bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Variation in Geometric Parameters and Structural Configurations on the Transmission Characteristics of Terahertz-Range Spoof Surface Plasmon Polariton Interconnects for Interchip Data Communication: A Finite Element Method Study
Authors: Daiyan K. M. , Abi Shaiokh Bin , Rashid A. B. M. Harun-Ur , Shawkat MST Shamim Ara
Published: September 2023

Interconnects have become a major obstacle in chip scaling. Spoof surface plasmon polariton (SSPP) modes have gained attention for their ability to manipulate light beyond diffraction limits at a given frequency, leading to SSPP interconnects. This article investigates the transmission characteristics of SSPP interconnect pairs placed side by side in the terahertz frequency range with comprehensive performance analysis. The proposed SSPP waveguide pair exhibits a maximum transmission coefficient of around −0.05 dB in the −3 dB band in the terahertz frequency range. Due to field confinement near the metal–dielectric interface, energy remains confined for the designed SSPP interconnect pair system. The proposed SSPP structure shows several bands in the terahertz frequency range, whereas conventional interconnects shows almost zero transmission at such frequencies. Additionally, the effect of geometric parameters on transmission coefficients (S21) and coupling coefficients (S41) has been investigated. Moreover, it has been shown that the bandwidth, as well as the upper cutoff frequency, can be tuned by varying the geometric parameters such as groove height, groove width and groove density. Since global interconnects undergo bending in actual circuits during distant data transmission on chips, geometric mismatches may occur between adjacent pairs of SSPP interconnects. Hence, it has also been examined how bending and mismatches affect transmission and coupling coefficients. Several SSPP schemes have been simulated, among which the best performance is obtained with 2 μm mismatch in groove height. For this optimized design, two corrugated metal interconnects are considered with groove heights of 20 μm and 22 μm, respectively, a groove width of 3 μm, a period of 20 μm, and the number of grooves at 50. For this particular configuration, an ultra-wide passband is found having a bandwidth of almost 400 GHz, with a signal reflection of below −12 dB and little insertion loss of ∼−1.43 dB.
Sensorless Control Method for SPMSMs Based on Improved Sliding Mode Reaching Rate
Authors: Chen Yuepeng , Li Aiyi , Li Hui , Yang Xu , Chen Wei
Published: September 2023

Due to the advantages of simple structure, small size, and high power density, permanent magnet synchronous motors (PMSM) have attracted the research interest of many scholars both domestically and abroad. However, traditional PMSM equipped with sensors, encoders, and other devices tend to have high equipment costs and rely heavily on the accuracy of the sensors for control effectiveness. Therefore, sensorless control has become a hot trend in the PMSM control field. In response to the chattering problem in sliding mode algorithms, this study first optimized the sliding mode reaching rate of a sensorless control system and applied it to construct a sliding mode observer and speed controller. Next, the improved sliding mode reaching rate-based sensorless control system was modeled and simulated in Matlab/Simulink, and its control performance was compared and analyzed with that of the traditional sliding mode reaching rate and replicated sliding mode reaching rate. Finally, comparative experiments were conducted on a test bench, and the results showed that, under the action of the improved sliding mode reaching rate, the chattering range of the output speed of the motor was +2%~+5%, which optimized the output speed of the PMSM and achieved the purpose of weakening the chattering.
A Family of Five-Level Pseudo-Totem Pole Dual Boost Converters
Authors: Zhao Qingsong , Miao Guixi , Dai Hong , Jing Cheng , Xu Jianyuan , Li Wenjing , Ma Hui
Published: September 2023

In this paper, based on the pseudo-totem pole (PTP) circuit, a family of five-level PTP dual boost converters (PDBC) is proposed. A dual boost converter has some unique advantages, such as having no risk of bridge arm shoot-through and no problems related to switch body diode reverse recovery; thus, it has a good potential for applications. First, the derivation process, working principle, modulation and strategy of the topology are analyzed. Further, the number of power devices, switch voltages and current stress of the proposed topology is analyzed. Finally, a representative five-level PDBC experimental prototype is designed with AC input 220 V/50 Hz, DC output 400 V/1 kW, and peak efficiency of 98.27%. The experimental results show that the five-level PDBC proposed in this paper has higher efficiency and the correctness of its topology is verified.
Multiobjective Learning to Rank Based on the (1 + 1) Evolutionary Strategy: An Evaluation of Three Novel Pareto Optimal Methods
Authors: Ismail Walaa N. , Ibrahim Osman Ali Sadek , Alsalamah Hessah A. , Mohamed Ebtesam
Published: September 2023

In this research, the authors combine multiobjective evaluation metrics in the (1 + 1) evolutionary strategy with three novel methods of the Pareto optimal procedure to address the learning-to-rank (LTR) problem. From the results obtained, the Cauchy distribution as a random number generator for mutation step sizes outperformed the other distributions used. The aim of using the chosen Pareto optimal methods was to determine which method can give a better exploration–exploitation trade-off for the solution space to obtain the optimal or near-optimal solution. The best combination for that in terms of winning rate is the Cauchy distribution for mutation step sizes with method 3 of the Pareto optimal procedure. Moreover, different random number generators were evaluated and analyzed versus datasets in terms of NDCG@10 for testing data. It was found that the Levy generator is the best for both the MSLR and the MQ2007 datasets, while the Gaussian generator is the best for the MQ2008 dataset. Thus, random number generators clearly affect the performance of ES-Rank based on the dataset used. Furthermore, method 3 had the highest NDCG@10 for MQ2008 and MQ2007, while for the MSLR dataset, the highest NDCG@10 was achieved by method 2. Along with this paper, we provide a Java archive for reproducible research.
A 110 GHz Feedback Amplifier Design Based on Quasi-Linear Analysis
Authors: Dong Ruibing , Song Yiheng , Xing Yang
Published: September 2023

The power gain and output power of millimeter-wave (mm-Wave) and terahertz (THz) amplifiers are critical performance metrics, particularly when the operating frequencies of amplifiers are near to the maximum oscillator frequency (fmax) of the transistor. This paper presents the design of a 110 GHz amplifier based on the quasi-linear method. The power gain can be boosted to maximum achievable gain (Gmax) using a linear, lossless, reciprocal feedback network, though this leads to a simultaneous decrease in output power. Based on quasi-linear analysis, for an amplifier with Gmax gain, when the K-factor is equal to 1, the output power is zero. To avoid the very low output power of amplifiers, a new approach is proposed to balance power gain and output power. A 110 GHz six-stage feedback amplifier was designed using the proposed approach and fabricated using 40 nm CMOS technology. The measured power gain is 26.5 dB, and the saturation output power is 13 dBm at 110 GHz.
Traffic Light Detection by Integrating Feature Fusion and Attention Mechanism
Authors: Chuang Chi-Hung , Lee Chun-Chieh , Lo Jung-Hua , Fan Kuo-Chin
Published: September 2023

Path planning is a key problem in the design of autonomous driving systems, and accurate traffic light detection is very important for robust routing. In this paper, we devise an object detection model, which mainly focuses on traffic light classification at a distance. In the past, most techniques employed in this field were dominated by high-intensity convolutional neural networks (CNN), and many advances have been achieved. However, the size of traffic lights may be small, and how to detect them accurately still deserves further study. In the object detection domain, the scheme of feature fusion and transformer-based methods have obtained good performance, showing their excellent feature extraction capability. Given this, we propose an object detection model combining both the pyramidal feature fusion and self-attention mechanism. Specifically, we use the backbone of the mainstream one-stage object detection model consisting of a parallel residual bi-fusion (PRB) feature pyramid network and attention modules, coupling with architectural tuning and optimizer selection. Our network architecture and module design aim to effectively derive useful features aimed at detecting small objects. Experimental results reveal that the proposed method exhibits noticeable improvement in many performance indicators: precision, recall, F1 score, and mAP, compared to the vanilla models. In consequence, the proposed method obtains good results in traffic light detection.
Transfer and CNN-Based De-Authentication (Disassociation) DoS Attack Detection in IoT Wi-Fi Networks
Authors: Gebresilassie Samson Kahsay , Rafferty Joseph , Chen Liming , Cui Zhan , Abu-Tair Mamun
Published: September 2023

The Internet of Things (IoT) is a network of billions of interconnected devices embedded with sensors, software, and communication technologies. Wi-Fi is one of the main wireless communication technologies essential for establishing connections and facilitating communication in IoT environments. However, IoT networks are facing major security challenges due to various vulnerabilities, including de-authentication and disassociation DoS attacks that exploit IoT Wi-Fi network vulnerabilities. Traditional intrusion detection systems (IDSs) improved their cyberattack detection capabilities by adapting machine learning approaches, especially deep learning (DL). However, DL-based IDSs still need improvements in their accuracy, efficiency, and scalability to properly address the security challenges including de-authentication and disassociation DoS attacks tailored to suit IoT environments. The main purpose of this work was to overcome these limitations by designing a transfer learning (TL) and convolutional neural network (CNN)-based IDS for de-authentication and disassociation DoS attack detection with better overall accuracy compared to various current solutions. The distinctive contributions include a novel data pre-processing, and de-authentication/disassociation attack detection model accompanied by effective real-time data collection and parsing, analysis, and visualization to generate our own dataset, namely, the Wi-Fi Association_Disassociation Dataset. To that end, a complete experimental setup and extensive research were carried out with performance evaluation through multiple metrics and the results reveal that the suggested model is more efficient and exhibits improved performance with an overall accuracy of 99.360% and a low false negative rate of 0.002. The findings from the intensive training and evaluation of the proposed model, and comparative analysis with existing models, show that this work allows improved early detection and prevention of de-authentication and disassociation attacks, resulting in an overall improved network security posture for all Wi-Fi-enabled real-world IoT infrastructures.
Portable Skin Lesion Segmentation System with Accurate Lesion Localization Based on Weakly Supervised Learning
Authors: Qin Hai , Deng Zhanjin , Shu Liye , Yin Yi , Li Jintao , Zhou Li , Zeng Hui , Liang Qiaokang
Published: September 2023

The detection of skin lesions involves a resource-intensive and time-consuming process, necessitating specialized equipment and the expertise of dermatologists within medical facilities. Lesion segmentation, as a critical aspect of skin disorder assessment, has garnered substantial attention in recent research pursuits. In response, we developed a portable automatic dermatology detector and proposed a dual-CAM weakly supervised bootstrapping model for skin lesion detection. The hardware system in our device utilizes a modular and miniaturized design, including an embedded board, dermatoscope, and display, making it highly portable and easy to use in various settings. Our software solution uses a convolutional neural network (CNN) with a dual-class activation map (CAM) weakly supervised bootstrapping model for skin lesion detection. The model boasts two key characteristics: the integration of segmentation and classification networks, and the utilization of a dual CAM structure for precise lesion localization. We conducted an evaluation of our method using the ISIC2016 and ISIC2017 datasets, which yielded findings that demonstrate an AUC of 86.3% for skin lesion classification for ISIC2016 and an average AUC of 92.9% for ISIC2017. Furthermore, our system achieved diagnostic results of significant reference value, with an average AUC of 92% when tested on real-life skin. The experimental results underscore the portable device’s capacity to provide reliable diagnostic information for potential skin lesions, thereby demonstrating its practical applicability.
Performance Analysis of Several Intelligent Algorithms for Class Integration Test Order Optimization
Authors: Zhang Wenning , Zhou Qinglei , Guo Li , Zhao Dong , Gou Ximei
Published: September 2023

Integration testing is an essential activity in software testing, especially in object-oriented software development. Determining the sequence of classes to be integrated, i.e., the class integration test order (CITO) problem, is of great importance but computationally challenging. Previous research has shown that meta heuristic algorithms can devise class integration test orders with lower test stubbing complexity, resulting in software testing cost reduction. This study focuses on the comparable performance evaluation of ten commonly used meta heuristic algorithms: genetic algorithm (GA), particle swarm optimization (PSO), cuckoo search algorithm (CS), firefly algorithm (FA), bat algorithm (BA), grey wolf algorithm (GWO), moth flame optimization (MFO), sine cosine algorithm (SCA), salp swarm algorithm (SSA) and Harris hawk optimization (HHO). The objective of this study is to identify the most suited algorithms, narrowing down potential avenues for future researches in the field of search-based class integration test order generation. The standard implementations of these algorithms are employed to generate integration test orders. Additionally, these test orders are evaluated and compared in terms of stubbing complexity, convergence speed, average runtime, and memory consumption. The experimental results suggest that MFO, SSA, GWO and CS are the most suited algorithms. MFO, SSA and GWO exhibit excellent optimization performance in systems where fitness values are heavily impacted by attribute coupling. Meanwhile, MFO, GWO and CS are recommended for systems where the fitness values are strongly influenced by method coupling. BA and FA emerge as the slowest algorithms, while the remaining algorithms exhibit intermediate performance. The performance analysis may be used to select and improve appropriate algorithms for the CITO problem, providing a cornerstone for future scientific research and practical applications.
A Method for Restoring γ-Radiation Scene Images Based on Spatial Axial Gradient Discrimination
Authors: Li Kun-Fang , Feng Jie , Li Yu-Dong , Wen Lin , Kan Yong-Jia , Guo Qi
Published: September 2023

Clear and reliable visual information is the premise and basis of work for nuclear robots. However, the ubiquitous γ rays in the nuclear environment will produce radiation effects on CMOS cameras and bring in complex visual noise. In this paper, combining the mechanism and characteristics of γ radiation noise, a method for restoring γ-radiation scene images based on spatial axial gradient discrimination is proposed. Firstly, interframe difference is used to determine the position of radiated noise on the image. Secondly, the gray gradients of different axes at noise pixels are calculated, and two axes with lager gray gradients are selected. Then, the adaptive medians are selected on the two axes, respectively and are weighted according to the gradient as the new value of the noise pixel. Finally, the Wallis sharpening filter is applied to enhance the detailed information and deblur the image. Plenty of experiments have been carried out on images collected in real γ radiation scenes, and image quality has been significantly improved, with Peak Signal to Noise ratio (PSNR) reaching 30.587 dB and Structural Similarity Index Mean (SSIM) reaching 0.82. It is obvious that this method has advanced performance in improving the quality of γ-radiation images. It can provide method guidance and technical support for the software module design of the anti-nuclear radiation camera.
Stabilized Temporal 3D Face Alignment Using Landmark Displacement Learning
Authors: Lee Seongmin , Yoon Hyunse , Park Sohyun , Lee Sanghoon , Kang Jiwoo
Published: September 2023

One of the most crucial aspects of 3D facial models is facial reconstruction. However, it is unclear if face shape distortion is caused by identity or expression when the 3D morphable model (3DMM) is fitted into largely expressive faces. In order to overcome the problem, we introduce neural networks to reconstruct stable and precise faces in time. The reconstruction network extracts the 3DMM parameters from video sequences to represent 3D faces in time. Meanwhile, our displacement networks learn the changes in facial landmarks. In particular, the networks learn changes caused by facial identity, facial expression, and temporal cues, respectively. The proposed facial alignment network exhibits reliable and precise performance in reconstructing static and dynamic faces by leveraging these displacement networks. The 300 Videos in the Wild (300VW) dataset is utilized for qualitative and quantitative evaluations to confirm the effectiveness of our method. The results demonstrate the considerable advantages of our method in reconstructing 3D faces from video sequences.
The Metaverse in Industry 5.0: A Human-Centric Approach towards Personalized Value Creation
Authors: Mourtzis Dimitris
Published: September 2023

In the context of Industry 5.0, the concept of the Metaverse aligns with the vision of Web 4.0, representing a digital ecosystem where individuals and organizations collaborate in a human-centric approach to create personalized value. This virtual universe connects multiple interconnected worlds, enabling real-time interactions between users and computer-generated environments. By integrating technologies like artificial intelligence (AI), virtual reality (VR), and the Internet of Things (IoT), the Metaverse within Industry 5.0 aims to foster innovation and enhance productivity, efficiency, and overall well-being through tailored and value-driven solutions. Therefore, this entry explores the concept of the Metaverse in the context of Industry 5.0, highlighting its definition, evolution, advantages, and disadvantages. It also discusses the pillars of technological advancement, challenges, and opportunities, including its integration into manufacturing. The entry concludes with a proposal for a conceptual framework for integrating the human-centric Metaverse into manufacturing.
The Impact of Natural Regeneration of Phoebe bournei in Anfu County, Jiangxi Province, on Community Diversity and Soil Nutrient Characteristics
Authors: Xiong Ziqian , Sun Jiawei , Zhong Ping , Liang Lixin , Dang Haoxuan , Wang Guangjun
Published: September 2023

The ecological process of natural regeneration in forests is achieved by altering the relationship between community diversity and abiotic factors, thereby influencing the structure and functioning of ecosystems. Phoebe bournei is a unique and endangered tree species in China, and due to the rarity of P. bournei (Phoebe bournei) populations, there is limited research on the interaction between plant community diversity and soil environment during its natural regeneration process. Jiangxi Mingyue Mountain Forest Farm is one of the few locations where the natural regeneration of P. bournei communities occurs. From 2018 to 2021, the DBH (diameter at breast height) method was employed to define the stages of P. bournei regeneration. Community tree diversity, productivity, soil nutrients, and microbial diversity were investigated. The results showed the following: (1) P. bournei exhibits a competitive advantage compared to other tree species during natural regeneration, and it becomes the main contributor to community biomass and productivity in the later stages of regeneration. (2) The regeneration process of P. bournei has significant effects on community tree diversity and soil environment. Community diversity and biomass show a trend of initial increase followed by a decrease. Soil moisture content, available phosphorus, and bacterial diversity significantly increase. P. bournei’s competitive advantage is likely derived from its regulation of soil nutrients and microorganisms. (3) Correlation analysis reveals a significant positive correlation between soil microbial diversity and community productivity. Therefore, it is necessary to consider the composition and diversity of underground soil microorganisms in studies aimed at improving the quality of P. bournei forests. In summary, the natural regeneration of P. bournei involves the gradual removal of the original dominant evergreen species in the community by increasing its own competitive advantage and productivity, while continuously regulating community diversity, soil nutrients, and microbial diversity to facilitate the growth and development of P. bournei, ultimately establishing it as the dominant species in the forest community.
Forest Vegetation Detection Using Deep Learning Object Detection Models
Authors: Mendes Paulo A. S. , Coimbra António Paulo , de Almeida Aníbal T.
Published: September 2023

Forest fires have become increasingly prevalent and devastating in many regions worldwide, posing significant threats to biodiversity, ecosystems, human settlements, and the economy. The United States (USA) and Portugal are two countries that have experienced recurrent forest fires, raising concerns about the role of forest fuel and vegetation accumulation as contributing factors. One preventive measure which can be adopted to minimize the impact of the forest fires is to cut the amount of forest fuel available to burn, using autonomous Unmanned Ground Vehicles (UGV) that make use of Artificial intelligence (AI) to detect and classify the forest vegetation to keep and the forest fire fuel to be cut. In this paper, an innovative study of forest vegetation detection and classification using ground vehicles’ RGB images is presented to support autonomous forest cleaning operations to prevent fires, using an Unmanned Ground Vehicle (UGV). The presented work compares two recent high-performance Deep Learning methodologies, YOLOv5 and YOLOR, to detect and classify forest vegetation in five classes: grass, live vegetation, cut vegetation, dead vegetation, and tree trunks. For the training of the two models, we used a dataset acquired in a nearby forest. A key challenge for autonomous forest vegetation cleaning is the reliable discrimination of obstacles (e.g., tree trunks or stones) that must be avoided, and objects that need to be identified (e.g., dead/dry vegetation) to enable the intended action of the robot. With the obtained results, it is concluded that YOLOv5 presents an overall better performance. Namely, the object detection architecture is faster to train, faster in inference speed (achieved in real time), has a small trained weight file, and attains higher precision, therefore making it highly suitable for forest vegetation detection.
Exogenous 5-Aminolevulinic Acid Promotes Osmotic Stress Tolerance of Walnuts by Modulating Photosynthesis, Osmotic Adjustment and Antioxidant Systems
Authors: Zhong Yan , Liu Changzhou , Wei Bo , Zhang Jianting , An Yuyan , Wang Liangju
Published: September 2023

The walnut (Juglans regia L.) is an important economic tree worldwide, often cultivated in arid and semiarid regions. Improving the drought tolerance is of significance for walnut growth, production, and economic effectiveness. 5-Aminolevulinic acid (ALA) is a novel plant growth regulator which raises plant tolerance to various stressful conditions. Here, foliage application of ALA was carried out to uncover its effect on walnuts under polyethylene glycol (PEG) 6000-stimulated osmotic stress. Our results displayed that exogenous ALA greatly promoted the chlorophyll content, photochemical activities, and gas exchange in walnuts under osmotic stress. ALA led to a considerable accumulation of compatible osmotic solutes, enabling walnuts to maintain osmotic equilibrium against drought stress. Furthermore, ALA alleviated the reactive oxygen species (ROS) damages on osmotically stressed walnuts through enhancing the antioxidant enzyme activities, as well as decreasing the ROS and malondialdehyde (MDA) content. The relative water content (RWC) in the ALA-treated leaves was higher than that of PEG-stressed, while the RWC in the substrate of ALA treatment was significantly lower than that of the PEG-stressed, further suggesting that ALA promotes plant water uptake from the substrate under osmotic stress. These demonstrate that ALA improves the photosynthesis, osmotic adjustment, antioxidant systems and, consequently, the walnuts’ drought tolerance.
Quantification of Ecosystem Services from Urban Mangrove Forest: A Case Study in Angke Kapuk Jakarta
Authors: Sumarga Elham , Sholihah Arni , Srigati Febby Angelina Edi , Nabila Servina , Azzahra Puteri Raysa , Rabbani Naufal Pasya
Published: September 2023

Coastal urban areas in Indonesia commonly encounter complex environmental problems, including bad air pollution and high risk of flooding due to sea level rise and land subsidence. The existence of urban mangrove forests potentially contributes to mitigating the environmental problems. Preserving mangrove forests in coastal urban areas requires continuous support from all stakeholders, which can be strengthened by good understanding on the comprehensive benefits provided by these ecosystems. This study aims to quantify key ecosystem services from urban mangrove forest, with a case study in Angke Kapuk Jakarta. Four types of key ecosystem services were quantified, i.e., carbon storage, air pollutant absorption, microclimate regulation, and nature recreation. A vegetation survey was conducted in 30 sample plots to collect data for carbon storage, which covers above-ground carbon, below-ground carbon, and carbon on deadwood. The absorption of six pollutants (CO, NO2, O3, SO2, PM10, and PM2.5) was analysed using the i-Tree Eco model. Field measurements of air temperature and humidity, as well as interviews with 99 visitors, were performed to analyse microclimate regulation. This study found a high quantity of carbon storage within mangrove trees and deadwood in the study area (111.6 tonnes C/ha) as well as high amounts of air pollutants absorbed by mangrove trees (11.3 tonnes/year). Mangrove trees in the study area effectively regulated microclimate conditions, indicated by a significant difference in average daily air temperature and humidity between inside and outside the mangrove forest. Meanwhile, the number of visitors benefiting from its recreation services has fluctuated during the last five years, with an average of 138,550 people per year. We discuss the implications of the findings of this study for urban mangrove forest management, including how to integrate ecosystem services quantification into mangrove preservation and rehabilitation.
Impacts of Tenure Security on Rural Households’ Forestland Investment: Evidence from Jiangxi, China
Authors: Liu Xiaojin , Guo Xuan , Li Lishan , Xie Fangting
Published: September 2023

This paper examines the distinct effects of actual and perceived security on forestland investment by rural households. To achieve this, we utilized Tobit and IV-Reg models to analyze repeated survey data from 500 households residing in 50 villages in Jiangxi Province during the years 2017 and 2018. We measured households’ investment in forest management by labor and cash inputs. The findings indicate that actual and perceived tenure security significantly influence forestland investment. Specifically, the possession of forestland certificates exhibiting a marked increase in labor and cash inputs. However, the logging quota system has a significant negative impact on cash input, but no significant effect on labor input. With regard to perceived tenure security, the evaluation and comprehension of the existing tenure policy by households contribute positively to both labor and cash inputs in forestland. From our analysis, it is recommended that the logging quota system be revised to incentivize farmers’ active participation in forest management, and the government should strive to raise awareness among rural households about forest tenure policy.
Precoding for RIS-Assisted Multi-User MIMO-DQSM Transmission Systems
Authors: Castillo-Soria Francisco R. , Del Puerto-Flores J. Alberto , Azurdia-Meza Cesar A. , Babu Kumaravelu Vinoth , Simón Jorge , Gutierrez Carlos A.
Published: September 2023

This paper presents two precoding techniques for a reconfigurable intelligent surface (RIS)-assisted multi-user (MU) multiple-input multiple-output (MIMO) double quadrature spatial modulation (DQSM) downlink transmission system. Instead of being applied at the remote RIS, the phase shift vector is applied at the base station (BS) by using a double precoding stage. Results show that the proposed RIS-MU-MIMO-DQSM system has gains of up to 17 dB in terms of bit error rate (BER) and a reduction in detection complexity of 51% when compared with the conventional MU-MIMO system based on quadrature amplitude modulation (QAM). Compared with a similar system based on amplify and forward (AF) relay-assisted technique, the proposed system has a gain of up to 18 dB in terms of BER under the same conditions and parameters.
Changes in Flavor and Volatile Composition of Meat and Meat Products Observed after Exposure to Atmospheric Pressure Cold Plasma (ACP)
Authors: Bak Kathrine H. , Paulsen Peter
Published: September 2023

Studies on the atmospheric pressure cold plasma (ACP) exposure of meat and meat products mainly determine microbial inactivation, lipid oxidation, and meat color. Some studies include sensory evaluation, but only a few determine the changes in volatile composition due to ACP treatment. The results of sensory evaluation are inconclusive and range from “improvement” to “off-odor”. This could be due to differences in the food matrix, especially in processed foods, or different experimental settings, including inadvertent effects such as sample heating. The few studies analyzing volatile composition report changes in alcohols, esters, aldehydes, and other compounds, but not necessarily changes that are novel for meat and meat products. Most studies do not actually measure the formation of reactive species, although this is needed to determine the exact reactions taking place in the meat during ACP treatment. This is a prerequisite for an adjustment of the plasma conditions to achieve antimicrobial effects without compromising sensory quality. Likewise, such knowledge is necessary to clarify if ACP-exposed meat and products thereof require regulatory approval.
Prevalence of Metabolic Syndrome According to Physical Activity, Dietary Habits, Mental Status, Social Status, Health Behavior, and Obesity Phenotypes in Korean Adolescents: 2016–2021
Authors: Dou Xiangxiang , Kim Yonghwan , Chu Hyunsik
Published: September 2023

Environmental factors play a role in increasing or decreasing the risk of metabolic syndrome (MetS) in adolescents. We analyzed the impact of physical activity (PA), dietary habits, and mental and socioeconomic status on MetS prevalence in 2143 (boys: 1113, girls: 1030, age: 13–18 years) Korean middle- and high-school students. Metabolically healthy obesity and metabolically unhealthy normal weight were also evaluated. MetS occurred in 215 participants (10.0%), and boys had a higher MetS rate than girls. There was no significant difference in alcohol consumption and smoking experience between individuals with and those without MetS. The odds ratio (OR) for high-school students was 1.33 (95%CI, 1.001–1.789, p = 0.043) times that of middle-school students. Depression, low aerobic PA, and high sedentary time increased the ORs to 1.64 (95%CI, 1.059–2.539, p = 0.020), 1.52 (95%CI, 1.092–2.203, p = 0.003), and 1.86 (95%CI, 1.342–2.587, p < 0.001), respectively. Higher energy intake and low weekly breakfast consumption frequency yielded ORs of 1.46 (95%CI, 1.046–2.555, p = 0.025) and 1.70 (95%CI, 1.244–2.339, p = 0.011), respectively. Strength training, stress, suicidal ideation, dining out frequency, and household income did not impact MetS prevalence. Despite obesity, MetS decreased by 29.7% with high aerobic PA and 37.9% with high weekly breakfast consumption frequency. In conclusion, MetS risk was higher for men, individuals with depression, and high-school students. Low aerobic activity, high calorie intake, and low weekly breakfast consumption frequency increased MetS risk. Despite obesity, high aerobic activity, low sedentary time, and breakfast consumption was associated with lower MetS risk.
Low-Temperature Vacuum Drying on Broccoli: Enhanced Anti-Inflammatory and Anti-Proliferative Properties Regarding Other Drying Methods
Authors: Vega-Galvez Antonio , Uribe Elsa , Pasten Alexis , Camus Javiera , Rojas Michelle , Garcia Vivian , Araya Michael , Valenzuela-Barra Gabriela , Zambrano Angara , Goñi Maria Gabriela
Published: September 2023

Low-temperature vacuum drying (LTVD) has shown great potential for drying vegetables. It could avoid excessive degradations of active compounds with potential therapeutic agents. In this study, the effect on several relevant bioactive compounds, anti-inflammatory activity, and anti-proliferative activity of broccoli (Brassica oleracea var. italica) were evaluated. Effects of other drying methods, including vacuum drying (VD), convective drying (CD), infrared drying (IRD), and freeze drying (FD), were also comparatively evaluated. The results of all dried samples showed high polyunsaturated fatty acid contents (of up to 71.3%) and essential amino acid contents (of up to 8.63%). The LTVD method stands out above the other drying methods, since it obtained the highest content of total phenols, chlorogenic acid, and ferulic acid. Both the LTVD and CD samples demonstrated high anti-inflammatory and anti-proliferative activities. These CD and LTVD samples were also the most active against the breast carcinoma MDA-MB-23 cell line. Due to the good retention of bioactive compounds via LTVD, the obtained dried broccoli here can be used in a near time as an ingredient for the development of novel natural products with anti-inflammatory and anti-proliferative effects.
Evaluation of a Standardized Extract Obtained from Cashew Apple (Anacardium occidentale L.) Bagasse in DSS-Induced Mouse Colitis
Authors: da Silva Gisele Goulart , Braga Lucia Elaine de Oliveira , de Oliveira Ellen Cristina Souza , de Carvalho João Ernesto , Lazarini Josy Goldoni , Rosalen Pedro Luiz , Dionísio Ana Paula , Ruiz Ana Lucia Tasca Gois
Published: September 2023

Inflammatory bowel diseases (IBD) include Crohn’s disease and ulcerative colitis. Several studies relate eating habits to different aspects of IBD, such as progression and worsening of the clinical condition. Therefore, many natural products (NPs) such as polyphenols and carotenoids have been identified as promising agents in supporting IBD. An interesting source for obtaining bioactive NPs is the by-products of the food industry. The present study evaluated the potential beneficial effect of a standardized extract (CAE) obtained from cashew apple bagasse in the dextran sulfate sodium (DSS)-induced ulcerative colitis model in mice. This was the first time that CAE had been evaluated in this experimental model. Chemical evaluation of CAE identified carotenoids (96.28 ± 0.15 mg/100 g), phenolic compounds (37.49 ± 0.64 mg/100 g), and a mixture of anacardic acids (C15:3 = 94.2 ± 0.6 mg/100 g; C15:2 = 108.4 ± 0.1 mg/100 g; C15:1 = 214.8 ± 0.2 mg/100 g). Administration of CAE (500 mg/kg, 4 days, p.o.) after DSS challenge was more effective in delaying disease progression compared with prior treatment (500 mg/kg, 30 days, p.o.), according to the disease activity index. However, no treatment strategy with CAE was able to prevent or inhibit disease progression, since all parameters evaluated (macroscopic, biochemical, and histopathological) in CAE-treated animals were similar to those observed in DSS-challenged animals. Despite the high dose (500 mg/kg), the standardized extract (CAE) did not result in an effective concentration of carotenoids. Furthermore, as some anacardic acids have been reported as histone acetyltransferases inhibitors, there could be a possible antagonistic relationship between carotenoids and anacardic acids. Complementary research will be necessary to test the hypothesis of antagonism. Thus, an optimized extract, with an even higher concentration of carotenoids, obtained from cashew apple bagasse, can be developed as a possible adjuvant food supplement for inflammatory bowel diseases.
Walnut Flour as an Ingredient for Producing Low-Carbohydrate Bread: Physicochemical, Sensory, and Spectroscopic Characteristics
Authors: Wójcik Monika , Dziki Dariusz , Matwijczuk Arkadiusz , Gawlik-Dziki Urszula
Published: September 2023

Walnut flour (WF) is a nutrient-rich source that can be used as an alternative for individuals on a gluten-free diet. This study aimed to assess the physical, chemical, and sensory changes in low-carbohydrate bread when supplemented with WF. Molecular-level changes were also examined using ATR-FTIR spectra. The bread recipe, containing buckwheat and flaxseed, was enriched with WF at levels ranging from 5% to 20%. The addition of WF resulted in increased loaf volume and decreased baking loss. Enriched bread samples showed higher protein content, while fat and available carbohydrate content decreased. Additionally, WF incorporation led to a decrease in crumb brightness and an increase in redness (from 23.1 to 25.4) and yellowness (from 23.8 to 26.7). WF also increased crumb hardness and chewiness. Moreover, the tested additives primarily influenced the intensity of FTIR spectra, indicating changes in protein, carbohydrate, and fat content, with increased band intensity observed in the protein region. We particularly recommend bread with a WF content of 15%. This type of bread is characterized by high consumer acceptance. Furthermore, compared to bread without the addition of WF, it has a higher content of phenolic compounds, protein, and fat by approximately 40%, 8%, and 4%, respectively. The antioxidant activity of this bread, determined using the ABTS and DPPH methods, is also significantly higher compared to the control bread.
The Spirit of Cachaça Production: An Umbrella Review of Processes, Flavour, Contaminants and Quality Improvement
Authors: Ratkovich Nicolas , Esser Christian , de Resende Machado Ana Maria , Mendes Benjamim de Almeida , Cardoso Maria das Graças
Published: September 2023

This review provides a comprehensive analysis of the production, classification, and quality control of cachaça, a traditional Brazilian sugarcane spirit with significant cultural importance. It explores the fermentation and distillation of sugarcane juice, the ageing process in wooden containers, and the regulatory aspects of cachaça labelling. It emphasises the role of quality control in maintaining the spirit’s integrity, focusing on monitoring copper levels in distillation stills. Ethyl carbamate (EC), a potential carcinogen found in cachaça, is investigated, with the study illuminating factors influencing its formation and prevalence and the importance of its vigilant monitoring for ensuring safety and quality. It also underscores the control of multiple parameters in producing high-quality cachaça, including raw material selection, yeast strains, acidity, and contaminants. Further, the impact of ageing, wood cask type, and yeast strains on cachaça quality is examined, along with potential uses of vinasse, a cachaça by-product, in yeast cell biomass production and fertigation. A deeper understanding of the (bio)chemical and microbiological reactions involved in cachaça production is essential to facilitate quality control and standardisation of sensory descriptors, promoting global acceptance of cachaça. Continued research will address safety concerns, improve quality, and support the long-term sustainability and success of the cachaça industry.
Searching for Promisingly Trained Artificial Neural Networks
Authors: Lujano-Rojas Juan M. , Dufo-López Rodolfo , Artal-Sevil Jesús Sergio , García-Paricio Eduardo
Published: September 2023

Assessing the training process of artificial neural networks (ANNs) is vital for enhancing their performance and broadening their applicability. This paper employs the Monte Carlo simulation (MCS) technique, integrated with a stopping criterion, to construct the probability distribution of the learning error of an ANN designed for short-term forecasting. The training and validation processes were conducted multiple times, each time considering a unique random starting point, and the subsequent forecasting error was calculated one step ahead. From this, we ascertained the probability of having obtained all the local optima. Our extensive computational analysis involved training a shallow feedforward neural network (FFNN) using wind power and load demand data from the transmission systems of the Netherlands and Germany. Furthermore, the analysis was expanded to include wind speed prediction using a long short-term memory (LSTM) network at a site in Spain. The improvement gained from the FFNN, which has a high probability of being the global optimum, ranges from 0.7% to 8.6%, depending on the forecasting variable. This solution outperforms the persistent model by between 5.5% and 20.3%. For wind speed predictions using an LSTM, the improvement over an average-trained network stands at 9.5%, and is 6% superior to the persistent approach. These outcomes suggest that the advantages of exhaustive search vary based on the problem being analyzed and the type of network in use. The MCS method we implemented, which estimates the probability of identifying all local optima, can act as a foundational step for other techniques like Bayesian model selection, which assumes that the global optimum is encompassed within the available hypotheses.
Comparison of Harmonic Oscillator Model in Classical and Quantum Theories of Light-Matter Interaction
Authors: Astapenko Valery , Bergaliyev Timur
Published: September 2023

A brief review of the classical and quantum description of the interaction of electromagnetic radiation with matter based on the model of a harmonic oscillator is presented. This review includes the generalized Bohr correspondence principle, the excitation of a quantum oscillator by electromagnetic pulses including saturation effect, the harmonic limit of the Bloch equations, and a phenomenological account of the damping of the quantum oscillator. In all cases, at the mathematical level, the relationship between the classical and quantum descriptions of the electromagnetic interaction is established and the conditions for such compliance are identified.
A New Optimized FOPIDA-FOIDN Controller for the Frequency Regulation of Hybrid Multi-Area Interconnected Microgrids
Authors: Ahmed Nessma M. , Ebeed Mohamed , Magdy Gaber , Sayed Khairy , Gamoura Samia Chehbi , Metwally Ahmed Sayed M. , A. Mahmoud Alaa
Published: September 2023

This paper proposes a combined feedback and feed-forward control system to support the frequency regulation of multi-area interconnected hybrid microgrids considering renewable energy sources (RESs). The proposed control system is based on a fractional-order proportional-integral-derivative-accelerated (FOPIDA) controller in the feed-forward direction and a fractional-order integral-derivative with a low-pass filter compensator (FOIDN) controller in the feedback direction, referred to as a FOPIDA-FOIDN controller. Moreover, the parameters of the proposed FOPIDA-FOIDN controller (i.e., twelve parameters in each area) are optimally tuned using a proposed hybrid of two metaheuristic optimization algorithms, i.e., hybrid artificial gorilla troops optimizer (AGTO) and equilibrium optimizer (EO), and this hybrid is referred to as HGTOEO. The robustness and reliability of the proposed control system are validated by evaluating its performance in comparison to that of other counterparts’ controllers utilized in the literature, such as PID, FOPID, and tilt integral derivative (TID) controller, under the different operating conditions of the studied system. Furthermore, the proficiency of the proposed HGTOEO algorithm is checked against other powerful optimizers, such as the genetic algorithm, Jaya algorithm, improved Jaya algorithm, multi-verse optimizer, and cost-effective multi-verse optimizer, to optimally design the PID controller for the load frequency control of the studied two-area interconnected microgrid. The MATLAB simulation results demonstrate the viability and dependability of the proposed FOPIDA-FOIDN controller based on the HGTOEO algorithm under a variety of load perturbations and random production of RESs.
Imiquimod-Loaded Chitosan-Decorated Di-Block and Tri-Block Polymeric Nanoparticles Loaded In Situ Gel for the Management of Cervical Cancer
Authors: Almomen Aliyah , Badran Mohamed , Alhowyan Adel Ali , Alkholief Musaed , Alshamsan Aws
Published: September 2023

Background: Cervical intraepithelial neoplasia, the predisposing factor for cervical cancer (CC), is caused by human papillomavirus (HPV) infection and can be treated with imiquimod (IMQ). However, poor water solubility and side effects such as local inflammation can render IMQ ineffective. The aim of this study is to design a prolonged release nano system in combination with mucoadhesive–thermosensitive properties for an effective vaginal drug delivery. Methods: Polylactic-co-glycolic acid (PLGA), polycaprolactone (PCL), poly lactide-co-caprolactone (PLA-PCL), and poly L-lactide-co-caprolactone-co-glycolide (PLGA-PCL) were used to create IMQ nanoparticles. Chitosan (CS) was then added to the surfaces of the IMQ NPs for its mucoadhesive properties. The NPs were then incorporated into poloxamer hydrogels. The NPs’ size and morphology, encapsulation efficiency (EE), in vitro drug release, gel characterization, ex vivo drug permeation, and in vitro safety and efficacy were characterized. Results: Two batches of NPs were prepared, IMQ NPs and CS-coated NPs (CS-IMQ NPs). In general, both types of NPs were uniformly spherical in shape with average particle sizes of 237.3 ± 4.7 and 278.2 ± 5.4 nm and EE% of 61.48 ± 5.19% and 37.73 ± 2.88 for IMQ NPs and CS-IMQ NPs, respectively. Both systems showed prolonged drug release of about 80 and 70% for IMQ NPs and CS-IMQ NPs, respectively, within 48 h. The gelation temperatures for the IMQ NPs and CS-IMQ NPs were 30 and 32 °C, respectively; thus, suitable for vaginal application. Although ex vivo permeability showed that CS-IMQ NPs showed superior penetration compared to IMQ NPs, both systems enhanced drug penetration (283 and 462 µg/cm2 for IMQ NPs and CS-IMQ NPs, respectively) relative to the control (60 µg/cm2). Both systems reduced the viability of cervical cancer cells, with a minimal effect of the normal vaginal epithelium. However, IMQ NPs exhibited a more pronounced cytotoxic effect. Both systems were able to reduce the production of inflammatory cytokines by at least 25% in comparison to free IMQ. Conclusion: IMQ and CS-IMQ NP in situ gels enhanced stability and drug release, and improved IMQ penetration through the vaginal tissues. Additionally, the new systems were able to increase the cytotoxic effect of IMQ against CC cells with a reduction in inflammatory responses. Thus, we believe that these systems could be a good alternative to commercial IMQ systems for the management of CC.