bluuebunny/crossref_metadata_2025 huggingface dataset:
Lactobacillus reuteri DSM 17938 Protects against Gastric Damage Induced by Ethanol Administration in Mice: Role of TRPV1/Substance P Axis
Authors: Oliveira Ana P. , Souza Luan K. M. , Araújo Thiago S. L. , Araújo Simone de , Nogueira Kerolayne M. , Sousa Francisca Beatriz M. , Silva Renan O. , Pacífico Dvison M. , Martins Conceição S. , Brito Gerly Anne de C. , Souza Marcellus H.L.P. , Medeiros Jand Venes R.
Published: January 2019

This study aimed to evaluate the effect of Lactobacillus reuteri DSM 17938 (DSM) on ethanol-induced gastric injury, and if its possible mechanism of action is related to inhibiting the transient receptor potential vanilloid type 1 (TRPV1). We evaluated the effect of supplementing 108 CFU•g body wt−1•day−1 of DSM on ethanol-induced gastric injury. DSM significantly reduced the ulcer area (1.940 ± 1.121 mm2) with 3 days of pretreatment. The effects of DSM supplementation were reversed by Resiniferatoxin (RTX), TRPV1 agonist (3 nmol/kg p.o.). Substance P (SP) (1 μmol/L per 20 g) plus 50% ethanol resulted in hemorrhagic lesions, and DSM supplementation did not reverse the lesion area induced by administering SP. TRPV1 staining intensity was lower, SP, malondialdehyde (MDA) and nitrite levels were reduced, and restored normal levels of antioxidant parameters (glutathione and superoxide dismutase) in the gastric mucosa in mice treated with DSM. In conclusion, DSM exhibited gastroprotective activity through decreased expression of TRPV1 receptor and decreasing SP levels, with a consequent reduction of oxidative stress.
Micellisation Mechanism and Behaviour of Soluplus®–Furosemide Micelles: Preformulation Studies of an Oral Nanocarrier-Based System
Authors: Alopaeus Julia F. , Hagesæther Ellen , Tho Ingunn
Published: January 2019

In this study, self-assembling Soluplus® micelles were examined for inherent properties. Through calorimetric analysis, the critical micelle concentration (CMC) could be determined at 25 and 37 °C, and the influence of three media (Milli-Q water, phosphate-buffered saline (PBS) with a pH of 7.4 and 0.1 M HCl) on the lower critical solution temperature (LCST) was detected. Furthermore, the solubilisation of a poorly soluble drug, furosemide, into the Soluplus® micelles was studied. The concentration-dependent properties of the micellar system were assessed through an examination of the micellar size, polydispersity, morphology, viscosity and solubilising properties, which were all found to be affected by the concentration, but temperature, pH and the composition of the test medium were also found to have an effect. Homogeneity in the estimated micellar size and morphology was shown for monophasic micelle dispersions in lower concentrations and with a shift towards more complex structures or aggregates in higher concentrations. The micelles were further investigated in terms of drug release and biocompatibility with mucus-producing HT29-MTX cells, where no biocompatibility issues were found. In this research, the implications for oral drug delivery are discussed and valuable preformulation information is provided on the micellar properties of a Soluplus® drug system in a liquid or semi-solid form.
Interactions of Self-Assembled Bletilla Striata Polysaccharide Nanoparticles with Bovine Serum Albumin and Biodistribution of Its Docetaxel-Loaded Nanoparticles
Authors: Zhang Guangyuan , Qiao Jin , Liu Xin , Liu Yuran , Wu Ji , Huang Long , Ji Danyang , Guan Qingxiang
Published: January 2019

Amphiphilic copolymers of stearic acid (SA)-modified Bletilla striata polysaccharides (BSPs-SA) with three different degrees of substitution (DSs) were synthesized. The effects of DS values on the properties of BSPs-SA nanoparticles were evaluated. Drug state, cytotoxicity, and histological studies were carried out. The affinity ability of bovine serum albumin (BSA) and the BSPs-SA nanoparticles was also characterized utilizing ultraviolet and fluorescence spectroscopy. Besides, the bioavailability and tissue distribution of docetaxel (DTX)-loaded BSPs-SA nanoparticles were also assessed. The results demonstrated that the DS increase of the hydrophobic stearic acid segment increased the negative charge, encapsulation efficiency, and drug-loading capacity while decreasing the critical aggregation concentration value as well as the release rate of docetaxel from the nanoparticles. Docetaxel was encapsulated in nanoparticles at the small molecules or had an amorphous status. The inhibitory capability of DTX-loaded BSPs-SA nanoparticles against 4T1 tumor cells was superior to that of Duopafei®. The ultraviolet and fluorescence results exhibited a strong binding affinity between BSPs-SA nanoparticles and bovine serum albumin, but the conformation of bovine serum albumin was not altered. Additionally, the area under the concentration–time curve (AUC0–∞) of DTX-loaded BSPs-SA nanoparticles was about 1.42-fold higher compared with Duopafei® in tumor-bearing mice. Docetaxel levels of DTX-loaded BSPs-SA nanoparticles in some organs changed, and more docetaxel accumulated in the liver, spleen, and the tumor compared with Duopafei®. The experimental results provided a theoretical guidance for further applications of BSPs-SA conjugates as nanocarriers for delivering anticancer drugs.
Behaviour of Tetrabenazine in Acid Medium: Reassessment and Impact on Formulation
Authors: Ettouati Laurent , Senta-Loys Zoé , Bourgeois Sandrine , Fenet Bernard , Le Borgne Marc , Fessi Hatem
Published: January 2019

Thorough studies of previous analytical stress data of tetrabenazine, a dopamine depleting agent, showed a potential susceptibility to acidic conditions. Hence, the behavior of tetrabenazine acidic solutions was studied by LC-MS and NMR spectroscopy. Reverse-phase LC-MS analysis of tetrabenazine acidic aqueous solutions consistently showed a main lipophilic impurity in a proportion of 15 to 20%. NMR spectroscopy studies did not allow to completely ascertain its structure. However, we hypothesize an interconversion of trans-tetrabenazine with its unstable cis isomer via an open isoquinolinium intermediate. Evaluation of tetrabenazine integrity in orodispersible films was reassessed in light of these observations after formulation and during stability study. Even if interconversion of trans-tetrabenazine with its cis isomer was observed in orodispersible films containing tetrabenazine, this phenomenon seems not to have any consequences for the overall tetrabenazine bioavailability.
Targeted Transfection Using PEGylated Cationic Liposomes Directed Towards P-Selectin Increases siRNA Delivery into Activated Endothelial Cells
Authors: Constantinescu Cristina Ana , Fuior Elena Valeria , Rebleanu Daniela , Deleanu Mariana , Simion Viorel , Voicu Geanina , Escriou Virginie , Manduteanu Ileana , Simionescu Maya , Calin Manuela
Published: January 2019

: The progress in small-interfering RNA (siRNA) therapeutics depends on the development of suitable nanocarriers to perform specific and effective delivery to dysfunctional cells. In this paper, we questioned whether P-selectin, a cell adhesion molecule specifically expressed on the surface of activated endothelial cells (EC) could be employed as a target for nanotherapeutic intervention. To this purpose, we developed and characterized P-selectin targeted PEGylated cationic liposomes able to efficiently pack siRNA and to function as efficient vectors for siRNA delivery to tumour necrosis factor-α (TNF-α) activated EC. Targeted cationic liposomes were obtained by coupling a peptide with high affinity for P-selectin to a functionalized PEGylated phospholipid inserted in the liposomes’ bilayer (Psel-lipo). As control, scrambled peptide coupled cationic liposomes (Scr-lipo) were used. The lipoplexes obtained by complexation of Psel-lipo with siRNA (Psel-lipo/siRNA) were taken up specifically and at a higher extent by TNF-α activated b.End3 endothelial cells as compared to non-targeted Scr-lipo/siRNA. The Psel-lipo/siRNA delivered with high efficiency siRNA into the cells. The lipoplexes were functional as demonstrated by the down-regulation of the selected gene (GAPDH). The results demonstrate an effective targeted delivery of siRNA into cultured activated endothelial cells using P-selectin directed PEGylated cationic liposomes, which subsequently knock-down the desired gene.
Advances in Drug Delivery and Biomaterials: Facts and Vision
Authors: Caliceti Paolo , Matricardi Pietro
Published: January 2019

Drug delivery and biomaterials are different fields of science but, at the same time, are tightly related and intertwined. The 2018 CRS Italy Chapter Annual Workshop aims to explore recent advances in design and development in these areas. Many colleagues from Europe participated to the Workshop, stimulating the discussion. To foster the discussion on recent research and networking opportunities, especially among younger attendees, all poster-presenting authors were asked to provide a short talk. The very friendly and stimulating atmosphere allowed the attendees to explore new frontiers and tackle new horizons.
Investigation of Chitosan Nanoparticles Loaded with Protocatechuic Acid (PCA) for the Resistance of Pyricularia oryzae Fungus against Rice Blast
Authors: Pham The Trinh , Nguyen Thi Hiep , Thi Thuan Vo , Nguyen Thanh-Truc , Le Tien Dung , Vo Do Minh Hoang , Nguyen Dai Hai , Nguyen Cuu Khoa , Nguyen Duy Chinh , Nguyen Trong Tuan , Bach Long Giang
Published: January 2019

In this study, chitosan nanoparticles were used as a carrier for Protocatechuic acid (PCA) to resist Pyricularia oryzae against rice blast. The final compound was characterized using zeta potentials for its surface electricity, Fourier transform infrared (FT-IR) analysis and transmission electron microscopy (TEM) were conducted for functional groups and for particle sizes and shape, respectively. The zeta potential results showed that loading PCA causes chitosan nanoparticle (CSNP) to decrease in surface electrons. The TEM images revealed that the particle size of chitosan (CS), although increasing in size when carrying PCA molecules, showed sufficient size for reasonable penetration into fungal cells. The FT-IR analysis showed that all functional group in CSNP carried PCA matched with previous studies. The antifungal test showed that diameters of inhibition zone of CS increases significantly after loading PCA, exhibiting the strongest antimicrobial effect on the Pyricularia oryzae fungus compared with weaker effects exhibited by CSNP alone or PCA. Our results suggested that CSNP loaded with PCA could be a potential compound for eradication of Pyricularia oryzae and that further testing on in vitro rice plants is recommended to reaffirm this possibility.
In Situ Growth of a High-Performance All-Solid-State Electrode for Flexible Supercapacitors Based on a PANI/CNT/EVA Composite
Authors: Guan Xipeng , Kong Debin , Huang Qin , Cao Lin , Zhang Peng , Lin Huaijun , Lin Zhidan , Yuan Hong
Published: January 2019

For the development of light, flexible, and wearable electronic devices, it is crucial to develop energy storage components combining high capacity and flexibility. Herein, an all-solid-state supercapacitor is prepared through an in situ growth method. The electrode contains polyaniline deposited on a carbon nanotube and a poly (ethylene-co-vinyl acetate) film. The hybrid electrode exhibits excellent mechanical and electrochemical performance. The optimized few-layer polyaniline wrapping layer provides a conductive network that effectively enhances the cycling stability, as 66.4% of the starting capacitance is maintained after 3000 charge/discharge cycles. Furthermore, the polyaniline (PANI)-50 displays the highest areal energy density of 83.6 mWh·cm−2, with an areal power density of 1000 mW·cm−2, and a high areal capacity of 620 mF cm−2. The assembled device delivers a high areal capacity (192.3 mF·cm−2) at the current density of 0.1 mA·cm−2, a high areal energy (26.7 mWh·cm−2) at the power density of 100 mW·cm−2, and shows no significant decrease in the performance with a bending angle of 180°. This unique flexible supercapacitor thus exhibits great potential for wearable electronics.
Valorization of Industrial Lignin as Biobased Carbon Source in Fire Retardant System for Polyamide 11 Blends
Authors: Mandlekar Neeraj , Cayla Aurélie , Rault François , Giraud Stéphane , Salaün Fabien , Guan Jinping
Published: January 2019

In this study, two different types of industrial lignin (i.e., lignosulphonate lignin (LL) and kraft lignin (DL)) were exploited as charring agents with phosphorus-based flame retardants for polyamide 11 (PA11). The effect of lignins on the thermal stability and fire behavior of PA11 combined with phosphinate additives (namely, aluminum phosphinate (AlP) and zinc phosphinate (ZnP)) has been studied by thermogravimetric analysis (TGA), UL 94 vertical flame spread, and cone calorimetry tests. Various blends of flame retarded PA11 were prepared by melt process using a twin-screw extruder. Thermogravimetric analyses showed that the LL containing ternary blends are able to provide higher thermal stability, as well as a developed char residue. The decomposition of the phosphinates led to the formation of phosphate compounds in the condensed phase, which promotes the formation of a stable char. Flammability tests showed that LL/ZnP ternary blends were able to achieve self-extinction and V-1 classification; the other formulations showed a strong melt dripping and higher burning. In addition to this, cone calorimetry results showed that the most enhanced behavior was found when 10 wt % of LL and AlP were combined, which strongly reduced PHRR (−74%) and THR (−22%), due to the interaction between LL and AlP, which not only promotes char formation but also confers the stability to char in the condensed phase.
A Parallel Bicomponent TPU/PI Membrane with Mechanical Strength Enhanced Isotropic Interfaces Used as Polymer Electrolyte for Lithium-Ion Battery
Authors: Cai Ming , Zhu Jianwei , Yang Chaochao , Gao Ruoyang , Shi Chuan , Zhao Jinbao
Published: January 2019

In this work, a side-by-side bicomponent thermoplastic polyurethane/polyimide (TPU/PI) polymer electrolyte prepared with side-by-side electrospinning method is reported for the first time. Symmetrical TPU and PI co-occur on one fiber, and are connected by an interface transition layer formed by the interdiffusion of two solutions. This structure of the as-prepared TPU/PI polymer electrolyte can integrate the advantages of high thermal stable PI and good mechanical strength TPU, and mechanical strength is further increased by those isotropic interface transition layers. Moreover, benefiting from micro-nano pores and the high porosity of the structure, TPU/PI polymer electrolyte presents high electrolyte uptake (665%) and excellent ionic conductivity (5.06 mS·cm−1) at room temperature. Compared with PE separator, TPU/PI polymer electrolyte exhibited better electrochemical stability, and using it as the electrolyte and separator, the assembled Li/LiMn2O4 cell exhibits low inner resistance, stable cyclic and notably high rate performance. Our study indicates that the TPU/PI membrane is a promising polymer electrolyte for high safety lithium-ion batteries.
Without Why: Useless Plants in Daoism and Christianity
Authors: Mickey Sam
Published: January 2019

This article focuses on three examples of religious considerations of plants, with specific attention to the uselessness of plants. Drawing on Christian and Daoist sources, the examples include the following: (1) the lilies of the field described by Jesus in the Gospels of Matthew and Luke; (2) the useless tree of Zhuangzi; and (3) Martin Heidegger’s reading of a mystic poet influenced by Meister Eckhart, Angelus Silesius, for whom a rose blooms “without why,” which resonates with Heidegger’s deconstruction (Destruktion) of the history of metaphysics and his interpretation of uselessness in Zhuangzi. Each of those examples involves non-anthropocentric engagements with the uselessness of plants, which is not to say that they are completely free of the anthropocentrically scaled perspectives that assimilate uselessness into the logistics of agricultural societies. In contrast to ethical theories of the intrinsic value (biocentrism) or systemic value (ecocentrism) of plants, these Christian and Daoist perspectives converge with ecological deconstruction in suggesting that ethical encounters with plants emerge through attention to their uselessness. A viable response to planetary emergency can emerge with the radical passivity of effortless action, which is a careless care that finds solidarity with the carefree ways of plants.
Erratum: Labelle, A., et al. Agent-Based Model for End-of-Life Product Flow Analysis, Resources 2018, 7, 42
Authors: Labelle Alexandre , Frayret Jean-Marc
Published: January 2019

The authors wish to make the following corrections to this paper [...]
Nonlocal Tensor Sparse Representation and Low-Rank Regularization for Hyperspectral Image Compressive Sensing Reconstruction
Authors: Xue Jize , Zhao Yongqiang , Liao Wenzhi , Chan Jonathan Cheung-Wai
Published: January 2019

Hyperspectral image compressive sensing reconstruction (HSI-CSR) is an important issue in remote sensing, and has recently been investigated increasingly by the sparsity prior based approaches. However, most of the available HSI-CSR methods consider the sparsity prior in spatial and spectral vector domains via vectorizing hyperspectral cubes along a certain dimension. Besides, in most previous works, little attention has been paid to exploiting the underlying nonlocal structure in spatial domain of the HSI. In this paper, we propose a nonlocal tensor sparse and low-rank regularization (NTSRLR) approach, which can encode essential structured sparsity of an HSI and explore its advantages for HSI-CSR task. Specifically, we study how to utilize reasonably the l 1 -based sparsity of core tensor and tensor nuclear norm function as tensor sparse and low-rank regularization, respectively, to describe the nonlocal spatial-spectral correlation hidden in an HSI. To study the minimization problem of the proposed algorithm, we design a fast implementation strategy based on the alternative direction multiplier method (ADMM) technique. Experimental results on various HSI datasets verify that the proposed HSI-CSR algorithm can significantly outperform existing state-of-the-art CSR techniques for HSI recovery.
Hyperspectral Image Classification Using Similarity Measurements-Based Deep Recurrent Neural Networks
Authors: Ma Andong , Filippi Anthony M. , Wang Zhangyang , Yin Zhengcong
Published: January 2019

Classification is a common objective when analyzing hyperspectral images, where each pixel is assigned to a predefined label. Deep learning-based algorithms have been introduced in the remote-sensing community successfully in the past decade and have achieved significant performance improvements compared with conventional models. However, research on the extraction of sequential features utilizing a single image, instead of multi-temporal images still needs to be further investigated. In this paper, a novel strategy for constructing sequential features from a single image in long short-term memory (LSTM) is proposed. Two pixel-wise-based similarity measurements, including pixel-matching (PM) and block-matching (BM), are employed for the selection of sequence candidates from the whole image. Then, the sequential structure of a given pixel can be constructed as the input of LSTM by utilizing the first several matching pixels with high similarities. The resulting PM-based LSTM and BM-based LSTM are appealing, as all pixels in the whole image are taken into consideration when calculating the similarity. In addition, BM-based LSTM also utilizes local spectral-spatial information that has already shown its effectiveness in hyperspectral image classification. Two common distance measures, Euclidean distance and spectral angle mapping, are also investigated in this paper. Experiments with two benchmark hyperspectral images demonstrate that the proposed methods achieve marked improvements in classification performance relative to the other state-of-the-art methods considered. For instance, the highest overall accuracy achieved on the Pavia University image is 96.20% (using both BM-based LSTM and spectral angle mapping), which is an improvement compared with 84.45% overall accuracy generated by 1D convolutional neural networks.
Evaluation of Different Machine Learning Methods and Deep-Learning Convolutional Neural Networks for Landslide Detection
Authors: Ghorbanzadeh Omid , Blaschke Thomas , Gholamnia Khalil , Meena Sansar Raj , Tiede Dirk , Aryal Jagannath
Published: January 2019

There is a growing demand for detailed and accurate landslide maps and inventories around the globe, but particularly in hazard-prone regions such as the Himalayas. Most standard mapping methods require expert knowledge, supervision and fieldwork. In this study, we use optical data from the Rapid Eye satellite and topographic factors to analyze the potential of machine learning methods, i.e., artificial neural network (ANN), support vector machines (SVM) and random forest (RF), and different deep-learning convolution neural networks (CNNs) for landslide detection. We use two training zones and one test zone to independently evaluate the performance of different methods in the highly landslide-prone Rasuwa district in Nepal. Twenty different maps are created using ANN, SVM and RF and different CNN instantiations and are compared against the results of extensive fieldwork through a mean intersection-over-union (mIOU) and other common metrics. This accuracy assessment yields the best result of 78.26% mIOU for a small window size CNN, which uses spectral information only. The additional information from a 5 m digital elevation model helps to discriminate between human settlements and landslides but does not improve the overall classification accuracy. CNNs do not automatically outperform ANN, SVM and RF, although this is sometimes claimed. Rather, the performance of CNNs strongly depends on their design, i.e., layer depth, input window sizes and training strategies. Here, we conclude that the CNN method is still in its infancy as most researchers will either use predefined parameters in solutions like Google TensorFlow or will apply different settings in a trial-and-error manner. Nevertheless, deep-learning can improve landslide mapping in the future if the effects of the different designs are better understood, enough training samples exist, and the effects of augmentation strategies to artificially increase the number of existing samples are better understood.
Improvement and Validation of NASA/MODIS NRT Global Flood Mapping
Authors: Lin Li , Di Liping , Tang Junmei , Yu Eugene , Zhang Chen , Rahman Md. Shahinoor , Shrestha Ranjay , Kang Lingjun
Published: January 2019

The remote-sensing based Flood Crop Loss Assessment Service System (RF-CLASS) is a web service based system developed and managed by the Center for Spatial Information Science and Systems (CSISS). The system uses Moderate Resolution Imaging Spectroradiometer (MODIS)-based flood data, which was implemented by the Dartmouth Flood Observatory (DFO), to provide an estimation of crop loss from floods. However, due to the spectral similarity between water and shadow, a noticeable amount of false classification of shadow can be found in the DFO flood products. Traditional methods can be utilized to remove cloud shadow and part of mountain shadow. This paper aims to develop an algorithm to filter out noise from permanent mountain shadow in the flood layer. The result indicates that mountain shadow was significantly removed by using the proposed approach. In addition, the gold standard test indicated a small number of actual water surfaces were misidentified by the proposed algorithm. Furthermore, experiments also suggest that increasing the spatial resolution of the slope helped reduce more noise in mountains. The proposed algorithm achieved acceptable overall accuracy (>80%) in all different filters and higher overall accuracies were observed when using lower slope filters. This research is one of the very first discussions on identifying false flood classification from terrain shadow by using the highly efficient method.
Optimization of Sensitivity of GOES-16 ABI Sea Surface Temperature by Matching Satellite Observations with L4 Analysis
Authors: Petrenko Boris , Ignatov Alexander , Kihai Yury , Pennybacker Matthew
Published: January 2019

Monitoring of the diurnal warming cycle in sea surface temperature (SST) is one of the key tasks of the new generation geostationary sensors, the Geostationary Operational Environmental Satellite (GOES)-16/17 Advanced Baseline Imager (ABI), and the Himawari-8/9 Advanced Himawari Imager (AHI). However, such monitoring requires modifications of the conventional SST retrieval algorithms. In order to closely reproduce temporal and spatial variations in SST, the sensitivity of retrieved SST to SSTskin should be as close to 1 as possible. Regression algorithms trained by matching satellite observations with in situ SST from drifting and moored buoys do not meet this requirement. Since the geostationary sensors observe tropical regions over larger domains and under more favorable conditions than mid-to-high latitudes, the matchups are predominantly concentrated within a narrow range of in situ SSTs >2 85 K. As a result, the algorithms trained against in situ SST provide the sensitivity to SSTskin as low as ~0.7 on average. An alternative training method, employed in the National Oceanic and Atmospheric Administration (NOAA) Advanced Clear-Sky Processor for Oceans, matches nighttime satellite clear-sky observations with the analysis L4 SST, interpolated to the sensor’s pixels. The method takes advantage of the total number of clear-sky pixels being large even at high latitudes. The operational use of this training method for ABI and AHI has increased the mean sensitivity of the global regression SST to ~0.9 without increasing regional biases. As a further development towards improved SSTskin retrieval, the piecewise regression SST algorithm was developed, which provides optimal sensitivity in every SST pixel. The paper describes the global and the piecewise regression algorithms trained against analysis SST and illustrates their performance with SST retrievals from the GOES-16 ABI.
Cropland Mapping Using Fusion of Multi-Sensor Data in a Complex Urban/Peri-Urban Area
Authors: Nduati Eunice , Sofue Yuki , Matniyaz Akbar , Park Jong Geol , Yang Wei , Kondoh Akihiko
Published: January 2019

Urban and Peri-urban Agriculture (UPA) has recently come into sharp focus as a valuable source of food for urban populations. High population density and competing land use demands lend a spatiotemporally dynamic and heterogeneous nature to urban and peri-urban croplands. For the provision of information to stakeholders in agriculture and urban planning and management, it is necessary to characterize UPA by means of regular mapping. In this study, partially cloudy, intermittent moderate resolution Landsat images were acquired for an area adjacent to the Tokyo Metropolis, and their Normalized Difference Vegetation Index (NDVI) was computed. Daily MODIS 250 m NDVI and intermittent Landsat NDVI images were then fused, to generate a high temporal frequency synthetic NDVI data set. The identification and distinction of upland croplands from other classes (including paddy rice fields), within the year, was evaluated on the temporally dense synthetic NDVI image time-series, using Random Forest classification. An overall classification accuracy of 91.7% was achieved, with user’s and producer’s accuracies of 86.4% and 79.8%, respectively, for the cropland class. Cropping patterns were also estimated, and classification of peanut cultivation based on post-harvest practices was assessed. Image spatiotemporal fusion provides a means for frequent mapping and continuous monitoring of complex UPA in a dynamic landscape.
Algorithms for Doppler Spectral Density Data Quality Control and Merging for the Ka-Band Solid-State Transmitter Cloud Radar
Authors: Liu Liping , Zheng Jiafeng
Published: January 2019

The Chinese Ka-band solid-state transmitter cloud radar (CR) can operate in three different work modes with different pulse widths and coherent integration and non-coherent integration numbers to meet the requirement for long-term cloud measurements. The CR was used to observe cloud and precipitation data in southern China in 2016. In order to resolve the data quality problems caused by coherent integration and pulse compression, which are used to detect weak cloud in the cloud radar, this study focuses on analyzing the consistencies of reflectivity spectra using the three modes and the influence of coherent integration and pulse compression, developing an algorithm for Doppler spectral density data quality control (QC) and merging based on multiple-mode observation data. After dealiasing Doppler velocity and artefact removal, the three types of Doppler spectral density data were merged. Then, Doppler moments such as reflectivity, radial velocity, and spectral width were recalculated from the merged reflectivity spectra. Performance of the merging algorithm was evaluated. Three conclusions were drawn. Firstly, four rounds of coherent integration with a pulse repetition frequency (PRF) of 8333 Hz underestimated the reflectivity spectra for Doppler velocities exceeding 2 m·s−1, causing a large negative bias in the reflectivity and radial velocity when large drops were present. In contrast, two rounds of coherent integration affected the reflectivity spectra to a lesser extent. The reflectivity spectra were underestimated for low signal-to-noise ratios in the low-sensitivity mode. Secondly, pulse compression improved the radar sensitivity and air vertical speed observation, whereas the precipitation mode and coherent integration led to an underestimation of the number concentration of big raindrops and an overestimation of the number concentration of small drops. Thirdly, a comparison of the individual spectra with the merged reflectivity spectra showed that the Doppler moments filled in the gaps in the individual spectra during weak cloud periods, reduced the effects of coherent integration and pulse compression in liquid precipitation, mitigated the aliasing of Doppler velocity, and removed the artefacts, yielding a comprehensive and accurate depiction of most of the clouds and precipitation in the vertical column above the radar. The recalculated moments of the Doppler spectra had better quality than those merged from raw data.
Evaluation of CLARA-A2 and ISCCP-H Cloud Cover Climate Data Records over Europe with ECA&D Ground-Based Measurements
Authors: Tzallas Vasileios , Hatzianastassiou Nikos , Benas Nikos , Meirink Jan Fokke , Matsoukas Christos , Stackhouse Paul , Vardavas Ilias
Published: January 2019

Clouds are of high importance for the climate system but they still remain one of its principal uncertainties. Remote sensing techniques applied to satellite observations have assisted tremendously in the creation of long-term and homogeneous data records; however, satellite data sets need to be validated and compared with other data records, especially ground measurements. In the present study, the spatiotemporal distribution and variability of Total Cloud Cover (TCC) from the Satellite Application Facility on Climate Monitoring (CM SAF) Cloud, Albedo And Surface Radiation dataset from AVHRR data—edition 2 (CLARA-A2) and the International Satellite Cloud Climatology Project H-series (ISCCP-H) is analyzed over Europe. The CLARA-A2 data record has been created using measurements of the Advanced Very High Resolution Radiometer (AVHRR) instrument onboard the polar orbiting NOAA and the EUMETSAT MetOp satellites, whereas the ISCCP-H data were produced by a combination of measurements from geostationary meteorological satellites and the AVHRR instrument on the polar orbiting satellites. An intercomparison of the two data records is performed over their common period, 1984 to 2012. In addition, a comparison of the two satellite data records is made against TCC observations at 22 meteorological stations in Europe, from the European Climate Assessment & Dataset (ECA&D). The results indicate generally larger ISCCP-H TCC with respect to the corresponding CLARA-A2 data, in particular in the Mediterranean. Compared to ECA&D data, both satellite datasets reveal a reasonable performance, with overall mean TCC biases of 2.1 and 5.2% for CLARA-A2 and ISCCP-H, respectively. This, along with the higher correlation coefficients between CLARA-A2 and ECA&D TCC, indicates the better performance of CLARA-A2 TCC data.
A Mobile Crowd Sensing Application for Hypertensive Patients
Authors: Jovanović Slađana , Jovanović Milan , Škorić Tamara , Jokić Stevan , Milovanović Branislav , Katzis Konstantinos , Bajić Dragana
Published: January 2019

Mobile crowd sensing (MCS) is an application that collects data from a network of conscientious volunteers and implements it for the common or personal benefit. This contribution proposes an implementation that collects the data from hypertensive patients, thus creating an experimental database using the cloud service Platform as a Service (PaaS). The challenge is to perform the analysis without the main diagnostic feature for hypertension—the blood pressure. The other problems consider the data reliability in an environment full of artifacts and with limited bandwidth and battery resources. In order to motivate the MCS volunteers, a feedback about the patient’s current status is created, provided by the means of machine-learning (ML) techniques. Two techniques are investigated and the Random Forest algorithm yielded the best results. The proposed platform, with slight modifications, can be adapted to the patients with other cardiovascular problems.
Screen-Printed, Pure Carbon-Black Thermocouple Fabrication and Seebeck Coefficients
Authors: Offenzeller Christina , Knoll Marcel , Jakoby Bernhard , Hilber Wolfgang
Published: January 2019

Thermocouples classically consist of two metals or semiconductor components that are joined at one end, where temperature is measured. Carbon black is a low-cost semiconductor with a Seebeck coefficient that depends on the structure of the carbon particles. Different carbon black screen-printing inks generally exhibit different Seebeck coefficients, and two can therefore be combined to realize a thermocouple. In this work, we used a set of four different commercially available carbon-black screen-printing inks to print all-carbon-black thermocouples. The outputs of these thermocouples were characterized and their Seebeck coefficients determined. We found that the outputs of pure carbon-black thermocouples are reasonably stable, linear, and quantitatively comparable to those of commercially available R- or S-type thermocouples. It is thus possible to fabricate thermocouples by an easily scalable, cost-efficient process that combines two low-cost materials.
A Fiber Optic Ultrasonic Sensing System for High Temperature Monitoring Using Optically Generated Ultrasonic Waves
Authors: Zhou Jingcheng , Guo Xu , Du Cong , Cao Chengyu , Wang Xingwei
Published: January 2019

This paper presents the design, fabrication, and characterization of a novel fiber optic ultrasonic sensing system based on the photoacoustic (PA) ultrasound generation principle and Fabry-Perot interferometer principle for high temperature monitoring applications. The velocity of a sound wave traveling in a medium is proportional to the medium’s temperature. The fiber optic ultrasonic sensing system was applied to measure the change of the velocity of sound. A fiber optic ultrasonic generator and a Fabry-Perot fiber sensor were used as the signal generator and receiver, respectively. A carbon black-polydimethylsiloxane (PDMS) material was utilized as the photoacoustic material for the fiber optic ultrasonic generator. Two tests were performed. The system verification test proves the ultrasound sensing capability. The high temperature test validates the high temperature measurement capability. The sensing system survived 700 °C. It successfully detects the ultrasonic signal and got the temperature measurements. The test results agreed with the reference sensor data. Two potential industry applications of fiber optic ultrasonic sensing system are, it could serve as an acoustic pyrometer for temperature field monitoring in an industrial combustion facility, and it could be used for exhaust gas temperature monitoring for a turbine engine.
The Sensitivity of Grating-Based SPR Sensors with Wavelength Interrogation
Authors: Cao Jianjun , Sun Yuan , Kong Yan , Qian Weiying
Published: January 2019

In this paper, we derive the analytical expression for the sensitivity of grating-based surface plasmon resonance (SPR) sensors working in wavelength interrogation. The theoretical analysis shows that the sensitivity increases with increasing wavelength and is saturated beyond a certain wavelength for Au and Ag gratings, while it is almost constant for Al gratings in the wavelength range of 500 to 1000 nm. More importantly, the grating period (P) and the diffraction order (m) dominate the value of sensitivity. Higher sensitivity is possible for SPR sensors with a larger grating period and lower diffraction order. At long wavelengths, a simple expression of P/|m| can be used to estimate the sensor sensitivity. Moreover, we perform experimental measurements of the sensitivity of an SPR sensor based on an Al grating to confirm the theoretical calculations.
Infrared-Inertial Navigation for Commercial Aircraft Precision Landing in Low Visibility and GPS-Denied Environments
Authors: Zhang Lei , Zhai Zhengjun , He Lang , Wen Pengcheng , Niu Wensheng
Published: January 2019

This paper proposes a novel infrared-inertial navigation method for the precise landing of commercial aircraft in low visibility and Global Position System (GPS)-denied environments. Within a Square-root Unscented Kalman Filter (SR_UKF), inertial measurement unit (IMU) data, forward-looking infrared (FLIR) images and airport geo-information are integrated to estimate the position, velocity and attitude of the aircraft during landing. Homography between the synthetic image and the real image which implicates the camera pose deviations is created as vision measurement. To accurately extract real runway features, the current results of runway detection are used as the prior knowledge for the next frame detection. To avoid possible homography decomposition solutions, it is directly converted to a vector and fed to the SR_UKF. Moreover, the proposed navigation system is proven to be observable by nonlinear observability analysis. Last but not least, a general aircraft was elaborately equipped with vision and inertial sensors to collect flight data for algorithm verification. The experimental results have demonstrated that the proposed method could be used for the precise landing of commercial aircraft in low visibility and GPS-denied environments.
Three-Dimensional Monitoring of Plant Structural Parameters and Chlorophyll Distribution
Authors: Itakura Kenta , Kamakura Itchoku , Hosoi Fumiki
Published: January 2019

Image analysis is widely used for accurate and efficient plant monitoring. Plants have complex three-dimensional (3D) structures; hence, 3D image acquisition and analysis is useful for determining the status of plants. Here, 3D images of plants were reconstructed using a photogrammetric approach, called “structure from motion”. Chlorophyll content is an important parameter that determines the status of plants. Chlorophyll content was estimated from 3D images of plants with color information. To observe changes in the chlorophyll content and plant structure, a potted plant was kept for five days under a water stress condition and its 3D images were taken once a day. As a result, the normalized Red value and the chlorophyll content were correlated; a high R2 value (0.81) was obtained. The absolute error of the chlorophyll content estimation in cross-validation studies was 4.0 × 10−2 μg/mm2. At the same time, the structural parameters (i.e., the leaf inclination angle and the azimuthal angle) were calculated by simultaneously monitoring the changes in the plant’s status in terms of its chlorophyll content and structural parameters. By combining these parameters related to plant information in plant image analysis, early detection of plant stressors, such as water stress, becomes possible.
Robust Kalman Filter Aided GEO/IGSO/GPS Raw-PPP/INS Tight Integration
Authors: Gao Zhouzheng , Li You , Zhuang Yuan , Yang Honglei , Pan Yuanjin , Zhang Hongping
Published: January 2019

Reliable and continuous navigation solutions are essential for high-accuracy location-based services. Currently, the real-time kinematic (RTK) based Global Positioning System (GPS) is widely utilized to satisfy such requirements. However, RTK’s accuracy and continuity are limited by the insufficient number of the visible satellites and the increasing length of base-lines between reference-stations and rovers. Recently, benefiting from the development of precise point positioning (PPP) and BeiDou satellite navigation systems (BDS), the issues existing in GPS RTK can be mitigated by using GPS and BDS together. However, the visible satellite number of GPS + BDS may decrease in dynamic environments. Therefore, the inertial navigation system (INS) is adopted to bridge GPS + BDS PPP solutions during signal outage periods. Meanwhile, because the quality of BDS geosynchronous Earth orbit (GEO) satellites is much lower than that of inclined geo-synchronous orbit (IGSO) satellites, the predicted observation residual based robust extended Kalman filter (R-EKF) is adopted to adjust the weight of GEO and IGSO data. In this paper, the mathematical model of the R-EKF aided GEO/IGSO/GPS PPP/INS tight integration, which uses the raw observations of GPS + BDS, is presented. Then, the influences of GEO, IGSO, INS, and R-EKF on PPP are evaluated by processing land-borne vehicle data. Results indicate that (1) both GEO and IGSO can provide accuracy improvement on GPS PPP; however, the contribution of IGSO is much more visible than that of GEO; (2) PPP’s accuracy and stability can be further improved by using INS; (3) the R-EKF is helpful to adjust the weight of GEO and IGSO in the GEO/IGSO/GPS PPP/INS tight integration and provide significantly higher positioning accuracy.
Ripeness Prediction of Postharvest Kiwifruit Using a MOS E-Nose Combined with Chemometrics
Authors: Du Dongdong , Wang Jun , Wang Bo , Zhu Luyi , Hong Xuezhen
Published: January 2019

Postharvest kiwifruit continues to ripen for a period until it reaches the optimal “eating ripe” stage. Without damaging the fruit, it is very difficult to identify the ripeness of postharvest kiwifruit by conventional means. In this study, an electronic nose (E-nose) with 10 metal oxide semiconductor (MOS) gas sensors was used to predict the ripeness of postharvest kiwifruit. Three different feature extraction methods (the max/min values, the difference values and the 70th s values) were employed to discriminate kiwifruit at different ripening times by linear discriminant analysis (LDA), and results showed that the 70th s values method had the best performance in discriminating kiwifruit at different ripening stages, obtaining a 100% original accuracy rate and a 99.4% cross-validation accuracy rate. Partial least squares regression (PLSR), support vector machine (SVM) and random forest (RF) were employed to build prediction models for overall ripeness, soluble solids content (SSC) and firmness. The regression results showed that the RF algorithm had the best performance in predicting the ripeness indexes of postharvest kiwifruit compared with PLSR and SVM, which illustrated that the E-nose data had high correlations with overall ripeness (training: R2 = 0.9928; testing: R2 = 0.9928), SSC (training: R2 = 0.9749; testing: R2 = 0.9143) and firmness (training: R2 = 0.9814; testing: R2 = 0.9290). This study demonstrated that E-nose could be a comprehensive approach to predict the ripeness of postharvest kiwifruit through aroma volatiles.
Chemical Source Searching by Controlling a Wheeled Mobile Robot to Follow an Online Planned Route in Outdoor Field Environments
Authors: Li Ji-Gong , Cao Meng-Li , Meng Qing-Hao
Published: January 2019

In this paper, we present an estimation-based route planning (ERP) method for chemical source searching using a wheeled mobile robot and validate its effectiveness with outdoor field experiments. The ERP method plans a dynamic route for the robot to follow to search for a chemical source according to time-varying wind and an estimated chemical-patch path (C-PP), where C-PP is the historical trajectory of a chemical patch detected by the robot, and normally different from the chemical plume formed by the spatial distribution of all chemical patches previously released from the source. Owing to the limitations of normal gas sensors and actuation capability of ground mobile robots, it is quite hard for a single robot to directly trace the intermittent and rapidly swinging chemical plume resulting from the frequent and random changes of wind speed and direction in outdoor field environments. In these circumstances, tracking the C-PP originating from the chemical source back could help the robot approach the source. The proposed ERP method was tested in two different outdoor fields using a wheeled mobile robot. Experimental results indicate that the robot adapts to the time-varying airflow condition, arriving at the chemical source with an average success rate and approaching effectiveness of about 90% and 0.4~0.6, respectively.
HEALPix-IA: A Global Registration Algorithm for Initial Alignment
Authors: Gao Yongzhuo , Du Zhijiang , Xu Wei , Li Mingyang , Dong Wei
Published: January 2019

Methods of point cloud registration based on ICP algorithm are always limited by convergence rate, which is related to initial guess. A good initial alignment transformation can sharply reduce convergence time and raise efficiency. In this paper, we propose a global registration method to estimate the initial alignment transformation based on HEALPix (Hierarchical Equal Area isoLatitude Pixelation of a sphere), an algorithm for spherical projections. We adopt EGI (Extended Gaussian Image) method to map the normals of the point cloud and estimate the transformation with optimized point correspondence. Cross-correlation method is used to search the best alignment results in consideration of the accuracy and robustness of the algorithm. The efficiency and accuracy of the proposed algorithm were verified with created model and real data from various sensors in comparison with similar methods.