esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Current Measurement Techniques
### Snow Property Determination Techniques
#### 3.2.2 Terrestrial and Airborne Laser Scanning  
Terrestrial Laser Scanning (TLS) can provide extremely accurate snow height information [37], but (as with the photogrammetric method described below in Section 3.2.4.), cannot measure during a snowstorm and usually requires manual operation. Accuracy of the method is approximately \(\pm\)2 cm relative to a tachymeter for ranges closer to 0.5 km, but dropping significantly for longer distances.  
Airborne laser-scanning (ALS) is currently the most promising technology for high accuracy surface measurement (_i.e._, \(<\)0.1 m) and high resolution (_i.e._, 0.1-1 m) independent of the vegetation cover. Moreover, its multi-echo reception capability allows us to not only pierce through vegetation, but also determine 3D structure [38]. ALS can thus be used to obtain the surface of the snow cover and thereby the snow depth (using pre-recorded elevation maps).  
Snow and avalanche research institutes have recently started to intensively use LIDAR and TLS measurements for a variety of purposes from surface deformation in permafrost areas to pre/post storm snow height measurements for analyzing snow distribution patterns (see, e.g., [6, 25, 39, 40]).  
Based on the statistics of the relationship of snow depth to SWE, it is possible to calculate a SWE value from the snow heights measured in a LIDAR scan. This technique is however currently only accurate to \(\pm\)8 cm SWE [41].
## 2 Analysis of Settlement of Composite Foundation of CFG Piles
### Numerical Analysis
#### 2.2.3 Integral Equivalent Method  
When the number of piles or the scale of the structure is particularly large (such as hundreds or even thousands of piles), or the structure is complex (e.g., has a basement or consists of multiple buildings), the convergence of the calculation is poor because of the large number of elements, which can easily lead to the appearance of deformed elements, and the complex interactions caused by a large number of interfaces between soil and structure. Methods using the solid pile element and interface, as well as those using the embedded pile element, cannot meet the requirements of the rapid assessment of the soundness of the project in practice in this case.  
In this paper, a simplified method based on the equivalent simulation is proposed for a large number of CFG piles, where the vertical reinforcement and soil are regarded as an anisotropic whole, and piles simulated using the embedded pile element or solid element are not needed in the model. Instead, the parameters of the stiffness and strength of the entire strengthened area are replaced by the equivalent settlement value and distribution. The CFG pile is a kind of geopolymer with high bond strength mixed by cement, fly ash, aggregate, and water. Its material composition and mechanical properties are similar to that of ordinary concrete. The material strength of CFG pile is usually determined through the unconfined compressive strength test [31; 32]. In calculations for the simulation, the equivalent reinforcement zone is regarded as an anisotropic elastoplastic material. The jointed rock model in PLAXIS was used to model this zone. The main parameters of the jointed rock model in the finite element program were density \(\rho\), cohesion force \(c\), friction angle \(\phi\), the elastic moduli (\(E_{1}\) and \(E_{2}\)) and Poisson's ratios (\(v_{1}\) and \(v_{2}\)) in horizontal and vertical directions, and the shear modulus \(G_{2}\) in the vertical direction in the process of numerical modeling. Density was expressed as the thickness-weighted average value of the density of each layer of soil in the reinforcement zone. The cohesion force could be obtained using the cement strength of the CFG pile. A friction angle of zero was used, Poisson's ratios in both directions were 0.3, the elastic moduli (\(E_{1}\) and \(E_{2}\)) were obtained via back-calculation according to the target settlement value and the horizontal deformation, and the shear modulus \(G_{2}\) was determined by converting \(E_{2}\) and \(v_{2}\).  
The integral equivalent method is practical for the three-dimensional numerical analysis of synergetic interaction between the raft of high-rise buildings and the composite foundation formed by a large number of CFG piles. The feasibility and practical application of this method are introduced in the sections below.  
Figure 2: Stiffness of the embedded interface elements at the skin of the pile.
# Assessing the Added Value of Sentinel-1 PolSAR Data for Crop Classification
## 5 Discussion
### Comparison of the GA with Other Feature Selection Methods  
In order to further validate GA's effectiveness as a feature selection method, we examined the performance of other well known and widely used feature selection algorithms, namely Mutual Regression (MR) [139; 140], coefficients of Lasso, feature importance of Random Forest (RF) and Recursive Feature Elimination (RFE) by recursively training RF and discard the less important features in each iteration. Table 6 presents the OA and the macro-averaged f1-score for both cases (with and without the addition of artificial clouds). GA achieves the best performance in both scenarios and, especially, in the case of artificial clouds, where the f1 score is more than 1.5% higher than any other method. These experimental results underline GA's efficiency and robustness, as well as its superiority compared to other feature selection modules.
# Design Methodology and Application Dynamics of Compact Quasi-Zero Stiffness Isolators
## 3 Compact Design of QZS Isolation
### Bionic Type
#### 3.3.1 Bionic Leg Structure  
As shown in Figure 10a, [PERSON] et al. [61; 62; 63] proposed a bionic quadrilateral X structure based on the running of a kangaroo, aiming at suppressing periodic or impulsive force vibrations suffered by a free-floating spacecraft during an orbital maintenance mission.  
[PERSON] et al. [64] investigated a new type of passive vibration isolation support with a compact X-shape structure with ideal weak nonlinear characteristics to achieve QZS characteristics at large amplitudes, combined with a special tilting and adjustable spring mechanism, which is capable of adjusting the stiffness according to the different payloads. [PERSON] et al. [65] proposed a passive compact X-shape vibration isolation mechanism possessing three-directional QZS characteristics, and through the rational arrangement of the X-shaped mechanism, one can obtain multi-directional vibration isolation capacity and adjustable nonlinear characteristics, with a large stroke, a large load-carrying capacity, and wider QZS characteristics, and also be able to optimize the vibration isolation capacity according to the demand of three-directional vibration isolation by using the key parameters. [PERSON] et al. [66] proposed a variety of adjustable nonlinear stiffness systems. On the basis of the basic X-mechanism, X-aSpr with a spring with a controlled delayed tensioning mechanism is installed; X-aSpr-aS with additional fixed support and installation of a horizontal spring is introduced; X-vSpr consisting of a vertical linear spring is introduced; and on the basis of the X-aSpr mechanism, the structure X-aSpr-aC is further designed as an adjustable contact. All of these systems can be easily fabricated with reliable and simple mathematical models for analyzing and designing nonlinear phenomena with a compact, in-situ adjustable resonance frequency of about 1 Hz, vibration transmission rate attenuation of 20 dB, etc. [PERSON] et al. [67] found that the M-shaped leg structure of frogs possesses excellent vibration suppression during jumping, and inspired by the M-shaped-like leg structure, a new type of biomimetic vibration isolator was designed by using torsion springs; the isolator model is shown in Figure 10b. And in Figure 10c, [PERSON] et al. [68] developed a polygonal skeleton by simulating spinal control and leg structure of cat structure that can effectively suppress vibration under multiple excitations. Experimental results show that this polygonal bone structure can effectively isolate vibrations with frequencies above 3 Hz.  
Figure 10: Bionic leg structure: (**a**) Bionic kangaroo leg isolator model [61]; (**b**) Bionic frog leg isolator model [67]; (**c**) Bionic cat leg isolator model [68].
## 2 Materials and Methods  
### Synthesis of NM (Ru, Rh, Pt, Pd, Au, Ir)/\(\gamma\)-Al\({}_{2}\)O\({}_{3}\)  
The hydrazine hydrate reduction method was used to synthesize the noble metal-based catalysts. Respectively, RuCl\({}_{3}\), (NH\({}_{4}\))\({}_{3}\)RhCl\({}_{6}\), H\({}_{2}\)PtCl\({}_{6}\);6H\({}_{2}\)O, PdCl\({}_{2}\), AuCl\({}_{3}\), and H\({}_{2}\)IrCl\({}_{6}\)\(\cdot\)xH\({}_{2}\)O were used for each noble metal precursor. During preparation, the loading amount of noble metal was set to 1.0 wt.%. In detail, 1 g of \(\gamma\)-Al\({}_{2}\)O\({}_{3}\) (a commercial sample that was purchased from Sigma-Aldrich Co., St. Louis, MO, USA) was dispersed in 60 mL deionized water, 60 mL absolute ethanol, and 20 mL precious metal precursor solution by ultrasonic for about 30 min, followed by stirring for another 20 min to mix evenly. Afterward, the mixture was transferred into a three-neck flask. The mixture was then saturated by N\({}_{2}\), 0.01 g NaBH\({}_{4}\) in 20 mL 0.5 M NaOH solution as an alkaline regulator and 6 mL hydrazine hydrate solution, while a reducing agent was added dropwise into the mixture under stirring by a peristaltic pump. After 4 h, the suspension blend was filtered, washed with deionized water and ethanol several times, and then the resultant solid was dried at 100 \({}^{\circ}\)C for 10 h. The final products were calcined at 450 \({}^{\circ}\)C for 4 h at a heating rate of 2 \({}^{\circ}\)C/min. The catalysts were denoted as Ru/\(\gamma\)-Al\({}_{2}\)O\({}_{3}\), Rh/\(\gamma\)-Al\({}_{2}\)O\({}_{3}\), Pt/\(\gamma\)-Al\({}_{2}\)O\({}_{3}\), Pd/\(\gamma\)-Al\({}_{2}\)O\({}_{3}\), Ir/\(\gamma\)-Al\({}_{2}\)O\({}_{3}\), and Au/\(\gamma\)-Al\({}_{2}\)O\({}_{3}\).
# Study on Vibration Effects and Optimal Delay Time for Tunnel Cut-Blasting Beneath Existing Railways
## 3 The Mechanism and Effect of Vibration Reduction Through Waveform Interference
### Principle of Vibration Reduction Through Waveform Interference
For blasting seismic waves characterized by a main period \(T\), the delay \(\Delta\)t must satisfy \(\frac{T}{3}<\Delta t<\frac{2T}{3}\) to achieve destructive interference.
# Enhancing Heterogeneous Communication for Foggy Highways Using Vehicular Platoons and SDN
## 4 Performance Evaluation
### Packet Delivery Ratio (PDR)  
PDR is defined as the ratio of packets received by the destination platoon to the packets sent by the source platoon. We tested the PDR as a function of vehicle density, as shown in Figure 5, and found that with increasing vehicle density, the PDR increases. Furthermore, Figure 5 shows all of our cases of high and low connectivity in terms of PDR. We observed an almost identical pattern of increase in PDR with the increasing number of vehicles. However, case (_i_) and (_ii_) show high PDR in comparison to sparse network conditions because in these cases, connectivity is high. Case (_ii_) shows a slight decreasedue to the increase in speed of the trailing platoon when vehicles are low, but it shows the maximum delivery ratio due to high connectivity. Case (_iii_) also requires a relay to demonstrate the connection between nodes, which is why its performance is lower than that of the other two cases. When the density of the vehicular network increases from 5 to 10 in case (_iii_), packet delivery is impeded because the increased distance between platoons occasionally prevents the packets from reaching their destination, resulting in reduced PDR. This shows that the two communicating platoons did not establish a link using LCs. The improvement in the PDR can be attributed to the consideration of LCs in the path when increasing the number of platoons in the network. Our proposed cases introduce the concept of vehicles communicating with LCs when there are no neighboring vehicles within their communication range. This ensures successful packet delivery, achieving 99% PDR, as all packets are effectively transmitted from the source platoon to the destination platoon, regardless of vehicular density in case (_i_) and case (_ii_). Regarding case (_ii_), because the platoons are moving in both lanes, it thereby further enhances the PDR. Figure 5 also shows that the reference scheme [10] exhibits better performance due to SDN than the reference scheme [11], but its performance is inferior to our scheme due to the consideration of high-height vehicles. However, the reference scheme [11] shows poor performance because it does not consider SDN and focuses more on broadcasting messages rather than ensuring successful delivery.
## 3 Results  
### Comparison Results with Camera-Based Measurements  
During the 3D video analysis sections, both subjects maintained a 'Fix' solution throughout, ensuring high positional accuracy for the GNSS measurements. The estimates of the _SF_, _SL_, and per-step _running velocity_ obtained from the two GNSS-based methods--Method 1 and Method 2--were compared with the camera-based measurements for the calibrated sections of the track. Data from both subjects were combined for analysis. The statistical metrics for these comparisons are summarized in Table 1.  
For the _SF_, both methods showed strong agreement with the camera-based values, with Method 2 exhibiting lower _RMSE_ and _bias_ and higher ICC and \(R\) values than Method 1. Similar trends were observed for the _SL_, where Method 2 demonstrated improved accuracy, reflected by lower _RMSE_ and _bias_ values, along with better consistency across subjects. Regarding the per-step _running velocity_, both methods exhibited excellent agreement with the camera-based measurements, as indicated by high ICC and \(R\) values.  
Visual representations of these comparisons are provided in Figure 3. The scatter plots (panels A, B, and C) demonstrate strong agreement between the GNSS-based estimates and camera-based measurements, with data closely aligning along the unity line. The Bland-Altman plots (panels D, E, and F) reveal that Method 2 exhibited smaller biases and narrower limits of agreement (LOAs) than Method 1 for the _SF_ and _SL_. For the _running velocity_, both methods showed comparable performance with minimal differences.
## 2 Materials and Methods
### Gas Exchange Method (Gex Method) for AerT Detection  
The gold standard method for the identification of critical physiological thresholds, such as the AerT, is the Gas Exchange Method (Gex method), which requires a Cardiopulmonary Exercise Test (CPET), an advanced and comprehensive test that measures pulmonary and cardiovascular response during exercise [18; 19]. During a CPET, individuals typically perform graded exercises on devices such as those manufactured by Cosmed(r). These devices are engineered to meticulously monitor and record various physiological parameters. The experimental setup diagram and a detailed description of the test system are reported in Figure 2.  
The Gex method specifically examines the relationship between the ventilatory equivalent for oxygen (VE/VO\({}_{2}\)) and oxygen consumption (VO\({}_{2}\)). The ventilatory equivalent for oxygen is a dimensionless number that represents the ratio of the volume of air ventilated to the amount of oxygen consumed. In practice, the method involves graphing VE/ VO\({}_{2}\) against VO\({}_{2}\) values to identify the AerT. The Aerobic Threshold is discerned (by visual inspection) at the point where the VE/VO\({}_{2}\) ratio reaches its minimum value before it begins to rise again during a progressively strenuous exercise protocol.  
Figure 1: An exemplificative graph depicting the original heart rate time series for a graded exercise over 500 points, along with the smoothed version using a 5-point moving average. The red line represents the smoothed heart rate.  
The Gex procedure for determining AerT was validated using a second method known as V-slope [2]. This method involves plotting a graph with VCO\({}_{2}\) on the y-axis and VO\({}_{2}\) on the x-axis. Two regression lines are then fitted to represent the upper and lower segments of this relationship. The intersection of these lines corresponds to the Aerobic Threshold determined by the Gex procedure.  
To accurately determine the HR and VO\({}_{2}\) at the Aerobic Threshold, a precise method is employed. The average values of HR and VO\({}_{2}\) are calculated over the final 30 s of the exercise stage just before the AerT is reached. This approach is taken because these last 30 s are seen as reflective of the individual's physiological state at the threshold. Capturing the average values during this critical period is thought to provide a stable and reliable set of data points. These data points are crucial for subsequent statistical analysis, offering a solid foundation for comparing various conditions or interventions that might affect the Aerobic Threshold.
## 4 Proposed Adaptive Linear Quadratic Regulator with Fractional Integral (LQR-FI) Control Structure
### Mathematical Model and Constraints of the Proposed Controller Based on PSO Optimization
The critical issue related to the online optimization process is the dependability of the closed-loop stability behavior on the appropriate selection of the control design parameters over evolutionary time, i.e., the convergence of the PSO algorithm to an appropriate selection of control design parameters. This holds true because the closed-loop system may be unstable for the consecutive time intervals of evolution in the case of inappropriate selection of control design parameters. Hence, in this paper, the selection of an ideal control design parameters vector to the next time PSO evolution interval is based on the instant positions of the poles on the \(s\)-plane for the closed-loop system. As known, the system is stable if the closed-loop poles lie on the left half of the complex plane. The best parameter selection during the optimization process is achieved by adding more constraints to force the PSO algorithm to converge into the global minimum to obtain the optimal controller parameters. We can summarize the idea as follows:  
1. Calculate the real value of eigenvalue of the closed-loop system according to the equation, \[A_{new\ c-l}=A_{new}-B_{new}\text{K}_{lqr}\] (16)
2. Then, according to the obtained eigenvalues in step one, the PSO particles are updated along with position and velocity values with or without constraints as follows: if the position of the pole \(n\) stays on the right half of the \(s\)-plane, the objective function, IAE, is allocated to \(10^{-3}\) to force the algorithm to find a better solution in the next election. If not, the obtained IAE value is carried out for the next selection. Moreover, the proposed controller is examined for actuator faults. The type of faults that are considered in this paper is the loss of effectiveness, which are an attenuation in the actuator efficiency or gains due to lack of hydraulic fluids or lubrication [39]. System actuator faults can be compensated by means of solving the optimization problem presented in Equations (11)-(14). Then, in the case of fault, the input to be optimized,  
\[U_{f}=\alpha\times u \tag{17}\]  
where, \(U_{f}\) is the faulty input, \(u\) is the nominal control, and \(\alpha=\text{diag}[\alpha_{1},\alpha_{2},\alpha_{3},\ldots\ldots\alpha_{m}]\). Here, the attenuation factor changes within the range of 0 (full fault) to 1 (no-fault).
## 5 Discussion  
In order to obtain good tracing capacity as well as the antidisturbing capability of a linear motor system, an adaptive robust controller based on MTN is proposed in this paper. The controller consists of three parts: the robust feedback part, the MTN compensation part and the linearized parameter adaptive part. The MTN can obtain the nonlinear mapping between the reference trajectory and the complex disturbance through learning and parameter adjustment so as to further improve the anti-interference ability of the controller. At the same time, the MTN generated by errors can further compensate for unmodeled dynamics and complex external disturbances. The stability of an adaptive robust controller based on MTN is analyzed directionally according to the Lyapunov theorem, and the relevant proof process is given. Taking the industrial two-sided moving magnet coreless permanent magnet synchronous linear motor system as the test object, the tracking and disturbance resistance experiments were carried out. The experimental results consistently verify that the adaptive robust controller of MTN proposed in this paper can achieve good control performance under complex external disturbances and that it has good disturbance suppression ability.  
Methodology, Q.S.; Software, S.W.; Validation, C.Z.; Investigation, Q.S., Y.Z. and X.W.; Writing--original draft, Q.S. All authors have read and agreed to the published version of the manuscript.  
This work was supported in part by the Natural Science Foundation of the Higher Education Institutions of Jiangsu Province, China (Grant No. 22 KJB510026), The Subject of Educational Informatization in Colleges and Universities in Jiangsu Province (Grant No. 2021 JSETKT062), Research Topic of Modern Educational Technology in Jiangsu Province (Grant No. 2022-R-101321), Research on Quality Assurance and Evaluation of Higher Education in Jiangsu Province (Grant No. 2021 JSETKT062), Entrepreneurship Training Program for College students in Jiangsu Province (Grant No. 202210298001T), State Scholarship Fund under Grant 202108410235,the Special Research and Promotion Program of Henan Province under Grant 212102210015 and the Education and Teaching Reform Research and Practice Project of Henan Institute of Technology under Grant DQXY-2021005.  
Data are contained within the article.  
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.