esa-sceva/satcom-chunk-collection huggingface dataset:
# Applications of Microseismic Monitoring Technique in Coal Mines: A State-of-the-Art Review
## 6 Conclusions  
Deep coal mining-induced disasters, e.g., rockbursts, water inrush, coal and gas outbursts, and roof-fall accidents, seriously threaten the safety of miners, equipment, and underground structures. The study of the coal/rock fracturing process plays a pivotal role in the prediction and control of mining-induced disasters. The microseismic monitoring technique is commonly used for the assessment of coal/rock instabilities and safety management in many Chinese coal mines. This study reviews the achievements, development, and applications of the microseismic monitoring technique in coal mines, and certain conclusions are drawn:  
1. The microseismic monitoring technique is capable of capturing coal/rock fractures at different scales, which is challenging for the traditional stress and deformation monitoring methods. Microseismicities contain abundant coal/rock fracturing information, and the quantitative interpretation of mining-induced microseismicities contributes to studying the generation process of disasters in coal mines. Furthermore, the microseismic monitoring technique is effective for the assessment of coal/rock instabilities and early warning of disasters.
2. Some source parameters and statistical parameters of microseismicities are effective and sensitive in evaluating the stress regime and characterizing the damage of surrounding rocks. These microseismic parameters can be used in conjunction with other monitoring methods, e.g., laser scanning and electromagnetic radiation, which are meaningful for the mitigation and control of mining-induced disasters.
3. Though fruitful achievements have been made in coal mines using the microseismic monitoring technique, there are certain problems to be addressed. To better monitor, warn, and control the disasters in deep coal mines, future research should focus on a precise microseismic source location method, an efficient and intelligent data processing method, a comprehensive assessment method for mining-induced instabilities, and the development of new microseismic equipment.  
Conceptualization, F.L. and Y.W.; methodology, F.L., Y.W. and M.K.; investigation, M.K. and C.L.; writing--original draft preparation, F.L.; writing--review and editing, Y.W., M.K. and C.L.; supervision, Y.W.; funding acquisition, Y.W. and F.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Open Fund of the State Key Laboratory of Water Resource Protection and Utilization in Coal Mining (Grant No. GJNY-21-41-04) and the Shandong Provincial Natural Science Foundation (Grant No. ZR2022 QD102).  
Not applicable.
## 5 Discussion  
### Comparison of Different Sample Representation Forms  
Machine learning is a typical data-driven approach. Different sample representation forms imply different data structures; thus, exploratory studies of sample representation forms are quite crucial. This study provided a comprehensive comparative study of three sample representation forms for DFSM: single grid, multi-grid, and watershed unit. The results show that the predictive ability of the conditioning factors, the performance of the machine learning models, and the quality of the debris flow susceptibility maps are all significantly affected by the sample representation forms. It is difficult to say which sample representation form is optimal, but the advantages and disadvantages of each form are fairly obvious. For the single-grid form, the advantages of easy collection and processing are obvious. However, a single grid usually describes the localized characterization of a debris flow event, which might be different from the overall characterization [11]. For the multi-grid form, the introduction of more grids better characterized the overall debris flow event, but also greatly expanded the sample size. A larger sample size means a higher computational cost and a higher chance of introducing some flawed data, which affects the model's performance [32]. As for the watershed unit, this sample representation form allows for a better overall characterization of debris flow events with fewer samples [17]. Moreover, combined with a suitable negative-sample acquisition strategy, watershed units have the potential to provide the most predictive conditioning factors, the best performing models, and the most plausible debris flow susceptibility maps. On the other hand, the shortcomings of watershed units are mainly due to their more time-consuming acquisition and adjustment processes.  
To summarize, the purpose of DFSM is to produce high-quality debris flow susceptibility maps. In this regard, the watershed unit demonstrated a major advantage in the present study. On the other hand, the overall performance of the single-grid datasets is largely satisfactory, which is suitable for scenarios that require a rapid evaluation.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Sample Representation Form** & **Susceptibility** & **Percentage** & \
\begin{tabular}{c} **No. of Debris Flow** \\ **Samples** \\ \end{tabular} &
\begin{tabular}{c} **Percentage of Debris** \\ **Flow Samples (\%)** \\ \end{tabular} \\ \hline \multirow{4}{*}{Watershed unit} & Low & 31.0 & 3 & 1.9 \\  & Moderate & 13.2 & 5 & 3.3 \\  & High & 20.1 & 34 & 21.9 \\  & Very high & 35.7 & 113 & 72.9 \\ \hline \hline \end{tabular}
\end{table}
Table 4: _Cont._  
Figure 8: Debris flow susceptibility maps based on the optimal models of (**a**) the single grid dataset; (**b**) multi-grid dataset; (**c**) watershed unit dataset.
# A Single-Phase Lightweight Double-Leaf Multi-Stage Acoustic Black Hole Model of Metamaterial
## 1 Introduction
Unit cells of multi-stage metamaterials typically comprise several resonators, which can generate multiple bandgaps, reduce the bandgap width, and widen it [22]. [PERSON] investigated the multi-stage spring-mass model and discovered that adjusting the structural parameters of the resonator can generate bandgaps in various frequency ranges [23]. [PERSON] proposed a two-dimensional multi-stage Hilbert fractal metamaterial. The unit cell internal resonator has similar properties that can stimulate multiple resonances, resulting in a bandgap broadened to 225-1175 Hz [24]. [PERSON] proposed a one-dimensional multi-stage metamaterial shaft that achieves low-frequency bandgap broadening while reducing weight compared to a single-stage metamaterial shaft [25]. [PERSON] conducted a study on three-dimensional discretised multi-stage metamaterial energy band structures. The results showed that increasing stages of the structure can result in an increase in the quantity of unit cell degrees of freedom, which in turn results in a wider band gap [26]. This paper proposes a single-phase double-leaf multi-stage acoustic black hole (SDM-ABH) metamaterial with low-frequency ultra-wide bandgap properties and light weight. The unit cell consists of multiple sub-ABH structures arranged in a multi-stage gradient arrangement. The structure of the paper is as follows: Part II investigates an SDM-ABH metamaterial model and a method for calculating the complex energy bands. Part III calculates the complex energy band structure, eigenmodes, and vibrational displacement response of SDM-ABH metamaterials. It also discusses the mechanism of the strong attenuation of the low-frequency broadband generation. Part IV investigates the effect of parameters of structure on the band gap mechanism. Part V discusses the effect of stages on the trap region. The paper concludes with a summary of the findings.
# Study of Load Calculation Models for Anti-Sliding Short Piles Using Finite Difference Method
###### Abstract  
Anti-sliding short piles, a novel technique for slope stabilization, have been applied in engineering practices. Nonetheless, a mature structural calculation theory for these piles is still lacking. In this paper, the study presents an internal force solution model for anti-sliding short piles using the finite difference method. By extending the Euler-Bernoulli beam theory and defining boundary conditions, this study develops a set of finite difference equations for computing the structural forces of anti-sliding short piles. Furthermore, this study conducted laboratory model tests on soil landslide cases reinforced with anti-sliding short piles. By comparing the internal forces and deformations of these piles, the test validates the proposed calculation model for anti-sliding short piles. The results suggest that treating the load-bearing and embedded sections as a unified entity during the calculation process, instead of applying continuity conditions separately at the sliding surface as performed in traditional methods, simplifies the complex solving procedure. Moreover, under identical loading conditions, the displacement, bending moment, and shear force data obtained through the finite difference method closely coincide with the measurements from the model tests, confirming the reliability of the anti-sliding short pile calculation model. Additionally, this study demonstrates that reducing the spacing between nodes along the entire anti-sliding short pile, i.e., decreasing the value of the differential segment length \"_h_\", results in more precise computational outcomes. This research offers valuable insights and references for sustainable solutions in the realm of geological disaster prevention and control.  
anti-slip short pile; finite difference method; force calculation model; model test +
Footnote †: journal: Applied Sciences
## 3 Results
### XPS Analysis  
#### 3.5.1 Analysis of the Ti2p and O1s Core-Level Spectra  
X-ray photoelectron spectroscopy (XPS) was performed to study the charge states of the elements on the surface. According to the XPS data (Figure 11), the state of titanium in all samples is characterized by a single doublet with a binding energy value E\({}_{\text{b}}\)(Ti2p\({}_{3/2}\)) = 458.6 eV, which, according to literature data [35], corresponds to Ti\({}^{4+}\) in titanium dioxide. The half-width of the titanium line does not change significantly and amounts to 1.6 eV for the Ti2p\({}_{3/2}\) component and 2.4 eV for Tip\({}_{1/2}\). The phase transition between rutile and anatase does not lead to a change in the charge state of titanium, and no change in the position and shape of the Ti2p core line can be observed.  
The spectral region of oxygen O1s contains two main lines at E\({}_{\text{b}}\) (O1s) = 529.9 and 531.7 eV (Figure 11,d) which correspond to oxygen in the lattice of titanium oxide and oxygen on the surface defects, respectively [29]. In case of the Pt/Ti-P25-800 sample oxygen is represented by three states. However, it should be taken into account that in this sample a large amount of carbon impurities is present on the surface (Table 3), some of which are related to the oxygen-containing CO\({}_{\text{x}}\) groups. The adsorption of hydrocarbon (HC) impurities on the surfaces is well known, e.g., due to back diffusion from the pumps. In fact, this HC is often used as an internal standard for XP spectra calibration. The increase in calcination temperature does not lead to carbon burning, proving that it is not an internal part of the samples. It should be considered as inert impurities on the surface, not affecting catalytic properties. From the presented Ti2p and O1s spectra, the O/Ti atomic ratios (Table 3) were calculated with the contribution of the lattice oxygen (O\({}_{\text{lat}}\)) and the surface oxygen groups (O\({}_{\text{ads}}\)) of the OH and CO\({}_{\text{x}}\) type (E\({}_{\text{b}}\) = 531.5-531.7 eV). The O\({}_{\text{ads}}\)/O\({}_{\text{lat}}\) ratio is lower for the Pt/Ti-PLA catalysts than for the Pt/Ti-P25 catalyst series. This ratio can be considered as an indirect indication of a different number of surface defects due to a different titania synthesis route.  
Figure 6: (**a**) Ex situ XANES and (**b**) Fourier transformed (FT) k\({}^{2}\)-weighted EXAFS (uncorrected for the phase shift) spectra of **Pt/Ti-PLA** and **Pt/Ti-P25** samples, and data for _PtO\({}_{2}\)_ and metallic _Pt_ reference samples. The EXAFS is Fourier-transformed in the k-range of: 2.5–11.0 Å\({}^{-1}\).
## 3 Results and Discussion
### Raman Spectroscopy  
The rust compositions for conventional rebar and DP rebar were determined using Raman spectroscopy. The main products were oxyhydroxides or iron oxides, which represent the corrosion products of conventional rebar used for reinforcing construction cement. The composition of rust is iron (Fe) and iron oxide (Fe\({}_{3}\)O\({}_{4}\)). Low oxygen availability and the restricting concrete surrounding are the main reasons for Fe\({}_{3}\)O\({}_{4}\) formation. Iron chloride (FeCl\({}_{2}\)) is generated because of the chloride augmented layer. The comparatively low-intensity peaks of FeCl\({}_{2}\) might be due to the thin FeCl\({}_{2}\) layer. In some regions, the Fe\({}_{3}\)O\({}_{4}\), \(\gamma\)-FeOOH, and \(\alpha\)-FeOOH formation indicates more oxidation, which might contribute to the cracking characteristics of the rust formed. There is a greater probability of \(\gamma\)-Fe\({}_{2}\)O\({}_{3}\) formation because of additional crystallization and dehydration at higher oxygen levels in external areas.  
Raman spectroscopy helps in determining the composition of steel surfaces and hence corrosion behavior. Figure 11 shows in situ Raman spectra for reinforcing steel submerged in SCPS (saturated Ca(OH)\({}_{2}\) solution) with and without NaCl. The wide peak close to 1650 cm\({}^{-1}\) clearly showed the bending vibration of H\({}_{2}\)O in SCPS [44]. In addition, the peaks at 277 and 713 cm\({}^{-1}\) belonged to \(\gamma\)-Fe\({}_{2}\)O\({}_{3}\) and \(\alpha\)-Fe\({}_{2}\)O\({}_{3}\), respectively [45; 46]. Steel can maintain passivity in chloride-free SCPS. In addition, the oxide or passive layer deposition (restoration) and dissolution occur all together in dynamic steadiness on the steel surface [47].  
In this study, oxide or passive layer dissolution formed Fe\({}^{2+}\) at the SCPS-steel interface, indicating that in chloride-free SCPS, there is no reaction because of the absence of Fe\({}^{2+}\), while in SCPS containing chloride, more Fe\({}^{2+}\) ions are produced to react with SCPS for the same duration.  
For conventional rebar, the Fe\({}_{2}\)O\({}_{3}\) Raman spectrum became more intense, displaying acceleration or oxide or passive film dissolution because of the chloride effect, confirmed by electrochemical studies. The low-intensity peaks at 722 and 282 cm\({}^{-1}\) showed \(\gamma\)-Fe\({}_{2}\)O\({}_{3}\) and \(\alpha\)-Fe\({}_{2}\)O\({}_{3}\), respectively (Figure 12) [48; 49]. Subsequently, \(\gamma\)-Fe\({}_{2}\)O\({}_{3}\) and \(\alpha\)-Fe\({}_{2}\)O\({}_{3}\) could be measured, compared to chloride-free SCPS, and were identified to be constituting the upper surface layer of steel [50; 51].
## 3 LPBF Sensing Techniques
### Optical Techniques
#### 3.1.1 Techniques with Electron Source
**Electron probe micro-analyzer (EPMA)** works like SEMs, bombarding parts with an electron beam and emitting X-rays at wavelengths characteristic of the analyzed elements. However, EPMAs are equipped with various crystal spectrometers that enable quantitative chemical analysis at high sensitivity. The advantages of EPMA analysis are that it is considered superior to EDS analysis and is non-destructive to the sample. The disadvantages of EPMA include complex sample preparation into polished and flat sections, overlapping peak positions hinting at inaccurate readings, and the inability of various valence states to differentiate. Figure 19 shows how EPMA can be used to analyze LPBF micro-cracking [46]. Figure 19: Example of EPMA imagery provided by [46], highlighting a micro-crack observed in a cross-section of a GH3536 superalloy LPBF-printed part along with element distribution of the scale. Figure 18: Example of XPS survey spectra provided by [45] for an AlSi10 Mg LPBF-printed part at (**a**) the free surface and (**b**) an etch depth of 4 nm.
## 2 Related Work
[29] proposed a Soft Label Mask Optimization (SLMO) network, in which a pixel shuffling module was introduced to replace the traditional upsampling module, and used an ice-covered transmission line dataset collected by a drone to segment the ice-covered area. The currently popular deep learning models are not suitable for edge computing devices. The computing power of edge devices is weak and cannot support the computing requirements of these models, so the models need to be lightweight. Currently, common lightweight models include MobileNet [30], ShuffleNet [31], SqueezeNet [32], etc. [PERSON] et al. [33] proposed a lightweight framework for accurately segmenting road cracks, achieving real-time processing capability. CamoFocus [34] introduces feature segmentation and modulation modules, as well as context refinement modules, to improve the performance of camouflage object detection. In addition, there are also lightweight networks designed for image segmentation, such as ENet [35], DABNet [36], etc. [PERSON] et al. [37] proposed a compression model for ice-thickness recognition. They extracted image features through a lightweight MobileNet and then used channel pruning to compress the model, making it suitable for end-side deployment. [PERSON] et al. [38] proposed an ice detection method suitable for edge devices. They used Ascend 310 to perform recognition model inference, classified the ice thickness into different levels, and determined the severity of the ice. These models do not optimize the design for the ice-covered transmission lines. This paper not only takes lightweight design into account, but also takes into account the high-precision ice segmentation effect.
# Design of Chaotic Interleaver Based on Duffing Map for Turbo Code
## 4 Empirical Tests in Software
### Test Results
The comparison in Figure 8 shows that for a 64-bit length and an SNR of 2 dB, the BER of the random interleaver reaches the value of \(1.4311\times 10^{-4}\), the result of the S-random interleaver is a BER of \(1.0408\times 10^{-4}\), and of the Lozi chaotic interleaver is a BER of \(2.6020\times 10^{-4}\). These three cases exhibit good performance. The result of the QPP  
Figure 8: BER \(\mathrm{v}/\mathrm{s}\)\(E_{\mathrm{b}}/N_{0}\) comparison for 64 bits. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Interleaver** & **0 dB** & **0.5 dB** & **1 dB** & **1.5 dB** & **2 dB** & **2.5 dB** & **3 dB** \\ \hline Random & 0.1056 & 0.0640 & 0.0325 & 0.0158 & 0.0059 & 0.0015 & \(1.4311\times 10^{-4}\) \\ Very Poor & Very Poor & Very Poor & Very Poor & Very Poor & Very Poor & Very Poor & Good \\ \hline S-random & 0.1018 & 0.0653 & 0.0301 & 0.0110 & 0.0032 & \(5.0739\times 10^{-4}\) & \(1.0408\times 10^{-4}\) \\ Very Poor & Very Poor & Very Poor & Very Poor & Very Poor & Very Poor & Safistactory & Good \\ \hline QPP & 0.1069 & 0.0685 & 0.0336 & 0.0136 & 0.0044 & \(7.4157\times 10^{-4}\) & \(7.8060\times 10^{-5}\) \\ Very Poor & Very Poor & Very Poor & Very Poor & Very Poor & Very Poor & Safistactory & Excellent \\ \hline Chaotic & 0.1066 & 0.0671 & 0.0323 & 0.0136 & 0.0043 & 0.0011 & \(2.6020\times 10^{-4}\) \\ Lozi map & Very Poor & Very Poor & Very Poor & Very Poor & Very Poor & Very Poor & Good \\ \hline Chaotic & 0.1030 & 0.0634 & 0.0328 & 0.0138 & 0.0037 & \(8.7167\times 10^{-4}\) & \(5.2040\times 10^{-5}\) \\ Duffing & Very Poor & Very Poor & Very Poor & Very Poor & Very Poor & Poor & Excellent \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Comparison of BER for the performance of the 64-bit turbo code. interleaver is a BER of \(7.8060\times 10^{-5}\), and that of the proposed chaotic interleaver reached \(5.2040\times 10^{-5}\). This is an excellent performance for both interleavers.
# A Finite Element Investigation into the Effect of Slope of Grain on Wood Baseball Bat Durability
## 1 Introduction
To explore if and how a further tightening of the allowable SoG could improve upon the MPF rate, the durability of sets of bats sorted by SoG, e.g., sorted into four SoG groupings, specifically (1) \(|\)SoG\(|\leq 1^{\circ}\), (2) \(1^{\circ}<|\)SoG\(|\leq 2^{\circ}\), (3) \(2^{\circ}<|\)SoG\(|\leq 3^{\circ}\), and (4) \(|\)SoG\(|>3^{\circ}\), could be tested in the lab. However, such an approach would be difficult due to the inherent variability of wood and the lack of control over the factors unrelated to SoG, such as density or the ultimate strength of the wood, thereby making it challenging to draw conclusive trends. In addition, it would also be expensive with respect to the large number of bats that would need to be explored for such a study, as well as the time required to characterize the durability of all bats in the study and subsequent examination of all bat failures. An alternative and cost-effective approach is to use the finite element method to investigate how the failure mode changes as a function of SoG for a range of representative on-field relative bat/ball speeds and impact locations [6; 7; 8]. In the current paper, a popular bat profile is used in a parametric study to investigate the relationship between SoG and bat durability. During a game, the relative bat/ball impact velocity can range from 90-180 mph (145-290 kph) and is a consequence of the combination of the pitch speed, swing speed, and impact location along the length of the bat. For the purposes of this paper, bat durability is defined as the relative bat/ball speed that results in bat breakage, i.e., the higher the speed required to initiate bat cracking, the better the durability. The finite element models of this bat profile are analyzed using LS-DYNA where the variables in the parametric study include (1) SoG--ranging between \(\pm\)10\({}^{\circ}\), (2) Wood species--Ash, Maple, and Yellow Birch, (3) two impact locations--2.0 in. (5.1 cm) and 14.0 in. (35.6 cm) as measured from the tip of the barrel, and (4) relative bat/ball impact speeds between 90 and 180 mph (145-290 kph). This paper presents the first comprehensive numerical investigation into the relationship between SoG and bat durability. Prior to this numerical study, limited empirical data from bats broken during games and in-laboratory studies where SoG was not a controlled variable were available to imply a qualitative relationship between SoG and bat durability. The results of this study can serve as the basis for developing future parametric studies using finite element modeling to explore a large set of bat profiles and thereby to develop a deep fundamental understanding of the relationship among bat profile, wood species, wood SoG, wood density, and on-field durability.