esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Additional CT-Measurable Parameters for Cardiovascular Risk Stratification
### Myocardial Scar
demonstrated that delayed phase cardiac CT could be a valid alternative to delayed enhancement CMR in detecting inflammatory segments in patients with acute myocarditis, with a diagnostic accuracy of 95% [162]. Furthermore, [PERSON] et al. showed that cardiac CT with delayed enhancement also provides a three-dimensional characterization of myocardial scars associated with ventricular tachycardias. This information may help to plan electrophysiological procedures such as electro-anatomic mapping and arrhythmias radiofrequency catheter ablation [163]. Lastly, delayed enhancement cardiac CT can be used to measure an index of diffuse myocardial fibrosis, which is named myocardial extracellular volume fraction (ECV) [164]. ECV can be estimated using the following method obtained from cardiac CT: ECV = (1-hematocrit) \(\times\) (\(\Delta\)HULV myocardium/\(\Delta\)HULV blood), where \(\Delta\)HU is the change in HU attenuation pre-contrast and in the delayed phase CT (HU delayed phase - HU pre-contrast) [157]. The measurement of ECV with cardiac CT can be helpful in the setting of non-ischemic cardiomyopathies, such as hypertrophic cardiomyopathy, cardiac amyloidosis, dilated cardiomyopathy, and sarcoidosis. Hence, several studies demonstrated that mean ECV values obtained with delayed phase cardiac CT are significantly higher in patients with hypertrophic cardiomyopathy, cardiac amyloidosis and dilated cardiomyopathy compared to healthy subjects [165; 166]. In these patients, delayed enhancement cardiac CT also assesses the identification of myocardial fibrosis areas with various delayed enhancement patterns (transmural, subepicardial, subendocardial, or mid myocardial).
# An In-Depth Assessment of the New BDS-3 B1C and B2a Signals
###### Abstract  
An in-depth and comprehensive assessment of new observations from BDS-3 satellites is presented, with the main focus on the Carrier-to-Noise density ratio (C/N\({}_{0}\)), the quality of code and carrier phase observations for B1C and B2a signal. The signal characteristics of geosynchronous earth orbit (GEO), inclined geosynchronous satellite orbit (IGSO) and medium earth orbit (MEO) satellites of BDS-3 were grouped and compared, respectively. The evaluation results of the new B1C and B2a signals of BDS-3 were compared with the previously B1I/B2I/B3I signals and the interoperable signals of GPS, Galileo and quasi-zenith satellite system (QZSS) were compared simultaneously. As expected, the results clearly show that B1C and B2a have better signal strength and higher accuracy, including code and carrier phase observations. The C/N\({}_{0}\) of the B2a signal is about 3 dB higher than other signals. One exception is the code observation accuracy of B3I, which value is less than 0.15 m. The carrier precision of B1C and B2a is better than that of B1I/B2I/B3I. Despite difference-in-difference (DD) observation quantity or zero-base line evaluation is adopted, while B1C is about 0.3 mm higher carrier precision than B2a. The BDS-3 MEO satellite and GPS, Galileo, and QZSS satellites have the same level of signal strength, code and phase observation accuracy at the interoperable frequency, namely 1575.42 MHz and 1176.45 MHz which are very suitable for the co-position application.  
BDS-3; B1C/B2a; comprehensive assessment; observation accuracy +
Footnote †: journal: Remote Sensing
# Optical Fiber Sensor with Stable Operating Point for AC Magnetic Field Measurement
## 3 Sensor Fabrication and Characterization  
### Fabrication Process  
Figure 1a-c shows the steps of the sensor fabrication process. Firstly, an HAF (Coractive, Quebec, QC, Canada; ATN-FB-22.1-2.6) was pre-treated by hydrogen loading to enhance its photosensitivity, and then it was spliced to a standard single-mode fiber (Corning, New York, NY, USA; SMF-28) by a commercial fusion splicer (FITEL, Tokyo, Japan; S178) (Figure 1a). Secondly, a section of the HAF was exposed by an excimer laser (Coherent, Santa Clara, CA, USA; Bragg Star S-Industrial, 248 nm) using a phase-mask with a pitch of 1072.88 nm to inscribe a segment of Bragg grating on the core of the HAF (Figure 1b). The length, original Bragg wavelength \(\lambda_{B}\), and full width at half maxima (FWHM) of \(\lambda_{B}\) of the fabricated HAFBG are 10 mm, 1549.50 nm, and 0.20 nm, respectively. To avoid Fresnel reflections, the other end-face of the HAF is cleaved at an 8\({}^{\circ}\) angle and the remaining HAF length is about 12 mm. Thirdly, the fabricated HAFBG sample and a prepared magnetostrictive rod with a square cross-section were placed on two separate three-dimensional manual adjustment stages and adjusted until the HAFBG was suspended above the magnetostrictive rod, after which two drops of 353 ND glue (Epoxy Technology, Billerica, MA, USA) were applied in the gap between the HAF and the magnetostrictive rod (Figure 1c). The 353 ND glue is obtained by mixing the 353 ND Part A and Part B with a weight ratio of 10:1. The distance between the two glue fixation points, that is, the effective sensing length, is around 10 mm. A microscope image of the fabricated sensor is shown in Figure 1d. The magnetostrictive rod is made by Terfenol-D (Suzhou A-one Special Alloy, Suzhou, China), which has a high saturation flux density of around 1 T, a high magnetostriction coefficient of over 1000 \(\times\) 10\({}^{-6}\), an ultralow resistivity of 60 \(\times\) 10\({}^{-8}\) Ohm-meters, and a thermal expansion coefficient of about 11 ppm/\({}^{\circ}\)C @ 25 \({}^{\circ}\)C. The length of the magnetostrictive rod is 12 mm, and the square cross-section is 2 \(\times\) 2 mm\({}^{2}\).  
Figure 1: _Cont._
# Influence of Preconditioning and Tunnel Support on Strain Burst Potential
## 3 Methodology
### Numerical Modeling of the Strain Burst and Mitigation Measures
#### 3.1.3 Integration of Mitigation Measures  
To model the shotcrete and rockbolts support system, an internal pressure is applied at the edge of the tunnel. The applied pressure is determined from the convergence-confinement method [58; 59]. The support characteristics have been defined using the RocSupport software Version 5.005 [60]. The rockbolts are considered to present a diameter of 34 mm, with a capacity of 0.354 MN. The spacing between the bolts is 0.2 m. The shotcrete presents a thickness of 0.30 m, a Young's modulus of 30 GPa and a Poisson's ratio of 0.2. The applied pressure is equal to 0.2 MPa (Figure 4), which means that the internal pressure  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**[PERSON]’s** & **[PERSON]’s** & **Uniaxial** & **Tensile** & **Hoek \& Brown** & **Hoek \& Brown** & **Hoek \& Brown** \\
**Modulus (E)** & **Ratio (v)** & **Compressive** & **Strength (\(\sigma\)t)** & **Strength (\(\sigma\)t)** & **Material** & **Material** & **Material** \\  & & & & **Constant \(a\)** & **Constant \(s\)** & **Constant \(m_{i}\)** \\ \hline
50 GPa & 0.25 & 120–320 MPa & 7 MPa & 0.5 & 1 & 25 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Mechanical and strength properties of the intact rock.  
Figure 4: (a) Geometry general and meshing of the model; (b) applied pressure of 0.2 MPa (in red) to simulate the support system and zone of destressing (in green).  
of the shotcrete and rockbolts is equivalent to 20% of the in situ stress, \(\sigma\)1. To be noted, this is an implicit way of modeling a rockbolts support system. To go further, one could explicitly define each rockbolt around the excavation. This has not been done in this work.  
To model the preconditioning by destress blasting, the method proposed by [PERSON] [61] is followed. This method proposes modeling the preconditioning by modifying the elastic constants that simulate the effect caused by induced fractures in the rock mass. To achieve this, the proposed model considers the parameters \(\alpha\) and \(\beta\) that represent the rock fragmentation and stress dissipation, respectively. For the proposed work, the parameter \(\alpha\) is taken as equal to 0.5 and the parameter \(\beta\) is taken as equal to 0.2. Considering these parameters, the elastic rock mass parameters are modified in the destressed zone around the tunnel. In this zone, the rock mass Young's modulus varies from 10.2 GPa to 24.5 GPa, and the rock mass Poisson's ratio varies from 0.27 to 0.36, in function of the GSI values. In the models, a section of 2.5 m is considered to be destressed (Figure 4).
# IRS, LIS, and Radio Stripes-Aided Wireless Communications: A Tutorial
###### Abstract
Another new and attractive concept for new research is radio stripes (RS). In traditional cell-free (CF) mMIMO systems, access points (APs) are distributed geographically and collaborate in transmitting and receiving by sharing critical data, including such channel state information (CSI) or other data, over a separate fronthaul link to the central processing unit (CPU). As a result, the fundamental barrier for the practical implementation of a cell-free (CF) mMIMO network is the significant fronthaul capacity and signaling demands between the APs and the CPU, as well as the high network implementation cost due to the extremely dense long-distance cable required to interconnect all components. The RS concept is one promising way to establish a CF mMIMO network. It is made up of a stripe coupled to a CPU and numerous antennae that collaborate phase-coherently. An AP is represented by a group of antenna elements that are linked to the local processing unit. As these APs are all connected to the same cable, they can share synchronization, data transfer, and power link. This means that each AP and the CPU that goes with it do not need a separate fronthaul link [9]. Previous works considered all IRS, LIS, and RS separately, and most studies evaluated LIS and IRS passively in the same way. In this new work, a comparison of the implementation and capabilities for the three-technique approach is carried out.
###### Abstract  
The short encapsulation pull-out test (SEPT) is extensively used in rockbolting research or engineering. The field SEPT is time-consuming and labor-intensive, and its result is only applicable to the tested in situ. The laboratory SEPT is usually employed in theoretical rockbolting research due to its easily controlled variables. However, the design of laboratory SEPT is quite different, as there is no standard testing method, resulting in the applicability and limitations of each study not being clear. Accordingly, the aim of this paper is to bridge the gap between laboratory SEPT research and field application. On the basis of thick-walled cylinder theory, a mechanical model of a rock bolt subjected to axial load was established under consideration of the deformational behavior of confining materials around the bolt. Plane stress analysis was introduced to derive the analytical relationship between the axial force of the bolt and the deformation of the confining materials. A new approach of laboratory SEPT sample design was established, namely, equivalent radial stiffness theory, to simulate anchorage performance in a specific in-situ geocondition. Consequently, the field SEPT could be replaced by laboratory testing using properly designed bolting samples with a certain level of accuracy. In addition, the application scope of previous laboratory SEPT research could be accurately defined. Laboratory SEPT was carried out to study the anchoring performance of right spiral redux bolts under different confining materials. Poly Vinyl Chloride (PVC) tubes with a thickness of 31 mm, #60 aluminum (AI) tubes with a thickness of 5.8 mm, and #20 steel tubes with a thickness of 5.5, 7.0 mm were used in sample preparation to simulate soft, medium, and hard surrounding rocks in the field. The anchorage performance of the bolt under different geoconditions was systematically proposed, which provides a technical approach for similar research using different anchoring materials. A negative exponential expression formulating the axial load capacity of the right spiral bolts for the full spectrum of the surrounding rocks' strength was derived on the basis of theoretical analysis and data regression. It can be used for preliminary reinforcement design, as well as the accurate key parameter setting in the numerical calculation of roadway deformation using right spiral bolts. The theoretical prediction is highly consistent with the testing results in the literature, which confirms the validity and reliability of this research. This study contributes to the establishment of a laboratory SEPT standard in rock mechanics.  
SEPT; equivalent radial stiffness; peak anchorage force; confinement; right spiral bolt
# Novel Processing Methods of Low-Clinker Multi-Component Cementitious Materials--A Review
## 1 Introduction
SCMs may improve concrete characteristics primarily in two ways: by reacting with cement hydration products in the first instance and by improving particle packing efficiency in the second [13; 14; 15; 25]. Nonetheless, the search for alternative SCMs has significantly intensified in recent years. In order to use low-clinker cement more widely, significant changes are needed in traditional concrete-production technologies. For the objective of accelerating the early hardening of concrete in precast settings, there are further options to apply hygro-thermal treatment and even gamma irradiation [26; 27] (only within radiation-controlled areas). When it comes to multi-component cement with a low clinker content, transmitting heat energy or gamma-ray energy to hardening concrete can also be a method to drive the hardening processes. Interactions with non-ionizing radiation, such as magnetic interactions, microwaves, and ultrasonic waves, offer exciting possibilities for adding extra energy to concrete mixtures [28]. The potential of ultrasonic waves to carry out detailed diagnostics on the features of hardened concrete and even to demolish concrete is well recognized. Research on concrete constituents and mixtures has occasionally focused on the effects of microwaves, ultrasonic waves, and magnetic interactions. There has not been any published research on the effectiveness of such energy-transmission methods. This study examines non-ionizing radiation technologies to enhance the dispersion of concrete mix components and promote the setting and early hardening processes of cement in concrete. The review also analyses how these interactions affect concrete's early and late strengths, microstructural features, and durability indices that have already been recognized. The applications of low-clinker factor multi-component cement in concrete may be promoted by a clearer grasp of how a non-ionizing radiation field affects constituents of the concrete mix.
# Interference Mitigation for Metro Train Location Based on Karhunen-Loeve Decomposition
## 4 Experimental and Analysis of Results
### Algorithm Computational Complexity  
The ability of the three algorithms mentioned above to suppress single-tone signals and chirp signals was analyzed previously. This section gives a comparison of STFT, WPCT, and KL algorithms in terms of single-tone suppression performance and complexity. As shown in Table 2, compared with the WPCT and STFT algorithms, the KL algorithm can provide better interference suppression performance, but the implementation complexity is the highest, and the computation of the KL algorithm is \(N^{2}\). In contrast, WPCT and STFT require less computation. In practice, the interference algorithm is chosen to compromise between the calculation amount and the suppression effect. To obtain better results, we can consider optimizing the calculation amount of the KL algorithm in the future.
## 3 Data Description and Methods
### The Baseline Methodologies
#### 3.2.4 Attention  
The Attention mechanism is a technique designed to allow models, particularly in various deep learning fields such as Natural Language Processing (NLP), to 'focus' on specific parts of the input sequence that are especially important for the current output. Originally developed to address the issue in RNN-based machine translation models (Sequence-to-Sequence structures) where treating all words in a long sentence with equal importance could lead to missing crucial information, the Attention mechanism calculates the interrelationships among all positions in a sequence through relatively simple computations. By assigning higher weights to important positions, it enables the model to accurately grasp the context. This process primarily involves three components: 'Query', 'Key', and 'Value' vectors. The Query represents what information needs to be found, the Key represents what information is held, and the Value represents the actual information to be referenced.  
Specifically, when calculating Attention at time step \(t\), the Query \(\mathbf{Q}\), Key \(\mathbf{K}\), and Value \(\mathbf{V}\) are derived for each element in the input sequence. The similarity between the Query and each Key is measured by taking their dot product, followed by normalization into a probability distribution using the softmax function. This distribution indicates where the model should focus, with higher probabilities indicating greater importance. Finally, this probability distribution is used to compute a weighted sum of the Value vectors, resulting in a 'Context' vector that the model can reference. The following equation outlines how Attention values are computed at each time step:  
\[\text{Attention}(\mathbf{Q},\mathbf{K},\mathbf{V})=\text{softmax}\Big{(} \frac{\mathbf{Q}\mathbf{K}^{\mathsf{T}}}{\sqrt{d_{k}}}\Big{)}\mathbf{V}. \tag{15}\]  
Here, \(\sqrt{d_{k}}\) is the square root of the dimension \(d_{k}\) of the Query and Key vectors, used to prevent scaling issues that can arise when the dot product becomes large. If multiple heads are used to compute Attention from different perspectives and their results are then combined, this approach is referred to as 'Multi-Head Attention'.  
By incorporating the Attention mechanism, models can focus on specific parts of the sequence, allowing them to effectively maintain contextual clues even in long sentences or large-scale time-series data. This significantly mitigates the issues of gradient vanishing and the need to compress all information into a single hidden state that were prevalent in previous RNN-based structures.
## 3 Inherent Flow Characteristics and Numerical Analysis
### Flow Coefficients  
Based on the conceptual design described in Section 2, the cylinder-in-ball valve was proposed with the opening hole starting at the center of the flow path. In order to evaluate the flow characteristics of the proposed cylinder-in-ball valve, computational fluid dynamic (CFD) analysis was carried out. CFD analyses of the flow coefficient, \(CV\), according to the opening rates were derived by calculating the velocity and pressure distributions. These distributions confirmed the inherent flow coefficients of the proposed cylinder-in-ball valve. Then, the cavitation that occurred at small opening rates was evaluated quantitatively and compared with that of a conventional V-port ball valve [12].  
To evaluate the flow characteristics, CFD analysis using the commercial software ANSYS 2020 R2 CFX (San Jose, CA, USA) [13] was carried out for each opening rate of the proposed cylinder-in-ball valve, in which the domestic code KS B 2101 [14], standardized for \(CV\) measurement, was taken into account. This code defined the working fluid as water at room temperature and stipulated that the upstream length from the inlet to the valve and the downstream length from the valve to the outlet should be 6 and 10 times longer than the pipe diameter, respectively. For the pre-processing of the CFD analysis, the finite element model was prepared, as shown in Figure 3. To construct the grid of the finite element model, the hex-dominant method was adopted to generate preferentially hexahedral elements in order to provide highly accurate results for the CFD analysis. The average number of elements was approximately 2.5 million, depending on the opening rates.  
Figure 2: The curves of the inherent flow characteristics for various valves.  
The \(CV\) was calculated using the \(Q\) at the outlet obtained by the results of the CFD analysis, as shown in Equation (1).  
\[CV=1.17\ Q\sqrt{\frac{SG}{\Delta P}}\ \left[\text{gal}\cdot\text{min}^{-1}\cdot \text{psi}^{-0.5}\right] \tag{1}\]  
\[Q=V\cdot A\ \left[\text{m}^{3}\cdot\text{h}^{-1}\right] \tag{2}\]  
In Equation (1), a coefficient of 1.17 was used to convert SI units into I-P units for the practical use of \(CV\) values. From the above equations, \(Q\), \(SG\), and \(V\) are the volumetric flow rate (m\({}^{3}\)/h) at the outlet, the specific gravity of water (1), and the average velocity (m/s) at the cross-sectional area, \(A\) (m\({}^{2}\)), respectively. \(\Delta P\) is the differential pressure (kPa) between the inlet and outlet, which is designated as 74 kPa according to KS B 2101. The \(Q\) at the outlet was determined by the CFD analysis using the boundary conditions such as the \(Q\) at the inlet and atmospheric pressure at the outlet met the requirement for a \(\Delta P\) of 74 kPa.
###### Abstract  
The observation of single mode propagation in an air-clad single crystal sapphire optical fiber at wavelengths at and above 783 nm is presented for the first time. A high-temperature wet acid etching method was used to reduce the diameter of a 10 cm length of commercially-sourced sapphire fiber from 125 micrometers to 6.5 micrometers, and far-field imaging provided modal information at intervals as the fiber diameter decreased. Modal volume was shown to decrease with decreasing diameter, and single mode behavior was observed at the minimum diameter achieved. While weakly-guiding approximations are generally inaccurate for low modal volume optical fiber with high core-cladding refractive index disparity, consistency between these approximations and experimental results was observed when the effective numerical aperture was measured and substituted for the theoretical numerical aperture in weakly-guiding approximation calculations. With the demonstration of very low modal volume in sapphire at fiber diameters much larger than anticipated by legacy calculations, the resolution of sapphire fiber distributed sensors may be increased and other sensing schemes requiring very low modal volume, such as fiber Bragg gratings, may be realized in extreme environment applications.  
s pacs: +
Footnote †: journal: Applied Physics Letters
# Machine Learning-Assisted Adaptive Modulation for Optimized Drone-User Communication in B5G
## 3 System and Channel Modeling  
### System Model  
A drone-user communication system is considered in the paper. The system consists of a drone acting as the transmitter and a user at the receiving end, as shown in Figure 1. Considering the position of transmitter and receiver, the channel is modeled as Rician with Rician factor \(\kappa\) and is affected by rain, which is modeled by an empirical model provided by ITU [37]. Furthermore, we assume that each transmitter and receiver use the same frequency for operation, forming an interference-limited system.
## 4 Overview: Signal Processing Methods
### Filters Applied
#### 4.2.1 Band-Pass Filter with a Range of 10 to 450 Hz  
The frequency range of EMG signals varies depending on the type of gesture being recorded. Each gesture activates a unique range of muscle groups with varying frequencies. In general, EMG signals can range from approximately 10 Hz to 450 Hz, with higher frequencies often associated with more forceful or rapid muscle contractions. However, in certain cases or pathological conditions, the EMG signals may display frequencies beyond the usual range. In Figure 13, point 1 highlighted in red represents the signal range preserved between 10 Hz and 450 Hz.