esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction  
For the potential powerful application of vortex EM waves carrying orbital angular momentum (OAM) in future communication systems, more and more scholars have not only focused on their generation [1, 2, 3] and transmission [4, 5], but also on the scattering [6, 7, 8] and radar imaging [9, 10, 11, 12] of vortex EM waves. The generation technology of vortex EM waves has matured. As a common approach, [PERSON] et al. proposed a reconfigurable graphene reflectarray to generate the vortex EM wave at THz [1]. Based on the leaky wave antenna [3], [PERSON] et al. used a substrate integrated waveguide to realize a circular-polarized vortex wave. With the increase in vortex EM waves, such as metasurface antennas [13, 14], multi-mode antennas [15], etc., the target scattering characteristics of vortex EM waves have also gained more and more attention in recent years.  
In [7], [PERSON] et al. proposed the interaction between vortex EM waves and electrically large sphere/cones by using the PO algorithm. Similarly, [PERSON] et al. investigated the scattering of Laguerre-Gaussian (LG) beams on electrically large-scaled targets by means of a parallel-processing PO [16]. However, the vector properties of the Bessel scattered field have not yet been revealed due to the application of the traditional Stratton-Chu integral. To address this problem, [PERSON] et al. applied a combination of ASE and PO to analyze the scattering near-field characteristic of the targets irradiated by the Bessel EM wave [17]. Meanwhile, [PERSON] used the same method to calculate the far-field RCS [18] of Bessel vortex EM waves upon the coated targets. Nevertheless, to the best of our knowledge, few experimental measurements of vortex EM scattering have been reported. Experiments on the reflection and refraction of vortex EM waves were carried out in [5]. [PERSON] et al. presented a target detection method [19] of vortex EM waves and verified the corresponding theory through experiments. As radar identification usually adopts the forward scattering signals provided by the moving targets crossing the baseline between the transmitter and receiver, forward scattering has vital significance in increasing the target RCS, and is quite advantageous for use in counter stealth detection. However, the bistatic scattering measurements of vortex EM waves are rarely reported.  
In this paper, the far-field bistatic RCS of Bessel waves on several classical standard targets were obtained by near-far-field conversion. The rest of this paper is organized as follows. In Section 2, the integrated PO method is presented. In Section 3, the results and analysis of measured scattering are discussed. Finally, our conclusions are drawn in Section 4.
# Experimental Study on Small-Strain Shear Modulus of Unsaturated Sility-Fine Sand
## 4 Shear Modulus of Sand with Different Saturations
### The Effect of Saturation on Dynamic Shear Modulus \(G\)  
Using the previously developed BE-RC test device, the dynamic shear modulus \(G\) of the silty-fine sand in the whole small-strain range in the dehumidification stress path was obtained by controlling different net stresses and matrix suction states, as shown in Figure 8. Figure 8 shows the variation curve for shear modulus \(G\) with the shear strain for sand at different saturations, where the scattered points are the measured values and the solid lines are the fitted values using the Hardin-Drnevich model [6].  
Figure 7: Prediction SWCC curve of VG model.  
Figure 8: _Cont._  
As shown in Figure 8, comparing the shear modulus curves of sand with the same saturation at different net stress levels, it can be found that the trend of decay in the dynamic shear modulus varies in the whole small-strain interval (\(10^{-6}\)-\(10^{-3}\)). When the strain is in a range of \(10^{-6}\)-\(10^{-5}\), the sand is basically in the linear elastic stage and the change in the shear modulus is not significant; when the strain is in a range of \(10^{-5}\)-\(10^{-3}\), the sand is in the elastoplastic stage and the shear modulus shows an obvious and rapid decrease; when the shear strain exceeds \(10^{-3}\), the sand is in the plastic stage and the shear modulus tends to level off [34]. The higher the initial net stress level, the larger the dynamic shear modulus \(G\) and the more significant the decay with the developing strain. Under the dehumidification path, the shear modulus \(G\) corresponding to the same strain does not vary monotonically with saturation. The maximum shear modulus \(G_{max}\) varies less with decreasing saturation at a higher saturation (\(S_{r}\geq 0.4\)). With a further decrease in saturation, the \(G_{max}\) increases gradually and reaches a peak at the saturation near 17%. This illustrates that: the matrix suction caused by saturation variation has a weak effect on the dynamic shear modulus of the sand at a higher saturation level; however, as the saturation decreases, the matrix suction increases and the ability of the sand to resist shear deformation increases, resulting in a slow increase in shear modulus \(G\). However, a peak exists at a certain saturation.
## 6 Discussion  
### Two Improved Algorithms  
#### 6.1.1 Multiple Links  
In this case, more than one link is used. We choose one of these spacecrafts as the chief spacecraft, and the others as the deputy spacecraft. Using multi-spacecraft constellation, the convergence region of the problem can be extended.  
Figure 8 shows an example (test 5). It is a constellation with one chief spacecraft and eight deputy spacecrafts. In this case, we put the deputy spacecraft in different types of orbits to obtain stronger signals from the non-spherical gravity. By our calculation, the spacecraft of prograde orbit do not collide with the asteroid for a 50(T) arc length. Thus, we  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameter** & **Initial Estimate** & **Test 4** \\ \hline C\({}_{20}\) & \(-5\times 10^{-2}\) & \(-5.3959\times 10^{-2}\) \\ \hline C\({}_{22}\) & \(9\times 10^{-2}\) & \(7.5978\times 10^{-2}\) \\ \hline
**Initial position error of** & & \\
**Satellite 1** & 50 m & 47.71 m \\ \hline
**Initial position error of** & & \\
**Satellite 2** & 50 m & 27.67 m \\ \hline
**RMS** & 39.9917 & 5.5752 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Recovery result of test 4.  
Figure 7: Residual in the observation data (**left**) and norm of the position error of the determined orbit from the true one (**right**) (test 4 with large errors in the initial estimate).  
put the chief spacecraft in the polar orbit (the black trajectory in the right picture of Figure 8, the orbital elements are the same as \(\sigma_{1}\) in Section 3.2). Four of the deputy spacecrafts are in the prograde orbits (the blue trajectories) and four of them are in the polar orbits (the red trajectories). The initial position error is set as 50 m (the same as test 4) randomly along all three directions of all the spacecraft. For the initial estimation, an error of 50 m is randomly added in all the three directions to the position vector of the chief and all of the deputy, respectively. Initial estimate of the gravity-field coefficients is \(C_{20}=-5\times 10^{-2}\) and \(C_{22}=9\times 10^{-2}\) (Table 6). Our test shows that the complete-inverse problem converges well in this example.  
Unlike test 4, the result after iteration is better than the initial estimate, so the iteration process has converged. Most of the residuals are less than 10 m and position errors of estimated orbits are less than 50 m. In addition, the value of \(C_{22}\) is much better than test 4. The error is only 0.15%. This improvement in this result is significant. As a feasibility analysis, test 5 is enough. It can prove that more links can extend the convergence region.
## 7 Concluding Remarks  
This paper has proposed a novel and challenging new measurement technique as a means of delivering high quality measurements of UTLS quantities, particularly water vapour which is a crucial atmospheric variable and poorly constrained in climate models. The key features of an observing system for UTLS water vapour are sensitivity to low concentrations and high vertical resolution, both of which an active limb sounding system has the potential to deliver. The technical challenges of such a mission have been acknowledged and are significant, and the concept presented here is a first attempt to address these.  
Although the results from this preliminary study are very encouraging (and may prove to be even more so after appropriate wavelengths optimization and systems trade-offs studies), it is difficult to make reliable predictions with respect to the final horizontal and vertical resolutions that can be achieved with the system after all sources of noise, and primarily, atmospheric refraction, ray bending and scintillation, have been taken into consideration. A detailed instrument end-to-end performance simulation would be required, not only to accurately model the forward propagation of the signal and receiver SNR but also to include the performance of potential retrieval algorithms, which will determine the number of shots that have to be averaged to achieve errors and biases within the required limits. The data retrieval simulation will also need to incorporate the synergistic combination of data from both limb and nadir measurements.  
In addition to the unprecedented water vapour information, the system generates collocated information on cloud properties and particles at cloud-resolving scales. This will provide valuable insights into aerosol-cloud-climate interaction processes, especially for the poorly understood ice nuclei and cirrus clouds, complementing the planned EarthCARE mission, and building on the CALIPSO-CloudSat formation within the A-train. Adding to already available aerosol LiDARs in orbit, the mission's UTLS and stratospheric aerosol detection capabilities will continue to be useful for the monitoring of potential intrusions of particles into upper air layers. This would be of particular use during volcanic eruptions or the possible deliberate introduction of stratospheric aerosol for solar radiation management as a geoengineering response to climate change, should this idea ever be explored seriously.
## 4 Discussion  
### Formation Mechanism of the Main Fractures  
It is important to understand the formation mechanism of the main fractures which is beneficial to the prediction of fracture propagation. By observing the fracture morphologies (Figure 6), three types of main fractures have been found in the experiments: longitudinal fracture, transverse fracture, and oblique fracture. The formation mechanisms of the three types of main fractures are different.  
[PERSON] et al. [23] simulated the stress field of the hollow cylindrical shale fractured by SC-CO\({}_{2}\) jet, and they found that the fractures could easily generate at three locations: the root, the middle, and the tip of perforation (Figure 15). Our results are well matched with  
Figure 14: The fracturing times of specimens in group A and B.  
Figure 13: Typical experimental results of strain curve during fracturing. (**a**) Hard rock (specimen A1) and (**b**) soft rock (specimen B2).  
the simulation results that the transverse fractures initiate from the tip of perforation, and the longitudinal and oblique fractures initiate from the middle of perforation. The casings of the specimens were separated from artificial sandstones in the experiments, due to the fractures propagating at the root of perforation and destroying the cement between the casing and artificial sandstone.  
[PERSON] et al. [12] conducted the SC-CO\({}_{2}\) jet fracturing experiments on the organic glasses, and three types of fractures were found: surface fracture, longitudinal fracture, and transverse fracture (Figure 16). The surface fracture, the longitudinal fracture, and the transverse fracture were mainly caused by SC-CO\({}_{2}\) jet flow impacting on the casing surface, the pres-surization of SC-CO\({}_{2}\) in perforation, and the stagnation pressure pressing on the tip of the perforation, respectively. The fracture initiation position in our experiments was consistent with his study.  
In our study, the longitudinal fracture was caused by the pressurization of SC-CO\({}_{2}\) in perforation. As for transverse fracture, which only occurred in hard-soft rocks and soft-hard rocks where the upper and lower layers were different, there were three factors contributing to it: the strong heterogeneity [45] at the middle of specimens, the stress concentration on the tip of perforation due to discontinuity of structure, and the stagnation pressure pressing on the tip of the perforation. The oblique fracture occurred in soft  
Figure 16: Fracture types in the experiment of [PERSON] et al. [12] (modified).  
Figure 15: (**a**) Different positions of perforation; (**b**) stress field after fracture initiation simulated by [PERSON] et al. [23].  
rocks and soft-hard rocks for which the upper layers were soft, and it was caused by the pressurization of SC-CO\({}_{2}\) in the perforation.
# Analysis of Scintillation Effects on Free Space Optical Communication Links in South Africa
## 3 Modified Rytov Theory for Gaussian Beam Waves  
Fluctuations in the wind speed and atmospheric temperature generate unstable air masses that eventually break up into turbulent eddies or cells of varying scale sizes with constant \(C_{n}^{2}\). These inhomogeneities vary in size from macroscale to microscale, and are of different densities [12]. As the Gaussian beams transverse the free space channel, these zones of turbulent air motion act as lenses that scatter the beams off their intended paths. The microscale eddies \(l_{o}\), also known as the inner scale of turbulence, are approximately 3 to 10 mm near the ground. The macroscale eddies \(L_{o}\), also referred to as the outer scale of turbulence, are in the range of several metres above the ground level. Optical turbulence is primarily defined by \(C_{n}^{2}\), \(l_{o}\), and \(L_{o}\)[43].
## 3 Materials and Methods
### Determination of Object Position  
The mathematical apparatus for determining the position of an object includes geometric transformations such as translation, rotation, and others. Geometric transformations in 3D space can be effectively represented using transformation matrices. These matrices allow the execution of linear geometric transformations of points in space, projecting them from the original position (\(P\)) to the new one (\(P^{\prime}\)). The main advantage of transformation matrices is their compact representation in a homogeneous form. Homogeneous coordinates enable the expression of different types of transformations (translation, rotation, scaling, etc.) using a single matrix \(A\)  
\[P=\begin{pmatrix}x\\ y\\ z\\ w\end{pmatrix}=A\cdot P=\begin{pmatrix}a_{11}&a_{12}&a_{13}&a_{14}\\ a_{21}&a_{22}&a_{23}&a_{24}\\ a_{31}&a_{32}&a_{33}&a_{34}\\ a_{41}&a_{42}&a_{43}&a_{44}\end{pmatrix}\cdot\begin{pmatrix}x\\ y\\ z\\ w\end{pmatrix} \tag{1}\]  
Translation matrices allow for the shifting of a point in 3D space by a translation vector \(\vec{t}=(t_{x},t_{y},t_{z})\), where \(t_{x}\), \(t_{y}\), and \(t_{z}\) are the translation components along the X, Y, and Z axes, respectively.  
\[Trans(\vec{t})=\begin{pmatrix}1&0&0&t_{x}\\ 0&1&0&t_{y}\\ 0&0&1&t_{z}\\ 0&0&0&0\end{pmatrix} \tag{2}\]  
Figure 5: Connection of cameras and the ABB Yumi robot with the PC for controlling and monitoring the workspace.  
A rotation matrix is used to rotate a point around an axis in 3D space.  
\[Rot_{x}(\alpha)=\begin{pmatrix}1&0&0&0\\ 0&\cos\alpha&-\sin\alpha&0\\ 0&\sin\alpha&\cos\alpha&0\\ 0&0&0&1\end{pmatrix} \tag{3}\]  
\[Rot_{y}(\beta)=\begin{pmatrix}\cos\beta&0&\sin\beta&0\\ 0&1&0&0\\ -\sin\beta&0&\cos\beta&0\\ 0&0&0&1\end{pmatrix} \tag{4}\]  
\[Rot_{z}(\gamma)=\begin{pmatrix}\cos\gamma&-\sin\gamma&0&0\\ \sin\gamma&\cos\gamma&0&0\\ 0&0&1&0\\ 0&0&0&1\end{pmatrix} \tag{5}\]  
The base transformation is a critical operation that allows the position and orientation of a point to be converted from one coordinate system to another. The key tool for performing a base transformation is the transformation matrix \(H_{10}\), also known as the coordinate transformation matrix. This matrix represents the relationship between two coordinate systems: the original coordinate system (0) from which the point is being transformed and the target coordinate system (1) to which the point is being transformed.  
\[H_{10}=\begin{pmatrix}R_{10}&T_{10}\\ 0&1\end{pmatrix} \tag{6}\]  
The matrix \(R_{10}\) is a rotation matrix that represents the rotation between coordinate systems. Similarly, the matrix \(T_{10}\) is a translation matrix that represents the displacement between coordinate systems [53; 54]. The calculation of the position and orientation of point \(P_{1}\) is, thus:  
\[P_{1}=H_{10}\cdot P_{0} \tag{7}\]
## 2 Decoupling Techniques (DTs) in Ultra-Wideband MIMO Antennas (UMAs)
### Defected Ground Structure (DGS)  
In this DT, by introducing various types of slits/slots in the ground surface, isolation is improved. This expands the path of the current to reduce the first resonance frequency and suppresses the surface currents to enhance isolation. In [62], the AE containing a T-shaped stub was connected to a rectangular patch for bandwidth enhancement, as presented in Figure 6a. The AEs were placed orthogonally to each other. Also, the antenna contained two open slots in the ground, which were located perpendicularly to each other to achieve high isolation. To further enhance the isolation between AEs, a narrow rectangular slot with a length of \(\lambda_{g}/4\) was cut into the ground surface. In reference [63], a Vivaldi MIMO antenna was presented with a modified ground surface and two microstrip line feedings, as shown in Figure 6b. By adding a T-slot in the ground, port isolation was significantly increased. By adding two SRRs of different sizes, dual notched bands were obtained to filter the interference of WLAN and satellite-based X-band. In reference [64], the antenna consisted of dual CPW-fed V-like parallel and symmetric radiators, as shown in Figure 6c. The T-slot was added on the ground plane to enhance isolation and increase the bandwidth. The radiator shape had a smooth transition of currents from the CPW feed line to the radiator.
###### Abstract  
(\(-\))-\(\alpha\)-Bisabolol, a naturally occurring sesquiterpene alcohol, has been used in pharmaceuticals and cosmetics owing to its beneficial effects on inflammation and skin healing. Previously, we reported the high production of (\(-\))-\(\alpha\)-bisabolol by fed-batch fermentation using engineered _Escherichia coli_ (_E. coli_) expressing the exogenous mevalonate (MVA) pathway genes. The productivity of (\(-\))-\(\alpha\)-bisabolol must be improved before industrial application. Here, we report enhancement of initial (\(-\))-\(\alpha\)-bisabolol productivity to 3-fold higher than that observed in our previous study. We first harnessed a farnesyl pyrophosphate (FPP)-resistant mevalonate kinase 1 (MvaK1) from an archaeon _Methanosarcina mazei_ (_M. mazei_) to create a more efficient heterologous MVA pathway that produces (\(-\))-\(\alpha\)-bisabolol in the engineered _E. coli_. The resulting strain produced 1.7-fold higher (\(-\))-\(\alpha\)-bisabolol relative to the strain expressing a feedback-inhibitory MvaK1 from _Staphylococcus aureus_ (_S. aureus_). Next, to efficiently convert accumulated MVA to (\(-\))-\(\alpha\)-bisabolol, we additionally overexpressed genes involved in the lower MVA mevalonate pathway in _E. coli_ containing the entire MVA pathway genes. (\(-\))-\(\alpha\)-Bisabolol production increased by 1.8-fold with reduction of MVA accumulation, relative to the control strain. Finally, we optimized the fermentation conditions including inducer concentration, aeration and enzymatic cofactor. The strain was able to produce 8.5 g/L of (\(-\))-\(\alpha\)-bisabolol with an initial productivity of 0.12 g/L h in the optimal fed-batch fermentation. Thus, the microbial production of (\(-\))-\(\alpha\)-bisabolol would be an economically viable bioprocess for its industrial application.  
(\(-\))-\(\alpha\)-bisabolol; mevalonate (MVA); mevalonate kinase 1; _Methanosarcina mazei_; fed-batch fermentation
## 3 Results
### Temporal and Spatial Characteristics of GPP, SIF, and VIs
From Figure 7, it can be seen that there was a substantial linear association between the anomalies of SIF and GPP, with an R\({}^{2}\) value of 0.78 (\(p<0.001\)), while the R\({}^{2}\) value between the anomalies of NDVI and GPP is only 0.64 (\(p<0.001\)), and there was no significant correlation between the anomalies of SIF\({}_{\text{yield}}\) and GPP. These results further confirmed that SIF can serve as an effective indicator of plant photosynthesis, accurately capturing the spatiotemporal changes in GPP, which was consistent with previous studies [51; 52]. However, whether SIF can quantify the spatiotemporal variations in GPP induced by drought still requires further evaluation. Figure 6: Monthly anomalies of SIF, SIF\({}_{\text{yield}}\), fPAR, PAR, and APAR in the Xilingol grassland for April to October 2009.
## 4 Discussion
### CW Performance
Phosphorus removal occurs mainly due to physical-chemical processes such as precipitation, sedimentation and substrate adsorption and uptake by plants [43]. In experiment#1 PO4\({}^{3-}\) removal was observed, although with a high variability, whereas in experiment#2 PO4\({}^{3-}\) was not removed. Removal efficiency of PO4\({}^{3-}\) can depended on input concentrations [46], but also on the substrate used. PO4\({}^{3-}\) removal in CWs is generally low [43] and substrate saturation can lead to PO4\({}^{3-}\) released in effluents, showing an insufficient high capacity to bind phosphorus for a prolonged period. In the present study, in experiment#2 the substrate, although identical to that of experiment#1, probably did not adsorb this nutrient. Moreover, PO4\({}^{3-}\) can also be released by plants aboveground tissues during plant decay [43]. In fact, some plants of CWs in experiment#2 showed signs of aging during experimental period. The presence of target contaminants (NP plus OP and PCP) did not interfere in phosphorus removal. Other studies have reported an inhibitory effect in PO4\({}^{3-}\) removal due to the presence of other contaminants, namely norfloxacin [47] and ciprofloxacin [48]. Therefore, in the present study, phenolic contaminants did not affect CW performance for nutrients removal.