esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Analysis of Key Strata Failure Structure and Movement Characteristics in Shallow Coal Seam Mining  
### Characteristics of Key Strata Fracture in Shallow Coal Seam Mining  
In order to obtain the relationship between the fracture-bearing characteristics of the key strata in the working face and the surface subsidence, Longhua Coal Mine, with two key strata in the overlying strata, was selected as the research background. Taking the left side of the model as the cutting point of the working face, the research on the fracture-bearing structure of the key strata was carried out, and the fracture-bearing structure and bearing structure movement and surface subsidence characteristics of each key strata were obtained. (1) Breakage characteristics of sub-key strata  
Physical similarity simulation experiments reveal that after coal seam mining, the immediate roof layer fractures and collapses, and the overlying strata undergo flexural deformation. In the central part of the goal, the sub-key stratum experiences inverted arch-shaped subsidence. After the initial fracture of the sub-key stratum, a three-hinged arch structure is formed, with hinged points located in the upper part of the solid coal. The sub-key stratum exhibits mechanical characteristics of upper tension and lower compression in relation to the intact coal, and the distance from the solid coal is proportional to the tangent function of the fracture angle and the height of the sub-key stratum. The hinged points of the three-hinged arch structure in the sub-key stratum are situated in the collapsed rock layer, and the load-bearing strata exhibit mechanical characteristics of upper compression and lower tension from the point of fracture in the rock layers. After the periodic fracture of the sub-key stratum, the interlayer rock layers fracture upward in a layered manner, at which point the load-bearing rock strata and the interlayer rock fracture blocks jointly form the structure controlling the overlying strata movement. Due to the relatively regular fracture blocks of the key strata, a supporting structure resembling a trapezoid but effectively transmitting stress as an arch is formed, which, in this paper, is referred to as the trapezoidal hinged arch structure. This structure exerts hinged load-bearing effects on both ends of the working face and shares the load with the fractured rock mass above the load-bearing strata, controlling the movement of the overlying strata. When load-bearing structures on both ends of the working face form hinged beam structures, it is referred to as the full-trapezoidal hinged arch structure. Due to mining activities causing the fracture of the sub-key stratum, factors such as coal body support, high-strength mining, and increased free movement space make the load-bearing rock strata prone to forming stepped beam
## 2 The Proposed Hybrid Time Series Forecasting Methodology
### Seasonal Trend Decomposition Method  
[PERSON] et al. (2016) proposed the decomposition technique where a seasonal time series model is split into three components of trend, seasonal, and stochastic. Seasonal trend decomposition (STLD) uses losses to decompose the seasonal component of a time series into other three components, including seasonal, trend, and stochastic. In particular, the steps included in STLD are: first de-trending; second cyclic smoothing of a sub-sequence, which creates the sequence of each seasonal component and smooths them individually; third, the regular sub-string is smoothed by a low-pass filter, which recombines and smooths sub-strings; fourth, we clean up the season series; fifth, the seasonal component computed in the previous step is used to de-trend the original series, and sixth, the seasonal sequence smoothing is used to get the trend component. To graphically explore the performance of the STLD method described above, the decomposed sub-series are shown in Figure 1. In each sub-figure (a to d) over a year (only winter season), the top panel indicates the long-term trend (\(\mathfrak{t}_{n}\)), the seasonal component is shown in the middle panel (\(\mathfrak{b}_{n}\)), and the residual component is presented in the bottom panel (\(\mathfrak{r}_{n}\)). Hence, the STLD technique was applied to decompose (\(\mathfrak{C}_{n}\)) to properly extract the long-term trend and hourly cycle in the ozone concentration time series. Moreover, the considered decomposition method extracts the specific features in all four station ozone concentration time series very well.  
Figure 1: Cont.
## 2 Materials and Methods
### Microwave Ablation Experiments  
Ex vivo porcine liver specimens were collected from the local abattoir less than an hour after animal slaughter. The specimens were transported in a plastic bag and kept inside a cooler bag to retain moisture. Then, the porcine liver was placed in a large plastic container and kept intact. A needle was used to pierce the liver's external tough tissue to serve as a guide to insert the antenna. Depth makers were drawn on each antenna every 10 mm above length D (refer to Figure 1), and all antennas were immersed 40 mm into the tissue. Four to five antennas were pre-positioned per porcine liver, depending on the specimen size, before the ablation experiments commenced. Even though the antennas were energised one at a time, sufficient distance was maintained between them to prevent mutual interference. This study consisted of 32 ablation procedures (16 with annealed antennas and 16 with non-annealed antennas) at 50 W for a duration of 180 s. Tap water was used as a reference material to evaluate structural changes in the antenna induced by PTFE expansion. Return loss measurements were utilised as the primary metric for this evaluation. The complex permittivity of tap water was measured at 2.45 GHz (\(\epsilon_{\text{Tap}}\): 76.14-j9.99) and was found to be in good agreement with both the experimentally measured permittivity of deionised  
Figure 4: Block diagram of the microwave ablation system: (1) signal generator, (2) 52 dB amplifier, (3) \(-\)50 dB dual directional coupler, (4) antenna in biological tissue, (5) power sensors, (6) power meter, (7) thermometry system, and (8) software control and data logging.  
water (\(t_{\text{DI}}\): 77.26-j9.215) and published literature values [37]. Although small differences in permittivity exist among water types, the study concentrated on relative variations in return loss rather than absolute values, thus making tap water a valid reference medium for assessing antenna performance under mechanical deformation. This experiment was conducted by first measuring return loss with the VNA in tap water, following antenna fabrication. The VNA was calibrated prior to each measurement campaign utilising an open, short, matched standard. Considering the brief duration of the experiment, instrument drift was deemed negligible. Return loss was measured across a frequency range of 1.1 GHz to 3.8 GHz, utilising 301 measurement frequency points, with the point of salient interest being 2.45 GHz. Then, following an ablation experiment, the antenna was removed from the liver sample, thoroughly cleaned with ethanol and deionised water to remove any residues, and then re-immersed in the formerly used tap water to re-measure the return loss.
## 4 Discussion  
In this study, the results show that sand sedimentation on the railway track of the concave subgrade was the most serious, and was about 10.7 and 4.4 times (\(u_{*}=0.9701\) m/s) that of convex and flat subgrade. However, the tall length of concave wind-break wall was shorter than that of convex wind-break wall that was most of the 462.4 km wind zone railway of Lanxin Railway II. Therefore, in order to balance the influence of sand sedimentation on the whole railway track, it was necessary to take measures to reduce sand sedimentation along convex wind-break walls with the longest mileage and concave wind-break walls with serious sand sedimentation harm.  
According to the flow field and sand sedimentation, some of the sand particles were carried back to the subgrade due to the existence of the backflow vortex. Therefore, in addition to setting up sand-fixing and sand-fence measures on the windward side of wind-break walls, it might be an effective measure to optimize the structure of wind-break walls or set up corresponding measures in the leeward backflow areas to reduce the sand deposition caused by backflow.  
Along convex and flat wind-break walls, a second retaining wall at the top of slope P2 could be added in order to block the backflow of sand particles and make sand deposit behind the second retaining wall (Figure 14a,b). Because the distance between the wind-break walls and railway track is long (8.5 m) along concave wind-break walls, an inclined board could be set at a certain angle with the wind direction on top of the existing wind-break wall to make the original backflow area move backwards. A second retaining wall could then be added on top of slope P4 (Figure 14c). However, the inclined board could not be applied to convex and flat wind-break walls because the distance between the wind-break wall and railway track was short (4.5 m), and it would affect the overhead catenary system and other power supplying equipment of the high-speed train, such as the overhead contact line and cantilever structures [8; 9].  
Through this study, the distribution laws of flow field and sand sedimentation on the leeward sides of three wind-break walls under different terrains were established, and some preliminary protective measures were accordingly proposed. Further studies on protective measures of wind-break walls within different terrains, such as the angle of the inclined board and the physical parameters of the second retaining wall, are continued and will be reported in the near future.  
Figure 13: Sand particle sedimentation on the leeward sides of three wind-break walls: (**a**) convex subgrade, (**b**) flat subgrade, and (**c**) concave subgrade.
## 7 Conclusions  
In this paper, we present a multi-carrier-based adaptive modulation optimization strategy by jointly optimizing the subcarrier bandwidth, transmission power and modulation order. We propose the BCD algorithm to solve the non-convex adaptive modulation optimization problem. Furthermore, we consider the user's mobility and design the adjustment rules of the modulation schemes when the user moves. The adjustment probability is derived for the different situations. Finally, simulations are conducted, and the results show that the data rate of the jointly optimized modulation strategy is higher than that of the equal-power and water-filling strategies. The modulation adjustment probability of the user moving farther from the base station is the highest due to the varying channel and distance-dependent available bandwidth.  
**Author Contributions:** Z.H.: conceptualization, methodology, software, and writing-original draft preparation. Y.X.: conceptualization, software, and writing-review and editing. Y.D.: conceptualization, software, and writing-review and editing. Z.Z.: conceptualization, resources, writing-review and editing, supervision, project administration, and funding acquisition. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work was supported in part by National Natural Science Foundation of China (NSFC) under Grant No. 62101076, in part by National Natural Science Foundation of Sichuan Province (NSFSC) under Grant No. (2022)0920, and in part by Talent Introduction Research Startup Project under Grant No. 376157.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author/s.  
**Conflicts of Interest:** The authors declare no conflicts of interest for publishing in this journal.
## 3 Results and Discussion  
### Thermal and Curvature Data Verifications  
For the calibration of the temperature field and gradient on the test sample during the reflow process, a Cu/core bi-material specimen (with a size of 40 \(\times\) 40 \(\times\) 0.4 mm) instrumented with back-to-back thermocouples was heated separately in a commercial IR reflow oven and a conventional oven. It is noted that the reason for the use of the bi-material specimen is that this specimen deforms with one curvature (almost across the entire surface) at a given temperature load. The temperature profiles from the Cu and core surfaces, as shown in Figure 4, indicate that there is no temperature gradient across the thickness of the bi-material specimen for the reflow oven with a specimen moving  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Material** & \(E\) **(GPa)** & \(\alpha\) **(ppm/\({}^{\circ}\)C)** & \(\
u\) \\ \hline PCB & 20 & 18 & 0.28 \\ DIMM Socket & 19 & 11.3 & 0.3 \\ Solder & 49 & 20 & 0.4 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Material properties of PCB, DIMM socket, and solder used in the finite element method (FEM) simulation  
Figure 3: (**a**) Schematic drawing and (**b**) the modeling of the PCB with DIMM sockets in the finite element method (FEM) simulation.  
velocity of 0.2 m/min, but not 0.4 m/min. This temperature profile on the Cu/core bi-material specimen in an IR reflow (with a specimen moving velocity of 0.2 m/min) and in a conventional oven, as shown in Figure 5, show no temperature gradient across the thickness of the specimen in both ovens. Furthermore, this bi-material specimen with back-to-back strain gauges was heated in both ovens, and then the curvatures of the specimen, obtained from the back-to-back strain data associated with Equations (1) and (2) and the moire data with Equation (3), are shown in Figure 6 with different temperatures. The results indicate that the curvature data from the strain gauge measurement in the IR reflow oven linearly change with the temperature, and are in a good agreement with those from both the strain gauge measurements and moire measurements in the conventional oven. Therefore, it has been proved that a strain gauge measurement can be used for extracting the curvature data from the test specimen during the IR reflow process.  
Figure 4: Temperature profiles for a Cu/core bi-material specimen with a size of 40 \(\times\) 40 \(\times\) 0.4 mm (Cu 0.03 mm/core 0.37 mm in the thickness) in an IR reflow process with a conveyer velocity of 0.2 m/min and 0.4 m/min.  
Figure 5: Temperature profiles on the Cu/core bi-material specimen in an IR reflow oven (with a specimen moving velocity of 0.2 m/min) and in a conventional oven.
###### Abstract  
The quantification and estimation of the driving style are crucial to improve the safety on the road and the acceptance of drivers with level2-level3(L2-L3) intelligent vehicles. Previous studies have focused on identifying the difference in driving style between categories, without further consideration of the driving behavior frequency, duration proportion properties, and the transition properties between driving style and behaviors. In this paper, a novel methodology to characterize the driving style is proposed by using the State-Action semantic plane based on the Bayesian nonparametric approach, i.e., hierarchical Dirichlet process-hidden semi-Markov model (HDP-HSMM). This method segments the time series driving data into fragment clusters with similar characteristics and construct the State-Action semantic plane based on the statistical characteristics of the state and action layer to label and interpret the fragment clusters. This intuitively and simply visualizes the driving performance of individual drivers, while the risk index of the individual drivers can also be obtained through semantic plane. In addition, according to the joint mutual information maximization (JIMI) approach, seven transition probabilities of driving behaviors are extracted from the semantic plane and applied to identify driving styles of drivers. We found that the aggressive drivers prefer high-risk driving behaviors, and the total duration and frequency of high-risk behaviors are greater than those of cautious and normal drivers. The transition probabilities among high-risk driving behaviors are also greater compared with low-risk behaviors. Moreover, the transition probabilities can provide rich information about driving styles and can improve the classification accuracy of driving styles effectively. Our study has practical significance for the regulation of driving behavior and improvement of road safety and the development of advanced driver assistance systems (ADAS).  
driving style; driving behaviors; intelligent vehicle; State-Action semantic plane; Bayesian nonparametric approach +
Footnote †: journal: Applied Sciences
## 5 Numerical Results
### The Impact of the BS Antenna  
As we already highlighted, the time-dependent spectral efficiency is a function of the interplay between macro- and micro-mobility and antenna radiation pattern. We now proceed to investigate the impact of the latter on the considered metric.  
Figure 12 shows the time-dependent spectral efficiency as a function of the antenna radiation pattern for three arrays \(4\times 4\), \(8\times 8\), and \(15\times 15\) elements, \(x_{0}=L/2\), \(y_{0}=0\), user displacement due to macro-mobility speed of approximately 0.8 m/s, mean displacement due to micro-mobility of 2 \({}^{\circ}\)/s. By analyzing the demonstrated results, we see that, surprisingly, the BS antennas do not provide a significant impact on the time-dependent spectral efficiency. To understand the rationale for this behavior, we also need an illustration of the time-dependent antenna gain, \(G_{A}\), for considered BS antenna arrays shown in Figure 13. Here, we see that as time goes on, there is a significant drop in the antenna gain caused by misalignment, reducing it to the averaged values of around 25 dBi at equilibrium. Meanwhile, the drop is rather large compared to the perfectly aligned antennas. However, for the practical dimensions of the 5G/6G mmWave/sub-THz systems' coverage considered in this paper (up to 200 m), this leads to rather high mean spectral efficiency at the expected distance from the BS. Thus, the additional gain caused by perfect antenna alignment does not contribute significantly to the spectral efficiency due to the use of the slowly increasing logarithmic function. As a result, we see no principal difference between different BS antenna arrays in Figure 12. We specifically note that for simplified antenna models utilized in, e.g., [13] that capture only the antenna gain over the HPBW assuming that there is no side and back lobes, the difference would be much more drastic. Therefore, the use of realistic antenna radiation patterns is critical for an accurate time-dependent spectral efficiency model.  
Figure 11: Spectral efficiency as a function of macro-mobility. (**a**) Macro-mobility. (**b**) Mean distance to the BS.  
Figure 12: Spectral efficiency as a function of antenna pattern at the BS. (**a**) Within 60 s. (**b**) Within 20 s.  
We also observe the second effect in Figure 12--antenna arrays having more elements, e.g., 15 \(\times\) 15, are characterized by higher fluctuations. The rationale is that arrays with higher antenna elements are characterized by more pronounced side and back lobes as well as nulls. We see that it directly translates to the attained spectral efficiency.
## 3 Results and Discussion
### Terawatt-Attosecond Soft X-ray Pulse Generation Tables and Schemes
Figure 8: (**a**) Stepwise tapering in the undulator parameter K for the attosecond-TW XFEL in soft X-ray region, and (**b**) variation of the electron beam energy spread along the undulator. Figure 9: (**a**) The average radiation power for 10 different random seeds along the uniform undulator (black line) and along the tapered undulator (red line) in the soft X-ray case, and (**b**) the power spectra for the uniform undulator (black line) and for the tapered undulator (red line). The realization of X-ray delay is important in this scheme. A soft X-ray mirror typically suffers from transmission losses while hard X-ray Bragg reflectors are only narrow-band, which cannot be applied to this scheme due to the broad-band nature of the radiation spikes [42]. Hence, the design of an X-ray delay unit using grazing incidence geometry has been discussed in detail in [32]. According to [32], a chicane-mirror system using mirrors with a length of 5-6 cm and a deflection angle of 0.1\({}^{\circ}\) in grazing incidence geometry would be suitable for obtaining the required optical delay. A similar X-ray delay unit would also be applicable in soft X-ray cases. Moreover, the mirror stages with a 10 nm resolution are commercially available. Therefore, the delay can be controlled with a high degree of precision. For meaningful pump-probe experiments at the XFEL end stations, the synchronization of the X-ray pulse and optical laser has to be sustained over the full legpath of the experimental configuration including the delay chicanes and other transport optics. Therefore, it is required that all electron beam and optical components are placed onto the same support system. The mechanical vibration leads to the instability in optical path lengths. However, using a feedback loop [43], such an instability can be suppressed and the time delay between pump and probe pulses can be controlled within 20 as RMS. Optical transport of ultrashort pulses generated by optical laser from its optical table to the experimental stations, which are \(\sim\)100 m away, requires ultra-high vacuum transport system. [PERSON] et al. [44] and [PERSON] et al. [45] have demonstrated that a carefully designed laser beam transport, including a free space propagation of 150 m and a number of beam folding mirrors allows one to keep the timing fluctuations to less than 4 femtoseconds RMS.
## 2 Literature Review
### Process-Induced Defects and Microstructural Characterization  
#### 2.2.1 Resin Curing Shrinkage and Microvoid Formation  
Curing shrinkage and the subsequent formation of microvoids remain significant challenges in optimizing 3D-printed photopolymer systems. The polymerization process often leads to dimensional inaccuracies, which can be attributed to the volumetric changes that occur when transitioning from a liquid to a solid state [16; 29]. The introduction of advanced materials, such as modified epoxy-acrylate resins, has shown promise in mitigating the effects of these volumetric changes. Research by [PERSON] et al. [16; 30] substantiates this by demonstrating that modifications can result in decreased curing shrinkage and reduced internal stresses, thus elevating the operational reliability of printed objects.  
Furthermore, detailed studies using micro-computed tomography (micro-CT) and scanning electron microscopy (SEM) have been pivotal in characterizing these microstructural defects. These methodologies facilitate an insightful analysis of void distributions and microstructural anomalies, which are critical to understanding the integrity of printed components [27; 31]. For example, recent advancements in utilizing micro-CT technologies enable non-destructive examinations that reveal internal flaws, informing design and process adjustments in real time [32; 33].