bluuebunny/crossref_metadata_2025 huggingface dataset:
Supervised Character Resemble Substitution Personality Adversarial Method
Authors: Wang Xiujuan , Cao Siwei , Zheng Kangfeng , Guo Xu , Shi Yutong
Published: February 2023

With the development of science and computer technology, social networks are changing our daily lives. However, this leads to new, often hidden dangers in areas such as cybersecurity. Of these, the most complex and harmful is the Advanced Persistent Threat attack (APT attack). The development of personality analysis and prediction technology provides the APT attack a good opportunity to infiltrate personality privacy. Malicious people can exploit existing personality classifiers to attack social texts and steal users’ personal information. Therefore, it is of high importance to hide personal privacy information in social texts. Based on the personality privacy protection technology of adversarial examples, we proposed a Supervised Character Resemble Substitution personality adversarial method (SCRS) in this paper, which hides personality information in social texts through adversarial examples to realize personality privacy protection. The adversarial examples should be capable of successfully disturbing the personality classifier while maintaining the original semantics without reducing human readability. Therefore, this paper proposes a measure index of “label contribution” to select the words that are important to the label. At the same time, in order to maintain higher readability, this paper uses character-level resemble substitution to generate adversarial examples. Experimental validation shows that our method is able to generate adversarial examples with good attack effect and high readability.
Predicting Model Training Time to Optimize Distributed Machine Learning Applications
Authors: Guimarães Miguel , Carneiro Davide , Palumbo Guilherme , Oliveira Filipe , Oliveira Óscar , Alves Victor , Novais Paulo
Published: February 2023

Despite major advances in recent years, the field of Machine Learning continues to face research and technical challenges. Mostly, these stem from big data and streaming data, which require models to be frequently updated or re-trained, at the expense of significant computational resources. One solution is the use of distributed learning algorithms, which can learn in a distributed manner, from distributed datasets. In this paper, we describe CEDEs—a distributed learning system in which models are heterogeneous distributed Ensembles, i.e., complex models constituted by different base models, trained with different and distributed subsets of data. Specifically, we address the issue of predicting the training time of a given model, given its characteristics and the characteristics of the data. Given that the creation of an Ensemble may imply the training of hundreds of base models, information about the predicted duration of each of these individual tasks is paramount for an efficient management of the cluster’s computational resources and for minimizing makespan, i.e., the time it takes to train the whole Ensemble. Results show that the proposed approach is able to predict the training time of Decision Trees with an average error of 0.103 s, and the training time of Neural Networks with an average error of 21.263 s. We also show how results depend significantly on the hyperparameters of the model and on the characteristics of the input data.
Chattering Free Sliding Mode Control and State Dependent Kalman Filter Design for Underground Gasification Energy Conversion Process
Authors: Ahmad Sohail , Uppal Ali Arshad , Azam Muhammad Rizwan , Iqbal Jamshed
Published: February 2023

The fluctuations in the heating value of an underground coal gasification (UCG) process limit its application in electricity generation, where a desired composition of the combustible gases is required to operate gas turbines efficiently. This shortcoming can be addressed by designing a robust control scheme for the process. In the current research work, a model-based, chattering-free sliding mode control (CFSMC) algorithm is developed to maintain a desired heating value trajectory of the syngas mixture. Besides robustness, CFSMC yields reduced chattering due to continuous control law, and the tracking error also converges in finite time. To estimate the unmeasurable states required for the controller synthesis, a state-dependent Kalman filter (SDKF) based on the quasi-linear decomposition of the nonlinear model is employed. The simulation results demonstrate that despite the external disturbance and measurement noise, the control methodology yields good tracking performance. A comparative analysis is also made between CFSMC, a conventional SMC, and an already designed dynamic integral SMC (DISMC), which shows that CFSMC yields 71.2% and 69.9% improvement in the root mean squared tracking error with respect to SMC and DISMC, respectively. Moreover, CFSMC consumes 97% and 23.2% less control energy as compared to SMC and DISMC, respectively.
Versatile DMA Engine for High-Energy Physics Data Acquisition Implemented with High-Level Synthesis
Authors: Zabołotny Wojciech Marek
Published: February 2023

FPGA-based cards for data concentration and readout are often used in data acquisition (DAQ) systems for high-energy physics experiments. The DMA engines implemented in FPGA enable efficient data transfer to the processing system’s memory. This paper presents a versatile DMA engine. It may be used in systems with FPGA-equipped PCIe boards hosted in a server and MPSoC-based systems with programmable logic connected directly to the AXI system bus. The core part of the engine is implemented in HLS to simplify further development and modifications. The design is modular and may be easily integrated with the user’s DAQ logic, assuming it delivers the data via a standard AXI-Stream interface. The engine and accompanying software are designed with flexibility in mind. They offer a simple single-packet mode for debugging and a high-performance multi-packet mode fully utilizing the computational power of the processing system. The number of used DAQ cards and the amount of memory used for the DMA buffer may be modified in the runtime without rebooting the system. That is particularly useful in the development and test setups. This paper also presents the development and testing methodology. The whole design is open-source and available in public repositories.
Research on Named Entity Recognition for Spoken Language Understanding Using Adversarial Transfer Learning
Authors: Guo Yao , Li Meng , Li Yanling , Ge Fengpei , Qi Yaohui , Lin Min
Published: February 2023

In this paper, we propose an adversarial transfer learning method to solve the lack of data resources for named entity recognition (NER) tasks in spoken language understanding. In the framework, we use bi-directional long short-term memory with self-attention and conditional random field (BiLSTM-Attention-CRF) model which combines character and word information as the baseline model to train source domain and target domain corpus jointly. Shared features between domains are extracted by a shared feature extractor. This paper uses two different sharing patterns simultaneously: full sharing mode and private sharing mode. On this basis, an adversarial discriminator is added to the shared feature extractor to simulate generative adversarial networks (GAN) and eliminate domain-dependent features. This paper compares ordinary adversarial discriminator (OAD) and generalized resource-adversarial discriminator (GRAD) through experiments. The experimental results show that the transfer effect of GRAD is better than other methods. The F1 score reaches 92.99% at the highest, with a relative increase of 12.89%. It can effectively improve the performance of NER tasks in resource shortage fields and solve the problem of negative transfer.
Hydraulic Integrated Interconnected Regenerative Suspension: Sensitivity Analysis and Parameter Optimization
Authors: Guo Sijing , Chen Liang , Pan Yu , Wang Xuxiang , Tan Gangfeng
Published: February 2023

Hydraulic integrated interconnected regenerative suspension (HIIRS) is a novel suspension system that can simultaneously harvest the vibration energy in the suspension and enhance the vehicle dynamics. The parameter sensitivity of the HIIRS system is analyzed and the significant parameters are optimized in this paper. Specifically, a half-vehicle model with the HIIRS is established. Based on the model, the parameter sensitivity of the hydraulic system is analyzed with three objectives, ride comfort, road holding, and average energy harvesting power. The parameters considered in this study are more abundant than those in previous related studies, including hydraulic cylinder inner diameter, hydraulic motor displacement, resistance, initial system pressure, and accumulator parameters. It turns out that the most sensitive parameters are the inner diameter of the hydraulic cylinder, the resistance, and the displacement of the hydraulic motor. To further study the performances that the HIIRS could present, both the single-objective optimization and the multi-objective optimization problems are solved and compared with the optimized traditional suspensions. The optimized HIIRS performs better in ride comfort and road holding than the optimized traditional suspension and anti-roll bar suspension. Different from the previous suspension optimization design, multi-objective optimization not only considers the traditional performance of the suspension but also incorporates the energy harvesting characteristics into the optimization objective. In the multi-objective optimization, a Pareto front is obtained, which shows that the ride comfort conflicts with the road holding and the energy harvesting power, while road holding and energy harvesting power did not conflict. The Pareto front shows that the optimized HIIRS is superior to the traditional suspension in ride comfort and road holding, and also harvests considerable energy.
Synthesis of Non-Mirror-Symmetrical Far-Field Patterns Using Two Parallel Current Sheets
Authors: Xiao Gaobiao , Zang Ting , Liu Rui
Published: February 2023

This paper shows that the radiation patterns and polarizations on the two sides of the source plane can be controlled separately if two parallel current sheets are used. An efficient algorithm is proposed to determine the propagation components of the currents on the two sheets directly from the specified radiation pattern. Numerical examples demonstrate that the algorithm is effective for synthesizing radiation patterns with complex footprints and beam-wise polarizations. Although the resultant continuous current distribution is not easy to implement in practical applications, it provides a useful base for further designs. If proper feeding techniques are developed, it will also be possible to spatially sample the continuous current distribution and realize the radiation pattern with large scale antenna arrays.
Intruder Detection in VANET Data Streams Using Federated Learning for Smart City Environments
Authors: Arya Monika , Sastry Hanumat , Dewangan Bhupesh Kumar , Rahmani Mohammad Khalid Imam , Bhatia Surbhi , Muzaffar Abdul Wahab , Bivi Mariyam Aysha
Published: February 2023

Vehicular networks improve quality of life, security, and safety, making them crucial to smart city development. With the rapid advancement of intelligent vehicles, the confidentiality and security concerns surrounding vehicular ad hoc networks (VANETs) have garnered considerable attention. VANETs are intrinsically more vulnerable to attacks than wired networks due to high mobility, common network medium, and lack of centrally managed security services. Intrusion detection (ID) servers are the first protection layer against cyberattacks in this digital age. The most frequently used mechanism in a VANET is intrusion detection systems (IDSs), which rely on vehicle collaboration to identify attackers. Regrettably, existing cooperative IDSs get corrupted and cause the IDSs to operate abnormally. This article presents an approach to intrusion detection based on the distributed federated learning (FL) of heterogeneous neural networks for smart cities. It saves time and resources by using the most efficient intruder detection approach. First, vehicles use a federated learning technique to develop local, deep learning-based IDS classifiers for VANET data streams. They then share their locally learned classifiers upon request, significantly reducing communication overhead with neighboring vehicles. Then, an ensemble of federated heterogeneous neural networks is constructed for each vehicle, including locally and remotely trained classifiers. Finally, the global ensemble model is again shared with local devices for their updating. The effectiveness of the suggested method for intrusion detection in VANETs is evaluated using performance indicators such as attack detection rates, classification accuracy, precision, recall, and F1 scores over a ToN-IoT data stream. The ID model shows 0.994 training and 0.981 testing accuracy.
Phase-Only Pattern Synthesis for Spaceborne Array Antenna Based on Improved Mayfly Optimization Algorithm
Authors: Hu Hongming , Li Huawang , Liang Guang , Zhao Lulu , Yang Jiashuo , Wei Xiaoli
Published: February 2023

A new optimization algorithm—Improved Mayfly Optimization Algorithm (IMOA)—is proposed in this paper to fulfill the low sidelobe level (SLL) design requirements of the spaceborne array antenna. MOA is a new heuristic algorithm inspired by the flying behavior and mating process of mayflies. It has a unique speed updating system with great convergence, strong stability, fast solution speed, and high precision. Based on the MOA, IMOA not only introduces the adaptive inertial weight factor to enhance the search ability, but also uses the Levy flight strategy and the golden sine operator to improve the disadvantage of easily falling into the local optimal solution. Firstly, according to the antenna pattern requirements of high gain and low sidelobe, an optimization problem model is carried out. Then, the IMOA is applied to solve the problem by only controlling the phase under a given secondary amplitude distribution. Simulation results show that IMOA has great advantages in the maximum sidelobe level (MSLL) suppression and convergence speed. Finally, the EM simulations are conducted on the 528-element planar array antenna. The maximum sidelobe level suppression performances in the test are very consistent with the theoretical simulation, which verifies the feasibility and effectiveness of the proposed IMOA.
FedUKD: Federated UNet Model with Knowledge Distillation for Land Use Classification from Satellite and Street Views
Authors: Kanagavelu Renuga , Dua Kinshuk , Garai Pratik , Thomas Neha , Elias Simon , Elias Susan , Wei Qingsong , Yong Liu , Rick Goh Siow Mong
Published: February 2023

Federated deep learning frameworks can be used strategically to monitor land use locally and infer environmental impacts globally. Distributed data from across the world would be needed to build a global model for land use classification. The need for a federated approach in this application domain would be to avoid the transfer of data from distributed locations and save network bandwidth to reduce communication costs. We used a federated UNet model for the semantic segmentation of satellite and street view images. The novelty of the proposed architecture involves the integration of knowledge distillation to reduce communication costs and response times. The accuracy obtained was above 95% and we also brought in a significant model compression to over 17 times and 62 times for street-view and satellite images, respectively. Our proposed framework has the potential to significantly improve the efficiency and privacy of real-time tracking of climate change across the planet.
Polymorphic Hybrid CMOS-MTJ Logic Gates for Hardware Security Applications
Authors: Kumar Rajat , Divyanshu Divyanshu , Khan Danial , Amara Selma , Massoud Yehia
Published: February 2023

Various hardware security concerns, such as hardware Trojans and IP piracy, have sparked studies in the security field employing alternatives to CMOS chips. Spintronic devices are among the most-promising alternatives to CMOS devices for applications that need low power consumption, non-volatility, and ease of integration with silicon substrates. This article looked at how hardware can be made more secure by utilizing the special features of spintronics devices. Spintronic-based devices can be used to build polymorphic gates (PGs), which conceal the functionality of the circuits during fabrication. Since spintronic devices such as magnetic tunnel junctions (MTJs) offer non-volatile properties, the state of these devices can be written only once after fabrication for correct functionality. Symmetric circuits using two-terminal MTJs and three-terminal MTJs were designed, analyzed, and compared in this article. The simulation results demonstrated how a single control signal can alter the functionality of the circuit, and the adversary would find it challenging to reverse-engineer the design due to the similarity of the logic blocks’ internal structures. The use of spintronic PGs in IC watermarking and fingerprinting was also explored in this article. The TSMC 65nm MOS technology was used in the Cadence Spectre simulator for all simulations in this work. For the comparison between the structures based on different MTJs, the physical dimension of the MTJs were kept precisely the same.
Semi-Supervised Gastrointestinal Stromal Tumor Detection via Self-Training
Authors: Yang Qi , Cao Ziran , Jiang Yaling , Sun Hanbo , Gu Xiaokang , Xie Fei , Miao Fei , Gao Gang
Published: February 2023

The clinical diagnosis of gastrointestinal stromal tumors (GISTs) requires time-consuming tumor localization by physicians, while automated detection of GIST can help physicians develop timely treatment plans. Existing GIST detection methods based on fully supervised deep learning require a large amount of labeled data for the model training, but the acquisition of labeled data is often time-consuming and labor-intensive, hindering the optimization of the model. However, the semi-supervised learning method can perform better than the fully supervised learning method with only a small amount of labeled data because of the full use of unlabeled data, which effectively compensates for the lack of labeled data. Therefore, we propose a semi-supervised gastrointestinal stromal tumor (GIST) detection method based on self-training using the new selection criterion to guarantee the quality of pseudo-labels and adding the pseudo-labeled data to the training set together with the labeled data after linear mixing. In addition, we introduce the improved Faster RCNN with the multiscale module and the feature enhancement module (FEM) for semi-supervised GIST detection. The multiscale module and the FEM can better fit the characteristics of GIST and obtain better detection results. The experiment results showed that our approach achieved the best performance on our GIST image dataset with the joint optimization of the self-training framework, the multiscale module, and the FEM.
A MIMO–ANFIS-Controlled Solar-Fuel-Cell-Based Switched Capacitor Z-Source Converter for an Off-Board EV Charger
Authors: Subramaniam Umashankar , Reddy Kuluru Sudarsana , Kaliyaperumal Deepa , Sailaja Vudithyala , Bhargavi Pedada , Likhith Seedarala
Published: February 2023

The efficiency of a nation’s progress is determined by a variety of factors; however, transportation plays a critical role in boosting progress because it facilitates trade and communication between countries. The majority of transportation is powered by fossil fuels such as gasoline or diesel, which will be depleted in less than 50 years. Another option is to operate transportation systems after replacing conventional vehicles with electric vehicles (EV). Powering these vehicles with green electricity contributes zero carbon emissions from production to the final product. Together with the controller, an efficient charger ensures that the entire system is reliable and stable. The current work focuses on charging an off-board EV from greener energy sources (both a fuel cell and PV array forming a micro-grid) based on their availability via an efficient converter controlled by an adaptive multi-objective controller. A novel multi-output-based adaptive neuro fuzzy inference system (ANFIS) controller for charging the off-board EV at a constant current and voltage for both line and load regulations is proposed, in the current work. A comparison study of grid partitioning and subtractive clustering was conducted in order to select an optimized algorithm for generating FIS. Novelty is achieved by ensuring closed-loop stability is the main aim of the work. The entire work was created with the MATLAB/Simulink software.
Economic Dispatch Model of High Proportional New Energy Grid-Connected Consumption Considering Source Load Uncertainty
Authors: Xu Min , Li Wanwei , Feng Zhihui , Bai Wangwang , Jia Lingling , Wei Zhanhong
Published: February 2023

To solve the problem regarding the large-scale grid-connected consumption of a high proportion of new energy sources, a concentrating solar power (CSP)-photovoltaic (PV)-wind power day-ahead and intraday-coordinated optimal dispatching method considering source load uncertainty is proposed. First, the uncertainty of day-ahead wind power output prediction is described by the multi-scenario stochastic planning method, and the uncertainty of intraday source-load is characterized by the trapezoidal fuzzy number equivalence model. Second, based on the combined scenario set of day-ahead wind power output prediction, the day-ahead optimal dispatch is performed by combining thermal and CSP plants, and the day-ahead thermal and CSP plant dispatch output and intraday source load fuzzy dataset are used as the input quantities for the day-ahead dispatch. Thus, the scheduling output and rotating backup plan for thermal power and CSP plants were determined; finally, the validity and feasibility of the model were verified using arithmetic examples.
Box-Type Solar Cookers: An Overview of Technological Advancement, Energy, Environmental, and Economic Benefits
Authors: Misra Navendu , Anand Abhishek , Pandey Saurabh , Kant Karunesh , Shukla Amritanshu , Sharma Atul
Published: February 2023

Being one of the major energy consumers, cooking is a necessary part of daily life. Non renewable cooking fuel sources, such as wood or cow dung cause hazardous pollution and a poor ecosystem worldwide. Over the past few decades, solar-powered cooking has undergone numerous improvements. Solar cooking has been predominantly used as a substitute for reducing oil and gas dependence, increasing environmental sustainability, and reducing global warming threats. This paper talks about the recent development of the box-type solar cooker. The paper discusses the principles and classifications of various parameters that affect the performance, energy, and exergy related to the solar cooking system. In line with the sustainable development goals of the UN agenda 2030 and especially the heed to the accomplishment of SDG 7 and SDG 13, various economic factors, such as the payback period (PP), net present value (NPV), benefit–cost (B–C) ratios, internal rate of return (IRR), levelized cost of heat (LCOH), and levelized cost of cooking a meal (LCCM) have been discussed. The environmental analysis has also been presented to show the overall benefit of solar cooking. The review also focuses on the current development of a box-type solar cooker, its components, and its heat transfer characteristic. Various geometrical modifications, the use of reflectors, and transparent insulating materials that improve cooking have been discussed. The concept of energy storage in the form of Phase change material (Latent heat storage) with the latest studied designs improvements of solar cookers has been obtained to be efficient, which also help in late-evening cooking. It can be said that with better policy implications, the social and economic acceptability of the solar cooker can be achieved.
Determination of Non-Zero Initial Conditions for IIR Notch Filters Using the Vector Projection Method with Minimum Delay
Authors: Kocoń Sławomir , Piskorowski Jacek
Published: February 2023

In this paper, two approaches to determining the non-zero initial conditions for the difference equation of notch filters are proposed and analyzed. The vector of non-zero initial conditions is determined to reduce the transient of the considered IIR notch filters. Both presented approaches are based on the vector projection method. The first method is based on the iterative determination of the vectors of initial conditions using samples available at a given moment. The main goal of the second approach is to reduce the computational cost compared to the first method with a slight deterioration in the quality of filtration. In order to demonstrate the suitability of the proposed methods, they have been used in simulation studies of power line interference filtering from disturbed ECG signals. The use of the proposed methods allowed for a significant reduction of the transient in the filter response with a shorter delay than in the classical vector projection method.
Energy Efficiency in Modern Power Systems Utilizing Advanced Incremental Particle Swarm Optimization–Based OPF
Authors: Nappu Muhammad Bachtiar , Arief Ardiaty , Ajami Willy Akbar
Published: February 2023

Since the power grid grows and the necessity for higher system efficiency is due to the increasing number of renewable energy penetrations, power system operators need a fast and efficient method of operating the power system. One of the main problems in a modern power system operation that needs to be resolved is optimal power flow (OPF). OPF is an efficient generator scheduling method to meet energy demands with the aim of minimizing the total production cost of power plants while maintaining system stability, security, and reliability. This paper proposes a new method to solve OPF by using incremental particle swarm optimization (IPSO). IPSO is a new algorithm of particle swarm optimization (PSO) that modifies the PSO structure by increasing the particle size, where each particle changes its position to determine its optimal position. The advantage of IPSO is that the population increases with each iteration so that the optimization process becomes faster. The results of the research on optimal power flow for energy generation costs, system voltage stability, and losses obtained by the IPSO method are superior to the conventional PSO method.
Direct Numerical Simulation of a Turbulent Boundary Layer Encountering a Smooth-to-Rough Step Change
Authors: Ismail Umair
Published: February 2023

Using a direct numerical simulation (DNS), we investigate the onset of non-equilibrium effects and the subsequent emergence of a self-preserving state as a turbulent boundary layer (TBL) encounters a smooth-to-rough (STR) step change. The rough surface comprises over 2500 staggered cuboid-shaped elements where the first row is placed at 50 θ0 from the inflow. A Reθ=4500  value is attained along with δk≈35 as the TBL develops. While different flow parameters adjust at dissimilar rates that further depend on the vertical distance from the surface and perhaps on δSTR/k, an equilibrium for wall stress, mean velocity, and Reynolds stresses exists across the entire TBL by 35 δSTR after the step change. First-order statistics inside the inner layer adapt much earlier, i.e., at 10–15 δSTR after the step change. Like rough-to-smooth (RTS) scenarios, an equilibrium layer develops from the surface. Unlike RTS transitions, a nascent logarithmic layer is identifiable much earlier, at 4 δSTR after the step change. The notion of equivalent sandgrain roughness does not apply upstream of this fetch because non-equilibrium advection effects permeate into the inner layer. The emergent equilibrium TBL is categorized by a fully rough state (ks+≈120–130; ks/k≈2.8). Decomposition of wall stress into constituent parts reveals no streamwise dependence. Mean velocity in the outer layer is well approximated by Coles’ wake law. The wake parameter and shape factor are enhanced above their smooth-wall counterparts. Quadrant analysis shows that shear-stress-producing motions adjust promptly to the roughness, and the balance between ejections and sweeps in the outer layer remains impervious to the underlying surface.
A Generalized Approach for Determining the Current Ripple RMS in Four-Leg Inverters with the Neutral Inductor
Authors: Mandrioli Riccardo , Lo Franco Francesco , Ricco Mattia , Grandi Gabriele
Published: February 2023

This manuscript proposes a novel approach for determining phase and neutral-current-ripple RMS in grid-connected four-leg inverters with the neutral inductor. The harmonic pollution is determined for any arbitrary pulse width modulation (PWM) technique and a generic value of the neutral inductor. Thanks to the proposed approach, it is possible to describe the neutral inductor in a parametric way with respect to phase inductors and obtain a wide range of results, ranging from a direct neutral connection (no neutral inductor) to a conventional three-phase inverter (no fourth wire) for any value of modulation index and common mode injection. The results permit one to compare different design choices in multiple scenarios effectively. The findings were validated by numerical simulations and experimental tests employing the most popular PWM techniques, such as space vector PWM (SVPWM) and discontinuous PWM (DPWM).
Numerical Study on the Evolution of Reservoir Pressure and CBM Concentration Considering Hydraulic Fractures
Authors: Wang Yuan , Zhong Liguo , Zhang Lei , Zou Junpeng
Published: February 2023

Based on the theories of mass conservation and coalbed methane (CBM) adsorption/desorption, this paper first establishes a novel reservoir pressure model for CBM production, following which, the CBM concentration and production models are also proposed. Then, these models are programmed and solved by means of the finite element method. Taking the Hunchun CBM field in Jilin province, China, as an example, the reservoir pressure, gas concentration, and production characteristics under different hydraulic fracture forms are simulated and investigated. In conclusion, the reservoir pressure decreases very rapidly in a small region near the fracture tip, which we called the “reservoir pressure singularity”. The existence of a hydraulic fracture greatly reduces the reservoir pressure in the process of CBM exploitation. The permeability sensitivity coefficient of reservoir pressure, Rpk, is defined to quantitatively describe the influence of coal seam permeability on the evolution of reservoir pressure. Rpk decreases logarithmically as the distance from the CBM extraction well increases. The reservoir pressure and CBM recovery rate characteristics in the presence of multiple hydraulic fractures are also investigated. We believe these results could contribute to the design of hydraulic fracturing wells and the evaluation of gas production in a CBM reservoir.
Millet Fermented by Different Combinations of Yeasts and Lactobacilli: Effects on Phenolic Composition, Starch, Mineral Content and Prebiotic Activity
Authors: Balli Diletta , Cecchi Lorenzo , Pieraccini Giuseppe , Venturi Manuel , Galli Viola , Reggio Marta , Di Gioia Diana , Furlanetto Sandra , Orlandini Serena , Innocenti Marzia , Mulinacci Nadia
Published: February 2023

Millet is the sixth-highest yielding grain in the world and a staple crop for millions of people. Fermentation was applied in this study to improve the nutritional properties of pearl millet. Three microorganism combinations were tested: Saccharomyces boulardii (FPM1), Saccharomyces cerevisiae plus Campanilactobacillus paralimentarius (FPM2) and Hanseniaspora uvarum plus Fructilactobacillus sanfranciscensis (FPM3). All the fermentation processes led to an increase in minerals. An increase was observed for calcium: 254 ppm in FPM1, 282 ppm in FPM2 and 156 ppm in the unfermented sample. Iron increased in FPM2 and FPM3 (approx. 100 ppm) with respect the unfermented sample (71 ppm). FPM2 and FPM3 resulted in richer total phenols (up to 2.74 mg/g) compared to the unfermented sample (2.24 mg/g). Depending on the microorganisms, it was possible to obtain different oligopeptides with a mass cut off ≤10 kDalton that was not detected in the unfermented sample. FPM2 showed the highest resistant starch content (9.83 g/100 g) and a prebiotic activity on Bifidobacterium breve B632, showing a significant growth at 48 h and 72 h compared to glucose (p < 0.05). Millet fermented with Saccharomyces cerevisiae plus Campanilactobacillus paralimentarius can be proposed as a new food with improved nutritional properties to increase the quality of the diet of people who already use millet as a staple food.
In Vitro Fecal Fermentation of Euphorbia humifusa-Derived Polysaccharides and Their Protective Effect against Ulcerative Colitis in Mice
Authors: Xiang Ning , Zhao Jianbo , Chang Siqiao , Li Shasha , Liu Shuwen , Wang Chan
Published: February 2023

Euphorbia humifusa is a plant species with medicinal and food characteristics used to treat diarrhea and other intestinal diseases. This study investigated the prebiotic effects of E. humifusa-derived polysaccharides (EHPs) on human colonic microbiota and their regulatory effects on ulcerative colitis (UC). Structural characterization showed that EHPs mainly consisted of galactose, glucose, and glucuronic acid and were heteropolysaccharides having molecular weights of 7.70 × 103 and 1.76 × 102 kDa, respectively. EHPs were identified as poorly absorbed macromolecules, verified by the apparent permeability coefficient values (Papp < 1.0 × 10−6 cm/s) and cellular uptake by Caco-2 cell monolayers. During in vitro fermentation studies, the contents of acetic, propionic, and valeric acids increased significantly in EHP-supplemented samples after 24 h compared to that in the control sample. Moreover, EHPs could alter the intestinal microbiota composition by increasing the relative abundance of Bifidobacterium and Holdemanella and reducing that of Escherichia-Shigella, Tyzzerella, and Parasutterella at the genus level. In a dextran sulfate sodium (DSS)-induced UC mouse model, EHPs alleviated UC symptoms by increasing the colon length, reversing the colon tissue damage and inhibiting pro-inflammatory cytokines. Overall, these results suggest that EHPs could be utilized as a potential prebiotic or a promising nutritional strategy for UC management.
Increasing Nitrogen Losses Due to Changing Food Consumption Patterns in Bayannur City, China
Authors: Liang Yihang , Zhang Yanqin , Wang Yuyue , Kong Xinggong , Cai Zucong , Wang Yanhua
Published: February 2023

Increasing urbanization and affluence have led to changes in food consumption patterns. The application of nitrogen (N) fertilizers ensures food security but also leads to environmental pollution due to N losses, through processes such as acidification, eutrophication, and greenhouse gas emissions. To clarify whether changes in food consumption patterns could increase N losses and to explore sustainable food system pathways, this study integrated the Chinese Food System Dashboard and the Nutrient Flows in Food Chains, Environment and Resources Use model to quantify and compare the link between food consumption and N losses in different agricultural regions using a case study of Bayannur City in the Yellow River Basin from 2000 to 2016. During the study period, Bayannur’s food consumption pattern changed from a “high carbohydrate and pork pattern” to a “high fiber and herbivore pattern”, which represents a shift from low to high N consumption. The per-capita food consumption decreased by 11.55% from 425.41 kg cap−1, whereas the per-capita N losses increased by 12.42% from 35.60 kg N cap−1. The average share of the plant-oriented and animal-oriented food supply in these losses was 53.39% and 46.61%, respectively. There were differences in the food consumption patterns and N losses in Bayannur’s farming, farming–pastoral, and pastoral regions. The changes in N losses were most significant in the pastoral region. The N losses to the environment increased sharply by 112.33% from 22.75 g N cap−1 over the past 16 years. The low level of economic development in Bayannur resulted in a shift in the food consumption pattern to a high N consumption. Four measures to protect food security and reduce the food N cost were proposed: (1) increasing the wheat planting area and maintaining the existing corn one; (2) expanding the scale of high-quality alfalfa planting; (3) enhancing the area of oat grass and wheat replanting; and (4) using modern planting technology.
Effects of Different Drying Methods on the Selenium Bioaccessibility and Antioxidant Activity of Cardamine violifolia
Authors: Wang Peiyu , Li Yue , Yu Ruipeng , Huang Dejian , Chen Shangwei , Zhu Song
Published: February 2023

Understanding the effects of drying on the selenium (Se) content and Se bioaccessibility of Se-rich plants is critical to dietary supplementation of Se. The effects of five common drying methods (far-infrared drying (FIRD), vacuum drying (VD), microwave vacuum drying (MVD), hot air drying (HD), and freeze vacuum drying (FD)) on the content and bioaccessibility of Se and Se species in Cardamine violifolia leaves (CVLs) were studied. The content of SeCys2 in fresh CVLs was the highest (5060.50 μg/g of dry weight (DW)); after FIRD, it had the lowest selenium loss, with a loss rate of less than 19%. Among all of the drying processes, FD and VD samples had the lowest Se retention and bioaccessibility. FIRD, VD, and FD samples have similar effects on antioxidant activity.
Ficus carica (Linn.) Leaf and Bud Extracts and Their Combination Attenuates Type-1 Diabetes and Its Complications via the Inhibition of Oxidative Stress
Authors: El Ghouizi Asmae , Ousaaid Driss , Laaroussi Hassan , Bakour Meryem , Aboulghazi Abderrazak , Soutien Rose Strutch , Hano Christophe , Lyoussi Badiaa
Published: February 2023

The current work was designed to evaluate the antioxidant activity and antidiabetic effect of Ficus carica L. extracts. For that, the leaves and buds of Ficus carica L. were analyzed to determine their polyphenolic and flavonoid contents and antioxidant activity. Diabetes was induced by a single dose of alloxan monohydrate (65 mg/kg body weight), then diabetic rats were treated with a dose of 200 mg/kg body weight of the methanolic extracts of Ficus carica leaves or buds or their combination for 30 days. Throughout the experiment, blood sugar and body weight were measured every 5 and 7 days respectively. At the end of the experiment, serum and urine were collected for analysis of alanine aminotransferase, aspartate aminotransferase, total cholesterol, triglycerides, creatinine, uric acid, urea, proteins, sodium, potassium, and chloride. Pancreas, liver, and kidney were removed to estimate catalase, glutathione peroxidase, and glutathione activities; lipid peroxidation products were also determined. The results obtained revealed that alloxan has induced hyperglycemia, increased liver and renal biomarkers levels, reduced antioxidative enzymes, and induced lipid peroxidation. However, the treatment with Ficus carica leaf and bud extracts, especially their combination, has attenuated all pharmacological perturbations induced by alloxan.
Total Utilization-Upcycling of Mushroom Protein By-Product: Characterization and Assessment as an Alternative Batter Ingredient for Fried Shrimp
Authors: Garcia Diego , You Seung Woon , Aleman Ricardo S. , King Joan M. , Komarnytsky Slavko , Hoskin Roberta Targino , Moncada Marvin
Published: February 2023

Mushroom by-products are economical and eco-friendly raw materials with bioactive and functional characteristics that allow for potential uses as food ingredients. However, mushroom upcycling has yet to be fully exploited, despite the many opportunities that mushrooms may offer. The mushroom protein by-product (MPBP) resulting from mushroom protein production was characterized (chemical composition, physicochemical attributes, and functional properties) and incorporated into plant-based batter formulations to prepare four experimental groups with different ratios (w/w, %) of wheat flour (W) to MPBP (100 W, 75 W/25 MPBP, 25 W/75 MPBP, and 100 MPBP). Subsequently, the batter was used for frying batter-coated shrimp, which was evaluated for cooking loss, coating pick-up, oil absorption, and color parameters (L*, a*, and b*). MPBP showed high content of dietary fiber, mainly insoluble fiber (49%), and it is potentially suited for the formulation of high-fiber food products. The MPBP physicochemical attributes pH (11.69), water activity (0.34), L* (58.56), a* (5.61), b* (18.03), and particle size distribution (250–500 µm (22.12%), 125–250 µm (41.18%), 63–125 µm (37.53%), and < 63 µm (0.82%) were noted. Concerning the MPBP functional characteristics, solubility (12.7%), emulsifying activity index (7.6 m2/gr), emulsion stability index (52.4 min), water holding capacity (4.9%), and oil holding capacity (4.8%) were reported. Adding MPBP into batter formulations for batter-coated shrimp resulted in higher values of cooking loss, oil absorption, coating pick-up, and a* color, while lowering L* and b* values. The best experimental results were reported for group 75 W/25 MPBP, which indicates that MPBP can potentially be accepted as a novel batter ingredient for partial substitution of wheat flour.
Three Phenolic Extracts Regulate the Physicochemical Properties and Microbial Community of Refrigerated Channel Catfish Fillets during Storage
Authors: Huang Jian , Wang Lan , Zhu Zhenzhou , Zhang Yun , Xiong Guangquan , Li Shuyi
Published: February 2023

It has been demonstrated that polyphenols have the potential to extend the shelf life of fish products. Thus, the effects of phenolic extracts from grape seed (GSE), lotus seedpod (LSPC), and lotus root (LRPE) were investigated in this study, focusing on the physicochemical changes and bacterial community of refrigerated channel catfish fillets during storage at 4 °C, using ascorbic acid (AA) as reference. As a result, GSE, LSPC, LRPE and AA inhibit the reproduction of microbials in catfish fillets during storage. According to the microbial community analysis, the addition of polyphenols significantly reduced the relative abundance of Proteobacterial in the early stage and changed the distribution of the microbial community in the later stage of storage. After 11 days of storage, the increase in total volatile base nitrogen (TVB-N) in fish was significantly reduced by 25.85%, 25.70%, 22.41%, and 39.31% in the GSE, LSPC, LRPE, and AA groups, respectively, compared to the control group (CK). Moreover, the lipid oxidation of samples was suppressed, in which thiobarbituric acid-reactive substances (TBARS) decreased by 28.77% in the GSE group, compared with the CK. The centrifugal loss, LF-NMR, and MRI results proved that GSE significantly delayed the loss of water and the increase in immobilized water flowability in catfish fillets. The polyphenol-treated samples also showed less decrease in shear force and muscle fiber damage in histology, compared to the CK. Therefore, the dietary polyphenols including GSE, LSPC, and LRPE could be developed as natural antioxidants to protect the quality and to extend the shelf life of freshwater fish.
The Prevalence and Antibiotic-Resistant of Listeria monocytogenes in Livestock and Poultry Meat in China and the EU from 2001 to 2022: A Systematic Review and Meta-Analysis
Authors: Zhang Haoqi , Luo Xin , Aspridou Zafeiro , Misiou Ourania , Dong Pengcheng , Zhang Yimin
Published: February 2023

To compare the prevalence and antibiotic resistance rate of Listeria monocytogenes in livestock and poultry (beef, pork and chicken) meat between China and the European Union (EU), a meta-analysis was conducted. Ninety-one out of 2156 articles in Chinese and English published between January 2001 and February 2022 were selected from four databases. The prevalence of L. monocytogenes in livestock and poultry (beef, pork and chicken) meat in China and Europe was 7.1% (3152/56,511, 95% CI: 5.8–8.6%) and 8.3% (2264/889,309, 95% CI: 5.9–11.0%), respectively. Moreover, a decreasing trend was observed in both regions over time. Regarding antibiotic resistance, for the resistance to 15 antibiotics, the pooled prevalence was 5.8% (95% CI: 3.1–9.1%). In both regions, the highest prevalence was found in oxacillin, ceftriaxone and tetracycline, and a large difference was reported between China and the EU in ceftriaxone (52.6% vs. 17.3%) and cefotaxime (7.0% vs. 0.0%). Based on the above, it remains a significant challenge to enforce good control measures against the meat-sourced L. monocytogenes both in China and in the EU.
Analyzing Urban Travel Behavior Components in Tehran, Iran
Authors: Alizadeh Hadi , Sharifi Ayyoob
Published: February 2023

This research is an attempt to explore the nature and characteristics of urban travel behavior in the metropolitan area of the Iranian capital, Tehran. To this end, using the perspectives of 822 participants via a questionnaire survey, we assessed six major Travel Behavior Components (TBCs)—namely, travel mode, travel time, travel destination, travel frequency, travel choice, and travel purpose—from the lens of five different sociodemographic characteristics—that is, gender, age, family structure, and educational and occupational groups. Using SPSS-26, MAXQDA, and Structural Equation Model (SEM) via AMOS software, we analyzed priorities and preferences related to TBCs across different social groups and explored the impact of preferences of different social groups on TBCs in the Tehran metropolitan area. The results indicate that firstly, the tendency to travel by private transport has the highest share among all groups compared with other modes of travel. Secondly, we identified four major challenges affecting urban travel behavior in Tehran: lacking diverse options for urban traveling, old vehicles and infrastructure, traffic congestion, and unequal access to travel facilities in the city. Finally, we found that sociodemographic characteristics have a relatively strong and significant impact on TBCs. The study highlights the role of sociodemographic characteristics in travel behavior transformations and gives more insights into the travel behavior preferences of urban residents. Such insights would be effective for city policymakers and planners to enhance the quality of urban transportation.
Pluronics-Based Drug Delivery Systems for Flavonoids Anticancer Treatment
Authors: Ronka Sylwia , Kowalczyk Aleksandra , Baczyńska Dagmara , Żołnierczyk Anna K.
Published: February 2023

This research concerns the investigation of the preparation of polymeric nanocarriers containing a flavonoid—naringenin, xanthohumol or isoxanthohumol—based on Pluronics by the thin-film formation method. The size of the formed micelles and their stability upon dilution were evaluated using Dynamic light scattering (DLS) analysis; the high values of the drug loading and the encapsulation efficiency confirmed that the proposed systems of flavonoids delivery consisting of Pluronic P123 and F127 nanomicelles could effectively distribute the drug into tumour tissues, which makes these nanocarriers ideal candidates for passive targeting of cancer cells by the enhanced permeation and retention (EPR) effect. The in vitro cytotoxicity of proposed flavonoids in the Pluronic formulations was investigated by the SRB assay with human colon cancer cells. We designed mixed polymeric micelles, which was a successful drug delivery system for the case of naringenin not being able to enhance the bioavailability and cytotoxic activity of xanthohumol and isoxanthohumol. Furthermore, it was observed that the higher amount of polymer in the formulation achieved better cytotoxic activity.