esa-sceva/satcom-chunk-collection huggingface dataset:
# Hybrid Shielding for Hypervelocity Impact of Orbital Debris on Unmanned Spacecraft
## 3 Results and Discussion
\begin{table}
\begin{tabular}{l l l l l} \hline \hline
**Model Label** & \begin{tabular}{l} **Kinetic Energy** \\ \(E_{k}\) (kNmm)** \\ \end{tabular} & \begin{tabular}{l} **Time Stamp** \\ **\(t\) (\(\mu\)s)** \\ \end{tabular} & \
\begin{tabular}{l} **Energy** \\ **Dissipation** \\ \end{tabular} \\ \hline C-0 & 575 & 20 &
\begin{tabular}{l} Reference @ 20 \(\mu\)s \\ \end{tabular} \\ \hline C-2 & 330 & & & & 42.6\(\%\) \\ C-4 & 202 & & & 64.9\(\%\) \\ C-6 & 164 & 20 & & 71.5\(\%\) \\ C-8 & 162 & & & 71.8\(\%\) \\ C-10 & 146 & & & 74.6\(\%\) \\ \hline T-0 & 1286 & & 17.5 & Reference @ 17.5 \(\mu\)s \\ \hline T-01 & 1285 & & & 0.1\(\%\) \\ T-05 & 1230 & & & 4.8\(\%\) \\ T-10 & 1040 & & & 19.5\(\%\) \\ T-15 & 773 & & & 40.2\(\%\) \\ T-20 & 432 & & & 66.6\(\%\) \\ T-30 & 280 & & & 78.4\(\%\) \\ T-50 & 172 & & & 86.8\(\%\) \\ \hline M-AL & 244 & & 20 & 57.6\(\%\) \\ M-TI & 177 & & & 69.2\(\%\) \\ \hline L-DP & 255 & & & 55.7\(\%\) \\ L-SE & 244 & & 20 & 57.6\(\%\) \\ L-MP & 225 & & & 60.9\(\%\) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Summary of main results and dissipation of kinetic energy for all numerical simulations.
# The Case for a More Holistic Approach to Dry Eye Disease: Is It Time to Move beyond Antibiotics?
## Other Functional Foods
### Glycerol Monolaurate  
Through the increased intake in the modern Western diet over the last 50 years of partially hydrogenated vegetable oils and trans fatty acids, such as linoleic acid, there has been a concomitant loss of dietary lauric acids (such as glycerol monolaurate or monolaurin) [181]. This shift has set the stage for a pro-inflammatory state in the human body. Glycerol monolaurate (GML) is found in coconut and breast milk. It is known to inhibit exoprotein production by Gram positive bacteria including _S. aureus_[182]. In vitro studies have shown GML inhibits bacterial lipases (particularly _Staphylococcal_ spp. that have been implicated in rosacea, plepharitis etc.) without disturbing the microbiota [183]. It is non-toxic and in low doses, not antimicrobial. It has the status of \"Generally Recognized as Safe\" by the FDA [183].  
GML is used widely used in the food industry as a surfactant and preservative and this raises the possibility of ingested GML as a potential agent for reducing systemic inflammation, in addition to topical ocular application, given its good safety profile on skin and mucosal surfaces [165] and negative ocular irritation [184].  
Previous studies conducted in our laboratory explored the efficacy of GML on inhibition of production of bacterial lipase from ocular isolates [40; 183]. Further, we determined a range of concentrations for which GML inhibits lipase production without substantial antimicrobial action. Translation into clinical trials (topical and oral) will give us some indication as to whether such an approach can not only provide immediate relief through the anti-inflammatory properties of GML [185] but might produce a stable shift in the gut and/or ocular microbiome that results in a decreased bacterial lipase production through a natural rebalancing of a healthy ocular community as opposed to the action of antibiotics that eradicate commensal bacteria while limit toxin production by pathogens. We are interested in exploring both oral and topical GML for dry eye and initial trials are underway. Preliminary data indicate significant improvement with the use of a topical GML ointment compared to placebo over 6 weeks in reducing the severity of DED and associated signs including plepharitis, limbal conjunctival redness, conjunctival palpebral redness, meibomian gland expressibility and meibum quality. As with many other studies, there was a significant improvement in ocular comfort from baseline but this was also reported by users of the placebo.
###### Abstract  
Currently, quite accurate measurements of atmospheric gusts are carried out by airport systems only in the vicinity of the runways. There is a still open issue of availability of information about real wind gusts at cruising altitudes and during approach at a considerable distance from the airfield. Standard on-board systems of a jet transport airplane provide some information which is desirable to have knowledge of how flight parameters reflect real gust parameters and their impact on the aircraft dynamics. The paper proposes an algorithm for headwind gust magnitude estimation in relation to aircraft response. The analysed estimation algorithms assume the use of data available from the existing on-board systems only without the employment of any extra sensors or ground and satellite systems. In this way, many problems caused by different structures, configurations, and ways of installation of additional sensors and structural changes are rejected. The algorithms use the classical method for estimation of wind parameters as well as a linear longitudinal model of aircraft dynamics, taking into account the influence of wind gusts. Data fusion was realised with the use of three filtration methods. Results were evaluated to select the most accurate method of the estimation. Test data were obtained from advanced flight simulation. The experimental scenario considered a flight of a passenger twin-engine jet airplane through a layer of programmed gusts. The results of the flight simulations allowed us to determine the accuracy of the proposed gust estimation algorithms in reference to the ideal wind-speed data analysis obtained directly from the simulation environment (with the accuracy of the simulation process). The use of the proposed gust estimation algorithms may provide more accurate signal for integrated on-board systems, especially for wind shear detection and sped-up response time of flight control systems, protecting aircrafts against the adverse impact of encountered wind shear or gusts, e.g., auto-thrust or auto-throttle systems. The dedicated algorithm presented in the paper may increase the safety level of take-off and approach phases in gusty conditions and also during significant changes in wind speed at cruising altitudes in the case of crossing the area of jet stream occurrence.  
wind; gust estimation; airplane; complementary filtering +
Footnote †: journal: Applied Sciences
# On the Needs and Requirements Arising from Connected and Automated Driving
## 3 5 GCAR Use Cases
### Lane Merge Coordination  
The lane merge coordination use case belongs to the class of _cooperative maneuvers_. The goal of this use case is the sharing and coordination of driving trajectories among a group of vehicles to improve the traffic safety and efficiency. A subject vehicle (e.g., Veh\({}_{1}\) in Figure 1) that plans to join a main lane is coordinated with remote vehicles driving on the main lane in order to merge smoothly, safely, and with minimal impact on the traffic flow. The trajectory recommendations are computed based on vehicle position, orientation and speed, being continuously transmitted by the connected vehicles. It is necessary that the system considers non-connected, i.e., non-communicating, road users, since it cannot be assumed that every road user is connected to the network. For the external observation of road users, a camera system is installed at the road infrastructure next to the lane merge location [11]. All road users (connected and non-connected) are localized and identified by the camera system. The estimated road user attributes, such as position, orientation, and speed, are transmitted to the data fusion function, which merges data that originated from the camera system and from connected road users. The lane merge coordination function analyzes the road situation and continuously provides trajectory recommendations for the connected vehicles while considering the behavior of unconnected vehicles with the aim of an optimal lane merge process.
# Aiding Dictionary Learning Through Multi-Parametric Sparse Representation
## 3 Analysis of the Multi-Parametric Formulation Induced by the DL Problem
### Geometrical Interpretation of the \(\ell_{1}\) Norm  
The first item stems from a well-known result from polyhedral sets' state of the art [18]: the norm inequality \(\|\mathbf{\xi}\|_{1}\leq 1\) describes the n-th order cross-polytope (the dual of a hypercube):  
\[C_{n}=\text{conv}\{\pm\mathbf{e}_{i}\}=\{\mathbf{\zeta}\in\mathbb{R}^{n}:\;\|\mathbf{\zeta }\|_{1}\leq 1\}, \tag{11}\]  
where \(\mathbf{e}_{i}\) are the column vectors that have '1' on the i-th position and '0' anywhere else. Consequently, it follows that \(\|\mathbf{\Delta}\xi\|_{1}\leq\delta\) is equivalent with  
\[\{\mathbf{\zeta}\in\mathbb{R}^{n}:\;\|\mathbf{\Delta}\mathbf{\zeta}\|_{1}\leq\delta\}= \text{conv}\{\pm\mathbf{\Delta}_{i}^{+}\}\cdot\delta, \tag{12}\]  
with \(\mathbf{\Delta}_{i}^{+}\in\mathbb{R}^{n}\), the column vectors of matrix \(\mathbf{\Delta}^{+}\), the pseudo-inverse of matrix \(\mathbf{\Delta}\). Through (11), we have that \(\mathbf{\Delta}\xi=\text{conv}\{\pm e_{i}\}\). Taking \(\mathbf{\Delta}^{+}\) which verifies \(\mathbf{\Delta}^{+}\mathbf{\Delta}=\mathbf{I}\) allows for writing relation (12). Writing explicitly the convex sum from (12), we arrive at  
\[\{\mathbf{\xi}\in\mathbb{R}^{n}:\;\|\mathbf{\Delta}\xi\|_{1}\leq\delta\}=\{\mathbf{\xi}: \;\mathbf{\zeta}=\mathbf{F}\mathbf{\alpha},\;\mathbf{\alpha}\geq 0,\;\mathbf{1}^{\top}\mathbf{ \alpha}=\delta\}. \tag{13}\]  
Note that we made the notation (for compactness reasons) \(\mathbf{F}=\begin{bmatrix}\mathbf{\Delta}^{+}&-\mathbf{\Delta}^{+}\end{bmatrix}\) and that \(\mathbf{\alpha}\in\mathbb{R}^{2n}\). Any permutation of column vectors \(\pm\mathbf{\Delta}_{i}^{+}\) in \(\mathbf{F}\) is equally valid. We have simply chosen this form as it permits for compactly writing \(\mathbf{F}\) with respect to \(\mathbf{\Delta}\). With these notations, we rewrite (10) into the form:  
\[\begin{array}{ll}\min_{\mathbf{\alpha}}&\|T\mathbf{F}\mathbf{\alpha}-\mathbf{y}\|_{2}^{2}, \\ \text{s.t.}&\mathbf{\alpha}\geq 0,\;\mathbf{1}^{\top}\mathbf{\alpha}=\delta.\end{array} \tag{14}\]  
Note that the optimal solution of (14) is \(\mathbf{\alpha}^{\star}\) and, thus, \(\mathbf{\xi}^{\star}=\mathbf{F}\mathbf{\alpha}^{\star}\).  
**Remark 1**: _Any polyhedral set has a dual representation: half-space (as a finite intersection of linear inequalities) and convex (as a convex sum of extreme points and linear combination of rays--in which case it is not bounded). Most often, the half-space representation is preferred since it is more compact (there are usually many fewer constraints than extreme points). On the other hand, the cross-polytope is the go-to counter-example: there are \(2n\) extreme points in (11) but to these correspond \(2^{n}\) inequalities in the half-space representation. It is thus significantly more efficient to exploit the convex representation in this particular case._
## 6 Simulation
### Protocol Characteristics  
Figure 16(left) shows the typical runs of sub-cluster formation with \(N_{S}=100\) and \(R/R_{e}=1\). Notice that the TCAT effectively organizes the sensors into tracking groups. Referring to Figures 12 (left) and Figure 16(right), observe that compared with the protocol in [5], the TCAT has a lower leader handoff frequency and there is no significant performance degradation during the leader handoff period. Moreover, considering different sub-cluster size \(n\) and a network with random uniform deployment, Figures 12(left) suggests that compared with the TCAT with \(n=2\), the TCAT with a smaller value of \(n\) (e.g., \(n=1\)) with respect to handoff condition 1 and the TCAT with a larger value of \(n\) (e.g., \(n=3,4\)) with respect to handoff condition 2 lead to a higher frequency of inter-cluster handoff. Thus, the TCAT with \(n=2\) may provide flexibility and robustness for distributed sensor scheduling management.  
Figure 15: The performance comparison of TCAT with joint AOA/TOA and CRLB: X-axis (**left**) and Y-axis (**right**).
# TER-CA-WGNN: Trimodel Emotion Recognition Using Cumulative Attribute-Weighted Graph Neural Network
## 3 Proposed Approach for Emotion Recognition
### Speaker Embedding
#### 3.2.1 Text Speaker Embedding Using LSTM  
An LSTM network is a marvel in the field of neural networks, distinguishing itself with its unique structure. Unlike traditional neural networks, LSTM are designed with interconnected nodes in their hidden layers. This architecture allows for the sequential flow of information, where the output of one layer seamlessly feeds into the input of the next. Such a configuration is particularly adept at handling time series data, which is a common characteristic of textual information in speech. The heart of the LSTM lies in its hidden layer, where time series data find their temporal abode. Figure 4 provides a visual representation of the LSTM's fundamental design [46], illustrating how it adeptly manages data over time.  
A critical component of the LSTM is the 'cell', the basic unit of memory within the network. Each cell is responsible for transmitting not only the cell state but also the hidden state to the subsequent cell, creating a continuous flow of information. This flow of text data through the LSTM chain is unique. The data can traverse through the cell state with minimal or no changes, although some linear transformations may occur. The real magic of LSTM lies in its use of sigmoid gates. These gates act as regulators, updating cell states by selectively adding or deleting text data. The operation of these gates involves a series of matrix operations, each with its independent weight selection, akin to a gate mechanism in traditional computing. One of the most significant advantages of LSTMs is their ability to circumvent the problem of long-term dependencies. Traditional neural networks often struggle with retaining information over extended sequences, but LSTMs overcome this hurdle. They employ gates to manage the network's memory effectively, ensuring that vital information is retained and irrelevant data is discarded, thus maintaining the integrity and relevance of the emotional cues encoded within the text.
## 2 Methodology
### Experimental and Diagnostic Approach
#### 2.1.2 SSG and Grid Currents  
As will be shown in detail in Section 3, the main source of electrons in the self-neutralized ion beams is SEE stemming from the facility walls. The SSG represents part of the facility; thus, it is to be expected that violation of the neutralization by the probes should influence the value of the electric current from the SSG to the facility grounds. The electron and ion flows contribute to the measured electric current with opposite signs. Hence, the electron emission from the SSG's surface should reduce the value of the measured SSG current. This circumstance is illustrated in Figure 5, where the SSG current together with the currents of the first and second RIT3.5 grids are highlighted.  
The data in Figure 5 are taken during the radial movement of the probes through the beam. Clear dependence of the SSG current on the position of the probes can be observed--the absolute value of the electric current leaving the SSG is smaller (blue curve in Figure 5; the measured negative values appear as a maximum on the diagram). The ion beam current (purple curve in Figure 5), which is equal to the electric current to the first grid, remains unchanged. This observation indicates that crossing of the beam by the probes yields higher electron emission from the SSG. The value of the SSG current is somewhat smaller than the value of the first grid current. This can be attributed to the influence of multiply charged ions present in the RF plasma of the RIT. The ratio of the currents of singly \(j_{+}\) and multiply \(j_{Z+}\) ionized ion beams for a given acceleration voltage can be estimated as  
Figure 4: Graphical representation of electron density (\(n_{e}\)) determination using orbital motion limited (OML) theory applied to Langmuir probe data. Each color represents a distinct set of experimental data taken at different radial positions, leading to varying electron densities within the plasma. The dashed black lines provide linear fits to the data. The presence of linear parts in the diagrams illustrates the applicability of the OML, allowing for the accurate determination of \(n_{e}\).  
\[\frac{j_{Z+}}{j_{+}}=Z\sqrt{Z}\frac{n_{Z+}}{n_{+}}\,, \tag{2}\]  
where \(n_{+}\) and \(n_{Z+}\) are the corresponding ion densities. The electric current of the multiply charged ions does not leave the SSG because their trajectories do not follow the optimal path of the electrostatic lens system. Applying Equation (2) with the assumption of a 5 % content of doubly charged ions results, in our case, in an electric current of 2.5 mA out of a total of 19 mA extracted from the plasma. This is in good agreement with the measured difference of 3 mA between the SSG and first grid currents in Figure 5.
## 2 Materials and Methods
### Study Area and Data Source
#### 2.1.5 Sample Point Acquisition  
ArcGIS software was used to generate random points within the vector boundaries of the farmland in the study area. These random points were visually interpreted based on GF images (including GF-2 and GF-6) and Google Earth images to obtain the samples with and without cropping activities in 2021 and 2022, respectively. The total number of sampling points was 6826, and 15% of the samples (1204 points) were randomly selected as training samples for the extraction of abandoned farmland data from 2021 and 2022, respectively. The distribution of the training sample points is shown in Figure 4.
## 3 Similar Simulation Test Analysis
### Analysis of Test Results
#### 3.4.2 Overburden Stress Distribution Pattern  
Figure 13(a) illustrates the pressure curve of the roof slab of the advancing bottom pulling roadway. As depicted in Figure 13(a), when the undercut area width reaches 20 m, although the relative range of the undercut area is small at this stage, there is a noticeable change in the surrounding rock stress within the undercut area space, ranging from 0.005 to 0.01 MPa. This stress change is also monitored at the pressure box measuring point located 30 m ahead of the undercut area face.  
As the undercut area width increases to 60 m, the stress in front of the working face continues to rise, reaching a maximum of 0.06 MPa within 10 m of the face. With the expanding undercut area, the ore body gradually accumulates energy. Once this energy reaches the rock body's strength limit, the ore body fractures and collapses. Concurrently, the disturbance in the overlying ore body caused by the mining area significantly increases. The peak stress above the top plate of the pull-down layer reaches 0.057 MPa, affecting a 60 m area.  
Upon reaching an 80 m pull-down layer width, the peak overpressure reaches 0.075 MPa, leading to rock layer collapse in the upper ore body. Comparing the pressure curves at measurement points 4 and 5 in the top plate of the pull-down layer between the 60 m and 80 m scenarios, they both converge to 0, indicating rockfall occurrence and the initiation of ore body collapse.  
Figure 13(b) displays the stress curve of the bottom plate of the advancing excavation roadway. It reveals a cyclic stress pattern as the excavation layer width advances on both sides of the rock. The pressure curve is a constant of 0.05 MPa, which is consistent with the experimental data.  
Figure 13: Pressure distribution graph: (**a**) roof pressure distribution curve; (**b**) bottom plate pressure distribution curve.  
sides. During bottom pulling work, stress from the overlying rock movement transfers to the bottom plate, creating stress concentration [38]. As the roadway advances, measurement points within the stress concentration area transition to pressure relief zones, leading to stress reduction until reaching 0 overburden pressure. Measurement points further from the roadway exhibit similar trends, with higher peak stress levels.
# Numerical Study of the Flow and Blockage Ratio of Cylindrical Pier Local Scour
## 4 Numerical Results
### Effects of the Channel Width on the Clear-Water Local Scour Pattern
As a result, the narrow channel effect results in a faster scour process and a deeper horseshoe scour hole in the clear-water test, as shown in Figure 16.  
Figure 16: Comparison of the bed topography at equilibrium condition in clear-water conditions in the narrow channel (**a**) and the wide channel (**b**). It is important to note that the live-bed tests were based on the configuration in [PERSON] et al., 2005 [4], while the clear-water conditions are based on the configuration in [PERSON], 2018 [18]. A notable difference is the pier diameter, which affects the relative coarseness (D/d) of the model. In the Roulund configuration, \(D/d\approx 370\), while in the Lachaussee case \(D/d\approx 37\). Several studies have pointed out the influence of the relative coarseness on the effect of the blockage ratio over the scouring process. [PERSON], 2014 [49], states that, for \(D/d<100\), the blockage ratio has minimal influence over the scour process. However, an experimental study by [PERSON] et al., 2018 [6], was performed with a relative coarseness \(D/d=81\) and it was found that the larger blockage ratio produced a larger scour depth. This suggests that the relationship between the relative coarseness and the blockage ratio may be more complex than previously thought. The effect of the roughness length \(z_{0}\) over the scouring process is a similar consideration to the relative coarseness effect. The behavior of \(z_{0}\), which directly influences the friction velocity, is directly influenced by the hydraulic regime of the flow (Equation (13)). It can be seen in Table 2 that the clear-water case is located in the transitional hydraulic regime, but very close to the smooth hydraulic regime at \(\text{Re}_{D}\approx 6\). Furthermore, considering the largest amplification factor seen in Figure 15, we obtain \(\text{Re}_{D}\approx 22.8\), which is within the transitional hydraulic regime. In contrast, the live-bed configuration (Table 2) results in a larger friction velocity amplification near the cylinder ([PERSON] et al., 2020 [20]), which locally overshoots the threshold for the rough hydraulic regime.