esa-sceva/satcom-chunk-collection huggingface dataset:
# The Effect of Space Objects on Ionospheric Observations: Perspective of SYISR  
[PERSON]  
1,2,3  
[PERSON]  
1,2,3,*  
[PERSON]  
1,2,3,  
bodies in optical observations based on the StarLink constellation [5; 6]. Meanwhile, simulations have been performed to analyze satellite light pollution with respect to geographic location and time [7; 8; 9]. Similar problems have been faced in radio observations. The disturbances from the space objects in ISR's ionosphere measurements are well-known [10; 11]. An automated detection method of satellite contamination has been introduced to check the data for anomalous spectra and isolate those cases [11]. Unlike scattering sunlight in optical observations, the space objects receive and scatter the transmitted radio signal when they are within the radar beam. If the scattering signal is sufficiently large to be detected, the space objects will appear in the original signal and causes an abnormal radar echo. If the pollution caused by space objects too frequently occurs, it will cause the failure of observations.  
Incoherent scatter radar (ISR), usually with high power and antenna gain, plays an important role in ground-based radio facilities for ionosphere research. High-performance incoherent scatter radars usually also have excellent space object detection capabilities and can find centimeter-level space objects at a kilometer height without integration [12; 13; 14]. The Sanya incoherent scatter radar (SYIS, 18.3\({}^{\circ}\)N, 109.6\({}^{\circ}\)E) is the new generation of incoherent scatter radar developed by China [15; 16]. It works at the ultra-high frequency band (\(\sim\)440 MHz). The active digital phased array antenna of SYISR realizes a microsecond-level beam switching capability by digital beam forming technology, which making the radar capable of fast wide-region detection. To ensure high-quality ionosphere results, the space object pollution in the radar measurements cannot be ignored. It is necessary to identify the impact of space object pollution on SYISR ionosphere observations and handle the obvious effects. Meanwhile, the assessment of the effects from large constellation satellites is important for understanding and handling the potential threats of this type of pollution, which is the main aim of the paper.  
This section summarizes the motivations of our study. In Section 2, we describe in detail the space objects found in the ionosphere observations when we used different waveforms during the experiment. To eliminate the effect of space object pollution, we adopt a special process to remove the obvious space objects from the data, which is shown in Section 3. Furthermore, we analyze the impacts of the increasing number of satellites, due to the StarLink constellation, on SYISR observations. The size of space objects with the risk of pollution after the special removal process is presented in Section 4.
###### Abstract
In addition, GNSS satellites determine atmospheric water vapor with a spatial resolution that varies within tens of kilometers based on the number of receiving stations and a temporal resolution of seconds to an hour [10]. Therefore, improving the accuracy and spatiotemporal resolution still remains an essential task for the measurements of _TWVC_ in addition to the _TEC_.
###### Abstract  
High-speed wireless communication devices need antennas to operate at multiple frequencies with high gain. The need for such antennas is increasing day by day. The proposed metamaterial superstrate antenna gives a high gain and multiband performance, which is required in high-speed wireless communication devices. The designed antenna is also applicable for C- and X-band communication devices. The structure consists of a simple patch and multiple split-ring resonator metamaterials on the superstrate region. The performance optimization is achieved by adjusting the feed position, varying the height of the superstrate layer and changing the thickness of metamaterial rings. The proposed design is analyzed for 4 GHz to 12 GHz. The performance analysis regarding the reflection coefficient, directivity, gain and electric field is observed. FR4 is used as a dielectric material that makes the design low-cost. The proposed design represents a minimum reflection coefficient response of \(-\)49 dB, a bandwidth of 490 MHz, a maximum electric field of 1.29 \(\times\) 10\({}^{4}\) v/m, good directivity and a broader radiation pattern. The comparison between the simulated and the measured results is incorporated in the manuscript. A comparison of the presented design with other articles is included to check the novelty of the design. The proposed method helps to target applications such as WiFi, Earth observation and microwave links.  
metamaterial; high gain; multiband; bandwidth; directivity Article
# Statistics on Typhoon Intensity and Rice Damage in Vietnam and the Philippines
## Discussion
### Rice Damage Not Solely Due to Strong Winds
Besides ERM, the storm surge hazard potential index (SSHPI) has been proposed to estimate typhoon-induced peak surge levels along the coastline. To predict surge potential, regional bathymetry information is combined with 10 min maximum wind speed, a radius of 50 kt wind, translation speed, and coastal geometry. SSHPI can provide an instantaneous measure of a typhoon's storm surge potential and measure the extent of a storm surge in a given location [30]. The magnitude and extent of the surge event can then be compared to the extent of rice damage or the volume of rice produce lost to obtain insights into the relationship between typhoon intensity and storm damage.
## 3 Result and Analysis
### Effect of Erosion under Different Conditions
#### 3.2.4 Effect of Gate Opening on Erosion  
Gate opening is one of the main parameters of gate operation. Gate opening will affect the characteristics of water flow in the spillway, so it will also affect the erosion wear.  
Figure 13: Velocity component of particle impact.  
Under the condition of water depth of 6.5 m, the erosion wear of spillway with the opening of 1 m, 2 m, 3 m, 4 m, 5 m and 6.5 m is simulated. The sediment concentration is 3.2 kg/m\({}^{3}\), the particle size of sediment is 0.025 mm, and the inlet velocity of the fluid domain is 5 m/s. The cloud diagram of spillway erosion results is shown in Figure 14. As the opening degree of the gate increases, the location where the maximum erosion occurs at the bottom of the spillway gradually moves backward, and the overall distribution of the erosion area has no obvious rule. The change in gate erosion with the opening is mainly reflected in that of the increase in the gate opening, the contact area between gate and water becomes smaller, and the corresponding erosion area becomes smaller.  
The relationship between the maximum erosion amount and the opening of the gate is shown in Figure 15. The erosion amount at the bottom of the spillway has a negative linear correlation with the opening of the gate when the opening of the gate is between 1 m and 3 m and tends to be stable when the opening of the gate surface reaches 3 m.  
The research objects of the other literature are all related to the influence of gate opening to offset erosion. According to the research results of [PERSON] [36], gate opening will change the flow field velocity. As this paper concludes in Section 3.2.3, flow velocity  
Figure 14: Erosion cloud diagram of spillway with different gate openings.  
Figure 15: Relationship between erosion and gate opening.  
also affects erosion. As shown in Figure 16, the change in gate opening causes significant changes in the flow velocity around the gate. When the gate opening is 1 m, 3 m and 6.5 m, the corresponding flow velocity behind the spillway gate is 13.7 m/s, 11.1 m/s and 9.52 m/s, respectively. In essence, the change in gate opening causes the change of flow velocity behind the gate, which leads to the change in erosion amount.
## 5 Simulation Calculation Model of Grouting
### Analysis of Influencing Factors of Slurry Diffusion Radius
Through the above method, the empirical formula between the diffusion radius R and the three influencing factors can be obtained: \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Specimen Name** & \begin{tabular}{c} **Injection** \\ **Pressure/MPa** \\ \end{tabular} & \begin{tabular}{c} **Drilling** \\ **Rate/m-min\({}^{-1}\)** \\ \end{tabular} & \
\begin{tabular}{c} **Slurry** \\ **Viscosity/mPa*s** \\ \end{tabular} &
\begin{tabular}{c} **Radius of Grouting** \\ **Spread/cm** \\ \end{tabular} \\ \hline
2-2-83.3 & 0.2 & 0.2 & 83.3 & 65.6 \\
2-3-416.6 & 0.2 & 0.3 & 416.6 & 16.3 \\
2-4-138.9 & 0.2 & 0.4 & 138.9 & 33.7 \\
3-2-138.9 & 0.3 & 0.2 & 138.9 & 58.3 \\
3-3-83.3 & 0.3 & 0.3 & 83.3 & 77.3 \\
3-4-416.6 & 0.3 & 0.4 & 416.6 & 19.2 \\
4-2-416.6 & 0.4 & 0.2 & 416.6 & 39.5 \\
4-3-138.9 & 0.4 & 0.3 & 138.9 & 67.6 \\
4-4-83.3 & 0.4 & 0.4 & 83.3 & 84.7 \\ \hline \hline \end{tabular}
\end{table} 
Table 11: Numerical simulation test scheme and simulation results. \[ \begin{cases}R=29.34p^{0.831}s^{-0.423}\mu^{-0.715}\\ \beta_{p}=0.439,\beta_{s}=-0.149\\ \beta_{\mu}=-0.841,r^{2}=0.988\end{cases}  \tag{9}\]  
In the above equation, \(\beta\), \(\beta\)s, \(\beta\mu\) is the standardized regression coefficients of grouting diffusion radius to grouting pressure, drilling speed and slurry viscosity; \(r^{2}\) is the multiple correlation coefficient. The results indicate that slurry viscosity has the greatest impact on the grouting diffusion radius, with grouting pressure being the second most influential factor, whereas drilling speed contributes relatively little to the slurry diffusion radius.
## 3 Results
### Flow Cytometric Analysis  
To study the effect of the extract on the cell cycle, flow cytometric analysis to evaluate the distribution of the cells in different phases of the cell cycle was performed. HeLa cancer cells were treated for 48 h with an extract of in vitro cultured _C. vulgare_ plants at concentrations of 600 \(\upmu\)g/mL and 800 \(\upmu\)g/mL and were analyzed using a Becton Dickinson flow cytometer according to a standard protocol. The obtained results show that treatment with _C. vulgare_ extract induces a redistribution of the cancer cells in the different phases of the cell cycle (Figure 6).  
As can be seen from the data presented, treatment with _C. vulgare_ extract resulted in a significant decrease in the percentage of cells in the G1 phase, while a statistically significant increase in the number of cells in the S and G2/M phases of the cell cycle was found. Furthermore, treatment with the extract at a concentration of 800 \(\upmu\)g/mL showed a statistically significant increase in the percentage of cells with a lower DNA content (<2 N).  
Figure 5: Fluorescence microscopy of the apoptotic alterations in HeLa cervical carcinoma cells induced by the extract of _C. vulgare_ in vitro cultured plants. (**a**) Control untreated cells; (**b**) cells treated with _C. vulgare_ extract 600 \(\upmu\)g/mL; and (**c**) cells treated with _C. vulgare_ extract and 800 \(\upmu\)g/mL Annexin V/propidium iodide staining. Fluorescence microscopy; objective 40\(\times\).
# Deep Representation of a Normal Map for Screen-Space Fluid Rendering
## 5 Experiments and Analysis
### Auxiliary Features  
As mentioned above, our model takes a normal map generated using the screen-space method as input and generates a highly refined normal map like a normal map generated using marching-cube method. Considering this, it is reasonable that only a normal map is used for training. However, recent deep learning-based research has reported that adopting auxiliary features for training improves training quality [37]. Accordingly, we introduced auxiliary features, including a depth map and a blurred depth map. To justify our choice, we investigated the effect of these auxiliary features.  
Figure 9 presents the results obtained using the same parameters and conditions with and without the auxiliary features. The images were generated by our model after 100 training epochs with the same training dataset. Without the auxiliary features (depth and blurred depth), the results appear faint near the edges, and some noisy artifacts exist. Although adding only one auxiliary feature (depth or blurred depth) produced better results than the results obtained without either, we decided to add both features because the result was improved at the point where the particles are tapered.  
We can hypothesize ways in which these auxiliary features can improve the training quality. The surface edge is typically generated when the distribution of the surface normal is diverse. However, there are some cases where the surface normal distribution is less varied (Figure 10). We assume that this is because the non-blurred depth map has a depth value in each pixel, and the surface edge can be improved (see the red circle in Figure 9). Because the blur method smoothens the distribution of the surface normal, the blurred depth map has information that improves the bumpy surface (see the yellow circle in Figure 9).  
Figure 8: Model architecture: (**left**) the model’s generator architecture and (**right**) the discriminator architecture. \(y\) is the conditional data, \(z\) is the noise data, \(\widetilde{x}\) is the generated data, and \(x\) is the target data.  
Figure 9: Comparisons of the results obtained with and without the auxiliary features.
## 3 Devices Setup and Field Test  
### Field Test Instruments and Related Equipment  
The test was conducted using hydraulic jacks and a hydraulic pump system, a DH612 sensor, an electric displacement meter, a computer, a DHDAS dynamic signal acquisition and analysis system, DHMA modal analysis software, and displacement dynamic acquisition and analysis software. The hydraulic pump system generates horizontal initial displacement of the isolation layer and a DH612 sensor is used to detect the floor's vibration signal, including speed and acceleration. The electric displacement meter is installed at the upper pier position on the I, I2, I3, and I4 isolation bearings (Figure 5) to monitor and record the horizontal displacement of the isolation layer and then transmit the measured displacement of the isolation layer to the displacement acquisition and analysis software. The data acquisition center comprises a data acquisition box and computer, which are used to load the dynamic signal acquisition and analysis system, the modal analysis software, and the displacement dynamic acquisition and analysis software. Figure 9 illustrates field testing instruments and related equipment.
# FBG-Based Monitoring of Geohazards: Current Status and Trends
## 3 Development of FBG-Based Geohazard Monitoring Systems  
As mentioned before, geohazard monitoring faces myriad challenges. In the past two decades, a number of FBG sensors and systems have been developed for providing valuable and timely information related to geohazards. Using quasi-distributed FBG sensors, the variations of temperatures, displacements, loads, earth pressures, pore water pressures and soil moistures can be captured with high accuracy.
# Research on Clock Synchronization of Data Acquisition Based on NoC
## 3 The Proposed Design Clock Synchronization Scheme
### Overall Design
A 2D mesh topology of nine routing nodes is taken as the example to design the corresponding router clock synchronization scheme, as shown in Figure 6.  
Firstly, the clock synchronization system uses the improved PTP to determine the clock offset between the master and slave clocks, and implement the rough synchronization. Secondly, DDMMTD is used to determine the phase relationship between master and slave clocks to achieve the fine synchronization. Finally, the phase of the slave clock is adjusted according to the TI-ADC sampling interval. In addition, there is a link delay between the master clock node and slave clock node during rough synchronization. Clock messages exchanged between master clock node R5 and slave clock nodes R1, R3, R7, and R9 need to be forwarded through transparent clock node R2 or R8. When solving the link delay and clock offset between the master and slave nodes, the message resident time of the forwarding node should be deducted, as shown in Figure 7.  
Figure 6: Data acquisition clock synchronization scheme. The central routing node R5 is the master node of the clock synchronization system, while R1, R3, R4, R6, R7, and R9 are slave nodes, and R2 and R8 are transparent nodes. All slave nodes’ clocks use the master node’s clock as a reference for clock and phase adjustment, while all transparent nodes’ clocks do not need clock synchronization since their clocks are only used as working clocks within the node. Therefore, the new link delay and clock offset between the master and slave nodes are shown in Equations (7) and (8) respectively. \[delay=\frac{(T_{2}-t_{2}-T_{1})+T_{4}-t_{5}-T_{3}}{2} \tag{7}\]  
\[offset=\frac{(T_{2}-t_{2}-T_{1})-T_{4}-t_{5}-T_{3}}{2} \tag{8}\]  
After determining the clock offset and the link delay between the master and slave nodes, the slave clock is roughly synchronized by subtracting the offset from the time. Then, DDMTD technology is used to determine the phases of the master and slave clocks, and achieve the fine synchronization of the slave clock.
# Lane-Level Traffic Flow Prediction with Heterogeneous Data and Dynamic Graphs
## 3 Experiments and Results
### Performance Comparison
#### 3.4.4 Training Cost Comparison  
As well as focusing on the accuracy of the algorithms, we compared the training costs as an indicator of the computational efficiency of T-GCN, ASTGCN, ST-AFN, and the heterogeneous graph convolution network. As shown in Table 5, the ST-AFN method showed the fastest training speed due to its efficient attention mechanism, and ASTGCN, with a multi-branched network, took the most time. Since the network structure of T-GCN is relatively simple, it also performed well with respect to time cost, though it was slightly inferior to ST-AFN. Regarding the heterogeneous graph convolution network, the performance was also good in terms of time consumption, and not too much time was expended.
## 2 Materials and Methods
### Screening Process and Search Strategy  
Two independent researchers ([PERSON] and CGP) conducted an electronic and manual search of the literature in several databases, including PubMed, Web of Science, EMBASE, and the Cochrane Central Register of Controlled Trials, for articles up to November 2023. Ethics approval was not required for this present review. For the selected databases, a combination of terms (MeSH) and keywords was used, where \"[mh]\" and \"[tiab]\" represent MeSH terms and a title/abstract search, as depicted in Table 1, Appendices A and B.  
Furthermore, a hand search was carried out in oral-surgery-, periodontal-, and orthodontics-related journals, which included the _Journal of Periodontology_, _Journal of Clinical Periodontology_, _The Angle Orthodontist_, _Dental Press Journal of Orthodontics_, _American Journal of Orthodontics and Dentofacial Orthopedics_, _Journal of Oral and Maxillofacial Surgery_, _Oraland Maxillofacial Surgery_, and _Journal of Cranio-Maxillo-Facial Surgery_, to ensure a thorough screening process up to November 2023. Additionally, we reviewed the reference lists of the included articles for full-text analysis and literature review articles. Google Scholar was used to identify potential articles among gray literature that were not included in the listed databases.  
\begin{table}
\begin{tabular}{p{34.1 pt} p{284.5 pt}} \hline \hline Focused question & Do adult patients with transverse maxillary deficiencies (P) treated with SARME (I) compared to NSRME (C) have an impact on the periodontal attachment apparatus (O) as observed in human trials, cohorts, and case series studies (S)? \\ \hline \hline PICOS & Population & Patients with transverse maxillary deficiencies \\ \cline{2-3}  & Intervention & SARME \\ \cline{2-3}  & Comparison & NSRME \\ \cline{2-3}  & Outcomes & PDs, BOP, CAL, REC, CCH, KTW, mobility, PI, GI, MBL, root resorption, dentinal hypersensitivity, and hard/soft tissue deficiencies \\ \cline{2-3}  & Study design & RCTs, prospective/retrospective cohorts, and case series \\ \hline \hline \end{tabular}
\end{table}
Table 1: Search strategy and selection criteria.
## 3 Results and Discussion
### Ion Exchange Runs  
#### 3.2.1 Preliminary Runs  
As previously pointed out, the effect of the pH on the removal process was checked, prior to further investigating the behavior of the SMNZs, by performing some preliminary tests at different pH values. In fact, it is well known that as the pH changes, both the surface charge of the SMNZ and the As speciation will change. The effect of pH on the As species uptake is reported in Figure 3 for CLI-Br and PHI-Br samples.  
From the comparison of the equilibrium values obtained at different pH, it can be observed that the higher uptake occurs at pH = 7 for both SMNZs. These results, supported by literature data [41], seem to indicate that the SMZ is selective towards HAsO\({}_{4}\)\({}^{2-}\) against H\({}_{2}\)AsO\({}_{4}\)\({}^{-}\), because the concentration of the former increases with the pH, while the positive charge (and consequently its ability to remove anions) of the SMZ decreases with the pH (actually, as previously reported [57], the point of zero charge (PZC) of the modified zeolites is around 8). The most favorable pH condition is then met when (at pH around 7) the higher amount of HAsO\({}_{4}\)\({}^{2-}\) (the species with the greatest affinity towards the exchanger) is associated with the positively charged surface of the exchanger [41]. Concerning the CLI-Cl and PHI-Cl samples, similar results have been obtained (here not reported for the sake of brevity).