esa-sceva/satcom-chunk-collection huggingface dataset:
# Mechanical Fault Prognosis through Spectral Analysis of Vibration Signals
## 2 Key Algorithms Based on Spectral Analysis
### Digital Integral
Moreover, the measurement accuracy of the acceleration sensor is poor for low frequency, and small measurement errors can cause large calculation deviations. Thus, the low frequency signal becomes an important error source for frequency domain integration. In consideration of actual machine operation, the vibration frequency must be far away from \(f=0\) Hz. Let \(f_{l}\) and \(f_{h}\) be the lower and upper cutoff frequencies, respectively, and choose \(f_{l}\) and \(f_{h}\) as integer multiples of \(\Delta f\). Under this condition, the discretized integrator is  
\[G_{k}= \begin{cases}\frac{1}{\sqrt{2\pi k\Delta f}},&k\in\left[\frac{f_{l}}{ \Delta f},\frac{f_{h}}{\Delta f}\right]\\ \frac{1}{2\pi(k-N)\Delta f},&k\in\left[N-\frac{f_{h}}{\Delta f},N-\frac{f_{l} }{\Delta f}\right]\\ 0,&\text{otherwise}\end{cases} \, \tag{5}\]  
and the sequence \(\{G_{0},\cdots,G_{N-1}\}\) is denotes as \(\mathbf{G}\). Equation (2) is discretized in order to obtain the velocity signal after the first-order integration. The expression for the velocity signal in the frequency domain is \(V_{k}=A_{k}G_{k}\). The corresponding expression in the time domain is obtained by applying the inverse discrete Fourier transform,  
\[v_{n}=\frac{1}{N}\sum_{k=0}^{N-1}V_{k}W_{N}^{-nk}= \frac{1}{N}\sum_{k=0}^{N-1}A_{k}G_{k}W_{N}^{-nk}\ \Rightarrow\mathbf{v}=\mathbb{F}^{-1}[\mathbf{A}\mathbf{G}]\, \tag{6}\]  
where \(\mathbf{v}=\{v_{0},\cdots,v_{N-1}\}\). Similarly, the acceleration signal is applied the second-order integral in order to obtain the displacement signal. Its expression in the frequency domain is \(D_{k}=A_{k}G_{k}^{2}\). Correspondingly, the discretized expression in the time domain of Equation (3) is obtained by applying the inverse discrete Fourier transform,  
\[d_{n}=\frac{1}{N}\sum_{k=0}^{N-1}D_{k}W_{N}^{-nk}= \frac{1}{N}\sum_{k=0}^{N-1}A_{k}G_{k}^{2}W_{N}^{-nk}=\mathbb{F}^{-1} \Big{[}A_{k}G_{k}^{2}\Big{]}\ \Rightarrow\mathbf{d}=\mathbb{F}^{-1}\Big{[} \mathbf{A}\mathbf{G}^{2}\Big{]}\, \tag{7}\]  
where \(\mathbf{d}=\{d_{0},\cdots,d_{N-1}\}\). In practical measurements, it is generally difficult to achieve whole-cycle sampling since the signal contains multiple frequency components. Hence, there is spectral leakage in the Fourier transform process. That is, some of the energy is dispersed to other frequencies. As it is well known, the transition time of a rectangular window is long and the out-of-band attenuation is not large enough, resulting in severe spectral leakage. Choosing an appropriate window, such as the Hanning window, may partially reduce the error in the frequency domain integration. Therefore, the lowest frequency of the original signal cannot be directly used as the lower cutoff frequency \(f_{l}\), which requires appropriate selection. Without doubt, increasing the sampling frequency \(f_{s}\) can reduce the error.
# Micromechanical Analysis in Applications of Active Mono-Slip and Continuum Dislocations in the MDCM
## 2 Continuum Dislocation Formulation  
### Kinematics  
Figure 1 shows the simplest representation of the MDCS unit cell to simplify the analytical formulations. The arrangement in Figure 1 is the Cartesian coordinate system, with \(x=(x_{1},\,x_{2},\,x_{3})\) and \(y=(y_{1},\,y_{2},\,y_{3})\), where \(x_{i}\) denotes the local system of coordinates to define the microscopic unit cell, and \(y_{i}\) represents the global coordinates to designate the unit cell. For a unit cell with a size of \(2\xi_{i}\) and \(2w_{i}\), we select the micro-coordinates \(x_{i}\) defined by \(x_{i}(2\xi_{i},\,2w_{i})\). The 2D MDCS comprises rectangular elastic inclusions in a  
plastically deformed matrix. The inclusions can be established in a bi-hexagonal periodic array, as presented in Figure 1.  
[PERSON] et al. [28; 29] analyzed MDCS by applying discrete dislocation to validate the precision of the modern continuum dislocation concept in reproducing size-dependent outcomes. Two forms of inclusion are considered, which have an identical fractional area of 0.2 but dissimilar geometrical arrangements of the strengthening material phase. The main materials are square geometrical inclusions segmented by the matrix, and the inclusions are rectangular and separated by matrix materials. As a consequence of the discontinuous structure of the unit cells, the analysis can be implemented discretely, in which the width is represented by \(2w\) and the height is represented by \(2\xi\Big{(}w/\xi=\sqrt{3}\Big{)}\), as illustrated in Figure 2. The inclusions have a size of \(2w_{f}\times 2\xi_{f}\), with \(\xi_{f}=w_{f}=0.416\xi\) for square geometry and \(\xi_{f}=2w_{f}=0.588\xi\) for quadrangular geometry. Shearing occurs in the \(x_{1}\)-direction; thus, boundary conditions (BCs) can be formulated as follows:  
\[u_{1}(t)=\pm\xi\Gamma,\ u_{2}(t)=0\ along\ x_{2}=\pm\xi \tag{1}\]  
where \(\Gamma(t)\) denotes the shear strain as a function of time.
# Assessing Voided Reinforced Concrete by Numerical Modelling of Impact-Generated Rayleigh Waves
## 2 Simulation Model  
### Reinforced Concrete Model  
A 2D model was developed in this study. The model consisted of three parts: concrete, steel reinforcement, and boundary reflection absorbing layers for the reinforced concrete (RC) model. The dimensions of the reinforced/plain concrete region were 1000 mm \(\times\) 300 mm (length \(\times\) width). The steel reinforcement had a length of 1000 mm and a diameter of 10 mm. The concrete cover thickness was 30 mm. The mechanical properties of the concrete and steel reinforcement were configured as uniform throughout the whole study and produced longitudinal wave velocities of approximately 4300 m/s and 6099 m/s, for concrete and steel reinforcement, respectively, as reported in [PERSON] et al., 2017 [13] for normal grade concrete. There were 10 layers of boundary reflection absorbing regions with increasing damping. The layers had a consistent thicknesses of 10 mm. The impact was defined by tabular amplitudes, in which the y coordinate is the amplitude of the impact wave, and the x coordinate is the time. The impact load was applied to a single node on the surface of the concrete. The sensors were arranged according to the experimental data acquisition layout to simplify the process of experimental validation ([PERSON], et al., 2017) [13]. There was a total of seven sensors. The distance between the first sensor and the impact point was 170 mm. There was a uniform spacing of 40 mm for the rest of the sensors. The impact sensor was placed at the centre of the concrete medium to reduce the contamination of the waveform by the boundary reflections. Due to the difference from the frequency range used in previous research ([PERSON], et al., 2017) [13], the sensor arrangement was checked against the 'near-field' effect in later stages. The configuration is shown in Figure 1.  
This study used distributed voids in a concrete block to resemble honeycombs inside RC. The size and shape of honeycombs are highly variable in reality. The distributed voids were packed within a square block with dimensions of 100 \(\times\) 100 mm. Then, the block was placed under the top reinforcement centre, and aligned with the very left, the middle or the very right sensor, as shown in Figure 2. The voids were randomly packed within the block with different densities using a MATLAB (R2020a) code ([PERSON], 2018) [14]. The diameter of the voids was chosen for efficient packing, so the required modelling effort was minimised.
# An Overview of Biopolymers for Drug Delivery Applications
## 3 Other Polymers Used in DDSs  
### Polyamide/Poly(amino acid) Polymers  
Among the above-mentioned polymers, polyamides or poly(amino acid)s present distinct properties such as great biocompatibility, gradual degradability, and adjustable physicochemical properties. Polyamide has repeating units linked by amide bonds. A group of small polyamides containing multiple amino acids of the same types linked through amide bonds are generally called poly(amino acid)s. Polyamide appears naturally or can be obtained synthetically [114]. Among naturally occurring polyamides are mentioned proteins (e.g., silk and wool), while synthetically obtained ones include different materials such as nylons, sodium poly(aspartate), and aramids [115]. Also, polyamides can be classified into homopolyamides (with one kind of monomer) and copolyamides (with different constituents) [116].  
The use of these polymers in DDSs presents several important advantages, such as localized target site action, constant release, and stabilization. There are also some disadvantages, such as the possibility of microbial contamination, extreme hydration, and reduced viscosity in storage [117].  
Synthetic poly(amino acid)s are also used in designing DDSs because they have a similar structure to the naturally occurring ones [118]. Poly(amino acid)s are mostly used in the design of chemotherapeutics for obtaining selective delivery for an acceptable duration of time. These polymers used in DDSs increase anti-tumor efficacy and lessen drug-related side effects [119].  
Polyasparamide biopolymer has recently gained attention as being non-toxic, extremely biocompatible, and biodegradable. Supplementarily, for different biological applications, its physicochemical properties present flexibility in functionalizing with different components, such as DNA and pharmaceuticals (doxorubicin or biotin) [120,121]. For cancer diagnosis and therapy, [PERSON] et al. recently synthesized superparamagnetic iron oxide nanoparticles by a thermal decomposition method and encapsulated them in a polyasparamide biopolymer to form a hydrophilic and biocompatible construct. In addition, polyasparamide was conjugated with biotin and doxorubicin functional groups to increase the targeting of cancer cells. In vivo tests demonstrated that the developed bio-construct decreased the magnitude of cancer tumor volume growth by three times, compared to the control cells [122].  
[PERSON] et al. developed a new polymeric product based on \(\alpha\),\(\beta\)-poly(N-2-hydroxyethyl) (2-aminoethylcarbamate)-d,l-aspartate complex covalently linked with doxorubicin for its application in anticancer treatment. In vitro tests demonstrated that the newly developed polymers had a retarded cytotoxic effect on tumor cells. Also, there was a noticeable improvement in the in vivo antitumor activity of the newly developed polymer and a survival advantage of the treated NOD-SCID mice [123].
## 3 Mathematical Model
### Operational Constraints  
The introduction of constraints ensures the balance between energy supply and consumption in the zero-carbon building system.  
1. Electricity balance: the system requires that electricity must remain balanced at all times. \[P_{buy,t}^{E}+P_{W,t}^{E}-P_{cur,t}^{E}+P_{CHP,t}^{E}+P_{GT,t}^{E}+P_{dis,t}^{E}= P_{load,t}^{E}+P_{CCS,t}^{E}+P_{P2G,t}^{E}+P_{cls,t}^{E}\] (28) where \(P_{W,t}^{E}\) is the electricity output of PV&WPP, and \(P_{load,t}^{E}\) is the total demand of electricity in the building system. 2. Gas balance: gas is supplied by the external gas market and P2G, and it is consumed by CHP and GT. \[G_{buy,t}+G_{P2G,t}=G_{CHP,t}+G_{GT,t}\] (29) 3. Carbon balance: CCS is a key device in the carbon cycle, and the total carbon input and output of CCS must remain consistent. \[C_{CHP,t}+C_{GT,t}=C_{cap}+C_{emi}\] (30) 4. Heat balance: considering the heat usage habits of building occupants, the heat supplied by the system should remain within a comfortable range. \[P_{load,t}^{H}-\Delta P^{H}\leq P_{CHP,t}^{H}+P_{P2G,t}^{H}\leq P_{load,t}^{H}+ \Delta P^{H}\] (31) Here, \(\Delta P^{H}\) is a constant referring to the comfortable range of occupants.
## 4 Results and Analysis of Three-Dimensional Forward Modeling
### Single-Anomaly Model  
To evaluate the detection capability of the configuration shown in Figure 1, a 3D model was designed to analyze the response of anomalous bodies under various scenarios. After obtaining the receivers along the survey line, the boundaries of the anomalous bodies could be identified through differentiation, as expressed below:  
\[E^{\prime}=\left[\begin{array}{ccc}\partial E_{1}&\partial E_{2}&\cdots& \partial E_{1n}\\ \partial r&\partial r&\partial r\\ \end{array}\right]^{\prime}, \tag{7}\]  
Since it is difficult to observe a spatially continuous electric field in practice and only spatially discrete electric fields can be measured, the difference in Equation (7) is expressed in following matrix:  
\[\mathbf{E}^{\prime}_{t\times(n-1)}=\frac{1}{\Delta r}\begin{bmatrix}E_{11}&E_{12}& \cdots&E_{1n}\\ E_{21}&E_{22}&\cdots&E_{2n}\\ \vdots&\vdots&\ddots&\vdots\\ E_{t1}&E_{t2}&\cdots&E_{tn}\\ \end{bmatrix}\begin{bmatrix}-1\\ 1&-1\\ 1&\ddots\\ \ddots&-1\\ 1\end{bmatrix}_{n\times(n-1)}, \tag{8}\]  
Figure 5: Diffusion of electric field response of grounded-wire-source EM method for full space model for time channel of (**a**) 0.020108 ms; (**b**) 0.069614 ms; (**c**) 0.241 ms; (**d**) 0.83435 ms; (**e**) 2.8885 ms; and (**f**) 10 ms.  
where r represents the direction vector of the survey line and \(\Delta\)r is the distance between receivers, with \(t\) and \(n\) denoting the number of time moments and measuring electrodes. In this paper, we focus our attention on the EM response of the cross-hole grounded-wire-source TEM model. Taking multiple forward models as examples, we verified the effectiveness of this exploration method and assessed its sensitivity to parameters such as the size, resistivity contrast, and spatial location of the anomalous bodies.
# FLATSIM: The ForM@Ter LArge-Scale Multi-Temporal Sentinel-1 InterferoMetry Service
## 3 FLATSIM Architecture
### Architecture of the FLATSIM Project: Distributed and Scalable by Design  
The strategy behind the integration of NSBAS in the FLATSIM project was to make NSBAS processing massively parallel. Even if most of its steps can be run in a parallel way, NSBAS was conceived as a global processing chain running on a single-node, monolithic workspace, in which all the data generated during the NSBAS workflow are stored, from acquisition of the Sentinel-1 single look complex (SLC), to production of the time-series and formatting of distributed data. The integration of NSBAS in FLATSIM is based on a different logic, that consists in splitting the NSBAS chain in a set of unitary processes for which the inputs and outputs are clearly identified and cataloged. This way, it is possible to create for each unitary process its own workspace, from the cataloged data, including only the data necessary for its execution. It then becomes easier to dispatch these treatments on the computing resources.
# Period Cycle Optimization of Integrated Energy Systems with Long-Term Scheduling Consideration
## 2 Materials and Methods
### System's Optimization Algorithms
#### 2.1.3 Economic Viability  
To validate the feasibility of the system operating with different energy structures, two crucial economic parameters are introduced: net present value (\(NPV\)) and internal rate of return (\(IRR\)).  
\(NPV\) refers to the difference between the discounted value of future cash flows generated by an energy structure investment and the project's investment cost. When \(NPV>0\), it indicates that the energy structure can yield profits while meeting the benchmark rate of return. The calculation formula for \(NPV\) is as follows:  
\[NPV=\sum_{i=1}^{n}\frac{CF_{i}}{(1+r)^{i}}-CF_{0} \tag{29}\]  
where \(CF_{i}\) is cash inflows for each period, \(CF_{0}\) is the initial capital investment, and \(r\) is the periodic interest rate.  
\(IRR\) is a closely related concept to \(NPV\) and refers to the discount rate at which the total present value of cash inflows equals the total present value of cash outflows, resulting in a net present value of zero. The calculation formula for \(IRR\) is as follows:  
\[\sum_{i=1}^{n}\frac{CF_{i}}{(1+IRR)^{i}}=CF_{0} \tag{30}\]  
The economic evaluation of the system's energy structure is conducted using the \(IRR\). When the \(IRR\) exceeds the current discount rate, the \(NPV\) of the energy structure becomes greater than zero, indicating the feasibility of this energy structure. Conversely, if the \(IRR\) falls below the current discount rate, the energy structure is considered unfeasible. The economic feasibility of the energy structure is assessed by calculating both pre-tax and post-tax values through system operation.
## 3 Verification of the Composite Main Reflector
### Selection of Composite Main Reflector for Deployable Reflector Antenna Application  
The performance verification results of the main reflector according to the manufacturing process are shown in Table 4.  
Figure 12: Coordinate measurement configuration considering gravity.  
Figure 13: Test configuration and result of modal test on reflector.  
All manufactured composite main reflectors satisfied the antenna design requirements. The composite main reflector manufactured under a co-curing process has more pin-holes than the co-bonding process, but it was judged that this would not have a significant effect on the antenna's RF performance. It was also confirmed that the two processes did not have a significant effect on the mechanical performance of the main reflector.  
It was estimated that de-bonding occurred after curing due to the internal pressure of the structure caused by the gas remaining inside of the core when the adhesive film was excluded during bonding between the CFRP sheet and the aramid honeycomb core. Accordingly, for the main reflectors in Cases 3 and 4 excluding the adhesive film, perforations were processed on the core wall to add a venting path inside of the structure, and it was confirmed that there was no problem with edge-closed-type composite manufacturing. In the case of the main reflectors in Cases 3 and 4, a weight reduction of approximately 5% was possible compared to the main reflectors in Cases 1 and 2 by excluding the adhesive film. And, it was confirmed that a weight reduction of approximately 2 kg was possible for the 24 main reflectors of the antenna. In the case of the main reflector in Case 4, the weight increased slightly compared to Case 3 due to the application of an additional lamination process, but it was confirmed that the rigidity also increased during deployment. In the case of deployable reflector antennas for satellites, because agile maneuvering in orbital operation conditions is important, the rigidity of the main reflector during deployment was considered the most important performance.  
Through this study, Case 4's main reflector, which enables additional weight reduction of the composite main reflector and secures high rigidity during deployment, was selected as the single main reflector of the deployable reflector antenna.
## 5 Experimental Verification and Analysis
### Case Study I: Fault Diagnosis of Rolling Bearing
#### 5.1.2 Analysis Results of RMSDE
Although MSE has a good separation of C2 and C3, the entropy characteristic curves of the other three healthy types overlap and cross many times during the change of scale factors. In addition to C3, the eigenvalue curve of MFE can identify the other four faults at most scales, but the entropy calculated by this method has poor regularity and large fluctuation. For example, MFE has an excellent distinction between C2 and C4 in the first 15 scales, but when the scale reaches 15 or more, the entropy fluctuation of the two health states leads to a certain overlap of the curve. Compared with the three traditional entropy methods, MSE, MFE and MPE, the RMSDE proposed in this chapter has the best separation and the most advantages in estimating stability. With the improvement of scale factors, RMSDE has a consistent trend of change in the entropy estimation of the five health status types, with almost no fluctuations. The extracted features are more stable than the traditional entropy method.
# On Global Quantum Communication Networking
## 3 Extending the Distance between Nodes in QCN
Regarding the transmission medium, it is assu  
Figure 4: Illustration of post-quantum cryptography-based information reconciliation. ultra-low-loss fiber of attenuation 0.1419 dB/km (at 1560 nm) is employed [28]. In the same Figure, the Pirandola-Laurenza-Ottaviani-Banchi (PLOB) bound on a linear key rate is provided as well. Both PM TF-QKD and joint TF-QKD-McEliece encryption schemes outperform the decoy-state BB84 protocol for distances larger than 162 km, while simultaneously outperforming the MDI-QKD protocol for all distances, and exceed the PLOB bound at a distance of 322 km. The PM TF-QKD protocol can achieve the maximum distance of 623 km. The proposed joint TF-QKD-McEliece encryption scheme is able to achieve the distance of even 1127 km, thus significantly outperforming all other schemes. Even though the operating wavelength was 1560 nm, other suitable wavelengths such as 2 \(\upmu\)m and 3.9 \(\upmu\)m can be used as well. Now, by connecting the _base stations_ to the nodes in the proposed QCNs, we can provide the unconditional security to the 5G+/6G wireless networks. By organizing the base stations in a quantum optical mesh network and employing the proposed hybrid QKD-PQC concept we can provide unconditional security to a large number of users. The Internet of Things (IoT) architecture will comprise widely distributed nodes connected via different types of channels to enable new functionalities in communication, sensing, and computing. Communication security in such a giant network is of paramount importance. Our proposed QCNs will underpin the unconditional physical-layer security of the IoT given that it will allow any two arbitrary nodes to securely transmit data at a high rate via an optical link. Critically, the security of such a network will not rest upon the trusted-node assumption, and a compromised node will not affect the security of other nodes. As such, the proposed QCNs will lead to a substantially stronger security level for the IoT. To enable security for future 6G wireless networks at a reasonable cost, the proposed joint satellite-terrestrial QCN can be based on the Cubesat satellites. For satellite-to-satellite quantum communications, in addition to the proposed hybrid QKD-PQC concept, it also possible to employ our recent restricted eavesdropping concept [29], which offers a significant increase in SKRs. This concept was presented in the ICTON 2020 paper [30]. Alternatively, the hybrid QKD can also be applied [13].