esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Methods
### Training Dataset  
We selected relatively clean seismic data with minimal noise and combined them with pure environmental recordings collected from noise-prone areas to create the training dataset. This combination ensures that the dataset is labeled more accurately, which is essential for effective supervised learning. Figure 3a shows an example of a pure environmental noise recording, characterized by irregular and high-amplitude fluctuations typical of field noise. In contrast, Figure 3b presents a relatively clean seismic recording, where coherent reflections are clearly visible with minimal contamination.  
We combined the signals from Figure 3a,b. During this process, we adjusted the relative amplitude between the noise and clean seismic signals to determine whether a trace should be labeled as noise. Labels are defined as (1, 0) for traces with strong noise and (0, 1) for traces with weak noise.  
\[mark=\left\{\begin{array}{ll}(1,0)&,NMean>m\times CMean\\ (0,1)&,NMean\leq m\times CMean\end{array}\right. \tag{2}\]  
where \(m\) is a threshold, _NMean_ is the mean of the noise, and _CMean_ is the mean of the seismic signal. After the training dataset is generated using this approach, each trace is first normalized by dividing it by its maximum value. Then, the one-dimensional time series is converted into a Mel-spectrogram. At present, most newly collected seismic data have a sampling rate of 1 ms and a recording time of about 8 s. Some older datasets may use a 4 ms sampling rate, with recording times usually longer than 6 s. When using Mel-spectrograms to build datasets, the effect of sampling rate is small. For example, the data in Figure 1a were resampled to 1 ms, 2 ms, and 4 ms, and then converted to Mel-spectrograms. The results are shown in Figure 4. As seen in the figure, the Mel-spectrograms look very similar under different sampling rates. This shows one advantage of the proposed method--it is not sensitive to the sampling rate. Since most seismic data have recording times longer than 6 s, we used 6 s as the standard length for building the dataset. All field data used in our experiments have a sampling rate of 1 ms. The data are segmented into 64 equally spaced windows, each overlapping by 50 samples. A Fourier transform is applied to each window, covering frequencies from 1 to 120 Hz. The resulting Mel-spectrograms have dimensions of 64 \(\times\) 64.  
Figure 3: Pure environmental recording (**a**) and relatively clean seismic recording (**b**).
# Statistical and Clustering Analysis of Safety Profiles of FDA-Approved Protein Kinase Inhibitors
## 2 Materials and Methods
### Preparation of AE Database for Approved Protein Kinase Inhibitors and Control Set  
The FDA Adverse Events Reporting System (FAERS) is one of the largest safety databases and is frequently used for signal detection by the FDA and by the Market Authorization Holders. It can be also used for other secondary analyses, including drug repurposing. In the context of secondary analyses and drug repurposing, one of the advantages of using FAERS over package inserts is that the users do not need to wait for a sufficient number of adverse effect incidents to occur to be included in the package inserts [22].  
For the consistent coding of AEs included in these databases, the Medical Dictionary for Regulatory Activities (MedDra) is used [17]. This is the worldwide dictionary used for coding of adverse events and drug indications for regulatory purposes. It is used by all Drug Agencies across the globe.  
OpenVigil 2.0 is a software package that analyses pharmacovigilance AE data from the FAERS system. Data mining features include highly configurable search criteria filters and output views. Results can be observed, sorted, and filtered in the web browser or saved for further analyses in statistical software packages [16]. OpenVigil 2.0 includes functionalities to clean and preprocess FAERS data, removing duplicates and handling missing data, which ensures higher data quality and accuracy. The tool standardizes drug names and adverse event terms to improve consistency and reliability in data analysis. This software was accessed in August 2022 and the AEs associated with the selected protein kinase inhibitors were extracted. The MedDra version used for the coding of AEs was 24.0, and AEs associated with the PKIs were extracted by the preferred term (PT). PKIs for which data were not available in OpenVigil 2.0 or that had insufficient data available for a statistical analysis were excluded.  
The frequency of each AE PT was calculated using the number of reported cases extracted from OpenVigil 2.0. This operation was performed for all the analyzed drugs and all PTs observed.
## 5 Simulation Results and Discussions
### Results with Ambient Light Noise  
In this subsection, we consider the effects of ambient light noise sources. As explained above, two ambient noise sources are considered, which are fluorescent lamps and white LEDs as presented in Section 3.2.  
Figures 10 and 11 present the BER and received power versus distance for both MIMO- and SISO-based VLC systems with ambient light noises. It is observed that MIMO enables more efficient transmission over longer distances, exhibiting better results in terms of received power and minimized BER even in the presence of ambient light noises. Also, the higher-order modulation technique, QPSK, demonstrates superior performance in MIMO-VLC systems. Table 4 presents the achievable link distance in both SISO and MIMO systems with ambient light noise.
###### Abstract  
Concrete edge failure of a single anchor in concrete is strongly dependent on the tensile performance of the concrete, which can be greatly improved by the addition of steel fibers. This study investigated the effect of steel fibers on the shear failure mode and edge breakout resistance of anchors installed in steel fiber-reinforced concrete (SFRC) with fiber volume percentages of 0.33, 0.67, and 1.00%. The anchor used in the study was 30 mm in diameter, with an edge distance of 75 mm and embedment depth of 240 mm. In addition to the anchor specimens, beam specimens were prepared to assess the relationship between the tensile performance of SFRC beams and the shear resistance of SFRC anchors. The ultimate flexural strength of the beam and the breakout shear resistance of the anchor increased almost linearly with increasing volume fractions of fiber. Therefore, based on the ACI 318 design equation, a term was proposed using the ultimate flexural strength of concrete instead of the compressive strength to determine the concrete breakout shear resistance of an anchor in the SFRC. The calculated shear resistance of anchors in both the plain concrete and SFRC were in good agreement with the measurements. In addition to the load capacity of the SFRC anchors, the energy absorption capacity showed a linear increase with that of the SFRC beam.  
anchor; shear behavior; concrete edge breakout resistance; ultimate flexural strength; energy absorption capacity; steel fiber +
Footnote †: journal: Applied Sciences
###### Abstract  
Redundant Switched-mode Power supplies (SMPSs) are commonly used to improve electronic systems' reliability, and accurate estimation of the current sharing state is significant for evaluating the system's health. Currently, the current sharing state estimation is mainly realized by using current sensors to detect each branch's current, and the deployment and maintenance costs are high. In this paper, a method for power supply current sharing state estimation based on LSTM recurrent neural network is proposed. By taking advantage of subtle differences in the inherent spectral characteristics of SMPSs, this method only needs to detect the voltage ripple at the switching frequency of the load terminal to estimate the output current of each power supply branch. The verification experiment on the three-power redundant experimental platform shows that the estimation error is less than 10%. The method has the characteristics of simple structure, non-invasion, convenient deployment and maintenance, so it has high application and promotion value.  
switched mode power supply; current sharing; ripple wave; spectrum signature +
Footnote †: journal: Applied sciences  
Article
# A Novel Optimal Control Strategy of Four Drive Motors for an Electric Vehicle
###### Abstract  
Based on the mobility requirements of electric vehicles, four-wheel drive (4 WD) can significantly enhance driving capability and increase operational flexibility in handling. If the output of different drive motors can be effectively controlled, energy losses during the distribution process can be reduced, thereby greatly improving overall efficiency. This study presents a simulation platform for an electric vehicle with four motors as power sources. This platform also consists of the driving cycle, driver, lithium-ion battery, vehicle dynamics, and energy management system models. Two rapid-prototyping controllers integrated with the required circuit to process analog-to-digital signal conversion for input and output are utilized to carry out a hardware-in-the-loop (HIL) simulation. The driving cycle, called NEDC (New European Driving Cycle), and FTP-75 (Federal Test Procedure 75) are used for evaluating the performance characteristics and response relationship among subsystems. A control strategy, called ECMS (Equivalent Consumption Minimization Strategy), is simulated and compared with the four-wheel average torque mode. The ECMS method considers different demanded powers and motor speeds, evaluating various drive motor power distribution combinations to search for motor power consumption and find the minimum value. As a result, it can identify the global optimal solution. Simulation results indicate that, compared to the average torque mode and rule-based control, in the pure simulation environment and HIL simulation during the UDDS driving cycle, the maximum improvement rates for pure electric energy efficiency for the 45 kW and 95 kW power systems are 6.1% and 6.0%, respectively. In the HIL simulation during the FTP-75 driving cycle, the maximum improvement rates for pure electric energy efficiency for the 45 kW and 95 kW power systems are 5.1% and 4.8%, respectively.  
electric vehicle; simulation platform; energy management system; equivalent consumption minimization strategy (ECMS); hardware-in-the-loop; rapid-prototyping controller +
Footnote †: journal: Applied Sciences  
0000-0001-5000-0002-0000][PERSON] and [PERSON]
## 5 Results and Discussion
### Performance of the FPI to Show Flood Process  
Based on the reconstructed complete TWSA dataset using the GAIN algorithm, we calculated the monthly FPI for the PRB using Equations (5)-(8). This index provides an intuitive reflection of the likelihood of flooding in the region. Figure 8 shows the long-term time series of FPI from 2002 to 2023 combined with the true flood events from EM-DAT and precipitation.  
The positioning of the true flood events' red dots corresponds closely with peaks in the FPI, indicating a correlation between the calculated flood potential and actual observed floods. This suggests that the FPI is a reasonable indicator of flood occurrence, capturing most of the observed flood events effectively. The alignment of flood events with high FPI values indicates that the index is a valuable tool for identifying periods of elevated flood risk. Most of the observed flood events align well with higher peaks in the FPI curve, demonstrating the predictive utility of the FPI. Based on the analysis of the results, the data demonstrate a strong correlation between gap-filling FPI values and actual flood events, affirming the effectiveness of FPI in predicting flood potential.  
It can be seen from Figure 7 that precipitation variability serves as one of the major driving factors of fluctuations in the FPI, with intense or frequent precipitation events significantly increasing TWSA and elevating FPI values due to the heightened flood risk when terrestrial water storage surpasses regional capacity. Additionally, regional hydrological conditions, such as soil moisture, groundwater recharge rates, and surface runoff, critically influence TWSA dynamics. Extreme weather events, including heavy precipitation and monsoonal activities, further exacerbate these variations, as evidenced by notable peaks in FPI during years with extreme precipitation, such as 2016. Seasonal and interannual climatic variability also play a significant role, as changes in precipitation patterns and seasonal water storage cycles lead to periodic fluctuations in FPI. Furthermore, the regional water storage capacity sets an upper limit to TWSA, beyond which even minor precipitation events can induce flooding. These findings underscore the complex interplay between climatic, hydrological, and regional factors in shaping the spatiotemporal dynamics of FPI, providing critical insights for flood risk assessment and management in vulnerable regions.
## 3 Blasting Test and Vibration Safety Evaluation
### Blasting Test and Vibration Safety Evaluation of Water Pipeline  
According to the relative locations of the tunnel and pipeline, the closest distance between the peripheral holes and pipeline was 2.3 m. A testing condition was found here that approximately reproduces the effect of the blasting face on the pipeline above it. Specifically, the research case was replicated by drilling blast holes at a distance of 2.3 m below the surface of the upper bench. Three blast holes were drilled at a depth of 2 m, with a 1 m interval on the lower bench, and each hole was loaded with 0.6 kg of explosive. Due to the close spacing of the blast holes, to eliminate mutual interference, their ignition times were defined as MS1, MS3, and MS5, respectively. After installing vibration monitoring equipment on the upper bench, the blasting vibration assessment test was carried out for the work on the lower bench, as shown in Figure 3. Design and implementation process of alternative in situ testing: (Figure 3a) Diagram of the testing; (Figure 3b) the operating process of testing. In addition, the monitoring equipment adopted the TC-4850N wireless network vibrometer developed by Zhongke (Chengdu) Instruments Co., Ltd. (Chengdu, China). The maximum sampling rate can be up to 100 k Sps, and the sampling rate of 5 k Sps can well meet the test requirements of blasting frequency. The result of the blasting response is shown in Figure 4. Vibration waveform monitored from tests. Figure 4a-c correspond to the vibration velocity in the \(x,y\), and \(z\) directions, respectively.  
The PPV in each direction of the monitoring results exceeds the standard required by the \"the safety standards for hydraulic tunnels in Blasting Safety Regulations (GB6722-2014) [20]\", which states that when subjected to high-frequency vibration (50 Hz), the maximum PPV should not exceed 15 cm/s. Therefore, vibration damage is likely to occur in the water pipeline when the closest peripheral holes are blasted.  
To further evaluate the degree of damage to the pipeline under the original blasting method, the vibration response and accumulative damage characteristics of the pipeline under non-electric detonator blasting were studied using numerical simulations. Subsequently, a vibration reduction blasting scheme for the electronic detonator was proposed, and the blasting vibration response and accumulative damage characteristics of the pipeline were analyzed. By comparing the pipeline damage characteristics of the two blasting methods described above, an optimal blasting scheme was obtained.
## 6 Conclusions  
The use of alum sludge in geotechnical engineering, has gained importance due to its cost-effectiveness and environmental benefits, as it has been found to improve the strength and stability of soils. The CBR test is a crucial parameter in geotechnical engineering, which measures the load-bearing capacity of soil. However, predicting the CBR of soil-alum sludge mixtures can be challenging, due to the large number of input variables. This highlights the significance of utilizing artificial intelligence (AI) methods to overcome this challenge, as this approach has not been widely used previously in this field.  
This study found that artificial intelligence (AI) methods can be utilized to predict the CBR, which is a crucial parameter in geotechnical engineering, that measures the load-bearing capacity of soil, of soil-alum sludge mixtures. The use of AI methods can overcome the challenge of predicting CBR, due to the large number of input variables. The study compared the performance of three different AI models (two black-box models and one grey-box model), using a database of 27 CBR test results, and found that the artificial neural network (ANN) and genetic programming (GP) methods outperformed the support vector machines (SVM) method. The database consisted of nine parameters, including liquid limit of soil, plasticity index of soil, specific gravity of soil, number of compaction blows, optimum moisture content of soil, maximum dry density of soil, optimum moisture content of mixture, maximum dry density of mixture, and sludge content.  
The ANN method achieved high accuracy, with \(R^{2}\) of 0.989 and 0.980 for the training and test databases, respectively. The GP method had slightly lower accuracy, but had the advantage of producing an equation as output, that can be used for other datasets. The study also determined the optimal number of neurons for the ANN model, which is 10 neurons. The examination of parameter sensitivity and importance, indicated that the number of compaction hammer blows, and the soil's liquid limit were the most significant parameters, while the maximum dry density parameters for soil and mixture were the least significant. This information is important for engineers and researchers, to optimize their soil stabilization process. Overall, the study provides valuable insights into the performance of different AI models for predicting CBR and can be useful for future research and practical applications.  
Conceptualization, M.D.N.; Methodology, A.B.; Software, A.B.; Validation, A.B.; Writing--original draft, A.B.; Writing--review & editing, M.D.N., A.A., N.M., T.B. and H.A.-N.; Supervision, H.A.-N. All authors have read and agreed to the published version of the manuscript.
# Urban Seismic Networks: A Worldwide Review
## 2 USN Catalogue
### Objectives
Their assessment is critical in the built environment, and is the reason behind the implementation of several USNs (usually temporary ones) worldwide. * _Structural health monitoring._ Earthquakes can affect the state of health of buildings and structures in general. Certain structures can be considered strategic because of their function or value. Networks conceived to monitor the vibrations of such strategic buildings and their behaviour over time represent fundamental tools to establish protection strategies and preserve their functions, and possibly their cultural value, in case of damaging earthquakes [8]. Moreover, grouped under _\"other\"_, we classified USNs with less common objectives such as the implementation of decision support systems [43; 45; 118], seismological studies [101; 107; 133; 136], and monitoring of geothermal stimulation, mines, or other industrial activities [18; 55; 134; 138]. For each record in Table 1, the main objective is reported along with any secondary ones where provided. The temporal trends of the objectives indicate that not all the objectives are prominent in the same way or within the same period (Figure 3). For instance, USNs for earthquake monitoring and seismic site response have been adopted all along the analysed period, while USNs for earthquake early warning have been implemented only since 2008, and their number has increased relatively quickly (c.f. [159]). Figure 3: Temporal trends of the main objective adopted by USNs (c.f. Table 1) and frequency of occurrence of all the objectives. The frequency of occurrence of the various objectives, distinguishing between the main and the secondary ones, is reported in Figure 3. Considering only the main objective, one-third of the considered USNs were established for earthquake monitoring; the study of site effects and the assessment of ground motion intensity are the second- and third-most frequent objectives, respectively. Considering the primary and secondary tasks together, earthquake monitoring and site effects make up the objectives for more than 40% of the collected USNs.
## 3 Results
### Test and Match Performance Data  
Test and match performance data are presented in Table 2. The MPS ranged from \(-1\) to 2 (0.42 \(\pm\) 0.69) and did not differ significantly (\(p\) = 0.684, \({\eta_{\text{p}}}^{2}\) = 0.011) between defenders (0.50 \(\pm\) 0.69) and forwards (0.36 \(\pm\) 0.71). The relationship of 29 IHCT parameters (9 stress parameters, 18 load parameters) to the MPS was calculated by linear regression analysis and summarized in Table 3; 52% (14/27) of the parameters explained at least 10% of the total variance, 26% (7/27) of the parameters explained at least 20% of variance, and 7% (2/27) of the parameters (maximum wrist shot, 30 m sprint without puck) before testing explained more than 30% of variance. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Defenders (r = 7)** & **Forwards (n = 10)** & **Total (n = 17)** \\ \hline Age [years] & 26.6 \(\pm\) 7.33 & 29.0 \(\pm\) 6.89 & 28.0 \(\pm\) 6.95 \\ Height [cm] & 186 \(\pm\) 4 & 181 \(\pm\) 5 & 183 \(\pm\) 6 \\ Body mass [kg] & 91.0 \(\pm\) 8.97 & 87.8 \(\pm\) 8.41 & 89.1 \(\pm\) 8.52 \\ Body fat [\%] & 17.6 \(\pm\) 425 & 19.1 \(\pm\) 5.40 & 18.5 \(\pm\) 4.87 \\ Resting heart rate [b x min\({}^{-1}\)] & 65 \(\pm\) 12 & 64 \(\pm\) 8 & 64 \(\pm\) 9 \\ Resting lactate [mmol/L] & 1.29 \(\pm\) 0.30 & 1.30 \(\pm\) 0.36 & 1.29 \(\pm\) 0.33 \\ Playing experience & Years & 8.57 \(\pm\) 7.59 & 8.20 \(\pm\) 5.83 & 8.35 \(\pm\) 6.38 \\ Number of matches & 386 \(\pm\) 383 & 342 \(\pm\) 268 & 360 \(\pm\) 310 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Demographic and anthropometric characteristics of ice hockey players in relation to playing positions (mean \(\pm\) standard deviation).
## 5 Optimization Design  
### Mathematical Modeling  
#### 5.1.1 Design Variables  
Among all the dimension parameters, \(a\), \(b\), \(c\), \(d\), \(l_{\text{a}}\) and \(l_{\text{b}}\) have an impact on each performance index. Therefore, the dimension parameters \(a\), \(b\), \(c\), \(d\), \(l_{\text{a}}\) and \(l_{\text{b}}\) are taken as the design variables in the optimization design.  
The initial value and constraint range of each design variable of the reconfigurable parallel mechanism are presented in Table 3.
# Structural Design and Study of an Integrated Cutter System Based on Machine Operation
## 4 Verification of the Anti-Loosening Performance of the Integrated Cutter System
### Experimental Results and Analysis
During the 8 h of vibration in the normal load  
Figure 16: EICS preload variation curves: (**a**) residual preload ratio on lateral and axial loads; (**b**) axial forces on lateral and axial loads; (**c**) residual preload ratio on normal load; (**d**) axial forces on normal load; (**e**) residual preload ratio over the whole process; (**f**) axial forces over the whole process. direction, there is a significant drop in the preload curve. After 10 h of vibration, the preload gradually stabilized, and the residual preload ratio decreased to about 92%. The preload of the S1 and S4 curves decreased from 265 kN to 240 kN, and the preload of the S3, S5 and S6 curves did not show any obvious decrease. The strain gauges at S2 failed after 6 h of vibration. In summary, the integrated cutter samples were stabilized at more than 90% of the residual preload ratio after 14 h of continuous vibration, and the loss of preload was within the acceptable range. Referring to the ISO 16130-2015 standard [25] and combining this with on-site inspection, it can be judged that the integrated cutter undergoes no loosening and has good locking performance.