bluuebunny/crossref_metadata_2025 huggingface dataset:
Road Surface Texture Evaluation and Relation to Low-Speed Skid Resistance for Different Types of Mixtures
Authors: Ren Wanyan , Li Jun , Zhang Yi , Wang Xinya , Shao Ruixue
Published: October 2024

Pavement skid resistance is significant for driving safety. British Pendulum Number (BPN) is commonly used as a low-speed skid resistance indicator, whereas sometimes it is impractical for data collection on roads in service. Since skid resistance is greatly affected by pavement surface texture, this research aims to evaluate pavement surface texture comprehensively and estimate the low-speed friction BPN from road surface texture on macro- and micro- scale. Asphalt Concrete (AC) and Stone Mastic Asphalt (SMA) were included. Road surface texture was evaluated from four aspects, texture depth, amplitude-related Root Means Square (RMS), elevation variances corresponding to different wavebands and texture spectral analysis. Texture depth indicators include Mean Texture Depth (MTD) and Mean Profile Depth (MPD). Elevation variances with three wavebands, from 5 mm to 50 mm, from 0.5 mm to 5 mm and from 0.024 mm to 0.5 mm respectively, were obtained. The results show that MPD is well correlated with MTD. Elevation variances with different wavebands demonstrates that the elevation variance of macro-texture with long wavelengths from 5 mm to 50 mm dominates the total variance. Spectral analysis shows that texture level is larger when the wavelength is beyond 4 mm, which is consistent with elevation variances. A linear regression between BPN and single texture index, as well as multiple linear regression analysis were conducted. The former regression result indicates that it is not feasible to estimate BPN using single index due to low correlation coefficient R2. The latter shows that the BPN can be estimated from texture levels corresponding to 64 mm and 2 mm, and the micro-texture. The R2 can be up to 0.684. This research will contribute to fast acquisition of BPN from pavement surface texture, thus improving skid resistance.
A Spray-Deposited Modified Silica Film on Selective Coatings for Low-Cost Solar Collectors
Authors: Lizama-Tzec Francisco Ivan , Cetina-Dorantes Marco de Jesús , Herrera-Zamora Dallely Melissa , Alvarado-Gil Juan José , Rodríguez-Gattorno Geonel , Estrella-Gutiérrez Manuel Alejandro , García-Valladares Octavio , Vales-Pinzón Caridad , Oskam Gerko
Published: October 2024

Solar collectors represent an attractive green technology for water heating, where sunlight is efficiently absorbed by a selective coating and the generated heat is transferred to water. In this work, the improvement and scale-up of an electrodeposited black nickel selective coating with a modified silica (MS) film deposited by spray pyrolysis are reported. The MS material was prepared by the sol–gel method using tetraethyl orthosilicate with the addition of n-propyl triethoxysilane to obtain a porous film with an adequate refractive index and enhanced flexibility. The reflectance of electrodeposited selective coatings was characterized with and without the MS film and compared to a commercially available coating of black paint. The MS film increased the solar absorptance from 89% to 93% while maintaining a much lower thermal emittance than the painted coating. The reflectance of the MS film remained unchanged after prolonged thermal treatment at 200 °C (200 h). The fabrication process was scaled up to 193 cm × 12 cm copper fins, which were incorporated in commercial-size flat-plate solar collectors. Three complete collectors of an area of 1.7 m2 were fabricated and their performance was evaluated under outdoor conditions. The results show that the electrodeposited selective coating with the MS film outperformed both the commercial black paint system and the system without the modified silica film.
Surface Mechanical Property Prediction and Process Optimization of 18CrNiMo7-6 Carburized Steel Stator Guide Based on Radial Basis Function Neural Network and NSGA-II Algorithm
Authors: Li Chunjin , Tang Yongjie , Chen Jianzhi , Xia Zhengwen
Published: October 2024

The carburizing process is a key technology that affects the mechanical properties of the surface of the hydraulic motor stator guide rail, and the related process parameters have an important influence on surface hardness, the thickness of the carburized layer, and the deformation of the guide rail. However, at present, the relationship between the carburizing process parameters and the surface mechanical properties of the target is not clear. This paper proposes a “hardness prediction and process parameter optimization” method. Firstly, a finite element model is established, with carburizing time, temperature, and carbon potential as the three input factors; the optimal Latin hypercubic experimental design and sensitivity analysis are applied. Secondly, surface hardness, carburized layer thickness, and deformation are taken as the output values, and an RBF neural network is used to construct the prediction model. The results show that the RBF neural network can be accurately used for the prediction of surface hardness, the thickness of the carburized layer, and deformation, and for the optimization of process parameters. The optimized parameters of surface hardness and the thickness of the carburized layer were increased by 4.2% and 5.1%, respectively, and the deformation amount was reduced to 0.31 mm, achieving the goal of optimal design.
Hydroponic Lettuce Cultivation with Organic Liquid Fertilizer: Examining Bacterial Inhibition and Phosphate Solubilization
Authors: Endoh Tomoka , Takagaki Michiko , Suwitchayanon Prapaipit , Chanseetis Charturong , Lu Na
Published: October 2024

This study explores organic hydroponic cultivation as a sustainable alternative to chemical fertilizers amid global supply challenges. With rising costs and the depletion of conventional nitrogen sources, organic liquid fertilizers are gaining attention for their microbial enrichment processes (MEP) that convert organic matter into plant-accessible nutrients. This experiment focuses on lettuce cultivation using two organic liquid fertilizers, Power Fish and POF vol. 2, in controlled environments. The results show that there are significant differences in plant growth parameters such as leaf number, fresh weight, chlorophyll content, and root length across different fertilizer treatments. Key findings include that effective management practices, including pH control and regular nutrient application, are crucial for maintaining microbial activity and optimizing nutrient uptake efficiency. Additionally, Bacillus sp. and Xanthomonas sp. were isolated from these fertilizers and dual-cultured with rot fungi, Pythium sp. and Fusarium sp. This dual cultivation demonstrated inhibitory activity against these pathogens, showcasing the potential of these microorganisms in promoting biofilm-mediated disease resistance in organic hydroponic systems. The study also emphasizes the phosphate solubilization capabilities of isolated bacteria, essential for sustainable nutrient cycling. Overall, organic hydroponic systems present a promising strategy for sustainable agriculture, reducing dependency on chemical inputs while enhancing crop productivity and resilience to environmental stressors.
Post-Quantum Secure ID-Based (Threshold) Linkable Dual-Ring Signature and Its Application in Blockchain Transactions
Authors: Gao Wen , Yao Haoyuan , Qin Baodong , Dong Xiaoli , Zhao Zhen , Zeng Jiayu
Published: October 2024

Ring signatures are widely used in e-voting, anonymous whistle-blowing systems, and blockchain transactions. However, due to the anonymity of ring signatures, a signer can sign the same message multiple times, potentially leading to repeated voting or double spending in blockchain transactions. To address these issues in blockchain transactions, this work constructs an identity-based linkable ring signature scheme based on the hardness of the lattice-based Module Small Integer Solution (M-SIS) assumption, which is hard even for quantum attackers. The proposed scheme is proven to be anonymous, unforgeable, linkable, and nonslanderable in the random oracle model. Compared to existing identity-based linkable ring signature (IBLRS) schemes of linear size, our signature size is relatively smaller, and this advantage is more pronounced when the number of ring members is small. We provide approximate signature size data for ring members ranging from 2 to 2048. When the number of ring members is 16 (or 512. resp.), the signature size of our scheme is 11.40 KB (or 24.68 KB, respectively). Finally, a threshold extension is given as an additional scheme with specifications and security analysis.
Design and Performance Evaluation of an Authentic End-to-End Communication Model on Large-Scale Hybrid IPv4-IPv6 Virtual Networks to Detect MITM Attacks
Authors: Ashraf Zeeshan , Sohail Adnan , Iqbal Muddesar
Published: October 2024

After the end of IPv4 addresses, the Internet is moving towards IPv6 address architecture quickly with the support of virtualization techniques worldwide. IPv4 and IPv6 protocols will co-exist long during the changeover process. Some attacks, such as MITM attacks, do not discriminate by appearance and affect IPv4 and IPv6 address architectures. In an MITM attack, the attacker secretly captures the data, masquerades as the original sender, and sends it toward the receiver. The receiver replies to the attacker because the receiver does not authenticate the source. Therefore, the authentication between two parties is compromised due to an MITM attack. The existing authentication schemes adopt complicated mathematical procedures. Therefore, the existing schemes increase computation and communication costs. This paper proposes a lightweight and authentic end-to-end communication model to detect MITM attacks using a pre-shared symmetric key. In addition, we implement and analyze the performance of our proposed security model on Linux-based virtual machines connected to large-scale hybrid IPv4-IPv6 virtual networks. Moreover, security analyses prove the effectiveness of our proposed model. Finally, we compare the performance of our proposed security model with existing models in terms of computation cost and communication overhead.
Enhanced Performance of Fluidic Phononic Crystal Sensors Using Different Quasi-Periodic Crystals
Authors: Sayed Ahmed G. , Hajjiah Ali , Tlija Mehdi , Bellucci Stefano , Abukhadra Mostafa R. , Elsayed Hussein A. , Mehaney Ahmed
Published: October 2024

In this paper, we introduce a comprehensive theoretical study to obtain an optimal highly sensitive fluidic sensor based on the one-dimensional phononic crystal (PnC). The mainstay of this study strongly depends on the high impedance mismatching due to the irregularity of the considered quasi-periodic structure, which in turn can provide better performance compared to the periodic PnC designs. In this regard, we performed the detection and monitoring of the different concentrations of lead nitrate (Pb(NO3)2) and identified it as being a dangerous aqueous solution. Here, a defect layer was introduced through the designed structure to be filled with the Pb(NO3)2 solution. Therefore, a resonant mode was formed within the transmittance spectrum of the considered structure, which in turn shifted due to the changes in the concentration of the detected analyte. The numerical findings demonstrate the role of the different sequences such as Fibonacci, Octonacci, Thue–Morse, and double period on the performance of the designed PhC detector. Meanwhile, the findings of this study show that the double-period quasi-periodic sequence provides the best performance with a sensitivity of 502.6 Hz/ppm, a damping rate of 5.9×10−5, a maximum quality factor of 8463.5, and a detection limit of 2.45.
Optimization of Magnetic Field-Assisted Laser Cladding Based on Hierarchical Analysis and Gray Correlation Method
Authors: Jiang Long , Qi Kang , Zhang Haitao , Yu Youliang , Sun Qinpeng
Published: October 2024

Process parameters directly affect the quality of laser cladding. In this study, magnetic field-assisted laser cladding experiments were carried out on the surface of 300 M ultra-high-strength steel by setting laser energy density, magnetic field strength, and frequency as processing parameters. The optimization of laser cladding process parameters was investigated based on evaluating the quality of the laser cladding layer through hierarchical analysis and gray correlation analysis. Based on orthogonal test data, the correlation coefficients of the process parameters with the single objective function and the correlation degree of the multi-objective function were calculated by using the gray theory. Then the comprehensive objective optimization was carried out according to the gray correlation degree. The optimization problem with multiple process objectives was transformed into a single gray correlation degree optimization method to realize the optimization of process objectives and obtain the optimal combination of process parameters. The validation experiments indicate that the quality of the laser cladding layer can be greatly improved by employing optimal process parameters. The optimized laser cladding layer shows a reduced microstructure size and enhanced wear resistance, indicating the effectiveness of the optimization approach.
Synthesis and Characterization of TiO2 Nanotubes for High-Performance Gas Sensor Applications
Authors: Bouktif Belgacem , Rashid Marzaini , Hajjaji Anouar , Choubani Karim , Alrasheedi Nashmi H. , Louhichi Borhen , Dimassi Wissem , Ben Rabha Mohamed
Published: October 2024

In this study, we investigated the fabrication, properties, and sensing applications of TiO2 nanotubes. A pure titanium metal sheet was used to demonstrate how titanium dioxide nanotubes can be used for gas-sensing applications through the electrochemical anodization method. Subsequently, X-ray diffraction indicated the crystallization of the titanium dioxide layer. Scanning electron microscopy and transmission electron microscopy then revealed the average diameter of the TiO2 nanotubes to be approximately 100 nm, with tube lengths ranging between 3 and 9 µm and the thickness of the nanotube walls being about 25 nm. This type of TiO2 nanotube was found to be suitable for NO2 gas sensor applications. With an oxidation time of 15 min, its detection of NO2 gas showed a good result at 250 °C, especially when exposed to a NO2 gas flow of 100 ppm, where a maximum NO2 gas response of 96% was obtained. The NO2 sensors based on the TiO2 nanotube arrays all exhibited a high level of stability, good reproducibility, and high sensitivity.
Review of Angular-Selective Windows with Guest–Host Liquid Crystals for Static Window Applications
Authors: An Chan-Heon , Oh Seung-Won
Published: October 2024

This review focuses on the development and advancements in angular-selective smart windows, with particular emphasis on static windows utilizing guest–host liquid crystal (GHLC) systems. Angular-selective windows are designed to adjust their transmittance based on the angle of incident light, offering enhanced energy efficiency and visual comfort in both architectural and automotive applications. By leveraging the anisotropic absorption properties of dichroic dyes, GHLC-based windows can selectively block oblique sunlight while preserving clear visibility from normal viewing angles. Various liquid crystal (LC) alignment configurations, including vertically aligned, homogeneously aligned, hybrid aligned, uniformly lying helix, and twisted aligned LC cells, have been investigated to optimize light control for different installation angles, such as for automotive windshields and building windows. These advancements have demonstrated significant improvements in energy conservation and occupant comfort by reducing cooling demands and regulating sunlight penetration. This review summarizes key findings from recent studies, addresses the limitations of current technologies, and outlines potential future directions for further advancements in smart window technology.
The Box Crab Calappa hepatica as a Nuclear Species for the Opportunistic Foraging Behaviour of the Flowery Flounder, Bothus mancus, in the Indo-Pacific
Authors: Betti Federico , Hoeksema Bert W.
Published: October 2024

Some predatory fishes may exhibit opportunistic feeding behaviour by exploiting potential prey that is distracted, displaced, or exposed by the activities of a third party that acts as a ‘nuclear’ species. Other fishes mostly perform the role of ‘nuclear’ species, but benthic invertebrates, such as octopuses, have also been reported. Crabs are rarely observed in this role, with only a few records from the tropical Atlantic Ocean. Here, we report the temporary association between two specimens of the flowery flounder, Bothus mancus (family Bothidae), and a box crab, Calappa hepatica (family Calappidae), from the Philippines, representing the first record of a crab–fish feeding association in the Indo-Pacific region.
Evaluating Machine Learning Models for Stroke Prognosis and Prediction in Atrial Fibrillation Patients: A Comprehensive Meta-Analysis
Authors: Goh Bill , Bhaskar Sonu M. M.
Published: October 2024

Background/Objective: Atrial fibrillation (AF) complicates the management of acute ischemic stroke (AIS), necessitating precise predictive models to enhance clinical outcomes. This meta-analysis evaluates the efficacy of machine learning (ML) models in three key areas: stroke prognosis in AF patients, stroke prediction in AF patients, and AF prediction in stroke patients. The study aims to assess the accuracy and variability of ML models in forecasting AIS outcomes and detecting AF in stroke patients, while exploring the clinical benefits and limitations of integrating these models into practice. Methods: We conducted a systematic search of PubMed, Embase, and Cochrane databases up to June 2024, selecting studies that evaluated ML accuracy in stroke prognosis and prediction in AF patients and AF prediction in stroke patients. Data extraction and quality assessment were performed independently by two reviewers, with random-effects modeling applied to estimate pooled accuracy metrics. Results: The meta-analysis included twenty-four studies comprising 7,391,645 patients, categorized into groups for stroke prognosis in AF patients (eight studies), stroke prediction in AF patients (thirteen studies), and AF prediction in stroke patients (three studies). The pooled AUROC was 0.79 for stroke prognosis and 0.68 for stroke prediction in AF, with higher accuracy noted in short-term predictions. The mean AUROC across studies was 0.75, with models such as Extreme Gradient Boosting (XGB) and Random Forest (RF) showing superior performance. For stroke prognosis in AF, the mean AUROC was 0.78, whereas stroke prediction yielded a mean AUROC of 0.73. AF prediction post-stroke had an average AUROC of 0.75. These findings indicate moderate predictive capability of ML models, underscoring the need for further refinement and standardization. The absence of comprehensive sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) metrics limited the ability to conduct full meta-analytic modeling. Conclusions: While ML models demonstrate potential for enhancing stroke prognosis and AF prediction, they have yet to meet the clinical standards required for widespread adoption. Future efforts should focus on refining these models and validating them across diverse populations to improve their clinical utility.
Contrast Enhancement in Breast Cancer: Magnetic Resonance vs. Mammography: A 10-Year Systematic Review
Authors: Filippone Francesco , Boudagga Zohra , Frattini Francesca , Fortuna Gaetano Federico , Razzini Davide , Tambasco Anna , Menardi Veronica , Balbiano di Colcavagno Alessandro , Carriero Serena , Gambaro Anna Clelia Lucia , Carriero Alessandro
Published: October 2024

PURPOSE: Contrast Enhancement Magnetic Resonance (CEMR) and Contrast-Enhanced Mammography (CEM) are important diagnostic tools to evaluate breast cancer patients, and both are objects of interest in the literature. The purpose of this systematic review was to select publications from the last ten years in order to evaluate the literature contributions related to the frequency of contrast agents used, administration techniques and the presence of adverse reactions. METHODS: We have selected, according to the PRISMA statement, publications reviewed on Pub Med in the period from 1 January 2012 to 31 December 2022. The search engine was activated using the following keywords: “CESM”, “CEM”, “CEDM”, “Contrast mammography” for CEM, “DCE-MRI”, “Contrast Enhancement MRI” for CEMR, excluding reviews, book chapters and meta-analyses. From the total number of publications, we made a preliminary selection based on titles and abstracts and excluded all articles published in languages other than English and all experimental studies performed on surgical specimen or animal population, as well as all articles for which the extended version was not available. Two readers evaluated all the articles and compiled a pre-compiled form accordingly. RESULTS: After a preliminary collection of 571 CEM publications, 118 articles were selected, relating to an overall population of 21,178 patients. From a total of 3063 CEMR publications, 356 articles relating to an overall population of 45,649 patients were selected. The most used contrast agents are Iohexol for CEM (39.83%) and Gadopentetic acid (Gd-DTPA) for CEMR (32.5%). Regarding the CEM contrast administration protocol, in 84.7% of cases a dose of 1.5 mL/kg was used with an infusion rate of 2–3 mL/s. Regarding the CEMR infusion protocol, in 71% of cases a dose of 1 mmol/kg was used at an infusion rate of 2–4 mL/s. Twelve out of 118 CEM articles reported allergic reactions, involving 29 patients (0.13%). In DCE-MRI, only one out of 356 articles reported allergic reactions, involving two patients (0.004%). No severe reactions were observed in either cohort of exams. CONCLUSIONS: CEM and CEMR are essential contrast methods to evaluate breast diseases. However, from the literature analysis, although there are preferences on the uses of the contrast agent (Iohexol for CESM, G-DTPA for CEMR), a wide range of molecules are still used in contrast methods, with different administration protocols. Based on the collected data, it is possible to state that both methods are safe, and no severe reactions were observed in our evaluation.
Histological Evaluation of Polyacid-Modified Composite Resin and Conventional Composite Resin Used for Primary Molars Restoration
Authors: El Meligy Omar A. , Othman Hisham I. , Abudawood Shahad N. , Al Tuwirqi Amani A. , Alkeheli Madawi Faisal , Abdelrehim Tarek R. , Talaat Dalia M.
Published: October 2024

Background: The present study evaluated the histological outcomes of two dental restorative materials, polyacid-modified composite resin (compomer) and conventional composite resin, in the primary molars of puppies. Materials and Methods: Twenty sound primary molars in four puppies were used. The puppies were rendered unconscious using general anesthesia. Similar cylindrical Class V cavities were prepared in 16 of the 20 selected primary molars. The teeth were divided into three groups: Group I: Eight cavities were restored with compomer; Group II: Eight cavities were restored with conventional composite resin; Group III: Four teeth remained untreated and were used as controls. In Groups I and II, four teeth were examined histologically after 2 weeks and the other four after 6 weeks. The histological findings were analyzed and compared to determine the effects of each type of resin material on the dentine and the pulp. Results: At 6 weeks, the specimens tested for compomer showed obvious destructive changes in the central region and the region of the pulp adjacent to the cavity. The specimens tested for conventional composite resin revealed, at 6 weeks, massive destruction of the pulp tissues and abscess formation was observed. All the specimens tested in the control group showed normal cellularity, normal vascularity, and proper alignment of odontoblast cells. Conclusions: The teeth restored with compomer demonstrated more favorable pulpal reactions when compared with the teeth restored with conventional composite resin after 6 weeks.
The Treatment Alliance and the Provision of Removable Dentures: Exploring the Emotional Work of the Dental Team
Authors: Gibson Barry John , Baker Sarah R. , Broomhead Tom , El-Dhuwaib Bilal , Martin Nicolas , Salama Heba R. , McKenna Gerry , Alavi Anousheh
Published: October 2024

Background: Research has demonstrated that the loss of one or more natural teeth can be an emotionally traumatic experience that mirrors processes associated with bereavement. There remains scant literature examining the role of emotions in dental encounters. One such exception is the literature on the idea of the ‘treatment alliance’ in dental encounters. The aim of this paper is to explore the role of the ‘treatment alliance’ in dentist–patient encounters. Methods: Data were collected from clinical observations, semi-structured interviews and focus groups exploring the experience of tooth loss and how the treatment alliance shaped the patient journey. Data analysis was conducted using the grounded theory method influenced by phenomenology. Coding was conducted using NVIVO and the unit of analysis was the treatment alliance. Results: Twenty participants took part in the interviews (eleven male; nine female; 22–86 years; mean age = 58.9 years). Observations were carried out with a further fourteen participants (seven male; seven female; 50–101 years; mean age = 62.2 years). The paper draws on four cases taken from the observational data to illustrate important dynamics underpinning how the treatment alliance varied. These case studies are then used as the basis for a critical discussion of the importance of the treatment alliance in dentistry. Conclusions: The treatment alliance acted as an important moderator in the clinical encounter, helping to influence successful outcomes. An important foundational component of the treatment alliance was the degree of emotional work the dental team conducted when ‘getting to know’ unfamiliar patients. Whilst emotions were an important factor in dental encounters, their acknowledgement and management were not essential to all successful outcomes. Much more research is therefore needed into the role of emotional labour in dental encounters.
A Serious Case of Poisoning Caused by Oral Ingestion of Water-Soluble Fertilizer
Authors: Ye Wei , Lin Shirong , Zheng Chengquan , Cao Chunshui
Published: October 2024

Current research is mostly focused on the impact of fertilizers on human health when they are ingested through food; the main form of this is chronic damage. Intoxication through oral ingestion of fertilizer is an extremely rare situation. We report a case of a 38-year-old man that attempted to commit suicide by ingesting only 20 mL of a water-soluble fertilizer. Acute kidney injury occurred early, which showed that the toxicity could not be ignored. It was necessary to seek medical attention as soon as possible. In addition, the patient experienced gastrointestinal dysfunction and a severe inflammatory response; inflammatory markers increased rapidly. Physicians implemented antimicrobial stewardship to reduce antimicrobial drug resistance and the risk of hospital infection, and the patient’s inflammatory response was well controlled. Although the damage was severe, the patient quickly recovered to normal after appropriate treatment. The prognosis is very good. This successful case provides guidance for clinical treatment.
The Effect of Self-Monitoring on Mental Effort and Problem-Solving Performance: A Mixed-Methods Study
Authors: Graham Madison , Ilic Marinela , Baars Martine , Ouwehand Kim , Paas Fred
Published: October 2024

Self-regulated learning (SRL) has become increasingly important for learners in the 21st century as they engage more frequently in student-centered education. Accurate self-monitoring of one’s learning process is central to SRL. However, research has shown that learners often struggle with monitoring accuracy. One possible explanation is that the process of self-monitoring itself may add cognitive load, potentially reducing both self-monitoring accuracy and overall performance. In the current study, we investigated the effects of self-monitoring on perceived mental effort and performance during problem-solving tasks of increasing complexity. Participants in the experimental condition were instructed to think aloud while problem-solving, while those in the control condition did not receive such instructions. Our findings indicate no interaction effect between the requirement for explicit and continuous self-monitoring and task complexity on perceived mental effort and performance. However, task complexity significantly impacted the perceived mental effort and performance in both conditions, while it affected monitoring accuracy exclusively in the experimental condition. Furthermore, qualitative analyses showed that the participants in the experimental conditions engaged in self-monitoring during 21.2 % of their think-aloud protocols. Contrary to previous research, self-monitoring did not appear to increase cognitive load, although the experimental participants took significantly longer to complete all the tasks. Possible explanations for these findings are discussed.
Overcoming Challenges and Promoting Positive Education in Inclusive Schools: A Multi-Country Study
Authors: Deroncele-Acosta Angel , Ellis Althia
Published: October 2024

Inclusive education faces significant challenges requiring deep understanding and comprehensive solutions. This study aims to establish a holistic framework for understanding the challenges in inclusive education, the core mission of inclusive schools, and the essential qualities of teachers. The methodology employed was qualitative, using the grounded theory method. A total of 59 experts from 13 countries participated in this study. Semi-structured asynchronous virtual interviews were conducted and analyzed using ATLAS.ti software (version 8). The results identified eight persistent challenges to inclusive education. In addition, positive education was highlighted as the fundamental core of inclusive schools, with emphasis on the development of learning, well-being, engagement, resilience, motivation, mental health, affective and social outcomes, creativity, and happiness. Finally, the integral profile of the inclusive teacher was defined based on a four-dimensional model. This groundbreaking study introduces a novel comprehensive framework that revolutionizes our understanding of the enduring challenges in inclusive education. Elucidating the core mission of inclusive schools and defining the essential qualities of inclusive teachers offers transformative insights. This study’s implications, future perspectives, and limitations provide a wealth of valuable information for policymakers, educators, and researchers, paving the way for innovative approaches and enhanced inclusive educational practices.
Artificial Intelligence-Assisted Music Education: A Critical Synthesis of Challenges and Opportunities
Authors: Merchán Sánchez-Jara Javier Félix , González Gutiérrez Sara , Cruz Rodríguez Javier , Syroyid Syroyid Bohdan
Published: October 2024

Artificial intelligence (AI) is a hot topic that presents new challenges and opportunities for the improvement of educational processes. The disruptive and transformative force of this new technological development implies the adaptation of educational ecosystems for its use and integration as a didactic and pedagogical resource. From this perspective, a systematic literature review has been conducted to analyze the didactic potential of generative AI tools in the field of promoting artistic creativity in music education. The research results confirm that the incorporation of AI in music education is paving the way for a more personalized, interactive and efficient learning experience. In addition, the analysis suggests nine fundamental fields of IA implementation in music education: virtual and augmented reality (VR; VA); learning personalization, intelligent tutoring systems; composition assistants; improved historical and contextual learning; assessment systems; interactive ear training and music theory systems; tools for music collaboration and performance; and assistive technologies. Furthermore, the challenges presented by the intersection of AI and digital didactics in the field of music education are discussed.
Social Diversity in Focus: Assessing the Impact of Socioeconomic Backgrounds and Work Experience on Psychological Well-Being and Academic Confidence Among German First-Year Medical Students
Authors: Gellisch Morris , Bablok Martin , Brand-Saberi Beate , Schäfer Thorsten
Published: October 2024

This investigation pioneers an examination of the scarcely explored terrain of social diversity in medical education, assessing the complex impacts of socioeconomic status (SES), prior working experiences, and completed apprenticeships on a spectrum of psychological and academic facets among first-year medical students (n = 336) in an urban university setting. By utilizing a systematic and detailed approach, the study illuminates prior anatomical knowledge and various psychological constructs, marking a significant stride into a domain where knowledge remains profoundly limited. Analyses indicated that SES significantly affects financial anxiety (F(4, 331) = 17.391, p < 0.001) and academic behavioral confidence (F(4, 331) = 4.323, p = 0.002). Students with prior working experience reported higher self-perceived clinical experience but lower A-level grades (t(279.459) = −6.690, p < 0.001), competence in natural sciences (t(321.045) = −3.178, p = 0.002), and online competence (t(319.429) = −2.026, p = 0.044). Those who completed an apprenticeship showed higher resilience, academic confidence, self-efficacy, and greater concerns about balancing studies and work (t values ranging from 2.020 to 3.158, p < 0.05). Correlation analysis revealed a positive relationship between resilience (RQS) and coping with academic stress (CAS) (r = 0.632, p < 0.001), as well as between resilience and academic behavioral confidence (ABC) (r = 0.608, p < 0.001). Negative correlations were observed between resilience, coping with academic stress, academic confidence, and cognitive test anxiety (CTA) (r values from −0.235 to −0.404, p < 0.001). The findings emphasize the need for tailored support for students from diverse SES backgrounds and with varying experiences. The study highlights the value of a comprehensive approach in medical education, considering the diverse backgrounds and experiences of students. Future research should explore the long-term impact of these factors on professional competencies and patient care, leveraging the diversity of the student body for a holistic educational experience.
Analysis of Intervention Effects of Prototyping Utilizing UI Stencils in Elementary School Students
Authors: Igarashi Toshiharu , Chen Yu
Published: October 2024

This study examines the impact of using stencils in paper prototyping on work time, subjective burden, and idea generation among Japanese sixth-grade students, focusing on the role of personality traits, specifically openness. Two groups were involved: Group 1 used stencils after a lecture, and Group 2 worked freehand without prior instruction. Results showed no significant difference in work time; however, a reduction in subjective burden was noted in the stencil group. While no significant correlation was found between openness and the number of stencil icons used, children with higher openness scores engaged more intensively, suggesting that stencils influence the quality and depth of engagement. The findings highlight the importance of tailored educational approaches to enhance learning outcomes.
Teacher Well-Being Under Threat: The Consequences of Workplace Bullying from Preschool to Higher Education
Authors: Portelada António , Candeias Adelinda , João Ana Lúcia
Published: October 2024

Workplace bullying can be defined as the repeated occurrence of aggressive behaviour by one or more persons in a position of power towards the victim. This phenomenon remains insufficiently researched among education professionals, especially between different levels of education. With this in mind, the present study aims to assess and characterise this phenomenon in the Portuguese teacher population, as well as its consequences. A digital questionnaire was used for the study, which includes a socio-demographic component and two scales, namely the LIPT-60 scale and the WBMMS scale. The questionnaire was published online and made accessible to all teachers employed in schools in Portugal. The final sample consisted of 2003 teachers. The obtained results revealed that 22.5% of the sample acknowledged experiencing workplace bullying. The most prevalent aggressive behaviours included communication blockage and defamation and disregard for work. Vertical descent emerged as the most common form of bullying. More than half of the victims reported experiencing health issues, with a quarter of them requiring a medical certificate. Finally, we would like to emphasize the significance of this study as an initial step towards the prevention and reduction of workplace bullying among Portuguese teachers.
A Case Study of an Antibiotic Discovery Laboratory Autonomous Learning Assignment—An Evaluation of Undergraduate Students’ Disciplinary Bias
Authors: Badrian Nadav , Iasur-Kruh Lilach , Ungar Yael , Weitz Iris Sonia
Published: October 2024

Current higher education trends are moving towards interdisciplinary curricula to provide new tools for solving complex issues. However, course design and learning tracks still create divisions between scientific disciplines. This study aimed to evaluate the disciplinary bias of second-year undergraduate students of biotechnology engineering in the organic chemistry laboratory class through a laboratory setting involving blended disciplines. An experiment on antibiotic discovery that integrates parallel and combinatorial organic chemistry syntheses with microbiology techniques was chosen. As a part of an activity, students had free choice in designing the arrangement of the organic compounds and the two bacterial species by setting up the layout for a 96-well plate. The study visually analyzed students’ plate layouts (n = 74) according to discipline classification and the spatial arrangements of organic compounds (e.g., products and libraries). The results identified four themes that are suggested to reflect students’ vertical, lateral, and interdisciplinary thinking, as most were found to be in the procedural knowledge range and between Bloom’s application and analysis dimensions. Using this study’s thematic analysis methodology in chemistry and related educational fields can provide a pedagogical reflective tool and advance personalized teaching and interdisciplinarity.
Memoization in Model Checking for Safety Properties with Multi-Swarm Particle Swarm Optimization
Authors: Kumazawa Tsutomu , Takimoto Munehiro , Kodama Yasushi , Kambayashi Yasushi
Published: October 2024

In software engineering, errors or faults in software systems often lead to critical social problems. One effective methodology to tackle this problem is model checking, which is an automated formal verification technique. In traditional model checking, the task of finding specification errors is reduced to deterministic search techniques such as Depth-First Search. Recent research has shown that swarm intelligence offers a powerful search capability compared to traditional techniques. In particular, multi-swarm Particle Swarm Optimization is known to be efficient and can mitigate the state-space explosion problem, i.e., the exponential increase in the search space with a linear increase in the problem size. However, the state-space explosion problem is still significant when verifying very large systems. Further performance improvement is needed. To achieve this, we propose a novel memoization or cache mechanism for storing tentative solutions for reuse in the later stages of the search procedure. For each stage, a candidate solution computed by a swarm is summarized efficiently and heuristically to consolidate similar solutions into a single representative solution. We store the summary and its associated solutions in key-value maps. Instead of computing known solutions repeatedly, we retrieve the solution if the stored key matches the summary. We incorporated the proposed mechanism into a model-checking technique with multi-swarm Particle Swarm Optimization and evaluated the search performance. We show in this paper that the proposed mechanism improved time and space consumption while maintaining solution quality.
Comprehensive Analysis and Reconstruction of Sensor Faults in Interleaved Buck Converters Using Sliding Mode Observers
Authors: Asensio Eduardo Maximiliano , Siu Ken King Man , Astrada Juan Carlos , Serra Federico Martín , De Angelo Cristian Hernán
Published: October 2024

This paper presents a fault signal reconstruction method for current sensors in an interleaved buck DC–DC converter, utilizing a sliding mode observer (SMO). A filter bank is used to design the observer within an extended-order system, effectively treating sensor faults as actuator faults, which enables precise estimation of the fault signal. Thus, the proposed approach allows for the identification of the faulty sensor and supports the implementation of fault-tolerant strategies. The paper provides an in-depth analysis of current sensor faults, verifies their impact on current balancing control, and demonstrates the challenge of achieving error-free current estimation in one phase using observers. A comprehensive set of simulation results is carried out, validating the method’s effectiveness and showing a strong correlation with theoretical principles.
Modeling and Simulation of Wide-Frequency Characteristics of Electromagnetic Standard Voltage Transformer
Authors: Wang Lewei , Li Zhenhua , Lu Heping , Zhou Feng , Diao Yinglong
Published: October 2024

To achieve the broadband applicability of standard voltage transformers in “dual high” power systems, an equivalent circuit model of the standard voltage transformer is first established. Using the complex magnetic permeability method and utilizing existing core parameters, the excitation impedance values are obtained. Next, based on the equivalent circuit model, the no-load error function of the standard voltage transformer is analyzed, and through simulation, the no-load error response curve of the standard voltage transformer in the frequency range of 20 Hz to 3000 Hz is derived. The simulation results indicate that within the 20 Hz to 700 Hz range, both the no-load ratio error and the no-load angular error meet the accuracy requirements, with the ratio error within ±0.05% and the angular error within 2′. Additionally, the derivation of the error transfer function demonstrates the correlation between the no-load error values and the number of turns and cross-sectional area of the standard voltage transformer. Simulation results, obtained by increasing and decreasing the number of turns and cross-sectional area by 10%, provide valuable insights for the error compensation and structural design of standard voltage transformers.
Graph Neural Network-Based Speech Emotion Recognition: A Fusion of Skip Graph Convolutional Networks and Graph Attention Networks
Authors: Wang Han , Kim Deok-Hwan
Published: October 2024

In speech emotion recognition (SER), our research addresses the critical challenges of capturing and evaluating node information and their complex interrelationships within speech data. We introduce Skip Graph Convolutional and Graph Attention Network (SkipGCNGAT), an innovative model that combines the strengths of skip graph convolutional networks (SkipGCNs) and graph attention networks (GATs) to address these challenges. SkipGCN incorporates skip connections, enhancing the flow of information across the network and mitigating issues such as vanishing gradients, while also facilitating deeper representation learning. Meanwhile, the GAT in the model assigns dynamic attention weights to neighboring nodes, allowing SkipGCNGAT to focus on both the most relevant local and global interactions within the speech data. This enables the model to capture subtle and complex dependencies between speech segments, thus facilitating a more accurate interpretation of emotional content. It overcomes the limitations of previous single-layer graph models, which were unable to effectively represent these intricate relationships across time and in different speech contexts. Additionally, by introducing a pre-pooling SkipGCN combination technique, we further enhance the ability of the model to integrate multi-layer information before pooling, improving its capacity to capture both spatial and temporal features in speech. Furthermore, we rigorously evaluated SkipGCNGAT on the IEMOCAP and MSP-IMPROV datasets, two benchmark datasets in SER. The results demonstrated that SkipGCNGAT consistently achieved state-of-the-art performance. These findings highlight the effectiveness of the proposed model in accurately recognizing emotions in speech, offering valuable insights and a solid foundation for future research on capturing complex relationships within speech signals for emotion recognition.
Online Three-Dimensional Fuzzy Reinforcement Learning Modeling for Nonlinear Distributed Parameter Systems
Authors: Zhang Xianxia , Yan Runbin , Zhou Gang , Wang Lufeng , Wang Bing
Published: October 2024

Distributed parameter systems (DPSs) frequently appear in industrial manufacturing processes, with complex characteristics such as time–space coupling, nonlinearity, infinite dimension, uncertainty and so on, which is full of challenges to the modeling of the system. At present, most DPS modeling methods are offline. When the internal parameters or external environment of DPS change, the offline model is incapable of accurately representing the dynamic attributes of the real system. Establishing an online model for DPS that accurately reflects the real-time dynamics of the system is very important. In this paper, the idea of reinforcement learning is creatively integrated into the three-dimensional (3D) fuzzy model and a reinforcement learning-based 3D fuzzy modeling method is proposed. The agent improves the strategy by continuously interacting with the environment, so that the 3D fuzzy model can adaptively establish the online model from scratch. Specifically, this paper combines the deterministic strategy gradient reinforcement learning algorithm based on an actor critic framework with a 3D fuzzy system. The actor function and critic function are represented by two 3D fuzzy systems and the critic function and actor function are updated alternately. The critic function uses a TD (0) target and is updated via the semi-gradient method; the actor function is updated by using the chain derivation rule on the behavior value function and the actor function is the established DPS online model. Since DPS modeling is a continuous problem, this paper proposes a TD (0) target based on average reward, which can effectively realize online modeling. The suggested methodology is implemented on a three-zone rapid thermal chemical vapor deposition reactor system and the simulation results demonstrate the efficacy of the methodology.