bluuebunny/crossref_metadata_2025 huggingface dataset:
Magnetic and Thermoelectric Detection of Sigma Phase in 2507 Duplex Stainless Steel
Authors: Mészáros István , Bögre Bálint , Szabó Péter János
Published: April 2022

Duplex stainless steel has significantly broadened the range of applications of stainless steel. They have a dual-phase microstructure containing ferrite and austenite at approximately a 50–50% phase ratio. Their corrosion resistance is much better compared to the traditional austenitic stainless steel, especially in surroundings containing chloride ion. Moreover, the large stress yield of duplex steels offers significant advantages in structural applications. The ferrite phase in some duplex stainless steels is metastable due to its composition. Consequently, the ferrite can decompose to a secondary austenite and sigma phase due to heat input. The sigma phase is a hard and brittle intermetallic compound phase that significantly deteriorates the mechanical and corrosion-resistant properties of duplex stainless steel. The embrittlement can cause a safety risk in industrial applications. This paper is a preliminary study to investigate what physical properties can be used to obtain information on sigma-phase-induced embrittlement. In this work, the effect of plastic deformation and heat treatment was studied in the appearance of the sigma phase in 2507 duplex stainless steel. Magnetic saturation polarization and thermoelectric power measurements were used to monitor the microstructural changes due to cold rolling and heat treatment. It was found that the magnetic saturation polarization and thermoelectric power measurements can be effective tools for monitoring the sigma-phase formation in duplex stainless steels due to heat input. Their application helps to prevent the embrittlement problems caused by the sigma-phase formation in duplex stainless steel structures.
ZnO Films from Thermal Oxidation of Zn Films: Effect of the Thickness of the Precursor Films on the Structural, Morphological, and Optical Properties of the Products
Authors: Sánchez-Dena Oswaldo , Hernández-López Susana , Camacho-López Marco Antonio , Acuña-Ávila Pedro Estanislao , Reyes-Esqueda Jorge Alejandro , Vigueras-Santiago Enrique
Published: April 2022

Zinc oxide (ZnO) films with different structural, morphological, and optical properties were obtained by (fixed) thermal oxidation of deposited metallic zinc (Zn) films. The main characteristics of the oxidized films are discussed in terms of the Zn film thickness. On-axis preferential crystallographic oriented growth of ZnO can be tuned based on the control of the thickness of the deposited Zn: c-axis (a-axis) for the thinnest (thicker) Zn film. The thicker ZnO film is rather a-textured, whereas the grains hosted by the ZnO films corresponding to the Zn films of intermediate thicknesses are more randomly oriented. For Zn films of ever-increasing thickness, a tendency towards the crystallization of larger ZnO nanocrystals holds, combined with a continuous increment on the surface roughness. In contrast, the fundamental bandgap of the resultant oxide-based films decreases with thickness. The roughness of the ZnO films is not directly measured. It is qualitatively described by the analysis of Zn-film micrographs obtained by Scanning Electron Microscopy and by the demonstration of strong optical scattering interactions present in the thicker ZnO films by their random lasing activity.
Improving Mini-LED Pattern Quality by Using Distributed Bragg Reflector and Digital Twin Technology
Authors: Chang Shu-Hsiu , Huang Che-Hsuan , Langpoklakpam Chatherine , James Singh Konthoujam , Lin Chien-Chung , Kuo Hao-Chung
Published: April 2022

Fine-pitch backlight technology is rapidly evolving along with display technology, and chips are increasingly designed for direct integration with modules. This study used a distributed Bragg reflector (DBR) for mini light-emitting diode (mini-LED) backlights with high dynamic contrast and developed a digital twin design by using a light-emitting diode (LED) and a distributed Bragg reflector (DBR).
A Qualitative Needs Analysis of Skin Cancer Care from the Perspectives of Patients, Physicians, and Health Insurance Representatives—A Case Study from Eastern Saxony, Germany
Authors: Mathiebe Josephine , Reinhardt Lydia , Bergmann Maike , Lindauer Marina , Herrmann Alina , Strasser Cristin , Meier Friedegund , Schmitt Jochen
Published: April 2022

Skin cancer is one of the most common cancers worldwide and the number of patients is steadily increasing. In skin cancer care, greater interdisciplinary cooperation is required for prevention, early detection, and new complex systemic therapies. However, the implementation of innovative medical care is a major challenge, especially for rural regions with an older than average, multimorbid population, with limited mobility, that are long distances from medical facilities. Solutions are necessary to ensure comprehensive oncological care in rural regions. The aim of this study was to identify indicators to establish a regional care network for integrated skin cancer care. To capture the perspectives of different stakeholder groups, we conducted two focus groups with twenty skin cancer patients and their relatives, a workshop with eight physicians, and three semi-structured interviews with health insurance company representatives. Qualitative data were recorded, transcribed, and analyzed following Mayring’s content analysis methods. We generated ten categories based on the reported optimization potentials; five categories were assigned to all three stakeholder groups: Prevention and early diagnosis, accessibility of physicians/clinics, physicians’ resources, care provider’s responsibilities, and information exchange. The results indicate the need for stronger integration of care in the region. They provide the basis for regional networking as, for example, the conception of treatment pathways or telemedicine with the aim to improve a comprehensive skin cancer care. Our study should raise awareness and postulate as a demand that all patients receive guideline-based therapy, regardless of where they live.
A Strategy to Provide a Present and Future Scenario of Mexican Biodiversity of Tardigrada
Authors: García-Román Jazmín , Dueñas-Cedillo Alba , Cervantes-Espinoza Montserrat , Flores-Martínez José Juan , Vargas-Mendoza Carlos Fabián , Ruiz Enrico Alejandro , Armendáriz-Toledano Francisco
Published: April 2022

Although the number of known tardigrade taxa in Mexico has increased significantly in the last ten years, the knowledge of their diversity faces challenges, as more than half of the Mexican territory has no records of this phylum. Thus, we developed a strategy to provide a present and future scenario for understanding the Mexican biodiversity of Tardigrada, described the distribution patterns of the current recorded species, calculated the estimated richness, and the estimated taxonomic effort needed to complete the national inventory. We obtained 474 records of 105 taxa, belonging to 42 genera and 75 species, distributed in 12 of the 14 biogeographical provinces of Mexico. We found that 54.72% of the species are present in more than three world regions and 3.79% of species that have been recorded only in Mexican provinces. Distribution patterns could be recognized for 11 species, two of which have a Nearctic distribution, seven are Neotropical and two are distributed in both regions. The Mexican biogeographical provinces with the greatest diversity of tardigrades, both at specific and generic level, were the Transmexican Volcanic Belt (TVBP) and the Sierras Madre Oriental (SMOrP) and Sierra Madre Occidental (SMOcP), which have been previously identified as particularly species-rich regions. Diversity estimation methods predict that more than 290 species of tardigrades could be found in Mexico.
Diversity 2022 Best Paper Award
Authors:   Diversity Editorial Office
Published: April 2022

Diversity is instituting the Best Paper Awards to recognize the outstanding papers published in the journal [...]
Understanding Extra-Pair Mating Behaviour: A Case Study of Socially Monogamous European Pied Flycatcher (Ficedula hypoleuca) in Western Siberia
Authors: Grinkov Vladimir G. , Bauer Andreas , Sternberg Helmut , Wink Michael
Published: April 2022

Extra-pair copulation (EPC) occurred in most socially monogamous bird species. The mechanisms leading to the frequent occurrence of extra-pair offspring (EPO, EPY) in socially monogamous couples, as well as the ‘function’ of EPC, are the subjects of strong debates and raise many unanswered questions. We studied the relationship between extra-pair paternity (EPP) and the different characteristics of males and females in the European pied flycatcher in Western Siberia (Russia). The analysis was based on the genotyping of 232 males, 250 females, 1485 nestlings (250 nests). The European pied flycatchers were predominantly socially and genetically monogamous, but about 20% of birds could be involved in EPP. Loss of paternity tended to be more frequent in one-year-old males. EPCs could be multiple: one individual may have up to three extra-pair partners. The EPP rate was independent of the breeding time. The extra-pair mates of an individual were mainly its near neighbours. The EPC status of an individual was unrelated to most of its morpho-physiological traits. The occurrence of EPP was almost twice as high in females nesting in good quality territories. The fitness of within-pair offspring, EPO, paternal half-sibs of EPO and maternal half-sibs of EPO did not differ statistically significantly. Assuming very low heritability of extra-pair mating, we argued that EPCs could be incidental side effects (by-product) of selection. We believe that the evolution and maintenance of extra-pair mating are the episelective processes in the case of the European pied flycatcher.
Pelvic Pain in Reproductive Age: US Findings
Authors: Di Serafino Marco , Iacobellis Francesca , Schillirò Maria Laura , Verde Francesco , Grimaldi Dario , Dell’Aversano Orabona Giuseppina , Caruso Martina , Sabatino Vittorio , Rinaldo Chiara , Cantisani Vito , Vallone Gianfranco , Romano Luigia
Published: April 2022

Pelvic pain in reproductive age often represents a diagnostic challenge due to the variety of potential causes characterized by overlapping clinical symptoms, including gynecological and other disorders (e.g., entero-colic or urological). It is also necessary to determine if there is a possibility of pregnancy to rule out any related complications, such as ectopic pregnancy. Although ultrasound (US), computed tomography (CT), and magnetic resonance imaging (MRI) are strongly integrated, the choice of which is the ideal diagnostic tool should be guided both by clinical suspicion (gynecological vs. non-gynecological cause) and by the risk ratio–benefit (ionizing radiation and instrumental costs), too. The didactic objective proposed by this review consists in the diagnosis of the cause and differential of pelvic pain in reproductive age by describing and critically analyzing the US diagnostic clues of the most frequent adnexal, uterine, and vascular causes.
Decreased Expression of Cell Adhesion Molecule 4 in Gastric Adenocarcinoma and Its Prognostic Implications
Authors: Bang Seongsik , Jee Seungyun , Son Hwangkyu , Cha Hyebin , Sim Jongmin , Kim Yeseul , Park Hosub , Myung Jaekyung , Shin Su-Jin , Kim Hyunsung , Paik Seungsam
Published: April 2022

Cell adhesion molecule 4 (CADM4) is a novel tumor suppressor candidate. The prognostic implications of CADM4 in gastric cancer have not been conclusively elucidated. Therefore, we evaluated the clinicopathological significance and prognostic value of CADM4 expression in a large series of patients with gastric adenocarcinoma. Immunohistochemical staining for CADM4 was performed on 534 gastric adenocarcinomas. We evaluated the associations between CADM4 expression and the clinicopathological and molecular characteristics of the adenocarcinomas. The prognostic effect of CADM4 expression was evaluated by survival analyses. Low CADM4 expression was significantly associated with young age (p = 0.046), aggressive histological type (p < 0.001), high pT category (p < 0.001), nodal metastasis (p < 0.001), high stage (p = 0.002), lymphovascular invasion (p = 0.001), and perineural invasion (p = 0.001). Low CADM4 expression was more frequently observed in tumors without human epidermal growth factor receptor 2 (HER2) amplification (p = 0.002). Low CADM4 expression was associated with worse overall survival (p = 0.007) and recurrence-free survival (p = 0.005) in the survival analyses. Low CADM4 expression was associated with aggressive clinicopathological features and poor clinical outcomes. CADM4 can act as a tumor suppressor in gastric adenocarcinoma and can be considered a prognostic biomarker.
Deep Learning Based Detection Tool for Impacted Mandibular Third Molar Teeth
Authors: Celik Mahmut Emin
Published: April 2022

Third molar impacted teeth are a common issue with all ages, possibly causing tooth decay, root resorption, and pain. This study was aimed at developing a computer-assisted detection system based on deep convolutional neural networks for the detection of third molar impacted teeth using different architectures and to evaluate the potential usefulness and accuracy of the proposed solutions on panoramic radiographs. A total of 440 panoramic radiographs from 300 patients were randomly divided. As a two-stage technique, Faster RCNN with ResNet50, AlexNet, and VGG16 as a backbone and one-stage technique YOLOv3 were used. The Faster-RCNN, as a detector, yielded a mAP@0.5 rate of 0.91 with ResNet50 backbone while VGG16 and AlexNet showed slightly lower performances: 0.87 and 0.86, respectively. The other detector, YOLO v3, provided the highest detection efficacy with a mAP@0.5 of 0.96. Recall and precision were 0.93 and 0.88, respectively, which supported its high performance. Considering the findings from different architectures, it was seen that the proposed one-stage detector YOLOv3 had excellent performance for impacted mandibular third molar tooth detection on panoramic radiographs. Promising results showed that diagnostic tools based on state-ofthe-art deep learning models were reliable and robust for clinical decision-making.
Personalized Diagnosis in Differentiated Thyroid Cancers by Molecular and Functional Imaging Biomarkers: Present and Future
Authors: Teodoriu Laura , Leustean Letitia , Ungureanu Maria-Christina , Bilha Stefana , Grierosu Irena , Matei Mioara , Preda Cristina , Stefanescu Cipriana
Published: April 2022

Personalized diagnosis can save unnecessary thyroid surgeries, in cases of indeterminate thyroid nodules, when clinicians tend to aggressively treat all these patients. Personalized diagnosis benefits from a combination of imagery and molecular biomarkers, as well as artificial intelligence algorithms, which are used more and more in our timeline. Functional imaging diagnosis such as SPECT, PET, or fused images (SPECT/CT, PET/CT, PET/MRI), is exploited at maximum in thyroid nodules, with a long history in the past and a bright future with many suitable radiotracers that could properly contribute to diagnosing malignancy in thyroid nodules. In this way, patients will be spared surgery complications, and apparently more expensive diagnostic workouts will financially compensate each patient and also the healthcare system. In this review we will summarize essential available diagnostic tools for malignant and benignant thyroid nodules, beginning with functional imaging, molecular analysis, and combinations of these two and other future strategies, including AI or NIS targeted gene therapy for thyroid carcinoma diagnosis and treatment as well.
Autonomous Unmanned Heterogeneous Vehicles for Persistent Monitoring
Authors: Lappas Vaios , Shin Hyo-Sang , Tsourdos Antonios , Lindgren David , Bertrand Sylvain , Marzat Julien , Piet-Lahanier Hélène , Daramouskas Yiannis , Kostopoulos Vasilis
Published: April 2022

Swarms of unmanned vehicles (air and ground) can increase the efficiency and effectiveness of military and law enforcement operations by enhancing situational awareness and allowing the persistent monitoring of multiple hostile targets. The key focus in the development of the enabling technologies for swarm systems is the minimisation of uncertainties in situational awareness information for surveillance operations supported by ‘system of systems’ composed of static and mobile heterogeneous sensors. The identified critical enabling techniques and technologies for adaptive, informative and reconfigurable operations of unmanned swarm systems are robust static sensor network design, mobile sensor tasking (including re-allocation), sensor fusion and information fusion, including behaviour monitoring. The work presented in this paper describes one of the first attempts to integrate all swarm-related technologies into a prototype, demonstrating the benefits of swarms of heterogeneous vehicles for defence applications used for the persistent monitoring of high-value assets, such as military installations and camps. The key enabling swarm system technologies are analysed here, and novel algorithms are presented that can be implemented in available COTS-based unmanned vehicles. The algorithms have been designed and optimised to require small computational power, be flexible, be reconfigurable and be implemented in a large range of commercially available unmanned vehicles (air and ground).
An Effective Synchronization Approach to Stability Analysis for Chaotic Generalized Lotka–Volterra Biological Models Using Active and Parameter Identification Methods
Authors: Chaudhary Harindri , Khan Ayub , Nigar Uzma , Kaushik Santosh , Sajid Mohammad
Published: April 2022

In this manuscript, we systematically investigate projective difference synchronization between identical generalized Lotka–Volterra biological models of integer order using active control and parameter identification methods. We employ Lyapunov stability theory (LST) to construct the desired controllers, which ensures the global asymptotical convergence of a trajectory following synchronization errors. In addition, simulations were conducted in a MATLAB environment to illustrate the accuracy and efficiency of the proposed techniques. Exceptionally, both experimental and theoretical results are in excellent agreement. Comparative analysis between the considered strategy and previously published research findings is presented. Lastly, we describe an application of our considered combination difference synchronization in secure communication through numerical simulations.
Preference-Driven Classification Measure
Authors: Kozak Jan , Probierz Barbara , Kania Krzysztof , Juszczuk Przemysław
Published: April 2022

Classification is one of the main problems of machine learning, and assessing the quality of classification is one of the most topical tasks, all the more difficult as it depends on many factors. Many different measures have been proposed to assess the quality of the classification, often depending on the application of a specific classifier. However, in most cases, these measures are focused on binary classification, and for the problem of many decision classes, they are significantly simplified. Due to the increasing scope of classification applications, there is a growing need to select a classifier appropriate to the situation, including more complex data sets with multiple decision classes. This paper aims to propose a new measure of classifier quality assessment (called the preference-driven measure, abbreviated p-d), regardless of the number of classes, with the possibility of establishing the relative importance of each class. Furthermore, we propose a solution in which the classifier’s assessment can be adapted to the analyzed problem using a vector of preferences. To visualize the operation of the proposed measure, we present it first on an example involving two decision classes and then test its operation on real, multi-class data sets. Additionally, in this case, we demonstrate how to adjust the assessment to the user’s preferences. The results obtained allow us to confirm that the use of a preference-driven measure indicates that other classifiers are better to use according to preferences, particularly as opposed to the classical measures of classification quality assessment.
Empirical Analysis of the Impact of Education on Economic Growth
Authors: Ziberi Besime Fekri , Rexha Donat , Ibraimi Xhemazie , Avdiaj Besnik
Published: April 2022

Education is a crucial factor for sustainable economic growth. Therefore, public expenditures on education are of great interest to both researchers and policy makers. The channels through which education affects economic growth differ according to the level of development of the country. This study aims to measure the impact of public expenditure on education for economic growth in North Macedonia. The data used are secondary data derived from the World Bank Indicators for the period 1917–2020. The econometric model employed in this study is an Instrumental Variable Two-Stage Least Square. The dependent variable in the model is Gross Domestic Product and the independent variables in the model are public expenditures on education, labor force participation rate, gross capital formation, unemployment, industry, wages, employment, information, and communication technology, and the instrumented variable is tertiary enrolment. This study suggests that a one-point increase in public expenditures on education will positively affect economic growth in the North Macedonia. The study also shows that a one-point increase in unemployment will increase economic growth and a one-point decrease in employment will increase economic growth in North Macedonia. These two results, which contradict the theoretical and empirical approaches, prove the mismatch between the supply and demand of real occupations in the labor market in North Macedonia.
The “Coherent Data Set”: Combining Patient Data and Imaging in a Comprehensive, Synthetic Health Record
Authors: Walonoski Jason , Hall Dylan , Bates Karen M. , Farris M. Heath , Dagher Joseph , Downs Matthew E. , Sivek Ryan T. , Wellner Ben , Gregorowicz Andrew , Hadley Marc , Campion Francis X. , Levine Lauren , Wacome Kevin , Emmer Geoff , Kemmer Aaron , Malik Maha , Hughes Jonah , Granger Eldesia , Russell Sybil
Published: April 2022

The “Coherent Data Set” is a novel synthetic data set that leverages structured data from Synthea™ to create a longitudinal, “coherent” patient-level electronic health record (EHR). Comprised of synthetic patients, the Coherent Data Set is publicly available, reproducible using Synthea™, and free of the privacy risks that arise from using real patient data. The Coherent Data Set provides complex and representative health records that can be leveraged by health IT professionals without the risks associated with de-identified patient data. It includes familial genomes that were created through a simulation of the genetic reproduction process; magnetic resonance imaging (MRI) DICOM files created with a voxel-based computational model; clinical notes in the style of traditional subjective, objective, assessment, and plan notes; and physiological data that leverage existing System Biology Markup Language (SBML) models to capture non-linear changes in patient health metrics. HL7 Fast Healthcare Interoperability Resources (FHIR®) links the data together. The models can generate clinically logical health data, but ensuring clinical validity remains a challenge without comparable data to substantiate results. We believe this data set is the first of its kind and a novel contribution to practical health interoperability efforts.
Crescent Microstrip Antenna for LTE-U and 5G Systems
Authors: Przesmycki Rafał , Bugaj Marek
Published: April 2022

The field of wireless cellular network technology has seen a significant development in recent years, allowing the emergence of many new applications in addition to the traditional mobile phone calls. We are currently implementing the 5G system, which is replacing the previous cellular technologies on the market. Parallel to the development of cellular technologies, wireless local networks based on the IEEE 802.11× standards are rapidly spreading. The desire to use the advantages of both mobile telephony and wireless local networks has led to the idea of integrating the currently used communication systems in one device and requires a well-designed antenna, which should be given a lot of attention when designing the radio system. This article presents the proposed model of a two-band microstrip antenna for which the main assumption is its operating frequencies in the LTE-U (LTE-Unlicensed) band and one of the 5G system bands. The antenna dimensions and parameters have been calculated, simulated, and optimized using CST Microwave Studio software. The developed antenna has a compact structure with dimensions of (60 × 40 × 1.57) mm. The dielectric material RT Duroid 5880 with a dielectric constant εr = 2.2 and thickness h = 1.57 mm was used as a substrate for the antenna construction. The article presents an analysis of the results of simulation and measurements of selected electrical parameters and radiation characteristics of the proposed antenna. The antenna described in the article, working in 5G systems and LTE-U systems, is characterized by two operating bands with center frequencies equal to 3.52 GHz and 5.37 GHz, a low reflection coefficient (for resonances −31.54 dB and −23.16 dB), a gain value of 4.45 dBi, a wide frequency band of 3.0 GHz (68.18%), and a high energy efficiency in the range of 80–96.68%.
Investigating Transfer Learning in Graph Neural Networks
Authors: Kooverjee Nishai , James Steven , van Zyl Terence
Published: April 2022

Graph neural networks (GNNs) build on the success of deep learning models by extending them for use in graph spaces. Transfer learning has proven extremely successful for traditional deep learning problems, resulting in faster training and improved performance. Despite the increasing interest in GNNs and their use cases, there is little research on their transferability. This research demonstrates that transfer learning is effective with GNNs, and describes how source tasks and the choice of GNN impact the ability to learn generalisable knowledge. We perform experiments using real-world and synthetic data within the contexts of node classification and graph classification. To this end, we also provide a general methodology for transfer learning experimentation and present a novel algorithm for generating synthetic graph classification tasks. We compare the performance of GCN, GraphSAGE and GIN across both synthetic and real-world datasets. Our results demonstrate empirically that GNNs with inductive operations yield statistically significantly improved transfer. Further, we show that similarity in community structure between source and target tasks support statistically significant improvements in transfer over and above the use of only the node attributes.
Reinforcement-Learning-Based Decision and Control for Autonomous Vehicle at Two-Way Single-Lane Unsignalized Intersection
Authors: Liu Yonggang , Liu Gang , Wu Yitao , He Wen , Zhang Yuanjian , Chen Zheng
Published: April 2022

Intersections have attracted wide attention owing to their complexity and high rate of traffic accidents. In the process of developing L3-and-above autonomous-driving techniques, it is necessary to solve problems in autonomous driving decisions and control at intersections. In this article, a decision-and-control method based on reinforcement learning and speed prediction is proposed to manage the conjunction of straight and turning vehicles at two-way single-lane unsignalized intersections. The key position of collision avoidance in the process of confluence is determined by establishing a road-geometry model, and on this basis, the expected speed of the straight vehicle that ensures passing safety is calculated. Then, a reinforcement-learning algorithm is employed to solve the decision-control problem of the straight vehicle, and the expected speed is optimized to direct the agent to learn and converge to the planned decision. Simulations were conducted to verify the performance of the proposed method, and the results show that the proposed method can generate proper decisions for the straight vehicle to pass the intersection while guaranteeing preferable safety and traffic efficiency.
Using Overlapped Resonators in Wireless Power Transfer for Uniform Electromagnetic Field and Removing Blank Spots in Free Moving Applications
Authors: Pahlavan Saeideh , Shooshtari Mostafa , Maleki Mohammadreza , Jafarabadi Ashtiani Shahin
Published: April 2022

We propose an induction link based on overlapping arrays to eliminate blank spots on the electromagnetic field for moving object applications. We use two arrays of four aligned coils that have a 50% overlap between the two plates. This mechanism compensates for the internal coil power drop at positions in the boundaries between two adjacent external coils. We showed that if these plates are excited, a uniform electromagnetic field is created in the movement direction of the moving object. This uniform electromagnetic field distribution will result in a constant receiving power at all points in the path of the moving internal coil with the same power consumption of one coil excitation. Power delivery to the moving object tolerance reaches 10% at most, while, in non-overlapped scenarios, it is approximately 50%. In addition, according to the theoretical calculations, printed circuit coils (PCB) for the array are designed for maximum efficiency. We found that the change in distance and dimensions of the receiver coil has a linear effect on power and efficiency. Moreover, a Specific Absorption Rate (SAR) simulation was performed for biocompatibility. In this paper, we investigate and record a 68% electrical power efficiency for the fabricated system. The array consists of eight transmitters coils of the same size and shape and a receiver coil at a distance of 4 cm. Furthermore, the fabricated coil has shown improved efficiency compared to similar studies in the literature and introduces a promising structure for bio-test applications.
Photovoltaic Performance of Dye-Sensitized Solar Cells with a Solid-State Redox Mediator Based on an Ionic Liquid and Hole-Transporting Triphenylamine Compound
Authors: Kong Minseon , Oh Da Hyeon , Choi Baekseo , Han Yoon Soo
Published: April 2022

An ionic liquid, 1-methyl-3-propylimidazolium iodide (MPII), was solidified with an organic hole-transporting material, 4,4′,4″-tris[(3-methylphenyl)phenylamino]triphenylamine (m-MTDATA), and the resulting solid-state redox mediator (RM) (m-MTDATA-solidified MPII) was employed in solar devices to realize solid-state dye-sensitized solar cells (sDSSCs). Solar devices with only MPII or m-MTDATA as an RM showed almost 0 mA/cm2 of short-circuit current (Jsc) and thus 0% power conversion efficiency (PCE). However, an sDSSC with the m-MTDATA-solidified MPII exhibited 4.61 mA/cm2 of Jsc and 1.80% PCE. It was found that the increased Jsc and PCE were due to the formation of I3−, which resulted from a reaction between the iodie (I−) of MPII and m-MTDATA cation. Further enhancement in both Jsc (9.43 mA/cm2) and PCE (4.20%) was observed in an sDSSC with 4-tert butylpyridine (TBP) as well as with m-MTDATA-solidified MPII. We attributed the significant increase (about 230%) in PCE to the lowered diffusion resistance of I−/I3− ions in the solid-state RM composed of the m-MTDATA-solidified MPII and TBP, arising from TBP’s role as a plasticizer.
Experimental Analysis of Ultra-High-Frequency Signal Propagation Paths in Power Transformers
Authors: Beura Chandra Prakash , Beltle Michael , Wenger Philipp , Tenbohlen Stefan
Published: April 2022

Ultra-high-frequency (UHF) partial discharge (PD) monitoring is gaining popularity because of its advantages over electrical methods for onsite/online applications. One such advantage is the possibility of three-dimensional PD source localization. However, it is necessary to understand the signal propagation and attenuation characteristics in transformers to improve localization. Since transformers are available in a wide range of ratings and geometric sizes, it is necessary to ascertain the similarities and differences in UHF signal characteristics across the different designs. Therefore, in this contribution, the signal attenuation and propagation characteristics of two 300 MVA transformers are analyzed and compared based on experiments. The two transformers have the same rating but different internal structures. It should be noted that the oil is drained out of the transformers for these tests. Additionally, a simulation model of one of the transformers is built and validated based on the experimental results. Subsequently, a simulation model is used to analyze the electromagnetic wave propagation inside the tank. Analysis of the experimental data shows that the distance-dependent signal attenuation characteristics are similar in the case of both transformers and can be well represented by hyperbolic equations, thus indicating that transformers with the same rating have similar attenuation characteristics even if they have different internal structures.
Short-Term Combined Forecasting Method of Park Load Based on CEEMD-MLR-LSSVR-SBO
Authors: Hu Bo , Xu Jian , Xing Zuoxia , Zhang Pengfei , Cui Jia , Liu Jinglu
Published: April 2022

To improve the accuracy of park load forecasting, a combined forecasting method for short-term park load is proposed based on complementary ensemble empirical mode decomposition (CEEMD), sample entropy, the satin bower bird optimization algorithm (SBO), and the least squares support vector regression (LSSVR) model. Firstly, aiming at the random fluctuation of park load series, the modes with different characteristic scales are divided into low-frequency and high-frequency according to the calculation of sample entropy, which is based on the decomposition of historical park load data modes by CEEMD. The low-frequency is forecast by multiple linear regression (MLR), and the high-frequency component is the training input of the LSSVR forecasting model. Secondly, the SBO algorithm is adopted to optimize the regularization parameters and the kernel function width of LSSVR. Then, the park load forecasting model of each sequence component is built. The forecast output of each sequence component is superimposed to get the final park load forecast value. Finally, a case study of a park in Liaoning Province has been performed with the results proving that the proposed method significantly outperforms the state-of-art in reducing the difficulty and complexity of forecasting effectively, also eliminating the defect of large reconstruction error greatly through the decomposed original sequence by the ensemble empirical model.
Influence of Hblock Fine-Grained Material on Selected Parameters of Cement Slurry
Authors: Kremieniewski Marcin
Published: April 2022

Fine-grained materials are used to seal the microstructure and improve the mechanical parameters of the formed cement sheath. They are used in cement slurries designed to seal casing columns at great depths and in geothermal boreholes to improve thermal conductivity. Such additions shorten the setting time and the transition time from the value of the initial time of the setting to the final of the setting. This allows the shortening of the time needed to bind the slurry and move on to further work. Additionally, it helps to eliminate the possibility of gaseous medium intrusion into the structure of the setting cement slurry. The goal of the work is to determine the influence of the Hblock fine-grained material on selected parameters of the cement slurry. Hblock is used in the research ranging from 1% to 20% (bwoc (bwoc—by weight of cement)), and the two types of cement most commonly used in the petroleum sector. Then the technological parameters of fresh and hardened cement slurries were tested. Research on rheological parameters, determined rheological models and flow curves are performed. On the basis of the obtained test results, the influence of the additive on the technological parameters of the cement slurry is discussed. The research results allow for further work and then the application of the fine-grained material in the petroleum sector.
A Novel Approach to Predict Transformer Temperature Rise under Harmonic Load Current Conditions
Authors: Thango Bonginkosi A. , Bokoro Pitshou N.
Published: April 2022

In South Africa, distribution transformers (DTs) facilitating solar photovoltaic applications represent the highest percentage of total ownership cost investment for independent power producers (IPPs). One of the most indispensable variables that regulate DTs’ operational life span is the hotspot temperature. The prevailing analytical approaches designated to guesstimate the transformer thermal necessities were fathered in accordance with the conservative foundation that an electrical transformer is prone to uniform mean daily and monthly peak loads. In order to appropriately puzzle out the transformer thermal necessities, the formation of a more detailed thermal model that operates with real-time contorted cyclic loading, ambient air temperature, and the intrinsic characteristics of the transformer in-service losses is required. In the current work, various regression models are proposed for the modification of the top-oil formula and the hotspot temperature formula in the IEEE loading guide standard to replicate the real harmonic load currents (HLCs) and the fluctuating ambient air temperature (AT) on an hourly and daily basis. The proposed thermal model is examined in various transformers case studies, in which the computed outcomes produce an error margin of no more than 3% throughout all test cases when compared to the measured data.
Numerical Simultaneous Determination of Non-Uniform Soot Temperature and Volume Fraction from Visible Flame Images
Authors: Yan Weijie , Hu Zhichao , Li Kuangyu , Xing Xiaoyu , Gong Huifang , Yu Bo , Zhou Huaichun
Published: April 2022

This paper presents a method to invert the two-dimensional distribution of a temperature and volume concentration of soot particles from color images. By using numerical simulation, the temperature field and particle volume-concentration field of a non-uniform soot flame are simultaneously reconstructed using the wide-response spectrum of a color CCD camera without adding monochromatic filters. The influence of number of cameras, error of camera position angle, measurement noise and different reconstruction algorithms on measurement accuracy are analyzed. The numerical-simulation results demonstrate that camera-position angle errors play a crucial role in the reconstruction accuracy. In addition, increasing the number of cameras can improve the reconstruction result accuracy. Compared with the least squares algorithm, the Tikhonov-regularization algorithm has a stronger anti-noise ability and can resist 39 dB of noise. The conclusions obtained in this paper are helpful to guide following experimental studies.
A Comprehensive Analysis of the Risks Associated with the Determination of Biofuels’ Calorific Value by Bomb Calorimetry
Authors: Shehab Moaaz , Stratulat Camelia , Ozcan Kemal , Boztepe Aylin , Isleyen Alper , Zondervan Edwin , Moshammer Kai
Published: April 2022

Two of the most commonly used solid biomass sources for fuel are wood chips and wood pellets. The calorific value and the moisture content of those biofuels determine the efficiency of the CHP and the biorefinery plants. Therefore, with the increased shift towards a biobased economy, the biomass cost and its physical properties must be precisely determined. Most of the current standards are lacking and provide neither enough details about the issues caused by the biomass heterogeneity nor with the variation in experimental practice. Phenomena such as data scattering, poor repeatability and wide uncertainty, are mostly observed during the measurements of the calorific value and the moisture content. To overcome such issues, an interlaboratory comparison between three national metrology institutes using bomb calorimetry has taken place. The comparison helped to identify the root causes behind the poor reproducibility of the wood samples. Factors such as the equilibrium moisture content of the biomass, the pellet mass, the applied pressure to form the pellet, the handling techniques and the determination errors are highlighted and analyzed. The final results paved the way to provide an enhanced detailed experimental practice where the repeatability and reproducibility have been strongly improved. Moreover, the detailed uncertainty sources and calculations are presented. It has been found that by fulfilling the recommended approach the measurement repeatability improved by up to 50–80%, while the final uncertainty improved by 10–30%. This enhancement leads to a maximum relative expanded uncertainty of around ±1% (coverage factor of k = 2 and a confidence level of 95%).
Defining and Specifying Design Considerations for Distribution Transformers in Large-Scale Solar Photovoltaic Plants
Authors: Thango Bonginkosi A. , Bokoro Pitshou N.
Published: April 2022

In the new era of the renewable energy market in South Africa, there is a knowledge gap in the technical standards relating to distribution transformers, which are exclusively intended to serve in large-scale solar photovoltaic (PV) applications. The problem arises from the reality that these transformers are compelled to facilitate an environment with a potentially high risk of an unacceptable level of harmonics and distortion. What manufacturers currently need is a comprehensive transformer specification for DT transformers in PV applications, as the standards currently in use for regular transformers have so far proven to be inadequate. The latter triggers the need for this work to contribute to the advancement of this knowledge gap by mapping a comparative analysis of defining and specifying the design considerations for solar PV transformers. Initially, the computation of the various transformer losses at multifaceted active-part structures under normal conditions by employing the proposed finite element analysis (FEA) is presented. Then, two design case studies are described and the harmonic load current content to which the transformer will be susceptible during operation is specified and used for the analysis. Lastly, the design losses computed using the proposed FEA are substantiated using practical measurements.
Direct Participation of Dynamic Virtual Power Plants in Secondary Frequency Control
Authors: Adabi M. Ebrahim , Marinescu Bogdan
Published: April 2022

This paper proposes a novel control strategy in which Renewable Energy Sources (RES) considered in a new Dynamic Virtual Power Plant (DVPP) concept directly participate to Secondary Frequency Control (SFC). This allows full participation of these generators to SFC, i.e., in the same manner as classic synchronous generators by fulfilling identical specifications from both control and contractual points of view. An internal real-time redispatch has been proposed to account in DVPP in order to determine the amount of active power injection by each RES unit for the provision of frequency support at the secondary level. The whole control scheme is designed to take into account both rapid and slow dynamics of modern power systems which contain both classic synchronous generators and rapid power electronics for renewable energy sources in which DVPP is supposed to be inserted. The performance of secondary frequency control strategy has been validated through simulation studies on a two-area benchmark with mixed wind power plants and classic synchronous generators. This work is part of the H2020 POSYTYF project
Increasing Magnetic Blow-Out Force by Using Ferromagnetic Side Plates inside MCB
Authors: Szulborski Michał , Łapczyński Sebastian , Kolimas Łukasz
Published: April 2022

The paper presents a modern method of computer modeling, concerning the low-voltage extinguishing chambers employed in modular apparatuses. The focus was put on presenting the phenomenon of increasing the blow-out, through the use of ferromagnetic plates, dividing the electric arc inside the electrical apparatus. The use of ferromagnetic material for the production of extinguishing chambers results in the distortion of the magnetic field generated by the electric arc. This creates a magnetic force that draws the arc towards the plate area of the extinguishing chamber. The authors presented a modern tool for the analysis of physical phenomena inside the extinguishing chamber. The presented material makes it possible to examine the influence of changes in the geometry and materials of the mentioned components on the process of switching off the current. The applied approach can be used to analyze physical phenomena in devices, not only for alternating current, but also for direct current. Moreover, the model is scaled to the various parameters of these devices.
Efficient Plasma Technology for the Production of Green Hydrogen from Ethanol and Water
Authors: Ulejczyk Bogdan , Nogal Łukasz , Młotek Michał , Krawczyk Krzysztof
Published: April 2022

This study concerns the production of hydrogen from a mixture of ethanol and water. The process was conducted in plasma generated by a spark discharge. The substrates were introduced in the liquid phase into the reactor. The gaseous products formed in the spark reactor were hydrogen, carbon monoxide, carbon dioxide, methane, acetylene, and ethylene. Coke was also produced. The energy efficiency of hydrogen production was 27 mol(H2)/kWh, and it was 36% of the theoretical energy efficiency. The high value of the energy efficiency of hydrogen production was obtained with relatively high ethanol conversion (63%). In the spark discharge, it was possible to conduct the process under conditions in which the ethanol conversion reached 95%. However, this entailed higher energy consumption and reduced the energy efficiency of hydrogen production to 8.8 mol(H2)/kWh. Hydrogen production increased with increasing discharge power and feed stream. However, the hydrogen concentration was very high under all tested conditions and ranged from 57.5 to 61.5%. This means that the spark reactor is a device that can feed fuel cells, the power load of which can fluctuate.
Field Test of Mini Photoionization Detector-Based Sensors—Monitoring of Volatile Organic Pollutants in Ambient Air
Authors: Bílek Jiří , Maršolek Petr , Bílek Ondřej , Buček Pavel
Published: April 2022

The determination of the concentrations of the organic compounds in ambient air using reference methods is a time-consuming process. The samples must be collected on a specific sorbent material and analyzed. In the best-case scenario, the analysis may be performed on site by portable chromatography techniques; otherwise, transport and laboratory analysis is necessary. Continuous sensory measurement is advantageous, especially concerning speed, resolution, price and ease of use. On the other hand, questions are raised, especially on the subject of the quality of data obtained by sensory measurements. The authors tested several types of volatile organic compound (VOC) sensors. The chosen type was deployed in a 25-unit sensor network for further testing by parallel measurements with the reference technique within the CLAIRO project.