esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion  
There is some controversy in the literature regarding the oral manifestations of NF1. [PERSON] et al. reported that oral manifestations are present in 4-7% of all cases [10], while other authors have reported much higher rates of oral findings [14; 15]. [PERSON] concluded that 66% of NF1 patients showed at least one oral manifestation related to the disease [14]. Moreover, a recent study indicated that oral manifestations are present in 3.4-92% of adult patients with NF1 [8]. Although there have been a number of reports in the literature regarding adult NF1 patients, few studies have evaluated the presence of oral manifestations in cases of paediatric NF1 [10].  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **NF1 Patients** & **Control Group** & \(p\) **Value** \\ \hline
**Shape Anomalies** & 18\% & 0\% & \textless{}0.001 \\ \hline
**Tooth** & 1\% & 2\% & 0.5 \\
**Agenesis** & 1\% & 4\% & 0.2 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Statistical comparisons between single dental abnormalities.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **NF1 Patients** & **Control Group** & \(p\) **Value** \\ \hline
**DMFT/dmft** & 3.0 & 2.2 & 0.090 \\ \hline
**Enamel defects** & 36\% & 15\% & 0.010 \\ \hline
**Malocclusion** & 52\% & 46\% & 0.240 \\ \hline
**Frenulum with low insertion** & 22\% & 17\% & \\ \hline
**Neurofibroma** & 4\% & 0 & 0.0043 \\ \hline
**Gingiva inflammation (CPI)** & 17\% & 15\% & 0.0423 \\ \hline
**Poor Oral Hygiene** & 41\% & 16\% & 0.0002 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Statistical comparisons between the oral conditions investigated in the two groups analyzed.  
The incidence of dental caries in NF1 patients (dmft = 3.0) was higher than that in healthy controls (dmft = 2.2) but without a statistically significant difference between two groups, in according with previous study [16]. [PERSON] et al. reported similar results in a study comparing 50 NF1 patients to 50 patients without NF1 [10].  
Other studies showed a significant difference between children with NF1 and healthy controls, in fact, a previous report by [PERSON] et al. and indicating an increased rate of dental caries in Canadian NF1 patients. However, this previous study was based on a questionnaire sent to families of children with NF1 and indicated an increased prevalence of caries in NF1 patients compared to unaffected siblings [17]. [PERSON] et al. explained the increase by referring to [PERSON]'s study indicating that individuals with NF1 have a lower mean serum 25-hydroxyvitamin D3 (vitamin D) concentration than those without NF1 [18]. Data obtained by clinical examination in the present study build on the results of [PERSON] et al. as dental caries was detected not only by a survey but through an objective intraoral exam. However, recent studies yielded contradictory results regarding caries in NF1. For example, [PERSON] et al. reported that increased caries is not a typical feature of NF1 [19]. Indeed, their study showed a cumulative prevalence rate (DMFT \(>\) 0) lower than that in the control group, probably due to increased efforts by parents to assist children with oral hygiene.
###### Abstract  
This article reports recent developments in modelling based on Finite Difference Time Domain (FDTD) and Finite Element Method (FEM) for dielectric resonator material measurement setups. In contrast to the methods of the dielectric resonator design, where analytical expansion into Bessel functions is used to solve the Maxwell equations, here the analytical information is used only to ensure the fixed angular variation of the fields, while in the longitudinal and radial direction space discretization is applied, that reduced the problem to 2D. Moreover, when the discretization is performed in time domain, full-wave electromagnetic solvers can be directly coupled to semiconductor drift-diffusion solvers to better understand and predict the behavior of the resonator with semiconductor-based samples. Herein, FDTD and frequency domain FEM approaches are applied to the modelling of dielectric samples and validated against the measurements within the 0.3% margin dictated by the IEC norm. Then a coupled in-house developed multiphysics time-domain FEM solver is employed in order to take the local conductivity changes under electromagnetic illumination into account. New methodologies are thereby demonstrated that open the way to new applications of the dielectric resonator measurements.  
m pacs: materials modelling; materials characterization; scanning microwave microscopy; dielectric resonators; electromagnetic modelling; semiconductor modelling; multiphysics modelling; frequency and time-domain methods; FEM; FDTD +
Footnote †: journal: Applied Physics Letters
## 5 Experimental Setup
### Routing Algorithms Used for Comparison  
For the sake of comparison, we selected the following routing algorithms:  
* **Epidemic**[15]--For this algorithm, every contact is an opportunity for the nodes to exchange all the messages stored in their buffers with each other. It is worth mentioning that, despite it achieving good performance, its routing strategy consumes many network resources. However, it is an interesting benchmark for comparison.  
* **PROPhet[14]--**This algorithm is based on determining the probability of meeting with the message destination. A node carrying a message will send it to another node if the delivery predictability of the destination of the message is higher at the other node. For every contact opportunity, this algorithm compares the probability of each node meeting the message destination node in the future. The node carrying a message will forward it to the other node if the latter has a higher meeting probability.
* **BUBBLE-RAP[12]--**This algorithm takes into account the concepts of nodes' popularity and centrality in the routing decisions. It selects high centrality nodes and community members related to the message destination node.
* **Friendship routing[13]--**This is the first algorithm that takes into account the friendship strength between the nodes in the routing decisions. It forwards messages to relay nodes having a greater friendship with the message destination.  
It is worth mentioning that these algorithms were not designed taking into account the existence of selfishness nodes in the network. In this way, in our simulations, we modified these algorithms to also consider the selfishness between the nodes. To achieve this aim, each of these algorithms takes advantage of our selfishness assessment system described in Section 4.2. Thus, if the relay node selected by them is assessed as a selfish node at that moment, the message is refused. Otherwise, they use their original routing decisions.
## 2 Materials and Methods
### IR Sensor-Based Satellite Products
Version 6 of the IMERG products was used for this study. All the details about the different MW products used in this study are given in Table 1.  
Carrier-to-Noise-Based Precipitation Product  
DATABOURG is a commercial product provided by the Databourg Systems Company based in Luxembourg. This product is based on broadband satellite Ka-band signals [22; 23]. Broadband satellite systems provide bidirectional communications between gateway stations and terminal users, allowing for internet provisioning [22]. The forward and return signals are monitored by the gateway, and a carrier-to-Noise (C/N) parameter is computed by measuring the quality of the communication link and received signal [22]. The C/N measurement was used in an artificial neural network technique to obtain a rain-regime classification required to determine a reference condition and the signal attenuation [53]. Finally, the rain rate was empirically deduced from the attenuation, with Ka-band signals being heavily attenuated in strong-intensity rain and less in light-rain conditions [53; 54]. In this study, we used the 5 min temporal resolution final product interpolated on a 1 km\({}^{2}\) grid.
# Analysis and Optimization of Output Low-Pass Filter
## 5 Experimental Validation of CL Filter Design
\begin{table}
\begin{tabular}{l l l l l l l} \hline \hline
**Setup** & **Filter** & \(Q\) & \(f_{R}\) & \(C_{n}\) & **Arrangement** & **THD** \\ \hline Prototype 1 & \(C_{F}\) & 2 & 649 Hz & 0.33 pu & & Resistive load & 9.2\% \\  & & 2 & 649 Hz & 0.33 pu & Resistive + grid & 16.0\% \\  & & & & Grid & 21.2\% \\ \hline Prototype 2 & \(C_{F}\) & 4 & 500 Hz & 0.12 pu & Resistive load & 3.3\% \\  & & & & & Resistive + grid & 6.1\% \\  & & & & Grid & 7.2\% \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Types and parameters of inverter output filters, including quality factor, resonance frequency, and normalized capacitance. The loading configurations for three different cases and their corresponding THD values are also included. Figure 22: Grid-connected inverter’s output voltage and current (**a**) simulation (**b**) measurement. The output filter configuration is FC 3. The parameters can be seen in Tables 5 and 6. The vertical and horizontal scales are 2 A, 20 V, and 5 ms per division.
## 3 Results
### Data Acquisition and Feature Extraction  
The resulting signals for the simulated conditions discussed in this paper are shown in Figure 6. As can be seen, there is a greater signal amplitude when the insulators are perforated and contaminated, this is because there is a shorter distance between the electrical potential and the ground, causing more partial discharges that generate ultrasonic noise. The distance is shorter because there is a shorter path from the conductor, where the electrical potential is applied, to the fixing pin that can be grounded and is inside the insulator. This can facilitate the development of partial discharges because with a shorter distance the electric field will be larger. A disruptive discharge does not need to circumvent the insulator's external surface until it reaches the pin, making the place more vulnerable.  
Figure 5: Flowchart of the used procedure presented in this paper. From the ultrasound data the features are extracted from.wav files. These features are then used to train the neural networks of interest, classifying the insulators using the double check technique.  
It is noticeable in Figure 6 that there is little visual difference between insulators with and without contamination, this makes it difficult to identify which component has greater contamination, and thus a greater chance of having a failure.  
As mentioned earlier, more significant contamination makes the surface more conductive and can leave the component more vulnerable to irreversible failure. Perforation is a failure in which the component needs to be replaced because it has lost its insulation properties, while contaminated insulators can be washed, returning their characteristics necessary for their correct functioning. For this reason, identifying perforated insulators is extremely important for electric utility operators, thus ensuring network reliability.  
Figure 6: Raw ultrasound recorded signals: (**A**) insulator without perforation and without contaminants; (**B**) insulator without perforation and with contaminants; (**C**) insulator without perforation and with contaminants (with added salt); (**D**) perforated insulator without contaminants; (**E**) perforated wet insulator; (**F**) perforated contaminated insulator.  
After obtaining the signals, the features were extracted following the methodology of Section 2.3. The extracted features for 1 st case are illustrated in Figure 7.
## 3 Analysis of the Working Ranges of Inerter in Different Conditions
### Response Characteristics of Primary System for Different Cases  
Based on Table 1, there are six ranges of inerter-mass ratio \(\beta\), and the parameters selected are shown in the Table 2. It should be noted that \(\mu L^{2}\) can use a range of values; here, we choose a value in the interval to calculate the optimal parameters. The normalized amplitude-frequency curves for different cases are shown in Figure 4. When \(\alpha_{1}>0\), the control effect of DVA is the best for case 1c and the worst for case 1a. When \(\alpha_{1}<0\), the damping effect of DVA is the best for case 2c and the worst for case 2a. In case 1c and case 2c, the corresponding grounded stiffness \(\alpha_{2}\) is positive. However, case 1c and case 2c require a high value of \(\mu L^{2}\). Whether positive stiffness is selected as grounded stiffness should be based on the actual situation.  
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Different Cases** & **The Sign of \(\alpha_{1}\)** & **The Sign of \(\alpha_{2}\)** & **Ranges of \(\mu L^{2}\)** & **Ranges of \(\beta\)** \\ \hline case 1a & \(\alpha_{1}>0\) & \(\alpha_{2}\leq 0\) & \((0,1]\) & \(0<\beta\leq\frac{1-\mu L^{2}}{\mu L^{2}}\) \\ case 1b & \(\alpha_{1}>0\) & \(\alpha_{2}>0\) & \((0,1]\) & \(\frac{1-\mu L^{2}}{\mu L^{2}}<\beta<\frac{4-\mu L^{2}}{\mu L^{2}}\) \\ case 1c & \(\alpha_{1}>0\) & \(\alpha_{2}>0\) & \((1,4)\) & \(0<\beta<\frac{4-\mu L^{2}}{\mu L^{2}}\) \\ case 2a & \(\alpha_{1}<0\) & \(\alpha_{2}\leq 0\) & \((0,3-2\sqrt{2}]\) & \(0<\beta\leq\frac{3-2\sqrt{2}-\mu L^{2}}{\mu L^{2}}\) \\ case 2b & \(\alpha_{1}<0\) & \(\alpha_{2}>0\) & \((0,3-2\sqrt{2}]\) & \(\frac{3-2\sqrt{2}-\mu L^{2}}{\mu L^{2}}<\beta<\frac{2-\mu L^{2}}{\mu LTo gain the optimal reduction vibration effect of the vibration absorber under different optimum grounded stiffness ratios, Figure 5 shows the dimensionless transient response \(x_{1}/x_{0}\) of the primary system under the six sets of parameters in Table 2. The initial displacement is selected as \(x_{0}=1\) m. The fourth-order Runge-Kutta method with a fixed time step of \(10^{-4}\) s is used for simulation. The primary system vibration attenuation speed under case 1c is obviously faster than that of the other cases. In all cases, shimmy will not occur after the system is stable.
# Research on the Flight Performance of Biomimetic Moth Based on Flapping Function Control
## 4 Flight Experiment and Result Analysis of Biomimetic Flapping-Wing Aircraft
### Lift Test  
#### 4.3.1 Experiment 1: Impact of Flapping Amplitude on Flight Capability of Flapping-Wing Aircraft  
Three flight tests were carried out using the flight controller to input parameters, as shown in Table 8.  
Figure 12: Flight Experiment Process Diagram.  
When the flapping amplitude is \(54^{\circ}\), the flight trajectory of the flapping-wing aircraft is horizontal, indicating that it generates sufficient and stable lift. The position of the flapping-wing aircraft is evenly distributed and scattered over time, indicating that it generates a large propulsive force. In general, with a flapping amplitude of around \(45^{\circ}\), the flapping-wing aircraft exhibits robust flight capabilities.  
When the flapping amplitude is \(45^{\circ}\), the flight trajectory of the flapping-wing aircraft slopes downward after fluctuating, indicating that the generated lift is just not enough to overcome its own weight and cannot fly stably. The position of the flapping-wing aircraft is evenly distributed and scattered over time, indicating that it generates a large propulsive force. In general, with a flapping amplitude of around \(45^{\circ}\), the flapping-wing aircraft exhibits subpar flight capabilities.  
When the flapping amplitude is \(36^{\circ}\), the flight trajectory of the flapping-wing aircraft slopes downward severely, indicating that the generated lift is seriously insufficient. The severe downward slope of the flight trajectory indicates that the position distribution of the flapping-wing aircraft over time does not signify the generation of propulsive force but merely indicates that the generated lift is insufficient to mitigate its descent rate. In general, with a flapping amplitude of around \(36^{\circ}\), the flapping-wing aircraft exhibits extremely subpar flight capabilities.  
In summary, the amplitude of flapping motion impacts the flight capability of the flapping-wing aircraft, and increasing the flapping amplitude can enable the aircraft to  
Figure 13: Results of Experiment 1 in Lift Test. (**a**) diagram with a \(54^{\circ}\) flapping amplitude; (**b**) diagram with a \(45^{\circ}\) flapping amplitude; (**c**) diagram with a \(36^{\circ}\) flapping amplitude; (**d**) Merged diagram of flight trajectories.  
\begin{table}
\begin{tabular}{c c c c} \hline
**Control Parameters** & **(a)** & **(b)** & **(c)** \\ \hline Flapping frequency & \(4\,\mathrm{Hz}\) & \(4\,\mathrm{Hz}\) & \(4\,\mathrm{Hz}\) \\ Mid-position angle & \(5^{\circ}\) & \(5^{\circ}\) & \(5^{\circ}\) \\ Flapping-wing aircraft & \(54^{\circ}\) & \(45^{\circ}\) & \(36^{\circ}\) \\ Initial pitch angle & \(10^{\circ}\) & \(10^{\circ}\) & \(10^{\circ}\) \\ \hline \end{tabular}
\end{table}
Table 8: Control parameter table of experiment 1.  
obtain better flight performance. This is consistent with the results of the simulation calculation, indicating that the simulation results are basically accurate.
# A Fast Acquisition Algorithm for Hybrid Signals of 5G and BeiDou B1
## 1 Introduction
Then, we propose a hybrid signal acquisition algorithm for BeiDou signals and 5G signals which takes advantage of the signal regime proximity and signal frequency proximity of BeiDou and 5G signals, and provide a detailed analysis of the performance improvement of the algorithm at the levels of signal capture accuracy, capture sensitivity, capture time, and capture probability. Finally, we conduct hybrid signal receiver performance testing and verification, introduce the basic hardware and software architecture of the hybrid signal receiver, build a test environment to conduct practical testing of the acquisition algorithm, and verify the experimental effect of the algorithm. In brief, the main contributions of our proposed method are as follows:  
1. We analyze the BeiDou and 5G system signals, summarize the 5G frequency bands close to the BeiDou signals, and discuss the NR spectrum characteristics and radiation characteristics of 5G. Finally, the current ITU protection standard for navigation signals is analyzed. 2. We provide a detailed analysis of the mixed-signal regime and frequency planning and design a hybrid receiver architecture compatible with both signals, and hardware design for the RF front-end circuit, clock circuit, baseband circuit, and interface circuit. 3. We propose a strong-correlation-based SC-PMF-FFT fast capture algorithm, which utilizes the strong correlation of signal broadcast on the B1 frequency point of BeiDou, performs fast decoding phase ambiguity processing for the strongly correlated signals from B1I to B1C, and reuses the structure of the CDMA system signal capture algorithm to complete the fast capture of 5G signals using an OFDM system.
# TRAP: A Three-Way Handshake Server for TCP Connection Establishment
## 3 Related Work
### SYN Proxy  
In order to distinguish legitimate clients and attacking clients, we can setup an intermediate server to filter the connection. If a client completes a TCP three-way handshake with the intermediate server, we consider this client as a legitimate client, and then the intermediate server will hand off the established socket to the backend servers. The intermediate server will translate the sequence number and acknowledgement number between the clients and the backend servers. We call this infrastructure a SYN proxy.  
SHAK [16] is an implementation based on this approach. By installing a separate front-end server between the back-end servers and the clients, the front-end server not only acts as a SYN proxy server, but also a load balancer. When a client connects to the front-end node, it chooses a back-end server to handle the request and reply to the clients with a \"address remap\" ACK packet. The client will then modify its stored socket destination address to the new one, handing off the socket.  
Similar socket handoff schemes were proposed by [PERSON], in which a SYN-ACK and TCP state are translated via an intermediate proxy server [17]. In the implementation, the TCP/IP protocol stack was heavily modified to accommodate the project needs.  
Figure 5: Illustration of TCP Cookies.  
However, these methods require extensive modification to the kernel and the TCP/IP stack, limiting its appliance across devices. On situations that modify the clients' kernel is not appropriate, this causes implementation difficulties.  
In 2006, [PERSON] and [PERSON] proposed a three-layer defense model against DDoS attacks. When a client attempts to connect to the SYN-Proxy enabled server, a SYN is sent to the intermediate firewall. The firewall will then send back a SYN-ACK packet, finishing the TCP three way handshake with the client [18]. If a client successfully established a connection with the firewall (thus proving itself not being a SYN flood attacker), the firewall then connects to a real server. The firewall acts as a transparent proxy server afterwards, only translating the TCP sequence number; hence, the name SYN Proxy.  
This method was implemented in the Netfilter framework, and is released along with the Linux kernel version 3.12 (2013) as SYNPROXY. SYNPROXY depends on SYN cookies and TCP timestamps [19].  
This architecture can mitigate moderate SYN flood attacks; however, the added components will make the server harder to maintain due to the complex design. The sequence number translating process cannot be load-balanced using multiple firewalls due to the nature of sequence number synchronization.
# Crop Growth Stage GPP-Driven Spectral Model for Evaluation of Cultivated Land Quality Using GA-BPNN
## 3 Results  
### Downscaling of MODIS GPPs by EBK Interpolation  
To improve the accuracy of evaluating CLQ, 2011-2015 MODIS-GPPs with the 500 m spatial resolution were scaled downs to a 30 m spatial resolution using the EBK interpolation. Compared with the original standard MODIS-GPP for the same date, the downscaled MODIS-GPP on the 233 rd to 289 th day in 2013 shows more detailed information (Figure 3), indicating that the quality of the downscaled data is higher than the original standard data.  
Figure 3: The spatial distribution maps of the cumulative GPP from the 233 rd to 289 th days in the study area in 2013: (**a**) 500 m original standard MODIS-GPPs and (**b**) 30 m MODIS-GPPs interpolated by the Empirical Bayes Kriging (EBK) method.  
Figure 2: The Flow chart of GA-BPNN.  
Table 2 shows the comparison results of MODIS-GPPs between the spatial resolutions of 500 m and 30 m based on the field observations (dry biomass) of 30 samples plots. The average MODIS-GPP was 475.09 g C/m\({}^{2}\) for the 500 m, 472.73 g C/m\({}^{2}\) for 30 m, and the average field observation was 465.49 g/m\({}^{2}\). Compared with the field observations, the 30 m spatial resolution MODIS GPP has a root mean square error (RMSE) of 7.43 and a normalized RMSE (NRMSE) of 1.59%, while the corresponding values for the 500 m MODIS GPP were 33.43 and 7.18%. The results imply that the downscaled MODIS-GPPs by EBK interpolation can reflect the productivity of cultivated land more accurately than the unscaled MODIS-GPPs.