esa-sceva/satcom-chunk-collection huggingface dataset:
## 6 A New Paleostress History and Tectonic Implications
Since no absolute age information is available, as [32] pointed out, we compare the T1 TRM through T5 TRM stress tensors with the suggested deformational events of [32] and other published information concerning the deformation of the region, as described above in the five stress regime outlines. Conclusively, the TRM application on the fault-slip data of [32] defines (a) a TRP-SS stress regime (T1) with NW-SE contraction, which can be correlated with the Late Eocene deformation of [73]; (b) an Oligocene E-W extensional regime (T2) fitting well with the E-W extension mentioned for the broader area due to a major change in subduction dynamics, perhaps as a consequence of collision and slowing down of the northward motion of Africa [51; 89]; (c) an N-S trans extension (T3), which has the \(\sigma_{3}\) axis perpendicular to the \(\sigma_{3}\) axis of the T2 stress regime; and (d) Miocene transpression (T4) with ENE-WNW contraction that changes to (e) transpression with NNE-SSW contraction (T5). Based on these, we can argue that the Late Oligocene-Early Miocene marks a crucial period for the stress evolution in the broader area, since the plate convergence transferred eastwards from the Pyrenees collision zone to the Corsica-Sardinia trench system and the stress regime in the Ligurian Alps shifted gradually from an NW-SE to NE-SW direction of compression [57; 90; 92]. In particular, considering that the 50\({}^{\circ}\) counterclockwise rotation occurred from the T4 to T5 stress regime, the T1 through T3 stress regimes should be restored to pre-rotational orientations. In that sense, the restored T1 represents a TRP-SS stress regime with contraction trending NNE-SSW. Such a contraction fits well with the NW-SE contraction in the Western Alps and its change to N-S towards the Pyrenees, placing the region along the Western Alps and Pyrenees (Figure 5a). The restored T2 stress regime is an extension trending NW-SE, similar to the extension dominating the Liguro-Provencal rifting (Figure 5b). The restored T3 stress regime, which is a transtension having a NE-SW trending \(\sigma_{3}\) axis, i.e., perpendicular to the NW-SE T2 \(\sigma_{3}\) axis, might be considered a local mutual permutation of the T2 stresses. The T4 and T5 stress regimes shown in Figure 5c,d indicate the gradual rotation that took place from the Early until the Middle Miocene. Since then, the area's configuration has been characterized by a gradual counterclockwise rotation and complex oblique and strike-slip deformation, as is documented in the upper crust via seismic tomography and earthquake alignments [100]. The change from the Oligocene extension to the Late Oligocene-Moocene compression and, in general, the stress reorganization in the Ligurian Alps, i.e., the internal area of the Northern Apennines and the Western Alps, can be attributed to the decrease in the retreating rate of the Apennines slab.
## 1 Introduction
Recently, some schemes combining PS and ML algorithms have been proposed to improve the performance of the optical communication systems. In the Ref. [19], a weighted K-means scheme for a PS 64 QAM signal was proposed in order to locate the decision points more accurately and enhance the robustness of clustering algorithm. In addition, the combined benefit of artificial neural network-based nonlinearity compensation and probabilistic shaping was experimentally demonstrated in the Ref. [20]. In this paper, we propose a novel nonlinear equalizer for PS-64 QAM based on CS and SVM. This scheme can effectively mitigate the fiber nonlinearity with lower complexity. The performance of CS M-ary SVM NLE has been demonstrated in a 120 Gb/s PS-64 QAM coherent optical communication system. The experimental results show that the LOPDR can be increased by 1.6 dBm and 0.6 dBm by employing the proposed scheme compared with the situation without NLE and employing the traditional M-ary SVM NLE, respectively. Moreover, by using the proposed scheme, the Q factor of PS-64 QAM is improved by about 0.50 dB and 0.96 dB compared with employing M-ary SVM NLE and without employing NLE, respectively. We use the number of SVs and CPU running time for both schemes to evaluate the complexity of the schemes. The results show that the complexity of the proposed scheme is lower than that of the M-ary SVM scheme under the entire measured launched optical power range from \(-\)5 dBm to \(+\)5 dBm. This paper is organized as follows. We begin in Section 2 by discussing the principles of PS, M-ary SVM and CS M-ary SVM. In Section 3, we describe the experimental system. In Section 4, we discuss the experimental results. Finally, we provide some concluding remarks in Section 5.
## 4 Simulation Results  
We simulated four well-known schemes (RPQ, CSFQ, CHOKe and FIFO) and compared their fairness by analyzing the NBR behaviors. We developed a software simulator to perform all simulations, which has been used in our previous study [6]. The traffic types of generating packets in each case are described in their respective figures. In Figure 2(a,b), we consider two categories of network topologies: those with a single congested link and those with multiple congested links. Unless otherwise specified, we use the following parameters in the simulations. Each link capacity is of 10 Mbps, and the packet size is fixed at 1 KB. The buffer size for all schemes is set to 256 KB. In addition, we neglect the propagation delay of each link. In AFQ, the initial value of \(\alpha_{new}\) is set to 32, and the other parameters are set to \(T_{d}=200\) ms, \(k_{a}=0.8\) and \(k_{b}=1.5\). In RPQ, each output queue is set to 32 KB, and the other parameters are set as follows: \(\Delta=0.8\) ms, \(\alpha=0.8\), \(K_{d}=200\) ms and \(N=129\). With respect to CSFQ, \(K\) and \(K_{\alpha}\) are both set to 200 ms. CHOKe's parameters are set to the following values: \(max_{th}=120\) KB, \(min_{th}=40\) KB, \(w_{q}=0.002\) and \(max_{p}=0.02\). Finally, the duration on each simulation is 200 s.  
Figure 2: Two-layer mapping mechanism.
# Decoration of Polyfluorene-Wrapped Carbon Nanotubes with Photoleavable Side-Chains
## 2 Results and Discussion
### Photocleavage Study of The Polymers  
With **PF-TEG** (**P1**) and **PF-oNB-TEG** (**P2**) in hand, we studied the cleavage of the side-chain using UV-Vis absorption spectroscopy. To confirm that the polyfluorene does not degrade upon irradiation, **PF-N3** was also studied. Polymers were dissolved in tetrahydrofuran (THF), transferred into quartz cuvettes, and irradiated at 365 nm in a UV reactor. The UV-Vis spectrum of each sample was measured every 15 min for a total duration of 2 h, when no further changes in absorbance were observed (Figure 2). Not surprisingly, **PF-N3** and **PF-TEG** do not show any degradation during the irradiation process (Figure 2A,B). As shown in Figure 2C, when **P2** was subjected to the irradiation process, a decrease in the absorbance is observed at 300 nm, corresponding to the cleavage of the _o_-nitrobenzyl linker. Meanwhile, as the peak at 300 nm decreases, a new peak at 350 nm arises. This new peak corresponds to the _o_-nitroobenzaldehyde compound produced during the cleavage (see Figure S4) [65]. As shown in the spectrum, this new peak overlaps with the absorption of the polyfluorene. Therefore, the cleavage was also monitored on the _o_**NB-TEG-alkyne** side-chain (Figure 2D) and provided similar observations. This suggests that the cleavage is effective, and 2 h is sufficient to cleave the side-chain.  
Figure 1: Chemical structure of **PF-TEG** (**P1**) and **PF-oNB-TEG** (**P2**).  
To further characterize the cleavage, we used \({}^{1}\)H-NMR spectroscopy (Figure 3). Polymers were dissolved in CDCl\({}_{3}\) and irradiated for 2 h. Despite the appearance of new signals at 11 ppm and in the aromatic region (6.5-8 ppm) corresponding to the aldehyde and the nitrosobenzaldehyde derivative, respectively, the cleavage of the side-chain was incomplete after 2 h. Therefore, the irradiation was resumed for one more hour. Surprisingly, the degradation was still incomplete as observed by the presence of the aromatic signals corresponding to the \(o\)NB linker (Figure 3). The sample was then irradiated overnight and, as shown in Figure 3, the complete disappearance of aromatic signals corresponding to the \(o\)NB linker was observed. The control sample **PF-TEG** was also irradiated overnight, and no changes were observed (see Figure S5). The difference in the irradiation time evaluated by UV-Vis absorption spectroscopy and \({}^{1}\)H NMR spectroscopy can be explained by the significant difference in concentration of the samples between the two techniques (-0.1 mg/mL for the UV-Vis absorbance spectroscopy sample compared to -5 mg/mL for the \({}^{1}\)H-NMR spectroscopy sample).  
Figure 2: UV-Vis absorbance spectra overlays of (**A**) **PF-N3**, (**B**) **PF-TEG**, (**C**) **PF-\(o\)NB-TEG**, and (**D**) **\(o\)-NB-TEG-alkyne** side-chain only upon irradiation for 2 h at 365 nm in THF (0.1 mg/mL).
## 4 SF-PPP Performance Analysis of Android Mobile Phones
### Positioning Performance Analysis of Android Mobile Phones
However, with the C/N0-dependent weighting approach, the errors were decreased to 0.65 m, 0.42 m, and 0.90 m, respectively; an improvement as large as 62% could be observed in the vertical component. For the uncombined approach using the C/N0-dependent weighting method, the east, north, and vertical errors were 0.72 m, 0.51 m, and 0.66 m, respectively. The vertical component exhibited an improvement of about 27% compared with the GRAPHIC model, while the horizontal component showed little degradation. Figure 9: Positioning errors (left panel) and RMS values of errors every 5 min (right panel) of the SF-PPP solutions for P40 smartphone with the internal antenna using the elevation-dependent weight model (**a**) and the C/N0-dependent weight model (**b**). Figure 10: Histograms of the SF-PPP positioning errors during the last 120 min for cases. The above results indicate that the uncombined approach could achieve better positioning precisions compared to the GRAPHIC model for P40 smartphones with either built-in or external antennas. For P40 GNSS data with its built-in antenna, the C/N0-dependent weighting strategy is more suitable and can improve positioning precision. Sub-meter level accuracy could be reached after about 1 h.
## 1 Introduction  
### Motivation  
Concerns about the depletion of IPv4 address space have existed ever since it was noticed that a possible address shortage might occur. As a result, a new version of the Internet Protocol (Version 6, IPv6) was specified in 1995 [1]. As of today, however, only few Internet Service Providers (ISPs) or other IT organizations have moved to the new protocol, even though the pool of available IPv4 addresses at the Internet Assigned Numbers Authority (IANA) was exhausted in 2011, which indicates that now is the time to gain knowledge, gather experience, and prepare for deployment of IPv6-ready infrastructures [2]. The main features of IPv6 are introduced in this paper and can be found in Section 2.  
While the IPv6 standard has matured, in particular during the last decade, a lot of research has been invested into finding possible IPv6 security issues and solutions. Two official organizations from the U.S. (National Institute of Standards and Technology, NIST) and Germany (Bundesamt fur Sicherheit in der Informationstechnik, BSI) have published guidelines for a secure IPv6 deployment. However, topicality of content and coverage of important IPv6 topics are crucial to make such guides useful for practitioners. As more organizations need to deploy IPv6 infrastructures, an evaluation of these guidelines is necessary in order to assess the quality of their advice and to make sure they provide the right information for a secure deployment, with up to date methods and techniques.  
The current article aims to close this gap by providing a methodology for evaluating and comparing theses two guidelines. This methodology can be adapted by individual organizations for prioritizing their individual knowledge needs and for selecting an appropriate guideline (or sections of it) accordingly. Moreover, we present the results of a small-sized global survey of IPv6 experts and their aggregated importance weightings of topic categories for a secure IPv6 deployment. Partly based on these weights, we conducted a first iteration of our methodology and present the results of our comparative evaluation of the guidelines.
## 3 The Proposed Distributed SPARQL Query Processing Scheme
### Overall Architecture  
The proposed scheme is a master-slave structure in the Spark cluster environment, as shown in Figure 1. RDF is a directed graph \(G=(V,E)\) represented by triple patterns such as subject-predicate-object, where the vertices \(V\) are the subject and the object, and the directed edges \(E\) are the predicates expressing the relation between the subject and object. A client sends a request for SPARQL query processing to the master, and the master divides the SPARQL query into subqueries \(SQ_{i}\) in the query decomposition. The divided subqueries \(SQ_{i}\) are grouped based on the criterion of related nodes. For the grouped subqueries \(SQ_{j}\), all possible query execution paths are created that are query-processable in the query execution path generation. From the created possible performing query paths, the optimal query execution path is identified through the algorithm that considers join and communication costs and queuing time in each of the query execution paths. The join and communication costs can be reduced during query processing by processing a query through the optimal query execution path. The subqueries that are grouped into slaves according to the selected query execution path are transferred as they are transformed into each of the RDD, and RDF subgraph \(SG_{i}\) that are matched with the subqueries are parsed. For each of the subqueries, the intermediate results \(IR_{i}\) are produced after data parsing, and query processing is performed through data communication and join according to the query execution path. After query processing is complete, a slave that owns the result sends the results to the master. Once the master receives the result from the slave, it sends the result to the client to complete the query processing.  
Figure 1: Overall architecture of the proposed scheme.
# A Crypto Accelerator of Binary Edward Curves for Securing Low-Resource Embedded Devices
## 1 Introduction
### Related Work
The work in [28] proposes a modular radix-2 interleaved multiplier for a low-latency architecture. This improved multiplier is intended to require less computing time, clock cycles, and area. For this purpose, the Montgomery ladder algorithm is utilized in this architecture. Nevertheless, the author in [28] does not mention the specific curve parameters or point multiplication scenarios where the proposed architecture might excel or face challenges. Understanding the scalability and adaptability of the multiplier to different curve sizes and security levels is crucial in assessing its applicability in real-world cryptographic systems. Finally, the authors in [29] propose a hybrid algorithm combining Montgomery and double-and-add techniques. The authors optimize the clock cycle by utilizing a modular Montgomery radix multiplier. Additionally, they design architectures for pipelining as well as those without pipelining. By leveraging the hybrid algorithm and incorporating the modular Montgomery radix multiplier, the authors are able to enhance the efficiency and security of point multiplication on BEC. The shortcoming of [29] is the lack of scalability. It causes uncertainty for how well the proposed designs will perform and adapt to larger or more complex cryptographic computations.
# Unsupervised Detection of Multiple Sleep Stages Using a Single FMCW Radar
## 3 Sleep Stage Detection
### FMCW Radar-Based Movement Detection  
The subject's motion \(Mov(t)\) is defined by accumulating the differences in the radar signal magnitude over time to measure the body movement observed during the \(REM\) sleep stage [33].  
\[Mov(t)=\sum_{t=1}^{T}|m(t)-m(t-1)| \tag{9}\]  
where \(T\) is the time window for the movement extraction. Figure 3 shows the change in the movement quantification indicator \(Mov(t)\) according to body movement. Figure 3a shows that a distortion in the intermediate-frequency signal occurred over the interval in which the subject moved in the sleep state. In the same interval, the subject's movement, as detected by the radar, increased sharply, as shown in Figure 3b.  
To investigate the application potential of radar-based motion estimation indicators, the sudden movement intervals were compared with the intervals in which the numerical changes in acceleration for each body part were measured using an accelerometer. Among the 14 Perception Neuron Studio motion sensors (Noitom Inc., Miami, FL, United States) attached to the body, and accelerometer data obtained from the three body parts where the actual object movement occurred were used as the ground truth for comparison. As the target movement detected by the FMCW radar coincided with the intervals of the numerical changes in body movement measured using an accelerometer, it was found that \(Mov(t)\) reflects the subject's body movement.  
Figure 2: \(REM\) sleep stage detected with the FMCW radar. (**a**) PSG results. (**b**) Changes in breathing rate per minute (**c**) Radar-detected \(REM\) sleep stage.
## 8 Technical and Ethical Considerations for Effective Implementation of 5G Security
### Integrated Approach for Effective Implementation  
For the effective implementation of 5G security, both technical and ethical considerations need to be integrated cohesively into a holistic framework. Technological solutions should be designed and deployed with ethical guidelines in mind, ensuring that advancements in security do not come at the cost of privacy or equity. Likewise, ethical considerations should be technically feasible and not hamper the performance or effectiveness of the security solutions. Standardization bodies and governance organizations have a significant role to play in ensuring that technical specifications include ethical mandates. Moreover, a multidisciplinary approach involving technologists, ethicists, policymakers, and legal experts is essential for comprehensively addressing the intricate landscape of 5G security.
# A Numerical Study on Computational Time Reversal for Structural Health Monitoring
## 4 Applications with Numerical Examples
### Damage Identification  
#### 4.4.1 One-Dimensional Beam  
In this section, a small damaged area is assumed on the beam, from \(x_{1}=0.1795\ L\) to \(x_{1}=0.18\ L\) where the modulus of elasticity \(E_{sc}=0.2\) for the material and the cross-section \(A_{sc}=0.5\) are reduced. The corresponding reduced wave speed on that altered area is \(c_{sc,1}=0.2\ \mathrm{m/s}\). For that controlled numerical experiment, it is possible to estimate or  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline  & \multicolumn{6}{c}{**Original Signals**} & \multicolumn{6}{c}{**Noise Considered**} \\ \hline \# **Recs/Opt.set** & \(\mathbf{A}\) & \(\mathbf{B}\) & \(\mathbf{C}\) & \(\mathbf{D}\) & \(\mathbf{B}\) & \(\mathbf{A}\) & \(\mathbf{B}\) & \(\mathbf{C  
even with accuracy, calculate the time needed for the incident field to reach the scatterer. The source pulse is emitted at 0.75 \(L\) and the first damaged boundary is at 0.18 \(L\), the distance between these nodes is 0.57 \(L=17.1\) m. The wave speed for axial waves is \(c_{1}=1\) m/s, therefore a time \(t=17.1\) s. The time \(t_{sc}^{a}\) that the damaged area acts as a source (scattered field) because of the damage corresponds to the time when the axial wave, originally created at time \(t_{0}\) because of the primal source, approaches the damaged area. Therefore, the corresponding refocusing time during the backward step is \(T-(t_{sc}^{a}+t_{0})\), where \(T\) is the total duration of forward process. Similarly, the refocusing time for transverse waves is \(T-(t_{sc}^{b}+t_{0})\), with \(t^{b}\) the time needed for bending waves initiated from the source to approach the damaged area. The plots of Figure 10 illustrate refocusing cases considering different receivers as well as distinguishing the case when axial or bending waves are examined. As it can be observed, the identification and location of the damage on the beam for almost any selection of receiver and wave monitoring (DOF type) is possible. The exception seems to be the case of Figure 10f, which is intentionally presented here, in order to mention the reason that is the limited duration time of the experiment. Bending waves initiated from the secondary source at the damage area do not have the necessary time to approach the rightmost receiver, also keeping in mind the initial time \(t_{0}\) and the time \(t_{sc}^{b}\) needed for the primal wave to approach the damage area and fire the secondary wave emission.
## 5 Feasibility Study Through System Simulations
### Mechanisms to Optimize the Models and Minimize the Error Distance
#### 5.7.2 Mechanism 2: Selection of the Best Model Weights Among Training Epochs  
Mechanism 2 consists of the selection of the best model weights among the training epochs. The goal is to select the model weights that minimize the positioning error, generalizing the model for fixed tiles. This is achieved using a checkpoint call-back function that retains the weights for the best optimization metric found among the epochs. The weights for the best value obtained of the selected optimization metric are retrieved at the end of all of the training epochs.  
This mechanism is explained in step 6 of the block diagram describing the model training execution flow in Section 5.6.3 and depicted in Figure 15.
## 4 Results
### Effects of LAI at Different Spatial Scales for Wheat Yield Estimation  
Regional crop yield estimates mainly rely on remotely-sensed LAIs during the crop growth season. In addition to the effects of LAI in different temporal scales (containing the phenological stages and temporal frequency), the spatial scale of LAI also affects the accuracy of regional yield estimations. For example, coarser pixels with abundant mixed landscape patterns usually result in greater spatial scale errors of LAI values obtained from more heterogeneous surface, which increase the errors of regional crop yield estimates. In addition, the abundant and detailed information that is supplied by remote sensing data with high spatio-temporal resolution is limited by high computational costs. To analyze the impacts of LAI at different spatial scales, six spatial scales of LAI (with pixel sizes of 1 km, 2.5 km, 5 km, 7.5 km, 10 km and 15 km) were aggregated based on the nearest neighbor algorithm by using the remotely-sensed LAI data and assimilated into a crop model using the POD4 DVar-based strategy to estimate regional yield. The results (Figure 12) showed that the accuracies of the assimilated yields at the county scale tended to gradually decrease as the pixel resolution of assimilating LAI decreased from 1 km-15 km, the RE increased from 7.77%-10.45% and the RMSE increased from the 172-573 kg-ha\({}^{-1}\), respectively. In contrast, the computation time decreased from 6.21 h down to 0.04 h. Consequently, it is important to select a reasonable pixel size for remotely-sensed observations to compromise between the accuracy and efficiency of operational regional crop yield estimation systems.  
Figure 11: Accuracy of estimated wheat yield using LAI from a different temporal frequency compared with the official statistical yields at the regional scale.