esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Conclusions  
In this research, the flow uniformity and the increase of vorticity are analyzed with computational fluid dynamics applying non-Newtonian fluid model in the range of laminar flow whose Reynolds number is 58.5 based on the inner diameter of feeding pipe.  
The remarkable findings on the present study are summarized as: with an inline transverse configuration of resistive obstacles and the control of gap interval, 12 cases are tested for numerical analysis, and finally an optimal case is determined for the uniformity of outlet flow as 60% of gap to diameter ratio and 2:1 ellipse shape. This result is not so different from that of Newtonian fluid [2].  
For a proper analysis with RMS values, the effect of boundary layer should be filtered, generated from two side walls in the diffuser. For the purpose of this, the boundary layer of two-dimensional non-Newtonian flow is calculated with a type of Blasius similarity solution, and the boundary layer thickness at the outlet is computed as 30 mm for the baseline case. From the RMS analysis excluding the effect of boundary layer at the side walls, the RMS of velocity deviation at the diffuser outlet indicates 77% decrease in Case 2 of circular cylinders and 92% decrease in Case 8 of 2:1 elliptic cylinders compared with the baseline case. If we just change the cross-sectional shape circle to longitudinal ellipse, the RMS error decreases no less than 15% points. The reason is analyzed that the smoother flow along the surface of body is extended at the wake region due to suppress of vortex shedding originated from the flow separation.  
The increases of pressure drop and vorticity are investigated for the best cases of Cases 2 and 8, when the cross sectional shape is changed from circle to ellipse, the pressure drop is increased just in minor 3%, but the vorticity at the body surface increased 49%, which means a remarkable improvement of mixing efficiency with a small effort. That is, the final configuration seems to be very effective for the enhancement of mixing properties for the laminar flow regime, and therefore it has so wide possibility of engineering application on various mechanical parts concerning low Reynolds number fluids.  
The analyses of flow vorticities at the cross sections around the obstacles results in overall \(\omega_{\rm x}\approx\omega_{\rm z}>\omega_{\rm y}\) for the order of magnitude, which are interpreted as the effect of diffuser walls, obstacles, and crossflow, respectively. The vorticity, \(\omega_{\rm z}\) drives primarily the supply of mixing energy to the main  
Figure 18: Comparison of \(z\)-component vorticity in Case 2 and Case 8.  
flow to enhance the mixing of outlet flow. When the z-axis component is compared for Cases 2 and 8 at the line cutting trailing edges, the amplitude was decreased almost half for the 2:1 ellipse case compared with the circle case, which has more uniform velocity distribution at the outlet.
# Research on Influence of Tank Sloshing on Ship Motion Response under Different Wavelengths
## 3 Numerical Model Establishment
### Model Reliability Analysis  
In order to verify the reliability of the model, the numerical calculation results are compared with the existing experimental results, or the results calculated by other methods. First, the numerical calculation of the pitch and heave motions of the ship under the condition of the head sea was carried out. Under this condition, the liquid loading rate of the tank was 0, and the wavelength of the incident wave was \(\lambda\) = 7.015 m (\(\lambda/L=1.15\)). After nondimensionalization, stable periodic changes emerged; the results of ten cycles are analyzed here. The calculation results are compared with the experimental data of the 2015 Tokyo Workshop [28] as shown in Figure 6.  
Figure 5: Comparison of numerical waves and theoretical waves.  
Figure 6a,b are the results of dimensionless ship heave and pitch motions, respectively. It can be seen that the CFD calculation results based on the overlapping grid method are in good agreement with the experimental data, and the error is within the acceptable range. Generally speaking, the calculation results are reliable.  
Subsequently, the rolling motion simulation of the liquid carrier was carried out, referring to the calculation results of [PERSON] [4]. The model used is the FPSO experimental model made by the MARINE laboratory. In this paper, the same numerical model and meshing method were used to calculate the rolling motion of an FPSO with a liquid loading rate of 0.56 under a transverse regular wave with an incident wave frequency of 1.14 rad/s. The calculation results are compared in Figure 7.  
Figure 6: Comparison between numerical calculation results of ship motion and experimental values. (**a**) Ship heaving motion; (**b**) ship pitching motion.  
Figure 7: Verification of rolling calculation results.  
It can be seen from Figure 7 that the CFD calculation results based on overlapping grids are in good agreement with the results in the literature as a whole. The change trend and cycle of the roll angle are basically the same, and the amplitude of the roll angle at different times is slightly different but within the acceptable range. In general, the numerical model and meshing method in this paper can well calculate the motion of the liquid carrier under regular waves.
## 2 Study Area and Materials
### Meteorological Forcing Data  
For regional estimations of ET, GPP, and WUE, the input datasets for the spatial meteorological variables mainly consisted of air temperature, wind speed, humidity, pressure, and downward shortwave radiation from the China Meteorological Forcing Dataset (CMFD) [67; 68; 69]. The CMFD was made by blending the remote sensing products, the reanalyzed dataset, and observation data from weather stations with high temporal and spatial resolutions (3 h and 0.1\({}^{\circ}\)). The evaluated uncertainty for various meteorological factors was based on independent site data and shows that the dataset is more accurate over China than the Global Land Data Assimilation System (GLDAS) dataset, which is widely used throughout the world.  
Detailed information on the CMFD dataset is available at [[https://data.tpdc.ac.cn/en/](https://data.tpdc.ac.cn/en/)]([https://data.tpdc.ac.cn/en/](https://data.tpdc.ac.cn/en/)) or [[https://data.tpdc.ac.cn/zh-hans/](https://data.tpdc.ac.cn/zh-hans/)]([https://data.tpdc.ac.cn/zh-hans/](https://data.tpdc.ac.cn/zh-hans/)) accessed on 6 April 2021. To more accurately estimate ET and GPP in the study area at high spatiotemporal resolution, it was necessary to match the meteorological variables with remote sensing images at 100 m spatial resolution. The bilinear resampling method was used to interpolate these meteorological variables, and then they were averaged to obtain the daily value. Then, to match the remotely sensed surface variables, the CMFD-derived variables were downscaled to 100 m spatial resolution with regression kriging (RK) [61; 70; 71].
## 3 Regulatory Barriers to Implementing an EU-Wide Grid Digital Twin  
Implementing a digital twin for Europe's electricity grid faces significant regulatory and policy challenges arising from a multi-layered governance structure. EU-level directives and regulations establish general rules, while national laws and regulatory authorities govern the practical details of grid operation and data management [23]. This fragmented regulatory environment complicates initiatives requiring extensive cross-border coordination and uniform data exchange practices [24]. Additionally, existing policies and standards frequently predate the latest digital and smart grid advancements, creating a mismatch between regulatory frameworks and current technological needs [25]. Key regulatory barriers involve constraints related to data governance, privacy, and cybersecurity, fragmented regulatory regimes and outdated market structures, insufficient standardization and interoperability mandates, and a lack of regulatory incentives promoting digital innovation [4]. Overcoming these challenges is essential to enabling the successful deployment and efficient operation of a pan-European grid digital twin.
## 2 Sensors
### Pressure Sensors  
In BSN applications, pressure sensors are generally used to monitor pressure changes of the underside of foot in real-time mode, providing data for pressure analysis, behavioral recognition, and energy expenditure detection. Because of its special position on the human body, it is difficult to integrate pressure sensors with other modules, such as wireless communication modules, in one sensor node. They are generally installed on a pressure plate or inside special insoles. The pressure sensors are always connected with an external micro-controller by cable. In Reference [47], a low-cost foot pressure measurement system has been developed to measure the pressure of each contact point of the pelma by a pressure plate, in order to calculate the contact area. The system adopts feature extraction and pattern recognition techniques to recognize clubfoot pattern, aiming to automatically design personalized insoles. In Reference [48], researchers place pressure sensors into insoles to calculate motion parameters, including distance, time, total weight, speed, and frequency. The parameters are used to recognize behaviors aided by feature extraction and support vector machine (SVM), providing a novel method to measure energy expenditure. However, the proposed method ignored the problem of temperature drift caused by motion, which affects the accuracy of pressure measurements. This is a considerable problem in pressure sensor design.
# A Network-Based Method to Analyze EMI Events of On-Board Signaling System in Railway
## 3 EN Model of the OTCS
### Traction System and the OTCS in EMU
#### 3.1.1 Traction System  
The traction system of the EMU consisted of the pantograph, high-voltage cable, traction transformer, traction converter, auxiliary power unit, traction motors, and ground device as shown in Figure 5. From the physical and electrical structure, it can be known that most of the devices and components of the traction system are concentrated on the top and bottom space of the EMU, except the pantograph on the roof. The electric energy is obtained through sliding on the contact wire of the catenary by the pantograph, and the motors propel the EMU in the traction drive system. As the conclusions in References [4,8], pantograph arcing is one of the sources in EMU.  
Figure 5: Structure diagram of the traction power and drive system of EMU.  
There are three main channels for EM disturbances from the outside of the train to enter the inside of it: (1) radiation coupling by antennas on the roof and bottom of the vehicle, (2) direct radiation coupling in the body space, (3) conduction coupling related to the channel of \"pantograph--traction transformer--traction converter--power line--ground device\". However, EM disturbances from the inside of the train are more complex, especially the auxiliary circuits (auxiliary converters, batteries, and battery chargers, etc.), air conditioning, traction converters, and traction motors make the coupling complicated.
# Bi-Stability in Flexure Beams: Introducing a Setup for Experimental Characterization
## 3 Results and Discussion
### Influence of Flexure Beam Thickness on Bi-Stability Performance  
#### 3.2.1 Critical Forces as a Function of Thickness  
The results from the _\"Performance by thickness\"_ tests demonstrate that larger thicknesses require larger forces. Figure 5f shows the mean curves of the five tested thicknesses. The critical forces range from 0.0277 N (for a thinner flexure beam c10) to 5.2724 N (for a thicker flexure beam c30). The distance traveled before the critical force is reached (critical force point) also varies from 2.47 mm to 7.99 mm.  
The variability of the critical forces also occurs within samples of the same thickness, due to fabrication and assembly imperfections inherent in experimental tests. Although the load-displacement curves converge near the end, they diverge at the beginning and around the highest part of the curve. The largest variation is presented in the caliber 10-flexure beams (0.25 mm thick), and variability decreases as thickness increases. When manually  
Figure 5: (**a**–**e**) Force-Displacement graph per thickness (c10 to c40), which represents the first part of the bi-stable curve. Three samples of each thickness were tested and are plotted in the graphs as a,b, c. The thicker black line plots the mean of the three sets of data. The standard deviation appears in light gray. (**f**) Force-Displacement graph comparing the mean curves of the five tested thicknesses. As the thickness increases, so do the critical force and the snap-through point.  
assembled and placed in the fixture, the components have millimetric differences that can be overlooked in thicker flexure beams but have a considerable affect the thinner ones. Also, in fine flexure beams, these irregularities are caused by the inability of the instrument to measure small forces accurately.  
As shown in Figure 6a, the critical force increases gradually at the beginning of the curve that corresponds to calibers 10, 15, and 20 and then rises notably for calibers 30 and 40. The data exhibits a non-linear force-thickness relationship, as the deformation response is governed by buckling. The geometric parameters \(t\) (thickness) and \(l\) (length) have a non-linear effect on structures that deform by buckling (similarly to their participation in the bending of beams). In such slender structures, their bending and buckling properties and the thickness of their rectangular cross-sections follow a cubic scaling law.
# A Robust UWSN Handover Prediction System Using Ensemble Learning
## 2 Background  
Machine learning and its applications have proven their success in many applications [8; 9; 10]. Therefore, in this paper, several machine learning models have been utilized, including DT, GNB, KNN, and gradient boosting. In this section, we explain the background of each of these models.
# Review of Satellite Remote Sensing of Carbon Dioxide Inversion and Assimilation
## 4 Carbon Flux Data Assimilation and Inversion Studies
### Application of Carbon Flux Estimation Based on Assimilation Schemes
#### 4.4.2 Assimilation of High-Resolution Carbon Fluxes Based on Satellite Observations
[186] developed a global carbon-assimilation inversion system using the MJ98-CDTM atmospheric transport model and the ensemble Kalman filter assimilation algorithm, assimilating both GOSAT and OCO-2 data to estimate global CO\({}_{2}\) flux. Furthermore, in 2020, scientists compared net CO\({}_{2}\) flux changes between European regional land ecosystems and the atmosphere using multiple assimilation system simulations within the EUROCOM program framework [187]. [PERSON] et al. [188] conducted global CO\({}_{2}\) flux inversion from 2010 to 2015 using the GCAS system and GOSAT CO\({}_{2}\) column concentration data, achieving robust surface carbon flux estimations. Although atmospheric CO\({}_{2}\) concentration data from satellite observations have greatly contributed to global carbon flux research, there are still significant limitations. The observed data obtained by carbon satellites generally represent the average column concentration of CO\({}_{2}\) from the ground to the top of the atmosphere. Such observations cannot meet the accuracy requirements of assimilation inversion systems for CO\({}_{2}\) concentration observations, and satellite data differs significantly from traditional ground-based CO\({}_{2}\) data in terms of processing, analysis, and scale. Therefore, how to assimilate two different types of CO\({}_{2}\) concentration-observation data simultaneously in atmospheric inversion models is a research challenge for atmospheric carbon-assimilation inversion systems.
# Polar Code Parameter Recognition Algorithm Based on Dual Space
## 3 Principle and Method of Polar Code Parameter Recognition
### Recognition Principle  
**Theorem 1**: _Denote the generator matrix of the polar code as \(\mathbf{G}_{n}\), the set of information-bit positions as \(A=\{\pi(1),\pi(2),\cdots,\pi(k)\}\), and the new matrix \(\mathbf{G}^{\prime}\) is obtained after removing the \((i,i+a,\cdots,i+c)^{\text{th}}\) row vector, and its dual space is \(\mathbf{H}_{n}\), if and only if \(i,i+a,\cdots,i+c\
otin A\); \(\mathbf{H}_{n}\) is orthogonal to the codeword space._  
Let \(\mathbf{g}_{1},\mathbf{g}_{2},\cdots,\mathbf{g}_{n}\) represent the row vector of \(\mathbf{G}_{n}\). After removing row vectors with index \(i,i+a,\cdots,i+c\), \(\mathbf{G}^{\prime}\) is obtained and the space formed by the row vector in \(\mathbf{G}^{\prime}\) is \(\mathbf{V}_{1}=\{\mathbf{g}_{1},\cdots,\mathbf{g}_{i-1},\mathbf{g}_{i+1}, \cdots,\mathbf{g}_{i+a-1},\mathbf{g}_{i+a+1},\cdots,\mathbf{g}_{i+c-1}, \mathbf{g}_{i+c+1},\cdots,\mathbf{g}_{n}\}\). The dual space of \(\mathbf{G}^{\prime}\) is \(\mathbf{H}_{n}\)= \(\{\mathbf{h}_{i},\mathbf{h}_{i+a},\cdots,\mathbf{h}_{i+c}\}\), and the space formed by all row vectors in \(\mathbf{G}_{n}\) with row label in \(A\) is \(\mathbf{V}_{2}=\left\{\mathbf{g}_{\pi(1)},\mathbf{g}_{\pi(2)},\cdots,\mathbf{g }_{\pi(n)}\right\}\). When \(i,i+a,\cdots,i+c\
otin A\), \(\mathbf{V}_{2}\subseteq\mathbf{V}_{1}\), and, therefore, \(\mathbf{V}_{1}^{\perp}\subseteq\mathbf{V}_{2}^{\perp}\); that is, \(\mathbf{H}_{n}\subseteq\mathbf{V}_{2}^{\perp}\), so \(\mathbf{H}_{n}\perp\mathbf{V}_{2}\); that is, \(\mathbf{H}_{n}\) is orthogonal to the polar code word. If any of \(i,i+a,\cdots,i+c\) belong to the set \(A\), \(\mathbf{V}_{2}\mathbb{C}\mathbf{V}_{1}\); that is, \(\mathbf{H}_{n}\) is not orthogonal to the polar code word. \(\square\)  
To explain the above theorem more understandably, a polar code length \(n^{\prime}\) is selected to calculate generator matrix \(\mathbf{G}_{n^{\prime}}\); then, some rows are removed according to certain rules to obtain \(\mathbf{G}^{\prime}=\mathbf{G}_{n^{\prime}}(A)\). If the real code length of the codeword and the positions set of all the information bits is \(A\), which can be obtained by the GA algorithm, the dual space \(\mathbf{H}_{n^{\prime}}\) is orthogonal to the intercepted codeword. This is the basic principle we use to identify polar parameters.
# Daily Flood Monitoring Based on Spaceborne GNSS-R Data: A Case Study on Henan, China
## 2 Materials and Methods
### Study Area  
Henan is located in central China. The province is bounded by latitude 31\({}^{\circ}\)23\({}^{\prime}\)-36\({}^{\circ}\)22\({}^{\prime}\) north, longitude 110\({}^{\circ}\)21\({}^{\prime}\)-116\({}^{\circ}\)39\({}^{\prime}\) east, bordering Anhui and Shandong in the east, Hebei and Shanxi in the north, Shaanxi in the west and Hubei in the south, a total area of 167,000 square kilometers. The terrain of Henan Province is high in the west and low in the east. It is composed of plains and basins, mountains, hills, and water surfaces. Most of them are located in the warm temperate area; and the south spans the subtropical area. The province has a continental monsoon climate with a transition from the northern subtropical area to the warm temperate area.  
Henan is on the verge of subtropical high in mid-July. The abundant water vapor in the atmosphere undergoes continuous and intense vertical ascension and turns into raindrops when it is cold, thus producing torrential rain. The Henan catastrophic flood disaster was caused by torrential rain. On 18 July 2021, Typhoon No. 6 'Fireworks' formed in the western Pacific region and approached China. A large amount of water vapor was transported from the sea to the inland of China under the guidance of the typhoon's peripheral and easterly airflow on the south side of the subtropical high pressure, which provided the rainfall in Henan. The entry of such warm air provides a constant and abundant source of water vapor. At the same time, the atmospheric circulation situation remains relatively stable. In mid-July, the western Pacific subtropical high and the continental high remain stable in the Sea of Japan and Northwest China, respectively. As a result, the low-pressure weather system between the two is stagnant and moves less into the Huanghuai area. The low-pressure weather system is conducive to the vertical upward movement of the atmosphere to produce precipitation. In addition, the particular topography of the Taihang and Funiu mountains in Henan Province has a convergent effect on the easterly airflow that transports water vapor, which makes the vertical ascent more intense and the rainfall stronger.  
Figure 1 is a map of Henan Province, including 17 prefecture-level cities and one provincial-level municipality. The cities affected by the flood are marked.
# Enzymatic Degradation of _Gracilariopsis lemaneiformis_
## 2 Results and Discussion  
### Chemical Analysis of polysaccharides  
The chemical compositions of the GLP and hydrolysis products produced by pectinase (GPP), glucoamylase (GGP), cellulose (GCP), xylanase (GXP), and \(\beta\)-dextranase (GDP) were obtained and shown in Table 1. The total sugar contents of the degradation products, except GXP, significantly increased relative to that of GLP, and GDP and GGP had the highest contents (Table 1). The contents of sulfate and protein were 18.71% and 1.10% in GLP, respectively, indicating that GLP was a sulfated polysaccharide. Moreover, enzymolysis had significant effects on the sulfate and uronic acid levels of the degradation products of the GLP. The sulfate contents of the degradation products except GGP decreased, and GCP possessed the lowest sulfate content (Table 1). Most of the GLP hydrolysates were desulfated at varying degrees, possibly because of long periods of degradation in an acidic environment [24]. After degradation, the contents of uronic acid in GPP and GXP obviously increased, whereas the content in GCP significantly decreased. The molecular weights of the GLP hydrolyses decreased at varying degrees (Table 1). Among them, GPP had the highest decrease in Mw, which dropped from 107 to 66 kDa, followed by the Mw of GDP, which decreased to 81 kDa.  
Monosaccharide composition will affect the activity of polysaccharides. As shown in Table 2, GLP was mainly composed of Gal (89.7%) with a lower level of Glu (2.3%) and Xyl (1.2%), which was consistent with the results obtained by [PERSON] et al. (2018) [25]. Enzymatic degradation significantly changed the monosaccharide composition of GLP. The degradation products showed a much higher Glu level than GLP and mainly consisted of Gal and Glu. The molar ratios of Gal and Glu in GLP, GPP, GGP, GCP, GXP, and GDP were 39.0:1, 1.8:1, 4.9:1, 0.3:1, 3.0:1, and 1.0:1, separately. In addition, GPP, GGP, and GDP contained a certain amount of Rho and Ara, while Man existed in GGP (10.9%), GCP (4.2%), GXP (0.8%), and GDP (11.1%). The differences in monosaccharide composition of these samples might be explained by the different hydrolyzed sites of different enzymes.