esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Processing and Extraction
### Other Alternative Methods of Extraction  
#### 3.6.1 Pressurized Liquid Extraction  
Pressurized liquid extraction (PLE) is one of the pressurized approaches, next to SFE. PLE may, however, be used to extract high- and medium-polarity substances, whereas SFE results in extracts rich in non-polar compounds, as supercritical CO2 is used as a solvent. Combining those two methods has the benefit of obtaining extracts containing compounds characterized by different polarities [137]. There are studies reporting the extraction of compounds from residues after SFE-CO2. [PERSON] et al. [138] studied PLE of compounds from black chokeberry pomace remaining after SFE-CO2. Water, ethanol and formic acid mixture was used as a solvent, a constant pressure was set at 10.3 MPa and variable conditions of temperature, ethanol and formic acid concentrations were examined. The optimum values were 165 \({}^{\circ}\)C, 46% ethanol and 1.8% formic acid, and resulted in response variables of 72.53% yield, 236.64 mg GAE/g extract TPC (Folin-Ciocalteu method), 4.346 mmol TE/g extract TEAC and 5.92 ug/mL as the EC50 value in a DPPH assay. [PERSON] et al. [139] also described PLE of chokeberry pomace residues after SFE-CO2. The procedure was performed at 70 \({}^{\circ}\)C, 10.3 MPa, using 96% ethanol or 100% acetone as a solvent and resulted in a 22.70% yield when ethanol was used and a 17.90% yield when acetone was used. Ethanol extract was characterized by a TPC of
# An Experimental Study of the Leakage Mechanism in Static Seals
## 3 Experimental Design for Sealing Surface Leak-Rate Measurement
### Experimental Implementation
#### 3.3.2 Effect of Sealing Device Working Conditions on Leak Rate  
In the experiment, the effects of the three working conditions, i.e., the contact load, fluid pressure, and apparent contact area of test piece No. 1 on the leak rate, were studied through single-factor comparison experiments. These three parameters were also the ones to be considered during the design of seals. The experimental parameters are shown in Table 2, with five levels of contact load, three levels of gas pressure, and two apparent contact surface sizes.  
As the surface topography of the test pieces would change under the contact load (plastic deformation), the experimental measurements with the 66.7 mm silicon wafer were performed first. During measurement, the contact load was increased in steps from 100 N to 500 N. For each contact load, the leak rate under an gas pressure of 0.1, 0.2, and 0.3 MPa was measured, followed by increasing the contact load for measurement, so that the total pressure on the contact surface was increased incrementally. After all measurements with the 66.7 mm silicon wafer were completed, it was replaced  
Figure 5: Fractal theory characterization of the sample sealing surface. (**a**) The logarithmic relationship between the structure function \(S(\beta)\) and the scale \(\beta\) obtained from one set of sample cross-sectional profile data. (**b**) The cross-sectional profile of sealing surface, and the blue line and the red line denote the fitted profile (AB model) and the measured profile (experiment data), respectively. (**c**) The fitted three-dimensional sealing surface.  
with a 33.3 mm silicon wafer, and leak rate measurements were continued with a contact load of 500 N and different gas pressures.
## 3 Materials and Methods  
The designed platform is a web application developed in accordance with the WCAG 2.1 standard [24]. Sighted students use a graphical user interface (GUI) with mouse and keyboard controls. On the other hand, visually impaired students have access to the platform using a keyboard and assistive technologies such as a screen reader and a speech synthesizer.  
All exercises on the platform are prepared by mathematics teachers in TeX format using LaTeX tags. Based on the developed exercises, HTML content is generated (using a previously prepared conversion tool), which includes images of mathematical formulas. The decision to present mathematical content in a graphical form was made due to the accurate display and scaling capabilities in various web browsers. For this reason, an alternative description is prepared for each mathematical formula in a semi-automatic way, which can then be read by a blind person using a screen reader. This gives the teacher the opportunity to change the description of the mathematical formula by including additional information about the structure of the formula, according to the level of experience of the student. Alternative descriptions for inexperienced students who have trouble understanding mathematical formulas can be much more detailed.  
In addition, such alternative descriptions can be read piece by piece by students using different screen renderers, which gives an easy way to navigate through the structure of the mathematical formula. The way of interacting with the platform is through an interface containing the following:  
* Multiple choice lists;
* Drop-down lists;
* Text fields/boxes to enter values.  
Moreover, all of the mentioned ways of interaction are available using a keyboard, and the blind student is notified (through the use of a screen reader) as to whether a particular list item is selected or not.  
As part of our study, we developed a method whose particular stages are illustrated in Figure 1. Each of the presented stages is described in detail below.
# Communication Network Standards for Smart Grid Infrastructures
## 2 Network Standards That Support Communication in Smart Grid Infrastructures
### Renewable Energy Generation  
Given the energy crisis, the depletion of natural resources, the destruction of the environment and the growing electricity demand the production of energy from renewable sources seems to be the only feasible solution to the upcoming energy crisis [38, 75, 76]. However, as such a solution is not based on quantifiable natural resources, it does not  
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Product and** & **Smart Grid** & **Physical** & **Communication** & **Market** & **General** \\
**Safety Standards** & **Standards** & **Interconnection** & **Information** & **Standards** \\ \hline  & IEC 60364-5-53 & & IEC 61850 & & ISO/CD 12405 \\  & IEC 60364-5-55 & IEC 60309 Ed. 4.1 & IEC 61968 & & ISO 6469-1,2,3 \\ IEC 61982-1,2,3,4,5 & IEC 603064-7-712 & IEC 60309-1 Ed 4.1 & IEC 61851-31 & & SAE J1772 \\ IEC 62576 & IEC 60364-7-722 & IEC 60309-2 Ed 4.1 & IEC 61851-32 & & IEC/TR 62325-501 & SAE J2836/1-3 \\ IEC/NWIP 62619 & IEC/NP & IEC 62196 Ed, 1,0 & ISO/IEC 15118 & & SAE J2847/1-3 \\  & 60364-7-760 & IEC 62196-1 & ISO/IEC & & USA-SAE J1771 \\  & IEEE P2030.1 & & 15118-1,2,3 & & USA-SAE J2836 \\ \hline \end{tabular}
\end{table}
Table 1: E-mobility Standards.  
provide a solid basis for planning and leads to performance uncertainty, which in turn creates many and diverse challenges [77, 78].  
Smart Grids, in terms of their interconnection with renewable energy sources, are facing various operational issues per sector of operation such as:  
1. Wind energy (control, certification, wind-generator design requirements, measurement, and evaluation of generated energy, etc.).
2. Solar energy (testing, certification, interconnection, protection of photovoltaic systems, measurement, and evaluation of produced energy, etc.).
3. Marine power (design requirements for marine energy systems, wave performance evaluation, energy converters, etc.).
4. Fuel cells (safety of fuel cell power generation systems, fuel efficiency and testing, etc.).
5. Pumped storage (hydraulic turbine tests, storage pumps, etc.).  
Overall, given the tremendous development of the sector and its standardization process, we can conclude that smart grids include technical standards that enable the interconnection of different scale systems as well the procedures of testing, maintenance, and management of these systems as shown in Table 2. Although wired communications are adequately supported, it is recognized that most telecommunication solutions are provided through wireless systems [7, 38].
## 3 Results  
A total of 60 individuals (\(n\) = 60) were initially assessed for eligibility. After applying the inclusion and exclusion criteria, seven individuals (\(n\) = 7) were excluded due to a history of lower back (\(n\) = 4) and hip (\(n\) = 3) surgeries. This resulted in a final sample of 53 participants, comprising 15 asymptomatic individuals and 38 cases with LBP. Since each participant was assessed (1) on both sides, (2) with two measurements per side (3) taken by each of the two examiners, this process resulted in a total of 120 images for the 15 asymptomatic participants and 304 images for the 38 participants with LBP. Overall, 424 images were collected and analyzed in the study. For the subjects with LBP, the measurement was classified by side into symptomatic and non-symptomatic sides. For the asymptomatic control group, the dominant side was considered equivalent to the symptomatic side and the non-dominant side as equivalent to the non-symptomatic side. Table 1 contains the demographic and clinical information of the sample with LBP and the sample consisting of asymptomatic individuals. Demographic characteristics of the participants showed no significant differences between the groups in terms of the proportion of females (\(p\) = 0.609), age (\(p\) = 0.983), or height (\(p\) = 0.870). However, significant differences were observed in weight and body mass index (BMI), with higher values in the  
Figure 2: Hip flexion angle measurement using Kinovea software. LBP group (weight: \(p\) = 0.030; BMI: \(p\) = 0.017). Regarding the hip flexion angle during the SLR test, the participants with LBP exhibited significantly reduced mobility compared to the asymptomatic controls. The mean hip flexion angle was 61.9 \(\pm\) 13.7\({}^{\circ}\) in the LBP group and 82.2 \(\pm\) 10.2\({}^{\circ}\) in the control group, with a mean difference of 20.3\({}^{\circ}\) (\(p\) < 0.001). Similarly, significant reductions in the hip flexion angles were found for the symptomatic side (60.6 \(\pm\) 13.7\({}^{\circ}\) vs. 81.7 \(\pm\) 10.0\({}^{\circ}\); mean difference: 21.0\({}^{\circ}\); \(p\) < 0.001) and the non-symptomatic side (63.2 \(\pm\) 13.7\({}^{\circ}\) vs. 82.7 \(\pm\) 10.8\({}^{\circ}\); mean difference: 19.5\({}^{\circ}\); \(p\) < 0.001). The Shapiro-Wilk normality test for all continuous variables showed a \(p\) > 0.05, so normal distribution of the data could be assumed. The histograms of the hip flexion angle measurements including the normality curve are shown in Figure 3.  
The intra-examiner reliability estimates of Kinovea for hip flexion angle measurement during the SLR test are available in Table 2. Analyses were conducted separately for patients with LBP and asymptomatic controls and controlling the examiners' experience. The results indicated no significant differences between trials 1 and 2 for the novel examiner assessing patients with LBP (\(p\) = 0.716) and asymptomatic controls (\(p\) = 0.856). Similarly,
# Adaptive Global Fast Sliding Mode Control for Steer-by-Wire System Road Vehicles
## 5 AGFSMC Control Design
### Convergence Proof  
The Lyapunov function candidate is defined as:  
Figure 4: AGFSMC scheme framework. \[V_{3}=\frac{1}{2}J_{ek}s^{2}+\frac{1}{2}\widetilde{a}^{T}\Gamma^{-1}\widetilde{a}+ \frac{1}{2}\widetilde{\beta}_{1}{}^{2}, \tag{59}\]  
where \(\widetilde{a}(t)=\hat{a}(t)-a\) is the parameter estimation error, \(\widetilde{\beta}_{1}(t)=\hat{\beta}_{1}(t)-\beta_{1}\) is the adaptive gain convergence error, and \(\Gamma^{-1}\) is the inverse of gain matrix. The time derivative of Lyapunov function \(V_{3}\) in terms of the SbW system (Equation (14)) and the control input (Equation (50)), with the considerations that \(\dot{a}=0\), \(\dot{\beta}_{1}=0\), are obtained as follows:  
\[ \begin{array}{rl}\dot{V}_{3}&=sJ_{ek}\dot{s}+\dot{\widetilde{a}}^{T}\Gamma^{ -1}\widetilde{a}+\widetilde{\beta}_{1}\dot{\hat{\beta}}_{1}\\ &=s[-J_{ek}\dot{\widetilde{\xi}}_{r}-B_{ek}\dot{\xi}_{fw}-\tau_{Fk}-\tau_{ak}+ u]+\dot{a}^{T}\Gamma^{-1}\widetilde{a}+\widetilde{\beta}_{1}\dot{\hat{\beta}}_{1}\\ &=s[-J_{ek}\dot{\widetilde{\xi}}_{r}-B_{ek}\dot{\xi}_{fw}-\tau_{Fk}-\tau_{ak}- \mbox{sign}(s)(|\xi\tau_{Fk}|\\ &\quad+|\xi\tau_{ak}|)+u_{A}]+\dot{\widetilde{a}}^{T}\Gamma^{-1}\widetilde{a}+ \widetilde{\beta}_{1}\dot{\hat{\beta}}_{1}\\ &=s[-J_{ek}\dot{\widetilde{\xi}}_{r}-B_{ek}\dot{\xi}_{fw}+u_{A}]-(s\tau_{Fk}+ |s||\xi\tau_{Fk}|)\\ &\quad-(s\tau_{Fk}+|s||\xi\tau_{ak}|)+\dot{\widetilde{a}}^{T}\Gamma^{-1} \widetilde{a}+\widetilde{\beta}_{1}\dot{\hat{\beta}}_{1}\\ &\leq s[-J_{ek}\dot{\widetilde{\xi}}_{r}-B_{ek}\dot{\xi}_{fw}+u_{A}]-|s|(|\xi \tau_{Fk}|-|\tau_{Fk}|)\\ &\quad-|s|(|\xi\tau_{ak}|-|\tau_{ak}|)+\dot{\widetilde{a}}^{T}\Gamma^{-1} \widetilde{a}+\widetilde{\beta}_{1}\dot{\hat{\beta}}_{1}.\end{array}  \tag{60}\]  
It is considered that \(|\xi\tau_{Fk}|<\tau_{Fk}\) and \(|\xi\tau_{aFk}|<\tau_{ak}\), such that:  
\[|\xi\tau_{Fk}|-|\tau_{Fk}|=-\mathcal{F}|\mbox{sign}(\dot{\xi}_{fw})| \tag{61}\]  
\[|\xi\tau_{ak}|-|\tau_{ak}|=-\mathcal{T}\Bigg{(}|\dot{\xi}_{fw}|+\Bigg{|}\frac {\dot{y}+l_{f}\dot{\Psi}}{V_{x}}\Bigg{|}\Bigg{)}, \tag{62}\]  
where \(\mathcal{F}\) and \(\mathcal{T}\) are the uncertain residual parameters of frictional torque and self-aligning torque, respectively.
# Towards an Optimized Blockchain-Based Secure Medical Prescription-Management System
## 4 Implementation and Test of Blockchain-Based Prescription Management System
### Web Application  
The web application, or the front-end of our system, is the interface through which users can conveniently interact with smart contracts. The proposed system aims to ensure the principle of least privilege for all participants in the system. As already seen in the previous sections, three actors are involved in the system, namely admin, pharmacist, and patient.  
We have adopted the **Vue.js** framework for crafting our user interface. Vue.js stands as a versatile JavaScript framework known for its user-friendly nature, facilitating the creation of code that is both straightforward to learn and amenable to testing and upkeep. Within the Vue.js environment, the necessary libraries and ecosystems are readily available for constructing client-side business logic. The development process involves segmenting  
Figure 3: Implementation environment.  
a web page into modular components, each encapsulating its own set of HTML, CSS, and JavaScript code.  
Figure 3(b) provides an example of the authentication interface within our DApp. Serving as the initial interface, this page promptly materializes when a pre-registered user connects to the blockchain platform. To unlock access to the array of interfaces within the platform, the user is required to accurately input his/her wallet address along with the password dispatched to his/her designated email address.  
The \"add prescription\" function, illustrated in Figure 3(a), initiates the prescription's life cycle. It is important to note that only the pharmacist within the system has the authorization to create and update prescriptions.  
The web application offers comprehensive functionality across all of the platform's interfaces. Notably, these interfaces enable the administrator to register pharmacists and oversee the roster of authorized pharmaceuticals. Pharmacists are empowered to generate and revise prescriptions, as well as to enroll patients. Furthermore, patients gain the ability to access their medical prescriptions at any given moment and maintain a record of their medical history. The DApp adheres to robust security measures to safeguard patient and prescription data. Patient confidentiality and data protection are prioritized, instilling trust among all stakeholders. Through its innovative approach, this DApp contributes to an efficient and patient-centric healthcare ecosystem, benefiting pharmacists, patients, and healthcare providers alike.
## 3 Results and Discussion
### Data Fusion Performance  
The above section shows that the feature subset selected by the mRMR has achieved an efficient effect. Here, we further study the issue of whether the feature data fusion with entropy weight improves the dataset quality.  
The proposed method with an entropy weight fusion mechanism and the other contrasting method without fusion are adopted for testing and comparing, respectively. They both use the original 630 group data as the input, while the mRMR step is carried out subsequently. Afterward, the two processes are executed and tested on each of the 270 groups. The corresponding results are displayed in Figure 12.  
In this part, the average validation indicator root-mean-square error (RMSE) and confidence interval are used for observation. We notice that in the two figures, the RMSE of the four SVMs after entropy weight data fusion decreased by about 25% compared with the unfused data. More obviously, the fluctuation of all RMSEs decrease, especially the confidence interval of the FA-ISSA-SVM, which approaches zero, which could be almost ignored. The reason is that the advantage of the entropy weight data fusion adopted in this paper lies in the dynamic allocation of the fusion weights according to the difference between the original information entropy and the conditional information entropy, which can achieve the optimal effect of minimum error fluctuation in the global data fusion.
## 2 Design Methods
### Construction of 1:5-Scaled IBS Components
#### 2.2.3. Design Process of Corbel and the Steel Bolts  
Design of Full-Scale Corbel  
The corbel of the steel-bolt-connected IBS structure is well designed using Eurocode 2 guidelines. Axial force, \(\mathrm{N_{Ed}}=651\) kN. Concrete strut  
d = 500 - 40 = 460 mm  
a\({}_{\mathrm{H}}\) = 40 mm  
a\({}_{\mathrm{C}}\) = 150 mm  
a\({}^{\prime}\) = a\({}_{\mathrm{C}}\) + 0.2 \(\times\) a\({}_{\mathrm{H}}\)  
a\({}^{\prime}\) = 150 + 0.2 \(\times\) 40 = 158  
\[\frac{a^{\prime}}{d}=\frac{158}{460}=0.343\]  
\[f_{cd}=0.34\ \biggl{(}1-\frac{f_{ck}}{250}\biggr{)}f_{ck}=0.34\biggl{(}1-\frac{30 }{250}\biggr{)}*30=8.98\ \mathrm{N/mm^{2}}\]  
\[\frac{F_{Ed}}{b_{w}*d*f_{cd}}=\frac{651}{500*460*8.98}=0.315\]  
Hence, from Table 7 ([PERSON], 2010), \(\theta=58^{\circ}\)  
\[\mathrm{z}=a^{\prime}\tan\theta=158*\tan 58^{\circ}=253\ \mathrm{mm}\]  
Main tension reinforcement  
\[\mathrm{F_{td}^{\prime}}=\mathrm{F_{Ed}}(\cot\theta+0.2)\]  
\[\mathrm{F_{td}^{\prime}}=651(\cot 58+0.2)=537\ \mathrm{kN}\]  
\[\mathrm{A_{s}},\ \mathrm{main}=\frac{537*10^{3}}{0.87t_{yk}}=\frac{537*10^{3}}{0.8 7*500}=1234.5\ \mathrm{mm^{2}}\]  
Provide = 4H20, \(\mathrm{A_{s}}=1257\ \mathrm{mm^{2}}\). Because \(\frac{\mathrm{a_{c}}}{\mathrm{h_{h}}}=\frac{150}{500}=0.3<0.5\), closed horizontal links will be provided. \[\mathrm{A_{s}}\mathrm{link}\geq\mathrm{k}*\mathrm{A_{s}},\ \mathrm{main}=0.5*1235=618\ \mathrm{mm^{2}}\]  
Provide 4H16, \(\mathrm{A_{s}}=804\ \mathrm{mm^{2}}\). Moreover, after designing the corbel, the design of column bolts using information presented by [PERSON] [52] is followed in the next section. Design of Steel Bolts  
The steel bolts of these IBS components were designed based on the method provided by [PERSON] [52]. The process is presented below. Axial force, \(\mathrm{N_{Ed}}=651\ \mathrm{kN}\)  
Materials:  
Characteristics strength of concrete, \(\mathrm{f_{ck}}=30\ \mathrm{N/mm^{2}}\)  
Characteristics strength of steel, \(\mathrm{f_{yk}}=500\ \mathrm{N/mm^{2}}\)  
Axial force, \(\mathrm{N_{Ed}}=651\ \mathrm{kN}\).
# Performance Analysis of a Vertical FSO Link with Energy Harvesting Strategy
## 4 Results and Discussions
In addition, solid lines represent the BER of the ideal channel with \(h=A_{o}\), i.e., assuming only the geometric loss; whereas the dashed lines include the adverse effect of the random medium, i.e., either solely turbulence or both turbulence and pointing error. These results, which are calculated from the expression (25) for the case of only considering turbulence-induced fading; and from (26) for the combined scenario with turbulence and pointing error, have been validated using Monte Carlo simulations. Note that BER curves for the ideal channel and the one associated to the turbulent channel with no pointing errors are identical for both \((\omega_{z}/r)\) ratios. In this figure, simulation (Monte Carlo) results are drawn with markers whereas theoretical results are drawn with either solid or dashed lines. In all cases, a perfect match is shown between the simulated results and those obtained from the derived expressions. From the aforementioned Figure 5, it can be seen that turbulence and pointing error affect the BER with different severity depending on the \(\omega_{z}/r\) ratio. As far as turbulence is concerned, it affects BER equally regardless of the ratio \(\omega_{z}/r\). However, as expected, pointing error causes a very severe degradation for lower \(\omega_{z}/r\) ratios. The figure shows that, for \((\omega_{z}/r)=3\), the SNR degradation caused by pointing errors is huge, on the order of 15 dB for a target BER of \(5\times 10^{-5}\), while for \((\omega_{z}/r)=10\), the degradation is nearly negligible. In fact, the BER curves considering turbulence and turbulence with pointing error almost overlap.
# Does Power Output at Critical Power Intensity Interchange between Cycling and Running?
## 2 Materials and Methods
### Cycling: 3-min All-Out Test  
To determine CP in cycling, the 3-min All-Out test was performed following the protocol applied in previous investigations [26; 27]. The cycling test was conducted outdoors, with identical weather conditions to the running test. All participants used their own bicycles. The rear wheel of each bicycle was removed and attached to a direct drive Tacx Flow Ergotrainer (Technische Industrie Tacx BV, Oogstgeest, Netherlands) with 11 speeds (11-28 tooth). Triathletes first performed a warm-up at 100 W, followed by 5 min of rest. The test started with 3 min of unloaded baseline pedaling at each subject's preferred cadence, followed by an all-out 3-min effort. Subjects were asked to increase their cadence to approximately 110 rpm during the last 5 s of the baseline period. Strong verbal encouragement was provided throughout the test, although the subjects were not informed of the elapsed time, to prevent pacing. To ensure all-out effort, subjects were instructed to maintain their cadence to be as high as possible at all times throughout the test. CP was calculated as the average power output during the final 30 s [26; 27]. For the cycling test to be valid, the maximum peak power had to be reflected within the first 5 s of the start of the test. This was checked using the publicly available software Golden Cheetah (v 3.5, Cycling Power Analysis Software) and Microsoft Excel 2022 (Redmond, WA, USA).
# Enhancing the 3 GPP V2X Architecture with Information-Centric Networking
## 2 V2X Communications in 3 GPP  
The role of 3 GPP cellular networks in supporting V2X communications has been rapidly and steadily growing. Motivations for such an acceleration are manifold.  
**Available ubiquitous network infrastructure**. Unlike IEEE 802.11, the cellular technology can rely on an already deployed ubiquitous network infrastructure, which eases the implementation of C-V2X and may accelerate its deployment on a large scale. This makes C-V2X a cost-effective solution that will incur a little-to-none time-to-market, with Mobile Network Operators (MNOs) taking the lion's share.  
**5G-native ultra-low latency and high reliability support**. 3 GPP has a clear roadmap to provide _ultra reliable_ and _ultra-low latency_ communication (URLLC) in high-mobility environments through the 5G technology. URLLC is crucial for many V2X applications (e.g., fully autonomous driving, remote driving, and high-density vehicle platooning), which makes the automotive vertical an undoubted key driver for 5G systems.  
**Reuse of existing upper-layer protocols**. Since upper-layer protocols, such as message sets, and service and application layers, by ETSI, Society of Automotive Engineers (SAE) and other SDOs, have been specified to be _media-agnostic_, they can be easily reused by 3 GPP, whose main duty is then to focus on the access interface and network architecture specifications.