bluuebunny/crossref_metadata_2025 huggingface dataset:
On Elastic Stability and Positive Definiteness for One-Dimensional Quasicrystals
Authors: Agiasofitou Eleni , Lazar Markus
Published: February 2025

In this work, a proper formulation of the elastic stability and positive definiteness of the elastic energy density of one-dimensional quasicrystals is provided. Based on an appropriate Voigt notation, the Sylvester criterion is applied and the necessary and sufficient conditions for the positive definiteness of the elastic energy density imposed on the elastic constants are derived for each Laue class from 4 to 10 of one-dimensional quasicrystals. Comparisons of the obtained sets of the necessary and sufficient conditions of one-dimensional quasicrystals with the corresponding ones of crystals are made, revealing that the phason fields, which characterize the quasicrystalline structure in any case, considerably influence the number as well as the degree of the obtained inequalities.
Administration of FOLFIRINOX for Advanced Pancreatic Cancer: Physician Practice Patterns During Early Use
Authors: Gotfrit Joanna , Marginean Horia , Ko Yoo-Joung , Ghafoor Akmal , Kavan Petr , Chalchal Haji , Ahmed Shahid , Mulder Karen , Tang Patricia , Goodwin Rachel
Published: February 2025

Advanced pancreatic cancer results in high morbidity and mortality. The standard of care treatment in the advanced setting changed in 2011 with the introduction of FOLFIRINOX (FFX) chemotherapy. However, it was highly toxic with significant risk of complications. We assessed the practice patterns of medical oncologists across Canada. Methods: We performed a retrospective study of consecutive patients with advanced pancreatic cancer treated with FFX at eight Canadian cancer centers. Demographic, treatment, and outcome data were collected and analyzed. Results: The median age of the patients was 61 (range 24–80), 43% were female, 96% had an ECOG PS of 0 or 1, and 50% had three or more metastatic sites. The median follow-up time was 20.8 months (95%CI 18.6–24.9). Physicians started FFX at the standard dose 31% of the time. Physicians prescribed GCSF for primary prophylaxis most when giving standard-dose FFX (30% of the time) in comparison to reduced dose with or without the 5-FU bolus. Dose reductions occurred in 78.1% of patients, while dose delay occurred in 65.2% of patients. Conclusions: Medical oncologists in Canada historically prescribed FFX to patients with advanced pancreatic cancer in a fashion that was not uniform, prior to the emergence of evidence for upfront dose reductions.
Changes and Influencing Factors of Carbon Content in Surface Sediments of Different Sedimentary Environments Along the Jiangsu Coast, China
Authors: Xu Linlu , Ye Hui , Yin Jianing , Shu Qiang , Fan Yuxin
Published: February 2025

Coastal areas are essential for global ‘blue carbon’ burial, significantly impacting the global carbon cycle. To better understand the carbon burial capacity, impact factors, and response mechanisms of surface sediments in different coastline regions, this study investigated the surface sediments of the Spartina alterniflora vegetation, transition, and bare flat areas along Jiangsu coast in China. The results indicated significant changes in organic carbon (OC), inorganic carbon (IC), and various physicochemical property indicators between the three coastal environments. There were also significant differences in the important impact factors of OC and IC in each region. In areas of vegetation, OC and IC influenced each other, while nitrogen (N), clay, and sand were common impact factors. The pH only had a significant impact on OC. In the bare flat area, the important impact factors of OC and IC were identical: OC/IC, clay, salinity (SAL), and sand. However, the important impact factors of OC and IC in the transition area have undergone significant changes. The important impact factors of OC were N, total phosphorus (TP), total sulfur (TS), SAL, and sand. The partial least squares regression analysis results of IC were poor, and there were no important impact factors. This study refined the spatial distribution patterns and response mechanisms to the important impact factors of carbon in different coastal subregions, providing a basis for accurately evaluating the role of coastal wetlands in mitigating global climate change.
Spatial–Temporal Pattern and Stability Analysis of Zooplankton Community Structure in the Lower Yellow River in China
Authors: Wang Yaowei , Zhang Shiyuan , Sun Minfang , Han Jiamin , Wang Ziyue , Chen Xinlei , Chen Zengfei , Qin Haiming
Published: February 2025

In March (spring), June (summer), October (autumn), and December (winter) 2022, zooplankton were quantitatively investigated in the lower reaches of the Yellow River in China. A total of 29 sampling points that were separated by about 20 km were set up in the survey area. The purpose of this study is to investigate the seasonal dynamics and spatial distribution characteristics of the zooplankton community in the Yellow River, which has a high sediment content. The main results are as follows: A total of 119 species of zooplankton were found during the survey, including 70 species of rotifers, 29 species of cladocerans, and 20 species of copepods. Because the temperate continental monsoon climate has four distinct seasons, the zooplankton community in the Yellow River showed typical seasonal dynamics. There were significant differences in the richness of zooplankton and dominant species across the four seasons (p < 0.05). There were 15 common species in each of the four seasons. The density and biomass of zooplankton were significantly higher in spring (16.76 ind./L; 0.049 mg/L) and summer (26.17 ind./L; 0.249 mg/L) compared to autumn (5.65 ind./L; 0.042 mg/L) and winter (1.56 ind./L; 0.006 mg/L) (p < 0.05). Additionally, the density and biomass of zooplankton were significantly lower in estuarine areas compared to other areas. The results of multidimensional non-metric ranking (NMDS) based on zooplankton abundance showed four distinct communities: a spring community, a summer community, an autumn community, and a winter community. The spatial heterogeneity of zooplankton communities in spring, summer, and autumn was significantly different (p < 0.05). However, only the estuarine area had a special zooplankton community in winter. Monte Carlo test results showed that pH, water temperature, electrical conductivity, dissolved oxygen, total nitrogen, and total phosphorus were the main environmental factors affecting the community structure of zooplankton (p < 0.05). The areas of the Yellow River affected by human disturbances have lower zooplankton community stability. Overall, the standing stock of zooplankton was very low (less than 15 ind./L), but the species richness was higher (119 species) in the river, which had a high sediment content and a fast flow.
Editorial for the Special Issue “Imaging Diagnosis in the Abdomen”—A Step Forward in Diagnostic Precision
Authors: Boraschi Piero , Donati Francescamaria
Published: February 2025

Abdominal imaging has undergone a significant transformation in recent years, driven by the rapid evolution of diagnostic technologies and their integration into clinical practice [...]
A Study of MANET Routing Protocols in Heterogeneous Networks: A Review and Performance Comparison
Authors: Sarkar Nurul I. , Ali Md Jahan
Published: February 2025

Mobile ad hoc networks (MANETs) are becoming a popular networking technology as they can easily be set up and provide communication support on the go. These networks can be used in application areas, such as battlefields and disaster relief operations, where infrastructure networks are not available. Like media access control protocols, MANET routing protocols can also play an important role in determining network capacity and system performance. Research on the impact of heterogeneous nodes in terms of MANET performance is required for proper deployment of such systems. While MANET routing protocols have been studied and reported extensively in the networking literature, the performance of heterogeneous nodes/devices in terms of system performance has not been fully explored yet. The main objective of this paper is to review and compare the performance of four selected MANET routing protocols (AODV, OLSR, BATMAN and DYMO) in a heterogeneous MANET setting. We consider three different types of nodes in the MANET routing performance study, namely PDAs (fixed nodes with no mobility), laptops (low-mobility nodes) and mobile phones (high-mobility nodes). We measure the QoS metrics, such as the end-to-end delays, throughput, and packet delivery ratios, using the OMNeT++-network simulator. The findings reported in this paper provide some insights into MANET routing performance issues and challenges that can help network researchers and engineers to contribute further toward developing next-generation wireless networks capable of operating under heterogeneous networking constraints.
Improved Droop Control Strategy for Islanded Microgrids Based on the Adaptive Weight Particle Swarm Optimization Algorithm
Authors: Tu Binge , Xu Xianglian , Gu Yifeng , Deng Kaitian , Xu Yuli , Zhang Tianyu , Gao Xinrong , Wang Kangning , Wei Qingjie
Published: February 2025

In islanded low-voltage microgrids, the parallel operation of inverters using traditional droop control strategies often results in imbalanced output impedances among inverters due to variations in line impedance. This imbalance prevents the equitable distribution of reactive power according to the designated droop coefficients. To address this challenge, this paper proposes an improved droop control strategy. First, the virtual impedance control method is added to the strategy of traditional droop control, and then an adaptive weight particle swarm optimization algorithm (APSO) is introduced in the voltage outer loop control module to optimize the parameter setting of the PID controller. Finally, a comparative analysis was conducted on the output results of the improved droop control before and after introducing the algorithm. This proposed strategy is systematically analyzed through modeling and simulation in the MATLAB/Simulink environment to assess its impact on output voltage stability, reactive power sharing, and circulating current magnitude among parallel inverters. The simulation results indicate that the improved droop control with the introduction of virtual impedance effectively achieves equal reactive power sharing among parallel inverters. Moreover, by employing the APSO algorithm, the stability of the inverter output voltage is significantly enhanced. The maximum voltage deviation between two inverters is reduced to below 0.03%, while the maximum reactive power deviation decreases from over 3.5% to less than 2.5%. These improvements effectively reduce the circulating currents between two paralleled inverters, ensuring that the maximum current remains below 1.5 A and the minimum stays above −1 A.
Review of Evolution and Rising Significance of Wafer-Level Electroplating Equipment in Semiconductor Manufacturing
Authors: Jiang Tao , Hu Huiyong
Published: February 2025

Electroplating has become a cornerstone technology in semiconductor manufacturing, enabling high-performance interconnects and advanced packaging. Since the introduction of the Damascene Cu process at the 180 nm node, it has evolved to meet the demands for precision, uniformity, and scalability in miniaturized nodes and complex packaging architectures. The shift to horizontal electroplating systems has enhanced uniformity and process stability, particularly for applications such as TSVs, Cu pillars, micro-bumps, and RDLs. Emerging innovations like pulse electroplating, segmented anode control, and AI-driven monitoring are addressing the challenges of fine-pitch interconnects and emerging interconnect materials, such as cobalt. These advancements are critical for high-density interconnects used in AI, HPC, and high-frequency applications. This review explores the advancements in electroplating technologies, focusing on their role in semiconductor manufacturing. It highlights the evolving equipment designs and their implications for achieving precision, scalability, and reliability at advanced nodes. The ongoing development of electroplating equipment and techniques will support the reliability and performance of future semiconductor devices, reinforcing electroplating as a cornerstone technology in advanced packaging and fabrication.
Fast-YOLO Network Model for X-Ray Image Detection of Pneumonia
Authors: Zhao Bin , Chang Lianjun , Liu Zhenyu
Published: February 2025

Pneumonia is a respiratory infection that affects the lungs. The symptoms of viral and bacterial pneumonia are similar. In order to improve automatic detection efficiency regarding X-ray images of pneumonia, this paper, we propose a novel pneumonia detection method based on the Fast-YOLO network model. First, we re-annotated the open-source dataset of MIMIC Chest X-ray pneumonia, enhancing the model’s adaptability to complex scenes by incorporating Mixup, Mosaic, and Copy–Paste augmentation methods. Additionally, CutMix and Random Erasing were introduced to increase data diversity. Next, we developed a lightweight FASPA Fast Pyramid Attention Mechanism and designed the Fast-YOLO network based on this mechanism to effectively address the complex features in pneumonia X-ray images, such as low contrast and an uneven distribution of local lesions. The Fast-YOLO network improves upon the YOLOv11 architecture by replacing the C3k2 module with the FASPA attention mechanism, significantly reducing the network’s parameter count while maintaining detection performance. Furthermore, the Fast-YOLO network enhances feature extraction capabilities when handling scenes with geometric deformations, multi-scale features, and dynamic changes. It expands the receptive field, thereby balancing computational efficiency and accuracy. Finally, the experimental results demonstrate that the Fast-YOLO network, compared to traditional convolutional neural network methods, can effectively identify pneumonia regions and localize lesions in pneumonia X-ray image detection tasks, achieving significant improvements in FPS, precision, recall, mAP @0.5, and mAP @0.5:0.95. This confirms that Fast-YOLO strikes a balance between computational efficiency and accuracy. The network’s excellent generalization capability across different datasets has been validated, showing the potential to accelerate the pneumonia diagnostic process for clinicians and enhance diagnostic accuracy.
Design and Control of the Resonant Auxiliary Circuit for Voltage Regulator Module (VRM) with Fast Load Step Transient
Authors: Li Yongjia , Xia Jianlin , Xu Shen , Zhu Encheng , Sun Weifeng
Published: February 2025

This paper proposes a transient energy auxiliary supply circuit architecture based on resonant switched-capacitor principles, aimed at optimizing the system’s transient response to meet the growing power supply demands. This paper first introduces the relevant principles of resonant switched-capacitor converters. Based on this, a transient energy path topology based on resonant principles is designed to achieve bidirectional, fast, and low electromagnetic interference energy transmission. Corresponding system coordination control strategies and high-precision switch control based on delay lines are proposed for the designed circuit topology. A circuit model is built in SIMPLIS (V8.20a) software for system simulation, and a prototype is built based on FPGA to verify circuit functionality and performance. Experimental results demonstrate that the resonant energy auxiliary circuit can operate in conjunction with a six-phase Buck circuit prototype. Under test conditions of a 500 kHz operating frequency, 6.5 V input voltage, and 0.75 V output voltage, the overshoot voltage is reduced by more than 17% across the entire operating range. When the load steps from 200 A to 20 A, the overshoot voltage is reduced to only 85 mV, a decrease of 27.97%, while the recovery time is 28.8 µs, a reduction of 37.66%. These results confirm that the auxiliary circuit can significantly improve the system’s transient response under large load steps, meeting the design requirements.
Bounded-Error LiDAR Compression for Bandwidth-Efficient Cloud-Edge In-Vehicle Data Transmission
Authors: Chang Ray-I , Hsu Ting-Wei , Yang Chih , Chen Yen-Ting
Published: February 2025

Recent advances in autonomous driving have led to an increased use of LiDAR (Light Detection and Ranging) sensors for high-frequency 3D perceptions, resulting in massive data volumes that challenge in-vehicle networks, storage systems, and cloud-edge communications. To address this issue, we propose a bounded-error LiDAR compression framework that enforces a user-defined maximum coordinate deviation (e.g., 2 cm) in the real-world space. Our method combines multiple compression strategies in both axis-wise metric Axis or Euclidean metric L2 (namely, Error-Bounded Huffman Coding (EB-HC), Error-Bounded 3D Compression (EB-3D), and the extended Error-Bounded Huffman Coding with 3D Integration (EB-HC-3D)) with a lossless Huffman coding baseline. By quantizing and grouping point coordinates based on a strict threshold (either axis-wise or Euclidean), our method significantly reduces data size while preserving the geometric fidelity. Experiments on the KITTI dataset demonstrate that, under a 2 cm bounded-error, our single-bin compression reduces the data to 25–35% of their original size, while multi-bin processing can further compress the data to 15–25% of their original volume. An analysis of compression ratios, error metrics, and encoding/decoding speeds shows that our method achieves a substantial data reduction while keeping reconstruction errors within the specified limit. Moreover, runtime profiling indicates that our method is well-suited for deployment on in-vehicle edge devices, thereby enabling scalable cloud-edge cooperation.
Enhancing Large Language Models with RAG for Visual Language Navigation in Continuous Environments
Authors: Bao Xiaoan , Lv Zhiqiang , Wu Biao
Published: February 2025

The task of Visual Language Navigation in Continuous Environments (VLN-CE) aims to enable agents to comprehend and execute human instructions in real-world environments. However, current methods frequently face challenges such as insufficient knowledge and difficulties in obstacle avoidance when performing VLN-CE tasks. To address these challenges, this paper proposes a navigation approach guided by a Retrieval Augmented Generation (RAG) large language model (RAGNav). By constructing a navigation knowledge base, we leverage RAG to enhance the input of LLM, enabling the generation of more precise navigation plans. Furthermore, we introduce a Prompt Enhanced Obstacle Avoidance strategy (PEOA) to improve the flexibility and robustness of agents in complex environments. Experimental results indicate that our method not only increases the navigation accuracy of agents but also enhances their obstacle avoidance capabilities, achieving a 2% and 2.32% increase in success rates on the public datasets R2R-CE and RxR-CE, respectively.
Liquid Level Detection of Polytetrafluoroethylene Emulsion Rotary Vibrating Screen Device Based on TransResNet
Authors: Liu Wenwu , Fan Xianghui , Liu Meng , Li Hang , Du Jiang , Liu Nianbo
Published: February 2025

The precise real-time detection of polytetrafluoroethylene (PTFE) emulsion rotary vibration sieve levels is critical for improving production efficiency, ensuring product quality, and safeguarding personnel safety. This research presents a deep-learning-oriented video surveillance model for the intelligent level detection of vibrating screens, waste drums, and emulsion outlets, effectively addressing the limitations of traditional methods. With the introduction of TransResNet, which combines Vision Transformer (ViT) with ResNet, we can utilize the advantages of both approaches. ViT has excellent global information capture capability for processing image features, while ResNet excels in local feature extraction. The combined model effectively recognizes level changes in complex backgrounds, enhancing overall detection performance. During model training, synthetic data generation is used to alleviate the marker scarcity problem and generate synthetic images under different liquid level states to further enrich the training dataset, solve the issue of unequal data distribution, and enhance the model’s capacity to generalize. In order to validate the efficacy of our proposed model, we carried out a performance test with real-world data obtained from a material production site. The test results show that the model achieves 96%, 99%, and 99% accuracy at three test points, respectively: the vibrating screen, waste drum, and emulsion. These results not only prove the efficiency of the model but also highlight its significant value in practical applications.
Inserted Window Recognition Based Capacitor Condition Monitoring Method for MMC Sub-Module with Nearest Level Modulation
Authors: Lin Wenqi , Pan Jianyu
Published: February 2025

The sub-module capacitor is the most vulnerable component in a modular multilevel converter (MMC), and its aging poses a significant challenge to system stability. To accurately monitor capacitor aging, this article utilizes capacitor voltage fluctuations to recognize the inserted window for capacitance calculation using nearest-level modulation. Additionally, a time-slicing method is developed to improve accuracy. The proposed method, which combines the inserted window recognition method with the time-slicing algorithm, offers a simple, easy-implementation approach. Simulations and experimental results validate that the method achieves high accuracy (less than 0.5%). Moreover, it does not require additional sensors, precise extraction of switching signals, or interruption to the system’s normal operation, making it highly suitable for MMC systems with a large number of sub-modules. Furthermore, the proposed method also demonstrates strong robustness in dynamic conditions and can be extended to all sub-modules.
Robust Optimal Sizing of a Stand-Alone Hybrid Renewable Energy System Using Machine Learning-Based Uncertainty Sets
Authors: Keyvandarian Ali , Saif Ahmed , Pelot Ronald
Published: February 2025

This study introduces an adaptive robust approach for optimally sizing hybrid renewable energy systems (HRESs) comprising solar panels, wind turbines, batteries, and a diesel generator. It integrates vector auto-regressive models (VAR) and neural networks (NN) into dynamic uncertainty sets (DUSs) to address temporal auto-correlations and cross-correlations among uncertain parameters like energy demand and solar and wind energy supply. These DUSs are compared to static and independent dynamic uncertainty sets based on time series (TS) from the literature. An exact iterative algorithm is developed to solve the problem effectively. A case study of a northern Ontario community evaluates the proposed framework and the solution method using real test data. Simulation reveals a 10.7% increase in capital cost on average but a 36.2% decrease in operational cost, resulting in a 16.4% total cost reduction and an 8.1% improvement in system reliability compared to the nominal model employing point estimates. Furthermore, the proposed VAR- and NN-based DUSs significantly outperform classical static and TS-based dynamic sets, underscoring the necessity of considering cross-correlations in uncertainty quantification.
Assessing Browser Security: A Detailed Study Based on CVE Metrics
Authors: Chalyi Oleksii , Driaunys Kęstutis , Rudžionis Vytautas
Published: February 2025

This study systematically evaluates the vulnerabilities of modern web browsers using developed indices derived from the CVE database, including ICVE, ICVSS, IR and IT. These indices incorporate metrics such as vulnerability severity and risks, along with browser popularity, to enable a balanced comparison of browser security. The results highlight significant differences in browser security: while Google Chrome and Samsung Internet exhibited lower threat indices, Mozilla Firefox demonstrated consistently higher scores, indicating greater exposure to risks. These observations a slightly contradict widespread opinion. The findings emphasize the importance of timely software updates in mitigating vulnerabilities, as many incidents were linked to outdated browser versions. This study also introduces a robust methodology for assessing browser threats, providing a framework for future research. Potential applications include developing browser-based penetration testing systems to simulate phishing and data extraction scenarios, offering insights into user-specific risks and broader organizational impacts. By combining theoretical analysis with practical implications, this work contributes to advancing browser security and lays the foundation for future applied research in cybersecurity.
Estimating Maximum Dwell Time for Firefighting Teams Based on Ambient Temperature and Radiant Heat Exposure
Authors: Romero-Barriuso Álvaro , Ballesteros-Álvarez Jesús Manuel , Villena-Escribano Blasa María , Fuentes-Bargues José Luis , González-Gaya Cristina
Published: February 2025

This research presents a scientifically grounded model designed to enhance the safety protocols for firefighting teams during fire intervention scenarios. The model estimates the maximum allowable exposure duration based on ambient temperature and radiant heat, employing data captured by thermal imaging cameras, which provide real-time measurements of infrared radiation emitted by fire-affected zones. Utilising the Stefan–Boltzmann law to quantify radiative heat transfer and Probit vulnerability analysis to assess thermal risk, critical temperature thresholds and corresponding exposure durations were determined. The results indicate that the maximum permissible ambient temperature for firefighting interventions is 263 °C, with a safe exposure duration of 26 s under these thermal conditions. This approach underscores the significance of ambient temperature as a pivotal parameter in risk assessment and intervention strategy development. Furthermore, the model’s applicability extends to other high-risk environments, including industrial operations, providing a robust and versatile framework for safety management. These findings contribute to advancing evidence-based protocols that mitigate injury risks, safeguard firefighting personnel, and optimise operational decision-making during emergencies.
Risk Assessment of Toxic Gas Dispersion from Electric Vehicle Fires in Underground Apartment Parking Garages Using Numerical Analysis
Authors: Jang Jiseong , Jeon Joonho , Oh Chang Bo
Published: February 2025

With the rising adoption of electric vehicles (EVs), fire-related issues have garnered significant attention, prompting extensive research efforts. This study investigates the dispersion of toxic gases generated during EV fires in confined spaces, such as underground parking garages, to enhance fire safety protocols. Using the fire dynamics simulator (FDS), simulations were conducted for 24 kWh, 53 kWh, and 99.8 kWh battery scenarios to assess the impact of increasing battery capacities on toxic gas emissions. The results indicate that hydrogen fluoride (HF) concentrations in poorly ventilated areas peaked at 488.2 ppm, significantly exceeding the Acute Exposure Guideline Level (AEGL-2) threshold of 12 ppm. The exposure time exceeding AEGL-2 (30 min) was recorded as 53 min and 49 s for the 99.8 kWh scenario, highlighting a substantial risk to occupants and emergency responders. Additionally, the fractional effective dose (FED) for asphyxiant gases and the fractional effective concentration (FEC) for irritant gases were analyzed, revealing that larger battery capacities and proximity to the fire source reduced tenability time by up to 47% compared to smaller batteries. These findings provide critical insights into fire safety measures, emphasizing the necessity of early fire detection systems, enhanced ventilation strategies, and battery-specific fire suppression technologies in confined environments.
Mushrooms as Nutritional Powerhouses: A Review of Their Bioactive Compounds, Health Benefits, and Value-Added Products
Authors: Singh Akruti , Saini Ramesh Kumar , Kumar Amit , Chawla Prince , Kaushik Ravinder
Published: February 2025

Mushrooms are known to be a nutritional powerhouse, offering diverse bioactive compounds that promote and enhance health. Mushrooms provide a distinguishable taste and aroma and are an essential source of vitamin D2, vitamin B complex, hydroxybenzoic acids (HBAs) and hydroxycinnamic acids (HCAs), terpenes, sterols, and β-glucans. Edible mushroom varieties such as Hericium erinaceus, Ganoderma sp., and Lentinula edodes are recognized as functional foods due to their remarkable potential for disease prevention and promotion of overall health and well-being. These varieties have antioxidants, anti-inflammatory, cytoprotective, cholesterol-lowering, antidiabetic, antimicrobial, and anticancer properties, as well as controlling blood pressure, being an immunity booster, and strengthening bone properties. In addition, they contain essential non-digestible oligosaccharides (NDOs) and ergothioneine, a potential substrate for gut microflora. Supplementing our daily meals with those can add value to our food, providing health benefits. Novel edible mushrooms are being investigated to explore their bioactive substances and their therapeutic properties, to benefit human health. The scientific community (mycologists) is currently studying the prospects for unlocking the full health advantages of mushrooms. This review aims to promote knowledge of mushroom culturing conditions, their nutritional potential, and the value-added products of 11 varieties.
Storage Stability and Lipidomic Analysis Reveal the Effect of Frozen Storage Temperature on Pacific Saury (Cololabis saira)
Authors: Zhao Ling , Wang Shanyu , Liu Qi , Cao Rong , Zhang Yating , Su Dong , Yu Yueqin
Published: February 2025

Objectives: This study aimed to assess the effects of storage temperature on the lipidomics profile change in Pacific saury (Cololabis saira). Methods: In this paper, C. saira underwent frozen storage at two different temperatures, T1 (−18 °C) and T2 (−25 °C), for a duration of three months. Chemical and lipidomic methods were used to determine the changes in lipids during the storage process. Results: Results showed that the content of triglyceride and phospholipid decreased significantly (p < 0.05), and free fatty acid increased significantly (p < 0.05), while the content of total cholesterol remained relatively constant across different storage temperatures. Additionally, an increasing trend in AV, POV, and TBARS contents was observed after the freezing process, with lipid oxidation being significantly higher in the −18 °C group compared to the −25 °C group (p < 0.05). A comprehensive analysis identified 4854 lipid molecules in the muscles of C. saira, categorized into 46 lipid subclasses, predominantly including triglycerides (TG), phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylinositol (PI), phosphatidylglycerol (PG), and diglycerides (DG). Among them, TG was the most abundant lipid, followed by PC. Using orthogonal partial least squares discriminant analysis (OPLS-DA) with a variable importance in projection (VIP) score > 1 and p value < 0.05 as criteria, 338, 271, and 103 highly significantly differentiated lipids were detected in the comparison groups CK vs. T1, CK vs. T2, and T1 vs. T2, respectively. The results indicated that storage at −18 °C had a more pronounced effect than storage at −25 °C. During the freezing process, TG expression was significantly down-regulated, and TG(18:4_14:0_20:5), TG(20:5_13:0_22:6), TG(22:6_14:1_22:6), and TG(18:4_13:0_22:6) were the most predominant individuals. The CK group was initially present in C. saira before storage. Differential lipid molecules in the CK vs. T1 and CK vs. T2 groups were screened using a fold change (FC) > 2 or FC < 0.5. In the CK vs. T2 group, 102 highly significant differential lipid molecules were identified, with 55 being down-regulated across seven subclasses. In contrast, the CK vs. T1 group revealed 254 highly significant differential lipid molecules, with 85 down-regulated across 13 subclasses. The results showed that more PCs and PEs were down-regulated, with a higher differential abundance of PE and PC in the −25 °C group compared to the −18 °C group. The differential metabolites were primarily enriched in 17 metabolic pathways, with glycerophospholipid metabolism being the most prominent, followed by sphingolipid metabolism during the frozen storage. Conclusions: Overall, −25 °C storage in production was more favorable for maintaining the lipid stability of C. saira. This work could provide useful information for aquatic product processing and lipidomics.
Flavonoid-Rich Extracts from Chuju (Asteraceae Chrysanthemum L.) Alleviate the Disturbance of Glycolipid Metabolism on Type 2 Diabetic Mice via Modulating the Gut Microbiota
Authors: Yin Yu , Nie Wen , Tang Zheng-Quan , Zhu Shuang-Jie
Published: February 2025

Type 2 diabetes mellitus (T2DM) and its associated complications represent a significant public health issue affecting hundreds of millions of people globally; thus, measures to prevent T2DM are urgently needed. Chuju has been proven to possess antihyperglycemic activity. However, the bioactive ingredients in chuju that contribute to its antihyperglycemic activity, as well as the relationship between its antihyperglycemic activity and the gut microbiota, remain unclear. To understand the potential effects that it has on T2DM, the glycolipid metabolism and gut microbiota regulation of flavonoid-rich extracts from chuju (CJE) were investigated. The results showed that the top ten flavonoid compounds in CJE are Apigenin 6, 8-digalactoside, Apigenin 6-C-glucoside 8-C-arabinoside, Luteolin-4′-O-glucoside, Isoshaftoside, Scutellarin, Quercetin 3-O-malonylglucoside, Chrysoeriol 7-O-glucoside, Quercetin-3,4′-O-di-beta-glucoside, Luteolin 6-C-glucoside 8-C-arabinoside, and Homoorientin. Furthermore, CJE mitigated hyperglycemia and glycolipid metabolism by reducing the abundance of Faecalibaculum, Coriobacteriaceae, and Romboutsia and increasing the abundance of Alistipes. In addition, the results of Western blot analysis showed that CJE could enhance glycogen synthesis and glucose transport by up-regulating the phosphorylation of IRS1-PI3K-Akt and AMPK-GLUT4. Simultaneously, CJE could decrease gluconeogenesis by down-regulating the phosphorylation of FoxO1/GSK 3β. In conclusion, the findings of this study provide new evidence supporting the hypothesis that CJE can be used as part of a therapeutic approach for treating disturbances in glycolipid metabolism via regulating the gut microbiota and mediating the IRS1-PI3K-Akt-FoxO1/GSK 3β and AMPK-GLUT4 pathways.
Isolation and Characterization of Enterocin-Producing Enterococcus faecium Strains from Algerian Traditional Food “Dried Figs Marinated in Olive Oil”: Functional and Safety Evaluations
Authors: Merzoug Mohamed , Bendida Keltoum , Aireche Marwa , Zater Zohra Yasmine , Brakna Chaimaa Naila , Hammadi Amaria Ilhem , Saidi Yasmine , Todorov Svetoslav Dimitrov , Saidi Djamal
Published: February 2025

The increasing consumer demand for natural and sustainable food preservation methods has highlighted the potential of lactic acid bacteria (LAB) and their bioactive metabolites, particularly bacteriocins, as effective antimicrobial agents. This study aimed to isolate and characterize Enterococcus faecium strains from Algerian traditional dried figs marinated in olive oil, a nutrient-dense and underexplored food matrix. Twelve isolates were identified as E. faecium using MALDI-TOF MS and 16S rRNA gene sequencing, ensuring precise taxonomic classification. Genotypic analyses (BOX-PCR, GTG-PCR, and ERIC-PCR) revealed substantial genetic diversity, with BOX-PCR demonstrating superior discriminatory power. Functional screening confirmed the presence of enterocin genes, including entA (100% of strains), entB (60%), and entL50A/B (20%), which correlated with inhibition zones against Enterococcus faecium VCY, Micrococcus luteus GPE 3001, Staphylococcus aureus ATCC 25923, Pseudomonas aeruginosa ATCC 27853, and Acinetobacter lwoffii GPE 3002. Genotype–phenotype correlation analysis identified strain HFM7 as the most potent antimicrobial strain, exhibiting the largest inhibition zone (20.0 ± 1.0 mm) and harboring three enterocin genes (entA, entL50A, and entL50B). Protease sensitivity confirmed the proteinaceous nature of the antimicrobial compounds. Importantly, no virulence factors (esp, gelE, and hyl) or antibiotic resistance genes (vanA, vanB, ermA, ermB, and aac(6′)-Ie-alph(2″)) were detected, underscoring the safety of these isolates for food applications. These findings suggest that E. faecium strains from traditional foods are promising candidates as natural biopreservatives and starter cultures in clean-label food systems. By bridging traditional food ecosystems and modern biotechnological advancements, this study provides a foundation for sustainable, minimally processed food preservation strategies with potential applications in enhancing food safety and shelf life.
Advances in Starch-Based Nanocomposites for Functional Food Systems: Harnessing AI and Nuclear Magnetic Resonance Technologies for Tailored Stability and Bioactivity
Authors: Sun Yue , Wang Ziyu , Ye Jian , Li Yinta , Wang Lili , Cao Ruge
Published: February 2025

Starch-based nanocomposites (SNCs) are at the forefront of innovations in food science, offering unparalleled opportunities for enhancing the stability, bioactivity, and overall functionality of food systems. This review delves into the potential of SNCs to address contemporary challenges in food formulation, focusing on the synergistic effects of their components. By integrating cutting-edge technologies, such as artificial intelligence (AI) and nuclear magnetic resonance (NMR), we explore new avenues for enhancing the precision, predictability, and functionality of SNCs. AI is applied to optimize the design of SNCs, leveraging predictive modeling to fine-tune material properties and streamline production processes. The role of NMR is also critically examined, with particular emphasis on its capacity to provide high-resolution structural insights, monitor stability over time, and elucidate molecular interactions within food matrices. Through detailed examples, the review highlights the impact of NMR in unraveling the complex behaviors of bioactive compounds encapsulated in SNCs. Additionally, we discuss the integration of functional assays and AI-driven analytics in assessing the bioactivity and sensory properties of these systems, providing a robust framework for the rational design of advanced food products. The synergy between AI, NMR, and SNCs opens new pathways for developing tailored, high-performance food formulations that address both health and consumer preferences.
The Effect of Protein–Starch Interaction on the Structure and Properties of Starch, and Its Application in Flour Products
Authors: Zhang Jiayan , Liu Yuhao , Wang Ping , Zhao Yansheng , Zhu Ying , Xiao Xiang
Published: February 2025

Grains are an energy source for human beings, and the two main components—starch and protein—determine the application of grains in food. The structure and properties of starch play a decisive role in determining processing characteristics, nutritional properties, and application in grain-based foods. The interaction of proteins with starch greatly affects the structure, physicochemical, and digestive properties of the starch matrix. Scientists have tried to apply this effect to create foods tailored to specific needs. Therefore, studying the effect of protein on the structure and properties of starch in the starch–protein complexes will help in designing personalized and improved starch-based food. This paper reviews the latest research about the effects of endogenous and exogenous proteins on the structure and properties of starch, as well as factors influencing the interaction between protein and starch. This includes investigations of the chain and aggregation structure of proteins with starch, as well as assessments of impacts on thermal properties, rheology, gel texture properties, hydration properties, aging, and digestion. In addition, particular examples illustrating the effects of protein–starch interaction on starch properties in various foods are discussed, providing a reference for designing starch–protein foods that are rich in terms of nutrition and easier to process.
Developing a Healthy and Climate-Friendly Community College Culinary Curriculum
Authors: Cohen Nevin , Fernandes Nicolle , D’Alessandro Mark , Fraser Katherine Tomaino , Greene Julia
Published: February 2025

This paper describes the development of the Climate-Friendly, Healthy, Efficient Food Service (CHEF) curriculum at the City University of New York (CUNY). The program addresses a critical gap between growing industry demand for sustainability-trained workers and limited community college culinary education in these areas. Through collaborative design with industry partners, public agencies, and non-profit organizations, we created four core courses covering sustainable food service operations, culinary practices, food systems, and nutrition. The curriculum offers two implementation pathways: a 100 h continuing education credential and an Associate of Applied Science degree concentration. Industry partners have committed to supporting the program through internships and recognition of the credential in hiring decisions. This model demonstrates the feasibility of integrating comprehensive sustainability education into community college culinary programs while enhancing graduates’ career prospects in the expanding sustainable food service sector.
Impact of the 1742–1743 Plague Epidemic on Global Excess Deaths and Social Dynamics in the City of Santa Fe and Along the Royal Road Between Buenos Aires and Lima
Authors: Villafañe Jorge Hugo
Published: February 2025

The 1742–1743 plague epidemic significantly impacted Santa Fe, a key city along the Royal Road (Camino Real), a vital colonial trade route connecting Buenos Aires and Lima. This study examines the epidemic’s demographic and socio-economic consequences in Santa Fe, focusing on excess mortality and its disproportionate impact on marginalized groups, such as Indigenous and African-descended populations. Utilizing parish records, census data, and archival sources, the research quantifies mortality rates during the epidemic and highlights the role of Santa Fe’s strategic position in facilitating the rapid spread of the disease. The findings underscore the intersection of systemic vulnerabilities and territorial dynamics shaped by Bourbon reforms, which exacerbated the epidemic’s effects. Furthermore, this study explores the resilience of local communities, emphasizing how cultural and religious practices contributed to recovery. By situating Santa Fe’s experience within the broader context of the Royal Road, this research provides a nuanced understanding of the complex interplay between epidemics, social structures, and demographic change in colonial Latin America, offering valuable insights for contemporary public health strategies.
Numerical and Experimental Seismic Characterization of Byblos Site in Lebanon
Authors: Abou Jaoude Rita , Makhoul Nisrine , Gesret Alexandrine , Fleurisson Jean-Alain
Published: February 2025

Geological and topographic site effects lead to variations in the spatial distribution of ground motion during large earthquakes. Despite the impact of such phenomena, they remain poorly understood. There is a lack of joint studies of numerical predictions and experimental observations on the geomorphological site effects. Therefore, a comparison between well-constrained models and experimental field observations is needed. Byblos is a seismic region in Lebanon surrounded by faults that historically generated destructive earthquakes. Its geological and geomorphological settings are interestingly characterized by fractured rocks and anthropic deposits altering seismic ground motions. Field surveys in Byblos gathered ambient vibration recordings and surface waves. It identified multiple resonant frequency peaks, suggesting impedance contrasts and lateral variations in subsurface stiffness, using Horizontal-to-Vertical Spectral Ratio (HVSR) and directivity. It also revealed soft, shallow layers with low velocities, indicating potential resonance during earthquakes, using Multichannel Analysis of Surface Waves (MASW) and 2D seismic arrays. Thus, our study on Byblos is a first step for seismic microzoning of the area that evaluated its heterogeneous subsoil, soft surface layers, and anthropic deposits. Finally, combining geophysical data and field measurements with a numerical model allowed a better understanding of Byblos seismic hazards and enhanced its resilience and sustainability.
Cucurbita ficifolia Rootstock Enhances Resistance to Low-Temperature Stress in Cucumber
Authors: Xiao Haojun , Deng Wenxin , Ahmad Bilal , Guo Chunmei , Shi Songmei , He Shuilian , Yang Zheng’an
Published: February 2025

Cucumber cultivation suffers from severe yield and quality decline due to cold damage. Cucurbita ficifolia is used as a rootstock for grafting cucumber to improve resistance due to its excellent resistance. This study used Yunnan C. ficifolia as the rootstock and Jingyan Xiamei 2 cucumber as the scion, simulating common low-temperature stress of 15 °C, 10 °C, and 5 °C in an artificial climate chamber, to study the mechanism of cucumber-grafted seedlings responding to low temperatures in terms of growth and development, photosynthesis, osmotic regulation substances, antioxidant system, and gene expression. The results showed that the growth and development of grafted seedlings of C. ficifolia was less inhibited, the chlorophyll content was less reduced, and the content of osmoregulatory substances was significantly increased under low-temperature stress. The activity of antioxidant enzymes in grafted seedlings of C. ficifolia was significantly upregulated at low temperatures, and the expression of antioxidant enzyme genes was consistently higher in grafted seedlings of C. ficifolia. These results confirmed that C. ficifolia as a rootstock could improve the cold resistance of cucumber. Collectively, this study provides the basis for revealing the physiological and molecular mechanism of grafting seedlings to improve cucumber’s low temperature tolerance.
Influence of CYP2C8 Polymorphism on the Exposure to Chloroquine in Patients with Malaria by Plasmodium vivax—A Preliminary Study
Authors: Pereira de Sena Luann Wendel , Fuzii Hellen Thais , Villanova Fabiola Elizabeth , Nunes Cardoso Mello Amanda Gabryelle , de Sena Maria Pantoja Moreira , Dias Ferreira Michelle Valéria , Fernandes Vieira José Luiz
Published: February 2025

Aim: To assess the impact of the CYP2C82 polymorphism on chloroquine and desethylchloroquine concentrations in patients with malaria caused by P. vivax. Methods: A prospective study was conducted on patients with malaria in an endemic area of the Amazon basin. Liquid chromatography was employed to measure the levels of chloroquine and desethylchloroquine, while molecular methods estimated the frequency of the CYP2C82 variant. Results: This study revealed that plasma levels of chloroquine were higher in patients with the CYP2C82 polymorphism compared to those without this variant. The difference in plasma levels ranged from 5% to 26.5%. Conversely, patients with the CYP2C82 polymorphism exhibited lower levels of desethylchloroquine. Conclusion: The findings of this study confirm the impairment of chloroquine metabolism by the CYP2C82 variant. However, it is noteworthy that in the dose regimen used for malaria treatment, these changes did not lead to toxic concentrations of the drug.