esa-sceva/satcom-chunk-collection huggingface dataset:
# Study of the Kinetics of Adhesive Bond Formation Using the Ultrasonic Method
## 2 Ultrasonic Testing of Materials
### Characteristics of the Study Object  
Prior to the start of the basic research, the adhesive for this study was selected. Preliminarily, the number of adhesives was limited to three different types: cyanoacrylate adhesive, polyurethane adhesive, and epoxy adhesive. These are the types of adhesives that are important in industry, including the automotive industry. Modern cyanoacrylate adhesives bond so quickly that it was not practically possible to evaluate the kinetics of the bond formation. Of the other adhesives, epoxy adhesive was chosen for testing because this adhesive crosslinked uniformly throughout the volume, which was important for ultrasonic testing. The preliminary tests showed that the speed of bonding did not depend on the size of the bond. The tests were carried out by gluing steel plates to the sheet and detaching them at every specified time interval. A view of an example specimen is shown in Figure 2, while a view of the adhesive after tearing the bonds is shown in Figure 3.  
Figure 3 clearly shows that the bonding process of the polyurethane adhesive (white color) occurs slowly and starts toward the outside of the joint. For the epoxy adhesive DP490 3M, the bonding of the adhesive occurred throughout. Joints were also made for the industrial cyanoxylate adhesive. However, it was noted that the bonding of the adhesive occurs unusually, and it is impossible to assess the kinetics of its formation. For this reason, epoxy adhesive was chosen for further research. This is a high-strength adhesive that, according to the manufacturer, achieves full strength in 7 days. Three different adhesive joints were used in this study. We used glued strips of sheet metal made of DC01 steel (Figure 4) and bonded steel discs made of 1.0503 steel (Figure 5). For the steel sheet, the surface to be bonded was only degreased, and its roughness was Ra-0.2 \(\upmu\)m. For the steel discs, the surface was sanded and degreased, and its roughness was Ra-0.2 \(\upmu\)m. For the Rayleigh wave test, the samples shown in Figure 6 were used. An additional sample was also made to test the hardness of the adhesive.  
Figure 1: Research plan for the kinetics of adhesive bond formation.  
Figure 2: An example of samples from the preliminary study (black epoxy adhesive visible DP490 SCOTCH-WELD 3M).
# Adaptive Pre/Post-Compensation of Cascade Filters in Coherent Optical Transponders
## 7 Discussions of Results and Research Findings
### Comparison of Contribution to Other Published Methods
#### 7.1.2 Requirement for a Communication Channel Between Tx and Rx  
With software-defined networks being designed, providers are moving to automated, zero-touch and zero-provisioning optical networks. Carrier-grade requirements are focused on features such as automatic rerouting and adaption of line rate based on available OSNR on the link [16]. Having said that, a backchannel between Tx and Rx will be a must in current and next-generation intelligent transponders. The feedback communication can be done using an optical service channel, if available in the network. Otherwise, since the vast majority of optical fiber deployments are duplex, a software-based feature that inserts information to communicate back to Tx as part of the frame load once every certain number of frames (based on the bandwidth of the loop) can be used. The loop bandwidth is very small therefore the overhead required is negligible compared to the capacity of the link. Since the variation of filtering effects are quasi-static (changes very slowly in time versus temperature and aging), we can capture the estimate and send it back to Tx even in the presence of propagation delay. We used 256 coefficients, each of 10 bits, required to be exchanged between Tx and Rx every 10 seconds, which adds a very small overhead to the data communicated. The challenge is that the feedback loop will not work with transponders required to support interoperability from different vendors unless the communication protocol is standardized in the Optical Internetworking Forum (OIF) body.
## 3 Synthesis of Transition-Metal-Sulfide-Based Nanomaterials
### Low-Temperature Aqueous Reactions  
A multitude of TMS has been synthesized using aqueous solutions containing a soluble sulfur source, such as CuS, FeS, and CdS. Typically, this synthesis method leads to the formation of simple sulfide nanomaterials, i.e., single metal ion-sulfide materials. These reactions may be as simple as the addition of Na\({}_{2}\)S to a solution followed by the addition of a TM salt. For example, the chemical equation below shows the reaction of copper ions with sodium sulfide in an aqueous solution:  
\[\mathrm{S^{2-}}_{\mathrm{(aq)}}+\mathrm{Cu^{2+}}_{\mathrm{(aq)}}\rightarrow \mathrm{CuS_{(s)}}. \tag{7}\]  
This synthesis method has been successful for the generation TMS with simple structures. Due to the low temperature used in the synthesis, the resultant materials from this reaction method are highly amorphous and not well characterized. Silver sulfide nanoparticles have been synthesized using this technique with precipitates sized from 40-50 nm [109]. [PERSON] has reviewed the precipitation of TMS from aqueous solutions which showed that the precipitation and formation of the TMS nanoparticles depended on several factors, specifically the pH and eH of the solutions [110]. The pH was observed to control the solution speciation of both the sulfur and the metal ions. Moreover, the low temperature aqueous phase reactions became the precursor for other synthesis techniques such as hydrothermal synthesis, which can have more control over phase and generate different phases. [PERSON] et al. used copper sulfide as a model to investigate the low-temperature aqueous solution sulfide precipitates [111]. The results from EPR and NMR showed a  
Figure 3: Crystal structures of Fe\({}_{3}\)S\({}_{4}\), Fe\({}_{7}\)S\({}_{8}\), and CuS.  
reduction of the Cu\({}^{2+}\) to Cu\({}^{+}\) by the S\({}^{2-}\), as well as the formation of Cu-S clustered rings in Cu\({}_{3}\)S\({}_{3}\) solution, which are the basic building blocks for CuS precipitation.
### Content, Contributions, and Organization of the Study  
In this paper, a mixed integer linear programming (MILP)-based mathematical modeling concept is proposed to find the optimal size of PV and ESS units for covering grid-connected smart home consumption in an economic fashion. The real measurement is performed for residential appliances considering the harmonic components caused by non-linear loads and afterwards the power consumption curve is obtained accurately. The cost function consisting of capital, investment, and maintenance of PV/ESS, is aimed to be minimized after the optimization procedure, thus satisfying the system's operational constraints. A dynamic pricing scheme is also incorporated into the methodology to determine energy transactions between home and utility grid. To the best knowledge of the Authors, this study attempts to be the first in terms of covering sizing, harmonic impact, dynamic pricing schemes implementation, and real measurements based on gathered data utilization facts in a single study within the existing literature.  
The organization of the paper is prepared as follows: Section 2 gives the mathematical background of the proposed optimization problem which is based on MILP with detailed explanations. Section 3 shows the simulation results and the conclusions with possible future studies discussed in Section 4.
## 3 Results
In addition, the results obtained in the LOS direction from ascending and descending acquisition geometries show similar deformation patterns. This suggests that vertical deformation is dominant and greater than horizontal deformation [65; 66]. However, in order to detect this situation and to determine the dominant deformation pattern in the study area to better the discussion of the analysis results, decomposition is performed using PSI measurements obtained from descending and ascending acquisition geometries. On the other hand, because the SAR satellites move in orbits close to the poles (parallel to the north-south direction) and illuminate the world with small incidence angles, the LOS direction deformation is less sensitive to north-south movements [67; 68; 69]. Therefore, in this study, the north-south movements were ignored, and displacements in the east-west directions were estimated using Equations (4) and (5), as shown in Figure 8.  
\[ \begin{bmatrix}d_{LOS}^{s_{uv}}\\ d_{LOS}^{s_{dv}}\end{bmatrix} =A \begin{bmatrix}d_{evr}\\ d_{hor}\end{bmatrix}  \tag{4}\]  
\[A= \begin{bmatrix}cos\theta_{asc}&-cos\alpha_{asc}sin\theta_{asc}\\ cos\theta_{dsc}&-cos\alpha_{dsc}sin\theta_{dsc}\end{bmatrix}  \tag{5}\]  
where \(d_{LOS}\), \(d_{evr}\), \(d_{hor}\), \(\alpha\), and \(\theta\) refer to the displacements along LOS direction, vertical displacement, horizontal displacement, incidence angle, and azimuth angle, respectively [70]. Figure 5: GACOS-based mean deformation velocity maps in the LOS direction from descending (**a**) and ascending (**b**) acquisition geometries. Standard deviation of GACOS-based mean deformation velocity map from descending (**c**) and ascending (**d**) acquisition geometries. Figure 6: Mean deformation velocity maps in the LOS direction from descending (**a**) and ascending (**b**) acquisition geometries. (**c,d**) N-S and E-W profiles of the LOS velocity from the descending geometry (blue dots) and the surface elevation (orange line). (**e,f**) N-S and E-W profiles of the LOS velocity from the ascending geometry (blue dots) and the surface elevation (orange line). Figure 7: (**a,b**) LOS direction displacement time series at selected points (1, 2 in Figure 6a) from the descending orbit. (**c,d**) LOS direction displacement time series at selected points (3, 4 in Figure 6b) from the ascending orbit. The components of the deformation show that the vertical deformation rate is between 5 and \(-15\) mm/yr, and the horizontal deformation rate is between 5 and \(-5\) mm/yr (Figure 8a,b). The vertical deformation component shows the subsidence of a peak calcer-centered region with a maximum of \(-15\) mm/yr. In addition, both the northern and southern parts of the deformed region show an eastward displacement. Regarding deformations in the east-west direction (Figure 8b), the rate of displacement is much smaller, and the maximum rate is approximately \(-5\) to \(5\) mm/yr. This shows that the deformation in the Tendurek volcano predominantly occurred in the vertical direction, and the horizontal deformation component is negligible.
## 4 Experiments
### Experimental Results  
#### Prediction Performance Comparison  
Table 3 displays the GSTGCN and all baseline models on the PeMSD4 and PeMSD7 datasets for prediction of MAE, RMSE, and MAPE of 15 min (3 steps), 30 min (6 steps), and 60 min (12 steps). As shown in the table, we observed that deep learning methods perform better than simple time series methods (ARIMA) and traditional machine learning methods (SVR), indicating that deep learning methods can model more complex traffic data. Graph-based models containing STGCN, DCRNN, Graph WaveNet, ST-MetaNet, and GSTGCN predict more accurately than SAE and SBU-LSTM. It means that the spatial topological information of the traffic data is critical to prediction performance. Compared to DCRNN, STGCN, ST-MetaNet, and Graph WaveNet, GSTGCN has a great advantage in long-term prediction with a slower error growth rate and achieves the best prediction accuracy on all metrics and both two datasets. To further verify the accuracy of our model, we compared the prediction performance of GSTGCN for the morning peak hours and weekends with that of Graph Wavenet. Based on the experimental result shown in Figure 8, we found that GSTGCN performs better  
than Graph WaveNet, which demonstrates that GSTGCN is more effective in modeling the complex spatiotemporal correlations.
# Calibration and Image Reconstruction in a Spot Scanning Detection System for Surface Defects
## 1 Introduction
However, the existing system deviations, such as the position deviation of the illuminated spot, will cause distortions and even a missing area in the reconstructed image, which will affect the detection results in many aspects and hence degrade the reliability of the system. Although there have been several studies on distortion correction [17; 18], they are mostly aimed at the optical distortion caused by imaging lenses and cameras, so they are not applicable to the situation in this paper. To address these issues, this paper develops a system calibration method based on straightness and scale constraints and an image reconstruction method based on weighted average. First, the system deviations are parameterized to model the practical scanning trace, which will be used to compute the image coordinate of each acquired intensity signal. On this basis, a calibration plate with specific defect patterns is employed as the test sample, and several constraints are established to constrain the image coordinates corresponding to these defects. Then, an optimization is implemented to minimize the constraints and hence to obtain the optimal estimate of the system deviations. This estimate is subsequently used to adjust the system and establish an accurate mapping relationship for image reconstruction. The adjusted system can perform the scan for the whole optical surface in a normal way but without any missing area. Finally, using the proposed image reconstruction method, a complete defect image with low noise and low distortion can be obtained; this will greatly improve the detection accuracy and reliability of the system. The proposed methods are applicable to any other detection systems based on spot scanning, such as those for wafers, films, and rough surfaces. The remainder of this paper is as follows. Section 2 introduces the configuration of the SS-SDES and the ideal image reconstruction and then summarizes the existing system deviations as well as their impacts. In Section 3, the modeling of practical scanning trace and the details of the proposed system calibration method and image reconstruction method are described. Section 4 shows the experiment and comparison results, and Section 5 presents a conclusion of this paper.
## 3 Results and Discussion
### SEM Analysis  
Figure 6 showed the electron micrographs of the egg yolk samples treated with ozone for 0 min, 10 min, 20 min, 30 min, and 40 min in that order. As seen from the SEM images, the control group of lyophilized egg yolk powder had larger masses and a single spatial structure. However, with the extension of ozone treatment time, the structure of the lyophilized powders in the 10 min and 20 min treatment groups gradually changed to disordered folding and the spatial network structure increased substantially. The freeze-dried egg yolk powder treated with ozone for 30 min had more pores and the structure became denser with a more uniform pore size distribution. The yolk powder structure was more disordered in the 40 min treatment group compared to the 30 min treatment group. Therefore, it could be speculated that ozone treatment improved the flexibility of egg yolk proteins and affected the conformation and interaction of proteins, which in turn drove the egg yolk powder structure towards a denser network structure. However, as the intensity of ozone treatment was further increased, some proteins of the yolk triggered aggregation behavior under the effect of excessive oxidation, resulting in aggregates that affected the structure of the yolk powder. The loose and porous network structure of egg yolk powder was thought to be closely linked to better functional properties, such as solubility [36]. In summary, moderate ozonation treatment (20 min and 30 min) obviously improved the structure of egg yolk powder and has the potential to improve the properties of egg yolk powder.  
Figure 5: Electrophograms of SDS-PAGE of egg yolk under different ozone treatment times.
# Forecast Analysis of Pollutant Emissions of Cruise Ship Routes in Western Mediterranean
## 4 Results
### Estimation of the Gas Emission Inventory
\begin{table}
\begin{tabular}{l c c c c c c} \hline \hline \multirow{2}{*}{**Cruise Route**} & \multirow{2}{*}{\begin{tabular}{c} **No. of** \\ **Connections** \\ \end{tabular} } & \multirow{2}{*}{\
\begin{tabular}{c} **Distance** \\ **(nm)** \\ \end{tabular} } & \multicolumn{5}{c}{**Emissions**} \\ \cline{4-7}  & & & **NO\({}_{\text{x}}\) (t)** & **SO\({}_{\text{2}}\) (t)** & **CO\({}_{\text{2}}\) (t)** &
\begin{tabular}{c} **Average** \\ **Share (\%)** \\ \end{tabular} \\ \hline Palma de Mallorca–Barcelona & 350 & 133 & 1262.9 & 219.6 & 72,035.4 & 4.9 \\ Livorno-Civitavecchia & 250 & 144 & 743.3 & 129.8 & 42,455.5 & 2.9 \\ Barcelona–Marseille & 194 & 185 & 888.1 & 155.8 & 49,388.5 & 3.4 \\ Ibiza–Palma de Mallorca & 125 & 116 & 373.1 & 65.1 & 21,209.0 & 1.4 \\ Valencia–Barcelona & 114 & 168 & 336.3 & 58.2 & 19,977.8 & 1.3 \\ Palma de Mallorca–Valencia & 77 & 141 & 224.0 & 38.8 & 13,665.4 & 0.9 \\ Barcelona–Valencia & 76 & 168 & 199.0 & 34.8 & 11,305.8 & 0.8 \\ Valencia–Palma de Mallorca & 76 & 141 & 219.7 & 38.0 & 13,425.4 & 0.9 \\ Palma de Mallorca–Marseille & 69 & 302 & 676.5 & 118.7 & 37,622.9 & 2.6 \\ Gibraltar–Malaga & 66 & 63 & 52.3 & 9.0 & 2963.3 & 0.2 \\ Livorno–Villerfanche & 66 & 131 & 101.0 & 17.3 & 6539.1 & 0.4 \\ Malaga–Cádz & 65 & 132 & 160.7 & 27.9 & 9218.7 & 0.6 \\ Livorno-Napples & 61 & 262 & 535.3 & 93.9 & 29,770.4 & 2.1 \\ Palma de Mallorca–Cagliari & 61 & 326 & 595.9 & 104.3 & 33,669.1 & 2.3 \\ Palma de Mallorca–Cannes & 61 & 340 & 695.0 & 121.9 & 38,650.1 & 2.7 \\ \(\sum\) Group of routes with 50–59 & & & 1203.1 & 209.7 & 68,115.4 & 4.6 \\ connections (4 routes) & & & & & & \\ \(\sum\) Group of routes with 40–49 & & & & & & \\ connections (8 routes) & & & & & & \\ \(\sum\) Group of routes with 30–39 & & & & & & \\ connections (11 routes) & & & & & & \\ \(\sum\) Group of routes with 20–29 & & & & & & \\ connections (15 routes) & & & & & & \\ \(\sum\) Group of routes with 10–19 & & & & & & \\ connections (31 routes) & & & & & & \\ \(\sum\) Group of routes with 1–9 & & & & & & \\ connections (208 routes) & & & & & & \\ \(\sum\) & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Distance, number of connections, and emissions associated with the cruise routes analysed. number of connections. The latter type of route has a decisive influence on the amount of emissions of the group with 30-39 connections, as they represented 7.5% out of 15.1% of the emissions of the group. Table 8 shows the details of the repositioning routes with the highest activity identified. For instance, the route Gibraltar-Southampton, with only 37 connections, has similar emissions of NOx, SO2, and CO2 as the route Palma de Mallorca-Barcelona, which has the highest number of connections. However, the sailing distance of the former is nine times higher.
# On Multi-Hop Decode-and-Forward Cooperative Relaying for Industrial Wireless Sensor Networks
## 6 Conclusions  
In this paper, we investigated the end-to-end average BER performance and the channel capacity of a multi-hop DF relay system over Nakagami-\(m\) fading in the presence of impulsive noise. The analysis were validated by showing the excellent agreement between the results obtained through the closed-form expressions and the Monte Carlo simulation results. The analysis is very general and can be easily extended to other channel conditions (e.g., the conventional Rayleigh fading over AWGN, etc.) by changing the parameters of the fading and the noise models. The impacts of the path loss exponent and the fading severity on the system performance are also investigated. It is shown that the increase of the number of hops will degrade both the BER and channel capacity but also decrease the variance of the channel capacity. In channel conditions with highly \"impulsive\" noise effects, the BER curve will experience a stagnant stage against the increase of the SNR due to the characteristics of the noise. As the path loss exponent of the propagation environment increases, the advantage of the balanced power allocation scheme becomes more obvious compared to the equal power allocation scheme with respect to the end-to-end BER.  
Future work includes improvement of system performance under impulsive noise conditions by noticing that the existence of impulsive noise significantly degrades the performance, especially in the \"null region\". This can be potentially achieved by predicting the occurrence of impulsive noise if possible and adjust the power or coding rate accordingly.  
**Acknowledgments:** We gratefully acknowledge the Regional Research Fund of Norway (RFF) for supporting our research.  
**Author Contributions:** [PERSON] proposed the research idea, performed the mathematical analysis and wrote the manuscript. [PERSON] supported and supervised the research as well as proofread the manuscript.  
**Conflicts of Interest:** The authors declare no conflict of interest.  
Figure 12: The variance of channel capacity for the relay fading channels with different values of \(m\) and \(L\), \(A=0.5,\rho=1\).
# Validation of Sentinel-2, MODIS, CGLS, SAF, GLASS and C3S Leaf Area Index Products in Maize Crops
## 3 Validation Methodology
### Validation of the Decametric LAI Product and Reference LAIs  
The SL2P-based Sentinel-2 LAI product was first validated. Then, two strategies for the generation of reference LAI were compared: (1) recalibrating the SL2P-based Sentinel-2 LAI product with a linear regression against the LAINet LAI, and (2) generating reference LAI through directly up-scaling the LAINet measurements with an empirical transfer function applied to Sentinel-2 reflectances. Results derived from the above two strategies were referred to as recalibrated SL2P-based and empirically based LAIs, respectively. Finally, the best performant LAI, assessed with k-fold cross-validation, was adopted as the reference LAI to validate the hectometric and kilometric LAI products.
# Low-Cost, Distributed Environmental Monitors for Factory Worker Health
## 2 Materials and Methods
### Sensor Performance
#### 2.4.3. Oxidizing Gas Sensors  
To measure sensor response of the oxidizing gas sensors, an AQUA-6 ozone generator (A2Z Ozone, Inc., Louisville, KY, USA) was used to generate ozone gas inside the chamber. Sensor measurements were compared to those observed with a Personal Ozone Monitor (2B Technologies Inc., PO3M, Boulder, CO, USA) reference instrument. The ozone generator wasoperated for five seconds and measurements were collected as the generated ozone dissipated. The conversion from mV to ppb was based on slope and intercept values from earlier laboratory experiments in which three sensors were exposed to ozone at concentration levels of 25, 50, 75 and 100 ppb and separate experiments where sensors were exposed to nitrogen dioxide concentrations of 0.2, 0.5, 1 and 1.5 ppm [40]. For this ozone decay experiment, we applied the sensors' relationship with O\({}_{3}\). Since the selection of the oxidizing gas sensors for this network, the manufacturer has proposed pairing the oxidizing gas sensor with a nitrogen dioxide sensor to improve the accuracy of measurements of both gases [42]. Evaluation of the paired oxidizing gas and nitrogen dioxide sensors to measure ozone and nitrogen dioxide in mixture will be evaluated in future studies.