bluuebunny/crossref_metadata_2025 huggingface dataset:
Catch the Cyber Thief: A Multi-Dimensional Asymmetric Network Attack–Defense Game
Authors: Wang Wenhao , Chen Xingguo , Li Yuwei , Zhu Cheng
Published: October 2024

This paper presents a novel multi-dimensional asymmetric game model for network attack–defense decision-making, called “Catch the Cyber Thief”. The model is built upon the concept of partially observable stochastic games (POSG) and is designed to systematically incorporate multi-dimensional asymmetry into network attack–defense problems. The attack agent is called a “thief” who wants to control a key host by exploring the unfamiliar network environment, and the defense agent is called a “police” who needs to catch the opponent before its goal is accomplished. The results indicate that the asymmetry of network attack and defense is not only influenced by attack and defense strategies but also by spatio-temporal factors such as the attacker’s initial position, network topology, and defense lag time. In addition, we have found that there may exist the “attack rhythm,” which makes “how to maintain a good attack rhythm” and “how to generate a robust defense strategy against different attackers” worth exploring. Compared with existing attack–defense game models, our game model can better generate a direct mapping relationship with real elements, enabling us to understand network attack and defense interactions better, recognize security risks, and design defense strategies that can directly serve real-world decision-making.
Investigating the Impact of Random Field Element Size on Soil Slope Reliability Analysis
Authors: Sun Jiewen , Guan Hong , Sun Boyan , Wan Yukuai
Published: October 2024

The determination of the optimal random field element (RFE) size is crucial in soil slope reliability analysis as it governs the trade-off between precision in failure probability calculations and computational efficiency. Given the substantial computational burden associated with smaller RFE sizes, studies on their impact on slope failure probability are scarce. This research examines the influence of RFE size on failure probability and safety factor, employing the Karhunen–Loève expansion to generate random fields and integrating the simplified Bishop method with particle swarm optimization (PSO) to assess slope stability. Through Monte Carlo Simulation (MCS), this study investigates the effects of the ratio of slope height to RFE size (H/De) on slope reliability metrics across two illustrative cases. Results reveal a notable influence of H/De on the distribution of safety factors (Fs) and failure probability (PF), with overestimation observed at smaller H/De ratios. When H/De exceeds 10 for Example 1 and 15 for Example 2, the Fs distribution patterns in both scenarios stabilize significantly, displaying minimal variability. The PF of Example 1 and Example 2 decreases with the increase of H/De and remains basically unchanged when H/De exceeds 10 and 15, respectively. Consequently, a recommended H/De ratio of 20 is proposed based on the analyzed cases, facilitating accurate calculations while mitigating computational overhead.
Use of Wireless Sensor Networks for Area-Based Speed Control and Traffic Monitoring
Authors: Rychlicki Mariusz , Kasprzyk Zbigniew , Pełka Małgorzata , Rosiński Adam
Published: October 2024

This paper reviews the potential of low-power wireless networks to improve road safety. The authors characterized this type of network and its application in road transport. They also presented the available technologies, highlighting one that was considered the most promising for transport applications. The study includes an innovative and proprietary concept of area-based vehicle speed monitoring using this technology and describes its potential for enhancing road safety. Assumptions and a model for the deployment of network equipment within the planned implementation area were developed. Using radio coverage planning software, the authors conducted a series of simulations to assess the radio coverage of the proposed solution. The results were used to evaluate the feasibility of deployment and to select system operating parameters. It was also noted that the proposed solution could be applied to traffic monitoring. The main objective of this paper is to present a new solution for improving road safety and to assess its feasibility for practical implementation. To achieve this, the authors conducted and presented the results of a series of simulations using radio coverage planning software. The key contribution of this research is the authors′ proposal to implement simultaneous vehicle speed control across the entire monitored area, rather than limiting it to specific, designated points. The simulation results, primarily related to the deployment and selection of operating parameters for wireless sensor network devices, as well as the type and height of antenna placement, suggest that the practical implementation of the proposed solution is feasible. This approach has the potential to significantly improve road safety and alter drivers′ perceptions of speed control. Additionally, the positive outcomes of the research could serve as a foundation for changing the selection of speed control sites, focusing on areas with the highest road safety risk at any given time.
Efficient Estimation of Synthetic Indicators for the Assessment of Nonlinear Systems Quality
Authors: Burrascano Pietro , Di Schino Andrea , Versaci Mario
Published: October 2024

The availability of synthetic indicators of the degree and type of nonlinearity in systems is used in various fields to assess system quality or to highlight possible malfunctions. Different distortion or damage indexes are synthetic measures designed (and standardized) to evaluate the frequency trend of specific aspects resulting from the nonlinear behavior of the system under consideration. The different measures of deviation from linear behavior quantitatively consider the system and its nonlinearity characteristics; they were defined according to practically feasible measurement methodologies and the various aspects of the system’s nonlinearity that needed to be highlighted. In parallel, techniques for representing and modeling nonlinear systems have been defined, capable of describing the system in a more general way, attempting to capture its input–output characteristics by varying the level of stress to which the system is subjected. Numerous modeling techniques have been proposed, aimed at representing the nonlinear behavior of physical devices. In this paper, after an extensive description of the Hammerstein model identification technique based on swept sinusoidal signals, we show how the nonlinear model of the system can be used to obtain accurate estimates of the parameter aimed at describing the nonlinearity characteristics of the system. This extensive description makes it possible to point out that the same Hammerstein model can be obtained not only from a single type of excitation, but it is shown that the identification technique can be extended to input signals of different types. The description of the method also makes clear the motivation behind the introduction of the proposed original technique for estimating, from a single measurement, the model parameters of the nonlinear system—and from these the synthetic estimators—relative to multiple values of the input signal amplitude, thus enabling a considerable increase in the estimation efficiency of these parameters. The proposed technique is verified with both synthetic and laboratory experiments, demonstrating the effectiveness of the method in evaluating nonlinear system parameters, distortion estimates, and parameters defined for an early detection of defects of the structure.
ARISE—The Accuracy Evaluation of a Patient-Specific 3D-Printed Biopsy System Based on MRI Data: A Cadaveric Study
Authors: Möbius Robert , Winkler Dirk , Kropla Fabian , Müller Marcel , Scholz Sebastian , Güresir Erdem , Grunert Ronny
Published: October 2024

Background: Brain biopsy is required for the accurate specification and further diagnosis of intracranial findings. The conventional stereotactic frames are used clinically for biopsies and offer the highest possible precision. Unfortunately, they come with some insurmountable technical and logistical limitations. The aim of the present work is to determine the clinical precision in the needle biopsy of the human brain using a new patient-specific stereotactic navigation device based on 3D printing. Methods: MRI data sets of human cadaver heads were used to plan 32 intracranial virtual biopsy targets located in different brain regions. Based on these data, 16 individualized stereotactic frames were 3D-printed. After the intraoperative application of the stereotactic device to the cadaver’s head, the actual needle position was verified by postoperative CT. Results: Thirty-two brain areas were successfully biopsied. The target point accuracy was 1.05 ± 0.63 mm, which represents the difference between the planned and real target points. The largest target point deviation was in the coronal plane at 0.60 mm; the smallest was in the transverse plane (0.45 mm). Conclusions: Three-dimensional-printed, personalized stereotactic frames or platforms are an alternative to the commonly used frame-based and frameless stereotactic systems. They are particularly advantageous in terms of accuracy, reduced medical imaging, and significantly simplified intraoperative handling.
Cardiac Function and Structure before and after Mild SARS-CoV-2 Infection in Elite Athletes Using Biventricular and Left Atrial Strain
Authors: Schellenberg Jana , Matits Lynn , Bizjak Daniel A. , Jenkins Freya S. , Kersten Johannes
Published: October 2024

Background/Objectives: Myocardial involvement has been observed in athletes following SARS-CoV-2 infection. It is unclear if these changes are due to myocardial damage per se or to an interruption in training. The aim of this study was to assess cardiac function and structure in elite athletes before and after infection (INFAt) and compare them to a group of healthy controls (CON). Methods: Transthoracic echocardiography was performed in 32 elite athletes, including 16 INFAt (median 21.0 (19.3–21.5) years, 10 male) before (t0) and 52 days after (t1) mild SARS-CoV-2 infection and 16 sex-, age- and sports type-matched CON. Left and right ventricular global longitudinal strain (LV/RV GLS), RV free wall longitudinal strain (RV FWS) and left atrial strain (LAS) were assessed by an investigator blinded to patient history. Results: INFAt showed no significant changes in echocardiographic parameters between t0 and t1, including LV GLS (−21.8% vs. −21.7%, p = 0.649) and RV GLS (−29.1% vs. −28.7%, p = 0.626). A significant increase was observed in LA reservoir strain (LASr) (35.7% vs. 47.8%, p = 0.012). Compared to CON, INFAt at t1 had significantly higher RV FWS (−33.0% vs. −28.2%, p = 0.011), LASr (47.8% vs. 30.5%, p < 0.001) and LA contraction strain (−12.8% vs. −4.9%, p = 0.050) values. Conclusions: In elite athletes, mild SARS-CoV-2 infection does not significantly impact LV function when compared to their pre-SARS-CoV-2 status and to healthy controls. However, subtle changes in RV and LA strain may indicate temporary or training-related adaptions. Further research is needed, particularly focusing on athletes with more severe infections or prolonged symptoms.
Advancements in Hyperspectral Imaging and Computer-Aided Diagnostic Methods for the Enhanced Detection and Diagnosis of Head and Neck Cancer
Authors: Wu I-Chen , Chen Yen-Chun , Karmakar Riya , Mukundan Arvind , Gabriel Gahiga , Wang Chih-Chiang , Wang Hsiang-Chen
Published: October 2024

Background/Objectives: Head and neck cancer (HNC), predominantly squamous cell carcinoma (SCC), presents a significant global health burden. Conventional diagnostic approaches often face challenges in terms of achieving early detection and accurate diagnosis. This review examines recent advancements in hyperspectral imaging (HSI), integrated with computer-aided diagnostic (CAD) techniques, to enhance HNC detection and diagnosis. Methods: A systematic review of seven rigorously selected studies was performed. We focused on CAD algorithms, such as convolutional neural networks (CNNs), support vector machines (SVMs), and linear discriminant analysis (LDA). These are applicable to the hyperspectral imaging of HNC tissues. Results: The meta-analysis findings indicate that LDA surpasses other algorithms, achieving an accuracy of 92%, sensitivity of 91%, and specificity of 93%. CNNs exhibit moderate performance, with an accuracy of 82%, sensitivity of 77%, and specificity of 86%. SVMs demonstrate the lowest performance, with an accuracy of 76% and sensitivity of 48%, but maintain a high specificity level at 89%. Additionally, in vivo studies demonstrate superior performance when compared to ex vivo studies, reporting higher accuracy (81%), sensitivity (83%), and specificity (79%). Conclusion: Despite these promising findings, challenges persist, such as HSI’s sensitivity to external conditions, the need for high-resolution and high-speed imaging, and the lack of comprehensive spectral databases. Future research should emphasize dimensionality reduction techniques, the integration of multiple machine learning models, and the development of extensive spectral libraries to enhance HSI’s clinical utility in HNC diagnostics. This review underscores the transformative potential of HSI and CAD techniques in revolutionizing HNC diagnostics, facilitating more accurate and earlier detection, and improving patient outcomes.
Effect of Surface Morphology and Internal Structure on the Tribological Behaviors of Snake Scales from Dinodon rufozonatum
Authors: Shi Ge , Wang Jinhao , Dong Yuehua , Hu Song , Zheng Long , Ren Luquan
Published: October 2024

Snakes can move freely on land, in lakes, and in other environments. During movement, the scales are in long-term contact with the external environment, providing protection to the body. In this study, we evaluated the mechanical properties and scratching performance of the ventral and dorsal scales from Dinodon rufozonatum, a generalist species that moves on both land and in streams under wet and dry conditions. The results showed that the elastic modulus and hardness of the dry scales were greater than those of the wet scales. The average scale friction coefficient under wet conditions (0.1588) was 9.3% greater than that under dry conditions (0.1453). The scales exhibit brittle damage in dry environments, while in wet environments, ductile damage is observed. This adaptation mechanism allows the scales to protect the body by dissipating energy and reducing stress concentration, ensuring efficient locomotion and durability in both terrestrial and aquatic environments. Understanding how this biomaterial adapts to environmental changes can inspire the development of bionic materials.
Sharing and Allocation in Preschool Children: The Roles of Theory of Mind, Anticipated Emotions, and Consequential Emotions
Authors: Shi Yingdi , Zhang Mengnan , Zhu Liqi
Published: October 2024

This study investigates the impact of theory of mind, anticipated emotions before actual behavior, and consequential emotions following the behavior on sharing and allocation behavior in 4–6-year-old children. In Experiment 1, 95 children were randomly assigned to three conditions (external emotion expectancy condition, internal emotion expectancy condition, and control condition) to explore the role of cognition and emotions in children’s sharing and allocation behaviors. Experiment 2 employed a dictator game to further validate the influence of theory of mind and consequential emotions on behavior. The findings indicated that both anticipated and consequential emotions influence sharing behavior, but neither serves as a key predictor of allocation behavior. Theory of mind influences children’s sharing behavior and is related to the fairness of allocation. Children with higher levels of theory of mind tend to rate consequential emotions more positively, while those with lower ratings of consequential emotions are more likely to reconsider sharing after reflection. Notably, theory of mind and emotional factors demonstrate distinct motivational effects on children’s prosocial sharing and resource allocation, with negative emotions exhibiting a more pronounced impact on decision-making processes.
Clinical and Histopathological Features of Thyroid Cancer with TERT Promoter Molecular Alterations in Isolation Versus with Concurrent Molecular Alterations: A Multicenter Retrospective Study
Authors: Steinberg Emily , Dimitstein Orr , Morand Grégoire B. , Forest Véronique-Isabelle , da Silva Sabrina D. , Pusztaszeri Marc , Alohali Sama , Payne Richard J.
Published: October 2024

Background/Objectives: Molecular testing of thyroid nodules enables the detection of genetic alterations, which can help assess the risk of malignancy and tumor behavior. While telomerase reverse transcriptase (TERTp) mutations are known to be associated with aggressive disease, their exact prognostic significance when occurring alone or with other molecular alterations remains underreported. Methods: This study examined patients with thyroid cancer treated at two tertiary care hospitals from 2017 to 2024. We compared tumor behavior in patients with TERTp molecular alterations occurring alone and with concurrent molecular alterations. Aggressive histologic subtypes were defined as tall-cell, hobnail, and columnar variants of papillary carcinoma, as well as poorly differentiated and anaplastic carcinoma. High-risk disease was defined according to the 2015 ATA guidelines as gross extrathyroidal extension, lymph node metastasis >3 cm, postoperative elevated serum thyroglobulin, distant metastases, and/or positive resection margins. Statistical analysis was performed to assess differences between groups. Results: 30 patients with TERTp-positive thyroid malignancies were included. TERTp/BRAF V600E was the most prevalent mutation combination (n = 13, 43.3%), followed by TERTp alone (n = 8, 26.7%) and TERTp/RAS (n = 7, 23.4%). TERTp/EIF1AX/GNAS and TERTp/EIF1AX/PIK3CA were the least common combinations (n = 1, 3.3% each). Nodules with TERTp and concurrent mutations were significantly more likely to be classified as high-risk (p = 0.006) and were more frequently associated with aggressive histologic subtypes (p = 0.003) compared to those with TERTp mutations alone, which tended to exhibit more benign behavior. Conclusions: Thyroid carcinomas harboring both TERTp and concurrent molecular alterations are associated with more aggressive features and a higher likelihood of being classified as high-risk. In contrast, TERTp mutations occurring alone do not confer an elevated risk.
Enhanced Photocatalytic Activity in Photocatalytic Concrete: Synthesis, Characterization, and Comprehensive Performance Assessment of Nano-TiO2-Modified Recycled Aggregates
Authors: Zhang Xiucheng , Chen Weizhi , Lin Wencong , Zheng Jiansheng , Yan Guohui , Chen Xuefei
Published: October 2024

This study presents an exhaustive exploration into the development and rigorous evaluation of nano-TiO2-modified recycled aggregates (NT@RAs) as an environmentally sustainable substitute for natural aggregates in concrete applications. A methodical framework was devised for the synthesis and thorough characterization of NT@RAs, emphasizing the optimization of nano-TiO2 loading onto the RA surface and within its intricate porous structure. The investigation encompassed three distinct types of recycled aggregates: recycled glass sands (RGSs), recycled clay brick sands (RCBSs), and recycled concrete sands (RCSs). Of particular interest, NT@RGS, with its properties of an inherently smooth surface texture and low water absorption, was found to exert a favorable influence on the rheological behavior of concrete, manifested in reduced yield stress, thereby underscoring the potential for fine-tuning mix designs to enhance workability. As the substitution levels of NT@RGS and NT@RCBS escalated, an initial decrement in compressive strength was discernible, which subsequently reversed to strength restoration at optimized substitution ratios. This phenomenon is attributed to the synergistic interplay among NT@RA components. Remarkably, NT@RA-incorporated concrete demonstrated unparalleled self-cleaning abilities, surpassing the performance of concrete with direct nano-TiO2 powder incorporation. This comprehensive research contributes significantly to the advancement in sustainable, high-performance photocatalytic construction materials within the realm of concrete technology. It underscores the potential for enhancing not only the rheological and mechanical properties but also the environmental responsiveness of concrete through the innovative utilization of NT@RAs.
Hydrogenation Studies of Iridium Pyridine Diimine Complexes with O- and S-Donor Ligands (Hydroxido, Methoxido and Thiolato)
Authors: Völker Max , Schreyer Matthias , Burger Peter
Published: October 2024

For square-planar late transition metal pyridine, diimine (Rh, Ir) complexes with hydro-xido, methoxido, and thiolato ligands. We could previously establish sizable metal-O- and S π-bonding interactions. Herein, we report the hydrogenation studies of iridium hydroxido and methoxido complexes, which quantitatively lead to the trihydride compound and water/methanol. The iridium trihydride displays a highly fluctional structure with scrambling hydrogen atoms, which can be described as a dihydrogen hydride system based on NMR and DFT investigations. This contrasts the iridium sulfur compounds, which are not reacting with dihydrogen. According to DFT and LNO-CCSD(T) calculations, hydrogenation of the methoxido complex proceeds by a two-step mechanism, i.e., an oxidative addition step of H2 to an Ir(III) dihydride intermediate with consecutive reductive O-H elimination of methanol. Based on PNO-CCSD(T) calculations, the reactivity difference between the O- and S-donors can be traced to the stronger H-O bonds in the water/methanol products compared to the S-H bonds in the sulphur congeners, which serves as a driving force for hydrogenation.
A Feasibility Study of a Music Enrichment Program on Relative Reinforcing Value of Food and Home Environmental Enrichment among Families of Low Socioeconomic Status
Authors: Kong Kai-Ling , Smith Amy R. , Salley Brenda , Hanson-Abromeit Deanna , Engel Hideko , Serwatka Catherine A.
Published: October 2024

Background: Emerging evidence suggests that low socioeconomic status (SES) home environments may play a role by promoting excess energy intake through a lack of access to non-food reinforcers. Because of the deleterious effects of SES-related disparities on child health and development, feasible and culturally acceptable interventions are urgently needed. Community-based music enrichment programs may be an ideal intervention strategy. Methods: In collaboration with a local non-profit organization and music studio, we conducted a pilot randomized controlled trial to assess the effects of a music enrichment program versus a play date control in a group of 9–24-month-old healthy infants (N = 16). The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of Children’s Mercy Hospital Kansas City. This study is registered with clinicaltrials.gov (NCT05868811). Results: Overall, we found some intervention effects on the relative reinforcing value of food (RRVfood) and the home environmental enrichment measures (i.e., increased music use at home and the home language environment). Our intervention demonstrated large effects on the increased use of music at home. We did not find significant group differences in the RRVfood and home language environment, but some of the effect sizes were medium-to-large. Results also suggest that our intervention is feasible and acceptable. Parent feedback indicated that the intervention was well-liked and that the steps we took to help reduce barriers worked. Conclusions: Music enrichment programs may be a high-impact, low-cost strategy to address socioeconomic disparities.
Thymol-Loaded Polymeric Nanocapsules’ Repellent Activity on Nymphs of Rhipicephalus sanguineus Sensu Lato
Authors: Sales Amanda M. R. , Pereira Gessyka R. S. , Lima Lais C. N. , Monteiro Caio M. O. , Matos Breno N. , Taveira Stephânia F. , Cunha-Filho Marcilio , Gelfuso Guilherme M. , Gratieri Tais
Published: October 2024

Thymol-loaded polymeric nanocapsules were developed in this study to control volatilization and drug release for repellent application on Rhipicephalus sanguineus nymphs. Policaprolactone-loaded nanocapsules were prepared and characterized by diameter, PdI, zeta potential, pH, entrapment efficiency, and thymol content. Moreover, drug release, skin permeation profile, and repellent activity were evaluated. Nanocapsules showed a mean diameter of 195.7 ± 0.5 nm, a PdI of 0.20 ± 0.01, a zeta potential of −20.6 ± 0.3 mV, a pH of 4.7 ± 0.1, and an entrapment efficiency and a thymol content of 80.1 ± 0.1% and 97.9 ± 0.2%, respectively. The nanosystem progressively released 68.6 ± 2.3% of the thymol over 24 h, demonstrating that it can control drug release. Thymol-loaded nanocapsules showed less epidermis penetration upon skin application than pure thymol (control). Moreover, nanocapsules showed 60–70% repellency for 2 h against Rhipicephalus sanguineus nymphs. Thus, the nanocapsules proved to be a promising alternative for use as an arthropod repellent.
Numerical Investigation of Film Formation Characteristics and Mechanisms through Airless Spraying on Spherical Surfaces
Authors: Wu Zhaojie , Wang Chuanshuo , Yang Guichun , Chen Shiming , Duan Jimiao , Chen Yan
Published: October 2024

This paper focuses on key engineering issues, particularly the overall turbulent transport of paint spray and coating film distribution characteristics, in the process of airless spraying film formation. By deeply considering the geometric features of spherical surfaces and their impact on the near-wall region of the flow field, an airless spraying film formation model consisting of the Eulerian multiphase model, the realizable k–ε turbulence model, and the Eulerian Wall Film model was established. Through numerical simulations of static spraying on the inner and outer walls of spherical surfaces with different radii, the influence of geometric features on the spray flow field and film formation characteristics on spherical surfaces was investigated. Subsequently, based on numerical simulations of dynamic spraying on different nozzle trajectories, the film formation characteristics were analyzed, and the optimal spray trajectory planning method was determined. Additionally, this study examined the coating distribution characteristics during dynamic spraying on spherical surfaces with varying geometric dimensions. Finally, a kind of chlorinated rubber anti-corrosion primer was chosen to carry out spraying experiments, which validated that the airless spray coating model and the corresponding numerical simulation methods established in this paper were reasonable and feasible for investigating the film formation characteristics on spherical surfaces. This work is expected to further promote the application of airless spray techniques in machinery, automotive, shipbuilding, and aviation industries.
Sustainable Near-Infrared Reflective Blue Pigments: Recycled Aluminum from Can Seals for Cobalt Aluminates in Cool Coatings
Authors: Horsth Dienifer F. L. , Primo Julia de O. , Anaissi Fauze J. , Umek Polona , Bittencourt Carla
Published: October 2024

Inorganic cool pigments are widely used as cooling agents in residential coatings due to their ability to achieve near-infrared reflectance. These coatings can be designed to exhibit a variety of colors independent of their reflectivity and absorption properties. Recent studies have highlighted the development of novel near-infrared (NIR) blue pigments, with an increasing emphasis on environmentally sustainable options that demonstrate high NIR reflectivity. This trend highlights the importance of creating novel and eco-friendly NIR reflective blue pigments. This study presents the synthesis of cobalt aluminates with varying concentrations of coloring ions (Co2+), achieved through the recycling of aluminum can seals via chemical precipitation. The formation of the spinel phase was confirmed through X-ray diffraction (XRD), and a colorimetric analysis was performed in the CIEL*a*b* color space. The synthesized pigments exhibited high near-infrared solar reflectance, with R% values ranging from 34 to 54%, indicating their potential as energy-efficient color pigments for use in coatings.
Enhanced Neonatal Brain Tissue Analysis via Minimum Spanning Tree Segmentation and the Brier Score Coupled Classifier
Authors: Jaware Tushar Hrishikesh , Nayak Chittaranjan , Parida Priyadarsan , Ali Nawaf , Sharma Yogesh , Hadi Wael
Published: October 2024

Automatic assessment of brain regions in an MR image has emerged as a pivotal tool in advancing diagnosis and continual monitoring of neurological disorders through different phases of life. Nevertheless, current solutions often exhibit specificity to particular age groups, thereby constraining their utility in observing brain development from infancy to late adulthood. In our research, we introduce a novel approach for segmenting and classifying neonatal brain images. Our methodology capitalizes on minimum spanning tree (MST) segmentation employing the Manhattan distance, complemented by a shrunken centroid classifier empowered by the Brier score. This fusion enhances the accuracy of tissue classification, effectively addressing the complexities inherent in age-specific segmentation. Moreover, we propose a novel threshold estimation method utilizing the Brier score, further refining the classification process. The proposed approach yields a competitive Dice similarity index of 0.88 and a Jaccard index of 0.95. This approach marks a significant step toward neonatal brain tissue segmentation, showcasing the efficacy of our proposed methodology in comparison to the latest cutting-edge methods.
Enhancing Information Exchange in Ship Maintenance through Digital Twins and IoT: A Comprehensive Framework
Authors: Golovan Andrii , Mateichyk Vasyl , Gritsuk Igor , Lavrov Alexander , Smieszek Miroslaw , Honcharuk Iryna , Volska Olena
Published: October 2024

This article proposes a comprehensive framework for enhancing information exchange in ship maintenance through the integration of Digital Twins (DTs) and the Internet of Things (IoT). The maritime industry faces significant challenges in maintaining ships due to issues like data silos, delayed information flow, and insufficient real-time updates. By leveraging advanced technologies such as DTs and IoT, this framework aims to optimize maintenance processes, improve decision-making, and increase the operational efficiency of maritime vessels. Digital Twins create virtual replicas of physical assets, allowing for continuous monitoring, simulation, and prediction of ship conditions. Meanwhile, IoT devices enable real-time data collection and transmission from various ship components, facilitating a seamless flow of information. This integrated approach enhances predictive maintenance capabilities, reduces downtime, and improves resource allocation. The article will delve into the architecture of the proposed framework, implementation steps, and potential challenges, supported by case studies that demonstrate its practical application and benefits. By addressing these aspects, the framework aims to provide a robust solution for modernizing ship maintenance operations and ensuring the longevity and reliability of maritime assets.
Chiral, Topological, and Knotted Colloids in Liquid Crystals
Authors: Yuan Ye , Smalyukh Ivan I.
Published: October 2024

The geometric shape, symmetry, and topology of colloidal particles often allow for controlling colloidal phase behavior and physical properties of these soft matter systems. In liquid crystalline dispersions, colloidal particles with low symmetry and nontrivial topology of surface confinement are of particular interest, including surfaces shaped as handlebodies, spirals, knots, multi-component links, and so on. These types of colloidal surfaces induce topologically nontrivial three-dimensional director field configurations and topological defects. Director switching by electric fields, laser tweezing of defects, and local photo-thermal melting of the liquid crystal host medium promote transformations among many stable and metastable particle-induced director configurations that can be revealed by means of direct label-free three-dimensional nonlinear optical imaging. The interplay between topologies of colloidal surfaces, director fields, and defects is found to show a number of unexpected features, such as knotting and linking of line defects, often uniquely arising from the nonpolar nature of the nematic director field. This review article highlights fascinating examples of new physical behavior arising from the interplay of nematic molecular order and both chiral symmetry and topology of colloidal inclusions within the nematic host. Furthermore, the article concludes with a brief discussion of how these findings may lay the groundwork for new types of topology-dictated self-assembly in soft condensed matter leading to novel mesostructured composite materials, as well as for experimental insights into the pure-math aspects of low-dimensional topology.
Data Descriptor for “Understanding and Perception of Automated Text Generation among the Public: Two Surveys with Representative Samples in Germany”
Authors: Lermann Henestrosa Angelica , Kimmerle Joachim
Published: October 2024

With the release of ChatGPT, text-generating AI became accessible to the general public virtually overnight, and automated text generation (ATG) became the focus of public debate. Previously, however, little attention had been paid to this area of AI, resulting in a gap in the research on people’s attitudes and perceptions of this technology. Therefore, two representative surveys among the German population were conducted before (March 2022) and after (July 2023) the release of ChatGPT to investigate people’s attitudes, concepts, and knowledge on ATG in detail. This data descriptor depicts the structure of the two datasets, the measures collected, and potential analysis approaches beyond the existing research paper. Other researchers are encouraged to take up these data sets and explore them further as suggested or as they deem appropriate.
Perception and Reuse of Open Data in the Spanish University Teaching and Research Community
Authors: Vidal-Cabo Christian , Sánchez-Pérez Enrique Alfonso , Ferrer-Sapena Antonia
Published: October 2024

Introduction. Open Government is a form of public policy based on the pillars of collaboration and citizen participation, transparency and the right of access to public information. With the help of information and communication technologies, governments and administrations carry out open data initiatives, making reusable datasets available to all citizens. The academic community, highly qualified personnel, can become potential reusers of this data, which would lead to its use for scientific research, generating knowledge, and for teaching, improving the training of university students and promoting the reuse of open data in the future. Method. This study was developed using a quantitative research methodology (survey), which was distributed by email in one context block and six technical blocks, with a total of 30 questions. The data collection period was between 15 March and 10 May 2021. Analysis. The data obtained through this quantitative methodology were processed, normalised, and analysed. Results. A total of 783 responses were obtained, from 34 Spanish provinces. The researchers come from 47 Spanish universities and 21 research centres, and 19 research areas of the State Research Agency are represented. In addition, a platform was developed with the data for the purpose of visualising the results of the survey. Conclusions. The sample thus obtained is representative and the conclusions can be extrapolated to the rest of the Spanish university teaching staff. In terms of gender, the study is balanced between men and women (41.76% W vs. 56.58% M). In general, researchers responding to the survey know what open data is (79.31%) but only 50.57% reuse open data. The main conclusion is that open government data prove to be useful sources of information for science, especially in areas such as Social Sciences, Industrial Production, Engineering and Engineering for Society, Information and Communication Technologies, Economics and Environmental Sciences.
Acute Effect of Three Aerobic Exercise Intensities on Glomerular Filtration Rate in Healthy Older Adults
Authors: Trejo-Trejo Marina , Gómez-Miranda Luis M. , Ramos-Jiménez Arnulfo
Published: October 2024

No consensus exists on whether acute aerobic exercise alters the glomerular filtration rate in older adults. Objective: To assess the immediate effects of three aerobic exercise intensities on the estimated glomerular filtration rate (eGFR) in healthy, sedentary older adults. Methods: Eighteen healthy, sedentary older adults (ten men and eight women) voluntarily participated in this study. The participants underwent three standardized aerobic exercise tests (100%, 80%, and 60% of the maximal heart rate) on a bicycle ergometer. Blood samples were collected to determine cholesterol, triacylglycerols, glucose, serum creatinine (Cr), Cystatin C (CysC) concentrations, and eGFR. Results: eGFR and serum concentrations of Cr and CysC were not modified at any exercise intensity. There was a negative correlation between blood total cholesterol vs. eGFR (R = −0.512, R = −0.582, R = −0.531; p < 0.05) at rest, 60%, and 100% of the maximal heart rate, respectively. In addition, a negative correlation existed for age vs. eGFR at 60% of the maximal heart rate (R = −0.516; p < 0.05). Conclusions: Short-duration aerobic exercise of low, moderate, and vigorous intensity did not significantly affect eGFR and is considered safe for kidney function in healthy, sedentary older adults. However, regular monitoring of kidney function in older people engaged in moderate- and high-intensity exercise is advised.
Robust Optimization Models for Planning Drone Swarm Missions
Authors: Panowicz Robert , Stecz Wojciech
Published: October 2024

This article presents methods of planning unmanned aerial vehicle (UAV) missions in which individual platforms work together during the reconnaissance of objects located within a terrain. The planning problem concerns determining the flight routes of a swarm, where each UAV has the ability to recognize an object using a specific type of sensor. The experiments described in this article were carried out for drone formation; one drone works as a swarm information hub and exchanges information with the ground control station (GCS). Numerical models for mission planning are presented, which take into account the important constraints, simplifying the description of the mission without too much risk of losing the platforms. Several types of objective functions were used to optimize swarm flight paths. The mission models are presented in the form of mixed integer linear programming problems (MILPs). The experiments were carried out on a terrain model built on the basis of graph and network theory. The method of building a network on which the route plan of a drone swarm is determined is precisely presented. Particular attention was paid to the description of ways to minimize the size of the network on which the swarm mission is planned. The presented methods for building a terrain model allow for solving the optimization problem using integer programming tasks.
Motivation and Engagement of Students: A Case Study of Automatics and Robotics Projects
Authors: Grobelna Iwona , Pławiak-Mowna Anna
Published: October 2024

Automatics and Robotics students usually engage in some interdisciplinary approaches on their courses at universities, joining the areas of computer science and control theory. During the limited duration of these courses, some knowledge must be acquired by the students. Remote education, temporarily enforced by the COVID-19 pandemic in recent years, has posed new challenges related to the limited contact that students have with academic staff, as well as the limited access students have to hardware facilities. This paper discusses the motivations of students after the COVID-19 pandemic based on a case study of student projects completed at the University of Zielona Gora (Poland). The conducted study was student-centered and highlighted some important aspects of motivation from the point of view of the students, focusing mostly on the emerging challenges, how they have been overcome, and what the students have learned from them. The results indicate that the students, minimally supported by an academic teacher, were able to plan everything by themselves and bring the project to completion according to their own intuition. In comparison to before the COVID-19 pandemic, students are now more independent and self-motivated.
Deep Learning-Based Decision Support System for Automatic Detection and Grading of Surface Corrosion on Galvanized Steel Sheets
Authors: Erkınay Özdemir Merve , Karakuş Fuat
Published: October 2024

Corrosion in the sheets produced leads to significant material losses, including the loss of resources, capital, labor, energy and knowledge. Corrosion control is significant for sheets produced and sent to customers in iron and steel factories. Surface corrosion testing of produced sheets and the accurate detection of corrosion levels are of great importance. The corrosion detection process for sheets in steel factories is performed visually with the naked eye. This is a subjective and time-consuming method. Identifying corrosion damage by visual detection and accurately determining the type and extent of corrosion requires expertise. Wrong decisions at this stage lead to losses during the production phase. Therefore, there is a need for systems that can automate this process and make it human-independent. In this study, a decision support system was designed to automatically detect the level of corrosion in galvanized sheets using convolutional neural networks. The average accuracy of the system is 97.5%, the average precision is 0.98, the average recall is 1 and the average F1 score is 0.99. The results we obtained indicate that a successful system has been developed for the detection and determination of corrosion levels. The high performance of the convolutional neural network models used for corrosion detection supports the practical applicability of the developed system. This system will increase the reliability and efficiency of industrial processes by enabling the accurate and automatic classification of corrosion. This system, which meets a significant need in this area for industrial organizations, reduces production costs and also makes the corrosion detection process more consistent and faster.
A Hierarchical Blockchain System for Social Economy Services
Authors: Chin Ya-Chi , Hsu Chien-Lung , Lin Tzu-Wei , Tsai Kuo-Yu
Published: October 2024

Social economy actors have assisted the recovery from crises by providing innovative solutions that are aimed at strengthening public services to complement government action. Currently, the widespread use of information and communication technologies (ICTs) by both citizens and organizations has changed society’s routine behavior, giving rise to the so-called information society. One of the major burdens of using big data for social problems is the lack of adequate data governance standards. Challenging and critical issues about big data include privacy and security for most of the social economy field of activities. Blockchain technology has attracted the attention of academic researchers and industries, which combines technologies like cryptography, end-to-end communication, and algorithms. Moreover, blockchain technology provides user anonymity to protect the privacy of users. We propose a hierarchical blockchain system for social economy services that can effectively protect the security and privacy of users and transmitted data. The proposed scheme was proven to ensure the legitimacy of all parties in the system and security of data and transactions, and blockchain technology and signcryption mechanisms were applied to achieve integrity, non-repudiation, and traceability. Security and performance analyses are also provided to prove that the proposed scheme achieved the above security concerns with efficiency.
Loss and Thermal Analysis of a High-Power-Density Permanent Magnet Starter/Generator
Authors: Ren Xiaojun , Chen Zhikai , Du Rui , Feng Ming
Published: October 2024

Reducing heat and improving the overall operation stability of the motor play a key role in the design of a starting engine. This paper focuses on the loss and thermal analysis of a permanent magnet (PM) brushless machine used in starter generators. The loss of the starter generator was calculated through a combination of theoretical analysis and the finite element method. A thermal analysis model was established based on the division of the fluid domain, boundary grid, heat source setting, and so on. The temperature fields of the whole motor and the main components were calculated and analyzed. The main factors affecting the air cooling effect were analyzed, including air flow rate, air temperature, and motor speed. A prototype experimental platform of the SG motor was built. The efficiency and temperature rise in the motor were tested. The temperature values were compared with the calculated values. The experimental results show that the performance of the motor is excellent, and the error between the temperature and the design calculation is less than 10% under each load torque. The accuracy of the thermal analysis method is verified. The correctness of the motor transient model was also confirmed through a temperature rise experiment under rated conditions, providing a research basis for improving operation efficiency.
Fault-Tolerant Performance Analysis of a Modified Neutral-Point-Clamped Asymmetric Half-Bridge Converter for an In-Wheel Switched Reluctance Motor
Authors: Oloo Jackson , Szamel Laszlo
Published: October 2024

Reliability is an essential factor for the operation of the Switched Reluctance Motor (SRM) drive. Electric vehicles operate in harsh environments, which may degrade the operation of power converters. These failure modes include transistor open- and short-circuits, freewheeling diode open- and short-circuits, and DC-link capacitor failures. This work presents a performance analysis of an in-wheel SRM for an electric vehicle under short-circuit (SC) and open-circuit (OC) faults of a modified Neutral-Point-Clamped Asymmetric Half-Bridge (NPC-AHB) Converter. The SRM is modeled as an in-wheel electric vehicle. A separate vehicle model attached to the motor is also developed for validation and performance of the NPC-AHB under different faulty scenarios. The performance of the modified NPC-AHB is also compared with that of a conventional AHB under faulty conditions for an in-wheel 8/6 SRM. The performance indicators such as torque, speed, current, and flux are presented from MATLAB/Simulink 2023b numerical simulations.