esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Study Area and Data  
### Study Area  
Tianshui City is located in the southeastern part of Gansu Province, in the middle reaches of the Weihe River, at the junction of the Shaanxi, Gansu, and Sichuan Provinces. National Highways 310 and 316 pass through the city, and urban-rural roads are well-developed, providing convenient transportation [16]. Based on the spatial distribution characteristics of landslides within the city and the coverage conditions of SAR data, this study selects the central region of Tianshui City as the research area, with geographical coordinates ranging from 36\({}^{\circ}\)29\({}^{\prime}\) N to 36\({}^{\circ}\)46\({}^{\prime}\) N and from 105\({}^{\circ}\)51\({}^{\prime}\) E to 105\({}^{\circ}\)22\({}^{\prime}\) E. The study area primarily covers the northeastern part of Maiji District, the northern part of Qinzhou District, and the adjacent areas of Gangu County, Qingan County, and Qingshui County, with a total area of approximately 1406.05 km\({}^{2}\). The geographical location of the study area is shown in Figure 1.  
The study area is located in the transitional zone of the Longxi Loess Plateau, featuring significant terrain relief. Within the area, there are valley regions along the Weihe River and its tributary, the Jiahe River, presenting a typical mountain valley basin loess mound landform. As shown in Figure 2, the study area is situated at the complex intersection of the middle segment of the Yinchuan-Tianshui-Wudu belt in the Liupan Mountains' north-south seismic zone and the central part of the Tianshui-Lanzhou belt along the northern margin of the Qinling Mountains' east-west seismic zone [17; 18; 19]. This region has a complicated seismic background with frequent activities. Due to the geological structure mainly consisting of loess, the rock layers are predominantly composed of weak mudstone and loess-mixed deposits. These formations are loosely structured and widely distributed, making them prone to geological disasters. Due to geological conditions, Tianshui City has a fragile geological environment and is a high-risk area prone to frequent geological disasters, mainly including landslides, collapses, and debris flows. On 23 July 2013, the city experienced a severe rainstorm, which triggered widespread landslides disasters that posed a serious threat to the lives and property of local residents [20]. Geological hazards have become a major constraint on urban development, making disaster prevention and mitigation a challenging task.  
Figure 1: Map of the study area. The red areas in the image represent high-altitude regions, while the blue areas indicate low-altitude regions. The color gradient from red to blue reflects the transition from higher to lower elevations. The blue dots mark locations where landslides have occurred historically.  
Figure 2: 1:200,000 geological map in study area.
# Statistics on Typhoon Intensity and Rice Damage in Vietnam and the Philippines
## 3 Results
### Area of Rice Crops Damaged  
The average area of rice crops damaged per typhoon event from 1970 to 2018 was higher in the Philippines compared to Vietnam. Notably, Vietnam had more data on areal losses (66 data points) as compared to the Philippines (26 data points). The average area of rice damaged per typhoon event ranged from 42,407 ha in Vietnam (range: 122-357,815 ha) to 83,571 ha in the Philippines (range: 85-425,134 ha). In Vietnam, the least damage was from Typhoon Vamco (2015), while the most damage was from Typhoon Frankie (1996), and both were classed as tropical storms based on their landfall wind speed. Conversely, the typhoon that caused the least damage was Rammasun in 2008, while the sole Category 4 storm in the Philippines in 2010 (Typhoon Megj) caused the most damage to the rice area in the Philippines (Supplementary Material S2). In Vietnam, tropical storms caused more damage than Category 1 events as the average area of rice damaged by typhoons in Vietnam follows the order: Category 1  
Figure 3: Frequency of cyclone-induced rice damage in the Philippines from 1970 to 2018. Rice damage was often reported in Cagayan, Tarlac (both 16 times), and Nueva Ecija (15 times). Albay, Aurora, Bulacan, Isabela, Pangasinan, Zambales, Camarines Sur, Ifugao, and Pamapanga were affected 13 to 14 times. Tarlac, Nueva Ecija, Aurora, Bulacan, Zambales, and Pampanga are in Central Luzon; Cagayan and Isabela are in the Cagayan Valley of Northern Luzon; Albay and Camarines Sur are in the Bicol Region of Southern Luzon; Pangasinan belong to Ilocos Region; Ifugao is in Cordillera Administrative Region. (18,758 ha) > No LF (18,774 ha) > TS (52,687 ha) (Figure 4a; Table 2). Although Category 3 and 4 events caused the most areal damage in the Philippines, the relationship between typhoon intensity and areal losses was not linear at lower wind speeds. Stronger typhoons did not necessarily result in the highest area of rice damaged, and this was confirmed by a linear regression which showed that the area of rice damaged had a weak relationship with landfall wind speed in both countries (Figure 5a,b). There was also a weak relationship between ACE and the area of rice damaged (Figure 6a,b). Ultimately, we acknowledge that the extent of areal losses is dependent on the size of the rice growing area; however, we did not have information on the extent of rice growing areas during our study period to do further analysis. Figure 4: (**a**) Landfall intensity of cyclone and the area of rice damaged in Vietnam and the Philippines. (**b**) Volume of rice production lost in Vietnam and the Philippines based on landfall intensity of the cyclone. (**c**) Value of rice crop lost in the Philippines against landfall intensity. According to the Saffir–Simpson scale, landfall wind speeds were classified into five categories: Tropical Cyclone (TS, 34–63 kts), Cat 1 (64–82 kts), Cat 2 (83–95 kts), Cat 3 (96–112 kts), and Cat 4 (113–136 kts). No landfall (LF) referred to cyclones that came within 500 km from the coast of each country, but no landfall was recorded.
# Influence of Joint Stiffness and Motion Time on the Trajectories of Underactuated Robots
## 3 Effect of Joint Stiffness on Trajectories
Figure 5: Motor torques calculated considering different stiffness values and the same motion time (0.6 s). Figure 7 shows the total area swept by the robot considering four different values of torsional stiffness \(k_{3}\) and the same motion time. The red trajectory is the trajectory of the tip of the end-effector, whereas the blue trajectory is the trajectory of the back-end of the third link (with the counterbalance). Figure 6: Area swept by the robot between two configurations: area swept by each link (a); total swept area (b). Figure 7: Areas swept by the robot considering four different stiffness values with the same motion time (\(t_{f}=0.6\) s): (**a**) \(k=1.5\cdot 10^{-3}\,\mathrm{Nm}/\mathrm{rad}\), (**b**) \(k=2.5\cdot 10^{-3}\,\mathrm{Nm}/\mathrm{rad}\), (**c**) \(k=4.0\cdot 10^{-3}\,\mathrm{Nm}/\mathrm{rad}\), (**d**) \(k=5.0\cdot 10^{-3}\,\mathrm{Nm}/\mathrm{rad}\). The white dots identify the tip and the back-end of the last link. At the beginning and at the end of the motion, the robot moves in the third and in the fourth quadrant, respectively. The areas swept by the robot in the third and fourth quadrants are scarcely influenced by torsional stiffness. However, the reduction in torsional stiffness causes a reduction in the swept area in the first and second quadrants, since the area changes from a semicircle (corresponding to the largest values) to a figure with three lobes. This effect can be exploited to move the robot when obstacles are present in these areas. It is worth noting that in Figure 7a, the area swept in the first and second quadrants is largely influenced by the motion of the back-end of the third link that describes a trajectory that is outside the trajectory of the end-effector. In Figure 7b, almost all of the area swept by the back-end of the third link is inside the trajectory of the end-effector, whereas in Figure 7c,d, all of the area swept by the back-end of the third link is inside the trajectory of the end-effector. To quantitatively evaluate the importance of the reduction in the swept area, the areas swept by the underactuated robot are compared with the one swept by an equivalent fully actuated 2-DOF robot having its last link as long as the sum of links 2 and 3: \(a_{2}^{\prime}=a_{2}+a_{3}\). Calculated results are summarized in Table 3. It is important to highlight that when the underactuated robot is equipped with a low stiffness spring, the reduction in the swept area reaches approximately 36%.
## 2 Background
### Radiation Effect  
Circuits operating in the space environment may experience unexpected faults due to the interaction between ionized particles (neutrons, etc.) caused by space radiation and the internal IC chip [1; 2]. Figure 1 summarizes the effects on FPGA that can be caused by space radiation. When the ionized particles generated by the activities of celestial bodies, such as the sun or stars in space, radiate electronic devices, they affect the charge of the internal transistors and disturb their states. Depending on the location and amount of charge transferred by collision of particles, temporary or permanent effects may occur at this time.  
The effects caused by single-event interactions are called single-event effects (SEEs), and they can be either temporary or permanent [3]. If SEEs exhibit transient characteristics, they are referred to as a soft error, as they do not result in permanent damage to the device. Examples of these soft errors are classified as single-event upsets (SEU) and single-event transient (SET), depending on the location of their influence, as follows: (1) SEU is the effect of a bit flip that occurs when an ionized particle strikes the transistor of a memory cell and transfers enough charge to invert the state of the memory cell. The memory cell still performs write or read operations normally, but the stored information is damaged. (2) SET is a phenomenon that occurs when ionized particles strike a logic cell.  
When a single-event effect (SEE) of two bits or more occurs in a memory cell, it is classified into multiple-cell upset (MCU) or multiple-bit upset (MBU), depending on whether it occurs within one word of the memory cell. For example, if a SEE of two bits or more occurs in a memory cell within the same word, it is called an MBU, while if a SEE of two bits or more occurs simultaneously in different words, it is called an MCU. If a SEE occurs permanently, it may be caused by single-event latch-up (SEL), single-event gate rupture (SEGR), or single-event burnout (SEB).  
When an FPGA is exposed to ionized particles for an extended period, an effect called total ionizing dose (TID) occurs due to the accumulation of particle interactions. TID reduces the transistor performance by altering the threshold voltage and leakage current. Unlike the single-event effect (SEEs) described earlier, this phenomenon cannot be mitigated through correction methods involving reset or reloading, as the characteristics of the IC have permanently changed.
## 2 Materials and Methods  
### Study Design and Case Selection  
This histo-radiographic study was performed to correlate the DFs of the impacted third molars that were digitally evaluated through CBCT and the histological features of the DFs of the same excised teeth. All the impacted third molars were mesioangular and shared radiographically normal DFs. This is the position that is most frequently observed [14]. Since mesioangular impacted third molars are known to be more closely placed to the mandibular canal, in these cases CBCT represents a valid tool to assess the fine relationships between the impacted tooth and the mandibular canal [25; 34; 42]. DFs were considered normal when the maximum width of the DF was <2.5 mm, as reported previously [3; 4; 5; 6; 7; 8; 9; 10; 11; 12; 13; 14]. This study was performed according to the guidelines recommended by the Consolidated Standard of Reporting Trials (CONSORT 2010) and was approved by the ethics review board of the Azienda Ospedaliero--Universitaria Policlinico Umberto I of Rome (Rif. 2947/24.10.2013). All patients and their parents/legal guardians were informed in advance that scans and histological samples might be anonymously used for research reasons later. All the extractions were performed at the Pediatric DentistryUnit of the Azienda Ospedaliero--Universitaria Policlinico Umberto I of Rome. Inclusion criteria included the following: patients aged between 13 and 17 years old, at least one germ of the mandibular third molar, mesoangular impaction according to [PERSON]'s classification, evidence of orthodontic indications for its extraction (e.g., the need to move the second molar distally), the absence of systemic disease, the availability of signed consent by the parents/legal guardians, and width of the DF at CBCT <2.5 mm [43]. Exclusion criteria included the following: patients aged outside the range 13-17 years, the absence of both germs of the mandibular third molar or indications of orthodontics, a lack of mesoangular impaction according to [PERSON]'s classification, the presence of systemic disease, the lack of signed consent by the parents/legal guardians, and width of the DF at CBCT >2.5 mm [43]. The excised DFs were examined histologically. Based on the above criteria, ten consecutive patients and thirteen impacted third molars were included in the study.
## 6 Discussion
### M2M Communication  
When looking at technologies for M2M communications, subcategories related to M2M communication overlays (e.g., MQTT, HTTP/Coap, XMPP), Internet technologies (e.g., IPv6, 6 LowPan), and radio access technologies for WAN (e.g., cellular 3G), LAN (e.g., WiFi) and sensor networks (e.g., Bluetooth Smart) can be found. M2M applications are usually based on messaging with M2M devices. Traditionally, such messaging is done with short message service (SMS) or Email systems. It is seen that real-time messaging, capabilities to handle not always on mobile devices and capabilities for more dynamic topologies are needed. Therefore, technologies such as, e.g., XMPP to enable real-time M2M messaging, presence management and dynamic topologies are potential for M2M systems. In addition, there is need for virtualization of communications, and having a kind of M2M communication overlay hiding the heterogeneity of underlying networks and ensuring security. This is because of, e.g., the need to connect M2M asset devices with limited power and computing capabilities into the system. In addition, the referred M2M asset devices ownership set limits for the communication. When connecting such resources into system, also lower levels of communication need optimization. Examples of potential areas of research may be related to novel Bluetooth profiles, IPv6 over Bluetooth low energy, energy efficient IPv6 multicast, Coap, 6 LowPAN and RPL including optimized M2M gateway and M2M messaging solutions.
# Stochastic Model Driven Performance and Availability Planning for a Mobile Edge Computing System
## 4 Evaluation of MEC Performance
### Refined Model with Absorbing State
#### 4.2.1 Case Study 1  
For this study, we set the master server capacity (MASTERC) as 40, the time between arrivals (AD) to 5 ms, and we created three scenarios by varying the server capacity with the slave nodes (SLAVEC) as 8, 16, and 32. These scenarios have been defined in order to verify which slave server configuration best meets the requirements of an infrastructure administrator, according to the total time desired for the application execution. Table 3 allows a better view of these variables.  
Figure 9 shows the results obtained for CDF. In general, scenario #1 is the one that takes the longest time to run the application. Note that the scenarios #2 and #3 are the best cases, and with performance levels close to each other. Despite some occurrences where scenario #3 fares better than #2, when the probability of execution ends near 1, the times balance out. We can also see that both scenarios have an execution time in which the probability increases intensely. Assuming that an infrastructure administrator wants their application to complete within 800 ms, this can be accomplished using scenarios #2 and #3, and a choice can be made based on resource availability.
# Research on Lazy Theta+
## 6 Simulation Experiment and Analysis  
### Meshing Experiment  
1. Simulation  
In the same environment, the same model is divided into a single-scale octree grid with increasing levels ranging over 1-10, and the number of divisions is 1000 times. Dividing the model into different levels requires calculating and analyzing the number of meshes to fit the model expressed by:  
\[O=\frac{V_{M}}{V_{\text{n}}} \tag{28}\]  
where \(V_{M}\) is the model volume and \(V_{\text{n}}\) is the mesh volume required to enclose the model.  
Figure 17 illustrates the effect of the octree meshing model, which is the seventh-level meshing.  
Figure 16: Schematic diagram of B-spline equally spaced sampling smoothing route.  
Figure 15: Schematic diagram of cumulative distance.  
The experimental results of the other levels of octree meshing are shown in Figure 11 of Appendix A. The following is a statistical analysis of the relevant data obtained from the experiment.  
2 Analysis of results  
Once the model is divided 1000 times, the average data values are obtained to define the number of grids. Then, a model-fitting process is required for each level, as reported in Table 1.  
By analyzing the data in Table 1, the changing trend illustrated in Figure 18 is obtained, highlighting that as the mesh level increases, the number of meshes required increases exponentially, and the corresponding model fit also increases significantly.  
In this experiment, the number of meshes required for one to ten-level mesh generation models and the degree of model fit are analyzed. Through the analysis of the data, it is concluded that with the increase in the grid level, the number of grids required is also increasing, and it increases exponentially after the eighth level, while the growth rate of the model fit is relatively stable. Therefore, in this experiment, we preliminarily judged that the eighth level is a more suitable calculation level.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Grid Level** & **Number of Grids** & **Model Fit** \\ \hline
1 & 1 & 40.2\% \\
2 & 8 & 40.2\% \\
3 & 41 & 65.40\% \\
4 & 264 & 73.76\% \\
5 & 1245 & 78.65\% \\
6 & 6457 & 83.70\% \\
7 & 30.994 & 87.24\% \\
8 & 147,925 & 91.08\% \\
9 & 711,874 & 93.16\% \\
10 & 3,405,644 & 94.56\% \\ \hline \hline \end{tabular}
\end{table}
Table 1: Single-scale octree gridded data.  
Figure 17: The seventh-level subdivision model of octree grid.
## 2 Methodology of DLR Measurements
### High PRF of DLR Technology
The range residual data of the debris target (ID 38346) show a visible signature effect, marked by boxes in Figure 3. This confirms that the attitude of debris targets changes and the laser ranging techniques are suitable for measuring the attitude of targets. (3) The 100 kHz PRF laser ranging  
A high PRF of laser ranging provides a high echo data density and allows a fast target search. It means that DLR makes lower laser energy available by increasing the PRF of laser ranging, to keep tracking capabilities. Adopting a high PRF for laser ranging systems is an important technical approach to improve detection capabilities and will be a trend in future technological development. SLR technology has surpassed a PRF of 100 kHz [16; 17; 18; 19], laying the foundation for an ultra-high DLR repetition rate of 100 kHz-1 MHz. Additionally, SHAO has developed laser ranging technology for an ultra-high PRF of 100 kHz. Figure 1: Schematic of an optical system for a high-power nanosecond laser with a PRF of 200 Hz. The ultra-high PRF of laser ranging causes a much higher intensity of the laser atmospheric back-scattered signal, which is likely to damage the single-photon detector. Figure 3: Laser ranging of the debris target (ID 38346) with a dual-pulse picosecond 532 nm laser at a repetition rate of 1 kHz and power of 4.2 W.  
Figure 2: Laser ranging results using a 60 W laser with the SHAO laser ranging system. Therefore, a method of alternately transmitting and receiving laser pulses has been adopted for the ultra-high PRF of laser ranging. In this method, when the laser light is emitted, the detector does not work until the laser echo returns. This laser ranging mode separates the back-scattered signal from the laser echo in time and avoids the interference of the back-scattered signal. The procedure of the above mode is shown in Figure 4, where \(I_{p}\) is the time interval between laser pulses within the group (5 \(\upmu\)s for 200 kHz), on/off refers to the working status of the laser and detector, and _ToF_ is the flight time of the laser from the ground to the target. The working time length of the alternating mode is calculated according to _ToF_, and the number of laser pulses within the time of flight is calculated as:  
\[N=\frac{\text{ToF}}{I_{p}} \tag{4}\]  
The laser emission and reception are processed alternately to perform 100 kHz SLR measurements. By updating data acquisition software and range gate generator, 100 kHz laser ranging was performed to track satellites with a laser retroreflector using the SHAO laser ranging system. Figure 5 shows the measurements of the Sentinel-3B satellite at a PRF of 100 kHz with single pulse energy of 40 uJ in wavelength of 532 nm. The range residuals for 100 kHz measurements are plotted in Figure 5, where the laser echo signals appear periodically because of laser transmitting and receiving alternately. In the next step, we have a plan to apply 100 kHz SLR technology to DLR measurements and develop 500 kHz laser ranging technology.