esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
### Design Consideration of the Magnetizing Inductor \(L_{m}\)  
The peak-to-peak value of the magnetizing inductor \(L_{M}\), which is denoted as \(\Delta I_{LM}\), can be given by  
\[\Delta I_{LM}=\frac{\left(V_{IN}-\frac{V_{OUT}}{2}\right)\cdot DT_{S}}{L_{M}}= \frac{V_{OUT}\cdot N_{P}\cdot(1-D)T_{S}}{2\cdot L_{M}\cdot N_{S}} \tag{3}\]  
The average value of the magnetizing inductor current \(I_{LMB}\) for the boundary cases of continuous conduction mode and discontinuous conduction mode can be expressed as  
\[I_{LMB}=I_{OB}=\frac{\Delta I_{LM}}{2} \tag{4}\]  
Combining Equation (3) with Equation (4), the magnetizing inductor in the boundary conduction mode, which is denoted as \(L_{MB}\), can be expressed by the following equation:  
\[L_{MB}=\frac{V_{OUT}\cdot N_{P}\cdot(1-D)}{2\cdot 2\cdot I_{OB}\cdot N_{S} \cdot f_{S}} \tag{5}\]  
As stated by Equation (5), Figure 9 shows the relationship between the magnetizing inductor in the boundary conduction mode \(L_{MB}\) and the switching frequency \(f_{S}\) at different duty cycles \(D\).  
Figure 8: The output voltage \(V_{O}\) versus the duty cycle \(D\) for various turns ratios \(N_{1}/N_{2}\).  
Assuming the average output current \(I_{OB}\) at the boundary condition is 1.3 times the average output current \(I_{O}\), the magnetizing inductance value for boundary conduction mode \(L_{MB}\) can be calculated using Equation (5). This calculation is based on the following conditions of a \(V_{OUT}\) of 10 V, an \(N_{P}\) of 1, an \(N_{S}\) of 1, an \(I_{OB}\) of 0.429 A, and an \(f_{S}\) of 50 kHz.  
\[L_{MB}=\frac{V_{OUT}\cdot N_{P}\cdot(1-D)}{2\cdot 2\cdot I_{OB}\cdot N_{S} \cdot f_{S}}=\frac{10\cdot 1\cdot(1-0.278)}{2\cdot 2\cdot 0.429\cdot 1\cdot 50000 }=84.1\ \mu\text{H}\]  
In order for the magnetizing inductor current to operate in continuous conduction mode, the magnetizing inductor \(L_{M}\) needs to be larger than the \(L_{MB}\) in boundary conduction mode and is set to 85 \(\mu\)H when the circuit is implemented.
## 3 Comparative Analysis of FEM-Calculated and ART-Measured Eigenfrequencies
### Validation of the Selected Model Adaption Strategy  
The adaption of the simulation model to measurement is demonstrated with the help of the 24 machine-made validation parts, which have not been included so far and are therefore to be regarded as unknown parts used within a blind test. The eigenfrequencies of the virtual representations of these parts were initially calculated by FEM simulations assuming our standard geometry and material according to Section 2 once again. The resulting frequency values were fitted with the help of the correction factors derived from the reference parts as described in the previous subsection.  
For validation, the synthetic eigenfrequencies were compared with the values accessed via ART from the manufactured parts. Figure 8 shows the relative differences of the adapted simulation values compared to ART data. The values from the virtual model fit very well to the measured values. The differences are less than 0.2% in nearly all cases. Mostly they are even smaller than 0.1%. Larger deviations were only detected for the parts no. 2, 8, and 20 with mode-specific deviations showing a similar pattern as can be seen in Figure 8. Even for these parts the maximum deviations are not much larger than 0.5%. Due to the good match, it is concluded that synthetic eigenfrequencies first generated via simulation techniques and then corrected multiplicatively are suitable for our application example and could be used successfully for an ART training procedure.  
Figure 8: Relative deviations between eigenfrequencies of virtual representations initially simulated by FEM and then adapted using correction factors and eigenfrequencies of the machine-made validation parts measured by ART depending on vibration mode (individual values for each validation part).
# Reducing Soil Permeability Using Bacteria-Produced Biopolymer
###### Abstract  
The building of civil engineering structures on some soils requires their stabilisation. Although Portland cement is the most used substance to stabilise soils, it is associated with a lot of environmental concerns. Therefore, it is very pertinent to study more sustainable alternative methodologies to replace the use of cement. Thus, this work analyses the ability of the more sustainable xanthan-like biopolymer, produced by _Stentroplomonas tanolrophula_Faro439 strain (LabXLC), to reduce the permeability of a sandy soil. Additionally, the effectiveness of this LabXLG is compared with the use of a commercial xanthan gum (XG) and cement for various hydraulic gradients and curing times. The results show that a treatment with either type of XG can be used to replace the cement over the short term (during time less than 14 days), although a greater level of effectiveness is obtained with the use of the commercial XG, due to its higher level of purity. The soil treatment with LabXLG creates a network of fibres that link the soil particles, while the commercial XG fills the voids with a homogeneous paste.  
biopolymer; soil stabilisation xanthan gum; sandy soil +
Footnote †: journal: Applied Sciences
# The Impact Assessment of Water Supply DMA Formation on the Monitoring System Sensitivity
## 2 Materials and Methods
### Model Network
In the second phase of the research, the problem of the uncertainty of pressure sensor indications was omitted. In the simulation studies, a network monitoring system was used, including the measurement of the pressure in four, identical in all variants, water demand nodes (p0, p1, p2, and p3), and the flow rate of water supplying the first node (q0). The location of the measurement points is shown in Figure 2. Simulation studies of the effectiveness of leak detection by the system of sensors designed in this way were carried out in three phases. In the first phase, during the simulation tests, each of the selected hydrants was assumed to open again and an attempt was made to find its location using the p0 and q0 sensors. Then, the monitoring system was gradually expanded to include the p1 sensor, then the p2 and p3. In total, 144 simulations were carried out at this stage. In order to locate the leakage, the Darwin Calibrator module of the Bentley WaterGEMS software was used. The Darwin Calibrator uses a genetic algorithm (GA). The general idea of the Darwin Calibrator is to compare the measured and calculated values of the same parameter and search for the most appropriate solution based on the principles of natural evolution and genetic reproduction [38]. The leakage is figuratively presented as an emitter coefficient, which is most often used for fire flows in hydrants [39]. The emitter flow varies as a function of the pressure available at the associated node, in accordance with the formula (Equation (2)) [40,41]. \[q=C\cdot p^{n}, \tag{2}\]  
where \(q\)--flow rate (dm\({}^{3}\)/s), \(C\)--emitter coefficient (dm\({}^{3}\)/(s m\({}^{n}\))), \(p\)--pressure head (m H\({}_{2}\)O), and \(n\)--pressure exponent (0.5). Evaluation of the effectiveness of leak detection was considered as the distance between the most probable location indicated by the Darwin Calibrator module and the actual open fire hydrant location. The distance, referred to in the article as the \"length of the error\", was measured along the route of the water supply pipes, i.e., the shortest path connecting the open hydrant with the location defined as the leakage node. The obtained  
Figure 2: Location of open fire hydrants (H1, H2, and H3) and monitoring points: q0; p0; p1; p2; and p3. results were compared with the total length of the pipes, the number of loops, and the fractal dimension in each network variant. The results of the tests carried out in the first and second stages provided an answer to the question of whether the commonly used leak detection system based only on network sensors and a flow meter at the point of supplying the zone with water can be effective.
# Multiple Elimination Based on Mode Decomposition in the Elastic Half Norm Constrained Radon Domain
## 2 Methods
### Improve GMD-R with the EH Norm Constraint Sparse Radon Transform  
GMD-R enables the decomposition of modes with distinct geometric characteristics. However, when the resolution of the input Radon model is insufficient, it can result in an overlap between multiples and primaries in the Radon domain, which reduces the effectiveness of mode decomposition. Moreover, the Radon model with low sparsity requires a substantial number of iterative calculations by GMD-R to ensure that the separated mode reaches convergence. To overcome these issues, the EH-SRT is introduced to improve the GMD-based multiple removal framework. The processing flow of the improved GMD-based demultiple framework is shown in Figure 2. Here, the yellow box represents the data in the time-offset domain, while the blue box represents the data in the Radon domain. The green box denotes the calculation procedures, including the EH-SRT, GMD and the inverse RT. Here, we replace the LSRT with the EH-SRT to perform the RT. The use of EH-SRT yields a Radon model with higher sparsity and stronger separability between primaries and multiples. This enhancement aids the GMD-R method in effectively separating multiple and primary modes. Moreover, the Radon model with high sparsity simplifies the convergence process during the GMD-R decomposition. Based on this, the combination of EH-SRT and GMD-R can not only achieve better separation of primary and multiple modes but also improve the computational efficiency of GMD-R.  
Figure 1: The shape of Wiener filter.
## 6 Discussion  
### Partition Imbalance Problem  
In ENRS, the range and number of LNs selected in a single i-th level HEA are determined by \(T_{\text{i}}\). However, this may result in the imbalance problem among partitions, i.e., the difference between the number of LNs assigned in the largest and smallest partitions, which is described as Partition_Imbalance [53], shown as Equation (8). Consequently, resolvers deployed in large partitions are overloaded and resolvers deployed in smaller partitions are lightly loaded.  
\[\text{Partition\_Imbalance}=\text{ max}\big{|}H_{i}^{k}\big{|}-\min\big{|}H_{i}^{j}\big{|} \tag{8}\]  
In Algorithm 1, we take the bandwidth, computing capacity, and storage capacity of resolvers into account. We also propose a strategy that takes into account the imbalance of HEAs. The candidate anchor node can be selected with the following strategy.  
Network Centrality of Resolvers: We can reduce the cluster imbalance by taking the capacity of resolvers into account. We can implement this by choosing the anchor node, which satisfied Equation (9), to replace Step 16 in Algorithm 1.  
\[d=\max(\textit{closeness\_centrality}(v_{p})) \tag{9}\]  
Figure 9: The total number of messages versus the numbers of queries; the number of nodes = 200. (**a**) shows the total number of messages with different number of queries when the number of query nodes is 50. (**b**) shows the variation of total number of messages with different number of queries when the number of query nodes is 100. (**c**) shows the total number of messages when the number of query nodes is 150.  
Here, \(d\) is the ID of the selected position of LN; \(0<p<N_{i}^{m}\), \(1\leq m\leq M\), \(0\leq i<L\). Choose \(d\) as the anchor node. This strategy ensures that each LN is assigned to the resolver located in the physical center of the graph.  
We define a metric _Imbalance_Degree_ to evaluate the effect of imbalance optimization. The definition is expressed as Equation (10):  
\[\text{Imbalance\_Degree}=\sum_{m=0}^{K}\sum_{n=0}^{K}\left|H_{i}^{m}\right|- \left|H_{i}^{n}\right|\text{, }0\leq i<L \tag{10}\]
## 3 Construction of Immersive Simulation Platform
### Data Interaction
#### 3.4.1 Path Data  
According to the waypoint transmitted by the network protocol, the carrier aircraft model moved to the waypoint, and the head of the carrier aircraft was toward the next waypoint, so as to realize the smooth path movement of the carrier aircraft. The steps are as follows:  
(1) Fetch and parse the data transmitted by the communication protocol.  
(2) Generate waypoints according to the analyzed data in Unity, generate quadratic Bezier curve based on the known data points in Unity, generate more detailed waypoints on the existing curve by using the generated quadratic Bezier curve segmentation, and form a smoother natural path trajectory. The path of a quadratic Bezier curve is given by a function \(B(t)\) at a given point \(P_{0},P_{1},P_{2}\):  
\[B(t)=(1-t)^{2}P_{0}+2t(1-t)P_{1}+t^{2}P_{2},t\in[0,1] \tag{20}\]  
Figure 6: Schematic diagram of wing folding of carrier aircraft.  
(3) The path following is realized by the position of the moving object, and the head of the carrier aircraft is oriented to the next waypoint, so as to realize the smooth path movement of the carrier aircraft.  
The coordinate system in Unity3D engine is inconsistent with the coordinate system established in the aircraft carrier model research. Corresponding coordinate transformation should be carried out to convert different spatial descriptions to ensure the spatial consistency between each simulation node. The attitude given by the carrier aircraft is under absolute coordinates, and the two points need to be uniformly converted to the relative coordinate system of the aircraft carrier model to match.  
If any point \((x,y,z)\) in the aircraft carrier model coordinate system is assumed, the transformation formula between \((x,y,z)\) and the corresponding point \((x^{\prime},y^{\prime},z^{\prime})\) in the aircraft flight coordinate system is as follows.  
\[\left[x,y,z\right]^{T}=A\cdot\left[x^{\prime},y^{\prime},z^{\prime}\right]^{T} \tag{21}\]  
where \(A\) is the coordinate transformation matrix:  
\[A= A_{\theta}A_{\varphi}A_{\psi}\] \[A_{\theta}= \begin{bmatrix}\cos\theta&0&-\sin\theta\\ 0&1&0\\ \sin\theta&0&\cos\theta\end{bmatrix}\] \[A_{\varphi}= \begin{bmatrix}1&0&0\\ 0&-\cos\varphi&\sin\varphi\\ 0&-\sin\varphi&\cos\varphi\end{bmatrix} \tag{22}\] \[A_{\psi}= \begin{bmatrix}\cos\psi&\sin\psi&0\\ \sin\psi&\cos\psi&0\\ 0&0&1\end{bmatrix}\]  
The coordinates of the center of gravity of the entity of the aircraft carrier model in the earth coordinate system based on the motion model are \((X,Y,Z)\), and the three attitude angles (yaw angle, pitch angle and roll angle) are denoted by \(\theta,\varphi,\psi\). In the visual simulation system, the coordinates of the aircraft carrier model in the absolute coordinate system are \((x,y,z)\), and the rotation angles around the \(X\), \(Y\), and \(Z\) axes are, respectively. There is a corresponding relationship:  
\[\begin{cases}h=-\psi\\ r=\varphi\\ p=-\theta\end{cases} \tag{23}\]
_ISPRS Int. J. Geo-Inf._**2014**, \(3\), 368-390; doi:10.3390/ijgi3010368  
ISPRS International Journal of _Geo-Information_  
**ISSN 2220-9964**  
www.mdpi.com/journal/ijgi/  
_Article_  
Monitoring Geologic Hazards and Vegetation Recovery in the Wenchuan Earthquake Region Using Aerial Photography  
**[PERSON] 1,2, [PERSON] 1, [PERSON] 1,*, [PERSON] 1,2 and [PERSON] 1**  
1. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China; E-Mails: [EMAIL_ADDRESS] (Z.L.); [EMAIL_ADDRESS] (Q.J.); [EMAIL_ADDRESS] (H.T.); [EMAIL_ADDRESS] (T.L.)
2. Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100094, China
* Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS]; Tel.: +86-10-8217-8163; Fax: +86-10-8217-8177.  
_Received: 25 November 2013; in revised form: 4 March 2014 / Accepted: 10 March 2014 / Published: 19 March 2014_  
**Abstract:** On 12 May 2008, the 8.0-magnitude Wenchuan earthquake occurred in Sichuan Province, China, triggering thousands of landslides, debris flows, and barrier lakes, leading to a substantial loss of life and damage to the local environment and infrastructure. This study aimed to monitor the status of geologic hazards and vegetation recovery in a post-earthquake disaster area using high-resolution aerial photography from 2008 to 2011, acquired from the Center for Earth Observation and Digital Earth (CEODE), Chinese Academy of Sciences. The distribution and range of hazards were identified in 15 large, representative geologic hazard areas triggered by the Wenchuan earthquake. After conducting an overlay analysis, the variations of these hazards between successive years were analyzed to reflect the geologic hazard development and vegetation recovery. The results showed that in the first year after the Wenchuan earthquake, debris flows occurred frequently with high intensity. Resultantly, with the source material becoming less available and the slope structure stabilizing, the intensity and frequency of debris flows gradually decreased with time. The development rate of debris flows between 2008 and 2011 was 3% per year. The lithology played a dominant role in the formation of debris flows, and the topography and hazard size in the earthquake affected area also had an influence on the debris flow development process. Meanwhile, the overall geologic hazard area decreased at 12% per year, and the vegetation recovery on the landslide mass was 15% to 20% per year between 2008 and 2011. The outcomes of this study provide supporting data for ecological recovery as well as debris flow control and prevention projects in hazard-prone areas.  
Keywords:Wenchuan earthquake; landslide; debris flow; vegetation recovery; aerial photography
# Silica Mesoporous Structures: Effective Nanocarriers in Drug Delivery and Nanocatalysts
## 4 Catalytic Applications of Mesoporous Silica Materials
### Organic Synthesis
#### 4.2.5 Condensation  
The hybrid mesoporous SBA-15 functionalized with choline hydroxide (Chol-SBA-15), hexamethyldisilazane as a capping agent (Chol-HMDS-SBA-15) and mesoporous silica microspheres (Chol-MSM) was created for the co-condensation method developed by [PERSON] et al. These Bronsted base solid materials were tested successfully as catalysts in Knoevenagel condensation reactions of benzaldehyde with malonomitrile and ethylcyanoacetate (Figure 11). These catalysts were easily recovered, and separation made them reusable, and hence eco-friendly, for several cycles without loss of activity. The Chol-MSM catalysts showed high catalytic activity and 99% selective conversions of ethyl-2-cyano-3-phenyl acrylate. In addition, their reusability without loss of activity has been demonstrated [123].  
Additionally, an interesting catalyst of cylindrical Fe-MCM-41-ionic liquid (Fe-MCM-41-IL) was prepared by anchoring an acidic trirazolium IL on the surface of Fe-loaded MCM. This cylindrical, mesoporous Fe-MCM-41-IL acted as an efficient, reusable, heterogeneous nanocatalyst for the one-pot synthesis of pyrimidine derivatives, producing high yields under mild conditions (Figure 12). Its operational simplicity, high yields, low cost, eco-friendly reaction conditions, reusability, and recoverability make this procedure much greener than the other reported procedures. Interestingly, this catalyst can be recovered via an external magnetic device [124].  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Raw Material** & **Catalyst** & **Solvent** & **Yield (\%)** \\ \hline Polysaccharide & HCl & H2O/MIBK & 33.3 \\ Corncob & H2 SO4 & H2O/Toluene & 65.5 \\ Wheat straw & CrPO4 & NaCl/THF & 67 \\ Xylose & CrPO4 & NaCl/THF & 88 \\ Biomass & SnXCSpyW & DMSO/H2O & 63 \\ Hydrolysate & HZSM-5 & H2O & 75 \\ Xylose & SO3H-KIT-6 & H2O/Toluene & 92 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparison of the furfural yield obtained using different raw materials and catalysts.  
Figure 11: Knoevenagel condensation in the presence of a mesoporous nanosilica microsphere.
# Synchronization of Monostatic Radar Using a Time-Delayed Chaos-Based FM Waveform
## 7 Comparative Performance with Existing Chaotic Radars  
This section clarifies the performance of existing systems in comparison to the time-delay based chaotic radar systems. For example, Table 1 compares the direct time-delay feedback chaotic radar [2] with Colpitts oscillator-based radar [8]. In contrast, Table 2 summarizes the comparison of Indirect FM Chaotic Radars for the proposed time-delay feedback radar versus Lorenz-based Radar [9; 10; 13]. Likewise, a signal design for generating wideband quasi-Frequency Modulated (FM) waveforms using chaotic systems was also suggested for joint radar-communication (RadComm) systems [37]. However, the receiver design is based on a self-synchronizing chaotic system in place of PLL in order to make fast synchronization and a robust system against the Doppler.  
Overall, it is noticed that our system based on PLL synchronization can also outperform in terms of low SNR range. It achieves successful recovery at SNR up to \(-15\) dB.  
On the other hand, when utilizing Matlab software, it was noticed that the simulation of FM-based time-delay chaotic radar had some problems. In fact, the massive data generated during signal processing (i.e., sampling-interval in ns) led to a storage limitation. Here we set the simulation stop time = 0.07 s to achieve the proper operation. Accordingly, the correlation forms in Figure 15 can exhibit satisfactory peaks but with less resolution; however, in the case of direct chaotic radar [2], once the simulation stop time is set to be 0.5 s, then the correlation peaks become more accurate by 50 times of the FM-based chaotic radar. As a result, one can conclude that more intensive research is needed to eliminate this difficulty in future work in order to create more realistic simulation findings.
# Automatic Modulation Classification Using Hybrid Data Augmentation and Lightweight Neural Network
## 4 Simulation Results and Analysis
### Simulation Results
#### 4.2.4 Ablation Experiments  
In this paper, ablation experiments were carried out to verify the effectiveness of the two data augmentation methods. The experimental results are shown in Figure 11 and Table 4. It can be seen that both rotation and RandMix methods can effectively improve the classification performance of the proposed lightweight CVResNet.  
Figure 11: Results of ablation experiments for different methods.  
Figure 10: The confusion matrices of the proposed AMC method and comparative AMC methods.
# Quadratic Clustering-Based Simplex Volume Maximization for Hyperspectral Endmember Extraction
## 3 Results and Discussion
### Comparison on Processing Time  
All the algorithms are implemented on Matlab R2019a with an Intel Core i5-10210U CPU at 1.60 GHz. The processing time of each test algorithm is shown in Table 4.  
It is noted that ECSO is the most time-consuming algorithm, which requires a lot of computations. VCA is the most efficient method, as it takes a short time and provides high accuracy on endmember extraction. CSVM consumes a certain time due to the spatial clustering operation. This issue can be solved by the graphics processing units (GPU) parallel platform, as it shows superior performance in floating-point operations and programming. The superpixel segmentation provides possibility for parallel acceleration of CSVM.