esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Conclusions  
In the present study, the combined effect of temperature and wounding stress on the accumulation of antioxidant phenolic compounds in potato tubers was reported. The study was focused on evaluating the effect of both abiotic stresses (wounding and temperature) on CGA and CGA isomers (neo-CGA and crypto-CGA) content, since 90% of phenolic composition in potatoes corresponds to these three hydroxycinamic acids. To the best of our knowledge, this is the first report in the literature that studied the effect of temperature on the accumulation of CGAs in wounded potatoes. Previous reports were focused on evaluating the effect of temperature on suberin and lignin accumulation, where a detailed study on the phenolic profile was overlooked. Herein, it was demonstrated that by modifying the temperature, the profile of CGAs could be altered, and thus appropriate storage conditions could be selected to trigger the accumulation of a specific phenolic. However, the physiological mechanism inducing the accumulation of specific CGA isomers has not been reported; thus, further studies should be focused on understanding the biosynthesis pathway of CGA isomers in potatoes under wounding stress.  
Interestingly, as observed in the chromatogram showing the phenolic profile of potato tubers (Figure 1), CGA and its isomers were well separated from each other, as their retention times in the column were 11.3, 16.3, and 20.2 min for CGA, neo-CGA, and crypto-CGA, respectively. Therefore, this chromatographic method could be used as a starting point to scale up the purification of CGA and its isomers for further uses in the pharmaceutical and dietary supplement industries. Likewise, to use stressed potatoes for human consumption, it would be desirable to have more than one isomer accumulated in the tissue. As such, pie-cut potatoes should be stored at 10 \({}^{\circ}\)C for 120 h, which would result in a high accumulation of CGA and neo-CGA in the tissue, when transforming into processed food. However, further research should evaluate the effect of wounding and storage time on the quality attributes of potatoes, as well as on the stability of CGA and its isomers when the tissue is subjected to different food processing conditions.  
Conceptualization, A.M.T.-C. and D.A.J.-V.; methodology, A.M.T.-C. and D.A.J.-V.; formal analysis, A.M.T.-C.; investigation, A.M.T.-C. and D.A.J.-V.; resources, D.A.J.-V.; data curation, A.M.T.-C.; writing--original draft preparation, A.M.T.-C. and D.A.J.-V.; writing--reviewand editing, D.A.J.-V.; supervision, D.A.J.-V.; funding acquisition, D.A.J.-V. All authors have read and agreed to the published version of the manuscript.  
This research was performed with research funds from Consejo Nacional de Ciencia y Tecnologia (CONACYT, Mexico) Grant (177012). Author [PERSON] also acknowledge the scholarship (279532) from CONACYT.  
Not applicable.  
The data presented in this study are available on request from the corresponding author.  
The authors declare no conflict of interest.
# Towards an Automatic Recognition of Artifacts and Features in Plethysmographic Traces
## 4 Detection of Artifacts
### Results  
The separation between the 10 th and 90 th quantiles (\(\Delta_{quant}\)) provides an indication of the accuracy of the prediction. Additionally, the residual difference between the predicted (50 th quantile) and the measured value \(\Delta_{pred}\) indicates how large the deviation in a specific timestep is from the expectation, as shown in Figure 4. A threshold, set to half of the maximum of \(\Delta_{comb}=\Delta_{pred}+\Delta_{quant}\), was applied to classify data points exceeding this value as artifacts. Figure 5 illustrates an example where the model identified artifacts in a compromised plethysmographic trace. By using three distinct indicators--the quantile separation, the prediction residual, and their combined effect--the exclusion criteria could be adjusted for various scenarios. Identified artifact intervals can be excluded from subsequent analyses to ensure data integrity.  
Future improvements in the network and in the training sample could enable its application to quasi-real-time data, providing immediate feedback to the operator acquiring the plethysmographic trace. The system could notify the operator about the validity of the data if one or more artifacts are detected during acquisition. Since the alert can be issued either during or immediately after data collection, the operator has the opportunity to repeat the measurement if necessary. This approach contrasts with the current standard,  
Figure 4: An example of a plethysmographic trace without artifacts. The prediction from the LSTM model does not significantly differ from the real measurement, which is also included within the 10 th–90 th quantiles interval.  
where analyses are often conducted hours or days after data acquisition. Such delays preclude the possibility of repeating measurements in cases where the artifact count is excessively high, as the patient may no longer be available.
## 3 Results
### Experimental Verification  
We tested the detection method by receiving an Alpha navigation signal in space. Figure 10 shows the testing scheme. A magnetic antenna was used to receive the Alpha signal in space, and the radio frequency (RF) signal was amplified using the Alpha receiver. We used a high-speed data collection board to obtain the Alpha navigation signal received by the antenna. The detection method proposed in this study was used to process the collected Alpha digital signal.  
Since the Alpha navigation system was not transmitting signals at the time, we used the Alpha navigation signal collected in February 2019. The test site is located in Xi'an City, and its coordinates are (034 deg15' N, 108 deg54' E). The great circle distance of the test site from the eastern secondary station is 6640 km. Figure 11 shows the signal waveforms and spectrograms at the test site. The waveform diagram shows that the received signal is not only weak but also has many continuous wave and pulse interferences. Although the spectrogram can slightly distinguish the existence of an Alpha navigation signal, the signal is weak, meaning that the signal belongs to an extremely low SNR signal.  
We used the proposed detection method to process the collected signals. Figure 12 shows the three frequency signals obtained after the notch and their correlation peaks. In Figure 12a, it can be observed that the notch filter can easily extract the three obvious frequency signals. In Figure 12b-d, the correlation peaks of the three frequency signals are sharp and obvious after orthogonal correlation. We used the threshold calculation method and the station sentence condition in Section 2.2.3 to detect the correlation peaks' positions for the three frequency signals. The detection results show that the three correlation peaks adhere to the transmission order of the eastern secondary station signal, showing that the eastern secondary station detection is successful. In this section, the proposed method is verified by using real signals, and it is proven that the method proposed in this paper can detect extremely weak signals.  
Figure 11: Signal collected at test site. (**a**) Signal waveform. (**b**) Signal spectrogram.  
Figure 10: The testing scheme of the proposed detection method.
## 2 Methodology
### Voltage Uprating for the Typical Tower of 132 kV Transmission Line Processes and Its Analyses  
Figure 3 depicts the processes in this voltage uprating for the transmission line system in Malaysia. In order to achieve voltage uprating, associated techniques and processes against electrical clearance requirements were used in this study. The proposed techniques of voltage uprating for existing transmission were divided into two parts. The first proposed technique was by increasing insulation strength, while the second proposed technique improved conductor air clearance. All proposed techniques and processes were measured to fulfill electrical clearances requirements under still air and windy conditions. The minimum air clearances required for each voltage level are given in IEC60071 [23; 24]. The minimum electrical clearances during still air and wind conditions for the 275 kV transmission line system can be seen in Tables 1 and 2.  
The nature of the voltage stresses that a transmission line system had experienced power frequency, lightning, and switching overvoltages [17; 25; 26; 27; 28; 29; 30; 31]. Both transient and power frequency overvoltages stresses appear in all shapes and with different amplitudes. Each type of transient and power frequency overvoltages may occur during most types of meteorological conditions, leading to the flashover strength differently [32]. In this study, the requirement of electrical clearances (i.e., phase-to-earth, phase-to-phase and phase-to-ground) under still air conditions subjected BIL of power frequency and transient overvoltages. The transmission line was exposed to environmental factors and it had experienced normal insulator string swing leading to reduction of phase-to-earth clearance,  
Figure 2: The typical of the 132 kV transmission tower in Malaysia; (**a**) type 23 L of tower geometry, and (**b**) available electrical clearance.  
however, the movement of insulator string under normal wind conditions is negligible. Thus, the requirement of electrical clearances of normal wind conditions is considered as under still air condition. For extreme wind conditions, insulator string experienced \(57^{\circ}\) swing angles, which are significant decrements of insulation strength (i.e., phase-to-earth) that may occur flashover under the normal operating voltage. The magnitude of the power frequency voltage is much lower than transient overvoltages, thus, it is essential to examine the BIL of power frequency voltage [33].  
\begin{table}
\begin{tabular}{c c c c} \hline
**BIL for 275 kV Line** & \multicolumn{3}{c}{**Minimum Clearance (m)**} \\ \cline{2-4} **(Highest System Voltage 300 kV)** & **Phase-to-Earth** & **Phase-to-Phase** & **Phase-to-Ground** \\ \hline Power frequency (300 kV) & 0.51 & 0.83 & \\ Switching impulse (850 kV) & 1.80 & 2.60 & 7.00 \\ Lightning impulse (1050 kV) & 1.90 & 2.10 & \\ \hline \end{tabular}
\end{table}
Table 1: Requirement of electrical clearance under still air condition [13; 23; 34].  
Figure 3: Techniques and processes of the voltage uprating proposed method.
## 3 Membrane Performance Measurements
### Test Condition and Cases  
The experimental conditions were created close to the environment in which the actual system could be applied, considering the problems described earlier. The configuration of conditions are listed in Table 1. Tests A and B were used for repeatability and tests C and D to compare membrane performance under difference absolute pressure conditions.  
+Experiments were conducted in two steps. The first was to compare two cells with nitrogen permeation set in opposite directions to determine whether nitrogen permeation  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Variables** & **Test A** & **Test B** & **Test C** & **Test D** \\ \hline Initial absorbent ray mass (g) & 77.31 & 79.92 & 89.19 & 75.78 \\ Distance from membrane to absorbent (mm) & 5 & 5 & 5 & 5 \\ Relative humidity (\%) & 50 & 50 & 50 & 50 \\ Temperature (\({}^{\circ}\)C) & 30 & 30 & 30 & 30 \\ Pressure difference, \(p-p_{atm}\) (kPa) & \(-\)42.22 & \(-\)41.98 & \(-\)42.25 & 162.46 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Experimental conditions for test setup.  
Figure 4: Scanning electron microscope (SEM) images of the membrane sample. (**a**) Hydrophobic membrane side with agglomerated silica nanoparticles of 5 wt\(\%\) and (**b**) the polyamide support (**c**) a membrane cross-section showing the thicknesses of each layer.  
affects the water vapor permeability of the dense membrane. In addition, the experiment was conducted with the existing cup method, comparing the variation in the permeability with the absolute pressure difference. Secondly, we measured the permeance and selectivity changes in response to changes in humidity. The data from the measurements allowed us to predict indicators in different humidity conditions by extrapolation.
# Lifetime Measurement of Cesium Atoms Using a Cold Rydberg Gas
## 1 Introduction  
Rydberg state of alkali atom, the principal quantum number \(n\gg 1\), has been extensively investigated due to its extraordinary properties. The attractiveness of Rydberg atom mainly arises from the properties of large size and transition dipole moment, strong interaction, and long radiative lifetime, and so on [1]. The lifetime of Rydberg atom scales as \(n^{3}\), for example, the calculated spontaneous radiative lifetime of the \(70S_{1/2}\) Rydberg atom is 371.6 \(\upmu\)s. However, the lifetime of Rydberg state is affected by the blackbody radiation and the strong interaction between Rydberg atoms scaling as \(n^{11}\)[2; 3; 4]. Therefore, accurate measurements of the lifetimes of Rydberg states are not only important to test theoretical calculations of the dipole matrix element and the oscillator strength but also for the determination of absolute cross section of collision and related phenomena such as population transfer due to blackbody radiation [1; 5] and the Rydberg-atom based quantum information process and quantum simulations [6; 7; 8; 9].  
The lifetime of rubidium \(|27D\rangle\) state [10] was firstly measured with the laser cooled rubidium atom [11; 12] and then the measurement of \(|nD\rangle\) Rydberg states for \(26<n<45\) range was reported with measurement accuracy less than 3% [13; 14]. The lifetime of cesium Rydberg \(|nD_{5/2}\rangle\) state for \(50<n<75\) range were measured in a 1064-nm far-off-resonance trap by the mean of measurements of photoionization rates [15]. The cesium \(|nS\rangle\) and \(|nD\rangle\) state for \(30<n<40\) range were measured in a magneto-optical trap (MOT) by the field ionization technique [4; 16]. In theory, [PERSON] et al. [5] calculated the spontaneous radiation lifetime and effective lifetime of alkali Rydberg atom with taking into account the blackbody radiation (BBR) in the range of \(10\leq n\leq 80\) employing the quasiclassical approximation.  
In this work, we present an experimental measurement of the lifetime of cesium \(|nS_{1/2}\rangle\) and \(|nD_{5/2}\rangle\) Rydberg atoms (\(n=60\)-83) with a MOT by the field ionization technique. Theeffects of the room temperature BBR and atomic density on the Rydberg decay rate and further lifetime are investigated, which show that the blackbody radiation and strong interaction between Rydberg atoms can enhance the decay rate and modify the lifetime of the given Rydberg state. Finally, the scaling law of Rydberg lifetime is investigated and the experimental measurements agree well with the calculations of literature [5], the cross section of Rydberg interaction is extracted from the density dependence of the decay rate. Difference from Refs. [15; 16], the \(n\)-range used here is \(n=60\)-\(83\), and the agreement between the lifetime measurements and model calculations provides an evidence that the calculation of the effective lifetime accounting BBR in the Ref. [5] can be extend to \(n=83\).
# Implementation of Autonomous Mobile Robot in SmartFactory
## 2 Autonomous Mobile Robots
### Navigation System  
For the navigation system to be able to find the route, it needs initialization data according to which it will plan the route. The user enters the information about where the robot should arrive. However, to plan a route, the mobile robot must also know the space in which it moves and its current position. For orientation in space, a virtual map is used, which is stored in the robot's memory and contains data about all walls and obstacles. This map must be created before it is possible to use the mobile robot. Once the virtual map is created, points can be inserted into it through which the robot moves. However, it is possible to edit the map using zones, landmarks, and special planning rules.  
After obtaining all the data for the start of route planning, the route is planned by the robot itself, which is in charge of the global planning system. This is an algorithm that generates a route to the desired point. However, it is important that the global planning system generates the path to the destination only once and follows only the fixed obstacles that are recorded on the virtual space map. This means that if a new obstacle arises in the environment of the robot that is not recorded on its virtual map, the global planning system does not know about this obstacle and plans a journey despite this obstacle. The planned route is shown on the map or on the dashboard using dots. If the robot cannot complete the move, planning is terminated with an error message, and the whole mission is suspended.  
The local planning system, unlike the global planning system, runs in a continuous cycle throughout the robot's operation. Its task is to respond to obstacles in the immediate vicinity of the robot that are detected by sensors and not recorded on a virtual map. In the case of detecting an obstacle on a route, the local planning task is to determine the route through which the mobile robot can bypass the obstacle. If an obstacle is out of range or out of the sensor's field of view, the system does not take this obstacle into account. In a route that is created using global planning, the robot dodges the obstacle only to embrace the obstacle and then returns to the generated original route. The mobile robot route can be blocked so that the system cannot find a detour route. In this case, the mobile robot has a set count of attempts, that is, how many times the robot tries to find a new route. The route can be blocked, for example, by a person who just walks through and then clears the way.  
Figure 2: Navigation principle of mobile robots [20].  
If the mobile robot does not find its way in any of the set attempts, it pauses the active mission and waits for further instructions.
## 3 Results
### Test Mission  
To test the effectiveness of the system in a real-life operation, a mission emulating helicopter surveillance to monitor a traffic situation was performed, as shown in Figure 11, which illustrates a police officer on the ground requesting a drone to establish better situational awareness of the current traffic from a mobile patrol car equipped with a drone surveillance system. Approval and dispatch of the drone to the requested area were obtained, and the video stream of the monitored environment was displayed on the car patrol monitor. Information about the environment was relayed back to the officer on the  
Figure 10: B-D4S prototype [authors].  
\begin{table}
\begin{tabular}{l l l l} \hline \hline
**Item** & **Requirement** & **Data Sheet Justification** & **Matching** \\ \hline \multirow{3}{*}{Communication link} & \multirow{3}{*}{Short range, secure, and reliable} & O3 & \\  & & 2.4 GHz/5.8 GHz Auto-Switching & \\  & & (compatible with Ocusync 2.0) & \\  & & 4-antenna 2T4R & \\ \hline \multirow{3}{*}{Ground control unit} & Portable & 5472 \(\times\) 3078 @ 24/25/30 fps & \\  & With HD display & & \\ \hline GPS & Accuracy for urban- and & & \\  & open-space navigation & GPS + GLONASS + GALILEO & \\ \hline Surveillance camera & HD with night vision & 5.4 K & \\ \hline Video recording facility & Based on the nature and duration of & Supports a microSD card with a & \\  & operational use & capacity of up to 256 G & \\ \hline High battery life & The longer the better & Approx. 4 h & \\ \hline Onboard charging facility & Wired/wireless charging or other technology & NO & \\ \hline Light & LED & Single LED & \\ \hline \hline \end{tabular}
\end{table}
Table 5: _Cont._ground to facilitate decisions about necessary actions. After the mission was accomplished, the drone was recalled back to the traffic police patrol car.  
Evaluation of the operational framework and system architecture was conducted by key stakeholders in order to obtain their feedback on the proposed framework and to make sure that it will tackle most of the issues required for the deployment of drone applications in Qatar, which does not currently have a framework for this kind of technology. The second evaluation was conducted by a consortium of 70 security experts with no previous experience of using such a system to assess whether the proposed architecture is achievable to be deployed within Qatar in particular and other countries in general, considering drone use for safety and security applications. Such evaluation extends beyond technical performance issues to include consideration of end-user safety to facilitate real-life deployment and acceptability among users and the general public related to the TAM.
## 6 Numerical Experiments  
This section of the manuscript presents the numerical experiments, which were undertaken to compare the proposed SAEA algorithm against the alternative EA algorithms. Specifically, performance of the developed SAEA algorithm, which relies on the self-adaptive parameter control strategy, was evaluated based on a comparative analysis against the following EA algorithms: (1) Adaptive EA (AEA)--an EA that relies on the adaptive parameter control strategy (i.e., the crossover and mutation probabilities are not encoded in the chromosomes, but are altered based on feedback from the search); (2) Deterministic Parameter Control EA (DPCEA)--an EA that relies on the deterministic parameter control strategy (i.e., the crossover and mutation probabilities are not encoded in the chromosomes, but are altered based on a certain counter without any feedback from the search); and (3) typical EA algorithm that does not use any parameter control strategies and solely relies on the parameter tuning (i.e., the crossover and mutation probabilities are set based on the parameter tuning and do not alter throughout evolution of the EA algorithm). For a detailed description of the AEA algorithm this study refers to Dulebenets [10], where the algorithmic parameters were altered if no changes in the objective function occurred after a pre-determined number of generations (\(g^{max}\)). For a detailed description of the DPCEA algorithm this study refers to Dulebenets [12], where the algorithmic parameters were altered based on a pre-determined piecewise function (i.e., the number of generations was used as a counter for changing the algorithmic parameters).  
Furthermore, the optimality gap analysis was conducted for all the considered solution algorithms to assess quality of the obtained solutions for the small size problem instances. The SAEA, AEA, DPCEA, and EA algorithms were designed in the MATLAB 2016a environment [25] on a CPU with Dell Intel(R) Core(tm) i7 Processor, 32 GB of RAM, and Windows 10 Operating System. The optimality gap analysis was conducted within the General Algebraic Modeling System (GAMS) environment [26], and CPLEX was used to solve the **BSPSR** mathematical model to the global optimality. The following sections of the manuscript elaborate on the input data generation for the **BSPSR** mathematical model, parameter tuning analysis for the developed solution algorithms, comparative analysis against the exact optimization algorithm, and comprehensive evaluation of the algorithms in terms of various performance indicators (including objective function and computational time values, convergence patterns, evolution of the self-adaptive algorithmic parameter values, algorithmic stability, and changes in the population diversity).