esa-sceva/satcom-chunk-collection huggingface dataset:
# A Review of Recent Advances in Roll Stability Control in On-Road and Off-Road Vehicles
## 5 Roll Stability Control in Off-Road Vehicles  
### Roll Characteristics of Off-Road Vehicles  
Compared with on-road vehicles, off-road vehicles typically operate in rugged and uneven terrain with significant slope variations, and their driving conditions are further complicated by factors such as load changes, shifts in the center of gravity, and ground irregularities [110, 111]. As a result, off-road vehicles are more susceptible to severe rolling or even tipping accidents, which pose significant threats to operational safety and equipment stability [29, 112, 113]. Among these, agricultural machinery, as a typical off-road vehicle, operates in environments involving complex terrain, soil properties, and dynamic changes in operational loads, leading to highly nonlinear characteristics in the vehicle mass distribution, suspension response, and roll stability [114]. Especially during operations such as hillside work, plowing, or heavy-duty towing, the contact conditions between the agricultural machine and the ground, the dynamic characteristics of the suspension system, and the height of the center of gravity all undergo significant changes, which, in turn, affect the roll stability [115; 116; 117; 118]. In response to these challenges, researchers have proposed various active posture and stability control methods in recent years to enhance the roll stability of agricultural machinery in complex terrains. Specifically, because tractors often use a rigid chassis structure, the vehicle roll angle is mainly absorbed by the suspension and tire deformations, making them more prone to tipping in harsh terrains [119]. The following sections will systematically discuss active roll stability control strategies applicable to agricultural machinery, with tractors as the primary representative.
# Personalized Contextual Information Delivery Using Road Sign Recognition
## 3 Proposed System
### Contextual Information Integration
#### 3.3.2 Chain of Thought-Based Information Processing  
To effectively combine the user context with the extracted road sign data, the system employs a step-by-step reasoning process based on the CoT framework. The overall workflow of the proposed system, integrating user context and extracted road sign data, is illustrated clearly in Figure 6. Unlike traditional text processing methods, which focus on static data interpretation, CoT facilitates the logical integration of user data with individually detected objects from road sign images [17; 18].  
Figure 5: User contextual data flow.  
Figure 6: Overall flowchart of the proposed system.  
The system begins by processing individual objects detected from the road signs. For instance, the text detection module may identify separate objects such as \"Mokpo\" and \"27 km\", each with their respective coordinates and labels. These objects are stored as structured data and associated with their contextual meaning based on their position and category. For example, \"Mokpo\" is recognized as a destination, while \"27 km\" is interpreted as a distance [11; 17].  
Using this structured data, the system combines user-specific inputs such as the current vehicle speed and destination. The CoT reasoning framework integrates these pieces of information to generate logical outputs. For instance, it produces a user-specific message such as, \"At your current speed, you will reach Mokpo in approximately 27 min\". This step-by-step integration ensures the information is dynamically tailored to the user's journey while maintaining high accuracy and relevance [18].  
By treating each detected object as a standalone piece of information and logically assembling them with user data, the system transitions from raw data processing to dynamic and context-aware information delivery. This structured approach makes the system particularly suitable for real-time navigation and decision-making scenarios, where actionable insights are critical [8; 17; 18].
## 2 Materials and Methods
### miRNA Extraction, cDNA Synthesis and qPCR  
The NucleoSpin miRNA Plasma kit (Macherey-Nagel GmbH & Co. KG., Duren, Germany) was employed to extract six circulating miRNAs from 200 \(\mu\)L serum samples. Following the assessment of RNA concentration and purity, cDNA synthesis was carried out on 90 ng of RNA. This process involved the use of stem-loop primers for miR-451a, miR-15a-5p, miR-320-5p, miR-28-5p, miR-103a-5p and miR-194-5p, and U6 reverse primers as the endogenous reference control (Table 1), via the RevertAid First Strand cDNA Synthesis kit (Thermo Fisher Scientific, Waltham, MA, USA). Luna Universal qPCR Master Mix (New England BioLabs, Ipswich, MA, USA) was used for quantitative PCR (qPCR), along with 3 \(\times\) diluted cDNA templates, miRNA-specific forward primers, a universal reverse primer, and U6 forward and reverse primers (Table 1). Triplicate runs were performed for all qPCR reactions. To mitigate batch effects and control experimental variability, we divided our qPCR reactions into two batches: the first batch included 17 PCOS samples, 6 HC samples, and 4 HAC samples; the second batch included 17 PCOS samples, 5 HC samples, and 4 HAC samples. The 2\({}^{-\Delta\Delta\text{Ct}}\) method was employed to determine the comparative expression levels of miRNAs. We performed two separate comparative analyses of miRNA expression: HC vs. PCOS and HAC vs. PCOS. For the first comparison, miRNA fold-change values in PCOS patients were calculated using HC as the reference group. For the second comparison, miRNA fold-change values in PCOS patients were calculated using HAC as the reference group. For conducting qPCR analyses, the QuantStudio 5 Real-Time PCR system (Applied Biosystems, Waltham, MA, USA) was used.
# Mapping irrigated Areas Using Sentinel-1 Time Series in Catalonia, Spain
## Materials
### SIGPAC Data  
SIGPAC data provides referenced geographic boundaries of plot land in Catalonia attributed with alphanumeric information. The data are produced and maintained by the General Direction of Rural Development of the Department of Agriculture, Livestock, Fishing and Food of the Generalitat of Catalunya. The plots are digitized using orthophoto images of 25-cm spatial resolution at scale 1:2000. Group of fields are associated in the database of the provided geographical data describing each plot by a unique identification code, surface area, land use, irrigation coefficient (0 for non-irrigated and 100 for irrigated), average slope and others. The SIGPAC data can be freely downloaded for the whole region in vector format [40]. For each plot, the crop type could be obtained from the agricultural crop map of Catalonia (DUN). This map is produced based on the SIGPAC geographic boundaries and the annual declaration of the agricultural exploitation. The agricultural map of Catalonia is also available in free and open access mode [40].  
In this study, SIGPAC data was used as a reference and validation of our proposed classification approaches. In our study, only agricultural crops (summer and winter crops) were considered for the irrigation classification. Forests, urban and orchards plots were removed from the SIGPAC database using the DUN crop map. Finally, a total of 193,327 plots of different crop types were used in the study forming a total area of 3795 km\({}^{2}\). The pie chart of Figure 3 summarizes the distribution of dominant crop types present in the studied zone. It shows the number of plots per crop type present in the study area. In general, winter cereals such as wheat, oat and barley are rarely irrigated. However, it may happen that these crops are exceptionally irrigated very few times. On the other hand, irrigated plots mainly include alfalfa, maize, grassland, beans, rapeseed and rice.
# Numerical Study on Track-Bridge Interaction of Integral Railway Rigid-Frame Bridge
## 4 Analysis of Additional Longitudinal Forces
### Additional Braking Force  
The calculating models of the live load were the same as the model stated in Section 4.2, and the braking coefficient of the HSR train was set as 0.164 [29,30]. The braking load can be calculated as q = 0.164 \(\times\) q\({}_{\text{zk}}\) =0.164 \(\times\) 64 kN/m = 10.5 kN/m. In the calculation, the braking load was only applied on one single line, as there is little possibility of trains braking on both lines of the bridge at the same time. The rightward braking loads of the HSTs were regarded as the positive direction, and vice versa. Furthermore, based on the consideration that Chinese high-speed trains basically consist of either 8 or 16 carriages, with a total length of about 200 m or 400 m, two calculation conditions with different loading positions were adopted herein: condition I: the braking load is positioned over the middle integral bridge (from pier 4 to pier 7); and condition II: the braking load is positioned over the middle and right integral bridges (from pier 4 to pier 10).  
When the train braked in the middle bridge (condition I), the maximum additional braking stress of the rail occurred at the two beam ends of the middle rigid-frame bridge, with the value of \(-\)26.5 MPa/26.9 MPa, as shown in Figure 12. However, the maximum additional stress of condition II appeared at the ends of the load position (piers 4 and 10), with the value of \(-\)55.6 MPa/36.8 MPa. After adopting the small resistance fasteners, the maximum additional braking stress of the rail decreased by 4.0%/3.8% under condition I and by 10.3%/19.6% under condition II.  
Figure 11: Additional bending force of rails: (**a**) under a single-line train; (**b**) under double-line trains.  
Figure 12: Additional braking force of rails under different braking conditions: (**a**) condition I; (**b**) condition II.  
With regard to the relative displacement between the rail and the beam, UIC code 774\(-\)3R [8] clearly requires that the relative displacement under the action of braking force should not exceed 5 mm. As shown in Figure 13, the relative displacements under condition I were less than those for condition II. Under condition II, the maximum relative displacement between the rail and the beam was 3.11 mm when WJ-8 fasteners were adopted. After small resistance fasteners were adopted, the relevant maximum value was 3.48, with an increase of 11.9%.
# Chemical Speciation of Antarctic Atmospheric Depositions
###### Abstract
Within this framework, the goal of the present work is (i) to provide quantitative information about the components of the atmospheric depositions in the Antarctica, and (ii) to propose a chemical model based on the interaction between the main components, with the final target of identifying the key species occurring in wet depositions, or in the soluble fraction of dry depositions. Particular attention was paid to those cations showing bioactivity and/or photo-activity. The results will direct further investigations on the definition of the formation constants of metal complexes, under temperature and ionic strength values that best suit atmospheric processes. In a project carried out within the National Research Program in the Antarctica (PNRA), entitled \"Spatial and temporal (intra- and inter-annual) evolution of the chemical composition of the aerosol in the Victoria Land (Antarctica) in relation with local and long-range transport processes\", atmospheric depositions were collected during the Antarctic summer 2017-2018. Only dry depositions actually occurred in the mentioned period and, therefore, analyses were conducted on the dissolved fraction after dissolution. Some cations were quantified by elemental analysis (Inductively Coupled Plasma--Optical Emission Spectroscopy, ICP-OES, or High Resolution--Inductively Coupled Plasma--Mass Spectroscopy, HR-ICP-MS), whereas anions, main cations, and ammonium were quantified by Ionic Chromatography, IC. The components of the samples considered in the chemical model are: Na\({}^{+}\), K\({}^{+}\), NH\({}^{+}\), Ca\({}^{2+}\), Mg\({}^{2+}\), Cu\({}^{2+}\), Mn\({}^{2+}\), Zn\({}^{2+}\), Fe\({}^{2+/3+}\), Cl\({}^{-}\), NO\({}_{3}\)\({}^{-}\), SO\({}_{4}\)\({}^{2-}\), PO\({}_{4}\)\({}^{3-}\), HCOO\({}^{-}\), and CH\({}_{3}\)COO\({}^{-}\), together with the species formed by their interactions. Hydrolytic species of the cations and dissociation constants of the protogenic components were also considered in the model. As a first approximation, the formation constants used here were those defined at 25 \({}^{\circ}\)C, because many formation equilibria have not yet been studied at lower temperature. The estimated ionic strength of the samples under study was very low, which allows for the use of thermodynamic formation constants (T = 298.15 K, I = 0 mol L\({}^{-1}\)).
## 3 Methodology
### Flood and Permanent Water Mapping  
All S1A images in the year of 2018 were collected to determine permanent water surface while a NRT S1A image during or after heavy rain was processed to create the NRT flood map. All S1A images were pre-processed by a similar procedure to that mentioned in Section 3.1. The VV channel was first evaluated with VH and then used for permanent water mapping [61]. Meanwhile, VH data were utilized for flood mapping because they are more sensitive than the VV channel for plant surface. When flooding occurs, the backscatter coefficient value of the VH channel will significantly decrease compared to the backscatter coefficient value of the plant surface [62].  
The Otsu thresholding method was adapted to distinguish the water surface from other surfaces [63]. The Otsu algorithm is a binary classification algorithm, which performs a comparison of all pixel values of a grayscale image with a threshold value. Pixels with values less than the threshold will be assigned to the background layer, while the others are classified as the foreground class. The idea of the Otsu algorithm is to find this threshold automatically when the within-class variance is minimal or between-class variance is maximal. After the temporal water map was calculated by adapting the Otsu method, morphological transformation techniques including an opening and closing operations were performed [64]. In particular, the opening transformation was applied to remove noises while closing transformation closes small holes or removes small points inside the object. In some high-mountain forest areas (the North region of Vietnam), the terrain shadows in some areas confuse with the surface water due to its low backscatter values. Therefore, a Digital Elevation Model (DEM) map was used to remove hilly areas that were misclassified into water surfaces. An empirical threshold was selected for the DEM map to differentiate the valley area which is affected by high mountain shadow. In this study, we used the DEM Shuttle Radar Topography Mission (SRTM) map from the U.S. Geological Survey (USGS) [65] with a spatial resolution of 30 m. Based on temporal water maps, permanent water, such as rivers, big lakes and watercourses, was extracted. If a pixel was classified as water for every single image in a month, it was labeled as permanent water for that month only. This process was repeated for available S1A data in 12 months of 2018 respectively to produce 12 monthly permanent water maps. Flooding was assumed to be a phenomenon of water surfaces appearing in a short time, while permanent water oppositely holds water for a long time. Flood maps would be obtained by excluding permanent water pixels from a temporal water map any time. The flood mapping process was deployed using a cloud computing platform provided by the Google Earth Engine.
# Advanced Technologies in Optical Wireless Communications
## 2 Visible-Light Communication (VLC)  
Indoor VLC is an important form of OWC that uses white-light-emitting diodes (LEDs) for indoor illumination and wireless data transmission simultaneously. The performance of a VLC system depends on various factors [6], including the characteristics of the LED transmitters, the sensitivity of the photodetector (PD) receivers, the optical components integrated into the system, and the signal modulation schemes used. Moreover, in a transmission system with multiple LED transmitters, the spatial configuration and alignment of the transmitters and receivers also play an important role in determining overall system performance.  
This Special Issue presents five articles related to VLC. Like other communication systems, the performance of a VLC system is influenced by the bandwidths of both the LED transmitter and the electronic circuits used to drive the LEDs. To enhance the bandwidths of LED transmitters, Contribution 1 investigates how different crystal orientations of the GaN structure impact the light emission lifetime of LEDs and, consequently, their modulation bandwidth. Contribution 2 focuses on improvements to the LED driving circuit, particularly enhancements to boost/buck DC-DC converters.  
Another notable challenge in VLC is mitigating interference from adjacent LED transmitters. Contribution 3 explores the use of a liquid lens to adjust the receiver's field of view (FOV), therefore reducing interference from nearby transmitters. In transmission scenarios involving multiple LED transmitters, the layout of these LEDs is crucial and must also satisfy illumination requirements. Contribution 4 investigates the optimization of LED layout while considering practical illumination distribution constraints. Finally, Contribution 5 presents a study on the channel characterization of visible-light bands in an industrial scenario and compares it with that of RF bands.
## 3 Confirmation of Single Additive Properties
### Single Additive Test Results
#### 3.3.3. Eva  
As shown in Table 9 below, as the amount of EVA added increased, the water-soluble rubber-asphalt-based waterproofing material whose properties were checked by adding only EVA showed that the tensile strength, tear strength, solid content, and viscosity decreased. This is considered to be due to the low crystallinity of EVA (the ratio of the weight of the crystalline part in the total center of the polymer material) and the improvement of the elongation due to elasticity. However, at the addition ratios of 2.0% and 2.5%, as the rates of increase of tensile strength, elongation, and tear strength were similar, only the solid content and viscosity increased. Therefore, in the case of EVA, it is considered that the use of 2.0% or less is required in the composite additive.  
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline  & \multicolumn{2}{c}{**Tensile Strength**} & \multicolumn{2}{c}{**Elongation**} & \multicolumn{2}{c}{**Tear Resistance**} & \multicolumn{2}{c}{**Solidity Ratio**} & \multicolumn{2}{c}{**Viscosity**} \\
**Item** & **Result** & **Change** & **Change** & **Change** & **Change** & **Change** & **Change** & **Change** & **Change** & **Change** & **Result** & **Change** \\
**(Code)** & **Result** & **from** & **Result** & **from** & **Result** & **from** & **Result** & **from** & **Result** & **from** \\
**(N/mm)** & **STD** & **(\%)** & **STD** & **(N/mm)** & **STD** & **(\%)** & **STD** & **(\%)** & **STD** & **(mPa-s)** & **STD** \\
**(N/mm)** & **STD** & **(\%)** & **(\%)** & **(\%)** & **(\%)** & **(\%)** & **(\%)** & **(\%)** & **(\%)** & **(\%)** \\ \hline STD & 0.33 & - & 1352 & - & 3.21 & - & 73.33 & - & 522 & - \\ SCA 0.3 & 0.57 & 173 & 1044 & 77 & 5.31 & 165 & 79.33 & 108 & 726 & 139 \\ SCA 0.6 & 0.63 & 191 & 997 & 74 & 6.34 & 198 & 80.67 & 110 & 1297 & 248 \\ SCA 0.9 & 0.7 & 212 & 906 & 67 & 7.02 & 219 & 82.67 & 113 & 1840 & 352 \\ SCA 1.2 & 0.78 & 236 & 832 & 61 & 7.67 & 239 & 84 & 115 & 2715 & 520 \\ SCA 1.5 & 0.81 & 245 & 711 & 53 & 8.24 & 257 & 85.33 & 116 & 3313 & 635 \\ \hline \hline \end{tabular}
\end{table}
Table 7: Physical property results according to the amount of silane coupling agent added and increase/decrease rate compared to STD.  
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline  & \multicolumn{2}{c}{**Tensile Strength**} & \multicolumn{2}{c}{**Elongation**} & \multicolumn{2}{c}{**Tear Resistance**} & \multicolumn{2}{c}{**Solidity Ratio**} & \multicolumn{2}{c}{**Viscosity**} \\
**Item** & **Result** & **Change** & **Change** & **Change** & **Change** & **Change** & **Change** & **Change** & **Change** & **Change** & **Change** & **STD** \\
**(Code)** & **Result** & **from** & **Result** & **from** & **Result** & **from** & **Result** & **from** & **Result** & **(mPa-s)** & **STD** \\
**(N/mm)** & **STD** & **(\%)** & **(\%)** & **(\%)** & **(\%)** & **
# Computer Vision and Image Processing Approaches for Corrosion Detection
## 4 Corrosion Detection Approaches
### Wavelet Domain  
Wavelet domain is a zero-averaging fast decaying technique using both frequency and spatial domains. It can be used to measure the corroded regions in an image. The minimization of entropy is used for illumination component correction in the corrosion image. Then, the wavelet transform is applied to the RGB channels to measure the entropy and energy values. The feature vectors are extracted, thus allowing the accurate detection of corroded regions. It is possible to recover noisy corrosion images without muddling or blurring the details of the corrosion in the image.  
The wavelet image coefficient [63] on the grid metal frame was studied to determine the atmospheric corrosion characteristics. This metal frame was used for power transmission in Chongqing. The structural materials were investigated in terms of corrosion product, quantity, and morphology using the wavelet transform algorithm. The images of the detection results were evaluated using the on-site samples which were consistent with the actual corrosion progression. Moreover, wavelet analysis [64] was used to determine the effect of nitrogen for pitting corrosion. The standard deviations of the partial signal and energy distribution were used to measure the energy of the low frequency signal. The hybrid wavelet packet transform [65] was combined with the support vector classifier for carbon-steel pipeline corrosion detection. The corrosion grades were predicted and determined using fast Fourier transform. This technique was evaluated with the linear polarization resistance (LPR) laboratory test to determine its prediction accuracy. The results showed that the proposed technique was effective for the detection and assessment of corrosion. The similar 2D-wavelet filtering technique can be used for damage detection in structures [66].