bluuebunny/crossref_metadata_2025 huggingface dataset:
High-Moisture Shear Processes: Molecular Changes of Wheat Gluten and Potential Plant-Based Proteins for Its Replacement
Authors: Gasparre Nicola , van den Berg Marco , Oosterlinck Filip , Sein Arjen
Published: September 2022

Nowadays, a growing offering of plant-based meat alternatives is available in the food market. Technologically, these products are produced through high-moisture shear technology. Process settings and material composition have a significant impact on the physicochemical characteristics of the final products. Throughout the process, the unfolded protein chains may be reduced, or associate in larger structures, creating rearrangement and cross-linking during the cooling stage. Generally, soy and pea proteins are the most used ingredients in plant-based meat analogues. Nevertheless, these proteins have shown poorer results with respect to the typical fibrousness and juiciness found in real meat. To address this limitation, wheat gluten is often incorporated into the formulations. This literature review highlights the key role of wheat gluten in creating products with higher anisotropy. The generation of new disulfide bonds after the addition of wheat gluten is critical to achieve the sought-after fibrous texture, whereas its incompatibility with the other protein phase present in the system is critical for the structuring process. However, allergenicity problems related to wheat gluten require alternatives, hence an evaluation of underutilized plant-based proteins has been carried out to identify those that potentially can imitate wheat gluten behavior during high-moisture shear processing.
Proanthocyanidins Modulate Rumen Enzyme Activities and Protein Utilization In Vitro
Authors: Singh Sultan , Koli Pushpendra , Bhadoria Brijesh K. , Agarwal Manjree , Lata Suman , Ren Yonglin , Du Xin
Published: September 2022

This study investigated the principal leaf protein (rubisco) solubilization and in vitro ruminal enzyme activity in relation to the molecular structure of proanthocyanidins extracted from leaves of Anogeissus pendula and Eugenia jambolana. Six proanthocyanidin fractions were extracted by 50% (v/v) methanol–water followed by 70% (v/v) acetone–water and then distilled water from leaves of A. pendula (AP) and E. jambolana (EJ) to yield EJ–70, EJ–50, EJ–DW, AP–70, AP–50 and AP–DW. Fractions were examined for their molecular structure and their effects on sheep ruminal enzymes and solubilization of rubisco in vitro. All fractions significantly (p < 0.05) inhibited the activity of ruminal glutamic oxaloacetic transaminase and glutamic pyruvic transaminase. The fractions AP–50 and EJ–50 significantly inhibited the activity of the R-cellulase enzyme. Most of the fractions inhibited R-glutamate dehydrogenase activity (p < 0.05) by increasing its concentration, while protease activity decreased by up to 58% with increasing incubation time and concentration. The solubilization of rubisco was observed to be comparatively higher in A. pendula (16.60 ± 1.97%) and E. jambolana (15.03 ± 1.06%) than that of wheat straw (8.95 ± 0.95%) and berseem hay (3.04 ± 0.08%). A significant (p < 0.05) increase in protein solubilization was observed when wheat straw and berseem hay were supplemented with A. pendula and E. jambolana leaves at different proportions. The efficiency of microbial protein was significantly (p < 0.05) greater with the supplementation of leaves of A. pendula in comparison to E. jambolana. The overall conclusion is that the proanthocyanidins obtained from E. jambolana exhibited greater inhibitory activities on rumen enzymes, whereas A. pendula recorded higher protein solubilization. Thus, PAs from A. pendula and E. jambolana appear to have the potential to manipulate rumen enzyme activities for efficient utilization of protein and fiber in ruminants.
Computational Prediction of Inhibitors and Inducers of the Major Isoforms of Cytochrome P450
Authors: Rudik Anastassia , Dmitriev Alexander , Lagunin Alexey , Filimonov Dmitry , Poroikov Vladimir
Published: September 2022

Human cytochrome P450 enzymes (CYPs) are heme-containing monooxygenases. This superfamily of drug-metabolizing enzymes is responsible for the metabolism of most drugs and other xenobiotics. The inhibition of CYPs may lead to drug–drug interactions and impair the biotransformation of drugs. CYP inducers may decrease the bioavailability and increase the clearance of drugs. Based on the freely available databases ChEMBL and PubChem, we have collected over 70,000 records containing the structures of inhibitors and inducers together with the IC50 values for the inhibitors of the five major human CYPs: 1A2, 3A4, 2D6, 2C9, and 2C19. Based on the collected data, we developed (Q)SAR models for predicting inhibitors and inducers of these CYPs using GUSAR and PASS software. The developed (Q)SAR models could be applied for assessment of the interaction of novel drug-like substances with the major human CYPs. The created (Q)SAR models demonstrated reasonable accuracy of prediction. They have been implemented in the web application P450-Analyzer that is freely available via the Internet.
Analysis and Comparison of Aroma Compounds of Brown Sugar in Guangdong, Guangxi and Yunnan Using GC-O-MS
Authors: Chen Erbao , Zhao Shuna , Song Huanlu , Zhang Yu , Lu Wanyao
Published: September 2022

Guangdong, Guangxi and Yunnan are the three provinces in China that yield the most brown sugar, a brown-red colored solid or powdered sugar product made from sugar cane. In the present study, the differences between odor compounds of brown sugar from Guangdong, Guangxi, and Yunnan provinces in China were compared and analyzed by gas chromatography-olfactometry-mass spectrometry (GC-O-MS). A total of 80 odor compounds, including 5 alcohols, 9 aldehydes, 8 phenols, 21 acids, 14 ketones, 5 esters, 12 pyrazines, and 6 other compounds, were detected. The fingerprint analysis of the brown sugar odor compounds showed 90% similarity, indicating a close relationship among the odor properties of brown sugar in each province. Moreover, the orthogonal partial least squares discriminant analysis (OPLS-DA) was performed to identify the compounds contributing to the volatile classification of the brown sugar from three provinces, which confirmed that OPLS-DA could be a potential tool to distinguish the brown sugar of three origins.
Benzo[k,l]xanthene Lignan-Loaded Solid Lipid Nanoparticles for Topical Application: A Preliminary Study
Authors: Torrisi Cristina , Cardullo Nunzio , Russo Stefano , La Mantia Alfonsina , Acquaviva Rosaria , Muccilli Vera , Castelli Francesco , Sarpietro Maria Grazia
Published: September 2022

Skin is the first human barrier that is daily exposed to a broad spectrum of physical and chemical agents, which can increase reactive oxygen species (ROS) and lead to the formation of topical disorders. Antioxidant molecules, such as benzo[k,l]xanthene lignans (BXL), are ideal candidates to eliminate or minimize the effects of ROS. Herein, we aimed to formulate BXL-loaded solid lipid nanoparticles (SLN-BXL) to improve the bioavailability and interaction with the skin, and also to investigate the protective impact against intracellular ROS generation in HFF-1 in comparison with the drug-free situation. SLN-BXL were formulated using the PIT/ultrasonication method, and then were subjected to physicochemical characterizations, i.e., average size, zeta potential (ZP), polydispersity index (PDI), encapsulation efficiency (%EE), thermotropic behavior, and interaction with a biomembrane model. The results show a mean size around 200 nm, PDI of 0.2, and zeta potential of about −28 mV, with values almost unchanged over a period of three months, while the EE% is ≈70%. Moreover, SLN-BXL are able to deeply interact with the biomembrane model, and to achieve a double-action release in mildly hydrophobic matrices; the results of the in vitro experiments confirm that SLN-BXL are cell-safe and capable of attenuating the IL-2-induced high ROS levels. In conclusion, based on our findings, the formulation can be proposed as a candidate for a preventive remedy against skin disorders induced by increased levels of ROS.
Antioxidant, Antidiabetic, Anticholinergic, and Antiglaucoma Effects of Magnofluorine
Authors: Durmaz Lokman , Kiziltas Hatice , Guven Leyla , Karagecili Hasan , Alwasel Saleh , Gulcin İlhami
Published: September 2022

Magnofluorine, a secondary metabolite commonly found in various plants, has pharmacological potential; however, its antioxidant and enzyme inhibition effects have not been investigated. We investigated the antioxidant potential of Magnofluorine using bioanalytical assays with 2,2-azinobis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS•+), N,N-dimethyl-p-phenylenediamine dihydrochloride (DMPD•+), and 1,1-diphenyl-2-picrylhydrazyl (DPPH•) scavenging abilities and K3[Fe(CN)6] and Cu2+ reduction abilities. Further, we compared the effects of Magnofluorine and butylated hydroxytoluene (BHT), butylated hydroxyanisole (BHA), α-Tocopherol, and Trolox as positive antioxidant controls. According to the analysis results, Magnofluorine removed 1,1-diphenyl-2-picrylhydrazyl (DPPH) radicals with an IC50 value of 10.58 μg/mL. The IC50 values of BHA, BHT, Trolox, and α-Tocopherol were 10.10 μg/mL, 25.95 μg/mL, 7.059 μg/mL, and 11.31 μg/mL, respectively. Our results indicated that the DPPH· scavenging effect of Magnofluorine was similar to that of BHA, close to that of Trolox, and better than that of BHT and α-tocopherol. The inhibition effect of Magnofluorine was examined against enzymes, such as acetylcholinesterase (AChE), α-glycosidase, butyrylcholinesterase (BChE), and human carbonic anhydrase II (hCA II), which are linked to global disorders, such as diabetes, Alzheimer’s disease (AD), and glaucoma. Magnofluorine inhibited these metabolic enzymes with Ki values of 10.251.94, 5.991.79, 25.411.10, and 30.563.36 nM, respectively. Thus, Magnofluorine, which has been proven to be an antioxidant, antidiabetic, and anticholinergic in our study, can treat glaucoma. In addition, molecular docking was performed to understand the interactions between Magnofluorine and target enzymes BChE (D: 6T9P), hCA II (A:3HS4), AChE (B:4EY7), and α-glycosidase (C:5NN8). The results suggest that Magnofluorine may be an important compound in the transition from natural sources to industrial applications, especially new drugs.
Identification of a Potential Inhibitor (MCULE-8777613195-0-12) of New Delhi Metallo-β-Lactamase-1 (NDM-1) Using In Silico and In Vitro Approaches
Authors: Muteeb Ghazala , Rehman Md Tabish , AlAjmi Mohamed F. , Aatif Mohammad , Farhan Mohd , Shafi Sheeba
Published: September 2022

New Delhi metallo-β-lactamase-1 (NDM-1), expressed in different Gram-negative bacteria, is a versatile enzyme capable of hydrolyzing β-lactam rings containing antibiotics such as penicillins, cephalosporins, and even carbapenems. Multidrug resistance in bacteria mediated by NDM-1 is an emerging threat to the public health, with an enormous economic burden. There is a scarcity in the availability of specific NDM-1 inhibitors, and also a lag in the development of new inhibitors in pharmaceutical industries. In order to identify novel inhibitors of NDM-1, we screened a library of more than 20 million compounds, available at the MCULE purchasable database. Virtual screening led to the identification of six potential inhibitors, namely, MCULE-1996250788-0-2, MCULE-8777613195-0-12, MCULE-2896881895-0-14, MCULE-5843881524-0-3, MCULE-4937132985-0-1, and MCULE-7157846117-0-1. Furthermore, analyses by molecular docking and ADME properties showed that MCULE-8777613195-0-12 was the most suitable inhibitor against NDM-1. An analysis of the binding pose revealed that MCULE-8777613195-0-12 formed four hydrogen bonds with the catalytic residues of NDM-1 (His120, His122, His189, and Cys208) and interacted with other key residues. Molecular dynamics simulation and principal component analysis confirmed the stability of the NDM-1 and MCULE-8777613195-0-12 complex. The in vitro enzyme kinetics showed that the catalytic efficiency (i.e., kcat/Km) of NDM-1 on various antibiotics decreased significantly in the presence of MCULE-8777613195-0-12, due to poor catalytic proficiency (kcat) and affinity (Km). The IC50 value of MCULE-8777613195-0-12 (54.2 µM) was comparable to that of a known inhibitor, i.e., D-captopril (10.3 µM). In sum, MCULE-8777613195-0-12 may serve as a scaffold to further design/develop more potent inhibitors of NDM-1 and other β-lactamases.
Expressive Interaction Design Using Facial Muscles as Controllers
Authors: French Fiona , Terry Cassandra , Huq Saif , Furieri Isaac , Jarzembinski Mateusz , Pauliukenas Simas , Morrison Neil , Shepherd Karen
Published: September 2022

Here we describe a proof-of-concept case study focusing on the design and development of a novel computer interface that uses facial muscles to control interactivity within a virtual environment. We have developed a system comprised of skin-mounted electrodes that detect underlying muscle activity through electromyography. The signals from the electrodes are filtered and smoothed, then used as input data to an application that displays a virtual environment with a 3D animated avatar. The user’s expressions control the facial movements of the avatar, thus conveying user emotions through real-time animation of a representative face in a virtual scenario. To achieve this, we collaborated with our Public and Patient Involvement focus group to discuss concepts and design appropriate interactions, while simultaneously developing a prototype system. Programmers and 3D artists worked together to create a system whereby individual user facial muscles are connected to 3D animated models of the same muscle features represented in an avatar, providing the user with an option to receive visual and numerical feedback on the extent of their muscle control. Using the prototype system, people can communicate facial expressions virtually with each other, without the need for a camera. This research is part of an on-going project to develop a facial muscle rehabilitation system that can be optimized to help patients with conditions such as hypomimia.
Effects of High-Fat Diet on the Gut Microbiota of Renalase Gene Knockout Mice
Authors: Fang Hui , Aoki Kai , Tokinoya Katsuyuki , Yonamine Masato , Sugasawa Takehito , Kawakami Yasushi , Takekoshi Kazuhiro
Published: September 2022

Metabolic diseases caused by gene and unhealthy living habits are increasing, which seriously threaten the life of people worldwide. Moreover, the microbiome has been shown to play an active role in the prevention and treatment of metabolic diseases. However, reliable evidence on renalase gene (Rnls), as a common gene related to metabolic diseases, is still lacking with regard to the influence on the microbiome. Hence, we investigated the effect of a normal diet (ND) and a high-fat diet (HFD) on the gut microbiota of Rnls knockout (Rnls−/−) and wild-type (Rnls+/+) mice. At the end of the 8-week experiment, DNA samples were extracted from fresh feces, and the composition of microbiota was profiled. The species in Rnls+/+-ND group were Bifidobacterium pseudolongum and Lactobacillus reuteri. Conversely, the species in Rnls−/−-ND group belonged to the genera Lactobacillus and Turicibacter. The HFD changed the ratio of Firmicutes/Bacteroidetes; while the bacteria in the Rnls+/+-HFD and Rnls−/−-HFD groups were different. Overall, this study not only revealed the composition of microbiota in Rnls−/− mice, but also indicated that Rnls and the bacteria related to Rnls may be new candidates in the prevention and diagnosis of metabolic diseases at an early stage.
Silicon-Induced Mitigation of NaCl Stress in Barley (Hordeum vulgare L.), Associated with Enhanced Enzymatic and Non-Enzymatic Antioxidant Activities
Authors: Akhter Muhammad , Noreen Sibgha , Ummara Ume , Aqeel Muhammad , Saleem Nawishta , Ahmed Muhammad , Mahmood Seema , Athar Habib-ur-Rehman , Alyemeni Mohammed , Kaushik Prashant , Ahmad Parvaiz
Published: September 2022

Salt stress obstructs plant’s growth by affecting metabolic processes, ion homeostasis and over-production of reactive oxygen species. In this regard silicon (Si) has been known to augment a plant’s antioxidant defense system to combat adverse effects of salinity stress. In order to quantify the Si-mediated salinity tolerance, we studied the role of Si (200 ppm) applied through rooting media on antioxidant battery system of barley genotypes; B-10008 (salt-tolerant) and B-14011 (salt-sensitive) subjected to salt stress (200 mM NaCl). A significant decline in the accumulation of shoot (35–74%) and root (30–85%) biomass was observed under salinity stress, while Si application through rooting media enhancing biomass accumulation of shoots (33–49%) and root (32–37%) under salinity stress. The over-accumulation reactive oxygen species i.e., hydrogen peroxide (H2O2) is an inevitable process resulting into lipid peroxidation, which was evident by enhanced malondialdehyde levels (13–67%) under salinity stress. These events activated a defense system, which was marked by higher levels of total soluble proteins and uplifted activities of antioxidants enzymatic (SOD, POD, CAT, GR and APX) and non-enzymatic (α-tocopherol, total phenolics, AsA, total glutathione, GSH, GSSG and proline) in roots and leaves under salinity stress. The Si application through rooting media further strengthened the salt stressed barley plant’s defense system by up-regulating the activities of enzymatic and non-enzymatic antioxidant in order to mitigate excessive H2O2 efficiently. The results revealed that although salt-tolerant genotype (B-10008) was best adopted to tolerate salt stress, comparably the response of salt-sensitive genotype (B-14011) was more prominent (accumulation of antioxidant) after application of Si through rooting media under salinity stress.
Antidiabetic Medicinal Plants Used in the Eastern Cape Province of South Africa: An Updated Review
Authors: Sagbo Idowu Jonas , Hussein Ahmed A.
Published: September 2022

Oral antidiabetic drugs are usually costly and are associated with several adverse side effects. This has led to the use of medicinal plants that are considered to have multiple therapeutic targets and are readily accessible. In the Eastern Cape province of South Africa, the number of people using medicinal plants for the management of diabetes has been climbing steadily over the past two decades due to their cultural acceptability, accessibility, affordability, efficacy, and safety claims. In this study, a review of antidiabetic medicinal plants used in the Eastern Cape province of South Africa was conducted. A comprehensive literature survey was thoroughly reviewed using several scientific databases, ethnobotanical books, theses and dissertations. About forty-eight (48) plant species were identified as being used to treat diabetes by the people of Eastern Cape province. Among the plant species, only eight (8) species have not been scientifically evaluated for their antidiabetic activities and twenty antidiabetic compounds were isolated from these medicinal plants. This review has confirmed the use and potential of the antidiabetic medicinal plants in the Eastern Cape province and identified several promising species for further scientific investigation.
Prediction of Strawberry Dry Biomass from UAV Multispectral Imagery Using Multiple Machine Learning Methods
Authors: Zheng Caiwang , Abd-Elrahman Amr , Whitaker Vance , Dalid Cheryl
Published: September 2022

Biomass is a key biophysical parameter for precision agriculture and plant breeding. Fast, accurate and non-destructive monitoring of biomass enables various applications related to crop growth. In this paper, strawberry dry biomass weight was modeled using 4 canopy geometric parameters (area, average height, volume, standard deviation of height) and 25 spectral variables (5 band original reflectance values and 20 vegetation indices (VIs)) extracted from the Unmanned Aerial Vehicle (UAV) multispectral imagery. Six regression techniques—multiple linear regression (MLR), random forest (RF), support vector machine (SVM), multivariate adaptive regression splines (MARS), eXtreme Gradient Boosting (XGBoost) and artificial neural network (ANN)—were employed and evaluated for biomass prediction. The ANN had the highest accuracy in a five-fold cross-validation, with R2 of 0.89~0.93, RMSE of 7.16~8.98 g and MAE of 5.06~6.29 g. As for the other five models, the addition of VIs increased the R2 from 0.77~0.80 to 0.83~0.86, and reduced the RMSE from 8.89~9.58 to 7.35~8.09 g and the MAE from 6.30~6.70 to 5.25~5.47 g, respectively. Red-edge-related VIs, including the normalized difference red-edge index (NDRE), simple ratio vegetation index red-edge (SRRedEdge), modified simple ratio red-edge (MSRRedEdge) and chlorophyll index red and red-edge (CIred&RE), were the most influential VIs for biomass modeling. In conclusion, the combination of canopy geometric parameters and VIs obtained from the UAV imagery was effective for strawberry dry biomass estimation using machine learning models.
Distribution and Driving Force of Water Use Efficiency under Vegetation Restoration on the Loess Plateau
Authors: Ma Ruixue , Wang Dacheng , Cui Ximin , Yao Xiaojing , Li Shenshen , Wang Hongsen , Liu Bingxuan
Published: September 2022

The Grain for Green Project (GGP) has considerably improved the vegetation cover of the Loess Plateau, as well as changed the carbon and water coupling process of local vegetation to a certain extent. Water use efficiency (WUE) is a crucial measure for evaluating ecosystem responses to global climate change and is a key indicator of the carbon–water coupling between terrestrial ecosystems and the environment. A comprehensive understanding of the impact of vegetation reconstruction on WUE on the Loess Plateau is of great significance to the vegetation growth and contribution to sustainable of the Loess Plateau. In recent years, scholars have gained a more comprehensive understanding of the distribution and drivers of WUE on the Loess Plateau. However, through the study of carbon and water coupling in the Loess Plateau, it is found that the effects of different vegetation restoration levels on WUE are still to be studied in depth in terms of spatial and temporal heterogeneity and long timeseries. In this paper, we analyzed the trends of Normalized Difference vegetation cover (NDVI) and WUE from 2001 to 2010 and 2011 to 2020, respectively, to research at the WUE of the vegetation in this area in relation to vegetation restoration. It was found that the Loess Plateau’s vegetation WUE rose from 2001 to 2020 at a rate of 0.023 g C kg−1 H2O per year, and that the increase from 2011 to 2020 was more significant than the growth from 2000 to 2010. The Loess Plateau’s area with a growing trend in vegetation water use rate increased from 77.12% in 2001–2010 to 88.63% in 2011–2020, with the majority of the increased area occurring in the northeastern Inner Mongolia region. After 20 years of the reforestation project, the area where NDVI and WUE increased simultaneously accounted for 71.54% of the Loess Plateau, the area where NDVI increased but WUE decreased accounted for 10.95% of the Loess Plateau, and the area where NDVI increased but WUE decreased accounted for 7.15% of the Loess Plateau. The correlation between temperature precipitation and WUE was not significant for the whole Loess Plateau, further indicating that the increase in vegetation cover was the main reason for the increase in vegetation water efficiency. Therefore, the effect of vegetation cover on WUE should be fully considered when vegetation restoration is carried out on the Loess Plateau.
Multi-Feature Information Complementary Detector: A High-Precision Object Detection Model for Remote Sensing Images
Authors: Wang Jiaqi , Gong Zhihui , Liu Xiangyun , Guo Haitao , Lu Jun , Yu Donghang , Lin Yuzhun
Published: September 2022

Remote sensing for image object detection has numerous important applications. However, complex backgrounds and large object-scale differences pose considerable challenges in the detection task. To overcome these issues, we proposed a one-stage remote sensing image object detection model: a multi-feature information complementary detector (MFICDet). This detector contains a positive and negative feature guidance module (PNFG) and a global feature information complementary module (GFIC). Specifically, the PNFG is used to refine features that are beneficial for object detection and explore the noisy features in a complex background of abstract features. The proportion of beneficial features in the feature information stream is increased by suppressing noisy features. The GFIC uses pooling to compress the deep abstract features and improve the model’s ability to resist feature displacement and rotation. The pooling operation has the disadvantage of losing detailed feature information; thus, dilated convolution is introduced for feature complementation. Dilated convolution increases the receptive field of the model while maintaining an unchanged spatial resolution. This can improve the ability of the model to recognize long-distance dependent information and establish spatial location relationships between features. The detector proposed also improves the detection performance of objects at different scales in the same image using a dual multi-scale feature fusion strategy. Finally, classification and regression tasks are decoupled in space using a decoupled head. We experimented on the DIOR and NWPU VHR-10 datasets to demonstrate that the newly proposed MFICDet achieves competitive performance compared to current state-of-the-art detectors.
Coupled Tensor Block Term Decomposition with Superpixel-Based Graph Laplacian Regularization for Hyperspectral Super-Resolution
Authors: Liu Hongyi , Jiang Wen , Zha Yuchen , Wei Zhihui
Published: September 2022

Hyperspectral image (HSI) super-resolution aims at improving the spatial resolution of HSI by fusing a high spatial resolution multispectral image (MSI). To preserve local submanifold structures in HSI super-resolution, a novel superpixel graph-based super-resolution method is proposed. Firstly, the MSI is segmented into superpixel blocks to form two-directional feature tensors, then two graphs are created using spectral–spatial distance between the unfolded feature tensors. Secondly, two graph Laplacian terms involving underlying BTD factors of high-resolution HSI are developed, which ensures the inheritance of the spatial geometric structures. Finally, by incorporating graph Laplacian priors with the coupled BTD degradation model, a HSI super-resolution model is established. Experimental results demonstrate that the proposed method achieves better fused results compared with other advanced super-resolution methods, especially on the improvement of the spatial structure.
Seasonal Mapping of Irrigated Winter Wheat Traits in Argentina with a Hybrid Retrieval Workflow Using Sentinel-2 Imagery
Authors: Caballero Gabriel , Pezzola Alejandro , Winschel Cristina , Casella Alejandra , Sanchez Angonova Paolo , Rivera-Caicedo Juan Pablo , Berger Katja , Verrelst Jochem , Delegido Jesus
Published: September 2022

Earth observation offers an unprecedented opportunity to monitor intensively cultivated areas providing key support to assess fertilizer needs and crop water uptake. Routinely, vegetation traits mapping can help farmers to monitor plant development along the crop’s phenological cycle, which is particularly relevant for irrigated agricultural areas. The high spatial and temporal resolution of the Sentinel-2 (S2) multispectral instrument leverages the possibility to estimate leaf area index (LAI), canopy chlorophyll content (CCC), and vegetation water content (VWC) from space. Therefore, our study presents a hybrid retrieval workflow combining a physically-based strategy with a machine learning regression algorithm, i.e., Gaussian processes regression, and an active learning technique to estimate LAI, CCC and VWC of irrigated winter wheat. The established hybrid models of the three traits were validated against in-situ data of a wheat campaign in the Bonaerense valley, South of the Buenos Aires Province, Argentina, in the year 2020. We obtained good to highly accurate validation results with LAI: R2 = 0.92, RMSE = 0.43 m2 m−2, CCC: R2 = 0.80, RMSE = 0.27 g m−2 and VWC: R2 = 0.75, RMSE = 416 g m−2. The retrieval models were also applied to a series of S2 images, producing time series along the seasonal cycle, which reflected the effects of fertilizer and irrigation on crop growth. The associated uncertainties along with the obtained maps underlined the robustness of the hybrid retrieval workflow. We conclude that processing S2 imagery with optimised hybrid models allows accurate space-based crop traits mapping over large irrigated areas and thus can support agricultural management decisions.
Analysis of the Long-Term Characteristics of BDS On-Orbit Satellite Atomic Clock: Since BDS-3 Was Officially Commissioned
Authors: Liang Yifeng , Xu Jiangning , Wu Miao , Li Fangneng
Published: September 2022

Satellite atomic clocks are the key elements for position, navigation, and timing services of the Global navigation satellite system (GNSS); it is necessary to research the characteristics of BDS-3 on-orbit satellite atomic clocks for their further optimization. In this study, clock offset data with a duration of 620 days since BDS-3 was officially commissioned were applied to long-term characteristic analysis. To begin with, the precision clock offset data of Deutsches geoforschungs zentrum (GFZ) processed by a MAD-based method were used as reliable test data. Herein, the working principle and main characteristics of satellite atomic clocks are analyzed and discussed, and thus, a comprehensive long-term characteristic analysis scheme is designed. On this basis, the performance indicators—mainly including physical parameters, periodic characteristics, frequency drift rate, frequency accuracy, frequency stability—were calculated and analyzed respectively, revealing the long-term characteristics of the BDS in orbit satellite atomic clocks during the test period. The results of experimental data testify that the performance of BDS-3 satellite atomic clocks is significantly superior to that of BDS-2, especially in terms of drift rate and frequency stability, and the performance of passive hydrogen maser (PHM) is generally superior to that of rubidium atomic frequency standards (RAFS). Within about half a year since BDS-3 was officially commissioned, the frequency stability of BDS-3 satellite atomic clock gradually improved and then reached the order of 10−15, reflecting the effectiveness of system maintenance and inter-satellite link. Furthermore, some novel conclusions are drawn, such as the long-term period term of the fitting residual and drift rate, which may be caused by the earth’s revolution.
Enhanced Multi-Stream Remote Sensing Spatiotemporal Fusion Network Based on Transformer and Dilated Convolution
Authors: Li Weisheng , Cao Dongwen , Xiang Minghao
Published: September 2022

Remote sensing images with high temporal and spatial resolutions play a crucial role in land surface-change monitoring, vegetation monitoring, and natural disaster mapping. However, existing technical conditions and cost constraints make it very difficult to directly obtain remote sensing images with high temporal and spatial resolution. Consequently, spatiotemporal fusion technology for remote sensing images has attracted considerable attention. In recent years, deep learning-based fusion methods have been developed. In this study, to improve the accuracy and robustness of deep learning models and better extract the spatiotemporal information of remote sensing images, the existing multi-stream remote sensing spatiotemporal fusion network MSNet is improved using dilated convolution and an improved transformer encoder to develop an enhanced version called EMSNet. Dilated convolution is used to extract time information and reduce parameters. The improved transformer encoder is improved to further adapt to image-fusion technology and effectively extract spatiotemporal information. A new weight strategy is used for fusion that substantially improves the prediction accuracy of the model, image quality, and fusion effect. The superiority of the proposed approach is confirmed by comparing it with six representative spatiotemporal fusion algorithms on three disparate datasets. Compared with MSNet, EMSNet improved SSIM by 15.3% on the CIA dataset, ERGAS by 92.1% on the LGC dataset, and RMSE by 92.9% on the AHB dataset.
Estimating Regional PM2.5 Concentrations in China Using a Global-Local Regression Model Considering Global Spatial Autocorrelation and Local Spatial Heterogeneity
Authors: Su Heng , Chen Yumin , Tan Huangyuan , Zhou Annan , Chen Guodong , Chen Yuejun
Published: September 2022

Linear regression models are commonly used for estimating ground PM2.5 concentrations, but the global spatial autocorrelation and local spatial heterogeneity of PM2.5 distribution are either ignored or only partially considered in commonly used models for estimating PM2.5 concentrations. Therefore, taking both global spatial autocorrelation and local spatial heterogeneity into consideration, a global-local regression (GLR) model is proposed for estimating ground PM2.5 concentrations in the Yangtze River Delta (YRD) and in the Beijing, Tianjin, Hebei (BTH) regions of China based on the aerosol optical depth data, meteorological data, remote sensing data, and pollution source data. Considering the global spatial autocorrelation, the GLR model extracts global factors by the eigenvector spatial filtering (ESF) method, and combines the fraction of them that passes further filtering with the geographically weighted regression (GWR) method to address the local spatial heterogeneity. Comprehensive results show that the GLR model outperforms the ordinary GWR and ESF models, and the GLR model has the best performance at the monthly, seasonal, and annual levels. The average adjusted R2 of the monthly GLR model in the YRD region (the BTH region) is 0.620 (0.853), which is 8.0% and 7.4% (6.8% and 7.0%) higher than that of the monthly ESF and GWR models, respectively. The average cross-validation root mean square error of the monthly GLR model is 7.024 μg/m3 in the YRD region, and 9.499 μg/m3 in the BTH region, which is lower than that of the ESF and GWR models. The GLR model can effectively address the spatial autocorrelation and spatial heterogeneity, and overcome the shortcoming of the ordinary GWR model that overfocuses on local features and the disadvantage of the poor local performance of the ordinary ESF model. Overall, the GLR model with good spatial and temporal applicability is a promising method for estimating PM2.5 concentrations.
Evaluation of Remote Sensing-Based Evapotranspiration Datasets for Improving Hydrological Model Simulation in Humid Region of East China
Authors: Pan Suli , Xu Yue-Ping , Gu Haiting , Yu Bai , Xuan Weidong
Published: September 2022

Conventional calibration methods used in hydrological modelling are based on runoff observations at the basin outlet. However, calibration with only runoff often produces reasonable runoff but poor results for other hydrological variables. Multi-variable calibration with both runoff and remote sensing-based evapotranspiration (ET) is developed naturally, due to the importance of ET and its data availability. This study compares two main calibration schemes: (1) calibration with only runoff (Scheme I) and (2) multi-variable calibration with both runoff and remote sensing-based ET (Scheme II). ET data are obtained from three remote sensing-based ET datasets, namely Penman–Monteith–Leuning (PML), FLUXCOM, and the Global Land Evaporation Amsterdam Model (GLEAM). The aforementioned calibration schemes are applied to calibrate the parameters of the Distributed Hydrology Soil Vegetation Model (DHSVM) through ε-dominance non-dominated sorted genetic algorithm II (ε-NSGAII). The results show that all three ET datasets have good performance for areal ET in the study area. The DHSVM model calibrated based on Scheme I produces acceptable performance in runoff simulation (Kling–Gupta Efficiency, KGE = 0.87), but not for ET simulation (KGE < 0.7). However, reasonable simulations can be achieved for both variables based on Scheme II. The KGE value of runoff simulation can reach 0.87(0.91), 0.72(0.85), and 0.75(0.86) in the calibration (validation) period based on Scheme II (PML), Scheme II (FLUXCOM), and Scheme II (GLEAM), respectively. Simultaneously, ET simulations are greatly improved both in the calibration and validation periods. Furthermore, incorporating ET data into all three Scheme II variants is able to improve the performance of extreme flow simulations (including extreme low flow and high flow). Based on the improvement of the three datasets in extreme flow simulations, PML can be utilized for multi-variable calibration in drought forecasting, and FLUXCOM and GLEAM are good choices for flood forecasting.
The 2021 Mw6.7 Lake Hovsgol (Mongolia) Earthquake: Irregular Normal Faulting with Slip Partitioning Controlled by an Adjacent Strike-Slip Fault
Authors: He Yuqing , Wang Teng , Zhao Li
Published: September 2022

In transtensional regions, structures striking obliquely to the extension direction generally exhibit oblique or partitioned slips. However, their on-fault partitioning patterns and controlling factors are less known, hindering our understanding of the evolution of the rifting process. Here, we study the slip distribution of the 2021 Mw6.7 Lake Hovsgol (Mongolia) earthquake occurred in a pull-apart basin using InSAR observations. Our preferred slip model shows a remarkable feature, with three zones exhibiting distinct slip directions at different depths. The Coulomb stress change analysis reveals that this pattern is likely controlled by the left-lateral motion of the Mondy Fault to the north, which also inhibits the growth of a boundary fault to the east of the lake, shaping the asymmetric graben structure in this region. Our results imply the important role of major strike-slip faults bounding the pull-apart basin in the formation and evolution of the oblique rift.
Spatiotemporal Variation of Actual Evapotranspiration and Its Relationship with Precipitation in Northern China under Global Warming
Authors: Su Tao , Sun Siyuan , Wang Shuting , Xie Dexiao , Li Shuping , Huang Bicheng , Ma Qianrong , Qian Zhonghua , Feng Guolin , Feng Taichen
Published: September 2022

The analysis of actual evapotranspiration (ETa) changes is of great significance for the utilization and allocation of water resources. In this study, ETa variability in northern China (aridity index < 0.65) is investigated based on the average of seven datasets (GLEAM, GLASS, a complementary relationship-based dataset, CRA-40, MERRA2, JRA-55, and ERA5-Land). The results show that ETa increases significantly from 1982 to 2017. Limited by water supply, ETa is significantly correlated with precipitation (R = 0.682), whereas the increase in precipitation is insignificant (p = 0.151). Spatially, the long-term trend of ETa is also not completely consistent with that of precipitation. According to a singular value decomposition (SVD) analysis, the trend of ETa is mainly related to the first four leading SVD modes. Homogeneous correlation patterns indicate that more precipitation generally leads to high ETa; however, this relationship is modulated by other factors. Overall, positive potential evapotranspiration anomalies convert more surface water into ETa, resulting in a higher increase in ETa than in precipitation. Specifically, ETa in the northern Tibetan Plateau is associated with meltwater generated by rising temperatures, and ETa in the Badain Jaran Desert is highly dependent on the wet-day frequency. Under global warming, the inconsistency between ETa and precipitation changes has a great impact on water resources in northern China.
Pulse Radar Imaging Method in an Anechoic Chamber Based on an Amplitude Modulation Design
Authors: Xie Ailun , Liu Xiaobin , Zhao Feng , Xiao Shunping
Published: September 2022

The application of a pulse radar in anechoic chamber imaging is a new way to obtain the electromagnetic characteristics of targets. However, the limited size of an anechoic chamber causes the coupling between the transmitted signal and echo so the target image cannot be accurately achieved. To solve this problem, an imaging method using a pulse radar in an anechoic chamber based on an amplitude modulation design is proposed in this paper. Firstly, amplitude modulation is performed to solve the coupling of the transmitted signal and echo. In order to cancel the false targets in the target image after the amplitude modulation, different amplitude modulation sequences are designed. Secondly, echo processing based on the designed amplitude modulation is discussed to obtain the target image. Simulations and experiments are conducted and the results show that the proposed amplitude design and echo processing method can accurately obtain the target image in an anechoic chamber.
Stress, Anxiety, and Depression in Pre-Clinical Medical Students: Prevalence and Association with Sleep Disorders
Authors: Alrashed Fahad Abdulaziz , Alsubiheen Abdulrahman M. , Alshammari Hessah , Mazi Sarah Ismail , Al-Saud Sara Abou , Alayoubi Samha , Kachanathu Shaji John , Albarrati Ali , Aldaihan Mishal M. , Ahmad Tauseef , Sattar Kamran , Khan Shakir , Dhiman Gaurav
Published: September 2022

Our aim was to assess sleep quality in different subgroups of preclinical medical students, and then to identify specific lifestyle factors, academic and social factors as well as Corona virus related factors that were associated with poor sleeping quality and poor psychological health. Study participants were all medical students at King Saud University of Medical Sciences in the first and second years (648 students), and the study was conducted from December 2021 to January 2022. We administered the survey on paper as well as online. We used three types of questionnaires in this study. The first was a self-administered questionnaire, the second was a validated Insomnia Severity Index (ISI) for finding sleeping problems, and the third was a validated DASS 10 for determining Depression, Anxiety, and Stress. A total of 361 pre-clinical medical students consisted of 146 (40.4%) males and 215 (59.5%) females. The majority of the students, 246 (68.1%), were in their second year. Furthermore, in the current study, students who had poor academic performance (15.8%), satisfactory academic performance (21.3%), or good academic performance (30.7%) had significant sleeping problems found (χ2 = 19.4; p = 0.001), among them poor academic performance students 21.6%, satisfactory academic performance students (29.3%), and good academic performance students (29.3%) had moderate to severe levelled sleeping problems. Similarly, poor, satisfactory, and good academic performers experienced the highest levels of anxiety (poor = 21.5%; satisfactory = 22.1%; and good = 22.8%); stress (poor = 22.4%; satisfactory = 25.2%; and good = 22.4%); and depression (poor = 40.5%; satisfactory = 40.5%; and good = 11.9%). The majority of students (64.8%) reported that during the pandemic crisis their anxiety levels were high. Additionally, students reported significantly high sleeping issues (χ2 = 10.6; p = 0.001) and also serious psychological issues (Anxiety = 34.9 (0.000); Stress = 32.5 (0.000); and Depression = 5.42 (0.01)). There was a high prevalence of sleep issues, anxiety, stress, and depression among the pre-clinical medical students, with significantly higher sleeping disorders, anxiety, stress, and depression levels among those medical students who struggle with their academic performances, poor lifestyle factor, and poor Social and COVID management.
Orangutan Ecotourism on Sumatra Island: Current Conditions and a Call for Further Development
Authors: Purwoko Agus , Kuswanda Wanda , Situmorang Rospita Odorlina Pilianna , Hutapea Freddy Jontara , Saputra Muhammad Hadi , Pasaribu Parlin Hotmartua Putra
Published: September 2022

This paper aimed to provide a narrative review of the current conditions of orangutan ecotourism on Sumatra Island, problems in the current management systems, and some recommendations for further development. Orangutan conservation centers have been developed on Sumatra Island since 1973. The Bukit Lawang Conservation Station is one of the orangutan conservation centers that have practiced ecotourism to overcome ecological and socio-economic issues. Even though the Bukit Lawang Conservation Station has operated for decades, this station has faced several issues, in particular a monetary crisis in 1997, a flash flood in 2003, and the COVID-19 pandemic. We identified that orangutan conservation centers on Sumatra Island have the potential to support orangutan ecotourism. These conservation centers have ecological support, available facilities, and rich local wisdom that can provide added value for orangutan ecotourism. Therefore, we propose that the development of orangutan ecotourism on Sumatra Island should accommodate surrounding communities through community-based wildlife ecotourism. We also recommend the following strategies to develop orangutan ecotourism on Sumatra Island: (1) mapping the location and distribution of wild orangutans in their natural habitats; (2) managing captive and semi-captive orangutans in conservation centers; (3) provision of tour packages; (4) community empowerment; (5) institutional strengthening of community-based ecotourism management (CBEM); (6) developing ecotourism through a benefit-sharing model; (7) anticipating and minimizing the negative impacts of ecotourism on orangutans; and (8) integrating orangutan tourism with local wisdom.
Metal-Tolerant Bacteria of Wastewater Treatment Plant in a Large City
Authors: Perelomov Leonid , Sizova Olga , Rahman Mohammad Mahmudur , Perelomova Irina , Minkina Tatiana , Sokolov Sergei , Atroshchenko Yury
Published: September 2022

Biological treatment methods are the most important part of the treatment process for domestic wastewater, the amounts of which are increasing every year due to rapid, unregulated urbanization and the rising number of people living in such areas. At the same time, microorganisms existing in treatment facilities should not only effectively utilize organic pollutants, but also be resistant to a variety of organic and inorganic contaminants. This study’s objective is to isolate and identify—using molecular genetic techniques—strains of bacteria that tolerate concentrations of heavy metals (Ni, Cd, Pb, Zn and Cu) in the 3–5 mM range. They were sourced from water and sludge samples obtained from sewage treatment facilities in a large city. Outcomes of phylogenetic analysis of 16S rRNA gene sequences revealed that tolerant strains of bacteria belonged to the genera Pseudomonas, Serratia and Klebsiella; strains belonging to the genus Pseudomonas dominated. Of ten resistant strains, nine were isolated from sludge and water samples of the secondary sedimentation tank, and the other one from a treatment plant’s digester. Changes in the color of microorganisms’ colonies became evident when cultivated on media enriched with heavy metals. Cultivating nonpathogenic strains of these bacteria and their introduction into communities of other activated sludge microorganisms could have practical application to biological decontamination of wastewater.