esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
The mechanical properties of water-rich coal and rock in a subzero environment are very different from those at room temperature, which causes many unexpected hazards for projects. In this study, coal and rock samples subjected to the coupled effects of water, temperature, and dynamic loads were taken as the research object, and the discussion was shaped around their mechanical properties. The crack evolution trend and different gradient impact velocities were determined using a split-Hopkinson pressure bar (SHPB). Multiple fractals were based on high-speed digital image correlation (HS-DIC) technology and the quality-screening method; the evolution trend of the surface cracks in the crushing process and the distribution characteristics of the specimen fragments after crushing were examined from the perspective of fractals. This provided a powerful supplement to the existing research system on the problem of mining via the freezing method, and it accounted for the shortcomings of the existing research to a certain extent. In this research, the results mainly showed four points: (1) The coal samples were determined to have a wave velocity between 1.68 and 2.01 km/s, while the rock samples were between 2.24 and 2.61 km/s. Under the same conditions, the rock's resistance to deformation and damage was greater than that of coal. (2) In the saturated state, the plastic strength of the coal and rock samples was greater than that in the dry state, due to the strengthening of their internal stresses caused by the presence of fissure water. (3) With decreasing temperature, the degree of the dynamic compression factor of coal and rock showed a trend of initially increasing, then decreasing, and then increasing. With the increase in the loading rate, the destruction of the coal and rock was more intense, and the destruction process was accelerated. (4) After the saturated coal and rock samples were frozen, their interiors were affected by the dual factors of contraction under the influence of temperature and expansion under the influence of the freezing expansion force. The internal fissures closed or shrank, and the water in the pores turned into ice, leading to an increase in pore volume.  
frozen coal and rock mass; impact failure; dynamic mechanical properties; crack propagation; box dimension; crushing form +
Footnote †: journal: Applied Sciences
# Potassium Recovery from Potassium Solution and Seawater Using Different Adsorbents
## 2 Materials and Methods
### Sorption Experiments with KCl Solutions
#### 2.2.2 Sorption Isotherm and Kinetic Models  
The K sorption test results were fitted to the Langmuir (Equation (1)) and Freundlich (Equation (2)) isotherm models to characterize the sorption potential of the different adsorbents. The Langmuir constant related to the maximum K sorption capacity, \(q_{m}\) (mg g\({}^{-1}\)), and the affinity of the binding sites, \(K_{d}\) (mg L\({}^{-1}\)), derived from the Langmuir isotherm model and the constants related to the sorption capacity, \(K_{F}\), and magnitude of the sorption driving force, n, derived from the Freundlich isotherm model were compared for the different adsorbents.  
\[q_{e}=\frac{q_{m}C_{e}}{(K_{d}+C_{e})} \tag{1}\]  
\[q_{e}=K_{F}C_{e}^{\frac{1}{2}} \tag{2}\]  
where \(q_{e}\) (mg g\({}^{-1}\)) and \(C_{e}\) (mg L\({}^{-1}\)) are the K sorbed per unit mass of adsorbents and K concentration at equilibrium, respectively.  
The sorption kinetics data were fitted to the pseudo-first-order kinetics (Equation (3)) and the pseudo-second-order kinetics (Equation (4)) equations.  
\[\ln(q_{e}-q_{t})=\ln q_{e}-k_{1}t \tag{3}\]  
\[\frac{t}{q_{t}}=\frac{1}{(k_{2}q_{e}^{2})}+\frac{t}{q_{e}} \tag{4}\]  
where \(q_{e}\) and \(q_{t}\) are the amounts of K sorbed (mg g\({}^{-1}\)) at equilibrium and time \(t\), respectively, and \(k_{1}\) and \(k_{2}\) are the pseudo-first-order (h\({}^{-1}\)) and pseudo-second-order (g mg\({}^{-1}\) h\({}^{-1}\)) rate constants, respectively.
# Diode-Pumped Solid-State Q-Switched Laser with Rhenium Diselenide as Saturable Absorber
## 4 Conclusions  
In summary, a few-layer ReSe\({}_{2}\) was prepared by ultrasonic exfoliation and demonstrated as SA in an all-solid-state pulsed Nd:YVO\({}_{4}\) laser. The passively Q-switched Nd:YVO\({}_{4}\) experiment acquired the maximum average output power of 125 mW with a slope efficiency of 17.27%. The spectrum was centered at 1064.4 nm. The shortest pulse width was 682 ns and the highest repetition rate was 84.16 kHz, corresponding to a pulse energy of 1.49 \(\upmu\)J and pulse peak power of 2.18 W. Further, the ReSe\({}_{2}\) SA was characterized with its saturation intensity of 6.37 MW/cm\({}^{2}\) and modulation depth of 1.89%. The experiment results show that ReSe\({}_{2}\) is an effective SA for 1 \(\upmu\)m all-solid-state pulse lasers and they promote the potential applications of weak-layered dependent TMDs.  
[PERSON] supervised and supported the experiment. [PERSON] executed the experiments, handled the experimental data and wrote the manuscript. [PERSON] provided the ReSe\({}_{2}\) SA and corresponding parameters.  
This research was funded by the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDB1603); International S&T Cooperation Program of China (Grant No. 2016 YFE0119300); National Natural Science Foundation of China (NSFC) (Grant Nos. 61521093, 61505234).  
The authors declare no conflict of interest.
## 2 The Fabry-Perot Microcavity  
The FPMC we used is made from an x-cut lithium niobate crystal sheet, and high-reflection coated on both facets. The lithium niobate crystal is, first, finely-polished down to the thickness of \(\sim\)100 \(\upmu\)m, with sub-micron surface roughness. The thickness of each coating layer is optimized for the desired reflectivity, which is 94.5% at 1550 nm wavelength. The total thickness of Ta\({}_{2}\)O\({}_{5}\) and SiO\({}_{2}\) layers were 1179.9 nm, and 1801.2 nm, respectively for both surfaces, and 15 periods are used to guarantee a sufficient reflection [31]. The exact thickness of each layer is listed in the Appendix A (Table A1).  
The surface roughness of the Ta\({}_{2}\)O\({}_{5}\) and SiO\({}_{2}\) coating (via evaporation) is essential in achieving a high finesse for FPMC. Figure 1a,c show the atomic-force microscope (AFM) image of the front, and rear surfaces of the coated crystal, respectively. Figure 1b,d shows zoom-in of the central parts in Figure 1a,c. It can be seen that for both surfaces, the roughness fluctuates within 3 nm, which is key to suppressing the light scattering and to achieve the high finesse. Figure 1e plots the measured cavity resonance by sweeping the frequency of a tunable laser, indicating the full-width half-maxim (FWHM) linewidth of \(\sim\)12 GHz. The theoretical linewidth of FPMC is estimated as \(\Delta\
u=\frac{c}{2\pi m}\frac{1-\pi}{\sqrt{\
u}}\), where n is refractive index, d is cavity length, r is surface reflectivity and c is vacuum speed of light. This gives 12.204 GHz, which is quite close to measured value. The free-spectral range (FSR) of the cavity is measured as \(\sim\)678.7 GHz, giving the finesse of \(\sim\)55.5 and the Q (central frequency over linewidth) of \(1.62\times 10^{4}\). One typical sample of the FPMC is shown in Figure 1e (The inset picture).  
Figure 1: (**a**) Surface morphology of the front and (**c**) rear surface of the sample. (**b**),**d**) Surface roughness scanned at center position of (**a**), and (**c**) respectively. (**e**) Measurement of the Fabry-Perot microcavities (FPMC) cavity linewidth. Full-width half-maxima (FWHM), full-width half-maxima. Inset: Image of the used FPMC sample.
## 2 Experimental Set-Up  
### Measurement System  
We used a sweep time delay cross-correlation channel sounder. This sounder consists of a signal transmitter (Tx) and a signal receiver (Rx). The sounder transmitted an \(m=2^{13}-1\) bit long pseudorandom binary sequence (PRBS) at a chip rate of \(f_{c}=500\) Mbps. This sequence was used to phase-modulate a frequency carrier of 60.48 GHz fed to a standard gain horn antenna. The signal was received using a similar antenna, down-converted to an intermediate frequency (IF) of 500 MHz, sampled at a rate of \(f_{s}=5\,\mathrm{Gs/s}\) and stored in a computer for offline analysis. This offline processing consisted of down-converting the signal from IF to baseband and then correlating it with an exact replica of the transmitted PRBS sequence to obtain the time-varying radio channel impulse response (CIR).  
Pictures of the Tx and Rx ends of the sounder are given in Figure 1, and the details of the sounder characteristics in Table 1 and in references [38; 39].  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Frequency & 60.48 GHz \\ PRBS chip rate (\(f_{c}\)) & 500 Mbps \\ RF bandwidth (null-to-null) & 1 GHz \\ Code length & \(2^{13}-1\) bit \\ Multipath time resolution & 2 ns \\ Max. Tx power & 15 dBm \\ Max. measurable path loss (10 dB SNR) & 150 dB \\ Tx/Rx antenna polarization & Vertical \\ Tx/Rx antenna gain & 20 dBi \\ Tx/Rx antenna azimuth 3 dB beamwidth & \(18^{\circ}\) \\ Tx/Rx antenna elevation 3 dB beamwidth & \(19^{\circ}\) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Sounder specifications. PRBS: pseudorandom binary sequence; Tx: signal transmitter; Rx: signal receiver.
## 2 Principles
### Geometric Shaping Scheme Based on Pair-Wise Optimization Algorithm  
As one of the typical research hot spots in the field of modulation format optimization technology, geometric shaping is widely used in optical communication systems. By changing the geometric distribution of the signal constellation, GS technology can effectively improve the overall quality of the received signal [22; 23; 24; 25; 26; 27]. The pair-wise optimization (PO) algorithm is a commonly used geometric shaping method to adjust and optimize the signal constellation structure iteratively [25; 26; 27]. The main idea of this scheme is to randomly select two constellation points as a pair during each iteration and optimize their coordinates according to a specific objective function (usually the bit error rate or symbol error rate under a specific channel condition), subject to [22]:  
\[\sum_{k=1}^{M}s_{k}=0\;\;\text{and}\;\sum_{k=1}^{M}\|s_{k}\|^{2}=M \tag{7}\]  
where \(s_{k}\) represents any constellation point in the \(M\)-order constellation diagram, and \(\|.\|\) represents the norm operation of a vector. For any pair of \(s_{i}\) and \(s_{j}\), where \(1\leq i\leq M\), \(1\leq j\leq M,i\
eq j\), both the zero mean and average power constraints in (6) can be rewritten as [26]  
\[s_{i}=-b-s_{j} \tag{8}\]  
\[\left\|s_{j}+\frac{b}{2}\right\|^{2}=\frac{M-d}{2}-\frac{\|b\|^{2}}{4} \tag{9}\]  
where \(b=\sum_{k=1,k\
eq i,k\
eq j}^{M}s_{k}\) and \(d=\sum_{k=1,k\
eq i,k\
eq j}^{M}\|s_{k}\|^{2}\). In other words, the optimization process can be simplified as finding the position of \(s_{j}\) on a circular trajectory centered at \(-\frac{b}{2}\) with a radius of \(\sqrt{\frac{(M-d)}{2}-\frac{\|b\|^{2}}{4}}\).  
Figure 3: MI trace curves for (**a**) 256 QAM and (**b**) 128 QAM.
## 3 Neutral Formats for Data Exchange
### Formats Compatible with the CAx Kernel  
In addition to neutral data exchange formats, there are also others ensuring proper data exchange between systems of a specific type.  
Parasolid Transmit File Format  
Parasolid Transmit file: This format enables data exchange between systems built on the Parasolid kernel. It allows for storing topological and geometric information of a created shape [7; 11; 18; 19; 21; 40].  
There are two types of translators:  
1. Parasolid X_T--text (saves information in a text file);
2. Parasolid X_B--binary (saving data using symbols 0 and 1).  
The purpose of the X_B format is usually limited to data exchange between the same type of systems (older or newer versions). The X_T format has a wider application for other systems as well. It does not mean that the file exported in the X_B format cannot be imported to other systems with the above-mentioned kernel.  
ACIS: This is a translator that enables data exchange between systems built on the kernel of the same name. Like Parasolid, it has the ability to save in text (SAT (_Standard ACIS Text_)) and binary (SAB (_Standard ACIS Binary_)). The format commonly used is SAT only, which uses the ASCII code for writing information. The saved file can be viewed using a simple text editor [54; 60; 62].  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Protocol No.** & **Application** & **Status** & **Remarks** \\ \hline AP203 & Structural design & IS & \begin{tabular}{c} Structural 3D models in the \\ manufacturing industry. \\ Functional record in AP214 \\ \end{tabular} \\ \hline AP212 & Description of the structure of & \begin{tabular}{c} Structure of electrical equipment record \\ in the construction of ships, cars, \\ airplanes, and in the space industry. \\ Compliance with AP214 \\ \end{tabular} \\ \hline AP214 & \
\begin{tabular}{c} Product data structure in the design of \\ manufacturing processes for automotive \\ components \\ \end{tabular} & IS &
\begin{tabular}{c} Structure development and record in the \\ machine industry \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table}
Table 1: The advancement of STEP standardization [26; 28; 29; 59; 64].
## Appendix A List of Symbols  
\begin{tabular}{l l l} _Symbol_ & _Description_ & \\ \(a\) & Particle radius & (m) \\ _a\({}_{ij}\)_ & Interfacial area density & (1/m) \\ _A\({}_{ij}^{D}\)_ & Linearized drag coefficient & (Pa s/m\({}^{2}\)) \\ _C\({}_{ij}^{D}\)_ & Standard drag coefficient & (-) \\ _C\({}_{ij}^{D}\)_ & Single particle drag coefficient & \\ _D\({}_{\mathrm{a}_{s}}\)_ & Volume fraction dependent diffusion coefficient & (m\({}^{2}\)/s) \\ _D\({}_{j\gamma}\)_ & Shear rate dependent diffusion coefficient & (m\({}^{2}\)) \\ _f\({}_{ij}^{D}\)_ & Drag correction factor & (-) \\ _f\({}_{\mathrm{a}_{p}}\)_ & Hindered settling function & (-) \\ _F\({}_{\mathrm{m}\mathrm{p}}\)_ & Particle mass flux & (kg/(m\({}^{2}\)-s)) \\ _F\({}_{pf}^{D}\)_ & Drag force on particle phase due to the fluid & (N/m\({}^{3}\)) \\ _F\({}^{SID}\)_ & Force due to shear induced diffusion & (N/m\({}^{3}\)) \\ \(g\) & Gravity vector & (m/s\({}^{2}\)) \\ \(M\) & Mobility & (m\({}^{2}\)/(Pa s)) \\ \(p\) & Pressure (assumed equal in both phases) & (Pa) \\ \(T\) & Transmission & (-) \\ _v\({}_{g}\)_ & Grid velocity & (m/s) \\ _v\({}_{l}\)_ & Velocity of phase i & (m/s) \\ Greek symbols & & \\ _Symbol_ & _Description_ & \\ _a\({}_{i}\)_ & Volume fraction of phase i & (-) \\ _a\({}_{max}\)_ & Maximum packing density & (-) \\ \(\overline{a_{p}}\) & Relative volume fraction \(\left(\frac{a_{p}}{a_{max}}\right)\) & (-) \\ _\(\dot{\gamma}\)_ & Shear rate & (1/s) \\ _\(\eta_{i}\)_ & Viscosity of phase i & (Pa s) \\ _\(|\eta|\)_ & Intrinsic viscosity & (-) \\ _\(\rho_{i}\)_ & Density of phase i & (kg/m\({}^{3}\)) \\ _\(\dot{\gamma}\)_ & Molecular stresses & (Pa) \\ \end{tabular}  
Figure 13: Grid refinement study for case 2. The relative particle volume fraction versus the channel height, measured 2.5 cm from the channel entrance. The grid cell number of the channel height is changed: 37 grid cells (black solid line); 41 grid cells (grey solid line); 45 grid cells (black dashed line); 47 grid cells (grey dashed line) and 49 grid cells (black dashed-dotted line).  
Figure 12: Grid refinement study for case 3. The relative particle volume fraction versus the channel height, measured 2.5 cm from the channel entrance. The grid cell number of the channel height is changed: 15 grid cells (black solid line); 19 grid cells (grey solid line); 21 grid cells (black dashed line); 23 grid cells (grey dashed line) and 27 grid cells (black dashed-dotted line).
# A Security and Privacy Scoring System for Contact Tracing Apps
## 2 Methodology
### Methodology of the Privacy Review
#### 2.2.1 Privacy Principles of Contact Tracing  
We chose to adopt the privacy principles articulated in an open letter widely signed by cyber-security researchers [21]. Other statements exist and are similar [22; 23; 24]; we chose to use these, as they are signed by a large group of privacy researchers. The 10 principles are as follows:  
* **Independent expert review** : the app should be reviewed by privacy and security experts prior to deployment.
* **Simple design**: the average user should be able to understand how the app performs its functions.
* **Minimal functionality**: the app should only perform contact tracing.
* **Data minimization**: the app should collect as little data as possible to function.
* **Trusted data governance**: who controls, has access to, and how the data are used should be known and subject to public review.
* **Cyber security**: best practices should be used for data storage and transmission throughout the system.
* **Minimum data retention**: collected data should only be stored for the infectious period of the individual, according to the WHO.
* **Protection of derived data and meta-data**: these data types should be deleted as soon as they are created in the system, as they are not required for contact tracing.
* **Proper disclosure and consent**: users should be provided easy to understand information on the functions of the app and all data it uses and stores. Users must consent to all data collection.
* **Provision to sunset**: there should be a timeline in place for when the app will not longer be used and all data will be deleted.
# Bearing Fault Diagnosis Approach under Data Quality Issues
## 1 Introduction
It outperforms the classical ML methods in accuracy and speed of feature extraction [23]. Moreover, auto-encoders' approach is an unsupervised DL method that has better anti-noise characteristics in feature extraction [24; 25]. Other DL methods include deep belief network (DBN) [26], recurrent neural network (RNN) [27], generative adversarial network (GAN) [28]. The detection of early stages of bearing degradation is feasible by tracking the changes in the characteristics of the bearing measurements, including vibration, temperature, and lubrication parameters. Evidently, these distinct changes could be symptoms of different bearing faults (ball, inner race, and outer race). As part of fault diagnostics in bearings, it is of great importance to extract the unique features associated with each of these faults. These features could serve as fault classifiers based on the bearing measurements. In the time domain, studying the statistical characteristics of the vibration measurements is one of the reliable fault diagnostic techniques. Under the different fault conditions, the vibration signals possess different statistical parameters (root mean square, kurtosis, skewness, etc.). In the literature, monitoring of these parameters has been exploited extensively in identifying bearing faults at different success rates. The statistical and fractal characteristics of the vibration signals can be inferred by calculating the scaling (Hurst) exponent of these signals. The scaling exponent serves as a measure of the level of long-range correlations in the time series. In general, the bearing vibration signals are known to be non-stationary in nature [29]. Therefore, we exploited the detrended fluctuation analysis (DFA) [30] in estimating the scaling exponents of the vibration signals with sampling rates of 12,000 and 48,000 samples/s. The DFA is one of the reliable methods in estimating the scaling exponents in non-stationary time series. Based on the estimated scaling exponents, we proposed a novel diagnostic approach of the different bearing faults. Our results showed that the proposed method can classify healthy and faulted bearings at high accuracy rates using vibration signals with 48,000 samples/s. On the other hand, it is not suitable to classify bearing faults in typical data acquisition systems with low sampling rates (12,000 samples/s) due to inaccurate estimation of the scaling exponent.
###### Abstract  
The observation of small to medium inland water targets with nadir radar altimeters is currently limited by the along-track resolution of UnFocused SAR (UFSAR) altimetry, which is approximately 300 m for Delay-Doppler processors. In this study, we analyze the benefits of the sub-meter along-track resolution provided by Fully Focused SAR (FFSAR) altimetry applied to Sentinel-6 Michael Freilich data over a collection of small to medium targets in the Ebre Basin, Spain. The obtained water level estimations over a 2-year period are compared to in situ data to evaluate the long-term accuracy of the algorithm. The proposed FFSAR altimetry methodology achieves an average MAD precision of roughly 4 cm, and allows for a full operational implementation as it can be processed in a totally unsupervised manner. The precision improvement with respect to Delay-Doppler products over the same targets is essentially attributed to the FFSAR capabilities to better filter out waveforms contaminated by off-nadir scatterers. Moreover, we evaluate the application of extended water masks, which exploit nadir-altimeter measurements where water is at nadir or up to 250 m across-track from nadir to increase the number of acquisitions while maintaining the same level of accuracy, increasing by an average of 48% the number of valid measurements per pass, while maintaining the same level of accuracy as nadir measurements over water. We thus demonstrate the potential of FFSAR altimetry to monitor the water level of small to medium inland water targets.  
radar altimetry; FFSAR; UFSAR; water level; inland waters Article
## 2 PV System Configuration
### Dc-dc Boost Converter Model  
The selection of the converter for the MPPT controller depends on the option of using it either with or without a battery [3]. The presence of the battery requires the design of the converter to meet its voltage criteria at a constant load. For a system without a battery, the output voltage depends on the load chosen (load matching), and the power transfer follows the maximum power transfer theory [3]. Maximum power transfer can only occur when the load resistance matches the internal resistance of the PV panel as shown in Figure 3 [3].  
The complexity to design the converter comes in due to the non-linearity of the PV module characteristics [13]. A few important steps in designing the converter are  
Figure 3: Impedance matching for maximum power transfer.  
considered. Firstly, the range of the output resistance, \(R_{load}\), needs to be determined. The range of \(R_{load}\) is calculated based on Equation (4) [13].  
\[R_{load}=\frac{R_{m}}{\left(1-D\right)^{2}} \tag{4}\]  
where \(R_{m}\) is the value of the resistance at the maximum power point and \(D\) is the duty cycle. The range of the optimum \(R_{load}\) is determined as shown in Equation (5) [13].  
\[\frac{R_{m(max)}}{\left(1-D_{min}\right)^{2}}\leq R_{load(opt)}\leq\frac{R_{m (min)}}{\left(1-D_{max}\right)^{2}} \tag{5}\]  
where \(R_{m(max)}\) denotes the resistance at the maximum power point at maximum irradiance, \(D_{min}\) is the minimum duty cycle, \(R_{load(opt)}\) is the optimum load resistance, \(R_{m(min)}\) is resistance at the maximum power point at minimum irradiance, and \(D_{max}\) is the maximum duty cycle. The determination of the range of the load resistance is crucial to ensure the maximum power transfer is achievable. The output voltage of the boost converter is determined by Equation (6) [13].  
\[V_{om}=\frac{V_{mC}}{1-D_{max}} \tag{6}\]  
where \(V_{om}\) is the output voltage and \(V_{mG}\) is the maximum voltage at maximum irradiance. The value of the inductor, \(L\), is given in Equation (7) [13].  
\[L=\frac{R_{m}}{\Delta i_{L}f}\left(1-\sqrt{\frac{R_{m}}{R_{load}}}\right) \tag{7}\]  
where \(\Delta i_{L}\) represents inductor ripple current and \(f\) is the switching frequency. The minimum input capacitance, \(C_{in_{t}}\) is calculated as shown in Equation (8) [13].  
\[C_{in}=\frac{D}{8L\gamma_{V_{m}}f^{2}} \tag{8}\]  
where \(\gamma_{Vm}\) is the voltage factor at the maximum power point. The minimum output capacitance, \(C_{out}\), is determined by Equation (9) [13].  
\[C_{o}=\frac{D(1-D)^{2}}{R_{m}\gamma_{V_{o}}f} \tag{9}\]  
Here, \(\gamma_{V_{o}}\) represents the ripple factor of the output voltage.