esa-sceva/satcom-chunk-collection huggingface dataset:
# Approximate Image-Space Multidirectional Occlusion Shading Model for Direct Volume Rendering
## 3 Image Space Multidirectional Occlusion Shading Model
### Occlusion Computation
#### 3.3.1 Full Occlusion  
In order to compute full occlusion, we generated paths from a pixel (\(P\)) to the light samples (\(Lp\)) and tested whether the paths were occluded by neighbors during ray marching. The ray marching is illustrated in Figure 4a and performed on the paths defined by:  
\[r(t)=P\cdot(1-t)+L_{sp}\cdot t, \tag{1}\]  
where \(t\) is between zero and one. In order to test whether \(r(t)\) passes through any opaque rendered scene, we sampled \(N_{R}\) test points (green dots in Figure 4a) along the path \(r(t)\). We incremented \(t\) by \(\Delta t=1.0/N_{R}\) from \(P\) and checked if the test point was occluded. For more efficient sampling of the test points, we calculated \(t_{b}\) at the boundary of the space and used it instead of 1.0. Therefore, the increment was rewritten as \(\Delta t=t_{b}/N_{R}\), where \(t_{b}<1.0\). The occlusion was tested by comparing the z-value of \(r(t)\) with the z-value fromthe depth buffer at a pixel onto which \(r(t)\) were projected. If the z-value from the depth buffer was higher than the z-value of \(r(t)\), the path \(r(t)\) was occluded; otherwise, the path was not blocked by any rendered scene. If the test point was occluded, we then terminated the ray marching and increased \(N_{o}\) by one. Otherwise, we moved to the next test point by adding \(\Delta t\) to \(t\). Finally, the occlusion from the light source was computed as:  
\[O_{cc}=\frac{N_{o}}{N}, \tag{2}\]  
where the \(N_{o}\) is the number of occluded light samples and \(N\) is the total number of light samples introduced in Section 3.2.  
Once the \(O_{cc}\) was calculated, the final color was computed as:  
\[C_{final}=C_{p}\cdot I_{L}\cdot\max((1.0-O_{cc}),I_{amb}) \tag{3}\]  
where \(C_{p}\) is a color at a pixel from the color buffer assuming that the color of the light source is white and \(I_{L}\) is the light intensity. \(I_{amb}\) is an ambient light term that adjusts the darkness of the occlusion and prevents completely dark pixels. An example of full occlusion is presented in Figure 5b. The effect of large \(I_{amb}\) is shown in (c).
## 4 Control Design
### Stability Experiment with Load  
The stability of the control system was tested by fixing a 2-kg mass block on the rotary table of the pneumatic rotary actuator. Then the moment of inertia \(J\) changed to 3.356 \(\times\) 10\({}^{-3}\) kg\(\cdot\)m\({}^{2}\). The mass block increased the moment of inertia of the rotary table, which affected the position accuracy of the system. Using the same method, first we used different control strategies to tune the controller coefficients and friction parameters of the system respectively, and then substituted them into the system for testing. Figure 15 describes the position tracking performance of the pneumatic rotary actuator with a load. Figure 16 shows the positioning performance of the actuator with a load.  
As shown in Figure 15b, the maximum angular errors of four control strategies (traditional PD control, PD with friction compensation, DE-PD and GA-PD control) were 0.885\({}^{\circ}\), 0.357\({}^{\circ}\), 0.125\({}^{\circ}\), and 0.27\({}^{\circ}\) respectively. In Figure 16b, the steady-state errors of the pneumatic rotary actuator were 0.25\({}^{\circ}\), 0.125\({}^{\circ}\), 0.025\({}^{\circ}\) and 0.1\({}^{\circ}\) respectively. Compared with Figures 11b and 14b, the errors of the actuator with a load are relatively large. This is because the increase of the load leads to an increase in the dead zone characteristic, which means that the micro pressure difference in the actuator chambers is difficult to change the rotation angle when the target angle is approached. Even so, the friction feedforward compensation based on evolutionary algorithm can still keep the error within a small range, which well verifies the strong stability of the control system.  
Figure 14: Position tracking performances under four control strategies. (**a**) Angle contrast curve; (**b**) error contrast curve; and (**c**) angular velocity contrast curve.  
The allowable load of the pneumatic rotary actuator is 48 N [37]. We tested the angle errors of the system when the load is 1 kg, 2 kg, 3 kg and 4 kg. Figure 17 shows their angle errors under different loads, and clearly describes the trends of errors. The result reveals that the evolutionary algorithm-turned errors are relatively small and have good stability, and that the DE-based case has higher accuracy. In conclusions, it is the smoothness and accuracy of the algorithm iterative process that make the system under different loads still have stable performances.  
Figure 16: Positioning performance in the stability experiment. (**a**) Angle contrast curve; (**b**) error contrast curve.  
Figure 15: Position tracking performance in the stability experiment. (**a**) Angle contrast curve; (**b**) error contrast curve.
# A Back-to-Back Gap Waveguide-Based Packaging Structure for E-Band Radio Frequency Front-End
## 4 Conclusions  
In this paper, we have proposed an E-band RF front-end packaging structure based on back-to-back GWs. By utilizing hybrid couplers as the core components and incorporating two types of fifth-order Chebyshev filters along with H-plane transitions, we have  
Figure 16: Measured and simulated results for the final packaging structure.  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Stage I** & **Stage II** & **Stage III** & **Stage IV** & **Stage V** \\ \hline \multirow{4}{*}{Determine the overall performance indicators, such as passband, insertion coupler, filter and transition structure respectively} & 1. Select the material of the substrate and the form of the & & 1. Metal structures are produced using & 1. Assemble using \\  & the form of the & Design the signal & CNC technology. & conductive glue and \\ \cline{1-1}  & transmission line & ports and connect & & screws \\ \cline{1-1}  & each component unit & & 2. Fabricate dielectric & \\ \cline{1-1}  & 2. Design the hybrid coupler, filter and transition structure & optimize the model & substrates using the & 2. Measure the \\ \cline{1-1}  & respectively & & & process. & packaging structure \\ \hline \end{tabular}
\end{table}
Table 3: The design and measurement steps for the proposed packaging structure.  
successfully achieved a complex packaging structure that is easily designable and optimizable. Meanwhile, the adoption of back-to-back structures effectively reduces the overall packaging volume. The results, subsequent to fabrication and measurement, demonstrate a passband range of 70.95-76.2 GHz and 80.92-86.25 GHz, with insertion losses below 2.26 dB and 2.42 dB, respectively, showcasing excellent electrical performance.  
Conceptualization, T.X. and Z.L.; methodology, Z.L. and T.X.; software, T.X. and Z.L.; validation, T.X., Z.L., L.W. and P.L.; formal analysis, Z.L. and L.W.; investigation, T.X. and Z.L.; resources, T.X., Z.L., L.W. and P.L.; data curation, T.X. and Z.L.; writing--original draft preparation, T.X.; writing--review and editing, Z.L., L.W. and P.L.; visualization, T.X.; supervision, Z.L. and L.W.; project administration, Z.L.; funding acquisition, Z.L. and L.W. All authors have read and agreed to the published version of the manuscript. This research received no external funding.  
The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.  
The authors declare no conflicts of interest.
# Review of Communication Technologies for Electric Vehicle Charging Management and Coordination
## 3 Dedicated Short-Range Communication (DSRC)  
Dedicated short-range communications (DSRC) is a wireless communication technology designed to support automotive and intelligent transportation system (ITS) applications to enable short-range information exchange between DSRC-enabled devices [50]. In general, there are two communication nodes defined in DSRC: the on-board unit (OBU), also known as the mobile node and is located in the vehicle, and the roadside unit (RSU), or the fixed node, which is installed on the roadside infrastructure. Two physical layer protocols are adopted in DSRC networks, namely IEEE 802.11p and IEEE 802.11 bd.
# Three-Phase Unbalance Analysis Method Based on Three-Phase Motor Current Instantaneous Information
### Park Vector Demodulation  
The speed of a three-phase asynchronous motor is calculated as shown in Equation (1).  
\[n=60\cdot\frac{1-s}{p}\cdot f \tag{1}\]  
where \(n\) is the rotational speed (r/min), \(s\) is the slip rate, \(p\) is the number of pole-pairs, and \(f\) is the rotational frequency.  
The three-phase current signal is a modulated signal with a 120\({}^{\circ}\) phase difference between any two phases. By using the Park transform, a 90\({}^{\circ}\) phase shift signal can be created as a way to complete the signal demodulation [22], as follows.  
\[\left\{\begin{aligned} I_{a}&=\frac{2I_{u}-I_{v}-I_{w} }{3}\\ I_{\beta}&=\frac{\sqrt{3}(I_{v}-I_{w})}{3}\end{aligned}\right. \tag{2}\]  
where \(I_{a}\) and \(I_{\beta}\) are the stator coordinate system currents, and \(I_{u}\), \(I_{v}\), and \(I_{w}\) are the motor U-phase, V-phase, and W-phase currents, respectively.  
Then, the three-phase current can be expressed as follows:  
\[\left\{\begin{aligned} I_{u}&=a\cdot\cos(2\pi f_{M}t) \\ I_{v}&=a\cdot\cos(2\pi f_{M}t-\frac{2\pi}{3})\\ I_{w}&=a\cdot\cos(2\pi f_{M}t-\frac{4\pi}{3})\end{aligned}\right. \tag{3}\]  
where \(f_{M}\) is the signal fundamental frequency and \(a\) is the amplitude of the signal.  
Combining Equations (2) and (3) yields the following:  
\[\left\{\begin{aligned} I_{a}&=a\cdot\cos(2\pi f_{M}t) \\ I_{\beta}&=a\cdot\sin(2\pi f_{M}t)\end{aligned}\right. \tag{4}\]  
The analytic signal is constructed from \(I_{a}\) and \(I_{\beta}\), as shown in Equation (5).  
\[I_{z}=I_{a}+I_{\beta}\cdot i \tag{5}\]  
where \(I_{z}\) is the constructed complex signal.  
The instantaneous amplitude and instantaneous phase are obtained by calculating the mode and amplitude angle of the constructed analytic signal. The mode and amplitude angles of \(I_{z}\) are obtained as follows:  
\[\left\{\begin{aligned} |I_{z}|&=\sqrt{{I_{a}}^{2}+{I_{ \beta}}^{2}}=a(t)\\ \arg(I_{z})&=\tan^{-1}\left(\frac{I_{\beta}}{I_{a}} \right)=2\pi f_{M}t=\varphi(t)\end{aligned}\right. \tag{6}\]  
where \(a(t)\) is the instantaneous amplitude and \(\varphi(t)\) is the instantaneous phase.  
The instantaneous frequency is the reciprocal of the instantaneous phase, i.e.,  
\[f(t)=\frac{1}{2\pi}.\frac{d\varphi(t)}{dt} \tag{7}\]  
where \(f(t)\) is the instantaneous frequency.  
The instantaneous amplitude and instantaneous frequency are the instantaneous information of the multi-sensor information fusion of the three-phase current signal, reflecting the comprehensive characteristics of the three-phase current.
# Dynamic Behavior Analysis and Stability Control of Tethered Satellite Formation Deployment
## 6 Conclusions  
In this paper, nonlinear dynamic characteristics of TSS during a configuration conversion process were analyzed based on a simplified rigid-rod model. Tether tension control was proposed, and numerical simulations show that the proposed law can suppress in-plane and out-of-plane librations of rigid tethered satellites during deployment, and spacecraft and tether stability control goals can be achieved. The periodic stability of time-varying control systems was analyzed by using Floquet theory, and small parameter regions of TSS in asymptotically stable states were expressed.  
In summary, this paper has provided tether release rate and tether tension control laws for suppressing wide-ranging TSS vibrations that are valuable for improving TSS attitude control accuracy and performance, specifically for TSSs that are operating in low-eccentricity orbits. Additionally, future studies based on existing research can be conducted with respect to two aspects: (1) A more accurate model can be established since, in the current study, the tether was discretized into a series of lumped masses connected by springs and dampers with mass. (2) Applications of accurate models can generate more dimensions, and Floquet theory used to analyze the stability of high-dimensional dynamic systems requires further verification.  
Conceptualization, K.Z. and K.L.; methodology, K.Z.; software, K.Z.; validation, K.Z., K.L. and X.G.; formal analysis, K.Z., K.L., C.F.; investigation, K.Z., K.L.; resources, K.L.; data curation, K.L.; writing--original draft preparation, K.Z.; writing--review and editing, C.F., S.Z.; visualization, K.L.; supervision, C.F., S.Z.; project administration, X.G.; funding acquisition, K.L. 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 No. 2020 YFA0711700); the National Natural Science Foundation of China (Grant Nos. 12072263, 11802235); Natural Science Foundation of Shaanxi Province (Grant No. 2020 JQ-129); State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures (Grant No. KF2020-26); and China Postdoctoral Science Foundation (2021T140033, 2021M690274).
# Supramolecular Materials as Solid-Phase Microextraction Coatings in Environmental Analysis
## 4 Covalent Organic Frameworks (COFs)
### COFs as SPME Coatings for Environmental Applications  
COFs as SPME coatings, prepared by physical adhesion, the sol-gel method, in situ growth, and chemical cross-linking, have recently attracted considerable attention for the analysis of organic pollutants, including polycyclic aromatic hydrocarbons [94; 101; 102; 103; 104; 105; 106; 107; 108; 109; 110; 111; 112], phenols [97; 113; 114; 115], polybrominated diphenyl ethers [98; 100; 116; 117; 118; 119; 120], polyhalogenated biphenyls [99; 121; 122], pesticides [123; 124; 125; 126; 127; 128], and PFASs [129; 130; 131] in environmental samples. The COF-based coatings used for the extraction of targeted compounds in environmental samples are summarized in Table 2.
# Determining Optimal Power Flow Solutions Using New Adaptive Gaussian TLBO Method
## 5 Conclusions  
This paper develops a new effective improved teaching-learning-based optimization (TLBO) algorithm called adaptive Gaussian TLBO (AGTLBO) to solve the optimum power flow (OPF) problem. This problem entails choosing decision variables such as transformer pulses, generator outputs, reactive power sources in the most efficient way possible and generator voltages. The adaptive Gaussian mechanism was incorporated into the teaching and learning phases and its mathematical relations to increase the exploration and exploitation capabilities of the conventional TLBO. Then, the solution method was expressed step by step using the proposed AGTLBO for solving the OPF problem. The AGTLBO was applied to three test networks, i.e., standard IEEE 30-, 57- and 118-bus systems, in 12 cases with a combination of different objective functions such as fuel cost, losses, voltage deviation, and pollution. Using the proposed method on these 12 cases was compared with other state-of-the-art optimization methods. It was shown that AGTLBO has a significant advantage in finding the optimal solutions compared to other algorithms. It has been shown from statistical and comparative analyses that AGTLBO produces excellent performance and outperforms both TLBO and other algorithms for most applications. Despite the longer computation time, AGTLBO outperforms all the different algorithms due to its superior results. In summary, it can be concluded that AGTLBO can be an effective alternative to solving OPF. Further reducing the computational burden with parallel computing will be a future challenge and opportunity. The multi-objective AGTLBO in a multi-objective OPF problem is under development and will be proposed soon. In addition, statistical results showed that this algorithm can be useful for practical applications and can also be used to solve other engineering problems well. In future work, the multi-objective model of OPF problem using an efficient method can be investigated, and the integration of intermittent renewable generations can also be considered in the optimization model. This approach provides robust and high-quality OPF solutions for single and multi-objective optimization problems, such as optimizing total fuel costs, minimizing active power losses, and minimizing pollution and voltage deviations. Compared with the original TLBO, three original algorithms, and many other well-known metaheuristic techniques reported in the literature, the proposed AGTLBO achieves acceptable and effective OPF solutions and converges to the global optimum with fewer iterations.  
Conceptualization and methodology, A.A. and M.A.; software, Z.A.M. and A.M.; validation, M.A. and Z.A.M.; formal analysis and investigation, A.A.; writing--original draft preparation, A.A.; writing--review and editing, M.A. and A.M.; visualization, A.M.; supervision. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The authors declare no conflict of interest.
# Low-Complexity High-Throughput QC-LDPC Decoder for 5G New Radio Wireless Communication
## 2 5G New Radio LDPC Codes
### Quasi-Cyclic LDPC Codes  
QC-LDPC codes [29], which are a class of structured LDPC codes, are widely used in many practical applications. A binary \((N,K)\) QC-LDPC code is characterized by the null space of an \(M\times N\) parity-check matrix \(H\), which consists of an array of circulant matrices of the same size [30; 31]. The parity-check matrix of a QC-LDPC code can be illustrated by its base graph and shift coefficients. Elements 1s in the base graph are replaced by a circulant permutation matrix of size \(Z\times Z\) and 0 s are replaced by and a zero matrix of the same size.  
Denote \(Z\) as the size of a circulant permutation matrix and \(P_{m,n}\) as the shift coefficient value. For any integer value \(P_{m,n}\), \(0\leq P_{m,n}\leq Z\), a \(Z\times Z\) circulant permutation matrix is defined as the cyclic-shift of the \(Z\times Z\) identity matrix \(I\) to the right by \(P_{m,n}\) times for the \((m,n)\)th non-zero element in a base matrix. This binary circulant permutation matrix is denoted as \(Q(P_{m,n})\). For simple notation, \(Q(-1)\) denotes the null matrix (i.e., all elements equal to zero) of the same size. Considering \(Q(1)\) as an example,  
\[Q(1)=\begin{bmatrix}0&1&0&\cdots&0\\ 0&0&1&\cdots&0\\ \vdots&\vdots&\vdots&\ddots&\vdots\\ 0&0&0&\cdots&1\\ 1&0&0&\cdots&0\end{bmatrix} \tag{1}\]  
For two positive integers \(m_{b}\) and \(n_{b}\), with \(m_{b}\leq n_{b}\), consider the QC-LDPC code expressed by the following \(m_{b}\times n_{b}\) array of \(Z\times Z\) circulants over GF(2):  
\[H=\begin{bmatrix}Q(P_{1,1})&Q(P_{1,2})&\cdots&Q(P_{1,n_{b}})\\ Q(P_{2,1})&Q(P_{2,2})&\cdots&Q(P_{2,n_{b}})\\ \vdots&\vdots&\ddots&\vdots\\ Q(P_{m_{b},1})&Q(P_{m_{b},2})&\cdots&Q(P_{m_{b},n_{b}})\end{bmatrix} \tag{2}\]  
The exponent matrix of \(H\), which is \(E(H)\), has the following form:  
\[E(H)=\begin{bmatrix}P_{1,1}&P_{1,2}&\cdots&P_{1,n_{b}}\\ P_{2,1}&P_{2,2}&\cdots&P_{2,n_{b}}\\ \vdots&\vdots&\ddots&\vdots\\ P_{m_{b},1}&P_{m_{b},2}&\cdots&P_{m_{b},n_{b}}\end{bmatrix} \tag{3}\]  
Each entry in the matrix \(E\) is denoted as a shift value. It should be noted that the parity-check matrix \(H\) in Equation (2) can be constructed by expanding the \(m_{b}\times n_{b}\) exponent matrix \(E(H)\). This procedure is referred to as protograph construction [32]. It follows that the parity-check matrix \(H\) is of size \(M\times N\) where \(M=Z\times m_{b}\) and \(N=Z\times n_{b}\).
## 2 Results and Discussion
### Experiments
In Figure 8c, the image of the EBT3 film at 4 cm after the Kapton window irradiated by 15 shots is reported showing slight ellipticity of the proton beam due to the MBL. The experimental measurements show a good agreement with the simulated beam reported in Figure 8a. The proton beam after 4-cm propagation in air shows a smoother profile with a few mm gradient region at the edge of the beam in agreement with the SRIM calculations. These results confirm that the MBL is producing a well-collimated proton beam for several centimeters in the air. The delivered dose is evaluated from the optical density of the scanned EBT3 radiochromic film and the calibrations reported for mono-energetic protons [42; 43]. Thus the calculated average dose is 1 Gy/shot and 0.4 Gy/shot after propagating in air for 1 cm and 4 cm respectively with an uncertainty estimated to be in the order of 20% (see the Material and Methods Experiments section). The reduced dose measured further away from the Kapton window reflects the loss of lower energy protons in air, as from the calculations reported in Figure 3b. The proton particle fluence per shot after propagating 4 cm in the air is estimated to be \(3\times 10^{7}\) cm\({}^{-2}\). Figure 7: Time-of-flight measurements with and without the MBL: The first peak is due to fast electrons and X-rays, and the second peak is due to protons (cut-off energy highlighted).
## 4 Results and discussion
### Pull-in parameters from the analysis of frequencies of a deformed plate  
In Figure 9, we report, for two different values of \(\mu\), the fundamental frequency \(\omega_{0}\) of the deflected microplate versus \(\lambda\) for \(\alpha=4\) and \(\beta=0\) and for a square and a rectangular plate. The natural frequency is normalized with respect to the value \(\bar{\omega}_{0}\) corresponding to \(\lambda=0\); values of non-dimensional \(\bar{\omega}_{0}\) for Figures 9 and 10 are reported in Table 1. The corresponding dimensional frequencies equal \(\bar{\omega}_{0}\sqrt{D/(\varrho\ell^{4})}\). As reported in [56], for \(\mu=0\) and \(\lambda=0\), the values of the non-dimensional frequency \(\bar{\omega}_{0}\) equal \(36.108\)  
**Figure 6**. For \(\mu\simeq 0.3\mu_{\rm cr}\) and \(\alpha=4\), deformed shape of (a) the square plate with \(\lambda\simeq 200\) and \(\|w\|_{\infty}\simeq 0.59\), and (b) rectangular plate with \(\varphi=1/2\), \(\lambda\simeq 1500\) and \(\|w\|_{\infty}\simeq 0.59\). Fringe plots of the van der Waals pressure are also displayed.  
**Figure 7**. For \(\alpha=1\) (solid line) and \(\alpha=4\) (dashed line), variation with \(\beta\) of the critical van der Waals force parameter \(\mu_{\rm cr}\) for (a) square plate and (b) rectangular plate with \(\varphi=1/2\).  
and \(98.592\) for the square and the rectangular plate with \(\varphi=1/2\), respectively.  
The variation of \(\omega_{0}/\bar{\omega}_{0}\) with \(\lambda\) is non-monotonic due to the combined effect of the strain hardening represented by \(k_{3}\zeta^{3}\) and the softening effect introduced by the Coulomb and the van der Waals forces. Indeed, from equation (26), it is clear that the overall behavior of the Coulomb and the van der Waals forces is equivalent to a nonlinear spring with negative spring constant. When the strain-hardening effect is negligible the fundamental frequency monotonically decreases to zero, as it is typically predicted by the linear plate theory.  
Results reported in Figure 10 show that for \(\alpha=1\) and \(\beta=0\) the fundamental frequency monotonically decreases, implying that in this case the softening effect related to the Coulomb and the van der Waals forces overwhelms the strain hardening effect due to the mechanical nonlinearity. We note that the value of \(\lambda\) corresponding to \(\omega_{0}=0\) agrees with the \(\lambda_{\rm PI}\) found from Figures 4 and 5 which of course should be true since in both cases \(K\left(\zeta,\lambda,\mu\right)=0\). This provides an alternative way to find the pull-in parameters.  
Figure 8: For \(\alpha=1\) (solid line), \(\alpha=4\) (dashed line), and \(\mu=0\), variation with \(\beta\) of the pull-in voltage parameter \(\lambda_{\rm PI}\) for (a) square plate, and (b) rectangular plate with \(\varphi=1/2\).