esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Detection and Analysis of Non-Volatile Compounds by UPLC-MS  
#### 2.5.1 Catechin and Caffeine Analysis  
Pre-treatment: The dried tea sample was thoroughly ground into a powder and sifted through a 0.4 mm sieve. The tea powder (200 mg) was put in a 100 mL centrifuge tube, and vortexed and mixed fully with preheated aqueous methanol (5 mL, 70% \(v/v\)), and then the sample was sustained at 70 \({}^{\circ}\)C for 10 min via a water bath, which was shaken well every 5 min. The sample was centrifuged at a speed of 3500 rpm for 10 min, and the supernatant was transferred to a 10 mL volumetric flask. Methanol was used for the re-extraction of residue. The above operation was repeated several times, and the extraction solution and the volume were brought up to 10 mL in a volumetric flask. After that, a 1 mL aliquot was transferred to a 2 mL centrifuge tube at 3500 rpm for 5 min with PSA (5 mg) and C18 (40 mg). The supernate was filtered through a 0.22 \(\upmu\)m organic filter membrane and was subjected to UPLC-MS analysis.  
UPLC-MS was utilized for catechin and caffeine analysis. A Q Exactive UPLC-MS system (Thermo Fisher Scientific, Rockford, IL, USA) was carried out on a Hypersil GOLD column (100 \(\times\) 2.1 mm 1.9 \(\upmu\)m, Thermo Fisher Scientific). The column temperature was 30 \({}^{\circ}\)C. The mobile phases were 0.1% formic acid (A) and acetonitrile with 0.1% formic acid (B), and the linear elution gradient program was 0-12 min, 5-17% B; 12-13 min, 17-100% B; 13-16.5 min, 100-5% B; and 16.6-20 min, 5% B. The total analysis time was 20 min, the flow rate was 0.3 mL/min, and the injection volume was 1 \(\upmu\)L.  
Mass spectrometry was performed in the ESI (Electron Spray Ionization) mode for catechins and the ESI+ mode for caffeine with the following settings: the capillary voltage was 3.5 kV (ESI+) and 3.8 kV (ESI-); the flow rates of the sheath and auxiliary gas were 20 arb and 8 arb, respectively; the source temperature and desolvation temperature were 350 \({}^{\circ}\)C and 400 \({}^{\circ}\)C; the pore gas and desolvent gas was nitrogen, and the collision gas was argon gas; the cone gas flow was 150 L/h; and the desolvation gas flow was 800 L/h. Collision energy and cone voltage were optimized for the above compounds with multiple reaction monitoring (MRM) for quantification. The optimization of MS parameters used a single standard of catechins (10 ng/mL) and caffeine (10 ng/mL) to determine characteristic parent and daughter ions [31].
# Pilot-Based Adaptive Channel Estimation for Underwater Spatial Modulation Technologies
## 6 Simulation Results and Discussion
### Fully Generalized Spatial Modulation  
The BER performance of the RLS channel estimator using a different number of pilots is compared with P-CSI for FGSM without Doppler-scaling factor over the time-varying MIMO channel provided in Figure 7. When the RLS channel estimator performance uses 2% of pilots as transmitted bits, the SNR gain difference is 9 dB between P-CSI and channel estimator at the target BER \(10^{-2}\), and this performance difference is nearly the same for SM and GSM system, as seen in Figures 3 and 5. In comparison to P-CSI, the SNR gain difference is 1.85 dB using 5% of pilots used to estimate the time-varying channel at BER \(10^{-2}\); this is far different than between P-CSI and the estimated results. Meanwhile using pilots = numbers 10% and 15%, the SNR gain difference at BER \(10^{-2}\) is 0.32 dB and 0.21 dB in comparison of P-CSI. The RLS channel estimator BER performance using 10% and 15% pilots is greater than 2% and 5% number of pilots.  
The BER performance of the RLS channel estimation method using pilots compared with a P-CSI for FGSM over time-varying MIMO channel in the presence of normalized Doppler-scaling factor is shown in Figure 8. As compared to a high number of pilots, the BER performance of 2% is not reasonable for SM, GSM, and FGSM with and without Doppler-scaling factor, as seen in Figures 3-8, respectively. At BER \(10^{-2}\), the SNR difference gain as compared with P-CSI is 1.93 dB, 0.34 dB, and 0.25 dB while using 5%, 10%, and 15% of pilots for estimating the channel. RLS channel estimator with and without Doppler-scaling factor in SM provides a better performance gain than GSM and FGSM, as depicted in Figures 3-8, respectively. This is because only one antenna is active in SM to transmit the data, and it helps the system to avoid inter-antenna interference as well as ICI. Additionally, the BER performance curve using with Doppler-scaling factor is shifted up approximately \(10^{1}\) times than without Doppler-scaling factor. SM, GSM, and FGSM exhibit the same performance loss by adding and ignoring the Doppler-scaling factor. Moreover, the BER performance using the RLS channel estimator for 2% pilots is extremely low as compared to a high number of pilots in all SM, GSM, and FGSM. All the simulation results and analysis explicitly indicate that the RLS estimator is an appropriate channel estimation technique for the UWA-SMTs communication system.  
Figure 6: BER performance of the 4 \(\times\) 4 underwater GSM-MIMO with Doppler-scaling factor.
## 1 Introduction
Since the gap caused by these cracks causes corrosion by creating a contact between the atmosphere and base materials/fasteners [30; 31], applying this method to CFRP is difficult. While CFRP and metal are still mainly bonded using traditional mechanical fastening, a chemical bonding method has been developed to minimize the hole generation and initial cracks in CFRP [32; 33; 34]. For the connection of CFRP and steel plate, [PERSON] et al. studied the surface treatments to improve the bonding force of chemical bonding with adhesive [33]. [PERSON] et al. investigated the environmental durability of CFRP/steel joints with chemical bonding using epoxy adhesive through a mode 1 fracture test [34]. In chemical bonding, structural adhesives are mainly composed of epoxy and are being researched to enhance the adhesive properties by adding reinforcing materials. However, the fundamental problem of chemical bonding is that it has a low bonding strength compared to mechanical bonding [35; 36; 37]. Chemical bonding, which is used for bonding CFRP and metals, exhibits a lap shear strength (LSS) of 20 MPa or more [38; 39]. Thus, further research on hybrids that use both mechanical and chemical bonding is needed. In this study, hybrid bonding that combines mechanical and chemical bonding is used to achieve a better method for improving the adhesion and stability of CFRP/steel bonding. Unlike general application on the adhesive surfaces to increase adhesive strength, chemical bonding is performed by filling the clearance between the material and fasteners, which inevitably occurs during mechanical bonding with a structural adhesive. This work aims to examine the effect of preventing the inclination of fasteners as well as the effect of improving the bonding strength. Experimental cases are set considering the fracture mechanism according to the fastening method. Finally, based on numerical analysis, a better method that uses hybrid bonding is suggested, which significantly improves bonding strength compared to mechanical bonding alone.
## 4 Simulation Results
### Two-Way Relaying PNC System Performance with Estimated Channel Coefficients  
So far, we have reported the results achieved for ideal knowledge of channel coefficients for each applied subcarrier. However, in reality, they must be estimated and the resulting estimates have to be used in the detection process in both the reference and proposed PNC algorithms in the relay. As WiFi transmission, which we had taken as the object of our simulation experiments, is not fitted to two-way relaying in the PNC scheme, we adopted the strategy previously presented by us in [17]. Namely, we used a simple method of channel estimation for both channels in the form of a short packet exchange at the start of the two-way relaying PNC operation. Such a procedure can be repeated after appropriate time intervals, if necessary, to follow the changes in channel characteristics. For convenience, we shortly summarize this strategy below. It is shown in graphical form in Figure 9 of [17].  
First, terminal A transmits a short packet consisting of a preamble only. If necessary, it can contain some additional OFDM symbols consisting of known data (pilots). As we have noticed in our simulation experiments reported below, and in [17], where it was reported for another application, the additional pilot symbols have a significant influence on the system performance. Then, terminal B, after a passive reception (detection without making valuable decisions) of the preamble from terminal A, transmits its own preamble as well. After that, the relay transmits the START signal and regular PNC operation begins when both terminals transmit their packets concurrently in the multiple access phase of two-way relaying. Let us recall that a standard preamble of an IEEE 802.11a data packet contains, among others, two long training OFDM symbols mostly aimed at channel estimation. Recall that such a preamble is a legacy part of the preambles of newer IEEE 802.11 standards, including IEEE 802.11 ax. As the samples of both long training symbols are known, the received FFT outputs, being the response of the channel to both training symbols, are averaged and subsequently divided by the ideal tones of both training symbols [35].  
It turns out that direct use only of the preamble symbols causes serious deterioration in the performance, as compared with the case when the channel characteristics are perfectly known. Thus, the improvement in channel estimates can be achieved if we perform averaging over a larger number of OFDM pilot symbols.  
Figure 8 shows the BER performance for both proposed and reference PNC algorithms applied in the relay of the two-way relaying system when \(g_{2}=0.5\), when the channel estimation is based on selected numbers \(N_{p}\) of pilot symbols.  
Figure 7: BER on the output of the receiver of terminal A (RxA) and terminal B (RxB) for several values of the weighting coefficient \(g_{2}\) after two-way data relaying.
# Open Loop Position Control of Soft Hydraulic Actuators for Minimally Invasive Surgery
## 3 Materials and Methods
### Positioning Test Setup
#### 3.3.3 Planar Parallel Mechanism  
The entry points of the cables to the parallel mechanism's workspace were arranged in an equilateral triangle as shown in Figure 4D,E. The cables are attached to a shaft intersecting the entry point plane, which is defined as the Y-Z plane. The cable entry points are at the end of capstans depicted in Figure 4 as point 8. Assuming that the connection to the shaft assembly stays in the plane of the entry points, the contact angle is equal to \(\pi/2\). The friction from these capstans is assumed to be zero, as PTFE tubes were inserted for their entire length. Given this structure, the planar parallel mechanism is an RPR type [28], where the prismatic joints are actuated. The two passive rotary joints are found at the cable entry points to the structure and at the coupling to the shaft because in both places the cables were free to rotate.  
The shaft coupling was designed such that the cables could rotate radially around the shaft while remaining perpendicular to it, depicted in Figure 4 as point 11. Each cable is attached to one of three nested pairs of rings that rotates independent of the others. This design meant that the point of intersection of the direction vectors of the cables was assumed to be in the centre of the shaft. Therefore, the cables were thought of as intersecting at a single point in the centre of the shaft, or, alternatively, the shaft could be thought of as having zero radius. In reality, each ring-pair of the cable coupling extends radially from the shaft and restricts the range of the actuators to a small degree. The coupling is also free to move axially along the shaft, meaning that the point of intersection of the direction vectors of the cables was assumed to exist in the entry point plane. The planar position of the point of intersection of the entry point plane, the shaft, and the three cables is controlled by the control system.  
Retro-reflective markers were placed at both ends of the short shaft to which the cables were attached. As the position of both ends of the shaft could be tracked, the direction vector of the axis of the shaft could be determined. The point of intersection of the direction vector of the shaft with the entry point plane was recorded as the measured position.  
A second support structure was constructed with an entry point equilateral triangle whose side length was double that of the first support structure. This was done because pulleys were again used to double the stroke of the actuators. The only difference between the two support structures other than the increased side length was the accommodation of a cable anchor point to create the block and tackle pulley.
## 9 Future Directions
### Consequences of Choosing the Best Model and Further Work  
The choice of the best model, particularly LAR and Elastic Net, carries significant implications for real-world applications. These models offer a balance of predictive performance and simplicity, handling key predictors like temperature (X2) and Relative Humidity (X5) effectively. However, the application of these models in diverse operational environments necessitates further work. Future efforts will focus on validating the models with real-time, site-specific data to ensure their robustness and accuracy in varying conditions. Moreover, incorporating more complex environmental factors and interactions could further refine model performance and ensure they meet the demands of large-scale SPVS optimization and monitoring.
## 4 Discussion
### Factors Influencing Quantitative Inversion Using UAV Visible Imagery  
Quantitative UAV remote sensing has become increasingly prevalent in ecology and environmental studies. While hyperspectral and multispectral sensors are commonly employed, visible-light cameras, though limited in spectral range, offer unique advantages, particularly for identifying red _Suueda salsa_. Given their widespread availability as standard components of UAVs, visible-light cameras represent a promising tool for quantitative inversion studies.  
To ensure standardized spectral results, exposure parameters (aperture, shutter speed, and ISO) were fixed during data acquisition. Additionally, DRSPs were used to convert raw pixel values into reflectance values. However, variations in camera sensitivity among different UAVs can lead to discrepancies in reflectance and hue angle measurements. Furthermore, weak light conditions can significantly reduce the signal-to-noise ratio of visible-light imagery, increasing the error in reflectance and chromaticity angle calculations.  
To mitigate these issues, it is recommended to use the same UAV and camera model for consistent data acquisition within a specific monitoring area. Optimal imaging conditions should be selected to ensure sufficient light. When monitoring areas or periods change, adjustments may be necessary to the hue angle cutoff thresholds for _Suueda salsa_ identification or biomass inversion models to maintain accurate results.
## 5 Discussion
### Accuracy of DEM based on Pleiades Tri-Stereo Data With and Without the Use of GCPs  
The DEM for the study area in the Alps, which were calculated using GCPs, show horizontal offsets of similar magnitude to the ones for the Khumbu Himal, which were calculated without GCP (see Tables 2 and 3), suggesting that horizontal accuracy for DEMs calculated from Pleiades tri-stereo images does not improve significantly if GCPs are included in the DEM generation. However, using GCPs appears to substantially improve the vertical accuracies. This agrees with the findings of [PERSON] et al. [PERSON] et al. (2018), who reported that GCPs mainly improved the vertical accuracy.  
As another measure of the accuracy of the calculated results, and correspondingly the applicability of the methods, the different periods of available surface difference data for the Khumbu Himal study area are compared. That the combined surface elevation changes of the winter and summer seasons compare well to the annual surface elevation changes between spring 2015 and spring 2016 provide evidence that the dDEM data is of sufficient quality to resolve sub-annual processes on Himalayan glaciers (see Figure 19).  
This comparison shows that the results are similar for the three rather similar glaciers in the Khumbu Himal (Lhotesup, Nuptse, and Lhotes glaciers, see Figure 19). Only in the lower parts of Nuptse glacier are some rather small differences are visible in several elevation bands. The larger and more complex Nogzumpa and Khumbu are behaving differently with slightly higher differences between the two curves.  
The distribution over the elevation bands as well as the magnitude of the surface elevation change is nearly identical in most cases. We therefore conclude that differential DEMs from Pleiades tri-stereo data provide meaningful results, which can be seen as a proof of concept for the applicability of Pleiades data for surface elevation change calculations in areas without field data to constrain the DEM accuracy. The relative accuracy of the DEM is higher than expected, even though the vertical actual accuracy, e.g., in comparison to GCP measured in the area, is lower than reported by previous studies. If this, and that problems which can arise in very steep and snow-covered terrain are kept in mind, Pleiades DEM are well-suited for a variety of applications, even in areas where no GCPs in sufficient number, accuracy, or spatial distribution are available.
###### Abstract  
Foliage profile is a key biophysical parameter for forests. Airborne Light Detection and Ranging is an effective tool for vegetation parameter retrieval. Data acquisition conditions influence the estimation of biophysical parameters. To acquire accurate foliage profiles at the lowest cost, we used simulations to explore the effects of data acquisition conditions on forest foliage profile retrieval. First, a 3-D forest scene and the airborne small-footprint full-waveform LiDAR data were simulated by the DART model. Second, the foliage profile was estimated from LiDAR data based on a Geometric Optical and Radiative Transfer model. Lastly, the effects of the airborne LiDAR scanning angle, flying altitude, and pulse density on foliage profile retrieval were explored. The results indicated that the scanning angle was an important factor in the foliage profile retrieval, and the optimal scanning angle was 20\({}^{\circ}\). The optimal scanning angle was independent of flying altitude and pulse density, and combinations of multiple scanning angles could improve the accuracy of the foliage profile estimation. The flying altitude and pulse density had little influence on foliage profile retrieval at plot level and could be ignored. In general, our study provides reliable information for selecting the optimal instrument operational parameters to acquire more accurate foliage profiles and minimize data acquisition costs.  
airborne full-waveform LiDAR; forest foliage profile; scanning angle; flying altitude; pulse density +
Footnote †: journal: Applied Sciences
# Investigating the Secondary Thermal Neutron Intensity of Neutron Capture-Enhanced Proton Therapy
## 2 Materials and Methods  
### Monte Carlo Simulation  
The nozzle of a HITACHI PROBEAT M1 at our facility was modeled to generate the proton beam (Figure 1). This PBT device enables irradiation with 71 proton-beam energies ranging from 70.2 MeV to 228.7 MeV. Previous studies have reported MCSs using the proton-beam model of our PBT system [13].  
Our MCS was conducted using the Particle and Heavy Ion Treatment Code System (PHITS) version 3.31 [14]. We used the Japanese Evaluated Nuclear Data Library 4.0 (JENDL 4.0) developed by the Japan Atomic Energy Agency [15]. The PHITS intranuclear cascade physics model uses the Liege Intranuclear Cascade Model version 4.6, and the Generalized Evaporation Model version 1 is used for de-excitation (Set _nevap_ to 3 and _ngem_ to 1). The \(\gamma\) decay of residual nuclei was calculated using the Evaluated NuclearStructure Data File-Based Isomeric Transition and Isomer Production Model (set _igamma_ to 2), and parameters were selected to account for energy straggling (set _nelisp_ to 1) in the deceleration process of charged particles other than electrons and positrons. Additionally, the Coulomb scattering of charged particles other than electrons and positrons was adjusted using [PERSON]'s equation based on the Moliere theory [16] (set _nspred_ to 2), and the settings were configured to ensure proper tabulation of high-energy neutron doses (set _e-mode_ to 2). In the MCS used in this study, the number of histories was determined to keep the statistical error in the simulation <0.1%.  
Secondary neutrons used in particle therapy can be classified into internal and external neutrons. External neutrons are generated by the interactions between the proton beam and beamline equipment outside the patient's body. However, internal neutrons are generated inside the patient's body. The number of external neutrons varies with the irradiation technique and is lower for the scanning-beam method than for the passive-beam method. However, a study reported no significant difference between the scanning-beam and the passive-beam methods regarding internal neutrons [17]. In this study, the absorbed dose distribution of the proton beam and the internal thermal neutron fluence generated within the phantom by the proton beam were analyzed. The thermal neutrons were defined as those with an energy of \(\leq\)0.5 eV [13; 15; 18].