bluuebunny/crossref_metadata_2025 huggingface dataset:
Proposals of Processes and Organizational Preventive Measures against Malfunctioning of Drones and User Negligence
Authors: Șcheau Mircea Constantin , Achim Monica Violeta , Găbudeanu Larisa , Văidean Viorela Ligia , Vîlcea Alexandru Lucian , Apetri Liliana
Published: January 2023

Drones have been included in more and more activities in various domains, such as military, commercial and personal use. The existing legislative framework insufficiently addresses the responsibility and preventive measures angles in case of vulnerability exploitation and negligence in drone usage. Such aspects can be addressed by the industry in technological processes and standardization. These are especially important aspects given the high impact that misuse of drones can have on individuals, property and buildings within the flight zone when the drone is misused. The aim of this research paper is to investigate how these elements are viewed in existing legislation and by individuals, while taking into account the technical specifics and the stakeholder ecosystem of drone usage. In this respect, we use a complex questionnaire which was sent to a final number of 233 respondents pertaining to firms specialized in IT, legal and cybersecurity. The responses have been analyzed from a qualitative and quantitative perspective. Our results highlight the areas of improvement in the existing standardization and find the followings: (1) stakeholders across the drone ecosystem are viewed as having a shared liability in certain use cases, (2) preventive measure implementation should be dispersed across the stakeholders of drone usage and (3) automation of prevention measures is considered more useful in case of malfunctioning or misuse of drones rather than user manual intervention. In addition, we make proposals to accommodate new policy requirements for the above use cases. The results of this research paper assist policy makers in improving existing standardization framework and technological processes concerning drone usage, but also stakeholders of the drone ecosystem in generating increased trust of the drone users. Further, this research paper can also assist drone software and hardware producers in calibrating their products to ensure trust of the users. In addition, trust in the use of drones for commercial and personal purposes is increased through standardization and proper approaches for situations that may cause damages to drones and to third parties.
Fluctuation Theorem for Information Thermodynamics of Quantum Correlated Systems
Authors: Park Jung Jun , Nha Hyunchul
Published: January 2023

We establish a fluctuation theorem for an open quantum bipartite system that explicitly manifests the role played by quantum correlation. Generally quantum correlations may substantially modify the universality of classical thermodynamic relations in composite systems. Our fluctuation theorem finds a non-equilibrium parameter of genuinely quantum nature that sheds light on the emerging quantum information thermodynamics. Specifically we show that the statistics of quantum correlation fluctuation obtained in a time-reversed process can provide a useful insight into addressing work and heat in the resulting thermodynamic evolution. We illustrate these quantum thermodynamic relations by two examples of quantum correlated systems.
GRPAFusion: A Gradient Residual and Pyramid Attention-Based Multiscale Network for Multimodal Image Fusion
Authors: Wang Jinxin , Xi Xiaoli , Li Dongmei , Li Fang , Zhang Guanxin
Published: January 2023

Multimodal image fusion aims to retain valid information from different modalities, remove redundant information to highlight critical targets, and maintain rich texture details in the fused image. However, current image fusion networks only use simple convolutional layers to extract features, ignoring global dependencies and channel contexts. This paper proposes GRPAFusion, a multimodal image fusion framework based on gradient residual and pyramid attention. The framework uses multiscale gradient residual blocks to extract multiscale structural features and multigranularity detail features from the source image. The depth features from different modalities were adaptively corrected for inter-channel responses using a pyramid split attention module to generate high-quality fused images. Experimental results on public datasets indicated that GRPAFusion outperforms the current fusion methods in subjective and objective evaluations.
Rethinking Liquid Crystal Tunable Phase Shifter Design with Inverted Microstrip Lines at 1–67 GHz by Dissipative Loss Analysis
Authors: Li Jinfeng
Published: January 2023

Growing 5G/6G phased-array beam-steering applications, for which liquid crystal (LC) is one of the enabling technology candidates, have sparked interest in the modulation of the phase (and amplitude) of microwave and millimeter-wave signals. In this communication, fresh insights into the systematic design analysis of a 1–67 GHz passive inverted microstrip line (IMSL) phase shifter filled with highly anisotropic LC as tunable dielectric media are obtained. Based on waveguide disturbance tests to characterize the dielectric properties of the non-tunable PCB and tunable LC used in the IMSL phase shift device filled with a GT3-24002 LC layer (125 µm thick) partially enclosing a 220 µm wide, 17 µm thick, 1.35 cm long copper core line, a 0–π differential phase shift in the 1–67 GHz range with less than 2 dB insertion loss is reported. Dissipative loss analysis shows that the dielectric absorption of the LC is 21.28% of the input signal power at 60 GHz. Further investigation is performed to quantify the impacts of dielectric substrate thicknesses (PCB and LC) on the wave-occupied volume ratio (and hence the phase tuning range), as well as on dissipative losses (including conductor loss and dielectric loss). Specifically, conductor loss is observed to follow a linear relationship with the reciprocal of the LC thickness.
Signal Modulation Recognition Algorithm Based on Improved Spatiotemporal Multi-Channel Network
Authors: Hou Shunhu , Fan Youchen , Han Bing , Li Yuhai , Fang Shengliang
Published: January 2023

Automatic modulation recognition (AMR) plays an essential role in modern communication systems. In recent years, various modulation recognition algorithms based on deep learning have been emerging, but the problem of low recognition accuracy has not been solved well. To solve this problem, based on the existing MCLDNN algorithm, in this paper, we proposed an improved spatiotemporal multi-channel network (IQ-related features Multi-channel Convolutional Bi-LSTM with Gaussian noise, IQGMCL). Firstly, dividing the input IQ signals into three channels, time sequence feature extraction is carried out for route I, route Q, and route IQ, respectively. For route IQ, convolution kernel (2,1) is first used to extract relevant features. Two layers of the small convolution kernel (1,3) are used to extract time sequence features further, and the three channels are used to extract features further. Then, a two-layer short-length memory network is used to extract features from time and space more effectively. Through comparison experiments, Bi-LSTM is introduced to replace one layer of LSTM, and a fully connected layer is removed to prevent overfitting. Finally, multiplicative Gaussian noise is introduced to naturally corrode the feature parameters, further improving the robustness and accuracy of the model. Experiments are carried out on three public datasets RML2016.10a, RML2016.10b, and RML2016.04C. The experiments show that the IQGMCL network has higher recognition accuracies on all datasets, especially on the RML2016.10a dataset. When the SNR is 4 dB, the recognition accuracy reaches 93.52%. When the SNR is greater than 0 dB, the average recognition accuracy reaches 92.3%, 1.31%, and 1.2% higher than the original MCLDNN network, respectively.
SHDL—A Hardware Description Language and Open-Source Web Tool for Online Digital Systems Design Teaching
Authors: Trost Andrej , Jamšek Janez , Žemva Andrej
Published: January 2023

Hardware description languages and tools require a considerable amount of teaching activities in a digital systems design course, which is difficult to accommodate in a limited time frame, and to use for e-learning. This paper presents our user-friendly and open-source web-based digital design tool, SHDL, which is used to describe and simulate hardware components and translate them into a standard language. SHDL is a teaching language and tool for digital design, which aims to improve the teaching and learning experience in digital systems design courses. The use and evaluation of the proposed online teaching model for the Digital Electronic Systems Design (DESD) course, using the SHDL tool for e-learning during the COVID-19 phase, is presented. Using the SHDL language and web tool, we have created many examples of digital circuits that prepare students to explore their own designs. The example components can also be used as digital system modules, leading to better modularity of the final project. The use of SHDL in the DESD course has shown that the proposed language leads to fewer syntax, simulation and synthesis errors in the designed circuits. The evaluation results show that at the end of the laboratory exercises, there was no longer a difference in knowledge between the students without prior VHDL experience and the other students. The results encourage us to continue using SHDL, and to complement the traditional DESD teaching methods with e-learning.
A Fuzzy-Based Evaluation of E-Learning Acceptance and Effectiveness by Computer Science Students in Greece in the Period of COVID-19
Authors: Chrysafiadi Konstantina , Virvou Maria , Tsihrintzis George
Published: January 2023

In this paper, a fuzzy-based evaluation method is presented for the impact of e-learning on several aspects of the learning lives of academic students of Information and Communication Technologies (ICT) during the COVID-19 pandemic. Specifically, the academic year 2020–2021 was considered when a general lockdown was imposed in Greece and all courses were delivered exclusively through the web. The evaluation criteria are (i) e-learning acceptance, (ii) learning effectiveness, (iii) students’ engagement and (iv) socializing and interpersonal relationships in the educational community. The evaluation was conducted through questionnaires. Ninety two (92) undergraduate and postgraduate students and Ten (10) computer science in-structors of the department of Informatics of the University of Piraeus, Greece, participated in this survey. The questionnaire answers were analyzed using a fuzzy-based mechanism. Particularly, five fuzzy sets were used to describe the 5-point Likert scale answers to the questionnaires with linguistic values, and four other fuzzy sets were used for the description of the evaluation results concerning the four defined evaluation criteria. Moreover, 209 fuzzy rules were created to analyze and calculate the evaluation results per criterion, considering both the students’ answers (119 fuzzy rules) and the instructors’ answers (90 fuzzy rules) to the questionnaires. The gain of this approach is that the analysis of evaluation data with fuzzy rules imitates the human way of thinking and, thus, makes the process more explainable. The evaluation results showed a positive impact of e-learning on student confidence, self-discipline and active participation and a negative impact on student interpersonal relationships. The impact of e-learning on other learning issues was neutral.
Micro-Expression Spotting Based on a Short-Duration Prior and Multi-Stage Feature Extraction
Authors: Xie Zhihua , Cheng Sijia
Published: January 2023

When micro-expressions are mixed with normal or macro-expressions, it becomes increasingly challenging to spot them in long videos. Aiming at the specific time prior of micro-expressions (MEs), an ME spotting network called AEM-Net (adaptive enhanced ME detection network) is proposed. This paper is an extension of the conference paper presented at the Chinese Conference on Biometric Recognition (CCBR). The network improves spotting performance in the following five aspects. Firstly, a multi-stage channel feature extraction module is constructed to extract the features at different depths. Then, an attention spatial-temporal module is leveraged to obtain salient and discriminative micro-expression segments while suppressing the generation of excessively long or short suggestions. Thirdly, a ME-NMS (non-maximum suppression) network is developed to reduce redundancy and decision errors. Fourthly, a multi-scale feature fusion module is introduced to fuse up-sampling features of high-level maps and fine-grained information, which obtains meaningful information on feature distribution and contributes to a good representation of MEs. Finally, two spotting mechanisms named anchor-based and anchor free were integrated to get final spotting. Extensive experiments were conducted on prevalent CAS(ME)2 and the SAMM-Long ME databases to evaluate the spotting performance. The results show that the AEM-Net achieves competitive performance, outperforming other state-of-the-art methods.
Design of Vehicle Tunnel Illumination Measurement Device Based on STC12C5A60S2 Single-Chip Microcomputer
Authors: Wang Ziyan , Gao Hui
Published: January 2023

In order to measure tunnel illumination with high efficiency and accuracy, a vehicle-mounted tunnel illumination measurement device is designed in this paper. The device comprises a measurement module, a control module, a display module, and a power module. The measurement module is composed of a BCE illuminance sensor and an inductive proximity switch, which can realize a single illuminance measurement within a fixed distance. The control module, i.e., the STC12C5A60S2 single-chip microcomputer, sends the single measurement data to the storage module to realize dynamic automatic measurement. The display module is an LCD1602 liquid crystal display, which displays the measured tunnel mileage and real-time illumination. The whole device is fed by the powered module. The man–machine exchange interface of the Visual Basic (VB) host computer and Access database are used to display and store the previous illuminance measurement data, respectively. Extensive experiments show that the device has the advantages of a simple structure, convenient installation, stable operation, and accurate and efficient measurement, and can realize an automatic measurement of illumination in a long tunnel.
Effective Resource Allocation Technique to Improve QoS in 5G Wireless Network
Authors: Jayaraman Ramkumar , Manickam Baskar , Annamalai Suresh , Kumar Manoj , Mishra Ashutosh , Shrestha Rakesh
Published: January 2023

A 5G wireless network requires an efficient approach to effectively manage and segment the resource. A Centralized Radio Access Network (CRAN) is used to handle complex distributed networks. Specific to network infrastructure, multicast communication is considered in the performance of data storage and information-based network connectivity. This paper proposes a modified Resource Allocation (RA) scheme for effectively handling the RA problem using a learning-based Resource Segmentation (RS) technique. It uses a modified Random Forest Algorithm (RFA) with Signal Interference and Noise Ratio (SINR) and position coordinates to obtain the position coordinates of end-users. Further, it predicts Modulation and Coding Schemes (MCS) for establishing a connection between the end-user device and the Remote Radio Head (RRH). The proposed algorithm depends on the accuracy of positional coordinates for the correctness of the input parameters, such as SINR, based on the position and orientation of the antenna. The simulation analysis renders the efficiency of the proposed technique in terms of throughput and energy efficiency.
Contagion Spillover from Bitcoin to Carbon Futures Pricing: Perspective from Investor Attention
Authors: Zhou Qingjie , Zhu Panpan , Zhang Yinpeng
Published: January 2023

The uniqueness of this investigation lies in empirically testing and proving the contagion spillover of Bitcoin attention to carbon futures. Specifically, several models are adopted to investigate the explanatory and predictive abilities of Bitcoin attention to carbon futures. The results can be generalized as follows. First, Bitcoin attention Granger causes the variation of carbon futures. Second, Bitcoin attention shows a negative impact on carbon futures and an addition, an invert U-shaped connection exists. Third, the Bitcoin attention-based models can beat the commonly used historical average benchmark during out-of-sample forecasting both in statistical and economic levels. Fourth, we complete robustness checks to certify that the contagion spillover from Bitcoin attention to the pricing of carbon futures does exist. Finally, we prove the linear and non-linear impacts from Bitcoin attention to realized volatility of carbon futures. All the results prove that Bitcoin attention is an important pricing factor for carbon futures market.
Pulverized Coal-Fired Boilers: Future Directions of Scientific Research
Authors: Ochowiak Marek , Bielecki Zdzisław , Krupińska Andżelika , Matuszak Magdalena , Włodarczak Sylwia , Bielecki Michał , Choiński Dariusz , Smyła Jarosław , Jagiełło Krzysztof
Published: January 2023

The paper provides an outlook on future directions of research and the possible applications for pulverized coal-fired boilers. One potential direction for future research is to focus on the ways to improve the efficiency of pulverized coal-fired boilers. This could involve developing new combustion technologies that are able to more thoroughly burn the coal and produce less waste or finding ways to capture and use the excess heat that is generated during the combustion process. The pulverized coal combustion process in power boilers is still being improved by the preliminary cleaning of coal and the use of various catalytic additives. Another area of research that could be valuable is the development of advanced control systems and monitoring technologies for pulverized coal-fired boilers. These systems could be used to optimize the performance of the boiler and ensure that it is operating at maximum efficiency while also providing real-time data on the condition of the boiler and any potential problems that may arise. The analysis of literature shows that several future paths of development and scientific research related to the technology of pulverized coal combustion in boilers can be distinguished.
Thermal Energy Storage with PCMs in Shell-and-Tube Units: A Review
Authors: Cieśliński Janusz T. , Fabrykiewicz Maciej
Published: January 2023

The paper presents a survey of the experimental and numerical studies of shell-and-tube systems in which phase change material (PCM) is used. Due to the multitude of design solutions for shell-and-tube systems, the emphasis is placed on double-tube (DT), triplex-tube (TT), and multi-tube (MT) units. Additionally, only single-pass systems are considered. Particular attention is paid to the method of heat transfer intensification. The analysis of the research results begins with the classification of each of the three mentioned systems. The systems are divided according to the angle of inclination, the method of heat transfer enhancement (HTE), the flow direction of heat transfer fluid (HTF), and the arrangement of tubes in the bundle. Moreover, the simplified schemes of the particular research cases are proposed. Then, the works on each of the mentioned systems, i.e., DT, TT, and MT, are discussed chronologically. Finally, in the corresponding tables, details of the discussed cases are presented, such as geometric dimensions, and the type of PCM or HTF used. A novelty in the present work is the precise classification of PCM TESUs as DT, TTH, and MTH. In the literature, there is a lot of discretion in this regard. Second, the methods of heat transfer intensification in the presented PCM TESUs are listed and discussed. Third, unified schemes of design solutions for the discussed PCM TESUs are proposed. The review shows that development directions for shell-and-tube TESUs include systems with high conductivity fins of different shapes, heights, and spacing, several PCMs, and modified shells.
Numerical Investigation of the Effects of the Hole Inclination Angle and Blowing Ratio on the Characteristics of Cooling and Stress in an Impingement/Effusion Cooling System
Authors: Li Haiwang , Zhang Dawei , You Ruquan , Zou Yifan , Liu Song
Published: January 2023

Due to the uneven temperature field and temperature gradient introduced by an efficient cooling structure, the analysis of the stress field is necessary. In this study, the cooling characteristics and stress characteristics such as the thermal stress and thermomechanical stress of an impingement/effusion cooling system were investigated by employing a fluid–thermal-structure coupling simulation method. The effects of film hole injection angle (30°–90°) and blowing ratio (0.5–2.0) were studied. The results showed that the film hole shape and the non-uniform temperature field introduced by the cooling structure had a great influence on the stress field distribution. With the increase in the blowing ratio, not only the overall cooling effectiveness of the cooling system increased, but the maximum thermal stress and thermomechanical stress near film holes also increased. The cases with a smaller inclination angle could provide a better cooling performance, but caused a more serious stress concentration of the film hole. However, the thermal stress difference at the leading and trailing edges of the film hole increased with a decreasing inclination angle. The cases with a = 30° and 45° showed serious thermal stress concentration near the hole’s acute region.
An Economic Analysis of Energy Consumption at Student Residences in a South African-Based Academic Institution Using NARX Neural Network
Authors: Ayeleru Olusola Olaitan , Adeniran Joshua Adeniyi , Ntsaluba Sula Bantubakhona Kwesi , Fajimi Lanrewaju Ibrahim , Olubambi Peter Apata
Published: January 2023

One of the issues associated with the supply of electricity is its generation capacity, and this has led to prevalent power cuts and high costs of usage experienced in many developing nations, including South Africa. Historical research has shown that the annual rate of increase for electricity has grown at an alarming rate since 2008 and, in some years, has grown as much as 16%. The objectives of this study are to estimate the cost analysis of electricity usage at the twenty-nine residences of the University of Johannesburg (UJ-Res) and propose a model for our university, as well as other South African universities, to become more energy-efficient. This was achieved by analyzing the tariffs between 2015 and 2021. A forecast was made for a period of five years (2021 to 2026) using a non-linear autoregressive exogenous neural network (NARX-NN) time-series model. From the results obtained, the better NARX-NN model studied has a root mean squared error (RMSE) of 2.47 × 105 and a determination coefficient (R2) of 0.9661. The projection result also shows that the annual cost of energy consumed will increase for the projected years, with the year 2022 being the peak with an estimated annual cost of over ZAR 30 million (USD 2,076,268).
Second Life of Lithium-Ion Batteries of Electric Vehicles: A Short Review and Perspectives
Authors: Illa Font Carlos Henrique , Siqueira Hugo Valadares , Machado Neto João Eustáquio , Santos João Lucas Ferreira dos , Stevan Sergio Luiz , Converti Attilio , Corrêa Fernanda Cristina
Published: January 2023

Technological advancement in storage systems has currently stimulated their use in miscellaneous applications. The devices have gained prominence due to their increased performance and efficiency, together with the recent global appeal for reducing the environmental impacts caused by generating power or by combustion vehicles. Many technologies have been developed to allow these devices to be reused or recycled. In this sense, the use of lithium-ion batteries, especially in electric vehicles, has been the central investigative theme. However, a drawback of this process is discarding used batteries. This work provides a short review of the techniques used for the second-life batteries of electric vehicles and presents the current positioning of the field, the steps involved in the process of reuse and a discussion on important references. In conclusion, some directions and perspectives of the field are shown.
Development and Validation of a CFD Combustion Model for Natural Gas Engines Operating with Different Piston Bowls
Authors: Gianetti Giovanni Gaetano , Lucchini Tommaso , D’Errico Gianluca , Onorati Angelo , Soltic Patrik
Published: January 2023

Nowadays, an accurate and precise description of the combustion phase is essential in spark-ignition (SI) engines to drastically reduce pollutant and greenhouse gas (GHG) emissions and increase thermal efficiency. To this end, computational fluid dynamics (CFD) can be used to study the different phenomena involved, such as the ignition of the charge, combustion development, and pollutant formation. In this work, a validation of a CFD methodology based on the flame area model (FAM) was carried out to model the combustion process in light-duty SI engines fueled with natural gas. A simplified spherical kernel approach was used to model the ignition phase, whereas turbulent flame propagation was described through two variables. A zero-dimensional evolution of the flame kernel radius was used in combination with the Herweg and Maly formulation to take the laminar-to-turbulent flame transition into account. To estimate the chemical composition of burnt gas, two different approaches were considered—one was based on tabulated kinetics, and the other was based on chemical equilibrium. Assessment of the combustion model was first performed by using different operating points of a light-duty SI engine fueled with natural gas and by using the original piston. The results were validated by using experimental data on the in-cylinder pressure, apparent heat release rate, and pollutant emissions. Afterward, two other different piston bowl geometries were investigated to study the main differences between one solution and the others. The results showed that no important improvements in terms of combustion efficiency were obtained by using the new piston bowl shapes, which was mainly due to the very low (+4%) or null increase in turbulent kinetic energy during the compression stroke and due to the higher heat losses (+20%) associated with the increased surface area of the new piston geometries.
Prediction Model for the DC Flashover Voltage of a Composite Insulator Based on a BP Neural Network
Authors: Zhou Zhenan , Li Haowei , Wen Silun , Zhang Chuyan
Published: January 2023

To be able to predict the DC flashover characteristics of composite insulators, a four-layer BP neural network model is established with composite insulator shed structure parameters as the input. Three algorithms (gradient descent with momentum, RMSProp gradient descent, and Adam gradient descent) are applied, and the DC pollution flashover experimental data of composite insulators are used as training data. The results show that all three algorithms have good prediction capabilities. Among them, the Adam gradient descent model has the best prediction result, which can make the average prediction with an error of less than 4% and a maximum error of less than 8%, so these results can provide a reference for the design of composite insulators in DC voltage and product performance verifications.
Ensuring the Reliability of Gas Supply Systems by Optimizing the Overhaul Planning
Authors: Grudz Volodymyr , Grudz Yaroslav , Pavlenko Ivan , Liaposhchenko Oleksandr , Ochowiak Marek , Pidluskiy Vasyl , Portechyn Oleksandr , Iakymiv Mykola , Włodarczak Sylwia , Krupińska Andżelika , Matuszak Magdalena , Czernek Krystian
Published: January 2023

The aim of the article is the development of methods for optimal overhaul planning of compressor station equipment. Nowadays, due to uncertainties in the forecast of gas supply flow rates, increasing the reliability and energy efficiency of main gas pipelines is an urgent problem. The dependence of operating costs for major repairs on the maintenance periodicity is extreme. Reducing equipment’s maintenance period leads to an increase in repair costs. It also increases the reliability of equipment operation. Overall, all these facts reduce the probability of emergency failures and related expenses for emergency recovery, gas losses, and undersupply to consumers. Therefore, an optimal maintenance frequency exists, at which the total operating costs will be minimal. A procedure for optimizing the periodicity of repairs and equipment replacement is proposed. It was realized by constructing an objective function as a dependence of exploitation costs on the inter-repair period of major repairs. A probabilistic approach was applied to assess the aging process. The characteristics of the equipment’s state are described by distribution densities (i.e., pre-repair, inter-repair, and full-service life), which vary depending on product initialization time. The main characteristics of major repairs are their duration and intensity, which are evaluated by the quality factor related to repair costs. The extremum of the objective function is sought by the method of competing options. It was determined that the optimal management of the frequency of equipment replacement can be realized by choosing the optimal values of the average service life, average operation time of units until the first planned and preventive repair, and quality factor. As a result, the required technical condition for the technological equipment is ensured under minimum operating costs without reducing the system’s reliability.
Stability and Control for Buck–Boost Converter for Aeronautic Power Management
Authors: Russo Antonio , Cavallo Alberto
Published: January 2023

The need for greener and cleaner aviation has accelerated the transition towards more electric systems on the More Electric Aircraft. One of the key challenges related to the increasing number of electrical devices onboard is the control of bidirectional power converters. In this work, stability analysis and control of a buck–boost converter for aeronautic applications are presented. Firstly, stability of the buck–boost converter in the Lyapunov sense is proven by resorting to input-to-state stability notions. Then, a novel control design based on second order sliding mode control and uniting control, aimed at overcoming the difficulties generated by the nonlinear input gain function of the system not being sign definite, is presented. Extensive and detailed simulations, designed to emulate one of the possible energy management policies onboard a More Electric Aircraft, confirm the correctness of the theoretical analysis both in buck and in boost mode.
Optimal Management of a Virtual Power Plant Consisting of Renewable Energy Resources and Electric Vehicles Using Mixed-Integer Linear Programming and Deep Learning
Authors: Ahmadian Ali , Ponnambalam Kumaraswamy , Almansoori Ali , Elkamel Ali
Published: January 2023

Recently, renewable energy resources (RESs) and electric vehicles (EVs), in addition to other distributed energy resources (DERs), have gained high popularity in power systems applications. These resources bring quite a few advantages for power systems—reducing carbon emission, increasing efficiency, and reducing power loss. However, they also bring some disadvantages for the network because of their intermittent behavior and their high number in the grid which makes the optimal management of the system a tough task. Virtual power plants (VPPs) are introduced as a promising solution to make the most out of these resources by aggregating them as a single entity. On the other hand, VPP’s optimal management depends on its accuracy in modeling stochastic parameters in the VPP body. In this regard, an efficient approach for a VPP is a method that can overcome these intermittent resources. In this paper, a comprehensive study has been investigated for the optimal management of a VPP by modeling different resources—RESs, energy storages, EVs, and distributed generations. In addition, a method based on bi-directional long short-term memory networks is investigated for forecasting various stochastic parameters, wind speed, electricity price, load demand, and EVs’ behavior. The results of this study show the superiority of BLSTM methods for modeling these parameters with an error of 1.47% in comparison with real data. Furthermore, to show the performance of BLSTMs, its results are compared with other benchmark methods such as shallow neural networks, support vector machines, and long short-term memory networks.
Dysmetabolic Iron Overload Syndrome: Going beyond the Traditional Risk Factors Associated with Metabolic Syndrome
Authors: Barbalho Sandra Maria , Laurindo Lucas Fornari , Tofano Ricardo José , Flato Uri Adrian Prync , Mendes Claudemir G. , de Alvares Goulart Ricardo , Briguezi Ana Maria Gonçalves Milla , Bechara Marcelo Dib
Published: January 2023

Dysmetabolic iron overload syndrome (DIOS) corresponds to the increase in iron stores associated with components of metabolic syndrome (MtS) and in the absence of an identifiable cause of iron excess. The objective of this work was to review the main aspects of DIOS. PUBMED and EMBASE were consulted, and PRISMA guidelines were followed. DIOS is usually asymptomatic and can be diagnosed by investigating MtS and steatosis. About 50% of the patients present altered hepatic biochemical tests (increased levels of γ-glutamyl transpeptidase itself or associated with increased levels of alanine aminotransferase). The liver may present parenchymal and mesenchymal iron overload, but the excess of iron is commonly mild. Steatosis or steatohepatitis is observed in half of the patients. Fibrosis is observed in about 15% of patients. Hyperferritinemia may damage the myocardium, liver, and several other tissues, increasing morbidity and mortality. Furthermore, DIOS is closely related to oxidative stress, which is closely associated with several pathological conditions such as inflammatory diseases, hypertension, diabetes, heart failure, and cancer. DIOS is becoming a relevant finding in the general population and can be associated with high morbidity/mortality. For these reasons, investigation of this condition could be an additional requirement for the early prevention of cardiovascular diseases.
Application of Connected Vehicle Data to Assess Safety on Roadways
Authors: Khanal Mandar , Edelmann Nathaniel
Published: January 2023

Using surrogate safety measures is a common method to assess safety on roadways. Surrogate safety measures allow for proactive safety analysis; the analysis is performed prior to crashes occurring. This allows for safety improvements to be implemented proactively to prevent crashes and the associated injuries and property damage. Existing surrogate safety measures primarily rely on data generated by microsimulations, but the advent of connected vehicles has allowed for the incorporation of data from actual cars into safety analysis with surrogate safety measures. In this study, commercially available connected vehicle data are used to develop crash prediction models for crashes at intersections and segments in Salt Lake City, Utah. Harsh braking events are identified and counted within the influence areas of sixty study intersections and thirty segments and then used to develop crash prediction models. Other intersection characteristics are considered as regressor variables in the models, such as intersection geometric characteristics, connected vehicle volumes, and the presence of schools and bus stops in the vicinity. Statistically significant models are developed, and these models may be used as a surrogate safety measure to analyze intersection safety proactively. The findings are applicable to Salt Lake City, but similar research methods may be employed by researchers to determine whether these models are applicable in other cities and to determine how the effectiveness of this method endures through time.
Optoelectronic Device for Measuring Radio Signal Samples and Evaluating Its Accuracy Characteristics
Authors: Safaryan Olga A. , Alferova Irina A. , Zvezdina Marina Yu. , Prygunov Alexander G.
Published: January 2023

When using quadrature signals in radio channels, flat and selective fading, multipath radio reception, intersymbol interference, and jitter occur. In addition to the need to accurately estimate the value of the phase difference at the current and previous clock intervals, a critical factor in receiving and demodulating such signals is the accuracy of measuring the amplitude of their samples. When demodulating such signals, an approach is possible, the basis of which is to measure the values of individual signal samples at discrete time points with higher accuracy than in existing electronic devices. Such an approach can be implemented by an optoelectronic device in which a coherent luminous flux is formed, the parameters of which are modulated by a voltage proportional to the readings of the received radio signal. Using a modulated light flux, an interferogram is formed, the parameters of which are directly related to the parameters of this light flux and accordingly to the parameters of the received radio signal. This makes it possible, by increasing the accuracy of estimating radio signal samples, to increase the base of the alphabet used for code manipulation, the efficiency of using the allocated frequency band for transmitting information and reduce the probability of a bit error. The article presents a mathematical model for converting the parameters of the received radio signal into the parameters of the generated interferogram. By mathematical modeling the accuracy characteristics of an optoelectronic device for measuring radio signal samples were evaluated. The results of mathematical modeling illustrating the relationship of the parameters of the optical elements of the device with the accuracy of estimates of the radio signal counts are presented. The practical significance of the proposed optoelectronic device can be used as an independent device for analog-to-digital conversion of radio signals, as well as part of demodulators for QAM and OFDM signals in networks and communication systems of 5G and the next generations.
Early Diagnosis of Pine Wilt Disease in Pinus thunbergii Based on Chlorophyll Fluorescence Parameters
Authors: Liu Fei , Zhang Maojiao , Hu Jiafeng , Pan Min , Shen Luyang , Ye Jianren , Tan Jiajin
Published: January 2023

As the most severe forestry quarantine disease in several countries, pine wilt disease (PWD) causes substantial economic losses and poses a significant threat to the forest ecosystem. It is necessary to find a rapid and sensitive method for the early diagnosis of the disease to control the development of the disease effectively. This paper investigated the effect of Bursaphelenchus xylophilus (the pinewood nematode; PWN) on the chlorophyll fluorescence kinetic curve (OJIP curve) and the parameters of needles using four-year-old Pinus thunbergii as experimental materials and chlorophyll fluorescence analysis as a technical tool. It was shown by the results in the OJIP curve that the fluorescence intensity of the inoculated plants was significantly increased at points O and I. Additionally, the relative variable fluorescence intensity at points K and J was comparable to that of the control plants. Several chlorophyll fluorescence parameters of the treatment significantly increased or decreased with disease progression. At the same time, the control group had no significant changes in each parameter. Therefore, chlorophyll fluorescence parameters can be used as indicators for the early diagnosis of PWD, among which the DIo/RC parameter was the best. In summary, PWN invasion will produce fluorescence on the PSII of P. thunbergii, and its chlorophyll fluorescence parameters are expected to achieve early PWD diagnosis.
Effect of Provenance and Environmental Factors on Tree Growth and Tree Water Status of Norway Spruce
Authors: Leštianska Adriana , Fleischer Peter , Merganičová Katarína , Fleischer Peter , Nalevanková Paulína , Střelcová Katarína
Published: January 2023

Changes in temperature regime, and a higher frequency of extreme weather conditions due to global warming are considered great risks for forest stands worldwide because of their negative impact on tree growth and vitality. We examined tree growth and water balance of two provenances of Norway spruce growing in Arboretum Borová hora (350 m a.s.l., Zvolen, central Slovakia) that originated from climatologically cooler conditions. The research was performed during three meteorologically different years from 2017 to 2019. We evaluated the impact of climatic and soil factors on intra-species variability in radial stem growth and tree water status that were characterised by seasonal radial increment, stem water deficit and maximum daily shrinkage derived from the records of stem circumference changes obtained from band dendrometers installed on five mature trees of each provenance. The impact of environmental factors on the characteristics was evaluated using the univariate factor analysis and four machine learning models (random forest, support vector machine, gradient boosting machine and neural network). The responses to climatic conditions differed between the provenances. Seasonal radial increments of the provenance from cooler conditions were greater than those of the provenance originating from cooler and wetter conditions due to the long-term shortage of water the latter provenance had to cope with in the current environment, while the provenance from the cooler region was more sensitive to short-term changes in environmental conditions.
Effects of Nitrogen Form on Root Activity and Nitrogen Uptake Kinetics in Camellia oleifera Seedlings
Authors: Wang Rui , He Zhilong , Zhang Zhen , Xv Ting , Wang Xiangnan , Liu Caixia , Chen Yongzhong
Published: January 2023

This study investigated the effects of nitrogen form on root activity and nitrogen uptake kinetics of Camellia oleifera Abel. seedlings, providing a scientific basis for improving nitrogen use efficiency and scientific fertilization in C. oleifera production. Taking one-year-old C. oleifera cultivar ‘Xianglin 27’ seedlings as subjects, 8 mmol·L−1 of nitrogen in varied forms (NO3−:NH4+ = 0:0, 10:0, 7:3, 5:5, 3:7, 0:10) was applied in this study as the treatment conditions to investigate the effects of different nitrogen forms on root activity and nitrogen uptake kinetics in C. oleifera seedlings. Comparing the performance of nutrient solutions with different NO3−:NH4+ ratios, the results showed that a mixed nitrogen source improved the root activity of C. oleifera seedlings based on total absorption area, active absorption area, active absorption area ratio, specific surface area, and active specific surface area. When NO3−:NH4+ = 5:5, the total absorption area and active absorption area of the seedling roots reached the maximum. The results of uptake kinetic parameters showed that Vmax NH4+ > Vmax NO3− and Km NO3− > Km NH4+, indicating that the uptake potential of ammonium–nitrogen by C. oleifera seedlings is greater than that of nitrate–nitrogen. The conclusion was that compared to either ammonium– or nitrate–nitrogen, the mixed nitrogen source was better for promoting the root activity of C. oleifera seedlings, and the best nitrate/ammonium ratio was 5:5.
The Dynamic Effects of COVID-19 and the March 2020 Crash on the Multifractality of NASDAQ Insurance Stock Markets
Authors: Li Xing , Su Fang
Published: January 2023

Triggered by COVID-19, one of the most dramatic crashes in the stock market in history occurred in March 2020. The sharp reductions in NASDAQ insurance stock indexes were observed after the occurrence of COVID-19 and in March 2020. In this study, the NASDAQ insurance stock markets (including NASDAQ Insurance Index, Developed Markets Insurance Index, and Emerging Markets Insurance Index) and NASDAQ Composite Index are utilized. The “scissors difference” between the NASDAQ Insurance Index and NASDAQ Composite Index is observed. The dynamic effects of the COVID-19 epidemic and the March 2020 crash on the multifractality of four series are explored. Firstly, the apparent and intrinsic multifractality, the components of multifractality, and the dynamic effects of the COVID-19 epidemic on these indexes are analyzed. Secondly, the multifractal cross-correlation between the NASDAQ Insurance Index and NASDAQ Composite Index is investigated. The dynamic influence of the COVID-19 epidemic on the cross-correlation is examined. The multifractal analysis results reveal that four series both before and after the occurrence of COVID-19 have multifractal characteristics. The stronger multifractal characteristics and the greater multifractal degree are obtained after the occurrence of COVID-19. The intrinsic multifractality of the three indexes ascends largely after the occurrence of COVID-19. The multifractal cross-correlation analysis illustrates that the cross-correlation between two indexes before and after the occurrence of COVID-19 is multifractal. The stronger multifractal cross-correlations and greater multifractal degrees are shown. The contribution of the intrinsic multifractal cross-correlation increased after the occurrence of COVID-19.
Impact of N,N-Bis(2-ethoxyethyl) Fatty Acid Amides on the Lubrication Performance of Kerosene Fuel F-34 for Use in CI Engines
Authors: Anastopoulos George , Schinas Petros , Zannikou Ypatia , Komiotou Maria , Zannikos Fanourios , Karonis Dimitrios
Published: January 2023

In an attempt to avoid serious problems that can affect the efficiency of refueling ground-operated vehicles and aircraft during military operations, the Armed Forces of the North Atlantic Treaty Organization (NATO) are introducing the use of a unique fuel for both air and land use. The fuel that has been selected is the F-34, similar to Jet A-1, which is used in civil aviation, in order to replace diesel fuel in many applications. It has to be mentioned that tests performed with this fuel, which is kerosene type on the high frequency reciprocating rig (HFRR) have shown that such fuel is responsible for severe wear. This very high wear is related to the very low lubricity of aviation fuel. Having the idea to improve the lubricity of aviation fuel to the level of fuels used in compression ignition engines (diesel fuel), seven N,N-Bis(2-ethoxyethyl) fatty acid amides were formulated from various vegetable oils (sunflower oil, soybean oil, cottonseed oil, olive oil, tobacco seed oil, coconut oil, used frying oil), and they were evaluated as lubricity improvers of the aviation fuel. The required tribological measurements for lubricity rating were carried out by employing ISO 12156-1 test method on an HFRR instrument. The test conditions during the measurements were in the range of 55% to 58% for the relative humidity and 24 °C for the temperature. The results from the tribological measurements showed that all N,N-Bis(2-ethoxyethyl) fatty acid amides used were rated as efficient in order to provide an acceptable mean wear scar diameter (below 460 μm) at concentrations from 150 to 300 ppm. Additive concentrations below 150 ppm did not improve the lubricity at the required level. The increase of N,N-Bis(2-ethoxyethyl) fatty acid amides at concentrations over 300 ppm did not have any significant decrease in the wear scar diameter. A comparison between the N,N-Bis(2-ethoxyethyl) fatty acid amides showed that those formulated by non-polyunsaturated oils like olive oil and coconut oil seem to have better lubricity improver characteristics.