esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 DoV Estimation: Description of the Methods
### Determination of the DoV Using the GNSS-LEV Technique
In addition, the top 1 m portion of the iron rods was isolated and protected from soil suction using a plastic tube coating (the white tube visible in the inset of Figure 4). The closed leveling loop shown in Figure 1 has an approximate length of 4.8 km and was measured with high precision spirit leveling in one day by two teams, using the digital levels Trimble DiNi12 and Leica DNA03 (first class: 0.3 mm/km). The different sections of the loop were measured forward and backward obtaining section closing errors well within the 1 mm/km limit overall sections. Performing a proper error propagation, a final 0.9 mm closure error was determined over the entire loop. At Noto observatory, the measurements were carried out in July 2014. The firmer terrain conditions and the availability of stable manmade artifacts made the use of metal rods to materialize the GNSS baseline endpoints unnecessary. However, no path directly connecting the East and North endpoints could be found. As a consequence, the high precision spirit leveling could not be carried out in a closed loop. The total length of the leveling loop amounts approximately to 2.4 km. The loop was measured forward and backward and it is represented in Figure 2. The measurements were carried out in two days by only one surveying team equipped with a Leica DNA03 digital level. The maximum discrepancy recorded between forward and backward measurements was 0.6 mm over a 600 m section, which is well compatible with the reference standard deviation of 1 mm/km for leveled height differences. Medicina and Noto leveling data sets were processed using STAR*NET software [28]. As for the GNSS surveys, at both sites, 8 h static sessions were carried out during the leveling surveys, using Trimble 5700 receivers and Leica AT504 choke ring antennas. The data were processed using Bernese GPS software [29]. The RMS errors obtained for the Up component downstream of data processing are in the range of 0.2 to 0.4 mm 95% for both sites. We consider these estimates too optimistic and therefore we prudentially account the above-mentioned uncertainties on GNSS-derived height differences. Figure 4: Zeiss Ni1 analogic measurement of the height difference between GNSS-ARP and the South leveling bolt at site Medicina. The inset shows the reference height marker: a bolt on top of a 1.5 m coated metal rod hammered into the ground. The GNSS antennas were set up in close proximity to the baseline endpoints (at a distance of less than 2 m). The height difference between the GNSS Antenna Reference Point (ARP) and the leveling benchmark was measured with a first class Zeiss Ni1 analogical level, which was set up at the same height of the ARP in the operating range of the micrometer level (Figure 4).
# Nanotechnology Solutions for Controlled Cytokine Delivery: An Applied Perspective
## 3 Nanoparticles as Cytokine Delivery Systems
### Types of Nanoparticles for Cytokine Delivery
#### 3.1.1 Polymeric Nanoparticles
The arginylglyglyaspartate acid (RGD) peptide was used as a targeting ligand to functionalize the nanocarriers. Therefore, the delivery of IL-10 allowed for the inhibition of pro-inflammatory cytokines, when compared to the empty nanoparticles. An important parameter that was evaluated in this study was the half-life of the cytokine, which extended to \(8.59\pm 0.21\) h, much longer than free IL-10 (\(0.58\pm 0.06\) h) [41]. Depending on the application, this parameter is essential for the clinical pharmacokinetics of the therapeutic route, yet it is not always assessed. The use of cytokines has also been extensively studied in tissue regeneration, since they are essential for proliferation and differentiation of cells in this process [49]. However, their low local concentration and short half-lives limit their application. [PERSON] and co-workers developed self-assembled chitosan/Heparine (CSO/H) nanoparticles that could load vascular endothelial growth factor (VEGF) to stimulate proliferation in vitro and vascularization in vivo [15]. Despite the aforementioned advantages of chitosan, the in vivo application of this biopolymer is sometimes limited, due to poor pH stability at values above 6.5 and considering that many cytokines need to be at pH 7.4 to be active. However, by using a low molecular weight chitosan soluble at physiological pH, the authors demonstrated high cytokine encapsulation efficiency at around 90% (tested also for stromal cell derived factor-1\(\alpha\)), able to preserve cytokine's bioactivity for tissue regeneration [15]. This indicates that chitosan-based NPs could be an appropriate system for loading and delivery of other cytokines [15]. Furthermore, the CSO/H nanoparticles demonstrated to be uniform in size and within the optimal range (50-150 nm) for the design of nanoparticles for drug delivery purposes, a feature not always obtained with particles constituted by other molecules [15].
# An Overview of Emergency Communication Networks
## 5 Sea Ad Hoc Network (SANET)
### Summary of Network Development Status
#### 3.2.3 Hybrid Networks
In view of the earthquake fieldwork, China Earthquake Administration proposed alleviating the problem of temporary communication terminals by building a 4G emergency command and dispatch system in severely affected areas, and realizing the functions of on-site personnel scheduling, real-time video transmission, and on-site data transmission by building a broadband emergency cluster private network system [116]. Narrowband networks represented by PDT and TETRA have the characteristics of low carrier frequency, good wireless transmission, strong single-station coverage ability, and high system reliability. In contrast, the broadband TrunC network based on the B-TrunC standard can provide multimedia cluster scheduling capability, including video for private network users. The broadband-narrowband fusion network architecture can integrate these complementary characteristics, and provide a more reliable task assurance in the mission-critical cluster command and emergency rescue dispatch by utilizing the multiple reliability of the multi-mode fusion network. As a result of the upgrading of broadband cluster private network technology, IoT technology and high reliability and low delay technology based on 5G characteristics will gradually enter the application field of the private network, which will lead to a brighter future for the development of broadband-narrowband converged cluster private networks.
# Optimized Wireless Sensor Network Architecture for AI-Based Wildfire Detection in Remote Areas
###### Abstract  
Wildfires are complex natural disasters that significantly impact ecosystems and human communities. The early detection and prediction of forest fire risk are necessary for effective forest management and resource protection. This paper proposes an innovative early detection system based on a wireless sensor network (WSN) composed of interconnected Arduino nodes arranged in a hybrid circular/star topology. This configuration reduces the number of required nodes by 53-55% compared to conventional Mesh 2D topologies while enhancing data collection efficiency. Each node integrates temperature/humidity sensors and uses ZigBee communication for the real-time monitoring of wildfire risk conditions. This optimized topology ensures 41-81% lower latency and 50-60% fewer hops than conventional Mesh 2D topologies. The system also integrates artificial intelligence (AI) algorithms (multiclass logistic regression) to process sensor data and predict fire risk levels with 99.97% accuracy, enabling proactive wildfire mitigation. Simulations for a 300 m radius area show the non-dense hybrid topology is the most energy-efficient, outperforming dense and Mesh 2D topologies. Additionally, the dense topology achieves the lowest packet loss rate (PLR), reducing losses by up to 80.4% compared to Mesh 2D. Adaptive routing, dynamic round-robin arbitration, vertical tier jumps, and GSM connectivity ensure reliable communication in remote areas, providing a cost-effective solution for wildfire mitigation and broader environmental monitoring.  
2025  
2025
## 3 Mathematical Model
### Grid Independence Verification  
To exclude the influence of the number of mesh cells in the computational domain on the simulation results, a grid independence verification was performed with four different grid sizes, as shown in Table 5. The result of the model with 3,135,433 cells was used as a reference. As the number of grids increased, the relative error of the CHTC on the exterior surface varied insignificantly. The effect of the grid number on the simulation results could be neglected with less than 7.69% difference. Considering the computing  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Item**} & \multirow{2}{*}{**Weather**} & \multirow{2}{*}{**Wind**} & \multirow{2}{*}{**Air**} & \multirow{2}{*}{**Speed**} & **Air** & **Air Thermal** & **Air Specific** & **Air** \\  & & & & **Speed** & **Density** & **Conductivity** & **Heat** & **Kinematic** \\  & & & & **(m/s)** & **(kg/m3)** & \(\times\)10 - 2/(Wi/(m\_K))** & **(kJ/(kg\_K))** & **Viscosity** \\ \hline I & Normal & West & \(-\)10 & 3 & 1.342 & 2.360 & 1.0090 & 1.243 \\ II & Snowy & West & \(-\)20 & 5 & 1.395 & 2.279 & 1.0090 & 1.161 \\ II & cold wave & Windy & West & \(-\)27 & 10 & 1.436 & 2.255 & 1.0118 & 1.104 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Simulation conditions.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Type** & **Mathematical Model** & **Definition** \\ \hline Continuity equation & \(\frac{\partial\overline{V}_{i}}{\partial x_{i}}=0\) & \(\overline{V}_{i}\) averaged velocity vector \\ \hline Momentum equation & \(\frac{\partial\left(\rho\overline{V}_{i}\right)}{\partial t}+\frac{\partial \left(\rho\overline{V}_{i}\overline{V}_{j}\right)}{\partial x_{j}}=-\frac{ \partial\overline{p}}{\partial x_{i}}+\frac{\partial}{\partial x_{j}}\left( \mu\frac{\partial\overline{V}_{i}}{\partial x_{j}}-\rho V_{i}^{\prime}V_{j}^{ \prime}\right)\) & \(\overline{T}  
speed and the accuracy of the results, it is reasonable to create 3,135,433 cells for discretizing computational domain in the numerical simulation.
## 2 3 GPP Reference Model of Antenna Patterns
This fact is presented in Figure 2. In the azimuth plane, changes in the direction of the main lobe for different directions \(\Phi_{0}=0^{\circ}\), \(\Phi_{0}=30^{\circ}\), and \(\Phi_{0}=60^{\circ}\) are 26.2 dBi, 24.9 dBi, and 20.9 dBi, respectively. Changes in the direction of the main lobe are also accompanied by a change in the directivity of the antenna array. For the analyzed set of structural parameters, the changes in the pattern directivities are shown in Figure 3.  
As shown in Figure 2, changing the direction of the beam affects the change in the main lobe level. Figure 3 shows that, for the analyzed antenna patch, the change in directivity can be as much as 5 dB for different \(\Phi_{0}\) values. This effect should be considered when using simple models of antenna patterns. Figure 1: Three-dimensional 3 GPP pattern of reference beam [23]. Figure 2: Reference and exemplary 3 GPP interfering beams in the azimuth plane.
## 2 A Generic Multi-Path and Multi-Channel Proposal for HWMP
### Multi-Channel Mechanism  
The objective of implementing multi-channel techniques is to increase the network performance mainly in demanding situations, that is when a high amount of data traffic is being transmitted by the network. Our proposal implements traffic differentiation in the following way. First, we have used different channels for control and data traffic, where just one channel is assigned to the control traffic (route management). On the other hand, as explained in the previous section, the different data traffic is mapped to the available paths depending on its priority, and a different channel is assigned to every path. Thus, each channel will have a specific metric value, which will be useful for future routing decisions.  
The airtime link metric is cumulative and updated in each node by the Path Request (PREQ) and Path Reply (PREP) messages. Therefore, to propagate the ALM metrics according to their respective channel, it is necessary to make modifications to the structure of the PREQ and PREP messages, as can be seen in Figure 4. The modification consists of the inclusion of the path identifier field, the metric value for the control channel, the number of available paths (channels), and the metric value for each of them.  
By default, the HWMP protocol performs a broadcast of PREQ messages for path discovery through all the available interfaces in the node. Therefore, with the multi-channel implementation, the number of broadcast messages could be increased excessively. This is the reason why a specific channel has been defined for control messages, thus avoiding a high and unnecessary load on the data channels.  
To implement the path/channel allocation, the applications are marked from the source with an Enhanced Distributed Channel Access (EDCA) category [4]. EDCA distinguishes between four types of traffic according to their QoS needs. The types of traffic with higher priority are mapped to the highest categories of EDCA (voice or video), and vice versa. Therefore, intermediate nodes are able to select the next hop node from their routing table among the multiple available paths to the destination and transmit the application traffic over the correct channel.
## 1 Introduction
### Modeling the Strain Rate Sensitivity of Multiphase Steels  
Most materials exhibit some sensitivity to the strain rate at which they are deformed. In the case of steels, numerous studies have shown that most of them are hardened when they are deformed at higher rates [21].  
Strain rate hardening is included in several crystal plasticity models where an ideal Schmid law is substituted by the viscoplastic strain rate sensitivity approach of [PERSON] [22]. This approach is equivalent to the usage of a factor that multiplies the stress response under quasi-static conditions (this stress is given by \(\sigma(\dot{\varepsilon}_{0})\), where \(\dot{\varepsilon}_{0}\) is the quasi-static strain rate). Such factor can be calculated as a power of the strain rate, \(\dot{\varepsilon}^{m}\), where the exponent \(m\) is called the strain rate sensitivity exponent:  
\[\sigma(\dot{\varepsilon})=\sigma(\dot{\varepsilon}_{0})\dot{\varepsilon}^{m} \tag{1}\]The Jonson-Cook model [23] uses a slightly different approach, in which strain rate sensitivity is represented by the parameter \(C\) (do not confuse with the stiffness tensor in the VPSC model, represented by \(C\), in bold typeface). The following expression is given for the calculation of the strain rate sensitivity factor:  
\[\sigma(\varepsilon)=\sigma(\varepsilon_{0})\bigg{(}1+C\ln\frac{\varepsilon}{ \varepsilon_{0}}\bigg{)} \tag{2}\]  
In [21], it is shown that the strain rate sensitivity of high-strength steels can be correlated with their elastic limit. After comparing a large number of results from the literature in which high-strength steels are tested at different strain rates, including several studies with high strain rate experiments, it is concluded that those steels with higher yield stress present a lower sensitivity than materials with lower yield stresses. Furthermore, an analytic expression is presented for the estimation of the \(C\) parameter in (2):  
\[C=C_{0}\,\sigma_{y}^{-n_{C}}=313\,\sigma_{y}^{-1.54} \tag{3}\]  
This formula, used in combination with (2), makes it possible to calculate an estimation of the yield stress of high-strength steels at any strain rate without performing specific experiments at different strain rates. This same method is extended to the calculation of critically resolved shear stresses in slip planes in Section 3.
###### Abstract  
In this paper, we study the three-dimensional (3D) trajectory optimization problems of unmanned aerial vehicles (UAV) with a solar energy supply, aiming to provide communication coverage for mobile users on the ground. In general, the higher UAVs fly, the more solar energy they collect, but the smaller the range of coverage they could achieve, and vice versa. How to plan optimal trajectories for UAVs so that more users can be encompassed, while allowing UAVs to collect enough solar energy, is a challenging issue. Moreover, we also consider how geographically fair coverage for each ground user can be achieved. To solve these problems, we designed a multiple solar-powered UAV (SP-UAV) energy consumption model and a fairness model, while designed an observation space, state space, action space, and reward function. Then, we proposed a multiple SP-UAV 3D trajectory optimization algorithm based on deep reinforcement learning (DRL). Our algorithm is able to balance the energy consumption of UAVs to extend the system's lifetime, while avoiding both collisions and flying out of communication range. Finally, we trained our model through simulation experiments and conducted comparative experiments and analysis based on real network topology data. The results show that our algorithm is superior to the existing typical algorithms in coverage, fairness, and lifetime.  
U  
26 March 2023  
14 April 2023  
Accepted: 19 April 2023  
Published: 20 April 2023
## 3 Results
### Stability under Different Tumor Radii  
This section provides a comprehensive analysis of the results obtained for different tumor radii. The models were trained using mean tumor radii of 7 mm and 10 mm, with a wide range of tumor radii from 6 mm to 13 mm. The evaluation focused on examining F1 scores across the range of tumour radii from 7 mm to 12 mm. Notably, both the training and evaluation datasets were free of noise, allowing a comprehensive analysis of the sole effect of tumor radii on the performance of the model. The F1 scores for the different combinations of training and evaluation radii are shown in Figures 10-12. The observations revealed a remarkable trend, indicating that when the models were trained with a mean tumor radius of 7 mm, the best performance was consistently associated with smaller radii, with a marginal increase noted for larger tumor sizes. Specifically, for training and testing with a mean radius of 7 mm, the RF model showed the lowest performance, achieving an F1 score of 0.59, while the SVM achieved the highest score of 0.82 and the ANN an intermediate score of 0.72. Notably, an increased F1 score was observed for the ANN when tested with higher radii (0.95), while the SVM showed a more modest increase, reaching 0.89, and the RF reached a score of 0.8. However, when trained with a mean radius of 10 mm, the F1 scores did not show significant differences, with the SVM, RF and ANN models achieving scores of 0.95, 0.89 and 0.89, respectively. Conversely, when testing with a lower mean tumor radius of 7 mm, the F1 scores experienced a significant reduction, dropping to 0.47 for the SVM, 0.37 for the RF and 0.55 for the ANN. Strikingly, training the models with a wide range of mean tumor radii yielded the most optimal performance for all models except the ANN. In contrast, training with a small mean tumor radius significantly favored the performance of the ANN model.  
Figure 10: Performance of the SVM for a fixed tumor radii ranges, while testing was done on the whole range of tumor radii.  
Figure 9: Performance of the ANN for fixed noise levels on different test data. The blue circular markers indicate a match in noise level between test and training data.
# Economic Analysis of a Zero-Water Solar Power Plant for Energy Security
###### Abstract  
Water dependency of power plants undermines energy security by making power generation susceptible to water scarcity. This study evaluates the economic performance of a novel dry-cooling system for a water-independent solar power plant. The proposed cooling system is based on the concept of earth-air heat exchangers, approaching zero environmental impact. The viability of the proposed design is discussed based on both costs and benefits, and it is compared to both conventional dry- and wet-cooling systems. The installation costs of the plant are found to be EUR 13,728/\(k\)W, resulting in the substantial levelized cost of electricity of EUR 505.97/MWh. The net present value of the studied design assuming a water-cost saving of EUR 1/m3 is found to be MEUR -139.59. Significantly higher water prices in the future might eventually make the proposed system economically attractive when compared to water-cooling systems. However, the new system would require drastic modifications to become more attractive when compared to existing dry-cooling systems. Specific possibilities to improve it for zero-water use in thermoelectric power plants are further discussed.  
water scarcity; dry cooling; solar power plants; zero-water plants; economic analysis; energy security +
Footnote †: journal: Applied Sci.
# Effect of Soil Box Boundary Conditions on Dynamic Behavior of Model Soil in 1 g Shaking Table Test
## 4 Conclusions  
One of the important requirements for performing the 1 g shaking table test or the centrifuge test is to use a soil box that can simulate the free field behavior of the soil as closely as possible. The RB is known to have some boundary problems due to the constraint of the lateral displacement of the model soil. In order to better simulate the model soil subjected to earthquake loadings, two types of soil boxes, the RB and the LSB, were compared for sine waves and artificial seismic waves. This study is focused on comparing PGA and response spectrum for the same soil to evaluate the performance of the RB and LSB, although there are many aspects in practice. Based on the test results, the following conclusions can be drawn:  
1. For the RB, the amplification of Peak Ground Acceleration and Spectral Acceleration at the center was greater than that of the wall. This implies that the ground model motion is different from free field because the lateral boundary of the RB is constrained, and the reflected wave occurring in the wall generates different stresses to amplify acceleration.
2. In contrast, for the LSB, both the Peak Ground Acceleration and the acceleration spectrum are similar at the same depth in the center and the wall of the soil box, respectively. This indicates that the LSB is better than the RB when performing the 1 g shaking table test for understanding the dynamic behavior of soil.
3. In order to evaluate the possible reduction in the boundary problems, sponges were attached to the side wall of the RB. Although the major amplification period of the wall and the center on the surface showed a slight difference when a sponge was attached to the RB, the center and the wall in the ground model showed similar behaviors, implying that the use of sponges in the RB may mitigate some boundary effects. However, because the rigidity varies with the types of sponges, the material selected for the test contributes to different effects of reducing boundary conditions, and the sponge thickness between 5 cm and 15 cm did not exhibit a significant impact on the result.  
H.K. ([PERSON]) has performed 1 g shaking table tests. [PERSON] has been in charge of organizing and leading the study. [PERSON] and H.K. ([PERSON]) have done some technical analyses. All authors have read and agreed to the published version of the manuscript. This research received no external funding. This study was supported by Chosun University and KHNP, 2020  
**Conflicts of Interest:** The authors declare that there are no conflicts of interest.