bluuebunny/crossref_metadata_2025 huggingface dataset:
Ocular Barriers and Their Influence on Gene Therapy Products Delivery
Authors: Leclercq Bastien , Mejlachowicz Dan , Behar-Cohen Francine
Published: May 2022

The eye is formed by tissues and cavities that contain liquids whose compositions are highly regulated to ensure their optical properties and their immune and metabolic functions. The integrity of the ocular barriers, composed of different elements that work in a coordinated fashion, is essential to maintain the ocular homeostasis. Specialized junctions between the cells of different tissues have specific features which guarantee sealing properties and selectively control the passage of drugs from the circulation or the outside into the tissues and within the different ocular compartments. Tissues structure also constitute selective obstacles and pathways for various molecules. Specific transporters control the passage of water, ions, and macromolecules, whilst efflux pumps reject and eliminate toxins, metabolites, or drugs. Ocular barriers, thus, limit the bioavailability of gene therapy products in ocular tissues and cells depending on the route chosen for their administration. On the other hand, ocular barriers allow a real local treatment, with limited systemic side-effects. Understanding the different barriers that limit the accessibility of different types of gene therapy products to the different target cells is a prerequisite for the development of efficient gene delivery systems. This review summarizes actual knowledge on the different ocular barriers that limit the penetration and distribution of gene therapy products using different routes of administration, and it provides a general overview of various methods used to bypass the ocular barriers.
D-Alpha-Tocopheryl Poly(ethylene Glycol 1000) Succinate-Coated Manganese-Zinc Ferrite Nanomaterials for a Dual-Mode Magnetic Resonance Imaging Contrast Agent and Hyperthermia Treatments
Authors: Wang Lin , Lai Syu-Ming , Li Cun-Zhao , Yu Hsiu-Ping , Venkatesan Parthiban , Lai Ping-Shan
Published: May 2022

Manganese-zinc ferrite (MZF) is known as high-performance magnetic material and has been used in many fields and development. In the biomedical applications, the biocompatible MZF formulation attracted much attention. In this study, water-soluble amphiphilic vitamin E (TPGS, d-alpha-tocopheryl poly(ethylene glycol 1000) succinate) formulated MZF nanoparticles were synthesized to serve as both a magnetic resonance imaging (MRI) contrast agent and a vehicle for creating magnetically induced hyperthermia against cancer. The MZF nanoparticles were synthesized from a metallic acetylacetonate in an organic phase and further modified with TPGS using an emulsion and solvent-evaporation method. The resulting TPGS-modified MZF nanoparticles exhibited a dual-contrast ability, with a longitudinal relaxivity (35.22 s−1 mM Fe−1) and transverse relaxivity (237.94 s−1 mM Fe−1) that were both higher than Resovist®. Furthermore, the TPGS-assisted MZF formulation can be used for hyperthermia treatment to successfully suppress cell viability and tumor growth after applying an alternating current (AC) electromagnetic field at lower amplitude. Thus, the TPGS-assisted MZF theranostics can not only be applied as a potential contrast agent for MRI but also has potential for use in hyperthermia treatments.
A Comprehensive Overview of Globally Approved JAK Inhibitors
Authors: Shawky Ahmed M. , Almalki Faisal A. , Abdalla Ashraf N. , Abdelazeem Ahmed H. , Gouda Ahmed M.
Published: May 2022

Janus kinase (JAK) is a family of cytoplasmic non-receptor tyrosine kinases that includes four members, namely JAK1, JAK2, JAK3, and TYK2. The JAKs transduce cytokine signaling through the JAK-STAT pathway, which regulates the transcription of several genes involved in inflammatory, immune, and cancer conditions. Targeting the JAK family kinases with small-molecule inhibitors has proved to be effective in the treatment of different types of diseases. In the current review, eleven of the JAK inhibitors that received approval for clinical use have been discussed. These drugs are abrocitinib, baricitinib, delgocitinib, fedratinib, filgotinib, oclacitinib, pacritinib, peficitinib, ruxolitinib, tofacitinib, and upadacitinib. The aim of the current review was to provide an integrated overview of the chemical and pharmacological data of the globally approved JAK inhibitors. The synthetic routes of the eleven drugs were described. In addition, their inhibitory activities against different kinases and their pharmacological uses have also been explained. Moreover, their crystal structures with different kinases were summarized, with a primary focus on their binding modes and interactions. The proposed metabolic pathways and metabolites of these drugs were also illustrated. To sum up, the data in the current review could help in the design of new JAK inhibitors with potential therapeutic benefits in inflammatory and autoimmune diseases.
New Autonomous Water-Enabled Self-Healing Coating Material with Antibacterial-Agent-Releasing Properties
Authors: Kim Ki-Hak , Mai Hang-Nga , Hyun Dong-Choon , Lee Du-Hyeong
Published: May 2022

A new autonomous water-enabled self-healing coating with antibacterial-agent-releasing capability was developed for the first time by precipitating an aqueous solution of hydrogen-bonded tannic acid (TA) and polyethylene glycol (PEG) (TA: 5 mg/mL; PEG: 5 mg/mL with MW = 100 kDa) to form a smooth, uniform coating layer with an average roughness of 0.688 nm and thickness of 22.3 μm on a polymethyl methacrylate (PMMA) substrate after 10 min of incubation. Our method is cost- and time-efficient, as the hydrophilic coating (water contact angle = 65.1°) forms rapidly, binding strongly to the PMMA substrate (adhesive energy = 83 mJ/m2), without the need for pretreatment or surface modification, and is capable of rapid self-repair (approximately 5 min) through hydrogen bonding in aqueous media. Furthermore, adding 0.5 mg/mL of chlorhexidine acetate (CHX), a commonly used antibacterial agent in dentistry, into the TA–PEG emulsion allowed the release of 2.89 μg/mL of the drug from the coating layer, which is promising for actively inhibiting the vitality and growth of bacteria around PMMA dental restorations. The use of CHX-loaded TA–PEG hydrogen-bonded complexes is highly favorable for the fabrication of an autonomous self-healing biocoating with active antibacterial-agent-releasing capability, which can be applied not only in dentistry but also in other medical fields.
Developing Clinically Relevant Dissolution Specifications (CRDSs) for Oral Drug Products: Virtual Webinar Series
Authors: McAllister Mark , Flanagan Talia , Cole Susan , Abend Andreas , Kotzagiorgis Evangelos , Limberg Jobst , Mead Heather , Mangas-Sanjuan Victor , Dickinson Paul A. , Moir Andrea , Pepin Xavier , Zhou Diansong , Tistaert Christophe , Dokoumetzidis Aristides , Anand Om , Le Merdy Maxime , Turner David B. , Griffin Brendan T. , Darwich Adam , Dressman Jennifer , Mackie Claire
Published: May 2022

A webinar series that was organised by the Academy of Pharmaceutical Sciences Biopharmaceutics focus group in 2021 focused on the challenges of developing clinically relevant dissolution specifications (CRDSs) for oral drug products. Industrial scientists, together with regulatory and academic scientists, came together through a series of six webinars, to discuss progress in the field, emerging trends, and areas for continued collaboration and harmonisation. Each webinar also hosted a Q&A session where participants could discuss the shared topic and information. Although it was clear from the presentations and Q&A sessions that we continue to make progress in the field of CRDSs and the utility/success of PBBM, there is also a need to continue the momentum and dialogue between the industry and regulators. Five key areas were identified which require further discussion and harmonisation.
Photothermal Therapy with HER2-Targeted Silver Nanoparticles Leading to Cancer Remission
Authors: Shipunova Victoria O. , Belova Mariia M. , Kotelnikova Polina A. , Shilova Olga N. , Mirkasymov Aziz B. , Danilova Natalia V. , Komedchikova Elena N. , Popovtzer Rachela , Deyev Sergey M. , Nikitin Maxim P.
Published: May 2022

Nanoparticles exhibiting the localized surface plasmon resonance (LSPR) phenomenon are promising tools for diagnostics and cancer treatment. Among widely used metal nanoparticles, silver nanoparticles (Ag NPs) possess the strongest light scattering and surface plasmon strength. However, the therapeutic potential of Ag NPs has until now been underestimated. Here we show targeted photothermal therapy of solid tumors with 35 nm HER2-targeted Ag NPs, which were produced by the green synthesis using an aqueous extract of Lavandula angustifolia Mill. Light irradiation tests demonstrated effective hyperthermic properties of these NPs, namely heating by 10 °C in 10 min. To mediate targeted cancer therapy, Ag NPs were conjugated to the scaffold polypeptide, affibody ZHER2:342, which recognizes a clinically relevant oncomarker HER2. The conjugation was mediated by the PEG linker to obtain Ag-PEG-HER2 nanoparticles. Flow cytometry tests showed that Ag-PEG-HER2 particles successfully bind to HER2-overexpressing cells with a specificity comparable to that of full-size anti-HER2 IgGs. A confocal microscopy study showed efficient internalization of Ag-PEG-HER2 into cells in less than 2 h of incubation. Cytotoxicity assays demonstrated effective cell death upon exposure to Ag-PEG-HER2 and irradiation, caused by the production of reactive oxygen species. Xenograft tumor therapy with Ag-PEG-HER2 particles in vivo resulted in full primary tumor regression and the prevention of metastatic spread. Thus, for the first time, we have shown that HER2-directed plasmonic Ag nanoparticles are effective sensitizers for targeted photothermal oncotherapy.
Intranasal Immunization with Zika Virus Envelope Domain III-Flagellin Fusion Protein Elicits Systemic and Mucosal Immune Responses and Protection against Subcutaneous and Intravaginal Virus Challenges
Authors: Chen Chi-Hsun , Chen Chung-Chu , Wang Wei-Bo , Lionel Vania , Liu Chia-Chyi , Huang Li-Min , Wu Suh-Chin
Published: May 2022

Zika virus (ZIKV) infections in humans are mainly transmitted by the mosquito vectors, but human-to-human sexual transmission is also another important route. Developing a ZIKV mucosal vaccine that can elicit both systemic and mucosal immune responses is of particular interest. In this study, we constructed a recombinant ZIKV envelope DIII (ZDIII) protein genetically fused with Salmonella typhimurium flagellin (FliC-ZDIII) as a novel mucosal antigen for intranasal immunization. The results indicated that the FliC-ZDIII fusion proteins formulated with E. coli heat-labile enterotoxin B subunit (LTIIb-B5) adjuvant greatly increased the ZDIII-specific IgG, IgA, and neutralizing titers in sera, and the ZDIII-specific IgA titers in bronchoalveolar lavage and vaginal fluids. Protective immunity was further assessed by subcutaneous and intravaginal ZIKV challenges. The second-generation FliCΔD3-2ZDIII was shown to result in a reduced titer of anti-FliC IgG antibodies in sera and still retained the same levels of serum IgG, IgA, and neutralizing antibodies and mucosal IgA antibodies without compromising the vaccine antigenicity. Therefore, intranasal immunization with FliCΔD3-2ZDIII fusion proteins formulated with LTIIb-B5 adjuvant elicited the greatest protective immunity against subcutaneous and intravaginal ZIKV challenges. Our findings indicated that the combination of FliCΔD3-2ZDIII fusion proteins and LTIIb-B5 adjuvant for intranasal immunization can be used for developing ZIKV mucosal vaccines.
Interconnection of Few-Mode Fibers and Photonic Integrated Circuits Using Mode-Field Adapters
Authors: González-Cortez Oscar , Velázquez-Benítez Amado M.
Published: May 2022

We propose a detailed method for the interconnection between optical fibers and waveguides of photonic integrated circuits. Appropriate modal transmission is accomplished by matching the mode field diameters from both waveguide structures. Links from one structure to another are created by an interconnecting waveguide, maintaining a fixed coupling efficiency as its size is modified to adjust to the target waveguide core. This tailored transition acts as a mode field adapter, equalizing the transmission among multiple modes and reducing the mode-dependent losses while coupling. We present an algorithm to design the mode field adapter based on matching the effective mode areas using the power overlap integral. A study case considering a polymer photonic integrated device immediately connected to a few-mode fiber is analyzed. Coupling efficiencies over 90% for every transmitted mode are achieved, showing an evident improvement compared to typical approaches only matching core sizes. Detailed comparison of the results for each transmission mode is presented. This same procedure can be used to interconnect optical waveguides with different refractive index profiles and core geometry.
UV-LED Curable Acrylic Films Containing Phosphate Glass Powder: Effect of the Filler Loading on the Thermal, Optical, Mechanical and Flame Retardant Properties
Authors: Pugliese Diego , Malucelli Giulio
Published: May 2022

In this work, we thoroughly investigate the effects of the incorporation of a phosphate glass micrometric powder on the morphology, as well as on the thermal, optical, mechanical and flame retardant properties of UV-LED curable acrylic films. To this aim, the filler loading was changed within 10 and 50 wt.%. UV-LED initiated curing was selected as a fast and reliable system, as the standard UV-curing process was not suitable because of the presence of the glass powder that decreased the quantum efficiency during the UV exposure, hence preventing the transformation of the liquid system into a solid network. The glass powder slightly increased the glass transition temperature of the acrylic network, hence showing a limited effect on the chain segments mobility; besides, increasing filler loadings were responsible for a progressive decrease of the transparency of films, irrespective of a marginal effect on their refractive index. Conversely, the presence of increasing amounts of phosphate glass improved the thermal and thermo-oxidative stability of the cured products. Besides, phosphate glass was capable of remarkably enhancing the flame retardance of the acrylic network at 50 wt.% loading, which achieved self-extinction in vertical flame spread tests (and was V-0 rated). This formulation, as assessed by forced-combustion tests, also displayed a remarkable decrease of peak of Heat Release Rate and Total Heat Release (by 44 and 33%, respectively) and of Total Smoke Release and Specific Extinction Area (by 53 and 56%, respectively). Further, the filler promoted an increase of the stiffness and surface hardness of the films, at the expense of a decrease in ductility. All these findings may justify the potential use of these composite films as flame retardant coatings for different flammable substrates.
Metal Nanoparticles–Polymers Hybrid Materials II
Authors: Venditti Iole
Published: May 2022

Despite the pandemic, the last five years have been marked by an extraordinary development of new advanced technologies, based not only on new materials but also on modeling, information technology and artificial intelligence, which have allowed for great leaps forward in various research fields [...]
Multi-Functional 3D-Printed Vat Photopolymerization Biomedical-Grade Resin Reinforced with Binary Nano Inclusions: The Effect of Cellulose Nanofibers and Antimicrobial Nanoparticle Agents
Authors: Vidakis Nectarios , Petousis Markos , Michailidis Nikolaos , Papadakis Vassilis , Korlos Apostolos , Mountakis Nikolaos , Argyros Apostolos
Published: May 2022

This study introduced binary nanoparticle (NP) inclusions into a biomedical-grade photosensitive resin (Biomed Clear-BC). Multi-functional, three-dimensional (3D) printed objects were manufactured via the vat photopolymerization additive manufacturing (AM) technique. Cellulose nanofibers (CNFs) as one dimensional (1D) nanomaterial have been utilized for the mechanical reinforcement of the resin, while three different spherical NPs, namely copper NPs (nCu), copper oxide NPs (nCuO), and a commercial antimicrobial powder (nAP), endowed the antimicrobial character. The nanoparticle loading was kept constant at 1.0 wt.% to elucidate any synergistic effects as a function of the filler loading. Raman, thermogravimetric analysis (TGA), and differential scanning calorimetry (DSC) revealed the chemical/spectroscopic and thermal properties of the different manufactured samples. Scanning electron microscopy and Atomic Force Microscopy (AFM) revealed the morphology of the samples. Mechanical properties revealed the reinforcement mechanisms, namely that BC/CNF (1.0 wt.%) exhibited a 102% and 154% enhancement in strength and modulus, respectively, while BC/CNF(1.0 wt.%)/AP(1.0 wt.%) exhibited a 95% and 101% enhancement, as well as an antibacterial property, which was studied using a screening agar well diffusion method. This study opens the route towards novel, multi-functional materials for vat photopolymerization 3D printing biomedical applications, where mechanical reinforcement and antibacterial performance are typically required in the operational environment.
Simultaneous Effects of Carboxyl Group-Containing Hyperbranched Polymers on Glass Fiber-Reinforced Polyamide 6/Hollow Glass Microsphere Syntactic Foams
Authors: Kim Jincheol , Lee Jaewon , Hwang Sosan , Park Kyungjun , Hong Sanghyun , Lee Seojin , Shim Sang Eun , Qian Yingjie
Published: May 2022

The hollow glass microsphere (HGM) containing polymer materials, which are named as syntactic foams, have been applied as lightweight materials in various fields. In this study, carboxyl group-containing hyperbranched polymer (HBP) was added to a glass fiber (GF)-reinforced syntactic foam (RSF) composite for the simultaneous enhancement of mechanical and rheological properties. HBP was mixed in various concentrations (0.5–2.0 phr) with RSF, which contains 23 wt% of HGM and 5 wt% of GF, and the rheological, thermal, and mechanical properties were characterized systematically. As a result of the lubricating effect of the HBP molecule, which comes from its dendritic architecture, the viscosity, storage modulus, loss modulus, and the shear stress of the composite decreased as the HBP content increased. At the same time, because of the hydrogen bonding among the polymer, filler, and HBP, the compatibility between filler and the polymer matrix was enhanced. As a result, by adding a small amount (0.5–2.0 phr) of HBP to the RSF composite, the tensile strength and flexural modulus were increased by 24.3 and 9.7%, respectively, and the specific gravity of the composite was decreased from 0.948 to 0.917. With these simultaneous effects on the polymer composite, HBP could be potentially utilized further in the field of lightweight materials.
Comparative Study on Macro-Tribological Properties of PLL-g-PEG and PSPMA Polymer Brushes
Authors: Ren Fue , Yang Shuyan , Wu Yang , Guo Feng , Zhou Feng
Published: May 2022

An ultra-low friction and high load capacity could be obtained on the surfaces grafted by a polymer brush even at relatively slow friction speeds in aqueous lubrication environments, which has attracted widespread attention to study the lubrication mechanism of polymer brushes; however, it has yet to be fully understood. The macroscopic tribological performance of two different polymer brushes, which were prepared by the method of “grafting to” and “grafting from” and named as PLL-g-PEG and PSPMA, respectively, were investigated. The friction results demonstrated that PLL-g-PEG obtained a lower friction coefficient than polymer brush PSPMA, which was ascribed to its unique “self-healing” behavior. The lubrication film was in situ observed and the film thickness induced by the polymer brush was measured using a laboratory set for film thickness measurement apparatus based on interference technology. It was found that PSPMA exhibited excellent lubrication performance not found in PLL-g-PEG, and two film-forming mechanisms highly dependent on velocity were revealed, which may be important to interpret the lubrication mechanism of polymer brushes in aqueous lubricants.
Continuous-Flow Magnetic Fractionation of Red Blood Cells Based on Hemoglobin Content and Oxygen Saturation—Clinical Blood Supply Implications and Sickle Cell Anemia Treatment
Authors: Weigand Mitchell , Gomez-Pastora Jenifer , Palmer Andre , Zborowski Maciej , Desai Payal , Chalmers Jeffrey
Published: May 2022

Approximately 36,000 units of red blood cells (RBCs) are used every day in the U.S. and there is a great challenge for hospitals to maintain a reliable supply, given the 42-day expiration period from the blood donation date. For many years, research has been conducted to develop ex vivo storage solutions that limit RBC lysis and maintain a high survival rate of the transfused cells. However, little attention is directed towards potential fractionation methods to remove unwanted cell debris or aged blood cells from stored RBC units prior to transfusion, which could not only expand the ex vivo shelf life of RBC units but also avoid adverse events in transfused patients. Such fractionation methods could also limit the number of transfusions required for treating certain pathologies, such as sickle cell disease (SCD). In this work, magnetic fractionation is studied as a potential technology to fractionate functional and healthy RBCs from aged or sickle cells. It has been reported that during ex vivo RBC storage, RBCs lose hemoglobin (Hb) and lipid content via formation of Hb-containing exosomes. Given the magnetic character of deoxygenated- or met-Hb, in this work, we propose the use of a quadrupole magnetic sorter (QMS) to fractionate RBCs based on their Hb content from both healthy stored blood and SCD blood. In our QMS, a cylindrical microchannel placed inside the center of the quadrupolar magnets is subjected to high magnetic fields and constant field gradients (286 T/m), which causes the deflection of the paramagnetic, Hb-enriched, and functional RBCs from their original path and their collection into a different outlet. Our results demonstrated that although we could obtain a significant difference in the magnetic mobility of the sorted fractions (corresponding to a difference in more than 1 pg of Hb per cell), there exists a tradeoff between throughput and purity. Therefore, this technology when optimized could be used to expand the ex vivo shelf life of RBC units and avoid adverse events in transfused individuals or SCD patients requiring blood exchange therapy.
Development of an Empathy-Centric Counseling Chatbot System Capable of Sentimental Dialogue Analysis
Authors: Trappey Amy J. C. , Lin Aislyn P. C. , Hsu Kevin Y. K. , Trappey Charles V. , Tu Kevin L. K.
Published: May 2022

College students encounter various types of stresses in school due to schoolwork, personal relationships, health issues, and future career concerns. Some students are susceptible to the strikes of failures and are inexperienced with or fearful of dealing with setbacks. When these negative emotions gradually accumulate without resolution, they can cause long-term negative effects on students’ physical and mental health. Some potential health problems include depression, anxiety, and disorders such as eating disorders. Universities commonly offer counseling services; however, the demand often exceeds the counseling capacities due to limited numbers of counsellors/psychologists. Thus, students may not receive immediate counseling or treatments. If students are not treated, some repercussions may lead to severe abnormal behavior and even suicide. In this study, combining immersive virtual reality (VR) technique with psychological knowledge base, we developed a VR empathy-centric counseling chatbot (VRECC) that can complementarily support troubled students when counsellors cannot provide immediate support. Through multi-turn (verbal or text) conversations with the chatbot, the system can demonstrate empathy and give therapist-like responses to the users. During the study, more than 120 students were required to complete a questionnaire and 34 subjects with an above-median stress level were randomly drawn for the VRECC experiment. We observed decreasing average stress level and psychological sensitivity scores among subjects after the experiment. Although the system did not yield improvement in life-impact scores (e.g., behavioral and physical impacts), the significant outcomes of lowering stress level and psychological sensitivity have given us a very positive outlook for continuing to integrate VR, AI sentimental natural language process, and counseling chatbot for advanced VRECC research in helping students improve their psychological well-being and life quality at schools.
Multi-Classifier Fusion for Open-Set Specific Emitter Identification
Authors: Zhao Yurui , Wang Xiang , Lin Ziyu , Huang Zhitao
Published: May 2022

To safeguard the privacy and security of IoT systems, specific emitter identification is utilized to recognize device identity with hardware characteristics. In view of the growing demand for identifying unknown devices, this paper aims to discuss open-set specific emitter identification. We firstly build up a problem formulation for open-set SEI by discussing the working mechanisms of radio signals and open-set recognition. And then it is pointed out that feature coincidence is an intractable challenge in open-set SEI. The reason, accounting for this phenome, is that pretrained fingerprint feature extractors are incapable of clustering unknown device features and differentiating them from known ones. Considering that feature coincidence leads to error recognition of unknown devices, we propose to fuse multi-classifiers in the decision layer to improve accuracy and recall. Three distinct inputs and four different fusion methods are adopted in this paper to implement multi-classifier fusion. The datasets collected at Huanghua Airport demonstrate that the proposed method can avoid the coincidence of feature space and achieve higher accuracy and recall.
Monitoring the Surface Elevation Changes of a Monsoon Temperate Glacier with Repeated UAV Surveys, Mainri Mountains, China
Authors: Wu Kunpeng , Liu Shiyin , Zhu Yu , Xie Fuming , Gao Yongpeng , Qi Miaomiao , Miao Wenfei , Duan Shimei , Han Fengze , Grünwald Richard
Published: May 2022

Due to the deep valleys, steep mountains and the influence of the Indian monsoon on the Mainri Mountains (Yunnan Province, China), it is difficult to estimate glacier change from microwave and optical remote sensing. To bridge the gap between low-quality space-borne remote sensing and scarce in situ measurements, airborne remote sensing, such as unmanned aerial vehicles (UAVs), may provide a remarkable opportunity to monitor glacier change with high-quality tools. To determine monsoon temperate glacier change, three UAV surveys were conducted on the Melang Glacier in the Mainri Mountains in November 2019, April 2020 and November 2020. Then, glacier surface elevation changes were estimated from UAV orthophotos and DSMs. High accumulation and high ablation (+10.5 m and −13.5 m) were observed in the accumulation period and ablation period, with a mean surface elevation change of −3.0 m in the surveyed glacier area from November 2019 to November 2020. The avalanche, debris cover, ice cliffs and proglacial lake resulted in a heterogeneous pattern of glacier surface elevation changes. Given that the glacier is more sensitive to temperature, the Melang Glacier may have experienced a substantial recession and mass loss in the past few decades. This study provides a more appropriate approach for monitoring the changes in a temperate glacier in the Mainri Mountains.
Low Observable Radar Target Detection Method within Sea Clutter Based on Correlation Estimation
Authors: Luo Zefeng , Li Zhengzhou , Zhang Chao , Deng Jiaqi , Qin Tianqi
Published: May 2022

The long-time coherent integration can effectively improve the detection ability of radar targets. However, this strategy usually shows poor effect in resisting the sea clutter, which produces difficulties for accurate estimation of sea clutter characteristics and results in the inability to differentiate between the target and sea clutter. To solve this problem, a two-stage method is proposed, which consists of the sea clutter suppression stage and target decision stage. In the sea clutter suppression stage, the correlation time differences in the time and the space domains are adopted to estimate the correlation of sea clutter. Then, a selective whitening filter is proposed, which is performed more adaptively according to the estimation results. In the decision stage, the peak average ratio in the fractional Fourier domain (FRFT-PAR) is presented, which can make better use of the energy accumulation characteristics and further suppress the interference of sea clutter. Experiments on the IPIX datasets with various observation times and polarization modes are included. The results indicate that the proposed method could not only effectively suppress sea clutter but also achieve better target detection performance than baseline algorithms.
A Landslide Numerical Factor Derived from CHIRPS for Shallow Rainfall Triggered Landslides in Colombia
Authors: Cullen Cheila Avalon , Al Suhili Rafea , Aristizabal Edier
Published: May 2022

Despite great advances in remote sensing technologies, accurate satellite information is sometimes challenged in tropical regions where dense vegetation prevents the instruments from retrieving reliable readings. In this work, we introduce a satellite-based landslide rainfall threshold for the country of Colombia by studying 4 years of rainfall measurements from The Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) for 346 rainfall-triggered landslide events (the dataset). We isolate the two successive rainy/dry periods leading to each landslide to create variables that simulate the dynamics of antecedent wetness and dryness. We test the performance of the derived variables (Rainfall Period 1 (PR1), Rainfall Sum 1 (RS1), Rainfall Period 2 (PR2), Rainfall Sum 2 (RS2), and Dry Period (DT)) in a logistic regression that includes three (3) static parameters (Soil Type (ST), Landcover (LC), and Slope angle). Results from the logistic model describe the influence of each variable in landslide occurrence with an accuracy of 73%. Subsequently, we use these dynamic variables to model a landslide threshold that, in the absence of satellite antecedent soil moisture data, helps describe the interactions between the dynamic variables and the slope angle. We name it the Landslide Triggering Factor—LTF. Subsequently, with a training dataset (65%) and one for testing (35%) we evaluate the LTF threshold performance and compare it to the well-known event duration (E-D) threshold. Results demonstrate that The LTF performs better than the E-D threshold for the training and testing datasets at 71% and 81% respectively.
Subsidence Detection for Urban Roads Using Mobile Laser Scanner Data
Authors: Song Hongxia , Zhang Jixian , Zuo Jianzhang , Liang Xinlian , Han Wenli , Ge Juan
Published: May 2022

Pavement subsidence detection based on point cloud data acquired by mobile measurement systems is very challenging. First, the uncertainty and disorderly nature of object points data results in difficulties in point cloud comparison. Second, acquiring data with kinematic laser scanners introduces errors into systems during data acquisition, resulting in a reduction in data accuracy. Third, the high-precision measurement standard of pavement subsidence raises requirements for data processing. In this article, a data processing method is proposed to detect the subcentimeter-level subsidence of urban pavements using point cloud data comparisons in multiple time phases. The method mainly includes the following steps: First, the original data preprocessing is conducted, which includes point cloud matching and pavement point segmentation. Second, the interpolation of the pavement points into a regular grid is performed to solve the problem of point cloud comparison. Third, according to the high density of the pavement points and the performance of the pavement in the rough point cloud, using a Gaussian kernel convolution to smooth the pavement point cloud data, we aim to reduce the error in comparison. Finally, we determine the subsidence area by calculating the height difference and compare it with the threshold value. The experimental results show that the smoothing process can substantially improve the accuracy of the point cloud comparison results, effectively reducing the false detection rate and showing that subcentimeter-level pavement subsidence can be effectively detected.
Comparing the Use of Red-Edge and Near-Infrared Wavelength Ranges for Detecting Submerged Kelp Canopy
Authors: Timmer Brian , Reshitnyk Luba Y. , Hessing-Lewis Margot , Juanes Francis , Costa Maycira
Published: May 2022

Kelp forests are commonly classified within remote sensing imagery by contrasting the high reflectance in the near-infrared spectral region of kelp canopy floating at the surface with the low reflectance in the same spectral region of water. However, kelp canopy is often submerged below the surface of the water, making it important to understand the effects of kelp submersion on the above-water reflectance of kelp, and the depth to which kelp can be detected, in order to reduce uncertainties around the kelp canopy area when mapping kelp. Here, we characterized changes to the above-water spectra of Nereocystis luetkeana (Bull kelp) as different canopy structures (bulb and blades) were submerged in water from the surface to 100 cm in 10 cm increments, while collecting above-water hyperspectral measurements with a spectroradiometer (325–1075 nm). The hyperspectral data were simulated into the multispectral bandwidths of the WorldView-3 satellite and the Micasense RedEdge-MX unoccupied aerial vehicle sensors and vegetation indices were calculated to compare detection limits of kelp with a focus on differences between red edge and near infrared indices. For kelp on the surface, near-infrared reflectance was higher than red-edge reflectance. Once submerged, the kelp spectra showed two narrow reflectance peaks in the red-edge and near-infrared wavelength ranges, and the red-edge peak was consistently higher than the near-infrared peak. As a result, kelp was detected deeper with vegetation indices calculated with a red-edge band versus those calculated with a near infrared band. Our results show that using red-edge bands increased detection of submerged kelp canopy, which may be beneficial for estimating kelp surface-canopy area and biomass.
SAR Image Fusion Classification Based on the Decision-Level Combination of Multi-Band Information
Authors: Zhu Jinbiao , Pan Jie , Jiang Wen , Yue Xijuan , Yin Pengyu
Published: May 2022

Synthetic aperture radar (SAR) is an active coherent microwave remote sensing system. SAR systems working in different bands have different imaging results for the same area, resulting in different advantages and limitations for SAR image classification. Therefore, to synthesize the classification information of SAR images into different bands, an SAR image fusion classification method based on the decision-level combination of multi-band information is proposed in this paper. Within the proposed method, the idea of Dempster–Shafer evidence theory is introduced to model the uncertainty of the classification result of each pixel and used to combine the classification results of multiple band SAR images. The convolutional neural network is used to classify single-band SAR images. Calculate the belief entropy of each pixel to measure the uncertainty of single-band classification, and generate the basic probability assignment function. The idea of the term frequency-inverse document frequency in natural language processing is combined with the conflict coefficient to obtain the weight of different bands. Meanwhile, the neighborhood classification of each pixel in different band sensors is considered to obtain the total weight of each band sensor, generate weighted average BPA, and obtain the final ground object classification result after fusion. The validity of the proposed method is verified in two groups of multi-band SAR image classification experiments, and the proposed method has effectively improved the accuracy compared to the modified average approach.
Graph-Based Deep Multitask Few-Shot Learning for Hyperspectral Image Classification
Authors: Li Na , Zhou Deyun , Shi Jiao , Zheng Xiaolong , Wu Tao , Yang Zhen
Published: May 2022

Although the deep neural network (DNN) has shown a powerful ability in hyperspectral image (HSI) classification, its learning requires a large number of labeled training samples; otherwise, it is prone to over-fitting and has a poor classification performance. However, this requirement is impractical for HSIs due to the difficulty in obtaining class labels. To make DNNs suitable for HSI classification with few labeled samples, we propose a graph-based deep multitask few-shot learning (GDMFSL) framework that learns the intrinsic relationships among all samples (labeled and unlabeled) of HSIs with the assistance of graph information to alleviate the over-fitting caused by few labeled training samples. Firstly, a semi-supervised graph is constructed to generate graph information. Secondly, a deep multitask network (DMN) is designed, which contains two subnetworks (tasks): a classifier subnetwork for learning class information from labeled samples and a Siamese subnetwork for learning sample relationships from the semi-supervised graph. To effectively learn graph information, a loss function suitable for the Siamese subnetwork is designed that shortens (and expands) the distance between the target sample and its nearest (and farthest) neighbors. Finally, since the number of training samples of the two subnetworks is severely imbalanced, a multitask few-shot learning strategy is designed to make two subnetworks converge simultaneously. Experimental results on the Indian Pines, University of Pavia and Salinas datasets demonstrate that GDMFSL achieves a better classification performance relative to existing competitors in few-shot settings. In particular, when only five labels per class are involved in training, the classification accuracy of GDMFSL on the three datasets reaches 87.58%, 86.42% and 98.85%, respectively.
Relative Merits of Optimal Estimation and Non-Linear Retrievals of Sea-Surface Temperature from MODIS
Authors: Szczodrak Malgorzata D. , Minnett Peter J.
Published: May 2022

We compared the results of an Optimal Estimation (OE) based approach for the retrieval of the skin sea surface temperature (SSTskin) with those of the traditional non-linear sea surface temperature (NLSST) algorithm. The retrievals were from radiance measurements in two infrared channels of the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA satellite Aqua. The OE used a reduced state vector of SST and total column water vapor (TCWV). The SST and atmospheric profiles of temperature and humidity from ERA5 provided prior knowledge, and we made reasonable assumptions about the variance of these fields. An atmospheric radiative transfer model was used as the forward model to simulate the MODIS measurements. The performances of the retrieval approaches were assessed by comparison with in situ measurements. We found that the OESST reduces the satellite–in situ bias, but mostly for retrievals with an already small bias between in situ and the prior SST. The OE approach generally fails to improve the SST retrieval when that difference is large. In such cases, the NLSST often provides a better estimate of the SST than the OE. The OESST also underperforms NLSST in areas that include large horizontal SST gradients.
City3D: Large-Scale Building Reconstruction from Airborne LiDAR Point Clouds
Authors: Huang Jin , Stoter Jantien , Peters Ravi , Nan Liangliang
Published: May 2022

We present a fully automatic approach for reconstructing compact 3D building models from large-scale airborne point clouds. A major challenge of urban reconstruction from airborne LiDAR point clouds lies in that the vertical walls are typically missing. Based on the observation that urban buildings typically consist of planar roofs connected with vertical walls to the ground, we propose an approach to infer the vertical walls directly from the data. With the planar segments of both roofs and walls, we hypothesize the faces of the building surface, and the final model is obtained by using an extended hypothesis-and-selection-based polygonal surface reconstruction framework. Specifically, we introduce a new energy term to encourage roof preferences and two additional hard constraints into the optimization step to ensure correct topology and enhance detail recovery. Experiments on various large-scale airborne LiDAR point clouds have demonstrated that the method is superior to the state-of-the-art methods in terms of reconstruction accuracy and robustness. In addition, we have generated a new dataset with our method consisting of the point clouds and 3D models of 20k real-world buildings. We believe this dataset can stimulate research in urban reconstruction from airborne LiDAR point clouds and the use of 3D city models in urban applications.
Antarctic Firn Characterization via Wideband Microwave Radiometry
Authors: Kar Rahul , Aksoy Mustafa , Kaurejo Dua , Atrey Pranjal , Devadason Jerusha Ashlin
Published: May 2022

Recent studies have demonstrated that wideband microwave radiometers provide significant potential for profiling important subsurface polar firn characteristics necessary to understand the dynamics of the cryosphere and predict future changes in ice and snow coverage. Different frequencies within the wide spectra of radiometers result in different electromagnetic propagation losses and thus reveal characteristics at different depths in ice and snow. This paper, expanding on those investigations, explores the utilization of the Global Precipitation Measurement (GPM) constellation as a single wideband (6.93 GHz–91.655 GHz) spaceborne radiometer, covering the entire microwave spectrum from C-band to W-band, to profile subsurface properties of the Antarctic firn. Results of the initial analyses over Concordia and Vostok Stations in Antarctica indicate that GPM brightness temperature measurements provide critical information regarding the subsurface temperatures and physical properties of the firn from the surface down to several meters of depth. Considering the high spatiotemporal coverage of polar-orbiting spaceborne radiometers, these results are promising for future continent-level thermal and physical characterization of the Antarctic firn.
Effect of the Shadow Pixels on Evapotranspiration Inversion of Vineyard: A High-Resolution UAV-Based and Ground-Based Remote Sensing Measurements
Authors: Lu Saihong , Xuan Junjie , Zhang Tong , Bai Xueer , Tian Fei , Ortega-Farias Samuel
Published: May 2022

Due to the proliferation of precision agriculture, the obstacle of estimating evapotranspiration (ET) and its components from shadow pixels acquired from remote sensing technology should not be neglected. To accurately detect shaded soil and leaf pixels and quantify the implications of shadow pixels on ET inversion, a two-year field-scale observation was carried out in the growing season for a pinot noir vineyard. Based on high-resolution remote sensing sensors covering visible light, thermal infrared, and multispectral light, the supervised classification was applied to detect shadow pixels. Then, we innovatively combined the normalized difference vegetation index with the three-temperature model to quantify the proportion of plant transpiration (T) and soil evaporation (E) in the vineyard ecosystem. Finally, evaluated with the eddy covariance system, we clarified the implications of the shadow pixels on the ET estimation and the spatiotemporal patterns of ET in a vineyard system by considering where shadow pixels were presented. Results indicated that the shadow detection process significantly improved reliable assessment of ET and its components. (1) The shaded soil pixels misled the land cover classification, with the mean canopy cover ignoring shadows 1.68–1.70 times more often than that of shaded area removal; the estimation accuracy of ET can be improved by 4.59–6.82% after considering the effect of shaded soil pixels; and the accuracy can be improved by 0.28–0.89% after multispectral correction. (2) There was a 2 °C canopy temperature discrepancy between sunlit leaves and shaded leaves, meaning that the estimation accuracy of T can be improved by 1.38–7.16% after considering the effect of shaded canopy pixels. (3) Simultaneously, the characteristics showed that there was heterogeneity of ET in the vineyard spatially and that E and T fluxes accounted for 238.05 and 208.79 W·m−2, respectively; the diurnal variation represented a single-peak curve, with a mean of 0.26 mm/h. Our findings provide a better understanding of the influences of shadow pixels on ET estimation using remote sensing techniques.
Remote Sensing Mapping of Build-Up Land with Noisy Label via Fault-Tolerant Learning
Authors: Xu Gang , Fang Yongjun , Deng Min , Sun Geng , Chen Jie
Published: May 2022

China’s urbanization has dramatically accelerated in recent decades. Land for urban build-up has changed not only in large cities but also in small counties. Land cover mapping is one of the fundamental tasks in the field of remote sensing and has received great attention. However, most current mapping requires a significant manual effort for labeling or classification. It is of great practical value to use the existing low-resolution label data for the classification of higher resolution images. In this regard, this work proposes a method based on noise-label learning for fine-grained mapping of urban build-up land in a county in central China. Specifically, this work produces a build-up land map with a resolution of 10 m based on a land cover map with a resolution of 30 m. Experimental results show that the accuracy of the results is improved by 5.5% compared with that of the baseline method. This notion indicates that the time required to produce a fine land cover map can be significantly reduced using existing coarse-grained data.
Hyperspectral Image Classification via Deep Structure Dictionary Learning
Authors: Wang Wenzheng , Han Yuqi , Deng Chenwei , Li Zhen
Published: May 2022

The construction of diverse dictionaries for sparse representation of hyperspectral image (HSI) classification has been a hot topic over the past few years. However, compared with convolutional neural network (CNN) models, dictionary-based models cannot extract deeper spectral information, which will reduce their performance for HSI classification. Moreover, dictionary-based methods have low discriminative capability, which leads to less accurate classification. To solve the above problems, we propose a deep learning-based structure dictionary for HSI classification in this paper. The core ideas are threefold, as follows: (1) To extract the abundant spectral information, we incorporate deep residual neural networks in dictionary learning and represent input signals in the deep feature domain. (2) To enhance the discriminative ability of the proposed model, we optimize the structure of the dictionary and design sharing constraint in terms of sub-dictionaries. Thus, the general and specific feature of HSI samples can be learned separately. (3) To further enhance classification performance, we design two kinds of loss functions, including coding loss and discriminating loss. The coding loss is used to realize the group sparsity of code coefficients, in which within-class spectral samples can be represented intensively and effectively. The Fisher discriminating loss is used to enforce the sparse representation coefficients with large between-class scatter. Extensive tests performed on hyperspectral dataset with bright prospects prove the developed method to be effective and outperform other existing methods.