esa-sceva/satcom-chunk-collection huggingface dataset:
# The Antimicrobial Potential of Hexane Oils and Polyphenols-Rich Extracts from _Pistacia vera_ [PERSON].
## 4 Discussion
Pistachios contain several antioxidant compounds, including vitamin C (5.6 mg/100 g as total ascorbic acid), alpha and beta caroten (10 and 305 ug/100 g, respectively), lutein + zeaxanthin (2900 ug/100 g), alpha and gammatocopherol (2.9 and 20.4 mg/100 g, respectively) ([[https://fdc.nal.usda.gov/fdc-app.html#/food-details/170184/nutrients](https://fdc.nal.usda.gov/fdc-app.html#/food-details/170184/nutrients)]([https://fdc.nal.usda.gov/fdc-app.html#/food-details/170184/nutrients](https://fdc.nal.usda.gov/fdc-app.html#/food-details/170184/nutrients)), accessed on 5 March 2022). The synergistic combination of these antioxidant compounds, as well as the identified polyphenols (Table 1) in the pistachio oils may be responsible for the observed antimicrobial action against the tested Gram-positive bacteria. Polyphenol compounds promote several benefits including the antimicrobial one [14,15]. The antimicrobial action of phenolic compounds can be due to different mechanisms, including the interaction with bacterial cell wall protein and fimbria which damages the cytoplasmic membrane, the inhibition of the energy metabolism and the inhibition of the synthesis of nucleic acids [14,16,17]. The main identified polyphenols in the pistachio extracts were hydroxybenzoic acids (as gallic), flavan-3-ols (as (+)-catechin), anthocyanins (as cyanidin 3-O-galactoside) and flavonoids (as issoquercetin). The bactericidal action of gallic acid is due to the increase in fluidity of both the outer and the inner bacterial membrane, disturbing the membrane potential [17,18]. The catechin antimicrobial activity is promoted by its hydrogen peroxide generation [19], which damages the bacterial cell membrane [20]. Cyanidin-3-O-galactoside acts also on the cytoplasmic membrane by adding phenolic groups to the lipid bilayer of cell membranes, causing an alteration of their structure, function and permeability [21]. The antimicrobial mechanism of isoquercetin, which has been observed on _E. coli_, is due to lipid oxidation causing membrane damage [22]. However, it has been shown that mixes of polyphenols, such as these extracts, have a higher antimicrobial activity than single compounds [23]. In this study, the inhibitory effect of pistachio polyphenols against _L. monocytogenes_ has been reported. This microorganism is responsible for causing the listeriosis. This infection is one of the most serious and important foodborne diseases, given the severity of its sequelae and the high fatality rate (20% and 30%) [24]. In humans, the 99% of _Listeria_ infections are foodborne [25,26]. These results, in line with previous studies, show that pistachio phytochemicals could be used in several biotechnological application. Alone, or in association with known antimicrobial agents, they could be a starting point for the development of novel formulations or topical agents. In combination with other preservatives, its phytochemicals could be used in the food industry to promote microbial stability and safety in foods [27].
## 2 Methods
### Block-Based PSInSAR Processing
#### 2.2.2 Block-Based PSInSAR Parameter Calculation  
Once the candidate point set has been optimized, each sub-block independently performs PSInSAR parameter calculations [11; 36]. The core process includes constructing the adjacency network, selecting reference points, performing a weighted least squares adjustment, and iterative optimization. First, an initial adjacency network is constructed based on the spatial distribution of candidate points, connecting candidate point pairs whose spatial distance is smaller than a preset threshold (default is 1 km) to suppress the phase noise introduced by atmospheric decorrelation in long baseline arc segments. Furthermore, arc segments are screened using overall coherence, retaining highly reliable connections to form the largest connected subnetwork. To ensure automated processing, the reference point selection strategy uses the candidate point with the minimum amplitude deviation within the sub-block. Based on this reference point [37], the deformation rate and elevation residuals are jointly solved using a weighted least squares adjustment. The weight design assigns a greater contribution to highly coherent arc segments, thus improving the robustness of the calculation results. Finally, the deformation rate field and elevation residual field of the sub-block are output as independent solving units for global stitching. To further improve the accuracy, the residual phase can undergo spatiotemporal filtering to separate nonlinear deformation components from the atmospheric phase, and the deformation model parameters can be iteratively updated. This process reduces the global \(O\big{(}N^{3}\big{)}\) complexity of traditional PSInSAR by converting it into multiple \(O\big{(}n^{3}\big{)}\) (where \(n\ll N\)) subproblems, significantly reducing the computational burden.
# Performance Analysis of the Shore-to-Reef Atmospheric Continuous-Variable Quantum Key Distribution
## 6 Conclusions  
In this paper, based on Mie scattering theory and atmospheric CVQKD model, the effects of sea salt particles on atmospheric channel CVQKD protocol are analyzed. Considering the practical application, the transmission channel is divided into two parts: the shore-based atmospheric channel and the ocean atmospheric channel. We implement the numerical simulation under the scenario of fixed different channels respectively. Consequences demonstrate that the radius and relative humidity of sea salt particles correspond to the performance of CVQKD protocol. No matter which part of channel distance we choose to fix, the secret key rate will decrease when the unfixed channel distance is increased. Simultaneously, with the increase of particle radius and relative humidity, the secret key rate also shows a downward trend. The results of this paper could lay a solid foundation for the establishment of shore-to-reef atmospheric CVQKD model and thus provide a basis for evaluating the performance of ocean atmospheric CVQKD protocol.  
Conceptualization, methodology, analysis, writing--review, and editing: S.Z., C.X., C.Z., X.W., J.Y., H.Z., W.B.  
This research was funded by the National Nature Science Foundation of China grant number 61505261.  
The author declares no conflicts of interest.  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l} QKD & Quantum key distribution \\ CVQKD & Continuous-variable quantum key distribution \\ EPR & Einstein-podolsky-Rosen \\ BS & Beam splitter \\ \end{tabular}
# Damage Detection Using Modal Rotational Mode Shapes Obtained with a Uniform Rate CSLDV Measurement
###### Abstract  
With the rapid development of a continuously scanning laser Doppler vibrometer (CSLDV) technique, the full-field mode shapes of structures with high accuracy can be obtained. In this paper, a novel damage detection method using modal rotational mode shapes obtained with a uniform rate CSLDV measurement is proposed. The modal rotational damage indicators considering the changes of modal rotational mode shapes between the damaged and the undamaged states are established. Because the modal rotational mode shapes are obtained through the derivative of the detailed displacement mode shapes of transitional degree-of-freedoms (DOFs) with respect to the orthogonal directions, they are more sensitive than the normal displacement mode shapes. The uniform rate CSLDV measurement is essentially a uniform straight-line scanning technique and the measured mode shapes can be directly obtained through the demodulation of vibration signals. Besides, taking it for granted that a priori knowledge of the undamaged structure is not known, the undamaged mode shapes can be reconstructed from the measured damaged data using the fitted polynomial functions in which the minimum number of polynomial function coefficients are determined by a fit value threshold. The proposed method is firstly demonstrated by numerical simulation of the crack plate and then a plate structure with three damaged cases is taken as an example for further experimental study. The experimental results indicate the following: (1) The uniform rate CSLDV measurement can obtain the high accuracy modal rotational mode shapes with the advantage of eliminating the contaminated noise in the measurement; (2) the modal rotational damage indicators of the torsional modes are the most sensitive to the crack damage and they can clearly identify single, multiple damages and locations of the plate, and even slight crack damage, respectively. The effectiveness of the method paves the way for practical applications, such as ultra-light or composite structures.  
damage detection; modal rotational mode shape; modal rotational damage indicator; a uniform rate CSLDV; the fitted polynomial functions; ODS +
Footnote †: journal: Applied Soft. 2019, 9, 4982; doi:10.3390/app9234982
## 5 Experiment and Verification  
### Verifying the Construction of the Platform  
Based on Xilinx's XCZU3 EG-SBVA484 MPSoC with 2 GB LPDDR4 off-chip memory, a computing power platform, Ultra96-V2, was constructed to validate the integrated implementation of neural network training and inference. The PS within the MPSoC integrates an Arm quad-core Cortex-A53 Application Processing Unit (APU) and an Arm dual-core Cortex-R5F real-time processing Unit (RPU), and the PL integrates 7.6 MB Block RAM and 360 digital signal processing module DSP48E, including rich logic resources.  
As shown in Figure 10, the entire convolutional neural network training and inference system is built in MPSoC based on IP core encapsulation and reuse techniques. The IP core for network training and inference is connected to the PS of the SoC through the AXI specification. The IP kernel of each module functions as follows:  
1. The training and inference module is used to conduct a large number of computational processes of convolutional neural network training and forward inference;
2. The Zynq Ultrascale+ MPSoC module is a PS mapping within MPSoC;
3. The AXI Interconnect module connects multiple AXI memory-mapped master devices to multiple memory-mapped slave devices through the switch structure, which is mainly used as the bridge connecting S_AXI peripheral;
4. The AXI SmartConnect module is used to connect AXI peripherals to PS, mainly as a bridge connecting M_AXI in this structure;
5. The process system reset module is used to generate reset signals for PS and the other three modules.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Index** & **BRAM\_18K** & **DSP48E** & **FF** & **LUT** \\ \hline Total & 27 & 103 & 17,443 & 28,787 \\ Utilization (\%) & 2 & 28 & 12 & 40 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Details about IP nuclear resource usage for LeNet-2.22.  
After synthesizing and implementing the overall structure of the image recognition system given in Figure 10, the logical resources of the PL used by the two network models are shown in Table 3.  
According to the power analysis tool integrated into Vivado, the total power consumption of the LeNet-3.3 image recognition voxel system is only 2.652 W, while the power consumption of the PL used for training and inference of the convolutional neural network is only 0.387 W. The total power consumption of the LeNet-2.22 image recognition voxel system is only 2.457 W, while the PL power consumption for training and inference of the convolutional neural network is only 0.217 W.
# Throughput and Packet Loss Probability Analysis of Long Range Wide Area Network
## 4 Performance Evaluation  
For performance evaluation, we employ the EU (863-870 MHz) standard which has been mostly studied. In Table 2, various transmission options from 1 to 7 used in the EU standard are shown including spreading factor, bandwidth, coding rate, and frame payload size. Combining these parameter sets and (1) results in ToA values, which are calculated in the rightmost column in this table. It is noted that frame payload size is set to the maximum size available defined in the EU standard. We set \(T_{U}\) as 30 s, and the length of the receive delay 1 as 1 second. We assume \(N\) EDs associated with a GW. The geographical position of each ED is randomly determined within the maximum transmission radius of a GW. SF of an ED is determined according to SINR of the ED based on the distance between the ED and the fading channel gain. \(A_{i},i\in(1,7)\) denotes the set with nodes using the transmission option \(i\) in Table 2. \(A_{All}\) denotes the set of all nodes in a network and is expressed as \(\cup_{i}A_{i}\).  
Figure 2 shows the normalized throughput for \(A_{i}\) and \(A_{All}\). Here, the normalized throughput for \(A_{x}\) is the average throughput of EDs in \(A_{x}\) which is obtained by the sum of the throughput of all EDs in \(A_{x}\) divided by the cardinality of \(A_{x}\). The result shows that the analysis result coincides with the simulation result. As the number of EDs in a GW increases, traffic load increases accordingly, which results in the increase of the normalized throughput at the initial phase for each region \(A_{i}\). However, the normalized throughput decreases gradually after it reaches its peak performance because of increased packet collisions and packet retransmissions. We can see that the peak value of the throughput is reached quickly as the length of ToA increases.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**No** & **SF** & **BW (kHz)** & CR & \(FRM_{pl}\) (Bytes) & _ToA_ (Sec) \\ \hline
1 & 7 & 250 & 4/5 & 242 & 0.199 \\
2 & 7 & 125 & 4/5 & 242 & 0.399 \\
3 & 8 & 125 & 4/5 & 242 & 0.707 \\
4 & 9 & 125 & 4/5 & 115 & 0.676 \\
5 & 10 & 125 & 4/5 & 51 & 0.698 \\
6 & 11 & 125 & 4/5 & 51 & 1.560 \\
7 & 12 & 125 & 4/5 & 51 & 2.793 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Transmission options in EU(863-870 MHz) standard.  
Figure 3 shows the packet loss probability of \(A_{i}\) and \(A_{All}\) as a function of \(N\). As the number of EDs in a GW increases, packet loss probability increases steadily because of increased packet collisions and packet retransmissions. We can see that the packet loss probability increases more rapidly as the length of ToA increases, and the overall packet loss probability \(A_{All}\) increases as the number of EDs in a GW increases.
## 3 Results
### Influence of Illumination with the White Light  
An influence of illumination with white light on transmission spectra was studied on unprocessed sample and samples with Au and etched grating of the period equal to 8 \(\upmu\)m. During the experiment, illumination of the sample was turned on for 15 min and then measurements started with the light on until the end of measurements. Results are presented in Figure 7. In general, illumination with white light leads to three effects: an increase of the amplitude of the signal, a broadening of the absorption line and--in the case of etched sample--a shift of the minimum of the transmission curve.  
The spectra of the sample with Au grating are practically the same as in the unprocessed sample. It is intersting to note, however, that the amplitude of the plasmonic resonance is bigger in proccessed than in unprocessed sample; we will discuss this point in the next section. The reaction of etched sample is quite different: the plasmonic shift is equal to about 0.18 T in the dark and to about 0.5 T after illumination. This shows that plasmonic resonances in etched samples are tuneable with white light--an effect which can potentially be used in tuneable detectors.  
We interpret the shifts of position of the resonance under illumination as resulting from the change of concentration of a 2 DEG which take part in plasmonic excitations. A shift to lower \(B\) indicates an increase of the frequency of plasmon (see Esquations (1) and (A1)) which can be attributed to an increase of concentration of the 2 DEG. This is consistent with an increase of concentration of the 2 DEG given by an analysis of magnetotransport data registered after illumination.  
Figure 7: Influence of illumination with white light on transmission spectra on unprocessed sample and samples with Au and etched grating of the period equal to 8 \(\upmu\)m. The wavelenght of radiation was 118.8 \(\upmu\)m. The vertical bar shows position of the CR in unprocessed sample.
# A Multi-Dimension Spatial Method for Topology Awareness and Multipath Generating
## 4 Multipath Generating
### Spatial Multipath Diversity  
We introduce some spatial mechanisms to characterize and improve multipath diversity. The relevant items and descriptions are listed in Table 2 referring to samples depicted in Figure 4a, where black circles denote coordinates of RSes. TD indicates the deterministic transmission trend so as to reduce aimless redirection and facilitate convergence. For instance, two paths 7\(\rightarrow\)5\(\rightarrow\)2\(\rightarrow\)9 and 7\(\rightarrow\)14\(\rightarrow\)15\(\rightarrow\)9 violate the principle of TD 7\(\rightarrow\)9 because hop 5\(\rightarrow\)2 reverses 7\(\rightarrow\)9, and hop 7\(\rightarrow\)14 diverges two much from 7\(\rightarrow\)9. TS constrains intermediate nodes to reduce search complexity and is constructed between two RSes with several criteria. The TS ABCD is a rectangle symmetric about 7-9. The TS ellipse EF contains the RS whose distance sum to 7 and 9 is smaller than a specific value, e.g.,1.5\(\times\)D(7,9). DA implies the direction difference of two links. Supposing that OMN is a triangle, according to the triangle geometric formula, \(2D_{OM}D_{ON}\cos\angle MON=D_{OM}^{2}+D_{ON}^{2}D_{MN}^{2}\); then, we get \(D_{MN}=\sqrt[2]{D_{OM}^{2}+D_{ON}^{2}D_{MN}^{2}-2D_{OM}D_{ON}\cos\angle MON}\). When \(D_{OM}\) and \(D_{ON}\) stay constant, \(\angle MON\) impacts \(D_{MN}\), i.e., within 0\({}^{\circ}\) to 180\({}^{\circ}\), bigger \(\angle MON\) brings bigger \(D_{MN}\). We adopt this geometry feature to characterize node diversity, so that, in Figure 4a, RS2 and RS12 would be more distant with bigger \(|\alpha|+|\beta|\) and thus links 7\(\rightarrow\)2 and 7\(\rightarrow\)12 would be with more difference, which we seem as link diversity.
# Finite-Time Tracking Control of a Flexible Link Manipulator Based on an Extended State Observer
Therefore, the research objective of this paper is to design an estimation method of unknown system parameters based on an adaptive ESO for FLM. Then, based on the above-estimated model parameters, an ANTSM controller based on ESO is designed to achieve finite-time tracking and vibration suppression of FLM. The parameter estimation method proposed in this paper can effectively estimate the unknown dynamic parameters of the FLM, which provides the necessary system knowledge for the controller design, especially the control gain, which provides a reference for engineers to design the FLM controller. At the same time, the proposed controller can achieve finite-time trajectory tracking and vibration suppression of FLM and improve the tracking accuracy and anti-interference ability of the system without the upper bound information of system uncertainty and external disturbance. It provides an effective robust controller design method for engineers and can be used for the controller design of various flexible robots. This paper is organized as follows. Section 2 gives the preliminaries and problem formulation. In Section 3, the design and stability analysis of the adaptive ESO are discussed. Then, an ANTSM controller based on ESO is proposed, and the stability is analyzed by Lyapunov theory. Section 4 shows the numerical simulation and experimental results of the FLM, which confirms the effectiveness of the proposed ANTSM controller based on the ESO. Finally, the conclusion is given in Section 5.
## 3 Results and Discussion  
### Optical Properties of Gala Apples at Different Depths  
The optical properties of the apples recovered by our frequency-domain DRS system at SDSs of 1 and 5 mm are displayed in Figure 3. The error bars indicating the standard deviation of five measurements for an apple are presented in the plots. Considering the computational error of ANN model and system stability, the maximal errors of \(\mu_{a}\) and \(\mu_{s}\)' recovered by our FDPM system were less than 10%. The impact of the errors that came from the system were relatively less compared to the impact of the deviation made from the individual character of each apple. At 1 mm SDS, our frequency-domain DRS system was sensitive to the property variation in the apple skin, whereas at 5 mm SDS, the system's probing volume mainly accounted for the apple outer flesh. The \(\mu_{a}\) recovered at 660 and 980 nm represented the absorption of chlorophyll and water in the apple tissues, respectively. The \(\mu_{s}\)' is related to the structural characteristics of apples; hence, it is potentially useful for estimating fruit firmness [18]. In Figure 3a, the \(\mu_{a}\) at 660 nm is much higher than that at 980 nm when measuring the optical properties at 1 mm SDS. This demonstrates that the absorption of chlorophyll was more significant than the absorption of water in the apple skin. In contrast to the optical properties recovered when the SDS is 5 mm, the \(\mu_{a}\) at 980 nm is higher than that at 660 nm. This demonstrates that the absorption of water was more significant than that of the chlorophyll in apple outer flesh. In Figure 3b, the \(\mu_{s}\)' at both wavelengths of 660 nm and 980 nm and SDS of 1 mm exceeds those at 5 mm, thus demonstrating that the firmness of apple skin is greater than the firmness of its outer flesh. Moreover, the error bar of the \(\mu_{a}\) is large at 660 nm at 1 mm; therefore, we speculate that the distribution of chlorophyll is uneven in apple skin. The optical parameters recovered at SDS 1 mm have contribution mainly from skin, and those recovered at 5 mm have contribution not only from flesh but also from skin, but flesh is more predominant than skin.