esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Energy Cost of the Nitrogen Fixation Process in the Multi-Pin System with and without Water
This can only be explained by the energy losses during H\({}_{2}\)O dissociation and/or evaporation and means that the extended Zeldovich mechanism Reactions (1)-(3) over the liquid electrode is less efficient compared to the  
Figure 8: (**a**) Energy cost and (**b**) production rate of the NF product in the Me–Me and Me–L configurations for different gas flow rates. Zeldovich mechanism Reactions (1) and (2) in nonequilibrium plasmas. Moreover, an elevated gas temperature of plasma streamers in the case of the Me-L system (\(\Delta\)T\({}_{\rm g}\)\(\approx\) 400 K) is also a good representative of the additional energy losses on gas heating. It is noteworthy that a similar reduced energy efficiency of plasma-based nitrogen fixation in the presence of water was also previously reported by [PERSON] et al. (20 \(\pm\) 6%) [23]. However, the latter investigation was dedicated to a single-pin (lab-scale) setup, operating within restricted plasma power (<20 W) and gas flow rate (<3 L min\({}^{-1}\)) ranges. Nevertheless, the similarity in occurring EC reductions clearly shows that the use of a liquid electrode does not improve the performance of NF process. To summarize, plasma-assisted NF was studied with (Me-L) and without (Me-Me) the presence of water in a multi-pin electrode system in this work. The comparison between both plasma configurations showed that the NF process is very sensitive to the plasma operational conditions, namely, the plasma frequency and the gas residence time. An increase in the appearance of plasma events per second (approximately <100 Hz) can trigger reverse nitrogen fixation processes, leading to the \"back\" formation of feedstock gas components (N\({}_{2}\) and O\({}_{2}\)). On the other hand, a significantly high plasma frequency (>100 Hz) can promote a thermal effect, increasing the reaction rates of the occurring chemical processes and making thermal-driven nitrogen fixation more dominant. In addition, using a higher gas flow rate increases the production rate of nitrogen-fixed products. Finally, the presence of water in the plasma zone has a negative effect on plasma-assisted nitrogen fixation, resulting in an elevated energy cost. However, in a hypothetical process of nitrogen fixation and subsequent generation of fertilizers, the plasma-generated NOx would have to be absorbed by an aqueous scrubber placed in line with a plasma reactor. In this way, NOx can accumulate in the liquid and be transferred to the final fertilizer.
## 3 Analysis of Experimental Results
### Exterior Erosion Characteristics  
All concrete prismoids in this section were examined to determine the degree of damage after the exposure to the sulfate solution was prolonged for up to four months (120 cycles of wetting and drying).  
Figure 3 depicts how the RCASCC changed following erosion. Figure 3a,b demonstrate that the amount of white material on the specimen's surface increased, and mortar and aggregate spalled on the prism's side and corners [9]. The graphs in Figure 3a-e demonstrate that \(\text{SO}_{4}\)\({}^{2}\)- erosion increased with the RCA substitution rate. The most significant damage was found in RCASS, where RCA entirely replaced NCA. The mortar layer's topmost portion had entirely peeled off, there were visible cracks, and the aggregate exposure issue was critical. Figure 2 shows that the self-compacting concrete with more than 50% RCA substitution was prone to \(\text{SO}_{4}\)\({}^{2}\)- erosion to the greatest extent. This finding was primarily supported by the most obvious cracking and spalling of the specimens as a whole, as well as the most erosion products on the specimens' surfaces [29].  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Type** & **\(\boldsymbol{\gamma}\)df\({}_{\text{ct}}\) (Mpa)** & **28 df\({}_{\text{ct}}\) (Mpa)** & **Elastic Modulus/Mpa** \\ \hline RCASCC-0 & 24.1 & 32.1 & 29.8 \\ RCASCC-25 & 24.2 & 31.9 & 29.3 \\ RCASCC-50 & 27.9 & 35.9 & 28.9 \\ RCASCC-75 & 19.2 & 27.8 & 27.6 \\ RCASCC-100 & 17.5 & 24.6 & 26.6 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Compressive strength.  
Figure 2: Compressive strength with different RCA replacement ratios and 7/28-day strength ratio.
## 5 Discussion
### Limitations  
Comparing with time series MODIS data and multi-temporal Landsat data, the reconstructed daily 30 m data showed a better performance in phenology extracting and crop mapping. However, it also has limitations. First, as mentioned in Section 5.2, it requires a lot of data processing work. Second, although the STDFA can generate synthetic 30 m data with a high accuracy, the simulated 30 m data also showed a small difference with the actual image. This problem can be addressed by launching new satellites to acquire real high spatial and temporal resolution data. Third, the environmental factors (e.g., precipitation, temperature, soil type, soil moisture) or management practices (e.g., souring date, fertilization) were not considered in the phenology monitoring and crops mapping. This should be an important work for the future studies.
# Nonlinear Metasurface for Structured Light with Tunable Orbital Angular Momentum
## 1 Introduction  
Structured light and, in particular, beams carrying orbital angular momentum (OAM) have been shown to enable and expand a plethora of photonic applications from optical trapping and manipulation, to astronomy and light filamentation [1]. Moreover, the OAM of light can be used as an alternate degree of freedom for expanding the capacity of communication channels [2; 3; 4; 5; 6]. Many of these systems require the development of dynamically reconfigurable and high-power OAM beams. Usually, the OAM beams are generated using bulk optical devices such as spiral phase plates (SPPs) and spatial light modulators (SLMs) [7]. However, an SPP is only suitable to generate an OAM beam with fixed topological charge for a designed wavelength. SLMs, dynamically controlled by computers, are able to generate tunable OAM beams with high intensities [8] but are limited by their resolution, bulky dimensions, and the switching speed. For nonlinear applications requiring dynamically changing topological charge of light together with high intensities [9], a tunable OAM metasurface-beam converter may enable new opportunities. To date, the realization of tunable OAMbeam converters that can be used in high-power applications with ultrafast switching speed and can be incorporated in micro-scale systems remains a grand challenge.  
Here, we propose and demonstrate a nonlinear metasurface based on chalcogenide glass (ChG) to generate reconfigurable topological charge, depending on the input intensity, and able to generate OAM beam with an input intensity higher than 4 GW/cm\({}^{2}\). Photonic metasurfaces attracted significant attention owing to their compact size, flat topology, and compatibility with existing integrated-optics fabrication methods [10; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23; 24; 25; 26; 27; 28; 29; 30; 31]. Recently, we have demonstrated the first step toward the realization of input-intensity-dependent optical metasurfaces capable of converting a beam with no OAM into an OAM-carrying beam in the near infrared range [32]. Here, we describe a nonlinear metasurface with the capability of switching between two opposite topological charges of OAM beams depending the intensity of the input beam.  
The proposed metasurface beam converter consisted of an array of nano-blocks made of As\({}_{2}\)S\({}_{3}\) ChG with high refractive index, low absorption and a very good nonlinear figure of merit in both the near-infrared and the mid-wave infrared spectral bands [33; 34; 35]. In addition, the fabrication procedure was a single-step electron-beam lithography since As\({}_{2}\)S\({}_{3}\) is sensitive to electron beam exposure [36].
# An Improved Routing Approach for Enhancing QoS Performance for D2D Communication in B5G Networks
## 4 Results and Discussion
### Packet Delivery Ratio  
The proposed MBLCR approach provides higher PDR value (80%) in all different device speed scenarios, which proves its performance in providing robust and reliable data transmission in wireless networks. Due to the device movement in the network, the network topology is changed in an unpredictable manner, which inconsistently causes the links to be broken and reconnected in the established network. In this situation, the MBLCR avoids forwarding the data packets to an unstable link that has a higher probability of being broken. Moreover, the MBLCR prevents devices with a high displacement, which leads to of the maximization of the PDR value for data transmission when establishing routes. The MBLCR scheme exploits the ETX value that minimizes the number of relay devices for the route computational mechanism, which mitigates the number of dropped packets in the wireless network. It can be observed from Figure 7 that the MBLCR obtains a higher PDR value compared to its counterpart routing schemes. The average values in high device speed scenarios are enhanced by 28.24%, 21.54% and 12.27% in comparison to the MP-OLSRv2, MEQSA-OLSRv2 and EMBLR schemes.  
Figure 6: End-to-end delay with various devices speeds.  
Figure 7: Packet delivery ratio with various device speeds.
# Multi-Sensor Face Registration Based on Global and Local Structures
## 4 Experimental Results
### Registration on Real Face Images of Self-Built Multi-Spectral Database  
In order to demonstrate the performance of our registration in the high-resolution multi-spectral imaging system, we built a four degree of freedom (DOF) pan and tilt head vision platform for multispectral database acquisition, which can be seen in Figure 6.  
This 4-DOF pan and tilt head vision platform can realize up-down pitch movement and left-right yaw movement, respectively. Moreover, a Belgium Raven-640-Analog thermal infrared camera with 10 mm short lens is used to acquire a 74\({}^{\circ}\)\(\times\) 59\({}^{\circ}\) field of view (FOV) infrared image (Figure 6(a) left), while a DAHENG MER-310-12 UC color camera with an Optotune EL-10-30-Ci variable-focus liquid lens is used to acquire a 28\({}^{\circ}\)\(\times\) 22\({}^{\circ}\) FOV visible image (Figure 6(a) right). Meanwhile, a visible image is always taken simultaneously with the infrared image to form a multi-spectral image pair, and the visible and infrared images are both compressed into 640 \(\times\) 480 pixels. The multi-spectral vision equipment and image acquisition scenario is shown in Figure 6(b). The self-built multi-spectral database is composed of 20 different individuals involving different illumination conditions and pose variations.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Methods**} & \multicolumn{4}{c}{**The Average Registration Errors**} \\ \cline{2-5}  & **[PERSON]** & **[PERSON]** & **[PERSON]** & **[PERSON]** \\ \hline CPD [19] & 3.04 & 2.58 & 2.73 & 2.35 \\ SMM [25] & 2.88 & 2.40 & 2.56 & 2.13 \\ RGF [20] & 2.40 & 2.24 & 2.24 & 1.92 \\ FR-GLS & 2.25 & 2.06 & 1.99 & 1.78 \\ \hline \hline \end{tabular}
\end{table}
Table 1: The average registration errors comparison of CPD, SMM, RGF and our FR-GLS method on four typical individuals in Figure 4.  
Figure 6: 4-DOF pan and tilt head vision platform for multi-spectral database acquisition: (**a**) Design mechanical model of vision platform; (**b**) Image acquisition scenario.  
In addition, for each individual, the sampled images are captured from 13 different angles (tilt head from \(-90^{\circ}\) to \(+90^{\circ}\)) and two illumination conditions (dark and light).
# Hybrid Dual-Polarization Synthetic Aperture Radar
## 2 Provenance
### Stokes Parameters  
The data resulting from a backscattered EM field as observed in the outputs of the pair of orthogonally-polarized receivers may be represented as a \(2\times 2\) coherence matrix or covariance matrix [9]. Those data are comprised of signal amplitudes, and the cross-products of their (complex) amplitudes. Each of the Stokes parameters (see Appendix C.2) is an elementary combination of two numbers drawn from the elements of one of those matrices. The resulting set of four real numbers, when evaluated at each pixel location in the multi-look SAR image domain, comprises a user-friendly form of the fundamental output data. Stokes parameter-based analysis methodology has a long and deep heritage in many fields (e.g., quantum physics, meteorology, crystallography, and radio astronomy).  
Each of the Stokes parameters is an averaged quantity. The first Stokes parameter indicates the total intensity of the radar's backscattered field, which is the sum of the output powers of the two orthogonally-polarized receivers. That total power includes the radar's additive noise along with the polarized and randomly polarized constituents of the backscattered signal.  
The other three parameters describe the properties of the polarized portion of the field. They have no additive noise component. The value of one of those Stokes parameters is the difference between the output powers of the two receive channels, so the averaged additive noise in the two channels cancels out. The other two Stokes parameters are derived from complex cross-products of the receivers' outputs, for which averaging also cancels out the additive noise contributions. In sum, additive receiver noise is random (modelled as a Gaussian process). Since it is not polarized, it cannot be a constituent in the three Stokes parameters that describe the polarized portion of the observed EM field.  
No matter the receivers' polarization basis, the fourth parameter is the key to the ellipticity of the backscattered field, including the degree of ellipticity (ranging from linear to perfect circularity), and the rotational direction of its polarization vector (left or right). The second and third parameters together describe the degree of linearity of the polarized portion of the field, and the orientation of the dominant linear component. The degree of polarization is defined by the square root of the sum of the last three of the parameters each squared, divided by the first Stokes parameter.
# Numerical Study of Viscoplastic Flows Using a Multigrid Initialization Algorithm
## 2 Numerical Methodology
### Multigrid Procedure
#### 2.5.2 Multigrid Cycles  
In our simple example we have illustrated the main concepts of the multigrid methods. In practical CFD calculations, the multigrid transfer process is more sophisticated and different cycles of coarsening and refinement are used with special schedules of restriction and prolongation at different refinement levels. Common choices of multigrid cycles are the so-called V- and W-cycles, which are illustrated in Figure 3.  
The simple V-cycle shown in Figure 3a consists of two legs. The calculation starts at the finer level. Iterations at any level are called relaxation. After a few relaxation sweeps on the finer level, the residuals are restricted to the next coarse level, and after relaxation on that level, the residuals are passed on to the next coarse level and so on until the coarsest level is reached. After final relaxation on the coarsest level, the prolongation steps are performed on the upward leg of the V-cycle until the finer level is reached. In the W-cycle, additional restriction and prolongation sweeps are used at coarser levels to obtain a better reduction of long-wavelength errors. A typical pattern is illustrated in Figure 3b.  
In general, the multigrid idea requires more than two grids, otherwise its remarkable power would be missed. The lowest frequency errors need to be reduced on a very coarse grid (8 h spacing or higher ) to decay quickly. The two-grid v-cycle can be extended in a natural way to more grids, going down to coarser grids (2 h, 4 h, 8 h,...). As the coarse grid iterations are much faster than fine grid iterations, efficiency may be improved by the decision to switch from one grid to another on the rate of convergence through the combination of V-W cycles. Therefore, the W-cycle, which stays on coarse grids longer, is generally superior to a V-cycle and is used in the present work. Let it be noted that the optimum choice of parameters remains problem-dependent, but their effect on performance is not as dramatic as for the single-grid method.
## 2 Results
### Optimization of the Extraction Method
#### 2.1.3 Extraction Temperature  
Different extracting temperatures (30, 40, 50, 60, and 70 \({}^{\circ}\)C) were evaluated in the HS-SPME parameter screening experiment (Figure 1C). The results showed that the peak area of volatile compounds increased first and then decreased, then reached the highest when extracting temperature was 50 \({}^{\circ}\)C. Thus, 50 \({}^{\circ}\)C was found to be the suitable extraction temperature. In general, heat provides energy for analyte molecules to overcome energy barriers that tie it to the matrix, thus facilitating the release of analytes into the headspace. However, it can adversely affect adsorption of analytes by coating due to the decrease in partition coefficients [22].
## 2 Literature Review
### Data Analysis  
An initial analysis was conducted using AMOS and SPSS software to show whether the data could answer the study objectives. Structural equation modeling (SEM) was also applied because it allows simultaneous analysis of many variables needed and tests the relationship with factor analysis [71]. Confirmatory factor analysis (CFA) testing was first performed to confirm the variables' validity and reliability, which estimated the instrument's internal consistency before processing data using SEM [72]. The Cronbach alpha value must exceed 0.6 to meet the convergent validity criteria [73]. Second, the factor loadings of observed items must exceed 0.5 [74]. Furthermore, the overall fit model in SEM is usually assessed based on the goodness-of-fit indices (GFI) value exceeding 0.90. The parsimonious goodness-of-fit index (PGFI) must exceed 0.50 [73]. RMR must be smaller than 0.08, including the minimum Chi-square value (CMIN) and the ratio of Chi-square to degrees of freedom (where 2/df must be less than 5.0) [75]. The hypothetical model is supported when all the value requirements for SEM are met.
# Challenges in Physical Layer Security for Visible Light Communication Systems
## 4 Future Directions
Hence, both technologies are likely to be combined in a single device to meet the demand for future wireless applications. In this sense, the combination of VLC and RF may significantly enhance secrecy performances by exploiting the inherently different characteristics of RF and VLC channels. More specifically, VLC may promise a very high secrecy capacity when employing an appropriate transmission scheme, while it is entirely subject to a favorable location of a UE concerning an ED. On the other hand, regardless of the receiver locations, RF may not ensure a required secrecy capacity in indoor environments due to shadowing and multipath fading, while it can facilitate uncorrelated transmissions. Utilizing the intrinsically different VLC and RF channels may enable finding an optimal solution that can always provide consumers with an adequate secrecy performance. For example, based on a given communication configuration, it would be possible to make an optimal choice between transmitting a secrecy key by using a keyless PLS scheme of VLC and generating and distributing a secret key by utilizing the distinct channel characteristics of the transmitter's and UE's reciprocal RF channel.
## 4 Discussion
### Study Limitations  
The test room was a training room, which was not operated and cleaned as regularly as typical process rooms in industry. Thus, the cleanroom status and its individual microbiome could still have been different, though cleaning and disinfection efforts were made prior to test start.  
This study provides results from one series of different test setups in one room only. Thus, the test results cannot be universally transferred to other, real-world manufacturing sites. However, they give a strong motivation to conduct further, long-term experimental studies with direct comparison of MCPs, CFUs and particles in a real operational cleanroom within the pharmaceutical industry. This should provide sufficient data to provide clear recommendations for reducing ACRs and MCP alert limits.  
This study focused only on numbers of MCPs detected by the BFPC, and CFUs found on agar samples, without identification of collected microbes (bacteria and fungi). As the regulatory limits refer to absolute numbers of any CFU the specific type of bacteria or fungi is not relevant. However, in real pharmaceutical operations an identification of the contaminating species should be performed in any case of deviation.
## 3 Results and Discussions
### Stiffness Degradation  
Figure 10 illustrates that with the increase in horizontal displacement, the stiffness begins to decrease. After TestA-2 and TestA-6 enter the plastic state, the stiffness degradation is not more obvious than that in the elastic stage. Figure 10 shows that with increasing horizontal loading points, the relationship curves between secant stiffness and displacement of corresponding models (TestA-7 and TestA-8) are smoother and closer to the displacement axis than that of TestA-2 and TestA-6. The lateral stiffness of the pier decreases very slowly in the latter stage of loading. Under the four loading modes, the stiffness attenuations are more than 92%. It can be seen from Figure 10,c that the horizontal lateral loading mode has no obvious impact on the stiffness degradation at the local position. Comparing the two figures, it can be concluded that under the horizontal loading mode of five points, a tremendous difference exists in the stiffness degradation at Node8 and Node18, which is due to the close distance between the two loading points corresponding to the top horizontal load of Node8. Thus, the pier body is squeezed and warped and the force and displacement at some positions are suddenly changed. The loading point at the top  
Figure 9: Accumulative energy dissipation curves: (**a**) Pier top; (**b**) Node8; (**c**) Node18.  
and middle of the pier corresponding to Node18 is far away from the edge load loading point, so the deformation and stress of the wall pier body is not being greatly affected. The stiffness degradation range of all the models is more than 94%, which is only about 2% different from the global stiffness degradation.