esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Methodology
### Spatiotemporal Prior Integration  
Geophysical Dependencies  
Railway deformation risks are profoundly affected by geophysical factors, such as terrain slope, soil composition, and underlying geological formations. These factors play a critical role in determining the stability and risk levels of railway segments. To effectively model these dependencies, the adjacency matrix \(\mathbf{A}\), which represents the connectivity between railway segments, is refined by incorporating geophysical similarity and structural connectivity. This refinement enhances the model's ability to capture domain-specific relationships.  
The geophysical similarity between two segments \(r_{i}\) and \(r_{j}\) is quantified through a similarity matrix \(\mathbf{P}\in\mathbb{R}^{N\times N}\). This matrix encodes both spatial proximity and geological similarity using the following formulation:  
\[\mathbf{P}_{ij}=\exp\left(-\frac{\|\mathbf{I}_{i}-\mathbf{I}_{j}\|_{2}^{2}}{ \sigma^{2}}\right)\cdot\kappa_{ij}, \tag{23}\]  
where \(\mathbf{I}_{i}\) and \(\mathbf{I}_{j}\) denote the geographical coordinates of segments \(r_{i}\) and \(r_{j}\), and \(\sigma\) is a scaling parameter that controls the sensitivity of the similarity to spatial distance. The term \(\kappa_{ij}\) is a binary indicator reflecting whether the two segments share common geological attributes, such as soil type or rock formations. This formulation ensures that segments that are both geographically close and geologically similar have stronger connections.  
To incorporate this geophysical information, the refined adjacency matrix \(\tilde{\mathbf{A}}\) is computed as a weighted combination of the original adjacency matrix \(\mathbf{A}\) and the geophysical similarity matrix \(\mathbf{P}\):  
\[\tilde{\mathbf{A}}=\lambda\mathbf{P}+(1-\lambda)\mathbf{A}, \tag{24}\]where \(\lambda\in[0,1]\) is a hyperparameter that balances the contributions of geophysical similarity and the original structural connectivity. A higher value of \(\lambda\) places greater emphasis on geophysical factors, while a lower value prioritizes the inherent structural relationships represented by \(\mathbf{A}\).  
This refined adjacency matrix enables the model to integrate geophysical priors seamlessly into the spatial attention mechanisms, ensuring that railway deformation risks are evaluated in a manner that respects both spatial and geological contexts. For example, segments with similar terrain slopes or soil compositions are more likely to share deformation characteristics, and the refined adjacency matrix captures these subtle relationships effectively. By embedding these domain-specific insights into the model, the framework gains enhanced predictive accuracy and interpretability, making it more robust in identifying high-risk segments influenced by geophysical conditions.
# Low Temperature Resistance Increase for Bitumen by Compounding with Tar
## 3 Results and Discussion
### Standard Indicators of Bitumens  
The main standard indicators for the compounded bitumen of optimal composition are given in Table 6. Comparing them with similar indicators of the virgin bitumen, it has been found that the penetration of the compounded bitumen has been increased by 54 decimillimeters, as a result of which, in accordance with the requirements of ST RK 1373-2013 [23], the bitumen changed the original grade of 100-130 to the grade of 130-200; softening point and dynamic viscosity decreased by 5 \({}^{\circ}\)C and 65%, respectively; the Fraas point decreased for 1 \({}^{\circ}\)C; and the ductility increased by 10.4%.  
Thus, optimal compounding (20% of the tar) significantly changes the main standard characteristics of the bitumen, and the obtained compounded bitumen of optimal composition transforms into a more \"liquid\" penetration grade 130-200.  
In Section 3.1, the results for the analysis of the stiffness and m-value of the compounded bitumen at low temperatures allowed determining the optimum tar content. Certainly, it would be desirable to consider the bitumen characteristics at high temperatures as well to justify the optimum tar content.  
In Kazakhstan, the high temperature resistance of the road bitumens is characterized by a softening point [23]. Table 7 shows the values for the softening point of the compounded bitumen at different tar contents. As could be expected, the softening point of the bitumen decreased with tar content increase. According to the standard ST RK 1373-2013 [23] for bitumen with penetration grade 130-200, the softening point should not be lower than 40 \({}^{\circ}\)C. As observed from Table 7, the maximum allowable (i.e., optimum) tar content in the compounded bitumen is equal to 20%, which with a high accuracy coincides with the optimum tar content determined at low temperatures.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Indicator**} & \multirow{2}{*}{**Measurement**} & \multicolumn{3}{c}{**Value**} \\  & **Unit** & **Standard** & **Virgin** & **Compounded** \\  & & & **Bitumen** & **Bitumen** \\ \hline Penetration (25 \({}^{\circ}\)C) & 0.1 mm & ST RK 1226-2003 & 116 & 170 \\ Ductility (25 \({}^{\circ}\)C) & cm & ST RK 1374-2005 & 115 & 127 \\ Softening point & \({}^{\circ}\)C & ST RK 1227-2003 & 45 & 40 \\ Fraas point & \({}^{\circ}\)C & ST RK 1229-2003 & \(-\)27 & \(-\)28 \\ Penetration index & - & ST RK 1226-2003 & \(-\)0.312 & \(-\)0.962 \\ Dynamic viscosity & Pa-s & ST RK 1211-2003 & 138 & 49 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Main standard indicators of the virgin and compounded (20% of the tar) bitumens.  
Figure 6: Stiffness variation of the virgin bitumen and the compounded one (20% of the tar) in time at the temperature of \(-\)36 \({}^{\circ}\)C.
# Efficient and Secured Mechanisms for Data Link in IoT WSNs: A Literature Review
## 5 The Architecture of WSN Nodes  
Wireless sensor network is a broad term that consists of several nodes; the more significant the WSN, the bigger the number of nodes. Each node acts as an individual unit consisting of a sensing unit, a communication unit, a processing unit, and a storage unit; these units make up a particular node [26]. The sensing unit exists to detect events and gather required data, such as temperature, humidity, sounds, light, etc., or the specific data it uses. The communication unit allows the collected data to be transferred; it makes the sensor communicate with other nodes for sending and receiving data. The storage unit is used to save the assembled data in a specific format for later use [27; 28]. Figure 6 shows the architecture of an individual WSN node [29]. A WSN is made up of hundreds of thousands of sensor nodes. These nodes can communicate with one another using multi-hop communication. WSNs have a lot of potential as a platform for various uses, including data collection and event prediction.  
Figure 6: Architecture of an individual node [30].
## 4 Conclusions  
A severe haze episode that occurred in central China (Wuhan) from 6-14 June 2012 was studied. The aerosol optical properties during the haze event were measured using ground-based equipment (nephelometer, aethalometer, meteorological station, and particle detector) and satellite (CALIPSO). The haze was caused mostly by the long-distance transport of particles from the combustion of biomass (such as straw) during the harvest season in northern Anhui Province. During the haze days, the mean mass concentrations of PM\({}_{2.5}\) and BC were 9.9 (332.79 _versus_ 33.66 \(\mathrm{\SIUnitSymbolMicro m}^{-3}\)) and 3.2 times (9.67 _versus_ 2.99 \(\mathrm{\SIUnitSymbolMicro m}^{-3}\)) greater, respectively, than during normal weather. The large aerosol loading contributed to the high coefficients of aerosol scattering coefficient (2.32 \(\mathrm{km}^{-1}\)) and absorption (0.086 \(\mathrm{km}^{-1}\)). Particle size became larger consistent with the reduced scattering Angstrom exponents. The high asymmetry parameter (0.65) and SSA (\(\sim\)0.97) observed during the haze coincided with the relatively low backscatter ratio (0.11) and up-scatter fraction (0.23), which were related to the increased particle size and led to a heating effect on the atmosphere. Pollutants accumulated primarily below the height of 3 km and their shapes remained regular. The mean extinction coefficient (\(\sim\)1 \(\mathrm{km}^{-1}\)) derived from CALIPSO was very close to that (1.27 \(\mathrm{km}^{-1}\)) obtained by the ground-based equipment, which revealed good agreement between the two types of observations.
## 2 Results and Discussion
### Effect of Nanoparticle on Mitotic Division  
Figure 9 presents normal and abnormal cell divisions in onion root tips exposed to different treatments of GW and Mg NP/GW nanoparticles. In the initial panels (A-D), we observe the typical stages of mitosis in onion root tip cells under control conditions. Panel A shows prophase, where chromosomes condense and become visible, and the nuclear envelope begins to disintegrate. Panel B depicts metaphase, characterized by chromosomes aligning at the cell's equatorial plate. Panel C illustrates anaphase, where sister chromatids are pulled towards opposite poles. Finally, Panel D shows telophase, where chromatids reach the poles and nuclear envelopes re-form around each set of chromosomes. These stages are essential for ensuring genetic stability during cell division. The remaining panels (E-L) display various abnormalities induced by treatments with GW and Mg NP/GW nanoparticles. Panel E shows multiple chromosomal bridges, indicating failures in proper chromosome segregation, which can lead to genomic instability. Panel F presents stickiness in anaphase, where chromosomes fail to separate correctly. Panel G shows lagging chromosomes in anaphase, suggesting improper attachment to spindle fibers. Panel H reveals a C-shaped metaphase, indicative of disturbances in chromosome alignment. Panels I and J show stickiness in metaphase, with chromosomes clumping together and failing to align properly. Panel K depicts DNA decay, indicating severe damage. Finally, Panel L displays breaks and disturbances in chromosomes, pointing to significant genotoxic effects. Table 4 details the effects of different concentrations of Mg NP/GW on mitotic abnormalities. At 0.5 g/L, all abnormalities, including disturbed metaphase, chromosomal bridges, laggards, and sticky chromosomes, are present across the replicates. At higher concentrations (1.0 g/L and 5.0 g/L), the presence of these abnormalities persists, indicating a dose-dependent response. This table underscores the severity and consistency of the abnormalities induced by nanoparticle treatments (Table S1). Figure 8: Photographs of plants illustrating the effect of three concentrations (0.5, 1.0, and 5.0 g/L) of Mg NP/GW and GW on the growth of _P. gravelens_ (**above**) and _S. allu_ (**below**). Table 4 provides the mitotic index and the distribution of cells across different mitotic stages. As shown in Table S2, under control conditions, the mitotic index averages 44.6%, with a balanced distribution across prophase, metaphase, anaphase, and telophase. However, with nanoparticle treatments, there is a marked increase in the mitotic index and a shift in the distribution. For example, at 0.5 g/L concentration, the mitotic index increases to 61.24%, with significant disturbances in metaphase and anaphase. Higher concentrations
## 3 Multiple Reconfigurable Features in Antenna
### Frequency and Bandwidth Reconfigurable Antennas
The switching mechanism of the antenna contained four PIN diodes leading to four distinct modes between 755 and 3450 MHz. In [53; 54], single-port wide to narrowband monopole antennas with uni-planar configurations were proposed. Switching between the wideband and narrow communication bands was obtained using two PIN diodes in a ring-slot filter design in the feed-line. The proposed antenna in [53] exhibited wide-to-narrow band reconfiguration from 1.6-6.0 GHz (UWB) to 3.39-3.80 GHz (5G). A pair of varactor diodes tunes the narrowband operation from 2.55-3.2 GHz [54]. The wideband state provides around 5 GHz bandwidth (1.35-6.2 GHz). For a new combined antenna system containing an UWB antenna for spectrum sensing and a dipole antenna narrowband, communication was proposed in [55], using two feeding ports to obtain wideband coverage of 2-5.5 GHz and narrow-band resonance at 2.8 GHz. The system can cover the spectra of IEEE 802.11 ac and 802.11n, universal mobile telecommunications service (UMTS) 2000, and 4G/5G mobile terminals and is suitable for use in front-end CR applications.
# 4D Printing of Multicomponent Shape-Memory Polymer Formulations
## 4 Vat-Photopolymerization Based 4D Printing
### Digital Light Processing (DLP) of trSMPs
Curing depth studies showed that SiO\({}_{2}\)-SMP composites  
Figure 13: (**a**) Schematic demonstration of sequential recovery of a permanent shape (PS) from a programmed temporary shape (TS), through different recovery stages (RS1, RS2, RS3 and RS4), by connecting two adjacent electrodes at a time. (**b**) Actual recovery ratios (\(R_{r}\)) at different time intervals Reproduced with permission from reference [71], copyright 2021 John Wiley & Sons. (**c**) Schematic demonstration of the fabrication of a multimaterial structure based on P\(\mu\)SL. (**d**) Demonstration of the transition between the as-printed shape and the temporary shape in multimaterial grippers. Reproduced with permission from reference [127], copyright 2016 Springer Nature. (**e**) Shape recovery of 3D printed silica-SMP composites upon exposure to hot air. Reproduced with permission from reference [128], copyright 2020 Elsevier. attained higher curing depths at a faster rate in comparison with the neat SMP. The fast polymerization rate of the SiO\({}_{2}\)-SMP composites was attributed to the nanosilica particles acting as heterogeneous nucleation sites for polymerization. Silica nanoparticles acted as multifunctional crosslinks enabling excellent dispersion and improved mechanical and shape memory properties of the composites. The SiO\({}_{2}\)-SMPs exhibited outstanding shape memory performance with 100% shape fixity and 90-97% shape recovery. Projection stereolithography fabrication was used to print a flower-shaped sample using the developed SMP composites. A printing speed of 2.8 mm/min \(\approx\) 168 mm/h was used to complete the printing of a flower (76 mm in height) in 27 min [128]. The shape recovery process of an SMP composite of this type under a hot air gun is shown in Figure 13d. [PERSON] et al. reported the 4D printing of a photocurable resin to produce chemically crosslinked SMP systems with self-healing capabilities [129]. These UV cured double-networks were based on the benzyl methacrylate (BMA) monomer and a poly(ethylene glycol)-dimethacrylate (PEGDMA) crosslinker, with linear polycaprolactone (PCL) added to impart self-healing (SH) capabilities to the 4D printed structures. Three-dimensional printing by DLP enabled highly deformable networks with remarkable shape-memory and self-healing capabilities. The effects of PCL concentration on the thermomechanical behavior, viscosity, and the self-healing capabilities of the SH-SMP systems were investigated. The mechanical properties of a damaged structure could be recovered to nearly 100% when more than 20 wt.% of PCL was present in the SH-SMP system.
# Elastic Modulus Prediction Model of Foamed Concrete Based on the Walsh Formula
###### Abstract  
Foamed concrete consists of cement matrix and air-foam and has more complicated structure characteristics than normal concrete. However, current research on the elastic modulus of foamed concrete is still limited to empirical equations. In this work, a new theoretical prediction model was proposed for calculating the elastic modulus of foamed concrete. The elastic modulus calculation model for the spherical shell element of foamed concrete is constructed based on the Walsh formula and the assumption of spherical pores. Moreover, the theoretical prediction model is established by introducing the two-layer embedded model for the elastic modulus of foamed concrete. Then, the compressive test is employed to verify the accuracy of the model. The results show that the elastic modulus of foamed concrete decreases with the increase in porosity and matrix Poisson's ratio, and increases with the increase in the matrix elastic modulus. The research results can improve the mechanical theories of foamed concrete materials and have good engineering application values.  
foamed concrete; elastic modulus; Walsh formula; two-layer embedded model; spherical pore assumption; mesomechanics
# Computational Vibro-Acoustic Time Reversal for Source and Novelty Localization
## 5 Examples
### Novelty Localization Examples
#### 5.2.1 Novelty Case A  
Two experiments were run, experiment A1 and experiment A2. Meanwhile, at the healthy beam case, both beams had Pined-Pinned (PP) boundary conditions (BC), in case A1 the horizontal beam's right end is switched to a free BC, representing, for example, a support failure. The simulation time was 1.333 ms, which corresponds to 4000 time steps or a traveled distance, which is approximately \(9\,L\), with \(L\) being the longest side of the rectangular domain. Since the center of the pulse is at time \(t_{0}=3\times 10^{-5}\) s and its half time span (see Figure 4a) is approximately \(\Delta t=2\times 10^{-5}\) s, considering the simulation time and the travel time to get to the novelty, the pulse midpoint should be found at the novelty at time \(t_{c}=1.291\,\mathrm{ms}\), while the activity at the novelty should present itself between times: \(t_{c}-\Delta t=1.271\,\mathrm{ms}\) and \(t_{c}+\Delta t=1.311\,\mathrm{ms}\).  
Shown in Figure 7 is the pressure time history at the point of the novelty, in which several peaks are identified at last part of the simulation. They represent pressure activity at the novelty location. To be mentioned that time reversed signals have been re-emitted back form the 24 stations located onto the boundary.  
A characteristic shot of the entire domain's absolute pressure at time step 3624, which corresponds to 1.208 ms, is given in Figure 8. The defect is clearly revealed at the right end of the horizontal (see also Figure 3), which has undergone the support modification.  
In case A2, the change of the vertical beam's top end boundary condition to a free end was considered as the novelty. The simulation time was again 1.333 ms, which corresponds to 4000 time steps or a \(9\,L\) traveled distance. The calculated travel time for the [PERSON]'s pulse midpoint to reach the novelty is \(t_{t}=42.325\,\mathrm{ms}\). The center of the pulse should reach the novelty at time \(t_{c}=1.274\,\mathrm{ms}\), while the activity at the novelty should present itself between times: \(t_{c}-\Delta t=1.254\,\mathrm{ms}\) and \(t_{c}+\Delta t=1.294\,\mathrm{ms}\). By looking at the pressure time series at the novelty (see Figure 9), we observe once again that several peaks are identified.  
A characteristic plot of the absolute pressure on the whole domain at time 1.212 ms, corresponding to the highest pressure peak (time step 3638), is shown in Figure 10, where it is evident that the pressure activity is located exactly at the top end of the vertical beam, where the novelty lies.  
Figure 8: Absolute pressure on the whole domain at time 1.208 ms. Beams are plotted with light blue color. The defect is clearly revealed at the right end of the horizontal beam.  
Figure 7: Backward step pressure time history, at the point of the novelty on the horizontal beam.  
Figure 9: Pressure time history at the point of the novelty of the vertical beam.
## 4 Design
### Model Comparison  
In this section, we will compare the model proposed in this paper with other models that combine PBFT and RAFT algorithms. We will also discuss the advantages of the algorithm proposed in this paper. The consensus process of the PBFT algorithm is depicted in Figure 3. It can be observed that PBFT's communication complexity during consensus can be O(N\({}^{2}\)). As a result, as the number of nodes increases, the consensus latency will significantly rise, leading to a decrease in performance, including throughput.  
Figure 2: Electoral process.  
Other models combine the original PBFT algorithm with the RAFT algorithm by dividing blockchain nodes into two groups: the consensus group and the candidate group. For example, RBFT proposed in [19] adopts a sharding approach to partition the blockchain network nodes into groups. Within each group, RAFT is used for consensus, and leaders are elected through the RAFT consensus mechanism. Between leaders, the PBFT mechanism is used for consensus, ensuring consensus efficiency. RBFT also incorporates supervisor nodes to address the issue of RAFT consensus being unable to resist Byzantine malicious behavior, thus ensuring the security of the consensus mechanism. Figure 4 illustrates the consensus process of the RBFT algorithm. As shown in the figure, RBFT's communication complexity is similar to PBFT, both being O(N\({}^{2}\)), indicating a relatively low scalability. When supervisor nodes detect Byzantine nodes within the group, a new node is re-elected to replace it as the leader and participate in consensus. While this approach effectively addresses the issue of RAFT's inability to detect Byzantine nodes, it introduces additional operations and cannot handle CFT problems promptly.  
Our algorithm is based on the HBFT algorithm model, integrating the RAFT election process, a trust mechanism, and corresponding detection mechanisms. Once a Byzantine node is detected, the algorithm initiates a re-election process within the group to select a new leader node, effectively pushing the Byzantine node to the lowest level of the layered network. This prevents the Byzantine node from quickly returning to the main consensus area and assuming the role of a leader node. Additionally, our algorithm, after incorporating the RAFT algorithm, can detect CFT (crash fault-tolerant) issues with leader nodes at other times. Moreover, our algorithm exhibits O(N) communication complexity, as discussed in Section 4.6 of this paper.
## 5 Challenges and Future Research Directions
### Future Research Directions
#### 5.2.4 Integration of SAGINs with Maritime Networks  
Underwater networks consist of underwater sensors, autonomous underwater vehicles, and buoy stations, connected through acoustic, radio, and optical communication methods. However, maritime communication faces challenges such as high transmission loss, strong channel variability, and limited coverage. To address these issues, technologies such as maritime collaborative positioning, UAV-based networks, and efficient data enhancement methods need to be adopted. Maritime SAGINs, through the cooperation of satellite-, UAV-, and sea-based nodes, can achieve seamless communication across land, sea, air, and space, overcoming communication obstacles in underwater environments, thereby providing more efficient network support for marine exploration and maritime safety. In addition, the integration of maritime communication also introduces additional security challenges that need to be addressed [9].