esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 EV Battery Chargers and Their Architectures
### Different Phase of Charger  
Electric vehicle charging equipment can be either single-phase or three-phase and can provide either unidirectional or bidirectional power flow. Three-phase chargers are utilized in public EV charging stations for faster charging while single-phase chargers are typically used for indoor or residential charging applications [67].  
Single-Phase Charger: The most common type of chargers used in EVs are single-phase chargers. They have emerged as the preferred option for domestic charging because of their low cost and ubiquitous availability, making them the most economical option. Single-phase chargers allow for the slow-motion charging of EVs at a rate of up to 7 kW. Because it enables the battery to fully charge before morning, this charging technique is ideal for overnight use. The benefits and drawbacks of Single-Phase Charger are analyzed critically in Table 12.  
Three-Phase Charger: The optimization of the charging output in EVs can be achieved through the utilization of a three-phase charger, which has the potential to deliver a maximum power of 22 kW. Compared to their single-phase counterparts, three-phase chargers are relatively costlier and necessitate a power source that has three phases. The expeditious charging capabilities of said charging stations are widely acknowledged, as  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Type of Connector** & **North America** & **China** & **Japan** & **EU** & **All Market except EU** & **India** \\ \hline AC Connector & & & & & & \\ \hline Plug Name & J1772 (Type-1) & GB/T & J1772 (Type-1) & Memnekes (Type-2) & Commando: IEC62196-2 & IEC60309 \\ DC Connector & & & & & & \\ \hline Plug Name & CCS-1 & GB/T & CHAdeMO & CCS-2 & TESLA & GB/T, CHAdeMO, CCS-2 \\ \hline \hline \end{tabular}
\end{table}
Table 11: Different types of connectors used in EV application throughout world.  
they possess the capacity to fully charge an EV within a concise timeframe. Table 13 presents a critical review of the benefits and drawbacks of Three-Phase Charger.
## 5 Conclusions  
Optimized swab and surge operations contribute to a reduction in tripping time, and hence, reduce non-productive time. This paper evaluates physics-based swab and surge simulation and the data-driven-based machine learning modeling of field surging field datasets.  
The summary of the analysis shows that:  
* Deviations of swab surge model predictions from each model are inconsistent.
* Physics-based models generally require model calibration based on accurately measured data.
* The reviewed physics models do not consider all operational parameters, constraints, fluid properties, and non-uniform eccentricity. Moreover, it is difficult to quantify these parameters precisely in a drilling well.
* Data-driven-based modeling predicts both training and unseen test data with higher accuracy.  
The application of ML models on the swabing pressure example presented in this paper indicates the potential of deploying an intelligent solution as online- or offline-based modeling. This will enable drilling engineers to perform drilling optimization and better plan wells.  
A.M. Conceptualization, Methodology, Data processing, Software simulation, ML modeling, Testing, Result Analysis, Interpretation, and Writing. M.B. Methodology, Draft Manuscript Preparation, Supervision, Review, and Editing. R.D. Supervision, Project administration, Funding acquisition, Review, and Editing. All authors have read and agreed to the published version of the manuscript.  
No external funding.  
Not applicable.  
We thank Schlumberger for providing free Drillbench software to conduct the swab/surge simulation.  
The authors declare no conflict of interest.
# Polar Code Parameter Recognition Algorithm Based on Dual Space
## 4 Numerical Simulation  
We first examined the algorithm validity and then executed the recognition algorithm presented in Section 3.4 to examine the influence of different factors. Then, the performance and complexity were compared with that of the algorithm presented in [15; 16]. Unless otherwise stated, the simulation takes the same parameters as in Section 3.4. Since this paper examines the problem of polar code parameter recognition under the AWGN channel, the simulations here were confined to the AWGN channel.
## 4 Analysis of Numerical Calculation Results
### Displacement Response  
The soil layer lateral deformation induced by the earthquake exerted pressure on the underground structure, which will cause relative displacement of the underground structure itself, resulting in excessive internal force in the structure or dislocation of pipe joints and damage.  
The circular tunnel deformation under earthquake conditions is generally an approximate ellipse symmetrical about the 45\({}^{\circ}\) axis [23]. In this study, take the horizontal displacement at the bottom of pipe as zero, the horizontal displacement at different heights of the pipe is obtained and the relative horizontal displacement curve is drawn. Figure 8 is the relative horizontal displacement curve of the upper and lower pipe jacking tunnels under different earthquake intensities.  
Figure 8: Relative horizontal displacement distribution curves: (**a**) Upper pipe jacking tunnel; (**b**) Lower pipe jacking tunnel.  
Figure 7: Acceleration time history curves at the bottom of pipe jacking.  
The following conclusions can be drawn: (1) The relative displacement curve of the upper pipe jacking structure presents an inverse S-shaped distribution and the maximum value of the relative displacement is located at the arch shoulder, which is basically located on the 45\({}^{\circ}\) symmetry axis of the pipe jacking and is consistent with the deformation of the circular tunnel. Meanwhile, the relative displacement of the upper part of the pipe does not continue to increase, which indicates that the soil deformation has less constrained effect on the top of the circular pipe jacking tunnel and the circular section is more conducive to resisting earthquake deformation. (2) The relative horizontal displacement curve of the lower pipe jacking tunnel along the height changes significantly. The displacement in the lower half of the pipe is basically constant, the maximum value is reached quickly and then the relative displacement decreases with the increase of the height, which is related to the larger deformation constraint effect due to the lower pipe being semi-embedded in the rock. (3) The relative horizontal displacement of the upper pipe jacking is more than twice that of the lower pipe jacking, which indicates that the closer to the ground, the larger the overall deformation of the underground structure. However, because the relative horizontal displacement in the soil-rock interface area changes sharply and the relative displacement curve in the upper soil layer is relatively gentle, this will lead to the pipe joints located in the lower soil rock stratum being more prone to deformation damage.
# Development and Evaluation of a LiFi-Transceiver Module for TMTC Intra-Satellite Communication +
## 2 Related Work  
The topics of LiFi, OWC or Visible Light Communication (VLC) for commercial applications are extensively presented and explained in [11; 12; 13]. LiFi is of great interest for the upcoming mobile radio standard 6G, particularly because of its high bandwidths [14]. However, the focus of this work is TMTC intra-satellite communication applications where high-bandwidth is less important but small form factors and reliability are required.  
There are already some works that use OWC technologies for intra-satellite communication. The FOTON-M3 mission and the Venus Express OWLS Flight Technology Demonstrator used and demonstrated an Optical Wireless Links for Intra-Satellite Communications (OWLS)--Controller Area Network (CAN) bus [15]. The OPTOS-Satellite is the first satellite whose communication bus is completely wireless and based on the OWLS-CAN bus [16; 17]. OWLS technology should mainly work as physical-layer substitution with zero or minimum impact on the network architecture [15]. In contrast, the presented work in this paper not only deals with the physical layer consisting of components and modulation, but also includes the coding of the data to make communication even more reliable. Furthermore, OWLS is based on infrared, while our work uses visible light.  
Similar to our work, Ref. [18] presents an OWC system for intra-satellite communication specifically designed for CubeSats up to 3U. Their main focus is the front-end for high throughput without considering possible control or Forward Error Correction (FEC) mechanisms. They used a Vertical Cavity Surface-emitting Laser (VCSEL) with a ball lens for better diverging light and an Avalanche Photodiode (APD) with integrated TIA, and they measured the BER and the optical power, achieving a data rate up to 100 Mbit/s and a distance of 40 cm.
## 3 Results
### Force Characteristics Results of Segment
#### 3.3.5 Influence of Backfill Layer Thickness on Segment Forces  
To provide structural strength, backfill materials, such as gravel and cement slurry, must be used to fill the space between the segments and the initial support while building a shield tunnel that passes through a mining region. As shown in Table 11 and Figure 7e, the stress curves of the segments with various backfill layer thicknesses were produced to analyse the impact of the backfill layer on the stress of the segments. The backfill layer thicknesses were 0.26, 0.28, 0.30, 0.32, 0.34, 0.36 and 0.38 m. It can be observed that the maximum bending moment of the segment has a positive correlation with the backfill layer thickness and increases as the layer thickness increases. Although the total size of the change is minimal, the change in the thickness of the backfill layer has a significant impact on the rate at which the maximum axial force increases.
## 3 Cold-Bending Test Results and Discussion
### Influence of Cold-Bending Curvature on Cold-Bending Stress and Its Distribution  
By comparing the cold-bending stress nephograms of specimens with the same interlayer thickness and different cold-bending curvatures in Figure 5, it could be concluded that as the cold-bending curvature became larger, the cold-bending stress at the two adjacent corner points of the cold-bending corner increased significantly, and the cold-bending stress distribution on the glass panels became more polarized while keeping a saddle-like shape.  
The cold-bending stress values of the key points on the tensile (lower) surface of each specimen are listed in Table 2. Because the maximum coupling stress in the uniform load tests was located at the panel center, the cold-bending stress of testing point S22 was also included.  
Judging from Table 2, when the interlayer thickness remained unchanged, the cold-bending stress rose with greater cold-bending curvature. More specifically, when the cold-bending curvature increased by 0.2%, the maximum cold-bending stress also rose by 33% on average, demonstrating a significant correlation between the two values.  
Figure 5: Cold-bending stress nephograms on the lower surface (MPa). (**a**) SJ1; (**b**) SJ2; (**c**) SJ3; (**d**) SJ4; (**e**) SJ5; (**f**) SJ6; (**g**) SJ7; (**h**) SJ8.  
The relationships between the cold-bending curvature and the cold-bending stress at testing points S14, S22, and S30 are drawn in Figure 6 to give a more intuitive demonstration. Due to the geometrical nonlinearity caused by the cold bending, the cold-bending stress showed an increase with declining growth rates along greater cold-bending curvatures, suggesting that the effect of cold-bending curvature on the cold-bending stress is stronger at the early stage of cold-bending loading.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Specimens** & **Testing Point S14** & **Testing Point S22** & **Testing Point S30** \\ \hline S1 & 11.06 & 3.86 & 15.80 \\ S2 & 17.51 & 5.95 & 24.32 \\ S3 & 22.42 & 7.65 & 31.58 \\ S4 & 26.04 & 9.05 & 37.17 \\ S5 & 13.76 & 4.43 & 19.31 \\ S6 & 20.91 & 7.33 & 29.15 \\ S7 & 26.65 & 9.45 & 37.28 \\ S8 & 31.23 & 11.28 & 43.63 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Cold-bending stress results (MPa).  
Figure 6: The cold-bending stress versus cold-bending curvature curves. (**a**) Testing point S14; (**b**) Testing point S22; (**c**) Testing point S30.
Consequently, they undergo changes in the processes of oxidation, hydrolysis, and polymerization [12]; thus, a number of compounds with different molecular weights are formed, which affect the health safety of food and its sensory acceptability [13,14]. Among the many methods of protecting fats against negative changes and degradation is the use of antioxidants that protect fatty acids against oxidation, e.g., synthetic (butylated hydroxytoluene-BHT, butylated hydroxyanisole-BHA, tert-butylhydroquinone-TBHQ, gallates, natural tocopherols, and phenolic compounds obtained as an extract from different plants) [15], and also encapsulation, which allows for the protection of compounds against a potentially aggressive environment yet this also often releases them in an active form in certain places of the gastrointestinal tract. In addition to the commonly used encapsulation method in saccharide matrices (e.g., using maltodextrin) [16,17], yeast cells are also known for their ability to absorb large amounts of both hydrophobic and hydrophilic substances. Yeast-based microcapsules (YBMCs) significantly increase the oxidative stability of the active ingredient compounds encapsulated in them compared to the methods of traditional encapsulation in polysaccharide shells [18]. Both native yeast and yeast subjected to technological processes, improving their ability to bind active substances, can be used for the encapsulation process. The main techniques used to empty yeast cells are plasmolysis, autolysis, and enzymatic hydrolysis [19]. Cold-pressed oils contain significant amounts of MUFA, PUFA, but also other biologically active compounds, which makes them difficult to store and use in food production, especially during thermal processing. Bearing the aforementioned in mind, the aim of this study was to evaluate the possibility of using _S. cerevisiae_ yeast cells as an encapsulating carrier for cold-pressed oil blends with a 5:1 ratio of \(\omega 6/\omega 3\) fatty acids to protect against adverse oxidative changes and in order to maintain high biological activity. To date, this method has not been used to protect oil blends with such a ratio of nutritionally important fatty acids. The obtained microcapsules were characterized in terms of their morphology and particle size distribution, but also their properties were examined using DSC, FT-IR, and low-field NMR techniques.
# A Tolerance Type Screening Method Based on Similarity Evaluation
## 5 Discussion
### Comparative Analysis of Evaluation Calculation Methods  
Taking Figure 7 as an example, compare and analyze the differences between the similarity evaluation formula in this article and the method provided in reference [17]. According to the similarity element analysis, the tolerance element set, spatial relationship set, composition element set, and usage function set of the target case are obtained separately. At the same time, the tolerance element set, spatial relationship set, composition element set, and usage function set of the case are obtained, as shown in Table 8.  
\begin{table}
\begin{tabular}{c c c c} \hline
**Targete Case** & **Resource Cases** & \(SY(E_{\text{tc}},E_{\text{to}})\) & \(SN(E_{\text{tc}},E_{\text{to}})\) \\ \hline \multirow{2}{*}{7a} & 7b & 0.6523 & 0.5850 \\ \cline{2-4}  & 7c & 0.4594 & 0.5850 \\ \hline \end{tabular}
\end{table}
Table 7: The similarities of tolerance elements considering relative scale or not.  
Figure 7: The geometric tolerance types in the case with the highest similarity.  
The similarity between target part 1 and case part 1 and case part 2 is calculated according to Equations (5), (9)-(11), and (13), respectively, and the calculation results are shown in Table 9. According to the calculation results, it can be seen that, for the same target case, the similarity assessment method proposed in this paper, the similarity assessment value between the tolerance specification case shown in Figure 7b, and the target case shown in Figure 7a is 0.7678, while the similarity assessment value between the tolerance specification case shown in Figure 7c and the target case shown in Figure 7a is 0.7841, which is shown in Table 8. The resource case has a more practical reference value than the resource case with a low similarity value because the use function of the resource case part Figure 7c is consistent with the use function of the target part Figure 7a, and the type of tolerance applied in the case is more in line with the screening requirements. While using the calculation method proposed in the literature [17], the similarity assessment values obtained by the calculation results are equal, and the value is 1. The similarity assessment results have no differentiation and cannot provide better guidance for the screening of tolerance types of the target case.
# Inverse Halftoning Methods Based on Deep Learning and Their Evaluation Metrics: A Review
## 2 Inverse Halftoning Technology for Digital Halftoning
### End-to-End Learning Method Based on Training of Multiple Sub-Networks (EEBMN)
#### 2.2.2 Deep Learning with Pre-Training (DLWPT)
To make the residual sub-network and the sub-network composed by V1, V2, and IH collaborate more seamless, the pixel value loss and the gradient loss are combined to fine-tune the parameters of two networks. Compared with the method in [21], the advantage of [22] is the introducing of the gradient guided block and residual learning model, which are beneficial in enhancing the fine image details. Nevertheless, some noise patterns in restored images still exist. Considering the restoration of non-smooth areas such as texture and details will affect the reproduction of smooth areas in a single network. [PERSON] et al. [23] proposed an opposite method that restores smooth area prior to restoring details. The network architecture is shown in Figure 9. Firstly, the halftone image is divided into flat area and non-flat area. Then, the pre-trained local adaptive adjustment method is used to smooth the flat area and the residual blocks are adopted to further construct the smooth area. The residual blocks consist of two convolutional layers, two batch normalizations, and ReLU. The non-flat area channel is restored by applying residual blocks alone. Finally, the reconstructed flat area and non-flat area are combined to generate an inverse halftone image. The method in reference [23] is proposed for bit-depth expansion and obtains favorable visual quality, but the halftone dot noises cannot be removed clean because the objective of this method is not designed for inverse halftoning. Figure 8: The network architecture in references [21] and [22].
## 4 Electromagnetic Exposure Safety Assessment and Uncertainty Quantification  
### Safety Assessment  
In order to assess the safety of the electromagnetic radiation received by the human head, the SAR calculation was performed based on the constructed electromagnetic simulation model. The selection of the simulation platform was a key task in the current analysis of the electromagnetic radiation. There are studies based on Comsol Multiphysics software to solve the computational problems of bioelectromagnetic models of heat transfer processes [30]. Compared to Comsol, CST has the advantage of balancing high accuracy and high speed when dealing with the electromagnetic problems of mobile phones. Therefore, CST electromagnetic simulation software was used in this paper to calculate the SAR of electromagnetic radiation from mobile phones to the human head. The simulation was simulated by CST and the radiation pattern is shown in Figure 6.  
Figure 5: Electromagnetic radiation scenario. (**a**) Simulation model diagram, (**b**) mesh diagram.  
Figure 6: Radiation pattern at four frequencies. Shown are (**a**) 2100 MHz, (**b**) 2300 MHz, (**c**) 3500 MHz, (**d**) 5200 MHz.  
It can be seen in Figure 6 that the radiation direction of the mobile phone antenna close to the human head was not consistent at different frequencies. At 2100 MHz and 2300 MHz, the antenna showed a relatively clear main lobe, and the beam direction was toward the human head; at 3500 MHz and 5200 MHz, the electromagnetic radiation of the mobile phone antenna showed spurious side lobes. The SAR value of the human head is related to the radiation area of different frequencies. Therefore, in the quantitative analysis of the electromagnetic radiation to the human head from mobile phones, this paper considered the SAR values of the human head at 2100 MHz, 2300 MHz, 3500 MHz, and 5200 MHz. The results obtained are shown in Figure 7.  
From the simulation results, the SAR value at 2100 MHz was 0.9580 W/kg, that at 2300 MHz was 1.4431 W/kg, that at 3500 MHz was 1.7621 W/kg, and that at 5200 MHz was 1.7737 W/kg. After comparing with the ICNIRP standard limit, we found that the SAR value of the mobile phone's electromagnetic radiation to the human body obtained in this paper was below the safety limit of the human body's electromagnetic environment. The safety of the human head exposure to electromagnetic radiation from mobile phones was assessed.