esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction  
Optical integrated circuits based on a lithium niobate crystal are used in fiber optic gyroscopes for phase modulation of a signal and in fiber trunk circuits for signal encoding at a frequency of up to 100 GHz [1; 2]. The main advantages of using a lithium niobate crystal are its wide transmission window, high electro-optical coefficient r\({}_{33}\) and the relative simplicity of creating waveguides [3]. The disadvantages of the crystal include its complex structure and the variety of defects, as well as the difference in the composition, structure and properties of the near-surface layers on crystals of different manufacturers [4]. The waveguides of optical integrated circuits are formed by the ion exchange method. As a rule, they either replace Li\({}^{+}\) ions with H\({}^{+}\) ions (proton exchange method), or Nb\({}^{5+}\) ions with Ti\({}^{5+}\) ions (titanium diffusion method). The proton exchange method is somewhat simpler, because it does not require heating the crystal above 350 \({}^{\circ}\)C [5].  
In this paper we studied the temperature behavior of phase signal modulators used in a fiber optic gyroscope and constructed according to the scheme of Y-splitter. Temperature effects limit the accuracy of fiber optic gyroscopes and affect their noise characteristics [6; 7; 8]. Phenomena of a similar nature are observed in radiation intensity modulators of optic fiber transmission system [9; 10].  
A model, in which charged defects in the matrix of lithium niobate can move near the waveguide, was proposed to explain the observed drifts. In this model, the refractive index of the waveguide changes due to the local electro-optical effect.  
The output power was used as the measurement signal, and the variable external temperature in the temperature chamber was used as the effect.
## 4 Genome Editing for Autosomal Dominant Retinitis Pigmentosa
### Snrnp200  
Small Nuclear Ribonucleoprotein U5 Subunit 200 (_SNRPN200_) encodes BRR2, which is a component of the spliceosome. BRR2 is a RNA helicase that is a component of the U5 snRNP. BRR2, together with PRPF31, PRPF3, PRPF6 and PRPF8, belongs to the group of splicing factors that are part of the U4/U6-U5 tri-snRNP complex and which, when mutated, cause adRP [110].  
_SNRNP200_ is responsible for approximately 2.5% of all adRP cases [55; 56]. In total, 35 _SNRNP200_ mutations have been identified. Most of them are grouped within the first DExD box of the helicase, which is necessary for the unwinding of RNA [111; 112]. _SNRNP200_ mutations reduce helicase activity [113; 114; 115]. Furthermore, two _SNRNP200_ adRP mutations (p.Ser1087 Leu and p.Arg1090 Leu) affect not only spliceosome activation but also proper recognition of splice sites [110; 116; 117].  
The mechanism of pathogenicity of _SNRNP200_ mutations is not clear but haploinsufficiency can probably be excluded as it has been reported that missing one allele is not pathogenic [118]. To our knowledge, no studies on gene therapy for this gene exist to date. Lacking more information, the safest therapeutic approach would be correction of the mutant allele.
## 3 Methodology
### The Case of Bearing Fault Classification
#### 3.2.2 Hybrid Machine Learning Model  
The hybrid machine learning pipeline, see Figure 12, is set up like the conventional model with an additional step of adding knowledge.  
As already mentioned, ball bearings have characteristic frequencies such as the rotational frequency, the doubled rotational frequency caused by asymmetries of the rotor and the number of balls multiplied with the rotational frequency. The signal of a new and unused bearing has a specific spectrum of frequencies. Each frequency has a related importance (value of the amplitude). If the bearing becomes damaged or faces wear, the spectrum and the importance change. This means that, for example, sidebands become visible as an indication of a damaged inner ring. The strategy is to extract frequencies that correspond with a common damage of this specific ball bearing in a separate loop and sensitize the algorithm to these few frequencies to improve its performance and reliability.  
For the presented work, the measurement data are transformed into the frequency space with the fast Fourier transformation (FFT). The FFT of the signal itself is not enough to obtain a better performance with the existing amount of data. As already mentioned, the characteristic frequencies and sidebands are indicators for different types of wear and damages. The positions of these peaks are known (visible in Figures 2-4), so it is easy to detect and extract them. The finally used number of peaks is optimised in different runs.  
The used LSTM model for the hybrid machine learning model is the same as in the conventional machine learning pipeline, shown in Figures 10 and 11, to show the benefit out of the additional knowledge.
# Adaptive Multi-Modal Ensemble Network for Video Memorability Prediction
## 3 Proposed Methods
### Text Representation  
Firstly, for text data, stopwords were used to process some unnecessary words. Then, we used the count-vectorizer method to extract text content as semantic features. For each training text, it only considers the frequency of each word. Countvectorizer converts the words in the text into a word frequency matrix, which uses the fit-transform function to calculate the number of times each word appears. After converting words into vectors, we used principal component analysis (PCA) to reduce dimension. PCA is a standard data analysis method that is often used for dimensionality reduction of high-dimensional data and can extract the main feature components of data. After PCA dimensionality reduction,the dimension of text features corresponding to each video is 500-dimensional. Considering that the Random Forest (RF) algorithm has strong model generalization ability and fast training speed and the multi-layer perceptron (MLP) can quickly regress high-dimensional features into a memorability score, we compared and analyzed these two methods through experiments to more accurately predict the memorability score of the base learner, and then the final video memorability score is predicted more accurately. Finally, we used [PERSON]'s correlation coefficient to judge the correlation. The experimental results show that the multi-layer perceptron (MLP) can predict the memorability scores more efficiently as an individual learner. The following results are described in Section 4.2.1.  
Given a video instance \(\mathbf{V}_{i}=(v_{i},i_{i},t_{i})\), transforms semantic information of video \(i\) into 500-dimensional vector features \(t_{i}\). Let us define \(\gamma_{t}\) as the parameter of the text branch, the learned image-output \(\mathbf{To}_{i}\) of video \(i\) can be represented as follows:  
\[\mathbf{To}_{i}=f_{t}(t_{i},\gamma_{i}) \tag{2}\]  
where \(f_{t}\) defines the function of text features \(t_{i}\), which is used to obtain the memorability score of the semantic derived from the video \(i\), and \(\mathbf{To}\in\mathbb{R}^{n\times 1}=\{\mathbf{To}_{i}\}_{i=1}^{n}\).
# Random Vibration Fatigue Analysis Using a Nonlinear Cumulative Damage Model
## 5 Conclusions  
1. Since the inputs for the nonlinear model are the response acceleration's \(A_{res}\) values, and because, by using the dynamic factor \(\sigma_{dynamic}\), the vibration bending stresses' \(\sigma_{vb}\) values can be determined, then the proposed model can be applied in any me  
Figure 8: Damage curve.  
chanical component analysis submitted to random vibration forces where \(A_{res}\) values are known.
2. Since the dynamic factor \(\sigma_{dynamic}\) allows us to obtain stress units from acceleration units, then the vibration bending stress \(\sigma_{vb}\) values can be used in the proposed model Equation (14) to calculate the fatigue damage accumulation induced by the random vibration.
3. The constant exponent parameter value of 0.4 in the Manson-Halford model has been replaced by a vibration bending stress relation that considers the effect sequence and interaction loads induced by the applied PSD.
4. As a result of the mechanical component case study, the model proposed to predict the fatigue damage accumulation shows good agreement with the reported experimental data. The model predicts 28 cycles of load to reach the failure (\(D=1\)), and the experiment data collected from the vibration shaker showing, after 28 cycles of load, the deformation on the component's material can be considered as a failure.
5. The efficiency of the model proposed offers the advantage that even though random vibration (PSD) provides a complex loading history, based on the corresponding PSD, it is possible to obtain the fatigue damage accumulation through general analysis.
6. Since the proposed method is based on the bending stress induced by random vibration PSD function and its response acceleration, then, knowing that the fatigue damage accumulation can also be analyzed from a strain and crack growth propagation point of view, it seems that the proposed model could also be used in those cases, but more research must be undertaken.  
Conceptualization, J.M.B.-C., M.R.P.-M. and A.M.; methodology, J.M.B.-C. and M.R.P.-M.; data analysis, J.M.B.-C. and A.M.; writing--original draft preparation, J.M.B.-C. and M.R.P.-M.; writing--review and editing, J.M.B.-C., M.R.P.-M. and R.C.T.-V.; supervision, M.R.P.-M.; funding acquisition, J.M.B.-C. and R.C.T.-V. All authors have read and agreed to the published version of the manuscript.  
The research received no external funding.  
Not applicable.  
The authors declare no conflict of interest.
## 3 Results and Discussion
### Discussion
Additionally, canopy height fluctuations in the center of town are substantial and may cover many different types of land use. This creates a problem for subdividing urban areas into generalized classes of urban land use and activity based on the spectral values of each individual pixel [23]. The higher spatial resolution of ALOS/AVNIR-2 improves the detection of specific land use features, such as settlements, that lead to highly heterogeneous landscapes. As a result, ALOS/AVNIR-2 measured a higher GPP from settlement land use than Aster. In general, flux measurements are complicated in urban areas by surface heterogeneity, and NDVI becomes less important for scaling the CO\({}_{2}\) exchange [23]. Figure 4: Total annual GPP for different types of land use in the ALOS/AVNIR-2 and Aster data. The lower spatial resolution of Aster results in a higher total annual GPP from settlement land use than that measured by ALOS/AVNIR-2. The Aster satellite detects sparse vegetation around a settlement as a pixel with a low vegetation index rather than as a residential pixel. In other words, increased pixel size (or decreased spatial resolution) results in the loss of image detail [32]. Satellite data with high spatial resolution may be able to narrow the gap that currently exists between field measurements and remotely-sensed data from coarse-resolution satellites [34]. Improving spatial resolution is key to enhancing our ability to map detailed, scale-dependent variation. However, the image has high spatial resolution which has the disadvantage of having low spectral range, as also has been discussed previously by [PERSON] [35]. This condition causes the choice of image resolution is important to support the research goals.
# Safety Evaluation of a Water-Immersed Bridge Against Multiple Hazards via Machine Learning
## 8 Results and Discussion
Please note that the interpolated data between authentic ones may have a higher/lower exceedance probability (EP) than that of the authentic one, as shown in Figure 20. The proposed surrogate model is applied to Equation (23) only when the authentic model is not available. That is, if EP from the authentic model is unavailable, interpolated data from LSSVM was adopted to build plots in Figure 21. The main purpose of utilizing LSSVM for fragility analysis is to reduce the computational cost and retain the correct trends for engineering preliminary analysis. A failure decision for a given bridge depends not only on the failure probability but also on other factors such as the safety threshold, PGA design, scour depth, and performance level. Taking the bridge in Figure 20 for example, based on the bridge site, the PGA design was 0.24 g, assuming that the safety threshold was 0.00135, which is equivalent to a common reliability index (i.e., \(\beta=3\)) used for infrastructure. Under these conditions, it was found that among four different scour depths with collapse performance limit states considered, the case of 8 m scour can be considered as a false negative event. Thus, if the predicted fragility is used accompanied with other factors. such as reliability target, scour depth, and PGA, for bridge safety judgement, caution should be taken. If computation time is an issue, LSSVM provides an alternative to shorten the analysis time. The effectiveness of the LSSVM approach depends on the complexity of a given bridge. If the authentic approach is used, many pre-analyses such as material nonlinear properties, added mass, soil spring, plastic hinge length and property, nonlinear pushover analysis, and time history analysis are needed to build the fragility curve. Taking nonlinear time history analysis in this study for example, for each seismic intensity (e.g., the 475 year return period), seven analyses are needed. Such analyses often need several days or weeks to complete. If LSSVM is adopted, one can acquire the displacement within a few minutes. Indicated in Figure 21 is the joint failure probability distribution subjected to 100 year return period scouring when the bridge is immersed underwater at a depth of 4 m. \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Mean absolute error (MAE) & 0.2167 \\ Mean absolute percentage error (MAPE) & 10.76 \\ Root-mean-square error (RMSE) & 0.3209 \\ \(R^{2}\) & 0.9053 \\ \(R\) & 0.9582 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Result values from the training.
## 2 System Model  
We investigated a trunk-assisted anti-interference communication system for UACN, which comprises a transmitter, receiver, relay node, and a hostile jammer. The transmitter operates intermittently as transmitting information is vulnerable to disruption by nearby hostile jammers. These jammers emit interference signals to degrade the performance of information transmission. To enhance the system's anti-interference capabilities, a relay node is introduced to forward information between the transmitter and receiver. The relay node effectively mitigates the impact of jamming, thereby improving the overall reliability and performance of the communication system.  
At time \(k\), the transmitter sends a signal to the receiver at the center frequency \(f_{0}\) and bandwidth \(w\). The transmitter decides whether to trigger \(x\in X=\{0,1\}\), where \(A\) is the set of feasible actions determined by the transmitter, to utilize the relay node for forwarding the signal. When \(x=1\), the transmitter activates the relay node, which forwards the signal to the receiver at a fixed transmission power \(P_{R}^{(k)}\) and transmission cost \(C_{R}\). Otherwise, the transmitter sends the signal directly to the receiver. The transmitting power \(P_{S}\) of the transmitter is selected from the range \(\left[0,P_{S}^{\max}\right]\), where \(P_{S}^{\max}\) is the maximum allowable transmission power. The cost incurred by the transmitter per unit of transmitted power is denoted as \(C_{S}\).
# An Overview of Biopolymers for Drug Delivery Applications
## 2 Types of Biopolymers Used in Drug Delivery Systems
### Polysaccharides
#### 2.1.2 Alginate  
Because of its remarkable encapsulating qualities and function in the healing of bruises, alginate is also a highly utilized biopolymer in the pharmaceutical and medical sectors. Since its first isolation in the 1980s, alginate has found numerous uses because of its many benefits, including being a mucoadhesive, biodegradable, biocompatible, renewable, and easily accessible substance. It is also non-toxic and immunogenic. This biopolymer is used to treat reflux esophagitis and is regarded as an excipient in the pharmaceutical sector [50; 51].  
Alginate is extracted from brown algae (_Macrocystis pyrifera, Laminaria hyperborea, saccharina japonica_, and _Ascophyllum nodosum_) and is found as sodium, calcium, and magnesium salts of alginic acid. Its synthesis can be performed by different species of bacteria (_Azotobacter vinelandii_ and various _Pseudomonas species_) [52]. Alginate can be extracted by grinding the raw material from algae, cleaning it with acid, and then using heated alkali to extract it. The obtained alginic acid is filtered, precipitated with calcium, and then acidified. By processing insoluble alginic acid with oxides, metallic carbonates, and hydroxides, the required alginate salt can be produced [53].  
Solutions of alginate quickly form gels in the presence of various divalent cations, calcium being the most extensively used. These gels are stable in the temperature range of 0 to 100 \({}^{\circ}\)C. These gels may dissociate in the presence of acids. The experimental conditions of forming gels (e.g., alginate concentration, temperature, cation type, etc.) need to be correctly controlled in order to produce gels with a homogeneous composition. In contact with intestinal fluids, the alginate particles break down due to the presence of Na+ ions and acids. To avoid this disintegration, most of the time, alginate is used in combination with one or more biopolymers for developing DDSs [54].  
[PERSON] et al. developed dual cross-linked chitosan/alginate hydrogels for pH-responsive drug delivery. The hydrogels that were developed demonstrated a hydrophobic drug loading capacity of 44% (\(wt./wt.\)) and did not cause any cytotoxicity on human cells when evaluated, showing their biocompatibility [55]. [PERSON] and colleagues created a pH- and temperature-responsive pectin/chitosan biopolymer hydrogel for use in medication delivery systems. The hydrogels that were created had a strong ability to mend themselves and were shown to be biocompatible, causing no adverse reactions in mouse fibroblast cells [56].
## 3 Results and Discussion  
In this section, the three beamformers (i.e., DAS, FDMAS, \(p\)-DAS) are analyzed and compared through the results obtained in simulation and experiments. In the first subsection, \(p\)-DAS is illustrated with a simulated point target. Then, the performances of the \(p\)-DAS in terms of the image quality (resolution and contrast) for the four phantoms of the PICMUS challenge are presented, for 1 PW and 11 PW. The last subsection makes the comparison of images reconstructed with FDMAS and \(p\)-DAS beamformers.  
Figure 2: B-mode images obtained with single plane wave imaging for the four phantoms and the four beamformers compared: DAS (**a**,**e**,**i**,**m**), FDMAS (**b**,**f**,**j**,**n**), 2-DAS (**c**,**g**,**k**,**o**), and 3-DAS (**d**,**h**,**l**,**p**). (**a**–**d**) the numerical phantom used for the resolution; (**e**–**h**) the numerical phantom used for the contrast; (**i**–**l**) the experimental phantom used for the resolution; and (**m**–**p**) the experimental phantom used for the contrast. All of the images are displayed with a 60-dB dynamic range. An example of the boundaries chosen for the contrast metrics is given for simulation (**e**) and experiment (**m**), with the inside of the cyst in red, and the outside of the speckle ring in green.
# Method of Calculating Desynchronization of DVB-T Transmitters Working in SFN for PCL Applications
## 10 Desynchronization Impact on PCL
\begin{table}
\begin{tabular}{l l l l l} \hline \hline  & **Station 1** & **Station 2** & **Station 3** & **Station 4** \\ \hline mean error [m] & \(1.892\times 10^{3}\) & \(1.954\times 10^{3}\) & \(1.913\times 10^{3}\) & \(2.091\times 10^{3}\) \\ \hline variance [m\({}^{2}\)] & \(1.495\times 10^{6}\) & \(1.558\times 10^{6}\) & \(1.547\times 10^{6}\) & \(1.431\times 10^{6}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Simulation Results of Localization Error. Figure 9: Visual example of a single simulation for station 4 (red marker) and two transmitters ([PERSON]—green marker, PKIN—blue marker). Target’s position (marked with pink cross) does not match the ellipses intersection point due to transmitter desynchronization. Depending on the geometry of the target and receiver, desynchronization of transmitters equal to the measured 3.63 \(\upmu\)s can introduce on average a 2 km error in passive radar localization for the geometry assumed in the simulation. In extreme cases, the error can reach over 6 km. Using the proposed method, the desynchronization error can be eliminated or greatly mitigated.
_Applied_  
_sciences_  
_Article_  
**The Transient Flow behind an Instantaneously Started Circular Cylinder with Two Symmetrical Strips**  
**[PERSON]\({}^{\copyright}\), [PERSON] \({}^{\star}\), [PERSON], [PERSON] and [PERSON]**  
College of Power and Energy Engineering, Harbin Engineering University, Harbin 150001, China;  
[EMAIL_ADDRESS] (J.Z.); [EMAIL_ADDRESS] (T.Y.); [EMAIL_ADDRESS] (K.W.);  
[EMAIL_ADDRESS] (K.S.)  
\({}^{\star}\) Correspondence: [EMAIL_ADDRESS]; Tel.: +86-139-4615-6585  
Received: 3 March 2020; Accepted: 22 March 2020; Published: 27 March 2020  
**Featured Application: The numerical approach in this article can provide abundant information about the transient flow of the fluid shape changes with boundary motion and may offer the control scheme for the transient flow behind an instantaneously started circular cylinder.**  
**Abstract:** The finite volume method, based on the dynamic mesh method, is used to investigate the transient viscous incompressible flow around an impulsively and translationally started cylinder with strips. The strips of different shapes are installed at different locations on the surface of the cylinder. The main purpose of this paper is to investigate the influence of the locations and shapes of strips on the flow caused by boundary motion. The present solutions agree well with the experimental results reported in literature. Six placement angles of strips were selected: \(0^{\circ}\), \(20^{\circ}\), \(60^{\circ}\), \(90^{\circ}\), \(120^{\circ}\) and \(150^{\circ}\). The development of wake shows some new phenomena with different strip locations, and the significant difference appears at \(\alpha=90^{\circ}\). The vortex intensity is much larger than that of other locations. On the other hand, four shapes of strips were selected: arc, triangle, rectangle and trapezoid. The rectangular strips had the greatest influence on the drag coefficient and the maximum of the drag coefficient increased from 0.4 to 2.8, compared with the smooth cylinder. The maximum of negative velocity had the most significant change when the shape of strip is arc, increasing by 34% compared with the smooth cylinder, at T = 3.  
**Keywords:** dynamic mesh method; finite volume method; transient flow; cylinder with strips; CFD (Computational Fluid Dynamics)