esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Results and Discussion  
### Mechanical Property and Viscosity Characteristics of the ESA Binder  
The tensile test results for different ESA binders are shown in Figure 5a. As the EP content increased from 35 wt% to 50 wt%, the \(TS\) of the ESA binder increased while the \(EB\) gradually decreased. Specifically, the \(TS\) increased from 2.56 MPa to 4.42 MPa, and the \(EB\) declined from 279% to 223%. As mentioned in the literature, an EP content of  
Figure 4: Designation of trial road lanes.  
35 wt% initially formed a cross-linked structure in the binder, and the structure was gradually enhanced with increasing EP content [25]. This contributed to the improvement of the mechanical properties of the ESA binder but compromised the toughness of the binder as the cross-linked structure would restrict the flow of the asphalt. In previous studies, the \(TS\) and \(EB\) of the EA50 binder were 3.6 MPa and 210%, respectively. Comparatively, the \(TS\) and \(EB\) of the ESA50 binder were elevated to 4.42 MPa and 223% [11; 14]. The main reason was that the SBS-modified asphalt binder used in this study was obtained by the modification of the base binder, which had a better general performance. The Chinese specification (JTG/T 3364-02-2019) requires that \(TS\geq 2\) MPa and \(EB\geq 100\%\) for the performance of the EA binder for SBDP [24]. Undoubtedly, the tensile properties of all ESA binders could meet the requirements of engineering applications.  
The generation of curing reactions in ESA binders leads to an increase in viscosity. The ESA binder was generally required for a sufficient allowable time to ensure successful construction [37]. Figure 5b illustrates the viscosity test results of the ESA binder. It can be seen that, as the EP system viscosity was lower than that of SBS-modified asphalt binder at the same temperature, the initial viscosity of the ESA binder reduced with increasing EP content, from 748 mPa\(\cdot\)s for ESA35 to 542 mPa\(\cdot\)s for ESA50. Notably, the SBS-modified asphalt binder had a higher viscosity, such that the viscosity of the ESA binder was higher than that of the EA binder prepared with the base binder. Meanwhile, with the extension of the test time, the viscosity of the ESA binder exhibited a gradual increase, which was mainly attributed to the curing reaction happening, and the higher the EP content, the more substantial the reaction in the system, the faster the viscosity growth. After the test was conducted for 30 min, the change in the ESA binder viscosity slowed and displayed a linear change. At 150 min, the viscosities of ESA35, ESA40, ESA45, and ESA50 binders were 1350, 1890, 2440, and 2950 mPa\(\cdot\)s, respectively. The Strategic Highway Research Program (SHRP) protocols stipulate that the asphalt binder viscosity should be \(\leq\)3000 mPa\(\cdot\)s, and the allowable time should be \(\geq\)45 min. The results showed that the allowable time of all ESA binders could exceed 150 min, which satisfied the specification requirements.
# Time-Domain Aeroelasticity Analysis by a Tightly Coupled Fluid-Structure Interaction Methodology
## 4 Mesh Deformation Method  
For volume mesh deformation driven by surface motion in FSI problems, mesh deformation method based on radial basis functions (RBF) is a powerful solution. RBF mesh deformation method with reduced point selection proposed by [PERSON] can achieve high quality deformed mesh efficiently for arbitrary topology. However, the improvements in deformation efficiency cause the problems of deformation errors on deformed surfaces and inverted boundary layer meshes near the wall.  
An improved option based on reduced point selection RBF method is proposed, details of the method can be found in the previous work [10]. The method selects two groups of control points from the object surfaces, and the one selected by the greedy method is used to roughly calculate the mesh position and the deformation error. Then surface points with deformation errors exceeding the tolerance are picked as the second group, which is utilized to interpolate the deformation errors to the mesh points nearby. Thus, the deformation errors on the surface are greatly reduced and the inverted boundary layer meshes near the wall are effectively avoided.
# Provably Secure ECC-Based Anonymous Authentication and Key Agreement for IoT
## 5 Security Analysis
### Descriptive Security Analysis
#### 5.2.6 IoT Nodes Capture Attack Resistance  
Some IoT end devices are placed in unattended environments and may be physically captured by an adversary. Thus, their credentials \(\{ID_{s},k_{s},PK_{s},ID_{sp},W_{ssp}\}\) can be easily extracted by \(\mathcal{A}\). The credentials for different end devices in the proposed scheme are different. Therefore, this will only lead to session key leakage between the captured \(S_{s}\) and the server \(SP\) but not between the uncorrupted end device \(S^{\prime}_{s}\) and the server \(SP\). This implies that the proposal can withstand IoT node capture attacks.
## 2 Numerical Modeling
### Boundary Condition  
In order to minimize the influence of boundary effects, the finite element model employs a width equal to twice the pile spacing 2 \(s\) in both horizontal directions (in the direction of traffic and perpendicular to the direction of traffic). At the bottom of the finite element model (z = 0 plane), the displacements in the x, y, and z directions are set to zero. The planes perpendicular to the \(x\)-axis and \(y\)-axis are fixed in their respective displacement directions. The analysis steps of the model include a geostatic stress balance, embankment construction, and subsoil consolidation. A free drainage model is established for the drainage boundary conditions by imposing zero pore pressure boundary conditions at the groundwater level surface in the consolidation analysis step. The vertical boundaries of the finite element model are defined as impermeable. The detailed boundary conditions are shown in Figure 2b.  
\begin{table}
\begin{tabular}{l c c} \hline
**Material Property** & **Embankment Fill** & **Pile** \\ \hline Unit weight, \(\gamma\) (kN/m\({}^{3}\)) & 19 & 24 \\ Young’s Modulus, \(E\) (MPa) & 25 & 20,000 \\ Poisson’s Ratio, \(v\) & 0.3 & 0.2 \\ Cohesion, \(c\) (kPa) & 1 & - \\ Friction angle, \(\varphi\) (\({}^{\circ}\)) & 30 & - \\ Dilation angle \(\psi\) (\({}^{\circ}\)) & 0 & - \\ Initial void ratio, \(\epsilon_{0}\) & 0.5 & - \\ Permeability, \(k\) (m/day) & 8.64 & - \\ \hline \end{tabular}
\end{table}
Table 1: Parameters of embankment fill and pile.  
Figure 1: The profile of a piled embankment.
# A High-Efficiency K-band MMIC Linear Amplifier Using Diode Compensation
## 5 Conclusions  
In this paper, a three-stage K-band 20-22 GHz high-efficiency linear MMIC power amplifier using 0.15 \(\upmu\)m GaAs pHEMT technology is reported. The design utilizes an optimum paralleled diode circuit for inner chip linear compensation. The MMIC generates an output power of 30 dBm and PAE of 33% at \(-\)1 dB gain compression under CW operation and delivers a lower than \(-\)20 dBe IMD3 performance with 10 MHz tone spacing. The MMIC has a smaller size and more than a 5 dB improvement of IMD3 was observed.  
Methodology, H.Z.; Software, J.H.; Validation, J.H.; Data Curation, H.Z.; Writing: Original Draft Preparation, H.Z.; Writing: Review and Editing, W.C.; Supervision, W.C.; Project Administration, Z.W.; Funding Acquisition, F.Y. This research was funded by the National Natural Science Foundation of China grant number 61604128 and the Fundamental Research Funds for the Central Universities grant number 2017 QN81002. The authors would like to thank the Institute of Aerospace Electronics Engineering of Zhejiang University for providing the research platform and technical support. The authors declare no conflict of interest.
# Adaptive Pre/Post-Compensation of Cascade Filters in Coherent Optical Transponders
## 4 Derivation of Proposed Method
As our spectrum is split into M (=256 in our case) frequency bins; therefore, we have to jointly estimate both \(G(f_{i})\) and \(W(f_{i})\) for \(i=1\ldots M\). It is worth noting that if noise at the channel output is negligible, \(P_{NN}(f)\) is approximated to zero and zero-forcing equalization can be used as near optimum. We define \(F\) as:  
\[F=\sum_{i=1}^{M}E\Big{\{}(W(f_{i})Y(f_{i})-X(f_{i}))^{2}\Big{\}}. \tag{10}\]  
Rearranging (10), we get:  
\[F=\sum_{i=1}^{M}\frac{N(f_{i})}{\Big{|}H_{c}^{-1}(f_{i})\ G(f_{i})\Big{|}^{2}+ N(f_{i})}. \tag{11}\]  
Then gradient descent approached can be used, with \(\mu\) defined as the step size. We picked a small value equal to 0.1 considering the slow dynamic of moving elements (such as the variability of total TF of cascaded WSSs over temperature):  
\[G(f_{i})=G(f_{i})+\mu*\frac{\partial F}{\partial G(f_{i})}. \tag{12}\]  
With the correction factor derived as:  
\[\frac{\partial F}{\partial G(f_{i})}=\frac{-2\big{|}H_{c}^{-1}(f_{i})\big{|}_ {2}G(f_{i})\ N(f_{i})}{(|H_{c}^{-1}(f_{i})\ G(f_{i})\big{|}^{2}+N(f_{i}))^{2}}. \tag{13}\]  
Normalization is required due to the total optical power constraint at the output of the Tx:  
\[Y(f)=X(f)G(f)Hc^{-1}(f)+N(f), \tag{5}\]0  
Finally, since both the estimated signal and noise profile are available at the output of the Rx, we can jointly derive \(W(f_{i})\) based on Equation (9) by replacing \(G\) with \(G\_norm\).
## 3 Results
### Year 2021 Optimization of the Irrigation Water Volume for Each Clone
#### 3.2.4 Berry and Must Quality Parameters and Oenological Potential
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Parameter** & **4** & **94** & **188** & **276** & **372** & **ANOVA** \\ a* & 31.85 ab & 31.62a & 31.76 ab & 31.78 ab & 32.41b & **ns** \\ b* & 7.84c & 5.68a & 6.42b & 9.53d & 7.94c & *** \\ C* & 32.8 & 32.13 & 32.40 & 33.18 & 33.05 & **ns** \\ h & 13.83c & 10.51a & 11.42b & 16.69d & 13.90c & *** \\ \hline
**Polyphenol content** & **4** & **94** & **188** & **276** & **372** & **ANOVA** \\ Quercetin 3-galactosidaseoside & & & & & \\ (mg L-1) & 0.22b & 0.19a & 0.24b & 0.29c & 0.36d & *** \\ Mirticenti 3-glucosidase + & & & & & \\ Mirticenti 3-glucuron & 2.73c & 2.0a & 2.17a & 2.43b & 2.53b & *** \\ (mg L-1) & & & & & & \\ Quercetin 3-glucuron + & & & & & & \\ Quercetin 3-glucose & 2.7d & 1.7a & 2.03b & 2.5 cd & 2.43c & *** \\ (mg L-1) & & & & & & \\ Resveratrol & & & & & & \\ (mg L-1) & & & & & & \\ \hline
**Amino acid profile** & **4** & **94** & **188** & **276** & **372** & **ANOVA** \\ His & 28.1 & 31.5 & 28.2 & 24.8 & 25.2 & ns \\ Ser & 5.31b & 5.32b & 4.67b & 1.77a & 4.14b & *** \\ Arg & 1.64 & 2.65 & 2.27 & 1.42 & 1.44 & ns \\ Gly & 39.1 & 37.8 & 54.4 & 36.6 & 68.6 & ns \\ Asp & 1.71 & 1.76 & 2.06 & 1.27 & 1.72 & ns \\ Glu & 61.9 & 58.0 & 59.6 & 49.4 & 55.5 & ns \\ Thr & 28.9 & 26.2 & 27.9 & 22.8 & 25.9 & ns \\ Ala & 9.9 & 13.3 & 11.7 & 9.6 & 12.9 & ns \\ Pro & 79.9 & 79.2 & 82.8 & 64.2 & 75.2 & ns \\ Cys & 6.3 & 27.4 & 7.6 & 22.0 & 8.4 & ns \\ Lys & 42.6 & 37.4 & 43.1 & 35.3 & 42.1 & ns \\ Tyr & 2.61a & 14.93c & 11.48b & 3.05a & 4.23a & *** \\ Met & 5.08a & 8.43b & 5.16a & 4.42a & 4.06a & *** \\ Val & 0.50a & 2.50b & 1.83b & 0.33a & 0.83a & *** \\ Ile & 0a & 1.67c & 1.00b & 0a & 0.33a & *** \\ Leu & 0.33a & 1.67b & 1.33b & 0.33a & 0.33a & *** \\ Phe & 0a & 1.33c & 1.0b & 0a & 0a & *** \\
**Total** & **314** & **346** & **277** & **331** & **ns** \\ \hline \hline \end{tabular} \({}^{\prime\prime}\)ns” not significant; *** *** indicate significant differences at the 0.1, 0.05, 0.01, and 0.001 levels of probability, respectively. In each row and for each factor, different letters indicate significant differences according to [PERSON]’s multiple range test at the 95% confidence level.  
\end{table} 
Table 12: _Cont._(2) productive water use efficiency, and (3) berry and wine quality potential, looking for an optimum balance among these three traits (Figure 10).
## 4 Test Results and Analysis  
### Hysteresis Curve  
The measured hysteresis curve of the frame is shown in Figure 9. It can be seen from the figure that the hysteresis curve of the RACFCST frame has the following characteristics:  
(1) The hysteresis curve of the RACFCST frame is symmetrical and not pinched. The reason for this is that the lateral constraint of the external steel tube on the core RAC improves the strength and deformation performance of the core RAC, so that the cracking and crushing of the core RAC will not cause a sudden change in the lateral stiffness of the whole frame. Generally speaking, the hysteresis curve presents a relatively full spindle shape, and the energy dissipation capacity of the specimen is good.  
(2) In the initial stage of load-control, the overall deformation of the frame is relatively small, the slope of the loading curve changes little, and there is basically no residual deformation after unloading. During the whole load-control stage, the hysteresis curve basically coincides, the hysteresis loop is not obvious, and the specimen is basically in the elastic stage.  
(3) In the initial stage of displacement-control, there are many cracks at the end of the beam, and the steel bars in the beam yield first, which causes the hysteresis loop to fill gradually, and the residual deformation of the frame occurs after unloading. When the lateral displacement reaches about \(\pm 2\Delta_{y}\), the frame begins to yield. After yielding, the hysteresis curve begins to incline to the displacement axis. With the increase in lateral displacement, the load acting on the specimen increases gradually, and the formed hysteresis loop becomes increasingly full. When the lateral displacement reaches \(\pm 3\Delta_{y}\), the peak load of the RACFCST frame appears. At this stage, the three hysteresis loops deviate from each other more and the strength and stiffness of the specimen show obvious degradation. At the same time, the frame has significant residual deformation after unloading, which indicates that the specimen has acquired cumulative damage.  
(4) When the lateral displacement goes up to \(\pm 4\Delta_{y}\), the bearing capacity of the RACFCST frame decreases to the level of the failure load, but the lateral displacement of the specimen can still increase, which indicates that the energy dissipation capacity of the specimen has been fully developed. At this stage, the three hysteresis loops of the specimen have deviated greatly, the strength and stiffness degradation are very obvious, and the cumulative damage of the specimen has increased significantly.  
Figure 9: Hysteretic curves of the recycled aggregate concrete filled circular steel tube (RACFCST) frame.
# A Review of Experimental Techniques for Measuring Micro- to Nano-Particle-Laden Gas Flows
## 3 Specific Measurement Methods
### Experimental Methods for Sub-micro- and Nano-particle Laden Gas Flow
Particles in well-defined charge states will collide against the outer cylinder at different electrometers, based on their electrical mobility, i.e., particles of lower electrical mobility will collide against electrometers closer to the outlet than ones with higher mobility. Hence, the current received by each electrometer can be used to reconstruct the number size distribution of the sampled particles. An FMPS does not need to scan through various voltages; hence, it has a time resolution of about 1 s for each size distribution in the size range of 5 nm to 560 nm. Similar to an FMPS, particles in an EPLI are first charged in a unipolar charger. However, unlike the SMPS and the FMPS, the EPLI [59] classifies sampled particles using a cascade low-pressure impactor, which is connected to individual electrometers. Particles impacting on a collection plate are deposited on the plate; thus, the charges on the plates generate currents related to their particle concentration. Both size and time resolutions of the EPLI are close to the FMPS, with a size resolution based on 14 channels and a time resolution of about 1 s. Moreover, it can measure high-temperature aerosols and is most commonly used in energy engineering for particles having a size range of 6 to 10 \(\upmu\)m.  
Both [PERSON] et al. [60] and [PERSON] et al. [61] found that particle size distributions (PSDs) acquired using an FMPS show a clear negative deviation from those acquired with an SMPS, although there is a strong linear relationship between these techniques. [PERSON] et al. [58] further demonstrated that PSDs measured using various SMPSs are consistent and proposed a correction expression for PSDs detected using an FMPS. High repeatability and consistency of SMPS led to its wide application in aerosol science and various industrial processes. It has been designated a standard meteorology technique for nano-aerosol measurements in many countries. A more detailed analysis of nano-particle measurement techniques can be found in [PERSON] et al. [61; 62].
# Research on the Jiamusi Area's Shallow Groundwater Recharge Using Remote Sensing and the SWAT Model
## 3 Materials and Methods
### Sources of Data
#### 3.1.5 Data for the Water Balance Technique Using Remote Sensing  
The Jiamusi hydrology station provided the majority of the data used in this computation approach. Among them were the precipitation, evapotranspiration, and regional average runoff depth, which were collected using TRMM [20] data, MOD16 software (MOD16A2 GF V061 version) [21] synthesis, and GLADS-2.1 (Global Land Data Assimilation System) [22] model estimation, respectively, and used to compute groundwater recharge in the research area by remote sensing technology.  
To sum up, details of all data studied in this paper are shown in Table 6.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Data Type** & **Data Source** \\ \hline \multirow{3}{*}{Digital Elevation Model (DEM)} & \multirow{3}{*}{NASA Earth Science data website ([[https://nasdaacs.eos.nasa.gov/](https://nasdaacs.eos.nasa.gov/)]([https://nasdaacs.eos.nasa.gov/](https://nasdaacs.eos.nasa.gov/))) accessed on} \\  & 15 June 2024 \\ \cline{3-3}  & & HWSD data downloaded from the National Tibetan \\ \cline{3-3}  & Plateau Scientific Data Center (World Soil Database) \\ \cline{3-3}  & ([[https://data.tpdc.ac.cn/home](https://data.tpdc.ac.cn/home)]([https://data.tpdc.ac.cn/home](https://data.tpdc.ac.cn/home))) accessed on 15 June 2024 \\ \cline{3-3}  & Institute of Aerospace Information Innovation, Chinese \\ \cline{3-3}  & Academy of Sciences \\ \cline{3-3}  & CMADS (V1.1) downloaded from the National Tibetan \\ \cline{3-3}  & Plateau Scientific Data Center \\ \cline{3-3}  & ([[https://data.tpdc.ac.cn/home](https://data.tpdc.ac.cn/home)]([https://data.tpdc.ac.cn/home](https://data.tpdc.ac.cn/home))) accessed on 15 June 2024 \\ \cline{3-3}  & Runoff data & Tongjiang City Hydrology Station \\ \cline{3-3}  & Precipitation data & TRMM data \\ \cline{3-3}  & Evapotranspiration & MOD16 software synthesis \\ \cline{3-3}  & Surface runoff depth & GLDAS model estimation \\ \hline \hline \end{tabular}
\end{table}
Table 6: Basic geographic data required.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Reclassification Coding** & **Name** & **SWAT Coding** \\ \hline
1 & Flowland & AGRL \\
2 & Forest land & FRST \\
3 & Meadow & RNGB \\
4 & Water & WATR \\
5 & Urban and rural, industrial and mining, & \\ \cline{3-3}  & residential land & URML \\
6 & Unused land & WETL \\ \hline \hline \end{tabular}
\end{table}
Table 5: SWAT code of land use.
## 2 Coding Metamaterials for RCS Reduction
### Elements '0' and '1' of One-Bit Coding Metamaterials  
For the optimization analyses in the above subsection, two unit cells were adopted to be assigned as '0' and '1' elements. The FR-4 substrate material without any metamaterial structure was adopted as element '0', while Design 1, with a combination of square and circular metamaterial designs, was adopted as element '1'. Figure 5a,b demonstrates the two unit cells selected for the coding metamaterial design. All the descriptions of the unit cells are tabulated in Table 5. Since the unit cells in one-bit coding metamaterials possess 0 and \(\pi\) phase responses, the selected unit cells were based on this criterion. Meanwhile, Figure 5c illustrates the phase responses and phase differences of elements '0' and '1'. The elements have a phase response difference of 180\({}^{\circ}\) at a frequency range from 7.07 GHz to 8.00 GHz (C-band) and 14 GHz to 18 GHz (Ku-band). However, the absolute phase response of the proposed element '0' may not exhibit a zero response at a specific frequency. It will not affect any physics because the phase can be normalized to zero. Although the phase-response properties have been seen in specific ranges, which were from 7.07 GHz to 8.00 GHz and 14 GHz to 18 GHz, this work used a frequency range from 0 to 18 GHz to analyse the alterations in the responses. The phase response properties were also validated by utilizing High-Frequency Structure Simulator (HFSS) software. The phase-response properties from the HFSS software revealed almost similar results compared to the CST  
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Designs** & **FR-4** & **Rogers RT6002** & **Rogers RO3006** \\ \hline Design 1 & & dB(m\({}^{\star}\)2) & dB(m\({}^{\star}\)2) & dB(m\({}^{\star}\)2) \\ \hline Design 2 & & -51.7 & -53 & -56.6 \\ \hline Design 3 & & -62.6 & -63.9 & -53.5 \\ \hline Design 4  
software, as illustrated in Figure 5c. Therefore, the monostatic RCS calculation for the proposed coding metamaterials is suitable to be applied to C- and Ku-band applications. However, the reflection coefficient results of both elements are demonstrated in Figure 5d. Element '1' exhibited peak points at approximately two frequency ranges: from 5.7 GHz to 8.0 GHz and 11.9 GHz to 15.9 GHz. Moreover, the first resonance curve fell only in the C-band, while the second curve manifested in two frequency bands--likely X- and Ku-bands. The element '0' exhibited an almost straight line near 0 dB for the whole frequency range. Note that the phase response of element '1' had a 180\({}^{\circ}\) phase shift when the first reflection-coefficient resonance moved to a second resonance.  
Figure 5: One-bit coding metamaterials with: (**a**) element ‘0’; (**b**) element ‘1’; (**c**) phase responses; and (**d**) S11 of both elements.
## 9 Optimization
### Reservoir Management and Production Optimization  
The case by [PERSON] et al. is used to showcase production optimization in Vaca Muerta. They employed a multidisciplinary approach to enhance oil production through reservoir simulation. The team initially examined the disparate production rates among three vertical wells in Vaca Muerta's shale deposits. An integrated methodology, incorporating history matching in reservoir simulation, was then applied to pinpoint the factors contributing to these production variances. Production determinants were classified into three categories: reservoir quality (RQ), completion quality (CQ), and additional variables influenced by human intervention, such as pore pressure, matrix permeability, and total organic carbon, among others.  
The study concluded that relying solely on production data is inadequate for comprehending the variances between different exploration zones, given the multiple factors like geological and fluid inconsistencies and completion methods. The research focused on a 570-square-kilometer region, ranging from volatile oil zones in the west to more stable black oil regions in the east. Despite Well 3 having the least favorable hydrocarbon-filled porosity, it exhibited superior production rates.  
The findings underscore the unique challenges in Vaca Muerta, including intricate stress patterns, thermal maturity variations, and formation water production. The study also emphasized the difficulty in determining the mobility of hydrocarbon-filled porosity, particularly in zones rich in liquid hydrocarbons.