bluuebunny/crossref_metadata_2025 huggingface dataset:
Brittleness of Concrete under Different Curing Conditions
Authors: Zhang Shuai , Han Bing , Xie Huibing , An Mingzhe , Lyu Shengxu
Published: December 2021

In order to shorten construction periods, concrete is often cured using steam and is loaded at an early age. This changes the performance and even the durability of the concrete compared to concrete that has been cured under normal conditions. Thus, the pattern and the mechanism of concrete performance change under different curing conditions, and loading ages are of great significance. The development of brittleness under different curing conditions and loading ages was studied. The evaluation methods that were used to determine concrete brittleness were expounded. Steam, standard, and natural curing conditions were carried out on single-side notched concrete beams as well as on a concrete prism and cubic blocks. The compressive strength and splitting tensile strength of the concrete blocks along with the fracture performance of the concrete beams were tested after 3, 7, 28, and 90 days. The steam curing condition significantly improved the strength of concrete before 28 days had passed, and the standard curing condition improved the strength of concrete after 28 days. Based on the experimental fracture parameters, a two-parameter fracture model was applied to study the development of fracture toughness KICS, critical crack tip opening displacement CTODc, and critical strain energy release rate GICS with hydration age under different curing conditions. With respect to long-term performance, the standard curing condition was better at resisting concrete crack propagations than the steam curing condition was. The characteristic length lch and the material length Q under the three curing conditions and the long-term development of brittleness in the concrete indicated that steam curing increased the concrete brittleness. Considering the effects of the curing condition and the loading age, a time-dependent concrete fracture toughness model was established, and the predicted value of the model was verified against the measured value. The results indicated that the model was able to accurately predict the fracture toughness with an error rate of less than 16%.
Determination of the Kinetics and Thermodynamic Parameters of Lignocellulosic Biomass Subjected to the Torrefaction Process
Authors: Ivanovski Maja , Petrovic Aleksandra , Ban Irena , Goricanec Darko , Urbancl Danijela
Published: December 2021

The torrefaction process upgrades biomass characteristics and produces solid biofuels that are coal-like in their properties. Kinetics analysis is important for the determination of the appropriate torrefaction condition to obtain the best utilization possible. In this study, the kinetics (Friedman (FR) and Kissinger–Akahira–Sunose (KAS) isoconversional methods) of two final products of lignocellulosic feedstocks, miscanthus (Miscanthus x giganteus) and hops waste (Humulus Lupulus), were studied under different heating rates (10, 15, and 20 °C/min) using thermogravimetry (TGA) under air atmosphere as the main method to investigate. The results of proximate and ultimate analysis showed an increase in HHV values, carbon content, and fixed carbon content, followed by a decrease in the VM and O/C ratios for both torrefied biomasses, respectively. FTIR spectra confirmed the chemical changes during the torrefaction process, and they corresponded to the TGA results. The average Eα for torrefied miscanthus increased with the conversion degree for both models (25–254 kJ/mol for FR and 47–239 kJ/mol for the KAS model). The same trend was noticed for the torrefied hops waste samples; the values were within the range of 14–224 kJ/mol and 60–221 kJ/mol for the FR and KAS models, respectively. Overall, the Ea values for the torrefied biomass were much higher than for raw biomass, which was due to the different compositions of the torrefied material. Therefore, it can be concluded that both torrefied products can be used as a potential biofuel source.
Antimicrobial, Antibiofilm, and Antioxidant Activity of Functional Poly(Butylene Succinate) Films Modified with Curcumin and Carvacrol
Authors: Łopusiewicz Łukasz , Macieja Szymon , Bartkowiak Artur , El Fray Mirosława
Published: December 2021

The use of food industry waste as bioactive compounds in the modification of biodegradable films as food packaging remains a major challenge. This study describes the preparation and bioactivity characterization of poly(butylene succinate) (PBS)-based films with the addition of the bioactive compounds curcumin (CUR) and carvacrol (CAR). Films based on PBS modified with curcumin and carvacrol at different concentration variations (0%/0.1%/1%) were prepared by solvent casting method. The antioxidant, antimicrobial, and antibiofilm properties were investigated against bacteria (Escherichia coli, Staphylococcus aureus) and fungi (Candida albicans). As a result of the modification, the films exhibited free radicals scavenging (DPPH up to 91.47% and ABTS up to 99.21%), as well as antimicrobial (6 log, 4 log, and 2 log reductions for E. coli, S. aureus, and C. albicans, respectively, for samples modified with 1% CUR and 1% CAR) activity. Moreover, antibiofilm activity of modified materials was observed (8.22–87.91% reduction of biofilm, depending on bioactive compounds concentration). PBS films modified with curcumin and carvacrol with observed bifunctional properties have many potential applications as active packaging.
Numerical and Experimental Study of Hydraulic Performance and Wear Characteristics of a Slurry Pump
Authors: Peng Guangjie , Tian Long , Chang Hao , Hong Shiming , Ye Daoxing , You Baojian
Published: December 2021

The slurry pump is widely used in ore mining, metal smelting, petrochemical, and other industries, mainly to transport fluid media containing large solid particles. Importantly, it is easy to damage the impeller of a slurry pump in the operation process, which greatly affects the performance of the pump. In this paper, a 25 MZ slurry pump was selected as the research object, and the Euler–Euler multiphase flow model was employed to analyze the internal flow characteristics of the slurry pump under the conditions of clear water and solid–liquid two-phase flow. Additionally, the flow characteristics of each part under different flow conditions were studied, and the effects of different particle volume concentrations, particle sizes, and pump speeds on the impeller’s wear characteristics and hydraulic performance were analyzed. In order to verify the reliability and accuracy of the numerical simulation results, clean water and solid–liquid two-phase flow wear tests of the slurry pump were carried out, and the results showed that a high solid volume fraction and solid–phase slip velocity were generated at the junction of the blade leading edge and the rear cover plate, thus leading to easier wear of the blade. Therefore, enhancing the strength of the junction between the blade leading edge and the rear cover plate is beneficial for improving service life and should be considered in the design of slurry pumps.
Volatile Organic Compounds, Indole, and Biogenic Amines Assessment in Two Mediterranean Irciniidae (Porifera, Demospongiae)
Authors: Aresta Antonella , Cotugno Pietro , De Vietro Nicoletta , Longo Caterina , Mercurio Maria , Ferriol Pere , Zambonin Carlo , Nonnis Marzano Carlotta
Published: December 2021

Solid phase microextraction (SPME) coupled to gas chromatography-mass spectrometry (GC-MS) was employed for the headspace determination of the volatile organic fraction emitted by two of the most common Mediterranean demosponges, Ircinia variabilis and Sarcotragus spinosulus, and of indole and some biogenic amines released by sponges in an aqueous medium. A total of 50/30 µm divinylbenzene/carboxen/polydimethylsiloxane and 75 µm carboxen/polydimethylsiloxane fibers were used for the headspace extraction of low molecular weight sulfur compounds from a hermetically sealed vial containing sponge fragments, while the direct immersion determination of indole and biogenic amines was performed. The biogenic amines were extracted after in-solution derivatization with isobutyl chloroformate. All analytical parameters (linearity, limits of detection, and quantification, precision, and recovery) were evaluated for indole and biogenic amines. SPME-GC-MS proved to be a reliable means of highlighting the differences between molecules released by different sponges, principally responsible for their smell. The combined approaches allowed the identification of several volatile compounds in the headspace and other molecules released by the sponges in an aqueous medium, including indole and the BAs cadaverine, histamine, isobutylamine, isopentylamine, propylamine, 2-phenylethylamine, putrescine and tryptamine. The results obtained represent a further contribution to the picture of odoriferous molecules secreted by sponges.
Protective Effect of Flavonoids from a Deep-Sea-Derived Arthrinium sp. against ox-LDL-Induced Oxidative Injury through Activating the AKT/Nrf2/HO-1 Pathway in Vascular Endothelial Cells
Authors: Hou Jia-Rong , Wang Yan-Hong , Zhong Ying-Nan , Che Tong-Tong , Hu Yang , Bao Jie , Meng Ning
Published: December 2021

Oxidized low-density lipoprotein (ox-LDL)-induced oxidative injury in vascular endothelial cells is crucial for the progression of cardiovascular diseases, including atherosclerosis. Several flavonoids have been shown cardiovascular protective effects. Recently, our research group confirmed that the novel flavonoids isolated from the deep-sea-derived fungus Arthrinium sp., 2,3,4,6,8-pentahydroxy-1-methylxanthone (compound 1) and arthone C (compound 2) effectively scavenged ROS in vitro. In this study, we further investigated whether these compounds could protect against ox-LDL-induced oxidative injury in endothelial cells and the underlying mechanisms. Our results showed that compounds 1 and 2 inhibited ox-LDL-induced apoptosis and adhesion factors expression in human umbilical vein vascular endothelial cells (HUVECs). Mechanistic studies showed that these compounds significantly inhibited the ROS level increase and the NF-κB nuclear translocation induced by ox-LDL. Moreover, compounds 1 and 2 activated the Nrf2 to transfer into nuclei and increased the expression of its downstream antioxidant gene HO-1 by inducing the phosphorylation of AKT in HUVECs. Importantly, the AKT inhibitor MK-2206 2HCl or knockdown of Nrf2 by RNA interference attenuated the inhibition effects of these compounds on ox-LDL-induced apoptosis in HUVECs. Meanwhile, knockdown of Nrf2 abolished the effects of the compounds on ox-LDL-induced ROS level increase and the translocation of NF-κB to nuclei. Collectively, the data showed that compounds 1 and 2 protected endothelial cells against ox-LDL-induced oxidative stress through activating the AKT/Nrf2/HO-1 pathway. Our study provides new strategies for the design of lead compounds for related cardiovascular diseases treatment.
Metabolomics Study of Flavonoids of Taxilluschinensis on Different Hosts Using UPLC-ESI-MS/MS
Authors: Li Li , Teng Jianbei , Zhu Yilin , Xie Fengfeng , Hou Jing , Ling Yuan , Zhu Hua
Published: December 2021

The goal of this study was to identify and compare the main biomarkers of Taxillus chinensis from different hosts. A metabolomics approach utilizing ultra-pressure liquid chromatography coupled with tandem mass spectrometry (UPLC-MS), including cluster analysis, sample correlation analysis and orthogonal partial least squares discriminant analysis, was used to explore the flavonoid metabolites of Taxillus chinensis growing on different hosts. Results: The total flavonoids content (up to 30.08 mg/g) in Taxillus chinensis from Morus alba (CSG) was significantly higher than that from growth on Liquidambar formosana (CFG) or Clausena lansium (CHG) (p < 0.01). There were 23 different metabolites between CSG and CHG, 23 different metabolites between CSG and CFG, and 19 different metabolites between CHG and CFG. The results demonstrated that different hosts exerted a large influence on the metabolites of Taxillus chinensis; it was found that CSG differed from CFG and CHG in eleven metabolic compounds, ten of which were upregulated and one of which was downregulated. Most of these metabolites derive from compounds contained in the host plant, white mulberry (Morus alba); many feature potent anti-cancer effects. Differences in host can influence the type and abundance of flavonoids in parasitic plants such as Taxillus chinensis, which is of great significance to researchers seeking to understand the formation mechanism of Taxillus chinensis metabolites. Therefore, attention should be paid to the species of host plant when studying the Taxillus chinensis metabolome. Plants grown on Morus alba offer the greatest potential for the development of new anti-cancer drugs.
Stevioside Attenuates Insulin Resistance in Skeletal Muscle by Facilitating IR/IRS-1/Akt/GLUT 4 Signaling Pathways: An In Vivo and In Silico Approach
Authors: Deenadayalan Abilasha , Subramanian Vijayalakshmi , Paramasivan Vijayalakshmi , Veeraraghavan Vishnu Priya , Rengasamy Gayathri , Coiambatore Sadagopan Janaki , Rajagopal Ponnulakshmi , Jayaraman Selvaraj
Published: December 2021

Type-2 diabetes mellitus (T2DM), the leading global health burden of this century majorly develops due to obesity and hyperglycemia-induced oxidative stress in skeletal muscles. Hence, developing novel drugs that ameliorate these pathological events is an immediate priority. The study was designed to analyze the possible role of Stevioside, a characteristic sugar from leaves of Stevia rebaudiana (Bertoni) on insulin signaling molecules in gastrocnemius muscle of obesity and hyperglycemia-induced T2DM rats. Adult male Wistar rats rendered diabetic by administration of high fat diet (HFD) and sucrose for 60 days were orally administered with SIT (20 mg/kg/day) for 45 days. Various parameters were estimated including fasting blood glucose (FBG), serum lipid profile, oxidative stress markers, antioxidant enzymes and expression of insulin signaling molecules in diabetic gastrocnemius muscle. Stevioside treatment improved glucose and insulin tolerances in diabetic rats and restored their elevated levels of FBG, serum insulin and lipid profile to normalcy. In diabetic gastrocnemius muscles, Setvioside normalized the altered levels of lipid peroxidase (LPO), hydrogen peroxide (H2O2) and hydroxyl radical (OH*), antioxidant enzymes (CAT, SOD, GPx and GSH) and molecules of insulin signaling including insulin receptor (IR), insulin receptor substrate-1 (IRS-1) and Akt mRNA levels. Furthermore, Stevioside enhanced glucose uptake (GU) and oxidation in diabetic muscles by augmenting glucose transporter 4 (GLUT 4) synthesis very effectively in a similar way to metformin. Results of molecular docking analysis evidenced the higher binding affinity with IRS-1 and GLUT 4. Stevioside effectively inhibits oxidative stress and promotes glucose uptake in diabetic gastrocnemius muscles by activating IR/IRS-1/Akt/GLUT 4 pathway. The results of the in silico investigation matched those of the in vivo study. Hence, Stevioside could be considered as a promising phytomedicine to treat T2DM.
A Food Frequency Questionnaire for Hemodialysis Patients in Bangladesh (BDHD-FFQ): Development and Validation
Authors: Ahmed Shakil , Rahman Tanjina , Ripon Md Sajjadul Haque , Rashid Harun-Ur , Kashem Tasnuva , Md Ali Mohammad Syafiq , Khor Ban-Hock , Khosla Pramod , Karupaiah Tilakavati , Daud Zulfitri Azuan Mat
Published: December 2021

Diet is a recognized risk factor and cornerstone for chronic kidney disease (CKD) management; however, a tool to assess dietary intake among Bangladeshi dialysis patients is scarce. This study aims to validate a prototype Bangladeshi Hemodialysis Food Frequency Questionnaire (BDHD-FFQ) against 3-day dietary recall (3DDR) and corresponding serum biomarkers. Nutrients of interest were energy, macronutrients, potassium, phosphate, iron, sodium and calcium. The BDHD-FFQ, comprising 132 food items, was developed from 606 24-h recalls and had undergone face and content validation. Comprehensive facets of relative validity were ascertained using six statistical tests (correlation coefficient, percent difference, paired t-test, cross-quartiles classification, weighted kappa, and Bland-Altman analysis). Overall, the BDHD-FFQ showed acceptable to good correlations (p < 0.05) with 3DDR for the concerned nutrients in unadjusted and energy-adjusted models, but this correlation was diminished when adjusted for other covariates (age, gender, and BMI). Phosphate and potassium intake, estimated by the BDHD-FFQ, also correlated well with the corresponding serum biomarkers (p < 0.01) when compared to 3DDR (p > 0.05). Cross-quartile classification indicated that <10% of patients were incorrectly classified. Weighted kappa statistics showed agreement with all but iron. Bland-Altman analysis showed positive mean differences were observed for all nutrients when compared to 3DDR, whilst energy, carbohydrates, fat, iron, sodium, and potassium had percentage data points within the limit of agreement (mean ± 1.96 SD), above 95%. In summary, the BDHD-FFQ demonstrated an acceptable relative validity for most of the nutrients as four out of the six statistical tests fulfilled the cut-off standard in assessing dietary intake of CKD patients in Bangladesh.
Well-Balanced Lunch Reduces Risk of Lifestyle-Related Diseases in Middle-Aged Japanese Working Men
Authors: Mori Mari
Published: December 2021

Based on the results of a previous WHO-CARDIAC study, this study was designed to test the effect of the daily consumption of a diet rich in potassium with optimal salt content, rich in fish meat and soy isoflavones, corresponding to the ingredients of a traditional Japanese diet. The test meals were a Balanced Lunch (BL) with chicken as the main dish and a Fortified Lunch (FL) with fish and soy as the main dish, which appeared the same. A double-blind, randomized controlled trial was conducted in 64 relatively obese men (47.2 ± 5.5 years old) who consumed the lunch at their work site for 4 weeks. All participants underwent fasting blood sampling, 24-h urine collection, as well as measurements of height, weight, and blood pressure before and after the intervention. Body mass index, blood pressure, and HbA1c were significantly improved and a 3-g reduction of salt intake was proven by 24-h urine collection in both groups. Moreover, HDL cholesterol and the Atherogenic Index (AI) were significantly improved in the FL group. In conclusion, the risks of lifestyle-related diseases in working men were reduced by one meal per day intervention of optimally-salted traditional Japanese diets containing soy and fish nutrients with high vegetable ingredients.
Satellite Cells Exhibit Decreased Numbers and Impaired Functions on Single Myofibers Isolated from Vitamin B6-Deficient Mice
Authors: Komaru Takumi , Yanaka Noriyuki , Kumrungsee Thanutchaporn
Published: December 2021

Emerging research in human studies suggests an association among vitamin B6, sarcopenia, and muscle strength. However, very little is known regarding its potential role at the cellular level, especially in muscle satellite cells. Therefore, to determine whether vitamin B6 affects the satellite cells, we isolated single myofibers from muscles of vitamin B6-deficient and vitamin B6-supplemented mice. Subsequently, we subjected them to single myofiber culture and observed the number and function of the satellite cells, which remained in their niche on the myofibers. Prior to culture, the vitamin B6-deficient myofibers exhibited a significantly lower number of quiescent satellite cells, as compared to that in the vitamin B6-supplemented myofibers, thereby suggesting that vitamin B6 deficiency induces a decline in the quiescent satellite cell pool in mouse muscles. After 48 and 72 h of culture, the number of proliferating satellite cells per cluster was similar between the vitamin B6-deficient and -supplemented myofibers, but their numbers decreased significantly after culturing the myofibers in vitamin B6-free medium. After 72 h of culture, the number of self-renewing satellite cells per cluster was significantly lower in the vitamin B6-deficient myofibers, and the vitamin B6-free medium further decreased this number. In conclusion, vitamin B6 deficiency appears to reduce the number of quiescent satellite cells and suppress the proliferation and self-renewal of satellite cells during myogenesis.
Evaluation of Nutri-Score in Relation to Dietary Guidelines and Food Reformulation in The Netherlands
Authors: ter Borg Sovianne , Steenbergen Elly , Milder Ivon E. J. , Temme Elisabeth H. M.
Published: December 2021

An unhealthy dietary pattern is an important risk factor for non-communicable diseases. Front-of-Pack nutritional labels such as Nutri-Score can be used to improve food choices. In addition, products can be improved through reformulation. The current study investigates to what extent Nutri-Score aligns with the Dutch Health Council dietary guidelines and whether it can be used as an incentive for reformulation. Nutri-Score calculations were based on the Dutch Branded Food database (2018). The potential shift in Nutri-Score was calculated with product improvement scenarios. The Nutri-Score classification is in line with these dietary guidelines: increase the consumption of fruit and vegetables, pulses, and unsalted nuts. It is, however, less in line with the recommendations to limit (dairy) drinks with added sugar, reduce the consumption of red meat and replace refined cereal products with whole-grain products. The scenario analyses indicated that a reduction in sodium, saturated fat or sugars resulted in a more favourable Nutri-Score in a large variety of food groups. However, the percentage of products with an improved Nutri-Score varied greatly between the different food groups. Alterations to the algorithm may strengthen Nutri-Score in order to help consumers with their food choices.
Inhibition Ability of Natural Compounds on Receptor-Binding Domain of SARS-CoV2: An In Silico Approach
Authors: Nedyalkova Miroslava , Vasighi Mahdi , Sappati Subrahmanyam , Kumar Anmol , Madurga Sergio , Simeonov Vasil
Published: December 2021

The lack of medication to treat COVID-19 is still an obstacle that needs to be addressed by all possible scientific approaches. It is essential to design newer drugs with varied approaches. A receptor-binding domain (RBD) is a key part of SARS-CoV-2 virus, located on its surface, that allows it to dock to ACE2 receptors present on human cells, which is followed by admission of virus into cells, and thus infection is triggered. Specific receptor-binding domains on the spike protein play a pivotal role in binding to the receptor. In this regard, the in silico method plays an important role, as it is more rapid and cost effective than the trial and error methods using experimental studies. A combination of virtual screening, molecular docking, molecular simulations and machine learning techniques are applied on a library of natural compounds to identify ligands that show significant binding affinity at the hydrophobic pocket of the RBD. A list of ligands with high binding affinity was obtained using molecular docking and molecular dynamics (MD) simulations for protein–ligand complexes. Machine learning (ML) classification schemes have been applied to obtain features of ligands and important descriptors, which help in identification of better binding ligands. A plethora of descriptors were used for training the self-organizing map algorithm. The model brings out descriptors important for protein–ligand interactions.
Impact of the COVID-19 Pandemic on the Consumer Credit Market in V4 Countries
Authors: Czech Maria , Puszer Blandyna
Published: December 2021

The aim of this article is to analyse and assess the impact of the COVID-19 pandemic on the consumer credit market in the countries of the Visegrad Group (V4, i.e., the Czech Republic, Poland, Slovakia, and Hungary). There is no doubt that the pandemic has determined the amount of household debt due to consumer credit in the V4 group, and thus the question arises of how the pandemic affects the propensity of households to take out loans and the propensity to lend to them, and therefore whether it affects both the behaviour of borrowers and lenders. The study used the time series and multiple linear regression methods. The results of the study show that the Covid-19 pandemic has determined the level of household debt in the V4 group and is not indifferent to household decisions regarding taking out consumer loans. Although the research is preliminary, it has contributed to some extent to a better understanding of household indebtedness at a time of turbulence and instability resulting from health factors in V4 countries. In the future, this research will serve as the basis for future research on the phenomenon of household indebtedness in other countries.
The Characterization of Haze and Dust Processes Using MAX-DOAS in Beijing, China
Authors: Ren Hongmei , Li Ang , Xie Pinhua , Hu Zhaokun , Xu Jin , Huang Yeyuan , Li Xiaomei , Zhong Hongyan , Zhang Hairong , Tian Xin , Ren Bo , Wang Shuai , Chai Wenxuan , Du Chuanyao
Published: December 2021

Haze and dust pollution have a significant impact on human production, life, and health. In order to understand the pollution process, the study of these two pollution characteristics is important. In this study, a one-year observation was carried out at the Beijing Southern Suburb Observatory using the MAX-DOAS instrument, and the pollution characteristics of the typical haze and dust events were analyzed. First, the distribution of aerosol extinction (AE) and H2O concentrations in the two typical pollution events were studied. The results showed that the correlation coefficient (r) between H2O and AE at different heights decreased during dust processes and the correlation slope (|k|) increased, whereas r increased and |k| decreased during haze periods. The correlation slope increased during the dust episode due to low moisture content and increased O4 absorption caused by abundant suspended dry crustal particles, but decreased during the haze episode due to a significant increase of H2O absorption. Secondly, the gas vertical column density (VCD) indicated that aerosol optical depth (AOD) increased during dust pollution events in the afternoon, while the H2O VCD decreased; in haze pollution processes, both H2O VCD and AOD increased. There were significant differences in meteorological conditions during haze (wind speed (WD) was <2 m/s, and relative humidity (RH) was >60%) and dust pollution (WD was >4 m/s, and RH was <60%). Next, the vertical distribution characteristics of gases during the pollution periods were studied. The AE profile showed that haze pollution lasted for a long time and changed slowly, whereas the opposite was true for dust pollution. The pollutants (aerosols, NO2, SO2, and HCHO) and H2O were concentrated below 1 km during both these typical pollution processes, and haze pollution was associated with a strong temperature inversion around 1.0 km. Lastly, the water vapor transport fluxes showed that the water vapor transport from the eastern air mass had an auxiliary effect on haze pollution at the observation location. Our results are of significance for exploring the pollution process of tropospheric trace gases and the transport of water vapor in Beijing, and provide a basis for satellite and model verification.
Reconstruction of Nineteenth-Century Channel Patterns of Polish Carpathians Rivers from the Galicia and Bucovina Map (1861–1864)
Authors: Witkowski Karol
Published: December 2021

Historical maps are often the only source of information allowing for the regional reconstructions of river channel patterns in the past. In the Polish Carpathians, analyses of historical channel patterns were performed mostly in river reaches scale. In this paper, the Galicia and Bucovina map (1861–1864) (the Second military survey of the Habsburg Empire) was used to reconstruct and map the historical channel patterns of seven rivers from the Polish Carpathians. It was found that, in the nineteenth century, rivers in the western part of the study area (Soła, Skawa, Raba, Dunajec) supported a multi-thread channel pattern, whereas rivers in the eastern part (Wisłoka, San, Wisłok) present a mostly single-thread channel pattern. These differences probably result from the higher relief energy and precipitation, lower proportions of forests in the catchments, and more frequent floods favouring high sediment supply to the fluvial system, and thus the formation of multi-thread reaches in the western part of the study area. At the local scale, the most important factor supporting multi-thread channel pattern development was the availability of gravel sediments in the wide valley floor sections. The formation of anabranching reaches with a single mid-channel form was probably associated with the channel avulsion process. There is no clear evidence linking the change in the channel pattern type with an abrupt change in the river channel slope. This study confirms the usefulness of the second military survey map of the Habsburg Empire for the regional reconstruction of river channel pattern types.
Artificial Neural Network-Based Microwave Satellite Soil Moisture Reconstruction over the Qinghai–Tibet Plateau, China
Authors: Wang Jie , Xu Duanyang
Published: December 2021

Soil moisture is a key parameter for land-atmosphere interaction system; however, fewer existing spatial-temporally continuous and high-quality observation records impose great limitations on the application of soil moisture on long term climate change monitoring and predicting. Therefore, this study selected the Qinghai–Tibet Plateau (QTP) of China as research region, and explored the feasibility of using Artificial Neural Network (ANN) to reconstruct soil moisture product based on AMSR-2/AMSR-E brightness temperature and SMAP satellite data by introducing auxiliary variables, specifically considering the sensitivity of different combination of input variables, number of neurons in hidden layer, sample ratio, and precipitation threshold in model building. The results showed that the ANN model had the highest accuracy when all variables were used as inputs, it had a network containing 12 neurons in a hidden layer, it had a sample ratio 80%-10%-10% (training-validation-testing), and had a precipitation threshold of 8.75 mm, respectively. Furthermore, validation of the reconstructed soil moisture product (named ANN-SM) in other period were conducted by comparing with SMAP (April 2019 to July 2021) for all grid cells and in situ soil moisture sites (August 2010 to March 2015) of QTP, which achieved an ideal accuracy. In general, the proposed method is capable of rebuilding soil moisture products by adopting different satellite data and our soil moisture product is promising for serving the studies of long-term global and regional dynamics in water cycle and climate.
Feasibility of Ground-Based Sky-Camera HDR Imagery to Determine Solar Irradiance and Sky Radiance over Different Geometries and Sky Conditions
Authors: Valdelomar Pedro , Gómez-Amo José L. , Peris-Ferrús Caterina , Scarlatti Francesco , Utrillas María Pilar
Published: December 2021

We propose a methodological approach to provide the accurate and calibrated measurements of sky radiance and broadband solar irradiance using the High Dynamic Range (HDR) images of a sky-camera. This approach is based on a detailed instrumental characterization of a SONA sky-camera in terms of image acquisition and processing, as well as geometric and radiometric calibrations. As a result, a 1 min time resolution database of geometrically and radiometrically calibrated HDR images has been created and has been available since February 2020, with daily updates. An extensive validation of our radiometric retrievals has been performed in all sky conditions. Our results show a very good agreement with the independent measurements of the AERONET almucantar for sky radiance and pyranometers for broadband retrievals. The SONA sky radiance shows a difference of an RMBD < 10% while the broadband diffuse radiation shows differences of 2% and 5% over a horizontal plane and arbitrarily oriented surfaces, respectively. These results support the developed methodology and allow us to glimpse the great potential of sky-cameras to carry out accurate measurements of sky radiance and solar radiation components. Thus, the remote sensing techniques described here will undoubtedly be of great help for solar and atmospheric research.
Assessing Post-Fire Effects on Soil Loss Combining Burn Severity and Advanced Erosion Modeling in Malesina, Central Greece
Authors: Tselka Ioanna , Krassakis Pavlos , Rentzelos Alkiviadis , Koukouzas Nikolaos , Parcharidis Issaak
Published: December 2021

Earth’s ecosystems are extremely valuable to humanity, playing a key role ecologically, economically, and socially. Wildfires constitute a significant threat to the environment, especially in vulnerable ecosystems, such as those that are commonly found in the Mediterranean. Due to their strong impact on the environment, they provide a crucial factor in managing ecosystems behavior, causing dramatic modifications to land surface processes dynamics leading to land degradation. The soil erosion phenomenon downgrades soil quality in ecosystems and reduces land productivity. Thus, it is imperative to implement advanced erosion prediction models to assess fire effects on soil characteristics. This study focuses on examining the wildfire case that burned 30 km2 in Malesina of Central Greece in 2014. The added value of remote sensing today, such as the high accuracy of satellite data, has contributed to visualizing the burned area concerning the severity of the event. Additional data from local weather stations were used to quantify soil loss on a seasonal basis using RUSLE modeling before and after the wildfire. Results of this study revealed that there is a remarkable variety of high soil loss values, especially in winter periods. More particularly, there was a 30% soil loss rise one year after the wildfire, while five years after the event, an almost double reduction was observed. In specific areas with high soil erosion values, infrastructure works were carried out validating the applied methodology. The approach adopted in this study underlines the significance of using remote sensing and geoinformation techniques to assess the post-fire effects of identifying vulnerable areas based on soil erosion parameters on a local scale.
Mapping Soil Organic Matter and Analyzing the Prediction Accuracy of Typical Cropland Soil Types on the Northern Songnen Plain
Authors: Zhang Meiwei , Liu Huanjun , Zhang Meinan , Yang Haoxuan , Jin Yuanliang , Han Yu , Tang Haitao , Zhang Xiaohan , Zhang Xinle
Published: December 2021

Soil organic matter (SOM) plays a critical role in agroecosystems and the terrestrial carbon cycle. Thus, accurately mapping SOM promotes sustainable agriculture and estimations of soil carbon pools. However, few studies have analyzed the changing trends in multi-period SOM prediction accuracies for single cropland soil types and mapped their spatial SOM patterns. Using time series 7 MOD09A1 images during the bare soil period, we combined the pixel dates of training samples and precipitation data to explore the variation in SOM accuracy for two typical cropland soil types. The advantage of using single soil type data versus the total dataset was evaluated, and SOM maps were drawn for the northern Songnen Plain. When almost no precipitation occurred on or near the optimal pixel date, the accuracies increased, and vice versa. SOM models of the two soil types achieved a lower root mean squared error (RMSE = 0.55%, 0.79%) and mean absolute error (MAE = 0.39%, 0.58%) and a higher coefficient of determination (R2 = 0.65, 0.75) than the model using the total dataset and resulted in a mean relative improvement (RI) of 30.21%. The SOM decreased from northeast to southwest. The results provide reference data for the accurate management of cultivated soil and determining carbon sequestration.
A scSE-LinkNet Deep Learning Model for Daytime Sea Fog Detection
Authors: Guo Xiaofei , Wan Jianhua , Liu Shanwei , Xu Mingming , Sheng Hui , Yasir Muhammad
Published: December 2021

Sea fog is a precarious weather disaster affecting transportation on the sea. The accuracy of the threshold method for sea fog detection is limited by time and region. In comparison, the deep learning method learns features of objects through different network layers and can therefore accurately extract fog data and is less affected by temporal and spatial factors. This study proposes a scSE-LinkNet model for daytime sea fog detection that leverages residual blocks to encoder feature maps and attention module to learn the features of sea fog data by considering spectral and spatial information of nodes. With the help of satellite radar data from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), a ground sample database was extracted from Moderate Resolution Imaging Spectroradiometer (MODIS) L1B data. The scSE-LinkNet was trained on the training set, and quantitative evaluation was performed on the test set. Results showed the probability of detection (POD), false alarm rate (FAR), critical success index (CSI), and Heidke skill scores (HSS) were 0.924, 0.143, 0.800, and 0.864, respectively. Compared with other neural networks (FCN, U-Net, and LinkNet), the CSI of scSE-LinkNet was improved, with a maximum increase of nearly 8%. Moreover, the sea fog detection results were consistent with the measured data and CALIOP products.
Estimating Stand and Fire-Related Surface and Canopy Fuel Variables in Pine Stands Using Low-Density Airborne and Single-Scan Terrestrial Laser Scanning Data
Authors: Alonso-Rego Cecilia , Arellano-Pérez Stéfano , Guerra-Hernández Juan , Molina-Valero Juan Alberto , Martínez-Calvo Adela , Pérez-Cruzado César , Castedo-Dorado Fernando , González-Ferreiro Eduardo , Álvarez-González Juan Gabriel , Ruiz-González Ana Daría
Published: December 2021

In this study, we used data from a thinning trial conducted on 34 different sites and 102 sample plots established in pure and even-aged Pinus radiata and Pinus pinaster stands, to test the potential use of low-density airborne laser scanning (ALS) metrics and terrestrial laser scanning (TLS) metrics to provide accurate estimates of variables related to surface and canopy fires. An exhaustive field inventory was carried out in each plot to estimate the main stand variables and the main variables related to fire hazard: surface fuel loads by layers, fuel strata gap, surface fuel height, stand mean height, canopy base height, canopy fuel load and canopy bulk density. In addition, the point clouds from low-density ALS and single-scan TLS of each sample plot were used to calculate metrics related to the vertical and horizontal distribution of forest fuels. The comparative performance of the following three non-parametric machine learning techniques used to estimate the main stand- and fire-related variables from those metrics was evaluated: (i) multivariate adaptive regression splines (MARS), (ii) support vector machine (SVM), and (iii) random forest (RF). The selection of the best modeling approach was based on a comparison of the root mean square error (RMSE), obtained by optimizing the parameters of each technique and performing cross-validation. Overall, the best results were obtained with the MARS techniques for data from both sensors. The TLS data provided the best results for variables associated with the internal characteristics of canopy structure and understory fuel but were less reliable for estimating variables associated with the upper canopy, due to occlusion by mid-canopy foliage. The combination of ALS and TLS metrics improved the accuracy of estimates for all variables analyzed, except the height and the biomass of the understory shrubs. The variability demonstrated by the combined use of both types of metrics ranged from 43.11% for the biomass of duff litter layers to 94.25% for dominant height. The results suggest that the combination of machine learning techniques and metrics derived from low-density ALS data, drawn from a single-scan TLS or a combination of both metrics, may represent a promising alternative to traditional field inventories for obtaining valuable information about surface and canopy fuel variables at large scales.
A Four-Step Method for Estimating Suspended Particle Size Based on In Situ Comprehensive Observations in the Pearl River Estuary in China
Authors: Wang Zuomin , Hu Shuibo , Li Qingquan , Liu Huizeng , Liao Xiaomei , Wu Guofeng
Published: December 2021

The suspended particle size has great impacts on marine biology environments and biogeochemical processes, such as the settling rates of particles and sunlight transmission in marine water. However, the spatial–temporal variations in particle sizes in coastal waters are rarely reported due to the paucity of appropriate observations and the limitations of particle size retrieval methods, especially in areas with complex optical properties. This study proposed a remote sensing-based method for estimating the median particle size Dv50 (calculated with a size range of 2.05–297 μm) that correlates Dv50 with the inherent optical properties (IOPs) retrieved from in situ remote sensing reflectance above the water’s surface (Rrs(λ)) in the Pearl River estuary (PRE) in China. Rrs(λ) was resampled to simulate the Multispectral Instrument (MSI) onboard Sentinel-2A/B, and the wavebands in 490, 560, and 705 nm were utilized for the retrieval of the IOPs. The results of this method had a statistical performance of 0.86, 18.52, 21.28%, and −1.85 for the R2, RMSE, MAPE, and bias values, respectively, in validation, which indicated that Dv50 could be estimated by Rrs(λ) with the proposed four-step method. Then, the proposed method was applied to Sentinel-2 MSI imagery, and a clear difference in Dv50 distribution which was retrieved from a different time could be seen. The proposed method holds great potential for monitoring the suspended particle size of coastal waters.
Electromagnetic Scattering of Near-Field Turbulent Wake Generated by Accelerated Propeller
Authors: Deng Yuxin , Zhang Min , Jiang Wangqiang , Wang Letian
Published: December 2021

The electromagnetic scattering study of the turbulent wake of a moving ship has important application value in target recognition and tracking. However, to date, there has been insufficient research into the electromagnetic characteristics of near-field propeller turbulence. This study presents a new procedure for evaluating the electromagnetic scattering coefficient and imaging characteristics of turbulent wakes in the near field. By controlling the different values of the net momenta, a turbulent wake was generated using the large-eddy simulation method. The results show that the net momentum transferred to the background flow field determines the development of the turbulent wake, which explains the formation mechanism of the turbulence. Combined with the turbulent energy attenuation spectrum, the electromagnetic scattering characteristics of the turbulent wake were calculated using the two-scale facet mode. Using this method, the impact of different parameters on the scattering coefficient and the electromagnetic image of the turbulence wake were investigated, to explain the modulation mechanism and electromagnetic imaging characteristics of the near-field turbulent wake. Moreover, an application for estimating a ship’s heading is proposed based on the electromagnetic imaging characteristics of the turbulent wake.
Metaknowledge Enhanced Open Domain Question Answering with Wiki Documents
Authors: Liu Shukan , Xu Ruilin , Duan Li , Li Mingjie , Liu Yiming
Published: December 2021

The commonly-used large-scale knowledge bases have been facing challenges in open domain question answering tasks which are caused by the loose knowledge association and weak structural logic of triplet-based knowledge. To find a way out of this dilemma, this work proposes a novel metaknowledge enhanced approach for open domain question answering. We design an automatic approach to extract metaknowledge and build a metaknowledge network from Wiki documents. For the purpose of representing the directional weighted graph with hierarchical and semantic features, we present an original graph encoder GE4MK to model the metaknowledge network. Then, a metaknowledge enhanced graph reasoning model MEGr-Net is proposed for question answering, which aggregates both relational and neighboring interactions comparing with R-GCN and GAT. Experiments have proved the improvement of metaknowledge over main-stream triplet-based knowledge. We have found that the graph reasoning models and pre-trained language models also have influences on the metaknowledge enhanced question answering approaches.
Manual Annotation of Time in Bed Using Free-Living Recordings of Accelerometry Data
Authors: Skovgaard Esben Lykke , Pedersen Jesper , Møller Niels Christian , Grøntved Anders , Brønd Jan Christian
Published: December 2021

With the emergence of machine learning for the classification of sleep and other human behaviors from accelerometer data, the need for correctly annotated data is higher than ever. We present and evaluate a novel method for the manual annotation of in-bed periods in accelerometer data using the open-source software Audacity®, and we compare the method to the EEG-based sleep monitoring device Zmachine® Insight+ and self-reported sleep diaries. For evaluating the manual annotation method, we calculated the inter- and intra-rater agreement and agreement with Zmachine and sleep diaries using interclass correlation coefficients and Bland–Altman analysis. Our results showed excellent inter- and intra-rater agreement and excellent agreement with Zmachine and sleep diaries. The Bland–Altman limits of agreement were generally around ±30 min for the comparison between the manual annotation and the Zmachine timestamps for the in-bed period. Moreover, the mean bias was minuscule. We conclude that the manual annotation method presented is a viable option for annotating in-bed periods in accelerometer data, which will further qualify datasets without labeling or sleep records.
Vehicle Destination Prediction Using Bidirectional LSTM with Attention Mechanism
Authors: Casabianca Pietro , Zhang Yu , Martínez-García Miguel , Wan Jiafu
Published: December 2021

Satellite navigation has become ubiquitous to plan and track travelling. Having access to a vehicle’s position enables the prediction of its destination. This opens the possibility to various benefits, such as early warnings of potential hazards, route diversions to pass traffic congestion, and optimizing fuel consumption for hybrid vehicles. Thus, reliably predicting destinations can bring benefits to the transportation industry. This paper investigates using deep learning methods for predicting a vehicle’s destination based on its journey history. With this aim, Dense Neural Networks (DNNs), Long Short-Term Memory (LSTM) networks, Bidirectional LSTM (BiLSTM), and networks with and without attention mechanisms are tested. Especially, LSTM and BiLSTM models with attention mechanism are commonly used for natural language processing and text-classification-related applications. On the other hand, this paper demonstrates the viability of these techniques in the automotive and associated industrial domain, aimed at generating industrial impact. The results of using satellite navigation data show that the BiLSTM with an attention mechanism exhibits better prediction performance destination, achieving an average accuracy of 96% against the test set (4% higher than the average accuracy of the standard BiLSTM) and consistently outperforming the other models by maintaining robustness and stability during forecasting.