esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Performance Modeling of the IASF-IoT Framework
### Sensitivity Analysis
The performance model focuses on four key areas: processing power utilization, memory usage, energy consumption, and network latency. These parameters are crucial in evaluating the practicality of security solutions, particularly for resource-constrained IoT devices that often operate on limited battery power and with minimal processing capabilities.
# Precise Calculation of Inverse Kinematics of the Center of Gravity for Bipedal Walking Robots
## 2 Materials and Methods
### Robot Dynamics  
The method developed in this study uses the reference CoG trajectory. Thus, the dynamics of the robot are obtained using the linear inverted pendulum method. In the 3-dimensional linear inverted pendulum model (3 DLIPM) shown in Figure 2, the desired surface equation is reached by setting \(k_{x}=0\) and \(k_{y}=0\). As the height of the inverted pendulum, \(z_{c}\) is taken as a constant.  
After making these arrangements, the differential equations that define the system can be given with Equations (12) and (13).  
\[\ddot{x}=\frac{g}{z}x \tag{12}\]  
\[\ddot{y}=\frac{g}{z}y \tag{13}\]  
Figure 2: Three-dimensional linear inverted pendulum model (3 DLIPM).  
Step positions are set in a matrix \(p\), as given in Equation (14). The trajectory of the CoG is obtained as the output.  
\[p=\begin{bmatrix}s_{x0}&s_{x1}&s_{x(n-1)}&s_{xn}\\ s_{y0}&s_{y1}&\dots&s_{y(n-1}&s_{yn}\\ s_{z0}&s_{z1}&s_{z(n-1)}&s_{zn}\\ \end{bmatrix} \tag{14}\]  
Using Equations (12)-(14), for a step length of 0.3 m (\(s_{x}\)), a step width of 0.065 m (\(s_{y}\)), and a CoG height of 0.45 m (\(z_{c}\)), the trajectory of the CoG is found, as shown in Figure 3. When the foot position is taken as a reference, the height of the hip of the robot in this case is 0.826 m. The step height is 0.075 m (\(I_{h}\)s). The foot trajectories are continuous up to the second derivation [36].  
In Figure 3, the robot starts its movement by taking a step with its right leg. It walks for a total of 6 steps and stops.
## 4 Quantum Exchange Lock Parallel Scheduler
### Quantum Circuit Hierarchical Strategy Based on Qelps  
The QELPS algorithm includes a greedy layering strategy based on SWAP conflicts and a secondary layering strategy leveraging quantum lock parallelism. Together, they aim to reduce SWAP gate usage, optimize circuit depth, and enhance execution efficiency. Its main operation steps are as follows: Additionally, the algorithm dynamically adapts to the circuit's evolving state to further refine the scheduling process. 1. **Initial layering:** First, identify all quantum gates that do not meet the CNOT constraints and analyze possible SWAP gate insertion schemes to ensure that the initial layer can meet the requirements of the hardware topology. Based on this analysis, build the first layer and use it as the basis for subsequent layering. 2. **Intra-layer filling and conflict handling:** Fill as many executable quantum gates as possible in the current layer to ensure maximum parallelism. If there is a conflict caused by topological restrictions or data dependencies, the conflicting quantum gates will be postponed to the next layer to avoid unnecessary SWAP gate overhead. 3. **Dynamic adjustment of the number of layers:** As the quantum gates are gradually filled in, the algorithm will flexibly increase or merge the layers according to the number of quantum gates in each layer, the execution parallelism and its conflict with the SWAP gate, thereby optimizing the circuit structure and improving the computing efficiency. 4. **Screening micro-conflicting SWAP gates:** In the first layer, simulated SWAP gate insertion is performed on all quantum gates that do not meet the quantum bit mapping requirements. By analyzing the impact of different SWAP gates, SWAP gates that onlyslightly conflict with the current layer are screened out to minimize the additional SWAP gate overhead. 5. **Quantum locking and gate movement:** The quantum gates in the first layer are locked to ensure the stability of circuit execution. In terms of execution order, CNOT gates are unlocked and executed before SWAP gates. Subsequently, quantum gates that will not conflict with the SWAP gates of the first layer and can be directly executed are selected in the subsequent layers to fill in the layer to optimize the entire scheduling process. 6. **Constructing all levels:** Repeat the optimization process of (4) and (5) for the subsequent levels, gradually fill in all quantum gates, and resolve mapping conflicts until the scheduling of the entire circuit is completed. The pseudo code of the QELPS algorithm is as follows (Algorithm 1). ``` Input: Quantum Circuit(\(Q\)) : The initial set of quantum operations to be optimized. Architecture(\(A\)) :The specific quantum computer's layout that dictates how qubits can interact. Output: Compiled Circuit(\(C\)) : The optimized version of \(Q\), adapted for efficient execution on \(A\).
## 3 Methodology
### Data Collection  
Data collection was carried out through interviews between August 2024 and February 2025, where structured and semi-structured responses were obtained from a sample of 200 profiles from different organisations (operational, administrative, and strategic). Also, cybersecurity incident documents published in different sources between 2024 and 2025 were collected (see Table 2).The interviews focused on understanding (a) security technical aspects to identify technological gaps in the infrastructure, (b) response and impact on work teams to understand how the crisis was managed within the organisation, and (c) to know the strategies implemented to safeguard the reputation and image by the organisations; for this purpose, different frameworks categorised with questions according to the interests of the case study and the scientific literature were analysed, (see Table 3). From there, an application instrument was designed for the interviews (see Appendix A). \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Sector** & **Description** & **Profit (USD M)** & **Companies** \\ \hline Banking and Financial & Financial institutions, including traditional banks & & \\ Banking and Financial & and emerging fintech companies offering & 3850 & 22 \\  & comprehensive banking services. & & \\ Healthcare & Medical service providers, hospitals, clinics, and & & \\  & pharmaceutical manufacturers with growing & 2100 & 30 \\  & telemedicine segment. & & \\ Government & Public entities at national, regional, and municipal & & \\  & levels, including regulatory bodies and state & 1450 & 12 \\  & enterprises. & & \\ Consulting & Professional services in business strategy, & & \\  & management, and specialised industry consulting. & 980 & 18 \\ Technology & Software development, IT services, & & \\  & telecommunications, and digital transformation & 1680 & 25 \\  & across major urban hubs. & & \\ Services & Diverse providers in telecommunications, & & \\  & transportation, logistics, hospitality, and personal & 4250 & 28 \\  & & & \\ Agriculture & Production and processing of coffee, flowers, & & \\  & tropical fruits, sugar, and livestock for domestic & 1950 & 15 \\  & and export markets. & & \\ EPS (Health Insurance) & Health promotion entities managing insurance & & \\  & and healthcare access under Colombia’s social & 1120 & 7 \\  & security system. & & \\  & Public and private institutions across all education & & \\ Education & levels from K-12 to higher education and & 920 & 16 \\  & vocational training. & & \\  & Generation, transmission, and distribution of & & \\ Energy & electricity, including growing renewable energy & 2750 & 14 \\  & initiatives. & & \\ Environment & Environmental consulting, waste management, & & \\  & water treatment, and sustainable development & 780 & 13 \\  & projects. & & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Colombian economic sector overview.
## 3 Full Description of the Approach
### Reconstruction of Structural Elements
#### 3.3.1 Element Description into _Obj_ Format  
Based on point clouds extracted in the first part of the approach, slabs and walls are reconstructed with either volumes or surfaces. Several assumptions are taken into account for the reconstruction: slabs are horizontal, walls follow the vertical and the two sides of a wall are parallel.  
For the description of slabs of the building, the altitudes of ceilings and grounds are used. The ground level of a floor describes the upper part of a slab whereas the ceiling level of the floor below describes the lower part of the slab. One should note that if several ceiling levels are encountered for a floor, the highest ceiling level is taken into account for the definition of the slab. A slab is described by a rectangular solid. In the vertical plane the level of the upper and the lower part of the slab is used and in the horizontal plane slab limits are determined considering the contours of the floor. For the two slabs located at the ends, a default value of thickness is used.  
The walls identified in the previous part of the approach are composed of 1 to \(p\) planes. Their reconstruction consists of adjusting either volumes or surfaces to the wall point clouds.  
1. **Wall composed of one plane:** It can be encountered when only one side of a wall is determined or for elements such as pillars. In this case a line is adjusted to the plane point cloud projected in an horizontal plane. The wall portion is described by two points in the X-Y plane.
2. **Wall composed of two planes:** If the two planes do not describe the two sides of a wall, the method of the case 1 is used. Otherwise, two lines are adjusted to the two plane point clouds projected in the horizontal plane. The wall axis is determined by the average of the two lines and the half-thickness is calculated by the average of distances between the points of both planes and the axis of the wall. Based on the axis and the thickness of the wall, four points are constructed to describe the wall in the X-Y plane.
3. **Wall composed of more than two planes:** In this case, planes located in each side of the wall are grouped. If only one side is identified, the method of case 1 is used. If two sides are identified, the method proposed in case 2 is considered.  
A slab is described by a volume composed of eight points and six facets. A wall is described either by a volume composed of eight points and six facets or by a surface composed of four points and one facet. Based on these information, a file in obj format is created. Figure 8 shows the result of the reconstruction for the 1 st floor of the INSA building. In this figure the slab is in grey, the walls reconstructed by volumes are in orange-red and portions of walls reconstructed by surfaces are in yellow.
## 3 Results and Discussion
### Initially Proposed Protocols (2014-2015)
#### 3.4.2 Submerged Neck Protocol  
Some research groups proposed the implant placement with the neck partially/completely submerged. These studies proposed this placement following the concept of submerged healing [23; 28]. The convergent neck was positioned along the soft tissues but still became completely immersed in the soft tissues. Using this protocol, a second surgery to expose the neck was necessary to proceed with the prosthetic phases. Some further investigations used healing abutments to avoid surgeries and bone loss [26; 27]. The prosthetic phases were performed with open custom ray impressions and the preparation of screw-retained provisional and definitive rehabilitations. High survival rates and reduced bone loss were observed in 1- to 3-year clinical studies, with the MBL ranging from 0.09 mm to 0.65 mm [19; 20; 23; 24; 25; 26; 27]. Some limitations, however, should be considered. The implant insertion at the crestal or deep crestal level implies the formation of a transmucosal tunnel and an implant abutment connection closer to the bone tissues. The transmucosal tunnel could be susceptible to bacterial infections [55; 56]. A large number of histological and clinical studies revealed that the implant-abutment connection suffers from high strains and is a critical area when marginal bone remodeling events start after the loading phases [53; 57].
## 6 Issues and Future Directions
### Standard Method and Dataset for Accuracy Assessment  
Accuracy assessment of fused results is an urgent issue for spatiotemporal data fusion field. There are two challenges: no widely accepted assessment method and no standard data sets. Basically, accuracy assessment is the evaluation of the similarity between fused and a true image (it is a known fine image at the prediction date). The similarity includes two aspects: the closeness of spectral values of the fused image to the true image, and the spatial details the fused image reserved compared with the true image. For the accuracy assessment methods, most existing studies use some global accuracy indices, including RMSE, the correlation coefficient, absolute difference, and relative difference. However, these indices most likely reflect the image-level spectral similarity rather than pixel-wise spatial details. In a current study of assessing downscaled results of thermal images, a new index was proposed [104]. A similar idea can be extended to evaluate accuracy of spatiotemporal data fusion. In addition, a standard dataset is important for the comparison among different spatiotemporal data fusion methods. As listed in Table 3, more than 40 spatiotemporal data fusion methods have been proposed. There is a need to have a cross-comparison to guide users to select the most suitable method for their specific cases. This standard dataset should include the most challenging cases in spatiotemporal data fusion, such as images with heterogeneous land surface and experiencing abrupt land cover change during the fusion period. A study used MODIS and Landsat images in two sites with contrasting spatial and temporal variability to compare STARFM and ESTARFM, and they released the dataset for public use [105]. This dataset has been used to test performance of some newly developed spatiotemporal data fusion methods [26; 43]. This dataset can be used as a starting point to develop a future standard dataset for testing the performance of spatiotemporal data fusion methods.
# Adsorption of Metolachlor and Its Transformation Products, ESA and OXA, on Activated Carbons
## 3 Results
### Characterization of Precursors and Activated Carbons
#### 3.1.2. Physico-Chemical Characterization of Activated Carbons
Figure 2 shows the comparison of the DTG profiles of the raw materials and impregnated samples with K\({}_{2}\)CO\({}_{3}\), where the profile of the K\({}_{2}\)CO\({}_{3}\) powder is also included for comparison. The first mass loss for both precursors was observed below 150 \({}^{\circ}\)C, associated with the desorption of the moisture, hydrocarbons and the residual volatile matter. The degradation of the lignocellulosic materials was observed between 200 and 400 \({}^{\circ}\)C, and a small shoulder followed by a main peak were observed for both residues. The shoulders at 280 and 290 \({}^{\circ}\)C for rape and sunflower, respectively, correspond to the hemicellulose degradation, while the main peak is associated with the cellulose decomposition at 320 and 340 \({}^{\circ}\)C, respectively. The lignin degradation peak (expected at ca. 375 \({}^{\circ}\)C) is probably masked by the other peaks [29; 30; 31; 32]. Similar total mass loss was observed for both precursors (67% for rape and 64% for sunflower). However, the thermal decomposition of the raw material impregnated with the activating agent revealed a shift in the mass loss to lower temperatures, being more remarkable for rape residue. This behavior was reported for other lignocellulosic materials [33; 34], suggesting that the presence of K\({}_{2}\)CO\({}_{3}\) modifies the carbonization process of the precursor. Additionally, in the case of sunflower, the mean peak was followed by a shoulder, indicating that the degradation is splitting. The material activated with phosphoric acid rendered a less porous material (R-PO) compared with those activated with K\({}_{2}\)CO\({}_{3}\), despite of the H\({}_{3}\)PO\({}_{4}\) is considered as strongest activating agent [35]. One of the reasons for this is that this activation process was carried out at a lower activation temperature (500 \({}^{\circ}\)C); additionally, the phosphoric acid could alter the structure of the lignocellulosic material, forming larger structural units, resulting in a rigid crosslinked solid affecting the final porous structure of the obtained material [36]. With respect to the activation yield, this material showed the highest value--almost three times that of R-KC's yield (Table 2)--due to the above-described crosslinking and the ability of the acid to lead the hydrolysis of hemicellulose and cellulose, leaving a high amount of carbon coming from lignin [32]. According to the superficial pH values (Table 2), sample R-PO shows a hydrophilic character, as expected considering the synthetic route. However, the samples obtained by activation with K\({}_{2}\)CO\({}_{3}\) presented a neutral-basic character. Figure 1: Nitrogen adsorption/desorption isotherms at \(-\)196 \({}^{\circ}\)C of the four activated carbons (close symbols represent adsorption and empty symbols represent desorption branch).
# Steady-Suction-Based Flow Control of Flutter of Long-Span Bridge
## 4 Concluding Remarks  
Wind tunnel experiments were conducted to prove the feasibility of the steady-suction-based flow control method in practical applications and to investigate the control effect on the flutter stability of the bridge deck. The impact of the self-defined control parameters (i.e., suction slot position, suction interval, and suction rate) was studied in detail, and the FDs were analyzed to investigate the control mechanisms. The following conclusions can be drawn:  
The flutter performance of the 2 DOF bridge section model could be improved with the steady-suction-based flow control. The critical flutter speed was increased by up to 10.5% with optimal control parameters.  
The effectiveness of the steady-suction-based flow control method was influenced by various control parameters, including the suction slot position, suction interval, and suction flow rate of the single slots. The experimental results showed that activating the suction slot on the windward side of the bridge to directly disturb the flow separation was the best control choice. Moreover, a superior aerodynamic shape was constructed when the relative suction interval was reduced and the suction flow rate increased to strengthen the control effect.  
Based on the FD analysis of all the studied cases, the steady-suction control system influenced the FDs, particularly \(A_{1}^{*}\), \(A_{2}^{*}\), \(H_{1}^{*}\), and \(H_{2}^{*}\), which were related to the aerodynamic damping of the structure. In conclusion, the steady-suction-based control method strengthens the total damping of the structure by reducing negative aerodynamic damping, which promotes the dissipation of vibration energy and improves the flutter stability of the bridge deck.  
Conceptualization, D.X.; methodology, H.Z. and Z.L.; validation, J.Z.; formal analysis, H.L.; investigation, Z.L.; resources, D.X.; data curation, H.Z.; writing--original draft preparation, J.Z. and H.L.; writing--review and editing, J.Z.; visualization, H.Z.; supervision, J.O.; project administration, Z.L. and H.L.; funding acquisition, D.X. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China, grant number 51878131.  
The work was conducted in the Joint Laboratory of Wind Tunnel & Wave Flume at the School of Civil Engineering, Harbin Institute of Technology, China.  
The authors declare no conflict of interest.  
Figure 13: Flutter wind speed versus suction flow rate.
# Predicting the Mine Friction Coefficient Using the GSCV-RF Hybrid Approach
###### Abstract  
The safety and reliability of a ventilation system relies on an accurate friction resistance coefficient (\(\alpha\)), but obtaining \(\alpha\) requires a great deal of tedious measurement work in order to determine the result, and many erroneous data are obtained. Therefore, it is vital that \(\alpha\) be obtained quickly and accurately for the ventilation system design. In this study, a passive and active support indicator system was constructed for the prediction of \(\alpha\). An RF model, GSCV-RF model and BP model were constructed using the RF algorithm, GSCV algorithm and BP neural network, respectively, for \(\alpha\) prediction. In the GSCV-RF and BP models, 160 samples compiled with the prediction indicator system and were used to construct a prediction dataset and, this dataset was divided into a training set and a test set. The prediction results were based on the quantitative evaluation models of _MAE_, _RMSE_ and \(R^{2}\). The results show that, among the three models, the GSCV-RF model's prediction result for \(\alpha\) was the best, the RF model performed well and the BP model performed worst. In the prediction for all the datasets obtained by GSCV-RF model, all the values of \(MAE\) and _RMSE_ were less than 0.5, the values of \(R^{2}\) were more than 0.85 and the value of \(R^{2}\) of the passive and active support test sets were 0.8845 and 0.9294, respectively. This proved that the GSCV-RF model can offer a more accurate \(\alpha\) and aid in the reasonable design and the safe operation of a ventilation system.  
safety engineering; mine friction resistance coefficient; random forest; GSCV-RF; roadway support +
Footnote †: journal: Applied Sciences
# Graph Layer Security: Encrypting Information via Common Networked Physics
## 4 Simulations and Results
### GLS Performance with Passive Eavesdroppers
It is seen that the ratios of (Tx,Rx) pairs belonging to the low BER regions are always larger than those from the passive eavesdroppers (except for the one hacking 25% network nodes and obtaining the full physical networked dynamics). For instance, when measurement noise variance \(\sigma^{2}<10^{-4}\), the ratio of (Tx,Rx) with BER less than \(10^{-3}\) approaches 1, larger than those eavesdroppers (i.e., with hacking 0%, 5%, and 10% nodes). This statistical result, combined with the previous average result in Figure 4, demonstrates the encryption robustness and reliability of the proposed GLS to secure wireless communications against potential passive eavesdroppers.