bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhanced Water Solubility and Oral Bioavailability of Paclitaxel Crystal Powders through an Innovative Antisolvent Precipitation Process: Antisolvent Crystallization Using Ionic Liquids as Solvent
Authors: Yang Qilei , Zu Chang , Li Wengang , Wu Weiwei , Ge Yunlong , Wang Lingling , Wang Li , Li Yong , Zhao Xiuhua
Published: October 2020

Paclitaxel (PTX) is a poor water-soluble antineoplastic drug with significant antitumor activity. However, its low bioavailability is a major obstacle for its biomedical applications. Thus, this experiment is designed to prepare PTX crystal powders through an antisolvent precipitation process using 1-hexyl-3-methylimidazolium bromide (HMImBr) as solvent and water as an antisolvent. The factors influencing saturation solubility of PTX crystal powders in water in water were optimized using a single-factor design. The optimum conditions for the antisolvent precipitation process were as follows: 50 mg/mL concentration of the PTX solution, 25 °C temperature, and 1:7 solvent-to-antisolvent ratio. The PTX crystal powders were characterized via scanning electron microscopy, Fourier transform infrared spectroscopy, high-performance liquid chromatography–mass spectrometry, X-ray diffraction, differential scanning calorimetry, thermogravimetric analysis, Raman spectroscopy, solid-state nuclear magnetic resonance, and dissolution and oral bioavailability studies. Results showed that the chemical structure of PTX crystal powders were unchanged; however, precipitation of the crystalline structure changed. The dissolution test showed that the dissolution rate and solubility of PTX crystal powders were nearly 3.21-folds higher compared to raw PTX in water, and 1.27 times higher in artificial gastric juice. Meanwhile, the bioavailability of PTX crystal increased 10.88 times than raw PTX. These results suggested that PTX crystal powders might have potential value to become a new oral PTX formulation with high bioavailability.
An Integrated Approach for Efficient and Accurate Medicinal Cuscutae Semen Identification
Authors: Park Inkyu , Yang Sungyu , Choi Goya , Moon Byeong Cheol , Song Jun-Ho
Published: October 2020

To guarantee the safety and efficacy of herbal medicines, accurate identification and quality evaluation are crucial. The ripe dried seeds of Cuscuta australis R.Br. and C. chinensis Lam. are known as Cuscutae Semen (CS) and are widely consumed in Northeast Asia; however, the seeds of other species can be misidentified as CS owing to morphological similarities, leading to misuse. In this report, we propose a multilateral strategy combining microscopic techniques with statistical analysis and DNA barcoding using a genus-specific primer to facilitate the identification and authentication of CS. Morphology-based identification using microscopy revealed that the useful diagnostic characteristics included general shape, embryo exudation, hairiness, and testa ornamentation, which were used to develop an effective identification key. In addition, we conducted DNA barcoding-based identification to ensure accurate authentication. A novel DNA barcode primer was produced from the chloroplast rbcL gene by comparative analysis using Cuscuta chloroplast genome sequences, which allowed four Cuscuta species and adulterants to be discriminated completely. Therefore, this investigation overcame the limitations of universal DNA barcodes for Cuscuta species with high variability. We believe that this integrated approach will enable CS to be differentiated from other species, thereby improving its quality control and product safety in medicinal markets.
Differences in Seed Weight, Amino Acid, Fatty Acid, Oil, and Squalene Content in γ-Irradiation-Developed and Commercial Amaranth Varieties (Amaranthus spp.)
Authors: Szabóová Monika , Záhorský Michal , Gažo Ján , Geuens Jeroen , Vermoesen Ann , D’Hondt Els , Hricová Andrea
Published: October 2020

Grain amaranth is known as an alternative crop with exclusive nutritional value and health benefits. The purpose of this study was to investigate the effect of gamma irradiation on quantitative and qualitative amaranth seed traits, including 1000-seed weight, amino acids, fatty acids content, oil, and squalene yield. Two Slovak mutant varieties “Pribina” (A. cruentus) and “Zobor” (A.hypochondriacus x A. hybridus) were evaluated and compared to nonirradiated controls Ficha (A. cruentus L.) and K-433 (A. hypochondriacus x A. hybridus) and commercial varieties, Aztec (A. cruentus L.), Plainsman and Koniz (A. hypochondriacus x A. hybridus). Mutant varieties, “Pribina” and “Zobor”, showed superior 1000-seed weight performance compared to all investigated amaranth samples. The change in quantitative seed trait was accompanied by significantly higher oil and squalene content compared to commercial varieties. Moreover, significantly higher content of essential linoleic acid was detected in mutant variety “Zobor”. The present findings suggest that seeds of irradiation-derived varieties have high nutritional potential and can be used as a supplementary crop in the human diet.
Photosynthetic Responses of Canola to Exogenous Application or Endogenous Overproduction of 5-Aminolevulinic Acid (ALA) under Various Nitrogen Levels
Authors: Feng Xinxin , An Yuyan , Gao Jingjing , Wang Liangju
Published: October 2020

Limited data are available on the effects of 5-aminolevulinic acid (ALA) on plant photosynthesis in relation to the nitrogen (N) level. In this study, we investigate photosynthetic responses to ALA in canola plants (Brassica napus L.). We used wild-type plants without ALA addition (controls), wild-type plants with exogenous ALA application, and transgenic plants that endogenously overproduced ALA. The plants were grown hydroponically in nutrient solutions with low, middle, and high concentrations of N. Our results indicate that plants in both treatment groups had higher chlorophyll contents and net photosynthetic rates and lower intracellular CO2 concentrations in the leaves, as compared to controls. Furthermore, simultaneous measurement of prompt chlorophyll fluorescence and modulated 820-nm reflections showed that the active photosystem II (PS II) reaction centers, electron transfer capacity, and photosystem I (PS I) activity were all higher in treated plants than controls at all N levels; however, the responses of some photochemical processes to ALA were significantly affected by the N level. For example, under low N conditions only, a negative ΔK peak appeared in the prompt chlorophyll fluorescence curve, indicating a protective effect of ALA on electron donation via activation of the oxygen-evolving complex. Taken together, our findings suggest that ALA contributes to the promotion of photosynthesis by regulating photosynthetic electron transport under various N levels. These findings may provide a new strategy for improving photosynthesis in crops grown in N-poor conditions or reduced N-fertilization requirements.
Laser-Induced Selective Electroless Plating on PC/ABS Polymer: Minimisation of Thermal Effects for Supreme Processing Speed
Authors: Ratautas Karolis , Vosylius Vytautas , Jagminienė Aldona , Stankevičienė Ina , Norkus Eugenijus , Račiukaitis Gediminas
Published: October 2020

The selective surface activation induced by laser (SSAIL) for electroless copper deposition on Polycarbonate/Acrylonitrile Butadiene Styrene (PC/ABS) blend is one of the promising techniques of electric circuit formation on free-shape dielectric surfaces, which broadens capabilities of 3D microscopic integrated devices (3D-MIDs). The process consists of laser excitation, chemical activation of laser-excited areas by dipping in a liquid and electroless copper deposition of the laser-treated areas. The limiting factor in increasing throughput of the technology is a laser activation step. Laser writing is performed by modern galvanometric scanners which reach the scanning speed of several meters per second. However, adverse thermal effects on PC/ABS polymer surface abridge the high-speed laser writing. In this work, an investigation was conducted on how these thermal effects limit surface activation for selective metal deposition from the view of physics and chemistry. An advanced laser beam scanning technique of interlacing with precise accuracy and the pulse-on-demand technique was applied to overcome mentioned problems for fast laser writing. Initially, the modelling of transient heat conduction was performed. The results revealed a significant reduction in heat accumulation. Applied methods of laser writing allowed the overall processing rate to increase by up to 2.4 times. Surface morphology was investigated by a scanning electron microscope. Energy-dispersive X-ray spectroscopy was used to investigate the modification of atomic concentration on the surface after laser treatment. Experiments did not show a correlation between surface morphology and electroless plating on laser-treated areas. However, significant variation in the composition of the material was revealed depending on the surface activity for electroless plating.
Circular Intensity Differential Scattering for Label-Free Chromatin Characterization: A Review for Optical Microscopy
Authors: Le Gratiet Aymeric , Marongiu Riccardo , Diaspro Alberto
Published: October 2020

Circular Intensity Differential Scattering (CIDS) provides a differential measurement of the circular right and left polarized light and has been proven to be a gold standard label-free technique to study the molecular conformation of complex biopolymers, such as chromatin. In early works, it has been shown that the scattering component of the CIDS signal gives information from the long-range chiral organization on a scale down to 1/10th–1/20th of the excitation wavelength, leading to information related to the structure and orientation of biopolymers in situ at the nanoscale. In this paper, we review the typical methods and technologies employed for measuring this signal coming from complex macro-molecules ordering. Additionally, we include a general description of the experimental architectures employed for spectroscopic CIDS measurements, angular or spectral, and of the most recent advances in the field of optical imaging microscopy, allowing a visualization of the chromatin organization in situ.
Comparative Study of Green and Synthetic Polymers for Enhanced Oil Recovery
Authors: Muhammed Nasiru Salahu , Haq Md. Bashirul , Al-Shehri Dhafer , Rahaman Mohammad Mizanur , Keshavarz Alireza , Hossain S. M. Zakir
Published: October 2020

Several publications by authors in the field of petrochemical engineering have examined the use of chemically enhanced oil recovery (CEOR) technology, with a specific interest in polymer flooding. Most observations thus far in this field have been based on the application of certain chemicals and/or physical properties within this technique regarding the production of 50–60% trapped (residual) oil in a reservoir. However, there is limited information within the literature about the combined effects of this process on whole properties (physical and chemical). Accordingly, in this work, we present a clear distinction between the use of xanthan gum (XG) and hydrolyzed polyacrylamide (HPAM) as a polymer flood, serving as a background for future studies. XG and HPAM have been chosen for this study because of their wide acceptance in relation to EOR processes. To this degree, the combined effect of a polymer’s rheological properties, retention, inaccessible pore volume (PV), permeability reduction, polymer mobility, the effects of salinity and temperature, and costs are all investigated in this study. Further, the generic screening and design criteria for a polymer flood with emphasis on XG and HPAM are explained. Finally, a comparative study on the conditions for laboratory (experimental), pilot-scale, and field-scale application is presented.
Directed Self-Assembly of Block Copolymers for the Fabrication of Functional Devices
Authors: Pinto-Gómez Christian , Pérez-Murano Francesc , Bausells Joan , Villanueva Luis Guillermo , Fernández-Regúlez Marta
Published: October 2020

Directed self-assembly of block copolymers is a bottom-up approach to nanofabrication that has attracted high interest in recent years due to its inherent simplicity, high throughput, low cost and potential for sub-10 nm resolution. In this paper, we review the main principles of directed self-assembly of block copolymers and give a brief overview of some of the most extended applications. We present a novel fabrication route based on the introduction of directed self-assembly of block copolymers as a patterning option for the fabrication of nanoelectromechanical systems. As a proof of concept, we demonstrate the fabrication of suspended silicon membranes clamped by dense arrays of single-crystal silicon nanowires of sub-10 nm diameter. Resulting devices can be further developed for building up high-sensitive mass sensors based on nanomechanical resonators.
Assessing the Radiological Density and Accuracy of Mandible Polymer Anatomical Structures Manufactured Using 3D Printing Technologies
Authors: Turek Paweł , Budzik Grzegorz , Przeszłowski Łukasz
Published: October 2020

Nowadays, 3D printing technologies are among the rapidly developing technologies applied to manufacture even the most geometrically complex models, however no techniques dominate in the area of craniofacial applications. This study included 12 different anatomical structures of the mandible, which were obtained during the process of reconstructing data from the Siemens Somatom Sensation Open 40 system. The manufacturing process used for the 12 structures involved the use of 8 3D printers and 12 different polymer materials. Verification of the accuracy and radiological density was performed with the CT160Xi Benchtop tomography system. The most accurate results were obtained in the case of models manufactured using the following materials: E-Model (Standard Deviation (SD) = 0.145 mm), FullCure 830 (SD = 0.188 mm), VeroClear (SD = 0.128 mm), Digital ABS-Ivory (SD = 0.117 mm), and E-Partial (SD = 0.129 mm). In the case of radiological density, ABS-M30 was similar to spongious bone, PC-10 was similar to the liver, and Polylactic acid (PLA) and Polyethylene terephthalate (PET) were similar to the spleen. Acrylic resin materials were able to imitate the pancreas, kidney, brain, and heart. The presented results constitute valuable guidelines that may improve currently used radiological phantoms and may provide support to surgeons in the process of performing more precise treatments within the mandible area.
Phase Equilibrium and Interdiffusion in Poly(Vinyl Methyl Ether)-Water System
Authors: Nikulova Uliana V. , Chalykh Anatoly E.
Published: October 2020

The phase state diagram of the poly(vinyl methyl ether)-water system in a wide concentration range was obtained by the optical interferometry method. It was shown that this system was characterized by a complicated phase equilibrium with two lower critical solution temperatures, one of which was located in the concentrated region at 21 °C, and the other one in the region of a dilute solution at 31 °C. In the framework of the Flory–Huggins theory, pair interaction parameters were calculated for different parts of the binodal curves, and an attempt was made to reverse simulate the diagram in different conditions. It was suggested that the unusual character of the diagram was associated with the formation of a complicated complex between PVME and water in the middle region of the compositions. Concentration profiles for different temperatures were constructed. For the first time for this system, the numerical values of the diffusion coefficients of poly(vinyl methyl ether) (PVME) into water and water in PVME were obtained. Concentration and temperature dependences of diffusion coefficients were constructed and analyzed. The kinetics of water sorption in PVME was plotted, the clustering integral was calculated, and the approximate number of molecules in a water cluster was estimated. It was shown that in the dilute solution region upon passing through the binodal curve, the interphase disappeared immediately, and the remaining fluctuation of the concentration decreased in size with time. The kinetics of this process was estimated from the change in the size of such a particle.
Solubility, Rheology, and Coagulation Kinetics of Poly-(O-Aminophenylene)Naphthoylenimide Solutions
Authors: Skvortsov Ivan. Y. , Kulichikhin Valery G. , Ponomarev Igor I. , Varfolomeeva Lydia A. , Kuzin Mikhail S. , Skupov Kirill M. , Volkova Yulia. A. , Razorenov Dmitry Y. , Serenko Olga A.
Published: October 2020

The effect of temperature and storage time at a constant temperature on the stability of poly-(o-aminophenylene)naphthoylenimide solutions in N-methylpyrrolidone has been analyzed using rotational rheometry. A temperature–time window beyond which an irreversible change in the viscoelastic properties of solutions due to cumulative reactions of continuous polymerization and possible intramolecular cyclization has been detected. The influence of polymer concentration and its molecular weight on the rheological properties of solutions determining the choice of methods for their processing into fibers and films has been investigated. The effect of non-solvents (water and ethanol) additives on the rheological properties of solutions and the kinetics of their coagulation has been studied. Dosed addition of non-solvent into the solution promotes a significant increase in the viscoelasticity up to gelation and phase separation. Non-solvent presence in the polymer solutions reduces the activity of the solvent, accelerates the movement of the diffusion front at coagulation, and minimizes the number of macro defects. The combination of parameters under investigation renders it possible for the first time to develop new principles modifying dopes for wet spinning into aqueous or ethanol coagulation bath and finally to obtain a heat- and fire-resistant polynaphthoylenebenzimidazole fibers.
A Phase Filtering Method with Scale Recurrent Networks for InSAR
Authors: Pu Liming , Zhang Xiaoling , Zhou Zenan , Shi Jun , Wei Shunjun , Zhou Yuanyuan
Published: October 2020

Phase filtering is a key issue in interferometric synthetic aperture radar (InSAR) applications, such as deformation monitoring and topographic mapping. The accuracy of the deformation and terrain height is highly dependent on the quality of phase filtering. Researchers are committed to continuously improving the accuracy and efficiency of phase filtering. Inspired by the successful application of neural networks in SAR image denoising, in this paper we propose a phase filtering method that is based on deep learning to efficiently filter out the noise in the interferometric phase. In this method, the real and imaginary parts of the interferometric phase are filtered while using a scale recurrent network, which includes three single scale subnetworks based on the encoder-decoder architecture. The network can utilize the global structural phase information contained in the different-scaled feature maps, because RNN units are used to connect the three different-scaled subnetworks and transmit current state information among different subnetworks. The encoder part is used for extracting the phase features, and the decoder part restores detailed information from the encoded feature maps and makes the size of the output image the same as that of the input image. Experiments on simulated and real InSAR data prove that the proposed method is superior to three widely-used phase filtering methods by qualitative and quantitative comparisons. In addition, on the same simulated data set, the overall performance of the proposed method is better than another deep learning-based method (DeepInSAR). The runtime of the proposed method is only about 0.043s for an image with a size of 1024×1024 pixels, which has the significant advantage of computational efficiency in practical applications that require real-time processing.
A Pseudo-Label Guided Artificial Bee Colony Algorithm for Hyperspectral Band Selection
Authors: He Chunlin , Zhang Yong , Gong Dunwei
Published: October 2020

Hyperspectral remote sensing images have characteristics such as high dimensionality and high redundancy. This paper proposes a pseudo-label guided artificial bee colony band selection algorithm with hypergraph clustering (HC-ABC) to remove redundant and noise bands. Firstly, replacing traditional pixel points by super-pixel centers, a hypergraph evolutionary clustering method with low computational cost is developed to generate high-quality pseudo-labels; Then, on the basis of these pseudo-labels, taking classification accuracy as the optimized objective, a supervised band selection algorithm based on artificial bee colony is proposed. Moreover, a noise filtering mechanism based on grid division is designed to ensure the accuracy of pseudo-labels. Finally, the proposed algorithm is applied in 3 real datasets and compared with 6 classical band selection algorithms. Experimental results show that the proposed algorithm can obtain a band subset with high classification accuracy for all the three classifiers, KNN, Random Forest, and SVM.
Patch Pattern and Ecological Risk Assessment of Alpine Grassland in the Source Region of the Yellow River
Authors: Liu Jia , Chen Jianjun , Qin Qiaoting , You Haotian , Han Xiaowen , Zhou Guoqing
Published: October 2020

The source region of the Yellow River (SRYR) is an important water conservation and animal husbandry resource in China. It is of great significance to understand the patch pattern and ecological risk of alpine grassland in the SRYR for ecological environment management. This study first used 12 unmanned aerial vehicle (UAV) aerial images and eight moderate resolution imaging spectroradiometer (MODIS) vegetation index product MOD13Q1 images from July to August in 2019 to extract alpine grassland patch patterns in the SRYR, then constructed an ecological risk model based on the landscape vulnerability index and landscape disturbance index, and finally combined spatial self-reliance correlation and semi-variance analysis methods to explore the spatial distribution of ecological risks. The results showed that the patch fragmentation degree (Pi), area weighted shape index (AWMSI), and separation degree (Si) of the four grassland types in the SRYR are ordered as follows: alpine steppe > degraded meadow > alpine meadow > swamp meadow. Moreover, the greater the fractional vegetation cover (FVC), the greater the landscape dominance index (DOi), and the better the ecosystem stability. The spatial difference of ecological risk in the SRYR shows a situation of low risk in the east (ERImin=1.5355) and high risk in the west (ERImax = 70.6429). High FVC was found in low and mild low risk areas where the vegetation types are mainly swamp meadow and shrub, while low FVC was found in high and mild high-risk areas where the vegetation types are mainly alpine steppe and degraded meadow. The spatial distribution of ecological risk of the SRYR has obvious positive spatial correlation (Moran's I = 0.863), the spatial aggregation distribution is distinct, and the local space has significant high-high aggregation and low–low aggregation phenomena. The results of this study reveal that patch characteristics have good indicative significance for alpine grassland ecological protection and should be considered in future studies. In addition, the ecological risk in the SRYR is relatively high, especially in the western region, which should be taken seriously in future ecological management and governance.
Three-Dimensional Time Series Movement of the Cuolangma Glaciers, Southern Tibet with Sentinel-1 Imagery
Authors: Yang Liye , Zhao Chaoying , Lu Zhong , Yang Chengsheng , Zhang Qin
Published: October 2020

Many debris-covered glaciers are broadly distributed across High Mountain Asia and have made a number of contributions to water circulation for Qinghai-Tibet Plateau (QTP). The formation of large supraglacial lakes poses risks for glacier lake outburst floods (GLOFs). Therefore, it is important to monitor the movement of glaciers and to analyze their spatiotemporal characteristics. In this study we take Cuolangma glaciers in the central Himalayas as study targets, where glacier No.1 is a lake-terminating debris-covered glacier and glacier No.2 is a land-terminating debris-covered glacier. The 3D deformation time series is firstly estimated by using the Pixel Offset-Small Baseline Subsets (PO-SBAS) based on the ascending and descending Sentinel-1 datasets spanning from January to December 2018. Then the horizontal and vertical time series displacements are obtained to show their spatiotemporal features. The velocities of glacier No.1 in horizontal and vertical direction were up to 16.0 ± 0.04 m/year and 3.4 ± 0.42 m/year, respectively, and the ones of the glacier No.2 were 12.0 ± 0.07 m/year and 2.0 ± 0.27 m/year, respectively. Next, the correlation between the precipitation and the surface velocity suggests that the glacier velocity does not show a clear association with daily precipitation alone. Finally, the debris-covered glaciers evolution is evaluated which shows that the tongue of the glacier No.1 is wasting away and the transition of glacier No.2 from land-terminating to lake-terminating is a probable scenario in the later period of glacier wastage. This research can significantly serve for glacier multidimensional monitoring and the mitigation of hazardous disaster caused by debris-covered glaciers in the central Himalayas.
A Review of Solar Energy Harvesting Electronic Textiles
Authors: Satharasinghe Achala , Hughes-Riley Theodore , Dias Tilak
Published: October 2020

An increased use in wearable, mobile, and electronic textile sensing devices has led to a desire to keep these devices continuously powered without the need for frequent recharging or bulky energy storage. To achieve this, many have proposed integrating energy harvesting capabilities into clothing: solar energy harvesting has been one of the most investigated avenues for this due to the abundance of solar energy and maturity of photovoltaic technologies. This review provides a comprehensive, contemporary, and accessible overview of electronic textiles that are capable of harvesting solar energy. The review focusses on the suitability of the textile-based energy harvesting devices for wearable applications. While multiple methods have been employed to integrate solar energy harvesting with textiles, there are only a few examples that have led to devices with textile properties.
Variational Channel Estimation with Tempering: An Artificial Intelligence Algorithm for Wireless Intelligent Networks
Authors: Liu Jia , Li Mingchu , Chen Yuanfang , Islam Sardar M. N. , Crespi Noel
Published: October 2020

With the rapid development of wireless sensor networks (WSNs) technology, a growing number of applications and services need to acquire the states of channels or sensors, especially in order to use these states for monitoring, object tracking, motion detection, etc. A critical issue in WSNs is the ability to estimate the source parameters from the readings of a distributed sensor network. Although there are several studies on channel estimation (CE) algorithms, existing algorithms are all flawed with their high complexity, inability to scale, inability to ensure the convergence to a local optimum, low speed of convergence, etc. In this work, we turn to variational inference (VI) with tempering to solve the channel estimation problem due to its ability to reduce complexity, ability to generalize and scale, and guarantee of local optimum. To the best of our knowledge we are the first to use VI with tempering for advanced channel estimation. The parameters that we consider in the channel estimation problem include pilot signal and channel coefficients, assuming there is orthogonal access between different sensors (or users) and the data fusion center (or receiving center). By formulating the channel estimation problem into a probabilistic graphical model, the proposed Channel Estimation Variational Tempering Inference (CEVTI) approach can estimate the channel coefficient and the transmitted signal in a low-complexity manner while guaranteeing convergence. CEVTI can find out the optimal hyper-parameters of channels with fast convergence rate, and can be applied to the case of code division multiple access (CDMA) and uplink massive multi-input-multi-output (MIMO) easily. Simulations show that CEVTI has higher accuracy than state-of-the-art algorithms under different noise variance and signal-to-noise ratio. Furthermore, the results show that the more parameters are considered in each iteration, the faster the convergence rate and the lower the non-degenerate bit error rate with CEVTI. Analysis shows that CEVTI has satisfying computational complexity, and guarantees a better local optimum. Therefore, the main contribution of the paper is the development of a new efficient, simple and reliable algorithm for channel estimation in WSNs.
Chitosan-Based Nanocomposites for Glyphosate Detection Using Surface Plasmon Resonance Sensor
Authors: Do Minh Huy , Dubreuil Brigitte , Peydecastaing Jérôme , Vaca-Medina Guadalupe , Nhu-Trang Tran-Thi , Jaffrezic-Renault Nicole , Behra Philippe
Published: October 2020

This article describes an optical method based on the association of surface plasmon resonance (SPR) with chitosan (CS) film and its nanocomposites, including zinc oxide (ZnO) or graphene oxide (GO) for glyphosate detection. CS and CS/ZnO or CS/GO thin films were deposited on an Au chip using the spin coating technique. The characterization, morphology, and composition of these films were performed by Fourier-transform infrared spectroscopy (FTIR), atomic force microscopy (AFM), and contact angle technique. Sensor preparation conditions including the cross-linking and mobile phase (pH and salinity) were investigated and thoroughly optimized. Results showed that the CS/ZnO thin-film composite provides the highest sensitivity for glyphosate sensing with a low detection limit of 8 nM and with high reproducibility. From the Langmuir-type adsorption model and the effect of ionic strength, the adsorption mechanisms of glyphosate could be controlled by electrostatic and steric interaction with possible formation of 1:1 outer-sphere surface complexes. The selectivity of the optical method was investigated with respect to the sorption of glyphosate metabolite (aminomethylphosphonic acid) (AMPA), glufosinate, and one of the glufonisate metabolites (3-methyl-phosphinico-propionic acid) (MPPA). Results showed that the SPR sensor offers a very good selectivity for glyphosate, but the competition of other molecules could still occur in aqueous systems.
Dwell Time Allocation Algorithm for Multiple Target Tracking in LPI Radar Network Based on Cooperative Game
Authors: Xue Chenyan , Wang Ling , Zhu Daiyin
Published: October 2020

To solve the problem of dwell time management for multiple target tracking in Low Probability of Intercept (LPI) radar network, a Nash bargaining solution (NBS) dwell time allocation algorithm based on cooperative game theory is proposed. This algorithm can achieve the desired low interception performance by optimizing the allocation of the dwell time of each radar under the constraints of the given target detection performance, minimizing the total dwell time of radar network. By introducing two variables, dwell time and target allocation indicators, we decompose the dwell time and target allocation into two subproblems. Firstly, combining the Lagrange relaxation algorithm with the Newton iteration method, we derive the iterative formula for the dwell time of each radar. The dwell time allocation of the radars corresponding to each target is obtained. Secondly, we use the fixed Hungarian algorithm to determine the target allocation scheme based on the dwell time allocation results. Simulation results show that the proposed algorithm can effectively reduce the total dwell time of the radar network, and hence, improve the LPI performance.
Development of a Linear Acoustic Array for Aero-Acoustic Quantification of Camber-Bladed Vertical Axis Wind Turbine
Authors: Butt Abdul Hadi , Akbar Bilal , Aslam Jawad , Akram Naveed , Soudagar Manzoore Elahi M , García Márquez Fausto Pedro , Younis Md. Yamin , Uddin Emad
Published: October 2020

Vertical axis wind turbines (VAWT) are a source of renewable energy and are used for both industrial and domestic purposes. The study of noise characteristics of a VAWT is an important performance parameter for the turbine. This study focuses on the development of a linear microphone array and measuring acoustic signals on a cambered five-bladed 45 W VAWT in an anechoic chamber at different tip speed ratios. The sound pressure level spectrum of VAWT shows that tonal noises such as blade passing frequencies dominate at lower frequencies whereas broadband noise corresponds to all audible ranges of frequencies. This study shows that the major portion of noise from the source is dominated by aerodynamic noises generated due to vortex generation and trailing edge serrations. The research also predicts that dynamic stall is evident in the lower Tip speed ratio (TSR) region making smaller TSR values unsuitable for a quiet VAWT. This paper compares the results of linear aeroacoustic array with a 128-MEMS acoustic camera with higher resolution. The study depicts a 3 dB margin between two systems at lower TSR values. The research approves the usage of the 8 mic linear array for small radius rotary machinery considering the results comparison with a NORSONIC camera and its resolution. These observations serve as a basis for noise reduction and blade optimization techniques.
Wireless Sensing of Concrete Setting Process
Authors: González-López Giselle , Romeu Jordi , Cairó Ignasi , Segura Ignacio , Ikumi Tai , Jofre-Roca Lluis
Published: October 2020

An RFID-based wireless system to measure the evolution of the setting process of cement-based materials is presented in this paper. The system consists of a wireless RFID temperature sensor that works embedded in concrete, and an external RFID reader that communicates with the embedded sensor to extract the temperature measurement conducted by the embedded sensor. Temperature time evolution is a well known proxy to monitor the setting process of concrete. The RFID sensor consisting of an UWB Bow Tie antenna with central frequency 868 MHz, matched to the EM4325 temperature chip through a T-match structure for embedded operation inside concrete is fully characterized. Results for measurements of the full set up conducted in a real-scenario are provided.
A Novel Alignment Method for SINS with Large Misalignment Angles Based on EKF2 and AFIS
Authors: Zhao Yanming , Yan Gongmin , Qin Yongyuan , Fu Qiangwen
Published: October 2020

In order to achieve the fine alignment of strapdown inertial navigation (SINS) under large misalignment angles, a novel filtering alignment method is proposed based on the second-order extended Kalman filter (EKF2) and adaptive fuzzy inference system (AFIS). Firstly, the quaternion is employed to represent the attitude errors of SINS. A second-order nonlinear state equation is made based on the nonlinear velocity error model and attitude error model, and the linear measurement equation is based on the velocity outputs from SINS. Then, the filtering scheme is designed based on EKF2 and AFIS. The error estimation and fine alignment can be achieved by using the proposed filtering scheme. The results of Monte Carlo Simulation show that the errors of pitch, roll and yaw misalignment angles quickly decrease to about 14″, 15″ and 7.62′ respectively in 350 s under the condition of any misalignment angles with pitch error from −40° to 40°, roll error from −40° to 40°, and yaw error from −50° to 50°. Even when the initial misalignment angles are all very large such as (80°, 120°, 170°), the proposed nonlinear alignment method still can converge normally by utilizing the adaptive fuzzy inference system (AFIS) to adjust the covariance matrix Pk/k−1. Finally, the turntable experiment was performed, and the effectiveness and superiority of the proposed method were further verified by compared with other nonlinear methods.
Enhanced Image-Based Endoscopic Pathological Site Classification Using an Ensemble of Deep Learning Models
Authors: Nguyen Dat Tien , Lee Min Beom , Pham Tuyen Danh , Batchuluun Ganbayar , Arsalan Muhammad , Park Kang Ryoung
Published: October 2020

In vivo diseases such as colorectal cancer and gastric cancer are increasingly occurring in humans. These are two of the most common types of cancer that cause death worldwide. Therefore, the early detection and treatment of these types of cancer are crucial for saving lives. With the advances in technology and image processing techniques, computer-aided diagnosis (CAD) systems have been developed and applied in several medical systems to assist doctors in diagnosing diseases using imaging technology. In this study, we propose a CAD method to preclassify the in vivo endoscopic images into negative (images without evidence of a disease) and positive (images that possibly include pathological sites such as a polyp or suspected regions including complex vascular information) cases. The goal of our study is to assist doctors to focus on the positive frames of endoscopic sequence rather than the negative frames. Consequently, we can help in enhancing the performance and mitigating the efforts of doctors in the diagnosis procedure. Although previous studies were conducted to solve this problem, they were mostly based on a single classification model, thus limiting the classification performance. Thus, we propose the use of multiple classification models based on ensemble learning techniques to enhance the performance of pathological site classification. Through experiments with an open database, we confirmed that the ensemble of multiple deep learning-based models with different network architectures is more efficient for enhancing the performance of pathological site classification using a CAD system as compared to the state-of-the-art methods.
Multi-Frame Star Image Denoising Algorithm Based on Deep Reinforcement Learning and Mixed Poisson–Gaussian Likelihood
Authors: Xie Ming , Zhang Zhenduo , Zheng Wenbo , Li Ying , Cao Kai
Published: October 2020

Mixed Poisson–Gaussian noise exists in the star images and is difficult to be effectively suppressed via maximum likelihood estimation (MLE) method due to its complicated likelihood function. In this article, the MLE method is incorporated with a state-of-the-art machine learning algorithm in order to achieve accurate restoration results. By applying the mixed Poisson–Gaussian likelihood function as the reward function of a reinforcement learning algorithm, an agent is able to form the restored image that achieves the maximum value of the complex likelihood function through the Markov Decision Process (MDP). In order to provide the appropriate parameter settings of the denoising model, the key hyperparameters of the model and their influences on denoising results are tested through simulated experiments. The model is then compared with two existing star image denoising methods so as to verify its performance. The experiment results indicate that this algorithm based on reinforcement learning is able to suppress the mixed Poisson–Gaussian noise in the star image more accurately than the traditional MLE method, as well as the method based on the deep convolutional neural network (DCNN).
A Unified Fourth-Order Tensor-Based Smart Community System
Authors: Liu Chang , Wu Huaiyu , Wang Junyuan , Wang Mingkai
Published: October 2020

Empowered by the ubiquitous sensing capabilities of Internet of Things (IoT) technologies, smart communities could benefit our daily life in many aspects. Various smart community studies and practices have been conducted, especially in China thanks to the government’s support. However, most intelligent systems are designed and built individually by different manufacturers in diverging platforms with different functionalities. Therefore, multiple individual systems must be deployed in a smart community to have a set of functions, which could lead to hardware waste, high energy consumption and high deployment cost. More importantly, current smart community systems mainly focus on the technologies involved, while the effects of human activity are neglected. In this paper, a fourth-order tensor model representing object, time, location and human activity is proposed for human-centered smart communities, based on which a unified smart community system is designed. Thanks to the powerful data management abilities of a high-order tensor, multiple functions can be integrated into our system. In addition, since the tensor model embeds human activity information, complex functions could be implemented by exploring the effects of human activity. Two exemplary applications are presented to demonstrate the flexibility of the proposed unified fourth-order tensor-based smart community system.
High-Temperature Hydrogen Sensing Performance of Ni-Doped TiO2 Prepared by Co-Precipitation Method
Authors: Fomekong Roussin Lontio , Kelm Klemens , Saruhan Bilge
Published: October 2020

This work deals with the substantially high-temperature hydrogen sensors required by combustion and processing technologies. It reports the synthesis of undoped and Ni-doped TiO2 (with 0, 0.5, 1 and 2 mol.% of Ni) nanoparticles by a co-precipitation method and the obtained characteristics applicable for this purpose. The effect of nickel doping on the morphological variation, as well as on the phase transition from anatase to rutile, of TiO2 was investigated by scanning electron microscopy, X-ray diffraction and Raman spectroscopy. The resistive sensors prepared with these powders were tested toward H2 at 600 °C. The results indicate that 0.5% Ni-doped TiO2 with almost equal amounts of anatase and rutile shows the best H2 sensor response (ΔR/R0 = 72%), response rate and selectivity. The significant improvement of the sensing performance of 0.5% Ni-doped TiO2 is mainly attributed to the formation of the highest number of n-n junctions present between anatase and rutile, which influence the quantity of adsorbed oxygen (i.e., the active reaction site) on the surface and the conductivity of the material.
Detection and Mitigation of RPL Rank and Version Number Attacks in the Internet of Things: SRPL-RP
Authors: A. Almusaylim Zahrah , Jhanjhi NZ , Alhumam Abdulaziz
Published: October 2020

The rapid growth of the Internet of Things (IoT) and the massive propagation of wireless technologies has revealed recent opportunities for development in various domains of real life, such as smart cities and E-Health applications. A slight defense against different forms of attack is offered for the current secure and lightweight Routing Protocol for Low Power and Lossy Networks (RPL) of IoT resource-constrained devices. Data packets are highly likely to be exposed in transmission during data packet routing. The RPL rank and version number attacks, which are two forms of RPL attacks, can have critical consequences for RPL networks. The studies conducted on these attacks have several security defects and performance shortcomings. In this research, we propose a Secure RPL Routing Protocol (SRPL-RP) for rank and version number attacks. This mainly detects, mitigates, and isolates attacks in RPL networks. The detection is based on a comparison of the rank strategy. The mitigation uses threshold and attack status tables, and the isolation adds them to a blacklist table and alerts nodes to skip them. SRPL-RP supports diverse types of network topologies and is comprehensively analyzed with multiple studies, such as Standard RPL with Attacks, Sink-Based Intrusion Detection Systems (SBIDS), and RPL+Shield. The analysis results showed that the SRPL-RP achieved significant improvements with a Packet Delivery Ratio (PDR) of 98.48%, a control message value of 991 packets/s, and an average energy consumption of 1231.75 joules. SRPL-RP provided a better accuracy rate of 98.30% under the attacks.
Voice Communication in Noisy Environments in a Smart House Using Hybrid LMS+ICA Algorithm
Authors: Martinek Radek , Vanus Jan , Nedoma Jan , Fridrich Michael , Frnda Jaroslav , Kawala-Sterniuk Aleksandra
Published: October 2020

This publication describes an innovative approach to voice control of operational and technical functions in a real Smart Home (SH) environment, where, for voice control within SH, it is necessary to provide robust technological systems for building automation and for technology visualization, software for recognition of individual voice commands, and a robust system for additive noise canceling. The KNX technology for building automation is used and described in the article. The LabVIEW SW tool is used for visualization, data connectivity to the speech recognizer, connection to the sound card, and the actual mathematical calculations within additive noise canceling. For the actual recognition of commands, the SW tool for recognition within the Microsoft Windows OS is used. In the article, the least mean squares algorithm (LMS) and independent component analysis (ICA) are used for additive noise canceling from the speech signal measured in a real SH environment. Within the proposed experiments, the success rate of voice command recognition for different types of additive interference (television, vacuum cleaner, washing machine, dishwasher, and fan) in the real SH environment was compared. The recognition success rate was greater than 95% for the selected experiments.
Linking Dynamic Building Simulation with Long-Term Energy System Planning to Improve Buildings Urban Energy Planning Strategies
Authors: Stermieri Lidia , Delmastro Chiara , Becchio Cristina , Corgnati Stefano Paolo
Published: October 2020

The building sector is currently responsible of 40% of global final energy consumption, influencing the broader energy system in terms of new electricity and heat capacity additions, as well as distribution infrastructure reinforcement. Current building energy efficiency potential is largely untapped, especially at the local level where retrofit interventions are typically enforced, neglecting their potential synergies with the entire energy system. To improve the understanding of these potential interactions, this paper proposes a methodology that links dynamic building simulation and energy planning tools at the urban scale. At first, a detailed bottom-up analysis was conducted to estimate the current and post-retrofit energy demand of the building stock. The stock analysis is further linked to a broader energy system simulation model to understand the impact of building renovation on the whole urban energy system in terms of cost, greenhouse gas emission, and primary energy consumption up to 2050. The methodology is suited to analyze the relationship between building energy demand reduction potential and clean energy sources’ deployment to shift buildings away from fossil fuels, the key priority for decarbonizing buildings. The methodology was applied to the case study city of Torino, Italy, highlighting the critical role of coupling proper building retrofit intervention with district-level heat generation strategies, such as modern district heating able to exploit low-grade heat. Being able to simulate both demand and supply future alternatives, the methodology provides a robust reference for municipalities and energy suppliers aiming at promoting efficient energy policies and targeted investments.