bluuebunny/crossref_metadata_2025 huggingface dataset:
Spatial Variability in a Symbiont-Diverse Marine Host and the Use of Observational Data to Assess Ecological Interactions
Authors: Cruz-Rivera Edwin , Sherif Mohy-El-Din , El-Sahhar Salma , Lombardi Thomas
Published: March 2022

Despite a rich taxonomic literature on the symbionts of ascidians, the nature of these symbioses remains poorly understood. In the Egyptian Red Sea, the solitary ascidian Phallusia nigra hosted a symbiotic amphipod and four copepod species, with densities as high as 68 mixed symbionts per host. Correlation analyses suggested no competition or antagonism between symbionts. Ascidian mass, ash-free dry mass per wet mass (AFDM/WM), and both symbiont density and diversity per host, differed significantly among three reefs from El Gouna, Egypt. However, there was no correlation between amphipod, total copepod, or total symbiont densities and host mass or AFDM/WM. A host condition index based on body to tunic mass ratio was significantly related to symbiont density overall, but this positive pattern was only strong at a single site studied. Despite assumptions based on the habit of some of the symbiont groups, our analyses detected little effect of symbionts on host health, suggesting a commensal relationship.
Deciphering the Neurosensory Olfactory Pathway and Associated Neo-Immunometabolic Vulnerabilities Implicated in COVID-Associated Mucormycosis (CAM) and COVID-19 in a Diabetes Backdrop—A Novel Perspective
Authors: Sharma Maryada , Vanam Hari Pankaj , Panda Naresh K. , Patro Sourabha K. , Arora Rhythm , Bhadada Sanjay K. , Rudramurthy Shivaprakash M. , Singh Mini P. , Koppula Purushotham Reddy
Published: March 2022

Recent Mucorales-mediated outbreaks of infections and an association of fungal infection with COVID-19 cases, as observed for COVID-19-associated mucormycosis (CAM), have posed new challenges for the management of patients in critical care units. Diabetes and hyperglycemia are integrally linked to the severity of COVID-19, and uncontrolled diabetes mellitus and COVID-19 have recently been (independently or in combination) associated with the emergence of aggressive mucormycosis due to attendant defects in innate immune recognition pathways. Therefore, the identification of novel global cellular stressors upregulated during diabetes to understand the contribution of diabetes-associated metabolic vulnerabilities can help build a Metabolic-Stress-Associated Interactome (MSAI). This interactome can help reshape the metabolic inflammation (meta-inflammation) underlying the clinical manifestations of COVID-19 to facilitate the rational design of effective therapies for COVID-19 and CAM. Accordingly, an important area of research in COVID-19 therapeutics is engaged with identifying diabetes-associated pan-cellular stressors to understand their role in immune deregulation during COVID-19 and CAM, including investigating the distant trans-neuro-vascular–endocrine axis’s role in coordinating cellular-stress recognition, transmission, compensation, and decompensation during inter-organ regulation of metabolic homeostasis in diabetes. We reviewed clinico-pathological and laboratory data to propose potential diabetes-linked novel neo-vulnerabilities that can reshape the olfactory mucosal immune landscape during airway infections such as COVID-19 and CAM.
The Significance of Systemic Immune-Inflammatory Index for Mortality Prediction in Diabetic Patients Treated with Off-Pump Coronary Artery Bypass Surgery
Authors: Urbanowicz Tomasz , Michalak Michał , Al-Imam Ahmed , Olasińska-Wiśniewska Anna , Rodzki Michał , Witkowska Anna , Haneya Assad , Buczkowski Piotr , Perek Bartłomiej , Jemielity Marek
Published: March 2022

Diabetes mellitus (DM) represents a complex carbohydrate metabolism disorder characterized by inflammatory over-reactivity. The study aimed to investigate the potential influence of postoperative inflammatory activation on mortality risk after off-pump coronary artery bypass grafting in diabetic patients. There were 510 patients treated with off-pump coronary artery bypass grafting due to stable complex coronary artery disease, including 175 patients with type-2 DM (T2DM.) The mean follow-up time was 3.7 +/− 1.5 years with a 9% all-cause mortality rate in the diabetic group. In multivariable analysis, preoperative comorbidities (stroke, peripheral artery disease, postoperative systemic inflammatory index >952, and postoperative left ventricle ejection fraction (LVEF) < 45%) were revealed as prognostic factors. The receiver operator characteristics curve analysis for postoperative calculations of systemic immune-inflammatory index (SII) appeared significant (AUC = 0.698, p = 0.008), yielding sensitivity of 68.75% and specificity of 71.07%. Systemic immune-inflammatory index (SII) can be regarded as a predictive marker for long-term prognosis in diabetic patients after off-pump coronary artery bypass grafting. The role of perioperative inflammatory activation may play a crucial role in mortality prediction.
Extraskeletal Mesenchymal Chondrosarcoma of the Uterus
Authors: Lee Yurimi , Choi Sangjoon , Kim Hyun-Soo
Published: March 2022

Mesenchymal chondrosarcoma is an uncommon malignant mesenchymal tumor with an aggressive behavior. Diagnoses of mesenchymal chondrosarcoma are established based on histomorphological, immunohistochemical, and molecular findings. Only one case of extraskeletal mesenchymal chondrosarcoma (EMC) of the uterus has been reported. This article presents the second case of primary uterine EMC, occurring in a 33-year-old woman. We describe the histological and immunophenotypical features of EMC. Our observations will help pathologists and clinicians perform accurate histological diagnoses of uterine EMC and plan appropriate treatment strategies for this rare tumor.
Can Self-Administered Rapid Antigen Tests (RATs) Help Rural India? An Evaluation of the CoviSelf Kit as a Response to the 2019–2022 COVID-19 Pandemic
Authors: Vicziany Marika , Hardikar Jaideep
Published: March 2022

This paper evaluates India’s first officially approved self-administered rapid antigen test kit against COVID-19, a device called CoviSelf. The context is rural India. Rapid antigen tests (RATs) are currently popular in situations where vaccination rates are low, where sections of the community remain unvaccinated, where the COVID-19 pandemic continues to grow and where easy or timely access to RTPCR (reverse transcription-polymerase chain reaction) testing is not an option. Given that rural residents make up 66% of the Indian population, our evaluation focuses on the question of whether this self-administered RAT could help protect villagers and contain the Indian pandemic. CoviSelf has two components: the test and IT (information technology) parts. Using discourse analysis, a qualitative methodology, we evaluate the practicality of the kit on the basis of data in its instructional leaflet, reports about India’s ‘digital divide’ and our published research on the constraints of daily life in Indian villages. This paper does not provide a scientific assessment of the effectiveness of CoviSelf in detecting infection. As social scientists, our contribution sits within the field of qualitative studies of medical and health problems. Self-administered RATs are cheap, quick and reasonably reliable. Hence, point-of-care testing at the doorsteps of villagers has much potential, but realising the benefits of innovative, diagnostic medical technologies requires a realistic understanding of the conditions in Indian villages and designing devices that work in rural situations. This paper forms part of a larger project regarding the COVID-19 pandemic in rural India. A follow-up study based on fieldwork is planned for 2022–2023.
Chemical Diagnosis of Calcium Pyrophosphate Deposition Disease of the Temporomandibular Joint: A Case Report
Authors: Terauchi Masahiko , Uo Motohiro , Fukawa Yuki , Yoshitake Hiroyuki , Tajima Rina , Ikeda Tohru , Yoda Tetsuya
Published: March 2022

Calcium pyrophosphate dihydrate (CPPD) deposition disease is a benign disorder characterized by acute gouty arthritis-like attacks and first reported by McCarty. CPPD deposition disease rarely occurs in the temporomandibular joint (TMJ), and although confirmation of positive birefringence by polarized light microscopy is important for diagnosis, it is not reliable because other crystals also show birefringence. We reported a case of CPPD deposition disease of the TMJ that was diagnosed by chemical analysis. A 47-year-old man with a chief complaint of persistent pain in the right TMJ and trismus was referred to our department in 2020. Radiographic examination revealed destruction of the head of the mandibular condyle and cranial base with a neoplastic lesion involving calcification tissue. We suspected CPPD deposition disease and performed enucleation of the white, chalky masses. Histopathologically, we confirmed crystal deposition with weak birefringence. SEM/EDS revealed that the light emitting parts of Ca and P corresponded with the bright part of the SEM image. Through X-ray diffraction, almost all peaks were confirmed to be CPPD-derived. Inductively coupled plasma atomic emission spectroscopy revealed a Ca/P ratio of nearly 1. These chemical analyses further support the histological diagnosis of CPPD deposition disease.
Four Types of Multiclass Frameworks for Pneumonia Classification and Its Validation in X-ray Scans Using Seven Types of Deep Learning Artificial Intelligence Models
Authors: Nillmani  , Jain Pankaj , Sharma Neeraj , Kalra Mannudeep , Viskovic Klaudija , Saba Luca , Suri Jasjit
Published: March 2022

Background and Motivation: The novel coronavirus causing COVID-19 is exceptionally contagious, highly mutative, decimating human health and life, as well as the global economy, by consistent evolution of new pernicious variants and outbreaks. The reverse transcriptase polymerase chain reaction currently used for diagnosis has major limitations. Furthermore, the multiclass lung classification X-ray systems having viral, bacterial, and tubercular classes—including COVID-19—are not reliable. Thus, there is a need for a robust, fast, cost-effective, and easily available diagnostic method. Method: Artificial intelligence (AI) has been shown to revolutionize all walks of life, particularly medical imaging. This study proposes a deep learning AI-based automatic multiclass detection and classification of pneumonia from chest X-ray images that are readily available and highly cost-effective. The study has designed and applied seven highly efficient pre-trained convolutional neural networks—namely, VGG16, VGG19, DenseNet201, Xception, InceptionV3, NasnetMobile, and ResNet152—for classification of up to five classes of pneumonia. Results: The database consisted of 18,603 scans with two, three, and five classes. The best results were using DenseNet201, VGG16, and VGG16, respectively having accuracies of 99.84%, 96.7%, 92.67%; sensitivity of 99.84%, 96.63%, 92.70%; specificity of 99.84, 96.63%, 92.41%; and AUC of 1.0, 0.97, 0.92 (p < 0.0001 for all), respectively. Our system outperformed existing methods by 1.2% for the five-class model. The online system takes <1 s while demonstrating reliability and stability. Conclusions: Deep learning AI is a powerful paradigm for multiclass pneumonia classification.
A Bayesian Approach to Predict Football Matches with Changed Home Advantage in Spectator-Free Matches after the COVID-19 Break
Authors: Lee Jaemin , Kim Juhuhn , Kim Hyunho , Lee Jong-Seok
Published: March 2022

Since the coronavirus disease 2019 (COVID-19) pandemic, most professional sports events have been held without spectators. It is generally believed that home teams deprived of enthusiastic support from their home fans experience reduced benefits of playing on their home fields, thus becoming less likely to win. This study attempts to confirm if this belief is true in four major European football leagues through statistical analysis. This study proposes a Bayesian hierarchical Poisson model to estimate parameters reflecting the home advantage and the change in such advantage. These parameters are used to improve the performance of machine-learning-based prediction models for football matches played after the COVID-19 break. The study describes the statistical analysis on the impact of the COVID-19 pandemic on football match results in terms of the expected score and goal difference. It also shows that estimated parameters from the proposed model reflect the changed home advantage. Finally, the study verifies that these parameters, when included as additional features, enhance the performance of various football match prediction models. The home advantage in European football matches has changed because of the behind-closed-doors policy implemented due to the COVID-19 pandemic. Using parameters reflecting the pandemic’s impact, it is possible to predict more precise results of spectator-free matches after the COVID-19 break.
Construction of a Family of Maximally Entangled Bases in ℂd ⊗ ℂd′
Authors: Wang Chenghong , Wang Kun , Zheng Zhu-Jun
Published: March 2022

In this paper, we present a new method for the construction of maximally entangled states in Cd⊗Cd′ when d′≥2d. A systematic way of constructing a set of maximally entangled bases (MEBs) in Cd⊗Cd′ was established. Both cases when d′ is divisible by d and not divisible by d are discussed. We give two examples of maximally entangled bases in C2⊗C4, which are mutually unbiased bases. Finally, we found a new example of an unextendible maximally entangled basis (UMEB) in C2⊗C5.
Information Field Theory and Artificial Intelligence
Authors: Enßlin Torsten
Published: March 2022

Information field theory (IFT), the information theory for fields, is a mathematical framework for signal reconstruction and non-parametric inverse problems. Artificial intelligence (AI) and machine learning (ML) aim at generating intelligent systems, including such for perception, cognition, and learning. This overlaps with IFT, which is designed to address perception, reasoning, and inference tasks. Here, the relation between concepts and tools in IFT and those in AI and ML research are discussed. In the context of IFT, fields denote physical quantities that change continuously as a function of space (and time) and information theory refers to Bayesian probabilistic logic equipped with the associated entropic information measures. Reconstructing a signal with IFT is a computational problem similar to training a generative neural network (GNN) in ML. In this paper, the process of inference in IFT is reformulated in terms of GNN training. In contrast to classical neural networks, IFT based GNNs can operate without pre-training thanks to incorporating expert knowledge into their architecture. Furthermore, the cross-fertilization of variational inference methods used in IFT and ML are discussed. These discussions suggest that IFT is well suited to address many problems in AI and ML research and application.
Discovering Entrepreneurship Competencies through Problem-Based Learning in Higher Education Students
Authors: Sousa Maria José , Costa Joana Martinho
Published: March 2022

The increase in student engagement in the learning process has driven educators to use more dynamic pedagogical methodologies. Several studies have shown evidence of increased interest in learning when real-world problems are integrated into the learning environment. This paper presents the competencies developed by higher education students through application of the problem-based learning (PBL) methodology in higher education courses. The research begins with the identification of a set of competencies developed by higher education students in other studies developed and reported in the last five years and includes them in a survey to analyze the level of development of those competencies when problem-based learning is applied in university courses. To identify the competencies developed by applying the problem-based learning methodology, the research employed a document analysis and a survey of the students that participated in the experimental application. The research questions “What are the competencies developed by students in problem-based learning?” and “Are the competencies identified by the students sufficiently learned in universities?” guided the study. The competencies found by the students were identified through a questionnaire given as an online survey to 76 students. The key outcome of the research is the identification in the bachelor courses of the competencies perceived as essential by students participating in the application of PBL in terms of their advancement.
Development of STEM Instructional Resources for Teaching Optics to Teachers-in-Training: Influence on Learning and Teacher Self-Efficacy
Authors: Martínez-Borreguero Guadalupe , Naranjo-Correa Francisco Luis , Mateos-Núñez Milagros
Published: March 2022

Studies related to teacher training in primary education indicate a lack of knowledge, low levels of teaching self-efficacy, and negative emotions towards the teaching of physics. The main objective of this research was to compare the influence of two teaching methodologies on the learning and teaching self-efficacy of teachers-in-training on optics content related to light and color. The research design was quasi-experimental with control and experimental groups, a pre-test, and two post-tests. A non-probabilistic sample of 173 trainee primary school teachers was used. The control group used an academic–expositional teaching methodology, and the experimental group used a practical methodology based on the use of STEM teaching tools. Measuring instruments were designed and applied before and after the interventions to measure the evolution of cognitive and competence variables of the participating sample, depending on the methodology applied, both in the short and long term. The results reveal statistically significant improvements between the control group and the experimental group, both in the knowledge level variable and in the teaching self-efficacy variable.
An Efficient Detour Computation Scheme for Electric Vehicles to Support Smart Cities’ Electrification
Authors: Mansfield Cole , Hodgkiss Jack , Djahel Soufiene , Nag Avishek
Published: March 2022

Achieving carbon-neutral transportation is the ultimate goal of the ongoing joint efforts of governments, policy-makers, and the transportation research community. Electrification of smart cities is a very important step towards the above objective; therefore, accelerating the adoption and widening the use of Electric Vehicles (EVs) are required. However, to achieve the full potential of EVs, ground-breaking detour computation and charging station selection schemes are needed. To this end, this paper developed a new scheme that finds the most suitable detour/route for an EV whenever an unexpected event occurs on the road. This scheme is based on A* and uses an original, Simple-Additive-Weighting (SAW)-based, charging station selection method. The performance evaluation carried out using the open-source traffic simulation platform SUMO under a grid map, as well as a real road network map highlighted that our scheme ensured more than 99% of EVs will reach their destination within a reasonable time even if a battery recharge is needed. This is a significant improvement compared to the baseline scheme that uses the A* only.
A Simple Commutation Method and a Cost-Effective Clamping Circuit for Three-to-Five-Phase Indirect-Matrix Converters
Authors: Tawfiq Kotb B. , Ibrahim Mohamed N. , Sergeant Peter
Published: March 2022

This article presents and analyzes a three-to-five-phase indirect matrix converter (IMC) structure for directly supplying a five-phase static R–L load from a three-phase supply. The IMC topology offers a lower number of switches, a simple commutation procedure and a cost-effective clamping circuit in comparison to the direct matrix converter (DMC). A simple clamping circuit with one ultrafast diode and one small capacitor is proposed to protect the switches of the IMC from overvoltage. The issues of powering up the IMC with the simple clamping circuit is discussed in detail. The instructions for the safe start-up of the IMC with the proposed clamping circuit is introduced based on the simulated and the measured analyses. Moreover, a carrier-based pulse-width-modulation (CBPWM) method is also presented in order to control the switches of the IMC. The presented CBPWM method creates PWM pulses for both the inverter and the rectifier legs by using only one symmetric and triangular carrier signal. Finally, experimental and simulation testing with a five-phase R–L load demonstrate the viability and the efficiency of the introduced CBPWM algorithm for the suggested IMC.
Theory of Peer-to-Peer Locking of High-Power Gyrotron Oscillators Coupled with Delay
Authors: Adilova Asel B. , Ryskin Nikita M.
Published: March 2022

Peer-to-peer locking is a promising way to combine the power of high-power microwave oscillators. The peer-to-peer locking of gyrotrons is especially important because arrays of coupled gyrotrons are of special interest for fusion and certain other applications. However, in case of coupled microwave oscillators, the effect of delay in coupling is very significant and should be taken into account. In this article, we present the model of two delay-coupled gyrotrons. We develop an approximate theory of phase locking based on the generalized Adler’s equation, which allows for the treatment of in-phase and anti-phase locking modes. We also present a more rigorous bifurcation analysis of phase locking by using XPPAUT software under the limitation of small delay time. The structure of the phase-locking domains on the frequency-mismatch–coupling-strength plane of parameters is examined. Finally, we verify the results by numerical simulations in the case of finite delay time. The simulations reveal various regimes, including peer-to-peer locking, the suppression of one gyrotron by another, as well as the excitation of one gyrotron by another.
Fast Design Space Exploration and Multi-Objective Optimization of Wide-Band Noise-Canceling LNAs
Authors: Elmeligy Karim , Omran Hesham
Published: March 2022

Design optimization of RF low-noise amplifiers (LNAs) remains a time-consuming and complex process. Iterations are needed to adjust impedance matching, gain, and noise figure (NF) simultaneously. The process can involve more iterations to adjust the non-linear behavior of the circuit which can be represented by the input-referred third-order intercept (IIP3). In this work, we present a variation-aware automated design and optimization flow for a wide-band noise-canceling LNA. We include the circuit non-linearity in the optimization flow without using a simulator in the loop. By describing the transistors using precomputed lookup tables (LUTs), a design database that contains 200,000 design points is generated in 3 s only without non-linearity computation and 10 s when non-linearity is taken into account. Using a gm/ID-based correct-by-construction design procedure, the generated design points automatically satisfy proper biasing, input matching, and gain matching requirements. The generated database enables the designer to visualize the design space and explore the design trade-offs. Moreover, multi-objective optimization across corners for a given set of specifications is applied to find the Pareto-optimal fronts of the design figures-of-merit. We demonstrate the presented flow using two design examples in a 65 nm process and the results are verified using Cadence Spectre.
Transient Modulation for the Step-Load-Change Process in a Dual-Bridge Series Resonant Converter
Authors: Xu Hui , Zhou Shengzhi , Li Xiaodong , Chen Hao , Hu Song
Published: March 2022

A phase-shifted dual-bridge series resonant DC-DC converter (DBSRC) is a competitive candidate for applications of an energy storage system. At the request of a step-load-change command such as the start-up and power-level change, the converter may suffer from large-amplitude transient oscillations due to improper transient modulation. Furthermore, the DC bias current and overshoot current/voltage in the resonant tank and transformer caused by oscillations may result in transformer saturation and poor dynamic performance. To solve these problems, two fast transient modulation (FTM) methods are proposed in this paper. First, based on the steady-state analysis of the converter with phase-shift control, the current and voltage trajectory of the resonant capacitor can be obtained. Then, the detailed principles of two FTM methods are explained for achieving a smooth transition. Through the adjustment of the durations of the adjacent switching intervals temporarily, the transient trajectory can be predicted and is expected to match the destination trajectory within one switching period. Consequently, the proposed FTM methods enable the converter to move from one steady state to another instantly and the step-load-change transition can be an overshoot-free procedure. Finally, both simulation and experimental tests prove that the two modulation methods can effectively eliminate DC bias current and overshoot current/voltage in the DBSRC transient process and obtain a fast transient response.
A 130-to-220-GHz Frequency Quadrupler with 80 dB Dynamic Range for 6G Communication in 0.13-μm SiGe Process
Authors: Wu Tianxiang , Cao Zhiyuan , Xu Zhuofan , Dai Liuyao , Mao Wei , He Jin , Ma Shunli , Yu Hao
Published: March 2022

This paper presents a broadband frequency quadrupler (FQ) implemented with a standard 130-nm SiGe BiCMOS process. Two broadband push-push frequency doublers (×2) operate at an input frequency of 32.5–55 GHz and 65–110 GHz, respectively. To properly drive the two doublers with enough input power and bandwidth, two transformer coupled power amplifiers (PAs) have been adopted. The former power amplifier is based on a neutralized capacitor structure and the latter is based on a transformer topology. A nonlinear device model and a systematic methodology to generate maximum power at second harmonic are proposed. By manipulating the device nonlinearity and optimizing the magnetically and capacitively coupled resonator (MCCR) matching networks, optimum conditions for harmonic power generation are provided. The measurement results show that the proposed quadrupler provides a 90-GHz bandwidth with an 80-dB dynamic range and a high energy efficiency η of 3.7% at 210 GHz.
Modeling and Performance Analysis in UAV-Assisted Cellular Networks with Clustered Edge Users
Authors: Yao Yuanyuan , Wu Yunga , Zhu Zhengyu , Qin Xiaoqi , Yue Xinwei
Published: March 2022

A UAV-assisted cellular network can provide ubiquitous links to everything and it is considered to be one of the key technologies for 6G wireless networks. In this paper, we consider an uplink wireless network with a macrobase station (MBS) and cellular users. However, the coverage equality of edge users cannot be guaranteed in scenarios where data service is dense. Specifically, a novel topology of the UAV-assisted wireless network is considered. UAVs are deployed upon the cell edge to serve edge users with poor communication quality. To avoid larger interference caused by users and UAVs in the overlapping area, the locations of these UAVs are modeled as a homogeneous Poisson point process (HPPP) under the Poisson cluster distance constraint (PCDC). In addition, we assume that edge users cluster around each UAV and model their locations as Poisson cluster processes (PCPs). Initially, the Laplace transforms of intra-cluster interference, inter-cluster interference, and other interference are derived. Subsequently, coverage probability and area spectrum efficiency are derived for UAVs and MBS using tools from stochastic geometry. Moreover, the energy efficiency of the system is obtained. Simulation results are examined to validate the accuracy of theoretical analysis and provide insights into the effects of the system parameters as well as useful guidelines for practical system design.
A Technique of Hydrocarbon Potential Evaluation in Low Resistivity Gas-Saturated Mudstone Horizons in Miocene Deposits, South Poland
Authors: Lis-Śledziona Anita , Kaczmarczyk-Kuszpit Weronika
Published: March 2022

The petrophysical properties of Miocene mudstones and gas bearing-heteroliths were the main scope of the work performed in one of the multihorizon gas fields in the Polish Carpathian Foredeep. Ten boreholes were the subject of petrophysical interpretation. The analyzed interval covered seven gas-bearing Miocene horizons belonging to Sarmatian and Badenian deposits. The water saturation in shaly sand and mudstone intervals was calculated using the Montaron connectivity theory approach and was compared with Simandoux water saturation. Additionally, the Kohonen neural network was used for qualitative interpretation of four PSUs (petrophysically similar units), which represent the deposits of comparable petrophysical parameters. This approach allowed us to identify the sediment group with the highest probability of hydrocarbon saturation. Then, the spatial distribution of PSUs and reservoir parameters was carried out in Petrel. The resolution of the model was selected to reflect the variability of log-derived parameters. The reconstruction of the spatial distribution of shale volume, porosity, and permeability was performed with standard parametric modeling procedures using the Gaussian random function simulation stochastic algorithm, while PSU distribution and hydrocarbon saturation (SH) required a separate approach. The distribution into PSU groups was carried out by facies classification. Predefined ranges of clay volume, effective porosity, and permeability were used as discriminators to achieve spatial distribution of the PSU groups. The spatial distribution of hydrocarbon saturation was performed by creating the meta-attribute of this parameter and then reducing the derived pseudo-saturation model to physical values. Results included the creation of maps of hydrocarbon saturation that show the preferable areas with the highest hydrocarbon saturation for each gas horizon.
A Strategy for Grid-Connected PV-Battery System of Mongolian Ger
Authors: Erdenebat Baigali , Urasaki Naomitsu , Byambaa Sergelen
Published: March 2022

One of the main sources of energy utilized in the Mongolian Gers is coal and wood mainly for the purpose of heating and other domestic use. This heavily increases the air pollution levels. A viable solution for handling the air pollution is switching to renewable energy sources (RES). Grid-connected photovoltaic (PV) systems with battery back-up provide a reliable solution to the problem addressing the energy demand and pollution control. This paper proposes a grid-connected PV–second-life battery system and its operation strategy. A single Ger, which consists of a PV array, battery energy storage system (BESS), and an electric heater (EH), is modeled and tested. The trading coefficient and selling unit price are calculated based on variables such as loan, selling price, and purchasing price. The advantages of the proposed strategy are its simple design and easy implementation. The economic result shows that there is a significant reduction in the electricity bill during winters, while the bill can be reduced to zero during summers. Furthermore, the annual profit from the proposed system is USD 15. The CO2 emissions are reduced from 32 to 7 tCO2.
Hourly Simulation of an Earth-to-Air Heat Exchanger in a Low-Energy Residential Building
Authors: Michalak Piotr
Published: March 2022

The earth-to-air heat exchanger (EAHE) is a well-founded and verified solution used in modern buildings both for heating and cooling purposes around the world. However, there is a lack of studies on operation of such devices cooperating with ventilation systems of buildings in hourly time step. In this study, the 5R1C thermal network model of a building from EN ISO 13790 was coupled with the EAHE model from EN 16798-5-1 to calculate hourly outlet air temperature. To improve the effectiveness of the considered solution, an additional algorithm was developed to choose between the EAHE outlet and ambient air as the source of ventilation air. Simulations were conducted in a spreadsheet for a low-energy single-family building. Ground temperature was compared with measurements taken in the considered location. The application of the EAHE with the proposed bypass resulted in a decrease in annual energy use for space heating and cooling from 14.82 GJ and 1.67 GJ to 12.74 GJ and 0.93 GJ, i.e., by 14% and 44%, respectively. Peak hourly heating and cooling thermal power decreased from 2.73 kW and 3.06 kW to 2.21 kW and 2.34 kW. Introduction of a bypass and switching between the EAHE and ambient air as the source of ventilation for the building resulted in annual energy savings of 123 kWh.
On the Crystal Chemistry of Photochromic Yttrium Oxyhydride
Authors: Sørby Magnus H. , Martinsen Fredrik , Karazhanov Smagul Zh. , Hauback Bjørn C. , Marstein Erik S.
Published: March 2022

Yttrium oxyhydride exhibits photochromic properties at ambient temperature and pressures. Although oxygen plays an important role in determining the optoelectronic properties of the material, the question remains open regarding the site that it occupies in the crystal structure. In this paper, we address the issue by synchrotron radiation and neutron powder diffraction measurements. We report that the oxide anions occupy tetrahedral sites together with hydride anions in the face-centered cubic structure.
Study on Combustion Characteristics of Cable Based on Cone Calorimeter
Authors: Zhang Hao , Yao Jinxia , Zhu Hui , Wang Xiaolong
Published: March 2022

Cross-linked polyethylene (XLPE) carries a high fire risk. In this paper, a cone calorimeter is used to carry out radiation ignition experiments, and the heat release rate (HRR), mass loss rate (MLR) and other combustion parameters of XLPE cables under three kinds of radiation intensity are measured. By comparing the ignition time and HRR of samples under different conditions, the following conclusions are drawn: (1) The ignition time of XLPE cables decreases significantly with the increase in external thermal radiation intensity. The critical ignition heat flux (CHF) is about 16.24 kW/m2. (2) The HRR curve of XLPE is consistent with the characteristics of hot, thick material. The HRR rises rapidly to the first peak after ignition and then rapidly decreases. Then, it slowly rises to the second peak. Finally, it slowly decays until the combustion stops. (3) The first peak values of HRR of XLPE under different radiation intensities are almost the same. The time for the second peak of HRR is shorter, and the value is larger with the increase in external thermal radiation intensity. (4) The cable ignition model is established, which can simulate the cable ignition time well under different radiant heat flow conditions. (5) Based on the mathematical model, the ignition time trend with the thickness of sheath layer and conductive core layer as variables is deduced.
Investigating Energy Use in a City District in Nordic Climate Using Energy Signature
Authors: Eriksson Martin , Akander Jan , Moshfegh Bahram
Published: March 2022

This paper focuses on multi-family buildings in a Swedish city district, erected between 1965 and 1973, which are now in need of renovation. For the two types of multi-family buildings in the district, tower buildings and low-rise buildings, dynamic energy use is predicted by using an energy signature method. The energy signature is then used to calculate the primary energy use number of the building stock, according to calculations methods dictated by Swedish building regulations. These regulations are also used to assess which multi-family buildings are in need of renovation, based on the buildings’ primary energy use. For buildings that need energy renovations, it is simulated so that the energy use of each multi-family building complies with these same building regulations. The proposed methodology for simulating energy renovation also determines new energy signature parameters, related to building heat loss coefficient, balance temperature and domestic hot water usage. The effects of simulated renovation are displayed in a duration diagram, revealing how a large-scale renovation affects the district’s heat load in different annual periods, which affects the local district heating system. Sensitivity analysis is also performed before and after simulated energy renovation.
Improved Design and Thermo-Mechanical Verification of Deflection Magnet Beam Collimator of EAST-NBI System
Authors: Tao Ling , Xie Yuanlai , Hu Chundong , Yi Wei , Liang Lizhen
Published: March 2022

The deflection magnet (DM) is the most important component of the Neutral Beam Injection (NBI) system of Experimental Advanced Superconducting Tokamak (EAST), which can magnetically deflect the un-neutralized charged particles after the neutralized process of the beam is extracted from the ion source, and then form a neutral beam injected into the tokamak. Under the operating conditions of the NBI system, by using the thermocouple monitoring system in the experiment, it can be found that the currently operating DM beam collimator has a quite high temperature rise. It is necessary to redesign the DM beam collimator to improve its heat transfer performance. The parallel arrangement of multiple rows of tubes is proposed as the basic method for the redesign of the beam collimator of DM, the thermal-fluid-structure analysis model of this redesign model is established and its temperature field, pressure field and stress field are analyzed. Taking the surface temperature of the beam collimator, the overall dimension after the total tube combination and the pressure drop of the whole structure of collimator as the optimization objectives, and setting the fluid velocity, the tube’s inner diameter and the number of tube rows as the design variables, the optimized design scheme of the beam collimator structure is obtained. From the results of simulation, the new structure can better meet the operation requirements of DM, and its maximum temperature rise is well controlled, which is expected to meet the long pulse operation requirements of the NBI system. The proposed simulation and design optimization method can provide a certain reference for the design and optimization of other high-heat-flux structures in complex large-scale neutral beam systems in the future.
Numerical Study of Constant Pressure Systems with Variable Speed Electric Pumps
Authors: Andrade-Cedeno Rogger José , Pérez-Rodríguez Jesús Alberto , Amaya-Jaramillo Carlos David , Rodríguez-Borges Ciaddy Gina , Llosas-Albuerne Yolanda Eugenia , Barros-Enríquez José David
Published: March 2022

This work focuses on the modeling and simulation of constant pressure systems based on variable speed pumps, with the aim of studying and evaluating their performance from a multidisciplinary approach. Using the physical models of the Simscape library, from MATLAB/Simulink R2019b, two study cases are assembled consisting of: piping system, a hydropneumatic tank, centrifugal pumps with an induction motor, variable speed drives, and a control system. Case one is comprised of one pump at a fixed speed and another at variable speed, and case two with both pumps at variable speed. For the parameterization of the models, data from manufacturers and process requirements are used. The different stages of the control system are integrated and configured; these are constant V/f control, slip compensation, space vector modulation (SVM,) and pressure controller. The dynamic response of the system, power saving, transient current at startup, and harmonic distortion are evaluated. The results showed that both cases kept the pressure constant in the face of variable flow demand and smoothed out the current during startup. Case two saved more energy (between 28 and 49%) but generated more harmonic distortion. In addition, both cases have better performance compared with traditional fixed-speed technologies.
Frequency Control in Power Systems with Large Share of Wind Energy
Authors: Lu Liang , Saborío-Romano Oscar , Cutululis Nicolaos A.
Published: March 2022

Fast frequency response from wind turbines and plants has been playing an increasingly important role in our modern power system, which has a large share of wind energy integration. Frequency control from grid-following wind turbines and plants has been extensively investigated in the literature, whereas grid-forming frequency control methods have aroused people’s attention in recent years, with relatively little comparison available. This paper provides such a comparison, illustrating the differences between the two methods of providing frequency support in a power system. The comparison shows the superiority of grid-forming frequency control methods over grid-following ones, and gives a glance into power system frequency stability in the transition from grid-following to grid-forming frequency support supplied by wind power. The results are elaborated in a benchmark WSCC 9-bus system, which features detailed electromagnetic transient modeling of the components from a single converter, a wind turbine, and a wind plant to the whole power system.
Input Small-Signal Characteristics of Selected DC–DC Switching Converters
Authors: Janke Włodzimierz , Bączek Maciej , Kraśniewski Jarosław , Walczak Marcin
Published: March 2022

The main goal of this study was to derive small-signal models of the input characteristics of buck, boost, and flyback converters working in continuous conduction mode (CCM) and discontinuous conduction mode (DCM). The models presented in the paper were derived using the separation of variables approach and included the parasitic resistances of all converter components. The paper features a discussion about the limitations of the model accuracy. The presented characteristics were obtained by calculation and verified by measurements. The input characteristics of converters are essential in the design of converters used in Power Factor Correction systems as well as in maximum power point tracking systems (MPPT).
Analyzing the Societal Cost of Electric Roads Compared to Batteries and Oil for All Forms of Road Transport
Authors: Coban Hasan Huseyin , Rehman Aysha , Mohamed Abdullah
Published: March 2022

This article is designed to demonstrate that electric roads are an affordable way to electrify all forms of road transport—not only cars, but also buses and trucks. Electric roads represent a way to power electric vehicles without relying solely on batteries. The idea is that when an electric vehicle reaches an electric road, it stops using power from the battery and instead uses power directly from the road itself. The primary challenge for electric vehicles is still the perception of a compromised quality of life in owning an electric vehicle due to a limited range compared with petrol and diesel cars, today. This paper introduces a new technology, currently experiencing rapid development, that can not only overcome range anxiety but make electric vehicles better, in terms of range, than petrol and diesel cars today. Furthermore, not only can this research help to arrange this, but it can also help, for the first time, to cost-effectively electrify heavy-duty transport, such as trucks and buses, which would be a huge breakthrough in terms of sustainability, as it is very important to start supplying electricity to heavy-duty vehicles. The case study provides a very hypothetical example of a trip with and without an electric road, covering a total of 26,011 km of highways and main roads. The results indicate that building electric roads is cheaper than many other alternatives. If a large battery is replaced with a smaller battery for each new vehicle sold, after 3 years, enough savings will be made to electrify all highways and main roads in Turkey. This paper can help transport operators and policymakers develop strategies to accelerate the adoption of electric vehicles by appropriately implementing electric road infrastructure.
Comparison of Environmental Impact Assessment Methods in the Assembly and Operation of Photovoltaic Power Plants: A Systematic Review in the Castilla—La Mancha Region
Authors: Zarzavilla Marichell , Quintero Andrea , Abellán Manuela Andrés , Serrano Francisco López , Austin Miguel Chen , Tejedor-Flores Nathalia
Published: March 2022

Solar energy is in high demand due to its environmental benefits and economic potential; however, concerns remain about the total impact it holds. In 2020, for Spain, Castilla-La Mancha was the second autonomous community with the highest photovoltaic energy production. Thus, a systematic review on 15 large-scale PV solar energy projects was carried out to assess the industry impacts, through environmental impact assessment (EIA), within the Autonomous Community of Castilla—La Mancha. An estimation of these impacts from a pre-operational approach is presented, based on primary energy needs and emissions discarded during its life cycle due to the manufacture, operation, and recycling of the photovoltaic modules. Based on both the life cycle assessment (LCA) and EIA, the approaches were compared with the results obtained. The obtained results suggest that determining the actual impacts of power plants in this region could provide justified information for the public administration and technicians in the measures for the installation and operation of PV plants and the future benefits of renewable solar technologies. Furthermore, the results indicate the possibility to recognize the relationship between the size of the plant and a high generation capacity, with a shorter time to pay for emissions from the manufacture and recycling of panels, suggesting that it is around 1.66–2.08 years for the Castilla-La Mancha region.
Study on Surface Subsidence Characteristics Based on Three-Dimensional Test Device for Simulating Rock Strata and Surface Movement
Authors: Ma Xingyin , Fu Zhiyong , Li Yurong , Zhang Pengfei , Zhao Yongqiang , Ma Guoping
Published: March 2022

The main functions of a three-dimensional test device for simulating rock formations and surface movement affected by underground coal mining were described in detail, and a series of similar related tests were carried out. The device consisted of an outer frame, a pressurization unit, a pulling unit, and a coal seam simulation portion. Using this test device, supported by monitoring methods such as the three-dimensional laser scanner method, a model test study on the surface subsidence characteristics caused by coal seam mining was carried out. Combined with the field measurements, the transfer law of surface subsidence caused by coal seam mining was revealed, and the whole surface subsidence response process was analyzed. The experimental results show that the subsidence caused by mining disturbances below the coal seam accounts for 79.3% of the total subsidence, which is the dominant factor of the total surface subsidence. After long-term surface observations, surface subsidence can be divided into four stages after coal mining, and the settlement value of the obvious settlement stage accounts for more than 60% of the total settlement value. The above test results fully reflect the feasibility and practicality of the three-dimensional test device to simulate rock strata and surface movement and provide a new experimental research tool that can be used to further study the surface subsidence characteristics and control caused by coal mining.
A Review about Flux-Weakening Operating Limits and Control Techniques for Synchronous Motor Drives
Authors: Bianchi Nicola , Carlet Paolo Gherardo , Cinti Luca , Ortombina Ludovico
Published: March 2022

This paper deals with motor design aspects and control strategies for the flux-weakening (FW) operation of synchronous motors. The theory of FW is described by taking into account different control schemes. The advantages and drawbacks of each one are discussed, as well. Moreover, some motor design considerations for achieving an effective FW operation are illustrated for permanent magnet (PM), wound rotor (WR) and reluctance (REL) synchronous machines, using the per unit approach. The distinguishing characteristic of this review provides two-fold attention on both machine design and control strategies obtained by several collaborations with industrial and commercial companies.