esa-sceva/satcom-chunk-collection huggingface dataset:
# Damage Detection Method Based on Continuous Wavelet Transformation of Lamb Wave Signals
## 5 Influence of Environmental Noise  
It is essential to test the noise tolerance of the proposed method for the real-world signals, which may be noisy and can influence the results when damage-scattered peaks are too small. The white noise signals in Gaussian distribution were artificially added to the original damaged signals. A high value of noise, i.e., signal-to-noise ratio (SNR) of 30 dB, was added to all the damaged signals, and envelopes formed by the coefficient of CWT were reevaluated. The signals shown in Figure 20a,b are presented again with SNR 30 dB in Figure 24a,b, respectively. A high influence of the noise in the signals can be observed in damaged-focused region of these plots separately shown in Figure 24c,d, respectively.  
The possibilities for damage existence for all sensing paths in the pulse-echo configuration were evaluated with noisy signals and then fused to get the aggregate damage image. The results for multiple damage scenario with noisy baseline-free signals are shown in Figure 25a,b, respectively, without and with the time compensation. Although the noise has a little influence on the resolution of damage imaging, the proposed method could still accurately locate both the damage, and also estimate the severity of one damage with respect to the other damage.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Pair Location (mm)** & **A1B1** & **A2B2** & **A3B3** & **A4B4** & **A5B5** & **A6B6** & **A7B7** & **A8B8** & \(DI_{m}\big{(}x_{i}y_{i}\big{)}\) \\ \hline D1 (45, –45) & 0.0073 & 0.0060 & 0.0032 & 0.0070 & 0.0024 & 0.0191 & 0.0155 & 0.0201 & \(1.41\times 10^{-17}\) \\ D2 (\(-30,50\)) & 0.0047 & 0.0325 & 0.0172 & 0.0205 & 0.0047 & 0.0064 & 0.0019 & 0.0073 & \(2.30\times 10^{-17}\) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Possibilities of damage existence values at damage locations from all sensing pairs in pulse–echo configuration.  
Figure 24: (**a**) Damaged signal at A8B8 with signal-to-noise ratio (SNR) 30 dB; (**b**) coefficient of CWT with (blue) and without (red) time compensation A8B8 with SNR 30 dB; (**c**) damage-focused region of signal (**a**); (**d**) damage-focused region of signal (**b**).
# Effect of Heat-Treatment Remediation on the Mechanical Behavior of Oil-Contaminated Soil
## 3 Results and Discussion
### Effect of Pollutant Removal Percentage on Permeability  
The permeability coefficient of the original soil was \(3.47\times 10^{-6}\) m/s, so the soil had low permeability. Heat treatment at various temperatures increased the permeability coefficient of the soil to \(4.25\times 10^{-6}\)\(\sim 1.38\times 10^{-4}\) m/s (Figure 6). The permeability coefficients of the 5000 ppm gasoline specimen after heat treatment at three temperatures were between \(6.32\times 10^{-6}\) and \(2.3\times 10^{-4}\) m/s; those of the 10,000 ppm gasoline specimen were between \(1.07\times 10^{-5}\) and \(7.88\times 10^{-4}\) m/s. Therefore, regardless of whether gasoline was added, the permeability coefficient of the soil after heat treatment exceeded that of the original soil specimen. Although treatment at 320 and 560 \({}^{\circ}\)C increased the permeability of the soil, the soil maintained low permeability.  
The permeability coefficient of the soil with 10,000 ppm of gasoline added that was treated at 900 \({}^{\circ}\)C was between approximately \(3.76\times 10^{-4}\) and \(1.65\times 10^{-3}\) m/s; that of the soil with diesel after heat treatment at the three temperatures was between \(1.9\times 10^{-4}\) and \(3.31\times 10^{-3}\) m/s, all consistent with soil with medium permeability. Therefore, high temperature increased the permeability coefficient.  
As plotted in Figure 6, the permeability coefficient of each soil specimen increases with the removal percentage under all operating conditions. Figure 7 demonstrates that the permeability coefficient of the heat-treated soil with diesel is greater than that of the soil with gasoline under the same treatment conditions.  
Figure 5: Comparison of the frictional angles of gasoline and diesel.  
Figure 6: Relationship between pollutant removal percentage and permeability. (**a**) Gasoline; (**b**) Diesel. Note: C: original soil; G: soil with gasoline pollutant; D: soil with diesel pollutant. L: heating temperature is 320 \({}^{\circ}\)C; M: heating temperature is 560 \({}^{\circ}\)C; H: heating temperature is 900 \({}^{\circ}\)C.
## 4 Discussion
### Circulation (\(\Gamma\))  
Examining the circulation values from Figure 10 reveals a distinct trend where the circulation increases significantly with a larger MVG height. This pattern is evident across all the simulations, which were conducted with a consistent boundary layer height. As the height of the MVG increases, a larger portion of it is situated in the faster-moving region of the boundary layer. This interaction with the higher-velocity flow increases the circulation value, leading to this trend. This relationship underscores the influence of the MVG height on the vortex characteristics within the boundary layer.  
When examining the trends for the same MVG height, as observed in the heatmaps of Figure 6, a peak is observed at lower lambda values and higher \(d\) over \(\Lambda\) values. This indicates that, as the inner distance of the MVG pair increases, the circulation also increases, whereas the opposite is true for the periodicity values. Additionally, a link can be made to the results of [PERSON] et al. (2011), where N factors are calculated. In short, the N factor essentially indicates the premature transition from laminar to turbulent flow. There is a strong correlation between circulation and the N factor. The reason for this is that a stronger vortex generates greater shear stresses in the boundary layer, which can accelerate flow destabilization. Furthermore, comparing the circulation values to the potential drag reduction downstream reveals a trend where higher drag reduction corresponds to higher circulation values, with a global Pearson correlation coefficient of 0.45. This is without taking out any outliers, which would show an even stronger correlation. However, no clear trend is observed within the same MVG height, suggesting that circulation is not the primary factor in drag reduction. This presents an interesting dilemma as circulation is crucial for assessing the potential flow destabilization. Consequently, there is a limit to increasing the height of the MVGs concerning the impact on circulation and flow stability. Understanding these relationships is essential for optimizing the MVG design to balance drag reduction and flow stability.
# ISAC towards 6G Satellite-Terrestrial Communications: Principles, Status, and Prospects
## 3 Development Status and Key Technologies of ISTNs
### Development Status  
There are many countries that aspire to achieve the construction of ISTNs as a significant objective. As early as the beginning of the twentieth century, the United States Department of Defense proposed the idea of building an integrated information network between the sky and the earth. It utilizes coordinated LEO satellites for efficient multicast communications, aiming to maximize user communication and provide a secure network environment for a comprehensive battlefield [64]. Europe and other related countries have also launched multiple ISTN projects, including CoRaSat, SANA, SaT5G, etc. [65]. In addition, China has launched a comprehensive project of an integrated information network of space and ground in Science and Technology Innovation 2030 to carry out technological research and development of ISTNs.  
In recent years, international organizations, such as 3 GPP, have established some special working groups to promote the standardization of ISTNs [66]. The development of relevant standards starts from satellite support for basic connectivity capabilities to satellite expansion and performance enhancement until the final large-scale constellation construction, which can realize inter-satellite collaboration and satellite-terrestrial integration. In 3 GPP technical report (TR) 38.811 [66], the deployment scenarios, and channel models of satellite networks are defined. The access to satellite networks as well as the modification and updating of terminals and original terrestrial networks are studied in 3 GPP TR 22.822 [67]. In the R17 standard [68], a complete non-terrestrial network deployment architecture is provided, stipulating the methods of time synchronization, mobility management, link switching, and so on.
secondary sources (electronic waste and jewelry waste) using microorganisms has gained importance in recent years. Studies have reported Au solubilization (20-90%) from printed circuit boards (PCBs) from cell phones and computers by cyanogenic bacteria (_Chromobacterium violaceum_, _Bacillus megaterium_ and _Pseudomonas balezica_) under different culture conditions [29; 30; 31; 32; 33; 34; 35]. In the case of filamentous fungi, there is less information; however, for instance, it has been mentioned that _Aspergillus niger_ is capable of recovering Au from secondary sources such as PCBs from cell phones and computers [36; 37; 38].  
On the other hand, even though Ag has been reported as a highly toxic metal for most microorganisms, some bacteria are able to accumulate and reduce it [39; 40; 41; 42]. Among these bacteria is the mixture of _Acidithiobacillus ferroxdans_ and _Acidithiobacillus thiooxidans_, which is capable of leaching Ag from sulfurrous minerals [43]. Research was also carried out to create biotechnological techniques with which Ag can be recovered from refractory minerals, but to a lesser extent than for Au [44; 45; 46]. Under other conditions, it had been shown that the recovery of Ag by microorganisms from secondary sources is poor. [PERSON] et al. [31] report that _Pseudomonas picoglossicida_ can mobilize around 5% of Ag found in jewelry waste dust in one-day incubation. Similarly, [PERSON] et al. [33] report that _Pseudomonas balezica_ managed to recover 33.8% of Ag from a PCB pulp, with a density of 10 g L\({}^{-1}\) and at pH 9.0.  
Regarding the information about the interaction of Pt with microorganisms, it has been reported that cultures of the halophilic bacteria of the families Halomonasae, Bacillaceae and Idiomarinaceae have recovered 98% of Pt (II) and 97% of Pt (IV) at pH 2, in a time of 3 to 21 h, from solutions of K\({}_{2}\)Pt(II)Cl\({}_{4}\) and K\({}_{2}\)Pt(IV)Cl\({}_{6}\) at 100 mg L\({}^{-1}\)[47]. In addition, for secondary sources of Pt, [PERSON] et al. have reported the recovery of Pt (0.2%) from waste from automobile catalytic converters using cyanogenic bacteria [31].  
As can be seen, most of the mentioned studies are oriented towards bacteria and, in a lesser extent, towards filamentous fungi. Thus, gathering additional information about the interaction of filamentous fungi with Ag and Pt is relevant to find new biotechnological applications.  
The present investigation focused on evaluating the effect of increasing doses of Au, Ag and Pt on the growth of _A. niger_, _Trichoderma harzianum_, _Trichoderma konigiopsis_, _Trichoderma viridescens_, _Trichoderma sp._, _Hypocrea lixii_, _Fusarium oxysporum_ and _Fusarium solani_ in order to use fungal tolerance as a simple tool for the selection of the fungi with the potential to be used in the recovery of Au, Ag and Pt from primary or secondary sources.
# Event-Based Emergency Detection for Safe Drone
## 4 Case Study
### Abnormal Case: Too Late (Motor Fail)  
For the last case we simulated a failure in one of the drone's four motors. Motor failure could be caused by many reasons in real world situations, and is one of the most catastrophic events, since the drone completely loses control. We let one of the motors fail completely right after the drone passed waypoint d and analyzed the response of our event-based controller, as shown in Figure 8a. The drone was not able to arrive at the next waypoint and our controller detected the time-window being exceeded. Figure 8b and Table 4 show more detailed analysis and data about the case.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Path** & \(\mathbf{T_{start}}\) & \(\mathbf{T_{min}}\) & \(\mathbf{T_{max}}\) & \(\mathbf{T_{arrival}}\) \\ \hline
**A** to **b** & 0.00 s & **4.50 s** & **5.50 s** & 5.28 s \\
**b** to **c** & 5.28 s & **9.78 s** & **10.78 s** & 10.32 s \\
**c** to **d** & 10.32 s & **14.82 s** & **15.82 s** & 15.51 s \\
**d** to **e** & 15.51 s & **20.01 s** & **20.01 s** & **x** \\
**e** to F & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 4: The actual numerical time data including \(\mathrm{T_{start}}\), \(\mathrm{T_{min}}\), \(\mathrm{T_{max}}\), and the actual arrival time \(\mathrm{T_{arrival}}\) for the air-collision case. For the first three intervals from A to d it arrived inside the time-window. However, due to the motor failure after waypoint d, the drone struggled to return to its mission path and exceeded the maximum time-window. This type of emergency is extremely dangerous, yet hard to handle.  
Figure 8: _Cont._  
Just like air collisions, motor failures are dangerous. Sometimes collisions can cause motor failures as a secondary effect. The 2D log from Figure 8a resulted in a somewhat similar situation as the one in Figure 7a. The drone totally lost its control and drifted far away from the safe boundaries. Luckily, as in the previous case, the event-based controller was able to detect the abnormality 5.5 s after the moment of incident. Detecting and handling this type of emergency situation is outside the PID controller's ability. We proved that our method is able to cover the shaded areas of PID controllers.
###### Abstract
Therefore, the information gathered by them can be used to evaluate and predict real-time traffic density and compute an accurate map of road traffic density, as well as assist VANET in improving transportation efficiency, and pedestrian comfort, and provide a QoS. Cloud, fog, and edge computing techniques enable the real-time transmission and processing of terabytes of data. The cloud node has a lot of memory and processing power, but the fog and edge nodes  
Figure 1: VANET in Smart Cities. have limited capacity. Additionally, the physical distance between the cloud data center and the fog and edge nodes influences the data transfer rate, and if it is long, it increases latency and potential packet loss. Furthermore, one of the primary goals of VANET is to provide QoS to end users, while infrastructure deployment is the most significant challenge in the traffic improvement application of VANET. In this context, we combined the Capacitated Dispersion Problem (CDP) and vehicular networks in order to efficiently allocate facilities which can result in proper utilization of all facilities as well as timely reaction, which is required for smart cities, to improve the QoS in VANET. CDP aims at maximizing the dispersion of the open facilities while fixing a given capacity threshold to make facility capacity sufficient to meet customers' demands. Since CDP is NP-hard, exact methods may take a long time to guarantee the optimality of a solution when dealing with large instances [8]. Furthermore, because approximate methods such as heuristics and metaheuristics have been demonstrated to be effective and capable of producing high-quality solutions for large-scale and complex real-world problems, optimization techniques such as these are now widely used. In particular, heuristics have a strong potential to offer agility and real-time responses, which are critical for an effective ITS [9]. In this paper, we aim at reaching the following goals: (i) to elaborate a comprehensive overview of vehicular networks; (ii) to provide optimization challenges regarding ridesharing, carsharing, VEC, and traffic improvement applications in VANETs; and (iii) to propose a case study, based on real-life data, which combines a CDP and vehicular networks. The organization of this paper is introduced as follows: Section 2 presents an overview of vehicular networks. In Section 3, we provided optimization challenges regarding ridesharing, carsharing, and traffic improvement applications in VANET. We present a case study and computational results in Section 4. Lastly, Section 5 summarizes our main conclusions and provides future research lines.
# Towards the Unmanned Aerial Vehicles (UAVs): A Comprehensive Review
## 4 UAV Battery Charging  
Drones are currently being used for several applications such as military operations, power lines inspection, forest monitoring, disaster prevention and smart agriculture [57; 67; 68]. Drones carry different types of payloads such as GPS, infrared cameras, batteries and sensors as a delivery vehicle. These drones usually carry high energy batteries e.g., lithium batteries that support flight time ranging from 20-40 min [69]. However, range and endurance are a critical challenge in UAVs due to limited battery capacity. It is not feasible to increase battery size of UAV as it will increase weight, which is another critical concern. Several research studies have addressed battery charging of UAVs but still it requires intensive investigations by research fraternity [16]. [PERSON] et al. [67] suggested three ways to enhance flying time: (i) drones can be equipped with high battery capacity but it can increase the drone weight. (ii) The battery swapping can be achieved after the landing of drone. However, it also causes complexity and high cost of swapping system. (iii) Recharging can be done at the base station of the drone. Charging can be achieved through wired or wireless power transfer (WPT) system [70]. Next, we have briefly discussed WPT techniques.
# Study on Microwave Deicing of Carbon-Fiber-Modified Concrete under Multi-Factor Coupling Effect
## 2 Materials and Methods
### Test Equipment and Method  
As shown in the Figure 4, 1 is the temperature measurement instrument for the edge of the concrete, 2 is the temperature measurement instrument for the center of the concrete, 3 is the microwave generated when the microwave-transmitting device is in operation, and 4 is the ruler with marker scale.  
The lower trumpet of the microwave emitter and the surface height of the specimen were set as 20 mm and 40 mm, respectively, and the length and dosage of carbon fiber were shown in Table 1.  
The absorbance and heating efficiency of different carbon-fiber-modified concrete samples was tested. The concrete surface was not covered with ice in this test.  
\begin{table}
\begin{tabular}{c c c} \hline
**Test Number** & **Fiber Length** & **Fiber Content** \\ \hline PC & 0 & 0 \\
0.1 CFC3 & 0.1 mm & 0.3\% \\
0.3 CFC3 & 0.3 mm & 0.3\% \\
0.6 CFC2 & 0.6 mm & 0.2\% \\
0.6 CFC3 & 0.6 mm & 0.3\% \\ \hline \end{tabular}
\end{table}
Table 1: Microwave deicing test group.  
Figure 4: Schematic diagram of the basic test device.  
Figure 3: Microwave emission source unit.  
At the end of the first test, 0.6 CFC3 carbon-fiber-modified concrete was prepared, and a 10 cm ice layer was deposited on its top surface. A second test was carried out for deicing of the ice layer with heating at different heights.  
On this basis, the third test was carried out on 0.6 CFC3 CFRP specimens at different initial temperatures of \(-\)10 \({}^{\circ}\)C, \(-\)6 \({}^{\circ}\)C and \(-\)2 \({}^{\circ}\)C with a 10 mm thick ice layer.  
The temperature acquisition instrument used in the test was an optical fiber thermometer, and the temperature-time variation curves of the center point (T\({}_{0}\)) and the edge point (T\({}_{1}\)) on the surface of the concrete specimen were obtained.
# Biomolecules from Microalgae and Cyanobacteria: Applications and Market Survey
## 2 Microalgae
### Compositions and Technologies for Photoautotrophic Production of Microalgae and Cyanobacteria
#### 2.3.5 Other Compounds  
Microalgae have also been recognized as an excellent source of vitamins and minerals, some of them having antioxidant properties such as the hydrosoluble vitamins (C, B1, B2, B3, B5, B6, B9, and B12) and fat-soluble ones (provitamin A and vitamins E, D, and K). They also contain nicotinate, biotin, folic acid, and pantothenic acid as well as macrominerals(Na, K, Ca, and Mg) and microminerals (Fe, Zn, Mn, and Cu) [81, 82, 83, 84]. Parts of prokaryotic microalgae are known for their large-scale production of vitamins of commercial interest, such as vitamins B and E, and _Spirulina_ is part of this. In fact, this Cyanobacterium is known to be a rich source of vitamin B12, \(\beta\)-carotene, thiamin, and riboflavin [77].  
Microalgal biomass also contains an abundance of a wide variety of secondary bioactive substances. Within this bioactive diversity, phenolic compounds constitute one of the most numerous and abundant groups of phytochemicals, which exhibit a wide range of biological properties, such as antioxidant, anti-inflammatory, anticancer, antialergic, antidiabetes, antiaging, and antimicrobial properties [39]. Moreover, microalgae and Cyanobacteria have great potential for synthesizing enzymes such as cellulases, galactosidases, amylases, proteases, lipases, phytases, lacases, phosphatases, and antioxidant enzymes, with high potential for several applications [77, 84]. Microalgae also produce phytohormones such as auxin, abscisic acid, cytokinin, ethylene, gibberellins, polyamines, and jasmonides, mainly known to regulate the main physiological processes of plants, terrestrial or aquatic organisms [79, 85, 86], phytosterols [39], and others.