bluuebunny/crossref_metadata_2025 huggingface dataset:
A Robust Method for Real Time Intraoperative 2D and Preoperative 3D X-Ray Image Registration Based on an Enhanced Swin Transformer Framework
Authors: Ye Wentao , Wu Jianghong , Zhang Wei , Sun Liyang , Dong Xue , Xu Shuogui
Published: January 2025

In image-guided surgery (IGS) practice, combining intraoperative 2D X-ray images with preoperative 3D X-ray images from computed tomography (CT) enables the rapid and accurate localization of lesions, which allows for a more minimally invasive and efficient surgery, and also reduces the risk of secondary injuries to nerves and vessels. Conventional optimization-based methods for 2D X-ray and 3D CT matching are limited in speed and precision due to non-convex optimization spaces and a constrained searching range. Recently, deep learning (DL) approaches have demonstrated remarkable proficiency in solving complex nonlinear 2D–3D registration. In this paper, a fast and robust DL-based registration method is proposed that takes an intraoperative 2D X-ray image as input, compares it with the preoperative 3D CT, and outputs their relative pose in x, y, z and pitch, yaw, roll. The method employs a dual-channel Swin transformer feature extractor equipped with attention mechanisms and feature pyramid to facilitate the correlation between features of the 2D X-ray and anatomical pose of CT. Tests on three different regions of interest acquired from open-source datasets show that our method can achieve high pose estimation accuracy (mean rotation and translation error of 0.142° and 0.362 mm, respectively) in a short time (0.02 s). Robustness tests indicate that our proposed method can maintain zero registration failures across varying levels of noise. This generalizable learning-based 2D (X-ray) and 3D (CT) registration algorithm owns promising applications in surgical navigation, targeted radiotherapy, and other clinical operations, with substantial potential for enhancing the accuracy and efficiency of image-guided surgery.
Antioxidative Function of Zinc and Its Protection Against the Onset and Progression of Kidney Disease Due to Cadmium
Authors: Satarug Soisungwan
Published: January 2025

Chronic kidney disease (CKD) is now the world’s top seventh cause of death from a non-communicable disease, and its incidence is projected to increase further as its major risk factors, including obesity, diabetes, hypertension, and non-alcoholic fatty liver disease (NAFLD), continue to rise. Current evidence has linked the increased prevalence of CKD, diabetes, hypertension, and NAFLD to chronic exposure to the metal pollutant cadmium (Cd). Exposure to Cd is widespread because diet is the main exposure route for most people. Notably, however, the health risk of dietary Cd exposure is underappreciated, and the existing tolerable exposure guidelines for Cd do not afford health protection. New health-protective exposure guidelines are needed. From one’s diet, Cd is absorbed by the intestinal epithelium from where it passes through the liver and accumulates within the kidney tubular epithelial cells. Here, it is bound to metallothionine (MT), and as it is gradually released, it induces tubular damage, tubulointerstitial inflammation and fibrosis, and nephron destruction. The present review provides an update on our knowledge of the exposure levels of Cd that are found to be associated with CKD, NAFLD, and mortality from cardiovascular disease. It discusses the co-existence of hypertension and CKD in people environmentally exposed to Cd. It highlights nuclear and mitochondrial targeting and zinc deficiency as the universal cytotoxic mechanisms of Cd. Special emphasis is placed on the novel antioxidative function of zinc involving de novo heme biosynthesis and the induced expression of heme oxygenase-1 (HO-1). Other exogenous biomolecules with promising anti-Cd toxicity are highlighted.
Biomechanical Behavior of Female Breast—A Review
Authors: Galbreath Sheila , Goswami Tarun
Published: January 2025

Introduction: Women wear exterior breast support for most of the day. A female’s breast tissue and skin affect the comfort of the ADLs, exercise, health, and work environments. Understanding the breast tissue’s normal anatomy and mechanical and material properties is related to a woman’s daily health and quality of life outcomes. Considering the importance and impact of female breasts throughout one’s lifespan, additional research is needed to address the research gaps to provide solutions to improve daily lives and clinical interventions. Breast stability and behavior are dependent on its internal mechanical properties and applied external forces. Objective: To evaluate the current knowledge and research gaps on the adult female breast tissue’s anatomy, the factors that impact its growth and development, variations among racial populations, the internal and external mechanical properties of the tissue, and the factors employed to evaluate the pathology risk. Review sections: The review sections are as follows: 3. Anatomy of Breast, 4. Effects of Age and Stages of Breast Development, 5. Breast Skin, and 6. Breast Tissue Mechanics. Conclusions: Numerous research gaps have been identified within the field of female breasts.
Prediction of Bladder Outlet Obstruction in Male Patients with Lower Urinary Tract Symptoms Based on Symptom Scores and Noninvasive Office-Based Diagnostic Tools
Authors: Liu Min-Ching , Jiang Yuan-Hong , Kuo Hann-Chorng
Published: January 2025

Purpose: The purpose of this study was to investigate the predictive values of combining symptom scores, prostatic parameters, uroflowmetry parameters, intravesical prostatic protrusion, and prostatic urethral angle for the establishment of a bladder outlet obstruction (BOO) risk score for diagnosing BOO in men with lower urinary tract symptoms. Materials and Methods: A total of 355 men with lower urinary tract symptoms were enrolled and divided into a training set (N = 285) and validation set (N = 70). Videourodynamic studies were used to diagnose lower urinary tract dysfunction subtypes, which were subdivided into a non-BOO and BOO group, which included bladder neck dysfunction and benign prostate obstruction. The parameters were categorized as 0, 1, 2, or 3 according to their cutoff value regarding the specificity of predicting BOO. The BOO risk score was constructed by summing scores of seven variables of symptoms and prostate and uroflowmetry parameters. The area under the curve (AUC) was used to select appropriate cutoff values for predicting lower urinary tract dysfunctions. Results: Among the 355 men examined, 234 (65.9%) had BOO, including 136 (38.3%) with bladder neck dysfunction and 98 (27.6%) with benign prostate obstruction. Other lower urinary tract dysfunctions included detrusor overactivity in 37 patients (10.4%), dysfunctional voiding in 28 patients (7.9%), poor relaxation of the external sphincter in 26 patients (7.3%), detrusor underactivity in 14 patients (3.9%), stable bladder in 9 patients (2.5%), and a hypersensitive bladder in 7 patients (2%). With the summation of the BOO risk scores from each variable, a BOO risk score of ≥10 could yield a sensitivity of 0.822 and specificity of 0.656 for benign prostate obstruction in the training set [AUC = 0.800 (0.741–0.859)] and a sensitivity of 0.80 and specificity of 0.64 in the validation set [AUC = 0.813 (0.701–0.925)]. Conclusions: With office-based diagnostic tools, including symptom scores and uroflowmetry and prostate parameters, a BOO risk score was established. A BOO risk score of ≥10 can predict the presence of benign prostate obstruction in >80% of men with lower urinary tract symptoms refractory to initial medication.
Identification of Key Risk Factors in Mechanical Cross Passage Construction Based on the Decision-Making Test and Evaluation Test Method and the Interpretation Structure Model
Authors: Zhang Wencui , Wang Xiaoqian , Yang Qiye , Li Shiqi , Chen Wenjie
Published: January 2025

In order to solve the problem that the key risk factors in the construction of mechanical cross passages are relatively vague, the decision-making test and evaluation test method (DEMATEL) and the interpretation structure model (ISM) are combined to analyze safety risks in the construction of mechanical cross passages scientifically and reasonably. Based on the ‘personnel’, ‘material’, ‘machine’, ‘method’, and ‘environment’ of 4M1E comprehensive management, the construction safety risk index system of mechanical method cross passage, including 18 risk factors, is extracted. DEMATEL was used to divide the risk factors into four factor sets: strong cause, weak cause, strong result, and weak result. Furthermore, ISM is used to construct a hierarchical structure diagram of risk factors, and deep risk factors and risk factors with a high node degree are divided. The results show that the safety awareness of construction personnel, the safety technology level of construction personnel, the establishment and implementation of the safety construction system, the level of construction management, and the degree of geological complexity are strong cause-type risk factors with both high centrality and high causality. Additionally, the effect of reinforcement of the internal support system, the setting of the digging parameter, the effect of grouting, and the effect of assembling the pipe sheet comprise the strong result-type risk factors with high centrality. The risk factors with higher node degree in ISM are consistent with the risk factors with higher centrality in the DEMATEL model, which are key factors that play an important role in risk control.
The Applications of Machine Learning in the Management of Patients Undergoing Stem Cell Transplantation: Are We Ready?
Authors: Garuffo Luca , Leoni Alessandro , Gatta Roberto , Bernardi Simona
Published: January 2025

Hematopoietic stem cell transplantation (HSCT) is a life-saving therapy for hematologic malignancies, such as leukemia and lymphoma and other severe conditions but is associated with significant risks, including graft versus host disease (GVHD), relapse, and treatment-related mortality. The increasing complexity of clinical, genomic, and biomarker data has spurred interest in machine learning (ML), which has emerged as a transformative tool to enhance decision-making and optimize outcomes in HSCT. This review examines the applications of ML in HSCT, focusing on donor selection, conditioning regimen, and prediction of post-transplant outcomes. Machine learning approaches, including decision trees, random forests, and neural networks, have demonstrated potential in improving donor compatibility algorithms, mortality and relapse prediction, and GVHD risk stratification. Integrating “omics” data with ML models has enabled the identification of novel biomarkers and the development of highly accurate predictive tools, supporting personalized treatment strategies. Despite promising advancements, challenges persist, including data standardization, algorithm interpretability, and ethical considerations regarding patient privacy. While ML holds promise for revolutionizing HSCT management, addressing these barriers through multicenter collaborations and regulatory frameworks remains essential for broader clinical adoption. In addition, the potential of ML can cope with some challenges such as data harmonization, patients’ data protection, and availability of adequate infrastructure. Future research should prioritize larger datasets, multimodal data integration, and robust validation methods to fully realize ML’s transformative potential in HSCT.
An Accelerated Spectroscopic MRI Metabolite Quantification Based on a Deep Learning Method for Radiation Therapy Planning in Brain Tumor Patients
Authors: Giuffrida Alexander S. , Ramesh Karthik , Sheriff Sulaiman , Maudsley Andrew A. , Weinberg Brent D. , Cooper Lee A. D. , Shim Hyunsuk
Published: January 2025

Background: Spectroscopic MRI (sMRI) is a quantitative imaging technique that maps infiltrated tumors in the brain without contrast injections. In a previous study (NCT03137888), sMRI-guided radiation treatment extended patient survival, showing promise for clinical translation. The spectral fitting of individual voxels in an sMRI dataset generate metabolite concentration maps that guide treatment. The established spectral analysis methods use iterative least-squares fitting (FITT) that are computationally demanding. This study compares the performance of NNFit, a neural network-based, accelerated spectral fitting model, to the established FITT for metabolite quantification and radiation treatment planning. Methods: NNFit is a self-supervised deep learning model trained on 50 ms echo-time (TE) sMRI data to estimate metabolite levels of choline (Cho), creatine (Cr), and NAA. We trained the model on 30 GBM patients (56 scans) and tested it on 17 GBM patients (29 scans). NNFit’s performance was compared to the FITT using structural similarity indices (SSIM) and the Dice coefficient. Results: NNFit significantly improved processing speed while maintaining strong agreement with FITT. The radiation target volumes defined by Cho/NAA ≥ 2x were visually comparable, with fewer artifacts in NNFit. Structural similarity indices (SSIM) indicated minimal bias and high consistency across methods. Conclusions: This study highlights NNFit’s potential for rapid, accurate, and artifact-reduced metabolic imaging, enabling faster radiotherapy planning.
Photocatalysis by Mixed Oxides Containing Niobium, Vanadium, Silica, or Tin
Authors: Feliczak-Guzik Agnieszka , Wawrzyńczak Agata , Nowak Izabela
Published: January 2025

Nb-Sn, V-Sn mixed-metal oxides and Nb-Si, V-Si metal oxide–silicas were successfully synthesized through a “soft” templating method, in which appropriate amounts of metal salts (either niobium(V) chloride, or vanadium(IV) oxide sulfate hydrate or tin(II) chloride dihydrate) or tetraethyl orthosilicate (TEOS) were mixed with hexadecyltrimethylammonium chloride (HDTA) or sodium dodecyl sulfate (SDS) solutions to obtain a new series of mesoporous oxides, followed by calcination at different temperatures. As-obtained samples were characterized by SEM, TEM, XRD, and UV-Vis spectra techniques. The photocatalytic activities of the samples were evaluated by degradation of methyl orange II (MO) under simulated sunlight irradiation. The effects of metal species and calcination temperature on the physicochemical characteristic and photocatalytic activity of the samples were investigated in detail. The results indicated that, compared to pure oxides, mixed-metal oxide showed superior photocatalytic performance for the degradation of MO. A maximum photocatalytic discoloration rate of 97.3% (with MO initial concentration of 0.6·10−4 mol/dm3) was achieved in 300 min with the NbSiOx material, which was much higher than that of Degussa P25 under the same conditions. Additionally, the samples were tested in the photochemical oxidation process, i.e., advanced oxidation processes (AOPs) to treat the commercial non-ionic surfactant: propylene oxide ethylene oxide polymer mono(nonylphenyl) ether (N8P7, PCC Rokita). A maximum of 99.9% photochemical degradation was achieved in 30 min with the NbSiOx material.
Lipid Emulsion Mitigates the Cardiotoxic Effects of Labetalol in Rat Cardiomyoblasts
Authors: Sim Gyujin , Ok Seong-Ho , Lee Soo Hee , Park Kyeong-Eon , Park Seunghyeon , Sohn Ju-Tae
Published: January 2025

Lipid emulsion has recently emerged as an effective agent for improving the cardiotoxicity of highly lipophilic drugs. However, its effect on cardiotoxicity induced by labetalol, a nonselective beta-blocker, remains unknown. In this study, we investigated the effects of lipid emulsion on the cardiotoxicity of labetalol in rat cardiomyoblasts and tried to decipher the underlying mechanisms. The effects of lipid emulsion on labetalol-induced changes in cell viability, expression of Bax/Bcl-2, cleaved caspase-3, and cleaved caspase-9, and phosphorylation of GSK-3β, Akt, and PI3K were examined. Lipid emulsion inhibited labetalol-induced decrease in cell viability, whereas LY294002, MK2206, and SB216763, the inhibitors of phosphoinositide 3-kinase (PI3K), Akt, glycogen synthase kinase-3β (GSK-3β), respectively, partially attenuated this restoration of cell viability. Lipid emulsion reversed the increase in expression of cleaved caspase-3, cleaved caspase-9, and Bax/Bcl-2 and decrease in the phosphorylation of GSK-3β, Akt, and PI3K by labetalol. Lipid emulsion and cyclosporin, a mitochondrial permeability transition pore (MPTP) inhibitor, reduced the labetalol-induced increase in the number of TUNEL-positive cells and promoted late-stage apoptosis. Overall, lipid emulsion inhibited apoptotic cell death caused by labetalol toxicity via the inhibition of intrinsic apoptotic pathway and MPTP in rat cardiomyoblasts, which appears to involve PI3K, Akt, and GSK-3β signaling pathways.
Implicit Measurement of Sweetness Intensity and Affective Value Based on fNIRS
Authors: Mai Jiayu , Li Siying , Wei Zhenbo , Sun Yi
Published: January 2025

This study explores the effectiveness of functional near-infrared spectroscopy (fNIRS) as an implicit measurement tool for evaluating sweetness intensity and affective value. Thirty-two participants tasted sucrose solutions at concentrations of 0.15 M, 0.3 M, and 0.6 M, while both their neural responses were recorded with a 24-channel fNIRS system and their self-reported assessments of sweetness intensity and affective value were collected. The neural fNIRS data were converted into oxygenated hemoglobin (HbO) and deoxygenated hemoglobin (HbR) concentrations using the modified Beer–Lambert Law, and analyzed through univariate activation analysis and multivariable decoding analysis to identify neural activation patterns associated with sweetness perception. The results showed significant activation in the dorsolateral prefrontal cortex (dlPFC) and orbitofrontal cortex (OFC) in response to varying levels of sweetness intensity and affective value, with channels 8, 10, 12, 13, 14, 15, and 17 consistently activated across all sucrose concentrations. As sweetness concentration increased from 0.15 M to 0.6 M, the number of significantly activated channels rose from seven to eleven, indicating stronger and more widespread neural responses corresponding to higher sweetness intensity. The multivariable decoding analysis further demonstrated the capability of fNIRS in accurately distinguishing positive affective responses, with up to 72.1% accuracy. The moderate positive correlation between explicit self-reports and implicit fNIRS data regarding sweetness intensity further supports the validity of fNIRS as a reliable tool for assessing taste perception. This study highlights the potential of fNIRS in sensory neuroscience, demonstrating its effectiveness in capturing the neural mechanisms underlying sweet taste perception.
Insight into Reduction Process of Diquat on Silver and Copper Electrodes Studied Using SERS
Authors: López-Ramírez María Rosa , Olivares-Fernández Lucas , Sanchez-Cortes Santiago
Published: January 2025

A surface-enhanced Raman scattering (SERS) study of diquat (DQ) on silver and copper electrodes is presented in this work in order to complete previous studies on the SERS of DQ on metal nanoparticles. We supported the experimental results with theoretical calculations of different species of DQ, analyzing the most important molecular differences and their corresponding Raman spectra. DQ SERS spectra on Ag and Cu electrodes were obtained at different excitation wavelengths. An analysis of the SERS spectra revealed that at more positive electrode potentials, the interaction of DQ with the metal formed a charge-transfer complex via the chloride anion previously adsorbed on the surface; additionally, at more negative potentials, other species of diquat, such as DQ2+, could be directly adsorbed on the metal’s surface. Finally, we detected new SERS bands corresponding to DQ at negative electrode potentials that were sensitive to the excitation wavelength, suggesting that lateral interactions between radical cation species on the electrode surface lead to intramolecular dimerization and a possible multilayer of the adsorbate.
Exploring the Effectiveness of Combining Social Skills Training and Two Parent Programs in Improving the Social Competence of Children with Attention-Deficit/Hyperactivity Disorder
Authors: García-Castellar Rosa , Sánchez-Chiva Desirée , Roselló-Miranda Belén , Flor-Arasil Patricia
Published: January 2025

Background/Objectives: The objective of the present study was to examine the extent of effectiveness of two parent programs to complement an intervention in social skills for children with attention-deficit/hyperactivity disorder (ADHD). Methods: Fifteen children with ADHD participated in a program to develop social skills, while their parents were randomly assigned to two parent training programs that had different formats: a Parenting School (N = 8) or a Parent Workshop (N = 7). There were no significant differences between parents of both groups in knowledge about ADHD, obedience to commands, or strategies for addressing desirable and undesirable behaviors. The pre- and post-intervention social cognition and social interaction of ADHD children were assessed using a SSRS-C questionnaire (Social Skills Rating System—Child Form) and a controlled chat room, which allowed for observing how children interact in a virtual environment. Results: Children showed significant improvements in social competencies, such as identifying social cues, generating appropriate responses, and reducing hostile responses, with large effect sizes, following the social skills intervention. Comparing the two parent training programs, the Parent Workshop program demonstrated significant improvements in social cue detection and conversation memory, with more children achieving reliable changes in these variables than in the Parenting School program. Conclusions: Finally, the reliable change indices for children showed that the Parent Workshop demonstrated improvements in more than half of the subjects across all analyzed variables. Study limitations, implications for research and practice are discussed.
Laryngeal Mask Airway Method for Minimally Invasive Surfactant Therapy in Neonates with Pneumothorax Complicating Respiratory Distress Syndrome
Authors: Pinheiro Joaquim M. B. , Fisher Marilyn , Tauber Kate A. , Pezzano Chad
Published: January 2025

Background/Objectives: Pneumothorax is a common complication of neonatal respiratory distress syndrome, which is decreased by surfactant therapy. Rescue administration of surfactant in neonates with severe RDS complicated by pneumothorax requires management of the pneumothorax to optimize surfactant distribution while avoiding positive pressure ventilation to minimize iatrogenic exacerbation of the air leak. Methods: We retrospectively reviewed our center’s experience with neonates who had clinically significant pneumothorax complicating RDS, in whom we used a novel technique to administer surfactant through a laryngeal mask/supraglottic airway device without applying positive pressure ventilation. Results: In 13 of the 20 neonates in our cohort, subsequent invasive ventilation and chest tube insertion were avoided. There were no major complications or unfavorable outcomes. We describe our experience with this method and suggest an approach to individualize the management of neonates with pneumothorax preceding surfactant therapy. Conclusions: In our setting, laryngeal mask airway devices are now the preferred method to deliver surfactant in neonates with RDS and pre-existing pneumothorax. We believe this approach is readily applicable in most neonatal care settings.
The Differential Impact of Clear Aligners and Fixed Orthodontic Appliances on Periodontal Health: A Systematic Review
Authors: Dipalma Gianna , Inchingolo Alessio Danilo , Fiore Arianna , Balestriere Liviana , Nardelli Paola , Casamassima Lucia , Di Venere Daniela , Palermo Andrea , Inchingolo Francesco , Inchingolo Angelo Michele
Published: January 2025

Background/objective: In orthodontic therapy, the periodontal ligament plays a critical role in the bone remodeling process by stimulating osteoblasts in tension zones and promoting bone resorption through osteoclasts in compression zones in response to mechanical stress. These processes are regulated by key cytokines, such as RANKL and IL-1, which are influenced by factors such as patient age and force application. This work evaluates the effectiveness of clear aligners versus traditional braces on periodontal health in patients with periodontitis, following PRISMA guidelines and utilizing specific inclusion and exclusion criteria. Methods: A systematic review of 1664 records was conducted, leading to the inclusion of eight studies that focus on the impact of orthodontic treatments on periodontal health. The review identifies various biases present in the literature. Results: The findings reveal that clear aligners, in contrast to fixed appliances, improve oral hygiene and reduce inflammation, leading to better periodontal outcomes. Fixed appliances, on the other hand, may exacerbate plaque accumulation and inflammation, which can worsen periodontal health. Conclusions: Clear aligners offer advantages over fixed appliances in terms of enhancing periodontal health, improving patient compliance, and providing long-term benefits, particularly in patients with severe periodontitis. The effectiveness of clear aligners is linked to better management of periodontal complications and overall oral hygiene. Treatment decisions should be based on patient-specific criteria to optimize outcomes.
A Surgical Hazard During Adenoidectomy in Children—A Case Report
Authors: Roje Željka , Kljajić Zlatko , Kolić Krešimir , Ilić Darko
Published: January 2025

Background: Adenoidectomy is one of the world’s most frequently performed surgical procedures. Although the operation is relatively simple and with a very low percentage of complications, it can sometimes be accompanied by fatal complications. One such scenario arises when an unrecognized aberrant course of the internal carotid artery is present, particularly if the artery is near or in contact with the oropharynx or nasopharynx. Methods: This report presents the case of a 3-year-old girl scheduled for adenoidectomy and the placement of ear aeration tubes. Following intubation, the oro-nasopharynx was inspected during the procedure, revealing a pulsatile mass suspected to be an aberrant right internal carotid artery (ICA). Results: A contrast-enhanced MSCT of the neck was performed, confirming the presence of an aberrant right carotid artery in direct contact with the posterior wall of the nasopharynx. Conclusions: In conclusion, a thorough visual and palpable examination by an otorhinolaryngologist after the induction of anesthesia, with the child’s neck in extension, is crucial for identifying aberrant carotid artery courses. Such careful assessment can help prevent potentially fatal complications.
Long-Term Corrosion Behavior of 434 Stainless Steel Coatings on T6061 Aluminum Alloy in Chloride Environments
Authors: Li Yaming , Li Wensheng , Chen Weiqian , Hong Hao , Zhang Ting
Published: January 2025

The low corrosion resistance of aluminum alloy materials in chloride environments limits their application in light metal structural components. In this study, 434 stainless steel (SS) powders with different numbers of scan layers were deposited on T6061 aluminum using high-velocity oxygen fuel (HVOF). Tafel curve, electrochemical impedance spectroscopy (EIS), salt spray, and galvanic corrosion tests were employed to investigate the comprehensive corrosion behavior of the SS coatings in a chlorine environment. The results showed that the porosity of the SS coatings decreased as the scanning layer increased. A lower porosity slowed the penetration of the corrosive solution and led to an enhanced long-term resistance to chloride attacks in immersion and salt spray corrosion. On this basis, the preferred SS4 sample and iron screw composition system was subjected to galvanic corrosion, and its electric current intensity (5.11 × 10−5 A) was two orders of magnitude lower than that of T6061 aluminum (9.14 × 10−3 A), as well as presenting better anti-corrosion behavior.
Commutative Quaternion Algebra with Quaternion Fourier Transform-Based Alpha-Rooting Color Image Enhancement
Authors: Grigoryan Artyom M. , Gomez Alexis A.
Published: January 2025

In this paper, we describe the associative and commutative algebra or the (2,2)-model of quaternions with application in color image enhancement. The method of alpha-rooting, which is based on the 2D quaternion discrete Fourier transform (QDFT) is considered. In the (2,2)-model, the aperiodic convolution of quaternion signals can be calculated by the product of their QDFTs. The concept of linear convolution is simple, that is, it is unique, and the reduction of this operation to the multiplication in the frequency domain makes this model very attractive for processing color images. Note that in the traditional quaternion algebra, which is not commutative, the convolution can be chosen in many different ways, and the number of possible QDFTs is infinite. And most importantly, the main property of the traditional Fourier transform that states that the aperiodic convolution is the product of the transform in the frequency domain is not valid. We describe the main property of the (2,2)-model of quaternions, the quaternion exponential functions and convolution. Three methods of alpha-rooting based on the 2D QDFT are presented, and illustrative examples on color image enhancement are given. The image enhancement measures to estimate the quality of the color images are described. Examples of the alpha-rooting enhancement on different color images are given and analyzed with the known histogram equalization and Retinex algorithms. Our experimental results show that the alpha-rooting method in the quaternion space is one of the most effective methods of color image enhancement. Quaternions allow all colors in each pixel to be processed as a whole, rather than individually as is done in traditional processing methods.
Lipid Nanoparticles and Skin: Discoveries and Advances
Authors: Santonocito Debora , Puglia Carmelo
Published: January 2025

Nowadays, skin is one of the organs most commonly affected by diseases (infections, inflammations, and injuries) due to exposure to the external environment. Although topical treatment represents the most suitable administration route, it is poorly effective due to the low permeability of the drug through the skin. Skin drug delivery by lipid nanocarriers (LNs) appears to be a suitable therapeutic strategy to overcome these issues, allowing it to reach a topical or systemic effect. Several LN-based products have been developed to enhance the permeation of bioactive compounds through the skin, obtaining interesting results in both pharmaceutical and cosmetic fields. Therefore, this review aims to analyze the scientific literature regarding the use of LNs to treat major skin diseases (psoriasis, wound healing, atopic dermatitis, and acne) and esthetic skin defects (wrinkles and cellulite). Furthermore, attention has been paid to the transdermal application of LNs (topical formulations, transdermal patches, and microneedles), being a new topic in recent years.
Blame Attribution and Compliance with COVID-19 Measures in Australia: The Theory of Planned Behaviour
Authors: Shim KyuJin , Zhang Dashi
Published: January 2025

This study scrutinizes the influence of “blame attribution” and the Theory of Planned Behaviour (TPB) on compliance with COVID-19 public health measures in Australia. This study elucidates that blaming individuals rather than governments surprisingly augments support for governmental regulations, highlighting the complexities of blame attribution in shaping public adherence to health policies. It underscores the nuanced roles of TPB elements like subjective norms and behavioural control, revealing that feelings of empowerment, social responsibility, and recognizing personal roles in pandemic control enhance the inclination to support governmental directives. The outcomes emphasize the criticality of understanding blame attribution and TPB dynamics for devising efficacious communication and management strategies, promoting societal adherence to essential regulations and actions during health crises, and fostering a more resilient societal infrastructure for dealing with pandemics.
MammoViT: A Custom Vision Transformer Architecture for Accurate BIRADS Classification in Mammogram Analysis
Authors: Al Mansour Abdullah G. M. , Alshomrani Faisal , Alfahaid Abdullah , Almutairi Abdulaziz T. M.
Published: January 2025

Background: Breast cancer screening through mammography interpretation is crucial for early detection and improved patient outcomes. However, the manual classification of mammograms using the BIRADS (Breast Imaging-Reporting and Data System) remains challenging due to subtle imaging features, inter-reader variability, and increasing radiologist workload. Traditional computer-aided detection systems often struggle with complex feature extraction and contextual understanding of mammographic abnormalities. To address these limitations, this study proposes MammoViT, a novel hybrid deep learning framework that leverages both ResNet50’s hierarchical feature extraction capabilities and Vision Transformer’s ability to capture long-range dependencies in images. Methods: We implemented a multi-stage approach utilizing a pre-trained ResNet50 model for initial feature extraction from mammogram images. To address the significant class imbalance in our four-class BIRADS dataset, we applied SMOTE (Synthetic Minority Over-sampling Technique) to generate synthetic samples for minority classes. The extracted feature arrays were transformed into non-overlapping patches with positional encodings for Vision Transformer processing. The Vision Transformer employs multi-head self-attention mechanisms to capture both local and global relationships between image patches, with each attention head learning different aspects of spatial dependencies. The model was optimized using Keras Tuner and trained using 5-fold cross-validation with early stopping to prevent overfitting. Results: MammoViT achieved 97.4% accuracy in classifying mammogram images across different BIRADS categories. The model’s effectiveness was validated through comprehensive evaluation metrics, including a classification report, confusion matrix, probability distribution, and comparison with existing studies. Conclusions: MammoViT effectively combines ResNet50 and Vision Transformer architectures while addressing the challenge of imbalanced medical imaging datasets. The high accuracy and robust performance demonstrate its potential as a reliable tool for supporting clinical decision-making in breast cancer screening.
Tomosynthesis-Guided Biopsy: A Troubleshooting Guide
Authors: Chahine Reve , Hijazi Madiha , Radwan Najwa , Berjawi Ghina , Nassar Lara
Published: January 2025

Since its introduction, digital breast tomosynthesis (DBT) has been widely incorporated in screening for breast cancer due to its lesser recall and higher cancer detection rates. Some screen-detected lesions may be visible only by DBT, requiring biopsy using DBT guidance. This review article dissects the different steps of tomosynthesis-guided biopsy and discusses the different obstacles that might be encountered during each step while providing the appropriate solutions, hence allowing physicians to perform a successful biopsy with the least patient discomfort.
Periodontitis Home Screening with Mouth Rinse Cut-Off 20 Ng/mL aMMP-8 Test and Mobile Application
Authors: Penttala Miika , Sorsa Timo , Thomas Julie Toby , Grigoriadis Andreas , Sakellari Dimitra , Gupta Shipra , Pärnänen Pirjo , Pätilä Tommi , Räisänen Ismo T.
Published: January 2025

Background: In this study, we describe a method by which a patient can independently assess their own periodontitis risk, for example, at home, with a mobile application. The aim of the study is to use active matrix metalloproteinase aMMP-8 mouth rinse cut-off 20 ng/mL point-of-care testing (POCT) and a polynomial function to reveal patients’ statistical risk of periodontitis. Methods: The polynomial function presented in this study was modeled with multiple logistic regression and the function estimates the risk of periodontitis using a probability measure. To investigate variables associated with periodontitis, we used data from adult patients visiting dental clinics in Thessaloniki, Greece. Results: The research results revealed that with appropriate information it is possible to obtain sufficient accuracy about a patient’s potential risk of periodontitis. The function for estimating risk of periodontitis is PERIORISK = (1 + e−(3.392×X1+0.002×X2+1.858×X3−9.151))−1, where X1 = aMMP-8 test result and tobacco smoking status, X2 = age × waist circumference and X3 = patient’s individual and parental history of diabetes. Conclusions: The prediction of periodontitis risk using an aMMP-8 test and a polynomial function seems to be a useful, non-invasive, safe-to-use and cost-effective tool for all people. Overall, in the model created, mouth rinse cut-off 20 ng/mL aMMP-8 test result, age, waist circumference, tobacco smoking status and patient’s individual and parental history of diabetes were found to be good factors explaining the risk of periodontitis.
Association of [68Ga]Ga-PSMA-11 PET/CT Metrics with PSA Persistence Following Radical Prostatectomy in Patients with Intermediate- and High-Risk Prostate Cancer
Authors: Rosales Juan J. , Betech-Antar Vicky , Mínguez Fernando , Guillén Edgar F. , Prieto Elena , Quincoces Gemma , Beorlegui Carmen , Fenor de la Maza María Dolores , Díez-Caballero Fernando , Miñana Bernardino , Pérez-Gracia José Luis , Rodríguez-Fraile Macarena
Published: January 2025

Background/Objectives: The aim of this study was to determine whether semiquantitative and volume-based metrics obtained from [68Ga]Ga-PSMA-11 PET/CT (PSMA-PET) scans before radical prostatectomy (RP) are associated with PSA persistence after surgery in patients with intermediate- (IR) and high-risk (HR) prostate cancer (PCa). Methods: We included 118 consecutive patients (IR = 57; HR = 61) with PCa with a PSMA-PET for initial staging and underwent subsequent RP. Clinical parameters and PSMA-PET metrics in the prostate were obtained to determine the following measurements: SUVmax, SUVmean, Target-to-Background Ratios (TBRs), Prostate Molecular Tumor (pMTV), Prostate Total Lesion Activity (pTLA), Prostate Volume (pV), and Prostate Disease Burden (pDB). The association of PSMA-PET metrics parameters before RP and PSA persistence were analyzed by multivariate logistic regression. Results: SUVmax and volume-based PSMA-PET metrics were significantly higher in patients with ISUP Grade 3–5 vs. ISUP Grade 1–2, and only pMTV, pTLA, and pDB were found to be significantly higher in HR patients, as compared with the IR group. During follow-up, 23 patients showed PSA persistence. pMTV, pTLA, and pDB were significantly higher among patients presenting PSA persistence after RP than in patients with undetectable PSA. Multivariate logistic regression analysis found that lymph node infiltration and pTLA were independent predictors for PSA persistence. A cut-off point of ≥25.1 allowed the best discrimination for PSA persistence (OR: 7.4; IQR: 1.4–39.1; p < 0.05). Conclusions: The identified association between PSA persistence and prostate TLA of PSMA-PET at initial staging highlights its potential as a valuable tool to improve risk prediction in prostate cancer patients. Further research is needed to confirm these results.
A New Lomax-G Family: Properties, Estimation and Applications
Authors: Baaqeel Hanan , Alnashshri Hibah , Baharith Lamya
Published: January 2025

Given the increasing number of phenomena that demand interpretation and investigation, developing new distributions and families of distributions has become increasingly essential. This article introduces a novel family of distributions based on the exponentiated reciprocal of the hazard rate function named the new Lomax-G family of distributions. We demonstrate the family’s flexibility to predict a wide range of lifetime events by deriving its cumulative and probability density functions. The new Lomax–Weibull distribution (NLW) is studied as a sub-model, with analytical and graphical evidence indicating its efficiency for reliability analysis and complex data modeling. The NLW density encompasses a variety of shapes, such as symmetrical, semi-symmetrical, right-skewed, left-skewed, and inverted J shapes. Furthermore, its hazard function exhibits a broad range of asymmetric forms. Five estimation techniques for determining the parameters of the proposed NLW distribution include the maximum likelihood, percentile, least squares, weighted least squares, and Cramér–von Mises methods. The performance of the estimators of the studied inferential methods is investigated through a comparative Monte Carlo simulation study and numerical demonstration. Additionally, the effectiveness of the NLW is validated by means of four real-world datasets. The results indicate that the NLW distribution provides a more accurate fit than several competing models.
CrackCLIP: Adapting Vision-Language Models for Weakly Supervised Crack Segmentation
Authors: Liang Fengjiao , Li Qingyong , Yu Haomin , Wang Wen
Published: January 2025

Weakly supervised crack segmentation aims to create pixel-level crack masks with minimal human annotation, which often only differentiate between crack and normal no-crack patches. This task is crucial for assessing structural integrity and safety in real-world industrial applications, where manually labeling the location of cracks at the pixel level is both labor-intensive and impractical. Addressing the challenges of labeling uncertainty, this paper presents CrackCLIP, a novel approach that leverages language prompts to augment the semantic context and employs the Contrastive Language–Image Pre-Training (CLIP) model to enhance weakly supervised crack segmentation. Initially, a gradient-based class activation map is used to generate pixel-level coarse pseudo-labels from a trained crack patch classifier. The estimated coarse pseudo-labels are utilized to fine-tune additional linear adapters, which are integrated into the frozen image encoders of CLIP to adapt the CLIP model to the specialized task of crack segmentation. Moreover, specific textual prompts are crafted for crack characteristics, which are input into the frozen text encoder of CLIP to extract features encapsulating the semantic essence of the cracks. The final crack segmentation is determined by comparing the similarity between text prompt features and visual patch token features. Comparative experiments on the Crack500, CFD, and DeepCrack datasets demonstrate that the proposed framework outperforms existing weakly supervised crack segmentation methods, and the pre-trained vision-language model exhibits strong potential for crack feature learning, thereby enhancing the overall performance and generalization capabilities of the proposed framework.
Exploring the Tourism and Economic Growth Relationship in Vietnam: A Cointegration Analysis with Model-Specific Structural Breaks
Authors: Kumar Ronald Ravinesh , Stauvermann Peter Josef , Dau Lien Thi Mai
Published: January 2025

In this study, we present a comprehensive analysis to examine the resilience of tourism in Vietnam since the Doi Moi period. Using an augmented Solow framework, data from 1986 to 2020, and the ARDL approach, we estimate the long-run and short-run effects, whilst accounting for model-specific structural breaks. To provide stronger validation and robustness of the results, we estimate eight models under four cases. We start with the base model, which includes tourism and capital (in per worker terms), and then augment it with factors that are carefully identified from the literature. The additional factors include urbanisation, financial development, trade openness, foreign direct investment (FDI), information and communication technology (ICT), and natural resources. We find that capital accumulation and tourism (in per worker terms) remain positive drivers of growth in all the estimations. Results from alternative models also highlight the pro-growth effects of urbanisation, financial development, and trade openness. A positive association between carbon emissions and economic growth is also noted, indicating the existing production–consumption setup, the pace of environmental harvesting, and the weak decoupling effects that could lead to negative externality in the long run. Factors like technology, natural resource rents, and FDI show negative effects on growth as well. Moreover, by examining the causality dynamics, the study further contributes to broader policy discussion. Hence, policies targeted to promote the growth process, and the advancement of the economy, should continue supporting capital accumulation, tourism development, urbanisation, financial development, and international trade. However, future economic policies should cautiously address emissions, natural resource use, and re-evaluate the gains from foreign direct investment (FDI) to ensure growth remains sustainable. With tourism and capital accumulation at the core of this study, the findings of this study are intended to generate deeper policy discussions on resource allocations and the need to harness and/or rely on contemporary sources of growth to promote the sustainable development of Vietnam.
Sociodemographic Teaching Variables with a Possible Impact on Educational Inclusion for Students with Giftedness in Portugal
Authors: Aguiar Ana Raquel C. , García-Perales Ramón , Rocha Alberto , Almeida Ana Isabel S.
Published: January 2025

This study explored the importance of ongoing, specialized training for Portuguese teachers about supporting gifted students in the context of inclusive education. This study was carried out with a sample of 863 school teachers in Portugal, using a questionnaire structured in four dimensions: conceptualization, legislation, identification and intervention. Female teachers demonstrated significantly greater knowledge and training across all dimensions. Similarly, teachers in urban schools had better results than those in rural areas, highlighting the need for greater support and resources for the latter. The findings of this study underline the urgency of reinforcing initial and ongoing teacher training to ensure that all students, regardless of their abilities, receive an education that meets their specific needs. The results also suggest that although Portuguese legislation is solid, it lacks more detailed guidelines that can effectively guide educational practices with these students. Greater commitment to teacher training, accompanied by consistent institutional support, is fundamental for promoting inclusive education that appreciates each student’s diversity and potential.
GENES: An Efficient Recursive zk-SNARK and Its Novel Application in Blockchain
Authors: Liu Jiaxi , Guo Li , Kang Tianyu
Published: January 2025

The rapid development of blockchain has significantly promoted research on zero-knowledge proofs (ZKPs), especially zero-knowledge succinct noninteractive arguments of knowledge (zk-SNARK). As is well known, protocol proof and verification time, as well as proof size, are the main obstacles that restrict the implementation of ZKPs in practical applications, so they have become the main concerns of researchers in recent years. This work achieves a new recursive zk-SNARK called GENES, which does not have a trusted setup and is secure under the standard discrete logarithm assumption. GENES is designed from the form of the rank-1 constraint system (R1CS) satisfiability problem. Recursive proof composition is achieved by merging multiple R1CS instances, which transforms the verification of numerous proofs into the verification of a single proof. Moreover, multi-helpers amortize proof commitments in this study, significantly reducing the computational pressure and time cost of proof generation. Compared with previous work, GENES effectively improves the proof time and verification time, but at the cost of larger proof sizes. We provide a blockchain Layer-1 scaling solution leveraging GENES to demonstrate its practicality.