bluuebunny/crossref_metadata_2025 huggingface dataset:
A Fault-Tolerant Bidirectional Converter for Battery Energy Storage Systems in DC Microgrids
Authors: Mahdavi Mohammad Saeed , Karimzadeh Mohammad Saleh , Rahimi Tohid , Gharehpetian Gevork Babamalek
Published: January 2023

Battery energy storage systems (BESSs) can control the power balance in DC microgrids through power injection or absorption. A BESS uses a bidirectional DC–DC converter to control the power flow to/from the grid. On the other hand, any fault occurrence in the power switches of the bidirectional converter may disturb the power balance and stability of the DC microgrid and, thus, the safe operation of the battery bank. This paper presents a fault-tolerant topology along with a fault diagnosis algorithm for a bidirectional DC–DC converter in a BESS. The proposed scheme can detect open circuit faults (OCFs) and reconfigure the topology to guarantee the safe and continuous operation of the system while it is connected to the DC microgrid. The proposed method can be extended to multi-phase structures of interleaved bidirectional DC–DC converters using only two power switches and n TRIACs to support the OCF occurrence on 2 × n switches of n legs. The proposed fault diagnosis algorithm detects OCFs only by observing the current of the inductors and does not require any sensor. Hence, the cost, weight, volume and complexity of the system is considerably reduced. Experimental results show that the reconfiguration of the converter, along with its fast fault detection, leads to fewer switches overloading and less DC voltage deviation.
Quality-Driven Dual-Branch Feature Integration Network for Video Salient Object Detection
Authors: Zhou Xiaofei , Gao Hanxiao , Yu Longxuan , Yang Defu , Zhang Jiyong
Published: January 2023

Video salient object detection has attracted growing interest in recent years. However, some existing video saliency models often suffer from the inappropriate utilization of spatial and temporal cues and the insufficient aggregation of different level features, leading to remarkable performance degradation. Therefore, we propose a quality-driven dual-branch feature integration network majoring in the adaptive fusion of multi-modal cues and sufficient aggregation of multi-level spatiotemporal features. Firstly, we employ the quality-driven multi-modal feature fusion (QMFF) module to combine the spatial and temporal features. Particularly, the quality scores estimated from each level’s spatial and temporal cues are not only used to weigh the two modal features but also to adaptively integrate the coarse spatial and temporal saliency predictions into the guidance map, which further enhances the two modal features. Secondly, we deploy the dual-branch-based multi-level feature aggregation (DMFA) module to integrate multi-level spatiotemporal features, where the two branches including the progressive decoder branch and the direct concatenation branch sufficiently explore the cooperation of multi-level spatiotemporal features. In particular, in order to provide an adaptive fusion for the outputs of the two branches, we design the dual-branch fusion (DF) unit, where the channel weight of each output can be learned jointly from the two outputs. The experiments conducted on four video datasets clearly demonstrate the effectiveness and superiority of our model against the state-of-the-art video saliency models.
Real-Time Finger-Writing Character Recognition via ToF Sensors on Edge Deep Learning
Authors: Zhang Jiajin , Peng Guoying , Yang Hongyu , Tan Chao , Tan Yaqing , Bai Hui
Published: January 2023

Human–computer interaction is demanded for natural and convenient approaches, in which finger-writing recognition has aroused more and more attention. In this paper, a device-free finger-writing character recognition system based on an array of time-of-flight (ToF) distance sensors is presented. The ToF sensors acquire distance values between sensors to a writing finger within a 9.5 × 15 cm square on a surface at specific time intervals and send distance data to a low-power microcontroller STM32F401, equipped with deep learning algorithms for real-time inference and recognition tasks. The proposed method enables one to distinguish 26 English lower-case letters by users writing with their fingers and does not require one to wear additional devices. All data used in this work were collected from 21 subjects (12 males and 9 females) to evaluate the proposed system in a real scenario. In this work, the performance of different deep learning algorithms, such as long short-term memory (LSTM), convolutional neural networks (CNNs) and bidirectional LSTM (BiLSTM), was evaluated. Thus, these algorithms provide high accuracy, where the best result is extracted from the LSTM, with 98.31% accuracy and 50 ms of maximum latency.
A Task Planning Method for UAV Swarm Dynamic Reconstruction Based on a Fourth-Order Motif
Authors: Duan Ting , Wang Weiping , Wang Tao , Huang Meigen , Zhou Xin
Published: January 2023

The primary purpose of task allocation is to build each equipment platform and quickly complete integration planning at the actual combat speed to achieve efficient management of the entire task. In this process, higher requirements are put forward for dynamic, cooperative, and highly adaptive drone colony organization. In this paper, the scheduling problem of hybrid unmanned aerial vehicle (UAV) systems is studied under an uncertain environment. First, the system-capability-task organizational structure is defined and quantified, which lays a foundation for dynamic adjustment of the organizational structure in the future. Then, combined with the theory of flexible network and elastic network management, the model is calculated, and the linear transformation function and fuzzy theory are used to stratify and cluster the capability layers. On this basis, four motif structures are introduced for abnormal nodes in the process of dynamic adjustment, and a dynamic group reconstruction algorithm (DRA-M) is established. Finally, the time and communication load indexes are determined, and the alternative strategy is designed for the failure point. The performance of the classical scheduling algorithm is evaluated by benchmarking it under different conditions. The results show that the algorithm has a good dynamic adjustment ability in the event of a UAV swarm emergency, which is a bright light for the future study of highly adaptive UAV cluster organization.
Limitations of Multi-GNSS Positioning of USV in Area with High Harbour Infrastructure
Authors: Makar Artur
Published: January 2023

Satellite surveying techniques are currently among the main measuring technologies in geodesy and the main technologies in navigation. Modern navigation requires high accuracy of position coordinate determination, particularly in bathymetric surveys and aerial photogrammetry. In most cases, the terrain conditions enable positioning with high accuracy and reliability. These particularly involve the terrain conditions, i.e., high harbour infrastructure for bathymetric surveys and trees for railway surveys that hinder the measurement performance with a pre-determined accuracy. This article presents the limitations in unmanned survey vehicle (USV) positioning in an area restricted by a high quay, and difficult observational conditions in the surrounding high harbour infrastructure. The positioning used a four-system receiver that determined position coordinates based on the signals from one, two, three and four satellite navigation systems. The number of available satellites was determined under conditions of the open upper hemisphere and the partially obscured hemisphere based on the surrounding geometry. The determined position coordinates were related to the position determined using robotic total station (RTS). An area was identified in which it becomes difficult or impossible to maintain the required positioning accuracy.
Study on the Spatial Characteristics and Spillover Effects of Carbon Emissions in the Yangtze River (Main Stream) Basin
Authors: Liu Qiongzhi , Zhao Dapeng
Published: January 2023

Carbon emissions reduction is crucial to global climate governance and sustainable development. By 2060, China envisioned being carbon-neutral, and it has adopted a series of policies and measures for environmental management, especially in the main stream of Yangtze River basin, where China’s carbon emissions are centered. The spatial distribution characteristics and agglomeration effects of carbon dioxide (CO2) emissions in the main stream of Yangtze River basin are analyzed from 2010 to 2019 based on the perspective of local (city and state) administrative regions, and uses the spatial Durbin model to examine the influencing factors and spatial spillover effects of carbon emissions. The findings discovered from the extensive research are as follows: First, carbon emissions in the main stream of Yangtze River basin present a fluctuating upward trend, and CO2 emissions in the lower reaches are significantly higher than those in the middle and upper reaches, which are closely related to the economic volume. Secondly, carbon emissions have a significant positive spatial correlation among prefecture-level cities, and carbon emissions show a high-high concentration in downstream regions and low-low concentration in upstream regions. Thirdly, regional economic development level, secondary industry development level, and population density have considerable influence on CO2 emissions, among which the Kuznets hypothesis is evidenced by the interaction between economic progress and carbon emissions. Therefore, strengthening regional cooperation efforts and collaborating to promote low-carbon development are the vital ways to achieve carbon emissions reduction.
Dual-Layer Q-Learning Strategy for Energy Management of Battery Storage in Grid-Connected Microgrids
Authors: Ali Khawaja Haider , Abusara Mohammad , Tahir Asif Ali , Das Saptarshi
Published: January 2023

Real-time energy management of battery storage in grid-connected microgrids can be very challenging due to the intermittent nature of renewable energy sources (RES), load variations, and variable grid tariffs. Two reinforcement learning (RL)–based energy management systems have been previously used, namely, offline and online methods. In offline RL, the agent learns the optimum policy using forecasted generation and load data. Once the convergence is achieved, battery commands are dispatched in real time. The performance of this strategy highly depends on the accuracy of the forecasted data. An agent in online RL learns the best policy by interacting with the system in real time using real data. Online RL deals better with the forecasted error but can take a longer time to converge. This paper proposes a novel dual layer Q-learning strategy to address this challenge. The first (upper) layer is conducted offline to produce directive commands for the battery system for a 24 h horizon. It uses forecasted data for generation and load. The second (lower) Q-learning-based layer refines these battery commands every 15 min by considering the changes happening in the RES and load demand in real time. This decreases the overall operating cost of the microgrid as compared with online RL by reducing the convergence time. The superiority of the proposed strategy (dual-layer RL) has been verified by simulation results after comparing it with individual offline and online RL algorithms.
Minimizing Internal Leaks of a Powered Roof Support’s Hydraulic Prop Based on Double Block with Charging
Authors: Szurgacz Dawid , Borska Beata , Diederichs Ryszard , Spearing Anthony J. S. , Zhironkin Sergey
Published: January 2023

The hydraulic system of a powered roof support performs two functions. The first function is to control the powered roof support in the extraction wall. The second function is to protect against adverse overloads resulting from rock mass pressing directly on the powered roof support. This damaging phenomenon is prevented by the protection of the powered roof support, with a safety valve built into the hydraulic system or directly into the prop. However, the third function proposed by the authors based on the research results is to minimize leaks. These leaks usually develop in the props or in the hydraulic system. The authors propose implementing changes to the hydraulic system for this purpose. The change consists of replacing the existing support block with a double block with charging. Tests were carried out in real conditions, that is, a mining wall. Tests in the mining wall were carried out on the powered roof support’s leaking prop. As a result of charging, the actual load capacity of the prop increased by about 10–50% in relation to the load capacity before charging. The use of a double block with charging ensured that the pressure in the under-piston space of the prop was maintained at a minimum of 250 bar. The results allowed us to determine the usefulness of the proposed solution and eliminate its disadvantages—the designated direction of research and development on the powered roof support allowed us to expand its functionality by minimizing leaks.
The Impact of Transmission Line Modeling on Lightning Overvoltage
Authors: Leon Colqui Jaimis Sajid , Ribeiro de Moura Rodolfo Antônio , De Oliveira Schroeder Marco Aurélio , Filho José Pissolato , Kurokawa Sérgio
Published: January 2023

In most of the work that investigates the backflashover phenomenon due to direct lightning strikes, using EMT-type simulators, transmission lines are represented by the J. Marti model and the ground effect is computed employing J. R. Carson’s formulations. Thus, the ground displacement current is neglected, the line voltage definition corresponds to the wire potential formulation, and soil resistivity is considered frequency-independent. These considerations can lead to erroneous measurements of the occurrences of the backflashover phenomenon in the insulator strings of transmission line. In this sense, this paper presents a systematic sensitivity analysis study of lightning overvoltage in insulator strings considering more physically consistent models of the transmission line, which consider the displacement current, ground admittance correction, rigorous voltage definition, and frequency-dependent soil parameters. According to the results, for the case study, transmission line parameters modeling can present a maximum percentual difference of around 71.54%, considering the frequency range of first strokes. This difference leads to a percent difference of around 5.25% in the maximum overvoltage across the insulator strings. These differences confirm that the occurrence or not of backflashover in the insulator strings, including the disruption time, are sensitive to the line model considered.
Electric Vehicle Fast Charging: A Congestion-Dependent Stochastic Model Predictive Control under Uncertain Reference
Authors: Di Giorgio Alessandro , De Santis Emanuele , Frettoni Lucia , Felli Stefano , Liberati Francesco
Published: January 2023

This paper presents a control strategy aimed at efficiently operating a service area equipped with stations for plug-in electric vehicles’ fast charging, renewable energy sources, and an electric energy storage unit. The control requirements here considered are in line with the perspective of a service area operator, who aims at avoiding peaks in the power flow at the point of connection with the distribution grid, while providing the charging service in the minimum time. Key aspects of the work include the management of uncertainty in the charging power demand and generation, the design of congestion and state-dependent weights for the cost function, and the comparison of control performances in two different hardware configurations of the plant, namely BUS and UPS connection schemes. All of the above leads to the design of a stochastic model predictive controller aimed at tracking an uncertain power reference, under the effect of an uncertain disturbance affecting the output and the state of the plant in the BUS and UPS schemes respectively. Simulation results show the relevance of the proposed control strategy, according to an incremental validation plan focused on the tracking of selected references, the mitigation of congestion, the stability of storage operation over time, and the mitigation of the effect of uncertainty.
An Effective Power Dispatch of Photovoltaic Generators in DC Networks via the Antlion Optimizer
Authors: Grisales-Noreña Luis Fernando , Rosales-Muñoz Andrés Alfonso , Montoya Oscar Danilo
Published: January 2023

This paper studies the problem regarding the optimal power dispatch of photovoltaic (PV) distributed generators (DGs) in Direct Current (DC) grid-connected and standalone networks. The mathematical model employed considers the reduction of operating costs, energy losses, and CO2 emissions as objective functions, and it integrates all technical and operating constraints implied by DC grids in a scenario of variable PV generation and power demand. As a solution methodology, a master–slave strategy was proposed, whose master stage employs Antlion Optimizer (ALO) for identifying the values of power to be dispatched by each PV-DG installed in the grid, whereas the slave stage uses a matrix hourly power flow method based on successive approximations to evaluate the objective functions and constraints associated with each solution proposed within the iterative process of the ALO. Two test scenarios were considered: a grid-connected network that considers the operating characteristics of the city of Medellín, Antioquia, and a standalone network that uses data from the municipality of Capurganá, Chocó, both of them located in Colombia. As comparison methods, five continuous optimization methods were used which were proposed in the specialized literature to solve optimal power flow problems in DC grids: the crow search algorithm, the particle swarm optimization algorithm, the multiverse optimization algorithm, the salp swarm algorithm, and the vortex search algorithm. The effectiveness of the proposed method was evaluated in terms of the solution, its repeatability, and its processing times, and it obtained the best results with respect to the comparison methods for both grid types. The simulation results obtained for both test systems evidenced that the proposed methodology obtained the best results with regard to the solution, with short processing times for all of the objective functions analyzed.
Recovery and Recycling of Valuable Metals from Spent Lithium-Ion Batteries: A Comprehensive Review and Analysis
Authors: Tawonezvi Tendai , Nomnqa Myalelo , Petrik Leslie , Bladergroen Bernard Jan
Published: January 2023

The recycling of spent lithium-ion batteries (Li-ion Batteries) has drawn a lot of interest in recent years in response to the rising demand for the corresponding high-value metals and materials and the mounting concern emanating from the detrimental environmental effects imposed by the conventional disposal of solid battery waste. Numerous studies have been conducted on the topic of recycling used Li-ion batteries to produce either battery materials or specific chemical, metal or metal-based compounds. Physical pre-treatment is typically used to separate waste materials into various streams, facilitating the effective recovery of components in subsequent processing. In order to further prepare the recovered materials or compounds by applying the principles of materials chemistry and engineering, a metallurgical process is then utilized to extract and isolate pure metals or separate contaminants from a particular waste stream. In this review, the current state of spent Li-ion battery recycling is outlined, reviewed, and analyzed in the context of the entire recycling process, with a particular emphasis on hydrometallurgy; however, electrometallurgy and pyrometallurgy are also comprehensively reviewed. In addition to the comprehensive review of various hydrometallurgical processes, including alkaline leaching, acidic leaching, solvent (liquid-liquid) extraction, and chemical precipitation, a critical analysis of the current obstacles to process optimization during Li-ion battery recycling is also conducted. Moreover, the energy-intensive nature of discussed recycling process routes is also assessed and addressed. This study is anticipated to offer recommendations for enhancing wasted Li-ion battery recycling, and the field can be further explored for commercialization.
The Sensitivity of 5MW Wind Turbine Blade Sections to the Existence of Damage
Authors: Algolfat Amna , Wang Weizhuo , Albarbar Alhussein
Published: January 2023

Due to the large size of offshore wind turbine blades (OWTBs) and the corrosive nature of salt water, OWTs need to be safer and more reliable that their onshore counterparts. To ensure blade reliability, an accurate and computationally efficient structural dynamic model is an essential ingredient. If damage occurs to the structure, the intrinsic properties will change, e.g., stiffness reduction. Therefore, the blade’s dynamic characteristics will differ from those of the intact ones. Hence, symptoms of the damage are reflected in the dynamic characteristics that can be extracted from the damaged blade. Thus, damage identification in OWTBs has become a significant research focus. In this study, modal model characteristics were used for developing an effective damage detection method for WTBs. The technique was used to identify the performance of the blade’s sections and discover the warning signs of damage. The method was based on a vibration-based technique. It was adopted by investigating the influence of reduced blade element rigidity and its effect on the other blade elements. A computational structural dynamics model using Rayleigh beam theory was employed to investigate the behaviour of each blade section. The National Renewable Energy Laboratory (NREL) 5MW blade benchmark was used to demonstrate the behaviour of different blade elements. Compared to previous studies in the literature, where only the simple structures were used, the present study offers a more comprehensive method to identify damage and determine the performance of complicated WTB sections. This technique can be implemented to identify the damage’s existence, and for diagnosis and decision support. The element most sensitive to damage was element number 14, which is NACA_64_618.
Deep Learning for Magnetic Flux Leakage Detection and Evaluation of Oil & Gas Pipelines: A Review
Authors: Huang Songling , Peng Lisha , Sun Hongyu , Li Shisong
Published: January 2023

Magnetic flux leakage testing (MFL) is the most widely used nondestructive testing technology in the safety inspection of oil and gas pipelines. The analysis of MFL test data is essential for pipeline safety assessments. In recent years, deep-learning technologies have been applied gradually to the data analysis of pipeline MFL testing, and remarkable results have been achieved. To the best of our knowledge, this review is a pioneering effort on comprehensively summarizing deep learning for MFL detection and evaluation of oil and gas pipelines. The majority of the publications surveyed are from the last five years. In this work, the applications of deep learning for pipeline MFL inspection are reviewed in detail from three aspects: pipeline anomaly recognition, defect quantification, and MFL data augmentation. The traditional analysis method is compared with the deep-learning method. Moreover, several open research challenges and future directions are discussed. To better apply deep learning to MFL testing and data analysis of oil and gas pipelines, it is noted that suitable interpretable deep-learning models and data-augmentation methods are important directions for future research.
Do Environmental Innovation and Green Energy Matter for Environmental Sustainability? Evidence from Saudi Arabia (1990–2018)
Authors: Kahia Montassar , Jarraya Bilel , Kahouli Bassem , Omri Anis
Published: January 2023

Climate change and global warming, caused by excessive carbon emissions from transportation and other environmentally hazardous activities, are serious problems for many countries nowadays. Therefore, while some countries are not making optimal use of their resources, others are working hard to preserve a green and clean environment in order to foster long-term growth. Governments and policymakers throughout the world are finally starting to take the risks of climate change and global warming seriously. This paper extends previous literature related to environmental design practices by investigating the impacts of environmental innovation and the deployment of green energy on decreasing carbon dioxide (CO2) emissions for Saudi Arabia during the period 1990–2018. Different CO2 emission measures are incorporated in the analysis, namely per capita CO2 emissions, CO2 intensity, CO2 emissions from liquid fuel use, and CO2 emissions from heat and electricity generation. Overall, the outcomes of the autoregressive distributed lag (ARDL) technique demonstrate the presence of a long-term association between our two main variables (green energy use and environmental innovation) and the different measures of CO2 emissions, except CO2 emissions from liquid fuels consumption for green energy use and CO2 intensity for environmental innovation. In another sense, the use of renewable energies and technologies linked to environmental patents proves to be a good alternative if they do not contribute to environmental pollution. On the basis of the results, this study offers several policy recommendations.
Design and Optimization of Organic Rankine Cycle Based on Heat Transfer Enhancement and Novel Heat Exchanger: A Review
Authors: Lu Pei , Liang Zheng , Luo Xianglong , Xia Yangkai , Wang Jin , Chen Kaihuang , Liang Yingzong , Chen Jianyong , Yang Zhi , He Jiacheng , Chen Ying
Published: January 2023

The effective exploitation of renewable energy and the recovery of waste heat are two crucial strategies in achieving carbon neutrality. As an efficient and reliable heat–to–power conversion technology, the organic Rankine cycle (ORC) has been recognized and accepted by academia and industry for use in solar energy, geothermal energy, biomass energy, and waste heat applications. However, there remain unsolved technical challenges related to the design and operation of the components and system. As the exergy destruction and investment cost of heat exchangers exert significant influence on the performance of ORC, investigations on the performance improvement of heat exchangers are of great significance. The aim of this paper was to provide a review on the performance improvement of ORC in relation to heat transfer enhancement, heat exchanger design optimization, and cycle construction based on a novel heat exchanger. The performance of ORC using different types of heat exchangers was discussed and the importance of revealing the influence of heat exchanger structural parameters on ORC performance was assessed. The heat transfer enhancement, novel heat exchanger investigation, and the ORC configuration development based on a novel heat exchanger were emphasized. Finally, developments and current challenges were summarized and future research trends were also identified.
New Topology of a Hybrid, Three-Phase, Four-Wire Shunt Active Power Filter
Authors: Freitas Stefani , Oliveira Luis , Oliveira Priscila , Exposto Bruno , Pinto José , Afonso Joao
Published: January 2023

With a view to reducing harmonic content in electrical power systems, and, consequently, improving power quality level, filters and other harmonic compensation devices are widely used. In the category of filters, they can be distinguished into two classes that are related to the operating mode, active or passive, both widely known and applied in electrical power grids and in the most diverse industry sectors. In this sense, taking into account the use of compensating devices in four-wire electrical systems feeding single-phase, non-linear loads, this paper presents a new hybrid arrangement of harmonic compensation that incorporates both active and passive filtering, which performs all functions concerning the harmonic compensation of a four-leg shunt active power filter. In this hybrid arrangement, the harmonic filtering of positive and negative sequence components is performed by a three-leg shunt active power filter, while the filtering of zero-sequence harmonics is attributed to the electromagnetic zero-sequence suppressor. The results, which confirm the effectiveness of the proposed hybrid arrangement, are proven through simulations and experimental tests in different operating scenarios, revealing a substantial improvement in the system’s power factor, as well as a reduction in harmonic distortions.
Energy Saving Optimization Technique-Based Routing Protocol in Mobile Ad-Hoc Network with IoT Environment
Authors: Krishnamoorthy Vinoth Kumar , Izonin Ivan , Subramanian Sugumaran , Shandilya Shishir Kumar , Velayutham Sivasankaran , Munichamy Thillai Rani , Havryliuk Myroslav
Published: January 2023

The Mobile Ad-hoc Network is a self-configuring decentralized network, where the network topology is dynamically modifiable. The IoT (Internet of Things) based Wireless Sensor Network contains more sensors and shares information over the Internet to a cloud server. However, the IoT-based wireless sensor network channel has moderate security is poor compared to MANET and packet loss is increased due to attackers. In IoT, all the sensors forward the detected data frequently to the internet gateway, so the energy saving in the network is low compared to MANET. In this work, the smart environment of IoT, Wireless Sensor Networks (WSN) and MANET make a great heterogeneous network in IT Technology; the combination of this heterogeneous network has new challenging issues. In this heterogeneous network, MANET provides a trusted route between the sensor to gateway nodes into the IoT environment using Energy Saving Optimization Techniques [MANET-ESO in IoT]. It saves energy for each node and reduces the economic level. The results of the ns-3 simulation show that the proposed method provides better results in Alive node counts, residual Energy, throughput, packet delivery ratio and routing overhead.
Energy Reduction with Super-Resolution Convolutional Neural Network for Ultrasound Tomography
Authors: Wójcik Dariusz , Rymarczyk Tomasz , Przysucha Bartosz , Gołąbek Michał , Majerek Dariusz , Warowny Tomasz , Soleimani Manuchehr
Published: January 2023

This study addresses the issue of energy optimization by investigating solutions for the reduction of energy consumption in the diagnostics and monitoring of technological processes. The implementation of advanced process control is identified as a key approach for achieving energy savings and improving product quality, process efficiency, and production flexibility. The goal of this research is to develop a cost-effective system with a minimal number of ultrasound sensors, thus reducing the energy consumption of the overall system. To accomplish this, a novel method for obtaining high-resolution reconstruction in transmission ultrasound tomography (t-UST) is proposed. The method involves utilizing a convolutional neural network to take low-resolution measurements as input and output high-resolution sinograms that are used for tomography image reconstruction. This approach allows for the construction of a super-resolution sinogram by utilizing information hidden in the low-resolution measurement. The model is trained on simulation data and validated on real measurement data. The results of this technique demonstrate significant improvement compared to state-of-the-art methods. The study also highlights that UST measurements contain more information than previously thought, and this hidden information can be extracted and utilized with the use of machine learning techniques to further improve image quality and object recognition.
Model of an Air Transformer for Analyses of Wireless Power Transfer Systems
Authors: Detka Kalina , Górecki Krzysztof , Ptak Przemysław
Published: January 2023

This article presents a new model of a dedicated air transformer for computer analyses of wireless power transfer systems. This model includes a form of subcircuit for SPICE. It takes into account the electric, magnetic and thermal properties of the modeled device. The form of the elaborated model is presented and the results of its experimental verification are shown. Some results from measurements and computations of an air transformer and a wireless power transfer system containing this transformer are shown and discussed. The structure of the tested system and the measuring setup used are also described. The results of measurements and computations illustrating the influence of the distance between the windings of the air transformer and the displacement between its windings on the output voltage of the power transfer system are presented and discussed. The influence of load resistance on the properties of the considered system is analyzed.
Review of Bioenergy Potential in Jordan
Authors: Nahar Myyas Ra’ed , Tostado-Véliz Marcos , Gómez-González Manuel , Jurado Francisco
Published: January 2023

Despite the enormous efforts put into practice by governmental entities, most of the energy consumption worldwide proceeds from fossil fuels. In this regard, there is a clear need to advance toward the use of cleaner energies. This situation is especially critical in developing countries, where a high population, increased commercial and industrial activities, and rising greenhouse gas (GHG) emissions are major concerns. This paper focuses on reviewing the current energy map in Jordan, one of the developing countries in the Southwest Asia area. Jordan generates 2.7 million tons of municipal solid waste annually, which can cause a variety of environmental problems rather than benefit the energy industry or the country’s economy. Jordan uses biomass energy to provide just 0.1% of its overall energy needs. Presently, produced energy comprises logs, chips, bark, and sawdust is made up of around 44% wood. Jordan has a high potential for producing biomass in the future. About 96% of the biomass is made up of animal manure, followed by olive trees and pomace, with a percentage of 1.8%. This work evaluates the theoretical energy potential of waste in Jordan based on previous studies. Moreover, this article looks at the biomass potential in Jordan, emphasizing how the country may become one of the top producers of bioenergy in terms of waste and identifying procedures to assess the biogas potential for common substrates in Jordanian communities (food and agricultural waste). Finally, some further recommendations are provided for developing the biomass sector in Jordan.
Slow-Release Lanthanum Effectively Reduces Phosphate in Eutrophic Ponds without Accumulating in Fish
Authors: McCright Callie , McCoy Jenna , Robbins Natalie , Comfort Steve
Published: January 2023

Nutrient runoff is a major water quality issue affecting water resources. Excess nutrients such as nitrate (NO3−) and phosphate (PO43−) entering surface waters promote eutrophication. Recent research showed that floating treatment wetlands combined with slow-release lanthanum composites deployed through airlift pumps can reduce NO3− and PO43− concentrations, minimize algae and weeds, and increase dissolved oxygen concentrations. While water quality improves following this biological and chemical approach, questions remain about the toxicity and potential accumulation of lanthanum in lentic organisms. We addressed this concern by analyzing flesh and liver of fish exposed to the slow-release lanthanum following two years of treatment and compared results to fish harvested from a control, untreated pond. We also conducted an aquarium fish study that used higher lanthanum concentrations than those observed in the field. The field study confirmed that under the concentrations of lanthanum released to treat eutrophic ponds (109 µg L−1), no adverse effects were observed in harvested fish. We also observed no significant differences between lanthanum-exposed and -unexposed fish (α = 0.05) in our controlled tank study. Given the laboratory tank lanthanum concentrations were approximately nine times higher (916 µg L−1) than the observed field concentrations, we conclude the slow-release lanthanum composites used to treat eutrophic ponds are effective in improving water quality and do not lead to significant lanthanum accumulation in fish.
Preliminary Investigation of Different Types of Inoculums and Substrate Preparation for Biohydrogen Production
Authors: Zainal Bidattul Syirat , Zaini Sabrina , Zinatizadeh Ali Akbar , Mohd Nuruol Syuhadaa , Ibrahim Shaliza , Ker Pin Jern , Mohamed Hassan
Published: January 2023

A pre-culture stage is required to obtain robustly-dividing cells with high hydrogen (H2) production capabilities. However, a step-by-step process for biohydrogen production is scarcely reported, mainly from palm oil wastewater. Therefore, this study developed a guideline to find the best inoculum heat treatment conditions and implement the selected conditions for biohydrogen production using palm oil wastewater. This study used raw palm oil mill effluent (POME) and POME sludge as substrate and inoculum, respectively. Our findings reveal that 80 °C and 30 min were the best conditions for inoculum heat treatment. When testing the conditions on POME sludge and inoculating with raw POME (28 g COD/L) at 37 °C (reaction temperature), 24 h (reaction time), and pH 5.5, 34 mL H2/d was recorded. A slight increase (1.1-fold) was observed compared to 5 g COD/L POME co-digested with 5 g/L glucose (31 mL H2/d). This discovery indicates that raw POME is a potential source for biohydrogen production under anaerobic fermentation and can be directly used as substrate up to 30 g COD/L. The proposed guideline could also be implemented for different organic wastes for biohydrogen production study.
Two-Stage Fermented Feather Meal Enhances Growth Performance and Amino Acid Digestibility in Broilers
Authors: Yeh Ruei-Han , Hsieh Chia-Wen , Chen Kuo-Lung
Published: January 2023

The study aimed to investigate the dose tolerance of enzymatically degraded feather meal (EFM) in the diet, and the effect of the two-stage fermented feather meal on the growth performance and amino acid digestibility of broilers. In trial 1, 160 one-day-old broilers were randomly assigned into 0, 10, 15, and 20% EFM groups. In trial 2, 160 one-day-old broilers were randomly assigned into control, 10% EFM, Bacillus subtilis var. natto N21 + B. coagulans L12 fermented EFM (BBEFM), and B. subtilis var. natto N21 + Saccharomyces cerevisiae Y10 fermented EFM (BSEFM) groups. Trial 3 involved 32 twenty-one-day-old male broilers randomly assigned into nitrogen-free diet, highly digestible protein, EFM, and BSEFM groups for a 7-day metabolic trial. During all of the feeding periods, increasing the EFM dosage in the diet linearly and quadratically inhibited weight gain (WG), feed intake, and feed conversion ratio (FCR) (p < 0.05), except the FCR at 22–35 days (p > 0.05). Dietary inclusion of more than 15% resulted in a negative impact on growth performance over days 1–35 (p < 0.05). Therefore, the EFM dose tolerance in the broiler diet is 10%. The WG, FCR, and production efficiency factor of the BSEFM group were better than those of the control group in days 1–35 (p < 0.05). The apparent and standardized ideal amino acid digestibility of BSEFM was higher than EFM in trial 3, except for Met, Cys, and Trp (p < 0.05). In conclusion, the EFM dose tolerance for the broiler diet is 10%. Bacillius subtilis var. natto N21 + S. cerevisiae Y10 fermentation can improve the amino acid digestibility of EFM and enhance broiler growth performance.
Enhancing Biodegradation of Pyridine with Trehalose Lipid in Rhodococcus pyridinivorans sp. Strain HR-1-Inoculated Microbial Fuel Cell
Authors: Cheng Peng , Usman Muhammad , Arslan Muhammad , Sun Huanqing , Zhou Li , Gamal El-Din Mohamed
Published: January 2023

A Gram-positive exoelectrogen Rhodococcus pyridinivorans sp. strain HR-1 was cultivated from leachate-fed microbial fuel cell (MFC) to study the biodegradation effect of pyridine. In the comparison with mixed cultured MFC, HR-1 presented a remarkable electrical capacity with a maximum output of 4.33 W/m3 under 30 °C in neutral anolyte with 1 g/L acetate as a substrate. Further, HR-1 demonstrated the environmental resistance as a Gram-positive strain. Microbial metabolism was evident at pH between 5–9 and temperature in the range of 20–40 °C, whereas optimal condition for pyridine degradation was observed at 30 °C. This is the first study reporting the degradation of pyridine in the bio-electrochemical system that achieved a 42% ± 5% degradation rate in a full operation cycle at 2 g/L of the concentration. Considering the nonnegligible internal resistance of HR-1-inoculated MFC, trehalose lipid was also introduced as a bio-surfactant to reduce the charge transfer obstacle between the microbes and the electrodes. The surface morphology illustrated that the strain had a plump shape with a high specific area. Accordingly, bio-surfactant addition promoted the anode biomass (1.2 ± 0.1 mg/cm2 to 1.7 ± 0.2 mg/cm2) and achieved a higher degradation rate (68% ± 4%). The feasibility of electrochemical disposal on pyridine and eminent adaptability of strain sp. HR-1 as a Gram-positive exoelectrogen makes MFC a practical approach for real application.
Physical, Chemical, and Mechanical Characterization of Natural Bark Fibers (NBFs) Reinforced Polymer Composites: A Bibliographic Review
Authors: Palanisamy Sivasubramanian , Kalimuthu Mayandi , Nagarajan Rajini , Fernandes Marlet José Maria , Santulli Carlo
Published: January 2023

The specific interest for the use of bark in materials, instead than for energy recovery, is owed to circular economy considerations, since bark fibers are normally byproducts or even waste from other sectors, and therefore their use would globally reduce the amount of refuse by replacing other materials in the production of composites. For the purpose of promoting their application in polymer composites, mainly under a geometry of short random fibers, bark fibers are extracted and treated, normally chemically by alkali. Following this, investigations are increasingly carried out on their chemical composition. More specifically, this includes measuring cellulose, hemicellulose, and lignin content and their modification with treatment on their thermal properties and degradation profile, and on the mechanical performance of the fibers and of the tentatively obtained composites. This work aims at reviewing the current state of studies, trying to elicit which bark fibers might be most promising among the potentially enormous number of these, clarifying which of these have received some attention in literature and trying to elicit the reason for this specific interest. These can be more thoroughly characterized for the purpose of further use, also in competition with other fibers not from bark, but from bast, leaves, etc., and pertaining to developed production systems (cotton, hemp, flax, jute, etc.). The latter are already widely employed in the production of composites, a possibility scantly explored so far for bark fibers. However, some initial works on bark fiber composites and both thermoplastic and thermosetting are indicated and the importance of some parameters (aspect ratio, chemical treatment) is discussed.
Reducing Plastic in Consumer Goods: Opportunities for Coarser Wool
Authors: Løvbak Berg Lisbeth , Klepp Ingun Grimstad , Sigaard Anna Schytte , Broda Jan , Rom Monika , Kobiela-Mendrek Katarzyna
Published: January 2023

Production and use of plastic products have drastically increased during the past decades and their environmental impacts are increasingly spotlighted. At the same time, coarse wool, a by-product of meat and dairy production, goes largely unexploited in the EU. This paper asks why more coarse wool is not used in consumer goods, such as acoustic and sound-absorbing products, garden products, and sanitary products. This is answered through a SWOT analysis of results from a desktop study and interviews with producers of these products made from wool, as well as policy documents relating to wool, waste, textiles, and plastic. Findings show that on a product level, the many inherent properties of wool create opportunities for product development and sustainability improvements and that using the coarser wool represents an opportunity for replacing plastics in many applications as well as for innovation. This is, however, dependent on local infrastructure and small-scale enterprises, but as such, it creates opportunities for local value chains, value creation, and safeguarding of local heritage. The shift to small-scale and local resource utilization requires systemic change on several levels: Here the findings show that policy can incentivize material usage transitions, but that these tools are little employed currently.
Non-Dose-Dependent Relationship between Antipredator Behavior and Conspecific Alarm Substance in Zebrafish
Authors: Li Yaxi , Yan Zhi , Lin Ainuo , Li Xiaodong , Li Ke
Published: January 2023

A series of behavioral detection paradigms have been developed for zebrafish (Danio rerio) to examine anxiety-like behavioral responses. Among them, the novel tank diving test is rapidly gaining popularity in translational neuroscience and behavioral research for the investigation of psychopharmacological activity focusing on stress. Zebrafish respond to conspecific epidermal-released alarm substances with antipredator reactions. Although the alarm responses of zebrafish were well characterized in a novel tank diving experiment, the relationship between the intensity of the alarm behavior and the concentration of the alarm substance needed to be understood more adequately. In the current paper, we investigated the behavioral phenotypes and potencies of zebrafish elicited by the serial dilution of an alarm substance in the novel tank diving test. Using a video-tracking assisted behavioral quantification approach, we demonstrated no linear concentration-dependent relationship between antipredator behavior and skin extracts, suggesting that an optimal concentration induced each typical behavioral response. The results showed that the freezing duration (%) significantly increased when stimulated with 104-fold times dilutions of skin extract (equivalent 5 × 10−5 fish/L), while erratic movements (%), time in the bottom half (%), and latency to the upper half (s) significantly elevated when stimulated with 103-fold times dilutions (equivalent 5 × 10−4 fish/L). Therefore, the concentration threshold for an alarm substance that elicited innate fear behavior in zebrafish was presumed to be an equivalent concentration of approximately 5 × 10−4 fish/L. The conclusions may fill a knowledge gap between the innate fear response triggered by injured skin and a novel tank diving paradigm that provides insights into the characterization of alarm substance, behavioral responses, and physiological response mechanisms in zebrafish.