esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Discussion  
Based on the calculations of the standard deviation and the average, it can be predicted that the radius value will be, in the vast majority of cases, in the range from 0.18 to 0.34 mm (range +/ -3\(\sigma\)). From the point of view of design requirements, these values are considered satisfactory. Based on experience related to the results of the manual process and histogram analysis, results from the automated stand are centered more correctly--the average value for the automated process is 0.26 mm, while for the manual process it is 0.16 mm.  
We carried out a feasibility study of robotizing the process; the possibility of human error during the evaluation of the process results was eliminated, and the entire brushing process was carried out with minimal use of human force.  
Based on the tests carried out and the results obtained, it can be stated:  
* The deburring operation performed on built test stand was performed correctly--based on the observed work-piece condition, burrs were removed successfully-- additionally, we created a histogram for the edge radius that confirms that the process is well centered;
* The preparation of an automated stand eliminates a lot of challenges related to human factor, process stability and repeatability, and allows us to eliminate the process of operator fatigue;
* Doubling the rotational speed of the brush results in a linear increase in torque. The obtained results confirm that the above relation is correct for different rotational speeds;
* Compared to manual processing, the operator (locksmith) was not able to work within the range of rotational speed tested. This is directly related to the physical endurance of a human, and directly translates into much faster wear of the brush in a manual process. In connection with these observations, it is important to introduce an industrial manipulator to the process in order to reduce tool wear;
* The increase in the engagement of the detail in the disc brush leads to a non-linear increase in torque. The observed effect is much smaller at higher rotational speeds;
* During the tests, tools that were not brand new were also used. Based on the tests carried out, it was observed that for the new disc, the measured moment during brushing was about 20% higher;
* During all the tests carried out, burr removal was recorded in a way that meets the design requirements.  
Figure 13: Typical work piece condition—before and after deburring operation.
## 4 Results and Discussion
### Linear Polarization Resistance Results  
Alternatively, electrochemical polarization tests allow us to obtain the corrosion rates in a fast way, in which the results obtained for the materials AISI 304, AISI 430, nickel-based alloy HR-224, and ferritic steel VM12 in both cases of salt mixture are shown in Table 11 and the Tafel curves shown in Figures 16 and 17. A comparison between the corrosion rates of the two study salts can be seen, taking into account the open circuit potential of the electrochemical system, the corrosion potential, and the current density.  
Figure 16: Polarization curves of stainless steel AISI 304, AISI 430, and nickel-based alloy HR-224 in KNaNO\({}_{3}\) (solar salt) at 550 \({}^{\circ}\)C and 100 h of exposure.  
Figure 17: Polarization curves of stainless steel AISI 304, AISI 430, nickel-based alloy HR-224 and ferritic steel VM12 in LiNaKNO\({}_{3}\) (ternary salt with lithium content) at 550 \({}^{\circ}\)C and 100 and 1000 h of exposure.  
The corrosion models mentioned in the article were confirmed by scanning electron microscopy SEM Inspect F50 (Scientific and Technical Instruments, Wilsonville, OR, USA). Figures 18 and 19 show the surface appearance of the AISI 304 and AISI 430 material after 100 h of exposure to both solar salt and the ternary lithium mixture, as well as an energy dispersive x-ray EDX analysis of the particles found on the surfaces. The layers of oxide formed are homogeneous in the same cases. The EDX analysis of the material on the surface indicated that the composition of the oxidation layer analysed was iron oxide and chromium, and therefore the presence of a protective layer was confirmed. Figure 20 shows the surface appearance of the nickel-based HR-224 alloy after 100 h of exposure for solar salt and for the ternary lithium containing molten salt, including EDX analysis of the surface. The oxide layer found shows a totally homogeneous layer in both cases. According to the EDX analysis of HR-224, it was shown to be composed of nickel, chrome, oxygen, and iron. Finally, Figure 21 shows the surface appearance of ferritic steel VM12 immersed in lithium nitrate molten salt for 100 and 1000 h of exposure. The oxide layer for 100 h shows a more homogeneous surface with respect to the 1000 h sample, where some areas with detachment of the corrosive  
Figure 19: Surface of 430 ferrite stainless steel in (**a**) Solar Salt (**b**) LiNaKNO\({}_{3}\), at 550 \({}^{\circ}\)C after 100 h.  
Figure 20: Surface of HR-224 Nickel alloy in (**a**) Solar Salt (**b**) LiNaKNO\({}_{3}\), at 550 \({}^{\circ}\)C after 100 h.
# Performance Analysis of Dual-Hop AF Relaying with Non-Linear/Linear Energy Harvesting
## 3 System Model  
The DH AF relaying system under consideration is given in Figure 1, where the source (S) and relay (R) are power-constrained nodes and harvest their energy from a dedicated power beacon (PB). Hence, S and R use their harvested powers for data transmission. In the absence of a direct link between S and the destination (D), the communication is provided with the help of R. All nodes are equipped with only one antenna.  
A typical RF EH process is achieved in a short range and a line of sight (LoS) exists between PB and the EH nodes. Inspired by this fact, we assume that the links between nodes in Figure 1 are exposed to mix-fading [30; 46]. The proper fading channel model, including an LoS component, is considered as the Rician model. However, the cumulative distribution function (CDF) and probability distribution function (PDF) of the Rician distribution include special functions which make the analysis more complicated and the results are not mathematically tractable. On the other hand, the Nakagami-\(m\) fading model provides a good approximation of the Rician channel model [47; 48; 49]. Motivated by this, we assume that the links PB\(\rightarrow\)S and PB\(\rightarrow\)R are exposed to Nakagami-\(m\) fading, represented by channel coefficients \(h_{s}\) and \(h_{r}\), with channel parameters \(m_{z}\) and \(m_{w}\), respectively. Moreover, the links S\(\rightarrow\)R and R\(\rightarrow\)D are subject to Rayleigh fading, with gains \(g_{1}\) and \(g_{2}\), respectively. It is assumed that the CSI is perfectly known at the receiving nodes, and the channels are assumed to be exposed to flat fading and remain fixed during a transmission interval and vary independently from one interval to another. The overall transmission time \(T\) is divided into three equal time slots, as shown in Figure 2. It should be noted that this assumption is considered in [2; 4] where it provides a maximized system performance. In the first time slot of duration \(T/3\), PB broadcasts the dedicated energy bearing signal. In the second and third time slots, S and R transmit their signals to R and D, respectively. \(n_{r}\) and \(n_{d}\) denote additive white Gaussian noise (AWGN) samples which are independent and identically distributed (i.i.d.) complex Gaussian random variables (r.v) as \(n_{r},n_{d}\sim\mathcal{CN}(0,N_{0})\). Finally, the notation and system parameters are listed in Tables 1 and 2, respectively.  
Figure 1: Wireless-powered DH AF relaying system model where S and R harvest their energy from a dedicated PB. S and R use their harvested power for data transmission.  
Figure 2: Transmission time frame of the considered wireless-powered system. The transmission frame is assumed to be equally-partitioned into three time slots for EH and information processing (IP).
## 2 Study Framework
#### Traffic Conflict Ratio  
To evaluate the effectiveness of increasing the TT speed limit with different traffic demand, the simulated conflicts before and after increasing the TT speed limit are estimated, and the conflict ratio (\(\rho\)) is obtained as follows [15; 16]:  
\[\rho=\frac{C_{a}}{C_{b}} \tag{3}\]  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Strategy**} & \multicolumn{2}{c}{**Total Volume**} & \multicolumn{2}{c}{**Tractor-Trailer (TT)**} \\  & **(Vehicle/h/Lane)** & **Volume (\% from** & **Speed Limit** \\  & & **Total Volume)** & \\ \hline \multirow{4}{*}{**USL**} & 500 & & **PCs:** 90 km/h \\  & 750 & & - & **TTs:** 90 km/h \\  & 1000 & and 15.0 & **PCs:** 100 km/h \\  & 1500 & & - & **TTs:** 100 km/h \\  & 2000 & & & \\ \hline \multirow{4}{*}{**DSL**} & 500 & & **PCs:** 90 km/h \\  & 500 & & - & **TTs:** 60 km/h \\  & & & - & **TTs:** 70 km/h \\  & 750 & 2.50, 5.0, 7.50, 10.0 & - & **TTs:** 80 km/h \\  & 1000 & and 15.0 & **PCs:** 100 km/h \\  & 1500 & & - & **TTs:** 70 km/h \\  & 2000 & & - & **TTs:** 90 km/h \\ \hline \hline \end{tabular}
\end{table}
Table 2: Different combinations of traffic volumes, %TTs and speed limit.  
Figure 2: Hypothetical highway section.  
with a variance of:  
\[Var(\rho)=(C_{a}/C_{b})^{2}\times\left[\left(Var(C_{a})/{C_{a}}^{2}\right)+\left( Var(C_{b})/{C_{b}}^{2}\right)\right] \tag{4}\]  
where:  
\(\rho=\) conflict ratio;  
\(C_{a}=\) average number of conflicts after increasing the speed limit (i.e., after);  
\(C_{b}=\) average number of conflicts before increasing the speed limit (i.e., before);  
\(Var(C_{a})=\) variance of the conflicts in the after;  
\(Var(C_{b})=\) variance of the conflicts in the before.  
The \"\(\rho\)\" value can be viewed as a modification factor based on conflicts [12]. A value of \"\(\rho\)\" greater than \"1.0\" means that increasing the TT speed limit would increase the number of simulated conflicts and thus the number of accidents, while a value of \"\(\rho\)\" less than \"1.0\" means that increasing the TT speed limit will reduce the number of simulated conflicts and therefore reduce the number of accidents. A value of \"\(\rho\)\" equal to \"1.0\" would suggest that there is no safety change due to the increase in TT speed limit. The \"\(\rho\)\" statistical significance can be obtained in the same way as collision modification factors (CMFs). For CMFs, the speed limit increase would be statistically significant if the given confidence interval does not contain \"1.0\" [49]. In this study, the increase in the TT speed limit can be concluded to be statistically significant if the given confidence interval of \"\(\rho\)\" does not contain \"1.0\", because a value of \"1.0\" would imply the absence of a treatment effect [49; 50]. The 5% significance level can be estimated as follows:  
\[CI_{95\%}=\rho\pm 1.96\times SE \tag{5}\]  
where:  
\(CI_{95\%}=\) the confidence interval at the 5% significance level;  
\(SE=\) the standard error from the 10 simulations.
# Thermal Relaxation Spectra for Evaluating Luminescence Quantum Efficiency of CASN:Eu2+
## 3 Results and Discussion
### Results and Discussion 2  
Further improvement in the S/N value was demonstrated by the intensity balanced detection system with using a birefringent crystal. As shown in Figure 4, by suppressing the probe laser beam intensity noise more effectively, the intensity balanced detection with the CaCO\({}_{3}\) crystal successfully increased the S/N by the factor of about 4.0 from the no balanced detection scheme. Generation of completely parallel beams was the most essential in this improvement. The average value of the noise intensity was decreased from 152 to 42. The experimental result with the CaCO\({}_{3}\) crystal indicated smaller noise intensity than without the CaCO\({}_{3}\) crystal. However, if the probe laser intensity noise was completely removed, the S/N should be improved by ten times. This insufficient S/N improvement suggested the other noise origin. A possible origin of this insufficient noise suppression is different paths between the signal and reference beam. If the signal and reference beams passed the different space, the probe laser beam may be suffered from the different fluctuation effect of the atmosphere on the optical path.  
Figure 4: Measurement results of balanced detection with the CaCO\({}_{3}\) crystal for activated carbon in air as a deflection medium on lock-in detection condition with AC gain: 0 dB, Sensitivity: 1 nA, Time Constant: 5 s, and Modulation Frequency: 20 Hz. The balanced detection result with the CaCO\({}_{3}\) crystal (blue line) shows smaller averaged noise intensity than with the measurement results of no-balanced detection (black line) and balanced detection without the CaCO\({}_{3}\) crystal (red line).  
Figure 3: Measurement results of balanced detection for activated carbon in air as a deflection medium on lock-in detection condition with alternating current (AC) gain: 0 dB, Sensitivity: 1 nA, Time Constant: 5 s, and Modulation Frequency: 20 Hz. (**a**) measured only with the probe laser beam with the BS inserted after the Sagnac interferometer without excitation. (**b**) measured with the optical system in Figure 1.  
The S/N for activated carbon was obtained to be more than 200 at the maximum excitation light intensity 5 mW/cm\({}^{2}\) @ 470 nm. Thus, the excitation light intensity required for S/N \(\approx\) 12 is estimated to be 50 \(\upmu\)W/cm\({}^{2}\).
# Polymerization and Collision in High Concentrations for Brownian Coagulation
## 4 Conclusions  
The effect of the particle volume fraction on particle collision and growth by Brownian coalescence in the dense system was investigated using LD simulation. Self-preserving particle size distributions (SPSDs) were obtained at all investigated particle volume fractions \(\phi\) from 0.05 to 0.3. With the increase in \(\phi\), the SPSD broadens, and the geometric standard deviation becomes 1.54, 1.98, and 2.73 at \(\phi=0.1,\ 0.2,\ 0.3\).  
Aggregates formed by particle collision have significant differences for the volume fraction \(\phi=0.05,\ 0.1,\ 0.2,\ 0.3\) with the same initial particle size \(d_{p}=3\) nm. When the volume fraction \(\phi\) is higher, the radius of gyration is smaller with the same cluster size (number-based), which means that the particle agglomerations are in a tighter coagulation. With the increase in the volume fraction, the aggregates tend to be fractal agglomeration and the fractal dimension in the range of 1.614-2.060. When the volume fraction is high, the agglomeration from the collision develops fractal-like structures.  
A summary of the fractal aggregate distribution range and fractal-like structures in the nanoscales is given, which could be applied to progress design for multi-collision nanoclusters. Finally, the detailed size distributions can be readily used with the dynamics of industrial progress design, air pollution, and meteorology.  
Conceptualization, M.Y.; methodology, M.Y.; software, X.W.; validation, X.W. and Y.L.; formal analysis, T.W.; investigation, M.Y.; resources, T.W.; data curation, X.W.; writing-original draft preparation, X.W.; writing-review and editing, Y.L.; visualization, X.W. All authors have read and agreed to the published version of the manuscript.  
This research was funded by National Natural Science Foundation of China (11872353, 91852102).  
Not applicable.  
Raw data are available on request.  
The authors thank the National Natural Science Foundation of China (11872353, 91852102) for their support.  
The authors declare no conflict of interest.  
Figure 10: The fractal dimension and monomers number in the aggregates with different volume fractions.
# A Joint Strategy for Fair and Efficient Energy Usage in WLANs in the Presence of Capture Effect
## 6 Conclusions  
PHY capture effect has been shown to improve the throughput of wireless networks. However, its effect has not yet been explored in the energy conservation domain in WLAN. Our paper is the first effort in this regard. We at first presented an analytical model based on Markov chain that takes into account capture effect to calculate energy efficiency in the presence of various parameters, such as bit error rate and traffic load. The presented analytical model was also validated using simulation showing capture effect improves energy efficiency by 20% in a network of size 30 nodes. Secondly, we showed that although capture effect improves overall network energy efficiency but causes unfair energy consumption among different groups of nodes based on their respective distances from the AP. Thirdly, we proposed a remedy based on the combination of frame level adaptive transmission power control (ATSPR) and contention window adjustment (CWAD) to overcome unfairness. Our proposed solution improves fairness by about 99% without degrading the overall aggregate energy efficiency and throughput.  
Conceptualization, B.K.; Data Curation, B.K.; Formal Analysis, B.K. and R.A.R.; Writing--Original Draft Preparation, B.K., R.A.R.; Writing--Review & Editing, B.K., R.A.R. and B.-S.K.; Funding Acquisition, B.-S.K.This work was supported by the Institute of Information and communications Technology Planning and Evaluation (IITP) grant funded by the Korea government(MSIT) (2018-0-01411, A Micro-Service IoTWare Framework Technology Development for Ultra small IoT Device).  
We would like to thanks [PERSON] for his encouragement and sincere support during this research.  
The authors declare that they have no any conflict of interest regarding this publication.  
Figure 14: Medium access control (MAC) delay comparison of AIMD+ with baseline.
# Spatio-Temporal Changes in Water Use Efficiency and Its Driving Factors in Central Asia (2001-2021)
Therefore, in the context of the severe lack of EC flux tower data in Central Asia, this study uses remote sensing to investigate the WUE of dryland ecosystems in Central Asia with the following main objectives: (1) to analyze the spatial and temporal variability and trends of WUE in Central Asia from 2001-2021 using GPP and ET products of MODIS in the GEE platform; (2) to explore the response of WUE to environmental factors in dryland ecosystems in Central Asia and to analyze the interaction between the drivers.
###### Abstract  
User evaluations of prototypes in virtual reality (VR) offer high potential for products that require resource-intensive prototype construction, such as drilling rigs. This study examined whether the user evaluation of a VR prototype for controlling an onshore drilling reproduces results comparable to an evaluation in the real world. Using a between-subject design, 16 drilling experts tested a prototype in VR and reality. The experts performed three different work processes and evaluated their satisfaction based on task performance, user experience, and usability via standardized questionnaires. A test leader evaluated the effectiveness of the work process execution using a 3-level rating scheme. The number of user interactions and time on task were recorded. There were no significant differences in the effectiveness, number of interactions required, perceived usability, and satisfaction with respect to task performance. In VR, the drilling experts took significantly more time to complete tasks and rated the efficiency of the VR prototype significantly higher. Overall, the real-world evaluation provided more insights into prototype optimization. Nevertheless, several usability issues have been identified in VR. Therefore, user evaluations in VR are particularly suitable in the early development phases to identify usability issues, without the need to produce real prototypes.  
virtual prototype; usability test; virtual reality (VR); oil and gas industry; human-technology interaction; control room design +
Footnote †: journal: Applied Sciences  
1 Center for Ergonomics and Medical Engineering, FH Munster University of Applied Sciences, Burgerkamp 3, 48565 Steinfurt, Germany; [EMAIL_ADDRESS] (S.K.); [EMAIL_ADDRESS] (C.S.) Institute of Psychology and Ergonomics, Technical University Berlin, Fasanenstrasse 1, 10623 Berlin, Germany; [EMAIL_ADDRESS]
## 3 Results and Discussion
### Phytochemical Assessment by HPLC Analysis  
Polyphenol identification was performed by HPLC-DAD, comparing R.T. of chromatographic peaks of unknown compounds with reference standards. In Figure S1 of Supplementary Material, a representative chromatogram of a standard mixture is reported, while a representative chromatogram obtained from the analysis of 40% ethanol extract of prickly pear seeds is reported in Figure S2. Results reported in Table 4 show that only six of the 12 phenols monitored were detected and quantified in the seed extracts, and the variability among the three cultivars was not significant.  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Peak N.** & **Compound** & **\(\mu\)g/100 g in Yellow** & **\(\mu\)g/100 g in Green** & **\(\mu\)g/100 g in Orange** \\ \hline
1. & Chlorogenic acid & 699.3 & 699.1 & 701 \\ \hline
2. & Gallic acid & 102 & 101.9 & 101.5 \\ \hline
3. & Hydroquinone & - & - & - \\ \hline
4. & Resorcinol & - & - & - \\ \hline
5. & Pyrocatech & - & - & - \\ \hline
6. & Catechin & - & - & - \\ \hline
7. & Hydrated catechin & - & - & - \\ \hline
8. & Syringic acid & - & - & - \\ \hline
9. & Caffe acid & - & - & - \\ \hline
10. & P-coumaric acid & 90.02 & 89.9 & 89.1 \\ \hline
11. & Ferulic acid & 19.8 & 21.01 & 20.00 \\ \hline
12. & Sinapic acid & 19.5 & 19.9 & 20.02 \\ \hline
13. & Rutin & - & - & - \\ \hline
14. & Naringenin & 100.1 & 98.7 & 99.9 \\ \hline
15. & Quercetin & - & - & - \\ \hline \end{tabular}
\end{table}
Table 4: Identification of different constituents of _Oputnia focus-indica_ seed extracts in different plant cultivars from the Souk Ahras area, Northeast Algeria.  
To the best of our knowledge, only a small amount of information is available about the composition and concentration of phenolic compounds in prickly pear seeds, as opposed to other plant parts. Regarding the phenols in seeds, available information has been summarized in a recent review [35]. The studies here described show a high variability among different fruit varieties, for instance, high amounts of chlorogenic acid have been reported in \(O\). _ficus-indica_ seeds (885.31-1148.41 \(\upmu\)g/g), but other compounds such as gallic acid and p-coumaric acid have not been found. It must be pointed out that the content of chlorogenic acid determined in our study is almost ten times lower than that reported in [35]. Nevertheless, as reported above for the TPC determination, and as suggested by other authors, all these variabilities can be attributed mainly to environmental factors, plant origin, species, developmental stage, and age [35].  
Another point should be raised. In our study, only a limited number of phenolic constituents was monitored, and this contributed to the high discrepancy observed between the TPC, TFC, and TC, and the low amounts of derivatives detected in the seed extracts. Further studies will be performed for a deeper characterization of these constituents in seeds from \(O\). _ficus-indica_ growing in Algeria.