrated high accuracy and reliability in predicting DI, flavonoids, and anthocyanins, with the highest R2 of 0.857, 0.910, and 0.963, respectively. The classification model using PLS, RF, and CNN successfully detected early physiological changes in lettuce within 24 h post-infection (highest accuracy = 0.764), offering an effective tool for early disease detection. The key spectral parameters in the PLS-DA model, like PRI, also demonstrated strong correlations with DI. These findings provide a scientific basis and practical tools for managing lettuce downy mildew and resistance breeding while laying a foundation for broader applications of hyperspectral imaging in plant pathology.
Influence of Astragalus extract on Gut Microbiome Regulation and Ammonia Emission Mitigation in Laying Hens
Authors: Xiao Shasha , Feng Kunxian , Li Shikai , Li Miao , Yan Xiliang , Wu Yinbao , Mi Jiandui , Liao Xindi , Wang Yan
Published: February 2025

Astragalus extract plays a dual role in gut microbiome regulation and ammonia (NH3) emission mitigation in laying hens. This study explored its effects through feeding experiments, with a focus on gut microbial metabolic pathways and NH3 reduction mechanisms. To achieve this, both in vitro fermentation experiments and in vivo feeding trials were conducted. In the in vitro study, cecal contents from laying hens were incubated with different concentrations of AE and Yucca extract (YE) to evaluate NH3 production, while in the feeding trial, 58-week-old Lohmann Pink laying hens were allocated into three groups (control, 0.1% YE, and 0.1% AE) and housed in controlled-environment respiration chambers for 21 days. Measurements included NH3 emissions, serum biochemical indices, immune parameters, gut physicochemical properties, and 16S rRNA-based microbiota analysis. Results showed that Astragalus extract reduced NH3 emissions by 29.3%, achieved by lowering urease and uricase activities and promoting the conversion of ammonium nitrogen to nitrate nitrogen. Additionally, it significantly enhanced gut immune function by increasing intestinal immunoglobulin levels. Microbial community analysis revealed an increased relative abundance of Bacteroides, Muribaculaceae, and Faecalibacterium, which are negatively correlated with NH3 emissions. These microbial shifts improved ammonium nitrogen utilization via the upregulation of CTP synthase and GMP synthase activities, contributing to higher NH3 reduction efficiency. This study highlights Astragalus extract as a cost-effective and sustainable strategy to regulate gut microbiota, optimize nitrogen metabolism, and mitigate NH3 emissions in laying hens.
Millimeter-Wave Imaging with Range-Resolved 3D Depth Extraction Using Glow Discharge Detection and Frequency-Modulated Continuous Wave Radar
Authors: Ramachandra Kurup Arun , Rozban Daniel , Abramovich Amir , Yitzhaky Yitzhak , Kopeika Natan
Published: February 2025

This paper presents a preliminary proof-of-concept study of a novel approach to 3D millimeter-wave (MMW) imaging, demonstrating the first implementation of Glow Discharge Detectors (GDDs) in this domain. GDDs offer significant advantages over conventional MMW detectors like Schottky diodes or bolometers due to their cost-effectiveness, robustness to high-power MMW signals, and reliable operation under diverse environmental conditions. Based on weakly ionized plasma (WIP) technology, GDDs detect changes in discharge current upon MMW exposure, providing an affordable and durable alternative to traditional MMW imaging systems. The system operates within a subset of the W-band (101–109 GHz), utilizing a customized transmitter (Tx 272 from VDI Technologies), which operates at a frequency range proportional to the VCO supply voltage level. The Frequency-Modulated Continuous Wave (FMCW) signal source is split into target and reference paths via a compact waveguide splitter, improving stability and reducing the complexity of the optical setup. Reflected signals are processed by the GDD, which functions as a heterodyne receiver, and Fast Fourier Transform (FFT) is used to extract range data. A 2D grid scanning mechanism, controlled by step motors, maps the surface of the object, while depth information is derived from FMCW frequency differentials to construct a complete 3D profile. This work demonstrates the potential of GDD-based 3D MMW imaging as a low-cost, efficient solution for security screening and industrial inspection. By addressing challenges in cost, scalability, and performance under high-power MMW signals, this approach represents a significant step forward in making MMW imaging technology more accessible, while highlighting the need for further development to achieve practical implementation.
Interpretable Identification of Dynamic Adaptive Streaming over HTTP (DASH) Flows Based on Feature Engineering
Authors: Biernacki Arkadiusz
Published: February 2025

Internet service providers allocate network resources for different network flows. Among them, video streaming requires substantial network bandwidth to provide a satisfactory user experience. The identification of video traffic is one of the tools that helps to manage and optimise network resources. However, available solutions usually focus on traffic traces from a single application and use black-box models for identification, which require labels for training. To address this issue, we proposed an unsupervised machine learning model to identify traffic generated by video applications from the three popular services, namely YouTube, Netflix, and Amazon Prime. Our methodology involves feature generation, filtering, and clustering. The clustering used the most significant features to group similar traffic patterns. We employed the following three algorithms that represent different clustering methodologies: partition-based, density-based, and probabilistic approaches. The clustering achieved precision between 0.78 and 0.93, while recall rates ranged from 0.68 to 0.84, depending on the experiment parameters, which is comparable with black-box learning models. The model presented is interpretable and scalable, which is useful for its practical application.
Determining a Suitable Reinforcement Strategy for TBM Advance in a Gully Fault Zone Without Jamming—A Numerical Analysis
Authors: Li Yuanzhuo , Li Qinglou , Tan Zhongsheng , Li Linfeng , Zhang Baojin
Published: February 2025

This study aims to identify the most suitable pre-reinforcement support measures to prevent TBM jamming when passing through the fractured zone of a gully fault. Given the high likelihood of jamming in such areas, the research focuses on selecting the most effective support system by considering factors such as surrounding rock stability, strata displacement, support structure stress, and cost-effectiveness. Theoretical analysis is employed to predict TBM jamming risks, based on design data, a 10 m gully unit and fractured rock mass were established at 75 m in the excavation direction with assigned parameters. Support effects of pipe curtains, grouting, anchors, and arch supports were analyzed under four conditions: chemical grouting, conduit installation, advanced pipe grouting, and double-layer pipe grouting. On-site verification reveals that TBM jamming occurs when the resisting torque on the cutter exceeds the maximum torque the cutter can generate. For the gully fault, pre-reinforcement measures are essential to stabilize the surrounding rock. Among the different methods, surface drilling reinforcement is the most effective. It significantly improves the surrounding rock’s stability, reducing the plastic zone’s depth by approximately 52.3% compared to the advanced pipe shed method. The axial force on the anchors decreases by 77.9–83.8%, arch stress is reduced by 68.9–90.8%, and tunnel deformation is minimized by 2.13–50.78%, all of which contribute to enhancing the safety of the initial support structure. On-site coring results, TBM boring parameters, and deformation monitoring data confirm that the surface drilling pre-reinforcement method outperforms the grouting pre-reinforcement for the pipe shed, ensuring the safe excavation of TBM in the gully fault conditions. These findings provide valuable insights for TBM tunnel construction in similar geological environments.
From Social to Academic: Associations and Predictions Between Different Types of Peer Relationships and Academic Performance Among College Students
Authors: Tian Jiadong , Lin Jiali , Li Dagang
Published: February 2025

This study aims to expose the correlation between different types of social behaviors and the academic performance of college students, and then to predict the academic performance of college students based on their social characteristics. We extracted and computed information on social relationships for roommates, classmates, members of the opposite sex, and others, based on real consumption data of 5597 freshmen students. The correlations between different types of peer relationships and academic performance were compared. Subsequently, we used Random Forests and Neural Networks as baseline methods, and introduced Graph Convolutional Network and Dynamic Graph Convolutional Network algorithms, on top of a graph network model based on social characteristics, to predict students’ academic performances. The results show that the quantity and quality of all types of socialization are positively correlated with academic performance, and socialization among classmates and roommates demonstrates a stronger correlation. In addition, with the construction of the graph model and the integration of time-series information, the prediction accuracy of the dynamic graph convolution method improved compared to other methods. The findings demonstrate the advantages of using social characteristics for academic performance prediction, and reveal the significant potential of AI applications in supporting the field of school management.
Design of a Video Otoscope Prototype with an Integrated Scanner for Hearing Aid Direct Digital Manufacturing: A Preliminary Study
Authors: Malça Cândida , Ganhão Francisco , Santos António Carvalho , Silva Carla , Moura Carla
Published: February 2025

In the current landscape of hearing rehabilitation, ear mold manufacturing typically involves the injection of silicone into the external ear canal (EEC) of each patient. This invasive procedure poses several risks, including the potential for silicone residue retention and tympanic membrane perforation, which may necessitate surgical intervention. To mitigate these risks, we present the design of a video otoscope that integrates a scanner capable of capturing high-precision, real-time images of the EEC’s geometry. The developed device allows (i) the generation of a 3D CAD model leading to the direct, quick, and low-cost production of customized hearing aids using 3D printing and (ii) the establishment of medical protocols for carrying out diagnoses and monitoring of hearing pathology evolution using methodologies based on Artificial Intelligence. Furthermore, the use of customized hearing aids that allow the application of Rhythmic Auditory Stimulation (RAS) and music therapy enhances audiology as an alternative and innovative way to treat cognitive and degenerative diseases, as well as pathological disorders.
A Study of the Impact of Heterogeneous Low Earth Orbit (LEO) Constellations on Global Ionospheric Tomography Inversions
Authors: Liu Yanwen , Huo Xingliang , Zhang Ting , Yuan Yunbin
Published: February 2025

The development of low earth orbit (LEO) satellites has provided the possibility to improve the accuracy of wide-area global navigation satellite system (GNSS) tomography; however, the existing LEO constellations were not designed to consider the effect on the improvement of the accuracy of GNSS computerized ionospheric tomography (CIT). In this paper, we use simulated observations to reconstruct a global higher-resolution three-dimensional (3D) ionospheric electron density (IED) model with a voxel-based model to explore the combined effects of heterogeneous LEO constellations on CIT. The results are as follows: (1) The number of grids crossed by rays increases after adding LEO satellites at different altitudes, while in the altitude interval of 100–300 km, the gain percentage increases with the number of LEO satellites at all four altitudes (300 km, 500 km, 800 km, and 1000 km). (2) The root mean square (RMS) gain percentages are positive after adding LEO satellite observations at 300 km and 500 km altitudes. Whereas, after adding LEO satellite observations at 800 km and 1000 km altitude, the RMS gain percentages from 100–300 km are negative. (3) From the overall percentage gain, the percentage RMS gain of all six plans exceeds 25%, with planB (96/96/60/30 LEO satellites at 300/500/800/1000 km, respectively) having the smallest percentage RMS gain of 27.31% and planA (192/96/60/30 LEO satellites at 300/500/800/1000 km, respectively) having the largest percentage RMS gain of 32.42%. Considering the LEO satellite launch maintenance cost for the enhancement effect of heterogeneous LEO constellations on CIT, this paper demonstrates that planA can effectively improve the accuracy of the 3D IED model.
Asymmetrical Time-Lagged Response of Vegetation to Drought and Extreme Precipitation Across China
Authors: Lai Wenli , Chen Yongxiang , Zhang Jie , Yang Huai
Published: February 2025

In this study, a study area was chosen in China to analyze the lagged response relationship between normalized difference vegetation index (NDVI) and extreme precipitation/drought from 1982 to 2015. A logistical function was applied to explain the increase in NDVI with mean annual precipitation in nine sub-regions, and the inflection point of precipitation was found to be very close to the threshold value for separating arid or humid regions. NDVI had a strong positive correlation with drought and extreme precipitation in the arid regions, while in humid regions, it presented a strong correlation with drought during 2000–2015; however, a weak correlation with drought was found before the 21st century. In this study, we quantified the time-lagged response of vegetation to drought (LTRD) and extreme precipitation (LTREP). Then, we defined four gradients (∂LTRD∂P, ∂LTRD∂T, ∂LTREP∂P, and ∂LTREP∂T) to quantify the precipitation and temperature gradients with the lag-time response to drought or extreme precipitation, respectively. Decreasing gradients were observed for humid regions with ∂LTRD∂P = −0.19 month·100 mm−1 for “wetting” and ∂LTRD∂T = −0.13 month·K−1 for “warming”, while increasing gradients were found in the same regions with ∂LTREP∂P = +0.18 month·100 mm−1 for “wetting” and ∂LTREP∂T = +0.14 month·K−1 for “warming”. These results suggest that the lagging responses of vegetation to extreme precipitation and droughts exhibit opposing regional patterns across China.
Nanostrategy for Selective Ethyl Carbamate Removal from Fermented Alcoholic Beverages via Molecular Imprinting Technology
Authors: Perestrelo Rosa
Published: February 2025

Ethyl carbamate (EC), known as urethane, is a naturally occurring potentially carcinogenic metabolite that is widely found in alcoholic beverages and other food-related fermented products. The concern related to the presence of the EC and its toxicity in regularly consumed fermented alcoholic beverages raises global interest in assessing the possible risks to human health. EC mitigation approaches, such as molecular imprinting technology (MIT), have been proposed to target EC while preserving the sensory quality of fermented alcoholic beverages. This review explores the principles of MIT, the advantages and disadvantages of the most common polymerisation approach for molecularly imprinted polymer (MIP) synthesis, the analytical techniques used for MIP characterisation, and the strategies used to mitigate EC in fermented alcoholic beverages, with studies reporting removal efficiencies of up to 84%. Additionally, it highlights the novelty and potential of MIPs, offering practical insights into their integration within the production of fermented alcoholic beverages, highlighting their scalability and cost-effectiveness compared to traditional EC mitigation strategies.
Rapid Genotyping of FecB Mutation in Sheep Using CRISPR-Cas12a Integrated with DNA Nanotree Biosensing Platform
Authors: Pan Dongxia , Mijit Mukaddas , Wang Hui , Sun Chaoqun , Pingcuo Bantan , Yu Zhixue , Xiong Benhai , Tang Xiangfang
Published: February 2025

The A-to-G mutation (FecB) in the BMPR1B gene is strongly linked to fertility in sheep, significantly increasing ovulation rates and litter sizes compared to wild-type populations. The rapid and reliable screening of the FecB gene is therefore critical for advancing sheep breeding programs. This study aimed to develop a fast and accurate method for detecting the FecB mutation and genotyping the gene to enhance sheep reproduction and productivity. To achieve this, we integrated the CRISPR-Cas12a system with an optimized amplification refractory mutation system (ARMS). A similar DNA origami technique-based fluorescence reporter nanotree structure was synthesized using gold nanomagnetic beads as carriers to amplify the fluorescence signal further. The resulting biosensing platform, termed CRISPR-ARMS, demonstrated excellent sensitivity for detecting FecB mutations, with a detection limit as low as 0.02 pmol. Therefore, this innovative approach shows great promise for single-base mutation detection and represents a pioneering tool for high-yield genetic screening.
Cannabinoids in Chronic Pain Management: A Review of the History, Efficacy, Applications, and Risks
Authors: Johnson Brooks W. , Strand Natalie H. , Raynak John C. , Jara Christian , Habtegiorgis Kisanet , Hand Brennan A. , Hong Sang , Maloney Jillian A.
Published: February 2025

Background/Objectives: Chronic pain remains a pervasive and challenging public health issue, often resistant to conventional treatments such as opioids, which carry substantial risks of dependency and adverse effects. Cannabinoids, bioactive compounds derived from the Cannabis sativa plant and their synthetic analogs, have emerged as a potential alternative for pain management, leveraging their interaction with the endocannabinoid system to modulate pain and inflammation. Methods: The current, evolving literature regarding the history, efficacy, applications, and safety of cannabinoids in the treatment of chronic pain was reviewed and summarized to provide the most current review of cannabinoids. Results: Evidence suggests that cannabinoids provide moderate efficacy in managing neuropathic pain, fibromyalgia, cancer-related pain, and multiple sclerosis-related spasticity. Patient-reported outcomes further indicate widespread perceptions of cannabinoids as a safer alternative to opioids, with potential opioid-sparing effects. However, the quality of existing evidence is limited by small sample sizes and methodological inconsistencies. Regulatory barriers, including the classification of cannabis as a Schedule I substance in the United States, continue to hinder robust research and clinical integration. Moreover, the risks associated with cannabinoids, such as psychiatric effects, addiction potential, and drug interactions, necessitate cautious application. Conclusions: Cannabinoids represent a promising, albeit complex, alternative for chronic pain management, particularly given the limitations and risks of traditional therapies such as opioids. However, significant deficiencies remain in the research. While smaller trials and systematic reviews indicate therapeutic potential, the quality of evidence is often low due to limited sample sizes, short study durations, and methodological inconsistencies. Large-scale, randomized controlled trials with long-term follow-up are urgently needed to confirm efficacy and safety across diverse patient populations and pain etiologies.
Resting-State Electroencephalogram and Speech Perception in Young Children with Developmental Language Disorder
Authors: Campos Ana , Loyola-Navarro Rocio , González Claudia , Iverson Paul
Published: February 2025

Background/Objectives: Endogenous oscillations reflect the spontaneous activity of brain networks involved in cognitive processes. In adults, endogenous activity across different bands correlates with, and can even predict, language and speech perception processing. However, it remains unclear how this activity develops in children with typical and atypical development. Methods: We investigated differences in resting-state EEG between preschoolers with developmental language disorder (DLD), their age-matched controls with typical language development (TLD), and a group of adults. Results: We observed significantly lower oscillatory power in adults than in children (p < 0.001 for all frequency bands), but no differences between the groups of children in power or hemispheric lateralisation, suggesting that oscillatory activity reflects differences in age, but not in language development. The only measure that differed between the children’s groups was theta/alpha band ratio (p = 0.004), which was significantly smaller in TLD than in DLD children, although this was an incidental finding. Behavioural results also did not fully align with previous research, as TLD children performed better in the filtered speech test (p = 0.01), but not in the speech-in-babble one, and behavioural test scores did not correlate with high-frequency oscillations, lateralisation indices, or band ratio measures. Conclusions: We discuss the suitability of these resting-state EEG measures to capture group-level differences between TLD/DLD preschoolers and the relevance of our findings for future studies investigating neural markers of typical and atypical language development.
Psychological Resilience and Future Anxiety Among University Students: The Mediating Role of Subjective Well-Being
Authors: Dalmış Alper Bahadır , Büyükatak Emrah , Sürücü Lütfi
Published: February 2025

Future anxiety is the worry and concern individuals experience regarding uncertainties and potential negative outcomes in their future. This emotional state can manifest at different stages of students’ academic lives and can impact their academic performance and social relationships. In the process of coping with negative experiences and overcoming challenges, psychological resilience plays a crucial role. Students who struggle to manage stress and have high levels of anxiety tend to experience future anxiety more intensely. The aim of this study is to determine the mediating role of subjective well-being in the relationship between psychological resilience and future anxiety among university students. The study was conducted with a total of 483 university students, including 280 females and 203 males. Data were collected using the Connor–Davidson Resilience Scale (CD-RISC-10), Subjective Well-Being Scale (SWB-7), and Future Anxiety (Dark Future) Scale (Short Form). Analyses were performed using AMOS 22.0 and SPSS 27.0 software. The findings indicate that psychological resilience has a significant negative effect on future anxiety, a significant positive effect on subjective well-being, and that subjective well-being has a significant negative effect on future anxiety. Additionally, the study found that subjective well-being mediates the relationship between psychological resilience and future anxiety.
A Unified Winkler Model for Vertical and Lateral Dynamic Analysis of Tapered Piles in Layered Soils in the Frequency Domain
Authors: Shua Qiangqiang , Xu Huanliang , Tu Wenbo , Li Mingkang , Shi Ningzhuo
Published: February 2025

Tapered piles are a new type of pile foundation known for their simple construction and high bearing capacity, commonly used in railway, highway, or building foundation treatment. This study proposes a unified dynamic Winkler model for vertical and lateral vibration response of tapered piles in the frequency domain using the impedance function transfer matrix method. The computational expressions are obtained for the different springs and damping of tapered piles with different dimensions using the elastodynamic theoretical of rigid embedded foundations, and the dynamic interaction mechanisms of vertical and lateral vibrations between tapered piles and soil are analyzed. The rationality of the simplified model is validated by comparison with existing literature and finite element simulation results. Finally, an example is provided to discuss the influences of the dimensional parameters of the pile and soil properties on vertical, lateral, and rocking dynamic impedance. The analytical findings demonstrate that the lateral and rocking dynamic impedances of tapered piles undergo a substantially greater enhancement relative to their vertical counterpart as the taper angle is progressively enlarged, assuming the pile volume remains constant. The dynamic impedance of tapered piles under vertical and lateral vibration in upper hard and lower weak soil layers, or upper weak and lower hard soil layers, are both greater than those in a homogeneous foundation. Specifically, the vertical dynamic stiffness of tapered piles in double-layered soils is approximately twice that of homogeneous soil. The rocking dynamic stiffness of the pile is significantly influenced by the soil properties around the pile foundation, whereas the soil properties have little impact on the rocking damping coefficient. Overall, the vertical dynamic characteristics are less influenced by the geometric features of the upper part of the tapered pile, while the lateral dynamic characteristics are significantly affected by these features. The lateral dynamic impedance of the tapered pile increases with the diameter of the upper part of the pile. Furthermore, the vertical, lateral, and rocking dynamic impedance of the pile can be effectively improved by enhancing the soil properties around its upper section. These results can provide theoretical references for the engineering practice.
Perioperative Intensive Smoking Cessation Intervention Among Smokers Who Underwent Transurethral Resection of Bladder Tumor (TURBT) in Two Different Settings: A Randomized Controlled Trial
Authors: Lydom Line N. , Lauridsen Susanne V. , Liljendahl Mie S. , Schmedes Anne V. , Joensen Ulla N. , Tønnesen Hanne
Published: February 2025

Background/Objective: Smoking is an individual risk factor for bladder cancer. Many patients are still smoking at the time of their diagnosis, yet few trials have examined smoking cessation interventions (SCIs) in relation to transurethral resection of the bladder tumor (TURBT). This study therefore aimed to compare the efficacy of a hospital-based 6-week intensive SCI with standard treatment among this patient group. Methods: A parallel-arm randomized controlled trial was conducted from December 2021 to March 2024 at two university hospital urology departments in Denmark. A total of 38 daily smokers undergoing TURBT were allocated to the hospital-based intensive SCI, including weekly meetings, patient education, motivational support, and complimentary nicotine replacement therapy or the standard treatment with very brief advice and referral to the same intensive SCI at a municipality clinic. The primary outcome was smoking cessation at the end of the intervention, assessed through participant interviews. The secondary outcomes included continuous abstinence at three and six months, quality of life, and frailty. Analyses were performed as intention-to-treat. Results: After six weeks, 37% in the hospital-based group and 6% in the standard group achieved smoking cessation (p = 0.042). At three and six months the quit rates were, 37% and 26% in the hospital-based group, compared to 0% and 0% in the standard group, respectively. No significant differences in quality of life or frailty were found. Conclusions: This trial found that hospital-based intensive SCI increased cessation rates compared to standard treatment. It would be valuable to evaluate the impact on postoperative complications, cancer prognosis, and long-term cessation in a sizeable new study.
Epidemiology of Thyroid Cancer in Tuscany (Central Italy) 2013–2017: Not Just Overdiagnosis
Authors: Capezzone Marco , Torregrossa Liborio , Poma Anello Marcello , Cartocci Alessandra , Petrone Luisa , Sparano Clotilde , Puccioni Matteo , Barbaro Daniele , Bigini Daniela , Marcantonio Annamaria , Pupilli Cinzia , Ladu Cristina , Gianetti Elena , Vezzosi Chiara , Belardini Valentina , Mancini Virginia , Morabito Eugenia Maria , Dalmazio Gilda , Tosti Balducci Massimo , Decarli Nicola Libertà , Giubbolini Giacomo , Boccuzzi Simone , Alessandri Massimo , Piacentini Paolo , Di Cosmo Caterina , De Servi Melissa , Tomisti Luca , Pellegri Marco , Gravina Giovanni , Ceroti Marco , De Napoli Luigi , Materazzi Gabriele
Published: February 2025

Thyroid cancer (TC) is the most common endocrine malignancy, and its incidence continues to rise worldwide [...]
Geometric Structure-Dependent Catalyst Performance in CH4 Reforming Using Ni-Based Catalysts
Authors: Dong Dongdong , Li Yanhui , Liu Min , Lu Bingwen , Yan Xingchen , Deng Zhaoyang , Chang Cheng , Zhou Kesong
Published: February 2025

The specific surface area, porosity, and mechanical properties of a catalyst are critical factors that significantly influence its performance. However, conventional preparation techniques are incapable of optimizing these properties simultaneously. Here, we present the performance of three kinds of catalysts with different geometric structures. Our findings indicated that the porosity, specific surface area, and mechanical properties of the 3D-printed catalysts achieved an optimal balance, exhibiting enhanced catalytic efficiency and mechanical integrity compared to commercial catalysts. Furthermore, the excellent ductility of the metal catalyst supports effectively prevented catalyst pulverization caused by carbon deposition and the thermal expansion of the supports. These results demonstrate that 3D printing technology can open up novel avenues for catalyst preparation, especially for metal-supported catalysts. The potential of metal additive manufacturing in chemical engineering is substantial, promising transformative advancements in the design and fabrication of catalytic converters and reactors.
Mapping Evidence on Integrated 24-Hour Movement Behaviors in Children and Adolescents: A Scoping Review of Reviews
Authors: Silva Andressa Ferreira da , Martins Priscila Custódio , Santiago Leandro Narciso , Silva Diego Augusto Santos
Published: February 2025

Background: There has been a substantial increase in research on the new 24-hour movement paradigm, emphasizing the importance of considering the “whole day” and investigating integrated movement behaviors (physical activity, sedentary behavior, and sleep). This scoping review aims to map the evidence from reviews that have summarized information on integrated 24-hour movement behaviors in children and adolescents. Methods: Eight databases were searched in May 2023, with an update in October 2024. The review followed the PRISMA-ScR framework and the guidelines of the Joanna Briggs Institute Reviewer’s Manual. Results: National 24-hour movement guidelines for children and adolescents exist in only a few countries (Australia, Canada, New Zealand, and South Africa). There is a lack of valid and reliable measurement tools for assessing 24-hour movement. Globally, children and adolescents, with and without disabilities, show low adherence to these guidelines. Reallocating time to moderate-to-vigorous physical activity was beneficial, while other reallocations had mixed results to health. COVID-19 reduced physical activity and increased screen time and sleep. Healthy movement behaviors are positively associated with better health outcomes in children and adolescents. There is a possible relationship between adherence to 24-hour movement behaviors and cognitive function, pollution measures, and eHealth interventions. Inconsistencies were identified in the terms used. Conclusions: High-quality research is needed to develop measurement tools that assess the long-term health impact of 24-hour movement and to create solutions for improving adherence, mainly in countries lacking specific guidelines.
Using 3D-Printed Formwork to Enable Controlled Crack Creation in Concrete Specimens
Authors: Solass Johannes , Schapfel Silvin , Stolz Alexander
Published: February 2025

The employment of automated non-destructive testing (NDT) methods for crack characterization in concrete, needs calibration and benchmarking in a controlled environment. This requires test specimen with comparable and ideally reproducible cracks. To this end, in this paper a method is presented that aims to mimic cracked concrete specimens with a high degree of control over the resulting crack parameters width, depth and length for material testing and calibration of automated (NDT) methods. The method comprises 3D-printing of formwork with integrated crack patterns. The obtained crack width accuracy is tested by comparing printed cracks and resulting cracks in the concrete with the desired width from the print file. This procedure enables the realization of crack widths ≥ 0.2 mm with a deviation in the range of 25% between desired and resulting crack width. Further, the proposed methodology is independent of intrinsic material properties which enables this accuracy.
Automated Orientation and Diffraction Intensity (AODI) Mapping on a Curved Surface
Authors: Pan Cheng , Wang Zhijun , Gao Xingyu
Published: February 2025

A method for automated orientation and diffraction intensity (AODI) mapping on a curved surface has been established at the Shanghai Synchrotron Radiation Facility (SSRF). In our method, the curved surface of the sample is measured as the three-dimensional positional changes in the sample stage during scanning of the sample surface using a laser rangefinder. The diffraction intensity at each scanning point is measured with micro-beam Laue diffraction technology; after crystal orientation is automatically determined, the orientation and diffraction intensity are mapped on the curved surface of the sample. Our method has been applied in the measurement and representation of the crystal orientation of a nickel-based single-crystal turbine blade. An AODI mapping approach can locate orientation or misorientation changes directly on the curved surface of the single-crystal sample. Therefore, the developed AODI mapping strategy demonstrates a straightforward solution for a spatially resolved microstructure study of single-crystal workpieces, which would have an impact on their research and industrial applications.
Examining the Potential of a University-Accredited Islamic Education Teacher Training Program: A Conceptual Exploration
Authors: Ahmed Asma
Published: February 2025

Public schools (K-12) are experiencing a remarkable decline in enrollment across Canada. More and more parents are choosing independent schools for their children’s education. Muslim parents, in particular, are transferring their children to Islamic schools as they are increasingly losing faith in public schools. Muslim students in the public school systems, wherever they are on the continuum of practice—from secular to orthodox—do not perceive their schools to be responsive to their religious beliefs, values, behaviours, and practices. However, Islamic schools are stuck in normative, secular, and reductive pedagogies, with most, if not all, Islamic teachers lacking training in Islamic pedagogy. This article is a conceptual exploration of various approaches to offering an Islamic teacher training program in Canada by an accredited university, including reintroducing the Islamic Teacher Education Programme (ITEP), which offered a one-year professional learning certificate. Another approach is establishing a stream in teacher education programs similar to the Catholic stream. The article serves as a stepping stone to initiate dialogue and collaborative efforts toward creating a comprehensive approach that includes all stakeholders tailored to the unique needs of Islamic school teachers in Ontario, Canada.
A Review of Earth-Air Heat Exchangers: From Fundamental Principles to Hybrid Systems with Renewable Energy Integration
Authors: Koshlak Hanna
Published: February 2025

Earth-Air Heat Exchangers (EAHEs) provide a compelling solution for improving building energy efficiency by harnessing the stable subterranean temperature to pre-treat ventilation air. This comprehensive review delves into the foundational principles of EAHE operation, meticulously examining heat and mass transfer phenomena at the ground-air interface. This study meticulously investigates the impact of key factors, including soil characteristics, climatic conditions, and crucial system design parameters, on overall system performance. Beyond independent applications, this review explores the integration of EAHEs with a diverse array of renewable energy technologies, such as air-source heat pumps, photovoltaic thermal (PVT) panels, wind turbines, fogging systems, water spray channels, solar chimneys, and photovoltaic systems. This exploration aims to clarify the potential of hybrid systems in achieving enhanced energy efficiency, minimizing environmental impact, and improving the overall robustness of the system.
Insights into Aquifer and Borehole Thermal Energy Storage Systems for Slovenia’s Energy Transition
Authors: Borko Karlo , Brenčič Mihael , Savšek Zdenko , Knez Jure , Vozelj Aleš , Kisel Gregor , Rman Nina
Published: February 2025

Since the heating and cooling sectors consume most of the energy in Europe through fossil fuels, the transition to a low-carbon and sustainable energy system is crucial. Underground Thermal Energy Storage (UTES) systems, such as aquifer thermal energy storage (ATES) and borehole thermal energy storage (BTES), offer promising solutions by enabling seasonal storage of renewable thermal energy, balancing the mismatch between supply and demand. ATES and BTES systems store excess heat or cold for later use, making them suitable for large-scale applications like residual heat storage from industrial or power generation processes by offering flexibility in heating and cooling. This review explores the geological and hydrogeological requirements for ATES and BTES systems, pointing out the importance of basic geological knowledge, laboratory and field investigations, and operational monitoring to optimize their performance. The study highlights the need for Slovenia to use the experiences of other European nations to overcome initial challenges, develop effective site evaluation methods, and integrate these systems into existing energy infrastructure.
Enhanced Dynamic Expansion Planning Model Incorporating Q-Learning and Distributionally Robust Optimization for Resilient and Cost-Efficient Distribution Networks
Authors: Lu Gang , Yuan Bo , Nie Baorui , Xia Peng , Wu Cong , Sun Guangzeng
Published: February 2025

The increasing integration of renewable energy-based distributed generation (DG) in modern distribution networks is essential for reducing reliance on fossil fuels. However, the unpredictability and intermittency of renewable sources such as wind and photovoltaic (PV) systems introduce significant challenges for distribution network planning. To address these challenges, this paper proposes a Q-learning-based Distributionally Robust Optimization (DRO) model for expansion planning of distribution networks and generation units. The proposed model incorporates energy storage systems (ESSs), renewable DG, substations, and distribution lines while considering uncertainties such as renewable generation variability, load fluctuations, and system contingencies. Through a dynamic decision-making process using Q-learning, the model adapts to changing network conditions to minimize the total system cost while maintaining reliability. The Latin Hypercube Sampling (LHS) method is employed to generate multi-scenario data, and piecewise linearization is used to reduce the computational complexity of the AC power flow equations. Numerical results demonstrate that the model significantly improves system reliability and economic efficiency under multiple uncertainty scenarios. The results also highlight the crucial role of the ESS in mitigating the variability of renewable energy and reducing the expected energy not supplied (EENS).
Innovative Method for Biomethane Production Based on a Closed Cycle of Biogas Upgrading and Organic Substrate Pretreatment—Technical, Economic, and Technological Fundamentals
Authors: Kazimierowicz Joanna , Dębowski Marcin , Zieliński Marcin
Published: February 2025

This study presents the technological, technical, and economic basis of the solution developed by the authors for the production of biomethane based on the pretreatment of organic substrates at low temperature using solidified CO2 captured during biogas upgrading in a closed cycle (TeCH4BiogasUp). TeCH4BiogasUp integrates the disintegration of organic substrates, biogas upgrading and the sequestration and utilization of CO2 in a closed cycle. The multifunctional and hybrid nature of TeCH4BiogasUp sets it apart from other available solutions that only perform selected, individual technological processes. This is a significant advantage and a competitive market edge; however, it also poses challenges in conducting comparative analyses with existing solutions on the market. The technology has been compared with traditional substrate pretreatment techniques and biogas purification technologies. Considering the origin of the solidified CO2, this method can be regarded as material recycling, which aligns fully with the principles of the circular economy. This technology supports the reduction in CO2 emissions by capturing the CO2 and introducing it into the closed process. This novel approach to the production and utilization of solidified CO2 largely overcomes previous limitations associated with the low profitability of the process. TeCH4BiogasUp could serve as a viable alternative to other methods, particularly in light of economic trends and the imperative to reduce CO2 emissions through the development of renewable energy sources.
Supercapacitor-Assisted Low-Frequency Converters for DC Microgrids, DC Homes, and DC Appliances for Increased End-to-End Efficiency: Implementation Example of a DC-Converted Refrigerator
Authors: Polwaththa Gallage Nirashi , Kularatna Nihal , Kularatna-Abeywardana Dulsha , Steyn-Ross Alistair
Published: February 2025

More recently, researchers and the industrial community have started researching DC appliances and DC microgrids as a means of increasing the end-to-end efficiency of systems. Given the fluctuating nature of renewable resources, energy storage becomes mandatory in powering households with minimal AC grid supply, and rechargeable battery packs with maximum power point tracking controllers with inverters are used. However, this approach is not the most efficient due to losses in the power converters used in the energy supply path, while short life and environmental concerns of battery storage also come into play. With the rapid development of commercial super-capacitors, with longer life, higher power density and wider operational temperature range, this device family can be at the center of a new development era, for power converters for DC homes and DC appliances. The new family of converters and protection systems known as supercapacitor-assisted techniques is a unique new approach to minimize or eliminate batteries while improving the ETEE. These new SCA techniques are based on a new theoretical concept now published as supercapacitor-assisted loss management theory. In this paper, we will demonstrate how we extend SCALoM theory to develop SCA converters for whiteware, with the example of a DC-converted commercial double-door refrigerator with implementation details.
Ecological Strategy for Restoring the Forest Ecosystem in the Taebaek Region of Baekdudaegan Mountains in Korea
Authors: Lee Min-Woo , Han Gyu-Il , Kim Young-Soo , Kim Seong-Bin , Heo Tae-Im
Published: February 2025

This study was conducted to classify the types of degraded land in the Taebaeksan region within the Baekdudaegan mountain range in Korea using image analysis and to assess the degree of degradation through a detailed survey of each type. Based on the findings, candidate tree species for restoration and strategies for land rehabilitation were proposed. The analysis identified 1589 degraded sites, classified into nine types of degradation. Using the Self-Organizing Map (SOM) method, these sites were further categorized into six environmental types. A survey was conducted on 25 degraded sites (encompassing 73 specific locations) in the Taebaeksan region, revealing that the sites fell into seven out of nine degradation categories: grassland, agricultural land, forest roads, ranches, cemeteries, logging sites, and abandoned quarries. The excluded categories were buildings and military facilities. A more focused survey was conducted on the 73 largest sites across the degradation types, with a reference ecosystem selected based on topographic analysis and succession processes. Diagnostic evaluations identified logging sites and severely degraded areas as the most urgent priorities for rehabilitation. Candidate tree species for restoration were proposed for each degradation type and environmental condition, based on ecological importance and reference ecosystem characteristics. This study provides a comprehensive assessment of degradation types following ecological restoration procedures and offers valuable baseline data for selecting restoration species and designing restoration strategies in conjunction with reference ecosystem studies.