esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract
For the correct assessment of human exposure, it is necessary to assess water quality, including the content of heavy metals and the presence of radionuclides [33]. Long-lived isotopes that can pose a threat to human health and life are particularly important. They also have an impact on the effective dose that a person receives as a result of their consumption with water [34; 35]. Each country has legal regulations regarding radiological requirements that water should meet. In Poland, this is included in the Regulation of the Minister of Health of 7 December 2017 [9] on the quality of water intended for human consumption. The requirements stipulate that the permissible concentration of tritium in drinking water must not exceed 100 Bq/L, and the total permissible dose is 0.1 mSv/a [8]. It should be mentioned that if the total \(\alpha\) radioactivity is not higher than 0.1 Bq/L and the total \(\beta\) radioactivity is not higher than 1 Bq/L, the dose limit is not exceeded [36; 37]. In the United States, the applicable legal regulations stipulate that the total concentration of \({}^{228}\)Ra and \({}^{226}\)Ra should be measured, and the total level of contamination must not exceed 185 MBq/L [38]. In Turkey and Hungary, according to the regulations in force, there are limit values for alpha and beta radiation, respectively: 0.1 Bq/L and 1 Bq/L [39; 40]. In Australia, the total effective dose of radionuclides (without \({}^{40}\)K potassium) in drinking water should not be greater than 1 mSv/a [41; 42]. Artificial radionuclides are found mainly in surface waters. Their occurrence is related to the operation of nuclear facilities including nuclear power plants, the processing of spent nuclear fuel, and the production of radiopharmaceutical. Drinking water is drawn from deep underground aquifers that are not exposed to contamination from anthropogenic radioactive elements. Natural radionuclides, found in the Earth's crust and thus also in deep-sea drinking waters, can be present in high concentrations and make a significant contribution to the total dose for consumers [43; 44]. In particular, long-life elements \({}^{40}\)K, \({}^{210}\)Pb, \({}^{226}\)Ra, \({}^{232}\)Th, and \({}^{238}\)U are important. For example, radioactive radon \({}^{226}\)Ra decays into alpha radioactive radon \({}^{222}\)Rn. It causes exposure of the lung epithelium to neoplastic changes [45; 46]. Knowledge of the distribution pathways for both metals and radionuclides is essential to maintain control of prevailing levels of contamination, radiation, and radioactive contamination. The aim of this study was to evaluate the contamination of mineral waters due to the content of trace metals and natural (\({}^{40}\)K--energy 1460 keV, \({}^{226}\)Ra--186 keV, \({}^{232}\)Th--63.8 keV) and artificial (\({}^{137}\)Cs--662 keV) levels of radioactivity in water samples available on the Polish market.
# Ultra-Low-Loss Silicon Waveguides for Heterogeneously Integrated Silicon/III-V Photonics
## 4 Photonic Integrated Circuits with Ultralow Loss Silicon Waveguides  
The ability to integrate ultralow loss waveguides inside the laser cavity or form fully integrated delay lines with active devices promises vastly superior performance at much-reduced footprint compared to e.g., fiber-based delays. Furthermore, full integration improves the robustness of devices and reduces cost of packaging. The key for integration is a low loss taper to transition from ULL waveguides to a waveguide geometry with smaller bend radius, which we describe in detail in following section. This allows us to expand the versatility of the heterogeneous silicon platform. Finally, we give two applications that benefit greatly from having ULL waveguides: narrow linewidth lasers and interferometric optical gyroscopes.
# Caching Placement Optimization Strategy Based on Comprehensive Utility in Edge Computing
###### Abstract  
With the convergence of the Internet of Things, 5G, and artificial intelligence, limited network bandwidth and bursts of incoming service requests seem to be the most important factors affecting user experience. Therefore, caching technology was introduced. In this paper, a caching placement optimization strategy based on comprehensive utility (CPOSCU) in edge computing is proposed. Firstly, the strategy involves quantifying the placement factors of data blocks, which include the popularity of data blocks, the remaining validity ratio of data blocks, and the substitution rate of servers. By analyzing the characteristics of cache objects and servers, these placement factors are modeled to determine the cache value of data blocks. Then, the optimization problem for cache placement is quantified comprehensively based on the cache value of data blocks, data block retrieval costs, data block placement costs, and replacement costs. Finally, to break out of the partial optimal solution for cache placement, a penalty strategy is introduced, and an improved tabu search algorithm is used to find the best edge server placement for cached objects. Experimental results demonstrate that the proposed caching strategy enhances the cache service rate, reduces user request latency and system overhead, and enhances the user experience.  
edge computing; caching placement; comprehensive utility; tabu search algorithm introduction +
Footnote †: journal: Applied sciences  
Article  
Caching Placement Optimization Strategy Based on Comprehensive Utility in Edge Computing
## 5 Discussion and Conclusions
### Comparison of System Prediction Results  
To classify the data sources of mainstream news and content farm outlets and compare the experimental results of the ANN system and the BERT system, the following phenomena are discovered:  
(1) The ANN and BERT systems show high similarity in their hit rates.  
In regard to the prediction of mainstream news source credibility, it is discovered that both the ANN system and the BERT system present the best hit rate for Liberty Times and the worst hit rate for EToday. Similarly, both the ANN system and the BERT system show the worst hit rate for nooho.net in the prediction of content farm source credibility.  
(2) In comparison with the ANN system, the BERT system presents a higher and more stable source credibility recognition rate.  
The experimental results with ANN and BERT systems reveal that the ANN system appears to have the highest hit rate of 98.0% and the lowest hit rate of 65.5% across all data source predictions, with a system hit rate of 84.75%. The BERT system, on the other hand, presents the highest hit rate of 100% and the lowest hit rate of 79.0% across all data source predictions, with the system hit rate of 91.13%.  
Further data analysis shows that the BERT system, in comparison to the ANN system, appears to have a higher hit rate across all data sources, and the hit rate of various platforms is relatively stable. This may be because the ANN system has a different data-processing mechanism than the BERT system; the ANN system is based on word frequency, while the BERT system is based on semantics, which could more easily learn the common composition among characters. In this case, the BERT system could maintain a higher source credibility recognition rate with relatively stable standards in the prediction process.  
Summarizing the above data, it could be reasonably inferred that the semantics-based BERT system outperforms the word frequency-based ANN system on the effectiveness of source credibility prediction of mainstream news or content farms. Nevertheless, the existence of the news source credibility recognition system, either the ANN or BERT system, is an information alert for people. Using artificial intelligence to recognize news source credibility could effectively enhance people's sensitivity to news sources, as well as cultivate people's media literacy in the long term to resist fake news using technology.  
Conceptualization, T.H.C.C. and W.-C.W.; methodology, T.H.C.C. and C.-S.L.; software, T.H.C.C. and C.-S.L.; validation, T.H.C.C., W.-C.W., and C.-S.L.; writing, T.H.C.C. All authors have read and agreed to the published version of the manuscript.  
This work is supported by the Ministry of Science and Technology, under grants NSC 111-2634-F-003-002-, and by the National Taiwan Normal University (NTNU) within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan.  
Not applicable.  
Written informed consent has been obtained from the patients to publish this paper.  
Not applicable.  
The authors declare no conflict of interest.
# Seismic Response Mitigation of Base-Isolated Buildings
## 4 Mathematical Model of the TMD  
Figure 2b shows schematic illustration of a TMD, which is made up of a mass attached to the floor by a spring and a dashpot. The \(i\)th TMD is illustrated by its stiffness (\(k_{i}\)), damping constant (\(c_{i}\)), and the mass (\(m_{i}\)). The TMD's mass ratio \(\mu\), designed frequency \(\omega_{i}\), tuning frequency ratio \(f\), and damping ratio \(\xi_{i}\), are given by  
\[\omega_{i}=\sqrt{\frac{k_{i}}{m_{i}}} \tag{9}\]  
\[\xi_{i}=\frac{c_{i}}{2\,\omega_{i}m_{i}} \tag{10}\]  
\[f_{i}=\frac{\omega_{i}}{\omega_{b}} \tag{11}\]  
\[\mu_{i}=\frac{m_{i}}{m_{s}} \tag{12}\]  
where \(m_{s}\) represents total mass of the BI building. The proposed formulas by [PERSON] et al. [39] for optimum tuning frequency ratio \(f_{STMD}=\frac{1}{1+\mu_{STMD}}\left[1-\xi_{b}\sqrt{\frac{\mu_{STMD}}{1+\mu_{ STMD}}}\,\right]\) and damping ratio \(\xi_{STMD}=\frac{\xi_{b}}{1+\mu_{STMD}}+\sqrt{\frac{\mu_{STMD}}{1+\mu_{STMD}}}\) are considered for STMD.  
Figure 1c-d show the main system equipped with \(n\) number of TMDs (MTMDs) with various dynamic characteristics. The BI system and each TMD is modeled with a single DOF. In this study, MTMDs and d-MTMDs are designed by considering unequal masses. The designed frequency of \(i\)th TMD is stated as  
\[\omega_{i}=\omega_{T}\left[1+\left(i-\frac{n+1}{2}\right)\frac{\beta}{n-1}\right] \tag{13}\]  
where \(\omega_{T}\) is the average frequency of all the MTMDs (i.e., \(\omega_{T}=\sum\limits_{j=1}^{n}\omega_{j}/n\)). Based on the recommendation of [PERSON] and [PERSON] [25], the average frequency is taken as 0.78 times the fundamental frequency of the BI building. Non-dimensional frequency spacing parameter \(\beta\) of the MTMDs is defined as  
\[\beta=\frac{\omega_{n}-\omega_{1}}{\omega_{T}} \tag{14}\]  
For a set of TMD units with equal stiffness (i.e., \(k_{1}=k_{2}=k_{3}=\cdots=k_{n}\)) and equal damping ratio (i.e., \(\xi_{1}=\xi_{2}=\xi_{3}=\cdots=\xi_{n}\)), the stiffness (\(k_{j}\)) is calculated as  
\[k_{j}=\frac{m_{n}}{\left(1/\omega_{1}^{2}+1/\omega_{2}^{2}+\cdots+1/\omega_{n }^{2}\right)} \tag{15}\]  
Figure 2: Schematic diagrams for (**a**) N-Z and (**b**) tuned mass dampers (TMD).  
where \(m_{n}\) is the total mass of all the TMD(s), and the mass of the \(i\)th TMD (\(m_{i}\)) is given by  
\[m_{i}=\frac{k_{i}}{\omega_{i}^{2}} \tag{16}\]  
and the damping coefficient of the TMDs is then given by  
\[c_{i}=2\xi_{i}m_{i}\omega_{i} \tag{17}\]  
In this study, \(n=3\) is assumed for the cases of MTMDs and d-MTMDs; for MTMDs cases, all the TMDs are placed at the top floor, whereas for d-MTMDs, the TMDs are placed at the top three floors.
# Flow Dynamics of Sulfate-Modified Water/Polymer Flooding in Micromodels with Modified Wettability
## Materials and Methods
### Porous Media/Microfluidics
#### 2.4.1 Wettability Evaluation  
To investigate the effect of wettability, micromodels were chemically modified to generate three types, based on the presented structures, namely: water-wet, oil-wet and complex-wet/mixed-wet, as shown in Table 4. Complex/mixed wettability type deals with the local variation of wettability areas, some parts/zones were oil-wet, while others were water-wet.  
The wettability alteration is achieved by a chemisorption of a fluorinated silane, applied on the micromodels inner glass and silicon surfaces. Silicon and glass are initially water-wet, with a contact angle (water) below \(\sim\)20\({}^{\circ}\). After treatment, this angle is increased up to 112\({}^{\circ}\). The oil contact angle of the modified surface is significantly lower with 77\({}^{\circ}\). The mixed-wet micromodel is obtained by fragmentary, acid-induced abrasion of the coating. Wettability treatment with fluorinated silane is almost permanent. Only very strong acids and bases can attack the adsorbed layers. Silane does not decompose in the presence of crude oils, as proven by a stability test at 120 \({}^{\circ}\)C for 8 h.  
Figure 3: Micromodels used in this study. (**A**) artificial-structure (**B**) real-structure micromodel [40].  
\begin{table}
\begin{tabular}{c c c} \hline \multirow{2}{*}{**Parameter**} & \multicolumn{2}{c}{**Glass-Silicon-Glass (GSG) Micromodel**} \\ \cline{2-3}  & **Artificial** & **Real** \\ \hline Porosity (\%) & 27.60 & 19.20 \\ Brine Permeability (mD) & 13,000.00 & 1237.00 \\ Min. Pore diameter (\(\upmu\)m) & 8.00 & 12.21 \\ Max. Pore diameter (\(\upmu\)m) & 2610.00 & 112.52 \\ Avg. Pore diameter (\(\upmu\)m) & 178.20 & 31.50 \\ \hline \end{tabular}
\end{table}
Table 3: Porous Media characteristics of micromodels used in this work.
# A Review of Advanced CMOS RF Power Amplifier Architecture Trends for Low Power 5G Wireless Networks
## Advanced RF PA Architectures
### Outphasing RF PA (LINC PA)
Common power combiners (Wilkinson, hybrid) do not provide sufficient performance, therefore specific phase-compensated ones are required. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Ref.** & **Process** & **\(V_{\text{DD}}\), V** & **Frequency, GHz** & **P1 dB, dBm** & **Overall PAE, \%** & **PA Class** \\ \hline
[33] & 180 nm CMOS & 1.8 & 5.2 & 17.4 & 62 (peak) & AB \\
[34] & 130 nm CMOS & 3.5 & 1.95 & 28.5 & 29.6 & E \\
[35] & 65 nm CMOS & 1.25 & 1.4 & 20 & 58 & E \\
[36] & 45 nm CMOS & 2.4 & 2.4 & 31.6 & 43.7 & E \\
[37] & 40 nm CMOS & 1.2 & 5.9 & 22.2 & 16.1 & E \\
[38] & 32 nm CMOS & 2 & 2.4 & 25.3 & 35 & D \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Summary of reviewed outphasing PAs in CMOS process. Figure 4: Simplified outphasing PA architecture diagram.
# A Survey of Wireless Sensor Network Based Air Pollution Monitoring Systems
###### Abstract  
The air quality in urban areas is a major concern in modern cities due to significant impacts of air pollution on public health, global environment, and worldwide economy. Recent studies reveal the importance of micro-level pollution information, including human personal exposure and acute exposure to air pollutants. A real-time system with high spatio-temporal resolution is essential because of the limited data availability and non-scalability of conventional air pollution monitoring systems. Currently, researchers focus on the concept of The Next Generation Air Pollution Monitoring System (TNGAPMS) and have achieved significant breakthroughs by utilizing the advance sensing technologies, MicroElectroMechanical Systems (MEMS) and Wireless Sensor Network (WSN). However, there exist potential problems of these newly proposed systems, namely the lack of 3D data acquisition ability and the flexibility of the sensor network. In this paper, we classify the existing works into three categories as Static Sensor Network (SSN), Community Sensor Network (CSN) and Vehicle Sensor Network (VSN) based on the carriers of the sensors. Comprehensive reviews and comparisons among these three types of sensor networks were also performed. Last but not least, we discuss the limitations of the existing works and conclude the objectives that we want to achieve in future systems.  
air pollution monitoring; Wireless Sensor Network (WSN); real-time monitoring; high spatio-temporal resolution; low-cost ambient sensor 20151531392-31427; doi:10.3390/s151229859
# Chaotic Characteristic Analysis of Spillway Radial Gate Vibration under Discharge Excitation
## 2 Methodology
### Identification of Chaotic Characteristics  
#### 2.2.1 Correlation Dimension  
The saturation correlation dimension is a dimension extracted from chaotic attractors, which describes the degree of chaos of nonlinear dynamical systems represented by time series. For an m-dimensional space, its correlation function is defined as:  
\[C(r)=\underset{M\rightarrow\infty}{lim}\frac{2}{M(M-1)}\sum_{1\leq i\leq j \leq M}H(r-\ \left\|\mathbf{Y}_{i}-\mathbf{Y}_{j}\right\|) \tag{8}\]  
where \(C(r)\) is the correlation function; \(r\) is the vector point; \(M\) is the phase-point numbers, and \(\left\|\mathbf{Y}_{i}-\mathbf{Y}_{j}\right\|\) is the distance between two points, \(i\) and \(j\), in the phase space.  
When the time series has a chaotic attractor feature, for a positive value, \(r\), the relation between \(C(r)\) and \(r\) is expressed as:  
\[C(r)\propto\alpha r^{D_{2}} \tag{9}\]  
where \(\alpha\) is the constant and \(D_{2}\) represents the correlation dimension, which can be calculated by the slope of the \(lnC(r)\)-\(lnr\) curve:  
\[D_{2}=\underset{r\to 0}{lim}\frac{lnC(r)}{lnr} \tag{10}\]  
Due to the existence of noise in the measured data, the initial embedding dimensions were usually specified at low numbers and gradually increased. In each embedding dimension, the part of the \(\ln C(r)\)-\(lnr\) curve that presented a constant slope was employed for fitting using the least squares method. The slope of this part of the \(\ln C(r)\)-\(lnr\) curveincreased with the increase in the embedding dimension and eventually reached the saturation value, which was the correlation dimension.
# Underwater Image Mosaic Algorithm Based on Improved Image Registration
## 4 Conclusions  
The problems of image registration and image fusion are studied in this paper. Firstly, mixed method and sigma filtering are used to enhance the images with low contrast and low definition. Then, IIR is proposed for image registration based on USAC. Finally, the method of weighted smoothing is used for image fusion. We tested the IIR algorithm via the Oxford Buildings Dataset to verify the effectiveness. Then, the algorithm was applied in an underwater environment. Compared with ORB, FAST, SURF, and I-RANSAC algorithms, the quantitative analysis results show the IIR algorithm can reduce the number of feature points and that of consistent matching points, and improve the fast index and accurate index. Furthermore, the algorithm in this paper avoids the appearance of image seams in the image quality, thus improving the image fusion effect.  
All authors contributed substantially to this study. Individual contributions were conceptualization, F.G., and Z.Y.; methodology, Y.Z., J.Y., and Z.Y.; software, J.Y.; validation, F.G., Y.Z., and J.Y.; formal analysis, Y.Z.; investigation, Z.Y., and X.Y.; resources, Z.Y. and X.Y.; writing--original draft preparation, Y.Z.; writing--review and editing, F.G. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Open Foundation of Key Laboratory of Submarine Geosciences, MNR (Grant No. KLSG2002), and the Opening Research Fund of National Engineering Laboratory for Test and Experiment Technology of Marine Engineering Equipment (Grant No. 750 NEL-2021-02).  
Not applicable.  
The publicly archived datasets of the image mosaic data used in this paper, are derived from website: [[https://www.robots.ox.ac.uk/~vgg/data/oxbuildings/](https://www.robots.ox.ac.uk/~vgg/data/oxbuildings/)]([https://www.robots.ox.ac.uk/~vgg/data/oxbuildings/](https://www.robots.ox.ac.uk/~vgg/data/oxbuildings/)) (accessed on 21 June 2021).  
We would like to thank the anonymous reviewers for their helpful and constructive comments, which have improved the paper.  
The authors declare no conflict of interest.  
Figure 18: The fusion images for T4: (**a**) I-RANSAC; (**b**) IIR.
## 2 Vibration Response Analysis of Different Roadbed-Foundation Systems
### Upper-Hard, Lower-Soft System  
When constructing roads and seawalls on thick soft clay foundations, the resulting roadbed-foundation system can be considered as a two-layer upper-hard, lower-soft system. The dynamic response of this system under vibration loads will be significantly different from that of an upper-soft, lower-hard system. Figure 2(b) illustrates the schematic of an upper-hard, lower-soft system, and the relevant parameters are listed in Table 2.  
Considering a vibration load frequency \(f\) of 2.5 Hz, calculations indicate a wavelength \(\lambda\) of approximately 64.7 m. Figure 6 presents the variation in the displacement of a ground surface point with horizontal distance \(x\). Figure 7 shows the variation in the displacement amplitude of points at different cross-sections \(x\) with depth \(y\).  
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Soil Layer** & **Thickness \(H\) (m)** & \begin{tabular}{c} **Shear Wave** \\ **Velocity \(v_{\mathbf{s}}\)** \\ **(m/s)** \\ \end{tabular} & \begin{tabular}{c} **Mass Den-** \\ **sity \(\rho\) (kg/m\({}^{3}\))** \\ \end{tabular} & \
\begin{tabular}{c} **Poisson’s** \\ **Ratio \(\mu\)** \\ \end{tabular} &
\begin{tabular}{c} **Damping** \\ **Ratio \(\xi\)** \\ \end{tabular} \\ \hline Roadbed & 10 & 400 & 2300 & 0.24 & 0.02 \\ Soft clay layer & \(\infty\) & 100 & 1700 & 0.32 & 0.2 \\ \hline \end{tabular}
\end{table}
Table 2: Parameters for the upper-hard, lower-soft system.  
Figure 6: Variation of **(a)** vertical and **(b)** horizontal displacement of a ground surface point with horizontal distance \(x\) in the upper-hard, lower-soft system.  
As observed in Figure 6, the displacement of ground surface points in the upper-hard, lower-soft system exhibits rapid attenuation with increasing horizontal distance \(x\). Figure 7 demonstrates that within the 10-m-thick roadbed, the vertical displacement of points is relatively large and remains almost constant with depth, while the horizontal displacement is smaller and decays with depth. Due to the low strength of soft clay, it can be assumed that the entire 10-m-thick roadbed undergoes vertical vibration as a whole. In the soft clay layer beneath the roadbed, the overall displacement of points decays with depth. However, this decay is slower compared to that observed in the upper-soft, lower-hard system. The predominant vibration within the entire system is concentrated in the roadbed and the underlying soft clay layer near the vibration source.  
Therefore, in the upper-hard, lower-soft system, the kinetic energy generated by traffic vibration loads primarily propagates in the vertical direction, transferring energy to the soft clay layer beneath the roadbed, with minimal propagation outward in the horizontal direction. This behavior contrasts with that of the upper-soft, lower-hard system.