esa-sceva/satcom-chunk-collection huggingface dataset:
#### 1.1.2 CRTSIII SBT Base Plate Structure  
With the development of railway technology around the world, China independently developed the CRTSIII SBT based on existing experience, construction technology and theoretical practice of CRTSI and CRTSII ballastless tracks [13,14]. From top to bottom, the CRTSIII ballastless track (CRTSIII BT) structure consists of rails, elastic fasteners, track slabs, self-compacting concrete (SCC), an isolation layer, and base plates as shown in Figure 1[15]. The rail usually adopted in CRTSIII BT applications is 60 kg/m, U71 MnG, 100 m fixed-length non-threaded new rail, while the fasteners are WJ-8B fasteners.  
In this research, the P5600 track slab was selected. The lower section of the SCC is equipped with two bosses and two grooves on the surface of the base plate as well as internal reinforcement mesh for occluding and limiting movement [16] (Figure 1a,b). The isolation layer is made of geotextile materials with a thickness of 4 mm and has longitudinal and lateral lengths consistent with the SCC. Except for the position where limiting structures are placed, the geotextile materials cover the entire base plate area. In practice, the geotextile materials are laid out to exceed the coverage of the base plate by about 5 cm; however, it is chopped off after the poured SCC layer reaches its standard design strength. The base plate adopts a unit structure, with a C35 concrete strength grade. It is noteworthy that every three-track slab corresponds to a base plate [17]. Expansion joints are provided for every two base plates, with polyethylene foam plastic board as filling material. (Figure 1c,d).  
The CRTSIII SBT has been successfully applied to high-speed railways and subway lines; however, currently there is little experience and few studies in the application of CRTSIII to heavy-haul railways. It is, therefore, necessary to carry out research with the view of exploring the characteristics of this track type in service [18]. The CRTSIII SBT base plate is equipped with a limiting groove combined with the upper self-compacting concrete boss to achieve the force transmission and movement limiting functions between the structural layers. This is particularly important and necessary for track stability and maintenance of geometric shape. Experience in the construction and operation of ballastless tracks has revealed that the connection between different structural layers is often weak. Since the base of CRTSIII slab track directly interacts with these basic structures, its fatigue damage performance under train load directly affects driving safety and comfort, especially under large axle loads when damage occurs frequently. At present, the research on CRTSIII  
Figure 1: Schematic and substructure diagram of CRTSIII SBT. (**a**) Size of base plate; (**b**) schematic diagram of internal reinforcement; (**c**) lateral section; (**d**) longitudinal section.  
SBT mostly focuses on the design and construction of each structural layer, and there is scarce research on damage of the base plate.
# Privacy Preserving Machine Learning with Homomorphic Encryption and Federated Learning
## 2 Related Work
### Federated Learning  
Concerning the data privacy protection and multi-party joint learning, a machine learning named federated learning was proposed by Google in 2016 [31]. As a multi-party cooperative machine learning, federated learning has gradually attracted much attention in research and industry [32; 33]. At the beginning, the purpose of federated learning was to help the Android users to solve the problem of updating their models locally. Furthermore, federated learning can be applied in various fields of machine learning. In 2019, Google scientists mentioned that they built a scalable production system for joint learning in the field of mobile devices based on tensorflow [34]. In addition, in 2019, more related works have been proposed. [PERSON] focused on the problem of learning model parameters when data distributed across multiple edge nodes, without sending raw data to a centralized node [35]. There is also some work focusing on federated transfer learning, such as the framework designed in [36], that can be flexibly applied to various secure multi-party machine learning. About performance, in [37], it proposed a framework SecureBoost with almost the same accuracy compared with the five privacy protection methods.  
Federated learning has been widely used in various fields. For example, the Gboard system designed by Google realizes keyboard input prediction while protecting privacy and helping users improve input efficiency [38; 39]. In the medical field, patients' medical data are sensitive, thus federated learning is very useful [40; 41]. Besides this, natural language processing [42] and recommendation systems [43] are also applicable for federated learning as well.  
In addition, in recent years, there is a lot of work on privacy protection machine learning worthy of attention. [PERSON] et al. proposed using differential privacy to protect privacy in machine learning, and SMC was used to reduce the noise caused by differential privacy [44; 45]. In 2020, [PERSON] et al. proposed a batchcrypt algorithm, which is based on the optimization of the FATE framework [46]. It encodes a batch of quantized gradients as a long integer, and then encrypts it at one time, which improves the efficiency of encryption and decryption by reducing the amount of calculation. [PERSON] et al. proposed a vertical federated learning system for Bayesian machine learning with homomorphic encryption, which can achieve 90% of the performance of a single union server training model [47].
## 3 Modeling of Non-Inverted DC-DC Buck-Boost Topology of Converter
\right] \tag{11}\]  
The output load voltage \(V_{R}\) of non-inverted DC-DC buck boost topology converter is computed as  
\[V_{R}=\frac{\mu}{1-\mu}V_{pv} \tag{12}\]  
Considering the ideal power transfer \(P_{pv}=P_{R}\) and eliminating the losses, the relationship between output impedance \(R\) and the input impedance \(R_{pv}\) is computed using (13)  
\[R_{pv}=(\frac{1-\mu}{\mu})^{2}R \tag{13}\]  
Assuming the average values for \(V_{pv}\), \(i_{L}\), \(V_{C2}\) and \(\mu\) as \(x_{1}\), \(x_{2}\), \(x_{3}\) and \(u\), respectively, the final state space representation looks like  
\[\left[ \begin{array}{c}\dot{x_{1}}\\ \dot{x_{2}}\\ \dot{x_{3}}\end{array} \right]=\left[ \begin{array}{ccc}0&-\frac{u}{C_{1}}&0\\ \frac{u}{L}&0&\frac{u}{L}-\frac{1}{L}\\ 0&\frac{1}{C_{2}}-\frac{u}{C_{2}}&-\frac{1}{R_{L}C_{2}}\end{array} \right] \left[ \begin{array}{c}x_{1}\\ x_{2}\\ x_{3}\end{array} \right]+\left[ \begin{array}{c}\frac{i_{pe}}{C_{1}}\\ 0\\ 0\end{array} \right] \tag{14}\]  
We have modeled the PV system accompanied by the non-inverting DC-DC converter, which extract maximum power when operates. Therefore, in the forthcoming sections, a control algorithm will be designed for changing duty cycle to meet the maximum power extraction.
## 6 Comparison of the Conventional and Proposed LVRT Strategies  
Figure 17 shows the schematic diagram for the DC breaking chopper implemented in the conventional scheme. When voltage sag occurs on the grid and the DCL voltage rises, the DC breaking chopper is enabled by a switch, and thus the power from the DCL is dissipated into the chopper resistor. The simulation results of the grid-connected SPV system with chopper control are shown in Figure 18. Figures 9a and 18a show that LVRT has been adapted, because both schemes provided approximately the same response; that is, the DCL over-voltage is maintained below the threshold value (25% of the rated voltage). Figures 9b and 18b show the active power injected into the grid under fault conditions. The simulation results presented in Ntare, R et.al, [33] show the effectiveness of the DC-break circuit and current limiter strategies to enhance the LVRT capability, mitigate voltage sag by addressing excessive DC link voltage, and ride through the grid fault safely. However, this control scheme does not analyze the inverter reactive power support to the grid under fault conditions. Alternatively, the proposed control system provides the DCL over voltage protection reactive power support, and mitigates voltage sag. From a practical implementation point of view, the application of the DC-breaking chopper scheme increases the overall system cost and power loss during the duration of a fault. However, the proposed control scheme contains two controllers, of which the MPPT controller exists in all SPV systems; therefore, it is not included in the cost calculation for the proposed control. The only additional unit is \"control without MPPT,\"--a PI controller based-PWM generator, as well as the voltage sensors and switch. Therefore, the proposed control scheme costs a little more than the existing MPPT system. However, the PI controller can be developed by using a simple operational amplifier with resistors and capacitors. These are basic components, and are inexpensive and easily available. Thus, the proposed control system can be implemented with larger grid-connected SPV systems easily.
# Helmholtz Coils Based WPT Coupling Analysis of Temporal Interference Electrical Stimulation System
## 2 Principles and Methods Analysis
### Differential Frequency Electrical Stimulation System Based on Temporal Interference
#### 2.3.2 Non-Physical Type Dynamic Adjustment of the Stimulation Location  
From the previous analysis, it is clear that the stimulation location for TI action needs to be determined by two mutually independent magnetic fields together. The magnetic field distribution after interference can be changed when the amplitude of the two output signals and the position of the coil are adjusted. In clinical treatment, patient posture changes can lead to a system instability [42]. This can be performed by adjusting the position of the transmitting coils to keep the received power stable, but the convenience of the adjustment is low. It is even faster if the electrical signal of the transmitting coils is adjusted. In addition, the movement of the transmitting coils can easily lead to an angular offset and misdirection between coils [41; 43]. The misalignment of this device will exacerbate the non-uniformity of the magnetic field and thus affect the transmission efficiency of the system [43]. Therefore, it is more feasible to keep the transmitting coils' position constant and achieve a dynamic and timely adjustment of the activation area by adjusting the current amplitude. Considering the attenuation of the electromagnetic waves caused by the body impedance, there is always a position in the body where the two magnetic field amplitudes are equal. This position is the peak position of the envelope modulation amplitude \(|B_{AM}|\).  
When the currents in the two coils are equal in amplitude, the peak of the envelope modulation amplitude falls exactly at the center, according to the symmetry. When the current \(I_{1}\) in coil 1 is constant, and the current in coil 2 is reduced from \(I_{2}\) to \(I_{2}^{\prime}\), its corresponding magnetic field amplitude is reduced from \(B_{2}\) to \(B_{2}^{\prime}\). In this case, the magnetic field \(B_{1}\), generated by coil 1, needs to be attenuated to a greater extent over a longer path so that its amplitude is equal to that of the magnetic field \(B_{2}\). This is shown by the peak position of \(|B_{AM}|\) being shifted from the center to the side of coil 2. Similarly, if the current in coil 2 is increased from \(I_{2}\) to \(I_{2}^{\prime}\), the corresponding magnetic field amplitude also increases from \(B_{2}\) to \(B_{2}^{\prime\prime}\). The peak position of \(|B_{AM}|\) is shifted from the center to the side of coil 1. From the above analysis, it is clear that the peak position of \(|B_{AM}|\) is always towards the side of the coil with the smaller output value. It has been shown that the magnitude of the envelope modulation amplitude directly determines the stimulus intensity [39], meaning that the peak position of \(|B_{AM}|\) represents the location of the activated region. Accordingly, electrical stimulation with a temporal interference can achieve dynamic adjustment of the activation area without moving the coil by varying the current magnitude of the coils.
## Abbreviations  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l} ABNO & Application-Based Network Operations \\ DPI & Deep Packet Inspection \\ ETSI & European Telecommunication Standard Institute \\ FE & Functional Entity \\ GGSN & Gateway GPRS (General Packet Radio Service) Service Node \\ HLR & Home Location Register \\ HSS & Home Subscriber Server \\ IETF & Internet Engineering Task Force \\ IMS & IP Multimedia Subsystem \\ IP/MPLS & Internet Protocol/Multi-Protocol Label Switching \\ MB & middlebox \\ NE & Network Element \\ NFV & Network Function Virtualization \\ NGSON & Next Generation Service Overlay Network \\ NSP & Network Service Providers \\ PDN-GW & Packet Data Network Gateway \\ SDN & Software-Defined Network \\ SGSN & Serving GPRS (General Packet Radio Service) Service Node (aka Serving GPRS Support Node) \\ SOA & Service Oriented Architecture \\ OTT & Over-The-Top \\ VN & Virtual Network \\ VNF & Virtual Network Function \\ WOC & WAN optimization controller \\
4G & 4 Generation \\ \end{tabular}
## 2 Materials and Methods
### Methodologies for the Assessment of Precipitation Products
The daily precipitation classes followed the World Meteorological Organization (WMO) standard [46] as follows: (1) rain \(<\) 1 mm (no/tiny rain); (2) 1 mm \(\leq\) rain \(<\) 2 mm (light rain); (3) 2 mm \(\leq\) rain \(<\) 5 mm (low moderate rain); (4) 5 mm \(\leq\) rain \(<\) 10 mm (high moderate rain); (5) 10 mm \(\leq\) rain \(<\) 20 mm (low heavy rain); (6) 20 mm \(\leq\) rain \(<\) 50 mm (high heavy rain); and (7) rain \(\geq\) 50 mm (violent rain). The ability of each precipitation product to discriminate between rain/no-rain events (days) can be evaluated using several categorical statistics. The accuracy (ACC) represents the level of agreement between the satellite estimate and the rain gauge precipitation data, the probability of detection (POD) measures how well SPPs correctly detected rainfall for all the actual occurrences of rainfall detected by the rain gauges, the false alarm ratio (FAR) measures how often SPPs detected rainfall when actually there was no rainfall, the critical success index (CSI) measures the fraction of a gauge's precipitation that was correctly detected by the SPPs, and the Heidke skill score (HSS) measures the fraction of correct SPP estimates without considering random matches. The equations used to calculate these quantities have all been given by [PERSON] _et al._[47]. ACC, POD, FAR, and CSI range from 0 to 1, with 1 being the perfect score for ACC, POD, and CSI and 0 being the perfect score for FAR. The HSS ranges from \(-\infty\) to 1, with 1 being a perfect score. All statistical equations used in this study are provided in the Supplementary Information.
## 5 Discussion
### Effect of the Matrix and Cleat Permeability  
The matrix and cleat permeability also played a crucial role in CMM extraction. As is apparent from Figure 14, the extraction time of completion was shorter for the matrix and cleat system with higher permeability. When \(k_{m0}\) or \(k_{f0}\) increased from \(0.1\times 10^{-3}\) mD to \(0.9\times 10^{-3}\) mD, the extraction time of completion decreased by 21.8% and 69.5%, respectively. The extraction time of completion was more sensitive to the cleat permeability than to the matrix permeability. Since high permeability of the cleat system improved gas extraction efficiency, many fracture treatment methods were adopted to create bigger fractures within the coal seam and enhance its permeability.  
Figure 12: Effect of initial hydraulic fracture aperture on extraction time of completion.  
Figure 13: Effect of the coal seam dip angle on extraction time of completion.
## 3 Results and Discussion
### Radius of Gyration Analysis
Trajectory analysis revealed that one end of the oligomer chain initially attached to the sand surface. After a period of fluctuation, the other end also adsorbed to the sand surface, leading to a stretched molecular conformation on the sand surface, which then stabilized. AEOR, due to its rigid structure, exhibited a stable Rg, while DGEBA and DGEDDS, with their more flexible structures, displayed greater Rg fluctuations.
# Evaluating Satellite Sounding Temperature Observations for Cold Air Aloft Detection
## 2 Data and Methods
### NUCAPS Technical Description
The Trace of the AKM returns the degrees of freedom (DOF) of the signal, which is the number of independent quantities measured from the subset of channels for the retrieved variable and using the internal signal-to-noise estimates. For sounding retrievals, the DOFs correspond to the vertical resolution of the retrieved variable [18; 19]. For NUCAPS temperature, the DOFs typically have a maximum of 6.0 in the boreal winter in the subarctic and Arctic [20]. As discussed in the introduction, NUCAPS can retrieve temperature from sounders on several platforms that have MW and IR sounders (e.g., Suomi National-Polar-orbiting Partnership (Suomi NPP), NOAA-20, MetOp-A/-B/-C, and soon, Aqua), which each provide roughly 4-6 daily overpasses between 45-75\({}^{\circ}\) N and up to 15 overpasses over the pole. For the present study, we examine NUCAPS from Suomi NPP, which was the only product available to NWS forecasters through the Satellite Broadcast Network (SBN) from 2014-2019. NUCAPS from Suomi NPP was replaced by NOAA-20 in the SBN beginning July 2019. Both NUCAPS from Suomi NPP and NOAA-20 are operational products, but only the NOAA-20 product is now available to NWS forecasters due to limitations in the SBN bandwidth. The NUCAPS data in this study was obtained from a historical archive on NOAA's Comprehensive Large Array-data Stewardship System (CLASS; www.class.noaa.gov).
## 5 Experiments  
### Evaluation of Real-Time Performance  
Several experiments of systems with different homography-based task functions are carried out. The time of consumed (TOC) is the most appropriate indicator to measure real-time performance. The TOC-H which is the time consumed on the homography matrix estimation, and the TOC-C, which includes the time consumed for Jacobian estimation and control output calculation, are selected as indicators to compare the real-time performance of the system. A PC with an Intel(R) Xeon(R) E5-1620 CPU at 3.5 GHz, 64-b operating system was chosen to run all experiments. The average values of TOC-H and TOC-C in each experiment with more than 10,000 control periods are shown in Table 2. The experiment in the article is only presented to compare the real-time performance of the two strategies. In practical space applications, this part of the function may be implemented using FPGA. Corresponding designs and improvements will be made to meet computational efficiency requirements.  
As shown in Table 4 and Figure 12, the TOC-H and TOC-C of the improved homography-based task function are always lower than the original homography-based task function with different numbers of feature points. According to the comparison of the results, the improved homography-based task functions with smaller dimensions show more convincing real-time performance, as expected.
## 2 Related Work
For example, in the distributed energy-efficient zonal relay node-based secure routing protocol (DEZMSR) [26], a relay node is selected based on zone radius by means of a division in two kinds of nodes, namely zonal and district relay nodes; other examples include using load balance [27], using comparison rules such as the Cauchy inequation [28] between energy used and routing distance, employing a specific hierarchy in the cluster deployment [29], and using a weighted product model (WPM) [30], among many others. In conclusion, the effectiveness of fuzzy algorithms for selecting the CH node in clusters has been proved. However, routing in an ad hoc topology requires first creating the paths between every node and the sink node (on the surface) with an unknown location of the nodes. On the other hand, complex multi-criteria decision problems can be managed efficiently by a standard formulation using hierarchy processes such as AHP. To our knowledge, there is no routing protocol using FAHP in the underwater environment for a random network topology that does not use clusters as hierarchy. In this work, we show that is possible to apply AHP including fuzzy decisions (FAHP) to the problem of the initial path creation after deployment of a random-topology UWSN. From our point of view, this is a new alternative for performing node forwarding selection in UWSNs.
## 3 Results and Discussion
### Validation of MW-SPM and HPLC-FD Methods
#### 3.3.2 Precision and Accuracy  
The precisions of the proposed MW-SPM and HPLC-FD were calculated using sample solutions of DUV and SEL at varying levels of concentration (Table 4). The relative standard deviations (RSD) in the case of MW-SPM were 1.02-2.01 and 1.82-2.41% for the intra- and inter-assay precisions, respectively. RSD values in the case of HPLC-FD were 0.89-1.52 and 1.04-1.72% for the intra- and inter-assay precisions, respectively. These small RSD values proved the high precisions of both MW-SPM and HPLC-FD. The accuracy of both MW-SPM and HPLC-FD was assessed by the recovery experiments at the same levels of concentration that were used for the precision assessment of both DUV and SEL. The recovery values were 98.5-102.5% and 98.8-101.4% for MW-SPM and HPLC-FD, respectively, indicating the accuracy of both methods.  
Figure 11: Calibration curves for quantitation of DUV (\(\blacktriangle\)) and SEL (\(\bullet\)) by MW-SPM (**A**) and HPLC-FD (**B**). Values of absorbance and peak area ratio are mean of 3 determinations \(\pm\) SD. On the graph, correlation coefficients (r) are provided for each corresponding calibration line along with linear fitting equations.
# Generic Methodology for Field Calibration of Nacelle-Based Wind Lidars
## 6 Uncertainties of Reconstructed Wind Characteristics  
In this section, the reconstruction case of a two-beam nacelle lidar system is used to demonstrate how, as facilitated by the white box methodology, uncertainties on multiple wind characteristics can be estimated. The propagation of calibration uncertainties through the reconstruction algorithm does not account for the flow model inadequacy. The wind model should be validated separately, and the uncertainty due to its inadequacy assessed.