esa-sceva/satcom-chunk-collection huggingface dataset:
# Mining Pool Selection under Block WithHolding Attack +
## 5 Numerical Results
### Both-Side Attack Case  
Finally, we focus on the both-side attack case with attack sizes of \(a_{12}=0.015\) and \(a_{21}=0.015\). Other parameters are set as those in Figure 3. Under this parameter setting, we obtain five NEs: \((0,1)\), \((0,2,0.8)\), \((0,4,0.6)\), \((0.8,0.2)\) and \((1,0)\) based on numerical calculations. We show in Figure 7(a) the phase portrait of the replicator dynamics. We can see from Figure 7(a) that the population states converge to \((0,1)\) for initial states with \(x_{1}\leq 0.2\), converge to \((1,0)\) for initial states with \(x_{1}\geq 0.8\) and converges to \((0.4,0.6)\) for initial states with \(0.2<x_{1}<0.8\). This implies that the ESSs in this case are \((0,1)\), \((1,0)\) and \((0.4,0.6)\). To verify the correctness of the analysis, we conducted simulations with three initial states \((x_{1},x_{2})=(0.20,0.80)\), \((0.75,0.25)\), \((0.85,0.15)\) and summarize the results in Figure 7(b). The results show that all the population states finally converge to the state \((0,1)\) from initial state \((0.2,0.8)\), converge to \((0.4,0.6)\) from initial state \((0.75,0.15)\) and converge to \((1,0)\) from initial state \((0.85,0.15)\), which agree with the theoretical results. Comparing the results with those of the no-attack case, we can see that the pool with sufficiently large initial population fraction (e.g., more than 0.8) will attract more miners to join. In addition, when the initial population fraction of either pool is not sufficiently large, attack has no impacts if the two pools attack with the same size, which can also be observed from Figure 7(a).  
Next, we investigate the impacts of attack sizes \(a_{12}\) and \(a_{21}\) on the converged population states. Figure 9 shows how the stable population state changes when the attack size of pool 1 (\(a_{12}\)) increases from 0 to 0.03 under various values of the attack size of pool 2 (\(a_{21}\)). In Figure 8(a), the initial state is fixed as \((0.50,0.50)\) and the attack size of pool 2 is set as \(0.010,0.015,0.020\). This figure shows that, as the attack size of pool 1 (resp. pool 2) increases, the stable population fraction of pool 1 (resp. pool 2) increases. This means that using more hash powers for attack will attract more miners to join the pool after convergence. Furthermore, we can see that when the two pools use the same attack size, the populations converge to nearly the stable state without attack \((0.4,0.6)\), which means that attack has no impacts in this case. The results with initial states \((0.1,0.9)\) and \((0.9,0.1)\) are also shown in  
Figure 7: One-side attack case with \(a_{21}=0.015\).  
Figure 9b,c. We can see the same phenomenon from these two figures that mining pools can attract more miners to join after convergence by increasing their attack sizes, implying that attack can give mining pools advantages.
# A Multiscale CNN-Based Intrinsic Permeability Prediction in Deformable Porous Media
## 2 Macroscopic Saturated Porous Media Model
### Kinematics of Multi-Phase Continua  
Within the framework of continuum mechanics applied to multiphase porous media, the individual constituents \(\varphi^{\alpha}\) are regarded to have unique states of motion (see, e.g., [44; 45]). Thus, with \(\mathbf{X}_{\alpha}\)as the position vector of \(\varphi^{\alpha}\) with respect to the reference configuration and \(\mathbf{x}\) as the position vector with respect to the current configuration, each constituent has an individual Lagrangian (material) motion function \(\mathbf{\chi}_{\alpha}\) and has its velocity field \(\mathbf{v}_{\alpha}\), viz.,  
\[\mathbf{x}=\mathbf{x}_{\alpha}(\mathbf{X}_{\alpha},t)\ \ \Leftrightarrow\ \ \mathbf{X}_{\alpha}=\mathbf{x}_{\alpha}^{-1}(\mathbf{x},t)\quad\text{and}\quad \mathbf{v}_{\alpha}:=\mathbf{\dot{\chi}}_{\alpha}^{\prime}=\frac{\mathrm{d}_{ \alpha}\mathbf{x}}{\mathrm{d}t} \tag{2}\]with \(\chi_{\alpha}^{-1}\) being the inverse (Eulerian or spatial) motion function and  
\[(\,\boldsymbol{\cdot}\,)^{\prime}_{\alpha}:=\frac{\mathrm{d}_{\alpha}(\, \boldsymbol{\cdot}\,)}{\mathrm{d}t}=\frac{\partial(\,\boldsymbol{\cdot}\,)}{ \partial t}+\mathrm{grad}(\,\boldsymbol{\cdot}\,)\cdot\mathbf{v}_{\alpha} \tag{3}\]  
representing the material time derivative of an arbitrary vector quantity \((\,\boldsymbol{\cdot}\,)\) with respect to the motion of \(\varphi^{\alpha}\) and \(\mathrm{grad}(\,\boldsymbol{\cdot}\,):=\partial(\,\boldsymbol{\cdot}\,)/ \partial\mathbf{x}\). In this work, the motion of the solid phase is described using a Lagrangian approach via the solid displacement \(\mathbf{u}_{S}\) and velocity \(\mathbf{v}_{S}\). For the pore-fluid phase, the motion is described either by an Eulerian description using the fluid velocity \(\mathbf{v}_{F}\) or by a modified Eulerian setting via the seepage velocity \(\mathbf{w}_{F}\), i.e.,  
\[\mathbf{u}_{S}=\mathbf{x}-\mathbf{X}_{S}\,,\ \ \ \mathbf{v}_{S}=(\mathbf{u}_{S})^{ \prime}_{S}\,,\ \ \ \mathbf{w}_{F}=\mathbf{v}_{F}-\mathbf{v}_{S}\,. \tag{4}\]  
Within a small strain assumption, the essential kinematic relation is the linearized small solid strain tensor \(\boldsymbol{\varepsilon}_{S}\), expressed as  
\[\boldsymbol{\varepsilon}_{S}\,=\,\tfrac{1}{2}\,(\mathrm{grad}\,\mathbf{u}_{S} \,+\,\mathrm{grad}^{T}\mathbf{u}_{S})\,. \tag{5}\]
# Data Matrix Based Low Cost Autonomous Detection of Medicine Packages
###### Abstract  
Counterfeit medicine is still a crucial problem for healthcare systems, having a huge impact in worldwide health and economy. Medicine packages can be traced from the moment of their production until they are delivered to the costumers through the use of Data Matrix codes, unique identifiers that can validate their authenticity. Currently, many practitioners at hospital pharmacies have to manually scan such codes one by one, a very repetitive and burdensome task. In this paper, a system which can simultaneously scan multiple Data Matrix codes and autonomously introduce them into an authentication database is proposed for the Hospital Pharmacy of the Centro Hospitalar de Vila Nova de Gaia/Espinho, E.P.E. Relevant features are its low cost and its seamless integration in their infrastructure. The results of the experiments were encouraging, and with upgrades such as real-time feedback of the code's validation and increased robustness of the hardware system, it is expected that the system can be used as a real support to the pharmacists.  
data matrix; codes scan; pharmaceutical industry; traceability +
Footnote †: journal: Medical Informatics
# Optimal Steady-State Range Prediction Filter for Tracking with LFM Waveforms
## 2 Problem Definition and Conventional Filter Design
### \(\alpha\)-\(\beta\) Filter for LFM Waveforms  
We focus attention on a steady-state second-order tracking filter for moving objects tracked using LFM waveforms. Filter gains become fixed values in steady-state tracking; a fixed-gain second-order tracking filter is known as an \(\alpha\)-\(\beta\) filter [9; 10; 13]. For LFM waveforms, a tracking of the range and range rate are considered along with range-Doppler coupling in range measurements. We investigate the range prediction performance using the \(\alpha\)-\(\beta\) filter characterized by the coefficient of range-Doppler coupling.  
The tracking filter invokes an iterative prediction and smoothing (update) process. The prediction process of the \(\alpha\)-\(\beta\) filter is [14]:  
\[r_{\mathrm{p},k} =r_{\mathrm{s},k-1}+Tv_{\mathrm{s},k-1}, \tag{1}\] \[v_{\mathrm{p},k} =v_{\mathrm{s},k-1}, \tag{2}\]  
where \(r_{\mathrm{s},k}\) is the smoothed target range at time \(kT\), \(T\) the sampling interval, \(r_{\mathrm{p},k}\) the predicted range, \(v_{\mathrm{s},k}\) the smoothed range rate, and \(v_{\mathrm{p},k}\) the predicted range rate. The smoothing process of the \(\alpha\)-\(\beta\) filter for the LFM waveforms is [8; 9; 10]:  
\[r_{\mathrm{s},k} =x_{\mathrm{p},k}+\alpha(r_{\mathrm{o},k}-r_{\mathrm{p},k}- \Delta tv_{\mathrm{p},k}), \tag{3}\] \[v_{\mathrm{s},k} =v_{\mathrm{p},k}+(\beta/T)(r_{\mathrm{o},k}-r_{\mathrm{p},k}- \Delta tv_{\mathrm{p},k}), \tag{4}\]  
where \(r_{\mathrm{o},k}\) is the measured range, \(\Delta t\) the coefficient of range-Doppler coupling, and \(\alpha\) and \(\beta\) are fixed filter gains. \(r_{\mathrm{o},k}\) and \(\Delta t\) is expressed as [10]:  
\[r_{\mathrm{o},k} =r_{\mathrm{t},k}+v_{\mathrm{t},k}\Delta t+w_{k}, \tag{5}\] \[\Delta t =f_{0}\tau/B_{\mathrm{w}}, \tag{6}\]  
where \(r_{\mathrm{t},k}\) and \(v_{\mathrm{t},k}\) are the true range and range rate, \(w_{k}\) the white noise associated with a Gaussian measurement with standard deviation of \(\sigma_{\mathrm{w}}\), and \(f_{0}\), \(\tau\), and \(B_{\mathrm{w}}\) are the carrier frequency, the pulse length, and the bandwidth of LFM waveform, respectively. \(B_{\mathrm{w}}\) becomes a negative value when a down-chirp waveform is used. Hence, \(\Delta t>0\) corresponds to an up-chirp waveform and \(\Delta t<0\) corresponds to a down-chirp waveform. We refer to the \(\alpha\)-\(\beta\) filter assumed by Equations (1)-(4) as the LFM \(\alpha\)-\(\beta\) filter.  
The purpose of this communication is _finding the optimal \(\alpha\) and \(\beta\) values that achieves minimum errors for the range prediction in steady-state conditions_. For simplicity, we assume that \(\Delta t\) and \(\sigma_{\rm w}\) are known and constant.
## 3 Study Results
### Delay Results
#### 3.1.2 Simulated Average Delay Results for Highway Speed Limit of 100 km/h
For DRAC \(\geq\) 6.0 m/s\({}^{2}\), the results show that there is no difference in conflict ratio (\(\rho\) = 1) for 500 and 1000 vehicles/h/lane; at 1500 vehicles/h/lane, there is a statistically significant reduction in the conflict ratio of 0.05 (i.e., increase in safety thereafter); and there is reduction in the conflict ratio at 2000 vehicles/h/lane, but this reduction is not statistically different from the one at the 5% level. For TTC \(\leq\) 0.50 s and TTC \(\leq\) 1.50 s, the results show that there is no statistically significant difference in conflict ratio for all traffic volumes, while for TTC \(\leq\) 2.50 s, the results show that there is significant reduction in conflict ratio for all traffic volumes (i.e., increased safety). * _TTs = 5.0-15.0%:_ For TT percentages of 5.0 to 15.0%, the results are similar to 2.5%, with no statistically significant increase in the conflict ratio, and all cases showing an increase in the conflict ratio in the after period. While for some cases there were statistically significant reductions in the conflict ratio, most of the reduction cases were not statistically different from the one at the 5% level, suggesting there was no change in safety. Increasing TT Speed Limit from 60 to 90 km/h (Table 7)  
The results of increasing the TT speed limit from 60 to 90 km/h are similar to the previous case (increase to 70 and 80 km/h). For all of the cases that showed an increase in the conflict ratio (one case for DRAC \(\geq\) 3.35 m/s\({}^{2}\); three cases for DRAC \(\geq\) 6.0 m/s\({}^{2}\), four cases for TTC \(\leq\) 0.5 s; one case for TTC \(\leq\) 1.50 s; and four cases for TTC \(\leq\) 2.50 s), no statistically significant differences were found compared to the 5% level. For other cases, there were significant reductions in the conflict ratio, but most cases showed either no change in the conflict ratio (\(\rho\) = 1), or no statistically significant difference compared to the 5% level for the other cases, showing a reduction in the conflict ratio.
## 1 Introduction
### 2.1 Primal Affine and Other Previously Available Algorithms for \(L_{1}\) Splines  
Minimization of the global \(L_{1}\) spline functionals (4), (5), (6) and (7) is a nonlinear programming problem. Direct minimization of (4) has been accomplished by an active set method [3]. Active set algorithms for minimizing (5), (6) and (7) have not been developed, but these functionals and functional (4) have been minimized by primal affine algorithms and primal-dual algorithms [12, 14]. Primal affine and primal-dual algorithms are linear (not nonlinear) programming procedures. To create a linear program suitable for application of these algorithms, the integrals in the \(L_{1}\) spline functionals need to be discretized. For the primal affine algorithm used in the present paper and in [5, 6, 8, 10, 11], the spline functionals were discretized by the midpoint rule with \(K\) equal subintervals in each interval \((x_{i},x_{i+1})\). In this paper, \(K=100\). For a detailed description of the primal affine algorithm, see [7].  
For calculation of \(L_{1}\) splines by the primal affine method using the global functionals (4), (5), (6) and (7), we add to these functionals the regularization terms  
\[\varepsilon\sum_{0}^{I}\left|b_{i}-\delta_{i}\right|,\ i=0,1,\ldots,I\,. \tag{8}\]  
When \(\varepsilon\) is sufficiently small, the \(L_{1}\) spline that minimizes the functional with the regularization term is unique. For the computational experiments of the present paper, \(\varepsilon=10^{-4}\).  
In addition to calculating \(L_{1}\) splines by minimizing the global functionals (4), (5), (6) and (7) by the primal affine method, we will calculate \(L_{1}\) splines using these functionals on 5-point and 7-point windows. To calculate the derivative \(b_{i}\) of a \"windowed\" \(L_{1}\) spline at node \(x_{i}\), we minimize functionals that are the same as (4), (5), (6) and (7) except that the integral is over a local set of intervals (\"window\") rather than over the global domain. For 5-point-window \(L_{1}\) splines, the window \([x_{i-2},x_{i+2}]\) is used for nodes \(x_{i}\), \(\hat{\imath}=2,3,\ldots,I-2\), the window \([x_{0},x_{4}]\) is used for nodes \(x_{i}\), \(\hat{\imath}=0,1\) and the window \([x_{I-4},x_{I}]\) is used for nodes \(x_{i}\), \(\hat{\imath}=I-1,I\). For 7-point-window \(L_{1}\) splines, the window \([x_{i-3},x_{i+3}]\) is used for nodes \(x_{i}\), \(\hat{\imath}=3,4,\ldots,I-3\), the window \([x_{0},x_{6}]\) is used for nodes \(x_{i}\), \(\hat{\imath}=0,1,2\) and the window \([x_{I-6},x_{I}]\) is used for nodes \(x_{i}\), \(\hat{\imath}=I-2,I-1,I\). When minimizing a \"windowed\" \(L_{1}\) spline functional for node \(x_{i}\) by the primal affine algorithm, we add to the spline functional the regularization term  
\[\varepsilon\left|b_{i}-\delta_{i}\right|. \tag{9}\]  
For the computational experiments of the present paper, \(\varepsilon=10^{-4}\).  
Figure 1: Data set and linear spline.
###### Abstract  
This paper presents the first hybrid supply modulator (HSM) designed for envelope tracking power amplifiers (ET-PAs) in base station applications. The focus is on a rail-to-rail Class-AB linear amplifier (LA) optimized for high-voltage and wide-bandwidth operation. The LA is designed using 130 nm BCD technology, utilizing Laterally Diffused Metal-Oxide Semiconductor (LDMOS) transistors for high-voltage operation and incorporating shielding MOSFETs to protect the low-voltage devices. The circuit utilizes dual power supply domains (5 V and 30 V) to improve power efficiency. The proposed LA achieves a bandwidth of 100 MHz and a slew rate of \(+1003/-852\) V/\(\,\mathrm{\SIUnitSymbolMicro s}\), with a quiescent power consumption of 0.89 W. Transient simulations using a 50 MHz bandwidth 5G NR envelope input demonstrate that the proposed HSM achieves a power efficiency of 83%. Consequently, the proposed HSM supports high-output (100 W) wideband 5G NR transmission with enhanced efficiency.  
class-AB buffer amplifier; rail-to-rail; linear amplifier; hybrid supply modulator; base station; wide bandwidth; power amplifier +
Footnote †: journal: Electronics Letters
###### Abstract  
Modernizing irrigation systems (ISs) from traditional gravity methods to sprinkler and drip technologies has significantly improved water use efficiency. However, it has simultaneously increased electricity demand and operational costs. Integrating photovoltaic generators into ISs represents a promising solution, as solar energy availability typically aligns with peak irrigation periods. Despite this potential, photovoltaic pumping systems (PVPSs) often face reliability issues due to fluctuations in solar irradiance, resulting in frequent start/stop cycles and premature equipment wear. The IEC 62253 standard establishes procedures for evaluating PVPS performance but primarily addresses steady-state conditions, neglecting transient regimes. As the main contribution, the current paper proposes a non-intrusive, high-resolution monitoring system and a methodology to assess the performance of an isolated, high-power PVPS, considering also transient regimes. The system records critical electrical, hydraulic and environmental parameters every second, enabling in-depth analysis under various weather conditions. Two performance indicators, pumped volume efficiency and equivalent operating time, were used to evaluate the system's performance. The results indicate that near-optimal performance is only achievable under clear sky conditions. Under the appearance of clouds, control strategies designed to protect the system reduce overall efficiency. The proposed methodology enables detailed performance diagnostics and supports the development of more robust PVPSs.  
photovoltaic pumping systems; photovoltaic irrigation; pumping system; operating performance; monitoring system; sensor measurements; performance indicators 2025
## 3 Results
### Power Input Correlation  
#### 3.1.1 Local Power Consumption  
Power is transmitted during the shaking owing to the friction between the rotating liquid volume and the OSB wall. Different measurement systems used to determine the average power consumption in a OSB are introduced. A simple and efficient measurement of power consumption can be achieved by integrating a power meter in the OSB [15; 18]. The method also permits online monitoring of power consumption during biological culture. However, integrating power meter into OSB is complex and requires a redesign of the OSB. The power consumption values in the cylindrical shaken reactor range from 37.1 W to 29.85 W, relying on the shaking frequency, filling volume and liquid viscosity. At 80 to 120 rpm shaking frequency, the filling volume for 20 L vessel influences local power consumption. Figure 2 shows local power consumption increases with the increased shaking frequency [14; 15; 47; 48; 49; 50], but decreases with the increased filling volume [14; 15; 47; 49] to be well mixed in-phase bulk liquid motion [49; 51] as the friction surface between the OSB wall and the liquid is not proportional to the filling volume and consistent with the research of [PERSON] and [PERSON] [38] at shaking frequencies 50 to 400 rpm in 250-mL Erlenmeyer flasks in a 1 kg L\({}^{-1}\) density organic dispersed phase of a mixture of four volumetric parts toluene and one part carbon tetrachloride. That power consumption significantly increases with viscosity in the case of 4 L filling volume is confirmed by the research of [PERSON] et al. [16] and [PERSON] et al. [50] at the shaking frequency of 80 rpm to 300 rpm in a 300-mL baffled shake flasks using different viscosities polyvinylpyrrolidone (PVP) and shaking diameters of 100 mm. This is consistent with the research of [PERSON] and [PERSON] [52] at shaking frequencies 80 to 300 rpm in 250-mL shake flasks, 40 mL filling volume and 25-mm shaking diameter in a viscous range of PVP. In case of 6 L to 10 L filling volume that the power consumption is found to decreases with viscosity. Nevertheless, the shaking device is quickly accelerated, a low level of power consumption is reached away from a specific shaking frequency. Decreasing the shaking frequency below a critical value of 90 rpm suddenly produce increase in power consumption reaching the standard level again [48]. The order of magnitude of the power consumption was shown with respect to shaking frequency and filling volume [53; 54]. Power consumption exponentially increased with increasing shaking frequency [55]. The functional correlation between power consumption and shaking frequency is verified [14; 51; 56]  
\[P=A\cdot N^{a} \tag{8}\]  
where \(A\) is the coefficient, \(a\) is the exponent is determined by experiments.  
\(a\) is approximately 0.34 with a coefficient of determination greater than 0.9992 in a 20 L vessel with different fill volumes as shown Figure 2.
## 2 Development and Validation of the Scaled-Down PCS Model
### Scaled-Down PCS Model Validation  
Figure 7 compares the simulated and experimental results for the scaled-down PCS model. The load-displacement curve in Figure 7a shows that the simulation results closely match the experimental data, especially before reaching the maximum load capacity. The ultimate load capacities obtained from the simulation and experiment are 144.1 kN and 142 kN, respectively, with a simulation error of only 1.47%. Figure 7b,c illustrates the damage distributions of the cantilever beam, as observed experimentally and in the simulation, respectively. Under vertical displacement loading, cracks propagate from the loading point toward the base of the cantilever beam, resulting in failure. The simulation results accurately reflect the experimental damage pattern. The high degree of similarity between the simulated and experimental results validates the accuracy of the developed model, which effectively captures the actual stress and damage behavior of the structure. Therefore, the material models and boundary conditions applied in the scaled-down model can be extended to the full-scale PCS model.  
Figure 6: Stress-strain curve of the bilinear hardening model for steel and reinforcement. Note: \(f_{u}\) and \(f_{y}\) represent the ultimate strength and yield strength of the steel, corresponding to the yield strain \(\varepsilon_{y}\) and ultimate strain \(\varepsilon_{u}\), respectively.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Material** & **Density (kg/m\({}^{3}\))** & **Elastic Modulus (GPa)** & **Poisson’s Ratio** \\ \hline C50 & 2400 & 35 & 0.2 \\ C30 & 2400 & 30 & 0.2 \\ Q345 & 7850 & 210 & 0.3 \\ HRB400 & 7850 & 200 & 0.3 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Used material parameters.
# Designed Circularly Polarized Two-Port Microstrip MIMO Antenna for WLAN Applications
###### Abstract  
The proposed work describes a corner square-cut square-patch multiple-input multiple-output (MIMO) antenna with reduced mutual coupling for circular polarization (CP). A two-port MIMO-CP antenna was designed and operated at 5.6 GHz for wireless local area network (WLAN) applications. The dimensions of the MIMO-CP antenna were \(22.5\times 50\) mm\({}^{2}\) (\(0.43\lambda_{0}\times 0.933\lambda_{0}\)) and the FR4 substrate height was 1.6 mm. Between the two-elements, the edge-to-edge distance was 12.2 mm (0.227 \(\lambda_{0}\)), where \(\lambda_{0}\) was the free space wavelength at 5.6 GHz. A slot was created in the middle of the ground in the proposed MIMO antenna to reduce mutual coupling and improve CP. The ground slot improves impedance matching and provides a better S-parameter and axial ratio (AR), according to the antenna results. According to the simulated results, the proposed antenna bandwidth of 5.23-6.42 GHz (21.4%) for S11 were \(<\)\(-\)10 dB, isolation was \(-\)37 dB with a peak gain of 6 dB and AR \(\leq\) 3 dB from 5.37 to 5.72 GHz (6.25%). The proposed antennas are simple to fabricate, have low profiles, are inexpensive, have good isolation, and are CP. The diversity gain (DG) and envelop correlation coefficient (ECC) results are better in the simulated frequency band. A MIMO-CP antenna geometry prototype is built and measured for comparison, yielding good results when compared to the simulated and measured results. The MIMO-CP antenna, as designed, is suitable for WLAN applications.  
circular polarization; ECC; ground slot; MIMO; mutual coupling; WLAN +
Footnote †: journal: Applied  
0
Footnote 0: 2022, 12, 1068. [[https://doi.org/10.3390/app12031068](https://doi.org/10.3390/app12031068)]([https://doi.org/10.3390/app12031068](https://doi.org/10.3390/app12031068))