bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysing Factory Workers’ Acceptance of Collaborative Robots: A Web-Based Tool for Company Representatives
Authors: Baumgartner Marco , Kopp Tobias , Kinkel Steffen
Published: January 2022

Collaborative robots are a new type of lightweight robots that are especially suitable for small and medium-sized enterprises. They offer new interaction opportunities and thereby pose new challenges with regard to technology acceptance. Despite acknowledging the importance of acceptance issues, small and medium-sized enterprises often lack coherent strategies to identify barriers and foster acceptance. Therefore, in this article, we present a collection of crucial acceptance factors with regard to collaborative robot use at the industrial workplace. Based on these factors, we present a web-based tool to estimate employee acceptance, to provide company representatives with practical recommendations and to stimulate reflection on acceptance issues. An evaluation with three German small and medium-sized enterprises reveals that the tool’s concept meets the demands of small and medium-sized enterprises and is perceived as beneficial as it raises awareness and deepens knowledge on this topic. In order to realise economic potentials, further low-threshold usable tools are needed to transfer research findings into the daily practice of small and medium-sized enterprises.
Recent Advances in Antenna Design for 5G Heterogeneous Networks
Authors: Elfergani Issa , Hussaini Abubakar Sadiq , Rodriguez Jonathan , Abd-Alhameed Raed A.
Published: January 2022

Fifth-generation will support significantly faster mobile broadband speeds, low latency, and reliable communications, as well as enabling the full potential of the Internet of Things (IoT) [...]
Enhanced Millimeter-Wave 3-D Imaging via Complex-Valued Fully Convolutional Neural Network
Authors: Jing Handan , Li Shiyong , Miao Ke , Wang Shuoguang , Cui Xiaoxi , Zhao Guoqiang , Sun Houjun
Published: January 2022

To solve the problems of high computational complexity and unstable image quality inherent in the compressive sensing (CS) method, we propose a complex-valued fully convolutional neural network (CVFCNN)-based method for near-field enhanced millimeter-wave (MMW) three-dimensional (3-D) imaging. A generalized form of the complex parametric rectified linear unit (CPReLU) activation function with independent and learnable parameters is presented to improve the performance of CVFCNN. The CVFCNN structure is designed, and the formulas of the complex-valued back-propagation algorithm are derived in detail, in response to the lack of a machine learning library for a complex-valued neural network (CVNN). Compared with a real-valued fully convolutional neural network (RVFCNN), the proposed CVFCNN offers better performance while needing fewer parameters. In addition, it outperforms the CVFCNN that was used in radar imaging with different activation functions. Numerical simulations and experiments are provided to verify the efficacy of the proposed network, in comparison with state-of-the-art networks and the CS method for enhanced MMW imaging.
Modeling and Fabrication of a Reconfigurable RF Output Stage for Nanosatellite Communication Subsystems
Authors: Alvarez-Flores Jose L. , Flores-Troncoso Jorge , Soriano-Equigua Leonel , Simón Jorge , Castillo Joel A. , Parra-Michel Ramón , Rodriguez-Abdala Viktor I.
Published: January 2022

Current small satellite platforms such as CubeSats require robust and versatile communication subsystems that allow the reconfiguration of the critical operating parameters such as carrier frequency, transmission power, bandwidth, or filter roll-off factor. A reconfigurable Analog Back-End for the space segment of a satellite communication subsystem is presented in this work. This prototype is implemented on a 9.5 cm2 6-layer PCB, and it operates from 0.070 to 6 GHz and complies with CubeSat and IPC-2221 standards. The processing, control, and synchronizing stages are carried out on a Software-Defined Radio approach executed on a baseband processor. Results showed that the signal power at the output of the proposed Analog Back-End is suitable for feeding the following antenna subsystem. Furthermore, the emitted radiation levels by the transmission lines do not generate electromagnetic interference.
Underwater Image Enhancement Using Improved CNN Based Defogging
Authors: Zheng Meicheng , Luo Weilin
Published: January 2022

Due to refraction, absorption, and scattering of light by suspended particles in water, underwater images are characterized by low contrast, blurred details, and color distortion. In this paper, a fusion algorithm to restore and enhance underwater images is proposed. It consists of a color restoration module, an end-to-end defogging module and a brightness equalization module. In the color restoration module, a color balance algorithm based on CIE Lab color model is proposed to alleviate the effect of color deviation in underwater images. In the end-to-end defogging module, one end is the input image and the other end is the output image. A CNN network is proposed to connect these two ends and to improve the contrast of the underwater images. In the CNN network, a sub-network is used to reduce the depth of the network that needs to be designed to obtain the same features. Several depth separable convolutions are used to reduce the amount of calculation parameters required during network training. The basic attention module is introduced to highlight some important areas in the image. In order to improve the defogging network’s ability to extract overall information, a cross-layer connection and pooling pyramid module are added. In the brightness equalization module, a contrast limited adaptive histogram equalization method is used to coordinate the overall brightness. The proposed fusion algorithm for underwater image restoration and enhancement is verified by experiments and comparison with previous deep learning models and traditional methods. Comparison results show that the color correction and detail enhancement by the proposed method are superior.
Joint Estimation of SOC and Available Capacity of Power Lithium-Ion Battery
Authors: Huang Bo , Liu Changhe , Hu Minghui , Li Lan , Jin Guoqing , Yang Huiqian
Published: January 2022

Temperature has an important effect on the battery model. A dual-polarization equivalent circuit model considering temperature is established to quantify the effect of temperature, and the initial parameters of the model are identified through experiments. To solve the defect of preset noise, the H-infinity filter algorithm is used to replace the traditional extended Kalman filter algorithm, without assuming that the process noise and measurement noise obey Gaussian distribution. To eliminate the influence of battery aging on SOC estimation, and considering the different time-varying characteristics of the battery states and parameters, the dual time scale double H-infinity filter is used to jointly estimate the revised SOC and available capacity. The simulation results at two temperatures show that, compared with the single time scale, the double time scale double H-infinity filter reduces the simulation time by nearly 90% under the premise that the accuracy is almost unchanged, which proves that the proposed joint estimation algorithm has the dual advantages of high precision and high efficiency.
Pipeline Leak Detection and Estimation Using Fuzzy PID Observer
Authors: Jafari Raheleh , Razvarz Sina , Vargas-Jarillo Cristóbal , Gegov Alexander , Arabikhan Farzad
Published: January 2022

A pipe is a ubiquitous product in the industries that is used to convey liquids, gases, or solids suspended in a liquid, e.g., a slurry, from one location to another. Both internal and external cracking can result in structural failure of the industrial piping system and possibly decrease the service life of the equipment. The chaos and complexity associated with the uncertain behaviour inherent in pipeline systems lead to difficulty in detection and localisation of leaks in real time. The timely detection of leakage is important in order to reduce the loss rate and serious environmental consequences. The objective of this paper is to propose a new leak detection method based on an autoregressive with exogenous input (ARX) Laguerre fuzzy proportional-integral-derivative (PID) observation system. The objective of this paper is to propose a new leak detection method based on an autoregressive with exogenous input (ARX) Laguerre fuzzy proportional-integral-derivative (PID) observation system. In this work, the ARX–Laguerre model has been used to generate better performance in the presence of uncertainty. According to the results, the proposed technique can detect leaks accurately and effectively.
An Efficient Method for Generating Adversarial Malware Samples
Authors: Ding Yuxin , Shao Miaomiao , Nie Cai , Fu Kunyang
Published: January 2022

Deep learning methods have been applied to malware detection. However, deep learning algorithms are not safe, which can easily be fooled by adversarial samples. In this paper, we study how to generate malware adversarial samples using deep learning models. Gradient-based methods are usually used to generate adversarial samples. These methods generate adversarial samples case-by-case, which is very time-consuming to generate a large number of adversarial samples. To address this issue, we propose a novel method to generate adversarial malware samples. Different from gradient-based methods, we extract feature byte sequences from benign samples. Feature byte sequences represent the characteristics of benign samples and can affect classification decision. We directly inject feature byte sequences into malware samples to generate adversarial samples. Feature byte sequences can be shared to produce different adversarial samples, which can efficiently generate a large number of adversarial samples. We compare the proposed method with the randomly injecting and gradient-based methods. The experimental results show that the adversarial samples generated using our proposed method have a high successful rate.
Mobility-Aware Hybrid Flow Rule Cache Scheme in Software-Defined Access Networks
Authors: Kim Youngjun , Park Jinwoo , Kyung Yeunwoong
Published: January 2022

Due to the dynamic mobility feature, the proactive flow rule cache method has become one promising solution in software-defined networking (SDN)-based access networks to reduce the number of flow rule installation procedures between the forwarding nodes and SDN controller. However, since there is a flow rule cache limit for the forwarding node, an efficient flow rule cache strategy is required. To address this challenge, this paper proposes the mobility-aware hybrid flow rule cache scheme. Based on the comparison between the delay requirement of the incoming flow and the response delay of the controller, the proposed scheme decides to install the flow rule either proactively or reactively for the target candidate forwarding nodes. To find the optimal number of proactive flow rules considering the flow rule cache limits, an integer linear programming (ILP) problem is formulated and solved using the heuristic method. Extensive simulation results demonstrate that the proposed scheme outperforms the existing schemes in terms of the flow table utilization ratio, flow rule installation delay, and flow rules hit ratio under various settings.
Electronically Adjustable Grounded Memcapacitor Emulator Based on Single Active Component with Variable Switching Mechanism
Authors: Petrović Predrag B.
Published: January 2022

New current mode grounded memcapacitor emulator circuits are reported in this paper, based on a single voltage differencing transconductance amplifier-VDTA and two grounded capacitors. The proposed circuits possess a single active component matching constraint, while the MOS-capacitance can be used instead of classical capacitance in a situation involving the simulator working within a high frequency range of up to 50 MHz, thereby offering obvious benefits in terms of realization utilising an IC-integrated circuit. The proposed emulator offers a variable switching mechanism—soft and hard—as well as the possibility of generating a negative memcapacitance characteristic, depending on the value of the frequency of the input current signal and the applied capacitance. The influence of possible non-ideality and parasitic effects was analysed, in order to reduce their side effects and bring the outcome to acceptable limits through the selection of passive elements. For the verification purposes, a PSPICE simulation environment with CMOS 0.18 μm TSMC technology parameters was selected. An experimental check was performed with off-the-shelf components-IC MAX435, showing satisfactory agreement with theoretical assumptions and conclusions.
Verification in Relevant Environment of a Physics-Based Synthetic Sensor for Flow Angle Estimation
Authors: Lerro Angelo , Gili Piero , Pisani Marco
Published: January 2022

In the area of synthetic sensors for flow angle estimation, the present work aims to describe the verification in a relevant environment of a physics-based approach using a dedicated technological demonstrator. The flow angle synthetic solution is based on a model-free, or physics-based, scheme and, therefore, it is applicable to any flying body. The demonstrator also encompasses physical sensors that provide all the necessary inputs to the synthetic sensors to estimate the angle-of-attack and the angle-of-sideslip. The uncertainty budgets of the physical sensors are evaluated to corrupt the flight simulator data with the aim of reproducing a realistic scenario to verify the synthetic sensors. The proposed approach for the flow angle estimation is suitable for modern and future aircraft, such as drones and urban mobility air vehicles. The results presented in this work show that the proposed approach can be effective in relevant scenarios even though some limitations can arise.
Coordinated Control of Voltage Balancers for the Regulation of Unbalanced Voltage in a Multi-Node Bipolar DC Distribution Network
Authors: Guo Chunsheng , Wang Yuhong , Liao Jianquan
Published: January 2022

In a bipolar DC distribution network, the unbalanced load resistance, line resistance and renewable energy source will cause an unbalanced current for each node of the neutral line and lead to its unbalanced voltage. This is a unique power quality problem of bipolar DC distribution networks, which will increase the power loss in the network and lead to overcurrent protection of the neutral line in serious cases. A voltage balancer can be adopted to suppress the unbalanced voltage and current. However, the existing literature does not consider the consistent application of multiple voltage balancers in a multi-node bipolar DC distribution network. This paper creatively proposes a consensus control topology combining primary control and secondary control in a radial multi-node bipolar DC distribution network with voltage balancers. In this paper, the formulas for the positive and negative current and duty cycle of a bipolar DC distribution network with voltage balancers are derived, and improved voltage balancer modeling based on a consensus algorithm is built. The radial multi-node bipolar DC distribution network is established in MATLAB/Simulink. The simulation results compare the consensus control with the traditional droop control and verify the effectiveness of the new control structure with voltage balancers.
Fine Grained Access Control Based on Smart Contract for Edge Computing
Authors: Zhu Yong , Wu Xiao , Hu Zhihui
Published: January 2022

Traditional centralized access control faces data security and privacy problems. The core server is the main target to attack. Single point of failure risk and load bottleneck are difficult to solve effectively. And the third-party data center cannot protect data owners. Traditional distributed access control faces the problem of how to effectively solve the scalability and diversified requirements of IoT (Internet of Things) applications. SCAC (Smart Contract-based Access Control) is based on ABAC (Attributes Based Access Control) and RBAC (Role Based Access Control). It can be applied to various types of nodes in different application scenarios that attributes are used as basic decision elements and authorized by role. The research objective is to combine the efficiency of service orchestration in edge computing with the security of consensus mechanism in blockchain, making full use of smart contract programmability to explore fine grained access control mode on the basis of traditional access control paradigm. By designing SSH-based interface for edge computing and blockchain access, SCAC parameters can be found and set to adjust ACLs (Access Control List) and their policies. The blockchain-edge computing combination is powerful in causing significant transformations across several industries, paving the way for new business models and novel decentralized applications. The rationality on typical process behavior of management services and data access control be verified through CPN (Color Petri Net) tools 4.0, and then data statistics on fine grained access control, decentralized scalability, and lightweight deployment can be obtained by instance running in this study. The results show that authorization takes into account both security and efficiency with the “blockchain-edge computing” combination.
Steering a Robotic Wheelchair Based on Voice Recognition System Using Convolutional Neural Networks
Authors: Bakouri Mohsen , Alsehaimi Mohammed , Ismail Husham Farouk , Alshareef Khaled , Ganoun Ali , Alqahtani Abdulrahman , Alharbi Yousef
Published: January 2022

Many wheelchair people depend on others to control the movement of their wheelchairs, which significantly influences their independence and quality of life. Smart wheelchairs offer a degree of self-dependence and freedom to drive their own vehicles. In this work, we designed and implemented a low-cost software and hardware method to steer a robotic wheelchair. Moreover, from our method, we developed our own Android mobile app based on Flutter software. A convolutional neural network (CNN)-based network-in-network (NIN) structure approach integrated with a voice recognition model was also developed and configured to build the mobile app. The technique was also implemented and configured using an offline Wi-Fi network hotspot between software and hardware components. Five voice commands (yes, no, left, right, and stop) guided and controlled the wheelchair through the Raspberry Pi and DC motor drives. The overall system was evaluated based on a trained and validated English speech corpus by Arabic native speakers for isolated words to assess the performance of the Android OS application. The maneuverability performance of indoor and outdoor navigation was also evaluated in terms of accuracy. The results indicated a degree of accuracy of approximately 87.2% of the accurate prediction of some of the five voice commands. Additionally, in the real-time performance test, the root-mean-square deviation (RMSD) values between the planned and actual nodes for indoor/outdoor maneuvering were 1.721 × 10−5 and 1.743 × 10−5, respectively.
A Road towards 6G Communication—A Review of 5G Antennas, Arrays, and Wearable Devices
Authors: Ikram Muhammad , Sultan Kamel , Lateef Muhammad Faisal , Alqadami Abdulrahman S. M.
Published: January 2022

Next-generation communication systems and wearable technologies aim to achieve high data rates, low energy consumption, and massive connections because of the extensive increase in the number of Internet-of-Things (IoT) and wearable devices. These devices will be employed for many services such as cellular, environment monitoring, telemedicine, biomedical, and smart traffic, etc. Therefore, it is challenging for the current communication devices to accommodate such a high number of services. This article summarizes the motivation and potential of the 6G communication system and discusses its key features. Afterward, the current state-of-the-art of 5G antenna technology, which includes existing 5G antennas and arrays and 5G wearable antennas, are summarized. The article also described the useful methods and techniques of exiting antenna design works that could mitigate the challenges and concerns of the emerging 5G and 6G applications. The key features and requirements of the wearable antennas for next-generation technology are also presented at the end of the paper.
Selection of the Optimal Window Type and Orientation for the Two Cities in Serbia and One in Slovakia
Authors: Djoković Jelena M. , Nikolić Ružica R. , Bujnak Jan , Hadzima Branislav , Pastorek Filip , Dwornicka Renata , Ulewicz Robert
Published: January 2022

The necessity of having windows on any building’s façade is not questionable. However, not every window is suitable for any building. The selection of an adequate window must include the analysis of various factors—the most important ones are the type of window (e.g., single or double glazing); filling gas in cavities (e.g., air, argon or some other gas); and placing, i.e., orientation of a window on a façade (facing north, south, or east, etc.). The research presented in this paper is dealing with the calculation of the window thermal loading for the cities of Kragujevac and Bor in Serbia and Žilina in Slovakia. These three cities were selected because they belong to different climate regions, according to the Köppen–Geiger climatic classification. The first two cities in Serbia belong to the same region Cf with difference only in the category of summer—Kragujevac Cfa and Bor Cfb—while the third city—Žilina in Slovakia—belongs to the Dfb region. The calculated thermal loading through the window was obtained as a sum of the thermal loading due to the heat conduction and thermal loading due to the solar radiation. The objective was to find the optimal window construction and orientation of a building’s façade for each of these cities, by varying the type of the window, its frame material and the filling gas. The results show that for the first two cities in Serbia, there is a difference in the window frame material in the optimal window construction, while for the third city (Žilina in Slovakia), the results are the same as for the second city (Bor in Serbia) despite the fact that they belong to different climate regions (Cfb and Dfb, respectively). These results support the fact that the climate affects the optimal window construction for any city/region in the world.
Cascaded H-Bridge Converter Based on Current-Source Inverter with DC Links Magnetically Coupled to Reduce the DC Inductors Value
Authors: Melín Pedro E. , Baier Carlos R. , Espinosa Eduardo E. , Espinoza José R.
Published: January 2022

The main drawback of the Cascaded-H Bridge converter based on three-phase/single-phase current-source inverters is the large DC inductors needed to limit the variation of the DC current caused by the single-phase inverter oscillating power. If the oscillating power is somehow compensated, then the DC inductor can be designed just as a function of the semiconductors’ switching frequency, reducing its value. This work explores the use of three-phase/single-phase cells magnetically coupled through their DC links to compensate for the oscillating power among them and, therefore, reduce the DC inductor value. At the same time, front ends controlled by a non-linear control strategy equalize the DC currents among coupled cells to avoid saturating the magnetic core. The effectiveness of the proposal is demonstrated using mathematical analysis and corroborated by computational simulation for a 110 kVA load per phase and experimental tests in a 2 kVA laboratory prototype. The outcomes show that for the tested cases, coupling the DC links by a 1:1 ratio transformer allows reducing the DC inductor value below 20% of the original DC inductor required. The above leads to reducing by 50% the amount of magnetic energy required in the DC link compared to the original topology without oscillating power compensation, keeping the quality of the cell input currents and the load voltage.
Automatic PRPD Image Recognition of Multiple Simultaneous Partial Discharge Sources in On-Line Hydro-Generator Stator Bars
Authors: Araújo Ramon C. F. , de Oliveira Rodrigo M. S. , Barros Fabrício J. B.
Published: January 2022

In this study, a methodology for automatic recognition of multiple simultaneous types of partial discharges (PDs) in hydro-generator stator windings was proposed. All the seven PD sources typical in rotating machines were considered, and up to three simultaneous sources could be identified. The functionality of identifying samples with no valid PDs was also incorporated using a new technique. The data set was composed of phase-resolved partial discharge (PRPD) patterns obtained from on-line measurements of hydro-generators. From an input PRPD, noise and interference were removed with an improved version of an image-based denoising algorithm previously proposed by the authors. Then, a novel image-based algorithm that separates partially superposed PD clouds was proposed, by decomposing the input pattern into two sub-PRPDs containing discharges of different natures. From the sub-PRPDs, one extracts features quantifying the PD distribution over amplitudes and the contour of PD clouds. Those features are fed as inputs to several artificial neural networks (ANNs), each of which solves a part of the classification problem and acts as a block of a larger system. Once trained, ANNs work collaboratively to identify an unknown sample. Good results were obtained, with overall accuracies ranging from 88% to 94.8% for all the considered PD sources.
A Calibration of the Solar Load Ratio Method to Determine the Heat Gain in PV-Trombe Walls
Authors: Bruno Roberto , Bevilacqua Piero , Cirone Daniela , Perrella Stefania , Rollo Antonino
Published: January 2022

The Trombe wall is a passive system used in buildings that indirectly transfers thermal energy to the adjacent environment by radiation and convection, and directly by the thermo-circulation that arises in the air cavity delimited between a transparent and an absorbing surface. Nevertheless, the latter is painted black to increase the energy gains, but this produces a negative visual impact and promotes the overheating risk in summer. To mitigate these aspects, a hybrid Trombe wall equipped with PV panels can be employed. The PV installation results in a more pleasing wall appearance and the overheating risk reduces because part of the absorbed solar radiation is transformed into electricity. To determine the actual performance of a such system, transient simulation tools are required to consider properly the wall thermal storage features, variation of the optical properties, air thermo-circulation, and PV power production. Alternatively, regarding the traditional Trombe wall, the literature provides a simplified empirical method based on the dimensionless parameter solar load ratio (SLR) that allows for preliminary evaluations and design. In this paper, the SLR method was calibrated to determine the monthly auxiliary energy to be supplied in buildings equipped with PV-Trombe walls in heating applications. The SLR method was tuned by a multiple linear regression by data provided by TRNSYS simulation that allowed to obtain the energy performances in actual conditions of PV-Trombe walls installed on the same building but located in different localities. The comparison between the TRNSYS results and the calibrated SLR method determined average errors ranging between 0.7% and 1.4%, demonstrating the validity of the proposed methodology.
Physicochemical Properties of Torrefied and Pyrolyzed Food Waste Biochars as Fuel: A Pilot-Scale Study
Authors: Ahn Kwang-Ho , Shin Dong-Chul , Jung Jinhong , Jeong Yoonah , Lee Ye-Eun , Kim I-Tae
Published: January 2022

Food waste is an important constituent of municipal solid waste, and research has been conducted to develop various methods for treating food waste and recycling it (e.g., fuel, landfilling, composting, conversion into animal feed, drying, and carbonization). Among these, the drying and carbonization techniques can change food waste into fuel; however, they need more energy than fermentation and anaerobic digestion procedures. In this study, we investigated the physicochemical properties of food waste biochar produced under torrefaction (270 °C) and pyrolysis (450 °C) conditions to establish its applicability as fuel by comparing temperatures, residence times, and conditions before and after demineralization. The higher heating value increased after the demineralization process under both temperature conditions (270 °C and 450 °C), and the chlorine level was lower at 270 °C temperature demineralization than at 450 °C. During the demineralization process, Na and K were better removed than Ca and Mg. Additionally, Cr, Hg, Cd, and Pb levels were lower than those according to the European Union and Korean domestic bio-SRF recovered fuel criteria, confirming the applicability of biochar as fuel.
Modeling Multivalued Dynamic Series of Financial Indexes on the Basis of Minimax Approximation
Authors: Mamedov Zahid , Vygodchikova Irina , Aliev Ayaz , Gurieva Lira , Rud Natalia
Published: January 2022

In this article, the problem of modeling a time series using the Minimax method is considered. The expediency of using Minimax to identify points of change in trends and the range of changes in the graphical figures of technical analysis is justified. Spline approximation of the dynamic process with range constraints was performed to improve the quality of the model. Investors are advised to refrain from making hasty decisions in favor of holding reliable shares (such as PJSC Novatek shares), rather than selling them. The purchase of new shares should be carefully analyzed. Through an approximation of the dynamic number of the applicable optimization problem of minimizing the maximum Hausdorff distances between the ranges of the dynamic series and the values of the approximating function, the applied approach can provide reliable justification for signals to buy shares. Energy policy occupies the highest place in the list of progress ratings according to news analytics of businesses related to the energy sector of the economy. At the same time, statistical indicators and technologies of expert developments in this field, including intellectual analysis, can become an important basis for the development of a robotic knowledge program in the field under study, an organic addition to which is the authors’ methodology of development in energy economics as in energy policy. This paper examines the model of approximation of the multivalued time series of PJSC Novatek, represented as a series of ranges of numerical values of the indicators of financial markets, with constraints on the approximating function. The authors consider it advisable for promising companies to apply this approach for successful long-term investment.
Forecasting of Wind and Solar Farm Output in the Australian National Electricity Market: A Review
Authors: Boland John , Farah Sleiman , Bai Lei
Published: January 2022

Accurately forecasting the output of grid connected wind and solar systems is critical to increasing the overall penetration of renewables on the electrical network. This is especially the case in Australia, where there has been a massive increase in solar and wind farms in the last 15 years, as well as in roof top solar, both domestic and commercial. For example, in 2020, 27% of the electricity in Australia was from renewable sources, and in South Australia almost 60% was from wind and solar. In the literature, there has been extensive research reported on solar and wind resource, entailing both point and interval forecasts, but there has been much less focus on the forecasting of output from wind and solar systems. In this review, we canvass both what has been reported and also what gaps remain. In the case of the latter topic, there are numerous aspects that are not well dealt with in the literature. We have added discussion on the value of forecasts, rather than just focusing on forecast skill. Further, we present a section on how to deal with conditionally changing variance, a topic that has little focus in the literature. One other topic may be particularly important in Australia at the moment, but may become more widespread. This is how to deal with the concept of a clear sky output from a solar farm when the field is oversized compared to the inverter capacity, resulting in a plateau for the output.
Biogas Generation from Maize and Cocksfoot Growing in Degraded Soil Enriched with New Zeolite Substrate
Authors: Chomczyńska Mariola , Pawłowska Małgorzata , Szczepaniak Oliwia , Duma Ewelina
Published: January 2022

Degraded lands are potential areas for obtaining biomass which can serve as an energy source after its conversion into biogas. Thus, the studies on biogas production from maize and cocksfoot biomasses obtained from degraded soil supplemented with additions of new zeolite substrate (Z-ion as the nutrient carrier) and on arable soil (reference soil) were carried out during batch digestion tests. It was found that the biogas and biomethane potentials and specific energy of the test species growing in degraded soil enriched with Z-ion additions (1% and 5% v/v in the cases of cocksfoot and maize, respectively) did not differ significantly from the values of these parameters that were found for the plants growing in arable soil. The application of Z-ion to the degraded soil (especially in a dose of 5% v/v) resulted in an increase in the nitrogen content and decrease (below the lower optimum value) in the C/N ratio in the plant biomass. However, these changes did not negatively influence the final values of the biogas or methane potentials or the specific energy found for the maize biomass. Therefore, the study results indicated the usefulness of Z-ion substrate for improving the growth conditions for energy crops in degraded soils and, as a consequence, obtaining a plant feedstock suitable for the digestion process.
A Comparative Study of Equivalent Circuit Models for Electro-Chemical Impedance Spectroscopy Analysis of Proton Exchange Membrane Fuel Cells
Authors: Zhao Lei , Dai Haifeng , Pei Fenglai , Ming Pingwen , Wei Xuezhe , Zhou Jiangdong
Published: January 2022

Electrochemical impedance spectroscopy is one of the important tools for the performance analysis and diagnosis of proton exchange membrane fuel cells. The equivalent circuit model is an effective method for electrochemical impedance spectroscopy resolution. In this paper, four typical equivalent circuit models are selected to comprehensively compare and analyze the difference in the fitting results of the models for the electrochemical impedance spectroscopy under different working conditions (inlet pressure, stoichiometry, and humidity) from the perspective of the fitting accuracy, change trend of the model parameters, and the goodness of fit. The results show that the fitting accuracy of the model with the Warburg element is the best for all under each working condition. When considering the goodness of fit, the model with constant phase components is the best choice for fitting electrochemical impedance spectroscopy under different inlet pressure and air stoichiometry. However, under different air humidity, the model with the Warburg element is best. This work can help to promote the development of internal state analysis, estimation, and diagnosis of the fuel cell based on the equivalent circuit modeling of electrochemical impedance spectroscopy.
OC6 Phase Ia: CFD Simulations of the Free-Decay Motion of the DeepCwind Semisubmersible
Authors: Wang Lu , Robertson Amy , Jonkman Jason , Kim Jang , Shen Zhi-Rong , Koop Arjen , Borràs Nadal Adrià , Shi Wei , Zeng Xinmeng , Ransley Edward , Brown Scott , Hann Martyn , Chandramouli Pranav , Viré Axelle , Ramesh Reddy Likhitha , Li Xiang , Xiao Qing , Méndez López Beatriz , Campaña Alonso Guillén , Oh Sho , Sarlak Hamid , Netzband Stefan , Jang Hyunchul , Yu Kai
Published: January 2022

Currently, the design of floating offshore wind systems is primarily based on mid-fidelity models with empirical drag forces. The tuning of the model coefficients requires data from either experiments or high-fidelity simulations. As part of the OC6 (Offshore Code Comparison Collaboration, Continued, with Correlation, and unCertainty (OC6) is a project under the International Energy Agency Wind Task 30 framework) project, the present investigation explores the latter option. A verification and validation study of computational fluid dynamics (CFD) models of the DeepCwind semisubmersible undergoing free-decay motion is performed. Several institutions provided CFD results for validation against the OC6 experimental campaign. The objective is to evaluate whether the CFD setups of the participants can provide valid estimates of the hydrodynamic damping coefficients needed by mid-fidelity models. The linear and quadratic damping coefficients and the equivalent damping ratio are chosen as metrics for validation. Large numerical uncertainties are estimated for the linear and quadratic damping coefficients; however, the equivalent damping ratios are more consistently predicted with lower uncertainty. Some difference is observed between the experimental and CFD surge-decay motion, which is caused by mechanical damping not considered in the simulations that likely originated from the mooring setup, including a Coulomb-friction-type force. Overall, the simulations and the experiment show reasonable agreement, thus demonstrating the feasibility of using CFD simulations to tune mid-fidelity models.
Electric Vehicles: Bibliometric Analysis of the Current State of the Art and Perspectives
Authors: Barbosa Willams , Prado Thomaz , Batista Cleovano , Câmara Julio César , Cerqueira Rodrigo , Coelho Rodrigo , Guarieiro Lilian
Published: January 2022

In order to gain a comprehensive view of electric vehicles (EVs) technologies and understand the emphasis of current research, this study evaluated the most relevant themes related to EVs through a bibliometric analysis using the keyword “electric vehicle” as the input. The Web of ScienceTM (WoS) database was used because it is considered ideal for bibliometric analysis. The VOSviewer software was adopted as a bibliometric analysis tool to visualize the networks of authors, countries, journals and keywords. The analysis carried out on 9 November 2021 retrieved a total of 29,304 documents in the period 2000 to 2021. The results show that in the last nine years the number of publications about EVs has grown significantly. The China is the leading nation in the field of EV research, contributing the largest number of publications in the world, with the main authors and research institutions involved. The journal Energies stands out as the main publishing periodical. Keyword analysis showed that studies on EVs in the last two decades have focused on themes related to energy management and storage, infrastructure and charging systems and environmental issues. The bibliometric analysis presented provides relevant information on the main themes studied about EVs and technological advances in development.
Dynamic Expression of the Homeobox Factor PBX1 during Mouse Testis Development
Authors: Moisan Vanessa , Brousseau Catherine , Tremblay Jacques J.
Published: January 2022

Members of the pre-B-cell leukemia transcription factor (PBX) family of homeoproteins are mainly known for their involvement in hematopoietic cell differentiation and in the development of leukemia. The four PBX proteins, PBX1, PBX2, PBX3 and PBX4, belong to the three amino acid loop extension (TALE) superfamily of homeoproteins which are important transcriptional cofactors in several developmental processes involving homeobox (HOX) factors. Mutations in the human PBX1 gene are responsible for cases of gonadal dysgenesis with absence of male sex differentiation while Pbx1 inactivation in the mouse causes a failure in Leydig cell differentiation and function. However, no data is available regarding the expression profile of this transcription factor in the testis. To fill this knowledge gap, we have characterized PBX1 expression during mouse testicular development. Real time PCRs and Western blots confirmed the presence Pbx1 mRNA and PBX1 protein in different Leydig and Sertoli cell lines. The cellular localization of the PBX1 protein was determined by immunohistochemistry and immunofluorescence on mouse testis sections at different embryonic and postnatal developmental stages. PBX1 was detected in interstitial cells and in peritubular myoid cells from embryonic life until puberty. Most interstitial cells expressing PBX1 do not express the Leydig cell marker CYP17A1, indicating that they are not differentiated and steroidogenically active Leydig cells. In adults, PBX1 was mainly detected in Sertoli cells. The presence of PBX1 in different somatic cell populations during testicular development further supports a direct role for this transcription factor in testis cell differentiation and in male reproductive function.
Correction: Strzałek et al. Activity of 137Cs and 40K Isotopes in Pine (Pinus sylvestris L.) and Birch (Betula pendula Roth) Stands of Different Ages in a Selected Area of Eastern Poland. Forests 2021, 12, 1205
Authors: Strzałek Małgorzata , Barczak Katarzyna , Karwowska Jadwiga , Królak Elżbieta
Published: January 2022

The authors wish to make the following corrections to their paper [...]
Scandinavian Forest Fire Activity Correlates with Proxies of the Baffin Bay Ice Cover
Authors: Drobyshev Igor , Bergeron Yves , Ryzhkova Nina , Kryshen Alexander
Published: January 2022

Understanding factors driving fire activity helps reveal the degree and geographical variability in the resilience of boreal vegetation to large scale climate forces. We studied the association between sea ice cover in the Baffin Bay and the Labrador Sea and observational records of forest fires in two Nordic countries (Norway and Sweden) over 1913–2017. We found a positive correlation between ice proxies and regional fire activity records suggesting that the Arctic climate and the associated changes in North Atlantic circulation exercise an important control on the levels of fire activity in Scandinavia. Changes in the sea cover are likely correlated with the dynamic of the North Atlantic Current. These dynamics may favor the development of the drought conditions in Scandinavia through promoting persistent high-pressure systems over the Scandinavian boreal zone during the spring and summer. These periods are, in turn, associated with an increased water deficit in forest fuels, leading to a regionally increased fire hazard. The Arctic climate will likely be an important future control of the boreal fire activity in the Nordic region.
Physiological and Biochemical Dynamics of Pinus massoniana Lamb. Seedlings under Extreme Drought Stress and during Recovery
Authors: Shao Changchang , Duan Honglang , Ding Guijie , Luo Xianying , Fu Yuanhong , Lou Qing
Published: January 2022

In recent years, global forests have been facing an increase in tree mortality owing to increasing droughts. However, the capacity for plants to adjust their physiology and biochemistry during extreme drought and subsequent recovery is still unclear. Here, we used 1.5-year-old Pinus massoniana Lamb. seedlings and simulated drought conditions to achieve three target stress levels (50%, 85%, and 100% loss of stem hydraulic conductivity (PLC)), followed by rehydration. Needle water status, gas exchange, and biochemical parameters were assessed during drought and recovery. The results showed that drought had significantly negative impacts on needle water status and gas exchange parameters, with gas exchange declining to 0 after PLC85 was achieved. Soluble protein concentration (SPC), soluble sugar concentration (SSC), malondialdehyde (MDA) content, superoxide dismutase (SOD) activity, and needle water-use efficiency showed fluctuations. The activity of antioxidant enzymes and the values of osmotic regulators were then gradually decreased as the physiological and biochemical functions of seedlings were disturbed. Seedlings showed a stronger ability to recover from PLC50 than PLC85 and PLC100. We conclude that the physiological and biochemical recovery of P. massoniana seedlings is more likely to be inhibited when plants experience increasing drought stress that induces 85% and greater loss of hydraulic conductance.
Urban Forest Ecosystem Services Vary with Land Use and Species: A Case Study of Kyoto City
Authors: Kang Jiefeng , Hirabayashi Satoshi , Shibata Shozo
Published: January 2022

The demand for urban ecosystem services increases with the rapid growth of the urban population. The urban forest is a crucial ecosystem services provider in cities. To achieve a better estimation of urban ecosystem services, an understanding of the link between heterogeneity and ecosystem services within cities is needed. Other than street trees and forest remnants, the contribution of dispersed green spaces should also be considered. In this study, a ground-based sample quadrat investigation of trees across a sequence of land types in Kyoto City was applied. The ecosystem services and monetary values of trees were further calculated using a customized i-Tree Eco tool. The ecosystem services calculated include carbon storage and sequestration, air pollutants removal, and runoff reduction. Ecosystem services of different land use classes were compared at both quadrat and single-tree levels. We found no significant difference across land use for all the ecosystem services at the quadrat level. However, ecosystem services were different across land use at the single-tree level. We performed a species-specific analysis and found that the pattern of ecosystem services at the single-tree level across land use varies with both the service tested and species. Our study suggests that the heterogeneity within a city should be considered when estimating urban ecosystem services. The results also provide insight into the urban green space management of Kyoto City.
Quantifying the Life Cycle Greenhouse Gas Emissions of a Mechanized Shelterwood Harvest Producing Both Sawtimber and Woodchips
Authors: Weyrens Joshua P. , Therasme Obste , Germain René H.
Published: January 2022

Forests are used to mitigate anthropogenic greenhouse gas (GHG) emissions through carbon offset programs, and forest management is generally accepted as “carbon neutral”. However, forest harvesting operations depend heavily on fossil fuels, so it would be remiss to broadly paint all forms of management as carbon neutral without empirical verification of this claim. Biomass feedstock, as a means to supplant fossil fuel consumption, has received the bulk of investigative efforts, as the carbon benefit of biomass is one of the most contentious among wood products, because it does not create long-term carbon storage. A life cycle assessment (LCA) was conducted on a winter shelterwood harvest occurring in the Adirondacks of upstate New York. Primary data were collected daily throughout the operation and used to model the impact attributed to producing clean chips and logs for delivery to a pulp mill and sawmill, respectively. This harvest produced 4894 Mg of clean chips and 527 Mg of sawtimber. We calculated that 39.77 and 25.16 kg of carbon dioxide equivalent were emitted per Mg of clean chips and sawtimber, respectively, with a total observed flow of GHG into the atmosphere between 206 and 210 thousand kilograms. The results contribute to our understanding of the global warming potential of implementing a forest harvest to produce raw materials for medium- and long-term carbon storage products such as paper and dimensional hardwood lumber.