bluuebunny/crossref_metadata_2025 huggingface dataset:
Wilms’ Tumor Primary Cells Display Potent Immunoregulatory Properties on NK Cells and Macrophages
Authors: Fiore Piera Filomena , Vacca Paola , Tumino Nicola , Besi Francesca , Pelosi Andrea , Munari Enrico , Marconi Marcella , Caruana Ignazio , Pistoia Vito , Moretta Lorenzo , Azzarone Bruno
Published: January 2021

The immune response plays a crucial defensive role in cancer growth and metastasis and is a promising target in different tumors. The role of the immune system in Wilm’s Tumor (WT), a common pediatric renal malignancy, is still to be explored. The characterization of the immune environment in WT could allow the identification of new therapeutic strategies for targeting possible inhibitory mechanisms and/or lowering toxicity of the current treatments. In this study, we stabilized four WT primary cultures expressing either a blastematous (CD56+/CD133−) or an epithelial (CD56−/CD133+) phenotype and investigated their interactions with innate immune cells, namely NK cells and monocytes. We show that cytokine-activated NK cells efficiently kill WT cells. However, after co-culture with WT primary cells, NK cells displayed an impaired cytotoxic activity, decreased production of IFNγ and expression of CD107a, DNAM-1 and NKp30. Analysis of the effects of the interaction between WT cells and monocytes revealed their polarization towards alternatively activated macrophages (M2) that, in turn, further impaired NK cell functions. In conclusion, we show that both WT blastematous and epithelial components may contribute directly and indirectly to a tumor immunosuppressive microenvironment that is likely to play a role in tumor progression.
Small-Cell Lung Cancer: Is the Black Box Finally Opening Up?
Authors: Hiddinga Birgitta I. , Kok Klaas
Published: January 2021

Small-cell lung cancer (SCLC) is an aggressive cancer that originates from the neuroendocrine crest [...]
The New Immuno-Oncology-Based Therapies and Their Perspectives in Hepatocellular Carcinoma
Authors: Merle Philippe
Published: January 2021

Hepatocellular carcinoma is a poor prognosis tumor. Systemic therapies are frequently used due to frequent recurrences after surgical or radiologic treatments. Anti-angiogenic tyrosine kinase inhibitors have shown efficacy in monotherapy, but with very low rates of long survival and exceptional recovery. Immuno-oncology based on immune checkpoint inhibitors has revolutionized the systemic therapies since showing long survival rates without any tumor progression or recurrence for some patients in partial or complete response, and possibly for some patients in stable disease. However, the rate of responders under immuno-oncology monotherapy is too low to increase significantly the median overall survival of the treated patients. The immuno-oncology-based combinations with different types of immune checkpoint inhibitors (PD-1/PD-L1 and CTLA-4 inhibitors such as nivolumab, pembrolizumab, atezolizumab, durvalumab, ipilimumab, tremelimumab), or the association of immune checkpoint inhibitors plus anti-angiogenic agents (bevacizumab, lenvatinib, cabozantinib), have led to a breakthrough in the treatment of hepatocellular carcinoma. Indeed, the first phase-3 trial, combining atezolizumab with bevacizumab, has dramatically changed the outcome of patients. Data from several other types of combinations assessed in phase-3 trials are pending, and if positive, will drastically arm the physicians to efficiently treat the patients, and disrupt the current algorithm of hepatocellular carcinoma treatment.
Personalized Medicine: Recent Progress in Cancer Therapy
Authors: Hoeben Ann , Joosten Elbert A. J. , van den Beuken-van Everdingen Marieke H. J.
Published: January 2021

Personalized medicine (PM) or precision medicine in oncology is an emerging approach for tumor treatment and prevention that takes into account inter- and intra-tumor variability in genes, tumor (immune) environment, and lifestyle and morbidities of each person diagnosed with cancer [...]
FAM188B Downregulation Sensitizes Lung Cancer Cells to Anoikis via EGFR Downregulation and Inhibits Tumor Metastasis In Vivo
Authors: Jang Eun-Ju , Sung Jee Young , Yoo Ha-Eun , Jang Hyonchol , Shim Jaegal , Oh Eok-Soo , Goh Sung-Ho , Kim Yong-Nyun
Published: January 2021

Anoikis is a type of apoptosis induced by cell detachment from the extracellular matrix (ECM), which removes mislocalized cells. Acquisition of anoikis resistance is critical for cancer cells to survive during circulation and, thus, metastasize at a secondary site. Although the sensitization of cancer cells to anoikis is a potential strategy to prevent metastasis, the mechanism underlying anoikis resistance is not well defined. Although family with sequence similarity 188 member B (FAM188B) is predicted as a new deubiquitinase (DUB) member, its biological function has not been fully studied. In this study, we demonstrated that FAM188B knockdown sensitized anoikis of lung cancer cell lines expressing WT-EGFR (A549 and H1299) or TKI-resistant EGFR mutant T790M/L858R (H1975). FAM188B knockdown using si-FAM188B inhibited the growth of all three human lung cancer cell lines cultured in both attachment and suspension conditions. FAM188B knockdown resulted in EGFR downregulation and thus decreased its activity. FAM188B knockdown decreased the activities of several oncogenic proteins downstream of EGFR that are involved in anoikis resistance, including pAkt, pSrc, and pSTAT3, with little changes to their protein levels. Intriguingly, si-FAM188B treatment increased EGFR mRNA levels but decreased its protein levels, which was reversed by treatment with the proteasomal inhibitor MG132, indicating that FAM188B regulates EGFR levels via the proteasomal pathway. In addition, cells transfected with si-FAM188B had decreased expression of FOXM1, an oncogenic transcription factor involved in cell growth and survival. Moreover, FAM188B downregulation reduced metastatic characteristics, such as cell adhesion, invasion, and migration, as well as growth in 3D culture conditions. Finally, tail vein injection of si-FAM188B-treated A549 cells resulted in a decrease in lung metastasis and an increase in mice survival in vivo. Taken together, these findings indicate that FAM188B plays an important role in anoikis resistance and metastatic characteristics by maintaining the levels of various oncogenic proteins and/or their activity, leading to tumor malignancy. Our study suggests FAM188B as a potential target for controlling tumor malignancy.
Radiosensitizing Chemotherapy (Irinotecan) with Stereotactic Body Radiation Therapy for the Treatment of Inoperable Liver and/or Lung Metastases of Colorectal Cancer
Authors: Vaugier Loïg , Mirabel Xavier , Martel-Lafay Isabelle , Racadot Séverine , Carrie Christian , Vendrely Véronique , Mahé Marc-André , Senellart Hélène , Raoul Jean-Luc , Campion Loïc , Rio Emmanuel
Published: January 2021

Background: Stereotactic body radiotherapy (SBRT) is a recognized treatment for colorectal cancer (CRC) metastases. We postulated that local responses could be improved by SBRT with a concomitant radiosensitizing agent (irinotecan). Methods: RADIOSTEREO-CAMPTO was a prospective multi-center phase 2 trial investigating SBRT (40–48 Gy in 4 fractions) for liver and/or lung inoperable CRC oligometastases (≤3), combined with two weekly intravenous infusions of 40 mg/m2 Irinotecan. Primary outcome was the objective local response rate as per RECIST. Secondary outcomes were early and late toxicities, EORTC QLQ-C30 quality of life, local control and overall survival. Results: Forty-four patients with 51 lesions (liver = 39, lungs = 12) were included. Median age was 69 years (46–84); 37 patients (84%) had received at least two prior chemotherapy treatments. Median follow-up was 48.9 months. One patient with two lung lesions was lost during follow-up. Assuming maximum bias hypothesis, the objective local response rate in ITT was 86.3% (44/51—95% CI: [76.8–95.7]) or 82.4% (42/51—95% CI: [71.9–92.8]). The observed local response rate was 85.7% (42/49—95% CI: [75.9–95.5]). The 1 and 2-year local (distant) progression-free survivals were 84.2% (38.4%) and 67.4% (21.3%), respectively. The 1 and 2-year overall survivals were 97.5% and 75.5%. There were no severe acute or late reactions. The EORTC questionnaire scores did not significantly worsen during or after treatment. Conclusions: SBRT with irinotecan was well tolerated with promising results despite heavily pretreated patients.
Heterogeneous Electro-Fenton as “Green” Technology for Pharmaceutical Removal: A Review
Authors: Meijide Jessica , Dunlop Patrick S. M. , Pazos Marta , Sanromán María Angeles
Published: January 2021

The presence of pharmaceutical products in the water cycle may cause harmful effects such as morphological, metabolic and sex alterations in aquatic organisms and the selection/development of organisms resistant to antimicrobial agents. The compounds’ stability and persistent character hinder their elimination by conventional physico-chemical and biological treatments and thus, the development of new water purification technologies has drawn great attention from academic and industrial researchers. Recently, the electro-Fenton process has been demonstrated to be a viable alternative for the removal of these hazardous, recalcitrant compounds. This process occurs under the action of a suitable catalyst, with the majority of current scientific research focused on heterogeneous systems. A significant area of research centres working on the development of an appropriate catalyst able to overcome the operating limitations associated with the homogeneous process is concerned with the short service life and difficulty in the separation/recovery of the catalyst from polluted water. This review highlights a present trend in the use of different materials as electro-Fenton catalysts for pharmaceutical compound removal from aquatic environments. The main challenges facing these technologies revolve around the enhancement of performance, stability for long-term use, life-cycle analysis considerations and cost-effectiveness. Although treatment efficiency has improved significantly, ongoing research efforts need to deliver economic viability at a larger scale due to the high operating costs, primarily related to energy consumption.
Tafel Slope Analyses for Homogeneous Catalytic Reactions
Authors: Yin Qiushi , Xu Zihao , Lian Tianquan , Musaev Djamaladdin G. , Hill Craig L. , Geletii Yurii V.
Published: January 2021

Tafel analysis of electrocatalysts is essential in their characterization. This paper analyzes the application of Tafel-like analysis to the four-electron nonelectrochemical oxidation of water by the stoichiometric homogeneous 1-electron oxidant [Ru(bpy)3]3+ to dioxygen catalyzed by homogeneous catalysts, [Ru4O4(OH)2(H2O)4(γ-SiW10O36)2]10− (Ru4POM) and [Co4(H2O)2(PW9O34)2]10– (Co4POM). These complexes have slow electron exchange rates with electrodes due to the Frumkin effect, which precludes the use of known electrochemical methods to obtain Tafel plots at ionic strengths lower than 0.5 M. The application of an electron transfer catalyst, [Ru(bpy)3]3+/2+, increases the rates between the Ru4POM and electrode, but a traditional Tafel analysis of such a complex system is precluded due to a lack of appropriate theoretical models for 4-electron processes. Here, we develop a theoretical framework and experimental procedures for a Tafel-like analysis of Ru4POM and Co4POM, using a stoichiometric molecular oxidant [Ru(bpy)3]3+. The dependence of turnover frequency (TOF) as a function of electrochemical solution potential created by the [Ru(bpy)3]3+/[Ru(bpy)3]2+ redox couple (an analog of the Tafel plot) was obtained from kinetics data and interpreted based on the suggested reaction mechanism.
A Review of the Critical Aspects in the Multi-Scale Modelling of Structured Catalytic Reactors
Authors: Cornejo Ivan , Hayes Robert E.
Published: January 2021

Structured catalytic reactors are enjoying an increasingly important role in the reaction engineering world. At the same time, there are large and growing efforts to use advanced computational models to describe such reactors. The structured reactor represents a multi-scale problem that is typically modelled at the largest scale only, with sub-models being used to improve the model granularity. Rather than a literature review, this paper provides an overview of the key factors that must be considered when choosing these sub-models (or scale bridges). The example structured reactor selected for illustration purposes is the washcoated honeycomb monolith design. The sub-models reviewed include those for pressure drop, inter- and intra-phase mass and heat transfer, and effective thermal conductivity.
Capacitance Electrochemical pH Sensor Based on Different Hafnium Dioxide (HfO2) Thicknesses
Authors: Fredj Zina , Baraket Abdoullatif , Ben Ali Mounir , Zine Nadia , Zabala Miguel , Bausells Joan , Elaissari Abdelhamid , Benson Nsikak U. , Jaffrezic-Renault Nicole , Errachid Abdelhamid
Published: January 2021

Over the past years, to achieve better sensing performance, hafnium dioxide (HfO2) has been studied as an ion-sensitive layer. In this work, thin layers of hafnium dioxide (HfO2) were used as pH-sensitive membranes and were deposited by atomic layer deposition (ALD) process onto an electrolytic-insulating-semiconductor structure Al/Si/SiO2/HfO2 for the realization of a pH sensor. The thicknesses of the layer of the HfO2 studied in this work was 15, 19.5 and 39.9 nm. HfO2 thickness was controlled by ALD during the fabrication process. The sensitivity toward H+ was clearly higher when compared to other interfering ions such as potassium K+, lithium Li+, and sodium Na+ ions. Mott−Schottky and electrochemical impedance spectroscopy (EIS) analyses were used to characterise and to investigate the pH sensitivity. This was recorded by Mott–Schottky at 54.5, 51.1 and 49.2 mV/pH and by EIS at 5.86 p[H−1], 10.63 p[H−1], 12.72 p[H−1] for 15, 19.5 and 30 nm thickness of HfO2 ions sensitive layer, respectively. The developed pH sensor was highly sensitive and selective for H+ ions for the three thicknesses, 15, 19.5 and 39.9 nm, of HfO2-sensitive layer when compared to the other previously mentioned interferences. However, the pH sensor performances were better with 15 nm HfO2 thickness for the Mott–Schottky technique, whilst for EIS analyses, the pH sensors were more sensitive at 39.9 nm HfO2 thickness.
Children’s Perspectives on Outpatient Physician Visits: Capturing a Missing Voice in Patient-Centered Care
Authors: Dalley Jessica S. , Morrongiello Barbara A. , McMurtry C. Meghan
Published: January 2021

Actively involving children in their healthcare is a core value of patient-centered care. This is the first study to directly obtain children’s detailed perspectives on positive and negative aspects of outpatient physician visits in a primary care setting (e.g., checkups) and their preferred level of participation. Individual interviews were conducted with 167 children (female n = 82, male n = 85; ages 7–10, Mage = 8.07 years, SD = 0.82). Open-ended questions were used so that children’s responses were not confined to researchers’ assumptions, followed by close-ended questions to meet specific objectives. Quantitative content analysis, correlations, logistic regression, and Cochran’s Q were used to explore the data. Children were highly fearful of needle procedures (61%), blood draws (73%), pain (45%), and the unknown (21%). Children indicated that they liked receiving rewards (32%) and improving their health (16%). Children who were more fearful during physician visits wanted more preparatory information (ExpB = 1.05, Waldx2(1) = 9.11, p = 0.003, McFadden’s R22 = 0.07) and more participation during the visit (ExpB = 1.04, Waldx2(1) = 5.88, p = 0.015, McFadden’s R22 = 0.03). Our results can inform efforts to promote positive physician visit experiences for children, reduce procedural distress, and foster children’s ability to take an active role in managing their health.
Flood Vulnerability Analysis in Urban Context: A Socioeconomic Sub-Indicators Overview
Authors: Bigi Velia , Comino Elena , Fontana Magda , Pezzoli Alessandro , Rosso Maurizio
Published: January 2021

Despite indicators-based assessment models for flood vulnerability being a well-established methodology, a specific set of indicators that are universally or widely accepted has not been recognized yet. This work aims to review previous studies in the field of vulnerability analysis in order to overcome this knowledge gap identifying the most accepted sub-indicators of exposure, sensitivity and adaptive capacity. Moreover, this review aims to clarify the use of the terms of vulnerability and risk in vulnerability assessment. Throughout a three-phase process, a matrix containing all the sub-indicators encountered during the review process was constructed. Then, based on an adaptation of the Pareto diagram, a set of the most relevant sub-indicators was identified. According to the citation count of each sub-indicator, indeed, 33 sub-indicators were chosen to represent the most universally or widely accepted sub-indicators.
Transvaginal Strain Elastosonography in the Differential Diagnosis of Rectal Endometriosis: Some Potentials and Limits
Authors: Scioscia Marco , Laganà Antonio Simone , Caringella Giuseppe , Guerriero Stefano
Published: January 2021

We sincerely thank Szabó et al [...]
Improving the Accuracy of the Fast Inverse Square Root by Modifying Newton–Raphson Corrections
Authors: Walczyk Cezary J. , Moroz Leonid V. , Cieśliński Jan L.
Published: January 2021

Direct computation of functions using low-complexity algorithms can be applied both for hardware constraints and in systems where storage capacity is a challenge for processing a large volume of data. We present improved algorithms for fast calculation of the inverse square root function for single-precision and double-precision floating-point numbers. Higher precision is also discussed. Our approach consists in minimizing maximal errors by finding optimal magic constants and modifying the Newton–Raphson coefficients. The obtained algorithms are much more accurate than the original fast inverse square root algorithm and have similar very low computational costs.
Deep Ensemble of Weighted Viterbi Decoders for Tail-Biting Convolutional Codes
Authors: Raviv Tomer , Schwartz Asaf , Be’ery Yair
Published: January 2021

Tail-biting convolutional codes extend the classical zero-termination convolutional codes: Both encoding schemes force the equality of start and end states, but under the tail-biting each state is a valid termination. This paper proposes a machine learning approach to improve the state-of-the-art decoding of tail-biting codes, focusing on the widely employed short length regime as in the LTE standard. This standard also includes a CRC code. First, we parameterize the circular Viterbi algorithm, a baseline decoder that exploits the circular nature of the underlying trellis. An ensemble combines multiple such weighted decoders, and each decoder specializes in decoding words from a specific region of the channel words’ distribution. A region corresponds to a subset of termination states; the ensemble covers the entire states space. A non-learnable gating satisfies two goals: it filters easily decoded words and mitigates the overhead of executing multiple weighted decoders. The CRC criterion is employed to choose only a subset of experts for decoding purpose. Our method achieves FER improvement of up to 0.75 dB over the CVA in the waterfall region for multiple code lengths, adding negligible computational complexity compared to the circular Viterbi algorithm in high signal-to-noise ratios (SNRs).
An ESR Framework for the Study of Consciousness
Authors: Stanciu Diana
Published: January 2021

I will argue that, in an interdisciplinary study of consciousness, epistemic structural realism (ESR) can offer a feasible philosophical background for the study of consciousness and its associated neurophysiological phenomena in neuroscience and cognitive science while also taking into account the mathematical structures involved in this type of research. Applying the ESR principles also to the study of the neurophysiological phenomena associated with free will (or rather conscious free choice) and with various alterations of consciousness (AOCs) generated by various pathologies such as epilepsy would add explanatory value to the matter. This interdisciplinary approach would be in tune with Quine’s well known idea that philosophy is not simple conceptual analysis but is continuous with science and actually represents an abstract branch of the empirical research. The ESR could thus resonate with scientific models of consciousness such as the global neuronal workspace model (inspired by the global workspace theory—GWT) and the integrated information theory (IIT) model. While structural realism has already been employed in physics or biology, its application as a meta-theory contextualising and relating various scientific findings on consciousness is new indeed. Out of the two variants: ontic structural realism (OSR) and epistemic structural realism (ESR), the latter can be considered more suitable for the study of consciousness and its associated neurophysiological phenomena because it removes the pressure of the still unanswered ‘What is consciousness?’ ontological question and allows us to concentrate instead on the ‘What can we know about consciousness?’ epistemological question.
Acquisition of Adaptive Traits via Interspecific Association: Ecological Consequences and Applications
Authors: Banerji Aabir
Published: January 2021

Adaptative traits enable organisms to survive and reproduce. Though these traits are often innate features (ones that may or may not exhibit variability in response to environmental cues or originate from horizontal gene transfer), this is not always the case. Many species endure natural selection not with the traits they possess intrinsically but with exogenous substances and abilities that they acquire from other species, via ecological interactions akin to outsourcing, pillaging, and fraud. Here, I review the mechanisms of this exogenous trait acquisition and highlight some of their repercussions and usefulness for natural resource management, industry, and human health.
CBase-EC: Achieving Optimal Throughput-Storage Efficiency Trade-Off Using Erasure Codes
Authors: Xiao Chuqiao , Xia Yefeng , Zhang Qian , Gong Xueqing , Zhu Liyan
Published: January 2021

Many distributed database systems that guarantee high concurrency and scalability adopt read-write separation architecture. Simultaneously, these systems need to store massive amounts of data daily, requiring different mechanisms for storing and accessing data, such as hot and cold data access strategies. Unlike distributed storage systems, the distributed database splits a table into sub-tables or shards, and the request frequency of each sub-table is not the same within a specific time. Therefore, it is not only necessary to design hot-to-cold approaches to reduce storage overhead, but also cold-to-hot methods to ensure high concurrency of those systems. We present a new redundant strategy named CBase-EC, using erasure codes to trade the performances of transaction processing and storage efficiency for CBase database systems developed for financial scenarios of the Bank. Two algorithms are proposed: the hot-cold tablets (shards) recognition algorithm and the hot-cold dynamic conversion algorithm. Then we adopt two optimization approaches to improve CBase-EC performance. In the experiment, we compare CBase-EC with three-replicas in CBase. The experimental results show that although the transaction processing performance declined by no more than 6%, the storage efficiency increased by 18.4%.
Modeling Power GaN-HEMTs Using Standard MOSFET Equations and Parameters in SPICE
Authors: Jadli Utkarsh , Mohd-Yasin Faisal , Moghadam Hamid Amini , Pande Peyush , Chaturvedi Mayank , Dimitrijev Sima
Published: January 2021

The device library in the standard circuit simulator (SPICE) lacks a gallium nitride based high-electron-mobility-transistor (GaN-HEMT) model, required for the design and verification of power-electronic circuits. This paper shows that GaN-HEMTs can be modeled by selected equations from the standard MOSFET LEVEL 3 model in SPICE. A method is proposed for the extraction of SPICE parameters in these equations. The selected equations and the proposed parameter-extraction method are verified with measured static and dynamic characteristics of commercial GaN-HEMTs. Furthermore, a double pulse test is performed in LTSpice and compared to its manufacturer model to demonstrate the effectiveness of the MOSFET LEVEL 3 model. The advantage of the proposed approach to use the MOSFET LEVEL 3 model, in comparison to the alternative behavioral-based model provided by some manufacturers, is that users can apply the proposed method to adjust the parameters of the MOSFET LEVEL 3 model for the case of manufacturers who do not provide SPICE models for their HEMTs.
A GAN-Based Video Intra Coding
Authors: Zhong Guangyu , Wang Jun , Hu Jiyuan , Liang Fan
Published: January 2021

Intra prediction is a vital part of the image/video coding framework, which is designed to remove spatial redundancy within a picture. Based on a set of predefined linear combinations, traditional intra prediction cannot cope with coding blocks with irregular textures. To tackle this drawback, in this article, we propose a Generative Adversarial Network (GAN)-based intra prediction approach to enhance intra prediction accuracy. Specifically, with the superior non-linear fitting ability, the well-trained generator of GAN acts as a mapping from the adjacent reconstructed signals to the prediction unit, implemented into both encoder and decoder. Simulation results show that for All-Intra configuration, our proposed algorithm achieves, on average, a 1.6% BD-rate cutback for luminance components compared with video coding reference software HM-16.15 and outperforms previous similar works.
Linear Characterization and Modeling of GaN-on-Si HEMT Technologies with 100 nm and 60 nm Gate Lengths
Authors: Colangeli Sergio , Ciccognani Walter , Longhi Patrick Ettore , Pace Lorenzo , Poulain Julien , Leblanc Rémy , Limiti Ernesto
Published: January 2021

Motivated by the growing interest towards low-cost, restriction-free MMIC processes suitable for multi-function, possibly space-qualified applications, this contribution reports the extraction of reliable linear models for two advanced GaN-on-Si HEMT technologies, namely OMMIC’s D01GH (100 nm gate length) and D006GH (60 nm gate length). This objective is pursued by means of both classical and more novel approaches. In particular, the latter include a nondestructive method for determining the extrinsic resistances and an optimizaion-based approach to extracting the remaining parasitic elements: these support standard DC and RF measurements in order to obtain a scalable, bias-dependent equivalent-circuit model capturing the small-signal behavior of the two processes. As to the noise model, this is extracted by applying the well known noise-temperature approach to noise figure measurements performed in two different frequency ranges: a lower band, where a standard Y-factor test bench is used, and an upper band, where a custom cold-source test bench is set up and described in great detail. At 5 V drain-source voltage, minimum noise figures as low as 1.5 dB and 1.1 dB at 40 GHz have been extracted for the considered 100 nm and 60 nm HEMTs, respectively: this testifies the maturity of both processes and the effectiveness of the gate length reduction. The characterization and modeling campaign, here presented for the first time, has been repeatedly validated by published designs, a couple of which are reviewed for the Reader’s convenience.
Impact of Revised Time of Use Tariff on Variable Renewable Energy Curtailment on Jeju Island
Authors: Lee Jinyeong , Lee Jaehee , Wi Young-Min
Published: January 2021

Jeju Island announced the “Carbon Free Island (CFI) Plan by 2030” in 2012. This plan aims to replace conventional generators with distributed energy resources (DERs) up to a level of 70% by 2030. Akin to Jeju Island, as DERs have been expanded in islanded power systems, variable renewable energy (VRE) has become a significant component of DERs. However, VRE curtailment can occur to meet power balance, and VRE curtailment generally causes energy waste and low efficiency, so it should be minimized. This paper first presents a systematic procedure for estimating the annual VRE curtailment for the stable operation of the islanded power systems. In this procedure, the VRE curtailment is estimated based on the power demand, the grid interconnection, the capacity factor of VRE, and conventional generators in the base year. Next, through the analysis of the hourly net load profile for the year in which the VRE curtailment is expected to occur, a procedure was proposed to find the season and hour when VRE curtailment occurs the most. It could be applied to revised Time-of-Use (ToU) tariff rates as the most cost-effective mitigation method of VRE curtailment on the retail market-side. Finally, price elasticity of electricity demand was presented for applying the revised ToU tariff rate scenarios in a specific season and hour, which found that VRE curtailment occurred the most. Considering self- and cross-price elasticity of electricity, revised ToU tariff rate scenarios were used in a case study on Jeju Island. Eventually, it was confirmed that VRE curtailment could be mitigated when the revised ToU tariff rates were applied, considering the price elasticity of demand.
Trapping Dynamics in GaN HEMTs for Millimeter-Wave Applications: Measurement-Based Characterization and Technology Comparison
Authors: Angelotti Alberto Maria , Gibiino Gian Piero , Florian Corrado , Santarelli Alberto
Published: January 2021

Charge trapping effects represent a major challenge in the performance evaluation and the measurement-based compact modeling of modern short-gate-length (i.e., ≤0.15 μm) Gallium Nitride (GaN) high-electron mobility transistors (HEMT) technology for millimeter-wave applications. In this work, we propose a comprehensive experimental methodology based on multi-bias large-signal transient measurements, useful to characterize charge-trapping dynamics in terms of both capture and release mechanisms across the whole device safe operating area (SOA). From this dataset, characterizations, such as static-IV, pulsed-IV, and trapping time constants, are seamlessly extracted, thus allowing for the separation of trapping and thermal phenomena and delivering a complete basis for measurement-based compact modeling. The approach is applied to different state-of-the-art GaN HEMT commercial technologies, providing a comparative analysis of the measured effects.
Predicting Fundraising Performance in Medical Crowdfunding Campaigns Using Machine Learning
Authors: Peng Nianjiao , Zhou Xinlei , Niu Ben , Feng Yuanyue
Published: January 2021

The coronavirus disease (COVID-19) pandemic has flooded public health organizations around the world, highlighting the significance and responsibility of medical crowdfunding in filling a series of gaps and shortcomings in the publicly funded health system and providing a new fundraising solution for people that addresses health-related needs. However, the fact remains that medical fundraising from crowdfunding sources is relatively low and only a few studies have been conducted regarding this issue. Therefore, the performance predictions and multi-model comparisons of medical crowdfunding have important guiding significance to improve the fundraising rate and promote the sustainable development of medical crowdfunding. Based on the data of 11,771 medical crowdfunding campaigns from a leading donation-based platform called Weibo Philanthropy, machine-learning algorithms were applied. The results demonstrate the potential of ensemble-based machine-learning algorithms in the prediction of medical crowdfunding project fundraising amounts and leave some insights that can be taken into consideration by new researchers and help to produce new management practices.
Design of Integrated Autonomous Driving Control System That Incorporates Chassis Controllers for Improving Path Tracking Performance and Vehicle Stability
Authors: Ahn Taewon , Lee Yongki , Park Kihong
Published: January 2021

This paper describes an integrated autonomous driving (AD) control system for an autonomous vehicle with four independent in-wheel motors (IWMs). The system consists of two parts: the AD controller and the chassis controller. These elements are functionally integrated to improve vehicle stability and path tracking performance. The vehicle is assumed to employ an IWM independently at each wheel. The AD controller implements longitudinal/lateral path tracking using proportional-integral(PI) control and adaptive model predictive control. The chassis controller is composed of two lateral control units: the active front steering (AFS) control and the torque vectoring (TV) control. Jointly, they find the yaw moment to maintain vehicle stability using sliding mode control; AFS is prioritized over TV to enhance safety margin and energy saving. Then, the command yaw moment is optimally distributed to each wheel by solving a constrained least-squares problem. Validation was performed using simulation in a double lane change scenario. The simulation results show that the integrated AD control system of this paper significantly improves the path tracking capability and vehicle stability in comparison with other control systems.
Online State-of-Charge Estimation Based on the Gas–Liquid Dynamics Model for Li(NiMnCo)O2 Battery
Authors: Jiang Haobin , Chen Xijia , Liu Yifu , Zhao Qian , Li Huanhuan , Chen Biao
Published: January 2021

Accurately estimating the online state-of-charge (SOC) of the battery is one of the crucial issues of the battery management system. In this paper, the gas–liquid dynamics (GLD) battery model with direct temperature input is selected to model Li(NiMnCo)O2 battery. The extended Kalman Filter (EKF) algorithm is elaborated to couple the offline model and online model to achieve the goal of quickly eliminating initial errors in the online SOC estimation. An implementation of the hybrid pulse power characterization test is performed to identify the offline parameters and determine the open-circuit voltage vs. SOC curve. Apart from the standard cycles including Constant Current cycle, Federal Urban Driving Schedule cycle, Urban Dynamometer Driving Schedule cycle and Dynamic Stress Test cycle, a combined cycle is constructed for experimental validation. Furthermore, the study of the effect of sampling time on estimation accuracy and the robustness analysis of the initial value are carried out. The results demonstrate that the proposed method realizes the accurate estimation of SOC with a maximum mean absolute error at 0.50% in five working conditions and shows strong robustness against the sparse sampling and input error.
Effect of Thermal, Acoustic and Air Quality Perception Interactions on the Comfort and Satisfaction of People in Office Buildings
Authors: Bourikas Leonidas , Gauthier Stephanie , Khor Song En Nicholas , Xiong Peiyao
Published: January 2021

Current research on human comfort has identified a gap in the investigation of multi-domain perception interactions. There is a lack of understanding the interrelationships of different physio-socio-psychological factors and the manifestation of their contextual interactions into cross-modal comfort perception. In that direction, this study used data from a post occupancy evaluation survey (n = 26), two longitudinal comfort studies (n = 1079 and n = 52) and concurrent measurements of indoor environmental quality factors (one building) to assess the effect of thermal, acoustic and air quality perception interactions on comfort and satisfaction of occupants in three mixed-mode university office buildings. The study concluded that thermal sensation (TSV) is associated with both air quality (ASV) and noise perception (NSV). The crossed effect of the interaction of air quality and noise perception on thermal sensation was not evident. The key finding was the significant correlation of operative temperature (Top) with TSV as expected, but also with noise perception and overall acoustic comfort. Regarding the crossed main effects on thermal sensation, a significant effect was found for the interactions of (1) Top and (2) sound pressure levels (SPL30) with air quality perception respectively. Most importantly, this study has highlighted the importance of air quality perception in achieving occupants’ comfort and satisfaction with office space.
A Model for Predicting Arsenic Volatilization during Coal Combustion Based on the Ash Fusion Temperature and Coal Characteristic
Authors: Zhao Bo , Chen Geng , Xiong Zijiang , Qin Linbo , Chen Wangsheng , Han Jun
Published: January 2021

Arsenic emission from coal combustion power plants has attracted increasing attention due to its high toxicity. In this study, it was found that there was a close relationship between the ash fusion temperature (AFT) and arsenic distribution based on the thermodynamic equilibrium calculation. In addition to the AFT, coal characteristics and combustion temperature also considerably affected the distribution and morphology of arsenic during coal combustion. Thus, an arsenic volatilization model based on the AFT, coal type, and combustion temperature during coal combustion was developed. To test the accuracy of the model, blending coal combustion experiments were carried out. The experimental results and published data proved that the developed arsenic volatilization model can accurately predict arsenic emission during co-combustion, and the errors of the predicted value for bituminous and lignite were 2.3–9.8%, with the exception of JingLong (JL) coal when combusted at 1500 °C.
Interior Permanent Magnet Synchronous Motor Drive System with Machine Learning-Based Maximum Torque per Ampere and Flux-Weakening Control
Authors: Lin Faa-Jeng , Liao Yi-Hung , Lin Jyun-Ru , Lin Wei-Ting
Published: January 2021

An interior permanent magnet synchronous motor (IPMSM) drive system with machine learning-based maximum torque per ampere (MTPA) as well as flux-weakening (FW) control was developed and is presented in this study. Since the control performance of IPMSM varies significantly due to the temperature variation and magnetic saturation, a machine learning-based MTPA control using a Petri probabilistic fuzzy neural network with an asymmetric membership function (PPFNN-AMF) was developed. First, the d-axis current command, which can achieve the MTPA control of the IPMSM, is derived. Then, the difference value of the dq-axis inductance of the IPMSM is obtained by the PPFNN-AMF and substituted into the d-axis current command of the MTPA to alleviate the saturation effect in the constant torque region. Moreover, a voltage control loop, which can limit the inverter output voltage to the maximum output voltage of the inverter at high-speed, is designed for the FW control in the constant power region. In addition, an adaptive complementary sliding mode (ACSM) speed controller is developed to improve the transient response of the speed control. Finally, some experimental results are given to demonstrate the validity of the proposed high-performance control strategies.
Optimal Decision-Making in Photovoltaic System Selection in Saudi Arabia
Authors: Al-Shammari Sultan , Ko Wonsuk , Al Ammar Essam A. , Alotaibi Majed A. , Choi Hyeong-Jin
Published: January 2021

In this study, optimal decision-making process in photovoltaic (PV) system location selection in Saudi Arabia is described. First, to identify the criteria that influence the decision of selecting a suitable location for the PV system, the geographical information system (GIS)-based multi-criteria decision making (MCDM) approach is used. Next, to assess the weights of the criteria that present different aspects of the investigated locations, four major criteria and 11 sub-criteria are proposed, and analytic hierarchy process (AHP) is applied to develop comparison decision matrix. Finally, the order preference by similarity to ideal solution (TOPSIS) technique evaluates and classifies 17 cities (such as Riyadh, Jeddah) in Saudi Arabia. The result shows that Tabuk city in the northern of Saudi Arabia is the best location. Among the 17 cities, the performance score of seven cities is above or equal 80%, and Tabuk city has the highest score with 87%. This analytical approach could contribute as an early planning to locate suitable sites for the selection of PV system region in Saudi Arabia.
Energy Markets Forecasting. From Inferential Statistics to Machine Learning: The German Case
Authors: Viviani Emma , Di Persio Luca , Ehrhardt Matthias
Published: January 2021

In this work, we investigate a probabilistic method for electricity price forecasting, which overcomes traditional ones. We start considering statistical methods for point forecast, comparing their performance in terms of efficiency, accuracy, and reliability, and we then exploit Neural Networks approaches to derive a hybrid model for probabilistic type forecasting. We show that our solution reaches the highest standard both in terms of efficiency and precision by testing its output on German electricity prices data.
Impact Assessment in the Process of Propagating Climate Change Uncertainties into Building Energy Use
Authors: Yassaghi Hamed , Hoque Simi
Published: January 2021

Buildings are subject to significant stresses due to climate change and design strategies for climate resilient buildings are rife with uncertainties which could make interpreting energy use distributions difficult and questionable. This study intends to enhance a robust and credible estimate of the uncertainties and interpretations of building energy performance under climate change. A four-step climate uncertainty propagation approach which propagates downscaled future weather file uncertainties into building energy use is examined. The four-step approach integrates dynamic building simulation, fitting a distribution to average annual weather variables, regression model (between average annual weather variables and energy use) and random sampling. The impact of fitting different distributions to the weather variable (such as Normal, Beta, Weibull, etc.) and regression models (Multiple Linear and Principal Component Regression) of the uncertainty propagation method on cooling and heating energy use distribution for a sample reference office building is evaluated. Results show selecting a full principal component regression model following a best-fit distribution for each principal component of the weather variables can reduce the variation of the output energy distribution compared to simulated data. The results offer a way of understanding compound building energy use distributions and parsing the uncertain nature of climate projections.
Non-Modal Three-Dimensional Optimal Perturbation Growth in Thermally Stratified Mixing Layers
Authors: Vitoshkin Helena , Gelfgat Alexander
Published: January 2021

A non-modal transient disturbances growth in a stably stratified mixing layer flow is studied numerically. The model accounts for a density gradient within a shear region, implying a heavier layer at the bottom. Numerical analysis of non-modal stability is followed by a full three-dimensional direct numerical simulation (DNS) with the optimally perturbed base flow. It is found that the transient growth of two-dimensional disturbances diminishes with the strengthening of stratification, while three-dimensional disturbances cause significant non-modal growth, even for a strong, stable stratification. This non-modal growth is governed mainly by the Holmboe modes and does not necessarily weaken with the increase of the Richardson number. The optimal perturbation consists of two waves traveling in opposite directions. Compared to the two-dimensional transient growth, the three-dimensional growth is found to be larger, taking place at shorter times. The non-modal growth is observed in linearly stable regimes and, in slightly linearly supercritical regimes, is steeper than that defined by the most unstable eigenmode. The DNS analysis confirms the presence of the structures determined by the transient growth analysis.
Functionality of Food Components and Emerging Technologies
Authors: Galanakis Charis M.
Published: January 2021

This review article introduces nutrition and functional food ingredients, explaining the widely cited terms of bioactivity, bioaccessibility, and bioavailability. The factors affecting these critical properties of food components are analyzed together with their interaction and preservation during processing. Ultimately, the effect of emerging (non-thermal) technologies on different food components (proteins, carbohydrates, lipids, minerals, vitamins, polyphenols, glucosinolates, polyphenols, aroma compounds, and enzymes) is discussed in spite of preserving their functional properties. Non-thermal technologies can maintain the bioavailability of food components, improve their functional and technological properties, and increase the recovery yields from agricultural products. However, the optimization of operational parameters is vital to avoid degradation of macromolecules and the oxidation of labile compounds.
Sensory Attributes, Microbial Activity, Fatty Acid Composition and Meat Quality Traits of Hanwoo Cattle Fed a Diet Supplemented with Stevioside and Organic Selenium
Authors: Shin Yong Geum , Rathnayake Dhanushka , Mun Hong Seok , Dilawar Muhammad Ammar , Pov Sreynak , Yang Chul Ju
Published: January 2021

This study examined the effects of stevioside (S) and organic selenium (O-Se) supplementation on the sensory attributes, microbial activity, fatty acid composition, and meat quality traits of Hanwoo cattle (Korean native cattle). Twenty-four Hanwoo cattle (663 ± 22 kg body weight) were assigned to two dietary treatments for 8 months: control diet and 1% stevioside with 0.08% organic selenium supplemented diet. S and O-Se inclusion in the diet enhanced the final body weight, weight gain, and carcass crude protein (p < 0.05). Moreover, supplementation with S and O-Se had a significant effect on lowering the drip loss and shear force and enhanced the a* (redness) of the longissimus dorsi muscle (p < 0.05). The inclusion of dietary S and O-Se improved the sum of the polyunsaturated fatty acid (ΣPUFAs) content of the meat, and the oxidative status (TBARS) values during second week of storage decreased by 42% (p < 0.05). On the other hand, the microbial count tended to decrease (7.62 vs. 7.41 log10 CFU), but it was not significant (p > 0.05), and all sensory attributes were enhanced in the S and O-Se supplemented diet. Overall, these results suggest that supplementation of the ruminant diet with stevioside and organic selenium improves the growth performance, carcass traits, and meat quality with enriched PUFAs profile and retards the lipid oxidation during the storage period in beef.