esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 The Conversion-Coating Process  
To enhance the corrosion resistance of aluminium alloys and increase organic coatings' adhesion to the surface, aluminium parts are subjected to a chemical or electrochemical treatment, to form protective inorganic films. When chemical treatments are employed, the most widely used method involves depositing \"conversion coatings\" on the surface to be protected [16].  
Efficient protective systems have been developed over the years by using chromium-based solutions. The best results were obtained employing CrVI-based acidic aqueous solutions, which, on the other hand, proved to be carcinogenic and harmful to the environment. More recently, the so-called \"Cr-free\" rinse treatments have become commercially available, showing a lower environmental impact and being less harmful to humans. These products are CrIII or phosphate-chromatic aqueous-solutions-based, still causing heavy environmental impact, due to the use of a massive quantity of water needed in the process and the need for waste disposal. The latter contains CrIII, CrVI or chromate-phosphate salts, among other chemicals, dissolved in acidic aqueous solutions that must be appropriately disposed of at the end of the industrial process. Therefore, the need to use eco-friendly goods for the corrosion protection of aluminium alloys, eliminating the Cr from the chemical formulation, has led to the development of products containing Zr, Ti, Y, Ce, etc., showing reduced environmental impact [17].  
The conversion coatings should guarantee high corrosion-resistance, delaying the oxidation of the metal substrate and allowing good adhesion of paints or organic films. An ideal conversion layer, therefore, should have characteristics such as:  
* Continuity and impermeability to gas and liquids;
* Inertia, or at least insolubility, in the environment in which it operates;
* Inhibition of metal-substrate attack by electrolytes;
* High resistance to mechanical damage from abrasion, scratching, or, if weak and of reduced thickness, they should exhibit self-repairing properties;
* Promoting the adhesion of paints or other organic coatings.
## 5 Experimental Results
### Results
#### 5.4.3 LMVSegRNN Outperforms Learning-Based Geometric Approaches  
The qualitative results obtained by the competing methods are summarized in Table 2. Our projection-based method consistently surpasses the performance of other approaches based on representation learning. More importantly, it shows the greatest generalization ability to complex atypical cases and, thus, the highest potential to be exploited in daily clinical practice. In competing point-based methods, including curvature information in the input representation is beneficial, which confirms and ties well with the results of our ablation study. The complete absence of local information in PointNet solutions and the very limited local information in PointNet++ methods, however, result in an inferior ability to uncover intricate patterns in the geometry of dental shapes, making the methods less accurate. In contrast, our projection-based method is built on hierarchical processing of depth and normal information via local 2D convolutions with 3D information shared among different views through recurrent units, effectively processing the input scan with information at different scales. Although much information may be lost by reducing to 2D, we argue that considerably more information is lost by strong undersampling of inputs required by point-based methods. The results of the qualitative analysis support the findings presented above. Refer to Figure 5 for segmentation results produced on two randomly selected test cases. By visually examining the performance of individual approaches, we deduce several valuable insights regarding their typical error patterns. Outputs for the PointNet-based approach without information about normal vectors are characterized by oversegmentation. As there is no curvature information, the method learns blobs around teeth that are not bounded by the tooth-gingiva transition. On the other hand, the remaining point-based methods produce under-segmented masks. During the qualitative evaluation of edge-based methods, we observe that the generated masks occasionally exhibit holes. We argue that the results of point- and edge-based methods are not practically applicable due to the considerable effort needed to tune most results. The Graph Cut solution provides more applicable results. The segmentation mask grows from landmark positions on cusps until some significant change in curvature is found. Such change in curvature should represent the tooth-gingiva boundary. However, in cases where the input mesh lacks high-frequency information, such boundaries are blurred, and the method fails. The performance is also limited in cases where the central pit of the occlusal surface is deep or dental appliances are present. Our proposed solution does not show evidence of these artifacts but may occasionally introduce errors in teeth areas occluded during rendering, such as narrow inter-dental spaces. Figure 6 depicts more results on test samples.
# Design Optimization of Reconfigurable Liquid Crystal Patch Antenna
## 1 Introduction  
Research on a multi-functional smart antenna is actively conducted. Systems that can quickly exchange large amounts of information, such as satellite communications, next-generation mobile networks, and radar systems, are required [1, 2]. At the same time, the size of the hardware is increasingly miniaturized and flattened. Therefore, it can be said that the development of an antenna for transmitting and receiving broadband information while covering various frequency bands in a limited space is an important task [3, 4, 5, 6].  
Accordingly, various studies have been performed on an active frequency-selective antenna to cover various application frequencies simultaneously. There is research of selectively using frequency by changing the size of the antenna mechanically [7, 8, 9, 10], electronically frequency tunable antennas using semiconductor devices such as MEMS [11, 12], and research of utilizing variations of material properties such as ferroelectric or ferrite [13, 14, 15].  
Here, we propose applying a liquid crystal to a frequency tunable patch antenna for a microwave frequency band. This liquid crystal is being actively studied in the field of an antenna for variable frequency [16, 17, 18, 19, 20] and an electronic beamforming antenna for the mm-wave frequency band [21, 22, 23, 24, 25, 26]. However, research on technology for securing antenna performance while using an expensive liquid crystal to a minimum is still insufficient [27]. In particular, we show a method of maximizing the antenna frequency change rate while using only the minimum amount of expensive liquid crystal. Considering the electric-field distribution on the surface of the patch antenna and the polarization ratio inside the liquid crystal according to the thickness of the antenna substrate, a design method that optimizes the injection position and quantity of liquid crystals in the directions parallel and perpendicular to the antenna surface was developed.
# Energy-Efficient Power Scheduling Policy for Cloud-Assisted Distributed PV System: A TD3 Approach
## 2 System Model
### Market Cleaning Mechanism  
In this paper, an internal trading market established in the cloud is used to realize the settlement of energy transactions between parks, and each park only needs to provide its own power buying or selling information to the cloud.  
Referring to the micro-grid internal electricity market settlement scheme [24], the cleaning price of the electricity trading market can be expressed as  
\[p_{t,s}=\left\{\begin{array}{ll}\frac{p_{t}^{in}E_{t,b}+p_{t,b}^{grid}\left(E _{t,s}-E_{t,b}\right)}{E_{t,s}},&\text{if }E_{t,s}\geq E_{t,b}\\ p_{t}^{in},&\text{if }E_{t,s}<E_{t,b}\end{array}\right. \tag{4}\]  
\[p_{t,b}=\left\{\begin{array}{ll}p_{t}^{in},&\text{if }E_{t,s}\geq E_{t,b}\\ \frac{p_{t}^{in}E_{t,s}+p_{t,b}^{grid}\left(E_{t,b}-E_{t,s}\right)}{E_{t,b}},& \text{if }E_{t,s}<E_{t,b}\end{array}\right. \tag{5}\]  
where \(p_{t,s}\) and \(p_{t,b}\) are the current selling and buying price in the trading market. \(E_{t,s}\) and \(E_{t,b}\) denote the total amount of selling and buying electricity by the all parks, respectively. \(p_{t}^{in}\) denotes internal cleaning price threshold, i.e., the maximum price of energy sold and the minimum price of energy purchased, which can be given by  
\[p_{t}^{in}=\frac{p_{t,s}^{grid}+p_{t,b}^{grid}}{2} \tag{6}\]  
From the cleaning Formulas (4) and (5), we can know that the cleaning price is jointly determined by all parks. When electricity supply exceeds demand among the parks, the internal energy purchase price will reach the lower limit, which is much lower than the price of energy purchased from the external grid; otherwise, the internal energy sale price will reach the upper limit, which is much higher than the price of energy sold to the external grid.
## 3 Results and Discussion
### Impact of Sonication and Suspension Liquid on Deagglomeration of Seeds  
To explore the influence of sonication treatment on the membrane's performance, three suspensions with a concentration of 1 wt % were prepared in different solvents including EtOH, DI water, and a mixture of EtOH and DI water (50-50 wt%), then sonicated for 30 min. Detailed solvent specifications can be found in Table S2 [34]. The results showed that sonication could efficiently diminish gaps and defects in the formed layer due to deagglomeration and good dispersion, therefore improving penetration and adhesion to the support surface. While CO2 permeance remained relatively constant, based on the results in Figure 2b, SF6 permeance exhibited variability influenced by the suspension liquid and sonication time. Furthermore, membranes prepared using ethanol-based seed suspensions and subjected to 30 min of sonication demonstrated superior performance. The lower surface tension of EtOH facilitated uniform seed crystal dispersion, resulting in a homogeneous layer on the support surface, as represented in Figure S3. As indicated by the results, the perme selectivities for the gas pairs CO2/CH4, CO2/N2, and H2/SF6 were calculated as 80, 20, and 90.
# Theory of Edge Effects and Conductance for Applications in Graphene-Based Nanoantennas
## 2 Optical Conductance of a Terminated Graphene Sheet
### Approximation for Zero Temperature  
Let us next consider the important case of the conductance at zero temperature, which opens the way for further simplifications of Equation (16). In this case the Fermi distribution may be replaced by a step function and its derivative in (16) can be transformed into a Dirac delta function \(\partial f/\partial\varepsilon=-\delta(\varepsilon-\mu)\), which allows an integration of (16). Performing such integration is possible in terms of the discrete number of roots of the following transcendental equation \(\varepsilon(k_{y})=\mu\) (qualitatively depicted in Figure 2), which may be also written as  
\[\mathrm{tg}\Big{(}\sqrt{\tilde{\mu}^{2}-k_{yn}^{2}}L\Big{)}=\frac{\sqrt{ \tilde{\mu}^{2}-k_{yn}^{2}}}{k_{yn}}. \tag{17}\]  
The value \(\tilde{\mu}=\mu/\hbar v_{F}\) means normalizing the electrochemical potential by the electron energy. The corresponding edge mode may be obtained by the formal exchange \(k_{yn}\to i\vec{k}\) (such root exists only under special conditions). For the integration over \(k_{y}\) we use the following property of the Dirac delta function  
\[\int\limits_{-\infty}^{\infty}\delta\big{(}\varepsilon(k_{y})-\mu\big{)}F(k_ {y})dk_{y}=\sum_{n}\frac{F(k_{yn})}{\left|\varepsilon^{\prime}\big{(}k_{yn} \big{)}\right|}, \tag{18}\]  
where \(\varepsilon^{\prime}\big{(}k_{y}\big{)}\) denotes the y-component of the group velocity of pseudo-spin (prime means the derivative). The final explicit result for the conductivity can thus be written as  
\[\sigma^{Intra}(x)=i\frac{e^{2}\mu}{\pi\hbar^{2}L(\omega+i0)}\sum_{n=1}^{2N+1} \frac{B_{n}}{\left|\varepsilon^{\prime}\big{(}k_{yn}\big{)}\right|}\bigg{[} \sin^{2}\!\left(\sqrt{\tilde{\mu}^{2}-k_{yn}^{2}}\!\left(x-\frac{L}{2}\right) \right)+\sin^{2}\!\left(\sqrt{\tilde{\mu}^{2}-k_{yn}^{2}}\!\left(x+\frac{L}{2 }\right)\right)\bigg{]}. \tag{19}\]The values of \(k_{yn}\) depend on the electrochemical potential and satisfy the characteristic Equation (17). The normalized coefficients \(B_{n}\) in (19) are defined by  
\[B_{n}=\left(1-\frac{\sin\Bigl{(}2\sqrt{\widetilde{\mu}^{2}-k_{yn}^{2}}L\Bigr{)} }{2\sqrt{\widetilde{\mu}^{2}-k_{yn}^{2}}L}\right)^{-1}=\frac{\widetilde{ \epsilon}_{n}^{2}}{2\bigl{(}\widetilde{\epsilon}_{n}^{2}L-k_{yn}\bigr{)}}. \tag{20}\]  
Equation (19) may be finally transformed to  
\[\begin{array}{l}\sigma^{Intra}(x)=i\frac{e^{2}\mu}{2\pi\widetilde{\mu}^{2}L( \omega+i0)}.\\ \sum\limits_{n=1}^{2N+1}\frac{1}{|k_{yn}(\widetilde{u})L-1|}\Bigl{[}\sin^{2} \Bigl{(}\sqrt{\widetilde{\mu}^{2}-k_{yn}^{2}}\Bigl{(}x-\tfrac{L}{2}\Bigr{)} \Bigr{)}+\sin^{2}\Bigl{(}\sqrt{\widetilde{\mu}^{2}-k_{yn}^{2}}\Bigl{(}x+\tfrac {L}{2}\Bigr{)}\Bigr{)}\Bigr{]}\end{array} \tag{21}\]  
For details see Appendix B.
## 3 Results and Discussion
### Real-Time Study
It is observed that the BER performance with the particle filter has been improved as illustrated in Figure 25. In real-time, the camera is randomly moved to create motion blurriness and to simulate the movement of a vehicle. However, this motion will not blur all the acquired images. The blurred out images may result in missing detection and results in loss of communication without the particle filter. However, the particle filter tends to predict the likelihood location of the QR-LEA and will result in a lossless communication. It significantly improves the BER performances as compared without the particle filter. Further, the performance of the ATT is evaluated and the BER improvement is calculated as in (3) using BER for with and without ATT. It is observed that the BER performance is improved by 49.8% during translation, 58.8% during rotation, 50.3% during scaling distortion and 55.5% during motion blur with the use of ATT along with the particle filter. \[\%Improvement_{BER}=\frac{|BER_{WithoutATT}-BER_{WithATT}|}{BER_{WithoutATT}} \times 100\% \tag{3}\]  
Figure 24: Real-time setup for Quick response QR inspired LEA.
# Modeling and Characterization of Complex Dynamical Properties of Railway Ballast
###### Abstract  
The nonlinear mechanical properties of ballasted tracks along railways result in complex dynamics of the vehicle-track systems. Employing localized characterization of ballast and a simplified model might underestimate the vehicle-track system's dynamical responses and safety. This paper presents a new dynamical stiffness model of railway ballast by incorporating the ballast's time-varying, nonlinear viscoelastic, and elastoplastic properties. The new nonlinear stiffness model is a versatile tool that comprehensively characterizes the ballast characteristics of displacement-dependent stiffness, frequency-dependent stiffness, hysteresis, and time/space-varying features. These features, widely reported in previous experimental research, can now be effectively understood. Conventionally, to characterize time/space-varying characteristics of ballast along the track, ground-penetrating radar (GPR) has been used as the most efficient approach to survey railway networks quickly and to infer track dynamical properties. Aiming to improve the present technique for characterizing time/space-varying properties of ballast stiffness by using a GPR signal, the adaptive optimal kernel time-frequency representation (AOKTFR) method is used to process a typical GPR signal from a railway ballast scanning. It is found that the results of AOKTFR exhibit a clear time-varying pattern and precise frequency modulation. In contrast, the conventional time-frequency methods failed to give a clear time-varying pattern. The results illustrate that AOKTFR is a practical approach for processing the time-varying nonlinear signal of GPR and correlating it with the time-varying nonlinear stiffness of ballast.  
vehicle-track system; railway ballast stiffness; ballast mechanical properties; GPR; signal processing
## 4 Results
### Results of the Sensitivity Analysis  
After the conclusions obtained in Section 4.1 about the Monte Carlo method, it was decided to set the number of samples per input to 5000, to only consider the independent parameters as inputs, and to define the ranges of all the inputs as a 10% of their nominal value.  
Therefore, the sensitivity analysis of the design parameters of the PMSM was performed under those conditions, in order to deduce their influence on the torque and the vibration response of the machine. In this section, the results of the sensitivity analysis are shown, and the most relevant conclusions are discussed.  
First, Figure 8 shows the total-effect indices of all the input parameters, which were calculated according to Equation (37). These indices measure the relative effect of modifying each of the inputs on the vibration response and the torque.  
Figure 8: Total-effect indices for the Vibration and Torque.  
Figure 7: Total-effect indices modifying the nominal value of \(g\), (**a**) Vibration, (**b**) Torque.  
The sensitivity indices in Figure 8 represent the total influence of the inputs, but they do not show if the output value is increased or decreased on each of the cases. Thus, the scattered plot of the entire sample set is shown in Figure 9, where the output values of the vibration and torque are represented with respect to the values of the corresponding input parameter.  
Therefore, the influence of the design parameters on the torque and the vibration response can be concluded observing the results in Figures 8 and 9.  
As it is logical, the machine produces a higher torque when increasing the diameter of the rotor and the height of the magnets. However, these two parameters have a similar effect on the vibration. Thus, if the objective is to increase the torque without worsening the vibration response, modifying these two parameters would not be a good solution.  
Moreover, increasing the length of the stator would produce a higher torque without affecting the vibrations of the machine. Theoretically, a longer machine would have a lower stiffness, resulting in a worse vibration response. However, this particular machine has a very short length compared to its diameter, which is why a relatively small change of the length shows a very small effect on the vibrations. In a much longer machine, a more significant effect of the stator length will be observed.  
An interesting solution might be to increase the width of the stator yoke, because it would produce a considerable reduction of vibrations without changing the torque. As the external diameter of the stator is kept constant, this would imply to reduce the height and the width of the stator teeth. Therefore, the increase of \(h_{\mathrm{sy}}\) should be limited so that the width of the teeth is not too small, as this would carry saturation issues that would affect the behaviour of the machine.  
Another option would be to increase the length of the air gap. Even though it would imply a reduction in the torque, its contribution to the reduction in vibrations would be even higher, which makes it an interesting alternative.
## 4 Tests
The correspondence between real and ideal centroids range between 15% and 20% in all cases but the 64 regions configuration, in which every centroid has only one correspondent. As it is expected, the statistical results are also very similar to the original configuration of the set, ranging from a coefficient of variation of 26.7% for 64 regions to a 29.9% for the 1024 configuration. The three color channels keep the proportions (Figure 13). The coefficient of variation is reduced with respect to the spot light tests as the artifact introduced is much subtler. The centroid average distance and coefficient of variation is also very similar to the one showed in the original configuration (Figure 12). This confirms the usefulness of the visual approach of the proposed calibration process, since apparently similar images have a correspondence of similar statistical results. Finally, the fourth distortion that was tested consisted on using the diffuse actor lights to create the over lighted area in the center left side of the cyclorama, in order to check if the position of more subtle variations had any influence in the results. The resulting images clearly show the location of the over lighted areas in the left and top of the cyclorama. The main difference between this configuration and the previous one is the light sources position. Whereas in the previous test the light came directly from a frontal position, in this case it comes crossed from the right side of the stage, increasing the distance  
Figure 13: Results of the four performed tests. and, therefore, the illuminated area. However, the amount of light that reaches the cyclorama is the same, as the same light sources were used. As a result, the statistical data obtained is very similar in both cases even when the artifacts introduced are visually different. The coefficient of variation in this case goes from 26.3% of the ideal area for 64 regions to 27.7% in the 1024 configuration. The number of centroids with no correspondence goes from 10% to 15%, except in the 64 regions configuration, in which, as in the previous test, every centroid has only one correspondence (Figure 12). The average color and coefficient of variation are also very similar to those showed in the center diffuse light artifact (Figure 13). The difference in the average distance of the centroids with respect to the geometric center of the regions is also very similar, apart from the 64 regions configuration, in which the distance is reduced in more than 2% of the side of the ideal area. Anyway, these differences are still very small to be appreciable at glance.