bluuebunny/crossref_metadata_2025 huggingface dataset:
Multi-Objective Optimization of Injection Parameters and Energy Consumption Based on ANN-Differential Evolution
Authors: Oktora Devic , Ting Yu-Hung , Sukoyo
Published: January 2025

Injection molding (IM) is one complex manufacturing process characterized by nonlinear behavior. Unlike classic linear modeling techniques like simple regression, many machine learning (ML) models have the ability to adjust to the nonlinear behaviors and interactions between input and output parameters. Artificial neural networks (ANNs) specifically have demonstrated exceptional performance in problems involving nonlinear modeling. This work will employ complete factorial design of experiments (DoE) to acquire a dataset which is both resilient and suitable for training, validation, and testing purposes. The predictive model demonstrated outstanding performance throughout the training, validation, and test sets. The aggregate R2 values for the training, validation, and tests datasets were 97.58%, 93.76%, and 91.31%, respectively, demonstrating a strong ability to accurately foresee outcomes. Differential evolution (DE) successfully achieved a 2% decrease in weight and a notable 14% decrease in energy consumption. The results indicate that combining an ANN with DE is a viable approach for enhancing injection molding parameters, especially in scenarios with multiple objectives.
Effect of High Percentages of Coated Recycled Aggregates on the Flexural Behavior of Reinforced Concrete Beams
Authors: Martínez Catalina , Letelier Viviana , Wenzel Bruno
Published: January 2025

Currently, the use of recycled aggregates (RA) in new concrete is allowed by several international regulations, although their replacement is limited to low percentages of the coarse fraction. In order to increase the percentage of RA, several authors have studied different processes to improve the microstructure of its surface. Therefore, it is necessary to analyze whether the current standards simulate the structural behavior of concretes with high percentages of RA. For this purpose, beams with 0%, 50% and 100% RA replacement coated with recycled binder paste (RBP) were made and their behavior was compared with the equations of the Eurocode 2 and ACI 318-19 code. As a result, we found that when 100% coated RA was used, the reduction in compressive strength was only 12.73%, with similar cracking patterns observed in RA beams across all series. In addition, the load capacity of the beams with RA was higher than the theoretical values provided by the codes. Finally, the experimental critical deflection was higher than that calculated by the code equations. Thus, it is recommended that these higher deflections be taken into account at the time of design.
Investigation of Segmented Halbach Array Design for Passive Magnetorheological Brake System
Authors: Shiao Yaojung , Bollepelly Manichandra
Published: January 2025

The Halbach array is a significant advancement in designing permanent magnets with a specialized arrangement due to their unique capacity to generate strong unidirectional magnetic fields, which have attracted substantial attention in various applications. This arrangement allows for the construction of more efficient and compact magnetic systems, contributing to innovation across multiple fields. This study introduces a segmented Halbach array design using NdFeB permanent magnets in a cylindrical configuration, optimized to maximize flux density and minimize flux leakage. Critical design parameters, including the magnet dimensions and the gap width between the magnets, are systematically analyzed to identify the optimal arrangement. A corresponding simulation design was performed by COMSOL Multiphysics software, which can model complex magnetic fields and flux patterns. The proposed Halbach array design offers significant advantages over conventional magnet arrangements, including a 50% increase in flux density, a 75% reduction in magnet material usage, and improved magnetic field uniformity. Using the segmented Halbach arrangement in the development of passive magnetorheological braking systems can double the braking torque, leading to higher torque output in more compact designs. The outcomes of this research contribute to the progress of energy efficiency, providing efficient and reliable braking performance.
The Use of Machine Learning Methods in Road Safety Research in Poland
Authors: Borucka Anna , Sobczuk Sebastian
Published: January 2025

Every year, thousands of accidents occur in Poland, often resulting in severe injuries or even death. The implementation of solutions supporting road safety analysis and management processes is necessary to reduce the risk of accidents and minimize their consequences. One of the rapidly developing tools that can play a key role in this area is machine learning. The aim of this study was to develop mathematical models based on ML algorithms describing road safety in Poland. First, variables with the strongest impact on safety were extracted. Then, mathematical modeling was performed using the k-Nearest Neighbors, Random Forest, and RPart algorithms. The best choice for imbalanced data, especially when the goal is to identify rare classes, is the RF model. The KNN model provides a compromise in situations where the highest overall accuracy is desired. On the other hand, the RPart model can be used as a fast, basic model, but it requires improvements to handle rare classes. The results not only identified factors that significantly affect the severity of injuries or the number of fatalities in accidents but, above all, also demonstrated the ability of ML-based models to predict threats and their consequences.
A Multivariate Machine Learning Approach for the Prediction of Wind Turbine Blade Structural Dynamics
Authors: Ismaiel Amr
Published: January 2025

Wind turbine blade structural dynamics are crucial in the turbine structural design phase. Blade deflections and loads can affect the weight of the rotor as well as the power performance of a wind turbine if the deflections are extremely high. Predictions of the turbine’s blade deflections and loads can lead to informative decisions on optimizing the design of the blade. In this work, a multivariate machine learning (ML) approach is used to predict the blade’s dynamics based on the wind flow conditions and control actions of the turbine. Three different datasets were generated using the OpenFAST software tool for three different wind turbulence classes. Various ML algorithms were trained to predict the blade deflections at the tip and blade loads at the root in the edgewise and flapwise directions. The ML models were tested for generalization of the model to different flow conditions. A model is trained for one dataset with one of the turbulence classes and then used to predict the outputs of the other two datasets. The random forest ML algorithm gave the best accuracy for predicting the outputs for the dataset it was trained for, as well as the other two datasets. The accuracy of predictions was found to be higher in the edgewise direction for both load and deflection outputs. In the flapwise direction, the model could predict the outputs of the data it was trained for with an accuracy of around 99% and for the other two datasets with an accuracy of over 75%. While in the edgewise direction, the model trained on only one dataset gave a prediction accuracy above 95% for all three datasets.
An Improvement of the Lower Bound on the Maximum Number of Halving Lines for Sets in the Plane with an Odd Number of Points
Authors: Rodrigo Javier , López Mariló , Magistrali Danilo , Alonso Estrella
Published: January 2025

In this paper, we give examples that improve the lower bound on the maximum number of halving lines for sets in the plane with 35, 59, 95, and 97 points and, as a consequence, we improve the current best upper bound of the rectilinear crossing number for sets in the plane with 35, 59, 95, and 97 points, provided that a conjecture included in the literature is true. As another consequence, we also improve the lower bound on the maximum number of halving pseudolines for sets in the plane with 35 points. These examples, and the recursive bounds for the maximum number of halving lines for sets with an odd number of points achieved, give a new insight in the study of the rectilinear crossing number problem, one of the most challenging tasks in Discrete Geometry. With respect to this problem, it is conjectured that, for all n multiples of 3, there are 3-symmetric sets of n points for which the rectilinear crossing number is attained.
Effects of Predation-Induced Emigration on a Landscape Ecological Model
Authors: Cronin James T. , Fonseka Nalin , Goddard Jerome , Shivaji Ratnasingham , Xue Xiaohuan
Published: January 2025

Predators impact prey populations directly through consumption and indirectly via trait-mediated effects like predator-induced emigration (PIE), where prey alter movement due to predation risk. While PIE can significantly influence prey dynamics, its combined effect with direct predation in fragmented habitats is underexplored. Habitat fragmentation reduces viable habitats and isolates populations, necessitating an understanding of these interactions for conservation. In this paper, we present a reaction–diffusion model to investigate prey persistence under both direct predation and PIE in fragmented landscapes. The model considers prey growing logistically within a bounded habitat patch surrounded by a hostile matrix. Prey move via unbiased random walks internally but exhibit biased movement at habitat boundaries influenced by predation risk. Predators are assumed constant, operating on a different timescale. We examine three predation functional responses—constant yield, Holling Type I, and Holling Type III—and three emigration patterns: density-independent, positive density-dependent, and negative density-dependent emigration. Using the method of sub- and supersolutions, we establish conditions for the existence and multiplicity of positive steady-state solutions. Numerical simulations in one-dimensional habitats further elucidate the structure of these solutions. Our findings demonstrate that the interplay between direct predation and PIE crucially affects prey persistence in fragmented habitats. Depending on the functional response and emigration pattern, PIE can either mitigate or amplify the impact of direct predation. This underscores the importance of incorporating both direct and indirect predation effects in ecological models to better predict species dynamics and inform conservation strategies in fragmented landscapes.
Twofold Auxiliary Information Under Two-Phase Sampling: An Improved Family of Double-Transformed Variance Estimators
Authors: Daraz Umer , Agustiana Della , Wu Jinbiao , Emam Walid
Published: January 2025

Outlier values and rankings are important for emphasizing data distribution variability, which improves the accuracy and effectiveness of variance estimations. To enhance the estimation of finite population variance in a two-phase sampling framework, this study presents an improved class of double exponential-type estimators by utilizing the outlier values and ranks of an auxiliary variable. A theoretical analysis is conducted to derive the biases and mean squared errors (MSEs) of these estimators using first-order approximations. A comprehensive simulation study is then performed to analyze the performance of the proposed estimators. The results clearly show that the new estimators provide more precise estimates, achieving a higher percentage relative efficiency (PRE) across all simulated scenarios. Furthermore, three data sets are analyzed to further confirm the efficiency of the proposed estimators as compared to other existing estimators. These results emphasize the potential of the proposed class of estimators to optimize variance estimation techniques, making it a more cost-effective and accurate choice for researchers using two-phase sampling in a variety of domains.
Orthogonal Polynomials on Radial Rays in the Complex Plane: Construction, Properties and Applications
Authors: Milovanović Gradimir V.
Published: January 2025

Orthogonal polynomials on radial rays in the complex plane were introduced and studied intensively in several papers almost three decades ago. This paper presents an account of such kinds of orthogonality in the complex plane, as well as a number of new results and examples. In addition to several types of standard orthogonality, the concept of orthogonality on arbitrary radial rays is introduced, some or all of which may be infinite. A general method for numerical constructing, the so-called discretized Stieltjes–Gautschi procedure, is described and several interesting examples are presented. The main properties, zero distribution and some applications are also given. Special attention is paid to completely symmetric cases. Recurrence relations for such kinds of orthogonal polynomials and their zero distribution, as well as a connection with the standard polynomials orthogonal on the real line, are derived, including the corresponding linear differential equation of the second order. Finally, some applications in physics and electrostatics are mentioned.
Comparison of Mirroring and Overlapping Analysis and Three-Dimensional Soft Tissue Spatial Angle Wireframe Template in Evaluating Facial Asymmetry
Authors: Yang Gengchen , Lyu Liang , Wen Aonan , Zhao Yijiao , Wang Yong , Li Jing , Yan Huichun , Zhang Mingjin , Yu Yi , Yu Tingting , Liu Dawei
Published: January 2025

Aim: The purpose of this study was to evaluate the accuracy and efficacy of a new wireframe template methodology in analyzing three-dimensional facial soft tissue asymmetry. Materials and methods: Three-dimensional facial soft tissue data were obtained for 24 patients. The wireframe template was established by identifying 34 facial landmarks and then forming a template on the face with the MeshLab 2020 software. The angle asymmetry index was automatically scored using the template. The mirroring and overlapping technique is accepted as the golden standard method to diagnose facial asymmetry by acquiring deviation values of one’s face. Consistency rates between the two methodologies were determined through a statistical comparison of the angle asymmetry index and deviation values. Results: Overall consistency rates in the labial, mandibular angle, cheek, chin, and articular regions were 87.5%, 95.8%, 87.5%, 91.7%, and 100%, respectively. Regions with consistency rates in three dimensions of more than 85% are the x-axis and the z-axis of all regions and the y-axis of the mandibular angle, chin, and articular region. Conclusions: Soft tissue facial asymmetry can be diagnosed accurately and effectively by using a three-dimensional soft tissue spatial angle wireframe template. Precise localization of asymmetry can be offered, and indiscernible tiny asymmetry can be identified.
Can CT Image Reconstruction Parameters Impact the Predictive Value of Radiomics Features in Grading Pancreatic Neuroendocrine Neoplasms?
Authors: Tixier Florent , Lopez-Ramirez Felipe , Blanco Alejandra , Yasrab Mohammad , Javed Ammar A. , Chu Linda C. , Fishman Elliot K. , Kawamoto Satomi
Published: January 2025

The WHO grading of pancreatic neuroendocrine neoplasms (PanNENs) is essential in patient management and an independent prognostic factor for patient survival. Radiomics features from CE-CT images hold promise for the outcome and tumor grade prediction. However, variations in reconstruction parameters can impact the predictive value of radiomics. 127 patients with histopathologically confirmed PanNENs underwent CT scans with filtered back projection (B20f) and iterative (I26f) reconstruction kernels. 3190 radiomic features were extracted from tumors and pancreatic volumes. Wilcoxon paired tests assessed the impact of reconstruction kernels and ComBat harmonization efficiency. SVM models were employed to predict tumor grade using the entire set of radiomics features or only those identified as harmonizable. The models’ performance was assessed on an independent dataset of 36 patients. Significant differences, after correction for multiple testing, were observed in 69% of features in the pancreatic volume and 51% in the tumor volume with B20f and I26f kernels. SVM models demonstrated accuracy ranging from 0.67 (95%CI: 0.50–0.81) to 0.83 (95%CI: 0.69–0.94) in distinguishing grade 1 cases from higher grades. Reconstruction kernels alter radiomics features and iterative kernel models trended towards higher performance. ComBat harmonization mitigates kernel impacts but addressing this effect is crucial in studies involving data from different kernels.
Automated Audit and Self-Correction Algorithm for Seg-Hallucination Using MeshCNN-Based On-Demand Generative AI
Authors: Kim Sihwan , Park Changmin , Jeon Gwanghyeon , Kim Seohee , Kim Jong Hyo
Published: January 2025

Recent advancements in deep learning have significantly improved medical image segmentation. However, the generalization performance and potential risks of data-driven models remain insufficiently validated. Specifically, unrealistic segmentation predictions deviating from actual anatomical structures, known as a Seg-Hallucination, often occur in deep learning-based models. The Seg-Hallucinations can result in erroneous quantitative analyses and distort critical imaging biomarker information, yet effective audits or corrections to address these issues are rare. Therefore, we propose an automated Seg-Hallucination surveillance and correction (ASHSC) algorithm utilizing only 3D organ mask information derived from CT images without reliance on the ground truth. Two publicly available datasets were used in developing the ASHSC algorithm: 280 CT scans from the TotalSegmentator dataset for training and 274 CT scans from the Cancer Imaging Archive (TCIA) dataset for performance evaluation. The ASHSC algorithm utilizes a two-stage on-demand strategy with mesh-based convolutional neural networks and generative artificial intelligence. The segmentation quality level (SQ-level)-based surveillance stage was evaluated using the area under the receiver operating curve, sensitivity, specificity, and positive predictive value. The on-demand correction performance of the algorithm was assessed using similarity metrics: volumetric Dice score, volume error percentage, average surface distance, and Hausdorff distance. Average performance of the surveillance stage resulted in an AUROC of 0.94 ± 0.01, sensitivity of 0.82 ± 0.03, specificity of 0.90 ± 0.01, and PPV of 0.92 ± 0.01 for test dataset. After the on-demand refinement of the correction stage, all the four similarity metrics were improved compared to a single use of the AI-segmentation model. This study not only enhances the efficiency and reliability of handling the Seg-Hallucination but also eliminates the reliance on ground truth. The ASHSC algorithm offers intuitive 3D guidance for uncertainty regions, while maintaining manageable computational complexity. The SQ-level-based on-demand correction strategy adaptively minimizes uncertainties inherent in deep-learning-based organ masks and advances automated auditing and correction methodologies.
Morphological, Physiological, and Transcriptional Changes in Crocus sativus L. Under In Vitro Polyethylene Glycol-Induced Water Stress
Authors: Gusain Suman , Joshi Rohit
Published: January 2025

Saffron (Crocus sativus L.), a perennial geophyte from the Iridaceae family, blooms in autumn and thrives in Mediterranean-like climates. It is highly valued for its therapeutic and commercial uses. While saffron cultivation generally requires minimal water, insufficient irrigation can negatively impact its yield. Although numerous studies have explored the detrimental impact of drought on saffron under field conditions, its impact in vitro remains largely unexplored. The present study aims to investigate the effects of polyethylene glycol (PEG) 6000 at concentrations of 0%, 5%, and 10% in inducing drought stress on saffron shoots under controlled conditions. The research focuses on evaluating morphological, physiological, and biochemical changes and analyzing the expression of drought-responsive genes. Shoot establishment was carried out on Murashige and Skoog (MS) medium supplemented with 6 mg/L 6-benzyladenine (BAP) and 1 mg/L naphthaleneacetic acid (NAA), while PEG 6000 was used to induce drought stress. Various morphological, biochemical, and molecular parameters were assessed 30 days after stress induction. Increasing PEG concentrations in the medium significantly reduced shoot regeneration, leading to increased apical tissue browning. Significant chlorophyll and carotenoid level changes were observed in shoots exposed to higher PEG concentrations. PEG-induced drought led to decreased plant growth and biomass and lowered relative water content of leaves. Lipid peroxidation, membrane damage, and H2O2 content increased, indicating heightened stress levels. Proline concentration significantly increased in plants subjected to 5% and 10% PEG compared to controls. Non-enzymatic antioxidant activity (phenolics, flavonoids, % inhibition, total reducing power, and total antioxidant activity) also increased with the severity of stress. In contrast, a decrease in the activity of superoxide dismutase (SOD) and peroxidase was observed in PEG-treated shoots. Significant changes in the expression of drought-related genes, such as DREB1, DREB2, AREB1, DHN1 (Dehydrin), and SnRK2, were observed in shoots exposed to 5% and 10% PEG. In conclusion, the study highlights that PEG, as an inducer of drought stress, negatively impacts saffron’s growth and physiological responses under in vitro conditions. It also triggers significant changes in biochemical and molecular mechanisms, indicating the plant’s susceptibility to water scarcity.
Cyperus esculentus var. sativus Adapts to Multiple Heavy Metal Stresses Through the Assembly of Endophytic Microbial Communities
Authors: Liu Qiaofeng , Lai Jialing , Zhang Yaozhong , Wang Xin
Published: January 2025

Interactions between plants and their endophytes alter their metabolic functions and ability to cope with abiotic stresses. In this study, high-throughput sequencing was used to analyze the species diversity and functions of endophytes in Cyperus esculentus var. sativus (CES) tubers under different heavy metal stress conditions. The results indicated that the number of observed endophytic species in the tubers increased under heavy metal stress (p < 0.05), leading to changes in species diversity and composition. The response of tuber endophytes to different metal concentrations varied, with certain endophytic bacteria and fungi, such as Pseudomonas, Novosphingobium, and Fusarium, showing increased abundance and becoming the dominant species in the tubers. Additionally, new endophytic genera, Actinophytocola and Monosporascus, emerged at specific metal concentrations (p < 0.05). Fatty acid salvage was enriched in the endophytes of CES, which may play an important role in assisting CES in responding to multiple heavy metal stresses. These findings showed that CES tuber endophytes undergo adaptive changes to support the ability of plants to cope with heavy metal stress.
Pseudotyped Viruses: A Useful Platform for Pre-Clinical Studies Conducted in a BSL-2 Laboratory Setting
Authors: Rizatdinova Sofiia N. , Ershova Alina E. , Astrakhantseva Irina V.
Published: January 2025

The study of pathogenic viruses has always posed significant biosafety challenges. In particular, the study of highly pathogenic viruses requires methods with low biological risk but relatively high sensitivity and convenience in detection. In recent years, pseudoviruses, which consist of a backbone of one virus and envelope proteins of another virus, have become one of the most widely used tools for exploring the mechanisms of viruses binding to cells, membrane fusion and viral entry, as well as for screening the libraries of antiviral substances, evaluating the potential of neutralizing monoclonal antibodies, developing neutralization tests, and therapeutic platforms. During the outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), pseudotyped virus-based assays played a pivotal role in advancing our understanding of virus–cell interactions and the role of its proteins in disease pathogenesis. Such tools facilitated the search for potential therapeutic agents and accelerated epidemiological studies on post-infection and post-vaccination humoral immunity. This review focuses on the use of pseudoviruses as a model for large-scale applications to study enveloped viruses.
Restoration of Genetic Code in Macular Mouse Fibroblasts via APOBEC1-Mediated RNA Editing
Authors: Bhakta Sonali , Kodama Hiroko , Mimaki Masakazu , Tsukahara Toshifumi
Published: January 2025

RNA editing is a significant mechanism underlying genetic variation and protein molecule alteration; C-to-U RNA editing, specifically, is important in the regulation of mammalian genetic diversity. The ability to define and limit accesses of enzymatic machinery to avoid the modification of unintended targets is key to the success of RNA editing. Identification of the core component of the apoB RNA editing holoenzyme, APOBEC, and investigation into new candidate genes encoding other elements of the complex could reveal further details regarding APOBEC-mediated mRNA editing. Menkes disease is a recessive X-chromosome-linked hereditary syndrome in humans, caused by defective copper metabolism due to mutations in the ATP7A gene, which encodes a copper transport protein. Here, we generated plasmids encoding the MS2 system and the APOBEC1 deaminase domain and used a guide RNA with flanking MS2 sites to restore mutated Atp7a in fibroblasts from a macular mouse model of Menkes disease withs T>C mutation. Around 35% of the mutated C nucleotide (nt) was restored to U, demonstrating that our RNA editing system is reliable and has potential for therapeutic clinical application. RNA base editing via human RNA-guided cytidine deaminases is a potentially attractive approach for in vivo therapeutic application and provides opportunities for new developments in this field.
Generalisation of EEG-Based Pain Biomarker Classification for Predicting Central Neuropathic Pain in Subacute Spinal Cord Injury
Authors: Anderson Keri , Stein Sebastian , Suen Ho , Purcell Mariel , Belci Maurizio , McCaughey Euan , McLean Ronali , Khine Aye , Vuckovic Aleksandra
Published: January 2025

Background: The objective was to test the generalisability of electroencephalography (EEG) markers of future pain using two independent datasets. Methods: Datasets, A [N = 20] and B [N = 35], were collected from participants with subacute spinal cord injury who did not have neuropathic pain at the time of recording. In both datasets, some participants developed pain within six months, (PDP) will others did not (PNP). EEG features were extracted based on either band power or Higuchi fractal dimension (HFD). Three levels of generalisability were tested: (1) classification PDP vs. PNP in datasets A and B separately; (2) classification between groups in datasets A and B together; and (3) classification where one dataset (A or B) was used for training and testing, and the other for validation. A novel normalisation method was applied to HFD features. Results: Training and testing of individual datasets achieved classification accuracies of >80% using either feature set, and classification of joint datasets (A and B) achieved a maximum accuracy of 86.4% (HFD, support vector machine (SVM)). With normalisation and feature reduction (principal components), the validation accuracy was 66.6%. Conclusions: An SVM classifier with HFD features showed the best robustness, and normalisation improved the accuracy of predicting future neuropathic pain well above the chance level.
Medial Open-Wedge High Tibial Osteotomy with Partial Meniscectomy and Without Cyst Excision for Popliteal Cysts: A Case Series
Authors: Kim Kang-Il , Kim Jun-Ho
Published: January 2025

Introduction: Popliteal cysts (PCs) are occasionally accompanied by knee osteoarthritis (OA) and varus malalignment. However, whether concomitant arthroscopic excision of PCs with medial open-wedge high tibial osteotomy (MOWHTO) improves the osteoarthritic environment remains unclear. Therefore, this study assessed serial changes in C-size, medial meniscus extrusion (MME), and cartilage status for up to 2 years following an MOWHTO. Methods: This study retrospectively used serial magnetic resonance imaging (MRI) evaluations to assess 26 consecutive patients who underwent MOWHTO. Of the 26 patients, six with preoperative PCs were included. Based on the arthroscopic findings at the time of the MOWHTO, concomitant meniscal and chondral lesions, and whether or not partial meniscectomy was performed, were evaluated. All patients underwent second-look arthroscopy with plate removal 2 years postoperatively. The PC size, MME, and cartilage sub-scores in the medial compartment of the whole-organ MRI score (WORMS) were assessed by serial MRI preoperatively and at 3, 6, 18, and 24 months postoperatively. The recurrence of PCs and clinical outcomes, including the Rauschning–Lindgren grade, were also evaluated when serial MRI was performed. Moreover, changes in cartilage status were assessed using two-stage arthroscopy. Results: All patients underwent concomitant partial meniscectomy for medial meniscal tears in the posterior horn. A significant decrease in the mean size of preoperative PCs (27.4 ± 22.3 mm) was noted from 3 months postoperatively (8.7 ± 7.6 mm, p = 0.018), and thereafter. The mean size of PCs further decreased with time until 2 years (1.5 ± 4.0 mm, p = 0.018) following an MOWHTO with partial meniscectomy. Moreover, significant improvements in the MME and WORMS values were noted from 3 to 24 months postoperatively. Meanwhile, no PC recurrence occurred during the follow-up period and the preoperative Rauschning–Lindgren grade improved significantly with time after MOWHTO (p = 0.026). Furthermore, the two-stage arthroscopic assessments showed significant improvements in ICRS grade in the medial femoral condyle (p = 0.038). Conclusions: After an MOWHTO with partial meniscectomy, PCs decreased with time up to 2 years postoperatively; no recurrence occurred during the follow-up period, although cyst excision was not concomitantly performed. Furthermore, the reduction in PCs corresponded with improvements in MME and chondral lesions in the knee joint following the MOWHTO.
Dietary Interventions and Physical Activity as Crucial Factors in the Prevention and Treatment of Metabolic Dysfunction-Associated Steatotic Liver Disease
Authors: Rajewski Paweł , Cieściński Jakub , Rajewski Piotr , Suwała Szymon , Rajewska Alicja , Potasz Maciej
Published: January 2025

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common chronic liver disease worldwide and affects nearly 30% of the adult population and 10% of the pediatric population. It is estimated that this number will double by 2030. MASLD is one of the leading causes of hepatocellular carcinoma, cirrhosis, and liver transplantation, as well as a significant risk factor for cardiovascular disease and mortality. Due to the ever-increasing number of patients, the long-term asymptomatic course of the disease, serious complications, and lack of preventive programs, as well as insufficient awareness of the disease among patients and doctors themselves, MASLD is a growing interdisciplinary problem and a real challenge for modern medicine. The main cause of MASLD is an inappropriate lifestyle—inadequate nutrition and insufficient physical activity, which lead to various components of metabolic syndrome. Lifestyle changes—appropriate diet, weight reduction, and systematic physical activity—are also the basis for the prevention and treatment of MASLD. Hence, in recent years, so much importance has been attached to lifestyle medicine, to non-pharmacological treatment as prevention of lifestyle diseases. The narrative review presents possible therapeutic options for non-pharmacological management in the prevention and treatment of MASLD. The best documented and available diets used in MASLD were discussed, focusing on the benefits and drawbacks of the Mediterranean, high-protein, ketogenic, and intermittent fasting diets. In addition, the most recent recommendations regarding physical activity are summarized.
Aptamer-Conjugated Multi-Quantum Dot-Embedded Silica Nanoparticles for Lateral Flow Immunoassay
Authors: Yoo Kwanghee , Cho Hye-Seong , Kim Jaehi , Shin Minsup , Chu Jun-Sik , Jang Sohyeon , Bae Han-Joo , Jung Heung Su , Kang Homan , Jun Bong-Hyun
Published: January 2025

Lateral flow immunoassays (LFIAs) are widely used for their low cost, simplicity, and rapid results; however, enhancing their reliability requires the meticulous selection of ligands and nanoparticles (NPs). SiO2@QD@SiO2 (QD2) nanoparticles, which consist of quantum dots (QDs) embedded in a silica (SiO2) core and surrounded by an outer SiO2 shell, exhibit significantly higher fluorescence intensity (FI) compared to single QDs. In this study, we prepared QD2@PEG@Aptamer, an aptamer conjugated with QD2 using succinimidyl-[(N-maleimidopropionamido)-hexaethyleneglycol]ester, which is 130 times brighter than single QDs, for detecting carbohydrate antigen (CA) 19-9 through LFIA. For LFIA optimization, we determined the optimal conditions as a 1.0:2.0 × 10−2 ratio of polyethylene glycol (PEG) to aptamer by adjusting the amounts of PEG and aptamer, phosphate-buffered saline containing 0.5% Tween® 20 as a developing solution, and 0.15 μg NPs by setting the NP weight during development. Under these conditions, QD2@PEG@Aptamer selectively detected CA19-9, achieving a detection limit of 1.74 × 10−2 mg·mL−1. Moreover, FI remained stable for 10 days after detection. These results highlight the potential of QD2 and aptamer conjugation technology as a reliable and versatile sensing platform for various diagnostic applications.
Basic Characteristics of Ionic Liquid-Gated Graphene FET Sensors for Nitrogen Cycle Monitoring in Agricultural Soil
Authors: Shiraishi Naoki , Lu Jian , Fauzi Fatin Bazilah , Imaizumi Ryo , Tsukahara Toyohiro , Mogari Satoshi , Iida Shosuke , Matsukura Yusuke , Teramoto Satoshi , Yokoi Keisuke , Ichinose Izumi , Kimura Mutsumi
Published: January 2025

Nitrogen-based fertilizers are crucial in agriculture for maintaining soil health and increasing crop yields. Soil microorganisms transform nitrogen from fertilizers into NO3−–N, which is absorbed by crops. However, some nitrogen is converted to nitrous oxide (N2O), a greenhouse gas with a warming potential about 300-times greater than carbon dioxide (CO2). Agricultural activities are the main source of N2O emissions. Monitoring N2O can enhance soil health and optimize nitrogen fertilizer use, thereby supporting precision agriculture. To achieve this, we developed ionic liquid-gated graphene field-effect transistor (FET) sensors to measure N2O concentrations in agricultural soil. We first fabricated and tested the electrical characteristics of the sensors. Then, we analyzed their transfer characteristics in our developed N2O evaluation system using different concentrations of N2O and air. The sensors demonstrated a negative shift in transfer characteristic curves when exposed to N2O, with a Dirac point voltage difference of 0.02 V between 1 and 10 ppm N2O diluted with pure air. These results demonstrate that the ionic liquid-gated graphene FET sensor is a promising device for N2O detection for agricultural soil applications.
Advanced Magnetic Resonance Imaging for Early Diagnosis and Monitoring of Movement Disorders
Authors: Ortega-Robles Emmanuel , de Celis Alonso Benito , Cantillo-Negrete Jessica , Carino-Escobar Ruben I. , Arias-Carrión Oscar
Published: January 2025

Advanced magnetic resonance imaging (MRI) techniques are transforming the study of movement disorders by providing valuable insights into disease mechanisms. This narrative review presents a comprehensive overview of their applications in this field, offering an updated perspective on their potential for early diagnosis, disease monitoring, and therapeutic evaluation. Emerging MRI modalities such as neuromelanin-sensitive imaging, diffusion-weighted imaging, magnetization transfer imaging, and relaxometry provide sensitive biomarkers that can detect early microstructural degeneration, iron deposition, and connectivity disruptions in key regions like the substantia nigra. These techniques enable earlier and more accurate differentiation of movement disorders, including Parkinson’s disease, progressive supranuclear palsy, multiple system atrophy, corticobasal degeneration, Lewy body and frontotemporal dementia, Huntington’s disease, and dystonia. Furthermore, MRI provides objective metrics for tracking disease progression and assessing therapeutic efficacy, making it an indispensable tool in clinical trials. Despite these advances, the absence of standardized protocols limits their integration into routine clinical practice. Addressing this gap and incorporating these techniques more systematically could bring the field closer to leveraging advanced MRI for personalized treatment strategies, ultimately improving outcomes for individuals with movement disorders.
The Mechanisms of Inclusive Leadership on Newcomers’ Proactive Socialization Behaviors—An Exploration Based on the Proactive Motivation Model
Authors: Shi Jingyi , Ye Long , Ren Junnan
Published: January 2025

This study advances newcomers’ socialization research by identifying and investigating the antecedents of newcomers’ proactive behaviors, a perspective often overlooked within the current studies, which primarily focuses on the outcomes of such behaviors. Based on the proactive motivation model, our core hypothesis is that inclusive leadership allows newcomers to experience psychological changes in control beliefs (can-do motivation), state promotion focus (reason-to motivation), and positive affect (energized-to motivation), which are stimulated following proactive behaviors. We further consider an individual values variable—individual power distance orientation—as the boundary condition on the influence of inclusive leadership. Research was conducted on 353 newcomers with less than one year of work experience to test the above hypothesis. The results show that inclusive leadership positively and indirectly influences the newcomers’ proactive behaviors via state promotion focus and positive affect. However, the mediating effect of control beliefs was not significant. Furthermore, the positive association between inclusive leadership and two kinds of newcomer proactive motivations, and their accompanying indirect impacts on newcomers’ proactive behaviors, was proved stronger at lower levels of individual power distance orientation. Additionally, it has been discovered in a follow-up complementary study that the effect of control beliefs on newcomers’ proactive behaviors is transmitted through positive affect.
Experimental and Finite Element Analysis on the Structural Performance of Lightweight Hollow Slab Prefabricated Staircases
Authors: Liu Jingmin , Bao Yiming , Qin Kang
Published: January 2025

Prefabricated staircases are crucial components in modern architectural structures, but traditional concrete staircases are too heavy for efficient prefabrication, transportation, and construction. Therefore, this paper proposes a novel lightweight hollow slab prefabricated staircase (referred to as the KXB staircase). The staircase achieves hollow designs for steps and the baseplate by incorporating hollow tubes in the steps and adding polyethylene foam boards in the baseplate. Additionally, a standard prefabricated slab staircase (referred to as the CG staircase) was subjected to static loading tests to analyze failure characteristics, load-deflection curves, and strain distribution. A finite element model was created using ABAQUS (2020) and validated for accuracy through a comparison with experimental results. The results indicate that the novel lightweight hollow-slab prefabricated staircase surpasses conventional slab staircases in load capacity, deflection, and crack control. Furthermore, it achieves a 16% reduction in weight, a 28.6% improvement in load capacity, and a maximum error of 9.9% between the model and experimental results. The novel lightweight prefabricated staircase satisfies engineering requirements, minimizes transportation and hoisting costs, and demonstrates strong application potential.
Understanding the Role of Processes in Shaping the Compatibility of Contemporary Architecture in Historical Urban Environments
Authors: Choi Jeongyoon
Published: January 2025

The compatibility of contemporary architecture with historic urban contexts presents a complex and often contentious challenge for many cities, which have traditionally focused on physical design elements. This study emphasizes the critical role of procedural frameworks in shaping harmonious historic urban landscapes. Through case studies from Seoul and Gimpo in South Korea, Tomioka in Japan, and Graz in Austria, this study highlights the importance of processes such as design reviews, stakeholder engagement, and public education in urban heritage management. These processes—encompassing regulatory frameworks and the active involvement of communities and heritage experts—are found to be crucial as physical design elements in determining the success of integrating new developments into historical environments. Moreover, they must be adaptive to and capable of addressing the dynamic nature of urban environments while safeguarding cultural heritage values. This study reveals that procedural approaches, when properly implemented, enable the successful integration of contemporary architecture within historic contexts, fostering sustainable urban conservation. This study contributes to the evolving discourse on urban heritage management by broadening the concept of compatibility beyond mere design considerations to include the essential role of processes in shaping historical urban environments.
Is the Children’s 15-Minute City an Effective Framework for Enhancing Children’s Health and Well-Being? An Empirical Analysis from Western China
Authors: Wang Xiao , Huang Jingping , Qin Zhengyou , Gan Wei , He Zhen , Li Xiang
Published: January 2025

Increasing attention is being directed toward understanding the impact of urban built environments on children’s health. The concept of the 15-minute city, or “15-minute life circle”, in China is significant; however, the needs of the pediatric population are often overlooked. Walkability and accessibility to urban service facilities are crucial for promoting children’s well-being. This paper focuses on the old city of Guilin in western China as a case study. It investigates the service facilities within a 15-minute life circle that affect children’s physical health, mental health, and social engagement. Utilizing the Walking Index method, this study assesses the walkability and rationality of these facilities in 621 neighborhoods. Data were gathered from 200 questionnaires and interviews with children, concentrating on their daily use of these facilities, supplemented by a multi-source analysis. The findings reveal that the Walking Index in the study area is generally low, with an uneven distribution, primarily influenced by road network density, block size, and urban landscape patterns. This study proposes the development of a “Children’s Healthy 15-minute Life Circle”, which would increase child-friendly service facilities, pedestrian infrastructure, and urban road network density. It also advocates for constructing service facilities that enhance children’s health and the optimization of the spatial arrangement of these facilities. Furthermore, it suggests the effective utilization of urban landscapes to create a diverse system of leisure spaces for children. This study offers valuable insights for enhancing the walkability of urban life circle service facilities and establishing a child-friendly city.
Shear Performance of Vertical Joints in Wind Turbine Concrete Towers with Different Interface Processes
Authors: Zhou Yang , Hao Ertong , Ran Yudong , Cao Hai , Li Yane , Tan Jike
Published: January 2025

As a weak part of the concrete tower in wind turbines, the insufficient shear capacity of vertical joints can cause the local shear failure of the tower, reduce the overall bearing capacity and stability of the tower, and lead to safety issues. At present, the splicing of tower vertical joints mainly uses epoxy resin filling and arc bolt connections. However, sometimes the concrete near the vertical joints is damaged due to compression after applying pretension to the arc bolts, which will affect the bearing capacity and stability of the entire tower structure. If other interface processes are used for vertical joint splicing, the shear performance will be directly affected. Therefore, in order to study the influence of different interface processes on the shear performance of vertical joints in concrete tower tubes, four vertical joint specimens were designed for a pull-out test under shear load and the failure mode of the specimens and the shear capacity of the vertical joint interface were analyzed and studied. The results showed that with an increase in epoxy thickness and the application of an interface chiseling treatment, as well as injecting epoxy resin into the channels, the shear performance of vertical joints could be enhanced. Finally, based on existing research and standardized design methods, the shear capacity of vertical joints in wind turbine concrete towers was predicted, which showed that the existing design methods were not yet fully applicable to the shear capacity design of vertical joints in wind turbine concrete towers with different interface processes. Further research is needed to supplement and improve them.
Recycling of Building Interior Decoration and Renovation Waste: A Case Study in China
Authors: Pan Wenjia , Zhang Hong , Hei Shanggang , Yang Yingjian , Xu Xifeng , Zhou Chao , Huang Baolin , Xu Haochen
Published: January 2025

Of all the construction waste, the building interior decoration and renovation waste (D&R waste) is difficult to dispose of and recycle due to its complex components and varied producers. The goal of this study is to reveal the current situation of D&R waste disposal through case studies and put forward the correlation proposal to improve standards of D&R waste recycling. This study investigated the various stages of the D&R waste management process, including generation, collection, transportation, sorting, recycling, and landfilling. Detailed studies were conducted for (i) the composition of D&R waste and (ii) the material flow analysis (MFA) of D&R waste recycling in different cases with different sorting technology. The results show that (i) concrete, stone, and other hard inorganic materials accounted for about 35–55% of the total. Soft inorganic materials such as aerated concrete and gypsum made up 5–25%, slag 15–20%, timber 5–10%, combustible matter such as plastic, rubber, and paper 9–12%, and glass and metal 1–5%, and (ii) artificial intelligence (AI) sorting offers better sorting performance and economic advantages over manual sorting, promoting the application of artificial AI sorting equipment as important solutions to face the key challenges of D&R waste recycling.