esa-sceva/satcom-chunk-collection huggingface dataset:
# Review of Advancement in Variable Valve Actuation of Internal Combustion Engines
## 9 Electro-Pneumatic VVA (EPVVA) Systems  
There were several studies and developments in electro-pneumatic VVA (EPVVA) systems [38; 39; 87; 88; 89]. As a work medium, air in an electro-pneumatic system is better than hydraulic fluid in an electro-hydraulic system in terms of the insensitivity of its viscosity to the system temperature. Air leakage also does not impose pollution problem. However, [PERSON] and [PERSON] [88] found the following issues with the pneumatic actuator:  
* Noise issues associated with air exhaust, choking, and hard valve seating associated with a pure pneumatic actuator design.
* Repeatability issues in lift control because of air flexibility.
* Sizing issues, at least for their particular design, due to the peak air pressure limit.  
The most serious development of an EPVVA system was carried out by the Swedish company Freevalve AB, formerly Cargine and a sister company to Koenigsegg Automotive AB, which developed an EPVVA system branded as Freevalve on an existing SAAB car engine [89; 90]. The Freevalve technology also appeared in the Qoros 1.6 L four-cylinder engine [89; 91]. The Freevalve system includes pneumatic valve actuators for opening, springs for valve closing, and position sensors for feedback control. An oil damping mechanism must be incorporated, as shown in Reference [38], to help resolve the seating issue, and the technology is, therefore, also called an electro-hydraulic-pneumatic actuator [89]. The claimed benefits include up to a 30% increase in horsepower and torque, up to a 30% improvement in fuel economy, and a 50% reduction in overall emissions, based on a report [90] in 2013.  
[PERSON] et al. [38] proposed an adaptive lift control scheme for an early version of the Freevalve technology to improve the intake valve lift repeatability. A control-oriented electro-pneumatic valve model was developed and used for adaptive parameter identification, and a closed-loop control scheme of valve lift was developed, utilizing the identified parameters in real-time. The main control techniques used in the process include model reference adaptation and the MIT rule [92]. The resulting maximum steady-state lift errors were less than 0.4 mm at high valve lift and less than 1.3 mm at low valve lift, which is still not accurate enough for commercial application.
## 2 Related Work
### RSSI-Based Signal Attenuation Model for Indoor Ranging  
Ranging information between two points is calculated using the received signal strength information. In free space, RSSI is inversely proportional to the square of the distance d between the receiving point and the transmitting point. Their relationship [21; 22; 23; 24] can be expressed using the famous Friis formula:  
\[P_{r}\left(d\right)=\frac{P_{t}G_{t}G_{r}\lambda^{2}}{\left(4\pi\right)^{2}d^{ 2}L} \tag{1}\]  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Category** & **RSSI** & **CSI** \\ \hline Time resolution & Packet & Multipath signal cluster \\ Frequency resolution & None & Subcarrier \\ Stability & Low & High \\ Dimension & One dimension & High dimension \\ Universality & All Wi-Fi devices & Some Wi-Fi devices \\ \hline \hline \end{tabular}
\end{table}
Table 1: The differences between Received Signal Strength Indicator (RSSI) and Channel State Information (CSI).  
Figure 2: Comparison of the stability between the sampled RSSI value and the amplitude of the CSI sampled on channel 2.  
In Equation (1), \(P_{r}(d)\) is the received power, and its unit is watts. \(P_{t}\) is the transmit power in watts. \(G_{t}\) is the transmit antenna gain. \(G_{r}\) is the gain of the receiving antenna. \(\lambda\) is the wavelength of the transmitted signal; its unit is meter. \(L\) is a loss parameter which is irrelevant to the propagation environment. The system loss parameters represent the total loss of the actual system hardware. It includes transmission lines, filters, and antennas.  
In general, \(L\) is greater than one. However, if we assume that the system hardware has no loss, we can let \(L=1\). From Equation (1), we can observe that the attenuation of the received power is exponential with the distance. So, the free-space path loss can be directly derived from Equation (1) without any system loss.  
\[PL_{F}\left(d\right)[dB]=10\log(\frac{P_{t}}{P_{r}})=-10 log(\frac{G_{t}G_{r} \lambda^{2}}{(4\pi)^{2}d^{2}}) \tag{2}\]  
We can ignore the antenna gain and let \(G_{t}=G_{r}=1\). In a free-space model, the average received signal is in a logarithmic relationship with the distance \(d\) between the transmitter and receiver in all environments. Basically, a more general path loss model can be constructed using the environment-dependent signal attenuation factor to change the free-space path loss model. The mathematical expression of the signal attenuation log model is as follows:  
\[RSSI=A-10n\log(\frac{d}{d_{0}})+X_{0}, \tag{3}\]  
where, RSSI indicates the received signal strength indication value in dBm. \(A\) is the signal strength at 1m from the source. \(d\) represents the distance between the transmitting node and the receiving node in meters. \(d_{0}\) is the unit distance and usually takes 1 m. \(X_{(0)}\) is a Gaussian random number taking a mean of 0 and its standard deviation range between 4 and 10. When the \(n\) value is smaller, the signal attenuation in the transmission process is smaller, and the signal can spread farther away. The range is generally between 2 and 4.
# A Systematic Approach for Energy-Efficient Design of Rolling Bearing Cages
## 2 Materials and Methods
### An Energy Efficient Cage Design  
With the help of the obtained model, an energy efficiency analysis and modernization of the cage of the cylindrical roller bearing type 2726, installed in the support nodes of the wagons, were carried out. An improved design of the polymer cage was proposed [29]. The cage of a cylindrical roller bearing that contained two rings 1, with cavities 2, and transverse partitions 3, the number of which is equal to the number of pockets 7, partitions 4 with stepped protrusions 5, which is distinguished by the fact that all sides of the seats 7 have a three-wave contour 6, and the convex surfaces of the contours are located in the middle of the cylindrical surfaces and the ends of the rollers, and two or more micro-indentations 8 are made on the friction surface 9 of the rings on the side of each pocket (Figure 3).  
When analyzing the energy losses that are due to the design of the cage, temperature gradients for typical and improved cage structures were determined. The calculation of the cooling factor \(K_{T}\) was performed, taking into account the forced external flow of air (blowing) in a single-phase environment with convective heat transfer according to the recommendations [30]. At a given environmental temperature (in summer) \(t=20\ ^{\circ}\)C, the speed of the train \(V=27.8\) m/s (\(100\) km/h) or the rotation frequency of the internal ring \(n=558.44\) rpm, the height of the axle box \(l_{0}=0.32\) m. Based on the tabular values of the physical properties of dry air: kinematic viscosity \(v=15.06\cdot 10^{-6}\)m\({}^{2}\)/s; thermal conductivity \(\lambda=3.57\cdot 10^{-2}\)W/m: \({}^{\circ}\)C; the number of Prandtl Pr = 0.7, were received: Reynolds number \(\mathrm{Re}=\frac{V\cdot l_{0}}{v}=\frac{27.8\cdot 0.32}{15.06\cdot 10^{-6}}=590,704\); the average Nusselt number \(Nu=0.023\cdot\mathrm{Re}^{0.8}\cdot\mathrm{Pr}^{0.4}=0.023\cdot 590,704^{0.8}.0^{7.0}=825\); the heat transfer coefficient \(\alpha=Nu\cdot\frac{\lambda}{\omega_{0}}=825.35\cdot 10^{-2}\cdot 92\) W/m\({}^{2}\). \({}^{\circ}\)C; the cooling factor \(K_{T}=\alpha\cdot A=92.04=36.8\) W/ \({}^{\circ}\)C. At the speeds of the train, respectively \(V=55.6\) m/s and \(V=83.4\) m/s (\(200\) km/h and \(300\) km/h ) or the rotation frequency of the internal ring \(n=1116.88\) rpm and \(n=1675.32\) rpm the cooling factor and \(K_{T}=64\) W/ \({}^{\circ}\)C and \(K_{T}=91\) W/ \({}^{\circ}\)C.
## 3 Results and Discussion
### Genotoxicity and Cytotoxicity Biomarkers  
#### 3.2.1 Sister Chromatid Exchanges (SCE)  
Regarding the results of the SCE analysis, Y\({}_{\text{SCE}}\), Y\({}_{\text{1 SCE}}\), Y\({}_{\text{2 SCE}}\), and Y\({}_{\text{3 SCE}}\) values for each concentration of KD and SD are shown in Table 2. All tested concentrations of fruit extracts produced a decrease in the Y\({}_{\text{SCE}}\) when the concentration-response data were analysed. In contrast, only the SD with the highest concentration (800 \(\mu\)g/mL) showed a significant reduction (\(p<0.05\)) compared to the blood control and the treatment with methanol/water (70:30). The general reasons can be attributed to antioxidants, including VC and phenolic compounds, that can prevent genotoxic damage, as reported by [PERSON] et al. (2012) [7].  
The treatment with methanol/water (70:30) slightly increased Y\({}_{\rm SCE}\); however, no significant differences (\(p>0.05\)) were observed compared to the blood control.  
As shown in Table 2, regarding Y\({}_{\rm 1 SCE}\), SD was the only extract that presented significant differences at any concentration tested (\(p<0.05\)). Our data also revealed that all concentrations of SD and KD presented a statistically significant Y\({}_{\rm 2 SCE}\) (\(p<0.05\)) when compared to the treatment with methanol/water (70:30). In our study, it was observed that SD at 800 \(\rm\mu g/mL\) concentration was the only extract that presented statistical differences in chromosomes with one, two, or three exchanges, implicating the non-genotoxicity of this extract at high concentrations. In their study of the protective role of VC, [PERSON] and [PERSON] (2012) [44] concluded that ascorbic acid was not genotoxic and reduced the frequencies of SCEs. [PERSON] et al. (2012) [7], in their study about the effects of orally administered antioxidants on the frequency of sister chromatid exchanges (SCEs) conducted on workers professionally exposed to antineoplastic agents, concluded that the combination of antioxidants could effectively prevent genotoxic damage induced by cytotoxic drugs. In this sense, the AOP of the studied extracts may have contributed to the decreased Y\({}_{\rm SCE}\).
# Empowering a Broadband Communications Course with a Unified Module on 5G and Fixed 5G Networks +
## 2 Approach and Learning Objectives
### Methodology
#### 2.1.4. Section D: Business Model of 5G and F5G  
The final section of the module discussed the business model of 5G/F5G. In particular, it outlined the primary service categories, goals, and target users for each category, as well as the market size and growth rate forecasts, which are presented in [23] and tabulated in Table 1. The network and service providers that will invest in the F5G will acquire a larger share of the continuously increasing digital economy, which is expected to rise to USD 23 trillion by 2025. As it is evident, Virtual Reality (VR), smart homes, social networking applications, and cloud desktops will grow at a very high rate, however, various other categories of services are expected to expand, ever at a slower pace, while others are expected to emerge during this decade.  
In this section, the main learning objectives were (a) a deeper understanding of the reasons behind which some services and technologies prevail while others fail to be adopted and (b) the understanding of the economic prospects of forward-looking categories of services, such as digital twin, virtual reality, smart infrastructure, etc.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Use Case** & **Annual Growth Rate (\%)** & **Market Size (USD Billions)** \\ \hline Cloud VR & 66.7 & 292 (2025) \\ Smart Home & 129 (in total between 2019–2023) & 154 (2023) \\ Gaming & 9.3 & 174 (2021) \\ Social Networking & 45 (in total between 2017–2022) & 57 (2022) \\ Cloud Desktop & 39.4 (compound annual rate & 2.58 (2022 in China) \\  & between 2016–2022) & 2.58 (2022 in China) \\ Safe City & 7.5 & 24.1 (2022) \\ Enterprise Cloudification & 30 & 103.5 (2022) \\ Online Education & 9.5 (compound annual rate & 400 (2026) \\  & between 2017–2026) & 400 (2026) \\ E-health & 22 & 39.2 (2023) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Growth rate and market size of F5G use cases according to [23].  
Figure 3: Illustration of the main services, network characteristics, novelties, limitations, and standards of the five generations of fixed networks in a layered approach [4].
## 3 The Numerical Simulation of the Floating Ring Rotor System  
### Analysis of Oil Film Pressure Distribution and Fluid Load  
The oil film pressure distribution of the inner and outer layers of the floating ring at the steady state of 8000 rad/min is shown in Figure 12. There are two obvious pressure concentration zones in each oil film. Blue represents the pressure divergence zone, namely negative pressure. Red represents the pressure convergence zone, namely positive pressure.  
Figure 11: Partial diagram of inner and outer oil film grid.  
Figure 10: Overall meshing result.  
It can be observed from the pressure contour that the maximum oil film pressure of the inner and outer oil films is located in the middle area of the floating ring. From the inside to the outside, the pressure decreases gradually, and the pressure at the outer end of the floating ring is the smallest. The simulation results of oil film pressure are consistent with the pressure distribution obtained using the numerical method in Section 2. Additionally, in the area of the minimum oil film clearance, the positive pressure of the oil film transits to the negative pressure. The wedge-shaped convergence zone forms positive pressure, while the divergence zone forms negative pressure. In a clockwise direction, the pressure in the wedge-shaped zone gradually increases from 0 to the peak of positive pressure and then begins to decrease. It enters the divergence zone through the region of minimum oil film clearance, and the pressure gradually reaches the peak of negative pressure.  
After calculating the oil film pressure distribution, the oil film pressure along the inner and outer surfaces of the floating ring is integrated. The fluid load components on the inner and outer surfaces of the floating ring in all directions are obtained, as shown in Figure 13.  
Figure 12: Oil film pressure distribution of the inner and outer layers of the floating ring. (**a**) Oil film pressure distribution of floating ring 1; (**b**) oil film pressure distribution of floating ring 2.  
Figure 13: _Cont._  
The following conclusions can be drawn from the figure: (1) The \(y\)-direction and \(z\)-direction components of the oil film fluid load inside and outside the floating ring are distributed in periodic sine waves. There is only a small fluctuation when the initial instantaneous load increases. (2) There is a phase difference between the inner oil film load and the outer oil film load. When the inner oil film load reaches the maximum value, the outer oil film load reaches the minimum value. (3) The fluid load on the floating ring 1 with larger bearing capacity and obvious oil film squeezing effect is greater than that on the lightly loaded floating ring 2. After reaching the steady state, the peak values of the fluid load components in the y and z directions received by the inner and outer membranes of the floating ring 1 are both 17 N. The peak values of the load components received by the floating ring 2 in different directions are both 9 N.
# Low-Cost Rapid Fabrication of Conformal Liquid-Metal Patterns
## 2 Spraying of Galinstan Liquid Metal  
Galinstan, which is 68.5% Ga, 21.5% In, and 10% Sn, is a liquid at room temperature, with a conductivity of \(3.5\times 10^{6}\) S/m [17]. A pressurized air gun was used to spray LM, as shown in Figure 1. Once Galinstan is exposed to air it forms a thin oxide film that can coat each LM droplet before it impacts the substrate. The sprayed LM droplets coalesce after hitting the substrate, forming a conductive Galinstan layer covered with the oxide film. Three spraying parameters have been varied in this work: spraying time, spraying distance, and pump pressure.  
Flexible UV-curable polyurethane acrylate (PUA) was used to pattern the sprayed LM. Another type of mask made of polyimide tape was cut into patterns using a craft cutter, in a process based on a previous study [18]. The patterned polyimide tape was used as a mask for patterning LM electrodes with different line widths by adhering the tape to the target substrate. The smallest pattern was a single line cut with the craft cutter, which corresponded to an 84-\(\upmu\)m-wide cut in the polyimide. The LM was sprayed on Rogers Duroid 5880, glass, and polydimethylsiloxane (PDMS) substrates. An air gun with a nozzle diameter of 300 \(\upmu\)m (BBA-003, Beetle Bug) connected to an air compressor was used to spray the LM films. The conductivity of the LM films was obtained by a parameter analyzer (Keithley 4200A-SCS) and a four-point probe. The thickness of the LM sample was measured by a scanning electron microscope (SEM) (JEOL, JSM-7500F). A 1-mm-wide LM line was sprayed on a glass substrate. The thickness of the LM film was measured from the cross-sectional SEM image of the LM film.  
Figure 1: Schematic illustration of liquid metal (LM) spraying process.
# Adaptive Salp Swarm Algorithm for Optimization of Geotechnical Structures
## 1 Introduction  
The objective function in most engineering problems is non-convex and discontinuous, with a large number of design variables. As a result, traditional deterministic optimization techniques based on mathematical principles may struggle to find a global optimum solution due to local optima trapping. The use of powerful metaheuristic optimization algorithms for obtaining a global optimum to overcome this limitation is of interest, and metaheuristic algorithms have proven to be an excellent alternative for solving complex problems in recent decades [1; 2; 3; 4; 5; 6]. The most common geo-structures in practical application are reinforced concrete retaining walls and spread footings, which have received considerable attention in recent studies [7; 8]. These structures are commonly used and typically involve a large volume of material. In the past, the initial anticipated dimensions of retaining structures were tested for stability and other building code requirements. If the dimensions were insufficient to meet the constraints, they were adjusted until all the requirements were met. During this time-consuming, iterative process, the cost of construction was not taken into account. In the optimum design of these structures, the dimensions that provide the lowest cost and weight of construction while meeting all the design requirements are automatically determined. Several metaheuristic algorithms for geotechnical engineering problems have recently been developed and are widely used. Despite the fact that metaheuristic methods can produce acceptable results, no algorithm outperforms another in solving all the optimization problems. Furthermore, the objective function in most geotechnical engineering optimization problems, such as shallow foundations, retaining structures, and pile optimization, is discontinuous and has a large number of design variables. As a result, several research projects have been launched in order to improve the performance and efficiency of the existing metaheuristics. Some of these are modified particle swarm optimizations [9; 10], modified harmony search algorithms [11], modified gravitational search algorithms [12], modified sine cosine algorithms [13], improved salp swarm algorithms [14], modified ant colony optimizations [15], modified teaching-learning-based optimizations [16], improved tunicate swarm algorithms [17], and modified wild horse optimizations [18]. According to the effectiveness of the metaheuristics and their modified versions, these methods have been widely used to solve several geotechnical engineering problems, as presented in Table 1.
# Data Synchronization: A Complete Theoretical Solution for Filesystems
## 7 Conclusions
### Synchronizing More Than Two Replicas  
The first natural question is to extend the synchronization algorithm from two to three or more replicas. An encouraging observation is that if several canonical sets are pairwise refluent (for any pair there is a filesystem on which both of them work), then they are _jointly refluent_, meaning that there is a single filesystem on which all of them work. The natural extension of Definition 6 for three canonical sets \(A\), \(B\) and \(C\) is to define their merger as a maximal canonical set \(M\subseteq A\cup B\cup C\). This definition has the additional advantage that it is symmetric in the filesystems, and does not give precedence to any of them over the others. We can prove that such a merger also satisfies an operational characterization similar to the one stated in Theorem 2. It seems that such a three-way merger can be generated first by merging \(A\) and \(B\) to \(M\), and then merging \(M\) and \(C\). Is this claim true?  
Another question is whether the general task of finding a three-way merger can be reduced to the case when \(A\), \(B\) and \(C\) are pairwise disjoint. Finally, at least in the case when the sets \(A\), \(B\), \(C\) are pairwise disjoint, whether the following variant of the Iteration step of Algorithm 2 generates a 3-way merger, and if yes, whether it generates all possibilities:  
_Iterate:_ Pick a winner command \(\sigma\) from \(A\cup B\cup C\), and discard those commands from the other two sets which are in conflict with \(\sigma\).
# Research on Effective Design Methods of Core Beam of Full Bridge Aeroelastic Model
## 3 Numerical Solution of Torsion Constant
### Finite Element Method  
The Galerkin method is applied to the variation \(\delta\phi\), namely  
\[\int_{\Omega}\Bigl{(}\
abla^{2}\phi+2\Bigr{)}\delta\phi dG_{0}=0, \tag{9}\]  
For simply connected sections, the expression is equivalent to the torsion constant when the stress function is 0 at the boundary \(\Gamma\). So, it is expressed as:  
\[J=\int_{\Omega}\frac{1}{2}\cdot\left[\left(\frac{\partial\phi}{\partial x} \right)^{2}+\left(\frac{\partial\phi}{\partial y}\right)^{2}\right]dG_{0}-\int_ {\Omega}2\phi dG_{0}, \tag{10}\]  
In the region \(\Omega\), the stress function at node \(i\) is supposed as \(\phi i\). For any point in the element \(e\), the stress function \(\phi\) can be interpolated as Equation (11), and the partial derivative of the stress function to the coordinate is expressed as Equation (12).  
\[\phi=N\mathbf{\Phi}_{e}, \tag{11}\]  
\[\left\{\begin{array}{c}\frac{\partial\phi}{\partial x}\\ \frac{\partial\phi}{\partial y}\end{array}\right\}=\left\{\begin{array}{c} \frac{\partial N}{\partial N}\\ \frac{\partial N}{\partial y}\end{array}\right\}\mathbf{\Phi}_{e}=B\mathbf{\Phi}_{e}, \tag{12}\]  
where, \(\Phi_{e}=\{\phi_{1},\,\ldots,\,\phi_{n}\}^{T}\) is the stress function vector of the element \(e\), and \(N=\{N_{1},\,\ldots,\,N_{n}\}\) is the shape function matrix.  
Substituting Equations (11) and (12) into (10), and letting \(\delta J=0\), leads to the balance equation of the element \(e\), as  
\[\mathbf{K}_{e}\mathbf{\Phi}_{e}=\mathbf{R}_{e}, \tag{13}\]  
\[\mathbf{K}_{e}=\int_{\Omega}\mathbf{B}^{T}\mathbf{B}dG_{0}, \tag{14}\]  
\[\mathbf{R}_{e}=2\int_{\Omega}\mathbf{N}^{T}dG_{0} \tag{15}\]  
where, \(\mathbf{K}_{e}\) and \(\mathbf{R}_{e}\) are, respectively, the stiffness matrix and equivalent node loading vector of element \(e\).  
Arranging the balance equations of all the elements in region \(\Omega\) leads to the general balance equation. Typical stress results are shown in Figure 4 by solving the general balance equation. According to Equation (3), the torsion constant is the double volume enclosed by the stress surface and the \(XY\) plane.  
Figure 3: Differential stress function in the region \(\Omega\).