esa-sceva/satcom-chunk-collection huggingface dataset:
# Recovery of Polyphenols from Agri-Food By-Products: The Olive Oil and Winery Industries Cases
## 5 From Agri-Food Wastes to Polyphenols: Processing Techniques
### Recovery of Polyphenols by Adsorption Technologies
The adsorption process in the column was evaluated by modifying the system variables (polyphenols concentration, flux, and bed height). PS-DVB copolymers with different hydrophobicity, Sepabeads SP700, and Amberlite XAD16 HP were used. The increase in bed depth from 10 to 20 cm, increased the breaking point time (t\({}_{\text{b}}\)) from 19.6 to 25.6 min, resulting in higher removal efficiency of phenolic compounds. The maximum removal capacity (q\({}_{\text{Th}}\)) calculated by the Thomas model reached 98.3 mg g\({}^{-1}\) at a flow rate of 5 mL min\({}^{-1}\). [PERSON] et al. [132] developed and applied a procedure for the selection of the optimal adsorbent for phenolic compounds recovery from olive mill wastewaters. They compared four non-functionalized resins (Amberlite XAD16N, Optipore SD-2, Amberlite FPX66, Amberlite XAD761) and one ion-exchange resin (Amberlite IRA958 Cl). In the initial batch isotherm tests, best results were obtained by neutral resin XAD16N and the ion exchange resin IRA958 (used in OH' form), with phenolic sorption capacities of 81 and 48 mg g\({}^{-1}\) dry resin, respectively; and phenolic content in the desorbed product of 0.19 and 0.21 g g\({}^{-1}\) volatile solids, respectively. In continuous-flow adsorption/desorption tests, results indicated that at low (20%) breakpoint, XAD16N had a better performance (0.14 g g\({}^{-1}\) volatile solids), but at high (90%) breakpoint the two resins produce similar results in terms of both phenolic content (0.19-0.21 g g\({}^{-1}\) volatile solids) and antioxidant capacity (4.6-4.9 g ascorbic acid equivalent g\({}^{-1}\)). [PERSON] and [PERSON] [52] isolated valuable biophenols from olive mill wastewater, using the procedures of acidification, sedimentation, and membrane filtration (MF and UF). Adsorption of hydroxytyrosol, tyrosol, caffeic acid, oleuproein, and luteolin was investigated onto 16 commercial sorbents (Amberlite XAD-4, XAD-7 HP, XAD-761, XAD-16 nonionic, FPX-66, PVPP, Lewatit AF5, AF6, AF7, MonoPlus-M800, VP OC-1064-MDPH, VP OC-1600, MonoPlus-SP 112, K6387, CAL I and GAC) in a multi-compound model and natural olive mill wastewater. MIPs were also tested. AFs resins demonstrated the highest selectivity for hydroxytyrosol and tyrosol while the desorbed ratios were much higher for the MIPs [52]. In this context, the studies carried out to date show that the purification of polyphenol extracts by using polymeric resins is an interesting alternative, especially when applied after a previous separation/concentration stage by filtration through membranes.
###### Abstract  
The kinetic analysis of joint work and joint contribution provides practitioners with information regarding movement characteristics and strategies of any jump test that is undertaken. This study aimed to compare joint works and contributions, and performance metrics in the countermovement jump (CMJ), drop jump (DJ), and countermovement rebound jump CMRJ. Thirty-three participants completed 18 jumps across two testing sessions. Jump height and strategy-based metrics (time to take-off [TTTO], countermovement depth [CM depth], and ground contact time [GCT]) were measured. Two-way analysis of variance assessed systematic bias between jump types and test sessions (\(\alpha=0.05\)). Reliability was evaluated via intraclass correlation coefficient [ICC] and coefficient of variation [CV]. Jump height and strategy-based metrics demonstrated good to excellent reliability (ICC = 0.82-0.98) with moderate CV (\(\leq\)8.64%). Kinetic variables exhibited moderate to excellent reliability (ICC = 0.64-0.93) with poor to moderate CV (\(\leq\)25.04%). Moreover, apart from TTO (\(p\leq 0.027\), effect size [ES] = 0.49-0.62) that revealed significant differences between jump types, CM depth (\(p\leq 0.304\), ES = 0.27-0.32) and GCT (\(p\leq 0.324\), ES = 0.24) revealed nonsignificant trivial to small differences between three jumps in both sessions. Finally, the negative and positive hip and knee works, and positive ankle contribution measured in the CMRJ showed significant differences from the CMJ and DJ (\(p\leq 0.048,g\leq 0.71\)), with no significant difference observed in other kinetic variables between the three jump actions (\(p\geq 0.086\)). Given the consistent joint works and joint contributions between jump types, the findings suggest that practitioners can utilize the CMRJ as a viable alternative to CMJ and DJ tests, and the CMRJ test offers valuable insights into movement characteristics and training suggestions.  
force platforms; kinetics; motion capture; reliability; jump strategy +
Footnote †: journal:  
0000-0001-5000-0001-5000]J.J.J.
# Seismic Response Analysis of Buried Nuclear Power Plant Structures in Non-Bedrock Sites
## 1 Introduction
### Artificial Boundary and Seismic Input Method  
The viscous boundary is implemented by placing remotely fixed dampers at each degree of freedom on the artificial boundary. It has clear physical significance, is easy to implement, and performs stably under high-frequency conditions, meeting engineering accuracy requirements. As a result, it has been widely used in the analysis of complex engineering problems and has been adopted by some commercial finite element software programs.  
Artificial boundary conditions [39] simulate radiation damping in truncated infinite domains. Viscoelastic boundaries use parallel spring-dashpot systems. As shown in Figure 5, each boundary degree of freedom connects to a fixed remote end. Springs add stiffness constraints. This prevents the low-frequency drift instability seen in viscous boundaries.  
The mechanical properties of parallel spring-dashpot systems are defined as follows:  
\[\text{Normal Direction}:\ K_{BN}=\frac{1}{1+A}\cdot\frac{\lambda+2G}{r},C_{BN}= B\rho c_{p} \tag{1}\]  
\[\text{Tangential Direction}:\ K_{BT}=\frac{1}{1+A}\cdot\frac{G}{r},C_{BT}=B\rho c _{s} \tag{2}\]  
The viscoelastic boundary components are defined as follows:  
* \(K_{BN}\): Normal spring coefficient.
* \(K_{BT}\): Tangential spring coefficient.
* \(C_{BN}\): Normal damping coefficient.
* \(C_{BT}\): Tangential damping coefficient.
* \(\rho\): Medium density.
* \(A\), \(B\): Dimensionless empirical parameters (recommended values: 0.8 and 1.1).
* \(r\): Near-field structure characteristic length.  
Site-specific ground response analysis is combined with viscoelastic boundary conditions. Free-field seismic motions are converted into equivalent nodal loads on truncated boundary surfaces.
## 3 Field Testing Results on Performance
### Traction  
This testing was conducted at the Daxing Oil Transfer Station (Niufang Village, Daxing District, Beijing, China). When the inspection robot is moving in a horizontally placed pipeline, a pull meter is used to perform multiple drag tests. These tests expected to obtain that the robot could generate a traction force of about 2000 N during normal operation. Part of the testing results are presented in Figure 7.
# Comprehensive Survey on VLC in E-Healthcare: Channel Coding Schemes and Modulation Techniques
## 5 Integration of VLC in Healthcare Environments
The data from the multiparameter monitor of patients in intensive care units is transmitted via lighting LEDs and collected by healthcare personnel smartphones, as well as by devices connected to computers located in a monitoring center. Figure 3: A schematic diagram of VLC systems based on healthcare information and monitoring by different channel coding techniques.
# Practical Performance Analyses of 5G Sharing Voice Solution
## 5 Performance Analysis
### NSA Sharing VoLTE Performance Analysis
When the contractor 4G LTE UE calls the sharer 4G LTE UE, the difference in delay between the two solutions is 33 ms, which is due to one additional handover of the sharer 4G LTE UE. The 4G LTE UE to the 4G LTE UE, both from the contractor, has almost no difference in delay, as no handover is required for either solution. The setup delay of sharer networks is, overall, about 4 ms shorter than the contractor, which is mainly suspected to be caused by the geographical proximity of the core network and thus can be ignored. The mean opinion score (MOS) of VoLTE service under each UE is normal, and the average value of NSA UE MOS is about 4.10; the average 4G MOS is about 4.17. The following conclusion can be drawn: in the 5G NSA sharing stage, VoLTE is not much improved compared with 4G, all around 2.2-2.8 s. The contractor and the sharer have the same delay, and sharing brings no additional difference in experience. The back-to-home solution is slightly worse than the non-back-to-home solution in terms of delay, which is brought about by the additional handover, with the handover delay of a single-end UE being around 35 ms. In summary, in the 5G NSA sharing VoLTE service scenario, the non-back-to-home solution can reduce the call setup delay. Therefore, from the time delay perspective, it is recommended to use the non-back-to-home voice solution.
## 3 The Proposed Method to Set the Initial Value for SES  
In this method, the first six observations are still used for taking the weighted average. Based on the concept of the weighted average of past observations, the closer it gets to the first observation, the greater the weight and the farther (Table 1). Hence, \(F_{1}\) is assigned more weight (\(w_{1}\)) for \(y_{1}\) than for \(y_{2},\ldots,y_{6}\).  
Performing SES with the proposed method is achieved as follows:  
1. Let \(F_{1}=\left(\frac{6}{21}y_{1}+\frac{5}{21}y_{2}+\frac{4}{21}y_{3}+\frac{3}{21 }y_{4}+\frac{2}{21}y_{5}+\frac{1}{21}y_{6}\right)\), where \(\sum\limits_{t=1}^{6}w_{t}=1\).
2. Use Solver in Microsoft Excel to find the optimal value for \(\alpha\) while minimizing MSE.
3. Provide the initial forecasting value via \(F_{t+1}=\alpha y_{t}+(1-\alpha)F_{t}\).
4. Calculate the MSE.  
An example of using the Solver in Microsoft Excel is presented in Figure 1. The time series dataset of S1 is set with the initial value of Method 1, and the optimal smoothing value returned is \(\alpha=0.3689\), whereas the MSE value is 896,212.76.  
\begin{table}
\begin{tabular}{c c c} \hline \hline \(t\) & \(y_{t}\) & \(w_{t}\) \\ \hline
1 & \(y_{1}\) & 6/21 \\
2 & \(y_{2}\) & 5/21 \\
3 & \(y_{3}\) & 4/21 \\
4 & \(y_{4}\) & 3/21 \\
5 & \(y_{5}\) & 2/21 \\
6 & \(y_{6}\) & 1/21 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Assigning weights to the first six observations.
## 3 Watermarking in Tensor Domain  
To enhance the robustness for the color image watermarking scheme, this paper blends QDFT and TD to embed a watermark. QDFT considers the correlation among color image channels. Tensor decomposition fully utilizes the correlation among frequency components, and watermark is scattering on frequency components further by the decomposition, so tensor decomposition improves the robustness of the watermarking scheme. The scheme utilizes the overall characteristics of RGB three channels that provides better embedding performance than single-channel or each channel of a color image, the scheme is more appropriate for color image watermarking.  
QDFT can process the three channels of the color image as a whole instead of processing them individually, thus avoiding unnecessary distortion and utilizing the inherent correlations among the three channels of the color image. The three imaginary components \(C\), \(D\), and \(E\) also have a strong correlation. Hence, three components can be used to construct a tensor \(T\). Figure 9 shows three imaginary components \(C\), \(D\), and \(E\).  
Tucker decomposition can maintain the internal structural relationship of an image. The core tensor obtained by Tucker decomposition represents the main properties of each slice of the original tensor and reflects the correlation among the slices. The core tensor \(K\) is a compressed version of the original tensor \(T\). Figure 3 shows the Tucker decomposition flowchart.  
We can use the method in the article [19] to embed the watermark in the core tensor \(K\), the maximum value of the core tensor is located in the upper-left corner, in the \(K(1,1,1)\) position, as shown in Figure 3. The position is robust when the image has experienced various attacks. Therefore, we modify the \(K(1,1,1)\) coefficient to embed the watermark. Then, we show the three slices of the core tensor \(K\), which is shown in Figure 4. The brighter part in Figure 4 corresponds to a larger value of magnitude. It can be clearly seen that \(K(1,1,1)\) is larger than the other position.  
The above content briefly introduces the proposed watermarking scheme in this paper. The rest of this section is arranged as below. This section introduces three contents,  
Figure 3: Flowchart for Tucker decomposition.  
including correlation analysis among three imaginary components of QDFT, procedures of a watermark embedding, and procedures of watermark extraction.
# Privately Generated Key Pairs for Post Quantum Cryptography in a Distributed Network
## 5 Discussion and Future Work  
We presented a CRP-based mechanism enabling the generation and distribution of cryptographic public-private key pairs in a public network in which client devices never share private keys. However, the CA can still verify the legitimacy of public keys, thereby protecting the privacy of clients. We presented an efficient way to implement the protocols with standardized Crystals-Dilithium. A multi-factor authentication scheme was suggested to add a KEM protocol to equip the communicating parties with ephemeral keys for symmetrical cryptography. Examples of practical applications include the following:  
* Standard Credit Cards and SIM Cards: During the personalization process, a Crypto-Table can be seamlessly integrated into the non-volatile memory of the credit card. This approach requires no additional changes to the hardware infrastructure; however, an update to the embedded software is necessary.
* Enhanced Credit Cards and SIM Cards: For modified cards, the microcontroller can be equipped with a Physical Unclonable Function (PUF), for instance, SRAM- or RRAM-based PUF technology. During personalization, the Crypto-Table is generated from the PUF and transmitted to the Certificate Authority (CA), where it is integrated into the non-volatile memory of the card.
* Cryptocurrencies and Tokenless Blockchains: An effective implementation option for the protocol is to generate Crypto-Tables from encrypted files. In this model, the trusted party transmits the Crypto-Table directly to clients instead of distributing key pairs. That is how the user will not require any HSM or token for key generation.
* On-Demand Utilization: We propose utilizing both tokens and biometric authentication, alongside the Key Encapsulation Mechanism (KEM) protocol, to enhance security and user experience. This can be directly implemented in secure retailing, online transactions, authentications of users utilizing template-less biometry, verifications of users, and so on. As part of future work, we are preparing a step-by-step optimization of the protocol:  
1. Use of Johnson-Lindenstrauss protocol as the CRP mechanism for biometry. Such a method has the potential to enhance the one-wayness of the mechanism and entropy.
2. Formulation of Design of Experiment (DOE) for testing purposes to enhance the performance of the overall protocol.
3. Optimization of the correcting schemes to recover the same responses from the Crypto-Tables and roots of trust.
4. Development of real-case applications with commercial partners.
# River Discharge and Saltwater Intrusion Level Study of Yangtze River Estuary, China
## 2 Data and Methodology
### River Discharge  
The Yangtze River is the longest river in China, with a total length of 6380 km. Its catchment area measures 1.8 \(\times\) 106 km\({}^{2}\). Its annual mean freshwater discharge of 27,856 m\({}^{3}\)/s was obtained using measurements recorded from 1957 to 2015 at the Datong hydrological station. The discharge has been observed to have obvious seasonal changes (Figure 2). During the dry seasons each year (November to April) the discharge averages approximately 16,542 m\({}^{3}\)/s. The construction of the Three Gorges Dam redistributed the annual discharge into the middle and lower reaches of the Yangtze River. The Three Gorges Dam was built in 1994 and completed in 2009. As of the end of September 2006, the flood control capacity of the Three Gorges Reservoir began to play a role in the flood seasons. Therefore, the distribution of the yearly discharge into the middle and lower reaches of the Yangtze River was determined to have changed after 2006 (Table 1).  
The average annual discharge of Datong hydrological station from 2006 to 2015 was 10.6% lower than the average flow from 1957 to 2005. Also, the annual distribution rate of the discharge had decreased by 2.4%. The average annual runoff during dry seasons basically remained unchanged. However, the distribution rate of discharge had increased by 2.4%.  
In this study, a Pearson III (P-III) frequency curve was used to analyze the monthly river discharges documented at the Datong station spanning from 1957 to 2015 [7]. The statistical analysis results obtained for the 25%, 50%, and 75% frequency of river discharges were 18,112, 16,331 and 14,832 m\({}^{3}\)/s, respectively, during the dry seasons (Figure 3). The multi-year average of the river discharges was approximately 27,856 m\({}^{3}\)/s during the dry seasons, where the fitting curve displayed a variation coefficient (Cv) of 0.13, and a deviation coefficient (Cs) of 0.65.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Time**} & \multicolumn{2}{c}{**Flood Season**} & \multicolumn{2}{c}{**Dry Season**} \\ \cline{2-5}  & **Annual** & **Distribution Rate** & **Annual** & **Distribution Rate** \\  & **Discharge/(m\({}^{3}\)/s)** & **(\%)** & **Discharge/(m\({}^{3}\)/s)** & **(\%)** \\ \hline
1957–2005 & 39,799 & 70.64\% & 16,541 & 29.36\% \\
2006–2015 & 35,579 & 68.26\% & 16,543 & 31.74\% \\ \hline \hline \end{tabular}
\end{table}
Table 1: Annual discharge characteristics before and after the establishment of the Three Gorges Dam.  
Figure 2: Annual runoff distribution process of Datong hydrological station for 1957–2015 years.
## 2 Theoretical Model of the Cycloid Disc Loading
The single-tooth meshing is the most unfavorable type because only one tooth of the cycloid disc and one roller of the ring gear is meshing. The cycloid disc of the single-stage cycloid speed reducer (Figure 2) used in this paper has the following characteristics:  
- Input power: \(P_{\text{in}}\) = 5.5 kW;  
- Input number of revolutions: \(n_{\text{in}}\) = 1450 min\({}^{-1}\);  
- Gear ratio: \(u_{\text{r}}\) = 11;  
- Eccentricity \(e\) = 4 mm. Numerical and experimental analyses were performed for all three types of meshing and for three different loads: 50% of \(F_{\text{Nmax}}\), 100% of \(F_{\text{Nmax}}\), and 150% of \(F_{\text{Nmax}}\). The overload of 150% of \(F_{\text{Nmax}}\) is taken into account in cases of shock loads or increased friction loads due to decreased lubrication occurring during the cycloid drive operation. Based on Equation (1), the normal forces were calculated as a function of the driving angle from the moment the cycloid disc teeth entered the mesh up to the moment they exited the mesh. Until the cycloid disc teeth enter the mesh, the normal meshing force equals zero. This procedure was carried out for all three types of meshing: single-tooth, double-tooth, and triple-tooth meshing. Based on the obtained values for the normal force, an approximate function of the normal force was obtained by function fitting and used in the experimental and numerical analyses. Approximate functions of the normal force are given in Table 1.  
Based on the obtained functions given in Table 1, a diagram of the normal force was prepared. The diagram of the normal force \(F_{\text{n}}\) as a function of the driving angle \(\phi\) is shown in Figure 3.
## 5 Conclusions  
In this paper, a microscopic model was developed to characterize traffic behavior at a bottleneck and evaluate the performance under cyberattacks. This model was evaluated for CAVs on a 1 km circular road and compared with the state-of-the-art intelligent driver (ID) model. The results obtained show that the proposed model provides a realistic characterization of traffic at bottlenecks. In particular, the traffic flow is low in dense traffic (\(S/S^{\prime}=0.2\)) and increases as the density decreases (\(S/S^{\prime}=0.5\) and \(0.8\)), as expected. Conversely, the flow with the ID model is based on a constant \(\delta\) and the flow increases with \(\delta\), resulting in unrealistic traffic characterization. Further, the ID model produces large speed variations and thus high acceleration and deceleration. With the proposed model, the variations in speed and acceleration are small and decrease over time. Further, the traffic capacity is higher than with the ID model. These results indicate that the proposed model can be used to reduce vehicle emissions and thus pollution. In addition, it provides better efficiency as vehicles spend less time in a queue than with the ID model. The results obtained indicate that the proposed model produces larger traffic flows and variations when the cyberattack intensity is higher. Thus, it provides realistic traffic flow behavior under cyberattacks and thus can effectively manage the corresponding disruptions.  
The results given highlight the potential benefits of adopting the proposed model to manage traffic flow, particularly for CAVs. It can be used by transportation agencies and planners to predict behavior at bottlenecks to control traffic flow and improve road safety and efficiency. Further, it can be employed to develop adaptive traffic control systems to reduce congestion and improve flow. This model can be used as an alternative or to complement traditional traffic control techniques such as VSL to provide adaptive control based on CAV reaction time and distance headway.  
The proposed model is based on real traffic parameters but was not validated with empirical data due to the limited number of CAVs currently on the road. Future research will consider real-time data to investigate the effect of CAVs at bottlenecks in more detail.  
Conceptualization, F.A. and Z.H.K.; methodology, F.A.; software, F.A.; validation, F.A., Z.H.K., T.A.G., K.S.K. and A.B.A.; formal analysis, F.A.; investigation, F.A., Z.H.K., T.A.G., K.S.K. and A.B.A.; writing--original draft preparation, F.A.; writing--review and editing, F.A., Z.H.K., T.A.G., K.S.K. and A.B.A.; visualization, F.A., Z.H.K., T.A.G., K.S.K. and A.B.A.; funding acquisition, F.A., Z.H.K., T.A.G., K.S.K. and A.B.A. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The data presented in this study are available in [[https://doi.org/10.3](https://doi.org/10.3)]([https://doi.org/10.3](https://doi.org/10.3)) 390/s23239385 (accessed on 9 January 2025).  
The authors declare no conflicts of interest.