esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Influence of Cr/Ti Ratio on Residual Stress  
Residual stress plays an important role when selecting coating parameters for wear resistance. The \"sin\({}^{2}\varphi\)\" method is used for biaxial stress calculation [39]. The following equation (Equation (6)) is used for stress calculation.  
\[\sigma=\left(\frac{E}{1+v}\right)\times\frac{1}{d_{o}}\times\left(\frac{ \partial d}{\partial sin^{2}\varphi}\right) \tag{6}\]  
where \(\sigma\) is stress, E is the modulus of elasticity, \(v\) is the Poisson's ratio, \(\varphi\) is the orientation of the sample, d\({}_{\text{o}}\) is the intercept from the plot of d versus sin\({}^{2}\)\(\varphi\), and d is the lattice spacing.  
The coating has a residual stress that ranges anywhere from 4.8 to 7 GPa (Figure 9). It is possible to draw the conclusion that the nitride film containing Cr/Ti ratio of 0.587 (T2) shows the greatest amount of compressive stress. The higher the magnitude of the compressive stress that the coating is subjected to, the greater its wear resistance [40]. Open microstructures presenting voids will generally have tensile intrinsic residual stresses due to attractive atomic forces acting across the voids [31]. Since attractive atomic forces act through voids in open microstructures, these residual stresses will typically be tensile [31]. However, denser films formed via ion bombardment typically exhibit compressive stresses that are highly dependent on the energy of the impinging ions, which can be controlled via species ionization and substrate bias. Compressive residual stresses (up to 10 GPa) can be produced when particles from a bombardment are implanted in the forming layer and disrupt the lattice. Hard protective thin films typically feature significant compressive stresses, which might be useful for halting fracture processes by closing forming cracks.  
Figure 8: Volume loss, wear rate, and coefficient of friction of counter body (WC ball) for each sample.  
Alternatively, delamination of a coating occurs under extreme tensile or compressive loads. Therefore, interface engineering to enhance adhesion is essential under these circumstances.
## 1 Introduction  
In recent years, heterocycles had been attracted in medicinal or pesticidal importance due to its wide and spectrum activity [1; 2; 3; 4; 5; 6]. The 1,2,4-triazole compounds represent an important nitro-containing heterocycles with extensively bioactivities [7; 8; 9; 10], such as anti-inflammatory activity [11], anticancer activity [12], anti-oxidation activity [13,14], herbicidal activity [15],antifungal activity [16,17], antiriease activity [18], antidepressant activity [19] and so on. Moreover, 1,2,4-triazole substructure was found in many commercial pesticide or drugs, especially in antifungal medicines (Figure 1). It is an important research field for developing novel 1,2,4-triazole derivatives. Meanwhile, the phenoxy nucleus is key fragment in many herbicides [20]. For example, it is reported that 2,4-dichlorophenoxyacyacetylhydazines exhibited excellent antifungal or herbicidal activity.  
On the other hand, 1,2,4-triazole-thiones are useful intermediates in the field of drug design and discovery. According the rule of bioisostere, when the oxygen atom was replaced by sulfur atom, the biological activity will be improved. So far, many bioactive 1,2,4-triazole-thioether or 1,2,4-triazole-thione derivatives have been reported. For example, [PERSON] and co-authors synthesized a series of alkylsulfonyl-1,2,4-triazole, which exhibited excellent anticancer activity [21]. Another interesting reference reported that a series of 1,2,4-triazole-thioether derivatives containing benzothiazinone and benzooxazinone moiety displayed excellent activity as non-glucose SGLT2 inhibitors [22]. Also, we had synthesized some interesting 1,2,4-triazole-thioether derivatives containing 1,2,3-thiadiazole [23] or pyridine [24] moiety, and these compounds possessed good antifungal activity.  
Figure 1: Some representative commercial drugs or pesticides.  
[PERSON] and co-workers [25] reported the synthesis method about 1,2,4-triazole-3-thiols and their \(S\)-substituted derivatives.  
Microwave-assisted technique is a green method in current organic synthesis [26; 27; 28]. It is attractive offering reduced pollution, low cost and high yields. The method can often shorten the reaction time. In recent years, many references had been reported this method. For example, MW-assisted synthesis heterocycles have been conducted successfully earlier [29; 30].  
In view of all these facts and as continuation of our research on bioactive compounds [31; 32; 33], herein a series of novel thioether derivatives containing 1,2,4-triazole moiety were synthesized under microwave irradiation. The antifungal activity of title compounds was tested.
# Efficient Wireless Monitoring and Control of a Grid-Connected Photovoltaic System
## 5 Experimental Verification
### Wireless Data Transmission Module  
Severe environments can cause temporary or permanent connection failure between sensor nodes. Successful data transmission from a sensor node to the coordinator relies on correct propagation between the nodes, with node failure potentially having a severe influence on network performance. To assess proper node operation, a diagnosis mechanism becomes necessary.  
In order to test if the power generated by the converters can alter the wireless data transmission of the sensor nodes placed near them, experimental measurements have been performed to determine the quality of the signal (link quality indicator (LQI)). Figure 12 shows the measured results providing a signal loss of only 2 dB when the converter is  
Figure 11: Experimental platform.  
stopped (blue line) compared to when it is put to its maximum power (red line), concluding the reliability of the data transmission under extreme working conditions of the converters.  
Figure 13 shows the power consumption of the sensor node, measured in the laboratory. It is observed that it uses an average power of 14.55 mW, while for the transmission of data it uses 46.77 mW.
## 6 Simulation Results  
In this section, simulations are performed on Matlab/Simulink, to show the impact of D-FACTS on the ability to control the voltage at the PCC between the electric distribution grid and the wind farm, which is described in the previous section (Figure 11). According to the previous section of the wind potential in the Algerian highland region, the considered wind speed in the simulation starts at 8 m/s and then reaches 9 m/s. The parameters of generators and D-FACTS are presented in the Appendix A.  
For the more detailed study, the proposed system devices, the D-SVC and D-STATCOM structures used in the context of this paper are the same as the SVC and STATCOM structures, which are presented in [36; 37], giving their associated models with their appropriate control schemes. In addition, the detailed model with some simulations for WECS based on DFIG in power system dynamics are described in [38; 39; 40; 41]. Generally, a short-circuit fault has a significant effect on the wind farm; a voltage drop is caused even if the fault is located near or far from the PCC or the wind farm. This voltage drop at the PCC leads to an over-current in the rotor circuit of DFIG, and fluctuations in the DC bus voltage. Therefore, the rotor side converter (RSC) of the DFIG should be blocked to avoid being damaged by overcurrent in the rotor circuit.  
The block diagram of the simulated wind farm connected to the electrical distribution grid is shown in Figure 12.  
Figure 11: Structure of the studied system based on a wind farm and a distributed-flexible AC transmission system (D-FACTS) connected to the Algerian distribution grid.  
Figure 12: Block diagram of the proposed system on Matlab/Simulink.  
In order to study the behavior and the impact of electrical faults in the distribution grid on the wind farm, worst-case scenarios of grid faults were assumed and included in the simulation. Therefore, the entire system was tested under two types of grid faults:  
* Line to line electrical grid fault.
* Voltage drop at the 60 kV bus.  
The wind speed is considered as constant during the grid fault period, except for this disturbance; and generators and the electrical distribution grid are considered to be working in ideal conditions (no disturbances and no parameter variations in the studied system).
# Landslide-Tunnel Interactions and Control Countermeasures under an Orthogonal System
## 4 Research on the Application Effect of Anti-Slide Piles
### Diameter of the Anti-Slide Pile  
The diameter of the anti-slide pile is an important factor affecting its control effects and cost. This section explores the effect of different pile diameters on their control of the rock surrounding the tunnel. The pile diameter ranges from 0.5 m to 3.0 m. Figure 17 shows the displacement changes in the tunnel crown, the arch shoulder on the far side of the mountain, and the arch shoulder on the near side of the mountain.  
Under the above three working conditions, the deformation of the surrounding rock at the three monitoring points gradually decreases with the increasing pile diameter. Figure 17a shows that the upper retaining anti-slide pile has a good control effect on the tunnel crown and the near-mountainside arch shoulder, and the change in pile diameter has little effect on the displacement of the far-mountainside arch shoulder. Figure 17b shows that, compared with the upper blocking anti-slide pile, the lower supporting anti-slide pile has a better control effect on the deformation of the arch shoulder on the far side of the mountain. When the pile diameter is 1.5-2 m, the deformation rate of the far-mountainside arch shoulder is the largest, and the control effect is the best. Figure 17c shows that the control effect of the upper block lower support anti-slide pile on the surrounding rock is better than that of the other two working conditions; 2.0-3.0 m is an effective range increase for the diameter of the anti-slide pile. By comparing the control effects of the different pile diameter changes on the tunnel under different working conditions, we can provide reference ideas for anti-slide piles used to control surrounding rock stability.  
Figure 16: Tunnel displacement curves at different distances between piles and tunnels.
# Blind Source Separation of Intermittent Frequency Hopping Sources over LOS and NLOS Channels +
## 3 Method
### Hidden State Filtering  
We let \(\hat{x}_{d}(t)\) denote a non-zero component of solution \(\hat{\mathbf{x}}_{d}(t)\) to the optimization problem in Equation (6). Then, \(\hat{x}_{d}(t)\) is associated with a single source, and if state \(s(t)\) of the source were known, \(\hat{x}_{d}(t)=\hat{x}_{d}(t)\cdot s(t)\) would be a refined estimate of \(\hat{x}_{d}(t)\) in the sense that a spurious component would be removed from the solution to Equation (6) if \(\hat{x}_{d}(t)\
eq 0\) but \(s(t)=0\). Conversely, the solution would stand if \(s(t)=1\). While state \(s(t)\) is hidden to the observer, it may be inferred from state observations. We let set \(C=\{x|x\
eq 0\}\); then, observation \(z(t)\) of the state of a source is obtained as \(z(t)=1_{C}\{\hat{x}_{d}(t)\}\), where \(1_{C}\) denotes the indicator function of set \(C\). Hidden state filtering is the problem of inferring state sequence \(s(1:T)\) for each source given an observation sequence \(z(1:T)\) of the source and an HMM model \(\Omega\). In the remainder of this subsection, we discuss the forward-backward procedure, which is then used to solve the HSF problem. The algorithms implementing these methods assume that the HMM parameter \(\Omega\) is known. The estimation of parameter \(\Omega\), when it is not known _a priori_, is addressed in the subsequent subsection.
# On the Application of Machine Learning to the Design of UAV-Based 5G Radio Access Networks
## 3 Technical Challenges and Requirements
### Channel Acquisition and Reconstruction  
In many applications involving U-RANs, acquisition and tracking of channel state information (CSI) at the transmitters and/or receivers is of paramount importance to optimize system performance [56]. Thus, large- and small-scale characterization of the communication channel plays a major role in U-RANs, especially for multiple-input multiple-output (MIMO) systems and mmWave transmissions. Most existing channel models and CSI acquisition/tracking methods targeted at terrestrial RANs cannot be directly applied to U-RANs. Indeed, although an UAV flying over a non-crowded zone might be experiencing favorable propagation conditions (e.g., strong LoS with negligible multipath), CSI acquisition is generally more challenging since both communicating parties (i.e., access points and user devices) might be in motion. Moreover, high-speed UAVs flying in urban environments experience different propagation scenarios (crowded and narrow streets, large roads, parks, etc.) which might induce variable SINR values and frequent changes in the fading scenario from LoS to non-LoS (NLOS) states [57]. In these cases, the capacity of radio links exhibits a highly-dynamic nature, which depends on an extremely large number of parameters. Therefore, one of the major tasks in cellular U-RANs is to continuously monitor the link quality and determine when handoff is required. If a poor signal quality is not detected fast enough (due to rapid changes in channel state), the system capacity may suddenly drop due to excessive co-channel interference and/or undue switching load.  
A reference scenario using ML methods to overcome channel modeling problems is given in [56]. The challenge hence is to reconstruct the path loss map of the environment on the basis of local measurements, together with the path loss values for those geographical locations where no measurements are available [55; 58; 59].
# Germanium Single Crystals for Photonics
###### Abstract  
Germanium (Ge) is a system-forming material of IR photonics for the atmospheric transparency window of 8-14 \(\upmu\)m. For optics of the 3-5 \(\upmu\)m range, more widespread silicon (Si), which has phonon absorption bands in the long-wave region, is predominantly used. A technology for growing Ge single crystals has been developed, allowing the production of precision optical parts up to 500 mm in diameter. Ge is used primarily for the production of transparent optical parts for thermal imaging devices in the 8-14 \(\upmu\)m range. In addition, germanium components are widely used in a large number of optical devices where such properties as mechanical strength, good thermal properties, and climatic resistance are required. A very important area of application of germanium is nonlinear optics, primarily acousto-optics. The influence of doping impurities and temperature on the absorption of IR radiation in germanium is considered in detail. The properties of germanium photodetectors are reported, primarily on the effect of photon drag of holes. Optical properties in the THz range are considered. The features of optical properties for all five stable isotopes of germanium are studied. The isotopic shift of absorption bands in the IR region, caused by phonon phenomena, which was discovered by the authors for the first time, is considered.  
germanium (Ge); single crystal; IR and THz optics; laser; nonlinear optics; acousto-optics; thermal imager; absorption; scattering; impurity +
Footnote †: journal: _crystals_
## 4 Experimental Setup and Procedures
### Response Time
The complete data can be seen in [[http://lirkis.kpi.fei.tuke.sk/wp-content/collVREvalScPIResponse.png](http://lirkis.kpi.fei.tuke.sk/wp-content/collVREvalScPIResponse.png)]([http://lirkis.kpi.fei.tuke.sk/wp-content/collVREvalScPIResponse.png](http://lirkis.kpi.fei.tuke.sk/wp-content/collVREvalScPIResponse.png)) (accessed on 22 April 2021). \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & & **E.ECA.5** & **E.ECA.10** & **E.ECA.15** & **E.ECA.20** \\ \hline \multirow{4}{*}{**ECA.15**} & **max** & 20 & 25 & 35 & 43 \\  & **avg** & 17.50 & 20.89 & 29.65 & 37.00 \\  & **min** & 15 & 17 & 24 & 31 \\  & **std** & 1.72 & 2.67 & 3.50 & 3.83 \\ \hline \multirow{4}{*}{**ECA.15**} & **max** & 20 & 22 & 31 & 40 \\  & **avg** & 17.11 & 19.32 & 26.70 & 36.00 \\ \cline{1-1}  & **min** & 14 & 17 & 22 & 32 \\ \cline{1-1}  & **std** & 1.98 & 1.67 & 2.88 & 2.54 \\ \hline \multicolumn{2}{c}{**RT.inc (\%)**} & 2.30 & 8.17 & 11.07 & 2.78 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Response time summary statistics of the data collected in the E.ECA experiments and response time increase computed from the averages. The statistics are given in _milliseconds_ and the response time increase as a percentage. All values are rounded to two decimal places. \"With\" means with the component, “Without” without the component and “RT.inc” means response time increase.
## 6 Experimental Results
### Cryptographic Processing Speed  
Using the SoC's internal timer, the number of executing cycles consumed by functions executed in the SoC's hardware accelerator core and software implementation can be determined. This was accomplished by modifying the verification function for each accelerator core to use the timer and begin counting each system clock cycle until the result from the test case was returned from the accelerator. For example, the PRINCE encryption test case was measured, as shown in Figure 17. Similar approaches were also created for the software implementation of each algorithm, except for PRESENT-80, which was also executed in the SoC, measuring only one simple test case of each algorithm.  
In comparison to the software implementation of all of the algorithms, the hardware accelerator cores had a much faster processing speed, with the fastest taking 4400 times fewer processing cycles. Table 6 compares the number of cycles required to execute a single test case in the hardware and software implementation of four algorithms. These performance gains demonstrated the efficacy of using a hardware accelerator for a cipher instead of executing it in software, allowing small devices, such as Internet of Things devices, to perform other tasks. The absence of a software implementation for PRESENT-80 was the case since the PRESENT block cipher was designed to be hardware-optimized in the first place, and a software implementation would provide no comparison value. Prior to this, numerous software implementations were attempted, and the processing clock cycle count varied between a few hundred and a few million [26].  
Figure 16: Verification result for the SHA3-512 hash function. Two test cases of a small different ASCII input message (inside the quotation marks) led to two completely different but expected hash output results.  
Figure 17: Hardware and software implementations executing cycle comparison.
# On the Needs and Requirements Arising from Connected and Automated Driving
## 3 5 GCAR Use Cases
\begin{table}
\begin{tabular}{c c} \hline \hline
**Use Case Class** & **Description** \\ \hline Cooperative maneuvers & Traffic safety and efficiency is improved by the coordinated movement of a group of vehicles. This is achieved with the exchange of information among nearby vehicles or with the roadside infrastructure via wireless communication. \\ \hline Cooperative perception & Using on-board sensors and information from nearby vehicles and the infrastructure it is possible to extend the perception range beyond the line-of-sight and local-field view of a vehicle. \\ \hline Cooperative safety & Detection of road users (e.g., pedestrians and cyclists) is improved and enabled by using their handheld devices in combination with information from vehicle on-board sensors and the communication system. \\ \hline Intelligent autonomous navigation & The acquisition of an HD local map is enabled for optimal route selection using long-term (e.g., road conditions) and short-term (e.g., collision avoidance) planning information. \\ \hline Remote Driving & Remote control of car actuators by a human operator or an application server is enabled, to partially or fully automate driving tasks for safety, convenience and efficiency. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Brief description of 5G Communication Automotive Research and innovation (5 GCAR) use cases. for enabling this type of services. Emergency trajectory alignment and traffic flow optimization are examples of use cases that belong to this class. **Remote driving** refers to controlling the different actuators of the car (steering wheel, brake, and throttle) from outside the vehicle through wireless communication. The goal is to enable remote driving of the vehicle by a human operator or an application server, in order to provide more safety, convenience, and efficiency, as well as partially or fully removing the driving task from passengers or vehicle itself. For this purpose, it is necessary for the remote driving controller to receive perception information (e.g., vehicles sensors and local dynamic maps) and, if possible, also data from road infrastructure. The remote driving use case class provides a feature to fill the gaps between a highly automated vehicle and a driverless vehicle. When the automated vehicle faces a complex situation, a remote entity can take the control to drive the car. Remote driving is the most challenging use case family in terms of network requirements, due to the high needs in terms of reliability and reaction time (low latency). Public transport remote driving, remote driving for the last mile delivery, or automated parking are examples of use cases that represent this class. In the following subsections, one representative use case has been selected and studied in more detail to illustrate the needs and particular requirements of each class of applications.