bluuebunny/crossref_metadata_2025 huggingface dataset:
Improving the Oral Bioavailability of an Anti-Glioma Prodrug CAT3 Using Novel Solid Lipid Nanoparticles Containing Oleic Acid-CAT3 Conjugates
Authors: Wang Hongliang , Li Lin , Ye Jun , Wang Rubing , Wang Renyun , Hu Jinping , Wang Yanan , Dong Wujun , Xia Xuejun , Yang Yanfang , Gao Yue , Gao Lili , Liu Yuling
Published: February 2020

13a-(S)-3-pivaloyloxyl-6,7-dimethoxyphenanthro(9,10-b)-indolizidine (CAT3) is a novel oral anti-glioma pro-drug with a potent anti-tumor effect against temozolomide-resistant glioma in vivo. However, poor lipid solubility has limited the encapsulation efficacy during formulation development. Moreover, although the active metabolite of CAT3, 13a(S)-3-hydroxyl-6,7-dimethoxyphenanthro(9,10-b)-indolizidine (PF403), can penetrate the blood-brain barrier and approach the brain tissue with a 1000-fold higher anti-glioma activity than CAT3 in vitro, its bioavailability and Cmax were considerably low in plasma, limiting the anti-tumor efficacy. In this study, a novel oleic acid-CAT3 conjugate (OA-CAT3) was synthesized at the first time to increase the lipid solubility of CAT3. The OA-CAT3 loaded solid lipid nanoparticles (OA-CAT3-SLN) were constructed using an ultrasonic technique to enhance the bioavailability and Cmax of PF403 in plasma. Our results demonstrated that CAT3 was amorphous in the lipid core of OA-CAT3-SLN and the in vitro release was well controlled. Furthermore, the encapsulation efficacy and the zeta potential increased to 80.65 ± 6.79% and −26.7 ± 0.46 mV, respectively, compared to the normal CAT3 loaded SLN. As indicated by the high-performance liquid chromatography-mass spectrometry (HPLC-MS/MS) quantitation, the monolayer cellular transepithelial transport rate of OA-CAT3-SLN improved by 2.42-fold relied on cholesterol compared to the CAT3 suspension. Hence, the in vitro cell viability of OA-CAT3-SLN in C6 glioma cells decreased to 29.77% ± 2.13% and 10.75% ± 3.12% at 48 and 72 h, respectively. Finally, compared to the CAT3 suspension, the in vivo pharmacokinetics in rats indicated that the plasma bioavailability and Cmax of PF403 as afforded by OA-CAT3-SLN increased by 1.7- and 5.5-fold, respectively. Overall, the results indicate that OA-CAT3-SLN could be an efficacious delivery system in the treatment of glioma.
Practical Guide for Quantification of In Vivo Degradation Rates for Therapeutic Proteins with Single-Cell Resolution Using Fluorescence Ratio Imaging
Authors: Nessler Ian , Cilliers Cornelius , Thurber Greg M.
Published: February 2020

Many tools for studying the pharmacokinetics of biologics lack single-cell resolution to quantify the heterogeneous tissue distribution and subsequent therapeutic degradation in vivo. This protocol describes a dual-labeling technique using two near-infrared dyes with widely differing residualization rates to efficiently quantify in vivo therapeutic protein distribution and degradation rates at the single cell level (number of proteins/cell) via ex vivo flow cytometry and histology. Examples are shown for four biologics with varying rates of receptor internalization and degradation and a secondary dye pair for use in systems with lower receptor expression. Organ biodistribution, tissue-level confocal microscopy, and cellular-level flow cytometry were used to image the multi-scale distribution of these agents in tumor xenograft mouse models. The single-cell measurements reveal highly heterogeneous delivery, and degradation results show the delay between peak tumor uptake and maximum protein degradation. This approach has broad applicability in tracking the tissue and cellular distribution of protein therapeutics for drug development and dose determination.
Absorption and Intestinal Metabolic Profile of Oleocanthal in Rats
Authors: López-Yerena Anallely , Vallverdú-Queralt Anna , Mols Raf , Augustijns Patrick , Lamuela-Raventós Rosa M. , Escribano-Ferrer Elvira
Published: February 2020

Oleocanthal (OLC), a phenolic compound of extra virgin olive oil (EVOO), has emerged as a potential therapeutic agent against a variety of diseases due to its anti-inflammatory activity. The aim of the present study is to explore its in vivo intestinal absorption and metabolism. An in situ perfusion technique in rats was used, involving simultaneous sampling from the luminal perfusate and mesenteric blood. Samples were analysed by UHPLC–MS–MS for the presence of oleocanthal (OLC) and its metabolites. OLC was mostly metabolized by phase I metabolism, undergoing hydration, hydrogenation and hydroxylation. Phase II reactions (glucuronidation of hydrogenated OLC and hydrated metabolites) were observed in plasma samples. OLC was poorly absorbed in the intestine, as indicated by the low effective permeability coefficient (2.23 ± 3.16 × 10−5 cm/s) and apparent permeability coefficient (4.12 ± 2.33 × 10−6 cm/s) obtained relative to the values of the highly permeable reference compound levofloxacin (LEV). The extent of OLC absorption reflected by the area under the mesenteric blood-time curve normalized by the inlet concentration (AUC) was also lower than that of LEV (0.25 ± 0.04 vs. 0.64 ± 0.03, respectively). These results, together with the observed intestinal metabolism, suggest that OLC has a moderate-to-low oral absorption; but higher levels of OLC are expected to reach human plasma vs. rat plasma.
Chemical Analysis of the Essential Oil from Siparuna echinata (Kunth) A. DC. (Siparunaceae) of Ecuador and Isolation of the Rare Terpenoid Sipaucin A
Authors: García Jessica , Gilardoni Gianluca , Cumbicus Nixon , Morocho Vladimir
Published: February 2020

The phytochemical research on the species Siparuna echinata, collected in the Province of Loja (Ecuador), led to the isolation of a rare sesquiterpenoid, called Sipaucin A. The structure was confirmed by nuclear magnetic resonance (NMR) and mass spectrometry (MS). Furthermore, the essential oil of the fruits was obtained by hydrodistillation and analyzed by gas chromatography, coupled to mass spectrometry (GC-MS) and flame ionization detector (GC-FID). Twenty-seven compounds were identified in a polydimethylsiloxane column (DB-5ms) and nineteen in a polyethylene glycol column (HP-INNOWax). Major compounds were α-pinene (24.3%, 20.3%), β-pinene (21.7%, 22.7%), β-myrcene (11.3%, 14.8%), limonene (10.0%, 11.3%), cis-ocimene (8.5%, 8.1%), and trans-ocimene (8.9%, 8.4%). In addition to the chemical analysis, the essential oil was submitted to enantioselective analysis of two major chiral monotherpenes, determining an enantiomeric excess of 100.0% for (+)-α-pinene and 6.7% for (+)-β-pinene.
Comparative Chloroplast Genomics of Endangered Euphorbia Species: Insights into Hotspot Divergence, Repetitive Sequence Variation, and Phylogeny
Authors: Khan Arif , Asaf Sajjad , Khan Abdul Latif , Shehzad Tariq , Al-Rawahi Ahmed , Al-Harrasi Ahmed
Published: February 2020

Euphorbia is one of the largest genera in the Euphorbiaceae family, comprising 2000 species possessing commercial, medicinal, and ornamental importance. However, there are very little data available on their molecular phylogeny and genomics, and uncertainties still exist at a taxonomic level. Herein, we sequence the complete chloroplast (cp) genomes of two species, E. larica and E. smithii, of the genus Euphorbia through next-generation sequencing and perform a comparative analysis with nine related genomes in the family. The results revealed that the cp genomes had similar quadripartite structure, gene content, and genome organization with previously reported genomes from the same family. The size of cp genomes ranged from 162,172 to 162,358 bp with 132 and 133 genes, 8 rRNAs, 39 tRNA in E. smithii and E. larica, respectively. The numbers of protein-coding genes were 85 and 86, with each containing 19 introns. The four-junction regions were studied and results reveal that rps19 was present at JLB (large single copy region and inverted repeat b junction) in E. larica where its complete presence was located in the IRb (inverted repeat b) region in E. smithii. The sequence comparison revealed that highly divergent regions in rpoC1, rpocB, ycf3, clpP, petD, ycf1, and ndhF of the cp genomes might provide better understanding of phylogenetic inferences in the Euphorbiaceae and order Malpighiales. Phylogenetic analyses of this study illustrate sister clades of E. smithii with E. tricullii and these species form a monophyletic clade with E. larica. The current study might help us to understand the genome architecture, genetic diversity among populations, and evolutionary depiction in the genera.
Electrospun Silver Nanoparticles-Embedded Feather Keratin/Poly(vinyl alcohol)/Poly(ethylene oxide) Antibacterial Composite Nanofibers
Authors: He Ming , Chen Man , Dou Yao , Ding Jiao , Yue Hangbo , Yin Guoqiang , Chen Xunjun , Cui Yingde
Published: February 2020

Feathers, which contain >90% keratin, are valuable natural protein resources. The aim of this study is to prepare antimicrobial feather keratin (FK)-based nanofibers by incorporating silver nanoparticles (AgNPs). A series of AgNPs-embedded feather keratin/poly(vinyl alcohol)/poly(ethylene oxide) (FK/PVA/PEO) composite nanofibers with varying amounts of AgNPs content were fabricated by electrospinning. Their morphology, crystallinity, thermal stability, tensile property, and antibacterial activity were systematically investigated. The average diameters of composite nanofibers gradually decreased with increases in the amount of AgNPs. The crystallinity, thermal stability, and antibacterial activity of FK/PVA/PEO nanofibers were enhanced by embedding AgNPs. When embedded with 1.2% AgNPs, both the tensile strength and elongation-at-break reached the highest level. This work has the potential to expand the application of FK-based nanofibers in the biomaterial field.
Physicochemical Evaluation of Insulin Complexes with QPDMAEMA-b-PLMA-b-POEGMA Cationic Amphiphlic Triblock Terpolymer Micelles
Authors: Skandalis Athanasios , Murmiliuk Anastasiia , Štěpánek Miroslav , Pispas Stergios
Published: February 2020

Herein, poly[quaternized 2-(dimethylamino)ethyl methacrylate-b-lauryl methacrylate-b-(oligo ethylene glycol)methacrylate] (QPDMAEMA-b-PLMA-b-POEGMA) cationic amphiphilic triblock terpolymers were used as vehicles for the complexation/encapsulation of insulin (INS). The terpolymers self-assemble in spherical micelles with PLMA cores and mixed QPDMAEMA/POEGMA coronas in aqueous solutions. The cationic micelles were complexed via electrostatic interactions with INS, which contains anionic charges at pH 7. The solutions were colloidally stable in all INS ratios used. Light-scattering techniques were used for investigation of the complexation ability and the size and surface charge of the terpolymer/INS complexes. The results showed that the size of the complexes increases as INS ratio increases, while at the same time the surface charge remains positive, indicating the formation of clusters of micelles/INS complexes in the solution. Fluorescence spectroscopy measurements revealed that the conformation of the protein is not affected after the complexation with the terpolymer micellar aggregates. It was observed that as the solution ionic strength increases, the size of the QPDMAEMA-b-PLMA-b-POEGMA/INS complexes initially decreases and then remains practically constant at higher ionic strength, indicating further aggregation of the complexes. atomic force microscopy (AFM) measurements showed the existence of both clusters and isolated nanoparticulate terpolymer/protein complexes.
Numerical and Experimental Investigation of Oil Palm Shell Reinforced Rubber Composites
Authors: Anandan Subhashini , Lim Cuin Yang , Tan Boon Thong , Anggraini Vivi , Raghunandan Mavinakere Eshwaraiah
Published: February 2020

This paper presents a pioneering effort to ascertain the suitability of hyperelastic modelling in simulating the stress–strain response of oil palm shell reinforced rubber (ROPS) composites. ROPS composites with different oil palm shell contents (0%, 5%, 10% and 20% by volume) were cast in the laboratory for the experimental investigation. ROPS specimens with circular, square, hexagon, and octagon shapes (loading surface) were considered to evaluate the accuracy of finite element simulation considering the shape effect of composites. Strain-controlled (compressive) tests with ε ≈ 50% at 0.8 Hz frequency were conducted in the laboratory and the test data obtained was used as input to simulate material coefficients corresponding to the strain energy functions chosen. Five different strain energy functions were selected and utilized for the hyperelastic modelling in this study using finite element approach. The shape effect was then used to ascertain any variation in the simulation outcomes and to discuss the effect of shape on the behaviour of ROPS composites in comparison to existing literature. The numerical predictions using the Yeoh model (error ≤ 2.7% for circular shaped ROPS) were found to perform best in comparison with the experimental results, thus a more stable and suitable hyperelastic model to this end. The Marlow (error ≤ 4.6% for circular shaped ROPS) and Arruda Boyce (error ≤ 4.7% for circular shaped ROPS) models were amongst the next alternatives to perform better. Even with the other shapes considered in this study, Yeoh, followed by the Marlow function, were more appropriate models. The shape effect was then studied with particular emphasis on comparing and assessing them with that observed in the literature. To this end, adopting the Yeoh function in the finite element model is the ideal approach to estimate the stress–strain response of ROPS composites.
The Effect of the Addition of Dietary Fibers from Apple and Oat on the Rheological and Textural Properties of Waxy Potato Starch
Authors: Adamczyk Greta , Krystyjan Magdalena , Jaworska Grażyna
Published: February 2020

The aim of this paper was to investigate the influence of dietary fibers from oat (OF) and apple (AF) (concentration 0.2%) on the pasting properties, rheological (including thixotropic and anti-thixotropic) and textural properties of 3% and 4% (w/w) waxy potato starch pastes. The samples were characterized by their pasting characteristics, the hysteresis loop test, and textural properties measured during storage. It was found that the breakdown viscosity values of the blends, including oat fibers, were lower than those of the others (waxy potato starch (WPS), WPS-AF), which suggests that these samples would have higher resistance to retrogradation and therefore would form a more stable paste. The pattern of flow curves showed that the investigated waxy potato starch and starch-fiber pastes were non-Newtonian fluids, thinned by shear. Areas of the hysteresis loops indicated that pastes with fibers had anti-thixotropic or mixed thixotropic/anti-thixotropic character. The greatest areas of the anti-thixotropy hysteresis loops were characteristic for WPS, while its mixtures with AF and OF caused a decrease in the value of these areas. It can indicate that starch-fiber blends were more stable during shearing. Fiber-type and starch concentration strongly affected the textural parameters of the starch-fiber gels.
Anion Exchange Membranes Obtained from Poly(arylene ether sulfone) Block Copolymers Comprising Hydrophilic and Hydrophobic Segments
Authors: Kim Jun Ha , Vinothkannan Mohanraj , Kim Ae Rhan , Yoo Dong Jin
Published: February 2020

The anion exchange membrane may have different physical and chemical properties, electrochemical performance and mechanical stability depending upon the monomer structure, hydrophilicity and hydrophobic repeating unit, surface form and degree of substitution of functional groups. In current work, poly(arylene ether sulfone) (PAES) block copolymer was created and used as the main chain. After controlling the amount of NBS, the degree of bromination (DB) was changed in Br-PAES. Following that, quaternized PAES (Q-PAES) was synthesized through quaternization. Q-PAES showed a tendency of enhancing water content, expansion rate, ion exchange capacity (IEC) as the degree of substitution of functional groups increased. However, it was confirmed that tensile strength and dimensional properties of membrane reduced while swelling degree was increased. In addition, phase separation of membrane was identified by atomic force microscope (AFM) image, while ionic conductivity is greatly affected by phase separation. The Q-PAES membrane demonstrated a reasonable power output of around 64 mW/cm2 while employed as electrolyte in fuel cell operation.
Highly Chlorinated Polyvinyl Chloride as a Novel Precursor for Fibrous Carbon Material
Authors: Liu Jinchang , Shimanoe Hiroki , Ko Seunghyun , Lee Hansong , Jo Chaehyun , Lee Jaewoong , Hong Seong-Hwa , Lee Hyunchul , Jeon Young-Pyo , Nakabayashi Koji , Miyawaki Jin , Yoon Seong-Ho
Published: February 2020

Pure, highly chlorinated polyvinyl chloride (CPVC), with a 63 wt % of chlorine, showed a unique-thermal-pyrolytic-phenomenon that meant it could be converted to carbon material through solid-phase carbonisation rather than liquid-phase carbonisation. The CPVC began to decompose at 270 °C, with a rapid loss in mass due to dehydrochlorination and novel aromatisation and polycondensation up to 400 °C. In this study, we attempted to prepare carbon fibre (CF) without oxidative stabilisation, using the aforementioned CPVC as a novel precursor. Through the processes of solution spinning and solid-state carbonisation, the spun CPVC fibre was directly converted to CF, with a carbonisation yield of 26.2 wt %. The CPVC-derived CF exhibited a relatively smooth surface; however, it still demonstrated a low mechanical performance. This was because the spun fibre was not stretched during the heat treatment. Tensile strength, Young’s modulus and elongation values of 590 ± 84 MPa, 50 ± 8 GPa, and 1.2 ± 0.2%, respectively, were obtained from the CPVC spun fibre, with an average diameter of 19.4 μm, following carbonisation at 1600 °C for 5 min.
4-n-Butylresorcinol-Based Linear and Graft Polymethacrylates for Arbutin and Vitamins Delivery by Micellar Systems
Authors: Odrobińska Justyna , Mielańczyk Łukasz , Neugebauer Dorota
Published: February 2020

A novel initiator, bromoester modified 4-n-butylresorcinol (4nBREBr2), was prepared and utilized in controlled atom transfer radical polymerization (ATRP) to obtain three series of amphiphilic copolymers. The V-shaped copolymers of methyl methacrylate (MMA), 2-hydroxyethyl methacrylate (HEMA), and poly(ethylene glycol) methyl ether methacrylate (MPEGMA), abbreviated to P(HEMA–co–MMA), P(HEMA–co–MPEGMA), and P(MMA–co–MPEGMA), were synthesized. Moreover, P((HEMA–graft–PEG)–co–MMA) graft copolymers were prepared by combining the pre-polymerization modification of HEMA and a “click” reaction using a “grafting onto” approach. All copolymers could form micelles with encapsulated active substances (vitamin C (VitC), vitamin E (VitE), arbutin (ARB)), which are used in cosmetology. In vitro studies carried out in a PBS solution (pH 7.4) demonstrates that in most cases the maximum release of active substance was after 1 h. The polymeric systems presenting satisfactory encapsulation characteristics and release profiles are attractive micellar carriers of cosmetic substances, which show a positive effect on the skin condition.
Application Progress of Polyaniline, Polypyrrole and Polythiophene in Lithium-Sulfur Batteries
Authors: Hong Xiaodong , Liu Yue , Li Yang , Wang Xu , Fu Jiawei , Wang Xuelei
Published: February 2020

With the urgent requirement for high-performance rechargeable Li-S batteries, besides various carbon materials and metal compounds, lots of conducting polymers have been developed and used as components in Li-S batteries. In this review, the synthesis of polyaniline (PANI), polypyrrole (PPy) and polythiophene (PTh) is introduced briefly. Then, the application progress of the three conducting polymers is summarized according to the function in Li-S batteries, including coating layers, conductive hosts, sulfur-containing compounds, separator modifier/functional interlayer, binder and current collector. Finally, according to the current problems of conducting polymers, some practical strategies and potential research directions are put forward. We expect that this review will provide novel design ideas to develop conducting polymer-containing high-performance Li-S batteries.
Novel Bio-Based Epoxy Thermosets Based on Triglycidyl Phloroglucinol Prepared by Thiol-Epoxy Reaction
Authors: Guzmán Dailyn , Santiago David , Serra Àngels , Ferrando Francesc
Published: February 2020

The pure trifunctional glycidyl monomer from phloroglucinol (3EPO-Ph) was synthesized and used as feedstock in the preparation of novel bio-based thermosets by thiol-epoxy curing. The monomer was crosslinked with different commercially available thiols: tetrafunctional thiol (PETMP), trifunctional thiol (TTMP) and an aromatic dithiol (TBBT) as curing agents in the presence of a base. As catalyst, two different commercial catalysts: LC-80 and 4-(N,N-dimethylamino) pyridine (DMAP) and a synthetic catalyst, imidazolium tetraphenylborate (base generator, BG) were employed. The curing of the reactive mixtures was studied by using DSC and the obtained materials by means of differential scanning calorimetry (DSC), thermogravimetric analysis (TGA) and dynamic mechanical thermal analysis (DMTA). The results revealed that only the formulations catalyzed by BG showed a latent character. Already prepared thermosetting materials showed excellent thermal, thermomechanical and mechanical properties, with a high transparency. In addition to that, when compared with the diglycidyl ether of bisphenol A (DGEBA)/PETMP material, the thermosets prepared from the triglycidyl derivative of phloroglucinol have better final characteristics and therefore this derivative can be considered as a partial or total renewable substitute of DGEBA in technological applications.
Novel Concept of Cogeneration-Integrated Heat Pump-Assisted Fractionation of Alkylation Reactor Effluent for Increased Power Production and Overall CO2 Emissions Decrease
Authors: Variny Miroslav , Furda Patrik , Švistun Ladislav , Rimár Miroslav , Kizek Ján , Kováč Norbert , Illés Peter , Janošovský Ján , Váhovský Jakub , Mierka Otto
Published: February 2020

Alkylate produced by catalyzed reaction of isobutane and olefin-rich streams is a desired component for gasoline blending. Fractionation of the alkylation reactor effluent is energy demanding due to the presence of close boiling point components and solutions cutting its energy intensity; expenses associated with this process are investigated intensely nowadays. This paper presents a novel conceptual design and techno-economic analysis of alkylation reaction effluent fractionation revamp to reach a cut in energy costs of the fractionation process without the need to revamp the rectification columns themselves, providing thus an alternative approach to a more sustainable alkylation process. Two cases are considered—A. additional steam turbine installation or B. combustion engine-driven heat pump-assisted rectification. Mathematical modeling of the considered system and its revamp is applied using the “frozen technology” approach. Real system operation features and seasonal variations are included considering the refinery’s combined heat and power (CHP) unit operation and CO2 emissions balance both internal and external to the refinery. Case A yields an expectable yearly benefit (saved energy minus additionally consumed energy minus CO2 emissions increase; expressed in financial terms) of €110–140 thousand, net present value (NPV) of −€18 to €272 thousand and produces 3.3 GWh/year of electric energy. Case B delivers a benefit of €900–1200 thousand, NPV of −€293 to €2823 thousand while producing 33 GWh/year of electricity. Both cases exhibit analogous simple payback periods (8–10 years). Marginal electric efficiency of Case B (78.3%) documents the energy integration level in this case, exploiting the system and CHP unit operation synergies. CHP unit summer operation mode and steam network restrictions significantly affect the seasonal benefit of Case B. CO2 emissions increase in both cases, Case A and Case B, considering the refinery level. However, including external CO2 emissions leads to emissions decrease in both cases of up to 26 kton/year (Case B.) The presented results document the viability of the proposed concepts comparable to the traditional (reference) solution of a high performance (COP = 8) heat pump while their performance sensitivity stresses the need for complex techno-economic assessment.
Wheat Growth Monitoring and Yield Estimation based on Multi-Rotor Unmanned Aerial Vehicle
Authors: Fu Zhaopeng , Jiang Jie , Gao Yang , Krienke Brian , Wang Meng , Zhong Kaitai , Cao Qiang , Tian Yongchao , Zhu Yan , Cao Weixing , Liu Xiaojun
Published: February 2020

Leaf area index (LAI) and leaf dry matter (LDM) are important indices of crop growth. Real-time, nondestructive monitoring of crop growth is instructive for the diagnosis of crop growth and prediction of grain yield. Unmanned aerial vehicle (UAV)-based remote sensing is widely used in precision agriculture due to its unique advantages in flexibility and resolution. This study was carried out on wheat trials treated with different nitrogen levels and seeding densities in three regions of Jiangsu Province in 2018–2019. Canopy spectral images were collected by the UAV equipped with a multi-spectral camera during key wheat growth stages. To verify the results of the UAV images, the LAI, LDM, and yield data were obtained by destructive sampling. We extracted the wheat canopy reflectance and selected the best vegetation index for monitoring growth and predicting yield. Simple linear regression (LR), multiple linear regression (MLR), stepwise multiple linear regression (SMLR), partial least squares regression (PLSR), artificial neural network (ANN), and random forest (RF) modeling methods were used to construct a model for wheat yield estimation. The results show that the multi-spectral camera mounted on the multi-rotor UAV has a broad application prospect in crop growth index monitoring and yield estimation. The vegetation index combined with the red edge band and the near-infrared band was significantly correlated with LAI and LDM. Machine learning methods (i.e., PLSR, ANN, and RF) performed better for predicting wheat yield. The RF model constructed by normalized difference vegetation index (NDVI) at the jointing stage, heading stage, flowering stage, and filling stage was the optimal wheat yield estimation model in this study, with an R2 of 0.78 and relative root mean square error (RRMSE) of 0.1030. The results provide a theoretical basis for monitoring crop growth with a multi-rotor UAV platform and explore a technical method for improving the precision of yield estimation.
Multi-Scale Evaluation of Drone-Based Multispectral Surface Reflectance and Vegetation Indices in Operational Conditions
Authors: Fawcett Dominic , Panigada Cinzia , Tagliabue Giulia , Boschetti Mirco , Celesti Marco , Evdokimov Anton , Biriukova Khelvi , Colombo Roberto , Miglietta Franco , Rascher Uwe , Anderson Karen
Published: February 2020

Compact multi-spectral sensors that can be mounted on lightweight drones are now widely available and applied within the geo- and environmental sciences. However; the spatial consistency and radiometric quality of data from such sensors is relatively poorly explored beyond the lab; in operational settings and against other sensors. This study explores the extent to which accurate hemispherical-conical reflectance factors (HCRF) and vegetation indices (specifically: normalised difference vegetation index (NDVI) and chlorophyll red-edge index (CHL)) can be derived from a low-cost multispectral drone-mounted sensor (Parrot Sequoia). The drone datasets were assessed using reference panels and a high quality 1 m resolution reference dataset collected near-simultaneously by an airborne imaging spectrometer (HyPlant). Relative errors relating to the radiometric calibration to HCRF values were in the 4 to 15% range whereas deviations assessed for a maize field case study were larger (5 to 28%). Drone-derived vegetation indices showed relatively good agreement for NDVI with both HyPlant and Sentinel 2 products (R2 = 0.91). The HCRF; NDVI and CHL products from the Sequoia showed bias for high and low reflective surfaces. The spatial consistency of the products was high with minimal view angle effects in visible bands. In summary; compact multi-spectral sensors such as the Parrot Sequoia show good potential for use in index-based vegetation monitoring studies across scales but care must be taken when assuming derived HCRF to represent the true optical properties of the imaged surface.
Spectral Imagery Tensor Decomposition for Semantic Segmentation of Remote Sensing Data through Fully Convolutional Networks
Authors: López Josué , Torres Deni , Santos Stewart , Atzberger Clement
Published: February 2020

This work aims at addressing two issues simultaneously: data compression at input space and semantic segmentation. Semantic segmentation of remotely sensed multi- or hyperspectral images through deep learning (DL) artificial neural networks (ANN) delivers as output the corresponding matrix of pixels classified elementwise, achieving competitive performance metrics. With technological progress, current remote sensing (RS) sensors have more spectral bands and higher spatial resolution than before, which means a greater number of pixels in the same area. Nevertheless, the more spectral bands and the greater number of pixels, the higher the computational complexity and the longer the processing times. Therefore, without dimensionality reduction, the classification task is challenging, particularly if large areas have to be processed. To solve this problem, our approach maps an RS-image or third-order tensor into a core tensor, representative of our input image, with the same spatial domain but with a lower number of new tensor bands using a Tucker decomposition (TKD). Then, a new input space with reduced dimensionality is built. To find the core tensor, the higher-order orthogonal iteration (HOOI) algorithm is used. A fully convolutional network (FCN) is employed afterwards to classify at the pixel domain, each core tensor. The whole framework, called here HOOI-FCN, achieves high performance metrics competitive with some RS-multispectral images (MSI) semantic segmentation state-of-the-art methods, while significantly reducing computational complexity, and thereby, processing time. We used a Sentinel-2 image data set from Central Europe as a case study, for which our framework outperformed other methods (included the FCN itself) with average pixel accuracy (PA) of 90% (computational time ∼90s) and nine spectral bands, achieving a higher average PA of 91.97% (computational time ∼36.5s), and average PA of 91.56% (computational time ∼9.5s) for seven and five new tensor bands, respectively.
Spatial Habitat Shifts of Oceanic Cephalopod (Ommastrephes bartramii) in Oscillating Climate
Authors: Alabia Irene D. , Saitoh Sei-Ichi , Igarashi Hiromichi , Ishikawa Yoichi , Imamura Yutaka
Published: February 2020

Short- and long-term climate oscillations impact seascapes, and hence, marine ecosystem structure and dynamics. Here, we explored the spatio-temporal patterns of potential squid habitat in the western and central North Pacific across inter-decadal climate transitions, coincident with periods of persistent warming and cooling. Potential habitat distributions of Ommastrephes bartramii were derived from the outputs of multi-ensemble species distribution models, developed using the most influential environmental factors to squid distribution and occurrence data. Our analyses captured the underlying temporal trends in potential squid habitat in response to environmental changes transpiring at each climatic transition, regulated by phase shifts in Pacific decadal oscillation (PDO) from 1999–2013. The spatial differences in environmental conditions were apparent across transitions and presumably modulate the local changes in suitable squid habitat over time. Specifically, during a cold to warm PDO shift, decreases in the summer potential habitat (mean rate ± standard deviation: −0.04 ± 0.02 habitat suitability index (HSI)/yr) were observed along the southern edge of the subarctic frontal zone (162°E–172°W). Coincidentally, this area also exhibits a warming trend (mean temporal trend: 0.06 ± 0.21 °C/yr), accompanied with the prevalence of cold-core mesoscale eddies, west of the dateline (mean temporal trend in sea surface height: −0.19 ± 1.05 cm/yr). These conditions potentially generate less favorable foraging habitat for squid. However, a warm-to-cold PDO transition underpins a northward shift of suitable habitat and an eastward shift of regions exhibiting the highest rate of potential squid habitat loss (170–160°W; mean temporal trend: −0.05 ± 0.03 HSI/yr). Nonetheless, the emergence of the areas with increasingly suitable habitat regardless of climate transitions suggests the ecological importance of these regions as potential squid habitat hotspots and climatic refugia.
Wavelet-Based Contourlet Transform and Kurtosis Map for Infrared Small Target Detection in Complex Background
Authors: Wang He , Xin Yunhong
Published: February 2020

Wavelet-based Contourlet transform (WBCT) is a typical Multi-scale Geometric Analysis (MGA) method, it is a powerful technique to suppress background and enhance the edge of target. However, in the small target detection with the complex background, WBCT always lead to a high false alarm rate. In this paper, we present an efficient and robust method which utilizes WBCT method in conjunction with kurtosis model for the infrared small target detection in complex background. We mainly made two contributions. The first, WBCT method is introduced as a preprocessing step, and meanwhile we present an adaptive threshold selection strategy for the selection of WBCT coefficients of different scales and different directions, as a result, the most background clutters are suppressed in this stage. The second, a kurtosis saliency map is obtained by using a local kurtosis operator. In the kurtosis saliency map, a slide window and its corresponding mean and variance is defined to locate the area where target exists, and subsequently an adaptive threshold segment mechanism is utilized to pick out the small target from the selected area. Extensive experimental results demonstrate that, compared with the contrast methods, the proposed method can achieve satisfactory performance, and it is superior in detection rate, false alarm rate and ROC curve especially in complex background.
Reusable Mesh Signature Scheme for Protecting Identity Privacy of IoT Devices
Authors: Gu Ke , Zhang WenBin , Lim Se-Jung , Sharma Pradip Kumar , Al-Makhadmeh Zafer , Tolba Amr
Published: February 2020

The development of the Internet of Things (IoT) plays a very important role for processing data at the edge of a network. Therefore, it is very important to protect the privacy of IoT devices when these devices process and transfer data. A mesh signature (MS) is a useful cryptographic tool, which makes a signer sign any message anonymously. As a result, the signer can hide his specific identity information to the mesh signature, namely his identifying information (such as personal public key) may be hidden to a list of tuples that consist of public key and message. Therefore, we propose an improved mesh signature scheme for IoT devices in this paper. The IoT devices seen as the signers may sign their publishing data through our proposed mesh signature scheme, and their specific identities can be hidden to a list of possible signers. Additionally, mesh signature consists of some atomic signatures, where the atomic signatures can be reusable. Therefore, for a large amount of data published by the IoT devices, the atomic signatures on the same data can be reusable so as to decrease the number of signatures generated by the IoT devices in our proposed scheme. Compared with the original mesh signature scheme, the proposed scheme has less computational costs on generating final mesh signature and signature verification. Since atomic signatures are reusable, the proposed scheme has more advantages on generating final mesh signature by reconstructing atomic signatures. Furthermore, according to our experiment, when the proposed scheme generates a mesh signature on 10 MB message, the memory consumption is only about 200 KB. Therefore, it is feasible that the proposed scheme is used to protect the identity privacy of IoT devices.
Precise Volumetric Measurements of Any Shaped Objects with a Novel Acoustic Volumeter
Authors: Sydoruk Viktor A. , Kochs Johannes , van Dusschoten Dagmar , Huber Gregor , Jahnke Siegfried
Published: February 2020

We introduce a novel technique to measure volumes of any shaped objects based on acoustic components. The focus is on small objects with rough surfaces, such as plant seeds. The method allows measurement of object volumes more than 1000 times smaller than the volume of the sensor chamber with both high precision and high accuracy. The method is fast, noninvasive, and easy to produce and use. The measurement principle is supported by theory, describing the behavior of the measured data for objects of known volumes in a range of 1 to 800 µL. In addition to single-frequency, we present frequency-dependent measurements that provide supplementary information about pores on the surface of a measured object, such as the total volume of pores and, in the case of cylindrical pores, their average radius-to-length ratio. We demonstrate the usefulness of the method for seed phenotyping by measuring the volume of irregularly shaped seeds and showing the ability to “look” under the husk and inside pores, which allows us to assess the true density of seeds.
Earthquake Detection in a Static and Dynamic Environment Using Supervised Machine Learning and a Novel Feature Extraction Method
Authors: Khan Irshad , Choi Seonhwa , Kwon Young-Woo
Published: February 2020

Detecting earthquakes using smartphones or IoT devices in real-time is an arduous and challenging task, not only because it is constrained with the hard real-time issue but also due to the similarity of earthquake signals and the non-earthquake signals (i.e., noise or other activities). Moreover, the variety of human activities also makes it more difficult when a smartphone is used as an earthquake detecting sensor. To that end, in this article, we leverage a machine learning technique with earthquake features rather than traditional seismic methods. First, we split the detection task into two categories including static environment and dynamic environment. Then, we experimentally evaluate different features and propose the most appropriate machine learning model and features for the static environment to tackle the issue of noisy components and detect earthquakes in real-time with less false alarm rates. The experimental result of the proposed model shows promising results not only on the given dataset but also on the unseen data pointing to the generalization characteristics of the model. Finally, we demonstrate that the proposed model can be also used in the dynamic environment if it is trained with different dataset.
Detection Principles of Temperature Compensated Oscillators with Reactance Influence on Piezoelectric Resonator
Authors: Matko Vojko , Milanovič Miro
Published: February 2020

This review presents various ways of detection of different physical quantities based on the frequency change of oscillators using piezoelectric crystals. These are influenced by the reactance changes modifying their electrical characteristics. Reactance in series, in parallel, or a combination of reactances can impact the electrical crystal substitute model by influencing its resonant oscillation frequency. In this way, various physical quantities near resonance can be detected with great sensitivity through a small change of capacitance or inductance. A piezoelectric crystal impedance circle and the mode of frequency changing around the resonant frequency change are shown. This review also presents the influence of reactance on the piezoelectric crystal, the way in which the capacitance lost among the crystal’s electrodes is compensated, and how the mode of oscillators’ output frequency is converted to lower frequency range (1–100 kHz). Finally, the review also explains the temperature–frequency compensation of the crystals’ characteristics in oscillators that use temperature–frequency pair of crystals and the procedure of the compensation of crystals own temperature characteristics based on the method switching between the active and reference reactance. For the latter, the experimental results of the oscillator’s output frequency stability (fout = ±0.002 ppm) at dynamical change of environment temperature (0–50 °C) are shown.
Attention Based CNN-ConvLSTM for Pedestrian Attribute Recognition
Authors: Li Yang , Xu Huahu , Bian Minjie , Xiao Junsheng
Published: February 2020

As a result of its important role in video surveillance, pedestrian attribute recognition has become an attractive facet of computer vision research. Because of the changes in viewpoints, illumination, resolution and occlusion, the task is very challenging. In order to resolve the issue of unsatisfactory performance of existing pedestrian attribute recognition methods resulting from ignoring the correlation between pedestrian attributes and spatial information, in this paper, the task is regarded as a spatiotemporal, sequential, multi-label image classification problem. An attention-based neural network consisting of convolutional neural networks (CNN), channel attention (CAtt) and convolutional long short-term memory (ConvLSTM) is proposed (CNN-CAtt-ConvLSTM). Firstly, the salient and correlated visual features of pedestrian attributes are extracted by pre-trained CNN and CAtt. Then, ConvLSTM is used to further extract spatial information and correlations from pedestrian attributes. Finally, pedestrian attributes are predicted with optimized sequences based on attribute image area size and importance. Extensive experiments are carried out on two common pedestrian attribute datasets, PEdesTrian Attribute (PETA) dataset and Richly Annotated Pedestrian (RAP) dataset, and higher performance than other state-of-the-art (SOTA) methods is achieved, which proves the superiority and validity of our method.
Evaluating the Vulnerability of Several Geodetic GNSS Receivers under Chirp Signal L1/E1 Jamming
Authors: Bažec Matej , Dimc Franc , Pavlovčič-Prešeren Polona
Published: February 2020

Understanding the factors that might intentionally influence the reception of global navigation satellite system (GNSS) signals can be a challenging topic today. The focus of this research is to evaluate the vulnerability of geodetic GNSS receivers under the use of a low-cost L1/E1 frequency jammer. A suitable area for testing was established in Slovenia. Nine receivers from different manufacturers were under consideration in this study. While positioning, intentional 3-minute jammings were performed by a jammer that was located statically at different distances from receivers. Furthermore, kinematic disturbances were performed using a jammer placed in a vehicle that passed the testing area at various speeds. An analysis of different scenarios indicated that despite the use of an L1/E1 jammer, the GLONASS (Russian: Globalnaya Navigatsionnaya Sputnikovaya Sistema) and Galileo signals were also affected, either due to the increased carrier-to-noise-ratio (C/N0) or, in the worst cases, by a loss-of-signal. A jammer could substantially affect the position, either with a lack of any practical solution or even with a wrong position. Maximal errors in the carrier-phase positions, which should be considered a concern for geodesy, differed by a few metres from the exact solution. The factor that completely disabled the signal reception was the proximity of a jammer, regardless of its static or kinematic mode.
A Novel Unitary ESPRIT Algorithm for Monostatic FDA-MIMO Radar
Authors: Liu Feilong , Wang Xianpeng , Huang Mengxing , Wan Liangtian , Wang Huafei , Zhang Bin
Published: February 2020

A novel unitary estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm, for the joint direction of arrival (DOA) and range estimation in a monostatic multiple-input multiple-output (MIMO) radar with a frequency diverse array (FDA), is proposed. Firstly, by utilizing the property of Centro-Hermitian of the received data, the extended real-valued data is constructed to improve estimation accuracy and reduce computational complexity via unitary transformation. Then, to avoid the coupling between the angle and range in the transmitting array steering vector, the DOA is estimated by using the rotation invariance of the receiving subarrays. Thereafter, an automatic pairing method is applied to estimate the range of the target. Since phase ambiguity is caused by the phase periodicity of the transmitting array steering vector, a removal method of phase ambiguity is proposed. Finally, the expression of Cramér–Rao Bound (CRB) is derived and the computational complexity of the proposed algorithm is compared with the ESPRIT algorithm. The effectiveness of the proposed algorithm is verified by simulation results.
Enhanced Passive GNSS-Based Radar Imaging Based on Coherent Integrated Multi-Satellite Signals
Authors: Zheng Yu , Zhang Zhuxian , Feng Lu , Zhu Peidong , Zhou Feng
Published: February 2020

Weak reflected signal is one of the main problems in a recent developing remote sensing tool—passive GNSS-based radar (GNSS radar). To address this issue, an enhanced GNSS radar imaging scheme on the basis of coherently integrating multiple satellites is proposed. In the proposed scheme, to avoid direct signal interference at surveillance antenna, the satellites that used as transmission of opportunity are in backscattering geometry model. To coherently accumulate echo signal magnitudes of the scene center in the targeted sensing region illuminated by the selected satellites, after performing the paralleled range compressions, a coordinates alignment operator is performed to the respective range domains, in which, pseudorandom noise (PRN) code phases are aligned. Thereafter, the coordinates aligned range compressed signals of the selected satellites are coherently integrated along azimuth domain so that imaging gain is improved and azimuth processing can be accomplished in only one state operation. The theoretical analysis and field proof-of-concept experimental results indicate that compared to both conventional bistatic imaging scheme and the state-of-the-art multi-image fusion scheme, the proposed scheme can provide a higher imaging gain; compared to the state-of-the-art multi-image fusion scheme, the proposed scheme has a less computational complexity and faster algorithm speed.