bluuebunny/crossref_metadata_2025 huggingface dataset:
Beneficial Effects of Micronutrient Supplementation in Restoring the Altered Microbiota and Gut–Retina Axis in Patients with Neovascular Age-Related Macular Degeneration—A Randomized Clinical Trial
Authors: Baldi Simone , Pagliai Giuditta , Di Gloria Leandro , Pallecchi Marco , Barca Francesco , Pieri Benedetta , Bartolucci Gianluca , Ramazzotti Matteo , Amedei Amedeo , Palendri Gianna , Sofi Francesco
Published: November 2024

Background/Objectives: Age-related macular degeneration (AMD) is a leading cause of visual impairment in the elderly and is characterized by a multifactorial etiology. Emerging evidence points to the potential involvement of the gut–retina axis in AMD pathogenesis, prompting exploration into novel therapeutic strategies. This study aims to investigate the effects of some micronutrients (such as lutein and zeaxanthin) and saffron (as a supplement)—known for their anti-inflammatory properties—on ophthalmological and microbial parameters in neovascular AMD (nAMD) patients. Methods: Thirty naive nAMD patients were randomized to receive daily micronutrient supplementation alongside anti-VEGF (vascular endothelial growth factor) therapy, or anti-VEGF treatment alone, over a 6-month period, with comparisons made to a healthy control (HC) group (N = 15). Ophthalmological assessments, biochemical measurements, and stool samples were obtained before and after treatment. Gut microbiota (GM) characterization was performed using 16S rRNA sequencing, while short-chain fatty acids (SCFAs), medium-chain fatty acids (MCFAs), and long-chain fatty acids (LCFAs) were analyzed with a gas chromatography–mass spectrometry protocol. Results: Compared to HC, nAMD patients exhibited reduced GM alpha diversity, altered taxonomic composition, and decreased total SCFA levels, in addition to elevated levels of proinflammatory octanoic and nonanoic acids. Micronutrient supplementation was associated with improved visual acuity relative to the group treated with anti-VEGF alone, along with a decrease in the total amount of MCFAs, which are metabolites known to have adverse ocular effects. Conclusions: In conclusion, despite certain limitations—such as the limited sample size and the low taxonomic resolution of 16S rRNA sequencing—this study highlights compositional and functional imbalances in the GM of nAMD patients and demonstrates that micronutrient supplementation may help restore the gut–retina axis. These findings suggest the therapeutic potential of micronutrients in enhancing ocular outcomes for nAMD patients, underscoring the complex interaction between GM and ocular health.
Calcium, Vitamin D, and Aging in Humans
Authors: Dominguez Ligia J. , Gonnelli Stefano
Published: November 2024

There is currently a growing awareness that nutritional factors have major impacts on the risk of age-associated chronic non-communicable diseases and mortality [...]
Tree Nut Allergy in Children—What Do We Know? —A Review
Authors: Chudoba Anna , Żebrowska Agata , Sybilski Adam J.
Published: November 2024

Food allergy represents a significant public health concern, with its prevalence increasing in recent decades. Tree nuts are among major allergenic foods, and allergies to them are frequently linked to severe and potentially life-threatening reactions. Data on the prevalence and natural history of tree nut allergy are limited. Primary nut allergy typically presents with rapid-onset IgE-mediated symptoms. Diagnosis can be confirmed by demonstrating a positive skin prick test (SPT), specific IgE (sIgE), or through an oral food challenge. Component-resolved diagnostics (CRD) can identify those with a high risk of anaphylaxis. The main management strategy involves avoiding the culprit allergen and treating symptoms after accidental exposure. New therapeutic options, such as sublingual immunotherapy, oral food immunotherapy, with or without omalizumab, and other monoclonal antibodies, are being investigated to modify tree nut allergy. Tree nut allergy is a lifelong disease with a low likelihood of resolution. The aim of this paper is to present the current data on the prevalence, diagnosis, natural history, and management options for tree nut allergy.
Exploring the Relationship Between Cooking and Food Skills and Eating Competence Among Brazilian Adults
Authors: Lins Maísa , Nakano Eduardo Yoshio , Soares João Rafael Queiroz , Queiroz Fabiana Lopes Nalon de , Botelho Raquel Braz Assunção , Raposo António , Zandonadi Renata Puppin
Published: November 2024

Background: Cooking skills (CSs) and food skills (FSs) are essential in promoting healthier eating habits. Eating competence (EC) encompasses an individual’s self-regulation, enjoyment, and positive attitude toward food, contributing to their overall well-being. However, no research has explored the relationship between CSs, FSs, and EC, particularly within the Brazilian context. Objective: This study aimed to assess the association between EC and CFSs among Brazilian adults. Methods: A cross-sectional survey was conducted among 1266 Brazilian adults using two validated instruments: the Cooking and Food Skill Confidence Questionnaire (CFS) and the Brazilian version of the Satter Eating Competence Inventory (ecSI2.0™BR). Pearson’s and Spearman’s correlations were used to analyze the relationships between CSs, FSs, and EC. Results: A significant positive correlation was found between higher levels of CSs and the overall EC (r = 0.417, p < 0.001), with complex cooking tasks showing stronger associations with EC. Contextual skills within EC exhibited the highest correlation with FSs (r = 0.487). Basic tasks, such as microwaving food, showed weaker associations with EC. Conclusions: The findings suggest that enhancing cooking and food skills may support greater eating competence, promoting healthier eating behaviors. Public health programs should consider integrating cooking skill development to foster better dietary outcomes and improve individual well-being.
The Presence of Added Sugars and Other Sweeteners in Food and Beverage Products Advertised on Television in the United States, 2022
Authors: Schermbeck Rebecca M. , Leider Julien , Powell Lisa M.
Published: November 2024

Background/Objectives: The Dietary Guidelines for Americans recommend consuming less than 10% of total calories from added sugars. Low-calorie sweeteners, sugar alcohols, and natural low-calorie sweeteners are used to reduce added sugar intake, but there are concerns about their long-term health impacts, especially for children. This paper describes the food and beverage television advertising landscape as it pertains to sweeteners. Methods: This cross-sectional study uses television ratings data licensed from The Nielsen Company for the United States in 2022. Nutrition facts panels and ingredient lists were collected for food and beverage product advertisements seen on television and assessed for the presence of added sugars, low-calorie sweeteners, sugar alcohols, and natural low-calorie sweeteners (forms of stevia and monk fruit), as well as whether products were high in added sugars based on federal Interagency Working Group guidelines for advertising to children. Results: Of the sweeteners examined, added sugars were most commonly found in food and beverage product advertisements seen on television (60–68% of advertisements seen across age groups), followed by low-calorie sweeteners (6–10%), sugar alcohols (2–4%), and natural low-calorie sweeteners (2%). About one-third (32–33%) of advertisements seen by 2–5- and 6–11-year-olds were high in added sugars, similar to the percentage seen by 12–17- and 18+-year-olds (34–35%). Advertisements seen for cereal (86–95%) and sweets (92–93%) were most likely to have added sugars, while those for sweets (89–90%) were most likely to be high in added sugars. Conclusions: Sweeteners are common in food and beverage product advertisements seen on television, including alternatives to added sugars for which there are concerns about long-term impacts on health. Continued monitoring and additional research on other advertising media platforms used by food and beverage companies (e.g., digital media) is needed.
Prevalence, Risk Factors and Association with Clinical Outcomes of Malnutrition and Sarcopenia in Inflammatory Bowel Disease: A Prospective Study
Authors: Bezzio Cristina , Brinch Daniele , Ribaldone Davide Giuseppe , Cappello Maria , Ruzzon Natalie , Vernero Marta , Scalvini Davide , Loy Laura , Donghi Sofia , Ciminnisi Stefania , Manes Gianpiero , Armuzzi Alessandro , Saibeni Simone
Published: November 2024

Introduction: The prevalences of malnutrition and sarcopenia in patients with IBD are not precisely known, and nutritional assessment is not standardized. We assessed the prevalence and risk factors of these conditions in outpatients and their impact on clinical outcomes. Methods: This prospective longitudinal study considered patients who had IBD for at least one year, were attending a tertiary IBD center, and were followed for the subsequent year. Results: In a sample of 158 consecutive patients (96 with Crohn’s disease and 62 with ulcerative colitis), the prevalence of malnutrition, according to GLIM criteria, was 13.3%. For identifying patients at risk of malnutrition, the Malnutrition Universal Screening Tool demonstrated better accuracy, (sensitivity 88.9 (65.3–98.6) and specificity 90.2 (83.8–93.4)) than the SaskIBD-NR questionnaire (sensitivity 69.3 (41.1–86.7) and specificity 60.9 (60.9–76.8)). The prevalence of sarcopenia was 34.2%. Considering clinical outcomes, sarcopenia at baseline was significantly associated with hospital admission within a year (p = 45.2% vs. 20.3%, 0.026). Conclusions: Malnutrition and sarcopenia were present in about one-third of IBD patients. Awareness should be raised among physicians caring for IBD patients about the need to evaluate patients’ nutritional statuses to help patients achieve a better quality of life.
Iodine-123 Metaiodobenzylguanidine (I-123 MIBG) in Clinical Applications: A Comprehensive Review
Authors: Chang Ming-Cheng , Peng Cheng-Liang , Chen Chun-Tang , Shih Ying-Hsia , Chen Jyun-Hong , Tai Yi-Jou , Chiang Ying-Cheng
Published: November 2024

Iodine-123 metaiodobenzylguanidine (I-123 MIBG) is a crucial radiopharmaceutical widely used in nuclear medicine for its diagnostic capabilities in both cardiology and oncology. This review aims to present a comprehensive evaluation of the clinical applications of I-123 MIBG, focusing on its use in diagnosing and managing various diseases. In cardiology, I-123 MIBG has proven invaluable in assessing cardiac sympathetic innervation, particularly in patients with heart failure, where it provides prognostic information that guides treatment strategies. In oncology, I-123 MIBG is primarily utilized for imaging neuroendocrine tumors, such as neuroblastoma and pheochromocytoma, where it offers high specificity and sensitivity in the detection of adrenergic tissue. Additionally, its role in neurology, specifically in differentiating between Parkinson’s disease, dementia, and Lewy body dementia, has become increasingly significant due to its ability to identify postganglionic sympathetic dysfunction. Despite its established clinical utility, the use of I-123 MIBG is not without limitations, including variability in imaging protocols and interpretation challenges. This review will explore these issues and discuss emerging alternatives, while also highlighting areas where I-123 MIBG continues to be a gold standard. By synthesizing the current research, this article aims to provide a clear understanding of the strengths, limitations, and prospects of I-123 MIBG in clinical practice.
Co-Amorphization, Dissolution, and Stability of Quench-Cooled Drug–Drug Coamorphous Supersaturating Delivery Systems with RT-Unstable Amorphous Components
Authors: Zhang Yan-Fei , Yao Qian , Lin Xiao-Ying , Ma Ying-Hui , Zhang Hui-Feng , Yu Huan , Mu Shang-Qiang , Zhang Chuang , Geng Hao , Hao Cheng-Yi , Zuo Li-Li , Wu Di , Li Yue , Jin Li-Li , Shi Nian-Qiu
Published: November 2024

Background: Supersaturating drug delivery systems (SDDSs) have gained significant attention as a promising strategy to enhance the solubility and bioabsorption of Biopharmaceutics Classification System (BCS) II drugs. To overcome challenges associated with polymer-based amorphous SDDS (aSDDS), coamorphous (CAM) systems have emerged as a viable alternative. Among them, “drug-drug” CAM (ddCAM) systems show considerable potential for combination drug therapy. However, many drugs in their pure amorphous forms are unstable at room temperature (RT), complicating their formation and long-term stability profiles. Consequently, limited knowledge exists regarding the behavior of ddCAMs containing RT-unstable components formed via quench cooling. Methods: In this study, we used naproxen (NAP), a RT-unstable amorphous drug, in combination with felodipine (FEL) or nitrendipine (NTP), two RT-stable amorphous drugs, to create “FEL-NAP” and “NTP-NAP” ddCAM pairs via quench cooling. Our work used a series of methods to perform a detailed analysis on the co-amorphization, dissolution, solubility, and stability profiles of ddCAMs containing RT-unstable drugs, contributing to advancements in co-amorphization techniques for generating SDDS. Results: This study revealed that the co-amorphization and stability profiles of ddCAMs containing RT-unstable components produced via a quench-cooling method were closely related to drug-drug pairing types and ratios. Both quench-cooling and incorporation into coamorphous systems improved the dissolution, solubility, and physical stability of individual APIs. Conclusions: Our findings provide deeper insight into the co-amorphization, dissolution, and stability characteristics of specific drug-drug coamorphous systems FEL-NAP and NTP-NAP, offering valuable guidance for developing new ddCAM coamorphous formulations containing some RT-unstable drugs.
Lipid Nanoparticle Formulations for the Skin Delivery of Cannabidiol
Authors: Calienni Maria Natalia , Scavone Mirian Ana , Sanguinetti Ana Paula , Corleto Merlina , Di Meglio Magalí Rocío , Raies Pablo , Cristos Diego Sebastián , Maffia Paulo César , Montanari Jorge
Published: November 2024

Background/Objectives: The aims of this work were to formulate cannabidiol in different lipid carriers for skin delivery after topical application and to study their stability, interaction with the skin, and antibacterial activity. Methods: Solid lipid nanoparticles and nanostructured lipid carriers loaded with cannabidiol were prepared and characterized in terms of their physicochemical properties, colloidal stability, protection of the antioxidant capacity of cannabidiol, as well as their retention over time. Skin penetration was assessed using an in vitro model with human skin. The antibacterial activity was tested against Staphylococcus aureus and compared to free cannabidiol. Results: Three nanoformulations exhibited the best size and reproducibility values and were selected for further studies. The formulations were stable, protected the active ingredient, succeeded in delivering it to deep skin layers, and demonstrated antibacterial activity. Conclusions: These cannabidiol nanoformulations show potential for use in skin diseases and conditions, as they protect the active ingredient, enhance its delivery to the skin, and exhibit antibacterial effects.
De Novo Transcriptome Assembly of Anoectochilus roxburghii for Morphological Diversity Assessment and Potential Marker Development
Authors: Zhang Wenting , Chen Ke , Mei Yu , Wang Jihua
Published: November 2024

Anoectochilus roxburghii is a rare and precious medicinal and ornamental plant of Orchidaceae. Abundant morphological characteristics have been observed among cultivated accessions. Our understanding of the genetic basis of morphological diversity is limited due to a lack of sequence data and candidate genes. In this study, a high-quality de novo transcriptome assembly of A.roxburghii was generated. A total of 138,385 unigenes were obtained, and a BUSCO (Benchmarking Universal Single-Copy Orthologs) analysis showed an assembly completeness of 98.8%. Multiple databases were used to obtain a comprehensive annotation, and the unigenes were functionally categorized using the GO (Gene Ontology), KOG (Eukaryotic Orthologous Groups), KEGG (Kyoto Encyclopedia of Genes and Genomes), and Nr databases. After comparing the phenotypic characteristics of five representative cultivars, a set of cultivar-specific, highly expressed unigenes was identified based on a comparative transcriptome analysis. Then, a WGCNA (Weighted Gene Co-expression Network Analysis) was performed to generate gene regulatory modules related to chlorophyll content (red) and sucrose synthase activity (black). In addition, the expression of six and four GO enrichment genes in the red and black modules, respectively, was analyzed using qRT-PCR to determine their putative functional roles in the leaves of the five cultivars. Finally, in silico SSR (Simple Sequence Repeat) mining of the assembled transcriptome identified 44,045 SSRs. Mononucleotide was the most dominant class of SSRs, followed by complex SSRs. In summary, this study reports on the phenomic and genomic resources of A. roxburghii, combining SSR marker development and validation. This report aids in morphological diversity assessments of Anoectochilus roxburghii.
Preharvest Application of Exogenous 2,4-Epibrassinolide and Melatonin Enhances the Maturity and Flue-Cured Quality of Tobacco Leaves
Authors: Wei Kesu , Tang Jiayi , Yang Lei , Chen Shaopeng , Cheng Zhijun , Yang Yijun , Xu Chen , Wu Shengjiang , Zhao Yuhang , Di Hongmei , Li Ling , Sun Dongyang , Li Jianwei , Sun Bo
Published: November 2024

Tobacco (Nicotiana tabacum) is a globally cultivated crop, with its quality closely associated with the color and chemical composition of cured tobacco leaves. In this experiment, the effects of spraying exogenous 2, 4-epibrassinolide (EBR) and melatonin (MT) on the development of tobacco leaves at maturity stage and the quality after curing were investigated. Both EBR and MT treatments significantly enhanced the appearance quality of tobacco leaves at the stem-drying stage. Following preharvest applications, the sugar-to-alkali ratio and potassium content increased, while the contents of starch, total alkaloids, and proteins decreased. The levels of conventional chemical components were improved, enhancing the overall coordination of the tobacco. Transcriptome analysis revealed that EBR treatment down-regulated the chlorophyll biosynthetic genes hemA, MgPEC, and ChlD, while up-regulating the chlorophyll degradation genes CHL2, SGR, and PAOs. Similarly, MT treatment down-regulated the chlorophyll biosynthetic genes FC2 and MgPEC and up-regulated the degradation genes CHL2 and SGR, thus promoting chlorophyll degradation. Furthermore, in the downstream carotenoid biosynthetic pathway, both EBR and MT treatments regulated abscisic acid-related genes, with NCEDs being up-regulated and CYP707A1s down-regulated, thereby promoting the leaf ripening. Metabolomics analysis indicated that EBR treatment primarily regulated alkaloids, terpenoids, and flavonoids, while MT treatment mainly affected flavonoids. Both treatments also reduced the accumulation of the harmful substance aristolochic acid B. Comprehensive evaluations of appearance quality, physiological parameters, transcriptome, and metabolomics analyses demonstrated that exogenous spraying of EBR and MT treatments improved the maturity and quality of cured tobacco leaves, with EBR treatment exhibiting a greater effect than MT treatment.
Smart Automatic Irrigation Enhances Sap Flow, Growth, and Water Use Efficiency in Containerized Prunus × yedoensis Matsum. Seedling
Authors: Jin Eon-Ju , Choi Myung-Suk , Lee Hyeok , Bae Eun-Ji , Kim Do-Hyun , Yoon Jun-Hyuck
Published: November 2024

This study conducted a comparative analysis on the effects of smart automatic and semi-automatic irrigation methods on the physiological characteristics and growth of Prunus × yedoensis Matsum. seedlings. The smart automatic irrigation system, which activates irrigation when the soil moisture drops below 15%, demonstrated superior characteristics in sap-wood area and bark ratio, as well as excellent water management efficiency, compared to the semi-automatic irrigation method, which involves watering (2.0 L) for 10 min at 60 min intervals starting at 8 AM every day. The analysis of soil moisture content changes under varying weather conditions and irrigation methods showed that smart automatic irrigation effectively maintained optimal moisture levels. Moreover, sap flow in the smart automatic irrigation treatment was more efficiently regulated in response to seasonal variations, showing a strong correlation with climatic factors such as temperature and solar radiation. In contrast, the semi-automatic irrigation treatment led to excessive sap flow during the summer due to a fixed watering schedule, resulting in unnecessary water supply. Analysis of photosynthesis parameters and chlorophyll fluorescence also revealed that smart automatic irrigation achieved higher values in light compensation and saturation points, maximizing photosynthetic efficiency. These findings suggest that the smart automatic irrigation system can enhance plant growth and water use efficiency, contributing to sustainable water management strategies. This research provides critical foundational data for developing efficient agricultural and horticultural irrigation management strategies in response to future climate change.
Dulcitol/Starch Systems as Shape-Stabilized Phase Change Materials for Long-Term Thermal Energy Storage
Authors: Szatkowska Martyna , Pielichowska Kinga
Published: November 2024

In recent years, there has been an increasing interest in phase change materials (PCM) based on dulcitol and other sugar alcohols. These materials have almost twice as large latent heat of fusion as other organic materials. Sugar alcohols are relatively cheap, and they can undergo cold crystallization, which is crucial for long-term thermal energy storage. The disadvantage of dulcitol and other sugar alcohols is the solid–liquid phase transition. As a result, the state of matter of the material and its volume change, and in the case of materials modified with microparticles or nanoparticles, sedimentation of additives in liquid PCM can occur. In this study, we obtained shape-stable phase change materials (SSPCM) by co-gelation of starch and dulcitol. To characterize the samples obtained, differential scanning calorimetry (DSC), step-mode DSC, thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM) were used, and they were also used to test for shape stabilization. The results show that the obtained systems have great potential as shape-stabilized phase change materials. The sample dulcitol/starch with a 50:50 ratio exhibited the highest heat of cold crystallization, up to 52.90 J/g, while the heat of melting was 126.16 J/g under typical DSC measuring conditions. However, depending on the applied heating program, the heat of cold crystallization can even reach 125 J/g. The thermal stability of all compositions was higher than the phase change temperature, with only 1% mass loss occurring at temperatures above 200 °C, while the phase change occurred at a maximum of 190 °C.
Synthesis, Characterization, and Application Prospects of Novel Soluble Polysilsesquioxane Bearing Glutarimide Side-Chain Groups
Authors: Bolgova Yuliya I. , Emel’yanov Artem I. , Trofimova Olga M. , Ivanova Anastasiya A. , Albanov Alexander I. , Kuznetsova Nadezhda P. , Semenova Tatyana A. , Pozdnyakov Alexander S.
Published: November 2024

The requirement for the development of advanced technologies is the need to create new functional thermostable soluble polysilsesquioxanes. Combining the potential of organosilicon chemistry and the chemistry of heterocyclic compounds is a promising direction for the formation of novel organosilicon polymer systems with new properties and new possibilities for their practical application. Using the classical method of hydrolysis and polycondensation of previously unknown trifunctional (trimethoxysilylpropyl)glutarimide in the presence or absence of an acid or base catalyst, a universal approach to the formation of new thermostable soluble polysilsesquioxanes with glutarimide side-chain groups is proposed, which forms the basis for the synthesis of polysilsesquioxane polymers with different functionality. The weight average molecular weight of silsesquioxanes, determined by gel permeation chromatography, is practically independent of the reaction conditions and is 10–12 kDa; at the same time, the molecular weight distribution remains low and amounts to 1.38–1.47. According to thermogravimetric analysis, the resulting polysiloxanes have high thermal stability up to 335 °C. By the dynamic light scattering method, it was established that in an aqueous solution, silsesquioxane macromolecules are in an associated state, forming supramolecular structures due to the intermolecular interaction of individual macromolecules. The average hydrodynamic diameter of the particles was 46 nm. X-ray diffraction analysis showed the amorphous nature of the polymer. Polymer film coatings based on synthesized silsesquioxanes are characterized by 98% transmission in the visible spectrum and resistance to ultraviolet radiation, which is promising for the creation of functional transparent film coatings.
A Discrete Distributed Activation Energy Model for Cedar and Polyethylene Fast Heating Pyrolysis Kinetics
Authors: Wu Sanjun , Liu Haiyang , Duan Qiwei , Li Jiaye , Sun Qi , Li Zhenshan
Published: November 2024

The pyrolysis of municipal solid waste (MSW) is an efficient, cost-effective, and environmentally beneficial thermochemical treatment method. A macro thermogravimetric analyzer (Macro TGA) was used to study the pyrolysis behavior of cedar and polyethylene (PE) at slow (10 K/min) and fast (700, 800, and 900 °C) heating rates. For cedar, the pyrolysis rate curve showed multi-peak characteristics at the slow heating rate and single-peak characteristics at the fast heating rate. Conversely, PE exhibited the opposite behavior. At fast heating rate of 700 °C, the pyrolysis rate for cedar increased from 0.685 to 0.847 min−1 as the sample temperature rose by over 100 °C, from 351 to 455 °C. By contrast, for PE, the rate increased from 0.217 to 1.008 min−1 with a smaller temperature rise of less than 30 °C, from 630 to 656 °C. According to the International Confederation for Thermal Analysis and Calorimetry (ICTAC) guidelines for analyzing pyrolysis thermogravimetric data, cedar pyrolysis primarily followed a single-step parallel reaction pathway, while PE exhibited some multi-step parallel reactions. A newly developed discrete distributed activation energy model (DDAEM), along with the traditional iso-conversional model (ICM) and distributed activation energy model (DAEM), were applied to predict pyrolysis characteristics at fast heating rates. For cedar, both DDAEM and ICM provide accurate predictions, with average activation energies calculated by these two models being 48.08 and 66.37 kJ/mol, respectively. For PE, DDAEM demonstrates significantly higher predictive accuracy than ICM, particularly when the conversion is below 0.2. As the pyrolysis conversion of PE increases from 0.25 to 0.65, the average activation energy calculated using ICM was found to be 58.32 kJ/mol. By contrast, for DDAEM, the activation energies for the first and second step reactions were 110 and 60 kJ/mol, respectively. This indicates that ICM can only calculate the activation energy for the final step and not for the rate-limiting step. For both cedar and PE, DAEM fails to provide accurate predictions due to the unsteady heating rate.
Application of SPEA2-MMBB for Distributed Fault Diagnosis in Nuclear Power System
Authors: Xu Ying , Ma Jie , Yuan Jinxiao
Published: November 2024

Accurate fault diagnosis in nuclear power systems is essential for ensuring reactor stability, reducing the risk of potential faults, enhancing system reliability, and maintaining operational safety. Traditional diagnostic methods, especially those based on single-system approaches, struggle to address the complexities of composite faults and highly coupled fault data. In this paper, we introduce a distributed fault diagnosis method for nuclear power systems that leverages the Strength Pareto Evolutionary Algorithm 2 (SPEA2) for multi-objective optimization and a modified MobileNetV3 neural network with a Bottleneck Attention Module (MMBB). The SPEA2 algorithm is used to optimize sensor feature selection, and the sensor data are then input into the MMBB model for training. The MMBB model outputs accuracy rates for each subsystem and the overall system, which are subsequently used as optimization targets to guide SPEA2 in refining the sensor selection process for distributed diagnosis. The experimental results demonstrate that this method significantly enhances subsystem accuracy, with an average accuracy of 98.73%, and achieves a comprehensive system accuracy of 95.22%, indicating its superior performance compared to traditional optimization and neural network-based approaches.
Underutilized Feature Extraction Methods for Burn Severity Mapping: A Comprehensive Evaluation
Authors: Nguyen Van Linh , Lee Giha
Published: November 2024

Wildfires increasingly threaten ecosystems and infrastructure, making accurate burn severity mapping (BSM) essential for effective disaster response and environmental management. Machine learning (ML) models utilizing satellite-derived vegetation indices are crucial for assessing wildfire damage; however, incorporating many indices can lead to multicollinearity, reducing classification accuracy. While principal component analysis (PCA) is commonly used to address this issue, its effectiveness relative to other feature extraction (FE) methods in BSM remains underexplored. This study aims to enhance ML classifier accuracy in BSM by evaluating various FE techniques that mitigate multicollinearity among vegetation indices. Using composite burn index (CBI) data from the 2014 Carlton Complex fire in the United States as a case study, we extracted 118 vegetation indices from seven Landsat-8 spectral bands. We applied and compared 13 different FE techniques—including linear and nonlinear methods such as PCA, t-distributed stochastic neighbor embedding (t-SNE), linear discriminant analysis (LDA), Isomap, uniform manifold approximation and projection (UMAP), factor analysis (FA), independent component analysis (ICA), multidimensional scaling (MDS), truncated singular value decomposition (TSVD), non-negative matrix factorization (NMF), locally linear embedding (LLE), spectral embedding (SE), and neighborhood components analysis (NCA). The performance of these techniques was benchmarked against six ML classifiers to determine their effectiveness in improving BSM accuracy. Our results show that alternative FE techniques can outperform PCA, improving classification accuracy and computational efficiency. Techniques like LDA and NCA effectively capture nonlinear relationships critical for accurate BSM. The study contributes to the existing literature by providing a comprehensive comparison of FE methods, highlighting the potential benefits of underutilized techniques in BSM.
An Efficient Flow-Based Anomaly Detection System for Enhanced Security in IoT Networks
Authors: Mutambik Ibrahim
Published: November 2024

The growing integration of Internet of Things (IoT) devices into various sectors like healthcare, transportation, and agriculture has dramatically increased their presence in everyday life. However, this rapid expansion has exposed new vulnerabilities within computer networks, creating security challenges. These IoT devices, often limited by their hardware constraints, lack advanced security features, making them easy targets for attackers and compromising overall network integrity. To counteract these security issues, Behavioral-based Intrusion Detection Systems (IDS) have been proposed as a potential solution for safeguarding IoT networks. While Behavioral-based IDS have demonstrated their ability to detect threats effectively, they encounter practical challenges due to their reliance on pre-labeled data and the heavy computational power they require, limiting their practical deployment. This research introduces the IoT-FIDS (Flow-based Intrusion Detection System for IoT), a lightweight and efficient anomaly detection framework tailored for IoT environments. Instead of employing traditional machine learning techniques, the IoT-FIDS focuses on identifying unusual behaviors by examining flow-based representations that capture standard device communication patterns, services used, and packet header details. By analyzing only benign traffic, this network-based IDS offers a streamlined and practical approach to securing IoT networks. Our experimental results reveal that the IoT-FIDS can accurately detect most abnormal traffic patterns with minimal false positives, making it a feasible security solution for real-world IoT implementations.
Intelligent Identification and Prediction of Roof Deterioration Areas Based on Measurements While Drilling
Authors: Wu Jing , Zhao Zhi-Qiang , Wang Xiao-He , Wang Yi-Qing , Wei Xiao-Xiang , You Zhi-Qiang
Published: November 2024

During roadway excavation, the presence of roof deterioration zones, such as layered spaces and weak interlayers, significantly affects the stability of the surrounding rock. To achieve timely and effective support for roadways, it is essential to utilize drilling measurement signals obtained during the construction of anchorage holes for the identification and prediction of these deterioration zones. This study systematically investigates the response characteristics of thrust, torque, and Y-direction vibration signals to different combinations of rock layers through theoretical analysis, laboratory experiments, ABAQUS dynamic numerical simulations, and field measurements. The results indicate that these drilling parameters effectively characterize variations in rock structure and strength, with distinct signal features observed particularly in roof deterioration zones. Based on these findings, this paper proposes a deep learning algorithm that employs Long Short-Term Memory (LSTM) recurrent neural networks for classification prediction, along with a random forest algorithm for regression prediction, aimed at the intelligent identification and prediction of roof deterioration zones. The algorithm demonstrates outstanding performance in both laboratory experiments and field tests, achieving a 100% recognition rate for layered spaces and a 96.6% accuracy for identifying deterioration zones, with high accuracy at lower values of mechanical specific energy (MSE). The proposed method provides significant insights for real-time monitoring and control of roof deterioration zones, enhancing the safety and stability of roadway excavations, and serves as a valuable reference for future research and practical applications.
Near-Field Communication (NFC) Cyber Threats and Mitigation Solutions in Payment Transactions: A Review
Authors: Onumadu Princewill , Abroshan Hossein
Published: November 2024

Today, many businesses use near-field communications (NFC) payment solutions, which allow them to receive payments from customers quickly and smoothly. However, this technology comes with cyber security risks which must be analyzed and mitigated. This study explores the cyber risks associated with NFC transactions and examines strategies for mitigating these risks, focusing on payment devices. This paper provides an overview of NFC technology, related security vulnerabilities, privacy concerns, and fraudulent activities. It then investigates payment devices such as smartphones, contactless cards, and wearables, highlighting their features and vulnerabilities. The study also examines encryption, authentication, tokenization, biometric authentication, and fraud detection methods as risk mitigation strategies. The paper synthesizes theoretical frameworks to provide insights into NFC transaction security and offers stakeholder recommendations.
Eddy Current Measurement of Electrical Resistivity in Heat-Treated Zr-2.5%Nb Pressure Tubes
Authors: Thorpe W. G. , Underhill P. R. , Krause T. W.
Published: November 2024

Zr-2.5%Nb pressure tubes (PTs) house uranium fuel bundles in the fuel channels of CANDU® nuclear reactors. Preventing a failure mode caused by contact of the PT with an outer calandria tube (CT) is performed by inspection using eddy current (EC) testing and ultrasonic testing (UT) to measure the PT-CT gap. EC gap measurements are particularly sensitive to circumferential variation of the PT’s electrical resistivity due to microstructural variations. A full-factorial experiment was performed to examine the statistical significance of variations in the EC test parameters and manufacturing conditions on the average circumferential electrical resistivity of as-manufactured PTs. It was found that 79% of the variance in the data could be attributed to variations caused by any of the test factors or combinations of test factors. The parameters that accounted for the majority of the variance were: (1) heat treatment (HT); (2) HT and EC frequency; (3) probe inner or outer surface placement; and (4) EC frequency. Measurements of circumferential resistivity showed up to ±2.3% variation from the average of either surface. HT caused the average PT resistivity to decrease at a rate of 1.53±0.08 μΩ·cmlog⁡hr and 1.1±0.4μΩ·cmlog⁡hr for inner and outer PT surfaces, respectively. The results are correlated with differences reported in the literature in the average βZr ribbon thickness in the axial-transverse cross-section between inner and outer PT surfaces. The results demonstrate potential for EC-based resistivity measurements to characterize variations and changes in the microstructure of Zr-2.5%Nb PT material.
The Design and Implementation of Kerberos-Blockchain Vehicular Ad-Hoc Networks Authentication Across Diverse Network Scenarios
Authors: Rahayu Maya , Hossain Md. Biplob , Huda Samsul , Kodera Yuta , Ali Md. Arshad , Nogami Yasuyuki
Published: November 2024

Vehicular Ad-Hoc Networks (VANETs) play an essential role in the intelligent transportation era, furnishing users with essential roadway data to facilitate optimal route selection and mitigate the risk of accidents. However, the network exposure makes VANETs susceptible to cyber threats, making authentication crucial for ensuring security and integrity. Therefore, joining entity verification is essential to ensure the integrity and security of communication in VANETs. However, to authenticate the entities, authentication time should be minimized to guarantee fast and secure authentication procedures. We propose an authentication system for VANETs using blockchain and Kerberos for storing authentication messages in a blockchain ledger accessible to Trusted Authentication Servers (TASs) and Roadside Units (RSUs). We evaluate the system in three diverse network scenarios: suburban, urban with 1 TAS, and urban with 2 TASs. The findings reveal that this proposal is applicable in diverse network scenarios to fulfill the network requirements, including authentication, handover, and end-to-end delay, considering an additional TAS for an increasing number of vehicles. The system is also practicable in storing the authentication message in blockchain considering the gas values and memory size for all scenarios.
Adaptive Optimization and Dynamic Representation Method for Asynchronous Data Based on Regional Correlation Degree
Authors: Tang Sichao , Zhao Yuchen , Lv Hengyi , Sun Ming , Feng Yang , Zhang Zeshu
Published: November 2024

Event cameras, as bio-inspired visual sensors, offer significant advantages in their high dynamic range and high temporal resolution for visual tasks. These capabilities enable efficient and reliable motion estimation even in the most complex scenes. However, these advantages come with certain trade-offs. For instance, current event-based vision sensors have low spatial resolution, and the process of event representation can result in varying degrees of data redundancy and incompleteness. Additionally, due to the inherent characteristics of event stream data, they cannot be utilized directly; pre-processing steps such as slicing and frame compression are required. Currently, various pre-processing algorithms exist for slicing and compressing event streams. However, these methods fall short when dealing with multiple subjects moving at different and varying speeds within the event stream, potentially exacerbating the inherent deficiencies of the event information flow. To address this longstanding issue, we propose a novel and efficient Asynchronous Spike Dynamic Metric and Slicing algorithm (ASDMS). ASDMS adaptively segments the event stream into fragments of varying lengths based on the spatiotemporal structure and polarity attributes of the events. Moreover, we introduce a new Adaptive Spatiotemporal Subject Surface Compensation algorithm (ASSSC). ASSSC compensates for missing motion information in the event stream and removes redundant information, thereby achieving better performance and effectiveness in event stream segmentation compared to existing event representation algorithms. Additionally, after compressing the processed results into frame images, the imaging quality is significantly improved. Finally, we propose a new evaluation metric, the Actual Performance Efficiency Discrepancy (APED), which combines actual distortion rate and event information entropy to quantify and compare the effectiveness of our method against other existing event representation methods. The final experimental results demonstrate that our event representation method outperforms existing approaches and addresses the shortcomings of current methods in handling event streams with multiple entities moving at varying speeds simultaneously.
Recent Developments in Aptamer-Based Sensors for Diagnostics
Authors: Sheraz Muhammad , Sun Xiao-Feng , Wang Yongke , Chen Jiayi , Sun Le
Published: November 2024

Chronic and non-communicable diseases (NCDs) account for a large proportion of global disorders and mortality, posing significant burdens on healthcare systems. Early diagnosis and timely interference are critical for effective management and disease prevention. However, the traditional methods of diagnosis still suffer from high costs, time delays in processing, and infrastructure requirements that are usually unaffordable in resource-constrained settings. Aptamer-based biosensors have emerged as promising alternatives to offer enhanced specificity, stability, and cost-effectiveness for disease biomarker detection. The SELEX (Systematic Evolution of Ligands by Exponential Enrichment) methodology allows developing aptamers with high-affinity binding capabilities to a variety of targets, for instance proteins, cells, or even small molecules, hence rendering them suitable for NCD diagnosis. Aptasensors—recent developments in the electrochemical and optical dominion—offer much enhanced sensitivity, selectivity, and stability of detection across a diverse range of diseases from lung cancer and leukemia to diabetes and chronic respiratory disorders. This study provides a comprehensive review of progress in aptamer-based sensors, focusing on their role in point-of-care diagnostics and adaptability in a real-world environment with future directions in overcoming current limitations.
Abnormal-Sound Diagnosis for Kaplan Hydroelectric Generating Units Based on Continuous Wavelet Transform and Transfer Learning
Authors: Liu Yu , Xu Zhuofei , Guo Pengcheng , Sun Longgang
Published: November 2024

To realize abnormal-sound diagnosis in hydroelectric generating units, this study proposes a method based on continuous wavelet transform (CWT) and Transfer Learning (TL). A denoising algorithm utilizing spectral noise-gate technology is proposed to enhance fault characteristics in hydroelectric units. Subsequently, Continuous Wavelet Transform is applied to obtain frequency components, and the results are converted into a series of pseudo-color images to highlight information differences. A transfer model is subsequently developed for feature extraction, utilizing simplified fully connected layers to reduce modeling costs. The study optimizes key parameters during the signal-processing stage and achieves an improved parameter-setting scheme. Acoustic signals corresponding to four different fault states and a normal state are collected from a Kaplan hydroelectric generating unit in a hydropower station. The signal diagnosis accuracy rates before filtering are 84.83% and 95.14%. These rates significantly improved to 98.88% and 98.06%, respectively, demonstrating the effectiveness of the noise-reduction process. To demonstrate the superiority of the improved model in this work, a series of classic deep-learning models, including AlexNet, Resnet18, and MobileNetV3, are used for comparative analysis. The proposed method can effectively diagnose faults in Kaplan hydroelectric generating units with a high accuracy, which is crucial for the daily monitoring and maintenance of these units.
Eating Disorders in Taekwondo Athletes: The Contribution of Coach Behavior, Body Satisfaction, and Goal Orientation
Authors: Barić Renata , Erdeljac Tanja
Published: November 2024

Taekwondo is a weight-classified combat sport. Taekwondo athletes often resort to restrictive eating behaviors and weight reduction, especially just before competitions, which, in the long run, endanger their physical and mental health. This study aimed to determine the incidence of eating disorder (ED) symptoms regarding sex, age, and competitive level categories and examine the correlation and contribution of coach behavior, body satisfaction, and goal orientation to the development of ED symptoms in different subgroups. A total of 335 active Croatian taekwondo athletes, with a mean age of 14.7 years, among whom were 132 males and 203 females (range 10–26 yrs, SD = 3.06), completed the Croatian version of the Eating Attitude Test, Figure Rating Scale, Croatian Task and Ego Orientation in Sport Questionnaire, Negative Coach Behavior Questionnaire, and a questionnaire related to taekwondo practice. The results showed that ED symptoms were more present in female than male athletes (p < 0.001), while there was no statistically significant difference among the age and competitive level categories between elite and non-elite athletes. The risk of ED was significantly correlated (p < 0.001) with taekwondo athletes’ body dissatisfaction, coach pressure, and task goal orientation. In general, regression analyses showed that athletes’ body image dissatisfaction (β = 0.310; p < 0.001), coach pressure on diet and weight (β = 0.156; p < 0.005), and athletes’ task goal orientation (β = 0.120; p < 0.032) are statistically significant predictors that explain the variance in ED symptoms in Croatian taekwondo athletes. The culture of taekwondo sports represents a risk factor for ED development.