esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
The Ultra-Reliable Low-Latency Communication (URLLC) is expected to be an important feature of 5G and beyond networks. Supporting URLLC in a resource-efficient manner demands optimal Modulation and Coding Scheme (MCS) selection and spectrum allocation. This paper presents a study on MCS selection and spectrum allocation to support URLLC. The essential idea is to establish an analytical connection between the delay and reliability requirements of URLLC data transmission and the underlying MCS selection and spectrum allocation. In particular, the connection factors in fundamental aspects of wireless data communication include channel quality, coding and modulation, spectrum allocation and data traffic characteristics. With this connection, MCS selection and spectrum allocation can be efficiently performed based on the delay and reliability requirements of URLLC. Theoretical results in the scenario of a 5G New Radio system are presented, where the Signal-to-Noise Ratio (SNR) thresholds for adaptive MCS selection, data-transmission rate and delay, as well as spectrum allocation under different configurations, including data duplication, are discussed. Simulation results are also obtained and compared with the theoretical results, which validate the analysis and its efficiency.  
URLLC; MCS selection; spectrum allocation; network calculus; data duplication Article  
A Hybrid Scheme of MCS Selection and Spectrum Allocation  
24 727[[https://doi.org/10.3390/e24050727](https://doi.org/10.3390/e24050727)]([https://doi.org/10.3390/e24050727](https://doi.org/10.3390/e24050727))
Some previous studies on precise point positioning (PPP) with WAAS/EGNOS/MSAS corrections showed that the SBAS-based PPP solution can achieve static positioning accuracy of several decimeters and kinematic positioning accuracy at sub-meter level [5; 6]. The WAAS/EGNOS/MSAS ionospheric corrections were used by [PERSON] and [PERSON] for orbit determination of low earth orbiting satellites during the high geomagnetic activity period of 2012 [7]. The GAGAN corrections were applied to Single Point Positioning (SPP) by [PERSON] et al. and the evaluation in Thailand from 1 January 2017 to 31 March 2017 showed that no significant improvements were gained due to the fact that GAGAN's ionosphere correction is not suitable for Thailand [8]. Similar research on the performance of GAGAN over Sri Lanka was conducted by [PERSON] et al [9]. The performance comparison of EGNOS and SDCM in different user scenarios in Finland were carried out in 2016 [10]. In addition, the maritime application of EGNOS was explored by [PERSON] and [PERSON] [11]. Except for using only SBAS corrections for positioning, the open-source PPP client of the Centre National d'Etudes Spatiales (CNES) PPP-WIZARD provides a PPP processing strategy by mixed use of SBAS ionospheric corrections and RTS precise ephemeris products [12]. As for the accuracy of SBAS corrections, [PERSON] et al. assessed the ionospheric correction accuracy of WAAS and EGNOS, which indicates that the ionospheric corrections from these two SBAS systems can eliminate about 85% of the total slant ionospheric delay [13]. [PERSON] et al. evaluated the accuracy of the WAAS and EGNOS orbit and clock corrections and showed that the scatter of SBAS-correctedGPS broadcast orbit and clock errors exceeds that of the GPS-only broadcast orbit and clock errors for GPS Block IIR, IIR-M and IIF satellites [14]. However, to date, there no comprehensive accuracy evaluation of corrections of different SBAS systems including WAAS, EGNOS, MSAS, GAGAN, and SDCM. Given the increasing application of SBAS systems, such a comprehensive evaluation is of great interest to the GNSS community. In this contribution, we carry out a comprehensive accuracy evaluation and comparison of the orbit, clock and ionospheric corrections from five currently available SBAS L1 services. The rest of the paper is organized as follows. The methodologies to evaluate SBAS orbit, clock and ionospheric corrections are first presented in detail in the next section. Then the accuracies of the orbit, clock and ionospheric corrections from the five SBAS systems over a period of half a year (from 1 January 2018, to 30 June 2018) are evaluated using IGS final ephemeris products and ionospheric delays derived from code-leveled phase ionosphere measurements as the references. Meanwhile, GPS broadcast orbit, clock and ionospheric correction are also evaluated at the same time for comparison. The results and findings are discussed in Section 4, and conclusions are drawn in the last section.
# Improving Vulnerability Management Through Process Mining
## 4 An Exemplary Use Case
### Evaluation
#### 4.8.3 Subgoal 3--Enable Continuous Management of the Process  
To achieve this goal, we have developed an app with five dashboards. The data are updated daily to enable continuous monitoring. The dashboards are as follows:  
1. Overview dashboard;
2. Process explorer;
3. Case explorer;
4. Conformance checker;
5. Benchmarking: assignment group, source, priority.  
The overview dashboard includes the most important KPIs, some general ones, and some specific to process mining. The general ones include the number of vulnerabilities per priority, source, and assignment group. The process-specific KPIs include the throughput time per priority, source, and assignment group. There is also a graph showing how the throughput time changed in the past months and one showing the throughput time to each state (\"Assigned\", \"Deferred\", \"Resolved\", \"Closed\").  
The process explorer as shown in Figure 17 shows the discovered process flows 1, 2, and 3. The number of cases covered can be adjusted manually as well as the enhancement dimension shown.  
The case explorer shows all cases with all case fields and details about the process flow, throughput time, and number of activities. This can be used for deep diving as well as for data verification.  
The conformance checker was already explained above. It can be used to monitor whether the process conformance to the target process improves or if unwanted activities start appearing.  
Finally, there are several benchmarking components. These can be used to deep dive into certain aspects of the process. There is one dashboard comparing KPIs and process flows of different assignment groups, one comparing the different sources, and another with details about the different criticalities. Furthermore, there is one dashboard detailing the deferral process since the service owner wanted more insight into it.  
All dashboards can be interacted with by clicking on a dimension or component. In this way, a single component, a dashboard, or all dashboards can be easily filtered by priority, source, and assignment group for cases including a specific activity or process flow. For more detailed filters, selections can be added that also allow the user to filter for cases with a certain rework or throughput between cases or to crop the process to only include a certain part.  
Figure 16: Violations to the target state process flow.  
Using these dashboards, any changes in the process could be monitored. This includes the impact of a new assignment group or the switch from one source to another. The impact of implementing the improvement ideas gathered from analyzing the above two goals will also be tracked using these dashboards. Furthermore, any deviation from the target process from a single vulnerability or clusters of vulnerabilities could be reacted to quickly.
## 2 Numerical Modeling
### Grid Sensitivity Study and Comparison with Experimental Data

Table 1: Percent difference between the aerodynamic loads computed on the reference grid and the counterparts achieved on the finer and on the coarser mesh; clean cascade, with PS the actuated cascade and SS the actuated cascade; Re \(\sim\)350,000; \(\alpha=8\) degrees. \begin{table}
\begin{tabular}{l l c c c} \hline \hline  & **Grids–Airloads** & \(\Delta\mathbf{C_{1}\ \%}\) & \(\Delta\mathbf{C_{d}\ \%}\) & \(\Delta\mathbf{C_{m_{\alpha}2}\ \%}\) \\ \hline \multirow{2}{*}{**CLEAN BLADE**} & reference/finer & 0.049 & 0.13 & 0.45 \\  & reference/coarser & 0.059 & 0.16 & 0.074 \\ \hline \multirow{2}{*}{**BLADE WITH PS PLASMA**} & reference/finer & 0.7 & 3.1 & 0.4 \\  & reference/coarser & 2.6 & 12.5 & 6.1 \\ \hline \multirow{2}{*}{**BLADE WITH SS PLASMA**} & reference/finer & 0.2 & 1.4 & 0.3 \\  & reference/coarser & 3.2 & 21.0 & 3.6 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Percent difference between the aerodynamic loads computed on the reference grid and the counterparts achieved on the finer and on the coarser mesh; clean cascade, with PS the actuated cascade and SS the actuated cascade; Re \(\sim\)350,000; \(\alpha=8\) degrees. developed periodic behaviour. Sensitivity studies to the time resolution and to the number of simulated periods--the latter shown in the following--have highlighted that these parameters give the best trade-off between accuracy and computational resources. Specifically, the real and imaginary parts of unsteady pressure are computed separately for the pressure and for the suction side of the central blade. The real part of the suction side is then subtracted to the counterpart of the pressure side, in order to get the displayed quantity \(\Delta_{\rm C_{P}}\). The same procedure is adopted for the imaginary part. The numerical results are found in good agreement with the experimental and literature data, in terms of both real and imaginary parts. Light differences are encountered just downstream of the leading edge, where, however, all the plotted data are remarkably scattered.
## 2 Materials and Methods
### Chemico-Physical Composition  
Samples of whole milk, skim milk, retentate and liquid milk-derived formulations (IF1 and IF2) were analyzed for fat, protein, casein, whey protein and lactose content using a Milkoscan FT+ (Foss, Hillerod, Denmark), pH using a Crison Basic 20+ pH meter (Crison Instruments S.A., Alella, Spain), dry matter (DM) according to the ISO reference method [14], ash according to the AOAC method [15]. For minerals (Ca, Mg, Na, K, P, S) and trace elements (B, Zn, Cu, Mn, Fe) determination, 5 g of the samples (whole and skim milk, retentate, IF1 and IF2) were previously dried at 102 \({}^{\circ}\)C for 24 h and then calcined at 550 \({}^{\circ}\)C in a muffle furnace (Gelman Instrument, Opera, Italy). The operating conditions were set to reach 550 \({}^{\circ}\)C in 8 h and hold 550 \({}^{\circ}\)C for another 8 h. The resulting ashes were solubilized with HCl (18.5%, \(w/w\)), transferred to a 100 mL volumetric flask and made up to the mark with ultra pure water. The solution was filtered using paper filters (ashless, Grade 40, Whatman(r), Merk, Darmstadt, Germany). The filtrate was used for subsequent analysis by the inductively coupled plasma optical emission spectrometry (ICP-OES) method, according to the ISO reference procedure [16]. The concentration of the elements Calcium (Ca, \(\lambda\) = 317.93 nm), Magnesium (Mg, \(\lambda\) = 279.07 nm), Potassium (K, \(\lambda\) = 766.49 nm), Sodium (Na, \(\lambda\) = 589.61 nm), Phosphorus (P, \(\lambda\) = 178.22 nm), Sulfur (S, \(\lambda\) = 180.67 nm), Boron (B, \(\lambda\) = 249.77 nm), Zinc (Zn, \(\lambda\) = 213.85 nm), Copper (Cu, \(\lambda\) = 324.75 nm), Manganese (Mn, \(\lambda\) = 257.61 nm), and Iron (Fe, \(\lambda\) = 238.20 nm) was determined using an ICP-OES spectrometer (OPTIMA 7300 DV, Perkin Elmer, Waltham, MA, USA) equipped with a GemTip Cross-Flow II nebulizer (Perkin Elmer) and an autosampler (SC-2 DX, Elemental Scientific Inc., Omaha, NE, USA). Argon flows to generate plasma, auxiliary argon flow and argon flow for the nebulizer were 15 L min\({}^{-1}\), 0.2 L min\({}^{-1}\) and 0.8 mL min\({}^{-1}\), respectively. Sample flow was set at 0.8 mL min\({}^{-1}\).
## 2 Results and Discussion
### Photocatalytic Activity
Such behavior suggested an excellent photostability of the photocatalyst. Photocrosslinked films were used since they maintain their integrity, and the particle leaching does not occur. Also, materials could be reused more easily than by using only simple particles, as previously demonstrated in the literature [38; 39; 68]. Additionally, to demonstrate that dye degradation took place as previously described, the \({}^{1}\)H NMR spectra and total organic carbon (TOC) analysis of MG water solution before and after irradiation were registered. \({}^{1}\)H NMR spectroscopy was used to identify the products that might appear during the degradation of MG. In Figure S5a, the appearance of the methyl group protons of MG at 1.28 ppm and 3.24 ppm were observed, while the signals corresponding to the aromatic protons were found between 5.82 ppm and 7.74 ppm. After visible irradiation in the presence of an L3 composite  
Figure 9: Irradiation-induced evolution of UV-Vis absorption spectra of malachite green (MG) solutions when L2 (**a**) and L3 (**b**) were used as photocatalysts and the corresponding kinetic curves for MG dye degradation (**c**,**d**). film containing ZnO-SnO\({}_{2}\), the disappearance of the peaks corresponding to the MG dye along with solution discoloration occurred (Figure S5b), demonstrating that the degradation process took place. This also demonstrated that the film was not subjected to photodegradation and was stable under irradiation with simulated solar light. The mineralization of MG dye and its decomposition to CO\({}_{2}\) was investigated by measuring the concentration of total organic carbon (TOC) in the solution irradiated with simulated solar light in the presence of the L3 film. The TOC analysis indicated mineralization of about 81%, the result suggesting that the present photocatalyst showed effective activity in the discoloration process and removal of dye organic carbon under simulated solar radiation.
# Mechanical Design and Gait Optimization of Hydraulic Hexapod Robot Based on Energy Conservation
## 3 Robot Modeling
### Statics Modeling  
The HHR structural diagram is illustrated in Figure 5. The HHR moves with triangle gait, and the supporting points on the ground are shown in Figure 6. The vertical projection of the center of mass (COM) should be inside the supporting triangle to ensure the motion stability. The distance from the projection point to the three sides of the supporting triangle is the stability margin of the robot motion. Considering that the robot may be subjected to lateral impact, the stability margin should be as large as possible.  
Taking the robot body's center projection as the origin of coordinate and the forward direction as the \(x\)-axis, the coordinate of the robot body's barycenter vertical projection is \(G\)(n,0) and the vertical projections of root joints are D\({}_{1}\)(b,a), D\({}_{2}\)(b,-a), D\({}_{3}\)(-m,a), D\({}_{4}\)(-m,-a), D\({}_{5}\)(-b,a), and D\({}_{6}\)(-b,-a). Leg (1,4,5) and leg (2,3,6) support the robot alternately, and its supporting force is symmetry in terms of the \(x\)-axis. Leg (1,4,5) is applied for calculation.  
\(G\) is the gravity of the HHR body, and the foot force of leg \(i\) (\(i\) = 1-6) can be expressed as  
\[\mathbf{F_{i}}=\left[\begin{array}{cc}0&0&F_{z,i}\end{array}\right]^{T} \tag{11}\]  
where  
\[F_{z,i}=\frac{d_{i}}{h_{i}}G \tag{12}\]  
The joint output torque can be obtained from Equations (10) and (11).  
\[\mathbf{N_{i}}=\mathbf{J_{i}^{T}}\mathbf{F_{i}} \tag{13}\]  
Figure 5: Structure diagram of the hydraulic hexapod robot (HHR).  
Figure 6: Supporting point of the HHR.  
According to Equations (2), (3), and (13), the hydraulic cylinder output force is  
\[\begin{array}{c}\mathbf{f_{i}}=\mathbf{L_{i}^{-1}N_{i}}\\ \mathbf{f_{i}}=\left[\begin{array}{cccc}f_{0,i}&f_{1,i}&f_{2,i}\end{array} \right]^{T}\end{array} \tag{14}\]
# SPME Method Optimized by Box-Behnken Design for Impact Odorants in Reduced Alcohol Wines
###### Abstract  
The important sampling parameters of a headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) procedure such as the extraction temperature, extraction time, and sample volume were optimized to quantify 23 important impact odorants in reduced alcohol red and white wines. A three-factor design of Box-Behnken experiments was used to determine the optimized sampling conditions for each analyte, and a global optimized condition at every ethanol concentration of interest determined using a desirability function that accounts for a low signal response for compounds. Shiraz and Chardonnay wines were dealcoholized from 13.7 and 12.2% \(v/v\) ethanol respectively, to 8 and 5% \(v/v\), using a commercially available membrane-based technology. A sample set of the reduced alcohol wines were also reconstituted to their natural ethanol level to evaluate the effect of the ethanol content reduction on volatile composition. The three-factor Box-Behnken experiment ensured an accurate determination of the headspace concentration of each compound at each ethanol concentration, allowing comparisons between wines at varying ethanol levels to be made. Overall, the results showed that the main effect of extraction temperature was considered the most critical factor when studying the equilibrium of reduced alcohol wine impact odorants. The impact of ethanol reduction upon the concentration of volatile compounds clearly resulted in losses of impact odorants from the wines. The concentration of most analytes decreased with dealcoholization compared to that of the natural samples. Significant differences were also found between the reconstituted volatile composition and 5% \(v/v\) reduced alcohol wines, revealing that the dealcoholization effect is the result of a combination between the type of dealcoholization treatment and reduction in wine ethanol content.  
reduced-alcohol wine; solid-phase microextraction; gas chromatography; chemometrics 2018/7, 127; doi:10.3390/foods7080127
# On the Energy Efficiency of On-Off Keying Transmitters with Two Distinct Types of Batteries
## 5 Simulation Results
### System Setup  
The system parameters used in simulation experiments are listed in Table 3. A Class-A PA is used at the transmitter (\(\psi=\pi\)), thus \(\eta_{PA}=0.5\) and \(\alpha=1\). In practice, the bandwidth \(B\) is set to be no more than 30 kHz, and the SER is set as \(\Gamma=10^{-3}\) for Rayleigh fading channel.  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \(k\) & \(M_{I}\) & \(G_{\mathbf{0}}\) & \(P_{\mathbf{a}}\) & \(P_{\mathbf{d}}\) & \(\eta\) & \(\alpha\) & \(N_{\mathbf{0}}\) & \(V_{\mathbf{b}}\) & \(\Gamma\) \\ \hline
3.2 & 40 dB & 27 dB & 225 mW & 10 mW & 0.8 & 1 & \(-\)164 dBm & 3.7 V & \(10^{-3}\) \\ \hline \hline \end{tabular}
\end{table}
Table 3: Parameters used in the numerical experiments.
## 1 Introduction
In [26], two kinds of terminal sliding mode control strategies are proposed for implementing the finite-time attitude tracking of spacecraft under environmental disturbances and model uncertainties. In [27], a smooth input MRS model is proposed, then a robust attitude-tracking control scheme is designed based on the backstepping and finite-time disturbance observer. In [28], using the fast terminal sliding mode algorithm, the disturbance observers are designed to generate the estimation of uncertainties and disturbances, while can ensure the estimation errors converge to the origin within a timely fashion. In [29], a worst-case Nash strategy is proposed against the disturbance defined as a player, the authors prove rigorously that an open-loop Nash equilibrium exists in the underlying problem. However, the above methods do not consider the inertia uncertainty specific to high maneuvering flight, which is a technical problem of the HFV that needs to be studied urgently, this study aims to address this issue. In this paper, a passive-active hybrid compensation control scheme is designed for the inertia uncertainty and disturbance of high maneuvering flight. The inertia uncertainty is suppressed by the direct passive compensation method, the disturbance is compensated by disturbance estimation and active sliding mode NDI control. Ultimately, the HFV maintains stable flight despite modeling errors, uncertain parameters, and disturbance. The contributions of this paper are as follows:  
A hybrid compensation scheme of passive robustness and observer-based active disturbance rejection keeps high maneuvering HFV stable when inertia uncertainty and disturbance occur concurrently, the two compensations do not affect each other;  
After the model error of the longitudinal HFV is shielded by the nominal NDI controller, the composite adaptive NDI laws are designed for the uncertain inertia parameter, the uncertainty is directly compensated without relying on the observer;  
The sliding mode disturbance observer is designed to enhance the dynamic suppression force of uncertain and unmodeled and enable the composite adaptive NDI controller to estimate and actively compensate for the elastic modal disturbance. The rest of this paper is as follows: Section 2 presents the linearized HFV model with modeling error and a nominal NDI controller; Section 3 presents a hybrid compensation strategy, namely passive compensation of uncertain parameters and active compensation of disturbance; Section 4 verifies the effectiveness of the proposed intelligent method; Section 5 summarizes the full text.