bluuebunny/crossref_metadata_2025 huggingface dataset:
Durability Evaluation of GGBS-RHA-Based Geopolymer Concrete Along with Lightweight Expanded Clay Aggregate Using SEM Images and EDAX Analysis
Authors: Hema P. , Revathi V.
Published: October 2024

The durability of geopolymer concrete containing Ground Granulated Blast Furnace Slag (GGBS) and Rice Husk Ash (RHA), along with Lightweight Expanded Clay Aggregate (LECA), was investigated. Six different LWGPC mixtures were made with NaOH molarities of 8, 10, and 12M. For each molarity, two combinations of source materials were selected: 100% GGBS (G) and 80% GGBS with 20% RHA (RG). In all the mixtures, coarse aggregate was substituted with 35% LECA. LWGPC mixtures were exposed to 3% HCl, 5% MgSO4, and 3.5% NaCl for studying the durability properties. The test results demonstrate that 100% GGBS with 12M NaOH (12G) outperformed all other mixtures. The residual compressive strength of 12G mix LWGPC specimens after six months of exposure was found to be 86.4% in an acid environment, 90.6% in a sulfate environment, and 91.4% in a salt environment. The elemental composition analyzed using EDAX reveals that silica, alumina, calcium, and sodium are the predominant elements that form a dense microstructure with N-A-S-H, C-A-S-H, and C-S-H. Further, the inner properties of the specimens exposed to chemicals were examined using MATLAB R2023b and ImageJ 1.54f based on SEM images. The SEM image showed that the porosity of LWGPC specimens ranged from 0.5194 to 0.6748 µm, signifying an enhanced durability performance. The experimental results and microstructural analysis show that the LWGPC incorporating RHA and GGBS with LECA offers a superior performance, making it a promising solution for sustainable and durable construction.
Indoor Environment in Kindergartens Located in the North of Portugal: Evaluation of Thermal Comfort and Carbon Dioxide Concentration
Authors: Barreira Eva , Almeida Ricardo M. S. F. , Guimarães Joana
Published: October 2024

Adequate school buildings are essential for the development of children, young people, and adolescents, as they must provide conditions that support their well-being and health. A healthy and comfortable indoor environment is critical for students’ performance in the learning process. This study aims to evaluate the indoor environment in kindergartens located in northern Portugal, with a primary focus on thermal comfort and indoor air quality. To achieve this, five buildings with varying construction characteristics were monitored, with temperature and relative humidity measurements taken in classrooms of different orientations over time. Additionally, the outdoor climate was also monitored. Based on the collected data, thermal comfort was evaluated using the adaptive model defined by the European standard EN 16798. Continuous monitoring of carbon dioxide concentration was also conducted in three of these buildings. The results reveal significant heterogeneity among the buildings, demonstrating the influence of construction characteristics on the interior thermal conditions. The recorded temperatures ranged from 10 °C to 27 °C, highlighting a substantial variability in performance across the different buildings. Particularly, the orientation and size of glazed openings, together with the lack of thermal insulation in the building envelope, especially in the roof, were found to have an important impact on the thermal comfort of the occupants. Furthermore, a relationship was observed between the daily maximum carbon dioxide concentration and the outdoor temperature, as a result of users’ efforts to minimize uncontrolled air infiltration, by limiting the opening of doors and windows, with consequences in the air exchange between the interior and exterior.
Cu-TiO2/Zeolite/PMMA Tablets for Efficient Dye Removal: A Study of Photocatalytic Water Purification
Authors: Armaković Sanja J. , Perić Milinko , Bilić Andrijana , Brkić Boris , Šćepanović Maja , Grujić-Brojčin Mirjana , Srđenović Čonić Branislava , Kladar Nebojša , Armaković Stevan
Published: October 2024

In this study, Cu-doped TiO2 combined with natural zeolite (ZT) was synthesized and applied as a fixed powder layer on poly(methyl methacrylate) (PMMA) tablets. The material’s morphology, structural, and chemical properties were characterized using high-resolution scanning electron microscopy, Raman spectroscopy, and Brunauer–Emmett–Teller analysis. The antioxidant capacity was evaluated by assessing the neutralization of hydroxyl radicals and iron (III) ions. For the first time, tablets with Cu-TiO2 and ZT deposited on PMMA as the carrier were investigated for removing two dyes, methyl orange (MO) and methylene blue (MB), from water under simulated solar (SS) and UVC irradiation. Under SS irradiation, the Cu-TiO2/PMMA and Cu-TiO2/ZT/PMMA tablets achieved about 21% degradation of MB after 240 min. This result is particularly noteworthy because SS radiation provides lower energy compared with UVC, making the process more economically efficient. Furthermore, the photocatalysts are immobilized on a stable carrier, which enhances the method’s cost-effectiveness by reducing material loss and simplifying recovery. In the presence of ZT/PMMA tablets, 69% of MB was removed by adsorption after 240 min. Additionally, we explored the mechanism of degradation, revealing that the enhanced generation of hydroxyl radicals plays a pivotal role in the effective degradation of MB. At the same time, photogenerated holes contribute to the removal of MO. The overall results suggest that the tablets obtained are a promising solution for water purification due to their effectiveness, simplicity, and low processing cost.
Using Zebrafish to Study Multiciliated Cell Development and Disease States
Authors: Nguyen Thanh Khoa , Baker Sophia , Rodriguez John-Michael , Arceri Liana , Wingert Rebecca A.
Published: October 2024

Multiciliated cells (MCCs) serve many important functions, including fluid propulsion and chemo- and mechanosensing. Diseases ranging from rare conditions to the recent COVID-19 global health pandemic have been linked to MCC defects. In recent years, the zebrafish has emerged as a model to investigate the biology of MCCs. Here, we review the major events in MCC formation including centriole biogenesis and basal body docking. Then, we discuss studies on the role of MCCs in diseases of the brain, respiratory, kidney and reproductive systems, as well as recent findings about the link between MCCs and SARS-CoV-2. Next, we explore why the zebrafish is a useful model to study MCCs and provide a comprehensive overview of previous studies of genetic components essential for MCC development and motility across three major tissues in the zebrafish: the pronephros, brain ependymal cells and nasal placode. Taken together, here we provide a cohesive summary of MCC research using the zebrafish and its future potential for expanding our understanding of MCC-related disease states.
The Three Pillars of Glioblastoma: A Systematic Review and Novel Analysis of Multi-Omics and Clinical Data
Authors: De Luca Ciro , Virtuoso Assunta , Papa Michele , Cirillo Giovanni , La Rocca Giuseppe , Corvino Sergio , Barbarisi Manlio , Altieri Roberto
Published: October 2024

Glioblastoma is the most fatal and common malignant brain tumor, excluding metastasis and with a median survival of approximately one year. While solid tumors benefit from newly approved drugs, immunotherapy, and prevention, none of these scenarios are opening for glioblastoma. The key to unlocking the peculiar features of glioblastoma is observing its molecular and anatomical features tightly entangled with the host’s central nervous system (CNS). In June 2024, we searched the PUBMED electronic database. Data collection and analysis were conducted independently by two reviewers. Results: A total of 215 articles were identified, and 192 were excluded based on inclusion and exclusion criteria. The remaining 23 were used for collecting divergent molecular pathways and anatomical features of glioblastoma. The analysis of the selected papers revealed a multifaced tumor with extreme variability and cellular reprogramming that are observable within the same patient. All the variability of glioblastoma could be clustered into three pillars to dissect the physiology of the tumor: 1. necrotic core; 2. vascular proliferation; 3. CNS infiltration. These three pillars support glioblastoma survival, with a pivotal role of the neurovascular unit, as supported by the most recent paper published by experts in the field.
New Nanovesicles from Prickly Pear Fruit Juice: A Resource with Antioxidant, Anti-Inflammatory, and Nutrigenomic Properties
Authors: Naselli Flores , Volpes Sara , Cardinale Paola Sofia , Palumbo Fabio Salvatore , Cancilla Francesco , Lopresti Francesco , Villanova Valeria , Girgenti Antonella , Nuzzo Domenico , Caradonna Fabio , Picone Pasquale
Published: October 2024

Plant-derived nanovesicles represent a novel approach in the field of plant-derived biomaterials, offering a sustainable and biocompatible option for various biomedical applications. The unique properties of these vesicles, such as their ability to encapsulate bioactive compounds, make them suitable for therapeutic, cosmetic, and nutraceutical purposes. In this study, we have, for the first time, successfully bio-fabricated vesicles derived from Opuntia ficus-indica (FicoVes) using an efficient and cost-effective method. Characterized by a size of approximately of 114 nm and a negative zeta potential of −20.9 mV, FicoVes exhibited excellent biocompatibility and hemocompatibility, showing no reduction in the viability of human and animal cells. Our results showed that FicoVes possess significant antioxidant properties as they reduced ROS generation in TBH-stimulated cells. FicoVes displayed anti-inflammatory properties by reducing the expression of pro-inflammatory cytokines (Il 1β, TNF α) and enhancing the expression of anti-inflammatory cytokines (IL4, IL10) following an inflammatory stimulus. Furthermore, FicoVes accelerated epithelial wound closure in L929 fibroblast monolayers in a dose-dependent manner, highlighting their potential role in tissue repair. This study establishes FicoVes as a promising candidate for nutrigenomic applications, particularly in the context of inflammation-related disorders and wound healing. Further research, including in vivo studies, is essential to validate these findings and fully explore their therapeutic potential.
SARS-CoV-2 and Environmental Changes: The Perfect Storm
Authors: Caldarelli Mario , Rio Pierluigi , Giambra Vincenzo , Palucci Ivana , Gasbarrini Antonio , Gambassi Giovanni , Cianci Rossella
Published: October 2024

The COVID-19 pandemic has had a significant impact on the global economy. It also provided insights into how the looming global climate crisis might be addressed, as there are several similarities between the challenges proposed by COVID-19 and those expected from the coming climate emergency. COVID-19 is an immediate health threat, but climate change represents a more gradual and insidious risk that will lead to long-term consequences for human health. Research shows that climate change, air pollution and the pandemics have a negative impact on health. Recent studies show that COVID-19 mortality increases with climate extremes. The goal of our review is to analyze the clinical findings of COVID-19 and how they are affected by the climate change, while also providing insight into the emergence of new variants and their ability to evade the immune system. We selected and synthesized data from primary studies, reviews, meta-analyses, and systematic reviews. Selection was based on rigorous methodological and relevance criteria. Indeed, a new variant of SARS-CoV-2, named JN.1, has emerged as the dominant, first in the United States and then worldwide; the variant has specific mutations in its spike proteins that increase its transmissibility. According to the World Health Organization (WHO), JN.1 is currently the most reported variant of interest (VOI), having been identified in 132 countries. We highlight the link between climate change and pandemics, emphasizing the need for global action, targeted medical approaches and scientific innovation.
Effect of Methane on Combustion of Glycerol and Methanol Blends Using a Novel Swirl Burst Injector in a Model Dual-Fuel Gas Turbine Combustor
Authors: Islam S. M. Rafiul , Patel Ishaan , Jiang Lulin
Published: October 2024

Glycerol, a byproduct of biodiesel, has moderate energy but high viscosity, making clean combustion challenging. Quickly evaporating fine fuel sprays mix well with air and burn cleanly and efficiently. Unlike conventional air-blast atomizers discharging a jet core/film, a newly developed swirl burst (SB) injector generates fine sprays at the injector’s immediate exit, even for high-viscosity fuels, without preheating, using a unique two-phase atomization mechanism. It thus resulted in ultra-clean combustion for glycerol/methanol (G/M) blends, with complete combustion for G/M of 50/50 ratios by heat release rate (HRR). Lower combustion efficiencies were observed for G/M 60/40 and 70/30, representing crude glycerol. Hence, this study investigates the effect of premixed methane amount from 0–3 kW, and the effect of atomizing gas to liquid mass ratio (ALR) on the dual-fuel combustion efficiency of G/M 60/40-methane in a 7-kW lab-scale swirl-stabilized gas turbine combustor to facilitate crude glycerol use. Results show that more methane and increased ALR cause varying flame lift-off height, length, and gas product temperature. Regardless, mainly lean-premixed combustion, near-zero CO and NOx emissions (≤2 ppm), and ~100% combustion efficiency are enabled for all the cases by SB atomization with the assistance of a small amount of methane.
Key Considerations for Frail Patients Undergoing Hip Fracture Surgery
Authors: Dumitriu Ana-Maria , Ene Rǎzvan , Mirea Liliana
Published: October 2024

Improving preoperative care for elderly patients with hip fractures is crucial for achieving the best outcomes. A multidisciplinary team that can improve overall care quality by addressing patient’s medical conditions, analgesia, timely surgery, and early postoperative mobilization is required. This narrative review provides insights regarding the extent of preoperative optimization needed for hip fracture surgery.
Program Equivalence in the Erlang Actor Model
Authors: Bereczky Péter , Horpácsi Dániel , Thompson Simon
Published: October 2024

This paper presents the formal semantics of concurrency in Core Erlang, an intermediate language for Erlang, along with a notion of program equivalence (based on barbed bisimulation) that is able to model equivalence between programs that have different communication structures but the same observable behaviour. The novelty in our formalisation is its extent: it includes semantics for messages and exit and link signals, in addition to most of Core Erlang’s sequential features. Furthermore, unlike previous studies, this work formalises message receipt using primitive operations, consistent with the standard as of Erlang/OTP 23. In this novel formalisation, we show some generally applicable program equivalences (such as process identifier renaming and silent evaluation) and present a practical case study featuring the equivalence of sequential and concurrent list processing.
Does Hand-Predominance Have a Predominant Influence on Craniofacial Asymmetric and Anthropometric Analysis in Preadolescences?
Authors: Chen Gloria , Tu Junior Chun-Yu , Chen Shih-Heng , Hsieh Emma Yuh-Jia , Pai Betty C. J. , Tsai Ching-Yen , Chou Pang-Yun
Published: October 2024

Background: Although the human body generally exhibits bilateral symmetry, achieving perfect symmetry is exceedingly uncommon. During preadolescent development, a face that approximates symmetry is considered both aesthetically and functionally ideal. This study aimed to investigate the relationship between craniofacial traits and hand predominance, using three-dimensional (3D) stereophotogrammetry to discern whether facial soft-tissue characteristics are correlated with hand preference. Materials and Methods: The study involved children aged 9 and 10 years who were free from any diagnosed craniofacial anomalies. Three-dimensional stereophotogrammetry was conducted to analyze their facial morphology, and 37 distinct anatomical landmarks were manually identified using a MATLAB-developed program. Results: A total of 188 Taiwanese children participated in the study. All participants were healthy, with a mean age of 9.79 years. Among them, 93.1% (175) were right-hand predominant, and 6.9% (13) were left-hand predominant. There were no significant differences in linear parameters or facial asymmetry between right-hand-predominant and left-hand-predominant participants (p > 0.05). However, a consistent trend toward right laterality, especially in the right lateral frontal region of the cranium, was observed, as illustrated by heat maps of the average three-dimensional model. Conclusions: The study found no association between facial morphology and hand predominance. A normal asymmetry with a rightward tendency was noted in children aged 9 to 10 years, which was particularly notable in the lateral frontal region of the head.
A Review of Artificial Intelligence-Based Dyslexia Detection Techniques
Authors: Alkhurayyif Yazeed , Sait Abdul Rahaman Wahab
Published: October 2024

Problem: Dyslexia is a learning disorder affecting an individual’s ability to recognize words and understand concepts. It remains underdiagnosed due to its complexity and heterogeneity. The use of traditional assessment techniques, including subjective evaluation and standardized tests, increases the likelihood of delayed or incorrect diagnosis. Motivation: Timely identification is essential to provide personalized treatment and improve the individual’s quality of life. The development of artificial intelligence techniques offers a platform to identify dyslexia using behavior and neuroimaging data. However, the limited datasets and black-box nature of ML models reduce the generalizability and interpretability of dyslexia detection (DD) models. The dimensionality reduction technique (DRT) plays a significant role in providing dyslexia features to enhance the performance of machine learning (ML)- and deep learning (DL)-based DD techniques. Aim: In this review, the authors intend to investigate the role of DRTs in enhancing the performance of ML- and DL-based DD models. Methodology: The authors conducted a comprehensive search across multiple digital libraries, including Scopus, Web of Science, PubMed, and IEEEXplore, to identify articles associated with DRTs in identifying dyslexia. They extracted 479 articles using these digital libraries. After an extensive screening procedure, a total of 39 articles were included in this review. Results: The review findings revealed various DRTs for identifying critical dyslexia patterns from multiple modalities. A significant number of studies employed principal component analysis (PCA) for feature extraction and selection. The authors presented the essential features associated with DD. In addition, they outlined the challenges and limitations of existing DRTs. Impact: The authors emphasized the need for the development of novel DRTs and their seamless integration with advanced DL techniques for robust and interpretable DD models.
A Feature-Fusion Technique-Based Alzheimer’s Disease Classification Using Magnetic Resonance Imaging
Authors: Sait Abdul Rahaman Wahab , Nagaraj Ramprasad
Published: October 2024

Background: Early identification of Alzheimer’s disease (AD) is essential for optimal treatment and management. Deep learning (DL) technologies, including convolutional neural networks (CNNs) and vision transformers (ViTs) can provide promising outcomes in AD diagnosis. However, these technologies lack model interpretability and demand substantial computational resources, causing challenges in the resource-constrained environment. Hybrid ViTs can outperform individual ViTs by visualizing key features with limited computational power. This synergy enhances feature extraction and promotes model interpretability. Objectives: Thus, the authors present an innovative model for classifying AD using MRI images with limited computational resources. Methods: The authors improved the AD feature-extraction process by modifying the existing ViTs. A CatBoost-based classifier was used to classify the extracted features into multiple classes. Results: The proposed model was generalized using the OASIS dataset. The model obtained an exceptional classification accuracy of 98.8% with a minimal loss of 0.12. Conclusions: The findings highlight the potential of the proposed AD classification model in providing an interpretable and resource-efficient solution for healthcare centers. To improve model robustness and applicability, subsequent research can include genetic and clinical data.
Proenkephalin A 119–159 in Perioperative and Intensive Care—A Promising Biomarker or Merely Another Option?
Authors: Walczak-Wieteska Paulina , Zuzda Konrad , Małyszko Jolanta , Andruszkiewicz Paweł
Published: October 2024

Acute kidney injury (AKI) is a severe and prevalent syndrome, primarily observed in intensive care units (ICUs) and perioperative settings. The discovery of a new biomarker for kidney function and injury, capable of overcoming the limitations of traditional markers, has the potential to improve the diagnosis and management of AKI. Proenkephalin A 119–159 (PENK) has emerged as a novel biomarker for AKI and has been validated in various clinical settings. It has demonstrated a faster response to AKI compared to creatinine and has been shown to predict successful weaning from renal replacement therapy in the ICU. PENK has also shown promise as an AKI biomarker in perioperative patients. Additionally, PENK has been proven to be effective in estimating mortality and morbidity in patients undergoing cardiac surgery, and those with traumatic brain injury or ischemic stroke. Incorporating PENK into a novel estimation of the glomerular filtration rate, referred to as the PENK-Crea equation, has yielded promising results.
CMDN: Pre-Trained Visual Representations Boost Adversarial Robustness for UAV Tracking
Authors: Yu Ruilong , Wu Zhewei , Liu Qihe , Zhou Shijie , Gou Min , Xiang Bingchen
Published: October 2024

Visual object tracking is widely adopted to unmanned aerial vehicle (UAV)-related applications, which demand reliable tracking precision and real-time performance. However, UAV trackers are highly susceptible to adversarial attacks, while research on developing effective adversarial defense methods for UAV tracking remains limited. To tackle these challenges, we propose CMDN, a novel pre-processing defense network that effectively purifies adversarial perturbations by reconstructing video frames. This network learns robust visual representations from video frames, guided by meaningful features from both the search region and the template. Comprehensive experiments on three benchmarks demonstrate that CMDN is capable of enhancing a UAV tracker’s adversarial robustness in both adaptive and non-adaptive attack scenarios. In addition, CMDN maintains stable defense effectiveness when transferred to heterogeneous trackers. Real-world tests on the UAV platform also validate its reliable defense effectiveness and real-time performance, with CMDN achieving 27 FPS on NVIDIA Jetson Orin 16 GB (25 W mode).
Inclusive Teaching and Learning Practices That Promote and Protect Reading and Science Literacy for Palestinian Children
Authors: Aleghfeli Yousef Khalifa
Published: October 2024

Despite adversities arising from the Palestinian experience, studies have shown that Palestinian students can demonstrate educational resilience. However, a gap in knowledge exists about inclusive teaching and learning strategies that contribute to Palestinian students’ educational resilience. This research uses mixed-effects regression modelling to examine reading and science literacy outcomes of 1279 Palestinian students in UNRWA schools in Jordan. The findings revealed two promotive factors (student online reading and teacher–student relations) and two protective factors (student enjoyment of reading and student control strategies) for reading, and two protective factors (student awareness of environmental matters and student epistemological beliefs about science) for science. Knowledge about the promotive and protective factors has important implications for reading and science educators working with Palestinian children.
How Artificial Intelligence (AI) Is Powering New Tourism Marketing and the Future Agenda for Smart Tourist Destinations
Authors: Florido-Benítez Lázaro , del Alcázar Martínez Benjamín
Published: October 2024

Artificial intelligence (AI) is a disruptive technology that is being used by smart tourist destinations (STDs) to develop new business models and marketing services to increase tourists’ experiences and sales, revenue, productivity, and efficiency and STDs. However, the adoption of AI applications and platforms requires a high economic budget for STDs that want to integrate this digital tool into their future agenda and tourism development plans, especially when they set them up for marketing plans and operational processes. This iterative technology needs regular maintenance as well, leading to recurring costs and specialised crews in advanced technologies and marketing activities. This study aims to show the impact of AI advancements on STDs’ tourism marketing to enhance the quality of services and illustrate their future agenda to improve tourists’ experiences. A comprehensive literature review on AI technology and STDs has been conducted to illustrate new tourism marketing in their future agenda. Moreover, this study presents real examples of AI technology in a tourism context to better understand the potential of this digital tool. The findings of the current study support the idea that AI is a multipurpose tool that helps manage, monitor, and analyse sales information; revenue management; minimise prediction errors; streamline operations; and develop better marketing strategies, optimising economic resources, reducing marketing costs, and responding dynamically to changing needs for tourists and residents in STDs. Furthermore, the investment in AI technologies by STDs helps enhance the quality of products and services, and attract new investments, which benefit the regional economies and population’s quality of life. This study is the first to address the use of AI to improve tourist marketing in STDs, which is its primary uniqueness. Also, this study identifies new opportunities and initiatives through AI that can be developed to help tourism marketing in STDs.
Hybridization of Learning Techniques and Quantum Mechanism for IIoT Security: Applications, Challenges, and Prospects
Authors: Sikiru Ismaeel Abiodun , Kora Ahmed Dooguy , Ezin Eugène C. , Imoize Agbotiname Lucky , Li Chun-Ta
Published: October 2024

This article describes our point of view regarding the security capabilities of classical learning algorithms (CLAs) and quantum mechanisms (QM) in the industrial Internet of Things (IIoT) ecosystem. The heterogeneity of the IIoT ecosystem and the inevitability of the security paradigm necessitate a systematic review of the contributions of the research community toward IIoT security (IIoTsec). Thus, we obtained relevant contributions from five digital repositories between the period of 2015 and 2024 inclusively, in line with the established systematic literature review procedure. In the main part, we analyze a variety of security loopholes in the IIoT and categorize them into two categories—architectural design and multifaceted connectivity. Then, we discuss security-deploying technologies, CLAs, blockchain, and QM, owing to their contributions to IIoTsec and the security challenges of the main loopholes. We also describe how quantum-inclined attacks are computationally challenging to CLAs, for which QM is very promising. In addition, we present available IIoT-centric datasets and encourage researchers in the IIoT niche to validate the models using the industrial-featured datasets for better accuracy, prediction, and decision-making. In addition, we show how hybrid quantum-classical learning could leverage optimal IIoTsec when deployed. We conclude with the possible limitations, challenges, and prospects of the deployment.
Unraveling the Nuclear Debate: Insights Through Clustering of Tweets
Authors: Katalinić Josip , Dunđer Ivan , Seljan Sanja
Published: October 2024

The perception of nuclear power, while central to energy policy and sustainability endeavors, remains a subject of considerable debate, in which some claim that the expansion of nuclear technology poses threats to global security, while others argue that its access should be shared for development and energy purposes. In this study, a total of 11,256 tweets were gathered over a three-month period using a keyword-based approach through the Twitter Standard Search API, focusing on terms related to nuclear energy. The k-means clustering algorithm was employed to analyze tweets with the aim of determining the underlying sentiments and perspectives within the public domain, while t-SNE was used for visualizing cluster separation. The results show distinct clusters reflecting various viewpoints on nuclear power, with 71.94% of tweets being neutral, 14.64% supportive, and 13.42% negative. This study also identifies a subset of users who appear to be seeking unbiased information, signaling an opportunity for educational outreach. By leveraging the immediacy and pervasiveness of X (formerly known as Twitter), this research provides a timely snapshot of the prevailing attitudes toward nuclear power and offers insights for policymakers, educators, and industry stakeholders.
Millimeter-Wave Radar Clutter Suppression Based on Cycle-Consistency Generative Adversarial Network
Authors: Li Ziyi , Li Yang , Wang Yanping , Zheng Tong , Qu Hongquan
Published: October 2024

Vehicle-mounted millimeter-wave radar is widely used in autonomous driving systems for its ability to observe road scenes at all times and in all weathers. However, the data collected by millimeter-wave radar are seriously affected by the existence of clutter. This clutter will result in false detection during object detection. To address this issue, a feature extraction network with clutter suppression is necessary. This paper proposes a new clutter suppression method for millimeter-wave Range–Angle (RA) images based on a cycle-consistency generative adversarial network (CycleGAN). The generator of the method can be used as the feature extraction network of the object detection. The method aims to convert cluttered images into clutter-free images by unsupervised learning. In this method, an attention gate (AG) is introduced into the generator, a spatial attention mechanism that improves the ability of the model to automatically learn to focus on the features of targets and suppress the clutter of the background. Additionally, the target consistency loss term is added to the loss function to maintain target integrity while suppressing network training overfitting. The public dataset CRUW is utilized to evaluate the performance of the proposed method, which is compared and analyzed with traditional methods and deep learning methods. Experimental results show that the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) of the proposed method reach 39.846 and 0.990, respectively.
Public Authentic-Replica Sampling Mechanism in Distributed Storage Environments
Authors: Ye Jiale , Bai Yongmei , Xu Jiang , Huang Shitao , Han Zhaoyang , Wan Wei
Published: October 2024

With the rapid development of wireless communication and big data analysis technologies, the storage of massive amounts of data relies on third-party trusted storage, such as cloud storage. However, once data are stored on third-party servers, data owners lose physical control over their data, making it challenging to ensure data integrity and security. To address this issue, researchers have proposed integrity auditing mechanisms that allow for the auditing of data integrity on cloud servers without retrieving all the data. To further enhance the availability of data stored on cloud servers, multiple replicas of the original data are stored on the server. However, in existing multi-replica auditing schemes, there is a problem of server fraud, where the server does not actually store the corresponding data replicas. To tackle this issue, this paper presents a formal definition of authentic replicas along with a security model for the authentic-replica sampling mechanism. Based on time-lock puzzles, identity-based encryption (IBE) mechanisms, and succinct proof techniques, we design an authentic replica auditing mechanism. This mechanism ensures the authenticity of replicas and can resist outsourcing attacks and generation attacks. Additionally, our schemes replace the combination of random numbers and replica correspondence tables with Linear Feedback Shift Registers (LFSRs), optimizing the original client-side generation and uploading of replica parameters from being linearly related to the number of replicas to a constant level. Furthermore, our schemes allow for the public recovery of replica parameters, enabling any third party to verify the replicas through these parameters. As a result, the schemes achieve public verifiability and meet the efficiency requirements for authentic-replica sampling in multi-cloud environments. This makes our scheme more suitable for distributed storage environments. The experiments show that our scheme makes the time for generating copy parameters negligible while also greatly optimizing the time required for replica generation. As the amount of replica data increases, the time spent does not grow linearly. Due to the multi-party aggregation design, the verification time is also optimal. Compared to the latest schemes, the verification time is reduced by approximately 30%.
The Potential of Wood Construction Waste Circularity
Authors: Kiesnere Gunita , Atstaja Dzintra , Cudecka-Purina Natalija , Susniene Rozita
Published: October 2024

Wood construction waste circularity presents enormous potential to significantly de-crease total greenhouse gas (GHG) emissions in the European Union (EU). Latvia could become a frontrunner due to its historic relationship with forestry, wood construction practises and unused potential of the innovative application of wood. This research examines what the potential of “circular wood” in Latvia is, how ready the Latvian wood house construction sector is to engage in a circular economy and wood waste circularity and whether the legal framework is ready to support wood waste management in the country. This study presents a combined approach for systematic wood construction product circularity assessment that includes a review of existing EU and Latvian frameworks for construction and demolition waste (CDW) management and wood construction, a general analysis of wood waste recycling systems and technologies, a quantitative data analysis of construction waste management in Latvia and qualitative data analysis of the Latvian wood house construction sector, and interviews with a focus group of Latvian wood industry representatives. The Latvian scope has allowed us to clarify the pattern methodology and impact points to be replicated, tested and measured further on a broader scale, in other countries, or throughout the whole EU. The main findings reveal a potential life cycle assessment (LCA) verifying the circularity of wood and limitations of wood construction waste circularity in Latvia in terms of wood house construction industry readiness and a legal framework as well as overall social prejudices for circular construction. Findings indicate an overall awareness and level of willingness to participate and engage in the circular construction models among Latvians; however, proactiveness and support (legal and financial) is expected from the government and municipalities. The recommendations point towards improvements in wood waste data management, the wood construction sector and the overall impact on sustainable development goals.
Enhancing Flame Retardancy in Epoxy Resin with Clever Self-Assembly Method for Optimizing Interface Interaction via Well-Dispersed Cerium Oxide on Piperazine Pyrophosphate
Authors: Zhao Jiajun , Wu Zhengqian , Hong Yutong , Li Hongyu , Qian Junbo , Wu Kailiang , Xia Yan
Published: October 2024

Developing flame-retardant epoxy resins (EPs) is essential to broaden their industrial applications, as their inherent flammability restricts their widespread use. In this study, commercial cerium oxide (CeO2) nanoparticles were modified with oleic acid and successfully assembled onto the surface of pyrophosphate piperazine (PAPP) through a simple solvophobic effect, constructing an integrated superstructure flame retardant, CeO2@PAPP, with enhanced performance integration. Compared to traditional simple blends, the EP composite with 10 wt% CeO2@PAPP displayed superior flame retardancy, thanks to the more subtle synergistic effects between flame retardant components and their favorable interface interactions. The EP composite achieved a UL-94 V-0 rating and increased the limiting oxygen index (LOI) to 34.2%. Significant reductions of 56.3% in peak heat release rate (PHRR) and 38.2% in total heat release (THR) were observed. Furthermore, total smoke release (TSR), carbon monoxide yield (COPR), and carbon dioxide yield (CO2PR) decreased by 52.2%, 50.2%, and 67.3%, respectively. Through comprehensive and detailed characterization, it was discovered that the assembled integrated CeO2@PAPP flame retardant can perform better in both the gas phase and condensed phase, resulting in superior flame-retardant properties. This study offers an effective strategy for developing highly flame-retardant EPs, thereby expanding their potential applications across various industries.
Characteristics and Typical Influential Factors of Wildfire Caused by High-Voltage Transmission Line Breakage Faults
Authors: Zhang Ruizhe , Zhou Kai , Zhang Pei , Cai Yingmiao , Li Chunsheng , Li Hongda
Published: October 2024

In order to investigate the characteristics and typical influential factors of wildfires caused by accidental faults in high-voltage transmission lines, a bespoke platform was constructed for the purpose of conducting simulation experiments. Discharge and ignition experiments were conducted on a variety of substrates, including kidney fern fragments, cedar needle fragments, poplar sawdust, and eucalyptus leaf fragments, to investigate the effects of different gaps on the initiation and propagation of wildfires. The results demonstrate that the discharge-inducing ignition stages can be succinctly summarized as “two phases and two points” (the discharge induction period, the gap breakdown point, the arc induction period and the fault removal point) when a suitable gap is maintained between the simulated falling lines and the vegetation surface. In the event of direct contact, the removal of the fault is not possible. The potential for ignition of the aforementioned vegetation types by the discharge is as follows: cedar needles > eucalyptus leaf fragments ≈ poplar sawdust > kidney fern fragments. As the water content increases, eucalyptus leaf fragments can still be ignited, and the breakdown voltages required for discharge-inducing ignitions gradually decrease. In the case of different forest ground vegetation types, when ignited by the discharge between the falling lines and the vegetation under conditions of proper gap and moisture content, the resulting ignition and sustained flames will promote the formation of streamer channels and further aggravate the discharges and burning processes, potentially leading to the ignition of a wildfire.
Impact of Drying Methods on Phenolic Composition and Bioactivity of Celery, Parsley, and Turmeric—Chemometric Approach
Authors: Latinović Staniša , Vasilišin Ladislav , Pezo Lato , Lakić-Karalić Nataša , Cvetković Dragoljub , Ranitović Aleksandra , Brunet Sara , Cvanić Teodora , Vulić Jelena
Published: October 2024

Drying is one of the most commonly used methods for food preservation, and in spice processing, it has a significant impact on quality. In this paper, the influences of drying at room temperature, 60 °C, and 90 °C and freeze-drying on celery and parsley roots and turmeric rhizomes were examined. The highest content of total phenolics was found in celery dried at 60 °C (C60), parsley at room temperature (PRT), and freeze-dried turmeric (TFD) (1.44, 1.58, and 44.92 mg GAE/gdm, respectively). Celery dried at room temperature (CRT), PRT, and TFD showed the highest antioxidant activity regarding the DPPH and ABTS radicals and FRAP. The analysis of color parameters revealed that celery dried at 90 °C (C90); PFD and TFD showed the most similar values to control samples. The drying process was optimized using a combination of standard score (SS) and artificial neural network (ANN) methods. The ANN model effectively evaluated the significance of drying parameters, demonstrating high predictive accuracy for total phenolics, total flavonoids, total flavonols, total flavan-3-ols, IC50ABTS, and FRAP. TFD showed the strongest α-glucosidase inhibitory potential. Also, TFD extract showed good antibacterial activity against Staphylococcus aureus but not against Escherichia coli. C90 and PFD extracts did not show antibacterial activity against the tested microorganisms.
Effects of Discharge Parameters on the Thawing Characteristics and Physicochemical Properties of Beef in a Dielectric Barrier Discharge (DBD) System
Authors: Zhang Jie , Zhao Rui , Zhang Yaming , Wang Huixin , Song Zhiqing , Xing Ru , Lu Jingli , Ding Changjiang
Published: October 2024

Traditional thawing techniques can cause certain losses to beef quality. Due to the increasing demand for high-quality beef, there is an urgent need to research new thawing techniques. Dielectric barrier discharge (DBD), as an innovative non-thermal thawing technology, still has a lot of work to be studied. In order to explore the influence of DBD on the thawing characteristics and quality of beef, different discharge parameters were used for thawing. The results show that voltage and needle distance have significant effects on ion wind speed and composition. Ion wind can improve the thawing rate, and the thawing time of DBD is 50% shorter than that of natural thawing. DBD improved the water-holding capacity, nutritional components, and color of beef, and the ordered structure of beef protein could be improved by 6.25% at most. The plasma emission spectrum shows that the plasma produced by DBD is mainly active substances of nitrogen and oxygen, which can reduce the fat oxidation of thawed beef and improve the quality of beef. This work provides the theoretical basis and practical guidance for deeply understanding the influencing parameters and thawing mechanism of DBD thawing technology.
Developing an Active Biodegradable Bio-Based Equilibrium Modified Atmosphere Packaging Containing a Carvacrol-Emitting Sachet for Cherry Tomatoes
Authors: Kapetanakou Anastasia E. , Mistriotis Antonis , Bozinaki Dimitra C. , Tserotas Philippos , Athanasoulia Ioanna-Georgia , Briassoulis Demetrios , Skandamis Panagiotis N.
Published: October 2024

This study aimed to develop an active biodegradable bio-based (polylactic acid/PLA) equilibrium modified atmosphere packaging (EMAP) containing a carvacrol-emitting sachet (created by poly-hydroxybutyrate) (PLA-PHB-CARV) to extend the shelf-life of cherry tomatoes at 15 °C and 25 °C. Cherry tomatoes in macro-perforated polypropylene (PP) films (mimicking the commercial packaging) or in PLA-based micro-perforated film without the carvacrol sachet (PLA) were also tested. Weight loss, decay, headspace gases, pH, titratable acidity (TA), total suspended solids (TSS), ripening index, color, texture, total viable counts (TVC), and sensory analysis were performed. Decay was 40% in PLA-PHB-CARV, and 97% in PP after 20 days at 25 °C. PLA-PHB-CARV showed lower weight loss (p < 0.05) and stable firmness compared to PP and PLA at both temperatures. TSS and TA were not affected by the packaging at 15 °C, while at 25 °C, the TSS accumulation was inhibited in PLA-PHB-CARV compared to in PLA and PP (p < 0.05), indicating a notable delay in the ripening process. PLA-PHB-CARV retained their red color during storage compared to PP and PLA. Carvacrol addition inhibited TVC compared to PP and PLA by ca. 2.0 log CFU/g during storage at 25 °C, while at 15 °C, the packaging did not reveal a significant effect. Overall, the results indicated that the developed active EMAP may be adequately used as an advanced and alternative packaging for tomatoes or potentially other fruits with a similar respiration rate versus their conventional packaging, showing several advantages, e.g., a reduction in petrochemical-based plastics use, shelf-life extension of the packaged food, and consequently, the perspective of limiting food waste during distribution and retail or domestic storage.
Comparative Study on the Fermentation Characteristics of Selective Lactic Acid Bacteria in Shanxi Aged Vinegar: Pure Culture Versus Co-Culture
Authors: Li Qi , Zhang Yujing , Wang Chaomin , Zhang Xiaoyu , Wei Ruteng , Li Yunlong , Li Qiqiong , Xu Nv
Published: October 2024

The diversity of the microbial community structure plays a crucial role in the flavor and nutritional value of Shanxi aged vinegar in fermentation. Illumina Miseq high-throughput sequencing identified thirteen bacterial genera, with Lactobacillales (44.89%) and Acetobacter (21.04%) being the predominant species. Meanwhile, the fermentation characteristics of selected lactic acid bacteria strains isolated from Shanxi aged vinegar were studied in different media. The results showed that the biomass, and physical and chemical indices, as well as flavor compounds of the four strains of lactic acid bacteria in the simulated vinegar fermented grains medium were superior to those in barley and pea medium and sorghum juice medium. The bacterial interaction was conducted to investigate the effects on growth, the physicochemical indices, and flavor substances in order to determine the optimal combination. Furthermore, the interaction between pure cultures and co-cultures of lactic acid bacteria in a simulated vinegar culture medium was investigated, with a focus on the impact of this interaction on strain growth, fermentation characteristics, and flavor compound production. Compared with the pure culture, when strains L7 and L729 were co-inoculated, the reducing sugar content was 0.31 ± 0.01 g/100 g, total acid content was 3.02 ± 0.06 g/100 g, acetoin content was 2.41 ± 0.07 g/100 g, and total organic acid content was 3.77 ± 0.17 g/100 g. In terms of flavor compounds, the combined culture system exhibited higher levels of esters, aldehydes, and acids compared to pure cultures or other co-culture systems. This study revealed the fermentation characteristics of selected lactic acid strains in Shanxi aged vinegar under different conditions and their interaction in simulated vinegar fermentation media, which could provide theoretical support for the safety and health evaluation of aged vinegar.