esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Experiments
### Experiment Setting  
In this study, we utilized the QWS dataset, consisting of 2507 real services, each with 9 QoS attributes. However, this dataset lacked essential cost attributes and energy consumption data required for our research objectives. To overcome this limitation, we augmented the dataset with additional data from multiple sources, ensuring it met our study's needs. Considering the multi-cloud context of our research, we extended the dataset to include up to 20 clouds, with each service assigned a 10% probability of belonging to a specific cloud. We designed multiple experimental scenarios based on prior research [25; 39; 43], including various subtask numbers (20, 40, 60, 80), and candidate cloud service numbers (100, 200, 300, 400, 500, 600). Our experiments were conducted based on the requirements of validating different indicators. To assess SkyDRL's effectiveness in addressing cloud service composition problems in a multi-cloud environment, we compared it against other methods, including PD-DQN [43], Q-learning with skyline [39], SFGA [23], and MAACS [25], all of which were machine learning-based methods and heuristic algorithms. All experiments were conducted under the same dataset, and we set the recommended parameters for these methods based on the prior research, ensuring a fair comparison. For the SkyDRL method, we set the capacity of the buffer to 10,000 and extracted 32 samples each time. The number of Q-target network update steps is set to 500. We set the learning rate to 0.01; the initial value of \(\epsilon\) used in the \(\epsilon\)-greedy policy is 0.9, which reduces linearly to 0.1 during training. The discount factor \(\gamma\) is set to 0.9.
# Recent Advances in Internet of Things Solutions for Early Warning Systems: A Review
## 8 Recommendations and Future Work  
Table 9 lists some possible solutions and recommended options to satisfy the requirements that were previously defined for an IoT Early Warning System, based on the reviewed literature. It is to be noted that some of these suggestions still require careful planning before the final implementation, for example evaluating link budgets or received signal strength when using a specific communication solution, or measuring energy consumption. While the requirements for each use case (floods, earthquakes, tsunamis, landslides) are widely different, for example in terms of latency, the table shows how Edge solutions can be used to satisfy different needs and as such should be taken into consideration during the development of an Early Warning system based on the IoT, regardless of the specific application. Edge Computing might also consist in the deployment of AI at the edge of the architecture. When using ML, learning at the Cloud might not be the best solution for wide monitored sites, geographically dispersed locations or rapidly changing environmental conditions [95], and as such Edge AI could be integrated into the architecture, keeping in mind possible additional processing time depending on the complexity of the ML model and the resources of the Edge devices. Besides ML, simpler algorithms or threshold based methods can also be employed on-site if the devices are limited in terms of computational capabilities. In conclusion, Cloud Computing should not be completely replaced by Edge Computing, but they should work in tandem to provide a better overall system. Moreover, we give the following recommendations for future work and research, also taking into account some of the gaps or trends that were found in the reviewed literature:  
* Optimization of MEMS sensors and widening of their employment. Since cost is an important factor in EW and IoT systems, they provide a valuable help in reducing costs while allowing to obtain dense sensor networks and the related benefits. MEMS sensors do not provide the same accuracy as other \"standard\" sensors, but they can still be used effectively in EW, and further research on sensors design and sensor signal conditioning can help improve their performance.
# Characterization of Narrowband Noise and Channel Capacity for Powerline Communication in France
## 3 Main Experimental Results and Discussion
### Estimation of the Channel Capacity  
The capacity of a channel is the maximum theoretical bit rate that it can support. It is important to note that the bit rate on a noisy channel is limited. Its limit both depends on the bandwidth of the transmission channel and its SNR [38; 39; 40]. The spectral capacity per dimension of the sub channel is given by (5):  
\[C=\Delta f\cdot\sum_{i=1}^{N}log_{2}(1+SNR_{i}) \tag{5}\]  
\(\bullet\)_SNR_: signal-to-noise ratio.  
\(\bullet\)_N_: number of carriers.  
\(\bullet\)_\(\Delta f\)_: frequency band of one carrier.  
The next sections of the manuscript describe the estimation of the channel capacity for two specific bands: the CENELEC A and the FCC bands.
## Using MCS in Industry 4.0 Scenarios
### MCS Architecture for Industry 4.0  
Based on the considerations of the previous sections, in order for MCS to be enabled in Industry 4.0 applications, there are some components that need to be included in traditional industrial communication systems [52; 53; 54; 12; 55]. Figure 4 shows an explanatory MCS-enabled Industry 4.0 architecture. The main components are explained in the following:  
* **MCS-enabled end device:** it is a mobile device that is provided with communication interfaces and enough computation capabilities to run the services that enable MCS in them. In particular, specific interfaces to communicate with the components residing in the cloud are needed. Furthermore, context-aware functionalities need to be implemented, so that data are collected depending on whenever the context (e.g., position, time) is relevant.
* **MCS-enabled gateway:** since not all the end devices can be MCS-enabled, the MCS-enabled gateway needs to provide the MCS functionalities to common nodes that do not have them. Hence, this gateway provides interfaces so that common nodes can communicate with the MCS components in the cloud, and augment data coming from these nodes with context-aware information.
* **Semantic information manager:** it is responsible for the management of the semantic data model thanks to which a common semantic description language is used to provide context-awareness to network nodes.
* **Big data analysis manager:** it receives the data collected by MCS-enabled nodes and gateways and analyses them in order to provide relevant information for the application that needs to be performed by the system.
* **Security manager:** provides security and privacy functionalities so that system nodes can communicate without any threat, and personal information is kept safe from malicious attacks.  
Figure 3: The advantages of using mobile crowdsensing and mobile crowdsourcing in Industry 4.0.
# The Role of PET and SPECT Imaging in Prostate Cancer Targeted Alpha Therapy: When and How?
## 3 Targeted Alpha Therapy
### Physical Characteristics of Alpha Particles and Advantages  
The use of alpha particle emitters can help to explain why targeted alpha treatment (TaT) is successful. Such particles have a much higher LET than \(\beta\) particle emitters (50-230 keV/\(\upmu\)m vs. 0.1-1.0 keV/\(\upmu\)m) with an average energy deposition of 100 keV/\(\upmu\)m. The range of \(\alpha\) particles in tissues is short, which limits radiation deposition to the target cell and closely neighboring cells [32]. Cellular DNA is the main molecular target of high-LET particles because of the effective production of double-stranded DNA breaks. As a result, TaT can target tumor cells and the tumor microenvironment with high targeted radiation doses while causing the least amount of harm to normal cells. Alpha-emitting particles are preferred over beta particle emitters and external beam radiation for the treatment of malignancies due to all of these advantages. Due to the fact that stable radionuclide sequestration in vivo is an essential part of targeted radiotherapy, the increased interest in TaT has resulted in the development of new chelating agents. Many radionuclides are known which emit one or more \(\alpha\) particles during the decay into stable nuclides. Only a small number of them, nevertheless, have been utilized in research projects that examined the effectiveness of targeted radionuclide treatment [33].
## 7 Conclusions  
To deal with the variant time delay caused by the dynamics of control plant in RTHS, a KF-based discrete-time adaptive delay compensation (KF-ADC) method was proposed. Numerical simulations on the Benchmark problem in RTHS were performed to examine the performance of the proposed method. The main conclusions are as follows.  
1. The principle of the proposed delay compensation method for RTHS was provided. The control plant is represented by a discrete model with time-varying coefficients, which are estimated and updated by KF using the displacement commands and measurements. Based on this model, the compensator is constructed by employing the desired displacements to deal with the variant time delay.
2. The performance of the KF used for parameter estimation in RTHS was investigated. By employing the Lyapunov stability theory, it was confirmed that the KF can converge to the true value. Simulations revealed that the KF converged rapidly. When the initial settings of the KF, namely \(R\), \(\mathbf{x}_{0}\), and \(\mathbf{P}_{0}\), varied with 30% of the nominal value, the relative errors of the converged values of the system parameters were less than 1%. It means errors in the initial settings of the KF had a limited effect on the convergent value, and the KF was robust to initial settings.
3. The effectiveness of the proposed method was validated through the Benchmark problem in RTHS. The results of 252 vRTHSs revealed a satisfactory tracking performance and robustness of the proposed strategy. Specifically, the maximum value of mean of the estimated time delay was less than 0.5 ms, the maximum value of tracking errors (\(J_{2}\) and \(J_{3}\)) was less than 2%, and the global errors (\(J_{4}\), \(J_{5}\), and \(J_{6}\)) and relative peak errors (\(J_{7}\), \(J_{8}\), and \(J_{9}\)) were less than 5%. Moreover, the proposed method was compared with the other four promising schemes. Results revealed that adaptive delay compensations were better than the constant delay-based compensation strategy. The proposed method was competitive compared with the adaptive model reference controller. In general, the proposed method exhibited a superior performance.  
Despite the performance of the proposed strategy can be well illustrated by the virtual RTHSs, where the measurement noise, uncertainties of loading system and specimen, real earthquake records and multiple degrees-of-freedom structures are considered, physical tests are also needed to further validate the actual performance. These actual tests are already planned.  
**Author Contributions:** Conceptualization, X.N. and Z.W.; methodology, X.N. and B.W.; validation and formal analysis, X.N. and Z.W.; writing--original draft, X.N.; writing--review and editing, Z.W.; project administration, Z.W. and B.W. All authors have read and agreed to the published version of the manuscript.  
**Funding:** The National Key Research and Development Program of China (Grant No. 2016 YFC0701106) and the National Natural Science Foundation of China (Grant Nos. 51908231, 52078398 and 51878525).  
**Conflicts of Interest:** The authors declare no conflict of interest.
## Theory
### Sound Power Contributed by Structural Modes  
For the abovementioned cylindrical shell, a normal excitation force of 1N is applied at a point in the middle of the cylindrical shell. In the whole frequency band, the excitation force does not change.  
The vibration displacement distribution on the surface and the radiated sound power of the cylindrical shell were calculated by using FEM software. According to the orthogonal decomposition method mentioned in Section 2.2.1, the participant coefficient of each mode can be acquired by decomposing the vibration displacement on the surface. A detail that should be pointed out is that these modal participant coefficients are frequency-dependent. Then, according to Equation (6), the radiated sound power under the circumstance where the participant coefficient is \(W_{nm}\) can be easily obtained from that under the circumstance where the participant coefficient is 1, as calculated by FEM. The results are compared with the total radiated sound power of the cylindrical shell, as shown in Figure 4.  
Figure 4: Radiated sound power curves of different order modes.  
Figure 3: Modal sound radiation efficiency curves of different order modes.  
As can be seen from Figure 4, the radiated sound power contributed by mode (3,1), mode (2,1), mode (0,1) and mode (1,1) are nearly equal to the total radiated sound power of the cylindrical shell in the corresponding frequency bands. These modes can be called DRSMs. For example, mode (0,1) is the DRSM in the frequency band below 100 Hz, mode (3,1) is the DRSM in the frequency band near the sound radiation peak at about 250 Hz, mode (2,1) is the DRSM in the frequency band near the sound radiation peak at about 310 Hz and mode (1,1) is the DRSM in the frequency band near the sound radiation peak at about 540 Hz. Moreover, this mode has a very high sound radiation contribution in the entire low frequency band, so it should be calculated over the entire band. Figure 4 also shows that the contribution of other modes to the total radiated sound power is much smaller, such as mode (4,1) and mode (5,1). Significantly, the sound radiation efficiency of these DRSMs is also very high, as shown in Figure 3, thus providing a method to preliminarily determine the DRSMs, because the high-efficiency modes are more likely to become the DRSM.  
A comparison among the radiated sound power of each mode with the total radiated sound power of the cylindrical shell indicates that the sound power of several DRSMs is the main component of the total sound power at low frequencies. This characteristic prompts a new direction of sound radiation prediction. That is, as long as the radiated sound power of these DRSMs can be predicted, the total radiated sound power can be easily derived from them--this approach is the sound radiation prediction method based on the DRSMs proposed in this paper. The key to the prediction is to identify the DRSMs and obtain their participant coefficients.
# Precise Positioning of BDS, BDS/GPS: Implications for Tsunami Early Warning in South China Sea
###### Abstract  
Global Positioning System (GPS) has been proved to be a powerful tool for measuring co-seismic ground displacements with an application to seismic source inversion. Whereas most of the tsunamis are triggered by large earthquakes, GPS can contribute to the tsunami early warning system (TEWS) by helping to obtain tsunami source parameters in near real-time. Toward the end of 2012, the second phase of the BeiDou Navigation Satellite System (BDS) constellation was accomplished, and BDS has been providing regional positioning service since then. Numerical results indicate that precision of BDS nowadays is equivalent to that of the GPS. Compared with a single Global Satellite Navigation System (GNSS), combined BDS/GPS real-time processing can improve accuracy and especially reliability of retrieved co-seismic displacements. In the present study, we investigate the potential of BDS to serve for the early warning system of tsunamis in the South China Sea region. To facilitate early warnings of tsunamis and forecasting capabilities in this region, we propose to distribute an array of BDS-stations along the Luzon Island (Philippines). By simulating an earthquake with Mw = 8 at the Manila trench as an example, we demonstrate that such an array will be able to detect earthquake parameters in real time with a high degree of accuracy and, hence, contribute to the fast and reliable tsunami early warning system in this region.  
BDS; BDS/GPS; South China Sea; tsunami early warning system Article
## 3 Results and Discussions
### Correlation Analysis  
Table 5 summarises the number of calculated and selected features at each stage.  
Correlation analysis shortlisted similar features, even though they were provided with a different number of features (Filtered, PCA on full, and PCA on filtered features). The selected features are tabulated and described in Table 6 and detailed in [58].  
It can be noted that all three ([PERSON], [PERSON], and Spearman) correlation analysis methods resulted in shortlisting the number of peaks within the time series, specifically for respiratory rate, as the most well-distinguishable feature for accurate stress monitoring. This finding is perfectly correlated with the previously published literature [6; 22; 35] and is true, as the breathing pattern is supposed to significantly vary during stress conditions when compared to baseline/normal conditions.  
As most of the shortlisted features belong to the respiratory rate signal, this study also performed a univariable time-series correlation analysis on the heart rate signal (only feeding the heart rate signal along with labels to the algorithm) to determine the most specific heart rate-related features. The [PERSON], [PERSON], and [PERSON] correlation analysis method determined that the 'number_cwt_peaks_n_5' feature (number of peaks that are at enough of a width scale (here, five) and have high signal-to-noise ratio) is the most specific feature of heart rate signal to distinguish stress from the baseline readings.
# Erosion Resistance Properties of Iron-Carbon Composite Plating to Molten Lead-Free Solder
## 4 Conclusions  
In this study, the solderability and the erosion resistance of the Fe-carbon filler composite plating layers to SAC305 solder were investigated. Fe-graphite and Fe-MWCNT composite plating layers were fabricated and investigated. The obtained results were compared to those of the Fe plating layer. Based on the experimental results, the following conclusions are drawn.  
1. Graphite and MWCNT were compounded not only on the Fe plating surface but also inside the plating film. Fibrous graphite can be uniformly dispersed in the Fe plating layer. MWCNTs are grouped together in small patches in the Fe plating layer.
2. Although the solderability of molten SAC305 decreased in the Fe-graphite and the Fe-MWCNT composite plating layers, the spread rates of SAC305 were more than 50%, which is a practical level. Therefore, they can be applied to the solder iron tip, the point soldering nozzle and so on.
3. From the results of the erosion-resistance test, it was shown that the Fe-graphite and the Fe-MWCNT composite plating layers have the effect of reducing erosion in molten SAC305 compared to the Fe plating layer.
4. EBSD analysis results revealed that a small amount of Fe\({}_{3}\)C compounds form in grain boundaries of \(\alpha\)-Fe in both Fe-graphite and Fe-MWCNT plating layers. Since Fe\({}_{3}\)C particles suppress the diffusion of Fe into SAC305 solder, erosion-resistance characteristics can be further improved by forming Fe\({}_{3}\)C in the plating film efficiently.
5. By using not only a solder iron tip but also soldering bath made of Fe-MWCNT composite plating, it is expected that erosion can be suppressed, and it can be used for a longer time.  
Figure 10: Electron back scatter diffraction pattern (EBSD) analysis results for composite plating layers after heating at 623 K for 7 h. (**a**) Fe–graphite; (**b**) Fe–MWCNT. The \(\alpha\)-Fe phase is indicated in red and the Fe\({}_{3}\)C phase is indicated in green.  
**Author Contributions:** [PERSON], [PERSON] and [PERSON] conceived and designed the experiments; [PERSON] performed the experiments; [PERSON], [PERSON] and [PERSON] project administration; [PERSON] supervision; [PERSON] and [PERSON] wrote the paper; The authors have all read and approved the submitted version of the manuscript.  
**Funding:** This research received no external funding.  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 2 Related Work and Problem Description
### Low Earth Orbit Satellite Routing and Optical Laser Interconnection
Compared to the former, laser inter-satellite links (LISLs) offer advantages, such as high transmission bandwidth, high channel throughput, strong anti-interference capabilities, high security, and confidentiality, making them an effective means for achieving high-speed satellite communication. In September 2020, Starlink first installed laser units on the 12 th batch of satellites at a 53\({}^{\circ}\) inclination, and, starting from 13 November 2021, subsequent launches of the V1.5 version satellites have all been equipped with laser units [22]. Due to the small divergence angle of laser communication, precise alignment of communication components at the transmitting and receiving ends is required to establish inter-satellite links. Currently, laser inter-satellite links rely on Acquiring, Tracking, and Pointing (ATP) systems to achieve high-precision tracking and pointing assistance [22]. According to documents submitted by SpaceX to the FCC in 2018, each Starlink satellite is equipped with four laser units distributed on the front, back, left, and right sides of the satellite's baseplate. Therefore, the satellite model used in the simulation in this paper is Starlink's satellite, with inter-satellite communication in the directions of front, back, left, and right [23].
## 3 Results and Discussion
### Physicochemical Properties of Emulsions
#### 3.1.1 Freshly Prepared Emulsion Systems
Interestingly, the presence of Toc in the emulsion system increases the droplet Z-ave and does not significantly influence the PDI and ZP, regardless of gallic acid (GA) presence in the emulsion. This can suggest strong interactions of fat-soluble Toc with fatty acid leading to the formation of bigger emulsion droplets. The effect of Toc on the physiochemical properties of emulsions that contain fatty fractions (such as oils, glycerides, etc.) is ambiguous and relies on both the ratio of Toc to fatty compounds and the specific compounds present. In certain formulations and specific ratios, a slight decrease in droplet size was observed [34], while in others, a significant increase occurred [35]. On the other hand, the Toc addition led to a decrease in PDI and an increase in the negative value of ZP, which is a good perspective application for the stability of these types of formulations. The positive effect of Toc on nanoemulsion stability has been also reported previously [34]. The GA presence in the formulations was expected to increase the quality of emulsion systems [17; 18], including the improvement of each of the parameters discussed above (decrease in droplet diameter, PDI, and ZP). However, the effect of GA on the examined emulsion was ambiguous. A slight decrease in the droplet size for freshly prepared emulsions was observed for all samples, but at the same time, minor changes in PDI and ZP take place. The only noticeable decrease in droplet size was observed for water extract, but this effect was not unequivocal, because the ZP value for the sample with GA was worse (less negative) compared with that same sample without GA.  
DLS results analyzed in the size distribution mode (Figure S2) show that, in the samples, there were also larger droplets in the range of 1000 nm and higher. Thus, it was possible to visualize each sample using optical microscopy. The 40-fold magnification objective was used, and the images were recorded with a CCD camera. The results are presented in Figure 2. The inhomogeneity of recorded droplets was highest for the emulsion system containing Toc. For this sample, the largest droplet sizes were observed. Additionally, large, but more homogenous droplets were observed for emulsion without any additive. The lowest droplet sizes were recorded for the emulsion with acetone extract. The presence of GA in the samples did not influence the droplet sizes. The visualization of emulsion samples presented in Figure 2 confirms the results obtained from the DLS measurements.