esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 The Expression of the Cracked Beam Deflection
Taking into account the above, we can conclude that the severity to be considered when calculating the natural frequencies of the defective beams is the one estimated to be obtained at \(x=0\) on the curve constructed using the deflections determined for different positions of the defect. This theoretical deflection corresponds to that resulting from the deformation on both sides of the crack, which is impossible to obtain directly from FEA. Note that this severity does not apply when the crack is very close to the fixed end; here it indicates a bigger damage severity than it is in the real case. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Crack Position [m]** & \begin{tabular}{c} \(\delta_{x}\) **(a)** **[mm]** \\ **for** **a = 0.4 mm** \\ \end{tabular} & \
\begin{tabular}{c} \(\delta_{x}\) **(a)** **[mm]** \\ **for** **a = 1 mm** \\ \end{tabular} &
\begin{tabular}{c} \(\delta_{x}\) **(a)** **[mm]** \\ **for** **a = 2 mm** \\ \end{tabular} \\ \hline \(x=800\) & 23.046 & 23.047 & 23.052 \\ \(x=600\) & 23.048 & 23.057 & 23.097 \\ \(x=400\) & 23.052 & 23.083 & 23.219 \\ \(x=200\) & 23.059 & 23.134 & 23.455 \\ \(x=20\) & 23.072 & 23.207 & 23.798 \\ \(x=0\) & 23.061 & 23.124 & 23.401 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Deflection at the free end for a cantilever beam affected by a transverse crack located at a distance \(x\) from the fixed end. Figure 1: Comparison of the transverse deflections for the cantilever beam segment clamped at the left end for two damage locations. Let us now introduce the pseudo-severity \(\gamma_{i}(a,x)\), which reflects the effect of the severity weighted with the effect of the crack position. In fact, it reflects a decrease in the beam's ability to store energy due to damage. This decrease, associated with the fact that energy distribution is in concordance with the modal curvature, permitted us to derive a function to calculate the natural frequency of a beam with a crack \(f_{i-D}(a,x)\). The obtained mathematical relation is [31]  
\[f_{i-D}(a,x)=f_{i-U}\Big{\{}1-\gamma(a)\big{[}\overline{\Phi_{i}^{\prime\prime }}(x)\big{]}^{2}\Big{\}} \tag{3}\]  
which makes use of the natural frequency of the intact beam \(f_{i-U}\), the damage severity \(\gamma(a)\), and the normalized mode shape curvature \(\overline{\Phi_{i}^{\prime\prime}}(x)\). This relationship was successfully used to assess cracks [32], which proves its reliability. From the right term in the parentheses of Equation (3), we can deduce the pseudo-severity as being  
\[\gamma_{i}(a,x)=\frac{\sqrt{\delta_{i}(a,x)}-\sqrt{\delta_{u}}}{\sqrt{\delta_ {i}(a,x)}}=\frac{\sqrt{\delta(a,0)}-\sqrt{\delta_{u}}}{\sqrt{\delta(a,0)}} \big{[}\overline{\Phi_{i}^{\prime\prime}}(x)\big{]}^{2}=\gamma(a)\big{[} \overline{\Phi_{i}^{\prime\prime}}(x)\big{]}^{2} \tag{4}\]  
In Equation (4) we denoted the deflection of the beam with a crack of depth \(a\) that is located at the distance \(x\) from the fixed end as \(\delta_{i}(a,x)\). One can observe that, dissimilar to the severity, the pseudo-severity severity depends on the vibration mode number \(i\).
# Flocking of Multi-Agent System with Nonlinear Dynamics via Distributed Event-Triggered Control
## 2 Preliminaries and Problems Formulation
### Problem Statement  
In this paper, flocking is investigated. Due to the fact that the sensing abilities of each agent is limited, the control law, except for achieving desired flocking motion, it should also guarantee for all \(t\in\mathcal{R}_{\geq 0}\) that i) the agents avoid collision with each other; ii) the communication graph \(\mathcal{G}\) is connected.  
Figure 1: The neighboring set of agent \(i\).  
**Definition 1**.: _Flocking motion is said to be achieved asymptotically for MAS (1), if for any initial condition,_  
\[\lim_{t\to\infty}\underline{d}\leq\left\|x_{i}(t)-x_{j}(t)\right\| \leq\bar{d},\] \[\lim_{t\to\infty}\left\|v_{i}(t)-v_{j}(t)\right\|=0,\quad\forall(i, j)\in\mathcal{E},\]  
**3. Flocking via Distributed ETC**  
In this section, a systematic solution to flocking problem is introduced. Our overall approach is to design a distributed action function for each agent that captures all the desired control specifications. The action function will then be implemented into the distributed controller of each agent.
# New Space Engineering Design: Characterization of Key Drivers
## 3 Results and Discussion
### Discussion per Application Domains
#### 3.2.2 Operations and Servicing in Space
A notable example is Astroscale, a Japanese company that, in 2024, successfully demonstrated, despite minor spacecraft anomalies and partial propulsion loss, advanced IOS technologies for active debris removal in LEO [114]. To achieve higher technology readiness for complex tasks such as propellant transfer and in-orbit repair, the role of standardized platforms and plug-in interfaces, modular architectures, intelligent algorithms, and robotic technology is essential [115,116]. In particular, IOS programs actively promote the adoption of standardized mechanical, electrical, and software interfaces to ensure interoperability during close-proximity and docking maneuvers [117]. The promising prospect of in-space servicing may be hindered by barriers related to policy coordination and legal uncertainty. A major challenge lies in the absence of internationally harmonized regulatory frameworks. Current liability instruments, such as the 1972 Liability Convention, follow a fault-based approach that complicates the assignment of responsibility in collision scenarios [118]. The situation is further complicated by restricted access to complete collision data and the growing congestion in Earth's orbits of recent years. Measures such as the development of international technical standards, the formalization of operational norms, and the definition of clear protocols for evidence collection have been proposed to address these challenges [119; 120]. These efforts are crucial in preventing the underutilization of available technologies due to regulatory ambiguity and in promoting coordinated action among space actors operating in shared orbital environments.
# Charging Platform of Chess-Pad Configuration for Unmanned Aerial Vehicle (UAV)
## 1 Introduction
Implementing this technique should consider the onboard charging circuit's weight to avoid a reduction of payload and conflict with the UAV electronic system. Furthermore, even with a high tolerance for coil misalignment, wireless power transfer technology must ensure an efficient transmission of power. Those issues were discussed in [24; 25; 26; 27; 28; 29; 30; 31]. In [32], the researcher adopted a design of two spiral coils in a circular shape. This design's drawback was the considerable weight and size of the installed onboard parts, which reduced the UAV payload and jeopardized the aerodynamics. In [33], the design model relied upon a mechanical relocating system to align a coil fixed on the onboard with a second coil installed on the landing station after UAV touchdown. The main disadvantage of this design was that the alignment process is complex, which may lead to reliability problems. The maximum achieved average of the wireless power transfer efficiency was found to be 63.4% and changed over time [34]. However, in [35], an excellent performance was shown in experiments and analyses. The average achieved efficiency of the WPT was around 75%. One of the other solutions for power transfer is using a contactable solution, which enables a high power transmission efficiency. However, that solution needs an accurate UAV landing system and mechanical process to achieve the connection of the electrodes for reliable connectivity, and this contributes to a rise in control system costs and complexity [36; 37; 38]. Moreover, it requires highly accurate positioning tools, which are difficult to have due to the lack of a reliable localization system in an outdoor environment [39; 40; 41]. In this work, a UAV charging station is proposed based on direct contact as an alternative solution for issues in similar existing systems. This solution requires onboard charging circuits to improve the degree of autonomy for an unmanned aerial vehicle system without any human intervention. When the UAV reaches its docking station, the recharging process starts. The electrode terminal on the four aerial skids is attached to a polarized copper plate, and those plates are arranged successively positively and negatively. The drone can take off and continue to operate without undocking after charging is done. Therefore, the UAV charging system's proposed design is entirely automated, and there is no need for precise drone positioning and adjustment equipment after landing.
## 2 Materials and Methods
### Oilfields in Italian Sedimentary Basins
#### 2.1.2 The Val d'Agri-Tempa Rossa Field  
The second case study, the Tempa Rossa 1D hydrocarbon well, is located within the Tempa Rossa oilfield (Figure 1). The Tempa Rossa system lies in the Mesozoic carbonate substratum of the foredeep and foreland areas and in the external thrust belt of the southern Apennines. The system bears the largest oil and gas accumulations in Italy, including the Val d'Agri and Tempa Rossa oil fields.  
The reservoirs are composed of fractured limestones from the buried Apulia Platform, which extends from the Cretaceous to the Miocene. The majority of the oil column exceeds 1000 m and sometimes exceeds 2000 m. The seal is composed of Lower Pliocene shales. The source rocks, identified in a few deep wells of the area, are mainly Albian-Cenomanian and are marine anoxic carbonates facies containing sulphur [19].  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Depth** & **Litho-Stratigraphic** & **Age** & \(\mathbf{\lambda_{\mathrm{s}}}\) & \(\mathbf{\rho_{\mathrm{cs}}}\) & \(\mathbf{\rho}\) \\
**m** & **Formation** & **W/mK** & **kJ/m3K** & **kg/m3** \\ \hline \multirow{3}{*}{609} & Terrigenous & \multirow{3}{*}{Hologene/Upper Pleistocene} & \multirow{3}{*}{0.30} & \multirow{3}{*}{800} & \multirow{3}{*}{1700} \\  & sedimentary deposits & & & & \\ Fine Sand (dry) & & & & & \\ \hline
1258 & Sand (dry) & Pleistocene & 0.30 & 800 & 1700 \\ \hline
1405 & Clay Sand & Low Pliocene & 1.61 & 1696 & 1890 \\ \hline \multirow{3}{*}{5493} & Classic sedimentary & \multirow{3}{*}{3.16} & \multirow{3}{*}{1937} & \multirow{3}{*}{2359} \\  & rocks (Sandstone, & & & \\ Congomerates and & & & & \\ Silty Marl) & & & & \\ \hline \multirow{3}{*}{6202} & Carbonate rocks— & Low Cretaceous - & \multirow{3}{*}{3.50} & \multirow{3}{*}{2010} & \multirow{3}{*}{2480} \\  & Calacrenite/Dolostone & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Villafortuna 1 hydrocarbon well-lithostratigraphic profile (Villafortuna Trecate Oilfield, Western Po Plain).  
Figure 2: Temperature data visualisation for the Villafortuna 1 hydrocarbon well: Depth (m); Temperature (\({}^{\circ}\)C).  
Unlike the Villafortuna 1 hydrocarbon well, the Tempa Rossa 1D well features lithost stratigraphic units mainly composed of sandstone and associated shales (Table 2). The maximum depth of the analysed well is 5042 m; temperatures reach 107 \({}^{\circ}\)C (Figure 3).
# Melamine Foams Decorated with In-Situ Synthesized Gold and Palladium Nanoparticles
## 3 Results and Discussion
### XPS Study of the ME/PDMS/Au and ME/PDMS/Pd Foams  
The surface of the obtained ME/PDMS/Au and ME/PDMS/Pd foams was further analyzed by XPS (Figure 7). After the treatment, the wide scan spectra confirm the presence of PDMS and of the metals on the surface of their struts for both foams. In fact, as shown in Figure 7a,b, the Si 2s and Si 2p peaks appear in both cases as well as the Au 4f and Pd 3d peaks for each type of foam. High-resolution XPS spectra of the Au and Pd peaks was performed to determine whether the Au and Pd signals come from metallic NPs or unreacted residual precursors (Figure 7c,d). On the one hand, the Au 4f spectrum of the ME/PDMS/Au foams was accurately fitted with the peaks corresponding to 4f\({}_{7/2}\) and 4f\({}_{5/2}\) of metallic gold (Au\({}^{9}\)), with binding energies of 84.0 and 87.7 eV, proving the metallic character of the obtained Au NPs [40]. No residues from the Au precursor (i.e., Cl signal) were found on the foams (see Supplementary Information, Figure S8). On the other hand, the characteristic Pd 3d\({}_{5/2}\) and Pd 3d\({}_{3/2}\) peaks of metallic Pd particles appeared respectively about 335.5-335.9 and 340.8-341.2 eV. The obtained values seem to be slightly shifted from the position of metallic Pd (335.2 and 340.5 eV) [36]. This shift of the energies of the peaks could be related to the presence of not only metallic Pd, but also a small amount of some Pd compound. The potential presence of residues of the Pd precursor, Na\({}_{2}\)PdCl\({}_{4}\), can be discarded as no Cl residues from the Pd precursor were found on the foams by XPS analysis  
Figure 6: HRSEM micrographs and NPs size distribution (insets) of the obtained ME/PDMS/Pd foams obtained after different reaction times in 0.50 mg/mL of Na\({}_{2}\)PdCl\({}_{4}\) in ethanol: 1 (**a**), 24 (**b**), and 120 h (**c**).  
(see Supplementary Information, Figure S8). On the contrary, according to previous works, this effect can be related to the spontaneous formation of a thin oxide layer (PdO, with 3d\({}_{5/2}\) and 3d\({}_{3/2}\) energies of 336.8 and 342.1 eV) around the Pd NPs [36]. Although this outer oxide layer could negatively affect the performance of the Pd NPs on different applications, it has been previously reported that the NPs are still active on catalysis procedures [36].  
Therefore, the proposed approach proved to be a suitable route to obtain nanocomposite polymer foams with a large number of noble metal NPs (up to \(10^{14}\) particles/m\({}^{2}\), according to SEM observations (Figures 5 and 6)), specifically located and stably anchored on the struts of the foams. Additionally, this versatile route can be applied to commercially available porous substrates other than ME foams (see Supplementary Information, Figure S9), without modifying their porous structure, proving the applicability and scalability of this approach, as well as the possibility to be used in diverse applications such as water treatment, catalysis, or sensoring.
## 1 Introduction
This design allows for the reporting of passenger locations to a central system to help the crew locate stray passengers. Additional functionality was incorporated in the form of potential personal area network connectivity with devices to collect additional data, such as bio metrics. To the best of our knowledge, this is the first such lifejacket presented in the literature, not only with the aim to apply haptic navigation for evacuation in vessels but also to collect and transmit all the information needed for a dynamic evacuation system to operate. As such, we believe that our smart lifejacket constitutes a new and and improved solution to the problem of evacuation of large passenger ships. The main contributions of this paper are as follows:  
* Demonstrate the benefits and viability of localization techniques in evacuation of large passenger ships;
* Demonstrate the ability to navigate non-expert users under difficult conditions;
* Demonstrate that such a system can be built in a reliable and cost-effective way, allowing for adoption at scale. The rest of the paper is organized as follows: Section 2 contains a detailed description of the architecture and implementation; Section 3 discusses outcomes and, finally, Section 4 provides the conclusions reached.
## 3 SaRT-CMSR-Based Signal Enhancement Method  
The detection of leakage-induced vibration signals in hydraulic valves presents significant challenges due to their susceptibility to environmental noise interference, resulting in obscured fault characteristics. To address this critical issue, this study proposes an innovative adaptive CMSR method integrated with the SaRT optimization algorithm. The implementation framework comprises the following systematic steps:  
* Spectral Analysis: The Fourier transform is performed on the leakage vibration signal inside the valve to observe the frequency domain characteristics of the original signal;
* Signal Preprocessing: Signal conditioning is implemented through a rescaling transformation, converting the leakage fault signals into small-parameter signals via secondary sampling to facilitate the subsequent processing;
* SaRT Algorithm Initialization: The optimization team parameters are configured, where each member's parameters are evaluated through the CMSR system. The system output is computed using the fourth-order Runge-Kutta method, with correlation coefficients calculated to identify optimal team members;* Iterative Optimization: Direction matrices are constructed and search spaces are defined for systematic optimization, providing continuous updates to team members and updating the center points through iterative refinement;
* Final Signal Processing: The optimization parameters obtained in step (4) and the pre-processing signal in step (2) are input into the CMSR system. The fourth-order Runge-Kutta method is used to solve the final output signal, and the noise reduction and feature enhancement of the noisy signal are realized. The algorithm flow chart is shown in Figure 2 below.
# Bearing Fault Diagnosis Using a Vector-Based Convolutional Fuzzy Neural Network
## 3 Vector-CFNN
### Fuzzification Layer  
Fuzzy operation is performed in this layer by using IF-THEN rules. The IF-THEN rule is determined as follows:  
\[R_{j}=IF\;u_{1}\;is\;S_{1j}\ldots\wedge u_{n}\;is\;S_{nj},THEN\;y_{j}=w_{j} \tag{5}\]  
where \(R_{j}\) represents a fuzzy rule; \(S_{ij}\) represents fuzzy sets; and \(w_{j}\) is a zero-order Takagi-Sugeno-Kang weight. A fuzzy set is governed by a Gaussian membership function that can be expressed as follows:  
\[S_{ij}=exp\left\{\frac{-\left(u_{i}-m_{ij}\right)^{2}}{2\sigma_{ij}^{2}}\right\} \tag{6}\]  
where \(exp(\cdot)\) is the exponential function and \(m_{ij}\) and \(\sigma_{ij}\) are the mean and standard deviation of a fuzzy set \(S_{ij}\), respectively.
# A Survey of Secure Time Synchronization
## 3 Current Time Synchronization Methods  
Recently, valuable studies have been conducted on secure time synchronization methods. Some of the research results are described below.
## 2 Six-Hardpoint Positioning Mechanism and Its Mathematical Model
### Kinematic Model of Six-Hardpoint Positioning Mechanisms  
#### 2.1.1 Inverse Kinematic Model  
The structural diagram of the six-hardpoint positioning mechanism is shown in Figure 2, which is a simplified version of Figure 1. Figure 2a shows the initial pose state of the mechanism, and Figure 2b shows the mechanism in the state after a pose adjustment. When considering the primary mirror as a rigid body, it has 6 degrees of freedom, so the pose of the primary mirror can be determined through 6 coordinate parameters, using \(\mathbf{q}=[x\ y\ z\ \mathbf{\beta}\ \gamma]^{\mathrm{T}}\) which represents the pose of the primary mirror. \(\mathbf{q}\) can be decomposed into a position vector \(\mathbf{t}=[x\ y\ z]^{\mathrm{T}}\) and an attitude vector \(\mathbf{s}=[\alpha\ \beta\ \gamma]^{\mathrm{T}}\). According to the geometric relationship in Figure 2, the inverse kinematic model of the six-hardpoint positioning mechanism can be directly obtained:  
\[\mathbf{l}_{i}=\mathbf{t}+\mathbf{R}\mathbf{a}_{i}-\mathbf{b}_{i} \tag{1}\]  
where \(i=1,2,...,6\), corresponding to the six hardpoints. \(\mathbf{l}_{i}\) is the vector in the direction of the hardpoint, and the norm of the vector is the length of the hardpoint. \(\mathbf{t}\) is the position vector of the primary mirror and the coordinate of the coordinate origin \(\mathbf{O}_{1}\) in the \(\mathcal{O}\)-xyz. \(\mathbf{a}_{i}\) is the coordinate of the upper support point \(\mathrm{A}_{\mathrm{i}}\) in the coordinate system \(\mathcal{O}_{1}\)-x\({}_{1}\)y\({}_{1}\)z\({}_{1}\), and \(\mathbf{b}_{i}\) is the coordinate of the lower support point \(\mathrm{B}_{\mathrm{i}}\) in the coordinate system \(\mathcal{O}\)-xyz (\(\mathcal{O}_{1}\) and \(\mathcal{O}_{2}\)) here refer to the coordinate origins, which are independent of the observability indices \(\mathcal{O}_{1}\) and \(\mathcal{O}_{2}\)). \(\mathbf{R}\) is the rotation matrix and is represented as follows:  
\[\mathbf{R}=\begin{bmatrix}\cos\gamma\cos\beta&\cos\gamma\sin\beta\sin\alpha-\sin \gamma\cos\alpha&\cos\gamma\sin\beta\cos\alpha+\sin\gamma\sin\alpha\\ \sin\gamma\cos\beta&\sin\gamma\sin\beta\sin\alpha+\cos\gamma\cos\alpha&\sin \gamma\sin\beta\cos\alpha-\cos\gamma\sin\alpha\\ -\sin\beta&\cos\beta\sin\alpha&\cos\beta\cos\alpha\end{bmatrix} \tag{2}\]  
where \(\alpha\), \(\beta\), and \(\gamma\) are the rotation angles of the primary mirror around the coordinate axes x\({}_{2}\), y\({}_{2}\), z\({}_{2}\), which are elements in the attitude vector \(\mathbf{s}=[\alpha\ \beta\ \gamma]^{\mathrm{T}}\). The inverse kinematics model can calculate the length and direction of each hardpoint through the primary mirror pose.  
Figure 1: Three-dimensional model of the six-hardpoint positioning mechanism and the primary mirror positioning system. For clarity of expression, the primary mirror has been changed to translucent, and the structure of the mirror cell has been simplified.
## 6 Conclusions  
The frequent topology changes of NTSN pose new challenges to the novel routing scheme. The efficiency of the power system is not taken into account by existing routing technologies. Many routing algorithms also do not optimize the energy problem. To solve above problems, a tubular sliding time window (TSTW) energy model is proposed, firstly. The dynamic charging feature of constellations can by predicted by this model. Secondly, a multi-objective algorithm is proposed to calculate multiple routing paths. This algorithm consists of a congestion feature, latency feature and energy feature. Lastly, a lot of simulation is achieved by a multiple services traffic model.  
Simulation results validate the effectiveness of the proposed energy sensitive and congestion balance (ESCB) routing scheme. Comparison of related studies also demonstrate superior performance in comparison with the VT-SPR routing algorithm.  
Methodology, Y.J.; software, Y.J.; validation, Y.J. and Q.M.; formal analysis, Y.J.; investigation, Q.M.; resources, Y.J. and W.I.; data curation, Y.J. and X.W.; writing--original draft preparation, Y.J.; writing--review and editing, Y.J.; supervision, S.W.; project administration, Q.M.; funding acquisition, S.W. All authors have read and agreed to the published version of the manuscript.  
This work is supported by the SAST-SJTU advanced space technology joint research fund on Grant No: USCAST2019-22. and Grant 19 GFH-HT01-625.  
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.