esa-sceva/satcom-chunk-collection huggingface dataset:
## Materials and Methods  
### Study Area  
The study was carried out in June 2019 in Montecristo and Giglio islands (Tuscany, Italy) (Figure 1). The Montecristo Island (42.3317\({}^{\circ}\) N, 10.3083\({}^{\circ}\) E) (Figure 1B) is an uninhabited and isolated island, sub-circular in shape, fourth in size after Elba, Giglio and Capraia islands, and completely mountainous, reaching a height of 645 m above sea-level with an almost constant slope of 25\({}^{\circ}\)[39, 40, 41, 42]. Its history and geography distinguish the island from the others: during the Quaternary period, Montecristo remained in contact with the Tuscany's littoral for a shorter period than the other islands, ending up located 63 km from the mainland, on the limit of the continental shelf, closer to Corsica than to the mainland [39].  
In 1971, Montecristo was established as an Integral Nature Reserve, and in 1988, was declared a biogenetic nature reserve by the Council of Europe. Moreover, the island has the status of Special Protection Area (SPA, Directive 79/409/EEC). The land and the adjacent waters, up to 1 km offshore, are controlled by the Coast Guard and the Carabinieri Corps [41,43]. Bathing, diving, fishing, mooring and circumnavigating are forbidden, while landing, berthing and scientific activities are allowed, only under specific conditions and with the permission of the Territorial Office for Biodiversity of the Carabinieri Corps of Follonica [41]. Due to the high protection which Montecristo has undergone, the island is considered one of the most pristine and best-preserved sites of the Mediterranean Sea, being previously identified as a reference site for the ecological quality assessment of the western Mediterranean benthic assemblages on rocky bottoms [44,45].  
The Giglio Island (42.3603\({}^{\circ}\) N, 10.9229\({}^{\circ}\) E) (Figure 1C), being the second in size after Elba, is included in the southern group of the Archipelago, only 14 km from the Italian coast [42,46]. It is an oval-shaped island, characterized by a mountain chain along the north-south axis, and it reaches a height of 496 m above the sea-level. Contrary to Montecristo, the island hosts 1500 residents, spread out among the villages of Giglio Castello, Giglio Porto and Campese [42]. Only 40% of the island is included inside the protected area, while adjacent waters and many terrestrial areas do not have any protection (DPR 22 July 1996) [47]. The areas included in the legislation of the TANP are divided into four zones: (1) zone A of strict reserve, including five rocks (Cappa, Corvo, Mezzo Franco, Pietra Bona, and Le Scole), (2) zone B of general reserve, (3) zone C of general protection and (4) zone D of socio-economic promotion [42]. In general, Giglio is considered to have undergone anthropogenic pressures [47], due to the high flow of tourists during Summer [42], and to be more exposed to potential stress deriving from the mainland.
# Train-Induced Vibration Analysis and Isolation Trench Measures in Metro Depot Structures
###### Abstract  
Many cities around the world are developing over-track buildings above metro depots to achieve efficient and economical land use. However, the vibrations generated by frequent train operations have a significant impact on the over-track buildings. Therefore, the analysis and control of vibrations at metro depots are of great importance. This paper focuses on the train-induced vibration propagation law and the application of vibration isolation trench measures of the over-track building in the metro depot. To this end, a typical metro depot is taken as the research object. The train-track model, used for simulating wheel-rail force, and the track-soil-building model, used for predicting structural response, are established, respectively. Then, the vibration response of the over-track building of the metro depot is explored, and the effects of vibration isolation measures of the open trench and infilled trench in the metro depot are studied. The results show that the train-induced vibration excitation of the metro is mainly concentrated in the range of 1 to 80 Hz, and the predominant frequency range of the floor vibration is 25 to 50 Hz. The vibration response of the floor is mainly affected by the stiffness. The larger the floor area, the smaller the vertical natural frequency, and the wider the range between the train vibration excitation areas, the more prone to resonance. In addition, the vibration isolation effect of the open trench is better than that of the infilled trench. The primary factor affecting the vibration isolation performance of open trenches is their depth; the influence of trench position and width on the vibration isolation performance is weaker compared to the depth. In the predominant frequency range of floor vibration, the overall vibration isolation effect of the flexible infilled trenches is better than that of the rigid infilled trenches. The main factor affecting the vibration isolation effect of the infilled trenches is the impedance ratio of the material. Among the six kinds of filling materials selected in this paper, the barrier effect of gravel is the worst, and the barrier effect of foam is the best. Using the measure of a foam infilled trench, Z-vibration levels of floors can be reduced by 8.6-13.9 dB.  
metro depot; open trench; infilled trench; vibration response +
Footnote †: journal: Applied Sciences
# Impact of Grounding Modeling on Lightning-Induced Voltages Evaluation in Distribution Lines
## 4 Electrical Grounding Modeling
Thus, in this paper, the frequency-dependence of the soil parameters is considered in the grounding modeling. Use is made by the formulations proposed in [31], since a CIGRE Brochure has suggested them [51]. Equations (4) and (5) illustrate the formulation. \[\sigma(f)=\sigma_{0}+\sigma_{0}h(\sigma_{0})\Big{(}f\times 10^{-6}\Big{)}^{\gamma} \tag{4}\]  
\[\epsilon_{r}(f)=\epsilon_{r\infty}+\frac{\tan(\pi\gamma/2)\times 10^{-3}}{2\pi \epsilon_{0}(10^{6})^{\gamma}}\sigma_{0}h(\sigma_{0})f^{(\gamma-1)} \tag{5}\]  
where \(\sigma(f)\) is the frequency-dependent soil conductivity (in mS/m), \(\sigma_{0}\) is the low-frequency soil conductivity (in mS/m), \(\epsilon_{r}(f)\) is the frequency-dependent soil permittivity and \(\epsilon_{0}\) is the vacuum permittivity. To obtain mean results (more details about it in [31]), one should use \(h(\sigma_{0})=1.26\sigma_{0}^{-0.73}\), \(\gamma=0.54\) and \(\epsilon_{r\infty}=12\). As specified before, the calculation of induced voltages is performed directly in the time domain; however, \(Z(\omega)\) is a frequency domain quantity. Thus, the well-known Vector Fitting (VF) approach is used for fitting the calculated frequency domain grounding response with rational function approximations [20]. The passivity is enforced by perturbation [21]. Finally, based on the obtained rational function, it is possible to synthesize an electric network that can be promptly included in the time-domain simulation. It is important to note that this electric circuit generates the same frequency response as the harmonic grounding impedance provided by HEM. Thus, it includes reactive and electromagnetic wave propagation effects.
## 3 Results and Discussion
### Comprehensive Discussion of Test Results
In addition, there is ultra-lightlightweight concrete with a unit weight of less than 1000 kg/m\({}^{3}\); its strength is less than 6.9 MPa and its thermal conductivity is less than 0.3 W/m\(\cdot\)K, and it is mainly used for heat insulation. Figure 17: Compressive strength of the textile-sludge-based LWA concrete. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Literature** & **Raw Material** & **LOI** & **Water Absorption** & **Particle Density** \\  & **(\%)** & **(\%)** & **(\%)** & **(g/cm\({}^{3}\))** \\ \hline
[16] & Reservoir sediments and wastewater treatment sludge & 9.8–28.9 & 1.2–20.3 & 0.41–1.63 \\
[17] & Sediment clay and paper sludge & 6–43 & 2–30 & 0.66–1.93 \\
[18] & Reservoir sediments and tile grinding sludge & 3.5–6.7 & 0.6–13.4 & 0.43–2.1 \\
[41] & Water treatment sludge & - & 0.5–15 & 0.65–2.05 \\
[11] & Water treatment sludge and acid clay & - & 2.5–20 & 0.8–1.2 \\ This study & Water purification sludge and textile sludge & 9.74–21.19 & 9.18–22.02 & 0.54–1.23 \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Comparison of test results of sintered lightweight aggregates with related literature. insulation, such as roof insulation or firewalls. It can be seen from Table 7 that under the condition of a sintering temperature of 1150 \({}^{\circ}\)C, the particle density of the sintered LWA was greater than 1.0 g/cm\({}^{3}\). However, under the conditions of sintering temperatures of 1175 \({}^{\circ}\)C and 1200 \({}^{\circ}\)C, the particle density of the sintered LWA was less than 1.0 g/cm\({}^{3}\). From this point of view, the textile-sludge-based LWAs sintered in this study were more suitable for secondary structural LWAC or thermal insulation LWAC.
# An Improved Forwarding of Diverse Events with Mobile Sinks in Underwater Wireless Sensor Networks
## 4 Problem Statement and Motivation  
This section is summarized in following points.  
* Initially, we present a comprehensive analysis on the ranges of forwarding functions defined in previous protocols. We have identified problems in those forwarding functions and redefined them in next section. These redefined forwarding functions causes much better and systematic forwarding.
* In second part of this section we explain broadcasting overhead issue in deep sea acoustic networks and motivation for event segregation approach.
# Ionospheric Polarization Techniques for Robust NVIS Remote Sensing Platforms
## 5 Results
### E\({}_{\text{b}}\)/N\({}_{0}\) CDF According to Polarization Techniques  
First of all, we measured the relationship between the E\({}_{\text{b}}\)/N\({}_{0}\) received from the ordinary and extraordinary waves and the E\({}_{\text{b}}\)/N\({}_{0}\) post-processed by the application of polarization techniques. The E\({}_{\text{b}}\)/N\({}_{0}\) of the signal frame received is calculated as:  
\[\frac{E_{b}}{N_{0}}(dB)=\text{SNR}(\text{dB})+10\cdot\log 10(B)-10\cdot\log 10( Rb), \tag{3}\]  
where the Rb is the bitrate of the signal (depending on the modulation order test), B is the noise bandwidth where we take the measurement of the bit error rate (BER) (which in our case is 2.3 kHz), and SNR is the signal noise ratio of the signal.  
To analyze the relationship, we make use of the cumulative distribution function (CDF). In Figure 6, we can see the CDF where it represents the probability to receive a given E\({}_{\text{b}}\)/N\({}_{0}\) value depending on whether it is received by the ordinary or extraordinary waves or by the application of a polarization technique. The \(y\)-axis shows us the probability P(E\({}_{\text{b}}\)/N\({}_{0}\) < Xo) of receiving an E\({}_{\text{b}}\)/N\({}_{0}\) less than or equal to value Xo of the \(x\)-axis. The graphic is obtained with the received signal of all power transmissions, which in this case is of a 4 QAM.  
First of all, we can see in Figure 6 that if we receive our signal by the ordinary and extraordinary waves, we have a slightly higher probability to receive a higher E\({}_{\text{b}}\)/N\({}_{0}\) by the ordinary layer. In the case of using a polarization technique, the selection combining technique looks to be the best option to always receive the highest E\({}_{\text{b}}\)/N\({}_{0}\) of the ordinary and the extraordinary layers. In the worst case, with the equal-gain technique, depending on the electromagnetic noise, we can obtain the same E\({}_{\text{b}}\)/N\({}_{0}\) as the lower E\({}_{\text{b}}\)/N\({}_{0}\) of the ordinary or extraordinary layer. In contraposition, in the best case, we can obtain 3 dB more than the selection combining technique in a probability of 1%. Despite this low probability,  
Figure 6: Bit energy to noise spectral density (E\({}_{\text{b}}\)/N\({}_{0}\)) cumulative distribution function (CDF) of 4 QAM at 50 W.  
we have a 20% probability to obtain a higher E\({}_{\text{b}}\)/N\({}_{0}\) than selection combining, as we can see in Figure 6. Furthermore, we have a 35% probability to obtain the same results as selection combining.
## 3 Literature Reviews
### LEACH-Based Secure Routing Protocols
#### 3.3.3 Ms-Leach  
MS-LEACH was proposed to enhance the security of SLEACH by providing data confidentiality and node-to-CH authentication using pairwise keys shared among nodes. Figure 4 shows the protocol.  
Step 1 and 2 are similar to SLEACH. In step 3, pairwise keys are generated between the CH and its member nodes. In step 4, the CH unicasts a TDMA schedule **sched** encrypted with the pairwise key and a counter to each member along with the MAC of the counter and the encrypted form of the TDMA schedule calculated with the pairwise key sent.  
In steady-state phase, every member sends the encrypted form of its measurement data and id calculated using the pairwise key and counter value to the CH along with the MAC value of the counter and the encrypted form of the node's id and its measurement data calculated also using the pairwise key. In step 6, the CH encrypts its id and aggregated data using the key \(K_{H}\) and counter shared with BS and also compute MAC of counter and the encrypted message using \(K_{H}\). Then it sends the encrypted  
Figure 3: SecLEACH protocol.  
Additional symbols denote:  
* Counter;
* The symmetric last key chain held by BS preloaded in each node;
* A family of pseudo-random function.
## 6 Evaluation and Analysis
### Performance Evaluation on the Success Probability and the Max Traffic Supported
the success probability is required to exceed 80%. The _MAX_ refers to the max average keys for one request, which can be supported by the resources. The results of the max number of requests supported per minute (_MNR_) for different algorithms on the four topologies are depicted in Figure 5b, where the \(\varpi\) is fixed as 100 kbits and the success probability is required to exceed 80%. The proposed algorithms are superior to the benchmark algorithms in terms of _MAX_ and _MNR_. For example, the MS-TAR algorithm can increase the _MAX_ by 70.1% compared to Benchmark-LFU on the six-plane Star topology. The LF-TAR algorithm can increase the _MNR_ by 69.5% compared to the Benchmark-LFU on the eight-plane Delta topology. This is because the proposed algorithms can save the secret keys in the QKPs of links on the abstracted topology as well as can reduce the key wastage both in the key processing stage and in the key relaying stage. It should be noted that the _MAX_ and _MNR_ are equal to 0 for Benchmark-GFN and Benchmark-GFU on the six-plane Delta topology. The reason is that the routing success probability is less than 80% on the six-plane Delta physical topology without GEOs, where some ground stations cannot be linked with quantum channels at certain moments. The proposed algorithms will not face this problem due to the existence of the abstracted topology and the utilization of the classical channels. The proposed algorithms have a stronger improvement effect on the Delta constellation compared to the benchmark algorithms. This is because the Delta constellation is poor in the coverage of the selected ground stations. In this situation, the benchmark algorithms are extremely weak, because it cannot save the keys in QKPs of links on the abstracted topology, resulting in the failure of requests for the ground stations connected to few or no satellites at certain moments. The LF-TAR algorithm performs similarly to the MS-TAR algorithm in terms of the _MAX_ and _MNR_, and they perform better than the GF-TAR algorithm due to the existence of GEO-based QKD. Hence, our proposed algorithms perform superior to the benchmark algorithms in terms of the success probability and the max traffic supported. The LF-TAR algorithm is the best compared to other proposed algorithms, which can fully utilize the characteristics of both LEO and GEO.
## 3 Results and Discussion  
### BET and SEM Results  
The structural parameters of the three selected carbon materials are shown in Table 1. The average values were determined by performing three tests. The BET surface areas of RHA, BC, and SC were 354.1 m\({}^{2}\)g\({}^{-1}\), 9.2 m\({}^{2}\)g\({}^{-1}\), and 148.3 m\({}^{2}\)g\({}^{-1}\), respectively. RHA had the largest specific surface area, and BC has the least specific surface area. The surface morphologies of RHA, BC, and SC are shown in Figure 2. At 100 k magnification, the surface morphology of the three types of biochar were similar. The surface morphology appeared cracked, characterized by a densely, randomly arranged network structure. This structure could easily contact the reaction gas. The active elements and related chemical bonds on the carbon surface were activated and formed more reactive sites, so that the biochar achieved  
Figure 1: Diagram of the denitration system.  
a higher nitrogen oxide conversion rate at high temperature. As shown in Table 1, the pore volumes of RHA, BC, and SC were 0.24 cm\({}^{3}\)g\({}^{-1}\), 0.02 cm\({}^{3}\)g\({}^{-1}\), and 0.12 cm\({}^{3}\)g\({}^{-1}\), respectively. According to the data, the pore volume of RHA was relatively larger than those of SC and BC is. The volume of the surface pores may be related to the denitration rate, which is affected by the concentration of reaction gas. An experimental analysis was performed.
# Improved Algorithm to Detect Clandestine Airstrips in Amazon RainForest
## 2 Materials and Methods
### Performance Metrics  
As in the original work, to enable comparison in this study, a predicted location is considered a true positive (TP), or a correct detection, if it is within a certain distance threshold from a previously mapped location. Conversely, a predicted location is classified as a false positive (FP) if no mapped location exists within the chosen distance threshold. Finally, a mapped location is considered a false negative (FN) if no predicted location falls within the defined distance threshold.  
To ensure the effectiveness of this metric, only one correct detection is considered per mapped location. For example, if two predicted locations are within the distance threshold of a mapped location, only one correct detection will be counted.  
When analyzing the impact of detections, it is evident that a false negative carries more weight than a false positive. A false negative means that a landing strip was not detected by the algorithm, implying that a potential focal point of illegal activity would not be identified by authorities. On the other hand, a false positive indicates a predicted location that does not correspond to a real landing strip, which is a less significant error since all locations must be visually validated by authorities. However, the number of false positives should be controlled, as a higher number would delay the visual validation process.  
Therefore, to evaluate which network composition produces superior results, the recall metric will be used, defined as follows:  
\[Recall=\frac{TP}{TP+FN}. \tag{2}\]  
The recall metric will be used to determine how many landing strips were detected by the algorithm in relation to the total number of landing strips. Additionally, the number of false positives will be analyzed to minimize such errors. Thus, the best composition will be the one that achieves the highest recall and the lowest number of FPs.  
A distance threshold of 1500 m between predictions and actual targets will be used to calculate performance metrics. This is because landing strips, being of considerable length, may have predictions that do not exactly coincide with the center or any specific point of the strip. A smaller distance could result in counting errors, as a prediction that represents a point on the strip might still be considered incorrect if it is not exactly at the center.
## 2 Deorbiting Technologies
The force of the drag sail is almost an exponential function of the altitude (as the atmospheric density). The thrust of the electric propulsion system is independent of the altitude. The force of the tether is calculated for a 45\({}^{\circ}\) orbital inclination, it is rather constant with altitude (slightly decreasing, <10% in LEO) and it is almost double that of the electric thruster. The solar sail force is negligible compared to the other devices (except when the drag sail loses usefulness), thus it is not considered a viable option. Therefore, for the rest of the paper, the term sail will be associated with aerodynamic drag sail. The drag sail is the most effective at very low altitudes while the tether is potentially the most performing solution at the majority of altitudes. Comparing the tether with the electric propulsion system (as it is the most similar) for different inclinations for 10 kg of device mass, we obtain the results presented in \[p_{rad}=I/c \tag{2}\]1 In this case, for the electric propulsion system the propellant mass together with its corresponding structural mass \(m=(1+k)m_{p}\), \(k=0.12\), have been also included considering a deorbiting from 750 to 200 km. It is possible to see that the superiority of the tether vanishes approaching the polar orbit and remains below the electric thruster for a sun-synchronous orbit, which is, at the moment, one of the most frequent in LEO. \[p_{rad}=I/c \tag{2}\]2 Comparison of different forces produced by different deorbiting devices (10 kg mass) as a function of altitude.
# Simulation and Design of Three 5G Antennas
## 3 Design of 5G Microstrip Array Antennas
### Design and Simulation of 4 \(\times\) 4 Antenna Units
#### 3.2.2 The Design and Simulation of the Feeding Network  
In the actual design of array antennas, the excitation of the antennas is typically achieved through feeding networks, and it is essential to consider principles such as wide bandwidth and simplicity in the design.  
Series feeding involves connecting individual antenna units in a serial manner via feed lines. However, the coupling between these units limits the operating bandwidth, resulting in a relatively narrow frequency range. In contrast, parallel feeding uses a power distributor to allocate input power to antenna units in specific proportions [24]. This approach offers a simpler and more easily implementable structure and achieves a broader frequency range. Nevertheless, it comes at the cost of a larger footprint for the feeding network. Considering the losses in the feed lines, antenna efficiency may be reduced.  
In the design of the feeding network, a quarter-wavelength impedance transformer is introduced to achieve impedance matching for the circuit. The impedance matching principle is illustrated in Figure 13.  
Figure 12: The simulated radiation pattern in the xoz plane at 3.5 GHz.  
Figure 13: Impedance matching principal diagram.  
To achieve impedance matching for \(Z_{\text{in}}=Z_{0}\), it is essential to meet the requirements outlined in Equation (27).  
\[Z_{01}=\sqrt{Z_{0}R_{\text{L}}}, \tag{27}\]  
To achieve a wide bandwidth and optimal matching characteristics, the incorporation of a multi-section impedance transformer is required [25]. In this instance, a T-type power divider structure is employed to facilitate the design of the multi-section impedance transformer. Figure 14 serves as an illustrative representation of the principles underlying the T-type power divider structure.  
To achieve impedance matching for the T-type power divider, it is necessary to satisfy Equation (28).  
\[Y_{\text{in}}=\text{jB}+\frac{1}{Z_{1}}+\frac{1}{Z_{2}}=\frac{1}{Z_{0}}, \tag{28}\]  
As illustrated in Figure 15, we have a parallel-fed T-junction structure composed of a 50 \(\Omega\) microstrip line, a 100 \(\Omega\) microstrip line, and a quarter-wavelength impedance transformer.
## 3 Results/Validation  
Two subsurface volumes have been chosen to validate that the methodology integrates into the workflow between publicly available data (SITG) and the GIS frontend: a first one being nearby the main train station (Cornavin, 0.32 km\({}^{2}\)) and a second one located around the Arve river (PAV, 0.31 km\({}^{2}\)).