esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### Simulated Case Study
#### 3.1.2 Damage Detection and Quantification
When comparing the capacity to quantify damage (PI1 and PI2 in Figure 8), the transmissibility- and the OMA-based DSFs yield superior results, while the DSFs that are based on the energy distribution have a poor performance. This is due to the inevitable sensitivity of the energy distribution with respect to the spectral content of the GM. The good performance of the OMA-based DSFs originates from the fact that AVs have reduced variability in comparison with DSFs that are derived from GMs that are transient in nature and thus characterized by significant variability in the frequency domain (as observed in Figure 4, top right). In terms of damage detection potential, as reflected by PI3 and PI4 in Figure 8), we observe a trade-off between probability of false detection (PI3) and early detection of damage. This underlines the need for combining multiple DSFs when constructing robust damage identification schemes. As shown in Figure 8, DSFs that are derived from AVs have good overall performance (PAAC is the best DSF overall with respect to \(DI_{PA}\)) due to the reduced uncertainty from the GM signals. Transmissibility-based DSFs can be derived from both GMs and AV; Figure 9 contains a comparison of the respective values for all three DSFs that derive from changes in transmissibility: \(T_{cnt}\), \(T_{max}\), and \(TAC\) on the right. While the scatter is low for \(T_{cnt}\) (Figure 9 left) and the values are centered around the the diagonal, a noticeable scatter appears for \(T_{max}\) (Figure 9 center). The largest difference is found for the \(TAC\) (Figure 9 right), which is more sensitive when derived from GMs and picks up damage at earlier stages than when derived from post-earthquake AVs. Indeed, almost all values lie above the diagonal. This behavior derives from the fact that the temporary stiffness drops created by nonlinearity are more pronounced than permanent stiffness drops related to damage (see Figure 3 bottom right). The differentiation in DSFs derived from AVs versus those extracted during strong ground motions is further analyzed in Section 3.1.5. Figure 7: Evaluation of the correlation of the phase-angle-based feature, \(PAAC_{05,M1}\), derived from post-earthquake AVs, with respect to four EDPs: hysteretic work (**left**), maximum transient roof displacement (**center left**), \(DI_{PA}\) (**center right**), and residual stiffness drop (**right**). While a good correlation is observed with respect to hysteretic work and residual stiffness drop, the scatter undermines the quantification of damage that depends on maximum transient displacement. The small variance in the healthy reference distribution enables the detection of damage from early stages.
# Privacy and Security in Digital Health Contact-Tracing: A Narrative Review
## 3 Results
### Privacy
#### 3.1.2 Privacy Concerns
In another study, some participants believed that contact-tracing apps violated their privacy, while others had no concerns and considered them secure [25]. An experimental study in the USA detected no relationship between privacy and intention to download. The study revealed no differences in downloads based on privacy messaging. However, when privacy messaging described how the app kept individuals' data safe and secure, perceptions of data security increased, but privacy concerns did not [71]. Another study in the USA revealed that age and race influenced how people perceived contact-tracing apps and their privacy issues. Furthermore, respondents of Asian descent expressed lower privacy concerns regarding contact-tracing apps, whereas those identified as Black showed more privacy apprehensions [72]. In a German study, privacy concerns did not appear to be the primary factor influencing adoption decisions, with 13% of participants indicating that they were very concerned about privacy violations [73]. Respondents did not consistently prioritise privacy; instead, they preferred a balanced approach that combined human and digital elements in contact-tracing. Surprisingly, privacy concerns did not have as much impact on the choice of the digital app as anticipated in the United Kingdom. Trust in the National Health evice (NHS) was found to override privacy concerns for many respondents [74]. In China, the users' perception of privacy was positively associated with trust in government institutions [75]. A German study has reported that users' decisions were based on their privacy concerns and the advantages of the contact-tracing app, and their privacy behaviour was situational rather than static [76]. While privacy and security concerns may be significant factors in the initial adoption and use of the app, in the long term, these concerns faded. This shift could be facilitated by the absence of significant data breaches [77]. The expected continued use of the app after the pandemic had a statistically significant negative correlation with privacy concerns [78]. Privacy concerns reduce the likelihood of downloading, but some concerns may decrease over time [79]. However, it is important to note that while privacy concerns significantly impacted current actions and adoption intentions, their influence declined when considering future intentions [44].
# Ultrasound Localization Microscopy in Liquid Metal Flows
## 4 Test Case: Rayleigh-Benard Convection Experiment  
### Set-Up  
The convection cell for this study was designed at the magnetohydrodynamics lab at Helmholtz-Zentrum Dresden-Rossendorf (HZDR) [8]. The container had a square cross-section with a side length of \(L=200\,\mathrm{mm}\) and a height of \(H=66.6\,\mathrm{mm}\). This produced an aspect ratio of \(\Gamma=\
icefrac{{L}}{{H}}=3\). The fluid layer was located between two copper plates on the top and bottom of the cell, in which there was a network of channels that were connected to a temperature-controlled water circulation system. The strength of the thermal forcing is described using the dimensionless Rayleigh number \(R_{a}\).The thermal boundary conditions were controlled by thermostatic baths and the temperature gradient across the liquid metal layer was controlled by nine thermocouples in each plate. The side walls were made of electrical non-conductive polyvinyl chloride. The influence of heat loss and environmental temperature conditions was reduced by encasing the entire convection cell in \(30\,\mathrm{mm}\) insulating foam. The fluid vessel was filled with the eutectic alloy GaInSn as the model fluid. At room temperature, it had a density of \(6.44\,\mathrm{g/cm^{3}}\), a viscosity that was approx. three times lower than water \(3.4\times 10^{-7}\,\mathrm{m^{2}/s}\) and a thermal diffusivity of \(1.05\times 10^{-5}\,\mathrm{m^{2}/s}\). Accordingly, the Prandtl number was \(0.03\). The convection cell was placed between two electromagnetic coils to provide a horizontal magnetic field. The spatial inhomogeneity of the magnetic field was less than \(5\%\) at maximum strength [49]. Different flow patterns appeared in the liquid metal convection depending on the ratio between the Lorentz force and the viscosity, which was represented by the Chandrasekhar number \(Q\). The ultrasound array probe was placed upright with \(66\,\mathrm{mm}\) offset from the side. The measurement area of the probe was aligned perpendicularly to the magnetic field lines, as shown in Figure 4.  
Figure 3: Calibration of the localization uncertainty: (**a**) the set-up, in which the experiment dimensions and materials were replicated and a fiber that used as the scatterer was positioned inside the container; (**b**) the calibration result, in which the position of the scatterer was estimated and the uncertainty was derived using the reference position. The overall average was \(\overline{\
u}_{l}=188\,\mathrm{\SIUnitSymbolMicro m}\).
# Fire Activity and Fuel Consumption Dynamics in Sub-Saharan Africa
## 4 Results
### Annual and Seasonal Fire Dynamics
The peak fire season in the northern hemisphere extends between November and March which, as evident in the southern hemisphere, has large annual variations in monthly fuel consumption of 20-30% and typically display negative trends. Note that some SEVIRI data was  
Figure 1: **(a)** Annual estimates of Spinning Enhanced Visible and Infrared Imager (SEVIRI) fire radiative energy (FRE, Tj); **(b)** Moderate Resolution Imaging Spectroradiometer (MODIS) MCD64 burned area (Mha) and **(c)** Global Fire Emissions Database (GFED, version 4) fuel consumption (Tg, DM) in the northern and southern hemisphere Africa. A least-squares linear trend line is shown. Note that in 2013, three months of SEVIRI data (March, April and May) were unavailable which will have a greater impact in the northern hemisphere where fire activity is higher during these months. missing in 2004 (January) and 2013 (March, April, May). A noticeable feature in Figure 2b is that several months outside of the biomass burning season (e.g., November-March) have strong positive trends in fuel consumption albeit at low magnitudes, which may have implications for emissions mitigation schemes employing early season burning as fires at these times tend to be low intensity due to higher fuel moisture content and relative humidity [61]. [PERSON] et al., [62] found the modified combustion efficiency (MCE) to vary seasonally over southern African grassland and woodland, which can have a significant impact on the chemical composition of the smoke emissions although similar seasonality was not found by reference [63] in Australian savanna fires. In the northern hemisphere, a weak positive trend in fuel consumption in months outside of the fire season is evident although the large variability makes the interpretation of these dynamics more uncertain than those in the southern hemisphere. Figure 2: Monthly estimates of SEVIRI Fire Radiative Energy (FRE)-derived fuel consumption (Tg DM) over northern (**a**) and southern (**b**) hemisphere Africa between 2004 and 2012. A least-squares linear trend line is shown. Note that the \(y\)-axis range differs among plots.
## 4 Discussion
### Practical Implications  
This system could have direct application in youth development settings. It relies on accessible field tests, requires minimal equipment, and integrates easily into seasonal assessments. The profile output enables coaches and clinicians to tailor training plans, track progress, and reassess athletes periodically to adjust interventions. In return-to-play contexts, the profiles offer a structured checklist of functional domains to restore before clearance. Coaches, clinicians, or sports scientists can use the profiles to tailor training, support return-to-play decisions, and monitor progress longitudinally. Although not intended as an injury prediction tool, early identification of functional deficits supports targeted intervention and aligns with preventative strategies in youth sports medicine.  
To support adoption, we developed a user-friendly, open-source web application (Streamlit-based) that automatically generates an individual athlete's profile report, including visualizations (e.g., radar chart of deficits) and training recommendations.  
To limit the real-world variability of FMS, YBT, and HHD scores we recommend (i) compulsory assessor training on the exact test batteries used here, with periodic recalibration sessions to control inter-rater drift; (ii) a locked-down protocol--identical warm-up, footwear, surface, and familiarization trials--and (iii) aggregation of limb-specific outputs into composite metrics (e.g., mean YBT reach, mean peak forces) that dilute single-measurement noise and yield the higher reliability coefficients reported for summary scores in the literature.
## 3 Implementation Details and Experimental Results  
### Production of Datasets  
The dataset included 400 images of pavement cracks captured with the DJI Mavic 3 Drone from China and 3266 open-source crack images collected by [PERSON] (2018). In addition, an innovative strategy of crack annotation was introduced for precise identification and measurement.  
Labeling, an open-source annotation tool, was used to label cracks according to the small-bounding-box overlay method, as shown in Figure 7. This annotation method allowed us to cover the full length of a crack, marking the various parts of the crack by means of small, dense bounding boxes. This annotation strategy is designed to support binocular-vision-based ranging algorithms. Accurate distance measurements of different parts of a single long crack can improve the quantification accuracy of crack width. This meticulous annotation method allows for further analyses of the cracks' spatial distribution characteristics.  
Figure 6: Crack segmentation process: (**a**) crack detection results, (**b**) extraction of crack images, (**c**) segmentation images, (**d**) edge detection results, and (**e**) crack skeletonization.  
The cracks needed to be segmented for quantitative analysis, and the algorithm used was U-Net++. The crack segmentation dataset was prepared by utilizing publicly available datasets. The dataset sources are detailed in Table 1, and they comprised a total of 2851 images. The images in the dataset underwent preprocessing to align with the network's requirements, which included cropping and resizing to ensure a consistent resolution of 256 \(\times\) 256 pixels for each image. Subsequently, a subset of 11,298 images was chosen from the preprocessed images to construct the segmentation dataset for our model training. This dataset was then partitioned into training, validation, and test sets, following an 8:1:1 ratio to facilitate model training and evaluation.
# Mechanical Behaviors and Numerical Simulation Analysis of a New Isolation System
## 2 Design of the Isolation System
### Test Results
#### 2.4.2 Friction Performance Test under the Action of Balls  
The ball in the system, combined with the spring and shim, plays a role. The main role played by the spring and shim is to adjust the force of the ball so that the total upper load is proportionally distributed to the ball group and PTFE.  
This part of the study focuses on the effect of the bearing ratio on the dynamic friction coefficient. The effect of the number of shims and balls on the dynamic friction coefficient is shown in Figures 7 and 8. The relationship between the number of shims and friction coefficient for four-roller ball and five-roller ball isolation bearings with horizontal velocities of 2 mm/s, 4 mm/s, and 10 mm/s, respectively, under different vertical pressures.  
In Figure 7a, when the horizontal speed is 2 mm/s, the friction coefficients under the action of three bearing ratios show different changes with an increase in the number of shims. When the ball group occupies 25%, the friction coefficient increases first and then decreases, and the minimum is 0.5516; when the ball group occupies 50%, the friction coefficient increases continuously, and the minimum is 0.05805; when the ball group occupies 100%, the friction coefficient decreases gradually, and the minimum is 0.06757.  
In Figure 7b,c, when the horizontal velocity is 5 mm/s and 10 mm/s, the friction coefficient has a tendency to increase and then decrease with the increase in the number of shims, and the minimum friction range occurs when the number of shims is 2 and the pressure-bearing ratio is between 25% and 50%, which are 0.05514-0.05614 and 0.05759-0.05804, respectively.  
Figure 7: The relationship between the number of shims and the friction coefficient of the four-ball composite isolation bearing at different motion speeds: (**a**) 2 mm/s; (**b**) 5 mm/s; (**c**) 10 mm/s.  
In Figure 8, at a certain horizontal velocity, the friction coefficients under the action of different bearing ratios showed a trend of decreasing and then increasing, and the minimum ranges, respectively, were 0.03458-0.03947, 0.03047-0.03869, and 0.02883-0.04169. Most of them were found when the number of shims was 4 and the pressure-bearing ratio was between 25 and 50%.  
In Figures 7 and 8, comparing the data of a four-roller ball and a five-roller ball, it can be found that the coefficient of friction decreases with the increase in the number of balls, and there is a difference in the influence of the parameters of the minimum coefficient of friction; the four-roller ball mostly appears when the number of shims is 2, the five-roller ball mostly appears when the number of shims is 4, and the pressure-bearing ratio is 25-50%.
# A Miniaturized Circularly-Polarized Antenna for In-Body Wireless Communications
## 3 Antenna Analysis  
### Miniaturization of the Proposed Antenna  
In order to investigate the mechanism of miniaturization, the corresponding topology of the antenna is evolved from Case 1 to Case 4 by subsequently cutting slots and loading patch into a conventional square patch antenna, as shown in Figure 5. Here, all antennas keep the fixed sizes of 9.2 mm \(\times\) 9.2 mm and the simulating settings are similar.  
Figure 4: Simulated radiation patterns at 2.45 GHz.  
Figure 3: Simulated reflection coefficient and axial ratio (AR) varying with frequency.  
With reference to Figure 5, Case 1 is a conventional square patch antenna with the feeding port at the upper right diagonal, Case 2 is obtained by etching an arrow-shaped slot in the upper and lower parts of the patch. In Case 3, two small triangle patches are respectively loaded on the arrow-shaped slot of Case 2 and connected with the main patch through two high impedance lines. As shown in Figure 6, the resonant frequency of 4 GHz in Case 1 shifts down to 3.6 GHz in Case 2, then converts to 3.16 GHz in Case 3, indicating that a 21% of miniaturization can be achieved.  
Theoretically, an antenna can be equivalent to a transmission line, as shown in Figure 7, which is characterized by a series inductance \(L_{0}\) and a shunt capacitance \(C_{0}\) per unit length. When the antenna is loaded with patch through a high impedance lines, the miniaturization of the proposed antenna can be achieved by taking advantage of the principle of slow waves [25]. The mechanism can be understood through calculating the propagation velocity as:  
\[\
u_{p}=\frac{1}{\sqrt{L_{0}C_{0}}}=\frac{c}{\sqrt{\epsilon_{eff}}}=\lambda_{ g}f \tag{1}\]  
Figure 5: Evolving structures of the proposed antenna in: (**a**) Case 1; (**b**) Case 2; (**c**) Case 3; and (**d**) Case 4.  
Figure 6: Simulated S11 of four cases embedded in the same phantom.  
Figure 7: Transmission line model with LC loadings.  
According to Equation (1), by adding triangle patches (equivalent to a capacitance \(C_{1}\)) and high impedance line (equivalent to an inductance \(L_{1}\)), total equivalent capacitance and/or inductance are increased, subsequently propagation velocity becomes slower, resulting in waveguide wavelength smaller when the frequency remains unchanged.  
To further miniaturize the proposed antenna, V-shaped patches are etched into the left and right sides of Case 3, lengthening the current path, as established in Case 4 of Figure 5d. Compared with Case 1, the corresponding resonate frequency of Case 4 is shifted down from 4 GHz to 2.51 GHz, demonstrating that 37.3% of miniaturization is achieved.
## 3 Background
### Internet of Thing (IoT)  
IoT describes a set of physical or digital objects that communicate via the Internet or similar communication technologies [43; 44; 45]. Such objects are referred to as \"things\", which are usually equipped with sensors, actuators, processing power, memory, and software to perform the required tasks [46; 47; 48]. The applications of IoT are very diverse and range from smart heating, smart agriculture, smart automation, smart military, smart industry, smart city, smart horticulture, smart building, smart consumer applications, smart health monitoring, and smart supply chain management [49; 50]. As the number of IoT devices is rapidly increasing, several governmental and international agencies are involved in developing policies, regulatory guidelines, and related standards [51].  
IoT ecosystems are enabled by various communication and networking technologies: (i) short-range: e.g., Bluetooth, near-field communication, Wi-Fi, Z-Wave, and radio frequency identification (RFID); (ii) medium-range: e.g., ZigBee and LTE-advanced; (iii) long-range: e.g., cellular, satellite communication, and low-power wide-area networks. Wired alternatives such as Ethernet, fiber, and powerline communications (PLC) can be complemented with existing IoT infrastructure [52; 53]. The IoT also supports heterogeneity and addressability. Despite the tremendous prospects, IoT suffers from the problems of platform fragmentation, privacy, autonomy, data storage, security, design, a negative environmental impact, and control mechanisms.
## 5 Evaluation and Results
### Access Outcome Analysis and Performance Metrics
#### 5.2.2 Pattern Observations  
Here, we analyze the trends observed in the simulation results. This includes the influence of user attributes, organizational affiliation, and license policy structure on access outcomes, providing insights into policy effectiveness and selectivity.  
1. Attribute combinations such as Regulator + Confidential showed high access alignment with policies.
2. Users from Org2 and those with Public clearance were largely filtered out by policy conditions.  
Figure 7: Docker Desktop environment showing running Hyperledger Fabric containers.  
* Licenses with broader attribute criteria (e.g., MIN4701) accounted for a majority of granted decisions.
## 7 Security Analysis
### Security Features  
In Table 2, we evaluate the security features of the proposed scheme with existing schemes [6; 20; 21; 28]. The schemes in [20; 28] cannot withstand session key disclosure attack and those in [20; 21; 28] provide dynamic node addition phase. The scheme in [6] cannot withstand various types of attacks and cannot ensure secure mutual authentication and anonymity. Consequently, the proposed scheme ensures better security functionality than all previous schemes.