esa-sceva/satcom-chunk-collection huggingface dataset:
# Free Vibrations and Flutter Analysis of Composite Plates Reinforced with Carbon Nanotubes
## 4 Conclusions  
The paper was dedicated to the study of the free vibration and flutter characteristics of carbon nanotube-reinforced composite plates, with the core issue being the in-depth analysis of the eigenfrequencies and flutter of classical carbon nanotube/nanocomposite thin plates in supersonic airflow environments. It was assumed that the reinforcing material of the thin plate is uniformly distributed and aligned in the polymer matrix with the low-volume fraction of carbon nanotubes. The analysis of free vibrations and supersonic flutter was presented considering the volume fraction of CNTs, geometrical parameters, and boundary conditions. Micromechanical modeling was applied to predict the mechanical properties of nanocomposites.  
The analyses performed led to the following conclusions:  
* For all nanotube volume fractions analyzed, increasing the aspect ratio decreases the fundamental frequency. When the volume fraction of CNTs was increased from 1% to 5%, a 2.7-fold improvement in frequency was observed. The effect of the volume fraction of CNTs on frequencies decreases with increasing aspect ratios.
* A lower frequency was observed with thinner nanocomposite sheets. However, the differences decrease as the aspect ratio of the plate increases. The growth in thickness at a constant width-to-length ratio influenced the increase in natural frequencies, and it was a constant increase of 2.5-fold.
* It was shown that even low-volume fractions of nanotubes can effectively increase the natural frequencies of nanocomposite plates.
* It was shown that the higher the volume fraction of CNTs, the narrower the eigenvalue curves. However, the discrepancies are less pronounced for higher CNT volume fractions than isotropic cases.
* It can be seen that the boundary conditions affect the eigenvalue curve more than the CNT volume fraction.
* The possible solution to the flutter problem was mainly influenced by the changes in the eigenvalue curves. The coincidence or small differences in the position of the coalescence point for higher volume fractions of CNTs were caused by the shape of the eigenvalue curves. For the higher volume fraction of CNTs, there was almost the same shape and position of the eigenvalue curve.  
The current study demonstrated the applicability of the analytical (graphical) method in predicting the pre-flutter and post-flutter behavior of nanocomposite plates. It was presented as plots of non-dimensional pressure, non-dimensional frequency, and eigenvalue curves that can be used to analytically find the coalescence point. The extension of the current work should take into account the damping analysis of nanocomposites with CNTs, which was proposed in [10,18].  
This research received no external funding.  
Not applicable.  
Data Availability StatementData are contained within the article.  
The author declares no conflict of interest.
# Remote Sensing and Machine Learning for Safer Railways: A Review
## 4 Discussion
### Challenges Reported  
Some publications discussed difficulties with their chosen methods, while others grappled with issues related to the quality of the captured images. For instance, [PERSON] et al. (2022) used three deep learning models: convolutional 1D (Conv1D), convolutional 2D (Conv2D), and long short-term memory (LSTM) [20]. Notably, the training time for Conv2D exceeded the duration required by the other models. [PERSON] et al. (2022) disclosed that one disadvantage of their approach was that it requires preprocessing to normalize the images before training the model [22]. [PERSON] et al. (2021) found that blurred images can severely decrease detection accuracy [74]. [PERSON] et al. (2019) reported that a general disadvantage of ML methods is oscillations in the training convergence, which require an optimized learning rate that the model cannot establish itself [53]. [PERSON] et al. (2021) described the need for continuous calibration of the data collection system to compensate for distance variations between the sensor and the object [35]. [PERSON] et al. (2022) emphasized the difficulty of pixel-level labeling of faults to train the network [68].
# GNSS Accuracy Under White Gaussian Noise Jamming +
## 4 Comparison of Theoretical and Measured Results
### Carrier-to-Noise Ratio  
In Figure 3, the measured versus theoretically expected decreases in the \(C/N_{0}\) and \(\Delta C/N_{0}\) are shown for a jammer with 1, 2, and 4 MHz bandwidths. The solid line is the expected \(\Delta C/N_{0}\) based on the theory, the cross is the average of the measured \(\Delta C/N_{0}\), and the error bar indicates the standard deviation of the measurements. The more negative the \(\Delta C/N_{0}\), the greater the impact of the jammer on the \(C/N_{0}\). The measured average \(\Delta C/N_{0}\) was determined by subtracting the average of the \(C/N_{0}\) measurements taken in the last minute (approx. 600 samples) by the average of the measurements taken in the last minute before the jammer was turned on.  
Figure 3: Comparison of the theoretical \(C/N_{0}\) with the simulated results. (**a**) GPS C/A and (**b**) Galileo E1. The solid lines indicate the theoretical \(C/N_{0}\), the cross denotes the average measured \(C/N_{0}\), and the error bar gives the standard deviation of the measurements.  
The \(C/N_{0}\) measurements confirm the theoretical results exceptionally well for both GPS C/A (Figure 3a) and Galileo E1 (Figure 3b). As expected, as shown in Figure 1, the impact of the jammer on the \(C/N_{0}\) of GPS C/A increases with a decreasing jammer bandwidth. For Galileo E1, the effect is different. The impact of the 1 MHz and 4 MHz jammers is less than the impact of the 2 MHz jammer. This was expected based on Figure 1, as the \(Q\) at 2 MHz is close to the theoretical minimum at a bandwidth of approximately 2.2 MHz. Also, as expected, the Galileo E1 signals are less affected by the jammer than the GPS C/A signals.  
From these results, we can conclude that the impact of a jammer on the \(C/N_{0}\) can be accurately predicted using (3) for both GPS C/A and Galileo E1 signals.
## 2 Theory and Modeling
### Simulation Model Coupled with Lidar System  
An improved semi-analytic simulation model was developed for estimating the probability of photon scatter back to a remote receiver \(E(k)\) at the surface coupled with lidar system parameters (see Figure 4).  
\[E(k)=\frac{P(\Theta)}{4\pi}\Delta\Omega\exp(\tau)=\frac{P(\theta)}{4\pi}\frac{ A_{r}}{H^{2}}\exp(\tau), \tag{34}\]  
where \(P(\Theta)\) is the scattering phase function value at angle \(\Theta\), \(\Delta\Omega\) is the small solid received angle by a remote detector, \(A_{r}\) is detector aperture, \(H\) is lidar flight height, and \(\tau\) is the atmosphere optical thickness. The solid angle of collision photon received by a remote detector is so small that the cosine value of the actual backscattering line is similar to the line perpendicular to the air/water interface. The atmosphere is purely Rayleigh atmosphere with no aerosols, and the oceanic constituents only consist of seawater molecules with no hydrosols. The factor of molecular depolarization in the air is zero. The detector height is 300 m, and the lidar frequency used here is 532 nm; thus, the atmosphere optical thickness can be negligible. The detector aperture \(A_{r}\) is 0.06 m\({}^{2}\). The water absorption coefficient is 0.04 m\({}^{-1}\) and the scattering coefficient is 0.06 m\({}^{-1}\). To avoid the solar noise, we simplify the simulation and assume nighttime conditions (i.e., the lidar is the only light source).  
The semi-analytic Monte Carlo radiative transfer model developed by [PERSON] [12; 14] is based on analytical estimate of the probability of photon scatter back to a remote receiver, and the lidar geometric model is considered for oceanographic lidar systems. The estimated value \(E(k)\) of the fraction of photons collected by the remoter receiver upon a scattering event at collision point \(k\) is calculated using [PERSON]'s method [29].  
Figure 4: Lidar geometric model for analytically estimating the probability of photon scatter back to a remote receiver.  
As shown in Figure 4, whether the photon's position is within the receiver field of view (FOV) needs to be determined.  
\[x_{k}^{2}+y_{k}^{2}\leq A, \tag{35}\]  
\[A=\Omega_{FOV}H^{2}, \tag{36}\]  
where \(\Omega_{FOV}\) is the receiver FOV solid angle, \(A\) is the area at the surface seen by the receiver, and \(x_{k}\) and \(y_{k}\) are the photon's position in Cartesian coordinates.
## 5 Discussion
### Perceived Workload  
For the NASA-TLX questionnaire results on perceived workload, we found that in both tasks, the overall workload score via the simplified 3D landmark-based minimap was significantly (\(p<0.05\)) lower than that of the normal 3D minimap. However, for the independent component in the exploration task, only the \(p\)-value of the mental demand scores of the two modes was significant (\(p<0.05\)). In the navigation task, the mental demand (\(p<0.05\)) and effort (\(p<0.05\)) differences between the two mode maps were statistically significant. We think this is because the self-location and wayfinding in both tasks require higher mental workloads for thinking, deciding, remembering, looking, and searching. The navigation task might require more effort than the free walking in the exploration task. This point was also verified in the interview session.  
We also considered the reason that the score differences were non-significant between the two modes for other independent components. We suppose that our task in the experiment was not too difficult in the virtual reality environment compared to the real-world experiment. Therefore, the independent components of physical, temporal demand, performance, and frustration made no significant difference in the two modes. Consequently, we plan to optimize our method and experiment in a more immersive way to simulate a mixed-reality environment and will conduct the outdoor field experiment to explore every independent component of the NASA-TLX workload.  
Based on the above discussion, we can answer Research Question 2 and conclude that the simplified 3D minimap mode decreases the overall workload and the mental demand during exploratory navigation.
## 3 Results
### Workload Measures and Player Experience  
Of the matches analyzed (N = 1002), 3.59% (N = 36) were played with athletes in their first year on the field, 45.51% (N = 456) with athletes in their second to fourth years, and 50.90% (N = 510) with athletes in their fifth year or greater of international competition experience. There was a main effect for player experience for mechanical work (\(F(2,\,999)\) = 23.81, \(p<0.05\)), sRPE (\(F(2,\,999)\) = 28.48, \(p<0.05\)), and the SDC model (\(F(2,\,999)\) = 41.10, \(p<0.05\)). [PERSON]'s post hoc tests identified significant differences in workload from all three player experience groups for mechanical work (year 1-year 2-4 mean difference = 16,121.72, 95% CI [7615.11, 24,628.33], \(p<0.05\), \(d=0.78\), indicating a large effect; year 1-year 5+ mean difference = 21,991.25, 95% CI [13,519.01, 30,463.49], \(p<0.05\), \(d=1.05\), indicating a very large effect; year 2-4-year 5+ mean difference = 5869.53, 95% CI [2713.09, 9025.97], \(p<0.05\), \(d=0.28\), indicating a small effect) and sRPE (year 1-year 2-4 mean difference = 18.14, 95% CI [0.90, 35.38], \(p<0.05\), \(d=0.45\), indicating a moderate effect; year 1-year 5+ mean difference = 36.19, 95% CI [19.02, 53.36], \(p<0.05\), \(d=0.83\), indicating a large effect; year 2-4-year 5+ mean difference = 18.04, 95% CI [11.65, 24.44], \(p<0.05\), \(d=0.52\), indicating a moderate effect) (Figure 4). In the SDC model, significant differences were present between the year 1 and year 5+ player experience groups (mean difference = 46,026.03, 95% CI [25,395.47, 66,656.58], \(p<0.05\), \(d=-0.73\), indicating a moderate-to-large effect) and the year 2-4 and year 5+ player experience groups (mean difference = 26,967.84, 95% CI [19,281.67, 34,654.01], \(p<0.05\), \(d=0.52\), indicating a moderate effect) (Figure 4).  
Figure 3: (**a**) Average game work, (**b**) sRPE, (**c**) SDC model, workload measures by match outcome, \({}^{*}\) denotes significant comparison (\(p<0.05\)).
## 3 Results and Discussion
### Hydrotreater of Oil Refinery Plant
#### 3.1.3 Testing of the Dismantled Object  
Thus, the results of the cluster analysis confirmed a previously determined degree of danger of AE source located in zone #5. A final decision to stop the hydrotreater was made. The dismantled hydrotreater was investigated by NDT in order to establish the reasons of its transition to the critical state. Internal examination revealed numerous disintegrations of the cladding layer (up to its complete absence in some areas) (Figure 4). Dimensions of damages were up to 5 mm. Ultrasonic testing revealed numerous discontinuities in welds and the base metal shell. The lengths of discontinuities were 100 mm along and 15 mm in depth. In one of the most active zones, discontinuities were detected both in welds and in the heat-affected zone. Certain discontinuities occurred at different depths, from 26 to 80 mm. These damages demonstrated significant degradation with loss of mechanical properties of the metal, which leads to brittle fracture of the structure [11].  
Thus, the use of SHM-system allowed, on the one hand, to extend the lifetime of the hydrotreater by 6 months and on the other hand, to prevent the destruction of the hydrotreater during operation with all the ensuing consequences.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameters** & **Channel No 8** & **Channel No 17** \\ \hline Signals in the cluster & 284 & 138 \\ Mean amplitude, dB\({}_{\text{AE}}\) & 72 & 69 \\ Mean rise time, us & 240 & 379 \\ Mean duration, us & 893 & 1057 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Parameters of clusters for channels 8 and 17.  
Figure 3: Waveforms corresponding to clusters centers of mass, for acoustic emission (AE) signals from channels: (**a**) channel #8; (**b**) channel #17.
## 4 Results and Discussion
### A Combination of Open and Short Faults at the Terminal Block  
In a seven-core C&l cable, short faults were emulated in Lines 3 and 4, and the open fault was applied to Line 2 at the terminal block. Figure 8 shows the fault detection and classification results with Line 6 as the generation line. The results of the TFCC and ANN indicate that the terminal block at 130 m was determined as an unbalanced fault point through the differences between the faulty line pair and the normal line pair data, as illustrated in Figure 8b. Therefore, the reflected signals at the faulty terminal block (130 m) require clustering to determine the faulty line. Next, hierarchy clustering was applied to the reflected signals at the unbalanced fault point. The multi-core diagnostic data was classified into three clusters which is shown in Figure 8c. One corresponds to line pairs where the short fault occurred(Lines 3-4, 4-3). Another contains all line pairs including Line 2, where an open fault occurred, and the last one contains the rest. In the open fault case, all lines including the open fault line (Line 2) were clustered. On the other hand, only the faulty line pair data (Line 3-4) was clustered in the short fault. The phase of the normal line pairs is normally close to zero but was slightly below  
Figure 7: Fault detection and classification results with the Line 3 as the generator line. (**a**) TFDR reflected signals, (**b**) phase estimation results, and (**c**) TFCC and ANN results and (**d**) heat-map representation and hierarchy clustering results on TFDR results.  
zero due to short fault crosstalk. Normal line pair data have low TFCC values, but the phases are long distributed due to the crosstalk. The centroid and the variance of each cluster are summarized in Table 1. The results show that it is possible to detect an open fault in all related faulty line pair data whereas the short fault is detected only in a line where a short fault occurs. Thus, open and short faulty lines in multi-core cables can be detected even with combined faults occurring at the same point.
###### Abstract
Combining these innovative technologies in a data-driven approach will enhance product traceability, simulate lifecycles, facilitate R-strategy adoption, and assess and predict environmental impacts. A digital product passport (DPP) refers to a system that contains detailed information about a product's materials, origin, use, and end-of-life handling instructions. The concept is becoming increasingly significant in the context of the European Union's circular economy action plan [5]. These passports provide comprehensive digital records of products, including their material composition, production history, lifecycle events, and compliance with environmental and social standards. By capturing detailed information about each product, DPPs enable greater transparency and traceability, which are essential for ensuring the responsible production, usage, and disposal of products.
# Performance Analysis of MIMO System with Single RF Link Based on Switched Parasitic Antenna
## 2 Theory of MIMO System  
In this section, the theory of the single RF link MIMO system will be introduced. The structure, principle, and key technologies of the single RF link MIMO system introduced in this chapter are based on switched parasitic antenna structure.
## 2 Precision Medicine and Cardiology
### Myocardial Infarction
#### 2.1.3 Biomarkers  
The development of biomarkers in precision medicine has been astounding and is still evolving. [PERSON] et al. suggested the use of computational modeling to provide precise diagnostic care to patients and improve individual risk prediction. Computed biomechanical parameters such as contractility, stiffness, myofilament kinetics, strain, and stress provide information about LV function, thus determining the extent of cardiac damage and future prognosis [37]. [PERSON] et al. established biomarkers such as myeloperoxidase and hyaluronidase-2 to identify plaque erosion among ACS patients [35]. The CD44v6 splicing variant of the hyaluron receptor was significantly higher in patients with plaque erosion than in plaque fissures, which can help detect silent myocardial infarctions. Adding to the evidence of the benefit of therapy individualization, [PERSON] et al. concluded that the decision to prolong DAPT therapy should be assessed individually for each patient [38]. For assessment, prognostic models should look at demographics and behavior, cardiovascular history, non-cardiovascular history, biomarkers, and drugs. [PERSON] et al. explored the use of basic fibroblast growth factor (bFGF) in myocardial ischemia injury [33]. Oxidative stress plays a major role in myocardial injury, and bFGF can reduce oxidative stress bypromoting the activation of NrF2 via the Akt/GSKb/Fyn pathway, which reduces cardiomyocytes apoptosis and thus the infarct size to a larger extent, ultimately alleviating the heart injury. More studies are being conducted to study the cardioprotective effect of bFGF, which is certainly a novel preventive tool to treat MI. Further, [PERSON] et al. found that epoxyeicosatrienoic acid (EET) elicits potent anti-inflammatory, vasodilatory, anti-apoptotic, pro-angiogenic, fibrinolytic, and smooth muscle cell anti-migratory effects with-in the cardiovascular system [41], and thus can be used in the treatment of acute MI. [PERSON] et al. investigated the application of telmisartan-doped co-assembly nanofibers (TDCNfs), dual-ligand supramolecular nanofibers that synergistically counter-regulate RAS through targeted delivery, and presented it as an option for combined therapy against cardiac deterioration post-MI [32]. It reduces apoptosis, alleviates inflammatory response, and inhibits fibrosis to potentially mitigate post-MI outcomes [32]. Aside from MI, the treatment for myocardial infarction with no obstructive coronary arteries (MINOCA) also requires an investigation of cause to determine the patient-specific treatment [36]. Collectively, precision medicine helps to individualize the therapy by blending various diagnostic modalities such as ECG, cardiac enzymes, other biomarkers, echocardiography, coronary angiography, coronary vasomotion, and intravascular imaging techniques.
# UAV-Derived Himalayan Topography: Hazard Assessments and Comparison with Global DEM Products
## 3 Results
### Applications
#### 3.2.2 Landslides  
A landslide occurred on the Marsyangdi River \(\sim\)1.5 km upstream from the village of Lower Pisang following the 2015 Gorkha earthquake (Figure 7). The landslide constricted the channel and formed a lake. The slump of the channel bank and deposition of the mass in the river was visible in the DEM of difference between the UAV and HMA DEMs (Figure 7c). The volume of mass loss was 83,100 m\({}^{3}\). Considering both mass loss and the channel deposition, the volume change was \(-\)37,600 m\({}^{3}\), suggesting that \(\sim\)45,500 m\({}^{3}\) of material was removed between the date of the landslide and the UAV survey. A DEM of difference between two HMA DEMs (May 2015 and March 2014) suggested a comparable but lower mass loss of 68,000 m\({}^{3}\), indicating that additional slumping likely occurred in the years following the initial landslide.
## 4 Results and Discussion
### Experimental Determination of the Capillary Action
#### 4.1.1 Sintered Powder Silica Gel Sheets  
Two types of commercial silica gel films commonly used for flat chromatography (Alugram and Nano Alugram) were characterized [38]. Their main physical characteristics are shown in Table 3, with methanol as the working fluid.  
Figure 4: Permeability test bench (left) and simplified scheme (right).  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & **Material** & **S (\(\mu\)m)** & **A (mm/s)** & **A\({}_{1}\) (mm)** & **t\({}_{1}\) (s)** & **A\({}_{2}\) (mm)** & **t\({}_{2}\) (s)** \\ \hline \multirow{3}{*}{**Silica Gel sheets**} & Alugram-SIL G & 5–17 & 0.14 & 18.22767 & 457.8688 & 30.47236 & 26.70651 \\ \cline{2-8}  & Nano & & & & & & \\ \cline{2-8}  & Alugram-SIL G & 2–10 & 0.16 & 23.52259 & 210.0246 & 25.98887 & 16.58615 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Properties of silica gel sheets and capillary action (methanol).  
The capillary action for the silica gel sheets and methanol, in accordance with the above-mentioned procedure and equipment, is shown in Figure 5.  
According to the results shown in Figure 5a, the smaller the pore size, the higher the ascension velocity. The flow speed (\(\alpha\)) was 14% higher for the Nano Alugram than for the Alugram. In both wicks, \(\alpha\) met the application specifications. The Nano Alugram had a superior initial velocity (1.6 mm/s) compared with that of the Alugram (1.2 mm/s), although it descended drastically with time, (Figure 5b).  
The maximum attainable height (H = A\({}_{1}\) + A\({}_{2}\)) in both the Alugram and the Nano Alugram was, respectively, 44.7 mm and 49.5 mm. In both cases, the maximum height pumped exceeded the specifications (L = 30 mm).