esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Proposed Protocol to Secure E-Commerce Transactions
### Employing Secret-Key and Public-Key Encryptions
#### 5.1.3. Dld  
Information or data in e-commerce transactions can be vulnerable to hacking and unauthorized access, leading to potential data leakage. Protecting sensitive information during the transmission is crucial. When a merchant sends a product request to a company's website, it is essential to safeguard the merchant's data. Any mishandling of the order data or involvement of third-party agents in data transmission can result in data leakage. To address this, our protocol incorporates technology to detect data leakage during key generation, encryption, and decryption processes. We utilize dummy objects that mimic real agents to trace the source of leaks and identify responsible parties.  
Give \(GM\) represents the group of \(\mathcal{M}\)s and \(GD\) denotes the company's group dataset. \(A\) is the agent, and \(GE_{A}\) refers to the agent's guilty event. It should calculate an agent's \(P_{i}\) probability of being a guilty agent. When given the leaked data \(LD\), the probability is indicated by \(P_{i}=GE_{A}|LD\). We suppose that \(\forall\ D_{i}\in LD\), \(D\) represents sensitive data from the database, and \(i=\{v_{1},v_{2}\ldots,v_{n}\}\). There can only be two conceivable outcomes. The first outcome is that any single agent from the set of \(S(D_{i})=A|D_{i}\in X_{j}\) has leaked \(D_{i}\) to target \(t\), where \(S(D_{i})\) signifies the set of agents who have \(D_{i}\) in their allocated database \(X_{j}\)\(\forall\ j=\{1,2,\ldots,n\}\). Alternatively, the target \(t\) obtained the data \(D_{i}\) by chance or some other means without the assistance of any agent \(A\). The probability of leaking any data item \(D_{i}\) from the leaked database \(LD\), i.e., \(P_{i}\) (leak \(D_{i}\) to \(LD\)) equals \(\forall\ A\in S(D_{i})\) if leaked by any agent \(A\in S(D_{i})\), otherwise \(P_{i}\) (leak \(D_{i}\) to \(LD\)) equals \(alpha\) if acquired by the target \(t\). We contend that \(A\)'s resolution to leak any data \(D_{i}\) is independent of the leaking of other data \(D_{i}\), \(\forall\ D_{i}\), \(D_{i}\
eq D_{i_{aw}}\). \(P_{i}(GE_{A}|LD)\) of the agent \(A\) to be a guilty agent \(GE_{A}\) is calculated, as shown in the following equation.  
\[P_{i}(GE_{A}|LD)=1-\prod_{D_{i}\in LD\cap X_{j}}(1-(1-\alpha)/C(D_{i})) \tag{1}\]
# A Comprehensive Study on EDFA Characteristics: Temperature Impact
## 3 Results and Discussion
### Saturation Pump Power Variation with Temperature  
The saturation pump power is another important factor in the study of the fiber performance in order to have a complete overview concerning the minimum required pump power to have an optically amplified signal. It could be defined as the input pump power at which the gain has been reduced by 3 dB of its saturation gain value. From previous studies [2; 3], increasing the input pump power will increase the number of carriers in the meta-stable state, and this continues until all of the carriers in the ground state are stimulated into the meta-stable state. At this level, any increase in the number of carriers in the meta-stable state will not affect the amplification, and the saturation region is reached. The saturation pump power investigation shows its dependency on several parameters, such as: input signal power and signal wavelength, as follows.  
Figure 8: Saturation signal power variation with temperature.  
Figure 7: Gain versus input signal power.  
The gain versus input pump power should be obtained first at different temperatures using the 1480-nm pumping wavelength, as shown in Figure 9. The EDFA length is 4 m, and the input signal power is 10 \(\upmu\)W. The effect of temperature is studied in the range from \(-40\)\({}^{\circ}\)C to \(+80\)\({}^{\circ}\)C. Again, the higher temperature sensitivity of the 1480-nm pumping compared to the 980-nm pumping regime is revealed when comparing the gain versus input pump power variation with temperature for both cases, as previously stated in Section 3.5.  
The effect of the input signal power on the saturation pump power variation with temperature is displayed in Figure 10. A 4-m fiber length is pumped using an 1480-nm laser beam at a temperature range from \(-40\)\({}^{\circ}\)C to \(+80\)\({}^{\circ}\)C. A notable decrease is observed in the value of the saturation pump power with the increase of the temperature. Also, one can notice the negative impact of temperature on the saturation pump power variation with the increase of the driven signal power in the 1480-nm pumping case.
## 3 DL Models for Ocean Studies
### Convolution-Based Architecture
#### 3.2.2 U-Net  
U-Net is widely used for image segmentation tasks, especially for remote sensing images [84]. It follows an encoder-decoder structure in which the encoder progressively downsamples the input image to capture high-level features, while the decoder upsamples to reconstruct spatial resolution. Another characteristic of U-Net lies in its skip connections,  
Figure 3: Commonly used neural network architectures in ocean studies.  
which transfer fine-grained features from the encoder to the corresponding decoder layers, contributing to producing accurate segmentation results. U-Net is well suited for sea ice, coastal habitats, or coral reef monitoring. By segmenting complex remote sensing imagery at high accuracy, U-Net provides valuable insights for marine ecosystem monitoring and climate change assessments [8].
# Enhancing Air Quality Prediction with an Adaptive PSO-Optimized CNN-Bi-LSTM Model
## 3 Model Introduction
### Model Performance Evaluation Indicators  
To rigorously assess the generalization capacity of the proposed model, the dataset was meticulously partitioned into two subsets: a training set, encompassing the initial 80% of the data, was utilized for model learning and parameter tuning, while the remaining 20% constituted the validation set, serving to gauge the model's performance on unseen data. This division adheres to standard practice in machine learning, ensuring that the model's predictive efficacy can be objectively evaluated. Consistent with many comparative predictive models, this study adopted the Mean Absolute Error (MAE) as the loss function. MAE is a prevalent metric for quantifying the discrepancy between the model's predicted outputs and the actual observations, with a particular sensitivity to large deviations. It provides a quadratic penalty for errors, emphasizing the significance of substantial prediction inaccuracies. The mathematical expression for calculating MAE is formally defined as follows:  
\[\text{E}_{\text{MAE}}=\frac{1}{\text{M}}\underset{j=1}{\overset{\text{M}}{ \sum}}\left|\text{x}_{\text{j}}-\overset{\sim}{\text{x}}_{\text{j}}\right|\]  
Among them, xj represents the actual value, \(\overset{\sim}{\text{x}}_{\text{j}}\) denotes the predicted value generated by the model, and M represents the total number of data points.
# Quasi-All-Passive Thermal Control System Design and On-Orbit Validation of Luojia 1-01 Satellite
## 2 TCS Design and Requirements
### Analysis of TCS Design Requirements
Owing to these characteristics, a quasi-all-passive TCS design is presented and implemented. Doing this helps make sure all onboard instruments can function well by meeting all temperature requirements.
## 3 Results and Discussion
### Road Condition Prediction Analysis  
According to the existing rural road conditions in Haimen City, the performance requirements in the planning period (the overall average value is not less than 85), and the input costs in previous years. This paper preliminarily selects five annual budget options for decision-making calculation, mainly including plan 1: no budget; plan 2: 5 million (\(\Psi\)); plan 3: 10 million (\(\Psi\)); plan 4: 15 million (\(\Psi\)); plan 5: 5 million (\(\Psi\)); (previous four years: 2023-2026), 10 million (\(\Psi\)) (medium-term five years: 2027-2031), 15 million (\(\Psi\)) (later five years: 203  
According to the above figure, the RPCI and RRQI values of rural road network performance in Haimen City are in a decreasing trend with the increase in the service life of the pavement. By comparing different plans, it is found that with the increase in annual budget investment, the overall performance of the road network gradually improves, and the improvement effect of road surface RPCI compared with RRQI during the planning period is more obvious. When the annual budget reached more than 10 million, the excellent, good, and average grade rate of RPCI and RRQI indicators reached 95%, and the predicted average reached more than 80 points. After adopting the budget investment of plan 5 phased maintenance, its overall road condition performance is at excellent and good levels, and the predicted value is above 85 points.  
Therefore, the phased increase in annual budget input according to budget plan 5 is more effective and reasonable than the above-mentioned conservation budget plan. Moreover, the functional priority maintenance strategy has played a significant role in improving the performance of the pavement, which can meet the service level requirements of the municipal road management department for the road network under its jurisdiction during the planning period.  
Figure 14: Predicted RRQI of rural roads in Haimen City under different budget plans.  
Figure 13: Frequency distribution of RRQI on rural roads in Haimen City under different budget plans.
# Blood Pressure Estimation by Photoplethysmogram Decomposition into Hyperbolic Secant Waves
## 2 Methods
### Dataset Construction for the Verification of Our Proposed Method  
#### 2.2.1 Vital Signs Acquisition  
We experimentally constructed a data set by continuously measuring blood pressure using a continuous sphygmomanometer (Finnometer MIDI, Finapres Medical Systems), which measures blood pressure with each beat of pulse and pulse wave with a sampling rate of 200 [Hz]. This continuous sphygmomanometer can measure blood pressure non-invasively by attaching a cuff to the fingertip. In addition, we simultaneously acquired the pulse wave, which was measured using photoplethysmography (Procomp/BVP fingertip PPG, 2048 samples per second, with an output sampling rate of 200 samples per second). The subjects in this experiment were 10 adult Japanese volunteer students, aged \(22.4\pm 1.7\) years (2 females, 8 males). The risks of the exercise were explained to each volunteer both orally and in writing before they consented to the experiment. Since it is necessary to vary the subject's blood pressure in the experiment, subjects were asked to repeatedly relax and hold their breath for as long as they comfortably could, or up to 60 s. The relaxation phase was placed before and after each breath-holding phase, and was repeated three times.
# Integrated Framework for Bus Timetabling and Scheduling in Multi-Line Operation Mode
###### Abstract  
Bus service is of great significance to urban residents. With the convergence of bus lines and the formation of bus hubs, a multi-line operation mode which can realize the centralized management of vehicles is applied to the daily bus service planning. To solve the bus service planning problem systematically in the multi-line operation mode, we propose an integrated framework for bus timetabling (TT) and vehicle scheduling (VS), which are the two fundamental processes of bus service planning. Firstly, the determination processes of TT and VS are correlated by constructing the multiple vehicles' trip-link chains with departure time information to facilitate simultaneous optimization. Secondly, a multi-objective optimization model is constructed, which considers higher service quality and lower operating costs as objectives. Logic and operational rules are also considered as constraints to ensure the implementation of the solutions. Thirdly, we propose and implement a heuristic solution algorithm based on neighborhood search to achieve high-performance solutions. Finally, we validate the efficiency and effectiveness of our framework under the actual bus operation scenario in Chongqing, China. The Pareto frontier solutions are provided to bus operators as alternative operation schemes.  
timetabling; vehicle scheduling; integrated framework; the multi-line operation mode; neighborhood search
## 3 Results and Discussion
### Results
#### 3.1.1 Evaluation of Budget Estimates of N and C Stocks  
The average modeled results of the key nitrogen and carbon stocks are consistent with budget-based measurements that are available from WS10 [29], or have been taken from similar forested regions [41]. Key features of the results include a dominance of carbon storage in woody material (65% of total carbon storage) and nitrogen storage in soils (75% of total nitrogen storage) (Figure 2). Differences between the modeled values and the measurements were anticipated, particularly because the measured stocks were not necessarily binned in the same manner as the model description, and because we are comparing average model results representing 20 years of simulation to measurements that were developed to represent a full year, and in the case of the Wind River data [41], at different location. Direct comparisons between the available budget-based measurements and the model-based estimates (Figures 3 and 4; Table 1)indicate that the model is able to capture the general magnitude of carbon and nitrogen storage, and also the differences between the key environmental compartments.  
Figure 3: Measured _versus_ modeled annual yearly storage of nitrogen and carbon. These data are also plotted in Figure 2. Each data point represents a different storage term, as outlined in Figure 2. A one to one line is included for reference.  
Figure 2: A comparison of simulated stocks of nitrogen (**a**) and carbon (**b**) against budget estimates from [29]. Note that estimates of observed C stocks (except for SOM, labelled above were originally derived by [28] and that we assumed the carbon content of dry mass was 50%. Additionally, we assumed that 50% of the category “Fallen foliage and fine woody litter” from [29] were dead foliage and that 50% were dead wood.
## 3 Results and Discussion
### Results of the Statistical Analysis
Dual interactions such as stiffness, soil moisture (\(k\times MC\)), depth-to-width ratio, and tool movement speed (\(d/w\times v\)) statistically affected both forces. These results indicate that independent variables do not act alone but, when combined, can produce synergies and significantly influence force values, underscoring the importance of analysing interactions in tillage tool research [42]. The analysis of variance also showed that triple interactions such as stiffness, soil moisture, and depth-to-width ratio (\(k\times MC\times d/w\)) had a very significant impact on the values of the \(F_{x}\) and \(F_{y}\) (\(p<0.0001\)). This indicates the complexity of the processes involved in soil-tool interactions, which requires consideration not only of individual factors but also \begin{table}
\begin{tabular}{c c c c c c c} \hline
**Parameter** & \(\mathbf{k}\) & \(\mathbf{MC}\) & \(\mathbf{d}\mathbf{w}\) & \(\mathbf{v}\) & \(\mathbf{F_{x}}\) & \(\mathbf{F_{y}}\) \\ \hline \(k\) & 1.000 & & & & & \\ \(MC\) & \(-0.123\) a & 1.000 & & & & \\ \(d/w\) & \(-0.057\) a & \(-0.010\) & 1.000 & & & \\ \(v\) & \(-0.033\) a & \(-0.009\) & 0.008 & 1.000 & & \\ \(F_{x}\) & 0.165 a & \(-0.019\) a & 0.326 a & 0.257 a & 1.000 & \\ \(F_{y}\) & 0.031 a & \(-0.032\) a & 0.547 a & 0.168 a & 0.566 a & 1.000 \\ \hline \end{tabular} \(k\), the stiffness of the tool; \(MC\), soil moisture content; \(d/w\), the ratio of depth to width; \(v\), movement speed.  
a statistical significance at \(p\)-value = 0.05.  
\end{table} 
Table 3: Matrix of the values of the correlation coefficients of the independent variables (\(k\), \(MC\), \(d/w\), and \(v\)) with the draught forces \(F_{x}\) and vertical \(F_{y}\). of multiple combinations of factors in predictive models. These relationships are consistent with the observations of other researchers, who suggest that models that consider the interactions of many variables are more precise and effective in predicting the actual forces acting on the tools [43]. Overall, statistical analysis provided vital information on the influence of individual variables and their interaction with the values of draught and vertical forces. The most important factors were the tool's depth-to-width ratio and the movement speed, while the stiffness and soil moisture had a more minor but still significant impact on the forces acting on the tools. These results confirm the complexity of soil-tool interactions, which requires considering multiple variables and their combinations in developing predictive models.
# Proteomic Evaluation of Insecticidal Action of Phosphine on Green Peach Aphids, _Myzus persicae_
## Material and Methods
### Proteomic Analysis Using a Nano-LC-ESI-MS/MS  
A Thermo Scientific Q Exactive Hybrid Quadrupole-Orbitrap (Thermo Fisher Scientific Inc., Waltham, MA, USA) equipped with Dionex U 3000 RSLCnano HPLC system was used for proteomic analyses. The mass spectrometric analyses were performed with a nano-electrospray ionization source (ESI) and a fused silica emitter tip (New Objective, Woburn, MA, USA). The water/acetonitrile (98:2 \(v/v\)) solution containing 0.1% formic acid was used as the aqueous mobile phase. The samples were trapped on an Acclaim PepMap 100 trap column (100 \(\upmu\)m \(\times\) 2 cm, nanoViper C18, 5 \(\upmu\)m, 100 A) and washed for 6 min at a flow rate of 4 \(\upmu\)L/min and then separated on an Acclaim PepMap 100 capillary column (75 \(\upmu\)m \(\times\) 15 cm, nanoViper C18, 3 \(\upmu\)m, 100 A) at a flow rate of 300 mL/min. The resulting peptides were electro-sprayed through a coated silica tip at an ion spray voltage of 2000 eV. The mass data were analyzed using Proteome Discoverer 1.4, MaxQuant 1.6, and Scaffold 4.8.4 against the protein databases for _M. persicae_. Significant differences between two groups of data were obtained using Student's \(t\)-test (\(p<0.05\)).
## 5 Conclusions  
This study demonstrated the applicability of PS-InSAR techniques for monitoring ground deformation along the Honam High-Speed Railway in South Korea. Through the analysis of multi-temporal SAR data from 2016 to 2019, the study successfully identified critical subsidence zones and revealed the temporal dynamics of ground movement in soft-ground regions.  
1. The PS-InSAR approach accurately captured millimeter-scale displacements, with subsidence rates exceeding \(-12\) mm/year in vulnerable embankment sections. Validation against leveling and corner reflector data showed a strong correlation (R\({}^{2}\) > 0.93), confirming the method's high reliability for infrastructure monitoring. Seasonal variations in deformation rates, linked to rainfall and soil moisture changes, were also observed, offering valuable insights into the dynamics of ground behavior under climatic influences.
2. These findings provide a practical foundation for enhancing railway asset management. Specifically, the integration of PS-InSAR into routine maintenance operations enables operators to identify high-risk sections in advance, prioritize reinforcement efforts, and allocate resources more strategically. By shifting from reactive to preventive maintenance practices, infrastructure safety and performance can be significantly improved while minimizing operational disruptions and emergency repair costs.
3. To strengthen the practical utility of this approach, future research should aim to combine PS-InSAR results with geotechnical, hydrological, and structural datasets to establish a comprehensive, data-driven monitoring framework. Moreover, extending the observation period and incorporating data from additional SAR platforms may improve the temporal resolution and support more effective early warning and risk mitigation strategies. In addition, introducing experimental variables--such as construction methods, subgrade material properties, drainage conditions, and traffic load variations--can further enhance the scientific contribution and broaden the applicability of PS-InSAR in infrastructure monitoring.  
Conceptualization, S.-J.L. and H.-S.Y.; methodology, S.-J.L.; software, S.-J.L.; validation, S.-J.L., H.-S.Y. and T.-Y.K.; formal analysis, T.-Y.K.; investigation, S.-J.L.; resources, S.-J.L.; data curation, S.-J.L.; writing--original draft preparation, S.-J.L.; writing--review and editing, H.-S.Y.; visualization, S.-J.L.; supervision, H.-S.Y.; project administration, H.-S.Y.; funding acquisition, T.-Y.K. All authors have read and agreed to the published version of the manuscript.  
This work was supported by a National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (RS-2021-NR059478).  
Not applicable.  
The original contributions presented in the study are included in the article; further inquiries can be directed to the corresponding author.  
The authors declare no conflicts of interest.
# Future Perspectives for Gamma-ray Burst Detection from Space
## 7 MoonBEAM  
### Mission Overview  
The Moon Burst Energetics All-sky Monitor (MoonBEAM) is a proposed gamma-ray mission to observe the entire sky instantaneously for relativistic astrophysical explosions from a cislunar orbit. It is designed to explore the behavior of matter and energy under extreme conditions by observing the prompt emission from GRBs, identifying the conditions capable of launching transient relativistic jets and the origins of high-energy radiation from the relativistic outflows. MoonBEAM provides the essential continuous all-sky gamma-ray observations for time domain and multi-messenger astrophysics by reporting on any prompt emission of a GRB and by providing the critical first alerts to the community for contemporaneous and follow-up observations.