esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion
### Limitations  
Despite the promising results, this study has some important limitations that should be acknowledged. First, although the aPWV values used as reference standard measurements were obtained using the Mobil-O-Graph(r), it does not represent the gold standard for AS assessment, which is the cfPWV measured via explanation tonometry. This difference may introduce some degree of measurement bias and should be considered when interpreting the results. In this regard, different studies [29, 30] emphasize that the methodologies used to assess PWV require validation in larger and more diverse populations, supporting the notion that further studies are needed to evaluate the clinical applicability of each device across different cardiovascular risk profiles. However, the use of the Mobil-O-Graph(r) was a deliberate methodological choice aligned with the study's translational aims. Unlike cfPWV measurements obtained via explanation tonometry, which require trained operators and longer acquisition times, the Mobil-O-Graph(r) provides a non-invasive, automated, and operator-independent alternative that enables broader applicability in real-world clinical settings.  
Second, the training data predominantly included individuals with aPWV values below 10 m/s, which is characteristic of apparently healthy populations. While the models were externally validated on the ExIC-FEp cohort, which includes patients with elevated AS due to cardiovascular conditions, additional validation on larger and more clinically representative cohorts, composed exclusively of patients with suspected or confirmed cardiovascular disease, will be necessary to confirm the model's generalizability across the full spectrum of vascular risk.
# Tele-Assessment of Executive Functions in Young Adults with ADHD: A Pilot Study
## 5 Materials and Methods
### Procedure  
The evaluation was carried out on an individual basis by psychologists who had received specific training in using the TeleFE platform (Anastasis Cooperativa, Bologna, Italy, 2023) [82] for online executive function assessments. These psychologists, referred to as \"remote operators\", conducted the sessions from their homes or clinics. The participants--young adults with and without ADHD--were instructed to situate themselves in a quiet room or classroom with a stable and strong Internet connection. Before each session, their Internet access (via Ethernet, Wi-Fi, or hotspot) was tested to ensure connectivity.  
Each assessment session lasted approximately one hour, which included a brief familiarization period. This initial phase was crucial to engage participants, helping them become comfortable with the tasks while fostering their curiosity and participation. To begin the session, the remote operator sent a one-time access link to the participant, allowing them to log in to the TeleFE platform. Once connected, participants shared their screens so that the remote operator could monitor their activity. The operator then read the task instructions aloud, which the participants could also read on their screens.
###### Abstract
In this study, an image fusion model (HGF) was constructed by employing harmonic analysis (HA), guided filtering (GF), and Gram-Schmidt (GS) transform, aiming to perform the fusion of panchromatic-hyperspectral images. By analyzing and comparing the evaluation metrics of the processing results from different fusion algorithms at different wavelength intervals, we determined the optimal fusion model for monitoring surface elements such as soil, vegetation, and water. Our exploration contributes to the high-quality application of hyperspectral satellite images for quantitative inversion of surface elements.
## 1 Introduction
### Contributions to Knowledge  
The detailed contributions of this work are outlined as follows:  
* In this work, a framework is proposed that highlights how the channel estimation-based Deep Learning (DL) and power optimization scheme are jointly utilized for multiuser (MU) detection in the PD-NOMA system.
* A structured and mathematical analysis is introduced to derive a non-complex analytical form for the optimum power coefficient for each user on the basis of maximizing the sum rates in a downlink NOMA system.
* An optimized power scheme and fixed power scheme are both evaluated and compared when the proposed Deep Learning-based channel estimation scheme is implemented.
* To validate the efficiency of the proposed Deep Learning channel estimation scheme, the DNN model is inspected using a Rayleigh fading channel and Rician fading channel.
* As a benchmark comparison, we have also conducted the simulation environment related to the work that consider the DL for joint channel estimation and signal detection and compared it with our proposed DL scheme. The simulation results emphasized that reliability can be guaranteed by our proposed DL channel estimation scheme even when cell capacity is increased.
* In addition, different from the aforementioned works, in our proposed DL channel estimation algorithm, we implement a minimum number of DNN layers and a minimum number of pilot symbols to achieve a remarkable improvement in system performance. Moreover, no additional interference cancelation or noise elimination factors are utilized on the receiver side.  
The rest of this paper is organized as follows. Section 2 presents the system model. In Section 3, the characterization for the optimization problem is introduced. In Section 4, the optimization analysis is discussed in detail. In Section 5, RNN and LSTM DL schemes are described. Section 6 discusses the LSTM and NOMA framework. The channel estimation algorithm is summarized in Section 7. In Section 8, the simulation environment is described. In Section 9, the simulation results are discussed. Finally, the conclusions and future work are drawn in Section 10.
## 2 Rock Specimens and Experiment Preparation  
### Rock Specimens and Testing System  
The granite specimens (Figure 2a) were sourced from intact bedrock formations in Liuyang City, Hunan province, China. The detailed procedure for extracting the specimens as follows: (1) core drilling is performed in designated areas using a 50 mm diameter bit, with core lengths controlled within 300 mm; (2) immediate paraffin sealing is applied to obtained cores to minimize moisture loss-induced damage, followed by storage in core boxes; (3) transportation packaging is implemented through a layered configuration (inner to outer): core specimen \(\rightarrow\) plastic membrane \(\rightarrow\) core box \(\rightarrow\) wooden boards \(\rightarrow\) foam padding; (4) upon arrival at the lab, secondary machining is conducted according to ISRM-suggested methods [29]. Cylindrical specimens (\(\Phi\)50 \(\times\) 100 mm) are fabricated through precision grinding, satisfying geometric requirements of <20 \(\upmu\)m end flatness and <50 \(\upmu\)m parallelism deviation (Figure 2a). Prepared specimens are stored in hermetic containers for subsequent testing. To minimize potential disturbances to rock cores during sampling, we implemented the following measures: (1) the selection of intact and structurally stable granite formations as sampling locations; (2) strictly control drilling speed to minimize core disturbance during coring; (3) borehole spacing exceeding five times the drilling diameter to prevent stress interference between adjacent cores; (4) immediate paraffin sealing upon core extraction to minimize moisture loss, coupled with a multi-layered anti-vibration transport system to mitigate mechanical disturbances during transportation; (5) a single standard specimen preparation per 300 mm core segment to eliminate end effects. The physical parameters of the specimens are systematically listed in Table 1. A standardized nomenclature (\"GS-S-N\") was adopted, where GS denotes the granite specimen, S represents triaxial compression, and N indicates the specimen number.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Specimen**} & \multirow{2}{*}{
\begin{tabular}{c} **Strain Rate** \\ **(s\({}^{-1}\))** \\ \end{tabular} } & \multirow{2}{*}{**CP (MPa)**} & \multirow{2}{*}{**D (mm)**} & \multirow{2}{*}{**H (mm)**} & \multirow{2}{*}{**M (g)**} & \multirow{2}{*}{**V (cm\({}^{3  
Scanning electron microscopy (SEM) observations at varying magnifications (Figure 2b-e) revealed microstructural features of the granite specimen, including densely packed mineral grains, small pores, closed microcracks, and smooth surfaces. XRD results show that the granite is predominantly composed of quartz, K-feldspar, and biotite, consistent with its classification as biotite granite.
## 3 Results
### End User Perception  
Next, Table 2 presents the perception from a group of nine members of the Clinical Documentation Committee (group 1) and a group of six principal investigators (group 2) collected through the Technology Acceptance Questionnaire. Global results show that both groups agree with the usefulness (4.2), attitude toward using (4.2) and intention to use (4.1) the tool. Although the overall result in the easy to use dimension was (3.6), there were differences found in the perception of how easy to use the tool was. On the one hand, group 1 only received 45 min of training about the system and resulted in a neutral perception (3.1). On the other hand, group 2 received 45 min of training and later agreed (4.3) that the system was easy to use.
# Onboard Processing in Satellite Communications Using AI Accelerators
## 3 Onboard AI Applications
### Use Cases
#### 3.1.5 Antenna Beamforming
If we apply a Hamming window to reduce the SLL by 30 dB, we need to increase the number of antenna elements to 24 \(\times\) 24 to keep a more or less equal beamwidth. Figure 8 shows the directivity at \(\phi=0^{\circ}\) cut for the case when the array has tapering for SLL reduction. Nulling  
Multibeam interference can be avoided by generating nulls in the radiation pattern at the position of the interfering beam. Controlling the nulling is a straightforward process because the interference direction is known, which makes the implementation of the algorithm relatively simple. First, we need to obtain the weights of a beam that points towards the null angle, and then scale the beam weights and subtract scaled weights from the weights for the beam patterns that point towards the beam steering direction. The formulation of this nulling is presented in (3)  
\[W_{T}=W_{\theta_{0}\phi_{0}}-W_{null}\frac{W_{null}^{\prime}W_{\theta_{0}\phi_{ 0}}}{W_{null}^{\prime}W_{null}} \tag{3}\]  
where \(W_{\theta_{0}\ \phi_{0}}\) is the weight vector with the beams steering towards a certain \(\theta_{0}\) and \(\phi_{0}\) direction, and \(W_{null}\) represents the weight vector with the direction where the null is intended to be. Figure 9 shows the amplitude distribution and radiation pattern of a 16 \(\times\) 16 DRA that generates multiple nulling in a multibeam scenario. Figure 8: Azimuth cut of a 16 \(\times\) 16 DRA using subarrays as radiating elements separated by 2.5 \(\lambda_{0}\) with a Hamming window applied to the weight vector. All previous parameters can be controlled by AI, especially for a multibeam scenario with SLL, beamwidth, and nulling constraints for multiple beams. Future satellites will be equipped with an array of active antennas rather than a fixed multipoint beam pattern. This allows the generation of multiple spot beams with different numbers, sizes, and shapes.
# The Effect of Non-Transferred Plasma Torch Electrodes on Plasma Jet: A Computational Study
## 3 Results
### Case 1: Study of Cathode Shapes
#### 3.1.1 Current and Voltage  
Current and voltage are key operational parameters in arc plasma torches. Figure 4a presents simulated current-voltage characteristics for different cathode shapes. For input currents below 30 A, the relationship between current and voltage is linear. However, above 30 A, an inverse trend emerges; the voltage decreases as the current increases, consistent with the findings by [PERSON] et al., who attributed this to increased arc conductance [34].  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Model** & **Solved Regions** & **Boundary Conditions** \\ \hline Electric currents & Fluid and anode & \(j_{n}\) at cathode tip \\  & & Ground = anode \\ \hline Magnetic fields & Fluid and anode & Field components = \\  & & in-plane \\  & & vector potential \\  & & \(\Psi_{o}\) = 1 A/m \\ \hline Laminar flow & Fluid & \(u_{pli}\) = 5.53 m/s \\  & & \(u_{z}\) = 5.53 m/s \\ \hline Heat transfer & cathode, anode & \(T_{cathode}\) = 3500 K \\ in solids and fluids & and fluid & \(T_{ustr}\) = 300 K \\  & & \(h_{anode}\) = \\  & & \(10^{4}\) W/(m\({}^{2}\)K) \\  & & \(T_{ext}\) = 500 K \\ \hline \hline \end{tabular}
\end{table}
Table 2: Models and boundary conditions.  
While the overall trend remains consistent across cathode designs, voltage values vary slightly depending on shape. In the low-current region (\(<\)30 A), cathodes a, d, and f show higher peak voltages than b, c, and e. These differences are related to how each geometry influences arc resistance. At higher currents, flat cathodes exhibit the highest voltages, followed by tapered and conical shapes.  
In the model, current density is prescribed at the cathode tip, and voltage is computed via [PERSON]'s law. To analyze variation in arc behavior, a reference line is defined from the cathode tip to the start of the anode (Figure A1). Along this line, temperature, electrical conductivity, and electric potential are extracted for different input currents that are shown in Figure 4c legends.  
Figure 4c show that both conductivity (dash and dotted line) and temperature (solid line) peak near the cathode tip and decline toward the anode. These values also increase with higher current input. In contrast, Figure 4b shows that the electric potential (dashed line)increases steadily from the cathode to the anode, reflecting [PERSON]'s law; as conductivity drops, potential must rise to maintain current.  
Figure 4: (a) Current and voltage variation for different cathodes. (b) Electric potential (dashed line), (c) temperature (solid line), and conductivity (dash and dotted line) changes along the path of the electric arc formed from the cathode tip to the anode for different input currents.
## 2 Industrial uses of FW, Different from Anaerobic Digestion
### Biomaterials Production  
From organic waste, and especially from FW, biopolymers can be produced [53] by obtaining the necessary monomers through the fermentation of carbohydrate feedstocks by microbes [54]. These biopolymers are a suitable option for substituting petrochemical products, as they have similar properties and they ensure biodegradability [55].  
Examples of these biopolymers are polylacate, a plastic constituent obtained from lactate and lactic acid, polyhydroxyalkanotes, such as polyhydroxybutyrate, with characteristics that are similar to polypropylene and polyethylene, and succinate, which can be used for plastic and detergent production [56; 57].  
Recent research shows that biopolymers production from FW could be implemented with bioenergy production when combining anaerobic and aerobic processes. In this case, part of the volatile fatty acids from the anaerobic process can be transformed into polyhydroxyalkanoates, combining both biogas and biopolymers production [58].
## 5 Evaluation and Testing  
### Ontological Model Testing to Verify Competence Questions Using DL in Protege  
In this section, we verify the Competence Questions (CQs) by explaining a success scenario. Figure 9 demonstrates the ontological model testing the success scenario.  
**CQ:**_What roles are involved in examining cardiac diseases, performing medical tests, and recommending medicine for effective treatment?_  
Figure 8: Transformation mapping bootstrappers: A sample of database results retrieved using the Ontop framework.  
Figure 9: Cardiovascular disease ontological model testing and verification of competence questions (CQs).  
**Success Scenario:** The Triage Nurse role (e.g., _Triage_Nurse1_) is assigned to healthcare worker \"A\", who plays an active role in hospital care management and performs various tasks within the medical institution. Healthcare worker \"A\" is responsible for several activities, including conducting physical examinations to identify medical issues for patient treatment planning. Additionally, healthcare worker \"A\" possesses competencies in cultural, occupational, educational, and general areas (which are not shown for brevity) [4].  
We employed two essential tools, the DL query plugin in Protege 5.6.4, to standardize metadata and validate competence-related queries. This tool is crucial for verifying CQs from the federated ontological model repository and delivering a comprehensive response regarding the success of the scenario mentioned above. Figure 9 showcases the verification and testing of CQs.  
For practical validation and testing, domain experts reviewed the CQs during the information acquisition sessions with healthcare practitioners (HPs) and acquired relevant information and standard vocabularies for cardiovascular diseases (CVDs) for developing ontological meta-models for developing a robust FVKG framework.
# Study on Mechanism of Static Blasting-Induced Hard Rock Fracture Expansion
## 2 Principles and Mechanisms of Hard Rock Fracturing Using Static Blasting Technology
### Mechanical Examination of Static Breakers' Suttering of Hard Rocks
#### 2.1.2 Double-Hole Cracking  
The rock undergoes fracturing during the static fracturing process, as shown in Figure 3, with the mechanical effect being predominantly radial.  
The following assumptions are made to represent the superposition of the mechanical field distribution of the dual pores: the elastomers that constitute the dual fracture-causing pores are assumed to be under infinite internal pressure; the forces acting on their walls are considered static homogeneous loads; and the effect of the dual fracture-causing pores is the result of combining the effects of each of them acting on the infinitely large elastomers [24].  
The unit is subjected to horizontal and vertical strains as determined by the theory of elastic mechanics.  
\[\left\{\begin{array}{l}\sigma_{r}=\sigma_{r_{1}}+\sigma_{r_{2}}=-\left[\frac{r_ {1}^{2}}{x^{2}}q_{1}(t)+\frac{r_{2}^{2}}{(l-x)^{2}}q_{2}(t)\right]\\ \sigma_{\theta}=\sigma_{\theta_{1}}+\sigma_{r_{2}}=\frac{r_{1}^{2}}{x^{2}}q_{1 }(t)+\frac{r_{2}^{2}}{(l-x)^{2}}q_{2}(t)\end{array}\right\} \tag{9}\]  
when the stress reaches its maximum point, damage occurs, and the value of the ultimate stress is determined.  
\[\sigma=\left\{\frac{2r_{1}^{2}q_{1}(t)}{l^{2}}+\frac{2r_{2}^{2}q_{2}(t)}{\sqrt {\frac{r_{2}^{2}q_{2}(t)}{r_{1}^{2}q_{1}(t)}}}\left[1+\sqrt[3]{\frac{r_{2}^{2} q_{2}(t)}{r_{1}^{2}q_{1}(t)}}\right]^{2}\right. \tag{10}\]  
In engineering applications, the same type of crushing agent is frequently used, the same diameter of the hole is arranged, and the injection duration is the same, thus the double cracking hole characteristics are the same, there will be \(r_{1}=r_{2}=r\) and \(q_{1}=q_{2}=q\), and the following results may be obtained:  
\[\sigma_{\min}=\min\left\{\frac{8r^{2}q}{(l+2r)^{2}},2q+\frac{2r^{2}q}{(l-2r)^{2 }}\right\}=\frac{8r^{2}q}{(l+2r)^{2}} \tag{11}\]  
The third strength implies that if the rock is to be shattered, it must satisfy the following conditions:  
\[q\geq\frac{8r^{2}q}{(l+2r)^{2}}[\sigma] \tag{12}\]  
where \([\sigma]\)--crushed rock's maximum tensile strength, MPa.  
The use of large-diameter drilling holes and reducing the distance between the two holes can enhance the expansion pressure exerted by the static crusher, promote fissure development, and ensure effective fracturing when the ultimate tensile strength of the fractured rock is known. In the case of a multi-hole equidistant configuration, the highest stress is expected to occur along the axis line of the two fracture holes due to the superposition of tensile stresses on the unit. The maximum tensile stress value is located at the hole wall on the axis surface, which initially exceeds the rock's maximum tensile  
Figure 3: Analysis of double-hole rocks’ mechanical fracturing action.  
strength. As the expansion pressure increases, the fracture propagates in the axial direction until penetration occurs, ultimately leading to rock breakage.
# Finite-Horizon Kinetic Energy Optimization of a Redundant Space Manipulator
## 1 Introduction
Their approach, which has been developed for hydraulic actuators, performs sensibly better than general energy minimizing algorithms in the considered application, proving that actuator models might be beneficial for specific problems. However, the related burden of computational complexity means that this method cannot be used in real time. Recently, [PERSON] et al. [25] proposed a globally optimal inverse kinematics method for redundant manipulators, which allows for the optimization of different integral cost functions, such as kinetic energy and joint torques norm, can provide solutions with a variety of constraints, both linear and nonlinear, and is suitable for multi-objective optimization. Finally, [PERSON] et al. [26] presented a fast online predictive method to solve the task-priority differential inverse kinematics of redundant manipulators under kinematic constraints. In this paper, a novel inverse kinematics method for redundant manipulators is presented, which is able to provide a solution near to the global optimal one, is able to avoid singularities, and is suitable for real-time implementation. The proposed method is based on the optimization of the kinetic energy integral on a limited subset of future end-effector path points, making the manipulator joints to move in the direction of minimum kinetic energy. Rather than optimizing the cost function at every time step, the cost function is updated at larger intervals, and the appropriate choice of the update interval and the number of future exploration points allows a limited computational cost. The proposed method is tested by simulation for a three degrees of freedom (DOF) planar manipulator in a number of test cases, and its performance is compared to the classical pseudoinverse solution and to the one computed with a global optimal method. The paper is organized as follows: Section 2 presents and discusses the proposed optimization method and its main parameters; then, Section 3 presents the simulation setup and results and, in particular, a comparison between the simulation results obtained with the proposed method, the classical pseudoinverse solution, and a global optimal method. Finally, Section 4 concludes the paper.
# Analysis of Security Issues and Countermeasures for the Industrial Internet of Things
## 3 Security Issues in IIoT Systems
### Security Issue 6--Device Impersonation  
This is defined as the use of another person's identity, pretending to be someone else. Device impersonations in IIoT are becoming a critical issue because a particular service in IIoT is constructed by a collection of data sources that come from various devices, contexts, locations, and users [99]. In the case of a heterogeneous, dynamic IIoT system, each device has its own unique identity, but they may not be known to each other in advance. Therefore, securing identity management is crucial to protect fraud against device impersonation [89,100].  
Identity in a system establishes the authorization of a device or another system that is allowed to access certain information [82]. Damage can be done by distorting a device's identity (using identity fabrication) and aggravating the reputation of a system. Further, this can be performed via identity spoofing, where malicious entities gain unlawful entry into IIoT regularities. This can lead to an attack that can block or manipulate a system's resources and disrupt the integrity of a database by data forgery. We note that design of an identity management mechanism would not only consider the device's identifiable information but also take into consideration the attributes and the context of the systems [101].