bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessing the Viability of Translocated Mongolian Dung Beetles (Gymnopleurus mopsus) for Ecological Restoration in Republic of Korea: An Analysis of Environmental Adaptability
Authors: Kim Hwang , Lee Doo-Hyung , Hong Sun-Hee , Park Jong-Seok , Kho Jung-Wook , Kim Young-Joong
Published: November 2024

This study investigates the reintroduction and ecological adaptation of the endangered dung beetle, Gymnopleurus mopsus, in South Korea, a region from which it has been absent since the 1970s. To facilitate this, we imported genetically identical populations of G. mopsus from Mongolia and embarked on a comprehensive restoration research project. A key focus of this endeavor was to evaluate the adaptability of these beetles to the local environment, an essential aspect of successful reintegration of species from foreign ecosystems. Under meticulously controlled field cage conditions, we conducted an in-depth monitoring of the life history traits of G. mopsus. This monitoring revealed that the adult beetles, which entered hibernation in September 2019, began emerging in stages from late April to May 2020. Following hibernation, we observed that the adults engaged in reproductive activities from late-May until early-August, with the emergence of the first-generation (F1) adults occurring from late-July to mid-September. This led to a notable tripling in population size, increasing from 34 to 109 individuals. The successful survival and reproductive behaviors of these Mongolian dung beetles in the climatic conditions of Korea suggest a promising potential for their adaptation when reintroduced into native habitats. We are now directing our efforts towards long-term monitoring, focusing on the survival and reproductive efficacy of these new generations, to further validate the success of this ecological restoration project.
Comparison of Orchid Conservation Between China and Other Countries
Authors: Li Shixing , Liang Cuiyi , Deng Shuwen , Chen Chen , Yuan Liangchen , Liu Zhen , Wu Shasha , Lan Siren , Tang Ziang , Liu Zhongjian , Zhai Junwen
Published: November 2024

Global attention is highly focused on biodiversity conservation. Various countries are actively implementing relevant conservation measures. To advance these efforts in China, it is essential to understand global conservation actions. The orchid family, one of the most diverse groups of flowering plants, has become a “flagship” group for plant conservation. In this study, we summarized 3418 policies and regulations related to orchid conservation in 45 countries. We found that orchid conservation actions in various countries have focused on in situ conservation, with 1469 policies and regulations issued for nature reserves, while ex situ conservation has been seriously neglected, with only seven relevant regulations. Most developing countries have experienced an increase in orchid conservation actions, while developed countries have plateaued. We amassed 370 non-governmental organizations (NGOs) for orchid conservation. At present, the total number of policies and regulations for orchid protection in China is approximately 84, with 67 issued since 2000. Two non-governmental organizations have been established for orchid conservation. Although the benefit of orchid conservation in China is significant, it still requires continuous improvement compared to many other countries. We recommend that the Chinese government draws on the experiences of the United States, Canada, and Australia in areas such as policy and regulation formulation, optimization of non-governmental organizations, and implementation of related conservation projects. Through learning and collaboration, challenges can be transformed into opportunities for development.
Additions to Space Physics Data Facility and pysatNASA: Increasing Mars Global Surveyor and Mars Atmosphere and Volatile EvolutioN Dataset Utility
Authors: Esman Teresa M. , Halford Alexa J. , Klenzing Jeff , Burrell Angeline G.
Published: November 2024

The Space Physics Data Facility (SPDF) is a digital archive of space physics data and is useful for the storage, analysis, and dissemination of data. We discuss the process used to create an amended dataset and store it on the SPDF. The operational software to generate the archival data software uses the open-source Python package pysat, and an end-user module has been added to the pysatNASA module. The result is the addition of data products to the Mars Global Surveyor (MGS) magnetometer (MAG) dataset, its archival location on SPDF, and pysat compatibility. The primary and metadata format increases the convenience and efficiency for users of the MGS MAG data. The storage of planetary and heliophysics data in one location supports the use of data throughout the solar system for comparison, while pysat compatibility enables loading data in an identical format for ease of processing. We encourage the use of the outlined process for past, present, and future space science missions of all sizes and funding levels. This includes balloons to Flagship-class missions.
Cytomegalovirus Infections in Hematopoietic Stem Cell Transplant: Moving Beyond Molecular Diagnostics to Immunodiagnostics
Authors: Gupta Chhavi , Mundan Netto George , Das Shukla , Jawed Arshad , Dar Sajad Ahmad , Dailah Hamad Ghaleb
Published: November 2024

Human CMV, regularly reactivated by simple triggers, results in asymptomatic viral shedding, powerful cellular immune responses, and memory inflation. Immunocompetent individuals benefit from a robust immune response, which aids in viral management without causing clinically significant illness; however, immunodeficient individuals are always at a higher risk of CMV reactivation and disease. Hematopoietic stem cell transplant (HSCT) recipients are consistently at higher risk of CMV reactivation and clinically significant CMV illness due to primary disease, immunosuppression, and graft vs. host disease. Early recovery of CMV-CMI responses may mitigate effects of viral reactivation in HSCT recipients. Immune reconstitution following transplantation occurs spontaneously and is mediated initially by donor-derived T cells, followed by clonal growth of T cells produced from graft progenitors. CMV-specific immune reconstitution post-transplant is related to spontaneous clearance of CMV reactivation and may eliminate the need for prophylactic or pre-emptive medication, making it a potential predictive marker for monitoring CMV reactivation. This review highlights current thoughts and therapeutic options for CMV reactivation in HSCT, with focus on CMV immune reconstitution and post-HSCT monitoring. Immune monitoring aids in risk stratification of transplant recipients who may progress from CMV reactivation to clinically significant CMV infection. Implementing this approach in clinical practice reduces the need for periodic viral surveillance and antiviral therapy in recipients who have a high CMV-CMI and thus may experience self-limited reactivation. Therefore, in the age of precision medicine, it is critical to incorporate CMV-specific cellular immune surveillance into conventional procedures and algorithms for the management of transplant recipients.
Comparative Analysis of 3D Cephalometry Provided with Artificial Intelligence and Manual Tracing
Authors: Khabadze Zurab , Mordanov Oleg , Shilyaeva Ekaterina
Published: November 2024

Objectives: To compare 3D cephalometric analysis performed using AI with that conducted manually by a specialist orthodontist. Methods: The CBCT scans (a field of view of 15 × 15 cm) used in the study were obtained from 30 consecutive patients, aged 18 to 50. The 3D cephalometric analysis was conducted using two methods. The first method involved manual tracing performed with the Invivo 6 software (Anatomage Inc., Santa Clara, CA, USA). The second method involved using AI for cephalometric measurements as part of an orthodontic report generated by the Diagnocat system (Diagnocat Ltd., San Francisco, CA, USA). Results: A statistically significant difference within one standard deviation of the parameter was found in the following measurements: SNA, SNB, and the left interincisal angle. Statistically significant differences within two standard deviations were noted in the following measurements: the right and left gonial angles, the left upper incisor, and the right lower incisor. No statistically significant differences were observed beyond two standard deviations. Conclusions: AI in the form of Diagnocat proved to be effective in assessing the mandibular growth direction, defining the skeletal class, and estimating the overbite, overjet, and Wits parameter.
Enhancing Epilepsy Seizure Detection Through Advanced EEG Preprocessing Techniques and Peak-to-Peak Amplitude Fluctuation Analysis
Authors: Bahhah Muawiyah A. , Attar Eyad Talal
Published: November 2024

Objectives: Naturally, there are several challenges, such as muscular artifacts, ocular movements and electrical interferences that depend on precise diagnosis and classification, which hamper exact epileptic seizure detection. This study has been conducted to improve seizure detection accuracy in epilepsy patients using an advanced preprocessing technique that could remove such noxious artifacts. Methods: In the frame of this paper, the core tool in the area of epilepsy, EEG, will be applied to record and analyze the electrical patterns of the brain. The dataset includes recordings of seven epilepsy patients taken by the Unit of Neurology and Neurophysiology, University of Siena. The preprocessing techniques employed include advanced artifact removal and signal enhancement methods. We introduced Peak-to-Peak Amplitude Fluctuation (PPAF) to assess amplitude variability within Event-Related Potential (ERP) waveforms. This approach was applied to data from patients experiencing 3–5 seizures, categorized into three distinct groups. Results: The results indicated that the frontal and parietal regions, particularly the electrode areas Cz, Pz and Fp2, are the main contributors to epileptic seizures. Additionally, the implementation of the PPAF metric enhanced the effectiveness of seizure detection and classification algorithms, achieving accuracy rates of 99%, 98% and 95% for datasets with three, four and five seizures, respectively. Conclusions: The present research extends the epilepsy diagnosis with clues on brain activity during seizures and further demonstrates the effectiveness of advanced preprocessing techniques. The introduction of PPAF as a metric could have promising potential in improving both the accuracy and reliability of epilepsy seizure detection algorithms. These observations provide important implications for control and treatment both in focal and in generalized epilepsy.
Enhancing Lung Ultrasound Diagnostics: A Clinical Study on an Artificial Intelligence Tool for the Detection and Quantification of A-Lines and B-Lines
Authors: Nekoui Mahdiar , Seyed Bolouri Seyed Ehsan , Forouzandeh Amir , Dehghan Masood , Zonoobi Dornoosh , Jaremko Jacob L. , Buchanan Brian , Nagdev Arun , Kapur Jeevesh
Published: November 2024

Background/Objective: A-lines and B-lines are key ultrasound markers that differentiate normal from abnormal lung conditions. A-lines are horizontal lines usually seen in normal aerated lungs, while B-lines are linear vertical artifacts associated with lung abnormalities such as pulmonary edema, infection, and COVID-19, where a higher number of B-lines indicates more severe pathology. This paper aimed to evaluate the effectiveness of a newly released lung ultrasound AI tool (ExoLungAI) in the detection of A-lines and quantification/detection of B-lines to help clinicians in assessing pulmonary conditions. Methods: The algorithm is evaluated on 692 lung ultrasound scans collected from 48 patients (65% males, aged: 55 ± 12.9) following their admission to an Intensive Care Unit (ICU) for COVID-19 symptoms, including respiratory failure, pneumonia, and other complications. Results: ExoLungAI achieved a sensitivity of 91% and specificity of 81% for A-line detection. For B-line detection, it attained a sensitivity of 84% and specificity of 86%. In quantifying B-lines, the algorithm achieved a weighted kappa score of 0.77 (95% CI 0.74 to 0.80) and an ICC of 0.87 (95% CI 0.85 to 0.89), showing substantial agreement between the ground truth and predicted B-line counts. Conclusions: ExoLungAI demonstrates a reliable performance in A-line detection and B-line detection/quantification. This automated tool has greater objectivity, consistency, and efficiency compared to manual methods. Many healthcare professionals including intensivists, radiologists, sonographers, medical trainers, and nurse practitioners can benefit from such a tool, as it assists the diagnostic capabilities of lung ultrasound and delivers rapid responses.
Natural History from Appendiceal Mucocele to Jelly Belly
Authors: Hoskovec David , Krška Zdeněk , Pudlač Adam , Lochman Matyáš , Strohalmová Sabina , Bocán Andrej , Koželský Pavel , Dytrych Petr
Published: November 2024

Mucocele of the appendix and pseudomyxoma peritonei are rare diseases. The clinical findings are nonspecific in the early stages of the disease. The sequelae of appendiceal mucocele, its perforation, and extensive peritoneal involvement via pseudomyxoma peritonei (jelly belly) are repeatedly described in the literature. We present the typical findings in the natural history of the disease.
Joint Sensing and Communications in Unmanned-Aerial-Vehicle-Assisted Systems
Authors: Bithas Petros S. , Efthymoglou George P. , Kanatas Athanasios G. , Maliatsos Konstantinos
Published: November 2024

The application of joint sensing and communications (JSACs) technology in air–ground networks, which include unmanned aerial vehicles (UAVs), offers unique opportunities for improving both sensing and communication performances. However, this type of network is also sensitive to the peculiar characteristics of the aerial communications environment, which include shadowing and scattering caused by man-made structures. This paper investigates an aerial JSAC network and proposes a UAV-selection strategy that is shown to improve the communication performance. We first derive analytical expressions for the received signal-to-interference ratio for both communication and sensing functions. These expressions are then used to analyze the outage and coverage probability of the communication part, as well as the ergodic radar estimation information rate and the detection probability of the sensing part. Moreover, a performance trade-off is investigated under the assumption of a total bandwidth constraint. Various numerical evaluated results have been presented complemented by equivalent simulated ones. These results reveal the applicability of the proposed analysis, as well as the impact of shadowing and multipath fading severity, and interference on the system’s performance.
Sensitivity of Bayesian Networks to Noise in Their Parameters
Authors: Onisko Agnieszka , Druzdzel Marek J.
Published: November 2024

There is a widely spread belief in the Bayesian network (BN) community that the overall accuracy of results of BN inference is not too sensitive to the precision of their parameters. We present the results of several experiments in which we put this belief to a test in the context of medical diagnostic models. We study the deterioration of accuracy under random symmetric noise but also biased noise that represents overconfidence and underconfidence of human experts.Our results demonstrate consistently, across all models studied, that while noise leads to deterioration of accuracy, small amounts of noise have minimal effect on the diagnostic accuracy of BN models. Overconfidence, common among human experts, appears to be safer than symmetric noise and much safer than underconfidence in terms of the resulting accuracy. Noise in medical laboratory results and disease nodes as well as in nodes forming the Markov blanket of the disease nodes has the largest effect on accuracy. In light of these results, knowledge engineers should moderately worry about the overall quality of the numerical parameters of BNs and direct their effort where it is most needed, as indicated by sensitivity analysis.
Evidential Analysis: An Alternative to Hypothesis Testing in Normal Linear Models
Authors: Dennis Brian , Taper Mark L. , Ponciano José M.
Published: November 2024

Statistical hypothesis testing, as formalized by 20th century statisticians and taught in college statistics courses, has been a cornerstone of 100 years of scientific progress. Nevertheless, the methodology is increasingly questioned in many scientific disciplines. We demonstrate in this paper how many of the worrisome aspects of statistical hypothesis testing can be ameliorated with concepts and methods from evidential analysis. The model family we treat is the familiar normal linear model with fixed effects, embracing multiple regression and analysis of variance, a warhorse of everyday science in labs and field stations. Questions about study design, the applicability of the null hypothesis, the effect size, error probabilities, evidence strength, and model misspecification become more naturally housed in an evidential setting. We provide a completely worked example featuring a two-way analysis of variance.
Universality of Dynamical Symmetries in Chaotic Maps
Authors: Acero Marcos , Lyons Sean , Aragoneses Andrés , Pattanayak Arjendu K.
Published: November 2024

Identifying signs of regularity and uncovering dynamical symmetries in complex and chaotic systems is crucial both for practical applications and for enhancing our understanding of complex dynamics. Recent approaches have quantified temporal correlations in time series, revealing hidden, approximate dynamical symmetries that provide insight into the systems under study. In this paper, we explore universality patterns in the dynamics of chaotic maps using combinations of complexity quantifiers. We also apply a recently introduced technique that projects dynamical symmetries into a “symmetry space”, providing an intuitive and visual depiction of these symmetries. Our approach unifies and extends previous results and, more importantly, offers a meaningful interpretation of universality by linking it with dynamical symmetries and their transitions.
Trends of Climate Extremes and Their Relationships with Tropical Ocean Temperatures in South America
Authors: dos Santos Luiz Octávio Fabrício , Machado Nadja Gomes , Querino Carlos Alexandre Santos , Biudes Marcelo Sacardi
Published: November 2024

South America has experienced significant changes in climate patterns over recent decades, particularly in terms of precipitation and temperature extremes. This study analyzes trends in climate extremes from 1979 to 2020 across South America, focusing on their relationships with sea surface temperature (SST) anomalies in the Pacific and Atlantic Oceans. The analysis uses precipitation and temperature indices, such as the number of heavy rainfall days (R10mm, R20mm, R30mm), total annual precipitation (PRCPTOT), hottest day (TXx), and heatwave duration (WSDI), to assess changes over time. The results show a widespread decline in total annual precipitation across the continent, although some regions, particularly in the northeast and southeast, experienced an increase in the intensity and frequency of extreme precipitation events. Extreme temperatures have also risen consistently across South America, with an increase in both the frequency and duration of heat extremes, indicating an ongoing warming trend. The study also highlights the significant role of SST anomalies in both the Pacific and Atlantic Oceans in driving these climate extremes. Strong correlations were found between Pacific SST anomalies (Niño 3.4 region) and extreme precipitation events in the northern and southern regions of South America. Similarly, Atlantic SST anomalies, especially in the Northern Atlantic (TNA), exhibited notable impacts on temperature extremes, particularly heatwaves. These findings underscore the complex interactions between SST anomalies and climate variability in South America, providing crucial insights into the dynamics of climate extremes in the region. Understanding these relationships is essential for developing effective adaptation and mitigation strategies in response to the increasing frequency and intensity of climate extremes.
Start Switch for Innovation in “Construction Sequencing”: Research Funding
Authors: Kuchiki Akifumi
Published: November 2024

Clusters of knowledge-intensive industries and manufacturing industries form industrial agglomeration in Step I and activate innovation in Step II. Industry clusters are formed by building segments. “Construction sequencing” in the construction industry refers to the process of determining the sequence of segments to optimize a project’s resources, budget, and scheduled timeline. The process usually begins by dividing a project into segments. Urban segments consist of public spaces, airports, factories, health, housing, etc. A “segment” is a component of a cluster; the organization of a cluster consists of constructing segments. These segments can be divided into four main categories: human resources, physical infrastructure, institutions, and the living environment. Each segment has a specific function in the process of building a cluster. This study focused on innovation in Step II and extended the Fujita–Thisse model of spatial economics to hypothesize that research expenditure per researcher leads to value being added. The Granger causality was tested for the knowledge and manufacturing industries in nine major countries including China and the U.S. The results showed that the hypothesis was significant in identifying the starting segment of innovation in Step II. Accordingly, it can be concluded that research funding is the start switch that triggers innovation. The policy implication is that activating innovation in cluster policies begins with the establishment of a research fund for researchers in its assigned clusters.
The Impact of Economic Factors on Saudi Arabia’s Foreign Trade with BRICS Countries: A Gravity Model Approach
Authors: Benlaria Houcine
Published: November 2024

Our investigation, bolstered by the robust gravity trade model and panel data econometric technique, underscores the pivotal factors that influence trade interactions between Saudi Arabia and the BRICS nations—Brazil, Russia, India, China, and South Africa. The study, spanning from 1998 to 2023, delves into key economic metrics such as the gross domestic product, exchange rate fluctuations, inflationary trends, political conditions, and trade deals. We employ a range of econometric strategies, including pooled Ordinary Least Squares (OLS) and fixed effects models, to reveal that the GDP of BRICS states consistently and significantly impacts trade volumes. Specifically, a 1% increase in the GDP of partner countries correlates with a 0.37% rise in trade volume within the pooled OLS model. This effect amplifies to 1.43% when adjusting for temporal and country-specific factors in the fixed effects, underscoring the importance of accommodating unobserved heterogeneity, which refers to the unmeasured factors that can influence the relationship between GDP and trade volume. The political stability of BRICS nations mitigates transactional risks and promotes more stable trade relationships, thereby enhancing trade flows. Fluctuations in exchange rates exert positive and significant effects. This indicates that a more robust Saudi Riyal, an essential policy instrument, can enhance trade by increasing the competitiveness of Saudi exports. This study demonstrates that economic magnitude, political stability, and exchange rates affect Saudi Arabia’s trade with BRICS nations. These results bolster the Kingdom’s Vision 2030 objectives for economic diversification. This research advocates for stable political climates and strategic trade agreements to enhance trade relations. This study asserts that this approach will guarantee sustainable growth and diminish the Kingdom’s reliance on oil exports, instilling optimism in the Saudi economy.
Positive Resources of School Class Communities—Determinants of Student Satisfaction
Authors: Bavčević Tonči , Milavić Boris , Bavčević Damir , Babić Matej , Čular Dražen
Published: November 2024

The aim of this study was to determine the factors affecting students’ satisfaction with their class community by measuring the contributions of “positive” resources: either the socio-demographic and individual characteristics of students, or common characteristics of the class community. The research was conducted anonymously using multiple questionnaires on a sample of 267 students attending the higher grades (5th–8th grades) of primary schools from an urban area of the city of Split. It was determined that social cohesion and prosocial behaviour within the class community were the strongest determinants and were also the most important positive resources of satisfaction with the class community. Individual psychological characteristics (especially self-esteem and hope) and the socio-demographic characteristics of students also played a significant role in explaining satisfaction with the class community, but their relative contribution was much weaker than social relations within the class community. The three types of psychological characteristics of the students were positively related to the degree of satisfaction with the class community, but this association was at a low level. More than half of the students were not completely satisfied with their class community. Furthermore, based on the five fundamental dimensions of intrinsic (IM) and extrinsic motivation (EM) within PE motivation, four types of students with different motivational characteristics were determined: the very low type; moderate type; very high IM and low EM type; and extremely high type. It is recommended that experts continue researching the relationship between psychological and social variables in class communities, as well as investigating the effectiveness of possible interventions aimed at the development and improvement of social relationships in the educational and sports talent development environment.
Ethical Principles in AI Use for Assessment: Exploring Students’ Perspectives on Ethical Principles in Academic Publishing
Authors: Lazăr (Cățeanu) Alexandra Maria , Repanovici Angela , Popa Daniela , Ionas Diana Geanina , Dobrescu Ada Ioana
Published: November 2024

Students’ comprehension of ethical principles and their application in the realm of AI technology play a crucial role in shaping the efficacy and morality of assessment procedures. This study seeks to explore students’ viewpoints on ethical principles within the context of AI-driven assessment activities to illuminate their awareness, attitudes, and practices concerning ethical considerations in educational environments. A systematic review of articles on this topic was conducted using scientometric methods within the Web of Science database. This review identified a research gap in the specialized literature regarding studies that delve into students’ opinions. Subsequently, a questionnaire was administered to students at Transilvania University of Brasov as part of the Information Literacy course. Statistical analysis was performed on the obtained results. Ultimately, students expressed a desire for the Information Culture course to incorporate a module focusing on the ethical use of AI in academic publishing.
Play-Based Assessment: Psychometric Properties of an Early Childhood Learning and Development Assessment Battery
Authors: Montoya-Fernández Carlos , Gil-Madrona Pedro , Losada-Puente Luisa , Gómez-Barreto Isabel María
Published: November 2024

This study aims to explore the reliability, construct validity, and content validity of the Child Learning and Developmental Playful Assessment Battery (Batería de Evaluación Lúdica del Aprendizaje y Desarrollo Infantil; BELADI), a quantitative instrument based on the authentic assessment and playful learning principles, the purpose of which is to assess infant learning and development through motor and competitive games as well as storytelling. The sample was composed of 113 children from Albacete (Spain) between 58 and 72 months of chronological age (M = 64.72; SD = 3.671). To explore the content validity, an expert judgement was carried out and the Content Validity Coefficient (CVC) was calculated. The reliability was analysed using the Cronbach’s alpha and McDonald’s Ω, and an exploratory factor analysis (EFA) was conducted. The results revealed high reliability indexes in each of the developmental domains, and the EFA included 11 items distributed in two factors for the psychomotor domain, 27 items grouped in three factors for the cognitive domain, and 20 items divided into four factors for the socioemotional domain. In conclusion, the study verifies the validity and reliability of the BELADI for the assessment of the infant learning and development through play, which may be used in research, education, and psychopedagogy.
Quadratic Boost Converter with Optimized Switching Ripple Based on the Selection of Passive Components
Authors: Silva-Vera Edgar D. , Rosas-Caro Julio C. , Valdez-Resendiz Jesus E. , Alejo-Reyes Avelina , Ruiz-Martinez Omar F. , Posada Contreras Johnny , García-Vite Pedro Martín
Published: November 2024

This work introduces a boost converter with quadratic gain. Its main advantage compared to well-known similar quadratic boost converters is that it requires capacitors with a relatively small capacitance and inductors with small inductance, leading to a reduction in the size or stored energy while performing a power conversion of similar power rating and the same switching ripples in both the input current and the output voltage. It is inspired by the recently introduced ISB converter and uses a specific PWM method. This results in achieving switching ripple constraints while using smaller energy storage elements (capacitors and inductors). The updated converter offers the same voltage gain compared to the conventional quadratic boost topology with the benefit of compact component sizes. While it has more passive elements, they are of reduced size. An analysis of energy storage revealed that this new converter uses only half the energy in inductors and 14% in capacitors when compared to specific design parameters.
Design of a High-Voltage Arbitrary Waveform Generator Using a Modular Cascaded H-Bridge Topology
Authors: Zhao Weichuan , Lagerweij Gijs Willem , Hurkmans Brecht , Niasar Mohamad Ghaffarian
Published: November 2024

As the integration of renewable energy sources into the grid increases, the insulation systems of grid components such as transformers and switchgear encounter significant challenges due to the transients and harmonics generated by power-electronic-based converters. A test generator capable of replicating these component stresses is essential to accurately evaluate these insulation systems under real-grid conditions. This paper proposes a modular cascaded H-bridge-based high-voltage arbitrary waveform generator, prototyped with three stages to generate customized waveforms (triangular, sawtooth, pulse, and complex) up to 8 kV. The H-bridge modules are designed using Si MOSFETs with a maximum blocking voltage of 4.5 kV. The input to the HV H-bridge module is provided by a 10 kV medium-frequency transformer, whose design is described with a focus on the insulation system and winding configuration. This transformer is driven by a zero-voltage switching driver. This arbitrary waveform generator excels in several aspects, including a straightforward design procedure, compact size, high voltage capability, ease of integration, and cost.
Anomaly Detection and Analysis in Nuclear Power Plants
Authors: Chaudhary Abhishek , Han Junseo , Kim Seongah , Kim Aram , Choi Sunoh
Published: November 2024

Industries are increasingly adopting digital systems to improve control and accessibility by providing real-time monitoring and early alerts for potential issues. While digital transformation fuels exponential growth, it exposes these industries to cyberattacks. For critical sectors such as nuclear power plants, a cyberattack not only risks damaging the facility but also endangers human lives. In today’s digital world, enormous amounts of data are generated, and the analysis of these data can help ensure effectiveness, including security. In this study, we analyzed the data using a deep learning model for early detection of abnormal behavior. We first examined the Asherah Nuclear Power Plant simulator by initiating three different cyberattacks, each targeting a different system, thereby collecting and analyzing data from the simulator. Second, a Bi-LSTM model was used to detect anomalies in the simulator, which detected it before the plant’s protection system was activated in response to a threat. Finally, we applied explainable AI (XAI) to acquire insight into how distinctive features contribute to the detection of anomalies. XAI provides valuable explanations of model behavior by revealing how specific features influence anomaly detection during attacks. This research proposes an effective anomaly detection technique and interpretability to better understand counter-cyber threats in critical industries, such as nuclear plants.
Color Models in the Process of 3D Digitization of an Artwork for Presentation in a VR Environment of an Art Gallery
Authors: Drofova Irena , Adamek Milan
Published: November 2024

This study deals with the color reproduction of a work of art to digitize it into a 3D realistic model. The experiment aims to digitize a work of art for application in a virtual reality environment concerning faithful color reproduction. Photogrammetry and scanning with a LiDAR sensor are used to compare the methods and work with colors during the reconstruction of the 3D model. An innovative tablet with a camera and LiDAR sensor is used for both methods. At the same time, current findings from the field of color vision and colorimetry are applied to 3D reconstruction. The experiment focuses on working with the RGB and L*a*b* color models and, simultaneously, on the sRGB, CIE XYZ, and Rec.2020(HDR) color spaces for transforming colors into a virtual environment. For this purpose, the color is defined in the Hex Color Value format. This experiment is a starting point for further research on color reproduction in the digital environment. This study represents a partial contribution to the much-discussed area of forgeries of works of art in current trends in forensics and forgery.
Robotic Grasping Detection Algorithm Based on 3D Vision Dual-Stream Encoding Strategy
Authors: Lei Minglin , Wang Pandong , Lei Hua , Ma Jieyun , Wu Wei , Hao Yongtao
Published: November 2024

The automatic generation of stable robotic grasping postures is crucial for the application of computer vision algorithms in real-world settings. This task becomes especially challenging in complex environments, where accurately identifying the geometric shapes and spatial relationships between objects is essential. To enhance the capture of object pose information in 3D visual scenes, we propose a planar robotic grasping detection algorithm named SU-Grasp, which simultaneously focuses on local regions and long-distance relationships. Built upon a U-shaped network, SU-Grasp introduces a novel dual-stream encoding strategy using the Swin Transformer combined with spatial semantic enhancement. Compared to existing baseline methods, our algorithm achieves superior performance across public datasets, simulation tests, and real-world scenarios, highlighting its robust understanding of complex spatial environments.
Physical Layer Security in RIS-NOMA-Assisted IoV Systems with Uncertain RIS Deployment
Authors: Gu Jinyuan , Zhang Zhao , Duan Wei , Song Feifei , Zhang Huaiping
Published: November 2024

Reconfigurable intelligent surfaces (RISs), as an emerging radio technology, are widely used to expand the transmission distance and structure cascade channels to improve the performance of communication systems. However, based on the continuous development of wireless communication technology, as Internet of Vehicles (IoV) communication systems assisted with RIS and non-orthogonal multiple access (NOMA) can improve the overall transmission rate and system performance, the physical layer security (PLS) issue has gradually attracted attention and has become more and more important in the application of the system. In this paper, our aim is to investigate the potential threats for PLS, where an RIS is utilized in order to improve the security of wireless communications. In particular, we consider the non-fixed RIS location and wiretapping behavior of eavesdroppers on the data in this work, and further analyze the maximum safe-rate for above location assumptions. Numerical results reveal that RIS provides significant advantages on security performance, as well as providing a useful reference for the security design of future wireless communication systems, which verify the correctness of our analysis and the effectiveness of the proposed scheme.
Hierarchical Image Quality Improvement Based on Illumination, Resolution, and Noise Factors for Improving Object Detection
Authors: Wang Tae-su , Kim Gi-Tae , Shin Jungpil , Jang Si-Woong
Published: November 2024

Object detection performance is significantly impacted by image quality factors such as illumination, resolution, and noise. This paper proposes a hierarchical image quality improvement process that dynamically prioritizes these factors based on severity, enhancing detection accuracy in diverse conditions. The process evaluates each factor—illumination, resolution, and noise—using discriminators that analyze brightness, edge strength, and noise levels. Improvements are applied iteratively with an adaptive weight update mechanism that adjusts factor importance based on improvement effectiveness. Following each improvement, a quality assessment is conducted, updating weights to fine-tune subsequent adjustments. This allows the process to learn optimal parameters for varying conditions, enhancing adaptability. The image improved through the proposed process shows improved quality through quality index (PSNR, SSIM) evaluation, and the object detection accuracy is significantly improved when the performance is measured using deep learning models called YOLOv8 and RT-DETR. The detection rate is improved by 7% for the ‘Bottle’ object in a high-light environment, and by 4% and 2.5% for the ‘Bicycle’ and ‘Car’ objects in a low-light environment, respectively. Additionally, segmentation accuracy saw a 9.45% gain, supporting the effectiveness of this method in real-world applications.
The Interplay Between China’s Regulated and Voluntary Carbon Markets and Its Influence on Renewable Energy Development—A Literature Review
Authors: Paraschiv Florentina , Schmid Hannah , Schmitz Marten , Dünwald Vivian , Groos Emma
Published: November 2024

This is the first review study that focuses on the interplay between China’s regulated and voluntary carbon markets, the Emissions Trading System (ETS), the China Certified Emission Reduction (CCER) scheme, and their combined influence on the development of renewable energy in the country. Through a comparative literature review of 52 peer-reviewed academic papers published between 2009 and 2024, this study aims to elucidate how these market mechanisms interact to drive renewable energy deployment. The findings indicate that both the ETS and the CCER system positively affect China’s renewable energy landscape. The ETS, with its Cap-and-Trade (CaT) mechanism, sets a cap on total emissions and allows for the trading of emission quotas, thereby creating financial incentives for companies to reduce emissions and invest in renewable energy. The CCER scheme complements the ETS by allowing companies to use the CCER scheme for a capped share of their ETS certificates, whereby the lower CCER price diverts investments to where the saved ton of CO2 in China is cheapest, further incentivizing investments in renewable energy. This dual mechanism allows for a more flexible and cost-effective approach to achieving emission reduction targets, thereby fostering an environment conducive to investment in renewable energy. It will stimulate additional investment in renewable energy projects in the long run, particularly in economically underdeveloped regions, contributing to both local economic development and national emission reduction targets.
The Temporal and Spatial Evolution and Influencing Factors of the Coupling Coordination Degree Between the Promotion of the “Dual Carbon” Targets and Stable Economic Growth in China
Authors: Dong Ruiyuan , Zhang Qian , Zhou Xiaowei
Published: November 2024

Coordinating the relationship between “dual carbon” targets and stable economic growth is crucial for promoting high-quality development in China. This study utilizes the coupling coordination model, kernel density estimation, and spatial econometric models to explore the temporal and spatial evolution characteristics and influencing factors of the coupling coordination degree between the promotion of the “dual carbon” targets and stable economic growth in 287 Chinese cities from 2011 to 2021. The results indicate that, in terms of temporal evolution, the promotion of China’s “dual carbon” targets increases yearly, while stable economic growth follows a “year-on-year increase—short-term decline—sustained recovery” pattern with the coupling coordination degree fluctuating upward. Regarding spatial evolution, the coupling coordination degree between the promotion of the “dual carbon” targets and stable economic growth in China presents a “higher in the east, lower in the west” spatial pattern, with varying gradient effects and polarization across the country and its regions. Influencing factors include government intervention, environmental regulations, energy efficiency, financial development, and R&D investment intensity. These findings provide scientific insights for addressing the mutual constraints between “dual carbon” targets and stable economic growth.
Preliminary Evaluation of Watermelon Liquid Waste as an Alternative Substrate for Microalgae Cultivation: A Circular Economy Approach to the Production of High-Value Secondary Products by Chlorella vulgaris, Scenedesmus sp., Arthrospira platensis, and Chlamydomonas pitschmanii
Authors: Scarponi Paolina , Fontana Lorenzo , Bertesi Francesco , D’Eusanio Veronica , Tassi Lorenzo , Forti Luca
Published: November 2024

In Italy, watermelon cultivation spans 9510 hectares, with production levels largely influenced by seasonal market demand. As a result, surplus watermelon left unsold by September often remain in the fields, where they decompose naturally and go to waste. A chemical analysis of the watermelon liquid fraction waste (WW) indicates a high carbohydrate concentration, highlighting the potential for biotechnological valorization of this waste stream, converting it into lipids or exopolysaccharides (EPSs). This study investigates the feasibility of utilizing WW as an alternative growth substrate for microalgae, aligning with circular economy principles and advancing sustainable agricultural practices. By repurposing agricultural byproducts, this research supports biorefinery objectives, aiming to convert biomass into high-value secondary products, including biofuels, pigments, and nutraceuticals. Scenedesmus and Chlorella strains demonstrated promising growth and adaptability in WW, achieving biomass yields of 0.95 ± 0.07 g L−1 and 0.37 ± 0.02 g L−1, respectively, with a significant EPS production observed as medium gelation. Although lipid accumulation was limited in this case by the WW substrate, the lipid profiles of both strains were distinctively altered, notably lacking linolenic acid.
Influence of the PAN:PEO Ratio on the Morphology of Needleless Electrospun Nanofiber Mats Before and After Carbonization
Authors: Mpofu Nonsikelelo Sheron , Topuz Yusuf , Stepula Elzbieta , Güth Uwe , Grothe Timo , Storck Jan Lukas , Wortmann Martin , Mahltig Boris , Ehrmann Andrea
Published: November 2024

Nanofiber mats with a high surface-to-volume ratio can be prepared by electrospinning. The Porosity is sometimes reported to be tunable by blending different materials, e.g., water-soluble poly(ethylene oxide) (PEO) with not water-soluble poly(acrylonitrile) (PAN). Here, nanofiber mats were electrospun from different PAN:PEO ratios, using a wire-based electrospinning machine “Nanospider Lab”. Investigations of the as-spun nanofiber mats as well as of membranes after washing off the water-soluble PEO by scanning electron microscopy (SEM) revealed severe differences in the nanofiber mat morphologies, such as varying fiber diameters and especially non-fibrous areas in the carbonized nanofiber mats, depending on the amount of PEO in the nanofiber mat as well as the molecular weight of the PEO. Similarly, the ratio and molecular weight of PEO influenced the results of stabilization and carbonization. This paper discusses the possibility of tailoring nanofiber porosity for the potential use of PAN nanofiber mats in tissue engineering, filtration, and other applications.
Non-Circular Cross-Section Fibres for Composite Reinforcement—A Review with a Focus on Flat Glass Fibres
Authors: Thomason James , Carlin Andrew , Yang Liu
Published: November 2024

Glass fibre reinforcements form the backbone of the composites industry. Today, glass fibre products account for more than 95% of the fibre reinforcements used in the composites industry. Since the first commercialisation of glass fibres for composite reinforcement in the 1930s, the cross-sectional shape of glass fibres has remained exclusively circular. However, many of the other types of fibre reinforcement have a non-circular cross section (NCCS). This paper reviews the available knowledge on the production of NCCS glass fibres and some of the possibilities that such fibres offer to enhance the performance of glass reinforced polymer composites. The three parts of the review focus on early research work on different shapes of glass fibre, the developments leading to industrial-level production of NCCS glass fibres, and the more recent data available on the influence of the available commercially produced NCCS flat glass fibres on composite performance. It Is concluded that the continued development of NCCS glass fibres may offer interesting potential to generate composites with increased performance and may also enable further tailoring of composite performance to enable new applications to be developed.
Cultivation and Growth Dynamics of Capelin (Mallotus villosus) from Hatch to Adulthood
Authors: Árnason Tómas , Bárðarson Birkir , Steinarsson Agnar
Published: November 2024

This study describes the first successful rearing of capelin from hatch to adulthood in a laboratory setting using intensive culture methods. Over the span of about two years, the capelin were reared in aquaculture tanks under a constant temperature of 7 °C. The capelin demonstrated a robust linear growth during their first year of life, with a mean length increment of 0.36 mm per day. Due to their accelerated growth, some of the capelin became sexually mature as early as one year post-hatch. The first year was characterized by a rapid increase in condition factor (CF) while the second year showed a plateau. The von Bertalanffy growth equation effectively described the two-year growth of the cultivated capelin, predicting an asymptotic length (L∞) of 18.4 cm, similar to the 18.6 cm median L∞ of wild Icelandic capelin (1981–2018 cohorts). The cultivated capelin were projected to reach this length in 2.6 years, compared to about 6 years for wild capelin. This study provides new insights into the growth dynamics of capelin and although the species is sensitive to handling, it demonstrates that intensive culture methods can be used to investigate biological aspects of this important forage species.