esa-sceva/satcom-chunk-collection huggingface dataset:
# Evaluating the Effect of Intensity Standardisation
## Appendix A Histograms of Intensity before and after Intensity Standardisation  
We measured standardisation quality based on the degree of overlap between histograms of intensities of baseline and follow-up scans using the KL divergence. To further illustrate the effect of intensity standardisation, we plotted the histograms of intensity before and after standardisation. The resulting figures for both OASIS and ADNI can be seen in Figures 12 and 12. In general, standardisation reduced inter-subject intensity differences. However, discrepancies in the left-most tails of the resulting histograms indicate there are remaining unwanted technical variations that intensity standardisation does not cope with. In the case of WhiteStripe, this situation has been also noted in previous works in the field [28].  
Figure A1: Histograms of intensity of OASIS scans before and after intensity standardisation.  
Figure 17: Histograms of intensity of ADNI scans before and after intensity standardisation. We noticed that intensity variations depend on acquisition site. In particular, scans from site 002 exhibited higher intensities than any other site.
###### Abstract  
Through Global Navigation Satellite System (GNSS) occultation measurement, the global ionosphere and atmosphere can be observed. When the navigation satellites' signal passes through the lower atmosphere, the rapid change of the atmospheric refractive index gradient will cause serious multipath phenomena in radio wave propagation. Atmospheric doppler frequency shift and amplitude signal fluctuations increase drastically. Due to the attenuation of signal amplitude and the rapid change of the Doppler frequency, the general phase locked loop (PLL) cannot work properly. Hence, a more stable tracking technology is needed to track the occultation signal passing through the lower atmosphere. In this paper, a mountain-top based radio occultation experiment is performed, where we employ an open-loop receiver and remove the navigation bits by the internal demodulation. In the process of the experiment, we adopt the open-loop tracking technique and there is no feedback between the observed signal and the control model. Specifically, taking the pseudo-range and doppler information from models as input, three key parameters, i.e., accurate code phase, carrier doppler and code doppler, can be obtained, and furthermore, the accurate accumulation is determined by them. For the full open-loop occultation data, a closed-loop observation assisted strategy is presented to compare the tracking results between open-loop and closed-loop occultation data. Through the compared results, we can determine whether the initial phase has been reversed or not, and obtain the high consistency corrected open-loop data that can be directly used for subsequent atmospheric parameters inversion. To verify the effect of open-loop tracking and open-loop inversion, we used the company's self-developed occult receiver system for verification. The company's self-developed occult receiver system supports Global Position System (GPS)/Beidou satellites constellation (BD, the 2 nd and 3 rd generations) dual systems. We have verified GPS and BD open-loop tracking and inversion, carried out in a three-week mountain-based experiment. We used closed-loop and open-loop strategies to track and capture the same navigation star to detect its acquisition effect. Finally, we counted the results of a week (we only listed the GPS data; BD's effect is similar). The experimental results show that the open-loop has expanded the signal-cut-off angle by nearly 20% under the condition of counting all angles, while the open-loop has increased the signal-cut-off angle value by nearly 89% when only calculating the negative angle. Finally, the atmosphere profiles retrieved from observations in open-loop tracking mode are evaluated with the local observations of temperature, humidity and pressure provided by the Beijing Meteorological Bureau, and it is concluded that the error of open-loop tracking method is within \(\sim\)4% in MSER (mean square error of relative error), which meets the accuracy of its applications (\(<\)5%, in MSER).  
**Keywords:** atmospheric occultation; open-loop tracking; mountain base test; BD3; internal processing
## 3 Prediction Results of Mining Surface Subsidence of Northern Pei County for Reusing Land Resources
### The Influence of Geological and Mining Conditions on Prediction Parameters
#### 3.1.5 Coal Seam Dip Angle  
Coal seam dip angle has a significant impact on the surface subsidence coefficient. The relationship between the coal seam dip angle and the subsidence coefficient can be expressed by Equation (11):  
\[q=\frac{W_{0}}{Mcos\alpha} \tag{11}\]  
where: \(W_{0}\) is the measured maximum surface subsidence when the strike and tendency achieve the full-mining, mm; \(M\) is the mining thickness, m; \(\alpha\) is the inclined angle of the coal seam, \({}^{\circ}\).  
The subsidence coefficient is directly associated with the coal seam dip angle according to Equation (11). When the maximum surface subsidence is the same, the subsidence coefficient increases with the increase of the coal seam dip angle.  
The bedrock points horizontally move to the uphill coal direction when mining the inclined coal seams, and this can drive the movement of the unconsolidated layers due to the friction role. Therefore, the horizontal movement pointing to district rise increases during the mining of inclined seams. The relationship between the horizontal movement coefficient of the inclined seam and the coal seam dip angle can be expressed by Equation (12) [26]:  
\[b_{c}=b(1+0.0086\alpha) \tag{12}\]  
where:  
\(b_{c}\) is the horizontal movement coefficient of the inclined seam;  
\(b\) is the horizontal movement coefficient of the flat coal seam;  
\(\alpha\) is the inclined angle of the coal seam, \({}^{\circ}\).  
The inclined angle of the coal seam has a certain influence on the inflection point offset. Voussoir beam structure cannot be formed in the boundary of district rise when the inclined angle of the coal seam is large, and the voussoir beam is easy to lose stability in the boundary of descends mountain direction due to the overburden load. Thus, the tangent of the major influence angle decreases with the increase of the coal seam inclined angle.  
The mining influence propagation angle is the key parameter for the surface subsidence prediction of the inclined seam, and it is mainly affected by the coal seam inclined angle. The mining influence propagation angle decreases with the increase of coal seam inclined angle. The relationship between the mining influence propagation angle and the coal seam inclined angle can be expressed by Equation (13) [8]:  
\[\theta=90^{\circ}-k\alpha \tag{13}\]  
where: \(k\) is the parameter that reflects the lithology of the overlying strata; \(\theta\) is the mining influence propagation angle, \({}^{\circ}\).
## 3 Electromagnetic-Thermal Bidirectional Coupling Model Formulation of TPMLG
### Thermal-Fluid Finite Volume Model of the TPMLG
#### 3.2.3 Air Flow  
The air flow condition should be judged first to select a proper turbulence model, significantly affecting results of air-cooling simulation. Dimensionless numbers are compared with critical values to judge air flow state transition. The critical value varies depending on the specific flow conditions and geometries involved. The Grashof number \(Gr\) plays a significant role in natural convection phenomena equivalent to that of the Reynolds number in forced convection phenomena. \(Gr\) is the principal criterion for the transition from laminar flow to turbulent flow in natural convection [32; 33; 34], which is mathematically given by the equation below:  
\[Gr=\frac{g\alpha_{V}\Delta Tl^{3}}{\
u^{2}} \tag{8}\]  
where \(g\) refers to gravitational acceleration; \(\alpha_{V}\) refers to volume expansion coefficient; \(\Delta T\) refers to excess temperature; \(l\) represents characteristic length; and \(v\) represents kinematic viscosity. For vertical planes and horizontal columns, the Grashof number of air in natural convection is calculated to be less than \(10^{8}\). For horizontal planes, the Rayleigh number \(Ra\) is adopted as the criterion for judgment on the transition of heat transfer law [32], which is defined as:  
\[Ra=GrPr=\frac{g!^{3}\alpha_{V}\Delta T}{va} \tag{9}\]  
where \(Pr\) is the Prandtl number and \(a\) is thermal diffusivity. The Rayleigh number of air in natural convection is also estimated to be smaller than \(10^{8}\). Thus, the flow condition of air is laminar flow and the laminar model is employed in the natural cooling simulation. In the forced air-cooling simulation, the standard \(k\)-\(\varepsilon\) turbulence model and the scalable wall function are used.
# _Laasonia inermis_ as an Active Corrosion Inhibitor for Mild Steel in Hydrochloric Acid
## 2 Material Preparation
### Electrochemical Measurements  
A three-electrode corrosion cell, having a PAR 263 potentiostat/galvanostat, was used for the electrochemical assessments. The metal specimens were encapsulated in epoxy resin such that one surface was left uncovered. The exposed area (1 cm\({}^{2}\)) was polished with emery papers of various grades (200-1000). A graphite rod and a saturated calomel electrode were used as counter and reference electrodes. Mild steel was used to fabricate the working electrode. The electrolyte solutions, which initiate the corrosion process, were chosen; in this case, they were 0.1 M and 1 M HCl acidic solutions. The potentiodynamic polarisation was initiated by applying a potential sweep at a potential range of \(\pm\)250 mV and scan rate of 0.333 mV/s. The readings were taken after 0.5 h of immersion, with the solution unstirred at 30 \({}^{\circ}\)C. The potentiodynamic polarisation curve was recorded as the applied potential versus the current density. Measurements were taken in triplicates to ensure reproducibility.  
\[\text{IE}\;(100)=((\text{i}_{\text{corrbl}}-\text{i}_{\text{corrinh}})/(\text{ i}_{\text{corrbl}}))\times 100 \tag{3}\]  
where i\({}_{\text{corrbl}}\) and i\({}_{\text{corrinh}}\) are the corrosion current densities in the absence and presence of the inhibitor.
## 2 Study Area and Materials
### Data Resources  
#### 2.2.1 The Normalized Microwave Reflection Index (NMRI)  
The NMRI was first proposed by [PERSON] and [PERSON] [21]. NMRI is an index reflecting the change of VWC estimated from data archived by GNSS instruments deployed for geodetic applications. GNSS satellites transmit L-band microwave signals, and some of this energy is reflected by the surface surrounding the antenna, which causes the multipath effect. Then, the GPS receivers receive the interference signal of the direct signal and reflected signal. The VWC variation can be estimated by the GNSS-IR system, since the multipath effect of GNSS satellites changes due to the existence of vegetation cover on the ground, as the amplitude of the GPS interferometric signal varies with the change of VWC. Based on this, the NMRI is defined, which increases as VWC increases. For the principle of the GNSS-IR technique and the detailed calculation process of NMRI, we refer the readers  
Figure 1: Study area in the western part of the CONUS. (**a**) Study area and PBO H2O sites ([[https://gnss-h2o.jpl.nasa.gov/index.php](https://gnss-h2o.jpl.nasa.gov/index.php)]([https://gnss-h2o.jpl.nasa.gov/index.php](https://gnss-h2o.jpl.nasa.gov/index.php))). (**b**) Land cover map in 2015 ([[http://maps.elie.ucl.ac.be/CCI/viewer/index.php](http://maps.elie.ucl.ac.be/CCI/viewer/index.php)]([http://maps.elie.ucl.ac.be/CCI/viewer/index.php](http://maps.elie.ucl.ac.be/CCI/viewer/index.php))).  
to the Appendix A. Furthermore, the NMRI was validated at four sites in Montana, and the results showed that the NMRI is correlated strongly with VWC and NDVI [33]. Recently, the NMRI was also used to evaluate the vegetation response to a recent drought in California, U.S., and was compared with the optical-based remote sensing NDVI [40].  
The NMRI data used in this study were obtained from the PBO H2O Data Portal ([[https://gnss-h2o.jpl.nasa.gov/index.php](https://gnss-h2o.jpl.nasa.gov/index.php)]([https://gnss-h2o.jpl.nasa.gov/index.php](https://gnss-h2o.jpl.nasa.gov/index.php))) [41], which up to now is the only operational network based on the GNSS-IR principle to produce archived and publicly available vegetation information products. There are 329 PBO H2O sites that meet the requirements within the study area, as shown in Figure 1a. At the locations of these PBO H2O sites, the types of land cover include shrubland, cropland, grassland, and savanna. The study period is from January 1, 2007, to December 31, 2016. The daily NMRI data can be obtained for each site.
# DkFD: Optimizing Common Pediatric Dermatoses Detection with Novel Loss Function and Post-Processing
## 2 Related Work
### Super-Resolution Reconstruction  
Super-resolution reconstruction can partially help compensate for issues such as blurry images, poor quality, insignificant interest areas [45], etc. Super-resolution reconstruction is frequently used in real-world applications such as satellite, remote sensing, astronomy, and biomedical feature identification due to the limitations of the image acquisition environment [46]. Traditional image super-resolution reconstruction techniques, such as the iterative inverse projection method, convex set projection method, and interpolation method, are quicker in reconstruction, but lose a lot of detail due to the small amount of prior knowledge used, which may make them less useful. The reconstructed image may also be relatively blurry. In recent years, image super-resolution reconstruction based on deep learning has made it possible to recover the detailed information in the images by transforming low-resolution images into high-resolution images using a variety of learning models. Learned from the real-world image super-resolution reconstruction tasks [47] and the characteristics of ESRGAN [48], RealSR [49], BSRGAN [50], and Real-ESRGAN [51], the SwinIR [52] proposed by [PERSON] et al., which is based on Swin Transformer, not only has fewer parameters and a lower training difficulty, but can also produce sharp and clear images.
###### Abstract  
Metasurfaces have recently become a promising material, offering new degrees of freedom in molding electromagnetic wave properties. In this work, we propose and numerically investigate ultrathin microwave devices for polarization-dependent wavefront shaping based on an anisotropic metasurface, which consists of a square metal ring with a cross, a dielectric substrate, and a metal ground plane. It is demonstrated the proposed metasurface can independently manipulate reflective \(x\)- and \(y\)-polarized wavefronts at frequency of 15 GHz via engineering of the metal cross. Furthermore, the reflective efficient is extremely high, reaching a near-unity value of 0.98. Based on this anisotropic metasurface, a polarization beam splitter is achieved by artificially arranging the spatial distribution of metasurfaces with prescribed geometries. In addition, we successfully design a focusing metasurface to separate the \(x\)- and \(y\)-polarized beams via focusing them at different positions. The proposed approach paves a way toward the applications of the metasurface in a microwave band.  
electromagnetic metamaterials; microwave propagation; microwave antennas; beam steering +
Footnote †: journal: Applied Physics Letters  
1
## 7 Conclusions
In noisy environments with a rapid increase in received events, the receiver may set lower bias sensitivity values, whereas, in low-noise environments, higher values could be applied to improve OCC link performance. This kind of configuration is framed within the new paradigm of joint sensing and communication (JC&S). The results presented in this paper, focusing on optical camera communication links using n-pulse modulation, can serve as a foundation for future experiments. It will be crucial to explore various scenarios, including longer distances between the transmitter and receiver or outdoor environments, to further assess the capabilities of this modulation. Conceptualization, V.G. ; Methodology, R.P.-J. ; Software, J.A. ; Validation, V.G. ; Formal analysis, J.A. ; Investigation, J.A. ; Writing--original draft, J.A. ; Writing--review & editing, V.G., J.R. and R.P.-J. ; Supervision, V.G. and J.R.; Funding acquisition, R.P.-J. All authors have read and agreed to the published version of the manuscript. This work was supported in part by the Spanish Research Agency, projects SUCCESS TED2021-130049B-C21 and OCCAM PID2020-114561 RB-I00. Data Availability Statement: Data are contained within the article. The authors declare no conflicts of interest.
# Synchronization and Application of a Novel Hyperchaotic System Based on Adaptive Observers
## 2 Materials and Methods  
In this paper, various analyses of the proposed 4-dimensional hyperchaotic system were executed. In order to prove that the new hyperchaotic system exhibits chaotic and hyperchaotic behavior, dynamic analysis studies were carried out. Some of these analyses were performed using the MATLAB platform. The hyperchaotic circuit implementation of the system was created on the Multisim platform. The synchronization of the proposed hyperchaotic system was designed using an adaptive observer. The novel 4-dimensional hyperchaotic system synchronization was tested in a secure communication application and its execution was successfully proved. The block diagram of the material and the method proposed in this paper are given in Figure 1.
## 5 Experiment and Analysis
The Newton-based GCNM algorithm is then used to reconstruct the static image. The reconstructed images under different SNR conditions are compared with the noise-free reconstructed image to analyze the anti-noise performance. Figure 7 displays the reconstructed images at different SNR levels. Figure 6: Transformation of finite element mesh data into graph structure. Figure 7: The effect of the reconstructed image under different SNR. The simulated test data results were obtained using a network trained on ACT 4 data. It is important to note that the training data only include a single horizontal segmentation of the lungs. Finally, we have tested the proposed algorithm on real data and illustrated the reconstruction performance, as shown in Figure 8.
# Cyclic Tests and Numerical Analyses on Bolt-Connected Precast Reinforced Concrete Deep Beams
## 3 Test Results
### Elastic Stiffness  
The boundary condition is an important factor to determine the stiffness as well as the ultimate strength of RC deep beams [29]. Thus, the boundary conditions of the RDBs can be simplified as a deep beam with fixed supports [8], and the idealized diagram is presented in Figure 8(a). The initial stiffness of the RDB could be obtained by considering the bending deformation and shearing deformation of the RDB. The deformation diagram and force distribution diagram of the RDBs associated with lateral force \(F\) are shown in Figure 8(b).  
Figure 8: Energy dissipation results of test specimens.  
Figure 9: Deformation and force diagrams for RDBs and bolt connections.  
The lateral displacement of RDBs \(\Delta_{\text{w}}\) is a combination of bending deformation \(\Delta_{\text{wM}}\) and shearing deformation \(\Delta_{\text{wV}}\). The displacement of RDBs can be calculated based on the Graph Multiplication Method in basic theory in structural mechanics:  
\[\Delta_{\text{w}}=\Delta_{\text{wM}}+\Delta_{\text{wV}}=\frac{V_{\text{w}}h^{3} }{12E_{\text{c}}I_{\text{w}}}+\frac{1.2V_{\text{w}}h}{GA} \tag{1}\]  
where \(I_{\text{w}}\), \(V_{\text{w}}\) and \(A\) are the moments of inertia, shear force and section area of RDBs, respectively; \(E_{\text{c}}\) and \(G\) are the elastic modulus and shearing modulus of concrete. Thus, Equation (1) can be expressed as:  
\[\Delta_{\text{w}}=\frac{V_{\text{w}}}{E_{\text{c}}t}\left[\frac{1}{\left(l/h \right)^{3}}+\frac{2.88}{\left(l/h\right)}\right] \tag{2}\]  
where \(h\) is the effective height and \(l\) is the effective length. The elastic lateral stiffness \(K_{\text{e}}\) is calculated as:  
\[K_{\text{e}}=\frac{E_{\text{c}}t}{\left[\left(h/l\right)^{3}+2.88(h/l)\right]} \tag{3}\]  
Table 3 presents the comparison of the elastic lateral stiffness of the test specimens obtained from Equation (3) and the tests. It was found that the error is no more than 20%, and the values derived from the equation slightly overestimate the lateral stiffness of the test specimens. It can be concluded that the imperfections of the specimens and uncertainty in test procedures were not considered in the equation. However, the overestimation can also be treated as safety reserves in the structural design of RDBs.
# Numerical Analysis of Laser Pattern Effects to Residual Stress on Metal 3D Printing
###### Abstract  
In this study, a metal 3D printing process was simulated using finite elements methods (FEM), and the specimens were printed under the same conditions. Subsequently, residual stress was measured to validate the results. The thermal-structure two-way coupled analysis confirmed the phenomenon that occurred during the additive process, thereby allowing the residual stress to be calculated more realistically. In addition, to simulate the printing process, a subroutine was configured to account for the laser heat input path and layer. The process of stacking and hatching in a snake pattern for an area measuring \(5\,\mathrm{mm}\times 5\,\mathrm{mm}\) was simulated. Four cases with different rotation angles of the layer pattern were calculated using FEM. The specimens were printed compared with the analysis results. To verify the printed condition of the specimen, computed tomography was performed to confirm the appearance of pores and cracks in the specimen. Cracks appeared in the \(180^{\circ}\) specimen, and the cause was analyzed based on the analysis results. Subsequently, the residual stress was measured by an X-ray diffractometer and compared; it was confirmed that the average error of the specimen without cracks is 8.86%, which is similar to the analysis results. These results confirm that the FEM model conducted in this study can be used to analyze residual stress and cracks in a material, which are difficult to analyze in previous studies. The FEM model constructed in this study is expected to facilitate investigations into 3D printing phenomena as well as enable a more efficient process design.  
finite element method; metal 3D printing; residual stress; structure-thermal coupled analysis +
Footnote †: journal: Applied Sciences