esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
The purpose of this paper is to present applications and design elements of scale models of the carbody of railway vehicles integrated in experimental laboratory systems to verify the effectiveness of the methods to reduce vertical bending vibration of the carbody. In the first part of the paper, some applications of such experimental systems are presented, which include different scale models of the railway vehicle carbody. In the second part of the paper, the structure and dimensioning elements of a new demonstrative experimental system, specially designed by the authors of the present paper for testing the functionality of an original method of reducing the vertical bending vibrations of the carbody of railway vehicles, are presented. This method is based on an innovative approach that involves the use of a passive system consisting of two bars rigidly mounted on the longitudinal beams of the carbody underframe, having the role of opposing the bending of the carbody. The main element of the demonstrative experimental system is the scale model of the vehicle carbody, reduced to a beam, on which the two bars, called anti-bending bars, are mounted. For the dimensioning of the experimental model of the carbody and the anti-bending bars, original methodologies are developed in which several conditions are involved. In the case of the dimensioning of the experimental model of the carbody, the conditions refer to the convenient adoption of the scaling factor of the dimensions of the real carbody from the perspective of the practical realization of the experimental model of the carbody, ensuring the buckling stability of the demonstrative experimental system, achieving natural frequency of the vertical bending of the real carbody and avoiding the interference of the bounce vibration with the vertical bending vibration of the demonstrative experimental model of the carbody. The dimensions of the anti-bending bars are established from the condition that the vertical bending frequency of the experimental model of the carbody is outside the range of sensitivity of the human body to vertical vibration. Additionally, the natural frequency of the vertical bending vibration of the anti-bending bars must be chosen to avoid interference with the vertical bending vibration of the experimental model of the carbody. The effectiveness of the anti-bending bars in reducing the vertical bending vibration of the experimental model of the carbody is investigated with the help of numerical simulation results developed based on an original theoretical model of the experimental model of the carbody with anti-bending bars.  
railway vehicle; bending vibration; ride comfort; demonstrative experimental system; scale model; anti-bending bars +
Footnote †: journal: Applied Sciences
## 3 Compact Model Validation
### Validation of RF Characteristics  
#### 3.2.1 Intrinsic Junction Capacitance Extraction  
In order to validate the dynamic behavior of the UTC-PD compact model, one-port \(S\)-parameter measurements were performed. Measurements up to 110 GHz under a reverse bias ranging from 0 to \(-2\) V were carried on the InGaAs/InGaAsP and InGaAs/InP UTC-PDs. Measurements up to 67 GHz under reverse bias ranging from 0 to \(-2.5\) V were performed on the GaInAsSb/InP UTC-PDs. After applying the suitable de-embedding method for each UTC-PD, following the procedure explained in Section 2, we can validate the compact model on the intrinsic \(S\)-parameters.  
Figures 10 and 11 show scalable compact model validation against \(S\)-parameter measurements of the amplitude and the phase of the different intrinsic UTD-PDs under study. Excellent agreement is observed for all geometries and all UTC-PD technologies affirming the scalability and versatility of the compact model. Note that, in some of the S11 measurements (Figure 10a,c,e) show fluctuations in the 80-100 Ghz frequency range, that are not captured by the model. The origin of these fluctuations is due to the reflection of the input signal from the chuck on which the wafer is placed, thereby causing these fluctuations in the measured S11. This has also been observed previously in other devices on InP substrate. The placement of an absorber between the chuck and the device under test can significantly reduce these fluctuations, which was, however, not available during this set of characterizations.  
The new implementation of the junction capacitance model (Equations (5)-(7)) captures the physics of UTC-PDs much better than the conventional model and thereby offers excellent scalability and agreement with measurement results as depicted in Figure 11. The extraction of the junction capacitances is performed at 10 GHz to avoid any inductive contribution.
## 4 Results
### Operational Flexibility  
The results explained so far focused on cyclic storage operation with the associated findings regarding systemic storage density, constant discharge and effective heating power. However, regardless of the optimization potentials still to be achieved, every storage system requires subsequent charging after complete discharging in order to maintain its functionality and thus its use.  
For the component developed here, an improved flexibility is given due to its integrated electric heating system allowing a bifunctional operational use: on the one hand as storage system with successive charging/discharging periods and on the other hand as convective heating system. For using the component in the heating mode, the air to be heated is passed through the honeycombs only, while the electric heating system is activated at the same time. First results for this operating mode with a heating power of 2.5 kW and inlet temperatures of 20 \({}^{\circ}\)C are shown in Figure 15.  
The characteristics show a decrease in the outlet temperatures with increasing mass flow rates with a good agreement between the experimental and simulative results. Compared to conventional PTC heaters, however, the significantly larger component mass within the system leads to increased thermal inertia resulting in lower dynamics when reaching steady state conditions. Despite this, it is obvious that the component developed here allows variable heating operations in addition to the cyclic storage mode. Due to its flexibility, the operating time and thus the utilization of the component can be improved significantly without increasing the overall systemic complexity inside the battery electric vehicle.
## 3 Results  
### Nanopowder Characterisation  
The morphological nature of the A-TiO\({}_{2}\) nanoparticles was examined using TEM, which revealed a pseudo-spherical structure of the nanoparticles, as shown in Figure 2. The sizes of over 200 nanosized particles were measured using TEM images, revealing a 21*/2 nm mean particle size, according to the manufacturer (<25 nm). Additionally, assuming a log-normal function [28], a polydispersity index of 0.16 was assessed.  
Figure 2: (a) TEM image of A-TiO\({}_{2}\) nanopowder and (b) size distribution of A-TiO\({}_{2}\) nanoparticles.  
The crystalline characteristics of the nanosized particles were determined through the XRD technique, and the obtained XRD pattern is depicted in Figure 3. The experimental pattern corresponds with JCPDS card no. 21-1272 for anatase TiO\({}_{2}\)[29] displaying diffraction peaks at 20 values of 25.3\({}^{\circ}\), 37.8\({}^{\circ}\), 48.0\({}^{\circ}\), 55.0\({}^{\circ}\), and 62.8\({}^{\circ}\), corresponding to (101), (004), (200), (105), and (204) planes, respectively. The 24.5 nm crystalline domain size was calculated from the (101) reflection, which represents the most prominent peak in the XRD pattern, using Equation (1).  
The pseudo-spherical shape and particle size observed through TEM align with the findings of other studies from the literature [17; 18], which reported good prospects in terms of thermophysical properties' improvements for using TiO\({}_{2}\) nanoparticles in nanofluids design.
# Joint Uplink and Downlink Resource Allocation for D2D Communications System
## 2 System Model and Problem Formulation  
In this section, we first build the system model and then formulate the joint uplink and downlink resource allocation problem for D2D communications system.
## 3 Design of the Measurement System
### Climate Chamber System
#### 3.2.2 Humidity Control  
In order to avoid the condensation of water on the electronic devices loaded into the climate chamber shown in Figure 5, the humidity was carefully monitored and controlled. The chamber used allows the fine control of the relative humidity from 10% to 95%, within \(\pm 3\)%, when the temperature \(T>5\)\({}^{\circ}\)C. Since it is necessary to take measurements at lower temperatures as well, particular attention has been paid to the atmosphere introduced into the climate chamber. Specifically, nitrogen gas was flowed into the metal box, suitably darkened, inside which the APD under test was placed. However, the nitrogen gas was passed through a long copper coil inside the chamber to avoid introducing gas at a different temperature than the set one. The temperature transducer mounted near the APD was therefore essential for monitoring any temperature variations caused by the nitrogen flow. Meanwhile, the entire climate chamber was connected to a dry-air generator.  
Figure 4: Wire diagram of the electronic circuit realized to adapt the current output of the AD590 temperature transducers to the input characteristics of the Picolog.
# Research on the Characteristics of Seepage Failure in the Surrounding Rock (Coal) of the Goafs
## 2 Materials and Methods  
### Preparation of Coal Samples  
The sampling location for this study is the Xishan Coalfield in Shanxi Province (as shown in Figure 1). The mining area is located in the northwestern part of Taiyuan City, Shanxi Province. The overall structural morphology consists of alternating anticline and syncline folds, with the strike and dip controlled by these fold structures. The dip angle of the strata ranges from 2\({}^{\circ}\) to 12\({}^{\circ}\), generally around 6\({}^{\circ}\). The main coal seams being mined are coal seam No. 2 and coal seam No. 8. The water-bearing rock formations in this area include the Quaternary Holocene gravel aquifer, the Permian Upper Shiqianfeng Formation sandstone fissure aquifer, the Permian Lower Shihezi Formation sandstone fissure aquifer, the Shanxi Formation sandstone fissure aquifer, the Carboniferous Upper Taiyuan Formation limestone karst fissure aquifer, the Ordovician Middle Fengfeng Formation limestone karst fissure aquifer, and the Upper Majiagou Formation limestone karst fissure aquifer. Mudstone and carbonate layers, where karst and fissures are underdeveloped, act as aquitards between these bedrock aquifers, preventing hydraulic connection or allowing only weak hydraulic connection between the various aquifer groups. These layers serve as aquitudes or relatively impermeable layers.  
To ensure the accuracy of the measured permeability during permeability tests, the coal sample surfaces were treated to prevent leakage between the sample surface and the pipe wall. The coal samples were cleaned to remove dust and impurities and wrapped with PTFE (polytetrafluoroethylene) waterstop tape to minimize boundary leakage. Due to the development of endogenous joints and fractures in the coal, the rock samples often became fragmented during sampling. Consequently, cylindrical coal samples with a diameter of approximately 25 mm and a length of approximately 30 mm were obtained using a coring drill bit, and a total of 10 coal samples were prepared for the experiment (Table 1). The ends of the coal samples were polished to ensure smooth and flat surfaces, ensuring tight contact with the sealing heads during permeability tests and uniform stress distribution during axial compression tests. Maintaining the integrity and good sealing of the coal sample structure provided a reliable guarantee for obtaining stable seepage data. The characteristic parameters of the coal samples are shown in the table below.
## 6 Simulation and Analysis of Protocol Based on BFGO-C in HWSN
### Comparison of Remaining Energy  
The energy consumption during network operation reflects the performance of the network. More remaining energy indicates less energy consumption and better network performance. The variation of remaining energy with the number of rounds for the protocols SEP, HCR, ERP, and the protocol based on BFGO-C running in the network is shown in Figure 14, and the remaining energy for the rounds when the first node dies and half of the nodes die is shown in Figure 15.  
The trend in energy consumption from Figure 14 shows that the protocol based on BFGO-C has more remaining energy than SEP, HCR, and ERP protocols. At the death of the first node in the network, the HCR protocol has the most residual energy and consumes the least, and the protocol based on BFGO-C is second. At the death of half of the nodes, the protocol based on BFGO-C and HCR protocol have similar residual energy, and both consume less energy than the SEP and ERP protocols. At the death of all nodes, the protocol based on BFGO-C consumes the least total energy than SEP, HCR, and ERP protocols. Protocol based on BFGO-C reduces network energy consumption to a certain extent.  
Figure 14: Variation of remaining energy with the number of rounds.  
Figure 13: Number of surviving nodes for rounds when the first node dies, half of the nodes die, and the last node dies.
## 3 Results and Discussion  
### Metallographic Observations and Microhardness Measurements  
Figure 3 shows the metallographic images of the surface on side A in two different positions. These positions were chosen as the locations emitting the lowest (540 mV) and highest (1440 mV) MBN after demagnetization. Figure 3a shows that the near-surface is not fully composed of martensite, but the microstructure is gently altered in the thin layer below the free surface. These laths are mixed with fine ferrite equiaxed grains, which appear white on the metallographic image. This effect becomes more pronounced in Figure 3b. This figure clearly demonstrates that the fine ferrite fully replaces the martensite in the near-surface region, and its extent is deeper in the bulk compared with Figure 3a. Figure 3b also shows that the fine ferrite is also mixed with martensite (or bainite) in the deeper regions, and the fraction of fine ferrite decreases towards the bulk at the expense of lath martensite (or bainite).  
Figure 4 indicates that the near-surface region is softened in contrast to the deeper bulk. The degree and extent of this thermal softening are deeper for the region emitting higher  
Figure 3: Metallographic images of the surface emitting different MBN in RD after demagnetization (1100 MC): (**a**) MBN = 540 mV and (**b**) MBN = 1440 mV.  
MBN. Thermo-mechanically treated sheets made of 1100 MC are hot rolled at temperatures exceeding the austenitization temperature. Performing such a process in the ambient atmosphere results in near-surface decarburizing. The transformation of martensite requires very high cooling rates, as well as a sufficient C content. The transformation of martensite is the shear process due to the over-saturation of C in the Fe lattice [28]. Decarburization remarkably reduces C over-saturation, which attenuates the shear process and results in a lower dislocation density. That is the reason why the decarburized surfaces suffer from softening. The decarburized layer usually appears white on metallographic images [29; 30].  
Due to the low penetration depth of decarburization and the corresponding microstructure heterogeneity, mechanical properties examined in the regions emitting different MBN (such as ultimate and yield strength as well as elongation at break) are nearly unaffected (above the nominal ones, uniaxial tensile test).
## 5 Conclusions  
In this paper, a new dimensionality reduction method SSRHE is proposed based on sparse hypergraph learning and spatial-spectral information for HSI. SSRHE computes two spatial neighborhood scatters to reveal the spatial correlation between each pixels in HSI, and it also constructs two discriminant hypergraphs by sparse representation to discover the complex multivariate relationships between interclass samples and intraclass samples, respectively. Based on the spatial neighborhood scatters and the Laplacian scatters of hypergraphs, a spatial-spectral combined objective function is designed to obtain an optimal projection matrix mapping original HSI data to low-dimensional embedding space where the intrinsic spatial and spectral properties are well preserved. some experiments were conducted on Indian Pines and PaviaU datasets to demonstrate that the proposed method possesses better performance compared with some existing state-of-the-art DR methods. In the future, we will optimize the proposed algorithm to reduce the running time and extend it to other related fields such as multi-spectral images and very-high resolution images, and the sparse hypergraph model in this paper can be used in some application domains with high-dimensional data such as face images, gene expression and radiomics features. Furthermore, It would also be interesting to study integrating hypergraph learning and heterogeneous information networks when exploring high-dimensional data with multiple adjacency relationships.  
Figure 11: Classification maps of different DR methods with 1-NN on the PaviaU dataset. Note that the time cost of corresponding DR algorithms is marked in bracket.  
**Author Contributions:** [PERSON] was primarily responsible for mathematical modeling and manuscript writing. [PERSON] contributed to the experimental design and experimental analysis. [PERSON] provided important suggestions for improving the paper.  
**Funding:** This work was supported in part by The Basic and Frontier Research Programmes of Chongqing under Grants cstc2018 icyjAX0093 and cstc2018 icyjAX0633, the Chongqing University Postgraduates Innovation Project under Grants CYB18048 and CYS18035, and the National Science Foundation of China under Grant 41371338.  
**Acknowledgments:** The authors would like to thank the anonymous reviewers and associate editor for their valuable comments and suggestions to improve the quality of the paper.  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 3 Experiment  
The infrared image signal applied in this article comes from the rolling bearing failure experimental bench in Figure 2a. The intercepted IR video interface is shown in Figure 2b. The experimental bench includes a servo motor, controller, coupling, shaft, faulty bearing and an infrared thermal image acquisition system. The bearing model is S6205-2 RSR. The motor speed is stabilized at 2000 rpm. The IR thermal image acquisition system includes BM_RI Software V7.4 and the IR thermal imaging camera FLIRA35. The parameters of the IR thermal imaging camera and the acquisition system are shown in Table 2.  
In order to test the performance of the proposed model, nine states of the bearing are set. They are health condition (HE), holder failure (HO), inner ring 0.5 mm crack (IN05), inner ring 1.0 mm crack (IN10), inner ring 1.5 mm crack (IN15), outer ring 0.5 mm crack (OU05), outer ring 1.0 mm crack (OU10), outer ring 1.5 mm crack (OU15) and rolling ball pitting (RO).  
During the acquisition process, the ambient temperature was maintained at about 24.5 \({}^{\circ}\)C. Each bearing state was waited for the temperature to remain stable while video acquisition was performed. Subsequently, 15 min of infrared video was acquired. The steps of infrared thermal image acquisition are shown below:  
Step 1: A state bearing is mounted to the shaft.  
Step 2: Turn on the motor controller and make sure the bearing is running at a constant speed of 2000 rpm.  
Step 3: Observe the temperature change and start collecting infrared video for 15 min after it is roughly stable.  
Step 4: Cool the rolling bearing failure test bench to ambient temperature of 24.5 \({}^{\circ}\)C.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Category** & **Content** & **Parameter** \\ \hline \multirow{2}{*}{FLIRA35} & Lens & FL019 \\  & Resolution & 320\({}^{\circ}\)256 \\  & Temperature measurement range & \(-\)40 \({}^{\circ}\)C\(-\)160 \({}^{\circ}\)C \\ \hline BM\_RI Software V7.4 & Color Palette & High contrast iron red \\ \hline \hline \end{tabular}
\end{table}
Table 2: Infrared thermal imaging camera and acquisition system parameters.  
Figure 2: Infrared image acquisition device and data acquisition interface. (**a**) The rolling bearing fault test bench; (**b**) Infrared video recording interface.  
Step 5: Repeat steps 1-4 to complete the acquisition of a total of nine 15 min infrared videos of different bearing failures.  
Step 6: Extract infrared images from the videos according to the 9 s time interval, 100 images for each category. In total, 900 images were extracted.  
Step 7: Select the bearing and shaft areas that produce temperature changes and crop them to obtain the RoI. The RoI of the extracted IR images for each category of bearings is shown in Figure 3.
## 3 Results  
### Chemical Composition of Unroasted and Roasted Cocoa Beans Criollo and Forastero  
The chemical composition of the unroasted and roasted cocoa beans from Peru (Criollo) and Ecuador (Forastero) is shown in Table 1. For both types, fat was the major nutrient (>40%), followed by carbohydrates (29-35%) and proteins (14.1-14.8%). Ash and moisture contents were less than 6% each. Unroasted and roasted cocoa bean composition varied significantly only in moisture content, 5.7 and 3.1 g per 100 g of the sample, respectively. The values found for proteins and total fat were different but comparable to those obtained by [PERSON] et al. [16] when studying differences in fatty acids profile in cocoa beans with different geographical origin. Results related to the mineral composition of unroasted and roasted cocoa beans, as shown in Table 1, indicated that cocoa beans contain several minerals which play a major role in different body functions including enzymatic reactions, energy production and transmission of nerve impulses [25; 26]. Significant differences due to the effect of roasting were found for iron, especially for Forastero species. Both cocoa beans were planted on the soil with comparable parameters. Cocoa is currently cultivated in most of the tropical lowlands throughout the world. Cocoa plantations are mostly suitable within 20\({}^{\circ}\) north and south of the Equator. An altitude between 200 m and 300 m is also suitable for cocoa cultivation. Cocoa requires a constant supply of rainfall that is evenly distributed throughout the year; preferably between 1500 mm to 2000 mm. Cocoa cultivation also requires temperatures between 18 \({}^{\circ}\)C and 32 \({}^{\circ}\)C. The soil conditions prevailing on cocoa plantations also require that they are porous, well-drained and more importantly rich in humus and other vital minerals needed for its growth. In effect, the soil should be fertile. Soil conditions exhibiting a pH between neutral and slightly acidic are also preferred, whilst carefully controlling the prevalence of pests and diseases ([27]; [PERSON], 1999). Cocoa trees may grow to a height of about 3 m or even more depending on the variety ([28]; Dissertation [PERSON] 2014, 17; [PERSON] 2018). Therefore the most probable explanation for this difference is the roasting procedure which always takes place in a metal container, so-called batch. Thermal treatment of the beans with the residues of acetic acid and lactic acid after the fermentation process and the presence of hot air together may cause the metal batch, mostly made of steel, to release traces of iron and other metals during the roasting process ([29; 30]). Composition and Distribution of Fatty Acids of Cocoa Butter Extracted from Unroasted and Roasted Cocoa Beans Criollo and Forastero  
Fatty acids from cocoa butter derived from roasted and unroasted cocoa beans were identified and quantified using GC-FID analyses, showing the separation of nine different fatty acid methyl esters (FAME) stated in Table 2.