bluuebunny/crossref_metadata_2025 huggingface dataset:
Privacy-Preserving Techniques in Generative AI and Large Language Models: A Narrative Review
Authors: Feretzakis Georgios , Papaspyridis Konstantinos , Gkoulalas-Divanis Aris , Verykios Vassilios S.
Published: November 2024

Generative AI, including large language models (LLMs), has transformed the paradigm of data generation and creative content, but this progress raises critical privacy concerns, especially when models are trained on sensitive data. This review provides a comprehensive overview of privacy-preserving techniques aimed at safeguarding data privacy in generative AI, such as differential privacy (DP), federated learning (FL), homomorphic encryption (HE), and secure multi-party computation (SMPC). These techniques mitigate risks like model inversion, data leakage, and membership inference attacks, which are particularly relevant to LLMs. Additionally, the review explores emerging solutions, including privacy-enhancing technologies and post-quantum cryptography, as future directions for enhancing privacy in generative AI systems. Recognizing that achieving absolute privacy is mathematically impossible, the review emphasizes the necessity of aligning technical safeguards with legal and regulatory frameworks to ensure compliance with data protection laws. By discussing the ethical and legal implications of privacy risks in generative AI, the review underscores the need for a balanced approach that considers performance, scalability, and privacy preservation. The findings highlight the need for ongoing research and innovation to develop privacy-preserving techniques that keep pace with the scaling of generative AI, especially in large language models, while adhering to regulatory and ethical standards.
AI Impact on Hotel Guest Satisfaction via Tailor-Made Services: A Case Study of Serbia and Hungary
Authors: Makivić Ranko , Vukolić Dragan , Veljović Sonja , Bolesnikov Minja , Dávid Lóránt Dénes , Ivanišević Andrea , Silić Mario , Gajić Tamara
Published: November 2024

This study examines the level of implementation of artificial intelligence (AI) in the personalization of hotel services and its impact on guest satisfaction through an analysis of tourists’ attitudes and behaviors The focus of the research is on how personalized recommendations for food and beverages, activities, and room services, delivered by trustworthy AI systems, digital experience, and the perception of privacy and data security, influence overall guest satisfaction. The research was conducted in Serbia and Hungary, using structural models to assess and analyze direct and indirect effects. The results show that AI personalization significantly contributes to guest satisfaction, with mediating variables such as trust in AI systems and technological experience playing a key role. A comparative analysis highlights differences between Hungary, a member of the European Union, and Serbia, a country in transition, shedding light on specific regulatory frameworks and cultural preferences in these countries.
Enhancing Real-Time Cursor Control with Motor Imagery and Deep Neural Networks for Brain–Computer Interfaces
Authors: Akuthota Srinath , Janapati Ravi Chander , Kumar K. Raj , Gerogiannis Vassilis C. , Kanavos Andreas , Acharya Biswaranjan , Grivokostopoulou Foteini , Desai Usha
Published: November 2024

This paper advances real-time cursor control for individuals with motor impairments through a novel brain–computer interface (BCI) system based solely on motor imagery. We introduce an enhanced deep neural network (DNN) classifier integrated with a Four-Class Iterative Filtering (FCIF) technique for efficient preprocessing of neural signals. The underlying approach is the Four-Class Filter Bank Common Spatial Pattern (FCFBCSP) and it utilizes a customized filter bank for robust feature extraction, thereby significantly improving signal quality and cursor control responsiveness. Extensive testing under varied conditions demonstrates that our system achieves an average classification accuracy of 89.1% and response times of 663 milliseconds, illustrating high precision in feature discrimination. Evaluations using metrics such as Recall, Precision, and F1-Score confirm the system’s effectiveness and accuracy in practical applications, making it a valuable tool for enhancing accessibility for individuals with motor disabilities.
Exploring Perspectives of Blockchain Technology and Traditional Centralized Technology in Organ Donation Management: A Comprehensive Review
Authors: Bawa Geet , Singh Harmeet , Rani Sita , Kataria Aman , Min Hong
Published: November 2024

Background/Objectives: The healthcare sector is rapidly growing, aiming to promote health, provide treatment, and enhance well-being. This paper focuses on the organ donation and transplantation system, a vital aspect of healthcare. It offers a comprehensive review of challenges in global organ donation and transplantation, highlighting issues of fairness and transparency, and compares centralized architecture-based models and blockchain-based decentralized models. Methods: This work reviews 370 publications from 2016 to 2023 on organ donation management systems. Out of these, 85 publications met the inclusion criteria, including 67 journal articles, 2 doctoral theses, and 16 conference papers. About 50.6% of these publications focus on global challenges in the system. Additionally, 12.9% of the publications examine centralized architecture-based models, and 36.5% of the publications explore blockchain-based decentralized models. Results: Concerns about organ trafficking, illicit trade, system distrust, and unethical allocation are highlighted, with a lack of transparency as the primary catalyst in organ donation and transplantation. It has been observed that centralized architecture-based models use technologies such as Python, Java, SQL, and Android Technology but face data storage issues. In contrast, blockchain-based decentralized models, mainly using Ethereum and a subset on Hyperledger Fabric, benefit from decentralized data storage, ensure transparency, and address these concerns efficiently. Conclusions: It has been observed that blockchain technology-based models are the better option for organ donation management systems. Further, suggestions for future directions for researchers in the field of organ donation management systems have been presented.
New Materials and Structures: Anti-Escape Trap Net for Trapping Eucryptorrhynchus brandti (Harold, 1880) (Coleoptera: Curculionidae)
Authors: Li Hongyu , Ding Weicheng , Wen Chao , Wen Junbao
Published: November 2024

The weevil Eucryptorrhynchus brandti (Harold, 1880), a wood-boring pest of Ailanthus altissima (Mill.) Swingle, has caused significant ecological damage and economic loss in China. Physical control was effective against the related species Eucryptorrhynchus scrobiculatus (Motschulsky). One type of trunk trap net controlled the adult weevil population through blocking and trapping. However, the effectiveness of this device was compromised by their tendency to escape when encountering such trapping nets. Therefore, it is crucial to enhance and optimize both the material composition and structural design of trap nets to enhance weevil capture rates by mitigating escape behavior. In this study, we compared the capture efficacy of an anti-escape trap net (AETN) with novel materials (Velcro) and a double-layer trap net (DLTN). The results indicate that the mean recapture rate of AETNs (50%) was significantly higher than that of DLTNs (3%) in laboratory tests. The total number of E. brandti captured using AETNs was 11 times higher than that of DLTNs in field marker recapture tests and 4 times higher in capture tests on field populations. The new AETN structures could effectively prevent the escape behavior of E. brandti and capture weevils. The use of Velcro made the AETN easier to manufacture, more convenient to use, and less costly. Overall, the AETN is an economical and environmentally friendly physical control device.
Taxonomy of the Genus Bryobia Koch (Acari: Tetranychidae): Reconsideration of Subgenera and Updated Species Groups
Authors: Mirza Jawwad Hassan , Alatawi Fahad Jaber , Kamran Muhammad , Flechtmann Carlos Holger Wenzel
Published: November 2024

The present study aimed to revise the subgeneric divisions of the genus Bryobia based on persistent characteristics and to propose species groups in each subgenus to further ease the identification of species. As a result, only three subgenera, based on literature, are recognized, viz, subgenus Bryobia Koch (duplex setae present on leg tarsi III–IV), subgenus Allobia Livschits and Mitrofanov (duplex setae absent on leg tarsi III–IV), and subgenus Lyobia Livschits and Mitrofanov (duplex setae present only on leg tarsus III). The analysis based on morphological characters and available COI sequences on the GenBank database did not resolve the phylogenetic relationship of Bryobia species, and likewise, no support could be found for the proposed subgeneric divisions. The species in each subgenus were further categorized into species groups based on the position of the fourth pair of dorsocentral setae f1, viz, three species groups, praetiosa, osterloffi, and neoephedrae in subgenus Bryobia; three species groups, pritchardi, abbatielloi, and deserticola in subgenus Allobia; and three species groups, eurotiae, sarothamni, and rubrioculus in subgenus Lyobia. Furthermore, detailed notes are provided on eight Bryobia species which were described by Meyer, having morphological characteristics of both the tribes Bryobiini and Hystrichonychini. The generic status of two bryobine species, B. pseudorubrioculus Smiley and Baker and B. tuttlie Smiley and Baker, is also discussed and considered as species inquirendae.
Enhancing Real-Time Emotion Recognition in Classroom Environments Using Convolutional Neural Networks: A Step Towards Optical Neural Networks for Advanced Data Processing
Authors: Avital Nuphar , Egel Idan , Weinstock Ido , Malka Dror
Published: November 2024

In contemporary academic settings, end-of-semester student feedback on a lecturer’s teaching abilities often fails to provide a comprehensive, real-time evaluation of their proficiency, and becomes less relevant with each new cohort of students. To address these limitations, an innovative feedback method has been proposed, utilizing image processing algorithms to dynamically assess the emotional states of students during lectures by analyzing their facial expressions. This real-time approach enables lecturers to promptly adapt and enhance their teaching techniques. Recognizing and engaging with emotionally positive students has been shown to foster better learning outcomes, as their enthusiasm actively stimulates cognitive engagement and information analysis. The purpose of this work is to identify emotions based on facial expressions using a deep learning model based on a convolutional neural network (CNN), where facial recognition is performed using the Viola–Jones algorithm on a group of students in a learning environment. The algorithm encompasses four key steps: image acquisition, preprocessing, emotion detection, and emotion recognition. The technological advancement of this research lies in the proposal to implement photonic hardware and create an optical neural network which offers unparalleled speed and efficiency in data processing. This approach demonstrates significant advancements over traditional electronic systems in handling computational tasks. An experimental validation was conducted in a classroom with 45 students, demonstrating that the level of understanding in the class as predicted was 43–62.94%, and the proposed CNN algorithm (facial expressions detection) achieved an impressive 83% accuracy in understanding students’ emotional states. The correlation between the CNN deep learning model and the students’ feedback was 91.7%. This novel approach opens avenues for the real-time assessment of students’ engagement levels and the effectiveness of the learning environment, providing valuable insights for ongoing improvements in teaching practices.
Rapid Prediction and Parameter Evaluation of Process-Induced Deformation in L-Shape Structures Based on Feature Selection and Artificial Neural Networks
Authors: Liu Qingchuan , Wang Xiaodong , Guan Zhidong , Li Zengshan
Published: November 2024

The process-induced deformation (PID) during the manufacturing of thermosetting composite materials can significantly compromise manufacturing precision. This paper introduces an innovative method that combines a finite element analysis (FEA), feature classification algorithms, and an Artificial Neural Network (ANN) framework to rapidly predict the PID of a typical L-shaped structure. Initially, a comprehensive range of parameters that influence PID are compiled in this research, followed by the generation of a dataset through FEA considering viscoelastic constitutive models, validated by experimental results. Influential parameters are classified using Random Forest and LASSO regression methods, with each parameter rated according to its impact on PID, delineating their varying degrees of importance. Subsequently, through a hyperparameter analysis, an ANN framework is developed to rapidly predict the PID, while also refining the assessment of the parameters’ significance. This innovative approach achieves a computational time reduction of 98% with less than a 5% loss in accuracy, and highlights that under limited computational conditions, considering only a subset or all of the parameters—the peak temperature, corner angle, coefficient of chemical shrinkage, coefficient of thermal expansion, curing pressure, and E1—minimizes accuracy loss. The study demonstrates that machine learning algorithms can effectively address the challenge of predicting composite material PID, providing valuable insights for practical manufacturing applications.
Mechanical, Durability, and Microstructure Characterization of Pervious Concrete Incorporating Polypropylene Fibers and Fly Ash/Silica Fume
Authors: Bilal Hassan , Gao Xiaojian , Cavaleri Liborio , Khan Alamgir , Ren Miao
Published: November 2024

Pervious concrete, because of its high porosity, is a suitable material for reducing the effects of water precipitations and is primarily utilized in road pavements. In this study, the effects of binder-to-aggregate (B/A) ratios, as well as mineral admixtures with and without polypropylene fibers (PPFs) (0.2% by volume), including fly ash (FA) or silica fume (SF) (10% by substitution of cement), on the mechanical properties and durability of pervious concrete were experimentally observed. The experimental campaign included the following tests: permeability, porosity, compressive strength, splitting tensile strength, and flexural strength tests. The durability performance was evaluated by observing freeze–thaw cycles and abrasion resistance after 28 d curing. X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), thermal analysis (TGA-DTA), and scanning electron microscopy (SEM) combined with energy dispersive spectroscopy (EDS) were employed to investigate the phase composition and microstructure. The results revealed that, for an assigned B/A ratio identified as optimal, the incorporation of mineral admixtures and fibers mutually compensated for their respective negative effects, resulting in the effective enhancement of both mechanical/microstructural characteristics and durability properties. In general, pervious concrete developed with fly ash or silica fume achieved higher compressive strength (>35 MPA) and permeability of 4 mm/s, whereas the binary combination of fly ash or silica fume with 0.2% PPFs yielded a flexural strength greater than 6 MPA and a permeability of 6 mm/s. Silica fume-based pervious concrete exhibited excellent performance in terms of freeze–thaw (F-T) cycling and abrasion resistance, followed by fiber-reinforced pervious concrete, except fly ash-based pervious concrete. Microstructural analysis showed that the inclusion of fly ash or silica fume reduced the harmful capillary pores and refined the pore enlargement caused by PPFs in the cement interface matrix through micro-filling and a pozzolanic reaction, leading to improved mechanical and durability characteristics of pervious concrete.
A Real-Time End-to-End Framework with a Stacked Model Using Ultrasound Video for Cardiac Septal Defect Decision-Making
Authors: Nurmaini Siti , Nova Ria , Sapitri Ade , Rachmatullah Muhammad , Tutuko Bambang , Firdaus Firdaus , Darmawahyuni Annisa , Islami Anggun , Mandala Satria , Partan Radiyati , Arum Akhiar , Bastian Rio
Published: November 2024

Echocardiography is the gold standard for the comprehensive diagnosis of cardiac septal defects (CSDs). Currently, echocardiography diagnosis is primarily based on expert observation, which is laborious and time-consuming. With digitization, deep learning (DL) can be used to improve the efficiency of the diagnosis. This study presents a real-time end-to-end framework tailored for pediatric ultrasound video analysis for CSD decision-making. The framework employs an advanced real-time architecture based on You Only Look Once (Yolo) techniques for CSD decision-making with high accuracy. Leveraging the state of the art with the Yolov8l (large) architecture, the proposed model achieves a robust performance in real-time processes. It can be observed that the experiment yielded a mean average precision (mAP) exceeding 89%, indicating the framework’s effectiveness in accurately diagnosing CSDs from ultrasound (US) videos. The Yolov8l model exhibits precise performance in the real-time testing of pediatric patients from Mohammad Hoesin General Hospital in Palembang, Indonesia. Based on the results of the proposed model using 222 US videos, it exhibits 95.86% accuracy, 96.82% sensitivity, and 98.74% specificity. During real-time testing in the hospital, the model exhibits a 97.17% accuracy, 95.80% sensitivity, and 98.15% specificity; only 3 out of the 53 US videos in the real-time process were diagnosed incorrectly. This comprehensive approach holds promise for enhancing clinical decision-making and improving patient outcomes in pediatric cardiology.
Effects on the Potential for Seepage Failure Under a Geotextile Mattress with Floating Plate
Authors: Zhu Yehui , Wang Qiyun , Wu Guokai , Li Yanhong , Xie Liquan
Published: November 2024

The geotextile mattress with floating plate (GMFP) is an innovative scour protection device. This study examines the potential for seepage failure under the GMFP, which has been previously documented. The effects of flow velocity and GMFP configuration on the potential for seepage failure were analyzed. The variation pattern of the sloping angle was first revealed in flume tests, and the bed pressure near the GMFP with various configurations in steady currents was thereafter simulated. The average hydraulic gradient across the GMFP was observed to increase with an increase in the Froude number before reaching a plateau, which can be explained by the coupled effects of the rising Froude number and the decreasing sloping angle. The average hydraulic gradient was approximately inversely proportional to the mattress length upstream of the floating plate. With the decreasing mattress length downstream of the floating plate, the average hydraulic gradient initially rose and then declined when the downstream mattress was relatively short. This trend can be associated with the amplification of the vortices in the top vortex zone downstream of the GMFP with the shortened downstream mattress, which pushed the bottom vortex to the leeside. The shortened downstream mattress could increase the risk of overturning and slipping of the GMFP, although the average hydraulic gradient decreased.
A Decision Model for Ship Overtaking in Straight Waterway Channels
Authors: Liu Nian , Shen Yong , Lin Fei , Liu Yihua
Published: November 2024

Overtaking situations are commonly encountered in maritime navigation, and the overtaking process involves various risk factors that significantly contribute to collision incidents. It is crucial to conduct research on the maneuvering behaviors and decision-making processes associated with ship overtaking. This paper proposes a method based on the analysis of ship maneuvering performance to investigate overtaking behaviors in navigational channels. A relative motion model is established for both the overtaking and the overtaken vessels, and the inter-vessel distance is calculated, taking into account the psychological perceptions of the ship’s driver. A decision-making model for ship overtaking is presented to provide a safety protocol for overtaking maneuvers. Applying this method to overtaking data from the South Channel shows that it effectively characterizes both the permissible overtaking space and the driver’s overtaking desire. Additionally, it enables the prediction of optimal overtaking timing and strategies based on short-term trajectory forecasts. Thus, this method not only offers a safe overtaking plan for vessels but also provides auxiliary information for decision making in intelligent ship navigation.
Acoustic Imaging Learning-Based Approaches for Marine Litter Detection and Classification
Authors: Guedes Pedro Alves , Silva Hugo Miguel , Wang Sen , Martins Alfredo , Almeida José , Silva Eduardo
Published: November 2024

This paper introduces an advanced acoustic imaging system leveraging multibeam water column data at various frequencies to detect and classify marine litter. This study encompasses (i) the acquisition of test tank data for diverse types of marine litter at multiple acoustic frequencies; (ii) the creation of a comprehensive acoustic image dataset with meticulous labelling and formatting; (iii) the implementation of sophisticated classification algorithms, namely support vector machine (SVM) and convolutional neural network (CNN), alongside cutting-edge detection algorithms based on transfer learning, including single-shot multibox detector (SSD) and You Only Look once (YOLO), specifically YOLOv8. The findings reveal discrimination between different classes of marine litter across the implemented algorithms for both detection and classification. Furthermore, cross-frequency studies were conducted to assess model generalisation, evaluating the performance of models trained on one acoustic frequency when tested with acoustic images based on different frequencies. This approach underscores the potential of multibeam data in the detection and classification of marine litter in the water column, paving the way for developing novel research methods in real-life environments.
Determination of Biological Activity and Biochemical Content of Ethanol Extract from Fruiting Body of Tricholoma bufonium (Pers.) Gillet
Authors: Benek Atakan , Turu Dilay , Canli Kerem
Published: November 2024

The current study investigates the biochemical composition and biological activities of ethanol extract from the fruit body of Tricholoma bufonium, marking the first detailed examination of this species. The primary goal was to assess the antimicrobial, anti-biofilm, and antioxidant properties of ethanol extract from the fruit body of T. bufonium against a range of bacterial strains. Conventional microbiological and biochemical techniques were employed to assess the antimicrobial efficacy of the extract and to determine its minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) values. Furthermore, a GC-MS analysis identified bioactive compounds, such as palmitic acid and oleic acid, which are likely contributors to the observed antimicrobial activity. The anti-biofilm activity was tested using glucose monohydrate-modified environments for biofilm formation, while the antioxidant potential was measured using the DPPH radical scavenging assay, CUPRAC (cupric ion reducing antioxidant capacity) assay, and FRAP (ferric ion reducing antioxidant power) assay. The ethanol extract exhibited potent antimicrobial activity, particularly against Enterococcus faecium, Bacillus subtilis, and Staphylococcus aureus MRSA, with MIC values as low as 0.0338 mg/mL for several pathogens. Additionally, the extract exhibited significant anti-biofilm activity against Bacillus cereus and antioxidant activity with an EC50 value of 11.745 mg/mL. These results suggest that ethanol extract from the fruit body of T. bufonium may be a potent candidate for developing novel antimicrobial agents, particularly against resistant strains such as MRSA, while also providing antioxidant benefits.
Biofilm Formation in Clinical Isolates of Fusarium
Authors: Zhang Ray , Wiederhold Nathan , Calderone Richard , Li Dongmei
Published: November 2024

Many microbial pathogens form biofilms, assemblages of polymeric compounds that play a crucial role in establishing infections. The biofilms of Fusarium species also contribute to high antifungal resistance. Using our collection of 29 clinical Fusarium isolates, we focused on characterizing differences in thermotolerance, anaerobic growth, and biofilm formation across four Fusarium species complexes commonly found in clinical settings. We investigated the role of carbon sources, temperature, and fungal morphology on biofilm development. Using fluorescence microscopy, we followed the stages of biofilm formation. Biofilms were screened for sensitivity/resistance to the antifungals voriconazole (VOR), amphotericin B (AmB), and 5-fluorocytosine (5-FC). Our findings revealed generally poor thermotolerance and growth under anaerobic conditions across all Fusarium species. VOR was more effective than AmB in controlling biofilm formation, but the combination of VOR, AmB, and 5-FC significantly reduced biofilm formation across all species. Additionally, Fusarium biofilm formation varied under non-glucose carbon sources, highlighting the species’ adaptability to different nutrient environments. Notably, early stage biofilms were primarily composed of lipids, while polysaccharides became dominant in late-stage biofilms, suggesting a dynamic shift in biofilm composition over time.
Minimally Invasive Approaches to Spinal Cerebrospinal Fluid Leak Repair: Current Strategies and a Novel Technique
Authors: Khalafallah Adham M. , Sanghera Bhavjeet S. , Kader Michael , Boddu James V. , Urakov Timur
Published: November 2024

Spinal cerebrospinal fluid (CSF) leaks can be caused by tears in the dura and are challenging to treat. Traditional methods of treating spinal CSF leakage include nonsurgical management, epidural blood patches (EBP), and direct surgical repair. Minimally invasive surgery (MIS) is rapidly progressing within neurosurgery due to its advantages for patient safety and comfort. Existing MIS techniques to spine surgery utilize a rigid endoscope, which has limitations when reaching smaller areas requiring greater degrees of visualization. The simultaneous use of a flexible endoscope and wearable heads-up display (wHUD) improves access and visualization in these small areas while allowing the surgeon to maintain optimal ergonomics. In this article, we review minimally invasive approaches to spine surgery and the management of spinal CSF leaks. We also demonstrate a novel minimally invasive technique utilizing flexible endoscopy and a wHUD to treat a case of recurrent CSF leak. We describe the successful utilization of this technology and provide the groundwork for future practitioners to incorporate this approach into their practice.
Carotid Artery Geometry Modifications and Clinical Implications after Carotid Artery Stenting
Authors: Pasqui Edoardo , Gargiulo Bruno , Pasquetti Leonardo , Lazzeri Elisa , Galzerano Giuseppe , de Donato Gianmarco
Published: November 2024

Background: Carotid artery stenting (CAS) could lead to a modification of the carotid bifurcation geometry with possible clinical implications. This study aimed to clarify the geometrical impact of three carotid stents with different designs on the carotid bifurcation and its clinical consequences. Methods: This was a retrospective single-center study. We included all patients who underwent CAS in a 3-year period. Anatomical changes of the carotid bifurcation were evaluated by reviewing angiographic images. The population was divided into three groups based on the stent implanted: Group 1 (Carotid Wallstent), Group 2 (Roadsaver), and Group 3 (C-Guard). Results: A total of 226 patients were included. The mean age was 77.0 ± 7.4 years and 72.5% (164/226) were male. Three different stents were implanted into three groups: Group 1 (n = 131/226, 58%), Group 2 (n = 57/226, 25.2%), and Group 3 (n = 38/226, 16.8%). The mean pre-stent implantation CCA-ICA angle of the entire population was 155 ± 14.9°, and the post-CAS angle was 167.7 ± 8.7° (p = 0.0001). In every subgroup, the difference was statistically different, with the biggest difference registered in Group 2 (−16.1 ± 13.2°). Regarding stent oversizing, there was a significant relationship between CCA oversizing and CCA-ICA angle modification (p = 0.006). During follow-up, a total of 14 (6.2%) restenoses were registered. The mean CCA-ICA angle modification in the restenosis group was −9.5 ± 14.4° vs. −12.8 ± 11.9° in the no-restenosis group with no significant statistical differences were outlined (p = 0.3). Conclusions: Compared to the Carotid Wallstent and C-Guard, the Roadsaver stent appears to have a lower adaptability to the carotid vascular territory, resulting in a higher CCA-ICA angle modification after implantation, with no impact on the stent restenosis rate.
Key Audit Matters Between Auditors and Auditees in Middle East and North Africa
Authors: Mahd Osama , Idris Mohammed
Published: November 2024

This study investigates the impact of auditor- and auditee-specific features on key audit matter disclosures in auditors’ reports. It focuses on client factors, including debt, profitability, financial distress, and audit factors, including auditor size, rotation, and opinion. A direct extraction of audit reports from different markets in Middle East and North Africa covering three years from 2020 to 2022 was carried out. A content analysis of the annual reports regarding key audit matters, client-specific characteristics, and auditor characteristics was performed in this research. The results of this study show that key audit matters are not correlated to profitability and financial distress, while the debt ratio is significantly related to the number of key audit matters. The results also indicate that audit rotation and opinion have a significant explanatory effect on key audit matters as the coefficients of both independent variables are positive and statistically significant while the size of the audit firm is not related to the number of key audit matters.
Housekeeping System for Suborbital Vehicles: VIRIATO Mock-Up Vehicle Integration and Testing
Authors: Rodrigues Geraldo , Arribas Beltran , Melicio Rui , Gordo Paulo , Valério Duarte , Casaleiro João , Silva André
Published: November 2024

The work presented in this paper regards the improvement of a housekeeping system for data acquisition of a suborbital vehicle (VIRIATO rocket or launcher). The specifications regarding the vehicle are presented and hardware is chosen accordingly, considering commercial off-the-shelf components. Mechanical and thermal simulations are performed regarding the designed system and a physical prototype is manufactured, assembled and programmed. Functional and field test results resorting to unmanned aerial vehicles, as well as the system’s integration within VIRIATO project’s mock-up vehicle, are presented. These tests demonstrate the viability of this system as an independent data acquisition system, and simulation results show that commercial off-the-shelf components have the capability of surviving expected launch environments.
Optimizing Railway Tribology: A Systematic Review and Predictive Modeling of Twin-Disc Testing Parameters
Authors: Zani Nicola , Petrogalli Candida , Battini Davide
Published: November 2024

Twin-disc testing is crucial for understanding wheel–rail interactions in railway systems, but the vast array of testing parameters and conditions makes data interpretation challenging. This review presents a comprehensive analysis of the twin-disc literature experimental data, focusing on how various parameters influence friction and wear characteristics under stationary contaminant conditions. We systematically collected and analyzed data from numerous studies, considering factors such as contact pressure, speed, material hardness, sliding speeds, adhesion, and a range of contaminants. This research showed inconsistent data reporting across different studies and statistical analyses revealed significant correlations between testing parameters and wear rates. For sand-contaminated tests, a correlation between particle size and flow rate was also highlighted. Based on these findings, we developed a simple predictive model for forecasting wear rates under varying conditions. This model achieved an adjusted R2 of 0.650, demonstrating its potential for optimizing railway component design and maintenance strategies. Our study provides a valuable resource for researchers and practitioners in railway engineering, offering insights into the complex tribological interactions in wheel–rail systems and a tool for predicting wear behavior.
Ultra-Short Pulses Laser Heating of Dielectrics: A Semi-Classical Analytical Model
Authors: Badea Liviu , Duta Liviu , Mihailescu Cristian N. , Oane Mihai , Trefilov Alexandra M. I. , Popescu Andrei , Hapenciuc Claudiu , Mahmood Muhammad Arif , Ticos Dorina , Mihailescu Natalia , Ristoscu Carmen , Anghel Sinziana A. , Mihailescu Ion N.
Published: November 2024

Femtosecond laser pulses are currently regarded as an emerging and promising tool for processing wide bandgap dielectric materials across a variety of high-end applications, although the associated physical phenomena are not yet fully understood. To address these challenges, we propose an original, fully analytical model combined with Two Temperatures Model (TTM) formalism. The model is applied to describe the interaction of fs laser pulses with a typical dielectric target (e.g., Sapphire). It describes the heating of dielectrics, such as Sapphire, under irradiation by fs laser pulses in the range of (1012–1014) W/cm2. The proposed formalism was implemented to calculate the free electron density, while numerical simulations of temperature field evolution within the dielectrics were conducted using the TTM. Mathematical models have rarely been used to solve the TTM in the context of laser–dielectric interactions. Unlike the TTM applied to metals, which requires solving two heat equations, for dielectrics the free electron density must first be determined. We propose an analytical model to solve the TTM equations using this parameter. A new simulation model was developed, combining the equations for non-equilibrium electron density determination with the TTM equations. Our analyses revealed the non-linear nature of the physical phenomena involved and the inapplicability of the Beer–Lambert law for fs laser pulse interactions with dielectric targets at incident laser fluences ranging from 6 to 20 J/cm2.
Coupling CALPHAD Method and Entropy-Driven Design for the Development of an Advanced Lightweight High-Temperature Al-Ti-Ta Alloy
Authors: Mundhra Gourav , Yeh Jien-Wei , Murty B. S.
Published: November 2024

In this study, a new lightweight Al-Ti-Ta alloy was developed through a synergistic approach, combining CALPHAD methodology and entropy-driven design. Following compositional optimization, the Al87.5Ti6.25Ta6.25 (at.%) alloy was fabricated and isothermally heat-treated at 475 °C for 24 h to attain equilibrium. X-ray diffraction (XRD), scanning electron microscopy (SEM), and differential scanning calorimetry (DSC) analyses revealed a dual-phase microstructure comprising a 50 vol.% FCC matrix enriched in Al and 50 vol.% Al3(Ti,Ta)-type intermetallic phase (IP). Notably, the FCC phase exhibited a high-melting transition temperature of 660 °C, surpassing conventional Al-Si cast alloys. Phase-specific nanomechanical properties were evaluated using Nanoindentation. Microindentation tests demonstrated exceptional microhardness of approximately 3300 MPa. These results indicate the alloy’s superior hardness compared to conventional alloys such as Al-Si (A390), 7075 Al alloy, and CP-Ti, even exceeding Ti-64 alloy at a 15% lower density. The alloy’s stability under prolonged heat treatment at 475 °C, reflected by stable phases, microstructure, and mechanical properties, highlights its enhanced thermal stability, which can be attributed to entropy-driven phase stabilization. This study underscores the effectiveness of integrating entropy-driven design strategy with CALPHAD predictions for the accelerated development of advanced Al-based alloys.
Physical–Mechanical Properties and Mineral Deposition of a Pit-and-Fissure Sealant Containing Niobium–Fluoride Nanoparticles—An In Vitro Study
Authors: Obeid Alyssa Teixeira , Nascimento Tatiana Rita de Lima , Ramos Carlos Alberto Spironelli , Mondelli Rafael Francisco Lia , Rastelli Alessandra Nara de Souza , Alhotan Abdulaziz , Velo Marilia Mattar de Amoêdo Campos , Bombonatti Juliana Fraga Soares
Published: November 2024

This study investigated the combined effects of adding niobium–fluoride (NbF5) nanoparticles to a pit-and-fissure sealant. One resin sealant was reinforced with varying amounts of nanoparticles (0.3, 0.6, and 0.9 wt%). The surface hardness (SH), energy-dispersive X-ray spectroscopy (EDX), surface roughness (Ra), color change (ΔE), and mineral deposition were assessed. Bovine enamel blocks were subjected to demineralization and pH-cycling for SH. The elemental composition and Ca/P ratio were evaluated using EDX, while the mineral deposition was measured using Fourier transform infrared spectroscopy (FTIR). Data were analyzed using ANOVA and Tukey’s test for the SH and EDX, ΔE, and Kruskal–Wallis for the Ra. The NbF5 modification increased the SH, with the 0.9 wt% sealant exhibiting higher SH values, and the 0.3 wt% one exhibiting significant differences compared to the control and the 0.9 wt% (p = 0.00) samples, even after pH-cycling. For the EDX analysis, the 0.3 and 0.6 wt% samples exhibited higher Ca/P ratios, with the 0.3% one showing evidence of P-O crystal formation. There was no significant difference in the Ra (p = 0.458), and the 0.6 and 0.9 wt% ones showed lower ΔE values compared to the control. The 0.3 wt% NbF5 demonstrated improved overall properties, making these results particularly promising for preventing tooth decay, reducing demineralization through increased ions release and promoting remineralization in posterior teeth.
Core–Sheath Fibers via Single-Nozzle Spinneret Electrospinning of Emulsions and Homogeneous Blend Solutions
Authors: Kyuchyuk Selin , Paneva Dilyana , Manolova Nevena , Rashkov Iliya
Published: November 2024

The preparation of core–sheath fibers by electrospinning is a topic of significant interest for producing composite fibers with distinct core and sheath functionalities. Moreover, in core–sheath fibers, low-molecular-weight substances or nanosized inorganic additives can be deposited in a targeted manner within the core or the sheath. Commonly, for obtaining a core–sheath structure, coaxial electrospinning is used. It requires a coaxial spinneret and suitable immiscible solvents for the inner and outer solutions. The single-nozzle spinneret electrospinning of emulsions can address these issues, but use of a stabilizing agent is needed. A third approach—preparation of core–sheath fibers by single-nozzle spinneret electrospinning of homogeneous blend solutions of two polymers or of a polymer/low-molecular-weight substance—has been much less studied. It circumvents the difficulties associated with the coaxial and the emulsion electrospinning and is thoroughly discussed in this review. The formation of core–sheath fibers in this case is attributed to phase-separation-driven self-organization during the electrospinning process. Some possibilities for obtaining core–double sheath fibers using the same method are also indicated. The gained knowledge on potential applications of core–sheath fibers prepared by single-nozzle spinneret electrospinning of emulsions and homogeneous blend solutions is also discussed.
In Vivo and In Vitro Response to a Regenerative Dental Scaffold
Authors: Gould Maree L. , Deng Xiaoxuan , Lyons Karl , Ali Azam
Published: November 2024

As dental pulp contains the stem cells necessary for regeneration, the tooth should hold the intrinsic capacity for self-repair. A triphasic hybrid dental biocomposite (3HB) composed of biocompatible biopolymers to provide strength, antibacterial properties and protein-based cell support could provide a conducive microenvironment for the regeneration of dental structures. 3HB was incorporated into Mineral Trioxide Aggregate (ProRoot MTA) to construct a malleable injectable implant. Human tooth pulp cells (hDPCs) significantly increased proliferation in the presence of 3HB+MTA compared to 3HB or MTA alone. Cell viability decreased with MTA alone but increased with 3HB and 3HB+MTA. 3HB+MTA was implanted into the residual tooth of drilled Wistar rat M2 molars for up to 45 days. Stereological analysis from micro-CT images showed the volume of the tooth remaining. Histologically, regenerative pulpal architecture was seen invading 3HB. A continuous odontoblastic profile lined a deposit of dentin-like material suggesting reparative dentinogenesis. Overall, no infection or encapsulation was seen. Immunohistochemically, odontoblasts were seen along the margins of the wounded tooth undergoing repair. Mesenchymal cells (MSCs) were seen at the base of the drilled tooth and by 21 days had translocated into the implant itself. Cells stimulating remineralization were highly expressed in the tooth undergoing repair. CD146-positive MSCs were seen in the center of the implant, possibly stimulating remineralization. In conclusion, behavior of 3HB+ in vitro and in vivo provided a promising start as 3HB+MTA may serve as a viable regenerative scaffold for pulp regeneration; however, this should be further studied before clinical use can be considered.
Fracture Toughness of Ordinary Plain Concrete Under Three-Point Bending Based on Double-K and Boundary Effect Fracture Models
Authors: Chen Huating , Zhuo Yifan , Li Dewang , Huang Yan
Published: November 2024

Fracture tests are a necessary means to obtain the fracture properties of concrete, which are crucial material parameters for the fracture analysis of concrete structures. This study aims to fill the gap of insufficient test results on the fracture toughness of widely used ordinary C40~C60 concrete. A three-point bending fracture test was conducted on 28 plain concrete and 6 reinforced concrete single-edge notched beam specimens with various depths of prefabricated notches. The results are reported, including the failure pattern, crack initiation load, peak load, and complete load versus crack mouth opening displacement curves. The cracking load showed significant variation due to differences in notch prefabrication and aggregate distribution, while the peak load decreased nonlinearly with an increase in the notch-to-height ratio. The reinforced concrete beams showed a significantly higher peak load than the plain concrete beams, attributed to the restraint of steel reinforcement, but the measured cracking load was comparable. A compliance versus notch-to-height ratio curve was derived for future applications, such as estimating crack length in crack growth rate tests. Finally, fracture toughness was determined based on the double-K fracture model and the boundary effect model. The average fracture toughness value for C50 concrete from this study was 2.0 MPa·m, slightly smaller than that of lower-strength concrete, indicating the strength and ductility dependency of concrete fracture toughness. The fracture toughness calculated from the two models is consistent, and both methods employ a closed-form solution and are practical to use. The derived fracture toughness was insensitive to the discrete parameters in the boundary effect model. The insights gained from this study significantly contribute to our understanding of the fracture toughness properties of ordinary structural concrete, highlighting its potential to shape future studies and applications in the field.
Piecewise Time Polynomials-Based Control Methods for Obstacle Avoidance and Precision Positioning of Tower Crane Systems with Varying Cable Lengths
Authors: Liu Zhiheng , Ma Xianghua
Published: November 2024

During the hoisting and lowering operations of a tower crane, dynamic variations in cable lengths significantly influence the oscillation frequency and amplitude of the load. These variations complicate the oscillation characteristics, heightening the challenge of balancing obstacle avoidance with precise positioning. To tackle this issue, we propose a trajectory planning and tracking control method that integrates hoisting control to reduce the impact of varying cable lengths on load swinging and achieve accurate positioning during obstacle navigation. A novel definition of swing angle is introduced to model the crane’s rigid and swinging components separately, enhancing model accuracy while simplifying complexity. A piecewise polynomial constructs the load trajectory in a low-dimensional flat space, which is then mapped to a high-dimensional generalized state space through a homeomorphic transformation, ensuring trajectory smoothness and traceability. A fractional-order sliding mode controller is employed to facilitate rapid and precise tracking of the actuated degrees of freedom, suppressing load oscillation while maintaining positioning accuracy. Experimental validation on a tower crane platform shows that the proposed strategy enables smooth obstacle avoidance and precise target point reaching, even with varying cable lengths.
Kernel Principal Component Analysis for Allen–Cahn Equations
Authors: Çakır Yusuf , Uzunca Murat
Published: November 2024

Different researchers have analyzed effective computational methods that maintain the precision of Allen–Cahn (AC) equations and their constant security. This article presents a method known as the reduced-order model technique by utilizing kernel principle component analysis (KPCA), a nonlinear variation of traditional principal component analysis (PCA). KPCA is utilized on the data matrix created using discrete solution vectors of the AC equation. In order to achieve discrete solutions, small variations are applied for dividing up extraterrestrial elements, while Kahan’s method is used for temporal calculations. Handling the process of backmapping from small-scale space involves utilizing a non-iterative formula rooted in the concept of the multidimensional scaling (MDS) method. Using KPCA, we show that simplified sorting methods preserve the dissipation of the energy structure. The effectiveness of simplified solutions from linear PCA and KPCA, the retention of invariants, and computational speeds are shown through one-, two-, and three-dimensional AC equations.
Truncation Error of the Network Simulation Method: Chaotic Dynamical Systems in Mechanical Engineering
Authors: Solano Joaquín , Mulas-Pérez Javier , Balibrea Francisco , Moreno-Nicolás José Andrés
Published: November 2024

This article focuses on the study of local truncation errors (LTEs) in the Network Simulation Method (NSM), specifically when using the trapezoidal method and Gear’s methods. The NSM, which represents differential equations through electrical circuit elements, offers advantages in solving nonlinear dynamic systems such as the van der Pol equation. The analysis compares the performance of these numerical methods in terms of their stability and error minimization, with particular emphasis on LTE. By leveraging circuit-based techniques prior to numerical application, the NSM improves convergence. This study evaluates the impact of step size on LTE and highlights the trade-offs between accuracy and computational cost when using the trapezoidal and Gear methods.