esa-sceva/satcom-chunk-collection huggingface dataset:
# Surface Charging on Insulating Films with Different Thicknesses in UPS
## 3 Results and Discussion
### Charging-Induced Surface Potential  
The investigation reveals that charging effects persistently manifest and interfere with spectral measurements. The direct measurement of surface potential induced by charging  
Figure 3: Sequential evolution regimes of UPS spectra for Sample 1 (**a**–**c**). (**d**) The normalized spectral comparison between regime 2 and regime 3. (**e.f**) Corresponding evolution sequences for Sample 2.  
effects during photoelectron spectroscopy remains technically challenging. However, a practical methodology has been implemented by analyzing the discrepancy between VBM positions derived from XPS and UPS spectra. This approach, though constrained by the inherent energy resolution limit of XPS, provides a viable solution for quantifying charging-induced surface potential on insulating surfaces. As demonstrated in Figure 4 for Sample 2, the surface potential values corresponding to different film thicknesses are labeled separately. Parallel analysis is also performed on Sample 1, and both results are shown in Figure 5.  
Figure 4: Comparative analysis of normalized UPS and XPS valence band spectral intensities during depth profiling of Sample 2. \(\Delta\)E denotes characteristic energy shift in UPS spectra induced by surface charging effects.  
Figure 5: Surface potential evolution during depth profiling of Sample 1 and Sample 2.  
Both samples exhibit analogous trends in surface potential evolution, with direct correlations observed between surface potential variations and UPS spectral shifts. For Sample 2, the surface potential shows gradual growth (0-1 V) within the 0-8 nm thickness range, where sufficient tunneling-assisted conduction maintains effective charge compensation [27], resulting in minimal spectral distortion. Beyond the critical thickness threshold (about 8 nm), the value of surface potential undergoes abrupt intensification (3-5 V) due to the weakening of the tunneling of electrons with the growth of the film resistivity. Meanwhile, internal electric fields between the charged surface and the conductive substrate are formed, and therefore the competing migration of UV-generated holes and compensation electrons under the field leads to the fact that the surface potential does not increase further.  
This stabilization mechanism persists through subsequent thickness increments. Similar behavior is also observed in Sample 1, though with modified dynamics: Enhanced substrate conductivity (0.001-0.005 \(\Omega\)-cm vs. 1-10 \(\Omega\)-cm for Sample 2) facilitates more efficient charge dissipation through the Si/SiO\({}_{2}\) interface. However, at thicknesses (>50 nm), weakened electron compensation via the substrate-film-surface pathway leads to progressive charge accumulation, and further results in the emergence of lateral potential inhomogeneity and consequent spectral attenuation and broadening.
# Thermal Energy Diffusion Incorporating Generalized Einstein Relation for Degenerate Semiconductors
## 2 The Effective Temperature of Electrons in Thermal Equilibrium
By using the empirical approximation, the density moment equation is evaluated as follows:  
\[\mathcal{D}=\tfrac{2(\lambda+1/2)!}{\sqrt{\pi}}(k_{B}T_{L})^{\lambda}N_{c}\Big{[} F_{(\lambda+1/2)}(\eta_{c})+\tfrac{12}{5}\,\beta(\lambda+3/2)F_{(\lambda+3/2)}( \eta_{c})+\tfrac{4}{5}\beta^{2}(\lambda+5/2)(\lambda+3/2)F_{(\lambda+5/2)}( \eta_{c})\Big{]}. \tag{17}\]  
By letting \(\lambda\) = 0 and \(\lambda\) = 1, the electron concentration and the thermal kinetic energy density are obtained, respectively, as:  
\[n=N_{c}\Big{[}F_{1/2}(\eta_{c})+(18/5)\beta F_{3/2}(\eta_{c})+3\beta^{2}F_{5/2 }(\eta_{c})\Big{]}, \tag{18}\]  
and  
\[W=\frac{3}{2}k_{B}T_{L}N_{c}\Big{[}F_{3/2}(\eta_{c})+6\beta F_{5/2}(\eta_{c})+ 7\beta^{2}F_{7/2}(\eta_{c})\Big{]}, \tag{19}\]  
where  
\[F_{j}(\eta_{c})=\frac{1}{j!}\int_{0}^{\infty}\frac{\chi^{j}}{1+\exp(\chi-\eta _{c})}d\chi \tag{20}\]  
for the Fermi-Dirac integral of order \(j\). Finally, from Equations (9), (18) and (19), the effective temperature of electrons for nonparabolic energy bands is obtained as:  
\[T_{E}=\bigg{[}\frac{F_{3/2}(\eta_{c})+6\beta F_{5/2}(\eta_{c})+7\beta^{2}F_{7/ 2}(\eta_{c})}{F_{1/2}(\eta_{c})+(18/5)\beta F_{3/2}(\eta_{c})+3\beta^{2}F_{5/2 }(\eta_{c})}\bigg{]}T_{L}\bigg{(}=\frac{2}{3k_{B}}w\bigg{)}. \tag{21}\]  
From this equation, it is worth noting that, for nonparabolic CBs where \(\beta\) > 0, we always have \(T_{E}\) > \(T_{L}\) for any values of \(\eta_{c}\). For parabolic CBs where \(\beta\) = 0, Equation (21) gives \(T_{E}\approx T_{L}\) for the nondegenerate condition and \(T_{E}\) = \(F_{3/2}(\eta_{c})/F_{1/2}(\eta_{c})T_{L}\) generally.
## 3 Materials
### Sealing Materials  
The mixing of fuel and oxidant in SOFC is avoided with the help of sealing materials. In tubular geometry of SOFCs, the sealing is not a major problem; however, in planar SOFCs it is one of the critical issues. The SOFCs seal must have matching thermal expansion coefficients with electrolyte, be non reactive in contact with SOFCs components and have thermal stability in SOFC environment. SOFCs seals can be divided into two types; compressive seals (mica sheets or metal gaskets) and rigid seals (composites of glass/ceramic or glass). The low cost and air tight seals are usually composite glass ceramic seals such as CaO-SiO\({}_{2}\) and BaO-Al\({}_{2}\)O\({}_{3}\)-SiO\({}_{2}\)[12; 50; 100; 101]. Furthermore, these materials show chemical inertness toward components in contact with them as compared to bare borosilicate type glasses. No doubt glass seals perform well in SOFC operating environment for short to midterm operations but their stability for long term operations (>20,000 operating h) is still not fully known. Furthermore, the ability of thermal cycling of these materials in startup and shutdown of SOFCs is a key issue. Also, in the case of rigid seal, whole SOFC stack will also become rigid, thus if the single cell cracks, the whole stack will become useless [50; 100]. On the other hand, compressive seal is much more resistant to thermal shocks and remains stable for long term operations, but if metal gaskets are used in these seal it can lead to short circuiting. An intense compression is needed in case of mica sheet seals in order to be hermetic [100]. Therefore, a hybrid approach can be taken, _i.e._, rigid seal along with compressive seal can be used. Minimal seal leakage with outstanding performance of thermal cycling is observed while using hybrid seals [102; 103]. It is observed from the literature that no single approach is taken by R & D groups and companies toward the usage of sealing technology [12; 35; 100; 102; 103].
# An Energy-Efficient Integration of a Digital Modulator and a Class-D Amplifier
## 5 Experimental Setup and Results
### Results  
Figure 14 shows the waveform acquired from testing the prototype circuit, which is similar to the waveform as obtained in Figure 11 from the simulation. The horizontal axis represents the time in seconds, while the amplitude is shown on the vertical axis in volts. The sawtooth waveform shown in green represents the carrier, i.e., the \(-ve\) input of the comparator IC LM393, while the binary input  
Figure 12: Power spectrum of proposed model.  
Figure 13: Circuit diagram of proposed design.  
signal is shown in red applied to the \(+ve\) input of the comparator. The PWM output of the comparator is shown in blue and passes to the buffers to drive the power MOSFET transistors. Finally, the filter output, i.e., amplified PSK-modulated signal, is shown in purple.
# Microcrack Detection Using Spectral Response Data Alone
## 4 Conclusions  
The feasibility of using spectral response data as a crack indicator was investigated and verified through experiments with simple specimens. An impact force was imposed using an impact hammer, and the responses at six different locations on the specimen were measured. The theoretical crack indicator was derived under the assumption that the input impact force is similar in all experimental cases. The sensitivity of the FRF was verified in accordance with a previous study and was found to be less dependent on the distance of the measurement location from the microcrack if the measurement location was in-plane with the responsible mode shape. The resonance frequency and the sideband frequency can be used as crack indicators; between the two, the sideband frequency was considered more suitable for crack detection because the coherence value from the original frequency varied with the measurement location. The crack indicator may be partially applicable at sideband frequency region if the measurement was done at out-of-plane with the critical mode shape. When using response data alone, the feasibility of microcrack detection can be proved using the crack indicator at these two frequencies as in the FRF case. However, the crack indicator obtained using the coherence function revealed that the dependency of these frequencies on the measurement location was higher than in the FRF case. For the in-plane (front) measurement locations, #1 and #2, the crack indicator at the sideband frequency was very sensitive whereas that at the resonance frequency varied at location #2. For other in-plane (rear) measurement locations, #3 and #4, the sensitivity at the sideband frequency decreased at location #4 (far from crack) but not at location #3; however, the sensitivity at the resonance frequency for these two measurement locations was consistently high. However, in case of out-of-plane measurement case, #5 and #6, the two sensitive frequencies were not valid for the crack indicator. So, the microcrack detection with response data only should consider the mode shape of critical resonance frequency by allocating all measurement location at in-plane. Under these requirements, the feasibility of microcrack detection is possible with response data only.  
Conceptualization, C-J-K.; methodology, C-J.K.; validation, C-J-K. and G-S.L.; formal analysis, G-S.L.; investigation, C-J.K.; resources, C-J.K.; data curation, C-J.K. and G-S.L.; writing--original draft preparation, C-J.K.; writing--review and editing, C-J.K. and G-S.L.; project administration, C-J.K. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
This work was supported by a Research Grant from the Ministry of Science and ICT/South Korea (#1711124126, 2020).  
The authors declare no conflict of interest.
# Reconstruction and Measurement of Irregular Karst Caves Using BLST along the Shield Metro Line
## 6 Conclusions  
(1) This paper discussed the application effect of laser point cloud scanning in dry caves and water-filled caves, designed a multiwavelength laser attenuation characteristic test for water-filled caves in order to solve the problem of excessive laser attenuation in the detection of water-filled caves, and investigated the effects of different laser wavelengths, different laser power levels, different suspended media, and different turbidity grades on the laser attenuation coefficient.  
(2) The effects of laser wavelength, power, and karst cave water environments on the attenuation characteristics were revealed, and the existence of a \"blue-green window\" with low turbidity and \"near infrared window\" with high turbidity were discovered. The laser attenuation coefficients of different wavelengths increased linearly with the increase of turbidity, while the laser attenuation  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Karst Cave** & **Orientation** & **Vertical** & **Horizontal** & **Actual** & **Volume (m\({}^{3}\))** \\
**Number** & **(\({}^{\circ}\))** & **Distance (m)** & **Distance (m)** & **Distance (m)** & **Volume (m\({}^{3}\))** \\ \hline
1 & 317.39 & 2.9 & 2.4 & 5.14 & 3.02 \\
2 & 42.89 & 6.5 & 5.8 & 10.09 & 3.89 \\
3 & 31.32 & 3.3 & 0.7 & 4.43 & 3.66 \\
4 & 7.67 & 2.6 & 0.8 & 2.65 & 3.84 \\
5 & 170.19 & 3.6 & 1.2 & 3.70 & 3.15 \\
6 & 90 & 0.9 & 0 & - & 3.71 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Parameters of irregular caverns.  
Figure 13: Relative positions between karst caves and the tunnel: (**a**) profile diagram; (**b**) plane graph.  
coefficients decreased with the increase of laser power. When the suspended media were CaCO\({}_{3}\) and fine sand, the attenuation of the 450 nm blue laser was the lowest; when the media were silt and clay, the attenuation of the 450 nm wavelength laser was the lowest with low cave water turbidity, and the attenuation of 650 nm wavelength laser was the lowest with high turbidity, for which 23.23 NTU and 27 NTU are the critical points of high or low turbidity, respectively.  
(3) In this paper, an optimization scheme for the maximum laser detection distance in complex karst cave water environments was proposed, and the three-dimensional point cloud acquisition method for karst cave shapes was created. These methods can realize coordinate splicing of multistation detection point clouds in complex karst caves, and can be applied for the detection of karst caves along the Jinan metro line.  
Methodology, S.S. ([PERSON]); writing--original draft preparation, L.L.; investigation, J.W.; validation, S.S. ([PERSON]); data curation, Z.F.; writing--review and editing, P.H. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Science Fund for Excellent Young Scholars (NO.51722904), the National Natural Science Foundation of China (51679131), and the Transportation Technology Program of Shandong Province, China (NO. 2019B47_1).  
The authors declare no conflict of interest.
## 5 Conclusions  
High-sensitivity and low-power GPS receiver could be an important building-block for the next-generation Internet-of-Things applications. Previous work focused on high-sensitivity GPS receivers. With the advent of the IoT, the energy consumption of GPS is an increasing concern. Most of the power is consumed in GPS acquisition engine. So, low-power acquisition engines are the main focus of GPS receivers in IoT devices.  
In general, our work is comprehensive from theory to practice in GPS acquisition. Its novelty mainly exists in ultra-low power acquisition for weak signals. Firstly, the AMCO metric of acquisition energy is proposed. Secondly, in order to reduce the acquisition energy in weak GPS signal scenarios, a novel multi-peak double-dwell acquisition method is proposed. A theoretical model was established to verify its rationality, and Monte-Carlo simulations show its high detection probability and low mean computation overhead with weak GPS signals. Finally, the VLSI architecture of coarse- and fine-grained acquisition engines suitable for the MP/DD method is proposed. The test chip was fabricated with 40 nm CMOS process, where actual energy measurements illustrate that the proposed metric AMCO can approximately characterize the acquisition energy of GPS receiver, and the acquisition engine using MP/DD method can reduce power consumption greatly for energy-constrained applications.  
In the future, there are more innovations for low-power GPS acquisition engines; for example, new acquisition methods using machine learning and analog computing for matched filter and IoT applications.  
Figure 7: Measured average acquisition energy versus carrier-to-noise ratio (CN0).  
**Acknowledgments:** This work is supported by the National Natural Science Foundation of China (Grant No. 61404028 and 61574033) and the National High Technology Research and Development Program of China (863 Program) (No. 2012 AA012703).  
**Author Contributions:** [PERSON], [PERSON] organized this work. [PERSON], [PERSON], [PERSON] performed the modeling, simulation and experimental work. The manuscript was written by [PERSON], [PERSON], [PERSON] and edited by all authors.  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 6 Discussion
### Surface Subsidence Analysis of the Mining Area
The angle \(\alpha\) in Figure 14a, which corresponds to the angle \(\theta_{1}\) in Figure 14b, representing the angle between the maximum principal stress and the horizontal line, can be calculated using the following equation. \[r=H/\tan\beta \tag{6}\]3  
where, \(L\) is the limit span of the stratum; \(h\) is the thickness of the stratum. According to the Mohr-Coulomb criterion, the angle \(\theta_{2}\) between the fracture plane and the maximum principal stress plane (\(\sigma_{1}>\sigma_{3}\)) when a rock fails along a certain direction is given by the following:  
\[r=H/\tan\beta \tag{6}\]4  
where \(\varphi\) is the internal friction angle of the rock. According to the geometric relationship shown in Figure 14b, the angle between the rock layer fracture plane and the horizontal line is the sum of the angle between the maximum principal stress and the horizontal line (\(\theta_{1}\)) and the angle between the maximum principal stress and the fracture plane (\(\theta_{2}\)). Equation (18) can be obtained as follows:  
\[r=H/\tan\beta \tag{6}\]5  
When the length of the masonry beam equals the limit span of the rock stratum, the modified equation for the angle of fracture in the probability integral method can be expressed as follows:  
\[r=H/\tan\beta \tag{6}\]6 Relationship between fracture surface and stress. (**a**) Unit stress state. (**b**) Angle between the rock fracture surface and the horizontal plane. \[r=H/\tan\beta \tag{6}\]7  
As shown in Figure 15, the surface subsidence values obtained from the experiment are similar to those calculated using the probability integral method (PIM) with fracture angle correction. The theoretical maximum surface displacement is 46.89 mm, while the experimental maximum is 45.98 mm, indicating that the modified model can effectively describe the surface subsidence behavior during room-and-pillar mining. In addition, the maximum curvature positions of the surface displacement curve obtained from the theoretical and experimental results are X = 601.65 mm and X = 541.01 mm, respectively.
## 3 Simulation Setup and Performance Evaluation  
This section shows the performance for some of the known routing protocols; QoSR, QoSAM, MQoSR, PRTR, QEMPAR, PT and MIMO. We selected these routing protocols from each different category. The reason of selecting these real-time QoS routing protocols for comparison is that they have a mobility and query-based support. The performance of the protocols is measured using Network Simulator-2 (NS2). We used a network size of 1600 m \(\times\) 1600 m.  
We assume that homogenous nodes are disseminated in a flat type network. Each node initially uses 5 J of energy. The nodes are responsible for forwarding the data to the base station. The base station is located at point (0, 500). The size of the packets is 128 bytes. The residual energy of each node after six cycles is calculated in order to prolong the network lifetime. The performance analysis of the routing protocols is made using the following assumptions.  
* A static sink node (base station) is set that is farther from the sensing field.
* Each node possesses uniform energy.
* Each node has a variable sensing capability and senses the field with variable rates and is also responsible for forwarding the data to a sink node.
* 50% of the nodes are mobile.
* Each sensor node has the same communication capacity and computing resources.
* The location of sensor nodes is determined prior to starting the simulation.  
The remaining parameters are explained in Table 1.  
Based on the simulation, we consider the following metrics for comparison.  
* Average delivery rate
* Average energy consumption
* End-to-end delay
* Lifetime
* Bandwidth Consumption
* Packet Loss
* Deadline
# Design and Evaluation of Steganographic Channels in Fifth-Generation New Radio +
## 4 Protocol Analysis and Covert Channel Design
### Analysis of Covert Storage Patterns
#### 4.2.2 Sequence (PS2)  
Pattern  
The hidden information is encoded by altering the sequence of the header fields. The header structure of PDCP is clearly specified in TS 38.323 [10]. Both the position and number of header elements are defined bit-exactly. It is not allowed to deviate from the specified header structure. Therefore, the _Sequence_ pattern as well as sub-patterns _Position (PS2a)_ and _Number of Elements (PS2b)_ are not suitable for hiding information in PDCP.
## 4 Experimental Verification
### Result of High-Speed Tactile and Vision Sensor Network System
#### 4.2.1 Experiment 1 [14]  
Figure 3(a),b illustrates the time series of the force and the ball position obtained by the tactile and the vision sensors, and the enlarged result of Figure 3(a), respectively. In the vision data, only the centroid \(C_{y}\) of the ball position is plotted because the ball is moved up and down. From the experimental result shown in Figure 4, we confirmed that the highly accurate data-acquisition synchronization in the network system was achieved successfully.  
Figure 5 depicts the time error of the data acquisition between the tactile sensor and the vision sensor. From the time error between each data acquisition shown in Figure 5, it could be suppressed to 15 us at the maximum; thus, we confirmed that the data-acquisition synchronization can also be performed successfully with sufficient accuracy.  
Figure 4: Result of Experiment 1: (**a**) shows tracking data and force data, and (**b**) shows enlarged result. Adapted from [14].
## 3 Structure of the Adaptive Controller
### Structure of the Adaptive Controller  
According to Section 2.3, the improved system identification technique using a null-space solution should adjust the weights \(w_{1}\), \(w_{2}\) and \(w_{3}\). The \(w_{1}\) and \(w_{3}\) are determined by each function that uses the motor torque as the variable. On the contrary, \(w_{2}\) is almost fixed as \(\varnothing\) is almost 0, so the relative sizes of each term of the \(N\) can be adjusted. Therefore, the \(X_{\mathrm{estimated}}\) can be derived to produce an appropriate controller for each demanded motor torque. Equations (25) and (26) are functions of each weight of the pitch axis and the roll axis.  
\[\mathrm{pitch\;axis}:w_{1}=-\frac{1.2\;T_{m}}{0.9},\;w_{2}=-\frac{\cos( \varnothing)}{2},\;w_{3}=-\frac{0.3\;T_{m}}{0.9} \tag{25}\]  
Figure 5: Gain-scheduling three-dimensional functions for the frame of the roll axis of the loading device: (**a**) I gain scheduler; (**b**) D gain scheduler.  
\[\text{oll axis}:\ w_{1}=-\frac{1.2\ T_{m}}{0.4},\ w_{2}=-\frac{cos(\varnothing)}{2},\ w_{3}=-\frac{5.3\ T_{m}}{0.4} \tag{26}\]  
The controller also includes a smoothing filter and anti-wind-up technique. The smoothing filter is intended to prevent instability due to overly sensitive parameter estimations of system identification. The anti-wind-up technique is intended to remove the accumulated error due to external force or other reasons. Figure 6 is the block diagram of the proposed adaptive control strategy.  
In summary of the proposed adaptive control strategy, the parameter estimator for system identification estimates the unknown parameter of the dynamic equation with only an IMU and an encoder of the motor. Then, the gain scheduler determines the gains of the controller using the estimated unknown parameter filtered stably by the smoothing filter. After the PID gains are determined, and the motor can control the balance of the loading device with the appropriate controller. Additionally, the anti-wind-up technique helps to remove unexpected and accumulated errors.