bluuebunny/crossref_metadata_2025 huggingface dataset:
Biochemical and Computational Assessment of Acute Phase Proteins in Dairy Cows Affected with Subclinical Mastitis
Authors: Ali Aarif , Rehman Muneeb U. , Mushtaq Saima , Ahmad Sheikh Bilal , Khan Altaf , Karan Anik , Bashir Wani Amir , Ganie Showkat Ahmad , Mir Manzoor Ur Rahman
Published: June 2023

Subclinical mastitis (SCM) is a predominant form of mastitis wherein major visible signs of disease are absent. The present study aimed to determine acute phase proteins (APPs) like ferritin, C-reactive protein (CRP), and microalbumin (Malb) in 135 composite milk and serum samples of healthy (n = 25) and SCM (n = 110) cows. As bovine mastitis is an inflammatory disease, the present study also aimed at finding novel anti-inflammatory compounds from natural sources by repurposing approach using computational studies. The findings of the present study revealed substantial elevation (p < 0.001) in milk SCC and an increase in ferritin, CRP, and Malb (p < 0.001) in milk and sera of the SCM group as compared to healthy animals. Receiver operating characteristics of milk SCC, milk, and serum APPs unraveled statistically substantial alteration (p < 0.001). Further, SCC was correlated with milk APPs ferritin (r = 0.26 **, p < 0.002), CRP (r = 0.19 *, p < 0.02), and Malb (r = 0.21 *, p < 0.01). Additionally, milk SCC was correlated with serum ferritin (r = 0.28 **, p < 0.001), CRP (r = 0.16, p > 0.05), and Malb (r = 0.16, p > 0.05). The findings of molecular docking revealed that Chaetoglobosin U was the most effective molecule that showed the highest binding affinity (kcal/mol) of −10.1 and −8.5 against ferritin and albumin. The present study concluded that the estimation of cow-side tests, SCC, and APPs in milk/serum is suitable to detect SCM and screening herd community. Furthermore, Chaetoglobosin U could be developed as a promising anti-inflammatory inhibitor; however, further studies are required to validate these findings.
Degradation Behavior of Arc-Sprayed Zinc Aluminum Alloy Coatings for the Vessel Yongle in the South China Sea
Authors: Huang Guo-Sheng , Li Zi-Lin , Zhao Xiao-Shuo , Xin Yong-Lei , Ma Li , Sun Ming-Xian , Li Xiang-Bo
Published: June 2023

Since thermally sprayed zinc and aluminum coatings were invented 100 years ago, they have realized extensive industrial applications for steel structure protection in a variety of fields for nearly 100 years and have been proven to be effective and reliable. However, it has seldom been reported in the ship industry in China since many workers worry about the risk of rapid corrosion, especially in harsh environments such as the South China Sea. In this paper, three kinds of arc-sprayed zinc aluminum coatings were tested to choose the best coating system for application on the research vessel Yongle by electrochemical behavior and a long-term atmospheric exposure experiment. The variation of the corrosion rate and the bonding strength was used to clarify the long-term protection performance. The results show that Zn15Al has the lowest corrosion (Rp larger than 2200 Ω·cm2) among the three kinds of coatings and has a bonding strength larger than 6.38 MPa after a 5 year test. The performance of the coatings in the South China Sea indicates that they can provide excellent protection for the hull above the waterline of the Yongle vessel in the 3 year test. It could be predicted that thermally sprayed zinc aluminum coating has vast application potential in the South China Sea due to its excellent anticorrosion performance.
Principles of Machine Learning and Its Application to Thermal Barrier Coatings
Authors: Liu Yuan , Chen Kuiying , Kumar Amarnath , Patnaik Prakash
Published: June 2023

Artificial intelligence (AI), machine learning (ML) and deep learning (DL) along with big data (BD) management are currently viable approaches that can significantly help gas turbine components’ design and development. Optimizing microstructures of hot section components such as thermal barrier coatings (TBCs) to improve their durability has long been a challenging task in the gas turbine industry. In this paper, a literature review on ML principles and its various associated algorithms was presented first and then followed by its application to investigate thermal conductivity of TBCs. This combined approach can help better understand the physics behind thermal conductivity, and on the other hand, can also boost the design of low thermal conductivity of the TBCs system in terms of microstructure–property relationships. Several ML models and algorithms such as support vector regression (SVR), Gaussian process regression (GPR) and convolution neural network and regression algorithms were used via Python. A large volume of thermal conductivity data was compiled and extracted from the literature for TBCs using PlotDigitizer software and then used to test and validate ML models. It was found that the test data were strongly associated with five key factors as identifiers. The prediction of thermal conductivity was performed using three approaches: polynomial regression, neural network (NN) and gradient boosting regression (GBR). The results suggest that NN using the BR model and GBR have better prediction capability.
Experimental Investigation of the Initial Stage of the Oxidation Mechanism of Co Coating for Solid Oxide Fuel Cell Interconnects at 650 °C
Authors: Mao Jingwen , Wang Enhua , Wang Hewu , Ouyang Minggao , Hu Haoran , Lu Languang , Ren Dongsheng , Liu Yadi
Published: June 2023

The evolution of Co coating in solid oxide fuel cells (SOFCs) under low and medium temperatures (<700 °C) is different from that under high temperatures. In this context, the oxidation corrosion of 441 ferritic stainless steel (FSS) with a Co coating in air under 650 °C was investigated. The results indicated that the Co coating was oxidized rapidly and a Co3O4 spinel layer formed in the initial exposure of 5 min, which improved the oxidation resistance of 441 steel. After oxidation at 650 °C for 120 h, a Cr2O3 layer with a thickness of 0.2–0.4 μm was observed on the surface of bare 441 steel, while the surface oxide scale of Co-coated 441 steel samples was composed of an inner Cr2O3 and Fe2O3 solid solution (0.1–0.3 μm thick), an intermediate (Fe, Co)3O4 layer and an outer Co3O4 spinel layer, respectively. The Co-coated 441 steel sample exhibited better electrical properties. After oxidation at 650 °C for 120 h, the area-specific resistance (ASR) of the Co-coated steel was 3.73 mΩ·cm2, which was 25.4% lower than that of bare 441 steel as 5 mΩ·cm2. Furthermore, the thermal growth process and protection mechanism of Co coating at 650 °C were discussed.
Photocured Zwitterionic Coatings Containing POSS for Antifogging Applications
Authors: Guo Lei , Li Zhuping , Wu Xiubang , Wang Kai , Abbas Faheem , Wu Yundong , Zhang Fan
Published: June 2023

The conventional fabrication of antifogging polymer coatings such as zwitterionic or amphiphilic copolymers typically require multiple processes. In this work, a simple photocuring method was used to create a series of zwitterionic coatings containing polyhedral oligomeric silsesquioxane (POSS) without the need to prepare copolymer. Surface analysis demonstrated that the coating thickness was typically about 6 μm, and the surface POSS content showed a tendency of increasing with POSS. A wettability analysis demonstrated that zwitterionic coating with high POSS content held better water absorbing capability than that with low POSS content and without POSS. Furthermore, it was found that a high proportion of POSS contributed towards the enhancement of transmittance. The excellent antifogging properties of coatings with a high mass fraction of POSS can be ascribed to the aforementioned good wettability and transmittance. It is expected that zwitterionic coating via the simple incorporation of POSS can be utilized for practical application.
Metal-Ion Batteries: Achievements, Challenges, and Prospects
Authors: Kiai Maryam Sadat , Eroglu Omer , Aslfattahi Navid
Published: June 2023

A new type of battery known as metal-ion batteries promises better performance than existing batteries. In terms of energy storage, they could prove useful and eliminate some of the problems existing batteries face. This review aims to help academics and industry work together better. It will propose ways to measure the performance of metal-ion batteries using important factors such as capacity, convertibility, Coulombic efficiency, and electrolyte consumption. With the development of technology, a series of metal ion-based batteries are expected to hit the market. This review presents the latest innovative research findings on the fabrication of metal-ion batteries with new techniques.
Laser-Induced Graphene in Polyimide for Antenna Applications
Authors: Sartanavičius Aivaras , Žemgulytė Justina , Ragulis Paulius , Ratautas Karolis , Trusovas Romualdas
Published: June 2023

Laser-induced graphene (LIG) has gained considerable attention recently due to its unique properties and potential applications. In this study, we investigated using LIG in polyimide (PI) as a material for antenna applications. The LIG-−PI composite material was prepared by a facile picosecond laser (1064 nm) irradiation process, which resulted in a conductive graphene network within the PI matrix. Furthermore, LIG formation was confirmed by Raman spectroscopy and sheet resistance measurements. Finally, a patch antenna from LIG with 2.45 GHz microwaves was simulated, produced and tested. These findings suggest that LIG−PI composites have great potential for use in high-frequency electronic devices and can provide a new avenue for the development of flexible and wearable electronics.
The Crystal-Wonder Cave System: A New Hotspot of Subterranean Biodiversity in the Southern Cumberland Plateau of South-Central Tennessee, USA
Authors: Niemiller Matthew L. , Zigler Kirk S. , Hinkle Amata , Stephen Charles D. R. , Cramphorn Brendan , Higgs Jared , Mann Nathaniel , Miller Brian T. , Niemiller K. Denise Kendall , Smallwood Kelly , Hardy Jason
Published: June 2023

The Crystal-Wonder Cave System developed in the Western Escarpment of the southern Cumberland Plateau in the Interior Low Plateau karst region of south-central Tennessee, USA is a global hotspot of cave-limited biodiversity. We combined historical literature, museum accessions, and database occurrences with new observations from bio-inventory efforts conducted between 2005 and 2022 to compile an updated list of troglobiotic and stygobiotic biodiversity for the Crystal-Wonder Cave System. The list of cave-limited fauna includes 31 species (23 troglobionts and 8 stygobionts) with 28 and 18 species documented from the Crystal and Wonder caves, respectively, which represents five phyla, ten classes, nineteen orders, and twenty-six families (six arachnids, three springtails, two diplurans, three millipedes, six insects, three terrestrial snails, one flatworm, five crustaceans, and two vertebrates, respectively). The Crystal-Wonder Cave System is the type locality for six species—Anillinus longiceps, Pseudanophthalmus humeralis, P. intermedius, Ptomaphagus hatchi, Tolus appalachius, and Chitrella archeri. The carabid beetle Anillinus longiceps is endemic to the Crystal-Wonder Cave System. Sixteen species are of conservation concern, including twelve taxa with NatureServe conservation ranks of G1–G3. The exceptional diversity of the Crystal-Wonder Cave System has been associated with several factors, including a high dispersal potential of cave fauna associated with expansive karst exposures along the Western Escarpment of the southern Cumberland Plateau, a high surface productivity, and a favorable climate throughout the Pleistocene.
Diversity and Biology of Terrestrial Orthopteroids (Insecta) in the Republic of Mordovia (Russia)
Authors: Aleksanov Victor V. , Karmazina Inessa O. , Ruchin Alexander B. , Esin Mikhail N. , Lukiyanov Sergei V. , Lobachev Evgeniy A. , Artaev Oleg N. , Ryzhov Maxim K.
Published: June 2023

Orthopteroidea is an ecologically diverse group of incompletely transformed insects that includes several insect orders similar in development and structure. Many species from Dermaptera, Orthoptera, Mantodea, and Blattodea are sensitive to anthropogenic influences and are indicators of the external environment. Some species cause damage to agriculture and forestry; others are inhabitants of human dwellings and pests of food supplies. The aim of this study is to describe fauna of some orders of Orthopteroidea in the Republic of Mordovia, in the central part of European Russia. This study was conducted in April–October 1971, 1984, 1995, 1996, 1998, 2000, 2001, and 2004–2023. All possible habitats were studied using a variety of methods (entomological traps, pitfall traps, pan traps, etc.). An acoustic method of species identification was also used. For each observation, the coordinates of location, abundance, and dates were recorded. The dataset contains 4865 occurrences. In total, 16,644 specimens of Orthopteroidea were studied. The dataset contains 71 species including Dermaptera (4), Orthoptera (62), Mantodea (1), and Blattodea (4). Of these, 13 species are identified for the first time in the region; these mainly inhabit steppe areas. The presence of two Orthoptera species has not been confirmed yet during our studies; these species are noted in this paper according an old published paper. The biodiversity of Mordovia includes 73 species from four orders. The biology of numerous species, their seasonal dynamics, and some descriptions of biotopes and number of new species are described.
Community Richness and Diversity of Endophytic Fungi Associated with the Orchid Guarianthe skinneri Infested with “Black Blotch” in the Soconusco Region, Chiapas, Mexico
Authors: Hernández-Ramírez Fabiola , Damon Anne , Fernández Pavía Sylvia Patricia , Guillén-Navarro Karina , Iracheta-Donjuan Leobardo , Zarza Eugenia , Castro-Chan Ricardo Alberto
Published: June 2023

Orchids coexist with a diversity of endophytic fungi within their roots and other parts of the plant. These are presumed to contribute to nutrition, and may protect the plants against pathogens and herbivores; however, some may be latent pathogens and/or bring no benefit to the plant. Guarianthe skinneri is an epiphytic Central American threatened orchid used as an ornamental plant and in the rituals and celebrations of many communities. However, in the Soconusco region (Chiapas, Mexico), the pseudobulbs of mature plants are affected by the Lasiodiplodia theobromae fungus, causing the disease “black blotch”. We evaluated and compared the diversity of the endophytic fungal community within the leaves, pseudobulbs and roots of mature plants in two conditions, asymptomatic and symptomatic. Thirty samples from each condition and tissue were amplified with ITS and sequenced by Illumina MiSeq. Sequences were obtained and analyzed to determine taxonomic assignment and functionality with FUNGuild, obtaining 1857 amplicon sequence variants (ASVs). Alpha diversity was similar between plant conditions. In symptomatic plants, significant differences were found between the three types of tissue. According to the FUNGuild functionality analysis, 368 ASVs were determined to be endophytic fungi. The tissues of G. skinneri plants are reservoirs of fungal endophytes that should be considered for further exploration for research and conservation purposes.
Construction of an Orthophoto-Draped 3D Model and Classification of Intertidal Habitats Using UAV Imagery in the Galapagos Archipelago
Authors: De Cock Andrée , Vandeputte Ruth , Bruneel Stijn , De Cock Laure , Liu Xingzhen , Bermúdez Rafael , Vanhaeren Nina , De Wit Bart , Ochoa Daniel , De Maeyer Philippe , Gautama Sidharta , Goethals Peter
Published: June 2023

Worldwide, an increasing number of marine islands suffer from various pressures on the environment, driven by climate change and increasing land demands. The Galapagos Archipelago is one of the most iconic group of islands, yet population growth and tourism have resulted in a rising need for efficient environmental monitoring of its fragile ecosystems, such as the intertidal zone which harbors diverse and unique fauna. The purpose of this study was to investigate the image classification opportunities for these intertidal habitats using Uncrewed Aerial Vehicle (UAV) imagery. The data for this research were collected in Puerto Ayora on Santa Cruz in August 2017, the most urbanized island of the Galapagos. An orthophoto, a digital elevation model (DEM), and an orthophoto-draped 3D model of the intertidal zone were obtained using image registration software. Based on the orthophoto, an initial classification of the intertidal zone was performed using the spectral angle mapper algorithm. A habitat map with four classes (water, sand, rock, and vegetation) was created with an overall classification accuracy of 77%, indicating the suitability of UAV high resolution aerial imagery for the classification of intertidal habitats. The developed method could be applied to map and monitor other coastal regions and islands systems.
Differential Shannon Entropies Characterizing Electron–Nuclear Dynamics and Correlation: Momentum-Space Versus Coordinate-Space Wave Packet Motion
Authors: Schürger Peter , Engel Volker
Published: June 2023

We calculate differential Shannon entropies derived from time-dependent coordinate-space and momentum-space probability densities. This is performed for a prototype system of a coupled electron–nuclear motion. Two situations are considered, where one is a Born–Oppenheimer adiabatic dynamics, and the other is a diabatic motion involving strong non-adiabatic transitions. The information about coordinate- and momentum-space dynamics derived from the total and single-particle entropies is discussed and interpreted with the help of analytical models. From the entropies, we derive mutual information, which is a measure for the electron–nuclear correlation. In the adiabatic case, it is found that such correlations are manifested differently in coordinate- and momentum space. For the diabatic dynamics, we show that it is possible to decompose the entropies into state-specific contributions.
Orders between Channels and Implications for Partial Information Decomposition
Authors: Gomes André F. C. , Figueiredo Mário A. T.
Published: June 2023

The partial information decomposition (PID) framework is concerned with decomposing the information that a set of random variables has with respect to a target variable into three types of components: redundant, synergistic, and unique. Classical information theory alone does not provide a unique way to decompose information in this manner, and additional assumptions have to be made. Recently, Kolchinsky proposed a new general axiomatic approach to obtain measures of redundant information based on choosing an order relation between information sources (equivalently, order between communication channels). In this paper, we exploit this approach to introduce three new measures of redundant information (and the resulting decompositions) based on well-known preorders between channels, contributing to the enrichment of the PID landscape. We relate the new decompositions to existing ones, study several of their properties, and provide examples illustrating their novelty. As a side result, we prove that any preorder that satisfies Kolchinsky’s axioms yields a decomposition that meets the axioms originally introduced by Williams and Beer when they first proposed PID.
The Interplay between Error, Total Variation, Alpha-Entropy and Guessing: Fano and Pinsker Direct and Reverse Inequalities
Authors: Rioul Olivier
Published: June 2023

Using majorization theory via “Robin Hood” elementary operations, optimal lower and upper bounds are derived on Rényi and guessing entropies with respect to either error probability (yielding reverse-Fano and Fano inequalities) or total variation distance to the uniform (yielding reverse-Pinsker and Pinsker inequalities). This gives a general picture of how the notion of randomness can be measured in many areas of computer science.
The Lacanian Subject and the Philosophy of Education: Diagnostic with, or without, Therapeutic?
Authors: Drousioti Kalli
Published: June 2023

Jacques Lacan’s ethical insights come up when he engages, inter alia, with Aristotelian and Kantian ethics. Tackling Aristotle’s ethics, Lacan complicates how human life would be best lived and fulfilled, and discussing Kant’s ethics, he sheds a different light on moral duty. In both cases, Lacan emphasizes the role of desire and law in the subject’s actions. Many Lacanian insights constitute a fertile context for political philosophy and philosophy of education to explore the ethic character of the subject. However, some postmodern political philosophers who draw on fundamental Lacanian concepts have theorized the “Self–Other” relationship in a way that ends up in a problematic ontological accommodation of evil. In this paper, I outline the aforementioned to highlight the following lacuna: much of the literature in educational philosophy that has utilized Lacan’s theory to deal with ethics has not addressed, head-on, whether the Lacanian subject is ethical, unethical, or none of these. Treating the subject as ethical or unethical would entail that Lacanian theory can mainly offer “diagnoses”. Treating the Lacanian subject as ethically neutral and, thus, as plastic, entails that Lacan’s theory leaves more ample space for “therapy”. My aim in this paper is to show that some unanswered questions regarding the (un)ethical subject in Lacan’s theory must be tackled if the philosophy of education that transfers Lacan’s ideas to the ethical educational context is to avoid self-contradiction.
Machine Learning-Based Estimation of COP and Multi-Objective Optimization of Operation Strategy for Heat Source Considering Electricity Cost and On-Site Consumption of Renewable Energy
Authors: Sagawa Daishi , Tanaka Kenji
Published: June 2023

Air conditioning is a significant consumer of electricity in buildings, accounting for around 40% of the total consumption. While previous studies have focused on planning methods to minimize electricity costs, recent years have seen an increasing need for energy management methods that consider environmental performance, such as CO2 emissions, alongside economic efficiency. This study proposes a mechanism to support stakeholders’ decision-making by calculating Pareto solutions based on the multi-objective optimization of economic and environmental characteristics for entities that own renewable energy generation facilities. Unlike many existing studies that assume a specific equation for COP (Coefficient of Performance) estimation, this study adopts a nonparametric COP estimation method using machine learning, resulting in a more realistic and flexible modeling of the system. The study also presents a model for selecting an operation strategy that balances environmental and economic goals, incorporating a thermal storage facility to improve the renewable energy rate. Specifically, we proposed and compared methods for calculating solutions using only the GA (Genetic Algorithm) and a two-step optimization method combining a GA and gradient-based optimization method, confirming the superiority of the two-step optimization method. The case study unveiled unique operational profiles corresponding to cost-saving, renewable-energy, and balanced orientation points, suggesting the existence of specific strategies tailored to each orientation. The findings of this study can help stakeholders make more informed decisions regarding energy management in air conditioning systems, with benefits for both the environment and the bottom line.
Efficient Management of Energy Consumption of Electric Vehicles Using Machine Learning—A Systematic and Comprehensive Survey
Authors: Adnane Marouane , Khoumsi Ahmed , Trovão João Pedro F.
Published: June 2023

Electric vehicles are growing in popularity as a form of transportation, but are still underused for several reasons, such as their relatively low range and the high costs associated with manufacturing and maintaining batteries. Many studies using several approaches have been conducted on electric vehicles. Among all studied subjects, here we are interested in the use of machine learning to efficiently manage the energy consumption of electric vehicles, in order to develop intelligent electric vehicles that make quick unprogrammed decisions based on observed data allowing minimal electricity consumption. Our interest is motivated by the adequate results obtained using machine learning in many fields and the increasing but still insufficient use of machine learning to efficiently manage the energy consumption of electric vehicles. From this standpoint, we have built this comprehensive survey covering a broad variety of scientific papers in the field published over the last few years. According to the findings, we identified the current trend and revealed future perspectives.
Laboratory Tests of the Resistance of an Unmanned Aerial Vehicle to the Normalized near Lightning Electrical Component
Authors: Kossowski Tomasz , Szczupak Paweł
Published: June 2023

This article describes a method of immunity testing for commercial unmanned aircraft vehicles relative to a variable near-lightning electric field component. The research focuses on one of the components of the electromagnetic field generated during a lightning discharge: the electrical component. Studies are proposed showing the influence of only this one factor on overvoltages arising in the drone. So far, no one has analyzed such an impact from emerging disturbances, because previous studies in the area have largely considered the impact of the entire electromagnetic field. This is justified practically, but not scientifically—it is necessary to determine the impact of each component separately. Selected electronic components are tested here. For that purpose, two types of pulses are used: Wave Form 4 (WF4–6.4/69 μs from DO-160 standard) and Voltage waveform 1.2/50 μs (PN-EN 61000-4-5:2014-10). The testing object is centrally placed in a capacitor between two parallel plates of dimensions 2 m by 2 m to provide a homogeneous electric field. The results (from a Rigol 1054Z oscilloscope) are saved in *.CSV files (for further analysis). The research shows that the greatest overvoltages are in active parts of the drone (higher-than-supply voltage level), such as the RF antenna or semiconductors. This emphasizes the need to pay special attention to the protection of these elements against a pulsed electromagnetic field, especially the electric component (e.g., lightning discharge).
Relationships between Selected Quality Tools and Energy Efficiency in Production Processes
Authors: Daroń Marta , Górska Monika
Published: June 2023

European manufacturing companies are currently in a very difficult situation. On the one hand, they have to strive for sustainable development. On the other hand, they have to face problems related to the geopolitical situation and the pursuit of cleaner production (including restrictive regulations on emissions). A significant increase in electricity prices means that companies have to take steps to use electricity rationally without reducing the level of production or incurring other additional costs. In this study, attention was paid to the influence of quality tools (QTs) in production process (PP) management on increasing energy efficiency (EE). Based on the literature review, it was found that the most frequently described QTs, i.e., SMED, TPM, Six Sigma, SPC, FMEA, 5S, or Poka-Yoke, used to improve PP did not take into account their impact on the EE of the enterprises. Therefore, the main purpose of this study was to examine this correlation and show that QTs can be helpful in shaping the energy management system (EMS). Achieving the research goal was possible thanks to surveys carried out among manufacturing companies. Using statistical tests, the existence of a statistically significant correlation was proved between QTs and EMS elements.
Selecting Suitable Battery Technologies for Untethered Robot
Authors: Verstraten Tom , Hosen Md Sazzad , Berecibar Maitane , Vanderborght Bram
Published: June 2023

Untethered robots carry their own power supply in the form of a battery pack, which has a crucial impact on the robot’s performance. Although battery technologies are richly studied and optimized for applications such as electric vehicles, computers and smartphones, they are often a mere afterthought in the design process of a robot system. This tutorial paper proposes criteria to evaluate the suitability of different battery technologies for robotic applications. Taking into consideration the requirements of different applications, the capabilities of relevant battery technologies are evaluated and compared. The tutorial also discusses current limitations and new technological developments, pointing out opportunities for interdisciplinary research between the battery technology and robotics communities.
Composite Insulator Defect Identification Method Based on Acoustic–Electric Feature Fusion and MMSAE Network
Authors: Zhang Bizhen , Shu Shengwen , Chen Cheng , Wang Xiaojie , Xu Jun , Fang Chaoying
Published: June 2023

Aiming to solve the partial discharge problem caused by defects in composite insulators, most existing live detection methods are limited by the subjectivity of human judgment, the difficulty of effective quantification, and the use of a single detection method. Therefore, a composite insulator defect diagnosis model based on acoustic–electric feature fusion and a multi-scale perception multi-input of stacked auto-encoder (MMSAE) network is proposed in this paper. Initially, during the withstanding voltage experiment, the electromagnetic wave spectrometer and ultrasonic detector were used to collect and process the data of six types of composite insulator samples with artificial defects. The electromagnetic wave spectrum, ultrasonic power spectral density, and n-S map were then obtained. Then, the network architecture of MMSAE was built by integrating a stacked auto-encoder and multi-scale perception module; the feature extraction and fusion methods of the electromagnetic wave spectrum and ultrasonic signal were investigated. The proposed method was used to diagnose test samples, and the diagnostic results were compared to those obtained using a single input source and the artificial neural network (ANN) method. The results demonstrate that the detection accuracy of acoustic–electric feature fusion is greater than that of a single feature; the accuracy of the proposed method is 99.17%, which is significantly higher than the accuracy of the conventional ANN method. Finally, composite insulator defect diagnosis software based on PYQT5 and Keras was developed. Ten 500 kV aging composite insulators were used to validate the effectiveness of the proposed method and design software.
CFD Prediction for Wind Power Generation by a Small Vertical Axis Wind Turbine: A Case Study for a University Campus
Authors: Tominaga Yoshihide
Published: June 2023

The accuracy of wind power generation predicted by computational fluid dynamics (CFD) simulations combined with meteorological wind data was validated based on comparisons with directly measured data for a small vertical axis wind turbine system installed on a university campus. The CFD simulations were performed in accordance with established guidelines and frameworks for the prediction of urban wind environments. At the rooftop location, where small wind turbines are typically installed, the deviations in wind velocity from the measurements are quite large. However, in the present study, the prediction accuracy for the wind turbine site, which was 4 m above the ground, was acceptable. The total power generation estimated using the assumed power curve based on the rated output of the turbine was 56% larger than that directly measured by the power generator. However, using the power curves obtained from the measurements, the total power generation could be predicted with a high degree of accuracy and with an error of approximately 3%. It is suggested that not only the accuracy of the wind velocity but also that of the power curve is very important because they are directly related to that of the predicted power generation.
Study on the Dynamic Characteristics of Tensional Force for Ice Accumulated Overhead Lines Considering Instantaneous Wind Speed
Authors: Li Meng , Hu Jianlin , Yang Yang , Zhao Mingguan , Wang Xiaofeng , Jiang Xingliang
Published: June 2023

Icing is one of the key factors affecting the security and reliability of power system operation. Ice accumulation on the overhead line (OHL) conductors is often accompanied by strong winds, whose magnitude and direction are varied constantly, which imposes challenges to the on-line monitoring of OHL’s ice load. This paper analyzed the dynamic characteristics of the tensional force for ice accumulated OHLs through both the on-site experiment and the finite element method (FEM). The correlation between the instantaneous wind speed, the thickness of the accumulated ice and the dynamic tensional force, the aerodynamic resistance coefficient of the conductor, is investigated. It is found that the axial dynamic tension at the end of the iced conductor is approximately proportional to the square of the instantaneous wind speed. The higher the wind speed, the larger the difference between the static tension and the maximum dynamic tension calculated using the 10-min average wind speed. Under the conditions of the example in this article (crescent-shaped icing), when the average wind speed is 20 m/s, the ratio of the difference to static tension is 11.19%. These conclusions are verified with the computational fluid dynamic (CFD) simulation, the same correlation is identified in comparison with the experiments. Due to the fact that the magnitudes of tensional force and vibration are determined by the instantaneous wind speed, significant error exists within traditional calculation methods where average wind speed is used instead.
Model of a Hybrid Electric Vehicle Equipped with Solid Oxide Fuel Cells Powered by Biomethane
Authors: Sandrini Giulia , Gadola Marco , Chindamo Daniel , Zecchi Laura
Published: June 2023

To promote the development of new technologies that allow an intensive use of renewable green energies and to overcome the problem of the lack of range of full electric vehicles, an interesting energy source is biomethane. The Fuel Cells (FCs) systems benefit from high efficiency and zero emissions, and they are generally powered by hydrogen. One of the main problems related to hydrogen FCs is the current weak network of infrastructure’s need to supply the hydrogen itself. An alternative may be the development of FC vehicles powered by methane, or biomethane, to exploit a renewable energy source. The type of Fuel Cells that lends itself to a methane (or biomethane) power supply is the Solid Oxide Fuel Cell (SOFC). Considering the limitations of the SOFCs, a vehicle model powered by Fuel Cells fueled by methane (or biomethane) is created. This work concerns the creation of a vehicle model, and the sizing of the SOFC system (generator delivering a constant 3 kW) and battery pack (30 Ah), for a door-to-door waste collection vehicle, whose mission is known. The latter is a fundamental requirement due to the limitations found for Solid Oxide Fuel Cells: slow transient and long ignition times.
Molecular Dynamics Simulation of High Temperature Mechanical Properties of Nano-Polycrystalline Beryllium Oxide and Relevant Experimental Verification
Authors: Hou Ming-Dong , Zhou Xiang-Wen , Liu Malin , Liu Bing
Published: June 2023

This article investigated the deformation behavior of nano-polycrystalline beryllium oxide under tensile and compressive stress using the molecular dynamics simulation method. Both the tensile and compressive test results indicate that beryllium oxide breaks mainly along grain boundaries. At low temperature, there is little internal deformation of beryllium oxide grains. When the temperature is above 1473 K, the internal deformation of beryllium oxide grains also occurs, and the phenomenon becomes more obvious with the increase in temperature. This deformation within the grain should be plastic. The flexural strength fracture morphology of beryllium oxide also shows that the fracture mode of beryllium oxide is a brittle fracture at low temperature, while the slip bands appear at 1773 K. This indicates that beryllium oxide, as a ceramic material, can also undergo plastic deformation under high temperature and stress.
The Future of Electrical Power Grids: A Direction Rooted in Power Electronics
Authors: Monteiro Vitor , Afonso Joao L.
Published: June 2023

Electrical power grids are changing with a focus on ensuring energy sustainability and enhanced power quality for all sectors. Over the last few decades, there has been a change from a centralized to a decentralized paradigm, which is the consequence of a large-scale incorporation of new electrical technologies and resultant equipment. Considering the foreseeable continuation of changes in electrical power grids, a direction rooted in power electronics with a focus on hybrid AC/DC grids, including the support of solid-state transformers and unified systems, is presented in this paper. Converging on hybrid AC/DC grids, DC grids (structured as unipolar and bipolar) and coupled and decoupled AC configurations are analyzed. On the other hand, in the context of solid-state transformers, feasible structures are analyzed, including the establishment of hybrid AC/DC grids, and the assessment of gains for boosting power quality is presented. Unified power electronics systems are also of fundamental importance when contextualized within the framework of future power grids, presenting higher efficiency, lower power stages, and the possibility of multiple operations to support the main AC grid. In this paper, such subjects are discussed and contextualized within the framework of future power grids, encompassing highly important and modern structures and their associated challenges. Various situations are characterized, revealing a gradual integration of the cited technologies for future power grids, which are also known as smart grids.
Increasing Thermal Efficiency: Methods, Case Studies, and Integration of Heat Exchangers with Renewable Energy Sources and Heat Pumps for Desalination
Authors: Osintsev Konstantin , Aliukov Sergei , Kuskarbekova Sulpan , Tarasova Tatyana , Karelin Aleksandr , Konchakov Vladimir , Kornyakova Olga
Published: June 2023

The article presents an overview of modern analytical methods and experimental studies on the use of heat exchangers as part of different schemes, as well as technologies that increase the efficiency of heat exchangers using renewable energy sources. The main types of heat exchangers, and the principles of their operation, are considered. In addition, modern technologies for increasing the efficiency of heat exchangers through design are described. The practical experience of using plate heat exchangers in industry has been studied. An overview of the software development that is used in the design and optimization of heat exchange devices, as well as for the improvement of their energy efficiency, is presented. The presented mathematical models can be used for software that is applicable both to individual segments of plates of heat exchangers and heat exchangers in general, taking into account the dependence of the installation of the entire circuit on environmental parameters and location. In conclusion, recommendations are given for further research directions in the field of using heat exchangers with the inclusion of renewable energy sources. The technique of an energy technology complex, including a heat pump, a photovoltaic panel, and a desalination plant, is presented. The methodology is built around the basic design and energy balance of the complex, and it is also considered from the point of view of the exergetic balance. This allows for the use of additional components, such as a turbo expander for the implementation of the organic Rankine cycle, a wind turbine, and a solar concentrator. This scientific approach can become unified for the design and operation of an energy technology complex. In addition, an exergetic calculation method is presented for a thermal desalination plant operating as part of an energy technology complex with renewable energy sources.
Electricity Blackout and Its Ripple Effects: Examining Liquidity and Information Asymmetry in U.S. Financial Markets
Authors: Kim Dosung , Kim Jang-Chul , Su Qing , Joo Sung-Kwan
Published: June 2023

The massive blackout that occurred in August 2003 left over 50 million people in the northeastern and midwestern parts of the United States without electricity and caused billions of dollars in economic losses. This event highlighted the importance of sustainable and resilient energy infrastructure. Our study examines the impact of this blackout on the sustainability of financial markets by analyzing the liquidity and information asymmetry of U.S. stocks listed on major exchanges. Our results show that the blackout had a negative impact on the financial market’s liquidity, as evidenced by a significant widening of bid–ask spreads and a decrease in the market quality index. We also find an increase in information asymmetry during the blackout period, as measured by higher realized spreads. Furthermore, our study reveals that the blackout had a border impact on global financial markets and the negative effect on liquidity persisted even after two weeks.
Liquid CO2 and Liquid Air Energy Storage Systems: A Thermodynamic Analysis
Authors: Marchionni Matteo , Cipollone Roberto
Published: June 2023

Energy storage is a key factor to confer a technological foundation to the concept of energy transition from fossil fuels to renewables. Their solar dependency (direct radiation, wind, biomass, hydro, etc. …) makes storage a requirement to match the supply and demand, with fulfillment being another key factor. Recently, the most attention is directed toward the direct electrical storage inside batteries, probably driven by interest in the transportation sector, which today is the main focus in the transition path. On the contrary, for the generation of electrical energy and, more generally, for industrial sectors whose CO2 emissions are defined as hard-to-abate, electrical storage is not a feasible answer to many political and non-technological concerns. Therefore, other storage methods must be considered to address excess electricity, the most characteristics of which being both the capacity and rate of charging/delivering. Among the efforts under consideration, the liquid storage of gases at ambient conditions is certainly an interesting option. This is the case with air and CO2. The paper focused on the storage of CO2 in liquid form, comparing its performance with those of air liquefaction, which well-studied in the literature. The paper proposed a novel plant layout design for a liquid CO2 energy storage system that can improve the round-trip efficiency by up to 57%. The system was also compared to a liquid air energy storage unit considering a state-of-the-art level of technology for components, showing better efficiency but lower energy density. Finally, a sensitivity analysis was used to discuss the most relevant variables for a plant design. Particular focus was devoted to the discharging time of the plant, one of the most relevant variables that matches the energy demand.
THD Minimization in a Seven-Level Multilevel Inverter Using the TLBO Algorithm
Authors: Gómez Díaz Kenia Yadira , de León Aldaco Susana Estefany , Aguayo Alquicira Jesus , Vela Valdés Luis Gerardo
Published: June 2023

This paper presents the minimization of total harmonic distortion in a seven-level cascaded H-bridge multilevel inverter with resistive load using the teaching–learning-based optimization algorithm. The minimization of Total Harmonic Distortion (THD)is a challenging optimization problem due to the fact that nonlinear equations are involved. Recently, bio-inspired algorithms have become very popular approaches to solving various optimization problems in different areas of engineering. For this reason, the results obtained with the Teaching–Learning-Based Optimization (TLBO)algorithm were compared with three other popular bio-inspired algorithms, the genetic algorithm, differential evolution, and particle swarm optimization. The comparative analysis, conducted by sweeping the modulation index, made it possible to obtain graphs and data on the behavior of the four analyzed algorithms. Finally, it was concluded that the TLBO algorithm is very effective and is able to solve the THD-minimization problem. Its main advantage over the other algorithms is the fact that it does not require control parameters for its correct operation in the solution of the problem.
A Neural Network-Based Hydrological Model for Very High-Resolution Forecasting Using Weather Radar Data
Authors: Santos Leonardo B. L. , Freitas Cintia P. , Bacelar Luiz , Soares Jaqueline A. J. P. , Diniz Michael M. , Lima Glauston R. T. , Stephany Stephan
Published: June 2023

Many hydro-meteorological disasters in small and steep watersheds develop quickly and significantly impact human lives and infrastructures. High-resolution rainfall data and machine learning methods have been used as modeling frameworks to predict those events, such as flash floods. However, a critical question remains: How long must the rainfall input data be for an empirical-based hydrological forecast? The present article employed an artificial neural network (ANN)hydrological model to address this issue to predict river levels and investigate its dependency on antecedent rainfall conditions. The tests were performed using observed water level data and high-resolution weather radar rainfall estimation over a small watershed in the mountainous region of Rio de Janeiro, Brazil. As a result, the forecast water level time series only archived a successful performance (i.e., Nash–Sutcliffe model efficiency coefficient (NSE) > 0.6) when data inputs considered at least 2 h of accumulated rainfall, suggesting a strong physical association to the watershed time of concentration. Under extended periods of accumulated rainfall (>12 h), the framework reached considerably higher performance levels (i.e., NSE > 0.85), which may be related to the ability of the ANN to capture the subsurface response as well as past soil moisture states in the watershed. Additionally, we investigated the model’s robustness, considering different seeds for random number generating, and spacial applicability, looking at maps of weights.
Epidemiology of COVID-19 among Children and Adolescents in Sudan 2020–2021
Authors: Khairy Amna , Elhussein Narmin , Elbadri Omer , Mohamed Sanad , Malik Elfatih M.
Published: June 2023

Children and adolescents account for a small proportion of confirmed COVID-19 cases, with mild and self-limiting clinical manifestations. The distribution and determinants of COVID-19 among this group in Sudan are unclear. This study used national COVID-19 surveillance data to study the epidemiology of COVID-19 among children and adolescents in Sudan during 2020–2021. A cross-sectional study was performed to estimate the reported incidence of children and adolescents with COVID-19; the clinical features; and the mortality among those who tested positive for COVID-19. A total of 3150 suspected cases of COVID-19 infection fulfilled the study criteria. The majority of cases were above 10 years of age, 52% (1635) were males, and 56% (1765) were asymptomatic. The reported incidence rates of COVID-19 among children and adolescents in Sudan was 1.3 per 10,000 in 2021. Fever, cough, and headache were the most frequent symptoms reported among the suspected cases. The case fatality rate was 0.2%. Binary logistic regression revealed that loss of smell was the most significantly associated symptom with a positive test. We recommend further study to identify risk factors. Additionally, we recommend including these age groups in the vaccination strategy in Sudan.