esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Results and Discussion
### Calibration
It is thus deduced that agglomerates retard the reaction rate at progressed conversion also in the indirectly operated reactor concept. The term \((1-X)^{k_{R,2}}\) represents the retardation at progressed conversion and describes the effect of the agglomerates phenomenologically. Thus, there is no easy physical interpretation of the parameter k\({}_{R,2}\); primarily, it fulfilled the purpose of identifying a relevant phenomenon, so it may only be interpreted qualitatively. As its inferred value is large (k\({}_{R,2}\)= 5.58), we conclude that the effect of agglomerates is important. If it was not important, k\({}_{R,2}\) would have a value close to zero. The surrogate model represents the conversion profile satisfactorily, see Figure 5d. At the beginning, the simulation overestimates the conversion, as the model does not represent the experimental procedure exactly. The pressure in the vapor vessel was used as initial condition in the reactive bed, whereas in the experiment, the reactor had been evacuated beforehand. However, the initial pressure of the experiment is unknown. The initial water pressure in the simulation setup leads to increased conversion at early simulation stages until the additional water vapor caused by the initial condition is consumed by the reaction. At later times, experimental and simulation results match well, also with respect to incomplete conversion. Figure 4: Temperature distribution of the outer pressure vessel according to the parameters k\({}_{1}\)–k\({}_{3}\) and at the top boundary of the reactive bed over the reactor length at different times simulated with the DuMu\({}^{x}\)-model with the parameters of Table 6.  
Figure 5 shows the simulation results of the surrogate model together with the experimental results for the temperature distributions at T1, T3, T7 and the conversion. The results of the calibrated model indicate a good agreement with the experimental data. In particular, the temperature curves T1 and T3 reflect the temperature profile well, including the slope of decreasing temperature at final conversion and the final temperature after conversion. The discrepancy in T7 is larger. As the reaction front moves from left to right, this measurement point is less determined by initial and boundary conditions. The surrogate model is built based on the 500 DuMux-simulations. Thus, the model uncertainties accumulate at this point. This explains furthermore the wavy shape of the surrogate model results for T7. The shape of T1 and T3 is smoother and features a smaller confidence interval especially at later simulation times compared to T7.
## 3 Results and Discussion
### Responses of the Compression Behavior of the SFRC: Non-Dimensional Analysis
For this reason, there will be a reduction in the number of factors to study in the compression behavior model of SFRC proposed by [PERSON] et al. [42]. Three parameters: \(\ell_{f}^{*}\), \(\lambda\), and \(\phi_{f}\), characteristic of fiber reinforcement and expressed in a non-dimensional manner, were selected. The reason for this choice was that the first two defined the geometry of the fiber and the last made reference to its content. In addition, \(\phi_{f}\) was the only factor that had a statistical significance in each of the responses, and \(\ell_{f}^{*}\) was the next factor with greater significance for all of them. On the other hand, these three parameters were those that intervened in the majority of the models existing in the literature that describes the \(\sigma\)-\(\epsilon\) compression response of SFRC.
###### Abstract  
In this study, a new method of estimating the leakage positions of cooling water using a stereo camera for the Fukushima Daiichi Nuclear Power Plant (FDNPP) is proposed. A stereo camera mounted on an inspection system with a rotating base was inserted into the pedestal below the reactor pressure vessel (RPV), and the waterdrops from the leakage position were captured using a stereo camera. We estimated the leakage positions by triangulating the waterdrop trajectory lines in the stereo image. The main contribution of this study is the extraction and matching of the waterdrop trajectories in a stereo image in the FDNPP. The radiation noise is intense inside the pedestal because of the presence of fuel debris. Therefore, we propose a method that is robust against radiation noise. We assume that the waterdrops drip vertically in indoor environments without wind, such as in the FDNPP. Hence, the orientation of the stereo camera can be adjusted by the rotating base such that the vertical lines in the three-dimensional space are also projected as vertical lines in the image planes. Thereafter, the columns of pixels in the images are treated as image features and used to extract and match the waterdrop trajectories. We demonstrated the effectiveness of our leakage position estimation method in a simulated environment of the FDNPP with gamma-ray image noise.  
leakage position estimation; Fukushima Daiichi Nuclear Power Plant; decommissioning: stereo camera +
Footnote †: journal: Applied Sciences
# Grasp Analysis for the Robot-Based Manipulation of Pre-Assembled Cables with Electrical Connectors
## 2 State of the Art
### Grasping and mating of ECs  
If one considers the grasping and mating of ECs without taking the cable into account, the task is mostly similar to a robotic peg-in-hole problem. For a survey on this current research area, please refer to [14]. Several works have already demonstrated the general feasibility of grasping and mating ECs using a robotic system. The approaches consider different types of ECs, which are associated with specific requirements for grasping and mating. [PERSON] et al. [15] present an approach for filigree multi-pole ECs and ribbon cables, among others. On the one hand, a feeding mechanism for the cables and EC is presented, which allows grasping from a predefined pose. On the other hand, an impedance control strategy is presented to compensate for the relative pose error between the plug and the socket for the mating of the ECs. Another force-control strategy is presented by [16] and applied to a multi-pole, cylindrical plug, which requires multi-stage mating with a specific orientation. Thereby, an individually designed gripper system is employed. As a use case, product testing is addressed, which requires alternately mating and releasing the same plug. In addition, approaches for the position-based mating of ECs exist. [PERSON] et al. [17] present a measurement study for the permissible error range in the relative position between the plug and socket for twelve different classes of ECs.  
The work presented so far predominantly focuses on the rigid component--the EC. In the following, publications which take the deformable part--the DLO--into account are described.
## 1 Introduction
Introducing ion-conducting and topographic heterogeneity on the membranes' surface is the most investigated method for enhancing electroconvection [11; 12]. In addition to membrane surface properties, the type of electrolyte has been also demonstrated to be an influencing parameter in the early onset and intensification of electroconvection. Several researchers have concluded from experimental studies that multivalent ions with larger Stokes radii are able to create larger vortices and boost electroconvection [13; 14; 15]. However, these ions also entail an additional complexity, since they can appear as free ions or combined in the form of complex species. The speciation and distribution of counter-ions can be altered upon application of an electric field and development of concentration polarization. Changes in speciation of electrolyte in the vicinities of the membrane may imply the generation, at an advanced stage of concentration polarization, of new counter-ions from other species with a different charge and thus, turn into changes in membrane selectivity and current efficiency in electromembrane processes. Also, membrane conductivity is influenced by the type of counter-ion equilibrating the membrane or by precipitates formation at the depleting membrane side [14; 16]. The aim of the present study is to recapitulate diverse phenomena that can arise during transport of multivalent ions through cation-exchange membranes under intense concentration polarization conditions and improve the understanding on the factors influencing them. These are investigated by means of chronopotentiometric measurements, where the dynamic response of membrane voltage drop upon different perturbation signals are interpreted on the realm of several competing and interrelated phenomena arising at overlimiting currents. Analysis of the current-voltage features is also assessed to obtain the steady state resistance of membrane systems. The different phenomena observed are treated and classified according to the cause for their emergence:  
1. Equilibrium shifts in the diffusion boundary layer
2. Overlimiting mass transfer with multivalent metals
## 3 Results  
### Results Obtained from Statistical Data Analysis  
#### 3.1.1 Correlation Matrix  
The correlation matrix presented in Table 1 elucidates several variables exhibiting moderate correlation coefficients. This observation suggests that there is no exigency to eliminate any variables owing to multicollinearity in subsequent regression analyses, nor does it necessitate the implementation of a principal component analysis.  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline  & **SMD** & **PCMD** & **OMD** & **SHT** & **TES** & **THD** & **IPT** & **IOT** & **OLD** \\ \hline SMD a & 1.00 & \(-\)0.27 & 0.11 & 0.00 & 0.26 & 0.49 & \(-\)0.06 & \(-\)0.21 & \(-\)0.22 \\ PCMD b & \(-\)0.27 & 1.00 & \(-\)0.18 & \(-\)0.27 & 0.09 & 0.54 & 0.46 & 0.22 & 0.34 \\ OMD c & 0.11 & \(-\)0.18 & 1.00 & 0.06 & 0.40 & 0.45 & \(-\)0.24 & 0.26 & 0.02 \\ SHT d & 0.00 & \(-\)0.27 & 0.06 & 1.00 & \(-\)0.22 & \(-\)0.19 & 0.00 & \(-\)0.12 & \(-\)0.23 \\ TES e & 0.26 & 0.09 & 0.40 & \(-\)0.22 & 1.00 & 0.46 & 0.05 & 0.27 & 0.12 \\ THD f & 0.49 & 0.54 & 0.45 & \(-\)0.19 & 0.46 & 1.00 & 0.21 & 0.18 & 0.14 \\ IPT g & \(-\)0.06 & 0.46 & \(-\)0.24 & 0.00 & 0.05 & 0.21 & 1.00 & 0.44 & 0.20 \\ IOT h & \(-\)0.21 & 0.22 & 0.26 & \(-\)0.12 & 0.27 & 0.18 & 0.44 & 1.00 & 0.14 \\ OLD i & \(-\)0.22 & 0.34 & 0.02 & \(-\)0.23 & 0.12 & 0.14 & 0.20 & 0.14 & 1.00 \\ \hline \end{tabular}
\end{table}
Table 1: Correlation Matrix.  
Specifically, a moderate positive correlation coefficient of +0.44 is discerned between the number of errors in the Ishihara Test conducted on the iPad (IOT) and the Ishihara Test administered via physical media (IPT). This moderate positive correlation, in conjunction with corroborating evidence from pertinent literature [8; 9], bolsters the validity of utilising the Ishihara Test on digital devices for the detection of congenital colour vision anomalies.
# Multi-Patch Time Series Transformer for Robust Bearing Fault Detection with Varying Noise
## Appendix A
### Experimental Results After Applying Electrical Interference Noise
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Model** & **SNR** & **Accuracy** & **Precision** & **Recall** & **F1** \\ \hline \multirow{4}{*}{LSTM} & 27 dB & 0.9253 & 0.9324 & 0.9281 & 0.9302 \\ \cline{2-6}  & 17 dB & 0.8096 & 0.8357 & 0.8182 & 0.8269 \\ \cline{2-6}  & 11 dB & 0.7915 & 0.8231 & 0.7992 & 0.8106 \\ \cline{2-6}  & 3 dB & 0.7857 & 0.8198 & 0.796 & 0.8076 \\ \hline \multirow{4}{*}{GRU} & 27 dB & 0.9244 & 0.9303 & 0.9279 & 0.9291 \\ \cline{2-6}  & 17 dB & 0.8146 & 0.837 & 0.8244 & 0.8306 \\ \cline{2-6}  & 11 dB & 0.7898 & 0.8251 & 0.7994 & 0.8114 \\ \cline{2-6}  & 3 dB & 0.7905 & 0.8209 & 0.7992 & 0.8098 \\ \hline \multirow{4}{*}{FCN} & 27 dB & 0.9267 & 0.9329 & 0.9292 & 0.9311 \\ \cline{2-6}  & 17 dB & 0.808 & 0.8371 & 0.817 & 0.8269 \\ \cline{2-6}  & 11 dB & 0.7967 & 0.8267 & 0.8061 & 0.8159 \\ \cline{2-6}  & 3 dB & 0.7909 & 0.8197 & 0.8006 & 0.8099 \\ \hline \multirow{4}{*}{ResNet} & 27 dB & 0.9263 & 0.9318 & 0.9289 & 0.9303 \\ \cline{2-6}  & 17 dB & 0.8125 & 0.8371 & 0.821 & 0.8289 \\ \cline{2-6}  & 11 dB & 0.791 & 0.8241 & 0.8002 & 0.8117 \\ \cline{2-6}  & 3 dB & 0.7948 & 0.8239 & 0.8037 & 0.8136 \\ \hline \multirow{4}{*}{InceptionTime} & 27 dB & 0.9241 & 0.9307 & 0.927 & 0.9288 \\ \cline{2-6}  & 17 dB & 0.8154 & 0.8364 & 0.8238 & 0.8299 \\ \cline{2-6}  & 11 dB & 0.7923 & 0.8227 & 0.8016 & 0.8116 \\ \cline{2-6}  & 3 dB & 0.7954 & 0.8234 & 0.8056 & 0.8144 \\ \hline \multirow{4}{*}{XceptionTime} & 27 dB & 0.9258 & 0.9338 & 0.9294 & 0.9315 \\ \cline{2-6}  & 17 dB & 0.8131 & 0.8373 & 0.8217 & 0.8293 \\ \cline{2-6}  & 11 dB & 0.7901 & 0.8227 & 0.7978 & 0.8098 \\ \cline{2-6}  & 3 dB & 0.7861 & 0.8148 & 0.7956 & 0.8049 \\ \hline \multirow{4}{*}{XCM} & 27 dB & 0.9255 & 0.9325 & 0.9271 & 0.9298 \\ \cline{2-6}  & 17 dB & 0.8157 & 0.838 & 0.8242 & 0.831 \\ \cline{2-6}  & 11 dB & 0.7928 & 0.8265 & 0.8024 & 0.8138 \\ \cline{2-6}  & 3 dB & 0.7893 & 0.8192 & 0.7992 & 0.809 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Experimental results on PU dataset with electrical interference noise.
## 2 Materials and Methods
### Forest Disturbance Mapping  
Data provided by the Landsat satellites constellations have long been used to conduct change detection analysis. The complete Landsat dataset (including Landsat 5, 7, and 8 missions) is available on Google Earth Engine (GEE), a cloud-based platform with high-performance or planetary-scale computing resources for processing vast geospatial datasets [45]. The long record of continuous measurement (since 1985), high spatial (30 m) and temporal (8-18 days) resolution, and near nadir observations [46; 47; 48] make Landsat imagery data one of the most valuable sources of information on forest disturbance detection [49; 50; 51; 52; 53]. On the other hand, cloud coverage [54] represents a limit to Landsat imagery implementation. In our study, we overcome this issue by applying the Best Available Pixel (BAP) composite procedure [55; 56]. Pixel-based image compositing applies a set of user-defined rules to employ the extensive Landsat archive to generate cloud-free and radiometrically- and phenologically-consistent image composites that are spatially contiguous over large areas [57; 58; 59]. Specifically, the BAP allows one to select for each pixel location the \"best\" pixel among those available--thus from images that are not covered by clouds or shadows--based on a set of scores, among which are (i) the sensor score, (ii) the day of year score, (iii) the distance to cloud or cloud shadows score, and (iv) the  
Figure 1: Study area, forest harvestings reference dataset (red boxes), and ALS data coverage.  
opacity score. The BAP was recently implemented in GEE [60] with the full code openly available [61]. A detailed description of the application, guidance, and suggestions on BAP parameter setting is also provided on GitHub [62]. As a result of the BAP application, we obtained cloud-free composites for the whole of Italy for each year between 1985 and 2019.  
Forest disturbance prediction was performed using the BAP composites and the GEE implementation [20] of the Three Indices Three Dimensions (3I3D) algorithm [19]. 3I3D is an unsupervised algorithm that predicts forest changes by analyzing the trends of three photosynthetic activity indices (3I) used as axes of three-dimensional space (3D) over three consecutive years. The photosynthetic activity indices are the Normalized Difference Moisture (NDMI) [63], the Normalized Burn Ratio (NBR) [64], and the Moisture Stress Index (MSI) [65]. For a detailed description of 3I3D, we refer to [PERSON] et al. [19; 20]. The complete 3I3D code is open access [66], for which further indications are provided on GitHub [67]. Thanks to the application of 3I3D, it was possible to obtain a set of 35 forest disturbance maps--one for each year between 1985 and 2019--with a spatial resolution of 30 m. 3I3D predict several different kinds of forest disturbance--including forest harvestings, forest fires, wind damages, insect attacks, drought, and frost damages--as long as they imply a decrease in the photosynthetic activity.
# BLE Signal Reception and Localization Performance with Varying Receiver and Beacon Setups
## 2 BLE Signal Collection Setup  
This study is conducted using Carecome equipment [31], IoT Controller \"TLM-001\", accessible through a web browser using a specific IP address and port, IoT Gateway \"TRX-302-GW\", BLE tag \"TTX-301-LG\", WiFi router, Switching Hub, and PC for WEB Console. Figure 1 illustrates the setup of BLE signal mapping equipment and network architecture employed in the process.
# Maintaining the Sense of Agency in Semi-Autonomous Robot Conferencing
## 2 Teleoperation Interface  
This section first introduces our teleoperation interface in order to describe our idea to make an operator feel the illusion that their teleoperation is responsible for autonomous behavior. The detailed experimental setup will be described in the Section 5.2. Figure 1 shows our semi-autonomous robot conferencing system. The upper part of the figure shows our teleoperation interface ((a) operator side), which allows an operator to control the facial direction of our robot using an eye tracker. The display presents a live video (\(1920\times 1080\) pixels, \(30\) fps) of the remote partner, which is captured by a camera included in a motion capture sensor (Microsoft Kinect for Windows) that is located on the remote side. The display was equipped with an eye tracking sensor (Tobii), and the green circle identified the place where the operator is looking. The diameter of the circle was set to \(90\) pixels, which is enough to contain the face of the partner who is sitting approximately \(1\) m away from the robot. The operator can look around the remote location on the display using only their eye movement, but the robot has to change its facial direction as well as its eye direction in order to look around the corresponding region in a natural movement. Therefore, the system determines the motor commands of the robot so that the place where the operator is looking matches that of the robot.  
The field of view of the web camera was adjusted to face the back of the head of the robot, based on the results of a pre-experiment that tested our interface. The results suggest that the sense of agency would decrease when the operator cannot see the movement of the robot. A headband was set on the head of the robot as a mark, so that the operator can easily understand which direction the robot is facing. Because the operator cannot directly see the eye movement of the robot, its vision line is shown as the yellow arrow. The arrow then moves to follow the green circle. When the view of the operator begins to change from one partner to the other (the operator's eye movement is approximately \(970\) pixels), the delay before the vision line of the robot reaches its conversation partner is \(0.5\) s, and the delay before the movement of the robot head is completed is \(1.5\) s.  
When the robot autonomously adjusts its view, the interface guides the operator's eye movement to the view point of the robot by moving the green circle. We considered that the operator will feel the illusion that the operator's teleoperation is responsible for the autonomous head movement, if the interface convinces her to believe that this induced gaze is her involuntary eye movement. It might be difficult to provide such an illusion through visual guidance alone. The movement of the green circle indicates the operator's eye movement, and so there is a possibility that the operator does not notice the autonomous movement of the circle mixed into the teleoperation.
## 6 Discussion
### Significance and Results of the Study  
The primary aim of the study was to conduct a preliminary investigation into the experimental feasibility of adapting the flat-jack test for assessing residual stress in post-tensioned concrete elements. Recognizing that concrete exhibited significantly higher stiffness compared with traditional masonry, a key focus was to evaluate the method's performance in this stiffer material. Specifically, the research sought to analyze the influence of varying gage lengths and flat-jack dimensions on measurement accuracy and consistency, with particular attention to smaller jacks for their potential in minimizing invasiveness and potential damage to steel elements. The study also aimed to assess the resolution achievable with the flat-jack test in concrete and to develop and implement a dedicated calibration procedure reflecting actual testing conditions to enhance the reliability of stress estimations.  
The data suggested a direct link between the flat-jack size, gage length, and accuracy. In the tests performed with the 25 cm flat jack and 14 cm gage length, the accuracy error \(E\) was typically less than 15%, and the reproducibility error (\(CoV\)) was around 40-45%. The 33 cm flat jack, with its deeper penetration, provided more accurate estimates (maximum average error \(E\) of 8%) but comparable reproducibility. While the achieved level of reproducibility suggested that further refinement was needed, the accuracy was deemed adequate for its practical purpose of providing an estimate of the level of prestressing in concrete. Considering additional advantages of the methodology, such as low invasiveness, relative ease of implementation, and potentially lower cost compared with techniques like X-ray diffractometry, the flat-jack test emerges as a promising alternative for evaluating residual prestress in PT concrete elements. However, the trends observed in this pilot study with a limited dataset require validation through a broader experimental campaign to confirm these findings and inform the development of standardized procedures.  
In conclusion, the observed variability, including both overestimation and underestimation of stress, was likely a consequence of the flat-jack test's interaction with the inherent heterogeneity of concrete, the localized nature of the measurement, and the specific geometric parameters of the test setup (gage length and flat-jack size). The trends observed, particularly regarding the benefits of the 14 cm gage length and the 33 cm flat jack's improved performance at higher stresses, underscore these complex interactions.  
However, as this is preliminary research with a limited dataset, the explanation is based on the initial observations and potential contributing factors, and future research will be performed in future studies.