esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion
Other imaging modalities provide information that would be of interest to relate to the ones obtained from X-ray tomography and microscopy. For example, magnetic resonance imaging gives access to local water status within the grain (e.g., for wheat [21]) but scans are very time-consuming, and spatial resolution is still low (cellular level cannot be reached). Mass-spectrometry imaging reveals chemical composition within tissues with improved discrimination power (e.g., for wheat [41]). To have a better understanding of the biologicalfunctions within a complex organ such as the wheat grain, it becomes necessary to merge the complementary information provided by the various imaging source. Due to its high resolution and to the 3D nature of the provided data, X-ray phase-contrast tomography appears as a crucial imaging method that can generate reference geometries of biological organs or tissues. Such reference geometries can be used to track the changes of morphology along the development of the grain, or to serve as a reference model for registering and merging the information provided by other complementary imaging modalities [42,43]. Conceptualization: D.L., A.-L.C.-B. and C.G. ; Methodology: E.B., A.K., C.R. and C.A. ; Data Processing and Visualization: D.L., T.D.Q.L. and L.P.; Writing: D.L., A.-L.C.-B. and C.G. ; Review editing: D.L., C.A., E.B., C.G., A.K., F.G., L.P., T.D.Q.L. and A.-L.C.-B. ; Funding: A.-L.C.-B., C.G. and D.L. Authorship is limited to those who have contributed substantially to the work reported. All authors have read and agreed to the published version of the manuscript. This research was funded in part by the PSICHE beamline (SOLEIL synchrotron facility, project 20170220). This project was also supported by grants from INRAE TRANSFORM (THESECEPIA-2017) and the financial assistance received from the region Pays de la Loire (AAP-ATC-2017). Not applicable. The data presented in this study are available on request. We thank the greenhouse team of IE Vegepole from INRAE Clermont-Ferrand for valuable assistance in plant preparation and care. The authors declare no conflict of interest.
# Gyrotrons as High-Frequency Drivers for Undulators and High-Gradient Accelerators
## 2 Microwave Wigglers and Undulators
In the case of a magnetostatic wiggler, the wavelength of the output radiation scales as \(\lambda\approx\lambda_{w}/2\gamma^{2}\) while the wavelength of the output radiation for an electromagnetic-wave wiggler scales as \(\lambda\approx\lambda_{w}/4\gamma^{2}\). This means that for fixed wiggler periods and beam energies, the electromagnetic-wave wiggler will generate shorter output wavelengths [22]. This makes the electromagnetic-wave wigglers very attractive alternatives to magnetostatic wigglers in the production of short wavelengths when the electron beam energy is constrained. Before going into detail about their realization it should be mentioned that, generally, the RF IDs provide fast dynamic control of the polarization, wavelength, and the dimensionless \(K\)-factor. Distinguishing advantage of the microwave undulators is that they allow much smaller undulator periods (\(\lambda_{w}\sim\lambda/2\) under the assumption \(h\approx k\)) and larger apertures (cm vs. mm) to be used. The latter circumstance makes it possible to use electron beams with a larger radius and emittance. A critical issue for the conventional undulators with permanent magnets is the potential danger of their demagnetization by radiation. In the case of a microwave undulator, however, such risk is absent. The microwave undulators, however, require extremely strong RF fields (tens of GW) that cannot be delivered directly even by the most powerful radiation sources. This makes it necessary to use waveguides and cavities in which the needed microwave energy is pumped and accumulated. The required field strength can be sustained by only compensating for the Ohmic losses in the cavity walls. In order to minimize the losses, the cavity dimensions have to be large enough. In such oversized structures, however, the eventual mode conversion losses can also be significant. Another severe problem is the RF breakdown. Both, the former and the latter problem require special structures to be used (e.g., corrugated waveguides [28; 33; 34]). Since the microwave wigglers and undulators have many promising and advantageous features in comparison with those utilizing static magnets it is believed that they will be used in the next generations of the FELs [23; 25]. The realization of this concept has been delayed due to the absence of powerful enough radiation sources operating at high frequencies and, correspondingly, at short wavelengths of the order of centimeters or several millimeters. The remarkable recent progress demonstrated by the klystrons, magnicon amplifiers, and various gyro-devices (gyro-monotron, cyclotron auto-resonance maser (CARM), etc.) has changed the situation dramatically and has made it possible to propose and develop a range of RF undulators and wigglers. The most notable schemes that utilize gyrotrons or other gyro-devices (e.g., relativistic gyro-klystron [35]) will be discussed in Sect. 3. There we skip, however, the undulators driven by CARM radiation since this topic has been extensively covered by the recent paper [30].
# Online Detection and Fuzzy Clustering of Anomalies in Non-Stationary Time Series +
## 2 Related Work
### Sequential Collective and Point Anomalies  
SCAPA [13] is an online anomaly detection method which detects and distinguishes point and collective anomalies within time series with stationary baselines [12].  
In the univariate setting, where a series \(u_{t}\sim D(\theta(t))\) follows some distribution \(D\), collective anomalies can be regarded as epidemic changes in parameters \(\theta(t)\) away from normal parameters \(\theta_{0}\)[12]. SCAPA identifies collective anomalies by minimising the following penalised cost over the number of collective anomalies \(K\), their start and end points, \(s_{i}\) and \(e_{i}\), and normal feature parameters \(\theta_{0}\)[12]:  
\[\min_{K,\mu_{1},K,\mu_{2},K,\theta_{0}}\sum_{t\in\cup[s_{i}+1,\mu_{i}]}C(u_{t},\theta_{0})+\sum_{j=1}^{K}\bigg{[}\min_{\theta_{j}}\bigg{(}\sum_{t=s_{j}+1}^{ e_{j}}C(u_{t},\theta_{j})\bigg{)}+\beta_{c}\bigg{]}, \tag{2}\]  
where \(C(.,.)\) is a cost function, and \(\beta_{c}>0\) is a penalty to prevent overfitting.  
In our illustrative examples, we consider the mean and variance as our feature parameters and adopt twice the negative of the Gaussian log-likelihood as our cost function--acommon choice, appropriate for our residual series. Within-anomaly parameter estimates \(\theta_{j},j=1,\ldots,K\) are not optimisation variables but are estimated by sample statistics within the set \(\{x_{sj+1},\ldots,x_{c_{j}}\}\). SCAPA has an efficient dynamic programming implementation in the R package anomaly[31]. We utilise this within our empirical examples with a minimum collective anomaly length of 2, a maximum anomaly length (chosen on a per-instance basis for computational efficiency), and a separate penalty \(\beta_{o}>0\) for point anomalies (which are regarded as changes in variance only, with a fixed length of 1).
## 2 Materials and Methods
### Measurements  
Fourier-transform infrared (FT-IR) spectra were obtained by a PerkinElmer (Frontier) instrument (Waltham, MA, USA). Raman spectra were recorded on a HORIBA HR Evolution instrument (Tokyo, Japan). Scanning electron microscopy (SEM) images were recorded by a ZEISS GeminiSEM 300 instrument (Oberkochen, Germany). Transmission electron microscopy (TEM) images were recorded by a JEOL JEM 1230 instrument (Tokyo, Japan) operated at 80 kV. Cyclic voltammetry (CV) and differential pulse voltammetry (DPV) were performed on a Metrohm Autolab PGSTAT302N instrument (Herisau, Switzerland)and controlled by a microcomputer with Metrohm Autolab Nova software. High performance liquid chromatography (HPLC) was performed on a Shimadzu LC-20 AT instrument (Kyoto, Japan).
# Heart Rate Dynamics and Quantifying Physical Fatigue in Canadian Football
## 4 Discussion
### Fatigue  
A new metric of cardiovascular cost (CVC) was explored in this study to evaluate fatigue on two timescales: (a) permanent fatigue experienced within a session, and (b) chronic fatigue experienced over the course of a season. Based on running performances within a session, the overall CVC was higher in linemen compared to skilled players. For both groups of athletes, we observed an increased CVC over the course of a session which could be linked to an increased and perhaps permanent fatigue state experienced by the athletes over the course of a game or training session. Higher CVC may indicate lower cardiovascular fitness, and since low-level evidence is reported linking aerobic fitness and concussion risks [35; 36], future work should explore relating baseline CVC and its changes during a session to head impacts experienced by the athlete.  
Previous studies in soccer have attempted to quantify permanent fatigue experienced by athletes by relating the amount of high-intensity running performed between the start and end of a session, as well as in relation to the peak intensity period and averages of the session [37]. Other methods for quantifying permanent fatigue have used physical tests such as vertical jumps or sprints before and after sessions [38]. These methods have examined fatigue from only physical outputs which may also be influenced by match context and pacing [39], and they use techniques which cannot be used to assess possible fatigue continuously during a session. By contrast, the cardiovascular cost metric proposed here represents the relationship between internal cardiac load and external physical loads, theoretically accounting for any changes in match context.  
Furthermore, when exploring the potential of CVC as a measure of chronic fatigue, there was a moderate positive correlation between the net CVC and days from the start of the season for the three skilled players who performed over the course of the whole season. No correlation was present for the one lineman analyzed, which may be due to the limited number of samples. As such, there may be some motivation for further investigating CVC as a metric for identifying the accumulation of fatigue over the course of a season as an alternative to resting heart rate or heart rate variability [6; 18]. Additionally, there may be added sensitivity of CVC to assess physical readiness or chronic fatigue due to its derivation from performance outcomes rather than measurements during resting state, which should be investigated further.
# Performance Comparisons of Broadband Power Line Communication Technologies
## 1 Introduction
The noise is modeled as background noise added by impulsive noise [10; 19; 20; 21; 22]. The performance of the OFDM transmission scheme for PLC applications was investigated with the channel model in the presence of noise [22; 23]. Studies on narrowband PLC standards such as G3-PLC and PRIME were conducted in [24; 25]. When it comes to performance comparisons of PLC standards, a few results have been reported. For narrowband PLC technologies, the performances of the physical layers of G3-PLC and PRIME were compared on a frequency-selective channel with additive white Gaussian noise (AWGN) [26]. In [27], performance comparisons were conducted with different noise environments. Physical layers of narrowband PLC including IEEE1901.2 were compared under AWGN and narrowband interferer in [28]. Recently, [PERSON] et al. [5] compared the performances of the latest versions of the standards including PRIME 1.4 with that of G3-PLC coherent mode. The comparisons were made through the test metrics defined by the European Telecommunications Standards Institute (ETSI) in the presence of standard and controlled noise patterns. Unlike the physical layer of the narrowband PLC standards, studies are not widely conducted on the physical layer of broadband PLC standards. Especially, results of performance comparisons of broadband PLC standards such as HPGP and HS PLC have not been reported yet. In this paper, studies on the performance evaluation of the IoT PLC as well as HPGP and HS PLC are conducted. The performances are evaluated in three aspects of the physical layer: the bit rate, power spectrum, and bit error rate (BER). The bit rates of the PLC are obtained with mathematical formulas. The power spectrum is obtained with a PLC signal generated by the computer in MATLAB codes. These two evaluations are relatively easy and simple compared to the BER evaluation. For the BER comparison, we obtain the upper bound of the performance for each standard. The BER performance depends on the transmitted signal specified in the standard and the receiver architecture. However, the receiver architecture is not specified in the standard. Therefore, it is assumed that each PLC receiver achieves the best performance possible. The equalizer in each receiver has a one-tap filter and is assumed to have a perfect channel estimation. In this context, impulsive noise is not included since our purpose is to obtain the upper performance bound for each PLC. For background noise, colored noise is known to reflect the noise of the PLC environment better. However, AWGN is also considered useful when comparing the upper performance bound of the PLC. Through computer simulations, the upper bound of the performance of each PLC standard is evaluated and compared.
# Coexistence Scheme for Uncoordinated LTE and WiFi Networks Using Experience Replay Based Q-Learning
## 6 Performance Evaluation
### Fairness and Throughput Performance
Even though there is a significant number of decisions where the second-best actions are executed by the optimal policy, the performance of the coexistence schemes is not highly degraded (as the second-best action can still lead to sufficient fairness and aggregated throughput).
# Investigation of Intermetallics Formation and Joint Performance of Laser Welded Ni to Al
## 3 Results
### Joint Strength Analysis  
As discussed in the previous sections, the samples welded using a PW laser with 150 W power and a focused CW laser with 1800 W power have obvious defects and brittle IMCs. These include AlNi\({}_{3}\) and AlNi. The samples are easily broken by hands, and it is difficult to analyze the weld performance quantitively. Thus, both shear test and 90-degree peel test were only conducted for the samples welded using the PW laser with 120 W power and the defocused CW laser with 1800 W power.  
The testing results are presented in Figure 10. A good reproducibility of the weld joint can be reflected by the error bars shown in Figure 10. It shows that the samples welded using a defocused CW laser with 1800 W laser power can withstand an average shear-force of 980 N, which is much higher than that of the samples welded using the PW laser. Similarly, it also shows a better performance under the 90-degree peel test with an  
Figure 9: The hardness distribution of laser weld: (**a**) PW (150 W), (**b**) CW (1800 W, focal point position 0), (**c**) PW (120 W) and (**d**) CW (1800 W, focal point position +5).  
average peel force of 110 N. The ability of the welds against the force applied shows close relationships with the weld quality and IMCs formation. According to the cross-section view and EDS analysis of the welded samples, the CW laser welding with defocused beam can achieve defect-free welds, and form Al\({}_{3}\)Ni with low hardness. As discussed previously, under this process condition, a weld-braze joint can be obtained, which means the melting of the Al sheet beneath the Ni sheet can be minimized. On one hand, the plasma at the Ni-Al interface can be suppressed to avoid the formation of pores; on the other hand, the melt temperature can be lowered to restrain material mixing, as well as to fulfil the conditions for formation of a thin layer of Al\({}_{3}\)Ni IMC. These beneficial conditions are difficult to manipulate when using a pulsed laser, as high peak power of the laser tends to increase the melting pool temperature and form a deep penetration weld with severe material mixing, leading to the formation of obvious defects, as well as brittle intermetallics, as verified by the results shown in this study.
## 4 Radiometric Processing Workflow
### Scene Reflectance Correction  
#### 4.4.1 BRDF Correction  
When analyzing imaging data measured with wide-angle FOVs, the anisotropy of the surface might cause significant radiometric differences within individual images and between neighboring images [42; 161; 162; 163]. Wide-angle FOVs are very common in UAV imaging spectroscopy to facilitate a larger spatial coverage. This introduces unwanted effects when mosaicing the images, and affects the spectral signature of objects within the scene [42; 161]. BRDF correction is defined as the process of compensating the influence of anisotropy, so that the image reflectance values correspond to the reflectance factor at the (mostly) nadir direction. The commonly used BRDF-models can be classified as physical, empirical, or semi-empirical [164; 165]. In classical remote sensing, a BRDF correction is usually carried out by means of empirical models [102; 166; 167; 119; 159]. The BRDF correction is calculated by determining the BRDF model of the target of interest, and then calculating a multiplicative correction factor for BRDF compensation [164; 159]. It may also include calculation and normalization to reflectance factors for a desired geometry [167; 118].  
The BRDF correction using the simple empirical model by [PERSON] et al. [168] and [PERSON] [169] has been used by [PERSON] [159; 164] and by [PERSON] et al. [44; 65; 163] in the radiometric block adjustment approach. Different statistical methods are also popular in correcting BRDF effects. [PERSON] et al. [112] used the dodging method to compensate for the uneven lighting conditions across a photo frame due to the BRDF effects, fragmented cloud cover, vignetting, and other factors. The process is based on global statistics calculations for a group of images, to balance the radiometry both within individual images and across groups of imagery. Their results showed less than 2% residual root mean square errors (RMSEs) (in reflectance) when calculating the linear fit of the reflectance mosaic and reference reflectance.
# Passive Control of Base Pressure: A Review
## 3 Findings Discussion
The payload fairing significantly modifies its flow field and reduces the aerodynamic drag at transonic and supersonic speeds. The simulations were done by solving time-dependent compressible turbulent axisymmetric Navier-Stokes equations. The closure of the system of equations is achieved using an algebraic turbulence model. The numerical simulation is performed on a single-block structured computational domain. The flow field over the aerospike depends on the freestream Mach number. The effects of the aerospike attached to payload fairing are studied with velocity and density plots. The schlieren pictures, oil flow, and the pressure measurements on an aerospike attached to the payload fairing are analyzed and compared with the present numerical results with the Mach number in the range of \(0.8\leq\rm{M}\leq 3.0\) and freestream Reynolds number range \(33.35\times 10^{6}/\rm{m}\)\(\leq\rm{Re_{\infty}}\leq 46.75\times 10^{6}/\rm{m}\). The Mach number range covers the maximum drag and dynamic conditions during the typical satellite launch vehicle's ascent flight. A distinct flow field is found for \(\rm{M_{\infty}}<1\) and \(\rm{M_{\infty}}>1\) with and without the aerospike attached to the payload fairing. The Flow separation is found at all the freestream Mach numbers over the aerospike, with the recirculation zone being Mach number dependent. As the freestream Mach number increases, the separation zone becomes steeper. It is found that the aerospike attached to the payload fairing leads to drag decline.
## 2 Structural Design of the Platform  
### Composition of the Platform  
The parallel platform designed in this paper consists of a mobile platform, a base platform, six legs, six leg drive components, and twelve offset joints, as shown in Figure 1. The parallel platform has a 6-\(P\)-RR-R-RR kinematic chain. According to the Kutzbach-Grubuler formula for the degrees of freedom of spatial mechanisms, the parallel platform has six degrees of freedom.  
To improve the motion resolution and accuracy of the proposed platform, a stepping motor was used to drive a high-precision ball screw through the zero-backlash harmonic reducer, and a grating ruler reading head with resolution of 50 nm was used as a feedback element to realize closed-loop control of the leg driving ramp block. Clearance elimination processing was performed for each link.  
The platform structure has small axial dimensions and large lateral stiffness characteristics. The conventional leg telescopic driving method was changed to a slider driving the lower joint, and the leg driving assembly was fixed directly to the base platform. The base platform was provided with a mounting surface for the driving component, which was set at an angle of 30\({}^{\circ}\) with respect to the horizontal plane, which is beneficial for the improvement of the movement stroke of the entire platform. This design also reduces the weight and the inertia of the entire collection of moving parts, thereby helping to reduce the number of harmful disturbances of the entire satellite platform caused by orbital motion.  
Figure 1: Configuration and structural components of the parallel platform.
# Simulation of Wind-Battery Microgrid Based on Short-Term Wind Power Forecasting
## 3 Simulation Study and Discussion of Results
### Simulation Results and Discussion
#### 3.4.1 Case Study 1--Constant Load Demand
Similarly, this is due to the particular characteristics of the sample under study. The PLM-based approach tends to be conservative in order to minimize the risk in the forecast, thus preventing the maximization of profits. The total savings in scenario (b) versus (a) is over 28.56%, while the total savings in scenario (c) as compared to the scenario (a) are slightly lower, i.e., 27.26%. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Variable** & **Scenario** & **Minimum** & **1 st Quartile** & **2 nd Quartile** & **Mean** & **3 rd Quartile** & **Maximum** \\ \hline Electricity & (a) & 10.60 & 38.30 & 72.27 & 67.59 & 87.61 & 127.60 \\ purchased & (b) & 0.35 & 20.60 & 40.77 & 49.44 & 49.48 & 141.30 \\ (kWh) & (c) & 0.35 & 25.21 & 41.24 & 50.46 & 79.48 & 135.50 \\ \hline Electricity & (a) & 0.00 & 0.00 & 15.11 & 31.97 & 31.33 & 234.20 \\ sold (kWh) & (b) & 0.00 & 0.00 & 32.57 & 42.89 & 55.92 & 223.30 \\  & (c) & 0.00 & 0.00 & 31.47 & 39.01 & 50.54 & 218.10 \\ \hline \multirow{3}{*}{Net profit (\(\mathbf{\xi}\))} & (a) & \(-25.54\) & \(-16.97\) & \(-10.90\) & \(-9.39\) & \(-6.03\) & 33.01 \\  & (b) & \(-28.25\) & \(-12.26\) & \(-3.26\) & \(-3.70\) & 2.11 & 30.28 \\  & (c) & \(-27.09\) & \(-12.42\) & \(-4.01\) & \(-4.46\) & 1.17 & 30.23 \\ \hline \multirowRegarding the observations of battery usage during the simulation, the comparison of the results in terms of battery charge for scenarios (a)-(c) is not straight-forward as in the previous variables (Table 3). The average battery charge in scenario (a) is significantly lower (by roughly 10%) than that of scenario (b), yet the maximum values of battery charge are almost the same in both of the scenarios. This further implies that the usage of energy storage is less efficient in scenario (a), explaining to a significant extent the lower net profit when compared to scenario (b). Moreover, it is important to note that the maximum battery charge in scenario (c) is slightly lower than scenario (b), implying that there are lower energy storage requirements, as a result of the higher-accuracy wind power forecasts, while maintaining the same average battery usage in both scenarios.