esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Methodology
### Fusion Processing
#### 2.3.2 KD-Tree Neighbor Search  
Based on the data structuring algorithm in NNL [21], KD-Tree (k-dimensional tree) serves as an efficient spatial indexing structure, widely adopted for its simplicity, low memory overhead, and high computational efficiency. The core idea of the KD-Tree algorithm is to select a dimension and split the set of points based on the median valuealong that dimension, ensuring that the resulting subsets are approximately equal in size. This binary partitioning process is repeated until the dataset can no longer be subdivided.  
Assuming a two-dimensional dataset, as illustrated in Figure 10, the construction begins by computing the median of all points along the \(X\)-axis, which serves as the initial splitting reference. This divides the dataset into left and right subsets. The median of the \(Y\)-axis is then computed within each subset to further split them into upper and lower partitions. This recursive partitioning continues, alternating between axes until each point is individually isolated. The positions of the sample points are then visualized within the 2D coordinate system.  
Based on this structure, KD-Tree enables efficient search operations. Compared with a traditional linear search, its average time complexity is \(O(logn)\), which is significantly better than the \(O(n)\) of a linear search. To validate this conclusion, we performed radius-based neighbor searches on point clouds with varying numbers of points and recorded the search time. As shown in Table 3, for small-scale point clouds, the linear search performs comparably to or even better than KD-Tree. However, as the point cloud size increases, KD-Tree demonstrates significantly higher search efficiency, confirming its acceleration advantage in large-scale data scenarios.  
As shown in Figure 11, this paper utilizes the neighbor search method of KD-Tree to rapidly extract the region of interest around the 3D target point, enabling efficient localization and segmentation of the target point cloud. By this method, the search range can be reduced and the initialization accuracy of point cloud matching can be effectively improved, thus accelerating the convergence speed of the alignment algorithm and improving the robustness.  
Figure 10: Binary tree diagram.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Number of Points** & **Search Radius (m)** & \
\begin{tabular}{c} **KD-Tree Radius** \\ **Search Time (ms)** \\ \end{tabular} &
\begin{tabular}{c} **Linear Search Time** \\ **(ms)** \\ \end{tabular} \\ \hline
1000 & 0.02 & 74 & 47 \\
10,000 & 0.02 & 184 & 501 \\
50,000 & 0.02 & 774 & 2387 \\
100,000 & 0.02 & 1752 & 5141 \\
500,000 & 0.02 & 7383 & 19,378 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Comparison of radius neighborhood search time.
## 6 Discussion
Again, the level of energy efficiency makes these systems deployable in mobile health units or point-of-care diagnostics, thus increasing access to advanced technologies for breast cancer detection. Also, moving from the 1000 dimensions using the full feature set to the feature set of 350 dimensions reduces memory consumption and processing loads, resulting in free and smooth integration into the existing hospital information systems without compromising their processing capabilities. This allows maximum flexibility for the proposed CAD system to perform thus it can be applied in high-end medical centers and decentralized healthcare setups. Eventually, goal-directed simplification of the model improves scalability and broadens accessibility without compromising diagnostic proficiency. By the integration of high performance with computational efficiency, the proposed framework will ensure that state-of-the-art detection for breast cancer does not remain exclusive to medical institutions of some level and therefore promotes equitable care in all environments.
# Monitoring and Data Analysis in Small-Scale Landslide Physical Model
## 3 Review of Landslide Monitoring Equipment
### Geodetic Monitoring System in Small-Scale Landslide Modeling
#### 3.1.2 Terrestrial Laser Scanner (TLS) and Structure-from-Motion (SfM) Photogrammetry
Scans can be conducted in color or monochromatic, which visually gives better information about the geometry itself because of the use of different shades of grey. The amount of  
Figure 4: (**a**) Terrestrial laser scanner FARO Focus 3D X 130; (**b**) Spheres used as reference targets. \begin{table}
\begin{tabular}{c c} \hline \hline
**Description** & **Value** \\ \hline Size & 240 \(\times\) 200 \(\times\) 100 mm \\ Weight & 5.2 kg \\ Range & 0.6–130 m indoor \\ Measurement speed & 122,000/244,000/488,000/976,000 pts/s \\ Ranging error & \(\pm\)2 mm \\ FOV & 300\({}^{\circ}\)/360\({}^{\circ}\) (vertical/horizontal) \\ Resolution & From 1/1 to 1/32 \\ Quality & From 1\(\times\) to 8\(\times\) \\ Color unit resolution & Up to 70 megapixels \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Technical specifications of the FARO Focus 3D X 130 laser scanner. light determines the intensity of the color, and after monochromatic measurements, there is spherical photographing which allows for a scan in color. References or targets are used to achieve the overlap of multiple individual scans, each with their own coordinate system, onto a single scan with aligned coordinate system. Different targets can be used as an artificial reference object, such as checkerboard paper targets or reference spheres which were used in this test (Figure 4b). Target spheres should be spaced as far apart as possible but within the overlapping scan areas. Higher number of references per scan may improve scan results and make the registration easier and less prone to errors [58]. If correctly positioned, the laser can see reference spheres in all conditions. It defines the center of the sphere, connects them over all the scans, and defines the relative coordinate system. SfM allows for the creation of 3D models from multiple overlapping images taken at distinct triangulation angles. Lighting differences usually cause problems while processing data, but many types of software have the ability to estimate potential errors and delete images whose accuracy is questionable [59]. The method works by analyzing whole images, searching sectors with similar pixels in all the taken images, and triangulating the position of the camera. SfM photogrammetry survey of the physical model was carried out only for the first test in the series by a Nikon D500 camera with an ultrawide angle lens Tokina AT-X 11-20, which allowed the determination of a 3D landslide surface model similar to that obtained by a laser scanner.
# Effect of Strain Hardening on Increase in Collapse Pressure during the Manufacture of ERW Pipe
###### Abstract  
Plastic deformation during the manufacture process of electric resistance welded (ERW) pipe determines the stress-strain relationship of the steel pipe, which affects the collapse pressure of offshore pipelines. To track the deformation history of the pipe, the entire process was simulated via finite element analysis using a solid element. A material model that considered both the Bauschinger effect and strain hardening was adopted. Various sizes of pipe cross-sections were simulated. As greater compression was applied during the sizing process, the strain hardening effect became more significant, so that the compressive yield strength was increased in the circumferential direction. The strain hardening effect was most prominent for a smaller diameter-to-thickness ratio (_D/t_), so that an increase in the collapse pressure could be obtained with a larger sizing ratio. Therefore, current design criteria for the collapse pressure recommended by Det Norske Verita (DNV) and API could be enhanced for a smaller _D/t_ to consider the strain hardening effect during the sizing process.  
ERW steel pipe; sizing ratio; collapse pressure; manufacture process; strain hardening; compressive yield strength +
Footnote †: journal: Applied Sciences
## 3 Results and Discussion
### Evaluation of Volatile Aroma Compounds
#### 3.1.3 Alcohols  
TM10-Y had the highest C\({}_{6}\)-alcohol levels, TM7-Y contained the most benzyl and 2-phenylethyll alcohol, while TM21-Y and TPHT-Y had the lowest concentrations of alcohols in general among young wines (Table 1). C\({}_{6}\)-alcohols are formed from long-chain fatty acids by enzymes such as lipoxygenase (LOX), hydroperoxide lyase (HPL), (32)-(2E)-enal isomerase, and alcohol dehydrogenase (ADH) released during grape crushing [39; 40]. Higher 1-hexanol concentrations were found in wines with shorter maceration durations (five days) compared to longer durations (10 and 15 days). Additionally, _trans-_ and _cis-_3-hexenol were not detected in wines macerated for 5 or 10 days but were present in those macerated for 15 days [41]. This trend was also observed in this study. Interactions between phenolic and volatile aroma compounds might have also occurred, potentially influencing C\({}_{6}\)- and other alcohol levels [42]. Decreases in alcohols can be attributed to their fixation onto macromolecules or berry skins, which can be beneficial as high C\({}_{6}\)-alcohol levels might negatively impact aroma [43]. The hydroperoxide lyase enzyme, optimal at 15 \({}^{\circ}\)C, is inhibited by higher temperatures [44], explaining the reduced enzyme activity and lower C\({}_{6}\)-alcohol concentrations in TPHT-Y treatment wine. Decreased C\({}_{6}\)-alcohol levels after pre-fermentation heating during winemaking have been observed in other studies as well, likely due to lipoxygenase inactivation [19; 31; 37; 45]. Lower levels of 2-phenylethyll alcohol in TPHT-Y wine with respect to control possibly resulted from the reduction of its amino acid or glycosidic precursors by heating. Previous research has reported significant decreases in some C\({}_{6}\)-alcohols after wine aging [37], which aligns with the trends observed in this study, although not all C\({}_{6}\)-alcohols followed this pattern. Aging reduced the concentrations of certain alcohols in TM7-A and TM10-A wines but increased them in TM21-A and TPHT-A wines, which altered the ratios of young to aged wine concentrations among the treatments. It was assumed that TM21 and TPHT treatments may have extracted more alcohol precursors compared to the other treatments. These precursors could have undergone hydrolysis and other transformations during aging, leading to higher concentrations of volatile alcohols in TM21-A and TPHT-A wines. This aligns with the previous observations (30), which suggest that differences in alcohol concentrations could similarly result from the extraction and subsequent chemical changes in alcohol precursors during aging.
# Curable Area Substantiation of Self-Healing in Concrete Using Neutral Axis
## 5 Conclusions  
In this study, the three-point bending test with a notch was performed for assessing the self-healing of concrete, and the neutral axis was estimated to investigate the curable area by self-healing. Our results are as follows:  
1. Within the scope of this study, the longer the healing period, the higher the healing effect. In the same healing period (21-day), the later the crack was induced, the less effective the healing effect was. These results are generally consistent with previous studies.
2. The method for estimating the neutral axis using successive strain gauges attached to the crack propagation part was proposed in this study. The estimated neutral axis showed proper behavior in comparison with Load-CMOD curve; the neutral axis moved slightly upward with crack propagation, but there was an insignificant move when the crack was closed or reopened.
3. Recovery of the flexural strength and the initial flexural stiffness before and after healing was confirmed, but no major fluctuations in the neutral axis were confirmed. Consequently, the curable area appears to be limited to the area between the neutral axis and the crack tip, as opposed to over the opened crack area.  
The conclusions were judged to be valid within the scope of this study. We noted that all results in this study show a certain trend while data is statistically insufficient. It is considered that further experiments will produce more significant results.  
Conceptualization, C.K. and T.K.; methodology, T.K.; software, C.K.; validation, C.K. and T.K.; formal analysis, C.K.; investigation, T.K.; writing--original draft preparation, C.K.; writing--review and editing, T.K.; visualization, T.K.; supervision, T.K.; project administration, C.K.; funding acquisition, C.K. This research was funded by the Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education, grant number NRF-2017R1D1A1B03034470. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.
## 2 Principle Analysis of the Proposed JSG-DPD Technique
### The Proposed JSD-DPD Technique  
The proposed system architecture depicted in Figure 2 is mainly based on the overall DPD structure of Figure 1b. However, the space-borne feedback loop is eliminated and replaced by a noise reduction and DPD coefficient extraction system at the ground station to save satellite resources. Certainly, the ground station faces the challenge of a low signal-noise ratio (SNR) resulting from high AWGN. To address this concern, the superimposed training sequences (STS) method is proposed. The nonlinearly compressed STS signals pass through the AWGN channel between the satellite and the ground and are captured by the receiving antenna of the ground station. Noise reduction is performed by exploiting the irrelevancy of the noise, as explained in the following Section 2.4. Then the DPD coefficients of the selected model are calculated with a suitable adaptive algorithm and uploaded to the baseband front-end of the LEO satellite using the satellite-ground bi-directional link. Hence, this joint satellite-ground DPD (JSG-DPD) structure does not occupy additional space-borne resources. It can greatly improve the linearity and the power efficiency of APA, enabling the application of DPD techniques to LEO satellite communications.
# Optimal Particle Filter Weight for Bayesian Direct Position Estimation in a GNSS Receiver
## 9 Conclusions
\begin{tabular}{l l} DPE & Direct Position Estimation \\ BDPE & Bayesian Direct Position Estimation \\ GNSS & Global Navigation Satellite System \\ PVT & Position, Velocity and Time \\ BPSK(1) & Binary Phase Shift Keying (with 1.023 MHz code rate) \\ SMC & Sequential Monte Carlo \\ EKF & Extended Kalman Filter \\ LTE & Long-Term Evolution \\ LOS & Line of Sight \\ VTL & Vector Tracking Loop \\ MC & Multi-Correlator \\ GPS & Global Positioning System \\ PF & Particle Filter \\ C/A & Coarse/Acquisition codes \\ RF & Radio Frequency \\ IF & Intermediate Frequency \\ ADC & Analogue to Digital Converter \\ USB & Universal Serial Bus \\ FFT & Fast Fourier Transform \\ CRLB & Cramer-Rao Lower Bound \\ AGC & Automatic Gain Control \\ CW & Continuous Wave \\ BW & Bandwidth \\ LAT & Latitude \\ LON & Longitude \\ RMS & Root Mean Square \\ PRN & Pseudo-Random-Noise \\ \end{tabular}
# Recombination of Poly(Acrylic Acid) Radicals in Acidic Aqueous Solutions: A Pulse Radiolysis Study
## 3 Results and Discussion
### Radical Decay Kinetics at pH 2
#### 3.4.3 Rate-Determining Step in Intermolecular Recombination of PAA Radicals  
Data at the low \(Z_{R0}\) limit of Figure 7, where intermolecular recombination dominates, can be used to determine the rate-controlling step of radical decay in dilute polymer solutions, where the coils are separated by void volumes of the solvent and each radical bears only one radical site. Such analysis may also be relevant to the termination step of free radical polymerization in dilute solutions. In principle, three steps can be considered in intermolecular recombination: translational diffusion of the coils until they collide, segmental diffusion needed for the two radical-bearing segments of two separate macromolecules to come into contact, and the chemical reaction itself (Figure 8). The latter is not probable as the rate-determining step since the typical rate constants for recombination of aliphatic low-molecular-weight radicals, including protonated carboxylic acids, are significantly higher (>4 \(\times\) 10\({}^{8}\) dm\({}^{3}\) mol\({}^{-1}\) s\({}^{-1}\)[84; 98]) than the values observed here.  
Based on the Smoluchowski equation for the second-order rate constant of a reaction between two identical spherical reagents controlled by translational diffusion (Equation (8), [14; 99; 100]), where \(R\) is the reaction radius of a sphere and \(D\) is its diffusion coefficient, we can estimate the expected rate constant for such process in our case.  
\[k=16\ \pi\ R\ D\ N_{A} \tag{8}\]  
Diffusion coefficient and hydrodynamic radius of our PAA at pH 2, as determined by dynamic light scattering, are 8.5 \(\times\) 10\({}^{-8}\) cm\({}^{2}\) s\({}^{-1}\) and 29 nm, respectively. Assuming \(R=R_{h}\) and substituting these values into Equation (8), we obtain an expected rate constant for translational diffusion-controlled reaction as 7.5 \(\times\) 10\({}^{9}\) dm\({}^{3}\) mol\({}^{-1}\) s\({}^{-1}\), i.e., much higher than the experimental values for low \(Z_{R0}\) (Figure 7). This comparison indicates that, most probably, the rate-determining step in intermolecular recombination of radicals in dilute polymer solution is not translational diffusion but segmental diffusion, causing the radical-bearing segments to be exposed for reaction in the case of collision.
## 2 Literature Review
### Gaps and Potential Innovations  
Although several studies have discussed recommendations for BCE design, they lack a clear, standardised, and comprehensive design process. As a result, BCE design often relies heavily on the engineer's personal judgement, impacting the design efficiency. The involvement of Australian standards is still minor. Furthermore, BCE, while a form of temporary construction equipment, exhibits some characteristics of permanent structures, resulting in high initial costs. To meet economic requirements, it is essential to maximise the number of life cycles for which BCE can be reused rapidly. However, bridge design requirements can be significantly different across projects, sometimes even within a single project. Therefore, complicated redesign processes are often necessary before the implementation of reliable BCE in engineering practice. This situation leads to significant time and financial consumption without a well-defined design framework.  
This project, therefore, aimed to propose a clear, adaptable, and evolvable design procedure for BCE and took the design process of OMSS as an example to validate the application of this new design guidelines. Through the newly proposed design procedure, the issues of high costs between work cycles and low redesign efficiency can be resolved.
# Charge-Line Dual-FET High-Repetition-Rate Pulsed Laser Driver
## 3 System Implementation
### +HV DC-DC Converter  
The peak pulse power of the laser diode is regulated directly via the +HV supply voltage (see Figure 2). In order to increase the versatility of the laser driver system, a DC-DC converter, regulated from 10 V up to 80 V was implemented.
# Photocatalytic Properties of Immobilised Graphitic Carbon Nitride on the Alumina Substrate
###### Abstract  
Textile industries significantly impact the contamination of wastewater. Conventional wastewater treatment methods consider the most common pollutants; however, they are very expensive and commonly produce toxic by-products. In the scientific community, advanced oxidation processes appear to be the most appealing, and a majority of the published work considers heterogeneous photocatalysis for the degradation of various toxic chemicals. For convenience, the reaction is performed directly in the water environment. In this work, a metal-free graphitic carbon nitride (\(g\)-C\({}_{3}\)N\({}_{4}\)) was prepared through a simple thermal method using urea as a precursor. Prepared \(g\)-C\({}_{3}\)N\({}_{4}\) was deposited on the surface of the alumina ceramic ring by the dip-coating method using ethylene glycol as binder. The alumina ceramic ring, as substrate, was prepared by the slip casting method. Photocatalytic properties of immobilised graphitic carbon nitride were used for degradation of methylene blue as a model pollutant under simulated solar light irradiation. The photocatalyst was characterised by XRD, FTIR, UV-Vis DRS, TGA, BET and SEM/EDX analyses. The photocatalytic degradation of MB from an aqueous solution was found to increase with increasing irradiation time. It was found that the graphitic carbon nitride immobilised on alumina ceramic is convenient for largescale environmental applications because the whole setup is cheap, nontoxic, easy to operate and offers reusability with a high removal rate of MB after three consecutive cycles.  
graphitic carbon nitride; alumina ceramic; photocatalysis; methylene blue +
Footnote †: journal: Applied Sciences
## 4 Results and Discussion  
### Factors Affecting Se Crop Content  
Studies have shown that total Se soil content, Se speciation and bioavailability, soil physicochemical properties (e.g., pH, Eh, SOM), and the synergistic or antagonistic interactions between Se and other soil elements are key factors that affect Se uptake by crops [43]. Because this study primarily used data on crop and root soil element contents and pH, the following discussion is focused on the synergistic and antagonistic effects of Se with other elements, as well as the impact of soil pH on Se crop content.  
Research indicates that elements such as Mn, Mo, and Cu exhibit synergistic effects with Se, while P, S show antagonistic effects [44; 45]. For instance, SO4\({}^{2-}\) and PO4\({}^{3-}\), as competitive ions, inhibit Se absorption by crops. Therefore, the presence of P, S reduces Se crop uptake [8; 46].  
In soils, the bioavailability of different Se species is generally in the following order [47]: selenate > organic selenium > selenite > elemental selenium > selenides. Soil pH and Eh significantly influence the distribution of Se species. Selenate is typically found in alkaline surface soils, whereas selenite is more common in acidic subsoils. Therefore, Se crop content generally increases with higher soil pH [8]. Additionally, total Se soil content remains a critical factor affecting Se crop content.  
To analyze the correlation between Se crop content and root soil indicators in the study area, we calculated Pearson correlation coefficients for 130 paired samples of Se crop content and root soil indicators, and a heatmap was generated (Figure 2).  
Figure 2: Heat map of correlation between Se crop and root soil elements.  
The analysis revealed significant positive correlations between Se crop content and root soil Cd, Mo, Se, and SiO\({}_{2}\) (\(p<0.01\)), as well as significant negative correlations with P and S (\(p<0.01\)). Among these, the findings for Se, P, and S align well with previous research conclusions [44; 46]. The high correlation between root soil Se and Mo (r = 0.89, \(p<0.01\)) and Cd (r = 0.77, \(p<0.01\)) indicates that Mo and Cd are commonly enriched in Se-rich soils in the study area, suggesting that Se crop content is positively correlated with root soil Mo and Cd. Therefore, in subsequent model construction, data on these elements were prioritized as evidence layers or training data.