esa-sceva/satcom-chunk-collection huggingface dataset:
# 2D Ultrasonic Antenna System for Imaging in Liquid Sodium
## 2 Imaging Principle of the 2-Antenna System
### Main Advantages and Drawbacks of the Imaging System  
As said in the introduction, the main advantage of the 2-antenna system is the large aperture of each antenna, much larger than that obtained with the same number of elements arranged in a matrix pattern, allowing the improvement of the spatial resolution (see, for example, numerical values of the spatial resolution in Section 3.2). The main drawback comes from the way the cigar-beam is formed from the two fan-beams. Indeed, as the combination of the two fan-beams leads to a deflected cigar-beam of which the orientation depends on the position of the focusing point in the field of vision, the system is suitable only for targets generating specular echoes that come back to the receiver regardless of their orientation and position in the field of vision (as spherical targets or targets with rounded parts) and for targets, as the large, rough, curved surfaces of a reactor vessel, that diffract the field in all directions (that is the main application presented in Reference [5]). A distortion could be observed for targets generating specular echoes that do not come back to the receiver, but some targets could also be not detected at all if the specular echoes completely miss the receiver. For targets for which low diffraction echoes are involved in the imaging process, a small signal-to-noise ratio (SNR) is obtained. These considerations on the orientation of the cigar-beam used for the scanning imaging are also valid for the elementary beams impacting the target in the FMC/TFM imaging. Thus, the elementary echoes of the FMC might be invisible and lost in the noise, with the total target echo emerging from the noise only after the TFM computation.
# A Novel Battery-Supplied AFE EEG Circuit Capable of Muscle Movement Artifact Suppression
## 5 Discussion
### Observed Limitations of the Proposed EEG Circuit Design
The transmission of the acquired signal could be materialized with the use of BLE or Wi-Fi to a computer for real-time mobile BCI applications. Extending the design based on the proposed AFE for multi-channel data acquisition is a self-evident next step for research. This will further increase spatial resolution in EEG data and can be combined with the use of highly sensitive dry or wet electrodes and well-shielded cables for minimal noise signal propagation between the electrodes and the AFE. A PCB design with meticulous care for signal integrity and avoidance of EMI is also a valid future perspective of the presented research. Furthermore, the design of a proof-of-concept BCI application using this AFE could also be a logical next step for extending the results of this research. This BCI could also take into account hardware problems related to the AFE that arise when the designer wants to enable user-specific calibration utilities in the circuit level, such as the use of case specific Programmable Gain Amplifiers for gain adjustment, based on input impedance measurements during usage. Lastly, a study on the choice of material with respect to preserving signal integrity while not minimizing signal accuracy could be a future topic of expansion of the present study. In recapitulation, the materialization of all the above propositions translates to a more robust AFE design that would allow for cost-effective multi-channel deployments and that could be crafted for compliance with all the legal medical requirement standards for the purpose of ensuring usability in medical settings. Fixing these technological bottlenecks and keeping these suggestions in mind during the design process show that the EEG systems could undergo potential improvements for use in research and therapeutics. This will lead to high usability and effectiveness in real-world applications. Allowing the scientific community access to the proposed ideas and concerns posed by this study could hopefully accelerate the process of reproducible AFE designs that support real-time EMI and muscle artifact removal.
## 2 Study Area  
The study site is centered on the Skukuza Eddy Covariance (EC) flux tower, which falls within the Lowveld in the north eastern part of Mpumalanga Province of South Africa (Figure 1). The Lowveld predominantly belongs to the large savanna biome, which covers one-third of the country. It is characterized by hot humid summers and mild dry winters. Summer rains occur between October and May across a west to east precipitation gradient, with a mean annual precipitation of 633 mm and mean annual temperature of 21 C [13]. The Lowveld's dominant geology includes granite and gneiss with local gabbro intrusions [14]. The slopes and crests are characterized by a mixture of tall shrubland with few trees to moderately dense low woodland, and valleys dominated by dense thicket and open savanna. Vegetation distribution and density in the region are influenced by the rainfall gradient, geology, fire events, mega-herbivore browsing, cattle grazing, and the anthropogenic harvesting of wood [14,15]. Coppicing is prominent in areas which experience high levels of anthropogenic utilization [9]. Granite lowveld is the main vegetation unit in the area, with dominant tree species, including _Terminalia serica_, _Combretum zeyheri_, _Combretum apiculum_, _Acacia nigrescens_, dominant shrub species, including _Dichrostachys cinerea_ and _Grewia bicolor_, and dominant grass species, including _Pogonarthria squarrosa_, _Tricholaena monadne_, _Engrarostis rigidity_, _Panicum maximum_, _Aristida congesta_, _Digitaria eriantha_, and _Urochla mossambicensis_[13].
## Appendix D Instability Detection Using Other \(k\) Lags
### Another Experiment Using Synthetic Samples Generated with the GGRBM  
We performed additional experiments with synthetic samples generated from the GGRBM. To generate the samples, we first presented variants of input vectors with clamped features at predicted values of interest (see Table 10) and other features we left free to run in the simulations. The results for each variant are shown in Figure 11.  
The most interesting results are in variants M and N (Case 6). In these simulations, we predefined a situation characteristic of a financial bubble in which we have substantial cumulative returns and slopes. In M, the volatilities of the last 4 days are high, while in N, they are low. This difference alone marks a noticeable change in the bubble probabilities according to the model, indicating that even when we have features that account for a bubble, the probability of this is strongly conditioned by the state of volatility of the last few days. Note that variants H and I (case 4) are very similar to M and N, only that we leave all volatility features free in these first two. While the model delivers probabilities over 50% in synthetic samples of M and N, neither is the median as high as in those of H and I.  
Figure 11: Violin plots for bubble probabilities of synthetic samples are estimated with the BRF trained with samples of the hidden units of a GGRBM of 16 hidden units. The GGRGM was trainedwith samples from the 1987 (Black Monday), 2000 (dot-com), and 2008 (Subprime) crises. Each box presents the bubble probabilities for three primary cases: Case 4 (slopes and cumulative returns at high levels), Case 5 (slopes and cumulative returns at low levels), and Case 6 (slopes and cumulative returns at high levels). In Cases 4 and 5, the \(k=8\) volatility features are free to run in the Gibbs sample, while the other features are clamped. In Case 6, only the first four volatility lags are free, and the remaining four are clamped at a high level, as well as the slopes and cumulated returns. The letters indicate the variants used to generate the 1000 synthetic samples. Note: The dotted line indicates the probability of a bubble at 50. The red line inside the violin represents the median.
## 3 Cutting-Edge Online Fault Diagnosis Techniques for Al-Caps
### Signal-Based Online Fault Diagnosis Techniques (SB-ON-FDTs)
Although the last two techniques are not entirely non-invasive, they impose fewer practical constraints compared to methods that require inserting a current sensor into the capacitor branch. In [36], the authors apply a bandpass filter to extract the AC components of the DC-link voltage and current in an uninterrupted power supply (UPS). By analyzing the modes of these signals, they calculate the power loss in the aluminum capacitor (al-cap) and estimate its equivalent series resistance (ESR). To overcome the practical limitations of placing a current sensor in the capacitor branch, the current in the capacitor is reconstructed using the output current of the rectifier, the current to the inverter, and the current to the battery module. In [37], the authors propose a method to estimate the ESR values of al-caps used in the output filters of boost converters by analyzing the inductor current and the output voltage waveforms. First, they apply an analog high-pass filter combined with a wavelet transform denoising (WTD) method to extract the ripple from the output voltage. Then, using the output voltage ripple, the inductor current, and a set of analytical expressions, they estimate the ESR value. This approach integrates time-domain and frequency-domain techniques, and is thus a hybrid method.
## 3 Results and Discussions
### Result of RSM/CCD Analysis
#### 3.3.2 Optimization of the PUCM Mixtures  
The optimization method aims to explore the correct proportion of independent parameters (PU binder and NS) suitable for achieving an optimized PUCM mixture, agreeing to peak values in relation to mechanical strength. The variables were adjusted to a specific range during the optimization method to account for all possible result combinations, and responses were maximized, as listed in Table 8. The solution revealing maximum desirability was considered as the optimal PU-cement mortar mixture, as listed in Table 8, and the optimized strength is depicted in Figure 12. The optimized PUCM mixture was achieved by adding 3.5% PU binder and the addition of 2.93 NS particles by weight of cement. The peak response values were 15.13 MPa and 52.21 MPa for flexural strength and  
Figure 11: Two-dimensional plots for the simultaneous effect of PU binder and NS in the PUCM for (**a**) flexural strength and (**b**) compressive strength.  
Figure 10: Three-dimensional plots for the simultaneous effect of PU binder and NS in the PUCM for: (**a**) Flexural strength and (**b**) compressive strength.  
compressive strength, respectively, with 97.1% of the overall desirability of independent variables, as shown in Table 9.
# Construction Progress and Aviation Flight Test of BDSBAS
## 2 Overview of BDSBAS
### BDSBAS SF Solution
#### 2.3.2 Atmospheric Delay Correction Calculation  
The atmospheric propagation delay of radio frequency (RF) signals is one of the main errors for GNSS. For the SF SBAS service, the tropospheric delay is corrected by using a dry-wet component model similar to that in GNSS, and the ionospheric delay is corrected by the broadcast corrections of the ionospheric grid points (IGP).  
Ionospheric Correction  
The ionospheric grid corrections of BDSBAS SF service are broadcast in the augmentation message type 26 (MT26). Since the system actually broadcasts the vertical delay corrections of the IGP, user needs to use the surrounding grid points to calculate the obliquity ionospheric delay corrections of its own pierce point.  
Specifically, the user needs to first calculate the latitude \(\phi_{pp}\) and longitude \(\lambda_{pp}\) of the pierce point. Then, the ionospheric grid points around the pierce point are used to interpolate and obtain the vertical ionospheric delay estimate \(\tau_{opp}\big{(}\phi_{pp},\lambda_{pp}\big{)}\) of the pierce point. At the same time, the residual variance \(\sigma_{\text{UVE}}^{2}\) of the vertical ionospheric delay correction at the pierce point is obtained.  
On this basis, the obliquity factor \(F_{pp}\) is introduced and \(\tau_{opp}\big{(}\phi_{pp},\lambda_{pp}\big{)}\) is further converted into the obliquity ionospheric delay correction \(IC_{i}\) for user's final use, which can be expressed as follows:  
\[IC_{i}=-F_{pp}\cdot\tau_{opp}\big{(}\phi_{pp},\lambda_{pp}\big{)} \tag{7}\]  
with  
\[F_{pp}=\left[1-\left(\frac{R_{e}\cos E}{R_{e}+h_{l}}\right)^{2}\right]^{-\frac {1}{2}} \tag{8}\]  
where \(E\) is the satellite elevation angle, \(R_{e}=6378.1363\) km is the radius of the earth, and \(h_{l}=350\) km is the height of the maximum electron density layer.  
Finally, the obliquity factor \(F_{pp}\) is used to update \(\sigma_{\text{UVE}}^{2}\), and obtain the residual variance \(\sigma_{\text{UVE}}^{2}\) of the obliquity ionospheric delay for the pierce point, which can be expressed by  
\[\sigma_{\text{UVE}}^{2}=F_{pp}^{2}\cdot\sigma_{\text{UVE}}^{2} \tag{9}\]  
where the residual variance \(\sigma_{\text{UVE}}^{2}\) will be used in the subsequent calculation of the protection level.
## 6 Evaluation Experiment of the Proposed Approach
### Qualitative Analysis of the Crowdsourced Requirements
Evaluating the feasibility of the crowdsourced requirements is important since some suggested requirements can be difficult to implement technically, require a long duration or would be too expensive. Therefore, we plan to explore how feasible the requirements and features elicited from the selected crowd could be. The 44 crowdsourced requirements are evaluated in terms of the aforementioned factors. A group of experts, including PhD, Master's and Bachelor's holders or studentswho either specialize in software engineering or have taken courses in the field, were invited to participate in evaluating each of the 44 requirements. In total, seven experts participated in the evaluation stage. Moreover, instead of assessing the requirements as a cohesive unit, each requirement is assessed independently based on clarity, creativity, relatedness and feasibility to derive accurately representative results. However, since diversity cannot be measured based on a single requirement, this factor is assessed by analyzing the requirements as a whole. A five-scale measure was utilized for evaluation, where 5 indicates strongly agree and 1 indicates strongly disagree. For each requirement, the average of the seven experts' assessments is calculated which represents the overall level of the measured factor. Figure 11 shows a heat map that demonstrates the averaged assessment scores for each requirement in terms of clarity, creativity, relatedness and feasibility; diversity was not included for the reasons declared previously. For better interpretability and to emphasize the requirements with low scores, light blue represents higher scores and dark blue represents lower scores. The heat map illustrated in Figure 11 has apparently shown that the crowdsourced fitness app requirements have achieved encouraging and valuable outcomes when assessed in terms of the four declared factors. Light areas cover the majority of the heat map, with fewer areas marked with dark blue. This indicates that the crowdsourced requirements meet our quality objectives. In addition, the heat map revealed that clarity and feasibility  
Figure 11: Heat map for the averaged assessment of the crowdsourced requirements. have the highest acceptance and creativity has the lowest since it has more dark areas than the other factors. To find the general overall evaluation score for each factor, we calculate the average assessment score for all 44 requirements. Furthermore, the diversity factor was measured by analyzing the requirements as a whole, and the overall score was obtained by taking the average of the diversity assessment scores from the seven experts. Table 9 shows the averaged assessment scores for all five factors.
_Article_  
**Comparative Study of the Trueness of the Inner**  
**Surface of Crowns Fabricated from Three Types of**  
**Lithium Disilicate Blocks**  
**[PERSON] 1,2\({}^{\bigcirc}\), [PERSON] 1,2\({}^{\bigcirc}\), [PERSON] 3 and [PERSON] 2,4,* * 1 Department of Dental Science, Graduate School, Kyungpook National University, Daegu 41940, Korea; [EMAIL_ADDRESS] (K.S.); [EMAIL_ADDRESS] (B.Y.) Advanced Dental Device Development Institute, Kyungpook National University, Daegu 41940, Korea 3 Department of Prosthodontes, Hamdan Bin Mohammed College of Dental Medicine, Mohammed Bin Rashid University, Dubai 505055, UAE; [EMAIL_ADDRESS] Department of Prosthodontes, School of Dentistry, Kyungpook National University, Daegu 41940, Korea * Correspondence: [EMAIL_ADDRESS]; Tel.: +82-053-600-7674 check for updates**  
Received: 21 March 2019; Accepted: 26 April 2019; Published: 29 April 2019  
**Abstract:** This study set out to compare the three-dimensional (3D) trueness of crowns produced from three types of lithium disilicate blocks. The working model was digitized, and single crowns (maximally left second molar) were designed using computer-aided design (CAD) software. To produce a crown design model (CDM), a crown design file was extracted from the CAD software. In addition, using the CDM file and a milling machine (\(N=20\)), three types of lithium disilicate blocks (e.max CAD, HASS Rosetta, and VITA Suprinity) were processed. To produce a crown scan model (CSM), the inner surface of each fabricated crown was digitized using a touch-probe scanner. In addition, using 3D inspection software, the CDM was partitioned (into marginal, axis, angular, and occlusal regions), the CDM and CSM were overlapped, and a 3D analysis was conducted. A Kruskal-Wallis test (\(\alpha=0.05\)) was conducted with all-segmented teeth with the root mean square (RMS), and they were analyzed using the Mann-Whitney \(U\)-test and the Bonferroni correction method as a post hoc test. There was a significant difference in the trueness of the crowns according to the type of lithium disilicate block (\(p<0.001\)). The overall RMS value was at a maximum for e.max (\(42.9\pm 4.4\)\(\upmu\)m), followed by HASS (\(30.1\pm 9.0\)\(\upmu\)m) and then VITA (\(27.3\pm 7.9\)\(\upmu\)m). However, there was no significant difference between HASS and VITA (\(p=0.541\)). There were significant differences in all regions inside the crown (\(p<0.001\)). There was a significantly high trueness in the angular region inside the crown (\(p<0.001\)). A correction could thus be applied in the CAD process, considering the differences in the trueness by the type of lithium disilicate block. In addition, to attain a crown with an excellent fit, it is necessary to provide a larger setting space for the angular region during the CAD process.  
**Keywords:** three-dimensional analysis; trueness; dental CAD-CAM; dental ceramic; dentistry
# Ventricular Fibrillation Prediction and Detection: A Comprehensive Review of Modern Techniques
## 2 Modern ECG Signal Processing Techniques for Detection and Prediction of Ventricular Fibrillation
### Neural Networks and Deep Learning Algorithms
#### 2.2.6 Validation Techniques  
* Cross-Validation: The use of k-fold cross-validation allows the evaluation of model performance on multiple subsets of the dataset, ensuring robust performance estimation.
* Independent Test Dataset: Keeping an independent test dataset that is not used during training is essential for the final evaluation of the model and to ensure that the observed performance is representative of new data.  
Neural networks, especially CNNs and RNNs, have been intensively studied for VF detection due to their ability to learn complex features from ECG data. In [1], the performance of CNN and LSTM in the detection of ventricular fibrillation was compared. CNN achieved an accuracy of 98.7%, sensitivity of 98%, and specificity of 99.2%. LSTM showed comparable performance, with an accuracy of 98.3%, sensitivity of 97.5%, and specificity of 99%. These results demonstrate that both networks are very efficient, with CNN having a slight superiority in terms of specificity.  
Neural networks, especially CNNs and RNNs, provide powerful and efficient methods for the detection and prediction of ventricular fibrillation from ECG signals. Integrating these techniques into portable medical devices and remote monitoring systems is an important step toward improving the diagnosis and treatment of cardiac arrhythmias. Future research could explore the use of generative neural networks for data augmentation and the development of hybrid models that combine the advantages of CNNs and RNNs for even better performance.
## Material and Methodology
### Statistical Analysis  
The results are displayed as averages with error bars representing the standard deviation (SD). Statistical analysis was conducted using one-way analysis of variance (ANOVA). The tested samples (\(n=5\)) were grouped based on sample weight composition and injection molding temperature for comparison. ANOVA was employed to determine the significance of material compositions and injection temperature effects on the mechanical properties obtained during tensile and bending tests of the miniplate samples. A significance level of \(\alpha=0.05\) was utilized and the \(p\)-value was compared in the mentioned comparisons. Results with a \(p\)-value less than 0.05 were considered significantly different and indicated by an asterisk (*) and (*) for injection temperature and material compositions effects, respectively.