esa-sceva/satcom-chunk-collection huggingface dataset:
# Reversible Data Hiding in Encryppted Images with Extended Parametric Binary Tree Labeling
## 3 Proposed EPBTL-RDHEI
### Pixel Labeling and Data Hiding
#### 3.2.2 Labeling of Embeddable Group  
The labeling of embeddable pixels follows PBTL. The mapping of prediction errors to the label codes for \(\alpha=3\) and \(\beta=2\) is given in Table 1. An example of pixel labeling is illustrated in Figure 9.  
According to Table 1, the pixels with prediction error ranged from \(-3\) to 2 are embeddable. The lowest three bits of an embeddable pixel are used to record the label code. All label codes are recorded backward. For example, the prediction error \(-1\) maps to '100'. Thus, '001' is recorded to the lowest three bits of the pixel.  
The mapping table in Table 1 is not a fixed version. In general, the histogram of prediction error decreases with increasing absolute error. For \(\alpha=3\) and \(\beta=2\), there are six G2 codes. Therefore, two possible ranges of prediction error can be selected, i.e., \(-3\) to 2 or \(-2\) to 3. We can select a better version according to the error distribution of the given image.  
Figure 10 shows two test images and Figure 11 is the histogram of prediction error at \(-3\) and \(3\) for the two images. As shown in the plot, the number of pixels with a prediction error of \(-3\) is greater than the number of pixels with an error of 3. But the other image behaves quite contrary. Thus, we select the version of \(-3\) to 2 for image 'Man' and the version of \(-2\) to 3 for image 'Mit'. The bit of version code is used to indicate the actual  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \(P_{n}\) & & & & \(P_{e}\) & & \\ \hline
00 & 2 & 1 & 0 & \(-1\) & \(-2\) & \(-3\) \\
111 & 110 & 101 & 101 & 100 & 011 & 010 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Coding table of the prediction error when \(\alpha=3\) and \(\beta=2\).  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multicolumn{2}{c}{Decimal Encrypted image \(I_{e}\)} & \multicolumn{5}{c}{Binary encrypted image} \\ \hline
169 & 97 & 81 & 94 & 212 & 1010001 & 01010001 & 0101110 & 11010100 \\ \hline
145 & 50 & 142 & 21 & 127 & 1001001 & 001010 & 0111111 \\ \hline
88 & 242 & 131 & 146 & 164 & 164 & 101000 & 1010010 \\ \hline
156 & 130 & 6 & 188 & 150 & 101 & 10011100 & 10010010 \\ \hline
41 & 172 & 185 & 180 & 22 & 22 & 1001001 & 10011100 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Coding table of the prediction error when \(\alpha=3\) and \(\beta=2\).  
Figure 9: The labeled encrypted image generation process.  
version applied. For the example given in Figure 9, we record the parameters and version code with '0011' for, '010' for, and '0' for the version of \(-3\) to \(2\).
# Application of RFID to Soil-Erosion Research
## 1 Introduction  
Soil erosion is a problem of global significance. Of the variety of agencies that may be responsible for soil erosion, water is a principal one. An estimate by Reference [1] put the annual global cost of soil erosion by water in excess of US$ 7 billion. Despite its importance, obtaining data on rates of soil erosion on which to base land-management practices is not straightforward. Although several methods have been used, the rates obtained have been called into question (e.g., References [2; 3]). More than 20 years ago, Reference [4] (p. 23) commented that to obtain estimates of rates of erosion \"Emphasis should be given to measuring the distance particles are transported by splash, wash and rills in an erosion event.\" However, because of their size and number, tracking the movement of individual soil particles has proved difficult in the past. For the most part tagging of bulk tracers has been used. (For a review and discussion of such tracers, see Reference [5]). More recently, tracking of individual particles has been achieved. Reference [6] reported on real-time tracking of individual fluorescent particles in a laboratory study, and Reference [7] used Radio-Frequency Identification (RFID) transponders to monitor the movement of tagged artificial'soil' particles in both laboratoryand field experiments. In this paper we report on two further experiments to assess the role of RFID to measure the distance travelled by soil particles during erosion events. In the first experiment we focus on RFID tagged particles that are the same size as their surrounding particles. The aim here is, in the longer term, to develop this study in conjunction with Reference [8] to demonstrate how the movement of tagged particles can be used to derive a rate of soil erosion. However, the particles used in this experiment need to be located within a reader in order to be identified, constraining the practical application of the study. In the second experiment, we used tags with a booster antenna that allowed remote detection to assess the range and accuracy of remote detection. Since both experiments can be described as feasibility studies, controlled laboratory conditions are used.
## 3 Comprehensive Evaluation Properties and Implementation Procedures
### Efficiency  
Efficiency, as defined in the literature [23], implies that effective IMs and DMs can minimize the variability of the structural dynamic response for a given level of ground motion intensity. This, in turn, reduces the number of ground motion records needed for an accurate IDA. The logarithmic standard deviation \(\beta_{\text{D}}\) between IMs and DMs serves as the metric for assessing efficiency. A smaller \(\beta_{\text{D}}\) value indicates lower dispersion in structural dynamic response, and consequently, higher efficiency for the associated IMs and DMs. The formula to calculate \(\beta_{\text{D}}\) is given as follows:  
\[\beta_{D}=\sqrt{\frac{\sum\left(\ln(DM)-\ln(a\,\text{1}M^{b})\right)^{2}}{N-2}} \tag{4}\]where \(a\) and \(b\) are the fitting parameters in Equation (3), and \(N\) is the total number of dynamic time history analyses. The specific meaning of \(\beta_{\rm D}\) is expressed in Figure 1.
## 3 Results and Discussion
### The Interpretation Examples
If data from the weather provider are lost, the user will see incorrect values in the visualisation dashboard. For example, the user may notice that the  
into account differences in meteorological conditions between different territories, the resulting accuracy for the 3-h-ahead forecast corresponds to the state-of-the-art level. The disadvantage of increasing the number of features is that the model becomes less transparent for users and developers. To overcome this shortcoming, the modified Shapley additive explanations method was proposed and applied. With this modification, features that have a meaning close to the user are aggregated and their weights are summed up. Examples were given to show how the visualisation of this method allows us to understand what a particular model forecast is based on. Such interpretive tools can increase specialists' confidence in the intelligent information systems in the power industry. The main contributions of the work comparing with already reported are the follows:  
* Previous studies devoted to solar irradiation or SPP generation forecasting have used only total cloud cover or cloud data extracted from satellite images. This paper proposes to use types of clouds and other features that can be identified from cloud observations in natural language. It was experimentally proven that the use of various features describing cloudiness increases SPP generation forecasting. * A new modification of the SHAP interpretation algorithm was proposed. For the first time, it was shown in detail how the SHAP algorithm can be used to explain obtained SPP generation forecasts. In the course of further research, it is planned to conduct experiments on other objects, as well as develop a generative language model that, based on the results of the SHAP algorithm, will write a textual explanation of the models' output. Conceptualization, A.I.K. and P.V.M. ; methodology, V.V.G. and P.V.M., software, V.V.G., P.V.M. and A.I.S. ; validation, P.V.M. and A.I.S. ; writing--original draft preparation, A.I.K. and V.V.G. ; writing--review and editing, A.I.K. and P.V.M. ; visualization, P.V.M. ; supervision, A.I.K. All authors have read and agreed to the published version of the manuscript. The research was carried out within the state assignment with the financial support of the Ministry of Science and Higher Education of the Russian Federation (subject No. FEUZ-2022-0030 Development of an intelligent multi-agent system for modelling deeply integrated technological systems in the power industry). Dataset available on request from the authors. The authors declare no conflict of interest.
# Circular Orbit Flip Trajectories Generated by E-Sail
###### Abstract  
An Electric Solar Wind Sail (E-sail) is a propellantless propulsion concept that extracts momentum from the high-speed solar wind stream to generate thrust. This paper investigates the performance of such a propulsion system in obtaining the transition from a prograde to a retrograde motion. The spacecraft is assumed to initially trace a circular heliocentric orbit of given radius. This particular trajectory, referred to as Circular Orbit Flip Trajectory (COFT), is analyzed in a two-dimensional mission scenario, by exploiting the capability of a medium-high performance E-sail to change the spacecraft angular momentum vector during its motion in the interplanetary space. More precisely, the paper describes a procedure to evaluate the E-sail optimal performance in a set of COFTs, by calculating their minimum flight times as a function of the sail reference propulsive acceleration. It is shown that a two-dimensional COFT can be generated by means of a simple steering law in which the E-sail nominal plane has a nearly fixed attitude with respect to an orbital reference system, for most of the time interval of the interplanetary transfer.  
e pacs: electric solar wind sail; orbit flip maneuver; preliminary mission design; H-reversal maneuver +
Footnote †: journal: Applied
# The Assisted Positioning Technology for High Speed Train Based on Deep Learning
## 5 Analysis of the Experimental Results
### The Detection Result of Kilometer Posts  
This section analyzes the detection results of kilometer posts, as shown in Figure 9. It can be seen that the model proposed in this paper can effectively detect and locate kilometer posts under different weather conditions or in cases where there are trackside interferences. Moreover, from the previous analysis, we know that the accuracy of the detection results reached 98.92%, and the detection time was only 35.43 ms. Therefore, it ensures both the detection accuracy and efficiency.
# Multi-Point Displacement Synchronous Monitoring Method for Bridges Based on Computer Vision
###### Abstract  
Bridge displacement is an important part of safety evaluations. Currently, bridge displacement monitoring uses only a few measurement points, making it difficult to evaluate safety. To address this problem, we propose a multi-point displacement synchronous monitoring method. The structural surface has abundant natural texture features, so we use the feature points of the structural surface as the displacement measurement points and propose a feature point displacement calculation method. Furthermore, we conduct experiments on a beam in the laboratory and obtain the beam's multi-point displacement monitoring results. The monitoring results show that the displacement of some feature points is mismatched. We propose the use of the structural deflection curve to eliminate the feature point displacement mismatches. This method uses the maximum rotation angle of the deflection curve to eliminate displacement mismatches. The results indicate that it is effective to eliminate displacement mismatches in simple structures, such as simply supported beams. Finally, we obtain the test beam's multi-point displacement synchronous monitoring results. Compared with the 3D laser scanning measurement method, the maximum error of the monitoring results is 8.70%. Research shows that the main reason for the monitoring error is image noise, and the noise interference problem due to its application in practical bridges requires further investigation. Compared with traditional displacement monitoring, this method has significant economic, efficiency, and data integrity advantages. The method has application prospects for multi-point displacement monitoring of simple structures, such as simply supported beams.  
structural health monitoring; displacement monitoring; deformation monitoring; feature point detection; feature extraction; deflection curve; safety evaluation
###### Abstract  
X-ray irradiation and modified atmospheres (MAs) provide eco-friendly, chemical-free methods for pest management. Although a low-oxygen atmospheric treatment improves the performance of some irradiated insects, its influence on the irradiation of quarantine insects and its impacts on pest control efficacy have yet to be investigated. Based on bioassay results, this study employed direct immersion solid-phase microextraction (DI-SPME) combined with gas chromatography-mass spectrometry (GC-MS) to determine metabolic profiles of late third-instar _B. dorsalis_ larvae under normoxia (CON, Air), hypoxia (95% N\({}_{2}\) + 5% O\({}_{2}\), HY), super-hypoxia (99.5% N\({}_{2}\) + 0.5% O\({}_{2}\), Sup-HY), irradiation-alone (116 Gy, IR-alone), hypoxia + irradiation (HY + IR) and super-hypoxia + irradiation (Sup-HY + IR). Our findings reveal that, compared to the IR-alone group, the IR treatment under HY and Sup-HY (HY + IR and Sup-HY + IR) increases the larval pupation of _B. dorsalis_, and weakens the delaying effect of IR on the larval developmental stage. However, these 3 groups further hinder adult emergence under the phytosanitary IR dose of 116 Gy. Moreover, all IR-treated groups, including IR-alone, HY + IR, and Sup-HY + IR, lead to insect death as a caractate larvae or pupae. Pathway analysis identified changed metabolic pathways across treatment groups. Specifically, changes in lipid metabolism-related pathways were observed: 3 in HY vs. CON, 2 in Sup-HY vs. CON, and 5 each in IR-alone vs. CON, HY + IR vs. CON, and Sup-HY + IR vs. CON. The treatments of IR-alone, HY + IR, and Sup-HY + IR induce comparable modifications in metabolic pathways. However, in the HY + IR, and Sup-HY + IR groups, the third-instar larvae of _B. dorsalis_ demonstrate significantly fewer changes. Our research suggests that a low-oxygen environment (HY and Sup-HY) might enhance the radiation tolerance in _B. dorsalis_ larvae by stabilizing lipid metabolism pathways at biologically feasible levels. Additionally, our findings indicate that the current phytosanitary IR dose contributes to the effective management of _B. dorsalis_, without being influenced by radioprotective effects. These results hold significant importance for understanding the biological effects of radiation on _B. dorsalis_ and for developing IR-specific regulatory guidelines under MA environments.  
Bactrocera dorsalis; modified atmosphere; irradiation; development; SPME technology; metabolites; radioprotective effects
# Research on Dynamic Searchable Encryption Method Based on Bloom Filter
## 6 Security Analysis
### Adaptive Security
Thus, we have:  
\[|Pr[G_{3}=1]-Pr[G_{2}=1]|\leq Adv_{\mathcal{A}}^{hash}(\lambda). \tag{15}\]  
G4: In this game, two tables, H1 and H2, need to be created to answer \(\mathcal{A}\)'s query. \(H1\) is to record the response to \(H_{2}(w||j)\) and H2 is to record the response to \(H_{3}()\). In our game, we only consider the leak function in the algorithms update, so we can define \(\mathfrak{L}_{Update}(DOC)\ =\ \Sigma_{w\in W}|EDB(w)\ |\), which only leak the number of keyword/document pairs. In game 2, we generate the search token \(st_{w}\) in the update algorithm as a random string instead of the search token generated in the algorithm. In addition, the \(H_{1}(st_{w},w_{i})\) and \(H_{2}^{ct_{w}}(st_{w})\) during token generation is also replaced by the random strings. If the adversary can distinguish between games 2 and 3, we can distinguish between hashed and truly random functions. Then, we have:  
\[Pr[Game_{4}=1]-Pr[Game_{3}=1]\leq Adv_{\mathcal{A}}^{hash}(\lambda). \tag{16}\]  
G5: In this game, we maintain a table \(UPDATE\) to generate the encrypted document. In the update protocol, game 5 uses random numbers instead of encrypted document \(IE\). It can be seen that games 4 and 5 are the same. \[Pr[Game_{4}=1]=Pr[Game_{5}=1]. \tag{17}\]  
G6: Simulator S simulates the adversary's point of view with a leak function L that includes search patterns and add history. From the opponent's point of view, G4 and G5 are exactly the same. Thus, they are indistinguishable:  
\[Pr[Game_{6}=1]=Pr[Game_{5}=1]=Pr\Big{[}Ideal_{A}^{\Pi}(\lambda)=1\Big{]}. \tag{18}\]  
Conclusion: To sum up the contributions of G0, G1, G2, G3, G4, G5, and G6 we have:  
\[Pr\Big{[}Real_{\mathcal{A}}^{\Pi}(\lambda)=1\Big{]}=Pr\Big{[}Ideal_{\mathcal{ A}}^{\Pi}(\lambda)=1\Big{]}\leq Adv_{\mathcal{A}}^{hash}(\lambda) \tag{19}\]  
Since the hash function is a one-way function, this scheme is an \(\mathcal{L}\)-adaptively-secure searchable encryption scheme.
## 2 Materials and Methods
### Preparation of the Samples and Graphene Nano-Coatings
#### 2.1.1 Transferred CVD Graphene  
The thermally activated Chemical Vapor Deposition (CVD) process was performed inside a hot wall fused silica tube reactor (ThermoFisher Scientific Lindberg/Blue M\({}^{\mathrm{TM}}\) Tube Furnace, Waltham, MA, USA) using H\({}_{2}\) as inert gas and methane as the gas-phase precursor of graphene. For the transferred graphene coating, the SLG film was grown on a sacrificial 25 \(\upmu\)m thick Cu foil (Alfa Aesar #13382, Shanghai, China), with 99.8% purity, that acted as the metal catalyst body, following a standard low pressure chemical vapor deposition (LPCVD) procedure. After evacuation of air by means of a vacuum pump, the chamber was filled back with hydrogen and heated at 1000 \({}^{\circ}\)C keeping pressure to about 120 Pa. Heating was maintained for 30\({}^{\prime}\) for annealing and removing the native oxide on the copper surface as well as to increase the grain size; then a flow of CH\({}_{4}\) (35 sccm) and H\({}_{2}\) (50 sccm) was guaranteed through the chamber for the whole growth time. After cooling to room temperature in pure hydrogen, a layer of ethylene-vinyl-acetate (EVA) was spin-coated on the graphene/copper foil to be used as a transfer supporting layer and baked in the oven at 80 \({}^{\circ}\)C. The copper foil was etched away (Copper Etchant TFB, Transense, Oxfordshire, UK) and the resulting EVA/graphene stack was rinsed in DI water. The Eva/graphene stack was subsequently transferred onto the copper sample surface by immersion into the DI water bath, and the sample heated at 80 \({}^{\circ}\)C into N\({}_{2}\) environment for one hour so that graphene grabbed onto the metallic surface. Finally, the EVA was removed from the sample using Xylene at 90 \({}^{\circ}\)C.  
The transferred graphene has a high-quality low-defect structure characterised as about 95% monolayer according to some authors [51; 52]. It gives the freedom to cover any kind of substrate, that could be also much rougher [49], but its production in large quantities may be expensive due to the cumbersome transfer process.
## 5 Pathogenesis  
AGEP has been classified as a T cell-related sterile neutrophilic inflammatory response (type IVd reaction) [25; 26; 27]. The activation, proliferation and migration of drug-specific cluster of differentiation (CD) 4 and CD8 T cells play an important role in the development of AGEP (Figure 1), as supported by the use of patch tests [17; 18; 19; 20] and in vitro tests [21; 22]. It is supposed that drug-specific cytotoxic T cells and cytotoxic proteins such as granzyme B and perforin induce the apoptosis of keratinocytes, leading to subcorneal vesicles [27; 28]. Recently, it has also been shown that, besides in toxic epidermal necrolysis (TEN), granulysin is also expressed by CD4 and CD8 T cells and natural killer (NK) cells in different drug reactions including AGEP, suggesting that granulysin may also play a role in the pathogenesis of AGEP [28]. Furthermore, in vitro tests have shown that drug-specific T cells in AGEP patients produced significantly more chemokine (C-X-C motif) ligand 8 (CXCL8)/IL-8, a potent neutrophil chemotactic chemokine [26; 27; 28; 29]. CXCL8/IL-8 is thought to play a central role in the formation of pustules by recruitment of neutrophils. The increased levels of IL-17 and IL-22 as well as granulocyte-macrophage colony-stimulating factor (GM-CSF) in AGEP patients may also participate in the strong neutrophilic activity by the synergistic effect on the production of CXCL8/IL-8 and the prevention of apoptosis of the neutrophils [28; 29]. Recent studies also described a higher level of IL-17 expression by neutrophils, mast cells (MC), and macrophages, and a lower level by T cells, in AGEP patients, indicating that innate cells may also be involved in the pathogenesis of AGEP [29]. Furthermore, a deficiency in the IL36-Ra in some AGEP patients seems to play a role, leading to the increased expression of various proinflammatory cytokines and chemokines such as IL-1, IL-6, IL-12, IL-23, IL-17, tumor necrosis factor alpha (TNF\(\alpha\)) and CXCL8/IL-8, which can further enhance neutrophil recruitment and activation [22; 23; 30].  
Figure 1: _Cont._  
In some AGEP patients, IL-5 expressed by infiltrating T cells may lead to the eosinophil presented in about 30% of AGEP patients [26]. An elevated expression of TNF\(\alpha\) in AGEP patients has been reported [31].  
Figure 1: Putative pathogenic mechanisms in acute generalized exanthematous pustulosis (AGEP). (**A**) In cases with drug involvement, the initial phase involves stimulation of drug-specific T cells and (**B**) their migration to the skin; (**C**) These T cells, possibly together with natural killer T (NKT) cells/natural killer (NK) cells are activated in the skin, where they induce apoptosis of keratinocytes through cytotoxic proteins and Fas/Fas ligand (FasL) interactions resulting in the formation of subcorneal vesicles; (**D**) Furthermore, these T cells together with subsequently activated bystander and inflammatory cells (keratinocytes, dendritic cells (DC), MC, neutrophils) release various cytokines and chemokines; (**E**) which predominately lead to neutrophil inflammation and the formation of pustules.