esa-sceva/satcom-chunk-collection huggingface dataset:
# Reducing the Uncertainty of Lidar Measurements in Complex Terrain Using a Linear Model Approach
## 2 Materials and Methods
### Test Site and Measurement Campaign
#### 2.1.3 Lidar  
The SWE Scanner system and Galion lidar were installed next to each other \(\approx\)300 m west of the met mast. Both lidar systems used pulsed lasers and so can measure several heights simultaneously.  
The global coordinate system is a right hand system where the \(u\) or \(x_{1}\)-axis points in north direction, the \(v\) or \(x_{2}\)-axis points west direction and the \(w\) or \(x_{3}\)-axis points vertical to the sky. The wind direction corresponds to the Geographic Coordinates from north clock wise. The device coordinate systems (\(\theta\ =0^{\circ}\)) correspond to the global coordinate system (North).  
The SWE Scanner was configured to use a modified VAD method known as the _six beam_ trajectory [23]. The trajectory has five points on a circle with a half-opening angle of \(\phi\ =15^{\circ}\) and one vertical point in the centre of the circle (Figure 4a). The azimuth angle \(\theta\) is equally spaced on the circle with \(\triangle\theta\ =72^{\circ}\). The scan duration of the trajectory was 8.8 s. Five focal distances were measured simultaneously (50 m, 75 m, 100 m, 125 m, 150 m) at each azimuthal position.  
The Galion lidar has a maximum measurement range of approximately 4000 m. The device is fully configurable, with freely chosen azimuth and elevation angles and a maximum half opening angle of \(\phi_{max}\ =92^{\circ}\). In this campaign, the device measured three _six beam_ trajectories with three different opening angles \(\phi_{1,2,3}=[20^{\circ},39.2^{\circ},55^{\circ}]\) one after another (Figure 4b). These measurements were also used to test a method for determining the second statistical moments of the measured wind speed in complex terrain [24; 25]. The opening angles used were therefore the same as used in [24]. The azimuth angle was equally spaced with \(\triangle\theta\ =72^{\circ}\). The order of trajectory points was chosen to give the least time for every measurement sequence. The trajectory looks like a pentagram (Figure 4c) because the elevation angle can be changed faster than the azimuth angle. For a given combination of \(\theta\) and \(\phi\) the device is able to measure the radial velocity \(v_{los}\) at multiple focal distances \(df\). The data  
Figure 3: The vertical wind profile near the escarpment and on the plateau. M4 is at the escarpment, M2 is closest to the lidar, and M1 is closest to the met mast (Figure adapted and translated from Figure 5.8 in Ref. [16]).  
includes measurements for different distances ranging from 45 m to 735 m in 30 m intervals. The scan duration for all 18 points within the trajectory was 49 s.  
The two lidar systems differ in trajectory duration and in the configuration of the half opening angle \(\phi\). This difference in configuration enables the influence of these parameters on the measurement quality to be studied.
## 3 Results  
### Integrated Circuit Design  
To validate the synthesized logic, a Design Vision e-2013 was employed to create the Verilog gate level code and design the layout. An integrated circuit chip that will be implanted inside the eye was created using a 0.18 \(\upmu\)m SK Hynix CMOS standardized procedure, which minimized the size and external connections. Figure 7 shows a representation of the complete system implemented on a non-biological eye model and the chip utilization. The non-biological eye model was used to test the feasibility of wireless power and data transmission. The LEDs illuminated in Figure 7a indicate that wirelessly transmitted power and data signals from the transmitter are being received successfully, as described in 2.2.3. The transmitter was designed and implemented on a single PCB, which included a complete wireless transmission system, and the digital controller was implemented on a smaller FPGA (CMOD A7, Xilinx, San Jose, CA, USA) to achieve a compact system. The receiver and stimulator were interconnected to deliver the data, and an enlarged image of the integrated system is shown in Figure 7b.  
Figure 8 shows the entire layout of the digital controller. A digital controller was fabricated along with a stimulator on a single chip following a 0.18 \(\upmu\)m SK Hynix CMOS standard process. Table 1 provides the performance of the 256-pixel chips. The combination of overlapping pulse techniques and precise control over biphasic pulses enabled effective current management, while a voltage range of \(-\)2.5 V to 2.5 V was applied across the system to minimize crosstalk and current leakage during stimulation.  
\begin{table}
\begin{tabular}{c c c c c c} \hline  & [6] & [19] & [29] & [18] & **This Work** \\ \hline CMOS Process & 0.35-\(\upmu\)m CIS * & 0.35-\(\upmu\)m & 0.18-\(\upmu\)m & 0.18-\(\upmu\)m & 0.18-\(\upmu\)m \\  & & BCD ** & CIS * & CIS * & Standard \\ Supply voltage [V] & \(\pm\)2 & 5, 12 & \(\pm\)1.65 & 0.5, 1.8 & \(\pm\)2.5 \\ Chip area [mm\({}^{2}\)] & 3 \(\times\) 3.5 & 2.5 \(\times\) 1.2 & 2.2 \(\times\) 2.2 & 1.9 \(\times\) 1.9 & 5.0 \(\times\) 4.0 \\ Dynamic range [Lux] & 0.1–10,000 & 100–250 & 400–1200 & 1–1000 & 400–1600 \\ Pulse amplitude [\(\upmu\)A] & 0–100 & 0–300 & 0–343 & 0–50 & 0–150 \\ On-chip digital controller & Yes & No & No & Yes & Yes \\ Power consumption & 1.6 mW & N/A & N/A & 2.1 mW & 3.2 mW \\ \hline \end{tabular} Note: N/A = Not Available. * CIS: CMOS image sensor, ** BCD: Bipolar CMOS and double-diffused MOS (DMOS).  
\end{table}
Table 1: Performance summary and comparison table.  
Figure 7: (**a**) Prototype of the complete system and implanted chip on top of the non-biological eye model. (**b**) Magnified image of the artificial retinal stimulator and receiver.
# Intelligent Fault Diagnosis of Rotating Machinery Using Hierarchical Lempel-Ziv Complexity
## 2 Proposed Hierarchical Lempel-Ziv Complexity
### Multi-Scale Lempel-Ziv Complexity  
On the basis of LZC and coarse-grained procedure [26], MLZC can be summarized into two steps. (1) Conduct the multiple series by the coarse-graining analysis; (2) calculate the LZC values of each coarse-grained time series.  
(1) Given an arbitrary time series \(X[x(k),k=1,2,\cdots,N]\), construct consecutive coarse-grained time series \(\left\{y^{(\tau)}\right\}\) according to Equation (4).  
\[y_{j}^{\tau}=\frac{1}{\tau}\sum_{i=(j-1)\tau+1}^{j\tau}x_{i}\ 1\leq j\leq\frac{N}{\tau} \tag{4}\]  
where \(\tau\) is a positive integer. The obtained coarse-grained time series \(\left\{y^{(1)}\right\}\) is equal to the original time series when \(\tau=1\).  
(2) Calculate the LZC for each coarse-grained time series according to the definition of LZC as written in Equation (5).  
\[MLZC(x,\tau)=LZC(y^{\tau}) \tag{5}\]The flowchart of MLZC is drawn in Figure 2. Additionally, we set the parameter scale \(\tau=20\) in the paper. The parameter \(\tau=20\) has been proven to be effective using experimental tests for multi-scale analysis in [12; 15; 18; 28].  
However, the MLZC algorithm only uses the low-frequency components generated by the multi-scale procedure for feature extraction, which unavoidably discards some useful fault information hidden in the high-frequency components. To address these shortcomings of MLZC, this paper developed a novel method called HLZC. First, the hierarchical decomposition is adopted to generate sub time series called hierarchical series. Second, the LZC values of all hierarchical nodes are all computed for comprehensive complexity estimation.
## 4 Experimental Comparison and Analysis  
The proposed strategies and the parameter adaption schemes are explained and analyzed firstly by empirical research in this section. Subsequently, the proposed aHSDE is compared with the classical HS and several state-of-the-art HS variants, which include IHS [3], SGHS [4] and IGHS [6]. It is also compared with other state-of-the-art evolutionary algorithms (non harmony ones), which are Adaptive Particle Swarm Optimization (APSO) [43] and Evolution Strategy with Covariance Matrix Adaptation (CMA-ES) [44].
# An Effective AUSM-Type Scheme for Both Cases of Low Mach Number and High Mach Number
## 4 Theoretical Analyses on Low Speed Issues
### Theoretical Demands of the AUSM-Type Schemes for Low Speeds  
Theoretically, a scheme should satisfy the following properties at low speeds:_Property_ 1: Free from the appearance of the unphysical solutions at low speeds  
\[\begin{array}{l}p_{i-1,j}^{0}-p_{i+1,j}^{0}=0\\ p_{i,j-1}^{0}-p_{i,j+1}^{0}=0\\ \\ p_{i-1,j}^{1}-p_{i+1,j}^{1}=0\\ \\ p_{i,j-1}^{1}-p_{i,j+1}^{1}=0\\ \\ \end{array} \tag{99}\]  
_Property_ 2: Free from the checkerboard decoupling at low speeds  
\[\begin{array}{l}\sum_{l\in\
u(i)}\Delta_{il}p^{0}=0\\ \\ \sum_{l\in\
u(i)}\Delta_{il}p^{1}=0\\ \\ \end{array} \tag{101}\]  
In fact, Equation (101) has a stronger influence on the checkerboard decoupling than Equation (102), and a low-speed scheme could just satisfy Equation (101) instead of satisfying Equations (101) and (102) at the same time. Test cases to verify it can be found in Ref. [18].  
For these, it is necessary for a low-speed scheme to satisfy Equations (99)-(101). However, all these parameter-free AUSM-type schemes above do not satisfy these properties. Furthermore, analyses in Section 4.2 show that the mass flux and the pressure flux play important roles in the AUSM-type schemes' performances at low speeds.
# Algorithm for Extraction of Reflection Waves in Single-Well Imaging Based on MC-ConvTasNet
## 3 Results
### Wave Separation for Noisy Data  
The noisy data are calculated in the hard-to-hard single-interface model (see Figure 6a). The full wave without noise, the theoretical reflection wave and the reflection wave extracted by MC-ConvTasNet are shown in Figure 7a,b,d. The Rrmse between the theoretical reflection wave and the extracted reflection wave in Figure 7d is 0.044 (see Table 5). Figure 11 shows the reflection wave extraction effect by MC-ConvTasNet when waveforms contain noise. Figure 11a,d show full waveforms containing Gaussian white noise with signal-to-noise ratios of 20 dB and 25 dB, respectively. Figure 11b,e show the reflected waves extracted by MC-ConvTasNet from full waves containing noise. The Rrmse between the theoretical reflection wave and the extracted reflection wave in Figure 11b,e is 0.100 and 0.065, respectively. Compared with noise-free data, the increase in the root mean square error is less than 0.06 when the signal-to-noise ratio is 20 dB. The performance of MC-ConvTasNet decreases slightly. In Figure 11c,f, traces 4 of Figure 11b,e are compared with the full wave and the theoretical reflected wave, respectively. The amplitude of the extracted reflection wave is close to that of the theoretical reflection wave, and some noise is retained. MC-ConvTasNet is still applicable for the case where there is noise.  
Figure 11: _Cont._  
Figure 10: Full waveforms and extracted reflected waves for the double-interface model. (**a,b**) are, respectively, the full waveform and the reflected waveform of the CSG at a depth of 6 inches. (**c,d**) are the reflected waves separated by MC-ConvTasNet and parameter estimation, respectively. (**a,c**) are normalized with the maximum amplitude of the flexural wave. (**b,d**) are normalized with the maximum amplitude of the reflected wave. The average Rstd for parameter estimation and MC-ConvTasNet is \(-25.0\) dB and \(32.3\) dB, respectively.
## 1 Introduction
Recently, an enhanced angular displacement system has been developed using a heterodyne light source and a common-path optical setup for small optical rotation angle detection of glucose [12] and other optically active medium [13]. This is a noninvasive and real-time approach, in which the heterodyne light source consists of two component beams with different frequencies, and the polarization of each component beam is orthogonal to the other. For instance, a beam parallel to the plane of incidence is the TM mode, and the other is the TE mode. Additionally, the heterodyne light source has the electric field represented by the Jones matrices, and is separated into two paths, the measurement path and the reference path, by a beam splitter [13]. However, these true phase measurements are not sensitive enough to detect a small optical rotation angle [14, 15, 16]. In this regard, [PERSON] _et al._, further modified the measurement with a high optical resolution of \(1\times 10^{-40}\) to monitor the blood glucose using an angular displacement-enhanced heterodyne polarimeter [13]. In this paper, we made an attempt to employ an angular displacement-enhanced heterodyne polarimeter to precisely monitor the effect of TFE on the thermal denaturation properties of collagen in rat tails. The TFE aqueous solution with wide range of concentration from 5% to 80% (\(v/v\)) was used to investigate the interaction of TFE and triple helical structures. Moreover, the inhibiting effect of glycerol on the thermal degradation of TFE-mixed collagen is investigated. The inhibiting mechanism of glycerol with three hydroxyl groups for the stabilization of the triple helix is discussed.
# Efficient Opportunistic Routing Protocol for Sensor Network in Emergency Applications
## 2 Related Work
This approach calculates a cost function for each node using information such as the hop-count and the average aggregated inter-contact time of the node. If the cost of a forwarder node is low, the sender transmits the data to that node. In this approach, a node does not track information about other nodes, thus, reducing privacy and security risks. However, this approach does not consider clustering. This work done in [23] introduces an opportunistic routing protocol (ORR) that finds the optimal number of forwarders based on a cost function using duty cycles and network topology. Moreover, this approach selects the forwarder from a list of forwarders with more residual energy. Opportunistic networks use epidemic routing protocols [11] where a node broadcasts or forwards messages to all other nodes, which results in high message overhead. To mitigate this problem, the work done in [13] proposes an energy efficient opportunistic routing protocol where a node forwards a packet based on its remaining energy and delivery predictability factor. However, most routing protocols of opportunistic networks do not consider real-time message delivery. The work done by [PERSON] et al. [14] introduces a real-time message propagation model with a maximum data transmission latency for opportunistic networks containing heterogeneous devices. While existing works mostly consider delay tolerant networks (DTN) to forward messages opportunistically to the destination node, they do not consider transmitting messages to the first responders, governmental agency, hospitals and other related organizations in response to disaster situations. In [15], the authors introduce a routing protocol comprising DTN and an Information-Centric Network (ICN). The DTN transfers data to the destination and the ICN propagates interest messages to the responding authorities. However, these routing protocols may not work well in emergency or disastrous situations. Hence, an efficient opportunistic routing protocol is greatly required for emergency disastrous situations with a higher packet deliver ratio and lower latency.
# Effects of Bridge Piers on Flood Hazards: A Case Study on the Jialing River in China
## 2 Materials and Methods
### Mesh Generation and Model Parameters  
A high-quality mesh is vital for the numerical simulations. In this study, the computational mesh was generated using the mesh generator provided by Mike 21 FM software. The input data to the mesh generator included scatter topography data and a file where the boundary of the computational domain was listed. The mesh generator provided three parameters to ensure the quality of the generated mesh. These were the maximum element area, the smallest allowable angle, and the maximum number of nodes. In the following analysis, we chose a maximum element area of 50 m\({}^{2}\), a smallest allowable angle of 29\({}^{\circ}\), and a maximum number of nodes of 100,000. By using an unstructured mesh, the circular bridge piers with diameters of 2 m are directly described (i.e., solid wall conditions) (Figure 2). Two sets of meshes with and without piers were used to investigate the impacts of bridge piers on the flow fields. Mesh independence is analyzed in Section 2.4. The input topography for the study area is presented in Figure 3.  
Figure 2: Simulation mesh near Fengxian Bridge (circles denote bridge piers).  
The Manning coefficient (\(n\)), which indicates the resistance of the channel bed, is an important parameter for flood simulations. At the two hydrological stations of Fengzhou and Ciba, when the average water depth is greater than 1.0 m, the roughness coefficient is between 0.03 and 0.038 m\({}^{-1/3}\) s. In this study, a constant Manning coefficient (\(n=0.038\) m\({}^{-1/3}\) s) was used in the entire study area for the sake of safety. A sensitivity analysis was also carried out to investigate the effects of the Manning coefficient on the computed results, as described in Section 2.4.  
The boundary conditions at the upstream and downstream cross-sections had to be specified. At the upstream boundary, flood discharge was used. Two scenarios with 10-year and 100-year floods were used in this study. From hydrological analysis, the discharges in 10-year and 100-year floods were 824 and 2241 m\({}^{3}\)/s, respectively. At the downstream boundary, water levels were specified, and calculated using the Chezy formula with an assumption of uniform flow. In this paper, water levels at the downstream boundary were 963.79 m and 965.82 m for the 10-year and 100-year floods, respectively. Initial water levels were set to be the same as those at the downstream boundary. Initial velocities were set to zero.
In previous studies, the unsteady Reynolds-averaged Navier-Stokes (RANS) model with large time steps has been used, wherein the damping of the fine-scale turbulent fluctuation of the flow was neglected. Such RANS simulations result in poor predictions of separated flows [20; 21]. In this study, we adopted a hybrid RANS/large eddy simulation (LES) approach to capture the small-scale vortex structures around the trains. This approach has been widely employed to capture wake vortex structures and is highly effective [12; 18; 19; 22; 23]. We selected the improved delayed detached eddy simulation (IDDES) model based on Spalart-Allmaras (SA), denoted as SA\(-\)IDDES, and shear stress transport (SST) k\(-\)\(\omega\), denoted as SST\(-\)IDDES. The SST k\(-\)\(\omega\) model was used to compare the unsteady RANS results. The main objective of this study was to compare the differences in the aerodynamic characteristics of MTs simulated by the SST k\(-\)\(\omega\), SA\(-\)IDDES, and SST\(-\)IDDES methods and to reveal the flow mechanisms around two trains passing each other along a double track. The remainder of this paper is organised as follows: Section 2 introduces the methodology, including the geometry model, computational domain, numerical setup, mesh generation, and mesh sensitivity; Section 3 presents the numerical results and analysis, including experimental validation, transient pressure, velocity profiles, wake flows, and aerodynamic force; and Section 4 presents the conclusions.
# E-Nose Quality Evaluation of Extra Virgin Olive Oil Stored in Different Containers
## 3 Results and Discussion
### Sensory Aroma of Olive Oils  
A tasting panel evaluated the sensory attributes of VOO in accordance with the official method, and positive and/or negative sensory attributes were rated. Positive sensory attributes related to fruits odor, while negative sensory attributes related to the principal defect, namely rancidity (Table 1).  
At t0, all samples were classified into the highest commercial category, EVOO, as a result of the positive attributes and the lack of defects identified. Olive oil stored in Tinplate containers presented the highest proportion of positive attributes during the conservation period. The intensity of fruitiness decreased for all packaging types during storage time. This decrease was slightly higher in oil packaged in dark crystal bottles and green PET containers. Polyethylene can adsorb considerable amounts of aroma compounds, resulting in the loss of aroma intensity with an unbalanced flavor [26].  
The negative attributes shown in Table 1 also demonstrate that defects were detected during storage time in two of the three assessed packaging types. EVOO stored in Tinplate containers showed no defects during the 21 months of storage. In contrast, the dark crystal and green PET containers showed defects related to rancidity at t5 and t6, respectively. These defects resulted in the olive oil changing its commercial category from EVOO to VOO. Furthermore, at the end of the storage time (t6), the quality of the olive oil stored in dark crystal bottles decreased to the lowest commercial category: lampante olive oil (LOO). The Tinplate containers avoided these defects as they provided total protection against light, oxygen, and water vapor, thereby allowing the olive oil to maintain the highest commercial category: EVOO. Transparent or translucent containers could not protect the olive oil from  
Figure 2: Study workflow.  
photo-oxidation, hence the presence of the rancid aroma. According to [PERSON] et al. (2017) a longer shelf life is obtained during storage at a lower temperature. They also suggested that the best packaging types to maintain the storage stability of olive oil are containers of tin, stainless-steel, and dark glass.
## 2 Background Overview
### Fiber Bragg Grating Deployment  
Fiber Bragg Gratings (FBGs) were inserted through boreholes into the section coal pillars located beneath the overlying goaf's oblique coal pillars. Four monitoring stations were set up to observe the deformation of these section coal pillars, located between the 22,206 transportation roadway and the 22,208 return air roadway as shown in Figure 3. Upon completing the installation of the FBG sensors underground, communication fiber-optic cables were connected to the control room, forming a complete FBG strain monitoring loop for collecting the strain data of the section coal pillars.  
In practical engineering applications, to monitor the deformation of the section coal pillars in the 2-2# coal seam, FBG sensors were inserted into boreholes drilled at a 5\({}^{\circ}\) upward angle into the section coal pillars between the main transportation roadway of the 22,206 working face and the return air roadway of the 22,208 working face. Nine FBG  
Figure 1: Working face layout and section coal pillar setup in the study area.  
Figure 3: Fiber-optic grating monitoring area.  
Figure 2: Coal bed map.  
strain monitoring points were arranged along the 15 m width of the section coal pillars, with the profile and layout of these nine points shown in Figure 4.  
Five FBG arrays were installed along the strike direction of the section coal pillars. One array was placed in the center, with two arrays on each side in an axially symmetrical manner to monitor the shoulder areas of the bell-shaped load, aiming to capture deformation data from different positions along the inclination direction of the coal pillars. Based on the calculation of the influence range of the overlying oblique coal pillars from the 22,208 working face, which is 72.26 m, the 5-1# section coal pillar is located directly below these oblique pillars and within their influence range, exhibiting a bell-shaped load distribution. Enhanced monitoring was conducted at the central position of the 5-1# section coal pillar, with the process layout along its strike direction illustrated in Figure 5.