esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Feature Reduction and Main Clustering  
In order to cope with the high dimensionality of the input light spectra, suitable dimension reduction algorithms need to be applied first to find a computationally manageable representation of their most relevant features in a lower dimensional latent space that is adequate to perform the main clustering. Figure 3 summarizes the corresponding algorithmic pipeline.  
The first three steps of the depicted cluster approach take into account the local connectivity of the input data space. A convolutional autoencoder (conv. autoencoder) will reduce the dimension (dim.) to 15, which represents a trade-off between accuracy and a maximal reduction of the feature vector. The corresponding features will then be ranked by the Laplacian Score [40] and the less important upper half will be truncated. The remaining dimensions are further reduced and transformed to a two-dimensional representation using the uniform manifold approximation and projection (UMAP) [41] algorithm. As the distance between vectors within this maximally reduced space is no longer meaningful, the choice of clustering algorithms suitable for this kind of data is limited to density-based approaches that do not rely on the distance between individual data. Due to its robustness against noise, the hierarchical density-based spatial clustering of applications with noise (HDBSCAN) [42] algorithm has been chosen for this work. Further details on each of these algorithms will be given in the following sections.
# A Simple Estimation Method of Weibull Modulus and Verification with Strength Data
## 3 Weibull Moduli of Five Metal Alloys  
ASTM Committee E28 on Mechanical Testing conducted an interlaboratory study on automated ball indentation testing, which included controlled tests of the tensile strength of four alloys, Al 6061-T651, Al 7075-T651, steel 1018, and steel 4142 [24]. The tensile strength datasets of 30 samples each were analyzed for this study to determine the Weibull modulus values for these common metal alloys. The bias of individual laboratory results was corrected based on the average deviation with global average for four alloys. The method discussed in Section 1 was used to obtain the m\({}_{\text{obs}}\) values from the Weibull plots. The scale parameter, \(\sigma_{\text{o}}\), was obtained using Equation (2). Weibull plots for the four alloys are shown in Figure 1, and m\({}_{\text{obs}}\) values of 124.0, 91.4, 73.8, and 78.1 were obtained as noted in the figure. Separately, the corresponding m\({}_{\text{est}}\) values were estimated from the values of \(<\)\(\sigma\)\(>\) and S using m = 1.1\(<\)\(\sigma\)\(>\)/S, yielding 124.9, 91.9, 73.3, and 77.8. The two sets matched well within \(\pm\) 1%. Another interlaboratory study under strict test protocol was conducted in Europe [25]. It produced a special ingot, from which 200 bars of Nimonic\({}^{\circledR}\) 75 Ni-base alloy (Special Metals Corp, Huntington, WV, USA) were fabricated. The tensile strength data from 18 bars of this Nimonic\({}^{\circledR}\) 75 alloy [25] was analyzed for the Weibull modulus, and m = 125.3 was obtained, as shown in Figure 1. The corresponding m\({}_{\text{est}}\) value was 129.7, matching to +3%. Thus, the commonly cited value for wrought metal alloys (m \(>\)100) is reasonable for these Al and Ni alloys, but appears \(\sim\)25% too high for ductile steels. More than 20 m values above 50 are included in the metals data below, but some, including pure copper, were below an m value of 20. More comprehensive testing is needed to better define the ranges of m values for various material types beyond those surveyed in this work.  
Figure 1: Weibull plots of the tensile strength of five structural alloys: Al 7075-T651 (in blue symbols), Al 6061-T651 (in purple), steel 1018 (in red), steel 4142 (in green), and Nimonic\({}^{\circledR}\) 75 Ni alloy (in brown). Data from [24; 25]. Values of m are shown. The horizontal axis is shifted to avoid overlaps.
# Comparison of Analytical Methods for Determining Methylesterification and Acetylation of Pectin
## 3 Results and Discussion
### Determination of DM by Titration  
The DM values of CP, CP-HG and CP-HM-HG were determined by using the titration method. The volumes of NaOH consumed during the titration of different samples are listed in Table 1. According to Equation (1) in Section 2.4, the DM of CP-HG was 0.0%, consistent with results from alkali de-esterification. The DM content of CP-HM-HG was calculated to be 88.0%, suggesting that it is a high methyl-esterified HG. Acetyl groups were not present in CP-HG and CP-HM-HG due to alkali saponification. The DM content of CP was determined to be 47.0%, and this was further analyzed by using other methods.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Pectin** & **V1 (mL)** & **V2 (mL)** & **DM (\%)** \\ \hline CP & 12.7 \(\pm\) 0.12 & 11.3 \(\pm\) 0.20 & 47.0 \(\pm\) 0.63 \\ CP-HG & 26.3 \(\pm\) 0.32 & 0.0 \(\pm\) 0.01 & 0.0 \(\pm\) 0.01 \\ CP-HM-HG & 3.3 \(\pm\) 0.15 & 24.3 \(\pm\) 0.24 & 88.0 \(\pm\) 0.59 \\ \hline \hline \end{tabular} The results are shown with the associated standard error of means (\(\pm\) SEM) of triplicate values from the average. V1 represents the content of GalA without esterification, V2 represents for the content of GalA esterification.  
\end{table}
Table 1: The titration of V1, V2 and the determination of DM for three pectins.  
Figure 1: Monosaccharide composition of CP, CP-HG and CP-HM-HG.
## 2 Materials and Methods
A fraction of the probe beam (not spectrally filtered) is sent to the other channel of the balanced detector; this arrangement allows the reduction of the signal noise due to pulse-to-pulse and beam pointing fluctuations, and, by careful adjustment of the beam intensities using neutral density filters, to have a null DC baseline output in the absence of spectral shifts. The signal from the balanced detector is amplified (Femto DLPVA-100-B-S) and then digitalized by a low-cost USB ADC (USB1608 GX, Measurement Computing Corp., Norton, MA, USA) triggered by the laser cavity dumper electronics so that the signal is measured for each laser pulse. The ADC is controlled by a LabView program which measures and averages the signal as a function of time for a pre-set number of the scanning delay cycles in phase with the delay modulation so that for each cycle, two sets of delay-dependent signal points are measured, corresponding to the back-and-forth movement of the actuator. Raw data were processed by averaging the two measurements and calibrating the time to obtain the true delay time. Since in this setup we do not employ a system for online real-time measurement of the pump-probe delay, in order to transform the signal measurement time into a calibrated delay scale, we used the signal of a standard CH\({}_{2}\)Br\({}_{2}\) sample which shows weakly damped, equally spaced oscillations with a period of 193 fs corresponding to the known Raman resonance at 173 cm\({}^{-1}\) due to the Br-C-Br bending mode [29]. In this way, we were able to calibrate the pump-probe delay up to more than 12 ps, accounting also for small nonlinearities of the delay actuator movement.
# Many-Body Effects in FeN\({}_{4}\) Center Embedded in Graphene
## 4 Results
The differences between DMRG and DFT reflected the effects of: (i) approximations inherent within the DFT, (ii) the parameters used in our DMRG modeling based on the DFT results, and (iii) the fact that we ignored Coulomb interactions between iron and nitrogen, as well as other parts of the defect complex even though these interactions were to some extent accounted for by the effective hopping parameters. As expected, the inclusion of interactions led to modifications in the partial density of states. It was clear that the \(U^{\prime}\) terms shifted the energies slightly upward, with the exception of the \(d_{xy}\) orbital, which was practically unchanged. Note however that the value of \(U\) was reduced substantially, from \(U=4.0\) to \(U=2.6\), indicating the importance of interaction terms. The \(d_{z^{2}}\) orbital was also affected greatly as seen from the splitting between the related peaks in Figure 7, which was controlled by \(U\), while its relative position with respect to other orbitals was dictated by \(U^{\prime}\) and \(J\). These results indicated that interaction effects would induce substantial changes in the binding energies of ligands, which normally involved the \(d_{z^{2}}\) orbital. We also extended our modeling to include more carbon atoms in order to gain insight into the effects of embedding our defect center in a \"bulk-like\" flake of graphene. Here, our calculations included all interaction terms. As shown in Figure 9, for certain values of \(U\), the spin actually increased compared to the molecular case. An intermediate \(S=3/2\) phase, which was not found before, appeared around \(U\approx 2.6\) eV, indicating that the surrounding material played a significant role in the physics of the defect center: a continuous density of states in bulk graphene compared to discrete \"delta\"-like peaks in the molecular case may allow for additional screening in the spirit of the Kondo effect. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{2}{c}{**DFT+U**} & \multicolumn{2}{c}{\(\mathbf{U^{\prime}=0}\)} & \multicolumn{2}{c}{**Full H**} \\ \hline
**Orbital** & \(\langle N\rangle\) & \(\langle S^{z}\rangle\) & \(\langle N\rangle\) & \(\langle S^{z}\rangle\) & \(\langle N\rangle\) & \(\langle S^{z}\rangle\) \\ \hline \(xy\) & 1.79 & 0.05 & 2.00 & 0.00 & 2.00 & 0.00 \\ \(z^{2}\) & 1.07 & 0.40 & 1.00 & 0.50 & 1.0 & 0.50 \\ \(x^{2}-y^{2}\) & 0.83 & 0.04 & 0.77 & 0.04 & 0.53 & 0.03 \\ \(\pi\) & 1.35 & 0.26 & 1.26 & 0.27 & 1.11 & 0.26 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Occupations and magnetic moments of various iron orbitals. The first two columns are results from DFT+U calculations. The next three columns are obtained from the method described in the text with \(U^{\prime}=0\), while the last three columns refer to calculations in which all inter-orbital interactions are included.
# Stability Evaluation of TBM Pilot Tunnels to Rear Blasting Using the Protection Shield
## 1 Introduction  
Recently, underground space development has attracted increased interest. In particular, developments in tunnel excavation technology have enabled more economical and rational planning of tunnels. Studies have investigated the stability and economic feasibility of tunnel excavation. Initially, tunnel excavation was widely performed using a small sectionally divided excavation method with considerable manpower and small equipment. In more recent years, advancements have been made in mechanized construction, including tunnel boring machines (TBM) and ground reinforcement technology, and excavation methods that are advantageous in terms of economic feasibility and constructability have been developed.  
The simultaneous excavation method, which uses a TBM pilot and New Austrian tunneling method (NATM) enlargement, involves excavating a pilot tunnel with a small-diameter TBM before excavating the full face of the tunnel without producing large disturbances in the surrounding rock mass. Therefore, there are advantages to investigating, analyzing, and evaluating the ground conditions in advance before performing the main NATM enlargement excavation; simultaneously, the blasting vibration greatly reduces because the center-cut blasting that produces a large vibration can be avoided (Figure 1). In addition, economic efficiency increases because the construction period is shortenedby appropriately controlling the pre-excavation and using a TBM with a high excavation speed and enlargement blasting/excavation stages.  
However, the required separation distance between the NATM blasting point and TBM, as well as the minimization of the effect on the TBM during the simultaneous excavation of the TBM pilot and NATM enlargement, remain understudied issues. Therefore, this study used a 3D numerical analysis to predict the effect of NATM enlargement blasting on the TBM pilot tunnel with the use of a protection shield in the middle of the TBM and NATM enlargement blasting points. Further, we aimed to shorten the construction period and improve construction safety by presenting the minimum required distance between the NATM enlargement blasting point and the protection shield.
# High Performance GaSb-Based DBR Laser with On-Chip Integrated Power Amplifier via Gain-Match Design
###### Abstract
The #3 laser with no DBR is in FP multimode operation with a low output power of 3 mW. Figure 10a shows the emission spectra of the #5 laser at the current range from 1 to 2 A. As expected, the spectra show a stable single-mode emission at the maximum outpower of the device. To achieve a perfect match between the gain peak and the Bragg wavelengths, we measured the drifting length between the gain peak and the Bragg wavelength, current ranges in a single-mode operation, and maximum output powers of MOPA-DBR lasers (#4, #5, #6), as shown in Figure 10b. With the increase of the grating period, the Bragg wavelength gradually shifts to a long wavelength. The #4 laser with a grating period of 534 nm operates in single mode with the emitting wavelength of 1900 nm at driving current from 1.1 A to 1.5 A, and its single-mode wavelength shift is 20 nm compared to the wafer's PL peak (1880 nm). The #6 laser with a grating period of 540 nm operates in single mode with the emitting wavelength of 1928 nm at a driving current above 1.8 A, and its single-mode wavelength shift is 42 nm compared to the wafer's PL peak. Excessively high driving currents for single-mode operation led to rapid saturation of the output power, which makes it difficult to maintain stable operation. The #5 laser with a grating period of 537 nm operates in single mode with the emitting wavelength of 1920 nm at driving current from 1.5 A to 2.0 A, and its single-mode wavelength shift is 40 nm compared to the PL peak. Since the lasers are fabricated by the same epitaxial wafer, the devices have similar P-I-V characteristics. Ignoring the influence of sintering and packaging, the relationship between output power and wavelength matching shows that in order to realize a high-power MOPA-DBR laser, the target wavelength is 40 nm red-shifted from room temperature PL of the wafer, which is the optimal gain corresponding relationship.
## 5 The Evolution towards a Global Smart Grid Deployment: Challenges and Perspectives
### Data Communication and WSANs  
Electrical grids present particular characteristics mainly in terms of infrastructure, equipment and electromagnetic interferences. The implantation of electrical MGs has a major impact over the classical network topology and power generation. Even more, the evolution towards a SG implies new issues in terms of communication and security, and WSANs are also constrained by power energy, in example.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**SG Network** & **Technology** & **Frequency Band** & **Data Rate** & **Range** & **Power Consumption** \\ \hline \multirow{3}{*}{HAN} & Bluetooth & 2.4 GHz & 720 kbps & 10 m & \
\begin{tabular}{c} Classical: \(\approx\)100 mW \\ Low-energy: \(\approx\)10 mW \\ \end{tabular} \\ \cline{2-6}  & ZigBee & 868 MHz/915 MHz & 250 kbps & 100 m & \(\approx\)10 mW \\ \hline \multirow{3}{*}{HAN and NAN} & WiFi & 2.4 GHz & Up to few Gbps & 200 m & \(\approx\)1.5 W \\ \cline{2-6}  & M2M solutions & ISM band & Up to 100 kbps &
\begin{tabular}{c} From 200 m to \\ tens of km \\ \end{tabular} & \(\approx\)50 mW \\ \hline \hline \end{tabular}
\end{table}
Table 2: Comparison of the main characteristics of the Home Area Network (HAN) and Neighborhood Area Network (NAN) communication solutions.  
Figure 7: The proposed communication technologies for each level of the SG.  
The combination of all these factors implies new solutions to be found to ensure the adequate reliability concerning the communication and the WSANs nodes operation.
## 3 Establishment of Integrated Navigation Model  
### State Equation and Measurement Equation  
#### 3.1.1 INS State Equation  
The error state equation of INS can be described as [6]:  
\[\dot{U}_{INS}(t)=A_{INS}(t)U_{INS}(t)+B_{INS}(t)V_{INS}(t), \tag{40}\]  
where the state variable \(U_{INS}(t)\) is as follows:  
\[U_{INS}=[\begin{array}{cccc}\Phi_{1\times 3}&V_{1\times 3}&\Lambda_{1\times 3 }&\psi_{1\times 3}&\Gamma_{1\times 3}\end{array}]^{T}, \tag{41}\]  
in the formula \(\Phi_{1\times 3}{=[\varphi_{E},\varphi_{N},\varphi_{U}]}\) represents the attitude matrix of the moving carrier's roll angle, pitch angle and yaw angle, respectively; and \(\Lambda_{1\times 3}{=[\delta L,\delta\lambda,\delta h]}\) represents the moving carrier's latitude, longitude and altitude error matrix, respectively. \(V_{1\times 3}=[\delta V_{E},\delta V_{N},\delta V_{U}]\) represents the velocity error matrix; \(\psi_{1\times 3}{=[\psi_{E},\psi_{N},\psi_{U}]}\) represents the first-order Markov shift matrix of the gyroscope; \(\Gamma_{1\times 3}=[\Gamma_{E},\Gamma_{N},\Gamma_{U}]\) is the first-order Markov shift matrix of the accelerometer; and E, N and U represent the east, north and up directions of the east-north-up coordinate system, respectively.  
The process noise matrix is:  
\[V_{INS}(t)=[\begin{array}{cccc}\varpi_{1\times 3}&\omega_{1\times 3} \end{array}]^{T}, \tag{42}\]  
where \(\varpi_{1\times 3}=[\varpi_{x},\varpi_{y},\varpi_{z}]\) is the random drift noise matrix of the accelerometer, and \(\omega_{1\times 3}{=[\omega_{x},\omega_{y},\omega_{z}]}\) is the random drift noise matrix of the gyroscope.  
\(A_{INS}(t)\in\mathbb{R}^{15\times 15}\) and \(B_{INS}(t)\in\mathbb{R}^{15\times 6}\) are the state transition matrix and the noise driving matrix, respectively.
# Blockchain-Based Decentralized Architecture for Software Version Control
## 4 Proposed Approach
### Blocks Contain the Data  
With our distributed repository, we have a self-constructing blockchain with blocks containing data about the project being developed, its version, timestamp and reference to the file stored in IPFS. Following data will be stored in each block.  
1. [label=.]
2. Hash of previous block;
3. Time stamp;
4. Project name;
5. Project ID;
6. File ID;
7. Version of change;
8. Previous version;
9. File name (saved on IPFS);
10. Developer ID.  
The blockchain will be constructed based on the hash of the previous block. The first block as we know in blockchain is known as the genesis block. The genesis block in our case will contain some basic information about the project being developed, and the next blocks will contain data specifically related to the changes made. For calculating the hash, Hyperledger Fabric uses the SHA256 algorithm that is also used for hash calculation in bitcoin blockchain [1]. SHA256 is an encryption algorithm that returns a string of fixed length when passed with any amount of data [51]. Our input to the encryption algorithm will be all the above-mentioned data stored in a single block, then the hash of the block will be generated and that hash will be stored in the next block, making a blockchain just like in the link list in which we have pointers working together to make a list. Figure 7 illustrates how our blockchain will work.  
Figure 7: Blockchain structure and consensus algorithms.  
Two essential blockchain qualities are immutability and distributed structure, and because the ledger is immutable you can always rely on it to be correct. Its decentralized nature protects it against network threats. On the ledger, each transaction or record is stored in a \"block\". Blocks on the bitcoin blockchain, for example, typically contain more than 500 bitcoin transactions, so on same structure our block will contain a limited amount of data. A block's data is dependent on and related to the data in the preceding block, forming a chain of transactions across time.
## 3 Materials and Methods
### Fabrication of Grating Surfaces
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Sample** &
\begin{tabular}{c} **Backscatter Angle** \\ **\(\theta\) (Degrees)** \\ \end{tabular} & \(\mathbf{\Lambda_{1}}\) (nm)** & \(\mathbf{\Lambda_{2}}\) (nm) \\ \hline Bi-grating-1 & 5 & 705.00 & 835.85 \\ Bi-grating-2 & 6 & 697.95 & 857.30 \\ Bi-grating-3 & 7 & 682.00 & 868.00 \\ Bi-grating-4 & 8 & 666.35 & 872.50 \\ Bi-grating-5 & 9 & 655.30 & 886.95 \\ Bi-grating-6 & 10 & 655.15 & 922.55 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Pitch values of the superimposed gratings for angle-independent retroreflection. Figure 3: Schematic depiction of a single bi-grating, highlighting its position on the actual glass slide sample. The slide contains six separate superimposed bi-gratings inscribed in an azobenzene thin film and coated with 50 nm gold layer. Analysis V2.0 software. Figure 4 presents the AFM analysis of Bi-grating-6. Figure 4a shows a 20 \(\upmu\)m \(\times\) 50 \(\upmu\)m AFM surface topography image, while Figure 4b provides the 3D visualization. The surface profile along the grating is shown in Figure 4c. The measured surface profile reveals periodic modulations resulting from the two sequential laser exposures during the fabrication process. Each grating's modulation depth and periodicity are influenced by the laser power, exposure time, and the laser incidence angle for the first and second exposures. The superposition of these two sinusoidal gratings generates a unique profile characterized by constructive and destructive interference patterns. This results in modulation depths that vary across the grating, creating the observed surface relief. These features are critical for the bi-gratings' ability to simultaneously support in-coupling and out-coupling of SPR in the designed retroreflectors.
###### Abstract  
In order to integrate data relevant to decision making, especially for the development of post-mining areas, it is important to ensure their uniform spatial reference. A problem arises when the coordinates of the boundary points of mining areas of neighboring mines are documented in different local rectangular flat coordinate systems. It is then necessary to transform the coordinates of these points into a uniform coordinate system. The currently implemented coordinate transformations in Poland, which are implemented separately for each area, do not allow the obtainment of the equal coordinates of identical boundary points. Therefore, topological consistency in such areas is missing. This problem was the focus of the research carried out by the authors. An authorial transformation procedure has been developed based on the method of independent models, which makes it possible to obtain the equal coordinates of identical boundary points using the transformation procedure. This procedure is presented in this article. The results of the transformation of the coordinates of boundary points of 14 mining areas located in the southern part of Poland, i.e., in the Upper Silesian Coal Basin, are also presented in this article. This task was carried out using the previously used transformation, performed separately for each of the mining areas and in accordance with the authorial procedure presented in this article. It was found that the values of differences in the locations of identical boundary points of the areas after the execution of separate transformation ranged from 0.002 m to 1.945 m. The difference in coordinates \(\Delta x\) and \(\Delta y\) reached a maximum value of 1.937 m and 0.542 m, respectively. The differences in the coordinates of identical boundary points, using the method of independent models, reached a maximum value of 0.001 m, which basically resulted from the rounding up of significant figures. The above facts indicate the validity of using the solution proposed by the authors, allowing topological consistency in areas where it is necessary to integrate the spatial data of neighboring areas.  
c 2025 15 5812 +
Footnote †: journal: Applied sciences  
Article