bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of Wearable Insole Sensors in In-Place Running: Estimating Lower Limb Load Using Machine Learning
Authors: Lang Shipan , Yang Jun , Zhang Yong , Li Pei , Gou Xin , Chen Yuanzhu , Li Chunbao , Zhang Heng
Published: February 2025

Musculoskeletal injuries induced by high-intensity and repetitive physical activities represent one of the primary health concerns in the fields of public fitness and sports. Musculoskeletal injuries, often resulting from unscientific training practices, are particularly prevalent, with the tibia being especially vulnerable to fatigue-related damage. Current tibial load monitoring methods rely mainly on laboratory equipment and wearable devices, but datasets combining both sources are limited due to experimental complexities and signal synchronization challenges. Moreover, wearable-based algorithms often fail to capture deep signal features, hindering early detection and prevention of tibial fatigue injuries. In this study, we simultaneously collected data from laboratory equipment and wearable insole sensors during in-place running by volunteers, creating a dataset named WearLab-Leg. Based on this dataset, we developed a machine learning model integrating Temporal Convolutional Network (TCN) and Transformer modules to estimate vertical ground reaction force (vGRF) and tibia bone force (TBF) using insole pressure signals. Our model’s architecture effectively combines the advantages of local deep feature extraction and global modeling, and further introduces the Weight-MSELoss function to improve peak prediction performance. As a result, the model achieved a normalized root mean square error (NRMSE) of 7.33% for vGRF prediction and 10.64% for TBF prediction. Our dataset and proposed model offer a convenient solution for biomechanical monitoring in athletes and patients, providing reliable data and technical support for early warnings of fatigue-induced injuries.
Electrochemical Technology for the Detection of Tau Proteins as a Biomarker of Alzheimer’s Disease in Blood
Authors: Wang Jianman , Lu Xing , He Yao
Published: February 2025

Alzheimer’s disease (AD) is a prevalent neurodegenerative disorder and a significant cause of dementia in elderly individuals, with a growing prevalence in our aging population. Extracellular amyloid-β peptides (Aβ), intracellular tau proteins, and their phosphorylated forms have gained prominence as critical biomarkers for early and precise diagnosis of AD, correlating with disease progression and response to therapy. The high costs and invasiveness of conventional diagnostic methods, such as positron emission tomography (PET) and magnetic resonance imaging (MRI), limit their suitability for large-scale or routine screening. However, electrochemical (EC) analysis methods have made significant progress in disease detection due to their high sensitivity, excellent specificity, portability, and cost-effectiveness. This article reviews the progress in EC biosensing technologies, focusing on the detection of tau protein biomarkers in the blood (a low-invasive, accessible diagnostic medium). The article then discusses various EC sensing platforms, including their fabrication processes, limit of detection (LOD), sensitivity, and clinical potential to show the role of these sensors as transformers changing the face of AD diagnostics.
A Pilot Study on Video Game Training Effects on Visual Working Memory: Behavioral and Neural Insights
Authors: Alfaro-Cortés Héctor Hugo , Torres-Ramos Sulema , Román-Godínez Israel , Ruiz-Stovel Vanessa Doreen , Salido-Ruiz Ricardo Antonio
Published: February 2025

Background/Objectives: Recent research suggests that video games may serve as cognitive training tools to enhance visual working memory (VWM) capacity. However, the effectiveness of game-based cognitive training remains debated, and the underlying neural mechanisms, as well as the relationship between training efficacy and game design factors, are unclear. This study aimed to evaluate the impact of video game training on VWM capacity and explore its neural correlates. Methods: Two groups underwent 56 daily 20 min training sessions with two distinct video games targeting different cognitive skills: a reaction-time training game and a VWM-specific training game. Behavioral assessments included accuracy, hit response times, correct rejection response times, and Cowan’s K values. Neural correlates were measured through Negative Slow Wave (NSW) activity using EEG. Decision tree classification analyses were applied to NSW data across sessions and set sizes to identify patterns linked to VWM capacity. Results: Preliminary results are that both groups showed improvements in behavioral measures (accuracy, response times, and Cowan’s K values). NSW analyses revealed a main effect of set size in both groups, and classification results indicated that NSW patterns differed between groups, across sessions, and set sizes, supporting the relationship between NSW and VWM capacity. Conclusions: These findings contribute to understanding NSW as a neurophysiological correlate of VWM capacity, demonstrating its plasticity through video game training. Simple video games could effectively enhance behavioral and neural aspects of VWM, encouraging their potential as accessible cognitive training tools.
Supporting Families to ‘Make the Most’ of the Relationship Between Their Companion Dogs and Their Children with Autism Spectrum Condition: A Qualitative Exploration of the ‘Family Dog Service’
Authors: Shoesmith Emily , Stevens Heidi , Gibsone Selina , Miles Cari , Beal Hannah , Jennings Kelly , Ratschen Elena
Published: February 2025

Evidence suggests that assistance and therapy dogs can positively impact the mental and physical health of children with autism spectrum condition (ASC) and their families. However, these services are often costly and inaccessible. As an alternative, companion dogs (e.g., non-specialist-trained pet dogs) may offer similar benefits. To support families in selecting and training a dog to benefit the whole family, a charity named Dogs for Good has designed the Family Dog Service. This qualitative study aimed to explore the perceived impact of human–dog interactions and relationships for children with ASC and their families, and their perceptions of the Family Dog Service. Interviews were conducted with 16 parents of children with ASC who had engaged with the service within the last five years. Thematic analysis identified four main themes. These related to the positive impact of the companion dog on the child with ASC (e.g., enhanced focus and attention, reduction in loneliness, and reduced anxiety-based behaviours) and the parents (e.g., increased respite and wellbeing). However, parents also reported challenges of dog ownership (e.g., adjustment to routines and barriers associated with the development of the human–dog relationship). These challenges appeared to be mitigated by tailored guidance and support from the Family Dog Service. The findings indicate that companion dog ownership provided benefits to children with ASC and their families, similar to those reported for autism assistance dogs. While the findings do not suggest that companion dogs can replace the important role played by specialist trained assistance dogs, it is possible that reported benefits may occur due to the development of the human–dog relationship, facilitated by the support offered by the Family Dog Service. The service may provide a practical, valuable alternative in light of restrictions and challenges often associated with securing assistance dog placements.
Energy Intensity and Uplift Load Resistance of Novel Hybrid Pile, Driven with Additional Compaction: Comparative Field Study
Authors: Atenov Yerlan , Bekbasarov Isabai , Shanshabayev Nurzhan
Published: February 2025

The article presents the results of an experimental study on driven reinforced concrete piles with hybrid shaft, which incorporates several wedge-shaped elements with inclined side faces. A technology for the installing of these piles, involving the addition of loose materials to enhance soil compaction, is herein proposed. Field experiments were conducted to determine the energy intensity of driving and the uplift load resistance of these piles. It was found that the energy intensity of a driving hybrid pile with loose materials addition is 1.4–3.5 times greater compared to conventional driven piles. However, the uplift bearing capacity was 1.5–4.4 times higher than that of piles with a traditional shape. The efficiency of the experimental piles is attributed to an increase in the volume of wedge-shaped elements on the pile shaft and the incorporation of loose materials, such as gravel and sand. The uplift capacity of hybrid shaft piles improves with the increasing volume of the aforementioned parameters. The obtained correlation dependencies enable a reliable calculation of the energy intensity and uplift resistance of hybrid shaft piles installed with the addition of loose materials. These findings hold significant practical importance for foundation design using piles with non-traditional shaft shapes in variant design assessments.
Research on Chinese Traditional Architectural Culture and Inheritance Strategy: A Case Study of the Goulou Cluster of Yue Dialects in Guangxi
Authors: Kuang Yuan , Zheng Feifei , Lin Chengzhi , Hu Yue
Published: February 2025

Traditional Chinese villages and architectural cultural resources are abundant. Against the backdrop of rapid development in contemporary socioeconomic and urbanization processes, rural construction is facing multiple challenges such as imbalanced urban–rural development, gradually fading cultural traditions, and disharmonious living environments. The cultural elements of rural architecture urgently need more systematic and effective protection, integration, and reuse. Therefore, the precise extraction of traditional architectural features and their translation applications in modern contexts are gradually becoming key issues in current research and practice fields. This study takes traditional architecture of the Goulou Cluster of Yue Dialects in Guangxi, China, as an example. Through field investigations and mathematical and GIS spatial analysis, architectural samples were identified and extracted typologically, and a database of traditional architecture was constructed, delineating architectural cultural zones and summarizing type characteristics to create a genealogy map. Based on the results of the architectural genealogy study, modern translation pathways for traditional architecture were proposed through spatial modeling, technical analysis, and iterative optimization. Modern translation experiments were conducted on selected typical villages and their traditional buildings, exploring the application model system of traditional architecture in modern contexts. This study not only deepens the scientific understanding of the genealogy zoning characteristics of traditional architecture in the Goulou Cluster of Yue Dialects in Guangxi but also provides a reference for the modern translation and optimization path of traditional architecture, providing important theoretical basis and application guidance for promoting the inheritance and innovation of rural culture, and realizing the protection and updating of rural architectural style.
The Current Status of Adjuvant Chemotherapy for Colorectal Cancer in Japan: A Paradigm Shift from Oral Fluoropyridine Single Therapy to the Oxaliplatin Regimen
Authors: Teranishi Nobuhisa , Uetake Hiroyuki
Published: February 2025

The effectiveness of oxaliplatin (L-OHP) has been reported overseas; however, in Japan, the prognosis of colorectal cancer (CRC) patients is reported to be good, and there has been a long debate about the applicability of L-OHP combination therapy in Japan. In recent years, the results of the ACHIEVE trial have become clear, and the standard consensus in Japan establishes L-OHP combination therapy for a duration of 3 months as the adjuvant treatment for CRC.
Efficacy and Toxicity of Bevacizumab in Children with NF2-Related Schwannomatosis: A Systematic Review
Authors: Tops Annemijn L. , Schopman Josefine E. , Koot Radboud W. , Gelderblom Hans , Putri Nabila A. , Rahmi Latifah N. A. , Jansen Jeroen C. , Hensen Erik F.
Published: February 2025

Background/Objectives: NF2-related schwannomatosis (NF2) is a tumor predisposition syndrome that typically presents with bilateral vestibular schwannomas, together with other intracranial and spinal schwannomas, meningiomas, and/or ependymomas. Bevacizumab, a VEGF inhibitor, has the potential to decrease schwannoma volume and improve hearing in adults, but the literature on the effects in children is sparse. This narrative review aims to evaluate the use of bevacizumab in pediatric NF2 patients, focusing on hearing, tumor progression, and toxicity. Methods: A literature review was conducted following PRISMA guidelines. Articles were searched in PubMed, Embase, Web of Science, Cochrane Library, Emcare, and Academic Search Premier on 18 July 2024. Inclusion criteria were patients ≤ 18 years, diagnosed with NF2 and treated with bevacizumab. Two authors independently assessed the quality of the evidence and extracted relevant data from the included articles. Results: Seventeen articles including 62 pediatric NF2 patients met the inclusion criteria. Studies varied widely in treatment regimens and outcome parameters. Tumor regression was reported in 6/56 patients (11%) and 38/56 (68%) remained stable. Hearing improved in 15/45 patients (33%) and did not further deteriorate in 27/45 (60%). An improvement in other symptoms was seen in 6/29 patients (28%). Toxicity was reported in five studies, documenting 13 adverse events in 28 patients ranging from grade 1 to grade 3. Treatment was discontinued in both patients who experienced grade 3 toxicity. Conclusions: Bevacizumab seems to be a viable treatment option for pediatric NF2 patients. Tumor regression or stabilization is achieved in the majority of patients (77%). Moreover, a considerable number of pediatric patients experience hearing stabilization or improvement (93%). Bevacizumab appears to be relatively well tolerated, offering a non-invasive therapeutic option for children with NF2 suffering from progressive vestibular schwannomas and hearing loss.
Modified Zeolites for the Removal of Emerging Bio-Resistive Pollutants in Water Resources
Authors: Samara Fatin , Al Abdel Hamid Amer A. , Gopal Venkatesh , Dronjak Lara , Feghaly Fares , Kanan Sofian
Published: February 2025

The increasing presence of pollutants, including pharmaceuticals and pesticides, in water resources necessitates the development of effective remediation technologies. Zeolites are promising agents for pollutant removal due to their high surface area, ion-exchange capacity, natural abundance, and diverse tailorable porous structures. This review focuses on the efficient application of modified zeolites and mesoporous materials as photocatalysts and adsorbents for removing contaminants from water bodies. The adsorption and photodegradation of pesticides and selected non-steroidal anti-inflammatory drugs and antibiotics on various zeolites reveal optimal adsorption and degradation conditions for each pollutant. In most reported studies, higher SiO2/Al2O3 ratio zeolites exhibited improved adsorption, and thus photodegradation activities, due to increased hydrophobicity and lower negative charge. For example, SBA-15 demonstrated high efficiency in removing diclofenac, ibuprofen, and ketoprofen from water in acidic conditions. Metal doped into the zeolite framework was found to be a very active catalyst for the photodegradation of organic pollutants, including pesticides, pharmaceuticals, and industrial wastes. It is shown that the photocatalytic activity depends on the zeolite-type, metal dopant, metal content, zeolite pore structure, and the energy of the irradiation source. Faujasite-type Y zeolites combined with ozone achieved up to 95% micropollutant degradation. Bentonite modified with cellulosic biopolymers effectively removed pesticides such as atrazine and chlorpyrifos, while titanium and/or silver-doped zeolites showed strong catalytic activity in degrading carbamates, highlighting their environmental application potential.
Cobalt Decarbonization Catalysts Turning Methane to Clean Hydrogen and Valuable Carbon Nanostructures: A Review
Authors: Zeza Elpida , Pachatouridou Eleni , Lappas Angelos A. , Iliopoulou Eleni F.
Published: February 2025

The continuous growth in world energy demands along with the urgent need for decarbonization are strong motivations for the development and usage of sustainable fuels. Hydrogen is highly anticipated to replace fossil fuels in energy production, as it is one of the cleanest energy sources with high energy density per weight. Among the hydrogen production methods, catalytic methane pyrolysis (CMP) stands out as it can contribute to the decarbonization process, since the only co-products include valuable carbon structures and no greenhouse emissions. Cobalt has been shown to be a competent metallic catalytic material with high activity in relation to hydrogen production and selectivity towards valuable carbon nanotubes (CNTs), or carbon nanofibers (CNFs). This review article aims to offer insights relevant to future developments in CMP, by reporting the advantages of methane decomposition over cobalt catalysts. It provides a summary of the factors that influence both hydrogen yield and carbon growth. More specifically, the impacts of different metal loadings and the benefits of utilizing both support carriers and bimetallic systems are addressed. Last but not least, the findings on the most efficient preparation procedures and the optimum operating conditions are also revealed, as supported by published experimental data.
Cigarette Smoke Contributes to the Progression of MASLD: From the Molecular Mechanisms to Therapy
Authors: Xu Jiatong , Li Yifan , Feng Zixuan , Chen Hongping
Published: February 2025

Cigarette smoke (CS), an intricate blend comprising over 4000 compounds, induces abnormal cellular reactions that harm multiple tissues. Non-alcoholic fatty liver disease (NAFLD) is a prevalent chronic liver disease (CLD), encompassing non-alcoholic fatty liver (NAFL), non-alcoholic steatohepatitis (NASH), cirrhosis, and hepatocellular carcinoma (HCC). Recently, the term NAFLD has been changed to metabolic dysfunction-associated steatotic liver disease (MASLD), and NASH has been renamed metabolic dysfunction-associated steatohepatitis (MASH). A multitude of experiments have confirmed the association between CS and the incidence and progression of MASLD. However, the specific signaling pathways involved need to be updated with new scientific discoveries. CS exposure can disrupt lipid metabolism, induce inflammation and apoptosis, and stimulate liver fibrosis through multiple signaling pathways that promote the progression of MASLD. Currently, there is no officially approved efficacious pharmaceutical intervention in clinical practice. Therefore, lifestyle modifications have emerged as the primary therapeutic approach for managing MASLD. Smoking cessation and the application of a series of natural ingredients have been shown to ameliorate pathological changes in the liver induced by CS, potentially serving as an effective approach to decelerating MASLD development. This article aims to elucidate the specific signaling pathways through which smoking promotes MASLD, while summarizing the reversal factors identified in recent studies, thereby offering novel insights for future research on and the treatment of MASLD.
Crystalline Coating and Its Influence on Chloride Ion Diffusion Resistance of Carbonated Concrete
Authors: Mottl Martin , Pazderka Jiří , Reiterman Pavel
Published: February 2025

Carbonation and chloride ingress are the most important damaging mechanisms for steel-reinforced concrete. The combination of these two corrosion processes accelerates the destruction of concrete, leads to extensive structural repairs, negatively impacts durability, and significantly reduces the service life of the structure. One possible and effective way to reduce chloride diffusion through the concrete pore system is through the use of crystalline materials. An experimental study focused on the ability of an applied crystalline coating to increase the chloride resistance of carbonated concrete is presented in this paper. Carbonated concrete specimens treated with a crystalline coating were exposed to a sodium chloride solution for various periods of time, and a water-soluble chloride ion content analysis was performed on powder samples taken from the tested specimens. Chloride profiles presenting the chloride ion concentrations at selected depths are presented for multiple types of concrete at various ages to show the effect of crystalline technology on the chloride resistance of concrete. The results of this study confirm the impact of carbonation on chloride ion ingress through concrete and show that crystalline coatings can improve the chloride resistance of concrete. Using crystalline coatings on carbonated concrete can, from a long-term perspective, significantly reduce the chloride ion content in concrete placed in an aggressive environment. The crystalline coatings were functional even after 28 days, when the concentration of chloride ions was below the critical concentration. The crystalline coating was able to reduce the concentration of chloride ions by 68% under the surface of the concrete and by 65% at depths of 20–25 mm after 180 days of immersion, compared to the untreated concrete. Crystalline coatings reduce the depth of critical chloride ion concentration, effectively protect the concrete reinforcement against corrosion and extend the service life of the structure.
Mechanism and Structural Defects of Zinc Film Deposited on a Copper Substrate: A Study via Molecular Dynamics Simulations
Authors: He Xin , Qin Xiangge , Zhan Lan
Published: February 2025

Epitaxial growth can be used to guide the controllable growth of one metal on the surface of another substrate by matching the interface lattice, thus improving the dendrite tendency of metal growth. The atomic arrangement of the Cu (111) crystal plane of the FCC structure is similar to that of the Zn (0002) crystal plane of the HCP structure, which is theoretically expected to promote the heterogeneous epitaxial nucleation growth of metal zinc under low strain. In this paper, the molecular dynamics method is used to simulate the atomic process of zinc film growth on the Cu (111) surface. It is found that the behavior of zinc-adsorbed atoms on the substrate surface conforms to the epitaxial growth mode. The close-packed structure grown along the (0002) direction of the layered clusters is tiled on the Cu (111) surface, forming a highly ordered low-lattice-mismatch interface. When a large area of layered zinc clusters cover the substrate, the growth mode will change from heteroepitaxial growth to homoepitaxial growth of Zn atoms on the zinc film, forming a lamellar distribution composed of FCC and HCP structure grains. Polycrystalline zinc film with a planar structure with a (0002) surface preferred a crystal plane. The increase in incident energy is helpful in improving the quality of zinc films, while the deposition rate, corresponding to the deposition temperature and electrolyte ion concentration, has no significant effect on the surface morphology and crystal structure of single metal films. In summary, the atomic arrangement of the Cu (111) surface has a strong guiding effect on the atomic ordered arrangement in the zinc film crystal, which is suitable for the epitaxial deposition of the substrate to induce the ordered growth of the Zn (0002) crystal plane.
Mineralogical Characteristics and Color Origin of Nephrite Containing Pink Minerals
Authors: Yuan Ye , Li Youxuan , Shi Miao
Published: February 2025

Recently, a variety of nephrite containing localized pink mineral aggregates has emerged on the market, which is sometimes referred to as “peach blossom jade” by some merchants. Currently, there is limited research on this type of nephrite containing pink minerals, and its detailed mineral composition characteristics and coloration mechanisms remain unclear. In this study, four samples of nephrite containing pink minerals were systematically investigated using conventional gemological tests, as well as modern analytical techniques such as X-ray powder diffraction (XRD), infrared spectroscopy (IR), laser Raman spectroscopy, ultraviolet–visible (UV-Vis) absorption spectroscopy, electron probe microanalysis (EPMA), and X-ray fluorescence spectroscopy (XRF). These techniques were employed to elucidate the mineral composition, chemical composition, spectroscopic features, and coloration origins of the samples. The results indicate that the primary mineral constituent of the samples is tremolite, with accessory minerals including zoisite, muscovite, orthoclase, andesine, diopside, and prehnite. The major chemical components of the samples are SiO2, CaO, and MgO, along with minor amounts of Al2O3, K2O, and FeOT. The overall green hue of the samples is positively correlated with Fe content. The pink mineral present in the samples is predominantly Mn-bearing zoisite, and the pink coloration of zoisite is primarily attributed to the energy level transitions of Mn2+ at approximately 540 nm and 440 nm.
Estimation of Hardness of Single-Phase Metallic Alloys
Authors: Temesi Ottó K. , Chinh Nguyen Q. , Vitos Levente , Varga Lajos K.
Published: February 2025

First, we discuss a common feature of single-phase pure metals and amorphous and high-entropy alloys: the maximum value of hardness corresponding to a valence electron count (VEC) value of around 6.5–7. This correlation is explained by the coincidence that by subtracting the number of sp valence electrons (Nsp = 2) from the VEC we obtain the maximal number of unpaired d electrons, Nd = 4.5–5 in the 3d, 4d, and 5d rows of transition elements. These unpaired d electrons form orbital overlap bonding, which is stronger than the isotropic metallic bonds of a delocalized electron cloud. The more unpaired d electrons there are, the higher the bonding strength. Second, we will discuss the hardness formulas derived from cohesion energy and shear modulus. We will demonstrate that both types of formulas originate in the electrostatic energy density of metallic bonds, expressing a 1/R4 dependence. Finally, we show that only two parameters are sufficient to estimate hardness: the atomic radius and the cohesion-based valence. In the case of alloys, our formula gives a lower bound on the hardness only. It is not suitable for calculation of the hardness increase caused by solid solution, grain size, precipitation, and phase mixture.
Landscape Heterogeneity and Island Identity as Drivers of Mesoscale Structure of Pollination Networks
Authors: Neokosmidis Lazaros , Zevgolis Yiannis G. , Dimitrakopoulos Panayiotis G. , Petanidou Theodora
Published: February 2025

Indirect interactions enforce ecological and evolutionary dynamics within pollination networks. An effective way to study overall indirect interactions in a network is through motif profiles, which represent the network’s mesoscale structure, as well as species’ structural roles, reflecting their participation in motifs. Here, we surveyed 37 pollination networks across eight Aegean islands, a region with a complex biogeographic history, to examine (a) whether species’ structural roles in pollination networks are determined by species, landscape, or island identity; (b) the impact of landscape heterogeneity and island identity on the mesoscale structure of pollination networks; and (c) the variation explained by landscape drivers and island identity in motif profiles compared to link composition. Using PERMANOVA, we found that all three factors significantly grouped species’ structural roles, indicating the combined influence of niche-based and neutral processes. Interestingly, using two dbRDA models to evaluate the combined effects of landscape context and island identity on motif profiles and network link compositions, we found that the first model explained 57% of the variance, whereas the second model accounted for only 16%. This finding emphasizes the potential of motif profiles in revealing interaction dynamics that might otherwise be overlooked. Furthermore, island identity significantly influenced all three responses, suggesting that regional island features play a key role in shaping local interactions.
Automatic Detection of Occluded Main Coronary Arteries of NSTEMI Patients with MI-MS ConvMixer + WSSE Without CAG
Authors: Goktekin Mehmet Cagri , Gul Evrim , Çakmak Tolga , Demir Fatih , Kobat Mehmet Ali , Akbulut Yaman , Işık Ömer , Kadiroğlu Zehra , Demir Kürşat , Şengür Abdulkadir
Published: February 2025

Background/Objectives: Heart attacks are the leading cause of death in the world. There are two important classes of heart attack: ST-segment Elevation Myocardial Infarction (STEMI) and Non-ST-segment Elevation Myocardial Infarction (NSTEMI) patient groups. While the STEMI group has a higher mortality rate in the short term, the NSTEMI group is considered more dangerous and insidious in the long term. Blocked coronary arteries can be predicted from ECG signals in STEMI patients but not in NSTEMI patients. Therefore, coronary angiography (CAG) is inevitable for these patients. However, in the elderly and some patients with chronic diseases, if there is a single blockage, the CAG procedure poses a risk, so medication may be preferred. In this study, a novel deep learning-based approach is used to automatically detect the occluded main coronary artery or arteries in NSTEMI patients. For this purpose, a new seven-class dataset was created with expert cardiologists. Methods: A new Multi Input-Multi Scale (MI-MS) ConvMixer model was developed for automatic detection. The MI-MS ConvMixer model allows simultaneous training of 12-channel ECG data and highlights different regions of the data at different scales. In addition, the ConMixer structure provides high classification performance without increasing the complexity of the model. Moreover, to maximise the classifier performance, the WSSE algorithm was developed to adjust the classification prediction value according to the feature importance weights. Results: This algorithm improves the SVM classifier performance. The features extracted from this model were classified with the WSSE algorithm, and an accuracy of 88.72% was achieved. Conclusions: This study demonstrates the potential of the MI-MS ConvMixer model in advancing ECG signal classification for diagnosing coronary artery diseases, offering a promising tool for real-time, automated analysis in clinical settings. The findings highlight the model’s ability to achieve high sensitivity, specificity, and precision, which could significantly improve.
Volume Changes in Brain Subfields of Patients with Alzheimer’s Disease After Transcranial Ultrasound Stimulation
Authors: Huang Sheng-Yao , Wu Meng-Ting , Sun Chung-Fu , Yang Feng-Yi
Published: February 2025

Background/Objectives: Alzheimer’s disease (AD) is characterized by progressive brain atrophy marked by cognitive decline and memory loss, which significantly affect patients’ quality of life. Transcranial ultrasound stimulation (TUS) is a potential physical treatment for AD patients. However, the specific brain regions stimulated by TUS and its therapeutic effects remain unclear. Methods: In this study, magnetic resonance imaging (MRI) and FreeSurfer segmentation were employed to assess alterations in the brain volume of AD patients after TUS. Results: Our findings revealed significant volume increases in the corpus callosum (CC) and lateral orbitofrontal cortex (lOFC) in the TUS group. Moreover, the volumetric changes in the CC were strongly correlated with improvements in the Mini-Mental State Examination score, which is a widely used measure of cognitive function of AD patients. Conclusions: TUS has the potential to alleviate disease progression and offers a non-invasive therapeutic approach to the improvement of cognitive function in AD patients.
Transfer Learning and Neural Network-Based Approach on Structural MRI Data for Prediction and Classification of Alzheimer’s Disease
Authors: Momeni Farideh , Shahbazi-Gahrouei Daryoush , Mahmoudi Tahereh , Mehdizadeh Alireza
Published: February 2025

Background: Alzheimer’s disease (AD) is a neurodegenerative condition that has no definitive treatment, and its early diagnosis can help to prevent or slow down its progress. Structural magnetic resonance imaging (sMRI) and the progress of artificial intelligence (AI) have significant attention in AD detection. This study aims to differentiate AD from NC and distinguish between LMCI and EMCI from the other two classes. Another goal is the diagnostic performance (accuracy and AUC) of sMRI for predicting AD in its early stages. Methods: In this study, 398 participants were used from the ADNI and OASIS global database of sMRI including 98 individuals with AD, 102 with early mild cognitive impairment (EMCI), 98 with late mild cognitive impairment (LMCI), and 100 normal controls (NC). Results: The proposed model achieved high area under the curve (AUC) values and an accuracy of 99.7%, which is very remarkable for all four classes: NC vs. AD: AUC = [0.985], EMCI vs. NC: AUC = [0.961], LMCI vs. NC: AUC = [0.951], LMCI vs. AD: AUC = [0.989], and EMCI vs. LMCI: AUC = [1.000]. Conclusions: The results reveal that this model incorporates DenseNet169, transfer learning, and class decomposition to classify AD stages, particularly in differentiating EMCI from LMCI. The proposed model performs well with high accuracy and area under the curve for AD diagnostics at early stages. In addition, the accurate diagnosis of EMCI and LMCI can lead to early prediction of AD or prevention and slowing down of AD before its progress.
Measurement of Fusion Control with Eye Tracking Device in Intermittent Exotropia
Authors: Kim Dong Hyun , Yang Hee Kyung , Han Sang Beom , Hwang Jeong Min
Published: February 2025

Background/Objectives: We wished to develop an automated method for quantifying fusion control in patients with intermittent exotropia (IXT) using an eye tracking device. Methods: Fifty subjects fixated on visual targets on an LCD monitor at a distance of 45 cm, consisting of dots moving horizontally and vertically and randomly appearing dots at fixed positions. The control group consisted of participants with less than 5 prism diopters (PD), and the IXT group consisted of IXT patients with 10 PD or more, excluding divergence excess types. Fixation disparity (FD) was measured using an eye tracking device, and the FD score was compared with the Newcastle Control Score (NCS) and the Mayo Clinic office-based scale (OCS) score. The subjects repeated the test twice, and the test–retest reliability was determined. Results: The fixation disparity scores of the IXT group during horizontal pursuit, vertical pursuit, and random dot fixation showed positive correlations with the NCS (r = 0.549, 0.583, and 0.481, respectively) and OCS score (r = 0.551, 0.570, and 0.505, respectively). The test–retest reliability of the FD scores of the IXT group using an eye tracking device was fair to good for each task (ICC = 0.633, 0.656, and 0.697, respectively). Conclusions: The eye tracking device developed for automated measurement of fusion control has the potential to assist in functional assessments of IXT.
The Role of Nailfold Videocapillaroscopy in the Diagnosis and Monitoring of Interstitial Lung Disease Associated with Rheumatic Autoimmune Diseases
Authors: Anghel Daniela , Prioteasă Oana-Georgiana , Nicolau Iulia-Nadine , Bucurică Săndica , Belinski Daniela-Opriș , Popescu Gilda-Georgeta , Ghinescu Minerva Claudia , Bobircă Anca , Groșeanu Maria-Laura , Bojincă Violeta-Claudia
Published: February 2025

Interstitial lung disease (ILD) is a severe complication of certain connective tissue diseases (CTDs) such as systemic sclerosis (SSc), mixed connective tissue disease (MCTD), idiopathic inflammatory myopathies (IIM), rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE), and it is associated with nailfold videocapillaroscopy (NVC) changes and increased morbidity and mortality rates. Early diagnosis is crucial in order to prevent the progression of ILD, prevent respiratory failure and enhance the patient’s overall quality of life. The most common paraclinical investigations are high-resolution computed tomography (HRCT) and functional respiratory tests such as forced vital capacity (FVC) and the diffusing capacity of the lungs for carbon monoxide (DLCO). The most frequent CTD associated with both ILD and NVC changes is systemic sclerosis. The “late” scleroderma pattern was the most common abnormality identified in NVC results in SSc patients. Other autoimmune diseases were also correlated with ILD and NVC changes, especially when the Raynaud phenomenon was present. Low capillary density was associated with the presence and severity of ILD and a reduction in FVC and DLCO. NVC can also differentiate the capillaroscopic changes in some particular types of ILD, such as the usual interstitial pneumonia (UIP) pattern from the non-specific interstitial pneumonia (NSIP) pattern. Nevertheless, further extensive research is necessary in order to establish the diagnostic value of NVC in CTD-ILD in clinical practice.
A Machine Learning Model Based on Radiomic Features as a Tool to Identify Active Giant Cell Arteritis on [18F]FDG-PET Images During Follow-Up
Authors: Vries Hanne S. , van Praagh Gijs D. , Nienhuis Pieter H. , Alic Lejla , Slart Riemer H. J. A.
Published: February 2025

Objective: To investigate the feasibility of a machine learning (ML) model based on radiomic features to identify active giant cell arteritis (GCA) in the aorta and differentiate it from atherosclerosis in follow-up [18F]FDG-PET/CT images for therapy monitoring. Methods: To train the ML model, 64 [18F]FDG-PET scans of 34 patients with proven GCA and 34 control subjects with type 2 diabetes mellitus were retrospectively included. The aorta was delineated into the ascending, arch, descending, and abdominal aorta. From each segment, 95 features were extracted. All segments were randomly split into a training/validation (n = 192; 80%) and test set (n = 46; 20%). In total, 441 ML models were trained, using combinations of seven feature selection methods, seven classifiers, and nine different numbers of features. The performance was assessed by area under the curve (AUC). The best performing ML model was compared to the clinical report of nuclear medicine physicians in 19 follow-up scans (7 active GCA, 12 inactive GCA). For explainability, an occlusion map was created to illustrate the important regions of the aorta for the decision of the ML model. Results: The ten-feature model with ANOVA as the feature selector and random forest classifier demonstrated the highest performance (AUC = 0.92 ± 0.01). Compared with the clinical report, this model showed a higher PPV (0.83 vs. 0.80), NPV (0.85 vs. 0.79), and accuracy (0.84 vs. 0.79) in the detection of active GCA in follow-up scans. Conclusions: The current radiomics ML model was able to identify active GCA and differentiate GCA from atherosclerosis in follow-up [18F]FDG-PET/CT scans. This demonstrates the potential of the ML model as a monitoring tool in challenging [18F]FDG-PET scans of GCA patients.
DEGNN: A Deep Learning-Based Method for Unmanned Aerial Vehicle Software Security Analysis
Authors: Du Jiang , Wei Qiang , Wang Yisen , Bai Xingyu
Published: February 2025

With the increasing utilization of drones, the cyber security threats they face have become more prominent. Code reuse in the software development of drone systems has led to vulnerabilities in drones. The binary code similarity analysis method offers a way to analyze drone firmware lacking source code. This paper proposes DEGNN, a novel graph neural network for binary code similarity analysis. It uses call-enhanced control graphs and attention mechanisms to generate dual embeddings of functions and predict similarity based on graph structures and node features. DEGNN is effective in cross-architecture tasks. Experimental results show that in the cross-architecture binary function search, DEGNN’s mean reciprocal rank and recall@1 surpass the state of the art by 12% and 28.6%, respectively. In the cross-architecture real-world vulnerability search, specifically targeting drone systems, it has a 33.3% performance improvement over the SOTA model, indicating its great potential in enhancing drone cyber security.
Quantum Dynamics Framework with Quantum Tunneling Effect for Numerical Optimization
Authors: Tang Quan , Wang Peng
Published: February 2025

In recent years, optimization algorithms have developed rapidly, especially those which introduce quantum ideas, which perform excellently. Inspired by quantum thought, this paper proposes a quantum dynamics framework (QDF) which converts optimization problems into the problem of the constrained ground state of the quantum system and analyzes optimization algorithms by simulating the dynamic evolution process of physical optimization systems in the ground state. Potential energy equivalence and Taylor expansion are performed on the objective function to obtain the basic iterative operations of optimization algorithms. Furthermore, a quantum dynamics framework based on the quantum tunneling effect (QDF-TE) is proposed which adopts dynamic multiple group collaborative sampling to improve the quantum tunneling effect of the QDF, thereby increasing the population diversity and improving algorithm performance. The probability distribution of solutions can be visually observed through the evolution of the wave function, which also indicates that the QDF-TE can strengthen the tunneling effect. The QDF-TE was evaluated on the CEC 2017 test suite and shown to be competitive with other heuristic optimization algorithms. The experimental results reveal the effectiveness of introducing a quantum mechanism to analyze and improve optimization algorithms.
Towed Video-Diver: A Useful Low-Cost Tool for Rapid Benthic Mapping and Biodiversity Monitoring
Authors: Bravo Gonzalo , Trobbiani Gaston A. , Bigatti Gregorio , Beltramino Lucas E. , Irigoyen Alejo J.
Published: February 2025

Marine Protected Areas (MPAs) require efficient monitoring tools to assess habitats and biodiversity, particularly in remote or understudied regions. This study demonstrates the utility of the towed video-diver technique combined with high-resolution video for rapidly surveying benthic habitats and associated taxa. Applied in Arredondo, a shallow bay within an MPA in Atlantic Patagonia, the method covered 14,000 m2 through eight transects, utilizing just 180 min of dive time and ~300 min of video analysis. Substrate types and their associated taxa were classified using the CATAMI framework, yielding a list of 28 taxa and density estimates of mobile organisms. Additionally, the percentage cover of Gracilaria sp.—a commercially valuable macroalga historically overexploited in the region—was estimated for the bay. The invasive crab Carcinus maenas was found across all substrate types on the bay, underscoring its ecological tolerance and the need for ongoing monitoring. This cost-effective, rapid methodology is highly effective for detecting and describing areas of ecological or conservation interest, providing critical baseline data for targeted, detailed studies. Its simplicity and efficiency make it ideal for initial surveys in remote regions, supporting the conservation and management of MPAs.
Species-Specific Effects of a Sound Prototype to Reduce Bird Use of Powerline Poles
Authors: Ribeiro-Silva Joana , Ribeiro Hélder , Pedroso Nuno M. , Mira António , Sillero Neftalí
Published: February 2025

Powerlines pose a significant threat to many bird species, impacting their conservation. Current research focuses on developing methods to mitigate bird mortality due to electrocution and collisions with powerlines. In this study, we designed a sound prototype to be installed on infrastructure poles, including powerlines, aiming to reduce their use by birds. We conducted bird surveys over 47 days, from February to May 2020, in five light poles: the central pole where the device was installed (0 m), two poles at 25 m, and two poles at 50 m from the central pole. The first 10 days served as a control period with the deterrent device switched off, followed by 37 days with the device switched on. In total, we recorded 1945 bird observations, of which 1569 occurred with the device on. The device was triggered by bird movements, resulting in 588 reactions to sound. When activated, 10.6% of large- and medium-sized birds were flushed from the surveyed poles: 2.6% were already perched and flushed due to the sound, 3.9% were prevented from perching, and 4.1% were flushed after perching, thereby reducing the risk of electrocution. Among the birds perching or approaching the pole where the device was installed, 25% were deterred by the sound. The black kite, Milvus migrans, was the most reactive species to the device (54.3% flushed at 0 m, and 8.8% flushed at 25 and 50 m), while the white stork, Ciconia ciconia, showed the least sensitivity to the disturbances (14.4% flushed at 0 m, and 2.7% flushed at 25 and 50 m). The corvids exhibited a response rate between the other two species (33.3% flushed at 0 m, and 6.8% flushed at 25 and 50 m). We identified significant limitations to this prototype and proposed recommendations to improve its efficiency.
Recovery of Streams in the Harz National Park (Germany)—The Attenuation of Acidification
Authors: Langheinrich Uta , Smith Kilian E. C. , Arevalo Jose Ramon , Schwarz Fabian , Lüderitz Volker
Published: February 2025

Between 1995 and 2022, 19 measuring points in small and medium sized streams in the Harz National Park, Germany, were sampled. The samples were evaluated in terms of their macroinvertebrate (MI) biology and hydrochemistry. Nearly all streams showed a natural hydromorphology, and low values of biological oxygen demand (BOD) characteristic for rivers not contaminated by organic matter. Nevertheless, in the 1990s, most streams were still only settled by a small number of MI species. However, by 2022, the MI species number had doubled or tripled in most cases, with a maximum increase from 14 to 52. There is a clear correlation between species number and pH. At 15 of the 19 sampling sites, the acidity class has gotten better by at least one value. Thus, acid-sensitive species, mainly from the taxonomic orders Trichoptera, Plecoptera, and Ephemeroptera, have been able to settle higher altitudes, as well as formerly acidic reaches. In general, the streams contain a very specific macroinvertebrate fauna that emphasizes the conservation value of the Harz National Park. Attenuation of acidification has not only influenced the MI diversity. Along with the increase in pH, fish populations have recovered, and formerly fish-free stream sections have been recolonised. The biological recovery of the streams has also been fostered by the breakdown of spruce forest monocultures in the surroundings, the natural development of deciduous trees on the banks, and increasing levels of DOC (dissolved organic carbon).