bluuebunny/crossref_metadata_2025 huggingface dataset:
One-Step, In Situ Hydrothermal Fabrication of Cobalt-Doped ZnO/CdS Nanosheets for Optoelectronic Applications
Authors: Maddi Lakshmiprasad , Vinukonda Khidhirbrahmendra , Gurugubelli Thirumala Rao , Koutavarapu Ravindranadh
Published: March 2023

An in-situ hydrothermal process was used to create Co-doped ZnO/CdS nanosheets in order to examine the effects of the divalent impurity (Co) ions on the structural, morphological, optical, and magnetic characteristics of the test material. For both ZnO and CdS, XRD verified the development of a hexagonal wurtzite structure. SEM, TEM, and HR-TEM studies produced sheet-like morphology. Elemental mapping and XPS examination verified the presence of essential elements (S, Cd, O, Co, and Zn). Co-doping dramatically increased the nanosheets’ ability to absorb light in the visible area. Comparing the bandgap energy to pure ZnO and ZnO/CdS nanocomposites, the bandgap energy (2.59 eV) was well-regulated. The PL spectrum at 577 nm showed a prominent yellow emission band that was attributed to the 4A2g(F) → 4T1g(F) transition. Improvement in the room temperature ferromagnetic properties was observed due to doping of Co2+ ions. Warm white light harvesting was confirmed by the estimated CCT value (3540 K). The test material appears to be suitable for the creation of next-generation optoelectronic devices.
Exploring Personal Data Processing in Video Conferencing Apps
Authors: Achilleos Georgios , Limniotis Konstantinos , Kolokotronis Nicholas
Published: March 2023

The use of video conferencing applications has increased tremendously in recent years, particularly due to the COVID-19 pandemic and the associated restrictions on movements. As a result, the corresponding smart apps have also seen increased usage, leading to a surge in downloads of video conferencing apps. However, this trend has generated several data protection and privacy challenges inherent in the smart mobile ecosystem. This paper aims to study data protection issues in video conferencing apps by statistically and dynamically analyzing the most common such issues in real-time operation on Android platforms. The goal is to determine what these applications do in real time and verify whether they provide users with sufficient information regarding the underlying personal data processes. Our results illustrate that there is still room for improvement in several aspects, mainly because the relevant privacy policies do not always provide users with sufficient information about the underlying personal data processes (especially with respect to data leaks to third parties), which, in turn, raises concerns about compliance with data protection by design and default principles. Specifically, users are often not informed about which personal data are being processed, for what purposes, and whether these processes are necessary (and, if yes, why) or based on their consent. Furthermore, the permissions required by the apps during runtime are not always justified.
Federated Learning-Based Lightweight Two-Factor Authentication Framework with Privacy Preservation for Mobile Sink in the Social IoMT
Authors: Deebak B. D. , Hwang Seong Oun
Published: March 2023

The social Internet of Medical Things (S-IoMT) highly demands dependable and non-invasive device identification and authentication and makes data services more prevalent in a reliable learning system. In real time, healthcare systems consistently acquire, analyze, and transform a few operational intelligence into actionable forms through digitization to capture the sensitive information of the patient. Since the S-IoMT tries to distribute health-related services using IoT devices and wireless technologies, protecting the privacy of data and security of the device is so crucial in any eHealth system. To fulfill the design objectives of eHealth, smart sensing technologies use built-in features of social networking services. Despite being more convenient in its potential use, a significant concern is a security preventing potential threats and infringement. Thus, this paper presents a lightweight two-factor authentication framework (L2FAK) with privacy-preserving functionality, which uses a mobile sink for smart eHealth. Formal and informal analyses prove that the proposed L2FAK can resist cyberattacks such as session stealing, message modification, and denial of service, guaranteeing device protection and data integrity. The learning analysis verifies the features of the physical layer using federated learning layered authentication (FLLA) to learn the data characteristics by exploring the learning framework of neural networks. In the evaluation, the core scenario is implemented on the TensorFlow Federated framework to examine FLLA and other relevant mechanisms on two correlated datasets, namely, MNIST and FashionMNIST. The analytical results show that the proposed FLLA can analyze the protection of privacy features effectively in order to guarantee an accuracy ≈89.83% to 93.41% better than other mechanisms. Lastly, a real-time testbed demonstrates the significance of the proposed L2FAK in achieving better quality metrics, such as transmission efficiency and overhead ratio than other state-of-the-art approaches.
Multi-Inverter Resonance Modal Analysis Based on Decomposed Conductance Model
Authors: Chen Lin , Xu Yonghai , Tao Shun , Wang Tianze , Sun Shuguang
Published: March 2023

The Norton equivalent model based on the transfer function and the frequency domain analysis method for inverter resonance analysis lacks a comprehensive analysis of the resonant characteristics, and more information about the resonant key components and the degree of participation cannot be obtained. In this paper, a decomposed conductance model is proposed to characterize the resonance characteristics of the multi-inverter grid-connected system and the effect of the equivalent control link of the inverter on the resonance in more detail by combining the modal analysis method and the sensitivity analysis method. Firstly, based on αβ coordinates, the conductance division is carried out for the dual-loop inverter control link with the voltage external loop and current internal loop using capacitor-current feedback damping, and the inverter model based on the decomposition conductance is derived. The mathematical model of the multi-inverter grid-connected system is then established. Secondly, the resonance characteristics of the system are analyzed by combining the modal and frequency domain analysis methods when the number of inverters, inverter parameters, and grid-side impedance are changed. Thirdly, the degree of involvement of the system components, especially the equivalent control link of the inverter in resonance conditions, is determined in combination with the proposed model and the sensitivity analysis method, which is the basis for proposing an effective suppression strategy. Finally, a simulation model is built to verify the proposed method and the analysis results.
Developments in Hydrogen Fuel Cells
Authors: Olabi Abdul Ghani , Sayed Enas Taha
Published: March 2023

The rapid growth in fossil fuels has resulted in climate change that needs to be controlled in the near future. Several methods have been proposed to control climate change, including the development of efficient energy conversion devices. Fuel cells are environmentally friendly energy conversion devices that can be fuelled by green hydrogen, with only water as a by-product, or by using different biofuels such as biomass in wastewater, urea in wastewater, biogas from municipal and agricultural wastes, syngas from agriculture wastes, and waste carbon. This editorial discusses the fundamentals of the operation of the fuel cell, and their application in various sectors such as residential, transportation, and power generation.
Peer-to-Peer Energy Trading through Swarm Intelligent Stackelberg Game
Authors: Edussuriya Chathurangi , Marikkar Umar , Wickramasinghe Subash , Jayasinghe Upul , Alawatugoda Janaka
Published: March 2023

The development of smart grids has paved the way for sustainable energy infrastructure to transition towards decentralized energy trading. As intelligent agents, energy sources engage in energy trading based on their energy surplus or deficit. Buyers and sellers (participants) should achieve maximum payoffs in which buyers cut costs and sellers improve their utilities, and the security of sensitive information of smart agents must be guaranteed. This paper provides a blockchain-based energy trading network where intelligent agents can exchange energy in a secure manner, without the intervention of third parties. We model energy trading as a Stackelberg game, ensuring that the platform maximizes social welfare while participants increase their payoffs. Using the inherited characteristics of blockchain technology, a novel decentralized swarm intelligence technique is applied to solve the game while ensuring the privacy of the smart agents’ sensitive information. The numerical analysis demonstrates that the suggested method outperforms the present methods (Constant Utility Optimization, average method...) for optimizing the objectives of each agent by maximizing the sellers’ utilities and reducing the buyers’ costs. In addition, the experimental results demonstrate that it significantly reduces carbon footprint (15%) by enhancing energy exchange between intelligent agents.
Progress of Seepage Law and Development Technologies for Shale Condensate Gas Reservoirs
Authors: Liu Wenchao , Yang Yuejie , Qiao Chengcheng , Liu Chen , Lian Boyu , Yuan Qingwang
Published: March 2023

With the continuous development of conventional oil and gas resources, the strategic transformation of energy structure is imminent. Shale condensate gas reservoir has high development value because of its abundant reserves. However, due to the multi-scale flow of shale gas, adsorption and desorption, the strong stress sensitivity of matrix and fractures, the abnormal condensation phase transition mechanism, high-speed non-Darcy seepage in artificial fractures, and heterogeneity of reservoir and multiphase flows, the multi-scale nonlinear seepage mechanisms are extremely complicated in shale condensate gas reservoirs. A certain theoretical basis for the engineering development can be provided by mastering the percolation law of shale condensate gas reservoirs, such as improvement of productivity prediction and recovery efficiency. The productivity evaluation method of shale condensate gas wells based on empirical method is simple in calculation but poor in reliability. The characteristic curve analysis method has strong reliability but a great dependence on the selection of the seepage model. The artificial intelligence method can deal with complex data and has a high prediction accuracy. Establishing an efficient shale condensate gas reservoir development simulation technology and accurately predicting the production performance of production wells will help to rationally formulate a stable and high-yield mining scheme, so as to obtain better economic benefits.
Optimal Axial-Probe Design for Foucault-Current Tomography: A Global Optimization Approach Based on Linear Sampling Method
Authors: Benaissa Brahim , Khatir Samir , Jouini Mohamed Soufiane , Riahi Mohamed Kamel
Published: March 2023

This paper is concerned with the optimal design of axial probes, commonly used in the Non-Destructive Testing (NDT) of tube boiling in steam generators. The goal is to improve the low-frequency Foucault-current imaging of these deposits by designing a novel probe. The approach uses a combination of an inverse problem solver with global optimization to find the optimal probe characteristics by minimizing a function of merit defined using image processing techniques. The evaluation of the function of merit is computationally intensive and a surrogate optimization approach is used, incorporating a multi-particle search algorithm. The proposed design is validated through numerical experiments and aims to improve the accuracy and efficiency of identifying deposits in steam generator tubes.
Distribution Network Reconfiguration Based on Hybrid Golden Flower Algorithm for Smart Cities Evolution
Authors: Swaminathan Dhivya , Rajagopalan Arul , Montoya Oscar Danilo , Arul Savitha , Grisales-Noreña Luis Fernando
Published: March 2023

Power losses (PL) are one of the most—if not the most—vital concerns in power distribution networks (DN). With respect to sustainability, distribution network reconfiguration (DNR) is an effective course of action to minimize power losses. However, the optimal DNR is usually a non-convex optimization process that necessitates the employment of powerful global optimization methods. This paper proposes a novel hybrid metaheuristic optimization (MO) method called the chaotic golden flower algorithm (CGFA) for PL minimization. As the name implies, the proposed method combines the golden search method with the flower pollination algorithm to multiply their benefits, guarantee the best solution, and reduce convergence time. The performance of the algorithm has been evaluated under different test systems, including the IEEE 33-bus, IEEE 69-bus, and IEEE 119-bus systems and the smart city (SC) network, each of which includes distributed-generation (DG) units and energy storage systems (ESS). In addition, the locations of tie-switches in the DN, which used to be considered as given information in previous studies, are assumed to be variable, and a branch-exchange adaption is included in the reconfiguration process. Furthermore, uncertainty analysis, such as bus and/or line fault conditions, are studied, and the performance of the proposed method is compared with other pioneering MO algorithms with minimal standard deviations ranging from 0.0012 to 0.0101. The case study of SC is considered and the obtained simulation results show the superiority of the algorithm in finding higher PL reduction under different scenarios, with the lowest standard deviations ranging from 0.012 to 0.0432.
Thermodynamic Performance of a Cogeneration Plant Driven by Waste Heat from Cement Kilns Exhaust Gases
Authors: Mungyeko Bisulandu Baby-Jean Robert , Ilinca Adrian , Tsimba Mboko Marcel , Mbozi Mbozi Lucien
Published: March 2023

The dwindling and scarcity of fossil energy sources is the basis of the energy transition, where renewable resources are increasingly valued. The purpose of the cogeneration system studied in this article is to recover the residual heat from the gases coming out of the chimneys of the cement kilns, to produce at the same time the electricity and the heat required for offices and residential houses of cement workers. Cement kilns are reputed to be energy-intensive, generating excessive heat losses. These heat losses are found mainly in the conduction–convective and radiative modes, representing about 26% of the overall heat input to the system. Nevertheless, the gases at the chimney outlet can still have temperatures between 250 and 350 °C, which presents a non-negligible potential for a cogeneration system. This study compares the thermal performance of different cogeneration plant configurations (KCA, KCB, and KCC systems) using the Kalina cycle to determine the best one. Several assumptions were made to reduce the complexity of the model. MATLAB and Excel software were used to solve the system of equations. After extensive analysis of the results, the KCA system showed the best performance, compared to the KCB and KCC systems, with a thermal efficiency of 22.15%, an exergy efficiency of 45.12%, and a net electrical capacity of 2565.03 kWe. Model sensitivity to concentration, temperature, and pressure variations also gave the KCA system the best-performing system. Evaluation of the excess heat flux removed from the process yields values of 7368.20 kW, 7421.86 kW, and 8094.15 kW for the KCA, KCB, and KCC systems. The results of this article serve as a decision support tool for installing the cogeneration system via the Kalina cycle in cement installations.
Enabling Floating Offshore VAWT Design by Coupling OWENS and OpenFAST
Authors: Devin Michael C. , Mendoza Nicole R. , Platt Andrew , Moore Kevin , Jonkman Jason , Ennis Brandon L.
Published: March 2023

Vertical-axis wind turbines (VAWTs) have a long history, with a wide variety of turbine archetypes that have been designed and tested since the 1970s. While few utility-scale VAWTs currently exist, the placement of the generator near the turbine base could make VAWTs advantageous over tradition horizontal-axis wind turbines for floating offshore wind applications via reduced platform costs and improved scaling potential. However, there are currently few numerical design and analysis tools available for VAWTs. One existing engineering toolset for aero-hydro-servo-elastic simulation of VAWTs is the Offshore Wind ENergy Simulator (OWENS), but its current modeling capability for floating systems is non-standard and not ideal. This article describes how OWENS has been coupled to several OpenFAST modules to update and improve modeling of floating offshore VAWTs and discusses the verification of these new capabilities and features. The results of the coupled OWENS verification test agree well with a parallel OpenFAST simulation, validating the new modeling and simulation capabilities in OWENS for floating VAWT applications. These developments will enable the design and optimization of floating offshore VAWTs in the future.
Integration of Stand-Alone Controlled Active Power Filters in Harmonic Power Flow of Radial Distribution Networks
Authors: Rezapour Hamed , Amini MohamadAli , Falaghi Hamid , Lopes António M.
Published: March 2023

Utilization of active power filters (APFs) is the most efficient method to reduce harmonic pollution in distribution networks. Previous approaches utilized APFs in integrated control schemes based on broad data-gathering systems. Since a broad data-gathering system is not available in most practical distribution networks, previously proposed approaches may not readily be implemented. This paper presents the utilization of stand-alone controlled APFs (SACAPFs) in radial distribution networks. Utilizing APFs with a stand-alone control system decreases implementation costs and complexity by making them autonomous and independent of integrated control systems, which are complicated and expensive in practical applications. In this paper, a single SACAPF is modeled as a dependent current source where its injection current is equal in amplitude but opposite in phase compared to the harmonic content of the current passing through the point of common coupling (reference current). Due to the presence of both linear and nonlinear loads in the distribution network, the reference current changes after injection by SACAPF, so it is necessary to modify the injection current until reaching a constant value in the reference current. This is considered via an iterative procedure in the modeling scheme. Operation of multiple SACAPFs is handled using a backward procedure based on a priority list. Simulation results on an IEEE 18-bus test system show the proper operation of the stand-alone control systems for both single and multiple SACAPF implementation. Furthermore, optimal allocation of the proposed SACAPFs is performed in an IEEE 33-bus test network and a 9-bus test network, and the results are discussed and compared with the allocation of integrated control system APFs.
Method Selection for Analyzing the Mesopore Structure of Shale—Using a Combination of Multifractal Theory and Low-Pressure Gas Adsorption
Authors: Wang Meng , Li Zhuo , Liang Zhikai , Jiang Zhenxue , Wu Wei
Published: March 2023

Nitrogen adsorption experiments have been extensively applied to shale pore structure research and evaluation. The pore structure can be quantitatively characterized in accordance with the nitrogen adsorption–desorption isotherm using various calculation models, whereas the results obtained using different models can more effectively indicate the pore characteristics of shale remains unclear. Further, there has not been any unified process in the optimization of calculation models for pore size distribution (PSD). In this study, the Barret–Joyner–Halenda adsorption (BJH-AD) and BJH desorption (BJH-DE) models were used with Longmaxi Formation shale as an example. Subsequently, the density functional theory (DFT) calculations were conducted on different shale lithofacies samples. Next, the pore structure parameters and heterogeneity obtained using different models were compared, and the consistency parameters of different models were obtained in accordance with Cronbach’s alpha. The results indicated that the pore structure parameters obtained using the BJH-AD model were underestimated since the macroscopic thermodynamic theory was not applicable to this study. The DFT model showed multiple peaks in the range of 1–10 nm, whereas the BJH-DE model had a significant artificial peak in the range of 3.8 nm due to the tensile strength effect, thus suggesting that the DFT model is more capable of characterizing the pores with a pore size 10 nm lower than the BJH model. The PSD curves generated using the three models exhibited multifractal characteristics, whereas the results of the heterogeneity achieved using different models were different. Moreover, the consistency of the results of different models can be studied in depth by combining Cronbach’s alpha with various heterogeneity parameters. The DFT model exhibited high consistency in pore structure parameters and pore heterogeneity, thus suggesting that the DFT method of N2 is the optimal physical adsorption data analysis method in the shale mesoporous range. Accordingly, the nitrogen adsorption curve, the hysteresis loop shape, multifractal parameters, and Cronbach’s alpha were integrated to generate a working flow chart of the nitrogen adsorption model for N2-adsorption-model optimization.
Optimal Operation of Park and Ride EV Stations in Island Operation with Model Predictive Control
Authors: Ueda Soichiro , Yona Atsushi , Rangarajan Shriram Srinivasarangan , Collins Edward Randolph , Takahashi Hiroshi , Hemeida Ashraf Mohamed , Senjyu Tomonobu
Published: March 2023

The urgent need to reduce greenhouse gas emissions to achieve a decarbonized society has led to the active introduction of electric vehicles worldwide. Renewable energy sources that do not emit greenhouse gases during charging must also be used. However, the uncertainty in the supply of renewable energy is an issue that needs to be considered in practical applications. Therefore, in this study, we predicted the amount of electricity generated by renewable energy using model predictive control, and we considered the operation of a complete island-operated park and ride EV parking station that does not depend on commercial electricity. To perform appropriate model predictive control, we performed comparative simulations for several different forecast interval cases. Based on the obtained results, we determined the forecast horizon and we simulated the economic impact of implementing EV demand response on the electricity demand side. We found that without demand response, large amounts of electricity are recharged and a very high return on investment can be achieved, but with demand response, the return on investment is faster. The results provide a rationale for encouraging infrastructure development in areas that have not yet adopted electric vehicles.
Best Practice in Battery Energy Storage for Photovoltaic Systems in Low Voltage Distribution Network: A Case Study of Thailand Provincial Electricity Authority Network
Authors: Kitworawut Pairach , Ketjoy Nipon , Suriwong Tawat , Kaewpanha Malinee
Published: March 2023

This research investigated the increases of the voltage profile on the Provincial Electricity Authority (PEA)’s low voltage (LV) network due to the solar photovoltaic (PV) penetration. This study proposed the solution to maintain the voltage profile within the PEA’s standard limitation by using battery energy storage system (BESS) application. The algorithm using bisection method to figure out the optimal size and location of BESS was examined and simulated in different scenarios such as summer/winter and weekend/weekday behaviors. Furthermore, the allocation of a battery in various locations was also considered. DIgSILENT power factory with DPL script and Python are the tools used to cover diverse scenario cases. The results showed that the best practice of how to implement BESS to solve the voltage rise problem was the BESS installation at the distribution transformer and the BESS installation separately at the end of each feeder near the loads. However, the optimal size of BESS installation at the distribution transformer was almost double that of installation at the end of each feeder.
Optimization of Setting Angle Distribution to Suppress Hump Characteristic in Pump Turbine
Authors: Qin Yonglin , Li Deyou , Wang Hongjie , Wei Xianzhu
Published: March 2023

Pump turbines play a quite important role of peak-valley shifting in the grid, and the hump margin is a critical criterion related to the safety and stability of operation in pump mode. Aiming at investigating the influence of runner outlet setting angle distribution on hump performance of a pump turbine, three runners with different linear distributions of setting angle at outlet were proposed, and the corresponding hump performance comparison was analyzed numerically through the SST k-ω turbulent model. The numerical result shows that, compared to the experiment, the relative errors of all simulated performances (energy characteristic, torque characteristic, and efficiency) were within 3%. Moreover, it was found that setting angle distribution modes could lead to a remarkably different performance in the hump region and, for the runner whose setting angle at shroud was 10° larger than that at hub, the hump safety margin could be increased from 4% to 4.5%. Thereafter, the corresponding mechanisms including energy input and hydraulic loss were investigated through the Euler head theory and the entropy method, respectively. It was found that hydraulic loss distribution played a more important role than the input energy on controlling hump performance. Moreover, for the runner with the largest hump margin, the hydraulic loss was distributed more evenly in the decreasing discharge direction, contributing to the elimination of hump performance. In addition, hydraulic loss distribution was calculated through local entropy production rate (LEPR) method. For all proposed runners, when the pump turbine entered the hump region from a normal operation point, the hydraulic loss was mainly concentrated in vaneless areas and guide/stay vane channels, while the runner with a large setting angle at shroud could better control the hydraulic loss distribution in both the spatial location and the discharge varying direction, increasing the hump margin. The design method presented in our paper is more likely to be applied in engineering applications.
Assessment of the Safety of Transport of the Natural Gas–Ammonia Mixture
Authors: Rusin Andrzej , Stolecka-Antczak Katarzyna
Published: March 2023

The decarbonisation of many sectors of the economy, including primarily the energy sector, results in the gradual elimination of hydrocarbon fuels, especially coal. During the transition period, it will be possible to use natural gas, the combustion of which is associated with lower carbon dioxide emissions. Further reduction in this emission is possible with the use of mixtures of natural gas with other gases, e.g., ammonia. Ammonia, widely used in many industries, has recently been described as the emission-free fuel of the future. However, both of these gases are hazardous substances. Natural gas is a flammable gas and ammonia is a toxic gas. This paper presents an assessment of the transport safety of natural gas (methane) and its mixture with ammonia. The uncontrolled release of these substances from a damaged gas pipeline may cause a fire or a toxic hazard. This work presents hazard zones arising in the event of such a failure and determines the impact of various mixture compositions on the level of the potential hazard. The level of risk related to the uncontrolled release of a mixture of natural gas and ammonia was analysed. It has been estimated that for pipelines with a diameter of 400 mm and a low-pressure mixture of methane and ammonia in the proportion of 50/50 v/v, the danger zone with the risk of loss of life above 1 × 10−3 is approximately 50 m. In the case of the same pipelines transmitting the mixture of these high-pressure gases, the high-risk zone may extend to approximately 175 m.
Modelling of the Risk of Budget Variances of Cost Energy Consumption Using Probabilistic Quantification
Authors: Kuźmiński Łukasz , Kes Zdzisław , Draskovic Veselin , Gawlik Andrzej , Rabe Marcin , Widera Katarzyna , Łopatka Agnieszka , Śniegowski Maciej
Published: March 2023

Budgets in organisational units are considered to be traditional management support tools. On the other hand, budgetary control is the essence of control measures, allowing for the increase in the efficiency of an enterprise through appropriate allocation of resources. The methodology used in the analysis of budget variances (obtained as a result of applying budgetary control) undoubtedly influences the management efficiency of almost every organizational unit. The authors indicate a research gap of methodological and application nature in the area of risk measurement in the analysis of budget variances. Therefore, the aim of the article is to create universal and flexible models enabling probabilistic quantification of the risk of budget variance regardless of the nature of the cost, the person budgeting and the budgeting unit. Extreme value theory was used to develop the model. The results of the work are models allowing for the estimation of the limit level of deviation for assumed probabilities and models determining the level of deviation for a given probability level. The application of these models in budgetary control will allow for a synthetic assessment of the degree of budget execution in the company, comparing the quality of budget execution over time as well as between units, defining the limits of materiality of budget variances. For the purpose of model verification, the authors have used budget variances of cost energy consumption, which have been determined on the basis of empirical distributions obtained from data coming from the system of budgetary control implemented at a university located in a larger European city.
Federated-Learning-Based Energy-Efficient Load Balancing for UAV-Enabled MEC System in Vehicular Networks
Authors: Shin Ayoung , Lim Yujin
Published: March 2023

At present, with the intelligence that has been achieved in computer and communication technologies, vehicles can provide many convenient functions to users. However, it is difficult for a vehicle to deal with computationally intensive and latency-sensitive tasks occurring in the vehicle environment by itself. To this end, mobile edge computing (MEC) services have emerged. However, MEC servers (MECSs), which are fixed on the ground, cannot flexibly respond to temporal dynamics where tasks are temporarily increasing, such as commuting time. Therefore, research has examined the provision of edge services using additional unmanned aerial vehicles (UAV) with mobility. Since these UAVs have limited energy and computing power, it is more important to optimize energy efficiency through load balancing than it is for ground MEC servers (MECSs). Moreover, if only certain servers run out of energy, the service coverage of a MEC server (MECS) may be limited. Therefore, all UAV MEC servers (UAV MECSs) need to use energy evenly. Further, in a high-mobility vehicle environment, it is necessary to have effective task migration because the UAV MECS that provides services to the vehicle changes rapidly. Therefore, in this paper, a federated deep Q-network (DQN)-based task migration strategy that considers the load deviation and energy deviation among UAV MECSs is proposed. DQN is used to create a local model for migration optimization for each of the UAV MECSs, and federated learning creates a more effective global model based on the fact that it has common spatial features between adjacent regions. To evaluate the performance of the proposed strategy, the performance is analyzed in terms of delay constraint satisfaction, load deviation, and energy deviation.
Application of Miller Cycle and Net-Zero Fuel(s) to Diesel Engine: Effect on the Performance and NOx Emissions of a Single-Cylinder Engine
Authors: Yang Motong , Wang Yaodong
Published: March 2023

Diesel engines play a very significant role in the automotive industry, but the total emissions of diesel engines are more than 1.8 times that of petrol engines. It is therefore important for diesel engines to control emissions. Theoretically, the Miller cycle can be used to achieve NOx reductions by changing the effective compression ratio, while it has become increasingly popular in recent years with the increasing maturity of current turbocharging technology. Based on Ricardo WAVE software, this paper analyses the NOx emissions and engine performance of diesel engines by modelling and simulating their operation under different loads with two types of Miller cycles (EIVC and LIVC) at different degrees. Simulation of engines operating under different loads allows a more comprehensive study of the effects of the Miller cycle on the engine, and a specific analysis in the context of the actual engine operating environment. The result is that both versions of the Miller cycle are most effective in reducing NOx emissions at 10% load, showing a maximum reduction of 21% for EIVC and 37% for LIVC. However, as the Miller cycle decreases engine power, the paper further investigates the application of turbocharger systems in the EIVC Miller cycle, with results showing a 32% increase in brake power at 10% load and −25% EIVC Miller cycle degree. Both ethanol-fueled diesel-cycle and Miller cycle engines were also analyzed, and a reduction in NOx emissions was observed, as well as hydrogen engine performance and NOx emissions.
Regional Stem Volume Mapping: A Feasibility Assessment of Scaling Tree-Level Estimates
Authors: Malambo Lonesome , Popescu Sorin C. , Rakestraw Jim , Ku Nian-Wei , Owoola Tunde A.
Published: March 2023

Spatially detailed monitoring of forest resources is important for sustainable management but limited by a lack of field measurements. The increasing availability of multisource datasets offers the potential to characterize forest attributes at finer resolutions with regional coverage. This study aimed to assess the potential of mapping stem volume at a 30 m scale in eastern Texas using multisource datasets: airborne lidar, Landsat and LANDFIRE (Landscape Fire and Resource Management Planning Tools Project) datasets. Gradient-boosted trees regression models relating total volume, estimated from airborne lidar measurements and allometric equations, and multitemporal Landsat and LANDFIRE predictors were developed and evaluated. The fitted models showed moderate to high correlation (R2 = 0.52–0.81) with reference stem volume estimates, with higher correlation in pine forests (R2 = 0.70–0.81) than mixed forests (R2 = 0.52–0.67). The models were also precise, with relative percent mean absolute errors (pMAE) of 13.8–21.2%. The estimated volumes also consistently agreed with volumes estimated in independent sites (R2 = 0.51, pMAE = 34.7%) and with US Forest Service Forest Inventory Analysis county-level volume estimates (R2 = 0.93, pBias = −10.3%, pMAE = 11.7%). This study shows the potential of developing regional stem volume products using airborne lidar and multisource datasets, supporting forest productivity and carbon modeling at spatially detailed scales.
Digital Approach to Successful Business Plans in Forestry and Related Fields
Authors: Pavlíková Eva Abramuszkinová , Meňházová Jitka , Lešinskis Kristaps
Published: March 2023

This paper introduces the KABADA (Knowledge Alliance of Business Idea Assessment: Digital Approach) tool, together with the opinions of young people about entrepreneurship, their skills, and their experience with this tool. The focus is on non-business students who study natural sciences, engineering, and other areas at the Faculty of Forestry and Wood Technology at Mendel University in Brno, Czech Republic. The KABADA tool has been developed and tested by a team of international experts. It can be used by a wide audience, including forester management specialists. This structured, web-based platform is based on theoretical research, relevant statistics, and artificial intelligence insights. It guides entrepreneurs through business idea assessment including challenges and opportunities. The research included survey answers from 60 university students before and after using the KABADA tool. The results show that students are interested in entrepreneurship but do not have the knowledge or experience, or support from the curriculum. The majority of the students had no or very low experience with entrepreneurship, no entrepreneurship training, and had not studied entrepreneurship. After using the tool, students declared that they had a higher knowledge of entrepreneurship and the number of students who intended to become an entrepreneur increased. The tool is available online, free of charge.
Parentage Analysis Reveals Unequal Family Sizes during Hatchery Production
Authors: Akers Mary , Quinlan Henry , Johnson Andrew , Baker Edward , Welsh Amy
Published: March 2023

Lake sturgeon (Acipenser fulvescens) is a species of conservation concern that has been stocked in several Great Lakes (North America) rivers. Lake sturgeon were extirpated in the Ontonagon River in Lake Superior and stocking began in 1998. In 2017, gametes were collected from spawning lake sturgeon (9 females, 36 males) caught at the nearby Sturgeon River spawning ground, generating nine family groups using a 1:4 mating design (n = 862). In 2018, gametes were collected from 3 females and 15 males, generating three family groups, and additional collections of drifting fry from the Sturgeon River were reared in the hatchery, resulting in 84 hatchery-produced and 675 wild-caught fry for stocking in the Ontonagon River. The objective of this study was to compare paternal representation and genetic diversity between the two stocking strategies. Parentage analysis based on genetic data from 12 microsatellite loci determined none of the family groups in the hatchery had equal paternal representation (p < 0.001), while wild-produced offspring had equal paternal representation. Despite the larger number of breeders contributing to the wild-caught larvae, there was no significant difference in genetic diversity between the wild-caught larvae and representative hatchery-produced offspring.
The Preparation and Potential Bioactivities of Modified Pectins: A Review
Authors: Jiao Xu , Li Fei , Zhao Jing , Wei Yunlu , Zhang Luyao , Yu Wenjun , Li Quanhong
Published: March 2023

Pectins are complex polysaccharides that are widely found in plant cells and have a variety of bioactivities. However, the high molecular weights (Mw) and complex structures of natural pectins mean that they are difficult for organisms to absorb and utilize, limiting their beneficial effects. The modification of pectins is considered to be an effective method for improving the structural characteristics and promoting the bioactivities of pectins, and even adding new bioactivities to natural pectins. This article reviews the modification methods, including chemical, physical, and enzymatic methods, for natural pectins from the perspective of their basic information, influencing factors, and product identification. Furthermore, the changes caused by modifications to the bioactivities of pectins are elucidated, including their anti-coagulant, anti-oxidant, anti-tumor, immunomodulatory, anti-inflammatory, hypoglycemic, and anti-bacterial activities and the ability to regulate the intestinal environment. Finally, suggestions and perspectives regarding the development of pectin modification are provided.
The Drying Kinetics and CFD Multidomain Model of Cocoa Bean Variety CCN51
Authors: Castillo-Orozco Eduardo , Garavitto Oguier , Saavedra Omar , Mantilla David
Published: March 2023

The CCN51 cocoa bean variety is known for being highly resistant to diseases and temperature variation and for having a relatively low cultivation risk for the producers. In this work, a computational and experimental study is performed to analyze the mass and heat transfer within the bean when dried by forced convection. A proximal composition analysis is conducted on the bean testa and cotyledon, and the distinct thermophysical properties are determined as a function of temperature for an interval between 40 and 70 °C. A multidomain CFD simulation, coupling a conjugate heat transfer with a semiconjugate mass transfer model, is proposed and compared to the experimental results based on the bean temperature and moisture transport. The numerical simulation predicts the drying behavior well and yields average relative errors of 3.5 and 5.2% for the bean core temperature and the moisture content versus the drying time, respectively. The moisture diffusion is found to be the dominant mechanism in the drying process. Moreover, a diffusion approximation model and given kinetic constants present a good prediction of the bean’s drying behavior for constant temperature drying conditions between 40 and 70 °C.
Screening of Lesser-Known Salted–Dried Fish Species for Fatty Acids, Tocols, and Squalene
Authors: Lyashenko Svetlana , Chileh-Chelh Tarik , Rincón-Cervera Miguel Ángel , Lyashenko Svetlana P. , Ishenko Zalina , Denisenko Oleg , Karpenko Valentina , Torres-García Irene , Guil-Guerrero José Luis
Published: March 2023

The fillets and roes of 29 species of dry-salted fishes consumed in Eurasian countries were analyzed for fatty acids (FAs), tocols, and squalene, looking for derived health benefits. FAs were analyzed by GC-FID, and tocols and squalene were analyzed by HPLC-DAD. With some exceptions, docosahexaenoic (DHA, 22:6n-3), eicosapentaenoic (EPA, 20:5n-3), and arachidonic (ARA, 20:4n-6) acids were the prominent polyunsaturated fatty acids (PUFAs). The fillets of Scardinius erythrophthalmus reached the highest amounts of total FAs, ARA, and DHA (23.1, 1.82, and 2.49 mg/100 g). The fillets of Seriola quinqueradiata showed the highest percentages of DHA (34.4% of total FAs). Nutritional quality indices for fish lipids were favorable in all samples, especially the n-6/n-3 PUFA ratio, which was below 1 in most cases. α-Tocopherol was found in all fillets and roes, especially in Cyprinidae and Pleuronectidae species, and the highest value was found in the roes of Abramis brama (5.43 mg/100 g). Most samples contained tocotrienols at trace levels. The fillets of Clupeonella cultriventris contained the highest amounts of squalene (1.83 mg/100 g). Overall, dry-salted fish stand out due to their high concentrations of ARA, EPA, and DHA, as well as for α-tocopherol concentrations in roes.
Preparation, Identification and Preliminary Application of the Fenvalerate Monoclonal Antibody in Six Kinds of Dark Tea
Authors: Wei Kang , Yang Qihui , Wei Yang , Wang Yuanfeng , Xu Naifeng , Wei Xinlin
Published: March 2023

Fenvalerate has the advantages of a broad insecticidal spectrum, high efficiency, low toxicity and low cost, and it is widely used in agriculture, especially in tea, resulting in the accumulation of fenvalerate residues in tea and the environment, posing a serious threat to human health. Therefore, the timely monitoring of fenvalerate residue dynamics is vital for ensuring the health of humans and the ecological environment, and it is necessary for establishing a fast, reliable, accurate and on-site method for detecting fenvalerate residues. Based on the methods of immunology, biochemistry and molecular biology, mammalian spleen cells, myeloma cells and mice were used as experimental materials to establish a rapid detection method of an enzyme-linked immunosorbent assay to detect the residues of fenvalerate in dark tea. Three cell lines—1B6, 2A11 and 5G2—that can stably secrete fenvalerate antibodies were obtained by McAb technology, and their sensitivities (IC50) were 36.6 ng/mL, 24.3 ng/mL and 21.7 ng/mL, respectively. The cross-reaction rates of the pyrethroid structural analogs were all below 0.6%. Six dark teas were used to detect the practical application of fenvalerate monoclonal antibodies. The sensitivity IC50 of the anti-fenvalerate McAb in PBS with 30% methanol is 29.12 ng/mL. Furthermore, a latex microsphere immunochromatographic test strip with an LOD of 10.0 ng/mL and an LDR of 18.9–357 ng/mL was preliminarily developed. A specific and sensitive monoclonal antibody for fenvalerate was successfully prepared and applied to detect fenvalerate in dark teas (Pu‘er tea, Liupao tea, Fu Brick tea, Qingzhuan tea, Enshi dark tea and selenium-enriched Enshi dark tea). A latex microsphere immunochromatographic test strip was developed for the preparation of rapid detection test strips of fenvalerate.
Study on Characteristics and Lignification Mechanism of Postharvest Banana Fruit during Chilling Injury
Authors: Xiao Lu , Jiang Xunyuan , Deng Yicai , Xu Kaihang , Duan Xuewu , Wan Kai , Tang Xuemei
Published: March 2023

The banana is prone to chilling injury (CI) at low temperature and showing a series of chilling symptoms, such as peel browning, etc. Lignification is a response to abiotic stress and senescence, which is an important manifestation of fruits and vegetables during chilling exposure. However, little is known about the lignification of bananas during low-temperature storage. Our study explored the characteristics and lignification mechanism of banana fruits during low-temperature storage by analyzing the changes of chilling symptoms, oxidative stress, cell wall metabolism, microstructures, and gene expression related to lignification. The results showed that CI inhibited post-ripening by effecting the degradation of the cell wall and starch and accelerated senescence by increasing O2− and H2O2 content. For lignification, Phenylalanine ammonia-lyase (PAL) might start the phenylpropanoid pathway of lignin synthesis. Cinnamoyl-CoA reductase 4 (CCR4), cinnamyl alcohol dehydrogenase 2 (CAD2), and 4-coumarate--CoA ligase like 7 (4CL7) were up-regulated to promote the lignin monomer’s synthesis. Peroxidase 1 (POD1) and Laccase 3 (LAC3) were up-regulated to promote the oxidative polymerization of lignin monomers. These results suggest that changes of the cell wall structure and cell wall metabolism, as well as lignification, are involved in the senescence and quality deterioration of the banana after chilling injury.
Decreasing the Crystallinity and Degree of Polymerization of Cellulose Increases Its Susceptibility to Enzymatic Hydrolysis and Fermentation by Colon Microbiota
Authors: Thielemans Karel , De Bondt Yamina , Comer Luke , Raes Jeroen , Everaert Nadia , Sels Bert F. , Courtin Christophe M.
Published: March 2023

Cellulose can be isolated from various raw materials and agricultural side streams and might help to reduce the dietary fiber gap in our diets. However, the physiological benefits of cellulose upon ingestion are limited beyond providing fecal bulk. It is barely fermented by the microbiota in the human colon due to its crystalline character and high degree of polymerization. These properties make cellulose inaccessible to microbial cellulolytic enzymes in the colon. In this study, amorphized and depolymerized cellulose samples with an average degree of polymerization of less than 100 anhydroglucose units and a crystallinity index below 30% were made from microcrystalline cellulose using mechanical treatment and acid hydrolysis. This amorphized and depolymerized cellulose showed enhanced digestibility by a cellulase enzyme blend. Furthermore, the samples were fermented more extensively in batch fermentations using pooled human fecal microbiota, with minimal fermentation degrees up to 45% and a more than eight-fold increase in short-chain fatty acid production. While this enhanced fermentation turned out to be highly dependent on the microbial composition of the fecal pool, the potential of engineering cellulose properties to increased physiological benefit was demonstrated.