esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Analysis of Test Results
### Failure Mode Analysis  
The high-speed camera captured the debonding failure process of rockbolt, and five pictures with obvious changes were selected, as shown in Figure 9.  
During debonding with the transparent rock sample, white spots were produced on the anchorage agent, indicating that it slipped. Combined with the schematic diagram of debonding failure process, the process is divided into three stages:  
In the crack initiation stage (459.7 ms), the first part of the rockbolt suffers from the bigger impact load, but the affected zone of impact load is lesser. Maximum shear stress occurs at I interface. At the local position of the anchoring agent faint white spots occur, which indicates a debonding slip at I interface. The anchoring agent suffers from shear crack in the middle of the rockbolt, as shown in Figure 9b.  
Figure 8: Axial force and interfacial shear stress distribution curve. (**a**) Distribution curve of rockbolt axial force (**b**) Distribution curve of shear stress.  
In the crack coalescence stage (459.7 ms-461.2 ms), when the impact load transfers to the middle of the sample, the affected zone of impact load spreads to both sides, and the whole sample bears the impact load, which results in cracks in the middle of the anchoring agent. The increase in white spots on II interface is especially obvious. At the back end of the sample, the rockbolt and the anchoring agent move slightly, and the shear cracks of the anchoring agent in the middle of II interface gradually increase and coalesce. There is no large slip in the first half of the interface of the anchorage agent, and local position has sporadic slip marks; there are also obvious shear slip marks in the second half of the anchorage agent, and the scratches are serration, as shown in Figure 9c.  
In the debonding slip stage (461.2 ms), when the load transfers to the left end, white spots at the anchoring agent of II interface gradually become bigger, and a few more white spots appear. The crack on the anchoring agent expands gradually, and the rockbolt and anchorage agent experience a significant slip, indicating debonding at both interfaces. The tear zone of the anchoring agent in the middle of II interface further increases, as shown in Figure 9d. The white spots on the II interface continue to increase, and the relative slip of the rockbolt and anchorage agent gradually increase; the tearing area of the anchoring agent also reaches its maximum. Due to the mechanical bite between the transverse rib of the rockbolt and the anchoring agent, it is difficult to observe a relative debonding slip. However, the intine of the reserved hole is smooth, and the rockbolt-anchoring agent appears to slip relative to the surrounding rock sample. Therefore, the rockbolt and anchoring agent are rushed out in the latter part, as shown in Figure 9e.  
To sum up, the debonding failure process of the anchoring agent under impact load is dual-interface mixed, as shown in Figure 10.  
Figure 9: Debonding failure process of anchorage specimen.
# A Review of Fabrication Technologies for Carbon Electrode-Based Micro-Supercapacitors
## 5 Fabrication Technologies of Carbon Electrode-Based Micro-Supercapacitors
### Etching Methods
#### 5.3.1 Laser Etching  
Laser etching is simple, clean, time-saving, and can be up-scaled. The fabrication of micro-supercapacitors can be precisely controlled with the laser parameters such as wavelength, scanning speed, pulses per area, pulse duration, pulse frequency, and power [85; 171; 172; 173].  
Laser direct writing has been used for the fabrication of micro-supercapacitors, as the laser can locally reduce graphite oxide to obtain a graphene porous structure, and this method offers more flexibility, in terms of patterning, in comparison to conventional printing or lithographic techniques [174; 175]. Moreover, as it does not require contact or masks, this method is simple and cost-effective, and this fabrication method can be used with a pulsed UV laser for micro-writing of reduced graphene oxide electrodes, which are separated by the unreduced portion of the graphite oxide film [176]. Interdigitated patterns were also produced by laser etching on reduced graphene oxide and poly (3,4-ethylenedioxythiophene)/poly(styrenesulfonate) (PEDOT/PSS) composite [177]. The laser direct writing was employed, as well, to fabricate integrated asymmetrical micro-supercapacitor arrays (on indium tin oxide-polyethylene terephthalate film) with good flexibility, high areal capacitance, and an energy density of 12.2 \(\upmu\)Wh/cm\({}^{2}\)[178]. Synthesis of P-doped porous graphene micro-capacitors was achieved using laser direct writing on freestanding H\({}_{3}\)PO\({}_{4}\)-incorporated polyimide/polyvinyl alcohol composite membranes [179].
# Machine Learning-Based Garbage Detection and 3D Spatial Localization for Intelligent Robotic Grasp
## 4 Experiments and Results
### Garbage Point Cloud Extraction
Vision-driven robotic grasp requires obtaining the garbage location and posture from a noisy, complex background scene image. In this work, deep learning networks like the Yolactedge model are then used for object recognition and segmentation. As we know, Robotic grasp is a challenging question that includes perception, planning, and control theory. Thus, research on the 3D reconstruction and measurement of objects helps with feature extraction or obtaining valuable information from RGB or point cloud data, which will then be used to grasp pose prediction. A typical vision-guided industrial robot system is shown as Figure 8.  
The robot grasp system consists of mobile vehicle, UR robot, stereo camera and clamping tool. As can be seen from Figure 8, a RealSense D415 (product of Intel company) camera is mounted on the tool of UR5 robot, a two driving-links of gripping jaw is employed to pick up garbage through object detection and localization algorithm. Hand-eye coordination calibration technology is performed to establish the mathematic relationship between camera coordinate and robot base coordinate. The internal and external parameters of the robot grasp system is calibrated as:  
\[\text{Intrinsic matrix}: \begin{bmatrix}616.7279&0&319.8949\\ 0&616.4918&248.8294\\ 0&0&1\end{bmatrix} \]  
Figure 8: Our vision-guided robotic grasp equipment for garbage picking up application. \[\text{Extrinsic matrix}: \begin{bmatrix}-0.6038&-0.3062&0.7358&642.4042\\ -0.7802&0.4156&-0.4673&928.8404\\ -0.1627&-0.8564&-0.4899&798.8497\\ 0&0&0&1\end{bmatrix} \]  
Thus, the garbage grasp pose in Figure 7 is converted through intrinsic and extrinsic matrix from camera coordinate to robot base coordinate, some examples are shown in Figure 9.
## 5 Reversibility Evaluation of VRIS Image Steganography Model  
Reversibility of image steganography algorithms is crucial for legitimate users during the information transmission process to ensure the integrity and accuracy of secret images during extraction. As for illegal users, reversibility leads to difficulties in obtaining information about the secret image, thus further enhancing the security of the information. In order to evaluate the reversibility of the VRIS image and hence the frontal model, we choose pixel error and extraction accuracy as evaluation metrics. Pixel error provides a visual measure of the difference between two images of the same resolution, while extraction accuracy is used to quantify the similarity between encrypted images and the secretly reconstructed image; a higher accuracy means that the extracted information is closer to the original secret image.
# A Reference Model for Monitoring IoT WSN-Based Applications
## 4 Model Description
### Information Layer
#### 4.2.3 Triggering  
Usually, information collected by a monitoring system is captured when some relevant event occurs in the monitored system. For instance, a software trap informs the monitoring system that a packet communication has been done successfully, or periodically informs of the remaining battery in the mode. In other cases, to characterize the global system functioning it is necessary to perform a synchronized capture in several modes when some events happen in other motes or even following external conditions defined by the user.  
However, sometimes the event that causes the acquisition of information is not generated by the monitored system. For instance, it may be of interest to measure the battery level when a special condition happens, i.e., when the mote is transmitting, or even triggered by a combination of several factors, some of them being system-dependent and other programmed by the monitoring user. The generation of a trigger signal, which indicates when the information has to be captured, may follow several policies:  
* Periodical: the trigger signal is generated with a predefined period. The Information Layer may synchronize the trigger signals in different probes in the system, even when those probes are located in different motes, in order to get a simultaneous snapshot of the system.
* On user query: the visualization element may receive from the user the order to capture the data from any probe in the system, and provide this information to user interface.
* In function of other variables: the information can be captured when one or several rules become true. These rules may involve events, thresholds of measured variables, time conditions, etc., all of them in the same or in other mote.  
The Information Layer Protocol must allow triggered operation. This way, the trigger condition of each probe must be selectable. Also, the states which may cause a trigger event in other monitor nodes must be disseminated during runtime. The trigger operation may define a set of rules to define trigger conditions, and variable and event notification to allow coordinate triggering. Those rules may be active at the same time, being combined for a flexible and powerful system analysis.  
The Information Layer Protocol also must grant the deliverance of all the data to the Analysis and Visualization & Control sub-systems. This is achieved by means of the Interchange layer services.
## 5 The Specific Case of DnaA in the _E. coli_ Cell Cycle
### DnaA Spirals and Foci  
To return to intensity sensing, consider again the distribution of DnaA. The protein, is distributed at the membrane either as foci that colocalise with the origin of replication, _oriC_[81], or as a helical spiral [80] or as both (but for _B. subtilis_ see [79]). Such hyperstructures may well contain acidic phospholipids such as cardiolipin [126]. In the following, we reason in terms of a linear polymer of DnaA rather than a cluster (or even a higher order spiral of clusters) because the role we propose for ion condensation is easier to explore for a linear polymer than for a two dimensional domain. The helical form of DnaA may--or may not--interact with both the numerous sites of DnaA on the chromosome and the membrane [80]. (Note here that the spiral is seen in the nucleoid regions and, even if it can be seen in inter-nucleoid regions, these regions may still contain DNA). If we suppose that the DnaA in this spiral is binding to both its sites on the chromosome and to membrane, there is an interesting possibility that this DnaA hyperstructure is involved in intensity sensing. This is because this spiral hyperstructure might well be responsive to the changes in superhelicity that can accompany growth [27] such that at a threshold superhelicity the spiral would be destabilized (e.g., partly unwound) and DnaA released from these sites ready to recharged and to participate in initiation; there is indeed evidence that DnaA in some circumstances can be detached from DNA by increased superhelicity [87]. The DnaA spiral would therefore constitute an intensity sensor. In fact, it might be even better than this: the DnaA spiral hyperstructure might act as a quantity sensor by responding to an increase in cardiolipin. This is because acidic phospholipids (such as cardiolipin) in a fluid phase can detach DnaA from DNA [87] and hence an increase in cardiolipin might also be sensed by the DnaA spiral hyperstructure and transduced into the signal for the initiation of replication.
# Physicochemical Properties and Volatile Profile of Chito: A Traditional Dry-Cured Goat Meat Product
## 1 Introduction  
Dry-curing is the oldest method employed for traditionally preserving meat products against the threat of spoilage and pathogenic organisms [1]. Nowadays, various dry-cured meat products are based on raw materials and processing conditions [2]. For example, \"pastirma\" in Turkey, \"carne de sol\" in Brazil, \"kaddid\" and \"bitong\" in north and south Africa, respectively, \"jerky\" in North America, \"bresaola\" and \"violin de capra\" in Italy, as well as \"ececina\" in Spain and Mexico, are just some of the many types of dried meat products [3, 4, 5].  
Goat meat is usually transformed by drying, salting, and smoking to extend its shelf life. These processes aim to reduce enzymatic activity and delay the oxidation of fats and microbial attacks. This meat is accepted around the world; however, cultural and social traditions, along with economic conditions, frequently impact consumer choices [6].  
Chito is a traditional salted and sun-dried goat meat product processed mainly in the states of Puebla and Oaxaca, Mexico. In general, the production process involves the use of meat from the goat's forearm, hips, breast, and neck. Firstly, this meat is salted in vats containing sea salt for 4 h at room temperature and covered with palm mats. After salting, the meat strips are placed on palm mats and dried in the sun for 3 or 4 days until the desired texture is achieved by the \"chitero\" (worker who processes chito); the texture is hard, similar to frozen meat. Two types of chito can be obtained: non-pressed for immediate consumption and pressed, which is destined for sale in other states. Chito that is destined for sale in other states is pressed with mallets made from sabino or oak wood and packed in jute bags.  
Considering the trend of increased production and consumption of goat meat worldwide, the objective of this research was to evaluate for the first time the physicochemical and microbiological characteristics as well as identify the volatile compounds of chito (non-pressed and pressed) over three consecutive years (2021, 2022, and 2023). The goal was to provide a scientific foundation for enhancing the quality of this intermediate moisture meat product.
# Integrated Model Selection and Scalability in Functional Data Analysis Through Bayesian Learning
###### Abstract  
Functional data, including one-dimensional curves and higher-dimensional surfaces, have become increasingly prominent across scientific disciplines. They offer a continuous perspective that captures subtle dynamics and richer structures compared to discrete representations, thereby preserving essential information and facilitating the more natural modeling of real-world phenomena, especially in sparse or irregularly sampled settings. A key challenge lies in identifying low-dimensional representations and estimating covariance structures that capture population statistics effectively. We propose a novel Bayesian framework with a nonparametric kernel expansion and a sparse prior, enabling the direct modeling of measured data and avoiding the artificial biases from regridding. Our method, Bayesian scalable functional data analysis (BSFDA), automatically selects both subspace dimensionalities and basis functions, reducing the computational overhead through an efficient variational optimization strategy. We further propose a faster approximate variant that maintains comparable accuracy but accelerates computations significantly on large-scale datasets. Extensive simulation studies demonstrate that our framework outperforms conventional techniques in covariance estimation and dimensionality selection, showing resilience to high dimensionality and irregular sampling. The proposed methodology proves effective for multidimensional functional data and showcases practical applicability in biomedical and meteorological datasets. Overall, BSFDA offers an adaptive, continuous, and scalable solution for modern functional data analysis across diverse scientific domains.  
Keywords:functional data analysis; principal component analysis; dimension reduction; sparse Bayesian learning; variational Bayesian inference; nonparametric methods; model selection +
Footnote †: journal: _Algorithms_
# Ramjet Nozzle Analysis for Transport Aircraft Configuration for Sustained Hypersonic Flight
## 3 Conceptual Design of a Ramjet Nozzle
### Characteristics of Flow through Ramjet Nozzles
#### 3.2.1 Shock Diamond  
Aerospace propulsive systems operating at supersonic Mach numbers including ramjets feature complex aerodynamic phenomena. A key such feature is the creation of shock diamonds, also known as Mach diamonds or disks, which are repeated shock patterns trailing the supersonic nozzle. This condition is caused due to the difference in pressure between the exit pressure (P\({}_{\text{e}}\)) and ambient pressure (P\({}_{0}\).) Under these conditions, the nozzle loses its efficiency during the thrust generation process. The pressure differential condition can result in either under-expansion (P\({}_{\text{e}}\) > P\({}_{0}\)) or over-expansion (P\({}_{\text{e}}\) < P\({}_{0}\)). The repeated formations result in friction between the exhausted jet air and the free stream, resulting in a turbulent shear layer which causes a viscous damping effect. This gradually dissipates the wave structure downstream of the nozzle exit [6].
# Research on Inertial Force Attenuation Structure and Semi-Active Control of Regenerative Suspension
## 5 The Verification of HVRS Suspension Characteristics
### Shock Absorber Structure with HVRS  
To verify whether the suspension can overcome the adverse effects of equivalent inertial mass after adding an HVRS, an HVRS is added to the original shock absorber structure, as shown in Figure 10a. The HVRS is set between the planetary gearbox and the motor, with minimal structural changes to the original shock absorber, which is most conducive to implementation. On the other hand, due to the amplification effect of the transmission, the stiffness and damping of the HVRS are equivalent to the values in the suspension.  
\begin{table}
\begin{tabular}{l l l l} \hline \hline
**Parameter** & **Symbol** & **Value** & **Unit** \\ \hline The back electromotive voltage constant & \(k_{e}\) & 0.057 & V/(r/min) \\ The torque constant & \(k_{t}\) & 0.454 & N-m/A \\ The internal resistance of the motor & \(R_{m}\) & 1.1 & \(\Omega\) \\ The load resistance & \(R_{r}\) & 20 & \(\Omega\) \\ \hline \hline \end{tabular}
\end{table}
Table 4: Parameters of shock absorber.  
Figure 10: (**a**) Shock absorber structure with an HVRS; (**b**) the structure of the HVRS.  
Figure 9: (**a**) The variation curve of dissipation resistance; (**b**) the variation curve of the suspension damping coefficient.  
The structure of the HVRS is shown in Figure 10b; it is mainly composed of a drive shaft, a buffer block, a driven shaft, and a flat key. The driven shaft is connected to the motor rotor through a flat key; the driving shaft is connected to the transmission output shaft through splines. The material for the buffer block is wet-process rubber, which allows to achieve the elastic deformation and energy absorption functions of the HVRS, ensuring stiffness and service life requirements. It has a long-term temperature resistance of over 150 \({}^{\circ}\)C and a compressive strength of 27.8 MPa.
## 2 Related Work
The authors of [19] proposed Cluster-Based Forwarding (CBF) which can be expanded into the existing routing schemes as an extension layer. CBF guarantees reliable transmission using a cluster that consists of helper nodes with a good link quality among the neighbor nodes of the receiver node. The helper nodes, which substitute for the receiver node that fails to receive the data packet, cooperatively retransmit the data packet they overheard. However, selecting helper nodes requires that all nodes should know in advance the whole path information of the next forwarding node for the destination sink. Furthermore, if the location of the sink changes all the nodes should go through the process of selecting helper nodes again. This results in a high cost. Therefore, CBF cannot be the general solution to provide reliability to realistic wireless sensor networks.
# Analysis of Mining Waste Dump Site Stability Based on Multiple Remote Sensing Technologies
## 4 Discussion of Experimental Results
### IRT Results  
In this study, IRT technology was used to detect aquifers in the dump site. Since the granularity of sand is smaller than that of rocks, it usually forms water-bearing aquifers. Due to the large thermal capacity and thermal inertia of water, the temperature change of the aquifer was less than that of dry rock. The evaporation of water also made the temperature of the aquifer decrease. Therefore, the radiant temperature of the aquifer was lower than that of the surrounding rocks in the thermal infrared images. According to the above principle, aquifer layers formed by water-containing sand could be detected using IRT.  
The thermographic camera used in this study was a VarioSCAN-3021 ST. It has a very high thermal resolution of 0.03 K with a working wavelength of 8-12 um. The calibration range varies from \(-40\)\({}^{\circ}\)C to 1200\({}^{\circ}\)C. In addition, a high-resolution digital camera (Cannon 40D) was used to shoot the study area. By comparing the thermal images and the photos, aquifers could be precisely located. The processed thermal image is shown in Figure 13, where we can see the temperature of the three areas (highlighted in blue rectangles) was lower than that of the surrounding areas, with a difference of approximately 5-6 degrees. All three low-temperature areas were sand layers according to the field investigation, indicating aquifers.  
The instability of a sliding body is closely related to inherent mechanical properties and external triggering factors [58]. The mechanical properties included the slope gradient and the characteristics of the slope-forming materials. The external triggering factors included rainfall, snow melt, ground water infiltration, volcanic eruption, seismic events and human activities. Previous studies have shown that most sliding body instability is caused by rainfall, in addition to its own rock and soil performance [44]. Rainfall infiltration increases the pore water pressure on the sliding material, thereby reducing its own shear strength and causing instability of the sliding body. The shear strength of the sand layers is relatively weak. Due to the relatively small granular size of sand layers, the pore water pressure even increases its ability to slide after intense rainfall [59]. According to engineering geology, aquifers are usually found at the lower part of a large sliding body [44]. Therefore, the slope body above the aquifer layers is the dangerous region which needs to be continuously monitored.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Point ID** & **A3** & **B1** & **B2/B2\_Corrected** & **B3/B3\_Corrected** \\ \hline \(error^{\prime}\) (mm) & \(-2.26\) & \(8.94\) & \(-17.18/-7.89\) & \(-20.99/-6.20\) \\ _RMSE_ (mm) & \(8.09\) & \(4.79\) & \(14.54/5.91\) & \(22.66/12.46\) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Relative Error and Standard Deviations.  
Figure 13: Thermal infrared image of the Xudonggou Dump site.