bluuebunny/crossref_metadata_2025 huggingface dataset:
TRPM3-Induced Gene Transcription Is under Epigenetic Control
Authors: Thiel Gerald , Rössler Oliver G.
Published: July 2022

Transient receptor potential M3 (TRPM3) cation channels regulate numerous biological functions, including gene transcription. Stimulation of TRPM3 channels with pregnenolone sulfate activates stimulus-responsive transcription factors, which bind to short cognate sequences in the promoters of their target genes. In addition, coregulator proteins are involved that convert the chromatin into a configuration that is permissive for gene transcription. In this study, we determined whether TRPM3-induced gene transcription requires coactivators that change the acetylation pattern of histones. We used compound A485, a specific inhibitor of the histone acetyltransferases CBP and p300. In addition, the role of bromodomain proteins that bind to acetylated lysine residues of histones was analyzed. We used JQ1, an inhibitor of bromodomain and extra terminal domain (BET) family proteins. The results show that both compounds attenuated the activation of AP-1 and CREB-regulated gene transcription following stimulation of TRPM3 channels. Inhibition of CBP/p300 and BET proteins additionally reduced the transcriptional activation potential of the transcription factors c-Fos and Elk-1. Transcriptional upregulation of the interleukin-8 gene was attenuated by A485 and JQ1, indicating that proinflammatory cytokine expression is controlled by CBP/p300 and bromodomain proteins. We conclude that TRPM3-induced signaling involves transcriptional coactivators and acetyl-lysine-bound bromodomain proteins for activating gene transcription.
Chalcones as Potential Ligands for the Treatment of Parkinson’s Disease
Authors: Królicka Ewelina , Kieć-Kononowicz Katarzyna , Łażewska Dorota
Published: July 2022

Along with the increase in life expectancy, a significant increase of people suffering from neurodegenerative diseases (ND) has been noticed. The second most common ND, after Alzheimer’s disease, is Parkinson’s disease (PD), which manifests itself with a number of motor and non-motor symptoms that hinder the patient’s life. Current therapies can only alleviate those symptoms and slow down the progression of the disease, but not effectively cure it. So now, in addition to understanding the mechanism and causes of PD, it is also important to find a powerful way of treatment. It has been proved that in the etiology and course of PD, the essential roles are played by dopamine (DA) (an important neurotransmitter), enzymes regulating its level (e.g., COMT, MAO), and oxidative stress leading to neuroinflammation. Chalcones, due to their “simple” structure and valuable biological properties are considered as promising candidates for treatment of ND, also including PD. Here, we provide a comprehensive review of chalcones and related structures as potential new therapeutics for cure and prevention of PD. For this purpose, three databases (Pubmed, Scopus and Web of Science) were searched to collect articles published during the last 5 years (January 2018–February 2022). Chalcones have been described as promising enzyme inhibitors (MAO B, COMT, AChE), α-synuclein imaging probes, showing anti-neuroinflammatory activity (inhibition of iNOS or activation of Nrf2 signaling), as well as antagonists of adenosine A1 and/or A2A receptors. This review focused on the structure–activity relationships of these compounds to determine how a particular substituent or its position in the chalcone ring(s) (ring A and/or B) affects biological activity.
Improving the Efficacy and Accessibility of Intracranial Viral Vector Delivery in Non-Human Primates
Authors: Griggs Devon J. , Garcia Aaron D. , Au Wing Yun , Ojemann William K. S. , Johnson Andrew Graham , Ting Jonathan T. , Buffalo Elizabeth A. , Yazdan-Shahmorad Azadeh
Published: July 2022

Non-human primates (NHPs) are precious resources for cutting-edge neuroscientific research, including large-scale viral vector-based experimentation such as optogenetics. We propose to improve surgical outcomes by enhancing the surgical preparation practices of convection-enhanced delivery (CED), which is an efficient viral vector infusion technique for large brains such as NHPs’. Here, we present both real-time and next-day MRI data of CED in the brains of ten NHPs, and we present a quantitative, inexpensive, and practical bench-side model of the in vivo CED data. Our bench-side model is composed of food coloring infused into a transparent agar phantom, and the spread of infusion is optically monitored over time. Our proposed method approximates CED infusions into the cortex, thalamus, medial temporal lobe, and caudate nucleus of NHPs, confirmed by MRI data acquired with either gadolinium-based or manganese-based contrast agents co-infused with optogenetic viral vectors. These methods and data serve to guide researchers and surgical team members in key surgical preparations for intracranial viral delivery using CED in NHPs, and thus improve expression targeting and efficacy and, as a result, reduce surgical risks.
Advanced Online Monitoring of In Vitro Human 3D Full-Thickness Skin Equivalents
Authors: Schaller-Ammann Roland , Kreß Sebastian , Feiel Jürgen , Schwagerle Gerd , Priedl Joachim , Birngruber Thomas , Kasper Cornelia , Egger Dominik
Published: July 2022

Skin equivalents and skin explants are widely used for dermal penetration studies in the pharmacological development of drugs. Environmental parameters, such as the incubation and culture conditions affect cellular responses and thus the relevance of the experimental outcome. However, available systems such as the Franz diffusion chamber, only measure in the receiving culture medium, rather than assessing the actual conditions for cells in the tissue. We developed a sampling design that combines open flow microperfusion (OFM) sampling technology for continuous concentration measurements directly in the tissue with microfluidic biosensors for online monitoring of culture parameters. We tested our design with real-time measurements of oxygen, glucose, lactate, and pH in full-thickness skin equivalent and skin explants. Furthermore, we compared dermal penetration for acyclovir, lidocaine, and diclofenac in skin equivalents and skin explants. We observed differences in oxygen, glucose, and drug concentrations in skin equivalents compared to the respective culture medium and to skin explants.
Critical Analysis and Quality Assessment of Nanomedicines and Nanocarriers in Clinical Trials: Three Years of Activity at the Clinical Trials Office
Authors: Dri Diego Alejandro , Gaucci Elisa , Torrieri Ilaria , Carafa Maria , Marianecci Carlotta , Gramaglia Donatella
Published: July 2022

Investigational medicinal products submitted over the course of 3 years and authorized at the Clinical Trials Office of the Italian Medicines Agency as part of a request for authorization of clinical trials were scrutinized to identify those encompassing nanomedicines. The quality assessment reports performed on the documentation submitted were analyzed, classifying and discussing the most frequently detected issues. The identification of nanomedicines retrieved and the information on their quality profiles are shared to increase the transparency and availability of information, providing feedback that can support sponsors in optimizing the quality part of the documentation and of the information submitted. Results confirm that nanomedicines tested as investigational medicinal products in clinical trials are developed and authorized in agreement with the highest standards of quality, meeting safety profiles according to the strong regulatory requirements in the European Union. Some key points are highlighted and indicate that the regulatory approach to innovation in a clinical trial setting could potentially be renewed to ride the wave of innovation, particularly in the nanotechnology field, capitalizing on lessons learned and still ensuring a strong and effective framework.
Double Heterojunction Crystalline Silicon Solar Cells: From Doped Silicon to Dopant-Free Passivating Contacts
Authors: Wong Terence K.S. , Pei Keyi
Published: July 2022

Carrier-selective passivating contacts for effective electron and hole extraction are crucial to the attainment of high efficiency in crystalline silicon (Si) solar cells. In this comprehensive review, the principle of carrier extraction and recombination mechanisms in conventional industrial Si solar cells are discussed first. Passivating contacts based on (i) amorphous hydrogenated Si and (ii) polysilicon/silicon oxide are next reviewed, with emphasis on carrier selectivity mechanisms including contact layer band alignment with silicon, and localized carrier transport in ultrathin oxides. More recent developments in dopant-free passivating contacts deposited by lower-cost fabrication processes with lower thermal budget are then described. This third category of non-Si based electron- and hole-selective passivating contacts include transition metal oxides, alkali/alkali earth metal fluorides and organic conjugated polymers. The photovoltaic performance of asymmetric double heterojunction Si solar cells fabricated using these non-Si passivating contacts and their stability in damp heat conditions are discussed and compared with Si based passivating contacts.
In Silico Conformation of the Drug Colchicine into Tubulin Models and Acute Phytotoxic Activity on Cucumis sativus Radicles
Authors: Peña-Morán Omar Aristeo , Jiménez-Pérez Jesús , Cerón-Romero Litzia , Rodríguez-Aguilar Maribel
Published: July 2022

Many tests are used to determine the toxic activity of miscellaneous substances, and those that are simple, fast, and inexpensive are useful for screening compounds with applications in different fields. The Cucumis sativus root growth inhibition test is an example of acute toxicity determinations. On the other hand, colchicine has been used as a herbicide to generate polyploids in plant species finally reaching the environment; for this reason, colchicine could become a point of attention in ecotoxicology. This work established that Cucumis sativus, at the colchicine binding site (CBS) in tubulin, shares 100% similarity with humans. Colchicine was docked on seven Cucumis sativus computational models of the αβ-tubulin heterodimer, allowing us to understand a possible conformation in tubulin to trigger its antimitotic effect. Furthermore, an in vitro phytotoxicity assay of colchicine-treated cucumber radicles indicated a hormetic-type concentration-dependent response with macroscopic changes in radicles and hypocotyl. These results support the highly preserved grade of tubulins in several species, and using microtubule inhibitors could require attention in ecotoxicological issues. The Cucumis sativus root growth test could help evaluate small molecules (colchicine analogs), chiefly by CBS interactions, a known druggable site, still a target in the search for antimitotic compounds.
Expression of GEX1 Orthologs of Brassica rapa and Oryza sativa Rescued the Nuclear Fusion Defect of the Arabidopsis GEX1 Mutant
Authors: Yabe Ayaka , Nishikawa Shuh-ichi
Published: July 2022

Nuclear fusion is required for the sexual reproduction of various organisms, including angiosperms. During the life cycle of angiosperms, nuclear fusion occurs three times: once during female gametogenesis, when the two polar nuclei fuse in the central cell, and twice during double fertilization. Nuclear fusion in plant reproduction is achieved by sequential nuclear fusion events: outer and inner nuclear membrane fusion. Arabidopsis gamete expressed 1 (GEX1) is a nuclear membrane protein of gametes that is required for nuclear fusion during reproduction. Although orthologs of GEX1 have been identified in various land plants, sequence identities are not high, even between angiosperm GEX1 orthologs; the sequence identity between Arabidopsis GEX1 and Oryza sativa GEX1 ortholog is lower than 50%. Here, we found that the expression of GEX1 orthologs of O. sativa, as well as of Brassica rapa from the Arabidopsis GEX1 promoter, rescued the polar nuclear fusion defect of the gex1 mutant. We also found that the expression of these GEX1 orthologs rescued the lethality of the gex1 homozygous mutant, which is proposed to be caused by the sperm nuclear fusion defects upon fertilization. Our results indicate a functional conservation between Arabidopsis and O. sativa GEX1 orthologs, despite their relatively low sequence identities.
Spectroscopic Evidence of Thermal Changes in Plant Oils during Deep-Frying—Chemical and Infrared Studies
Authors: Dymińska Lucyna , Albegar Abduladhim Moamer Moftah , Sąsiadek Wojciech , Kucharska Edyta , Zając Adam , Hanuza Jerzy
Published: July 2022

For this study, the thermal degradation of palm, coconut, rice bran, and rapeseed (canola) oils was studied. Products formed during deep-frying were identified using chemical methods and these results were verified with those derived from FT-IR (Fourier-transform infrared spectroscopy) studies. Mathematically processed spectral data were analyzed in terms of the breaking of double bonds, the decomposition of the carotenoids, and the reduction of the C=O carbonyl group. Clearly visible changes in the position and intensity of some bands were used for explaining the structural changes in the studied oils. These changes prove that during the heating of the oils, decomposition of the plant fat into fatty acids appears, together with the reduction of the number of certain bonds (e.g., C=C, =C-H, and C=O) and cracking of the acylglycerol chains. The iodine values of the heated oils, determined from the FT-IR spectra measurements, show a significant decrease in their degree of unsaturation level. These effects, visible in the FT-IR spectra, confirm the chemical and structural changes derived from the chemical and physicochemical studies of the plant oils. The influence of heating time on the band intensity of proteins was also studied.
Consumer Hedonic Ratings and Associated Sensory Characteristics and Emotional Responses to Fourteen Pecan Varieties Grown in Texas
Authors: Du Xiaofen , Wang Xinwang , Muniz Adriana , Kubenka Keith
Published: July 2022

Pecan is one of the top five most widely consumed tree nuts, and pecan nut quality is a major factor for consideration in breeding better pecan cultivars for use by producers. However, the pecan industry faces a hurdle to evaluate its nutmeat taste, and there has so far been limited evaluation of consumer attitudes toward pecan nutmeat. This study aimed to investigate the consumer (n = 198) hedonic rating, diagnostic sensory attribute intensity, and emotional response for 14 pecan samples, consisting of native/seedling and improved varieties. The results showed all kernels received positive hedonic scores (>5, 9-point hedonic scale) for overall acceptance and the acceptability of size, interior color, typical-pecan flavor, and raw-nut flavor. The primary sensory attributes (intensities > 5.0, 0–10 line scale) were typical-pecan and raw-nut flavors, followed by buttery flavor, sweetness, and astringency. Kernel off-flavors were not perceived in general. For 20 emotion-associated terms, the intensity of the satiating effect was medium, while the energizing effect was lower. The major emotional responses were healthy, satisfied, and comfort, followed by calm, interested, premium, and relaxed. Kernel variety difference was significant (p ≤ 0.05) for all these measured variables. Consumer overall acceptance toward pecan kernels was driven by the acceptability of flavor and interior color, flavor intensities, no off-flavors, and positive emotional responses; kernel size was not an impactful factor. The six most preferred varieties were 86TX2-1.5, Pawnee, Barton, 1997-09-0012, 1991-01-0026, and Harris Super. This study is the first to use consumer input to assess nut quality and consumption preference and will be foundational to ongoing breeding programs to develop new pecan cultivars that will better meet consumer preferences and expectations, and therefore will be accepted by the processing industry and growers.
Thermal Decomposition Behavior of Polyimide Containing Flame Retardant SiO2 and Mg(OH)2
Authors: Wang Jie , Jiang Aifeng , Li Yanchun , Song Dongming , Li Yifan , Cheng Long
Published: July 2022

The effects of flame retardant silica (SiO2) and magnesium hydroxide (Mg(OH)2) on the thermal decomposition process of polyimide (PI) are discussed in this paper. Firstly, the decomposition process of PI in a nitrogen and oxygen atmosphere was studied by thermogravimetric analysis and differential scanning calorimetry methods, and the kinetic parameters were calculated by the nonlinear fitting method. In an inert atmosphere, PI decomposition consists of a three-step endothermic reaction, whereas in an oxygen atmosphere, PI decomposition consists of two steps, in which the first step does not change, and the second step changes to a violent exothermic peak. The effects of 3 wt % SiO2 (SPI) and 3 wt % Mg(OH)2 (MPI) on the degradation kinetics of PI are discussed. The results show that under an oxygen atmosphere, SiO2 and Mg(OH)2 hydroxide mainly delayed the second-step oxidation exothermic peak temperature of PI by 5 °C. In summary, the first step of the PI degradation is not affected by oxygen, and the flame retardant mainly acts in the second step, which can delay the oxidation heat release. In addition, the addition of SiO2 could prevent PI from aging whereas Mg(OH)2 has barely effect on the aging of PI.
The Role of Molar Mass in Achieving Isotropy and Inter-Layer Strength in Mat-Ex Printed Polylactic Acid
Authors: Costanzo Andrea , Poggi Alice , Looijmans Stan , Venkatraman Deepak , Sawyer Dan , Puskar Ljiljana , Mcllroy Claire , Cavallo Dario
Published: July 2022

There has been extensive research in the field of material-extrusion (Mat-Ex) 3D printing to improve the inter-layer bonding process. Much research focusses on how various printing conditions may be detrimental to weld strength; many different feedstocks have been investigated along with various additives to improve strength. Surprisingly, there has been little attention directed toward how fundamental molecular properties of the feedstock, in particular the average molar mass of the polymer, may contribute to microstructure of the weld. Here we showed that weld strength increases with decreasing average molar mass, contrary to common observations in specimens processed in more traditional ways, e.g., by compression molding. Using a combination of synchrotron infra-red polarisation modulation microspectroscopy measurements and continuum modelling, we demonstrated how residual molecular anisotropy in the weld region leads to poor strength and how it can be eradicated by decreasing the relaxation time of the polymer. This is achieved more effectively by reducing the molar mass than by the usual approach of attempting to govern the temperature in this hard to control non-isothermal process. Thus, we propose that molar mass of the polymer feedstock should be considered as a key control parameter for achieving high weld strength in Mat-Ex.
Synthesis of New Type Polymers by Quasi-Living Atom Transfer Radical Polymerization
Authors: Illés Gergely , Németh Csaba , Hidas Karina Ilona , Surányi József , Tóth Adrienn , Pajor Ferenc , Póti Péter
Published: July 2022

Thanks to the polymer revolution of the 20th century, plastics are now part of our everyday lives. We use plastics as naturally as if they had always been an integral part of our lives. However, in the recent past, we were still predominantly using wood, metal, and glass objects, which were replaced by plastic products at an explosive rate. In many cases, this replacement has resulted in products with better physical, chemical, or biological properties. The changeover was too rapid, and the consequences were not recognized in time. This is evidenced by the huge scale of plastic pollution worldwide today. It is therefore in the interests of the future of both humans and animals that we must pay particular attention to the direct and indirect environmental impact of plastics introduced in animal husbandry. Starting from the tetrafunctional initiator produced as the first step of my work, poly(n-butyll acrylate) star polymers of different molecular weights were synthesized by atom transfer radical polymerization, using the so-called “core first” method. The bromine chain end of the produced star polymers was replaced by an azide group using a substitution reaction. Propalgyl telechelic PEGs were synthesized as a result of lattice end modification of poly(ethylene glycol) with different molecular weights. The azidated star polymers were connected with propalgyl telechelic PEGs using Huisgen’s “click” chemical process, and as a result of the “click” connection, amphiphilic polymer networks with several different structures were obtained.
A Microvascular System Self-Healing Approach on Polymeric Composite Materials
Authors: Vintila Ionut Sebastian , Ghitman Jana , Iovu Horia , Paraschiv Alexandru , Cucuruz Andreia , Mihai Dragos , Popa Ionut Florian
Published: July 2022

The paper addresses the synthesis of a nano-fibre network by coaxial electrospinning, embedding the healing agent dicyclopentadiene (DCPD) in polyacrylonitrile (PAN) fibres. Compared to other encapsulation methods, the use of nano-fibres filled with healing agent have no effect on the mechanical properties of the matrix and can address a larger healing area. Additionally, carbon nanotubes were added as nanofillers to enhance the reactivity between DCPD and the epoxydic matrix. The self-healing capability of the nano-fibre network was carried out by flexural tests, at epoxy resin level and composite level. Results obtained from Fourier transform infrared (FTIR) spectrometry, thermogravimetric analysis (TGA) and scanning electron microscopy (SEM) confirmed the successful encapsulation of DCPD healing agent in PAN fibres. Flexural tests indicate that after 48 h, the epoxy resin has recovered 84% of its flexural strength while the composite material recovered 93%.
Strategies Addressing the Challenges of the COVID-19 Pandemic in Long-Term, Palliative and Hospice Care: A Qualitative Study on the Perspectives of Patients’ Family Members
Authors: Pacolli Latife , Wahidie Diana , Erdogdu Ilknur Özger , Yilmaz-Aslan Yüce , Brzoska Patrick
Published: July 2022

Patients in long-term, palliative, and hospice care are at increased risk of a severe course of COVID-19. For purposes of infection control, different strategies have been implemented by the respective health care facilities, also comprising visitation and other forms of contact restrictions. The aim of the present study was to examine how these strategies are perceived by family members of patients in these settings. An exploratory, qualitative approach was used to examine perceptions of policies and strategies using partially standardized guided interviews analyzed by means of a thematic approach. Interviews were conducted with 10 family members of long-term, palliative, and hospice care patients. Interviewees were between 30 and 75 years old. Because of the pandemic-related measures, respondents felt that their basic rights were restricted. Results indicate that perceptions of strategies and interventions in long-term, palliative, and hospice care facilities are particularly influenced by the opportunity to visit and the number of visitors allowed. Strict bans on visits, particularly during end-of-life care, are associated with a strong emotional burden for patients and family members alike. Aside from sufficient opportunities for visits, virtual communication technologies need to be utilized to facilitate communication between patients, families, and caregivers.
Evaluation of the Analysis of Record for Calibration (AORC) Rainfall across Louisiana
Authors: Kim Hanbeen , Villarini Gabriele
Published: July 2022

The use of a long-term and high-quality precipitation dataset is crucial for hydrologic modeling and flood risk management. This study evaluates the Analysis of Period of Record for Calibration (AORC) dataset, a newly released product with high temporal and spatial resolutions. Our study region is centered on Louisiana because of the major flooding it has been experiencing. We compare the AORC hourly precipitation to other widely used gridded rainfall products and rain-gauge observations. To evaluate the performance of rainfall products according to different weather conditions causing severe flooding, we stratify the analyses depending on whether precipitation is associated with a tropical cyclone (TC) or not. Compared to observations, our results show that the AORC has the highest correlation coefficients (i.e., values above 0.75) with respect to observations among all rainfall products for both TC and non-TC periods. When the skill metric is decomposed into the potential skill and biases, the AORC clearly shows the highest potential skill with relatively small biases for the whole period. In addition, the AORC performs better for the TC period compared to the non-TC ones. Our results suggest that AORC precipitation shows good potential to be viable for hydrologic modeling and simulations of TC and non-TC events.
A New Line Matching Approach for High-Resolution Line Array Remote Sensing Images
Authors: Wang Jingxue , Liu Suyan , Zhang Ping
Published: July 2022

In this paper, a new line matching approach for high-resolution line array remote sensing images is presented. This approach establishes the correspondence of straight lines on two images by combining multiple constraints. Firstly, three geometric constraints, epipolar, direction and the point-line geometric relationship, are used in turn to reduce the number of matching candidates. After this, two similarity constraints, the double line descriptor and point-line distance, are used to determine the optimal matches. Finally, the co-linearity constraint is used to check the one-to-many and many-to-one correspondences in the results. The proposed approach is tested on eight representative image patches selected from the ZY-3 line array satellite images, and the results are compared with those of two state-of-the-art approaches. Experiments demonstrate the superiority and potential of the proposed approach due to its higher accuracy and greater number of matches in most cases.
Operational Use of EO Data for National Land Cover Official Statistics in Lesotho
Authors: De Simone Lorenzo , Ouellette William , Gennari Pietro
Published: July 2022

The Food and Agriculture Organization of the United Nations (FAO) is building a land cover monitoring system in Lesotho in support of ReNOKA (‘we are a river’), the national program for integrated catchment management led by the Government of Lesotho. The aim of the system is to deliver land cover products at a national level on an annual basis that can be used for global reporting of official land cover statistics and to inform appropriate land restoration policies. This paper presents an innovative methodology that has allowed the production of five standardized annual land cover maps (2017–2021) using only a single in situ dataset gathered in the field for the reference year, 2021. A total of 10 land cover classes are represented in the maps, including specific features, such as gullies, which are under close monitoring. The mapping approach developed includes the following: (i) the automatic generation of training and validation datasets for each reporting year from a single in situ dataset; (ii) the use of a Random Forest Classifier combined with postprocessing and harmonization steps to produce the five standardized annual land cover maps; (iii) the construction of confusion matrixes to assess the classification accuracy of the estimates and their stability over time to ensure estimates’ consistency. Results show that the error-adjusted overall accuracy of the five maps ranges from 87% (2021) to 83% (2017). The aim of this work is to demonstrate a suitable solution for operational land cover mapping that can cope with the scarcity of in situ data, which is a common challenge in almost every developing country.
Long-Tailed Graph Representation Learning via Dual Cost-Sensitive Graph Convolutional Network
Authors: Duan Yijun , Liu Xin , Jatowt Adam , Yu Hai-tao , Lynden Steven , Kim Kyoung-Sook , Matono Akiyoshi
Published: July 2022

Deep learning algorithms have seen a massive rise in popularity for remote sensing over the past few years. Recently, studies on applying deep learning techniques to graph data in remote sensing (e.g., public transport networks) have been conducted. In graph node classification tasks, traditional graph neural network (GNN) models assume that different types of misclassifications have an equal loss and thus seek to maximize the posterior probability of the sample nodes under labeled classes. The graph data used in realistic scenarios tend to follow unbalanced long-tailed class distributions, where a few majority classes contain most of the vertices and the minority classes contain only a small number of nodes, making it difficult for the GNN to accurately predict the minority class samples owing to the classification tendency of the majority classes. In this paper, we propose a dual cost-sensitive graph convolutional network (DCSGCN) model. The DCSGCN is a two-tower model containing two subnetworks that compute the posterior probability and the misclassification cost. The model uses the cost as ”complementary information” in a prediction to correct the posterior probability under the perspective of minimal risk. Furthermore, we propose a new method for computing the node cost labels based on topological graph information and the node class distribution. The results of extensive experiments demonstrate that DCSGCN outperformed other competitive baselines on different real-world imbalanced long-tailed graphs.
Multi-Parameter Inversion of AIEM by Using Bi-Directional Deep Neural Network
Authors: Wang Yu , He Zi , Yang Ying , Ding Dazhi , Ding Fan , Dang Xun-Wang
Published: July 2022

A novel multi-parameter inversion method is proposed for the Advanced Integral Equation Model (AIEM) by using bi-directional deep neural network. There is a very complex nonlinear relationship between the surface parameters (dielectric constant and roughness) and radar backscattering coefficient. The traditional inverse neural network, which is constructed by using the backscattering coefficients as the input and the surface parameters as the output, leads to bad convergence and wrong results. This is because many sets of surface parameters can get the same backscattering coefficient. Therefore, the proposed bi-directional deep neural network starts with building an AIEM-based forward deep neural network (AIEM-FDNN), whose inputs are the surface parameters and outputs are the backscattering coefficients. In this way, the weights and biases of the forward deep neural network can be optimized and predicted, which can be used for the backward deep neural network (AIEM-BDNN). Then, the multi-parameters are updated by minimizing the loss between the output backscattering coefficients with the measured ones. By inserting a sigmoid function between the input and the first hidden layer, the input multi-parameters can be efficiently approximated and continuously updated. As a result, both the forward and backward deep neural networks can be built with these weights and biases. By sharing the weights and biases of the forward network, the training of the inverse network is avoided. The bi-directional deep neural network can not only predict the backscattering coefficient but can also inverse the surface parameters. Numerical results are given to demonstrate that the RMSE of the backscattering coefficients calculated by the proposed bi-directional neural network can be reduced to 0.1%. The accuracy of the inversion parameters, including the real and imaginary parts of the dielectric constant, the root mean square height and the correlation length, can be improved to 97.56%, 91.14%, 99.04% and 98.45%, respectively. At the same time, the bi-directional neural network also has good accuracy for the inversion of the POLARSCAT measured data.
Evaluation of Global Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) Products at 500 m Spatial Resolution
Authors: Zheng Yajie , Xiao Zhiqiang , Li Juan , Yang Hua , Song Jinling
Published: July 2022

The fraction of absorbed photosynthetically active radiation (FAPAR) is a key biophysical variable directly associated with the photosynthetic activity of plants. Several global FAPAR products with different spatial resolutions have been generated from remote sensing data, and much work has focused on validating them. However, those studies have primarily evaluated global FAPAR products at a spatial resolution of 1 km or more, whereas few studies have evaluated the global 500 m resolution FAPAR product distributed in recent years. Furthermore, there are a few FAPAR products, including black-sky, white-sky and blue-sky FAPAR datasets, and almost no studies have evaluated these products. In this article, three global FAPAR products at 500 m resolution, namely MODIS (only black-sky FAPAR), MUSES and EBR (black-sky, white-sky and blue-sky FAPAR) were compared to evaluate their temporal and spatial discrepancies and direct validation was conducted to compare these FAPAR products with the FAPAR values derived from the high-resolution reference maps from the Validation of Land European Remote Sensing Instrument (VALERI) and Implementing Multi-Scale Agricultural Indicators Exploiting Sentinels (IMAGINES) projects. The results showed that the MUSES FAPAR product exhibited the best spatial integrity, whereas the MODIS and EBR FAPAR products had many missing pixels in the equatorial rainforest regions and at high latitudes in the Northern Hemisphere. The MODIS, MUSES and EBR FAPAR products were generally consistent in their spatial patterns. However, a relatively large discrepancy among these FAPAR products was present in the equatorial rainforest regions and the middle and high latitude regions where the main vegetation type was forest. The differences between the black-sky and white-sky FAPAR datasets at the global scale were significant. In January, the MUSES and EBR black-sky FAPAR values were larger than their white-sky FAPAR values in the region north of 30° north latitude but they were smaller than their white-sky FAPAR values in the region south of 30° north latitude. In July, the MUSES and EBR black-sky FAPAR values were lower than their white-sky FAPAR values in the region north of 30° south latitude and they were larger than their white-sky FAPAR values in the region south of 30° south latitude. The temporal profiles of the MUSES FAPAR product were continuous and smooth, whereas those of the MODIS and EBR FAPAR products showed many fluctuations, particularly during the growing seasons. Direct validation indicated that the MUSES FAPAR product had the best accuracy (R2 = 0.6932, RMSE = 0.1495) compared to the MODIS FAPAR product (R2 = 0.6202, RMSE = 0.1710) and the EBR FAPAR product (R2 = 0.5746, RMSE = 0.1912).
Dynamic Monitoring of Laohugou Glacier No. 12 with a Drone, West Qilian Mountains, West China
Authors: Liu Yushuo , Qin Dahe , Jin Zizhen , Li Yanzhao , Xue Liang , Qin Xiang
Published: July 2022

Laohugou glacier No. 12 (LHG12), located in the northeast of the Qinghai–Tibet Plateau, is the largest valley glacier in the Qilian mountains. Since 1957, LHG12 has shrunk significantly. Due to the limitations of in situ observations, simulations and investigations of LHG12 have higher levels of uncertainty. In this study, consumer-level, low-altitude microdrones were used to conduct repeated photogrammetry at the lower part of LHG12, and a digital orthophoto map (DOM) and a digital surface model (DSM) with a resolution at the centimeter scale were generated, from 2017 to 2021. The dynamic parameters of the glacier were detected by artificial and automatic extraction methods. Using a combination of GNSS and drone-based data, the dynamic process of LHG12 was analyzed. The results show that the terminus of LHG12 has retreated by 194.35 m in total and by 19.44 m a−1 on average during 2008–2021. The differential ablation leading to terminus retreat distance markedly increased during the study period. In 2019–2021, the maximum annual surface velocity was 6.50 cm day−1, and during ablation season, the maximum surface velocity was 13.59 cm day−1, 52.17% higher than it is annually. The surface parameters, motion, and mass balance characteristics of the glacier had significant differences between the west and east branches. The movement in the west branch is faster than it is in the east branch. Because of the extrusion of the two ice flows, there is a region with a faster surface velocity at the ablation area. The ice thickness of LHG12 is decreasing due to intensified ablation, leading to a deceleration in the surface velocity. In large glaciers, this phenomenon is more obvious than it is in small glaciers in the Qilian mountains.
Automatic Mapping of Karez in Turpan Basin Based on Google Earth Images and the YOLOv5 Model
Authors: Li Qian , Guo Huadong , Luo Lei , Wang Xinyuan
Published: July 2022

As a large-scale irrigation and water conservancy project in ancient times, karez are common in Central Asia and arid regions with a history of thousands of years. Turpan, which is located in the Xinjiang Uyghur Autonomous Region, has the most extensive and concentrated distribution of karez shafts in China. There are tens of thousands of shafts, some of which are in use and are living cultural heritage. According to radiocarbon (14C) dating, some karezs are over 600 years old. The karez is of great significance to the research on geology, hydrology, oasis, climate change, and development history of karez in Turpan. With the development of the population, arable land, industrialization, and urbanization, karez systems are facing the risk of abandonment. Detailed karez distribution mapping or dynamic monitoring data are important for their management or analysis; although there are related methods, due to Turpan’s large desert and “Gobi” environments, field surveys are time- and energy-consuming, and some areas are difficult to access. Precise shaft locations and distribution maps are scarce and often lack georeferencing. The distribution and preservation of karez have not yet been fully grasped. In this study, we evaluated the effectiveness of You Only Look Once version 5 (YOLOv5) in automatically detecting karez in high-resolution images of the Turpan region. We propose post-processing steps to reduce the false karez identified by YOLOv5. Our results demonstrate the feasibility of using YOLOv5 and post-processing techniques to detect karez automatically, and the detected results are sufficient to capture the linear alignment of karez. Target detection based on YOLOv5 and post-processing can greatly improve automatic shaft identification and is therefore useful for the fine mapping of karez. We also applied this method in Shanshan County (for which no detailed mapping data on karez has been obtained before) and successfully detected some karez that had not been archived before. The number of shafts in Turpan is 82,493. Through DBSCAN clustering, it was identified which karez line belonged to which shaft; the number of sections of karez that have been used is 5057, which have a total length of 2387.2 km. The karez line obtained was overlaid with the crop-land data, and the positional relationship between the karez line and the crop land was analyzed. The cultivated area is basically surrounded by karez. Our method can potentially be applied to construct an inventory for all karez shafts globally.
Change Detection Techniques with Synthetic Aperture Radar Images: Experiments with Random Forests and Sentinel-1 Observations
Authors: Mastro Pietro , Masiello Guido , Serio Carmine , Pepe Antonio
Published: July 2022

This work aims to clarify the potential of incoherent and coherent change detection (CD) approaches for detecting and monitoring ground surface changes using sequences of synthetic aperture radar (SAR) images. Nowadays, the growing availability of remotely sensed data collected by the twin Sentinel-1A/B sensors of the European (EU) Copernicus constellation allows fast mapping of damage after a disastrous event using radar data. In this research, we address the role of SAR (amplitude) backscattered signal variations for CD analyses when a natural (e.g., a fire, a flash flood, etc.) or a human-induced (disastrous) event occurs. Then, we consider the additional pieces of information that can be recovered by comparing interferometric coherence maps related to couples of SAR images collected between a principal disastrous event date. This work is mainly concerned with investigating the capability of different coherent/incoherent change detection indices (CDIs) and their mutual interactions for the rapid mapping of “changed” areas. In this context, artificial intelligence (AI) algorithms have been demonstrated to be beneficial for handling the different information coming from coherent/incoherent CDIs in a unique corpus. Specifically, we used CDIs that synthetically describe ground surface changes associated with a disaster event (i.e., the pre-, cross-, and post-disaster phases), based on the generation of sigma nought and InSAR coherence maps. Then, we trained a random forest (RF) to produce CD maps and study the impact on the final binary decision (changed/unchanged) of the different layers representing the available synthetic CDIs. The proposed strategy was effective for quickly assessing damage using SAR data and can be applied in several contexts. Experiments were conducted to monitor wildfire’s effects in the 2021 summer season in Italy, considering two case studies in Sardinia and Sicily. Another experiment was also carried out on the coastal city of Houston, Texas, the US, which was affected by a large flood in 2017; thus, demonstrating the validity of the proposed integrated method for fast mapping of flooded zones using SAR data.
NrtNet: An Unsupervised Method for 3D Non-Rigid Point Cloud Registration Based on Transformer
Authors: Hu Xiaobo , Zhang Dejun , Chen Jinzhi , Wu Yiqi , Chen Yilin
Published: July 2022

Self-attention networks have revolutionized the field of natural language processing and have also made impressive progress in image analysis tasks. Corrnet3D proposes the idea of first obtaining the point cloud correspondence in point cloud registration. Inspired by these successes, we propose an unsupervised network for non-rigid point cloud registration, namely NrtNet, which is the first network using a transformer for unsupervised large deformation non-rigid point cloud registration. Specifically, NrtNet consists of a feature extraction module, a correspondence matrix generation module, and a reconstruction module. Feeding a pair of point clouds, our model first learns the point-by-point features and feeds them to the transformer-based correspondence matrix generation module, which utilizes the transformer to learn the correspondence probability between pairs of point sets, and then the correspondence probability matrix conducts normalization to obtain the correct point set corresponding matrix. We then permute the point clouds and learn the relative drift of the point pairs to reconstruct the point clouds for registration. Extensive experiments on synthetic and real datasets of non-rigid 3D shapes show that NrtNet outperforms state-of-the-art methods, including methods that use grids as input and methods that directly compute point drift.
Whole-Body Photoacoustic Imaging Techniques for Preclinical Small Animal Studies
Authors: Kye Hyunjun , Song Yuon , Ninjbadgar Tsedendamba , Kim Chulhong , Kim Jeesu
Published: July 2022

Photoacoustic imaging is a hybrid imaging technique that has received considerable attention in biomedical studies. In contrast to pure optical imaging techniques, photoacoustic imaging enables the visualization of optical absorption properties at deeper imaging depths. In preclinical small animal studies, photoacoustic imaging is widely used to visualize biodistribution at the molecular level. Monitoring the whole-body distribution of chromophores in small animals is a key method used in preclinical research, including drug-delivery monitoring, treatment assessment, contrast-enhanced tumor imaging, and gastrointestinal tracking. In this review, photoacoustic systems for the whole-body imaging of small animals are explored and summarized. The configurations of the systems vary with the scanning methods and geometries of the ultrasound transducers. The future direction of research is also discussed with regard to achieving a deeper imaging depth and faster imaging speed, which are the main factors that an imaging system should realize to broaden its application in biomedical studies.
Wearable Sensors for Healthcare: Fabrication to Application
Authors: Mukhopadhyay Subhas Chandra , Suryadevara Nagender Kumar , Nag Anindya
Published: July 2022

This paper presents a substantial review of the deployment of wearable sensors for healthcare applications. Wearable sensors hold a pivotal position in the microelectronics industry due to their role in monitoring physiological movements and signals. Sensors designed and developed using a wide range of fabrication techniques have been integrated with communication modules for transceiving signals. This paper highlights the entire chronology of wearable sensors in the biomedical sector, starting from their fabrication in a controlled environment to their integration with signal-conditioning circuits for application purposes. It also highlights sensing products that are currently available on the market for a comparative study of their performances. The conjugation of the sensing prototypes with the Internet of Things (IoT) for forming fully functioning sensorized systems is also shown here. Finally, some of the challenges existing within the current wearable systems are shown, along with possible remedies.
Dual Attention-Based Industrial Surface Defect Detection with Consistency Loss
Authors: Li Xuyang , Zheng Yu , Chen Bei , Zheng Enrang
Published: July 2022

In industrial production, flaws and defects inevitably appear on surfaces, resulting in unqualified products. Therefore, surface defect detection plays a key role in ensuring industrial product quality and maintaining industrial production lines. However, surface defects on different products have different manifestations, so it is difficult to regard all defective products as being within one category that has common characteristics. Defective products are also often rare in industrial production, making it difficult to collect enough samples. Therefore, it is appropriate to view the surface defect detection problem as a semi-supervised anomaly detection problem. In this paper, we propose an anomaly detection method that is based on dual attention and consistency loss to accomplish the task of surface defect detection. At the reconstruction stage, we employed both channel attention and pixel attention so that the network could learn more robust normal image reconstruction, which could in turn help to separate images of defects from defect-free images. Moreover, we proposed a consistency loss function that could exploit the differences between the multiple modalities of the images to improve the performance of the anomaly detection. Our experimental results showed that the proposed method could achieve a superior performance compared to the existing anomaly detection-based methods using the Magnetic Tile and MVTec AD datasets.