bluuebunny/crossref_metadata_2025 huggingface dataset:
Metal-Support Synergy of Supported Gold Nanoclusters in Selective Oxidation of Alcohols
Authors: Liu Lu , Li Huayin , Tan Yuan , Chen Xingkun , Lin Ronghe , Yang Wenshao , Huang Chuanqi , Wang Saisai , Wang Xuepeng , Liu Xiao Yan , Zhao Min , Ding Yunjie
Published: January 2020

Gold catalysts have been reported to exhibit good performance in aerobic oxidation of alcohols, but the intrinsic origin of the catalytic reactivity is still illusive. The catalyst preparation method, the morphology of the gold particles, and even the support might be key factors that determine the activity. Here, we prepared a series of gold catalysts with different supports, i.e., the hydrotalcite (HT), ZnO, MgO, Al2O3, and SiO2, by using the atomically controlled Au25 nanoclusters (NCs) as the gold precursor. The characterization results of the X-ray diffraction (XRD), UV-vis and transmission electron microscopy (TEM) show that the gold particles were mostly uniformly distributed on the supports, with a mean particle size within 3 nm. In aerobic oxidation of benzyl alcohol, the MgAl-HT- and Al2O3-supported Au25 NCs display good performances, with turnover frequency (TOF) values of ~2927 and 2892 h−1, respectively, whereas the SiO2-, MgO-, and ZnO-supported analogues show much inferior activity. The high resolution TEM and X-ray photoelectron spectra (XPS) results suggest that the interactions between gold and the supports in different samples are differing, which influences the morphology and the nature of gold. Our results further point to the importance of acid-base property of the support and the metal-support synergy rather than the gold particle size alone in achieving high-performance in selective alcohol oxidation. Moreover, this work provided a good way to design gold catalysts with controllable sizes that is crucial for understanding the reaction process in aerobic oxidation of alcohol.
Parsing the IL-37-Mediated Suppression of Inflammasome Function
Authors: Rudloff Ina , Ung Holly K. , Dowling Jennifer K. , Mansell Ashley , D’Andrea Laura , Ellisdon Andrew M. , Whisstock James C. , Berger Philip J. , Nold-Petry Claudia A. , Nold Marcel F.
Published: January 2020

Interleukin (IL)-37 is a member of the IL-1 family of cytokines. Although its broad anti-inflammatory properties are well described, the effects of IL-37 on inflammasome function remain poorly understood. Performing gene expression analyses, ASC oligomerization/speck assays and caspase-1 assays in bone marrow-derived macrophages (BMDM), and employing an in vivo endotoxemia model, we studied how IL-37 affects the expression and maturation of IL-1β and IL-18, inflammasome activation, and pyroptosis in detail. IL-37 inhibited IL-1β production by NLRP3 and AIM2 inflammasomes, and IL-18 production by the NLRP3 inflammasome. This inhibition was partially attributable to effects on gene expression: whereas IL-37 did not affect lipopolysaccharide (LPS)-induced mRNA expression of Il18 or inflammasome components, IL-37-transgenic BMDM displayed an up to 83% inhibition of baseline and LPS-stimulated Il1b compared to their wild-type counterparts. Importantly, we observed that IL-37 suppresses nigericin- and silica-induced ASC oligomerization/speck formation (a step in inflammasome activation and subsequent caspase-1 activation), and pyroptosis (−50%). In mice subjected to endotoxemia, IL-37 inhibited plasma IL-1β (−78% compared to wild-type animals) and IL-18 (−61%). Thus, our study adds suppression of inflammasome activity to the portfolio of anti-inflammatory pathways employed by IL-37, highlighting this cytokine as a potential tool for treating inflammasome-driven diseases.
Study of Melatonin as Preventive Agent of Gastrointestinal Damage Induced by Sodium Diclofenac
Authors: Sánchez Aroha B. , Clares Beatriz , Rodríguez-Lagunas María J. , Fábrega María J. , Calpena Ana C.
Published: January 2020

Safety profile of nonsteroidal anti-inflammatory drugs (NSAIDs) has been widely studied and both therapeutic and side effects at the gastric and cardiovascular level have been generally associated with the inhibitory effect of isoform 1 (COX-1) and 2 (COX-2) cyclooxygenase enzymes. Now there are evidences of the involvement of multiple cellular pathways in the NSAIDs-mediated-gastrointestinal (GI) damage related to enterocyte redox state. In a previous review we summarized the key role of melatonin (MLT), as an antioxidant, in the inhibition of inflammation pathways mediated by oxidative stress in several diseases, which makes us wonder if MLT could minimize GI NSAIDs side effects. So, the aim of this work is to study the effect of MLT as preventive agent of GI injury caused by NSAIDs. With this objective sodium diclofenac (SD) was administered alone and together with MLT in two experimental models, ex vivo studies in pig intestine, using Franz cells, and in vivo studies in mice where stomach and intestine were studied. The histological evaluation of pig intestine samples showed that SD induced the villi alteration, which was prevented by MLT. In vivo experiments showed that SD altered the mice stomach mucosa and induced tissue damage that was prevented by MLT. The evaluation by quantitative reverse transcription PCR (RT-qPCR) of two biochemical markers, COX-2 and iNOS, showed an increase of both molecules in less injured tissues, suggesting that MLT promotes tissue healing by improving redox state and by increasing iNOS/NO that under non-oxidative condition is responsible for the maintenance of GI-epithelium integrity, increasing blood flow and promoting angiogenesis and that in presence of MLT, COX-2 may be responsible for wound healing in enterocyte. Therefore, we found that MLT may be a preventive agent of GI damages induced by NSAIDs.
Missing Information from the Estrogen Receptor Puzzle: Where Are They Localized in Bull Reproductive Tissues and Spermatozoa?
Authors: Antalikova Jana , Secova Petra , Horovska Lubica , Krejcirova Romana , Simonik Ondrej , Jankovicova Jana , Bartokova Michaela , Tumova Lucie , Manaskova-Postlerova Pavla
Published: January 2020

Estrogens are steroid hormones that affect a wide range of physiological functions. The effect of estrogens on male reproductive tissues and sperm cells through specific receptors is essential for sperm development, maturation, and function. Although estrogen receptors (ERs) have been studied in several mammalian species, including humans, they have not yet been described in bull spermatozoa and reproductive tissues. In this study, we analyzed the presence of all types of ERs (ESR1, ESR2, and GPER1) in bull testicular and epididymal tissues and epididymal and ejaculated spermatozoa, and we characterize them here for the first time. We observed different localizations of each type of ER in the sperm head by immunofluorescent microscopy. Additionally, using a selected polyclonal antibody, we found that each type of ER in bull sperm extracts had two isoforms with different molecular masses. The detailed detection of ERs is a prerequisite not only for understanding the effect of estrogen on all reproductive events but also for further studying the negative effect of environmental estrogens (endocrine disruptors) on processes that lead to fertilization.
Are Liver Pericytes Just Precursors of Myofibroblasts in Hepatic Diseases? Insights from the Crosstalk between Perivascular and Inflammatory Cells in Liver Injury and Repair
Authors: da Silva Meirelles Lindolfo , Marson Renan Fava , Solari Maria Inês Gonzalez , Nardi Nance Beyer
Published: January 2020

Cirrhosis, a late form of liver disease, is characterized by extensive scarring due to exacerbated secretion of extracellular matrix proteins by myofibroblasts that develop during this process. These myofibroblasts arise mainly from hepatic stellate cells (HSCs), liver-specific pericytes that become activated at the onset of liver injury. Consequently, HSCs tend to be viewed mainly as myofibroblast precursors in a fibrotic process driven by inflammation. Here, the molecular interactions between liver pericytes and inflammatory cells such as macrophages and neutrophils at the first moments after injury and during the healing process are brought into focus. Data on HSCs and pericytes from other tissues indicate that these cells are able to sense pathogen- and damage-associated molecular patterns and have an important proinflammatory role in the initial stages of liver injury. On the other hand, further data suggest that as the healing process evolves, activated HSCs play a role in skewing the initial proinflammatory (M1) macrophage polarization by contributing to the emergence of alternatively activated, pro-regenerative (M2-like) macrophages. Finally, data suggesting that some HSCs activated during liver injury could behave as hepatic progenitor or stem cells will be discussed.
Cytokine Directed Chondroblast Trans-Differentiation: JAK Inhibition Facilitates Direct Reprogramming of Fibroblasts to Chondroblasts
Authors: Cota Perla , Helmi Summer A. , Hsu Charlie , Rancourt Derrick E.
Published: January 2020

Osteoarthritis (OA) is a degenerative disease of the hyaline articular cartilage. This disease is progressive and may lead to disability. Researchers proposed many regenerative approaches to treat osteoarthritis, including stem cells. Trans-differentiation of a fully differentiated cell state directly into another different differentiated cell state avoids the disadvantages of fully reprogramming cells to induced pluripotent stem cells (iPSCs) in terms of faster reprogramming of the needed cells. Trans-differentiation also reduces the risk of tumor formation by avoiding the iPSC state. OSKM factors (Oct4, Sox2, Klf4, and cMyc) accompanied by the JAK-STAT pathway inhibition, followed by the introduction of specific differentiation factors, directly reprogrammed mouse embryonic fibroblasts to chondroblasts. Our results showed the absence of intermediate induced pluripotent stem cell formation. The resulting aggregates showed clear hyaline and hypertrophic cartilage. Tumor formation was absent in sub-cutaneous capsules transplanted in SCID mice.
Photocatalytic Activity for Hydrogen Evolution of Heteroatom-Doped SrTiO3 Prepared Using a Graphitic-Carbon Nitride Nanosheet
Authors: Ikeue Keita , Yamamoto Yuta , Suzuki Masashige
Published: January 2020

We developed a novel method to synthesize a visible-light-responsible photocatalyst from a composite of SrTiO3 and a graphitic carbon nitride (g-C3N4) nanosheet. Heteroatoms were successfully doped into a lattice of SrTiO3 by mild calcination of a composite that the g-C3N4 nanosheet adsorbed on to the SrTiO3 surface. The absorption edge in the UV-Vis absorption spectrum of the doped sample was shifted to a longer wavelength region. The photocatalytic activity of the doped sample under UV light irradiation was higher than those of both pristine SrTiO3 and the g-C3N4 nanosheet, suggesting that the photocatalytic property of SrTiO3 was enhanced by doping. The doped sample showed photocatalytic activity under visible light irradiation (>420 nm), which was enhanced by Pt loading.
Improvement in Slag Resistance of No-Cement Refractory Castables by Matrix Design
Authors: Peng Hong , Liu Jun , Wang Qinghu , Li Yawei
Published: January 2020

The corrosion resistance of spinel containing cement bonded castables has been extensively investigated in the past. However, corrosion of no-cement refractory castables (NCC) has not been widely studied since the use of NCC has been relatively limited up till now. This paper focuses on the slag resistance of NCCs, and the often-used spinel containing low cement castable (LCC) is used as the reference. Three different NCC binders were designed: (i) Al2O3 + MgO (alumina bond), in situ spinel formation; (ii) Al2O3 + SiO2 (microsilica-gel bond), mullite formation; and (iii) Al2O3 + MgO + SiO2 (MgO-SiO2 bond). Slag resistance tests were conducted using the static crucible method with ladle slag. The corrosion mechanisms were studied by means of Scanning Electron Microscopy (SEM/EDS), X-ray Diffraction (XRD), and thermodynamic simulations. The results confirmed that the mineral phases, microstructure, and liquid formation at a high temperature of the refractory materials had a strong impact on the corrosion resistance. The slag resistance was significantly improved when the cement was replaced by the cement-free binders.
Pancreatitis in A Patient with Cystic Fibrosis Taking Ivacaftor
Authors: Petrocheilou Argyri , Kaditis Athanasios G. , Loukou Ioanna
Published: January 2020

Pancreatitis is rare in pancreatic insufficient cystic fibrosis patients. While pancreatic insufficiency has been considered irreversible until now, in the current era of new therapies with modulators of the Cystic Fibrosis Transmembrane Regulator CFTR channel, there are reports of improvement of pancreatic exocrine function. We describe the case of an adolescent with cystic fibrosis who developed pancreatitis after the partial recovery of pancreatic function while taking ivacaftor. This case adds to the limited body of evidence that CFTR modulators lead to the improvement of pancreatic exocrine function in cystic fibrosis.
The Effects of Historical Housing Policies on Resident Exposure to Intra-Urban Heat: A Study of 108 US Urban Areas
Authors: Hoffman Jeremy S. , Shandas Vivek , Pendleton Nicholas
Published: January 2020

The increasing intensity, duration, and frequency of heat waves due to human-caused climate change puts historically underserved populations in a heightened state of precarity, as studies observe that vulnerable communities—especially those within urban areas in the United States—are disproportionately exposed to extreme heat. Lacking, however, are insights into fundamental questions about the role of historical housing policies in cauterizing current exposure to climate inequities like intra-urban heat. Here, we explore the relationship between “redlining”, or the historical practice of refusing home loans or insurance to whole neighborhoods based on a racially motivated perception of safety for investment, with present-day summertime intra-urban land surface temperature anomalies. Through a spatial analysis of 108 urban areas in the United States, we ask two questions: (1) how do historically redlined neighborhoods relate to current patterns of intra-urban heat? and (2) do these patterns vary by US Census Bureau region? Our results reveal that 94% of studied areas display consistent city-scale patterns of elevated land surface temperatures in formerly redlined areas relative to their non-redlined neighbors by as much as 7 °C. Regionally, Southeast and Western cities display the greatest differences while Midwest cities display the least. Nationally, land surface temperatures in redlined areas are approximately 2.6 °C warmer than in non-redlined areas. While these trends are partly attributable to the relative preponderance of impervious land cover to tree canopy in these areas, which we also examine, other factors may also be driving these differences. This study reveals that historical housing policies may, in fact, be directly responsible for disproportionate exposure to current heat events.
Surface Morphological Features of Molybdenum Irradiated by a Single Laser Pulse
Authors: Montanari Roberto , Pakhomova Ekaterina , Rossi Riccardo , Richetta Maria , Varone Alessandra
Published: January 2020

Molybdenum (Mo) is considered a plasma facing material alternative to tungsten (W) for manufacturing the divertor armours of International Thermonuclear Experimental Reactor (ITER). Transient thermal loads of high energy occurring in a tokamak during the service life have been simulated through a single laser pulse delivered by a Nd:YAG/Glass laser, and the effects have then been examined through scanning electron microscopy (SEM) observations. An erosion crater forms in correspondence with the laser spot due to the vaporization and melting of the metal, while all around a network of cracks induced by thermal stresses is observed. The findings have been compared to results of similar experiments on W and literature data. The morphology of the crater and the surrounding area is different from that of W: the crater is larger and shallower in the case of Mo, while its walls are characterized by long filaments, not observed in W, because the lower viscosity and surface tension of Mo allow an easier flow of the liquid metal. Most importantly, the volume of Mo ablated from the surface by the single laser pulse is about ten times that of W. This critical aspect is of particular relevance and leads us to conclude that W remains the best solution for manufacturing the armours of the ITER divertor.
Inhomogeneity and Segregation Effect in the Surface Layer of Fe-Doped SrTiO3 Single Crystals
Authors: Wojtyniak Marcin , Balin Katarzyna , Szade Jacek , Szot Krzysztof
Published: January 2020

The effect of Fe doping on SrTiO3 single crystals was investigated in terms of crystal and electronic structure over a wide temperature range in both oxidizing and reducing conditions. The electrical properties were thoroughly studied with a special focus on the resistive switching phenomenon. Contrary to the undoped SrTiO3 crystals, where isolated filaments are responsible for resistive switching, the iron-doped crystals showed stripe-like conducting regions at the nanoscale. The results showed a non-uniform Fe distribution of as-received crystals and the formation of new phases in the surface layer of reduced/oxidized samples. The oxidation procedure led to a separation of Ti(Fe) and Sr, while the reduction resulted in the tendency of Fe to agglomerate and migrate away from the surface as seen from the time of flight mass spectroscopy measurements. Moreover, a clear presence of Fe-rich nano-filament in the reduced sample was found.
The Panel of 12 Cell-Free MicroRNAs as Potential Biomarkers in Prostate Neoplasms
Authors: Konoshenko Maria Yu. , Lekchnov Evgeniy A. , Bryzgunova Olga E. , Zaporozhchenko Ivan A. , Yarmoschuk Sergey V. , Pashkovskaya Oksana A. , Pak Svetlana V. , Laktionov Pavel P.
Published: January 2020

Prostate cancer is a global biological, medical, and social issue aggravated by the lack of reliable, highly specific, and sensitive non-invasive tests for diagnosis and staging of prostate cancer. One prospective source of biomarkers are the cell-free miRNAs present in various biological fluids. In the present study, we validated the diagnostic potential of cell-free miRNAs: miR-19b, miR-22, miR-92a, miR-378, miR-425, miR-30e, miR-31, miR-125b, miR-200b, miR-205, miR-375, and miR-660; we estimated the required sample size and the minimal miRNA set for a subsequent large-scale validation study. Relative expression of 12 miRNA combined in 31 ratios was investigated in three fractions of biological fluids (urine extracellular vesicles, clarified urine, and plasma) obtained from patients with prostate cancer (n = 10), benign prostate hyperplasia (n = 8), and healthy volunteers (n = 11). Eight of the miRNAs found in urine vesicles (miR-19b, miR-30e, miR-31, miR-92a, miR-125, miR-200, miR-205, and miR-660) showed great promise and when combined into six ratios (miR-125b/miR-30e, miR-200/miR-30e, miR-205/miR-30e, miR-31/miR-30e, miR-660/miR-30e, and miR-19b/miR-92a) could classify patients with prostate cancer, benign prostate hyperplasia, and healthy donors with 100% specificity, 100% sensitivity, and with a high degree of reliability for most donors.
(Generalized) Maximum Cumulative Direct, Residual, and Paired Φ Entropy Approach
Authors: Klein Ingo , Doll Monika
Published: January 2020

A distribution that maximizes an entropy can be found by applying two different principles. On the one hand, Jaynes (1957a,b) formulated the maximum entropy principle (MaxEnt) as the search for a distribution maximizing a given entropy under some given constraints. On the other hand, Kapur (1994) and Kesavan and Kapur (1989) introduced the generalized maximum entropy principle (GMaxEnt) as the derivation of an entropy for which a given distribution has the maximum entropy property under some given constraints. In this paper, both principles were considered for cumulative entropies. Such entropies depend either on the distribution function (direct), on the survival function (residual) or on both (paired). We incorporate cumulative direct, residual, and paired entropies in one approach called cumulative Φ entropies. Maximizing this entropy without any constraints produces an extremely U-shaped (=bipolar) distribution. Maximizing the cumulative entropy under the constraints of fixed mean and variance tries to transform a distribution in the direction of a bipolar distribution, as far as it is allowed by the constraints. A bipolar distribution represents so-called contradictory information, which is in contrast to minimum or no information. In the literature, to date, only a few maximum entropy distributions for cumulative entropies have been derived. In this paper, we extended the results to well known flexible distributions (like the generalized logistic distribution) and derived some special distributions (like the skewed logistic, the skewed Tukey λ and the extended Burr XII distribution). The generalized maximum entropy principle was applied to the generalized Tukey λ distribution and the Fechner family of skewed distributions. Finally, cumulative entropies were estimated such that the data was drawn from a maximum entropy distribution. This estimator will be applied to the daily S&P500 returns and time durations between mine explosions.
Deep Learning-Based Stacked Denoising and Autoencoder for ECG Heartbeat Classification
Authors: Nurmaini Siti , Darmawahyuni Annisa , Sakti Mukti Akhmad Noviar , Rachmatullah Muhammad Naufal , Firdaus Firdaus , Tutuko Bambang
Published: January 2020

The electrocardiogram (ECG) is a widely used, noninvasive test for analyzing arrhythmia. However, the ECG signal is prone to contamination by different kinds of noise. Such noise may cause deformation on the ECG heartbeat waveform, leading to cardiologists’ mislabeling or misinterpreting heartbeats due to varying types of artifacts and interference. To address this problem, some previous studies propose a computerized technique based on machine learning (ML) to distinguish between normal and abnormal heartbeats. Unfortunately, ML works on a handcrafted, feature-based approach and lacks feature representation. To overcome such drawbacks, deep learning (DL) is proposed in the pre-training and fine-tuning phases to produce an automated feature representation for multi-class classification of arrhythmia conditions. In the pre-training phase, stacked denoising autoencoders (DAEs) and autoencoders (AEs) are used for feature learning; in the fine-tuning phase, deep neural networks (DNNs) are implemented as a classifier. To the best of our knowledge, this research is the first to implement stacked autoencoders by using DAEs and AEs for feature learning in DL. Physionet’s well-known MIT-BIH Arrhythmia Database, as well as the MIT-BIH Noise Stress Test Database (NSTDB). Only four records are used from the NSTDB dataset: 118 24 dB, 118 −6 dB, 119 24 dB, and 119 −6 dB, with two levels of signal-to-noise ratio (SNRs) at 24 dB and −6 dB. In the validation process, six models are compared to select the best DL model. For all fine-tuned hyperparameters, the best model of ECG heartbeat classification achieves an accuracy, sensitivity, specificity, precision, and F1-score of 99.34%, 93.83%, 99.57%, 89.81%, and 91.44%, respectively. As the results demonstrate, the proposed DL model can extract high-level features not only from the training data but also from unseen data. Such a model has good application prospects in clinical practice.
New Application of an Instantaneous Frequency Parameter for Assessing Far Infrared Fabric Effects in Aged Subjects
Authors: Wei Hai-Cheng , Li Yun-Qin , Wu Guan-Sheng , Xiao Ming-Xia , Tang Xiao-Jing , Chen Jian-Jung , Wu Hsien-Tsai
Published: January 2020

A microcirculation microscope has recently been introduced to reveal finger blood flow changes by visualization, before and after using far-infrared fabric. Digital volume pulses (DVPs) from the dominant index fingertip of healthy young subjects (Group 1, n = 66) and healthy upper middle-aged subjects (Group 2, n = 33) were acquired through a photoplethysmographic electrical device (PED). By using the one intrinsic mode function (i.e., IMF5), an instantaneous frequency difference (ΔfEmax) was revealed through the second part of the Hilbert–Huang transformation. Parameters from DVPs in the time domain, i.e., the stiffness index, crest time, crest time ratio, and finger perfusion index, were also obtained for comparison. The results showed significant differences in FPI and ΔfEmax between the two groups (p = 0.002 and p = 0.043, respectively). A significant ΔfEmax was also noted for the two groups under the effects of far-infrared radiation (FIR) (Group 1: p = 0.046; Group 2: p = 0.002). In conclusion, this study aimed to validate a self-developed and economical device, with a good extensibility, which can be operated in a domestic setting, and to demonstrate that the PED performed quantitative indexes on finger blood flow comparable to those investigated through a microcirculation microscope.
Secondary Control for Storage Power Converters in Isolated Nanogrids to Allow Peer-to-Peer Power Sharing
Authors: González-Romera Eva , Romero-Cadaval Enrique , Roncero-Clemente Carlos , Ruiz-Cortés Mercedes , Barrero-González Fermín , Milanés Montero María-Isabel , Moreno-Muñoz Antonio
Published: January 2020

It is usual in literature that power sharing among grid-forming sources of an isolated microgrid obeys their energy rating, instead of economic agreements between stakeholders, and circulating energy among them is usually avoided. However, these energy interchanges make strong sense and classical power sharing methods must be reformulated in the context of prosumer-based microgrids. This paper proposes a secondary control method for a prosumer-based low-voltage nanogrid that allows for energy interchange between prosumers, where storage systems, together with PV generators, are the controllable grid-forming sources. A power flow technique adapted to islanded microgrids is used for secondary control algorithm and the whole hierarchical control strategy for the prosumer converter is simulated and validated. This hierarchical control consists of three stages: tertiary control plans the energy interchange among prosumers, secondary obtains different voltage and power setpoints for each of the grid-forming sources, and, finally, primary control guarantees stable voltage and frequency values within the nanogrid with droop rules. Inner control loops for the power converter are also defined to track setpoints and assure stable performance. Simulation tests are carried out, which prove the stability of the proposed methods and the accuracy of the setpoint tracking.
Towards a Lightweight Detection System for Cyber Attacks in the IoT Environment Using Corresponding Features
Authors: Soe Yan Naung , Feng Yaokai , Santosa Paulus Insap , Hartanto Rudy , Sakurai Kouichi
Published: January 2020

The application of a large number of Internet of Things (IoT) devices makes our life more convenient and industries more efficient. However, it also makes cyber-attacks much easier to occur because so many IoT devices are deployed and most of them do not have enough resources (i.e., computation and storage capacity) to carry out ordinary intrusion detection systems (IDSs). In this study, a lightweight machine learning-based IDS using a new feature selection algorithm is designed and implemented on Raspberry Pi, and its performance is verified using a public dataset collected from an IoT environment. To make the system lightweight, we propose a new algorithm for feature selection, called the correlated-set thresholding on gain-ratio (CST-GR) algorithm, to select really necessary features. Because the feature selection is conducted on three specific kinds of cyber-attacks, the number of selected features can be significantly reduced, which makes the classifiers very small and fast. Thus, our detection system is lightweight enough to be implemented and carried out in a Raspberry Pi system. More importantly, as the really necessary features corresponding to each kind of attack are exploited, good detection performance can be expected. The performance of our proposal is examined in detail with different machine learning algorithms, in order to learn which of them is the best option for our system. The experiment results indicate that the new feature selection algorithm can select only very few features for each kind of attack. Thus, the detection system is lightweight enough to be implemented in the Raspberry Pi environment with almost no sacrifice on detection performance.
Action Recognition Using Deep 3D CNNs with Sequential Feature Aggregation and Attention
Authors: Anvarov Fazliddin , Kim Dae Ha , Song Byung Cheol
Published: January 2020

Action recognition is an active research field that aims to recognize human actions and intentions from a series of observations of human behavior and the environment. Unlike image-based action recognition mainly using a two-dimensional (2D) convolutional neural network (CNN), one of the difficulties in video-based action recognition is that video action behavior should be able to characterize both short-term small movements and long-term temporal appearance information. Previous methods aim at analyzing video action behavior only using a basic framework of 3D CNN. However, these approaches have a limitation on analyzing fast action movements or abruptly appearing objects because of the limited coverage of convolutional filter. In this paper, we propose the aggregation of squeeze-and-excitation (SE) and self-attention (SA) modules with 3D CNN to analyze both short and long-term temporal action behavior efficiently. We successfully implemented SE and SA modules to present a novel approach to video action recognition that builds upon the current state-of-the-art methods and demonstrates better performance with UCF-101 and HMDB51 datasets. For example, we get accuracies of 92.5% (16f-clip) and 95.6% (64f-clip) with the UCF-101 dataset, and 68.1% (16f-clip) and 74.1% (64f-clip) with HMDB51 for the ResNext-101 architecture in a 3D CNN.
An Investigation of Spectral Band Selection for Hyperspectral LiDAR Technique
Authors: Shao Hui , Chen Yuwei , Li Wei , Jiang Changhui , Wu Haohao , Chen Jie , Pan Banglong , Hyyppä Juha
Published: January 2020

Hyperspectral LiDAR (HSL) has been widely discussed in recent years, which attracts increasing attention of the researchers in the field of electronic information technology. With the application of supercontinuum laser source, it is now possible to develop an HSL system, which can collect spectral and spatial information of targets simultaneously. Meanwhile, eye-safety and miniature HSL device with multiple spectral bands are given more priorities in on-site applications. In this paper, we tempt to investigate how to select spectral bands with a selection method. The proposed method consists of three steps: first, the variances among the classes based on hyperspectral feature parameters, termed inter-class variances, are calculated; second, the channels are sorted based on corresponding variances in descending order, and those with the two highest values are adopted as the initial input of classification; finally, the channels are selected successively from the rest of the sorted sequence until the classification accuracy reaches 100%. To test the performance of the proposed method, we collect 91/71-channel hyperspectral measurements of four different categories of materials with 5 nm spectral resolution using an acousto-optic tunable filter (AOTF) based HSL. Experimental results demonstrate that the proposed method could achieve higher classification accuracy than a random band selection method with different classifiers (naïve Bayes (NB) and support vector machine (SVM)) regardless of classification feature parameters (echo maximum and reflectance). To reach 100% accuracy, it demands 8–9 channels on average by echo maximum and 4–5 channels on average by reflectance based on NB classifier; these figures are 3–4 by echo maximum and 2–3 by reflectance with SVM classifier. The proposed method can complete classification task much faster than the random selection method. We further confirm the specific channels for the classification of different materials, and find that the optimal channels vary with different materials. The experimental results prove that the optimal band selection of HSL system for classification is reliable.
Commercial ICT Smart Solutions for the Elderly: State of the Art and Future Challenges in the Smart Furniture Sector
Authors: Frischer Robert , Krejcar Ondrej , Maresova Petra , Fadeyi Oluwaseun , Selamat Ali , Kuca Kamil , Tomsone Signe , Teixeira João Paulo , Madureira Joana , Melero Francisco Jose
Published: January 2020

Within a ubiquitous environment, home and office furniture can be maximally utilized to provide ease, especially if the items are designed based on smart technology. For this reason, the acceptance of smart furniture has soared over the years. Given the vast influence of the Internet of Things (IoT) and Industry 4.0 on technological advancement in furniture design, it is imperative to examine information and communication technology (ICT) solutions for the elderly in the context of smart furniture design and implementation. This article presents a review of the state-of-the-art literature in smart solutions for the elderly based on publications under ICT smart solutions for these elderly, along with smart furniture options and manufacturer activities in terms of fixing market prices for these furniture materials. Furthermore, patenting rights on some existing smart furniture designs for the elderly, given the current trends in worldwide acceptance, are examined. Moreover, this article also highlights opportunities introduced by IoT-based solutions for the elderly as current trends in research and their effects on human life. Some smart product examples from different enterprises are also presented. New, innovative and active designs must be developed, focusing upon human healthcare, and in turn providing greater comfort and convenience for elderly people. To fulfil these requirements, the also selected technical aspects of new Smart Furniture solutions in connection to the cost of these solutions are discussed. Simultaneously, Smart Furniture solutions need to be flexible, low-cost, easy to buy and install without expert knowledge, and widely available on the market.
Methodology for an Opto-Geometric Optimization of a Linear Fresnel Reflector for Direct Steam Generation
Authors: González-Mora Eduardo , Durán García Ma. Dolores
Published: January 2020

A methodology for an optical optimization of the intercept factor concerning a linear Fresnel reflector is described to increase the amount of solar irradiation that will be delivered in the absorber for Agua Prieta, Sonora; taking the FRESDEMO’s Fresnel field as the reference design. For the performed optimization, the intercept factor is determined as a function of the receiver’s height, establishing a simple criterion for the optimization. The FRESDEMO’s field description is determined and briefly discussed, next compared with the proposed optimization. The compound parabolic concentrator (CPC) Winston function for a circular absorber is modified to relocate the cusp of the reflector and the absorber. This modified CPC will redirect all the reflected rays that do not hit directly the absorber, as in the FRESDEMO field, so all of them are captured by the absorber. Through ray-tracing, the graphic flux distribution in the receiver aperture is conceived. This flux distribution is compared with the FRESDEMO field and with a PTC with a flat absorber, ensuring an adequate optimization regarding the intercept factor. The result of the opto-geometric optimization is compared between the FRESDEMO and the optimized field for a specified thermal process, addressing a considerable reduction in the length of the loops.
Efficiency Analysis of Fractional KiloWatt Reluctance Motors with Various Frame Sizes, Taking into Account the Impact of the Punching Process
Authors: Gmyrek Zbigniew , Smółka Krzysztof
Published: January 2020

The need to reduce electricity consumption by electrical devices, including electric motors, is the reason for the development of new designs. Designers strive to improve operational parameters, including efficiency, using, for example, new types of magnetic materials, new types of stator windings, etc. Currently, in mass production, motor cores are made of punched laminations—punching causes damage of core parts. For motors of relatively large geometrical sizes, this effect is ignored during design. For motors having small dimensions, this negative effect results in a reduction in efficiency, which is mostly small for this type of motor. In this paper, the authors propose a new rapid algorithm based on simple measurements to determine the material characteristics of the damaged material part. Then, using them in the FEM models, they determine the efficiency of motors with various powers and frame sizes. On this basis, the conclusions are formulated, they may be helpful for motor designers.
Qualitative and Quantitative Characterisation of Major Elements in Particulate Matter from In-use Diesel Engine Passenger Vehicles by LIBS
Authors: Viskup Richard , Wolf Christoph , Baumgartner Werner
Published: January 2020

In this research we apply a high-resolution optical emission spectroscopy technique for spectrochemical analysis of collected diesel particulate matter. We use the laser-induced breakdown spectroscopy technique (LIBS) for qualitative and quantitative measurements of major chemical elements present in the particulate matter generated from different diesel engine passenger vehicles in use. The high-resolution LIBS technique can instantly measure major chemical elements within the diverse particulate matter matrices.
Different Conventional and Soft Computing MPPT Techniques for Solar PV Systems with High Step-Up Boost Converters: A Comprehensive Analysis
Authors: Basha CH Hussaian , Rani C
Published: January 2020

Solar photovoltaic (PV) systems are attracting a huge focus in the current energy scenario. Various maximum power point tracking (MPPT) methods are used in solar PV systems in order to achieve maximum power. In this article, a clear analysis of conventional MPPT techniques such as variable step size perturb and observe (VSS-P&O), modified incremental conductance (MIC), fractional open circuit voltage (FOCV) has been carried out. In addition, the soft computing MPPT techniques such as fixed step size radial basis functional algorithm (FSS-RBFA), variable step size radial basis functional algorithm (VSS-RBFA), adaptive fuzzy logic controller (AFLC), particle swarm optimization (PSO), and cuckoo search (CS) MPPT techniques are presented along with their comparative analysis. The comparative analysis is done under static and dynamic irradiation conditions by considering algorithm complexity, tracking speed, oscillations at MPP, and sensing parameters. The single-diode model PV panel and double-diode model PV panel are also compared in terms of fill factor (FF) and maximum power extraction. Clear insight is presented supporting the suitability of MPPT techniques for different types of converter configurations.
Real-Time Hardware in the Loop Simulation Methodology for Power Converters Using LabVIEW FPGA
Authors: Estrada Leonel , Vázquez Nimrod , Vaquero Joaquín , de Castro Ángel , Arau Jaime
Published: January 2020

Nowadays, the use of the hardware in the loop (HIL) simulation has gained popularity among researchers all over the world. One of its main applications is the simulation of power electronics converters. However, the equipment designed for this purpose is difficult to acquire for some universities or research centers, so ad-hoc solutions for the implementation of HIL simulation in low-cost hardware for power electronics converters is a novel research topic. However, the information regarding implementation is written at a high technical level and in a specific language that is not easy for non-expert users to understand. In this paper, a systematic methodology using LabVIEW software (LabVIEW 2018) for HIL simulation is shown. A fast and easy implementation of power converter topologies is obtained by means of the differential equations that define each state of the power converter. Five simple steps are considered: designing the converter, modeling the converter, solving the model using a numerical method, programming an off-line simulation of the model using fixed-point representation, and implementing the solution of the model in a Field-Programmable Gate Array (FPGA). This methodology is intended for people with no experience in the use of languages as Very High-Speed Integrated Circuit Hardware Description Language (VHDL) for Real-Time Simulation (RTS) and HIL simulation. In order to prove the methodology’s effectiveness and easiness, two converters were simulated—a buck converter and a three-phase Voltage Source Inverter (VSI)—and compared with the simulation of commercial software (PSIM® v9.0) and a real power converter.
SOH and RUL Prediction of Lithium-Ion Batteries Based on Gaussian Process Regression with Indirect Health Indicators
Authors: Jia Jianfang , Liang Jianyu , Shi Yuanhao , Wen Jie , Pang Xiaoqiong , Zeng Jianchao
Published: January 2020

The state of health (SOH) and remaining useful life (RUL) of lithium-ion batteries are two important factors which are normally predicted using the battery capacity. However, it is difficult to directly measure the capacity of lithium-ion batteries for online applications. In this paper, indirect health indicators (IHIs) are extracted from the curves of voltage, current, and temperature in the process of charging and discharging lithium-ion batteries, which respond to the battery capacity degradation process. A few reasonable indicators are selected as the inputs of SOH prediction by the grey relation analysis method. The short-term SOH prediction is carried out by combining the Gaussian process regression (GPR) method with probability predictions. Then, considering that there is a certain mapping relationship between SOH and RUL, three IHIs and the present SOH value are utilized to predict RUL of lithium-ion batteries through the GPR model. The results show that the proposed method has high prediction accuracy.
Optimization of Fluidization State of a Circulating Fluidized Bed Boiler for Economical Operation
Authors: Liu Xuemin , Yang Hairui , Lyu Junfu
Published: January 2020

To reduce the auxiliary power consumption and improve the reliability of large-scale circulating fluidized bed (CFB) boilers, we developed energy-saving CFB combustion technology based on the fluidization state re-specification. A calculation model of coal comminution energy consumption was used to analyze the change in comminution energy consumption, and a 1D CFB combustion model was modified to predict the operation parameters under the fluidization state optimization conditions. With a CFB boiler of 480 t/h, the effect of fluidization state optimization on the economical operation was analyzed using the above two models. We found that combustion efficiency presents a nonmonotonic trend with the change in the bed pressure drop and feeding coal size. There are an optimal bed pressure drop and a corresponding feeding coal size distribution, under which the net coal consumption is the lowest. Low bed pressure drop operation achieved by reducing the coal particle size is not beneficial to SO2 and NOx emission control, and the pollutant control cost increases. The effect of fluidization state optimization on the gross cost of power supply can be calculated, and the optimal bed pressure drop can be obtained.
Constitutive and Cold Acclimation-Regulated Protein Expression Profiles of Scots Pine Seedlings Reveal Potential for Adaptive Capacity of Geographically Distant Populations
Authors: Baniulis Danas , Sirgėdienė Monika , Haimi Perttu , Tamošiūnė Inga , Danusevičius Darius
Published: January 2020

Geographically distant Scots pine (Pinus sylvestris L.) populations are adapted to specific photoperiods and temperature gradients, and markedly vary in the timing of growth patterns and adaptive traits. To understand the variability of adaptive capacity within species, molecular mechanisms that govern the physiological aspects of phenotypic plasticity should be addressed. Protein expression analysis is capable of depicting molecular events closely linked to phenotype formation. Therefore, in this study, we used comparative proteomics analysis to differentiate Scots pine genotypes originating from geographically distant populations in Europe, which show distinct growth and cold adaptation phenotypes. Needles were collected from 3-month-old seedlings originating from populations in Spain, Lithuania and Finland. Under active growth-promoting conditions and upon acclimation treatment, 65 and 53 differentially expressed proteins were identified, respectively. Constitutive protein expression differences detected during active growth were associated with cell metabolism and stress response, and conveyed a population-specific adaptation to the distinct climatic conditions. Acclimation-induced protein expression patterns suggested the presence of a similar cold adaptation mechanism among the populations. Variation of adaptive capacity among the genotypes was potentially represented by a constitutive low level of expression of the Ser/Thr-protein phosphatase, the negative regulator of the adaptive response. Also, overall less pronounced acclimation-induced response in seedlings from the Spanish population was observed. Thus, our study demonstrates that comparative proteomic analysis of young conifer seedlings is capable of providing insights into adaptation processes at the cellular level, which could help to infer variability of adaptive capacity within the plant species.
The Effects of Ecological Factors on the Main Medicinal Components of Dendrobium officinale under Different Cultivation Modes
Authors: Yuan Yingdan , Tang Xinggang , Jia Zhaohui , Li Chong , Ma Jieyi , Zhang Jinchi
Published: January 2020

Dendrobium officinale is an important traditional Chinese medicinal plant and crop, which contains many kinds of medicinal components. The quality of medicinal plants is closely related to the ecological factors in a growing environment. The main components of D. officinale determined in this study were polysaccharides, total alkaloids and total flavonoids. In addition, this study dealt with the correlation of these components to 16 ecological factors under three different cultivation modes (Greenhouse, Bionic, Wild; Lu’an, Anhui Province, China). The relationship between ecological factors and quality factors was analyzed step by step using correlation analysis, principal component analysis and stepwise multiple linear regression. Eight ecological factors: maximum relative humidity, minimum relative humidity, maximum temperature, sunshine duration, soil pH, soil total nitrogen, soil total phosphorus and soil available phosphorus were considered as key factors that influenced the main medicinal qualities of cultivated D. officinale. This study provides an insight for exploring the complex relationship between ecological factors and D. officinale medicinal value in artificial cultivation.