bluuebunny/crossref_metadata_2025 huggingface dataset:
Earth-Abundant Electrocatalysts for Water Splitting: Current and Future Directions
Authors: Ibn Shamsah Sami M.
Published: March 2021

Of all the available resources given to mankind, the sunlight is perhaps the most abundant renewable energy resource, providing more than enough energy on earth to satisfy all the needs of humanity for several hundred years. Therefore, it is transient and sporadic that poses issues with how the energy can be harvested and processed when the sun does not shine. Scientists assume that electro/photoelectrochemical devices used for water splitting into hydrogen and oxygen may have one solution to solve this hindrance. Water electrolysis-generated hydrogen is an optimal energy carrier to store these forms of energy on scalable levels because the energy density is high, and no air pollution or toxic gas is released into the environment after combustion. However, in order to adopt these devices for readily use, they have to be low-cost for manufacturing and operation. It is thus crucial to develop electrocatalysts for water splitting based on low-cost and land-rich elements. In this review, I will summarize current advances in the synthesis of low-cost earth-abundant electrocatalysts for overall water splitting, with a particular focus on how to be linked with photoelectrocatalytic water splitting devices. The major obstacles that persist in designing these devices. The potential future developments in the production of efficient electrocatalysts for water electrolysis are also described.
Conversion of Oxygenates on H-ZSM-5 Zeolites—Effects of Feed Structure and Si/Al Ratio on the Product Quality
Authors: Gille Torsten , Seifert Markus , Marschall Mathias , Bredow Sascha , Schneider Tobias , Busse Oliver , Reschetilowski Wladimir , Weigand Jan
Published: March 2021

The conversion of different biogenic feedstocks to hydrocarbons is a major challenge when ensuring hydrocarbon and fuel supply in spite of the heterogeneity of this feed. Flexible adaptation to changing compositions is mandatory for the respective processes. In this study, different oxygenate model feeds, such as alcohols, aldehydes, carboxylic acids and esters, were converted at 500 °C and 5 barg H2 using H-ZSM-5 zeolite catalysts with various Si/Al ratios to identify the relationship between the feed structure and the final product distribution. As the main outcome, the product distribution becomes increasingly independent of the feed structure for Al-rich H-ZSM-5 catalyst samples at low Time on Stream (ToS). Some minor exceptions are the increased formation of aromatics during ToS for carbonyl oxygenates compared to primary alcohols and the dominance of initial deoxygenation products for Si-rich H-ZSM-5 samples. This is interpreted by a multi-stage reaction sequence, which involves the initial deoxygenation of the feed and the subsequent integration of the olefin intermediates into a reaction network. The results pave the way towards the achievement of a desired product distribution in the conversion of different oxygenates simply by the adaption of the Al content of H-ZSM-5.
Biochar Derived from Agricultural Wastes as a Means of Facilitating the Degradation of Azo Dyes by Sulfides
Authors: Han Qilin , Yang Yadong , Wang Ruofan , Zhang Kai , Liu Na , Hong Mei
Published: March 2021

Dyes are common contaminants, some of which are teratogenic, carcinogenic, and causative of ecological damage, and dye wastewater often contains toxic sulfides. Biochar has been widely used for the adsorption and catalysis degradation of pollutants, including dyes and sulfides, due to its abundant surface functional groups and large specific surface area. Therefore, the simultaneous treatment of dyes and sulfides with biochar may be a feasible, effective, and novel solution. This study sought to utilize low-cost, environmentally friendly, and widely sourced biochar materials from agricultural wastes such as corn stalk, rice chaff, and bean stalk to promote the reduction of dyes by sulfides. Through the action of different biochars, sulfides can rapidly decompose and transform oxidizing dyes. The RCB800 (rice chaff biochar material prepared at 800 °C) was observed to have the best effect, with a degradation rate of 96.6% in 40 min and 100% in 50 min for methyl orange. This series of materials are highly adaptable to temperature and pH, and the concentration of sulfides has a significant effect on degradation rates. Compared with commercial carbon materials, biochars are similar in terms of their catalytic mechanism and are more economical. Scanning electron microscopy, transmission electron microscopy, and nitrogen adsorption and desorption characterization results indicated that biochar contains more pores, including mesopores, and a sufficient specific surface area, both of which are conducive to the combination of sulfides and dyes with biochar. X-ray photoelectron spectroscopy and Fourier transform infrared spectroscopy showed that there are oxygen-containing functional groups (examples include quinones and carboxyl groups) on the surface of biochar that promote the reaction of sulfide and dye. The formation of active polysulfides also potentially plays an important role in the degradation reaction. This article outlines a new method for improving the degradation efficiency of azo dyes and sulfides via biochar materials derived from widely sourced agricultural wastes.
Laboratory-Scale Research of Non-Catalyzed Supercritical Alcohol Process for Continuous Biodiesel Production
Authors: Hassan Aso A. , Smith Joseph D.
Published: March 2021

This work investigates the non-catalyzed supercritical methanol (SCM) process for continuous biodiesel production. The lab-scale setup was designed and used for biodiesel production in the temperature range of 520–650 K and 83–380 bar with an oil-to-methanol molar ratio ranging from 1:5 to 1:45. The experiments were performed in the coiled plug flow tubular reactor. The volumetric flow rate of the methanol/oil ranged from 0.1–10 mL/min. This work examines a new reactor technology involving preheating and pre-mixing of the methanol/oil mixture to reduce setup cost and increase biodiesel yield under the same reaction conditions. Work performed showed that FAME’s yield increased rapidly with temperature and pressure above the methanol critical points (i.e., 513 K and 79.5 bar). The best methyl-ester yield using this reaction technology was 91% at 590 K temperature and 351 bars with an oil-to-methanol ratio of 39 and a 15-min residence time. Furthermore, the kinetics of the free catalyst transesterification process was studied in supercritical methanol under different reaction conditions.
LTβR Signaling Controls Lymphatic Migration of Immune Cells
Authors: Piao Wenji , Kasinath Vivek , Saxena Vikas , Lakhan Ram , Iyyathurai Jegan , Bromberg Jonathan S.
Published: March 2021

The pleiotropic functions of lymphotoxin (LT)β receptor (LTβR) signaling are linked to the control of secondary lymphoid organ development and structural maintenance, inflammatory or autoimmune disorders, and carcinogenesis. Recently, LTβR signaling in endothelial cells has been revealed to regulate immune cell migration. Signaling through LTβR is comprised of both the canonical and non-canonical-nuclear factor κB (NF-κB) pathways, which induce chemokines, cytokines, and cell adhesion molecules. Here, we focus on the novel functions of LTβR signaling in lymphatic endothelial cells for migration of regulatory T cells (Tregs), and specific targeting of LTβR signaling for potential therapeutics in transplantation and cancer patient survival.
Trends in the Implementation of Advanced Plasmonic Materials in Optical Fiber Sensors (2010–2020)
Authors: Martínez-Hernández María Elena , Rivero Pedro J. , Goicoechea Javier , Arregui Francisco J.
Published: March 2021

In recent years, the interaction between light and metallic films have been proven to be a highly powerful tool for optical sensing applications. We have witnessed the development of highly sensitive commercial devices based on Surface Plasmon Resonances. There has been continuous effort to integrate this plasmonic sensing technology using micro and nanofabrication techniques with the optical fiber sensor world, trying to get better, smaller and cost-effective high performance sensing solutions. In this work, we present a review of the latest and more relevant scientific contributions to the optical fiber sensors field using plasmonic materials over the last decade. The combination of optical fiber technology with metallic micro and nanostructures that allow plasmonic interactions have opened a complete new and promising field of study. We review the main advances in the integration of such metallic micro/nanostructures onto the optical fibers, discuss the most promising fabrication techniques and show the new trends in physical, chemical and biological sensing applications.
The Spatial and Temporal Characteristics of Urban Heat Island Intensity: Implications for East Africa’s Urban Development
Authors: Li Xueqin , Stringer Lindsay C. , Dallimer Martin
Published: March 2021

Due to the combination of climate change and the rapid growth in urban populations in Africa, many urban areas are encountering exacerbated urban heat island (UHI) effects. It is important to understand UHI effects in order to develop suitable adaptation and mitigation strategies. However, little work has been done in this regard in Africa. In this study, we compared surface UHI (SUHI) effects between cities located in different climate zones in East Africa, investigating how they change, both spatially and temporally. We quantified the annual daytime and night-time SUHI intensities in the five most populated cities in East Africa in 2003 and 2017, and investigated the links to urban area size. We consider the possible drivers of SUHI change and consider the implication for future development, highlighting the role of factors such as topography and building/construction materials. We suggest that UHI mitigation strategies targeting East African cities may benefit from more comprehensive analyses of blue and green infrastructure as this offers potential opportunities to enhance human comfort in areas where UHI effects are highest. However, this needs careful planning to avoid increasing associated issues such as disease risks linked to a changing climate.
Oxovanadium(V/IV) Complexes as Redox Mediators for Biofuel Cells: Physical, Magnetic, and Electrochemical Characterization, DFT and Molecular Docking
Authors: Katsuumi Natsuki , Sehimi Hiba , Pradhan Sayantan , Kim Sanyobi , Haraguchi Tomoyuki , Akitsu Takashiro
Published: March 2021

Based on the potential redox and catalytic ability of oxovanadium complexes, our goal was to characterize the physical properties of two such complexes to be used as mediators for laccase. Computational studies, TD-DFT calculations and docking simulations were performed to elucidate the interaction between laccase and the two anionic complexes (aquabis(oxalato)oxidovanadate(IV) (1) and bis(oxalato)dioxidovanadate(V)) (2), respectively. Electrochemical measurements carried out on anion complexes of 1 and 2 docked into laccase were compared to laccase alone, showing changes in oxidation-reduction potential and current value, especially with the oxovanadium anion of 2. Since both internal tiny magnetic fields of ferromagnetic catalysts and external applied magnetic fields were found in previous investigations to constitute effective ways to improve the oxygen transfer rate, the magnetic susceptibility was measured. A valence change proneness was confirmed with higher valence for the oxovanadium anion of 2, which is in accordance with the electrochemical results.
Improving the Solubility of Aripiprazole by Multicomponent Crystallization
Authors: Zhou Qi , Tan Zhongchuan , Yang Desen , Tu Jiyuan , Wang Yezi , Zhang Ying , Liu Yanju , Gan Guoping
Published: March 2021

Aripiprazole (ARI) is a third-generation antipsychotic with few side effects but a poor solubility. Salt formation, as one common form of multicomponent crystals, is an effective strategy to improve pharmacokinetic profiles. In this work, a new ARI salt with adipic acid (ADI) and its acetone hemisolvate were obtained successfully, along with a known ARI salt with salicylic acid (SAL). Their comprehensive characterizations were conducted using X-ray diffraction and differential scanning calorimetry. The crystal structures of the ARI-ADI salt acetone hemisolvate and ARI-SAL salt were elucidated by single-crystal X-ray diffraction for the first time, demonstrating the proton transfer from a carboxyl group of acid to ARI piperazine. Theoretical calculations were also performed on weak interactions. Moreover, comparative studies on pharmaceutical properties, including powder hygroscopicity, stability, solubility, and the intrinsic dissolution rate, were carried out. The results indicated that the solubility and intrinsic dissolution rate of the ARI-ADI salt and its acetone hemisolvate significantly improved, clearly outperforming that of the ARI-SAL salt and the untreated ARI. The study presented one potential alternative salt of aripiprazole and provided a potential strategy to increase the solubility of poorly water-soluble drugs.
Artificial Intelligence in Differential Diagnostics of Meningitis: A Nationwide Study
Authors: Mentis Alexios-Fotios A. , Garcia Irene , Jiménez Juan , Paparoupa Maria , Xirogianni Athanasia , Papandreou Anastasia , Tzanakaki Georgina
Published: March 2021

Differential diagnosis between bacterial and viral meningitis is crucial. In our study, to differentiate bacterial vs. viral meningitis, three machine learning (ML) algorithms (multiple logistic regression (MLR), random forest (RF), and naïve-Bayes (NB)) were applied for the two age groups (0–14 and >14 years) of patients with meningitis by both conventional (culture) and molecular (PCR) methods. Cerebrospinal fluid (CSF) neutrophils, CSF lymphocytes, neutrophil-to-lymphocyte ratio (NLR), blood albumin, blood C-reactive protein (CRP), glucose, blood soluble urokinase-type plasminogen activator receptor (suPAR), and CSF lymphocytes-to-blood CRP ratio (LCR) were used as predictors for the ML algorithms. The performance of the ML algorithms was evaluated through a cross-validation procedure, and optimal predictions of the type of meningitis were above 95% for viral and 78% for bacterial meningitis. Overall, MLR and RF yielded the best performance when using CSF neutrophils, CSF lymphocytes, NLR, albumin, glucose, gender, and CRP. Also, our results reconfirm the high diagnostic accuracy of NLR in the differential diagnosis between bacterial and viral meningitis.
Comparison of Innovative and Traditional Cardiometabolic Indices in Estimating Atherosclerotic Cardiovascular Disease Risk in Adults
Authors: Huang Ya-Chin , Huang Jiun-Chi , Lin Chia-I , Chien Hsu-Han , Lin Yu-Yin , Wang Chao-Ling , Liang Fu-Wen , Dai Chia-Yen , Chuang Hung-Yi
Published: March 2021

This study aimed to investigate the performance of innovative and traditional cardiometabolic indices, including body mass index (BMI), waist circumference (WC), Chinese visceral adiposity index (CVAI), visceral adiposity index, lipid accumulation product, a body shape index (ABSI), body roundness index, conicity index (CI), triglyceride-glucose (TyG) index, TyG-BMI, and TyG-WC, in estimating atherosclerotic cardiovascular disease (ASCVD) risk in 3143 Taiwanese adults aged 20–79 years. Elevated 10-year ASCVD risk was defined as ≥7.5% using the Pooled Cohort Equations. The performance of different indices in estimating elevated ASCVD risk was assessed by receiver operating characteristic (ROC) curves. In multivariate-adjusted logistic regression analyses, all cardiometabolic indices (p-value < 0.001) were significantly associated with elevated ASCVD risk in both genders, except for ABSI and CI in women. In particular, CVAI had the largest area under the curve (AUC) in men (0.721) and women (0.883) in the ROC analyses. BMI had the lowest AUC in men (0.617), while ABSI had the lowest AUC in women (0.613). The optimal cut-off value for CVAI was 83.7 in men and 70.8 in women. CVAI performed best among various cardiometabolic indices in estimating elevated ASCVD risk. CVAI may be a reliable index for identifying people at increased risk of ASCVD.
GATA3 as an Adjunct Prognostic Factor in Breast Cancer Patients with Less Aggressive Disease: A Study with a Review of the Literature
Authors: Querzoli Patrizia , Pedriali Massimo , Rinaldi Rosa , Secchiero Paola , Rossi Paolo Giorgi , Kuhn Elisabetta
Published: March 2021

Background: GATA binding protein 3 (GATA3) expression is positively correlated with estrogen receptor (ER) expression, but its prognostic value as an independent factor remains unclear. Thus, we undertook the current study to evaluate the expression of GATA3 and its prognostic value in a large series of breast carcinomas (BCs) with long-term follow-up. Methods: A total of 702 consecutive primary invasive BCs resected between 1989 and 1993 in our institution were arranged in tissue microarrays, immunostained for ER, progesterone receptor (PR), ki-67, HER2, p53, and GATA3, and scored. Clinico-pathological data were retrospectively collected. Results: GATA3 was evaluable in 608 (87%) of the 702 cases; it was positive in 413 (68%) cases and negative in 195 (32%) cases. GATA3 positivity was significantly associated with lower grade (p < 0.0001), size (p = 0.0463), stage (p = 0.0049), ER+ (p < 0.0001), PR+ (p < 0.0001), HER2− (p = 0.0175), and p53 wild-type pattern (p < 0.0001). The median follow-up was 183 months, GATA3 positivity was associated with better overall survival (HR 0.70, p = 0.001), and its prognostic value was retained in a multivariate analysis. The association with better overall survival was stronger in patients with grade 1–2, pT1–2, pN0, stage I–II, ER+, PR+, ki-67 < 20%, HER2−, a wild-type p53 immunohistochemical pattern, and in luminal B BC. Conclusions: Our findings indicate that GATA3 is a positive prognostic marker in BC patients, especially in patients with biologically less aggressive BC. Incorporating GATA3 immunohistochemistry into routine practice could help further stratify BC patients for their risk.
CXCR4-Directed PET/CT in Patients with Newly Diagnosed Neuroendocrine Carcinomas
Authors: Weich Alexander , Werner Rudolf A. , Buck Andreas K. , Hartrampf Philipp E. , Serfling Sebastian E. , Scheurlen Michael , Wester Hans-Jürgen , Meining Alexander , Kircher Stefan , Higuchi Takahiro , Pomper Martin G. , Rowe Steven P. , Lapa Constantin , Kircher Malte
Published: March 2021

We aimed to elucidate the diagnostic potential of the C-X-C motif chemokine receptor 4 (CXCR4)-directed positron emission tomography (PET) tracer 68Ga-Pentixafor in patients with poorly differentiated neuroendocrine carcinomas (NEC), relative to the established reference standard 18F-FDG PET/computed tomography (CT). In our database, we retrospectively identified 11 treatment-naïve patients with histologically proven NEC, who underwent 18F-FDG and CXCR4-directed PET/CT for staging and therapy planning. The images were analyzed on a per-patient and per-lesion basis and compared to immunohistochemical staining (IHC) of CXCR4 from PET-guided biopsies. 68Ga-Pentixafor visualized tumor lesions in 10/11 subjects, while18F-FDG revealed sites of disease in all 11 patients. Although weak to moderate CXCR4 expression could be corroborated by IHC in 10/11 cases, 18F-FDG PET/CT detected significantly more tumor lesions (102 vs. 42; total lesions, n = 107; p < 0.001). Semi-quantitative analysis revealed markedly higher 18F-FDG uptake as compared to 68Ga-Pentixafor (maximum and mean standardized uptake values (SUV) and tumor-to-background ratios (TBR) of cancerous lesions, SUVmax: 12.8 ± 9.8 vs. 5.2 ± 3.7; SUVmean: 7.4 ± 5.4 vs. 3.1 ± 3.2, p < 0.001; and, TBR 7.2 ± 7.9 vs. 3.4 ± 3.0, p < 0.001). Non-invasive imaging of CXCR4 expression in NEC is inferior to the reference standard 18F-FDG PET/CT.
Asymptotic Information-Theoretic Detection of Dynamical Organization in Complex Systems
Authors: D’Addese Gianluca , Sani Laura , La Rocca Luca , Serra Roberto , Villani Marco
Published: March 2021

The identification of emergent structures in complex dynamical systems is a formidable challenge. We propose a computationally efficient methodology to address such a challenge, based on modeling the state of the system as a set of random variables. Specifically, we present a sieving algorithm to navigate the huge space of all subsets of variables and compare them in terms of a simple index that can be computed without resorting to simulations. We obtain such a simple index by studying the asymptotic distribution of an information-theoretic measure of coordination among variables, when there is no coordination at all, which allows us to fairly compare subsets of variables having different cardinalities. We show that increasing the number of observations allows the identification of larger and larger subsets. As an example of relevant application, we make use of a paradigmatic case regarding the identification of groups in autocatalytic sets of reactions, a chemical situation related to the origin of life problem.
Can a Questionnaire Be Useful for Assessing Reading Skills in Adults? Experiences with the Adult Reading Questionnaire among Incarcerated and Young Adults in Norway
Authors: Asbjørnsen Arve E. , Jones Lise Øen , Eikeland Ole Johan , Manger Terje
Published: March 2021

Background: Good screening tools can be of immense value in educational counselling for adults. We report two studies where we explored the factor structure and discriminative power of the Adult Reading Questionnaire (ARQ) in different samples of young adults at risk for reading impairments. Method: The ARQ was designed to screen for literacy skills with low resource requirement. The instrument includes 11 questions regarding reading and writing skills and 6 questions regarding attention deficits and hyperactivity. The first study included of 246 undergraduate students. One-third of the sample were under assessment of specific learning impairments/dyslexia. The second study included 1475 incarcerated adults, where 1 in 4 reported specific reading impairments. Results: Principal Component Analyses (PCA) with varimax rotation returned four components for the participants in Study 1: Reading skills, Reading habits, Attention, and Hyperactivity. For the incarcerated sample in Study 2, the analysis returned three components, as the Attention and Hyperactivity items were combined. Conclusion: The ARQ is useful for identifying individuals at risk for dyslexia with acceptable measures of sensitivity and specificity, as well as for identifying those who report difficulties with reading and writing but have not been assessed for their difficulties earlier. The increased prevalence of attention-deficit/hyperactivity disorder (ADHD) seen among incarcerated adults must be considered when screening for reading problems as it may confound the scores on reading questionnaires.
An Improved Approach for Object Proposals Generation
Authors: Deng Yao , Liang Huawei , Yi Zhiyan
Published: March 2021

The objectness measure is a significant and effective method used for generic object detection. However, several object detection methods can achieve accurate results by using more than 1000 candidate object proposals. In addition, the weight of each proposal is weak and also cannot distinguish object proposals. These weak proposals have brought difficulties to the subsequent analysis. To significantly reduce the number of proposals, this paper presents an improved generic object detection approach, which predicts candidate object proposals from more than 10,000 proposals. All candidate proposals can be divided, rather than preclassified, into three categories: entire object, partial object, and nonobject. These partial object proposals also display fragmentary information of the objectness feature, which can be used to reconstruct the object boundary. By using partial objectness to enhance the weight of the entire object proposals, we removed a huge number of useless proposals and reduced the space occupied by the true positive object proposals. We designed a neural network with lightweight computation to cluster the most possible object proposals with rerank and box regression. Through joint training, the lightweight network can share the features with other subsequent tasks. The proposed method was validated using experiments with the PASCAL VOC2007 dataset. The results showed that the proposed approach was significantly improved compared with the existing methods and can accurately detect 92.3% of the objects by using less than 200 proposals.
Fading Channel Models for mm-Wave Communications
Authors: Sánchez José David Vega , Urquiza-Aguiar Luis , Paredes Paredes Martha Cecilia
Published: March 2021

A realistic performance assessment of any wireless communication system requires the use of a fading channel model that reflects its main characteristics. The traditional Rayleigh and Nakagami-m models have been (and still are) the basis of most theoretical research on wireless technologies today, even for emerging technologies, such as millimeter-wave communications (mm-Wave). In this article, we show that the fluctuating multiple-ray (FMR) and κ-μ shadowed models had a better fit (i.e., lowest mean square error statistical test) to field measurements in outdoor environments at 28 GHz than the conventional channel models. Therefore, these generalized models are feasible alternatives that can be used as a benchmark when evaluating communication performance in mm-Wave scenarios.
A Hybrid Model for COVID-19 Monitoring and Prediction
Authors: Castillo Ossa Luis Fernando , Chamoso Pablo , Arango-López Jeferson , Pinto-Santos Francisco , Isaza Gustavo Adolfo , Santa-Cruz-González Cristina , Ceballos-Marquez Alejandro , Hernández Guillermo , Corchado Juan M.
Published: March 2021

COVID-19 is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and has a case-fatality rate of 2–3%, with higher rates among elderly patients and patients with comorbidities. Radiologically, COVID-19 is characterised by multifocal ground-glass opacities, even for patients with mild disease. Clinically, patients with COVID-19 present respiratory symptoms, which are very similar to other respiratory virus infections. Our knowledge regarding the SARS-CoV-2 virus is still very limited. These facts make it vitally important to establish mechanisms that allow to model and predict the evolution of the virus and to analyze the spread of cases under different circumstances. The objective of this article is to present a model developed for the evolution of COVID in the city of Manizales, capital of the Department of Caldas, Colombia, focusing on the methodology used to allow its application to other cases, as well as on the monitoring tools developed for this purpose. This methodology is based on a hybrid model which combines the population dynamics of the SIR model of differential equations with extrapolations based on recurrent neural networks. This combination provides self-explanatory results in terms of a coefficient that fluctuates with the restraint measures, which may be further refined by expert rules that capture the expected changes in such measures.
A Hardware-in-the-Loop-on-Chip Development System for Teaching and Development of Dynamic Systems
Authors: Jiang Wei , Sun Linfeng , Chen Yan , Ma Haining , Hashimoto Seiji
Published: March 2021

This paper proposes a low-cost on-chip Hardware-in-the-Loop (HIL) platform for teaching and fast prototyping of dynamic systems. A dual-core digital signal controller (DSC)-based solution is proposed for the HIL system. CPU core A, as the simulation engine, is dedicated to circuit and system simulation. The actuation and control logic are implemented in CPU core B, which is working as the control engine. Inter-processor communication is used to interchange variables between the CPUs. The digital-to-analog converter and digital outputs are used to send the duty cycle and system state variables to the oscilloscope for users’ visual feedback. Two typical systems with fast and slow dynamics are modeled and implemented in the simulation engine. Under the excitation generated by the control engine, system dynamics can be observed for studying purposes. Close-loop control for a buck converter is also demonstrated on the developed prototype, where both input voltage and load variations performance are tested. The test results indicate that the digital simulator can well emulate the average small signal model of a power converter in open-loop and close-loop scenario. Meanwhile, the control parameters can be modified for system performance evaluation and education purposes. The proposed low-cost HIL system can be easily applied to the engineering teaching as well as fast prototype development phase of product design.
Comparative Study on the “Soft Errors” Induced by Single-Event Effect and Space Electrostatic Discharge
Authors: Chen Rui , Chen Li , Han Jianwei , Wang Xuan , Liang Yanan , Ma Yingqi , Shangguan Shipeng
Published: March 2021

Single event effect (SEE) and space electrostatic discharge (SESD) are two important types of effects causing spacecraft anomalies. However, it is difficult to differentiate them to identify the root cause of on-orbit anomalies. This paper pioneers the comparative study of the “soft errors” induced by the SEE and SESD with a well-known static random-access memory (SRAM). The similarity and difference of the physical mechanisms between the “soft errors” induced by SEE and SESD are studied with the technology computer-aided design (TCAD) simulations. Meanwhile, the characteristics of the “soft errors” and the relation with external stimulus between SEE and SESD are further investigated with the pulsed laser SEE facility and SESD test system. The results showed that the similar appearances of “soft errors” can be generated by both SEE and SESD, while multiple-bit upset (MBU) has been observed only in SESD testing. In addition, in comparison to the random distribution of SEE sensitivity areas, the SESD sensitivity areas are in closer proximity to the power supply regions. The different symptoms in upsets can be used to identify the root causes of the spacecraft anomalies.
Object Classification with Roadside LiDAR Data Using a Probabilistic Neural Network
Authors: Zhang Jiancheng , Pi Rendong , Ma Xiaohong , Wu Jianqing , Li Hongtao , Yang Ziliang
Published: March 2021

Object classification is important information for different transportation areas. This research developed a probabilistic neural network (PNN) classifier for object classification using roadside Light Detection and Ranging (LiDAR). The objective was to classify the road user on the urban road into one of four classes: Pedestrian, bicycle, passenger car, and truck. Five features calculated from the point cloud generated from the roadside LiDAR were selected to represent the difference between different classes. A total of 2736 records (2062 records for training, and 674 records for testing) were manually marked for training and testing the PNN algorithm. The data were collected at three different sites representing different scenarios. The performance of the classification was evaluated by comparing the result of the PNN with those of the support vector machine (SVM) and the random forest (RF). The comparison results showed that the PNN can provide the results of classification with the highest accuracy among the three investigated methods. The overall accuracy of the PNN for object classification was 97.6% using the testing database. The errors in the classification results were also diagnosed. Discussions about the direction of future studies were also provided at the end of this paper.
Reconfigurable Multiband Operation for Wireless Devices Embedding Antenna Boosters
Authors: Anguera Jaume , Andújar Aurora , Leiva José Luis , Massó Oriol , Tonnesen Joakim , Rindalsholt Endre , Brandsegg Rune , Gaddi Roberto
Published: March 2021

Wireless devices such as smart meters, trackers, and sensors need connections at multiple frequency bands with low power consumption, thus requiring multiband and efficient antenna systems. At the same time, antennas should be small to easily fit in the scarce space existing in wireless devices. Small, multiband, and efficient operation is addressed here with non-resonant antenna elements, featuring volumes less than 90 mm3 for operating at 698–960 MHz as well as some bands in a higher frequency range of 1710–2690 MHz. These antenna elements are called antenna boosters, since they excite currents on the ground plane of the wireless device and do not rely on shaping complex geometric shapes to obtain multiband behavior, but rather the design of a multiband matching network. This design approach results in a simpler, easier, and faster method than creating a new antenna for every device. Since multiband operation is achieved through a matching network, frequency bands can be configured and optimized with a reconfigurable matching network. Two kinds of reconfigurable multiband architectures with antenna boosters are presented. The first one includes a digitally tunable capacitor, and the second one includes radiofrequency switches. The results show that antenna boosters with reconfigurable architectures feature multiband behavior with very small sizes, compared with other prior-art techniques.
Overview of Sustainable Aviation Fuels with Emission Characteristic and Particles Emission of the Turbine Engine Fueled ATJ Blends with Different Percentages of ATJ Fuel
Authors: Kurzawska Paula , Jasiński Remigiusz
Published: March 2021

The following article focuses on sustainable aviation fuels, which include first and second generation biofuels and other non-biomass fuels that meet most of environmental, operational and physicochemical requirements. Several of the requirements for sustainable aviation fuels are discussed in this article. The main focus was on researching the alcohol-to-jet (ATJ) alternative fuel. The tests covered the emission of harmful gaseous compounds with the Semtech DS analyzer, as well as the number and mass concentration of particles of three fuels: reference fuel Jet A-1, a mixture of Jet A-1 and 30% of ATJ fuel, and mixture of Jet A-1 and 50% of ATJ fuel. The number concentration of particles allowed us to calculate, inter alia, the corresponding particle number index and particle mass index. The analysis of the results made it possible to determine the effect of the content of alternative fuel in a mixture with conventional fuel on the emission of harmful exhaust compounds and the concentration of particles. One of the main conclusion is that by using a 50% blend of ATJ and Jet A-1, the total number and mass of particulate matter at high engine loads can be reduced by almost 18% and 53%, respectively, relative to pure Jet A-1 fuel.
Positive Correlations between Short-Term and Average Long-Term Fluctuations in Wind Power Output
Authors: Urabe Chiyori T. , Saitou Tetsuo , Kataoka Kazuto , Ikegami Takashi , Ogimoto Kazuhiko
Published: March 2021

Wind power has been increasingly deployed in the last decade to decarbonize the electricity sector. Wind power output changes intermittently depending on weather conditions. In electrical power systems with high shares of variable renewable energy sources, such as wind power, system operators aim to respond flexibly to fluctuations in output. Here, we investigated very short-term fluctuations, short-term fluctuations (STFs), and long-term fluctuations (LTFs) in wind power output by analyzing historical output data for two northern and one southern balancing areas in Japan. We found a relationship between STFs and the average LTFs. The percentiles of the STFs in each month are approximated by linear functions of the monthly average LTFs. Furthermore, the absolute value of the slope of this function decreases with wind power capacity in the balancing area. The LTFs reflect the trend in wind power output. The results indicate that the flexibility required for power systems can be estimated based on wind power predictions. This finding could facilitate the design of the balancing market in Japan.
A Hybrid Hilbert-Huang Method for Monitoring Distorted Time-Varying Waveforms
Authors: Plamanescu Radu , Dumitrescu Ana-Maria , Albu Mihaela , Suryanarayanan Siddharth
Published: March 2021

The electric power systems together with the entire energy sector are rapidly evolving towards a low-carbon, secure, and competitive economy facing revolutionary transformations from technical structure to economic value chain. Pathways to achieve sustainability led to the development of new technologies, accommodation of larger shares of unpredictable and stochastic electricity transfer from sources to end-users without loss of reliability, new business models and services, data management, and so on. The new technologies and incentives for local energy communities along with large development of microgrids are main forces driving the evolution of the low voltage energy sector changing the context and paradigm of rigid contractual binding between utilities and end-user customers (now progressing to flexible prosumers with generation and storage capabilities). The flexibility and operation of a prosumer can be enhanced by a non-intrusive time-frequency analysis of distorted power quality waveforms for both generation and demand at the point of common connection. Therefore, it becomes of importance to discriminate among successive quasi-steady-state operation of a given local system using only the aggregated waveforms information available in the PCC. This paper focuses on the Hilbert–Huang method with modifications such as empirical mode decomposition improved with masking signals based on the Fast Fourier Transform, Hilbert spectral analysis, and a post-processing method for separating components and their amplitudes and frequencies within distorted power signals for a low-voltage prosumer operation. The method is used for a time-frequency-magnitude representation with promising localization capabilities enabling efficient operation for prosumers.
An Improved Artificial Jellyfish Search Optimizer for Parameter Identification of Photovoltaic Models
Authors: Abdel-Basset Mohamed , Mohamed Reda , Chakrabortty Ripon K. , Ryan Michael J. , El-Fergany Attia
Published: March 2021

The optimization of photovoltaic (PV) systems relies on the development of an accurate model of the parameter values for the solar/PV generating units. This work proposes a modified artificial jellyfish search optimizer (MJSO) with a novel premature convergence strategy (PCS) to define effectively the unknown parameters of PV systems. The PCS works on preserving the diversity among the members of the population while accelerating the convergence toward the best solution based on two motions: (i) moving the current solution between two particles selected randomly from the population, and (ii) searching for better solutions between the best-so-far one and a random one from the population. To confirm its efficacy, the proposed method is validated on three different PV technologies and is being compared with some of the latest competitive computational frameworks. The numerical simulations and results confirm the dominance of the proposed algorithm in terms of the accuracy of the final results and convergence rate. In addition, to assess the performance of the proposed approach under different operation conditions for the solar cells, two additional PV modules (multi-crystalline and thin-film) are investigated, and the demonstrated scenarios highlight the utility of the proposed MJSO-based methodology.
Numerical Study of Hydrogen Auto-Ignition Process in an Isotropic and Anisotropic Turbulent Field
Authors: Wawrzak Agnieszka , Tyliszczak Artur
Published: March 2021

The physical mechanisms underlying the dynamics of the flame kernel in stationary isotropic and anisotropic turbulent field are studied using large eddy simulations (LES) combined with a pdf approach method for the combustion model closure. Special attention is given to the ignition scenario, ignition delay, size and shape of the flame kernel among different turbulent regimes. Different stages of ignition are analysed for various levels of the initial velocity fluctuations and turbulence length scales. Impact of these parameters is found small for the ignition delay time but turns out to be significant during the flame kernel propagation phase and persists up to the stabilisation stage. In general, it is found that in the isotropic conditions, the flame growth and the rise of the maximum temperature in the domain are more dependent on the initial fluctuations level and the length scales. In the anisotropic regimes, these parameters have a substantial influence on the flame only during the initial phase of its development.
Modulation Variants in DC Circuits of Power Rectifier Systems with Improved Quality of Energy Conversion—Part I
Authors: Pajchrowski Tomasz , Krystkowiak Michał , Matecki Dominik
Published: March 2021

The article presents various concepts of three-phase power rectifiers with improved quality of converted electric power. This effect is obtained by modulating the currents in the DC output circuits of the rectifiers by means of power electronics controlled voltage or current sources, working as a so-called voltage or current modulators. For further quality improvement of the grid currents of the analyzed systems, it was proposed to use an additional controlled current source connected in parallel to the DC load, hereinafter referred to as a supporting system. The original elaborated method of controlling this source (supporting system) was presented. The main goal of the work was to propose a solution for an effective method of improving the quality of energy conversion in rectifier systems, especially high power ones, by using controlled current sources in DC circuits, operating as the power electronics current modulator and the supporting system.
Biochemical Conversion of Lignocellulosic Biomass from Date Palm of Phoenix dactylifera L. into Ethanol Production
Authors: Antit Yousra , Olivares Inmaculada , Hamdi Moktar , Sánchez Sebastián
Published: March 2021

Cellulosic fibers from date palm are among the most promising lignocellulose feedstock for biorefinery purposes. The world production is between 1.9 and 2.4 million t/year. Initially, a pretreatment with dilute-sulphuric acid of these fibers was performed using a response surface methodology, with temperature and process time as factors. The aim is to produce bioethanol from young and old fibers from date palm, Phoenix dactylifera L. Optimal thermochemical pretreatment conditions for both fibers palms were 220 °C in hydrothermal conditions (without acid); in these conditions pretreated young fibers presented a maximum content in holocelluloses of 45.18% and old fibers 61.97%. Subsequently, during the enzymatic hydrolysis a maximum yield of total reducing sugars (TRS) was reached, 46.32 g/100 g for pretreated dry young fibers and 48.54 g/100 g for pretreated dry old fibers. After enzymatic saccharification, hydrolysates were fermented by Pachysolen tannophilus (ATCC 32691) to ethanol, reaching yields (YE/TRS) of 37.94 g ethanol/100 g of TRS for young fibers and 35.84 g ethanol/100 g of TRS for old fibers. Globally, considering the full process, in the fermentation of the hydrolysates, a yield (YE) of 10.64 g ethanol/100 g of dry young fibers and 10.88 g ethanol/100 g of dry old fibers was reached.
Optimization of a Gate Distribution Layout to Compensate the Current Imbalance Generated by the 3D Geometry of a Railway Inverter
Authors: Nakahata-Medrado Andressa , Schanen Jean-Luc , Guichon Jean-Michel , Jeannin Pierre-Olivier , Batista Emmanuel , Desportes Guillaume
Published: March 2021

The impact of the stray inductances originated from interconnects in power electronics becomes crucial with the next generation of SiC devices. This paper shows that the existing layout of a railway inverter, operating with Si IGBTs already exhibits a dynamic current imbalance between paralleled modules. This will not allow using this geometry with SiC MOSFETs. A complete investigation of the electromagnetic origin of this issue has been performed. A generic circuit model has been proposed to establish a cabling rule to design a Gate Distribution Printed Circuit Board (PCB) in such a way that it compensates the power dissymmetry. An optimization strategy has been used to obtain a new geometry of this PCB, which has been validated with a time domain simulation.
Analysis of Heat Exchange Rate for Low-Depth Modular Ground Heat Exchanger through Real-Scale Experiment
Authors: Kim Kwonye , Kim Jaemin , Nam Yujin , Lee Euyjoon , Kang Eunchul , Entchev Evgueniy
Published: March 2021

A ground source heat pump system is a high-performance technology used for maintaining a stable underground temperature all year-round. However, the high costs for installation, such as for boring and drilling, is a drawback that prevents the system to be rapidly introduced into the market. This study proposes a modular ground heat exchanger (GHX) that can compensate for the disadvantages (such as high-boring/drilling costs) of the conventional vertical GHX. Through a real-scale experiment, a modular GHX was manufactured and buried at a depth of 4 m below ground level; the heat exchange rate and the change in underground temperatures during the GHX operation were tracked and calculated. The average heat exchanges rate was 78.98 W/m and 88.83 W/m during heating and cooling periods, respectively; the underground temperature decreased by 1.2 °C during heat extraction and increased by 4.4 °C during heat emission, with the heat pump (HP) working. The study showed that the modular GHX is a cost-effective alternative to the vertical GHX; further research is needed for application to actual small buildings.
Antioxidant Properties of Pecan Shell Bioactive Components of Different Cultivars and Extraction Methods
Authors: Cason Cameron , Yemmireddy Veerachandra K. , Moreira Juan , Adhikari Achyut
Published: March 2021

Pecan shells are a rich source of various bioactive compounds with potential antioxidant and antimicrobial properties. This study investigated the effect of pecan variety and method extraction on the antioxidant property of shell extracts. Twenty different varieties of pecan shells were subjected to either aqueous or ethanolic extraction and were examined for total phenolics and antiradical activity. The phenolic content and antiradical activity of shell extracts were significantly (p < 0.05) varied with different pecan cultivars. The total phenolic content of ethanol extracts ranged from 304.2 (Caddo) to 153.54 (Cherokee) mg GAE g−1 of dry extract and was significantly greater (p < 0.05) than those obtained by aqueous extraction. The antiradical activity of ethanol extracts ranged from 840.6 (Maramec) to 526.74 (Caper Fear) mg TE g−1, while aqueous extracts ranged from 934.9 (Curtis) to 468.3 (Elliot) mg TE g−1. Chemical profiling of the crude and acid hydrolyzed extracts was performed by reverse phase high performance liquid chromatography and flow injection electrospray ionization mass spectrometry. Lignin degradation products such as lignols, dilignols, trilignols, and oligolignols were found to be the major components of tested extracts. Phenolic content and antiradical activity of pecan shell extracts are significantly varied with cultivars and methods of extraction.