esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
First-principles density functional theory was used to determine the surface band structures of CsPbBr\({}_{x}\)I\({}_{3-x}\) (\(x\) = 0, 1, 2, and 3) perovskites. The equilibrium lattice constants of CsPbBr\({}_{x}\)I\({}_{3-x}\) were obtained from the minimum of the total energy as a function of the iodine concentration. We discovered that the band gaps of CsPbBr\({}_{x}\)I\({}_{3-x}\) decreased monotonically under pressure. The phase change from a normal insulator to a topological insulator was found at approximately 2-4 GPa. The Pbp- and Brs-orbitals inverted at the R symmetric point with and without spin-orbit coupling. Nontrivial \(Z_{2}\) topological numbers were obtained, and the surface conduction bands were demonstrated theoretically using a 1 \(\times\) 1 \(\times\) 10 supercell. We ascertained that CsPbBr\({}_{2}\)I has the largest electric polarization 0.025 C/m\({}^{2}\) under a compression strain of 10%. We also observed that in the normal insulation phase, the band gap increases with a small displacement of the central Pb atom in the \(z\)-direction, but in the topological insulator phase, the band gap decreases with the movement of the Pb atom in the \(z\)-direction. Additionally, in the supercell structure, CsPbBr\({}_{x}\)I\({}_{3-x}\) is a ferroelectric topological insulator because the Pb atom leaves its own equilibrium position.  
Keywords:CsPbBr\({}_{3}\); CsPbI\({}_{3}\); topological insulator; band structures; first-principles calculations +
Footnote †: journal: Applied Sciences
# Performance Analysis of On-Demand Scheduling with and without Network Coding in Wireless Broadcast
## 6 Performance Evaluation
### Simulation Results in Non-Real-Time Models
#### 6.2.1 Impact of Skewness Parameter (\(\theta\))  
Figure 4 shows the impact of the data access pattern \(\theta\) on the non-real-time algorithms. Evidently, both the non-coding and the coding versions of the algorithms have better performance in terms of minimizing the average response time (ART) with an increased value of \(\theta\). With an increased \(\theta\), the data access pattern is getting skewed. Previous studies [4; 23; 9] have demonstrated that algorithms will perform better when the data access pattern is getting skewed. This is because each broadcast data item has the potential to satisfy more requests. In addition, the coding version of an algorithm achieves a much lower response time (Figure 3(b)) than its non-coding version (Figure 3(a)). On an average, irrespective of the skewness of the data access pattern, the coding version of each algorithm has at  
Figure 5: Impact of workload on the non-real-time model.  
least 40% less ART than the non-coding version. The relative performance positions of the algorithms in the coding group are identical to the non-coding group. MRF performs the best when the data access pattern is less skewed. When the data access pattern is skewed, MRF becomes the worst because unpopular data items may suffer from starvation, which causes the large ART. The result is consistent with the findings in previous works [10; 34; 51]. MRF_N shows similar trend in Figure 4b. FCFS which only considers the request waiting time, performs the worst in most cases. Similarly, FCFS_N has the worst performance among the coding versions. R \(\times\) W and LWF have similar performance, because both the algorithms consider the item popularity and the request waiting time in scheduling. In the coding version, LWF_N significantly outperforms other algorithms in a highly skewed data access pattern environment. In the non-coding version, excepting MRF, the ABPs of all the algorithms increase steadily when the data access pattern is getting skewed (Figure 4c). This is because MRF solely considers item popularity in scheduling, resulting in very low ABP for unpopular data items. Similar results are observed in the coding versions of the algorithms (Figure 4d). The AELs increase when the data access pattern is getting skewed (Figure 4e). These results further explain the relative performance of algorithms as shown in Figure 4a,b.
## 6 Conclusions  
The cognitive dynamic system (CDS) is inspired by the human brain and can be regarded as the brain-like intelligence. The principles of CDS are applied to a nonlinear fiber optic communication system for the bit error rate (BER) improvement and the data rate enhancement. The executive and preceptor of CDS are implemented in the optical receiver, but executive sends actions to the transmitter such as new data rate. The block diagram of the CDS consisting of the preceptor, the main feedback channel, and executive is presented. The preceptor operates in two modes: prediction mode and BER improvement mode. When there is a fluctuation in the fiber optic network parameters, such as reach or amplifier gain, the BER may exceed the forward error correction (FEC) threshold. In this case, the preceptor operates in prediction mode and, working closely with the executive, it lowers the BER to meet FEC threshold. Once the BER comes below the FEC threshold, the perceptor operates in the BER improvement mode. In this mode, it extracts a statistical model for the fiber optic channel for the current fiber optic link parameters and saves it in the model library for future use. By cycling through the prediction mode and BER improvement mode with appropriate actions by the executive, we have found that the data rate and Q-factor can be enhanced by 12.5% and 2.74 dB, respectively, as compared to the conventional fiber optic system. The key advantage of CDS is that it is intelligent, and software-defined, and it can automatically recognize and extract information about the fiber optic channel. In addition, it can enhance the data rate and improve the BER for different fiber optic link characteristics such as the span length, input power, and other system/signal parameters. These characteristics may change during the data transmission in a fiber optic network, but the CDS can still adapt to these changes. The computational cost of the proposed technique is much lower than the methods used to mitigate nonlinear impairments, such as digital back propagation (DBP). It should be noted that the simplified CDS implemented in this paper is not a substitute for nonlinear compensation techniques such as DBP, although it provides performance benefits comparable to that obtained by DBP. The future application of CDS for fiber optic communications system will include advanced actions such as probabilistic and geometric modulation shaping to mitigate nonlinear distortion in conjunction with the current perceptor, which is expected to improve the BER further and enhance the maximum achievable data rate.  
All authors equally contributed.  
This research received no external funding.  
The authors would like to thank Natural Sciences and Engineering Research Council (NSERC), and Canada Research Chairs Program (CRCP).  
The authors declare no conflict of interest.
## 2 Materials and Methods
### Statistics  
All experiments were performed in triplicate at least, and data were expressed as mean \(\pm\) standard deviation (SD). The data were analyzed using SPSS 17.0 (SPSS, Armonk, NY, USA) and GraphPad Prism 9.0 (GraphPad Software, San Diego, CA, USA) software.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Primer Name** & **Direction** & **Primer Sequences (5/-3/)** \\ \hline \multirow{2}{*}{GAPDH} & F & TCGAACACACATGGGAAAGGT \\  & R & TCCCGTTCTCAGCCATGTAG \\ \hline \multirow{2}{*}{COL4A5} & F & CAAGGTCTACACAGGTCCAGAAA5 \\  & R & TCAITCCAATTGAGGCCCC \\ \hline \multirow{2}{*}{FN1} & F & CCCAATTGACCTT  
One-way analysis of variance was used to determine the significance of differences between the groups (#, * \(p\) < 0.05; ##, ** \(p\) < 0.01).  
**3. Results**  
_3.1. Cell Viability of Ectoin and Oxidative Stress Damaged Cells_  
\(\mathrm{UVA/H_{2}O_{2}}\) can decrease cell viability and cause the oxidative damage of cells. As the dose of UVA or H\({}_{2}\)O\({}_{2}\) was increased, the survival rate of the HSF cells gradually decreased (Figure 1).  
Figure 1A shows the survival rates of the HSF cells after treatment with different doses of UVA. When the UVA radiation dose was 22 J/cm\({}^{2}\), the cell survival rate was (50.89 \(\pm\) 3.84)%. Figure 1B shows the survival rate of the HSF cells treated with 250-3000 \(\upmu\)mol-L\({}^{-1}\) H\({}_{2}\)O\({}_{2}\) for 0.5 h. After treatment with 1000 \(\upmu\)mol-L\({}^{-1}\) H\({}_{2}\)O\({}_{2}\) for 0.5 h, the cell survival rate decreased to (57 \(\pm\) 2.03)%. Therefore, we chose to use IC\({}_{50}\) parameters to establish the damage models. UVA at a dose of 20 J/cm\({}^{2}\) was used to establish the UVA-induced oxidative stress damage model. The modeling condition of the H\({}_{2}\)O\({}_{2}\)-induced oxidative stress damage model was 1000 \(\upmu\)mol-L\({}^{-1}\) H\({}_{2}\)O\({}_{2}\) for 0.5 h.  
Ectoin protects cells from damage by \(\mathrm{UVA/H_{2}O_{2}}\) and improves cell viability. Ectoin at a concentration ranging from 8 to 500 \(\upmu\)g/mL is nontoxic to HSF cells (Figure 2A) and is able to exert a good promotion effect on cell proliferation. Ectoin at a concentration ranging from 8 to 125 \(\upmu\)g/mL for 24 h was able to significantly promote the proliferation of the HSF cells in a time-dependent manner. Two different concentrations (8 and 16 \(\upmu\)g/mL for 24 h, separately) were used in subsequent experiments. Both 8 and 16 \(\upmu\)g/mL for Ectoin enhanced cell viability under UVA or H\({}_{2}\)O\({}_{2}\) stimulation, and there was no significant difference in cell viability between either of the two concentrations of Ectoin (Figure 2B,C).  
Therefore, to facilitate the comparison of the protective effect of the same concentration of Ectoin exerted during \(\mathrm{UVA/H_{2}O_{2}}\) oxidative damage, 8 \(\upmu\)g/mL of Ectoin was selected as the treatment concentration to be used on subsequent UVA and H\({}_{2}\)O\({}_{2}\) damage models.
## 5 Example Analysis of Deformation Allowance of Loess Tunnel
### Analysis on Assurance Rate of Deformation Allowance of Surrounding Convergence  
The statistical range of surrounding convergence deformation U\({}_{\max}\) is (\(-\)12.1\(-\)122.0) mm. Based on the statistical analysis of measured data, the 95% confidence interval of U\({}_{\max}\) is [\(-\)35.08, \(-\)43.39]. For tunnel cover depths h \(\leq\) 3(H + B), surrounding convergence deformation remains below 75.0 mm, while sections exceeding this threshold are primarily found in tunnels with cover depths h \(>\) 3(H + B), as illustrated in Figure 17b. In the aforementioned analysis, the data from field measurements exhibit relatively high variability due to the intricate interplay between loess and tunnel support systems, as well as various uncertain factors impacting the initial support deformation. Hence, the deformation  
Figure 16: Analysis of assurance rate of deformation allowance for crown settlement of different test sections.  
Figure 15: Geological longitudinal section of the entrance and exit section of loess tunnel [74].  
allowance should vary based on the vault settlement. Referring to Figure 17, the guarantee rate for crown settlement is 94.9% and 98.9% when deformation allowances are set to 15 cm and 20 cm, respectively. When the deformation allowance is set at 15 cm, the assurance rate has reached 100% in contrast. Hence, the figure analysis compares crown settlement with surrounding convergence deformation (Figures 16 and 17). In the same test section, crown settlement deformation surpasses surrounding convergence deformation, emphasizing the need for deformation allowance in the tunnel to prioritize crown settlement impact. The suggested deformation allowance range for grade V surrounding rock in a loess tunnel is (\(-10\) to \(-15\)) cm. Based on the preceding analysis, it is recommended to set the deformation allowance for tunnel vaults in grade V surrounding rock within the silty loess section to be less than 15 cm. Therefore, the validity and precision of the previous analysis are confirmed.
# Pixel Interaction Model for Contrast Enhancement: Bridging Social Science and Image Processing
## 4 Experimental Results
### Performance Evaluation  
This section presents the outcomes of experimental evaluations conducted to assess the performance of the proposed method, called the C-OPINION algorithm, in comparison to other existing grayscale image contrast enhancement algorithms. The experiments utilized all images from the provided dataset [27], but we selected only six images to present the results. The results are structured as follows: the first part of this section focuses on the assessment of the performance from a visual point of view, while the second part deals with the numerical performance analysis by evaluating different indexes.  
The visual evaluation process involves comparing the images generated by each of the algorithms under consideration. The purpose of this comparison is to identify any noticeable differences between the methods and determine which algorithm enhances image contrast the most effectively and produces higher-quality images.  
In the numerical performance evaluation, six comprehensive metrics are utilized to assess the images evaluated in the previous step. These metrics, which measure contrast improvement, image fidelity, and perceptual quality, provide a thorough assessment of image quality. The results are presented in a table, facilitating a direct comparison of the numerical performance of all contrast algorithms and enabling the identification of the algorithm that produces the highest-quality images.
# Along-Track Multistatic Synthetic Aperture Radar Formations of Miniatellites
## 3 Reconstruction of the Scene
### Focusing of Equivalent Monostatic SAR  
The focusing of the equivalent monostatic system, can be performed with any efficient SAR focusing algorithm. In practice, since, after recombination, data are in the double wavenumber domain, the most easy way to proceed is using a wavenumber focusing method such as the \(\Omega\)-K algorithm [23]. The wavenumber to build the \(\Omega\)-K operator is now large \(2\pi\cdot R\cdot PRF/v\) and includes \(R\cdot M\) bins.  
In principle, since SAR impulse response is range-variant, the \(\Omega\)-K algorithm is exact only at range \(r_{0}\) and the reconstruction should be repeated for each slant range of the received signal. In practice, anyway, the monochromatic assumption is a good approximation for SAR focusing and a sufficient accuracy can be achieved also by processing narrow slant range strips at a time, using the central range as reference. The width of these strips must be large enough to include the range migration cells of a synthetic aperture for the central target. For LEO orbit SAR, we found that processing few hundreds of range bins produces sufficient accurate results.  
A point target focused using \(N=R=5\) sensor at 500 km of altitude with \(L_{a}=3.5\) m, PRF = 880 Hz, \(\lambda=0.055\) m and formation extent 500 m is shown in Figure 3. Uniform and optimal spacing between sensors has been supposed. As can be seen, the azimuth ambiguities have been reduced to less than \(-70\) dB and, at the same time, the azimuth resolution has been improved to about 2 m. In these optimal conditions, the estimated gain is 13.56 dB, very close to the ideal value 13.98 dB (i.e., \(10\log_{10}5^{2}\)).
## 2 Sensor Principle
### Principle of a Fiber Optic Sensor Probe for Water Leak Detection  
A fiber optic sensor probe is designed to detect water leakage using a pair of high reflection connectors and a vessel with water combination soil (WCS) as shown in Figure 2(a). The chemical elements of WCS are acrylate polymers with an absorbance rate of 30 seconds. This probe has a vessel full of WCS and a mesh cloth and a metal wire on the opening part of the vessel. An optical fiber is located on the mesh cloth under the metal wire of the vessel. When the probe is in the state before absorbing water, the optical fiber is not bent, as shown in Figure 2(b). The volume of WCS will expand about 20 times the initial volume when it absorbs water as shown in Figure 3.  
This WCS material becomes jellylike when it absorbs water. The holes of the mesh cloth should be small enough to prevent the WCS from falling out of the vessel. However, water should be able to enter this vessel and contact the WCS. If the WCS meets water, then it will expand through the opening part of the vessel. Then, the mesh cloth will expand by the expansion of WCS, and the optical  
Figure 3: Feature of water combination soil (WCS).  
Figure 2: Configuration of a probe for water leak detection.  
fiber will be bent by the wire preventing this expansion as shown in Figure 2(c). The mesh used is a stocking material which consists of nylon and polyurethane. The breaking strength per 0.01 mm is 4 kg, and the mesh size is less than 1 mm [16]. As a result of this bending, the sensing signal of the sensor probe will be changed. Therefore, this signal change can indicate the water leakage. In order to define the output (\(S_{k}\)) at the k\({}^{\text{th}}\) sensor probe, we employ an equation using the ratio between the reference signal and the sensing signal as follows:  
\[S_{k}=-10\log_{10}\Biggl{(}\frac{I_{s,k}\ /\ I_{s0}}{I_{r,k}\ /\ I_{r0}} \Biggr{)} \tag{1}\]  
where \(I_{s0}\) and \(I_{r0}\) are the intensities of a sensing and reference signal at the initial state of the sensor probe, and \(I_{s,k}\) and \(I_{r,k}\) are the intensities of the sensing signal and the reference signal respectively at the present time in the k\({}^{\text{th}}\) sensor probe. As shown in Equation (1), the sensor output, \(S\), will be zero at the initial state or there is no water leak. However, if some water gets into the probe, then the sensor output will increase. This sensor probe having special two connectors is novel because the signal output, S\({}_{\text{k}}\), can be optimized by the reflection applying the connectors having optimal reflection rate. In other words, we can adjust the magnitude of the signal output of each sensor probe by controlling the reflection rate of the connectors.
## 4 Experiment
### The Influence of the Meta-Path Length  
Figure 9 illustrates the impact of the meta-path length on the MIMA algorithm's performance. The results of the precision and recall indicators gradually increase first and then decrease when the meta-path length is from 1 to 5. Shorter meta-paths may result in loss of feature information and weaker generalization capability because the meta-paths lack the refinement of complex relationships. Specifically, a meta-path with only one node cannot capture deeper association information, resulting in poor recommendation performance. Conversely, having too many nodes in a meta-path introduces too much noise and redundant information, making it difficult for the algorithm to extract useful features from the meta-path. Therefore, there is a trade-off between the number of nodes and model performance when choosing meta-path. In the MIMA algorithm, the optimal results are achieved when the meta-path includes three nodes.
## 2 Related Works  
With the rapid development of communication technology and changes in the communication environment, CP and dual-CP technologies have made significant advancements. Currently, many structures and processes for dual-CP antennas have been proposed: a typical method is to use a feeding network, which can output two signals with equal amplitude and phase orthogonal to each other [15; 16; 17; 18; 19]. This type of dual-CP antenna exhibits excellent directional radiation performance. However, the feeding network and the 90-degree phase shifter have complex structures and high design requirements, which can cause additional losses, thereby reducing the radiation efficiency of the antenna. Scholars have proposed antenna designs based on square slot [20; 21; 22; 23; 24; 25] structures and monopole antenna structures [26; 27]. These two types of dual-CP antennas usually have advantages such as wide bandwidth, low profile, and ease of fabrication. However, this type of antenna has a bidirectional radiation characteristic, which severely limits its application in communication systems. Additionally, there are some multi-feed dual-CP dual-band antennas [28; 29; 30; 31; 32; 33; 34; 35; 36] that achieve dual-band and dual-CP through multi-feeding ports and array forms but cannot achieve wide-beam coverage, or that rely on feeding networks to realize angle scanning, making them unsuitable for airborne platforms. Moreover, horn antennas are also frequently used to generate dual-CP radiation [37; 38; 39; 40; 41]. However, due to the characteristics of horn antennas, the beam width of the antennas is generally narrow, unable to meet the requirements for wide-beam coverage.  
Given that, this paper focuses on the destination of the antenna structure suitable for airborne relay communication systems, with the merits of dual-CP, wide beam width, and features such as high gain and miniaturization.
## 2 Confocal Ellipsoidal Densification Model (CEDM)
### Ellipsoid Equation for CEDM  
The equations for the vertical sections of the HCZ and WCZ ellipsoids shown in Figure 1, in rectangular coordinates, are as follows:  
\[\frac{\left(z-h_{i1}\right)^{2}}{b_{i1}^{2}}+\frac{x^{2}}{a_{i1}^{2}}=1 \tag{1}\]  
\[\frac{\left(z-h_{i2}\right)^{2}}{b_{i2}^{2}}+\frac{x^{2}}{a_{i2}^{2}}=1 \tag{2}\]  
where \(h_{i1}\) is the vertical coordinate of the HCZ ellipsoid; \(a_{i1}\) and \(b_{i1}\) are the minor axis and major axis of the HCZ ellipsoid, respectively; \(h_{i2}\) is the vertical coordinate of the WCZ ellipsoid; \(a_{i2}\) and \(b_{i2}\) are the minor axis and major axis, respectively, of the WCZ ellipsoid; and \(i\) is the number of tampings. Taking the common focus as the origin of polar coordinates, the equations for the vertical sections of the HCZ and WCZ ellipsoids, in polar coordinates, are as follows:  
\[\rho=\frac{e_{i1}p_{i1}}{1-e_{i1}\cos\theta} \tag{3}\]  
\[\rho=\frac{e_{i2}p_{i2}}{1-e_{i2}\cos\theta} \tag{4}\]  
where \(e_{i1}=c_{i1}/b_{i1}\) and \(e_{i2}=c_{i2}/b_{i2}\); \(p_{i1}=a_{i1}^{2}/c_{i1}\) and \(p_{i2}=a_{i2}^{2}/c_{i2}\); \(c_{i1}\) is the eccentric distance of the HCZ ellipsoid, where \(c_{i1}=\sqrt{b_{i1}^{2}-a_{i1}^{2}}\); and \(c_{i2}\) is the eccentric distance of the WCZ ellipsoid, where \(c_{i2}=\sqrt{b_{i2}^{2}-a_{i2}^{2}}\). Because the edges of the HCZ and WCZ ellipsoids pass through the corner point \((R,d_{i})\) of the tamper, substituting this point into Equations (1) and (2) gives  
\[\frac{\left(d_{i}-h_{i1}\right)^{2}}{b_{i1}^{2}}+\frac{R^{2}}{a_{i1}^{2}}=1 \tag{5}\]  
\[\frac{\left(d_{i}-h_{i2}\right)^{2}}{b_{i2}^{2}}+\frac{R^{2}}{a_{i2}^{2}}=1 \tag{6}\]Applying \(\xi_{i1}=h_{i1}-d_{i}>0\) and \(\xi_{i2}=h_{i2}-d_{i}>0\), Equations (5) and (6) are transformed into the following expressions:  
\[\frac{\xi_{i1}^{2}}{b_{i1}^{2}}+\frac{R^{2}}{a_{i1}^{2}}=1 \tag{7}\]  
\[\frac{\xi_{i2}^{2}}{b_{i2}^{2}}+\frac{R^{2}}{a_{i2}^{2}}=1 \tag{8}\]  
Taking the derivation of Equations (1) and (2) with respect to \(x\), we obtain  
\[\frac{dz}{dx}=-\frac{xb_{i1}^{2}}{(z-h_{i1})a_{i1}^{2}}=\frac{xb_{i1}^{2}}{(h _{i1}-z)a_{i1}^{2}} \tag{9}\]  
\[\frac{dz}{dx}=-\frac{xb_{i2}^{2}}{(z-h_{i2})a_{i2}^{2}}=\frac{xb_{i2}^{2}}{(h _{i2}-z)a_{i2}^{2}} \tag{10}\]  
In addition, Equation (11) is obtained as follows:  
\[\frac{\left(z-h_{i2}\right)^{2}}{b_{i2}^{2}}+\frac{x^{2}}{a_{i2}^{2}}=1 \tag{2}\]0  
where \(\alpha_{1}\) and \(\alpha_{2}\) are the angles between the connecting lines of the common focus and the corner point \((R,d_{i})\) and the tangent lines of HCZ and WCZ ellipsoids. During the dynamic compacting process, the soil at the corner point of the crater \((R,d_{i})\) is in a state of limit equilibrium. According to the Mohr-Coulomb strength criterion, the angle between the two failure surfaces (the tangent line of the ellipsoid) is expressed as \(45^{\circ}+\varphi/2\), in which \(\varphi\) is the friction angle of soil for the improved zones.