bluuebunny/crossref_metadata_2025 huggingface dataset:
Volatile Profile in Yogurt Obtained from Saanen Goats Fed with Olive Leaves
Authors: Bennato Francesca , Innosa Denise , Ianni Andrea , Martino Camillo , Grotta Lisa , Martino Giuseppe
Published: May 2020

The aim of this study was to evaluate the development of volatile compounds in yogurt samples obtained from goats fed a dietary supplementation with olive leaves (OL). For this purpose, thirty Saanen goats were divided into two homogeneous groups of 15 goats each: a control group that received a standard diet (CG) and an experimental group whose diet was supplemented with olive leaves (OLG). The trial lasted 28 days, at the end of which the milk of each group was collected and used for yogurt production. Immediately after production, and after 7 days of storage at 4 °C in the absence of light, the yogurt samples were characterized in terms of fatty acid profile, oxidative stability and volatile compounds by the solid-phase microextraction (SPME)–GC/MS technique. Dietary OL supplementation positively affected the fatty acid composition, inducing a significant increase in the relative proportion of unsaturated fatty acids, mainly oleic acid (C18:1 cis9) and linolenic acid (C18:3). With regard to the volatile profile, both in fresh and yogurt samples stored for 7 days, the OL supplementation induced an increase in free fatty acids, probably due to an increase in lipolysis carried out by microbial and endogenous milk enzymes. Specifically, the largest variations were found for C6, C7, C8 and C10 free fatty acids. In the same samples, a significant decrease in aldehydes, mainly heptanal and nonanal, was also detected, supporting—at least in part—an improvement in the oxidative stability. Moreover, alcohols, esters and ketones appeared lower in OLG samples, while no significant variations were observed for lactones. These findings suggest the positive role of dietary OL supplementation in the production of goats’ milk yogurt, with characteristics potentially indicative of an improvement in nutritional properties and flavor.
Preparation of Protein–Peptide–Calcium Phosphate Composites for Controlled Protein Release
Authors: Kato Katsuya , Lee Sungho , Nagata Fukue
Published: May 2020

Protein–peptide–calcium phosphate composites were developed for achieving sustainable and controlled protein release. Bovine serum albumin (BSA) as a model acidic protein was efficiently encapsulated with basic polypeptides such as polylysine and polyarginine during the precipitation of calcium phosphate (CaP). The prepared composites were fully characterized in terms of their morphologies, crystallinities, and the porosity of their structures, and from these analyses, it was observed that there are no significant differences between the composites. Scanning transmission electron microscopy and energy dispersive X-ray spectroscopy analysis indicated a homogeneous distribution of nitrogen and sulfur, confirming the uniform distribution of BSA and polypeptide in the CaP composite. In vitro release studies demonstrated that the composite prepared with the peptides α-polylysine and polyarginine were suitable for the gradual release of the protein BSA, while those containing ε-polylysine and no peptide were unsuitable for protein release. Additionally, these composites showed high hemocompatibility for mouse red blood cells, and the osteoblast-like cell proliferation and spread in media with the composites prepared using BSA and α-polylysine showed similar tendencies to medium with no composite. From these results, protein–peptide–CaP composites are expected to be useful as highly biocompatible protein delivery agents.
Methods to Enhance the Metabolic Stability of Peptide-Based PET Radiopharmaceuticals
Authors: Evans Brendan J. , King Andrew T. , Katsifis Andrew , Matesic Lidia , Jamie Joanne F.
Published: May 2020

The high affinity and specificity of peptides towards biological targets, in addition to their favorable pharmacological properties, has encouraged the development of many peptide-based pharmaceuticals, including peptide-based positron emission tomography (PET) radiopharmaceuticals. However, the poor in vivo stability of unmodified peptides against proteolysis is a major challenge that must be overcome, as it can result in an impractically short in vivo biological half-life and a subsequently poor bioavailability when used in imaging and therapeutic applications. Consequently, many biologically and pharmacologically interesting peptide-based drugs may never see application. A potential way to overcome this is using peptide analogues designed to mimic the pharmacophore of a native peptide while also containing unnatural modifications that act to maintain or improve the pharmacological properties. This review explores strategies that have been developed to increase the metabolic stability of peptide-based pharmaceuticals. It includes modifications of the C- and/or N-termini, introduction of d- or other unnatural amino acids, backbone modification, PEGylation and alkyl chain incorporation, cyclization and peptide bond substitution, and where those strategies have been, or could be, applied to PET peptide-based radiopharmaceuticals.
New Donor-Acceptor Stenhouse Adducts as Visible and Near Infrared Light Polymerization Photoinitiators
Authors: Noirbent Guillaume , Xu Yangyang , Bonardi Aude-Héloise , Duval Sylvain , Gigmes Didier , Lalevée Jacques , Dumur Frédéric
Published: May 2020

Polymerization photoinitiators that can be activated under low light intensity and in the visible range are being pursued by both the academic and industrial communities. To efficiently harvest light and initiate a polymerization process, dyes with high molar extinction coefficients in the visible range are ideal candidates. In this field, Donor-acceptor Stenhouse Adducts (DASA) which belong to a class of recently discovered organic photochromic molecules still lack practical applications. In this work, a series of DASA-based dyes are proposed as photoinitiators for the free radical polymerization of (meth)acrylates upon exposure to a near infrared light (laser diode at 785 nm).
1,2,4-Triazine Sulfonamides: Synthesis by Sulfenamide Intermediates, In Vitro Anticancer Screening, Structural Characterization, and Molecular Docking Study
Authors: Branowska Danuta , Karczmarzyk Zbigniew , Wolińska Ewa , Wysocki Waldemar , Morawiak Maja , Urbańczyk-Lipkowska Zofia , Bielawska Anna , Bielawski Krzysztof
Published: May 2020

In this study, we synthesized novel sulfonamides with a 1,2,4-triazine moiety according to pharmacophore requirements for biological activity. All the synthesized compounds were tested in vitro to verify whether they exhibited anticancer activity against the human breast cancer cell lines MCF-7 and MDA-MB-231. Among them, two most active ones, having IC50 values of 50 and 42 µM, respectively, were found to show higher anticancer activity than chlorambucil used as the reference in the in vitro tests. In addition, two other compounds, which had IC50 values of 78 and 91 µM, respectively, exhibited a similar level of activity as chlorambucil. X-ray analysis carried out for two of the compounds confirmed their synthesis pathway as well as their assumed molecular structures. Furthermore, a conformational analysis was performed, and electronic parameters of molecules were characterized using theoretical calculations at AM1 and DFT level. Moreover, molecular docking revealed the mode of binding of the investigated 1,2,4-triazine sulfonamides with the human estrogen receptor alpha (ERα).
Last Decade of Unconventional Methodologies for the Synthesis of Substituted Benzofurans
Authors: Chiummiento Lucia , D’Orsi Rosarita , Funicello Maria , Lupattelli Paolo
Published: May 2020

This review describes the progress of the last decade on the synthesis of substituted benzofurans, which are useful scaffolds for the synthesis of numerous natural products and pharmaceuticals. In particular, new intramolecular and intermolecular C–C and/or C–O bond-forming processes, with transition-metal catalysis or metal-free are summarized. (1) Introduction. (2) Ring generation via intramolecular cyclization. (2.1) C7a–O bond formation: (route a). (2.2) O–C2 bond formation: (route b). (2.3) C2–C3 bond formation: (route c). (2.4) C3–C3a bond formation: (route d). (3) Ring generation via intermolecular cyclization. (3.1) C7a-O and C3–C3a bond formation (route a + d). (3.2) O–C2 and C2–C3 bond formation: (route b + c). (3.3) O–C2 and C3–C3a bond formation: (route b + d). (4) Benzannulation. (5) Conclusion.
Exploiting the Indole Scaffold to Design Compounds Binding to Different Pharmacological Targets
Authors: Taliani Sabrina , Da Settimo Federico , Martini Claudia , Laneri Sonia , Novellino Ettore , Greco Giovanni
Published: May 2020

Several indole derivatives have been disclosed by our research groups that have been collaborating for nearly 25 years. The results of our investigations led to a variety of molecules binding selectively to different pharmacological targets, specifically the type A γ-aminobutyric acid (GABAA) chloride channel, the translocator protein (TSPO), the murine double minute 2 (MDM2) protein, the A2B adenosine receptor (A2B AR) and the Kelch-like ECH-associated protein 1 (Keap1). Herein, we describe how these works were conceived and carried out thanks to the versatility of indole nucleus to be exploited in the design and synthesis of drug-like molecules.
Geographical Classification of Italian Saffron (Crocus sativus L.) by Multi-Block Treatments of UV-Vis and IR Spectroscopic Data
Authors: Biancolillo Alessandra , Foschi Martina , D’Archivio Angelo Antonio
Published: May 2020

One-hundred and fourteen samples of saffron harvested in four different Italian areas (three in Central Italy and one in the South) were investigated by IR and UV-Vis spectroscopies. Two different multi-block strategies, Sequential and Orthogonalized Partial Least Squares Linear Discriminant Analysis (SO-PLS-LDA) and Sequential and Orthogonalized Covariance Selection Linear Discriminant Analysis (SO-CovSel-LDA), were used to simultaneously handle the two data blocks and classify samples according to their geographical origin. Both multi-block approaches provided very satisfying results. Each model was investigated in order to understand which spectral variables contribute the most to the discrimination of samples, i.e., to the characterization of saffron harvested in the four different areas. The most accurate solution was provided by SO-PLS-LDA, which only misclassified three test samples over 31 (in external validation).
Green Tea Seed Isolated Theasaponin E1 Ameliorates AD Promoting Neurotoxic Pathogenesis by Attenuating Aβ Peptide Levels in SweAPP N2a Cells
Authors: Khan Muhammad Imran , Shin Jin Hyuk , Kim Min Yong , Shin Tai Sun , Kim Jong Deog
Published: May 2020

Alzheimer’s disease (AD) is the most frequent type of dementia affecting memory, thinking and behaviour. The major hallmark of the disease is pathological neurodegeneration due to abnormal aggregation of Amyloid beta (Aβ) peptides generated by β- and γ-secretases via amyloidogenic pathway. Purpose of the current study was to evaluate the effects of theasaponin E1 on the inhibition of Aβ producing β-, γ-secretases (BACE1, PS1 and NCT) and acetylcholinesterase and activation of the non-amyloidogenic APP processing α-secretase (ADAM10). Additionally, theasaponin E1 effects on Aβ degrading and clearing proteins neprilysin and insulin degrading enzyme (IDE). The effect of theasaponin E1 on these crucial enzymes was investigated by RT-PCR, ELISA, western blotting and fluorometric assays using mouse neuroblastoma cells (SweAPP N2a). theasaponin E1 was extracted and purified from green tea seed extract via HPLC, and N2a cells were treated with different concentrations for 24 h. Gene and protein expression in the cells were measured to determine the effects of activation and/or inhibition of theasaponin E1 on β- and γ-secretases, neprilysin and IDE. Results demonstrated that theasaponin E1 significantly reduced Aβ concentration by activation of the α-secretase and neprilysin. The activities of β- and γ-secretase were reduced in a dose-dependent manner due to downregulation of BACE1, presenilin, and nicastrin. Similarly, theasaponin E1 significantly reduced the activity of acetylcholinesterase. Overall, from the results it is concluded that green tea seed extracted saponin E1 possess therapeutic significance as a neuroprotective natural product recommended for the treatment of Alzheimer’s disease.
Radiosensitization by Gold Nanoparticles: Impact of the Size, Dose Rate, and Photon Energy
Authors: Morozov Kirill V. , Kolyvanova Maria A. , Kartseva Maria E. , Shishmakova Elena M. , Dement’eva Olga V. , Isagulieva Alexandra K. , Salpagarov Magomet H. , Belousov Alexandr V. , Rudoy Victor M. , Shtil Alexander A. , Samoylov Alexander S. , Morozov Vladimir N.
Published: May 2020

Gold nanoparticles (GNPs) emerged as promising antitumor radiosensitizers. However, the complex dependence of GNPs radiosensitization on the irradiation conditions remains unclear. In the present study, we investigated the impacts of the dose rate and photon energy on damage of the pBR322 plasmid DNA exposed to X-rays in the presence of 12 nm, 15 nm, 21 nm, and 26 nm GNPs. The greatest radiosensitization was observed for 26 nm GNPs. The sensitizer enhancement ratio (SER) 2.74 ± 0.61 was observed at 200 kVp with 2.4 mg/mL GNPs. Reduction of X-ray tube voltage to 150 and 100 kVp led to a smaller effect. We demonstrate for the first time that the change of the dose rate differentially influences on radiosensitization by GNPs of various sizes. For 12 nm, an increase in the dose rate from 0.2 to 2.1 Gy/min led to a ~1.13-fold increase in radiosensitization. No differences in the effect of 15 nm GNPs was found within the 0.85–2.1 Gy/min range. For 21 nm and 26 nm GNPs, an enhanced radiosensitization was observed along with the decreased dose rate from 2.1 to 0.2 Gy/min. Thus, GNPs are an effective tool for increasing the efficacy of orthovoltage X-ray exposure. However, careful selection of irradiation conditions is a key prerequisite for optimal radiosensitization efficacy.
Nanoparticulate Gels for Cutaneous Administration of Caffeic Acid
Authors: Sguizzato Maddalena , Mariani Paolo , Ferrara Francesca , Drechsler Markus , Hallan Supandeep Singh , Huang Nicolas , Simelière Fanny , Khunti Nikul , Cortesi Rita , Marchetti Nicola , Valacchi Giuseppe , Esposito Elisabetta
Published: May 2020

Caffeic acid is a natural antioxidant, largely distributed in plant tissues and food sources, possessing anti-inflammatory, antimicrobial, and anticarcinogenic properties. The object of this investigation was the development of a formulation for caffeic acid cutaneous administration. To this aim, caffeic acid has been loaded in solid lipid nanoparticles by hot homogenization and ultrasonication, obtaining aqueous dispersions with high drug encapsulation efficiency and 200 nm mean dimension, as assessed by photon correlation spectroscopy. With the aim to improve the consistence of the aqueous nanodispersions, different types of polymers have been considered. Particularly, poloxamer 407 and hyaluronic acid gels containing caffeic acid have been produced and characterized by X-ray and rheological analyses. A Franz cell study enabled to select poloxamer 407, being able to better control caffeic acid diffusion. Thus, a nanoparticulate gel has been produced by addition of poloxamer 407 to nanoparticle dispersions. Notably, caffeic acid diffusion from nanoparticulate gel was eight-fold slower with respect to the aqueous solution. In addition, the spreadability of nanoparticulate gel was suitable for cutaneous administration. Finally, the antioxidant effect of caffeic acid loaded in nanoparticulate gel has been demonstrated by ex-vivo evaluation on human skin explants exposed to cigarette smoke, suggesting a protective role exerted by the nanoparticles.
Hydrothermal Synthesis of Hematite Nanoparticles Decorated on Carbon Mesospheres and Their Synergetic Action on the Thermal Decomposition of Nitrocellulose
Authors: Benhammada Abdenacer , Trache Djalal , Kesraoui Mohamed , Chelouche Salim
Published: May 2020

In this study, carbon mesospheres (CMS) and iron oxide nanoparticles decorated on carbon mesospheres (Fe2O3-CMS) were effectively synthesized by a direct and simple hydrothermal approach. α-Fe2O3 nanoparticles have been successfully dispersed in situ on a CMS surface. The nanoparticles obtained have been characterized by employing different analytical techniques encompassing Fourier transform infrared (FTIR) spectroscopy, Raman spectroscopy, X-ray diffraction (XRD) and scanning electron microscopy (SEM). The produced carbon mesospheres, mostly spherical in shape, exhibited an average size of 334.5 nm, whereas that of Fe2O3 supported on CMS is at around 80 nm. The catalytic effect of the nanocatalyst on the thermal behavior of cellulose nitrate (NC) was investigated by utilizing differential scanning calorimetry (DSC). The determination of kinetic parameters has been carried out using four isoconversional kinetic methods based on DSC data obtained at various heating rates. It is demonstrated that Fe2O3-CMS have a minor influence on the decomposition temperature of NC, while a noticeable diminution of the activation energy is acquired. In contrast, pure CMS have a slight stabilizing effect with an increase of apparent activation energy. Furthermore, the decomposition reaction mechanism of NC is affected by the introduction of the nano-catalyst. Lastly, we can infer that Fe2O3-CMS may be securely employed as an effective catalyst for the thermal decomposition of NC.
RETRACTED: Expression Profile of Long Non-Coding RNAs during Early Postnatal Development of Mouse Spinal Cord
Authors: Verheijen Bert
Published: May 2020

Out of respect for the institution’s wishes, in agreement with the Non-Coding RNA Editorial Office, and in agreement with the author, this article has been removed from the public record and marked as retracted. Please refer to the retraction note.
Mangosteen Concentrate Drink Supplementation Promotes Antioxidant Status and Lactate Clearance in Rats after Exercise
Authors: Chang Ching-Chien , Chen Chia-Wen , Owaga Eddy , Lee Wan-Ting , Liu Ting-Ni , Hsieh Rong-Hong
Published: May 2020

High-strength or long-duration exercise can lead to significant fatigue, oxidative stress, and muscle damage. The purpose of this study was to examine the effect of mangosteen concentrate drink (MCD) supplementation on antioxidant capacity and lactate clearance in rats after running exercise. Forty rats were divided into five groups: N, non-treatment; C, control; or supplemented with MCD, including M1, M5, and M10 (0.9, 4.5, and 9 mL/day) for 6 weeks. The rats were subjected to 30 min running and exhaustive-running tests using a treadmill. The blood lactate; triglyceride; cholesterol and glucose levels; hepatic and muscular malonaldehyde (MDA) levels; and antioxidant enzymes, including superoxide dismutase (SOD), glutathione peroxidase (GPx), and catalase (CAT), were analyzed. The results of this study demonstrated that MCD supplementation can increase GPx and CAT activities, alleviate oxidative stress in muscle, and increase lactate clearance, and is thereby beneficial to reduced muscle fatigue after exercise.
The Correlation between Physical Crosslinking and Water-Soluble Drug Release from Chitosan-Based Microparticles
Authors: Szymańska Emilia , Woś-Latosi Katarzyna , Jacyna Julia , Dąbrowska Magdalena , Potaś Joanna , Markuszewski Michał Jan , Winnicka Katarzyna
Published: May 2020

Microparticles containing water-soluble zidovudine were prepared by spray-drying using chitosan glutamate and beta-glycerophosphate as an ion crosslinker (CF). The Box–Behnken design was applied to optimize the microparticles in terms of their drug loading and release behavior. Physicochemical studies were undertaken to support the results from dissolution tests and to evaluate the impact of the crosslinking ratio on the microparticles’ characteristics. The zidovudine dissolution behavior had a complex nature which comprised two phases: an initial burst effect followed with a prolonged release stage. The initial drug release, which can be modulated by the crosslinking degree, was primarily governed by the dissolution of the drug crystals located on the microparticles’ surfaces. In turn, the further dissolution stage was related to the drug diffusion from the swollen polymer matrix and was found to correlate with the drug loading. Differential Scanning Calorimetry (DSC) studies revealed the partial incorporation of a non-crystallized drug within the polymer matrix, which correlated with the amount of CF. Although CF influenced the swelling capacity of chitosan glutamate microparticles, surprisingly a higher amount of CF did not impact the time required for 80% of the drug to be released markedly. The formulation with the lowest polymer:CF ratio, 3:1, was selected as optimal, providing satisfactory drug loading and displaying a moderate burst effect within the first 30 min of the study, followed with a prolonged drug release of up to 210 min.
Salvianolic Acid B in Microemulsion Formulation Provided Sufficient Hydration for Dry Skin and Ameliorated the Severity of Imiquimod-induced Psoriasis-like Dermatitis in Mice
Authors: Guo Jiun-Wen , Cheng Yu-Pin , Liu Chih-Yi , Thong Haw-Yueh , Huang Chi-Jung , Lo Yang , Wu Chen-Yu , Jee Shiou-Hwa
Published: May 2020

Psoriasis is a chronic inflammatory skin disorder with a pathogenesis involving the interleukin-23/interleukin-17 axis. Salvianolic acid B exerts several pharmacological effects, such as antioxidation, anti-inflammation, and antitumor effects. The anti-psoriatic effects of salvianolic acid B have not been reported. In this study, we aimed to determine the optimum vehicle for salvianolic acid B, investigate its therapeutic effect on psoriatic-like skin conditions, and explore its underlying mechanisms of action. BALB/c mice were administered topical imiquimod to induce psoriasis-like skin and were then randomly assigned to control, vehicle control, salvianolic acid B in vehicles, and 0.25% desoximetasone ointment treatment groups. Barrier function, cytokine expression, histology assessment, and disease severity were evaluated. The results showed that salvianolic acid B-containing microemulsion alleviated disease severity, reduced acanthosis, and inhibited interleukin-23/interleukin-17 (IL-23/IL-17) cytokines, epidermal proliferation, and increased skin hydration. Our study suggests that salvianolic acid B represents a possible new therapeutic drug for the treatment of psoriasis. In addition, such formulation could obtain high therapeutic efficacy in addition to providing sufficient hydration for dry skin.
Redox-Sensitive Linear and Cross-Linked Cystamine-Based Polymers for Colon-Targeted Drug Delivery: Design, Synthesis, and Characterisation
Authors: Ng Yoke Mooi , Mat Yusuf Siti Nur Aishah , Chiu Hock Ing , Lim Vuanghao
Published: May 2020

Cystamine-based polymers may help to achieve controlled and targeted drug delivery to the colon due to their susceptibility to breakage of the disulfide linkage in the low redox potential environment of the colon. In this study, two linear cystamine-based polymers with similar repeating units (LP1 and LP2) and a cross-linked cystamine-based polymer (BP) were synthesised and their kinetics and the various physical conditions underlying cystamine-based polymerisation were evaluated. In brief, N1,N6-bis(2-(tritylthio)ethyl)adipamide (2) was synthesised from the reaction of triphenylmethanol and cysteamine. Next, the trityl group of 2 was removed with trifluoroacetic acid and triethylsilane before proceeding to oxidative polymerisation of the end product, N1,N6-bis(2-mercaptoethyl)adipamide (3) to LP1. The Schotten-Bauman reaction was applied to synthesise LP2 and BP from the reaction of cystamine with adipoyl chloride or trimesoyl chloride. Scanning electron microscopy, energy-dispersive X-ray spectroscopy, and mapping showed that oxygen, nitrogen, sulfur, and carbon were homogenously distributed in the polymers, with LP2 and BP having less porous morphologies compared to LP1. Results of zinc-acetic acid reduction showed that all polymers began to reduce after 15 min. Moreover, all synthesised polymers resisted stomach and small intestine conditions and only degraded in the presence of bacteria in the colon environment. Thus, these polymers have great potential for drug delivery applications. LP2 and BP, which were synthesised using the Schotten-Bauman reaction, were more promising than LP1 for colon-targeted drug delivery.
Indoxacarb-Loaded Anionic Polyurethane Blend with Sodium Alginate Improves pH Sensitivity and Ecological Security for Potential Application in Agriculture
Authors: Wang Shiying , Zhang Yi , Yang Liupeng , Zhu Qizhan , Ma Qianli , Wang Ruifei , Zhang Chaoqun , Zhang Zhixiang
Published: May 2020

Traditional pesticide formulations show poor utilization and environmental safety due to their low foliage adhesion and large auxiliaries. In this study, a novel and environment-friendly indoxacarb formulation was prepared to improve the pesticide’s utilization rate, target control characteristics and ecological security. Indoxacarb-loaded waterborne polyurethane–sodium alginate (PU/SA) nanoemulsions with film forming properties, alkaline responsive release, high effectiveness against Spodoptera litura, and reduced acute contact toxicity for nontarget organisms were successfully prepared. The colloidal properties, swelling and release behaviors, leaf adhesion, degradation dynamics and bioactivity assay of the indoxacarb-loaded PU/SA nanoemulsions were determined. Results showed that the obtained indoxacarb-loaded microcapsule particulates were approximately 57 nm in diameter, electronegative −45.9 mV, and uniformly dispersed in the nanoemulsions. The dried latex films of PU/SA in the alkaline environment revealed better responsive swelling and release characteristics than those in acidic and neutral conditions. Compared with a commercial emulsifiable concentrate, the indoxacarb-loaded PU/SA nanoemulsions were useful for the targeted control of S. litura, which have alkaline gut and showed reduced acute contact toxicity to Harmonia axyridia. Furthermore, the PU/SA formulation had better foliage adhesion and indicated the property of controlled-release and a persistent effect.
Mechanical Properties of a Soy Protein Isolate–Grafted–Acrylate (SGA) Copolymer Used for Wood Coatings
Authors: Feng Bin , Wang Di , Li Yuhui , Qian Junpeng , Yu Chenlei , Wang Mingsi , Luo Danni , Wei Shuangying
Published: May 2020

Changing demands have led to rapidly growing interest in the modification of waterborne wood coatings. To improve the performance of a polyacrylate wood coating, especially the strength, hardness, and abrasion resistance of the film, a soy protein isolate–grafted–acrylate (SGA) copolymer was prepared in an aqueous solution with ammonium persulfate (APS) as an initiator and sodium pyrosulfite (SPS) as an unfolding agent for the soybean protein isolate (SPI). The emulsion was characterized using transmission electron microscopy, Fourier-transform infrared spectroscopy (FTIR), and a particle size analyzer. Furthermore, the mechanical properties of the film, including the tensile strength, elastic modulus, elongation at break, and pencil hardness, were measured. The results showed that the glass transition temperature of the polyacrylic resin decreased to 35 °C after the SPI grafting. The elastic modulus of the film increased from 0.317 to 46.949 MPa, and the elongation at break decreased from 453.133% to 187.125% as the addition of SPI varied from 0 to 4 g, respectively. The pencil hardness of the wood coating increased from HB to 3H. This paper proposes a feasible route for the utilization of SPI for wood coatings.
Recent Applications of Advanced Atomic Force Microscopy in Polymer Science: A Review
Authors: Nguyen-Tri Phuong , Ghassemi Payman , Carriere Pascal , Nanda Sonil , Assadi Aymen Amine , Nguyen Dinh Duc
Published: May 2020

Atomic force microscopy (AFM) has been extensively used for the nanoscale characterization of polymeric materials. The coupling of AFM with infrared spectroscope (AFM-IR) provides another advantage to the chemical analyses and thus helps to shed light upon the study of polymers. This paper reviews some recent progress in the application of AFM and AFM-IR in polymer science. We describe the principle of AFM-IR and the recent improvements to enhance its resolution. We also discuss the latest progress in the use of AFM-IR as a super-resolution correlated scanned-probe infrared spectroscopy for the chemical characterization of polymer materials dealing with polymer composites, polymer blends, multilayers, and biopolymers. To highlight the advantages of AFM-IR, we report several results in studying the crystallization of both miscible and immiscible blends as well as polymer aging. Finally, we demonstrate how this novel technique can be used to determine phase separation, spherulitic structure, and crystallization mechanisms at nanoscales, which has never been achieved before. The review also discusses future trends in the use of AFM-IR in polymer materials, especially in polymer thin film investigation.
Quantifying Seagrass Distribution in Coastal Water with Deep Learning Models
Authors: Perez Daniel , Islam Kazi , Hill Victoria , Zimmerman Richard , Schaeffer Blake , Shen Yuzhong , Li Jiang
Published: May 2020

Coastal ecosystems are critically affected by seagrass, both economically and ecologically. However, reliable seagrass distribution information is lacking in nearly all parts of the world because of the excessive costs associated with its assessment. In this paper, we develop two deep learning models for automatic seagrass distribution quantification based on 8-band satellite imagery. Specifically, we implemented a deep capsule network (DCN) and a deep convolutional neural network (CNN) to assess seagrass distribution through regression. The DCN model first determines whether seagrass is presented in the image through classification. Second, if seagrass is presented in the image, it quantifies the seagrass through regression. During training, the regression and classification modules are jointly optimized to achieve end-to-end learning. The CNN model is strictly trained for regression in seagrass and non-seagrass patches. In addition, we propose a transfer learning approach to transfer knowledge in the trained deep models at one location to perform seagrass quantification at a different location. We evaluate the proposed methods in three WorldView-2 satellite images taken from the coastal area in Florida. Experimental results show that the proposed deep DCN and CNN models performed similarly and achieved much better results than a linear regression model and a support vector machine. We also demonstrate that using transfer learning techniques for the quantification of seagrass significantly improved the results as compared to directly applying the deep models to new locations.
Assessment of AMSR2 Ice Extent and Ice Edge in the Arctic Using IMS
Authors: Liu Yinghui , Helfrich Sean , Meier Walter N. , Dworak Richard
Published: May 2020

This work assesses the AMSR2 (the Advanced Microwave Scanning Radiometer 2) ice extent and ice edge in the Arctic using the ice extent products of NOAA’s Interactive Multisensor Snow and Ice Mapping System (IMS) from the period of July 2015 to July 2019. Daily values and monthly means of four statistical scores (hit rate, false alarm ratio, false alarm rate, and Hanssen-Kuiper Skill Score) over the Arctic Ocean show distinct annual cycles. IMS ice edges often extend further south compared to those from AMSR2, with up to 100 km differences over the Beaufort, Chukchi, and East Siberian Seas in August and September.
Spatiotemporal Variations of Precipitation over Iran Using the High-Resolution and Nearly Four Decades Satellite-Based PERSIANN-CDR Dataset
Authors: Mosaffa Hamidreza , Sadeghi Mojtaba , Hayatbini Negin , Afzali Gorooh Vesta , Akbari Asanjan Ata , Nguyen Phu , Sorooshian Soroosh
Published: May 2020

Spatiotemporal precipitation trend analysis provides valuable information for water management decision-making. Satellite-based precipitation products with high spatial and temporal resolution and long records, as opposed to temporally and spatially sparse rain gauge networks, are a suitable alternative to analyze precipitation trends over Iran. This study analyzes the trends in annual, seasonal, and monthly precipitation along with the contribution of each season and month in the annual precipitation over Iran for the 1983–2018 period. For the analyses, the Mann–Kendall test is applied to the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) estimates. The results of annual, seasonal, and monthly precipitation trends indicate that the significant decreases in the monthly precipitation trends in February over the western (March over the western and central-eastern) regions of Iran cause significant effects on winter (spring) and total annual precipitation. Moreover, the increases in the amounts of precipitation during November in the south and south-east regions lead to a remarkable increase in the amount of precipitation during the fall season. The analysis of the contribution of each season and month to annual precipitation in wet and dry years shows that dry years have critical impacts on decreasing monthly precipitation over a particular region. For instance, a remarkable decrease in precipitation amounts is detectable during dry years over the eastern, northeastern, and southwestern regions of Iran during March, April, and December, respectively. The results of this study show that PERSIANN-CDR is a valuable source of information in low-density gauge network areas, capturing spatiotemporal variation of precipitation.
Strong Interrelation between the Short-Term Variability in the Ionosphere, Upper Mesosphere, and Winter Polar Stratosphere
Authors: Yasyukevich Anna , Medvedeva Irina , Sivtseva Vera , Chernigovskaya Marina , Ammosov Petr , Gavrilyeva Galina
Published: May 2020

We perform a joint analysis of short-period (up to several hours) variability in parameters of the ionosphere, the mesosphere, and the stratosphere at mid-latitude, subauroral, and high-latitude points for a long time interval. The study is based on the ionospheric total electron content (TEC) measurements and data on the OH rotational temperature at the mesopause height. We reveal similar seasonal variations in the dynamics of the short-term variability level, both in the ionosphere and the mesosphere. Maximum variability is observed during winter months and it exceeds the values in summer period up to 5–6 times. The revealed dynamics has no explicit relation to the levels of geomagnetic and solar activities. We suggest that the instabilities in the high-velocity stratospheric subauroral winter jet stream may be a source of the recorded variability seasonal variations in the ionosphere and the mesosphere. We propose a new index to estimate a short-term variability in the stratosphere. The index is shown to experience similar regular seasonal variations with a maximum during winter months. We show a clear correlation between the mesosphere/ionosphere variability indices values and the stratosphere disturbance index. The correlation is shown to be higher for the mesosphere variability index as compared with that in the ionosphere, and at the high-latitude point located closer to the jet stream. The obtained results indicate a strong interrelation between the short-period variability in the ionosphere, in the upper mesosphere, and in the subauroral stratosphere. The results contribute to elucidating the basic mechanisms for a vertical coupling between different atmospheric layers.
National Scale Spatial Variation in Artificial Light at Night
Authors: Cox Daniel T.C. , Sánchez de Miguel Alejandro , Dzurjak Simon A. , Bennie Jonathan , Gaston Kevin J.
Published: May 2020

The disruption to natural light regimes caused by outdoor artificial nighttime lighting has significant impacts on human health and the natural world. Artificial light at night takes two forms, light emissions and skyglow (caused by the scattering of light by water, dust and gas molecules in the atmosphere). Key to determining where the biological impacts from each form are likely to be experienced is understanding their spatial occurrence, and how this varies with other landscape factors. To examine this, we used data from the Visible Infrared Imaging Radiometer Suite (VIIRS) day/night band and the World Atlas of Artificial Night Sky Brightness, to determine covariation in (a) light emissions, and (b) skyglow, with human population density, landcover, protected areas and roads in Britain. We demonstrate that, although artificial light at night increases with human density, the amount of light per person decreases with increasing urbanization (with per capita median direct emissions three times greater in rural than urban populations, and per capita median skyglow eleven times greater). There was significant variation in artificial light at night within different landcover types, emphasizing that light pollution is not a solely urban issue. Further, half of English National Parks have higher levels of skyglow than light emissions, indicating their failure to buffer biodiversity from pressures that artificial lighting poses. The higher per capita emissions in rural than urban areas provide different challenges and opportunities for mitigating the negative human health and environmental impacts of light pollution.
Ice Concentration Retrieval from the Analysis of Microwaves: Evaluation of a New Methodology Optimized for the Copernicus Imaging Microwave Radiometer
Authors: Prigent Catherine , Kilic Lise , Aires Filipe , Pellet Victor , Jimenez Carlos
Published: May 2020

A new methodology has been described in Kilic et al. (Ice Concentration Retrieval from the Analysis of Microwaves: A New Methodology Designed for the Copernicus Imaging Microwave Radiometer, Remote Sensing 2020, 12, 1060, Part 1 of this study) to estimate Sea Ice Concentration (SIC) from satellite passive microwave observations between 6 and 36 GHz. The Ice Concentration Retrieval from the Analysis of Microwaves (IceCREAM) algorithm is based on an optimal estimation, with a simple radiative transfer model derived from satellite observations at 0% and 100% SIC. Observations at low and high frequencies have different spatial resolutions, and a scheme is developed to benefit from the low errors of the low frequencies and the high spatial resolutions of the high frequencies. This effort is specifically designed for the Copernicus Imaging Microwave Radiometer (CIMR) project, equipped with a large deployable antenna to provide a spatial resolution of ∼5 km at 18 and 36 GHz, and ∼15 km at 6 and 10 GHz. The algorithm is tested with Advanced Microwave Scanning Radiometer 2 (AMSR2) observations, for a clear scene over the north polar region, with collocated Moderate Resolution Imaging Spectroradiometer (MODIS) estimates and the Ocean Sea Ice—Satellite Application Facilities (OSI SAF) operational products. Several algorithm options are tested, and the study case shows that both high spatial resolution and low errors are obtained with the IceCREAM method. It is also tested for the full polar regions, winter and summer, under clear and cloudy conditions. Our method is globally applicable, without fine-tuning or further weather filtering. The systematic use of all channels from 6 to 36 GHz makes it robust to changes in ice surface conditions and to weather interactions.
Transforming Unmanned Aerial Vehicle (UAV) and Multispectral Sensor into a Practical Decision Support System for Precision Nitrogen Management in Corn
Authors: Thompson Laura J. , Puntel Laila A.
Published: May 2020

Determining the optimal nitrogen (N) rate in corn remains a critical issue, mainly due to unaccounted spatial (e.g., soil properties) and temporal (e.g., weather) variability. Unmanned aerial vehicles (UAVs) equipped with multispectral sensors may provide opportunities to improve N management by the timely informing of spatially variable, in-season N applications. Here, we developed a practical decision support system (DSS) to translate spatial field characteristics and normalized difference red edge (NDRE) values into an in-season N application recommendation. On-farm strip-trials were established at three sites over two years to compare farmer’s traditional N management to a split-application N management guided by our UAV sensor-based DSS. The proposed systems increased nitrogen use efficiency 18.3 ± 6.1 kg grain kg N−1 by reducing N rates by 31 ± 6.3 kg N ha−1 with no yield differences compared to the farmers’ traditional management. We identify five avenues for further improvement of the proposed DSS: definition of the initial base N rate, estimation of inputs for sensor algorithms, management zone delineation, high-resolution image normalization approach, and the threshold for triggering N application. Two virtual reference (VR) methods were compared with the high N (HN) reference strip method for normalizing high-resolution sensor data. The VR methods resulted in significantly lower sufficiency index values than those generated by the HN reference, resulting in N fertilization recommendations that were 31.4 ± 10.3 kg ha−1 higher than the HN reference N fertilization recommendation. The use of small HN reference blocks in contrasting management zones may be more appropriate to translate field-scale, high-resolution imagery into in-season N recommendations. In view of a growing interest in using UAVs in commercial fields and the need to improve crop NUE, further work is needed to refine approaches for translating imagery into in-season N recommendations.
Improving Low Earth Orbit (LEO) Prediction with Accelerometer Data
Authors: Ge Haibo , Li Bofeng , Ge Maorong , Nie Liangwei , Schuh Harald
Published: May 2020

Low Earth Orbit (LEO) satellites have been widely used in scientific fields or commercial applications in recent decades. The demands of the real time scientific research or real time applications require real time precise LEO orbits. Usually, the predicted orbit is one of the solutions for real time users, so it is of great importance to investigate LEO orbit prediction for users who need real time LEO orbits. The centimeter level precision orbit is needed for high precision applications. Aiming at obtaining the predicted LEO orbit with centimeter precision, this article demonstrates the traditional method to conduct orbit prediction and put forward an idea of LEO orbit prediction by using onboard accelerometer data for real time applications. The procedure of LEO orbit prediction is proposed after comparing three different estimation strategies of retrieving initial conditions and dynamic parameters. Three strategies are estimating empirical coefficients every one cycle per revolution, which is the traditional method, estimating calibration parameters of one bias of accelerometer hourly for each direction by using accelerometer data, and estimating calibration parameters of one bias and one scale factor of the accelerometer for each direction with one arc by using accelerometer data. The results show that the predicted LEO orbit precision by using the traditional method can reach 10 cm when the predicted time is shorter than 20 min, while the predicted LEO orbit with better than 5 cm for each orbit direction can be achieved with accelerometer data even to predict one hour.
Estimation of Noise in the In Situ Hyperspectral Data Acquired by Chang’E-4 and Its Effects on Spectral Analysis of Regolith
Authors: Lin Honglei , Lin Yangting , Wei Yong , Xu Rui , Liu Yang , Yang Yazhou , Hu Sen , Yang Wei , He Zhiping
Published: May 2020

The Chang’E-4 (CE-4) spacecraft landed successfully on the far side of the Moon on 3 January 2019, and the rover Yutu-2 has explored the lunar surface since then. The visible and near-infrared imaging spectrometer (VNIS) onboard the rover has acquired numerous spectra, providing unprecedented insight into the composition of the lunar surface. However, the noise in these spectral data and its effects on spectral interpretation are not yet assessed. Here we analyzed repeated measurements over the same area at the lunar surface to estimate the signal–noise ratio (SNR) of the VNIS spectra. Using the results, we assessed the effects of noise on the estimation of band centers, band depths, FeO content, optical maturity (OMAT), mineral abundances, and submicroscopic metallic iron (SMFe). The data observed at solar altitudes <20° exhibit low SNR (25 dB), whereas the data acquired at 20°–35° exhibit higher SNR (35–37 dB). We found differences in band centers due to noise to be ~6.2 and up to 28.6 nm for 1 and 2 μm absorption, respectively. We also found that mineral abundances derived using the Hapke model are affected by noise, with maximum standard deviations of 6.3%, 2.4%, and 7.0% for plagioclase, pyroxene, and olivine, respectively. Our results suggest that noise has significant impacts on the CE-4 spectra, which should be considered in the spectral analysis and geologic interpretation of lunar exploration data.
3D Registration and Integrated Segmentation Framework for Heterogeneous Unmanned Robotic Systems
Authors: Balta Haris , Velagic Jasmin , Beglerovic Halil , De Cubber Geert , Siciliano Bruno
Published: May 2020

The paper proposes a novel framework for registering and segmenting 3D point clouds of large-scale natural terrain and complex environments coming from a multisensor heterogeneous robotics system, consisting of unmanned aerial and ground vehicles. This framework involves data acquisition and pre-processing, 3D heterogeneous registration and integrated multi-sensor based segmentation modules. The first module provides robust and accurate homogeneous registrations of 3D environmental models based on sensors’ measurements acquired from the ground (UGV) and aerial (UAV) robots. For 3D UGV registration, we proposed a novel local minima escape ICP (LME-ICP) method, which is based on the well known iterative closest point (ICP) algorithm extending it by the introduction of our local minima estimation and local minima escape mechanisms. It did not require any prior known pose estimation information acquired from sensing systems like odometry, global positioning system (GPS), or inertial measurement units (IMU). The 3D UAV registration has been performed using the Structure from Motion (SfM) approach. In order to improve and speed up the process of outliers removal for large-scale outdoor environments, we introduced the Fast Cluster Statistical Outlier Removal (FCSOR) method. This method was used to filter out the noise and to downsample the input data, which will spare computational and memory resources for further processing steps. Then, we co-registered a point cloud acquired from a laser ranger (UGV) and a point cloud generated from images (UAV) generated by the SfM method. The 3D heterogeneous module consists of a semi-automated 3D scan registration system, developed with the aim to overcome the shortcomings of the existing fully automated 3D registration approaches. This semi-automated registration system is based on the novel Scale Invariant Registration Method (SIRM). The SIRM provides the initial scaling between two heterogenous point clouds and provides an adaptive mechanism for tuning the mean scale, based on the difference between two consecutive estimated point clouds’ alignment error values. Once aligned, the resulting homogeneous ground-aerial point cloud is further processed by a segmentation module. For this purpose, we have proposed a system for integrated multi-sensor based segmentation of 3D point clouds. This system followed a two steps sequence: ground-object segmentation and color-based region-growing segmentation. The experimental validation of the proposed 3D heterogeneous registration and integrated segmentation framework was performed on large-scale datasets representing unstructured outdoor environments, demonstrating the potential and benefits of the proposed semi-automated 3D registration system in real-world environments.