bluuebunny/crossref_metadata_2025 huggingface dataset:
Occlusion-Aware Path Planning to Promote Infrared Positioning Accuracy for Autonomous Driving in a Warehouse
Authors: Li Bai , Tang Shiqi , Zhang Youmin , Zhong Xiang
Published: December 2021

Infrared positioning is a critical module in an indoor autonomous vehicle platform. In an infrared positioning system, the ego vehicle is equipped with an infrared emitter while the infrared receivers are fixed onto the ceiling. The infrared positioning result is accurate only when the number of valid infrared receivers is more than three. An infrared receiver easily becomes invalid if it does not receive light from the infrared emitter due to indoor occlusions. This study proposes an occlusion-aware path planner that enables an autonomous vehicle to navigate toward the occlusion-free part of the drivable area. The planner consists of four layers. In layer one, a homotopic A* path is searched for in the 2D grid map to roughly connect the initial and goal points. In layer two, a curvature-continuous reference line is planned close to the A* path using numerical optimal control. In layer three, a Frenet frame is constructed along the reference line, followed by a search for an occlusion-aware path within that frame via dynamic programming. In layer four, a curvature-continuous path is optimized via quadratic programming within the Frenet frame. A path planned within the Frenet frame may violate the curvature bounds in a real-world Cartesian frame; thus, layer four is implemented through trial and error. Simulation results in CarSim software show that the derived paths reduce the poor positioning risk and are easily tracked by a controller.
Harnessing the Power of Sensors and Machine Learning to Design Smart Fence to Protect Farmlands
Authors: Suman Preetam , Singh Deepak Kumar , Albogamy Fahad R. , Shibee Mohammad
Published: December 2021

Agriculture and animals are two crucial factors for ecological balance. Human–wildlife conflict is increasing day-by-day due to crop damage and livestock depredation by wild animals, causing local farmer’s economic loss resulting in the deepening of poverty. Techniques are needed to stop the crop damage caused by animals. The most prominent technique used to protect crops from animals is fencing, but somehow, it is not a full-proof solution. Most fencing techniques are harmful to animals. Thousands of animals die due to the side effects of fencing techniques, such as electrocution. This paper introduces a virtual fence to solve these issues. The proposed virtual fence is invisible to everyone, because it is an optical fiber sensor cable, which is laid 12-inches-deep in soil. A laser light is used at the start of the fiber sensor cable, and a detector detects at the end of the cable. The technique is based on the reflection of light inside the fiber optic cable. The interferometric technique is used to predict the changes in the pattern of the laser light. The fiber cable sensors are connected to a microprocessor, which can predict the intrusion of any animal. The use of machine learning techniques to pattern detection makes this technique highly efficient. The machine learning algorithms developed for the identification of animals can also classify the animal. The paper proposes an economical and feasible machine-learning-based solution to save crops from animals and to save animals from dangerous fencing. The description of the complete setup of optical fiber sensors, methodology, and machine learning algorithms are covered in this paper. This concept was implemented and regressive tests were carried out. Tests were performed on the data, which were not used for training purposes. Sets of people (50 people in each set) were randomly moved into the fiber optic cable sensor in order to test the effectiveness of the detection. There have been very few instances where the algorithm has been unable to categorize the detections into different animal classes. Three datasets were tested for configuration effectiveness. The complete setup was also tested in a zoo to test the identification of elephants and tigers. The efficiency of identification is 94% for human, 80% for tiger, and 75% for elephant.
Short and Long-Run Causal Effects of CO2 Emissions, Energy Use, GDP and Population Growth: Evidence from India Using the ARDL and VECM Approaches
Authors: Pachiyappan Duraisamy , Ansari Yasmeen , Alam Md Shabbir , Thoudam Prabha , Alagirisamy Kuppusamy , Manigandan Palanisamy
Published: December 2021

This paper investigates the nexus between CO2 emissions (CO2E), GDP, energy use (ENU), and population growth (PG) in India from 1980–2018 by comparing the “vector error correction” model (VECM) and “auto regressive distributed lag” (ARDL). We applied the unit root test, Johansen multi-variate cointegration, and performed a Variance decomposition analysis using the Cholesky approach. The VECM and ARDL-bound testing approaches to cointegration suggest a long-term equilibrium nexus between GDP, energy use, population growth and CO2E. The empirical outcomes show the existence of a long-term equilibrium nexus between the variables. The Granger causality results show that short-term bi-directional causality exists between GDP and ENU, while a uni-directional causality between CO2E and GDP, CO2E and ENU, CO2E and PG, and PG and ENU. Evidence from variance decomposition indicates that 58.4% of the future fluctuations in CO2E are due to changes in ENU, 2.8% of the future fluctuations are due to changes in GDP, and 0.43% of the future fluctuations are due to changes in PG. Finally, the ARDL test results indicate that a 1% increase in PG will lead to a 1.4% increase in CO2E. Our paper addresses some important policy implications.
Performance Analysis of a Floating Photovoltaic System and Estimation of the Evaporation Losses Reduction
Authors: Majumder Arnas , Innamorati Roberto , Frattolillo Andrea , Kumar Amit , Gatto Gianluca
Published: December 2021

Our research aims to achieve dual-positive effects in the presented study by raising photovoltaic (PV) panels over the water surface. With this, target experiments were primarily conducted to evaluate the efficiency increments of the PV panel while reducing its operating temperature through passive convective cooling obtained by raising it over water. The following objective was to estimate the reduction in water evaporation due to the shading effect induced by the panel placed inside the same basin. The performance of two PV panels was analyzed, one used for tests, the other as a reference. The characteristic curves were determined under the local environmental conditions of Cagliari, Italy. The true temperature reduction and efficiency gain calculations of panel P1 due to water cooling was achieved via the measured temperatures and calculated efficiencies of panel P2 at environmental conditions. The water height inside the basin was constantly monitored and maintained at approximately 7.5 cm below panel P1, which covered about 17% of the total water surface area. The presence of water underneath P1 leads to its efficiency increment on average by 2.7% (absolute) and about 17.22% (relative). At the same time, temperature of panel P1 dropped by 2.7 °C on average. The comparative water evaporation study conducted with and without P1 inside the basin showed a 30% reduction in water evaporation.
Cascade Control of the Ground Station Module of an Airborne Wind Energy System
Authors: Uppal Ali Arshad , Fernandes Manuel C. R. M. , Vinha Sérgio , Fontes Fernando A. C. C.
Published: December 2021

An airborne wind energy system (AWES) can harvest stronger wind streams at higher altitudes which are not accessible to conventional wind turbines. The operation of AWES requires a controller for the tethered aircraft/kite module (KM), as well as a controller for the ground station module (GSM). The literature regarding the control of AWES mostly focuses on the trajectory tracking of the KM. However, an advanced control of the GSM is also key to the successful operation of an AWES. In this paper we propose a cascaded control strategy for the GSM of an AWES during the traction or power generation phase. The GSM comprises a winch and a three-phase induction machine (IM), which acts as a generator. In the outer control-loop, an integral sliding mode control (SMC) algorithm is designed to keep the winch velocity at the prescribed level. A detailed stability analysis is also presented for the existence of the SMC for the perturbed winch system. The rotor flux-based field oriented control (RFOC) of the IM constitutes the inner control-loop. Due to the sophisticated RFOC, the decoupled and instantaneous control of torque and rotor flux is made possible using decentralized proportional integral (PI) controllers. The unknown states required to design RFOC are estimated using a discrete time Kalman filter (DKF), which is based on the quasi-linear model of the IM. The designed GSM controller is integrated with an already developed KM, and the AWES is simulated using MATLAB and Simulink. The simulation study shows that the GSM control system exhibits appropriate performance even in the presence of the wind gusts, which account for the external disturbance.
Numerical Study of (Au-Cu)/Water and (Au-Cu)/Ethylene Glycol Hybrid Nanofluids Flow and Heat Transfer over a Stretching Porous Plate
Authors: Rashid Umair , Iqbal Azhar , Alsharif Abdullah
Published: December 2021

The purpose of the study is to investigate the (Au-Cu)/Water and (Au-Cu)/Ethylene glycol hybrid nanofluids flow and heat transfer through a linear stretching porous plate with the effects of thermal radiation, ohmic heating, and viscous dissipation. Similarity transformations technique is used to transform a governing system of partial differential equations into ordinary differential equations. The NDSolve Mathematica program is used to solve the nonlinear ordinary differential equations. Furthermore, the results are compared with the results of homotopy analysis method. The impacts of relevant physical parameters on velocity, temperature, and the Nusselt number are represented in graphical form. The key points indicate that the temperature of (Au-Cu)/water and (Au-Cu)/Ethylene glycol hybrid nanofluids is increased with the effects of Eckert number and magnetic field. The (Au-Cu)/Ethylene glycol hybrid nanofluid also has a greater rate of heat transfer than (Au-Cu)/Water hybrid nanofluid.
A Comparative Feasibility Study of the Use of Hydrogen Produced from Surplus Wind Power for a Gas Turbine Combined Cycle Power Plant
Authors: Pyo Min-Jung , Moon Seong-Won , Kim Tong-Seop
Published: December 2021

Because of the increasing challenges raised by climate change, power generation from renewable energy sources is steadily increasing to reduce greenhouse gas emissions, especially CO2. However, this has escalated concerns about the instability of the power grid and surplus power generated because of the intermittent power output of renewable energy. To resolve these issues, this study investigates two technical options that integrate a power-to-gas (PtG) process using surplus wind power and the gas turbine combined cycle (GTCC). In the first option, hydrogen produced using a power-to-hydrogen (PtH) process is directly used as fuel for the GTCC. In the second, hydrogen from the PtH process is converted into synthetic natural gas by capturing carbon dioxide from the GTCC exhaust, which is used as fuel for the GTCC. An annual operational analysis of a 420-MW-class GTCC was conducted, which shows that the CO2 emissions of the GTCC-PtH and GTCC-PtM plants could be reduced by 95.5% and 89.7%, respectively, in comparison to a conventional GTCC plant. An economic analysis was performed to evaluate the economic feasibility of the two plants using the projected cost data for the year 2030, which showed that the GTCC-PtH would be a more viable option.
Automated Conflict Management Framework Development for Autonomous Aerial and Ground Vehicles
Authors: Sziroczák David , Rohács Daniel
Published: December 2021

The number of aerial- and ground-based unmanned vehicles and operations is expected to significantly expand in the near future. While aviation traditionally has an excellent safety record in managing conflicts, the current approaches will not be able to provide safe and efficient operations in the future. This paper presents the development of a novel framework integrating autonomous aerial and ground vehicles to facilitate short- and mid-term tactical conflict management. The methodology presents the development of a modular web service framework to develop new conflict management algorithms. This new framework is aimed at managing urban and peri-urban traffic of unmanned ground vehicles and assisting the introduction of urban air mobility into the same framework. A set of high-level system requirements is defined. The incremental development of two versions of the system prototype is presented. The discussions highlight the lessons learnt while implementing and testing the conflict management system and the introduced version of the stop-and-go resolution algorithm and defines the identified future development directions. Operation of the system was successfully demonstrated using real hardware. The developed framework implements short- and mid-term conflict management methodologies in a safe, resource efficient and scalable manner and can be used for the further development and the evaluation of various methods integrating aerial- and ground-based autonomous vehicles.
Optimization Algorithm of Effective Stress Coefficient for Permeability
Authors: Zhang Xiaolong , Liu Jianjun , Song Jiecheng
Published: December 2021

The effective stress coefficient for permeability is a significant index for characterizing the variation in permeability with effective stress. The realization of its accuracy is essential for studying the stress sensitivity of oil and gas reservoirs. The determination of the effective stress coefficient for permeability can be mainly evaluated using the cross-plotting or response surface method. Both methods preprocess experimental data and preset a specific function relation, resulting in deviation in the calculation results. To improve the calculation accuracy of the effective stress coefficient for permeability, a 3D surface fitting calculation method was proposed according to the linear effective stress law and continuity hypothesis. The statistical parameters of the aforementioned three methods were compared, and the results showed that the three-dimensional (3D) surface fitting method had the advantages of a high correlation coefficient, low root mean square error, and low residual error. The principal of using the 3D surface fitting method to calculate the effective stress coefficient of permeability was to evaluate the influence of two independent variables on a dependent variable by means of a 3D nonlinear regression. Therefore, the method could be applied to studying the relationship between other physical properties and effective stress.
Interior Heating and Its Influence on Electric Bus Consumption
Authors: Čulík Kristián , Štefancová Vladimíra , Hrudkay Karol , Morgoš Ján
Published: December 2021

This paper focuses on the statistical evaluation of various operating characteristics of electric buses. The data obtained for statistical evaluation come from practice. In this paper, we focus on electricity consumption—an important aspect of electric bus operation. The ambient temperature significantly affects electricity consumption. In this paper, we use applied mathematics—correlation analysis, we accurately identify the effect of temperature on the consumption of the electric bus. Our next goal was to define the relationship between the loss of energy from the battery and driving power. We used regression analysis to describe this relation. Our article also includes an example of the practical use of ANOVA analysis in identifying a statistically significant effect of a particular vehicle on average consumption. We also show results from previous research and compare two different types of electric buses in operation.
Analysis of Stationary- and Synchronous-Reference Frames for Three-Phase Three-Wire Grid-Connected Converter AC Current Regulators
Authors: Costa Israel D. L. , Brandao Danilo I. , Matakas Junior Lourenço , Simões Marcelo G. , Morais Lenin M. F.
Published: December 2021

The current state of the art shows that unbalance and distortion on the voltage waveforms at the terminals of a grid-connected inverter disturb its output currents. This paper compares AC linear current regulators for three-phase three-wire voltage source converters with three different reference frames, namely: (1) natural (abc), (2) orthogonal stationary (αβ), and (3) orthogonal synchronous (dq). The quantitative comparison analysis is based on mathematical models of grid disturbances using the impedance-based analysis, the computational effort assessment, as well as the steady-state and transient performance evaluation based on experimental results. The control scheme devised in the dq-frame has the highest computational effort and inferior performance under negative-sequence voltage disturbances, whereas it shows superior performance under positive-sequence voltages among the reference frames evaluated. In contrast, the stationary natural frame abc has the lowest computational effort due to its straightforward implementation, with similar results in terms of steady-state and transient behavior. The αβ-frame is an intermediate solution in terms of computational cost.
Induction Heating for Variably Sized Ferrous and Non-Ferrous Materials through Load Modulation
Authors: Ramalingam Senthil , Boopthi C. , Ramasamy Sridhar , Ahsan Mominul , Haider Julfikar
Published: December 2021

Induction heating (IH) is a process of heating the electrically conducting materials especially ferromagnetic materials with the help of electromagnetic induction through generating heat in an object by eddy currents. A well-entrenched way of IH is to design a heating system pertaining to the usage of ferromagnetic materials such as stainless steel, iron, etc., which restricts the end user’s choice of using utensils made of ferromagnetic only. This research article proposes a new scheme of induction heating that is equally effective for heating ferromagnetic and non-ferromagnetic materials such as aluminium and copper. This is achieved by having a competent IH system that embodies a series resonant inverter and controller where a competent flexible load modulation (FLM) is deployed. FLM facilitates change in operating frequency in accordance with the type of material chosen for heating. The recent attempts by researchers on all metal IH have not addressed much on the variable shapes and sizes of the material, whereas this research attempts to address that issue as well. The proposed induction heating system is verified for a 2 kW system and is compatible with both industrial and domestic applications.
Big Data Analysis and Research on Fracturing Construction Parameters of Shale Gas Horizontal Wells—A Case Study of Horizontal Wells in Fuling Demonstration Area, China
Authors: Li Minxuan , Cheng Liang , Liu Dehua , Hu Jiani , Zhang Wei , Li Kuidong , Xiao Jialin , Wang Xiaojun , Zhang Feng
Published: December 2021

With the rapid development of computer science and technology, the Chinese petroleum industry has ushered in the era of big data. In this study, by collecting fracturing data from 303 horizontal wells in the Fuling Shale Gas Demonstration Area in China, a series of big data analysis studies was conducted using Pearson’s correlation coefficient, the unweighted pair group with arithmetic means method, and the graphical plate method to determine which is best. The fracturing parameters were determined through a series of big data analysis studies. The big data analysis process is divided into three main steps. The first is data preprocessing to screen out eligible, high-yielding wells. The second is a fracturing parameter correlation clustering analysis to determine the reasonableness of the parameters. The third is a big data panel method analysis of specific fracturing construction parameters to determine the optimal parameter range. The analyses revealed that the current amount of 100 mesh sand in the Fuling area is unreasonable; further, there are different preferred areas for different fracturing construction parameters. We have combined different fracturing parameter schemes by preferring areas. This analysis process is expected to provide new ideas regarding fracturing scheme design for engineers working on the frontline.
Mathematical Description of Energy Transition Scenarios Based on the Latest Technologies and Trends
Authors: Akaev Askar A. , Davydova Olga I.
Published: December 2021

This work, dedicated to a mathematical description of energy transition scenarios, consists of three main parts. The first part describes modern trends and problems of the energy sector. A large number of charts reflecting the latest updates in energy are provided. The COVID-2019 pandemic’s impacts on the energy sector are also included. The second part of the paper is dedicated to the analysis of energy consumption and the structure of the world fuel and energy balance. Furthermore, a detailed description of energy-efficient technologies is given. Being important and low-carbon, hydrogen is discussed, including its advantages and disadvantages. The last part of the work describes the mathematical tool developed by the authors. The high availability of statistical data made it possible to identify parameters used in the algorithm with the least squares method and verify the tool. Performing several not complicated steps of the algorithm, the tool allows calculating the deviation of the average global temperature of the surface atmosphere from preindustrial levels in the 21st century under different scenarios. Using the suggested mathematical description, the optimal scenario that makes it possible to keep global warming at a level below 1.7 °C was found.
Will the Reduction of CO2 Emissions Lower the Cost of Debt Financing? The Case of EU Countries
Authors: Kozak Sylwester
Published: December 2021

The main objective of this article is to test the relationship between the intensity of CO2 emissions and company’s cost of debt capital. This study fills a gap in the financial literature on this compound by examining a sample of 225 large nonfinancial enterprises operating in 15 EU countries in the years 2018–2021. The fractional logit regression controlling for company’s characteristics (assets, profitability, liquidity and leverage) was used. The results show that by reducing the intensity of CO2 emissions, a company can reduce the cost of debt. This relationship was confirmed for three measures of intensity, i.e., CO2 emissions in relation to revenues, assets and number of employees. Markets and financial institutions impose an additional risk premium in relation to companies operating in an industry considered to be comprised of strong CO2 emitters. The use of the latest data for a wide sample of European enterprises provides an up-to-date assessment of the analyzed issues and the results can be used by enterprises and public authorities when analyzing the benefits of implementing a technology that reduces CO2 emissions.
Analysis of Biological Degradation and Life Cycle Indicators of Mineral Diesel Fuel Mixtures, Containing 10% Biodiesel, Obtained by Simultaneous Oil Extraction and Transesterification
Authors: Makareviciene Violeta , Santaraite Migle , Sendzikiene Egle
Published: December 2021

This article provides data on the environmental properties of biofuels obtained by the simultaneous extraction of oil from spoiled rapeseed and transesterification, with the addition of mineral diesel to the reaction mixture. The resulting reaction product contained 10% biodiesel: fatty acid methyl, ethyl, or butyl esters in mixtures with mineral diesel. The addition of biodiesel has been found to increase the rate of biodegradation of fuels. Such fuels are classified as partially biodegradable, according to the OECD classification. Life cycle analysis showed that the mixtures of biodiesel and mineral diesel have lower negative environmental impacts, compared to pure mineral diesel. The values of indicators such as abiotic depletion, acidification, global warming, ozone depletion, and human toxicity for these mixtures were 40–58% lower compared to the corresponding values for mineral diesel.
Optimal Individual Phase Voltage Regulation Strategies in Active Distribution Networks with High PV Penetration Using the Sparrow Search Algorithm
Authors: Lee Yih-Der , Lin Wei-Chen , Jiang Jheng-Lun , Cai Jia-Hao , Huang Wei-Tzer , Yao Kai-Chao
Published: December 2021

This study aimed to propose individual phase voltage regulation strategies using the sparrow search algorithm (SSA) in the IEEE 8500-node large-scale unbalanced distribution network with high photovoltaic (PV) penetration. The proposed approach is capable of individual phase regulation, which coordinates the on-load tap changer (OLTC), voltage regulator (VR), switched capacitor bank (SCB), and volt–var setting controlled by a smart inverter to improve voltage variation and unbalance. Consequently, the change time of VRs, the switched times of SCBs, and the individual phase voltage magnitude and unbalance ratio are considered in the fitness function for the SSA. The simulation scenarios fully consider the unbalanced load conditions and PV power output patterns, and the numerical results demonstrate that the voltage variation and unbalance are clearly improved, by 15% and 26%, respectively. The fitness values, operation times of OLTC, VR, and SCB, and the settings of the volt–var controlled smart inverter are also optimized by the SSA. The outcomes of this study are helpful for distribution system operators in formulating voltage control strategies corresponding to different system conditions.
Project Portfolio Selection of Solar Energy by Photovoltaic Generation Using Gini-CAPM Multi-Criteria and Considering ROI Covariations
Authors: Isaias José Claudio , Balestrassi Pedro Paulo , Marcondes Guilherme Augusto Barucke , Silva Wesley Vieira da , Pereira Mello Carlos Henrique , Veiga Claudimar Pereira da
Published: December 2021

For some time, renewable solar energy generations using cellular photovoltaic panels have stood out among the options, especially in the segment of micro and small companies, where the return on investment is usually higher. In this context, when micro and small companies do not have the capital for the enterprises, several others, mainly small ones, have emerged to finance. However, significant difficulties occur for financiers in selecting investment portfolios, especially when considering the trade-off between return and risk and the covariations of return on investment, which are very common. In this type of selection, the Capital Asset Pricing Model criteria using the Gini risk can help significantly because this one is a more robust risk coefficient for assessments of non-normal probability distributions. However, searches for methods that meet the selection needs using the adjacent criteria are unsuccessful. Thus, this work seeks to help minimize the gap by presenting a new method for selection using the criteria. Historical and simulations data stochastic evaluations indicate that the portfolios selected by the method are attractive options for implementations. These portfolios have reasonable probabilistic expectations and satisfactory protection to avoid mistakes caused for not considering covariations in return on investment, which indicates a significant advance on the current knowledge frontier and will likely allow the increased use of the concept. The method also presents theoretical contributions in adaptations of the benchmark models, which help to minimize the adjacent literary gap of similar methods.
CFD Study on the Ventilation Effectiveness in a Public Toilet under Three Ventilation Methods
Authors: Zhang Zhonghua , Zeng Lingjie , Shi Huixian , Liu Hua , Yin Wenjun , Shen Haowen , Yang Libin , Gao Jun , Wang Lina , Zhang Yalei , Zhou Xuefei
Published: December 2021

The indoor air quality (IAQ) of severely polluted toilets is associated with the transmission of diseases. Computational fluid dynamics (CFD) methods and experimental measurements were used to analyze the diffusion characteristics of pollutants. This study investigated the diffusion characteristics and normalized concentration of ammonia and hydrogen sulfide pollutants under three ventilation systems—mixing ventilation (MV), personalized ventilation (PV), and impinging jet ventilation (IJV)—in a public toilet. The mean age of air (MAA) and air exchange efficiency (AEE) were also analyzed in our study. The results show that the MV scheme has a poor removal effect on pollutants compared with PV and IJV. IJV has advantages in reducing the normalized concentration of pollutants and improving the IAQ. Increasing the number of air changes per hour (ACH) may lead to a longer MAA and reduced air exchange efficiency. Choosing an appropriate number of air changes is very important to improve the IAQ in the toilet.
Commercial Aircraft Electrification—Current State and Future Scope
Authors: Tom Liya , Khowja Muhammad , Vakil Gaurang , Gerada Chris
Published: December 2021

Electric and hybrid-electric aircraft propulsion are rapidly revolutionising mobility technologies. Air travel has become a major focus point with respect to reducing greenhouse gas emissions. The electrification of aircraft components can bring several benefits such as reduced mass, environmental impact, fuel consumption, increased reliability and quicker failure resolution. Propulsion, actuation and power generation are the three key areas of focus in more electric aircraft technologies, due to the increasing demand for power-dense, efficient and fault-tolerant flight components. The necessity of having environmentally friendly aircraft systems has promoted the aerospace industry to use electrically powered drive systems, rather than the conventional mechanical, pneumatic or hydraulic systems. In this context, this paper reviews the current state of art and future advances in more electric technologies, in conjunction with a number of industrially relevant discussions. In this study, a permanent magnet motor was identified as the most efficient machine for aircraft subsystems. It is found to be 78% and 60% more power dense than switch-reluctant and induction machines. Several development methods to close the gap between existing and future design were also analysed, including the embedded cooling system, high-thermal-conductivity insulation materials, thin-gauge and high-strength electrical steel and integrated motor drive topology.
Importance of Machine Modernization in Energy Efficiency Management of Manufacturing Companies
Authors: Górska Monika , Daroń Marta
Published: December 2021

Saving energy and looking for alternative energy sources are both elements of energy efficiency management, which is still a significant challenge for many companies around the world. Unfortunately, energy efficiency in companies is often equated only with thermo-modernization or the replacement of lighting. However, one of the most important methods of improving energy use in manufacturing companies may be the modernization of the machine park. Therefore, the main purpose of the paper was to investigate the activities of enterprises in the field of the modernization of machines and the impact of this on the actual improvement of energy efficiency. The modernization of machines in production plants is understood as adapting new parts to the old device or rebuilding the machine in such a way that it can cooperate with its new subassemblies. Companies usually decide to modernize the machinery fleet, bearing in mind the benefits of production efficiency, and they do not always combine this modernization with energy efficiency improvement measures. This is confirmed by the presented results of a survey conducted with a group of 111 manufacturing companies. Several important statistical relationships in the studied area were indicated by conducting an analysis based on the chi-square test and, in some cases, by clarifying the results of the z-test with the Bonferroni correction.
Characterizing the Utility of the Root-to-Shoot Ratio in Douglas-Fir Seedling Production
Authors: Sheridan Rebecca A. , Davis Anthony S.
Published: December 2021

Nursery-grown tree seedlings are a vital component of successful restoration and reforestation programs, useful when calls for increased planting for industrial forest management are made, and a tool for climate change mitigation. One of the most extensively planted and studied trees in Western North America is Douglas-fir. Building on that body of work, this review was conducted to identify if the root-to-shoot ratio (root:shoot, R:S), a commonly referred-to metric in reforestation planning, yields meaningful guidance for producing seedlings that are better able to establish across a variety of field conditions. The results indicated that there is wide variability in R:S of nursery-grown seedlings. The relationship between R:S and subsequent root growth and seedling survival varies depending on Douglas-fir variety, seedling stocktypes, and site conditions. The biological and physiological basis for using R:S remains, and likely could be used to enhance seedling quality; however, there is an ongoing need for planning and collaboration between researchers and practitioners to identify how to best deploy this evaluation tool.
Estimation of Plant Height and Aboveground Biomass of Toona sinensis under Drought Stress Using RGB-D Imaging
Authors: Liu Wenjian , Li Yanjie , Liu Jun , Jiang Jingmin
Published: December 2021

Rapid and accurate plant growth and biomass estimation is essential for formulating and implementing targeted forest cultivation measures. In this study, RGB-D imaging technology was used to obtain the RGB and depth imaging data for a Toona sinensis seedling canopy to estimate plant growth and aboveground biomass (AGB). Three hundred T. sinensis seedlings from 20 varieties were planted under five different drought stress treatments. The U-Net model was applied first to achieve highly accurate segmentation of plants from complex backgrounds. Simple linear regression (SLR) was used for plant height prediction, and the other three models, including multivariate linear (ML), random forest (RF) and multilayer perceptron (MLP) regression, were applied to predict the AGB and compared for optimal model selection. The results showed that the SLR model yields promising and reliable results for the prediction of plant height, with R2 and RMSE values of 0.72 and 1.89 cm, respectively. All three regression methods perform well in the prediction of AGB estimation. MLP yields the highest accuracy in predicting dry and fresh aboveground biomass compared to the other two regression models, with R2 values of 0.77 and 0.83, respectively. The combination of Gray, Green minus red (GMR) and Excess green index (ExG) was identified as the key predictor by RReliefF for predicting dry AGB. GMR was the most important in predicting fresh AGB. This study demonstrated that the merits of RGB-D and machine learning models are effective phenotyping techniques for plant height and AGB prediction, and can be used to assist dynamic responses to drought stress for breeding selection.
Shifting Precipitation Patterns Drive Growth Variability and Drought Resilience of European Atlas Cedar Plantations
Authors: Camarero Jesús Julio , Gazol Antonio , Colangelo Michele , Linares Juan Carlos , Navarro-Cerrillo Rafael M. , Rubio-Cuadrado Álvaro , Silla Fernando , Dumas Pierre-Jean , Courbet François
Published: December 2021

Tree plantations have been proposed as suitable carbon sinks to mitigate climate change. Drought may reduce their carbon uptake, increasing their vulnerability to stress and affecting their growth recovery and resilience. We investigated the recent growth rates and responses to the climate and drought in eight Atlas cedar (Cedrus atlantica) plantations located along a wide climate gradient from wetter sites in south-eastern France and north Spain to dry sites in south-eastern Spain. The cedar growth increased in response to the elevated precipitation from the prior winter to the current summer, but the influence of winter precipitation on growth gained importance in the driest sites. The growth responsiveness to climate and drought peaked in those dry sites, but the growth resilience did not show a similar gradient. The Atlas cedar growth was driven by the total precipitation during the hydrological year and this association strengthened from the 1980s onwards, a pattern related to the winter North Atlantic Oscillation (NAO). High winter NAO indices and drier conditions were associated with lower growth. At the individual level, growth resilience was related to tree age, while growth recovery and year-to-year growth variability covaried. Plantations’ resilience to drought depends on both climate and tree-level features.
Long Short-Term Memory Network for Predicting Exchange Rate of the Ghanaian Cedi
Authors: Adekoya Adebayo Felix , Nti Isaac Kofi , Weyori Benjamin Asubam
Published: December 2021

An accurate prediction of the Exchange Rate (ER) serves as the basis for effective financial management, monetary policies, and long-term strategic decision making worldwide. A stable and competitive ER enables economic diversification. Economists, researchers, and investors have conducted several studies to predict trends and facts that influence the ER’s rise or fall. This paper used the Long Short-Term Memory Networks (LSTM) framework to predict the weekly exchange rate of one Ghanaian Cedis (GH₵) to three different currencies (United States Dollar, British Pound, and Euro), using Google Trends and historical macroeconomic data. We fused past exchange rates, fundamental macroeconomic variables, commodity prices (cocoa, gold, and crude oil) and public search queries (Google Trends) as input parameters. An empirical analysis using publicly available ER data from the Bank of Ghana (BoG) from January 2004 to October 2019 showed satisfactory results. We observed that the proposed LSTM model outperformed the Support Vector Regressor (SVR) and Back-propagation Neural Network (BPNN) models in accuracy and closeness metrics. That is, our LSTM model obtained (MAE = 0.033, MSE = 0.0035, RMSE = 0.0551, R2 = 0.9983, RMSLE = 0.0129 and MAPE = 0.0121) compared with SVR (MAE = 0.05, MAE = 0.005, RMSE = 0.0683, R2 = 0.9973, RMSLE = 0.0191 and MAPE = 0.0241) and BPNN (MAE = 0.04, MAE = 0.0056, RMSE = 0.0688, R2 = 0.9974, RMSLE = 0.0172 and MAPE = 0.0168). Moreover, we observed a strong positive correction (0.98–0.99) between Google Trends on the currency of focus and its exchange rate to the Ghanaian cedis. The study results show the importance of incorporating public search queries from search engines to predict the ER accurately.
Numerical Investigation of the Effect of Sloped Terrain on Wind-Driven Surface Fire and Its Impact on Idealized Structures
Authors: Edalati-nejad Ali , Ghodrat Maryam , Simeoni Albert
Published: December 2021

In this study, a time-dependent investigation has been conducted to numerically analyze the impact of wind-driven surface fire on an obstacle located on sloped terrain downstream of the fire source. Inclined field with different upslope terrain angles of 0, 10, 20, and 30° at various wind-velocities have been simulated by FireFoam, which is a large eddy simulation (LES) solver of the OpenFOAM platform. The numerical data have been validated using the aerodynamic measurements of a full-scale building model in the absence of fire effects. The results underlined the physical phenomena contributing to the impact of varying wind flow and terrain slope near the fire bed on a built area. The findings indicated that under a constant heat release rate and upstream wind velocity, increasing the upslope terrain angle leads to an increase in the higher temperature areas on the ground near the building. It is also found that raising the inclined terrain slope angle from 0 to 30°, results in an increase in the integrated temperature on the surface of the building. Furthermore, by raising the terrain slope from 0 to 30°, the integrated temperature on the ground for the mentioned cases increases by 16%, 10%, and 13%, respectively.
Investigation of a Light Boxplane Model Using Tuft Flow Visualization and CFD
Authors: Karpovich Elena , Gueraiche Djahid , Sergeeva Natalya , Kuznetsov Alexander
Published: December 2021

In this paper, we addressed the flow patterns over a light boxplane scale model to explain the previously discovered disagreement between its predicted and experimental aerodynamic characteristics. By tuft flow and CFD visualization, we explored the causes yielding a large zero lift pitching moment coefficient, lateral divergence, difference in fore and aft elevator lift, and poor high lift performance of the aircraft. The investigation revealed that the discrepancy in the pitching moment coefficient and lateral stability derivatives can be attributed to insufficient accuracy of the used predictive methods. The difference in fore and aft elevator lift and poor high lift performance of the aircraft may occur due to the low local Reynolds number, which causes the early flow separation over the elevators and flaperons when deflected downward at angles exceeding 10°. Additionally, some airframe changes are suggested to alleviate the lateral divergence of the model.
Nutrition and Physical Activity-Induced Changes in Gut Microbiota: Possible Implications for Human Health and Athletic Performance
Authors: Cella Vittoria , Bimonte Viviana M. , Sabato Claudia , Paoli Antonio , Baldari Carlo , Campanella Matteo , Lenzi Andrea , Ferretti Elisabetta , Migliaccio Silvia
Published: December 2021

The gut microbiota is a complex heterogeneous microbial community modulated by endogenous and exogenous factors. Among the external causes, nutrition as well as physical activity appear to be potential drivers of microbial diversity, both at the taxonomic and functional level, likely also influencing endocrine system, and acting as endocrine organ itself. To date, clear-cut data regarding which microbial populations are modified, and by which mechanisms are lacking. Moreover, the relationship between the microbial shifts and the metabolic practical potential of the gut microbiota is still unclear. Further research by longitudinal and well-designed studies is needed to investigate whether microbiome manipulation may be an effective tool for improving human health and, also, performance in athletes, and whether these effects may be then extended to the overall health promotion of general populations. In this review, we evaluate and summarize the current knowledge regarding the interaction and cross-talks among hormonal modifications, physical performance, and microbiota content and function.
The Impact of COVID-19 on Food Stockpiling Behavior over Time in China
Authors: Wang Erpeng , Gao Zhifeng
Published: December 2021

Studying the impact of COVID-19 on consumer food stockpiling behavior is timely and imperative. It can provide important information and help to understand whether consumers permanently change their behavior or return to their old habits in the long run. This study analyzed Chinese consumers’ food stockpiling behavior using six rounds of nationwide surveys in China from December 2020 to July 2021. The results show that the scale of food reserves extended from 3.03 to 10.01 days after the outbreak of COVID-19, then dropped to a “new normal” plateau and kept fluctuating with the tide of the COVID-19 pandemic. Consumers who stockpile food for “Avoiding shortage” and “Pursuing ease” are going to stockpile food on a larger scale, implying a supply shock may affect the demand side. Those who perceive a higher level of severity of the pandemic are less likely to return to their old habits. Finally, although consumers’ food stockpiling behavior fluctuates with the tide of COVID-19 pandemic, it gradually returns to old habits over time.
Effect of Different Black Quinoa Fractions (Seed, Flour and Wet-Milling Coproducts) upon Quality of Meat Patties during Freezing Storage
Authors: Sayas-Barberá Estrella , Valero-Asencio María Maite , Navarro Rodríguez-Vera Casilda , Fernández-López Juana , Haros Claudia Monika , Pérez-Álvarez José Ángel , Viuda-Martos Manuel
Published: December 2021

In this study, the quality of meat patty samples containing different black quinoa fractions (seed, flour and wet-milling coproducts) was evaluated during freezing preservation. Composition, physicochemical parameters (aw, pH, colour and texture), cooking properties, lipid oxidation and sensory characteristic were studied in four batches (control and 8% concentration of quinoa seed, flour and wet-milling coproducts added) at 30, 60 and 90 days of freezing (−20 ± 1 °C). Different black quinoa fraction addition affected (p < 0.05) physiochemical properties, improved cooking properties and reduced lipid oxidations during freezing storage. Batches with flour and wet-milling coproducts added were the most stable for texture parameters and lipid oxidation during freezing. The results obtained showed that quinoa wet-milling co-products could be considered a valuable sustainable and organic food ingredient, maintaining nutritional and global qualities of the fresh meat product. In addition, freezing storage is an effective way to prolong the shelf life of patties with different black quinoa fractions, added without affecting quality.
In Vitro and In Vivo Digestion of Persimmon and Derived Products: A Review
Authors: M. González Cristina , Hernando Isabel , Moraga Gemma
Published: December 2021

The link between nutrition and health has focused on the strategy of diet-based programs to deal with various physiological threats, such as cardiovascular disease, oxidative stress, and diabetes. Therefore, the consumption of fruits and vegetables as a safeguard for human health is increasingly important. Among fruits, the intake of persimmon is of great interest because several studies have associated its consumption with health benefits due to its high content of bioactive compounds, fiber, minerals, and vitamins. However, during digestion, some changes take place in persimmon nutritional compounds that condition their subsequent use by the human body. In vitro studies indicate different rates of recovery and bioaccessibility depending on the bioactive compound and the matrix in which they are found. In vivo studies show that the pharmacological application of persimmon or its functional components, such as proanthocyanidins, can help to prevent hyperlipidemia and hyperglycemia. Thus, persimmon and persimmon derived products have the potential to be a fruit recommended for diet therapy. This review aims to compile an updated review of the benefits of persimmon and its derived products, focusing on the in vitro and in vivo digestibility of the main nutrients and bioactive compounds.