esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Lead, Cobalt and Nickel Concentrations in the Water Column
The coastal zones of the lake water area in the surface layers are subjected to intensive nickel pollution under the influence of inflowing rivers, up to 41.6-49.0 \(\mathrm{\SIUnitSymbolMicro g}\)/L at points 11 and 12 (Matabai River--24.7 \(\mathrm{\SIUnitSymbolMicro g}\)/L), up to 47.2 \(\mathrm{\SIUnitSymbolMicro g}\)/L at point 10 (Zhirelka River--77.1 \(\mathrm{\SIUnitSymbolMicro g}\)/L), up to 37.8 \(\mathrm{\SIUnitSymbolMicro g}\)/L at point 16 (Tikhushka River--39.7 \(\mathrm{\SIUnitSymbolMicro g}\)/L), and up to 35.9 \(\mathrm{\SIUnitSymbolMicro g}\)/L at point 3 (Yelovka River--84.6 \(\mathrm{\SIUnitSymbolMicro g}\)/L) (Figures 2 and 3). No definite regularity of nickel pollution present in bottom water layers can be traced from the lake depth or from the influence of inflowing rivers. In addition, there is no correlation in the concentrations of cobalt (r = \(-\)0.02) and nickel (r = 0.06) between the water layers, as well as in the coefficients of determination (Figure 2), which is associated with the different physical and chemical properties of the metals and processes occurring in the water, such as geological, anthropogenic, chemical factors, and sedimentation or complexation, affecting the distribution of metals in different layers. There is an increase in nickel and cobalt concentrations in the tributaries of both the northern and the southern parts of the lake, exceeding fishery standards by tens of  
Figure 3: Lead, cobalt and nickel concentrations in river water of the study area. Figure 2: Lead (Pb), cobalt (Co) and nickel (Ni) concentrations in the water column of Lake Markakol and the correlation of their concentrations between water layers (dotted lines–trend lines). times, both at the inflowing rivers and at the outflow of the Kalzhyr River. The metal-contaminated water masses of the Kalzhyr River, originating from Lake Markakol, flow into one of the major rivers of Central Asia, the Irtysh (Yertis) River (Figure 3). High values of cobalt and nickel in the aquatic environment and their localization in deep bottom water layers may indicate various processes and factors affecting the structure of these metals in the lake, such as the geological structure and composition of rocks around the lake, which are dominated by minerals rich in these metals, which may lead to their leaching into the water. Consequently, the rich rock deposits of cobalt-mickel ores found in Eastern Kazakhstan, \"Gornostaevskoye\" and \"Belogorskoye\", belong to the silicate-type containing Ni (1083-2482 g/t) and Co (50-72 g/t), are responsible for reversing the effect of natural-anthropogenic pollution in relation to the ecosystem of the water bodies in the eastern region, increasing the technogenic load on the water bodies [38; 39; 40; 41].
## 2 Our Contribution  
In essence, this work contributes in the following ways:  
* The ESRVR algorithm is proposed for sparsely deployed WUSNs, which provides reliability in packets' delivery by finding connected paths up to two hops. That is, a sender node selects a routing path that involves two relay nodes without any presence of a void-hole. If a void-holeexists, the backward transmission mechanism is used by the sender node. In this mechanism, a sender node finds other nodes towards the sea surface that are at the same or a higher depth than the sender node, but have path connectivity up to two hops. These two strategies overcome packets' loss and improve reliable advancement of information towards the sea surface. The two hop connectivity is chosen because one hop connectivity cannot identify the presence of a void-hole beyond the transmitter-receiver nodes pair. At the same time, more than two hop connectivity is difficult to establish in sparse conditions.
* The uniqueness of the time for which a node holds a packet ensures that low power nodes do not hold packets for a long time to avoid packets loss. Furthermore, it ensures that nodes with a low count of neighbors or no neighbors at all hold the packet for a long time. This is because in sparse conditions, nodes do not have enough neighbors to forward packets further towards the sea surface. Therefore, nodes wait unless one or more suitable neighbors are available in their vicinity due to water currents and tides. These strategies contribute to reliable advancement of packets to the end target.
* The ESRVR protocol routes information via only one link, which may not be always reliable since the sea channel is harsh. Therefore, the concept of cooperative routing is further combined with ESRVR, which leads to the development of the Co-ESRVR algorithm, which uses the source-delay-destination triplet; instead of only the source-destination pair as in ESRVR, so that packets are routed over multiple paths. Therefore, if some of the paths get corrupted by adverse channel characteristics, others may not be. Consequently, the probability of reliable advancement of packets to the end target is enhanced.
* When adverse channel characteristics are coped with by the development of Co-ESRVR, the complexity in electronic circuitry required to process such signals reduces, which in effect, relaxes the requirement of highly sophisticated and expensive circuitry.
* Unlike the approach existing in the literature, the construction of routing paths and the backward transmission mechanism are independent of the distance from the sea surface or the geographical coordinates of nodes, which reduces the computational complexity and increases network scalability. This is because nodes move with sea tides and currents and often change their positions. Therefore, determining the distance or geographical positions of nodes becomes cumbersome and computationally inefficient.
* Based on the simulation analysis, the proposed algorithms are suitable for applications that involve reliability in data transfer such as military applications and disaster detection.
# Two-Dimensional Interference Estimator with Parallel Structure for Holographic Data Storage Channel
## 4 Proposed Model  
The model proposed in this study is shown in Figure 2. The original data \(u[k]\) are modulated into the data page \(a[j,k]\), using a spatial light modulator (SLM), and stored in the HDS channel. The received data \(y[j,k]\) is equalized into signal \(z[j,k]\) using equalizer \(\mathbf{F}\). Signal \(z[j,k]\) is used to estimate LRI and ULI. Thereafter, we can remove the interference from signal \(z[j,k]\) and apply SOVA to recover \(\hat{a}[j,k]\). Finally, \(\hat{a}[j,k]\) is demodulated to restore the original signal \(\hat{u}[k]\). In Figure 2, the dashed line represents the signal during the training process. It did not work during the testing process.
## 3 Research Methods
### Tracking and Speed Measurement Central-ByteTrack Module
#### 3.2.1 Transformation Between the World Coordinate System and the Image Coordinate System
The point \((X_{w},Y_{w},Z_{w})^{T}\) represents the origin of the world coordinate system, with \(R\) and \(t\) being the rotation matrix and translation vector between the two, and \(K\) is a constant. (3) The transformation relationship between the image pixel coordinate system and the world coordinate system. \[Z_{p} \begin{bmatrix}u\\ \
u\\ 1\end{bmatrix} = \begin{bmatrix}\frac{1}{2x}&0&u_{0}\\ 0&\frac{1}{4y}&v_{0}\\ 0&0&1\end{bmatrix}\begin{bmatrix}f&0&0&0\\ 0&f&0&0\\ 0&0&1&0\end{bmatrix}\begin{bmatrix}R&t\\ T&1\end{bmatrix}\begin{bmatrix}X_{w}\\ Y_{w}\\ Z_{w}\\ 1\end{bmatrix}  \tag{5}\]  
This equation is obtained by combining Equations (1)-(4). This conversion mechanism serves as a crucial foundation for drilling debris speed detection, enabling the reconstruction of debris trajectories, obtained using the ByteTrack algorithm, in the real-world space. By incorporating time information, it calculates the actual movement speed of the debris, thereby significantly enhancing the accuracy and practicality of the unmanned drilling rig's intelligent monitoring system.
# Numerical Analysis of Friction Reduction of Grouting in Long-Distance Pipe Jacking
###### Abstract  
During pipe jacking construction, in addition to overcoming the resistance at the front, there is also the need to overcome significant frictional resistance. Grouting technology is commonly used in engineering to reduce the frictional resistance exerted on the pipe's external surface during the jacking process. This paper first reviews the commonly used grouting materials and processes, summarizes their mechanisms for friction reduction, and then establishes a numerical analysis model for grouting in pipe jacking, enhancing the common theoretical methods based on simulation results. The study employs different interface reduction coefficients to simulate the different effects of friction reduction by grouting, focuses on the impact of grouting on friction reduction during long pipe jacking, and compares the results with those calculated using common methods. The results show that the frictional resistance around the pipe is the main source of jacking force in long-distance pipe jacking, and the jacking force increases approximately linearly with the interface reduction coefficient.  
long-distance pipe jacking; grouting friction reduction; jacking force; interface reduction coefficient 2025  
15 1782
# Research on Risk Assessment Method for Land Subsidence in Tangshan Based on Vulnerability Zoning
## 3 Hazard Assessment Results for the Study Area  
### Construction of Hazard Assessment Index System for Ground Subsidence  
The hazard assessment model for ground subsidence in this study integrates the analytic hierarchy process (AHP) and the information value model. This model takes into account a variety of natural, engineering, and triggering factors that contribute to ground subsidence in the study area. A total of 12 evaluation indicators have been identified and incorporated into the Urban Ground Subsidence Hazard Assessment Index System, as depicted in Figure 9.  
The hazard assessment is structured across three levels: the evaluation objective level, the evaluation criterion level, and the evaluation indicator level. The evaluation objective level is centered on the assessment of the urban ground subsidence hazard. The evaluation criterion level is divided into three categories: natural factors, engineering factors, and triggering factors. The natural factors comprise four evaluation indicators: the lithology, quaternary groundwater, geological faults, and proximity to water systems. The engineering factors include four evaluation indicators: the road load, distribution of subsidence areas, distribution of mined-out areas, and road network density. The triggering factors incorporate four evaluation indicators: the rainfall impact, underground pipeline leakage, earthquake-induced liquefaction, and seismic acceleration.  
The construction of this comprehensive evaluation index system for the ground subsidence hazard enables the calculation of the single-factor information entropy for each evaluation indicator. By integrating the weights derived from the analytic hierarchy process (AHP), a classification map of the ground subsidence hazard for the study area was produced. This approach provides a holistic and nuanced assessment of the ground subsidence hazard, reflecting the multifaceted nature of the phenomenon.
# Three-Dimensional Broadband and Isotropic Double-Mesh Twin-Wire Media for Meta-Lenses
###### Abstract  
Lenses are used for multiple applications, including communications, surveillance and security, and medical instruments. In homogeneous lenses, the contour is used to control the electromagnetic propagation. Differently, graded-index lenses make use of inhomogeneous materials, which is an extra degree of freedom. This extra degree of freedom enables the design of devices with a high performance. For instance, rotationally symmetric lenses without spherical aberrations, e.g., the Luneburg lens, can be designed. However, the manufacturing of such lenses is more complex. One possible approach to implement these lenses is using metamaterials, which are able to produce equivalent refractive indices. Here, we propose a new type of three-dimensional metamaterial formed with two independent sets of wires. The double-mesh twin-wire structure permits the propagation of a first mode without cut-off frequency and with low dispersion and high isotropy. These properties are similar to periodic structures with higher symmetries, such as glide symmetry. The variations of the equivalent refractive index are achieved with the dimension of the meandered wires. The potential of this new metamaterial is demonstrated with simulated results of a Luneburg meta-lens.  
blide symmetry; meta-lens; double-mesh; wire medium; broadband response; isotropic response; metamaterials; Luneburg lens +
Footnote †: journal: Applied Sciences
# Challenges, Threats, Security Issues and New Trends of Underwater Wireless Sensor Networks
## 3 Threats and Challenges in Underwater Wireless Sensor Networks (UWSNs)
### DoS Attacks
#### 3.3.3 Network Layer  
Network layer is responsible for routing packets from the source node to the destination node. Owing to the particularities and constraints discussed in Section 2, the network layer is vulnerable to many threats and attacks which aim to disturb the routing of the network, including the _Replay Attack_, _Selective Forwarding Attack_, _Neglect and Greed_, _Misdirection Attack_, _Black hole/Gray hole Attack_, _Sinkhole Attack_, _Wormhole Attack_, _Sybil Attack_, _Hello Flooding Attack_, and _Homing Attack_.
## 2 Materials and Methods
### Synthesis of 1, 3 Indandione (**1**)  
Intermediate **1** was prepared in a similar fashion as reported in our previous work [13]. In a round bottom Schlenk flask, benzoyl chloride (0.913 g, 6.496 mmol), malonyl chloride (0.915 g, 6.496 mmol) and dry AlCl\({}_{3}\) (2.598 g, 19.490 mmol) were dissolved in anhydrous nitrobenzene (50 mL) and stirred at 80 \({}^{\circ}\)C for 8 h under argon atmosphere. After refluxing and cooling, the mixture was poured into an aqueous solution of Na\({}_{2}\)CO\({}_{3}\) (120 mL). The organic layer was extracted with dichloromethane (4 \(\times\) 50 mL), acidified with aqueous HCl (80 mL), separated by diethyl ether (2 \(\times\) 80 mL) and later dried over Na\({}_{2}\)SO\({}_{4}\). Applying flash column chromatography, the organic crude product was purified using a mixture of diethyl ether:hexane (1:5, _v/v_) as eluent, followed by drying in a vacuum oven at 70 \({}^{\circ}\)C. The recrystallization of the obtained product was carried out in diethyl ether: EtOH (1:5, _v/v_) and finally collected as a pale yellow solid product (yield 67.09%, 0.637 g). \({}^{1}\)HNMR (500 MHz, CDCl\({}_{3}\), ppm) 8: 7.94 (dd, J = 2.6 Hz, 2.3 Hz, 2H), 7.82 (dd, J = 2.6 Hz, 2.3 Hz, 2H), 3.23 (s, 2H). \({}^{13}\)CNMR (100 MHz, CDCl\({}_{3}\), ppm) 8: 197.57, 143.40, 135.68, 123.27, 45.12. MS: m/z calc. for [C\({}_{9}\)H\({}_{6}\)O\({}_{2}\) + H]\({}^{*}\): 147.14. Found: 147.13.
## 5 Conclusions  
In this paper, analytical solutions of the longitudinal equivalent bending stiffness (LEBS) for a shield tunnel are first derived considering the residual jacking force and bending moment. Then, the calculated results of two well-documented cases are both compared with the calculated results of the solution degenerated into the special case with no residual jacking force, which proved the feasibility of the presented method. Finally, using the solution, sensitivity analyses of the bending moment, tunnel geometry, tensile stiffness for bolts, and lining concrete grade are carried out on the LEBS and effective ratio of LEBS of a tunnel with consideration of residual jacking force. From the theoretical research conducted on the LEBS of a shield tunnel, the following conclusions can be made:  
1. It is demonstrated that the proposed method can better evaluate the LEBS for a tunnel. This work reveals a mechanism of the residual jacking force affecting LEBS and the effective ratio of LEBS for a tunnel. Because the residual jacking force changes the contact area between tunnel lining, which increases linearly at first, and then nonlinearly, the LEBS and the effective ratio of LEBS increase linearly and nonlinearly in the S-curve. The LEBS and the effective ratio of LEBS decrease with increasing bending moment, but which do not affect the maximum and minimum LEBS;
2. The influential order on the LEBS of shield tunnels is the tunnel diameter > lining thickness > bolts diameter > ring width > the number of bolts > elastic modulus of bolts. When the contact area between tunnel lining reaches 85% (i.e., the effective ratio of LEBS is more than 0.85), the parameters of ring width, tunnel lining thickness, tensile stiffness for bolts, and lining concrete grade have little influence on the stiffness. The effect of the lining concrete grade on the LEBS and the effective ratio of the LEBS is not significant;
3. When a new tunnel undercrossing occurs in an existing tunnel, it is advised to increase the longitudinal compressive stress (residual jacking force) of the existing tunnel by setting some engineering measures conducive to improving the LEBS of the existing tunnel and reducing the longitudinal deformation of the shield tunnel. In this paper, the response characteristics of the tunnel parameters on the LEBS considering the residual jacking force could provide a theoretical basis for the design and deformation control of shield tunnels when undercrossing tunnelling.  
Methodology, software, validation, writing--original draft preparation, X.J.; supervision, conceptualization, project administration, WL.; writing--review and editing, B.Z.; investigation, J.Y.; resources, T.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Science Foundation of China (grant number No. 52225210), National Science Foundation of China (grant number No. 51978265), National Science Foundation of China (grant number No. 41972291), and Science and Technology Research Project of Education Department of Jiangxi province (grant number No. GJJ2205312).
## 2 Materials and Methods
### Change Detection Analysis  
This study employed post-classification comparison, a widely used change detection method, implemented through QGIS 3.36 and ArcGIS Pro 2.8.0 post-processing tools. This approach has been shown to accurately represent land use changes in previous studies [53; 54]. Change detection was carried out within the two areas, their consecutive conservation units, and buffer areas.  
The analysis involved cross-tabulating classification results for consecutive years (2018-2019, 2019-2020, 2020-2021, 2021-2022, 2022-2023) and the overall study period (2018-2023). This process identified how each land cover class changed between consecutive years and between the initial and final dates of the study period. Transition maps were then generated to visualize these changes, providing a spatial representation of land cover dynamics. To calculate changes inside conservation units, polygons representing the boundaries of the units were used to extract LULC change information and summarize deforestation and forest degradation.  
To assess the frequency of change, all six LULC maps were combined into a single raster in ArcGIS 2.8.0 Pro using the Combine tool. Each unique combination of LULC classes across all maps was assigned a unique value, with class pixel value information remaining for each year, which was organized in columns, or \"fields\", in the raster's attribute table. Using Field Calculation, new columns were created and changes were calculated between consecutive years. Pixels that underwent changes were assigned a value of 1, while pixels with no changes were assigned a value of 0. Subsequently, this information was aggregated, and a new raster was created using the Frequency tool to summarize the change frequency across the study areas. The tool sums all changes that occurred over the years, assigning each pixel a value between 0 (no changes) and 5 (changed every year), providing a comprehensive view of landscape dynamics throughout the study period.
## Methods
### Analysis
#### 2.5.3 Event-Related Potentials  
Brain potential changes were recorded at a rate of 2048 samples/s using a 64-channel BioSemi Active Two system and ActiView software (BioSemi, Amsterdam, The Netherlands). Data sets were batch processed using EEG-Display (version 6.4.8; Fulham, Newcastle, Australia). During processing the sampling rate was reduced to 256 samples/s and a band pass filter of 0.1 to 30 Hz was applied. ERP epochs were defined in relation to the presentation of each IAPS image from \(-\)100 ms pre- to 1000 ms post-stimulus onset. All epochs were baseline corrected with the correction occurring 100 ms prior to stimulus onset and data points along the ERP were reduced to 15 data points along the first second post-stimulus presentation for further statistical analysis. A Repeated Measures ANOVA was used to analyse ERP amplitudes at each time point using the within-subject factors _emotion_ (pleasant, unpleasant, erotic, violent, and neutral) and _hemisphere_ (left, right).  
Upon visual inspection, it was observed that the main differences between each group were obviously occurring for the ERP curves of the \"Violent\" and \"Erotic\" condition relative to other conditions, and so these two emotion categories were used as references for the contrasts. To correct for violations of sphericity, the Greenhouse-Geisser procedure was utilised. Simple contrasts were used to determine the direction of any significant main effects.
# Urban Road Anomaly Monitoring Using Vision-Language Models for Enhanced Safety Management
## 2 Methods
### Data Collection and Annotation
GREEN signifies optimal safety with no anomalies, allowing for no more than 10 mm of standing water. LIGHT GREEN indicates minor issues such as traffic congestion, garbage accumulation, or slight flooding, advising drivers to exercise caution and necessitating minor interventions like waste removal or drainage improvements. YELLOW denotes severe problems, including road damage, fires, deep flooding, or accidents, advising drivers to avoid the area and requiring urgent actions such as road repairs or traffic rerouting. This classification provides a clear framework for road authorities and drivers to respond appropriately to varying road conditions, thereby enhancing safety and efficiency in urban environments [48]. To conduct the models' tests, we randomly selected 20% of the images from each type to form the test set after completing the dataset annotation. The distribution of images in the test set is as follows (Tables 3 and 4). \begin{table}
\begin{tabular}{c c c c} \hline
**No.** & **Safety Levels** & **Types** & **Description** \\ \hline \multirow{2}{*}{1} & \multirow{2}{*}{GREEN} & Normal & The road is in good condition, exhibiting no noticeable hazards, and has waterlogging measuring less than 10 mm, which facilitates normal traffic flow. \\  & & Flooding (depth \(\leq\) 10) & The presence of traffic congestion, garbage accumulation, and minor flooding (10 mm \(<\) depth \(\leq\) 150 mm) has a negligible impact on vehicular traffic. \\ \hline \multirow{2}{*}{3} & \multirow{2}{*}{YELLOW} & Bad road & \\  & & Fallen tree & Road damages, fires, substantial flooding (water \\  & & Fire & depth \(>\) 150 mm), or traffic accidents pose a significant \\  & & Traffic accident & threat to vehicular traffic flow. \\  & & Flooding (depth \(>\) 150 mm) & \\ \hline \end{tabular}
\end{table} 
Table 2: The urban road safety level annotations. \begin{table}
\begin{tabular}{c c c c c} \hline
**No.** & **Types** & **Number of Data Points** & **Number of Data Points** \\  & & **Points (Total)** & **(Training Dataset)** & **(Testing Dataset)** \\ \hline
1 & Bad road & 1068 & 854 & 214 \\
2 & Fallen tree & 1480 & 1184 & 296 \\
3 & Fire & 1523 & 1218 & 305 \\
4 & Flooding & 1598 & 1288 & 310 \\
5 & Garbage & 1819 & 1455 & 364 \\
6 & Normal & 3375 & 2700 & 675 \\
7 & Traffic accident & 2163 & 1730 & 433 \\
8 & Traffic jam & 2185 & 1748 & 437 \\  & Total & 15,211 & 12,177 & 3034 \\ \hline \end{tabular}
\end{table} 
Table 3: The training and testing datasets.