bluuebunny/crossref_metadata_2025 huggingface dataset:
Genetic Risk of Ankylosing Spondylitis and Second-Line Therapy Need in Crohn’s Disease: A Mendelian Randomization Study
Authors: Omar Mahmud , Omar Mohammad , Patt Yonatan Shneor , Ukashi Offir , Sharif Yousra , Lahat Adi , Selinger Christian Phillip , Sharif Kassem
Published: December 2024

Background: Crohn’s disease (CD) and Ankylosing Spondylitis (AS) are chronic conditions with overlapping inflammatory pathways. This research investigates the genetic association between AS and the requirement for more aggressive therapeutic interventions in CD, suggesting a likelihood of increased severity in CD progression among individuals diagnosed with AS. Methods: This study utilized two-sample Mendelian randomization (TSMR) to analyze GWAS datasets for AS and CD requiring second-line treatment. Instrumental variables were selected based on single-nucleotide polymorphisms of genome-wide significance. Analytical methods included inverse-variance weighted (IVW), MR Egger, and other MR approaches, alongside sensitivity analysis, to validate the findings. Results: Our results indicated a significant association between AS genetic predisposition and the increased need for second-line treatments in CD. The IVW method showed an Odds Ratio (OR) of 2.16, and MR Egger provided an OR of 2.71, both were statistically significant. This association persisted even after the exclusion of influential outlier SNP rs2517655, confirming the robustness of our findings. Conclusions: This study suggests that genetic factors contributing to AS may influence the progression of CD, potentially necessitating more intensive treatment strategies. These findings underscore the importance of early screening in patients with co-existing AS and CD for tailoring treatment approaches, thus advancing personalized medicine in the management of these complex conditions.
Dulaglutide and Dapagliflozin Combination Concurrently Improves the Endothelial Glycocalyx and Vascular and Myocardial Function in Patients with T2DM and Albuminuria vs. DPP-4i
Authors: Korakas Emmanouil , Thymis John , Oikonomou Evangelos , Mourouzis Konstantinos , Kountouri Aikaterini , Pliouta Loukia , Pililis Sotirios , Pavlidis George , Lampsas Stamatios , Katogiannis Konstantinos , Palaiodimou Lina , Tsivgoulis Georgios , Siasos Gerasimos , Ikonomidis Ignatios , Raptis Athanasios , Lambadiari Vaia
Published: December 2024

Background: The association between diabetic nephropathy and arterial elasticity and endothelial function is well established. In this study, we compared the effect of the combination of dulaglutide and dapagliflozin versus DPP-4 inhibitors on the endothelial glycocalyx, arterial stiffness, myocardial function, and albuminuria. Methods: Overall, 60 patients were randomized to combined dulaglutide and dapagliflozin treatment (n = 30) or DPP-4 inhibitors (DPP-4i, n = 30) (ClinicalTrials.gov: NCT06611904). We measured at baseline and 4 and 12 months post-treatment: (i) the perfused boundary region of the sublingual arterial microvessels, (ii) pulse wave velocity (PWV) and central systolic blood pressure (cSBP), (iii) global left ventricular longitudinal strain (GLS), and (iv) urine albumin-to-creatinine ratio (UACR). Results: After twelve months, dual therapy showed greater improvements vs. DPP-4i in PBR (2.10 ± 0.31 to 1.93 ± 0.23 μm vs. 2.11 ± 0.31 to 2.08 ± 0.28 μm, p < 0.001), UACR (326 ± 61 to 142 ± 47 mg/g vs. 345 ± 48 to 306 ± 60 mg/g, p < 0.01), and PWV (11.77 ± 2.37 to 10.7 ± 2.29 m/s vs. 10.64 ± 2.44 to 10.54 ± 2.84 m/s, p < 0.001), while only dual therapy showed improvement in cSBP (130.21 ± 17.23 to 123.36 ± 18.42 mmHg). These effects were independent of glycemic control. Both treatments improved GLS, but the effect of dual therapy was significantly higher compared to DPP-4i (18.19% vs. 6.01%, respectively). Conclusions: Twelve-month treatment with dulaglutide and dapagliflozin showed a greater improvement in arterial stiffness, endothelial function, myocardial function, and albuminuria than DPP-4is. Early initiation of combined therapy as an add-on to metformin should be considered in these patients.
Patterns of Brain Injury and Clinical Outcomes Related to Trauma from Collisions Involving Motor Vehicles
Authors: Sharma Bharti , Agcon Aubrey May B. , Agriantonis George , Kiernan Samantha R. , Bhatia Navin D. , Twelker Kate , Shafaee Zahra , Whittington Jennifer
Published: December 2024

Background: Despite improvements in technology and safety measures, injuries from collisions involving motor vehicles (CIMVs) continue to be prevalent. Therefore, our goal is to investigate the different patterns of head injuries associated with CIMVs. Method: This is a single-center, retrospective study of patients with motor vehicle-related trauma between 1 January 2016–31 December 2023. Patients were identified based on the International Classification of Diseases (ICD) injury codes and the Abbreviated Injury Severity (AIS) for body region involvement. Result: 536 patients met the inclusion criteria. The majority of the injured population includes pedestrians (46.8%), followed by motorcycle drivers (25.2%), bicyclists (18.7%), and motor vehicle drivers (9.3%). The male-to-female ratios for bicyclists and motorcyclists were 13.7:1 and 11.9:1, respectively, which is higher compared with motor vehicle occupants and pedestrians, with ratios of 2.3:1 and 1.5:1. Patients with blunt trauma (99.63%) were higher than penetrating trauma (0.37%). In most cases, the head had the highest AIS score, with a mean of 3.7. Additionally, the median Injury Severity Score (ISS) was 20. Skull fractures were the most prevalent, followed by hemorrhages, lacerations, contusions, and abrasions. Conclusions: The most prevalent injuries were head injuries and fractures. Fractures were the most common, followed by hemorrhage, laceration, contusion, and abrasion. These findings underscore the high incidence of TBI and fractures in such CIMVs, highlighting the need for targeted trauma interventions and the need for injury prevention strategies to mitigate these severe outcomes.
Three-Dimensional Modelling of Indexed Papillary Muscle Displacement in Patients Requiring Mitral Valve Surgery Using Four-Dimensional Echocardiography Variables
Authors: Ong Zhi Xian , Ler Ashlynn Ai Li , Shen Liang , Kofidis Theo , Ti Lian-Kah , Sazzad Faizus
Published: December 2024

Background: Two-dimensional and three-dimensional echocardiographic imaging are commonly used in assessing ischemic mitral regurgitation (IMR) and degenerative mitral regurgitation (DMR) in patients with mitral valve disease. However, the use of 4D echocardiographic imaging has not yet been reported. The objectives of this study were to explore the efficacy of utilizing 4D echocardiographic variables, determine papillary muscle displacement in patients with either IMR or DMR, and compare the differences in papillary muscle displacement between groups. Methods: Thirty-four patients were divided into two groups: Group 1 (with IMR) and Group 2 (with DMR). Using clinical ultrasound software, 4D echocardiographic variables were obtained and compared between the groups. Pearson’s product–moment correlation test was used to assess the relationship between the presence of IMR and both papillary muscle displacement and indexed papillary muscle displacement. Results: The mean values for papillary muscle displacement in Groups 1 and 2 were 38 ± 6.7 mm and 31.8 ± 6.1 mm, respectively. Indexed papillary muscle displacement was 22.8 ± 3.7 mm in Group 1 and 18.4 ± 3.5 mm in Group 2. There were statistically significant correlations between the presence of IMR and papillary muscle displacement (p = 0.009) and indexed papillary muscle displacement (p = 0.002). A significant correlation was also observed between IMR and PL (p = 0.001), with mean values of 15.7 ± 3.9 mm in Group 1 and 20.2 ± 5.6 mm in Group 2. Conclusions: Four-dimensional echocardiography is effective in evaluating morphological variations in IMR. It successfully determined papillary muscle displacement in patients undergoing mitral valve surgery and demonstrated a positive correlation between IMR and indexed papillary muscle displacement.
The Role of Age and Comorbidity Interactions in COVID-19 Mortality: Insights from Cardiac and Pulmonary Conditions
Authors: Patrascu Raul , Dumitru Cristina Stefania , Laza Ruxandra , Besliu Razvan Sebastian , Gug Miruna , Zara Flavia , Laitin Sorina Maria Denisa
Published: December 2024

Background: Understanding the interactions between age and comorbidities is crucial for assessing COVID-19 mortality, particularly in patients with cardiac and pulmonary conditions. This study investigates the relationship between comorbidities and mortality outcomes in a cohort of hospitalized COVID-19 patients, emphasizing the interplay of age, cardiac, and pulmonary conditions. Methods: We analyzed a cohort of 3005 patients hospitalized with COVID-19 between 2020 and 2022. Key variables included age, comorbidities (diabetes, cardiac, pulmonary, and neoplasms), and clinical outcomes. Chi-square tests and logistic regression models were used to assess the association between comorbidities and mortality. Stratified analyses by age, diabetes, and pulmonary conditions were conducted to explore interaction effects. Additionally, interaction terms were included in multivariable logistic regression models to evaluate the combined impact of age, comorbidities, and mortality. Results: Cardiac conditions such as hypertension, ischemic cardiopathy, and myocardial infarction showed significant protective effects against mortality in younger patients and in those without pulmonary conditions (p < 0.001). However, these protective effects were diminished in older patients and those with pulmonary comorbidities. Age was found to be a significant modifier of the relationship between cardiac conditions and mortality, with a stronger protective effect observed in patients under the median age (p < 0.001). Pulmonary comorbidities significantly increased the risk of mortality, particularly when co-occurring with cardiac conditions (p < 0.001). Diabetes did not significantly modify the relationship between cardiac conditions and mortality. Conclusions: The findings highlight the complex interactions between age, cardiac conditions, and pulmonary conditions in predicting COVID-19 mortality. Younger patients with cardiac comorbidities show a protective effect against mortality, while pulmonary conditions increase mortality risk, especially in older patients. These insights suggest that individualized risk assessments incorporating age and comorbidities are essential for managing COVID-19 outcomes.
The Prevalence of Metabolic Syndrome and Undiagnosed Diabetes in Periodontitis Patients and Non-Periodontitis Controls in a Dental School
Authors: Kosho Madeline X. F. , Verhelst Alexander R. E. , Teeuw Wijnand J. , van Bruchem Sebastiaan , Nazmi Kamran , Gerdes Victor E. A. , Loos Bruno G.
Published: December 2024

Background/Objectives: Metabolic syndrome (MetS) and type 2 diabetes mellitus (T2DM) are major global health concerns, and they often go undetected. Periodontitis shares risk factors and is associated with both conditions. Assessing MetS risk factors among dental patients, especially those with periodontitis, may contribute to early detection and prompt treatment. However, current information about MetS prevalence rates in dental settings is limited. Therefore, our aim was to investigate the prevalence of MetS among patients with generalized periodontitis stage III/IV (GenPD), localized periodontitis stage III/IV (LocPD), and non-periodontitis controls. We also investigated the prevalence of undiagnosed T2DM in the same population. Moreover, we performed a pilot study to evaluate the possibility of measuring fructosamine levels in oral rinse samples, as an alternative to HbA1c, to screen for hyperglycemia. Methods: Periodontitis patients and non-periodontitis controls were recruited from a dental school, all aged ≥ 40 years. MetS prevalence was determined according to four different MetS definitions. T2DM prevalence was based on elevated HbA1c levels (HbA1c ≥ 7.0%). Biochemical analysis from blood was carried out by finger stick sampling. A subset of participants was asked to provide an oral rinse sample for the measurement of fructosamine, which was correlated to HbA1c from blood. Results: A total of 105 patients with periodontitis (GenPD stage III/IV: n = 44, LocPD stage III/IV: n = 61) and 88 non-periodontitis controls, with a mean age of 54.4 years, were included. The prevalence of MetS, according to four different MetS definitions, was 68.2–81.8% in GenPD patients, 42.6–62.3% in LocPD patients, and 52.3–69.3% in controls. The prevalence of T2DM, as evidenced by elevated HbA1c, was 20.5% in GenPD patients, 18.3% in LocPD patients, and 10.2% in controls (p = 0.094). A substantial number of subjects were not aware that they were being suspected to have T2DM, i.e., 13.6% in GenPD patients, 8.2% in LocPD patients, and 8.0% in controls (p = 0.335). In a subset of participants (n = 48), we found no significant correlation between HbA1c and oral fructosamine (r= 0.24, p = 0.103). Conclusions: The overall results showed a relatively high prevalence of patients with MetS and/or elevated HbA1c among periodontitis patients and controls in the dental school. Of those with suspected T2DM, a substantial number were not aware of having T2DM. Oral health care professionals could therefore contribute to early detection for T2DM and/or create awareness in patients at risk for a disease related to MetS. To date, initial results on the use of oral fructosamine as an alternative for HbA1c cast doubt, and further research is needed.
Operational Efficiency of Public Hospitals in Greece During the COVID-19 Pandemic: A Comparative Analysis Using DEA and AHP Models
Authors: Mitakos Athanasios , Mpogiatzidis Panagiotis
Published: December 2024

This study evaluates the efficiency of public hospitals in Greece during the COVID-19 epidemic in 2020, using Data Envelopment Analysis (DEA) and the Analytical Hierarchy Process (AHP). Faced with unprecedented pressure from increased demand for medical services, these hospitals had to adapt quickly while playing a crucial role in supporting local economies, similar to the effect of tourism on rural economies. This study reveals that, despite average efficiency scores of 83% for result-oriented models (BCC) and 65% for constant return models (CCR), inefficiencies of scale emerged under the pressures of the pandemic. The AHP, by incorporating qualitative criteria and decision-makers’ preferences, offers a valuable perspective but shows little correlation with DEA’s quantitative results. This research emphasizes the importance of utilizing integrated methods to formulate a more comprehensive assessment, adapted to the complex challenges of the healthcare sector during crisis periods.
Allocation Strategy Optimization Using Repulsion-Enhanced Quantum Particle Swarm Optimization for Multi-AUV Systems
Authors: Lin Changjian , Yu Dan , Lin Shibo
Published: December 2024

In the context of multi-autonomous underwater vehicle (multi-AUV) operations, the target assignment is addressed as a multi-objective allocation (MOA) problem. The selection of strategy for multi-AUV target allocation is dependent on the current non-cooperative environment. This paper establishes a multi-AUV allocation situation advantage evaluation system to assess and quantify the non-cooperative environment. Based on this framework, a multi-AUV target allocation model using a bi-matrix game theory is developed, where multi-AUV target allocation strategies are considered as part of the strategic framework within the game. The payoff matrix is constructed based on factors including the situational context of multi-AUV operations, effectiveness, and AUV operational integrity. The Nash equilibrium derived from the game analysis serves as the optimal solution for resource distribution in multi-AUV non-cooperative scenarios. To address the challenge of finding the Nash equilibrium in bi-matrix games, this paper introduces a repulsion process quantum particle swarm optimization (RPQPSO) algorithm. This method not only resolves the complexities of Nash equilibrium computation but also overcomes the limitations of traditional optimization methods that often converge to local optima. A simulation experiment of multi-AUV operations is designed to validate the multi-AUV target allocation model, demonstrating that the RPQPSO algorithm performs effectively and is applicable to multi-AUV task scenarios.
Aeroelastic Simulation of Full-Machine Wind Turbines Using a Two-Way Fluid-Structure Interaction Approach
Authors: Lu Nan-You , Lam Jia Kai , Lin Yu , Chau Shiu-Wu
Published: December 2024

Two-way fluid–structure interaction (FSI) simulation of wind turbines has gained significant attention in recent years due to the growth of offshore wind energy development. Strong coupling procedures in these simulations predict realistic behavior with higher accuracy but result in increased computational costs and potential numerical instabilities. This paper proposes a mixed weak and strong coupling approach for the FSI simulation of a 5 MW wind turbine. The deformation of the turbine blade is calculated using a weak coupling approach, ensuring blade deflection meets a convergence criterion before rotating to the next azimuthal position. Fluid and solid solvers are partitioned, utilizing the commercial software packages STAR-CCM+ and Abaqus, respectively. Flexible and rigid blade cases are modeled, and the calculated loads, power, and blade tip displacement for the rotor at a constant rotating speed are compared. The proposed model is validated, showing good agreement with the existing literature and results comparable to those from another validated wind turbine simulator. The effect of rotor–tower interaction is evident in the results. Based on our calculations, the power production of flexible blades is evaluated to be 9.6% lower than that of rigid blades.
Large Drawdowns and Long-Term Asset Management
Authors: Jondeau Eric , Pauli Alexandre
Published: December 2024

Long-term investors are often hesitant to invest in assets or strategies prone to significant drawdowns, primarily due to the challenge of predicting these drawdowns. This study presents a multivariate Markov-switching model for small- and large-cap returns in the U.S. equity markets, demonstrating that three distinct regimes are necessary to capture the negative trends in expected returns during financial crises. Our findings indicate that this framework enhances the prediction of conditional drawdowns compared to standard alternative models of financial returns. Furthermore, out-of-sample analysis shows that investment strategies based on these predictions outperform those relying on models with one or two regimes.
Exploring the Relationship Between Visual Perception of the Urban Riverfront Core Landscape Area and the Vitality of Riverfront Road: A Case Study of Guangzhou
Authors: Zhang Shawei , Lu Junwen , Guo Ran , Yang Yiding
Published: December 2024

The vitality of riverfront districts, as a crucial component of urban livability, is profoundly influenced by human visual perception of the surrounding environment. This study takes the Pearl River in Guangzhou as an example and explores the relationship between the visual perception of the urban riverfront core landscape area and the vitality of Riverfront Road. Employing subjective environment perception prediction methods and analyzing the riverfront landscape pictures captured by the research team, we quantified six essential perceptual dimensions. Furthermore, we evaluated the vitality of Riverfront Road through a four-step process: 1. measuring key visual indices of Riverfront Road, including the green view index (GVI), water view index (WVI), sky view index (SVI), and building view index (BVI); 2. evaluating the proximity of cultural landmarks to Riverfront Road; 3. calculating the convenience of driving, buses, and subways for Riverfront Road with the network analysis method; 4. deriving the vitality value of Riverfront Road through the combination of hotspot data from Baidu. With the application of random forest and result comparisons, we obtained a comprehensive analysis of the correlation between visual perception of the urban riverfront core landscape area and the vitality of Riverfront Road. The results reveal the significant correlation between these two factors and highlight that visual perception of the old city landscape area is superior to that of the new city, although the cultural landmarks and transportation convenience play essential roles in the improvement of vitality in Riverfront Road. It is evident that relying solely on visual design may fail to prominently boost vitality. Overall, spatial design should adopt a multidimensional approach, integrating various factors such as transportation convenience, social interaction venues, cultural activities, etc., to create a cohesive vitality network.
Spatiotemporal Patterns and Driving Factors of Carbon Footprint in Coastal Saline Cropland Ecosystems: A Case Study of the Yellow River Delta, China
Authors: Li Yang , Zhang Dingwen , Wen Ying , Liu Xiaoling , Zhang Yi , Wang Guangmei
Published: December 2024

Coastal saline cropland ecosystems are becoming increasingly vital for food security in China, driven by the decline in arable land and the growing demand for resource-intensive diets. Although developing and utilizing saline land can boost productivity, it also impacts greenhouse gas (GHG) emissions. This study uses the Yellow River Delta as a case study to analyze the spatial-temporal patterns of carbon footprints in saline croplands from 2001 to 2020 and their correlations with climate factors, cropland management scale, and agricultural mechanization. The results reveal that agricultural production in this region is characterized by high inputs, emissions, and outputs, with carbon emission efficiency improving significantly due to a reduction in net carbon emissions. Major sources of carbon emissions include electricity, chemical nitrogen fertilizers, nitrogen input, and straw return, which together account for 65.06% of total emissions. Based on these findings, three key principles have been proposed for policy recommendations to enhance carbon emission efficiency. First, adopt tailored strategies for regions with different salinization levels. Second, strengthen cropland drainage infrastructure to mitigate the adverse effects of heavy rainfall. Third, expand the scale of cropland management through land transfers and promote agricultural mechanization. These insights offer valuable guidance for mitigating GHG emissions in coastal saline cropland ecosystems.
Bioenergy for Sustainable Rural Development: Elevating Government Governance with Environmental Policy in China
Authors: Li Yue , Sohail Muhammad Tayyab , Zhang Yanan , Ullah Sana
Published: December 2024

Energy is not only the crucial driver of economic activities within rural areas. Conventional energy sources are crucial for the prosperity of rural areas; however, they also prove detrimental to the rural ecosystem. To achieve sustainable rural development, increasing the consumption of renewable energy sources can prove vital. Among all the renewable energy sources, bioenergy is the cheapest and easiest to produce in rural areas. Therefore, it is crucial to estimate the impact of bioenergy on the rural development of China. Thus, the primary purpose of this analysis is to analyze the impact of bioenergy and environmental policy stringency on the rural development of China from 1995 to 2022 by employing the autoregressive distributed lag (ARDL) and quantile autoregressive distributed lag (QARDL) framework. The results highlight the significance of bio-energy for rural development in the short and long run. Likewise, environmental policy stringency is also a vital factor in fostering short- and long-run rural development. Based on these outcomes, it is recommended that policymakers integrate bioenergy development policies into broader rural development strategies.
A Comprehensive Study of Spatial Distribution, Pollution Risk Assessment, and Source Apportionment of Topsoil Heavy Metals and Arsenic
Authors: Chen Honghua , Sun Xinxin , Sun Longhui , An Yunce , Xiao Ying , Zhang Jintao , Hong Yunpeng , Song Xiaodong
Published: December 2024

Accurately identifying pollution risks and sources is crucial for regional land resource management. This study takes a certain coastal county in eastern China as the object to explore the spatial distribution, pollution risk, and source apportionment of heavy metals in topsoil. A total of 633 samples were collected from the topsoil with a depth ranging from 0 to 20 cm, which came from different topographical and land use types (e.g., farmland, industrial areas, and mining areas), and the concentrations of HMs and As were measured by using atomic fluorescence spectrometry and inductively coupled plasma mass spectrometry. Firstly, the spatial distribution of soil HMs (Cd, Cr, Hg, Ni, and Pb) and arsenic (As) was predicted by incorporating environmental variables strongly affecting soil formation into geostatistical methods and machine learning approaches. Then, various pollution indicators were employed to conduct pollution evaluations, and potential ecological risk assessments were implemented based on the generated soil map. Finally, source apportionment was conducted using random forest (RF), absolute principal component score–multiple linear regression (APCS-MLR), correlation analysis, and spatial distribution of soil HMs and As. Findings in this research reveal that the RF approach yielded the best spatial prediction performance (0.59 ≤ R2 ≤ 0.73). The Nemerow and geoaccumulation indices suggest that various pollution levels exist in this area. The average concentrations of As, Hg, and Ni are 7.233 mg/kg, 0.051 mg/kg, and 27.43 mg/kg respectively, being 1.14 times, 1.27 times, and 1.15 times higher than the background levels, respectively. The central–northern region presented a slight potential ecological risk, with Hg and Cd being identified as the primary risk factors. Natural, agricultural, transportation, and industrial and mining activities were identified as the main HMs and As sources. These findings will assist in the design of targeted policies to reduce the risks of HMs and As in urban soil and offer useful guidelines for soil pollution research in similar regions.
Omics Biology in Diagnosis of Diseases: Towards Empowering Genomic Medicine from an Evolutionary Perspective
Authors: Maldonado Emanuel , Khan Imran
Published: December 2024

In this section, we reintroduce the original aims and scope of the Special Issue entitled “Omics Biology in Diagnosis of Diseases: Advances in Bioinformatics and Data Analyses”, enabling readers to find an appropriate framing for the remainder of the present closing editorial [...]
A Pareto-Based Clustering Approach for Solving a Bi-Objective Mobile Hub Location Problem with Congestion
Authors: Dehghan Chenary Maryam , Ferdowsi Arman , Hartl Richard F.
Published: December 2024

Background: This paper introduces an enhanced multi-period p-mobile hub location model that accounts for critical factors such as service time, flow processing delays, and congestion impacts at capacity-constrained hubs. As (urban) transportation networks evolve, mobile hubs play an increasingly vital role in promoting sustainable logistics solutions and addressing complex operational challenges. By enabling the repositioning of hubs across periods, this model seeks to minimize overall costs, particularly in response to dynamic demand fluctuations. Method: To solve this problem, we propose a bi-objective optimization model and introduce a hybrid meta-heuristic algorithm tailored to this application. The algorithm involves a clustering-based technique for evaluating solutions and a refined genetic approach for producing new sets of solutions. Results: Various experiments have been conducted on the Australian Post dataset to evaluate the proposed method. The results have been compared with Multiple-Objecti-ve Particle Swarm Optimization (MOPSO) and Non-Domi-nated Sorting Genetic Algorithm (NSGA-II) using several performance evaluation metrics. Conclusions: The results indicate that the proposed algorithm can provide remarkably better Pareto sets than the other competitive algorithms.
Modeling and Dynamic Analysis of Double-Row Angular Contact Ball Bearing–Rotor–Disk System
Authors: Zhang Haibiao , Li Zhen , Liu Haijian , Liu Tao , Wang Qingshan
Published: December 2024

This article presents a general numerical method to establish a mathematical model of a bearing–rotor–disk system. This mathematical model consists of two double-row angular contact ball bearings (DRACBBs), a rotor and a rigid disk. The mathematical model of the DRACBB is built on the basis of elastic Hertz contact by adopting the Newton Raphson iteration method, and three different structure forms are taken into account. The rotor is modeled by employing a finite element method in conjunction with Timoshenko beam theory, and the rigid disk is modeled by applying the lumped parameter method. The mathematical model of the bearing–rotor–disk system is constructed by the coupling of the bearing, rotor and disk, and the dynamic response of the bearing–rotor–disk system can be solved by employing the Newmark-β method. The validation of the above mathematical model is demonstrated by comparing the proposed results with the results from the existing literature and finite element software. The dynamic characteristics of the DRACBBs and the dynamic response of the bearing–rotor–disk system are investigated by parametric study. A dynamic characteristic analysis of the DRACBB is conducted to ensure the optimal structure form of the DRACBB under complex external loads, and it can provide a reference for the selection of the structural forms of DRACBBs.
Hybrid Deep Learning Model for Fault Diagnosis in Centrifugal Pumps: A Comparative Study of VGG16, ResNet50, and Wavelet Coherence Analysis
Authors: Zaman Wasim , Siddique Muhammad Farooq , Ullah Saif , Saleem Faisal , Kim Jong-Myon
Published: December 2024

Significant in various industrial applications, centrifugal pumps (CPs) play an important role in ensuring operational efficiency, yet they are susceptible to faults that can disrupt production and increase maintenance costs. This study proposes a robust hybrid model for accurate fault detection and classification in CPs, integrating Wavelet Coherence Analysis (WCA) with deep learning architectures VGG16 and ResNet50. WCA is initially applied to vibration signals, creating time–frequency representations that capture both temporal and frequency information, essential for identifying subtle fault characteristics. These enhanced signals are processed by VGG16 and ResNet50, each contributing unique and complementary features that enhance feature representation. The hybrid approach fuses the extracted features, resulting in a more discriminative feature set that optimizes class separation. The proposed model achieved a test accuracy of 96.39%, demonstrating minimal class overlap in t-SNE plots and a precise confusion matrix. When compared to the ResNet50-based and VGG16-based models from previous studies, which reached 91.57% and 92.77% accuracy, respectively, the hybrid model displayed better classification performance, particularly in distinguishing closely related fault classes. High F1-scores across all fault categories further validate its effectiveness. This work underscores the value of combining multiple CNN architectures with advanced signal processing for reliable fault diagnosis, improving accuracy in real-world CP applications.
A Multi-Objective Optimization Design Method for High-Aspect-Ratio Wing Structures Based on Mind Evolution Algorithm Backpropagation Surrogate Model
Authors: Nan Jin , Zheng Junhua , Jiang Bochuan , Li Yuhang , Chen Jiayun , Fan Xuanqing
Published: December 2024

The design of high-aspect-ratio wings enhances the flight efficiency of UAVs but also introduces significant aeroelasticity challenges. The efficient optimization of wing structures in complex environments has become critical. To address the current challenges in balancing wing strength with lightweight structural designs, this study proposed an intelligent solution method for optimizing wing dimensions and structural layout. Driven by mechanical simulation data, the method established a mapping relationship between the structural layout and dimensions of the wing and its bending stiffness. This approach was further enhanced by the mind evolution algorithm (MEA) to optimize the solution performance of the surrogate model. The wing structure optimization model was established using the multi-objective grey wolf optimizer (MOGWO) based on the surrogate model for search and optimization. This study focused on the composite material wing of a long-endurance unmanned aerial vehicle (UAV). The established MEA-BP surrogate model demonstrated high computational efficiency, with the prediction error standard deviation (STD) of wing deflection not exceeding 0.495 mm. The optimization model required 175 s to calculate the Pareto front solutions. The optimized structure resulted in a 28.32% increase in wing equivalent stiffness, and weight only increased by 6.67% compared to the original structure. These results showcased the effectiveness of the proposed method and validated the feasibility of integrating intelligent optimization algorithms and machine learning in the field of aircraft design.
Approximation of the Fractional SDEs with Stochastic Forcing
Authors: Kubilius Kęstutis
Published: December 2024

Using the implicit Euler and Milstein approximation schemes, the conditions for the pathwise convergence rate of these approximations to the solution of the fractional SDEs with stochastic forcing are found.
Review of Experimental, Theoretical and Numerical Advances in Multi-Crack Fracture Mechanics
Authors: Wang Zhao-Wei , Li D. M. , Zhong Yi-Fan , Liu Yi-Kung , Shao Yu-Nong
Published: December 2024

In engineering fracture problems, cracks tend to interact with each other rather than exist singly. In recent years, the phenomenon of multi-cracking has received attention from both academia and industry. This article firstly emphasizes the importance and research trends of crack interactions. The article then discusses the experimental observation and theoretical modeling of the multi-crack problem and compares the different numerical methods in detail. Finally, this paper offers a comprehensive summary and in-depth analysis of the advancements in multi-crack fracture mechanics, aiming to provide reliable support for solving the multi-crack problem in engineering.
Potential Use of Plasma Rich in Growth Factors in Age-Related Macular Degeneration: Evidence from a Mouse Model
Authors: Anitua Eduardo , Muruzabal Francisco , Recalde Sergio , Fernandez-Robredo Patricia , Alkhraisat Mohammad Hamdan
Published: December 2024

Background and Objectives: Age-related macular degeneration (AMD) is the leading cause of low vision and legal blindness in adults in developed countries. Wet AMD can be successfully treated using vascular endothelial growth factor (VEGF) inhibitors; however, dry AMD currently has no effective treatment. The purpose of this study is to analyze the efficacy of intraocular injection of plasma rich in growth factors (PRGF) in an AMD mouse model induced by intraperitoneal administration of sodium iodate. Materials and Methods: Intravitreal application of PRGF (experimental group) and saline (control group) was performed immediately after intraperitoneal injection of sodium iodate. Retinographies were performed at 2 and 7 days after treatment administration. The eyes were retrieved for histological and immunohistological analysis. Statistical analysis was performed to compare the outcomes between the study groups. Results: In comparison to saline solution, PRGF significantly decreased the depigmentation of the RPE, showing a more reddened retina. PRGF intravitreal treatment significantly reduced the glial fibrillary acidic protein (GFAP) stained processes, suggesting a significant reduction in the risk of scar formation. Moreover, the myofibroblast invasion into the RPE cell layer was significantly reduced in the PRGF-treated group of mice. There was a tendency for better preservation of the photoreceptors in the PRGF group. Conclusions: Within the limitations of this study, intravitreal injection of PRGF provided significant protection against the degeneration of the photoreceptors and the RPE induced by the systemic administration of NaIO3.
Burnout and Turnover Intention Among Community and Hospital Pharmacists in Metro Manila, Philippines
Authors: Carandang Rogie Royce , Puguon Jr. Forter , Santos Mary Louisse , Ilagan Elizabeth , Gamboa Kellie Gwyneth , Aquino Jose Gerardo
Published: December 2024

Burnout among pharmacists is an increasingly urgent concern, with previous studies emphasizing its physical, psychological, and occupational consequences. However, limited research has explored specific burnout experiences and their impact on turnover intentions among Filipino pharmacists. This study examined the association between burnout, its symptoms, and turnover intentions among pharmacists in Metro Manila, Philippines. We used the Burnout Assessment Tool and Turnover Intention Scale to conduct a cross-sectional study among 300 community and hospital pharmacists. A multiple logistic regression analysis examined the association between burnout and turnover intentions among pharmacists. Of the 300 pharmacists, 73.0% were at risk of or experiencing severe burnout, and 75.7% reported a turnover intention. Pharmacists at risk of or experiencing severe burnout showed a higher likelihood of leaving their jobs (Adjusted Odds Ratio [AOR] = 7.59; 95% Confidence Interval [CI] = 3.68, 15.64), especially if they felt exhausted (AOR = 2.49, 95% CI = 1.27, 4.89) or mentally distant (AOR = 3.92, 95% CI = 1.95, 7.86) from their work. Furthermore, dissatisfaction with salary, lack of incentives and promotions, and insufficient staffing emerged as other factors associated with the desire to leave. Addressing pharmacists’ physical and mental well-being, alongside workplace improvements, is crucial for reducing turnover intentions.
Effect of Rotational Speed on Mechanical Properties of AA5083/AA6082 Friction Stir Welded T-Joints for Naval Applications
Authors: Di Bella Guido , Borsellino Chiara , Chairi Mohamed , Campanella Davide , Buffa Gianluca
Published: December 2024

This study evaluates the influence of rotational speed on the mechanical and microstructural properties of T-joints fabricated via friction stir welding (FSW) using dissimilar aluminum alloys, AA5083 and AA6082, for naval applications. Three types of joints were produced by maintaining a constant traverse speed of 100 mm/min and varying the tool rotational speed at 500, 700, and 900 rpm. Mechanical performance was assessed through pull-out tests and microhardness measurements. The joints fabricated at 500 rpm demonstrated superior mechanical properties, including a more uniform hardness distribution and higher pull-out strength, attributed to optimized material mixing and heat input at this speed. In contrast, higher rotational speeds led to defect formation, such as wormholes, and compromised mechanical performance. These findings underscore the importance of optimizing rotational speed to enhance joint quality, making FSW a viable solution for manufacturing durable, lightweight structures in demanding marine environments.
From Pairwise Comparisons of Complex Behavior to an Overall Performance Rank: A Novel Alloy Design Strategy
Authors: Herschberg Rafael , Rateau Lisa , Martinelli Laure , Balbaud-Célérier Fanny , Dhers Jean , Fraczkiewicz Anna , Ramstein Gérard , Tancret Franck
Published: December 2024

A method is developed to exploit data on complex materials behaviors that are impossible to tackle by conventional machine learning tools. A pairwise comparison algorithm is used to assess a particular property among a group of different alloys tested simultaneously in identical conditions. Even though such characteristics can be evaluated differently across teams, if a series of the same alloys are analyzed among two or more studies, it is feasible to infer an overall ranking among materials. The obtained ranking is later fitted with respect to the alloy’s composition by a Gaussian process. The predictive power of the method is demonstrated in the case of the resistance of metallic materials to molten salt corrosion and wear. In this case, the method is applied to the design of wear-resistant hard-facing alloys by also associating it with a combinatorial optimization of their composition by a multi-objective genetic algorithm. New alloys are selected and fabricated, and their experimental behavior is compared to that of concurrent materials. This generic method can therefore be applied to model other complex material properties—such as environmental resistance, contact properties, or processability—and to design alloys with improved performance.
Microstructural Suitability and Stability of AlSi10Mg–Sn Plasma Coatings for Thermal Energy Storage Purposes
Authors: Molteni Matteo , Bona Marco , Chierichetti Andrea , Trecordi Giacomo , Gariboldi Elisabetta
Published: December 2024

The study explored the possibility of producing thick coatings of fully metallic composite phase change materials with suitable microstructure for thermal energy storage or thermal energy management purposes. The composite materials are based on Al-Si-based alloys with Sn additions, potentially obtainable from scraps. This leads to an Sn-rich low-melting phase which is able to store/release heat when it melts/solidifies. The material can thus be considered as a composite phase change material (C-PCM). A thick coating was deposited on an Al alloy substrate by plasma spray, mixing AlSi10Mg and Sn powders in a 60:40% mass ratio. Optical scanning microscopy and X-ray diffraction revealed a microstructure suitable for a C-PCM, presenting Sn basins interrupted by a matrix made up of primary Al and Al–Si eutectic. Preliminary investigation into the reliability of the coating was conducted by performing up to 10 heat cycles across the melting temperature of the low-melting phase, simulating service in TES/TEM devices. No significant changes in its coating microstructure were observed. Minor surface leakage of molten Sn occurred, mainly during the first heat cycle. No detachment of the coating or cracks formed within the coating were observed, which could have been expected due to the mismatch in the coefficients of thermal expansion of the main phases and to the expansion/shrinkage due to Sn melting/solidification.
Structure of Eutectic Al-Si Alloy Subjected to Compression Plasma Flow Impact
Authors: Bibik Natallia , Metel Alexander , Cherenda Nikolai , Sotova Catherine , Astashynski Valiantsin , Kuzmitski Anton , Melnik Yury , Vereschaka Alexey
Published: December 2024

The structure and phase composition of a eutectic silumin surface layer modified by compression plasma flow impact were investigated in this work. Plasma flows were generated by a magnetoplasma compressor of a compact geometry in a nitrogen atmosphere. The energy density absorbed by the surface layer was varied in the range of 10–35 J/cm2. X-ray diffraction analysis, scanning electron microscopy, transmission electron microscopy and X-ray microanalysis were used as investigation techniques. It was found that the plasma impact led to the formation of a molten layer with a thickness of up to 50 μm. The layer thickness increased with the growth of the absorbed energy density. Dissolution of the intermetallic compounds and primary silicon crystals occurred as a result. The modified surface layer contained grains of a supersaturated solid silicon solution in aluminum. Grains with sizes of 100–500 nm were separated by interlayers of hypereutectic silumin containing nanocrystalline silicon precipitates. The doping elements of the alloy were concentrated mainly in these interlayers. The plasma impact resulted in a 1.5-fold microhardness increase.
Design and Implementation of a CMOS-MEMS Out-of-Plane Detection Gyroscope
Authors: Tian Huimin , Zhang Zihan , Liu Li , Wei Wenqiang , Cao Huiliang
Published: December 2024

A MEMS gyroscope is a critical sensor in attitude control platforms and inertial navigation systems, which has the advantages of small size, light weight, low energy consumption, high reliability and strong anti-interference capability. This paper presents the design, simulation and fabrication of a Y-axis gyroscope with out-of-plane detection developed using CMOS-MEMS technology. The structural dimensions of the gyroscope were optimized through a multi-objective genetic algorithm, and modal, harmonic response and range simulation analyses were carried out to verify the reasonableness of the design. The chip measured 1.2 mm × 1.3 mm. The simulation results indicate that the driving and detecting frequencies of the gyroscope were 9215.5 Hz and 9243.5 Hz, respectively; the Q-factors were 83,790 and 46,085; the mechanical sensitivity was 4.87 × 10−11 m/°/s; and the operational range was ±600°/s. Chip testing shows that the static capacitance was consistent with the preset value. The error between the measured frequency characteristics and the simulation results was 1.9%. This design establishes a foundation for the integration of the gyroscope’s structure and circuitry.
Bioremediation of Oil-Contaminated Soils Using Biosurfactants Produced by Bacteria of the Genus Nocardiopsis sp.
Authors: Biktasheva Liliya , Gordeev Alexander , Usova Arina , Kirichenko Anastasia , Kuryntseva Polina , Selivanovskaya Svetlana
Published: December 2024

One of the effective and safe methods of soil cleanup from oil pollution is bioremediation by introducing microorganisms or their metabolites. In this study, the effect of biosurfactants produced by Nocardiopsis sp. 3mo on the rate of bioremediation of oil-contaminated soils was assessed. Biosurfactants were introduced into soils contaminated with 2% oil at a concentration of 0.05 and 0.1%, and the degree of hydrocarbon degradation was estimated within 63 days. It was found that the studied biosurfactant belonged to the glycopeptide type. The aeration and irrigation of oil-contaminated soil (PSA) resulted in a 5% decrease in the number of hydrocarbons. The introduction of biosurfactants into oil-contaminated soil at a concentration of 0.5 (BS(0.5)) and 1 g kg−1 (BS(1)) resulted in a 29 and 35% decrease in the content of hydrocarbons, respectively. The state of the soil microbiome was assessed by its metabolic activity. Thus, the respiratory activity of microorganisms on the first day after contamination increases by 5–7 times, and urease activity by 3–4 times. The introduction of oil into the soil during the first day reduces the activity of dehydrogenase by 2.3–1.6 times. In the process of bioremediation, the indicators of microbial activity returned to values close to the original. Thus, it was established that the use of biosurfactants produced by Nocardiopsis sp. 3mo increases the ability of the native soil community to degrade hydrocarbons.