esa-sceva/satcom-chunk-collection huggingface dataset:
# A Proposal for Rapid Assessment of Long-Distance Oil and Gas Pipelines After Earthquakes
## 5 Limitations and Outlook  
This study constitutes an initial exploration into the intricate relationship between seismic hazards and oil and gas pipelines, the prevailing monitoring systems, and pipeline engineering attributes. It subsequently proposes a comprehensive methodology for the evaluation of pipeline safety, encompassing a novel post-earthquake evaluation technique for long-distance oil and gas pipelines. This system integrates the results of multi-source monitoring data based on pipeline seismic geological disaster risk evaluation, and it can realise risk level adjustment based on field data. However, this study is still in the preliminary construction stage; it lacks empirical validation through real-world test results or comparisons with past earthquake events, and there are still many detailed issues that need to be deepened:  
1. Firstly, how to ensure the accuracy and timeliness of various types of monitoring data in the practical application of the evaluation method and how to better integrate the data from different sources.  
Figure 11: Schematic of pipeline risk adjustment considering monitoring data along the pipeline route.  
Figure 12: Seismic hazard information for a single point along the pipeline.  
2 The second issue pertains to the evaluation criteria for pipeline vulnerability to coseismic landslides, which is contingent on the pipeline's laying method. The parameter determination and model optimisation in the evaluation model require additional data support and practical validation.
3 Thirdly, the application of the theoretical framework presented in this paper to regions with different geology and seismic intensity needs to be refined. For example, it is important to highlight the differences between mountains and plains, and active and inactive fault zones.  
By solving the issues mentioned above, it is possible to continually refine the theoretical framework presented in this paper. A more perfect pipeline safety evaluation data platform can then be established to achieve efficient collection, transmission, storage and analysis of various types of data, providing a solid data foundation for the evaluation method. Building a rapid assessment system for oil and gas pipeline safety will further enhance the evaluation process. Concurrently, efforts should be directed towards the advancement of practical research on oil and gas pipelines in diverse regions and configuration types. This endeavour aims to facilitate the continual enhancement of the evaluation system, thereby ensuring its elevated scientific rigor and operational efficiency. These efforts are imperative to ensure optimal resilience against the threats posed by seismic hazards to the secure and reliable operation of oil and gas pipelines. Furthermore, this research is essential for safeguarding the seamless functioning of these pipelines in the presence of natural disasters such as earthquakes.
## 3 Results
### Workload  
The participants' self-reported workload data were weighted and averaged, and then they were tested for normality, indicating that the workload data were not normally distributed (\(p<0.05\)). Thus, non-parametric analyses were performed. Tests revealed that the main effect of SAT on the participants' workload approached significance, H(2) = 5.220, \(p\) = 0.074. Tests also revealed there was no significant effect of scenario urgency on the participants' workload, \(p>0.05\).  
According to the descriptive statistics, the participants' workloads were lower under the SAT level 1 + 3 (M = 78.22, SD = 39.811) and SAT level 1 conditions (M = 84.12, SD = 54.706) than under the SAT level 1 + 2 + 3 condition (M = 100.64, SD = 39.966). The participants' workloads were numerically higher under the high-urgency condition (M = 92.52, SD = 48.436) than under the low-urgency condition (M = 82.81, SD = 42.993).
# Increasing the Bioactive Compound Content of Olive Oil by Acidification of Olive Paste
## 4 Discussion
### Volatile Compound Content in the Oils Obtained with Acids  
As shown in Table 5, ascorbic and citric acids enhance the concentration of C6 compounds compared to the control oils, whereas acetic acid does not appear to influence these compounds at low concentrations but reduces them at higher concentrations. Both acetic and citric acids exhibit a dose-dependent reduction in C6 compounds, whereas ascorbic acid does not show a clear dose-dependent effect. The lowest dose of citric acid resulted in a twofold increase in C6 compound content in the oils compared to the control. Focusing on oils obtained with 1% ascorbic acid--which yielded the highest extraction efficiency, oleuppein derivatives content, and antioxidant capacity, the primary objectives of this study--the results indicate an approximate 50% increase in C6 compounds.  
For C5 compounds, a similar trend to C6 compounds was observed, with a slight increase when ascorbic acid was applied. The highest C5 concentration was detected at the highest ascorbic acid concentration and the lowest citric acid concentration. Both ascorbic and citric acids slightly reduced ethanol content, while acetic acid led to a more pronounced decrease. In oils extracted with 1% ascorbic acid, the ethanol content was approximately 18% lower than in the control samples. Thus, the incorporation of 1% ascorbic acid into the paste promotes enzymatic pathways responsible for generating desirable volatile compounds while simultaneously reducing the presence of ethanol, an undesirable fermentation byproduct.  
As with phenolic compounds, the volatile compound composition of olive oils is highly variable, influenced by both extrinsic and intrinsic factors related to cultivation and processing [50]. [PERSON] et al. [51], in their study on the Royal cultivar, reported variations in volatile compound concentrations depending on whether the analyzed oil was collected from the decanter outlet or the vertical centrifuge and whether malaxation lasted 15 or 30 min. Their findings closely align with the results obtained in this study.
# Advanced Scale-Propeller Design Using a MATLAB Optimization Code
## 2 Materials and Methods
### Propeller/Rotor Efficiency  
The efficiency calculation of a blade propulsion system varies depending on whether the system is a rotor or propeller driven system. Rotor driven systems, such as those found on helicopters, use a hover efficiency metric called the Figure of Merit (FoM), whilst propeller driven systems use a more conventional propulsive efficiency term \(\eta_{P}\).
## 4 Results and Discussion
### DA-OA-ICOS Combined with White Noise Perturbation
#### 4.1.4 Measurement Stability and MDL for DA-OA-ICOS  
In order to fully evaluate the performance of the sensor, measurements were conducted on standard CH4 gas with a concentration of 1000 ppm for 10 min with 1 s sampling intervals. The MDL was analyzed in detail by the Allan deviation. The concentration data were collected by the sensor under the original signal and the white noise perturbation, as shown in Figure 6a. The results showed that the concentration fluctuation range of the original signal (black) was less than 60 ppm, while the fluctuation range of the white noise perturbation (red) was reduced to 30 ppm. The average concentration, standard deviation, and maximum uncertainty obtained by the original system were 1009.5 ppm, 11.1 ppm, and 4.0%, respectively. The average concentration, standard deviation, and maximum uncertainty obtained after adding the white noise perturbation were 1004.3 ppm, 3.6 ppm, and 1.8%, respectively. The Allan deviation was further calculated for both the original signal and the white noise perturbation, as shown in Figure 6b. The detection limit of the  
Figure 5: Fitting curves between CH4 concentration and the direct absorption peak under the original signal (black) and the white noise perturbation of 30% modulation depth (red).  
original signal (black) was 9.1 ppm at 2 s integration time, and the MDL was 5.4 ppm at 122 s integration time. The detection limit of the white noise perturbation (red) was 5.7 ppm at 2 s integration time, and the MDL was 2.2 ppm at 117 s integration time. Compared to the original system under the same conditions, the sensing system with the white noise perturbation of 30% modulation depth improved the MDL by 2.5 times. It was shown that the addition of white noise perturbation not only enhanced the stability of the sensor, but also substantially improved the measurement sensitivity.
## 2 Data Preprocessing
### Outlier Detection  
To have a reliable and automated sensor system, data pre-treatment also needs to detect possible outliers that could influence modeling effects. Unlike noise, an outlier is an observation that disobeys the distribution of the rest of the data [16]. Outliers can also be called \"questionable data\", \"strange points\", or \"doubtable observations\", and are often caused by confounding system mechanisms or instrument error [17]. Outliers may cause damage to a modeling system to which they do not belong, so a broad range of techniques have been applied for outlier detection. Statistical analysis methods are widely used to detect outliers in linear systems, estimating the standardized residual of each observation in the regression model [17; 18]. Self-organizing map (SOM) was introduced to detect outliers in nonlinear systems, based on the distance between data points [19]. However, in some cases, distance is not a proper criterion for outlier verification, because some normal data may deviate more from the majority of the data than outliers, especially for highly nonlinear systems. A method integrating a linear outlier detection strategy with radial basis function neural networks (RBFNN) was proposed to detect outliers in complex nonlinear systems [20]. Outliers are not noise, so simply excluding outliers from analysis may be not beneficial to the discovery of the hidden mechanisms and rules.
###### Abstract  
The measurement accuracy of trace gas detection based on infrared absorption spectroscopy is influenced by the overlap of absorption lines. A method for correcting the interference of overlapping absorption lines using second harmonic spectral reconstruction (2f-SR) is proposed to improve the measurement accuracy. 2f-SR includes three parts: measurement of gas temperature and use of the differences in temperature characteristics of absorption lines to correct the temperature error, 2f signal restoration based on laser characteristics to eliminate the influence of waveform change on overlapping absorption lines, and fast multi-peak fitting for the separation of interference from overlapping absorption lines. The CH\({}_{4}\) measurement accuracy based on overlapping absorption lines is better than 0.8% using 2f-SR. 2f-SR has a lower minimum detection limit (MDL) and a higher detection accuracy than the separation of overlapping absorption lines based on the direct absorption method. The MDL is reduced by two to three orders of magnitude and reaches the part per million by volume level. 2f-SR has clear advantages for correcting the interference of overlapping absorption lines in terms of both MDL and measurement accuracy.  
overlapping absorption lines; absorption spectroscopy; second harmonic spectral reconstruction; carbon dioxide monitoring +
Footnote †: journal: Applied  
Accepted: 20 December 2021  
Published: 22 December 2021  
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###### Abstract  
The Virtual Synchronous Generator (VSG) control strategy has garnered widespread application during the low-voltage ride-through (LVRT) of distributed energy resources integrated into power grids, primarily due to its inertia and damping properties. However, grid voltage dips frequently coincide with unbalanced conditions and harmonic disturbances, against which traditional VSG LVRT control strategies offer limited resilience, resulting in unbalanced and unstable grid-connected currents. Consequently, this impacts the VSG's support for voltage at the point of common coupling (PCC) during LVRT, potentially leading to control system failure. To tackle this challenge, this paper introduces a VSG LVRT control strategy tailored for complex grid faults. Initially, a mathematical model is developed to analyze the impact on the VSG control system's grid-connected current when the PCC voltage of the LC filter experiences harmonic-laden unbalanced dips. Subsequently, the traditional dual second-order generalized integrator phase-locked loop (DSOGI-PLL) is enhanced to bolster its filtering capabilities. Additionally, PCC voltage feedforward control is incorporated, with a meticulously derived feedforward function to counteract the disturbances caused by unbalanced grid voltage dips, thereby enhancing the VSG system's anti-interference ability and stabilizing the grid-connected current. This enables effective VSG LVRT control in the face of complex grid faults and ensures successful LVRT of the grid-connected system. Ultimately, the efficacy of the proposed control strategy is confirmed through PSCAD simulations.  
complex grid faults; improved DSOGI-PLL; grid voltage feedforward; low-voltage ride-through Article
###### Abstract  
Over the past decade, cold atmospheric plasma (CAP) has undergone extensive research as a promising therapeutic approach in oncology, with different treatment methods and exposure configurations being investigated and resulting in various biological effects, most of them after long exposure or treatment durations. This study aimed to evaluate the potential of a custom-made CAP generation source to produce plasma-activated medium (PAM) with cytotoxic effects and subsequently to establish the optimal exposure and treatment parameters. The exposure's electrical parameters, as well as pH and NO\({}_{2}^{-}\) content of PAM were analyzed. The cytotoxic potential and optimal parameters of the treatment were established by evaluating the viability of human osteosarcoma cells (HOS cell line) and human osteoblasts (HOB cell line) treated with PAM under different conditions. Our results showed that indirect treatment with CAP presents selective dose-dependent cytotoxic effects, while the cell viability decrease was not found to be correlated with the PAM acidification due to CAP exposure. The Griess assay revealed very high and long-term stable concentrations of NO\({}_{2}^{-}\) in PAM. Overall, this study presents a simple and faster method of producing PAM treatment with cytotoxic effects on HOS cells, by using a custom-built CAP source.  
cold atmospheric plasma; dielectric barrier discharge; indirect treatment; osteosarcoma; PAM
## 3 Insulator Conductivity Measurement
Moreover, at 80 \({}^{\circ}\)C, the influence of electric field strength on volume resistivity diminishes, as shown in the experimental data. Based on experimental data of insulator volume conductivity under varying temperature and electric field conditions, a functional relationship for the volume resistivity with respect to temperature and electric field was derived. Furthermore, the volume conductivity of the insulator is expressed by Equation (24), and the results demonstrate that the volume conductivity exhibits exponential growth with increasing temperature and electric field strength. \[\sigma_{v}=\frac{1}{\rho_{Rv}}=\frac{1}{7.894\times 10^{21}e^{-0.0476T-0.139E}} \tag{24}\]  
The surface resistivity parameter measurement platform is illustrated in Figure 5, where the experimental electrodes are situated within a closed experimental container filled with SF\({}_{6}\) gas at a pressure of 0.5 MPa. [PERSON] et al. [26] experimentally investigated the effects of temperature and electric field on the surface conductivity of insulators. The results show that, within a temperature range  
Figure 4: Bulk resistivity measurement data. \[S=\frac{(d+g)^{2}}{4} \tag{21}\]0 Surface conductivity measurement platform. of 40 \({}^{\circ}\)C to 80 \({}^{\circ}\)C, the surface conductivity is more significantly influenced by the tangential electric field than by temperature. In this investigation, surface conductivity measurements were conducted under varying tangential electric field intensities at a constant ambient temperature of 20 \({}^{\circ}\)C. This is mainly because, within the temperature range examined in this study, the surface conductivity is primarily determined by changes in the tangential electric field, so the effects of temperature changes can be ignored while also taking into account the environmental conditions of the laboratory. The surface resistivity distribution across varying electric field conditions at a constant temperature of 20 \({}^{\circ}\)C was determined through experimental measurements, as illustrated in \[S=\frac{(d+g)^{2}}{4} \tag{21}\]1 Moreover, the surface resistivity declines with increasing electric field strength. Analysis of the experimental data yielded a functional relationship describing the relationship between the surface resistivity of the insulator and the tangential electric field, while the surface conductance of the insulator can be expressed as  
\[S=\frac{(d+g)^{2}}{4} \tag{21}\]2  
where \(E_{t}\) is the tangential electric field strength, V/m. We acknowledge that measuring surface conductivity at a fixed 20 \({}^{\circ}\)C may limit the generalizability of our findings, as temperature significantly affects conductivity. Future studies will explore surface conductivity across a broader temperature range to validate our conclusions under varied operational conditions.
## 1 Introduction
In general, amongst research about the material composition and performance of SMA, research on gradations whose nominal maximum size of aggregate is 4.75 mm (dense-graded) is still rare. Still, in the current mix design of small-particle size asphalt mixture, high-temperature performance and water stability were used to evaluate the performance of asphalt mixture. Thus, more investigations including material composition and anti-crack performance are therefore needed to establish a systematic study on small-particle size (SPS) asphalt mixture. Top-down cracks usually appear in asphalt surface layers within 5 years after construction and research showed that temperature and loads stresses under high and low temperatures are major factors. The relationship between pavement surface cracks and pavement structure is still uncertain; however, in fact, the appearance of cracks is closely related to asphalt mixture. Meanwhile, the severe oxidation of asphalt binder within a few millimeters of the pavement surface will reduce the tensile strength of the mixture, a larger tensile strain will appear in the pavement surface when the surface temperature approximates or exceeds the softening point at high temperatures. All of these are main contributors of top-down cracks [22; 23]. Thus, it would be more effective to improve pavement crack resistance based on the material composition of asphalt mixture. The small particle-size (SPS) asphalt mixture proposed in this paper is dense-graded mixture with a high content of asphalt. The nominal maximum size of aggregate is 4.75 mm, the proportion of aggregate passing a 2.36-mm sieve is 70%, asphalt content is between 6% and 8%.
# Multi-Dimensional Sparse-Coded Ambient Backscatter Communication for Massive IoT Networks
## 6 Conclusions  
In this paper, we have proposed the MSC-AmBC system based on sparse codes to support long-range and high-rate ambient backscatter communications for massive IoT networks. To design such a system, we utilized the inherent characteristics of ambient sources as well as multiple tags. By utilizing the common OFDM carriers from these sources, we can effectively eliminate the strong DLI with DFT operation and band-pass filtering to extract the useful pilots contained in ambient signals. Also, utilization of the sparsity in batteryless RF tags can increase the dimension of signal space to achieve diversity or multiplexing in AmBC. We have proposed the heuristic algorithm for optimal design of the constellation mapping matrix and the reflection coefficient projection and expansion method in MPA to effectively construct the multi-dimensional constellation essential for high-order backscatter modulation. The proposed modulation can readily be implemented at batteryless IoT devices without increasing hardware costs whose effectiveness was confirmed by numerical evaluations. Therefore, the MSC-AmBC will be a promising solution for massive IoT networks where a huge number of active and passive IoT devices coexist, such as smart city/factory, or LP-WAN.  
Figure 13: Effect of the overloading factor \(\lambda\) and the reflection coefficient \(\alpha\) for detection performance at the reader when \(\zeta=0.16\), \(D=0.2\), and \(M=2\).  
**Author Contributions:** T.Y.K. has contributed to the theoretical approaches, simulation and preparing the paper; D.I.K. provides revision.  
**Funding:** This work was funded by the Korean government (MSIT) (NRF-2014R1A5A1011478).  
**Acknowledgments:** This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (NRF-2014R1A5A1011478).  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 4 Discussion
### Segmentation Results  
The evaluation metrics in Table 4 shows that the CNN performs better than any threshold in average for the entire dataset. The values of F1 and IoU around 0.66 and 0.50 are not enough to be used in a production environment. Despite this, the distance to production-level results is not far. Strategies such as the ones mentioned in the state-of-the-art, combining A-scan signal data with C-scans and a bigger dataset may raise the performance level to the requirements. In addition, the evaluation of the models in object detection metrics remains a future work.  
As Figures 7 and 8 show, the performance varies in a range up to 0.2 in F1 and IoU across the different projections. The CNN fails with respect to challenging segmentation cases, such as projections near to the front surface, e.g., the two first projections in the Coupon 2 dataset and the last one in Coupon 1 (see dataset in the appendix), which are  
Figure 9: Detail of a projection illustrating the differences between the two labels used. (**a**) Ultrasonic input. (**b**) XCT labels superimposed. (**c**) Manual labels superimposed.  
noisier, or in resin-rich pocket regions. The orientation of the voids played a role as well, in projections such as 3 and 4 with more presence of horizontal and diagonal aligned voids the metrics decreased. The visual evaluation after the 3D prediction confirmed these challenging cases: resin structures, slices near the front or back surfaces, showed echoes that were indistinguishable from the defects. This is a future line of research, where possible solutions include improving the signal-to-noise ratio, deconvolution of the A-scan signals, further optimization of the ultrasonic imaging, and the integration of additional features of the ultrasonic signal.  
A key result is the robustness of the training, irrespective of whether the CNN is trained on the data of Coupon 1 or Coupon 2, the training and test results are equivalent. In other words, the evaluation metrics are equivalent when the projections of Coupon 1 are used for training to when they are used in testing. The network appears to be able to interpret where segmentation must be performed and is consistent even if the training and test data roles are inverted.