bluuebunny/crossref_metadata_2025 huggingface dataset:
Dietary Chloride Deficiency Syndrome: Pathophysiology, History, and Systematic Literature Review
Authors: Signorelli Giulia C. , Bianchetti Mario G. , Jermini Luca M. M. , Agostoni Carlo , Milani Gregorio P. , Simonetti Giacomo D. , Lava Sebastiano A. G.
Published: November 2020

Metabolic alkalosis may develop as a consequence of urinary chloride (and sodium) wasting, excessive loss of salt in the sweat, or intestinal chloride wasting, among other causes. There is also a likely underrecognized association between poor salt intake and the mentioned electrolyte and acid–base abnormality. In patients with excessive loss of salt in the sweat or poor salt intake, the maintenance of metabolic alkalosis is crucially modulated by the chloride–bicarbonate exchanger pendrin located on the renal tubular membrane of type B intercalated cells. In the late 1970s, recommendations were made to decrease the salt content of foods as part of an effort to minimize the tendency towards systemic hypertension. Hence, the baby food industry decided to remove added salt from formula milk. Some weeks later, approximately 200 infants (fed exclusively with formula milks with a chloride content of only 2–4 mmol/L), were admitted with failure to thrive, constipation, food refusal, muscular weakness, and delayed psychomotor development. The laboratory work-up disclosed metabolic alkalosis, hypokalemia, hypochloremia, and a reduced urinary chloride excretion. In all cases, both the clinical and the laboratory features remitted in ≤7 days when the infants were fed on formula milk with a normal chloride content. Since 1982, 13 further publications reported additional cases of dietary chloride depletion. It is therefore concluded that the dietary intake of chloride, which was previously considered a “mendicant” ion, plays a crucial role in acid–base and salt balance.
Protein Labelling Accuracy for UK Patients with PKU Following a Low Protein Diet
Authors: Kraleva Dilyana , Evans Sharon , Pinto Alex , Daly Anne , Ashmore Catherine , Pointon-Bell Kiri , Rocha Júlio César , MacDonald Anita
Published: November 2020

A phenylalanine (protein)-restricted diet is the primary treatment for phenylketonuria (PKU). Patients are dependent on food protein labelling to successfully manage their condition. We evaluated the accuracy of protein labelling on packaged manufactured foods from supermarket websites for foods that may be eaten as part of a phenylalanine-restricted diet. Protein labelling information was evaluated for 462 food items (“free from”, n = 159, regular, n = 303), divided into 16 food groups using supermarket website data. Data collection included protein content per portion/100 g when food was “as sold”, “cooked” or “prepared”; cooking methods, and preparation instructions. Labelling errors affecting protein content were observed in every food group, with overall protein labelling unclear in 55% (n = 255/462) of foods. There was misleading, omitted, or erroneous (MOE) information in 43% (n = 68/159) of “free from” foods compared with 62% (n = 187/303) of regular foods, with fewer inaccuracies in “free from” food labelling (p = 0.007). Protein analysis was available for uncooked weight only but not cooked weight for 58% (n = 85/146) of foods; 4% (n = 17/462) had misleading protein content. There was a high rate of incomplete, misleading, or inaccurate data affecting the interpretation of the protein content of food items on supermarket websites. This could adversely affect metabolic control of patients with PKU and warrants serious consideration.
Sodium and Potassium Intake and Cardiovascular Disease in Older People: A Systematic Review
Authors: Gonçalves Carla , Abreu Sandra
Published: November 2020

This review aims to examine the relationship of sodium and potassium intake and cardiovascular disease (CVD) among older people. Methods: We performed a literature search using PubMed and Web of Science (January 2015 to July 2020) without language restriction. Observational and experimental studies that reported the relationship between sodium, potassium, or sodium-to-potassium ratio with CVD among older adults aged higher than 60 years were included. The authors independently screened all identified studies, extracted information, and assessed the quality of included studies. Risk of bias was assessed using the Risk of Bias Assessment Tool for Nonrandomized Studies (RoBANS) for observational studies and the revised Cochrane risk-of-bias tool (RoB 2 tool) for randomized trials. Results: We included 12 studies (6 prospective cohort studies, 5 cross-sectional studies, and 1 experimental study). Five of the studies reported on sodium-to-potassium ratio (n = 5), and the others on potassium and/or sodium intake. Cardiovascular events (e.g., stroke and heart failure) were the most reported outcome (n = 9). Of the 12 studies included, five observational studies had low bias risk and the randomized controlled trial was judged as uncertain risk of bias. We found inconsistent results for the effect of the reduction of sodium intake in this population for lower risk of CVD. We found that both the increase of potassium intake and the decrease of sodium-to-potassium ratio were associated with lower risk of hypertension and CVD, particularly stroke. Conclusion: The present review suggests that both higher potassium and lower sodium-to-potassium ratio are associated with lower risk of CVD.
Anti-Vascular Inflammatory Effect of Ethanol Extract from Securinega suffruticosa in Human Umbilical Vein Endothelial Cells
Authors: Han Byung Hyuk , Song Chun Ho , Yoon Jung Joo , Kim Hye Yoom , Seo Chang Seob , Kang Dae Gill , Lee Yun Jung , Lee Ho Sub
Published: November 2020

Securiniga suffruticosa is known as a drug that has the effect of improving the blood circulation and relaxing muscles and tendons, thereby protects and strengthen kidney and spleen. Therefore, in this study, treatment of Securiniga suffruticosa showed protective effect of inhibiting the vascular inflammation in human umbilical vein endothelial cells (HUVECs) by inducing nitric oxide (NO) production and endothelial nitric oxide synthase (eNOS) coupling pathway. In this study, Securiniga suffruticosa suppressed TNF-α (Tumor necrosis factor–α) induced protein and mRNA levels of cell adhesion molecules such as intracellular adhesion molecule-1 (ICAM-1), vascular cell adhesion molecule-1 (VCAM-1) and Interleukin-6 (IL-6). Pretreatment of HUVEC with Securiniga suffruticosa decreased the adhesion of HL-60 cells to Ox-LDL (Oxidized Low-Density-Lipoprotein)-induced HUVEC. Moreover, Securiniga suffruticosa inhibited TNF-α induced intracellular reactive oxygen species (ROS) production. Securiniga suffruticosa also inhibited phosphorylation of IκB-α in cytoplasm and translocation of NF-κB (Nuclear factor-kappa B) p65 to the nucleus. Securiniga suffruticosa increased NO production, as well increased the phosphorylation of eNOS and Akt (protein kinase B) which are related with NO production. In addition, Securiniga suffruticosa increased the protein expression of GTPCH (Guanosine triphosphate cyclohydrolase Ⅰ) and the production of BH4 in HUVEC which are related with eNOS coupling pathway. In conclusion, Securiniga suffruticosa has a protective effect against vascular inflammation and can be a potential therapeutic agent for early atherosclerosis.
Developments in Carbohydrate-Based Metzincin Inhibitors
Authors: Cuffaro Doretta , Nuti Elisa , D’Andrea Felicia , Rossello Armando
Published: November 2020

Matrix metalloproteinases (MMPs) and A disintegrin and Metalloproteinase (ADAMs) are zinc-dependent endopeptidases belonging to the metzincin superfamily. Upregulation of metzincin activity is a major feature in many serious pathologies such as cancer, inflammations, and infections. In the last decades, many classes of small molecules have been developed directed to inhibit these enzymes. The principal shortcomings that have hindered clinical development of metzincin inhibitors are low selectivity for the target enzyme, poor water solubility, and long-term toxicity. Over the last 15 years, a novel approach to improve solubility and bioavailability of metzincin inhibitors has been the synthesis of carbohydrate-based compounds. This strategy consists of linking a hydrophilic sugar moiety to an aromatic lipophilic scaffold. This review aims to describe the development of sugar-based and azasugar-based derivatives as metzincin inhibitors and their activity in several pathological models.
Bioinspired Composite, pH-Responsive Sodium Deoxycholate Hydrogel and Generation 4.5 Poly(amidoamine) Dendrimer Improves Cancer Treatment Efficacy via Doxorubicin and Resveratrol Co-Delivery
Authors: Mekonnen Tefera Worku , Andrgie Abegaz Tizazu , Darge Haile Fentahun , Birhan Yihenew Simegniew , Hanurry Endiries Yibru , Chou Hsiao-Ying , Lai Juin-Yih , Tsai Hsieh-Chih , Yang Jen Ming , Chang Yen-Hsiang
Published: November 2020

Maximizing the antitumor efficacy of doxorubicin (DOX) with a new drug delivery strategy is always desired in the field of biomedical science. Because the clinical applications of DOX in the treatment of cancer is limited by the side effects related to the dose. Herein, we report the co-loading of DOX and resveratrol (RESV) using an injectable in situ formed sodium deoxycholate hydrogel (Na-DOC-hyd) at the pH of the tumor extracellular microenvironment. The sequential, controlled, and sustained release of RESV and DOX for synergistic antitumor effects was confirmed by entrapping G4.5-DOX in the RESV-loaded Na-DOC hydrogel (Na-DOC-hyd-RESV). The synergistic antitumor activity of Na-DOC-hyd-RESV+G4.5-DOX was assessed on HeLa cell xenograft tumor in BALB/c nude mice. In the MTT biocompatibility assay, both the G4.5 PAMAM dendrimer and Na-DOC-hyd exhibited negligible cytotoxicity up to the highest dose of 2.0 mg mL−1 in HeLa, MDA-MB-231, and HaCaT cells. The release profiles of DOX and RESV from the Na-DOC-hyd-RESV+G4.5-DOX confirmed the relatively rapid release of RESV (70.43 ± 1.39%), followed by that of DOX (54.58 ± 0.62%) at pH 6.5 in the 7 days of drug release studies. A single intratumoral injection of Na-DOC-hyd-RESV+G4.5-DOX maximally suppressed tumor growth during the 28 days of the treatment period. Na-DOC-hyd-RESV+G4.5-DOX did not cause any histological damage in the major visceral organs. Therefore, this Na-DOC-hydrogel for dual drugs (DOX and RESV) delivery at the pH of the tumor extracellular microenvironment is a promising, safe, and effective combination for antitumor chemotherapy.
Antimicrobial Peptide against Mycobacterium Tuberculosis That Activates Autophagy Is an Effective Treatment for Tuberculosis
Authors: Peláez Coyotl Erika A. , Barrios Palacios Jacqueline , Muciño Gabriel , Moreno-Blas Daniel , Costas Miguel , Montiel Montes Teresa , Diener Christian , Uribe-Carvajal Salvador , Massieu Lourdes , Castro-Obregón Susana , Espinosa Octavio Ramos , Mata Espinosa Dulce , Barrios-Payan Jorge , León Contreras Juan Carlos , Corzo Gerardo , Hernández-Pando Rogelio , Del Rio Gabriel
Published: November 2020

Mycobacterium tuberculosis (MTB) is the principal cause of human tuberculosis (TB), which is a serious health problem worldwide. The development of innovative therapeutic modalities to treat TB is mainly due to the emergence of multi drug resistant (MDR) TB. Autophagy is a cell-host defense process. Previous studies have reported that autophagy-activating agents eliminate intracellular MDR MTB. Thus, combining a direct antibiotic activity against circulating bacteria with autophagy activation to eliminate bacteria residing inside cells could treat MDR TB. We show that the synthetic peptide, IP-1 (KFLNRFWHWLQLKPGQPMY), induced autophagy in HEK293T cells and macrophages at a low dose (10 μM), while increasing the dose (50 μM) induced cell death; IP-1 induced the secretion of TNFα in macrophages and killed Mtb at a dose where macrophages are not killed by IP-1. Moreover, IP-1 showed significant therapeutic activity in a mice model of progressive pulmonary TB. In terms of the mechanism of action, IP-1 sequesters ATP in vitro and inside living cells. Thus, IP-1 is the first antimicrobial peptide that eliminates MDR MTB infection by combining four activities: reducing ATP levels, bactericidal activity, autophagy activation, and TNFα secretion.
Solid-State Fermentation with Aspergillus niger GH1 to Enhance Polyphenolic Content and Antioxidative Activity of Castilla Rose (Purshia plicata)
Authors: José Carlos De León-Medina , Leonardo Sepúlveda , Jesús Morlett-Chávez , Paola Meléndez-Renteria , Alejandro Zugasti-Cruz , Juan Ascacio-Valdés , Cristóbal Noé Aguilar
Published: November 2020

This work was performed to study Castilla Rose (Purshia plicata) as a potential source of polyphenols obtained by solid-state fermentation (SSF)-assisted extraction using the microorganism Aspergillus niger GH1 and to evaluate the antioxidant activity of the extracted compounds. First, water absorption capacity (WAC) of the plant material, radial growth of the microorganism, determination of best fermentation conditions, and maximum accumulation time of polyphenols were tested. Then, a larger-scale fermentation, polyphenols isolation by column liquid chromatography (Amberlite XAD-16) and recovered compounds identification by HPLC-MS were made. Finally, the antioxidant activity of the recovered compounds was tested by ABTS, DPPH, and lipid oxidation inhibition assays. The best fermentation conditions were temperature 25 °C and inoculum 2 × 106 spores/g, while the maximum extraction time of polyphenols was 24 h (173.95 mg/g). The HPLC/MS analysis allowed the identification of 25 different polyphenolic compounds, and the antioxidant activity of the obtained polyphenols was demonstrated, showing ABTS assay the most effective with inhibition of 94.34%.
Evaluation of Plant-Derived Promoters for Constitutive and Tissue-Specific Gene Expression in Potato
Authors: Miroshnichenko Dmitry , Firsov Aleksey , Timerbaev Vadim , Kozlov Oleg , Klementyeva Anna , Shaloiko Lyubov , Dolgov Sergey
Published: November 2020

Various plant-derived promoters can be used to regulate ectopic gene expression in potato. In the present study, four promoters derived from the potato genome have been characterized by the expression of identical cassettes carrying the fusion with the reporter β-glucuronidase (gusA) gene. The strengths of StUbi, StGBSS, StPat, and StLhca3 promoters were compared with the conventional constitutive CaMV 35S promoter in various organs (leaves, stems, roots, and tubers) of greenhouse-grown plants. The final amount of gene product was determined at the post-transcriptional level using histochemical analysis, fluorometric measurements, and Western blot analysis. The promoter strength comparison demonstrated that the StUbi promoter generally provided a higher level of constitutive β-glucuronidase accumulation than the viral CaMV 35S promoter. Although the StLhca3 promoter was predominantly expressed in a green tissue-specific manner (leaves and stems) while StGBSS and StPat mainly provided tuber-specific activity, a “promoter leakage” was also found. However, the degree of unspecific activity depended on the particular transgenic line and tissue. According to fluorometric data, the functional activity of promoters in leaves could be arranged as follows: StLhca3 > StUbi > CaMV 35S > StPat > StGBSS (from highest to lowest). In tubers, the higher expression was detected in transgenic plants expressing StPat-gusA fusion construct, and the strength order was as follows: StPat > StGBSS > StUbi > CaMV 35S > StLhca3. The observed differences between expression patterns are discussed considering the benefits and limitations for the usage of each promoter to regulate the expression of genes in a particular potato tissue.
Incorporating Space: Protestant Fundamentalism and Astronomical Authorization
Authors: Bielo James S.
Published: November 2020

The problem of authority is vital for understanding the development of Protestant creationism. Two discursive fields have figured centrally in this religious movement’s claims to authoritative knowledge: The Bible and science. The former has been remarkably stable over a century with a continuing emphasis on inerrancy and literalism, while the latter has been more mutable. Creationism’s rejection of scientific evolution has endured, but its orientation to a range of scientific models, technologies, and disciplines has changed. Astronomy is a prime example; once relatively absent in creationist cultural production, it emerged as yet another arena where creationists seek to corrode scientific authority and bolster biblical fundamentalism. Drawing on archival documents of creationist publications and the ongoing media production of an influential creationist ministry based in Kentucky, this article illustrates how creationism has sought to incorporate astronomy into their orbit of religious authorization. Ultimately, the case of incorporating space helps clarify fundamentalism’s machinations of power.
Effectiveness of an Educational Intervention to Teach Spiritual Care to Spanish Nursing Students
Authors: Fernández-Pascual María Dolores , Reig-Ferrer Abilio , Santos-Ruiz Ana
Published: November 2020

Spirituality and spiritual care in professional nursing are conceptualised and recognised as fundamental components of holistic healthcare. Despite the acceptance of and interest in spiritual care, a lack of education and clinical training on the subject limits nurses’ ability to meet patients’ spiritual needs. Consequently, the aim of this study was to analyse the effectiveness of a training programme designed to teach the specific knowledge, attitudes and competencies necessary to provide spiritual care in nursing practice. This study consisted of a one-group pre-post intervention design with two measurement times (baseline/pre-intervention and post-intervention). A teaching activity about spiritual care in nursing practice was designed and implemented (focal groups, open discussion, discussion groups and clinical case studies). The educational intervention was developed by the authors based on a literature review, research and feedback from the undergraduate students. A convenience sample of 369 nursing students at the University of Alicante (Spain) who were enrolled in the teaching subject of Psychology participated in this study. The effectiveness of the teaching activity was assessed through a self-administered 15-item questionnaire. The post-intervention results indicated that the programme was effective in improving knowledge, competencies and attitudes related to spiritual care. The implications of this study for teaching practice and future research are discussed
Special Issue “Hyperspectral Remote Sensing of Agriculture and Vegetation”
Authors: Pascucci Simone , Pignatti Stefano , Casa Raffaele , Darvishzadeh Roshanak , Huang Wenjiang
Published: November 2020

The advent of up-to-date hyperspectral technologies, and their increasing performance both spectrally and spatially, allows for new and exciting studies and practical applications in agriculture (soils and crops) and vegetation mapping and monitoring atregional (satellite platforms) andwithin-field (airplanes, drones and ground-based platforms) scales. Within this context, the special issue has included eleven international research studies using different hyperspectral datasets (from the Visible to the Shortwave Infrared spectral region) for agricultural soil, crop and vegetation modelling, mapping, and monitoring. Different classification methods (Support Vector Machine, Random Forest, Artificial Neural Network, Decision Tree) and crop canopy/leaf biophysical parameters (e.g., chlorophyll content) estimation methods (partial least squares and multiple linear regressions) have been evaluated. Further, drone-based hyperspectral mapping by combining bidirectional reflectance distribution function (BRDF) model for multi-angle remote sensing and object-oriented classification methods are also examined. A review article on the recent advances of hyperspectral imaging technology and applications in agriculture is also included in this issue. The special issue is intended to help researchers and farmers involved in precision agriculture technology and practices to a better comprehension of strengths and limitations of the application of hyperspectral measurements for agriculture and vegetation monitoring. The studies published herein can be used by the agriculture and vegetation research and management communities to improve the characterization and evaluation of biophysical variables and processes, as well as for a more accurate prediction of plant nutrient using existing and forthcoming hyperspectral remote sensing technologies.
A New Approach of Ensemble Learning Technique to Resolve the Uncertainties of Paddy Area through Image Classification
Authors: Lei Tsu Chiang , Wan Shiuan , Wu Shih-Chieh , Wang Hsin-Ping
Published: November 2020

Remote sensing technology has rendered lots of information in agriculture. It has usually been used to monitor paddy growing ecosystems in the past few decades. However, there are uncertainties in data fusion techniques which can be resolved in image classification on paddy rice. In this study, a series of learning concepts integrated by a probability progress Fuzzy Dempster-Shafer (FDS) analysis is presented to upgrade various models and different types of image data which is the goal of this study. More specifically, the study utilized the FDS to generate a series of probability models in the classification of the system. In addition, Logistic Regression (LR), Support Vector Machine (SVM), and Neural Network (NN) approaches are employed into the developed FDS system. Furthermore, two different image types are Satellite Image and Aerial Photo used as the analysis material. The overall classification accuracy has been improved to 97.27%, and the kappa value is 0.93. The overall accuracy of the paddy field image classification for a multi-period of mid-scale satellite images is between 85% and 90%. The overall accuracy of the classification using multi-spectral numerical aerial photos can be between 91% and 95%. The FDS improves the accuracy of the above image classification results.
Spatiotemporal Changes in 3D Building Density with LiDAR and GEOBIA: A City-Level Analysis
Authors: Zięba-Kulawik Karolina , Skoczylas Konrad , Mustafa Ahmed , Wężyk Piotr , Gerber Philippe , Teller Jacques , Omrani Hichem
Published: November 2020

Understanding how, where, and when a city is expanding can inform better ways to make our cities more resilient, sustainable, and equitable. This paper explores urban volumetry using the Building 3D Density Index (B3DI) in 2001, 2010, 2019, and quantifies changes in the volume of buildings and urban expansion in Luxembourg City over the last two decades. For this purpose, we use airborne laser scanning (ALS) point cloud (2019) and geographic object-based image analysis (GEOBIA) of aerial orthophotos (2001, 2010) to extract 3D models, footprints of buildings and calculate the volume of individual buildings and B3DI in the frame of a 100 × 100 m grid, at the level of parcels, districts, and city scale. Findings indicate that the B3DI has notably increased in the past 20 years from 0.77 m3/m2 (2001) to 0.9 m3/m2 (2010) to 1.09 m3/m2 (2019). Further, the increase in the volume of buildings between 2001–2019 was +16 million m3. The general trend of changes in the cubic capacity of buildings per resident shows a decrease from 522 m3/resident in 2001, to 460 m3/resident in 2019, which, with the simultaneous appearance of new buildings and fast population growth, represents the dynamic development of the city.
Spatio-Temporal Evolution, Future Trend and Phenology Regularity of Net Primary Productivity of Forests in Northeast China
Authors: Wang Chunli , Jiang Qun’ou , Deng Xiangzheng , Lv Kexin , Zhang Zhonghui
Published: November 2020

Net Primary Productivity (NPP) is one of the significant indicators to measure environmental changes; thus, the relevant study of NPP in Northeast China, Asia, is essential to climate changes and ecological sustainable development. Based on the Global Production Efficiency (GLO-PEM) model, this study firstly estimated the NPP in Northeast China, from 2001 to 2019, and then analyzed its spatio-temporal evolution, future changing trend and phenology regularity. Over the years, the NPP of different forests type in Northeast China showed a gradual increasing trend. Compared with other different time stages, the high-value NPP (700–1300 gC·m−2·a−1) in Changbai Mountain, from 2017 to 2019, is more widely distributed. For instance, the NPP has an increasing rate of 6.92% compared to the stage of 2011–2015. Additionally, there was a significant advance at the start of the vegetation growth season (SOS), and a lag at the end of the vegetation growth season (EOS), from 2001 to 2019. Thus, the whole growth period of forests in Northeast China became prolonged with the change of phenology. Moreover, analysis on the sustainability of NPP in the future indicates that the reverse direction feature of NPP change will be slightly stronger than the co-directional feature, meaning that about 30.68% of the study area will switch from improvement to degradation. To conclude, these above studies could provide an important reference for the sustainable development of forests in Northeast China.
The Ultra-Short-Term Forecasting of Global Horizonal Irradiance Based on Total Sky Images
Authors: Jiang Junxia , Lv Qingquan , Gao Xiaoqing
Published: November 2020

Solar photovoltaics (PV) has advanced at an unprecedented rate and the global cumulative installed PV capacity is growing exponentially. However, the ability to forecast PV power remains a key technical challenge due to the variability and uncertainty of solar irradiance resulting from the changes of clouds. Ground-based remote sensing with high temporal and spatial resolution may have potential for solar irradiation forecasting, especially under cloudy conditions. To this end, we established two ultra-short-term forecasting models of global horizonal irradiance (GHI) using Ternary Linear Regression (TLR) and Back Propagation Neural Network (BPN), respectively, based on the observation of a ground-based sky imager (TSI-880, Total Sky Imager) and a radiometer at a PV plant in Dunhuang, China. Sky images taken every 1 min (minute) were processed to determine the distribution of clouds with different optical depths (thick, thin) for generating a two-dimensional cloud map. To obtain the forecasted cloud map, the Particle Image Velocity (PIV) method was applied to the two consecutive images and the cloud map was advected to the future. Further, different types of cloud fraction combined with clear sky index derived from the GHI of clear sky conditions were used as the inputs of the two forecasting models. Limited validation on 4 partly cloudy days showed that the average relative root mean square error (rRMSE) of the 4 days ranged from 5% to 36% based on the TLR model and ranged from 12% to 32% based on the BPN model. The forecasting performance of the BPN model was better than the TLR model and the forecasting errors increased with the increase in lead time.
Development of a Seamless Forecast for Solar Radiation Using ANAKLIM++
Authors: Urbich Isabel , Bendix Jörg , Müller Richard
Published: November 2020

A novel approach for a blending between nowcasting and numerical weather prediction (NWP) for the surface incoming shortwave radiation (SIS) for a forecast horizon of 1–5 h is presented in this study. The blending is performed with a software tool called ANAKLIM++ (Adjustment of Assimilation Software for the Reanalysis of Climate Data) which was originally designed for the efficient assimilation of two-dimensional data sets using a variational approach. A nowcasting for SIS was already presented and validated in earlier publications as seamless solar radiation forecast (SESORA). For our blending, two NWP models, namely the ICON (Icosahedral Non-hydrostatic model) from the German weather Service (DWD) and the IFS (Integrated Forecasting System) from the European Centre for Medium-Range Weather Forecasts (ECMWF), were used. The weights for the input data for ANAKLIM++ vary for every single forecast time and pixel, depending on the error growth of the nowcasting. The results look promising, since the root mean square error (RMSE) and mean absolute error (MAE) of the blending are smaller than the error measures of the nowcasting or NWP models, respectively.
An Improved Spatiotemporal Data Fusion Method Using Surface Heterogeneity Information Based on ESTARFM
Authors: Liu Mengxue , Liu Xiangnan , Dong Xiaobin , Zhao Bingyu , Zou Xinyu , Wu Ling , Wei Hejie
Published: November 2020

The use of the spatiotemporal data fusion method as an effective data interpolation method has received extensive attention in remote sensing (RS) academia. The enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM) is one of the most famous spatiotemporal data fusion methods, as it is widely used to generate synthetic data. However, the ESTARFM algorithm uses moving windows with a fixed size to get the information around the central pixel, which hampers the efficiency and precision of spatiotemporal data fusion. In this paper, a modified ESTARFM data fusion algorithm that integrated the surface spatial information via a statistical method was developed. In the modified algorithm, the local variance of pixels around the central one was used as an index to adaptively determine the window size. Satellite images from two regions were acquired by employing the ESTARFM and modified algorithm. Results showed that the images predicted using the modified algorithm obtained more details than ESTARFM, as the frequency of pixels with the absolute difference of mean value of six bands’ reflectance between true observed image and predicted between 0 and 0.04 were 78% by ESTARFM and 85% by modified algorithm, respectively. In addition, the efficiency of the modified algorithm improved and the verification test showed the robustness of the modified algorithm. These promising results demonstrated the superiority of the modified algorithm to provide synthetic images compared with ESTARFM. Our research enriches the spatiotemporal data fusion method, and the automatic selection of moving window strategy lays the foundation of automatic processing of spatiotemporal data fusion on a large scale.
Ensemble of Machine-Learning Methods for Predicting Gully Erosion Susceptibility
Authors: Pal Subodh Chandra , Arabameri Alireza , Blaschke Thomas , Chowdhuri Indrajit , Saha Asish , Chakrabortty Rabin , Lee Saro , Band Shahab. S.
Published: November 2020

Gully formation through water-induced soil erosion and related to devastating land degradation is often a quasi-normal threat to human life, as it is responsible for huge loss of surface soil. Therefore, gully erosion susceptibility (GES) mapping is necessary in order to reduce the adverse effect of land degradation and diminishes this type of harmful consequences. The principle goal of the present research study is to develop GES maps for the Garhbeta I Community Development (C.D.) Block; West Bengal, India, by using a machine learning algorithm (MLA) of boosted regression tree (BRT), bagging and the ensemble of BRT-bagging with K-fold cross validation (CV) resampling techniques. The combination of the aforementioned MLAs with resampling approaches is state-of-the-art soft computing, not often used in GES evaluation. In further progress of our research work, here we used a total of 20 gully erosion conditioning factors (GECFs) and a total of 199 gully head cut points for modelling GES. The variables’ importance, which is responsible for gully erosion, was determined based on the random forest (RF) algorithm among the several GECFs used in this study. The output result of the model’s performance was validated through a receiver operating characteristics-area under curve (ROC-AUC), sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) statistical analysis. The predicted result shows that the ensemble of BRT-bagging is the most well fitted for GES where AUC value in K-3 fold is 0.972, whereas the value of AUC in sensitivity, specificity, PPV and NPV is 0.94, 0.93, 0.96 and 0.93, respectively, in a training dataset, and followed by the bagging and BRT model. Thus, from the predictive performance of this research study it is concluded that the ensemble of BRT-Bagging can be applied as a new approach for further studies in spatial prediction of GES. The outcome of this work can be helpful to policy makers in implementing remedial measures to minimize damages caused by gully erosion.
Modeling and Theoretical Analysis of GNSS-R Soil Moisture Retrieval Based on the Random Forest and Support Vector Machine Learning Approach
Authors: Jia Yan , Jin Shuanggen , Savi Patrizia , Yan Qingyun , Li Wenmei
Published: November 2020

Global Navigation Satellite System-Reflectometry (GNSS-R) as a microwave remote sensing technique can retrieve the Earth’s surface parameters using the GNSS reflected signal from the surface. These reflected signals convey the surface features and therefore can be utilized to detect certain physical properties of the reflecting surface such as soil moisture content (SMC). Up to now, a serial of electromagnetic models (e.g., bistatic radar and Fresnel equations, etc.) are employed and solved for SMC retrieval. However, due to the uncertainty of the physical characteristics of the sites, complexity, and nonlinearity of the inversion process, etc., it is still challenging to accurately retrieve the soil moisture. The popular machine learning (ML) methods are flexible and able to handle nonlinear problems. It can dig out and model the complex interactions between input and output and ultimately make good predictions. In this paper, two typical ML methods, specifically, random forest (RF) and support vector machine (SVM), are employed for SMC retrieval from GNSS-R data of self-designed experiments (in situ and airborne). A comprehensive simulated dataset involving different types of soil is constructed firstly to represent the complex interactions between the variables (reflectivity, elevation angle, dielectric constant, and SMC) for the requirement of training ML regression models. Correspondingly, the main task of soil moisture retrieval (regression) is addressed. Specifically, the post-processed data (reflectivity and elevation angle) from sensor acquisitions are used to make predictions by these two adopted ML methods and compared with the commonly used GNSS-R retrieval method (electromagnetic models). The results show that the RF outperforms the SVM method, and it is more suitable for handling the inversion problem. Moreover, the RF regression model built by the comprehensive dataset demonstrates satisfactory accuracy and strong universality, especially when the soil type is not uniform or unknown. Furthermore, the typical task of detecting water/soil (classification) is discussed. The ML algorithms demonstrate a high potential and efficiency in SMC retrieval from GNSS-R data.
PSI Clustering for the Assessment of Underground Infrastructure Deterioration
Authors: Amoroso Nicola , Cilli Roberto , Bellantuono Loredana , Massimi Vincenzo , Monaco Alfonso , Nitti Davide Oscar , Nutricato Raffaele , Samarelli Sergio , Taggio Niccolò , Tangaro Sabina , Tateo Andrea , Guerriero Luciano , Bellotti Roberto
Published: November 2020

Remote sensing images find application in several different domains, such as land cover or land usage observation, environmental monitoring, and urbanization. This latter field has recently witnessed an interesting development with the use of remote sensing for infrastructural monitoring. In this work, we present an analysis of Sentinel-1 images, which were used to monitor the Italian provinces of Bologna and Modena located at the Emilia Region Apennines foothill. The goal of this study was the development of a machine learning-based detection system to monitor the deterioration of public aqueduct infrastructures based on Persistent Scatterer Interferometry (PSI). We evaluated the land deformation over a temporal range of five years; these series feed a k-means clustering algorithm to separate the pixels of the region according to different deformation patterns. Furthermore, we defined the critical areas as those areas where different patterns collided or overlapped. The proposed approach provides an informative tool for the structural health monitoring of underground infrastructures.
Autonomous Vehicles Mapping Plitvice Lakes National Park, Croatia
Authors: Kapetanović Nadir , Kordić Branko , Vasilijević Antonio , Nađ Đula , Mišković Nikola
Published: November 2020

Plitvice Lakes National Park is the largest national park in Croatia and also the oldest from 1949. It was added to the UNESCO World Natural Heritage List in 1979, due to the unique physicochemical and biological conditions that have led to the creation of 16 named and several smaller unnamed lakes, which are cascading one into the next. Previous scientific research proved that the increased amount of dissolved organic matter (pollution) stops the travertine processes on Plitvice Lakes. Therefore, this complex, dynamic but also fragile geological, biological and hydrological system required a comprehensive limnological survey. Thirteen of the sixteen lakes mentioned above were initially surveyed from the air by an unmanned aircraft equipped with a survey grade GNSS and a full frame high-resolution full-screen camera. From these recordings, a georeferenced, high-resolution orthophoto was generated, on which the following surveys by a multibeam sonar depended. It is important to mention that this was the first time that these lakes had ever been surveyed both with the multibeam sonar technique and with such a high-resolution camera. Due to the fact that these thirteen lakes are difficult to reach and often too shallow for a boat-mounted sonar, a special autonomous surface vehicle was developed. The lakes were surveyed by the autonomous surface vehicle mounted with a multibeam sonar to create detailed bathymetric models of the lakes. The missions were planned for the surface vehicle based on the orthophoto from the preliminary studies. A detailed description of the methodology used to survey the different lakes is given here. In addition, the resulting high-resolution bathymetric maps are presented and analysed together with an overview of average, maximum depths and number of data points. Numerous interesting depressions, which are phenomena consistent with previous studies of Plitvice Lakes, are noted at the lake beds and their causes are discussed. This study shows the huge potential of remote sensing technologies integrated into autonomous vehicles in terms of much faster surveys, several orders of magnitude more data points (compared to manual surveys of a few decades ago), as well as data accuracy, precision and georeferencing.
Use of an Active Canopy Sensor Mounted on an Unmanned Aerial Vehicle to Monitor the Growth and Nitrogen Status of Winter Wheat
Authors: Jiang Jie , Zhang Zeyu , Cao Qiang , Liang Yan , Krienke Brian , Tian Yongchao , Zhu Yan , Cao Weixing , Liu Xiaojun
Published: November 2020

Using remote sensing to rapidly acquire large-area crop growth information (e.g., shoot biomass, nitrogen status) is an urgent demand for modern crop production; unmanned aerial vehicle (UAV) acts as an effective monitoring platform. In order to improve the practicability and efficiency of UAV based monitoring technique, four field experiments involving different nitrogen (N) rates (0–360 kg N ha−1) and seven winter wheat (Triticum aestivum L.) varieties were conducted at different eco-sites (Sihong, Rugao, and Xinghua) during 2015–2019. A multispectral active canopy sensor (RapidSCAN CS-45; Holland Scientific Inc., Lincoln, NE, USA) mounted on a multirotor UAV platform was used to collect the canopy spectral reflectance data of winter wheat at key growth stages, three growth parameters (leaf area index (LAI), leaf dry matter (LDM), plant dry matter (PDM)) and three N indicators (leaf N accumulation (LNA), plant N accumulation (PNA) and N nutrition index (NNI)) were measured synchronously. The quantitative linear relationships between spectral data and six growth indices were systematically analyzed. For monitoring growth and N nutrition status at Feekes stages 6.0–10.0, 10.3–11.1 or entire growth stages, red edge ratio vegetation index (RERVI), red edge chlorophyll index (CIRE) and difference vegetation index (DVI) performed the best among the red edge band-based and red-based vegetation indices, respectively. Across all growth stages, DVI was highly correlated with LAI (R2 = 0.78), LDM (R2 = 0.61), PDM (R2 = 0.63), LNA (R2 = 0.65) and PNA (R2 = 0.73), whereas the relationships between RERVI (R2 = 0.62), CIRE (R2 = 0.62) and NNI had high coefficients of determination. The developed models performed better in monitoring growth indices and N status at Feekes stages 10.3–11.1 than Feekes stages 6.0–10.0. To sum it up, the UAV-mounted active sensor system is able to rapidly monitor the growth and N nutrition status of winter wheat and can be deployed for UAV-based remote-sensing of crops.
The Integration of Remote Sensing and Field Surveys to Detect Ecologically Damaged Areas for Restoration in South Korea
Authors: Lee Kyungil , Sung Hyun Chan , Seo Joung-Young , Yoo Youngjae , Kim Yoonji , Kook Jung Hyun , Jeon Seong Woo
Published: November 2020

Ecological damage refers to the reduction in the value of the environment due to human activities such as development. The intensity of ecosystem damage is worsening worldwide. Although the importance of restoration projects to reduce ecosystem damage is increasing, they are difficult to carry out, owing to the absence of data and monitoring of damaged areas. In this study, ecologically damaged areas for restoration in South Korea were detected using remote sensing and field surveys. For the analysis, national standardized vector datasets and Google Earth images were used; field surveys were conducted from 2018 to early 2020. Our results showed that 62% of the ecological damage that occurred in South Korea existed in forest ecosystems; the damaged areas were mostly smaller than 50,000 m2. Additionally, most of the causes and types of damage due to human activities such as development were soil erosion related. The results also suggest the importance of obtaining monitoring data on ecologically damaged areas and the importance of establishing an appropriate restoration plan using this data.
Beryllium-Ion-Selective PEDOT Solid Contact Electrode Based on 9,10-Dinitrobenzo-9-Crown-3-Ether
Authors: Kim Junghwan , Kim Dae Hee , Yang Jin Cheol , Kim Jae Sang , Lee Ji Ha , Jung Sung Ho
Published: November 2020

A beryllium(II)-ion-selective poly(ethylenedioxythiophene) (PEDOT) solid contact electrode comprising 9,10-dinitrobenzo-9-crown-3-ether was successfully developed. The all-solid-state contact electrode, with an oxygen-containing cation-sensing membrane combined with an electropolymerized PEDOT layer, exhibited the best response characteristics. The performance of the constructed electrode was evaluated and optimized using potentiometry, conductance measurements, constant-current chronopotentiometry, and electrochemical impedance spectroscopy (EIS). Under optimized conditions, which were found for an ion-selective membrane (ISM) composition of 3% ionophore, 30% polyvinylchloride (PVC), 64% o-nitro phenyl octyl ether (o-NPOE), and 3% sodium tetraphenylborate (NaTPB), the fabricated electrode exhibited a good performance over a wide concentration range (10−2.5–10−7.0 M) and a wide pH range of 2.0–9.0, with a Nernstian slope of 29.5 mV/D for the beryllium (II) ion and a detection limit as low as 10−7.0 M. The developed electrode shows good selectivity for the beryllium(II) ion over alkali, alkaline earth, transition, and heavy metal ions.
Capacitive-Coupling Impedance Spectroscopy Using a Non-Sinusoidal Oscillator and Discrete-Time Fourier Transform: An Introductory Study
Authors: Yamaguchi Tomiharu , Ueno Akinori
Published: November 2020

In this study, we propose a new short-time impedance spectroscopy method with the following three features: (1) A frequency spectrum of complex impedance for the measured object can be obtained even when the measuring electrodes are capacitively coupled with the object and the precise capacitance of the coupling is unknown; (2) the spectrum can be obtained from only one cycle of the non-sinusoidal oscillation waveform without sweeping the oscillation frequency; and (3) a front-end measuring circuit can be built, simply and cheaply, without the need for a digital-to-analog (D-A) converter to synthesize elaborate waveforms comprising multiple frequencies. We built the measurement circuit using the proposed method and then measured the complex impedance spectra of 18 resistive elements connected in series with one of three respective capacitive couplings. With this method, each element’s resistance and each coupling’s capacitance were estimated independently and compared with their nominal values. When the coupling capacitance was set to 10 nF or 1.0 nF, estimated errors for the resistive elements in the range of 2.0–10.0 kΩ were less than 5%.
Physically Plausible Spectral Reconstruction
Authors: Lin Yi-Tun , Finlayson Graham D.
Published: November 2020

Spectral reconstruction algorithms recover spectra from RGB sensor responses. Recent methods—with the very best algorithms using deep learning—can already solve this problem with good spectral accuracy. However, the recovered spectra are physically incorrect in that they do not induce the RGBs from which they are recovered. Moreover, if the exposure of the RGB image changes then the recovery performance often degrades significantly—i.e., most contemporary methods only work for a fixed exposure. In this paper, we develop a physically accurate recovery method: the spectra we recover provably induce the same RGBs. Key to our approach is the idea that the set of spectra that integrate to the same RGB can be expressed as the sum of a unique fundamental metamer (spanned by the camera’s spectral sensitivities and linearly related to the RGB) and a linear combination of a vector space of metameric blacks (orthogonal to the spectral sensitivities). Physically plausible spectral recovery resorts to finding a spectrum that adheres to the fundamental metamer plus metameric black decomposition. To further ensure spectral recovery that is robust to changes in exposure, we incorporate exposure changes in the training stage of the developed method. In experiments we evaluate how well the methods recover spectra and predict the actual RGBs and RGBs under different viewing conditions (changing illuminations and/or cameras). The results show that our method generally improves the state-of-the-art spectral recovery (with more stabilized performance when exposure varies) and provides zero colorimetric error. Moreover, our method significantly improves the color fidelity under different viewing conditions, with up to a 60% reduction in some cases.