esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Test Site Results: Statistical Analysis
### Results Analysis
Therefore, this parameter influenced the retroreflectivity over time instead of the initial retroreflectivity. Retroreflectivity decreases progressively over time, but the model's estimated parameters show that the reduction over time is not linear. There is a severe decrease for the first 100 days (until X\({}_{t,5}\)) and a relative continuous reduction for the other time intervals. However, the retroreflectivity reduction is more intense for the time interval X\({}_{t,7}\) than the time interval X\({}_{t,8}\), which shows that the estimated retroreflectivity is higher for interval X\({}_{t,8}\) than X\({}_{t,7}\). This occurs because the evaluation of time as an interval accounts for the seasonal variation of retroreflectivity, which may present higher values after rain due to surface cleaning, as reported by [PERSON] et al. [42]. Considering a one-unit increase in the volume solids of paints, the retroreflectivity improves by 9.15% when it shifts from being measured within the time interval X\({}_{t,1}=(0,20]\) to being measured within the interval X\({}_{t,2}=(20,40]\). Analogously, the average retroreflectivity improvement is, on average, 14.0%, 12.3%, 15.7%, 17.0%, 16.6%, and 12.6% for time intervals X\({}_{t,3}\), X\({}_{t,4}\), X\({}_{t,5}\), X\({}_{t,6}\), X\({}_{t,7}\), and X\({}_{t,8}\), respectively. The positive contribution of volume solids to the average retroreflectivity shows that the retroreflectivity decreases slower for paints with higher volume solids, i.e., higher volume solids paints reduce the degradation rate of pavement markings' retroreflectivity. An increase in paints' volume solids contributes to the occurrence of the retroreflectivity peak and improves the expected service life of pavement markings. The V.sol is responsible for the thickness of the paints' film on the pavement surface after the drying of paint. Higher V.sol leads to higher dry paint thickness compared to lower V.sol paints if they are applied at the same wet thickness. Therefore, the glass beads present higher embedment depths that will require more wear to remove the particles from the markings' surface, which improves the service life of pavement markings. Finally, random effects were incorporated into the model to deal with the variability between the test sites. The random effect in the intercept for the variable u\({}_{k}\) refers to each test site, in which u\({}_{1}=-0.1097\) for test site 1, u\({}_{2}=-0.0082\) for test site 2, and u\({}_{3}=0.1179\) for test site 3. The intercepts indicates that the retroreflectivity values were, on average, higher for test site 3, followed by test site 2 and test site 1, respectively. The results show that, even with the higher concentration of glass beads at test site 2 (600 g/m\({}^{2}\)), the retroreflectivity values were most impacted by material characteristics.
# Punching Shear Strength of Reinforced Concrete Flat Plates with GFRP Vertical Grids
## 5 Conclusions  
In this study, the experiments were performed on concrete flat plates shear reinforced with GFRP to compare their shear performance in terms of the amount and the spacing of the shear reinforcement. In addition, the test results were used to examine the validity of different design codes for the shear strength of a concrete flat plate. The following conclusions were drawn from this study:  
1. The control specimen showed a cone-shaped, sharply sloped punching shear failure mode within the critical section that was 1/2 of the effective slab depth from the column face. The specimen with a GFRP plate reinforcement showed a cone-shaped failure with a gentle slope and the failure mode had wide critical sections.
2. The shear strength of the concrete flat plates shear reinforced with a GFRP exhibited an increase of an average of 30% compared with that of the specimen without shear reinforcement. That is, the GFRP plate shear reinforcement effectively resisted the punching shear.
3. The shear strength also appeared to increase with the amount of the GFRP plate. From the analysis of the shear strength attributed to the spacing of the vertical strips of the GFRP plate, the shear strength appeared to be the highest when the reinforcement spacing was 0.3d.
4. When comparing the test results with the computed shear strengths using the equations of 318, BS 8110 and Eurocode 2, we found that BS 8110 with an average ratio of shear strength of 1.06 and a standard deviation of 0.15 and Eurocode 2 with an average ratio of shear strength of 1.16 and a standard deviation of 0.08 yielded shear strength values closer to the experimental values than 318. This was because they incorporated the effects of the tension reinforcement ratio. 318, with an average ratio of shear strength of 1.67 and a standard deviation of 0.12, underestimated the experiment results.  
Conceptualization, M.S.K. and Y.H.L.; methodology, M.S.K.; validation, Y.H.L.; investigation, M.S.K. and Y.H.L.; writing--original draft preparation, M.S.K.; writing--review and editing, Y.H.L. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No. 2019R1A2C1090033).  
Not applicable.  
Figure 10: Comparison between the calculated and experimental maximum shear.
## 3 Results
### Effects of CWP on Concrete Microstructure
#### 3.4.1 Scanning Electron Microscopy (SEM)  
[PERSON] et al. [44], using SEM at 5000\(\times\) magnification, observed that CWP particles, identified as white dots, were well-dispersed within the cement matrix. Figure 14 shows the SEM image at 10% CWP replacement. The SEM image displays minimal microcracks, suggesting CWP compatibility with cement and aggregate bonding, with no significant alkali-silica reaction noted at this replacement level.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Author(s)** & **Testing Method** & **Summary of Key Findings on Microstructure** \\ \hline \multirow{3}{*}{[PERSON] al. [44]} & \multirow{3}{*}{SEM and EDS} & Observed well-dispersed CWP particles within cement matrix, reducing microcracks; 10%, CWP replacement showed no significant alkali-silica reaction; indicating stable integration in the microstructure. \\  & & XRD, TGA, and SEM & formation through pozzolanic reaction; 10% CWP produced a denser microstructure with fewer pores after 28 days. \\ \cline{3-3}  & & Identified pozzolanic interactions between CWP and cement hydrates, with reduced CH content over time and a denser ITZ in recycled \\ \cline{3-3}  & & and EDS & aggregate concrete; EDS confirmed Ca, S, and Al Variations indicating calcium-silica-aluminative hydrate formation. \\ \cline{3-3}  & & Frattini test at 28 days confirmed pozzolanic activity with a reduction in \\ \cline{3-3}  & & CH levels and formation of complex calcium-silica-aluminate hydrates \\ \cline{3-3}  & & & 240-4075, CWP replacement levels. \\ \hline \hline \end{tabular}
\end{table}
Table 6: Overview of the Key findings on the microstructural properties of CWP concrete.  
Figure 14: SEM image of concrete with 10% CWP at 28 days [44].  
[PERSON] et al. [52] conducted SEM imaging on CWP-cement pastes. The researchers observed a denser microstructure at 10% replacement, particularly after 28 days of curing. This compactness was attributed to CWP's pozzolanic reaction of CWP, which forms additional hydration products, reduces the pore size, and improves the microstructure.  
[PERSON] et al. [84] examined the effects of substituting PC with CWP on the microstructure and performance of high-strength concrete. SEM analysis of the samples after 28 days of curing revealed that concrete with 10% CWP had a less homogeneous and compact microstructure than the reference sample. The researcher observed that the roughness of the CWP particles led to stress concentrations at sharp edges, causing increased cracking and reduced strength characteristics. However, blending CWP with waste brick powder improved the compactness and reduced crack formation due to better packing of particles with different sizes and shapes.  
[PERSON] et al. [56] reported that SEM EDX suggests pozzolanic reactions on CWP surfaces, particularly between the ceramic grains and hydration products. The SEM images also show a more compact ITZ, improving the overall durability by reducing the porosity within the concrete structure.
## 3 System Requirements for BVLOS Flight Operations
### RAVEN-Proposed Small UAS DAA System
#### 3.5.3 Determine Alerting Boundaries for Hazard Identification  
As introduced in [3], the NMAC boundary is a standard cylinder around the UA: 500 ft in radius horizontally, and \(\pm\)100 ft in height vertically. Moreover, in Figure 10a, the Collision Avoidance Alerting Threshold (CAAT) boundary is defined as the closest range boundary at which the UA can still avoid NMAC with the traffic by a horizontal maneuver within the Flight Performance Envelope (FPE), i.e., an outer layer outside of the NMAC cylinder. Since small UAS are sensitive to ever-changing flight environments such as encounter geometries, relative velocities, and wind conditions (i.e., wind speed and wind direction), small UAS CAAT boundaries cannot be directly calculated through mathematical equations. These are usually estimated based on simulation methods via millions of simulated mid-air encounters, e.g., a Monte Carlo (MC) simulation method designed and developed in [18].  
For simplicity, the vertical CAAT boundary is pre-defined at fixed heights \(\pm\)450 ft. Thus, only the horizontal CAAT boundary needs to be determined via simulation methods by a series of co-altitude mid-air encounters [18]. As described in Figure 10b, a web structure is adopted in MC simulations to locate CAAT boundaries in various wind conditions, where traffic aircraft are initiated from inner circles to outer circles at bearing angles [0\({}^{\circ}\), 360\({}^{\circ}\)) with heading angles in [0\({}^{\circ}\), 360\({}^{\circ}\)); UA are initiated at the web center with the 0\({}^{\circ}\) heading angle (to the north). At each bearing angle, we locate the shortest horizontal range between UA and traffic, at which UA can avoid NMACs with traffic in all possible headings by one of the appropriate horizontal maneuvers. Through MC simulations, a set of sample summarized CAAT boundaries are acquired and drawn in Figure 10b with their maximum range at each bearing angle to cover encounters in various wind conditions [18]. In general, the UA front CAAT boundaries in Figure 10b are enlarged in comparison with the ones without wind in Figure 10a. Furthermore, Figure 11a,b show that UA require longer horizontal ranges to avoid NMACs for traffic  
Figure 9: ADS-B and ground portable radar assembly. (**a**) AWSAS box; (**b**) Zeus without radome [17].  
from the side regions of UA, such as at the bearing angles [60\({}^{\circ}\), 120\({}^{\circ}\)] and [240\({}^{\circ}\), 300\({}^{\circ}\)], because during UAS operations they are the most vulnerable bearing regions on CAAT boundaries in various wind conditions [18].
# Exploring Data Model Relations in OpenStreetMap
## 4 Experimental Analysis
### Relation Analysis
#### 4.2.1 Composition of Relations  
As discussed in Section 3, relations are composed of members. A member can be a node, way or a relation itself. Table 2 summaries compositions of data types within relations in these four cities. In the city column, the bound sign # indicates the number of relations with the corresponding member composition while the % indicates this number as a percentage of all relations in the city. The column \(N\) indicates the numbers of relations comprised of only node objects, \(W\) indicates the number of relations comprised of only way objects, \(R\) indicates the number of relations comprised of only relation objects. The remaining columns represent combinations of compositions of nodes, ways and relations. The most frequently occurring composition for relations are those composed of only ways (the W column) and then relations composed of nodes and ways (the N + W column). These two composition represent at least 85% of all relations in all of the four cities. We believe that this is a healthy situation. It would appear to indicate that these relations are more efficiently handled, managed and visualized by OSM software tools. It may also indicate that the contributors of these relations are focused on expressing real-world relationships between objects in a simplified way. By far the least popular compositions of data types for members within relations in the four cities involve compositions which include  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Type** & **Zurich** & **Rome** & **Vienna** & **Madrid** \\ \hline Total Relations & 1855 & 13,226 & 9177 & 6403 \\ Area km2 & 88.10 & 1250 & 414.65 & 605.45 \\ restriction \% & 28.46 & 26.33 & 11.27 & 24.99 \\ multipolygon \% & 15.63 & 60.36 & 61.03 & 50.74 \\ route \% & 21.99 & 7.89 & 14.10 & 13.93 \\ public\_transport \% & 14.12 & 0.95 & 4.16 & 0.92 \\ route\_master \% & 4.64 & 3.02 & 2.53 & 4.62 \\ Total \% & 84.84 & 98.55 & 93.09 & 95.20 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Summary of the five most popular types of relations in all of the case study cities. Values are expressed as percentages of the total number of relations.  
relations themselves. As mentioned above, the OSM Wiki pages on Relations [25] indicate that this recursive definition of relations creates what is known as a super relation. While these super relations are a valid logical construct, their use is discouraged due to the very poor software support for them when processing and using OSM data at this time.
# Development of a Non-Invasive On-Chip Interconnect Health Sensing Method Based on Bit Error Rates
###### Abstract  
Electronic products and systems are widely used in industrial network systems, control devices, and data acquisition devices across many industry sectors. Failures of such electronic systems might lead to unexpected downtime, loss of productivity, additional work for repairs, and delay in product and service development. Thus, developing an appropriate sensing technique is necessary, because it is the first step in system fault diagnosis and prognosis. Many sensing techniques often require external and additional sensing devices, which might disturb system operation and consequently increase operating costs. In this study, we present an on-chip health sensing method for non-destructive and non-invasive interconnect degradation detection. Bit error rate (BER), which represents data integrity during digital signal transmission, was selected to sense interconnect health without connecting external sensing devices. To verify the health sensing performance, corrosion tests were conducted with in situ monitoring of the BER and direct current (DC) resistance. The eye size, extracted from the BER measurement, showed the highest separation between the intact and failed interconnect, as well as a gradual transition, compared with abrupt changes in the DC resistance, during interconnect degradation. These experimental results demonstrate the potential of the proposed sensing method for on-chip interconnect health monitoring applications without disturbing system operation.  
bit error rates; interconnect; prognostics; diagnosis; health management +
Footnote †: journal: Sensors
## 2 Materials and Methods
### Calculation of the TVDI  
To monitor the drought stress experienced by vegetation in Central Asia, we developed the temperature vegetation dryness index (TVDI). The TVDI is based on the triangular relationship between vegetation condition and land surface temperature (NDVI-LST) described in the literature (Figure 3) [53]. TVDI can be used as a vegetation moisture stress index in conjunction with other vegetation indices to establish productivity estimation models [54; 55]. It exhibits a strong correlation with soil moisture, which is well demonstrated in our validation results (Figure 4). Due to the universality of its construction method, we can obtain more precise data on vegetation moisture stress (vegetation drought). This allows for greater accuracy in assessing vegetation drought [56; 57]. Furthermore, this method is applicable to drought monitoring under different climatic and topographical conditions [58]. The formula for constructing the _TVDI_ using the _NDVI_ and \(LST\) is as follows in Equation (2):  
\[TVDI=\frac{LST-LST_{min}}{LST_{max}-LST_{min}} \tag{2}\]  
In this equation, \(LST\) represents the land surface temperature of any given grid cell. \(LST_{min}\) refers to the lowest land surface temperature, which defines the wet edge along the horizontal base of the triangle (Figure 3). \(LST_{max}\) denotes the highest land surface temperature, defined as the dry edge.  
\[LST_{min}=a_{1}+b_{1}\times NDVI \tag{3}\]  
\[LST_{min}=a_{2}+b_{2}\times NDVI \tag{4}\]  
Linear regression analysis was employed to determine the dry edge Equation (3) and wet edge Equation (4). The coefficients for the dry edge and wet edge are \(a_{1}\) and \(b_{1}\) and \(a_{2}\) and \(b_{2}\), respectively, representing the intercept and slope of their respective equations. The _TVDI_ ranges from 0 to 1, with values closer to 1 indicating proximity to the dry edge and a higher degree of drought. The _TVDI_ is classified into five categories based on its intensity (Table 3) [59]. The calculations are implemented in python 3.8. The relevant code and computational steps are sourced from [[https://gma.luosgeo.com/Introduce.html](https://gma.luosgeo.com/Introduce.html)]([https://gma.luosgeo.com/Introduce.html](https://gma.luosgeo.com/Introduce.html)) (accessed on 10 February 2024).  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Level** & **Climate Types** & **De Martonne Value** \\ \hline
1 & Arid & 0–10 \\
2 & Semiarid & 10–20 \\
3 & Mediterranean & 20–24 \\
4 & Semhiumd & 24–28 \\
5 & Humid & 28–35 \\
6 & Very humid & \textgreater{}35 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Climatic regions based on the De Martonne index.
# The Future of Cybersecurity in the Age of Quantum Computers
## 5 Quantum Supremacy and the Q-Day Threat
### Potential Quantum Computing Business Model  
It is estimated that breaking the classical encryption will require 317 million qubits [34]. Today, each qubit costs around USD 10,000 a piece [35]. Even if the qubit price comes down a hundredfold, an encryption-breaking quantum computer will cost hundreds of millions apiece. Due to the very high costs and the race to protect trade secrets, the expected business model for quantum computing is likely to resemble the current model for cloud-based computing dominated by Amazon/AWS (33%) [36]. This essentially means that, unlike a standard computer that almost anyone can own, ordinary citizens or, for that matter, hackers cannot afford a quantum computer. They will have to rely on the quantum computing service providers (QCSPs) for leasing quantum computing resources to design and execute their quantum malware to launch a quantum attack on any  
Figure 6: Three scenarios of client-server network architecture: (**A**) legacy, (**B**) 3 SoC client only, and (**C**) 3 SoC client + 3 SoC server (intranet).  
victim computing device remotely. The astronomical cost of quantum computers rules out the possibility of an encryption-breaking personal desktop version anytime in the future and, in fact, comes as a blessing in disguise. The QCSP business model makes the job of standard-regulating authorities such as the NIST in the US and ENISA, its equivalent in Europe, a lot easier. Building standards to regulate cloud service providers is much easier than regulating a desktop hacker. These standardizing and policy-making agencies are currently focusing exclusively on PQC (post-quantum cryptography) to withstand the decryption capabilities of powerful quantum computers. Although we have seen over 90% of the candidate PQC algorithms that the NIST reviewed over the past 5 years fail [20; 21], even if none of the candidate PQC algorithms succeed, these agencies can draft technical standards for operating QCSPs and let government regulatory agencies implement those standards as rules for availing quantum computing services. However, in the given circumstances, it is worth looking beyond PQC for safeguarding classical computers from future quantum hackers.
# Experimental and Numerical Predictions of Cryogenic Leakages in Welded Steel Plates
## 4 Results and Discussion  
### Cryogenic Liquid Leakage Test  
Figure 11a shows an image of the cryogenic liquid leakage test for investigating the temperature conditions of the welded steel plate by exposing the inside of the plate trough to LN\({}_{2}\). As shown in the figure, the liquid nitrogen pipeline is located at the center of the trough, and there is no leakage to the outside of the trough. The liquid nitrogen is vaporized once it is supplied to the welded plate due to the difference between the temperatures of the surface of the plate and the liquid nitrogen. After reaching thermal equilibrium, liquid nitrogen can be supplied to the inside of the trough. When the plate inside of the trough is submerged in LN\({}_{2}\), it cools rapidly to the temperature of the LN\({}_{2}\) and undergoes significant thermal contraction due to the remarkable reduction in temperature. However, the outside of the trough cools slowly by thermal convection, which leads to minor thermal deformation. Additionally, the welded plate undergoes shrinkage due to the abrupt addition of the cryogenic liquid. However, the adjacent region, which is unaffected by the LN\({}_{2}\), suffers relative thermal tensile stress.  
Figure 11b shows the time-dependent temperature relationship under cryogenic liquid exposure at six different measurement points. As shown in the figure, the temperature decreases significantly from thermal shock due to the temperature difference between the ambient temperature at the steel plate surface and the temperature of the liquid nitrogen (\(-196\)\({}^{\circ}\)C). Subsequently, the temperature decreases quickly and remains approximately constant until the cryogenic liquid supply is terminated. The thermocouples TC1, TC2, and TC5 eventually reach a cryogenic temperature of \(-196\)\({}^{\circ}\)C because they contact liquid nitrogen inside the trough. However, the time required to reach a temperature of \(-196\)\({}^{\circ}\)C shows different trends, depending on the location of the thermal couples. TC5 and TC2 reach a temperature of \(-196\)\({}^{\circ}\)C in approximately \(160\) s and \(280\) s, respectively. In the cases of TC3 and TC6, which are located outside the trough, the temperature is maintained at approximately \(-75\)\({}^{\circ}\)C by conduction and convection thermal transmission through the plate. In the case of TC4, the temperature is maintained at about \(-25\)\({}^{\circ}\)C due to its position at a relatively long distance from the liquid nitrogen inside of the trough. All temperatures increase rapidly with the termination of the liquid nitrogen supply. Finally, the temperature gradually converges to room temperature in the interval between \(4000\) s and \(5000\) s.  
Figure 10: Validation of the experiment data and numerical simulation for: (**a**) transverse residual stress and (**b**) Z-directional displacement distribution.