bluuebunny/crossref_metadata_2025 huggingface dataset:
The Arthropod Fauna of Oak (Quercus spp., Fagaceae) Canopies in Norway
Authors: Thunes Karl H. , Søli Geir E. E. , Thuróczy Csaba , Fjellberg Arne , Olberg Stefan , Roth Steffen , Coulianos Carl-C. , Disney R. Henry L. , Starý Josef , Vierbergen G. (Bert) , Jonassen Terje , Anonby Johannes , Köhler Arne , Menzel Frank , Szadziewski Ryszard , Stur Elisabeth , Adaschkiewitz Wolfgang , Olsen Kjell M. , Kvamme Torstein , Endrestøl Anders , Podenas Sigitas , Kobro Sverre , Hansen Lars O. , Kvifte Gunnar M. , Haenni Jean-Paul , Boumans Louis
Published: July 2021

(1) We document the invertebrate fauna collected from 24 oak canopies in east and west Norway as a contribution to the Norwegian Biodiversity Information Centre’s ‘The Norwegian Taxonomy Initiative’. (2) A snap-shot inventory of the canopies was recorded by means of emitting a mist of natural pyrethrum into the canopies at night using a petrol-driven fogger and collecting the specimens in butterfly nets spread on the ground under the canopy. (3) Almost the entire catch of more than 6800 specimens was identified to 722 species. Out of 92 species new to the Norwegian fauna, 21 were new to science and, additionally, 15 were new to the Nordic fauna. Diptera alone constituted nearly half of the species represented, with 61 new records (18 new species). Additionally, 24 Hymenoptera (one new species), six oribatid mites (two new species) and one Thysanoptera were new to the Norwegian fauna. (4) Our study emphasizes the importance of the oak tree as a habitat both for a specific fauna and occasional visitors, and it demonstrates that the canopy fogging technique is an efficient way to find the ‘hidden fauna’ of Norwegian forests. The low number of red listed species found reflects how poor the Norwegian insect fauna is still studied. Moreover, the implication of the IUCN red list criteria for newly described or newly observed species is discussed.
Microfiltration and Ultrafiltration Process to Produce Micellar Casein and Milk Protein Concentrates with 80% Crude Protein Content: Partitioning of Various Protein Fractions and Constituents
Authors: Salunke Prafulla , Marella Chenchaiah , Metzger Lloyd E.
Published: July 2021

The objective of the study reported in this research paper was to produce micellar casein concentrate (MCC) and milk protein concentrate (MPC) with 80% crude protein relative to total solids (TS) using MF and UF processes respectively. Additionally, capillary gel electrophoresis (CGE) was used to study the protein fractions in retentate and permeate. For MCC production, 227 L of pasteurized SM was subjected to MF using 0.5-micron spiral wound polyvinylidene fluoride membrane. During the process, diafiltration (DF) water was added at six intervals, totaling 100% of the feed volume. For MPC production, 227 L of pasteurized SM from the same lot was subjected to UF using 10 kDa Polyethersulfone membranes. During the process, DF water was added at four different intervals, with a final total addition of 40% of the feed volume. Both processes used a volume reduction of five. There were significant (p < 0.05) differences in all of the compositional parameters, except fat and casein for the MF retentate (MFR) and UF retentate (UFR). UFR had a higher crude protein (CP), TS, lactose, ash and calcium content as compared to MFR and this affected the CP/TS ratio found in both the retentates. The differences in membrane pore sizes, operating pressures and level of DF used all contributed to the differences in final CP/TS ratio obtained. The CGE analysis of individual protein fractions present in the UFR and MFR showed that UFR has a β-lactaglobulin to α-lactalbumin (α-LA) ratio similar to SM, whereas the MFR has a higher ratio, indicating preferential transmission for α-LA by the MF membrane. The results from this study show that MF and UF processes could be used for production of MCC and MPC with similar CP/TS ratio with careful selection of operating parameters, and that CGE can be used for detailed analysis of various protein fractions.
Comprehensive Echocardiography of Left Atrium and Left Ventricle Using Modern Techniques Helps in Better Revealing Atrial Fibrillation in Patients with Hypertrophic Cardiomyopathy
Authors: Wabich Elżbieta , Zienciuk-Krajka Agnieszka , Nowak Radosław , Raczak Alicja , Daniłowicz-Szymanowicz Ludmiła
Published: July 2021

Atrial fibrillation (AF) is an important arrhythmia in hypertrophic cardiomyopathy (HCM). We aimed to explore whether a complex evaluation of the left ventricle (LV) using modern echocardiography techniques, additionally to the left atrium (LA) boosts the probability of AF diagnosis. Standard echocardiography, 2D and 3D speckle tracking, were performed for LA and LV evaluation in HCM patients and healthy volunteers. Of 128 initially qualified HCM patients, 60 fulfilled included criteria, from which 43 had a history of AF, and 17 were without AF. LA volume index and peak strain, LV ejection fraction, and strains were significant predictors of AF. In addition, 2D global longitudinal strain (GLS) for LV at cut off −16% turned out to be the most accurate predictor of AF (OR 48.00 [95% CI 2.68–859.36], p = 0.001), whereas the combination of LA peak strain ≤ 22% and LV GLS ≥ −16% had the highest discriminatory power (OR 76.36 [95% CI 4.13–1411.36], p = 0.001). AF in HCM patients seems to be LA as well as LV disease. Revealing lower strain for LV, in addition to lower LA strain, may have an important impact on accurate characteristics of HCM patients with AF history.
Independent Validation of Sepsis Index for Sepsis Screening in the Emergency Department
Authors: Agnello Luisa , Iacona Alessandro , Maestri Salvatore , Lo Sasso Bruna , Giglio Rosaria Vincenza , Mancuso Silvia , Ciaccio Anna Maria , Vidali Matteo , Ciaccio Marcello
Published: July 2021

(1) Background: The early detection of sepsis is still challenging, and there is an urgent need for biomarkers that could identify patients at a high risk of developing it. We recently developed an index, namely the Sepsis Index (SI), based on the combination of two CBC parameters: monocyte distribution width (MDW) and mean monocyte volume (MMV). In this study, we sought to independently validate the performance of SI as a tool for the early detection of patients at a high risk of sepsis in the Emergency Department (ED). (2) Methods: We enrolled all consecutive patients attending the ED with a request of the CBC. MDW and MMV were measured on samples collected in K3-EDTA tubes on the UniCel DxH 900 haematology analyser. SI was calculated based on the MDW and MMV. (3) Results: We enrolled a total of 703 patients stratified into four subgroups according to the Sepsis-2 criteria: control (498), infection (105), SIRS (52) and sepsis (48). The sepsis subgroup displayed the highest MDW (median 27.5, IQR 24.6–32.9) and SI (median 1.15, IQR 1.05–1.29) values. The ROC curve analysis for the prediction of sepsis showed a good and comparable diagnostic accuracy of the MDW and SI. However, the SI displayed an increased specificity, positive predictive value and positive likelihood ratio in comparison to MDW alone. (4) Conclusions: SI improves the diagnostic accuracy of MDW for sepsis screening.
To the Question on the Use of Multivariate Analysis and 2D Visualisation of Synchrotron ATR-FTIR Chemical Imaging Spectral Data in the Diagnostics of Biomimetic Sound Dentin/Dental Composite Interface
Authors: Seredin Pavel , Goloshchapov Dmitry , Kashkarov Vladimir , Ippolitov Yuri , Ippolitov Ivan , Vongsvivut Jitraporn
Published: July 2021

In this short communication, we provide information on the use of the hierarchical cluster analysis of synchrotron ATR-FTIR 2D chemical imaging spectral data as a useful and powerful approach to the microspectroscopic diagnostics of molecular composition in the hybrid sound dentin/dental composite interfaces and materials, including ones developed with the use of biomimetic strategies. The described diagnostic approach can be successfully transferred to the analysis and visualisation of 2D spectral data, collected using laboratory Raman and FTIR microspectroscopy techniques.
Adaptive Two-Step Bearing-Only Underwater Uncooperative Target Tracking with Uncertain Underwater Disturbances
Authors: Hou Xianghao , Zhou Jianbo , Yang Yixin , Yang Long , Qiao Gang
Published: July 2021

The bearing-only tracking of an underwater uncooperative target can protect maritime territories and allows for the utilization of sea resources. Considering the influences of an unknown underwater environment, this work aimed to estimate 2-D locations and velocities of an underwater target with uncertain underwater disturbances. In this paper, an adaptive two-step bearing-only underwater uncooperative target tracking filter (ATSF) for uncertain underwater disturbances is proposed. Considering the nonlinearities of the target’s kinematics and the bearing-only measurements, in addition to the uncertain noise caused by an unknown underwater environment, the proposed ATSF consists of two major components, namely, an online noise estimator and a robust extended two-step filter. First, using a modified Sage-Husa online noise estimator, the uncertain process and measurement noise are estimated at each tracking step. Then, by adopting an extended state and by using a robust negative matrix-correcting method in conjunction with a regularized Newton-Gauss iteration scheme, the current state of the underwater uncooperative target is estimated. Finally, the proposed ATSF was tested via simulations of a 2-D underwater uncooperative target tracking scenario. The Monte Carlo simulation results demonstrated the reliability and accuracy of the proposed ATSF in bearing-only underwater uncooperative tracking missions.
Tsallis q-Stat and the Evidence of Long-Range Interactions in Soil Temperature Dynamics
Authors: Ogunsua Babalola O. , Laoye John A.
Published: July 2021

The complexities in the variations of soil temperature and thermal diffusion poses a physical problem that requires more understanding. The quest for a better understanding of the complexities of soil temperature variation has prompted the study of the q-statistics in the soil temperature variation with the view of understanding the underlying dynamics of the temperature variation and thermal diffusivity of the soil. In this work, the values of Tsallis stationary state q index known as q-stat were computed from soil temperature measured at different stations in Nigeria. The intrinsic variations of the soil temperature were derived from the soil temperature time series by detrending method to extract the influences of other types of variations from the atmosphere. The detrended soil temperature data sets were further analysed to fit the q-Gaussian model. Our results show that our datasets fit into the Tsallis Gaussian distributions with lower values of q-stat during rainy season and around the wet soil regions of Nigeria and the values of q-stat obtained for monthly data sets were mostly in the range 1.2≤q≤2.9 for all stations, with very few values q closer to 1.2 for a few stations in the wet season. The distributions obtained from the detrended soil temperature data were mostly found to belong to the class of asymmetric q-Gaussians. The ability of the soil temperature data sets to fit into q-Gaussians might be due and the non-extensive statistical nature of the system and (or) consequently due to the presence of superstatistics. The possible mechanisms responsible this behaviour was further discussed.
Channel Quality-Based Optimal Status Update for Information Freshness in Internet of Things
Authors: Peng Fuzhou , Chen Xiang , Wang Xijun
Published: July 2021

This paper investigates the status updating policy for information freshness in Internet of things (IoT) systems, where the channel quality is fed back to the sensor at the beginning of each time slot. Based on the channel quality, we aim to strike a balance between the information freshness and the update cost by minimizing the weighted sum of the age of information (AoI) and the energy consumption. The optimal status updating problem is formulated as a Markov decision process (MDP), and the structure of the optimal updating policy is investigated. We prove that, given the channel quality, the optimal policy is of a threshold type with respect to the AoI. In particular, the sensor remains idle when the AoI is smaller than the threshold, while the sensor transmits the update packet when the AoI is greater than the threshold. Moreover, the threshold is proven to be a non-increasing function of channel state. A numerical-based algorithm for efficiently computing the optimal thresholds is proposed for a special case where the channel is quantized into two states. Simulation results show that our proposed policy performs better than two baseline policies.
Numerical Simulation of Swirl Flow Characteristics of CO2 Hydrate Slurry by Short Twisted Band
Authors: Rao Yongchao , Liu Zehui , Wang Shuli , Li Lijun , Sun Qi
Published: July 2021

The development of oil and gas resources is gradually transferring to the deep sea, and the hydrate plugging of submarine pipelines at high pressures and low temperatures is becoming an important problem to ensure the safety of pipeline operations. The swirl flow is a new method to expand the boundary of hydrate safe flow. Numerical simulation of the hydrate slurry flow characteristics in a horizontal pipeline by twisted band has been carried out, and the flow of CO2 hydrate slurry in low concentration has been simulated by the RSM and DPM models. The results show that the heat transfer efficiency is also related to Re and particle concentration. The velocity distribution has the form of symmetrical double peaks, and the peaks finally merge at the center of the pipeline. Vortexes firstly appear on both sides of the edge of the twisted band, and then move to the middle part of the twisted band. Finally, the vortex center almost coincides with the velocity center. The rotation direction of hydrate particles is the same as the twisted direction of the twisted band, twist rate (Y) is smaller, Re is larger, and the symmetric vortex lines merge farther away. The initial swirl number is mainly related to Y, but not Re. The swirl flow attenuates exponentially, and its attenuation rate is mainly related to Re, but not Y. Compared with ordinary pipelines, the swirl flow can obviously improve the transportation distance of hydrate slurry.
Crystal Structure and Preparation of Li7La3Zr2O12 (LLZO) Solid-State Electrolyte and Doping Impacts on the Conductivity: An Overview
Authors: Raju Md Mozammal , Altayran Fadhilah , Johnson Michael , Wang Danling , Zhang Qifeng
Published: July 2021

As an essential part of solid-state lithium-ion batteries, solid electrolytes are receiving increasing interest. Among all solid electrolytes, garnet-type Li7La3Zr2O12 (LLZO) has proven to be one of the most promising electrolytes because of its high ionic conductivity at room temperature, low activation energy, good chemical and electrochemical stability, and wide potential window. Since the first report of LLZO, extensive research has been done in both experimental investigations and theoretical simulations aiming to improve its performance and make LLZO a feasible solid electrolyte. These include developing different methods for the synthesis of LLZO, using different crucibles and different sintering temperatures to stabilize the crystal structure, and adopting different methods of cation doping to achieve more stable LLZO with a higher ionic conductivity and lower activation energy. It also includes intensive efforts made to reveal the mechanism of Li ion movement and understand its determination of the ionic conductivity of the material through molecular dynamic simulations. Nonetheless, more insightful study is expected in order to obtain LLZO with a higher ionic conductivity at room temperature and further improve chemical and electrochemical stability, while optimal multiple doping is thought to be a feasible and promising route. This review summarizes recent progress in the investigations of crystal structure and preparation of LLZO, and the impacts of doping on the lithium ionic conductivity of LLZO.
Modeling Radio-Frequency Devices Based on Deep Learning Technique
Authors: Guan Zhimin , Zhao Peng , Wang Xianbing , Wang Gaofeng
Published: July 2021

An advanced method of modeling radio-frequency (RF) devices based on a deep learning technique is proposed for accurate prediction of S parameters. The S parameters of RF devices calculated by full-wave electromagnetic solvers along with the metallic geometry of the structure, permittivity and thickness of the dielectric layers of the RF devices are used partly as the training and partly as testing data for the deep learning structure. To implement the training procedure efficiently, a novel selection method of training data considering critical points is introduced. In order to rapidly and accurately map the geometrical parameters of the RF devices to the S parameters, deep neural networks are used to establish the multiple non-linear transforms. The hidden-layers of the neural networks are adaptively chosen based on the frequency response of the RF devices to guarantee the accuracy of generated model. The Adam optimization algorithm is utilized for the acceleration of training. With the established deep learning model of a parameterized device, the S parameters can efficiently be obtained when the device geometrical parameters change. Comparing with the traditional modeling method that uses shallow neural networks, the proposed method can achieve better accuracy, especially when the training data are non-uniform. Three RF devices, including a rectangular inductor, an interdigital capacitor, and two coupled transmission lines, are used for building and verifying the deep neural network. It is shown that the deep neural network has good robustness and excellent generalization ability. Even for very wide frequency band (0–100 GHz), the maximum relative error of the coupled transmission lines using the proposed method is below 3%.
Error-Tolerant Reconfigurable VDD 10T SRAM Architecture for IoT Applications
Authors: Gupta Neha , Shah Ambika Prasad , Khan Sajid , Vishvakarma Santosh Kumar , Waltl Michael , Girard Patrick
Published: July 2021

This paper proposes an error-tolerant reconfigurable VDD (R-VDD) scaled SRAM architecture, which significantly reduces the read and hold power using the supply voltage scaling technique. The data-dependent low-power 10T (D2LP10T) SRAM cell is used for the R-VDD scaled architecture with the improved stability and lower power consumption. The R-VDD scaled SRAM architecture is developed to avoid unessential read and hold power using VDD scaling. In this work, the cells are implemented and analyzed considering a technologically relevant 65 nm CMOS node. We analyze the failure probability during read, write, and hold mode, which shows that the proposed D2LP10T cell exhibits the lowest failure rate compared to other existing cells. Furthermore, the D2LP10T cell design offers 1.66×, 4.0×, and 1.15× higher write, read, and hold stability, respectively, as compared to the 6T cell. Moreover, leakage power, write power-delay-product (PDP), and read PDP has been reduced by 89.96%, 80.52%, and 59.80%, respectively, compared to the 6T SRAM cell at 0.4 V supply voltage. The functional improvement becomes even more apparent when the quality factor (QF) is evaluated, which is 458× higher for the proposed design than the 6T SRAM cell at 0.4 V supply voltage. A significant improvement of power dissipation, i.e., 46.07% and 74.55%, can also be observed for the R-VDD scaled architecture compared to the conventional array for the respective read and hold operation at 0.4 V supply voltage.
Multi-Layer Latency Aware Workload Assignment of E-Transport IoT Applications in Mobile Sensors Cloudlet Cloud Networks
Authors: Lakhan Abdullah , Dootio Mazhar Ali , Groenli Tor Morten , Sodhro Ali Hassan , Khokhar Muhammad Saddam
Published: July 2021

These days, with the emerging developments in wireless communication technologies, such as 6G and 5G and the Internet of Things (IoT) sensors, the usage of E-Transport applications has been increasing progressively. These applications are E-Bus, E-Taxi, self-autonomous car, E-Train and E-Ambulance, and latency-sensitive workloads executed in the distributed cloud network. Nonetheless, many delays present in cloudlet-based cloud networks, such as communication delay, round-trip delay and migration during the workload in the cloudlet-based cloud network. However, the distributed execution of workloads at different computing nodes during the assignment is a challenging task. This paper proposes a novel Multi-layer Latency (e.g., communication delay, round-trip delay and migration delay) Aware Workload Assignment Strategy (MLAWAS) to allocate the workload of E-Transport applications into optimal computing nodes. MLAWAS consists of different components, such as the Q-Learning aware assignment and the Iterative method, which distribute workload in a dynamic environment where runtime changes of overloading and overheating remain controlled. The migration of workload and VM migration are also part of MLAWAS. The goal is to minimize the average response time of applications. Simulation results demonstrate that MLAWAS earns the minimum average response time as compared with the two other existing strategies.
Multi-Objective Energy Management Strategy for PV/FC Hybrid Power Systems
Authors: Bizon Nicu , Thounthong Phatiphat
Published: July 2021

In this paper, a new control of the DC–DC power converter that interfaces the fuel cell (FC) system with the DC bus of the photovoltaic (PV) power system is proposed to increase the battery lifespan by its operating in charge-sustained mode. Thus, the variability of the PV power and the load demand is compensated by the FC power generated considering the power flows balance on the DC bus. During peak PV power, if the PV power exceeds the load demand, then the excess power on the DC bus will power an electrolyzer. The FC system operation as a backup energy source is optimized using a new fuel economy strategy proposed for fueling regulators. The fuel optimization function considers the fuel efficiency and electrical efficiency of the FC system to maximize fuel economy. The fuel economy obtained in the scenarios considered in this study is compared with reference strategies reported in the literature. For example, under scenarios considered in this paper, the fuel economy is between 4.82–20.71% and 1.64–3.34% compared to a commercial strategy based on static feed-forward (sFF) control and an advanced strategy recently proposed in the literature, respectively.
Improved Droop Control Strategy of Multiple Energy Storage Applications in an AC Microgrid Based on the State of Charge
Authors: Wang Xiaogang , Wang Hongdong
Published: July 2021

Distributed energy storage technology is used to stabilize the frequency and voltage of the microgrid operating in islanded mode. However, due to the inconsistent state of charge (SoC) of the energy storage unit (ESU), the active power output of the ESU cannot be shared reasonably. On the basis of stabilizing voltage and frequency, this paper presents a power exponential function droop control (PEFDC) strategy considering the SoC. In this control strategy, the ESU is allowed to adjust the output power adaptively according to its own SoC level during discharge and reaches SoC equilibrium. Simulation models are built to compare the PEFDC strategy with conventional droop control (CDC) and power function droop control (PFDC) approaches. The simulation results illustrate the superiority of the proposed control strategy over the other two methods. Finally, the hardware-in-the-loop experiment is conducted to verify the effectiveness of the PEFDC strategy.
Lightweight Physical Layer Aided Key Agreement and Authentication for the Internet of Things
Authors: Han Seungnam , Lee Yonggu , Choi Jinho , Hwang Euiseok
Published: July 2021

In this paper, we propose a lightweight physical layer aided authentication and key agreement (PL-AKA) protocol in the Internet of Things (IoT). The conventional evolved packet system AKA (EPS-AKA) used in long-term evolution (LTE) systems may suffer from congestion in core networks by the large signaling overhead as the number of IoT devices increases. Thus, in order to alleviate the overhead, we consider cross-layer authentication by integrating physical layer approaches to cryptography-based schemes. To demonstrate the feasibility of the PL-AKA, universal software radio peripheral (USRP) based tests are conducted as well as numerical simulations. The proposed scheme shows a significant reduction in the signaling overhead, compared to the conventional EPS-AKA in both the simulation and experiment. Therefore, the proposed lightweight PL-AKA has the potential for practical and efficient implementation of large-scale IoT networks.
Normalized Partial Scattering Cross Section for Performance Evaluation of Low-Observability Scattering Structures
Authors: Abdullah Muhammad , Koziel Slawomir , Szczepanski Stanislaw
Published: July 2021

The development of diffusion metasurfaces created new opportunities to elevate the stealthiness of combat aircraft. Despite the potential significance of metasurfaces, their rigorous design methodologies are still lacking, especially in the context of meticulous control over the scattering of electromagnetic (EM) waves through geometry parameter tuning. Another practical issue is insufficiency of the existing performance metrics, specifically, monostatic and bistatic evaluation of the reflectivity, especially at the design stage of metasurfaces. Both provide limited insight into the RCS reduction properties, with the latter being dependent on the selection of the planes over which the evaluation takes place. This paper introduces a novel performance metric for evaluating scattering characteristics of a metasurface, referred to as Normalized Partial Scattering Cross Section (NPSCS). The metric involves integration of the scattered energy over a specific solid angle, which allows for a comprehensive assessment of the structure performance in a format largely independent of the particular arrangement of the scattering lobes. We demonstrate the utility of the introduced metric using two specific metasurface architectures. In particular, we show that the integral-based metric can be used to discriminate between the various surface configurations (e.g., checkerboard versus random), which cannot be conclusively compared using traditional methods. Consequently, the proposed approach can be a useful tool in benchmarking radar cross section reduction performance of metamaterial-based, and other types of scattering structures.
A Review of DC Microgrid Energy Management Systems Dedicated to Residential Applications
Authors: Ali Sadaqat , Zheng Zhixue , Aillerie Michel , Sawicki Jean-Paul , Péra Marie-Cécile , Hissel Daniel
Published: July 2021

The fast depletion of fossil fuels and the growing awareness of the need for environmental protection have led us to the energy crisis. Positive development has been achieved since the last decade by the collective effort of scientists. In this regard, renewable energy sources (RES) are being deployed in the power system to meet the energy demand. The microgrid concept (AC, DC) is introduced, in which distributed energy resources (DERs), the energy storage system (ESS) and loads are interconnected. DC microgrids are appreciated due to their high efficiency and reliability performance. Despite its significant growth, the DC microgrid is still relatively novel in terms of grid architecture and control systems. In this context, an energy management system (EMS) is essential for the optimal use of DERs in secure, reliable, and intelligent ways. Therefore, this paper strives to shed light on DC microgrid architecture, control structure, and EMS. With an extensive literature survey on EMSs’ role, different methods and strategies related to microgrid energy management are covered in this article. More attention is centered on the EMS for DC microgrids in terms of size and cost optimization. A very concise analysis of multiple optimization methods and techniques has been presented exclusively for residential applications.
Decarbonization of Marine Fuels—The Future of Shipping
Authors: Herdzik Jerzy
Published: July 2021

The goal of reducing the climate impact of shipping requires many different activities. To reduce greenhouse gas emissions, the International Maritime Organization prepared some proposals to meet and fulfill the requirements. It sets out the provisions of the International Convention for the Prevention of Pollution from Ships 73/78 Annex 6—Prevention of the Air Pollution from Ships (1997) with the amendments and the future objectives set. The main objective is to achieve climate neutrality from shipping by 2050. One method is the decarbonization of marine fuels. The types of fuels that are transient fuels, with the final target fuel being hydrogen, are shown. Carbon dioxide emissions depend on the chemical composition of the fuel, its Lower Heating Value and the engine efficiency. The aim of the manuscript is to demonstrate that the use of fuels with lower carbon content is a transitional process enabling the hydrogen era to take place. An analysis of this problem is presented as a review of the subject along with the author’s comments and observations. The development of technologies for adapting potential fuels to combustion requirements in marine diesel engines and gas turbines, together with their storage and bunkering capabilities, are the main barriers to their limited use. The efficiency of marine diesel engines reaches a value of about 50%, while that of fuel cells are close to 100%. It seems that hydrogen will be the fuel of the future, including in shipping. Its basic use is in fuel cells, the efficiency of which is almost twice that of current thermal internal combustion engines.
Autonomous Analysis of Infrared Images for Condition Diagnosis of HV Cable Accessories
Authors: Mu Lixiao , Xu Xiaobing , Xia Zhanran , Yang Bin , Guo Haoran , Zhou Wenjun , Zhou Chengke
Published: July 2021

Infrared thermography has been used as a key means for the identification of overheating defects in power cable accessories. At present, analysis of thermal imaging pictures relies on human visual inspections, which is time-consuming and laborious and requires engineering expertise. In order to realize intelligent, autonomous recognition of infrared images taken from electrical equipment, previous studies reported preliminary work in preprocessing of infrared images and in the extraction of key feature parameters, which were then used to train neural networks. However, the key features required manual selection, and previous reports showed no practical implementations. In this contribution, an autonomous diagnosis method, which is based on the Faster RCNN network and the Mean-Shift algorithm, is proposed. Firstly, the Faster RCNN network is trained to implement the autonomous identification and positioning of the objects to be diagnosed in the infrared images. Then, the Mean-Shift algorithm is used for image segmentation to extract the area of overheating. Next, the parameters determining the temperature of the overheating parts of cable accessories are calculated, based on which the diagnosis are then made by following the relevant cable condition assessment criteria. Case studies are carried out in the paper, and results show that the cable accessories and their overheating regions can be located and assessed at different camera angles and under various background conditions via the autonomous processing and diagnosis methods proposed in the paper.
Electricity Markets during the Liberalization: The Case of a European Union Country
Authors: Bojnec Štefan , Križaj Alan
Published: July 2021

This paper analyzes electricity markets in Slovenia during the specific period of market deregulation and price liberalization. The drivers of electricity prices and electricity consumption are investigated. The Slovenian electricity markets are analyzed in relation with the European Energy Exchange (EEX) market. Associations between electricity prices on the one hand, and primary energy prices, variation in air temperature, daily maximum electricity power, and cross-border grid prices on the other hand, are analyzed separately for industrial and household consumers. Monthly data are used in a regression analysis during the period of Slovenia’s electricity market deregulation and price liberalization. Empirical results show that electricity prices achieved in the EEX market were significantly associated with primary energy prices. In Slovenia, the prices for daily maximum electricity power were significantly associated with electricity prices achieved on the EEX market. The increases in electricity prices for households, however, cannot be explained with developments in electricity prices on the EEX market. As the period analyzed is the stage of market deregulation and price liberalization, this can have important policy implications for the countries that still have regulated and monopolized electricity markets. Opening the electricity markets is expected to increase competition and reduce pressures for electricity price increases. However, the experiences and lessons learned among the countries following market deregulation and price liberalization are mixed. For industry, electricity prices affect cost competitiveness, while for households, electricity prices, through expenses, affect their welfare. A competitive and efficient electricity market should balance between suppliers’ and consumers’ market interests. With greening the energy markets and the development of the CO2 emission trading market, it is also important to encourage use of renewable energy sources.
Model-Free Control of UCG Based on Continual Optimization of Operating Variables: An Experimental Study
Authors: Kačur Ján , Laciak Marek , Durdán Milan , Flegner Patrik
Published: July 2021

The underground coal gasification (UCG) represents an effective coal mining technology, where coal is transformed into syngas underground. Extracted syngas is cleaned and processed for energy production. Various gasification agents can be injected into an underground georeactor, e.g., air, technical oxygen, or water steam, to ensure necessary temperature and produce syngas with the highest possible calorific value. This paper presents an experimental study where dynamic optimization of operating variables maximizes syngas calorific value during gasification. Several experiments performed on an ex situ reactor show that the optimization algorithm increased syngas calorific value. Three operation variables, i.e., airflow, oxygen flow, and syngas exhaust, were continually optimized by an algorithm of gradient method. By optimizing the manipulation variables, the calorific value of the syngas was increased by 5 MJ/m3, both in gasification with air and additional oxygen. Furthermore, a higher average calorific value of 4.8–5.1 MJ/m3 was achieved using supplementary oxygen. The paper describes the proposed ex situ reactor, the mathematical background of the optimization task, and results obtained during optimal control of coal gasification.
Thermodynamic Performance Investigation of a Small-Scale Solar Compression-Assisted Multi-Ejector Indoor Air Conditioning System for Hot Climate Conditions
Authors: Eveloy Valerie , Alkendi Yusra
Published: July 2021

In year-round hot climatic conditions, conventional air conditioning systems consume significant amounts of electricity primarily generated by conventional power plants. A compression-assisted, multi-ejector space cooling system driven by low-grade solar thermal energy is investigated in terms of energy and exergy performance, using a real gas property-based ejector model for a 36 kW-scale air conditioning application, exposed to annually high outdoor temperatures (i.e., up to 42 °C), for four working fluids (R11, R141b, R245fa, R600a). Using R245fa, the multi-ejector system effectively triples the operating condenser temperature range of a single ejector system to cover the range of annual outdoor conditions, while compression boosting reduces the generator heat input requirement and improves the overall refrigeration coefficient of performance (COP) by factors of ~3–8 at medium- to high-bound condenser temperatures, relative to simple ejector cycles. The system solar fraction varies from ~0.2 to 0.9 in summer and winter, respectively, with annual average mechanical and overall COPs of 24.5 and 0.21, respectively. Exergy destruction primarily takes place in the ejector assembly, but ejector exergy efficiency improves with compression boosting. The system could reduce annual electric cooling loads by over 40% compared with a conventional local split air conditioner, with corresponding savings in electricity expenditure and GHG emissions.
Investigations of Flow and Heat Transfer Characteristics in a Channel Impingement Cooling Configuration with a Single Row of Water Jets
Authors: Shin Min-Seob , Senguttuvan Santhosh , Kim Sung-Min
Published: July 2021

The present study experimentally and numerically investigates the effect of channel height on the flow and heat transfer characteristics of a channel impingement cooling configuration for various jet Reynolds numbers in the range of 2000–8600. A single array consisting of eleven jets with 0.8 mm diameter injects water into the channel with 2 mm width at four different channel heights (3, 4, 5, and 6 mm). The average heat transfer coefficients at the target surface are measured by maintaining a temperature difference between the jet exit and the target surface in the range of 15–17 °C for each channel height. The experimental results show the average heat transfer coefficient at the target surface increases with the jet Reynolds number and decreases with the channel height. An average Nusselt number correlation is developed based on 85 experimentally measured data points with a mean absolute error of less than 4.31%. The numerical simulation accurately predicts the overall heat transfer rate within 10% error. The numerical results are analyzed to investigate the flow structure and its effect on the local heat transfer characteristics. The present study advances the primary understanding of the flow and heat transfer characteristics of the channel impingement cooling configuration with liquid jets.
MC-NILM: A Multi-Chain Disaggregation Method for NILM
Authors: Ma Hao , Jia Juncheng , Yang Xinhao , Zhu Weipeng , Zhang Hong
Published: July 2021

Non-intrusive load monitoring (NILM) is an approach that helps residents obtain detailed information about household electricity consumption and has gradually become a research focus in recent years. Most of the existing algorithms on NILM build energy disaggregation models independently for an individual appliance while neglecting the relation among them. For this situation, this article proposes a multi-chain disaggregation method for NILM (MC-NILM). MC-NILM integrates the models generated by existing algorithms and considers the relation among these models to improve the performance of energy disaggregation. Given the high time complexity of searching for the optimal MC-NILM structure, this article proposes two methods to reduce the time complexity, the k-length chain method and the graph-based chain generation method. Finally, we use the Dataport and UK-DALE datasets to evaluate the feasibility, effectiveness, and generality of the MC-NILM.
Using Machine Learning to Predict Retrofit Effects for a Commercial Building Portfolio
Authors: Xu Yujie , Loftness Vivian , Severnini Edson
Published: July 2021

Buildings account for 40% of the energy consumption and 31% of the CO2 emissions in the United States. Energy retrofits of existing buildings provide an effective means to reduce building consumption and carbon footprints. A key step in retrofit planning is to predict the effect of various potential retrofits on energy consumption. Decision-makers currently look to simulation-based tools for detailed assessments of a large range of retrofit options. However, simulations often require detailed building characteristic inputs, high expertise, and extensive computational power, presenting challenges for considering portfolios of buildings or evaluating large-scale policy proposals. Data-driven methods offer an alternative approach to retrofit analysis that could be more easily applied to portfolio-wide retrofit plans. However, current applications focus heavily on evaluating past retrofits, providing little decision support for future retrofits. This paper uses data from a portfolio of 550 federal buildings and demonstrates a data-driven approach to generalizing the heterogeneous treatment effect of past retrofits to predict future savings potential for assisting retrofit planning. The main findings include the following: (1) There is high variation in the predicted savings across retrofitted buildings, (2) GSALink, a dashboard tool and fault detection system, commissioning, and HVAC investments had the highest average savings among the six actions analyzed; and (3) by targeting high savers, there is a 110–300 billion Btu improvement potential for the portfolio in site energy savings (the equivalent of 12–32% of the portfolio-total site energy consumption).
Thermochemical Energy Storage Based on Carbonates: A Brief Overview
Authors: Ortiz Carlos
Published: July 2021

Energy storage is becoming one of the main challenges facing the massive integration of Variable Renewable Energy (VRE) in the coming years [...]
Leadership Competencies in Making Industry 4.0 Effective: The Case of Polish Heat and Power Industry
Authors: Kwiotkowska Anna , Gajdzik Bożena , Wolniak Radosław , Vveinhardt Jolita , Gębczyńska Magdalena
Published: July 2021

Leadership competencies are of crucial importance in every organisation as to a large extent they determine its success. This is especially evident in the time of Industry 4.0. Given this fact, the aim of our paper is to examine the relationship between leadership competencies and 4.0 leadership effectiveness. The heat and power plants industry was chosen as the subject of our research. The fuzzy-set qualitative comparative analysis (fs/QCA) was used as the research method. It enabled us not only to analyse particular variables, competences, and typical statistical relations between them, but we also revealed the patterns of causal relationships between particular variables. The key finding of our research was the juxtaposition of leadership competencies that are indispensable for 4.0 leaders in the CHP plants. We also found out that managerial competencies were not sufficient, and they should be supported by intellectual or socio-emotional ones.
Effects of Bent Outlet on Characteristics of a Fluidic Oscillator with and without External Flow
Authors: Kim Nam-Hun , Kim Kwang-Yong
Published: July 2021

A fluidic oscillator with a bent outlet nozzle was investigated to find the effects of the bending angle on the characteristics of the oscillator with and without external flow. Unsteady aerodynamic analyses were performed on the internal flow of the oscillator with two feedback channels and the interaction between oscillator jets and external flow on a NACA0015 airfoil. The analyses were performed using three-dimensional unsteady Reynolds-averaged Navier-Stokes equations with a shear stress transport turbulence model. The bending angle was tested in a range of 0–40°. The results suggest that the jet frequency increases with the bending angle for high mass flow rates, but at a bending angle of 40°, the oscillation of the jet disappears. The pressure drop through the oscillator increases with the bending angle for positive bending angles. The external flow generally suppresses the jet oscillation, and the effect of external flow on the frequency increases as the bending angle increases. The effect of external flow on the peak velocity ratio at the exit is dominant in the cases where the jet oscillation disappears.
Evaluating the Dynamic Energy Production Efficiency in APEC Economies
Authors: Wu Dan , Lu Ching-Cheng , Chen Xiang , Tu Pei-Chieh , Yang An-Chi , Yang Chih-Yu
Published: July 2021

This study introduces the translation adjustment model of Seiford and Zhu (2002) into dynamic DEA models to measure and analyze the dynamic energy efficiency of Asia-Pacific Economic Cooperation (APEC) economies from 2010 to 2014. The APEC economies are divided into annual energy and overall energy efficiency ratings, and improvement directions are proposed for the different variables. With the proposal of magnitude, this study discusses the changes in intertemporal conversion variables and proposes suggestions for improvement. Finally, this study analyzes the implications of energy investment and the efficiency policies of APEC economies. The results show that economies with the lowest overall energy efficiency ratings have great potential for improvement. Reducing capital stock, labor, fossil fuel consumption, and CO2 emissions while increasing GDP can increase energy efficiency ratings. However, economies do not want to reduce the state’s capital stock, and labor and population birth adjustments are difficult. Energy efficiency can only start by adjusting the consumption of fossil fuels, CO2 emissions, and GDP. The results indicate that to improve energy efficiency and reduce fossil fuel consumption and CO2 emissions, economies are expected to increase their GDP unless they enact cuts through policy and technical approaches, appropriately adjust their energy policies, and actively develop new energy technologies to effectively reduce CO2 emissions and achieve optimal energy efficiency.
Optimal Selection of Asynchronous Motor-Gearhead Couple Fed by VFD for Electrified Vehicle Propulsion
Authors: Rajput Shailendra , Farber Eliyahu , Averbukh Moshe
Published: July 2021

Widespread applications of AC motors fed by variable frequency drives in electrified vehicles have become a conventional technical solution. The flexibility of control, low cost, and high energy efficiency attract developers and engineers to apply these appliances in cars, railway trains, trams, etc. The distinctive characteristic of vehicles is a wide range of required rotation speed and torque. This circumstance means that the problems of the AC motor (nominal power, synchronous speed) and gearbox (transmission ratio) become non-trivial and necessitate optimal selection to ensure the best functionality of the entire driving system. This study proposes an approach for the optimal choice of a specific AC motor (nominal rating, synchronous speed) and the transmission ratio of the gearbox by analyzing the entire system’s losses. The optimal selection of an AC motor ensures maximum energy efficiency for a specific transportation driving cycle.