esa-sceva/satcom-chunk-collection huggingface dataset:
# Effects of Grout Compactness on the Tensile Behavior of Ground Splice Sleeve Connectors
## 2 Tensile Tests on GSS Connectors with Different Compactness
### Preparation of GSS  
The sleeves used in the experiments were manufactured by Shanghai Jusong Engineering Material Corporation, and they were cast from ductile iron. Four types of rebar with a nominal diameter \(d\) of 18 mm, 20 mm, 22 mm, and 25 mm were used, denoted as D18, D20, D22, and D25, respectively. The length of rebars and sleeves were designed according to the core [26], as shown in Figure 1. More specifically, \(L\) is the length of the sleeves, \(L_{1}\) is the gauge length of elongation, \(D_{\text{g}}\) is the outer diameter of the sleeves, \(d_{\text{si}}\) is the inter diameter of the sleeves, and \(t_{\text{sl}}\) is the pipe thickness of the sleeves. Their dimensions are shown in Table 1. The strength grade of the special purpose grouting material was \(M80\). Manual pressure grouting was adopted for sleeve grouting, and the grouting tool was shown in Figure 2. The expansion agent was added in the grouting material in order to fill pores in the hardening process. Therefore, it is feasible to classify the compactness of grouted sleeves by controlling the volume of grouting material. Figures 3 and 4 show the schematic diagram and pictures of four compactness cases (100%, 90%, 70%, and 50% compactness), respectively. After grouting, the connectors were cured at a temperature of 20 \({}^{\circ}\)C and relative humidity of 90% for 28 days. After curing, the specimens were placed in a normal indoor environment for tensile loading tests [2]. For each type of GSS (D18, D20, D22, D25), three specimens were fabricated in accordance with the technical specification [26].  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Types of Sleeves** & **Length \(L\)/mm** & **Outer Diameter \(D\)/mm** & **Pipe Thickness \(t_{\text{sl}}\)/mm** & **Inner Diameter \(d_{\text{sl}}\)/mm** \\ \hline D18 & 348.0 & 48.0 & 4.0 & 40.0 \\ D20 & 380.0 & 51.0 & 4.5 & 42.0 \\ D22 & 412.0 & 54.4 & 5.2 & 44.0 \\ D25 & 460.0 & 59.4 & 6.2 & 47.0 \\ \hline \hline \end{tabular}
\end{table}
Table 1: The dimensions of the sleeves.  
Figure 4: Pictures of different grout compactness. (**a**) 100% compactness. (**b**) 90% compactness. (**c**) 70% compactness. (**d**) 50% compactness.  
Figure 3: Schematic diagrams of different grout compactness. (**a**) 100% compactness. (**b**) 90% compactness. (**c**) 70% compactness. (**d**) 50% compactness.  
Figure 2: Schematic diagrams of grout sleeve.
# An Interactive Real-Time Locating System Based on Bluetooth Low-Energy Beacon Network +
## 4 Implementation and Experiments
### Discussions
#### 4.5.1 The Communication Range of Bluetooth Beacons  
Theoretically the transmission range of Bluetooth 4 can be up to 100 m [35]. In our experimental deployment the maximum distance between neighboring Mesh Beacons is about 8 to 10 m. The reason is that after several field tests, we found that if the distance is greater than 10 m, packet losses would become significant. This is due to the limited transmission range of the development boards we used, as well as the non-line-of-sight deployment of the devices. Since we need to deploy the Mesh Router in our own lab for a stable network connection to the Application Server (a PC in the same lab), we have no choice but to deploy part of the system non-line-of-sight. In real deployments such as airports or exhibition centers, one can choose Bluetooth devices with stronger output power or external antennas to increase the radio coverage, along with proper line-of-sight placement of the Bluetooth devices to improve the transmission quality. Doing so can also reduce the total number of devices needed to cover the whole field of deployment.
# Self-Isolated Dual-Mode High-Pass Birdcage RF Coil for Proton and Sodium MR Imaging at 7 T MRI
## 5 Conclusions  
In conclusion, the study has detailed the development and construction of the self-isolated DMBC RF coil designed for \({}^{1}\)H and \({}^{23}\)Na MR imaging at UHF, 7 T. Through comparative performance evaluations against STBC RF coils, we have established the utility and practicality of the DMBC RF coil, demonstrating its capacity to enhance \({}^{1}\)H and \({}^{23}\)Na MR imaging with minimal impact on image quality. Furthermore, the DMBC RF coil is not subject to the performance degradation typically caused by active switching schemes or limiting patient access, thereby offering a more efficient workflow for multi-nuclei MR imaging. The design of the DMBC RF coil is inherently flexible and can be adapted to resonate at various frequencies, accommodating a broad spectrum of x-nuclei, including \({}^{13}\)C, \({}^{31}\)P, and \({}^{19}\)F.  
**Author Contributions:** Conceptualization, C.-H.O.; methodology, Y.-J.J., S.-W.P. and C.-H.O.; validation, Y.-J.J., S.K., C.H.M. and C.-H.O.; formal analysis, Y.-J.J. and C.-H.O.; investigation, [PERSON]-J.J. and C.-H.O.; writing--original draft preparation, Y.-J.J.; writing--review and editing, [PERSON]-J.J., S.K., C.H.M. and C.-H.O.; visualization, Y.-J.J.; support and supervision of MRI experiments, Y.S., J.-H.C. and C.-H.O.; supervision, C.-H.O.; project administration, C.-H.O.; funding acquisition, C.-H.O. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Institute of Information and Communications Technology Planning and Evaluation (IITP) grant funded by the Korea government (MSIT) (grant no. 171160590, Development of digital twin based real-time untact cardiovascular disease prediction and monitoring technology).  
The study was conducted and approved by the Institutional Review Board of Korea University (KUIRB-2021-0143-04, date of approval--25 April 2023).  
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.  
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy.  
The authors would like to acknowledge ZMT for providing the free academic license of Sim4 Life used in this study.  
The authors declare no conflict of interest.
# Low-Power, High Data-Rate Digital Capsule Endoscopy Using Human Body Communication
## 2 CEHBC System Architecture
### CEHBC Physical Structure
The LineSync block decides the sign of the data and adjusts the synchronization of each line from the specific information data and the image data. The FS de-spreader de-spreads the data using Walsh code. The P2S converts the parallel bits to serial bits. The CRC decoder block performs error detection. Table 1 shows the main parameters used in the CEHBC system that are presented in this paper. The CEHBC system generates the signal from the capsule inside the body and receives signals via the receiving electrodes attached to the body exterior. The CEHBC system is an example of in-body to on-body communication. The main clock of the CEHBC system uses a 32 MHz signal and the FSDT modulation method with 64 bit Walsh code. Therefore this system could spread the spectrum and generate a signal, of which the center frequency varies from direct current (DC) to 16 MHz. However, the CEHBC system utilizes the 8-16 MHz frequency band, which has less signal attenuation effect in the body. The resolution of the transfer image data is 480 \(\times\) 480 byte, and it is transmitted at 3.13 f/s. One frame requires 319,440 \(\upmu\)s of transmission time. It is possible to generate data rates up to 6 Mbps with FSDT high-rate mode modulation. The CEHBC system takes the combination structure formed with the short preamble generator output (SP) and the long preamble generator output (LPn). The SP takes on the properties of the 7-bit pseudo-random noise (PN) code; whereas the LPn has  
the properties of the 12-bit PN code. The combination structure has the advantage of increasing the accuracy of the receiving synchronization while having less hardware complexity. This system uses the LineSync generator, which keeps signal synchronization per line to maintain performance for data that is received over long transmission times. The LineSync uses the properties of the 5-bit PN code. It also exploits the CRC formed from a 12-bit polynomial to find out whether an error has occurred.
## 1 Introduction  
Research on the frost behavior of soils has been carried out since the 1960s in the cold regions of northern America, northern Asia, and northern Europe. Recent infrastructure developments of road and railways networks in Norway have led to renewed interests on the geotechnical challenges associated with slope stability under freezing-thawing cycles. The freezing-thawing cycles may cause slope instability due to soil deformation and strength reduction [1; 2; 3].  
When saturated fine-grained soil is subjected to freezing temperatures (below 0 \({}^{\circ}\)C), part of the water in the soil voids is frozen to ice. A film of unfrozen water closed to the frozen soil particles is absorbed into the ice and formulate ice lenses. In this procedure, water is sucked up from the unfrozen soil void developing a gradient in the water potential in the same direction as the temperature gradient. [4]. Once freezing stops, due to the air temperature above 0 \({}^{\circ}\)C, the thawing progresses from the ground surface begins. During thawing, water escapes easily through the spaces formerly occupied by the ice, leaving the void empty and leading high compressibility and low soil strength [5]. This freezing-thawing cycles in a soil can significantly impact on the stability of a slope. The impact of freezing-thawing on the stability of slopes has been studied by numerical simulations using, e.g.,coupled thermal-hydraulic-mechanical models [6]. Such numerical research concluded that freezing of the soil on the slope increases its volume by attracting water from the groundwater table, while thawing reduces the effective soil strength by increasing hydraulic gradients, which can lead to slope failure ([PERSON], 2004) [7]. To prevent slope failure, slope monitoring practices typically involve the periodic measurement of slope stability by scanning the slope surface to identify and quantify the nature and extent of pit slope movements [8]. Field monitoring techniques may also include devices that measure matric suction and volumetric water content [9].  
The individual study of laboratory testing, numerical analysis, or field monitoring on the slope has been done to evaluate the stability of a slope subjected to freezing-thawing cycles. However, there are few studies available that have tested the soil in the laboratory, evaluated the slope stability, and monitored a man-made real scale slope. The purposes of this study are to investigate the changes of the slope stability at the \(\mathcal{O}\)ysand site by performing site investigation (Section 2), laboratory test (Section 2), to evaluate the governing factor influencing the slope stability using numerical simulations (Section 3), establishing a suitable monitoring system and predicting the slope stability based on the measured data (Section 4).
## Materials and Methods
### Amino Acids Analysis  
The amino acids composition was determined using the oxidative-hydrolysis method by the AOAC Official Method 994.12 [33]. Samples (0.5 g) of each species were oxidised with a 5 mL of chilled hydrogen peroxide/formic acid/phenol mixture for 16-18 h. The mixture was prepared at two steps; (a) mixing 735 mL formic acid with 111 mL deionised water then adding 4.73 g phenol, (b) dispensing 10 mL of 30% hydrogen peroxide into a 100 mL volumetric flask then making up to volume with the formic acid/phenol solution. Subsequently, 0.84 g of sodium metabisulfite and 50 mL of the hydrolysis reagent (6 M HCl) were added to each sample and then placed in the oven at 110 \({}^{\circ}\)C for 24 h with loosened bottles' lids to prevent the gas pressure building up. The pH of each sample was adjusted to 2.20 using 1 N sodium hydroxide and 4 mL of internal standard (norleucine) was added. Samples were then rinsed using tri-sodium citrate (pH 2.20) and the flask volume was filled to 200 mL. Diluted hydrolysate (20 mL) was centrifuged (Biofuge stratos) at 3000 rcf for 2 min. The supernatant was filtered with a 0.22 \(\upmu\)m filter syringe. Subsequently, amino acids were separated by ion-exchange chromatography (Pharmacia Biochrom, Cambridge, UK) and determined by reaction with ninhydrin using photometric detection at 570 nm (440 nm for proline).  
Essential amino acid score (\(EAAS\)) was calculated according to the Equation (1):  
\[EAAS = \sqrt[n]{\frac{eaa1}{EAA1}\times\frac{eaa2}{EAA2}\times\ldots\ldots \frac{eaan}{EAAn}\ldots} \tag{1}\]  
where \(eaa1\) is the concentration of one essential amino acid (mg) per g protein of the sample and \(EAA1\) is the concentration of the same essential amino acid (mg) per g of the reference protein. An essential amino acid score of \(>\) 0.95 defines a \"high\" quality protein, a score of 0.86-0.95 implies a \"good\" quality protein, a score of 0.75-0.86 indicates a \"useful\" protein and a score of \(<\) 0.75 means an \"inadequate\" protein according to the FAO/WHO/UNU [34].
# The Influence of Laser Linewidth on the Brillouin Shift Frequency Accuracy of BOTDR
## 2 Numerical Simulation
Further, the BFS measurement error was calculated based on Equation (1) and normalized as shown in Figure 5b. From Figure 5, it is obvious that the SNR is improved as the pulse width increases and the laser linewidth narrows. Under the same pulse width, the BFS error, \(\Delta\alpha\), increases sharply as the laser linewidth broadens from 0.1 kHz to 10 kHz, and grows slowly when the laser linewidth exceeds 10 kHz. Based on the above numerical simulations, it is theoretically proven that the BFS accuracy of BOTDR is improved as the laser width narrows and the pulse width increases. \[G_{\text{B}}(f)=g_{0}\frac{(w/2)^{2}}{\left(f-f_{\text{B}}\right)^{2}+\left(w /2\right)^{2}} \tag{2}\]7 Numerical simulation results versus laser linewidth under different pulse widths: (**a**). Relative signal-to-noise ratio (SNR); (**b**). BFS accuracy. Model parameters utilized for simulations are listed in \[G_{\text{B}}(f)=g_{0}\frac{(w/2)^{2}}{\left(f-f_{\text{B}}\right)^{2}+\left(w /2\right)^{2}} \tag{2}\]8
# Modeling and Simulation of IGCC Considering Pressure and Flow Distribution of Gasifier
## 3 IGCC System Modeling  
The volume-resistance (V-R) method is utilized for gasifier modeling to obtain several simplified ordinary differential equations to describe the pressure and flow characteristics of the gasification process [16]. Furthermore, we deal with the IGCC system simulation in this paper, and thus the modular modeling method is utilized to build the gas turbine and steam system model. Generally, the flow characteristics can be described through basic equations in models of power machines, for example the Frugal formula in the model of the steam turbine. Therefore, the pressure state equations are proposed in other modular components, such as the combustor and heat exchanger.
## 1 Introduction  
### Background  
The rapid development of human information society has seen the demands for ubiquitous network access and rapid growth of various services. As a result, increasingly more attention has been paid to integrated systems and future-oriented traffic types (as follows).
## 2 System Model
 \tag{5}\]  
Therefore, the overall signal to noise ratio (\(SNR\)) from S to D can be given by  
\[SNR=\frac{\mathrm{E}\Big{(}\big{|}signal\Big{|}^{2}\Big{)}}{\mathrm{E}\big{[} noise\big{|}^{2}\Big{)}}=\frac{\frac{(1-\rho)P_{s}|h_{sr}|^{2}\big{|}h_{rd_{i}} \big{|}^{2}}{d_{i}^{m}}\frac{\beta^{2}}{\big{|}h_{rd_{i}}\big{|}^{2}}}{\big{|} \frac{\big{|}h_{rd_{i}}\big{|}^{2}\big{|}^{2}h_{rd_{i}}\big{|}^{2}}{d_{i}^{m}} +N_{0}}=\frac{(1-\rho)P_{s}|h_{sr}|^{2}\big{|}h_{rd_{i}}\big{|}^{2}}{\big{|}h_ {rd_{i}}\big{|}^{2}d_{sr}^{m}N_{0}+\frac{N_{0}d_{i}^{m}d_{sr}^{m}}{\beta^{2}}}. \tag{6}\]  
After doing some algebra, using the fact that \(\mathrm{N_{0}}<<\mathrm{P_{r}}\) and denote \(\gamma_{1}=|h_{sr}|^{2},\gamma_{i}=\big{|}h_{rd_{i}}\big{|}^{2}\), Equation (6) can be rewritten as  
\[SNR=\frac{(1-\rho)P_{s}P_{r}|h_{sr}|^{2}\big{|}h_{rd_{i}}\big{|}^{2}}{\big{|} h_{rd_{i}}\big{|}^{2}d_{sr}^{m}P_{r}N_{0}+(1-\rho)P_{s}|h_{sr}|^{2}N_{0}d_{i}^{m}}. \tag{7}\]  
Combined with Equation (2), we have the \(SNR\):  
\[SNR=\frac{\eta\rho(1-\rho)\psi|h_{sr}|^{2}\big{|}h_{rd_{i}}\big{|}^{2}}{\eta \rho\big{|}h_{rd_{i}}\big{|}^{2}d_{sr}^{m}+(1-\rho)d_{i}^{m}} \tag{8}\]  
where \(\psi=P_{s}/N_{0}\). In our proposed model, we assume that the S-R link belongs to a Nakagami-m fading channel and the R-D\({}_{l}\) link belongs to a Rayleigh fading channel. In the next section, we derive the analytical expression of OP and EC as in [26; 27; 28; 29; 30; 31].
# Self-Attention GAN for Electromagnetic Imaging of Uniaxial Objects
## 2 Theoretical Formulation
### Inverse Problem
\begin{bmatrix}[G_{3}]&[G_{4}]\\ [G_{4}]&[G_{5}]\end{bmatrix}\begin{pmatrix}I_{x}^{b}\\ I_{y}^{b}\end{pmatrix}  \tag{30}\]  
The relationship between \(I_{z}^{b}\) and the contrast \( \begin{bmatrix}\tau_{z}^{b}\end{bmatrix} \) is shown below:  
\[ \begin{pmatrix}I_{z,p}^{b}\end{pmatrix} =diag\Big{(} \begin{bmatrix}\tau_{z}^{b} \end{bmatrix} \Big{)} \begin{pmatrix}E_{z}^{b}\end{pmatrix}  \tag{31}\]  
while the relationship between \(I_{x,p}^{b}\) and \(I_{y,p}^{b}\) with the contrast \( \begin{bmatrix}\tau_{x}^{b}\end{bmatrix} \) and \( \begin{bmatrix}\tau_{y}^{b}\end{bmatrix} \) can be expressed as:  
\[ \begin{pmatrix}I_{x,p}^{b}\\ I_{y,p}^{b}\end{pmatrix} =diag\Bigg{(}\begin{bmatrix} \begin{bmatrix}\tau_{x}^{b} \end{bmatrix} &0\\ 0& \begin{bmatrix}\tau_{y}^{b}\end{bmatrix} \Bigg{)} \begin{pmatrix}E_{x}^{b}\\ E_{y}^{b}\end{pmatrix}  \tag{32}\]where \(p\) represents each incident wave, while \(\left[\tau_{z}^{b}\right]\), \(\left[\tau_{x}^{b}\right]\), and\(\left[\tau_{y}^{b}\right]\) correspond to the dielectric coefficient distributions derived through back-propagation. By applying the least squares method to all incident cases in Equation (31), we can derive the analytical solution for the n-th element of the contrast \(\left[\tau_{z}^{b}\right]\). \[\left[\tau_{z}^{b}\right]=\frac{\sum_{p=1}^{N_{i}}l_{z,\ p}^{b}\left(n\right) \cdot\left[E_{z}^{b}(n)\right]^{*}}{\sum_{p=1}^{N_{i}}\left\|E_{z}^{b}(n) \right\|^{2}} \tag{33}\]  
Likewise, incorporating all incidences from Equation (32) yields a least squares problem. The expressions for the n-th components of the contrast terms \(\left[\tau_{x}^{b}\right]\) and \(\left[\tau_{y}^{b}\right]\) can be explicitly obtained as follows:  
\[\left[ \begin{matrix}\left[\tau_{x}^{b}\right]&0\\ 0&\left[\tau_{y}^{b}\right]\end{matrix} \right]=\frac{\sum_{p=1}^{N_{i}}l_{x,p} ^{b}\left(n\right)\cdot\left[\left( \begin{matrix}E_{z}^{b}\\ E_{y}^{b}\end{matrix} \right)\left(n\right)\right]^{*}}{\sum_{p=1}^{N_{i}} \left\|E_{x}^{b}(n)\right\|^{2}} \tag{34}\]  
where \(N_{i}\) is the number of incident waves. The forward model in this study is rigorously derived from [PERSON]'s equations, and the scattered field is computed using the Method of Moments (MoM). This numerical formulation inherently satisfies the physical principles of reciprocity and continuity, owing to the mathematical properties of the Green's function and the enforcement of boundary conditions. The initial estimate of the permittivity distribution, obtained via the Back Propagation Scheme (BPS), is directly based on these physically consistent fields, thereby ensuring adherence to energy conservation at the initialization stage.
# Quantum Image Steganography Schemes for Data Hiding: A Survey
## 1 Introduction
[16]'s newest approach of using classical protocols to develop the double-layer matrix coding protocol. In addition, [PERSON] et al. [17]'s enhanced version of the exploiting modification direction protocol (EMD) [18] implements steganography in quantum contexts. The paper also discusses the four types of quantum noise channels, showing their effect on implementing steganography [19]. The structure of this survey paper is sketched in Figure 1, below. In this survey paper, we provide the necessary background and components found in the quantum image steganography field, including the quantum image representations commonly used for data hiding. Moreover, we discuss the available solutions for compensating for the lack of real quantum computers for the implementation process, and the use of high-performance computing (HPC for short) to simulate quantum machines. The main goal behind this paper is to present the latest advances in implementing quantum steganography and image steganography along with the recent improvements implemented in these fields. Furthermore, we explore the most recent methodologies proposed as well as a brief segment in each methodology explaining its background history and the inspiration behind it. The paper also covers the results of each method discussed and the improvement each has created compared to previous research papers. Our motivation behind conducting this survey is the absence of research papers summarizing the latest progress in quantum image steganography and the overall shortage of works presented in the quantum computing domain. In addition, we aim to encourage future research in quantum steganography, data hiding, and other related fields, by summarizing the most recent works presented in this domain and discussing the latest challenges faced in this domain. Additionally, our goal is to provide us and researchers interested in the HPC and quantum computing fields with an adequate source of information on all the necessary background to generate improvement in the quantum steganography field and quantum computing in general. The survey paper includes five sections. In Section 2, we provide the necessary background by describing quantum image representation, while a detailed analysis and comparison of various schemes are shown in Section 3. In Section 4, we discuss the points made in the previous sections as well as the future opportunities for researchers in quantum steganography. In addition, lastly, we conclude our paper in Section 5.