bluuebunny/crossref_metadata_2025 huggingface dataset:
Leveraging Incremental Learning for Dynamic Modulation Recognition
Authors: Ma Song , Zhang Lin , Song Zhangli , Yu Wei , Liu Tian
Published: October 2024

Modulation recognition is an important technology used to correctly identify the modulation modes of wireless signals and is widely used in cooperative and confrontational scenarios. Traditional modulation-recognition algorithms require the assistance of expert experiences, which constrains their applications. With the rapid development of artificial intelligence in recent years, deep learning (DL) is widely advocated for intelligent modulation recognition. Typically, DL-based modulation-recognition algorithms implicitly assume a relatively static scenario in which the signal samples of all the modulation modes can be completely collected in advance. In practical situations, the radio environment is quite dynamic and the signal samples with new modulation modes may appear sequentially, in which the current DL-based modulation-recognition algorithms may require unacceptable time and computing resource consumption to re-train the optimal model from scratch. In this study, we leveraged incremental learning (IL) and designed a novel IL-based modulation-recognition algorithm that consists of an initial stage and multiple incremental stages. The main novelty of the proposed algorithm lies in the new loss function design in each incremental stage, which combines the distillation loss of recognizing old modulation modes and the cross-entropy loss of recognizing new modulation modes. With the proposed algorithm, the knowledge of the signal samples with new modulation modes can be efficiently learned in the current stage without forgetting the knowledge learned in the previous stages. The simulation results demonstrate that the proposed algorithm could achieve a recognition accuracy close to the upper bound with a much lower computing time and it outperformed the existing IL-based benchmarks.
DLCH-YOLO: An Object Detection Algorithm for Monitoring the Operation Status of Circuit Breakers in Power Scenarios
Authors: Shu Riben , Chen Lihua , Su Lumei , Li Tianyou , Yin Fan
Published: October 2024

In the scenario of power system monitoring, detecting the operating status of circuit breakers is often inaccurate due to variable object scales and background interference. This paper introduces DLCH-YOLO, an object detection algorithm aimed at identifying the operating status of circuit breakers. Firstly, we propose a novel C2f_DLKA module based on Deformable Large Kernel Attention. This module adapts to objects of varying scales within a large receptive field, thereby more effectively extracting multi-scale features. Secondly, we propose a Semantic Screening Feature Pyramid Network designed to fuse multi-scale features. By filtering low-level semantic information, it effectively suppresses background interference to enhance localization accuracy. Finally, the feature extraction network incorporates Generalized-Sparse Convolution, which combines depth-wise separable convolution and channel mixing operations, reducing computational load. The DLCH-YOLO algorithm achieved a 91.8% mAP on our self-built power equipment dataset, representing a 4.7% improvement over the baseline network Yolov8. With its superior detection accuracy and real-time performance, DLCH-YOLO outperforms mainstream detection algorithms. This algorithm provides an efficient and viable solution for circuit breaker status detection.
Assessment of Ensemble-Based Machine Learning Algorithms for Exoplanet Identification
Authors: Luz Thiago S. F. , Braga Rodrigo A. S. , Ribeiro Enio R.
Published: October 2024

This paper presents a comprehensive assessment procedure for evaluating Ensemble-based Machine Learning algorithms in the context of exoplanet classification. Each of the algorithm hyperparameter values were tuned. Deployments were carried out using the cross-validation method. Performance metrics, including accuracy, sensitivity, specificity, precision, and F1 score, were evaluated using confusion matrices generated from each implementation. Machine Learning (ML) algorithms were trained and used to identify exoplanet data. Most of the current research deals with traditional ML algorithms for this purpose. The Ensemble algorithm is another type of ML technique that combines the prediction performance of two or more algorithms to obtain an improved final prediction. Few studies have applied Ensemble algorithms to predict exoplanets. To the best of our knowledge, no paper that has exclusively assessed Ensemble algorithms exists, highlighting a significant gap in the literature about the potential of Ensemble methods. Five Ensemble algorithms were evaluated in this paper: Adaboost, Random Forest, Stacking, Random Subspace Method, and Extremely Randomized Trees. They achieved an average performance of more than 80% in all metrics. The results underscore the substantial benefits of fine tuning hyperparameters to enhance predictive performance. The Stacking algorithm achieved a higher performance than the other algorithms. This aspect is discussed in this paper. The results of this work show that it is worth increasing the use of Ensemble algorithms to improve exoplanet identification.
Personal Identity Proofing for E-Commerce: A Case Study of Online Service Users in the Republic of Korea
Authors: Kim Jongbae
Published: October 2024

The rapid expansion of non-face-to-face e-commerce services in the Korea has significantly increased the importance of personal identity proofing (PIP) for verifying users in online transactions, such as payments, refunds, membership registrations, and access to age-restricted products. Currently, personal identity proofing agencies (PIPAs) indiscriminately provide all of a user’s personal information to internet service providers (ISPs), leading to substantial privacy concerns and preventing users from selectively disclosing only the necessary information. The objective of this paper is to enhance the safety, convenience, and security of PIP services by proposing a method that empowers users to control the personal information they disclose while enabling digital identity integration for both online and offline applications. To achieve this, an extensive overview and analysis of the current PIP systems in Korea is presented, including methods. The strengths and weaknesses of these systems are critically examined, revealing limitations in privacy protection, user convenience, and security. Based on this analysis, a new method is proposed that introduces differentiated levels of PIP means according to authentication strength, allowing for the minimal necessary disclosure of personal information. The proposed method aims to improve the stability and reliability of the PIP service environment by addressing current privacy concerns and enhancing user control over personal information. This approach can be applied to e-commerce services in Korea and other countries facing similar challenges, contributing to the development of safer and more reliable online services.
Thermodynamics-Informed Neural Networks for the Design of Solar Collectors: An Application on Water Heating in the Highland Areas of the Andes
Authors: Cáceres Mauricio , Avila Carlos , Rivera Edgar
Published: October 2024

This study addresses the challenge of optimizing flat-plate solar collector design, traditionally reliant on trial-and-error and simplified engineering design methods. We propose using physics-informed neural networks (PINNs) to predict optimal design conditions in a range of data that not only characterized the highlands of Ecuador but also similar geographical locations. The model integrates three interconnected neural networks to predict global collector efficiency by considering atmospheric, geometric, and physical variables, including overall loss coefficient, efficiency factors, outlet fluid temperature, and useful heat gain. The PINNs model surpasses traditional simplified thermodynamic equations employed in engineering design by effectively integrating thermodynamic principles with data-driven insights, offering more accurate modeling of nonlinear phenomena. This approach enhances the precision of solar collector performance predictions, making it particularly valuable for optimizing designs in Ecuador’s highlands and similar regions with unique climatic conditions. The ANN predicted a collector overall loss coefficient of 5.199 W/(m2·K), closely matching the thermodynamic model’s 5.189 W/(m2·K), with similar accuracy in collector useful energy gain (722.85 W) and global collector efficiency (33.68%). Although the PINNs model showed minor discrepancies in certain parameters, it outperformed traditional methods in capturing the complex, nonlinear behavior of the data set, especially in predicting outlet fluid temperature (55.05 °C vs. 67.22 °C).
Energy Demand Estimation in Turkey According to Road and Rail Transportation: Walrus Optimizer and White Shark Optimizer Algorithm-Based Model Development and Application
Authors: Korkmaz Ersin , Doğan Erdem , Akgüngör Ali Payıdar
Published: October 2024

Transport energy demand (TED) forecasting is a crucial issue for countries like Turkey that are dependent on external resources. The accuracy and effectiveness of these forecasts are extremely important, especially for the strategies and plans to be developed. With this in mind, different forms of forecasting models were developed in the present study using the Walrus Optimizer (WO) and White Shark Optimizer (WSO) algorithms to estimate Turkey’s energy consumption related to road and railway transportation modes. Additionally, another objective of this study was to examine the impacts of different transport modes on energy demand. To investigate the effect of demand distribution among transport modes on energy consumption, model parameters such as passenger-kilometers (P-km), freight-kilometers (F-km), carbon dioxide emissions (CO2), gross domestic product (GDP), and population (POP) were utilized in the development of the models. It was found that the WO algorithm outperformed the WSO algorithm and was the most suitable method for energy demand forecasting. All the developed models demonstrated a better performance level than those reported in previous studies, with the best performance achieved by the semi-quadratic model developed with the WO, showing a 0.95% MAPE value. Projections for energy demand up to the year 2035 were established based on two different scenarios: the current demand distribution among transport modes, and a demand shift from road to rail transportation. It is anticipated that the proposed energy demand models will serve as an important guide for effective planning and strategy development. Moreover, the findings suggest that a balanced distribution among transport modes will have a positive impact on transport energy and will result in lower energy requirements.
Sensorless DFIG System Control via an Electromagnetic Torque Based on MRAS Speed Estimator
Authors: Lama Abdelbadia , Serhoud Hicham , Benchouia Mohamed Toufik
Published: October 2024

The main goals of this research are to develop a method for obtaining the rotor position and speed in a doubly fed induction generator (DFIG) without using sensors in a variable-speed wind turbine installation. The considered method is based on the Model Reference Adaptive System (MRAS). According to this method, electromagnetic torque is used as an error variable for the adaptation process in order to refine the estimate. A good assessment is very important when trying to put into place any strategy that can control the behavior of a DFIG. This method of estimation functions by comparing the actual performance of the DFIG with that of a reference model and adjusting the system parameters to reduce any mismatch between the two. One notable advantage of this developed estimator is its stability across a broad range of speeds. Additionally, it is designed to exhibit resilience in the face of uncertainties in machine parameters. The proportional integral (PI) gains for the MRAS estimator are determined via pole placement. To assess and validate the entire DFIG model and the sensorless estimation method, comprehensive simulations are carried out using MATLAB/Simulink.
Research and Application Progress of Aerogel Materials in the Field of Batteries and Supercapacitors
Authors: Chen Junyong , Li Qingyuan
Published: October 2024

Aerogels, characterized by their exceptional porosity, vast specific surface areas, minimal density, and unparalleled thermal insulation capabilities, have become a focal point of attention in the energy sector over the past decade, particularly in the realms of batteries and supercapacitors. This comprehensive review delves into aerogels and their preparation methods, while reviewing their recent applications in batteries and supercapacitors. It delves deeply into the research and development progress, as well as the application advancements of aerogel materials in separators, electrolytes, and electrodes. Furthermore, this article highlights that the research on aerogels still faces some challenges, such as steep costs, sophisticated production steps, and relatively weak overall mechanical strength. Therefore, in the future, it is necessary to further strengthen the fundamental research and technological innovation of aerogel materials, and promote their industrialization process and wide application in the field of energy storage, particularly in the areas of batteries and supercapacitors.
Environmental Impacts and Contaminants Management in Sewage Sludge-to-Energy and Fertilizer Technologies: Current Trends and Future Directions
Authors: Grobelak Anna , Całus-Makowska Klaudia , Jasińska Anna , Klimasz Marek , Wypart-Pawul Aleksandra , Augustajtys Dominika , Baor Estera , Sławczyk Daria , Kowalska Aneta
Published: October 2024

The increasing focus on sustainability and the circular economy has brought waste-to-energy technologies to the forefront of renewable energy research. However, the environmental impacts and management of contaminants associated with these technologies remain critical issues. This article comprehensively reviews the environmental impacts of converting sewage sludge into energy and fertilizers, focusing on managing potential contaminants and assessing the implications and ecological risks. It also highlights the latest trends in waste-to-energy technologies, waste-to-soil amendment, and their integration into circular economy frameworks. The discussion encompasses challenges and opportunities in optimizing these processes in wastewater treatment plants to minimize pollutants and enhance sustainability. Addressing these challenges is essential for ensuring the long-term viability and acceptance of waste-to-energy solutions, making this topic highly relevant and timely.
A Novel Hybrid Harris Hawk Optimization–Sine Cosine Algorithm for Congestion Control in Power Transmission Network
Authors: Kumar Vivek , Rao R. Narendra , Ansari Md Fahim , Shekher Vineet , Paul Kaushik , Sinha Pampa , Alkuhayli Abdulaziz , Khaled Usama , Mahmoud Mohamed Metwally
Published: October 2024

In a deregulated power system, managing congestion is crucial for effective operation and control. The goal of congestion management is to alleviate transmission line congestion while adhering to system constraints at minimal cost. This research proposes a hybrid Harris Hawk Optimization–Sine Cosine Algorithm (hHHO-SCA) for an efficient generation rescheduling approach to achieve the lowest possible congestion cost. The hybridization has been performed by introducing the features of SCA in the HHO to boost the exploration and exploitation steps of HHO, providing an efficient global solution and effectively optimizing rescheduled power output. The effectiveness of this methodology is evaluated using IEEE 30 and IEEE 118-bus test systems, taking into account system parameters. The potency of the proposed method is analyzed by comparing the results of the hHHO-SCA with those from other recent optimization techniques. The findings show that the hHHO-SCA outperforms other methods by avoiding local optima and demonstrating promising convergence characteristics.
Study on the Economic Operation of a 1000 MWe Coal-Fired Power Plant with CO2 Capture
Authors: Yang Jinning , Wang Chaowei , Xu Dong , Yu Xuehai , Yang Yang , Wang Zhiyong , Wu Xiao
Published: October 2024

The flexible operation of carbon capture units is crucial for the economic performance of coal-fired power plants equipped with CO2 capture systems. This paper aims to investigate the impact of electricity, CO2, and fuel prices on the economic operation of such plants. A novel economic optimization model is proposed, integrating a static model of the carbon capture system with a particle swarm optimization algorithm. A new concept, the CO2 boundary price, is introduced as a key metric for determining the operating conditions of CO2 capture units. The CO2 boundary price rises when the power load decreases due to the decline in power generation efficiency, and it also increases with rising fuel prices, as the cost of steam for CO2 capture increases. Additionally, when the objective is to meet power load demand, CO2 prices have a great influence on the operation of CO2 capture units, assuming fixed coal and electricity prices. However, when the primary goal is to maximize plant profitability, the system’s operational conditions are strongly influenced by the relative prices of electricity and CO2. The proposed optimization model and the uncovered price-effect mechanisms provide valuable insights into the economic operation of carbon capture power plants.
A Lyapunov Theory-Based SEIG–STATCOM Voltage Regulation Control Strategy
Authors: Zhang Zeyu , Gong Pingping , Lu Ziguang
Published: October 2024

To improve the voltage regulation of asynchronous generators during load switching, a Lyapunov-based control strategy has been proposed to stabilize the generator’s voltage by connecting a static synchronous compensator. By constructing a Lyapunov function from the mathematical model, the error tracking problem is transformed into a global asymptotic stability problem of the Lyapunov function at the equilibrium point. The outer loop linearizes the direct current (DC) voltage control process, while the inner loop replaces integral terms with differential terms. The proposed Lyapunov method achieves linearized voltage control with a quadratic outer loop structure and the inner loop differential structure exhibits a shorter transient process, outperforming traditional methods. Simulation and experimental tests were then used, where the latter was a down-scale laboratory prototype experiment. Compared to traditional (voltage-oriented control) VOC, the outer loop (Lyapunov-function-based control) LBC reduces the DC voltage transient processes by approximately 9.4 milliseconds, while the inner loop LBC reduces both alternating current (AC) and DC voltage transient processes by approximately 2.6 ms and 8.7 ms, respectively.
Impact of Air Conditioning Type on Outdoor Ozone Intrusion into Homes in a Semi-Arid Climate
Authors: Johnston James D. , Van Roosendaal Seth , West Joseph , Jung Hanyong , Sonntag Darrell
Published: October 2024

Outdoor ozone (O3) is elevated on hot, sunny days when residential air conditioning is used most. We evaluated the impact of direct evaporative coolers (ECs) and vapor-compression air conditioners (ACs) on indoor O3 concentrations in homes (N = 31) in Utah County, Utah, United States of America. Indoor and outdoor O3 concentrations were measured for 24 h at each home using nitrite-impregnated glass-fiber filters. AC homes (n = 16) provided a protective envelope from outdoor O3 pollution. Only one AC home had O3 levels above the limit of detection (LOD). Conversely, EC homes (n = 15) provided minimal protection from outdoor O3. Only one EC home had O3 levels below the LOD. The average indoor O3 concentration in EC homes was 23 ppb (95% CI 20, 25). The indoor-to-outdoor (I/O) ratio for O3 in EC homes was 0.65 (95% CI 0.58, 0.72), while the upper bound for the I/O ratio for AC homes was 0.13 (p < 0.001). Indoor exposure to O3 for residents in EC homes is approximately five times greater than for residents of AC homes. Although ECs offer energy and cost-saving advantages, public health awareness campaigns in O3-prone areas are needed, as well as research into O3 pollution controls for direct ECs such as activated carbon filtration.
Understanding the Role of Visitor Behavior in Soundscape Restorative Experiences in Urban Parks
Authors: Guo Xuan , Jiang Si-Yu , Liu Jiang , Chen Zhu , Hong Xin-Chen
Published: October 2024

The restorative effects of soundscapes on human physical and mental well-being are widely recognized, but their effectiveness is influenced by various factors, including external environments and individual characteristics. Despite being a crucial element in environmental experience, the role of individual behavior in the restorative effects of soundscapes has been insufficiently studied. To address this research gap, we conducted a survey in five parks in Fuzhou, China, using questionnaires to assess visitors’ evaluations of soundscape characteristics, their soundscape restorative experiences, and behavioral characteristics. A total of 419 valid responses were collected. Using these data, we employed a structural equation model and conditional process analysis to explore the interaction between visitor behavior and soundscape experiences. The results show that soundscapes with pleasantness and eventfulness promote static behaviors to a certain degree, while dynamic behaviors are influenced solely by eventfulness soundscapes. In the process by which soundscape characteristics influence restorative experiences, static behavior is the only mediating factor, accounting for 8% of the total effect. Additionally, increased visit intensity enhances the impact of pleasantness soundscape on restorative experiences while weakening the mediating effect of static behavior. These findings provide strong support for relevant design considerations.
Human Physiological Responses to Sitting and Walking in Green Spaces with Different Vegetation Structures: A Seasonal Comparative Study
Authors: Duan Yifan , Bai Hua , Li Shuhua
Published: October 2024

This study seeks to address the gap in knowledge regarding the varying effects of vegetation on human perception and preference, and to comprehend how green spaces can better serve community needs. The research assessed the impact of different vegetation structures on physiological responses during two types of on-site perceptions: sitting and walking, in both winter and summer. The green spaces included single-layer grassland, single-layer woodland, tree-shrub-grass composite woodlands, and tree-grass composite woodlands, and a non-vegetated square. The findings indicated the following. (1) The physiological recovery effect of walking in green spaces is relatively greater than that of sitting; walking in green spaces with different vegetation types was found to enhance participants’ pNN50 values (p = 0). (2) During the summer, sitting and observing provided a better physiological recovery effect (p < 0.05), whereas in the winter, walking was more beneficial (p < 0.05). (3) Green spaces with vegetation were more beneficial for physiological recovery than the non-vegetated square, which could not sustain recovery effects for more than 1 min. Single-layer grassland and tree-shrub-grass composite woodlands had the most significant physiological recovery effects on health (p < 0.01). (4) Based on these conclusions, it is suggested that a combination of sitting and walking can lead to improved recovery outcomes. Therefore, when visiting parks during extreme weather conditions, individuals should adjust the duration of their sitting and walking experiences to enhance their overall experience.
Effect of Dietary Supplementation with Different Proportions of Amaranthus hypochondriacus Stem and Leaf Powder on Intestinal Digestive Enzyme Activities, Volatile Fatty Acids and Microbiota of Broiler Chickens
Authors: Sun Qianqian , Yang Ying , Chen Huiru , Zhou Shilong , Zhao Shengjun , Chen Wenxun
Published: October 2024

Amaranthus hypochondriacus is rich in nutrients and represents a feed resource with significant potential. This experiment aimed to study the effects of different proportions of Amaranthus hypochondriacus stem and leaf powder (AHSL) on intestinal digestive enzyme activities, cecal volatile fatty acids, and the microbiota of broilers. A total of 288 one-day-old male broilers (Ross 308) were randomly assigned to the control diet group and the 3%, 6%, and 9% AHSL diet group for days 0–21. Subsequently, the 3%, 6%, and 9% AHSL diets were switched to 5%, 10%, and 15% AHSL diets for days 22–42. The results demonstrated that the dietary inclusion of AHSL significantly affected sucrase activity in the jejunal mucosa (p < 0.05). The 5% AHSL group exhibited the highest sucrase activity, followed by the control group, both of which showed significantly higher activity compared to the 10% and 15% AHSL groups (p < 0.05). The cecal pH in the 5%, 10%, and 15% AHSL groups was significantly lower than that in the control group (p < 0.05). The contents of acetate, propionate, butyrate, and valerate in the cecum of the 10% and 15% AHSL groups were significantly higher than those of the control group (p < 0.05). The addition of AHSL had no significant effect on the alpha diversity of cecum microorganisms. The relative abundance of Ruminococcaceae_UCG_005 and Lactonifactor was significantly higher in the 10% AHSL group compared to the control group, whereas the 15% AHSL group had a significantly higher relative abundance of Clostridium_sensus_tricto12, Peptoclostridium, Anaerofilum, and Peptococcaceae. In summary, the inclusion of 5% AHSL in the diet enhances sucrase activity in the jejunum of broilers, while 10% or 15% AHSL increases the volatile fatty acid content and reduces the pH value in the cecum, without adverse effects on the cecal microbiota.
Combating Web Tracking: Analyzing Web Tracking Technologies for User Privacy
Authors: Sim Kyungmin , Heo Honyeong , Cho Haehyun
Published: October 2024

Behind everyday websites, a hidden shadow world tracks the behavior of Internet users. Web tracking analyzes online activity based on collected data and delivers content tailored to users’ interests. It gathers vast amounts of information for various purposes, ranging from sensitive personal data to seemingly minor details such as IP addresses, devices, browsing histories, settings, and preferences. While Web tracking is largely a legitimate technology, the increase in illegal user tracking, data breaches, and the unlawful sale of data has become a growing concern. As a result, the demand for technologies that can detect and prevent Web trackers is more important than ever. This paper provides an overview of Web tracking technologies, relevant research, and website measurement tools designed to identify web-based tracking. It also explores technologies for preventing Web tracking and discusses potential directions for future research.
Active Fire Clustering and Spatiotemporal Dynamic Models for Forest Fire Management
Authors: Dastour Hatef , Bhuian Hanif , Ahmed M. Razu , Hassan Quazi K.
Published: October 2024

Forest fires are increasingly destructive, contributing to significant ecological damage, carbon emissions, and economic losses. Monitoring these fires promptly and accurately, particularly by delineating fire perimeters, is critical for mitigating their impact. Satellite-based remote sensing, especially using active fire products from VIIRS and MODIS, has proven indispensable for real-time forest fire monitoring. Despite advancements, challenges remain in accurately clustering and delineating fire perimeters in a timely manner, as many existing methods rely on manual processing, resulting in delays. Active fire perimeter (AFP) and Timely Active Fire Progression (TAFP) models were developed which aim to be an automated approach for clustering active fire data points and delineating perimeters. The results demonstrated that the combined dataset achieved the highest matching rate of 85.13% for fire perimeters across all size classes, with a 95.95% clustering accuracy for fires ≥100 ha. However, the accuracy decreased for smaller fires. Overall, 1500 m radii with alpha values of 0.1 were found to be the most effective for fire perimeter delineation, particularly when applied at larger radii. The proposed models can play a critical role in improving operational responses by fire management agencies, helping to mitigate the destructive impact of forest fires more effectively.
Otolith Microchemistry Reveals the Diversity of Migration Patterns and Spawning Ground Distribution of Coilia nasus from the Yangtze River Estuary
Authors: Song Chao , Yu Wenjie , Liu Ruohui , Xie Jilin , Li Feipeng , Zhao Feng , Zhuang Ping
Published: October 2024

Coilia nasus are an important fish resource in the Yangtze River, and the Yangtze River Estuary is a crucial migration pathway for them. In this study, we used otolith microchemistry to analyze the strontium/calcium (Sr/Ca) ratios and Sr contents in the sagitta otolith of C. nasus from the south branch (SB) and north branch (NB) of the Yangtze River Estuary and obtained the diversity of migration patterns and spawning ground distribution for C. nasus. The results indicate that C. nasus from both branches include two types of habitat history: freshwater (F)–brackish water (B) (Type I) and F-B seawater (S) (Type II), with Type I being dominant at 62.50% in both branches. The C. nasus from the SB comprise six migration patterns, while that from the NB has seven migration patterns. The C. nasus from both branches hatch in F habitats. At the time of capture, the C. nasus from the SB predominantly remain in F, accounting for 62.5%, while C. nasus from the NB primarily stay in B, accounting for 87.5%. Throughout the migration process, C. nasus from both branches switch between different habitats, with C. nasus from the NB exhibiting more frequent transitions between F and B, showing a greater reliance on the estuarine brackish habitat. The radius of the first blue region near the core (Lf) and freshwater coefficient (Fc) of the otolith for C. nasus from both branches are divided into three groups: long-distance freshwater dependence (LD), medium-distance freshwater dependence (MD), and short-distance freshwater dependence (SD), with the LD only appearing in the SB, while the NB is primarily represented by MD. There is a correlation between the differences in Lf among different groups of C. nasus and the differences in the distance from the spawning grounds of C. nasus in different sections of the Yangtze River to the estuary (DYRE), reflecting the distribution pattern of C. nasus spawning grounds in different sections of the Yangtze River. This study provides theoretical guidance for the protection of migration pathways and maintenance of spawning grounds for C. nasus, which have significant practical value in the precise management of C. nasus resources in the Yangtze River Estuary.
Construction of a Growth Model and Screening of Growth-Related Genes for a Hybrid Puffer (Takifugu obscurus ♀ × Takifugu rubripes ♂)
Authors: Wang Chaoyu , Shi Yan , Gao Yuanye , Shi Shuo , Wang Mengmeng , Yao Yunlong , Sun Zhenlong , Wang Yaohui , Zhao Zhe
Published: October 2024

The obscure puffer (Takifugu obscurus) is a popular cultured species and accounts for around 50% of the total pufferfish production in China. A hybrid puffer was generated by crossing a female obscure puffer with a male tiger puffer (T. rubripes). Its growth model has not been developed and the genetic basis underlying its growth superiority has not yet been fully investigated. In this study, the growth model and morphological traits of the hybrid puffer were explored. The results indicated that the hybrid puffer exhibited a significant growth advantage compared to the obscure puffer. There were also significant differences in their morphological traits. We conducted genotyping-by-sequencing (GBS) on hybrid and obscure puffer groups, identifying 215,288 high-quality single nucleotide polymorphisms (SNPs) on 22 chromosomes. Subsequently, a total of 13 growth-related selection regions were identified via a combination of selection signatures and a genome-wide association study (GWAS); these regions were mainly located on chromosomes 10 and 22. Ultimately, the screened regions contained 13 growth-related genes, including itgav, ighv3-43, ighm, atp6v1b2, pld1, xmrk, inhba, dsp, dsg2, and dsc2, which regulate growth through a variety of pathways. Taken together, the growth models and candidate genes used in this study will aid our understanding of production characteristics and the genetic basis of growth rates. The hybrid will also be of great significance for the genome-assisted breeding of pufferfish in the future.
Effect of the Addition of Yellow Mealworm (Tenebrio molitor) on the Physicochemical, Antioxidative, and Sensory Properties of Oatmeal Cookies
Authors: Draszanowska Anna , Kurp Lidia , Starowicz Małgorzata , Paszczyk Beata , Czarnowska-Kujawska Marta , Olszewska Magdalena Anna
Published: October 2024

Edible insects are receiving increased attention as a new food source, although research on their implementation in confectionary products remains scarce. The study analyzed the chemical composition, physical parameters, antioxidative, and sensory characteristics of oatmeal cookies reformulated with yellow mealworm larvae (Tenebrio molitor L.; TM) at 0% (TM0), 10% (TM10), and 30% (TM30). The inclusion of TM in the cookie recipe increased the protein and fat content, improved the ratio of n-6/n-3 acids, and raised oleic acid levels while reducing palmitic acid. Oatmeal cookies were rich in K and P, and including TM significantly increased the content of most minerals, except for Mn and Na. The cookies held significant antioxidant capacity that increased as the concentration of TM increased due to hydrophilic antioxidants. Although lightness decreased with the increase in mealworm substitution, the yellowness, chroma, and hue angle remained similar for TM0 and TM10. The TM30 cookies were significantly darker and softer, which was further confirmed by panelists. The cookie formulation effectively masked the taste and smell of TM since there were no evident differences between the control and TM10 cookies. Cookies with TM30 received high enough ratings to be considered attractive if differentiated sensory characteristics are desired.
Efficacy of an Edible Coating with Carvacrol and Citral in Frozen Strawberries and Blueberries to Control Foodborne Pathogens
Authors: Pié-Amill Anna , Colás-Medà Pilar , Viñas Inmaculada , Falcó Irene , Alegre Isabel
Published: October 2024

Adding essential oils in an edible coating could be an alternative for the food industry to control foodborne pathogens. In 2014, EFSA published a report highlighting the risk associated with Salmonella spp. and Norovirus in fresh and frozen berries. This study aimed to evaluate the efficacy of an edible coating (RP-7) with carvacrol and citral on reducing the population of Salmonella enterica, Escherichia coli O157:H7, Listeria monocytogenes, and murine Norovirus (MNV-1) in frozen strawberries and blueberries. Before evaluating the efficacy, the best method for applying the coating on fruit was studied. The immersion method was selected, with an optimal drying time of 45 min. After this, the berries were frozen and stored for one, two, three, four, and eight weeks at −18 °C. In strawberries, all bacteria were reduced to below 0.7 log cfu/strawberry in the eighth week, and the MNV-1 infectivity showed a reduction of nearly 2 logarithmic units. In blueberries, S. enterica and E. coli O157:H7 were reduced to 0.8 log cfu/blueberries within a week, and MNV-1 achieved a reduction of 0.8 logarithmic units at the end of the assay. The application of RP-7 affected the studied microorganisms in frozen strawberries and blueberries.
Exploring Community Succession, Assembly Patterns, and Metabolic Functions of Ester-Producing-Related Microbiota during the Production of Nongxiangxing baijiu
Authors: Yi Xiawei , Xia Huan , Huang Ping , Ma Shiyuan , Wu Chongde
Published: October 2024

Esters are vital flavor compounds in Chinese Nongxiangxing baijiu and greatly affect the quality of baijiu. Microbial communities inhabiting fermented grains (FGs) have a marked impact on esters. However, the specific microorganisms and their assembly patterns remain unclear. This study utilized high-throughput sequencing and a culture-based method to reveal ester-producing microorganisms. A total of 33 esters were detected, including 19 ethyl esters, 9 linear chain esters, and 2 branched chain esters. A correlation analysis indicated that the bacterial genus Lactobacillus (relative abundance in average: 69.05%) and fungal genera Pichia (2.40%), Aspergillus (11.84%), Wickerhamomyces (0.60%), Thermomyces (3.57%), Saccharomycopsis (7.87%), Issatchenkia (0.96%), and Thermoascus (10.83%) were dominant and associated with esters production and their precursors. The numbers of esters positively correlated with them were 1, 17, 3, 2, 1, 1, 1, and 1, respectively. The modified stochasticity ratio (MST) index and Sloan neutral model revealed that bacteria were predominantly governed by deterministic processes while fungal assemblies were more stochastic. Saturnispora silvae and Zygosaccharomyces bailii were isolated and identified with ester synthesis potential. PICRUSt2 analysis showed that fungi in FG had a high potential for synthesizing ethanol, while 14 enzymes related to esters synthesis were all produced by bacteria, especially enzymes catalyzing the synthesis of acyl-CoA. In addition, ester synthesis was mainly catalyzed by carboxylesterase, acylglycerol lipase and triacylglycerol lipase. These findings may provide insights into ester production mechanism and potential strategies to improve the quality of Nongxiangxing baijiu.
Phytosterol Depletion in Soybean Oil Using a Synthetic Silica Adsorbent
Authors: Steiner-Zitzenbacher Birgit , Velasco Joaquín , Gallegos Crispulo , Ruiz-Méndez Maria-Victoria
Published: October 2024

Phytosterols in vegetable oils have gained attention for their nutritional benefits in foods and food supplements. However, the use of vegetable oils in emulsions for infant formulas and parenteral nutrition has raised some concerns, as phytosterols may contribute to phytosterolemia in the case of infant formulas and, in a second scenario, to parenteral nutrition-associated liver disease. The present study proposes removing phytosterols from soybean oil using a synthetic amorphous silica Trisyl® (E551) as an adsorbent material. The process is simple and involves stirring the oil at a high temperature under vacuum conditions followed by filtration to remove the adsorbent. A rotational factorial design of experiments, considering the adsorbent/oil ratio, temperature, and time was carried out to determine the optimal conditions. Additionally, the effects on tocopherols levels and formation of trans fatty acids were explored. The total sterol content in the initial refined soybean oil was 2540 mg/kg, with 32% in ester form (813 mg/kg). The treatments effectively reduced the sterol concentration, achieving a reduction of nearly 70% when 10% Trisyl®, 140 °C, and a 90-min treatment were applied. Under these conditions, nearly 80% of the oil was recovered. Campesterol and stigmasterol levels were almost halved. Tocopherol losses were found to be below 20%. Thermal degradation, as analyzed by triacylglycerol polymers and trans fatty acids, was not observed in the treatments.
Mechanisms of Degradation of Insoluble Dietary Fiber from Coconut Chips by Ultra-High Pressure
Authors: Wei Qiaozhu , Cui Jingtao , Zhang Weimin , Jiang Lianzhou , Li Tian
Published: October 2024

Coconut chips are a popular leisure food, but the residual crumbly feeling after chewing affects the eating experience. To address this problem, we investigated the mechanism of degradation of insoluble dietary fiber (IDF) from coconut chips by ultra-high pressure (UHP). The optimal conditions for UHP treatment were 100 MPa and 40 min. After UHP treatment, the hardness decreased by 60%, and the content of soluble dietary fiber (SDF) increased by 55%. So far, the meaning of SDF has not been defined. The microstructure of IDF was damaged and the surface was rough. There was no obvious change in the chemical structure. The position of the characteristic diffraction peaks was basically unchanged, but the crystallinity dropped by almost three times. The thermal stability decreased, and the composition of the monosaccharides changed. Together, UHP treatment can improve the problem of the residual crumbly feeling after chewing coconut chips and improve the quality of the product.
Inhibitory Effects of Fruit Powders on the Formation of Polycyclic Aromatic Hydrocarbons in Charcoal-Grilled Pork
Authors: Huang Shang-Ming , Tung Bo-Chen , Hsieh Cheng-Hong , Yang Deng-Jye , Huang Ching-Wei , Chang Ling-Hsuan , Hsu Kuo-Chiang
Published: October 2024

Polycyclic aromatic hydrocarbons (PAHs), carcinogenic substances primarily formed through pyrolysis and oxidation of fat at high cooking temperatures, are commonly found at high levels in grilled meats. Reducing PAHs formation by incorporating natural antioxidants, such as through marination, has been demonstrated to be effective. However, the inhibitory effect of fresh phenolic-rich fruit powders on PAHs formation in charcoal-grilled meats remains unknown. To clarify the application of the fruit powders, 15 experimental groups were conducted. All pretreatment techniques (spraying, marinating, and mixing) were applied across all four freeze-dried fruit powders (lemon, guava, papaya, and mango). Each method was systematically tested with each fruit powder to evaluate its effect on inhibiting the formation of the four PAHs (BaA, CHR, BbF, and BaP) in charcoal-grilled pork belly and loin. Firstly, guava powder exhibited the highest phenolic content and antioxidant activity compared to the lemon, papaya, and mango powders (p < 0.05), among which the main phenolic compounds were ellagic acid, quercetin, and epigallocatechin gallate (EGCG). Further, marination of pork belly with guava powder exhibited the highest inhibition rate of PAHs (94.8%), followed by lemon (91.1%), papaya (89.8%), and mango (89.0%), with a statistically significant difference at p < 0.05. The reduction in estimated daily intake (EDI) and the increase in the margin of exposure (MOE) indicate that consuming grilled meat treated with these fruit powders poses no safety concerns and may potentially reduce health risks. Finally, the sensory evaluation showed that marinating with guava powder did not perceptibly affect the sensory attributes of the meat. Overall, this study provides a potent strategy for inhibiting the formation of PAHs in meat during charcoal grilling by incorporating fruit powder while preserving sensory qualities.
Potassium Hydroxide Extraction of Polyphenols from Olive Leaves: Effect on Color and Acrylamide Formation in Black Ripe Olives
Authors: Brenes-Álvarez Mercedes , García-García Pedro , Ramírez Eva María , Medina Eduardo , Brenes Manuel , Romero Concepción
Published: October 2024

Olive leaves are generated in large quantities in olive oil and table olive factories. This waste is currently used for multiple purposes, one of them being the extraction of bioactive substances, in particular phenolic compounds. The aims of this study were (i) to obtain a new polyphenolic extract from potassium hydroxide (KOH) -treated olive leaves; and (ii) to reduce acrylamide formation in black olives by using this extract. The results showed that olive leaves and leafless branches of the Manzanilla cultivar treated with 10 g/L KOH provide a solution that, concentrated under vacuum, had >6000 mg/L hydroxytyrosol and >2000 mg/L of hydroxytyrosol 4-glucoside. Moreover, the residual material generated after the treatment with KOH could be used for agronomic purposes, due to its high potassium content. The employment of this non-bitter extract during the darkening step of black ripe olive processing then resulted in darker fruits with higher potassium content. Likewise, the addition of the extract into the packing brine reduced the acrylamide formation by up to 32%, although this effect was batch-dependent. KOH olive extract could be useful for the reduction in acrylamide in black ripe olives along with the enrichment of this product in phenolic compounds and potassium.
The Diversity of N-Glycans of Chlorella Food Supplements Challenges Current Species Classification
Authors: Mócsai Réka , Helm Johannes , Polacsek Karin , Stadlmann Johannes , Altmann Friedrich
Published: October 2024

N-glycans have recently emerged as highly varied elements of Chlorella strains and products. Four years and eighty samples later, the increasing N-glycan diversity calls for a re-examination in the light of concepts of species designations and product authenticity. N-glycans of commercial products were analyzed by matrix-assisted time-of-flight mass spectrometry (MALDI-TOF MS) supported by chromatography on porous graphitic carbon with mass spectrometric detection. Although 36% of 172 products were labeled C. vulgaris, only 9% presented what could be taken as a C. vulgaris type N-glycan pattern. Respectively, 5 and 20% of the products matched with C. sorokiniana strains SAG 211-8k and SAG 211-34, which, however, carry entirely different structures. Furthermore, 41% presented with one of four frequently occurring glyco-types while 26% of the samples showed unique or rare N-glycan patterns. These glycan signatures thus profoundly challenge the stated species designations. By no means do we want to question the presumed health benefits of the products or the sincerity of manufacturers. We rather aim to raise awareness of the fascinating but also concerning diversity of microalgal N-glycans and suggest it as a means for defining product identity and taxonomic classifications.
Monitoring and Risk Assessment of Multi-Pesticide Residues in Apples: A Focus on Consumer Safety
Authors: Odabas Eylem , Keklik Mehmet , Golge Ozgur , González-Curbelo Miguel Ángel , Kabak Bulent
Published: October 2024

Pesticide residues in human diets pose significant health hazards, particularly for vulnerable populations such as infants and children. This study aimed to determine pesticide residues in apples and to assess the cumulatively chronic risk posed to adult and child consumers from simultaneous exposure to multiple residues. During the 2022–2023 harvest seasons, 100 apple samples from Turkey were analyzed for the presence of 225 different pesticide residues. Pesticide extraction was performed using the QuEChERS method, followed by detection through liquid chromatography coupled with tandem mass spectrometry. Fifteen distinct pesticides (ten insecticides and five fungicides) were detected in 64 out of the 100 apple samples analyzed. Eleven samples contained pesticide residues that exceeded the maximum residue limit (MRL) set by the Turkish Food Codex and the European Union. Thiophanate-methyl was the most frequently detected pesticide (34%) in apples, with concentrations ranging from 0.012 to 0.108 mg kg−1, all of which were well below the MRL of 0.5 mg kg−1. Other commonly detected residues included chlorantraniliprole (28%), acetamiprid (24%), sulfoxaflor (22%), bifenazate (18%), indoxacarb (13%), diflubenzuron (12%), and carbendazim (10%). Under a worst-case scenario, the hazard index (HI) values for adults and children were 0.85% and 2.60%, respectively, indicating that these values remain significantly below the risk threshold of 100%, suggesting no associated health risks from apple consumption. However, regular monitoring of pesticide residues in fresh fruits and vegetables remains critically important.