bluuebunny/crossref_metadata_2025 huggingface dataset:
IoT-Enabled Chlorine Level Assessment and Prediction in Water Monitoring System Using Machine Learning
Authors: Chinnappan Chandru Vignesh , John William Alfred Daniel , Nidamanuri Surya Kalyan Chakravarthy , Jayalakshmi S. , Bogani Ramadevi , Thanapal P. , Syed Shahada , Venkateswarlu Boppudi , Syed Masood Jafar Ali Ibrahim
Published: March 2023

The significance of user participation in sustaining drinking water quality and assessing other factors, such as cleanliness, sanitary conditions, preservation, and waste treatment, is essential for preserving groundwater quality. Inadequate water quality spreads disease, causes mortality, and hinders socioeconomic growth. In addition, disinfectants such as chlorine and fluoride are used to remove pathogens, or disease-causing compounds, from water. After a substantial amount of chlorine has been added to water, its residue causes an issue. Since the proposed methodology is intended to offer a steady supply of drinkable water, its chlorine concentration must be checked in real-time. The suggested model continually updates the sensor hub regarding chlorine concentration measurements. In addition, these data are transmitted over a communication system for data analysis to analyze chlorine levels within the drinking water and residual chlorine percentage over time using a fuzzy set specifically using a decision tree algorithm. Additionally, a performance investigation of the proposed framework is undertaken to determine the efficiency of the existing model for predicting the quantity of chlorine substance employing metrics such as recall, accuracy, F-score, and ROC. Henceforth, the proposed model has substantially better precision than the existing techniques.
Boosting Adversarial Attacks with Nadam Optimizer
Authors: Zhang Qikun , Zhang Yuzhi , Shao Yanling , Liu Mengqi , Li Jianyong , Yuan Junling , Wang Ruifang
Published: March 2023

Deep neural networks are extremely vulnerable to attacks and threats from adversarial examples. These adversarial examples deliberately crafted by attackers can easily fool classification models by adding imperceptibly tiny perturbations on clean images. This brings a great challenge to image security for deep learning. Therefore, studying and designing attack algorithms for generating adversarial examples is essential for building robust models. Moreover, adversarial examples are transferable in that they can mislead multiple different classifiers across models. This makes black-box attacks feasible for practical applications. However, most attack methods have low success rates and weak transferability against black-box models. This is because they often overfit the model during the production of adversarial examples. To address this issue, we propose a Nadam iterative fast gradient method (NAI-FGM), which combines an improved Nadam optimizer with gradient-based iterative attacks. Specifically, we introduce the look-ahead momentum vector and the adaptive learning rate component based on the Momentum Iterative Fast Gradient Sign Method (MI-FGSM). The look-ahead momentum vector is dedicated to making the loss function converge faster and get rid of the poor local maximum. Additionally, the adaptive learning rate component is used to help the adversarial example to converge to a better extreme point by obtaining adaptive update directions according to the current parameters. Furthermore, we also carry out different input transformations to further enhance the attack performance before using NAI-FGM for attack. Finally, we consider attacking the ensemble model. Extensive experiments show that the NAI-FGM has stronger transferability and black-box attack capability than advanced momentum-based iterative attacks. In particular, when using the adversarial examples produced by way of ensemble attack to test the adversarially trained models, the NAI-FGM improves the success rate by 8% to 11% over the other attack methods. Last but not least, the NAI-DI-TI-SI-FGM combined with the input transformation achieves a success rate of 91.3% on average.
Incremental Connected Component Detection for Graph Streams on GPU
Authors: Bok Kyoungsoo , Kim Namyoung , Choi Dojin , Lim Jongtae , Yoo Jaesoo
Published: March 2023

Studies on the real-time detection of connected components in graph streams have been carried out. The existing connected component detection method cannot process connected components incrementally, and the performance deteriorates due to frequent data transmission when GPU is used. In this paper, we propose a new incremental processing method to solve the problems found in the existing methods for detecting connected components on GPUs. The proposed method minimizes the amount of data to be sent to the GPU by determining the subgraph affected by the graph stream update and by detecting the part to be recalculated. We consider the number of vertices to quickly determine the connected components of a graph stream on the GPU. An asynchronous execution method is used to shorten the transfer time between the CPU and the GPU according to real-time graph stream changes. In order to show that the proposed method provides fast incremental connected component detection on the GPU, we evaluated its performance using various datasets.
Ground-Based MIMO-SAR Fast Imaging Algorithm Based on Geometric Transformation
Authors: Dan Qihong , Yu Chunrui , Huang Shisheng , Lai Tao , Huang Haifeng , Chen Wu , Weng Duojie
Published: March 2023

Ground-based multiple-input multiple-output synthetic aperture radar (MIMO-SAR) is a new type of deformation monitoring sensor that has the advantages of no mechanical motion and fast echo acquisition. Ground-based MIMO-SAR can significantly improve the data rate of deformation monitoring. In this paper, a fast imaging algorithm tailored for ground-based MIMO-SAR data is proposed, which can be applied in both far-field and near-field scenarios. First, the phase center approximation error of the non-collinear array in the near field is analyzed. Then, a fast imaging algorithm based on geometric transformation for the coherent synthesis of subimages is put forward. The algorithm uses the geometric transformation to convert the subaperture imaging results into the full aperture coordinate system, which avoids the point-by-point interpolation calculation and further reduces the computational cost of the subimage coherent synthesis algorithm. Simulations and experiments show that the algorithm can achieve high-precision focusing imaging, and its operation efficiency is significantly improved compared with the algorithm based on interpolation.
Real-Time Detection System for Data Exfiltration over DNS Tunneling Using Machine Learning
Authors: Abualghanam Orieb , Alazzam Hadeel , Elshqeirat Basima , Qatawneh Mohammad , Almaiah Mohammed Amin
Published: March 2023

The domain name system (DNS) plays a vital role in network services for name resolution. By default, this service is seldom blocked by security solutions. Thus, it has been exploited for security breaches using the DNS covert channel (tunnel). One of the greatest current data leakage techniques is DNS tunneling, which uses DNS packets to exfiltrate sensitive and confidential data. Data protection against stealthy exfiltration attacks is critical for human beings and organizations. As a result, many security techniques have been proposed to address exfiltration attacks starting with building security policies and ending with designing security solutions, such as firewalls, intrusion detection or prevention, and others. In this paper, a hybrid DNS tunneling detection system has been proposed based on the packet length and selected features for the network traffic. The proposed system takes advantage of the outcome results conducted using the testbed and Tabu-PIO feature selection algorithm. The evolution of the proposed system has already been completed using three distinct datasets. The experimental outcome results show that the proposed hybrid approach achieved 98.3% accuracy and a 97.6% F-score in the DNS tunneling datasets, which outperforms the other related works’ techniques using the same datasets. Moreover, when the packet length was added into the hybrid approach, the run-time shows better results than when Tabu-PIO was used when the size of the data increases.
Selection of the Depth Controller for the Biomimetic Underwater Vehicle
Authors: Przybylski Michał
Published: March 2023

The aim of this paper is to select a depth controller for innovative biomimetic underwater vehicle drives. In the process of optimizing depth controller settings, two classical controllers were used, i.e., the proportional–integral–derivative (PID) and the sliding mode controllers (SM). The parameters of the regulators’ settings were obtained as a result of optimization by three methods of the selected quality indicators in terms of the properties of the control signal. The starting point for the analysis was simulations conducted in the MATLAB environment for the three optimization methods on three types of indicators for three different desired depth values. The article describes the methods and quality indicators in detail. The paper presents the results of the fitness function obtained during the optimization. Moreover, the time courses of the vehicle position relative to the desired depth, the side fin deflection angles, the calculated parameters of the control signals, and the observations and conclusions formulated in the research were presented.
Impact of the High Penetration of Renewable Energy Sources on the Frequency Stability of the Saudi Grid
Authors: Alqahtani Saad , Shaher Abdullah , Garada Ali , Cipcigan Liana
Published: March 2023

The high penetration of inverter-fed renewable energy sources (RESs) in modern energy systems has led to a reduction in the system’s inertial response. This reduction in the rotational inertial response is associated with synchronous generation and might result in a deteriorated frequency response following a power disturbance. This paper investigates the frequency stability of the Kingdom of Saudi Arabia’s (KSA) grid. It includes a description of the changing energy landscape of the KSA’s electricity grid and an investigation of the impact of high penetration levels of inverter-fed RESs on the dynamic behavior of the KSA grid. The impact of RESs has been studied through a simulation of case studies of the future KSA power system using the MATLAB/Simulink simulation software. The frequency stability of the KSA’s power system has been evaluated with various RES levels under peak and base load conditions. The simulation results show that the high penetration levels of RESs dramatically affect the system’s frequency response, especially under off-peak conditions. In addition, the significance of battery energy storage systems (BESSs) for compensating the reduction in the system inertial response has been addressed. The results show the effectiveness of aggregated BESSs for enhancing the system frequency control of the KSA grid.
Resistive Switching Characteristic of Cu Electrode-Based RRAM Device
Authors: Yuan Huanmei , Wan Tianqing , Bai Hao
Published: March 2023

The conductive bridge random access memory (CBRAM) device has been widely studied as a promising candidate for next-generation nonvolatile memory applications, where Cu as an electrode plays an important role in the resistive switching (RS) process. However, most studies only use Cu as one electrode, either the top electrode (TE) or the bottom electrode (BE); it is rarely reported that Cu is used as both TE and BE at the same time. In this study, we fabricated CBRAM devices by using Cu as both the TE and BE, and studied the RS characteristic of these devices. With Al2O3 as the switching layer (5~15 nm), the devices showed good bipolar RS characteristics. The endurance of the device could be as high as 106 cycles and the retention time could be as long as 104 s. The Al2O3 thickness influences the bipolar RS characteristic of the devices including the initial resistance, the forming process, endurance, and retention performance. The Cu electrode-based RRAM devices also present negative bias-suppressed complementary resistive switching (CRS) characteristics, which makes it effective to prevent the sneak path current or crosstalk problem in high-density memory array circuits.
Validation of Estimating Stress from Fracture Injection Tests Using Continuous Wavelet Transform with Experimental Data
Authors: Gabry Mohamed Adel , Eltaleb Ibrahim , Soliman Mohamed Y. , Farouq-Ali S. M.
Published: March 2023

The article discusses the new technique for fracture closure pressure detection using continuous wavelet transform (CWT). The study focuses on calibrating the CWT technique and comparing it with different techniques for closure detection. According to the article, traditional methods for identifying the closure of hydraulic fracturing operations are based on assumptions that can conflict with one another, resulting in greatly varying approximations of closure pressure and duration. To address this issue, the article employs a set of diagnostic fracture injection tests that utilize the Step-Rate Injection Method for Fracture In-Situ Properties tool (SIMFIP). By directly observing wellbore deformation, the SIMFIP tool determines the minimum principal stress, while strain gauges monitor the opening and closing of fractures during multiple tests. The publicly accessible data are used to evaluate the accuracy of the new closure detection technique using CWT. The findings indicate that the CWT method aligns with measurements of deformation and can identify the impact of intricate closure events and pre-existing natural fractures. In conclusion, the article suggests that the CWT technique shows great potential as an alternative to traditional approaches for detecting closure pressure.
An Ageing Test Standards Analysis on Thermoplastic Liners of Type IV Composite Hydrogen Storage Tanks
Authors: Li Jun , Lv Rongrong , Gu Chunlin , Liu Yitao , Li Jiepu , Li Xiang
Published: March 2023

The liner of a carbon fiber fully reinforced composite tank with thermoplastic liner (type IV) works in a hydrogen environment with varying temperature and pressure profiles. The ageing performance of the thermoplastic liner may affect hydrogen permeability and the consequent storage capacity, degrade the mechanical properties, and even increase the leakage risks of type IV tanks. In this paper, both testing procedures and evaluation parameters of an ageing test in a hydrogen environment required in several standards are compared and analyzed. Hydrogen static exposure in a high-temperature condition with a constant temperature and pressure is suggested to be a reasonable way to accelerate the ageing reaction of thermoplastic materials. A total of 192 h is considered a superior ageing test duration to balance the test economy and safety. The ageing test temperature in the high-temperature condition is suggested as no lower than 85 °C, while the upper limit of test pressure is suggested to be 1.25 NWP. In addition, the hydrogen permeation coefficient and mechanical properties are recognized as important parameters in ageing performance evaluation. Considering the actual service conditions, the influence of temperature/pressure cycling, depressurization rate, and humidity on the ageing performance of thermoplastics in hydrogen are advised to be investigated experimentally.
Reliability Testing of Wind Farm Devices Based on the Mean Time to Failures
Authors: Duer Stanisław , Woźniak Marek , Paś Jacek , Zajkowski Konrad , Ostrowski Arkadiusz , Stawowy Marek , Budniak Zbigniew
Published: March 2023

Nowadays, one of the main sources of renewable energy is wind energy; therefore, a wind farm’s electricity system must be effective. As a result, wind farm (WF) equipment must continuously operate without failure or damage. To achieve this, it is necessary to regularly monitor and assess the reliability of WF systems at every point of their “life”, including design, implementation, and continued use. Three key goals are presented in the article. First, a theory of fundamental theoretical quantities that can be used in reliability and maintenance analysis is presented. The second is to put forth a theoretical reliability link between mean time to failure and WF system fitness probability (Mean Time to Failures (MTTF—Mean time between failures. MTTF = t1 + t2 + … + tn/m, where: m—the number of all failures at time T, ti—i—ty time to failure)). The third goal is to analyze the time to failure as a function of service life and to assess the dependability of the WF under consideration as a function of service life. The three-state model of the WF operation process presented in the research serves as the foundation for the analytical analysis of WF reliability. The probability of fitness (Po(t)) of the WF system and the mean time to failure were calculated based on the analytical quantities denoting this model (MTTF). The WF owner can make the best choice regarding the proper WF renewal actions with the help of knowledge of these current dependability values for an in-service WF system.
Aromatic Clusters and Hydrogen Storage
Authors: Mondal Sukanta , Chattaraj Pratim Kumar
Published: March 2023

Concurrence of aromaticity and hydrogen trapping potential of some atomic clusters has drawn the attention of scientific community, although in a few cases it has been reported that the partial charges on the constituent atoms of the clusters are probably responsible for H2 trapping via frail van der Waals type of interactions. In this article, an effort is made to review the studies which address the conjunction of aromaticity and hydrogen storage potential of different atomic clusters and the contribution of our research group to this particular topic.
A Review of Efficient and Low-Carbon Pile Technologies for Extra-Thick Soft Strata
Authors: Zhang Chaozhe , Han Jianyong , Liu Songyu , Cao Zhenglong , Jiang Chen , Diao Xuhan , Chen Guangwei , Tian Li
Published: March 2023

With the development of urban underground space and increased infrastructure functions, both the scale of engineering construction and engineering difficulties have increased globally. In the construction of structures in soft strata, especially in coastal areas, the limited bearing capacity of the foundations poses a significant challenge. The composite pile technologies employing an organic combination of the rigid pile andthe flexible column can enable efficient soft ground treatment. In light of prominent global environmental issues, low-carbon energy-saving curing technologies have been rapidly developed for application in geotechnical engineering. This paper discusses progress in research on the mechanical properties of the efficient and low-carbon pile technologies, including the stiffened deep mixing (SDM) column, squeezed branch pile, pre-bored grouting plated nodular (PGPN) pile, precast cement pile reinforced by cemented soil with a variable section (PCCV), and carbonized composite pile (CCP). In addition, it reviews the technical characteristics and recent progress of feasible low-carbon energy-efficient curing technologies. The paper also proposes future directions for theoretical research and technological development of low-carbon pile technologies. The key contribution of this review is to provide insights into efficient and low-carbon pile technologies. In addition, the findings from the study of the pile technologies used in extra-thick soft strata also provide industry practitioners with a comprehensive guide regarding the specific applications and mechanical performance of the pile technologies, which can serve as a stepping stone to facilitate the technological development of the underground space industry.
Biodiesel Production Catalyzed by Lipase Extract Powder of Leonotis nepetifolia (Christmas Candlestick) Seed
Authors: Ávila Vázquez Verónica , Aguilera Flores Miguel Mauricio , Hernández Casas Luis Felipe , Medellín Castillo Nahum Andrés , Rocha Uribe Alejandro , Correa Aguado Hans Christian
Published: March 2023

This work aimed to evaluate the ability of lipase extract powder obtained from Leonotis nepetifolia seed for enzyme-catalyzed biodiesel production using Leonotis nepetifolia oil, commercial olive oil, and waste cooking oil as substrates. The lipase extract powder showed an enzymatic activity and hydrolysis percentage of 24.7 U/g and 21.31%, respectively, using commercial olive oil as a reference. Transesterification reaction conditions were 40 g of substrate, 34 °C, molar ratio oil: methanol of 1:3, lipase extract powder 20 wt%, phosphates buffer (pH 4.8) 20 wt%, and a reaction time of 8 h. Transesterification yields of 74.5%, 71.5%, and 69.3% for commercial olive oil, waste cooking oil, and Leonotis nepetifolia oil were obtained, respectively. Biodiesel physicochemical parameters were analyzed and compared with the international standards: EN 14214 (European Union) and ASTM D6751 (American Society for Testing and Materials). The biodiesel’s moisture and volatile matter percentages, iodine index, cooper strip corrosion, and methyl esters content conformed to the standards’ specifications. The fatty acid methyl ester content of the vegetable oils showed the presence of methyl oleate after enzyme-catalyzed transesterification. This study reveals that biodiesel production catalyzed by lipase extract powder from Leonotis nepetifolia could be a viable alternative, showing that transesterification yields competitive results.
Review of the Data-Driven Methods for Electricity Fraud Detection in Smart Metering Systems
Authors: Badr Mahmoud , Ibrahem Mohamed , Kholidy Hisham , Fouda Mostafa , Ismail Muhammad
Published: March 2023

In smart grids, homes are equipped with smart meters (SMs) to monitor electricity consumption and report fine-grained readings to electric utility companies for billing and energy management. However, malicious consumers tamper with their SMs to report low readings to reduce their bills. This problem, known as electricity fraud, causes tremendous financial losses to electric utility companies worldwide and threatens the power grid’s stability. To detect electricity fraud, several methods have been proposed in the literature. Among the existing methods, the data-driven methods achieve state-of-art performance. Therefore, in this paper, we study the main existing data-driven electricity fraud detection methods, with emphasis on their pros and cons. We study supervised methods, including wide and deep neural networks and multi-data-source deep learning models, and unsupervised methods, including clustering. Then, we investigate how to preserve the consumers’ privacy, using encryption and federated learning, while enabling electricity fraud detection because it has been shown that fine-grained readings can reveal sensitive information about the consumers’ activities. After that, we investigate how to design robust electricity fraud detectors against adversarial attacks using ensemble learning and model distillation because they enable malicious consumers to evade detection while stealing electricity. Finally, we provide a comprehensive comparison of the existing works, followed by our recommendations for future research directions to enhance electricity fraud detection.
A Comprehensive Examination of Vector-Controlled Induction Motor Drive Techniques
Authors: Aziz Ahmed G. Mahmoud A. , Abdelaziz Almoataz Y. , Ali Ziad M. , Diab Ahmed A. Zaki
Published: March 2023

This paper introduces a comprehensive examination of vector-controlled- (VC-) based techniques intended for induction motor (IM) drives. In addition, the evaluation and critique of modern control techniques that improve the performance of IM drives are discussed by considering a systematic literature survey. Detailed research on variable-speed drive control, for instance, VC and scalar control (SCC), was conducted. The SCC-based systems’ speed and V/f control purposes are clarified in closed and open loops of IM drives. The operations, benefits, and drawbacks of the direct and indirect field-oriented control systems are illustrated. Furthermore, the direct torque control (DTC) method for IMs is reviewed. Numerous VC methods established along with microprocessor/digital control, model reference adaptive control (MRAC), sliding mode control (SMC), and intelligent control (in terms of fuzzy logic (FL) and artificial neural networks (ANNs)) are described and examined. Uncertainties in the IM parameter are a considerable problem in VC drives. Therefore, this problem is addressed, and some studies that attempted to provide solutions are listed. Magnetic saturation and core loss impact are mentioned, as they are important issues in IM drives. Toward demonstrating the strengths and limitations of various VC configurations, a few experiments were simulated via MATLAB® and Simulink® that show the influence of machine parameter variation. Efforts are made to supply powerful guidelines for practicing engineers and researchers in AC drives.
Potential Pathway for Reliable Long-Term CO2 Storage as Clathrate Hydrates in Marine Environments
Authors: Castellani Beatrice
Published: March 2023

A countermeasure to global warming is removing high CO2 amounts from the atmosphere and locating the emitted CO2 into long-term stable carbon storage sites. The sequestration technologies must be reliable, long-lasting, and environmentally friendly. An alternative and innovative approach that may meet the sequestration requirements is CO2 storage as clathrate hydrates in marine environments. Extensive research has been devoted to CO2-CH4 replacement in natural gas hydrates. Another option is the direct formation of CO2 hydrates into deep ocean water or into marine underfloor sediments. This article deals with the positioning of direct hydrate-based CO2 storage among the other traditional geological options and the discussion of new, by-far, state-of-the-art knowledge required for the development of a hydrate-based CO2 storage pathway that is reliable, stable, durable, efficient, and environmentally benign.
A Modified Decentralized Droop Control Method to Eliminate Battery Short-Term Operation in a Hybrid Supercapacitor/Battery Energy Storage System
Authors: Papageorgiou Pavlos , Oureilidis Konstantinos , Tsakiri Anna , Christoforidis Georgios
Published: March 2023

Employment of a battery energy storage system to compensate for the generation-consumption mismatch is a vital element for a resilient microgrid. However, the frequent (i.e., short-term) cyclic activity and the abrupt current variations (i.e., high di/dt) have adverse effects on the energy-type battery’s lifespan. On the other hand, the power-type supercapacitor energy storage system (SCES) has almost zero lifetime degradation when it is subjected to irregular charging/discharging patterns. Therefore, the hybridization between them can reduce battery stress levels. This study proposes a droop control algorithm with multiple segments for a SCES/battery hybrid energy storage system (HESS) that is employed in a solar/wind DC microgrid. The presented control scheme is decentralized since it avoids the central controller (CC) and the communication links between the controllers of SCES and battery units. To eliminate the short-term cyclic operation of the battery, the SCES regulates the bus voltage inside a narrow zone with a droop curve that exploits all its available energy capacity. Inside this zone, the battery is kept inactive. As soon as the bus voltage deviates from this band, the SCES enters the idle mode, and the battery is triggered following a droop curve different for charging or discharging mode to stabilize the bus voltage. To evaluate the effectiveness of the proposed system over a battery-only system and a hybrid SCES/battery system controlled with the classical droop method, a comparative analysis under different scenarios is presented.
An Improved Artificial Ecosystem-Based Optimization Algorithm for Optimal Design of a Hybrid Photovoltaic/Fuel Cell Energy System to Supply A Residential Complex Demand: A Case Study for Kuala Lumpur
Authors: Yang Jing , Chen Yen-Lin , Yee Por Lip , Ku Chin Soon , Babanezhad Manoochehr
Published: March 2023

In this paper, the optimal design of a hybrid energy system (HES), consisting of photovoltaic technology integrated with fuel cells (HPV/FC) and relying on hydrogen storage, is performed to meet the annual demand of a residential complex to find the minimum total net present cost (TNPC), while observing the reliability constraint as the energy-not-supplied probability (ENSP) and considering real meteorological data of the Kuala Lumpur city in Malaysia. The decision variables include the size of system components, which are optimally determined by an improved artificial ecosystem-based optimization algorithm (IAEO). The conventional AEO is improved using the dynamic lens-imaging learning strategy (DLILS) to prevent premature convergence. The results demonstrated that the decrease (increase) of the reliability constraint leads to an increase (decrease) in the TNPC, as well as the cost of electricity (COE). For a maximum reliability constraint of 5%, the results show that the TNPC and COE obtained USD 2.247 million and USD 0.4046 million, respectively. The superior performance of the IAEO has been confirmed with the AEO, particle swarm optimization (PSO), and manta ray foraging optimization (MRFO), with the lowest TNPC and higher reliability. In addition, the effectiveness of the hydrogen tank efficiency and load changes is confirmed in the hybrid system design.
Study on Multi-Scale Characteristics and Influencing Factors of Trade-Offs and Synergies between Ecosystem Services in Jiangxi Province
Authors: Duan Ping , Xu Yongwen , Guo Xi , Luo Zhijun , Zhao Xiaomin
Published: March 2023

The trade-offs and synergies reveal the profit and loss relationship between ecosystem services, which is of great significance to the sustainable development of natural resources. The ecosystem services in Jiangxi Province, such as net primary productivity (NPP), soil conservation (SC) and water yield (WY) during 2000–2020, were estimated in this study. The correlation coefficient was adopted to analyze the trade-offs and synergies between the three ecosystem services by static space correlation and dynamic space correlation from such perspectives as Watershed, county and grid. Moreover, the influence of the three ecosystem services and the relations between them were explored from four aspects: landform, NDVI, accumulated temperature and precipitation. The results showed that the ecological environment quality in Jiangxi Province was improved and that the distribution of ecosystem services had significant regional characteristics. In the static analysis, ecosystem services at all scales were remarkably synergistic, and synergies weakened rapidly and even turned into trade-offs as the scale decreased. In the dynamic analysis, ecosystem services at all scales were mainly synergistic; the proportion of significant samples was much lower than that in the static analysis, the degree of trade-offs/synergies decreased with the decrease in scale, and the decrease was smaller than that in the static analysis. The major constraints for SC were landform and NDVI. The main constraint for WY was precipitation, and that for NPP was NDVI. Affected by various factors, NPP and SC were stably synergistic, NPP and WY were in a stable trade-off relationship, and the relationship between SC and WY was unstable. The trade-offs and synergies changed with factors and zoning.
Patterns of Needle Nutrient Resorption and Ecological Stoichiometry Homeostasis along a Chronosequence of Pinus massoniana Plantations
Authors: Guo Qiqiang , Li Huie , Sun Xueguang , An Zhengfeng , Ding Guijie
Published: March 2023

Nutrient resorption and stoichiometry ratios are vital indicators to explore nutrient transfer and use efficiency for plants, particularly under the condition of nutrient limitation. However, the changing rules about nutrient resorption and ecological stoichiometry homeostasis are still unclear with the development of plantations. We determined carbon (C), nitrogen (N), and phosphorus (P) concentrations in soil and in fresh and senesced needles along a chronosequence of Pinus massoniana plantations (10, 20, 30, and 36 years old) in Guizhou Province, China. We also calculated the N and P resorption efficiency (NRE and PRE, respectively) and the homeostasis coefficient. The results showed that fresh and senesced needles’ C and N concentrations maintained an increasing trend, whereas their P concentrations decreased initially and subsequently increased as the plantations’ ages increased. Fresh needles’ N:P ratios indicated that N limitation existed before 20 years old, while P limitation appeared in the 30-year-old plantations. The NRE and PRE showed patterns of increasing initially and decreasing subsequently along the chronosequence of P. massoniana plantations, which was coupled with weak stoichiometric homeostasis to reduce nutrient deficiency. Therefore, the appropriate nutrient management measurements should be induced to promote tree growth and the sustainable development of P. massoniana plantations.
Spatio-Temporal Variation and Climatic Driving Factors of Vegetation Coverage in the Yellow River Basin from 2001 to 2020 Based on kNDVI
Authors: Feng Xuejuan , Tian Jia , Wang Yingxuan , Wu Jingjing , Liu Jie , Ya Qian , Li Zishuo
Published: March 2023

The Yellow River Basin (YRB) is a fundamental ecological barrier in China and is one of the regions where the ecological environment is relatively fragile. Studying the spatio-temporal variations in vegetation coverage in the YRB and their driving factors through a long-time-series vegetation dataset is of great significance to eco-environmental construction and sustainable development in the YRB. In this study, we sought to characterize the spatio-temporal variation in vegetation coverage and its climatic driving factors in the YRB from 2001 to 2020 by constructing a new kernel normalized difference vegetation index (kNDVI) dataset based on MOD13 A1 V6 data from the Google Earth Engine (GEE) platform. Using Theil–Sen median trend analysis, the Mann–Kendall test, and the Hurst exponent, we investigated the spatio-temporal variation characteristics and future development trends of the vegetation coverage. The climatic driving factors of vegetation coverage in the YRB were obtained via partial correlation analysis and complex correlation analysis of the associations between kNDVI and both temperature and precipitation. The results reveal the following: The spatial distribution pattern of kNDVI in the YRB showed that vegetation coverage was high in the southeast and low in the northwest. Vegetation coverage fluctuated from 2001 to 2020, with a main significant trend of increasing growth at a rate of 0.0995/5a. The response of vegetation to climatic factors was strong in the YRB, with a stronger response to precipitation than to temperature. Additionally, the main driving factors of vegetation coverage in the YRB were found to be non-climatic factors, which were mainly distributed in Henan, southern Shaanxi, Shanxi, western Inner Mongolia, Ningxia, and eastern Gansu. The areas driven by climatic factors were mainly distributed in northern Shaanxi, Shandong, Qinghai, western Gansu, northeastern Inner Mongolia, and Sichuan. Our findings have implications for ecosystem restoration and sustainable development in the YRB.
Fungal Resistance and Leaching Behavior of Wood Treated with Creosote Diluted with a Mixture of Biodiesel and Diesel
Authors: Walker Kathleen , Rajput Himadri , Murray Alexander , Stratton Glenn W. , Murray Gordon , He Quan (Sophia)
Published: March 2023

This study evaluated the effect of biodiesel as a co-solvent with the wood preservative creosote to reduce the amount of hydrocarbon-based carrier utilized. Small blocks of wood were treated at a pilot scale using three different creosote concentrations. The diluent used was a blend of 80% soybean biodiesel and 20% petroleum diesel. The efficacy of creosote was tested against brown rot and white rot fungi. The results of the wood-block test and agar test suggested that there was no significant effect of biodiesel on the efficacy of creosote as a wood preservative. As creosote-treated wood is commonly used for railway ties, its potential impact on the surrounding environment was also assessed by studying the leaching behavior of creosote–biodiesel–diesel blend treated railway ties. Rainfall simulators were used to imitate an exposure of treated wood to a significant amount of rainfall. Wood core drilled from the exposed railway ties and leaching water samples were analyzed for the levels of polycyclic aromatic hydrocarbons (PAHs) and total petroleum hydrocarbons (TPHs). Overall, this study demonstrated that the diluent containing biodiesel had no negative effect on the performance of creosote as a wood preservative and towards the natural environment.
A Dual-Baseline PolInSAR Method for Forest Height and Vertical Profile Function Inversion Based on the Polarization Coherence Tomography Technique
Authors: Zhao Rong , Cao Shicheng , Zhu Jianjun , Fu Longchong , Xie Yanzhou , Zhang Tao , Fu Haiqiang
Published: March 2023

Forest height and vertical structure profile functions can be estimated using polarimetric interferometric synthetic aperture radar (PolInSAR) data based on the random volume over ground (RVoG) model and polarization coherence tomography (PCT) theory, respectively. For each resolution cell, considering different forest vertical scattering structure functions to solve the corresponding forest height, the accuracy of PolInSAR forest height inversion will be improved. In this study, a forest vertical structure profile function and forest height inversion algorithm based on PCT technology was developed by using dual-baseline PolInSAR data. Then the deviation of forest height was corrected according to the inverted forest vertical structure. Finally, the LiDAR and PolInSAR data were employed to verify the proposed method. The experimental results show that the accuracy of the proposed method (tropical forest: RMSE = 5.96 m, boreal forest: RMSE = 3.11 m) is 25.5% and 30.43% higher than that of the dual-baseline RVoG model algorithm (tropical forest: RMSE = 8 m, boreal forest: RMSE = 4.47 m).
Effect of Lipase and Phospholipase A1 on Foaming and Batter Properties of Yolk Contaminated Egg White
Authors: Liu Xiao-Yan , Chen Wei , Wang Cheng-Tao
Published: March 2023

Egg white (EW) is frequently used in bakery products because of its excellent foaming capabilities. However, egg yolk (EY) contamination often degrades the foaming characteristics of EW. The purpose of this study was to investigate the effect of different concentrations of phospholipase A1 (PLPA1) and lipase (LP) on EW. The changes in particle size distribution and potential before and after enzymatic digestion of EW with contaminated 0.5 wt% and 1.0%wt EY were tested. The foaming rate and foam stability were measured after the dispersions were digested with different concentrations of PLPA1 and LP. Additionally, the dispersion samples were used to prepare batter and angel cake, and the modulus, density, and microstructure of the batter were analyzed. Results showed that the potential absolute value increased when the EY was hydrolyzed by PLPA1. The distribution of yolk particle size showed a new aggregation and the average particle size decreased after LP hydrolysis. The dispersion samples hydrolyzed by PLPA1 and LP recovered all the properties of the samples at enzymatic concentrations of 500 U/g and 2500 U/g. This may be attributed to the changes in yolk particles resulting from the enzymatic digestion of EY and the production of amphiphilic lysophospholipids, fatty acids, and glycerol.
Accelerated Accumulation of γ-Aminobutyric Acid and Modifications on Its Metabolic Pathways in Black Rice Grains by Germination under Cold Stress
Authors: Yu Yingjie , Li Min , Li Chunxiao , Niu Meng , Dong Huilong , Zhao Siming , Jia Caihua , Xu Yan
Published: March 2023

Germination can increase γ-aminobutyric acid (GABA) accumulation in grains, but the combined effects of germination and other external stress on rice grains have been little studied. In this investigation, enhanced accumulation of GABA and modification of its metabolic pathways in black rice grains were investigated during germination under cold stress. The combination of cold stress and germination resulted in a greater accumulation of GABA than germination alone. The treatment of cold stress at 0 °C for 1 h and germination for 72 h induced a maximum GABA content of 195.64 mg/100 g, 51.54% higher compared to the control, which was superior to any other treatment. We modified the metabolism of the GABA shunt to the orientation of GABA synthesis, in which the activity of glutamic acid decarboxylase and protease were stimulated. The total content of free amino acid indicated an upward trend as germination prolonged. The degradation of polyamines was partly promoted due to elevated diamine oxidase and polyamine oxidase activity, but the activity of amino-aldehyde dehydrogenase for the direct synthesis of GABA in the pathway was suppressed. The result implied that the GABA shunt might play a major role in enhancing GABA accumulation induced by cold stress and germination rather than the polyamines degradation pathway. This investigation provides a practical reference for GABA accumulation by germination under cold stress and a theoretical basis for the possible mechanism underlying the accelerating action.
From Medical Herb to Functional Food: Development of a Fermented Milk Containing Silybin and Protein from Milk Thistle
Authors: Liu Yanxia , Wu Minghuo , Ren Miaomiao , Bao Haijun , Wang Qing’an , Wang Nan , Sun Shibo , Xu Jianqiang , Yang Xiaojing , Zhao Xu , Bao Yongming , He Gaohong , Xu Weiping
Published: March 2023

Milk thistle is a traditional medicinal herb. Silybin is a medicinal component found in the seed coat of milk thistle, which has liver-protective and anti-cancer properties. Conventional studies have focused on the extraction of silybin with organic reagents, which was inapplicable to the food industry. This study aims to develop a fermented milk containing silybin and protein from the milk thistle seeds. A three step procedure was developed, comprising homogenization of milk thistle seeds, NaHCO3 heat treatment, and microbial fermentation. The silybin was characterized by high performance liquid chromatography, and the protein was quantified and electrophorized. It was found that the homogenization step was essential for the preparation of protein, and the NaHCO3 heat treatment was the crucial step in obtaining silybin. The optimal NaHCO3 treatment settings were 1% NaHCO3, 60°C, and 3 h, and the optimal strains for microbial fermentation were L131 (Rummeliibacillus stabekisii) and RS72 (Lactobacillus plantarum). The silybin yield in the fermented milk reached 11.24–12.14 mg/g seeds, accounting for 72.6–78.4% of the total silybin in the milk thistle seeds, and the protein yield reached 121.8–129.6 mg/g seeds. The fermented milk had a slightly sweet yoghurt-like flavor and could be used as a dietary supplement for silybin and protein.
Relationship between Dietary Polyphenols and Gut Microbiota: New Clues to Improve Cognitive Disorders, Mood Disorders and Circadian Rhythms
Authors: Liu Siyu , Cheng Lu , Liu Yanan , Zhan Shengnan , Wu Zufang , Zhang Xin
Published: March 2023

Cognitive, mood and sleep disorders are common and intractable disorders of the central nervous system, causing great inconvenience to the lives of those affected. The gut–brain axis plays a vital role in studying neurological disorders such as neurodegenerative diseases by acting as a channel for a bidirectional information exchange between the gut microbiota and the nervous system. Dietary polyphenols have received widespread attention because of their excellent biological activity and their wide range of sources, structural diversity and low toxicity. Dietary intervention through the increased intake of dietary polyphenols is an emerging strategy for improving circadian rhythms and treating metabolic disorders. Dietary polyphenols have been shown to play an essential role in regulating intestinal flora, mainly by maintaining the balance of the intestinal flora and enhancing host immunity, thereby suppressing neurodegenerative pathologies. This paper reviewed the bidirectional interactions between the gut microbiota and the brain and their effects on the central nervous system, focusing on dietary polyphenols that regulate circadian rhythms and maintain the health of the central nervous system through the gut–brain axis.
Effects of Ginger and Garlic Powders on the Physicochemical and Microbiological Characteristics of Fruit Juices during Storage
Authors: Prisacaru Ancuța Elena , Ghinea Cristina , Albu Eufrozina , Ursachi Florin
Published: March 2023

Natural preservatives such as garlic and ginger can be added to the formulation of fresh fruit juices to encourage the consumption of health-promoting foods. In this study, the influence of garlic and ginger and the storage conditions on physicochemical and microbiological characteristics of fruit juices were investigated. The fruit juice assortments were produced from apple, apple and pumpkin, and apple and pomegranate and were treated with 0.5 g garlic powder, 0.5 g ginger powder, and 0.25 g mix of garlic and ginger powders. A total of 12 unpasteurized samples were produced, of which 3 were control samples. Samples stored at 20 and 4 °C were analyzed at 0, 3, 6, and 9 days for water activity (aw), pH, titratable acidity (TA), total soluble solids (TSS), electrical conductivity (EC), vitamin C, color parameters, total number of germs, yeasts, and molds, Listeria, Enterobacteriaceae, and Escherichia coli. Results showed that aw, pH, TSS, and vitamin C content decreased during storage of fruit juice samples, while TA increased. The lowest increase in total number of aerobic mesophilic germs was determined for the apple and pumpkin juice with garlic and ginger and apple juice with garlic.
Whole-Cell Biocatalytic Production of Acetoin with an aldC-Overexpressing Lactococcus lactis Using Soybean as Substrate
Authors: Luo Huajun , Liu Weihong , Luo Yiyong , Tu Zongcai , Liu Biqin , Yang Juan
Published: March 2023

Douchi is a traditional Chinese fermented soybean product, in which acetoin is a key flavor substance. Here, the α-acetolactate decarboxylase gene aldC was cloned from Lactiplantibacillus (L.) plantarum and overexpressed in Lactococcus (L.) lactis NZ9000 by nisin induction. The ALDC crude enzyme solution produced an enzyme activity of 35.16 mU. Next, whole cells of the recombinant strain NZ9000/pNZ8048-aldC were employed as the catalyst to produce acetoin in GM17 medium. An optimization experiment showed that an initial OD600 of 0.6, initial pH of 7.5, nisin concentration of 20 ng/mL, induction temperature of 37 °C and static induction for 8 h were the optimal induction conditions, generating the maximum acetoin production (106.93 mg/L). Finally, after incubation under the optimal induction conditions, NZ9000/pNZ8048-aldC was used for whole-cell biocatalytic acetoin production, using soybean as the substrate. The maximum acetoin yield was 79.43 mg/L. To our knowledge, this is the first study in which the aldC gene is overexpressed in L. lactis and whole cells of the recombinant L. lactis are used as a biocatalyst to produce acetoin in soybean. Thus, our study provides a theoretical basis for the preparation of fermented foods containing high levels of acetoin and the biosynthesis of acetoin in food materials.