esa-sceva/satcom-chunk-collection huggingface dataset:
# Review of Flexible Piezoresistive Strain Sensors in Civil Structural Health Monitoring
## 3 Elaboration of Sensor Materials
### Conductive Materials
#### 3.1.3 Hybrid Materials  
According to the explanations above, each type of conductive material has its own pros and cons in application. To improve the sensing and mechanical properties of single-material sensors, numerous studies have focused on the combination of nanomaterials with different dimensional sizes and properties. One value of hybrid materials is the ability to compensate for the disadvantage of a single material by combining the merits of other materials, as shown in Figure 7. For example, compared with graphene- or CNT-based strain sensors, strain sensors based on graphene-hybridized CNT films are beneficial for achieving higher linearity and reproducibility under cyclic tensile strains of up to 20%. This was ascribed to the strong interaction and effective load transfer within the hybridized films that successfully resisted the buckling of CNTs. In addition, soft AuNWs and hard AgNWs were combined to make stretchable transparent films [73], which showed a wide measurable strain range of 0.05-70% and a high sensitivity of 236.6 within the 5% strain level. These attributes are difficult to achieve with a single component of either AuNWs or AgNWs.  
Another benefit of hybrid conductive fillers is the ability to tune the piezoresistive sensitivity of flexible strain sensors. For example, the incorporation of CB reduced entanglement in the MWCNT network, which promoted strain sensitivity [74]. Similarly, a composite film composed of CB and CNTs exhibited high sensitivity, high durability and electrical stability under fatigue cycles owing to the synergistic effect of the dual conductive network formed by CNTs and CB [75]. Furthermore, combinations of MWCNTs and CB [74,76], CNTs and graphene [77], AgNWs and graphene particles [43] and AgNPs and SWCNTs [47] have been reported.  
Figure 6: Carbon-type conductive materials.  
In a word, hybrid fillers show benefits for the improvement of electrical conductivity, sensing properties and stretchable range in flexible piezoresistive sensors because of the various conductive connections and the complementary mechanical properties amongst different materials.
## 5 Performance Test of BFGO Algorithm
### Test of Engineering Optimization  
Three classical engineering optimization problems are used to test the performance of the BFGO algorithm in finding appropriate parameters to optimize the solution of practical problems, including compression spring design, welded beam design, and speed reducer design [48,49]. The three issues are optimized with parameters 3, 4, and 7 to minimize cost dissipation.  
Tables 3-5 compare the results of the BFGO algorithm with the BA, GWO, PSO, and SOA algorithms tested on the three engineering design problems 30 times, respectively. The table shows the optimal parameters, the mean (Mean), the standard deviation (Std), and the minimum (Min) values for the 30 tests. Where underline represents the same optimum and bold represents the optimum.  
In the test of compression spring design, the BGO algorithm obtains the same optimal value as the GWO and SOA algorithms in the mean and minimum values. The standard deviation is slight, indicating that the algorithm is stable. In the test of welded beam design, the mean value of 30 tests obtained by the BFGO algorithm ranks second, second only to the GWO algorithm, and other algorithms are still far behind the BFGO algorithm. Similarly, in the speed reducer design problem, the mean value of the BFGO algorithm in the 30 tests  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Algorithm**} & \multicolumn{4}{c}{**Optimize Variable**} & \multirow{2}{*}{**Mean**} & \multirow{2}{*}{**Std**} & \multirow{2}{*}{**Min**} \\  & \(\mathbf{T_{s}}\) & \(\mathbf{T_{h}}\) & & & & & \\ \hline BA & 0.196600 & 0.101700 & 10.193600 & 67.907400 & 3074.41 & \(7.7449\times 10^{3}\) & 119.658 \\ PSO & 1.584700 & 20.84740 & 10.100800 & 104.54950 & 103,174.1 & \(9.9926\times 10^{4}\) & 6158.07 \\ GWO & 0.192900 & 0.095300 & 10.00000 & 64.124600 & **108.910** & \(5.688\times 10^{-3}\) & 108.902 \\ SOA & 0.192900 & 0.095200 & 10.000000 & 64.197300 & 5617.420 & \(1.3710\times 10^{4}\) & 109.001 \\ BFGO & 0.192800 & 0.095400 & 10.000000 & 64.270600 & 112.824 & 4.5868 & 109.097 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Comparison of BFGO algorithm and other algorithms in optimizing welded beam design.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Algorithm**} & \multicolumn{4}{c}{**Optimize Variable**} & \multirow{2}{*}{**Mean**} & \multirow{2}{*}{**Std**} & \multirow{2}{*}{**Min**} \\  & \(\mathbf{x_{1}}\) & \(\mathbf{x_{2}}\) & \(\mathbf{x_{3}}\) & \(\mathbf{x_{4}}\) & \(\mathbf{x_{5}}\) & \(\mathbf{x_{6}}\) & \(\mathbf{x_{7}}\) \\ \hline BA & 3.60000 & 0.800000 & 28.00000 & 7.300000 & 7.800000 & 3.900000 & 5.283700 & 201,614.63 & 1.592047 & 201,613.20 \\ PSO & 3.492600 & 0.792700 & 25.847700 & 7.691400 & 8.274700 & 3.841700 & 5.315900 is the first, the minimum value is tied for the first best with the GWO algorithm, and the standard deviation is still tiny, indicating that the algorithm is relatively stable.  
Therefore, compared with other algorithms, the BFGO algorithm also has powerful optimization ability for engineering optimization problems.
## 4 The Design of the Proposed Filter
### Proposed Combined Resonator Design  
As seen in the previous structures, the obtained frequency responses are not perfect, because these responses do not have a wide stop-band bandwidth, and none of these responses have a proper sharpness in the transition band. Therefore, to improve the frequency response, a combination of these resonators is proposed, as shown in Figure 11. The dimensions of the proposed combined resonator, which are depicted in Figure 11, are listed as follows: L\({}_{1}\) = 1.2 mm, W\({}_{1}\) = 1.56 mm, L\({}_{5}\) = 3 mm, W\({}_{5}\) = 0.1 mm, L\({}_{6}\) = 1.8 mm, W\({}_{6}\) = 1.4 mm, L\({}_{7}\) = 0.8 mm, W\({}_{7}\) = 9.9 mm, L\({}_{8}\) = 0.8 mm, W\({}_{8}\) = 2.2 mm, W\({}_{9}\) = 0.1 mm, W\({}_{10}\) = 0.2 mm, S = 0.2 mm, L\({}_{T}\) = 19.3 mm, W\({}_{T}\) = 9.9 mm.  
Figure 11: The structure of the proposed combined resonator.  
Figure 10: The S-parameters results of the proposed dual-side resonators.  
Figure 9: The structure of the proposed dual-side resonators.  
The frequency response of proposed combined resonator is shown in Figure 12. As seen, the proposed combined resonator creates three transmission zeros and provides a wide stop band bandwidth from approximately 1.9 GHz to 8.9 GHz, with an attenuation level of more than 20 dB. The proposed combined resonator has a sharp transition band of about 0.294 GHz from \(-\)3 to \(-\)20 dB, which provides a 57.8 dB/GHz roll of the rate parameter, which is a desirable result.
## 4 Conclusions  
In this work, the optical characteristics of ceria NPs have been studied due to the addition of different plasmonic nanostructures. We have selected Au NPs and QDs using plasmonic resonance wavelength selection through overlapping with both excitation and the emissions spectra of ceria NPs. It has been found that in-situ Au NPs provide the best enhancement of ceria fluorescence emissions, compared to post-added gold or added QDs, regardless of whether they are in-situ or post-added. Based on absorbance and bandgap analysis, Au NPs contribute to improving the formation of tri-valent cerium ions with associated O-vacancies, in addition to the coupling between the plasmonic resonance of gold and fluorescence emissions of ceria. Based on their fluorescence enhancement, ceria-gold NPs are used as an optical sensor for iron tiny particles in aqueous media through a fluorescence quenching mechanism with a Stern-Volmer constant of 8.6 M\({}^{-1}\), which is 2.4 times more effective than pure ceria nanoparticles. The quenching mechanism was found to be static based on absorbance dispersion measurements and corresponding bandgap calculations, which shows the change in the bandgap of gold-ceria NPs due to being adsorbed iron tiny particles.  
Conceptualization, N.S. and I.K.; Methodology, N.S., E.S. and I.K.; Resources, N.S.; Data Curation, E.S.; Writing--Original Draft Preparation, N.S.; Writing--Review & Editing, N.S. and I.K.; Visualization, E.S.; Supervision, N.S. and I.K.; Project Administration, N.S.; Funding Acquisition, N.S. All authors have read and agreed to the published version of the manuscript.  
The project was funded \"partially\" by Kuwait Foundation for the Advancement of Sciences under project code: PR17-15 EE-01.  
The authors would like to thank Mohamed Salah for his support in initiating the optical fluorescence setup at Kuwait College of Science and Technology (KCST). Also, the authors would like to thank KCST administration for logistic support along with offering some chemical facilities inside Lab Nanotechnology and Photonics (LNP) at KCST.  
Figure 8: (**a**) Absorbance dispersion curve of in-situ gold-ceria NPs at different iron concentrations, and (**b**) the corresponding bandgap calculations.  
Conflicts of Interest: 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.
# Survey on Ranging Sensors and Cooperative Techniques for Relative Positioning of Vehicles
## 2 Requirement Analysis
### Availability  
It is of high importance that a positioning system is as available as often possible. Multiple causes can be the reason for a diminished availability. A GNSS-based positioning system might not be available in situations with complete obstruction in the line-of-sight to the satellites, e.g., in tunnels. Not only GNSS, but any type of radio-based positioning system can be made unavailable by jamming the signal. Vision-based ranging systems might not be available in adverse whether conditions, such as fog, heavy rain or at night. Cooperative approaches are only available if each of the vehicles is equipped with the required localization and communication devices. At the early development stages, the low penetration rate will yield a de facto low availability. Hence, in order to provide a continuous operation of a safety system, the requirement on availability should reach a value near 100%.
## 5 Results and Discussion
### Effects of the Microcapsule Size on the Load-Carrying Capacity  
The effects of the microcapsule size, which is defined by the core/shell ratio on the load-carrying capacity for the SHC samples with different capsular circumferential contact lengths (Lcs), are shown in Figure 14. The load-carrying capacity for the sample with the microcapsule core/shell ratio 1:1 and Lcs 100% is 108.3 N. This is reduced by 3.8% for the sample with the microcapsule core/shell ratio 15:1 and Lcs 100% to 104.2 N. While the load-carrying capacity for the sample with the microcapsule core/shell ratio 1:1 and Lcs 25% is 103.3 N. This is reduced by 0.28% for the sample with the microcapsule core/shell ratio 15:1 and Lcs 25% to 102.99 N. This shows that the lower the core/shell ratio (larger shell thickness) of the microcapsule, the higher the load-carrying capacity of the sample. However, on other hand, the higher Lcs ratio also increases the load-carrying capacity of the sample that it can withstand.  
Figure 14: Effects of the Lcs ratios to the maximum load with different microcapsule core/shell ratios.  
Figure 13: Load displacement curves for microcapsule core/shell ratio 15:1 with different Lcs values.  
In addition to zero contact case (Lcs = 0%), which means there is no contact between the microcapsule and concrete. In this case, the model could be considered as a concrete plate with a hole. The load-carrying capacity of the specimen decreased to 102.7 N. This means when the contact length of the interface between the microcapsule and the concrete is equal to the microcapsule circumference, the specimen will reach the maximum carrying load. It is also clearly shown that Lcs is a dominant factor in determining the maximum load.
## 5 Experimental Analysis of Acoustic Propagation Characteristics about High-Energy Pulse Excitation
### Received Ultrasonic Signal Analysis of High-Energy Pulse EMAT  
In the paper, the high-energy pulse EMAT was designed to excite the Lamb wave with A0 as the primary mode. And the experiment about the effect of high-energy pulse EMAT excitation Lamb wave was carried out. At lift-off distance \(h=0\) mm, the Lamb wave excited by the high-energy pulse EMAT is shown in Figure 12.  
In Figure 12, the arrival time of the Lamb wave S0 mode direct wave is 31.01 \(\upmu\)s, the arrival time of the A0 mode direct wave is 68.15 \(\upmu\)s, and the distance of the transceiver is 170 mm. The calculated S0 group velocity is 5482 m/s and A0 group velocity is 2494 m/s. The theoretical value of the S0 group velocity is 5489 m/s and that of the A0 group velocity is 2498 m/s. Within the error tolerance range, the experimental results and theoretical values are the same. At the lift-off distance \(h=0\) mm, the A0 mode peak-to-peak value is 490 mV, and the S0 mode peak-to-peak value is 40 mV. The signal strength of A0 mode is much higher than that of S0 mode.
# UAV Communication Recovery under Meteorological Conditions
## 3 Methods
### UAV Coverage Radius with Elevation Angle under Different Weather Conditions
#### 3.3.3. Compensated Path Loss in UAV-Ground Communications
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Weather** & **Regions** & **28 GHz** & **71 GHz** \\ \hline \multirow{4}{*}{Rain (\(0<R_{\rm rain}<100\) mm/h)} & Region 1 & 6.5202 & 4.4548 \\ \cline{2-4}  & Region 2 & 5.5417 & 3.7718 \\ \cline{2-4}  & Region 3 & 4.5689 & 3.1075 \\ \cline{2-4}  & Region 4 & 3.8657 & 2.6386 \\ \hline \multirow{4}{*}{Fog (\(0.05<R_{\rm fog}<0.5\) g/m\({}^{3}\))} & Region 1 & 0.2052 & 0.2984 \\ \cline{2-4}  & Region 2 & 0.1744 & 0.2527 \\ \cline{2-4}  & Region 3 & 0.1438 & 0.2082 \\ \cline{2-4}  & Region 4 & 0.1217 & 0.1767 \\ \hline \multirow{4}{*}{Snow (\(0<R_{\rm snow}<10\) mm/h)} & Region 1 & 0.0475 & 0.6545 \\ \cline{2-4}  & Region 2 & 0.0404 & 0.5542 \\ \cline{2-4}  & Region 3 & 0.0333 & 0.4566 \\ \cline{2-4}  & Region 4 & 0.0282 & 0.3878 \\ \hline \hline \end{tabular}
\end{table} 
Table 10: The extent of increase in the compensated path loss (in dB) due to increases in rainfall rate, liquid water density, and snowfall rate. Figure 17: Compensated path loss versus snowfall rate in four regions.
# Research on an Improved Method for Galloping Stability Analysis Considering Large Angles of Attack
## 5 Conclusions  
In this study, the [PERSON]'s classical method of calculating the quasi-steady critical wind speed of galloping was studied. By taking a square column section as the target and through theoretical analysis, a correction method for the galloping force coefficient that considered the influence of the wind attack angle is proposed. A wind tunnel test was carried out to verify this method with an H-shaped section. At the same time, the flow around the section at the critical wind speed of galloping was studied with a numerical simulation. The research results are as follows:  
1. Compared with the classical [PERSON] calculation method and the method proposed by [PERSON], this study proposes a modified judgment criterion for the galloping force coefficient that considers the impact of the wind attack angle. In the range of wind attack angles of less than 25\({}^{\circ}\), the calculation results were basically consistent. The correction method proposed in this study was better than the classical calculation method based on the [PERSON] criterion, which did not consider the influence of the wind attack angle.
2. To further verify the applicability of this method, a model wind tunnel test was conducted on an H-shaped section at a high angle of attack. It was found that the critical wind speed of galloping calculated with the method that considered the wind's angle of attack was 10.2 m/s, which was closer to the critical wind speed of 11.2 m/s measured in the wind tunnel.
3. The results of the numerical simulation showed that at the critical wind speed of galloping, there was obvious airflow separation around the H-shaped section, and a large number of vortices fell off at the tail edge of the section, resulting in the instability of the section, which further verified the existence of severe aerodynamic instability at this wind speed.  
Conceptualization, Z.M. and J.L.; methodology, Z.M.; software, Z.M.; validation, Z.M., J.L. and S.L.; formal analysis, S.L. and H.L.; investigation, Z.M. and J.L.; resources, Z.M. and H.L.; data curation, F.W.; writing--original draft preparation, Z.M.; writing--review and editing, J.L. and F.W.; visualization, H.L.; supervision, H.L. and F.W.; project administration, J.L. and F.W.; funding acquisition, J.L. All authors have read and agreed to the published version of the manuscript.  
The authors acknowledge the financial support from the China Scholarship Council (CSC No. 202106560040).  
The study did not involve humans or animals.  
Not applicable.  
Figure 15: Pressure distribution around the H-shaped section.  
Data Availability Statement: No new data were created or analyzed in this study. Data sharing is not applicable to this article.  
The authors declare no conflict of interest.
# A Phase Correction Model for Fourier Transform Spectroscopy
## 5 Simulation Experiment  
### Filter Optimization Algorithm Performance Comparison  
In this section, we focus on comparing the improved GS-SABO algorithm with the traditional PSO algorithm when optimizing the all-pass filter parameters.  
The wavenumber range of spectra in the simulation experiment was set to be 1000-4000 cm\({}^{-1}\) (maximum wave number: 15,802 cm\({}^{-1}\)). The spectral phase error function was \(\theta(\omega)=0.5\sin(4\omega)\). The computer hardware configuration used in the simulation was 11 th Gen Intel (Santa Clara, CA, USA) (R) Core (TM) i5-11300H CPU with 16 GB of memory. We calculated the size of the output phase error by using these two algorithms.  
The total number of individuals \(M=20\), the individual dimension (all-pass filter order) \(N=8\), and the number of iterations \(n_{max}=200\). Twenty repetitions of the experiment were performed for both algorithms and the output phase error results obtained are shown in Figure 5(a),b. Overall, the correction using the proposed GS-SABO algorithm outperforms the conventional PSO: the average maximum phase error of GS-SABO is 3.25\({}^{\circ}\) compared to 4.43\({}^{\circ}\) for PSO; and GS-SABO is also better in terms of optimization stability.  
We also focus on the convergence of the two algorithms in the all-pass filter optimization problem, and Figure 6c shows the convergence curves of the two algorithms within 400 iterations. Overall, the proposed GS-SABO algorithm has better optimization results, as well as optimization efficiency, with fewer iterations.
## 4 Results and Discussion
### Effects of the EGR Rate on Engine Performance  
#### 4.3.1 Combustion Characteristics  
Figure 18 shows the average in-cylinder pressure and average in-cylinder temperature under different EGR rates. It can be seen that as the EGR rate increases from 0.0 to 0.5, the maximum in-cylinder pressure decreases by 20.8%, and the in-cylinder temperature decreases by 27.1%. Although increasing the EGR rate can effectively reduce the in-cylinder temperature and control NOx emission, an excessive EGR rate will deteriorate the engine combustion process and reduce the power. Therefore, the EGR rate needs to be controlled according to the requirements of the engine operating conditions within a reasonable range.
## 3 Results and Discussion
### Event 5 (10 May 2022)  
On 10 May 2022, a solar flare of X1.5 type occurred in the AR13006 region located at S31 W10. The peak intensity was reached at 13:55 UTC, while the onset and end of the flare were recorded at 13:50 UTC and 13:59 UTC, respectively. During this event, all stations (UNPM, OXUM, SPIG, SSNX, and UCOE) experienced disturbances in the ionosphere, and the disturbances could also be observed in all satellites.  
This event exhibited the most significant alterations in the wavelet results (Figure 10), displaying a pronounced disturbance with values nearing 0.05 at the level of detail 8. Considering that the average for the other events is around 0.02, this event experienced a more substantial alteration according to the wavelets. One possible reason for such pronounced disturbances in this event could be its solar flare's location on the solar disk, originating from the central part of the Sun. It is worth mentioning that, in the case of the calm day, we obtained maximum wavelet values less than 0.01, demonstrating the correlation between flare-induced disturbances and wavelet outcomes.  
Figure 9: Visualization of Total Electron Content Wavelet Analysis from GNSS Signals for the Event on 30 April 2022.
# Learning-Based Traffic Scheduling in Non-Stationary Multipath 5G Non-Terrestrial Networks
## 5 Conclusions  
In this work, we proposed an actor-critic RL agent for LOS estimation in non-stationary conditions deployed in multi-link NTNs in dense urban environments. The simulation results showed that the learning agent had a performance similar to an optimal policy which had total knowledge of the channel model in estimating the LOS probabilities of multiple satellite links, selecting the suitable scheduling policy for the selection of the links and tracking the predefined E2E loss threshold and bandwidth utilization. Multiple links were used to increase the resilience to E2E loss, reliability, data rate and throughput and thus improve the QoS. In this work, we outlined the handoffs between LEO satellites with real traces from the Starlink constellation that lead to an abrupt change in the elevation angles with respect to the user equipment. In future research, we plan to deepen the analysis of the handoff policies and investigate the integration of both ground and terrestrial segments.  
**Author Contributions:** Conceptualization, A.M., A.G. and P.C.; methodology, A.G. and P.C.; software, A.M.; supervision, G.A. and C.G.; validation, A.M., A.G. and P.C.; visualization, A.M.; writing--original draft, A.M.; writing--review and editing, A.G. and P.C. All authors have read and agreed to the published manuscript.  
**Funding:** This work has been funded by The HORIZON-CLA-2021-SPACE-01 project \"5G+ evoluTion to mutioRbitAl multibaNd neTwORks\" (TRANTOR) No. 101081983.  
**Data Availability Statement:** No new data were created or analyzed in this study. Data sharing is not applicable to this article.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# Edge-Driven Multiple Trajectory Attention Model for Vehicle Routing Problems
## 4 Experiments
### Ablation Analysis  
#### 4.4.1 Effect of Each Component  
The proposed E-MTAM incorporates three innovative components: (1) the EDMHA block; (2) dynamic graph embedding; and (3) the multi-decoder-based JS loss. To investigate the individual and combined effects of these components on model performance, we conducted ablation experiments on TSPs, CVRPs, and OPs, as shown in Tables 4-6. Specifically, we start with a vanilla model and progressively integrate the components, evaluating the model's performance on different problems at each stage. Taking TSP100 as an example, we incorporate the EDMHA block, dynamic graph embedding, and JS loss into the vanilla model and obtain improved routing performance with gaps of **2.45%**, **3.22%**, and **2.84%**, respectively. These correspond to absolute gap reductions of **1.80%**, **1.03%**, and **1.41%** compared to the baseline. For CVRP100, the individual addition of each component leads to gap reductions of