esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Analysis of Gin, Rum, and Whiskey Samples by HS-SPME-GC-Ms
\begin{table}
\begin{tabular}{l l l l l l l} \hline \hline
**Chemical Class** & **Compound** & **exp. RI** & **th. RI a** & **Gin b** & **Rum b** & **Whiskey b** \\ \hline \multirow{9}{*}{monoterpene} & \(\alpha\)-thujene & 920 & 929 & + & - & - \\  & \(\alpha\)-pinene & 929 & 937 & ++ & - & - \\  & dehydroosabinene & 937 & 956 & tr & - & - \\  & camphene & 939 & 952 & tr & - & - \\  & thuja-2,4(10)-diene & 945 & 956 & + & - & - \\  & sabinene & 965 & 974 & + & - & - \\  & \(\beta\)-pinene & 967 & 979 & + & - & - \\  & \(\beta\)-myrce & 989 & 991 & ++ & - & - \\  & \(\alpha\)-phellandrene & 997 & 1005 & + & - & - \\  & \(\alpha\)-terpinene & 1009 & 1017 & + & - & - \\  & p-cymene & 1018 & 1025 & + & - & - \\  & limonene & 1023 & 1030 & ++ & tr & tr \\  & (Z)-\(\beta\)-ocimene & 1031 & 1038 & + & - & - \\  & (E)-\(\beta\)-ocimene & 1041 & 1049 & + & - & - \\  & y-terpinene & 1052 & 1060 & ++ & - & - \\  & terpiolene & 1080 & 1088 & + & - & - \\  & perillene & 1092 & 1101 & + & - & - \\  & p-mentha-1,3,8-triene & 1101 & 1119 & tr & - & - \\ \hline \multirow{9}{*}{monoterpene} & 1094 & 1099 & + & - & - \\  & 1-octem-3-yl acetate & 1105 & 1111 & + & - & - \\  & \(\alpha\)-pinene epoxide & 1116 & 1095 & + & - & - \\  & unknown 3 & 1121 & - & + & - & - \\  & pinocarveol & 1127 & 1138 & tr & - & - \\  & camphor & 1132 & 1144 & tr & - & - \\  & citronell & 1143 & 1153 & tr & - & - \\  & unknown 4 & 1147 & - & + & - & - \\  & unknown 5 & 1151 & - & + & - & - \\  & menthol & 1159 & 1170 & - & + & - \\  & isopinocamphone & 1161 & 1173 & tr & - & - \\  & terpinen-4-ol & 1167 & 1177 & + & - & - \\  & verbenyl ethyl ether & 1174 & 1186 & + & - & - \\ oxygenated & \(\alpha\)-terpineol & 1180 & 1189 & tr & - & - \\ monoterpene & piperitol & 1206 & 1208 & + & - & - \\  & fenchyl acetate & 1209 & 1224 & tr & - & - \\  & citronell & 1221 & 1228 & + & - & - \\  & thymm methyl ether & 1226 & 1235 & ++ & - & - \\  & carvacrol methyl ether & 1233 & 1244 & tr & - & - \\  & carvotanacetone & 1236 & 1246 & tr & - & - \\  & linalyl acetate & 1247 & 1257 & + & - & - \\  & geranial & 1261 & 1270 & tr & - & - \\  & bornyl acetate & 1277 & 1285 & ++ & - & - \\  & lavandulyl acetate & 1283 & 1289 & + & - & - \\  & myrtenyl acetate & 1315 & 1327 & + & - & - \\  & citronellyl acetate & 1346 & 1353 & + & - & - \\  & neryl acetate & 1360 & 1365 & ++ & - & - \\  & geranyl acetate & 1381 & 1282 & ++ & - & - \\ \hline \multirow{9}{*}{ sesquiterpene} & unknown 8 & 1321 & - & + & - & - \\  & unknown 10 & 1329 & - & + & - & - \\  & \(\alpha\)-cubebene & 1342 & 1351 & ++ & - & - \\  & \(\alpha\)-ylangene & 1363 & 1372 & + & - & - \\  & \(\alpha\)-copaene & 1369 & 1376 & ++ & - & - \\  & \(\beta\)-elemene & 1389 & 1391 & ++ & - & - \\  & isolongifolene & 1396 & 1391 & + & - & - \\  & \(\beta\)-caryophyllene & 1419 & 1425 & ++ & - & - \\  & \(\beta\)-cubebene & 1424 & 1433 & + & - & - \\ \hline \hline \end{tabular}
\end{table} 
Table 4: _Cont._
## 5 Gaofen-3 Time Series Results Analysis and Comparison
### The Comparison with the Results from Sentinel-1 Images  
To access the accuracy of InSAR results derived from Gaofen-3 images, both Gaofen-3 and Sentinel-1 SAR images were available over the study area from September 2020 to April 2021. The SBAS-InSAR results derived from the two datasets could be used to cross-validate for the precision of our InSAR results of the Gaofen-3 dataset. As shown in Figures 9 and 11, due to the similar spatial distribution of the subsidence signatures derived from the two independent SAR datasets, the subsidence rates of the Gaofen-3 images agree well with the observations of the Sentinel-1 images. The largest subsidence velocity reached \(\sim\)--98 mm/a, located at Chaoyang District, but most of the subsidence velocities of the two datasets ranged from \(\sim\)--80 mm/a to 30 mm/a. To validate the precision of  
Figure 10: The time series results of feature points (black star) for Gaofen-3 in Figure 9.  
Figure 9: Average subsidence velocity map derived from Gaofen-3 between September 2020 and March 2021, the areas of red dash lines are the main subsidence bowls during the monitoring period.  
our InSAR results of the Gaofen-3 images, the subsidence velocity maps were selected to compare the difference between the two independent SAR datasets in vertical directions. Figures 12 and 13 demonstrate the correlation between the Gaofen-3 and Sentinel-1 annual velocity maps, with most of the difference values between the two datasets ranging from \(-10\) to \(\sim\)10 mm/a, indicating a similar subsidence pattern.  
Figure 11: Average subsidence velocity map of Sentinel-1 from August 2020 to April 2021, the areas with red dash lines are the main subsidence bowls during the monitoring period.  
Figure 12: The difference subsidence velocity map between Sentinel-1 (August 2020–April 2021) and Gaofen-3 (September 2020 and March 2021).
## 2 Quadrotor UAV: Modeling and Control
### System Description and Modeling of a QUAV
\[m\dot{\mathbf{v}}=\mathbf{F}_{g}+\mathbf{F}_{d}+\mathbf{F} \tag{1}\]  
\[\mathbf{I}_{B}\dot{\omega}_{B}+(\mathbf{\omega}_{B}\times I_{B}\mathbf{\omega}_{B})+ \mathbf{M}_{a}=\mathbf{M}_{B} \tag{2}\]  
In Equation (1), the acceleration of mass \((m\dot{\mathbf{v}}=m(\ddot{x}\ \ddot{y}\ \ddot{z})^{T})\), depends on gravity force \((F_{g}=(0,0,-mg)^{T})\), drag forces \((\mathbf{F}_{d}=diag(k_{1},k_{2},k_{3})\mathbf{v}^{T})\) and the total thrust of the four rotors \((\mathbf{F}=\ ^{W}R_{B}[0,0,u_{1}]^{T})\). In Equation (2), the angular acceleration of the inertia \((I_{B}\dot{\omega}_{B})\), the centripetal forces \(((\mathbf{\omega}_{B}\times I_{B}\omega_{B}))\) and the aerodynamic forces \((\mathbf{M}_{a}=diag(k_{4},k_{5},k_{6})\omega_{B}^{2})\) are equal to the external torque \((\mathbf{M}_{B}=(u_{2},u_{3},u_{4})^{T})\). Substituting forces expressions and each moment into (1) \(y\) (2) we have the following translational and rotational dynamics of the QUAV:\[ \begin{bmatrix}\dot{x}\\ \dot{y}\\ \dot{z}\\ \dot{\phi}\\ \ddot{\theta}\\ \ddot{\psi}\end{bmatrix} = \begin{bmatrix}\frac{1}{m}(\cos(\psi)\sin(\theta)\cos( \phi)+\sin(\phi)\sin(\psi))u_{1}-\frac{k_{1}}{m}\dot{x}\\ \frac{1}{m}(\sin(\psi)\sin(\theta)\cos(\phi)-\sin(\phi)\cos(\psi))u_{1}-\frac{ k_{2}}{m}\dot{y}\\ \frac{1}{m}(\cos(\phi)\cos(\theta))u_{1}-g-\frac{k_{2}}{m}\dot{z}\\ \frac{(Iy-Iz)}{Ix}\dot{\phi}\psi-\frac{k_{3}}{Ix}\dot{\phi}^{2}+\frac{1}{Ix}u_ {2}\\ \frac{(Iz-Ix)}{Iy}\dot{\phi}\dot{\psi}-\frac{k_{5}}{Iy}\dot{\theta}^{2}+\frac{ 1}{Iy}u_{3}\\ \frac{(Ix-Iy)}{Iz}\dot{\phi}\dot{\phi}-\frac{k_{6}}{Iz}\dot{y}^{2}+\frac{1}{Iz} u_{4}\end{bmatrix} . \tag{3}\]
## 3 Results and Discussion
### Phytochemical Characterization and Bioactivity
#### 3.3.1 Composition in Individual Phenolic Compounds
maritium_ plants were an important source of \(p\)-coumaroylquinic acid isomeric forms, compounds **38** and **41**, 78.310 \(\upmu\)g/g FW and 43.242 \(\upmu\)g/g FW, respectively, which is in line with [PERSON] et al. [84]. The compound \(p\)-coumaroylquinic acid was also present with a high content in _S. fruticosa_ and _S. ramossissima_ plants (11.764 \(\upmu\)g/g FW and 3.644 \(\upmu\)g/g FW, respectively). Diverse \(p\)-coumaric acid derivatives were found with considerably high contents among the analyzed halophytes (compounds **12** and **34** in _C. maritium_; compounds **44** and **23** in _S. fruticosa_; compounds **88** in _D. crassifolium_; and compounds **54** and **56** in _M. crystallizationum_). The non-conjugated form of \(p\)-coumaric acid (compound **13**) was quantified in _I. crithmoides_ and _S. ramossissima_ plants in a relatively lower content than the \(p\)-coumaric acid conjugated forms. The presence of \(p\)-coumaric acid and its derivatives in halophyte plants, such as _M. crystallimum_, have been related to the in vitro and in vivo antioxidant metal-ion scavenging properties of these plants [12]. _M. nodiforum_ was the species with the lowest amount of hydroxycinnamic acids.
## 4 Materials and Methods
### Synchrotron Radiation Circular Dichroism Spectroscopy (SRCD)  
The SRCD spectra of Pln149-PEP20 were collected at the AU-CD beamline on the ASTRID2 synchrotron (University of Aarhus, Aarhus, Denmark) over the wavelength range of 280-170 nm, using a 1 nm interval in a 0.0101 cm pathlength quartz Suprasil cuvette (Hellma Scientific) at 25 \({}^{\circ}\)C. Three individual scans were recorded for each sample: Pln149-PEP20 (0.73 mM) incubated in 10 mM sodium phosphate buffer (pH 7), or the peptide in 50% trifluoroethanol (TFE), in the presence of membrane models composed of 20 mM sodium dodecyl sulfate (SDS) or N-hexadecyl-N-N' dimethyl- 3-ammonia-1-propane-sulfonate (HPS), or in the presence of large unilamellar vesicles (LUVs) of 1-palmitoyl-2-oleoyl-phosphcholine (POPC), 1-palmitoyl-2-oleoyl-phosphoethanolamine (POPE), 1-palmitoyl-2-oleoyl-phospho-L-serine (POPS), and 1-palmitoyl-2-oleoyl-phosphoglycerol (POPG) at a 1/50 peptide-to-lipid molar ratio. Micelles and LUVs were prepared in sodium phosphate buffer (pH 7.0). In addition, the SRCD spectra of a partially dehydrated film deposited on the surface of a quartz glass plate were collected in the wavelength range of 280-155 nm at 25 \({}^{\circ}\)C, with successive rotations on the plate at 0\({}^{\circ}\), 90\({}^{\circ}\), 180\({}^{\circ}\), and 270\({}^{\circ}\).  
The oriented SRCD (o-SRCD) of Pln149-PEP20 in lipid bilayers deposited in a circular spot on the surface of a quartz glass Suprasil plate (Hellma Scientific) was measured from 280 nm to 155 nm at 1 nm intervals at 25 \({}^{\circ}\)C. Oriented bilayers composed of POPS and POPG were prepared as described by [PERSON] et al. [61]. The spectra of the bilayers were measured under the same conditions and subtracted from the corresponding sample. All SRCD/o-SRCD spectra were processed using CDToolX [62], by averaging the individual scans, subtracting the respective baseline spectrum, calibrating versus a camphorsulfonic acid standard, zeroing in the 263-270 nm region, smoothing with Savitzky-Golay, and scaling to delta epsilon (\(\Delta\varepsilon\)) units using a mean amino acid residue weight of 155.4 Da.
## 3 Biosynthesis of Aromatic and Isoprenic Precursors of Prenylquinones in Parasitic Protozoa
### Isoprenic Side Chain Biosynthesis
#### 3.2.1. Mevalonate Pathway  
Generalities about the Mevalonate Pathway  
The MVA pathway was the first isoprenoid synthesis pathway to be discovered and for many years was believed to be the only isoprenoid source in plants, fungi, archaebacteria, eubacteria, and some protozoa groups [45; 96; 99]. The MVA pathway begins with the condensation of two acetyl-CoA molecules for HMG formation) formation, a reaction catalyzed by the enzyme HMG-CoA synthase. Then, the enzyme HMG-CoA reductase catalyzes mevalonate formation, a reaction that can be inhibited by statins [97]. Finally, mevalonate is phosphorylated twice and decarboxylated to IPP [105]. However, in other organisms, such as _Thermoplasma acidophilum_, there are other MEV variants that use mevalonate 3-phosphate intermediates [69].  
The Mevalonate Pathway in Parasitic Protozoa  
Several _Leishmania_ species and _Trypanosoma_ possess enzymes of the mevalonate pathway. Experiments carried out by [PERSON] et al. showed that _T. brucei_ bloodstream forms synthesize 1-12 isoprene-unit dolichols, all of which were metabolically labeled by [3H] mevalonate. Similarly, _Leishmania_ tropica and _T. brucei_ synthesize the polyprenylated side chain of UQ via the MEV pathway [70; 71; 72]. The routes that allow the synthesis of isoprenoids in _E.__histolytica_ have not yet been identified; however, in _G.__lamblia_, one of the most closely related protozoans according to taxonomic group, the effects of inhibitors of the synthesis have been previously studied [106]. It was shown that the most widely used MVA pathway inhibitors for clinical applications, namely, mevastatin (also known as compactin or ML-236B) and mevinolin, affected trophozoite growth, an effect that could be reversed by the addition of mevalonate in the culture medium [106]. Even _Blastocystis_, _Acanthamoeba_ and some apicomplexan parasites, including _Toxoplasma_, _Cryptosporidium_ and _Plasmodium_, showed susceptibility to statins and apparent enzymatic capacity to metabolize MVA in protein extracts [76; 77; 84; 107; 108; 109].
# Asymmetry Propagation in a Pipe Flow Downstream of a 90\({}^{\circ}\) Sharp Sarp Elbow Bend
## 3 Results
### Asymmetry in Wall Shear Stress  
Wall shear stress (WSS) was used as the first criterium for estimation of the flow recovery length. WSS is defined as  
\[\tau(x,\theta)=\
u\left(\frac{\partial\overline{U}}{\partial r}\right)_{r=R} \tag{4}\]  
where \(x\), \(r\), and \(\theta\) are axial, radial and azimuthal coordinates in the pipe downstream of the pipe elbow, \(\overline{U}\) is the magnitude of the time-averaged velocity and \(R=D/2\) is the pipe radius. Figure 9 shows the calculated WSS at the pipe walls downstream of the exit of the sharp elbow. Location \(x=0\) corresponds to the outlet of the elbow, whereas azimuth \(\theta=180^{\circ}\) corresponds to the direction of the inlet pipe flow, i.e., direction \(z\) in Figure 2. It is evident that the WSS was much smaller for the transitional case than the other two turbulent cases. In the transitional case, the WSS gradually decreased along the axial (streamwise) direction, but it did not achieve a converged final value within the 100 D long domain. Contrarily, in the two turbulent cases, the converged final value of WSS was achieved at a distance of about 30-40 D and 20-30 D downstream of the elbow at the \(Re\) of 5600 and 10,000, respectively. In the flow-developing region, the WSS exhibited dependence not only in the axial coordinate but also in azimuth \(\theta\), i.e., at constant \(x=20D\), the WSS was smaller at \(\theta=0^{\circ}\) than at \(\theta=180^{\circ}\), which corresponds to the flow-impinging wall of the pipe. Furthermore, WSS exhibited strong dependence on \(Re\) with shorter recovery length at a larger \(Re\), which can be attributed to better mixing in highly turbulent flows.  
\begin{table}
\begin{tabular}{l c c c} \hline \hline
**Asymmetry Parameter \(\mathbf{\alpha}\)** & \(\mathbf{\alpha_{U}}\) & \(\mathbf{\alpha_{\sigma}}\) & \(\mathbf{\alpha_{\omega}}\) \\ \hline
**Variable _fx,r,\(\mathbf{\theta}\)_**)** & \(\overline{U_{x}}\) & \(\overline{u_{x}}^{2}\) & \(\overline{\|\omega\|}\) \\
**Normalization N** & \(\mathcal{U}_{b}\)\(R\) & \(\mathcal{U}_{b}^{2}\)\(R\) & \(\mathcal{U}_{b}\) \\ \hline \hline \end{tabular}
\end{table}
Table 3: The introduced asymmetry parameters for different flow variables \(f\) in Equation (3).
## 2 Drawbacks and Deficiencies of Benchmark Fiber Non-Linearity Compensation Schemes
_IVSTF_--The deterministic IVSTF algorithm (or simply called V-non-linear equalization, V-NLE) was introduced to relax the complexity of DBP by eliminating the need for the SSF method which is computationally inefficient. The VSTF provides an analytical tool for representing the fiber non-linear effects by similarly constructing the inverse channel based on VSTF, where in contrast to DBP it depends on the number of spans in long-haul network and not on the fiber length. This occurs using non-linear Kernel functions and, similarly to DBP, the CD and fiber non-linearity are compensated in frequency and time domain, respectively. Typically, up to 2 nd order kernels are used to account for 2 nd order CD, above which does not significantly improve the system performance in single-channel CO-OFDM [12; 13; 45]. In Figure 2 below, we show the recent implementation of IVSTF for CO-OFDM [13] that is typically placed in a time domain before OFDM demodulation and performs non-linearity compensation per span in parallel processing. Such implementation offers significantly reduced complexity compared to FS-DBP and inherits some of the features of the hybrid time-and-frequency domain implementation, such as non-frequency aliasing and simple implementation.
# FPGA Applied to Latency Reduction for the Tactile Internet
## 1 Introduction
Thus, this work makes the following contributions:  
* A new discrete reference model for a tactile internet system. * The novel reference architecture for hardware design on FPGA for tactile master and slave devices. * A new reference architecture for forward and inverse kinematics on FPGA. * A new strategy to reduce the latency on tactile internet based on FPGA. * Comparison of performance of the proposed hardware model with other proposals in the literature. The remainder of this paper is organized as follows: Section 2 presents the related works in the literature; Section 3 introduces a new discrete reference model for a tactile internet system; Section 4 describes the PHANToM Omni robot used with master and slave device; Section 5 presents the simulated tactile internet model; Section 6 gives all detailed description of the reference hardware architectures proposed in this paper; Section 7 presents and analyzes the synthesis results obtained from the described implementation, including a comparison to other works; Section 8 presents the final considerations.
# Design of an Energy Harvester Based on a Rubber Bearing Floating Slab Track
## 3 Proposal of the Spherical Energy Harvester  
The disk energy harvester is the simplest type, being mainly composed of the piezoelectric layer in the middle and force transmission structures at both ends. The piezoelectric layer is made of piezoelectric ceramic (PZT-5H), while the force transmission structure is made of steel, and they are both wafer-shaped. The geometric dimensions of the disk energy harvester are shown in Figure 2.  
Here, \(d=0.3\) mm denotes the thickness of force transmission structures at both ends; \(D=2\) mm indicates the thickness of the piezoelectric layer; and \(\phi_{p}=32\) mm shows the diameter of the disk energy harvester.  
The cymbal energy harvester is one kind of energy harvester with better performance, mainly consisting of the piezoelectric element and metal caps on both sides, which are generally bonded by epoxy resin or anchored by bolts. The material used is consistent with that of the disk energy harvester, that is, PZT-5H is used for piezoelectric elements, and steel is used for metal caps.  
Due to the special structure of the metal cap, the axial load applied on the metal cap is converted and amplified into two components along the axial and radial directions of the piezoelectric layer, resulting in a larger voltage than that of the general disk energy harvester. The geometric dimensions of the cymbal energy harvester are shown in Figure 3[31].  
Here, \(t_{m}=0.3\) mm denotes the thickness of the metal cap; \(t_{p}=2\) mm indicates the thickness of the piezoelectric layer; \(\phi_{C}=22\) mm is the inner cavity bottom diameter; \(\phi_{d}=10\) mm is the inner cavity top diameter; \(d_{c}=2\) mm indicates the height of the inner cavity; and \(\phi=32\) mm denotes the diameter of cymbal energy harvester.  
The spherical energy harvester studied in this paper is composed of the piezoelectric layer and spherical shells at both ends. The piezoelectric layer is a circular sheet structure with a thickness of 2 mm and a diameter of 32 mm. The outer diameter of spherical shells at both ends is the same as that of piezoelectric layer, that is, 32 mm. The whole structure is shown in Figure 4. Similarly, the piezoelectric layer is made of PZT-5H, and the spherical shell is made of steel [34].  
Figure 3: Dimensions of the cymbal energy harvester.  
Figure 2: Dimensions of the disk energy harvester.  
The material parameters of PZT-5H and steel used for each energy harvester are shown in Tables 1 and 2 [8].
## 2 A New Approach for Optical Encoders
### Photodiode Readout Circuits of the Opto-ASIC  
In order to convert the photodiode current into voltage, transimpedance amplifiers were integrated inside the opto-ASIC. The photodiodes of the Gray code structure were read out in a differential mode, as can be seen in Figure 10. Therefore, all dark photodiodes (PDdark) of one ring were shorted, together as well as the bright photodiodes (PDbright). The output voltage of the transimpedance amplifiers of those two pairs was compared using a comparator and translated into a logical signal at once. The 10 bit positions of the spot were achieved by implementing ten similar circuit structures and were read out in parallel. A following digital block calculated the spot location and output the result via a serial interface.  
The simplified readout circuit of the segmented photodiode structure can be seen in Figure 11. In comparison to the Gray code structure, each of the 1024 photodiodes had to be read out separately to get the spot position. To overcome the limited chip array, speed, and the power consumption, 128 segmented photodiodes were connected to one read-out circuit consequently via a multiplexer structure, followed by a transimpedance amplifier and a comparator for a sequential selection. This yielded eight independent read-out blocks, which could be controlled and read out in parallel by the digital block. The threshold reference voltages of the comparator could be separately adjusted for each block, also allowing a compensation of the photodiode process variation. The comparator decisions of all eight blocks were connected to a digital logic block, which calculated the spot position.  
Figure 10: Read-out circuit of the Gray code structure (photodiode ring bit 1).  
Figure 9: Spot shape measured with log-scale HDRC® image sensor.