esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
### The Governing Equation  
A schematic diagram of the vibration of an infinite E-B beam supported by a foundation under a moving load is shown in Figure 1. The governing equation that describes the dynamic behavior of the beam is provided below:  
\[EI\frac{\partial^{4}w}{\partial x^{4}}+\rho A\frac{\partial^{2}w}{\partial t^{2} }+c\frac{\partial w}{\partial t}+k\,w=P\,\delta(x-v\,t), \tag{1}\]  
where \(w=w(x,t)\) represents the beam's transverse deflection, with \(E\) as the modulus of elasticity and \(I\) as the second moment of area. \(\rho\) stands for the beam material's density, and \(A\) denotes the beam's cross-sectional area. The foundation's stiffness and damping coefficient are indicated by \(k\) and \(c\), respectively. The moving load's magnitude and velocity are represented by \(P\) and \(v\), while \(\delta(\cdot)\) signifies the Dirac function. Since the beam is of infinite length, the boundary conditions can be expressed as  
\[\lim_{x\rightarrow\pm\infty}w(x,t)=0,\quad\lim_{x\rightarrow\pm\infty}\frac{ \partial^{i}w(x,t)}{\partial x^{i}}=0,\,\,j=1,2,3,4. \tag{2}\]  
The boundary conditions indicate that the slopes and curvatures of points far from the moving load tend to zero. To analyze the beam's steady-state response, a new coordinate system can be introduced, fixed relative to the moving load, as follows:  
\[y=x-v\,t. \tag{3}\]  
From the differentiation chain rule, one has  
\[\frac{\partial^{4}w}{\partial x^{4}}=\frac{d^{4}w}{dy^{4}},\quad\frac{\partial w }{\partial t}=-v\frac{dw}{dy},\quad\frac{\partial^{2}w}{\partial t^{2}}=v^{2} \frac{d^{2}w}{dy^{2}}. \tag{4}\]  
Then Equation (1) can be converted into  
\[\frac{\mathrm{d}^{4}w}{\mathrm{d}y^{4}}+\beta_{1}\frac{\mathrm{d}^{2}w}{ \mathrm{d}y^{2}}+\beta_{2}\frac{\mathrm{d}w}{\mathrm{d}y}+\beta_{3}w=\beta_{4} \delta(y), \tag{5}\]  
where  
\[\beta_{1}=\frac{\rho Av^{2}}{EI},\quad\beta_{2}=-\frac{cv}{EI},\quad\beta_{3}= \frac{k}{EI},\quad\beta_{4}=\frac{P}{EI}.\]
## 3 Results and Discussion
### Effect of stabilizers on the Performance of AR  
The test results of asphalt rubber properties with three different stabilizers are shown in Figure 5. It can be seen that the physical properties of AR with different types of stabilizers changed significantly. In Figure 4(b), the softening point of A-2 and B-2 were 65.7 \({}^{\circ}\)C and 72.1 \({}^{\circ}\)C, respectively, which was significantly higher than that of the base AR. This indicated that AR with stabilizer 2# could provide higher stiffness to resist long-term traffic and environmental impact. In comparison, stabilizer 1# and 3# did not result in obvious increase in stiffness and achieved similar results to that of the base AR. In terms of penetration (Figure 4(a)) it could be concluded that the value of A-2 and B-2 were 44.5 and 34.2 dmm, respectively, which was significantly lower than that of the base AR (62.6 and 40.2 dmm).  
Figure 4: Effect of CR content on conventional tests result for 70# asphalt.  
The incorporation of stabilizer 2# resulted in an obvious improvement in penetration. Considering these test results, the stabilizer 2# and 3# could help asphalt rubber obtain better high-temperature property.  
Figure 5c-e shows the ductility of the two types of AR decreased slightly after the stabilizers were added. The 180 \({}^{\circ}\)C viscosity had an opposite trend with ductility, which increased significantly with stabilizers, in particular, stabilizer 2#. This indicated that all stabilizers could affect the low-temperature property. When the stabilizers were added in the AR, a stable phase interface adsorption layer was formed between the polymer phase in the AR and the virgin asphalt phase, the surface tension of the phase interface was lowered and the two phases were increased [35]. In terms of storage stability, the A type AR had much better stability than that of B. This indicated that B type could only be mixed and  
Figure 5: Effect of three stabilizers on the conventional test of AR of A and B.  
applied on site. On the contrary, all the softening point difference of A type AR with stabilizers were less than 1 \({}^{\circ}\)C, which was much smaller than the standard requirements. Judging from the results, A type AR could be stored. When the stabilizer was added in the AR, it swelled and promoted the expansion of the volume of the rubber powder particles, which improved the stability and the dynamic viscosity of the asphalt rubber.  
Based on these results, the stabilizer produced active radicals, which were cross-linked and grafted with polymer molecular chains such as rubber powder and asphalt functional groups under certain thermal conditions, which influenced the asphalt properties [36]. The stable colloidal system formed between the powder and the asphalt could improve the high-temperature property. It provides a wider range and long-distance transportation of usage for AR. The final choice of stabilizers depends on the construction areas and performance requirements.
## 4 Discussion
### Strengths, Limitations, and Future Directions  
These conclusions make miRNAs important as diagnostic markers, as well as prognostic and predictive biomarkers of response to therapy especially in the stage I-II CRC. Nevertheless, there are several issues that currently restrict their usage in clinical practice on a more widespread basis. The first challenge is the complex regulatory interactions of miRNAs: a single miRNA can control multiple target genes, even the single gene targeted in multiple miRNAs. This can lead to unpredictable and tricky situations in therapeutic applications, especially in the case of using miRNAs as therapeutics. However, the issue of maintaining miRNAs stable inside the body and creating acceptable ways to deliver them to target cells remains a technical challenge.  
From an economic point of view, the technologies that are necessary to perform miRNA profiling and to modify miRNA levels, including next-generation sequencing and synthesis of specific oligonucleotides, are still expensive and need appropriate facilities. At the practical level, extensive clinical correlation and establishment of protocols are required to incorporate miRNAs into clinical practice, which is going to be a time and cost-consuming process. Thus, there is a need for improvement of the methods to stabilize and deliver the miRNAs, the development of new cost-effective methods to detect miRNAs and, finally, the understanding of the complexity of the regulation of miRNAs.  
Nevertheless, this review has some limitations that cannot be eliminated. First, the review is dependent on diverse types of publications, which may lead to selection bias. Second, most of the studies in the Asian region might reduce the external validity of the findings. Third, some of the studies included few participants, and this increases the possibility of sample bias and randomization errors. Fourth, although miRNA-139-3p exhibited the best diagnostic accuracy for CRC, it appears from a single study. Therefore, the performance may vary across populations due to genetic variability.  
In order to address these limitations, the authors have also used regression analysis and tried to control for potential confounding factors. However, there is still a need to replicate these findings with a larger sample size and a more diverse sample to generalize these results. These findings will serve as a foundation for future studies with larger sample sizes and participants from various ethnic backgrounds to further validate and expand upon the current results.
# Estimating Position from Millisecond Samples of GPS Signals (the \"FastFix\" Algorithm)
## 3 The FastFix Positioning Algorithm
### Algorithm Outline  
The algorithm begins with an estimate of the local time \(t_{0}\), and, by acquiring the codephase, Doppler-shift and \(X_{max}/\sigma_{X}\) for each visible satellite from the previously stored GPS \(L_{1}\)-data. These measurements are then used for three successive least-squares estimations of position. Starting with a global minimization based on Doppler-shift measurement, the successive stages each further refine the position from the preceding stage. A flow-chart for the algorithm is shown in Figure 2. Each of the minimization stages requires knowledge to the satellite orbital elements, and it is assumed that these are downloaded separately from a suitable catalog.  
The sensitivity of the \(\Delta f^{i}\) to the solution is quite low, so, from an initial measurement of \(t_{0}\), an initial first pass is made searching for a position that minimizes \(L_{\
u}\) from Equation (7). This results in a rough position estimate \(\mathbf{r}_{1}\).  
This Doppler-estimate is refined by searching in the region near \(\mathbf{r}_{1}\) for a position \(\mathbf{r}_{2}\) that optimizes the relative fractional codephase estimator, \(L_{\delta\phi}\) at time \(t_{0}\).  
The final step is a full four-dimensional space-time optimisation using a Nelder-Meade [24] optimisation algorithm. This yields an estimate for the receiver position, \(\mathbf{r}_{3}\), as well as the local time \(t_{1}\)
# Application of Fly Ash as an Adsorbent for Removal of Air and Water Pollutants
## 4 Application of Fly Ash for Treatment of Pollutants
### Removing Air Pollutants
#### 4.1.3 Removal of Sulfur Dioxide  
Coal power generation plays an important role in electricity generation worldwide, accounting for about 41% of the world's power generation in 2006. In some countries, this percentage is even higher, such as Poland (92%), China (79%), and India (69%) [125; 126]. The large amount of coal used causes an increase in SO\({}_{2}\) and a small amount of SO\({}_{3}\), which pollute the air. SO\({}_{2}\) is the main chemical responsible for formation of acid rain [127; 128; 129]. In addition, SO\({}_{2}\) and SO\({}_{3}\) are harmful gases that contribute to formation of submicron acid particles that can penetrate human lungs and be absorbed into the bloodstream [130]. Many researchers have reported that blending FA with Ca(OH)\({}_{2}\) or CaO can produce an adsorbent via a hydration process with a better SO\({}_{2}\) reduction than that of hydrated lime [131; 132; 133]. [PERSON] et al. [134] found similar results, as shown in Figure 13. An adsorbent composed of a mixture of FA/CaO/CaSO\({}_{4}\) was successfully synthesized with a higher SO\({}_{2}\) adsorption capacity than that of pure FA, CaSO\({}_{4}\), and CaO, due to its larger specific surface area (64.5 m\({}^{2}\)/g). In addition, no adsorbents exhibited significant desulfurization activity. SEM images of adsorbent before and after SO\({}_{2}\) adsorption are shown in Figure 14. The high density of pore structures on the surface of the adsorbent before adsorbing SO\({}_{2}\) can be clearly seen. However, the pores disappear after adsorption of SO\({}_{2}\), due to SO\({}_{2}\) being converted into sulfate salts (CaSO\({}_{4}\)) and covering the surface of the adsorbent.  
Figure 12: Relationship between BET surface area of adsorbent and adsorbed NOx (reproduced with permission from [123], Elsevier, 2018).  
From the above results, it can be concluded that the ability of FA to capture SO2 is mainly related to its surface area, pore structures and calcium ion content. Specific surface area is increased after the FA is hydrated, leading to more calcium ions that can react with SO2 to produce CaSO4 [135; 136].
## 4 Performance evaluation
### Data Analysis
\begin{table}
\begin{tabular}{c c c c c} \hline
**EUI-64** & **Received** & **RSSI** & **CCA** & **PDR** \\
**(2 bytes)** & **Packets** & **(dBm)** & **(dBm)** & **(\%)** \\ \hline
56–53 & 924574 & \(-84.0\) & \(-112.4\) & 72.1 \\ \hline
55–AD & 1024664 & \(-83.7\) & \(-115.5\) & 79.9 \\ \hline
55–E4 & 872200 & \(-82.1\) & \(-111.2\) & 68.0 \\ \hline
55–99 & 897718 & \(-96.2\) & \(-117.5\) & 70.0 \\ \hline
55–DD & 1091950 & \(-92.5\) & \(-117.3\) & 85.1 \\ \hline
55–65 & 1058746 & \(-85.3\) & \(-118.3\) & 82.5 \\ \hline
56–0B & 871477 & \(-91.3\) & \(-118.4\) & 67.9 \\ \hline
56–32 & 1121696 & \(-96.1\) & \(-119.9\) & 87.4 \\ \hline
55–B3 & 1076572 & \(-95.0\) & \(-119.3\) & 83.9 \\ \hline
55–63 & 926221 & \(-101.7\) & \(-118.1\) & 72.2 \\ \hline
63–0A & 845050 & \(-101.6\) & \(-119.0\) & 65.9 \\ \hline
**Mean** & 10710868 & \(-91.8\) & \(-117.0\) & 75.9 \\ \hline \end{tabular}
\end{table} 
Table 3: Node identifier (EUI-64), received packets, RSSI, CCA, and PDR. Table 5 shows the per-node reception probability for each independent transmission attempt (i.e., \(\text{P}_{1}\), \(\text{P}_{2}\), \(\text{P}_{3}\)) using each modulation (i.e., SUN-FSK, SUN-OQPSK, and SUN-OFDM). From the data, it is clear that there is no strong relationship between the modulation, the distance, and the transmission attempt, except for the fact that SUN-OFDM presents the lowest mean and the highest standard deviation of all modulations. As detailed earlier, this can be explained by the fact that the SUN-OFDM transmission power is 6 dBm lower than SUN-FSK and SUN-OQPSK. As an example, we pick nodes of the medium group (i.e., distance from the gateway equal to 115 m). Within that group, we observe that node 56-OB presents a high variability for SUN-OFDM transmissions, where the PDR ranges from 64.5% in the first transmission attempt to 35.9% in the third transmission attempt. On the contrary, the PDR for node 55-65 ranges from 63.1% in the first transmission attempt to 85.7% in the third transmission attempt. Hence, despite transmission attempts having a large degree of correlation for a given node and modulation given the short time interval between them, variations over 30 percentage points on average can still occur due to the effects of multi-path propagation. Figure 8 shows the daily average RSSI values for each modulation and node. The shadowed region for each modulation represents the maximum and minimum values observed for each given
# Removal of Contaminants in Water with Scallop Shell Waste
## 2 Materials and Methods
### Arsenic(III) Removal Tests  
To remove arsenic(III), the same system used to determine caffeic acid removal was used. Into this system was added 300 mL of a 1.6 ppm arsenic(III) solution. Subsequently, 500 ppm of scallop shell waste with different diameter ranges of BS, MS, and SS (see Table 1) were added. Samples of 30 mL were taken every 10 min until 60 min were complete. All samples were centrifuged for 15 min at 4500 rpm to remove scallop shell waste.  
The removal percentage of arsenic(III) was determined using a colorimetric method using a UV-visible Evolution 220 Thermo Scientific. The colorimetric method uses a 30 mL sample aliquoted into a 125 mL frosted Erlenmeyer. After, 70 mL of deionized water was added. A total of 20 mL of concentrated sulfuric acid was added to the same flask and cooled in a water bath to room temperature. At the same time, 0.0100 g of silver diethylditiocarbamate (DDCT Ag) was weighed in a beaker and dissolved with 5 mL of pyridine; this solution was placed in an arsenic(III) absorption tube, 16 g of granular zinc was added to the frosted Erlenmeyer and connected to the absorption tube, ensuring proper sealing with a clamp (see Figure 2).  
The system was left under moderate agitation for two hours. Finally, the absorbance of the solution contained was determined in the range of 450 and 650 nm, setting 523 nm as the wavelength to calculate the arsenic(III) removal percentage by this technique. Tests with each diameter of scallop shell waste (BS, MS and SS) were performed three times.
# Application of Gas Foil Bearings in China
## 4 Conclusions  
The development of applications for gas foil bearings in China was summarized in this paper. Related challenges during the development process were discussed, including analyses of static and dynamic characterizations, thermal characterization, and lubricating coatings. Based on the above review and discussion, the following conclusions could be drawn:  
(1) Gas foil bearing technology developed rapidly in China because of application prospects in high-speed turbo machinery. The diversity of gas foil bearing applications also put forward higher requirements on bearing design. Currently, the design criteria of gas foil bearings need to be configured for different application considerations, especially for high-performance gas foil journal and thrust bearings.  
(2) Advances in foil coating technology could greatly improve the reliability and service life of turbo machinery. Research on solid lubricating coating of gas foil bearings was closely related to solid lubricating technology and coating technology. Limited by the temperature range of coating materials, friction pair selection and feasibility of manufacturing and processing, further foil coating technology research is thus needed for bearing applications.  
(3) One of the major failure modes for gas foil bearing was due to thermal instability. Research is needed to develop suitable predictive tools to address this problem at the design stage. A detailed non-linear thermo-elastohydrodynamic analysis is needed, considering thermal, hydrodynamic, and structural deformation. In the design and application process, different measures should be adopted to reduce heat accumulation and bearing failure during bearing operation.  
**Funding:** This project was funded by the National Key R&D Program of China (2018 YFB2000100), the Na-tional Natural Science Foundation of China (51976150) and the Youth Innovation Team of Shaanxi Universities.  
**Institutional Review Board Statement:** This paper does not involve humans or animals.  
**Informed Consent Statement:** This paper does not involve humans or animals.  
**Data Availability Statement:** The study did not report any data.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# Statistical Power Analysis in Reliability Demonstration Testing: The Probability of Test Success
## 3 Calculation of the Probability of Test Success
### Calculation by Test Simulation  
To ensure proper reflection of the large possible number of correlations and effects in a test that is actually carried out and evaluated following test planning, it is possible to use those methods for test evaluation and calculation of confidence bounds which are used in the actual test. For this purpose, the hypothesis-testing concepts can be left aside in favor of the MCS approach of [PERSON] et al. [45; 46; 61], which relies solely on the law of large numbers. The procedure is as follows: draw pseudo-random failure times to generate samples according to the sample behavior of the test and prior knowledge; estimate the failure distribution and confidence level using this sample along with the methods which are actually used later on; and check whether the requirement is met. By iterating multiple times, \(P_{\text{ts}}\) can be calculated via [46]  
\[P_{\text{ts}}=\frac{\text{Number of successful simulated tests}}{\text{Total number of simulated tests}}. \tag{42}\]  
The idea is to use the methods of test evaluation which are used on the actual test later on. No constructs or alterations for a hypothesis-testing approach are needed. The very popular Fisher and likelihood ratio confidence bounds [8; 10] can be used here. However, there may be drawbacks in terms of accuracy due to a high number of MCS iterations and possible estimation bias amplification.
## 3 Accelerated Corrosion Test of Steel Bars in Different Corrosion Degree
### Detection of Electrochemical Corrosion Potential of Different Corroded Steel Bars  
The potential of steel reinforcement with different thicknesses of the protective layer (4 cm, 6 cm, 7 cm, and 9 cm) was detected at different durations of accelerated corrosion (0-408 h):  
Corrosion potential analysis for 4 cm protective layer  
Based on the reference standard of ASTM C876 for the corrosion potential of steel bars, we obtained the critical levels of the corrosion potential of the 4 cm protective layer for slight, moderate, and serious corrosion at the accelerated durations of 192 h and 312 h, as shown in Figure 17. The slight corrosion of the reflected voltage of the electromagnetic wave means that the reflected voltage of the ground penetrating radar in its early stage changed significantly at 72 h, which was 120 h earlier than the corrosion potential. The results demonstrated that the reflected voltage of the ground penetrating radar can detect the corrosion of steel bars more precisely. When the corrosion product (iron oxide) is generated, the reflected voltage of the ground penetrating radar can detect the corrosion more precisely than the corrosion potential.  
Figure 16: Reflected Voltage of 9 cm Protective Layer.
## 5 Tests and Results Analysis  
### Dataset  
To evaluate the performance of the improved network and the proposed method, the dataset used in this paper was from surveillance videos in some areas of Zhenjiang, Jiangsu province, China. In the Figure 4, these video datasets contain real image data from urban, rural and highway scenes, with up to 30 cars per image and varying degrees of occlusion. In this paper, the experimental dataset consisted mainly of 30,000 images from the video, of which 24,000 images are the training and verification dataset, and 6000 images are the testing dataset. Each test image is labeled by LabelImg All vehicle categories were cars, buses and trucks. The monitoring period included 24 h a day, sunny days, cloudy days and rainy days, etc., which are representative to some extent.