bluuebunny/crossref_metadata_2025 huggingface dataset:
GAL3ST1 Deficiency Reduces Epithelial–Mesenchymal Transition and Tumorigenic Capacity in a Cholangiocarcinoma Cell Line
Authors: Chen Lin , Elizalde Montserrat , Dubois Ludwig J. , Roeth Anjali A. , Neumann Ulf P. , Olde Damink Steven W. M. , Schaap Frank G. , Alvarez-Sola Gloria
Published: July 2024

Cholangiocarcinoma (CCA), or bile duct cancer, is the second most common liver malignancy, with an increasing incidence in Western countries. The lack of effective treatments associated with the absence of early symptoms highlights the need to search for new therapeutic targets for CCA. Sulfatides (STs), a type of sulfoglycosphingolipids, have been found in the biliary tract, with increased levels in CCA and other types of cancer. STs are involved in protein trafficking and cell adhesion as part of the lipid rafts of the plasma membrane. We aimed to study the role of STs in CCA by the genetic targeting of GAL3ST1, an enzyme involved in ST synthesis. We used the CRISPR-Cas9 system to generate GAL3ST1-deficient TFK1 cells. GAL3ST1 KO cells showed lower proliferation and clonogenic activity and reduced glycolytic activity compared to TFK1 cells. Polarized TFK1 GAL3ST1 KO cells displayed increased transepithelial resistance and reduced permeability compared to TFK1 wt cells. The loss of GAL3ST1 showed a negative effect on growth in 30 out of 34 biliary tract cancer cell lines from the DepMap database. GAL3ST1 deficiency partially restored epithelial identity and barrier function and reduced proliferative activity in CCA cells. Sulfatide synthesis may provide a novel therapeutic target for CCA.
Stable Production of a Recombinant Single-Chain Eel Follicle-Stimulating Hormone Analog in CHO DG44 Cells
Authors: Byambaragchaa Munkhzaya , Park Sei Hyen , Kim Sang-Gwon , Shin Min Gyu , Kim Shin-Kwon , Park Myung-Hum , Kang Myung-Hwa , Min Kwan-Sik
Published: July 2024

This study aimed to produce single-chain recombinant Anguillid eel follicle-stimulating hormone (rec-eel FSH) analogs with high activity in Cricetulus griseus ovary DG44 (CHO DG44) cells. We recently reported that an O-linked glycosylated carboxyl-terminal peptide (CTP) of the equine chorionic gonadotropin (eCG) β-subunit contributes to high activity and time-dependent secretion in mammalian cells. We constructed a mutant (FSH-M), in which a linker including the eCG β-subunit CTP region (amino acids 115–149) was inserted between the β-subunit and α-subunit of wild-type single-chain eel FSH (FSH-wt). Plasmids containing eel FSH-wt and eel FSH-M were transfected into CHO DG44 cells, and single cells expressing each protein were isolated from 10 and 7 clones. Secretion increased gradually during the cultivation period and peaked at 4000–5000 ng/mL on day 9. The molecular weight of eel FSH-wt was 34–40 kDa, whereas that of eel FSH-M increased substantially, with two bands at 39–46 kDa. Treatment with PNGase F to remove the N glycosylation sites decreased the molecular weight remarkably to approximately 8 kDa. The EC50 value and maximal responsiveness of eel FSH-M were approximately 1.23- and 1.06-fold higher than those of eel FSH-wt, indicating that the mutant showed slightly higher biological activity. Phosphorylated extracellular-regulated kinase (pERK1/2) activation exhibited a sharp peak at 5 min, followed by a rapid decline. These findings indicate that the new rec-eel FSH molecule with the eCG β-subunit CTP linker shows potent activity and could be produced in massive quantities using the stable CHO DG44 cell system.
Vitamin C Supplementation in the Treatment of Autoimmune and Onco-Hematological Diseases: From Prophylaxis to Adjuvant Therapy
Authors: Isola Stefania , Gammeri Luca , Furci Fabiana , Gangemi Sebastiano , Pioggia Giovanni , Allegra Alessandro
Published: July 2024

Vitamin C is a water-soluble vitamin introduced through the diet with anti-inflammatory, immunoregulatory, and antioxidant activities. Today, this vitamin is integrated into the treatment of many inflammatory pathologies. However, there is increasing evidence of possible use in treating autoimmune and neoplastic diseases. We reviewed the literature to delve deeper into the rationale for using vitamin C in treating this type of pathology. There is much evidence in the literature regarding the beneficial effects of vitamin C supplementation for treating autoimmune diseases such as Systemic Lupus Erythematosus (SLE) and Rheumatoid Arthritis (RA) and neoplasms, particularly hematological neoplastic diseases. Vitamin C integration regulates the cytokines microenvironment, modulates immune response to autoantigens and cancer cells, and regulates oxidative stress. Moreover, integration therapy has an enhanced effect on chemotherapies, ionizing radiation, and target therapy used in treating hematological neoplasm. In the future, integrative therapy will have an increasingly important role in preventing pathologies and as an adjuvant to standard treatments.
Long-Term Proton Pump Inhibitor–Acid Suppressive Treatment Can Cause Vitamin B12 Deficiency in Zollinger–Ellison Syndrome (ZES) Patients
Authors: Ito Tetsuhide , Ramos-Alvarez Irene , Jensen Robert T.
Published: July 2024

Whether the long-term treatment of patients with proton pump inhibitors (PPIs) with different diseases [GERD, Zollinger–Ellison syndrome (ZES), etc.] can result in vitamin B12 (VB12) deficiency is controversial. In this study, in 175 patients undergoing long-term ZES treatment with anti-acid therapies, drug-induced control acid secretory rates were correlated with the presence/absence of VB12 deficiency, determined by assessing serum VB12 levels, measurements of VB12 body stores (blood methylmalonic acid (MMA) and total homocysteine[tHYC]), and other features of ZES. After a mean of 10.2 yrs. of any acid treatment (5.6 yrs. with PPIs), 21% had VB12 deficiency with significantly lower serum and body VB12 levels (p < 0.0001). The presence of VB12 deficiency did not correlate with any feature of ZES but was associated with a 12-fold lower acid control rate, a 2-fold higher acid control pH (6.4 vs. 3.7), and acid control secretory rates below those required for the activation of pepsin (pH > 3.5). Over a 5-yr period, the patients with VB12 deficiency had a higher rate of achlorhydria (73% vs. 24%) and a lower rate of normal acid secretion (0% vs. 49%). In conclusion, in ZES patients, chronic long-term PPI treatment results in marked acid hyposecretion, resulting in decreased serum VB12 levels and decreased VB12-body stores, which can result in VB12 deficiency.
From Atherosclerotic Plaque to Myocardial Infarction—The Leading Cause of Coronary Artery Occlusion
Authors: Młynarska Ewelina , Czarnik Witold , Fularski Piotr , Hajdys Joanna , Majchrowicz Gabriela , Stabrawa Magdalena , Rysz Jacek , Franczyk Beata
Published: July 2024

Cardiovascular disease (CVD) constitutes the most common cause of death worldwide. In Europe alone, approximately 4 million people die annually due to CVD. The leading component of CVD leading to mortality is myocardial infarction (MI). MI is classified into several types. Type 1 is associated with atherosclerosis, type 2 results from inadequate oxygen supply to cardiomyocytes, type 3 is defined as sudden cardiac death, while types 4 and 5 are associated with procedures such as percutaneous coronary intervention and coronary artery bypass grafting, respectively. Of particular note is type 1, which is also the most frequently occurring form of MI. Factors predisposing to its occurrence include, among others, high levels of low-density lipoprotein cholesterol (LDL-C) in the blood, cigarette smoking, chronic kidney disease (CKD), diabetes mellitus (DM), hypertension, and familial hypercholesterolaemia (FH). The primary objective of this review is to elucidate the issues with regard to type 1 MI. Our paper delves into, amidst other aspects, its pathogenesis, risk assessment, diagnosis, pharmacotherapy, and interventional treatment options in both acute and long-term conditions.
Heat Load Development and Heat Map Sensitivity Analysis for Civil Aero-Engines
Authors: Ebrahimi Alireza , Jafari Soheil , Nikolaidis Theoklis
Published: July 2024

The design complexity of the new generation of civil aero-engines results in higher demands on engines’ components, higher component temperatures, higher heat generation, and, finally, critical thermal management issues. This paper will propose a methodological approach to creating physics-based models for heat loads developed by sources, as well as a systematic sensitivity analysis to identify the effects of design parameters on the thermal behavior of civil aero-engines. The ranges and levels of heat loads generated by heat sources (e.g., accessory gearbox, bearing, pumps, etc.) and the heat absorption capacity of heat sinks (e.g., engine fuel, oil, and air) are discussed systematically. The practical research challenges for thermal management system design and development for the new and next generation of turbofan engines will then be addressed through a sensitivity analysis of the heat load values as well as the heat sink flow rates. The potential solutions for thermal performance enhancements of propulsion systems will be proposed and discussed accordingly.
The Development of a Prototype Solution for Collecting Information on Cycling and Hiking Trail Users
Authors: Miguel Joaquim , Mendonça Pedro , Quelhas Agnelo , Caldeira João M. L. P. , Soares Vasco N. G. J.
Published: July 2024

Hiking and cycling have gained popularity as ways of promoting well-being and physical activity. This has not gone unnoticed by Portuguese authorities, who have invested in infrastructure to support these activities and to boost sustainable and nature-based tourism. However, the lack of reliable data on the use of these infrastructures prevents us from recording attendance rates and the most frequent types of users. This information is important for the authorities responsible for managing, maintaining, promoting and using these infrastructures. In this sense, this study builds on a previous study by the same authors which identified computer vision as a suitable technology to identify and count different types of users of cycling and hiking routes. The performance tests carried out led to the conclusion that the YOLOv3-Tiny convolutional neural network has great potential for solving this problem. Based on this result, this paper describes the proposal and implementation of a prototype demonstrator. It is based on a Raspberry Pi 4 platform with YOLOv3-Tiny, which is responsible for detecting and classifying user types. An application available on users’ smartphones implements the concept of opportunistic networks, allowing information to be collected over time, in scenarios where there is no end-to-end connectivity. This aggregated information can then be consulted on an online platform. The prototype was subjected to validation and functional tests and proved to be a viable low-cost solution.
Age-Stage, Two-Sex Life Table of Atractomorpha lata (Orthoptera: Pyrgomorphidae) at Different Temperatures
Authors: Li Wenbo , Bashir Nawaz Haider , Naeem Muhammad , Tian Ruilin , Tian Xinyue , Chen Huanhuan
Published: July 2024

Atractomorpha lata Motschoulsky (Orthoptera: Pyrgomorphidae) has recently emerged as an important agricultural pest in China. Understanding the impact of temperature on its developmental period is crucial for predicting its population dynamics. This study systematically observed the biological characteristics of A. lata at five temperatures (16, 20, 24, 28, and 32 °C) using the age-stage, two-sex life table method. The effects of temperature on the developmental period, survival rate, and fecundity of A. lata were studied using fresh bean leaves as host. The results demonstrated that as temperature increased from 16 °C to 32 °C, the developmental period, preadult time, adult longevity, adult preoviposition period (APOP), and total preoviposition period (TPOP) significantly decreased. The developmental threshold temperatures for various stages were calculated, ranging from 10.47 °C to 13.01 °C, using the linear optimal method. As temperature increased, both the intrinsic rate of increase (r) and the finite rate of increase (λ) also increased, while the mean generation time (T) decreased. The optimal values of the net reproductive rate (R0 = 54.26 offspring), gross reproductive rate (GRR = 185.53 ± 16.94 offspring), and fecundity (169.56 ± 9.93 eggs) were observed at 24 °C. Similarly, the population trend index (I) for A. lata peaked at 24 °C (61.64). Our findings indicate that A. lata exhibits its highest population growth rate at 24 °C, providing a scientific basis for predicting its population dynamics in the field.
Road Anomaly Detection with Unknown Scenes Using DifferNet-Based Automatic Labeling Segmentation
Authors: Nguyen Phuc Thanh-Thien , Nguyen Toan-Khoa , Nguyen Dai-Dong , Su Shun-Feng , Kuo Chung-Hsien
Published: July 2024

Obstacle avoidance is essential for the effective operation of autonomous mobile robots, enabling them to detect and navigate around obstacles in their environment. While deep learning provides significant benefits for autonomous navigation, it typically requires large, accurately labeled datasets, making the data’s preparation and processing time-consuming and labor-intensive. To address this challenge, this study introduces a transfer learning (TL)-based automatic labeling segmentation (ALS) framework. This framework utilizes a pretrained attention-based network, DifferNet, to efficiently perform semantic segmentation tasks on new, unlabeled datasets. DifferNet leverages prior knowledge from the Cityscapes dataset to identify high-entropy areas as road obstacles by analyzing differences between the input and resynthesized images. The resulting road anomaly map was refined using depth information to produce a robust drivable area and map of road anomalies. Several off-the-shelf RGB-D semantic segmentation neural networks were trained using pseudo-labels generated by the ALS framework, with validation conducted on the GMRPD dataset. Experimental results demonstrated that the proposed ALS framework achieved mean precision, mean recall, and mean intersection over union (IoU) rates of 80.31%, 84.42%, and 71.99%, respectively. The ALS framework, through the use of transfer learning and the DifferNet network, offers an efficient solution for semantic segmentation of new, unlabeled datasets, underscoring its potential for improving obstacle avoidance in autonomous mobile robots.
Adaptive Variable Design Algorithm for Improving Topology Optimization in Additive Manufacturing Guided Design
Authors: Vadillo Morillas Abraham , Meneses Alonso Jesús , Bustos Caballero Alejandro , Castejón Sisamón Cristina , Ceruti Alessandro
Published: July 2024

CAD-CAE software companies have introduced numerous tools aimed at facilitating topology optimization through Finite Element Simulation, thereby enhancing accessibility for designers via user-friendly interfaces. However, the imposition of intricate constraint conditions or additional restrictions during calculations may introduce instability into the resultant outcomes. In this paper, an algorithm for updating the design variables called Adaptive Variable Design is proposed to keep the final design space volume of the optimized part consistently under the target value while giving the main algorithm multiple chances to update the optimization parameters and search for a valid design. This algorithm aims to produce results that are more conducive to manufacturability and potentially more straightforward in interpretation. A comparison between several commercial software packages and the proposed algorithm, implemented in MATLAB R2023a, is carried out to prove the robustness of the latter. By simulating identical parts under similar conditions, we seek to generate comparable results and underscore the advantages stemming from the adoption and comprehension of the proposed topology optimization methodology. Our findings reveal that the integrated enhancements within MATLAB pertaining to the topology optimization process yield favourable outcomes with respect to discretization and the manufacturability of the resultant geometries. Furthermore, we assert that the methodology evaluated within MATLAB holds promise for potential integration into commercial packages, thereby enhancing the efficiency of topology optimization processes.
Association between Systolic Blood Pressure Variability and Incident Aortic Stenosis
Authors: Kim Hyun-Jung , Kim Ji-Eon , Jung Jae-Seung , Kim Hee-Jung , Son Ho-Sung
Published: July 2024

Background: This study investigated the potential link between blood pressure variability (BPV) and the incidence of aortic stenosis (AS) using Korean National Health Insurance Service data from 2002 to 2019. Methods: We collected annual systolic blood pressure variability (SBPV) measurements consisting of three consecutive blood pressure readings each year over three years. The obtained SBPV data was divided into five quantiles, with the highest quintile representing a high fluctuation of blood pressure. Results: Analyzing 9,341,629 individuals with a mean age of 40.7 years, the study found 3981 new AS diagnoses during an average 8.66-year follow-up. Independent predictors for AS included higher blood pressure levels and elevated systolic blood pressure variability (SBPV). The hazard ratios (HR) for different SBPV quintiles compared to the reference (1st quintile) were as follows: 2nd quintile HR 1.09 (p = 0.18), 3rd quintile HR 1.13 (p = 0.04), 4th quintile HR 1.13 (p = 0.04), and 5th quintile HR 1.39 (p < 0.001). Conclusion: Our findings suggest that both hypertension and high fluctuations in SBP during consecutive visits are associated with an increased risk of incident AS. These results emphasize the importance of blood pressure management and stability in the prevention of AS.
The Asian Fabry Cardiomyopathy High-Risk Screening Study 2 (ASIAN-FAME-2): Prevalence of Fabry Disease in Patients with Left Ventricular Hypertrophy
Authors: Leung Sophia Po-Yee , Dougherty Scott , Zhang Xiao-Yu , Kam Kevin K. H. , Chi Wai-Kin , Chan Joseph Y. S. , Fung Erik , Wong Jeffrey K. T. , Choi Paul C. L. , Chan David K. H. , Sheng Bun , Lee Alex Pui-Wai
Published: July 2024

Background: Fabry disease (FD) is a rare X-linked lysosomal storage disorder that commonly manifests cardiovascular complications. We aimed to assess the prevalence of FD in a Chinese population with left ventricular hypertrophy (LVH) whilst implementing a gender-specific screening approach. Methods: Patients with LVH, defined as a maximum thickness of the left ventricular septal/posterior wall ≥ 13 mm, were considered eligible. All patients with hypertrophic cardiomyopathy (HCM) were excluded. Plasma α-galactosidase (α-GLA) enzyme activity was assessed using a dried blood spot test. Males with low enzyme activity underwent genetic testing to confirm a diagnosis of FD whereas females were screened for both α-GLA and globotriaosylsphingosine concentration and underwent genetic analysis of the GLA gene only if testing positive for ≥1 parameter. Results: 426 unrelated patients (age = 64.6 ± 13.0 years; female: male = 113:313) were evaluated. FD was diagnosed in 3 unrelated patients (age = 69.0 ± 3.5 years, female: male = 1:2) and 1 related female subject (age = 43 years). Genetic analyses confirmed the late-onset cardiac variant GLA c.640-801G>A (n = 3) and the missense variant c.869T>C associated with classic FD (n = 1). Cardiac complications were the only significant findings associated with the late-onset c.640-801G>A mutation, manifesting as mild or severe concentric LVH. In contrast, the classic c.869T>C mutation FD exhibited multisystemic manifestations in addition to severe concentric LVH. Conclusions: The prevalence of FD is lower in Chinese patients with LVH when HCM is excluded. The pathological variant c.640-801G>A remains the most common cause of late-onset FD, while the detection of FD in females can be improved by utilizing a gender-specific screening method.
Urinary Tract Infections in Relation to Bladder Emptying in Patients with Spinal Cord Injury
Authors: Milicevic Sasa , Sekulic Aleksandra , Nikolic Dejan , Tomasevic-Todorovic Snezana , Lazarevic Konstansa , Pelemis Svetislav , Petrovic Masa , Mitrovic Sindi Z.
Published: July 2024

Background/Objectives: Spinal cord injuries are debilitating conditions with significant impacts on physical function and patient quality of life. The high incidence of urinary tract infections in these patients can be attributed to neurogenic bladder—a major complication of spinal cord injuries. The aim of this study is to investigate the incidence of urinary tract infections in patients with spinal cord injuries and their relation to the method of bladder emptying. Methods: A retrospective analysis on 560 patients admitted for rehabilitation at the Clinic for Rehabilitation “Dr Miroslav Zotovic” from December 2009 to January 2023 was conducted. Patients over 18 years old who were inpatients for longer than 30 days without any symptoms of urinary tract infection on admission were included. Patient demographics, injury details, and bladder emptying methods were recorded. Results: In our study, 402 (71.8%) participants developed a urinary tract infection during their rehabilitation. Urinary tract infections were significantly more common in patients with traumatic spinal cord injuries, lower ASIA scores, and thoracic-level injuries. The highest incidence of urinary tract infections was observed in intermittent self-catheterization patients (62.7%), with Escherichia coli and Proteus mirabilis being the most frequently isolated pathogens. Conclusions: The method of bladder emptying significantly impacted the incidence of urinary tract infection in patients with spinal cord injuries. Despite guidelines favoring intermittent catheterization, this study found it to be associated with the highest infection rates. These findings suggest a need for personalized bladder management strategies to reduce the risk of urinary tract infections and improve outcomes for spinal cord injury patients.
Wind and Wave-Induced Vibration Reduction Control for Floating Offshore Wind Turbine Using Delayed Signals
Authors: Yan Shouxiang , Wang Yilong , Pang Fengbin , Zhang Wei , Zhang Bao-Lin
Published: July 2024

Active vibration control is a critical issue of the wind turbine in the field of marine energy. First, based on a three-degree-of-freedom wind turbine, a state space model subject to wind and wave loads is obtained. Then, a delayed state feedback control scheme is illustrated to reduce the vibration of platform pitch angle and tower top foreaft displacement, where the control channel includes time-delay state signals. The designed controller’s existence conditions are investigated. The simulation results show that the delayed feedback H∞ controller can significantly suppress wind- and wave-induced vibration of the wind turbine. Furthermore, it presents potential advantages over the delay-free feedback H∞ controller and the classic linear quadratic regulator in two aspects: vibration control performance and control cost.
Advances in Marine Mechanical and Structural Engineering
Authors: Liu Kun , Liu Bin , Li Chenfeng
Published: July 2024

In the design of modern ship and offshore structures, one of the key issues is the accurate prediction of strength with regard to various new materials and structures used in the structural design stage and under extreme sea environment and accidental states [...]
Autonomous Underwater Vehicle Trajectory Prediction with the Nonlinear Kepler Optimization Algorithm–Bidirectional Long Short-Term Memory–Time-Variable Attention Model
Authors: Yao Jieen , Yang Junzheng , Zhang Chenghao , Zhang Jing , Zhang Tianchi
Published: July 2024

Autonomous underwater vehicles (AUVs) have been widely used in ocean missions. When they fail in the ocean, it is important to predict their trajectory. Existing methods rely heavily on historical trajectory data while overlooking the influence of the ocean environment on an AUV’s trajectory. At the same time, these methods fail to use the dependency between variables in the trajectory. To address these challenges, this paper proposes an AUV trajectory prediction model known as the nonlinear Kepler optimization algorithm–bidirectional long short-term memory–time-variable attention (NKOA-BiLSTM-TVA) model. This paper introduces opposition-based learning during the initialization process of the KOA and improves the algorithm by incorporating a nonlinear factor into the planet position update process. We designed an attention mechanism layer that spans both time and variable dimensions, called TVA. TVA can extract features from both the time and variable dimensions of the trajectory and use the dependency between trajectory variables to predict the trajectory. First, the model uses a convolutional neural network (CNN) to extract spatial features from the trajectory. Next, it combines a BiLSTM network with TVA to predict the AUV’s trajectory. Finally, the improved NKOA is used to optimize the model’s hyperparameters. Experimental results show that the NKOA-BiLSTM-TVA model has an excellent parameter optimization effect and higher prediction accuracy in AUV trajectory prediction tasks. It also achieves excellent results in ship trajectory prediction.
Spontaneous Coronary Artery Dissection in Patients with Autosomal Dominant Polycystic Kidney Disease: A Systematic Review of the Literature
Authors: Milutinovic Stefan , Bell Abraham , Jancic Predrag , Stanojevic Dragana , Borghol Abdul Hamid , Mina Jonathan , Chebib Fouad T. , Khambati Ibrahim , Escarcega Ricardo O. , Wood Malissa J.
Published: July 2024

Spontaneous coronary artery dissection (SCAD) is a spontaneous intimal tear of the coronary artery wall. A factor rarely associated with SCAD is autosomal dominant polycystic kidney disease (ADPKD). Using the PRISMA guidelines, we identified 10 unique cases of SCAD in ADPKD patients reported between 1998 and 2021. Ages ranged from 36 to 59 years, with an average of 44.6 years. The majority of patients were female (80%). Each case was diagnosed with a cardiovascular event: ST-elevation myocardial infarction (STEMI) in 40%, non-ST elevation myocardial infarction (NSTEMI) in 50%, and stable angina in 10%. Conservative management was used in 60% of cases. There is a significant gap in our understanding of the relationship between SCAD and ADPKD. Polycystin complex can lead to structural abnormalities in blood vessels, resulting in vascular leaks and vessel rupture. This suggests that ADPKD patients may have an elevated risk of arteriopathies, including coronary artery dissection.
Synthetic Genitourinary Image Synthesis via Generative Adversarial Networks: Enhancing Artificial Intelligence Diagnostic Precision
Authors: Van Booven Derek J. , Chen Cheng-Bang , Malpani Sheetal , Mirzabeigi Yasamin , Mohammadi Maral , Wang Yujie , Kryvenko Oleksander N. , Punnen Sanoj , Arora Himanshu
Published: July 2024

Introduction: In the realm of computational pathology, the scarcity and restricted diversity of genitourinary (GU) tissue datasets pose significant challenges for training robust diagnostic models. This study explores the potential of Generative Adversarial Networks (GANs) to mitigate these limitations by generating high-quality synthetic images of rare or underrepresented GU tissues. We hypothesized that augmenting the training data of computational pathology models with these GAN-generated images, validated through pathologist evaluation and quantitative similarity measures, would significantly enhance model performance in tasks such as tissue classification, segmentation, and disease detection. Methods: To test this hypothesis, we employed a GAN model to produce synthetic images of eight different GU tissues. The quality of these images was rigorously assessed using a Relative Inception Score (RIS) of 1.27 ± 0.15 and a Fréchet Inception Distance (FID) that stabilized at 120, metrics that reflect the visual and statistical fidelity of the generated images to real histopathological images. Additionally, the synthetic images received an 80% approval rating from board-certified pathologists, further validating their realism and diagnostic utility. We used an alternative Spatial Heterogeneous Recurrence Quantification Analysis (SHRQA) to assess the quality of prostate tissue. This allowed us to make a comparison between original and synthetic data in the context of features, which were further validated by the pathologist’s evaluation. Future work will focus on implementing a deep learning model to evaluate the performance of the augmented datasets in tasks such as tissue classification, segmentation, and disease detection. This will provide a more comprehensive understanding of the utility of GAN-generated synthetic images in enhancing computational pathology workflows. Results: This study not only confirms the feasibility of using GANs for data augmentation in medical image analysis but also highlights the critical role of synthetic data in addressing the challenges of dataset scarcity and imbalance. Conclusions: Future work will focus on refining the generative models to produce even more diverse and complex tissue representations, potentially transforming the landscape of medical diagnostics with AI-driven solutions.
Special Issue “New Updates in Oral and Maxillofacial Surgery”
Authors: Maglitto Fabio , Copelli Chiara , Manfuso Alfonso , Cocis Stefan , Salzano Giovanni
Published: July 2024

In the ever-evolving landscape of medical science, few fields have witnessed as profound a transformation as oral and maxillofacial surgery [...]
Prevalence of Progressive Fibrosing Interstitial Lung Disease in Patients with Primary Sjogren Syndrome
Authors: Manfredi Andreina , Sambataro Gianluca , Rai Alessandra , Cerri Stefania , Sambataro Domenico , Vacchi Caterina , Cassone Giulia , Vancheri Carlo , Sebastiani Marco
Published: July 2024

Background: Interstitial lung disease (ILD) represents a frequent cause of morbidity and mortality in primary Sjogren syndrome (pSS). However, the prevalence and behavior of pSS-ILD remains incomplete, largely based on retrospective heterogeneous studies. Aim of the study: To investigate the prevalence of progressive pulmonary fibrosis (PPF) in a multicentric cohort of patients with pSS-ILD. Additionally, this study explored possible correlations between PPF and clinical, demographic, and serological features of pSS. Methods: All consecutive patients with pSS-ILD were enrolled in a 6-month period. Clinical, demographic, and serological features of pSS, other than functional and radiological lung features, were collected. Clinical behaviors of ILD other than PPF were also investigated. Results: Seventy-two patients were enrolled. A fibrosing ILD pattern was observed in 65.3% of patients with pSS-ILD; among them, 55.3% showed a PPF. The radiologic pattern (NSIP, UIP, or others) was not associated with PPF; in particular, patients with PFF had UIP in 42.3% of cases and NSIP in 57.7%, without a significant difference with respect to the non-PPF group (p = 0.29). Shorter pSS disease duration, higher age at pSS diagnosis, and lower frequency of antinuclear antibodies were correlated with the PPF subgroup. However, multivariate analysis did not confirm these associations. Discussion: This study provides valuable insights into the prevalence and characteristics of PPF in pSS-ILD. In particular, UIP and NSIP showed a similar evolution towards PPF in patients with pSS; for NSIP, this behavior was more frequent than for other rheumatic diseases. Our results emphasize the importance of early recognition of PPF for timely intervention and careful follow-up. Conclusions: This study provides valuable insights into the prevalence and characteristics of PPF in pSS-ILD. In particular, UIP and NSIP showed a similar evolution towards PPF in patients with pSS; for NSIP, this behavior was more frequent than for other rheumatic diseases. Our results emphasize the importance of early recognition of PPF for timely intervention and careful follow-up.
Optimization of Variational Mode Decomposition-Convolutional Neural Network-Bidirectional Long Short Term Memory Rolling Bearing Fault Diagnosis Model Based on Improved Dung Beetle Optimizer Algorithm
Authors: Sun Weiqing , Wang Yue , You Xingyi , Zhang Di , Zhang Jingyi , Zhao Xiaohu
Published: July 2024

(1) Background: Rolling bearings are important components in mechanical equipment, but they are also components with a high failure rate. Once a malfunction occurs, it will cause mechanical equipment to malfunction and may even affect personnel safety. Therefore, studying the fault diagnosis methods for rolling bearings is of great significance and is also a current research hotspot and frontier. However, the vibration signals of rolling bearings usually exhibit nonlinear and non-stationary characteristics, and are easily affected by industrial environmental noise, making it difficult to accurately diagnose bearing faults. (2) Methods: Therefore, this article proposes a rolling bearing fault diagnosis model based on an improved dung beetle optimizer (DBO) algorithm-optimized variational mode decomposition-convolutional neural network-bidirectional long short-term memory (VMD-CNN-BiLSTM). Firstly, an improved DBO algorithm named CSADBO is proposed by integrating multiple strategies such as chaotic mapping and cooperative search. Secondly, the optimal parameter combination of VMD was adaptively determined through the CSADBO algorithm, and the optimized VMD algorithm was used to perform modal decomposition on the bearing vibration signal. Then, CNN-BiLSTM was used as the model for fault classification, and hyperparameters of the model were optimized using the CSADBO algorithm. (3) Results: Finally, multiple experiments were conducted on the bearing dataset of Case Western Reserve University, and the proposed method achieved an average diagnostic accuracy of 99.6%. (4) Conclusions: Experimental comparisons were made with other models to verify the effectiveness of the proposed model. The experimental results show that the proposed model based on an improved DBO algorithm optimized VMD-CNN-BiLSTM can effectively be used for rolling bearing fault diagnosis, with high diagnostic accuracy, and can provide a theoretical reference for other related fault diagnosis problems.
Enhancing Flexural Behavior of Reinforced Concrete Beams Strengthened with Basalt Fiber-Reinforced Polymer Sheets Using Carbon Nanotube-Modified Epoxy
Authors: Shi Changchun , Jin Shengji , Wang Chengjie , Yang Yuhao
Published: July 2024

The external bonding (EB) of fiber-reinforced polymer (FRP) is a usual flexural reinforcement method. When using the technique, premature debonding failure still remains a factor of concern. The effect of incorporating multi-wall carbon nanotubes (MWCNTs) in epoxy resin on the flexural behavior of reinforced concrete (RC) beams strengthened with basalt fiber-reinforced polymer (BFRP) sheets was investigated through four-point bending beam tests. Experimental results indicated that the flexural behavior was significantly improved by the MWCNT-modified epoxy. The BFRP sheets bonded by the MWCNT-modified epoxy more effectively mitigated the debonding failure of BFRP sheets and constrained crack development as well as enhanced the ductility and flexural stiffness of strengthened beams. When the beam was reinforced with two-layer BFRP sheets, the yielding load, ultimate load, ultimate deflection, post-yielded flexural stiffness, energy absorption capacity and deflection ductility of beams strengthened using MWCNT-modified epoxy increased by 7.4%, 8.3%, 18.2%, 22.6%, 29.1% and 14.3%, respectively, in comparison to the beam strengthened using pure epoxy. It could be seen in scanning electron microscopy (SEM) images that the MWCNTs could penetrate into concrete and their pull-out and crack bridging consumed more energy, which remarkably enhanced the flexural behavior of the strengthened beams. Finally, an analytical model was proposed for calculating characteristic loads and characteristic deflections of RC beams strengthened with FRP sheets, which indicated a reasonably good correlation with the experimental results.
Structural, Morphological and Ferroelectric Properties of Sr-Cd Co-Doped Nickel Ferrite for Energy Storage Devices
Authors: Alburaih Huda A. , ul Haq Muhammad Ahsan , Jabbar Abdul , ur Rehman Atiq , Laref Amel , Saad Hasb Elkhalig Mohamed Musa , Noor Naveed Ahmad
Published: July 2024

Ferroelectric materials, renowned for their capacity to demonstrate spontaneous electric polarization reversible through an external electric field, are essential in numerous technological applications owing to their distinctive characteristics. For this, a series of spinel Sr-Cd co-doped nickel ferrite nanomaterials Cd0.5−xSrxNi0.5Fe2O4 (x = 0.0, 0.1, 0.2 and 0.3) were prepared through the standard sol-gel auto combustion method The XRD patterns showed that the prepared samples have a cubic spinel structure. The crystallite sizes of the samples vary from 29 to 40 nm. The morphology of prepared samples showed uniformly distributed spheres. Magnetic properties showed the soft magnetic nature of the prepared ferrites. The ferroelectric study revealed that Sr-Cd substituted ferrites exhibited the elliptical nature of ferroelectric loops at normal room temperature. The maximum polarization has been achieved at x = 0.3. The understanding of current and voltage (I–V) showed a slowly decreasing tendency of leakage current on both sides symmetrically against the increasing Sr content. The conductivity of the prepared spinel increases as a function of higher Sr doping. The real part of dielectric constant increases with increasing frequency. The materials show large elliptical loops indicating high asymmetric ferroelectric energy storage capability.
Time-Delay Dynamic Model and Cost-Effectiveness Analysis of Major Emergent Infectious Diseases with Transportation-Related Infection and Entry-Exit Screening
Authors: Xie Yi , Zhang Ziheng , Wu Yan , Li Shuang , Pang Liuyong , Li Yong
Published: July 2024

We analyze a time-delayed SIQR model that considers transportation-related infection and entry–exit screening. This model aims to determine the measures for preventing and controlling major emergent infectious diseases and the associated costs. We calculate the basic reproduction number (R0) and prove that the disease-free equilibrium is locally and globally asymptotically stable. We collect COVID-19 infection data from two regions in the United States in 2020 for data fitting, obtain a set of optimal parameter values, and find that transportation-related infection rates increase the basic reproduction number, enhancing the impact on disease spread. Entry–exit screening effectively suppresses the spread of disease by reducing the basic reproduction number. Furthermore, we investigate the influence of the incubation period on disease and find that a shorter incubation period results in a shorter duration but a larger scale of infection and that the peaks are reduced. We conduct a sensitivity analysis of the R0 and propose three measures to prevent the spread of new infectious diseases based on the most sensitive parameters: wearing masks, implementing urban closures, and administering medication to sick but not yet hospitalized patients promptly. In the case of COVID-19, optimal control effectively controls the development and deterioration of the disease. Finally, several control measures are compared through cost-effectiveness analysis, and the results show that wearing masks is the most cost-effective measure.
Inverse Geometric Reconstruction Based on MW-NURBS Curves
Authors: Ali Musrrat , Saini Deepika , Kumar Sanoj
Published: July 2024

Currently, rational curves such as the Non-Uniform Rational B-Spline (NURBS) play a significant role in both shape representation and shape reconstruction. NURBS weights are often real in nature and are referred to as challenging to assign, with the exception of conics. ‘Matrix Weighted Rational Curves’ are the expanded form of rational curves that result from replacing these real weights with matrices, or matrix weights. The only difference between these curves and conventional curves is the geometric definition of the matrix weights. In this paper, MW-NURBS curves are used to reconstruct space curves from their stereo perspectives. In particular, MW-NURBS fitting is carried out in stereo views, and the weight matrices for the MW-NURBS curves are produced using the normal vectors provided at the control points. Instead of needing to solve a complicated system, the MW-NURBS model can reconstruct curves by choosing control points and control normals from the input data. The efficacy of the proposed strategy is verified by using many examples based on both synthetic and real images. The various error types are compared to those of conventional methods like point-based and NURBS-based approaches. The results demonstrate that the errors acquired from the proposed approach are much fewer than those obtained from the point-based method and the NURBS-based method.
An Error Segment Bit-Flip Algorithm for Successive Cancellation List Decoding of Polar Codes
Authors: Zhang Jing , Qiu Hongbing , Zhan Ling , Chen Lili
Published: July 2024

Polar codes have garnered significant attention since they were proposed due to their capacity-achieving properties and their low-complexity decoding process, and they were selected as the coding scheme for the control channel in 5G mobile communication technology. A successive cancellation list (SCL) decoder, aided by a cyclic redundancy check (CRC), performs the competitive error correcting performance for polar codes compared to other sophisticated codes. The SCL-Flip decoding algorithm is proposed to enhance the error correction performance of the SCL. However, the SCL-Flip is hampered by a high decoding complexity due to the necessary selection and sorting process of path metrics (PMs). Additionally, it requires a large number of iterations to achieve a good error correction performance. In this paper, we propose the error segment bit-flip (ES-SCL-Flip) decoding algorithm, a simplified bit-flip approach for the SCL decoder based on analyzing the distributions of the first error bit. Firstly, we construct an index set with a high probability of the first erroneous bit. Second, a bit-flip criterion is introduced to prevent the costly operation of the PM selection and sorting without compromising the error correction performance. Finally, a search strategy is employed that utilizes segmented error indication to target and rectify the initial error segment sequentially. The simulation results demonstrate that the ES-SCL-Flip decoder provides an improved error correction performance with only a minimal increase in decoding complexity compared to the conventional CRC-aided SCL decoder. This algorithm attains a commendable equilibrium between the error correction performance and decoding complexity.
A Study of Movable Singularities in Non-Algebraic First-Order Autonomous Ordinary Differential Equations
Authors: Liu Xingyu
Published: July 2024

We studied the movable singularities of solutions of autonomous non-algebraic first-order ordinary differential equations in the form of y′=I(y(t)) and y′=I1(y(t))+I2(y(t))+⋯+In(y(t)), aiming to prove that all movable singularities of all complex solutions of these equations are at most algebraic branch points. This study explores the use of the constructing triangle method to analyze complex solutions of autonomous non-algebraic first-order ordinary differential equations. For complex solutions in the form of y=w+iv, we treat the constructing triangle method as a way to construct a right-angled triangle in the complex plane, with the lengths of the adjacent sides being w and v. We use the definitions of the trigonometric functions sin and cos (the ratio of the adjacent side to the hypotenuse) to represent the trigonometric functions of complex solutions y=w+iv. Since the movable singularities of the inverse functions of trigonometric functions are easy to analyze, the properties of the movable singularities of the complex solutions are then easy to deal with.
Improved Bayesian Model Updating Method for Frequency Response Function with Metrics Utilizing NHBFT-PCA
Authors: Li Jinhui , Deng Zhenhong , Tang Yong , Wang Siqi , Yang Zhe , Luo Huageng , Feng Wujun , Zhang Baoqiang
Published: July 2024

To establish a high-fidelity model of engineering structures, this paper introduces an improved Bayesian model updating method for stochastic dynamic models based on frequency response functions (FRFs). A novel validation metric is proposed first within the Bayesian theory by using the normalized half-power bandwidth frequency transformation (NHBFT) and the principal component analysis (PCA) method to process the analytical and experimental frequency response functions. Subsequently, traditional Bayesian and approximate Bayesian computation (ABC) are improved by integrating NHBFT-PCA metrics for different application scenarios. The efficacy of the improved Bayesian model updating method is demonstrated through a numerical case involving a three-degrees-of-freedom system and the experimental case of a bolted joint lap plate structure. Comparative analysis shows that the improved method outperforms conventional methods. The efforts of this study provide an effective and efficient updating method for dynamic model updating based on the FRFs, addressing some of the existing challenges associated with FRF-based model updating.
Coupled Simultaneous Evolution of Policy, Enterprise Innovation Awareness, and Technology Diffusion in Multiplex Networks
Authors: Wang Jingyi , Hu Rui , Xu Hua
Published: July 2024

This study comprehensively examines the coupling effect of government policies, enterprise behavior, and existing technology on the diffusion of innovative technology. Utilizing multiplex network theory, a multiplex network model is constructed to couple policy incentives, enterprise innovation consciousness, and technology diffusion. Both global- and local-order parameters are introduced to characterize the interaction mechanisms between new and old technologies. By employing the microscopic Markov chain approach (MMCA), the threshold for technology diffusion is derived, theoretically revealing the mechanisms behind the diffusion of innovative technology. Considering the heterogeneity of enterprises, a numerical simulation is conducted on a scale-free network. The results indicate that, as the intensity of policy incentives increases, the threshold for technology diffusion decreases, promoting the spread of innovative technology. Additionally, the coupling relationship between existing technology and innovative technology influences the diffusion scale of the latter. The innovation behavior of enterprises further facilitates the adoption and dissemination of innovative technology.
Fuzzy Bipolar Hypersoft Sets: A Novel Approach for Decision-Making Applications
Authors: Asaad Baravan A. , Musa Sagvan Y. , Ameen Zanyar A.
Published: July 2024

This article presents a pioneering mathematical model, fuzzy bipolar hypersoft (FBHS) sets, which combines the bipolarity of parameters with the fuzziness of data. Motivated by the need for a comprehensive framework capable of addressing uncertainty and variability in complex phenomena, our approach introduces a novel method for representing both the presence and absence of parameters through FBHS sets. By employing two mappings to estimate positive and negative fuzziness levels, we bridge the gap between bipolarity, fuzziness, and parameterization, allowing for more realistic simulations of multifaceted scenarios. Compared to existing models like bipolar fuzzy hypersoft (BFHS) sets, FBHS sets offer a more intuitive and user-friendly approach to modeling phenomena involving bipolarity, fuzziness, and parameterization. This advantage is underscored by a detailed comparison and a practical example illustrating FBHS sets’ superiority in modeling such phenomena. Additionally, this paper provides an in-depth exploration of fundamental FBHS set operations, highlighting their robustness and applicability in various contexts. Finally, we demonstrate the practical utility of FBHS sets in problem-solving and introduce an algorithm for optimal object selection based on available information sets, further emphasizing the advantages of our proposed framework.