bluuebunny/crossref_metadata_2025 huggingface dataset:
Characterization of Wingbeat Frequency of Different Taxa of Migratory Insects in Northeast Asia
Authors: Yu Wenhua , Zhang Haowen , Xu Ruibin , Sun Yishu , Wu Kongming
Published: June 2022

The ability to migrate is an important biological trait of insects, and wingbeat frequency (WBF) is a key factor influencing migratory behavior. The WBF of insects has been shown to be species-specific in previous studies; however, there is scant information on variations in WBF among different taxa of migratory insects. In 2018 and 2019, we investigated the relationship between WBF and 12 morphological variables (e.g., body mass, body length, total wing area, etc.) of the main migratory insects (77 species in 3 orders and 14 families) over the Bohai Sea in China. The WBF of migratory insects was negatively correlated with the 12 morphological variables and varied significantly among orders. In migratory lepidopterans, neuropterans, and odonatans, the ranges of WBF were 6.71–81.28 Hz, 19.17–30.53 Hz, and 18.35–38.01 Hz, respectively. Regression models between WBF and connecting morphological variables were established for these three orders. Our findings revealed the relationship between WBF and morphometrics of migratory insects in Northeast Asia, increased our knowledge on the flight biology of migratory insects, and provided a basis for developing morphological and WBF-based monitoring techniques to identify migrating insects.
Robotic Single-Site Plus Two-Port Myomectomy versus Conventional Robotic Multi-Port Myomectomy: A Propensity Score Matching Analysis
Authors: Won Seyeon , Choi Su Hyeon , Lee Nara , Shim So Hyun , Kim Mi Kyoung , Kim Mi-La , Jung Yong Wook , Yun Bo Seong , Seong Seok Ju
Published: June 2022

Background: Robotic single-site plus two port myomectomy (RSTM) was designed to reduce the number of incision sites while retaining the advantage of conventional robotic multi-port myomectomy (CRM). This study aimed to explicate RSTM and compare surgical outcomes between it and CRM. Methods: The medical records of 146 patients who had undergone RSTM and 173 who had undergone CRM were reviewed. The surgical outcomes between them were compared by propensity score matching (PSM) analysis. Results: The PSM analysis showed no statistically significant inter-group differences in patient characteristics. With regard to surgical outcomes, the RSTM group enjoyed shorter operative time (148.30 ± 44.8 vs. 162.3 ± 47.4 min, p = 0.011), less hemoglobin decrement (1.8 ± 0.9 vs. 2.3 ± 1.0 g/dL, p < 0.001), and shorter duration of hospital stay (5.4 ± 0.7 vs. 5.8 ± 0.7 days, p < 0.001). Conclusions: RSTM was associated with shorter operative time relative to CRM. Further prospective studies are needed in order to more fully investigate the advantages of RSTM.
Evolution of the Geometric Structure of X39Cr13 Steel upon Thermochemical Treatment Specific to Medical-Grade Steels
Authors: Gwoździk Monika , Bramowicz Mirosław , Kulesza Sławomir
Published: June 2022

This paper presents the results of the multi-aspect surface characterization of X39Cr13 steel samples subjected to technological processes specific to medical instrumentation, such as heat and thermochemical treatment, as well as sterilization, which are implemented in corrosion resistance measurements. The application of numerical methods of fractal analysis to averaged profiles obtained from SEM images resulted in double-log plots of structure function, from which the determination of the fractal parameters of interest was possible. The discussion was focused on the fractal dimension D, which governs relative height variations upon scaling in length, and corner frequency fc, which separates the scaling behavior of different-order structures (particles and their aggregates). The obtained results show that the heat treatment leaves behind a granular structure of steel (D2 = 2.43; fc2 = 1.97 nm), whereas corrosion tests reveal the appearance of pits (D1 = 2.17; fc1 = 0.303 nm; D2 = 2.59; fc2 = 4.76 nm). In turn, the ion nitriding improves the resistance of steel X39Cr13 to local corrosion. The fractal analysis also shows that the structure of the nitrided layer differs insignificantly from that of the untreated material, seen only as a shortening of the radius of the self-similarity area by a factor of two (fc2 = 1 nm).
All-Solid-State Beam Steering via Integrated Optical Phased Array Technology
Authors: Zhao Shi , Chen Jingye , Shi Yaocheng
Published: June 2022

Light detection and ranging (LiDAR), combining traditional radar technology with modern laser technology, has much potential for applications in navigation, mapping, and so on. Benefiting from the superior performance, an all-solid-state beam steering realized by integrated optical phased array (OPA) is one of the key components in the LiDAR system. In this review, we first introduce the basic principle of OPA for beam steering. Then, we briefly review the detailed advances of different solutions such as micro-electromechanical system OPA, liquid crystal OPA, and metasurface OPA, where our main focus was on the recent progress of OPA in photonic integrated chips. Finally, we summarize the different solutions and discuss the challenges and perspectives of all-solid-state beam steering for LiDAR.
Study on the Stability of Functionally Graded Simply Supported Fluid-Conveying Microtube under Multi-Physical Fields
Authors: Ma Tao , Mu Anle
Published: June 2022

The stability of functionally graded simply supported fluid-conveying microtubes under multiple physical fields was studied in this article. The strain energy of the fluid-conveying microtubes was determined based on strain gradient theory, and the governing equation of the functionally graded, simply supported, fluid-conveying microtube was established using Hamilton’s principle. The Galerkin method was used to solve the governing equation, and the effects of the dimensionless microscale parameters, temperature difference, and magnetic field intensity on the stability of the microtube were investigated. The results showed that the dimensionless microscale parameters have a significant impact on the stability of the microtube. The smaller the dimensionless microscale parameters were, the stronger the microscale effect of the material and the better the microtube stability became. The increase in the temperature difference decreased the eigenfrequency and critical velocity of the microtube and reduced the microtube stability. However, the magnetic field had the opposite effect. The greater the magnetic field intensity was, the greater the eigenfrequency and critical velocity were, and the more stable the microtube became.
A Methodology Combining IDEF0 and Weighted Risk Factor Analysis for the Strategic Planning of Mine Reclamation
Authors: Spanidis Philip-Mark , Roumpos Christos , Pavloudakis Francis
Published: June 2022

The reclamation of lignite surface mines is a long-term commitment of high complexity. These reclamation projects consist of land use repurposing, reinstatement of landforms and landscape, remediation of polluted soils and water bodies, restoration of ecosystems, and other related activities, which are usually developed when mines enter the ultimate phase of their operational life. Nowadays, reclamation is supported by regulatory settings and legislative provisions, which motivate the affected communities to move towards a circular economy and sustainable development. This paper investigates the geoenvironmental and socioeconomic problems of reclamation and draws research questions on how the strategic planning of a reclamation project can be performed and how the relevant project risks can be investigated and managed. In turn, a prototype methodology based on experts’ judgment is suggested with a case study combining: (a) the IDEF0 (Integrated DEFinition Function) modelling technique, as a low cost and easy-to-develop tool enabling strategic planning of reclamation projects, and (b) the Weighted Risk Factor analysis (WRF) as a suitable method for effective risk analysis and response planning in post-mining frameworks. Finally, a discussion on the methodology and proposals for further research are provided.
Fluid-Induced Inhomogeneous Cr-spinel in Dunite and Wehrlite from the Duke Island Complex, Southeastern Alaska
Authors: Luo Yang , Su Ben-Xun , Thakurta Joyashish , Xiao Yan , Bai Yang
Published: June 2022

Cr-spinel [(Mg, Fe2+)(Cr, Al, Fe3+)2O4)] is a common mineral in the ultramafic core of the Duke Island complex in southeastern Alaska, US. Cr-spinel grains with an unmixed texture have been observed in dunite and wehrlite of the complex. Inhomogeneous Cr-spinel with a ratio of Cr/(Al + Cr + Fe3+) <0.37 is prominent in dunite. The inhomogeneous Cr-spinel consists of two completely different compositions: Al-rich Cr-spinel, and Fe3+-rich Cr-spinel with a wide range of Cr content (from 11.8 wt.% to 28.6 wt.% Cr2O3). The unmixed texture is complex, and three subtypes of inhomogeneous Cr-spinel are recognized: TypeB1 Cr-spinel showing complete separation, crystallographically oriented type B2 Cr-spinel, and irregular Al-rich Cr-spinel rimmed type B3 Cr-spinel. The unmixed texture was achieved by an unmixing process at around 600 °C due to the miscibility gap of spinel between Al-rich and Fe3+-rich phases. The unmixed patterns of inhomogeneous Cr-spinel are controlled by the initial chemical composition, grain size of the initial spinel, and the cooling process. We propose that the initial composition of inhomogeneous Cr-spinel was formed by the interaction of high-temperature fluid and olivine; Cr-spinel that experienced unmixing may be a useful proxy to unveil the activity of high-temperature fluid in the formation of Alaskan-type complexes.
Quantitative Retention (Structure)–Activity Relationships in Predicting the Pharmaceutical and Toxic Properties of Potential Pesticides
Authors: Janicka Małgorzata , Śliwińska Anna
Published: June 2022

The micellar liquid chromatography technique and quantitative retention (structure)–activity relationships method were used to predict properties of carbamic and phenoxyacetic acids derivatives, newly synthesized in our laboratory and considered as potential pesticides. Important properties of the test substances characterizing their potential significance as pesticides as well as threats to humans were considered: the volume of distribution, the unbonded fractions, the blood–brain distribution, the rate of skin and cell permeation, the dermal absorption, the binding to human serum albumin, partitioning between water and plants’ cuticles, and the lethal dose. Pharmacokinetic and toxicity parameters were predicted as functions of the solutes’ lipophilicities and the number of hydrogen bond donors, the number of hydrogen bond acceptors, and the number of rotatable bonds. The equations that were derived were evaluated statistically and cross-validated. Important features of the molecular structure influencing the properties of the tested substances were indicated. The QSAR models that were developed had high predictive ability and high reliability in modeling the properties of the molecules that were tested. The investigations highlighted the applicability of combined chromatographic technique and QS(R)ARs in modeling the important properties of potential pesticides and reducing unethical animal testing.
A Computational Analysis of the Reaction of SO2 with Amino Acid Anions: Implications for Its Chemisorption in Biobased Ionic Liquids
Authors: Piacentini Vanessa , Le Donne Andrea , Russo Stefano , Bodo Enrico
Published: June 2022

We report a series of calculations to elucidate one possible mechanism of SO2 chemisorption in amino acid-based ionic liquids. Such systems have been successfully exploited as CO2 absorbents and, since SO2 is also a by-product of fossil fuels’ combustion, their ability in capturing SO2 has been assessed by recent experiments. This work is exclusively focused on evaluating the efficiency of the chemical trapping of SO2 by analyzing its reaction with the amino group of the amino acid. We have found that, overall, SO2 is less reactive than CO2, and that the specific amino acid side chain (either acid or basic) does not play a relevant role. We noticed that bimolecular absorption processes are quite unlikely to take place, a notable difference with CO2. The barriers along the reaction paths are found to be non-negligible, around 7–11 kcal/mol, and the thermodynamic of the reaction appears, from our models, unfavorable.
The Kinetics of Formation of Microporous Polytriazine in Diphenyl Sulfone
Authors: Galukhin Andrey , Nikolaev Ilya , Nosov Roman , Vyazovkin Sergey
Published: June 2022

This study highlights the value of nonisothermal kinetic methods in selecting temperature conditions for the isothermal preparation of microporous polymeric materials. A dicyanate ester is synthesized and the kinetics of its polymerization in diphenyl sulfone are studied by calorimetry under nonisothermal conditions. The kinetics are analyzed by a model-based approach, using the Kamal model, as well as by a model-free approach, using an advanced isoconversional method. Both approaches correctly predict the time to completion of polymerization at a given temperature. The material prepared independently at the predicted temperature is characterized by electron microscopy and CO2 adsorption measurements and is confirmed to possess a microporous structure with a multimodal distribution of micropores with two major maxima at ~0.5 and 0.8 nm.
Photoelectrochemical Enhancement of Graphene@WS2 Nanosheets for Water Splitting Reaction
Authors: Nasr Mahmoud , Benhamou Lamyae , Kotbi Ahmed , Rajput Nitul S. , Campos Andrea , Lahmar Abdel-Ilah , Hoummada Khalid , Kaja Khaled , El Marssi Mimoun , Jouiad Mustapha
Published: June 2022

Tungsten disulfide nanosheets were successfully prepared by one-step chemical vapor deposition using tungsten oxide and thiourea in an inert gas environment. The size of the obtained nanosheets was subsequently reduced down to below 20 nm in width and 150 nm in length using high-energy ball milling, followed by 0.5 and 1 wt% graphene loading. The corresponding vibrational and structural characterizations are consistent with the fabrication of a pure WS2 structure for neat sampling and the presence of the graphene characteristic vibration modes in graphene@WS2 compounds. Additional morphological and crystal structures were examined and confirmed by high-resolution electron microscopy. Subsequently, the investigations of the optical properties evidenced the high optical absorption (98%) and lower band gap (1.75 eV) for the graphene@WS2 compared to the other samples, with good band-edge alignment to water-splitting reaction. In addition, the photoelectrochemical measurements revealed that the graphene@WS2 (1 wt%) exhibits an excellent photocurrent density (95 μA/cm2 at 1.23 V bias) compared with RHE and higher applied bias potential efficiency under standard simulated solar illumination AM1.5G. Precisely, graphene@WS2 (1 wt%) exhibits 3.3 times higher performance compared to pristine WS2 and higher charge transfer ability, as measured by electrical impedance spectroscopy, suggesting its potential use as an efficient photoanode for hydrogen evolution reaction.
US Consumer Identification of the Health Benefits of Dietary Fiber and Consideration of Fiber When Making Food Choices
Authors: Gustafson Christopher R. , Rose Devin J.
Published: June 2022

The purposes of this study were to (1) determine beliefs in the health benefits of dietary fiber, an under-consumed nutrient of public health concern, and (2) determine the relationship between beliefs about dietary fiber and consideration of fiber when making food choices. We conducted a nationally representative within-subject randomized online survey of 42,018 US primary shoppers in May–June 2021. Participants selected health benefits they believed were associated with consumption of fiber from a list of six benefits recognized by the Food and Drug Administration (FDA), one indirect benefit, and one unrelated benefit. Respondents then indicated which nutrients, if any, they considered when making food choices. Respondents selected 1.77 (95% CI = 1.76–1.77) FDA-recognized benefits out of a total six; half (50.6%) of respondents identified zero or one FDA-recognized benefit. The most-cited benefit was “improving bowel movements” (64.4%). Older participants perceived significantly more FDA-recognized fiber benefits. Identification of FDA-recognized benefits increased odds ratios for consideration of fiber during food choice (relative to zero benefits) from 3.0 for one benefit (95% CI = 2.8–3.3) to 14.3 for six benefits (95% CI = 12.4–16.6). Consumers are largely unaware of the many health benefits of dietary fiber, which dramatically decreases the likelihood that they consider this important, under-consumed nutrient during food choice.
Gluten-Free Cereals and Pseudocereals as a Potential Source of Exposure to Toxic Elements among Polish Residents
Authors: Bielecka Joanna , Markiewicz-Żukowska Renata , Puścion-Jakubik Anna , Grabia Monika , Nowakowski Patryk , Soroczyńska Jolanta , Socha Katarzyna
Published: June 2022

Background: Nutritional food quality plays a crucial role in maintaining human health. However, food and drinking water, along with occupational exposure, are the main routes of exposure to toxic elements for humans. The main aim of this study was to determine the content of As, Cd, Pb and Hg in naturally gluten-free grains and products made from buckwheat, millet, maize, quinoa and oat. The safety of consumption of the products tested was also assessed. Methods: The contents of As, Cd and Pb were determined using inductively coupled plasma mass spectrometry (ICP-MS). To measure Hg, an atomic absorption spectrometry method (AAS) with the amalgamation technique was applied. To assess the level of consumption of the tested products, an online survey was conducted. To estimate health risk, three indicators were used: the target hazard quotient (THQ), cancer risk (CR) and hazard index (HI). The research material obtained 242 different samples without replications. Results: The highest average content of As, Cd, Pb and Hg were observed for the following groups of products: oat (10.19 µg/kg), buckwheat (48.35 µg/kg), millet (74.52 µg/kg) and buckwheat (1.37 µg/kg), respectively. For six samples, exceedance of established limits was found—three in the case of Cd and three of Pb. Due to the lack of established limits, As and Hg content of the tested products was not compared. Generally, no increased health risks were identified. Conclusions: Based on the obtained results, the consumption of gluten-free cereals and pseudocereals available on the Polish market seems to be safe. However, there is a great need to establish maximum levels of the toxic elements, especially As and Hg in cereal products in European legislation.
Foot-and-Mouth Disease Virus Interserotypic Recombination in Superinfected Carrier Cattle
Authors: Fish Ian , Stenfeldt Carolina , Spinard Edward , Medina Gisselle N. , Azzinaro Paul A. , Bertram Miranda R. , Holinka Lauren , Smoliga George R. , Hartwig Ethan J. , de los Santos Teresa , Arzt Jonathan
Published: June 2022

Viral recombination contributes to the emergence of novel strains with the potential for altered host range, transmissibility, virulence, and immune evasion. For foot-and-mouth disease virus (FMDV), cell culture experiments and phylogenetic analyses of field samples have demonstrated the occurrence of recombination. However, the frequency of recombination and associated virus–host interactions within an infected host have not been determined. We have previously reported the detection of interserotypic recombinant FMDVs in oropharyngeal fluid (OPF) samples of 42% (5/12) of heterologously superinfected FMDV carrier cattle. The present investigation consists of a detailed analysis of the virus populations in these samples including identification and characterization of additional interserotypic minority recombinants. In every animal in which recombination was detected, recombinant viruses were identified in the OPF at the earliest sampling point after superinfection. Some recombinants remained dominant until the end of the experiment, whereas others were outcompeted by parental strains. Genomic analysis of detected recombinants suggests host immune pressure as a major driver of recombinant emergence as all recombinants had capsid-coding regions derived from the superinfecting virus to which the animals did not have detectable antibodies at the time of infection. In vitro analysis of a plaque-purified recombinant virus demonstrated a growth rate comparable to its parental precursors, and measurement of its specific infectivity suggested that the recombinant virus incurred no penalty in packaging its new chimeric genome. These findings have important implications for the potential role of persistently infected carriers in FMDV ecology and the emergence of novel strains.
Recent Progress in the Synthesis of Drugs and Bioactive Molecules Incorporating Nitro(het)arene Core
Authors: Bastrakov Maxim , Starosotnikov Alexey
Published: June 2022

Aromatic nitro compounds play a unique role in the synthesis of drugs and pharmaceutically oriented molecules. This field of organic chemistry continues to be in demand and relevant. A significant number of papers are published annually on new general methods for the synthesis of nitrodrugs and related biomolecules. This review is an analysis of the literature on methods for the synthesis of both new and already-known aromatic and heteroaromatic nitrodrugs covering the period from 2010 to the present.
Lower Inspiratory Breathing Depth Enhances Pulmonary Delivery Efficiency of ProAir Sprays
Authors: Talaat Mohamed , Si Xiuhua , Xi Jinxiang
Published: June 2022

Effective pulmonary drug delivery using a metered-dose inhaler (MDI) requires a match between the MDI sprays, the patient’s breathing, and respiratory physiology. Different inhalers generate aerosols with distinct aerosol sizes and speeds, which require specific breathing coordination to achieve optimized delivery efficiency. Inability to perform the instructed breathing maneuver is one of the frequently reported issues during MDI applications; however, their effects on MDI dosimetry are unclear. The objective of this study is to systemically evaluate the effects of breathing depths on regional deposition in the respiratory tract using a ProAir-HFA inhaler. An integrated inhaler mouth-throat-lung geometry model was developed that extends to the ninth bifurcation (G9). Large-eddy simulation (LES) was used to compute the airflow dynamics due to concurrent inhalation and orifice flows. The discrete-phase Lagrangian model was used to track droplet motions. Experimental measurements of ProAir spray droplet sizes and speeds were used as initial and boundary conditions to develop the computational model for ProAir-pulmonary drug delivery. The time-varying spray plume from a ProAir-HFA inhaler into the open air was visualized using a high-speed imaging system and was further used to validate the computational model. The inhalation dosimetry of ProAir spray droplets in the respiratory tract was compared among five breathing depths on a regional, sub-regional, and local basis. The results show remarkable differences in airflow dynamics within the MDI mouthpiece and the droplet deposition distribution in the oral cavity. The inhalation depth had a positive relationship with the deposition in the mouth and a negative relationship with the deposition in the five lobes beyond G9 (small airways). The highest delivery efficiency to small airways was highest at 15 L/min and declined with an increasing inhalation depth. The drug loss inside the MDI was maximal at 45–60 L/min. Comparisons to previous experimental and numerical studies revealed a high dosimetry sensitivity to the inhaler type and patient breathing condition. Considering the appropriate inhalation waveform, spray actuation time, and spray properties (size and velocity) is essential to accurately predict inhalation dosimetry from MDIs. The results highlight the importance of personalized inhalation therapy to match the patient’s breathing patterns for optimal delivery efficiencies. Further complimentary in vitro or in vivo experiments are needed to validate the enhanced pulmonary delivery at 15 L/min.
Effect of Diluents on Mechanical Characteristics of Epoxy Compounds
Authors: Rudawska Anna , Frigione Mariaenrica
Published: June 2022

The aim of this work is to assess the influence of different commercial diluents on some mechanical properties of two bisphenolic epoxy compounds, cold-cured by a polyamide curing agent, to be employed as epoxy structural adhesives for building and industrial applications. The diluents under analysis were epoxy, bituminous, nitro, acrylic and extraction. The choice of these products was made on the basis of their wide commercial availability as diluents for epoxies used as adhesives and in different industrial and construction applications. The diluents were all added in small proportions, i.e., from 1 to 10 g per 100 g of epoxy resin. The cold-cured epoxy compounds were subjected to compressive (according to ISO 604) and static tensile (according to ISO 527-1) tests. The same mechanical tests were performed on both unmodified epoxy resins, for comparison purposes. On the basis of the obtained results, it was concluded that the influence of the presence of a diluent, and of its amount, on the mechanical properties of epoxy compounds depends on the type of resin and of diluent, as well as on the mechanical characteristics analyzed.
The Loss of the Self—Spiritual Abuse of Adults in the Context of the Catholic Church
Authors: Demasure Karlijn
Published: June 2022

Interest in spiritual abuse is a fairly recent phenomenon in research. Originally, it received attention only in the context of child sexual abuse perpetrated by the clergy in the Catholic Church before it was recognized as a specific form of abuse in its own right. In line with Paul Ricœur, I agree that a narrative best describes a person’s identity. I, therefore, give space to the voices of three women who were spiritually abused as adults in France in the context of new religious communities that originated after the Second Vatican Council: Sophie Ducrey, Anne Mardon and Marie-Laure Janssens. The social constructionist method allows the uniqueness of each of their narratives to be recognized, while also accounting for shared experiences such as the dynamics of control, desocialization and intrusion into the private spheres of life. Spiritual abuse, which is at the hinge point between the moral and spiritual and the psychological realms, is perpetrated by a spiritual leader who has power over women. The abuse serves to fulfill the psychological or sexual needs of the leader. Abuse of the conscience, theology and spirituality are the spiritual means used, alongside the psychological ones, to cause the women to become dependent. In the process, their desire for God and the affective needs that some may have are abused. The consequences are many, but the loss of self, of which faith is the core, summarizes it well.
Monitoring Desertification Using Machine-Learning Techniques with Multiple Indicators Derived from MODIS Images in Mu Us Sandy Land, China
Authors: Feng Kun , Wang Tao , Liu Shulin , Kang Wenping , Chen Xiang , Guo Zichen , Zhi Ying
Published: June 2022

Mu Us Sandy Land is a typical semi-arid vulnerable ecological zone, characterized by vegetation degradation and severe desertification. Effectively identifying desertification changes has been a topical environmental issue in China. However, most previous studies have used a single method or remote sensing index to monitor desertification, and lacked an efficient and high-precision monitoring system. In this study, an optimal monitoring scheme that considers multiple indicators combination and different machine learning methods (Classification and Regression Tree-Decision Tree, CART-DT; Random Forest, RF; Convolutional Neural Networks, CNN) was developed and used to analyze the spatial–temporal patterns of desertification from 2000 to 2018 in Mu Us Sandy Land. The results showed that: (a) The random forest model performed best for monitoring desertification based on medium and low-resolution remote sensing images, and the four-index combination (Albedo, NDVI, LST and TGSI) obtained the highest classification accuracy (OA = 87.67%) in Mu Us Sandy Land. Surprisingly, the model accuracy of the three-index combination (NDVI, LST and TGSI) (OA = 85.74%) is comparable to the four-index combination. (b) The TGSI index used to characterize soil information performs well, while the LST is not conducive to the extraction of desertified land in several desertification monitoring indicators. (c) Since 2000, the area of extremely severe desertified land has shown a reversal trend; however, there is significant interannual fluctuation in the total and light desertification land area affected by extreme climate. This research provides a novel approach and a valuable reference for monitoring the evolution of desertification in regional studies, and the results improve the research system of desertification and provide a data basis for desertification cause analysis and prevention.
Machine-Learning for Mapping and Monitoring Shallow Coral Reef Habitats
Authors: Burns Christopher , Bollard Barbara , Narayanan Ajit
Published: June 2022

Mapping and monitoring coral reef benthic composition using remotely sensed imagery provides a large-scale inference of spatial and temporal dynamics. These maps have become essential components in marine science and management, with their utility being dependent upon accuracy, scale, and repeatability. One of the primary factors that affects the utility of a coral reef benthic composition map is the choice of the machine-learning algorithm used to classify the coral reef benthic classes. Current machine-learning algorithms used to map coral reef benthic composition and detect changes over time achieve moderate to high overall accuracies yet have not demonstrated spatio-temporal generalisation. The inability to generalise limits their scalability to only those reefs where in situ reference data samples are present. This limitation is becoming more pronounced given the rapid increase in the availability of high temporal (daily) and high spatial resolution (<5 m) multispectral satellite imagery. Therefore, there is presently a need to identify algorithms capable of spatio-temporal generalisation in order to increase the scalability of coral reef benthic composition mapping and change detection. This review focuses on the most commonly used machine-learning algorithms applied to map coral reef benthic composition and detect benthic changes over time using multispectral satellite imagery. The review then introduces convolutional neural networks that have recently demonstrated an ability to spatially and temporally generalise in relation to coral reef benthic mapping; and recurrent neural networks that have demonstrated spatio-temporal generalisation in the field of land cover change detection. A clear conclusion of this review is that existing convolutional neural network and recurrent neural network frameworks hold the most potential in relation to increasing the spatio-temporal scalability of coral reef benthic composition mapping and change detection due to their ability to spatially and temporally generalise.
GPR Application on Geothermal Studies: The Case Study of the Thermal Baths of San Xusto (Pontevedra, Spain)
Authors: Solla Mercedes , Blázquez Cristina Sáez , Nieto Ignacio Martín , Rodríguez Juan Luis , Maté-González Miguel Ángel
Published: June 2022

Geophysical studies are frequently used on the geothermal field to define and characterize deep structures. However, shallow investigations are also needed for understanding the origin and local potential structures of a promising geothermal site. In this research, it is intended to present a review of the possibilities of the application of ground-penetrating radar (GPR) on the study of geothermal resources and how this geophysical technique can contribute to improving the energy use of these thermal resources. For this, the specific case of application to the investigation of the thermal baths of San Xusto (Pontevedra, Spain) is included in this work, whose interest for the region makes it necessary to perform an in-depth analysis of the original thermal structure. A GPR survey with frequency antennas of 200 and 500 MHz was conducted. Additionally, chemical analyses were performed to characterize the thermal water in the San Xusto site. As a result, a hot spring was detected by identifying reverberation phenomena in GPR imaging due to the presence of metal compounds and silica. Locating the origin of the thermal springs could allow for a more efficient use of the thermal resources as well as the hydrothermal possibilities of the area.
Estimation of Corn Latent Heat Flux from High Resolution Thermal Imagery
Authors: Zhu Yan , Ludwig Elaina M. , Cherkauer Keith A.
Published: June 2022

Crop evapotranspiration (ET), which is directly related to latent heat flux, is also a key indicator in determining the water status of crops. In order to estimate the latent heat flux, two-source energy balance (TSEB) models have been developed for thermal imagery from satellite platforms. However, because of the coarse resolution of thermal sensors on the satellite, distinguishing soil and vegetation is difficult which complicates the calculation process and introduces errors in latent heat estimates. In this research, high-resolution thermal datasets (0.05 m) and corresponding RGB datasets (0.03 m) were used for calculating crop latent heat flux using an adapted TSEB model. The RGB datasets were used for supervised classification of soil and vegetation, and the classification results were then used to filter the thermal mosaics to separate vegetation and soil temperatures. The vegetation temperature is used for calculating latent heat flux and the results are validated against the ground reference measurements of latent heat using a handheld porometer. The objective of this research is to introduce a workflow including an adapted TSEB model which is customized for high resolution thermal images from unmanned aircraft systems (UAS) to estimate the latent heat flux of row crops in agricultural fields. Nine dates of data collection in 2018 and 2020 have been evaluated and the root mean square error (RMSE) varies between 16 to 106 W/m2 depending on the days after planting (DAP) and the time of measurement for each day. The results indicate that the workflow introduced here is able to provide estimates of instantaneous latent heat flux (evapotranspiration) measurements for row crops in agricultural fields which will enable people to make reliable decisions related to irrigation scheduling.
Displacement Back Analysis of Reservoir Landslide Based on Multi-Source Monitoring Data: A Case Study of the Cheyiping Landslide in the Lancang River Basin, China
Authors: Guo Chengqian , Ma Gang , Xiao Haibin , Zhou Wei , Chen Hongjie , Zhou Zhiwei , Cheng Xiang
Published: June 2022

Landslides that occur in the littoral zone of a reservoir can directly damage the hydraulic structures and threaten the lives and property around the reservoir. Due to the spatial variability and heterogeneities of rock mass, a limited amount of data obtained from laboratory and in situ tests cannot comprehensively characterize the mechanical properties of rock and soil masses. Therefore, displacement back analysis is often performed to determine the mechanical parameters of rock and soil masses. The spaceborne Interferometric synthetic aperture radar (InSAR) has proved to be a powerful tool for geodesy in the measurement of landslide movement. However, InSAR can only measure the surface motion of the landslide without the subsurface information. This study uses multi-source monitoring data in the landslide displacement back analysis, including surface InSAR and an internal borehole inclinometer. The identified material parameters and finite element simulation are used to predict the landslide deformation. The case study of the Cheyiping landslide located in the Lancang River basin demonstrates the necessity and feasibility of using multi-source monitoring data in landslide displacement back analysis. The Cheyiping landslide is currently in the creep deformation stage. The decrease in shear strength of rock masses due to the rheological deformation and the change in reservoir water level are the internal and external factors leading to excessive landslide deformation. The numerical modeling can accurately simulate the landslide movement using the identified material parameters. By combing multi-source monitoring data and numerical modeling, the reservoir landslide deformation analysis can help evaluate the landslide deformation state and stability, which is vital for reservoir risk mitigation and the sustainable development of hydropower resources.
Characteristics of the Spatio-Temporal Dynamics of Aerosols in Central Asia and Their Influencing Factors
Authors: Zhou Yongchao , Gao Xin , Meng Xiaoyu , Lei Jiaqiang , Halik Ümüt
Published: June 2022

Aerosols are an important component of the atmospheric system. Long time-series observations for aerosols are essential for examining global climate change and the ecological environment. Based on Google Earth Engine and MODIS MCD19A2 data, we monitored the spatio-temporal dynamic characteristics of the aerosol optical depth (AOD) in Central Asia from 2001 to 2020. The effects of six environmental factors on the AOD distribution were explored using a geographic detector model and analysed in combination with the land-use/land-cover change (LUCC) and desertification in different periods. The results showed that the average multi-year AOD in Central Asia was 0.1442, with insignificant interannual variations. The high-value areas were mainly distributed in the Aral Sea and surrounding areas of the Tarim Basin in Xinjiang, with notable seasonal variations. The evaluation results for the influencing factors showed that the relative humidity and precipitation had a large effect on the spatial distribution of the AOD. The LUCC directly affected contributions to the AOD. Desertification of land provides rich dust sources, which are the main aerosol sources in Central Asia, thus exacerbating dust aerosol pollution. This study investigated the temporal and spatial characteristics and influencing factors of the AOD in Central Asia, providing a theoretical basis for the prevention and control of air pollution.
Dual-Frequency Radar Retrievals of Snowfall Using Random Forest
Authors: Yu Tiantian , Chandrasekar V. , Xiao Hui , Yang Ling , Luo Li , Li Xiang
Published: June 2022

The microphysical parameters of snowfall directly impact hydrological and atmospheric models. During the International Collaborative Experiment hosted at the Pyeongchang 2018 Olympic and Paralympic Winter Games (ICE-POP 2018), dual-frequency radar retrievals of particle size distribution (PSD) parameters were produced and assessed over complex terrain. The NASA Dual-frequency Dual-polarized Doppler Radar (D3R) and a collection of second-generation Particle Size and Velocity (PARSIVEL2) disdrometer observations were used to develop retrievals. The conventional look-up table method (LUT) and random forest method (RF) were applied to the disdrometer data to develop retrievals for the volume-weighted mean diameter (Dm), the shape factor (mu), the normalized intercept parameter (Nw), the ice water content (IWC), and the snowfall rate (S). Evaluations were performed between the D3R radar and disdrometer observations using these two methods. The mean errors of the retrievals based on the RF method were small compared with those of the LUT method. The results indicate that the RF method is a promising way of retrieving microphysical parameters, because this method does not require any assumptions about the PSD of snowfall.
A Land Use Classification Model Based on Conditional Random Fields and Attention Mechanism Convolutional Networks
Authors: Zheng Kang , Wang Haiying , Qin Fen , Han Zhigang
Published: June 2022

Land use is used to reflect the expression of human activities in space, and land use classification is a way to obtain accurate land use information. Obtaining high-precision land use classification from remote sensing images remains a significant challenge. Traditional machine learning methods and image semantic segmentation models are unable to make full use of the spatial and contextual information of images. This results in land use classification that does not meet high-precision requirements. In order to improve the accuracy of land use classification, we propose a land use classification model, called DADNet-CRFs, that integrates an attention mechanism and conditional random fields (CRFs). The model is divided into two modules: the Dual Attention Dense Network (DADNet) and CRFs. First, the convolution method in the UNet network is modified to Dense Convolution, and the band-hole pyramid pooling module, spatial location attention mechanism module, and channel attention mechanism module are fused at appropriate locations in the network, which together form DADNet. Second, the DADNet segmentation results are used as a priori conditions to guide the training of CRFs. The model is tested with the GID dataset, and the results show that the overall accuracy of land use classification obtained with this model is 7.36% and 1.61% higher than FCN-8s and BiSeNet in classification accuracy, 11.95% and 1.81% higher in MIoU accuracy, and with a 9.35% and 2.07% higher kappa coefficient, respectively. The proposed DADNet-CRFs model can fully use the spatial and contextual semantic information of high-resolution remote sensing images, and it effectively improves the accuracy of land use classification. The model can serve as a highly accurate automatic classification tool for land use classification and mapping high-resolution images.
Satellite Video Tracking by Multi-Feature Correlation Filters with Motion Estimation
Authors: Zhang Yan , Chen Deng , Zheng Yuhui
Published: June 2022

As a novel method of earth observation, video satellites can observe dynamic changes in ground targets in real time. To make use of satellite videos, target tracking in satellite videos has received extensive interest. However, this also faces a variety of new challenges such as global occlusion, low resolution, and insufficient information compared with traditional target tracking. To handle the abovementioned problems, a multi-feature correlation filter with motion estimation is proposed. First, we propose a motion estimation algorithm that combines a Kalman filter and an inertial mechanism to alleviate the boundary effects. This can also be used to track the occluded target. Then, we fuse a histogram of oriented gradient (HOG) features and optical flow (OF) features to improve the representation information of the target. Finally, we introduce a disruptor-aware mechanism to weaken the influence of background noise. Experimental results verify that our algorithm can achieve high tracking performance.
A Coherent Integration Segment Searching Based GRT-GRFT Hybrid Integration Method for Arbitrary Fluctuating Target
Authors: Zhang Zhenghe , Liu Nan , Hou Yongning , Zhang Shiyu , Zhang Linrang
Published: June 2022

Long-time integration is an effective method for improving the signal–to–noise ratio (SNR) of an echo. However, if the target radar cross-section (RCS) fluctuates over the long integration time, the traditional coherent integration and noncoherent integration methods will produce significant performance losses, making it impossible to achieve a favorable integration performance at low SNRs. This study proposes a new hybrid integration method based on the generalized Radon–Fourier transform (GRFT) and generalized Radon transform (GRT) for targets with which echoes are partially coherent. First, a coherent integration is performed with GRFT within the optimal coherent processing segment using optimal coherent processing segmented matching. Then, the GRT is used for noncoherent integration between the coherent processing sections, and the target motion parameters are obtained through a global search. Compared with the GRFT, GRT, and moving target detection (MTD)-GRT methods, the proposed method applies to targets with arbitrary RCS fluctuations, arbitrary cross-range cells, and cross-Doppler cells, and offers the best detection performance. Finally, both simulation results and measured data processing results demonstrate the effectiveness of the algorithm.
Noise2Kernel: Adaptive Self-Supervised Blind Denoising Using a Dilated Convolutional Kernel Architecture
Authors: Lee Kanggeun , Jeong Won-Ki
Published: June 2022

With the advent of unsupervised learning, efficient training of a deep network for image denoising without pairs of noisy and clean images has become feasible. Most current unsupervised denoising methods are built on self-supervised loss with the assumption of zero-mean noise under the signal-independent condition, which causes brightness-shifting artifacts on unconventional noise statistics (i.e., different from commonly used noise models). Moreover, most blind denoising methods require a random masking scheme for training to ensure the invariance of the denoising process. In this study, we propose a dilated convolutional network that satisfies an invariant property, allowing efficient kernel-based training without random masking. We also propose an adaptive self-supervision loss to increase the tolerance for unconventional noise, which is specifically effective in removing salt-and-pepper or hybrid noise where prior knowledge of noise statistics is not readily available. We demonstrate the efficacy of the proposed method by comparing it with state-of-the-art denoising methods using various examples.
Optimization of Medication Delivery Drone with IoT-Guidance Landing System Based on Direction and Intensity of Light
Authors: Baloola Mohamed Osman , Ibrahim Fatimah , Mohktar Mas S.
Published: June 2022

This paper presents an optimization of the medication delivery drone with the Internet of Things (IoT)-Guidance Landing System based on direction and intensity of light. The IoT-GLS was incorporated into the system to assist the drone’s operator or autonomous system to select the best landing angles for landing. The landing selection was based on the direction and intensity of the light. The medication delivery drone system was developed using an Arduino Uno microcontroller board, ESP32 DevKitC V4 board, multiple sensors, and IoT mobile apps to optimize face detection. This system can detect and compare real-time light intensity from all directions. The results showed that the IoT-GLS has improved the distance of detection by 192% in a dark environment and exhibited an improvement in face detection distance up to 147 cm in a room with low light intensity. Furthermore, a significant correlation was found between face recognition’s detection distance, light source direction, light intensity, and light color (p < 0.05). The findings of an optimal efficiency of facial recognition for medication delivery was achieved due to the ability of the IoT-GLS to select the best angle of landing based on the light direction and intensity.