esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Results of Experiments
### Vdata Dataset  
This experiment takes the 43 instances of the Vdata dataset, all of which have a flexibility rate \(\beta=0.5\). The results generated by the GA-RRHC have been compared again with those obtained by the GLNSA, HA, and IJA (Table 9).  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Instance** & **n \(\times\) m** & \(\beta\) & **BKV** &
\begin{tabular}{c} **GA-** \\ **RRHC** \\ \end{tabular} & **GLNSA** & **HA** & **IJA** \\ \hline mt06 & 6 \(\times\) 6 & 0.5 & 47 & 47 \({}^{*}\) & 47 \({}^{*}\) & 47 \({}^{*}\) & 47 \(  
Figure 18 presents the number of best results obtained for each algorithm in this dataset, where the GA-RRHC calculated the 43 best values, the same as the HA and superior to the GLNSA and IJA.  
Figure 18: Number of best results per algorithm for the Vdata dataset.  
Table 10 shows the ranking, the average \(RPD\), and the non-parametric Friedman pairwise test values of each algorithm. The results show that the GA-RRHC obtained the first place concerning the RPD of the 43 problems, and the results indicate a significant difference with the IJA.  
Figure 19 depicts the difference of the average RPD between the GA-RRHC and the other methods.
## 2 Improvement of Post-Processing and Localization  
To improve the AE source location results in RC, a post-processing protocol was developed and implemented in Matlab. A flowchart of the protocol is shown in Figure 1. Each step will be explained in the following subsections.
## 7 Reinforced GPC
In addition, when reinforced GPC beam was subjected to corrosive sodium chloride solution, it exhibited more flexural degradation than normal concrete [186]. When GPC is used in columns; its behavior depends on the eccentricity of loads, ratios of reinforcement, additional steel fibers, and compressive strength along with bond strength. [PERSON] et al. [187] found that the loading capacity of reinforced GPC columns increased when the eccentricity of loading was reduced. In addition, with high reinforcement ratio and concrete strength and lower load eccentricity, the reinforced GPC columns exhibit brittle failure. Similarly, while increasing strength and longitudinal reinforcement and decreasing load eccentricity, the loading capacity of the column increased [179]. However, to further improve the ductility and load-carrying capacity of reinforced GPC columns, the use of steel fibers and confinement was recommended [188; 189]. In addition to beams and columns, the structural member includes reinforced structure GPC slab panels. [PERSON] and [PERSON] [190] performed flexural test on GPC and reinforced concrete slabs. It was found that GPC reinforced slab has a higher ultimate load, yield load, and cracking load with more micro-cracks and deflection when compared to the normal reinforced concrete. However, the number of cracks in the GPC slab were more, but their average crack width and spacing were less than conventional concrete, which might be due to improved microstructure of GPC. In addition to the beams, columns, and slabs, one of the most important structural members to be considered are GPC wall panels. It was found from previous researches [173; 191] that GPC walls when compared to normal OPC walls, exhibit more deflection and softening behavior under axial loading. Thus, it behaved more in a ductile manner. This ductility was due to the presence of a higher amount of finer aluminosilicate particles in the GPC mix [191]. This study also proposed equation 9 for finding the ultimate strength of GPC walls. \[P_{u}=0.585\left[f_{c}Lt+(f_{y}-f_{c})\;A_{sc}\right][1+(h/40\;t)-(h/30\;t)^{ 2}]\left[1-(h/18\;L)\right] \tag{9}\]where,  
P\({}_{\text{u}}\)= ultimate load,  
L= length of wall,  
t = thickness of wall,  
f\({}_{\text{y}}\) = steel reinforcement strength,  
A\({}_{\text{sc}}\) = steel reinforcement area,  
H = height of wall.
## 5 Conclusions  
The findings in laboratory conditions of this study are indeed promising, suggesting that formulations containing _B. bassiana(r)_ and _M. anisopliae(r)_ can be effective in controlling _A. mexicana_ within a controlled environment.  
The most efficient biological control observed in this study was achieved with the combination of _B. bassimana_ (MA-Bb1) and Diatomin(r), which demonstrated the highest total mortality rate of _A. mexicana_ 96 h post infection, in contrast to the control group (Tween 80), which exhibited the lowest specific mortality rate in the study.  
It is important to note that results obtained in laboratory settings often serve as a starting point for assessing the efficacy of treatments. However, field trials are essential to determine their practical applicability in real-world scenarios. Additionally, the effectiveness of these treatments may vary depending on the insect species and environmental conditions. Therefore, further studies are necessary to validate and fine-tune these biological control strategies before considering their large-scale implementation.  
Conceptualization, L.J.A.L., I.O.F. and O.R.-A.; methodology, L.J.A.L., N.V.-R. and O.R.-A.; software, N.V.-R. and O.R.-A.; validation, I.O.F., A.H.d.l.P. and O.R.-A.; formal analysis, L.J.A.L., P.A.L. and O.R.-A.; resources, L.J.A.L. and O.R.-A.; original--draft preparation, N.V.-R., I.O.F. and O.R.-A.; writing--review and editing, I.O.F., O.R.-A. and P.A.L.; visualization, O.R.-A. and N.V.-R.; supervision, A.H.d.l.P., project administration, O.R.-A.; funding acquisition, O.R.-A. All authors have read and agreed to the published version of the manuscript.  
The authors are grateful to Consejo Nacional de Humanidades, Ciencia y Tecnologia (Conahcyt) (No. CVU 775050), Colegio de Postgraduados, Campus Puebla (No. ID 21931001) and Benemerita Universidad Autonoma of Puebla (No. ID 100420500).  
Not applicable.  
The raw data supporting the conclusions of this article will be made available by the authors on request.  
The authors declare no conflicts of interest.
# An Improved Hybrid Routing Protocol Combining MANET and DTN
## 3 Proposed Protocol
Otherwise, the source node checks E-RERR is received. If E-RERR is received successfully, virtual source nodes which satisfying the condition of the proposed protocol, the message is delivered to a destination node of the message. Figure 3: The operation of the proposed protocol. A source node broadcast RREQ messages but E-RERR messages are returned to the source node (**a**) because routing path from the source node to the destination node is not successfully established. Then, virtual source nodes are selected based on the delivery predictability to the destination node and messages are forwarded to the virtual source nodes (**b**). In this example, three nodes are selected as virtual source nodes. After that, selected virtual source nodes operates as original source node and forwards message to neighboring node when they contact another nodes by DTN protocol after movement, and the receiving nodes also move and contact another nodes (**c**). Finally, the message is delivered from the virtual source node to a destination node after exchange of RREQ and RREP messages defined by MANET protocol (**d**). Equation (1) are selected as virtual source nodes. Then the source node deliver the message to the selected virtual source nodes. If E-RERR is not received, it firstly checks predefined switching timer expires. If the timer expires, it switched to DTN phase. Otherwise, it waits for a next RREQ broadcast period and then broadcast RREP. In DTN phase, a source node checks any neighboring node N. If there is a neighboring node N, it checks whether it is the destination nod of the message. If it is, the message is forwarded to the destination node. Otherwise, a source node compares delivery predictability and if the neighboring node N has larger delivery predictability, the message is forwarded to the neighboring node N. Then, it checks predefined switching timer expires. If the timer expires, it switched to MANET phase, and MANET operation is carried out to deliver messages to a destination node. Otherwise, the above message delivery process is repeated in DTN phase until timer expires. Figure 4: Flowchart of the proposed protocol.
# Methods Improving Energy Efficiency of Photovoltaic Systems Operating under Partial Shading
## 3 Efficiency Estimation of PV Installation
### PV Installation with Reconfigurable Switching Systems  
Another way to increase the energy efficiency of solar installations operating in conditions of uneven illumination is the use of reconfigurable switching systems. This method has not yet received practical implementation in industrial solar power plants.  
Figure 7: Results of modeling the operation of a solar cell array with individual matching converters, (**a**)—volt-ampere characteristics of the matching converter at different values of the radiation intensity; (**b**)—dependence of the array output power on the radiation intensity of one of the modules (dots show the results of experimental measurements).  
However, at present, scientists and researchers from many countries are actively working in this direction [39; 40].  
The principle operation of reconfigurable switching systems is that by using a switching matrix, such switching is performed, in which shaded modules located in different arrays are included in one array, and their places are replaced by normally illuminated modules (Figure 8).  
The use of this method makes it possible to partially solve both the problem of disconnecting the shaded modules by shunt diodes and the problem of voltage mismatch in parallel connected arrays of modules operating in conditions of uneven illumination. In this case, the disadvantages of the method are:  
* practical complexity of the method implementation in industrial solar power plants;
* high cost, justified by the use of expensive switching matrices and a large number of connecting wires designed for a current of at least 10 A;
* inefficiency with a small number of shaded solar modules.
## 4 Experimental Results
### Hive  
#### 4.4.1 Default Environment Outcome  
Upon attempting to download the Hive ransomware in the default environment, Windows Defender instantly detected the malicious content and did not even allow the completion of the download. This immediate detection signifies that Windows Defender identified the ransomware pattern in real-time as the file was being downloaded. Figures S11 and S12 show the Windows Defender logs in the default testing environment when attempting to download the Hive ransomware. The key testing observations from executing the Hive ransomware variant on Windows 11 can be summarized as follows:  
Key Observations:  
The notification indicating the threat is a system-generated alert and does not necessitate any user acknowledgment. It serves to inform the user about the blocked content but does not require any further action on their part. The identified threat is termed as \"Trojan:Script/Sabsik.TE.A!ml\". This classification indicates that Hive contains malicious scripts commonly associated with Trojan activities. The detection source, \"Downloads and attachments\", reinforces the idea that Defender halted the ransomware during the download process itself.  
Name of the Threat: Trojan:Script/Sabsik.TE.A!ml  
This specifies the type and variant of malware detected. In this case, it is a Trojan, which is malicious software that masquerades as legitimate software. This is a unique identifier assigned to this specific threat by Microsoft Defender.  
Severity: Severe.  
This indicates the potential harm the detected threat can cause to the system. \"Severe\" indicates it can inflict significant damage or unauthorized access.  
Category: Trojan.  
This confirms the type of malware detected.  
Detection Origin: Internet.  
This means the malware was detected during a download or while interacting with online content.  
Detection Source: Downloads and attachments.  
This indicates that the malware was detected as part of a downloaded file or an email attachment.  
Action: Quarantine.  
This is the action Defender took upon detecting the threat. \"Quarantine\" means the suspicious file was isolated to prevent it from causing harm.  
Action Status: No additional actions required.  
After quarantining the threat, Windows Defender determined no further actions were needed. The threat has been contained.
# Research on Risk Quantification Methods for Connected Autonomous Vehicles Based on CNN-LSTM
## 4 CAV Driving Risk Quantification Model
### Collision Probability  
When vehicles are traveling at similar low speeds or are far apart, the likelihood of a collision and its potential severity are relatively low (Figure 5a). However, when the MTTC value is low and the vehicle is traveling at a relatively low speed, the probability of a collision increases, although the severity remains low (Figure 5b). In contrast, if the following vehicle is traveling at a higher speed with a significant relative velocity, the potential severity of a rear-end collision becomes greater (Figure 5c). Finally, as the following vehicle approaches the lead vehicle with a large speed differential, the worst-case scenario emerges, characterized by both a high collision probability and high severity (Figure 5d).  
The \(MTTC\) is selected as the metric for calculating the collision probability because, compared to the \(TTC\), the \(MTTC\) can encompass a wider range of collision scenarios. At each time step, the \(MTTC\) between the target vehicle and the lead vehicle is calculated. The collision probability function is a monotonically decreasing function of the \(MTTC\), meaning that, as the \(MTTC\) increases, the likelihood of a collision should decrease, and vice versa. The collision probability is defined as a negative exponential function of the \(MTTC\):  
\[P=\left\{\begin{array}{ccc}\exp\left(-\frac{MTTC}{\eta}\right)&,p_{q}=1,MTTC >0\\ 0&,p_{q}=0\end{array}\right\} \tag{13}\]  
where \(P\) represents the collision probability; \(p_{q}=1\) indicates the presence of a vehicle ahead; \(p_{q}=0\) indicates the absence of a vehicle ahead; and \(\eta\) is the decay parameter of  
\(P_{z}\) is then divided by the sum of \(\theta\), yielding the average collision probability (ACP) for each vehicle over the given time segment (Equation (15)).  
\[P_{z}=\sum_{i}^{n}\sum_{t_{a}}^{t_{b}}(P\cdot\theta) \tag{14}\]  
\[ACP=\frac{P_{z}}{\sum_{t}^{n}\sum_{t_{a}}^{t_{b}}(\theta)} \tag{15}\]  
where \((t_{a},t_{b})\) is the observation time period and n is the total number of vehicles within the observation period. According to [14], \(\theta\) is a binary function: If and only if the vehicle appears within the observation time period and maintains either a lane-changing or car-following state, \(\theta=1\); otherwise, \(\theta=0\).
# Efficient Resource Scheduling for Multipath Retransmission over Industrial WSAN Systems
## 3 Network Model
### System Model
Without loss of generality, we transfer the period of all flows to the regular period through Equation (5), since it can let the scheduling fit with the data period better. \[p_{k}=p_{m}\cdot 2^{\lfloor log_{2}\frac{p_{k}^{\prime}}{p_{m}}\rfloor},p_{k}^{ \prime}\geq p_{m},k=0,1,\ldots,\gamma \tag{5}\]  
For example, assuming the basic period is 20 ms, then the supported periods can be 20 ms, 40 ms, 80 ms, and so on. All the superframes constitute a hyperframe, the period of which is the maximum period among the superframes. The period is denoted as \(T\) and is expressed by Equation (6). \[T=max\{p_{k},k=0,1,\ldots,\gamma\} \tag{6}\]  
We use \(H[t][c]\) to denote which transmission is allocated on time slot \(t\) and channel \(c\). The number of slots in a hyperframe is denoted by \(|H|=T/\kappa\). As an example, if the first transmission of flow \(F_{1}\) is allocated for slot 0 and channel offset 0, it can be expressed as \(H[0][0]=x^{1}(s_{1},d_{1})\), otherwise, it is \(H[0][0]=EMPTY\) if there is no transmission allocated to \(H[0][0]\). We assume that the deadline of a flow transmission is equal to its period in this paper. Thus, all the transmissions in a flow should be scheduled within the period, where the constraint can be expressed by Equation (7). \[t\leq\frac{p_{k}}{\kappa},\forall x^{k}(s_{\tau},n_{\tau}),k\in\{0,1,\ldots,\gamma\} \tag{7}\]
# Performance Evaluation Method for Intelligent Computing Components for Space Applications
## 3 Evaluation Method
### High-Performance Computing Benchmark  
The complexity of current space missions is increasing, and high-performance computing is more and more widely applied to space missions, such as remote sensing data processing [21] and satellite visual navigation [22]. This work builds a diverse set of HPC-based benchmark tests; each benchmark is implemented in a parameterized way, and they are specified during the build configuration with CMake's -D flag. The first parameter selects the type of benchmark to be compiled, and supports standard programming languages such as C, CUDA, and OpenMP; it then defines the data type, which, for all the benchmarks tested in this section, supports floating-point and double-precision floating-point numbers, and the last parameter defines the block size, which applies only to the GPU version of the code (this parameter is not required for OpenMP).
# Simulation of Gas Fracturing in Reservoirs Based on a Coupled Thermo-Hydro-Mechanical-Damage Model
## 5 Conclusions  
1. The process of gas fracturing involves the propagation of cracks within rock specimens from the borehole towards the interior, eventually leading to complete fracturing. The efficiency of shale gas extraction is significantly affected by variations in rock parameters, and selecting appropriate rock parameters can enhance the extraction efficiency of shale gas.
2. The thermal aspect significantly influences the efficacy of gas fracturing. Lower temperatures result in poor gas fracturing effects, leading to lower efficiency in extracting  
Figure 16: The relationship between shale gas content of rock mass specimens at the same time under different permeability.  
Figure 15: The relationship between the gas content of rock mass specimens at the same time under different permeability.  
shale gas. On the other hand, higher temperatures enhance the effectiveness of gas fracturing, resulting in higher extraction efficiency. Therefore, maintaining an appropriately high temperature can improve gas fracturing efficiency and promote more efficient shale gas extraction. It is important to note that gas fracturing technology can induce damage to the surrounding rocks, reducing their compressive strength while increasing their permeability. Additionally, under the influence of temperature, gas fracturing technology can achieve even better results.
3. Increasing the volume constant leads to an upward trend in gas content. This indicates that during the gas fracturing process, the gas present around the borehole is extracted, resulting in a significant decrease in gas content. However, the gas content within the undamaged regions of the rock specimen remains relatively stable. This suggests that an increase in the volume constant makes gas fracturing more challenging, consequently reducing the efficiency of shale gas extraction. Conversely, maintaining a constant pressure of the specimen results in an upward trajectory of the instantaneous extraction rate over the same time period. This increase in the pressure constant improves the fracturing effects on the rock, thereby enhancing gas extraction efficiency. Moreover, the increased degree of rock damage indirectly contributes to improved extraction efficiency. Thus, increasing the pressure constant proves beneficial for enhancing gas fracturing efficiency.  
Conceptualization, E.Q., F.X. and Z.C.; Methodology, Y.Z. and Y.X.; Data curation, Z.Z. and M.J. All authors have read and agreed to the published version of the manuscript.  
The authors are grateful to the financial support from the Key Research and Development Program of Shaanxi Province, China (2022 ZDLSF07-06 and 2023-YBSF-369), and the Natural Science Basic Research Program of Shaanxi (2022)M-216 and 2022 JC-LHJJ-08).  
Not applicable.  
The data used to support the findings of this study are included within the article.  
The authors declare no conflict of interest.
# ISAR Image Quality Assessment Based on Visual Attention Model
## 2 Proposed Method  
### Overall Architecture  
The Transformer encoder extracts global features from ISAR image patches through a multi-head attention mechanism. Then, the Gramin matrix of features is computed to acquire score tokens strongly associated with the features through one attention layer. The Gramin matrix of features can be seen as dots of different features, which can capture the similarity and diversity of different features. Because the similarity and diversity of different features are directly related to the quality score due to the score token, the features can learn more information about the quality level. This method promotes features extracted from similar quality level images to contain common information about similar quality levels and features extracted from diverse quality level images to contain discriminative information about different quality levels. Moreover, image quality information can be explored in the process of feature extraction rather than the final fully connected layer, avoiding information loss significantly. The extracted features pass through the CAB and IRAB to increase interactions among regions and channels. In this way, detailed information of the images can be explored and the representation is more robust. Figure 1 illustrates the overall architecture, which comprises Gram-T and two attention blocks.
## 3 Results and Discussion
### Cross-Sectional Structures
The amount of carbon on the top layer was smaller than that found on the sample surface after nanopore fabrication, where all surface organic materials were completely removed by ablation [29], indicating that the most of PVP dispersants in the nano-silver dispersion were removed by the laser treatment, and residual PVP, identified in EDX mapping results (Figures 7 and 13), was almost negligible. For the detailed analysis, silver (Ag) was extracted from the graph, as shown in Figure 14b. Silver significantly increased as the surface was approached. It seems that silver existed at the depth in the range from 600 nm to 800 nm, and this value corresponded well to the grain size of the sample. Our previous study showed that localized energy absorption within the grains of the top layer of the YSZ results in the formation of long-elongated nanopores form within the grains. Pore size depends on the zirconia grain size, and thus the maximum depth of the pore also corresponds to the grain size. Therefore, the fact that silver was detected in the GDOES analysis to the same depth as the grain size of the sample indicates that silver has reached the deepest part of the pre-fabricated nanopores. In addition, the result that the silver peak gradually decreased within the range of the grain size of the surface grains indicates that silver was present without extreme bias from the top to the deepest point in the nanopore. This indicates that the silver in the pore was not removed by laser treatment with appropriate irradiation conditions and that the pore was filled to the deepest part. The measurements were taken over a wide area, approximately 40 mm in diameter, of a sample that had pores on the entire surfaces. Hence, it can be said that in all areas, silver nanoparticles firmly penetrated the bottom of the pores and still remained after laser treatment.