esa-sceva/satcom-chunk-collection huggingface dataset:
# FEM Analysis of Piezoelectric Resonator Polarization Process
## 2 Materials and Methods
### Boundary Conditions  
The boundary conditions correspond to the real polarization conditions. The resonator is held in its center by removable power supply leads. Thus, the Dirichlet boundary condition \(u_{x}=u_{y}=u_{z}=0\) is given on the bottom side at the mounting location, and the Dirichlet boundary condition \(u_{x}=u_{y}=0\) is given on the top side. At the top electrode, the transducer is not fixed in the thickness direction (z-axis) because the temporary power supplies are not ideally rigid. The transducer is not mechanically stressed during the polarization process, and the homogeneous Neumann condition \(\mathbf{T}\cdot\mathbf{n}=0\) is entered on the remaining edge.  
The wrap-around electrode is grounded, i.e., the electrical potential of the electrode is 0 V. A polarization voltage, the electric potential \(\varphi_{p}\) is applied to the top electrode. Homogeneous Neumann condition \(D_{N}=0\) is given on the remaining surface of the transducer (not covered by the electrodes). This boundary condition can be entered due to the fact that the permittivity of piezoelectric materials reaches orders of magnitude \(10^{2}\)-\(10^{3}\) times higher than the permittivity of air or silicone oil [23], in the bath of which the polarization takes place. At constant electric field strength, electrical induction is directly proportional to the magnitude of the permittivity. At the interface of two materials with significantly different permittivities, the electrical induction will be higher in the ratio of the permittivities in an environment with higher permittivity. The component of the electric induction vector perpendicular to the material interface (the normal component) will be negligible in such a case.
# Honey Therapy in Diabetic Foot Ulcers: A Promising Strategy for Effective Wound Healing
## 4 Honey's Antimicrobial Properties
### Non-Peroxide Antimicrobial Activity
#### 4.2.4 Bee Defensin-1 (Def-1)  
Bee-derived defensin-1 is an antibacterial peptide secreted in honey by the hypopharyngeal glands of honeybees [126, 127]. Def-1 acts in bees as an innate immune response against microbial and fungal pathogens [127]. Due to its ability to induce DNA, RNA, and protein synthesis inhibition, as well as to decrease the bacterial viability, Def-1 has a crucial role in wound treatment, especially in biofilm destruction [128]. Despite Def-1 being effective against Gram-positive bacteria [129], controversial results are still observed in Gram-negative bacteria [39], possibly because they are resistant to insect defensins [130]. In the early biofilm stage, Def-1 might prevent biofilm formation, impairing the bacterial adhesion or inhibiting the growth of attached cells, as well as altering the production of extracellular polymeric substances [39]. In the wound healing process, Def-1 also acts by stimulating matrix metalloproteinase-9 (MMP-9) secretion from keratinocytes, as well as by enhancing the migration of keratinocytes in vitro and favoring wound closure and re-epithelialization in vivo [126]. An in vitro study showed that Def-1, together with H\({}_{2}\)O\({}_{2}\), was involved in the rapid bactericidal activity against _B. subtilis_, _E. coli_, and _P. aeruginosa_ in Revamil honey [76]. Moreover, the neutralization of Def-1 reduced the honey's effectiveness in the killing of vancomycin-resistant _E. ficeum_, showing the bactericidal activity of Def-1 [79]. Despite this evidence, no correlation was found between the amount of Def-1 in honeydew honey and the bactericidal activity against _S. aureus_[68]. Different types of honey might present different Def-1 concentrations, since the amounts of bee gland secretion added to the honey may strongly vary [68, 76].
# A Novel Energy-Efficient Contention-Based MAC Protocol Used for OA-UWSN
## 4 OA-UWSN MAC Protocol Simulation Environment Settings
### Optical Properties of Underwater Channels
#### 4.1.1 Attenuation Effect of Water  
The incident light can be absorbed or scattered in water. The total effect of these two mechanisms is called attenuation, resulting from water molecules and atoms, biomass, and chemicals dissolved in seawater. Underwater, blue-green light attenuation at a wavelength of 450-530 nm is much smaller than other light wavebands, so blue-green light [25; 26] is generally assumed for underwater optical communication.  
\begin{table}
\begin{tabular}{c c} \hline
**Parameters** & **Value** \\ \hline Frame length & 2 s \\ Acoustic handshaking time & 0.4 s \\ Optical handshaking time & d \\ Acoustic bit rate & 10 kbps \\ Optical bit rate & 1 Mbps \\ \hline \end{tabular}
\end{table}
Table 1: Channel simulation parameters.  
Figure 4: Relationship between optical handshake success rate and optical handshake time.  
The total absorption coefficient of water can be expressed as the sum of the absorption coefficients of various substances in water, as shown in Equation (5):  
\[a(\lambda)=a_{w}(\lambda)+a_{ph}(\lambda)+a_{d}(\lambda)+a_{y}(\lambda). \tag{5}\]  
In Equation (5), \(a_{w}\) is the absorption coefficient of pure water, \(a_{ph}\) is the absorption coefficient of chlorophyll or phytoplankton, \(a_{d}\) is the absorption coefficient of nonpigment suspended particles, and \(a_{y}\) is the absorption coefficient of yellow substances.  
When light travels in water, the scattering effect causes the light to deviate from the original propagation direction. The scattering of light by water is caused by water itself, chlorophyll, and suspended particles [27]. The scattering coefficient is shown in Equation (6):  
\[b(\lambda)=b_{w}(\lambda)+b_{ph}(\lambda)+b_{d}(\lambda). \tag{6}\]  
In Equation (6), \(b_{w}\) is the scattering coefficient of pure water, \(b_{ph}\) is the scattering coefficient of chlorophyll or phytoplankton in water, and \(b_{d}\) is the scattering coefficient of nonpigmented suspended particles. The parameters in Equations (5) and (6) are all relative to the wavelength \(m^{-1}\) in units.
## 5 Field Test Configuration and Results
### Credibility Evaluation Results
#### 5.2.3 Results of Dynamics-Based Evaluation
In particular, the dynamics-based fidelity evaluation captured the various disturbances and vehicle dynamics characteristics encountered in real-world driving environments, demonstrating the potential of virtual-environment testing to replace real-world testing. Our integrated evaluation methodology can serve as a dependable validation framework during the development of ADSs and ADASs, ultimately helping address the technical limitations and social acceptance issues surrounding the commercialization of autonomous driving technologies.
# Value of Information Based Data Retrieval in UWSNs
## 5 Performance Measures, Simulation Setup and Results
### Performance Measures and Experiments
We define \(\Psi\) as the ratio of the score of the path planner schedule for visiting hot-spots \(S_{I}\) to the score of an expected perfect schedule to visit hot-spots \(S_{P}\). Let there be \(n\) sensor nodes and \(m\) hot-spots. Then, the score \(S_{I}\) & \(S_{P}\) are determined as  
\[S_{I}=\sum_{i=0}^{m-1}n-seq\#_{s_{i}}\text{, }S_{P}=\sum_{i=1}^{m-1}n-i \tag{27}\]  
where \(seq\#_{s_{i}}\) is the number at which a node is visited in the schedule of visitation given by a path planner. \(\Psi\) is, therefore, determined as  
\[\Psi=\frac{S_{I}}{S_{P}}=\frac{\sum_{i=0}^{m-1}n-seq\#_{s_{i}}}{\sum_{i=1}^{m- 1}n-i} \tag{28}\]  
The intuition behind urgency score \(\Psi\) can be understood by the following example. Assume that there is a sensor network with 8 sensor nodes \(\{s_{1},s_{2},s_{3},s_{4},s_{5},s_{6},s_{7},s_{8}\}\) and 3 hot-spots \(\{s_{3},s_{6},s_{7}\}\). Here \(n=8\) & \(m=3\). The hot-spots in sequence of their precedence are \([s_{6},s_{3},s_{7}]\), i.e., it is most urgent to visit \(s_{6}\) on priority, then \(s_{3}\) and then \(s_{7}\). The perfect visitation sequence should be \([s_{6},s_{3},s_{7},\ldots]\). Let there be a path-planner \(PP\) such that it gives us the following schedule of visitation \([s_{1},s_{3},s_{2},s_{6},s_{5},s_{7},s_{8},s_{4}]\). In this visitation sequence \(s_{6}\) has a \(seq\#_{s_{6}}=3\), \(s_{3}\) has \(seq\#_{s_{3}}=1\) while \(s_{7}\) has \(seq\#_{s_{7}}=5\). In a perfect visitation sequence \(s_{6}\) should have \(seq\#_{s_{6}}=0\), \(s_{3}\) should have \(seq\#_{s_{3}}=1\) while \(s_{7}\) should have \(seq\#_{s_{7}}=2\). We can now calculate \(S_{I}\) and \(S_{P}\) as \(S_{I}=(8-3)+(8-1)+(8-5)=15\) and \(S_{P}=(8-0)+(8-1)+(8-2)=21\). The smaller a \(seq\#_{s_{i}}\) is, the higher the difference \(n-seq\#_{s_{i}}\) will be and hence the greater the score. The urgency score for \(PP\) is \(\Psi=S_{I}/S_{P}=15/21=0.714\). Therefore, the complete list of measures that we use in this study for adjudication are Y\({}_{ACC}\), Y\({}_{L}\), \(T_{four}\), \(\Omega\), \(v_{HS_{L}}\), \(\tau_{HS}\) & \(\Psi\).
## 4 Discussion
### Upscalling from Sample Measurements to Field Scale  
Data from two large scale experimental sites are compared with our pore-scale data. On one hand, well loggings have been conducted on boreholes in Majorana chalks [9] to measure P waves velocities \(Vp\), resistivity of the reservoir and water that have been used to deduce formation factor \(F\). Additionally, porosity has been measured on small cores extracted from these boreholes, with the same method as us. On the other hand, two sinkholes are used as boreholes on either side of a tunnel, dug inside detrital limestone on the Causse du Larzac [62; 63]. P waves velocities \(Vp\), rock resistivity, density and water saturation have been measured. Formation factor \(F\) has been deduced from resistivity and porosity from density and water saturation. These three properties enable us to partly characterize the two reservoirs.  
The evolution of formation factor \(F\), porosity and P waves velocities \(Vp\) with depth in Majorca illustrate that formation factor \(F\) and P waves velocities \(Vp\) increase with decreasing porosity. This has also been observed on our pore-scale data, following well-known trends previously mentioned [46]. Then, large-scale properties compared with our dataset present some similarities and disparities (Figure 13). For a similar porosity, formation factors are on the same order of magnitude with very similar values. Data from Majorca experimental site are similar to Normandie data, which are both chalks; while Larzac data are similar to Euville data, which are both detrital limestones. However, for similar porosity, \(Vp\) from chalk are higher for large-scale measurements than for laboratory ones, and are then closer to the RHG and WTA curves [50; 51]. For detrital limestones, the same values of \(Vp\) occur for lower porosity.  
Consequently, electrical properties and calculations seem to be applicable to each scale. However, even if \(Vp\) measurements at large-scale are in the same order of magnitude than at pore-scale, and follow the known trends [46], correlations are not optimal. Acoustic measurements being usually correlated with microporosity proportion [27], disparities in \(Vp\) measurements are explained by the difficulty of taking into account microporosity at large-scale. This validates the importance of pore-scale study.
# Isometric Strength in Volleyball Players of Different Age: A Multidimensional Model
## 3 Results
\begin{table}
\begin{tabular}{c c c c} \hline
**Variable** & **U15 (Mean \(\pm\) SD)** & **U17 (Mean \(\pm\) SD)** & **U19 (Mean \(\pm\) SD)** & **U21 (Mean \(\pm\) SD)** \\ \hline HGR \(\mathrm{F}_{\mathrm{max}}\) (\(n\)) & 272.9 \(\pm\) 50.9 & 290.1 \(\pm\) 47.6 & 302.0 \(\pm\) 51.4 & 347.4 \(\pm\) 55.2 \\ HGR \(\mathrm{RFD}_{\mathrm{max}}\) (\(n\)/s) & 1819.1 \(\pm\) 438.6 & 1946.77 \(\pm\) 365.3 & 2072.1 \(\pm\) 385.4 & 2344.8 \(\pm\) 431.9 \\ HGL \(\mathrm{F}_{\mathrm{max}}\) (\(n\)) & 260.4 \(\pm\) 48.7 & 273.49 \(\pm\) 46.4 & 288.2 \(\pm\) 51.1 & 331.3 \(\pm\) 53.5 \\ HGL \(\mathrm{RFD}_{\mathrm{max}}\) (\(n\)/s) & 1700.5 \(\pm\) 427.9 & 1827.34 \(\pm\) 389.6 & 1914.2 \(\pm\) 409.4 & 2241.6 \(\pm\) 436.6 \\ LB \(\mathrm{F}_{\mathrm{max}}\) (\(n\)) & 766.8 \(\pm\) 133.1 & 845.18 \(\pm\) 143.3 & 865.4 \(\pm\) 144.5 & 978.9 \(\pm\) 167.2 \\ LB \(\mathrm{RFD}_{\mathrm{max}}\) (\(n\)/s) & 4713.2 \(\pm\) 1699.6 & 5836.19 \(\pm\) 1781.2 & 6054.8 \(\pm\) 1917.2 & 6769.5 \(\pm\) 1873.6 \\ AE \(\mathrm{F}_{\mathrm{max}}\) (\(n\)) & 2558.1 \(\pm\) 582.8 & 2825.24 \(\pm\) 582.1 & 2981.4 \(\pm\) 547.0 & 3337.9 \(\pm\) 647.6 \\ AE \(\mathrm{RFD}_{\mathrm{max}}\) (\(n\)/s) & 12196.7 \(\pm\) 3169.6 & 13776.27 \(\pm\) 2810.4 & 14514.9 \(\pm\) 2658.2 & 15824.6 \(\pm\) 3214.1 \\ \hline \end{tabular} Legend: HGR—isometric handgrip right; HGL—isometric handgrip left; LB—isometric lumbar extensors; AE—isometric ankle extensors; \(\mathrm{F}_{\mathrm{max}}\)—maximal force; \(\mathrm{RFD}_{\mathrm{max}}\)—maximal rate of force development.  
\end{table} 
Table 3: Descriptive statistics of female subjects’ isometric strength. \begin{table}
\begin{tabular}{c c c} \hline
**Sample** & **Male** & **Female** \\  & **(Mean \(\pm\) SD)** & **(Mean \(\pm\) SD)** \\ \hline U15 & 30.46 \(\pm\) 12.30 & 41.50 \(\pm\) 15.09 \\ U17 & 48.10 \(\pm\) 10.99 & 49.11 \(\pm\) 13.57 \\ U19 & 51.94 \(\pm\) 10.17 & 53.37 \(\pm\) 14.06 \\ U21 & 71.03 \(\pm\) 11.03 & 66.18 \(\pm\) 15.11 \\ \hline
**ANOVA** & F = 53.17 (\(p<\) 0.001) & F = 41.61 (\(p<\) 0.001) \\ \hline \end{tabular}
\end{table} 
Table 5: Descriptive statistics of all subject groups’ Scores with F values (ANOVA).
_Applied_  
_sciences_  
**Improving Nanofiber Membrane Characteristics and Membrane Distillation Performance of Heat-Pressed Membranes via Annealing Post-Treatment**  
**[PERSON], [PERSON], [PERSON] \({}^{\star}\), [PERSON] and [PERSON] \({}^{\star}\)**  
Centre for Technology in Water and Wastewater, School of Civil and Environmental Engineering, University of Technology Sydney (UTS), 15 Broadway, Ultimo NSW 2007, Australia; [EMAIL_ADDRESS] (M.Y.); [PERSON]ESS] (Y.C.W.); [PERSON](C.C.)  
\({}^{\star}\) Correspondence: [PERSON]] (L.D.T.); [PERSON]] (H.K.S.); Tel.: +61-2-9514-2652 (L.D.T.); +61-2-9514-2629 (H.K.S.)  
Academic Editor: [PERSON]  
Received: 16 December 2016; Accepted: 5 January 2017; Published: 12 January 2017  
**Abstract: Electrospun membranes are gaining interest for use in membrane distillation (MD) due to their high porosity and interconnected pore structure; however, they are still susceptible to wetting during MD operation because of their relatively low liquid entry pressure (LEP). In this study, post-treatment had been applied to improve the LEP, as well as its permeation and salt rejection efficiency. The post-treatment included two continuous procedures: heat-pressing and annealing. In this study, annealing was applied on the membranes that had been heat-pressed. It was found that annealing improved the MD performance as the average flux reached 35 L/m\({}^{2}\)-h or LMH (>10% improvement of the ones without annealing) while still maintaining 99.99% salt rejection. Further tests on LEP, contact angle, and pore size distribution explain the improvement due to annealing well. Fourier transform infrared spectroscopy and X-ray diffraction analyses of the membranes showed that there was an increase in the crystallinity of the polyvinylidene fluoride-_co_-hexafluoropropylene (PVDF-HFP) membrane; also, peaks indicating the \(\alpha\) phase of polyvinylidene fluoride (PVDF) became noticeable after annealing, indicating some \(\beta\) and amorphous states of polymer were converted into the \(\alpha\) phase. The changes were favorable for membrane distillation as the non-polar \(\alpha\) phase of PVDF reduces the dipolar attraction force between the membrane and water molecules, and the increase in crystallinity would result in higher thermal stability. The present results indicate the positive effect of the heat-press followed by an annealing post-treatment on the membrane characteristics and MD performance.**  
**Keywords: membrane distillation; post-treatment; annealing; PVDF-HFP; crystallinity**
# A QoS-Guaranteed and Congestion-Controlled SDN Routing Strategy for Smart Grid
## 3 Design of QCORS Algorithm  
In this section, we will elaborate on the proposed QCORS in detail. Generally, before the link congestion actually occurs, the traffic on the overloaded link should be transferred to the remaining free links to meet the different QoS requirements of the SG application and improve the link utilization. Based on this idea, QCORS predicts the link loads by analyzing the overall network status and then constructs the virtual uncongested topology. To make final routing decisions, a queueing model is first constructed and further solved by the Lyapunov optimization theory [37; 38]. The dynamic analysis of the congestion state not only helps solve the congestion problem of the network, but also guarantees the reliability of the application [39]. By QCORS, the whole network could be continuously re-scheduled according to the application priorities. A list of acronyms used throughout the paper is presented in Table 1.
# Conical Emission Induced by the Filamentation of Femtosecond Vortex Beams in Water
## 3 Results and Discussion
More importantly, in the interaction between the intense femtosecond laser pulses and condensed state matters, the OAM has nearly no effect on the generated phenomena, which can be attributed to several factors. Firstly, the number density of atoms/molecules in the condensed medium is high, and numerous plasmas are generated during the interaction. Consequently, the OAM carried by newly generated components in the supercontinuum is transferred to the electrons, atoms and molecules in the medium, leading to the depletion of the OAM [11; 12; 13]. Secondly, the angular momentum conservation is preserved in the optical parametric process like the optical parametric down-conversion [14], four-wave mixing [15], stimulated Raman scattering [40], high-harmonic generation [41], etc., leading to the fact that the newly generated spectral components carry the OAM, whereas, the photoionization, SPM and other nonlinear effects that occur during the femtosecond filamentation are non-optical parametric processes, in which the angular momentum conservation is broken. Consequently, during the filamentation of femtosecond vortex beams in condensed state matters like water, the newly generated spectral components do not carry the OAM; however, the supercontinuum induced by the femtosecond vortex beams in air possesses the OAM, which was confirmed by the interferometry [26]. Apart from the SPM, the four-wave mixing scheme may partly account for the supercontinuum generation in air, for the OAM can be transferred to the newly generated spectral components in the optical parametric processes. It seems that the density of the medium affects the mechanism of supercontinuum generation as well as the transfer of angular momentum during femtosecond filamentation. This interesting fact stimulates us to continue to study the interaction between the intense vortex beam and matter and thoroughly explore the transfer of angular momentum and the coupling of spin-orbital angular momentum during the interaction between high-intensity laser and matter.
# Voxel-Based Navigation: A Systematic Review of Techniques, Applications, and Challenges
## 2 Review Methodology
### Initial Search  
This review selected three data sources: Web of Science (www.isiknowledge.com, accessed on 25 June 2024) Scopus (www.scopus.com, accessed on 25 June 2024), and Google Scholar (www.scholar.google.com, accessed on 25 June 2024). The initial search was conducted using a core keyword (\"voxel\") to capture a wide range of the literature related to the research topic. We identified common themes and high-frequency terms by analyzing the search results, which were then used to optimize the keyword combinations. The optimized keywords mainly focused on the following research directions: \"voxel AND 3D mapping\", \"voxel AND pathfinding/navigation\", and \"voxel AND GIS AND routing\". This process effectively helped us focus on the latest research findings related to voxel technology and its applications, providing more precise references for future research. Using the abovementioned keywords and data sources, we initially obtained 157 relevant papers. These papers spanned multiple disciplines, including computer vision, computing, engineering, and geology, demonstrating the wide range of applications and developments of voxel technology in various fields.
# Temperature Condition Analysis for Freezing on Tunnel Lining Back Side According to Tunnel Length
## 4 Freezing Prediction of Minimum Air Temperature by Tunnel Length
### The Freezing Temperature at the Tunnel Entrance  
The standard Korean railway tunnel section and inside air temperature changes were applied to the numerical analysis to investigate the freezing conditions. The high-speed railway lines are mainly designed as double-track tunnels, and the inner cross-section is 11.0 m wide and 7.82 m high. When the mechanical properties of the rock surrounding the tunnel are normal, the tunnel structure is usually designed with a concrete lining (300 mm), a waterproofing membrane (1.2 mm), and shotcrete (80 mm), which are modeled as shown in Figure 13a. The previous research and experimental data were applied to the thermal properties of the tunnel structures, which are summarized in Table 2. The ground temperature at a depth of 5 m from the tunnel surface was set to 17.0 \({}^{\circ}\)C as a temperature boundary condition. A 24-h periodic function with the diurnal temperature range (DTR = 10.5 \({}^{\circ}\)C) was set for the temperature change inside the tunnel entrance. Assuming that the minimum temperature inside the tunnel lasts for 7 days, the temperature on the backside of the waterproofing membrane at the tunnel entrance was investigated.  
The results showed that the back of the tunnel waterproofing membrane temperature underwent repeated freezing and thawing due to the diurnal temperature range (DTR). The freeze-thawing was repeated when the minimum inside air temperature was \(-\)10.0 \({}^{\circ}\)C at the tunnel entrance. When the minimum temperature dropped to \(-\)10.2 \({}^{\circ}\)C, the back of the waterproofing membrane froze constantly without thawing after 146 h. It took 74 h to freeze the groundwater at the back of the waterproof membrane when the minimum inside air temperature was \(-\)11.0 \({}^{\circ}\)C.  
Figure 12: Hwaak Tunnel modeling and numerical analysis. (**a**) Hwaak Tunnel modeling and contour; (**b**) Comparison of measurement and numerical analysis data.
# Review of Studies on User Research Based on EEG and Eye Tracking
## 4 Application Scope  
EEG and eye-tracking technologies are used as physiological measurement techniques that can provide visual objective evidence of user preferences. They are helpful in understanding people's real thoughts, and are useful for user positioning, product design, and implementation and improvement of consumption strategies at the management level. They play a very important role in user research by compensating for the shortcomings of commonly used subjective measurement methods such as semantic differences (SD) and Likert scales in past research. The visualization results of Citespace on the research keywords are shown in Figure 7. The superiority of objective and visual data support provided by EEG and eye-tracking has been widely applied in measuring aesthetic preferences and emotional perception. Currently, it is mostly used for user research on industrial product appearance and usability performance, on digital interfaces as well as transportation, consumption, and other spatial environments. After further analysis, organization, and summarization, we divided the application scope into three main parts, as shown in Figure 8: industrial products, including human-computer interaction, appearance form, usability, and ease of use; digital interface, including information distribution area and interface elements; spatial environments, including public navigation systems, transportation systems, and consumer spaces.  
Figure 7: The visualization results of research keywords.