bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of Gold Nanoparticles Decorated Molecularly Imprinted–Based Plasmonic Sensor for the Detection of Aflatoxin M1 in Milk Samples
Authors: Akgönüllü Semra , Yavuz Handan , Denizli Adil
Published: December 2021

Aflatoxins are a group of extremely toxic and carcinogenic substances generated by the mold of the genus Aspergillus that contaminate agricultural products. When dairy cows ingest aflatoxin B1 (AFB1)−contaminated feeds, it is metabolized and transformed in the liver into a carcinogenic major form of aflatoxin M1 (AFM1), which is eliminated through the milk. The detection of AFM1 in milk is very important to be able to guarantee food safety and quality. In recent years, sensors have emerged as a quick, low–cost, and reliable platform for the detection of aflatoxins. Plasmonic sensors with molecularly imprinted polymers (MIPs) can be interesting alternatives for the determination of AFM1. In this work, we designed a molecularly–imprinted–based plasmonic sensor to directly detect lower amounts of AFM1 in raw milk samples. For this purpose, we prepared gold–nanoparticle–(AuNP)−integrated polymer nanofilm on a gold plasmonic sensor chip coated with allyl mercaptan. N−methacryloyl−l−phenylalanine (MAPA) was chosen as a functional monomer. The MIP nanofilm was prepared using the light–initiated polymerization of MAPA and ethylene glycol dimethacrylate in the presence of AFM1 as a template molecule. The developed method enabled the detection of AFM1 with a detection limit of 0.4 pg/mL and demonstrated good linearity (0.0003 ng/mL–20.0 ng/mL) under optimized experimental conditions. The AFM1 determination was performed in random dairy farmer milk samples. Using the analogous mycotoxins, it was also demonstrated that the plasmonic sensor platforms were specific to the detection of AFM1.
Automatic Assessment of Buildings Location Fitness for Solar Panels Installation Using Drones and Neural Network
Authors: Alzarrad Ammar , Emanuels Chance , Imtiaz Mohammad , Akbar Haseeb
Published: December 2021

Solar panel location assessment is usually a time-consuming manual process, and many criteria should be taken into consideration before deciding. One of the most significant criteria is the building location and surrounding environment. This research project aims to propose a model to automatically identify potential roof spaces for solar panels using drones and convolutional neural networks (CNN). Convolutional neural networks (CNNs) are used to identify buildings’ roofs from drone imagery. Transfer learning on the CNN is used to classify roofs of buildings into two categories of shaded and unshaded. The CNN is trained and tested on separate imagery databases to improve classification accuracy. Results of the current project demonstrate successful segmentation of buildings and identification of shaded roofs. The model presented in this paper can be used to prioritize the buildings based on the likelihood of getting benefits from switching to solar energy. To illustrate an implementation of the presented model, it has been applied to a selected neighborhood in the city of Hurricane in West Virginia. The research results show that the proposed model can assist investors in the energy and building sectors to make better and more informed decisions.
Nonuniformity of Isometric Properties of Automotive Driveshafts
Authors: Bugaru Mihai , Vasile Andrei
Published: December 2021

This paper presents an analysis of the CVJ (constant velocity joint) of automotive driveshafts from a point of view concerning the nonuniformity of isometric properties. In the automotive industry, driveshafts are considered to have constant velocity through its joints: free tripode joints and fixed ball joints, which has been proved by Mtzner’s indirect method and Orain’s direct method for tripod joint. Based on vectorial mechanics, the paper proved the quasi-isometry of velocity for polypod joints such as fixed ball joints. In the meantime, it was computed that the global nonuniformity of constant velocity joints for modern driveshafts based on the Dudita-Diaconescu homokinetic approach for the driveshafts. The nonuniformity of the velocity isometry of driveshafts was computed as a function of the input angular velocity of the driveshaft, angular inclination between the tripod–tulip axis and the midshaft axis and the angular inclination between the bowl axis and midshaft axis. The main aim of this article is how to improve the geometric and kinematic approach to add an important correction when designing the driveshaft dynamics prediction such as: forced torsional vibrations, forced bending–shearing vibrations, and coupled torsional–bending vibrations for the automotive driveshaft in the regions of specific resonances such as principal parametric resonance, internal resonance, combined resonance, and simultaneous resonances. By the way it is added, there are important corrections for the design of driveshafts, for the torsional dynamic behavior prediction, and for bending–shearing dynamic behavior of the driveshafts in the early stages of design. The results presented in the article represent a starting point for future research on dynamic phenomena in the area mentioned previously.
Acoustic Tunneling Study for Hexachiral Phononic Crystals Based on Dirac-Cone Dispersion Properties
Authors: Chen Luyun , Liu Yong , Kong Hui
Published: December 2021

Acoustic tunneling is an essential property for phononic crystals in a Dirac-cone state. By analyzing the linear dispersion relations for the accidental degeneracy of Bloch eigenstates, the influence of geometric parameters on opening the Dirac-cone state and the directional band gaps’ widths are investigated. For two-dimensional hexachiral phononic crystals, for example, the four-fold accidental degenerate Dirac point emerges at the center of the irreducible Brillouin zone (IBZ). The Dirac cone properties and the band structure inversion problem are discussed. Finally, to verify acoustic transmission properties near the double-Dirac-cone frequency region, the numerical calculation of the finite-width phononic crystal structure is carried out, and the acoustic transmission tunneling effect is proved. The results enrich and expand the manipulating method in the topological insulator problem for hexachiral phononic crystals.
Effect of Sodium Hydroxide, Liquid Sodium Silicate, Calcium Hydroxide, and Slag on the Mechanical Properties and Mineral Crystal Structure Evolution of Polymer Materials
Authors: Huang Guodong , Li Yaqian , Zhang Yuting , Zhu Jielei , Li Dawei , Wang Bo
Published: December 2021

To study the key factors that affect the mechanical properties of polymer materials and explore the relationship between mineral crystal formation and strength development, fly ash (FA) polymer samples were prepared using sodium hydroxide, slag, liquid sodium silicate, and hydrated lime as activators. A change in the compressive strength was observed, and X-ray diffraction measurements were carried out to confirm the change. The effects of different types and amounts of activators on the formation and transformation of mineral crystals in FA polymer samples as well as on the development of compressive strength were studied. Moreover, the relationship between the formation and transformation of mineral crystals and the development of compressive strength was established. The results show that the strongly alkaline excitation environment established by sodium hydroxide is the prerequisite for crystal formation and development of compressive strength. Under this strongly alkaline excitation environment, slag, hydrated lime, and liquid sodium silicate can increase the amounts of calcium and silicon, which promote the formation and development of hydrated calcium silicate and hydrated calcium silicoaluminate in polymers and significantly improve the compressive strength.
Uncovering Hidden Diversity: Three New Species of the Keratella Genus (Rotifera, Monogononta, Brachionidae) of High Altitude Water Systems from Central Mexico
Authors: García-Morales Alma E. , Domínguez-Domínguez Omar , Elías-Gutiérrez Manuel
Published: December 2021

The correct identification of species is an essential step before any study on biodiversity, ecology or genetics. Keratella is a genus with a predominantly temperate distribution and with several species being endemics or restricted geographically. Its diversity may be underestimated considering the confusing taxonomy of species complexes such as K. cochlearis. In this study, we examined genetic diversity and morphology among some Keratella populations from Mexico in order to determine if these populations represent different species. We analyzed a dataset of previously published and newly generated sequences of the mitochondrial COI gene and the nuclear ITS1 marker. We conducted phylogenetic analyses and applied three methods of species delimitation (ABGD, PTP and GMYC) to identify evolutionary significant units (ESUs) equivalent to species. Morphological analyses were conducted through scanning electron microscope (SEM) and morphometry under a compound microscope. In the present study, three new species Keratella cuitzeiensis sp. nov., Keratella huapanguensis sp. nov., and Keratella albertae sp. nov., are formally described. These species were collected in high-altitude water bodies located in the Central Plateau of Mexico. Combining DNA results through COI and ITS1 molecular markers and morphology it was possible to confirm the identity of the new species.
The Reef Coral Coscinaraea marshae Is Not a High-Latitude Endemic
Authors: Hoeksema Bert W. , Johan Ofri , Kunzmann Andreas
Published: December 2021

The ‘temperate’ reef coral Coscinaraea marshae Wells, 1962, is reported from Siberut Island (West Sumatra, Indonesia), a near-equatorial locality, 3375 km away from its northernmost range limit in Western Australia, where it is considered a high-latitude endemic. This tropical record suggests that the latitudinal distributions of poorly recorded reef corals may not yet be fully understood, which might be relevant in the light of progressing seawater warming.
Treatment of Dental Anxiety and Phobia—Diagnostic Criteria and Conceptual Model of Behavioural Treatment
Authors: Wide Ulla , Hakeberg Magnus
Published: December 2021

Dental anxiety and dental phobia are still prevalent among adult individuals and should be considered a dental public health issue. Dental anxiety/phobia is often described as a vicious cycle where avoidance of dental care, poor oral health, and psychosocial effects are common features, often escalating over time. Treatment should include therapy for dental anxiety/phobia and oral diseases. This paper discusses aetiology, prevalence, and diagnosis of dental anxiety/phobia and, in detail, presents a conceptual treatment model at the Dental Fears Research and Treatment Center in Gothenburg, Sweden. In addition, based on systematic reviews, evidence-based treatment for dental anxiety is revealed including the interdisciplinary approach between psychology and dentistry.
Information Flow Network of International Exchange Rates and Influence of Currencies
Authors: Cao Hongduo , Lin Fan , Li Ying , Wu Yiming
Published: December 2021

The main purpose of the study is to investigate how price fluctuations of a sovereign currency are transmitted among currencies and what network traits and currency relationships are formed in this process under the background of economic globalization. As a universal equivalent, currency with naturally owned network attributes has not been paid enough attention by the traditional exchange rate determination theories because of their overemphasis of the attribute of value measurement. Considering the network attribute of currency, the characteristics of the information flow network of exchange rate are extracted and analyzed in order to research the impact they have on each other among currencies. The information flow correlation network between currencies is researched from 2007 to 2019 based on data from 30 currencies. A transfer entropy is used to measure the nonlinear information flow between currencies, and complex network indexes such as average shortest path and aggregation coefficient are used to analyze the macroscopic topology characteristics and key nodes of information flow-associated network. It was found that there may be strong information exchange between currencies when the overall market price fluctuates violently. Commodity currencies and currencies of major countries have great influence in the network, and local fluctuations may result in increased risks in the overall exchange rate market. Therefore, it is necessary to monitor exchange rate fluctuations of relevant currencies in order to prevent risks in advance. The network characteristics and evolution of major currencies are revealed, and the influence of a currency in the international money market can be evaluated based on the characteristics of the network. The world monetary system is developing towards diversification, and the currency of developing countries is becoming more and more important. Taking CNY as an example, it was found that the international influence of CNY has increased, although without advantage over other major international currencies since 2015, and this trend continues even if there are trade frictions between China and the United States.
Breaking Data Encryption Standard with a Reduced Number of Rounds Using Metaheuristics Differential Cryptanalysis
Authors: Dworak Kamil , Boryczka Urszula
Published: December 2021

This article presents the author’s own metaheuristic cryptanalytic attack based on the use of differential cryptanalysis (DC) methods and memetic algorithms (MA) that improve the local search process through simulated annealing (SA). The suggested attack will be verified on a set of ciphertexts generated with the well-known DES (data encryption standard) reduced to six rounds. The aim of the attack is to guess the last encryption subkey, for each of the two characteristics Ω. Knowing the last subkey, it is possible to recreate the complete encryption key and thus decrypt the cryptogram. The suggested approach makes it possible to automatically reject solutions (keys) that represent the worst fitness function, owing to which we are able to significantly reduce the attack search space. The memetic algorithm (MASA) created in such a way will be compared with other metaheuristic techniques suggested in literature, in particular, with the genetic algorithm (NGA) and the classical differential cryptanalysis attack, in terms of consumption of memory and time needed to guess the key. The article also investigated the entropy of MASA and NGA attacks.
Interdisciplinary, International Exploration to Strengthen Creativity, Giftedness and Leadership
Authors: Ambrose Don
Published: December 2021

Creativity, giftedness, and leadership are complex, important phenomena, especially in the threatening turbulence of 21st-century conditions; consequently, there is an increasing need to understand how to strengthen them. We can learn much about these phenomena from within the borders of specialized disciplines; however, they are too complex and multifaceted to fit within the walls of disciplinary silos. Interdisciplinary explorations can reveal theories and research findings that expand our knowledge bases about creativity, giftedness, and leadership. This analysis includes the rationale for engaging in interdisciplinary investigations for these purposes. It includes examples of the ways in which interdisciplinary thinking invigorates creativity and cognitive diversity; illuminates the benefits of visual–spatial gifts that strengthen the development of important talents in gifted students who can go on to become creative leaders; and shows how human rights can be strengthened by constraining economic and political corruption. It also describes the benefits of using interdisciplinary navigation through different levels of analysis, each of which includes a number of academic disciplines.
Communication Bandwidth Prediction Technology for Smart Power Distribution Business in Smart Parks
Authors: Zhou Xia , Lu Jianqiang , Xie Xiangpeng , Bu Chengjie , Wan Lei , Xue Feng
Published: December 2021

Accurate prediction of power business communication bandwidth is the premise for the effectiveness of power communication planning and the fundamental guarantee for regular operation of power businesses. To solve the problem of scientifically and reasonably allocating bandwidth resources in smart parks, communication bandwidth prediction technology of intelligent power distribution service for smart parks is proposed in this paper. First, the characteristics of mixed service data arrival rate of power distribution and communication mixed services in smart parks were analyzed. Poisson process and interrupted Poisson process were used to simulate periodic and sudden business of smart parks to realize accurate simulation of the business arrival process. Then, a service arrival rate model based on the Markov modulation Poisson process was constructed. An active buffer management mechanism was used to dynamically discard data packets according to the set threshold and achieve accurate simulation of the packet loss rate during the arrival of smart park business. At the same time, considering the communication service quality index and bandwidth resource utilization, a business communication bandwidth prediction model of smart parks was established to improve the accuracy of business bandwidth prediction. Finally, a smart power distribution room in a smart park was used as an application scenario to quantitatively analyze the relationship between the communication service quality and bandwidth configuration. According to the predicted bandwidth, the reliability and effectiveness of the proposed method were verified by comparison with the elastic coefficient method.
Selected Genetic Algorithms for Vehicle Routing Problem Solving
Authors: Ochelska-Mierzejewska Joanna , Poniszewska-Marańda Aneta , Marańda Witold
Published: December 2021

The traveling salesman problem (TSP) consists of finding the shortest way between cities, which passes through all cities and returns to the starting point, given the distance between cities. The Vehicle Routing Problem (VRP) is the issue of defining the assumptions and limitations in mapping routes for vehicles performing certain operational activities. It is a major problem in logistics transportation. In specific areas of business, where transportation can be perceived as added value to the product, it is estimated that its optimization can lower costs up to 25% in total. The economic benefits for more open markets are a key point for VRP. This paper discusses the metaheuristics usage for solving the vehicle routing problem with special attention toward Genetic Algorithms (GAs). Metaheuristic algorithms are selected to solve the vehicle routing problem, where GA is implemented as our primary metaheuristic algorithm. GA belongs to the evolutionary algorithm (EA) family, which works on a “survival of the fittest” mechanism. This paper presents the idea of implementing different genetic operators, modified for usage with the VRP, and performs experiments to determine the best combination of genetic operators for solving the VRP and to find optimal solutions for large-scale real-life examples of the VRP.
Smart Manufacturing and Tactile Internet Based on 5G in Industry 4.0: Challenges, Applications and New Trends
Authors: Mourtzis Dimitris , Angelopoulos John , Panopoulos Nikos
Published: December 2021

For many applications deployed in manufacturing networks, communication latency has been a significant barrier. Despite the constant development of improved communication protocols and standards during Industry 4.0, the latency problem persists, lowering quality of services (QoS) and quality of experience (QoE). Tactile internet (TI), with its high availability, security, and ultra-low latency, will add a new dimension to human-machine interaction (HMI) by enabling haptic and tactile sensations. The tactile internet (TI) is a cutting-edge technology that uses 5G and beyond (B5G) communications to enable real-time interaction of haptic data over the internet between tactile ends. This emerging TI technology is regarded as the next evolutionary step for the Internet of Things (IoT) and is expected to bring about massive changes towards Society 5.0 and to address complex issues in current society. To that end, the 5G mobile communication systems will support the TI at the wireless edge. As a result, TI can be used as a backbone for delay mitigation in conjunction with 5G networks, allowing for ultra-reliable low latency applications like Smart Manufacturing, virtual reality, and augmented reality. Consequently, the purpose of this paper is to present the current state of 5G and TI, as well as the challenges and future trends for 5G networks beyond 2021, as well as a conceptual framework for integrating 5G and TI into existing industrial case studies, with a focus on the design aspects and layers of TI, such as the master, network, and slave layers. Finally, the key publications focused on the key enabling technologies of TI are summarized and the beyond 5G era towards Society 5.0 based on cyber-physical systems is discussed.
Unsupervised Anomaly Detection in Printed Circuit Boards through Student–Teacher Feature Pyramid Matching
Authors: Adibhatla Venkat Anil , Huang Yu-Chieh , Chang Ming-Chung , Kuo Hsu-Chi , Utekar Abhijeet , Chih Huan-Chuang , Abbod Maysam F. , Shieh Jiann-Shing
Published: December 2021

Deep learning methods are currently used in industries to improve the efficiency and quality of the product. Detecting defects on printed circuit boards (PCBs) is a challenging task and is usually solved by automated visual inspection, automated optical inspection, manual inspection, and supervised learning methods, such as you only look once (YOLO) of tiny YOLO, YOLOv2, YOLOv3, YOLOv4, and YOLOv5. Previously described methods for defect detection in PCBs require large numbers of labeled images, which is computationally expensive in training and requires a great deal of human effort to label the data. This paper introduces a new unsupervised learning method for the detection of defects in PCB using student–teacher feature pyramid matching as a pre-trained image classification model used to learn the distribution of images without anomalies. Hence, we extracted the knowledge into a student network which had same architecture as the teacher network. This one-step transfer retains key clues as much as possible. In addition, we incorporated a multi-scale feature matching strategy into the framework. A mixture of multi-level knowledge from the features pyramid passes through a better supervision, known as hierarchical feature alignment, which allows the student network to receive it, thereby allowing for the detection of various sizes of anomalies. A scoring function reflects the probability of the occurrence of anomalies. This framework helped us to achieve accurate anomaly detection. Apart from accuracy, its inference speed also reached around 100 frames per second.
Experimental Evaluation of Malware Family Classification Methods from Sequential Information of TLS-Encrypted Traffic
Authors: Ha Joonseo , Roh Heejun
Published: December 2021

In parallel with the rapid adoption of transport layer security (TLS), malware has utilized the encrypted communication channel provided by TLS to hinder detection from network traffic. To this end, recent research efforts are directed toward malware detection and malware family classification for TLS-encrypted traffic. However, amongst their feature sets, the proposals to utilize the sequential information of each TLS session has not been properly evaluated, especially in the context of malware family classification. In this context, we propose a systematic framework to evaluate the state-of-the-art malware family classification methods for TLS-encrypted traffic in a controlled environment and discuss the advantages and limitations of the methods comprehensively. In particular, our experimental results for the 10 representations and classifier combinations show that the graph-based representation for the sequential information achieves better performance regardless of the evaluated classification algorithms. With our framework and findings, researchers can design better machine learning based classifiers.
Optimal Placement of Reclosers in a Radial Distribution System for Reliability Improvement
Authors: Alam Afroz , Tariq Mohd , Zaid Mohammad , Verma Preeti , Alsultan Marwan , Ahmad Shafiq , Sarwar Adil , Hossain Md. Alamgir
Published: December 2021

There is a need for the optimal positioning of protective devices to maximize customers satisfaction per their demands. Such arrangement advances the distribution system reliability to maximum achievable. Thus, radial distribution system (RDS) reliability can be improved by placing reclosers at suitable feeder sections. This article presents comprehensive details of an attempt to determine the reclosers’ optimal location in an RDS to maximize the utility profit by reliability improvement. Assessment of different reliability indices such as SAIDI, SAIFI, CAIFI, CAIDI, etc., with recloser placement, exhibits a considerable improvement in these indices in contrast with the absence of recloser. Consequently, a new bidirectional formulation has been proposed for the optimized arrangement of reclosers’. This formulation efficiently handles the bidirectional power flow, resulting from distributed generation (DG) unit (s) in the system. The proposed model has been solved for a test system by utilizing the Genetic algorithm (GA) optimization method. Later, test results conclude that reclosers’ optimal placement contributes significantly towards utility profit with minimum investment and outage costs.
Comparative Analysis of Low-Grade Heat Utilization Methods for Thermal Power Plants with Back-Pressure Steam Turbines
Authors: Rogalev Nikolay , Kindra Vladimir , Komarov Ivan , Osipov Sergey , Zlyvko Olga , Lvov Dmitrii
Published: December 2021

Thermal power plants (TPPs) with back-pressure steam turbines (BPSTs) were widely used for electricity and steam production in the Union of Soviet Socialist Republics (USSR) due to their high efficiency. The collapse of the USSR in 1991 led to a decrease in industrial production, as a result of which, steam production in Russia was reduced and BPSTs were left without load. To resume the operation of TPPs with BPSTs, it is necessary to modernize the existing power units. This paper presents the results of the thermodynamic analysis of different methods of modernization of TPPs with BPSTs: the superstructure of the steam low-pressure turbine (LPT) and the superstructure of the power unit operating on low-boiling-point fluid. The influence of ambient temperature on the developed cycles’ efficiency was evaluated. It was found that the usage of low-boiling-point fluid is thermodynamically efficient for an ambient temperature lower than 7 °C. Moreover, recommendations for the choice of reconstruction method were formulated based on technical assessments.
The Analysis of the Possibility of Feeding a Liquid Catalyst to a Coal Dust Channel
Authors: Bielecki Zdzisław , Ochowiak Marek , Włodarczak Sylwia , Krupińska Andżelika , Matuszak Magdalena , Lewtak Robert , Dziuba Jarosław , Szajna Ernest , Choiński Dariusz , Odziomek Marcin
Published: December 2021

This article presents the concept of a method of improving the dynamics of combustion in boilers operating in power plants, cogeneration plants, and heating plants by introducing a catalyst that is fed with a carrier in the form of droplets. Thanks to the proposed method, a greater degree of fuel burnout can be obtained, which, in turn, results in lower energy consumption in the case of producing the same amount of power. The parameters of the emitted exhaust gases and ash are also improved. The method described in the article involves the adding of a catalyst to the dust pipe of the boiler, which improves the combustion parameters. The catalyst was implemented using a sprayer/nebulizer. In order to obtain the correct flow parameters, the sprayer was modeled using CFD calculations. The calculations include trajectories, velocities and concentrations with regards to various flow parameters. Particular attention should be paid to the model of the evaporation of moving droplets. The results of these calculations enable the parameters that guarantee that the catalyst reaches the dust channel outlet in the desired form to be assessed. The analysis is an introduction to experimental research that is carried out on a medium and large scale.
Techno-Economic Assessment of a Standalone Hybrid System Using Various Solar Tracking Systems for Kalpeni Island, India
Authors: Prakash Vinoth John , Dhal Pradyumna Kumar
Published: December 2021

Achieving electrification in an island considering less emission and levelized energy cost is a challenging goal on developing islands such as Kalpeni Island. This work exhibits the techno-economic assessment of a standalone hybrid system to generate power to Kalpeni Island, India through sensitivity and optimization analysis using HOMER software. Various system configurations like solar/DG, wind/DG, solar/wind/DG, and solar/wind are analyzed based on cost and electrical parameters. Based on the optimization results, the best hybrid system is chosen for Kalpeni Island considering different solar tracking methods. Then, multi-year and sensitivity analysis are performed to analyze the effect of load growth, rising diesel price, rising battery minimum SOC, rising PVS derating, rising photovoltaic cell temperature, and changing inverter and rectifier efficiency. The system operated with a solar photovoltaic system (PVS) and diesel generator (DG) with a tracking system on a vertical axis (TSVA) shows the best optimization result compared to other hybrid configurations with a low levelized energy cost (LEC) of 0.222 $/kWh and net present cost (CNP) of $448,269 for the chosen location. The TSVA plays a vital role on power production in the system operated with solar and DG sources, which produces 9.77% more power compared to fixed system without tracking (FSWT). The total emission produced in the system operated with solar and diesel generator with TSVA is 88.2% less compared to an WT/DG configuration operated with FSWT.
Review of the Hydrogen Evolution Reaction—A Basic Approach
Authors: Ferriday Thomas B. , Middleton Peter Hugh , Kolhe Mohan Lal
Published: December 2021

An increasing emphasis on energy storage has resulted in a surge of R&D efforts into producing catalyst materials for the hydrogen evolution reaction (HER) with emphasis on decreasing the usage of platinum group metals (PGMs). Alkaline water electrolysis holds promise for satisfying future energy storage demands, however the intrinsic potential of this technology is impeded by sluggish reaction kinetics. Here, we summarize the latest efforts within alkaline HER electrocatalyst design, where these efforts are divided between three catalyst design strategies inspired by the three prevailing theories describing the pH-dependence of the HER activity. Modifying the electronic structure of a host through codoping and creating specific sites for hydrogen/hydroxide adsorption stand out as promising strategies. However, with the vast amount of possible combinations, emphasis on screening parameters is important. The authors predict that creating a codoped catalyst using the first strategy by screening materials based on their hydrogen, hydroxide and water binding energies, and utilizing the second and third strategies as optimization parameters might yield both active and stable HER catalyst materials. This strategy has the potential to greatly advance the current status of alkaline water electrolysis as an energy storage option.
EMT Real-Time Simulation Model of a 2 GW Offshore Renewable Energy Hub Integrating Electrolysers
Authors: Marchand Jane , Shetgaonkar Ajay , Rueda Torres Jose Luis , Lekic Aleksandra , Palensky Peter
Published: December 2021

Due to their weak nature, such as low inertia, offshore energy hubs are prone to unprecedented fast dynamic phenomena. This can lead to undesired instability problems. Recent literature, with main focus on onshore systems, suggests that electrolysers could be an attractive option to support wind generators in the mitigation of balancing problems. This paper presents an Electromagnetic Transient (EMT) model for real-time simulation based study of the dynamics of active power and voltage responses of offshore hubs due to wind speed fluctuations. The purpose of this study was to ascertain the ability of an electrolyser to support an offshore energy hub under different scenarios and with different locations of the electrolyser. Two locations of Proton Exchange Membrane (PEM) electrolysers were considered: centralised (at the AC common bus of the hub) or distributed (at the DC link of the wind turbines). Numerical simulations conducted in RSCAD® on a 2 GW offshore hub with 4 × 500 MW wind power plants and 330 or 600 MW PEM electrolysers show that electrolysers can effectively support the mitigation of sudden wind speed variations, irrespective of the location. The distributed location of electrolysers can be beneficial to prevent large spillage of wind power generation during the isolation of faults within the hub.
Evaluation on the Performance of Automobile Engine Using Air Injection Nozzle in the Intake Manifold
Authors: Kim Taejung , Shin Yunchan , Park Jungsoo , Cho Honghyun
Published: December 2021

In the present study, a nozzle was used to improve the flow performance of an intake manifold, and its effects on the automobile engine output and the exhaust gas were experimentally studied. It was found that the engine output of a vehicle with a mileage of 30,000 km increased by 4.7% and 6.5% when nozzles with diameters of 5 and 2.5 mm were used. In addition, the engine output of a vehicle with a mileage of 180,000 km increased by 3.3% and 13.3% when nozzles with diameters of 5 and 2.5 mm were used compared to those of the same vehicle when no nozzle was used. Thus, using a nozzle for the inflow of outside air created a uniform combustion environment to improve the engine output and reduce harmful exhaust gases, such as hydrocarbon, carbon monoxide, and nitrogen oxides, by generating vortexes inside the intake manifold and increasing the degree of mixing. Furthermore, the smaller nozzle with a diameter of 2.5 mm had greater effects.
Adaptive Smooth Variable Structure Filter Strategy for State Estimation of Electric Vehicle Batteries
Authors: Rahimifard Sara , Habibi Saeid , Goward Gillian , Tjong Jimi
Published: December 2021

Battery Management Systems (BMSs) are used to manage the utilization of batteries and their operation in Electric and Hybrid Vehicles. It is imperative for efficient and safe operation of batteries to be able to accurately estimate the State of Charge (SoC), State of Health (SoH) and State of Power (SoP). The SoC and SoH estimation must remain robust and accurate despite aging and in presence of noise, uncertainties and sensor biases. This paper introduces a robust adaptive filter referred to as the Adaptive Smooth Variable Structure Filter with a time-varying Boundary Layer (ASVSF-VBL) for the estimation of the SoC and SoH in electrified vehicles. The internal model of the filter is a third-order equivalent circuit model (ECM) and its state vector is augmented to enable estimation of the internal resistance and current bias. It is shown that system and measurement noise covariance adaptation for the SVSF-VBL approach improves the performance in state estimation of a battery. The estimated internal resistance is then utilized to improve determination of the battery’s SoH. The effectiveness of the proposed method is validated using experimental data from tests on Lithium Polymer automotive batteries. The results indicate that the SoC estimation error can remain within less than 2% over the full operating range of SoC along with an accurate estimation of SoH.
Area under Rapeseed Cultivation as a Factor Differentiating the Economic Performance of Biodiesel Producers
Authors: Bełdycka-Bórawska Aneta , Jankowski Krzysztof Józef , Rokicki Tomasz , Gostkowski Michał
Published: December 2021

The aim of this study was to assess the impact of the area under rapeseed cultivation on the economic performance and organization of farms. The study was conducted in 164 rapeseed farms in different Polish voivodeships. A targeted sampling procedure was used to select farms for the study. The studied population was divided into four groups depending on area under rapeseed cultivation rates. The selected farms were located in voivodeships with the highest rapeseed acreage rates of the total cropped area. The economic performance of the examined farms improved with increases in rapeseed area. Farms with larger rapeseed areas were characterized by higher production values and better economic performance. On average, the total production value per farm was highest in the group of farms with rapeseed areas of 20.1–30 ha. Similar results were noted when total production values were expressed per ha of arable land, per full-time employee and per man-hour. Total production value was lowest in farms with the smallest rapeseed areas. Farms with the largest areas under rapeseed cultivation achieved the highest farm household income. The farm household income values per full-time employee and per man-hour were highest in farms with the largest areas under rapeseed cultivation. The values of fixed assets and current assets increased with increases in rapeseed area. Most farms were run by owners with secondary school education. The highest percentages of farmers with university education were noted in farms with rapeseed areas of 10–20.1 ha (37.5%) and above 30 ha (30.4%). The vast majority of farms from all groups were run by male farmers. The research results could be useful for policy makers, because they indicate that rapeseed production can not only be profitable but can also be used for biofuel production.
Editorial for Special Issue: “Clean Energy Innovations: Challenges and Strategies for Low and Middle Income Countries”
Authors: Batchelor Simon , Brown Ed
Published: December 2021

All the papers in this Special Issue situate their research in the context of a failing clean cooking strategy and the potential contribution of electricity to this [...]
Suppression Method of Partial Discharge Interferences Based on Singular Value Decomposition and Improved Empirical Mode Decomposition
Authors: Li Linao , Wei Xinlao
Published: December 2021

Partial discharge detection is an important means of insulation diagnosis of electrical equipment. To effectively suppress the periodic narrowband and white noise interferences in the process of partial discharge detection, a partial discharge interference suppression method based on singular value decomposition (SVD) and improved empirical mode decomposition (IEMD) is proposed in this paper. First, the partial discharge signal with periodic narrowband interference and white noise interference x(t) is decomposed by SVD. According to the distribution characteristics of single values of periodic narrowband interference signals, the singular value corresponding to periodic narrowband interference is set to zero, and the signal is reconstructed to eliminate the periodic narrowband interference in x(t). IEMD is then performed on x(t). Intrinsic mode function (IMF) is obtained by EMD, and based on the improved 3σ criterion, the obtained IMF components are statistically processed and reconstructed to suppress the influence of white noise interference. The methods proposed in this paper, SVD and SVD + EMD, are applied to process the partial discharge simulation signal and partial discharge measurement signal, respectively. We calculated the signal-to-noise ratio, normalized correlation coefficient, and mean square error of the three methods, respectively, and the results show that the proposed method suppresses the periodic narrowband and white noise interference signals in partial discharge more effectively than the other two methods.
A Review on Power Electronics Technologies for Power Quality Improvement
Authors: Afonso Joao L. , Tanta Mohamed , Pinto José Gabriel Oliveira , Monteiro Luis F. C. , Machado Luis , Sousa Tiago J. C. , Monteiro Vitor
Published: December 2021

Nowadays, new challenges arise relating to the compensation of power quality problems, where the introduction of innovative solutions based on power electronics is of paramount importance. The evolution from conventional electrical power grids to smart grids requires the use of a large number of power electronics converters, indispensable for the integration of key technologies, such as renewable energies, electric mobility and energy storage systems, which adds importance to power quality issues. Addressing these topics, this paper presents an extensive review on power electronics technologies applied to power quality improvement, highlighting, and explaining the main phenomena associated with the occurrence of power quality problems in smart grids, their cause and effects for different activity sectors, and the main power electronics topologies for each technological solution. More specifically, the paper presents a review and classification of the main power quality problems and the respective context with the standards, a review of power quality problems related to the power production from renewables, the contextualization with solid-state transformers, electric mobility and electrical railway systems, a review of power electronics solutions to compensate the main power quality problems, as well as power electronics solutions to guarantee high levels of power quality. Relevant experimental results and exemplificative developed power electronics prototypes are also presented throughout the paper.
Greek Honey Authentication: Botanical Approach
Authors: Xagoraris Marinos , Revelou Panagiota-Kyriaki , Alissandrakis Eleftherios , Tarantilis Petros A. , Pappas Christos S.
Published: December 2021

Honey is a functional, honeybee product with a useful role in human nutrition and several health benefits. Greece is a Mediterranean region with several types of monofloral honey. Today, Greek honey has acquired an important position in national and international markets. Due to this increased industrialization and globalization, quality control is a necessity. Mislabeling constitutes one of the most notable types of fraudulence, while most consumers are looking for authentic honey. Moreover, producers and suppliers are searching for rapid and analytical methodologies to secure Greek honey in a competitive environment. In this context, we aimed to describe the classical (melissopalynological, physicochemical) and analytical (chromatographic, spectrometric, and spectroscopic) methods for the standardization of the botanical origin of Greek honey.
Impact Resistance of Functionally Layered Two-Stage Fibrous Concrete
Authors: Murali Gunasekaran , Prasad Nandhu , Klyuev Sergey , Fediuk Roman , Abid Sallal R. , Amran Mugahed , Vatin Nikolai
Published: December 2021

The impact resistance of functionally layered two-stage fibrous concrete (FLTSFC) prepared using the cement grout injection technique was examined in this study. The impact resistance of turtle shells served as the inspiration for the development of FLTSFC. Steel and polypropylene fibres are used in more significant quantities than usual in the outer layers of FLTSFC, resulting in significantly improved impact resistance. An experiment was carried out simultaneously to assess the efficacy of one-layered and two-layered concrete to assess the effectiveness of three-layered FLTSFC. When performing the drop-mass test ACI 544, a modified version of the impact test was suggested to reduce the scattered results. Instead of a solid cylindrical specimen with no notch, a line-notched specimen was used instead. This improvement allows for the pre-definition of a fracture route and the reduction of the scattering of results. The testing criteria used in the experiments were impact numbers associated to first crack and failure, mode of failure, and ductility index. The coefficient of variation of the ACI impact test was lowered due to the proposed change, indicating that the scattering of results was substantially reduced. This research contributes to the idea of developing enhanced, more impact-resistant fibre composites for use in possible protective structures in the future.
Amyotrophic Lateral Sclerosis: A Diet Review
Authors: D’Antona Salvatore , Caramenti Martina , Porro Danilo , Castiglioni Isabella , Cava Claudia
Published: December 2021

Amyotrophic lateral sclerosis (ALS) is a fatal disease related to upper and lower motor neurons degeneration. Although the environmental and genetic causes of this disease are still unclear, some factors involved in ALS onset such as oxidative stress may be influenced by diet. A higher risk of ALS has been correlated with a high fat and glutamate intake and β-methylamino-L-alanine. On the contrary, a diet based on antioxidant and anti-inflammatory compounds, such as curcumin, creatine, coenzyme Q10, vitamin E, vitamin A, vitamin C, and phytochemicals could reduce the risk of ALS. However, data are controversial as there is a discrepancy among different studies due to a limited number of samples and the many variables that are involved. In addition, an improper diet could lead to an altered microbiota and consequently to an altered metabolism that could predispose to the ALS onset. In this review we summarized some research that involve aspects related to ALS such as the epidemiology, the diet, the eating behaviour, the microbiota, and the metabolic diseases. Further research is needed to better comprehend the role of diet and the metabolic diseases in the mechanisms leading to ALS onset and progression.
Tilapia Head Protein Hydrolysate Attenuates Scopolamine-Induced Cognitive Impairment through the Gut-Brain Axis in Mice
Authors: Ji Jun , Yi Xiangzhou , Zhu Yujie , Yu Hui , Huang Shuqi , Liu Zhongyuan , Zhang Xueying , Xia Guanghua , Shen Xuanri
Published: December 2021

The destruction of the homeostasis in the gut-brain axis can lead to cognitive impairment and memory decline. Dietary intervention with bioactive peptides from aquatic products is an innovative strategy to prevent cognitive deficits. The present study aimed to determine the neuroprotective effect of tilapia head protein hydrolysate (THPH) on scopolamine-induced cognitive impairment in mice, and to further explore its mechanism through the microbiota–gut-brain axis. The results showed that THPH administration significantly improved the cognitive behavior of mice, and normalized the cholinergic system and oxidative stress system of the mice brain. The histopathological observation showed that THPH administration significantly reduced the pathological damage of hippocampal neurons, increased the number of mature neurons marked by NeuN and delayed the activation of astrocytes in the hippocampus of mice. In addition, THPH administration maintained the stability of cholinergic system, alleviated oxidative stress and further improved the cognitive impairment by reshaping the gut microbiota structure of scopolamine-induced mice and alleviating the disorder of lipid metabolism and amino acid metabolism in serum. In conclusion, our research shows that THPH supplementation is a nutritional strategy to alleviate cognitive impairment through the gut-brain axis.