bluuebunny/crossref_metadata_2025 huggingface dataset:
Study on the Thermodynamic–Kinetic Coupling Characteristics of Free-Piston Stirling Air Conditioning
Authors: Wang Yajuan , Zhao Kang , Zhang Jun’an
Published: November 2024

Unlike traditional free-piston Stirling heat engines or heat pumps, the free piston Stirling air conditioning (FPSAC) is specifically designed for electric vehicle air conditioning under ambient room temperature conditions. In the FPSAC system, the displacer and the power piston are coupled through gas forces, emphasizing the importance of investing the thermodynamic–kinetic coupling characteristics. This study analyzed the damping terms within the dynamic equations of the FPSAC model and solved these equations to reveal system dynamics. By linearizing the working chamber’s pressure, the study examined the machine’s dynamic behavior, presenting solutions for amplitude and phase angle. Derived expressions for the displacement and acceleration of both the power piston and the displacer further support this analysis. The research evaluates the influence of driving force on amplitude and phase angle, alongside the impact of damping coefficients, thereby isolating thermodynamic–dynamic coupling characteristics. Control equations integrating dynamics and thermodynamics were developed, and a comprehensive system model was constructed using MATLAB(2020a)/Simulink to simulate acceleration and displacement variation in the pistons. Key findings include: (1) a positive correlation between driving force and displacer, where increased force leads to higher amplitudes; (2) a frequency of 65 Hz reveals a singularity occurs in displacer amplitude, resulting in system instability; (3) phase angle between pistons reduces to below 10° when the driving force exceeds 150 N; and (4) the power piston’s amplitude decreases with an increase in damping C1, while changes in damping C2 primarily affect the displacer’s singularity position around 65 Hz, with higher C2 values shifting the singularity to lower frequencies.
Key Role and Optimization Dispatch Research of Technical Virtual Power Plants in the New Energy Era
Authors: Jin Weigang , Wang Peihua , Yuan Jiaxin
Published: November 2024

This comprehensive review examines the key role and optimization dispatch of Technical Virtual Power Plants (TVPPs) in the new energy era. This study provides an overview of Virtual Power Plants (VPPs), including their definition, development history, and classification into Technical and Commercial VPPs. It then systematically analyzes optimization methods for TVPPs from five aspects: deterministic optimization, stochastic optimization, robust optimization, and bidding-integrated optimization. For each method, this review presents its mathematical models and solution algorithms. This review highlights the significance of TVPPs in enhancing power system flexibility, improving renewable energy integration, and providing ancillary services. Through methodological classification and comparative analysis, this review aims to provide valuable insights for the design, operation, and management of TVPPs in future power systems.
The State of the Art Electricity Load and Price Forecasting for the Modern Wholesale Electricity Market
Authors: Laitsos Vasileios , Vontzos Georgios , Paraschoudis Paschalis , Tsampasis Eleftherios , Bargiotas Dimitrios , Tsoukalas Lefteri H.
Published: November 2024

In a modern and dynamic electricity market, ensuring reliable, sustainable and efficient electricity distribution is a pillar of primary importance for grid operation. The high penetration of renewable energy sources and the formation of competitive prices for utilities play a critical role in the wider economic development. Electricity load and price forecasting have been a key focus of researchers in the last decade due to the substantial economic implications for both producers, aggregators and end consumers. Many forecasting techniques and methods have emerged during this period. This paper conducts a extensive and analytical review of the prevailing load and electricity price forecasting methods in the context of the modern wholesale electricity market. The study is separated into seven main sections. The first section provides the key challenges and the main contributions of this study. The second section delves into the workings of the electricity market, providing a detailed analysis of the three markets that have evolved, their functions and the key factors influencing overall market dynamics. In the third section, the main methodologies of electricity load and price forecasting approaches are analyzed in detail. The fourth section offers a comprehensive review of the existing literature focusing on load forecasting, highlighting various methodologies, models and their applications in this field. This section emphasizes the advances that have been made in all categories of forecasting models and their practical application in different market scenarios. The fifth section focuses on electricity price forecasting studies, summarizing important research papers investigating various modeling approaches. The sixth section constitutes a fundamental discussion and comparison between the load- and price-focused studies that are analyzed. Finally, by examining both traditional and cutting-edge forecasting methods, this review identifies key trends, challenges and future directions in the field. Overall, this paper aims to provide an in-depth analysis leading to the understanding of the state-of-the-art models in load and price forecasting and to be an important resource for researchers and professionals in the energy industry. Based on the research conducted, there is an increasing trend in the use of artificial intelligence models in recent years, due to the flexibility and adaptability they offer for big datasets, compared to traditional models. The combination of models, such as ensemble methods, gives us very promising results.
Constraint Optimal Model-Based Disturbance Predictive and Rejection Control Method of a Parabolic Trough Solar Field
Authors: Wei Shangshang , Gao Xianhua , Li Yiguo
Published: November 2024

The control of the field outlet temperature of a parabolic trough solar field (PTSF) is crucial for the safe and efficient operation of the solar power system but with the difficulties arising from the multiple disturbances and constraints imposed on the variables. To this end, this paper proposes a constraint optimal model-based disturbance predictive and rejection control method with a disturbance prediction part. In this method, the steady-state target sequence is dynamically corrected in the presence of constraints, the lumped disturbance, and its future dynamics predicted by the least-squares support vector machine. In addition, a maximum controlled allowable set is constructed in real time to transform an infinite number of constraint inequalities into finite ones with the integration of the corrected steady-state target sequence. On this basis, an equivalent quadratic programming constrained optimization problem is constructed and solved by the dual-mode control law. The simulation results demonstrate the setpoint tracking and disturbance rejection performance of our design under the premise of constraint satisfaction.
An Assessment of the Bearing Capacity of High-Strength-Concrete-Filled Steel Tubular Columns Through Finite Element Analysis
Authors: Rossato Leonardo André , Rossi Alexandre , Martins Carlos Humberto , Gidrão Gustavo de Miranda Saleme , Silvestro Laura , Bosse Rúbia Mara
Published: November 2024

This work aimed to evaluate the accuracy of analytical models for predicting the behavior of concrete-filled steel tubular (CFST) columns via finite element analysis coupled with physical nonlinearity. The methodology involved an extensive review of experimental tests from the literature, numerical modeling of columns with different configurations, and a comparison of the results obtained with available experimental data. Several characteristics were evaluated, such as the load capacity, confinement factor, and relative slenderness. The numerical model agreed well with the experimental results, with a less than 10% relative error. The results indicated that analytical models of the Chinese (GB 50936) and European (EC4) codes overestimated some load capacity values (up to 14.9% and 8.7%, respectively). In comparison, the American (AISC 360) and Brazilian (NBR 8800) standards underestimated the ultimate loads (23.3% and 31.6%, respectively). An approach coefficient β is proposed, contributing to safer and more efficient design practices in structural engineering.
Economic Values for Coral Reef Conservation and Restoration in Florida
Authors: Wallmo Kristy , Allen Mary E.
Published: November 2024

Florida’s coral reef is the third-largest barrier reef system in the world and provides valuable ecosystem services, such as recreation and tourism, erosion protection, and other services. Florida’s reefs have been declining due to impacts from climate change, pollution, and other pressures. In response, various conservation strategies have been implemented, including education and outreach, growing corals in nurseries and transplanting them to degraded reef sites, and deploying artificial reefs. However, few studies have estimated an explicit value for different strategies to attain conservation goals. Understanding economic values for reef restoration and enhancement is needed to help inform decision-making and support marine policy. This study conducted a stated preference choice experiment survey to examine the way U.S. residents make economic trade-offs among different restoration strategies, including increasing coral cover, deploying artificial reefs, and limiting visitor access to reef sites. The results suggest that, on average, the economic value of increasing coral cover is about twice as high as the value of increasing the number of artificial reef sites. Economic values for reducing visitation were similar to values for increasing the number of artificial reefs. These results provide essential information to policy analysts concerning reef use, reef importance, and economic values for reef restoration.
Net Forest Carbon Loss Induced by Forest Cover Change and Compound Drought and Heat Events in Two Regions of China
Authors: Gu Chenfeng , Wang Tongyu , Shen Wenjuan , Tai Zhiguo , Su Xiaokun , He Jiaying , He Tao , Gong Weishu , Huang Chengquan
Published: November 2024

Compound drought and heat events (CDHEs) and forest cover change influence regional forest carbon dynamics. Changes in regional vegetation biomass and soil carbon storage induced by forest cover change often exhibit considerable uncertainty, and previous research on the impacts of CDHEs on forest carbon dynamics is limited. To accurately quantify the specific effects of forest cover change and CDHEs on forest carbon dynamics in different regions, we employed a combined algorithm of the Carnegie–Ames–Stanford Approach (CASA) and bookkeeping empirical models to examine the impact of regional forest cover changes on forest carbon dynamics during 2000–2022 in Nanjing and Shaoguan, Southern China. Using the Geographical Detector model, we then analyzed the effects of CDHEs on forest carbon dynamics. Next, we used the photosynthesis equation and the optimal response time of forests to drought (heat) events to calculate the changes in forest carbon sequestration caused by CDHEs in both regions during 2000–2022. The results indicated that afforestation and deforestation led to +0.269 TgC and +1.509 TgC of carbon sequestration and 0.491 TgC and 2.802 TgC of carbon emissions in Nanjing and Shaoguan, respectively. The overall effects of CDHEs on the change in forest carbon sequestration were manifested as net carbon loss. In Nanjing, the net carbon loss caused by CDHEs (0.186 TgC) was lower than the loss due to forest cover change (0.222 TgC). In Shaoguan, the net forest carbon loss caused by CDHEs (3.219 TgC) was much more significant than that caused by forest cover change (1.293 TgC). This study demonstrated that forest carbon dynamics are dominated by different factors in different regions, which provides a scientific basis for local governments to formulate targeted forest management policies.
Fault Prediction and Reconfiguration Optimization in Smart Grids: AI-Driven Approach
Authors: Carrascal David , Bartolomé Paula , Rojas Elisa , Lopez-Pajares Diego , Manso Nicolas , Diaz-Fuentes Javier
Published: November 2024

Smart grids (SGs) are essential for the efficient and distributed management of electrical distribution networks. A key task in SG management is fault detection and subsequently, network reconfiguration to minimize power losses and balance loads. This process should minimize power losses while optimizing distribution by balancing loads across the grid. However, the current literature yields a lack of methods for efficient fault prediction and fast reconfiguration. To achieve this goal, this paper builds on DEN2DE, an adaptable routing and reconfiguration solution potentially applicable to SGs, and investigates its potential extension with AI-based fault prediction using real-world datasets and randomly generated topologies based on the IEEE 123 Node Test Feeder. The study applies models based on Machine Learning (ML) and Deep Learning (DL) techniques, specifically evaluating Random Forest (RF) and Support Vector Machine (SVM) as ML methods, and Artificial Neural Network (ANN) as a DL method, evaluating each for accuracy, precision, and recall. Results indicate that the RF model with Recursive Feature Elimination (RFECV) achieves 94.28% precision and 81.05% recall, surpassing SVM (precision 89.32%, recall 6.95%) and ANN (precision 72.17%, recall 13.49%) in fault detection accuracy and reliability.
Optimizing Fire Scene Analysis: Hybrid Convolutional Neural Network Model Leveraging Multiscale Feature and Attention Mechanisms
Authors: Muksimova Shakhnoza , Umirzakova Sabina , Abdullaev Mirjamol , Cho Young-Im
Published: November 2024

The rapid and accurate detection of fire scenes in various environments is crucial for effective disaster management and mitigation. Fire scene classification is a critical aspect of modern fire detection systems that directly affects public safety and property preservation. This research introduced a novel hybrid deep learning model designed to enhance the accuracy and efficiency of fire scene classification across diverse environments. The proposed model integrates advanced convolutional neural networks with multiscale feature extraction, attention mechanisms, and ensemble learning to achieve superior performance in real-time fire detection. By leveraging the strengths of pre-trained networks such as ResNet50, VGG16, and EfficientNet-B3, the model captures detailed features at multiple scales, ensuring robust detection capabilities. Including spatial and channel attention mechanisms further refines the focus on critical areas within the input images, reducing false positives and improving detection precision. Extensive experiments on a comprehensive dataset encompassing wildfires, building fires, vehicle fires, and non-fire scenes demonstrate that the proposed framework outperforms existing cutting-edge techniques. The model also exhibited reduced computational complexity and enhanced inference speed, making it suitable for deployment in real-time applications on various hardware platforms. This study sets a new benchmark for fire detection and offers a powerful tool for early warning systems and emergency response initiatives.
Development of Single-Nucleotide Polymorphism (SNP)-Based Species-Specific Real-Time PCR Assays for Authenticating Five Highly Priced Tuna
Authors: Qu Meng , Jiang Yanhua , Li Na , Guo Yingying , Zhu Wenjia , Li Na , Zhao Xinnan , Yao Lin , Wang Lianzhu
Published: November 2024

Tuna are economically important as food resources in food markets. However, because tuna is often processed into steaks or fillets, the meat can be difficult to identify through morphological features. For effective fishery management and to protect the rights of consumers, it is necessary to develop a molecular method to accurately identify the species used in tuna products. Herein, we discovered five single-nucleotide polymorphism (SNP) sites via 2b-RAD sequencing and developed five SNP-based real-time polymerase chain reaction assays for the rapid identification of five highly priced tuna species. Three species-specific TaqMan systems were designed to identify albacore tuna (Thunnus alalunga), bigeye tuna (T. obesus), and southern bluefin tuna (T. maccoyii) and two cycling systems were designed to identify yellowfin tuna (T. albacares) and Atlantic bluefin tuna (T. thynnus). The systems showed good specificity and sensitivity (sensitivity of 0.0002 ng μL−1 for albacore tuna, bigeye tuna, and southern bluefin tuna and 0.002 ng μL−1 for yellowfin tuna and Atlantic bluefin tuna). Both systems were able to distinguish the target species from other species in a specific, sensitive, and accurate manner. Thus, these methods can be employed for the identification of species used in tuna products, protecting consumers and producers from economic fraud.
Food Public Opinion Prevention and Control Model Based on Sentiment Analysis
Authors: Chen Leiyang , Peng Xiangzhen , Dong Liang , Wang Zhenyu , Shen Zhidong , Cui Xiaohui
Published: November 2024

Food public opinion is characterized by its low ignition point, high diffusibility, persistence, and strong negativity, which significantly impact food safety and consumer trust. This paper introduces the Food Public Opinion Prevention and Control (FPOPC) model driven by deep learning and personalized recommendation algorithms, rigorously tested and analyzed through experimentation. Initially, based on an analysis of food public opinion development, a comprehensive FPOPC framework addressing all stages of food public opinion was established. Subsequently, a sentiment prediction model for food news based on user comments was developed using a Stacked Autoencoder (SAE), enabling predictions about consumer sentiments toward food news. The sentiment values of the food news were then quantified, and improvements were made in allocating Pearson correlation coefficient weights, leading to the design of a collaborative filtering-based personalized food news recommendation mechanism. Furthermore, an enhanced Bloom filter integrated with HDFS technology devised a rapid recommendation mechanism for food public opinion. Finally, the designed FPOPC model and its associated mechanisms were validated through experimental verification and simulation analysis. The results demonstrate that the FPOPC model can accurately predict and control the development of food public opinion and the entire food supply chain, providing regulatory agencies with effective tools for managing food public sentiment.
Widely Targeted Metabolomics Reveal the Distribution of Metabolites in Shatian Pomelo Fruit
Authors: Wen Jing , Liu Haocheng , Lai Huining , Xu Yujuan , Wu Jijun , Yu Yuanshan , Huang Wenqian , Fu Manqin , Liu Haiyang
Published: November 2024

Using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) technology in multiple reaction monitoring mode, a widely targeted metabolomics approach was employed to identify metabolites in five tissues (exocarp, endocarp, segment membrane, pulp, and seeds) of the Shatian pomelo fruit. The differences in metabolite composition and abundance among different tissues were analyzed using multivariate statistical analysis methods. The results showed that a total of 1722 metabolites were identified from the five tissues of the Shatian pomelo, including 413 flavonoids and 277 amino acids and their derivatives. Flavonoid metabolites accumulate the most abundantly in the exocarp and seeds, while amino acids and their derivatives are primarily accumulated in the exocarp and pulp. A total of 649 key differential metabolites were screened, including flavonoids, amino acids, and their derivatives, indicating the presence of tissue-specific accumulation of metabolites in the Shatian pomelo. This study systematically investigated the metabolite distribution in different tissue parts of the Shatian pomelo, and validated the feasibility of widely targeted metabolomics technology in pomelo quality analysis. It provided a theoretical reference for metabolic research on the Shatian pomelo and other citrus fruits, and offered a theoretical basis for the efficient utilization of pomelo resources.
Alteration of the Morphological and Physicochemical Characteristics of Corn and Wheat Starch via Dry Heating with Whey Protein Isolates
Authors: Adal Eda , Aktar Tugba , Keskin Çavdar Hasene
Published: November 2024

This study investigated the impact of whey protein isolate (WPI) addition on the dry heat modification of corn (CS) and wheat starch (WS). Starches were treated under dry heating conditions at 130 °C for 2 and 4 h. The physicochemical and structural properties of the modified starches, such as color, particle size, thermal behavior (DSC), crystalline structure (XRD), and surface morphology (SEM), were analyzed. The results show that adding WPI significantly altered the gelatinization properties, surface morphology, and crystalline structure of both starches. DSC indicated that the gelatinization properties of starch/WPI mixtures varied, with corn starch showing a decreased gelatinization temperature and increased enthalpy, whereas wheat starch exhibited a more complex response, likely due to different structural changes. The XRD and FTIR results revealed WPI-enhanced crystallinity and structural changes, highlighting WPI-induced aggregation. Wheat starch, in particular, exhibited stronger interactions with WPI than corn starch, as evidenced by the accumulation patterns in the SEM images. The oil-binding capacity of native starches increased with dry heating and WPI addition, suggesting an improved hydrophobicity of starch granules. Dry heating and WPI addition significantly altered starch properties, highlighting the potential of thermal modulation to enhance starch–protein systems for targeted food applications.
Enzymatic Oxidation of Aflatoxin M1 in Milk Using CotA Laccase
Authors: Guo Yongpeng , Lv Hao , Rao Zhiyong , Wang Zhixiang , Zhang Wei , Tang Yu , Zhao Lihong
Published: November 2024

Aflatoxin M1 (AFM1) in milk poses a significant threat to human health. This study examined the capacity of Bacillus licheniformis CotA laccase to oxidize AFM1. The optimal conditions for the CotA laccase-catalyzed AFM1 oxidation were observed at pH 8.0 and 70 °C, achieving an AFM1 oxidation rate of 86% in 30 min. The Km and Vmax values for CotA laccase with respect to AFM1 were 18.91 μg mL−1 and 9.968 μg min−1 mg−1, respectively. Computational analysis suggested that AFM1 interacted with CotA laccase via hydrogen bonding and van der Waals interactions. Moreover, the oxidation products of AFM1 mediated by CotA laccase were identified as the C3-hydroxy derivatives of AFM1 by HPLC-FLD and UPLC-TOF/MS. Toxicological assessment revealed that the hepatotoxicity of AFM1 was substantially reduced following oxidation by CotA laccase. The efficacy of CotA laccase in removing AFM1 in milk was further tested, and the result showed that the enzyme agent achieved an AFM1 removal rate of 83.5% in skim milk and 65.1% in whole milk. These findings suggested that CotA laccase was a novel AFM1 oxidase capable of eliminating AFM1 in milk. More effort is still needed to improve the AFM1 oxidase activity of CotA laccase in order to shorten the processing time when applying the enzyme in the milk industry.
Effect of Inulin and Psyllium Husk Powder on Gel Properties and In Vitro Digestion of Hypophthalmichthys molitrix and Argopecten irradians Blended Surimi
Authors: Geng Wenhao , Tian Miaomiao , Zhang Xinyue , Song Maodong , Fan Xinru , Li Meng , Ma Yongsheng , Benjakul Soottawat , Zhao Qiancheng
Published: November 2024

Dietary fiber is crucial in enhancing the nutritional and textural properties of surimi-based products. This study investigated blended surimi produced from silver carp and bay scallops, with the addition of different amounts (0%, 0.5%, 1%, 2%, and 3%) of inulin (INU) or psyllium husk powder (PHP) for their textural properties, protein conformation, and in vitro digestibility. The addition of INU negatively affected gel strength. However, incorporating 2.0% PHP into the blended gel improved gel strength and water-holding capacity by 8.01% and 0.79% compared to the control, respectively. Furthermore, PHP significantly increased the total sulfhydryl content and surface hydrophobicity of the blended gels (p < 0.05). Additionally, increases in endogenous fluorescence intensity accompanied by a blue shift were observed, indicating that the fluorophores (Trp and Tyr) were sequestered into a more non-polar environment due to conformational changes. The incorporation of PHP enhanced both the quality and digestibility of the blended surimi. This study provides a novel perspective for developing surimi-based food with improved quality, augmented digestion, and enhanced absorption.
Effect of Brassica rapa L. Polysaccharide on Lewis Lung Cancer Mice by Inflammatory Regulation and Gut Microbiota Modulation
Authors: Du Changhui , Zhao Yong , Shen Fanglin , Qian He
Published: November 2024

Lung cancer is the leading cause of cancer-related fatalities globally, related to inflammatory and gut microbiota imbalance. Brassica rapa L. polysaccharide (BP) is a functional compound, which is utilized by the gut microbiota to regulate immunity and metabolism. However, the effect of BP on lung cancer and whether it affects the “gut–lung” axis remains unclear. This study explored the intervention of BP in Lewis lung cancer (LLC) mice and its effect on the gut microbiota. The results revealed that BP reduced tumor weight and downregulated the expression of Ki67 protein. Additionally, BP reduced the content of inflammatory factors and growth factors, promoting tumor cell apoptosis and inhibiting the growth of LLC. The intervention of BP suppressed intestinal inflammation, preserved intestinal barrier integrity, and augmented the level of beneficial microbiota, such as Blautia and Bifidobacterium. Furthermore, BP significantly increased the production of short-chain fatty acids (SCFAs), particularly butyrate and propionate. A correlation analysis showed significant correlations among the gut microbiota, SCFAs, inflammatory factors, and tight junction proteins. A functional analysis indicated that BP promoted amino acid metabolism and fatty acid metabolism. These findings suggested that BP had the potential to act as prebiotics to prevent disease and improve lung cancer progression by regulating the gut microbiota.
Microbiological and Physicochemical Profile of Traditionally Produced Chouriça de Carne Dry-Fermented Sausages: Towards Benchmarking of Products Against Established Quality Groups
Authors: Faria Ana Sofia , Bonilla-Luque Olga María , Carvalho Laís , Fernandes Nathália , Prieto Miguel Angel , Cadavez Vasco , Gonzales-Barron Ursula
Published: November 2024

The physicochemical and microbiological properties of traditional Portuguese ready-to-eat dry fermented sausage chouriça de carne samples from 14 regional producers were analysed and subjected to multivariate analysis to determine the relationships between them and to evaluate how the quality and safety of these sausages is affected by these properties. Producer-mean values for physicochemical analyses were quite variable, with intervals of 4.87–6.11 for pH, 0.803–0.965 for aw, moisture 19.5–48.5%, protein 32.0–60.1% (db), fat 22.0–53.3% (db), ash 3.52–9.69% (db), and carbohydrates 1.66–13.5% (db). Mesophilic counts varied (5.61–8.68 log CFU/g), while lactic acid bacteria were generally high (MRS: 8.21–10.2; M17: 7.66–10.0 log CFU/g). S. aureus was enumerated in levels up to 2.55 log CFU/g, while presumptive C. perfringens never surpassed 2 log CFU/g. Salmonella spp. and Listeria spp. were also detected in the samples tested. Principal component (PC) analysis yielded a three-dimension solution that explained 60% of the data variation; PC1 (26%) characterized chorizo formulations with more meat, while PC2 (19.3%) described sausages with longer/rapid fermentation, and PC3 (14.5%) highlighted chouriços with poorer hygiene. Cluster analysis identified three quality groups: (i) chorizos with high moisture, high protein content, and lowest pH; (ii) sausages with low moisture, high fat content, and elevated pH; and (iii) chouriças with high moisture and high protein but lower fat contents, low pH, and improved hygiene. Lastly, factor analysis yielded a varimax-rotated three-factor solution that explained 65% of the data, with similar results to PCA; factor 1 (23.5%) depicted chorizos with low pH but high moisture, factor 2 (20.8%) described sausages with more meat in the formulation, and factor 3 (20.6%) longer or rapid fermentation. Overall, the results evidenced the great variability in the quality attributes of Portuguese chorizo sausages, very likely to arise from multiple recipes, ingredients, and manufacturing practices. The definition of quality clusters is expected to play a crucial role for the self-denominated “artisanal” food companies to benchmark their chouriço sausages against the proper artisanal quality group.
High-Energy Fluidic Microfluidizer Produced Whole Germinant Oat Milk: Effects on Physical Properties and Nutritional Quality
Authors: Wei Qimin , Chen Jun , Dai Taotao , Ma Feiyue , Deng Lizhen , Ke Yingying , Wang Yihui , Guo Laichun , Wang Chunlong , Zhan Chao , Ren Changzhong , Li Ti
Published: November 2024

Whole oat milk (WOM) was prepared from germinated oat by an innovatively designed high-energy fluidic microfluidizer (HEFM). The results indicated that germination treatment significantly raised the content of total protein, γ-aminobutyric acid, total phenolics, and reducing sugar, while it decreased the content of total starch and β-glucan. Oat with a germination time of 48 h had the best nutritional quality for producing WOM. The physical stability of the WOM prepared from germinated oat was effectively improved by HEFM treatment. The apparent viscosity increased, the instability index reduced from 0.67 to 0.37, and the precipitate weight ratio decreased from 13.54% to 9.51%. As the pressure of the HEFM increased from 0 to 120 MPa, the particle size decreased from 169.5 to 77.0 µm, which was helpful to improve the physical stability of the WOM. Meanwhile, the color of the WOM became whiter after the HEFM treatment. The content of β-glucan and soluble protein in the WOM significantly increased, which was due to the disruption of cells by the HEFM processing. The optimal HEFM pressure for WOM production is 120 MPa. This study provided a new way to produce whole oat milk with a high nutritional quality and good physical properties.
The Impact of Mechanized and Traditional Processes on Microbial Diversity and Volatile Flavor Compound Formation During Xifeng Baijiu Fermentation
Authors: Jin Chengyong , Jin Guangyuan , Jin Juan , Lv Yutao , Dang Zhe , Feng Yafang , Xu Yan
Published: November 2024

The impact of mechanized processes on the properties of Xifeng Baijiu, as well as the differences between Baijiu produced through mechanized versus traditional methods, remains insufficiently understood. In this study, the differences in physicochemical properties, microorganisms, volatile flavor compounds, and their correlations in the traditional and mechanized processes of producing Xifeng Baijiu were compared. High-throughput sequencing revealed that the abundance and diversity of bacteria and fungi were higher in the traditional process compared to the mechanized one. The bacterial population exhibited a more pronounced succession pattern than the fungal population throughout the fermentation. In the early stages, Firmicutes and Actinobacteria were the dominant bacterial phyla in both processes, with Lactobacillus, Saccharopolyspora, Bacillus, Acetobacter, Weissella, and Thermoactinomyces being the predominant bacterial genera, and Saccharomycopsis, Issatchenkia, Kazachstania, Thermoascus, Pichia, and Rhizopus are the dominant fungi. Chemical analysis identified 71 volatile flavor components in the fermented grains, predominantly esters and alcohols. Ethyl caproate, 1-nonyl alcohol, ethyl acetate, acetic acid, butyric acid, furfuryl alcohol, caproic acid, and 2,4-di-tert-butylphenol were the key differential compounds between the two production methods. Pearson correlation analysis indicated a stronger relationship between bacteria and flavor compounds than between fungi and these substances, with Lactobacillus showing a negative correlation with other dominant bacterial genera. These findings offer a foundation for future research into the factors contributing to differences in Baijiu produced by traditional and mechanized methods and serve as a reference for improving mechanized processes.
Approximate Solution of a Kind of Time-Fractional Evolution Equations Based on Fast L1 Formula and Barycentric Lagrange Interpolation
Authors: Liu Ting , Liu Hongyan , Ma Yanying
Published: November 2024

In this paper, an effective numerical approach that combines the fast L1 formula and barycentric Lagrange interpolation is proposed for solving a kind of time-fractional evolution equations. This type of equation contains a nonlocal term involving the time variable, resulting in extremely high computational complexity of numerical discrete formats in general. To reduce the computational burden, the fast L1 technique based on the L1 formula and sum-of-exponentials approximation is employed to evaluate the Caputo time-fractional derivative. Meanwhile, a fast and unconditionally stable time semi-discrete format is obtained. Subsequently, we utilize the barycentric Lagrange interpolation and its differential matrices to achieve spatial discretizations so as to deduce fully discrete formats. Then error estimates of related fully discrete formats are explored. Eventually, some numerical experiments are simulated to testify to the effective and fast behavior of the presented method.
Systematic Analysis of Commuting Behavior in Italy Using K-Means Clustering and Spatial Analysis: Towards Inclusive and Sustainable Urban Transport Solutions
Authors: Babapourdijojin Mahnaz , Corazza Maria Vittoria , Gentile Guido
Published: November 2024

Transport Demand Management (TDM) is crucial in shaping travel behavior and enhancing urban mobility by promoting sustainable transport options. This study represents a comprehensive analysis of employee commuting behavior across seventy-seven cities in Italy, with a focus on Rome as a case study. It investigates some requirements of the workplace travel plan as a TDM strategy for promoting sustainable commuting. An online survey conducted in June 2022 yielded 2314 valid responses, including 1320 from private car drivers. K-means clustering was used to identify distinct behavioral patterns among commuters, revealing four clusters based on demographic factors and transport preferences, such as age, gender, family circumstances, vehicle ownership, willingness to walk, ride bicycles, or e-scooters, and reasons for mode choice. This study analyzed Rome’s public transport network, land use, and private car use. Results underscore the need for tailored transport policies that enhance inclusivity and accessibility, especially for employees with family members who cannot commute independently. A spatial analysis of Rome reveals significant infrastructure deficiencies, such as complicated transfers and inaccessible stations, which discourage PT use. Future research should explore the impact of remote work and psychological factors and conduct in-depth subgroup analyses to inform inclusive transport policy development.
TOrsion-Bar Antenna: A Ground-Based Detector for Low-Frequency Gravity Gradient Measurement
Authors: Takano Satoru , Shimoda Tomofumi , Oshima Yuka , Ooi Ching Pin , Forsyth Perry William Fox , Cao Mengdi , Komori Kentaro , Michimura Yuta , Sugimoto Ryosuke , Kame Nobuki , Watada Shingo , Yokozawa Takaaki , Miyoki Shinji , Washimi Tatsuki , Ando Masaki
Published: November 2024

The Torsion-Bar Antenna (TOBA) is a torsion pendulum-based gravitational detector developed to observe gravitational waves in frequencies between 1 mHz and 10 Hz. The low resonant frequency of the torsion pendulum enables observation in this frequency band on the ground. The final target of TOBA is to observe gravitational waves with a 10 m detector and expand the observation band of gravitational waves. In this paper, an overview of TOBA, including the previous prototype experiments and the current ongoing development, is presented.
Low-Grade Appendiceal Mucinous Neoplasm vs. Appendiceal Diverticulum: Distinction with Histomorphologic Features
Authors: Ersöz Cevriye Cansiz , Ersöz Siyar , Savas Berna , Ensari Arzu
Published: November 2024

Background: Low-grade appendiceal mucinous neoplasms (LAMNs) are rare lesions of the vermiform appendix and characterized by mucinous epithelial proliferation, extracellular mucin, and the absence of destructive invasion. Appendiceal diverticulum (AD) is also an uncommon condition that may be challenging to differentiate from acute appendicitis when it is superimposed by diverticulitis or perforation. Some recently published studies emphasized that complicated AD with mucosal hyperplasia can be confused with LAMNs, leading to overdiagnosis. The present study aimed to determine the histopathological features which can be used in the differential diagnosis of LAMNs and ADs, particularly complicated diverticula, in a large cohort. Methods: Cases comprising LAMNs and ADs diagnosed between 2011 and 2021 were included in the study. All cases were evaluated for the epithelial lining, the wall of the lesions, and the presence of cellular or acellular mucin, with its localization in terms of level and site of involvement within the appendix also recorded. Results: The hypermucinous epithelium characteristic of LAMNs, fibrosis, and calcification in the wall and the absence of lamina propria and muscularis mucosa proved to be the most discriminatory features in the differential diagnosis of LAMNs and ADs. Conclusions: The distinction between mucinous neoplasia and its mimics is critically important, since mucinous neoplasia requires surveillance imaging and potential surgery or chemotherapy depending on the extent of the disease, whereas non-neoplastic lesions are treated by an appendectomy and require no future intervention or surveillance.
Assessing Knowledge, Practices, and Barriers to PrEP and nPEP Prescription Among Texas Healthcare Providers
Authors: Tiruneh Yordanos M. , Rachmale Ruchi , Elerian Nagla , Lakey David L.
Published: November 2024

Background: The effectiveness of pre-exposure prophylaxis (PrEP) and non-occupational post-exposure prophylaxis (nPEP) in preventing HIV is well-established, yet their use in clinical practice remains low. Healthcare providers, especially those in primary and emergency care settings, play a crucial role in adopting and implementing these prevention strategies. We conducted a statewide survey with 519 healthcare providers in Texas to assess their knowledge, practices, and barriers related to prescribing PrEP and nPEP. Methods: The survey collected data on demographics, clinical experience, practice type, awareness of recommended guidelines, knowledge of PrEP and nPEP, prescribing practices, and challenges encountered to prescribe these medications. We used multiple regression analysis to identify factors associated with PrEP and nPEP prescribing behavior. Results: While most providers were familiar with CDC and/or USPSTF-recommended PrEP guidelines, fewer had adequate knowledge of nPEP. Key challenges identified by providers included concerns about cost (48%), limited time (40% for PrEP and 51% for nPEP), and insufficient education or training (40% for PrEP and 35% for nPEP). Providers who were more familiar with the recommended guidelines and had greater experience in sexual health assessment were more likely to prescribe both PrEP and nPEP. Conclusions: This study highlights the need for enhanced education and training to boost providers’ knowledge and confidence in prescribing PrEP and nPEP. It also underscores the importance of addressing cost-related barriers and simplifying care processes to better integrate these HIV prevention strategies into primary and emergency care settings.
A Multicenter Survey on Pharmacists’ Perspectives on Self-Medication Issues in Romania: A Descriptive Study Towards Sustainable and Safe Pharmaceutical Practices
Authors: Gheorman Victor , Mărcău Flavius Cristian , Peptan Cătălin , Gheorman Veronica , Cojoaca Marian Emanuel , Musetescu Alina Magdalena , Daniela Mitutoiu , Militaru Felicia
Published: November 2024

Background/Objectives: This study evaluates the perceptions of pharmacists in Romania regarding self-medication, a growing practice with significant implications for public health and sustainable development. The main objective is to analyze the role of pharmacists in managing self-medication and educating the public on rational medication use. Methods: A descriptive and exploratory methodology was employed, using a questionnaire administered to 300 pharmacists from various regions in Romania between March and April 2024. The data analysis included Chi-square tests and linear regression to identify predictive factors. Results: The findings reveal a direct correlation between the frequency of self-medication and the perceived severity of conditions, with self-medication being more common for minor ailments. Experienced pharmacists are less likely to encourage self-medication. Public education on the risks of self-medication significantly reduces the prevalence of this practice. Conclusions: Self-medication, without proper regulation and education, risks becoming unsustainable. Targeted informational campaigns and educational programs tailored to diverse demographic groups are essential. Pharmacists play a critical role in promoting safe and responsible medication use.
Use of the Consumer Health Literacy Quotient to Quantify and Explore Self-Care Readiness Among Consumers in Four Asia-Pacific Countries
Authors: Garg Vandana , Alcasid Zee , Mendoza Katherine , Lee Heesoo , Loo Yi Xin , Nong Andy , Toh Gerard W. , Tan Sheryl
Published: November 2024

Background/Objectives: Self-care has great potential to benefit consumers and health systems, but its mainstream adoption is hindered by a systemic lack of consumer health literacy (HL). Published data on consumer awareness of self-care and HL are limited for regions in Asia, and are needed to develop interventions to enhance HL and self-care for diverse populations in this region. The aim of this research was to describe and analyze patterns of HL and awareness of self-care among consumers in Asia. Methods: We conducted a mixed-methods study comprising qualitative focus group discussions (FGDs; 64 participants) followed by a quantitative online survey (1200 participants) among consumers in four Asian countries (India, Philippines, Malaysia, and Republic of Korea). We examined five dimensions of HL and self-care relevant to consumers: actively managing health; confidence/skills to find and access health information; confidence/skills to appraise information; support from social circle; and support from healthcare providers. From the quantitative survey, responses for 16 questions covering the five dimensions were used to calculate the Consumer Health Literacy Quotient (CHLQ; normalized range 0–100), an index we developed to assess HL in the context of personal wellness and self-treatable conditions. Latent class analysis (LCA) was applied to identify distinctive patterns of consumer HL within the sample. Results: The mean CHLQ was 75 out of 100 (SD ± 12.9), indicating ‘moderate’ levels of consumer HL across the countries. LCA identified five distinct consumer HL profiles, differing in their average CHLQ (overall score) and along the CHLQ dimensions. Consistent with CHLQ results, the profiles differed in their response patterns for common self-manageable ailments. Conclusions: This study identified distinct patterns of HL and awareness of self-care among consumers in four Asian countries through combined use of the CHLQ and quantitative profiling. This offers a promising approach for understanding self-care-related HL among consumers in Asia. Our findings on patterns of strengths and weakness in specific dimensions of HL and self-care in diverse populations can inform research, communications, and targeted interventions to empower consumers and foster self-care.
Development of a Machine Learning Natural Ventilation Rate Model by Studying the Wind Field Inside and Around Multiple-Row Chinese Solar Greenhouses
Authors: Liu Ran , Shi Yunyan , Bournet Pierre-Emmanuel , Liu Kaige
Published: November 2024

This paper experimented with a methodology of machine learning modelling using virtual samples generated by fast CFD (Computational Fluid Dynamics) simulations in order to predict the greenhouse natural ventilation. However, the output natural ventilation rates using fast two-dimensional (2D) CFD models are not always consistent with the three-dimensional (3D) one for all the scenarios. The first contribution of this paper is a proposed comparative modelling methodology between two-dimensional and three-dimensional CFD studies, regarding its validity, especially when buildings are in rows. The results show that the error of the ventilation rate prediction could exceed 50%, if 2D models are not properly used. Subsequently, in those scenarios where the 2D and the 3D models had equal accuracy, nearly one thousand samples were generated using fast 2D CFD simulations to train a natural ventilation rate regression tree model. This model is efficient to deal with the combined effect of wind pressure and thermal gradients under various vent configurations, with only four necessary inputs. In addition, by analyzing the wind speed distribution contour of the outdoor wind field around the greenhouse rows, the optimal wind speed-measuring locations were determined to eliminate interference for predicting the natural ventilation rate.
Genome-Wide Identification of AGO, DCL, and RDR Genes and Their Expression Analysis in Response to Drought Stress in Peach
Authors: Belal Mohammad , Ntini Charmaine , Sylvia Cherono , Wassie Misganaw , Magdy Mahmoud , Ogutu Collins , Ezzat Mohamed , Mollah Md Dulal Ali , Cao Yunpeng , Zhang Weihan , Nishawy Elsayed , Han Yuepeng
Published: November 2024

Small RNAs (sRNAs) control a wide range of development and physiological pathways in plants. To address the response of sRNA biogenesis to drought stress, we identified sRNA biogenesis genes, including 11 encoding argonautes (AGO), 8 encoding Dicer-like proteins (DCL), and 9 encoding RNA-dependent RNA polymerases (RDR) in the peach genome. Notably, the largest numbers of sRNA biogenesis genes are located to chromosome 1. The PAZ, PIWI, and MID domains were identified in PpAGOs, while the ribonuclease IIIa and IIIb domains were characterized in PpDCLs. The RDRP domain was recognized in PpRDRs. Orthologous similarity and collinearity analyses between Arabidopsis and peach revealed 5, 1, and 2 collinear blocks in AGOs, DCLs, and RDRs, respectively. Moreover, 41, 40, and 42 cis-acting elements were located in the promoters of PpAGOs, PpDCLs, and PpRDRs, respectively, with the majority related to drought stress response. Analysis of RNA sequencing (RNA-seq) data revealed that sRNA biogenesis genes were involved in drought stress response in different tissues. Furthermore, the expression of candidate genes was verified in two peach cultivars, Beijing 2-7 (BJ2-7) and Sinai (SN), which are tested as drought-tolerant and sensitive cultivars, respectively, based on the physiological and biochemical analyses, which revealed that the Chinese peach cultivar ‘BJ2-7’ exhibits greater drought resistance compared to the Egyptian peach cultivar ‘SN’. Interestingly, the expression of PpAGO2b, PpDCL2b, PpDCL4, and PpRDR4 genes was induced in ‘BJ2-7’ but inhibited in ‘SN’ under drought stress. Overall, this study provides insight into the roles of sRNA biogenesis genes in response to drought stress in peach.