bluuebunny/crossref_metadata_2025 huggingface dataset:
Machine Learning-Based Intrusion Detection for Rare-Class Network Attacks
Authors: Yang Yu , Gu Yuheng , Yan Yu
Published: September 2023

Due to the severe imbalance in the quantities of normal samples and attack samples, as well as among different types of attack samples, intrusion detection systems suffer from low detection rates for rare-class attack data. In this paper, we propose a geometric synthetic minority oversampling technique based on the optimized kernel density estimation algorithm. This method can generate diverse rare-class attack data by learning the distribution of rare-class attack data while maintaining similarity with the original sample features. Meanwhile, the balanced data is input to a feature extraction module built upon multiple denoising autoencoders, reducing information redundancy in high-dimensional data and improving the detection performance for unknown attacks. Subsequently, a soft-voting ensemble learning technique is utilized for multi-class anomaly detection on the balanced and dimensionally reduced data. Finally, an intrusion detection system is constructed based on data preprocessing, imbalance handling, feature extraction, and anomaly detection modules. The performance of the system was evaluated using two datasets, NSL-KDD and N-BaIoT, achieving 86.39% and 99.94% multiclassification accuracy, respectively. Through ablation experiments and comparison with the baseline model, it is found that the inherent limitations of a single machine-learning model directly affect the accuracy of the intrusion detection system, while the superiority of the proposed multi-module model in detecting unknown attacks and rare classes of attack traffic is demonstrated.
Topologies and Design Characteristics of Isolated High Step-Up DC–DC Converters for Photovoltaic Systems
Authors: Meshael Hazem , Elkhateb Ahmad , Best Robert
Published: September 2023

This paper aims to investigate the state-of-the-art isolated high-step-up DC–DC topologies developed for photovoltaic (PV) systems. This study categorises the topologies into transformer-based and coupled inductor-based converters, as well as compares them in terms of various parameters such as component count, cost, voltage conversion ratio, efficiency, voltage stress, input current ripple, switching mode, and power rating. The majority of the topologies examined exhibit peak efficiencies of 90% to 97%, with voltage conversions in excess of eight, as well as power ratings ranging from 100 W to 2 kW. The existing literature has found that most isolated DC–DC converters increase their turn ratios in order to achieve high step-up ratios. As a result, voltage spikes have increased significantly in switches, resulting in a decrease in overall system efficiency. In this research, the use of passive and active snubbers to provide soft switching in isolated step-up DC–DC converters is investigated. Moreover, a comprehensive analysis of the three most widely used boost techniques is provided. A reduction in turn ratio and a decrease in voltage stress were the results of this process. The main purpose of this study is to provide a comprehensive overview of the most used high-boost isolated DC–DC topologies in PV systems, including flyback, isolated SEPIC, forward, push-pull, half- and full-bridge, and resonant converter, with a focus on the recent research in the field and the recent advancements in these topologies. This study aims to guide further research and analysis in selecting appropriately isolated topologies for PV systems.
Enhancing Elderly Health Monitoring: Achieving Autonomous and Secure Living through the Integration of Artificial Intelligence, Autonomous Robots, and Sensors
Authors: Cantone Andrea Antonio , Esposito Mariarosaria , Perillo Francesca Pia , Romano Marco , Sebillo Monica , Vitiello Giuliana
Published: September 2023

The use of robots in elderly care represents a dynamic field of study aimed at meeting the growing demand for home-based health care services. This article examines the application of robots in elderly home care and contributes to the literature by introducing a comprehensive and functional architecture within the realm of theInternet of Robotic Things (IoRT). This architecture amalgamates robots, sensors, and Artificial Intelligence (AI) to monitor the health status of the elderly. This study presented a four-actor system comprising a stationary humanoid robot, elderly individuals, medical personnel, and caregivers. This system enables continuous monitoring of the physical and emotional well-being of the elderly through specific sensors that measure vital signs, with real-time updates relayed to physicians and assistants, thereby ensuring timely and appropriate care. Our research endeavors to develop a fully integrated architecture that seamlessly integrates robots, sensors, and AI, enabling comprehensive care for elderly individuals in the comfort of their homes, thus reducing their reliance on institutional hospitalization. In particular, the methodology used was based on a user-centered approach involving geriatricians from the outset. This has been of fundamental importance in assessing their receptivity to the adoption of an intelligent information system, and above all, in understanding the issues most relevant to the elderly. The humanoid robot is specifically designed for close interaction with the elderly, capturing vital signs, emotional states, and cognitive conditions while providing assistance in daily routines and alerting family members and physicians to anomalies. Furthermore, communication was facilitated through an external Telegram bot. To predict the health status of the elderly, a machine learning model based on the Modified Early Warning Score (MEWS), a medical scoring scale, was developed. Five key lessons emerged from the study, showing how the system presented can provide valuable support to physicians, caregivers, and older people.
A Novel Method for Battery SOC Estimation Based on Slime Mould Algorithm Optimizing Neural Network under the Condition of Low Battery SOC Value
Authors: Zhang Xuesen , Liu Xiaojing , Li Jianhua
Published: September 2023

The State of Charge (SOC) is a crucial parameter in battery management systems, making accurate estimation of SOC essential for adjusting control strategies in automotive energy management and ensuring the performance of electric vehicles. In order to solve the problem that the estimation error of the traditional BP neural network increases sharply under complex conditions and low battery SOC values, a recurrent neural network estimation method based on slime mould algorithm optimization is proposed. Firstly, the data are serialized to include multiple discharge data. Secondly, the data are input into a recurrent neural network for SOC estimation, with a self-attention mechanism added to the network. Furthermore, it is found in the experiment that parameters have an impact on the estimation accuracy of the neural network, so the slime mould algorithm is introduced to optimize the parameters of the neural network. The experiment results show that the maximum error of the novel method is limited to within 5% under two conditions. It is worth noting that the SOC estimation error at low SOC value decreases instead of increasing, which shows the advantages of the novel method.
A Transmission Price Design Considering the Marginal Benefits of the Transmission and Spatiotemporal Information of Electricity Demand
Authors: Liu Shuangquan , Xie Yigong , Zhu Xinchun , Shao Qizhuan , Li Wenxuan , Guo Zhuochen , Liu Xue
Published: September 2023

One of the most critical tasks of China’s power sector reformation is re-designing transmission and distribution (T&D) prices, which are essential in establishing fair and ordered power markets and encouraging the efficient allocation of resources. In view of the problems in China’s power market, such as the lack of a market mechanism for the reasonable allocation of congestion revenue, unreasonable transmission cost composition, and the failure of the transmission pricing mechanism to reflect the utilization degree of transmission resources by users in different geographical locations, this study proposes a transmission price design under the application scenarios of regional power grids and provincial power grids dominated by meshed AC networks in China that considers the marginal benefit of the transmission and spatiotemporal information of electricity demand. The proposed method effectively tackles the above-mentioned problem, with the transmission cost being divided into two parts: the expansion cost reflecting the marginal benefits of transmission, and the residual cost reflecting the rest. The expansion cost is objective and based on power system economics; it is calculated as the congestion revenue under the location marginal price-based wholesale electricity markets, resulting in a more reasonable division of transmission costs and allocation of congestion revenue. Furthermore, allocating the residual cost with the power flow distribution factor and the postage stamp method also reflects the utilization degree of transmission resources by users in different geographical locations. The effectiveness of this transmission price design is confirmed by testing it against a 3-bus and an IEEE 30-bus system.
Comparative Analysis of Consequent-Pole Flux-Switching Machines with Different Permanent Magnet Arrangements for Outer-Rotor In-Wheel Direct-Drive Applications
Authors: Bi Yanding , Fu Weinong , Niu Shuangxia , Huang Jiahui
Published: September 2023

Recently, the interest in consequent-pole flux-switching permanent magnet (CP-FSPM) machines has been increasing because of the flux-focusing PM arrangements and the removal of the flux-barrier effect. A simple and rigid outer-rotor salient pole rotor structure can be adopted in CP-FSPM machines, making them applicable for in-wheel direct-drive applications. In this study, three CP-FSPM machines with II-shaped (II-PM), V-shaped (V-PM), and straight U-shaped PM (SU-PM) arrays are analyzed and compared. Moreover, a CP-FSPM machine with inclined U-shaped PM (IU-PM) arrays is proposed to improve the flux-focusing effect and stator slot utilization. The working principles of CP-FSPM machines are analyzed by adopting a semi-analytical model. Combining the finite element analysis (FEA) results of air gap flux density and the analytical model of phase back electromotive force (EMF), the contributions of multiple working harmonics to the back EMF are quantitatively analyzed. Additionally, 6/16 and 6/17 CP-FSPM machines with different PM arrangements are globally optimized. Both the no-load and on-load performance of the optimized machines are included in the performance comparison. The results illustrate that the 6/16 and 6/17 machines exhibit their respective merits, and the IU-PM machine shows the best torque production ability in these CP-FSPM machines with the same design criteria.
Enhancing Sustainable Assessment of Electric Vehicles: A Comparative Study of the TOPSIS Technique with Interval Numbers for Uncertainty Management
Authors: Kaczyńska Aleksandra , Sulikowski Piotr , Wątróbski Jarosław , Sałabun Wojciech
Published: September 2023

The subject of electric vehicles (EVs) is constantly relevant from the perspective of climate change and sustainability. Multi-Criteria Decision Analysis (MCDA) methods can be successfully used to evaluate models of such vehicles. In many cases, the MCDA methods are modified to account for uncertainty in the data. There are many ways to express uncertainty, including more advanced ones, such as fuzzy sets, for example, but expressing attributes in terms of interval numbers remains a popular method because it is an easy-to-implement and easy-to-understand technique. This study focuses on interval extensions of the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method. It aims to compare the most popular extension proposed by Jahanshahloo and the proposed new modification, which returns the result in an interval form. Certain inconsistencies of the Jahanshahloo extension are discussed, and it is explained how the new extension avoids them. Both extensions are applied to an EV evaluation problem taken from the literature as an example for sustainable assessment. The results are then analyzed, and the question of whether the input data of the interval should receive an evaluation in the form of interval results is addressed.
Optimal Asymmetric Duty Modulation for Dual Active Bridge Converters with DC Blocking Capacitors
Authors: Dai Peng , Liu Shuyu , Fang Shiqi , Gong Zheng
Published: September 2023

Aiming at the optimization of current stress with low voltage ratio and full ZVS, a control method combining variable duty cycle and phase shift was proposed based on dual active bridge (DAB) converters with DC blocking capacitors. By adding DC bias to the DC blocking capacitors, asymmetric duty modulation (ADM) can adjust the bias as needed. Based on the theoretical analysis of steady-state operation, the operating modes can be divided into eight modes. According to the features of each mode, equivalent circuits are established. The transmission power and the boundary of zero-voltage-switching (ZVS) are deduced through a detailed analysis of each mode. Based on the theoretical deduction, ADM is more suitable for a low voltage ratio. Verified by experiment, optimized asymmetric duty modulation (OADM) can increase efficiency by 3.58%, 6.57%, 8.81%, and 10.33% compared with DPS when P is equal to 0.36 and m is equal to 0.4, 0.3, 0.2, and 0.1, respectively. Using this method, the current stress of the converter is lighter than that under regular modulation when the voltage ratio m ≤ 0.5 with full ZVS.
Effect of Scale and Structure Changes of China’s High-Carbon Industries on Regional Carbon Emissions
Authors: Liang Jing , Pan Lingying
Published: September 2023

China’s carbon emissions have a stable industrial concentration. In recent years, the carbon emissions of the six major high-carbon industries have accounted for approximately 80% of the national total and are thus priority areas for emission reduction. With the promotion of energy-saving and emission-reduction policies, the structure and scale of high-carbon industries in various regions have undergone changes, but their carbon reduction effects show significant regional differences. Based on China’s provincial panel data from 2006 to 2020, this study discusses the structural characteristics of high-carbon industries with their proportion of energy-based industries and measures their scale characteristics with their output values. On this basis, a fixed-effects model is used to analyze the single and synergistic effects of the scale and structure of high-carbon industries on carbon emissions in each province. The results indicate that changes in the scale and structure of high-carbon industries significantly affect carbon emissions but show regional differences in both the single and synergistic effects. When considering these synergistic effects, the single effect of high-carbon industries on carbon emissions will be weakened. In regions with large-scale high-carbon industries, the increase in the proportion of energy-based industries significantly increases carbon emissions, but this effect gradually weakens as the overall scale expands. In areas with small-scale high-carbon industries, the increase in the proportion of energy-based industries has a relatively small effect on carbon emission growth that gradually increases with the overall scale. In addition, the implementation of the carbon emission trading policy has a significant moderating effect on the carbon emissions of high-carbon industries and strongly promotes its reduction.
Anomaly Detection in Power System State Estimation: Review and New Directions
Authors: Cooper Austin , Bretas Arturo , Meyn Sean
Published: September 2023

Foundational and state-of-the-art anomaly-detection methods through power system state estimation are reviewed. Traditional components for bad data detection, such as chi-square testing, residual-based methods, and hypothesis testing, are discussed to explain the motivations for recent anomaly-detection methods given the increasing complexity of power grids, energy management systems, and cyber-threats. In particular, state estimation anomaly detection based on data-driven quickest-change detection and artificial intelligence are discussed, and directions for research are suggested with particular emphasis on considerations of the future smart grid.
Meta In-Context Learning: Harnessing Large Language Models for Electrical Data Classification
Authors: Zhou Mi , Li Fusheng , Zhang Fan , Zheng Junhao , Ma Qianli
Published: September 2023

The evolution of communication technology has driven the demand for intelligent power grids and data analysis in power systems. However, obtaining and annotating electrical data from intelligent terminals is time-consuming and challenging. We propose Meta In-Context Learning (M-ICL), a new approach that harnesses large language models to classify time series electrical data, which largely alleviates the need for annotated data when adapting to new tasks. The proposed M-ICL consists of two stages: meta-training and meta-testing. In meta-training, the model is trained on various tasks that have an adequate amount of training data. The meta-training stage aims to learn the mapping between electrical data and the embedding space of large language models. In the meta-testing stage, the trained model makes predictions on new tasks. By utilizing the in-context learning ability of large language models, M-ICL adapts models to new tasks effectively with only a few annotated instances (e.g., 1–5 training instances per class). Our contributions lie in the new application of large language models to electrical data classification and the introduction of M-ICL to improve the classification performance with the strong in-context learning ability of large language models. Furthermore, we conduct extensive experiments on 13 real-world datasets, and the experimental results show that the proposed M-ICL improves the average accuracy over all datasets by 19.06%, 12.06%, and 6.63% when only one, two, and five training instances for each class are available, respectively. In summary, M-ICL offers a promising solution to the challenges of electrical data classification.
Small-Scale Marine Fishers’ Possession of Fishing Vessels and Their Impact on Net Income Levels: A Case Study in Takalar District, South Sulawesi Province, Indonesia
Authors: Muslim Ahmad Imam , Fujimura Miho , Kazunari Tsuji , Salam Muslim
Published: September 2023

Over the last two decades, the growth of the fisheries sector in Indonesia has shown an increasing trend; however, behind the rapid development of this sector, the role of small-scale fisheries as one of the main actors supporting the whole industry is often neglected. They remain poor and continue to conduct fishing activities traditionally. Therefore, this study aims to describe the real situation of small-scale fishers, analyzing the fishers’ ownership of the boat they use, analyzing their income level to reveal their poverty status, and analyzing the factors affecting their income. The regression analysis results indicate that boat category, sea fish catch, fish selling price, fixed costs, and variable costs have significant effects on fishers’ net incomes.
Mitochondrial Analysis of Sparidae Species to Detect a New DNA Barcoding Marker for Dentex gibbosus to Utilize against Fraud
Authors: Venuti Iolanda , Ceruso Marina , Muscariello Tiziana , Ambrosio Rosa Luisa , Di Pinto Angela , Pepe Tiziana
Published: September 2023

Dentex gibbosus (Pink dentex) is a fish species of increasing economic interest in the Mediterranean Sea that is consumed both whole and processed. The growing value of this sparid in European markets is responsible for its substitution with fraudulent species. The distinctive morphologic feature of D. gibbosus is the conspicuous hump on the forehead in the older and larger specimens. However, the head is regularly convex in young individuals, requiring high skills and competencies for correct identification. Authentication becomes even more challenging in the case of prepared and processed products. Therefore, the molecular characterization of Pink dentex plays a crucial role in preventing commercial fraud with species substitution. This paper proposes a comparative mitogenome analysis between 19 sparid species of commercial interest as a tool to accurately design species-specific primers targeting a fragment of the NAD2 gene for the identification of D. gibbosus. We successfully detected Pink dentex DNA both using endpoint and real-time PCR. The findings showed the high specificity of the designed primers, demonstrating this a suitable, fast, and cost-effective method that could be used for the unambiguous identification of Pink dentex. This innovative approach for sparid authentication is expected to contribute to seafood traceability, public health assurance, integrity, and the credibility of the seafood industry.
Antimicrobial Activity of Frankincense (Boswellia sacra) Oil and Smoke against Pathogenic and Airborne Microbes
Authors: Al-Kharousi Zahra S. , Mothershaw Ann S. , Nzeako Basil
Published: September 2023

As they continuously evolve, plants will remain a renewable source for antimicrobial compounds. Omani frankincense is produced by B. sacra trees and is graded into Hojari, Nejdi, Shazri or Sha’bi. Air can be a source for pathogenic or food spoilage microbes; thus, inactivating airborne microbes is necessary in environments such as food and animal production areas. This study investigated the antimicrobial activity and the chemistry of steam-distilled oils of Hojari and Sha’bi grades. It also analyzed the antimicrobial activity of frankincense smoke and the size of its solid particles. Chemical analysis was performed using gas chromatography mass spectrometry (GC-MS). The antimicrobial activity of the oils against Staphylococcus aureus (NCTC 6571), Bacillus spp., Escherichia coli (NCTC 10418), Pseudomonas aeruginosa (NCTC 10662), Saccharomyces cerevisiae, Candida albicans, Aspergillus flavus, Aspergillus ochraceus, Aspergillus niger, Penicillium citrinum, Alternaria alternata and Fusarium solani was determined using well diffusion and micro-well dilution methods. A microscopic technique was used to determine the size of frankincense smoke solid particles. Microbes were exposed to frankincense smoke to test their susceptibility to the smoke. Hojari and Sha’bi oils were similar in composition and contained monoterpenes and sesquiterpenes. The Hojari and the Sha’bi oils possessed broad spectrum antimicrobial activity. The largest growth inhibition zones were obtained with S. cerevisiae and F. solani. An MIC of 1.56% (v/v) was found with E. coli, S. cerevisiae and F. solani. Frankincense smoke contained fine irregular solid particles with a diameter range of 0.8–2287.4 µm, and thus may pose a health risk to susceptible individuals. The smoke had potent antimicrobial activity against S. aureus, E. coli, and airborne bacteria, yeast and mold, with a maximum inhibition of 100%. It was concluded that Hojari and Sha’bi frankincense oils and smoke had significant antimicrobial activity that can be exploited in controlling human, animal and plant pathogenic microbes.
A Comparative Analysis of Phenolic Content, Antioxidant Activity, Antimicrobial Activity, and Chemical Profile of Coffea robusta Extracts Using Subcritical Fluid Extraction and Supercritical Carbon Dioxide Extraction
Authors: Supanivatin Pattarin , Thipayarat Aluck , Siriwattanayotin Suwit , Ekkaphan Paweena , Deepatana Anat , Wongwiwat Jakrapop
Published: September 2023

In this study, extracts of Robusta-roasted coffee were obtained using various extraction techniques, including subcritical fluid extractions using HFC-134a and HCFC-22 under room-temperature batch extraction, frozen-temperature batch extraction, and continuous extraction conditions. Additionally, supercritical carbon dioxide (SCCO2) extraction was performed using ethanol and tetrahydrofuran as co-solvents. These extractions were performed due to the presence of potent antioxidants and antibacterial substances in the extracts. Extraction machines were built to process the extraction. The antioxidant potential of the extracts was evaluated using total phenolic content and DPPH and FRAP assays, while antibacterial potential was identified using the disk diffusion method. The results showed that HCFC-22 extraction produced the highest yield compared to other extraction methods, but HFC-134a extraction had the highest antioxidant potential values. The yield and antioxidant potential of the extracts obtained using room-temperature batch extraction were slightly higher than those obtained using frozen-temperature batch extraction and continuous extraction. The yield and antioxidant potential of the extracts obtained using SCCO2 extraction were similar to those obtained using HFC-134a and HCFC-22 extractions, and co-solvents slightly improved the extraction performance. The extracts were found to be more effective as inhibitors of Gram-positive bacteria than Gram-negative bacteria. Caffeine was the most prominent tentative chemical compound in all coffee extracts. This research study provides a better understanding of various extraction techniques using HFC-134a, HCFC-22, and SCCO2 when applied to roasted Robusta coffee beans, with a focus on yield, antioxidant potential, antimicrobial potential, and tentative chemical profiles.
Nanoscale Materials Applying for the Detection of Mycotoxins in Foods
Authors: Hu Xiaochun , Li Huilin , Yang Jingying , Wen Xintao , Wang Shuo , Pan Mingfei
Published: September 2023

Trace amounts of mycotoxins in food matrices have caused a very serious problem of food safety and have attracted widespread attention. Developing accurate, sensitive, rapid mycotoxin detection and control strategies adapted to the complex matrices of food is crucial for in safeguarding public health. With the continuous development of nanotechnology and materials science, various nanoscale materials have been developed for the purification of complex food matrices or for providing response signals to achieve the accurate and rapid detection of various mycotoxins in food products. This article reviews and summarizes recent research (from 2018 to 2023) on new strategies and methods for the accurate or rapid detection of mold toxins in food samples using nanoscale materials. It places particular emphasis on outlining the characteristics of various nanoscale or nanostructural materials and their roles in the process of detecting mycotoxins. The aim of this paper is to promote the in-depth research and application of various nanoscale or structured materials and to provide guidance and reference for the development of strategies for the detection and control of mycotoxin contamination in complex matrices of food.
The Effect of Sodium Chloride on the Physicochemical and Textural Properties and Flavor Characteristics of Sous Vide Cooked Duck Meat
Authors: Zhang Man , Fu Cuncun , Chen Mengfei , Jin Changhai
Published: September 2023

This study was conducted to evaluate the effect of salt brining process parameters (salt concentration 0–15%, brining time 4–12 h, brining temperature 4–20 °C) on the quality of sous vide cooked duck meat by a single factor combined with response surface methodology (RSM). The sensory evaluation, physicochemical indexes (color, weight loss, NaCl content, TBARS value, and texture properties), and flavor characteristics were analyzed. The sensory overall mean score was applied as the evaluation index to optimize the brining conditions by RSM, and the optimum results contained a salt concentration of 11.69%, a brining temperature of 7.35 °C, and a brining time of 8.03 h. Under these conditions, the sensory overall mean score of duck meat was 8.59, with a relatively higher a* value and moderate NaCl content. GC-MS and odor activity value (OAV) results indicated that salt brining treatment significantly promoted the formation of the major odorants in duck meat, including pentanal, heptanal, octanal, (E)-2-nonenal, cis-4-decenal, decanal, 2,4-decadienal, (E,E)-2,4-decadienal, 1-heptanol, and 2-methyl-3-octanone, but decreased the content of hexanal, (E)-2-octenal, nonanal, (E,E)-2,4-nonadienal, 1-octen-3-ol, and 1-octen-3-one. 5′-nucleotides in duck meat were significantly increased after brining treatment. Therefore, salt brining treatment could be regarded as an efficient way to improve the sensory, aroma, and taste quality of sous vide cooked meat.
Instrumental Analysis or Human Evaluation to Measure the Appearance, Smell, Flavor, and Physical Properties of Food
Authors: Saleh Mohammed , Lee Youngseung
Published: September 2023

Instrumental analysis and sensory evaluation are two fundamental approaches used to assess the quality of food products, encompassing attributes such as appearance, smell, flavor, and physical properties [...]
Assessment of the Quality Attributes of Oat β-glucan Fortified Reduced-Fat Goat Milk Yogurt Supported by Microfluidization
Authors: Anli Elif Ayse , Gursel Asuman , Gursoy Ayse , Mert Behic
Published: September 2023

In this study, goat milk blends (1.5% fat) fortified with 0%, 0.25%, and 0.50% oat β-glucan were coded as YC, Y1, and Y2 and MFYC, MFY1, and MFY2. Microfluidization was applied at 103.4 MPa pressure in a 100 µm-process chamber at one stage for MFYC, MFY1, and MFY2 prior to yogurt making. Phase separation occurred due to the casein-β-glucan interaction observed at the oat β-glucan ratio (≥0.25%) but was more distinct at 0.50%. Microfluidization solved the textural instability at all ratios of β-glucan; a creamy and less cohesive structure was maintained in all yogurt samples. Among the samples, Y2 and MFY2 were the least viscous (p < 0.05), and syneresis was the highest and the lowest for Y2 and MFY1, respectively (p < 0.01). Lightness (L*) decreased, and yellowness (b*) and greenness (a*) increased with oat β-glucan concentration (p < 0.01) and MFYC. MFY1 and MFY2 were brighter and less green (p < 0.05). Microfluidization enhanced sensory attributes and oat β-glucan suppressed the goaty and salty taste, but the cereal taste became more obvious with the increase in the oat β-glucan ratio. Y1 and MFY1 were generally acceptable, and Y2 was less (p < 0.01). A liquid-like structure was observed in Y2 and this affected the sensorial perception in Y2.
Quantitative Risk Assessment of Five Foodborne Viruses in Shellfish Based on Multiplex qPCR
Authors: Yu Zhendi , Xu Zhangkai , Chen Jiang , Chen Lili , Liao Ningbo , Zhang Ronghua , Cheng Dongqing
Published: September 2023

Foodborne diseases are currently the most critical food safety issue in the world. There are not many hazard identification and exposure assessments for foodborne viruses (Norovirus GI, GII, Hepatitis A Virus, Rotavirus, Adenovirus) in shellfish. Multiplex qPCR for the simultaneous detection of five foodborne viruses was established and used to assess infection risk based on a 1-year pathogenesis study. The sensitivity, specificity and reproducibility of the multiplex qPCR method are consistent with that of conventional qPCR, which saves more time and effort. Overall, 37.86% of shellfish samples had one or more foodborne viruses. Risk assessment formulae and matrices were used to develop risk assessments for different age groups, different seasons and different shellfish. The annual probability of contracting a foodborne virus infection from shellfish is greater than 1.6 × 10−1 for all populations, and even for infants aged 0–4 years, it is greater than 1.5 × 10−2, which is much higher than the risk thresholds recommended by WHO (10−6) and the US EPA (10−4). High risk (level IV) is associated with springtime, and medium risk (level III) is associated with Mussel consumption. This study provides a basis for the risk of foodborne viral infections in people of different ages, in different seasons, and by consuming different shellfish.
The Differences in Protein Degradation and Sensitization Reduction of Mangoes between Juices and Pieces Fermentation
Authors: Tian Mengtian , Zhang Qiuqin , Zeng Xianming , Rui Xin , Jiang Mei , Chen Xiaohong
Published: September 2023

Given the allergic reaction caused by mangoes, nonthermal food technologies for allergenicity reduction are urgently desired. This study aimed to assess the impact of kombucha fermentation on the allergenicity of mangoes. The total proteins, soluble proteins, peptides, amino acid nitrogen, the SDS–PAGE profiles of the protein extracts, and immunoreactivity of the sediment and supernatant were measured in two fermentation systems (juices and pieces fermentation). Throughout the fermentation, the pH decreased from about 4.6 to about 3.6, and the dissolved oxygen reduced about 50% on average. However, the protein degradation and sensitization reduction of mangoes were different between the two fermentation systems. In juices fermentation, there was a drop in proteins and peptides but an increase in amino acids, due to the conversion of proteins and peptides into amino acids both in the supernatant and sediment. The allergenicity decreased both in the solid and liquid phases of juices fermentation. In pieces fermentation, proteins and peptides were decreased in the solid phase but increased in the liquid phase. This was due to the fact that proteins and peptides were partly transported into the culture liquid, resulting in a decrease of allergenicity in fruit pieces and an increase in culture liquid. The principal component analysis results showed that the fermentation type had significant effects on the protein degradation and sensitization reduction, while mango variety had no significant effect. These results demonstrate that kombucha fermentation can reduce the allergenicity of mangoes, and it is more effective in juices fermentation than in pieces fermentation. The present study provides a theoretical basis for developing hypoallergenic mango products.
Synergistic Effect of Combined Treatment with Allicin and Antioxidant of Bamboo Leaves and Preservation of Bullfrogs (Lithobates catesbeiana) during Refrigeration Storage
Authors: Lan Weiqing , Zhang Bingjie , Du Jintao , Zhu Shengyun , Xu Xiao , Xie Jing
Published: September 2023

The effects of allicin and antioxidant of bamboo leaves (AOB) on the quality of bullfrogs (Lithobates catesbeiana) during refrigerated storage (4 °C) were investigated. The quality changes in samples treated with deionized water (CK), allicin solution (All), antioxidant of bamboo leaves (AOB), and allicin solution combined with AOB solution (AA) in microbiological, physicochemical, and sensory evaluation were analyzed, respectively. The results demonstrated that combination treatment inhibited the increase in total viable counts, delayed the decrease in amino acid content, and retarded the sensory deterioration. Preservative treatment has an inhibitory effect on the early storage of PBC, which can reduce PBC by about 1.0 log CFU/g. The reduction in thiobarbituric acid (TBA) content and total volatile basic nitrogen (TVB-N) content indicated that combination treatment could better restrain the lipid oxidation and degradation of protein than the CK group and single-treatment group. In addition, the TVB-N content in the AA group still did not exceed the threshold on the 14th day. As a consequence, combination treatment prolonged the shelf life of bullfrogs for another six days. Therefore, allicin and AOB with excellent antioxidant and antimicrobial activity could be an effective approach to delay the biochemical reaction of refrigerated bullfrogs. This study has provided a potential approach for increasing the shelf life of bullfrogs and preserving their quality during refrigerated storage.
A Marine-Predator-Algorithm-Based Optimum FOPID Controller for Enhancing the Stability and Transient Response of Automatic Voltage Regulators
Authors: Noman Abdullah M. , Almutairi Sulaiman Z. , Aly Mokhtar , Alqahtani Mohammed H. , Aljumah Ali S. , Mohamed Emad A.
Published: September 2023

An improved design optimization method for fractional-order-based proportional integral derivative (FOPID) controllers is proposed in this paper to enhance the stability and transient response of automatic voltage-regulator systems. The FOPID represents a higher degree-of-freedom controller through having five tunable parameters, compared with only three parameters in the integer-order PID controller. In the literature, the performance of the FOPID is highly determined through the design method and its parameter-determination process. Recently, optimum design of the FOPID has found wide employment in several engineering applications through using metaheuristic optimization algorithms. In this paper, an improved method for the FOPID’s parameter optimization is proposed for AVR applications using the marine predator optimization algorithm (MPA). The proposed MPA–FOPID controller is verified through comparing its performance with other featured and newly developed optimization algorithms. The proposed MPA–FOPID comparative analysis has been proven to have better stability, frequency response, robustness, faster response, and disturbance-rejection ability over the other studied methods in this paper.
Robot Manipulator Control Using a Robust Data-Driven Method
Authors: Rahmani Mehran , Redkar Sangram
Published: September 2023

Robotic manipulators with diverse structures find widespread use in both industrial and medical applications. Therefore, designing an appropriate controller is of utmost importance when utilizing such robots. In this research, we present a robust data-driven control method for the regulation of a 2-degree-of-freedom (2-DoF) robot manipulator. The nonlinear dynamic model of the 2-DoF robot arm is linearized using Koopman theory. The data mode decomposition (DMD) method is applied to generate the Koopman operator. A fractional sliding mode control (FOSMC) is employed to govern the data-driven linearized dynamic model. We compare the performance of Koopman fractional sliding mode control (KFOSMC) with conventional proportional integral derivative (PID) control and FOSMC prior to linearization by Koopman theory. The results demonstrate that KFOSMC outperforms PID and FOSMC in terms of high tracking performance, low tracking error, and minimal control signals.
Nanocomposite Hydrogels and Extracellular Matrix—Advantages and Associated Risks
Authors: Kerch Garry
Published: September 2023

Hydrogels can be considered as mimics of the extracellular matrix (ECM). Through integrins, the cytoskeleton is connected to the ECM, and cytoskeleton tension depends on ECM stiffness. A number of age-related diseases depend on cellular processes related to cytoskeleton function. Some examples of cancer initiation and progression and heart disease in relation to ECM stiffness have been analyzed. The incorporation of rigid particles into the ECM can increase ECM stiffness and promote the formation of internal residual stresses. Water migration, changes in water binding energy to biomactomolecules, and changes in the state of water from tightly bound water to free and loosely bound water lead to changes in the stiffness of the ECM. Cardiac tissue engineering, ECM stiffness and cancer, the equivalence of ECM stiffness, oxidative stress, inflammation, multi-layer polyelectrolyte complex hydrogels and bioprinting, residual internal stresses, viscoelastic hydrogels, hydrogel nanocomposites, and the effect of water have been reported. Special attention has been paid to the role of bound water and internal stresses in ECM stiffness. The risks related to rigid particle incorporation into the ECM have been discussed. The potential effect of polyphenols, chitosan, and chitosan oligosaccharide on ECM stiffness and the potential for anti-TNF-α and anti-NF-κB therapies have been discussed.
Modification of Acorn Starch Structure and Properties by High Hydrostatic Pressure
Authors: Castro Luís M. G. , Caço Ana I. , Pereira Carla F. , Sousa Sérgio C. , Brassesco María E. , Machado Manuela , Ramos Óscar L. , Alexandre Elisabete M. C. , Saraiva Jorge A. , Pintado Manuela
Published: September 2023

Despite being rich in starch, over half of acorn production is undervalued. High hydrostatic pressure was used to modify the properties of Q. pyrenaica (0.1 and 460 MPa for 20 min) and Q. robur (0.1 and 333 MPa for 17.4 min) acorn starches to obtain high-valued ingredients. Pressure significantly altered the span distribution and heterogeneity of the acorn starch granules depending on the species, but their morphology was unaffected. Pressurization increased the amylose/amylopectin ratio and damaged starch contents, but the effect was more prominent in Q. pyrenaica than in Q. robur. However, the polymorphism, relative crystallinity, gelatinization temperatures, and enthalpies were preserved. The pressure effect on the starch properties depended on the property and species. The solubility, swelling power, and acorn gels’ resistance towards deformation for both species decreased after pressurization. For Q. pyrenaica starch, the in vitro digestibility increased, but the pseudoplastic behavior decreased after pressurization. No differences were seen for Q. robur. Regarding the commercial starch, acorn starches had lower gelatinization temperatures and enthalpies, lower in vitro digestibility, lower resistance towards deformation, superior pseudoplastic behavior, and overall higher solubility and swelling power until 80 °C. This encourages the usage of acorn starches as a new food ingredient.
Hydrogel Coating versus Calcium Sulphate Beads as a Local Antibiotic Carrier for Debridement Procedures in Acute Periprosthetic Joint Infection: A Preliminary Study
Authors: De Meo Daniele , Martini Paolo , Pennarola Maria Francesca , Guarascio Giovanni , Rivano Capparuccia Marco , Iaiani Giancarlo , Candela Vittorio , Gumina Stefano , Villani Ciro
Published: September 2023

Periprosthetic joint infections (PJI) are among the most difficult complications to treat in orthopaedic surgery. Debridement, antibiotics, and implant retention (DAIR) represent an efficient strategy for acute PJI, especially when resorbable local antibiotic carriers and coatings are used. The aim of this pilot study was to evaluate the difference between using antibiotic-loaded hydrogel (ALH) and calcium sulphate (CS) beads in the DAIR procedure. We analysed 16 patients who had been treated since 2018 for acute PJI, namely eight patients with knee PJI (50%), seven with hip PJI (43.7%), and one with shoulder PJI (6.2%). Nine patients were treated with the Debridement, Antibiotic Coating and Retention of the Implant (DACRI) method, while seven were treated with the Debridement, Antibiotic Pearls, Retention of the Implant (DAPRI) method. We found no significant differences between the two groups in terms of age, sex, the American Society of Anesthesiologists risk score, Charlson Comorbidity Index, localisation, days from onset to diagnosis and pathogenesis. Furthermore, no differences were found between the DACRI and DAPRI groups in terms of infection control (15 patients, 93.75% with p = 0.36) and last C-Reactive Protein values (p = 0.26), with a mean follow-up of 26.1 ± 7.7 months. Treatment for one patient affected by knee Candida albicans PJI in the DACRI group was not successful. In conclusion, DAPRI and DACRI appear to be safe and effective treatments for PJIs. This evidence will encourage the development of new clinical research into local carriers and coatings for use in acute implant-associated infections.
Multifunctional Drugs-Loaded Carbomol Hydrogel Promotes Diabetic Wound Healing via Antimicrobial and Immunoregulation
Authors: Wang Hehui , Jin Jiale , Zhang Chi , Gong Fangyi , Hu Baiwen , Wu Xiaochuan , Guan Ming , Xia Dongdong
Published: September 2023

Diabetic wound healing poses a significant clinical dilemma. Bacterial infection and immune dysregulation are the predominant reasons. However, conventional wound dressings with a single treatment approach often limit therapeutic efficacy and continue working with difficulty. These limitations cause high treatment failure for diabetic wounds. In this study, we developed a multiple drug-loaded carbomer hydrogel containing Que/Van/Rif (QVR-CBMG) for the simultaneous treatment of infection and immune dysregulation. Honeycomb-like QVR-CBMG hydrogel exhibits excellent abilities to eliminate bacterial infection and biofilms in vitro. Moreover, QVR-CBMG hydrogel possesses an immunomodulatory capacity via affecting the Sirt3/SOD2 signaling pathway to promote M2 macrophages. Furthermore, QVR-CBMG hydrogel effectively promotes wound healing in diabetic rats through several mechanisms. The multidrug-loaded wound dressing not only eliminates bacterial infection and facilitated angiogenesis but also promotes collagen deposition and remodulates the local immune microenvironment in the areas of wounds. In summary, this synthetic strategy to eliminate infection and regulate immune disorders has potential translational value for the prevention and management of diabetic wounds.
Investigating the Significance of Non-jejuni/coli Campylobacter Strains in Patients with Diarrhea
Authors: Teksoy Nermin , Ilktac Mehmet , Ongen Betigul
Published: September 2023

Campylobacter is one of the most commonly reported foodborne bacteria worldwide. Although Campylobacter jejuni and Campylobacter coli have been reported to be responsible for the great majority of campylobacteriosis, the burden of infections by species other than C. jejuni and C. coli have been increasing as a result of a transition to diagnostic test methods that enable the isolation of emerging species. The aim of the present study was to recover C. jejuni, C. coli, and emerging species from the stool samples of 500 patients with gastroenteritis and 100 healthy subjects via the use of a filtration method and culture techniques using Butzler agar and mCCDA under a microaerobic or hydrogen-enriched atmosphere, identify the species by multiplex PCR methods and assess the significance of emerging species in enteric diseases. Thirty-one (6.2%) Campylobacter spp. were isolated from the stool samples of diarrheic patients but none from healthy individuals. Of 31 isolates, 21 (67.8%), nine (29%), and one (3.2%) were identified as C. jejuni, C. coli, and Campylobacter concisus by multiplex PCR, respectively. The filtration method was superior to the culture technique using mCCDA under a microaerobic atmosphere. C. concisus was evaluated as the etiology of gastroenteritis as a result of laboratory and clinical evaluations. The present study was the first to indicate that emerging Campylobacter species are rarely detected and C. concisus is linked to acute gastroenteritis in Turkey where additional studies are warranted to clarify the significance of emerging species in gastroenteritis.