bluuebunny/crossref_metadata_2025 huggingface dataset:
Partial Characterization, the Immune Modulation and Anticancer Activities of Sulfated Polysaccharides from Filamentous Microalgae Tribonema sp.
Authors: Chen Xiaolin , Song Lin , Wang Hui , Liu Song , Yu Huahua , Wang Xueqin , Li Rongfeng , Liu Tianzhong , Li Pengcheng
Published: January 2019

Recently, Tribonema sp., a kind of filamentous microalgae, has been studied for biofuel production due to its accumulation of triacylglycerols. However, the polysaccharides of Tribonema sp. and their biological activities have rarely been reported. In this paper, we extracted sulfated polysaccharides from Tribonema sp. (TSP), characterized their chemical composition and structure, and determined their immunostimulation and anticancer activities on RAW264.7 macrophage cells and HepG2 cells. The results showed that TSP is a sulfated polysaccharide with a Mw of 197 kDa. TSP is a heteropolysaccharide that is composed mainly of galactose. It showed significant immune-modulatory activity by stimulating macrophage cells, such as upregulating interleukin 6 (IL-6), interleukin 10 (IL-10), and tumor necrosis factor α (TNF-α). In addition, TSP also showed significant dose-dependent anticancer activity (with an inhibition rate of up to 66.8% at 250 µg/mL) on HepG2 cells as determined by the 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. The cycle analysis indicated that the anticancer activity of TSP is mainly the result of induced cell apoptosis rather than affecting the cell cycle and mitosis of HepG2 cells. These findings suggest that TSP might have potential as an anticancer resource, but further research is needed, especially in vivo experiments, to explore the anticancer mechanism of TSP.
Polymerizable Ionic Liquids for Solid-State Polymer Electrolytes
Authors: Löwe Robert , Hanemann Thomas , Hofmann Andreas
Published: January 2019

Eight new polymerizable ammonium-TFSI ionic liquids were synthesized and characterized with respect to an application in energy storage devices. The ionic liquids feature methacrylate or acrylate termination as polymerizable groups. The preparation was optimized to obtain the precursors and ionic liquids in high yield. All products were characterized by NMR and IR spectroscopy. Phase transition temperatures were obtained by DSC analysis. Density, viscosity and ionic conductivity of the ionic liquids were compared and discussed. The results reveal that the length of attached alkyl groups as well as the methyl group at the polymerizable function have significant influences on the ionic liquids physicochemical properties. Ionic conductivity values vary between 0.264 mS cm−1 for [C2NA,22]TFSI and 0.080 mS cm−1 for [C8NMA,22]TFSI at 25 °C. Viscosity values are within a range of 0.762 Pa s for [C2NA,22]TFSI and 1.522 Pa s for [C6NMA,22]TFSI at 25 °C.
The Triple-Decker Complex [Cp*Fe(µ,η5:η5-P5)Mo(CO)3] as a Building Block in Coordination Chemistry
Authors: Elsayed Moussa Mehdi , Welsch Stefan , Dütsch Luis , Piesch Martin , Reichl Stephan , Seidl Michael , Scheer Manfred
Published: January 2019

Although the triple-decker complex [Cp*Fe(µ,η5:η5-P5)Mo(CO)3] (2) was first reported 26 years ago, its reactivity has not yet been explored. Herein, we report a new high-yielding synthesis of 2 and the isolation of its new polymorph (2’). In addition, we study its reactivity towards AgI and CuI ions. The reaction of 2 with Ag[BF4] selectively produces the coordination compound [Ag{Cp*Fe(µ,η5:η5-P5)Mo(CO)3}2][BF4] (3). Its reaction with Ag[TEF] and Cu[TEF] ([TEF]− = [Al{OC(CF3)3}4]−) leads to the selective formation of the complexes [Ag{Cp*Fe(µ,η5:η5-P5)Mo(CO)3}2][TEF] (4) and [Cu{Cp*Fe(µ,η5:η5-P5)Mo(CO)3}2][TEF] (5), respectively. The X-ray structures of compounds 3–5 each show an MI ion (MI = AgI, CuI) bridged by two P atoms from two triple-decker complexes (2). Additionally, four short MI···CO distances (two to each triple-decker complex 2) participate in stabilizing the coordination sphere of the MI ion. Evidently, the X-ray structure for compound 3 shows a weak interaction of the AgI ion with one fluorine atom of the counterion [BF4]−. Such an Ag···F interaction does not exist for compound 4. These findings demonstrate the possibility of using triple-decker complex 2 as a ligand in coordination chemistry and opening a new perspective in the field of supramolecular chemistry of transition metal compounds with phosphorus-rich complexes.
Anti-Depressive Effectiveness of Baicalin In Vitro and In Vivo
Authors: Liu Li , Dong Yu , Shan Xin , Li Lin , Xia Baomei , Wang Hanqing
Published: January 2019

Baicalin (BA), a major polyphenol compound isolated from the extracts of Scutellaria radix, has been previously reported to ameliorate depressive-like behaviors in mice with chronic unpredictable mild stress (CUMS). However, its underlying antidepressant mechanisms remain unclear. This study was designed to confirm the antidepressant-like effects of BA on CUMS induced behavioral abnormalities in mice, and sought to explore the pharmacological mechanisms in vivo and in vitro. The CUMS procedure was carried out to induce depression in mice. Afterwards, the tail suspension test (TST), forced swim test (FST), and open field test (OFT) were performed within 24 h, then sucrose preference test (SPT) was conducted. Additionally, PC12 cells were pretreated with BA for 2 h, then further stimulated with corticosterone for 24 h. The levels of Interleukin-1β (IL-1β), IL-6 and Tumor Necrosis Factor-α (TNF-α) in serum, hippocampus homogenate and cell culture medium were determined using the enzyme-linked immunosorbent assay (ELISA) method. The protein expressions of inhibition of high mobility group box 1 protein (HMGB1)/Toll-like receptor 4 (TLR4)/nuclear factor kappa B (NF-κB) pathways in hippocampus and PC12 cells were detected. Our results showed that CUMS-treated mice presented notable depressive-like symptoms, such as decreased sucrose consumption, increased FST and TST immobility time. While BA (25, 50 mg/kg) significantly attenuated these changes. Besides, BA treatment considerably inhibited inflammatory cytokinesl (IL-1β, IL-6, TNF-α) levels in serum, hippocampus homogenate and cell culture medium. Western blot analysis indicated that BA inhibited the expressions of HMGB1, TLR4, and p-NF-κBp65 both in vivo and in vitro. In conclusion, the present study confirmed that BA possessed efficient antidepressant effects on depression, which was possibly related to the inhibition of HMGB1/TLR4/NF-κB pathways.
Synthesis, In Silico, and In Vitro Evaluation of Long Chain Alkyl Amides from 2-Amino-4-Quinolone Derivatives as Biofilm Inhibitors
Authors: Espinosa-Valdés Mariana Paola , Borbolla-Alvarez Sara , Delgado-Espinosa Ana Elena , Sánchez-Tejeda Juan Francisco , Cerón-Nava Anabelle , Quintana-Romero Osvaldo Javier , Ariza-Castolo Armando , García-Del Río Diego Fernando , Loza-Mejía Marco A.
Published: January 2019

Infection from multidrug resistant bacteria has become a growing health concern worldwide, increasing the need for developing new antibacterial agents. Among the strategies that have been studied, biofilm inhibitors have acquired relevance as a potential source of drugs that could act as a complement for current and new antibacterial therapies. Based on the structure of 2-alkyl-3-hydroxy-4-quinolone and N-acylhomoserine lactone, molecules that act as mediators of quorum sensing and biofilm formation in Pseudomonas aeruginosa, we designed, prepared, and evaluated the biofilm inhibition properties of long chain amide derivatives of 2-amino-4-quinolone in Staphylococcus aureus and P. aeruginosa. All compounds had higher biofilm inhibition activity in P. aeruginosa than in S. aureus. Particularly, compounds with an alkyl chain of 12 carbons exhibited the highest inhibition of biofilm formation. Docking scores and molecular dynamics simulations of the complexes of the tested compounds within the active sites of proteins related to quorum sensing had good correlation with the experimental results, suggesting the diminution of biofilm formation induced by these compounds could be related to the inhibition of these proteins.
Phytochemical Composition and Antioxidant Activities of Two Different Color Chrysanthemum Flower Teas
Authors: Han Ah-Reum , Nam Bomi , Kim Bo-Ram , Lee Ki-Chang , Song Beom-Seok , Kim Sang Hoon , Kim Jin-Baek , Jin Chang Hyun
Published: January 2019

Chrysanthemum morifolium Ramat is a perennial flowering plant widely cultivated for use in a tea infusion and as a popular beverage. To identify and evaluate the tea infusion made with a γ-irradiated mutant chrysanthemum cultivar with dark purple petals (cv. ARTI-Dark Chocolate), its phytochemical composition and antioxidant activity were tested and compared with those of the commercially available chrysanthemum cultivar with yellow petals (cv. Gamguk) by HPLC-DAD-ESIMS, as well as DPPH and ABTS radical scavenging assays. The purple chrysanthemum tea contained anthocyanins and linarin, which were not detected in the yellow chrysanthemum tea and the content of chlorogenic acid, acacetin-7-O-β-glucoside, and luteolin was higher compared with the yellow chrysanthemum tea. In contrast, the yellow chrysanthemum tea had higher luteolin-7-O-β-glucoside, 3,5-dicaffeoylquinic acid, apigenin-7-O-β-glucoside, and apigenin contents in comparison with the purple chrysanthemum tea. In addition, the content and antioxidant activity of the two chrysanthemum teas were investigated according to different water temperatures and infusing time. The yellow chrysanthemum tea did not show any significant differences according to infusing time and temperature, while the purple chrysanthemum tea was more influenced by the infusing time than water temperature, showing the highest total compound content in the infusing condition of 100 °C and 4 min. Moreover, the floral scent volatiles of the two chrysanthemum tea sources were analyzed using HS-SPME-GC-MS. In the DPPH radical scavenging assay, the purple chrysanthemum tea broadly showed greater antioxidant activity than did the yellow chrysanthemum tea, corresponding to the high content of anthocyanins known as the powerful antioxidant. Further, both chrysanthemum flower teas exhibited strong ABTS radical scavenging effects ranging from 76% to 61% under all infusing conditions. Therefore, the purple chrysanthemum cultivar, ARTI-Dark Chocolate, is worthy of breeding as a new tea cultivar.
Fluoropolymer-Containing Opals and Inverse Opals by Melt-Shear Organization
Authors: Kredel Julia , Dietz Christian , Gallei Markus
Published: January 2019

The preparation of highly ordered colloidal architectures has attracted significant attention and is a rapidly growing field for various applications, e.g., sensors, absorbers, and membranes. A promising technique for the preparation of elastomeric inverse opal films relies on tailored core/shell particle architectures and application of the so-called melt-shear organization technique. Within the present work, a convenient route for the preparation of core/shell particles featuring highly fluorinated shell materials as building blocks is described. As particle core materials, both organic or inorganic (SiO2) particles can be used as a template, followed by a semi-continuous stepwise emulsion polymerization for the synthesis of the soft fluoropolymer shell material. The use of functional monomers as shell-material offers the possibility to create opal and inverse opal films with striking optical properties according to Bragg’s law of diffraction. Due to the presence of fluorinated moieties, the chemical resistance of the final opals and inverse opals is increased. The herein developed fluorine-containing particle-based films feature a low surface energy for the matrix material leading to good hydrophobic properties. Moreover, the low refractive index of the fluoropolymer shell compared to the core (or voids) led to excellent optical properties based on structural colors. The herein described fluoropolymer opals and inverse opals are expected to pave the way toward novel functional materials for application in fields of coatings and optical sensors.
Acknowledgement to Reviewers of Polymers in 2018
Authors:   Polymers Editorial Office
Published: January 2019

Rigorous peer-review is the corner-stone of high-quality academic publishing [...]
Preparation of PVDF/Hyperbranched-Nano-Palygorskite Composite Membrane for Efficient Removal of Heavy Metal Ions
Authors: Zhang Xiaoye , Qin Yingxi , Zhang Guifang , Zhao Yiping , Lv Chao , Liu Xingtian , Chen Li
Published: January 2019

In this work, three kinds of hyperbranched polyamidoamine-palygorskite (PAMAM-Pal) were designed and synthesized by grafting the first generation polyamidoamine (G1.0 PAMAM), G2.0 PAMAM and G3.0 PAMAM onto Pal surfaces, respectively. Then, these PAMAM-Pals were used as additives to prepare polyvinylidene fluoride (PVDF)/hyperbranched polyamidoamine-palygorskite bicomponent composite membranes. The structures of the composite membranes were characterized by Fourier transform infrared spectroscopy (FTIR), thermo gravimetric analysis (TEM), X-ray photoelectron spectroscopy (XPS), field-emission scanning electronmicroscopy (SEM), atomic force microscope (AFM) and Thermogravimetric analysis (TGA). The adsorption properties of composite membranes to heavy metal ions was studied, and the results found that the maximum adsorption capacities for Cu(II), Ni(II) and Cd(II) could reach 155.19 mg/g, 124.28 mg/g and 125.55 mg/g, respectively, for the PVDF/G3.0 PAMAM-Pal membrane, while only 23.70 mg/g, 17.74 mg/g and 14.87 mg/g could be obtained for unmodified membranes in the same conditions. The high adsorption capacity can be ascribed to the large number of amine-terminated groups, amide groups and carbonyl groups of the composite membrane. The above results indicated that the prepared composite membrane has a high adsorption capacity for heavy metal ions removal in water treatment.
Estimation and Mapping of Sub-National GDP in Uganda Using NPP-VIIRS Imagery
Authors: Wang Xuantong , Rafa Mickey , Moyer Jonathan D. , Li Jing , Scheer Jennifer , Sutton Paul
Published: January 2019

Uganda is one of the poorest nations in the world. It is important to obtain accurate, timely data on socio-economic characteristics sub-nationally, so as to target poverty reduction strategies to those most in need. Many studies have demonstrated that nighttime lights (NTL) can be used to measure human activities. Nevertheless, the methods developed from these studies (1) suffer from coarse resolutions, (2) fail to capture the nonlinearity and multi-scale variability of geospatial data, and (3) perform poorly for agriculture-dependent regions. This study proposes a new enhanced light intensity model (ELIM) to estimate the gross domestic product (GDP) for sub-national units within Uganda. This model is developed by combining the NTL data from the Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS), the population data from the Global Human Settlement Layer (GHSL), and information on agricultural production and market prices across several commodity types. This resulted in a gridded dataset for Uganda’s GDP at sub-national levels, to capture the spatial heterogeneity in the economic activity.
Subsidence Zonation Through Satellite Interferometry in Coastal Plain Environments of NE Italy: A Possible Tool for Geological and Geomorphological Mapping in Urban Areas
Authors: Floris Mario , Fontana Alessandro , Tessari Giulia , Mulè Mariachiara
Published: January 2019

The main aim of this paper is to test the use of multi-temporal differential interferometric synthetic aperture radar (DInSAR) techniques as a tool for geological and geomorphological surveys in urban areas, where anthropogenic features often completely obliterate landforms and surficial deposits. In the last two decades, multi-temporal DInSAR techniques have been extensively applied to many topics of Geosciences, especially in geohazard analysis and risks assessment, but few attempts have been made in using differential subsidence for geological and geomorphological mapping. With this aim, interferometric data of an urbanized sector of the Venetian-Friulian Plain were considered. The data derive by permanent scatterers InSAR processing of synthetic aperture radar (SAR) images acquired by ERS 1/2, ENVISAT, COSMO SKY-Med and Sentinel-1 missions from 1992 to 2017. The obtained velocity maps identify, with high accuracy, the border of a fluvial incised valley formed after the last glacial maximum (LGM) and filled by unconsolidated Holocene deposits. These consist of lagoon and fluvial sediments that are affected by a much higher subsidence than the surrounding LGM deposits forming the external plain. Displacement time-series of localized sectors inside the post-LGM incision allowed the causes of vertical movements to be explored, which consist of the consolidation of recent deposits, due to the loading of new structures and infrastructures, and the exploitation of the shallow phreatic aquifer.
Thermal Energy Release Measurement with Thermal Camera: The Case of La Solfatara Volcano (Italy)
Authors: Marotta Enrica , Peluso Rosario , Avino Rosario , Belviso Pasquale , Caliro Stefano , Carandente Antonio , Chiodini Giovanni , Macedonio Giovanni , Avvisati Gala , Marfè Barbara
Published: January 2019

Quiescent volcanoes dissipate a large part of their thermal energy through hot soils and ground degassing mainly in restricted areas called Diffuse Degassing Structures. La Solfatara crater represents the main spot of thermal release for the Campi Flegrei volcano (Italy) despite its reduced dimensions with regards to the whole caldera. The purpose of this study was to develop a method to measure thermal energy release extrapolating it from the ground surface temperature. We used imaging from thermal cameras at short distances (1 m) to obtain a mapping of areas with thermal anomalies and a measure of their temperatures. We built a conceptual model of the energy release from the ground to atmosphere, which well fits the experimental data taken in the La Solfatara crater. Using our model and data, we could estimate the average heat flux in a portion of the crater as q a v g = 220 ± 40 W / m 2 , compatible with other measurements in literature.
The Assessment of Landsat-8 OLI Atmospheric Correction Algorithms for Inland Waters
Authors: Wang Dian , Ma Ronghua , Xue Kun , Loiselle Steven Arthur
Published: January 2019

The OLI (Operational Land Imager) sensor on Landsat-8 has the potential to meet the requirements of remote sensing of water color. However, the optical properties of inland waters are more complex than those of oceanic waters, and inland atmospheric correction presents additional challenges. We examined the performance of atmospheric correction (AC) methods for remote sensing over three highly turbid or hypereutrophic inland waters in China: Lake Hongze, Lake Chaohu, and Lake Taihu. Four water-AC algorithms (SWIR (Short Wave Infrared), EXP (Exponential Extrapolation), DSF (Dark Spectrum Fitting), and MUMM (Management Unit Mathematics Models)) and three land-AC algorithms (FLAASH (Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes), 6SV (a version of Second Simulation of the Satellite Signal in the Solar Spectrum), and QUAC (Quick Atmospheric Correction)) were assessed using Landsat-8 OLI data and concurrent in situ data. The results showed that the EXP (and DSF) together with 6SV algorithms provided the best estimates of the remote sensing reflectance (Rrs) and band ratios in water-AC algorithms and land-AC algorithms, respectively. AC algorithms showed a discriminating accuracy for different water types (turbid waters, in-water algae waters, and floating bloom waters). For turbid waters, EXP gave the best Rrs in visible bands. For the in-water algae and floating bloom waters, however, all water-algorithms failed due to an inappropriate aerosol model and non-zero reflectance at 1609 nm. The results of the study show the improvements that can be achieved considering SWIR bands and using band ratios, and the need for further development of AC algorithms for complex aquatic and atmospheric conditions, typical of inland waters.
A Generic Classification Scheme for Urban Structure Types
Authors: Lehner Arthur , Blaschke Thomas
Published: January 2019

This paper presents a proposal for a generic urban structure type (UST) scheme. Initially developed in the context of urban ecology, the UST approach is increasingly popular in the remote sensing community. However, there is no consistent and standardized UST framework. Until now, the terms land use and certain USTs are often used and described synonymously, or components of structure and use are intermingled. We suggest a generic nomenclature and a respective UST scheme that can be applied worldwide by stakeholders of different disciplines. Based on the insights of a rigorous literature analysis, we formulate a generic structural- and object-based typology, allowing for the generation of hierarchically and terminologically consistent USTs. The developed terminology exclusively focuses on morphology, urban structures and the general exterior appearance of buildings. It builds on the delimitation of spatial objects at several scales and leaves out all social aspects and land use aspects of an urban area. These underlying objects or urban artefacts and their structure- and object-related features, such as texture, patterns, shape, etc. are the core of the hierarchically structured UST scheme. Finally, the authors present a generic framework for the implementation of a remote sensing-based UST classification along with the requirements regarding sensors, data and data types.
Noise Estimation for Image Sensor Based on Local Entropy and Median Absolute Deviation
Authors: Li Yongsong , Li Zhengzhou , Wei Kai , Xiong Weiqi , Yu Jiangpeng , Qi Bo
Published: January 2019

Noise estimation for image sensor is a key technique in many image pre-processing applications such as blind de-noising. The existing noise estimation methods for additive white Gaussian noise (AWGN) and Poisson-Gaussian noise (PGN) may underestimate or overestimate the noise level in the situation of a heavy textured scene image. To cope with this problem, a novel homogenous block-based noise estimation method is proposed to calculate these noises in this paper. Initially, the noisy image is transformed into the map of local gray statistic entropy (LGSE), and the weakly textured image blocks can be selected with several biggest LGSE values in a descending order. Then, the Haar wavelet-based local median absolute deviation (HLMAD) is presented to compute the local variance of these selected homogenous blocks. After that, the noise parameters can be estimated accurately by applying the maximum likelihood estimation (MLE) to analyze the local mean and variance of selected blocks. Extensive experiments on synthesized noised images are induced and the experimental results show that the proposed method could not only more accurately estimate the noise of various scene images with different noise levels than the compared state-of-the-art methods, but also promote the performance of the blind de-noising algorithm.
IB-MAC: Transmission Latency-Aware MAC for Electro-Magnetic Intra-Body Communications
Authors: Kim Seungmin , Ko JeongGil
Published: January 2019

Intra-body Communication (IBC) is a communication method using the human body as a communication medium, in which body-attached devices exchange electro-magnetic (EM) wave signals with each other. The fact that our human body consists of water and electrolytes allows such communication methods to be possible. Such a communication technology can be used to design novel body area networks that are secure and resilient towards external radio interference. While being an attractive technology for enabling new applications for human body-centered ubiquitous applications, network protocols for IBC systems is yet under-explored. The IEEE 802.15.6 standards present physical and medium access control (MAC) layer protocols for IBC, but, due to many simplifications, we find that its MAC protocol is limited in providing an environment to enable high data rate applications. This work, based on empirical EM wave propagation measurements made for the human body communication channel, presents IB-MAC, a centralized Time-division multiple access (TDMA) protocol that takes in consideration the transmission latency the body channel induces. Our results, in which we use an event-based simulator to compare the performance of IB-MAC with two different IEEE 802.15.6 standard-compliant MAC protocols and a state-of-the art TDMA-based MAC protocol for IBC, suggest that IB-MAC is suitable for supporting high data rate applications with comparable radio duty cycle and latency performance.
Pose Estimation for Straight Wing Aircraft Based on Consistent Line Clustering and Planes Intersection
Authors: Teng Xichao , Yu Qifeng , Luo Jing , Zhang Xiaohu , Wang Gang
Published: January 2019

Aircraft pose estimation is a necessary technology in aerospace applications, and accurate pose parameters are the foundation for many aerospace tasks. In this paper, we propose a novel pose estimation method for straight wing aircraft without relying on 3D models or other datasets, and two widely separated cameras are used to acquire the pose information. Because of the large baseline and long-distance imaging, feature point matching is difficult and inaccurate in this configuration. In our method, line features are extracted to describe the structure of straight wing aircraft in images, and pose estimation is performed based on the common geometry constraints of straight wing aircraft. The spatial and length consistency of the line features is used to exclude irrelevant line segments belonging to the background or other parts of the aircraft, and density-based parallel line clustering is utilized to extract the aircraft’s main structure. After identifying the orientation of the fuselage and wings in images, planes intersection is used to estimate the 3D localization and attitude of the aircraft. Experimental results show that our method estimates the aircraft pose accurately and robustly.
Virtual View Generation Based on 3D-Dense-Attentive GAN Networks
Authors: Fu Junwei , Liang Jun
Published: January 2019

A binocular vision system is a common perception component of an intelligent vehicle. Benefiting from the biomimetic structure, the system is simple and effective. Which are extremely snesitive on external factors, especially missing vision signals. In this paper, a virtual view-generation algorithm based on generative adversarial networks (GAN) is proposed to enhance the robustness of binocular vision systems. The proposed model consists of two parts: generative network and discriminator network. To improve the quality of a virtual view, a generative network structure based on 3D convolutional neural networks (3D-CNN) and attentive mechanisms is introduced to extract the time-series features from image sequences. To avoid gradient vanish during training, the dense block structure is utilized to improve the discriminator network. Meanwhile, three kinds of image features, including image edge, depth map and optical flow are extracted to constrain the supervised training of model. The final results on KITTI and Cityscapes datasets demonstrate that our algorithm outperforms conventional methods, and the missing vision signal can be replaced by a generated virtual view.
Skull’s Photoacoustic Attenuation and Dispersion Modeling with Deterministic Ray-Tracing: Towards Real-Time Aberration Correction
Authors: Mohammadi Leila , Behnam Hamid , Tavakkoli Jahan , Avanaki Mohammad R. N.
Published: January 2019

Although transcranial photoacoustic imaging has been previously investigated by several groups, there are many unknowns about the distorting effects of the skull due to the impedance mismatch between the skull and underlying layers. The current computational methods based on finite-element modeling are slow, especially in the cases where fine grids are defined for a large 3-D volume. We develop a very fast modeling/simulation framework based on deterministic ray-tracing. The framework considers a multilayer model of the medium, taking into account the frequency-dependent attenuation and dispersion effects that occur in wave reflection, refraction, and mode conversion at the skull surface. The speed of the proposed framework is evaluated. We validate the accuracy of the framework using numerical phantoms and compare its results to k-Wave simulation results. Analytical validation is also performed based on the longitudinal and shear wave transmission coefficients. We then simulated, using our method, the major skull-distorting effects including amplitude attenuation, time-domain signal broadening, and time shift, and confirmed the findings by comparing them to several ex vivo experimental results. It is expected that the proposed method speeds up modeling and quantification of skull tissue and allows the development of transcranial photoacoustic brain imaging.
Aspect Entropy Extraction Using Circular SAR Data and Scattering Anisotropy Analysis
Authors: Teng Fei , Hong Wen , Lin Yun
Published: January 2019

In conventional synthetic aperture radar (SAR) working modes, targets are assumed isotropic because the viewing angle is small. However, most man-made targets are anisotropic. Therefore, anisotropy should be considered when the viewing angle is large. From another perspective, anisotropy is also a useful feature. Circular SAR (CSAR) can detect the scattering variation under different azimuthal look angles by a 360-degree observation. Different targets usually have varying degrees of anisotropy, which aids in target discrimination. However, there is no effective method to quantify the degree of anisotropy. In this paper, aspect entropy is presented as a descriptor of the scattering anisotropy. The range of aspect entropy is from 0 to 1, which corresponds to anisotropic to isotropic. First, the method proposed extracts aspect entropy at the pixel level. Since the aspect entropy of pixels can discriminate isotropic and anisotropic scattering, the method prescreens the target from the isotropic clutters. Next, the method extracts aspect entropy at the target level. The aspect entropy of targets can discriminate between different types of targets. Then, the effect of noise on aspect entropy extraction is analyzed and a denoising method is proposed. The Gotcha public release dataset, an X-band circular SAR data, is used to validate the method and the discrimination capability of aspect entropy.
Low-Cost and Data Anonymised City Traffic Flow Data Collection to Support Intelligent Traffic System
Authors: Handscombe Jonathon , Yu Hong Qing
Published: January 2019

There are many methods of collecting traffic flow data, especially using smart phone apps. However, few current solutions balance the need for collecting full route data whilst respecting privacy and remaining low-cost. This project looks into the creation of a wireless sensor network (WSN) that can balance these requirements in an attempt to negate some of the concerns that come with this type of technology. Our proposed system only collects location data within a defined city area. This data is collected with a randomized identifier, which limits repeated identification of the source vehicle and its occupants. Data collected is shared between vehicle and roadside base stations when the two are in range. To deal with the fluid nature of this scenario, a purposely designed Media Access Control (MAC) protocol was designed and implemented using the beacon-slotted ALOHA (Advocates of Linux Open-source Hawaii Association) mechanism.
A Method for Analyzing the Impact of Intra-System and Inter-System Interference on DME Based on Queueing Theory
Authors: Jiang Guofeng , Fan Yangyu
Published: January 2019

In order to use Distance Measuring Equipment (DME) properly, the impact of intra-system and inter-system electromagnetic interference must be analyzed firstly. However, the error of interference analysis using present methods based on pulse overlap is large when there are more aircraft. The aim of this article is to study a method of analyzing interference on DME whether the number of aircraft is small or not. According to the flow chart of DME signal, we studied the limitations of present methods; then constructed a model of analyzing the collision between duration of desired signal and dead time of receiver based on M/M/1/0 queueing system. Combing this model with other methods, we present a analytic model of analyzing intra-system and inter-system interference on DME. Using this analytic model, we analyzed reply efficiency (RE) and capacity of DME under intra-system and Joint Tactical Information Distribution System (JTIDS) interference. The result shows that the calculation for the probability of overlap between DME dead time and subsequent signals using queueing model agrees well with simulation. Consequently, the analytic model is more accurate than using a single method to analyze interference on DME.
A Novel Method for Extrinsic Calibration of Multiple RGB-D Cameras Using Descriptor-Based Patterns
Authors: Liu Hang , Li Hengyu , Liu Xiahua , Luo Jun , Xie Shaorong , Sun Yu
Published: January 2019

This paper presents a novel method to estimate the relative poses between RGB-D cameras with minimal overlapping fields of view. This calibration problem is relevant to applications such as indoor 3D mapping and robot navigation that can benefit from a wider field of view using multiple RGB-D cameras. The proposed approach relies on descriptor-based patterns to provide well-matched 2D keypoints in the case of a minimal overlapping field of view between cameras. Integrating the matched 2D keypoints with corresponding depth values, a set of 3D matched keypoints are constructed to calibrate multiple RGB-D cameras. Experiments validated the accuracy and efficiency of the proposed calibration approach.
Embracing the Future Internet of Things
Authors: Cirillo Flavio , Wu Fang-Jing , Solmaz Gürkan , Kovacs Ernö
Published: January 2019

All of the objects in the real world are envisioned to be connected and/or represented, through an infrastructure layer, in the virtual world of the Internet, becoming Things with status information. Services are then using the available data from this Internet-of-Things (IoT) for various social and economical benefits which explain its extreme broad usage in very heterogeneous fields. Domain administrations of diverse areas of application developed and deployed their own IoT systems and services following disparate standards and architecture approaches that created a fragmentation of things, infrastructures and services in vertical IoT silos. Coordination and cooperation among IoT systems are the keys to build “smarter” IoT services boosting the benefits magnitude. This article analyses the technical trends of the future IoT world based on the current limitations of the IoT systems and the capability requirements. We propose a hyper-connected IoT framework in which “things” are connected to multiple interdependent services and describe how this framework enables the development of future applications. Moreover, we discuss the major limitations in today’s IoT and highlight the required capabilities in the future. We illustrate this global vision with the help of two concrete instances of the hyper-connected IoT in smart cities and autonomous driving scenarios. Finally, we analyse the trends in the number of connected “things” and point out open issues and future challenges. The proposed hyper-connected IoT framework is meant to scale the benefits of IoT from local to global.
Modeling of Rate-Independent and Symmetric Hysteresis Based on Madelung’s Rules
Authors: Cao Kairui , Li Rui
Published: January 2019

Hysteresis is a kind of nonlinearity with memory, which is usually unwanted in practice. Many phenomenological models have been proposed to describe the observed hysteresis. For instance, the Prandtl-Ishlinskii (PI) model, which consists of several backlash operators, is the most widely used. On the other hand, the well-known Madelung’s rules are always used to validate hysteresis models. It is worth pointing out that the PI model obeys Madelung’s rules. In this paper, instead of considering these rules as criteria, we propose a modeling method for symmetric hysteresis by directly constructing the trajectory based on Madelung’s rules. In the proposed method, turning points are recorded and wiped out according to the input value. After the implementation of the recording and wiping-out mechanisms, the curve which the current trajectory moves along can be determined and then the trajectory can be described. Furthermore, the relationship between the proposed method and the PI model is also investigated. The effectiveness of the presented method is validated by simulation and experimental results.
Smart Meeting Room Usage Information and Prediction by Modelling Occupancy Profiles
Authors: Saralegui Unai , Antón Miguel Ángel , Arbelaitz Olatz , Muguerza Javier
Published: January 2019

The monitoring of small houses and rooms has become possible due to the advances in IoT sensors, actuators and low power communication protocols in the last few years. As buildings are one of the biggest energy consuming entities, monitoring them has great interest for trying to avoid non-necessary energy waste. Moreover, human behaviour has been reported as being the main discrepancy source between energy usage simulations and real usage, so the ability to monitor and predict actions as opening windows, using rooms, etc. is gaining attention to develop stronger models which may lead to reduce the overall energy consumption of buildings, considering buildings thermal inertia and additional capabilities. In this paper, a case study is described in which four meeting rooms have been monitored to obtain information about the usage of the rooms and later use it to predict their future usage. The results show the possibility to deploy a simple and non-intrusive sensing system whose output could be used to develop advanced control strategies.
Blind Estimation of the PN Sequence of A DSSS Signal Using A Modified Online Unsupervised Learning Machine
Authors: Wei Yangjie , Fang Shiliang , Wang Xiaoyan , Huang Shuxia
Published: January 2019

Direct sequence spread spectrum (DSSS) signals are now widely used in air and underwater acoustic communications. A receiver which does not know the pseudo-random (PN) sequence cannot demodulate the DSSS signal. In this paper, firstly, the principle of principal component analysis (PCA) for PN sequence estimation of the DSSS signal is analyzed, then a modified online unsupervised learning machine (LEAP) is introduced for PCA. Compared with the original LEAP, the modified LEAP has the following improvements: (1) By normalizing the system state transition matrices, the modified LEAP can obtain better robustness when the training errors occur; (2) with using variable learning steps instead of a fixed one, the modified LEAP not only converges faster but also has excellent estimation performance. When the modified LEAP is converging, we can utilize the network connection weights which are the eigenvectors of the autocorrelation matrix of the DSSS signal to estimate the PN sequence. Due to the phase ambiguity of the eigenvectors, a novel approach which is based on the properties of the PN sequence is proposed here to exclude the wrong estimated PN sequences. Simulation results showed that the methods mentioned above can estimate the PN sequence rapidly and robustly, even when the DSSS signal is far below the noise level.
A Strain Distribution Sensing System for Bone-Implant Interfaces Based on Digital Speckle Pattern Interferometry
Authors: Zhong Ping , Li Zhisong , Yang Huazheng , Tang Xin , He Guoxing
Published: January 2019

This paper aims to provide an effective measurement method for the distribution of deformations and strains focusing on the response to external loading of bone-implant interfaces. To achieve this target, a novel speckle interference imaging method is proposed by introducing phosphate buffer saline medium, in which the samples were completely placed into a phosphate buffer saline solution medium to stable the water molecules. The stability of interferometry imaging is analyzed by using the concepts of co-occurrence matrix and moment of inertia. A series of experiments to measure load-driven deformation and strain in the bone-implant interface was carried out, and the experiments results were analyzed and discussed. It shows that the proposed method is feasible and effective for the no-contact strain measurements of biomaterials in a physiological condition. The proposed strain distribution sensing system will contribute to evaluating computational simulations and improving selection of implant designs and materials.
An Unbalanced Weighted Sequential Fusing Multi-Sensor GM-PHD Algorithm
Authors: Shen-Tu Han , Qian Hanming , Peng Dongliang , Guo Yunfei , Luo Ji-An
Published: January 2019

In this paper, we study the multi-sensor multi-target tracking problem in the formulation of random finite sets. The Gaussian Mixture probability hypothesis density (GM-PHD) method is employed to formulate the sequential fusing multi-sensor GM-PHD (SFMGM-PHD) algorithm. First, the GM-PHD is applied to multiple sensors to get the posterior GM estimations in a parallel way. Second, we propose the SFMGM-PHD algorithm to fuse the multi-sensor GM estimations in a sequential way. Third, the unbalanced weighted fusing and adaptive sequence ordering methods are further proposed for two improved SFMGM-PHD algorithms. At last, we analyze the proposed algorithms in four different multi-sensor multi-target tracking scenes, and the results demonstrate the efficiency.
Unconstrained Monitoring Method for Heartbeat Signals Measurement using Pressure Sensors Array
Authors: Jiang Yongxiang , Deng Sanpeng , Sun Hongchang , Qi Yuming
Published: January 2019

An unconstrained monitoring method for a driver’s heartbeat is investigated in this paper. Signal measurement was carried out by using pressure sensors array. Due to the inevitable changes of posture during driving, the monitoring place for heartbeat measurement needs to be adjusted accordingly. An experiment was conducted to attach a pressure sensors array to the backrest of a seat. On the basis of the extreme learning machine classification method, driving posture can be recognized by monitoring the distribution of pressure signals. Then, a band-pass filter in heart rate range is adapted to the pressure signals in the frequency domain. Furthermore, a peak point array of the processed pressure frequency spectrum is derived and has the same distribution as the pressure signals. Thus, the heartbeat signals can be extracted from pressure sensors. Then, the correlation coefficient analysis of heartbeat signals and electrocardio-signals is performed. The results show a high level of correlation. Finally, the effects of driving posture on heartbeat signal extraction are discussed to obtain a theoretical foundation for measuring point real-time adjustment.
Inferring Static Hand Poses from a Low-Cost Non-Intrusive sEMG Sensor
Authors: Nasri Nadia , Orts-Escolano Sergio , Gomez-Donoso Francisco , Cazorla Miguel
Published: January 2019

Every year, a significant number of people lose a body part in an accident, through sickness or in high-risk manual jobs. Several studies and research works have tried to reduce the constraints and risks in their lives through the use of technology. This work proposes a learning-based approach that performs gesture recognition using a surface electromyography-based device, the Myo Armband released by Thalmic Labs, which is a commercial device and has eight non-intrusive low-cost sensors. With 35 able-bodied subjects, and using the Myo Armband device, which is able to record data at about 200 MHz, we collected a dataset that includes six dissimilar hand gestures. We used a gated recurrent unit network to train a system that, as input, takes raw signals extracted from the surface electromyography sensors. The proposed approach obtained a 99.90% training accuracy and 99.75% validation accuracy. We also evaluated the proposed system on a test set (new subjects) obtaining an accuracy of 77.85%. In addition, we showed the test prediction results for each gesture separately and analyzed which gestures for the Myo armband with our suggested network can be difficult to distinguish accurately. Moreover, we studied for first time the gated recurrent unit network capability in gesture recognition approaches. Finally, we integrated our method in a system that is able to classify live hand gestures.
Economic Analysis of a Multi-Sided Platform for Sensor-Based Services in the Internet of Things
Authors: Guijarro Luis , Vidal Jose R. , Pla Vicent , Naldi Maurizio
Published: January 2019

A business model for sensor-based services is proposed where a platform creates a multi-sided market. The business model comprises a platform that serves as an intermediary between human users, app developers, and sensor networks, so that the users use the apps and the apps process the data supplied by the sensor networks. The platform, acting as a monopolist, posts a fee for each of the three sides so as to maximize its profit. This business model intends to mimic the market-creating innovation that main mobile apps platforms have generated in the smartphone sector. We conduct an analysis of the profit maximization problem faced by the platform, show that optimum prices exist for any parameter value, and show that these prices always induce an equilibrium in the number of agents from each side that join the platform. We show that the relative strength of the value that advertisers attach to the users determines the platform price structure. Depending on the value of this relative strength, two alternative subsidizing strategies are feasible: to subsidize either the users’ subscription or the developers’ registration. Finally, all agents benefit from an increase in the population at any of the three sides. This result provides a rationale for incentivizing not only the user participation, but also the entry of developer undertakings and the deployment of wireless sensor network infrastructure.
Improved Sensing Capability of Integrated Semiconducting Metal Oxide Gas Sensor Devices
Authors: Lahlalia Ayoub , Le Neel Olivier , Shankar Ravi , Selberherr Siegfried , Filipovic Lado
Published: January 2019

Semiconducting metal oxide (SMO) gas sensors were designed, fabricated, and characterized in terms of their sensing capability and the thermo-mechanical behavior of the micro-hotplate. The sensors demonstrate high sensitivity at low concentrations of volatile organic compounds (VOCs) at a low power consumption of 10.5 mW. In addition, the sensors realize fast response and recovery times of 20 s and 2.3 min, respectively. To further improve the baseline stability and sensing response characteristics at low power consumption, a novel sensor is conceived of and proposed. Tantalum aluminum (TaAl) is used as a microheater, whereas Pt-doped SnO2 is used as a thin film sensing layer. Both layers were deposited on top of a porous silicon nitride membrane. In this paper, two designs are characterized by simulations and experimental measurements, and the results are comparatively reported. Simultaneously, the impact of a heat pulsing mode and rubber smartphone cases on the sensing performance of the gas sensor are highlighted.