bluuebunny/crossref_metadata_2025 huggingface dataset:
A Divine Rebellion: Indigenous Sacraments among Global “Lamanites”
Authors: Hernandez Daniel
Published: April 2021

This essay engages with some of the experiences and metaphysics of Indigenous peoples who are members of The Church of Jesus Christ of Latter-day Saints (Mormonism/LDS/the Church) by responding to their structural construction as “Lamanites”. Lamanites have been interpreted within Mormonism to be ancestors of various global Indigenous peoples of the “Americas” and “Polynesia”. This essay reveals how contemporary Indigenous agency by presumed descendants of the Lamanites, who embrace both an Indigenous and a Mormon identity, shifts the cosmology of the Church. Interpretations of TheBook of Mormon that empower contemporary Indigenous agency paradoxically materialize a divinely inspired cultural rebellion within the Church itself. However, this tension that is mediated by Lamanites in the Church is not framed as an exclusive response to the Church itself but, rather, to a larger global hegemony of coloniality to which the Church is subject. These Lamanite worldviews can be understood as a process of restoring ancestral Indigenous sacraments (rituals) through Mormon paradigms, which are found and nurtured in the cracks and fissures of both the material and ontological infrastructure of Mormonism’s dominant paradigm. When Indigenous Mormons assert autonomous authorship of their own cosmogony and metaphysics, the Church beliefs of restoring a ‘primitive Christian church’ and ‘becoming Gods’ is creatively transformed into a more relevant and liberating possibility here and now.
The Use of Sentinel-2 for Chlorophyll-a Spatial Dynamics Assessment: A Comparative Study on Different Lakes in Northern Germany
Authors: Ogashawara Igor , Kiel Christine , Jechow Andreas , Kohnert Katrin , Ruhtz Thomas , Grossart Hans-Peter , Hölker Franz , Nejstgaard Jens C. , Berger Stella A. , Wollrab Sabine
Published: April 2021

Eutrophication of inland waters is an environmental issue that is becoming more common with climatic variability. Monitoring of this aquatic problem is commonly based on the chlorophyll-a concentration monitored by routine sampling with limited temporal and spatial coverage. Remote sensing data can be used to improve monitoring, especially after the launch of the MultiSpectral Instrument (MSI) on Sentinel-2. In this study, we compared the estimation of chlorophyll-a (chl-a) from different bio-optical algorithms using hyperspectral proximal remote sensing measurements, from simulated MSI responses and from an MSI image. For the satellite image, we also compare different atmospheric corrections routines before the comparison of different bio-optical algorithms. We used in situ data collected in 2019 from 97 sampling points across 19 different lakes. The atmospheric correction assessment showed that the performances of the routines varied for each spectral band. Therefore, we selected C2X, which performed best for bands 4 (root mean square error—RMSE = 0.003), 5 (RMSE = 0.004) and 6 (RMSE = 0.002), which are usually used for the estimation of chl-a. Considering all samples from the 19 lakes, the best performing chl-a algorithm and calibration achieved a RMSE of 16.97 mg/m3. When we consider only one lake chain composed of meso-to-eutrophic lakes, the performance improved (RMSE: 10.97 mg/m3). This shows that for the studied meso-to-eutrophic waters, we can reliably estimate chl-a concentration, whereas for oligotrophic waters, further research is needed. The assessment of chl-a from space allows us to assess spatial dynamics of the environment, which can be important for the management of water resources. However, to have an accurate product, similar optical water types are important for the overall performance of the bio-optical algorithm.
Toward a Comprehensive Dam Monitoring: On-Site and Remote-Retrieved Forcing Factors and Resulting Displacements (GNSS and PS–InSAR)
Authors: Maltese Antonino , Pipitone Claudia , Dardanelli Gino , Capodici Fulvio , Muller Jan-Peter
Published: April 2021

Many factors can influence the displacements of a dam, including water level variability and environmental temperatures, in addition to the dam composition. In this work, optical-based classification, thermal diachronic analysis, and a quasi-PS (Persistent Scatter) Interferometric SAR technique have been applied to determine both forcing factors and resulting displacements of the crest of the Castello dam (South Italy) over a one-year time period. The dataset includes Sentinel-1A images acquired in Interferometric Wide swath mode using the Terrain Observation with Progressive Scans SAR (TOPSAR); Landsat 8 Thermal Infrared Sensor (TIRS) thermal images, and Global Navigation Satellite System (GNSS) for interpreting the motion of the top of the dam retrieved via interferometry. Results suggest that it is possible to monitor both dam water level and temperature periodic forcing factors and resulting displacements via a synergistic use of different satellite images.
Design of a Local Nested Grid for the Optimal Combined Use of Landsat 8 and Sentinel 2 Data
Authors: Hernández-López David , Piedelobo Laura , Moreno Miguel A. , Chakhar Amal , Ortega-Terol Damián , González-Aguilera Diego
Published: April 2021

Earth Observation (EO) imagery is difficult to find and access for the intermediate user, requiring advanced skills and tools to transform it into useful information. Currently, remote sensing data is increasingly freely and openly available from different satellite platforms. However, the variety of images in terms of different types of sensors, spatial and spectral resolutions generates limitations due to the heterogeneity and complexity of the data, making it difficult to exploit the full potential of satellite imagery. Addressing this issue requires new approaches to organize, manage, and analyse remote-sensing imagery. This paper focuses on the growing trend based on satellite EO and the analysis-ready data (ARD) to integrate two public optical satellite missions: Landsat 8 (L8) and Sentinel 2 (S2). This paper proposes a new way to combine S2 and L8 imagery based on a Local Nested Grid (LNG). The LNG designed plays a key role in the development of new products within the European EO downstream sector, which must incorporate assimilation techniques and interoperability best practices, automatization, systemization, and integrated web-based services that will potentially lead to pre-operational downstream services. The approach was tested in the Duero river basin (78,859 km2) and in the groundwater Mancha Oriental (7279 km2) in the Jucar river basin, Spain. In addition, a viewer based on Geoserver was prepared for visualizing the LNG of S2 and L8, and the Normalized Difference Vegetation Index (NDVI) values in points. Thanks to the LNG presented in this paper, the processing, storage, and publication tasks are optimal for the combined use of images from two different satellite sensors when the relationship between spatial resolutions is an integer (3 in the case of L8 and S2).
Joint Ship Detection Based on Time-Frequency Domain and CFAR Methods with HF Radar
Authors: Yang Zhiqing , Tang Jianjiang , Zhou Hao , Xu Xinjun , Tian Yingwei , Wen Biyang
Published: April 2021

Compact high-frequency surface wave radar (HFSWR) plays a critical role in ship surveillance. Due to the wide antenna beam-width and low spatial gain, traditional constant false alarm rate (CFAR) detectors often induce a low detection probability. To solve this problem, a joint detection algorithm based on time-frequency (TF) analysis and the CFAR method is proposed in this paper. After the TF ridge extraction, CFAR detection is performed to test each sample of the ridges, and a binary integration is run to determine whether the entire TF ridge is of a ship. To verify the effectiveness of the proposed algorithm, experimental data collected by the Ocean State Monitoring and Analyzing Radar, type SD (OSMAR-SD) were used, with the ship records from an automatic identification system (AIS) used as ground truth data. The processing results showed that the joint TF-CFAR method outperformed CFAR in detecting non-stationary and weak signals and those within the first-order sea clutters, whereas CFAR outperformed TF-CFAR in identifying multiple signals with similar frequencies. Notably, the intersection of the matched detection sets by TF-CFAR and CFAR alone was not immense, which takes up approximately 68% of the matched number by CFAR and 25% of that by TF-CFAR; however, the number in the union detection sets was much (>30%) greater than the result of either method. Therefore, joint detection with TF-CFAR and CFAR can further increase the detection probability and greatly improve detection performance under complicated situations, such as non-stationarity, low signal-to-noise ratio (SNR), and within the first-order sea clutters.
Spectral Assessment of Organic Matter with Different Composition Using Reflectance Spectroscopy
Authors: Francos Nicolas , Ogen Yaron , Ben-Dor Eyal
Published: April 2021

Soil surveys are critical for maintaining sustainable use of natural resources while minimizing harmful impacts to the ecosystem. A key soil attribute for many environmental factors, such as CO2 budget, soil fertility and sustainability, is soil organic matter (SOM), as well as its sequestration. Soil spectroscopy is a popular method to assess SOM content rapidly in both field and laboratory domains. However, SOM source composition differs from soil to soil, and the use of spectral-based models for quantifying SOM may present limited accuracy when applying a generic approach to SOM assessment. We therefore examined the extent to which the generic approach can assess SOM contents of different origin using spectral-based models. We created an artificial big dataset composed of pure dune sand as a SOM-free background, which was artificially mixed with increasing amounts of different organic matter (OM) sources obtained from commercial compost of different origins. Dune sand has high albedo and yields optimal conditions for SOM detection. This study combined two methods: partial least squares regression for the prediction of SOM content from reflectance values across the 400–2500 nm region and a soil spectral detection limit (SSDL) to judge the prediction accuracy. Spectral-based models to assess SOM content were evaluated with each OM source as well as with a merged dataset that contained all of the generated samples (generic approach). The latter was concluded to have limitations for assessing low amounts of SOM (<0.6%), even under controlled conditions. Moreover, some of the OM sources were more difficult to monitor than others; accordingly, caution is advised when different SOM sources are present in the examined population.
Joint Interpretation of Geophysical Results and Geological Observations for Detecting Buried Active Faults: The Case of the “Il Lago” Plain (Pettoranello del Molise, Italy)
Authors: Nappi Rosa , Paoletti Valeria , D’Antonio Donato , Soldovieri Francesco , Capozzoli Luigi , Ludeno Giovanni , Porfido Sabina , Michetti Alessandro Maria
Published: April 2021

We report a geophysical study across an active normal fault in the Southern Apennines. The surveyed area is the “Il Lago” Plain (Pettoranello del Molise), at the foot of Mt. Patalecchia (Molise Apennines, Southern Italy), a small tectonic basin filled by Holocene deposits located at the NW termination of the major Quaternary Bojano basin structure. This basin, on the NE flank of the Matese Massif, was the epicentral area of the very strong 26 July, 1805, Sant’Anna earthquake (I0 = X MCS, Mw = 6.7). The “Il Lago” Plain is bordered by a portion of the right-stepping normal fault system bounding the whole Bojano Quaternary basin (28 km long). The seismic source responsible for the 1805 earthquake is regarded as one of the most hazardous structures of the Apennines; however, the position of its NW boundary of this seismic source is debated. Geological, geomorphological and macroseismic data show that some coseismic surface faulting also occurred in correspondence with the border fault of the “Il Lago” Plain. The study of the “Il Lago” Plain subsurface might help to constrain the NW segment boundary of the 1805 seismogenic source, suggesting that it is possibly a capable fault, source for moderate (Mw < 5.5) to strong earthquakes (Mw ≥ 5.5). Therefore, we constrained the geometry of the fault beneath the plain using low-frequency Ground Penetrating Radar (GPR) data supported by seismic tomography. Seismic tomography yielded preliminary information on the subsurface structures and the dielectric permittivity of the subsoil. A set of GPR parallel profiles allowed a quick and high-resolution characterization of the lateral extension of the fault, and of its geometry at depth. The result of our study demonstrates the optimal potential of combined seismic and deep GPR surveys for investigating the geometry of buried active normal faults. Moreover, our study could be used for identifying suitable sites for paleoseismic analyses, where record of earthquake surface faulting might be preserved in Holocene lacustrine sedimentary deposits. The present case demonstrates the possibility to detect with high accuracy the complexity of a fault-zone within a basin, inferred by GPR data, not only in its shallower part, but also down to about 100 m depth.
Characterizing the Topographic Changes and Land Subsidence Associated with the Mountain Excavation and City Construction on the Chinese Loess Plateau
Authors: Pu Chuanhao , Xu Qiang , Zhao Kuanyao , Jiang Yanan , Hao Lina , Liu Jialiang , Chen Wanlin , Kou Pinglang
Published: April 2021

A mega project, Mountain Excavation and City Construction (MECC), was launched in the hilly and gully region of the Chinese Loess Plateau in 2012, in order to address the shortage of available land and create new flat land for urban construction. However, large-scale land creation and urban expansion significantly alters the local geological environment, leading to severe ground deformation. This study investigated the topographic changes, ground deformation, and their interactions due to the MECC project in the Yan’an New District (YND). First, new surface elevations were generated using ZiYuan-3 (ZY-3) stereo images acquired after the construction in order to map the local topographic changes and the fill thickness associated with the MECC project. Then, the interferometric synthetic aperture radar (InSAR) time series and 32 Sentinel-1A images were used to assess the spatial patterns of the ground deformation in the YND during the postconstruction period (2017–2018). By combining the InSAR-derived results and topographic change features, the relationship between the ground deformation and large-scale land creation was further analyzed. The results indicated that the MECC project in the YND has created over 22 km2 of flat land, including 10.8 km2 of filled area, with a maximum fill thickness of ~110 m. Significant uneven ground deformation was detected in the land-creation area, with a maximum subsidence rate of approximately 121 mm/year, which was consistent with the field survey. The strong correlation between the observed subsidence patterns and the land creation project suggested that this recorded uneven subsidence was primarily related to the spatial distribution of the filling works, along with the changes in the thickness and geotechnical properties of the filled loess; moreover, rapid urbanization, such as road construction, can accelerate the subsidence process. These findings can guide improvements in urban planning and the mitigation of geohazards in regions experiencing large-scale land construction.
Spatio-Temporal Changes of Vegetation Net Primary Productivity and Its Driving Factors on the Qinghai-Tibetan Plateau from 2001 to 2017
Authors: Zhang Yin , Hu Qingwu , Zou Fengli
Published: April 2021

The Qinghai-Tibetan Plateau (QTP) is the highest plateau in the world. Under the background of global change, it is of unique significance to study the net primary productivity (NPP) of vegetation on the QTP. Based on the Google Earth Engine (GEE) cloud computing platform, the spatio-temporal variation characteristics of the NPP on the QTP from 2001 to 2017 were studied, and the impacts of climate change, elevation and human activity on the NPP in the QTP were discussed. The mean and trend of NPP over the QTP were “high in the southeast and low in the northwest” during 2001–2017. The trend of NPP was mostly between 0 gC·m−2·yr−1 and 20 gC·m−2·yr−1 (regional proportion: 80.3%), and the coefficient of variation (CV) of NPP was mainly below 0.16 (regional proportion: 89.7%). Therefore, NPP was relatively stable in most regions of the QTP. Among the correlation coefficients between NPP and temperature, precipitation and human activities, the positive correlation accounted for 81.1%, 48.6% and 56.5% of the QTP area, respectively. Among the two climatic factors, the influence of temperature on NPP was greater than that of precipitation. The change of human activities and the high temperature at low altitude had positive effects on the increase of NPP.
A Spectral-Spatial Features Integrated Network for Hyperspectral Detection of Marine Oil Spill
Authors: Wang Bin , Shao Qifan , Song Dongmei , Li Zhongwei , Tang Yunhe , Yang Changlong , Wang Mingyue
Published: April 2021

Marine oil spills are one of the most serious problems of marine environmental pollution. Hyperspectral remote sensing has been proven to be an effective tool for monitoring marine oil spills. To make full use of spectral and spatial features, this study proposes a spectral-spatial features integrated network (SSFIN) and applies it for hyperspectral detection of a marine oil spill. Specifically, 1-D and 2-D convolutional neural network (CNN) models have been employed for the extraction of the spectral and spatial features, respectively. During the stage of spatial feature extraction, three consecutive convolution layers are concatenated to achieve the fusion of multilevel spatial features. Next, the extracted spectral and spatial features are concatenated and fed to the fully connected layer so as to obtain the joint spectral-spatial features. In addition, L2 regularization is applied to the convolution layer to prevent overfitting, and dropout operation is employed to the full connection layer to improve the network performance. The effectiveness of the method proposed here has firstly been verified on the Pavia University dataset with competitive classification experimental results. Eventually, the experimental results upon oil spill datasets demonstrate the strong capacity of oil spill detection by this method, which can effectively distinguish thick oil film, thin oil film, and seawater.
Landslide and Wildfire Susceptibility Assessment in Southeast Asia Using Ensemble Machine Learning Methods
Authors: He Qian , Jiang Ziyu , Wang Ming , Liu Kai
Published: April 2021

Southeast Asia (SEA) is a region affected by landslide and wildfire; however, few studies on susceptibility modeling for the two hazards together have been conducted for this region, and the intersection and the uncertainty of the two hazards are rarely assessed. Thus, the intersection of landslide and wildfire susceptibility and the spatial uncertainty of the susceptibility maps were studied in this paper. Reliable landslide and wildfire susceptibility maps are necessary for disaster management and land use planning. This work used three advanced ensemble machine learning algorithms: RF (Random Forest), GBDT (Gradient Boosting Decision Tree) and AdaBoost (Adaptive Boosting) to assess the landslide and wildfire susceptibility for SEA. A geo-database was established with 2759 landslide locations, 1633 wildfire locations and 18 predictor variables in total. The performances of the models were assessed using the overall classification accuracy (ACC), Precision, the area under the ROC (receiver operating curve) (AUC) and confusion matrix values. The results showed RF performs superior in both landslide (ACC = 0.81, Precision = 0.78 and AUC= 0.89) and wildfire (ACC= 0.83, Precision = 0.83 and AUC = 0.91) susceptibility modeling, followed by GBDT and AdaBoost. The overall superiority of RF over other models indicates that it is potentially an efficient model for landslide and wildfire susceptibility mapping. The landslide and wildfire susceptibility were obtained using the RF model. This paper also conducted an overlay analysis of the two hazards. The uncertainty of the susceptibility was further assessed using the coefficient of variation (CV). Additionally, the distance to roads is relatively important in both landslide and wildfire susceptibility, which is the most important in landslides and the second most important in wildfires. The result of this paper is useful for mastering the whole situation of hazard susceptibility and proves that RF is a robust model in the hazard susceptibility assessment in SEA.
Probing the Fault Complexity of the 2017 Ms 7.0 Jiuzhaigou Earthquake Based on the InSAR Data
Authors: Tang Xiongwei , Guo Rumeng , Xu Jianqiao , Sun Heping , Chen Xiaodong , Zhou Jiangcun
Published: April 2021

On 8 August 2017, a surface wave magnitude (Ms) 7.0 earthquake occurred at the buried faults extending to the north of the Huya fault. Based on the coseismic deformation field obtained from interferometric synthetic aperture radar (InSAR) data and a series of finite fault model tests, we propose a brand-new two-fault model composed of a main fault and a secondary fault as the optimal model for the Jiuzhaigou earthquake, in which the secondary fault is at a wide obtuse angle to the northern end of the main fault plane. Results show that the dislocation distribution is dominated by sinistral slip, with a significant shallow slip deficit. The main fault consists of two asperities bounded by an aftershock gap, which may represent a barrier. In addition, most aftershocks are located in stress shadows and appear a complementary pattern with the coseismic high-slip regions. We propose that the aftershocks are attributable to the background tectonic stress, which may be related to the velocity-strengthening zones.
Evaporation Duct Height Nowcasting in China’s Yellow Sea Based on Deep Learning
Authors: Han Jie , Wu Jia-Ji , Zhu Qing-Lin , Wang Hong-Guang , Zhou Yu-Feng , Jiang Ming-Bo , Zhang Shou-Bao , Wang Bo
Published: April 2021

The evaporation duct is a weather phenomenon that often occurs in marine environments and affects the operation of shipborne radar. The most important evaluation parameter is the evaporation duct height (EDH). Forecasting the EDH and adjusting the working parameters and modes of the radar system in advance can greatly improve radar performance. Traditionally, short-term forecast methods have been used to estimate the EDH, which are characterized by low time resolution and poor forecast accuracy. In this study, a novel approach for EDH nowcasting is proposed based on the deep learning network and EDH data measured in the Yellow Sea, China. The factors that affect nowcasting were analyzed. The time resolution and forecast time were 5 min and 0–2 h, respectively. The results show that our proposed method has a higher forecast accuracy than traditional time series forecasting methods and confirm its feasibility and effectiveness.
Decision-Level and Feature-Level Integration of Remote Sensing and Geospatial Big Data for Urban Land Use Mapping
Authors: Yin Jiadi , Fu Ping , Hamm Nicholas A. S. , Li Zhichao , You Nanshan , He Yingli , Cheshmehzangi Ali , Dong Jinwei
Published: April 2021

Information about urban land use is important for urban planning and sustainable development. The emergence of geospatial big data (GBD), increased the availability of remotely sensed (RS) data and the development of new methods for data integration to provide new opportunities for mapping types of urban land use. However, the modes of RS and GBD integration are diverse due to the differences in data, study areas, classifiers, etc. In this context, this study aims to summarize the main methods of data integration and evaluate them via a case study of urban land use mapping in Hangzhou, China. We first categorized the RS and GBD integration methods into decision-level integration (DI) and feature-level integration (FI) and analyzed their main differences by reviewing the existing literature. The two methods were then applied for mapping urban land use types in Hangzhou city, based on urban parcels derived from the OpenStreetMap (OSM) road network, 10 m Sentinel-2A images, and points of interest (POI). The corresponding classification results were validated quantitatively and qualitatively using the same testing dataset. Finally, we illustrated the advantages and disadvantages of both approaches via bibliographic evidence and quantitative analysis. The results showed that: (1) The visual comparison indicates a generally better performance of DI-based classification than FI-based classification; (2) DI-based urban land use mapping is easy to implement, while FI-based land use mapping enables the mixture of features; (3) DI-based and FI-based methods can be used together to improve urban land use mapping, as they have different performances when classifying different types of land use. This study provides an improved understanding of urban land use mapping in terms of the RS and GBD integration strategy.
Downscaling Land Surface Temperature Based on Non-Linear Geographically Weighted Regressive Model over Urban Areas
Authors: Wang Shumin , Luo Youming , Li Xia , Yang Kaixiang , Liu Qiang , Luo Xiaobo , Li Xiuhong
Published: April 2021

Land surface temperature (LST) is a vital physical parameter in geoscience research and plays a prominent role in surface and atmosphere interaction. Due to technical restrictions, the spatiotemporal resolution of satellite remote sensing LST data is relatively low, which limits the potential applications of these data. An LST downscaling algorithm can effectively alleviate this problem and endow the LST data with more spatial details. Considering the spatial nonstationarity, downscaling algorithms have been gradually developed from least square models to geographical models. The current geographical LST downscaling models only consider the linear relationship between LST and auxiliary parameters, whereas non-linear relationships are neglected. Our study addressed this issue by proposing an LST downscaling algorithm based on a non-linear geographically weighted regressive (NL-GWR) model and selected the optimal combination of parameters to downscale the spatial resolution of a moderate resolution imaging spectroradiometer (MODIS) LST from 1000 m to 100 m. We selected Jinan city in north China and Wuhan city in south China from different seasons as study areas and used Landsat 8 images as reference data to verify the downscaling LST. The results indicated that the NL-GWR model performed well in all the study areas with lower root mean square error (RMSE) and mean absolute error (MAE), rather than the linear model.
New Biomass Estimates for Chaparral-Dominated Southern California Landscapes
Authors: Schrader-Patton Charlie C. , Underwood Emma C.
Published: April 2021

Chaparral shrublands are the dominant wildland vegetation type in Southern California and the most extensive ecosystem in the state. Disturbance by wildfire and climate change have created a dynamic landscape in which biomass mapping is key in tracking the ability of chaparral shrublands to sequester carbon. Despite this importance, most national and regional scale estimates do not account for shrubland biomass. Employing plot data from several sources, we built a random forest model to predict aboveground live biomass in Southern California using remote sensing data (Landsat Normalized Difference Vegetation Index (NDVI)) and a suite of geophysical variables. By substituting the NDVI and precipitation predictors for any given year, we were able to apply the model to each year from 2000 to 2019. Using a total of 980 field plots, our model had a k-fold cross-validation R2 of 0.51 and an RMSE of 3.9. Validation by vegetation type ranged from R2 = 0.17 (RMSE = 9.7) for Sierran mixed-conifer to R2 = 0.91 (RMSE = 2.3) for sagebrush. Our estimates showed an improvement in accuracy over two other biomass estimates that included shrublands, with an R2 = 0.82 (RMSE = 4.7) compared to R2 = 0.068 (RMSE = 6.7) for a global biomass estimate and R2 = 0.29 (RMSE = 5.9) for a regional biomass estimate. Given the importance of accurate biomass estimates for resource managers, we calculated the mean year 2010 shrubland biomasses for the four national forests that ranged from 3.5 kg/m2 (Los Padres) to 2.3 kg/m2 (Angeles and Cleveland). Finally, we compared our estimates to field-measured biomasses from the literature summarized by shrubland vegetation type and age class. Our model provides a transparent and repeatable method to generate biomass measurements in any year, thereby providing data to track biomass recovery after management actions or disturbances such as fire.
Assessment of Selected Spatio-Temporal Gait Parameters on Subjects with Pronated Foot Posture on the Basis of Measurements Using OptoGait. A Case-Control Study
Authors: Requelo-Rodríguez Inmaculada , Castro-Méndez Aurora , Jiménez-Cebrián Ana María , González-Elena María Luisa , Palomo-Toucedo Inmaculada C. , Pabón-Carrasco Manuel
Published: April 2021

Walking is part of daily life and in asymptomatic subjects it is relatively easy. The physiology of walking is complex and when this complex control system fails, the risk of falls increases. As a result, gait disorders have a major impact on the older adult population and have increased in frequency as a result of population aging. Therefore, the OptoGait sensor is intended to identify gait imbalances in pronating feet to try to prevent falling and injury by compensating for it with treatments that normalize such alteration. This study is intended to assess whether spatiotemporal alterations occur in the gait cycle in a young pronating population (cases) compared to a control group (non-pronating patients) analyzed with OptoGait. Method: a total of n = 142 participants consisting of n = 70 cases (pronators) and n = 72 healthy controls were studied by means of a 30 s treadmill program with a system of 96 OptoGait LED sensors. Results: Significant differences were found between the two groups and both feet in stride length and stride time, gait cycle duration and gait cadence (in all cases p < 0.05). Conclusions: pronating foot posture alters normal gait patterns measured by OptoGait; this finding presents imbalance in gait as an underlying factor. Prevention of this alteration could be considered in relation to its relationship to the risk of falling in future investigations.
An Efficient Anomaly Recognition Framework Using an Attention Residual LSTM in Surveillance Videos
Authors: Ullah Waseem , Ullah Amin , Hussain Tanveer , Khan Zulfiqar Ahmad , Baik Sung Wook
Published: April 2021

Video anomaly recognition in smart cities is an important computer vision task that plays a vital role in smart surveillance and public safety but is challenging due to its diverse, complex, and infrequent occurrence in real-time surveillance environments. Various deep learning models use significant amounts of training data without generalization abilities and with huge time complexity. To overcome these problems, in the current work, we present an efficient light-weight convolutional neural network (CNN)-based anomaly recognition framework that is functional in a surveillance environment with reduced time complexity. We extract spatial CNN features from a series of video frames and feed them to the proposed residual attention-based long short-term memory (LSTM) network, which can precisely recognize anomalous activity in surveillance videos. The representative CNN features with the residual blocks concept in LSTM for sequence learning prove to be effective for anomaly detection and recognition, validating our model’s effective usage in smart cities video surveillance. Extensive experiments on the real-world benchmark UCF-Crime dataset validate the effectiveness of the proposed model within complex surveillance environments and demonstrate that our proposed model outperforms state-of-the-art models with a 1.77%, 0.76%, and 8.62% increase in accuracy on the UCF-Crime, UMN and Avenue datasets, respectively.
Real-Time Vehicle Positioning and Mapping Using Graph Optimization
Authors: Das Anweshan , Elfring Jos , Dubbelman Gijs
Published: April 2021

In this work, we propose and evaluate a pose-graph optimization-based real-time multi-sensor fusion framework for vehicle positioning using low-cost automotive-grade sensors. Pose-graphs can model multiple absolute and relative vehicle positioning sensor measurements and can be optimized using nonlinear techniques. We model pose-graphs using measurements from a precise stereo camera-based visual odometry system, a robust odometry system using the in-vehicle velocity and yaw-rate sensor, and an automotive-grade GNSS receiver. Our evaluation is based on a dataset with 180 km of vehicle trajectories recorded in highway, urban, and rural areas, accompanied by postprocessed Real-Time Kinematic GNSS as ground truth. We compare the architecture’s performance with (i) vehicle odometry and GNSS fusion and (ii) stereo visual odometry, vehicle odometry, and GNSS fusion; for offline and real-time optimization strategies. The results exhibit a 20.86% reduction in the localization error’s standard deviation and a significant reduction in outliers when compared with automotive-grade GNSS receivers.
Algorithm of FBG Spectrum Distortion Correction for Optical Spectra Analyzers with CCD Elements
Authors: Anfinogentov Vladimir , Karimov Kamil , Kuznetsov Artem , Morozov Oleg G. , Nureev Ilnur , Sakhabutdinov Airat , Lipatnikov Konstantin , Hussein Safaa M. R. H. , Ali Mustafa H.
Published: April 2021

Nonlinear spectrum distortions are caused by the peculiarities of the operation of charge-coupled device elements (CCD), in which the signal exposition time (Time of INTegration–TINT) is one of the significant parameters. A change of TINT on a CCD leads to a nonlinear distortion of the resulting spectrum. A nonlinear distortion of the spectrum, in turn, leads to errors in determining the central wavelength of fiber Bragg gratings (FBGs) and spectrally sensitive sensors, which, in general, negatively affects the accuracy of the measuring systems. This paper proposes an algorithm for correcting the nonlinear distortions of the spectrum obtained on a spectrum analyzer using CCD as a receiver. It is shown that preliminary calibration of the optical spectrum analyzer with subsequent mathematical processing of the signal makes it possible to make corrections in the resulting spectrum, thereby leveling the errors caused by measurements at different TINT.
Movement Path Data Generation from Wi-Fi Fingerprints for Recurrent Neural Networks
Authors: Shin Hong-Gi , Choi Yong-Hoon , Yoon Chang-Pyo
Published: April 2021

The recurrent neural network (RNN) model, which is a deep-learning network that can memorize past information, is used in this paper to memorize continuous movements in indoor positioning to reduce positioning error. To use an RNN model in Wi-Fi-fingerprint based indoor positioning, data set must be sequential. However, Wi-Fi fingerprinting only saves the received signal strength indicator for a location, so it cannot be used as RNN data. For this reason, we propose a movement path data generation technique that generates data for an RNN model for sequential positioning from Wi-Fi fingerprint data. Movement path data can be generated by creating an adjacency list for Wi-Fi fingerprint location points. However, creating an adjacency matrix for all location points requires a large amount of computation. This problem is solved by dividing indoor environment by K-means clustering and creating a cluster transition matrix based on the center of each cluster.
To the question about the prevalence of prenosological forms of eating disorders among students of a medical university
Authors: Voitovich Anna Aleksandrovna , Milashevskaya Taisiya Valerievna , Moskvina Aleksandra Olegovna
Published: April 2021

Today eating disorders and metabolic disorders are increasingly observed among the adult and children’s population. One of the ways to prevent these pathologies is the timely detection and correction of prenosological forms, one of them is orthorexia neurosa. The aim of our study was to identify the prevalence and characteristics of the manifestation of orthorexia nervosa (ON) among students. A survey was conducted among 60 students of a medical university with the «ORTO-15» and the «Food Frequency Questionnaire questionnaires» to obtain the necessary data. We took into account the height and weight of students and calculated body mass index (BMI) according to the Kettle’s formula. The results were statistically processed and calculated the average value (M), the deviation from the average (m). The correlation dependence between the values was estimated by the nonparametric Spearman’s coefficient (p). The data were considered statistically significant at p < 0.05 and a significance level of at least 95 %. The study showed a high prevalence of orthorexia nervosa among the examined individuals (in 80 % of cases, signs of ON were determined). The average BMI was 24.35 ± 5.3 among men and 20.9 ± 4.7 among girls. The normal BMI values among men were determined reliably more often than among girls (p˂0.05). In this case, a correlation between the values of BMI and the severity of signs of orthorexia nervosa was not found among students. According to the results of the «Food Frequency Questionnaire», a significant concern was identified with nutrition issues, both among girls and men. The above allowed us to conclude that the subjects examined constituted a risk group for the formation of mental disorders and eating disorders.
Religious life of Crimea in the early Middle Ages
Authors: Mineeva A.
Published: April 2021

The paper describes a brief history of the Crimean ethnic groups, describing their religion and the development of culture and Christianity in the Crimea during the early middle Ages.
Christian mission in Northern Black Sea region and its geopolitical significance
Authors: Kusenkov P.
Published: April 2021

The spread of Christianity in the Northern Black Sea Region was a continuation of the vector of cultural expansion into this region, outlined in Antiquity and opposing the region’s stable geopolitical ties in the latitudinal direction, with the steppe world of the nomads of Eurasia. The stages of this process were: the Great Greek colonization on Pontus Euxinus; the spread of Pax Romana to the territory of Crimea; the Christianization of the region and the strengthening of Byzantium in the Northern Black Sea Region through an alliance with the Khazaria and the creation of the Klimata-Cherson thema; finally, the emergence of Italian trading posts and the emergence of Genoese Gazaria. The success of the Christian mission of Byzantium would not have been possible without the oncoming movement from the north, which determined the reception of the Byzantine civilization by Rus’-Russia and predefined the geopolitical contours of the modern world. In the opposite direction there was an advance to the south of Rus’ and the formation of the path “from the Varangians to the Greeks”, sea voyages of the Rus’ princes to Constantinople, the capture of Korsun’Cherson by Vladimir the Saint and the baptism of Rus’, the inclusion of Russia in the system of the Byzantine church administration. At the new historical stage, after the fall of Byzantium, the role of the Christian Orthodox empire passed to Russia, and the processes of intercivilizational interaction in the region changed their vector. But even in the new conditions, the meridional dimension remains incomparably more important than the latitudinal dimension: a fact that determines the future geopolitical perspective.
Methods for reducing the cost of production of commercial carp when feeding grain crops
Authors: Servetnik G. E. , Pishchenko E. V.
Published: April 2021

Feeding is one of the main methods of intensification of agricultural fish farming. Based on FAO reports, the share of aquaculture products grown with feed is gradually increasing. In pond farms with medium and high degree of intensification, up to 80% of fish products are produced due to feeding. Moreover, in the structure of the cost of fish production, compound feeds account for up to half of the total costs, and in industrial aquaculture up to 65–70%. It is shown that it is Known that feeding and growing technology account for about 55% of the success rate of increasing fish productivity, while the genetic potential is only about 25%, and the share of veterinary and sanitary well-being of fish accounts for about 20%. In Russia and many other countries, cereals are used to reduce the cost of carp farming products, as a relatively cheap and affordable source of energy compared to granulated feed. The availability and low cost of such feed is of paramount importance in pond aquaculture and currently all cereal species are used for artificial feeding. Information about feeding carp with grain crops, as well as requirements for the quality and safety of feed is provided. It is indicated that feeding carp with whole grains is advisable if the natural food base is well developed. Traditional fish farming experience shows that feeding carp with whole wheat grain is advisable when the planting density of two-year-olds is up to 3.5 thousand / ha and mainly in August-September. Before eating fish, the grain must necessarily swell in water, otherwise it injures the intestines and is excreted from the digestive tract poorly digested.
Problems of compensative fisheries: increasing the adaptive potential of broad whitefish Coregonus nasus (Pallas) in early ontogenesis by weak magnetic fields. 1. Morphometric analysis
Authors: Selyukov Alexander Germanovich , Efremova Ekaterina Vladimirovna , Selyukova Svetlana Aleksandrovna , Shuman Leonid Alexandrovich
Published: April 2021

The article presents the results of a production experiment with the embryos of Coregonus nasus, delivered at the Sobsk fish hatchery (settlement Kharp, YaNAO). The plant is taking compensatory measures to restore the number of valuable species of whitefishes in the Ob river basin. The purpose of our study was to increase the biological potential of juvenile broad whitefish for their subsequent release to the Ob river. At the last stage of the embryonic period, the embryos were treated with ultra-weak pulsed magnetic fields for several days. In the postembryonic period, the control and experimental juveniles of broad whitefish were fixed for subsequent morphometric and cytological-histological analysis. After conducting a morphometric analysis, we found that already at the early stages of the postembryonic period, the experimental larvae and fry exceeded the control ones in most parameters. Later, these differences persisted. At the same time, the juveniles of the experimental batch showed, as a rule, less variability of morphological characters. Also, the weight of the experimental fry before release to the Ob significantly exceeded the weight of the control fry. We calculated the degree of correlation of morphometric characters in juvenile broad whitefish of both parties in the process of rearing and found that during the first month the correlation of most parameters in the experimental juveniles was lower than in the control. However, with further development, the degree of relationship between the parameters in juveniles in the experiment increased and reached it in the control. Later, the allometric growth of the experimental juveniles began, which caused a decrease in the connection between some characters. We are discussing the features of the development of experimental juvenile fish; activation of its natural mechanisms of autorehabilitation by using weak physical factors. We explain the reasons for the stable, but insignificant differences between the experimental fish fry over the control treatment with an ultra-weak pulsed magnetic field at the last stages of embryogenesis, when the main organ systems are already formed. We conclude that this approach is advisable, starting with fertilization and early embryogenesis.
Technological project of standard series of pig farms for small forms of management
Authors: Shishkin V. V. , Shulzhenko E. A. , Shishkina G. Yu. , Ryzhkov E. V.
Published: April 2021

Signifi cant proportion in the growth of livestock of pigs, production of meat in short and with the smallest expenses agricultural producers of small forms of management are capable to assume. In order to increase the number and profi tability of growing pigs the technological project of standard series of pig farms is developed for peasant (farmer) and personal subsidiary farms at continuous fl ow system of production of pork and two-phase technology of piglets rearing. The increase in the production of pork and decrease in its prime cost by development of the technological project of pig farms for small forms of management on 30–500 heads with the fi nished cycle of production has been studied. It is established that the quantity of pig stalls for the majority of the production groups of pigs has to be projected 2,2 times more than a number of pigs in the group.
Agricultural transportation and technological chassis with agrophilic wheel drives
Authors: Popov S. D. , Komissarov D. S. , Lavrov A. V. , Gulyaev A. A.
Published: April 2021

Currently, not a single serially produced vehicle used in agriculture meets the requirements of the state standard for the maximum permissible impact of propellers on the soil. This leads to significant losses and shortage of agricultural products. As a promising direction for increasing the efficiency of the transport infrastructure of agricultural production, it is proposed to develop an environmentally friendly transport and technological chassis for agricultural purposes.
Normalization of reliability indicators taking into account the requirements of consumers and the competitiveness of agricultural machinery
Authors: Kostomakhin M. N.
Published: April 2021

At present, there is a need to develop new methodological approaches for evaluating and normalizing machine reliability indicators, as agreed proportions between competitive price and quality.
The technical support of the zootechnical and veterinary measures
Authors: Dzhulamanov K. M. , Rogachev B. G. , Kharlamov V. A. , Kolpakov V. I.
Published: April 2021

The procedures of the technical support of zootechnical and veterinary measures for beef cattle breeding were considered in the article.
Methods of effective use machine and tractor units in melioration
Authors: Apatenko A. S.
Published: April 2021

Questions of efficiency of operation of machine and tractor units are considered and recommendations about improvement of system and infrastructure of ensuring operability of cars taking into account features of structure of park of machine and tractor units in today’s conditions are offered during the ameliorative works.