esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Results and Discussion
### Satisfaction Evaluation Results  
Table 1 shows the scores given by the participants and the average scores for each item after using the system proposed in this study. All six participants were mostly satisfied with all items, resulting in an overall average score of 5 for Q1, 4.67 (0.52) for Q2, 4.83 (0.41) for Q3, and 4.83 (0.41) for Q4. Notably, all participants scored 5 for Q1, a perfect overall  
Figure 4: Example of a screen where an object’s event occurs due to contraction (**a**) when holding an object lightly, (**b**) when holding an object strongly.  
average. This indicates that incorporating muscle activity into existing VR content allows for more sensory interaction and reflects the users' intentions directly into the VR content, thereby improving user satisfaction.  
Below are similar qualitative opinions and the percentage of participants who presented them, calculated as (number of responses/total number of participants)*100.  
33.33%: \"It was interesting to see the difference between the green (lv 1) and black (lv 4), but it was hard to feel the difference between the red (lv 2) and purple (lv 3)\".  
33.33%: \"It would be good if the object showed quantitatively how much force was applied along with the event occurrence threshold\".  
16.67%: \"I wish the hand tracking recognition was better\".  
16.67%: \"It was difficult to break the objects because my nails were long\".  
The qualitative opinion \"It was interesting to see the difference between green (lv 1) and black (lv 4), but hard to feel the difference between red (lv 2) and purple (lv 3)\" implies that users may find it difficult to closely distinguish or control each stage when threshold levels are divided into four. Reducing the number of stages or ensuring a certain difference between thresholds could enable users to sufficiently differentiate and feel satisfied with their interactions. Second, the qualitative opinion \"It would be good if the object showed quantitatively how much force was applied along with the event occurrence threshold\" indicates that users expect objective feedback when providing complex and continuous inputs like biosignals, and they want to verify their inputs with quantitative figures. Third, the opinion \"I wish the hand tracking recognition was better\" suggests the need for hand tracking technology that guarantees higher reliability software-wise, broader camera angles, different VR environments hardware-wise, or the need to eliminate elements that could be misrecognized as hands before using the system. Lastly, the opinion \"It was difficult to break the objects because my nails were long,\" suggests that when using the system barehanded, the length of the nails can impact the system's usability, particularly during the MVC measurement phase and object interaction phase when clenching a fist, as nails digging into the palm can be a problem. This could be improved by notifying participants of the potential issues caused by long nails before the experiment.
## 5 Conclusions  
A broad-beam antenna using a microstrip patch parasitic array, which is excited by the cavity-backed slot coupling, has been proposed in this paper. In order to achieve the broad-beam antenna, the square patch sizes, the slot length, the slot width, the probe length, the cavity positions, and the gaps between the parasitic patches array around the radiation patch were simulated. The key characteristics, especially the return loss and radiation patterns, were acquired with the assistance of the CST software. Measurements of the fabricated antenna have shown that the proposed antenna has a gain of 5.6 dB and the half-power beam widths of 130\({}^{\circ}\) and 80\({}^{\circ}\) in E-plane and H-plane, respectively. The return loss of the antenna at the operating frequency (at 5.0 GHz) is approximately \(-22.39\) dB. Consequently, the antenna can be promisingly applied in LEO satellite for an earth coverage beam or could be used for other applications in the wireless communications system, such as WLAN and sub-6 GHz 5G communications.  
Figure 16: Comparison between the measured and the simulated normalized radiation pattern at 5.0 GHz: (**a**) E-plane (y-z plane); (**b**) H-plane (x-z plane).  
**Author Contributions:** Conceptualization, T.P. and W.S.-N.; methodology, T.P. and W.S.-N.; software, T.P. and W.S.-N.; validation, T.P. and W.S.-N.; formal analysis, T.P. and W.S.-N.; investigation, T.P. and W.S.-N.; resources, T.P. and W.S.-N.; data curation, T.P. and W.S.-N.; writing--original draft preparation, T.P. and W.S.-N.; writing--review and editing, W.S.-N.; visualization, T.P. and W.S.-N.; supervision, W.S.-N.; project administration, W.S.-N.; funding acquisition, T.P. and W.S.-N. All authors have read and agreed to the published version of the manuscript.  
This research project was financially supported by Mahasarakham University, Kantarawichai, Maha Sarakham, Thailand. The grant number is 5801008.  
Not applicable.  
**Data Availability Statement:** The data presented in this study are available on request from the authors.  
The research project was supported by Rajamangala University of Technology Isan, Thailand.  
The authors declare no conflict of interest.
## 3 Results
### Validity: Comparison between ventilatory and Electromyography Thresholds  
Table 2 summarizes the average values of VT\({}_{1}\) and EMG\({}_{\text{T1}}\) expressed in W, VO\({}_{2}\) (ml/kg/min), and %VO2 MAX for all muscles. There were no significant differences between the means of EMG\({}_{\text{T1}}\) and VT\({}_{1}\) for the VL, VM, and BF muscles. However, for the GLM muscle, the means of EMG\({}_{\text{T1}}\) were significantly greater than those of VT\({}_{1}\) (\(p<0.05\)).  
Table 3 summarizes the average values of VT\({}_{2}\) and EMG\({}_{\text{T2}}\) expressed in W, VO2 (ml/kg/min), and %VO2 MAX for all muscles. There was no significant differences between means of EMG\({}_{\text{T2}}\) and VT\({}_{2}\) (\(p>0.05\)) for four muscles.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Variables** & **Mean (SD)** & **Range** \\ \hline VT\({}_{1}\) (L min\({}^{-1}\)) & 3.3 \(\pm\) 0.6 & 1.9–4.4 \\ VT\({}_{2}\) (L min\({}^{-1}\)) & 4.6 \(\pm\) 0.5 & 3.4–5.6 \\ VO2 MAX (ml Kg\({}^{-1}\) min\({}^{-1}\)) & 4.9 \(\pm\) 0.7 & 4.5–5.7 \\ VO2 MAX (L min\({}^{-1}\)) & 71.6 \(\pm\) 4.1 & 62.3–81.0 \\ Power at end of exercise (W) & 406 \(\pm\) 36 & 325–450 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Physiological (mean \(\pm\) SD) characteristics of the participants (N = 16) calculated from the incremental test.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & & & \multicolumn{3}{c}{**EMG\({}_{\text{T1}}\)**} \\ \hline
**Variable** & **VT\({}_{1}\)** & **Vastus Lateralis** & **Vastus Medialis** & **Biceps Femoris** & **Gluteus Maximus** \\ \hline W & 278.2 \(\pm\) 34.5 & 291.1 \(\pm\) 44.3 & 294.0 \(\pm\) 46.9 & 295.6 \(\pm\) 47.3 & 300.8 \(\pm\) 37.9 * \\ VO2 (ml/kg/min) & 51.5 \(\pm\) 6.8 & 54.5 \(\pm\) 6.9 & 55.7 \(\pm\) 5.9 & 56.5 \(\pm\) 8.0 & 57.8 \(\pm\) 5.7 * \\ \%VO2 MAX & 71.9 \(\pm\) 9.4 & 76.1 \(\pm\) 8.9 & 77.8 \(\pm\) 9.5 & 78.9 \(\pm\) 11.5 & 80.7 \(\pm\) 6.1 * \\ \hline \hline \end{tabular}  
* Significant difference between the mean values at EMG\({}_{\text{T1}}\) and at VT\({}_{1}\) (\(p<0.05\)).  
\end{table}
Table 2: Mean values of the power output (W), VO\({}_{2}\), and %VO2 MAX obtained at the first electromyographic threshold (EMG\({}_{\text{T1}}\)) and at the first ventilatory threshold (VT\({}_{1}\)). All values are expressed as mean \(\pm\) SD.  
To further examine the validity of the EMG method, the Bland-Altman method was applied to assess the degree of agreement between the EMG thresholds and ventilatory thresholds (see Figure 3). This figure shows that, for all muscles, the bias and error of the multi-segment regression method was relatively low. Note that the levels of agreement were especially low for the comparison between VT2 and EMGT2 (Figure 3b). Moreover, for all comparisons, at least 90% of the individual values were within the limits of agreement.
# Nighttime Image Dehazing Based on Point Light Sources
## 3 Proposed Method
### Light Source Influence Matrix
#### 3.3.1 Judging the Near and Far Light Source Area  
Convert the image to HSI space, and extract the photometric map of the image. Fully considering nighttime conditions, we default the brightness of artificial light sources to a great extent. The average value of the pixels in the top 0.5% of the photometric value is selected as the light source candidate threshold \(C_{max}\). In the photometric map, filter out the light source pixel points whose photometric values are greater than or equal to the threshold value. Keep the light source pixel points in the photometric map to obtain the light source map, and define the pixel blocks in the top 2% of the photometric value as the near light source region \(\Omega\).
## 5 Conclusions  
R600a has been selected as the most efficient working fluid among the proposed four working fluids according to results of the study. Besides its performance, it is important to take into consideration global warming potential and ozone depletion potential of the fluid while selecting the most efficient working fluid. At this point, R600a has zero ODP and less GWP when compared most of used working fluids.  
High evaporator and boiler temperatures as well as high turbine and compressor isentropic efficiencies have great effect to achieve best \(\mathrm{COP_{sys}}\). In addition, low condenser temperature causes rise in \(\mathrm{COP_{sys}}\). To get better \(\mathrm{n_{lex,sys}}\), evaporator and condenser temperatures should be decreased. Also, high boiler temperature, high turbine and compressor isentropic efficiencies enhance \(\mathrm{\eta_{lex,sys}}\).  
The highest exergy destruction occurs in the boiler in both of the combined systems no matter whether its with the single evaporator or dual evaporator. The highest exergy destruction happens in the compressor in the refrigeration cycle of both of combined systems.  
The pump has the biggest second law efficiency in combined system with single evaporator. For combined system with dual evaporator, mixing chamber takes the lead in terms of second law efficiency. The component that shows the highest degree of thermodynamic perfection is pump in both of combined systems.  
Component size that is one of design parameters has not been included in this study. We suggest researchers to consider component size in their further studies.  
As a result, addition of an extra evaporator in combined system causes a significant decrease in \(\mathrm{COP_{sys}}\) and reduces \(\mathrm{\eta_{lex,sys}}\). Total exergy destruction also increases with an additional evaporator.  
O.P. and H.I.A. designed and analyzed proposed systems. O.P. wrote the paper.  
This research received no external funding.  
The authors declare no conflict of interest.
# Reconditioning of Diamond Coated Tools and Its Impact on Cutting Performance for CFRP Laminates
## 3 Results and Discussion
### Cutting Edge Rounding Evaluation  
In this study, the cutting edge rounding (CER) value was employed for the evaluation changing of the geometric shapes of drill cutting edges through the initial and reconditioning cycles of the experiments. A number of references reported the correlation between CER values and cutting forces, machined material delamination, etc. [26; 27; 28]. In addition, the CER parameter is frequently used as a criterion of tool wear, especially for non-coated WC-Co-based tools [29].  
The CER values were measured on the tool substrates in two cutting edge places based on the applied one-shot drill shape.  
The first measurement position was determinate on the secondary cutting edge at 6 mm from the drill tip, and the drill cutting edge profile was characterized. It should be noted that the same position was used for the flank wear evaluation, described in the following section. The second measurement position, associated with the reamer geometry, was on the tertiary cutting edge at 11 mm from the tip. Figure 9 shows the cutting edge profiles for both measurement positions described above carried out by a laser microscope (OLS4100, Olympus, Tokyo, Japan). First, the three-dimensional (3D) images of the cutting edge in the measurement positions were obtained from a surface area of 129 \(\upmu\)m \(\times\) 129 \(\upmu\)  
Figure 8: Scanning electron microscopy (SEM) images of indentation morphologies, obtained by a Rockwell testing machine with a load of 980.7 N on the TLC0 (**a**), the TLC1 (**b**), and the TLC2 (**c**,**d**).  
by an optical magnification of the system (\(100\times\)). Then average values in this area for the edge radius were determined.  
Figures 10 and 11 reveal the evolution of the CER values measured after the substrate treatment procedures. As shown in Figure 10, each pretreatment before diamond deposition led to increasing CER values. Because the chemical etching process accompanied the Co binder's removal and loss of tungsten carbide grains, influencing the tool size and shape. On the contrary, the cutting edge sharpening effect was observed after the decoating stages. Although the film removal was not released uniformly for a complicated shape of the drill and the sputtering of the substrate occurred as well, the CER values decreased by approximately 0.5 \(\upmu\)m every time for both the cutting edge geometries. The observed effect of micro-sharpening has been previously reported for medical needles exposed to ion beam irradiation with similar process parameters in the present study [30]. The mechanism consists in the incident angle-dependent sputtering yield, which drives the shape modification towards sharper edges in certain angle ranges and ion energies. For the cutting tools, the ion-induced sharpening of the edges may be beneficial from the standpoint of the cutting force reduction.  
Figure 10: Change of the CER (6 mm measured point).  
Figure 9: Measurement results of the cutting edge rounding (CER).
## 3 Results
### PRO Score Histological Correlation  
The comparison of EVCM PRO score assessment with gold-standard histology demonstrated a strong concordance for both assessment methods, with an overall diagnostic agreement of 46/48 lesions (95.8%). Divided into both cohorts using FCF Fast Green staining, 24/25 lesions (96%) were correctly graded (6/6 of PRO I, 11/12 of PRO II, and 7/7 of PRO III). For classical acridine orange staining, 22/23 lesions (95.6%) were classified correctly (6/6 of PRO I, 8/9 of PRO II, and 8/8 of PRO III). The two EVCM cases that did not agree with histology were both overclassified as PRO III in EVCM, while histological assessment reported PRO II (see Table 1).  
Figure 2: Calculation of the fiber brightness index (=FBI). FCF fluorescence image showing exemplarily the selection of representative collagen fibers (blue squares) and three basal keratinocytes as reference (red squares).  
Importantly, FCF staining had no discernible impact on PRO score assessment compared to the standard AO staining, as evidenced by nearly similar agreement rates with histology.
# DEM Simulation of the Load Transfer Mechanism of a GRPS Embankment with a Fixed Geogrid Technique
## 2 Establishment and Calibration of DEM Model
### Geogrid Modeling  
Reinforcement was not considered in the laboratory pile-supported embankments model by [PERSON] et al. (2019). To study the fixed geogrid technique, a numerical geogrid tensile test was carried out for calibration. The reinforcement was produced using the regular arrangement of particles with a diameter of 2 mm. For the contact between the particles, parallel bonding that could bear the tensile stress and the bending moment was selected to reproduce the tensile mechanical response of the geogrid. A numerical tensile specimen with a length of 100 mm was established. The particle at one end of the specimen was fixed, while a tensile rate (\(v_{\mathrm{t}}\)) of 20 mm/min was applied to the particle at the other end. As shown in Figure 4, the DEM tensile results were in reasonable agreement with the laboratory tensile test.
## 4 Experimental Results for 3 kW Six-Phase PMa-SynRM  
The motor manufactured based on the optimal LPM design result is shown in Figure 10. For the motor-performance test, a 7.5 kW servo motor, three-phase inverter, DC input power supply, torque sensor, and DSP were used in the experimental system. Figure 11 shows the assembly of the experimental instrument. The torque sensor used in this study was of a type that could only measure the average torque 30 times per rotation of the rotor shaft. Therefore, information on torque ripple could not be provided through experimental results.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Parameters** & **6 PH\_5A** & **3 PH\_5A** & **3 PH\_10A** & **6 PH\_4A** & **3 PH\_4A** & **3 PH\_8A** \\ \hline Operation mode & Initial & CC & CT & Initial & CC & CT \\ Max. torque [Nm] & 8.5 & 4.3 & 8.7 & 6.8 & 3.5 & 6.9 \\ Min. torque [Nm] & 7.7 & 3.6 & 7.8 & 6.1 & 2.8 & 6.1 \\ Mean torque [Nm] & 8.1 & 4.0 & 8.2 & 6.4 & 3.2 & 6.5 \\ Difference of min/max [Nm] & 0.8 & 0.7 & 0.9 & 0.7 & 0.7 & 0.8 \\ Ripple factor [\%] & 9.9 & 17.5 & 11.0 & 10.9 & 21.9 & 12.3 \\ Power factor & 0.951 & 0.974 & 0.924 & 0.965 & 0.983 & 0.969 \\ Efficiency [\%] & 92.0 & 84.9 & 75.9 & 95.9 & 87.0 & 79.2 \\ \hline \hline \end{tabular}
\end{table}
Table 7: Performance of each case of operation modes for six- and three-phase.  
Figure 10: Manufactured motor; (**a**) Stator, (**b**) rotor.  
The specifications of each instrument are presented in Table 8. Six- and three-phase BEMF and load tests in a steady state condition were conducted under the conditions of 480 r/min and 2-10 A, as shown in Table 6. Table 3 shows that low efficiency at the test point was meaningless, so it was excluded from analysis of the experimental results.  
The experiment proceeded as follows. First, the test speed was attained through speed control in the servo motor. At this time, the six-phase motor operated in generating mode, and when the load current was not applied, the back electromotive force could be measured. Here, when a load current was applied to the motor, it became a motoring mode, and torque was generated by a rotating force in the opposite direction.
# A Framework for Assessing the Interference from NGSO Satellite Systems to a Radio Astronomy System
## 2 Model Description
### NGSO Satellite System Model
#### 2.3.4 Out-of-Band Emission  
For the NGSO satellite frequency bands adjacent to RAS bands, the out-of-band interference from satellite downlink beams needs to be evaluated. For example, 10.6\(\sim\)10.7 GHz of the Ku band is assigned to the RAS as the primary service, and 10.7\(\sim\)12.75 GHz of the Ku band includes the downlink of the NGSO satellite fixed service. The out-of-band interference from the NGSO satellite can affect the reception of the RAS telescope, and the out-of-band interference is mainly affected by the characteristics of filters and amplifiers.  
According to NTIA requirements, the out-of-band radiated power spectrum density (psd) needs to meet the following conditions:  
\[psd(f)=psd_{max}10^{\frac{s_{EM}(f_{off})}{10}} \tag{14}\]  
\[S_{EM}(f_{off})=max\{-40\log_{10}(\frac{2f_{off}}{B_{A}})-8,-60\} \tag{15}\]  
where \(pfd_{max}\) is the power spectral density in the in-band of the NGSO satellite, \(f_{off}\) is spectrum offset from the central frequency of the in-band, and \(B_{A}\) is the bandwidth of NGSO satellite beam. According to the transmitting power of the NGSO satellite beam, the \(pfd_{max}\) could be written as \(\frac{P_{l}}{B_{A}}\). Therefore, the maximum emission power in the RAS band, such as 10.6\(\sim\)10.7 GHz, is formulated below.  
\[P_{RAS}=\int_{f_{l}}^{f_{u}}\frac{P_{l}}{B_{A}}10^{\frac{s_{EM}(f-f_{c})}{10}}df \tag{16}\]  
where \(f_{l}\) and \(f_{u}\) are the upper and lower boundaries of the in-band of the NGSO satellite beam, and \(f_{c}\) is its central frequency.
# Laser Vision Correction for Regular Myopia and Supracor Presbyopia: A Comparison Study
## 3 Results
### Astgmatism Change  
Corneal astigmatism, assessed with the Galilei G4, showed very little difference (\(p>0.6\)), between preoperative (\(0.98\)D \(\pm\) 0.53 SD) and postoperative measurements (\(1.01\)D \(\pm\) 0.50 SD) over the whole study population. Likewise, the myopia group had preoperative astigmatism of \(1.17\)D \(\pm\) 0.63 (SD), which changed to postoperative astigmatism of \(0.78\)D \(\pm\) 0.74 (SD) \(p>0.02\). The presbyopia group had preoperative astigmatism of \(1.02\)D \(\pm\) 0.42 (SD), which changed to postoperative astigmatism of \(0.96\)D \(\pm\) 0.58 (SD) \(p>0.02\). Also, Figure 2 shows double-angle polar plots of pre-, and post-operative astigmatism measurements for both groups, myopia and presbyopia, and suggests only small changes in astigmatism from pre--to postoperative measurements. However, the Alpins method [14] vector analysis (including the astigmatism orientation) showed that astigmatism changed significantly, by \(0.78\)D \(\pm\) 0.74 (SD) for myopia and by \(0.96\)D \(\pm\) 0.58 (SD) for presbyopia, respectively. The intended astigmatic change (planned astigmatic LASIK ablations) was \(0.94\)D \(\pm\) 0.84 (SD) for myopia group and \(0.65\)D \(\pm\) 0.41 (SD) for presbyopia group.  
Figure 1: Trend analysis for presbyopia treatments (**b**) showed a mild correlation (R\({}^{2}\) = 0.01 with slope 0.005) that greater dioptric corrections resulted in lower uncorrected visual acuity (UCVA). No such correlation (R\({}^{2}\) = 1E-05 with slope \(<\) 0.001) between dioptric correction and resulting UCVA could be observed in the myopia (**a**) results, though.  
Figure 2: Double-angle polar plots comparing (**a**) pre- to (**b**) postoperative astigmatism. Myopia results are shown as circles and presbyopia results are shown as solid squares. No obvious differences between myopia and presbyopia correction were visible.
## 2 Terminologies in EMI Shielding
### Shielding Due to Multiple Internal Reflections (\(\mathrm{SE_{M}}\))  
When the thickness of the shield is low, the incident EM waves are reflected between the first and second boundaries. The shielding effectiveness due to multiple internal reflections, \(\mathrm{SE_{M}}\), is expressed as the following equation [89]:  
\[\mathrm{SE_{M}}=20\ \log_{10}\left(1-\mathrm{e}^{-2\mathrm{t}/\delta}\right)=20 \ \log_{10}\left[1-10^{-\frac{\mathrm{SE_{A}}}{10}}\right] \tag{6}\]  
From the above equation, it is clear that \(\mathrm{SE_{M}}\) is directly related to absorption losses (\(\mathrm{SE_{A}}\)). This loss is of more importance in foamed polymer nanocomposite materials, where air is present in the pores and hence reduces the dielectric constant of the material (dielectric constant of air = 1). As the dielectric constant decreases, the reflection losses will be minimal, and hence the shielding mechanism will be mostly governed by the absorption mechanism.  
\(\mathrm{SE_{M}}\) can be neglected when the thickness of the shield is high, then the \(\mathrm{SE_{A}}\) value will be high, and by the time the EM waves reach the second boundary, its amplitude becomes negligible. In addition, if \(\mathrm{SE_{A}}\geq 10\) dB, \(\mathrm{SE_{M}}\) can be neglected [89]. \(\mathrm{SE_{M}}\) is usually important in cases of thin conductors when used at lower frequencies (in the \(\mathrm{KHz}\) region). However, for absorbing shields in the high-frequency region (\(\mathrm{GHz}\) region), if \(\mathrm{SE_{A}}\geq 10\) dB, \(\mathrm{SE_{MR}}\) can be considered negligible.  
The ability of any shield material to attenuate EM waves is termed as EMI shielding effectiveness (EMI SE), and is usually expressed in terms of decibels (dB). It can also be expressed in terms of percentage (%), which can be calculated with the following equation [90]:  
\[\mathrm{Shielding~{}efficiency~{}(\%)}=\left(\frac{1}{10^{\frac{\mathrm{SE}}{10} }}\right)\times 100 \tag{7}\]