esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Experimental Verification
Figure 6: The laboratory prototype: (**a**) System coupling mechanism prototype; (**b**) overall system prototype. Figure 7: The backward data transfer waveform when (**a**) there is no power resonance circuit and (**b**) there is power resonance circuit. As can be seen from Figure 8, with the power transfer resonance circuit, the data transfer capacity is not affected by the power transfer. The power transfer channel and the data transfer channel do not affect each other. Figure 9 shows the bit error rate (BER) test results of the data transfer. It can be seen that in the bidirectional data transmission test, the data can be transmitted correctly. For the rotary steering system of oil drilling, the system shall withstand high temperatures. Table 3 shows the comparison data of normal temperature (i.e., 25 \({}^{\circ}\)C) and high temperature (i.e., 135 \({}^{\circ}\)C, where the temperature is simulated by the high-temperature test box). Figure 8: (**a**) The forward data transfer results when power transfer is off; (**b**) the forward data transfer results when power transfer is on; (**c**) the backward data transfer results when power transfer is off; (**d**) the backward data transfer results when power transfer is on. Figure 9: The bit error rate test results of data transfer. As can be seen from Table 3, under the tested temperature conditions, with the increase in output power, the output voltage of the system remains basically constant at 48 V under the action of the closed-loop control circuit. The working efficiency of the system is maintained at more than 80%, and the data transmission is error-free.
# Investigation on Aerodynamic Noise Characteristics of Coaxial Rotor in Hover
## 2 Methodology
### Validation Cases  
The CFD solver and trim model used in this paper have been validated through different experimental cases (see Refs. [18; 19]), which show reasonable accuracy in the prediction of aerodynamic performance. Current existing experiments are mostly about the aerodynamics of coaxial rotors [29; 30]. There are few experimental acoustic data for coaxial rotors. For the single rotor in hover state, the noise is dominated by the thickness and loading noise components, at a low tip Mach number. The UH-1H rotor is often used for acoustic validation. Although the existing experimental data focus on high tip Mach number states, the calculated results by [PERSON] [31] are reliable for validation. Figure 3 shows the comparison of sound pressure results. It can be seen that results of this paper demonstrate good agreement with those of [PERSON].  
Figure 4 shows the experimental sound pressure of the AH-1/OLS [32] single rotor, compared with the calculated results of this paper. The state is \(\text{Ma}_{\text{tip}}=0.664\), \(\mu=0.164\), which has obvious blade vortex interaction (BVI). At this time, the rotor works in a complex interaction flow field, and it is difficult to accurately predict the load fluctuations on the blade surface. Thus, the calculated sound pressure results have some expected errors, which is similar to the simulation of [PERSON] [33]. However, the main sound pressure fluctuations can be captured well.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Observation Point** & **X (m)** & **Y (m)** & **Z (m)** \\ \hline \#1 & \(-10\) & \(0\) & \(0\) \\ \#2 & \(-9.238\) & \(-3.827\) & \(0\) \\ \#3 & \(-7.071\) & \(-7.071\) & \(0\) \\ \#4 & \(-9.238\) & \(0\) & \(-3.827\) \\ \#5 & \(-7.071\) & \(0\) & \(-7.071\) \\ \#6 & \(-3.827\) & \(0\) & \(-9.239\) \\ \#7 & \(0\) & \(0\) & \(-10\) \\ \hline \hline \end{tabular}
\end{table}
Table 3: Coordinate values of observation points.  
Figure 3: Sound pressure history of UH-1H rotor at low Mach number. (**a**) \(\text{Ma}_{\text{tip}}=0.6\); (**b**) \(\text{Ma}_{\text{tip}}=0.7\).
# A Multi-Layer Secure Sharing Framework for Aviation Big Data Based on Blockchain
## 4 Data Security Sharing Modeling
### Constraints for Secure Data Sharing  
Traditional finite state machines (FSMs) or infinite state machines (ISMs) are typically defined as quintuples \((Q,\Sigma,\delta,q_{0},F)\). However, the ATM data secure sharing scenario possesses unique characteristics. ATM data sharing must satisfy stringent security and timeliness constraints, which are fundamental to ATM operations and have irreplaceable impacts on data sharing. Therefore, this paper augments the quintuple with a constraint tuple. The constraints for secure data sharing include the following aspects.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Tuple** & **Description** & **Example/Range** \\ \hline Data\_Providers & Set of ATM units providing data/models (data owners \(O_{k}\)) & Airport towers, weather stations, etc. \\ Data\_Consumers & Set of ATM units receiving data/models (data consumers \(A_{j}\)) & Airlines, regional ATC centers, etc. \\ Data & Shared data/model \(D_{j}\) & Data: flight trajectories, weather data \\ Data & Shared data/model \(D_{j}\) & Models: traffic prediction, conflict \\  & & detection models \\ Sharing\_Mode & Current sharing mode & Data \_Sharing (raw data), \\  & & Model\_Sharing (parameters/gradients), Hybrid \\ Topology & Network topology determining data flow paths and fault tolerance & Centralized, Decentralized (P2P), \\ Timeliness & Maximum allowed latency for real-time data sharing & Distributed, Hybrid \\ Security\_Measures & Aggregated security mechanisms & \(\tau_{max}=5\)s \\ Utility & Quantified value of data/model \(D_{j}\) to receiver & Encryption, access control, integrity checks \\ \hline \hline \end{tabular}
\end{table}
Table 1: The definitions of each element in the system state.
## 2 Materials and Methods
### Data Preprocessing
#### 2.2.4 Unified Scale  
Thirty uniformly distributed ground control points were manually collected from the study area boundaries. The three nighttime light images were geometrically corrected using the Landsat 8 imagery with a uniform spatial coordinate system of WGS1984. The three corrected Luojia1-01, NPP-VIIRS, and Flint datasets were cropped using ArcGIS 10.2. The images were projected in the Lambert equal area projection coordinate system and resampled to achieve identical resolutions of 100 m. Figure 2 shows the corrected images separately. Areas with monthly mean NDVI \(>\) 0.9 and NDVI \(<\) 0.1 are excluded as uninhabited areas [43,44].
## 5 Case Study
### Measure Results  
According to Section 4.2, the composite robustness criterion of the construction schedule can be obtained as: \(r=0.374r_{s}+0.219r_{p}+0.407r_{c}\). Meanwhile, the three robustness criteria of this project can, respectively, be calculated as follows:  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \(\mathbf{r_{s}}\) & \(\mathbf{r_{p}}\) & \(\mathbf{r_{c}}\) \\ \hline \(\left\{\begin{array}{c}\left(\mathbf{c}\kappa_{\text{\tiny{subjective}}},0.005 \right),\left(\mathbf{c}\kappa_{\text{\tiny{subjective}}},0.15\right),\\ \left(\mathbf{c}\chi_{\text{\tiny{subjective}}},0.295\right),\left(\mathbf{c}\chi_{ \text{\tiny{SY,subjective}}},0.05\right),\\ \left(\mathbf{c}\chi_{\text{\tiny{subjective}}},0.05\right),\left(\mathbf{c}\chi_{ \text{\tiny{SY,subjective}}},0.05\right),\\ \left(\mathbf{c}\chi_{\text{\tiny{subjective}}},0.05\right),\left(\mathbf{c}\chi_{ \text{\tiny{ABjective}}},0.15\right),\\ \left(\mathbf{c}\chi_{\text{\tiny{ABjective}}},0.05\right),\left(\mathbf{c}\chi_{ \text{\tiny{ABjective}}},0.2\right),\\ \left(\mathbf{c}\chi_{\text{\tiny{ABjective}}},0.05\right),\\ \left(\mathbf{c}\chi_{\text{\tiny{ABjective}}},0.05\right),\left(\mathbf{c}\chi_{ \text{\tiny{ABjective}}},0.15\right),\\ \left(\mathbf{c}\chi_{\text{\tiny{ABjective}}},0.15\right),\\ \left(\mathbf{c}\chi_{\text{\tiny{ABjective}}},0.  
\[\begin{array}{llllll}r_{s}&=\sum\limits_{i=1}^{n}\omega_{i}(|S_{i}-s_{i}|)\\ &=0.0173\times|121-138|+&0.0173\times|179-183|+&0.0119\times|237-243|+&\ldots=419.31\\ &\uparrow&\uparrow&\uparrow\\ &\text{main transformer}&\text{main transformer}&\text{main transformer}&\ldots\\ &\text{hall layer \#2-1}&\text{hall layer \#2-2}&\text{hall layer \#3}\\ &r_{p}&=\sum\limits_{i=1}^{n}\omega_{i}\Big{(}|P_{i}-p_{i}|\Big{)}\\ &=0.0173\times|7-7|+&0.0173\times|11-12|+&0.0119\times|12-15|+&\ldots=21.64\\ &\uparrow&\uparrow&\uparrow\\ &\text{main transformer}&\text{main transformer}&\ldots\\ &\text{hall layer \#2-1}&\text{hall layer \#2-2}&\text{hall layer \#3}\\ &r_{c}&=-P(T\leq T)\\ &=-P(T\leq 2043)=-67.98\end{array}\]  
So, the composite robustness criterion of this project is \(r=133.89\). The range of r is \([0,\,275]\) and the schedule robustness is divided into five levels according to the contribution of criterion r change to schedule robustness: the schedule robustness is Very good when \(0\leq r<55\), the schedule robustness is Good when \(55\leq r<110\), the schedule robustness is Normal when \(110\leq r<165\), the schedule robustness is Bad when \(165\leq r<220\), and the schedule robustness is Very bad when \(220\leq r<275\). Thus, \(r=133.89\) means the schedule robustness of the underground power station is at the Normal level and the schedule is reasonable.
## 3 Results and Discussion
### FT-IR Spectroscopy  
FT-IR spectroscopy can be used for approximate identification of polysaccharides in plant materials when combined with chemical analyses [41]. The FT-IR spectrum of GPPP at modified optimal conditions is shown in Figure 3. The strong peak of the O-H stretching vibration was observed at 3406.72 cm\({}^{-1}\), and the weak absorption peak of the C-H stretching vibration was found at 2923.56 cm\({}^{-1}\), including CH, CH\({}_{2}\) and CH\({}_{3}\) stretching and bending vibrations. The C=O asymmetric stretching vibrations of the carboxylate (-COO\({}^{-}\)) groups was observed at 1614.22 cm\({}^{-1}\). The absorption peak at around 1416.22 indicated the presence of a carboxyl group. The peaks in the range 1300-1000 cm\({}^{-1}\) were characteristic of carbohydrates. The peaks around 1264 cm\({}^{-1}\) and 1086 cm\({}^{-1}\) were caused using the stretching vibration of C-O-C on the glycosidic ring and C-OH, respectively [6]. The absorption bands at about 590-900 cm\({}^{-1}\) were attributed to skeletal modes of pyranose, and this FT-IR analysis result confirmed that the monosaccharide composition of green pea polysaccharides mainly contains pyranose [42]. The peaks in the range 330-960 cm\({}^{-1}\) were characteristic of acidic pectins, xyloglucans and xylogalacturonans.
# Improving Passive Time Reversal Underwater Acoustic Communications Using Subarray Processing
## 5 Lake Experiment  
We start by describing the 2015 Danjiangkou (DJK15) experiment in which QPSK signals are transmitted from one source to eight receivers. BER and output SNR performances are obtained by applying different algorithms to the DJK15 data. The relationship between output SNR and the number of subarrays is studied using the experimental data.
# X-ray Spectroscopies of High Energy Density Matter Created with X-ray Free Electron Lasers
## 2 General Concept of Investigation  
Figure 2a shows the general sketch of the experiment. For efficient heating, a large number of X-ray photons need to be focused tightly. Using advanced focusing optics, such as Kirkpatrick-Baez mirror and compound refractive lens (CRL), XFEL beam can be focused to micro- to nano-meter sizes, and X-ray peak intensity in excess of \(10^{16}\) W/cm\({}^{2}\) can be achieved [20]. It is noted that the laser intensity of \(3\times 10^{16}\) W/cm\({}^{2}\) correspondsto the Coulomb field which binds 1s electron in a hydrogen atom (\(5\times 10^{11}\) V/m), and prior to XFELs, such light intensity was only available in the infrared and optical regimes. As samples, free-standing foils are the simplest cases. However, other forms, such as multi-layered targets [21] and liquid droplets [22], can also be used.  
Considering typical XFEL parameters (1 keV photon energy, \(10^{12}\) photons in 30 fs pulse, 1 \(\upmu\)m\({}^{2}\) focal spot area), the corresponding electric field (\(2\times 10^{12}\) V/m) is strong enough to induce nonlinear phenomena in atoms interacting with XFEL pulses. The photon number density in a cylinder volume corresponding to 1 \(\upmu\)m\({}^{2}\) focal spot area and 9 \(\upmu\)m propagation length in 30 fs is about \(10^{29}\) m\({}^{-3}\). It is similar to the typical atomic number densities of condensed matter (diamond: 1.76 \(\times\) 10\({}^{29}\), water: \(3.3\times 10^{28}\) m\({}^{-3}\)), and the photon to atom ratio could be of the order of unity. Depending on X-ray photon energy and absorption, the energy density in excess of 1 eV/atom as well as \(10^{11}\) J/m\({}^{3}\) can be achieved.  
To diagnose extreme light-matter interactions and different properties of the HED sample, various experimental techniques including imaging, diffractions, scattering, and spectroscopies with various wavelengths can be utilized. In this article, two spectroscopic techniques have been examined, namely, XES and XAS. The basic schemes of XES and XAS are illustrated in Figure 2b. These are complimentary  
Figure 2: (**a**) General concept of experimental setup for the spectroscopic study of XFEL heated matter. An XFEL beam is tightly focused on a solid-density target to create warm/hot dense conditions. XES and XAS are the major diagnostics to be discussed in this paper. (**b**) Basic schemes of XES and XAS.  
to each other to probe occupied and unoccupied electronic states. With proper simulation on population kinetics in energy levels, various core-level processes and material properties of HED matter, such as resonant and non-resonant core-level transitions, collisions, continuum lowering, and opacity can be investigated [23; 24; 25].
# Improving Graph-Based Movie Recommender System Using Cimenatic Experience +
## 4 Experiment
### Results
\begin{table}
\begin{tabular}{c c} \hline \hline
**Model Type** & **Best RMSE** \\ \hline CF (item-based) & 1.0840 \\ CF (user-based) & 1.0528 \\ SVD & 0.9872 \\ GCMC & 0.9852 \\ SVD++ & 0.9798 \\ IGMC & 0.9657 \\ IGMC + CX (ours) & 0.9621 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: RMSE Table of Amazon movie data. \begin{table}
\begin{tabular}{c c} \hline \hline
**Model Type** & **Best RMSE** \\ \hline Rating & 0.8051 \\ Rating, Emotion & 0.8036 \\ Rating, Sentiment & 0.8029 \\ Rating, Sentiment, Emotion (ours) & 0.8004 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: RMSE Table for Cinematic Experience’s influence. The results of the ablation study also showed better performance when combining sentiments with ratings rather than emotions. However, when sentiment and emotion were used altogether, the performance was the best, implying that they would complement one another. In the graph between the sentiment and rating, 'negative review and high rating' or 'positive review and low rating' could somewhat hinder the performance of the recommendation, but such information should be reflected to see similar results to the existing industrial recommender system. Therefore, when experimenting in such an environment, it sounds plausible that exploiting both sentiment and emotion could produce the best results. In summary, our model aggregated a multi-relational graph by performing GNN's operations for each edge type. Latent vectors were used to predict missing ratings, and when combined with CX information, they showed improved results. _F. The impact of parameter_  
**GCMC model** For the final model run, drop out was set to 0.5, the dimension was set to 256, and learning rate was set to 0.006. However, when the hyperparameters were changed, there was no significant effect because the range of changes in RMSE was small. **Surprise** In both KNNwithMeans of user-based and item-based, the performance was the best when \(k\) was 25 and _name_ was cosine, meaning that the higher the \(k\), the more neighbors can be considered. In both SVD and SVDpp, the performance was the best when _learning_rate_ was 0.006. _G. Visualization of subgraph_  
Inspired by [6], we visualized subgraphs of testing data with the highest and lowest predicted ratings for Rotten Tomatoes, as shown in Figures 8 and 9, respectively. As IGMC produces distinct subgraph patterns for each rating, it is helpful to look at those patterns for further investigation closely. In each subgraph, nodes on the left are users, and nodes on the right are 100 neighbor items that the model referred to produce the predicted rating for the target item. In Figure 8, the model produced a low score (i.e., 0.73) for the target item, and the items the model referred to tended to have relatively lower ratings, colored in blue. On the other hand, Figure 9 visualized a case where the higher the predicted score was (i.e., 4.68), the higher the actual ratings of the neighboring nodes were, colored in red. Figure 8: A visualized subgraph when the predicted score is low.
## 3 Therapeutic Use
### Antibacterial Activity  
Considering the Doctrine of Signatures, _Pulmonaria_ has been used in lung infections; hence, an important pathogen of the bronchial region, _Staphylococcus aureus_, isolated from clinical samples of cystic fibrosis patients, has been used to study its antimicrobial activity. The minimum inhibitory concentration (MIC) and virulence factors such as anti-biofilm properties, protein A (SpA) surface expression, \(\alpha\)-hemolysin (Hla) synthesis, staphylococcal sortase A (StrA) activity, and adherence to A549 cells were studied to assess the antimicrobial potential of methanolic extract from _P. officinalis_ (Figure 4). The MIC was found to be 1-2 mg/mL, which is not considered to be highly effective, but other virulence factors were also found to be reduced with the application of the extract.  
Figure 4: Antibacterial activity of lungworts studied through different methods.  
Biofilm formation on both inert and mucin- or elastin-coated surfaces by _S. aureus_ can be reduced with the application of the extract. Similarly, the adhesion of _S. aureus_ to mucin was also significantly decreased by up to 36% due to the application of the extract [56].  
The strong inhibition of staphylococcal sortase A activity of up to 70% in comparison to the positive control of the active enzyme was observed at the sub-MIC concentration (500 microgram/mL) of the extract (Table 1). The secretion of \(\alpha\)-hemolysin, the pore-forming toxin (cytotoxin) from the _S. aureus_, was also found to be significantly decreased by up to 50%. The extract from _P. officinalis_ can be considered as an anti-virulent against staphylococcus according to in vitro studies, such as the inhibition of microbial adhesion, sortase A activity, and \(\alpha\)-toxin secretion. These properties may be beneficial to cystic fibrosis patients, but further in vivo studies are required to confirm the result and development of _P. officinalis_ extract as a supplement for CF patients and/or as an anti-microbial agent [56].
## 3 Results and Discussion
### Commissioning of Full-Scale Technology and Adjustment of Process Parameters
\begin{table}
\begin{tabular}{c c c c c c c c} \hline
**Experiment** & **SHA** & **t\({}_{\text{in}}\)** & **\(\boldsymbol{\tau}\)** & **W\({}_{\text{gran}}\)** & **Crushing** & **K\({}_{2}\)O** & **P\({}_{2}\)O\({}_{5}\)** \\  & **Sample** & \({}^{\circ}\)**C** & **min** & **wt. \%** & **Test** & **wt. \%** & **wt. \%** \\ \hline Exp. 1 & SHA1-F & 80 & 20 & \textgreater{}5 & Passed & 23.3 & 4.3 \\ Exp. 2 & SHA2-F & 100 & 20 & \textgreater{}5 & Passed & 18.9 & 5.6 \\ Exp. 3 & SHA7-F & 100 & 20 & \textgreater{}5 & Passed & 27.0 & 6.9 \\ Exp. 4 & SHA7-F & 100 & 40 & \textgreater{}5 & Passed & 22.3 & 5.1 \\ Exp. 5 & SHA7-S & 180 & 20 & 5 & Passed & 28.7 & 5.4 \\ Exp. 6 & SHA7-F & 220 & 20 & 5 & Passed & 29.8 & 5.0 \\ Exp. 7 & SHA1-F & 320 & 20 & \textless{}3 & Failed & 26.5 & 5.2 \\ \hline \end{tabular}
\end{table} 
Table 4: Experimental conditions and results from the drying process adjustment.
## 3 Results and Discussion
### Correlation Analysis between HMs and Other Environmental Factors  
The concentrations of HMs in surface sediments are affected by various conditions, including environmental background, marine physical and chemical properties, biological effects, and human activities [39]. Analyzing the correlation between HMs and environmental factors (e.g., oils, TOC, sulfides) is helpful in determining the possible sources of HMs [40].  
In this study, the data followed a normal distribution, and the Pearson coefficient analysis was performed using SPSS 25 software. In Table 3, organic carbon had a significant positive correlation with Cu and Zn (\(p<0.01\)), indicating that Cu and Zn were closely related to organic matter, which was a main carrier. Additionally, organic carbon and HMs easily form organic matter complexes. Therefore, organic carbon plays an important role in the distribution of HMs. Among the six HMs, Zn was significantly correlated with Cu (\(p<0.01\)) and moderately correlated with As and Pb (\(p<0.05\)). Hg and Cd were significantly correlated with As but not with the other three HMs, implying that Hg and Cd might have sources similar to As, which differed from those of other metals. Oils and sulfides were not correlated with the concentrations of the six HMs, indicating that they had no effect on HMs in the dumping area.