esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Testing Procedures  
Isokinetic and isometric strength were evaluated with a functional electromechanical dynamometer (FEMD) (Dynasystem, Symotech, Granada, Spain) [18]. A standard grip was used to execute the two TRE. The distance between the acromion and the knuckle of the middle finger was measured manually to establish the range of motion (ROM) of the HCW exercise, and the distance between the acromion and the end of the middle finger was the ROM of the LCW exercise. Measurements were made by applying an anthropometric measurement protocol based on the internationally validated recommendation [20] and using a SECA brand measuring tape.  
The initial position of HCW was with the participant standing with feet shoulder-width apart, holding the grip with both hands, elbows extended, and the shoulder flexed at 90\({}^{\circ}\) measured with a goniometer (Gymna hoofdzetel, Bilzen, Belgium). Then, with a slight flexion of the knees (<20\({}^{\circ}\)), the participant rotated the trunk with a forceful horizontal movement until the end of the ROM (concentric phase) and then had to try to retain the movement back (eccentric phase) (Figure 1).  
And the initial position of the LCW exercise was with the participant standing with feet shoulder-width apart, holding the grip with both hands below the hip, (at the level of the anterior superior iliac spine), elbows extended. The initial position of the arms was with the grip in contact with the participant's thigh. Then, with a slight flexion of the knees (<20\({}^{\circ}\)), the participant rotated the trunk with a forceful movement while raising the arms diagonally until the end of the ROM (concentric phase) and then had to try to retain the movement of return (eccentric phase) (Figure 2).  
The participants attended a familiarization session with the FEMD. Familiarization consisted of a 60-min session, a 10-min warm-up, and then the familiarization with the FEMD was performed at the same velocities as the assessment, with a specific ROM for each subject (one series of two submaximal and five maximal repetitions). These velocities were selected for participants to ensure that they did not lose the correct exercise technique. In this session, the ROM for each subject was recorded. The instructions given to the participants were always the same, and no feedback or encouragement was provided.  
Figure 1: Assessment of horizontal cable woodchop exercise using a functional electromechanical dynamometer.  
Figure 2: Assessment of low cable woodchop exercise using a functional electromechanical dynamometer.  
After the warm-up, participants performed one set of five repetitions of two exercises in each test condition. The LCW and HCW exercises were tested in isokinetic mode at two different speeds (0.50 m\(\cdot\)s\({}^{-1}\) and 0.70 m\(\cdot\)s\({}^{-1}\)) and (0.40 m\(\cdot\)s\({}^{-1}\) and 0.60 m\(\cdot\)s\({}^{-1}\)), respectively. In addition, a 6-s isometric evaluation was performed in the initial position of each exercise. Between each series, rest for 3 min. The rater was blind to the results of their measurements and additional cues that were not part of the test.
## 2 Computational Methods and Model
### Wavenumber-Frequency Analysis  
The phase speed \(v_{p}=\omega/k\) can be used as a criterion to decompose wall pressure fluctuations into its incompressible and compressible components [20]. The periodogram of surface pressure fluctuation can be obtained from the 3-D Fourier transform of the surface pressure in the 2-D space and time domain [21]. The power spectral density (PSD) of the  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Equations** & **Discretization Method** \\ \hline Pressure & Second order \\ Momentum & Bounded central differencing \\ Energy & Second-order upwind \\ Transient formulation & Second-order implicit \\ \hline \hline \end{tabular}
\end{table}
Table 2: Discretization schemes of governing equations.  
wall pressure fluctuations can be estimated using the periodogram method in the following form [19]:  
\[S(\mathbf{k},\omega)=\lim_{T,L_{1},L_{2}\rightarrow\infty}\frac{1}{L_{1}}\frac{1}{L_{2 }}\frac{1}{T}\ \langle\hat{p}_{L,T}(\mathbf{k},\omega)\cdot\hat{p}_{L,T}^{*}(\mathbf{k},\omega)\rangle \tag{8}\]  
where  
\[\hat{p}_{L,T}(\mathbf{k},\omega)=\int_{-T/2}^{T/2}\int_{-L_{1}/2}^{L_{1}/2}\int_{-L _{2}/2}^{L_{2}/2}p^{\prime}(\mathbf{x},t)e^{-i(\mathbf{kx}+\omega t)}dx_{1}dx_{2}dt \tag{9}\]  
and \(\hat{p}_{L,T}^{*}\) is a complex conjugate of \(\hat{p}_{L,T}\). In Equations (8) and (9), \(L_{1}\), and \(L_{2}\) are the length of space domain in \(x_{1}\) and \(x_{2}\) direction, respectively, and \(T\) is the period. In the 3-D periodogram, the acoustic and hydrodynamic components can be separated using the slanted Dirac cone. The acoustic wavenumber \(k_{a}\) is used as the criteria to distinguish between the incompressible and compressible components defined as  
\[k_{a}=\omega/c_{0}=\sqrt{k_{x_{1}}^{2}+k_{x_{2}}^{2}}+k_{x_{1}}M \tag{10}\]  
where \(M\) is the Mach number. A region that satisfies the unequal equation of \(|\mathbf{k}|>k_{a}\) are then classified as incompressible waves and otherwise as compressible ones. Figure 2 illustrates the slanted Dirac cone, which separates the compressible and incompressible components, for the case where \(U_{0}=300\) km/h and \(c_{0}=343\) m/s. For more detailed description please refer to reference [15].
## 3 Resonant Converter Families
### Classification of Resonant Converter
#### 3.2.2 Parallel Resonant Converters  
The parallel resonant converter is classified as a two-element tank converter, as shown in Figure 19b. The resonant capacitor \(Cr\) must be in parallel with the load and the diode rectifier network \(DR\). In the case of effective load resistance \(R_{ac}\), the value is obviously larger compared to resonant capacitor reactance \(Cr\), meaning that the resonant current is independent from the load. Furthermore, the voltage across the parallel resistance \(R_{ac}\) and  
Figure 24: \(SRC\) half-bridge configuration [103].  
Figure 25: Equivalent circuit of the DC-DC series resonant converter [16].  
the resonant capacitor can be increased by reducing the load. Due to its voltage filtering, the _RTN_ delivers a sinusoidal voltage \(V_{R}\) and the _DR-LPF_ set must be of an inductive nature. The equivalent resistance \(R_{ac}\) seen from the input terminals of the _DR-LPF_ set is given by Equation (18), the load quality factor by Equation (19), and _PRC_ voltage gain is given by Equation (20). _PRCs_ can step the output voltage down or up depending on the variation in the control switching system frequency. The voltage output can be adjusted with load states, whereas the resonant current is restricted to resonant inductor data; this causes the _PRC_ to be appropriate for open and short circuit applications [80]. _AC_-equivalent circuits are shown in Figure 26.  
\[R_{ac}=\frac{\pi^{2}}{8}R_{L}\text{ {Reflected load resistance}} \tag{18}\]  
\[Q=\frac{R_{ac}}{Z_{O}}\text{ {The load quality factor}} \tag{19}\]  
\[M=\frac{V_{o}}{V_{in}}=\frac{1}{\sqrt{\left[1-\left(\frac{f_{s}}{f}\right)^{ 2}\right]^{2}+\left[\frac{f_{s}}{f_{r}}\times\left(\frac{1}{Q}\right)\right]^ {2}}}\text{ {Voltage gain}} \tag{20}\]
## 1 Introduction  
In the event of an acute ischemic stroke, the blood supply is occluded in the cerebral blood vessels, thus causing cerebral infarction which may lead to severe neurological impairment and even death [1]. Studies have shown that thrombol treatment is feasible and effective in treating patients with acute ischemic stroke using tissue plasminogen activator (tPA), which is the only thrombol drug approved by the Food and Drug Administration (FDA) and, correspondingly, therapeutic goods administration (TGA) [2]. However, the administration of tPA requires a prior brain scan via a CT scanner to determine the suitability of such medication, and its usage is generally constrained to a time window of up to 4.5 h (or up to 9 h with CT-perfusion selection to detect potentially reversible ischemia) after the onset of stroke, where its effectiveness decreases as time progresses [3]. Due to its highly time-sensitive nature, earlier stroke treatments should be enforced to improve the likely patient outcome, where ideally treatment should be administered within the first hour after the onset of stroke symptoms--the 'golden hour' for the best recovery result [4; 5]. In order to treat such disorders in large countries where the community is sparsely located away from hospital services, alternative avenues are being assessed. One such avenue is a mobile stroke unit.
# 3 GPP Evolution from 5G to 6G: A 10-Year Retrospective
## 1 Introduction
It also introduces subband non-overlapping full duplex (SBFD) for more efficient spectrum use, low-power wake-up signal (LP-WUS) to extend device battery life, and ambient IoT, which facilitates ultra-low-power connectivity for massive IoT applications. Additionally, 3 GPP conducts studies on channel modeling for integrated sensing and communication (ISAC) and the 7-24 GHz spectrum (aka., frequency  
Figure 1: 3 GPP evolution roadmap from 5G to 6G (indicative). range 3 (FR3)). These advancements not only enhance 5G-Advanced capabilities but also prepare the evolution toward 6G. Release 20, set to start in the second half of 2025, represents a critical juncture in the evolution from 5G to 6G. It will serve as both the culmination of 5G-Advanced and the early bridge to 6G. On one hand, it will focus on a more selective set of essential enhancements for addressing commercial deployment needs. On the other hand, it will start a series of 6G studies, covering use cases, service requirements, scenarios, performance requirements, architecture, and technology components. These 6G studies will guide the development of 6G specifications in Release 21, aligning with the ITU's IMT-2030 timeline [13]. Throughout this 10-year journey, 3 GPP's evolution has been marked by collaboration among stakeholders. The collective effort has driven advancements not only in 5G performance but also in addressing societal needs such as digital inclusion, sustainability, and public safety [14]. As we approach the 6G era, the lessons learned from 5G's development will serve as valuable guidelines. This article aims to provide a holistic look at the milestones, breakthroughs, and challenges that defined 3 GPP's progression from Release 15 to Release 20, as summarized in Table 1. After examining the 3 GPP evolution path from 5G to 6G, this article presents five key lessons, offering guidelines on 6G evolution for 2030 and beyond.
## 3 Use Case. CEDER-CIEMAT Microgrid
### Microgrid Energy Management  
According to the methodology defined in this paper, when the microgrid consumes power from the distribution network, if possible, the output of renewable generators should be increased. If this is not possible, the dispatchable storage and generation systems will be started up according to the performance calculations we conducted in the previous section. When the microgrid injects energy into the distribution network, the storage systems will be recharged (if they have the capacity to store more energy) according to their performance.  
Energy management for recharging the ESS will be such that batteries will only be charged or the pumping system will only be used when there is surplus energy in the microgrid, so that the energy used is free. This recharging will be conducted according to the performance of the systems, starting with charging the lead-acid PEPA I batteries, then the lead-acid PEPA II batteries, followed by the LFP batteries, and lastly, the pumping system will be used. With this strategy, enough energy is stored during the months of April to October when there is abundant solar radiation, but not during the winter months when there is less radiation and therefore lower surplus generation.  
Energy management for discharging the ESS is carried out with two different objectives: on the one hand, to reduce consumption from the distribution network for periods of several hours, and on the other hand, to eliminate power peaks (maximum 1 h), always depending on their efficiency. This is always conducted on the basis of efficiency, so that the most efficient ESS is used first, followed by the second most efficient system, and so on. Each type of management will be explained in the following section, Results.
## 2 OBS Networks
### Functional Mechanisms of OBS Nodes  
Depending on their sending/receiving status, OBS edge nodes can be viewed either as ingress or as egress nodes. When acting as ingress nodes (see Figure 3(a)), edge nodes are responsible for burst assembly and connection setup mechanisms. Core nodes are located in the core of OBS networks where a transparent switching of bursts from one optical fiber to another takes place (see Figure 1). Core nodes (see Figure 3(b)) perform, the following main functions: scheduling of resources and contention resolution.  
Figure 2: Functional block diagram of IP over OBS (adapted from [20]).
## 4 Challenges
### Security and Privacy Challenges  
We now discuss the security and privacy challenges. Since DT needs to update the state of physical objects in real time through network communications, DT will be subject to cyber attacks, such as integrity attacks on physical hardware and sensors, transmission, and digital systems. Taking the data integrity attack as an example, the adversary can directly attack IoT devices as data collectors, causing them to upload invalid/misleading data. Alternatively, an adversary can attack the gateway, to which the IoT device uploads data, mixing the invalid/misleading data with the correct data collected by IoT devices. Finally, the adversary could directly inject false data into the DT. Because the DT and physical objects are closely connected, any one of these attacks will yield a significant impact on the integrity of the entire system.  
Additionally, from the perspective of confidentiality, the DT applications contain a large amount of privacy-sensitive information, such as medical records, autonomous vehicle sensing information, and real-time smart grid operation information. Therefore, it is not only necessary to implement an authentication mechanism for physical objects but also an authentication mechanism for digital communication and machine-to-machine transmission. Nonetheless, it can be costly to implement authentication mechanisms on low-energy IoT devices. In this case, knowing how to handle the authentication process on devices with limited power has become a challenge. From a usability point of view, DT applications rely on sensor information from the object layer to help the DT build the digital clone of the physical system. In this case, adversaries can launch attacks on sensor or gateway, such as a denial of service (DoS) attack or malware propagation. Once the gateway or sensor is compromised, it is difficult for DT to obtain the overall states of the physical system. For this reason, it is important to propose and validate mitigation mechanisms to reduce the impact of such attacks.
# Application of Riemannian Seismic Ray Path Tracing in Salt Dome Prospecting
## 4 Results (Geophysical Applications)
### Simplified Speed Profile of Earth's Mantle  
In order to try to emulate the behaviour of P-wave speed along the mantle, the velocity model is simplified by neglecting the well-known 410 and 660 discontinuities, and before reaching the D\({}^{\prime\prime}\) layer [58]. The simplified velocity model for the mantle herein applied is given by  
\[v(x,z)=6(1+z)^{1/9} \tag{19}\]  
which yields the following geodesic (refraction) equations:  
\[\ddot{x}(t)=\frac{2\dot{x}(t)\dot{z}(t)}{9[1+z(t)]}\, \tag{20}\]  
and  
\[\ddot{z}(t)=\frac{\dot{z}^{2}(t)-\dot{x}^{2}(t)}{9[1+z(t)]}. \tag{21}\]  
The obtained ray diagram in the geophysical strata shown in Figure 2. The three rays \(R_{1},R_{2}\) and \(R_{3}\) depicted in such a figure have the same initial position conditions, \(x(0)=0\) and \(z(0)=0\), as well as \(v_{x}(0)=50\) km/s and \(v_{z}(0)=283.56\), 137.37, 86.60 km/s, respectively, as speed initial conditions.  
In this case, as the velocity model in Equation (19) is simple enough to obtain the Ricci scalar,  
\[R=R(z)=-\frac{8}{(1+z)^{16/9}} \tag{22}\]  
which indicates that for the underground, the curvature is negative.  
Figure 1: Refracted seismic ray (black line) in a synthetic setup with two different homogeneous strata horizontally separated at \(z=2500\) km. The original trajectory of the ray in the second stratum is shown in dashed yellow line.
## 4 ITS Threats Analysis and Classification
### Classification of ITS Attacks and Cryptographic Countermeasures  
ITS applications are susceptible to several kinds of threats and attacks, as shown in Figure 8, such as passive and active attacks. While the passive attacks seriously impair the confidentiality and privacy of the network, the active attacks can damage the network resources and functioning, by inserting, deleting or modifying the exchanged packets. Several classifications of these attacks have been proposed in  
\begin{table}
\begin{tabular}{l|c|c|c|c|c|c|c} \hline AttacksCompromised Security Services & Availability & Authentication & Non-Repudiation & Integrity & Privacy & Confidentiality \\ \hline Denial of service attacks (DoS) & & & & & & & \\ \hline Jamming attack & & & & & & & \\ \hline Sybil attack & & & & & & & \\ \hline Variants of DoS (greedy, & & & & & & & \\ Black hole, gray hole, sink hole & & & & & & & \\ Wormhole, malware, masquerading & & & & & & & \\ Spamming, tunneling) & & & & & & & \\ \hline Loss of event traceability & & & & & & & \\ \hline Illusion & & & & & & & \\ \hline Replay & & & & & & & \\ \hline Key and/or certificate replication & & & & & & & \\ \hline GPS spoofing/position faking & & & & & & & \\ \hline Message tampering/ & & & & & & & \\ suppression/fabrication/alteration & & & & & & & \\ \hline Broadcast tampering & & & & & & & \\ \hline Node impersonation & & & & & & & \\ \hline Brute force & & & & & & & \\ \hline Eavesdroping & & & & & & & \\ \hline Traffic analysis & & & & & & & \\ \hline Tracking/social engineering & & & & & & & \\ \hline Timing attack & & & & & & & \\ \hline Man in the middle attack & & & & & & & \\ \hline \end{tabular}
\end{table}
Table 4: Impact of attacks _versus_ compromised security services.  
the literature [18,50]. As in [13], this section adopts a cryptography-based classification to classify all of the major ITS attacks and to analyze the existing cryptographic countermeasures. Indeed, modern cryptography offers a variety of security methods that can be used to ensure the aforementioned ITS security requirements, such as encryption and decryption algorithms, key generation and exchange protocols, hash functions, digital signatures and many others. In the following, we analyze in detail the attacks and countermeasures on the availability, authenticity and identification, integrity and data trust, confidentiality, privacy and non-repudiation security requirements, as listed in Table 4.
## 2 Material and Methods
### Composite Fabrication Process  
In the composite fabrication process, two AA5083 plates were initially joined using Friction Stir Welding (FSW), as illustrated in Figure 1a. Following this, the weld joint was drilled repeatedly to create small holes measuring 2.5 mm in diameter and 4 mm deep, with a spacing of 15 mm between the holes, as shown in Figure 1b; reinforcing particles were then introduced into these holes. To prevent the scattering of particles during subsequent Friction Stir Processing (FSP), the holes were sealed using a pin-less FSP tool, with this step depicted in Figure 1c. The final pass of FSP was carried out at room temperature, and the process is illustrated in Figure 1d. Figure 2 shows the tools, both with pin and pin-less configurations, utilized in the fabrication of the composite materials. A high-speed steel tool (AISI 4140) with a shoulder diameter of 20 mm, a triangular pin measuring 5.8 mm, and a probe diameter of 7 mm was employed for both the FSW and FSP procedures.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**No of Tests** & **Traverse Speed [mm/min]** & **Rotational Speed [rpm]** & **Tilt Angle [\({}^{\circ}\)]** \\ \hline
1. & 30 & 600 & 1 \\
2. & 45 & 600 & 1.75 \\
3. & 60 & 600 & 2 \\
4. & 30 & 900 & 1.75 \\
5. & 45 & 900 & 2 \\
6. & 60 & 900 & 1 \\
7. & 30 & 1200 & 2 \\
8. & 45 & 1200 & 1 \\
9. & 60 & 1200 & 1.75 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Taguchi L9 design matrix.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Processing Parameters**} & \multicolumn{3}{c}{**Levels of Parameters**} \\ \cline{2-4}  & **1** & **2** & **3** \\ \hline Tool traverse speed (TS) in mm/min & 30 & 45 & 60 \\ Tool rotational speed (RS) in rpm & 600 & 900 & 1200 \\ Tool tilt angle (TA) in \({}^{\circ}\) & 1 & 1.75 & 2 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Processing parameters with their levels.
## 5 Results
### Role of Cloud Cover in Modulating OSR  
A key aspect is examining how OSR varies with cloud cover. Figure 7 highlights the temporal relationship between Cloud Area Fraction (CAF) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and OSR as observed by Uvsq-Sat and CERES.  
As highlighted by [PERSON] et al. (2024) [35], cloud variability is one of the dominant factors driving changes in OSR. This relationship is reflected in recent trends, with similar patterns observed between CAF (2013-2024) and OSR as measured by CERES (2013-2024) and Uvsq-Sat (2021-2024). Cloud cover is influenced by a complex interplay of atmospheric,  
Figure 7: 12-month running means of OSR anomalies from Uvsq-Sat and CERES (EBAF and SSF1 deg products), alongside CAF data derived from MODIS.  
oceanic, and surface factors. Key drivers include atmospheric moisture and humidity, which provide the water vapor necessary for cloud formation, and temperature profiles that affect cloud altitude and type. Large-scale atmospheric circulation patterns, such as the Hadley cell and jet streams, modulate regional cloud distribution, while ocean-atmosphere interactions--particularly ENSO phases--alter SST and convection, impacting cloud dynamics. Aerosols act as cloud condensation nuclei, influencing cloud microphysics and coverage. Additionally, surface characteristics, including land-ocean contrasts, vegetation, and urbanization, affect local cloud formation through modifications of heat flux and surface roughness. Orographic effects from topography further induce localized cloud formation. Human activities, such as pollution and land-use changes, also play a significant role in altering cloud properties and spatial patterns. Understanding these factors is crucial for interpreting observed cloud cover variability and its effects on Earth's radiation budget. This integrated approach offers valuable insights into how cloud dynamics modulate radiative fluxes, improves the interpretation of satellite-based observations, and supports the evaluation and enhancement of climate model performance. The Uvsq-Sat NG mission aims to demonstrate the technical feasibility of combining visible cloud imagery with Earth's radiation budget measurements aboard a small satellite. Future developments will focus on enhancing spatial and temporal resolution, integrating multi-spectral observations, and improving retrieval algorithms to better quantify cloud radiative effects and their role in the climate system.