esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Conclusions  
In conclusion, an FLDI system with a tailored spatial resolution is demonstrated, and the spatial resolution of this FLDI system can be adjusted between 83 \(\upmu\)m and 382 \(\upmu\)m continuously. The density fluctuation at different locations of a supersonic shear flow from the customized shear flow device is measured using this FLDI system with a spatial resolution of 182 \(\upmu\)m. Under this spatial resolution, the measurement capability of this FLDI system is above 84 kHz. No other higher frequency components are found in numerical simulations, so the measured spatial statistics will remain constant with an increase in FLDI resolution, and the density fluctuation frequency less than 84 kHz can be measured well. The operating mode of the supersonic shear flow is Ma 3.0-2.0. According to the analysis of the fluctuation frequencies and power spectra, the evolution of density fluctuation characteristics with shear flow transmission is revealed. The frequency decreases gradually as the measurement point is further from the nozzle, which indicates the scale of the turbulence structure of the shear flow gradually becomes larger as the shear flow propagates downstream. Our work is of great significance for enhancing the spatial resolution and application flexibility of the FLDI system.  
Conceptualization, H.L. and X.Y.; methodology, H.L.; software, Y.L.; investigation, H.L.; resources, Y.L. and L.C.; writing--original draft preparation, H.L.; writing--review and editing, H.L., X.Y. and Y.L.; visualization, L.C. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Key R&D Program of China, grant number 2020 YFA0405700.  
Not applicable.  
The authors declare no conflict of interest.
# Feature Extraction of Bearing Weak Fault Based on Sparse Coding Theory and Adaptive EWT
## 3 AEWT Based on Optimized Component Screening  
### EWT  
In proposing EWT [16], [PERSON] idea was to achieve adaptive signal decomposition by subdividing the Fourier spectrum and constructing a series of orthogonal wavelet filter banks. Firstly, the fault signal is transformed into its Fourier transform, and the frequency range is defined in \(\omega\in[0,\pi]\) according to the Shannon criterion. Then the Fourier spectrum is divided into n-continuous boundaries (\(\omega_{0}=0\), \(\omega_{N}=\pi\)), and each frequency band can be expressed as \(\lambda_{n}=[\omega_{n-1},\omega_{n}]\), satisfying \(\cup_{n=1}^{N}\lambda_{n}=[0,\pi]\). The boundary \(\omega_{n}\) is taken as the center and \(T_{n}=2\tau_{n}\) is taken as the transition band of the band-pass filter, as shown in Figure 1.  
The band-pass filter that meets the above characteristics in each frequency band \(\lambda_{n}\) is defined as an empirical wavelet. Based on the wavelet construction idea of Littlewood-Paley and Meyer theory, the scale function \(\hat{\phi}_{n}(\omega)\) and wavelet function \(\hat{\psi}_{n}(\omega)\) are defined as follows:  
\[\hat{\phi}_{n}(\omega)=\left\{\begin{array}{l}1,if|\omega|\leq(1-\eta) \omega_{n}\\ \cos\Big{[}\frac{\pi}{2}\beta\Big{(}\frac{1}{2\eta\omega_{n}}(|\omega|-(1- \eta)\omega_{n})\Big{)}\Big{]},if(1-\eta)\omega_{n}\leq|\omega|\leq(1+\eta) \omega_{n}\\ 0,otherwise\end{array}\right. \tag{8}\]  
\[\hat{\phi}_{n}(\omega)=\left\{\begin{array}{l}1,if(1+\eta)\omega_{n}\leq| \omega|\leq(1-\eta)\omega_{n+1}\\ \cos\Big{[}\frac{\pi}{2}\beta\Big{(}\frac{1}{2\eta\omega_{n+1}}(|\omega|-(1- \eta)\omega_{n+1})\Big{)}\Big{]},if(1-\eta)\omega_{n+1}\leq|\omega|\leq(1+\eta )\omega_{n+1}\\ \sin\Big{[}\frac{\pi}{2}\beta\Big{(}\frac{1}{2\eta\omega_{n}}(|\omega|-(1- \eta)\omega_{n})\Big{)}\Big{]},if(1-\eta)\omega_{n}\leq|\omega|\leq(1+\eta) \omega_{n}\\ 0,otherwise\end{array}\right. \tag{9}\]  
where \(\beta(x)\) is the indicative function, \(\eta\) is the transition zone coefficient, which should satisfy \(0<\eta<1\) and \(\eta<\min_{n}\Big{(}\frac{\omega_{n+1}-\omega_{n}}{\omega_{n+1}+\omega_{n}} \Big{)}\), and \(\tau_{n}=\eta\omega_{n}\).
## 1 Introduction
As can be seen in the figure, the independently biased 3-stack configuration is realized by connecting the independently biased cascode one with a third common-gate (CG) transistor. By inserting the two additional bias terminals, operation condition of the three transistors can be freely adjusted which cannot be done in conventional configurations. This helps to optimize both small-signal (SS) and large-signal (LS) characteristics effectively by adjusting bias condition of each individual transistor appropriately. Nevertheless, it is worth noting that if the number of transistor increases more, parasitic components will take effect seriously at higher frequencies limiting both SS and LS performance improvement. Although the advantages of such an independently biased technique have been investigated for GaAs HBT devices, including independently biased cascode and independently biased 3-stack in [29; 30; 31; 32], the investigations for GaN HEMT devices have never been performed elsewhere. The rest of this paper is organized as follows. Section 2 investigates both the SS and LS characteristics of the proposed configuration in a comparison with other typical configurations. Section 3 will summarize and discuss the simulated results as well as give the future directions of the study.
# Research and Progress on Truing and Sharpening Process of Diamond Abrasive Grinding Tools
## 2 Dressing Status of Diamond Abrasive Grinding Tools  
The development of grinding technology has experienced three stages: ordinary grinding, precision grinding, and ultra-precision grinding [2]. With the development of various new materials, the ordinary grinding wheel cannot meet their increasing processing requirements. The role of the diamond abrasive grinding wheel is prominent and its application is increasing rapidly. In addition, the shaping accuracy and topography are important indicators for the quality evaluation of diamond abrasive grinding tools, because the shaping accuracy determines the dimensional accuracy and surface quality of the grinding workpiece, and the topography determines the holding force of abrasive grains and the chip holding space around them.  
The dressing of diamond abrasive tools mainly includes two steps: truing and sharpening. Truing refers to cutting blunt diamond abrasive grains to make their tips finely broken and obtain appropriate shape accuracy to form a sharp grinding edge. Sharpening refers to removing the excess bond materials between diamond abrasive grains, making them possess appropriate chip holding space, and making the grinding edge higher than the bond to obtain the ideal abrasive grain height and form the cutting edge [3]. The dressing technology of diamond abrasive grinding tools has developed step-by-step from the traditional single \"hard touch\" dressing [4], and a series of effective dressing methods have been obtained, as shown in Figure 1. It can be seen from Figure 1 that improvements in traditional machining technologies, such as the diamond pen truing method, grinding method, rolling method, free abrasive grain sharpening method, consolidated dressing tool sharpening method, and the innovation of new processing technologies, such as the electric discharge machining (EDM) dressing method and laser dressing method, can provide feasible schemes for the development of diamond abrasive grinding tools dressing technology.  
Figure 1: Diamond abrasive grinding tools dressing technology.
## 3 Numerical Details  
Numerical computations were performed using the commercial software COMSOL-Multiphysics (V 5.3a). The complete reactor was discretized into a physics-based free tetrahedral mesh. Mesh independence analysis was performed to choose a mesh that ensures a high accuracy of results at a low computational cost by considering three different levels of mesh refinement: fine mesh (523,359 domain elements and 352,730 boundary elements), normal mesh (134,183 domain elements and 91,130 boundary elements), and coarse mesh (60,175 domain elements and 3456 boundary elements). The average velocity on the entire reactor volume is computed for all three cases (Table 2). The variation in the CFD predictions is marginal. Consequently, the normal mesh with 134,183 domain elements and 91,130 boundary elements was adopted for all further simulations.  
In COMSOL-Multiphysics (V 5.3a), the k-\(\omega\) model with a time-dependent solver was used to simulate the flow. At the inlet, the mass flow rate was varied, and the atmospheric boundary condition (1.0 atm) was assigned at the outlet. No slip boundary condition was applied to the sidewalls and the bottom of the reactor. The slip boundary condition was adapted to the open surfaces of the reactor. Particle tracing for the fluid flow was chosen to investigate the algae cell mixing. A total of 0.2 million particles based on cell density were introduced at the inlet of the reactor. Flow field parameters obtained from the reactor analysis were used to analyze the flow mixing and residence time of algae particles. All simulations were run for 100 s with a step size of 1 s. All numerical calculations were carried out at an Intel Core i7-3370 3.90 GHz processor with a 16 GB RAM operating system. The solver takes approximately 13 and 24 h to achieve complete convergence of the solution for the flow field and 0.2 million algae particles, respectively.
# A Survey on Mobility Support in Wireless Body Area Networks
## 1 Introduction
However, even though they provide an overview of recent approaches in WBAN, there is no acceptable survey paper to focus on mobility support in WBAN yet. The sensors embedded or implanted in the body naturally have mobility according to human movement or specific behavior. Since such movements show different patterns with other typical mobility models in the several aspects, communication protocols for WBAN need to be developed to reduce the negative impact of movements. For example, [PERSON] et al. studied the effect of critical nodes in mobile ad hoc networks. In order to remove negative effects such as network partition, it is necessary to identify the critical nodes in an efficient way. To achieve this goal, unlike the previous works demanding periodical updating for whole topology information, a Localized Algorithm for Segregation of Critical/Non-critical nodes (LASCNN) [12] was proposed to find the critical nodes with the partial information within a few hops. Moreover, [PERSON] et al. [13] introduced an Application-centric Connectivity Restoration (ACR) algorithm aiming at minimum recovery time and overhead to restore connectivity for mission-critical application. Since connectivity is mostly dependent on critical nodes in Wireless Sensor and Actor Networks (WSAN), algorithms to identify and monitor critical nodes, and select backup nodes in the case of critical nodes' failure were introduced. As a primary strategy, a node with the highest degree in an overlapped coverage area is set to be a critical node while the backup node is selected by taking multiple attributes, neighbor position, application-level interests, connectivity and overlapped coverage. When a failure is detected by a primary monitoring function for critical nodes, one of the post-failure recovery procedures is performed according to current critical and backup node status. In conformity with mobility properties for WBANs and similarities between WSNs and WBANs, we can expect that performance of WBANs is also affected by nodes' movement significantly. Nevertheless, the mobility issue is not highlighted in the above survey papers for WBAN, while there are many good survey and research papers to focus on mobility model and simulation tools in WSN. Motivated by this analysis, in this article, we survey the effects of mobility models in the design of WBANs and group them according to the number of moving nodes. Moreover, we review recent advances related to mobility for WBAN in networking techniques and present analysis with comparison of methods aforementioned. Finally, we conclude this article with a discussion of potential open issues.
## 4 Applications to Field Data  
In this paper, two typical stratigraphic models in the Wuhan area are taken as the research object for microtremor measurement and analysis. The layout of the survey lines and the distribution of the boreholes nearby are shown in Figure 1.  
The He'an Line in study area I is located in the Dongxihu District of Wuhan City, in the north of the Yangtze River, where the Hanjiang River, the Hanbei River, and the Fuhuan River meet and surround. The landform of this district is mainly low plain accumulated by rivers and lakes, with flat terrain. According to the results of a previous drilling, field in situ test and an indoor geotechnical test, the shallow stratum velocity model of the site is of an increasing type.  
The Shamao Line in study area II is located in the Hannan District in the southwest suburb of Wuhan City, bounded by the Yangtze River in the east and south. The landform of this district is mainly river alluvial plain and wide plain formed by lake deposition, with flat terrain. According to previous drilling data of the site, there is a layer of plastic silt mixed with silty clay in between medium-coarse sand mixed with gravel and underlying argillaceous siltstone, with thickness of about 20 m. According to the results of a previous field in situ test and an indoor geotechnical test, the shallow stratum velocity model of the site is of a low-velocity interlayer type.
# Comparison of Thermal Response for RF Exposure in Human and Rat Models
## 3 Computational Results  
### Distribution of SAR and Temperature Elevation  
Figure 2 shows the SAR distribution on the cross section of the rat through the antenna feed point at 3, 6, and 10 GHz. The peak SAR averaged over 10 g of tissue was adjusted to 10 W/kg for proper comparison. As shown in Figure 2, the SAR was distributed over the entire head at 3 GHz, whereas it is more localized at 10 GHz. Because of the smaller dimensions of the rat head, SAR averaged over 10 g of tissue almost coincides with the average SAR of the entire head.  
Figure 3 shows the SAR distributions on the cross section of TARO through the feed point at 3, 6, and 10 GHz. The distances between the antenna and surface of the head were 5, 15, and 25 mm at each frequency. The peak SAR averaged over 10-g tissue was adjusted to 10 W/kg, as for the rat model. The SAR was also distributed in the brain surface at 3 GHz, whereas for frequencies above 6 GHz, it was only distributed in the superficial tissues (such as skin and muscle), because of shallower penetration depth of the electromagnetic fields. Further, the lateral extent of SAR was more widespread at lower frequencies. As shown in Figure 3, the exposure volume was smaller for the antenna distance \(d=5\) mm than that at \(d=25\) mm.  
Figure 4 shows the temperature elevation distributions in the rat and TARO at 3, 6, and 10 GHz. The distance from the head to the antenna was 5 mm. The temperature elevation had a similar tendency to SAR, but was smoother owing to heat diffusion.  
Figure 2: Specific absorption rate (SAR) distributions in the rat model at 3, 6, and 10 GHz. The distance between the skin surface and the dipole antenna was set to 5 mm. The output power of the antenna was adjusted so that the peak SAR averaged over 10-g tissue was equal to 10 W/kg. The dashed square shows the region with a computed peak of 10-g SAR.  
Figure 4: Distribution of temperature elevation in the rat and TARO models at 3, 6, and 10 GHz. The distance between the skin surface and the dipole antenna was set to 5 mm. The output power of the antenna was adjusted so that the peak SAR averaged over 10-g tissue was equal to 10 W/kg.  
Figure 3: SAR distribution in the TARO model at 3, 6, and 10 GHz. The distances between the skin surface and the dipole antenna \(d\) were set to 5, 15, and 25 mm. The output power of the antenna was adjusted so that the peak SAR averaged over 10-g tissue was equal to 10 W/kg. The dashed square shows the region with a computed peak of 10-g SAR.
# Design for Additive Manufacturing and for Machining in the Automotive Field
## 2 Materials and Methods  
### Definition of Functions and Requirements  
The present contribution was dedicated to the DfAM of an automotive bracket to hold an electric motor. The original part geometry is shown in Figure 1a.  
Figure 1: (**a**) Original geometry of the automotive bracket (box dimensions 135 \(\times\) 80 \(\times\) 65 mm): the two superimposed static load cases are shown by red and black arrows, the constraints are schematized by the green triangles in fixed points. (**b**) Geometry resulting from the TO of the bracket. (**c**) Final geometry of the stock part with the three appendices added for clamping. (**d**) Industrialized stock part. (**e**) Stock part after LPBF, support removal and shot peening. (**f**) Finished workpiece after machining.  
The main purpose of redesigning the bracket was to enhance its stiffness without increasing its weight. The following design requirements and constraints were taken into consideration:  
* Increasing the stiffness under two assigned static load cases as described in Section 2.2;
* Leaving the weight unincreased;
* Fitting the design space (DS) limits;
* Allowing for a structural safety factor, Sf, not lower than 2, where Sf is the ratio between maximum applied stress, \(\sigma_{\text{max}}\), and tensile strength, \(\text{R}_{\text{m}}\);
* Meeting dimensional and geometrical tolerances.  
The HyperMeshTM TO algorithm used is the solid isotropic material with penalization (SIMP) method, which sets density to void (0) and solid (1), assuming it to be linearly dependent on the stiffness [29].
## 3 Results
### Technical Potential Estimation  
The three islands currently use diesel generators with an installed rated capacity of 1.386, 1.086, and 3.2 MW. Based on the ranked locations from Table 8, the first-ranked locations are chosen as the most feasible locations. These were then simulated in HelioScope to determine the generated potential rated capacity and solar PV's estimated annual generation potential. Simulation results in HelioScope were used in HOMER Pro to determine the system's feasibility. The most viable power system was obtained with different technology options and resource availability. Table 9 shows each renewable resource's demand and production profile and the energy storage needed to replace the existing diesel generator sets, while Figures 11-13 display the time series plots on an hourly basis of the demand, production, and unmet electrical loads of solar PV and wind. \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**Total Area (m\({}^{2}\))**} & \multicolumn{6}{c}{**Performance Score**} \\ \cline{2-10}
**Study Area** & \multirow{2}{*}{**Solar PV**} & \multirow{2}{*}{**Wind**} & \multicolumn{3}{c}{**Solar PV**} & \multicolumn{3}{c}{**Wind**} \\ \cline{3-10}
**and Locations** & & & \(d_{i}\)\({}^{*}\) & \(d_{i}\)\({}^{-}\) & \(CP_{i}\) & Rank & \(d_{i}\)\({}^{*}\) & \(d_{i}\)\({}^{-}\) & \(CP_{i}\) & Rank \\ \hline \hline \multicolumn{10}{c}{Araceli} \\ L1 & 131,813 & 4,563,000 & 0.048 & 0.088 & 0.646 & 3 rd & 0.110 & 0.133 & 0.546 & 1 st \\ L2 & 182,860 & 8178,000 & 0.088 & 0.059 & 0.404 & 5 th & 0.133 & 0.110 & 0.454 & 2 nd \\ L3 & 181,688 & – & 0.047 & 0.087 & 0.649 & 2 nd & – & – & – & – \\ L4 & 51,585 & – & 0.060 & 0.086 & 0.590 & 4 th & – & – & – & – \\ L5 & 238,280 & – & 0.008 & 0.101 & 0.922 & 1 st & – & – & – & – \\ \multicolumn{10}{c}{Balabc} \\ L1 & 226,891 & – & 0.054 & 0.058 & 0.514 & 3 rd & – & – & – & – \\ L2 & 238,558 & – & 0.025 & 0.065 & 0.723 & 1 st & – & – & – & – \\ L3 & 121,919 & – & 0.060 & 0.037 & 0.381 & 4 th & – & – & – & – \\ L4 & 133,057 & – & 0.043 & 0.055 & 0.563 & 2 nd & – & – & – & – \\ \multicolumn{10}{c}{Cuyo} \\ L1 & 200,565 & 4,330,000 & 0.020 & 0.025 & 0.550 & 2 nd & ** & ** & 1 st \\ L2 & 54,498 & – & 0.036 & 0.004 & 0.092 & 3 rd & – & – & – & – \\ L3 & 225,405 & – & 0.005 & 0.035 & 0.881 & 1 st & – & – & – & – \\ \hline \hline \end{tabular}  
**Ranking is not applicable since it has only one alternative.  
\end{table} 
Table 8: Calculated area and performance scores of possible locations. Figure 10: Possible locations for solar PV farms: (**a**) Araceli; and (**b**) Cuyo. Figure 9: Possible locations for solar PV farms: (**a**) Araceli; (**b**) Balabac; and (**c**) Cuyo. Figure 11: Demand, production, and unmet electrical loads in Araceli: (**a**) solar PV and (**b**) wind. Figure 12: Demand, production, and unmet electrical loads of solar PV in Balabac. Figure 13: Demand, production, and unmet electrical loads in Cuyo: (**a**) solar PV and (**b**) wind.
## 3 Results and Discussion
### Raw Image Price per Hectare Comparison  
Raw image price refers to raw image cost regardless of minimum order area, take-off costs, and all further image analysis processes. Raw image price per hectare is sometimes used to compare sensor costs. Thus, satellite, plane, and UAV raw image prices per hectare were analyzed to study their range. Figure 3 shows the results of the price per hectare comparison for UAV, plane and satellite raw images, based on the 2020 survey. Average prices ranged from 43.36 EUR ha\({}^{-1}\) for UAVs, to 1.68 EUR ha\({}^{-1}\) for planes, to 0.09 EUR ha\({}^{-1}\) for satellites. Although UAV and plane prices did not show high variability, satellite price distribution showed higher heterogeneity. For this reason, the following analyses were carried out grouping satellite data into three clusters. A K-means unsupervised algorithm based on (i) minimum price per hectare, (ii) data per hectare, (iii) spatial resolution, (iv) radiometric resolution, (v) revisit time, and (vi) error propagation in the NDVI formula was used for clustering. The average cluster value for each feature is reported in Table 3.  
Figure 2: Comparison of UAV-acquired VI prices in Italy between 2017 and 2020 for arable and specialized crops. (**A**) and (**B**) shows the price for arable and specialized in 2017 and 2020. (**C**) and (**D**) shows the price in 2017 and 2020 for arable and specialized crops. The average price of a VI map acquired by UAVs decreased by 28.5% between 2017 and 2020.  
Considering that the European average utilized agricultural area per holdings is 16.1 ha, a medium resolution satellite, such as Sentinel-2, could be considered as a dissemination driver of variable rate nitrogen application in Europe. The application of satellite imagery in smallholder farming should take into consideration the reduced capability of medium resolution satellites (above 10 m of spatial resolution) to detect field variability. In that case, higher spatial resolution satellites showed higher consistency [53]; however, the economic sustainability of such sources of information was reduced. Although crop monitoring may not be profitable using the presented satellite constellation to detect field variability below a defined field size, new application and data processing protocols, such as biotic stress monitoring [54] and evapotranspiration assessment [55], may be performed and may contribute to the profitability of such technologies.