esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Technique** & **Application** & **References** \\ \hline Visible Reflectance (Vis-R) & \
\begin{tabular}{c} Individual of: \\ Pigments/elemental composition/degradation process \\ \end{tabular} & [28; 29] \\ \hline X-ray Fluorescence (XRF) & Elemental composition, painting techniques & [21; 22; 28; 29; 30; 31; 32; 33; 34; 35; 36; 37; 38; 39; 40; 41; 42; 43; 44; 45; 46; 47; 48] \\ \hline X-ray diffraction &
\begin{tabular}{c} [20; 31; 32; 33; 34; 35; 36; 37; 38; 39; 40; 41; 42; 43; 44; 46; 47; 48] \\ \end{tabular} \\ \hline X-ray absorption & Colors fading/Degradation process & [33; 34; 35; 36; 37; 38; 39; 40; 41; 42; 43; 44; 45; 46; 47; 48] \\ \hline X-ray synchrotron radiation & Colors fading/Degradation process & [33; 34; 35; 36; 37; 38; 39; 40; 41; 42; 43; 44; 48; 49; 55; 56; 57; 58] \\ \hline Induced X-ray emission (PIXE) & Compositional analysis & [59] \\ \hline Fourier Transform Infrared & Degradation process & [23; 24; 28; 31; 60; 61; 62] \\ \hline Raman Spectroscopy & Modern Art analysis & [28; 63; 64; 65] \\ \hline Infrared Spectroscopy & Elemental/organic substances characterization & [28; 49; 66] \\ \hline \hline \end{tabular}  
* A multi-technique approach is now common practice; this is why the same reference may be cited for multiple techniques.  
\end{table} 
Table 3: EM techniques of wider application nowadays for diagnosis, mostly on paintings and relative reference 1.  
standardized terminology. Furthermore, researchers such as [PERSON] et al. have reported difficulties related to protocol consistency and the reproducibility of results [83; 84]. The goal of this review is to provide a clear and practical guide to the most recent EM techniques used in CH, offering newcomers a structured path into this dynamic field without the burden of exhaustive research. The paper is structured as follows: Section 2 introduces the general principles of EM techniques. Section 3 presents the diagnostic EM techniques that have captured the attention of conservators, curators, museum directors, and scientists over the past two decades, proving to be the most effective in achieving safe, efficient, and long-lasting results. Section 4 focuses on the challenges and approaches in Modern and Contemporary Art. Section 5 explores terahertz (THz) technology, including THz spectroscopy and imaging and their respective subtypes. Section 6 examines the role of Artificial Intelligence (AI) in CH, including its subsets--Machine Learning (ML) and Deep Learning (DL)--and discusses associated ethical considerations. Section 7 presents the conclusions and outlines future prospects.
## 2 Materials and Methods
### Numerical Implementation  
The ICEM method is used to implement geometry models and generate a computational mesh. A two-dimensional mesh is adopted for solving the governing equations, and the simulations are performed using the ANSYS Fluent double precision solver. Other solvers supporting the VOF method may also be applicable. A second-order upwind scheme is employed for the discretization of the convective terms.  
To capture the turbulent mixing induced by vapor-liquid phase change, natural convection, and wall shear effects, the Shear Stress Transport (SST) k-\(\omega\) turbulence model is selected. This model combines the near-wall accuracy of the standard k-\(\omega\) formulation with the robustness of the k-\(\varepsilon\) model in the free-stream region, making it particularly suitable for buoyancy-driven and phase-change-dominated flows. Its ability to resolve flow separation, interface deformation, and recirculation zones ensures a more accurate prediction of mixing behavior and heat/mass transport inside the tank. The second-order upwind scheme is also used to discretize the turbulent kinetic energy and the specific dissipation rate equations.  
The pressure-velocity coupling is handled using the Pressure Implicit with Splitting of Operators (PISO) algorithm. The volume fraction equation is solved using the compressive scheme to preserve sharp interfaces. A time step of 0.001 s is used in combination with an implicit first-order time discretization scheme for transient simulation. Convergence is monitored via residuals, and all governing equations are considered to have converged when residuals fall below 10\({}^{-6}\).
## 5 Conclusions  
This paper proposes an effective method for detecting signed fingermark liveness to counter fingermark spoofing attacks and meet the needs of applications like judicial document authentication. The method is based on deep residual networks and multi-probability labels. The method combines the residual network structure and the multi-scale backbone structure to improve the accuracy of liveness detection. This is achieved through the use of a multi-probability label classification strategy, a multi-input score fusion strategy, and a model fusion strategy. The signed fingermark liveness detection method achieved a remarkable 99.17% success rate on the comprehensive dataset using different strategies, which was further improved to 99.30% after model fusion. These results demonstrate the method's high effectiveness. It is worth noting that the method can also handle signed fingermarks on special paper backgrounds, such as squares and stripes, in practical scenarios. In the future, we will study liveness detection algorithms for  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Type**} & \multicolumn{2}{c}{**SFNet after**} & \multicolumn{2}{c}{**Inception with**} & \multicolumn{1}{c}{**Slim-ResCNN**} \\  & & **Model Fusion** & **Patch-Label [21]** & **[24]** \\ \hline \multirow{4}{*}{Fake} & Glass glue & 96.38 & 91.30 & 81.88 \\  & Vulcanized Silicone & 97.73 & 93.18 & 75.14 \\ \cline{1-1}  & Glue & 98.96 & 91.67 & 83.32 \\ \cline{1-1}  & Emulsion & 92.96 & 89.63 & 72.59 \\ \cline{1-1}  & Bionic finger & 89.17 & 83.33 & 69.17 \\ \hline \hline \end{tabular}
\end{table}
Table 10: The performance of migration methods on unknown materials. Unit: %.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Model** & **Live** & **Fake** & **Overall** \\ \hline Slim-ResCNN [24] & 92.36 & 91.03 & 91.73 \\ An CNN architecture [25] & 82.13 & 84.47 & 83.24 \\ Inception with patch-label [21] & 98.57 & 98.14 & 98.37 \\ SFNet after model fusion & 99.15 & 99.46 & 99.30 \\ \hline \hline \end{tabular}
\end{table}
Table 9: The performance of migration methods on signed fingermark database. Unit: %.  
signed fingermarks with complex backgrounds to significantly improve the practicality of fingermark liveness detection.  
Conceptualization, Y.Z.; Methodology, Y.Z.; Software, Y.Z., Z.Z. and J.W.; Validation, Z.Z. and J.W.; Data curation, Y.Z.; Writing--original draft, Z.Z. and Z.C.; Writing--review & editing, Y.Z. and J.W.; Visualization, Z.Z. and Z.C. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China, 62102364, and the Natural Science Foundation of Zhejiang Province, LY22F020016.  
Not applicable.  
The data presented in this study are available upon request from the corresponding author. The data are not publicly available due to privacy.  
The authors declare no conflicts of interest.
# Dynamic UAV Inspection Boosted by Vehicle Collaboration Under Harsh Conditions in the IoT Realm
## 5 Simulation
### Experimental Setup
#### 5.1.3 Experimental Parameter Settings  
The target region \(\Omega(\Omega\
eq\emptyset)\) was defined as a square area with dimensions of 50 km by 50 km, where each side of the region measured 50 km. Within this region, 2000 data collection task points were randomly generated. Additionally, candidate anchor points were established at intervals of 2.5 km in both vertical and horizontal directions across the region. The starting point for the vehicle carrying multiple UAVs was positioned at the center of the region. The vehicle departed from this starting point, carrying 3 UAVs. The speed of the UAVs fluctuated randomly within the range of [7; 13] m/s, while the speed of the vehicle fluctuated randomly within the range of [10; 20] m/s. Furthermore, the communication distance and maximum single flight distance of the UAVs were both set to 15 km. The limitations and their impacts of these settings were as follows:  
1. Speed Fluctuation Range: The UAV speed fluctuated within [7; 13] m/s and the vehicle speed fluctuated within [10; 20] m/s. This range may not have fully captured extreme weather conditions, where UAV speeds could drop significantly lower or increase higher. In real-world applications, such extreme conditions could lead to longer task completion times and increased system inefficiency.
2. Communication Delay: The model assumes negligible communication delay between UAVs and the vehicle. However, in complex urban environments with high-rise buildings or in remote areas with poor signal coverage, communication delays could be significant, affecting the real-time performance of the system.
3. Battery and Communication Range: The model assumes that the vehicle has unlimited fuel and communication range. In practice, fuel limitations and communication range constraints could restrict the vehicle's ability to reach certain anchor points, necessitating more frequent refueling stops or the use of relay stations.  
This study primarily investigated the effects of varying the following parameters on algorithm performance: the number of task points, the range of the target area, and the number of UAVs. For these parameters, variations within specified ranges were set to observe their impact on algorithm performance. It is important to note that when one parameter varied, the principle of controlling variables was maintained by keeping the other parameters constant.
###### Abstract  
The importance of a reliable blade root connection has grown due to the higher-gravity-induced edgewise loads on the blade root that resulted from the recent increased size and weight of a wind turbine rotor blade. To avoid the loosening of a bolt joint connection or even consecutive blade failures, the stress concentration factor (SCF) at the bolt thread root that is sensitive to fatigue should be understood comprehensively. In this work, two-dimensional and three-dimensional finite element (FE) analysis methods were used to determine the SCF at the bolt threads both between an insert and a M42 bolt used for a large offshore blade, and between a M42 bolt and a nut. The effect of various geometric parameters on the SCF were also investigated, which included shank diameter, nut height, nut type, and relief cone. Results showed that the decreased diameter of a M42 bolt shank diameter was the dominant design driver in reducing the stress concentration factor by 40%, from 3.94 to 2.32. The round nut type was also a recommended factor to be implemented to connect bolts and inner pitch bearing with an additional 10% SCF reduction. The relief cones applied to bolt threads and insert threads also contributed to the reduction of SCF to 2.01, a 49% reduction in total. This work not only provides guidelines by which to choose the proper geometry of the bolt and nut for a large blade, but also could be beneficial in designing bolted joint connections of segment or modular blades.  
wind turbine rotor blade; stress concentration factor (SCF); insert; M42 bolt; relief cone +
Footnote †: journal: Applied Sciences
## 7 Conclusions  
Concerned with the threat of seismic liquefaction hazards in the deeply deposited saturated liquefiable soil along the Aksu-kashgar highway (which is currently under construction), the seismic subsidence, distribution of dynamic pore pressure, and excess pore pressure ratio were analyzed and compared.  
According to the embankment characteristics of the highway, and in order to address the liquefaction hazards in the deeply deposited saturated liquefiable soil, a subarea long-short gravel piles foundation reinforcement scheme was proposed. In this reinforcement scheme, a few long gravel piles were arranged in the foundation under the embankment's sides, while many short gravel piles were arranged beneath the middle of the embankment. This resulted in the formation of a special shielding region between the long gravel piles on the sides and below the short gravel piles in the middle. With this shielding effect, the subarea long-short gravel piles scheme not only eliminated liquefaction in the deeply deposited liquefiable soil, but they also had an outstanding advantage in that the total length of gravel piles was greatly reduced and, therefore, the project's cost was reduced.  
Implementation of the proposed reinforcement scheme along the Aksu-kashgar highway is an economical and effective measure to eliminate the large displacement caused by liquefaction. Moreover, this scheme will protect the highway from future earthquakes.  
Subarea long-short gravel piles schemes should be considered for reinforcing foundations susceptible to liquefaction. The anti-liquefaction reinforcement scheme suggested in this paper can not only eliminate the large ground displacement caused by earthquake liquefaction, but it also reduces project costs through the produced shielding effect.  
Figure 13: Shielding region and shielding effect.  
**Author Contributions:** Conceptualization, J.L. and R.L.; methodology, J.L.; software, R.L.; validation, S.Z., W.B. and Z.L.; formal analysis, J.L.; investigation, S.Z.; resources, R.L.; data curation, J.L.; writing--original draft preparation, J.L.; writing--review and editing, J.L. and W.B.; visualization, Z.L.; supervision, R.L.; project administration, R.L.; funding acquisition, R.L. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work was supported by the Key R & D program of Shaanxi Province (2020 ZDLGY07-03), and China Geological Survey (DD20190268).  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The data presented in this study are all available in the article.  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 3 Results
### Spatiotemporal Distribution of Normal and Extreme Climate Indices  
#### 3.2.1 Temporal Variation Characteristics  
The interannual variation of normal climatic and extreme factors in the desert steppe of the NFYS from 2001 to 2023 was shown in Figures S3-S5 of the supplementary document. During the observed period, the desert steppe of the NFYS demonstrated a pronounced trend toward warmer and drier conditions. Notably, the maximum temperature (T\({}_{\rm max}\)) and minimum temperature (T\({}_{\rm min}\)) exhibited upward trends, increasing at rates of 0.046 \({}^{\circ}\)C per year and 0.031 \({}^{\circ}\)C per year, respectively. Concurrently, the total annual precipitation (PP) displayed a downward trajectory, declining at a rate of 2.41 mm annually (Figure S3 of the supplementary document).  
As T\({}_{\rm max}\) and T\({}_{\rm min}\) increase, the extreme temperature indices exhibit a distinct trend characterized by a gradual rise in maximum temperature extremes and a corresponding decline in minimum temperature extremes, as illustrated in Figure S4 of the supplementary document. With upward trends of T\({}_{\rm Xx}\) (Max T\({}_{\rm max}\)) and T\({}_{\rm Nx}\) (Max T\({}_{\rm min}\)), and decline trends of T\({}_{\rm Xh}\) (Min T\({}_{\rm max}\)) and T\({}_{\rm Nn}\) (Min T\({}_{\rm min}\)), the DTR (Daily temperature range) demonstrates a significantly increasing trend at a rate of 0.01 \({}^{\circ}\)C/yr. The study also identified significant changes in temperature-related indices. The GSL (Growing season length) showed the most substantial increase at 0.38 d/yr, followed by CSDI (cold spell duration index) at 0.32 d/yr and WSDI (warm spell duration index) at 0.06 d/yr. These comprehensive observations collectively indicate a pronounced shift towards warmer climatic conditions in the NFYS desert steppe, characterized by increasing high-temperature events and decreasing cold-temperature occurrences, providing strong evidence of ongoing climate warming in the region.  
As precipitation gradually decreases, the extreme precipitation indices show a certain downward trend, as illustrated in Figure S5 of the supplementary document. These findings demonstrate a consistent reduction in both total precipitation amounts and precipitation intensity within the desert steppe of the NFYS. The simultaneous increase in CDD coupled with decreases in various precipitation indices strongly suggests an intensification of regional aridification trends during the study period. This pattern of declining precipitation metrics, particularly the reduction in extreme precipitation events, indicates a shift towards drier conditions in the region.
# Developing a Cybersecurity Training Environment through the Integration of OpenAI and AWS
## 5 Conclusions  
In this work, we explore the potential of AI and AWS cloud computing to improve cybersecurity. Through a series of experiments and tests, we obtained significant results that highlight the effectiveness of this innovative collaboration. First, we demonstrated that AI, represented by OpenAI's GPT-3 and DALL-E models, can generate high-quality synthetic training data that simulate real cyber threats. These data are essential for training threat detection systems and improving the resilience of organizations against computer attacks.  
Regarding the speed of data generation, we found that AI significantly outperforms traditional methods. Data generation times with GPT-3 and DALL-E are considerably lower than conventional approaches, allowing faster and more efficient data generation. Additionally, AI offers substantial resource savings, including CPU usage, time, and human effort. This is essential in a cybersecurity environment where efficiency and resource optimization are crucial.  
It is important to note that this study is not without limitations. Although AI has proven effective in generating cybersecurity data, it is essential to continue researching and improving models to address even more sophisticated threats. Additionally, further consideration of AI's ethical and privacy implications in cybersecurity is required.  
Therefore, this work represents a significant step towards improving cybersecurity through AI and cloud applications. The results support the idea that this collaboration can revolutionize how organizations address cyber challenges, providing greater efficiency, speed, and accuracy in threat detection and mitigation. In future work, there is a need to continue researching and refining AI and addressing ethical and privacy considerations to strengthen cybersecurity in a constantly evolving digital world.  
Conceptualization, W.V.-C.; methodology, I.O.-G.; software, J.G.; validation, I.O.-G.; formal analysis, W.V.-C.; investigation, I.O.-G.; data curation, W.V.-C. and J.G.; writing--original draft preparation, I.O.-G.; writing--review and editing, J.G.; visualization, I.O.-G.; supervision, W.V.-C. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The data presented in this study are available upon request from the corresponding author. Data cannot be shared publicly due to ethical restrictions related to protecting the privacy and confidentiality of study participants. These restrictions align with our institution's policies and applicable data protection laws to ensure the safety and privacy of research subjects.  
The authors declare no conflicts of interest.
# Cross-Layer-Aided Opportunistic Routing for Sparse Underwater Wireless Sensor Networks
## 4 CLOR Protocol  
CLOR is a distributed cross-layer routing protocol, which integrates the candidate set selection algorithm, negotiation, and burst transmission strategy. In this section, we first introduce the main idea in CLOR. Then, the major process of CLOR is exhaustively described.
## 4 Results and Discussion
### Diffusion Leaching Tests in FRC Specimens Made with RPF  
#### 4.3.1 Basic Characterisation: 24 h Tank Leaching Test by CEN/TS 15862: 2012  
Leaching of monolithic materials is essentially governed by diffusion phenomena. Thus, for a previously basic characterisation, the diffusion leaching tank test was performed according to the CEN/TS 15862:2012 standard. This is a fast test (24 h) that allows the measurement of concentrations of the legally regulated elements, as shown in Table 3. Anions (sulphate, chloride, and fluoride) and heavy metals (Hg, Pb, Cd, Mo, As, Ni, and Se) are not represented because they are under the detection limits.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multicolumn{6}{c}{**Leachate Concentrations from Concrete (mg/m\({}^{2}\))**} \\ \hline
**Elements** & **C-REF** & **FRC2-REF** & **FRC2** & **FRC4** & **FRC6** \\ \hline pH values & 10.2 & 10.1 & 10.4 & 10.3 & 10.2 \\ Cr & 0.0042 & 0.0072 & 0.0030 & 0.0027 & 0.0032 \\ Zn & 0.0568 & 0.0495 & 0.0508 & 0.0576 & 0.0545 \\ Sb & 0.0149 & 0.0033 & 0.0105 & 0.0076 & 0.0059 \\ Ba & 0.0159 & 0.0058 & 0.0100 & 0.0061 & 0.0080 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Leachate concentrations (mg/m\({}^{2}\)) from concrete specimens according to the diffusion leaching test.  
Figure 4: Comparison of two pH regimes in the availability test (pH 7 and pH 4) for heavy metals in samples: (**a**) control C-REF; (**b**) control FRC-REF; (**c**) FRC2 specimen; (**d**) FRC4 specimen; and (**e**) FRC6 specimenThe 24-h dynamic tank test was carried out and it provided a basic and quick characterisation of the levels released by the concrete specimens. The heavy metals listed in Table 3 were released at low rates for all specimens and non-relevant differences are observed between the control specimen without fibre (C-REF) and specimens prepared with fibre reinforced concrete. The low release levels detected on the concrete specimens are justified, since solidification and stabilisation (S/S) using cement as a binder is most often applied (worldwide) for controlling the environmental impact of residues; it involves a conversion of the residues into a monolithic or granular material, ensuring easy handling and transportation to landfill sites. It also immobilises toxic pollutants by physical encapsulation, chemical incorporation and/or adsorption [41; 42].  
The data showed that the level of the heavy metals presented in Table 3 were similar to the RPF except to the antimony ones, which were lower than in RPF and inert limit, classifying them as inert material.