bluuebunny/crossref_metadata_2025 huggingface dataset:
The Impact of the COVID-19 Pandemic on the Volume of Fuel Supplies to EU Countries
Authors: Dembińska Izabela , Barczak Agnieszka , Szopik-Depczyńska Katarzyna , Dul Irena , Koliński Adam , Ioppolo Giuseppe
Published: November 2022

The COVID-19 pandemic is undoubtedly a destructive factor, strongly affecting the economic fields. From the perspective of the countries affected by the pandemic, almost all sectors of the economy saw declines in economic indicators. First, the lockdown and its social consequences contributed to this. The increasing time perspective since the outbreak of the COVID-19 pandemic implies increasingly more studies analyzing its impact on various economic spheres. The aim of the research is to determine the difference in the level of fuel supplies between a pandemic situation and a situation where a pandemic would not occur. We assumed that the pandemic is a determinant of the decline in fuel supplies. The subjects of the analysis were the following fuels: kerosene-type jet fuel, gas oil and diesel oil, motor gasoline, and oil products. The countries of the European Union were analyzed. Monthly data from 2015–2021 provided by Eurostat were used for the analyses. The forecasts for 2020–2021 were determined using the exponential smoothing method. The assumption was shown to be accurate in the case of kerosene-type jet fuel, gas oil, and diesel oil. In this case, there was a clear drop in the level of supplies. The analysis of forecasts shows that if it were not for the COVID-19 pandemic, in the years 2020–2021, in accordance with the forecasts obtained, approximately 31,495 thousand tons of kerosene-type jet fuel and 11,396 thousand tons of gas oil and diesel oil would have been additionally supplied to the EU countries. For oil products, supply volumes also decreased, but unlike previously mentioned fuels, supply levels had not recovered to pre-pandemic levels by the end of 2021. On the other hand, the forecast of deliveries indicates the volume of 95,683 thousand tons of oil products.
Optimizing Current Profiles for Efficient Online Estimation of Battery Equivalent Circuit Model Parameters Based on Cramer–Rao Lower Bound
Authors: Pillai Prarthana , Sundaresan Sneha , Pattipati Krishna R. , Balasingam Balakumar
Published: November 2022

Battery management systems (BMS) are important for ensuring the safety, efficiency and reliability of a battery pack. Estimating the internal equivalent circuit model (ECM) parameters of a battery, such as the internal open circuit voltage, battery resistance and relaxation parameters, is a crucial requirement in BMSs. Numerous approaches to estimating ECM parameters have been reported in the literature. However, existing approaches consider ECM identification as a joint estimation problem that estimates the state of charge together with the ECM parameters. In this paper, an approach is presented to decouple the problem into ECM identification alone. Using the proposed approach, the internal open circuit voltage and the ECM parameters can be estimated without requiring the knowledge of the state of charge of the battery. The proposed approach is applied to estimate the open circuit voltage and internal resistance of a battery.
Method Construction and Evaluation: A More Comprehensive and Reliable Classification of Coal Mine Gas Explosion Causes
Authors: Jia Qingsong , Fu Gui , Xie Xuecai , Hu Shihan
Published: November 2022

Coal is an important fossil fuel energy that occupies a high position in the energy use of China and even the world. However, gas explosions are still the deadliest coal mine accident in China, which has long plagued the safety of energy mining. Only through accident cause analysis can we know the exact cause of the accident so as to make targeted policies, safety trainings, etc. However, the lack of detailed accident cause classification in current coal mine gas explosion accidents affects the comprehensiveness and accuracy of energy mining safety strategies. Therefore, in this study, a classification method for coal mine gas explosion accident causes based on the sixth edition 24Model and the three-element classification of gas explosions was proposed. Then, the consistency and validity of the newly established classification system were evaluated based on the three indicators, i.e., observer consistency, content validity, and criterion validity, and the performance of the classification system was verified. The results showed that the classification method exhibits good consistency and validity, and, compared with other classification methods, it can significantly improve the comprehensiveness of accident cause analysis results so as to obtain a more scientific energy mining safety strategy. In addition, the process used in this study to construct the classification and evaluate the performance of the classification is transferable, and it can provide a reference for the construction and evaluation of accident cause classifications in other fields.
Short-Term Electricity Price Forecasting Based on the Two-Layer VMD Decomposition Technique and SSA-LSTM
Authors: Guo Fang , Deng Shangyun , Zheng Weijia , Wen An , Du Jinfeng , Huang Guangshan , Wang Ruiyang
Published: November 2022

Accurate electricity price forecasting (EPF) can provide a necessary basis for market decision making by power market participants to reduce the operating cost of the power system and ensure the system’s stable operation. To address the characteristics of high frequency, strong nonlinearity, and high volatility of electricity prices, this paper proposes a short-term electricity price forecasting model based on a two-layer variational modal decomposition (VMD) technique, using the sparrow search algorithm (SSA) to optimize the long and short-term memory network (LSTM). The original electricity price sequence is decomposed into multiple modal components using VMD. Then, each piece is predicted separately using an SSA-optimized LSTM. For the element with the worst prediction accuracy, IMF-worst is decomposed for a second time using VMD to explore the price characteristics further. Finally, the prediction results of each modal component are reconstructed to obtain the final prediction results. To verify the validity and accuracy of the proposed model, this paper uses data from three electricity markets, Australia, Spain, and France, for validation analysis. The experimental results show that the proposed model has MAPE of 0.39%, 1.58%, and 0.95%, RMSE of 0.25, 0.9, and 0.3, and MAE of 0.19, 0.68, and 0.31 in three different cases, indicating that the proposed model can well handle the nonlinear and non-stationarity characteristics of the electricity price series and has superior forecasting performance.
Traffic Signal Optimization to Improve Sustainability: A Literature Review
Authors: Alshayeb Suhaib , Stevanovic Aleksandar , Mitrovic Nikola , Espino Elio
Published: November 2022

Optimizing traffic signals to improve traffic progression relies on minimizing mobility performance measures (e.g., delays and stops). However, delay and stop minimizations do not necessarily lead to minimal sustainability measures (e.g., fuel consumption and emissions). For that reason, researchers have focused, for decades, on integrating traffic models, signal optimization models, and fuel consumption and emissions models to minimize sustainability metrics while keeping acceptable levels of mobility metrics. Therefore, this paper reviews, classifies, and analyzes studies found in the literature regarding optimizing sustainable traffic signals. This paper provides researchers with a good starting point to further develop solutions which can address sustainable traffic control. To achieve that, this study details the most notable sustainable signal timing optimization studies from six perspectives: traffic models, fuel consumption and emissions models, optimization methods, objective functions, operating conditions, and reported sustainability savings. Outcomes of this research show that the previous studies deployed many combinations of elements from the six-perspective mentioned above, leading to a wide range of fuel consumption and emissions savings. The study also concludes that the available fuel consumption and emissions models are relatively old. Hence, future research is needed to develop new fuel consumption and emissions models based on recently collected data.
A New Ice Quality Prediction Method of Wind Turbine Impeller Based on the Deep Neural Network
Authors: Cui Hongmei , Li Zhongyang , Sun Bingchuan , Fan Teng , Li Yonghao , Luo Lida , Zhang Yong , Wang Jian
Published: November 2022

More and more wind turbines are installed in cold regions because of better wind resources. In these regions, the high humidity and low temperatures in winter will lead to ice accumulation on the wind turbine impeller. A different icing location or mass will lead to different natural frequency variations of the impeller. In order to monitor the icing situation in time and in advance, a method based on depth neural network technology to predict the icing mass is explored and proposed. Natural-environment icing experiments and iced-impeller modal experiments are carried out, aiming at a 600 W wind turbine, respectively. The mapping relationship between the change rate of the natural frequency of the iced impeller at different icing positions and the icing mass is obtained, and the correlation coefficients are all above 0.93. A deep neural network (DNN) prediction model of ice-coating quality for the impeller was constructed with the change rate of the first six-order natural frequencies as the input factor. The results show that the MAE and MSE of the trained model are close to 0. The average prediction error of the DNN model is 4.79%, 9.35%, 3.62%, 1.63%, respectively, under different icing states of the impeller. It can be seen that the DNN shows the best prediction ability among other methods. The smaller the actual ice-covered mass of the impeller, the larger the relative error of the ice-covered mass predicted by the DNN model. In the same ice-covered state, the relative error will decrease gradually with the increase in ice-covered mass. In a word, using the natural frequency change rate to predict the icing quality is feasible and accurate. The research achievements shown here can provide a new idea for wind farms to realize efficient and intelligent icing monitoring and prediction, provide engineering guidance for the wind turbine blade anti-icing and deicing field, and further reduce the negative impact of icing on wind power generation.
Design of Ventilation Systems in a Single-Family House in Terms of Heating Demand and Indoor Environment Quality
Authors: Grygierek Krzysztof , Ferdyn-Grygierek Joanna
Published: November 2022

In buildings with good-quality thermal insulation of external partitions, the main component of the building’s heat balance is the heat demand for ventilation. The reduction of this energy demand cannot be achieved at the expense of thermal comfort of the occupants and indoor air quality. The aim of this article is to analyze the impact of various ventilation strategy (natural and mechanical) on heating demand, thermal comfort, and CO2 concentration in a single-family house located in Poland. The benefits of using fans integrated with the earth tube were tested. The study was based on the numerical energy simulation of a multi-zone building model for the entire calendar year. Contam, EnergyPlus, and Python programs were used to perform calculations. The thermal model was validated on the results of temperature measurements in the building. To obtain the best solutions, the parameters of the systems considered have been optimized with the use of genetic algorithms. Various optimal parameters of the earth tube (diameter, length, and foundation depth) were obtained during this research. The highest number of thermal discomfort hours was obtained in the naturally ventilated building with automatic window opening. This system supplied to the rooms a large amount of cool outdoor air in winter and warm air in summer, causing instantaneous rapid fluctuations in indoor temperature. Supplementing the mechanical ventilation control system with CO2 concentration sensors resulted in a much higher amount of ventilation air supplied to the rooms compared to systems controlled only by temperature sensors, resulting in an increase in heat demand.
Bioelectrochemical Remediation for the Removal of Petroleum Hydrocarbon Contaminants in Soil
Authors: Noori Md Tabish , Thatikayala Dayakar , Min Booki
Published: November 2022

Consistent accumulation of petroleum hydrocarbon (PH) in soil and sediments is a big concern and, thus, warrants a static technology to continuously remediate PH-contaminated soil. Bioelectrochemical systems (BESs) can offer the desired solution using the inimitable metabolic response of electroactive microbes without involving a physiochemical process. To date, a wide range of BES-based applications for PH bioremediations under different environmental conditions is readily available in the literature. Here, the latest development trend in BESs for PH bioremediation is critically analyzed and discussed. The reactor design and operational factors that affect the performance of BESs and their strategic manipulations such as designing novel reactors to improve anodic reactions, enhancing soil physiology (electrical conductivity, mass diffusion, hydraulic conductivity), electrode modifications, operational conditions, microbial communities, etc., are elaborated to fortify the understanding of this technology for future research. Most of the literature noticed that a low mass diffusion condition in soil restricts the microbes from interacting with the contaminant farther to the electrodes. Therefore, more research efforts are warranted, mainly to optimize soil parameters by specific amendments, electrode modifications, optimizing experimental parameters, integrating different technologies, and conducting life cycle and life cycle cost analysis to make this technology viable for field-scale applications.
Energy Analysis and Cost-Effective Design Solutions for a Dual-Source Heat Pump System in Representative Climates in Europe
Authors: Milanowski Maciej , Cazorla-Marín Antonio , Montagud-Montalvá Carla
Published: November 2022

Ground-source heat pumps are an efficient technology for heating and cooling in buildings. However, the main limitation of their widespread application is the borehole heat exchanger’s (BHE) high investment cost. Hybridizing GSHP systems may overcome this limitation. This research work analyzes the long-term energy performance of a dual-source heat pump (DSHP) system, which uses the air or the ground as external heat/sink sources, in three representative European climates. First, a BHE cost-effective design solution is proposed for each climatology; then, a complete energy analysis is carried out, and the optimal source control parameters that best enhance the system performance in each climate are determined with the use of a complete dynamic model of the DSHP system developed in TRNSYS. Simulations were carried out for a 25-year operation period. Results show that the DSHP maintains the efficiency during the simulated period, with deviations lower than 1.7% in all cases. Finally, the source control optimization method results in only slight efficiency gains (<0.35%) but with a stronger effect on the ground/air use ratio (up to 25% use of air in cold climates), reducing the thermal imbalance of the ground and leading to a consequent BHE size length and cost reduction.
Overview of Natural Gas Boiler Optimization Technologies and Potential Applications on Gas Load Balancing Services
Authors: Tsoumalis Georgios I. , Bampos Zafeirios N. , Chatzis Georgios V. , Biskas Pandelis N.
Published: November 2022

Natural gas is a fossil fuel that has been widely used for various purposes, including residential and industrial applications. The combustion of natural gas, despite being more environmentally friendly than other fossil fuels such as petroleum, yields significant amounts of greenhouse gas emissions. Therefore, the optimization of natural gas consumption is a vital process in order to ensure that emission targets are met worldwide. Regarding residential consumption, advancements in terms of boiler technology, such as the usage of condensing boilers, have played a significant role in moving towards this direction. On top of that, the emergence of technologies such as smart homes, Internet of Things, and artificial intelligence provides opportunities for the development of automated optimization solutions, which can utilize data acquired from the boiler and various sensors in real-time, implement consumption forecasting methodologies, and accordingly provide control instructions in order to ensure optimal boiler functionality. Apart from energy consumption minimization, manual and automated optimization solutions can be utilized for balancing purposes, including natural gas demand response, which has not been sufficiently covered in the existing literature, despite its potential for the gas balancing market. Despite the existence of few research works and solutions regarding pure gas DR, the concept of an integrated demand response has been more widely researched, with the existing literature displaying promising results from the co-optimization of natural gas along with other energy sources, such as electricity and heat.
A Normal Behavior-Based Condition Monitoring Method for Wind Turbine Main Bearing Using Dual Attention Mechanism and Bi-LSTM
Authors: Xiao Xiaocong , Liu Jianxun , Liu Deshun , Tang Yufei , Qin Shigang , Zhang Fan
Published: November 2022

As clean and low-carbon energy, wind energy has attracted the attention of many countries. The main bearing in the transmission system of large-scale wind turbines (WTs) is the most important part. The research on the condition monitoring of the main bearing has received more attention from many scholars and the wind industry, and it has become a hot research topic. The existing research on the condition monitoring of the main bearing has the following drawbacks: (1) the existing research assigns the same weight to each condition parameter variable, and the model extracts features indiscriminately; (2) different historical time points of the condition parameter variable are given the same weight, and the influence degree of different historical time points on the current value is not considered; and (3) the existing literature does not consider the operating characteristics of WTs. Different operating conditions have different control strategies, which also determine which condition parameters are artificially controlled. Therefore, to solve the problems above, this paper proposes a novel method for condition monitoring of WT main bearings by applying the dual attention mechanism and Bi-LSTM, named Dual Attention-Based Bi-LSTM (DA-Bi-LSTM). Specifically, two attention calculation modules are designed to extract the important features of different input parameters and the important features of input parameter time series, respectively. Then, the two extracted features are fused, and the Bi-LSTM building block is utilized to perform pre-and post-feature extraction of the fused information. Finally, the extracted features are applied to reconstruct the input data. Extensive experiments verify the performance of the proposed method. Compared with the Bi-LSMT model without adding an attention module, the proposed model achieves 19.78%, 2.17%, and 18.92% improvement in MAE, MAPE, and RMSE, respectively. Compared with the Bi-LSTM model which only considers a single attention mechanism, the proposed model achieves the largest improvement in MAE and RMSE by 28.84% and 30.37%. Furthermore, the proposed model has better stability and better interpretability of the monitoring process.
Numerical Simulation of Spray Combustion with Ultrafine Oxygen Bubbles
Authors: Yamamoto Kazuhiro , Akai Yusei , Hayashi Naoki
Published: November 2022

In this study, we focused on a fuel reforming technology by applying ultrafine oxygen bubble as the pretreatment for in-cylinder combustion s. It is assumed that oxygen is dissolved in the droplets in the form of ultrafine bubbles, and released into air when the decane fuel evaporates. A numerical simulation of the spray combustion was conducted using a PSI-CELL model. We changed the oxygen concentration of the droplets, the initial droplet diameter, and the number of injected droplets per unit time to discuss the ignition time and the temperature field. When there is no oxygen in the fuel droplet, most of the flames are diffusion flames. On the other hand, when oxygen exists in the droplets, premixed flames are formed at the upstream edge of the fuel spray. Due to the effects of ultrafine oxygen bubbles, the ignition time is shortened. However, on the condition that there is only a small amount of oxygen in the fuel droplets, as more fuel is supplied by enlarging the droplet diameter or increasing the number of injected droplets per unit time, the ignition time increases. Thus, when discussing ignition time, the balance between evaporated fuel and oxygen in the gas phase is important.
The Self-Actuating Droplet That Can Turn: A Molecular Dynamics Simulation
Authors: Kong Yalong , Liu Zhigang , Guo Lin , Qiu Yu
Published: November 2022

Water collection remains a fundamental challenge to stable and efficient operation of the solar desalination system. Functional surfaces that can realize self-actuation of droplets have shown great potential in improving droplet dynamics without external energy. Therefore, a surface that can make a droplet move spontaneously along a curve was designed for smart droplet manipulation, and the mechanism of the droplet motion was revealed through molecular dynamics simulations. Influences of the wettability difference between the curved track and the background, the width of curved track, and the temperature were evaluated via simulations. The results show that the surface on which the curved track and the background are both hydrophobic enables a faster actuating velocity of the droplet than the hydrophilic-hydrophobic surface and the hydrophilic-hydrophilic surface. The width of the curved track also affects the actuating velocity of the droplet and increasing the TRACK width can increase the actuating velocity of the droplet. However, actuation of the droplet slows down if the width of the curved track is too large. Overall, the mechanism driving the motion of the droplet along the curve was investigated, which opens new opportunities for the application and manufacturing of water collection in solar desalination.
The Impact of Frequency Support by Wind Turbines on the Small-Signal Stability of Power Systems
Authors: Pepiciello Antonio , Domínguez-García José Luis , Vaccaro Alfredo
Published: November 2022

Rising wind energy integration, accompanied by a decreasing level of system inertia, requires additional sources of ancillary services. Wind turbines based on doubly fed induction generators (DFIGs) can provide inertial and primary frequency support when equipped with specific controls. This paper investigates the effect of frequency support provision by DFIGs on the small-signal stability of power systems. To this end, a modified version of the Kundur two-area test system is employed to analyze different scenarios. Wind energy generation is either added to the existing system or displaces part of the synchronous generation. Simulations show that primary frequency support tends to improve the damping of electromechanical oscillations and deteriorate it for converter control-based ones. On the other hand, the inertial response depends on the control parameters.
Applying the Geodetic Adjustment Method for Positioning in Relation to the Swarm Leader of Underwater Vehicles Based on Course, Speed, and Distance Measurements
Authors: Naus Krzysztof , Piskur Paweł
Published: November 2022

The research consisted of simulating the movement of a single vehicle in relation to the swarm leader on a square-shaped path, taking into account measurement errors characteristic of typical cheap navigation devices and the hydroacoustic system. The research showed that these methods allow for estimating position coordinates with an accuracy of about 0.5 m (RMS) in the case of a calibrated navigation system and about 3.6 m (RMS) in the case of a non-calibrated navigation system. It also showed that it can provide a higher accuracy of estimating position coordinates in terms of abeam angles of the swarm leader (relative bearing equal to approximately ±90°), as well as while ensuring minimizing systematic errors values and proper estimation of mean errors values concerning course and speed measurements.
Heat Transfer and Fluid Circulation of Thermoelectric Fluid through the Fractional Approach Based on Local Kernel
Authors: Al Owidh Maryam , Souayeh Basma , Memon Imran Qasim , Ali Abro Kashif , Alfannakh Huda
Published: November 2022

A thermoelectric effect occurs when a material’s intrinsic property directly converts temperature differences applied across its body into electric voltage. This manuscript presents the prediction for maximum and optimal heat transfer efficiency of a thermoelectric fluid via the non-classical approach of the differential operator. The fractionalized mathematical model is also established to analyze the efficiency and characteristics of thermoelectric fluid through a temperature distribution and velocity field. The comprehensive analytical approach of integral transforms and Cardano’s method are applied to provide analytical solutions that include the dynamic investigation of the temperature distribution and velocity field. A dynamic investigation of the temperature distribution and velocity field of the thermoelectric fluid is explored on the basis of magnetization and anti-magnetization, which describe the behavior for sine and cosine sinusoidal waves. The rheological parameter, i.e., magnetization, suggests that by employing varying magnetic fields, the magnetized intensity generates 34.66% of the magnetic hysteresis during the thermoelectric effect.
Rural–Urban Differences in Solar Renewable Energy Investments Supported by Public Finance in Poland
Authors: Rakowska Joanna , Maciejczak Mariusz , Batyk Iwona M. , Farelnik Eliza
Published: November 2022

The deployment of renewable energy (RE) needs to be policy-driven and supported by public funds. Hence, the aim of this study was to find out whether urban and rural areas benefit from public funds for RE deployment equally and whether factors determining other types of investments also determine investments in RES. To do so, we carried out: (i) comparative analyses of qualitative and quantitative data describing 2642 investments in solar RE supported by the European Union funds and carried out in Poland under operational programmes in 2014–2020; (ii) multiple linear regressions, evaluating the predictions. Findings showed that principles of supporting solar RE investments were the same for all kinds of beneficiaries in both urban and rural areas. However, in rural areas, most RE investments cumulated in eastern, north-eastern and south-eastern parts of Poland, and depended only on few socio-economic characteristics. RE investments in urban areas were dispersed all over the country rather evenly and did not depend on any of the socio-economic characteristics. Individual households appeared to be important silent partners to RE investments carried out by local governments. Thus, future policies should focus on them more to increase the deployment and use of solar RE.
Power System Rotor Angle Stability Enhancement Using Lyapunov-Based Trajectory Tracking Controller and Model Reference Adaptive Control
Authors: Banga-Banga Tswa-wen Pierre-Patrick , Mfoumboulou Yohan Darcy , Kriger Carl
Published: November 2022

It is vital that the synchronous generator rotor angle be kept stable to avoid disastrous consequences such as the loss of synchronism amongst generators within a power system network. Once it is unstable, the time that is taken to remedy this is advised to be 5–10 s for smaller power systems and 15–20 s for larger ones. The instability that is caused by poorly damped Low-Frequency Electromechanical Oscillations (LFEOs) may result in inter-area oscillations, where a group of generators in one area oscillates against those in another area, thus affecting the stability of the entire network. This paper explores two control architectures, namely, a nonlinear Lyapunov-based trajectory tracking controller and a Model Reference Adaptive Controller (MRAC) as options to enhance the stability of the rotor angle. The performance of each of these controllers was assessed under steady-state conditions, and then, the synchronous generator was subjected to Gaussian noise and an impulse. While the first one is aimed at emulating small variations in the system loads that are responsible for inter-area oscillations, the latter one is an attempt to explore their performance for transient stability.
A Novel Approach to Achieve MPPT for Photovoltaic System Based SCADA
Authors: Alhasnawi Bilal Naji , Jasim Basil H. , Alhasnawi Arshad Naji , Sedhom Bishoy E. , Jasim Ali M. , Khalili Azam , Bureš Vladimír , Burgio Alessandro , Siano Pierluigi
Published: November 2022

In this study, an improved artificial intelligence algorithms augmented Internet of Things (IoT)-based maximum power point tracking (MPPT) for photovoltaic (PV) system has been proposed. This will facilitate preventive maintenance, fault detection, and historical analysis of the plant in addition to real-time monitoring. Further, the simulation results validate the improved performance of the suggested method. To demonstrate the superiority of the proposed MPPT algorithm over current methods, such as cuckoo search algorithms and the incremental conductance approach, a performance comparison is offered. The outcomes demonstrate the suggested algorithm’s capability to track the Global Maximum Power Point (GMPP) with quicker convergence and less power oscillations than before. The results clearly show that the artificial intelligence algorithm-based MPPT is capable of tracking the GMPP with an average efficiency of 88%, and an average tracking time of 0.029 s, proving both its viability and effectiveness.
A Design of a 2-DoF Planar Parallel Manipulator with an Electro-Pneumatic Servo-Drive
Authors: Takosoglu Jakub , Janus-Galkiewicz Urszula , Galkiewicz Jarosław
Published: November 2022

This paper presents the design of a planar parallel manipulator with a pneumatic drive. Such manipulators are used in production lines for sorting, selecting, packing, and palletizing workpieces. This paper presents simulation studies of the designed manipulator in Matlab/Simulink software and using the SimMechanics library. A simple kinematics problem and an inverse kinematics problem were solved in order to carry out simulation studies of the designed manipulator. Simulation studies were also carried out on the dynamics of the manipulator using a mathematical model describing the physical phenomena occurring during the operation of the manipulator’s electro-pneumatic servo-drives. The main objective of the simulation study was to determine the manipulator working space and the possibility of positional control of the manipulator end-effector using a fuzzy logic controller.
Active Power Filters and Power Quality
Authors: Maciążek Marcin
Published: November 2022

The transmission of electricity from the source to the load is mainly carried out using a three-phase line [...]
A Model Combining Forest Environment Images and Online Microclimate Data Instead of On-Site Measurements to Predict Phytoncide Emissions
Authors: Choi Yeji , Park Sujin , Kim Soojin , Kim Eunsoo , Kim Geonwoo
Published: November 2022

In the existing phytoncide-prediction process, solar radiation and photosynthetically active radiation (PAR) are difficult microclimate factors to measure on site. We derived a phytoncide-prediction technique that did not require field measurements. Visual indicators extracted from forest images and statistical analysis were used to determine appropriate positioning for forest environment photography to improve the accuracy of the new phytoncide-prediction formula without using field measurements. Indicators were selected from the Automatic Mountain Meteorology Observation System (AMOS) of the Korea Forest Service to replace on-site measured climate data and the phytoncide-prediction equation was derived using them. Based on regression analyses, we found that forest density, leaf area, and light volume above the horizon could replace solar radiation and PAR. In addition, AMOS data obtained at 2 m altitudes yielded suitable variables to replace microclimate data measured on site. The accuracy of the new equation was highest when the surface area in the image accounted for 25% of the total. The new equation was found to have a higher prediction accuracy (71.1%) compared to that of the previous phytoncide-prediction equation (69.1%), which required direct field measurements. Our results allow the public to calculate and predict phytoncide emissions more easily in the future.
The Separation Mechanism of Bamboo Bundles at Cellular Level
Authors: Hao Xiu , Tian Xinchi , Li Shunong , Yang Chunmei , Yu Yanglun , Yu Wenji
Published: November 2022

Bamboo bundles with linear cracks were produced using mechanical treatments that were more environmentally friendly and more efficient than chemical decomposition and steam explosion. This study presented the separation mechanism by analyzing the structure, micro-mechanical properties and chemical constituent of bamboo bundles at the cellular level. The micro X-ray tomography technology (u-CT) morphology of bamboo and bamboo bundles presented that the separation of bamboo bundles was caused by crack propagation, which was related to the structure of the cell types in bamboo. Field emission scanning microscopy (SEM) was performed to observe the appearance of bamboo bundles at the cellular level, which illustrated that the cracks were prone to grow in the middle lamella (ML) in fiber cells and parenchymal cells. The nanoindentation technique and Raman microscopy was used to illustrate that the middle lamella (ML)with low indentation moduli and high lignin content was the weak structure in bamboo. This is interpreted as how the structure and mechanical properties contributed to the separation of the bamboo.
Integrating Analytical Hierarchical Process and Network Optimization Model to Support Decision-Making on Biomass Terminal Selection
Authors: Gautam Shuva , LeBel Luc , Rijal Baburam
Published: November 2022

Forest biomass is an appealing bioenergy feedstock due its renewability, availability and potential to stimulate local economies. It is, however, voluminous, with heterogenous fuel characteristics and uncertainties in its supply. The feasibility of a bioenergy facility is contingent on a secure supply of uniform feedstock; a terminal in the supply chain can be useful in this regard. Biomass can be treated in the terminal to meet quality specifications and stored to overcome seasonality and supply disruptions. Nonetheless, such terminals require a significant capital investment; thus, the decision to use a terminal needs to be made judiciously. The decision process must account for a diverse set of factors that influence the terminal’s effectiveness. These include both quantitative and qualitative factors. The objective of this study is to develop a multi-criteria decision-making framework that takes quantitative and qualitative factors into consideration while selecting a terminal. The framework consists of analytical hierarchy process to analyze qualitative information, and a mixed-integer programming model to evaluate quantitative information including fuel quality (moisture content and thermal value). This hybrid framework was implemented in a case study. It proved to be an effective tool for identifying terminals with the highest potential to generate value for the bioenergy supply chain.
Toward Vulnerability Detection for Ethereum Smart Contracts Using Graph-Matching Network
Authors: Zhang Yujian , Liu Daifu
Published: November 2022

With the blooming of blockchain-based smart contracts in decentralized applications, the security problem of smart contracts has become a critical issue, as vulnerable contracts have resulted in severe financial losses. Existing research works have explored vulnerability detection methods based on fuzzing, symbolic execution, formal verification, and static analysis. In this paper, we propose two static analysis approaches called ASGVulDetector and BASGVulDetector for detecting vulnerabilities in Ethereum smart contacts from source-code and bytecode perspectives, respectively. First, we design a novel intermediate representation called abstract semantic graph (ASG) to capture both syntactic and semantic features from the program. ASG is based on syntax information but enriched by code structures, such as control flow and data flow. Then, we apply two different training models, i.e., graph neural network (GNN) and graph matching network (GMN), to learn the embedding of ASG and measure the similarity of the contract pairs. In this way, vulnerable smart contracts can be identified by calculating the similarity to labeled ones. We conduct extensive experiments to evaluate the superiority of our approaches to state-of-the-art competitors. Specifically, ASGVulDetector improves the best of three source-code-only static analysis tools (i.e., SmartCheck, Slither, and DR-GCN) regarding the F1 score by 12.6% on average, while BASGVulDetector improves that of the three detection tools supporting bytecode (i.e., ContractFuzzer, Oyente, and Securify) regarding the F1 score by 25.6% on average. We also investigate the effectiveness and advantages of the GMN model for detecting vulnerabilities in smart contracts.
Generating Indicators of Disruptive Innovation Using Big Data
Authors: Brackin Roger C. , Jackson Michael J. , Leyshon Andrew , Morley Jeremy G. , Jewitt Sarah
Published: November 2022

Technological evolution and its potential impacts are of significant interest to governments, corporate organizations and for academic enquiry; but assessments of technology progression are often highly subjective. This paper prototypes potential objective measures to assess technology progression using internet-based data. These measures may help reduce the subjective nature of such assessments and, in conjunction with other techniques, reduce the uncertainty of technology progression assessment. The paper examines one part of the technology ecosystem, namely, academic research and publications. It uses analytics performed against a large body of academic paper abstracts and metadata published over 20 years to propose and demonstrate candidate indicators of technology progression. Measures prototyped are: (i) overall occurrence of technologies used over time in research, (ii) the fields in which this use was made; (iii) the geographic spread of specific technologies within research and (iv) the clustering of technology research over time. An outcome of the analysis is an ability to assess the measures of technology progression against a set of inputs and a set of commentaries and forecasts made publicly in the subject area over the last 20 years. The potential automated indicators of research are discussed together with other indicators which might help working groups in assessing technology progression using more quantitative methods.
Malleability and Physicochemical Properties of Industrial Sheet Margarine with Shea Olein after Interesterification
Authors: Gao Houbin , Gao Wei , Yang Xiaomin , Liu Yuanfa , Wang Zhouping
Published: November 2022

The malleability of Industrial Sheet Margarine (ISM) is essential for the formation of consistent layered structures of pastry products. However, there is limited reporting on how to improve the malleability of ISM with zero trans fatty acids (TFA) at an industrial production scale. Therefore, herein, Shea Olein (SHOL), rich in stearic acid C18:0, was employed as a value-added formulation ingredient to replace palm olein (POL) in palm-based formula (palm stearin:palm kernel olein:palm olein, 50:15:35, w/w/w) and the chemical interesterification (CIE) fat as ISM material was performed to improve the application performance. The addition of SHOL improved the crystallization characteristics by increasing the β’ crystal content from 70.86% to 92.29% compared with a POL-added formula. The hardness of the two formulations after CIE decreased by 60% and 65%, respectively, compared with that before CIE due to the decrease of PPP and POP, and the increase of POS and PSS triacylglycerols. Melting profiles, polymorphism, and crystal structures systematically proved the bending and sheeting features and functional properties. The bending abilities and malleability of ISM with SHOL and CIE fats were significantly improved, resulting in a more conducive application performance. The study provided a practical approach to improving the malleability of ISM in industrial-level production.
Dietary DHA Enhanced the Textural Firmness of Common Carp (Cyprinus carpio L.) Fed Plant-Derived Diets through Restraining FoxO1 Pathways
Authors: He Zijie , Xu Chao , Chen Fang , Lou Yunkun , Nie Guoxing , Xie Dizhi
Published: November 2022

Omega-3 fatty acids have a positive effect on the muscle textural firmness of fish, while the intrinsic mechanism is poorly understood. To investigate the potential mechanism of textural modification caused by dietary docosahexaenoic acid ( DHA) in common carp (Cyprinus carpio L.), three plant-derived diets with varying DHA levels (0%, 0.5%, 1%, D1–D3) were prepared to feed juveniles (initial weight 15.27 ± 0.77 g) for 8 weeks, and the muscular texture, fibers density, and transcriptome were analyzed. The results showed that the growth performance, muscular DHA content, fibers density, and texture of the fish fed diets D2 and D3 were significantly ameliorated compared with the fish fed diet D1. The muscular transcriptome profiles indicated that the up-regulated genes of fish fed dietary DHA mainly in response to muscle proliferation, as well as the FoxO pathway, were significantly enriched in the D2 and D3 groups. Consistent with this, the Quantitative Real-Time PCR (qRT-PCR ) assays indicated that the expression of myogenic regulatory factors (myog, myod, mrf4, mrf5) was up-regulated in the high-DHA groups. Additionally, the expression of foxo1 (inhibitor of myofiber development) mRNA was down-regulated, while its negative regulatory pathway (MAPK and PI3K) was activated in the D2 and D3 groups. The results suggested that the DHA supplementation is beneficial to modifying the muscular textural firmness of common carp fed plant-derived diets, which could be attributed to the inhibition of FoxO1 pathways.
The Impact of Different Withering Approaches on the Metabolism of Flavor Compounds in Oolong Tea Leaves
Authors: Wang Yahui , Li Chenxue , Lin Jiaqi , Sun Yun , Wei Shu , Wu Liangyu
Published: November 2022

In this study, complementary metabolomic and proteomic analyses were conducted on the solar- and indoor-withered oolong tea leaves, and freshly plucked leaves as the control, for the purpose to reveal the mechanisms underlying the initial formation of some flavor determinants during the early stage of oolong tea processing. As a result, a total of 978 non-volatile compounds and 152 volatile compounds were identified, the flavonoids and several esters were differently accumulated in various tea samples. In total, 7048 proteins were qualitatively and quantitatively determined, the analysis on pathway enrichment showed that phenylpropanoid, flavonoid metabolisms, and protein processing in endoplasmic reticulum were the major pathways discriminating the different tea samples. The joint protein–metabolite analysis showed that the multiple stresses such as dehydration, heat, and ultra-violet irradiation occurred during the withering step induced the dynamic and distinct changes in the biochemical network in the treated leaves compared to fresh leaves. The significant decreases in flavonoids, xanthine alkaloids, and several amino acids contributed to the alleviation of bitter or astringent taste of withered leaves, although the decomposition of L-theanine resulted in the loss of umami flavor over the solar-withering step. Moreover, the fruity or floral aromas, especially volatile terpenoids and phenylpropanoids/benzenoids, were retained or accumulated in the solar withered leaves, potentially aiding the formation of a better characteristic flavor of oolong tea made by indoor withered tea leaves. Distinct effects of solar- and indoor-withering methods on the flavor determinant formation provide a novel insight into the relationship between the metabolite accumulation and flavor formation during the withering step of oolong tea production.
Parameter Estimation of Dynamic Beer Fermentation Models
Authors: Zamudio Lara Jesús Miguel , Dewasme Laurent , Hernández Escoto Héctor , Vande Wouwer Alain
Published: November 2022

In this study, two dynamic models of beer fermentation are proposed, and their parameters are estimated using experimental data collected during several batch experiments initiated with different sugar concentrations. Biomass, sugar, ethanol, and vicinal diketone concentrations are measured off-line with an analytical system while two on-line immersed probes deliver temperature, ethanol concentration, and carbon dioxide exhaust rate measurements. Before proceeding to the estimation of the unknown model parameters, a structural identifiability analysis is carried out to investigate the measurement configuration and the kinetic model structure. The model predictive capability is investigated in cross-validation, in view of opening up new perspectives for monitoring and control purposes. For instance, the dynamic model could be used as a predictor in receding-horizon observers and controllers.
Carcass Characteristics, Meat Quality and Nutritional Composition of Kadaknath, a Native Chicken Breed of India
Authors: Haunshi Santosh , Devatkal Suresh , Prince Lawrence Leslie Leo , Ullengala Rajkumar , Ramasamy Kannaki , Chatterjee Rudranath
Published: November 2022

The study was carried out to investigate the carcass and meat quality traits and nutritional profile of the meat of the Kadaknath, a unique native chicken breed in comparison with commercial broilers. The yield of the carcass, breast and giblets of the Kadaknath was lesser (p < 0.01), while that of the legs, wings, back, and neck was higher (p < 0.01) than broilers. The meat of the Kadaknath was significantly (p < 0.0001) darker (42.44, 50.92) and more yellow (6.23, 8.99) than broilers. The decline in pH of the meat was lower (p < 0.001) in the Kadaknath compared to broilers. Kadaknath meat had more protein and less fat, moisture and ash content than broilers (p < 0.01). Furthermore, it was richer (p < 0.01) in 11 amino acids, including those which are known to impart a sweet and umami taste, than the meat of broilers (3 amino acids). Both genotypes were almost similar in meeting the daily requirements of indispensable amino acids of adult human. The study concluded that the Kadaknath differed in carcass and meat quality characteristics from the broilers, and the nutritional quality of Kadaknath meat in terms of high protein and less fat and higher content of amino acids (tasty type) was better in Kadaknath meat as compared to broiler meat.