esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Recommendations Using the Deep Neural Network Model
#### 2.3.1 Model Training  
The structure of the proposed neural network is shown in Figure 5. A pair of vectors at the bottom represents a user profile vector and an item triple vector. The user profile vector in the example can be interpreted by itself; the frequent subgraph of the user contains two triples wherein PERS_0006908 (\"[PERSON]\") participates as an actor and three triples wherein GENR_00018 (\"Drama\") is the genre.  
Figure 5: Structure of proposed prediction model.  
There are various methods to embed items, with the simplest method setting the dimension of the item vector to that of the user profile vector. Here, the value of each element of the item vector is binary and is determined according to whether the corresponding item is connected to each triple in the KG.  
The user profile and item vectors, which are sparse vectors, were transformed into dense representations \(v_{u}^{\prime}\) and \(v_{i}^{\prime}\) through each fully connected layer. Then, the two vectors were concatenated and passed through a layer that interpreted the relationship between them. Finally, a probability value \(\hat{y}_{ui}\) that predicted whether the user would interact with the item was outputted using the sigmoid function. A brief formula for the model is shown as follows:  
\[v_{u}^{\prime}=f_{m}(W_{u}v_{u}+b_{u}), \tag{6}\]  
\[v_{i}^{\prime}=g_{n}(W_{i}v_{i}+b_{i}), \tag{7}\]  
\[\hat{y}_{ui}=\sigma\Big{(}h_{o}\Big{(}W\Big{(}v_{u}^{\prime}\bigoplus v_{i}^{ \prime}\Big{)}+b_{ui}\Big{)}\Big{)}, \tag{8}\]  
where the functions \(f_{m},g_{n}\), and \(h_{o}\) represent the fully connected layers of the user profile vectors, item vectors, and their concatenated embedding vectors, respectively, while \(m\), \(n\), and \(o\) represent the number of hidden layers.  
Each input vector does not represent the ID of a specific user or item. As different users can have the same user profile vector, the proposed model calculates the probability that a user with a specific preference would watch a movie with a specific characteristic, rather than the probability of them watching a specific movie.  
The input of the training data consisted of a pair of user profile and item vectors from the sample set \(S\), and the label was either zero or one. For a set of positive samples \(S_{pos}\), the label was one. The samples in \(S_{pos}\) were the samples included in the user-item interaction data. Label 0 was assigned to the samples in \(S_{neg}\), which were obtained through negative sampling among the items that each user did not interact with.  
\[S_{pos}=\Big{\{}(v_{u},v_{i})\Big{|}v_{u},v_{i}\in\mathbb{R}^{k},i\in I_{u} \Big{\}}, \tag{9}\]  
\[S_{neg}=\Big{\{}(v_{u},v_{i})\Big{|}v_{u},v_{i}\in\mathbb{R}^{k}i\in(I-I_{u}) \Big{\}}, \tag{10}\]  
\[S=S_{pos}+S_{neg}. \tag{11}\]  
As a binary classification task, it aimed to minimize the following loss:  
\[\mathcal{L}=-\frac{1}{|S|}\sum_{(u,i)\in S}[(y_{ui}logS(\hat{y}_{ui})+(1-y_{ui })logS(1-\hat{y}_{ui})]. \tag{12}\]
## 1 Introduction
Combining gear ratios with propellant requirements for ascent, even if lunar ISRU and Mars ISRU were equally feasible, the total mass savings in Earth LEO per ascent is about:  
Lunar: (4 to 6) (2.5) = 10 to 14 tons  
Mars: (30) (8 to 10) = 240 to 300 tons  
In addition to leverage, Mars atmospheric processing is far simpler, and more reliable and credible than lunar ISRU. Simply pull in atmosphere through a filter, compress it, and pass it through electrolysis cells. On the Moon, you must dig tons of soil, heat to >1650 C via solar concentrators in the carbothermal process, or mine tons of icy regolith in deep polar crevasses where there is no available power. [PERSON] [1] estimated zero return on investment for both lunar processes compared to launch from Earth. Figure 1 provides a simplified timeline of highlights from the history of Mars ISRU, relevant NASA studies, and relevant events in relevant terrestrial technology. The modern era began with the landmark paper by [PERSON], [PERSON], and [PERSON] [4], lay dormant until the late 1990s, and then continued at low levels of funding thereafter until the advent of MOXIE in 2014, which completed in 2023. NASA DRA 5.0 [5] demonstrated the benefits of Mars ISRU for long-stay missions, but NASA reverted to a short-stay concept without ISRU around 2020. Terrestrial developments that benefit Mars ISRU are also included. In this paper, we will:  
1. Place the relatively mature MOXIE technology advance and solid oxide electrolysis in general in perspective to the historical evolution of low TRL Mars ISRU technology. 2. Provide a summary of advances in Mars ISRU technology since the 1990s. 3. Develop a perspective of how the MOXIE Project relates to other advances in Mars ISRU technology. 4. Review the accomplishments of MOXIE and follow-on work, and identify technical issues left incomplete for Mars ISRU. 5. Suggest further work needed to fill the gaps left by MOXIE, as well as additional opportunities in solid-oxide electrochemical cell (SOEC) technology.
## 1 Introduction
[32] designed a patient-specific prosthetic socket using composite materials, with FE analysis revealing that maximum von Mises stresses occurred in the upper posterior region, while the minimum was in the lower medial region. [PERSON] et al. [33] demonstrated that 3D-printed PLA prosthetic sockets could withstand von Mises stresses of 5.4 MPa and 10.8 MPa under heel-strike and push-off gait conditions, respectively. Beyond biomechanics, FE methods have been used to optimize prosthetic socket designs, achieving weight reduction without compromising stiffness and load-bearing capacity [34; 35]. Experimental or clinical measurements are essential for validating FE models. Researchers have employed various pressure-measuring sensors, including capacitive [36], piezo-resistive [37; 38], strain gauges [39], and fiber-optic-based sensors [40], to validate interface pressure and shear stress results. These sensors can be mounted directly on the amputee's skin or positioned on the socket or liner walls [21; 41]. Although considerable research exists on the effects of different parameters on interface stresses and slips in PTB sockets [42], studies focusing on TSB sockets for trans-tibial amputees remain limited. This paper aims to develop a patient-specific TSB socket for trans-tibial amputees. A non-linear surface-to-surface FE model was created to investigate the effects of design parameters on interface pressure and frictional sliding under static loading conditions. The FE model was validated using experimental measurements of a patient-specific additively manufactured below-knee TSB prosthesis.
## 4 Aeroelastic Stability Analysis
### Stability Analysis  
To detect stability of the periodic solutions, the 1-dimensional dynamical system described by Equation (27)-a is perturbed, by letting \(a\to a_{\pm}+\delta a\), where \(\delta a\) is a small deviation from the steady solution solution \(a_{\pm}\). By linearizing in the perturbation, the following variational equation is obtained:  
\[\delta a=\left(d_{0}+d_{1}u+\frac{3d_{3}}{4u}a_{\pm}^{2}+\frac{5d_{5}}{16u^{3}} a_{\pm}^{4}\right)\delta a \tag{33}\]  
which decides about stability of \(a_{\pm}\). From this, by using Equation (30), the following conclusions are derived:  
* the lower non-trivial solution \(a_{-}\) is unstable in its domain of existence \(u^{*}<u<u_{c}\);
* the upper non-trivial solution \(a_{+}\) is stable in its domain of existence \(u>u^{*}\).  
By summarizing (Figure 2), a subcritical Hopf bifurcation occurs at \(u=u_{c}\). Here, the trivial solution loses stability, and a family of unstable limit cycles of amplitude \(a_{-}\left(u\right)\) bifurcates, whose existence is limited to a portion of the subcritical range. Indeed, at \(u=u^{*}\), a turning point modifies unstable to stable cycles, which extend their existence to the supercritical range. As a consequence, if the wind velocity is quasi-statically increased from below through \(u_{c}\), the rest position loses stability and the system jumps from zero to a finite value \(a_{+}\left(u_{c}\right)\). A reverse jump occurs at \(u^{*}\) when the wind velocity is decreased from above. An hysteresis can occur for wind velocity periodically changed. Such a behaviour is related to the opposite signs of the aerodynamic coefficients, \(b_{3}\) and \(b_{5}\), causing a change of the qualitative behaviour of the system, namely: (i) at small amplitudes the cubic terms in the motion Equation (8) prevails over the quintic term; (ii) at higher amplitudes, the opposite occurs. This phenomenon is known in literature as \"hard loss of stability\", and observed in several different problems (see, e.g., [53], where the effects of the nonlinear damping on the post-critical behavior of the [PERSON]'s column are discussed).
## 4 Conclusions  
The Rubin CMS technique, enhanced with the static modal derivatives, has demonstrated its performance for the time domain analysis of a beam subjected to both local and distributed nonlinearities. The Enhanced Craig-Bampton method has also exhibited a comparable performance, particularly in a stick-slip configuration. These enhanced CMS techniques owe their performance to the addition of the static modal derivatives that allow ROMs to predict the geometrical nonlinear effects and to maintain contact DOFs that allow the accurate prediction of contact forces. The proposed strategy for the selection of modal derivatives based on the nonlinear static analysis and geometrically transient analysis with friction contact demonstrates its accuracy. The higher accuracy is due to the selection of the geometrically coupled modes and internally resonant modes as dominant modes that lead to the computation and selection of their derivatives.  
Geometric nonlinear models provide more accuracy even when dealing with low-amplitude vibrations, particularly in cases when the coupling between modes could significantly impact the contact state. In the beam model with friction contact at its tip, the axial-bending coupling leads to liftoff states that cannot be predicted using a geometrically linear model. This effect can be extended to 3D models in which the coupling between the lower and higher modes is more complicated. The coupling by itself may cause small differences in structural deformation, but in the presence of friction contact, these discrepancies can result in different contact behaviors and ultimately lead to entirely different structural responses.  
The nonintrusive implementation of these approaches is of particular interest, since it enables the accurate and efficient computation of the nonlinear elastic forces based on the generalized coordinates, while the distinct contact states and contact forces are anticipated accurately.  
All authors were equally involved in the conceptualization of the problem and the results analysis. [PERSON] performed the numerical simulation and prepared the original draft. [PERSON] reviewed and edited the manuscript. All authors have read and agreed to the published version of the manuscript.  
This research is supported by the Horizon Europe framework program under the Marie Sklodowska-Curie Actions grant agreement 101061195.  
Not applicable.  
Figure 14: Accuracy of reduced models in response prediction to the number of normal modes (\(N_{0}=250\) N and Excitation Frequency = 8.1 Hz).
# Arc Shape Characteristics with Ultra-High-Frequency Pulsed Arc Welding
## 3 Results and Discussion
### Arc Core Region, Total Area and the Ratio of the Core Region to the Total Area
The results above demonstrated the increased arc region at 20-40 kHz; however, the core region was larger than C-GTAW. That meant a large ratio of the core region in arc plasma. We can also assume the movement of dynamically charged particles. The particles with large kinetic energy will be affected by a large Lorentz force, and they will be forced to deflect to the center of the arc plasma, which would create a region with a large absolute energy density. Additionally, the region can be assumed to possess a large current density. Significant numbers of moving particles can be predicted in this region and light, and transferred energy reflections with collisions or other processes will be much easier to capture, and they are displayed in Section 3.2. The authors predict that the energy input to the base metal is mostly from the core region. It can be concluded that when the pulsed current frequency is constant at 20 kHz, 40 kHz, or C-GTAW, with a current of 80 or 60 A, the arc plasma possesses a constriction phenomenon both for the total area and the core region, a lower ratio of the core region to the total area, a lower temperature, a smaller current density, a slower ionization thermal motion, and a lower efficiency of energy transfer. When the current is constant at 60 or 80 A, from a pulsed frequency of 40 kHz to 20 kHz to C-GTAW, the arc plasma possesses the same phenomenon. Above all, the effect of the pulsed arc plasma can be considered as the constriction, which reflects an expanded core region. The large ratio of the core region means there is energy concentration, or the enlarged area of the high energy region. This phenomenon is created by the Lorentz force which deflects the charged particles, especially for electrons that have large velocities. Such a deflection causes more possibilities for collisions which would create more heat or higher temperatures. Thus, the heat input of the arc plasma is believed to be more effective with a pulsed current, and the pulsed arc is supposed to obtain significant penetration.
## 3 DILIT Trials  
DLIT tests were carried out on the R2R printed thin film samples provided by VTT. The conductors are rotary screen-printed Ag-wires (Dupont 5025) on a polyethylene terephthalate (PET) foil (Melinex ST506) [18]. Figure 3 shows one piece of R2R printed silver conductor on PET foil.  
To validate the developed DLIT system's ability to identify electrical defects on the R2R printed thin film, the test sample was created by cutting a small piece of specific printing pattern with five printing wires (8 cm \(\times\) 12 cm) from the full piece of printed thin film (Figure 3). Figure 4a-d show the cropped single piece of test sample of four printing patterns to be used for laboratory trial. Four patterns (meander, U-shape, rectangular, straight) were R2R printed with different widths (80, 100, 300, 500, 1000 \(\upmu\)m).  
Figure 3: R2R printed silver conductor on PET foil.  
A test jig was specifically designed and additively consisted of a specimen holder that enables the application of voltage across five printed wires simultaneously using pogo pins. As shown in Figure 5, a cropped test sample, with printing patterns of meander shape, was installed on the test jig. During DLIT test, two terminals were connected to the signal generator to apply 5 Ag-wires with 0-5 V square wave at 1 Hz. The infrared camera was set to record the data at 60 Hz for a period of 5 s.  
Figure 4: Cropped test sample with printing patterns (a) meander; (b) U-shape; (c) rectangular; (d) straight.  
Figure 5: Test sample installed on test jig.  
Artificial defects were induced on the test samples to replicate defected printing. Two types of typical printing defects were considered in this study, which were:  
1. Complete wire breaks--artificially created by cutting through the printed Ag-wire. The complete wire breaks result in open circuits so zero current can flow between the two terminals;
2. Partial wire breaks--artificially created by scratching and partially cutting the printed Ag-wire. The partial wire breaks result in a local increased resistance consequently a higher temperature to be detected by an infrared camera, which is so-called hot spot.
# Forecasting the Distortion in Solar Radiation during Midday
## 4 Conclusions  
Forecasting solar radiation is essential for power systems penetrated by high solar PV generation. However, this task is very complicated. In this paper, we tried another route by trying to forecast the distortion in the solar radiation during the midday hours by analyzing the solar radiation in the early morning. A distortion index was proposed based on the mathematical difference of the per-minute readings of the global solar radiation. The sign and amplitude of the differences between the readings were utilized to formulate a distortion index that helps the power systems operators in determining the reliability of PV plants' generation. The method was tested using the global radiation for the year 2019 for two locations in Saudi Arabia. The results showed that there are correlations between the solar radiation distortions in the early hours with the solar radiation distortion in the midday hours. The results showed that the proposed distortion index was able to classify the days with high, medium, and low distortion in solar radiation. The accuracy was 85.2% and the error was 14.8% for one site. This work needs to be improved and tested more; therefore, the proposed methodology will be improved by adding more parameters such as wind speed and will be tested for more years and using data from different cities with different climates.  
Conceptualization, A.M.N. and Z.A.H.; methodology, A.M.N. and Z.A.H.; software, A.M.N., Z.A.H., A.S.A. and S.Z.A.; validation, M.H.A., S.Z.A. and A.S.A.; formal analysis, A.M.N., Z.A.H., S.Z.A.; investigation, A.S.A., M.H.A. and S.Z.A.; resources, A.M.N. and Z.A.H.; writing--original draft preparation, A.M.N. and Z.A.H.; visualization, A.M.N. and Z.A.H.; project administration, A.M.N., M.H.A. and A.S.A.; funding acquisition, A.M.N., S.Z.A., M.H.A. and A.S.A. All authors have read and agreed to the published version of the manuscript.  
Deputyship for Research & Innovation, Ministry of Education: Project Number (IF2/PSAU/2022/01/23150).  
Not applicable.  
The authors extend their appreciation to the Deputyship for Research & Innovation, Ministry of Education in Saudi Arabia for funding this research work through the project number (IF2/PSAU/ 2022/01/23150).  
The authors declare no conflict of interest.
# Study on Microseismic Monitoring of Landslide Induced by Blasting Caving
## 5 Conclusions  
This study utilizes microseismic event data collected prior to the blasting-induced mountain body slide failure. The attitude of the sliding surface is analyzed using principal component analysis (PCA), and the source mechanism of precursor events is investigated through moment tensor theory. By solving and inverting the moment tensors of microseismic events, the rupture mechanisms and failure types are determined. The following key conclusions are drawn:  
1. The PCA-derived attitude of the sliding surface aligns closely with the field-measured attitude, with a dip angle difference of 2.8\({}^{\circ}\) and a dip direction difference of 2.4\({}^{\circ}\). This demonstrates that the PCA method can effectively analyze the clustering of microseismic events and determine the spatial orientation of clustered events. It provides a reliable technical basis for identifying potential sliding surfaces and monitoring early warnings of mountain body slides.
2. The moment tensor analysis of the blasting-induced mountain body slide failure reveals that the method accurately classifies rock mass rupture types. The results are consistent with the observed macroscopic shear sliding failure along the fault plane in the field. This confirms the validity and applicability of microseismic source mechanism analysis in engineering rock mass rupture studies.
3. Microseismic monitoring technology can detect precursor rock mass rupture events before a mountain body slide. By analyzing the clustering degree of microseismic events, the attitude and rupture type of potential sliding surfaces can be determined. This enables effective monitoring and early warning of potential mountain body failures, offering a novel approach for studying mining-induced mountain body slides.  
F.P.: Funding acquisition, investigation, data curation, methodology, writing--original draft. W.W.: Project administration, conceptualization, review and editing. All authors have read and agreed to the published version of the manuscript.  
This Project was supported by the National Natural Science Foundation of China (No. 52374088), and the National Key Research and Development Program Project of China (2022 YFC2904002).  
Not applicable.  
All the data, models, and codes generated or used during the study appear in the submitted article.  
Figure 19: Aerial photo of landslide: (**a**) measurement of the inclination angle of the sliding surface; (**b**) measurement of the tendency of the sliding surface.  
**Acknowledgments:** We would like to express our sincere gratitude to The Shizhuyuan Polymetallic Mine for providing valuable monitoring data.  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 6 Conclusions  
A multiple resources coordinated EFC strategy considering V EPR is proposed to deal with a HVDC blocking disturbance at the receiving-end grid. An approximate aggregation model of VPP response process is constructed to reflect the difference in communication delay and response speed between different DER devices. The electromechanical transient simulation is parallelized in each iteration of PSO to speed up the model solving. The DERs dynamic response priority sequence in the VPP is constructed.  
The effectiveness of the proposed method is verified by a provincial receiving-end power grid with multi-infeed HVDC. The simulation results show that considering V EPR can reduce the control cost of EFC while satisfying the system frequency constraints. In addition, parallel simulation can speed up the solution so that the algorithm can be used for online decision-making.  
In the future, a more accurate VPP response process aggregation model considering grid frequency and bus voltage dynamics will be further studied. Additionally, more resources, such as renewable energy and battery energy storage, will be further considered.  
Conceptualization, Y.C. and X.S.; methodology, J.X. and Z.Z.; software, J.X. and R.M.; writing--original draft preparation, J.X.; writing--review and editing, Y.C. and J.Z.; supervision, X.S. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Key R&D Program of China (No. 2021 YFB2400800) and the science and technology project of SGCC (No. SGSDDK00 WJJS2200092).  
Not applicable.  
Data Availability Statement: Data are available upon reasonable request to the corresponding author.  
The authors declare no conflict of interest.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Number of** & **1** & **4** & **8** & **10** & **16** & **20** & **40** & **50** & **60** \\
**Sub-Processes** & & & & & & & & & \\ \hline Computation Time(s) & 6.142 & 7.273 & 9.429 & 10.363 & 14.230 & 20.308 & 36.843 & 44.904 & 50.435 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Computation time under different number of sub-processes.