esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Test Results and Analyses
### Pull-Out Load-Slip Curves  
Figure 10 and Table 5 present the characteristic pull-out load-slip curves and their key points of different deformed steel fibers. Steel fibers with the failure modes of fiber breakage would not obtain the characteristic point R.  
Figure 10: The characteristic pull-out load-slip curves of different deformed steel fibers: (**a**) hooked steel fiber; (**b**) crimped steel fiber; (**c**) steel fibers of indentation, milled, and large-end.  
Figure 9: Typical failure modes of pull-out tests with different steel fibers.  
The slip \(s_{\rm d}\) ranged from 0.252 mm to 0.335 mm for hooked-end steel fibers, 0.156 mm to 0.404 mm for indentation steel fibers, 0.241 mm and 0.333 mm, respectively, for CF and CF2, and the same as 0.220 mm for LF and MF. No obvious differences were regularly observed in the \(s_{\rm d}\).  
The slip \(s_{\rm p}\) ranged from 0.760 mm to 1.322 mm for hooked-end steel fibers, 0.156 mm to 0.590 mm for indentation steel fibers, 1.457 mm and 0.944 mm, respectively, for CF and CF2, and 0.314 mm and 0.334 mm, respectively, for LF and MF. The slip \(s_{\rm r}\) ranged from 2.50 mm to 2.74 mm for hooked-end steel fibers, 2.50 mm and 2.46 mm, respectively, for CF and CF2, and 1.01 mm for indentation steel fiber IF2.  
It could be observed that the hooked-end and crimped steel fibers obviously have larger \(s_{\rm p}\) and \(s_{\rm r}\) than indentation, milling, and large-end steel fibers. This is due to their different bonding mechanisms. The hooked-end and crimped steel fibers are flexible in the process of the pull-out test, and they have obvious changes in shape. The bond performance of hooked-end steel fiber mainly depends on the mechanical anchoring of shape deformation at the hooked end. The bond performance of crimped steel fiber is mainly decided by the mechanical anchoring of shape deformation of the crimps. Their energy dissipations are dependent on the shape deformations of the fiber with a small damage of mortar.  
The indentation, milling, and large-end steel fibers are rigid with less changes in shapes and lengths in the test. Their bond performances are mainly dependent on the mechanical anchoring of fiber surfaces. Their energy dissipations largely depend on the failures of mortar near the interface. These lead to small \(s_{\rm p}\) with large damages of mortar observed in the tests.
# An Adaptive Security Framework for Internet of Things Networks Leveraging SDN and Machine Learning
## 5 Enhanced SCAFFOLD Protocol
### SCAFFOLD Algorithm  
The operation of the Enhanced SCAFFOLD protocol is precisely defined through high-level algorithm pseudocode. Figure 5 shows an abstract specification in a Python-like language that concisely captures the key procedures executed by the IoT nodes, SDN controller, and network switches to establish secure communication channels, encrypt data, detect attacks, and mitigate threats. The pseudocode spans the major protocol components, including preliminary key exchange, secure channel creation, traffic encryption, controller monitoring, attack detection via ensemble learning, precision mitigation enabled by SDN, and periodic reauthentication. Modular functions describe the critical steps within each stage, such as generating keys, deriving session keys, encrypting packets, extracting flow features, classifying flows, and installing blocking rules. The comment text provides additional insights into the logic. This well-structured pseudocode provides a high-level definition of the Enhanced SCAFFOLD protocol, complementing the detailed mathematical model and formal protocol specification. Execution of the pseudocode algorithms helps validate the design and surface potential issues prior to implementation.
# Towards Bio-Hybrid Energy Harvesting in the Real-World:
## 5 Research Progress in Biomechanical Energy-Harvesting Technologies
### Energy Harvesting from Non-Human Living Organisms  
In addition to human-centered applications, biomechanical harvesters have also been tested for powering up cyborg-animal applications, targeted either toward environmental monitoring or observation of physiological parameters of the host animal. [PERSON] et al. [42] reported a vibration energy scavenger for _Cotinis nitida_ (Linnaeus) that could extract energy from the beetle's wing vibrations without affecting its movement. [PERSON] et al. [301] implanted a TENG-based energy harvester in a living rat for powering up a pacemaker. [PERSON] et al. [293] reported developing an electromagnetic generator implantation in the subcutaneous area or abdominal cavity of chicken-like birds and obtained a maximum 7 V peak-to-peak signal at 560/min of flapping of wings. [PERSON] et al. [321] presented an energy-harvesting module containing a flexible piezoelectric beam for extracting energy from fish movement to power up an acoustic transducer. Similarly, [PERSON] et al. [294] utilized a \"magneto-acoustic\" resonator that converts low-frequency motions, ranging from 0.15 to 100 Hz into high-frequency acoustic signals. [PERSON] et al. [322] reported a mountable energy harvester for bees that extracts energy from wing vibrations and powers up a radio frequency bee tracker with minimal physical hindrance.
## 4 Numerical Experiments  
### Measurement Campaign  
The measurements took place during the APART GAS 2019 (Active PAssive Radar Trials Ground based, Airborne, Sea-borne) trials. The trials were described by [PERSON] et al. [19], nevertheless some details of the measurement FSR scenario geometry will be examined here. The positions of the receiving station, transmitter of opportunity, aircraft trajectory, and transmitter-receiver baselines are depicted in Figure 2.  
Figure 2: Scenario geometry: transmitter–receiver baseline (white line) cross point marked by a green circle, aircraft trajectory in red.  
During the passive FSR measurements, the radar receiving station was placed in an open space, on an airfield (see Figure 3). The location was chosen to also test FSR geometry in foliage penetration conditions. The receiver was placed close to the forest line, where the trees were in the direction of the transmitter of opportunity--see Figure 2b. The radar demonstrator was equipped with 6 antennas, but only two of them were used in the presented FSR experiment. During the trials the signal from both V- and H-polarized receiving antennas was gathered, however, due to the lack of significant differences between the results only the selected pair of the receiving channels was analyzed. Hence, in the further part of this paper the signal from V-polarized antennas mounted on a tripod mast at the height of ca. 3 m above the ground is presented. The parameters of the employed transmitter of opportunity are listed in Table 1.  
During the measurements a cooperative target was used--a light Cessna aircraft (see Figure 4). At the moment of crossing the transmitter-receiver baseline, the aircraft flight parameters were as follows: the target altitude was 196 m above terrain level and velocity was 44 m/s. The distance between receiver and target was 280 m, the distance between transmitter and target was 27.5 km, and the distance between receiver and transmitter was 27.706 km.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Name** & **“Lebork Skórowo Nowe”** \\ \hline Distance to receiver & 27.8 km \\ \hline Location height & 96 m a.m.s.1 \\ \hline Mast height & 93 m \\ \hline EIRP & 10.4 kW \\ \hline Frequency & 184.5 MHz \\ \hline Signal bandwidth & 7 MHz \\ \hline Polarization & Vertical \\ \hline \hline \end{tabular}
\end{table}
Table 1: Main parameters of the transmitter of opportunity.  
Figure 3: Radar demonstrator during measurements.  
The composition of the receiving station was as follows. Antennas: commercial-off-the-shelf (COTS) 4-element Uda-Yagi, with directivity from 6 dBi to 8 dBi, operating in an upper VHF frequency band (170 MHz up to 230 MHz). Analog front-end: COTS channel amplifier, operating in 87-230 MHz frequency band, with 25 dB gain. Digital signal recorder (see Figure 5): Vector Signal Analyzer (VSA) based on National Instruments PXIe components, with six independent input channels synchronized coherently with GPS signal, operating in the frequency range 10 MHz-6.6 GHz with the maximum bandwidth of 50 MHz. More detailed description, of the radar demonstrator hardware, has been presented by [PERSON] et al. [19].
# Empowering WBANs: Enhanced Energy Efficiency Through Cluster-Based Routing and Swarm Optimization
## 4 Results and Discussion
### Alive Sensor Nodes  
Our simulations consider a node dead when its battery is completely depleted. Figure 5 depicts the number of active nodes in a round. The proposed method balances power consumption among nodes, reducing node mortality. By improving the cluster, increasing the number of CHs, preserving the transmission distance inside the cluster, decreasing the distances between the clusters, and reducing the network's power consumption, our proposed method effectively reconciles the network's structure. Low power consumption, high residual energy, and many active nodes indicate that the protocol is stable.
## 4 Results and Discussion
### Day-Ahead Demand Response Model for the Selected Case Study  
The proposed day-ahead DR system for the residential sector's demand is shown in Figure 18, which was applied to a selected day in December 2019. The contribution of JEPCO, IDECO, and EDCO in providing the total residential electricity demand is considered about 32.4%, 5.08%, and 9.98%, respectively. This is calculated by multiplying the peak power of each distribution company by the percentage of residential and commercial energy consumption for each company. The estimated demand is also used to calculate the amount of power purchased from each power plant, after deducting the usage of the renewable power. Finally, after the peak bulk prices are selected for each distribution company, the model is applied to each PEMD case scenario to estimate the potential generation cost savings, peak demand reduction, and load factor improvements.
## 3 Results
### Correlation of NEP, WUE, and CUE with Climate Variables
#### 3.4.3 Correlation with DSI  
The temperature and precipitation reflect the hydrothermal conditions under which local vegetation grows. The factors affecting the NEP, WUE, and CUE are intricate. Moisture limitation has an important impact on the water-carbon cycle in inland areas. Thus, there is a need to explore the relationship of these factors with the moisture limitation index. The drought severity index (DSI) was selected for the correlation analysis (Figure 10g-i). The correlation of the NEP, WUE, and CUE with the DSI all showed a high value, with mean values of 0.82, 0.43, and 0.64, respectively; the regions with a positive correlation accounted for 99.89%, 81.79%, and 94.01% of the MRYR, respectively. The regions in which each index reached the level of significance (\(p\) < 0.05) were also very high, accounting for 97.08%, 71.89%, and 86.66% of the respective positively correlated regions.  
Given the above, the environment in the MRYR became wetter during the study years, and more biomass was accumulated by the consumption of more water. It is noteworthy that there is a large negative correlation in the southeastern part of the MRYR. This may be because the forest cover reached saturation and the increase in precipitation could no longer improve the vegetation cover [54]. On the contrary, in the north, under ecological engineering and warm humidification trends, the grass cover increased significantly, and biomass accumulated substantially. In terms of the different vegetation types, the areas with a significant positive correlation between the DSI and NEP accounted for more than 80% of the respective vegetation types; the proportion of areas with a negative correlation between the WUE and CUE and DSI was even higher in the forests and shrubs (Figure 11).
# Evaluation of Agricultural Soil-Improving Zeolite for Improving Irrigation Water Quality
## 3 Results and Discussion
### Adsorption Kinetics
#### 3.4.2 Zeolite Effect on pH and Cation Removal  
One of the factors that significantly influences sorption processes is undoubtedly the pH at which the process occurs, as it directly interferes with the behavior of charges susceptible to sorbent-sorbate interactions. The results showed a significant variation in the pH of irrigation water during the first 5 min of contact with zeolite, changing from an initial pH of 8.3 to 8 (Figure 3). After this time, the pH remained relatively constant at around 8 for the first 720 min, decreasing to 7.9 and remaining stable until the end of the test (6200 min). This slight decrease in the pH of irrigation water may help explain the low adsorption of sodium by zeolite. [PERSON] et al. [64] identified that the sorption of sodium ions increases as the solution pH increases, due to the deprotonation process of various functional groups on the adsorbent. This results in more negatively charged sites, leading to greater electrostatic attraction between these sites and sodium, facilitating the sorption of the cation on the adsorbent's surface. This trend is similar to that of boron, but with some nuances. [PERSON] and [PERSON] [65] defined the maximum adsorption of boron at alkaline pH (9.3) but determined acceptable sorption in the pH range between 5.8 and 9.3. This would explain boron sorption by zeolite in irrigation water even with a pH < 9.3.  
Figure 3: Water samples’ pH variation as a function of contact time with zeolite and its correlation with the percentages of boron (B) and sodium (Na) cation removal.  
Figure 2: Removal of sodium and boron cations (%) on zeolite as a function of contact time.
###### Abstract  
This paper investigates outage probability (OP) performance predictions using transmit antenna selection (TAS) and derives exact closed-form OP expressions for a TAS scheme. It uses Monte-Carlo simulations to evaluate OP performance and verify the analysis. A back-propagation (BP) neural network-based OP performance prediction algorithm is proposed and compared with extreme learning machine (ELM), locally weighted linear regression (LWLR), support vector machine (SVM), and BP neural network methods. The proposed method was found to have higher OP performance prediction results than the other prediction methods.  
mobile cooperative communication; outage probability; performance prediction; BP neural network +
Footnote †: journal: Accepted: 1 November 2019; Published: 4 November 2019
# An Interpretable XGBoost Framework for Predicting Oxide Glass Density
## 3 Results
### Feature Importance (XGBoost)
Each point represents a single glass sample, with its color indicating the feature's value (red for high, blue for low) and its position on the x-axis showing the feature's contribution (SHAP value) to the final density prediction. The SHAP analysis provides a detailed confirmation of the trends observed in the feature importance study. For the model based on Compositional features (Figure 7a), the plot reveals that high fractions of heavy elements like Pb and Ba consistently push the predicted density higher (positive SHAP values), while light network-forming elements such as B and Si have the opposite effect. Interestingly, while oxygen had a high weight (Figure 6a), its SHAP values are clustered around zero, confirming the permutation importance analysis that it has a lower direct predictive impact compared to the cations that differentiate the glass structures. Introducing Atomic types attributes (Figure 7b) clarifies these relationships. A high fraction of network formers consistently drives the predicted density down, whereas a high fraction of intermediates, which often include heavier elements, contributes positively. This shows that the model learns to associate these structural roles with specific density outcomes. The true power of physically informed descriptors becomes evident in the SHAP plots for the Meredig (Figure 7c) and Magpie (Figure 7d) feature sets. The mean atomic weight emerges as the dominant driver of the predictions; its SHAP plot shows a linear relationship where higher values strongly and positively impact the predicted density. This demonstrates that the model has successfully learned that the mean atomic weight is directly related to molar mass and thus the density. Furthermore, features related to electronic structure, such as the mean fraction of d and s valence electrons, show clear trends that the model uses to approximate the molar volume (V\({}_{\text{m}}\)). For example, a higher fraction of d-valence electrons, characteristic of heavy transition metals, is associated with an increase in predicted density. This detailed, instance-level analysis confirms that by providing the algorithm with physically meaningful features, the XGBoost model does not merely find correlations but builds a predictive framework that mirrors the underlying physical principles governing glass density.
# Flexural Behavior of an RC Beam Externally Strengthened with a Steel- and CFRP-Based Method
## 1 Introduction
In engineering applications, two end-anchorage devices can only prestress FRPs of a limited width compared with the large width of the retrofitted cross-section. To balance the dosage of the FRP and the installation of the anchoring device, a larger gap should also be prepared for the adjacent pair of devices. As the device is usually designed as a steel anchorage, the aforementioned steel-based method can function in a similar role [39; 40; 41]. Therefore, if the retrofitting can combine the advantages of both the steel- and FRP-based methods, not can only the debonding failure of the FRP be avoided, but the flexural capacity can be improved through the cooperation of various materials. [PERSON] et al. [42] pointed out that the flexural capacity of beams strengthened with multiple reinforcements was 27.9% better than those retrofitted only with CFRP laminates. [PERSON] et al. [43] found that hybrid retrofitting can strengthen the existing structure, leading to improvements of up to 25.0%. In this study, the two steel- and FRP-based methods were combined to retrofit an existing bridge. The corresponding flexural performance was shown to dramatically improve, and the local bonding failure of the FRP plate could be avoided through effective anchorage from the steel components. To investigate the effect of the cooperation strengthening, six full-scale RC beam specimens were designed and evaluated through a monotonic four-point bending test. Among them, five specimens were retrofitted with a single or collaborative method, while one was designed as a standard RC beam without any retrofitting. The failure mode, load-deflection relationship, critical parameters, and crack development were systematically and sequentially analyzed. Finally, to ensure the applicability of the proposed method, a prediction method was used to calculate the flexural capacity.
## 4 Conclusions  
In this paper, the 1 g model test was conducted to study the cumulative deformation of the pile group in saturated clay soil under horizontal cyclic loading. Using the self-made loading test system, the soil dynamic response and the development of the deformation, as well as the bending moment of the pile group, were investigated in detail. Based on the experimental results, the following conclusions were drawn:  
1. The horizontal displacement and the rotation angle of the bearing platform demonstrated a trend of growth at first, followed by stabilization, as the number of cycles increased when the load amplitude was small (CLR \(\leq\) 0.5), and they continuously increased throughout the cycles when the load amplitude was large (CLR \(=\) 0.75).
2. The development trend of pore water pressure around the pile was basically consistent with the horizontal cumulative deformation of the pile group under the horizontal cyclic loading, and its growth rate was fast in the first 1000 cycles, and then slowed down in the later stages.
3. Under the horizontal cyclic loading, the bending moment of the front-row piles was larger than the back-row piles, and the bending moment of each pile increased with the increase of the burial depth, and then gradually decreased after reaching the peak.
4. The horizontal cyclic stiffness of the pile group increased with the increase of the loading cycles and the decrease of the loading amplitude.
5. It is necessary to consider the effects of changes in the cyclic stiffness of pile foundations on the analysis of cumulative deformation of structures in practical engineering.  
Conceptualization, D.W. and Y.H.; Methodology, Y.H.; Software, L.D.; Validation, L.W., J.C. and L.H.; Formal analysis, Y.H.; Investigation, M.J.; Resources, L.D.; Data curation, L.W.; Writing--original draft, Y.H.; Writing--review & editing, Y.H.; Visualization, L.D.; Supervision, M.J.; Project administration, Y.H.; Funding acquisition, D.W. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China (Grant No. 52108268, 51979017), and the Chongqing Natural Science Foundation (cstc2021 jcyj-msxmX1123).  
Not applicable.  
The authors would like to thank the technical staff of the Key Laboratory of Hydraulic and Waterway Engineering of the Ministry of Education, Chongqing Jiaotong University for their technical support.  
The authors declare no conflict of interest.
## 3 Simulations  
### Methods  
#### 3.1.1 Simulation and Reconstruction Programs Description  
Simulations to validate the proposed stopping rules were performed in an idealized setting to minimize computation time. Matched distance-driven projectors and backprojectors were used [12], simulating a single slice of a scanner with a 829 mm ring diameter, and 4.3 mm crystals. The same projectors were used for image reconstruction. Images were generated at high resolution (1.36 mm pixel size), smoothed with a 4.5 mm FWHM Gaussian kernel, then forward projected.  
Two additive corrections were simulated: a uniform background in sinogram space (representing random coincidences) and a multi-kernel convolution of the true sinogram (to represent scatter coincidences). For every true coincidences 0.9 random and 0.5 scattered coincidences were added. After forward projection, Poisson noise was simulated. Sinograms were then reconstructed in a 512 mm FOV, using 2 mm pixels and 200 MLEM iterations, without OS acceleration. Reconstructions were initialized with a unitary circle as large as the FOV.
## 5 Use Case: Dynamic Radio/MEC Resource Allocation and Slicing Management in High Mobility Scenarios
### System Evaluation
#### 5.2.2 Joint Evaluation  
To conduct this evaluation, one of the nodes defined in the use case was selected, and an evaluation period of 100 timesteps was executed. During this period, the two DQN models deployed on this node were run simultaneously, mimicking their operation in a real-world scenario. Both models interacted with their respective databases to prevent inconsistencies in the current status of processed requests and available resources, as outlined in [7] for the centralized approach. The results of this evaluation period are presented in Figure 14, showing that both models achieved the maximum number of rewards, thereby validating the system's effectiveness.