bluuebunny/crossref_metadata_2025 huggingface dataset:
Hierarchical Dynamic Spatio-Temporal Graph Convolutional Networks with Self-Supervised Learning for Traffic Flow Forecasting
Authors: Wei Siwei , Song Yanan , Liu Donghua , Shen Sichen , Gao Rong , Wang Chunzhi
Published: September 2024

It is crucial for both traffic management organisations and individual commuters to be able to forecast traffic flows accurately. Graph neural networks made great strides in this field owing to their exceptional capacity to capture spatial correlations. However, existing approaches predominantly focus on local geographic correlations, ignoring cross-region interdependencies in a global context, which is insufficient to extract comprehensive semantic relationships, thereby limiting prediction accuracy. Additionally, most GCN-based models rely on pre-defined graphs and unchanging adjacency matrices to reflect the spatial relationships among node features, neglecting the dynamics of spatio-temporal features and leading to challenges in capturing the complexity and dynamic spatial dependencies in traffic data. To tackle these issues, this paper puts forward a fresh approach: a new self-supervised dynamic spatio-temporal graph convolutional network (SDSC) for traffic flow forecasting. The proposed SDSC model is a hierarchically structured graph–neural architecture that is intended to augment the representation of dynamic traffic patterns through a self-supervised learning paradigm. Specifically, a dynamic graph is created using a combination of temporal, spatial, and traffic data; then, a regional graph is constructed based on geographic correlation using clustering to capture cross-regional interdependencies. In the feature learning module, spatio-temporal correlations in traffic data are subjected to recursive extraction using dynamic graph convolution facilitated by Recurrent Neural Networks (RNNs). Furthermore, self-supervised learning is embedded within the network training process as an auxiliary task, with the objective of enhancing the prediction task by optimising the mutual information of the learned features across the two graph networks. The superior performance of the proposed SDSC model in comparison with SOTA approaches was confirmed by comprehensive experiments conducted on real road datasets, PeMSD4 and PeMSD8. These findings validate the efficacy of dynamic graph modelling and self-supervision tasks in improving the precision of traffic flow prediction.
Serum Klotho Is Elevated in Patients with Acute Myocardial Infarction and Could Predict Poor In-Hospital Prognosis
Authors: Pei Yuanyuan , Huang Wenfeng , Cao Lingjie , Yang Fengtao , Chi Cheng , Zhu Jihong
Published: September 2024

Introduction: Klotho has emerged as a potential protective factor for cardiovascular diseases recently. Nevertheless, the levels of serum Klotho in acute coronary syndrome (ACS) have not been reported. Hence, we undertook a study to investigate the potential correlation between serum Klotho and ACS patients. Method: This observational cohort study was conducted at Peking University People’s Hospital between May 2016 and April 2020. Upon admission, we collected the patients’ clinical data and conducted ELISA tests to measure their serum Klotho levels. Result: A total of 349 patients were enrolled in this study, including 14 patients with UA and 335 patients with AMI. We observed that serum Klotho levels were obviously higher in the AMI group compared to the UA group (median 479.8 vs. 233.8 pg/mL, p = 0.035). In addition, serum Klotho levels were positively correlated with cardiac function and more pronounced in patients who died in the hospital (median 721.1 vs. 468.3 pg/mL, p < 0.001). A logistic regression analysis indicated that age ≥ 78 years old, HR ≥ 90 bpm, Killip classification ≥ 3 grade, and serum Klotho > 645.0 pg/mL were risk factors for poor prognosis. Conclusions: Serum Klotho is obviously increased in patients with AMI and with a positive correlation with cardiac function, and its elevation could serve as a predictor of poor prognosis in ACS patients.
Stress Echocardiography in the Follow-Up of Young Patients with Repaired Aortic Coarctation
Authors: Di Salvo Giovanni , Fumanelli Jennifer , Graziano Serena , Pozza Alice , Cattapan Irene , Moscatelli Sara , Castaldi Biagio , Galzerano Domenico
Published: September 2024

Background: Aortic coarctation (CoA) is a congenital heart disease affecting 5–8% of patients, with long-term complications persisting despite successful correction. Stress echocardiography (SE) is increasingly used for evaluating cardiac function under stress, yet its role in repaired CoA remains under-explored. Objective: This study aimed to assess the predictive value of SE and myocardial strain in repaired CoA patients with a history of hypertension without significant gradients or with borderline gradients at rest. Methods: Between June 2020 and March 2024, we enrolled 35 consecutive CoA patients with successful repairs and either a history of hypertension or borderline Doppler gradients. Baseline and peak exercise echocardiographic measurements, including left ventricular mass index (LVMi) and global longitudinal strain (LVGLS), were recorded. Patients were followed for up to 4 years. Results: At baseline, the positive SE group had higher systolic blood pressure (SBP) and diastolic blood pressure (DBP) compared to the negative SE group. The positive SE group also exhibited significantly higher basal and peak trans-isthmic gradients. Positive SE was found in 45.7% of patients, with 68.7% of these requiring re-intervention during follow-up. A peak trans-isthmic gradient > 61 mmHg during exercise predicted recoarctation with 100% sensitivity and 71% specificity (AUC = 0.836, p < 0.004). Conclusions: SE identifies at-risk patients post-CoA repair, aiding in early intervention. A peak trans-isthmic gradient > 61 mmHg during exercise is a strong predictor of recoarctation. These findings support incorporating SE into routine follow-up protocols for CoA patients, particularly those with a history of hypertension and borderline gradients, to improve long-term outcomes and quality of life.
Advancing Thermochromic Glass Durability: Reinforcing Thermosensitive Hydrogels with Enhanced Adhesion Techniques
Authors: Qian Dewei , Peng Suili , Zhang Tao , Qin Liang , Wen Weijia
Published: September 2024

The growing use of glass in architecture has driven research into reducing its energy consumption. Thermochromic (TC) glass technology shows promise for enhancing building energy efficiency by regulating solar heat dynamically. Although TC glass helps reduce heat radiation, additional solutions like Low-E or vacuum glass are needed to control heat convection and conduction. Low-E glass, while effective in lowering heat transfer, may increase surface temperature. Thermo-sensitive hydrogels, known for their light-scattering properties at high temperatures, have been explored to complement TC glass. However, their stability at elevated temperatures remains a challenge, especially for applications requiring durability under varying weather conditions. This study proposes enhancing the adhesion between hydrogel and glass by introducing silica–oxygen bonds. As a result, TC glass demonstrates stable performance over 100 cycles within temperature ranges from 85 °C to 30 °C in summer and 40 °C to −20 °C in winter. Furthermore, by incorporating ethylene glycol, the freezing point of TC glass is reduced to −26 °C, rendering it suitable for use in colder regions. The implementation of TC glass effectively addresses the dual requirements of summer shading and winter heating in areas with both cold winters and hot summers, significantly reducing building energy consumption. This study contributes substantially to developing advanced intelligent building materials, paving the way for more sustainable architectural designs.
Short-Term Hydrolytic Degradation of Mechanical Properties of Absorbable Surgical Sutures: A Comparative Study
Authors: Szabelski Jakub , Karpiński Robert
Published: September 2024

Surgical sutures play a crucial role in wound closure, facilitating the tissue-healing process across various fields of medicine. The objective of this study was to analyse the impact of seasoning time during the initial days/weeks of seasoning in Ringer’s solution on the mechanical properties of five commercial absorbable sutures: SafilQuick+®, Novosyn®, MonosynQuick®, Monosyn® and Monoplus®, each with different absorption periods. The results demonstrated that the SafilQuick+ and MonosynQuick sutures lost strength within 9–12 days, as evidenced by statistically significant changes in tensile strength. In contrast, the Novosyn and Monoplus sutures did not exhibit significant changes in strength during the study period. Statistical analysis confirmed significant differences in the behaviour of the individual sutures, highlighting the importance of selecting appropriate suture material in the context of the specific medical procedure.
Experimental Study on Dry Milling of Stir-Casted and Heat-Treated Mg-Gd-Y-Er Alloy Using TOPSIS
Authors: Upadrashta Abhinav , Saravanan Sudharsan , Annamalai A. Raja
Published: September 2024

This study examines the dry milling process of a rare-earth-based magnesium alloy, emphasizing the optimization of the milling parameters and their impact on the surface quality, cutting forces, and the rate of material removal. The objective is to improve our comprehension of the milling behavior of the Mg-Gd-Y-Er alloy. The Taguchi technique is adopted to formulate the experimental design. This study methodically investigates the influence of heat treatment (T4 and T6) on milling performance, and the effects of speed, feed rate, and depth of cut. The output variables considered for this investigation are the surface roughness (Ra, Rz, Sa, and Sz), material removal rate (MRR), and cutting force. To optimize the milling parameters and achieve superior outcomes, the multi-objective optimization technique TOPSIS is used. At a feed rate of 150 mm/min, a spindle speed of 1500 rpm, and a depth of cut of 1 mm, the T4-treated sample exhibits a minimum surface roughness value of 0.0305 µm. The highest resultant force values of 96.4416 N and 176.1070 N for 200 °C and 225 °C T6-treated alloys are obtained by combining process parameters such as a spindle speed of 1500 rpm, a feed rate of 50 mm/min, and a depth of cut of 1.5 mm. Furthermore, the maximum closeness coefficient value is achieved by combining a spindle speed of 1000 to 1500 rpm, a feed rate of 150 mm/min, and a depth of cut of 0.5 mm to 1 mm. The closeness coefficient value is significantly influenced by the most significant process parameters, as indicated by the ANOVA results.
Ocean Currents Velocity Hindcast and Forecast Bias Correction Using a Deep-Learning Approach
Authors: Muhamed Ali Ali , Zhuang Hanqi , Huang Yu , Ibrahim Ali K. , Altaher Ali Salem , Chérubin Laurent M.
Published: September 2024

Today’s prediction of ocean dynamics relies on numerical models. However, numerical models are often unable to accurately model and predict real ocean dynamics, leading to a lack of fulfillment of a range of services that require reliable predictions at various temporal and spatial scales. Indeed, a numerical model cannot fully resolve all the physical processes in the ocean due to various reasons, including biases in the initial field and calculation errors in the numerical solution of the model. Thus, bias-correcting methods have become crucial to improve the dynamical accuracy of numerical model predictions. In this study, we present a machine learning-based three-dimensional velocity bias correction method derived from historical observations that applies to both hindcast and forecast. Our approach is based on the modification of an existing deep learning model, called U-Net, designed specifically for image segmentation analysis in the biomedical field. U-Net was modified to create a Transform Model that retains the temporal and spatial evolution of the differences between the model and observations to produce a correction in the form of regression weights that evolves spatially and temporally with the model both forward and backward in time, beyond the observation period. Using daily ocean current observations from a 2.5-year current meter array deployment, we show that significant bias corrections can be conducted up to 50 days pre- or post-observations. Using a 3-year-long virtual array, valid bias corrections can be conducted for up to one year.
Periodic Behavior and Noise Characteristics of Cavitating Flow around Two-Dimensional Hydrofoils
Authors: Heo Namug , Kim Ji-Hye
Published: September 2024

The occurrence of cavitation in marine propellers is a major source of noise in ships. Consequently, the occurrence and noise characteristics of cavitation must be better understood to control this issue. This study focuses on identifying the occurrence and noise characteristics of cavitating flow around two-dimensional (2D) hydrofoils. Using the commercial computational fluid dynamics software STAR-CCM+, a numerical analysis was conducted on the partial cavity flow occurring around 2D hydrofoils at specific angles of attack. In addition, the cavitation noise characteristics were analyzed by conducting a frequency analysis using the predicted pressure data obtained via a fluctuating pressure sensor positioned vertically above the hydrofoil. Consequently, the numerical results were compared with existing experimental data to validate the accuracy of the simulation. This study identifies the limitations of the Reynolds-averaged Navier–Stokes (RANS) method by closely comparing it with the large eddy simulation (LES) method for assessing noise characteristics in unsteady cavitating flow. Although RANS has limitations in qualitatively assessing periodic behavior compared to LES, it effectively predicts cavitation extent and is valuable for relative assessments in practical applications.
Diagnostic Value of Serum Biomarkers for Invasive Aspergillosis in Haematologic Patients
Authors: Montesinos Isabel , Saad Albichr Imane , Collinge Elodie , Delaere Bénédicte , Huang Te-Din , Bogaerts Pierre , Deckers Corentin , Hamouda Mai , Honoré Patrick , Bulpa Pierre , Sonet Anne
Published: September 2024

Background: Invasive aspergillosis (IA) is a significant cause of morbidity and mortality in patients with haematological malignancies. Accurate diagnosis of IA is challenging due to non-specific symptoms and the impact of antifungal prophylaxis on biomarker sensitivity. Methods: This retrospective study evaluated the diagnostic performance of three serum biomarkers: Aspergillus Galactomannan Ag VirClia Monotest® (VirClia), Wako β-D-Glucan Test® (Wako BDG), and MycoGENIE Real-Time PCR® (MycoGENIE PCR). True positives were defined as patients with proven or probable IA (n = 14), with a positive Platelia Aspergillus Antigen® (Platelia) serving as a mycological criterion. True negatives were identified as patients with a positive Platelia assay but classified as non-probable IA (n = 10) and outpatients who consistently tested negative with the Platelia test throughout the study period (n = 20). Results: Most patients diagnosed with proven or probable IA were acute myeloid leukaemia or myelodysplastic syndrome patients receiving mould-active antifungal prophylaxis or treatment (71%). VirClia demonstrated high sensitivity (100%) for detecting IA, with a specificity of 83%. Wako BDG and MycoGENIE PCR showed lower sensitivities for IA (57% and 64%, respectively). MycoGENIE PCR detected Aspergillus spp. and Mucorales in two patients. Conclusions: Accurate diagnosis of IA remains challenging, especially in patients who have received mould-active antifungal treatment. VirClia showed comparable performance to Platelia, suggesting its potential for routine use. However, Wako BDG and MycoGENIE PCR results were less favourable in our study cohort. Nevertheless, MycoGENIE PCR detected two probable co-infections with Aspergillus spp. and Mucorales.
Dysfunctional High-Density Lipoprotein Cholesterol and Coronary Artery Disease: A Narrative Review
Authors: Madaudo Cristina , Bono Giada , Ortello Antonella , Astuti Giuseppe , Mingoia Giulia , Galassi Alfredo Ruggero , Sucato Vincenzo
Published: September 2024

High-density lipoprotein (HDL) cholesterol is traditionally viewed as protective against cardiovascular disease (CVD). However, emerging evidence reveals that dysfunctional HDL, characterized by impaired reverse cholesterol transport (RCT), reduced anti-inflammatory and antioxidant activities and increased endothelial dysfunction, which can contribute to coronary artery disease (CAD). Dysfunctional HDL, resulting from oxidative modifications of Apolipoprotein A-1 (Apo A-1) and enzyme inactivation, fails to effectively remove cholesterol from peripheral tissues and may promote inflammation and atherosclerosis. Genetic mutations affecting HDL metabolism further complicate its role in cardiovascular health. Studies have shown that conventional therapies aimed at raising HDL-C levels do not necessarily reduce cardiovascular events, highlighting the need for new approaches that improve HDL functionality. Therapeutic strategies such as Apo A-1 mimetic peptides, reconstituted HDL infusions, and drugs targeting specific HDL metabolic pathways are being explored. Additionally, weight loss, statin therapy, and niacin have shown potential in enhancing HDL function. The pathophysiology of dysfunctional HDL involves complex mechanisms, including oxidative stress, inflammation, and genetic mutations, which alter its structure and function, diminishing its cardioprotective effects. New functional assays, such as the cholesterol efflux capacity (CEC) and HDL inflammatory index, provide more accurate predictions of cardiovascular risk by assessing HDL quality rather than quantity. As research progresses, the focus is shifting towards therapeutic strategies that enhance HDL function and address the root causes of its dysfunction, offering a more effective approach to reducing cardiovascular risk and preventing CAD.
Investigation of Depression and Post-Traumatic Growth in Renal Transplant Recipients via Self-Assessment
Authors: Simsek Yaban Zuleyha , Bulbuloglu Semra
Published: September 2024

Objective: In this study, we aimed to determine post-traumatic growth and depression levels in renal transplant recipients and the relationship between these two variables. Design and Methods: The study was conducted with a descriptive, cross-sectional, and correlational design. The data for the study were collected at the organ transplant unit of a research and training hospital located in the west of Turkey. The sample of the study included 122 kidney transplant recipients (n = 122). A Sociodemographic Information Form, the Post-Traumatic Growth (PTG) Inventory, and the Beck Depression Inventory (BDI) were employed to collect data. In the analyses of the data, descriptive statistics, ANOVA, an independent-samples t-test, post hoc tests, and Pearson correlation tests were used. Results: As the ages of the renal transplant recipients increased, their depression scores decreased, while their PTG scores increased. Higher depression levels were identified in the female participants compared to the male participants and in those with a low income compared to other income groups. The lowest PTG levels were found in the recipients who received their kidney transplants from third-degree relatives. Age, gender, economic status, and time of transplant were predictors of depression. The identity of the donor was the most significant predictor of PTG (62% explanation rate). A strong and inverse correlation was found between depression and PTG (p < 0.05). Conclusions: Post-traumatic growth was found to decrease depression. However, while poor economic status led to depression, high economic status did not lead to a significant change in PTG. As education levels increased, PTG decreased, but education status did not have any significant effect on depression. On the other hand, there was a negative correlation between PTG and depression. The results obtained in this study are valuable and important in terms of understanding depression better and determining PTG as a significant factor that could alleviate it.
Optimizing Anticoagulation in Valvular Heart Disease: Navigating NOACs and VKAs
Authors: Ouatu Anca , Buliga-Finiș Oana Nicoleta , Tanase Daniela Maria , Badescu Minerva Codruta , Dima Nicoleta , Floria Mariana , Popescu Diana , Richter Patricia , Rezus Ciprian
Published: September 2024

Background/Objectives: Non-vitamin K antagonist oral anticoagulants (NOACs) have demonstrated similar effectiveness and safety profiles to vitamin K antagonists (VKAs) in treating nonvalvular atrial fibrillation (AF). Given their favorable pharmacological profile, including the rapid onset and offset of action, fixed dosing, and predictable pharmacokinetics with a consistent dose-response relationship, reducing the need for frequent blood tests, researchers have investigated the potential of NOACs in patients with AF and valvular heart disease (VHD). Methods: Clinical trials, excluding patients with mechanical prosthetic valves or moderate/severe mitral stenosis, have shown the benefits of NOACs over VKAs in this population. However, there is a need for further research to determine if these findings apply to mechanical valve prostheses and NOACs. Results: Several ongoing randomized controlled trials are underway to provide more definitive evidence regarding NOAC treatment in moderate to severe rheumatic mitral stenosis. Importantly, recent trials that included patients with atrial fibrillation and bioprosthetic valves (also transcatheter heart valves) have provided evidence supporting the safety of NOACs in this specific patient population. Ongoing research aims to clearly define the specific scenarios where NOACs can be safely and effectively prescribed for various types of VHD, including moderate/severe mitral stenosis and mechanical valves. Conclusions: The aim of this review is to accurately identify the specific situations in which NOACs can be prescribed in patients with VHD, with a focus centered on each type of valvulopathy.
Investigating Painkiller Use in Amateur Football: A Coach’s Perspective
Authors: Kopf Andreas , Krutsch Werner , Szymski Dominik , Weber Johannes , Alt Volker , Bail Hermann Josef , Engel Niklas , Rüther Johannes , Huber Lorenz
Published: September 2024

Background/Objectives: Painkiller use in amateur sports and, especially, in football is increasingly being discussed, but the scientific data on this field are very limited. Therefore, the aim of this study was to investigate the prevalence of painkiller use in amateur football from the perspective of coaches, as well as to determine how and to which extent coaches can influence their teams in terms of painkiller use and prevention. Methods: Using an online questionnaire, a cross-sectional analysis of painkiller use in German amateur football from the 4th league to the lowest amateur classes was carried out from the perspective of team coaches. A total of 628 participants were contacted, and 400 (63.7%) completed the questionnaire completely and were therefore included in the evaluation. Results: Of the 400 participating team coaches in amateur football, 369 (92.3%) were male and 31 (7.7%) were female. The coaches reported that 36.2% (SD = 29.1) of their players have used painkillers at some point due to football-related pain in their career. The majority of coaches believed that the use of painkillers is not compatible with competition (74%), and even more believed that it is not compatible with football training (90.8%). Furthermore, 56.2% of the coaches themselves had already taken painkillers in their own football career for football-related pain, and 64% had already bought over-the-counter painkillers without a prescription. The use of painkillers increased in the higher playing levels. The availability of painkillers in first aid kits was reported by around 60%, but they were reported as freely accessible in the dressing room by only 10% of the coaches. Conclusions: This is the first study to describe the painkiller use in amateur football from the perspective of coaches. The prevalence of painkiller use in this study was found to be significantly lower than what is indicated in the data from the existing literature. The majority of coaches see the use of painkillers during games and training as incompatible, even though there is a large proportion of coaches who have already bought over-the-counter painkillers for football-related pain. As the first scientific analysis of team coaches, this study provides fundamental data for the prevention of excessive painkiller use in amateur football.
Boosting Customers’ Co-Creation in Open-Source Software Environments: The Role of Innovativeness and a Sense of Community
Authors: Rebelo Antonio , Varela-Neira Concepción , Ruzo-Sanmartín Emilio
Published: September 2024

The increasing need for continuous innovation has given rise to a substantial increase in co-creation initiatives. Since the co-creation of value involves customers participating in the creation of product offerings voluntarily and actively, this investigation tries to understand what drives customers to participate in these co-creation initiatives. To do so, this study employs a probabilistic sample of 683 users enrolled in Linux forums for open-source software distributions. The path analysis and bootstrap samples revealed that customers who exhibit a high innate innovativeness and feel that they belong in the online community show a greater motivation towards platform exploration and participation in co-creation. Moreover, the effect of this synergic interaction on their co-creation participation was partially mediated by the normative dimension of their intrinsic motivation, while the hedonic dimension was not a strong predictor of co-creation contributions. This study fills the voids in the existing literature by showcasing the relevance of personal characteristics, beyond individual motivation, in co-creation behavior.
Metabolic Shift and Hyperosmolarity Underlie Age-Related Macular Degeneration
Authors: Schwartz Laurent , Schwartz Jules , Henry Marc , Bakkar Ashraf
Published: September 2024

Age-related macular degeneration (AMD) is both a poorly understood and devastating disease. Here, we analyze the physico-chemical forces at stake, including osmolarity, redox shift, and pressure due to inflammation. Hyperosmolarity plays a key role in diseases of the anterior segment of the eye such as glaucoma, cataracts or dry eyes, and corneal ulceration. However, its role in macular degeneration has been largely overlooked. Hyperosmolarity is responsible for metabolic shifts such as aerobic glycolysis which increases lactate secretion by Muller cells. Increased osmolarity will also cause neoangiogenesis and cell death. Because of its unique energetic demands, the macula is very sensitive to metabolic shifts. As a proof of concept, subretinal injection of drugs increasing hyperosmolarity such as polyethylene glycol causes neoangiogenesis and drusen-like structures in rodents. The link between AMD and hyperosmolarity is reinforced by the fact that treatments aiming to restore mitochondrial activity, such as lipoic acid and/or methylene blue, have been experimentally shown to be effective. We suggest that metabolic shift, inflammation, and hyperosmolarity are hallmarks in the pathogenesis and treatment of AMD.
A Method for Real-Time Lung Nodule Instance Segmentation Using Deep Learning
Authors: Santone Antonella , Mercaldo Francesco , Brunese Luca
Published: September 2024

Lung screening is really crucial in the early detection and management of masses, with particular regard to cancer. Studies have shown that lung cancer screening, can reduce lung cancer mortality by 20–30% in high-risk populations. In recent times, the advent of deep learning, with particular regard to computer vision, demonstrated the ability to effectively detect and locate objects from video streams and also (medical) images. Considering these aspects, in this paper, we propose a method aimed to perform instance segmentation, i.e., by providing a mask for each lung mass instance detected, allowing for the identification of individual masses even if they overlap or are close to each other by classifying the detected masses into (generic) nodules, cancer or adenocarcinoma. In this paper, we considered the you-only-look-once model for lung nodule segmentation. An experimental analysis, performed on a set of real-world lung computed tomography images, demonstrated the effectiveness of the proposed method not only in the detection of lung masses but also in lung mass segmentation, thus providing a helpful way not only for radiologist to conduct automatic lung screening but also for discovering very small masses not easily recognizable to the naked eye and that may deserve attention. As a matter of fact, in the evaluation of a dataset composed of 3654 lung scans, the proposed method obtains an average precision of 0.757 and an average recall of 0.738 in the classification task. Additionally, it reaches an average mask precision of 0.75 and an average mask recall of 0.733. These results indicate that the proposed method is capable of not only classifying masses as nodules, cancer, and adenocarcinoma, but also effectively segmenting the areas, thereby performing instance segmentation.
Applications of Phyllosilicates Mineral Powder as Anti-Wear Lubricating Materials in Lubricating Oil and Grease: A Review
Authors: Jiang Nan , Nan Feng
Published: September 2024

Wear caused by friction is one of the main causes of most mechanical component failures. The application of powders as anti-wear lubricating materials has achieved great advances, which are of great significance in reducing friction and wear. This review focuses on the applications of phyllosilicates mineral powders as anti-wear lubricating materials in lubricating oil. The tribological behaviors of phyllosilicates mineral powders and the combination of phyllosilicates mineral powders with other materials as lubricant additives are provided. Moreover, the fundamental mechanism are systematically reviewed and concluded based on tribology data and surface, and interface analysis. Finally, current unsolved issues and suggestions for future research on phyllosilicates mineral powders as lubricant additives are proposed.
Novel Hybrid Optimization Techniques for Enhanced Generalization and Faster Convergence in Deep Learning Models: The NestYogi Approach to Facial Biometrics
Authors: Altaher Raoof , Koyuncu Hakan
Published: September 2024

In the rapidly evolving field of biometric authentication, deep learning has become a cornerstone technology for face detection and recognition tasks. However, traditional optimizers often struggle with challenges such as overfitting, slow convergence, and limited generalization across diverse datasets. To address these issues, this paper introduces NestYogi, a novel hybrid optimization algorithm that integrates the adaptive learning capabilities of the Yogi optimizer, anticipatory updates of Nesterov momentum, and the generalization power of stochastic weight averaging (SWA). This combination significantly improves both the convergence rate and overall accuracy of deep neural networks, even when trained from scratch. Extensive data augmentation techniques, including noise and blur, were employed to ensure the robustness of the model across diverse conditions. NestYogi was rigorously evaluated on two benchmark datasets Labeled Faces in the Wild (LFW) and YouTube Faces (YTF), demonstrating superior performance with a detection accuracy reaching 98% and a recognition accuracy up to 98.6%, outperforming existing optimization strategies. These results emphasize NestYogi’s potential to overcome critical challenges in face detection and recognition, offering a robust solution for achieving state-of-the-art performance in real-world applications.
Upper Bounds for the Remainder Term in Boole’s Quadrature Rule and Applications to Numerical Analysis
Authors: Javed Muhammad Zakria , Awan Muhammad Uzair , Bin-Mohsin Bandar , Treanţă Savin
Published: September 2024

In the current study, we compute some upper bounds for the remainder term of Boole’s quadrature rule involving convex mappings. First, we build a new identity for first-order differentiable mapping, an auxiliary result to establish our required estimates. We provide several upper bounds by utilizing the identity, convexity property, and bounded property of mappings and some well-known inequalities. Moreover, based on our primary findings, we deliver applications to the means, quadrature rule, special mappings, and non-linear analysis by developing a novel iterative scheme with cubic order of convergence. To the best of our knowledge, the current study is the first attempt to derive upper bounds for Boole’s scheme involving convex mappings.
Fast Analysis and Optimization of a Magnetic Gear Based on Subdomain Modeling
Authors: Nguyen Manh-Dung , Jung Woo-Sung , Hoang Duy-Tinh , Kim Yong-Joo , Shin Kyung-Hun , Choi Jang-Young
Published: September 2024

This study presents a two-dimensional analytical method for fast optimization, taking into consideration the influence of the eddy current in a magnet and iron loss within a coaxial magnetic gear. Subdomain modeling was utilized to obtain vector potentials in the air-gap, magnet, and modulation regions by solving Maxwell’s equations. After that, the magnet, rotor, and modulation losses were predicted and then compared using a finite element method simulation within three topologies with gear ratios ranging from five to six. The authors improved the machine performance, specifically the torque density, by employing a multi-objective function with particle swarm optimization. The flux density obtained using subdomain modeling in just 0.5 s benefits the optimization process, resulting in a torque-density optimal model after around 3 h. A 3/19/16 prototype targeting a low-speed, high-torque, permanent generator application was fabricated to verify the analytical and simulation results.
Robust Negative Binomial Regression via the Kibria–Lukman Strategy: Methodology and Application
Authors: Lukman Adewale F. , Albalawi Olayan , Arashi Mohammad , Allohibi Jeza , Alharbi Abdulmajeed Atiah , Farghali Rasha A.
Published: September 2024

Count regression models, particularly negative binomial regression (NBR), are widely used in various fields, including biometrics, ecology, and insurance. Over-dispersion is likely when dealing with count data, and NBR has gained attention as an effective tool to address this challenge. However, multicollinearity among covariates and the presence of outliers can lead to inflated confidence intervals and inaccurate predictions in the model. This study proposes a comprehensive approach integrating robust and regularization techniques to handle the simultaneous impact of multicollinearity and outliers in the negative binomial regression model (NBRM). We investigate the estimators’ performance through extensive simulation studies and provide analytical comparisons. The simulation results and the theoretical comparisons demonstrate the superiority of the proposed robust hybrid KL estimator (M-NBKLE) with predictive accuracy and stability when multicollinearity and outliers exist. We illustrate the application of our methodology by analyzing a forestry dataset. Our findings complement and reinforce the simulation and theoretical results.
Bacterial Diversity in Sediments from Lianhuan Lake, Northeast China
Authors: Pu Wenmiao , Wang Mingyu , Song Dan , Zhao Wei , Sheng Xuran , Huo Tangbin , Du Xue , Sui Xin
Published: September 2024

Lake microbiota play a crucial role in geochemical cycles, influencing both energy flow and material production. However, the distribution patterns of bacterial communities in lake sediments remain largely unclear. In this study, we used 16S rRNA high-throughput sequencing technology to investigate the bacterial structure and diversity in sediments across different locations (six independent lakes) within Lianhuan Lake and analyzed their relationship with environmental factors. Our findings revealed that both the alpha and beta diversity of sediment bacterial communities varied significantly among the six independent lakes. Furthermore, changes between lakes had a significant impact on the relative abundance of bacterial phyla, such as Pseudomonadota and Chloroflexota. The relative abundance of Pseudomonadota was highest in Habuta Lake and lowest in Xihulu Lake, while Chloroflexota abundance was lowest in Habuta Lake and highest in Tiehala Lake. At the genus level, the relative abundance of Luteitalea was highest in Xihulu Lake compared to the other five lakes, whereas the relative abundances of Clostridium, Thiobacillus, and Ilumatobacter were highest in Habuta Lake. Mantel tests and heatmaps revealed that the relative abundance of Pseudomonadota was significantly negatively correlated with pH, while the abundance of Chloroflexota was significantly positively correlated with total phosphorus and total nitrogen in water, and negatively correlated with electrical conductivity. In conclusion, this study significantly enhances our understanding of bacterial communities in the different lakes within the Lianhuan Lake watershed.
Advances and Prospects on Flotation Enhancement of Difficult-to-Float Coal by Emulsion: A Review
Authors: Wang Xin , Cheng Huaigang , Ding Danjing
Published: September 2024

Coal is expected to continue dominating the global energy landscape for a considerable period in the future. However, the depletion of high-quality coal resources and the increasing proportion of difficult-to-float coals are exacerbating environmental issues and leading to significant waste of carbon resources, making the clean and efficient utilization of such coals imperative. Enhancing the quality of coal through flotation is a prerequisite for the resource utilization of coal. Difficult-to-float coal, characterized by high hydrophilicity, complex pore structures, and fine particle size, poses challenges for efficient flotation using conventional collectors. Emulsions, owing to their exceptional surface and interfacial regulation capabilities and environmental adaptability, have been employed as flotation collectors for various minerals and have garnered significant attention in recent years for their application in the flotation of difficult-to-float coals. In the pursuit of green and cost-effective flotation technologies for such coals, this paper systematically reviews the causes of poor floatability in difficult-to-float coals and their latest research progress by emulsion flotation. It summarizes the impact of emulsion types and preparation methods on their properties and application areas, with a particular focus on the key mechanisms by which emulsion collectors enhance the flotation of difficult-to-float coals, including surface charge regulation, surface hydrophobicity modification, and interfacial tension control. Finally, this paper outlines future research directions on emulsion flotation, which will likely focus on the precise control of emulsion structure and size, the targeted separation of organic components by emulsion collectors under complex conditions, the development of low-cost and highly biocompatible synthetic reagents, and the development of efficient emulsion storage and transportation equipment.
Bioactive Compounds Produced by Endophytic Bacteria and Their Plant Hosts—An Insight into the World of Chosen Herbaceous Ruderal Plants in Central Europe
Authors: Drożdżyński Piotr , Rutkowska Natalia , Rodziewicz Magdalena , Marchut-Mikołajczyk Olga
Published: September 2024

The natural environment has been significantly impacted by human activity, urbanization, and industrialization, leading to changes in living organisms and their adaptation to harsh conditions. Species, including plants, adapt to these changes by creating mechanisms and modifications that allow them to survive in harsh environments. Also, endophytes, microorganisms that live inside plants, can support plant growth and defense mechanisms in these conditions by synthesizing antimicrobial secondary metabolites. What is more, endophytes produce bioactive metabolites, including alkaloids, amines, and peptides, which play a crucial role in the relationship between endophytes and their host organisms. Endophytes themselves benefit from this by creating a stable environment for their survival and development. The aim of this review is to gain insight into endophytic bioactive metabolites from chosen synanthropic ruderal plants. Industrial activities release pollutants like heavy metals, by-products, and waste, which challenge living organisms and require adaptation. Synanthropic plants, where endophytes are abundant, are particularly valuable for their bioactive compounds, which are used in agriculture and medicine. This review presents, among others, endophytes of herbaceous ruderal plants from central Europe—Chelidonium majus L., Urtica dioica L., Plantago lanceolata L., Matricaria chamomilla L., Equisetum arvense L., Oenothera biennis L., Silybum marianum L., and Mentha piperita L.
Modulating the Conductivity of Light-Responsive Ionic Liquid Crystals
Authors: Bendaoud Umama , Bhowmik Pradip K. , Chen Si L. , Han Haesook , Cox Seonghyeok L. , Liebsch Jasmin , Ros M. Blanca , Selvi Velayutham Thamil , Aripin Nurul Fadhilah Kamalul , Martinez-Felipe Alfonso
Published: September 2024

In this work, we describe the phase behaviour and the dielectric and conductivity response of new light-responsive ionic liquid crystals, ILCs, which can be applied as controllable electrolytes. The materials include two different dicationic viologens, the asymmetric 6BP18 and the symmetric EV2ON(Tf)2, containing bistriflimide as the counterions, mixed with 5% and 50% molar, respectively, of one new photoresponsive mesogen called CNAzO14. These mixtures exhibit liquid crystal behaviour, light responsiveness through the E-Z photoisomerisation of the azobenzene groups in CNAzO14, and strong dielectric responses. The 5%-CNAzO14/Ev2ON(Tf)2 mixture displays direct current conductivities in the 10−7 S·cm−1 range, which can be increased by a two-fold factor upon the irradiation of UV light at 365 nm. Our findings set the grounds for designing new smart ionic soft materials with nanostructures that can be tuned and used for energy conversion and storage applications.
Ethylene/Styrene Copolymerization by (Me3SiC5H4)TiCl2(O-2,6-iPr2-4-RC6H2) (R = H, SiEt3)-MAO Catalysts: Effect of SiMe3 Group on Cp for Efficient Styrene Incorporation
Authors: Huang Tiantian , Fujioka Taiga , Shimoyama Daisuke , Nomura Kotohiro
Published: September 2024

The synthesis and structural analysis of (Me3SiC5H4)TiCl2(OAr) [OAr = O-2,6-iPr2-4-RC6H2; R = H, SiEt3] revealed that it exhibits higher catalytic activities than (tBuC5H4)TiCl2(OAr), Cp*TiCl2(OAr), with efficient comonomer incorporation in ethylene/styrene copolymerization in the presence of a methylaluminoxane (MAO) cocatalyst. The catalytic activity in the copolymerization increased upon increasing the charged styrene concentration along with the increase in the styrene content in the copolymers, whereas the activities of other catalysts showed the opposite trend. (Me3SiC5H4)TiCl2(O-2,6-iPr2C6H3) displayed the most suitable catalyst performance in terms of its activity and styrene incorporation, affording amorphous copolymers with styrene contents higher than 50 mol% (up to 63.6 mol%) and with random styrene incorporation confirmed by 13C-NMR spectra.
Different Optical Behaviors Revealed by Electroluminescence and Photoluminescence of InGaN/GaN Coupled Quantum Wells
Authors: Xu Huan , Wang Yachao , Hou Xin , Ou Wei , Yang Tao , Mei Yang , Zhang Baoping
Published: September 2024

The optical properties of wurtzite violet InGaN/GaN coupled quantum well (QW) structures are experimentally studied using photoluminescence (PL) and electroluminescence (EL) spectroscopy. Two emission peaks, referred to as Peak H and Peak L, are observed in both PL and EL spectra, due to the ground state splitting induced by the well coupling. Experimental PL and EL results reveal that coupled QWs show different optical responses due to the different variation in the electric field inside the QW structure. Since the direction of the polarization electric field of the as-grown well/barrier layers is different, the external electric field applied by electrodes can change the energy band alignment between the well and the barrier layers, thus adjusting the coupling between the wells. Our results provide relevant information to improve our understanding of the optical properties of InGaN/GaN QWs and to develop novel optoelectronic devices.
Development and Validation of a Game for Older Adults on Lifestyles and Frailty
Authors: Faria Ana da Conceição Alves , Martins Maria Manuela , Laredo-Aguilera José Alberto , Ventura-Silva João Miguel Almeida , Ribeiro Olga Maria Pimenta Lopes
Published: September 2024

Background: Games are a promising strategy for rehabilitating older adults. The effect of games on promoting healthy lifestyles and preventing frailty remains uncertain. This article aims to describe the process of development and validation of the game “Bem-me-quer para a saúde”® to promote the acquisition of healthy lifestyles and prevent frailty in over 65-year-olds. Methods: This study comprised three distinct phases, spanning from December 2023 to June 2024. The first phase comprised a thorough review of the scientific literature on the frailty and lifestyles of older adults, a second phase of game design, and a third phase of content and semantic validation conducted by specialized nurses and older adults. Results: After revising literature, this study utilized an e-Delphi with a panel of 14 specialist nurses who underwent two rounds of evaluation. The “Bem-me-quer para a saúde”® game includes a puzzle board with 54 pieces and 30 educational cards. In the final phase, we evaluated the game on a cohort of 50 older adults, highlighting its reflective, interactive, and educational aspects. Conclusions: The game presented sufficient evidence of content validity and relevance to clinical practice. We should conduct additional research to evaluate its impact on lifestyle modification and frailty prevention.
Nanotechnology in Advancing Chimeric Antigen Receptor T Cell Therapy for Cancer Treatment
Authors: Kang Xuejia , Mita Nur , Zhou Lang , Wu Siqi , Yue Zongliang , Babu R. Jayachandra , Chen Pengyu
Published: September 2024

Chimeric antigen receptor (CAR) T cell therapy has emerged as a groundbreaking treatment for hematological cancers, yet it faces significant hurdles, particularly regarding its efficacy in solid tumors and concerning associated adverse effects. This review provides a comprehensive analysis of the advancements and ongoing challenges in CAR-T therapy. We highlight the transformative potential of nanotechnology in enhancing CAR-T therapy by improving targeting precision, modulating the immune-suppressive tumor microenvironment, and overcoming physical barriers. Nanotechnology facilitates efficient CAR gene delivery into T cells, boosting transfection efficiency and potentially reducing therapy costs. Moreover, nanotechnology offers innovative solutions to mitigate cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS). Cutting-edge nanotechnology platforms for real-time monitoring of CAR-T cell activity and cytokine release are also discussed. By integrating these advancements, we aim to provide valuable insights and pave the way for the next generation of CAR-T cell therapies to overcome current limitations and enhance therapeutic outcomes.