bluuebunny/crossref_metadata_2025 huggingface dataset:
SIRT1 Deficiency, Specifically in Fibroblasts, Decreases Apoptosis Resistance and Is Associated with Resolution of Lung-Fibrosis
Authors: Bulvik Raanan , Breuer Raphael , Dvir-Ginzberg Mona , Reich Eli , Berkman Neville , Wallach-Dayan Shulamit B.
Published: July 2020

In contrast to normal regenerating tissue, resistance to Fas- and FasL-positive T cell-induced apoptosis were detected in myofibroblasts from fibrotic-lungs of humans and mice following bleomycin (BLM) exposure. In this study we show, decreased FLIP expression in lung-tissues with resolution of BLM-induced fibrosis and in isolated-lung fibroblasts, with decreased resistance to apoptosis. Using a FLIP-expression vector or a shFLIP-RNA, we further confirmed the critical need for FLIP to regain/lose susceptibility of fibrotic-lung myofibroblast to Fas-induced apoptosis. Our study further show that FLIP is regulated by SIRT1 (Sirtuin 1) deacetylase. Chimeric mice, with SIRT1-deficiency in deacetylase domain (H355Y-Sirt1y/y), specifically in mesenchymal cells, were not only protected from BLM-induced lung fibrosis but, as assessed following Ku70 immunoprecipitation, had also decreased Ku70-deacetylation, decreasedKu70/FLIP complex, and decreased FLIP levels in their lung myofibroblasts. In addition, myofibroblasts isolated from lungs of BLM-treated miR34a-knockout mice, exposed to a miR34a mimic, which we found here to downregulate SIRT1 in the luciferase assay, had a decreased Ku70-deacetylation indicating decrease in SIRT1 activity. Thus, SIRT1 may mediate, miR34a-regulated, persistent FLIP levels by deacetylation of Ku70 in lung myofibroblasts, promoting resistance to cell-death and lung fibrosis.
Physiopathology of the Permeability Transition Pore: Molecular Mechanisms in Human Pathology
Authors: Bonora Massimo , Patergnani Simone , Ramaccini Daniela , Morciano Giampaolo , Pedriali Gaia , Kahsay Asrat , Bouhamida Esmaa , Giorgi Carlotta , Wieckowski Mariusz , Pinton Paolo
Published: July 2020

Mitochondrial permeability transition (MPT) is the sudden loss in the permeability of the inner mitochondrial membrane (IMM) to low-molecular-weight solutes. Due to osmotic forces, MPT is paralleled by a massive influx of water into the mitochondrial matrix, eventually leading to the structural collapse of the organelle. Thus, MPT can initiate outer-mitochondrial-membrane permeabilization (MOMP), promoting the activation of the apoptotic caspase cascade and caspase-independent cell-death mechanisms. The induction of MPT is mostly dependent on mitochondrial reactive oxygen species (ROS) and Ca2+, but is also dependent on the metabolic stage of the affected cell and signaling events. Therefore, since its discovery in the late 1970s, the role of MPT in human pathology has been heavily investigated. Here, we summarize the most significant findings corroborating a role for MPT in the etiology of a spectrum of human diseases, including diseases characterized by acute or chronic loss of adult cells and those characterized by neoplastic initiation.
RETRACTED: Optimized Ellagic Acid–Ca Pectinate Floating Beads for Gastroprotection against Indomethacin-Induced Gastric Injury in Rats
Authors: Alhakamy Nabil , Badr-Eldin Shaimaa , Ahmed Osama , Halwani Abdulrahman , Aldawsari Hibah , El-Moselhy Mohamed , Anter Aliaa , Sharkawi Sara , Sultan Muhammad , Madkhali Osama , Bakhrebah Muhammed , Alomary Mohammad , Abdulaal Wesam , A. Fahmy Usama
Published: July 2020

A peptic ulcer is an alimentary tract injury that leads to a mucosal defect reaching the submucosa. This work aimed to optimize and maximize ellagic acid (EA) loading in Ca pectinate floating beads to maximize the release for 24 h. Three factors were selected: Ca pectinate concentration (X1, 1–3 w/v %), EA concentration (X2, 1–3 w/v %) and the dropping time (X3, 10–30 min). The factorial design proposed eight formulations. The optimized EA–Ca pectinate formulation was evaluated for the gastric ulcer index and the oxidative stress parameter determination of gastric mucosa. The results indicated that the optimum EA–Ca pectinate formula significantly improved the gastric ulcer index in comparison with raw EA. The protective effect of the optimized EA–Ca pectinate formula was further indicated by the histopathological features of the stomach. The results of the study indicate that an EA formulation in the form of Ca pectinate beads would be effective for protection against gastric ulcers because of Nonsteroidal anti-inflammatory drugs (NSAID) administration.
Hemocyanins from Helix and Rapana Snails Exhibit in Vitro Antitumor Effects in Human Colorectal Adenocarcinoma
Authors: Georgieva Ani , Todorova Katerina , Iliev Ivan , Dilcheva Valeriya , Vladov Ivelin , Petkova Svetlozara , Toshkova Reneta , Velkova Lyudmila , Dolashki Aleksandar , Dolashka Pavlina
Published: July 2020

Hemocyanins are oxygen-transporting glycoproteins in the hemolymph of arthropods and mollusks that attract scientific interest with their diverse biological activities and potential applications in pharmacy and medicine. The aim of the present study was to assess the in vitro antitumor activity of hemocyanins isolated from marine snail Rapana venosa (RvH) and garden snails Helix lucorum (HlH) and Helix aspersa (HaH), as well the mucus of H. aspersa snails, in the HT-29 human colorectal carcinoma cell line. The effects of the hemocyanins on the cell viability and proliferation were analyzed by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay and the alterations in the tumor cell morphology were examined by fluorescent and transmission electron microscopy. The results of the MTT assay showed that the mucus and α-subunit of hemocyanin from the snail H. aspersa had the most significant antiproliferative activity of the tested samples. Cytomorphological analysis revealed that the observed antitumor effects were associated with induction of apoptosis in the tumor cells. The presented data indicate that hemocyanins and mucus from H. aspersa have an antineoplastic activity and potential for development of novel therapeutics for treatment of colorectal carcinoma.
Going Beyond Code: Monitoring Disaggregated Energy and Modeling Detached Houses in Hawai‘i
Authors: Meguro Wendy , Peppard Eileen , Meder Stephen , Maskrey James , Josephson Riley
Published: July 2020

Hawai‘i was the first state to establish a statewide 100% renewable energy goal to be met by 2045. To address the potential impact of new residential construction, a team conducted field studies and developed whole-building energy models of detached houses in Hawai‘i. The goal was to inform the state, a major developer, and the Hawai‘i design community on how current residential design could be modified to meet the newly adopted energy codes and renewable energy goals. Seven houses with air-conditioning were monitored for disaggregated energy use, temperature, and humidity for one year. The building simulation software BEoptTM v.2.8 was used to conduct parametric analyses and cost/energy optimizations to evaluate design options. The energy-optimized model for this hot-humid climate included the following: increasing the efficiency of the air-conditioning system; utilizing ceiling fans with occupancy sensors while increasing the thermostat set-point; a light-colored exterior finish and roof; a radiant barrier; longer eaves; and Energy Star appliances. The energy-optimized model reduced the annual site energy by approximately 47.1% compared to the model that minimally complied with the International Energy Conservation Code 2015. A 4.5-kW grid-tied photovoltaic array would achieve a net-zero annual site energy value.
Annealing Temperature-Dependent Effects of Fe-Loading on the Visible Light-Driven Photocatalytic Activity of Rutile TiO2 Nanoparticles and Their Applicability for Air Purification
Authors: Kim Soong Yeon , Saqlain Shahid , Cha Byeong Jun , Zhao Shufang , Seo Hyun Ook , Kim Young Dok
Published: July 2020

Commercial rutile TiO2 particles (200–300 nm) were modified by the temperature-regulated chemical vapor deposition (tr-CVD) of Fe-oxide and subsequent annealing at various temperatures (300~750 °C). As a result of the modification, the photocatalytic activity of the TiO2 regarding acetaldehyde removal under visible light was enhanced, and the enhancement effects were dependent on the annealing temperature. Specifically, the enhancement effects of the modification were most pronounced when Fe-TiO2 was annealed at 375 °C, whereas the effects were significantly reduced by annealing at higher temperatures (525 and 750 °C). The analytical results with various techniques, including two surface-sensitive methods (XPS (X-ray photoelectron spectroscopy) and TOF-SIMS (time of fight-secondary ion mass spectrometry)), revealed that the stronger metal support interaction between TiO2 and the loaded Fe-oxide at high temperature (>375 °C) resulted in the decreased charge separation efficiency and photocatalytic activity of the Fe-TiO2 under light irradiation. The production scale for the Fe-TiO2 photocatalysts can be easily increased (from 200 g to 8 kg per the unit process) by upsizing the reactor volume. The mass-produced samples exhibited similar activity to the samples produced at small scale, and they were photocatalytically active after being spread on a cement block (stainless steel plate) using a surface hardening agent (paint), showing the high applicability in real applications.
COVID-19 Serological Tests: How Well Do They Actually Perform?
Authors: Ghaffari Abdi , Meurant Robyn , Ardakani Ali
Published: July 2020

In only a few months after initial discovery in Wuhan, China, SARS-CoV-2 and the associated coronavirus disease 2019 (COVID-19) have become a global pandemic causing significant mortality and morbidity and implementation of strict isolation measures. In the absence of vaccines and effective therapeutics, reliable serological testing must be a key element of public health policy to control further spread of the disease and gradually remove quarantine measures. Serological diagnostic tests are being increasingly used to provide a broader understanding of COVID-19 incidence and to assess immunity status in the population. However, there are discrepancies between claimed and actual performance data for serological diagnostic tests on the market. In this study, we conducted a review of independent studies evaluating the performance of SARS-CoV-2 serological tests. We found significant variability in the accuracy of marketed tests and highlight several lab-based and point-of-care rapid serological tests with high levels of performance. The findings of this review highlight the need for ongoing independent evaluations of commercialized COVID-19 diagnostic tests.
Different Biomarker Kinetics in Critically Ill Patients with High Lactate Levels
Authors: Matsuura Ryo , Komaru Yohei , Miyamoto Yoshihisa , Yoshida Teruhiko , Yoshimoto Kohei , Hamasaki Yoshifumi , Nangaku Masaomi , Doi Kent
Published: July 2020

We evaluated the association of the kinetics of interleukin-6 (IL-6), neutrophil gelatinase-associated lipocalin (NGAL), and high-mobility group box 1 (HMGB1) with intensive care unit (ICU) mortality in critically ill patients with hyperlactatemia. This proof-of-concept study was conducted with prospectively enrolled patients admitted to a medical/surgical ICU with hyperlactatemia (lactate levels >4 mmol/L). Blood lactate, IL-6, NGAL, and HMGB1 were measured every 2 h until 6 h post ICU admission. The primary outcome was ICU mortality. Of thirty patients in this study, 14 patients (47%) had sepsis, and the ICU mortality was 47%. IL-6 and NGAL levels were significantly higher in septic patients than in non-septic patients. On kinetic analysis, the lactate levels were significantly decreased in survivors, and the NGAL levels were significantly increased in non-survivors. Among septic patients, a decline in IL-6 levels were observed in survivors. The HMGB1 levels were unchanged in survivors and non-survivors regardless of sepsis complication. Non-septic patients with higher reduction rate of lactate and HMGB1 had the lowest mortality than the others. ICU patients exhibited different kinetic patterns in lactate, NGAL, and IL-6, but HMGB1 did not seem to change over the 6-h duration. Further studies are necessary to evaluate the efficacy of the combination of the inflammatory biomarkers with lactate.
Influence of Diabetes on Implant Failure and Peri-Implant Diseases: A Retrospective Study
Authors: Alberti Alice , Morandi Paolo , Zotti Beatrice , Tironi Francesco , Francetti Luca , Taschieri Silvio , Corbella Stefano
Published: July 2020

Diabetes is an important modifying factor of periodontitis, but its association with peri-implant diseases has not been fully explored and the existing literature reports controversial results. The aim of this retrospective study was to evaluate the influence of diabetes on peri-implantitis and implant failure. Smoking status, history of periodontal disease, presence of diabetes, diabetes type, therapy and glycaemia levels were collected in a total of 204 subjects treated with 929 implants, with a mean follow-up time of 5.7 ± 3.82 years after loading. Odds ratio (OR) for diabetes as a direct cause of peri-implantitis and implant failure were calculated, adjusted for smoking status and history of periodontitis. Nineteen patients were diabetic and most of them presented a good control of the disease at the time of surgery. The overall patient-level prevalence of peri-implantitis was 11.3%. Among diabetic patients, one developed peri-implantitis, whereas one experienced multiple implant failures. The calculated ORs, adjusted for smoking status and periodontitis, were not statistically significant. The results revealed no association between diabetes and peri-implantitis or implant failure coherently with the existing scientific literature. The actual influence of hyperglycemia on implant failure is still uncertain and new studies with larger cohorts of patients are needed.
Application of Classification Algorithms to Diffuse Reflectance Spectroscopy Measurements for Ex Vivo Characterization of Biological Tissues
Authors: Fanjul-Vélez Félix , Pampín-Suárez Sandra , Arce-Diego José Luis
Published: July 2020

Biological tissue identification in real clinical scenarios is a relevant and unsolved medical problem, particularly in the operating room. Although it could be thought that healthy tissue identification is an immediate task, in practice there are several clinical situations that greatly impede this process. For instance, it could be challenging in open surgery in complex areas, such as the neck, where different structures are quite close together, with bleeding and other artifacts affecting visual inspection. Solving this issue requires, on one hand, a high contrast noninvasive technique and, on the other hand, powerful classification algorithms. Regarding the technique, optical diffuse reflectance spectroscopy has demonstrated such capabilities in the discrimination of tumoral and healthy biological tissues. The complex signals obtained, in the form of spectra, need to be adequately computed in order to extract relevant information for discrimination. As usual, accurate discrimination relies on massive measurements, some of which serve as training sets for the classification algorithms. In this work, diffuse reflectance spectroscopy is proposed, implemented, and tested as a potential technique for healthy tissue discrimination. A specific setup is built and spectral measurements on several ex vivo porcine tissues are obtained. The massive data obtained are then analyzed for classification purposes. First of all, considerations about normalization, detrending and noise are taken into account. Dimensionality reduction and tendencies extraction are also considered. Featured spectral characteristics, principal component or linear discrimination analysis are applied, as long as classification approaches based on k-nearest neighbors (k-NN), quadratic discrimination analysis (QDA) or Naïve Bayes (NB). Relevant parameters about classification accuracy are obtained and compared, including ANOVA tests. The results show promising values of specificity and sensitivity of the technique for some classification algorithms, even over 95%, which could be relevant for clinical applications in the operating room.
A Unified Theory of Human Judgements and Decision-Making under Uncertainty
Authors: Pisano Raffaele , Sozzo Sandro
Published: July 2020

Growing empirical evidence reveals that traditional set-theoretic structures cannot in general be applied to cognitive phenomena. This has raised several problems, as illustrated, for example, by probability judgement errors and decision-making (DM) errors. We propose here a unified theoretical perspective which applies the mathematical formalism of quantum theory in Hilbert space to cognitive domains. In this perspective, judgements and decisions are described as intrinsically non-deterministic processes which involve a contextual interaction between a conceptual entity and the cognitive context surrounding it. When a given phenomenon is considered, the quantum-theoretic framework identifies entities, states, contexts, properties and outcome statistics, and applies the mathematical formalism of quantum theory to model the considered phenomenon. We explain how the quantum-theoretic framework works in a variety of judgement and decision situations where systematic and significant deviations from classicality occur.
Measuring Independence between Statistical Randomness Tests by Mutual Information
Authors: Karell-Albo Jorge Augusto , Legón-Pérez  Carlos Miguel , Madarro-Capó  Evaristo José , Rojas Omar , Sosa-Gómez Guillermo
Published: July 2020

The analysis of independence between statistical randomness tests has had great attention in the literature recently. Dependency detection between statistical randomness tests allows one to discriminate statistical randomness tests that measure similar characteristics, and thus minimize the amount of statistical randomness tests that need to be used. In this work, a method for detecting statistical dependency by using mutual information is proposed. The main advantage of using mutual information is its ability to detect nonlinear correlations, which cannot be detected by the linear correlation coefficient used in previous work. This method analyzes the correlation between the battery tests of the National Institute of Standards and Technology, used as a standard in the evaluation of randomness. The results of the experiments show the existence of statistical dependencies between the tests that have not been previously detected.
Labor Market Segmentation and Immigrant Competition: A Quantal Response Statistical Equilibrium Analysis
Authors: Wiener Noé M.
Published: July 2020

Competition between and within groups of workers takes place in labor markets that are segmented along various, often unobservable dimensions. This paper proposes a measure of the intensity of competition in labor markets on the basis of limited data. The maximum entropy principle is used to make inferences about the unobserved mobility decisions of workers in US household data. The quantal response statistical equilibrium class of models can be seen to give robust microfoundations to the persistent patterns of wage inequality. An application to labor market competition between native and foreign-born workers in the United States shows that this class of models captures a substantial proportion of the informational content of observed wage distributions.
The Design of Compact SM4 Encryption and Decryption Circuits That Are Resistant to Bypass Attack
Authors: Zhou Fang , Zhang Benjun , Wu Ning , Bu Xiangli
Published: July 2020

In order to achieve the purpose of defending against side channel attacks, a compact SM4 circuit was designed based on the mask and random delay technique, and the linear transformation module was designed with random insertion of the pseudo operation method. By analyzing the glitch data generated by the S-box of SM4 with different inputs, the security against glitch attacks was confirmed. Then, the DPA (Differential Power Analysis) was performed on the designed circuit. The key could not be successfully obtained even in the case of 100,000 power curves, so that the safety of SM4 against DPA is verified. Finally, using Synopsys DC (Design Compiler, Mountain View, CA94043DC, USA) to synthesize the designed circuit, the results show that the area of the designed circuit in the SMIC 0.18 process is 82,734 μm2, which is 48% smaller than results reported in other papers.
Application of Solid-State Transformers in a Novel Architecture of Hybrid AC/DC House Power Systems
Authors: Bignucolo Fabio , Bertoluzzo Manuele
Published: July 2020

The ongoing diffusion of solid-state DC/DC converters makes possible a partial migration of electric power systems from the present AC paradigm to a future DC scenario. In addition, the power demand in the domestic environment is expected to grow considerably, for example, due to the progressive diffusion of electric vehicles, induction cooking and heat pumps. To face this evolution, the paper introduces a novel electric topology for a hybrid AC/DC smart house, based on the solid-state transformer technology. The electric scheme, voltage levels and converters types are thoroughly discussed to better integrate the spread of electric appliances, which are frequently based on internal DC buses, within the present AC distribution networks. Voltage levels are determined to guarantee high safety zones with negligible electric risk in the most exposed areas of the house. At the same time, the developed control schemes assure high power quality (voltage stability in the case of both load variations and network perturbations), manage power flows and local resources according to ancillary services requirements and increase the domestic network overall efficiency. Dynamic simulations are performed, making use of DIgSILENT PowerFactory software, to demonstrate the feasibility of the proposed distribution scheme for next-generation smart houses under different operating conditions.
Can Effects of Temperature on Two-Phase Gas/Oil-Relative Permeabilities in Porous Media Be Ignored? A Critical Analysis
Authors: Kumar Saket , Esmaeili Sajjad , Sarma Hemanta , Maini Brij
Published: July 2020

Thermal recovery processes for heavy oil exploitation involve three-phase flow at elevated temperatures. The mathematical modeling of such processes necessitates the account of changes in the rock–fluid system’s flow behavior as the temperature rises. To this end, numerous studies on effects of the temperature on relative permeabilities have been reported in the literature. Compared to studies on the temperature effects on oil/water-relative permeabilities, studies (and hence, data) on gas/oil-relative permeabilities are limited. However, the role of temperature on both gas/oil and oil/water-relative permeabilities has been a topic of much discussion, contradiction and debate. The jury is still out, without a consensus, with several contradictory hypotheses, even for the limited number of studies on gas/oil-relative permeabilities. This study presents a critical analysis of studies on gas/oil-relative permeabilities as reported in the literature, and puts forward an undeniable argument that the temperature does indeed impact gas/oil-relative permeabilities and the other fluid–fluid properties contributing to flow in the reservoir, particularly in a thermal recovery process. It further concludes that such thermal effects on relative permeabilities must be accounted for, properly and adequately, in reservoir simulation studies using numerical models. The paper presents a review of most cited studies since the 1940s and identifies the possible primary causes that contribute to contradictory results among them, such as differences in experimental methodologies, experimental difficulties in flow data acquisition, impact of flow instabilities during flooding, and the differences in the specific impact of temperature on different rock–fluid systems. We first examined the experimental techniques used in measurements of oil/gas-relative permeabilities and identified the challenges involved in obtaining reliable results. Then, the effect of temperature on other rock–fluid properties that may affect the relative permeability was examined. Finally, we assessed the effect of temperature on parameters that characterized the two-phase oil/gas-relative permeability data, including the irreducible water saturation, residual oil saturation and critical gas saturation. Through this critical review of the existing literature on the effect of temperature on gas/oil-relative permeabilities, we conclude that it is an important area that suffers profoundly from a lack of a comprehensive understanding of the degree and extent of how the temperature affects relative permeabilities in thermal recovery processes, and therefore, it is an area that needs further focused research to address various contradictory hypotheses and to describe the flow in the reservoir more reliably.
Promotion of RES in a Technology Transfer Network. Case Study of the Enterprise Europe Network
Authors: Gródek-Szostak Zofia , Luc Małgorzata , Szeląg-Sikora Anna , Sikora Jakub , Niemiec Marcin , Ochoa Siguencia Luis , Velinov Emil
Published: July 2020

The promotion of renewable energy is a key concept in the European Union for both environmental and economic reasons. It contributes to securing the objectives set out in the Kyoto Protocol. In addition, it brings various social and economic benefits, e.g., diversification of the energy offer, new jobs, improvement of regional and local development opportunities and building a solid national industry. The main purpose of the article is to contribute to the debate on the instruments promoting renewable energy sources (RES) by emphasizing its importance within the technology transfer network. The subject is an empirical study of an actual technology transfer network. Its international activity promotes RES among entrepreneurs. Data related to meetings as part of brokerage events (BE) and company missions (CM) were subject to statistical and visual analysis, based on the data obtained from the Enterprise Europe Network from the years 2017–2018. The presented results are the foundation for future theoretical and practical studies. One of the important aspects to be examined is the intensity of cooperation launched during CM and BE. It is related to the results of partnership agreements and the importance of increasing the knowledge flow and creating opportunities for partners to acquire foreign technologies.
Optimum Synthesis of a BOA Optimized Novel Dual-Stage PI − (1 + ID) Controller for Frequency Response of a Microgrid
Authors: Latif Abdul , Hussain S. M. Suhail , Das Dulal Chandra , Ustun Taha Selim
Published: July 2020

A renewable and distributed generation (DG)-enabled modern electrified power network with/without energy storage (ES) helps the progress of microgrid development. Frequency regulation is a significant scheme to improve the dynamic response quality of the microgrid under unknown disturbances. This paper established a maiden load frequency regulation of a wind-driven generator (WG), solar tower (ST), bio-diesel power generator (BDPG) and thermostatically controllable load (heat pump and refrigerator)-based, isolated, single-area microgrid system. Hence, intelligent control strategies are important for this issue. A newly developed butterfly algorithmic technique (BOA) is leveraged to tune the controllers’ parameters. However, to attain a proper balance between net power generation and load power, a dual stage proportional-integral- one plus integral-derivative PI − (1 + ID) controller is developed. Comparative system responses (in MATLAB/SIMULINK software) for different scenarios under several controllers, such as a proportional-integral (PI), proportional-integral-derivative (PID) and PI − (1 + ID) controller tuned by particle swarm optimization (PSO), grasshopper algorithmic technique (GOA) and BOA, show the superiority of BOA in terms of minimizing the peak deviations and better frequency regulation of the system. Real recorded wind data are considered to authenticate the control approach.
Electro-Thermal Simulation of Vertical VO2 Thermal-Electronic Circuit Elements
Authors: Darwish Mahmoud , Neumann Péter , Mizsei János , Pohl László
Published: July 2020

Advancement of classical silicon-based circuit technology is approaching maturity and saturation. The worldwide research is now focusing wide range of potential technologies for the “More than Moore” era. One of these technologies is thermal-electronic logic circuits based on the semiconductor-to-metal phase transition of vanadium dioxide, a possible future logic circuits to replace the conventional circuits. In thermal-electronic circuits, information flows in a combination of thermal and electronic signals. Design of these circuits will be possible once appropriate device models become available. Characteristics of vanadium dioxide are under research by preparing structures in laboratory and their validation by simulation models. Modeling and simulation of these devices is challenging due to several nonlinearities, discussed in this article. Introduction of custom finite volumes method simulator has however improved handling of special properties of vanadium dioxide. This paper presents modeling and electro-thermal simulation of vertically structured devices of different dimensions, 10 nm to 300 nm layer thicknesses and 200 nm to 30 μm radii. Results of this research will facilitate determination of sample sizes in the next phase of device modeling.
Critical Review of Mitigation Solutions for SSO in Modern Transmission Grids
Authors: Sewdien Vinay , Wang Xiongfei , Rueda Torres Jose , van der Meijden Mart
Published: July 2020

The replacement of conventional generation by power electronics-based generation changes the dynamic characteristics of the power system. This results in, among other things, the increased susceptibility to subsynchronous oscillations (SSO). First, this paper discusses three recently emerging SSO phenomena, which arise due to the interactions between (1) a doubly-fed induction generator and a series compensated transmission system; (2) a voltage source converter (VSC) and a weak grid; and (3) nearby VSCs. A fundamental review of these phenomena resulted in the requirement for a reclassification of the existing SSO phenomena. This reclassification is proposed in this work and is based on interacting components identified using participation factor analysis for the distinct phenomena. Second, a critical review of the existing mitigation measures is performed for these phenomena, highlighting the advantages and disadvantages of the solutions. The influence of the wind speed, grid strength, number of wind turbines, and several converter controller parameters are also discussed. To assist equipment manufacturers, control design engineers, and system operators in selecting and designing effective mitigation measures, the existing solutions are categorized in control solutions, hardware solutions, and solutions based on system level coordination. Finally, perspectives on open issues conclude this paper.
The Use of Ground Source Heat Pump to Achieve a Net Zero Energy Building
Authors: D’Agostino Diana , Mele Luigi , Minichiello Francesco , Renno Carlo
Published: July 2020

Currently, ground source heat pump (GSHP) technology is being studied, as the use of the ground as a source of renewable energy allows significant energy savings to be obtained. Therefore, it is useful to quantify how these savings help to achieve the energy balance of a Net Zero Energy Building (NZEB) compared to an air source heat pump or a condensing boiler coupled to a chiller. This paper assesses how these savings affect the number of photovoltaic panels installed on the roof of a building to obtain the NZEB target. The study is conducted by dynamic simulation for a building used as a bed and breakfast, virtually placed in two Italian towns. The energy savings and reduction of CO2 emissions, the percentage of renewable energy used, and the photovoltaic surface needed are assessed. Finally, the discounted payback period is calculated. The results show that the GSHP, unlike the systems to which it is compared, allows an NZEB to be obtained by balancing yearly energy consumption with energy production systems which only use on-site renewable energy sources (by exploiting the surface available on the roof) for both of the climatic conditions considered. GSHP also allows primary energy requests equal to or less than 57 kWh/m2 to be obtained.
Finite Control Set Model Predictive Control for Paralleled Uninterruptible Power Supplies
Authors: Oliveira Tiago , Caseiro Luís , Mendes André , Cruz Sérgio
Published: July 2020

Nowadays, uninterruptible power supplies (UPS) play an important role in feeding critical loads in the electric power systems such as data centers or large communication hubs. Due to the increasing power of these loads and frequent need for expansion or redundancy, UPS systems are frequently connected in parallel. However, when UPS systems are parallel-connected, two fundamental requirements must be verified: potential circulating currents between the systems must be eliminated and the load power must be distributed between the systems according to UPS systems availability. Moreover, a high-quality load voltage waveform must be permanently ensured. In this paper innovative control strategies are proposed for paralleled UPS systems based on Finite Control Set Model Predictive Control (FCS-MPC). The proposed strategies simultaneously provide: controlled load power distribution, circulating current suppression and a high-quality load voltage waveform. A new dynamic converters deactivation mechanism is proposed. This new technique provides improved overall system efficiency and reduced power switches stress. In this paper, two multilevel based UPS systems are parallel-connected. Each UPS contains two three-level Neutral Point-Clamped-Converters (3LNPC) and a three-level DC-DC converter. The presented experimental results demonstrate the effectiveness of the proposed control strategies in several operating conditions.
Optimal Dispatch of High-Penetration Renewable Energy Integrated Power System Based on Flexible Resources
Authors: Feng Jiawei , Yang Junyou , Wang Haixin , Ji Huichao , Okoye Martin Onyeka , Cui Jia , Ge Weichun , Hu Bo , Wang Gang
Published: July 2020

The volatility and uncertainty of high-penetration renewable energy (RE) challenge the stability of the power system. To tackle this challenge, an optimal dispatch of high-penetration RE based on flexible resources (FRs) is proposed to enhance the ability of the power system to cope with uncertain disturbances. Firstly, the flexibility of a high-penetration RE integrated power system is analyzed. The flexibility margin of power supply and flexible adaptability of RE are then introduced as the evaluation indices for optimal operation. Finally, a multi-objective optimal dispatch model for power system flexibility enhancement based on FRs under the constraint of flexibility indices is proposed. The simulation results show that the proposed optimal dispatch can effectively enhance the flexibility of the power system and the penetration of RE and reduce pollutant emissions. Compared with the conventional method, the daily average emissions of CO2, SO2, and NOx with the proposed method are reduced by about 83,600 kg, 870 kg, and 370 kg, respectively, the maximum allowable volatility of net load is increased by 7.63%, and the average volatility of net load is reduced by 2.67%.
Design of a Methodology to Evaluate the Impact of Demand-Side Management in the Planning of Isolated/Islanded Microgrids
Authors: Oviedo Cepeda Juan Carlos , Osma-Pinto German , Roche Robin , Duarte Cesar , Solano Javier , Hissel Daniel
Published: July 2020

The integration of Demand-Side Management (DSM) in the planning of Isolated/Islanded Microgrids (IMGs) can potentially reduce total costs and customer payments or increase renewable energy utilization. Despite these benefits, there is a paucity in literature exploring how DSM affects the planning and operation of IMGs. The present work compares the effects of five different strategies of DSM in the planning of IMGs to fulfill the gaps found in the literature. The present work embodies a Disciplined Convex Stochastic Programming formulation that integrates the planning and operation of IMGs using three optimization levels. The first level finds the capacities of the energy sources of the IMG. The second and third levels use a rolling horizon for setting the day-ahead prices or the stimulus of the DSM and the day-ahead optimal dispatch strategy of the IMG, respectively. A case study shows that the Day-Ahead Dynamic Pricing DSM and the Incentive-Based Pricing DSM reduce the total costs and the Levelized Cost of Energy of the project more than the other DSMs. In contrast, the Time of Use DSM reduces the payments of the customers and increases the delivered energy more than the other DSMs.
Microgrid Fault Detection and Classification: Machine Learning Based Approach, Comparison, and Reviews
Authors: Rahman Fahim Shahriar , K. Sarker Subrata , Muyeen S. M. , Sheikh Md. Rafiqul Islam , Das Sajal K.
Published: July 2020

Accurate fault classification and detection for the microgrid (MG) becomes a concern among the researchers from the state-of-art of fault diagnosis as it increases the chance to increase the transient response. The MG frequently experiences a number of shunt faults during the distribution of power from the generation end to user premises, which affects the system reliability, damages the load, and increases the fault line restoration cost. Therefore, a noise-immune and precise fault diagnosis model is required to perform the fast recovery of the unhealthy phases. This paper presents a review on the MG fault diagnosis techniques with their limitations and proposes a novel discrete-wavelet transform (DWT) based probabilistic generative model to explore the precise solution for fault diagnosis of MG. The proposed model is made of multiple layers with a restricted Boltzmann machine (RBM), which enables the model to make the probability reconstruction over its inputs. The individual RBM layer is trained with an unsupervised learning approach where an artificial neural network (ANN) algorithm tunes the model for minimizing the error between the true and predicted class. The effectiveness of the proposed model is studied by varying the input signal and sampling frequencies. A level of considered noise is added with the sample data to test the robustness of the studied model. Results prove that the proposed fault detection and classification model has the ability to perform the precise diagnosis of MG faults. A comparative study among the proposed, kernel extreme learning machine (KELM), multi KELM, and support vector machine (SVM) approaches is studied to confirm the robust superior performance of the proposed model.
Techno-Economic Analysis of Pressurized Oxy-Fuel Combustion of Petroleum Coke
Authors: Hamadeh Hachem , Toor Sannan Y. , Douglas Peter L. , Sarathy S. Mani , Dibble Robert W. , Croiset Eric
Published: July 2020

Petroleum coke (petcoke) is a by-product of heavy petroleum refining, with heating values comparable to that of coal. It is readily available in oil-producing countries such as the United States of America (USA) and the Kingdom of Saudi Arabia (KSA) at minimum costs and can be used as an inexpensive fossil fuel for power generation. Oxy-petcoke combustion is an attractive CO2 capture option as it avoids the use of additional absorption units and chemicals, and results in a CO2 + H2O flue gas stream that is compressed and dehydrated in a CO2 capture and purification unit (CO2CPU). The additional cost of the CO2CPU can be reduced through high pressure combustion. Hence, this paper reports a techno-economic analysis of an oxy-petcoke plant with CO2 capture simulated at pressures between 1 and 15 bars in Aspen PlusTM based on USA and KSA scenarios. Operating at high pressures leads to reduced equipment sizes and numbers of units, specifically compressors in CO2CPU, resulting in increased efficiencies and decreased costs. An optimum pressure of ~10 bars was found to maximize the plant efficiency (~29.7%) and minimize the levelized cost of electricity (LCOE), cost of CO2 avoided and cost of CO2 captured for both the USA and KSA scenarios. The LCOE was found to be moderately sensitive to changes in the capital cost (~0.7% per %) and increases in cost of petcoke (~0.5% per USD/tonne) and insensitive to the costs of labour, utilities and waste treatment.
A Block Bi-Diagonalization-Based Pre-Coding for Indoor Multiple-Input-Multiple-Output-Visible Light Communication System
Authors: Subramani Prabu , Rajendran Ganesh Babu , Sengupta Jewel , Pérez de Prado Rocío , Divakarachari Parameshachari Bidare
Published: July 2020

Visible Light Communication (VLC) is a promising field in optical wireless communications, which uses the illumination infrastructure for data transmission. The important features of VLC are electromagnetic interference-free, license-free, etc. Additionally, Multiple-Input-Multiple-Output (MIMO) techniques are enabled in the VLC for enhancing the limited modulation bandwidth by its spectral efficiency. The data transmission through the MIMO-VLC system is corrupted by different interferences, namely thermal noise, shot noise and phase noise, which are caused by the traditional fluorescent light. In this paper, an effective precoding technique, namely Block Bi-Diagonalization (BBD), is enabled to mitigate the interference occurring in the indoor MIMO-VLC communications. Besides, a Quadrature Amplitude Modulation (QAM) is used to modulate the signal before transmission. Here, the indoor MIMO-VLC system is developed to analyze the communication performance under noise constraints. The performance of the proposed system is analyzed in terms of Bit Error Rate (BER) and throughput. Furthermore, the performances are compared with three different existing methods such as OAP, FBM and NRZ-OOK-LOS. The BER value of the proposed system of scenario 1 is 0.0501 at 10 dB, which is less than that of the FBM technique.
Extruded Solid Biofuels of Rice Straw Plus Oriented Strand Board Residues at Various Proportions
Authors: Tian Feiyu , Xu Deliang , Xu Xinwu
Published: July 2020

Disposal of vast agricultural residues has been a nerve-wracking social problem in many agriculture-intensive regions. Open-field combustion both squanders those biomass resources and causes severe atmospheric pollution and hazards. In addition, wood industries yield residues such as sanding powders without value application. Production of biofuels out of these biomass provides a multiple beneficial solution. To that end, this work focused on fabrication of biomass fuels using rice straws (Calorific value: 14.7 MJ/Kg) and wood residues from OSB industries (Calorific value: 17.3 MJ/Kg). Biofuel sticks from various proportions of biomass residues were made using an 18.5 KW industrial biomass extruder without adding bonding agents, achieving densities of 1.0–1.6 g/cm3 and comparative calorific values. The biofuel sticks exhibit moisture sensitivity when subjected to a ten-day conditioning. Release of residual stresses that were created during the densification process led to structural destruction of the products under moisture aggression. It’s highlighted that combination of rice straw particles with OSB residues gives sound extrusion process ability and high combustibility. The blend of rice straws and OSB residues are proven practically feasible for making solid biofuels. It’s suggested to promote the waste-to-wealth technological scheme in addressing the energy crisis worldwide, especially in those regions rich in agricultural residues while poor in non-renewable energy sources.
Carbon Price Prediction Based on Ensemble Empirical Mode Decomposition and Extreme Learning Machine Optimized by Improved Bat Algorithm Considering Energy Price Factors
Authors: Sun Wei , Zhang Junjian
Published: July 2020

In response to climate change and environmental issues, many countries have gradually optimized carbon market management and improved the carbon market trading mechanism. Carbon price prediction plays a pivotal role in promoting carbon market management when investors are guided by prediction to conduct rational carbon trading. A novel carbon price prediction methodology is constructed based on ensemble empirical mode decomposition, improved bat algorithm, and extreme learning machine (EEMD-IBA-ELM) in this study. Firstly, the carbon price is decomposed into multiple regular intrinsic mode function (IMF) components by the ensemble empirical mode decomposition, and partial autocorrelation analysis (PACF) is used to find IMF historical data affecting the current value of IMF. Secondly, the improved bat algorithm (IBA) is used to heighten extreme learning machine (ELM) while adaptive parameters are obtained. Finally, EEMD-IBA-ELM was established to predict carbon price. Simultaneously, energy price fluctuation is introduced into the carbon price prediction model. As a consequence, EEMD-IBA-ELM carbon price prediction ability is further improved. In the empirical analysis, the historical carbon price of European Climate Exchange (ECX) and Korea Exchange (KRX) markets are used to examine the effectiveness and stability of the model. Errors of carbon price prediction in ECX and KRX is 2.1982% and 1.1762%, respectively. The results show that the EEMD-IBA-ELM carbon price prediction model can accurately predict carbon price when prediction effect shows strong stability. Furthermore, carbon price prediction accurateness was significantly enhanced by using energy price fluctuation as an influencing factor of carbon price prediction.
Gassing Tendency of Fresh and Aged Mineral Oil and Ester Fluids under Electrical and Thermal Fault Conditions
Authors: Loiselle Luc , Mohan Rao U. , Fofana Issouf
Published: July 2020

Operational factors are known to affect the health of an in-service power transformer and to reduce the capabilities and readiness for energy transmission and distribution. Hence, it is important to understand the degradation rate and corresponding behavioral aspects of different insulating fluids under various fault conditions. In this article, the behavior of mineral oil and two environmentally friendly fluids (a synthetic and a natural ester) are reported under arcing, partial discharges, and thermal fault conditions. Arcing, partial discharges and thermal faults are simulated by 100 repeated breakdowns, top oil electrical discharge of 9 kV for five hours, and local hotspots respectively by using different laboratory-based setups. Some physicochemical properties along with the gassing tendency of fresh and aged insulating liquids are investigated after the different fault conditions. UV spectroscopy and turbidity measurements are used to report the degradation behavior and dissolved gas analysis is used to understand the gassing tendency. The changes in the degradation rate of oil under the influence of various faults and the corresponding dissolved gasses generated are analyzed. The fault gas generations are diagnosed by Duval’s triangle and pentagon methods for mineral and non-mineral oils. It is inferred that; the gassing tendency of the dielectric fluids evolve with respect to the degradation rate and is dependent on the intensity and type of fault.