bluuebunny/crossref_metadata_2025 huggingface dataset:
Structural Polymorphism of Sorafenib Tosylate as a Key Factor in Its Solubility Differentiation
Authors: Wiergowska Gabriela , Stasiłowicz Anna , Miklaszewski Andrzej , Lewandowska Kornelia , Cielecka-Piontek Judyta
Published: March 2021

The presence of active pharmaceutical ingredients (APIs) in the forms of different polymorphic states can induce differences in their physicochemical properties. In the case of poorly soluble APIs, like the oncological drug sorafenib tosylate, small variations in solubility may result in large bioavailability differences. The control of its therapeutic dose is crucial from the effective pharmacotherapy point of view and the reduction of side effects. Therefore, this study aimed to assess the influence of sorafenib tosylate polymorphic forms on its solubility and, consequently, permeability, based on passive diffusion through membranes simulating the gastrointestinal tract (GIT) conditions. In the first part of the work, two crystalline forms of sorafenib tosylate were identified using the X-ray powder diffraction, FT-IR, and Raman spectroscopy. Subsequently, solubility studies were carried out. Both forms of sorafenib tosylate were insoluble in 0.1 N hydrochloric acid (HCl), in acetate buffer (pH 4.5), and in phosphate buffer (pH 6.8). Solubility (mg/mL) of form I and III of sorafenib tosylate in 0.1 N HCl + 1.0% SDS was 0.314 ± 0.006 and 1.103 ± 0.014, respectively, in acetate buffer pH 4.5 + 1.0% SDS it was 2.404 ± 0.012 and 2.355 ± 0.009, respectively, and in phosphate buffer pH 6.8 + 1.0% SDS it was 0.051 ± 0.005 and 1.805 ± 0.023, respectively. The permeability study was assessed using the parallel artificial membrane permeability assay (PAMPA) model. The apparent permeability coefficient (Papp—cm s−1) of form I and III in pH 1.2 was 3.01 × 10−5 ± 4.14 × 10−7 and 3.15 × 10−5 ± 1.89 × 10−6, respectively, while in pH 6.8 it was 2.72 × 10−5 ± 1.56 × 10−6 and 2.81 × 10−5 ± 9.0 × 10−7, respectively. Changes in sorafenib tosylate concentrations were determined by chromatography using the high-performance liquid chromatography (HPLC)–DAD technique. As a result of the research on the structural polymorphism of sorafenib tosylate, its full spectral characteristics and the possibility of using FT-IR and Raman spectroscopy for the study of polymorphic varieties were determined for the first time, and the HPLC method was developed, which is appropriate for the assessment of sorafenib solubility in various media. The consequences of various physicochemical properties resulting from differences in the solubility of sorafenib tosylate polymorphs are important for pre-formulation and formulation studies conducted with its participation and for the safety of oncological sorafenib therapy.
Nasal Powder Formulations: In-Vitro Characterisation of the Impact of Powders on Nasal Residence Time and Sensory Effects
Authors: Trenkel Marie , Scherließ Regina
Published: March 2021

Nasal drug delivery is still primarily associated with locally-effective drugs, but next-generation products utilising the benefits of nasal administration—such as easy access to a relatively permeable mucosa, the presence of immunocompetent cells, and a direct route to the brain—are under investigation. Nasal powders offer the potential to improve the drugs’ effects by providing higher resistance against the mucociliary clearance, and thus prolonging the contact time of the drug with its target site. However, suitable and easy-to-use in-vitro setups tailored to the characterisation of this effect are missing. In this study, a selection of excipients for powder formulations were used to evaluate the applicability of different methods which investigate the influence on the contact time. The combination of the assessment of rheological properties, dynamic vapour sorption, and adhesiveness on agar–mucin plates was found to be a valuable predictive tool. For the additional assessment of the sensations associated with the close contact of powders and the mucosa, a slug mucosal irritation assay was conducted and adapted to powders. These methods are regarded as being especially useful for comparative screenings in early formulation development.
Excipients in the Paediatric Population: A Review
Authors: Rouaz Khadija , Chiclana-Rodríguez Blanca , Nardi-Ricart Anna , Suñé-Pou Marc , Mercadé-Frutos Dèbora , Suñé-Negre Josep María , Pérez-Lozano Pilar , García-Montoya Encarna
Published: March 2021

This theoretical study seeks to critically review the use of excipients in the paediatric population. This study is based on the rules and recommendations of European and American drug regulatory agencies. On the one hand, this review describes the most frequent excipients used in paediatric medicine formulations, identifying the compounds that scientific literature has marked as potentially harmful regarding the side effects generated after exposure. On the other hand, this review also highlights the importance of carrying out safety -checks on the excipients, which, in most cases, are linked to toxicity studies. An excipient in the compilation of paediatric population databases is expected to target safety and toxicity, as in the STEP database. Finally, a promising pharmaceutical form for child population, ODT (Orally Disintegrating Tablets), will be studied.
Co-Amorphous Drug Formulations in Numbers: Recent Advances in Co-Amorphous Drug Formulations with Focus on Co-Formability, Molar Ratio, Preparation Methods, Physical Stability, In Vitro and In Vivo Performance, and New Formulation Strategies
Authors: Liu Jingwen , Grohganz Holger , Löbmann Korbinian , Rades Thomas , Hempel Nele-Johanna
Published: March 2021

Co-amorphous drug delivery systems (CAMS) are characterized by the combination of two or more (initially crystalline) low molecular weight components that form a homogeneous single-phase amorphous system. Over the past decades, CAMS have been widely investigated as a promising approach to address the challenge of low water solubility of many active pharmaceutical ingredients. Most of the studies on CAMS were performed on a case-by-case basis, and only a few systematic studies are available. A quantitative analysis of the literature on CAMS under certain aspects highlights not only which aspects have been of great interest, but also which future developments are necessary to expand this research field. This review provides a comprehensive updated overview on the current published work on CAMS using a quantitative approach, focusing on three critical quality attributes of CAMS, i.e., co-formability, physical stability, and dissolution performance. Specifically, co-formability, molar ratio of drug and co-former, preparation methods, physical stability, and in vitro and in vivo performance were covered. For each aspect, a quantitative assessment on the current status was performed, allowing both recent advances and remaining research gaps to be identified. Furthermore, novel research aspects such as the design of ternary CAMS are discussed.
Aerosolized In Vivo 3D Localization of Nose-to-Brain Nanocarrier Delivery Using Multimodality Neuroimaging in a Rat Model—Protocol Development
Authors: Veronesi Michael C. , Graner Brian D. , Cheng Shih-Hsun , Zamora Marta , Zarrinmayeh Hamideh , Chen Chin-Tu , Das Sudip K. , Vannier Michael W.
Published: March 2021

The fate of intranasal aerosolized radiolabeled polymeric micellar nanoparticles (LPNPs) was tracked with positron emission tomography/computer tomography (PET/CT) imaging in a rat model to measure nose-to-brain delivery. A quantitative temporal and spatial testing protocol for new radio-nanotheranostic agents was sought in vivo. LPNPs labeled with a zirconium 89 (89Zr) PET tracer were administered via intranasal or intravenous delivery, followed by serial PET/CT imaging. After 2 h of continuous imaging, the animals were sacrificed, and the brain substructures (olfactory bulb, forebrain, and brainstem) were isolated. The activity in each brain region was measured for comparison with the corresponding PET/CT region of interest via activity measurements. Serial imaging of the LPNPs (100 nm PLA–PEG–DSPE+89Zr) delivered intranasally via nasal tubing demonstrated increased activity in the brain after 1 and 2 h following intranasal drug delivery (INDD) compared to intravenous administration, which correlated with ex vivo gamma counting and autoradiography. Although assessment of delivery from nose to brain is a promising approach, the technology has several limitations that require further development. An experimental protocol for aerosolized intranasal delivery is presented herein, which may provide a platform for better targeting the olfactory epithelium.
Effect of Seasonal Decrease in Temperature on the Content and Composition of Guayulins in Stems of Guayule (Parthenium argentatum, Gray)
Authors: Rozalén Juana , García-Martínez M. Mercedes , Carrión Maria Engracia , Zalacain Amaya , López-Córcoles Horacio , Carmona Manuel
Published: March 2021

The guayulins are a family of sesquiterpene compounds that consist of an isoprenoid nucleus substituted either by trans-cinnamic or p-anisic acid, and are present only in the resinous fraction of the rubber plant guayule (Parthenium argentatum, Gray). While the natural role of the guayulins remains enigmatic, they may serve as a defense function against other plants or herbivores by virtue of the accumulation of cinnamic acid. Prior research has suggested seasonal variation in guayulin content, which has been shown to decrease as winter arrives in two different varieties. In the present study, the effect of guayulins has been evaluated in 13 different accessions cultivated under the same conditions during autumn. A general reduction in guayulin content was found in the stems from all varieties between the September and November harvest, which was accompanied by an increase in the resin content. With respect to individual guayulins, while guayulin A was the most prominent member during most of the year, guayulin C had more prominence when temperature started to decrease. In this seasonal period, the production of each member of the guayulin family in the leaves was very balanced.
Chemical Screening of Metabolites Profile from Romanian Tuber spp.
Authors: Segneanu Adina-Elena , Cepan Melinda , Bobica Adrian , Stanusoiu Ionut , Dragomir Ioan Cosmin , Parau Andrei , Grozescu Ioan
Published: March 2021

Truffles are the rarest species and appreciated species of edible fungi and are well-known for their distinctive aroma and high nutrient content. However, their chemical composition largely depends on the particularities of their grown environment. Recently, various studies investigate the phytoconstituents content of different species of truffles. However, this research is still very limited for Romanian truffles. This study reports the first complete metabolites profiles identification based on gas chromatography-mass spectrometry (GC-MS) and electrospray ionization quadrupole time-of-flight mass spectrometry (ESI-QTOF-MS) of two different types of Romania truffles: Tuber magnatum pico and Tuber brumale. In mass spectra (MS) in positive mode, over 100 metabolites were identified from 14 secondary metabolites categories: amino acids, terpenes, alkaloids, flavonoids, organic acids, fatty acids, phenolic acids, sulfur compounds, sterols, hydrocarbons, etc. Additionally, the biological activity of these secondary metabolite classes was discussed.
Wheat Developmental Traits as Affected by the Interaction between Eps-7D and Temperature under Contrasting Photoperiods with Insensitive Ppd-D1 Background
Authors: Basavaraddi Priyanka A. , Savin Roxana , Bencivenga Stefano , Griffiths Simon , Slafer Gustavo A.
Published: March 2021

Earliness per se (Eps) genes are important to fine tune adaptation, and studying their probable pleiotropic effect on wheat yield traits is worthwhile. In addition, it has been shown that some Eps genes interact with temperature and therefore determining the likely Eps × temperature interaction is needed for each newly identified Eps gene. We studied two NILs differing in the newly identified Eps-7D (carrying insensitive Ppd-D1 in the background) under three temperature regimes (9, 15 and 18 °C) and two photoperiods (12 and 24 h). Eps-7D affected time to anthesis as expected and the Eps-7D-late allele extended both the period before and after terminal spikelet. The interaction effect of Eps-7D × temperature was significant but not cross-over: the magnitude and level of significance of the difference between NILs with the late or early allele was affected by the growing temperature (i.e., difference was least at 18 °C and largest at 9 °C), and the differences caused due to temperature sensitivity were influenced by photoperiod. The rate of leaf initiation was faster in NIL with Eps-7D-early than with the late allele which compensated for the shorter duration of leaf initiation resulting in similar final leaf number between two NILs. Eps-7D-late consistently increased spike fertility through improving floret primordia survival as a consequence of extending the late reproductive phase.
Vegetable Oil-Based Thiol-Ene/Thiol-Epoxy Resins for Laser Direct Writing 3D Micro-/Nano-Lithography
Authors: Grauzeliene Sigita , Navaruckiene Aukse , Skliutas Edvinas , Malinauskas Mangirdas , Serra Angels , Ostrauskaite Jolita
Published: March 2021

The use of renewable sources for optical 3D printing instead of petroleum-based materials is increasingly growing. Combinations of photo- and thermal polymerization in dual curing processes can enhance the thermal and mechanical properties of the synthesized thermosets. Consequently, thiol-ene/thiol-epoxy polymers were obtained by combining UV and thermal curing of acrylated epoxidized soybean oil and epoxidized linseed oil with thiols, benzene-1,3-dithiol and pentaerythritol tetra(3-mercaptopropionate). Thiol-epoxy reaction was studied by calorimetry. The changes of rheological properties were examined during UV, thermal and dual curing to select the most suitable formulations for laser direct writing (LDW). The obtained polymers were characterized by dynamic-mechanical thermal analysis, thermogravimetry, and mechanical testing. The selected dual curable mixture was tested in LDW 3D lithography for validating its potential in optical micro- and nano-additive manufacturing. The obtained results demonstrated the suitability of epoxidized linseed oil as a biobased alternative to bisphenol A diglycidyl ether in thiol-epoxy thermal curing reactions. Dual cured thermosets showed higher rigidity, tensile strength, and Young’s modulus values compared with UV-cured thiol-ene polymers and the highest thermal stability from all prepared polymers. LDW results proved their suitability for high resolution 3D printing—individual features reaching an unprecedented 100 nm for plant-based materials. Finally, the biobased resin was tested for thermal post-treatment and 50% feature downscaling was achieved.
Incorporation of In Situ Synthesized Nano-Copper Modified Phenol-Formaldehyde Resin to Improve the Mechanical Properties of Chinese Fir: A Preliminary Study
Authors: Li Fan , Ye Cuiyin , Huang Yanhui , Liu Xianmiao , Fei Benhua
Published: March 2021

Phenol-formaldehyde (PF) resin, modified using nano-copper with varying contents (0 wt%, 1 wt%, 3 wt%), was manufactured to improve the mechanical properties of Chinese fir. The morphology, chemical, micromechanical and micromechanical properties of the samples were determined by transmission electron microscopy (TEM), atomic force microscopy (AFM), environmental scanning electron microscopy (ESEM), Fourier transform infrared spectroscopy (FTIR), nanoindentation (NI) and traditional mechanical testing. The TEM and AFM results indicated that the in situ synthesized nano-copper particles were well-dispersed, and spherical, with a diameter of about 70 nm in PF resin. From the FTIR chemical changes detected by FTIR inferred that the nano-copper modified PF resin penetrated into the Chinese fir cell walls and interacted with the acetyl groups of hemicellulose by forming a crosslinked structure. Accordingly, the micro-mechanical properties of the Chinese fir cell walls were enhanced after treatment with nano-copper modified PF resin. The filling of the PF-1-Cu resin (1 wt% nano-copper) in the wood resulted in 13.7% and 22.2% increases in the elastic modulus (MOE) and hardness, respectively, of the cell walls. Besides, the impact toughness and compressive strength of the Chinese fir impregnated with PF-1-Cu resin were 21.8% and 8.2% higher than that of the PF-0-Cu resin. Therefore, in situ synthesized nano-copper-modified PF resin is a powerful treatment method for Chinese fir due to improved diffusive properties and reinforcement of the mechanical properties.
Preparation, Thermal, and Thermo-Mechanical Characterization of Polymeric Blends Based on Di(meth)acrylate Monomers
Authors: Wnuczek Krystyna , Puszka Andrzej , Klapiszewski Łukasz , Podkościelna Beata
Published: March 2021

This study presents the preparation and the thermo-mechanical characteristics of polymeric blends based on di(meth)acrylates monomers. Bisphenol A glycerolate diacrylate (BPA.GDA) or ethylene glycol dimethacrylate (EGDMA) were used as crosslinking monomers. Methyl methacrylate (MMA) was used as an active solvent in both copolymerization approaches. Commercial polycarbonate (PC) was used as a modifying soluble additive. The preparation of blends and method of polymerization by using UV initiator (Irqacure® 651) was proposed. Two parallel sets of MMA-based materials were obtained. The first included more harmless linear hydrocarbons (EGDMA + MMA), whereas the second included the usually used aromatic copolymers (BPA.GDA + MMA). The influence of different amounts of PC on the physicochemical properties was discussed in detail. Chemical structures of the copolymers were confirmed by attenuated total reflection–Fourier transform infrared (ATR/FT-IR) spectroscopy. Thermo-mechanical properties of the synthesized materials were investigated by means of differential scanning calorimetry (DSC), thermogravimetric (TG/DTG) analyses, and dynamic mechanical analysis (DMA). The hardness of the obtained materials was also tested. In order to evaluate the surface of the materials, their images were obtained with the use of atomic force microscopy (AFM).
Green Natural Rubber Composites Reinforced with Black/White Rice Husk Ashes: Effects of Reinforcing Agent on Film’s Mechanical and Dielectric Properties
Authors: Sintharm Praewpakun , Phisalaphong Muenduen
Published: March 2021

Green natural rubber (NR) composites reinforced with black rice husk ash (BRHA)/white rice husk ash (WRHA), using alginate as a thickening and dispersing agent and crosslinking by CaCl2, was developed to improve mechanical, chemical and dielectric properties of NR-based films by using a latex aqueous microdispersion process. A maximum of 100 per hundred rubbers (phr) of rice husk ashes (RHAs) could be integrated in NR matrix without phase separation. Mechanical properties of the composite films were considerably enhanced, compared to the neat NR film. The composite films reinforced with WRHA demonstrated relatively better mechanical properties than those reinforced with BRHA, whereas the composites filled with BRHA demonstrated higher elongation at break. The crosslinking by CaCl2 improved the film tensile strength but lowered the film elasticity. The reinforcement strongly improved chemical resistance of the composite films in toluene. The films are biodegradable in soil, with weight loss of 7.6–18.3% of the initial dry weight after 3 months. Dielectric constant and dielectric loss factors of the composite films were enhanced with RHAs loading. According to the obtained properties, the composites offer potential for further development as stretchable conductive substrate or semiconducting polymer films for electronic applications.
What Fate for Plastics in Artworks? An Overview of Their Identification and Degradative Behaviour
Authors: Lazzari Massimo , Reggio Daniela
Published: March 2021

This review is conceived as a guide for material science researchers and conservators aiming to face the problem of deterioration of contemporary artworks entirely or partially made of plastics. It initially illustrates the analytical approaches for identifying polymeric material components in 3D art objects, such as sculptures and installations, and provides a perspective of their limits and advantages. Subsequently, the methodologies used for studying the deterioration of contemporary art plastics are reviewed, emphasising the main effects of the different types of degradation (i.e., migration of additives, oxidation and hydrolysis) and suggesting the appropriate techniques for their detection. Finally, the application of artificial ageing tests is critically assessed. All the concepts are elaborated through case studies and examples.
Fast-Scanning Chip-Calorimetry Measurement of Crystallization Kinetics of Poly(Glycolic Acid)
Authors: Chen Yongxuan , Xie Kefeng , He Yucheng , Hu Wenbing
Published: March 2021

We report fast-scanning chip-calorimetry measurement of isothermal crystallization kinetics of poly(glycolic acid) (PGA) in a broad temperature range. We observed that PGA crystallization could be suppressed by cooling rates beyond −100 K s−1 and, after fast cooling, by heating rates beyond 50 K s−1. In addition, the parabolic curve of crystallization half-time versus crystallization temperature shows that PGA crystallizes the fastest at 130 °C with the minimum crystallization half-time of 4.28 s. We compared our results to those of poly(L-lactic acid) (PLLA) with nearby molecular weights previously reported by Androsch et al. We found that PGA crystallizes generally more quickly than PLLA. In comparison to PLLA, PGA has a much smaller hydrogen side group than the methyl side group in PLLA; therefore, crystal nucleation is favored by the higher molecular mobility of PGA in the low temperature region as well as by the denser molecular packing of PGA in the high temperature region, and the two factors together decide the higher crystallization rates of PGA in the whole temperature range.
Transference Number Determination in Poor-Dissociated Low Dielectric Constant Lithium and Protonic Electrolytes
Authors: Siekierski Maciej , Bukat Marcin , Ciosek Marcin , Piszcz Michał , Mroczkowska-Szerszeń Maja
Published: March 2021

Whereas the major potential of the development of lithium-based cells is commonly attributed to the use of solid polymer electrolytes (SPE) to replace liquid ones, the possibilities of the improvement of the applicability of the fuel cell is often attributed to the novel electrolytic materials belonging to various structural families. In both cases, the transport properties of the electrolytes significantly affect the operational parameters of the galvanic and fuel cells incorporating them. Amongst them, the transference number (TN) of the electrochemically active species (usually cations) is, on the one hand, one of the most significant descriptors of the resulting cell operational efficiency while on the other, despite many years of investigation, it remains the worst definable and determinable material parameter. The paper delivers not only an extensive review of the development of the TN determination methodology but as well tries to show the physicochemical nature of the discrepancies observed between the values determined using various approaches for the same systems of interest. The provided critical review is supported by some original experimental data gathered for composite polymeric systems incorporating both inorganic and organic dispersed phases. It as well explains the physical sense of the negative transference number values resulting from some more elaborated approaches for highly associated systems.
Quantifying the Role of Occurrence Losses in Catastrophe Excess of Loss Reinsurance Pricing
Authors: Khare Shree , Roy Keven
Published: March 2021

The aim of this paper is to merge order statistics with natural catastrophe reinsurance pricing to develop new theoretical and practical insights relevant to market practice and model development. We present a novel framework to quantify the role that occurrence losses (order statistics) play in pricing of catastrophe excess of loss (catXL) contracts. Our framework enables one to analytically quantify the contribution of a given occurrence loss to the mean and covariance structure, before and after the application of a catXL contract. We demonstrate the utility of our framework with an application to idealized catastrophe models for a multi-peril and a hurricane-only case. For the multi-peril case, we show precisely how contributions to so-called lower layers are dominated by high frequency perils, whereas higher layers are dominated by low-frequency high severity perils. Our framework enables market practitioners and model developers to assess and understand the impact of altered model assumptions on the role of occurrence losses in catXL pricing.
Generative Adversarial Learning in YUV Color Space for Thin Cloud Removal on Satellite Imagery
Authors: Wen Xue , Pan Zongxu , Hu Yuxin , Liu Jiayin
Published: March 2021

Clouds are one of the most serious disturbances when using satellite imagery for ground observations. The semi-translucent nature of thin clouds provides the possibility of 2D ground scene reconstruction based on a single satellite image. In this paper, we propose an effective framework for thin cloud removal involving two aspects: a network architecture and a training strategy. For the network architecture, a Wasserstein generative adversarial network (WGAN) in YUV color space called YUV-GAN is proposed. Unlike most existing approaches in RGB color space, our method performs end-to-end thin cloud removal by learning luminance and chroma components independently, which is efficient at reducing the number of unrecoverable bright and dark pixels. To preserve more detailed features, the generator adopts a residual encoding–decoding network without down-sampling and up-sampling layers, which effectively competes with a residual discriminator, encouraging the accuracy of scene identification. For the training strategy, a transfer-learning-based method was applied. Instead of using either simulated or scarce real data to train the deep network, adequate simulated pairs were used to train the YUV-GAN at first. Then, pre-trained convolutional layers were optimized by real pairs to encourage the applicability of the model to real cloudy images. Qualitative and quantitative results on RICE1 and Sentinel-2A datasets confirmed that our YUV-GAN achieved state-of-the-art performance compared with other approaches. Additionally, our method combining the YUV-GAN with a transfer-learning-based training strategy led to better performance in the case of scarce training data.
Changes in the End-of-Summer Snow Line Altitude of Summer-Accumulation-Type Glaciers in the Eastern Tien Shan Mountains from 1994 to 2016
Authors: Yue Xiaoying , Li Zhongqin , Zhao Jun , Li Huilin , Wang Puyu , Wang Lin
Published: March 2021

For summer-accumulation-type glaciers, the glaciological literature is lacking studies on determining the snow line altitude (SLA) from optical images at the end of the summer as an indicator of the equilibrium line altitude (ELA). This paper presents a workflow for extracting the SLA from Landsat images based on the variation in the albedo with the altitude in the central line area of glaciers. The correlation of >0.8 at the 99% confidence level between the retrieved SLAs with ELAs derived from the interpolation of ground-based, mass balance measurements indicated that the workflow can be applied to derive the SLA from end-of-summer satellite data as an indicator of ELA. The ELA was under-estimated by the calculated SLA. The relationship between the end-of-summer SLA and the ELA depends on the intensity of glacier melting. Subsequently, the workflow was applied to the seven glaciers in the Eastern Tien Shan Mountains, and a time series of the SLA was obtained using 12 end-of-summer Landsat scenes from 1994 to 2016. Over the whole study period, a mean SLA of 4011.6 ± 20.7 m above sea level (a.s.l.) was derived for the seven investigated glaciers, and an increasing SLA was demonstrated. The increase in SLAs was consistent for the seven glaciers from 1994 to 2016. Concerning the spatial variability, the east–west difference was prominent, and these differences exhibited a decreasing trend. The average SLA of each glacier is more influenced by its morpho-topographic variables. The interannual variations in the average SLA are mainly driven by the increasing summer air temperature, and the high correlation with the cumulative summer solid precipitation reflects the characteristics of the summer-accumulation-type glaciers.
Continuous Particle Swarm Optimization-Based Deep Learning Architecture Search for Hyperspectral Image Classification
Authors: Liu Xiaobo , Zhang Chaochao , Cai Zhihua , Yang Jianfeng , Zhou Zhilang , Gong Xin
Published: March 2021

Deep convolutional neural networks (CNNs) are widely used in hyperspectral image (HSI) classification. However, the most successful CNN architectures are handcrafted, which need professional knowledge and consume a very significant amount of time. To automatically design cell-based CNN architectures for HSI classification, we propose an efficient continuous evolutionary method, named CPSO-Net, which can dramatically accelerate optimal architecture generation by the optimization of weight-sharing parameters. First, a SuperNet with all candidate operations is maintained to share the parameters for all individuals and optimized by collecting the gradients of all individuals in the population. Second, a novel direct encoding strategy is devised to encode architectures into particles, which inherit the parameters from the SuperNet. Then, particle swarm optimization is used to search for the optimal deep architecture from the particle swarm. Furthermore, experiments with limited training samples based on four widely used biased and unbiased hyperspectral datasets showed that our proposed method achieves good performance comparable to the state-of-the-art HSI classification methods.
On the Impact and Mitigation of Signal Crosstalk in Ground-Based and Low Altitude Airborne GNSS-R
Authors: Lubeigt Corentin , Ortega Lorenzo , Vilà-Valls Jordi , Lestarquit Laurent , Chaumette Eric
Published: March 2021

Global Navigation Satellite System Reflectometry (GNSS-R) is a powerful way to retrieve information from a reflecting surface by exploiting GNSS as signals of opportunity. In dual antenna conventional GNSS-R architectures, the reflected signal is correlated with a clean replica to obtain the specular reflection point delay and Doppler estimates, which are further processed to obtain the GNSS-R product of interest. An important problem that may appear for low elevation satellites is signal crosstalk, that is the direct line-of-sight signal leaks into the antenna dedicated to the reflected signal. Such crosstalk may degrade the overall system performance if both signals are very close in time, similar to multipath in standard GNSS receivers, the reason why mitigation strategies must be accounted for. In this article: (i) we first provide a geometrical analysis to justify that the estimation performance is only affected for low height receivers; (ii) then, we analyze the impact of crosstalk if not taken into account, by comparing the single source conditional maximum likelihood estimator (CMLE) performance in a dual source context with the corresponding Cramér–Rao bound (CRB); (iii) we discuss dual source estimators as a possible mitigation strategy; and (iv) we investigate the performance of the so-called variance estimator, which is designed to eliminate the coherent signal part, compared to both the CRB and non-coherent dual source estimators. Simulation results are provided for representative GNSS signals to support the discussion. From this analysis, it is found that: (i) for low enough reflected-to-direct signal amplitude ratios (RDR), the crosstalk has no impact on standard single source CMLEs; (ii) for high enough signal-to-noise ratios (SNR), the dual source estimators are efficient irrespective of the RDR, then being a promising solution for any reflected signal scenario; (iii) non-coherent dual source estimators are also efficient at high SNR; and (iv) the variance estimator is efficient as long as the non-coherent part of the signal is dominant.
Evaluation of Multiple Methods for the Production of Continuous Evapotranspiration Estimates from TIR Remote Sensing
Authors: Delogu Emilie , Olioso Albert , Alliès Aubin , Demarty Jérôme , Boulet Gilles
Published: March 2021

Continuous daily estimates of evapotranspiration (ET) spatially distributed at plot scale are required to monitor the water loss and manage crop irrigation needs. Remote sensing approaches in the thermal infrared (TIR) domain are relevant to assess actual ET and soil moisture status but due to lengthy return intervals and cloud cover, data acquisition is not continuous over time. This study aims to assess the performances of 6 commonly used as well as two new reference quantities including rainfall as an index of soil moisture availability to reconstruct seasonal ET from sparse estimates and as a function of the revisit frequency. In a first step, instantaneous in situ eddy-covariance flux tower data collected over multiple ecosystems and climatic areas were used as a proxy for perfect retrievals on satellite overpass dates. In a second step, instantaneous estimations at the time of satellite overpass were produced using the Soil Plant Atmosphere and Remote Sensing Evapotranspiration (SPARSE) energy balance model in order to evaluate the errors concurrent to the use of an energy balance model simulating the instantaneous IRT products from the local surface temperature. Significant variability in the performances from site to site was observed particularly for long revisit frequencies over 8 days, suggesting that the revisit frequency necessary to achieve accurate estimates of ET via temporal upscaling needs to be fewer than 8 days whatever the reference quantity used. For shorter return interval, small differences among the interpolation techniques and reference quantities were found. At the seasonal scale, very simple methods using reference quantities such as the global radiation or clear sky radiation appeared relevant and robust against long revisit frequencies. For infra-seasonal studies targeting stress detection and irrigation management, taking the amount of precipitation into account seemed necessary, especially to avoid the underestimation of ET over cloudy days during a long period without data acquisitions.
Evaluation of the FluorWPS Model and Study of the Parameter Sensitivity for Simulating Solar-Induced Chlorophyll Fluorescence
Authors: Tong Chiming , Bao Yunfei , Zhao Feng , Fan Chongrui , Li Zhenjiang , Huang Qiaolin
Published: March 2021

Solar-induced chlorophyll fluorescence (SIF) has been used as an indicator for the photosynthetic activity of vegetation at regional and global scales. Canopy structure affects the radiative transfer process of SIF within canopy and causes the angular-dependencies of SIF. A common solution for interpreting these effects is the use of physically-based radiative transfer models. As a first step, a comprehensive evaluation of the three-dimensional (3D) radiative transfers is needed using ground truth biological and hyperspectral remote sensing measurements. Due to the complexity of forest modeling, few studies have systematically investigated the effect of canopy structural factors and sun-target-viewing geometry on SIF. In this study, we evaluated the capability of the Fluorescence model with the Weighted Photon Spread method (FluorWPS) to simulate at-sensor radiance and SIF at the top of canopy, and identified the influence of the canopy structural factors and sun-target-viewing geometry on the magnitude and directional response of SIF in deciduous forests. To evaluate the model, a 3D forest scene was first constructed from Goddard’s LiDAR Hyperspectral and Thermal (G-LiHT) LiDAR data. The reliability of the reconstructed scene was confirmed by comparing the calculated leaf area index with the measured ones from the scene, which resulted in a relative error of 3.5%. Then, the performance of FluorWPS was evaluated by comparing the simulated at-sensor radiance spectra with the spectra measured from the DUAL and FLUO spectrometer of HyPlant. The radiance spectra simulated by FluorWPS agreed well with the measured spectra by the two high-performance imaging spectrometers, with a coefficient of determination (R2) of 0.998 and 0.926, respectively. SIF simulated by the FluorWPS model agreed well with the values of the DART model. Furthermore, a sensitivity analysis was conducted to assess the effect of the canopy structural parameters and sun-target-viewing geometry on SIF. The maximum difference of the total SIF can be as large as 45% and 47% at the wavelengths of 685 nm and 740 nm for different foliage area volume densities (FAVDs), and 48% and 46% for fractional vegetation covers (FVCs), respectively. Leaf angle distribution has a markedly influence on the magnitude of SIF, with a ratio of emission part to SIF range from 0.48 to 0.72. SIF from the grass layer under the tree contributed 10%+ more to the top of canopy SIF even for a dense forest canopy (FAVD = 3.5 m−1, FVC = 76%). The red SIF at the wavelength of 685 nm had a similar shape to the far-red SIF at a wavelength of 740 nm but with higher variability in varying illumination conditions. The integration of the FluorWPS model and LiDAR modeling can greatly improve the interpretation of SIF at different scales and angular configurations.
An Efficient Method for Ground Maneuvering Target Refocusing and Motion Parameter Estimation Based on DPT–KT–MFP
Authors: Tian Mingming , Liao Guisheng , Zhu Shengqi , He Xiongpeng , Liu Yongjun , Li Yunpeng
Published: March 2021

The image of ground maneuvering targets may be defocused due to the Doppler ambiguity, high-order range migration (RM), and Doppler frequency migration (DFM) caused by the target’s complex motions in a synthetic aperture radar (SAR) system. To settle these problems, an efficient algorithm based on discrete polynomial-phase transform (DPT), keystone transform (KT), and matched filtering processing (MFP) is presented for ground maneuvering target refocusing and motion parameter estimation in this paper. Firstly, the DPT is applied to transform the cubic phase into the quadratic phase and simultaneously eliminate the quadratic RM, cubic RM, and quadratic DFM. Furthermore, the Doppler ambiguity containing Doppler center blur and Doppler spectrum ambiguity is also dealt with effectively by introducing a very small fixed lay time after DPT operation. Then, the KT is performed to correct the linear RM. After that, the matched filtering function related to the target’s equivalent third-order coefficient is constructed to compensate for the residual linear DFM in the range-time and slow-time domain. Lastly, a well-refocused image of the maneuvering target can be acquired, and the target’s motion parameters can be estimated effectively. The proposed algorithm has high computational efficiency and possesses favorable refocusing performance and motion parameter estimation precision. Simulation and real data processing results prove the effectiveness of the presented algorithm.
Destructive M6.2 Petrinja Earthquake (Croatia) in 2020—Preliminary Multidisciplinary Research
Authors: Markušić Snježana , Stanko Davor , Penava Davorin , Ivančić Ines , Bjelotomić Oršulić Olga , Korbar Tvrtko , Sarhosis Vasilis
Published: March 2021

On 28 December 2020, seismic activity in the wider Petrinja area strongly intensified after a period of relative seismological quiescence that had lasted more than 100 years (since the well-known M5.8 Kupa Valley earthquake of 1909, which is known based on the discovery of the Mohorovičić discontinuity). The day after the M5 foreshock, a destructive M6.2 mainshock occurred. Outcomes of preliminary seismological, geological and SAR image analyses indicate that the foreshocks, mainshock and aftershocks were generated due to the (re)activation of a complex fault system—the intersection of longitudinal NW–SE right-lateral and transverse NE–SW left-lateral faults along the transitional contact zone of the Dinarides and the Pannonian Basin. According to a survey of damage to buildings, approximately 15% of buildings were very heavily damaged or collapsed. Buildings of special or outstanding historical or cultural heritage significance mostly collapsed or became unserviceable. A preliminary analysis of the earthquake ground motion showed that in the epicentral area, the estimated peak ground acceleration PGA values for the bedrock ranged from 0.29 to 0.44 g. In the close Petrinja epicentral area that is characterized by the superficial deposits, significant ground failures were reported within local site effects. Based on that finding and building damage, we assume that the resulting peak ground acceleration (PGAsite) values were likely between 0.4 and 0.6 g depending on the local site characteristics and the distance from the epicentre.
Recent Advancement in Remote Sensing Technology for Hydrology Analysis and Water Resources Management
Authors: Duan Weili , Maskey Shreedhar , Chaffe Pedro L. B. , Luo Pingping , He Bin , Wu Yiping , Hou Jingming
Published: March 2021

Water is undoubtedly the most valuable resource of human society and an essential component of the ecosystem [...]
Variational Low-Rank Matrix Factorization with Multi-Patch Collaborative Learning for Hyperspectral Imagery Mixed Denoising
Authors: Liu Shuai , Feng Jie , Tian Zhiqiang
Published: March 2021

In this study, multi-patch collaborative learning is introduced into variational low-rank matrix factorization to suppress mixed noise in hyperspectral images (HSIs). Firstly, based on the spatial consistency and nonlocal self-similarities, the HSI is partitioned into overlapping patches with a full band. The similarity metric with fusing features is exploited to select the most similar patches and construct the corresponding collaborative patches. Secondly, considering that the latent clean HSI holds the low-rank property across the spectra, whereas the noise component does not, variational low-rank matrix factorization is proposed in the Bayesian framework for each collaborative patch. Using Gaussian distribution adaptively adjusted by a gamma distribution, the noise-free data can be learned by exploring low-rank properties of collaborative patches in the spatial/spectral domain. Additionally, the Dirichlet process Gaussian mixture model is utilized to approximate the statistical characteristics of mixed noises, which is constructed by exploiting the Gaussian distribution, the inverse Wishart distribution, and the Dirichlet process. Finally, variational inference is utilized to estimate all variables and solve the proposed model using closed-form equations. Widely used datasets with different settings are adopted to conduct experiments. The quantitative and qualitative results indicate the effectiveness and superiority of the proposed method in reducing mixed noises in HSIs.
Assessing Vegetation Response to Multi-Scalar Drought across the Mojave, Sonoran, Chihuahuan Deserts and Apache Highlands in the Southwest United States
Authors: Khatri-Chhetri Pratima , Hendryx Sean M. , Hartfield Kyle A. , Crimmins Michael A. , Leeuwen Willem J. D. van , Kane Van R.
Published: March 2021

Understanding the patterns and relationships between vegetation productivity and climatic conditions is essential for predicting the future impacts of climate change. Climate change is altering precipitation patterns and increasing temperatures in the Southwest United States. The large-scale and long-term effects of these changes on vegetation productivity are not well understood. This study investigates the patterns and relationships between seasonal vegetation productivity, represented by Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI), and the Standardized Precipitation Evapotranspiration Index (SPEI) across the Mojave, Sonoran, and Chihuahuan Deserts and the Apache Highlands of the Southwest United States over 16 years from 2000 to 2015. To examine the spatiotemporal gradient and response of vegetation productivity to dry and wet conditions, we evaluated the linear trend of different SPEI timescales and correlations between NDVI and SPEI. We found that all four ecoregions are experiencing more frequent and severe drought conditions in recent years as measured by negative SPEI trends and severe negative SPEI values. We found that changes in NDVI were more strongly correlated with winter rather than summer water availability. Investigating correlations by vegetation type across all four ecoregions, we found that grassland and shrubland productivity were more dependent on summer water availability whereas sparse vegetation and forest productivity were more dependent on winter water availability. Our results can inform resource management and enhance our understanding of vegetation vulnerability to climate change.
An Enhanced Smartphone Indoor Positioning Scheme with Outlier Removal Using Machine Learning
Authors: Zhang Zhenbing , Liu Jingbin , Wang Lei , Guo Guangyi , Zheng Xingyu , Gong Xiaodong , Yang Sheng , Huang Gege
Published: March 2021

In smartphone indoor positioning, owing to the strong complementarity between pedestrian dead reckoning (PDR) and WiFi, a hybrid fusion scheme of them is drawing more and more attention. However, the outlier of WiFi will easily degrade the performance of the scheme, to remove them, many researches have been proposed such as: improving the WiFi individually or enhancing the scheme. Nevertheless, due to the inherent received signal strength (RSS) variation, there still exist some unremoved outliers. To solve this problem, this paper proposes the first outlier detection and removal strategy with the aid of Machine Learning (ML), so called WiFi-AGNES (Agglomerative Nesting), based on the extracted positioning characteristics of WiFi when the pedestrian is static. Then, the paper proposes the second outlier detection and removal strategy, so called WiFi-Chain, based on the extracted positioning characteristics of WiFi, PDR, and their complementary characteristics when the pedestrian is walking. Finally, a hybrid fusion scheme is proposed, which integrates the two proposed strategies, WiFi, PDR with an inertial-navigation-system-based (INS-based) attitude heading reference system (AHRS) via Extended Kalman Filter (EKF), and an Unscented Kalman Filter (UKF). The experiment results show that the two proposed strategies are effective and robust. With WiFi-AGNES, the minimum percentage of the maximum error (MaxE) is reduced by 66.5%; with WiFi-Chain, the MaxE of WiFi is less than 4.3 m; further the proposed scheme achieves the best performance, where the root mean square error (RMSE) is 1.43 m. Moreover, since characteristics are universal, the proposed scheme integrated the two characteristic-based strategies also possesses strong robustness.