esa-sceva/satcom-chunk-collection huggingface dataset:
## 7 Validation and Results
### Negation and Speculation Results
#### 7.3.2. Scope Recognition Results  
Five experiments were performed in order to analyze the impact for each rule proposed for scope recognition (see Section 5.4):  
1. The first rule is used to recognize the scope. As mentioned in Section 5.4, this rule searches for a termination term in the sentence which indicates the end of the scope. This approach is commonly used by previous rule-based approaches [53; 60; 61].
2. The second rule is added to take into account contiguous cues for recognizing the scope.
3. The _short sentence heuristic_ is used by adding the third rule.
4. Adding the fourth rule to include POS tagging features.
5. The fifth rule is added to include the parse tree analysis for extracting the scope.  
Table 5 shows the results obtained in the scope recognition task. According to this table, the best results were obtained when all the proposed rules were included in the fifth experiment. An 89% F-score in the negation scope, and an 85% F-score in speculation scope detection were obtained. This fact indicates that the proposed approach outperforms previous rule-based approaches that use only termination terms for scope recognition in Spanish [60; 61]. In fact, when using only termination terms, a mere 70% in F-score for negation and an 71% in F-score for speculation detection were obtained. This is due to the fact that not all sentences have termination terms.  
For the particular case of negation detection, Table 5 depicts that the use of contiguous negation, short sentence heuristic, POS tagging, and sentence parse tree (Rules 2 to 5) shows to be useful to improve the scope recognition task. All these rules have similar improvement rates. This proposal improves previous rule-based approaches which recognize the scope using only termination terms [60; 61].  
In speculation scope detection, the behavior of the rules were found to be different. Specifically, the contiguous cues and the _short sentence heuristic_ do not have a significant improvement rate (See Table 5). This situation suggests that contiguous cues and short sentences are not so related to speculation as they are for negation. On the contrary, POS tagging and sentence parse tree features result in a significant improvement for speculation scope detection.  
In addition, speculation detection has not yet been fully addressed for Spanish clinical narratives. We found only the [12] proposal dealing with this issue. Obtained results in our approach show similar performance rates than those reported by [12].
# Wind-Wave-Current Coupled Modeling of the Effect of Artificial Island on the Coastal Environment
## 2 Materials and Methods
### Data Source and Model Setup
#### 2.2.3 Wind and Wave Conditions  
The hydrodynamics and wave boundary conditions were determined using meteorological data of wind speed, wind direction, air temperature, and air pressure in 2020, which were collected from the meteorological station in Gangbei Town. In addition, for Typhoon 19 in July 2017, Gangbei Town recorded the wind field (including wind speed and direction) and water level process of the typhoon, as shown in Figure 6. The typhoon caused obvious water increases, and water increase and wind speed showed a positive correlation. At the same time, the wind direction during the typhoon was mainly northeasterly, which had a more obvious water increase effect on the Wanquan estuary and the area near Tannen Port. Therefore, this study included both general meteorological conditions and extreme typhoon meteorological conditions, and the data were highly representative.
# Integrating Inland and Coastal Water Quality Data for Actionable Knowledge
## 3 Overview of Observational Methods and Platforms
### Models  
A major benefit to the integration of modeling with monitoring datasets is the greater explanatory power over single observations alone [107]. Although remote sensing and most citizen science programs provide surface measures, and discrete and continuous sampling provide measures at depth, they all are limited to observation times. One- and three-dimensional integrated models provide time-stepped processes and distribution of water quality parameters laterally, as well in depth. Models provide tools quantifying rate processes and managing the ecosystem response to anthropogenic and natural conditions. Deterministic water quality models rely on a first correct description of hydrodynamic processes and conditions (e.g., stratification, shear, etc.) [108]. Compared with three-dimensional process-based models, one-dimensional (1-D) models have the advantage of being computationally inexpensive and can provide good estimates of the seasonal dynamics [109]. They are, thereby, excellent candidates for global scale and long-term climate change studies [110, 111]. Yet, short-time responses and lateral variability remain out of the scope of such an approach. In three-dimensional (3-D) modeling, the horizontal and vertical variability are resolved over time. Extensive reviews of common ecosystem models are available elsewhere [112, 113, 114]. Ecosystem models often focus on plankton communities, food-web structures, and population dynamics. The combination of such coupled hydrodynamic-biological models with in situ observations and associated data analysis has been widely demonstrated [115, 116, 117]. A range of models are available for lake ecosystems [113, 118], though, applying 3D hydrodynamic models in lake environments is more challenging than for coastal systems and the open ocean. The thinner and stronger stratification and weaker level of turbulence observed in lakes remain challenging to correctly reproduce with standard turbulence closure schemes [119]. The delay in adapting state-of-the-art techniques in lakes also is explained by the small size of research groups, however increasing, in limnology [120], focusing on particular lakes. Hydrodynamic and coupled biogeochemical outputs of the large-scale dynamics are improved by the addition of data assimilation from in situ and remotely sensed data [121, 122, 123, 124, 125, 126]. However, fine-scale hydrodynamic processes and, even more so, biogeochemical processes become more diverse and difficult to resolve. Boundary effects, shallowness of the systems, and, thus, strong influence
# Estimation of Terrestrial Water Storage Changes at Small Basin Scales Based on Multi-Source Data
## 4 Results  
### Small-Scale Basin Division in the GRB  
Based on the slope runoff simulation algorithm, the small-scale basin division of the GRB was completed. The small-scale basin division results of the GRB can be divided into two levels. The first level is the control layer of hydrological stations, each hydrological station controls a basin, and the only outlet in the basin is the corresponding hydrological station (as shown in Figure 2a). The second level is the area control layer, subdivided according to the topographic features and river direction based on the first level results. Finally, the GRB is divided into 172 sub-basins, with an average basin area of 591 km\({}^{2}\) (as shown in Figure 2b).  
Because the real river network information of the GRB is difficult to obtain, our study used the river network data provided by Open Street Map (OSM) to calculate the match error of the extracted river network in the GRB. The results showed that the match error of the extracted river network in our study is 0.013, which meets the accuracy requirement.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Component** & **Source** & **Forecing Data** & **Temporal Resolution** & **Spatial Resolution** & **Reference** \\ \hline \multirow{4}{*}{Precipitation (\(P\))} & \multicolumn{4}{c}{GEWEX-SRB, GLDAS,} \\  & \multicolumn{4}{c}{TRMM, Meteorological data} \\  & \multicolumn{4}{c}{from the China Meteorological} \\  & \multicolumn{4}{c}{Administration (CMA)} \\ \hline Evapotranspiration & PML\_V2-simulated & \multicolumn{4}{c}{CMFD, MCD15A3H.006,} \\  & \multicolumn{4}{c}{MCD43A3.006,} \\  & \multicolumn{4}{c}{MCD11A2.006, MCD12Q1} \\ \hline \multirow{4}{*}{Runoff (\(Q\))} & \multicolumn{4}{c}{CMFD, SRTMGL1, Land} \\  & \multicolumn{4}{c}{Use/Land Cover Data, Soil map data, Meteorological data} \\ \cline{1-1}  & \multicolumn{4}{c}{from the CMA} \\ \hline \hline \end{tabular}
\end{table}
Table 1: Detailed water balance components.
# 3D Reconstruction Based on Iterative Optimization of Moving Least-Squares Function
## 4 Experiments
### Ablation Studies
#### 4.5.2 Gru  
To verify the effectiveness of the GRU module in the paper, an ablation experiment was performed, and the visualization results are presented in Figure 9. In the experiment, \"GRU*1\" indicates that only one GRU module is connected after the shallowest octant (third layer). From the results of observation, when there is only one GRU module, it is difficult to keep the generated surface smooth and continuous. In contrast, \"GRU*3\" refers to the insertion of three GRU modules after the octant of the third-to-fifth layers. By observing the experimental results, compared with \"GRU*1\", the surface quality generated by \"GRU*3\" is significantly improved, and although the GRU is not connected to the deepest octant node, the generated surface still maintains good continuity and avoids sharp edges. In addition, \"GRU*4\" means that four GRU modules are connected after the octant of the third to sixth layers. According to the results, \"GRU*4\" is more accurate than \"GRU*3\" in the expression of wires, and at the same time, it can better show the sharp features of the edge of the lampshade, making it closer to the ground truth surface. This shows that adding the GRU module can effectively extract the relationship between local and global features, which helps to improve the quality of generated surfaces, especially when dealing with complex structures and details.  
The effect of different numbers of GRU modules on the generated surface can be observed through the ablation experiments on GRU, and the gradual increase of the number of GRU modules can improve the continuity and fineness of the surface, which provides strong support for the effectiveness of the proposed method and further verifies the important role and superiority of GRU modules in the 3D surface generation task.
# Signal Detection Based on Separable CNN for OTFS Communication Systems
## 3 Problem Formulation  
### OTFS Transmitter  
OTFS modulation maps information symbols onto a 2D DD domain, which can directly capture the geometric features of delay and Doppler shifts caused by relative motion. This mapping transforms time-varying multipath channels into time-invariant channels in the DD domain, making it highly advantageous for high-mobility scenarios.  
As illustrated in Figure 1, the OTFS modulator maps the input symbols \(x[k,l]\) onto a 2D DD grid, where \(k=0,1,\ldots,N-1\) and \(l=0,1,\ldots,M-1\) represent the Doppler and delay indices, respectively.  
The inverse symplectic finite fourier transform (ISFFT) is applied to transform the DD-domain signal into the time-frequency (TF) domain:  
\[X[m,n]=\frac{1}{\sqrt{NM}}\sum_{k=0}^{N-1}\sum_{l=0}^{M-1}x[k,l]\cdot e^{|2\pi \left(\frac{m}{N}-\frac{m}{M}\right)}, \tag{1}\]  
where \(X[m,n]\) is the TF domain symbol at delay index \(m\) and Doppler index \(n\).  
Then, the Heisenberg transform converts \(X[m,n]\) to the time-domain signal \(s(t)\):  
\[s(t)=\sum_{m=0}^{M-1}\sum_{n=0}^{N-1}X[m,n]\cdot g_{tx}(t-nT)\cdot e^{2\pi m\Delta f (t-nT)}, \tag{2}\]  
where \(g_{tx}(t)\) is the transmit pulse shaping function, \(T\) is the symbol duration, and \(\Delta f\) is the subcarrier spacing.
## 3 Materials and Methods
### Breast Ultrasound Report Classification Model
#### 3.4.1 Feature Extraction Module  
To perform subsequent classification operations, feature extraction from breast ultrasound images is essential. We employed ResNet50 as the backbone of the feature extraction module. To prevent overfitting, we utilized transfer learning to initialize the network parameters with pre-trained parameters and fine-tuned them. We opted for the non-medical dataset ImageNet as the pre-training dataset. Although the ImageNet and breast ultrasound datasets differ, most images share similar underlying features. Consequently, pre-training allows the model to possess a general feature extraction ability, thus diminishing the need for extensive datasets and reducing training time and memory costs. ResNet50 is composed of several similar residual blocks, with a mapping path connecting the input and output of these residual blocks. Based on ResNet50, we eliminated the final average pooling layer and fully connected layer from the original network structure while retaining only residual blocks using feature maps output by final residual block as inputs for the channel attention module. In order to simultaneously extract information from low-quality breast ultrasound images and high-quality generated images, we designed two feature extraction modules.
## 2 Theoretical Considerations
### Limitation in the Usage of the ESG-Cowl Pair for ASP Control  
In the usage of an ESG-cowl pair for the secondary actuator in the ASP control, the secondary path between the actuator and the error microphone is vulnerable to be exposed to an increased uncertainty especially when the temperature of the cowl panel of a car varies while driving. This is mainly caused by the nature of the vibro-acoustic property of a thin steel plate as its mechanical characteristics including the elastic modulus are dependent upon the temperature and, thus, its impulse response can be varied [14].  
Hence, the actual secondary path \(S(z)\) using the ESG-cowl pair can be perturbed due to the uncertainty, and this can be expressed as [12]  
\[S(z)=[1+B(z)]S_{0}(z), \tag{5}\]  
where \(S_{0}(z)\) is the nominal secondary path and \(B(z)\) is the fractional change due to uncertainty [12]. Assuming the secondary path model is designed as \(\hat{S}(z)\approx S_{0}(z)\), the error between the actual path \(S(z)\) and the path model \(\hat{S}(z)\) can exist. The larger the temperature variation, the greater the uncertainty and error, especially at higher frequencies.  
Such an increased error can affect the control performance and stability of the ASP algorithm. For noise canceling at lower engine orders, the ASP algorithm can work properly as the uncertainty in the secondary path is low such as C2. Thus, as plotted in Figure 2a, some booming noise at some engine speeds can be attenuated considerably although the achieved sound levels do not reach the target levels. However, for enhancing sound, the ASP algorithm may suffer from achieving the target levels when the engine orders are higher such as C9. As illustrated in Figure 2b, the amount of the gap between the target and the achieved levels can be very large at a higher engine speed range because the control logic is intentionally \"off\" to prevent from diverging of the ASP algorithm due to the increased uncertainty at higher frequencies.  
Therefore, as depicted in Figure 2c, a noble additive ASP approach with a feedforward enhancement that can reduce the level gap by generating an additional enriching sound is proposed in Section 2.3.
# Cyclic Elasto-Plastic Behaviour of 51 CrV4 Steel for Railway Parabolic Leaf Spring Design
## 4 Results and Discussion
### Determination of the Kinematic Hardening Properties
In the case where hysteresis loops of 50% of the total life were chosen, the RO cyclic curve described with \(K^{\prime}=1514.3\) MPa (more 4.09%), \(n^{\prime}=0.0790\) (more 16.20%), and \(\sigma^{\prime}_{y}\) of 731.5 MPa (less 7.49%) resulted in \(C_{1}=80\),097.1 MPa, \(\gamma_{1}=648.4\), \(C_{2}=20\),486.2 MPa, \(\gamma_{2}=164.9\), \(C_{3}=5650.1\) MPa, \(\gamma_{3}=40.64\), and \(C_{4}=2673.4\) MPa (presented in Table 4), whose highest differences occurred for constants \(C_{3}\) and \(C_{4}\). Note that in the case where the RO cyclic model parameters were fitted by estimation models using monotonic properties, for example the Modified Universal Slopes method, MUSM (with coefficients \(\sigma^{\prime}_{f}=2057.36\) MPa, \(\epsilon^{\prime}_{f}=0.2339\) exponents \(b^{\prime}_{f}=-0.09\), and \(c^{\prime}_{f}=-0.56\)[100]), this resulted in \(C_{1}=82\),787.4 MPa, \(\gamma_{1}=580.07\), \(C_{2}=22\),260.6 MPa, \(\gamma_{2}=136.5\), \(C_{3}=5835.24\) MPa, \(\gamma_{3}=31.29\), and \(C_{4}=2305.5\) MPa, with an \(RRMSE\) of 0.3167% and a cyclic yield strength of \(\sigma^{\prime}_{y}=579.1\) MPa (which resulted in a variation in the size of the elastic limit surface of \(R^{\prime}_{y}=-510.1\) MPa). Comparing both Chaboche kinematic data, it is verified that the constants \(C\) are in the same order of magnitude, except the constants \(\gamma\). These constants obtained from the experimental data at \(R_{\epsilon}=0\) tended to be lower than the \(R_{\epsilon}=-1\) value (the MUSM method). The highest reduction occurred in \(\gamma_{1}\), which was responsible for the first hardening zone and along the way was the zone most affected by the parameter \(n^{\prime}\). \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline  & \(\sigma^{\prime}_{y}\) & \(R_{y}\)\({}^{\prime}\) & \(K^{\prime}\) & \(n^{\prime}\) & \(C_{1}\) & \(C_{2}\) & \(C_{3}\) & \(C_{4}\) & \(RRMSE\)\({}^{*}\) \\  & [MPa] & [MPa] & [MPa] & [MPa] & [MPa] & [MPa] & \(\gamma_{1}\) & [MPa] & \(\gamma_{2}\) & [MPa] & \(\gamma_{3}\) & [MPa] & \% \\ \hline
50\% & 731.5 & \(-\)357.7 & 1514.3 & 0.0790 & 80,097.1 & 648.4 & 20,486.2 & 164.9 & 5650.1 & 40.64 & 2302.7 & 0.2594 \\
90\% & 676.7 & \(-\)412.5 & 1576.5 & 0.0918 & 81,701.2 & 610.2 & 22,035.4 & 159.1 & 6332.2 & 39.93 & 2673.4 & 0.2853 \\ Diff. & 7.49 & 15.32 & 4.09 & 16.20 & 2.00 & 5.89 & 7.56 & 3.49 & 12.07 & 1.75 & 13.87 & 9.98 \\ \hline \end{tabular} \({}^{*}\) RRMSE is the relative root mean square error.  
\end{table} 
Table 4: Hardening parameters that define the [PERSON]’s kinematic hardening model for steady-state cyclic conditions at 50 and 90% of the total life to failure. Figure 6: Evolution and decomposition of the back stress components with the plastic strain amplitude.
# Distributed Satellite Relay Cooperative Communication with Optimized Signal Space Dimension
## 3 Results
### Spectral Efficiency
The method proposed in this paper leads to a significant increase in throughput, but BER simulation performance is not completely consistent with theoretical analysis. This is because sometimes the calculated signaling (spatial) dimensions for aligned symbols result in the low minimum distance between the symbols, and this affects BER performance. This problem is overcome by adding redundant antennas at every user and calculating the corresponding precoding vectors to obtain the flexibility in the selection of orthogonal signaling dimensions as well as to simplify the decoding at the relay. The sum rate is used to characterize the channel capacity characteristics of all users in the system. As shown in Figure 10, the slope of the curve represents the approximate system degrees of freedom. The system transmission efficiency can be improved by increasing the number of users or sending more independent streams at the same time. In order to increase the degree of freedom of the system, traditional communication technologies must consume more time, frequency or airspace resources. The advantages brought by large-scale antennas cannot be fully exploited by using multiple access technology. The method proposed in this paper studies the superposition characteristics and signal spatial structure of signals in different degrees of freedom and designs separable superimposed signals through distribution characteristics to eliminate intersymbol interference. Any node in the satellite network may be the transmitter or receiver. The method can flexibly configure the number of antennas at the transceiver by combining with the existing schemes. When the number of antennas is greater than the method requirements, the antenna selection technology can be used to obtain the selection gain.
## 3 Test Results
### Insufficient Support Pressure
#### 3.2.4 Measurement of Soil Deformation with PIV  
The displacement field for different overburden-to-diameter ratios is compared in Figure 13, which is when the displacement of the faceplate is approximately 2 mm and the support pressure reaches its limit value in each buried depth. Usually, failure initiates near the tunnel face and propagates toward the ground surface until either a stabilizing arch is formed, or it reaches the ground surface causing a cavein [25]. For shallower tunnels located at C/D ratio equals to 0.5 and 1.0, a wedge-prism failure mechanism occurs in front of the tunnel face, and the failure zone has expanded to the ground surface while for deeper tunnels located at C/D ratio equaling to 1.5, it is difficult to expand to the ground surface which means the arch effect still exists [40]. For the latter, the ground movement appeared in a narrow vertical band only. Besides, at smaller overburden-to-diameter ratios, the extent of the chimney was wider, especially near the ground surface.  
Figure 12: Curves of the settlement and support pressure.  
Figure 13: Characteristic vector diagram of ground deformation under different buried depths (insufficient support pressure).
# Optical Technology for NFV Converged Networks
## 3 Silicon Photonics Devices in Optical Transport: Challenges and Opportunities  
Silicon photonics is a photonic integration technology that can exploit standardized Complementary Metal Oxide Semiconductor (CMOS) fabrication processes to produce optical components in high volumes with low manufacturing costs. Its transparency to wavelengths longer than 1.1 um makes silicon an attractive material for optical devices that work in the 1.3 and 1.55 um wavelength windows. Silicon photonic chips can include various functional blocks such as optical waveguides, variable optical attenuators, optical bandpass filters, optical switches, amplitude and phase optical modulators, and wavelength multiplexers and demultiplexers. However, there is a long road ahead before silicon can achieve, in photonics, the pervasiveness it has in digital integrated circuits. In particular, considerable research effort is spent on the following interwoven design issues: achieving low coupling loss between a silicon photonics chip and input and output optical fibers; coupling input light having an unknown polarization state to silicon photonics chips that can only sustain linearly polarized light, along the Transversal Electric (TE) propagation mode; including optical amplification functionalities on chip to mitigate coupling and propagation losses, and embed light sources; realizing cost effective packaging processes suitable of productions in high volumes.  
Figure 4: Ring topology [7].