esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Implementation and Power Estimation
Thus we see that saving in power can be approximately seven times when \(\text{SNR}_{FE}\) is high and interferences are absent. Looking into Table 1, when there is no interference (Case-I), the variation in power is from \(2.49\) mW to \(0.49\) mW. It suggests that even with a high-order interference reject filter in RF chain of the receiver, just by \(\widehat{\text{SNR}}_{FE}\) estimation power saving of the order of 5 times is possible. It is evident from the Table 1 that when \(\widehat{\text{SNR}}_{FE}\) is very high ( \(>\)\(20\) dB), \(f_{s}\) of \(2\) Msps and \(Q_{dig}\) of \(1\)-bit works for all interference condition. Thus inaccuracy in interference detection is tolerable at very high \(\widehat{\text{SNR}}_{FE}\) as mentioned in a previous section on IDSE. Since this is the power averaged over the maximum packet length possible, the lowest power values is a function of packet length. The average packet length depends on the application and usage. The power numbers for different packet length can be obtained from Equation (12). One more point to consider while looking at the power numbers is, the numbers do not include the possible power savings that can be obtained from a variable resolution ADC. A variable resolution and variable sampling rate ADC can take advantage of different possible \(Q_{dig}\) and \(f_{s}\) settings to lower the power consumption. Table 2 shows break-up of gate count of the design in percentage. Total gate count of the design is approximately \(606\) K gates. We see that tracking unit has largest gate count. We see that expense of adaptivity and lowering power is \(16\)% additional gate count of IDSE unit. The design contains approximately \(4.5\)% memory elements (ROM). The design has many Baugh-Wooley 2's complement signed multipliers in it, it is by virtue of many FIR filters in IDSE unit and in data-path. Though synchronization units consume more area as shown in Table 2, average power consumed by synchronization units is very less. Considering this, we realize that adding any component to data-path requires more attention than adding a component to synchronization unit. Finally, Figure 14 shows the power consumption as a function of \(Q_{dig}\) and \(f_{s}\), as was discussed while formulating the design problem in Equation (1). \begin{table}
\begin{tabular}{|c|c|c|c|c|c|c|c|c|} \hline \multirow{2}{*}{Interference attenuation} & No. of bits & \multicolumn{8}{c|}{Sampling Frequency (\(f_{s}\)/\(f_{per}\)) in Mops, Power in mW} \\ \cline{2-10}  & \(Q_{dig}\) & \(\text{SNR}_{FE}=-6.0\) dB & \(\text{SNR}_{FE}=-4.0\) dB & \(\text{SNR}_{FE}=-2.0\) dB & \(\text{SNR}_{FE}=0.0\) dB & \(\text{SNR}_{FE}=5\) dB & \(\text
# Direct Selective Oxidation of Hydrogen Sulfide: Laboratory, Pilot and Industrial Tests
## 9 Modifications of the Claus Process
### Chemism of the Process of Direct Catalytic Oxidation of Hydrogen Sulfide
When these pores are blocked with sulfur, the catalyst is deactivated. When CO and CO\({}_{2}\) are present in the gas, a side product, COS, appears [78; 79]. The impregnation of AC with sodium hydroxide facilitates hydrogen sulfide conversion [71; 80; 81; 82], as NaOH improves H\({}_{2}\)S dissociation to form hydrosulfide ion (HA\({}^{-}\)) followed by its oxidation to S, SO\({}_{2}\), and H\({}_{2}\)SO\({}_{4}\). Hydroxyl groups (OH\({}^{-}\)) on the carbon surface enable binding SO\({}_{2}\) with COS due to an ion-dipole interaction between OH\({}^{-}\) and COS. Reaction conditions for the selective catalytic oxidation of hydrogen sulfide (temperatures, ratios of O\({}_{2}\)/H\({}_{2}\)S, and volumetric flow rate) have a significant effect on the activity and selectivity of AC-based catalysts [61]. Herewith, the microporosity and relatively small pore volume limit adsorptive capacity, with values of 0.2-0.6 g of H\({}_{2}\)S/g for AC treated with alkalis and 1.7-1.9 g of H\({}_{2}\)S/g for AC with oxygenated groups on the surface; sulfur saturation of the catalyst requires its frequent replacement. Other drawbacks of such adsorbents/catalysts preventing their wide applications are connected with the trend to spontaneously ignite upon hydrogen sulfide adsorption on alkaline AC and limited regeneration possibilities. [PERSON] and co-authors [83] describe the synthesis and properties of nitrogen-doped mesoporous carbon. This material shows a high concentration of catalytically active sites and a large pore volume. When nitrogen content is 8%, adsorptive capacity values of 2.77 g of H\({}_{2}\)S/g at 30 \({}^{\circ}\)C and relative moisture content of 80% were achieved. The presence of pyridine nitrogen explains the elevated capacity. Nitrogen atoms located at the facets of graphite cavities have a high electron acceptor capacity, which facilitates the adsorption of oxygen atoms and therefore facilitates the oxidative reaction. Furthermore, the presence of pyridine active sites on the surface increases the basicity of the aqueous layer therein and simplifies H\({}_{2}\)S dissociation to form HS\({}^{-}\) ions. The nitrogen content plays a key role, affecting the basicity and thus the concentration of HS\({}^{-}\).
## 5 Induced Aging Mechanisms of STSCs
### Diffusion Aging Mechanism  
The diffusion mechanism in STSCs generally manifests in two essential configurations: inward and outward diffusion schemes. Outward diffusion mainly entails interactions with the environment, such as the diffusion of oxygen into the absorber substrate or coating. Inward diffusion happens through two primary mechanisms: inherent segregation and inherent penetration [103; 104]. The diffusion mechanism induced by inherent penetration is the more commonly documented mode in the testing in the previous relevant investigations.  
[PERSON] et al. [105] examined the thermal stability of a three-layer SiON/NbTiON structure, which demonstrated a high absorptance of 0.95 and a low emittance of 0.07. However, degradation of the STSC occurs at temperatures above 500 \({}^{\circ}\)C due to oxidation and diffusion of copper. The stainless steel substrated STSC exhibited superior thermal stability compared to that of a copper substrated STSC. [PERSON] et al. [106] demonstrated that the development of nanocrystalline AlCrN/AlCrON STSCs improved the tolerance of the multilayered STSC by limiting nanoparticle accumulation and interface degradation. The enhanced selectivity observed after vacuum-annealing was due to the partial recrystallization of the amorphous matrices, leading to the formation of nitride nanoparticles that increased intrinsic absorption by extending the optical path. However, the multilayered STSC became unstable after being annealed at 550 \({}^{\circ}\)C in air for 2000 h. [PERSON] et al. [107] deposited AlNi-Al\({}_{2}\)O\({}_{3}\) on a stainless steel substrate and subjected it to heating at 500 \({}^{\circ}\)C for 138 and 284 h in a vacuum to assess optical stability. They found that the highly stable AlNi compound, as opposed to traditional Mo used in Mo-Al\({}_{2}\)O\({}_{3}\) coatings, exhibited good thermal stability at 500 \({}^{\circ}\)C. The optical properties of the coating showed no significant change following the heat treatment. [PERSON] et al. [108] developed an STSC of SiO\({}_{2}\)/CrNxOy on a copper substrate. Their research highlighted that the diffusion, whether occurring throughout the stacked layers, as well as chemical interactions close to the interface and the broadening of the interface width, are critical factors impacting the thermal stability of STSC. [PERSON] et al. [65] observed that while the Al\({}_{2}\)O\({}_{3}\)/SS/ZrC-ZrOx coating demonstrated good thermal stability in a vacuum at 500 \({}^{\circ}\)C for 5 h, higher annealing temperatures led to the formation of irregular particles and numerous small pores. After being exposed to air for 4 months, the coating changed to a purple color, showcasing 0.112 emittance and 0.456 absorptance, respectively.
## 3 Test Results and Analysis  
### Failure Modes  
The tensile strength of concrete is lower than that of steel bars. During the drawing process, the steel bars have not yet reached the yield stage. In contrast, the concrete had already reached its ultimate tensile strength, exhibiting distinctly brittle failure characteristics, as shown in Figure 5a. Figure 5b depicts splitting shear failure, a form of bond anchoring failure between steel bars and concrete. Throughout the loading process, the load escalates rapidly with slip, and concrete splitting failure occurs in the horizontal or descending section of the load-slip curve. However, in contrast to splitting failure, the load does not suddenly plummet to zero, and the specimen retains a specific load-bearing capacity at a later stage. Figure 6c shows the steel bar pull-out failure, an ideal failure mode that allows for the acquisition of the complete process curve of the bond slip. Throughout the loading process, both the free end and loading end slip incrementally with the increasing load, resulting in a relatively steep slope of the bond-slip curve. Upon reaching the ultimate load, the steel bars are gradually pulled out, inducing a shear slip between the steel bars and the concrete along the longitudinal direction of the steel bars, leading to a failure pattern resembling a plough. The pulling process is relatively slow, with the load also reducing to approximately 20% of the peak load and stabilising thereafter.  
Figure 4: Loading device.  
Figure 5: Specim failure pattern. (**a**) Concrete splitting; (**b**) split-shear failure; (**c**) steel bar pull-out.  
Figure 6: Bond–slip curve of hybrid fiber-reinforced concrete. (**a**) The influence of concrete strength on the bond–slip curve; (**b**) the influence of steel bar diameter on the bond–slip curve; (**c**) the influence of protective layer thickness on the bond–slip curve; (**d**) the influence of anchorage length on the bond–slip curve. Note: \(\tau\) is the bond stress between steel bars and concrete. \(S\) is the value of steel bar slip.
# Application of Compressive Sensing in the Presence of Noise for Transient Photometric Events
## 3 Noise in Compressive Sensing Measurements
### Expected Value and Variance for CS Applications  
Since \(A\) and \(n_{b}\) are independent random variables, the expected value of the noise is  
\[E[N]=E[A]E[n_{b}]+E[n_{s}]+E[n_{t}] \tag{15}\]  
Given that \(n_{b}\) has a Gaussian distribution with mean 0, the expected value of \(E[A]E[n_{b}]=0\). If we assume thermal noise to be normally distributed as well, \(E[n_{t}]=0\). Hence, \(E[N]=E[n_{s}]\) in those circumstances. For all independent noise sources, variance is given by  
\[Var[N]=Var[A]Var[n_{b}]+Var[n_{s}]+Var[n_{t}] \tag{16}\]  
In our work, we propose to construct \(A\) so that it has a low variance. We compare the results with a binomial distribution as well as Gaussian distribution.  
In this section, we also describe mutual coherence of a matrix and its relation to CS reconstruction. Hence, the variance of the noise as well as mutual coherence, \(\mu\), of \(A\) will factor in the reconstruction accuracy using CS methods.
## 5 NB-IoT System Implementation
### Hardware Set-Up  
Here, the whole system setup is presented; as mentioned before, three USRPs are utilized working at a frequency of 900 MHz and a gain of 30 dB and two FPGAs. As shown in Figure 22, the two FPGAs and the three USRPs are ready for transmission and reception. The parameters of NB-IoT hardware setup components are described in Table 2.  
As illustrated in Figure 23, when the USRP of the base station receives the data from the UE1, its red LED turns on, and the FFT plot on GNU Radio has a peak.  
Then, when the base station MATLAB code finishes running, two files are generated; one contains the real part of OFDM symbols, and the other contains their imaginary part.  
\begin{table}
\begin{tabular}{l l} \hline (1) and (A) & The USRP and the FPGA of the UE1, respectively \\ \hline (2) and (B) & The USRP and the FPGA of the UE2, respectively \\ \hline (3) & The USRP of the base station \\ \hline \end{tabular}
\end{table}
Table 2: NB-IoT hardware setup components.  
Figure 23: Receiving data on the base station.  
Figure 22: NB-IoT Hardware Setup.  
Finally, the USRP of the UE2 receives the data from the base station, as its red LED turns on, and the FFT plot on GNU Radio has a peak as shown in Figure 24.
# Compact Full Ka-Band Waveguide Directional Coupler Based on Rectangular Aperture Array with Stairs
## 1 Introduction
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Coupler** & **Frequency(GHz)** &
\begin{tabular}{c} **Coupling Strength** \\ **Imbalance (dB)** \\ \end{tabular} & **Bandwidth (\%)** & **Relative Length** & **Type** \\ \hline
[11] & 31–36.7 & \(\pm\)0.54 & 16.8 & 1.41 \(\times\)\(\lambda\)g & SIW \\ \hline
[18] & 6.57–9.99 & \(\pm\)0.6 & 41.3 & 3.37 \(\times\)\(\lambda\)g & RW \\ \hline
[19] & 10.675–13.325 & \(\pm\)0.5 & 22.08 & 1.66 \(\times\)\(\lambda\)g & HMSIW \\ \hline
[20] & 13–17 & \(\pm\)0.5 & 26.67 & 1.41 \(\times\)\(\lambda\)g & ESIW \\ \hline
[21] & 33–37 & \(\pm\)0.33 & 11.43 & 0.71 \(\times\)\(\lambda\)g & SIW \\ \hline This work & 26.5–40 & \(\pm\)0.53 & 40.6 & 1.35 \(\times\)\(\lambda\)g & RW \\ \hline \end{tabular} HMSIW: half-mode substrate-integrated waveguide. RW: rectangular waveguide. ESIW: empty substrate-integrated waveguide. SIW: substrate-integrated waveguide. \(\lambda\)g: operation wavelength of the center frequency.  
\end{table} 
Table 1: Performance comparison of some recently reported 3 dB directional couplers.
## 2 Background
### Network Traffic Entropy  
Entropy was introduced as a measure of uncertainty by [PERSON] in 1948 [22]. Assuming that \(X\) is a dataset with a finite number \(n\) of independent symbols, represented by \(x_{1},x_{2},\ldots,x_{n}\), with corresponding probabilities \(p=p_{1},p_{2},\ldots,p_{n}\), the entropy of \(X\) is defined as follows:  
\[H(X)=-\sum_{i=1}^{n}p_{i}\log p_{i} \tag{1}\]  
The entropy value ranges between 0 and \(\log n\), reaching the upper bound when \(X\) has a uniform distribution. To make entropy values independent of the number of distinct symbols, entropy can be normalized to vary from 0 to 1 as follows:  
\[H_{N}(X)=\frac{H(X)}{\log n} \tag{2}\]  
Figure 1: Comparison of the architecture of a traditional switch and a P4 programmable switch. The forwarding behavior of the P4 programmable switch can be configured directly from the application, setting the P4 program, while in a legacy switch, the application will determine the behavior of the control plane that will then configure the data plane.  
From the above definitions, it is possible to define network traffic entropy as an indication of traffic distribution across the network [23]. Each network switch can evaluate the traffic entropy related to the network flows that cross it in a given time interval \(T_{int}\) as:  
\[H=-\sum_{i=1}^{n}\frac{f_{i}}{|S|_{tot}}\log_{d}\frac{f_{i}}{|S|_{tot}} \tag{3}\]  
where \(f_{i}\) is the packet count of the incoming flow \(i\), \(|S|_{tot}\) is the total number of processed packets by the switch during \(T_{int}\), \(n\) is the overall number of distinct flows and \(d\) is the base of the logarithm. Network traffic entropy reaches its minimum value \(H=0\) when in the given time interval \(T_{int}\), all packets \(|S|_{tot}\) belong to the same flow \(i\), while it reaches its maximum value \(H=\log_{d}n\) when each of the \(n\) flows transports only one packet.
## 2 Materials and Methods
### Determination of Land Use  
#### 2.3.1 Image Processing  
The images used for land use classification were downloaded from NASA's official web page [[https://earthexplorer.usgs.gov](https://earthexplorer.usgs.gov)]([https://earthexplorer.usgs.gov](https://earthexplorer.usgs.gov)), accessed on 3 February 2023. From Landsat 7 and Landsat 8 satellites, considering a cloud cover of less than 30% so that the visible field is as wide as possible. Twenty satellite scenes from the years 2000, 2010, and 2020 with path = 10 and row = 61 were used for the central area of the country and aggregated into a single layer. The atmospheric correction and geometric verification procedures of the images were performed with QGIS 3.4 software. The software was downloaded on January 20, 2023 through the following page [[https://qgis.org/es/site/forusers/download.html](https://qgis.org/es/site/forusers/download.html)]([https://qgis.org/es/site/forusers/download.html](https://qgis.org/es/site/forusers/download.html)) [28]. Atmospheric correction was performed using the dark object subtraction method, which aims to correct the electromagnetic energy scattering effect of water particles suspended in the atmosphere [28]. The geometric accuracy of the images was verified using topographic maps and base maps of rivers and roads, georeferenced in the UTM Datum WGS84 projection of the Ecuadorian Military Geographic Institute [29].
## 4 Discussion  
The pulse-width subdivision detection algorithm proposed in this paper can, in theory, completely solve the problem of insufficient encoder pulse resolution. The simulation experiment test results verify the effectiveness of the algorithm presented in Figure 12. However, according to the industrial-application production test results in Figure 15, the register error of the final printed products is also affected by many other factors, such as color difference variation, mechanical vibration and transmission error, etc. In Figure 16, it is obvious that a longer error compensation time results in more printing waste produced in a high-speed printing situation (e.g., 150-180 m/min production speed). The optimized error compensation strategy has a good effect on improving this problem. However, the setting of appropriate, relevant parameters (e.g., stacking velocity) depends on various external conditions, such as printing speed, photoelectric sensor installation position and web tension, etc. Therefore, there is still a lot of room for improvement in the intelligence level of the printing register control system. To sum up, for the improvement of the final production efficiency, the impact of each operating link must be comprehensively considered.  
In comparison with similar register control approaches, such as fully decoupled proportional-derivative control or model-based feedforward proportional differential control, the novelty of this work can be summarized as the efficiency and practicality of the proposed control algorithm. Existing control algorithms are based on complex, time-consuming tension decoupling mathematical models and are difficult to apply in engineering practice. The impacts of color mark detection accuracy are also rarely considered in the existing research literature. The proposed register control approach is based on engineering application practice, studying the principle of color mark detection, printing pattern quality influence and the output compensation mechanism, significantly improving the accuracy and speed of the register control system.
# Propagation, Scattering and Defect Detection in a Circular Edge with Quasi-Edge Waves
## 3 Experimental Study
### Experimental Setup  
The experimental setup for generating and sensing \(QES_{0}\) is presented in Figure 11a. The input signal, an eight-cycle Hann-windowed tone burst, was generated using a signal generator (National Instrument PXIe-5412). The central frequency of the input signal was 200 kHz. Then, a signal amplifier (Ciprian HVA-800-A) was used to amplify the input signal to \(\pm\)200 V. The amplified signal was then sent to a transducer (ULTRAN-GC200), which could generate a longitudinal wave. The transducer was installed on a 53\({}^{\circ}\) wedge, which was made of 'Polystone', as shown in Figure 11b. The wedge was clamped to the top edge of an aluminium tube-like specimen. A coupling gel (Dow corning high-vacuum grease) was applied on the interface between the wedge and the top edge of the specimen to ensure the effective transmission of the longitudinal wave from the wedge into the specimen, thereby generating the \(QES_{0}\) mode. The locations of the two measurement points for measuring reflected and transmitted waves were defined as consistent with the configuration of the FE model described in Section 2.3. The normal displacement of the measurement points located on the top edge was collected by a one-dimensional (1D) laser Doppler vibrometer (Polytech PSV-400-M2-20). The measurement distance was fixed at 1 m. The sampling frequency was set to 25.6 MHz, and each measurement was averaged by 200 acquisitions. To improve the signal-to-noise ratio, the edge was coated with reflective paint, and a low-pass filter with a cut-off frequency of 1 MHz was applied to the laser Doppler vibrometer.
# Dynamic Instability Analysis of a Double-Blade Centrifugal Pump
## 4 Conclusions  
In this study, the flow instability of a double-blade centrifugal pump was investigated. The following specific conclusions can be obtained:  
1. The region in the pump experiencing the largest pressure pulsation is located at the vicinity of tongue of solute. The amplitude of pressure pulsation decreases as the relative gap between the impeller outlet and the solute wall surface increases. The rotor-stator interference between the impeller and solute is the main source of pressure pulsation. Highly intensive pressure pulsation is found at part-load conditions due to serious flow instability.
2. A strong vorticity fields in the vicinities of solute tongue and suction side of impeller blade were observed. These vortices are unstable, and they influence the normal flow streamlines, and destabilize the radial forces on each blade. Additionally, the interaction between blade and tongue causes the dynamic fluctuation of blade loads.
3. The main excitation frequencies were identified by measuring the vibration data of the double-blade centrifugal pump. In general, vibration amplitude at blade passing frequency (St = 1) is higher than others. There is a direct link between pressure pulsation and pump vibration, and pressure pulsation is a major source of fluid-induced vibration.
4. Considering the difficulties in performing the dynamic pressure measurement on pump solute, due to the pump solute being located inside the chamber, CFD was used as a main tool to analyze the dynamic instability of pump model. In future, it will be more comprehensive to involve the measurement on rotor movement orbit to help observe the dynamic behaviors of double-blade centrifugal pump.  
Conceptualization, D.W. and S.Y.; methodology, D.W. and Y.R.; software, D.W., S.Y. and Y.G.; validation, D.W., Y.R. and P.Z.; formal analysis, D.W. and Y.G.; investigation, D.W. and R.L.; resources, J.M.; data curation, D.W.; writing--original draft preparation, D.W.; writing--review and editing, D.W. and S.Y.; supervision, R.L. and J.M.; project administration, R.L. and J.M.; funding acquisition, D.W., Y.R., P.Z. and J.M. All authors have read and agreed to the published version of the manuscript.  
This research was funded by National Natural Science Foundation of China (Grant No. 51779226), Zhejiang Provincial Natural Science Foundation (Grant No. LGG21E090002, LY21E060004, LGG21E090003), the China Postdoctoral Science Foundation (Grant No. 2021M691383) and Science and Technology Plan Project of State Administration for Market Regulation (Grant No. 2020 MK192).  
Not applicable.  
The authors declare no conflict of interest.