bluuebunny/crossref_metadata_2025 huggingface dataset:
Clinical Utility of Virtual Kitchen Errand Task for Children (VKET-C) as a Functional Cognition Evaluation for Children with Developmental Disabilities
Authors: Ju Yumi , Kang Sura , Kim Jihye , Ryu Jeh-Kwang , Jeong Eun-Hwa
Published: October 2024

Background/Objectives: This study evaluated the clinical utility of a virtual reality (VR)-based kitchen error task for children (VKET-C) to assess functional cognition in children. Methods: In total, 38 children aged 7–12 years were included, comprising 23 typically developing (TD) children and 15 children with developmental disabilities (DDs), including autism spectrum disorder, attention deficit hyperactivity disorder, and intellectual disability. While performing the VKET-C, performance errors were analyzed. The Stockings of Cambridge (SOC) and Spatial Working Memory (SWM) tasks from the Cambridge Neuropsychological Test Automated Battery (CANTAB) were used to assess cognitive function. The Brunner–Munzel test was performed to compare performance errors between the TD and DD groups, and correlations between performance errors and cognitive measures were analyzed. Results: Omission and commission errors were significantly different between the groups (p < 0.001), with no significant difference in motor errors (p > 0.05). Omission errors were correlated with the initial thinking time mean (ITMN) in all items of the SOC task and the between errors (BE) of the SWM task. Commission errors were correlated with the ITMN in the difficult items of the SOC task and the BE of the SWM task. Additionally, motor errors were significantly correlated with problems solved in minimum moves (PSMM) and ITMN in the difficult items of the SOC task and BE in the SWM task. Conclusions: The VKET-C shows promise as an effective tool for assessing executive function and working memory in children with DDs, offering an engaging and ecologically valid alternative to traditional methods.
Loneliness and Problematic Internet Use in Adolescents: The Mediating Role of Dissociation
Authors: Matiz Alessio , D’Antoni Fabio , Pascut Stefania , Ciacchini Rebecca , Conversano Ciro , Gemignani Angelo , Crescentini Cristiano
Published: October 2024

Background/Objectives. Problematic Internet uUse (PIU) is a multifaceted syndrome characterized by excessive or poorly controlled preoccupations, urges, or behaviors regarding Internet use leading to significant impairments in daily life and mental health. Previous research has separately related PIU to loneliness and dissociation, both in adults and adolescents. The aim of the present study is to analyze the mutual relationship between PIU, loneliness, and dissociation in an adolescent sample, in particular evaluating the indirect effect of dissociation on the relationship between loneliness and PIU. Methods. A cross-sectional design was used with 243 Italian high school students (69.1% females), from year 9 to 13 (age: M = 17.1, SD = 1.4 years), who participated in the study from January to June 2020. They completed measures of PIU (Generalized Problematic Internet Use Scale-2), loneliness (UCLA Loneliness Scale), and dissociation (Adolescent Dissociative Experiences Scale). Socio-demographic and contextual variables were also collected (i.e., age, gender, type of school, school year, sport practice, hobby engagement, assessment before/during the COVID-19 pandemic). Data were analyzed using regression, Pearson’s correlation, and mediation analysis. Results. Severe PIU was observed in 8.6% of the sample. None of the socio-demographic and contextual variables had a significant effect on PIU. Positive medium-sized correlations were observed between PIU, loneliness, and dissociation. Mediation analyses showed an indirect effect of loneliness on PIU through dissociation. Conclusions. Feelings of loneliness may significantly exacerbate adolescents’ PIU by increasing their dissociative tendency. Understanding this dynamic is crucial for developing targeted interventions to address both loneliness and dissociation in efforts to mitigate PIU among adolescents.
Preschoolers’ Moderate-to-Vigorous Physical Activity Measured by a Tri-Axial Accelerometer: Compliance with International Guidelines and Different Cut-Points
Authors: Machado-Rodrigues Aristides M. , da Silva Thales P. Rodrigues , Mendes Larissa L. , Neto António Stabelini , Nogueira Helena , Rodrigues Daniela , Padez Cristina
Published: October 2024

Background/Objectives: This study aimed to investigate the effect of the most frequently used accelerometer CoPs on the quantification of active preschoolers by weekday; and to analyze children’s physical activity (PA) quantification using a vertical axis and vector magnitude (VM). Methods: A cross-sectional sample of 134 children (70 males) aged 3–5 years was studied. Height, body weight, and BMI were assessed. A tri-axial accelerometer was used for seven consecutive days of MVPA and sedentary behavior (SB). Data were analyzed using the three most used CoPs for active preschooler classification (Johansson, Butte, and Pate). A general linear model with repeated measures examined differences in PA and SB, and the agreements of all CoPs were analyzed using the Kappa index. Results: The CoPs adopted by Pate had the highest percentage of children classified as active for the weekdays (73.9%) and weekend (85.6%). The Johansson CoP classified all children as inactive. Furthermore, the prevalence of active boys was significantly higher than their female counterparts based on the Pate and Butte CoPs for the week and weekends. Conclusions: The lowest prevalence rates of active children were observed at the weekend based on all accelerometer CoPs, especially among girls. The choice of cut-points significantly affects the times calculated for different movement intensities.
Comparative Analysis of 24-h Movement Behaviours in Non-Overweight and Overweight/Obese Children: Findings from the FAMIly Physical Activity, Sedentary Behaviour, and Sleep (FAMIPASS)
Authors: Sigmund Erik , Voráčová Jaroslava , Dygrýn Jan , Vorlíček Michal , Sigmundová Dagmar
Published: October 2024

Background: Childhood overweight and obesity are global health concerns associated with insufficient physical activity (PA), excessive sedentary behaviour (SB), and inadequate sleep. This study aimed to determine whether differences exist in 24 h movement behaviours between Czech non-overweight children and children with overweight/obesity aged 3–10 years, with respect to their gender, age, or family socioeconomic status (SES). Methods: A total of 381 children (49.9% girls), aged 3–10 years, participated. Their PA, SB, and sleep were continuously monitored over a regular week using wrist-worn accelerometers. Weight status was determined by BMI z-scores, according to World Health Organization standards. SES was assessed using the Family Affluence Scale. Results: Non-overweight children had averages of 414 min of PA, 472 min of SB, and 554 min of sleep per day, while children with overweight/obesity had averages of 392 min of PA, 503 min of SB, and 545 min of sleep. Non-overweight children engaged in significantly more PA (22 min per day; p = 0.014) and significantly less SB (31 min per day; p = 0.002) than children with overweight/obesity. No significant differences were found between the weight groups in gender distribution, age, family SES, or maternal and paternal obesity. Conclusions: Non-overweight children exhibited higher levels of PA and lower levels of SB compared to their counterparts with overweight/obesity, independent of gender, age, or family SES. These findings highlight an association between daily movement behaviours and weight status in young children. Further research is needed to explore the impact of modifying PA and SB on weight outcomes.
Focused on the Family: Development of a Family-Based Intervention Promoting the Transition to Adult Health Care for Adolescents with Type 1 Diabetes
Authors: Papadakis Jaclyn L. , Suhs Madeleine C. , O’Donnell Alexander , Harris Michael A. , Anderson Lindsay M. , Garza Kimberly P. , Weil Lindsey , Weissberg-Benchell Jill
Published: October 2024

Background/Objectives: There is minimal evidence for current interventions promoting the transition to adult healthcare for youth with type 1 diabetes (T1D). Few interventions exclusively target modifiable individual and family-based factors that contribute to transition readiness. The purpose of this paper is to describe the development of Behavioral Family Systems Therapy for Diabetes Transition (BFST-DT), a virtual family-based transition readiness intervention for adolescents with T1D. Methods: The development of BFST-DT occurred in three phases. In phase 1, focus groups with adolescents and young adults with T1D, their caregivers, and pediatric and adult diabetes providers were conducted to assess perspectives on common family challenges surrounding diabetes management and the transition to adult healthcare. In phase 2, focus group data were used to create video vignettes to be used as part of the intervention. In phase 3, BFST-DT was created through the adaptation of a previous evidence-based family intervention for families of adolescents with T1D. Results: BFST-DT is a virtual, 6-month family-based intervention involving four multi-family group meetings and six individual family meetings. It targets the modifiable and reciprocal interactions among individual and family transition readiness factors. Conclusions: BFST-DT is the first family-focused intervention promoting transition readiness in adolescents with T1D and is currently being tested. Intervention development benefits from prioritization of engagement with patients, caregivers, and providers, as their perspectives are invaluable for creating interventions that are relevant and acceptable to communities.
Long-Term Mechanical Deterioration Trends and Mechanisms of SBS-Modified Asphalt Mixtures
Authors: Wang Jinquan , Liu Maijian
Published: October 2024

Understanding the long-term performance deterioration trends and mechanisms of asphalt pavement is crucial for effective maintenance strategies. This study characterizes and correlates the multi-scale performance deterioration of a 14-year asphalt pavement. Air void measurements, indirect tensile (IDT) fatigue testing, Fourier transform infrared spectroscopy (FTIR), and dynamic shear rheometer (DSR) testing were conducted on pavement cores and recovered binder. Multiple regression analysis was then performed on various performance indicators. Laboratory results indicate that the chemical composition and viscoelastic properties of SBS-modified binders evolve rapidly in the first few years, followed by a relatively stable aging rate. After 14 years, the mechanical and rheological properties of lower-layer mixtures deteriorate to a similar degree as the surface layer. Correlation analysis revealed that the residual strength of the mixture is more influenced by air voids, while reductions in fatigue life are primarily driven by binder aging. These findings highlight the necessity of applying preventive maintenance within the first 3–5 years to rejuvenate the surface asphalt and rehabilitate both the surface and underlying layers after long-term service.
Protection of 316L Steel Against LBE Corrosion by a CaO-MgO-Al2O3-SiO2 Glass–Ceramic Coating
Authors: Xiao Zunqi , Jiang Zhizhong , Luo Lin , Wan Yi , Liu Aixue , Zhang Bin , Ren Bing , Liu Jing
Published: October 2024

A CaO-MgO-Al2O3-SiO2 glass–ceramic coating was prepared by the slurry method and subsequent sintering to improve the corrosion resistance of 316L steel in liquid lead–bismuth eutectic alloy at high temperatures. The glass–ceramic coating, sintered at 884 °C, was dense and demonstrated strong adhesion to the substrate. It was composed of the crystalline phases diopside (CaMgSi2O6) and anorthite (CaAl2Si2O8) and had an average Vickers hardness of 595 HV, which was over three times that of 316L steel. After corrosion in an oxygen-saturated, static lead–bismuth eutectic alloy at 500 °C for 1000 h, the uncoated 316L experienced significant mass gain (0.04 g) due to severe oxidative corrosion, resulting in the formation of Fe3O4 and Pb2O on its surface. In contrast, the glass–ceramic-coated specimens showed a very small mass gain (0.0012 g) after corrosion. The coating maintained good thermal stability; its crystalline phase composition remained largely unchanged after the corrosion test. The glass–ceramic coating still exhibited dense microstructure and tightly adhered to the substrate after corrosion. There was no evident penetration of lead–bismuth into the coating, and no dissolution of the coating’s elements into the lead–bismuth alloy was detected. These observations confirm that the glass–ceramic coating possessed superior corrosion resistance in liquid lead–bismuth eutectic environments.
Effects of Slurry Composition and Interfacial Adhesion of Monolithic Coatings on FeCrAl Honeycombs
Authors: Ren Yanlun , Xu Hong , Zhang Li
Published: October 2024

Excellent coating adhesion is a crucial requirement for monolithic catalysts. Within this investigation, a Design of Experiments (DOEs) Taguchi approach was leveraged to construct a 9-factor-3-level matrix encompassing 27 parallel experiments. This framework was employed to scrutinize the pivotal elements influencing the adhesion of FeCrAl metal-based integral coatings, which were prepared using the slurry method. Moreover, an unprecedented endeavor was made to scrutinize the mechanism of coating delamination from the vantage points of macroscopic slurry, microscopic coatings, and nanoscale interfaces. The findings reveal the following: (1) The inclusion of a high-acidity additive (>5%) emerges as one of the pivotal factors in achieving superior adhesion, particularly when the boehmite content exceeds 1%. (2) The existence of binder-filled interstices within the coating, smaller by 1–2 orders of magnitude than the carrier particles, significantly contributes to heightened adhesion. (3) A bonding region of approximately 5 nm is present at the interfaces between carrier particles, resulting in augmented adhesion.
Three-Dimensional Reconstruction of the Right Ventricle from a Radial Basis Morphing of the Inner Surface
Authors: Fontana Carlotta , Cappetti Nicola
Published: October 2024

In the realm of cardiac health research, accurate fluid dynamics simulations are vital for comprehending the heart function and diagnosing conditions. Central to these simulations is the precision of ventricular wall meshes used to model heart geometry. However, segmenting the wetted surface, particularly in the right ventricle (RV) with its significantly thinner parietal thickness compared to the left ventricle, presents challenges. This study focuses on qualitatively evaluating an automated reconstruction model for the RV’s outer wall using Radial Basis function (RBF) morphing. Two procedural criteria were compared, a random selection of control points and a curvature-based approach, which differ in terms of the identification of the control points of the RBF function. From these considerations, it emerges that a controlled use of the RBF function on the basis of the curvatures guarantees the greater controllability of the shape evolutions of the parietal structure of the RV, but it is more sensitive to any anomalies in the distribution of the vertices, as can be seen from the number of outliers, and its controllability is a function of the percentage of points chosen, exerting a greater impact on the required computational capacity. The definition of a strategic criterion for the selection of control points could represent a crucial aspect in the definition of an automatic reconstruction procedure of anatomical elements, which guarantees a morphological variability in line with the need to expand the pathological sample to be used for statistical formulations in the clinical field.
Advanced Frequency Analysis of Signals with High-Frequency Resolution
Authors: Flegner Patrik , Kačur Ján , Durdán Milan , Laciak Marek , Frančáková Rebecca
Published: October 2024

In today’s era, it is important to analyze and utilize various signals in industrial or laboratory applications. Measured signals provide critical information about the controlled system, which can be contained precisely within a narrow frequency range. Many methods and algorithms exist to process such signals in both the time and frequency domains. In particular, signal processing in the frequency domain is primary in industrial practice because dominant components within a specific narrow frequency band are sought. The discrete Fourier transformation (DFT) algorithm is the tool used in practice to find these frequency components. The DFT algorithm provides the full frequency spectrum with a higher number of calculation steps, and its spectrum frequency resolution is low. Therefore, research has focused on finding a method to achieve high-frequency spectrum resolution. An important factor in selecting the technique was that such an algorithm should be implementable on a microprocessor-based system under harsh industrial conditions. Research results showed that the DFT ZOOM method meets these requirements. The frequency zoom has many advantages but requires some modification. It is implemented in high-performance analyzers, but a thorough and detailed description of the respective algorithm is lacking in technical articles and literature. This article mathematically and theoretically describes the modified frequency zoom algorithm in detail. The steps of the frequency zoom, from creating an analytical signal through frequency shifting and decimation to the frequency analysis of the signal, are realized. The algorithm allows for the analysis of a signal with high-frequency resolution in a limited frequency band. A significant modification of DFT ZOOM is that of using the Hilbert transform to create an analytic signal. This resolves the aliasing issue caused by the overlap between fundamental and sideband spectra. Results from processing deterministic and stochastic signals using the modified DFT ZOOM are presented. The presented experimental results contribute to a more detailed frequency analysis of the signal. As part of this scientific research, the issues of frequency zoom were thoroughly addressed, solving the partial problems of this algorithm, both in theory and in the context of signal theory.
Enhancing 5G Vehicular Edge Computing Efficiency with the Hungarian Algorithm for Optimal Task Offloading
Authors: Benbraika Mohamed Kamel , Kraa Okba , Himeur Yassine , Telli Khaled , Atalla Shadi , Mansoor Wathiq
Published: October 2024

The rapid advancements in vehicular technologies have enabled modern autonomous vehicles (AVs) to perform complex tasks, such as augmented reality, real-time video surveillance, and automated parking. However, these applications require significant computational resources, which AVs often lack. To address this limitation, Vehicular Edge Computing (VEC) has emerged as a promising solution, allowing AVs to offload computational tasks to nearby vehicles and edge servers. This offloading process, however, is complicated by factors such as high vehicle mobility and intermittent connectivity. In this paper, we propose the Hungarian Algorithm for Task Offloading (HATO), a novel approach designed to optimize the distribution of computational tasks in 5G-enabled VEC systems. HATO leverages 5G’s low-latency, high-bandwidth communication to efficiently allocate tasks across edge servers and nearby vehicles, utilizing the Hungarian algorithm for optimal task assignment. By designating an edge server to gather contextual information from surrounding nodes and compute the best offloading scheme, HATO reduces computational burdens on AVs and minimizes task failures. Through extensive simulations in both urban and highway scenarios, HATO achieved a significant performance improvement, reducing execution time by up to 75.4% compared to existing methods under full 5G coverage in high-density environments. Additionally, HATO demonstrated zero energy constraint violations and achieved the highest task processing reliability, with an offloading success rate of 87.75% in high-density urban areas. These results highlight the potential of HATO to enhance the efficiency and scalability of VEC systems for autonomous vehicles.
Enhancing Antioxidant Activity from Aquatic Plant Cymodocea nodosa for Cosmetic Formulation Through Optimized Ultrasound-Assisted Extraction Using Response Surface Methodology
Authors: Chaabani Emna , Mgaidi Sarra , Ben Abdennebi Ameni , Dakhlaoui Sarra , Hammami Majdi , Selmi Sawssen , Zariat Mohamed , Shili Abdessalem , Merah Othmane , Bettaieb Rebey Iness
Published: October 2024

This study aimed to enhance antioxidant extraction from the aquatic plant Cymodocea nodosa for cosmetic formulation through optimized ultrasound-assisted extraction using response surface methodology. The optimized conditions—30 min of extraction time, 30% ultrasonic power, and 25% hydro-ethanolic solvent—resulted in a high total phenolic content of 113.07 mg EAG/g DM and antioxidant activity of 67.02%. Chromatographic analysis revealed a rich profile of phenolic compounds, including sinapic acid (0.741 mg/g), myricetin (0.62 mg/g), and quercetin-3-O-rutinoside (0.3 mg/g), demonstrating the extract’s potent therapeutic properties. While the extract exhibited limited anti-inflammatory activity, it showed no cytotoxic effects on RAW 267.4 cells, ensuring its safety for cosmetic applications. The formulated cream maintained stable pH (6.58 to 6.6), consistent viscosity (5966.38 to 5980.6 cp), and minimal color changes over a 30-day period, indicating robust stability across various temperatures (4 °C, 25 °C, and 40 °C). These results confirm the potential of C. nodosa extracts to develop effective, stable, and eco-friendly cosmetic products, offering substantial benefits for skin health and emphasizing the importance of sustainable extraction processes in the cosmetics industry.
Ce-Doped Iron Oxide Anticorrosive Coatings: Effect of c(Ce4+):c(Fe3+) Ratio on Structure, Morphology, and Coating Anticorrosion Performance
Authors: Ning Junxiang , Tang Xinyi , Shi Peiyang
Published: October 2024

Utilizing hydrothermal methods, Ce-doped iron oxide nanoparticles were synthesized from precursor solutions under different c(Ce4:c(Fe3+) precursor solutions. The effects of the c(Ce4+):c(Fe3+) ratio in the precursor solutions on the nanoparticle morphology and nanoparticle structure of the Ce-doped iron oxide were investigated using X-Ray diffraction, transmission electron microscopy, and scanning electron microscopy. Fourier transform infrared spectroscopy (FTIR) was used to examine the bond energy strength of the Ce-doped iron oxide nanoparticles. The electrochemical properties of the Ce-doped iron oxide nanoparticles were tested using an electrochemical workstation and a saltwater immersion resistance test. The corrosion resistance of Ce-doped iron oxide coatings at different c(Ce4+):c(Fe3+) ratios was systematically analyzed, uncovering corrosion resistance mechanisms and self-healing capabilities. The results show that as the c(Ce4+):c(Fe3+) ratio decreases, the lattice constants of the samples increase along with the average grain size. Both smaller and larger c(Ce4+):c(Fe3+) ratios are detrimental to lattice distortion in α-Fe2O3. The reduced number of valence electrons provided by cerium ions in Ce-doped iron oxide hinders the generation of holes and exerts a minor influence on the crystal band structure, leading to weaker electrochemical stability. The Ce-doped iron oxide coating prepared at a c(Ce4+):c(Fe3+) ratio of 1:60 readily generates a higher number of reactive hydroxyl radicals during corrosion, thus exhibiting enhanced self-healing capabilities and corrosion resistance.
Bilateral Idiopathic Neuroretinitis
Authors: Teodoru Cosmin Adrian , Dura Horațiu , Roman Mihai Dan , Hașegan Adrian , Tănăsescu Ciprian , Moisin Andrei , Giurgiu Doina Ileana , Vică Mihaela Laura , Stanca Horia , Cerghedean-Florea Maria-Emilia , Suteu Corina
Published: October 2024

Background/Objectives: Neuroretinitis (NR) is a rare inflammatory condition characterized by sudden vision loss, optic disc edema and macular star appearance predominantly affecting individuals in their third and fourth decades of life. Methods: This paper describes the case of 33-year-old Caucasian man with no significant medical history complaining of decreased vision for about a week. Results: The ophthalmological exam revealed best-corrected visual acuity (BCVA) for the right eye (RE) of 0.8 (decimal notation) and of 0.9 for the left eye (LE). Intraocular pressure (IOP) was 20 mmHg in RE and 18 mmHg in LE. Slit-lamp examination of both eyes (OU) showed no evidence of intraocular inflammation in the anterior chamber or vitreous cavity. Examination of the posterior pole of the right eye showed bilateral papilledema with an incomplete macular fan pattern. Conclusions: Despite extensive laboratory tests, including serologic and imaging investigations, a definitive etiology remained unclear. It is very important to differentiate NR from other optic nerve disorders, requiring careful clinical evaluation and observation of the evolution of symptoms.
B-Lines in the Assessment of Interstitial Lung Disease Associated with Scleroderma: The Role of Handheld Devices
Authors: Ancuța Codrina , Pomirleanu Cristina , Gănceanu Ecaterina , Man Milena Adina , Ancuta Eugen , Postolache Paraschiva
Published: October 2024

Background: Timely detection and aggressive management of interstitial lung disease (ILD) in systemic sclerosis (SSc) are essential to improving outcomes and reducing risks of irreversible lung injury. Objective: to explore the usefulness of an ultraportable ultrasound device for the management of SSc-related ILD and to compare it with clinical and instrumental data. Methods: A total of 19 consecutive SSc patients underwent a comprehensive pulmonary evaluation: clinical, pulmonary function tests (PFTs) (spirometry, DLCO), lung CT (1.5 mm slice thickness reconstruction; HRCT), and lung ultrasound (LUS). A total score was calculated based on the number of color-coded B-lines recorded for each lung sliding. B-lines were analyzed against dyspnea, cough, Velcro, CT imaging (Warrick’s score), and PFTs. Global and subgroup analysis were performed (diffuse versus limited cutaneous SSc, Warrick’s < 7 versus >7). Results: Symptomatic lung involvement with varying degrees of dyspnea was reported in about 74% of cases (functional NYHA > 2 in more than half), chronic dry cough in one-third, Velcro rales in 42%. A total of 84.24% were classified as SSc with ILD on CT imaging. Statistically significant mild-to-moderate correlations between B-lines and clinical manifestations were demonstrated, as well as PFTs and Warrick’s scores (more B-lines, lower pulmonary function, but higher extent and severity on CT) (p < 0.05); there were differences between SSc patients without and with ILD in terms of the number and distribution of B-lines (p < 0.05), as well as different B-lines patterns and numbers in diffuse versus limited SSc (p < 0.05). Conclusions: Ultraportable handheld LUS is a promising method suitable for the management (screening, early detection, and evaluation) of SSc patients.
Takotsubo Cardiomyopathy After Cytoreductive Surgery and Hyperthermic Intraperitoneal Chemotherapy for a Recurrent Colon Cancer: A Life-Threatening Complication
Authors: Moldovan Bogdan , Adam Iris-Iuliana , Pisică Radu-Mihai , Untaru Vlad , Stoica Doly , Șpac Alexandra , Modrigan Irina , Ursu Mihai , Jupoiu Liliana , Frâncu Adina , Pescaru Florentina , Hubeishie Amir , Zolog Adriana , Vecerzan Liliana
Published: October 2024

(1) Background: Takotsubo cardiomyopathy, or stress cardiomyopathy, is an acute heart failure condition with transient left ventricular (LV) motion abnormalities but no significant coronary artery obstruction. It mimics acute coronary syndrome (ACS), with symptoms like chest pain, dyspnea, and ECG changes. (2) Case Report: We present the case of a 44-year-old female with relapsed colon cancer and peritoneal carcinomatosis. After undergoing cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC), she experienced cardiac arrest from ventricular fibrillation 18 h postoperatively. Echocardiography revealed a reduced LV ejection fraction (20%) and apical akinesia, suggesting a Takotsubo Cardiomyopathy. Intensive resuscitation and inotropic support led to gradual recovery. Coronary angiography confirmed no coronary artery obstruction. (3) Discussion: This case highlights TTS as a rare but severe complication following major oncological surgeries, possibly triggered by both physical and emotional stressors. TTS should be considered in the differential diagnosis of perioperative cardiac events in cancer patients. (4) Conclusions: Prompt recognition and management of TTS in the perioperative period are crucial to improving outcomes, especially in high-risk oncological patients undergoing extensive surgeries.
Some Improvements on Good Lattice Point Sets
Authors: Lin Yu-Xuan , Yan Tian-Yu , Fang Kai-Tai
Published: October 2024

Good lattice point (GLP) sets are a type of number-theoretic method widely utilized across various fields. Their space-filling property can be further improved, especially with large numbers of runs and factors. In this paper, Kullback-Leibler (KL) divergence is used to measure GLP sets. The generalized good lattice point (GGLP) sets obtained from linear-level permutations of GLP sets have demonstrated that the permutation does not reduce the criterion maximin distance. This paper confirms that linear-level permutation may lead to greater mixture discrepancy. Nevertheless, GGLP sets can still enhance the space-filling property of GLP sets under various criteria. For small-sized cases, the KL divergence from the uniform distribution of GGLP sets is lower than that of the initial GLP sets, and there is nearly no difference for large-sized points, indicating the similarity of their distributions. This paper incorporates a threshold-accepting algorithm in the construction of GGLP sets and adopts Frobenius distance as the space-filling criterion for large-sized cases. The initial GLP sets have been included in many monographs and are widely utilized. The corresponding GGLP sets are partially included in this paper and will be further calculated and posted online in the future. The performance of GGLP sets is evaluated in two applications: computer experiments and representative points, compared to the initial GLP sets. It shows that GGLP sets perform better in many cases.
The Sense of Security and Comfort in Education—Development, Validation, and Interpretation of a New Questionnaire
Authors: Huber Matthias , Helm Christoph
Published: October 2024

The purpose of this study was to measure the sense of security and comfort (SSC) as a latent construct in compulsory education. Taking theoretical considerations into account, a questionnaire for primary and secondary schools was developed in several pre-studies and then empirically tested. The sample consisted of 1462 students from 17 schools and 87 classes (n = 1376) in Austria. For the validation, the structural equation modeling (SEM) approach was used to test the dimensional plausibility, the nomological plausibility, and the measurement invariance of the SSC, as well as to identify the central predictors of the SSC. The results indicate that the four-factor solution found is empirically valid and plausible against the background of the theoretical assumptions. Therefore, this study opens up the possibility of appropriately addressing this complex social emotion in the educational context in the future.
Teaching Statistics for the Social Sciences Using Active Learning: A Case Study
Authors: Douglas Daniel
Published: October 2024

US college students are typically required to take at least one mathematics or statistics course, either as part their major area of study, or as a general education requirement. College mathematics requirements are an obstacle for many college students. Active learning, a pedagogical approach that places emphasis on students’ collaborative work, has been shown to increase student learning and course success in STEM fields of study and in mathematics courses. Active learning has also been shown to be adaptable to courses involving computer software and programming, such as introductory statistics. This case study is based on the author’s experience implementing an active learning model in an introductory statistics course for students majoring in sociology and related social sciences. Results indicate that the active learning approach was adaptable to the structure and particular learning goals of the course. Students perceived greater learning relative to other courses despite doing less work outside of class, and attributed this to the active learning structure of the course. These findings align with more systematic studies on the impacts of active learning in science and mathematics courses.
Cloud-Based Automatic Configuration and Disaster Recovery of Communication Systems Applied in Engineering Training
Authors: Morillo Reina J. D. , Mateo Sanguino T. J.
Published: October 2024

Network management and troubleshooting require not only a grasp of advanced concepts but also the development of analytical and problem-solving skills. To bridge this gap, this paper introduces a novel network administration system, DRACSC (Spanish acronym for device for automatic recovery and configuration of communication systems), designed for the automatic configuration and disaster recovery of communication equipment. This system transcends the limitations of current hardware and software solutions by combining their advantages, boasting portability, automated functions, and a cloud-based repository as its main features. The DRACSC system, undergoing a comprehensive large-scale evaluation involving diverse user groups across multiple institutions, was tested with 89 users, including students and teachers at educational centers and ICT (Information and Communication Technology) professionals. The benefits of the system were evaluated through a training program based on simulated real-world ICT environments, focusing on both quantitative results on the reduction in time to complete user tasks, as well as qualitative results on the interface and usability of the system. Statistical analysis, including Welch’s t-test on opinion surveys, indicated a significant increase in knowledge and understanding, demonstrating the system’s potential to enhance education and practice. Moreover, the evaluation shed light on the user experience, with positive impacts observed for learning and teaching implications. As a result, the study has verified that the system has the potential to significantly influence network management practices, enhancing both learning and professional application through improved efficiency and usability.
Smart Sleep Monitoring: An Integrated Application for Tracking and Analyzing Babies’ Sleep—BabyCare
Authors: Beňo Lukáš , Kučera Erik , Bašista Matej
Published: October 2024

This article presents an innovative application designed to assist parents in monitoring and analyzing their children’s sleep patterns, contributing to insights into their health and development. The application integrates a hardware solution that captures sleep data through sensors. These data are then processed, analyzed, and securely stored in a cloud database. Key features of the application include real-time monitoring of the child’s sleep status, historical sleep data visualization through graphical representations, and alert notifications for any detected abnormalities. The system offers a comprehensive tool for parents to ensure the well-being of their children by providing valuable sleep-related information.
Design of Voltage–Current Reference Source in CMOS Technology
Authors: Borejko Tomasz , Pleskacz Witold Adam
Published: October 2024

A design methodology for a resistorless low-power two-in-one voltage and current reference source working in subthreshold and moderate regions is described. The presented novel universal reference voltage–current source was implemented in ten different designs for seven different CMOS technologies. Six versions of these designs were silicon-proven using four different CMOS technologies. The example of implementation in 130 nm technology provides a reference current of 5 µA and reference voltage of 800 mV at supply voltages ranging from 0.9 V to 2.0 V with a total current consumption of 15 µA. The proposed circuit occupies a 1200 µm2 chip area and achieves 280 and 118 ppm/°C for all process corners and temperature variation from −40 °C to 125 °C. The power supply rejection ratio of output IREF without any filtering capacitor at 100 Hz and 10 MHz is 128 dB and 100 dB, respectively. The equivalent output current noise in the bandwidth from 1 Hz to 10 MHz reaches 9.1 nARMS.
A Classification and Segmentation Model for Diamond Abrasive Grains Based on Improved Swin-Unet-SAM
Authors: Lin Yanfen , Fan Tinghao , Fang Congfu
Published: October 2024

The detection of abrasive grain images in diamond tools serves as the foundation for assessing the overall condition of the tools, encompassing crucial aspects of diamond abrasive grains like the quantity, size, morphology, and distribution. Given the intricate background textures and reflective characteristics exhibited by diamond images, diamond detection and segmentation pose a significant challenge. Recently, numerous defect detection methods based on machine learning and deep learning have emerged. However, several issues persist, such as detection accuracy and the interference caused by intricate background textures. The present work demonstrates an efficient classification and segmentation network algorithm that combines Swin-Unet with SAM (Segment Anything Model) to alleviate the existing problems. Specifically, four embedding structures were devised to bridge the two models for iterative training. The transformer blocks within the Swin-Unet model were enhanced to facilitate classification and coarse segmentation, and the mask structure in SAM was refined to enable fine segmentation. The experimental results show that under a small sample dataset with complex background textures, the average index values of ACC (accuracy), SE (Sensitivity), and DSC (Dice Similarity Coefficient) for the classification and segmentation of diamond abrasive grains reached 98.7%, 92.5%, and 85.9%, respectively. Compared with the model before improvement, its ACC, SE and DSC increased by 1.2%, 15.9%, and 7.6%, respectively. The test results, based on four different datasets, consistently indicated that this model has excellent segmentation performance and robustness and has great application potential in the industrial field.
Linguistic Secret Sharing via Ambiguous Token Selection for IoT Security
Authors: Gao Kai , Horng Ji-Hwei , Chang Ching-Chun , Chang Chin-Chen
Published: October 2024

The proliferation of Internet of Things (IoT) devices has introduced significant security challenges, including weak authentication, insufficient data protection, and firmware vulnerabilities. To address these issues, we propose a linguistic secret sharing scheme tailored for IoT applications. This scheme leverages neural networks to embed private data within texts transmitted by IoT devices, using an ambiguous token selection algorithm that maintains the textual integrity of the cover messages. Our approach eliminates the need to share additional information for accurate data extraction while also enhancing security through a secret sharing mechanism. Experimental results demonstrate that the proposed scheme achieves approximately 50% accuracy in detecting steganographic text across two steganalysis networks. Additionally, the generated steganographic text preserves the semantic information of the cover text, evidenced by a BERT score of 0.948. This indicates that the proposed scheme performs well in terms of security.
A Study of Recommendation Methods Based on Graph Hybrid Neural Networks and Deep Crossing
Authors: Hai Yan , Wang Dongyang , Liu Zhizhong , Zheng Jitao , Ding Chengrui
Published: October 2024

In the face of complex user behavior patterns and massive data, improving the performance of recommender system models is an urgent challenge. Traditional methods often struggle to effectively handle feature interactions and complex user-item relationships. Combining the advantages of graph neural networks and the Deep Crossing network, this paper proposes a recommendation method based on hybrid neural networks with Deep Crossing (Deep Crossing with Graph Convolution and GRU, DCGCN-GRU). First, by constructing the graph structure of users and items, higher-order feature representations are extracted, and node features are updated using a multilayer graph convolution operation. Then, the higher-order features learned by the graph convolution network are spliced and weighted with the original features to form new feature inputs. Next, a Gated Recurrent Unit (GRU) is introduced to capture the inter-feature temporal dynamic relationships and sequence information. Finally, the Deep Crossing model is utilized to learn the interactions between the fused features at multiple levels and enhance the interactions between the features. Comparative experiments on three public datasets, MovieLens-ml-25m, Book-Crossings, and Amazon Reviews’23, show that the model achieves significant improvements in accuracy, mean square error (MSE), and mean absolute error (MAE).
Hybridization of Concentrated Solar Thermal, Geothermal, and Biomass: Case Study on Kizildere-2 Geothermal Power Plant
Authors: Celebi Bertug , Rohani Shahab , Derin-Güre Pınar , Chandler Nicholas , Hazar Tuğrul , Halaçoğlu Ural , Baker Derek
Published: October 2024

The usage of fossil fuel in the energy sector is the primary factor for global GHG emissions, so it is crucial to better utilize RE sources. One way to do that is to hybridize RE technologies to make up for their deficiencies while enabling a more synergistic power production. This study utilizes such an approach to hybridize the KZD-2 Geothermal Power Plant (GPP) with CST and biomass in the southwest region of Turkiye. The main motivation is to address the two main issues of GPPs—excess turbine capacities happening over the operating years and decreasing performance during hot summer months—while also increasing the flexibility of KZD-2. A topping cycle of CST–biomass is added utilizing a PTC field as the CST technology and olive residual biomass combustion as the biomass technology. The hybrid plant is simulated on TRNSYS, and the energetic data show that it is possible to generate more than 20 MWe of additional power during sunny and clear sky conditions while also increasing the Capacity Factor (CF) from 69% to 74–76%. Moreover, the financial results show that the resulting LCOAE is 81.19 USD/MWh, and the payback period is five or nine years for using the YEKDEM incentive or the spot market prices, respectively.
Effect of Temperature and Electric Field Strength on Carrier Mobility of Oil-Impregnated Pressboard Under DC Voltage
Authors: Deng Jun , Xie Zhicheng , Ge Hao , Xue Xiaoqiang , Gao Chunjia , Cheng Jianwei , Zhou Haibin , Pan Zhicheng , Lyu Gang , Wu Heng
Published: October 2024

The influence of carrier mobility on the space charge transport behavior inside the oil-impregnated pressboard insulation of converter transformers cannot be neglected. However, at present, current knowledge is usually derived from empirical or theoretical values, lacks experimental studies, and often ignores the effects of temperature and field strength under actual operating conditions. In this paper, based on the variable-temperature surface potential decay (SPD) method, a carrier mobility measurement platform for oil-impregnated pressboard is established, and the carrier mobility values for different combinations of oil and oil-impregnated pressboard are obtained experimentally to analyze and reveal the influence mechanisms of temperature and field strength on the carrier mobility. The results indicate the following: (1) The positive and negative carrier mobilities of oil-impregnated pressboard are in the range of 10−12–10−13 m2·V−1·s−1, and the negative carrier mobility is always higher than the positive carrier mobility. (2) The carrier mobility is positively correlated with the changes of temperature and field strength, and when the temperature increases from 20 °C to 80 °C, the positive and negative carrier mobilities increase by 4.01 times and 4.72 times, respectively; when the field strength increases from 1 kV/mm to 7 kV/mm, the positive and negative carrier mobility increases by 2.53 and 2.72 times, respectively. (3) The carrier mobility of the pressboard with a higher oil absorption rate changes more significantly with temperature; when the field strength is 7 kV/mm and the temperature increases from 20 °C to 80 °C, the positive polarity carrier mobility increases from 3.96 × 10−13 m2·V−1·s−1 to 2.64 × 10−11 m2·V−1·s−1, an increase of 66.67 times, while the increase in the carrier mobility of the pressboard with a lower oil absorption rate is only 1.59 times. (4) The carrier mobility of the naphthenic transformer oil-impregnated pressboard is higher than that of the paraffin-based transformer oil-impregnated pressboard, and the carrier mobility of two kinds of naphthenic transformer oil-impregnated pressboard is 3.16 times and 2.47 times higher than that of the paraffin-based transformer oil-impregnated pressboard, respectively, under the conditions of 60 °C and 7 kV/mm. (5) Utilizing the Darcy model and microscopic scanning results of the pressboard morphology, it was revealed that permeability and fiber structure are key factors influencing the variation in carrier mobility. The research results of this paper can provide theoretical basis for the calibration and optimization of the oil-pressboard insulation structure of converter transformers.
Leveraging the Synergy of Digital Twins and Artificial Intelligence for Sustainable Power Grids: A Scoping Review
Authors: Ranawaka Ama , Alahakoon Damminda , Sun Yuan , Hewapathirana Kushan
Published: October 2024

As outlined by the International Energy Agency, 44% of carbon emissions in 2021 were attributed to electricity and heat generation. Under this critical scenario, the power industry has adopted technologies promoting sustainability in the form of smart grids, microgrids, and renewable energy. To overcome the technical challenges associated with these emerging approaches and to preserve the stability and reliability of the power system, integrating advanced digital technologies such as Digital Twins (DTs) and Artificial Intelligence (AI) is crucial. While existing research has explored DTs and AI in power systems separately, an overarching review of their combined, synergetic application in sustainable power systems is lacking. Hence, in this work, a comprehensive scoping review is conducted under the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). The main results of this review analysed the breadth and relationships among power systems, DTs, and AI dynamics and presented an evolutionary timeline with three distinct periods of maturity. The prominent utilisation of deep learning, supervised learning, reinforcement learning, and swarm intelligence techniques was identified as mainly constrained to power system operations and maintenance functions, along with the potential for more sophisticated AI techniques in computer vision, natural language processing, and smart robotics. This review also discovered sustainability-related objectives addressed by AI-powered DTs in power systems, encompassing renewable energy integration and energy efficiency, while encouraging the investigation of more direct efforts on sustainable power systems.