esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Case Analysis
### Case Analysis of the Access Tunnel in the Main Powerhouse
The FD range of the event was about 100-600 Hz during 0.03-0.13 s. The FD range had a downward shift phenomenon over time. The frequency points had good continuity. The FD range of the event gradually narrowed. The coda was developed, and the energy distribution was relatively dispersed. The signal lasted approximately 0.1 s.  
Figure 10g shows an MS signal captured at 03:27:39 on 13 January 2018. The apparent stress value of the event was 24.959 KPa, which was relatively high. The energy released was 43 J. The Es/Ep was 7.74, which indicated that the rock damage type was mainly mixed damage. The FD range of the event was about 200-500 Hz during 0.025-0.13 s. The FD range had a downward shift phenomenon over time. The frequency points had good continuity. The FD range gradually narrowed. The coda was very developed, and the energy distribution of the event was relatively dispersed. The signal lasted approximately 0.105 s.  
Figure 10h shows an MS signal captured at 03:38:41 on 13 January 2018. The apparent stress value of the event was 15.936 KPa. The energy released was 64 J. The Es/Ep was 2.06, which indicated that the rock damage type was mainly tensile damage. The FD range of the event was about 200-600 Hz during 0.025-0.07 s, and was about 300-400 Hz during 0.07-0.14 s. The FD range had a downward shift phenomenon over time. The frequency points had good continuity. The FD range gradually narrowed. The coda was very developed. The signal lasted approximately 0.115 s.  
Figure 10i shows a slight rockburst signal captured at 04:07:44 on 13 January 2018. The apparent stress value of the event was 58.516 KPa. The energy released was 1154 J. The Es/Ep was 2.91, which indicated that the rock damage type was mainly tensile damage. The FD range of the event was about 100-700 Hz during 0.025-0.065 s. There was obvious energy distribution in the low-frequency band. The signal was relatively complex. Figure 10j shows a rockburst signal captured at 04:19:06 on 13 January 2018. The apparent stress value of the event was 130.864 KPa. The energy released was 6597 J. The Es/Ep was 1.96, which indicated that the rock damage type was mainly tensile damage. The FD range of the event was about 100-700 Hz during 0.01-0.06 s. There was obvious energy distribution in the low-frequency band. The coda was very developed. The signal was relatively complex. Before the occurrence of a rockburst, there were several indicators that needed to be noted. The event FD range had a significant downward shift phenomenon over time. The frequency points of some events had good continuity. The energy distribution of some events was in the low-frequency range. The FD range of some events gradually narrowed. Before the rockbursts, only some of these indicators may have occurred. For the comparison of multiple events, there was obvious energy distribution for some events in the low-frequency band over time. The HHT spectrum can well reflect the MS activity characteristics and timely feedback the anomalies inside the surrounding rocks on site.
## 2 Materials and Methods
### Multiple Linear Regression Model  
MLR (multiple linear regression) is the process that obtains a linear relationship between DAT affinity and molecular descriptors using the OLS (ordinary least squares) method [35]. We used the QSARINS (QSAR-Insubria) software (version 2.2.4 year 2019) [36] developed by the QSAR Research Unit, University of Insubria, Italy. It allows the creation of MLR models using the GA (genetic algorithm) method for variable selection [35; 37]. This software permits dividing the database into training and prediction sets by either modeled endpoint responses or structure; in our case, we used the first option. Figure 1 shows the structures of the molecules included in the training (learning) set, and Figure 2 shows the structures of the compounds used in the prediction set. The best model was selected based on several criteria such as a high value of R\({}^{2}\) (good fitting) and Q\({}^{2}_{\text{LOO}}\) (robustness), a low value for R\({}^{2}\)-Q\({}^{2}_{\text{LOO}}\) (stability) and K\({}_{\text{XX}}\) (low correlation of descriptors), and the greatest R\({}^{2}_{\text{ext}}\) (predictability), among others, so that it has a slight difference between fitting, cross-validation, and external validation parameters.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline
**No** & **Ligand** & **Kd (nM)** & **Log Kd** & **No** & **Ligand** & **Kd (nM)** & **Log Kd** \\ \hline
11 & BDBM30130 & 3600 & 3.556 & 40 & BDBM50105417 & 8400 & 3.924 \\
12 & BDBM50069442 & 27,000 & 4.431 & 41 & BDBM50176062 & 2100 &  
Figure 1: Molecular structures of compounds used in the training set.
# Self-Recognition Grasping Operation with a Vision-Based Redundant Manipulator System
## 1 Introduction
The inverse solution problem [34] is an old question for robotics, which can be solved in either the velocity or position forms. The inverse solution in velocity form (ISVF) relies on the Jacobian matrix of the manipulator, which represents the relationship between the joint velocity and the velocity of the end-effector. In ISVF, an initial configuration should be set, then simulated, where planning is carried out from the initial configuration to the pose of the object. The angles of each joint are converged by an integral of joint velocity at each motion interval. The process is fussy and costly in time, making ISVF suitable for offline trajectory planning. The inverse solution in position form (ISPF) can obtain joint angles directly, and can generally be divided into numerical [35] and geometric methods [36]. However, the numerical method presents an abundant computation cost, leading to poor real-time adaption. Additionally, it often falls into a local optimum. The geometric method is only effective for low DOF manipulators (i.e., those not exceeding 6-DOF). For manipulators with a spatial redundancy (i.e., those with at least 7-DOF), this method is not compatible. Indeed, there are infinite solutions for a particular pose with redundant manipulators (DOF > 6). Less methods can achieve the expression of all feasible solutions, rapid calculation, and optimal solution selection simultaneously, which are imperative for pose transformation in self-recognized grasping operation. Thus, a method of ISPF, which can express the whole solution set rapidly and build up a rule selecting the global optimal solution, is significant for redundant manipulator application in unstructured environments and environments with clutter. The contribution of the paper is exposing the process of self-recognition grasping operation with a vision-based spatially redundant manipulator. Instance segmentation is used to distinguish the object and describe the contour. Within the contour, pose estimation is carried out via a grasping network. On this basis, a method is proposed to calculate the inverse solution in position form to transfer the pose into the joint space of the manipulator for direct motion control. The Section 2 shows the process of the vision-based self-recognized grasping operation, including the framework of instance segmentation, the grasping network of pose estimation, and the methods of pose transformation. In the Section 3, the inverse method of ISPF is described in detail. In the Section 4, experiments on self-recognition grasping operation are carried out. The process of self-recognition is verified and the method of ISPF is proven to be effective for real-time calculation and global optimal solution selection. The Section 5 presents our conclusion.
# Numerical Study of Aircraft Wake Vortex Evolution under the Influence of Vertical Winds
## 2 Materials and Methods  
The overall structure and framework of this chapter are illustrated in Figure 1. In this chapter, the typical medium-sized aircraft, Airbus A320, is selected as the numerical simulation subject, and simplified wing and fluid domain models are constructed. Using the simplified wing model for the study is beneficial to the extraction and analysis of vortex parameters and saves computational resources. The fluid domain is subjected to structured grid division based on the O-block method in ICEM. Grid independence tests are conducted to determine the appropriate number of grids and grid partitioning parameters. The governing N-S equations, turbulence models, and boundary conditions are selected to reflect real-world situations, where the turbulence model is the SST k-\(\omega\) turbulence model, a hybrid model of k-\(\omega\) and k-\(\omega\). It can simulate the transport and diffusion of vortices in the wake more accurately, and the computational speed is faster than that of the traditional method, which is suitable for calculating the high back-pressure gradient and shear flow. Numerical simulations are performed on the Ansys Fluent2021R1 platform, and investigations are stopped when the parameter errors meet the simulation requirements or after a certain number of iterations.
## 4 Materials and Methods
### Identification Confirmation and Quantitation of Volatile Compounds  
Compounds of interest were putatively identified in several fermentations through SPME-GCMS analysis. These fermentations were then repeated and used for extraction of volatile compounds to determine fermentation yield and confirm identification using pure standards. For each extraction, the homogenised sample (2 g) was weighed into a Kimax test tube and distilled water (1 mL), internal standard (5 \(\upmu\)L, 12-bromo-dodecanol 10 mM) and sodium chloride (\(\sim\)100 mg) were added. Tetrahydrofuran (1 mL) was aliquoted into each tube, capped, and vigorously mixed using a vortex mixer (2 min). Samples were sonicated for 30 min followed by centrifugation at 4000 rpm for 10 min. The organic phase was aspirated into GC-MS vials and kept at 4 \({}^{\circ}\)C in a cooling tray pending GC-MS analysis.  
The analytes were quantified using a GC-7890 gas chromatograph (Agilent Technologies, Santa Clara, CA) coupled to an MSD-5975 mass spectrometer (Agilent Technologies, Santa Clara, CA). The column used was a fused silica Rtx(r)-5 Si MS 30 m \(\times\) 250 \(\upmu\)m \(\times\) 0.25 \(\upmu\)m (Restek). The GC-MS parameters used for the SPME analysis described above were kept the same.  
The identity of all four compounds was confirmed by comparing their chromatographic retention times and mass spectra to those of pure standards. A calibration curve was built for each compound of interest using pure chemical standards obtained from Sigma Aldrich and analysed in the same time as the extracted samples. Each compound was quantified using peak height normalised by internal standard peak height using the calibration curve of pure standard. Calibration curve characteristics are presented in Table A1 (Appendix A). Yield was determined from the wet weight fermented substrate and was scaled up to reflect how much compound would theoretically be produced and extracted from 1 kg of fermented substrate.
# A Study on a Mechanism of Lateral Pedestrian-Footbridge Interaction
## 4 Amplitude Frequency Curve  
### Amplitude Frequency Curve of Pedestrians  
Equation (42) is related to the unary cubic equation \(A_{p}\), which has a zero solution \(A_{p}=0\) only, while the rest are related to the unary quadratic equation \(A_{p}\). Hence, its discriminate can be rewritten as:  
\[\begin{array}{l}\Delta_{p}=k_{2}^{2}-4k_{1}k_{3}{=[}(\frac{m^{2}}{8M^{2}c_{s }^{2}}-\frac{1}{2})\eta c{]}^{2}-4(\frac{1}{16}-\frac{m^{2}}{64M^{2}c_{s}^{2}} )c^{2}(\eta^{2}+4\sigma^{2}\\ -\frac{m^{2}\omega_{p}^{2}}{4M^{2}c_{s}^{2}}-\frac{m^{2}\eta^{2}}{4M^{2}c_{s}^ {2}}){=(\frac{m^{2}}{4M^{2}c_{s}^{2}}-1)\varsigma^{2}(\sigma^{2}-\frac{m^{2} \omega_{p}^{2}}{16M^{2}c_{s}^{2}})}\end{array} \tag{43}\]  
For convenience of the following analysis, the modal mass ratio parameters of pedestrians and the footbridge are defined as:  
\[m_{r}=\frac{m}{M}. \tag{44}\]  
If \(\Delta_{p}=0\), then \(m_{r}=2\zeta_{s}\), or if \(\sigma=\frac{m_{r}\omega_{p}}{4\zeta_{s}}\), Equation (42) has a zero solution and two equal real roots, namely, \(A_{p1}=0\) and \(A_{p2,3}=\frac{-k_{2}}{2k_{1}}\). Therefore, the pedestrians' amplitude frequency curve equation becomes:  
\[a_{p1}=0 \tag{45}\]  
\[a_{p2,3}=\sqrt{\frac{-k_{2}}{2k_{1}}}=2\sqrt{\frac{\eta}{\xi+\rho\omega_{p}^{2 }}}. \tag{46}\]  
If \(\Delta_{p}>0\), then \(m_{r}>2\zeta_{s}\), and if \(\sigma>\frac{m_{r}\omega_{p}}{4\zeta_{s}}\), \(\sigma<-\frac{m_{r}\omega_{p}}{4\zeta_{s}}\) or if \(0<m_{r}<2\zeta_{s}\) or even \(-\frac{m_{r}\omega_{p}}{4\zeta_{s}}<\sigma<\frac{m_{r}\omega_{p}}{4\zeta_{s}}\), then Equation (42) has a zero solution and two equal real roots, namely, \(A_{p1}=0\) and \(A_{p2,3}=\frac{-k_{2}\pm\sqrt{k_{2}^{2}-4k_{1}k_{3}}}{2k_{1}}\). Thus, the pedestrians' amplitude frequency curve equation can be derived:  
\[a_{p1}=0 \tag{47}\]  
\[a_{p2,3}=2\sqrt{\frac{(4\zeta_{S}^{2}-m_{r}^{2})\eta\pm\sqrt{(m_{r}^{2}-4 \zeta_{S}^{2})(16\zeta_{S}^{2}\sigma^{2}-m_{r}^{2}\omega_{p}^{2})}}{(\xi+\rho \omega_{p}^{2})(4\zeta_{S}^{2}-m_{r}^{2})}}. \tag{48}\]  
Equations (45) and (47) are trivial solutions for the pedestrians' lateral vibration, while Equations (46) and (48) are nontrivial solutions for the pedestrians' lateral vibration. Equation (46) implies that in the case where \(m_{r}=2\zeta_{s}\) or \(\sigma=\frac{m_{r}\omega_{p}}{4\zeta_{s}}\), the pedestrians' lateral vibration is related only to the pedestrians' parameters. Moreover, according to Equation (48), it is indicated that the pedestrians' lateral amplitude is related to the modal mass ratio, the pedestrians' parameters, and the damping of the footbridge.
# Research on Multi-Scale Point Cloud Completion Method Based on Local Neighborhood Dynamic Fusion
## 5 Conclusions  
This paper presents an end-to-end network model for multi-scale point cloud completion based on LNDM-Net. The model begins with a multi-scale point cloud extractor that processes point clouds at three different scales in parallel. It dynamically fuses local neighborhoods around key points in each scale of incomplete point clouds, incorporating a bias attention mechanism to preserve local feature information. This enhances the extractor's ability to capture both global and local features effectively.  
Next, the design of the point cloud generator leverages a multi-scale pyramid-like structure, which progressively refines the local details of the point cloud from coarse to fine. Inspired by generative adversarial networks (GANs), the model introduces a single-scale attention discriminator. Through adversarial competition between the discriminator and the pyramid generator, the accuracy of point cloud completion is significantly improved.  
Finally, LNDM-Net undergoes extensive experiments on the ShapeNet and PCN datasets. The results demonstrate that compared to the PF-Net algorithm, the average Chamfer Distance (CD) for some samples improves by 4.54% and 4.42%, respectively. Future work will focus on developing a more efficient point cloud completion model, aiming for finer granularity, more uniform distribution, and higher precision in the generated point clouds.  
Data curation, Y.L.; Methodology, Y.L. and J.S.; Validation, L.Z.; Writing-original draft, Y.L.; Writing--review and editing, J.S. and L.Z. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Natural Science Foundation of Hubei Province, grant number 2023 AFB993.  
Not applicable.  
The raw data on which the results of this article are based can be requested from the authors, and the raw data will be made available when necessary.  
We would like to express our sincere thanks to the School of Intelligent Manufacturing, Jianghan University, and [PERSON] of the State Key Laboratory of Precision Blasting, Jianghan University, for their contributions to and help with our research work.  
Figure 9: Visualization of the robustness of point cloud completion with different missing ratios.
## 3 Results and Discussion
### Calorimetric Tests  
As it is mentioned above, the palladium coating enables the low-temperature first hydrogenation, which allowed us to perform a correct calorimetric study of this process. At the initial stage of the reaction (hydrogen concentration in the metallic phase of 0 to 0.7H/M), the maximum heat release close to 100 kJ/mol H\({}_{2}\) in absolute value has been recorded (Figure 5), which corresponds to the equilibrium pressure range of 0.03-0.1 bar at 308 K (Figure 4). As the reaction proceeds, the heat release gradually decreases to 80 kJ/mol H\({}_{2}\). In the hydrogen concentration range from 1 to 1.5 H/M, one can observe a constant value of the reaction enthalpy of 60 kJ/mol H\({}_{2}\). Most likely, this corresponds to the phase transformation of a monohydride to dihydride phase, similarly described in [9]. When the phase transition is completed, the thermal effect of the reaction reduces sharply to 40 kJ/mol H\({}_{2}\).  
Figure 4: Hydrogen absorption isotherms of the T,ZrVNbTa alloy.  
Figure 5: Concentration dependence of the enthalpy of hydrogen absorption by Pd@TiZrVNbTa; T = 308 K.  
The analysis of experimental heat release curves (Figure 6) provides some important additional items of information.  
First, we point out the absence of any induction period for all curves corresponding to different concentration ranges. Second, there is an acceleration section on each curve, and in all cases, the maximum heat release rate is reached after 15-17 min, regardless of the concentration range and the overall thermal effect on each section. This peculiarity is not related to the inertia of the measuring system, the response time of which is at the level of several seconds. The nature of the phenomenon is not entirely clear. It is quite likely that it is related to the features of the crystallite structure of the alloy under test and the time to reach the maximum heat release rate (i.e., the maximum reaction rate) is determined by the characteristic migration path of hydrogen in the metal lattice. Third, all experimental heat release curves can be conditionally divided into three groups depending on the concentration range described by them (Figure 6). Each of these groups corresponds to processes similar in nature and thermochemical characteristics. The concentration ranges 0-0.3 and 0.3-0.7 are characterized by the maximum heat release rate, and the curves practically coincide. Based on the general concepts of phase transformations in metal-hydrogen systems, this concentration range may correspond to the formation of a solid solution in an HEA matrix. In the range of 0.7-1.25 H/M, the formation of a monohydride phase occurs, and at higher concentrations, this monohydride turns into a dihydride. Probably, the boundaries of these concentration ranges require further clarification, although the very fact of their separation is quite clearly seen from the results of the thermochemical analysis.
# Safety Issues Referred to Induced Sheath Voltages in High-Voltage Power Cables--Case Study
## 4 Power Losses for the Analyzed Types of Bonding
The effect of the natural reactive power of the cable line is seen especially in Figure 13a when the transferred power is only 1 MW, tg\(\phi\) = 0 (for the simplicity of the analysis, only the active power transfer is modelled). The natural reactive power of the analyzed line of the length 12 km is approx. 6 Mvar and significantly exceeds the transferred active power (1 MW). In such low-load conditions (active load current in the cable core is approx. 5 A; reactive/capacitive current in the cable core is approx. 30 A), the single-point bonding gives the highest total power losses. It should also be noted that the reactive/capacitive current coming from the natural power of the line is not the same along its whole length--it is a normal phenomenon of the current flowing via capacitance-to-earth of the cables. If the cable line transfers the power equal to 80 MW, tg\(\phi\) = 0 (Figure 13b), giving practically the max permissible load (load current approx. 420 A), the value of the power losses is two orders higher, compared to the results from Figure 13a. What was expected, the highest value of the power losses is for the both-ends bonding. In this case, when the transferred power is many times higher than the natural reactive power, the effect of the latter power is negligible. The analysis of the results of the power losses calculations shows that all types of bonding are acceptable for the transferred power equal to 10 MW. Admittedly, the cross bonding gives the lowest losses but introduces the most complicated technical solution to the power line. Figure 12: Power losses in the analyzed three-phase cable system for the transferred power 10 MW, tg\(\phi\) = 0.4: (**a**) losses in the metallic sheaths; (**b**) comparison of the losses in the metallic sheaths, cores and total losses; s-p: single-point bonding; b-e: both-ends bonding; c-b: cross bonding.
###### Abstract  
The future power system, characterized by lower inertia, reduced programmability and more distributed architecture, will depend on prompt and reliable control systems. Quick ancillary services provided by battery energy storage systems (BESS) could be a resource in order to deliver fast and precise response to frequency events. Degrees of freedom in the design of innovative products traded on ancillary services markets give the asset manager room for developing state-of-charge (SoC) restoration mechanisms. These are necessary to effectively exploit BESS as key resources for electricity balancing. This study compares the main SoC restoration strategies. It aims to define which ones are suitable for guaranteeing the reliability of the provision and the return on the investment. A robust regulatory framework analysis describes the degrees of freedom guaranteed by the main experiences around Europe. In this paper, a BESS model with variable efficiency is used to compare the provision of Frequency Containment Reserve (FCR) with different SoC restoration strategies exploiting one or more degrees of freedom. Here, we show that the degrees of freedom are key to the reliability of provision. Among most diffused mechanisms, dead-band strategies secure the desired consistency, but require large energy flows for SoC management. Thus, BESS life and economics decrease. The strategies based on minimum available energy guarantee assured reliability while being fair with BESS life and operation costs.  
**Keywords:** batteries; BESS; frequency regulation; SoC restoration; ancillary services; EFR; degrees of freedom; balancing; energy storage; Fast Reserve