bluuebunny/crossref_metadata_2025 huggingface dataset:
Cytotoxic Effect of Paclitaxel and Lapatinib Co-Delivered in Polylactide-co-Poly(ethylene glycol) Micelles on HER-2-Negative Breast Cancer Cells
Authors: Zajdel Alicja , Wilczok Adam , Jelonek Katarzyna , Musiał-Kulik Monika , Foryś Aleksander , Li Suming , Kasperczyk Janusz
Published: April 2019

To find better strategies to enhance the cytotoxic effect of paclitaxel (PTX) and lapatinib (LAP) against breast cancer cells, we analyzed the efficacy of a novel delivery system containing polylactide-co-poly(ethylene glycol) (PLA-PEG) filomicelles of over 100 nm in length and spherical micelles of approximately 20 nm in diameter. The 1H NMR measurements confirmed the incorporation of PTX and LAP into micelles. Analysis of the drug release mechanism revealed the diffusion-controlled release of LAP and anomalous transport of PTX. Drug content analysis in lyophilized micelles and micellar solution showed their good storage stability for at least 6 weeks. Blank micelles, LAP-loaded micelles and free LAP did not affect MCF-7 breast cancer cell proliferation, suggesting that the cytotoxicity of PTX-, PTX/LAP-loaded micelles, and the binary mixture of free PTX and LAP was solely caused by PTX. PTX/LAP-loaded micelles showed greater toxicity compared to the binary mixture of PTX and LAP after 48 h and 72 h. Only free PTX alone induced P-gp activity. This study showed the feasibility of using a LAP and PTX combination to overcome MDR in MCF-7 cells, particularly when co-loaded into micelles. We suggest that PTX/LAP micelles can be applicable not only for the therapy of HER-2-positive, but also HER-2-negative breast cancers.
Numerical Analysis of Nonlocal Optical Response of Metallic Nanoshells
Authors: Khalid Muhammad , Ciracì Cristian
Published: April 2019

Nonlocal and quantum effects play an important role in accurately modeling the optical response of nanometer-sized metallic nanoparticles. These effects cannot be described by conventional classical theories, as they neglect essential microscopic details. Quantum hydrodynamic theory (QHT) has emerged as an excellent tool to correctly predict the nonlocal and quantum effects by taking into account the spatial dependence of the charge density. In this article, we used a QHT to investigate the impact of nonlocality and electron spill-out on the plasmonic behavior of spherical Na and Au nanoshells. We adopted a self-consistent way to compute the equilibrium charge density. The results predicted by QHT were compared with those obtained with the local response approximation (LRA) and the Thomas–Fermi hydrodynamic theory (TFHT). We found that nonlocal effects have a strong impact on both the near- and far-field optical properties of nanoshells, in particular, for the antibonding resonant mode. We also investigated the optical response of these systems for different thicknesses of the shell, both for Na and Au metals.
Blue Light added with Red LEDs Enhance Growth Characteristics, Pigments Content, and Antioxidant Capacity in Lettuce, Spinach, Kale, Basil, and Sweet Pepper in a Controlled Environment
Authors: Naznin Most Tahera , Lefsrud Mark , Gravel Valerie , Azad Md Obyedul Kalam
Published: April 2019

The aim of this study was to investigate the different combinations of red (R) and blue (B) light emitting diode (LEDs’) lighting effects on growth, pigment content, and antioxidant capacity in lettuce, spinach, kale, basil, and pepper in a growth chamber. The growth chamber was equipped with R and B light percentages based on total light intensity: 83% R + 17% B; 91% R + 9% B; 95% R + 5% B; and control was 100% R. The photosynthetic photon flux density (PPFD), photoperiod, temperature, and relative humidity of the growth chamber were maintained at 200 ± 5 μmol m−2 s−1, 16 h, 25/21 ± 2.5 °C, and 65 ± 5%, respectively. It is observed that the plant height of lettuce, kale, and pepper was significantly increased under 100% R light, whereas the plant height of spinach and basil did not show any significant difference. The total leaf number of basil and pepper was significantly increased under the treatment of 95% R + 5% B light, while no significant difference was observed for other plant species in the same treatment. Overall, the fresh and dry mass of the studied plants was increased under 91% R + 9% B and 95% R + 5% B light treatment. The significantly higher flower and fruit numbers of pepper were observed under the 95% R + 5% B treatment. The chlorophyll a, chlorophyll b, and total chlorophyll content of lettuce, spinach, basil, and pepper was significantly increased under the 91% R + 9% B treatment while the chlorophyll content of kale was increased under the 95% R + 5% B light treatment. The total carotenoid content of lettuce and spinach was higher in the 91% R + 9% B treatment whereas the carotenoid content of kale, basil, and pepper was increased under the 83% R + 17% B treatment. The antioxidant capacity of the lettuce, spinach, and kale was increased under the 83% R + 17% B treatment while basil and pepper were increased under the 91% R + 9% B treatment. This result indicates that the addition of B light is essential with R light to enhance growth, pigment content, and antioxidant capacity of the vegetable plant in a controlled environment. Moreover, the percentage of B with R light is plant species dependent.
Cytokinin-Dependent Control of GH3 Group II Family Genes in the Arabidopsis Root
Authors: Pierdonati Emanuela , Unterholzner Simon Josef , Salvi Elena , Svolacchia Noemi , Bertolotti Gaia , Dello Ioio Raffaele , Sabatini Sabrina , Di Mambro Riccardo
Published: April 2019

The Arabidopsis root is a dynamic system where the interaction between different plant hormones controls root meristem activity and, thus, organ growth. In the root, a characteristic graded distribution of the hormone auxin provides positional information, coordinating the proliferating and differentiating cell status. The hormone cytokinin shapes this gradient by positioning an auxin minimum in the last meristematic cells. This auxin minimum triggers a cell developmental switch necessary to start the differentiation program, thus, regulating the root meristem size. To position the auxin minimum, cytokinin promotes the expression of the IAA-amido synthase group II gene GH3.17, which conjugates auxin with amino acids, in the most external layer of the root, the lateral root cap tissue. Since additional GH3 genes are expressed in the root, we questioned whether cytokinin to position the auxin minimum also operates via different GH3 genes. Here, we show that cytokinin regulates meristem size by activating the expression of GH3.5 and GH3.6 genes, in addition to GH3.17. Thus, cytokinin activity provides a robust control of auxin activity in the entire organ necessary to regulate root growth.
Influence of Al2O3 Nanoparticle Addition on a UV Cured Polyacrylate for 3D Inkjet Printing
Authors: Graf Dennis , Burchard Sven , Crespo Julian , Megnin Christof , Gutsch Sebastian , Zacharias Margit , Hanemann Thomas
Published: April 2019

The brittleness of acrylic photopolymers, frequently used in 3D Inkjet printing, limits their utilization in structural applications. In this study, a process was developed for the production and characterization of an alumina-enhanced nanocomposite with improved mechanical properties for Inkjet printing. Ceramic nanoparticles with an average primary particle size (APPS) of 16 nm and 31 nm, which was assessed via high-resolution scanning electron microscopy (HRSEM), were functionalized with 3.43 and 5.59 mg/m2 3-(trimethoxysilyl)propyl methacrylate (MPS), respectively, while being ground in a ball mill. The suspensions of the modified fillers in a newly formulated acrylic mixture showed viscosities of 14 and 7 mPa∙s at the printing temperature of 60 °C. Ink-jetting tests were conducted successfully without clogging the printing nozzles. Tensile tests of casted specimens showed an improvement of the tensile strength and elongation at break in composites filled with 31 nm by 10.7% and 74.9%, respectively, relative to the unfilled polymer.
Ball Milling to Produce Composites Based of Natural Clinoptilolite as a Carrier of Salicylate in Bio-Based PA11
Authors: Bugatti Valeria , Bernardo Paola , Clarizia Gabriele , Viscusi Gianluca , Vertuccio Luigi , Gorrasi Giuliana
Published: April 2019

Antimicrobial packaging systems are recognized as effective approaches to prolong food shelf life. In this context, Bio-based PA11 loaded with a food-grade zeolite were prepared using ball milling technology in the dry state. Zeolite was filled with sodium salicylate, as an antimicrobial agent, and incorporated into the polymer matrix (~50 wt % of salicylate) at different loadings (up to 10 wt %). Structural characterization and an analysis of the physical properties (thermal, barrier, mechanical) were conducted on the composites’ films and compared with the unfilled PA11. The successful entrapment of the antimicrobial molecule into the zeolite’s cavities was demonstrated by the thermal degradation analysis, showing a delay in the molecule’s degradation. Morphological organization, evaluated using SEM analysis, indicated the homogeneous distribution of the filler within the polymer matrix. The filler improves the thermal stability of PA11 and mechanical properties, also enhancing its barrier properties against CO2 and O2. The elongated form of the zeolite particles, evaluated through SEM analysis, was used to model the permeability data. The controlled release of salicylate, evaluated as a function of time and found to depend on the filler loading, was analyzed using the Gallagher‒Corrigan model.
Molecular Assembly between Weak Crosslinking Cyclodextrin Polymer and trans-Cinnamaldehyde for Corrosion Inhibition towards Mild Steel in 3.5% NaCl Solution: Experimental and Theoretical Studies
Authors: Ma Yucong , Fan Baomin , Zhou Tingting , Hao Hua , Yang Biao , Sun Hui
Published: April 2019

Constructing molecular assembly between a soluble cyclodextrin polymer (SCDP) and an anticorrosive component is conducive to increasing the availability of a corrosion inhibitor with low molecular polarity in aqueous solution. The SCDP was prepared via the weak crosslinking effect of glutaraldehyde using β-cyclodextrin as the subunit, whose structure was confirmed by proton nuclear magnetic resonance spectra (1H NMR), X-ray diffraction and morphology. An assembly between SCDP (host) and trans-cinnamaldehyde (guest, CA) was constructed, and the intermolecular interactions were disclosed by Fourier transform infrared spectra (FTIR). The corrosion inhibition of SCDP/CA assembly for mild steel in 3.5% NaCl solution was assessed through electrochemical and surface analyses. 1H NMR results showed that exterior hydroxyls of β-cyclodextrin were the active sites for crosslinking. Hydrogen bonds might be the binding force between SCDP and CA according to FTIR analyses. Electrochemical measurements revealed that SCDP/CA assembly could suppress both cathodic and anodic reactions and enhance the polarization impedance for mild steel in the corrosive medium with a maximum efficiency of 92.2% at 30 °C. Surface analyses showed that CA molecules could be released from the assembly followed by the energy competition mechanism, and solely adsorb on the steel surface in parallel form, which was further evidenced by theoretical modeling.
Preparation and Properties of Polyester Modified Waterborne High Hydroxyl Content and High Solid Content Polyacrylate Emulsion
Authors: Zhu Zhewen , Zhang Chaoying , Gong Shuling
Published: April 2019

A high hydroxyl content waterborne polyester-acrylate emulsion was successfully synthesized in two steps. Firstly, the carboxyl terminated unsaturated polyester was synthesized, then it was reacted as a monomer with acrylate monomer by emulsion polymerization using the semi-continuous seeded method. The effects of the amount of hydroxyethyl methacrylate (HEMA), the ratio of polyester/acrylic, the ratio of soft/hard monomer, and the content of chain transfer agent to the properties of the composite emulsion were investigated. Through a variety of tests, both the emulsion and film properties of the composite emulsion were better than polyacrylate emulsion. The introduction of polyester improved the flexibility and impact resistance of hydroxyl acrylate film, and made the modified resin have advantages of both.
Influence of Combustion Modifiers on the Cure Kinetics of Glycidyl Azide Polymer Based Propellant-Evaluated through Rheo-Kinetic Approach
Authors: He Liming , Zhou Jun , Dai Sulan , Ma Zhongliang
Published: April 2019

To investigate the influence of combustion modifiers on the curing of glycidyl azide polymer spherical propellants (GAPSPs), the curing process of the GAPSPs was explored using an isothermal rheological measurement method. The parameters of cure kinetics were solved to further establish a kinetic model for the curing reaction of GAPSPs. The results showed that the curing process of GAPSPs under isothermal conditions conformed to the Kamal and LSK (Lu–Shim–Kim) models. The model data indicated significant agreement with the experimental data. The influence of four kinds of combustion performance modifiers on the curing process was explored and the results demonstrated that lead phthalate had a catalytic effect on the curing reaction of GAPSPs, whilst oxides of lead and copper, and copper adipate had no influence on the curing reaction.
Polymer Grafted Aluminum Nanoparticles for Percolative Composite Films with Enhanced Compatibility
Authors: Yang Chenggong , Marian Chufarov , Liu Jie , Di Qi , Xu Mingze , Zhang Yunhe , Han Wei , Liu Kun
Published: April 2019

Aluminum nanoparticles hold promise for highly energetic materials and sustainable surface plasmonic materials. Most of the commercial Al nanoparticles are prepared via a high-throughput electrical explosion of wires method (up to 200 g h−1). However, the use of Al nanoparticles produced by an electrical explosion of wires is limited by their micrometer-sized aggregations and poor stability. Here, we use polystyrene with –COOH end-group to graft onto isolated Al nanoparticles and dramatically enhance their colloidal stability in various organic solvents. We further demonstrate that the polystyrene grafted Al nanoparticles can be doped into polystyrene films with high compatibility, leading to enhanced dielectric properties, such as higher dielectric constant, lower dielectric loss, and stronger breakdown strength. Moreover, the composite film can improve the moisture resistance of embedded Al nanoparticles.
Enhancing Oxygen Permeation via the Incorporation of Silver Inside Perovskite Oxide Membranes
Authors: Ma Teng , Han Ning , Meng Bo , Yang Naitao , Zhu Zhonghua , Liu Shaomin
Published: April 2019

As a possible novel cost-effective method for oxygen production from air separation, ion-conducting ceramic membranes are becoming a hot research topic due to their potentials in clean energy and environmental processes. Oxygen separation via these ion-conducting membranes is completed via the bulk diffusion and surface reactions with a typical example of perovskite oxide membranes. To improve the membrane performance, silver (Ag) deposition on the membrane surface as the catalyst is a good strategy. However, the conventional silver coating method has the problem of particle aggregation, which severely lowers the catalytic efficiency. In this work, the perovskite oxide La0.8Ca0.2Fe0.94O3−a (LCF) and silver (5% by mole) composite (LCFA) as the membrane starting material was synthesized using one-pot method via the wet complexation where the metal and silver elements were sourced from their respective nitrate salts. LCFA hollow fiber membrane was prepared and comparatively investigated for air separation together with pure LCF hollow fiber membrane. Operated from 800 to 950 °C under sweep gas mode, the pure LCF membrane displayed the fluxes from 0.04 to 0.54 mL min−1 cm−2. Compared to pure LCF, under similar operating conditions, the flux of LCFA membrane was improved by 160%.
A Hybrid Multi-Objective Optimization Framework for Preliminary Process Design Based on Health, Safety and Environmental Impact
Authors: Teh Shin Yee , Chua Kian Boon , Hong Boon Hooi , Ling Alex J. W. , Andiappan Viknesh , Foo Dominic C. Y. , Hassim Mimi H. , Ng Denny K. S.
Published: April 2019

Due to increasingly stringent legal requirements and escalating environmental control costs, chemical industries have paid close attention to sustainable development without compromising their economic performance. Thus, chemical industries are in need of systematic tools to conduct sustainability assessments of their process/plant design. In order to avoid making costly retrofits at later stages, assessments during the preliminary design stage should be performed. In this paper, a systematic framework is presented for chemical processes at the preliminary design stage. Gross profit, Health Quotient Index (HQI), Inherent Safety Index (ISI) and the Waste Reduction (WAR) algorithm are used to assess the economic performance, health, safety and environmental impact of the process, respectively. The fuzzy optimization approach is used to analyse the trade-off among the four aspects simultaneously, as they often conflict with each other. Deviation between the solution obtained from mathematical optimization model and process simulator is determined to ensure the validity of the model. To demonstrate the proposed framework, a case study on 1, 4-butanediol production is presented.
Roots, Routes, and Routers: Social and Digital Dynamics in the Jain Diaspora
Authors: Vekemans Tine
Published: April 2019

In the past three decades, Jains living in diaspora have been instrumental in the digital boom of Jainism-related websites, social media accounts, and mobile applications. Arguably, the increased availability and pervasive use of different kinds of digital media impacts how individuals deal with their roots; for example, it allows for greater contact with family and friends, but also with religious figures, back in India. It also impacts upon routes—for example, it provides new ways for individual Jains to find each other, organize, coordinate, and put down roots in their current country of residence. Using extensive corpora of Jainism-related websites and mobile applications (2013–2018), as well as ethnographic data derived from participant observation, interviews, and focus groups conducted in the United States, United Kingdom, and Belgian Jain communities (2014–2017), this article examines patterns of use of digital media for social and religious purposes by Jain individuals and investigates media strategies adopted by Jain diasporic organizations. It attempts to explain commonalities and differences in digital engagement across different geographic locations by looking at differences in migration history and the layout of the local Jain communities.
A Spatially Resolved Thermodynamic Assessment of Geothermal Powered Multi-Effect Brackish Water Distillation in Texas
Authors: Birney Catherine I. , Jones Michael C. , Webber Michael E.
Published: April 2019

Brackish groundwater desalination is increasingly being considered as a means to supplement drinking water in regions facing scarce freshwater supplies. Desalination is more energy intensive and expensive than traditional freshwater sources. One method of offsetting carbon emissions is to pair desalination technology with renewable energy sources. This research assesses the geographical feasibility of using a geothermal multi-effect distillation (MED) plant to produce freshwater from brackish aquifers in Texas. The system is analyzed using a thermodynamic model of a binary cycle MED plant. The thermodynamic model is integrated with spatially resolved information of Texas’ geothermal gradient and existing brackish well data (such as depth, salinity, and temperature) to quantify production potential. The results from this study allow for a comparison of potential geothermal desalination plant implementation across all of Texas, rather than a single site assessment. Although this water treatment approach is technologically viable across much of Texas, the system proves to be very energy intensive in all areas except for two hot geopressured fairways in Southeast Texas, the Frio and the Wilcox. In both locations, our research concludes the binary cycle-MED plant can operate self-sufficiently, producing both freshwater and electricity. One well in the fairways can produce 121–1132 m3 of water per day, enough for 232–2133 people. The framework outlined in this paper can be useful to policymakers and water planners considering where to build desalination facilities.
Development of Alloyed Pipe Steel Composition for Oil and Gas Production in the Arctic Region
Authors: Poletskov Pavel , Gushchina Marina , Polyakova Marina , Alekseev Daniil , Nikitenko Olga , Chukin Dmitrii , Vasil’ev Yuri
Published: April 2019

Gas and oil pipelines for the Arctic region must sustain low temperatures and high internal pressures of a corrosive active medium. Generation of new steel compositions for oil and gas pipelines is an urgent issue in order to ensure their high reliability. Low-carbon steels with a ferritic–pearlitic structure are normally used in pipe production, but they are unable to cope with increased market demands. The main objective of this study is to investigate the influence of the cooling rate on the structure and morphological characteristics of bainite, which determines the exploitation properties of the pipe steels. Dilatometric tests were carried out using a Gleeble 3500 complex. Optical microscope and scanning electron microscope analysis, with the computer image analysis system Thixomet PRO, were used to study the microstructure of steel. Hardness was measured in accordance with ASTM E-384. Morphological characteristics of bainite components that were formed at various cooling rates from 0.05 to 100 °C/s were defined. The novel result of this study is the continuous cooling transformation diagram of undercooled austenite of the steel containing 0.062% C; 1.80% Mn; 0.120% Mo; 0.032% Cr, 0.90% Ni and other elements (Al, Cu, V, Nb, Ti).
A Toolbox for the Analysis of the Grasp Stability of Underactuated Fingers
Authors: Zappatore Giovanni Antonio , Reina Giulio , Messina Arcangelo
Published: April 2019

In the design of humanoid robotic hands, it is important to evaluate the grasp stability, especially when the concept of underactuation is involved. The use of a number of degrees of actuation lower than the degrees of freedom has shown some advantages compared to conventional solutions in terms of adaptivity, compactness, ease of control, and cost-effectiveness. However, limited attention has been devoted to the analysis of grasp performance. Some specific issues that need to be further investigated are, for example, the impact of the geometry of the fingers and the objects to be grasped and the value of the driving mechanical torques applied to the phalanges. This research proposes a software toolbox that is aimed to support a user towards an optimal design of underactuated fingers that satisfies stable and efficient grasp constraints.
Monitoring Reservoir Drought Dynamics with Landsat and Radar/Lidar Altimetry Time Series in Persistently Cloudy Eastern Brazil
Authors: Van Den Hoek Jamon , Getirana Augusto , Jung Hahn Chul , Okeowo Modurodoluwa A. , Lee Hyongki
Published: April 2019

Tropical reservoirs are critical infrastructure for managing drinking and irrigation water and generating hydroelectric power. However, long-term spaceborne monitoring of reservoir storage is challenged by data scarcity from near-persistent cloud cover and drought, which may reduce volumes below those in the observational record. In evaluating our ability to accurately monitor long-term reservoir volume dynamics using spaceborne data and overcome such observational challenges, we integrated optical, lidar, and radar time series to estimate reservoir volume dynamics across 13 reservoirs in eastern Brazil over a 12-year (2003–2014) period affected by historic drought. We (i) used 1560 Landsat images to measure reservoir surface area; (ii) built reservoir-specific regression models relating surface area and elevation from ICESat GLAS and Envisat RA-2 data; (iii) modeled volume changes for each reservoir; and (iv) compared modeled and in situ reservoir volume changes. Regression models had high goodness-of-fit (median RMSE = 0.89 m and r = 0.88) across reservoirs. Even though 88% of an average reservoir’s volume time series was based on modeled area–elevation relationships, we found exceptional agreement (RMSE = 0.31 km3 and r = 0.95) with in situ volume time series, and accurately captured seasonal recharge/depletion dynamics and the drought’s prolonged drawdown. Disagreements in volume dynamics were neither driven by wet/dry season conditions nor reservoir capacity, indicating analytical efficacy across a range of monitoring scenarios.
Accounting for Surface Roughness Scattering in the Characterization of Forest Litter with Ground-Penetrating Radar
Authors: André Frédéric , Jonard François , Jonard Mathieu , Vereecken Harry , Lambot Sébastien
Published: April 2019

Accurate characterization of forest litter is of high interest for land surface modeling and for interpreting remote sensing observations over forested areas. Due to the large spatial heterogeneity of forest litter, scattering from litter layers has to be considered when sensed using microwave techniques. Here, we apply a full-waveform radar model combined with a surface roughness model to ultrawideband ground-penetrating radar (GPR) data acquired above forest litter during controlled and in situ experiments. For both experiments, the proposed modeling approach successfully described the radar data, with improvements compared to a previous study in which roughness was not directly accounted for. Inversion of the GPR data also provided reliable estimates of the relative dielectric permittivity of the recently fallen litter (OL layer) and of the fragmented litter in partial decomposition (OF layer) with, respectively, averaged values of 1.35 and 3.8 for the controlled experiment and of 3.9 and 7.5 for the in situ experiment. These results show the promising potentialities of GPR for efficient and non-invasive characterization of forest organic layers.
Mapping Plantations in Myanmar by Fusing Landsat-8, Sentinel-2 and Sentinel-1 Data along with Systematic Error Quantification
Authors: Poortinga Ate , Tenneson Karis , Shapiro Aurélie , Nquyen Quyen , San Aung Khun , Chishtie Farrukh , Saah David
Published: April 2019

Forests in Southeast Asia are experiencing some of the highest rates of deforestation and degradation in the world, with natural forest species being replaced by cropland and plantation monoculture. In this work, we have developed an innovative method to accurately map rubber and palm oil plantations using fusion of Landsat-8, Sentinel 1 and 2. We applied cloud and shadow masking, bidirectional reflectance distribution function (BRDF), atmospheric and topographic corrections to the optical imagery and a speckle filter and harmonics for Synthetic Aperture Radar (SAR) data. In this workflow, we created yearly composites for all sensors and combined the data into a single composite. A series of covariates were calculated from optical bands and sampled using reference data of the land cover classes including surface water, forest, urban and built-up, cropland, rubber, palm oil and mangrove. This training dataset was used to create biophysical probability layers (primitives) for each class. These primitives were then used to create land cover and probability maps in a decision tree logic and Monte-Carlo simulations. Validation showed good overall accuracy (84%) for the years 2017 and 2018. Filtering for validation points with high error estimates improved the accuracy up to 91%. We demonstrated and concluded that error quantification is an essential step in land cover classification and land cover change detection. Our overall analysis supports and presents a path for improving present assessments for sustainable supply chain analyses and associated recommendations.
Retrieval of High Spatial Resolution Aerosol Optical Depth from HJ-1 A/B CCD Data
Authors: Fan Xianlei , Qu Ying
Published: April 2019

A high-spatial resolution aerosol optical depth (AOD) dataset is critically important for regional meteorology and climate studies. Chinese Huanjing-1 (HJ-1) A/B charge-coupled diode (CCD) data are a suitable data source for retrieving AODs. However, AOD cannot be retrieved based on the dark target method due to the absence of a shortwave infrared band. In this study, an AOD estimation method based on the relationships between visible bands of HJ-1 A/B CCDs is proposed. The Polarization and Directionality of the Earth’s Reflectances (POLDER) Bidirectional Reflectance Distribution Function (BRDF) dataset was used to construct a lookup table for interband regression coefficients that varied by solar/view angle and land cover type. Finally, high-spatial resolution AODs could be retrieved with the aerosol lookup table and constraints. The results showed that the AODs retrieved from the HJ-1 A/B CCD data had the same range of distribution and trends as a visual interpretation of the images and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products did. The validation results using four sites of the Aerosol Robotic Network (AERONET) in Beijing showed that the value of the correlation coefficient R was 0.866, the root mean square error (RMSE) was 0.167, the mean absolute error (MAE) was 0.131, and the expected error (EE) was 53.9%. If the measurements of an AERONET site were used as prior knowledge, AOD retrieval results could be much more accurately obtained by this method (R is 0.989, RMSE is 0.052, MAE is 0.042, and EE is 96.7%).
Hyperspectral Image Classification Based on Fusion of Curvature Filter and Domain Transform Recursive Filter
Authors: Liao Jianshang , Wang Liguo
Published: April 2019

In recent decades, in order to enhance the performance of hyperspectral image classification, the spatial information of hyperspectral image obtained by various methods has become a research hotspot. For this work, it proposes a new classification method based on the fusion of two spatial information, which will be classified by a large margin distribution machine (LDM). First, the spatial texture information is extracted from the top of the principal component analysis for hyperspectral images by a curvature filter (CF). Second, the spatial correlation information of a hyperspectral image is completed by using domain transform recursive filter (DTRF). Last, the spatial texture information and correlation information are fused to be classified with LDM. The experimental results of hyperspectral images classification demonstrate that the proposed curvature filter and domain transform recursive filter with LDM(CFDTRF-LDM) method is superior to other classification methods.
L-Band Passive Microwave Data from SMOS for River Gauging Observations in Tropical Climates
Authors: Kugler Zsofia , Nghiem Son V. , Brakenridge G. Robert
Published: April 2019

The Global Flood Detection Systems (GFDS) currently operated at the European Commission’s Joint Research Centre (JRC) is a satellite-based observation system that provides daily stream flow measurements of global rivers. The system was initially established using NASA Advanced Microwave Scanning Radiometer—Earth Observing System (AMSR-E) Ka-band passive microwave satellite data. Since its initiation in 2006, the methodology and the GFDS database have been further adapted for data acquired by the Tropical Rainfall Measuring Mission (TRMM) GOES Precipitation Index (GPI), the AMSR2 sensor onboard the Global Change Observation Mission – Water satellite (GCOM-W1), and the Global Precipitation Measurement (GPM) GPM Microwave Imager (GMI) sensor. This paper extends the same flow monitoring methodology to low frequency (L-band) passive microwave observations obtained by the European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) sensor that was launched in 2009. A primary focus is tropical climate regions with dense rainforest vegetation (the Amazon, the Orinoco, and the Congo basins) where high-frequency microwave observations from GFDS reveal a significant influence of vegetation cover and atmospheric humidity. In contrast, SMOS passive microwave signatures at the much lower L-band frequency exhibit deeper penetration through the dense vegetation and minimal atmospheric effects, enabling more robust river stage retrievals in these regions. The SMOS satellite river gauging observations are for 2010–2018 and are compared to single-sensor GFDS data over several river sites. To reduce noise, different filtering techniques were tested to select the one most suitable for analysis of the L-band time series information. In-situ water level (stage) measurements from the French Observation Service SO Hybam database were used for validation to further evaluate the performance of the SMOS data series. In addition to GFDS data, water stage information from Jason-2 and Jason-3 altimetry was compared to the microwave results. Correlation of SMOS gauging time series with in-situ stage data revealed a good agreement (r = 0.8–0.94) during the analyzed period of 2010–2018. Moderate correlation was found with both high frequency GFDS data series and altimetry data series. With lower vegetation attenuation, SMOS signatures exhibited a robust linear relationship with river stage without seasonal bias from the complex hysteresis effects that appeared in the Ka-band observations, apparently due to different attenuation impacts through dense forests at different seasonal vegetation stages.
IMU/Magnetometer/Barometer/Mass-Flow Sensor Integrated Indoor Quadrotor UAV Localization with Robust Velocity Updates
Authors: Li You , Zahran Shady , Zhuang Yuan , Gao Zhouzheng , Luo Yiran , He Zhe , Pei Ling , Chen Ruizhi , El-Sheimy Naser
Published: April 2019

Velocity updates have been proven to be important for constraining motion-sensor-based dead-reckoning (DR) solutions in indoor unmanned aerial vehicle (UAV) applications. The forward velocity from a mass flow sensor and the lateral and vertical non-holonomic constraints (NHC) can be utilized for three-dimensional (3D) velocity updates. However, it is observed that (a) the quadrotor UAV may have a vertical velocity trend when it is controlled to move horizontally; (b) the quadrotor may have a pitch angle when moving horizontally; and (c) the mass flow sensor may suffer from sensor errors, especially the scale factor error. Such phenomenons degrade the performance of velocity updates. Thus, this paper presents a multi-sensor integrated localization system that has more effective sensor interactions. Specifically, (a) the barometer data are utilized to detect height changes and thus determine the weight of vertical velocity update; (b) the pitch angle from the inertial measurement unit (IMU) and magnetometer data fusion is used to set the weight of forward velocity update; and (c) an extra mass flow sensor calibration module is introduced. Indoor flight tests have indicated the effectiveness of the proposed sensor interaction strategies in enhancing indoor quadrotor DR solutions, which can also be used for detecting outliers in external localization technologies such as ultrasonics.
Sea Surface Ka-Band Doppler Measurements: Analysis and Model Development
Authors: Yurovsky Yury Yu. , Kudryavtsev Vladimir N. , Grodsky Semyon A. , Chapron Bertrand
Published: April 2019

Multi-year field measurements of sea surface Ka-band dual-co-polarized (vertical transmit–receive polarization (VV) and horizontal transmit–receive polarization (HH)) radar Doppler characteristics from an oceanographic platform in the Black Sea are presented. The Doppler centroid (DC) estimated using the first moment of 5 min averaged spectrum, corrected for measured sea surface current, ranges between 0 and ≈1 m/s for incidence angles increasing from 0 to 70 ∘ . Besides the known wind-to-radar azimuth dependence, the DC can also depend on wind-to-dominant wave direction. For co-aligned wind and waves, a negative crosswind DC residual is found, ≈−0.1 m/s, at ≈20 ∘ incidence angle, becoming negligible at ≈ 60 ∘ , and raising to, ≈+0.5 m/s, at 70 ∘ . For our observations, with a rather constant dominant wave length, the DC is almost wind independent. Yet, results confirm that, besides surface currents, the DC encodes an expected wave-induced contribution. To help the interpretation, a two-scale model (KaDOP) is proposed to fit the observed DC, based on the radar modulation transfer function (MTF) previously developed for the same data set. Assuming universal spectral shape of energy containing sea surface waves, the wave-induced DC contribution is then expressed as a function of MTF, significant wave height, and wave peak frequency. The resulting KaDOP agrees well with independent DC data, except for swell-dominated cases. The swell impact is estimated using the KaDOP with a modified empirical MTF.
Monitoring Cliff Erosion with LiDAR Surveys and Bayesian Network-based Data Analysis
Authors: Terefenko Paweł , Paprotny Dominik , Giza Andrzej , Morales-Nápoles Oswaldo , Kubicki Adam , Walczakiewicz Szymon
Published: April 2019

Cliff coasts are dynamic environments that can retreat very quickly. However, the short-term changes and factors contributing to cliff coast erosion have not received as much attention as dune coasts. In this study, three soft-cliff systems in the southern Baltic Sea were monitored with the use of terrestrial laser scanner technology over a period of almost two years to generate a time series of thirteen topographic surveys. Digital elevation models constructed for those surveys allowed the extraction of several geomorphological indicators describing coastal dynamics. Combined with observational and modeled datasets on hydrological and meteorological conditions, descriptive and statistical analyses were performed to evaluate cliff coast erosion. A new statistical model of short-term cliff erosion was developed by using a non-parametric Bayesian network approach. The results revealed the complexity and diversity of the physical processes influencing both beach and cliff erosion. Wind, waves, sea levels, and precipitation were shown to have different impacts on each part of the coastal profile. At each level, different indicators were useful for describing the conditional dependency between storm conditions and erosion. These results are an important step toward a predictive model of cliff erosion.
Decreasing the Uncertainty of the Target Center Estimation at Terrestrial Laser Scanning by Choosing the Best Algorithm and by Improving the Target Design
Authors: Janßen Jannik , Medic Tomislav , Kuhlmann Heiner , Holst Christoph
Published: April 2019

During the registration and georeferencing of terrestrial laser scans, it is common to use targets to mark discrete points. To improve the accuracy of the registration, the uncertainties of the target center estimation (TCE) have to be minimized. The present study examines different factors influencing the precision of the TCE. Here, the focus is on the algorithm and the target design. It is determined that, in general, the uncertainties of the TCE are much smaller than those indicated by the manufacturers. By comparing different algorithms for the first time, it was possible to clearly determine that an algorithm using image correlations yields the smallest standard deviations for the TCE. A comparison of different target designs could not identify an ideal commercially available target. For this reason, a new target, the BOTA8 (BOnn TArget with 8-fold pattern) was developed, which leads to smaller standard deviations than the previous targets. By choosing the best algorithm and improving the target design, standard deviations of 0.5 mm in distance direction and 1.2 arcsec in angular direction for a scan distance up to 100 m were achieved with the laser scanner Leica ScanStation P20. The uncertainties could be reduced by several millimetres and angular seconds compared to the manufacturer’s targets and software.
Vision for Robust Robot Manipulation
Authors: Martinez-Martin Ester , del Pobil Angel
Published: April 2019

Advances in Robotics are leading to a new generation of assistant robots working in ordinary, domestic settings. This evolution raises new challenges in the tasks to be accomplished by the robots. This is the case for object manipulation where the detect-approach-grasp loop requires a robust recovery stage, especially when the held object slides. Several proprioceptive sensors have been developed in the last decades, such as tactile sensors or contact switches, that can be used for that purpose; nevertheless, their implementation may considerably restrict the gripper’s flexibility and functionality, increasing their cost and complexity. Alternatively, vision can be used since it is an undoubtedly rich source of information, and in particular, depth vision sensors. We present an approach based on depth cameras to robustly evaluate the manipulation success, continuously reporting about any object loss and, consequently, allowing it to robustly recover from this situation. For that, a Lab-colour segmentation allows the robot to identify potential robot manipulators in the image. Then, the depth information is used to detect any edge resulting from two-object contact. The combination of those techniques allows the robot to accurately detect the presence or absence of contact points between the robot manipulator and a held object. An experimental evaluation in realistic indoor environments supports our approach.
Detection of Physiological Signals Based on Graphene Using a Simple and Low-Cost Method
Authors: Xie Liping , Zi Xingyu , Meng Qingshi , Liu Zhiwen , Xu Lisheng
Published: April 2019

Despite that graphene has been extensively used in flexible wearable sensors, it remains an unmet need to fabricate a graphene-based sensor by a simple and low-cost method. Here, graphene nanoplatelets (GNPs) are prepared by thermal expansion method, and a sensor is fabricated by sealing of a graphene sheet with polyurethane (PU) medical film. Compared with other graphene-based sensors, it greatly simplifies the fabrication process and enables the effective measurement of signals. The resistance of graphene sheet changes linearly with the deformation of the graphene sensor, which lays a solid foundation for the detection of physiological signals. A signal processing circuit is developed to output the physiological signals in the form of electrical signals. The sensor was used to measure finger bending motion signals, respiration signals and pulse wave signals. All the results demonstrate that the graphene sensor fabricated by the simple and low-cost method is a promising platform for physiological signal measurement.
MIMO Fuzzy Sliding Mode Control for Three-Axis Inertially Stabilized Platform
Authors: Zhou Zhanmin , Zhang Bao , Mao Dapeng
Published: April 2019

In this paper, a MIMO (Multi-Input Multi-Output) fuzzy sliding mode control method is proposed for a three-axis inertially stabilized platform. This method is based on the MIMO coupling model of the three-axis inertially stabilized platform in which the dynamic coupling among the three frames, namely the azimuth frame, the pitch frame and the roll frame, is fully considered. Firstly, the dynamic equation of the three-axis inertially stabilized platform is analyzed and its linearized model is obtained. After this, the controller is designed based on the model, during which fuzzy logic is introduced to deal with the frame coupling and the adaptive fuzzy coupling compensation factor is designed to be part of the algorithm. A complete proof of the stability and convergence is also provided in this paper. Finally, the performance of the platform with a MIMO fuzzy sliding mode controller and PI controller is analyzed. The simulation results show that the proposed scheme can guarantee tracking accuracy and effectively suppress the coupling interference between the three frames.
An Anti-Jamming Null-Steering Control Technique Based on Double Projection in Dynamic Scenes for GNSS Receivers
Authors: Wang Hao , Chang Qing , Xu Yong
Published: April 2019

When a global navigation satellite system (GNSS) receiver suppresses interference in a dynamic scene, the direction of the interference signal arriving at the receiver may change rapidly. The null formed by the spatial filtering based on the array antenna will become wider and shallower, and the anti-jamming performance will deteriorate. A null-steering control technique based on a dual projection algorithm is proposed in this paper, which can effectively increase the depth of the null. In this paper, the dynamic model between the interference and the receiver is established first. Based on the model, the rate of change of the arrival direction of the interference is analyzed, and the phenomenon of the spatial filtering null becoming wider and shallower is simulated and verified. Then, the double projection algorithm is introduced to effectively deepen the null. The simulation results show that the proposed method can effectively increase the null depth by 30 to 50 dB, which significantly improves the anti-jamming performance of the spatial filtering in dynamic scenes.
Electromagnetic Medical Sensing
Authors: Abbosh Amin
Published: April 2019

In recent years, electromagnetic (EM) techniques have been widely investigated and researched for different medical applications, from early diagnosis to therapy and monitoring [...]
Machine Learning for Long Cycle Maintenance Prediction of Wind Turbine
Authors: Yeh Chia-Hung , Lin Min-Hui , Lin Chien-Hung , Yu Cheng-En , Chen Mei-Juan
Published: April 2019

Within Internet of Things (IoT) sensors, the challenge is how to dig out the potentially valuable information from the collected data to support decision making. This paper proposes a method based on machine learning to predict long cycle maintenance time of wind turbines for efficient management in the power company. Long cycle maintenance time prediction makes the power company operate wind turbines as cost-effectively as possible to maximize the profit. Sensor data including operation data, maintenance time data, and event codes are collected from 31 wind turbines in two wind farms. Data aggregation is performed to filter out some errors and get significant information from the data. Then, the hybrid network is built to train the predictive model based on the convolutional neural network (CNN) and support vector machine (SVM). The experimental results show that the prediction of the proposed method reaches high accuracy, which helps drive up the efficiency of wind turbine maintenance.
A Sensor Network Approach for Violence Detection in Smart Cities Using Deep Learning
Authors: Baba Marius , Gui Vasile , Cernazanu Cosmin , Pescaru Dan
Published: April 2019

Citizen safety in modern urban environments is an important aspect of life quality. Implementation of a smart city approach to video surveillance depends heavily on the capability of gathering and processing huge amounts of live urban data. Analyzing data from high bandwidth surveillance video streams provided by large size distributed sensor networks is particularly challenging. We propose here an efficient method for automatic violent behavior detection designed for video sensor networks. Known solutions to real-time violence detection are not suitable for implementation in a resource-constrained environment due to the high processing power requirements. Our algorithm achieves real-time processing on a Raspberry PI-embedded architecture. To ensure separation of temporal and spatial information processing we employ a computationally effective cascaded approach. It consists of a deep neural network followed by a time domain classifier. In contrast with current approaches, the deep neural network input is fed exclusively with motion vector features extracted directly from the MPEG encoded video stream. As proven by results, we achieve state-of-the-art performance, while running on a low computational resources embedded architecture.