esa-sceva/satcom-chunk-collection huggingface dataset:
# NPS6D200--A Long Range Nanopositioning Stage with 6D Closed Loop Control
## 3 Setup and Subsystems of the 6D Nanopositioning System
### Planar Drive System with Aerostatic Guiding
With the whole system in operation, the drop in force constant was investigated in situ, and the results are contained in Figure 4 together with the corresponding increase in the coil currents and the closed loop servo error. The results confirm the expectations and indicate that the RMS servo error is not significantly affected by a levitation level of up to 6 mm. At this levitation height, the remaining force constant of the planar drive is approximately \(\frac{2}{3}\) of the nominal value. However, we conclude from these investigations that up to a vertical displacement of approximately 6 mm, the planar drive system does not experience substantial loss in performance and can be utilized even without repositioning the coils. Figure 3: Components of the planar direct drive and their arrangement. Note: The top part of the coil encapsulation is not shown for visibility of drive coils.
## 6 Experimental Results
### Experimental Results of Different Users  
Upon assessing the effect of different environments on recognition classification accuracy, the recognition results displayed good accuracy. Since gesture size, gesture speed, and gesture specification differ for different people, this section examined the influence of the listed three factors. Thus, a series of experiments was conducted on different experimenters. Referring to the results (see Figure 13 below), the recognition accuracy of user 3 was slightly lower than the rest due to different gesture size and specification. This signified that gesture posture, size, etc, drawn by different users, exerted a relatively small effect on the accuracy recognition outcomes.  
Figure 11: Recognition accuracy of each gesture.  
Figure 12: Recognition accuracy in different environments.
## 3 Results and Discussion
### Binding Free Energy Calculation
This coincides with the MD studies where it is shown that the stability of the analyzed ligands starts with acarbose, followed by luteolin, and ends with maysin. In summary, the strategy followed in this work defined a route for the prediction of molecular properties relevant to the biological activity of molecules. In this case, the quantum-chemical analysis provided useful information about the molecular geometry, as well as, the determination of the most susceptible zones for the hydrogen bond formation, which was crucial for a comprehensive study of the interaction within the active site of the macromolecule. Additionally, the regions of high electron density, called pharmacophores, were identified by the determination of HOMO and LUMO orbitals in the three ligands. These regions along with electrostatic potential surface (EPS) were employed in the binding sites analysis. The intestinal absorption of the ligands was predicted by cheminformatics calculations, using the molecular polar surface (PSA) and logP values. Once these properties regarding the molecules under study (ACA, MAY, and LUT) were determined, it was possible to analyze the interactions with the active site of NtMGAM. The best position of the ligand inside the active site and the binding affinity were identified by molecular \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Ligand** & **vdW** & **elec** & **PB** & **SA** & **G\({}_{\text{gas}}\)** & **G\({}_{\text{solv}}\)** & **G\({}_{bind}\)** \\ \hline ACA & \(-20.6092\) & \(-106.5299\) & \(113.4123\) & \(-5.1635\) & \(-127.1391\) & \(108.2488\) & \(-18.8903\) \\ LUT & \(-1.6924\) & \(-106.7976\) & \(93.7014\) & \(-3.3515\) & \(-108.4900\) & \(90.3499\) & \(-18.1401\) \\ MAY & \(-22.3635\) & \(-51.0776\) & \(72.2392\) & \(-4.2913\) & \(-73.4411\) & \(67.9480\) & \(-5.0346\) \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Binding free energy contributions for ACA, LUT, and MAY complexes. All energies are in kcal/mol. docking analysis. These results were determinant to define a starting point for molecular dynamics simulations. The stability of the coupling between ligand and macromolecule was analyzed by these simulations where the effects of the solvent and temperature were incorporated, showing that the hydrophobicity of the ligand is determinant to the affinity with the active site. On the other hand, the determination of oxidative damage in the amino acids of the active site was predicted by the charge transfer values, which were calculated with the chemical reactivity parameters and the molecular docking results.
# Microscope Enclosure for Temperature Regulation and Light Isolation
## 1 Introduction
An enclosure for the whole system has an advantage in that it can isolate laboratory lights from the sample and microscope optics. In addition, a whole-system enclosure can also provide a level of safety to laboratory occupants by isolating bright illumination sources, including UV-rich arc lamps utilized for conventional fluorescence microscopy and lasers used in specialized techniques such as confocal and multi-photon laser scanning, STED, TIRF, STORM/PALM, and SIM [13; 14; 21; 22; 23; 24; 25]. Microscope enclosures are available from commercial suppliers. However, a commercially designed and manufactured enclosure for a custom imaging system is often expensive. Some commercial systems also do not provide light isolation capability. To satisfy custom imaging systems, many research labs construct homemade enclosures out of various materials such as wood board, foam, plexiglass, polycarbonate, and PVC. The quality of these enclosure varies, with some suffering from light and air leaks, temperature gradients, and poor accessibility. From experience constructing multiple generations of enclosures, we have found that user-friendly and stable enclosures can be easily designed and constructed from lightweight expanded PVC board held by lightweight aluminum t-slot profiles mounted securely to an optics breadboard. These materials create a stable enclosure, which also does not significantly raise the system's center of mass, which can cause vibrational instabilities with a floating optics table. Considering the necessity of customization, we developed an enclosure platform that can be adapted to a variety of imaging systems. The design consists of vertical aluminum t-slot profiles which securely support black expanded PVC panels. These vertical posts create a stable structure for holding the panels, while also securely sealing the panels to create a dark interior. The vertical posts also enable easy access to the inside of the enclosure because the panels can readily slide along the posts. In addition, air baffles are incorporated to distribute air throughout the enclosure, producing a more uniform temperature when compared to an enclosure without baffles.
## 4 Results and Discussion  
In addition to MATLAB simulations, we performed comprehensive Verilog simulations using Synopsys tools to validate the functionality of the design. We employed Synopsys VCS as a simulation and verification tool, while we utilized Synopsys digital design tools for synthesis, placement, routing, and estimation of area and power consumption.
## 5 Regression Estimation Results
### All Sample Countries (90)  
Estimation results of the impacts of the influencing factors and control variables on ecological consumption for all sample countries are presented in Table 8. As can be seen from Models (1) and (2), the estimation results based on the country random effects model and the country fixed effects model were different, especially for the impacts of URB and MYS. Therefore, the Hausman test was conducted to select an appropriate model. The result of the Hausman test (the chi-square statistic was significant at the 1% level) shows that the null hypothesis, i.e., the country random effects model is appropriate, was rejected. Therefore, the country fixed effects model was selected. In Model (3), _Ln(GNIPC)_ was not statistically significant. In Model (4), neither _Ln(GNIPC)_ nor _Ln(GNIPC)_2 was significant. According to the arguments in Section 4, an inversed U-shaped or U-shaped relationship between ecological consumption and income could not be statistically validated. Therefore, a linear relationship was explored instead. The scatter plot of EF and GNIPC (Figure 3) further demonstrates that a linear relationship was more appropriate. We ought to interpret the estimated relationships between the independent variables and EF based on the Models (5) and (6). In Models (5) and (6), the estimated coefficients and significant extents of URB, REN, SER, MYS, and _Ln(GNIPC)_ showed small differences. URB, REN, and SER had statistically significant and negative impacts on EF. _Ln(GNIPC)_ had statistically significant and positive impacts on EF. MYS was statistically insignificant. The fact that INT was statistically significant in Model (6) and insignificant in Model (5) demonstrates that INT only had significant lagged impacts on EF. Relative to URB, REN, and SER, the lagged impacts of INT were weaker. The variance inflation factor (VIF) values of MYS and INT were 4.69 and 3.22, respectively, which demonstrates that the estimations of MYS and INT were not likely affected by the problems with multicollinearity. To sum up, for all sample countries, urbanization, renewable energy consumption, and service industries were the significant influencing factors of reducing ecological consumption; internet usage
# 3D Reconstruction of a Single Bubble in Transparent Media Using Three Orthographic Digital Images
## 4 Benchmark with Synthetic Bubbles
### Effects of Azimuth Angle  
The effect of azimuth angle on the accuracy of the reconstruction methods is studied by reconstructing three ellipsoids (samples No. 1, 3, and 7), as delineated in Figure 13. The mean relative error in the bubble volume calculated by the three methods, which denotes the accuracy of the methods in reconstructing the bubble, is similar when the azimuth angle is close to either 0 or 90\({}^{\circ}\). However, when the azimuth angle gradually deviates from either 0 or 90\({}^{\circ}\), the mean relative errors calculated by both the method in [PERSON] et al. [21] and [PERSON] et al. [20] are obviously larger than the MRE obtained by the method in this paper. Figure 13 shows the methods of [PERSON] et al. [21] and [PERSON] et al. [20] were more sensitive to bubble shape and rotation angles. Besides, the method in this paper was more stable in measuring bubble volume. It is notable that the bubble shapes and rotation angles had little impact on the volume measurement accuracy using the method in this paper.  
The ellipsoid (No.1) in 3 rd graph of Figure 13 was visualized in Figure 14 as an example, with their corresponding projection images for front view, side view, and top view. As shown in case 1 to 3 of Figure 14, the projection contours always overstated the bubble size. If bubble rotated around z  
Figure 12: The accuracy of the reconstruction methods as a function of sphericity.  
Figure 13: The accuracy of the reconstruction methods as a function of azimuth angle.  
axis, the front view and side view projection contours would become much larger. The reconstruction methods based on [PERSON] et al. (2018) and [PERSON] et al. (2019), by this token, would have larger uncertainties and unstable predictions. This scenario got significant when the azimuth angle was approximate to 45\({}^{\circ}\).
## 5 Evaluation and Results  
This section presents an experimental evaluation of GenSQLi and reports its performance metrics. The evaluation addresses the following key research questions:  
* RQ1: Generative Effectiveness--How effective are the SQL injection (SQLi) attacks generated by the Large Language Model (LLM)?
* RQ2: Attack Novelty--How many of these generated attacks successfully bypass Web Application Firewalls (WAFs) configured with state-of-the-art rules?
* RQ3: Rule Generation--How effective are the defense rules produced by our combined machine-learning and generative AI approach in mitigating these attacks?
* RQ4: LLM Portability--How well does the methodology generalize when applied to different LLMs?
## 3 Results and Discussions
### Variation in the Drag Line length with Laser Cutting Speed  
Based on the previous experiment, we conducted other experiments, changing the cutting speeds to 30, 50, 90, 130, and 150 mm/min at the focal position of \(-\)30 mm and the laser power of 9 kW. At the cutting speed of 150 mm/min, the material was not completely cut, owing to a delay in cutting. Therefore, the results for cutting speeds up to 130 mm/min were compared and are shown in Figures 8 and 9.  
Figure 9 shows the front- and rear-surface kerf widths and taper values as functions of the laser cutting speed. The front-surface kerf widths were generally similar for all conditions, and no clear trend could be observed with respect to the parameters. However, the rear-surface kerf width tended to decrease as the laser cutting speed increased. This is  
Figure 7: Topographic color distribution of cutting surface according to the laser power; (**a**) \(P=7\) kW, (**b**) \(P=9\) kW, (**c**) \(P=11\) kW, (**d**) \(P=13\) kW (Processing conditions: \(f_{\rm d}=-30\) mm, \(v=30\) mm/min, \(d_{\rm N}=3\) mm, \(P_{\rm G}=10\) bar, Nozzle type = Normal plate).  
because the mass flux of the assist gas into the kerf decreased with the heat input owing to the high speed, and the molten metal was not completely discharged. Therefore, the smallest difference between the front- and rear-surface kerf widths was at a cutting speed of 30 mm/min.  
Figure 10 shows the cross-section and topographic color distribution of the cutting surface at different laser cutting speeds. As the cutting speed increased, the length of the drag line gradually decreased in the middle area, which can be observed from the  
Figure 8: Variation in roughness by the distance from the front surface according to the laser power.  
Figure 9: Variation in kerf width and taper according to the cutting speed.  
cross-section and the cutting surface. The drag line in the middle area indicates the region created when a large quantity of metal is melted near the depth of focus and the melt flow direction is changed from downward to partially backward. This decrease in the drag line length in the middle area can be attributed to the increase in cutting speed, the decrease in the corresponding heat input, as well as the reduced effect of the depth of focus. The roughness of the cutting surface, which can be confirmed based on the topographic color distribution, increased as the mass flux of the assist gas into the kerf decreased with increasing cutting speed.  
These results using a stand-off distance of 1 mm were compared with [PERSON] et al.'s study [25] conducted under the condition of a standoff distance of 10 mm. As a result, it was possible to obtain a high-quality cutting surface with a relatively small taper and low roughness of the cutting surface as the inflow of the assist gas into the kerf was increased.
## 3 Materials and Methods
### Methods
#### 3.2.4 Performance Metrics  
For segmentation tasks, the five metrics used to evaluate performance are the Dice Similarity Coefficient, Jaccard Index, specificity, sensitivity, and accuracy. The formulas for these metrics are as follows:  
\[\text{Acc}\ =\ (\text{TP}+\text{TN})/(\text{TP}+\text{TN}+\text{FP}+\text{ FN}) \tag{9}\]  
\[\text{Dice}\ =\ (2\times\text{TP})/(2\times\text{TP}+\text{FP}+\text{FN}) \tag{10}\]  
\[\text{Jaccard Index}\ =\ \text{TP}/(\text{TP}+\text{FP}+\text{FN}) \tag{11}\]  
\[\text{Specificity}\ =\ \text{TN}/(\text{TN}+\text{FP}) \tag{12}\]  
\[\text{Sensitivity}\ =\ \text{TP}/(\text{TP}+\text{FN}) \tag{13}\]For classification tasks, in addition to accuracy, sensitivity, and specificity, we commonly use F1 score and precision. The formulas for these metrics are as follows:  
\[\text{Precision}\ =\ \text{TP}/(\text{TP}+\text{FP}) \tag{14}\]  
\[\text{F1 Score}\ =\ 2\times(\text{Precision}*\text{Recall})/(\text{Precision}+ \text{Recall}) \tag{15}\]
# Study on Shear Mechanism of Bolted Jointed Rocks: Experiments and CZM-Based FEM Simulations
###### Abstract  
Based on the underground jointed rock of the Huangdao water sealed oil depot in China, the shear failure mechanism of bolted jointed rock is studied through laboratory experiments and numerical simulation. Laboratory experiments are performed to explore the shear behavior of bolted jointed rock with different joint roughness. Our results show that using high strength bolts is beneficial to improving the shear strength of the jointed rock, but the high strength of bolts can also lead to the rock fracture, which should be avoided. For this particular project site, experimental results indicate that 15% elongation is the best. In addition, a new numerical simulation method with CZM (cohesive zone model) used for modeling the shearing process of bolted jointed rock is proposed. It can reasonably describe the characteristics of jointed rock as a discontinuous medium, and bolt as a continuous medium, that replicate well the shearing process. The numerical model is then verified by comparing the experiment results, and it can be effectively be applied to the simulation of joint shearing process. Finally, we use this simulation method to explore the shear failure mechanism of bolted joints, and find that the root cause of rock failure is the deformation mismatch between the bolt and the surrounding rock. The tensile stress between them eventually causes the rock to fracture near the bolt hole.  
Keywords:bolted jointed rock; elongation; shearing process; cohesive zone model +
Footnote †: journal: Applied Sciences
## 4 The Proposed Development Model: Holistic Security and Accessibility Layered Architecture (HSALA)
### Description of the Architectural Models  
#### 5.1.1 _Holistic Security and Accessibility Layered Architecture_ (HSALA)  
HSALA introduces a multi-layered approach that integrates both functionality and security at each level. The model consists of five main functional layers (Data, Persistence, Application, Content Presentation, and Accessibility Enhancement), each paired with a corresponding security layer. Table 1 summarizes the core responsibilities of each layer and its associated security measures.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Layer** & **Functionality** & **Security Layer** \\ \hline \multirow{3}{*}{1. Data Layer} & Responsible for data storage and management, utilizing databases like MySQL, PostgreSQL, or MongoDB. & Data Security Layer: Ennsures detection through encryption, data masking, and compliance with data protection regulations (e.g., GDPR). \\ \cline{2-3}  & Handles data access logic, providing an abstraction over the Data Layer using Object-Relational Mapping (ORM) tools. & Persistence Security Layer: Implements secure data access practices, including authentication, authorization, and protection against SQL injection. \\ \hline \multirow{3}{*}{3. Application Layer} & Contains the core business logic, processing user inputs, and enforcing application workflows. & Application Security Layer: Secures the application logic through secure coding practices, input validation, and application-level firewalls. \\ \cline{2-3}  & Manages the user interface using web standards (HTML, CSS, JavaScript) and focuses on UX/UI design. & Content Presentation Security Layer: Protects the front-end from client-side attacks, implementing measures like Content Security Policy (CSP) and HTTPS enforcement. \\ \hline \multirow{3}{*}{5. Accessibility Enhancement Layer} & Enhances the application’s accessibility by implementing standards like WAI-ARIA, ensuring compliance with WCAG. & Accessibility Security Layer: Ensures that accessibility features do not introduce vulnerabilities and that security measures are accessible to all users. \\ \cline{2-3}  & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Description of HSALA model.  
The layered structure of HSALA highlights the comprehensive integration of functionality and security at every level. This ensures that both operational effectiveness and protective measures are inherently built into the architecture. By pairing each functional layer with a corresponding security layer, HSALA provides a robust framework for developing secure and accessible web applications.
# Efficient V2V Communications by Clustering-Based Collaborative Caching +
## 2 Related Work  
Here, we introduce the basic CCN and review related work on clustering algorithms, collaborative caching methods, and routing protocols for vehicular networks. Table 1 shows a brief explanation of each related method.  
\begin{table}
\begin{tabular}{l c l} \hline \hline
**Reference** & **Kind** & **Description** \\ \hline
[10] & Cluster construction & Construct clusters based on inter-vehicle distances, vehicle heights, and route stability \\
[11] & Cluster construction & Clusters may be constructed with multi-hop distances \\
[3] & Reducing the cache redundancy & Cache probability is determined by channel usage \\
[7] & Reducing the cache redundancy & Cache probability is determined by content \\  & & similarity and vehicle mobility \\
[8] & Reducing the cache redundancy & Cache probability is determined by the \\  & & characteristics of vehicles’ mobility \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparison of related methods.
## 6 Results
### Total RE Installed Capacity vs. Total no. of Policies  
Table 11 depicts a brief summary for the linear regression results, relating the total RE installed capacity and total policies. The correlation coefficients of the China, Brazil, and USA models are 0.985, 0.962, and 0.82, respectively. All the coefficients are positive, have large values, and are statistically significant in the 1% confidence level. This emphasizes the existence of a strong positive relation between the RE development and the total number of policies. The F-statistics for all three countries are statistically significant (having \(p\)-values \(<\) 0.01), which gives credence to the fitness of the model. Additionally, the adjusted R\({}^{2}\) for the three countries lie between 0.651 and 0.968, which indicates that the total number of policies explain from 65.1% to 96.8% of the total RE capacity variation. It should be indicated that China has a larger capacity per policy ratio than Brazil and the USA (because the slope of the linear relation is the largest for China; coefficient = 4.967). It is worth noting that the correlation coefficient and R\({}^{2}\)adj in the USA model are less than the corresponding values for China and Brazil. This may mainly be due to the fact that there are many states with different regulations in the USA, and the policies are not the main drivers of RE installations.
# State-of-the-Art DC-DC Converters for Satellite Applications: A Comprehensive Review
## 5 Future Directions
### Wide-Band-Gap Devices  
New technologies like WBG devices (SiC and GaN) provide better performance compared to Si technology [134; 135; 136; 137]. Recent research on WBG devices has demonstrated their superior efficiency and power density compared to Si-based devices [138; 139]. However, the capabilities of WBG devices cannot be fully exploited by simple replacement. System- and component-level refinements need to be performed. With the integration of WBG, switching frequencies above hundreds of kilohertz are theoretically allowed. This can help reduce the value of the inductors and hence the dimensions of the converter. Nonetheless, increasing the switching frequency poses various challenges, such as increased switching losses, parasitic effects, and heat management, which should be carefully studied. Additionally, the reliability of such devices for application in space needs to be studied in detail, especially their performance under radiation regarding single-event effect (SEE) and single-event burnout (SEB) [140]. Heat management at high power levels, which affects the efficient operation of a power converter, is another open area of research in the future [141].