esa-sceva/satcom-chunk-collection huggingface dataset:
## 6 Applications in Medical and Food Systems  
_W. somnifera_ is rapidly advancing and is used for wide range of applications in medicinal and food sectors. Its potential is widely studied and can be used tradionally to treat number of health problems. The Table 7 shows some of its functions in different modes of uses which are as follows.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline Scheme & Plant Parts & **Mode Of Uses** & **Functions** & **Reference** \\ \hline \hline \multirow{10}{*}{1.} & \multirow{5}{*}{Leaves} & \multirow{5}{*}{Paste} & On enlarged cervical and other glands, & \multirow{5}{*}{[28; 29]} \\  & & & reduce edema and pain & \\  & & & Paste & Applied to burns and wounds & \\  & & & Used as a sunscreen & \\  & & & Treat skin diseases, carbonates, syphilicity & \\  & & & sores, tumors, ulcers, tubercul & \\  & & & inflammation, and also helps to heal ulcers & \\  & & & and bronchitis & \\  & & & As eardrops, decreases ear discharge & \\  & & Juice & & problems & \\  & & & Treating conjunctivitis and anthrax pustules & \\  & & & Fodder & Given to livestock & [5] \\  & & Powder & Applied to burns and wounds & [28] \\  & & Warm Leaves & Provides relief against eye illnesses & [29] \\  & & Infusions & Treat fevers & [5; 8; 78] \\  & & Decoctions & Treat sore eyes, boils, swellings in limbs and & [29; 118] \\  & & & piles & \\  & & & Serves as an insecticide to kill lice infesting & \\  & & & the body, and is also useful to treat bed sores, & [29; 37] \\  & & & wounds, and cuts & \\ \hline \hline \multirow{10}{*}{2.} & \multirow{5}{*}{Roots} & Milk boiled with fresh & \multirow{5}{*}{To teach out undesirable waste from the body} & [28; 37] \\  & & roots & & Treats swellings and ulcers & [28; 37] \\  & & Paste & & Treat sexual deficiency in males & [29; 37; 119] \\  & & & Powder & To slow the growth of tumors, and improve & \\  & & & male sperm count & [37] \\  & & & Decoctions & To treat sterility in females, chest complaints, & \\  & & & scrofula, and odds & \\  & & & Black ashes & To heal blisters and swellings & [5] \\  & & & & To treat rheumat, loss of appetite, cough, & \\  & & & drops, dysppemia, joint pain, leukoderma (a & \\  & & & skin disorder), inflammation, nervous & \\  & & & breakdown, senility, debility, loss of memory, & \\  & & & goiter, lower back pain, scatica, boost & \\  & & & immunity, increase white blood cells in the & \\  & & & body, treat insomnia, the regulation of blood & \\  & & & sugar, and reduction in bad cholesterol & \\ \hline \hline
3. & Seeds & N/A &
\begin{tabular}{c} To expel parasites out of the body, to treat \\ chest problems, to thicken milk \\ \end{tabular} & [29; 37; 78] \\ \hline \hline \end{tabular}
\end{table}
Table 7: Various modes of uses of different parts of plant.
## Nomenclature and Abbreviations  
\(A_{i}\)Signal amplitude  
\(B\)Length of the pipe  
\(c\)Guided wave velocity  
\(D\)Standard Euclidian distance  
\(E\)Location of the excitation nodes  
\(F\)Location of the reflector  
\(f_{c}\)Center frequency  
\(g\)The Gabor pulse  
\(H_{i\gamma}\)Data matrix of original guided wave signals  
\(\mathbf{I_{m}}\)Imaginary part of the RC  
\(f\)Oluter radius  
\(k\)Wavenumber  
\(p\)Acoustic pressure  
\(p\)Maximum acoustic pressure  
\(Q\)Radial depth  
\(r\)Inner radius  
\(\mathbf{R_{e}}\)Real part of the RC  
\(S_{i}\), \(S_{r}\)Incident signal and reflection signal  
\(\overline{S_{i}}\)The same as \(S_{i}\) except that the phase is opposite  
\(T\)Observation time  
\(t_{0}\)The time delay  
\(u\theta\)Circumferential displacement  
\(v\)particle velocity  
\(w\)Rectangular window function  
\(\hat{x}\)Numerical guided wave signal (including two Gabor pulses: \(x_{1}\), \(x_{2}\))  
\(Y\)Data matrix of guided wave signals after preprocessing  
\(Z\)Axial length  
\(\alpha\)Slope angle  
\(\beta\)Circumferential extent  
\(\gamma\)Analysis step  
\(\omega\)Angular frequency
# Virtual Reality-Based Interface for Advanced Assisted Mobile Robot Teleoperation
## 3 Results  
With respect to the remote workspace hardware, Figure 3 shows the two different platforms that were used to demonstrate the suitability and effectiveness of the proposed approach. Figure 3a shows the simulator setup using Gazebo [64,65], whilst Figure 3b shows the real platform. In both cases, the robot used was the Turtlebot3 Burger, a differential-drive mobile robot equipped with two servos Dynamixel XL430-W250-T for the wheels, an OpenCR (32-bit ARM Cortex-M7) embedded controller (Robot controller), a RaspBerry Pi-3 (High-level controller), and an LDS, see [56] for further details. Obstacles with different shapes such as cylinders, ellipsoids (rounded corners) or boxes (sharp corners) were used in both platforms. Remark that the correct measurement of the distance from the mobile robot to the obstacles in the environment directly depends on the sensors used and the typology of the obstacle to be detected. In this work, an LDS sensor is sufficient to properly detect the obstacles used in the real experimentation. However, for objects with different characteristics (e.g., reflective materials and irregular shapes) other appropriate sensors (e.g., vision system, infrared sensors and ultrasonic sensors) could be required to obtain a proper obstacle detection so that these sensors could complement or replace the one used in this work.  
With respect to the local workspace hardware, the Oculus Quest 2 VR headset [53] and the Xbox Wireless Controller (gampad) [55] were used.  
The communication protocol between the robot high-level controller and the VR headset was via Wi-Fi Ethernet TCP/UDP. The LSD data were updated at 1 Hz, and the robot pose (i.e., position and orientation) and user commands were updated at 20 Hz. The communication protocol between the VR headset and the Xbox wireless controller was via Bluetooth.  
The parameter values used for the high level controller of the robot are as follows: potential field-based method \(\{\rho_{0}=0.35,K_{att}=0.75,K_{rep}=1\}\); robot kinematics \(\{L=0.16\) m, \(M=0.052\) m, \(r=0.033\) m\(\}\); and boundary circle with radius \(R=0.18\) m and center located at the mobile robot tracking point.
## 4 NFV and SFC Frameworks Taxonomy
### Resilience and Fault Recovery Frameworks
#### 4.3.5 OpenFlow Fault Recovery  
The framework proposed by [PERSON] et al. [93] used the OpenFlow group table to provide a quick fault recovery and fast fail-over scheme. Their proposal eliminates the use of a centralised logical controller by exploiting the use of the OpenFlow group table for managing service function chains. Fault recovery and detection were implemented in local OpenFlow switches, which utilise an OF group table.  
The need to contact the controller or NFV-MANO in the event of a failure is eliminated, which saves time on fault notification and recovery. The framework was tested using OpenStack and OF, with two vFirewall functions deployed for redundancy, which showed a reduction in SFC packet loss and an improvement in link throughput, as well as quick failure recovery. We briefly explain the aspects of SFC resilience that require further attention from the research community in Section 5.4.
# Trust and Mobility-Based Protocol for Secure Routing in Internet of Things
## 5 Simulation Study
### Experimental Setup
#### 5.1.1 Mobility  
Stationary as well as mobile devices are used a great deal in IoT applications, for example, in the smart hospital context. These devices include mobile devices, wearable external devices, stationary, implantable, and supportive devices [71]. Therefore, the ratio of mobile to static nodes is kept at 1:3 (approximately) to depict the real-world scenario of a simple smart home or smart hospital application. In order to evaluate the SMTrustOF performance in a mobile IoT environment, a mobility plugin with Cooja is used. The BonnMotion-3.0.1 tool [72] was used to produce the mobility scenario for the nodes using the Random Waypoint mobility model. The output of the BonnMotion tool is converted using a built-in application WiseML to make it compatible with the Cooja supported mobility extension movement file.
## 1 Introduction
The attack is termed as a false image injection attack (FIIA), where the attacker gains access to the medical imaging repositories and injects a false image to manipulate the original image, the decision or diagnosis based on these manipulated images will put the patient in jeopardy and in the worst case, might cause death. This is highly probable as attackers have already tried to assassinate political figures by compromising implanted medical devices [9; 10]. Therefore, in this paper, a countermeasure is proposed for such attacks, _i_Chain. The proposed countermeasure framework exploits the effectiveness  
Figure 1: Conceptual view of False Data/Image Injection in the Internet of Medical Things (IoMT). of blockchain technology [11] to ensure the security and privacy of the medical images. The recent literature [12] reflects that existing image tampering detection techniques fail to provide real time results. These techniques need to be applied on the suspicious images, which results in high false positive rates and is not effective in real time diagnosis. The key contributions of this paper are listed below:  
* Introduction of false image injection attack (**FIIA**);
* Critical analysis of image tampering detection techniques; and
* Blockchain-based security framework, **tChain** to prevent **FIIA**. In summary, the key objective of this paper is to raise awareness of considering preventive measures for **FIIA** in healthcare in the hope of saving lives. The rest of the paper is organized as follows. Section 2 describes the false image injection attacks followed by critical analysis of existing security measures on image tampering in Section 3. The backbone of the proposed framework to fight false image injection attacks, blockchain is discussed in Section 4 and the proposed security framework, **iChain** is showcased in Section 5. Evaluation of the existing techniques for image tampering detection and blockchain based frameworks are presented in Section 6. The paper is concluded with future research directions in Section 7.
# Detecting Change at Archaeological Sites in North Africa Using Open-Source Satellite Imagery
## 3 Results  
### Aswan and Kom Ombo  
The algorithm highlighted 73 of 279 sites in the Aswan and Kom Ombo area as having change within the buffered area, with an overall accuracy of 85% (Figure 3). Some of the sites had already been destroyed prior to the analysis period, although remaining subsurface material cannot be ruled out. A range of modern activities was represented, especially planned urban expansion, unplanned smaller scale construction, agricultural changes, and bulldozing. Table 3 shows the results of validating the data. The graph (Figure 4) shows the distribution of the mean pre-thresholded values for each buffer. The unaffected sites tend to have low mean change values, under 0.1. Some of the true positives are also under or close to 0.1 because the 'any non zero' parameter allows even small instances of change represented by a single pixel to be picked up. The graph also shows that the false positives were incorrectly labelled as changed due to relatively high values in the original change layer, while the false negatives had low values even though the change could be identified by examining other imagery and during fieldwork.  
Figure 4: Mean change values (prior to thresholding) for each buffer for the Aswan and Kom Ombo results.  
Figure 3: Sites analysed in the Aswan and Kom Ombo area. Sentinel-2 composite 2018–2019.
## 2 Results and Discussion
### Effects of Germination on the FA Profile of IWG
Lipoxygenase was also associated with the degradation of lipids during germination. Lipoxygenase catalyzes the oxygenation of linoleic acid (C18:2n-6) and other PUFAs containing the cis,cis-1,4-pentadiene moiety, forming monohydroperoxides with conjugated double bonds as primary products. It can act on free or esterified FAs [31]. [PERSON] and co-workers [16] demonstrated that lipoxygenase activity increased after one day of germination in chickpea, lentil, and yellow peas, leading to the generation of volatile substances responsible for beauty-related odors, such as (E)-2-octen-1-ol, hexanal, and 3-octen-2-one. The formation of these compounds showed a high correlation with the concentration of lipoxygenase and PUFAs. Another factor that could be associated with the reduction in FA content is the temperature used for germination. Although temperatures of 10, 15, and 20 \({}^{\circ}\)C have not significantly impacted the concentration of FAs, the combination of enzyme activity and temperature should be considered. This combination can favor lipid oxidation and the formation of hydroperoxides [29]. Moreover, the IWG FA profile is mainly composed of linoleic acid (C18:2 n-6), which is more prone to oxidation than monounsaturated or saturated FAs. [PERSON] et al. [32] pointed out that temperature plays a more significant role in the oxidation of C18:2 n-6 and the formation of volatiles than time. Furthermore, as observed during germination, most volatiles formed at lower temperatures have shorter carbon chains. In contrast, volatiles with longer carbon chains are more likely to be generated at higher temperatures. The short-chain compounds generated are potent odorants and can be associated with green, fatty, or vegetable-like flavors. Efforts should be made to avoid these off-notes in foods, as they are considered undesirable [33].
## 7 Conclusions and Further Work  
In this paper, we detail a method for defining SACs on the globe. Further, we compare our approach with some classical DGGS methods. We also compare the performance between SAC DGGSs and three classical DGGSs. The analysis results illustrate that the DGGSs based on SACs have an average performance. This means that they have small area and shape distortions simultaneously. Another advantage is the explicit transformation equation between the Cartesian coordinates and SACs.  
We show that the SAC system is a global coordinate system and can be used to represent different kinds of spherical signals: continuous function (Figure 27) and discrete sampling data (Figure 28). On the other hand, contrary to many other approaches, such as the methods of [1,9], the transformations between Cartesian coordinates and SACs are analytical and compact. Because the global grid system constructed by our method is triangular, techniques that have been proposed for processing the triangular grid [33] can also be used to deal with our system.  
It would be interesting to establish a general theory of SACs for spherical signal processing. Could the SACs be used in spherical CAGD (Computer Aided Geometric Design) or solve partial differential equations in spherical geometry? Another future work is how to describe the surface with a single binary number. Using the binary description it would be much more computationally efficient to calculate gradients, etc. These topics need exploration in future studies.  
Figure 26: Maps of the spatial variation in the area and ZSC measurements for the Geo Bisector, Snyder, Dymaxion, and SAC methods for the icosahedron and 9-fold density ratio.  
**Author Contributions:** Conceptualization, K.L. and D.Q.; methodology, K.L. and D.Q.; software, K.L.; writing--original draft preparation, K.L.; writing--review and editing, K.L. and X.T.; visualization, K.L. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by The Science and Technology Development Fund, Macau SAR (File No. 099/2016/A3).  
**Conflicts of Interest:** The authors declare no conflicts of interest.
# Variational Mode Decomposition Based Time-Varying Force Identification of Stay Cables
## 3 Stay Cable Experiments
### Scale-Model Experiment  
To verify the feasibility of the proposed method, a scaled stay cable model was established in this paper first by using a single strand of steel wire to simulate the vibration of the cable under different tensions and obtained vibration acceleration information. The scaled model is shown in Figure 1. The distance between the anchoring ends of the steel wire was 15 m, the mass per unit length was 0.25 kg/m, and the diameter was 8 mm, the boundary condition of this experiment is that one end is fixed and the other is simply supported, the left part in this Figure is the enlarged sketch of tension sensor and anchor. Only the acceleration information is necessary in the proposed method, which can be obtained by only one acceletation sensor. However, to prevent cases in which the sensor data were abnormal, an additional sensor was added as a backup. Two acceleration sensors were fixed at 3.8 m and 4.8 m from the anchor point on the side of the tension sensor, the sampling frequency of which was 200 Hz, and the stay cable was excited by a blower with 550 kW motor power; the field layout of the entire experiment is shown in Figure 2. Considering the tensile bearing capacity of the cable, the range of the tension force in this cable was from 5 kN to 7.5 kN. In addition, to make the cable vibration more obvious, a baffle was made in front of the blower to enlarge the wind affected  
Irregular random interference signals usually occur in the collected vibration signals, which causes that the deviation of the sampling values of the signal points is too large, and the collected signals may generate a large number of \"burrs\". To reduce the influence of the interference signal on the collected signal, the original signal needs to be smoothed before the signal is analyzed according to Equation (9). A five-point and three-time smoothing method was adopted in this study, and the number of smoothing iterations was 100. In the process of data smoothing, the signal usually contained the environment vibration information. To preserve the frequency band of the cable vibration, bandpass filtering was used to filter the signal. The initial parameters of the VMD algorithm were selected as \(K=3\), \(\alpha=2000\), and stop condition \(\epsilon=1\times 10^{-6}\) The entire process was divided into the following steps. First, signal smoothing and fundamental frequency determination were conducted. Then, a bandpass filter for signal filtering was constructed based on the fundamental frequency. Then, the VMD algorithm was used to decompose the filtered signal and the Hilbert-Huang transform was applied to the 1 st component to obtain the instantaneous frequency. Finally, the time-varying cable force was calculated according to the instantaneous frequency and the cable force-frequency formula as shown in Equation (16).
## 4 Results
### Invention Classification
#### 4.2.6 Hybrid Propulsion  
Patents in this category focus on combining hydrogen fuel cells with gas turbines, batteries, or other power sources to enable flexible, efficient, and resilient propulsion across diverse flight conditions. These systems dynamically switch or blend power from fuel cells, turbines, or batteries based on operational phases (take-off, cruise, or emergency situations) to optimize energy use, thrust, and thermal integration. Innovations include integrated fuel cell-turbine configurations where fuel cell outputs enhance combustion, recover waste heat, or drive electric machines. Some designs incorporate cryogenic hydrogen storage to enable superconducting components, improve cooling, or act as a thermal sink. Others utilize exhaust-activated turbines, chemically rechargeable ultracapacitors, or real-time atmospheric adaptation to balance emissions and performance. Multiple systems claimed in this category leverage energy recovery, air compression, and onboard reforming to create closed-loop or multi-source architectures. Together, patents in this category forecast a transition toward multi-modal, hydrogen-centric propulsion strategies that maximize efficiency, reduce emissions, and support mission flexibility.  
The following are examples of how hybrid propulsion systems strive to blend the high efficiency of fuel cells with the thrust capability of gas turbines. [PERSON] and [PERSON] (2024) proposed a hybrid system where hydrogen flows in parallel to both fuel cells and a turbine ([PERSON] et al., 2024). The system includes shared heat exchangers and compressor bleeds air to optimize thermal performance and propulsion flexibility. [PERSON] et al. (2024) further enhanced this architecture by integrating an auxiliary power unit with thermal energy recovery via an expander-driven generator ([PERSON] et al., 2024). This solution supports both propulsion and auxiliary systems. These systems reflect a trend toward energy-flexible propulsion networks that dynamically balance power sources depending on flight phase and system demands.
# Several Cases for the Validation of Turbulence Models Implementation
## 5 Conclusions  
Four test cases were used to validate the implementation of the Shear Stress Transport and Spalart-Allmaras turbulence models in the UNS3D code. Two versions of the UNS3D code were considered: a sequential code, UNS3D-SEQ, and its parallel version, UNS3D-PAR. The validation of the implementation was done using experimental data and results generated by two NASA codes: FUN3D and CFL3D. The four cases considered were (i) a flat plate case, (ii) an airfoil near-wake, (iii) a backward facing step, and (iv) a turbine cascade known as the eleventh standard configuration. In all cases, the residuals of the solutions were less than \(10^{-11}\). The numerical results generated by the UNS3D codes with the two turbulence models compared well with the experimental data and the results of NASA codes FUN3D and CFL3D. The two turbulence models produced similar results. Compared to the experimental data, the Spalart-Allmaras turbulence model did not predict the turbulent fluctuations and skin friction coefficient as well as the Shear Stress Transport turbulence model. The Spalart-Allmaras model predicted the velocity profiles better than the Shear Stress transport model as the flow moved away from the backward-facing step. Overall, the results generated with the Shear Stress Transport model were closer to the experimental data, the only exception being the prediction of the reattachment point on the backward-facing step, where the Spalart-Allmaras model outperformed the Shear Stress Transport model. The computational time of the Shear Stress Transport model solution exceeded that of the Spalart-Allmaras model by 4% to 38%. In addition, the solution generated by the Shear Stress Transport model was more sensitive to the far-field boundary conditions than that of the Spalart-Allmaras model.  
Conceptualization: M.D.P. and P.G.A.C.; methodology: M.D.P. and P.G.A.C.; software: M.D.P. and P.G.A.C.; validation: M.D.P.; formal analysis: M.D.P.; investigation: M.D.P. and P.G.A.C.; resources: P.G.A.C.; data curation: M.D.P.; writing--original draft preparation: M.D.P.; writing--review and editing: M.D.P. and P.G.A.C.; visualization: M.D.P.; supervision: P.G.A.C.; project administration: P.G.A.C.; funding acquisition: P.G.A.C. All authors have read and agreed to the published version of the manuscript.  
The authors would like to thank the High-Performance Research Computing center at Texas A&M University for providing the computational resources that were required to complete the work presented in this paper.  
The authors declare no conflict of interest.