esa-sceva/satcom-chunk-collection huggingface dataset:
# In-Field Load Acquisitions on a Variable Chamber Round
## 3 Load Acquisition Results and Discussion
### Load Spectra
Figure 20: Load spectra calculated according to ASTM E1049-85 from the _acceleration followed by emergency braking with an empty baler_ maneuver: (**a,b**) horizontal loads on the dynamometric towing pin, (**c,d**) vertical loads on the R hub carrier, and (**e,f**) vertical loads on the L hub carrier. Figure 21: **(a,c,e)** Load spectra calculated according to ASTM E1049-85 from the _high-speed running perpendicular to the swing lines_ maneuver and (**b,d,f**) load spectra calculated according to ASTM E1049-85 from _road transportation_: (**a,b**) horizontal loads on the dynamometric towing pin, (**c,d**) vertical loads on the R hub carrier, and (**e,f**) vertical loads on the L hub carrier. Figure 22: (**a**) Recorded time mix of the in-field load acquisition: (**b**,**d**,**f**) load spectra calculated according to ASTM E1049-85 from all maneuvers, where each maneuver is identified by a different color (see (**a**)), and (**c**,**e**,**g**) amplitude-only acquired load spectra, where each maneuver is identified by a different colour (see (**a**)). The black line is the sum of all spectra. (**b**,**c**) Horizontal loads on the dynamometric towing pin, (**d**,**e**) vertical loads on the R hub carrier, and (**f**,**g**) vertical loads on the L hub carrier. Considering now the vertical loads at the hub carriers, both the highest peak load and load amplitude were registered at the right hub carrier during _high-speed running (at approximately 12 km/h) perpendicular to the sowing lines_ with an empty baler because of the highly pronounced terrain irregularities. Specifically, Table 4 reports a peak load F\({}_{\text{v,max}}\) equal to 38.8 kN, while Figure 22e reports a load amplitude equal to 21.1 kN at the right hub carrier. Considering another demanding situation, namely, the higher speed of 30 km/h and smoother terrain irregularities during running parallel to the sowing lines, the second highest peak loads and load amplitudes were registered. In fact, considering the left hub carrier, a peak load F\({}_{\text{v,max}}\) equal to 33.2 kN was measured with a loaded baler (see Table 4) and a load amplitude equal to 19.7 kN was measured with an empty baler (see Figure 22g). These observations suggest that uneven terrain and baler speed play crucial roles in the determination of the extreme horizontal and vertical loads to which an agricultural implement may be subjected during its service life. Table 4 and Figure 22 demonstrate also that both peak loads and load amplitudes are significantly lower than the abovementioned values when the product collection maneuver is considered, due to the much lower speed (approximately between 3 and 5 km/h) the baler experiences in this case. All previous observations suggest that uneven terrain and baler speed are the primary factors that induce the extreme horizontal and vertical loads to which the baler may be subjected during its service life.
## 4 Conclusions  
The BGFT-x (x = 0; 0.2; 0.4; 0.6) research material was successfully obtained as a result of a solid-state synthesis reaction by free sintering in an air atmosphere. The X-ray diffraction (XRD), microstructure (SEM, EDS), dielectric properties, and magnetoelectric effect of obtained ceramics have been studied. The XRD results show the BGFT-x ceramics are single-phase with an orthorhombic structure with the \(Fm2m\) space group. SEM images have shown that doping the base material with gadolinium ions Gd\({}^{3+}\) causes changes in the microstructure, namely, the shape of the plate-like grains changes to rounded. As the admixture grows, large plates begin to appear, but they are few in number compared to the rest of the grains. EDS analysis confirmed the obtained ceramics' qualitative and quantitative chemical composition and excluded the involvement of foreign elements or possible impurities. Dielectric measurements have shown that the admixture of gadolinium ions affects the electric permittivity values, in particular, its maximum value and the temperature at which this value occurs. Frequency-dependent characteristics of electric permittivity have revealed the presence of strong relaxation, which can be associated with the characteristic disorder of dipoles in the Aurivillius phase and with ordering errors in the sequence of perovskite-like layers. The study of the magnetoelectric effect by calculating the magnetoelectric coupling coefficient \(\alpha\) shows that the magnitude of the magnetoelectric effect depends not only on the frequency of the electric measurement field but also on the amount of gadolinium ions added. The strongest coupling effect is demonstrated by material BGFT-x with \(x\) = 0.2.  
Conceptualization, M.A.-H.; methodology, D.S. and K.O.; software, M.C. and M.A.-H., validation, M.A.-H.; formal analysis, M.A.-H. and J.A.B.; investigation, D.S.; resources, M.A.-H.; data curation, J.M.; writing--original draft preparation, D.S.; writing--review and editing, J.M.; visualization, M.C., M.A.-H., J.M. and J.A.B.; supervision, M.A.-H.; project administration,  
\begin{table}
\begin{tabular}{c c c c c} \hline  & **1000 Hz** & **10,000 Hz** & **100,000 Hz** & **1,000,000 Hz** \\ \hline Gd\({}^{3+}\) ions & \multicolumn{4}{c}{\(\alpha\) [10\({}^{-9}\) s/m]} \\ \hline \(x=0\) & 1.49 & 3.49 & 5.22 & 8.62 \\ \hline \(x=0.2\) & 9.28 & 11.73 & 11.45 & 12.58 \\ \hline \(x=0.4\) & 1.50 & 2.97 & 7.00 & 9.80 \\ \hline \(x=0.6\) & 1.28 & 2.85 & 6.93 & 10.24 \\ \hline \end{tabular}
\end{table}
Table 6: Values of the magnetoelectric coupling coefficient \(\alpha\), calculated for undoped and doped with Gd\({}^{3+}\) ions multiferroic Aurivillius-type material and for several frequencies of the electric measurement field.  
M.A.-H.; funding acquisition, M.A.-H. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
**Data Availability Statement:** Data are contained within the article.  
The authors declare no conflicts of interest.
## 3 Discussion
The expression levels of 17 orthologues of eight structural genes in the L-galactose pathway showed that _GMP_, _GME_, and _GGP_ were highly expressed (Figure 4A), suggesting that these three genes may play important roles in AsA synthesis in kiwifruit. _GMP_ and _GGP_ in _Arabidopsis_[16; 35; 37; 38], _GME_ and _GGP_ in tomatoes and tobacco [16; 39; 40; 41; 42], and _GGP_ in apples [43] mainly regulate AsA accumulation. However, in kiwifruit, we found high correlations between the expression of _GME_ and _GGP_ and AsA content, especially for _GGP3_ (Actinidia33270), which is an orthologue of _GGP_ (Figures 1B and 4A). We analyzed the expression level of genes in L-galactose pathway at different developmental stages. The _GGP3_ (Actinidia32270) had the highest expression, and its expression pattern was highly consistent with transcriptome analysis (Figures 4 and S2). Analysis of the transcription factor abundance in different modules of the co-expression network revealed a significant enrichment of transcription factors during DAF40 (Figures S4B and S5), which we suggest is the main reason for the dramatic increase in AsA content in _A. latifolia_ at DAF40. In summary, we selected _GGP3_ to construct an overexpression vector and transformed it into kiwifruit call to obtain transgenic lines by an _Agrobacterium_-mediated method, resulting in a significant increase in the AsA content in transgenic calli (Figure 6). Our results further confirm the results of previous studies [9; 44; 45]. The transgenic lines were subjected to transcriptome analysis, and two transcription factors with the highest correlation with _GGP3_ (Table S5) were screened to verify their protein interaction relationships. The results showed that AcESE3 (an ethylene-responsive TF) interacts with _AcGGP3_ and AcMYBR (an MYB transcription factor) at the protein level (Figure 8), implying that the interactions of these proteins may play an important role in the regulation of AsA synthesis. Our experimental results confirm the predicted key structural genes regulating AsA synthesis in transcriptome analysis and the predicted DEGs in response to abiotic signals.
## 5 Results
### Full Multispectral Band Features
#### 5.2.2 Classification Maps  
Quantitative results are very useful to compare the performance of different models, it would also be visually useful to assess the spatial classification maps by different methods. To this end, the three trained models are applied to both the labeled areas and the whole images, respectively. The trained models with all multispectral band features are first applied to the labeled areas, where the spatial classification maps are shown in Figure 11. It can be seen that all three models generate satisfying spatial classification maps; however, the RF with Bayesian optimization has the fewest wrongly classified pixels and noises.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Methods** & **OA** & **Kappa Value** \\ \hline SVM & 0.9322 & 0.9002 \\ Random forest & 0.9650 & 0.9485 \\ Optimized random forest & 0.9834 & 0.9751 \\ \hline \hline \end{tabular}
\end{table}
Table 4: A comparison between different methods using OA and kappa value (full bands features).  
Figure 10: Curvature test result for the features in the random forest classifier with Bayesian optimization.  
In addition to applying the trained models to the labeled areas, it would also be interesting and useful to see the classification results on the whole satellite images for the purpose of urban land cover analysis. Based on the five labeled classes, the classification maps by using the three different models with full band features are shown in Figure 12. It can be seen that the RF with a Bayesian optimization approach again generates the best land cover classification result, which has fewer noises by comparing the areas highlighted by red rectangles.  
Figure 11: Classification map for labeled areas by three models with all band features: (**a**) SVM; (**b**) conventional RF; (**c**) RF with Bayesian optimization.  
Figure 12: Classification maps using different trained models to the original image: (**a**) SVM; (**b**) conventional RF; (**c**) RF with Bayesian optimization (red rectangles mean obvious improvements for different regions among various classifiers).
# Collective Attestation for Manageable IoT Environments
## 6 Evaluation  
We performed the evaluation to answer the following questions:  
* How scalable CAMIE is against a large-scale malware infection?
* How much overhead does CAMIE have to pay to gain the regional detection feature?
* How much are the communication and computation overheads of CAMIE?  
In this section, we analyze the security of CAMIE and then look into the overhead compared to the two representative schemes, SEDA and SANA. SEDA is a generalized swarm attestation with the minimum overhead. SANA supports the identification of compromised devices. Both schemes require no hardware additions (e.g., as in SeED) except the minimum trust anchor. Since the overhead of a swarm attestation consists of multiple factors, we represent the factors in terms of the energy cost. We also check the resiliency against the large-scale malware infection. Finally, we present the simulation results to show the overhead of CAMIE in more realistic device deployment.  
**Feature comparison.** We can compare the features of CAMIE to other scheme, SEDA and SANA, as follows:  
* Identification of compromised devices: CAMIE and SANA facilitate the identification of compromised devices, but SEDA does not. However, the identification method of CAMIE is more scalable but probabilistic because the identified devices are represented in a feature-vector form. SANA can provide a deterministic report on the compromised devices, but linearly increasing as the number of compromised devices.
* Target search: CAMIE supports a target searching along with an attestation process. Finding the target for update is essential for the swarm network management. However, SEDA and SANA focus on the attestation process only.
* Region-based information: Although SEDA and SANA report the attestation result for a whole network, CAMIE provides regional information. In other words, each region generates a regional attestation result, called a region summary.
## 3 Results
### FEM Results  
In this section, FEM results are used to plot values for variables that were not experimentally acquired, such as punch load, stresses and radial displacement. The accuracy of the test simulation is first confirmed in Figure 11, which shows a comparison of experimental, FEM and CAD cup linear profiles. All graphs are focused on cup fillet radius values within the higher deviation zone.  
Figure 11: Comparison of cup LP between experimental (red), simulation (black dashed) and CAD (black).  
Figure 10: Main results of punch RP analysis.  
Figure 9: Filled radius morphology of (**a**) real and (**b**) prototype geometry with (**c**) scale bar.  
The FEM curves for the two punches lie between those of the CAD and experimental; this indicates a good ability to simulate the deep drawing process. After validation, simulations were used to highlight the behaviour of punches during the deep drawing process. Figure 11(a) plots the punch load as a function of the stroke. It can be seen that both RG and PG loads exhibit increasing trends with similar slopes. At a 15 mm stroke, PG attains a maximum load of 91 kN; however, RG values increase further until a maximum value of 136 kN is attained, which then remains constant. Contrarily, the plots of effective stress in Figure 11(b) show trends characterized by different slopes (higher in PG, lower in RG) in which both simulations nonetheless attain a similar maximum value of around 80 MPa. The noise phenomenon visible in the RG plot is due to a loss of contact between the cup and the selected node during the simulation process.  
Finally, a comparison of the radial displacements undergone by the punches due to the compression loads is shown in Figure 13. Simulation results show a significant difference between RG and PG: the RG exhibited a displacement in a range of hundredths of a millimeters, with a maximum value equal to 0.07 mm; however, PG exhibited a maximum displacement of 0.33 mm.  
Figure 12: Load and stress punch analysis during deep drawing process.  
Figure 13: Radial displacement of simulated punches at the end of the deep drawing process.
# Origin and Function of Structural Diversity in the Plant Specialized Metabolome
## 3 Structure-Antioxidant Activity Relationships of Flavonoids
Combinatorial coupling between a flavonoid semiquinone radical and a phenylpropanol radical, such as coniferyl alcohol, forms a flavonoidignan [111; 112]. Combinatorial radical-radical coupling among flavones, flavonols, dihydroflavonols, flavanones, isoflav, neurones, neurones and chal-cones forms bi-, tri-, and tetraflavonoids [113; 114; 115; 116; 117; 118; 119; 120; 121]. Because the radical can be delocalized along the flavonoid conjugated system, various C-C or C-O-C linkage types are produced. These flavonoid oligomers can be distinguished from proanthocyanidin oligomers by the coupling mechanisms (proanthocyanidins are coupled through nucleophilic attacks) and by their monomers (proanthocyanidins are coupling products of flavan-3-ol monomers); however, the distinction is somehow arbitrary because \"mixed\" dimers, for example, flavan-3-ol \(\rightarrow\) dihydroflavonol, and \"nonproanthocyanidins\" comprising oxidatively coupled flavan-3-ols have also been identified [113]. Similarly to proanthocyanidins, dimer or oligomer molecules may exhibit enhanced activity relative to the simple monomer units. For example, bikaempfer showed stronger ROS scavenging activity than kaempfer [121]. This amplifying effect can be induced by the increased number of phenolic hydroxyl groups and by the extension of the conjugated system over the two molecules. Not all plant extracted bif flavonoids, however, exhibit strong antioxidant activity [120]. In certain cases, dimerization may have led to new functionalities. Biflavonoids have been mainly studied for their strong cytotoxic activity, suggesting a defensive role against herbivores in plants [119; 122; 123]. It is not known if the coupling occurs in a directed way, guided by a dirigent protein, in analogy with lignan biosynthesis, and also demonstrated for the synthesis of the phenolic terpenoid (+)-gossypol in cotton (_Gossypium_ sp.) [124; 125]. In certain cases, however, racemic mixtures of biflavonoids have been reported, indicating an uncontrolled, non-stereospecific radical-radical coupling [120]. Undirected radical-radical coupling in an oxidative cell environment could terminate radical chain reactions. The coupling products would then be, in some way, waste products with highly variable structures but, a priori, no proper function. In poplar, under oxidative conditions, monolignol radical coupling occurs within the cytoplasm [4; 71]. Phenylcournaran benzylic ether reductase (PCBER), an extremely abundant enzyme in poplar wood, reduces various products that arise from the oxidative coupling of monolignols, regenerating, as such, radical scavengers in an oxidative intracellular environment [71]. Similar recycling loops of other types of polyphenolic radical coupling products could be highly efficient contributors of radical scavengers in plant cells, although confirmation of this functionality awaits, today, the functional characterization of more PCBER-like reductases in the plant specialized metabolism.
## Materials and Methods
### Extraction of Land Surface Phenology Metrics  
We used the dynamic threshold method to extract metrics of LSP. The polynomial method was used to fit and reconstruct the NDVI time series data from 2000 to 2016. The software TIMESAT with a seasonal parameter of 0.5, an adaptation strength of 2.0, a Savitzky-Golay window size of 2, and an amplitude of 20% was run in MATLAB R2015b (The Mathworks, Inc., Natick, MA, USA). The parameters were set according to [PERSON] et al. [18]. The start of growing season (SOS) and the end of season (EOS) for each year were calculated, and the length of season (LOS) was obtained as the difference between SOS and EOS in each grid.
## 3 Results
### Intelligibility Comparisons between Stimuli with the Same MBDs within Each Language Group  
Due to stretching or compressing, the mosaic speech stimuli with a 20-ms and a 40-ms OMBD contained blocks of the same duration, and we also wanted to know whether the word intelligibility for stimuli with the same MBD would be similar or not. Regarding the stimuli with an MBD of 20 ms, the results showed that compressing the 40-ms OMBD into the 20-ms MBD caused significantly lower intelligibility compared with that obtained with the MBD of 20 ms (\(p=0.004\)) after preserving for the native-English listeners. Between the stimuli of the same MBD of 40, 80, or 160 ms, no significant differences in intelligibility were found (\(p>0.05\)).  
For the Indonesian group, there was no significant effect of compression for the stimuli with an MBD of 20 ms (\(p=0.088\)). Moreover, the Indonesian group had similar results as the native-English group, in that there were no significant differences in intelligibility between the stimuli with an MBD of 40 ms, 80 ms, or 160 ms (\(p>0.05\)). Meanwhile, for the Chinese group, similar to the native- English group, compressing the 40-ms OMBD into 20-ms blocks caused significantly lower intelligibility compared with that obtained with the MBD of 20 ms after preserving (\(p=0.002\)). Furthermore, for the Chinese group, there were significant differences between the stimuli with an OMBD of 20 ms stretched into 80 ms and the stimuli with the OMBD of 40 ms stretched into 80 ms (\(p<0.05\)). Similarly, there were also significant differences between the stimuli with an OMBD of 20 ms stretched into 160 ms and the stimuli with an OMBD of 40 ms stretched into 160 ms (\(p<0.05\)).
## 3 Results
### Application to PWR Containment  
The contain3D code validated in this study was applied to evaluate the three-dimensional behavior of hydrogen and water vapor in the APR1400 containment building during severe accidents. APR1400, which has a power generation capacity of 1400 MWe, has two main coolant loops, and each loop consists of one steam generator (SG) and two coolant pumps. The nuclear reactor is located in the center of the containment building, two steam generators are placed symmetrically in line with the reactor, and two coolant pumps are located on the left and right of the steam generator. The containment building of APR1400 consists of cylindrical vertical walls and a hemispherical dome on top, with an inner wall diameter of 22.86 m and a total height of 79.4 m. The geometry modeling, mesh generation, and source modeling for APR1400 were performed and simulations were conducted for two postulated accidents of SBLOCA and SBO.
# A Convolutional Neural Network SAR Image Denoising Algorithm Based on Self-Learning Strategies
## 2 SAR Image Denoising Algorithm Based on Self-Learning Strategy DnCNN
### Complexity Analysis  
The computational complexity of our proposed CNN-based SAR denoising algorithm is primarily determined by the convolutional layers. For each convolutional layer, the complexity is approximately  
\[O(H\times W\times C_{in}\times C_{out}\times K^{2}) \tag{4}\]  
where \(H\) and \(W\) denote the height and width of the feature maps, \(C_{in}\) and \(C_{out}\) are the numbers of input and output channels, and \(K\) is the kernel size. Since the proposed network consists of several such layers, the total computational load scales linearly with the number of layers.
## 4 Results and Discussion
### Reliability of TLPS Joints during Thermal Cycling
Figure 10: Evolution of calculated (**a**) normalized Mises strain and (**b**) Mises stress in TLPS, SAC305, and IMC (Cu\({}_{6}\)Sn\({}_{5}\)) joints during the ten thermal cycles. Figure 9: FE simulation results of total strain distribution (**a**) at cross-sections along the diagonal axis of the joint and (**b**) in the transient liquid-phase sintering (TLPS) bonding layer. Simulated Mises stress distribution (**c**) at cross-sections along the diagonal axis of the joint and (**d**) in the TLPS bonding layer at minimum temperature during the thermal cycling. Furthermore, although the reinforcement of solder-based joint by mold resin is generally effective, the reinforcement of IMC-based joint is not required because of its temperature-stable characteristics. The temperature-stable mechanical properties of the IMC enable the utilization of a soft resin as a part of the composite microstructure; in other words, significant stiffness reduction could be achieved by utilizing the resin with soft material properties and the temperature-stable IMC.