esa-sceva/satcom-chunk-collection huggingface dataset:
# Improvement of Surface Roughness and Cracking Study of Nb\({}_{3}\)Sn SRF Films
## 5 Conclusions  
We have successfully applied the BEP method as a pretreatment for Nb\({}_{3}\)Sn film preparation and also studied the cracking risk of Nb\({}_{3}\)Sn film under different stresses of the tin vapor diffusion method-coated Nb\({}_{3}\)Sn on Nb substrates in order to explore possible ways to improve the performance of Nb\({}_{3}\)Sn films and the reliability of Nb\({}_{3}\)Sn-coated cavities. By using BEP pre-polished substrate, we reduced the average roughness of the film to 26 nm, which is much lower than that of the EP-ed sample. By performing tension and compression experiments on Nb\({}_{3}\)Sn-coated flat and curved samples, we determined a safe residual strain range of (\(-\)2.3%, 0.9%) for a 2 \(\upmu\)m thick film without any visible cracks. For 1.3 GHz single-cell Nb\({}_{3}\)Sn cavities, tuning of 158 kHz at room temperature will decrease the Q according to our experiments. For the thin-film cavity of Nb\({}_{3}\)Sn, it can be tuned at a low temperature in the future, and together with the extrusion study mentioned in this paper, the tunability of Nb\({}_{3}\)Sn thin film can be studied.  
Conceptualization, Z.W., G.W., S.Q. and J.H.; Methodology, Z.W., G.W., S.Q., L.L., M.R., J.H., F.W., F.Z. and F.J.; Software, Z.W. and G.W.; Formal analysis, Z.W., G.W., S.Q. and J.H.; Investigation, S.Q. and J.H.; Writing--original draft, Z.W. and G.W.; Writing--review & editing, S.Q. and J.H.; Supervision, S.Q., J.H. and S.H. All authors have read and agreed to the published version of the manuscript.  
This research was funded by State Key Laboratory of Nuclear Physics and Technology, Peking University, under Grant Numbers NPT2023 ZX04 and SKL2023K004; and National Key Programme for S&T Research and Development, under Grant No. 2023 YFA1606802.  
Not applicable.  
The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.  
The authors would like to thank Ningxia Orient Superconductor Technology Co., Ltd. (OSTEC) for the cavity fabrication and postprocessing. The support from the Guangdong Institute of Laser Plasma Accelerator Technology, China is also greatly appreciated.  
The authors declare no conflict of interest.
# Rapid Restoration Techniques for Software-Defined Networks
## 5 Experimental Evaluation
### Performance Evaluation
#### 5.2.2 Path Operation Cost  
The performance of the proposed approaches was studied with respect to the operation cost, that is, the number of added and removed rules. Paths with different lengths were selected in the manner described in Section 5.2.1. Figure 8 shows the the average operation cost achieved by Algorithms 1-4 versus the percentage of path length for all the simulated topologies. The cost here implies the number of operations required to establish the obtained paths. The max and min values were also reported. The dotted bar represents the required rules to install the optimal path, which serves as the case before failure (i.e., BF) scenario. In most cases, Algorithms 2-4 outperformed Algorithm 1 in terms of the  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & & & & & & \multicolumn{2}{c}{**Completion Rates**} \\
**Network** & **Communities** & **Intra Links** & **Inter Links** & **Intra Links Density** & **Success Rate** & **Fail Rate** & **Modularity** \\ \hline NR & 18 & 852 & 62 & 93.21\% & 97\% & 3\% & 0.838 \\ Germany & 6 & 68 & 20 & 77.27\% & 96\% & 4\% & 0.597 \\ ERnet & 5 & 44 & 13 & 77.19\% & 93\% & 7\% & 0.533 \\ Brite1 & 9 & 263 & 137 & 65.75\% & 80.7\% & 19.3\% & 0.530 \\ Brite2 & 13 & 360 & 240 & 60\% & 69.4\% & 30.6\% & 0.506 \\ Brite3 & 11 & 496 & 304 & 62\% & 75.3\% & 24.7\% & 0.515 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Completion rate, link density and modularity achieved by Algorithm 3 for all topologies.  
average operation cost. This is due to the fact that the proposed approaches obtained alternative paths by achieving the restoration across a path segment rather than the entire path.  
As a consequence the required number of rule updates was reduced. Compared to the operation cost of the optimal path before failure scenarios (i.e., BF), the average operation cost of Algorithm 1 was relatively high and usually depended on the length. The relative increase of the operation cost never exceeded 80% for short paths and 66.6% for long paths. However, compared to the average operation cost obtained by Algorithm 1, the average operation costs achieved by Algorithms 2-4 were lower. The relative decrease in the path operation cost was significant (using Algorithms 2-4) as illustrated in Table 4. We observed that the operation cost was inversely proportional to the path length. The longer the path the lower the operation cost and therefore the higher the reduction rate. In general, Algorithms 2-4 performed better than Algorithm 1 in terms of the operation cost of alternative paths. However, Algorithms 2-4 only failed in 5 out of 162 cases. This is highlighted in bold in Table 4. These 5 cases arose on the Brite2 topology and their occurrence is explained by the discussion in Section 5.2.1.  
Figure 7: Flowchart for calculating Success and Fail variables.
## 3 Discussion  
A recent survey [45] of the medical literature shows that there has been an increase in systematic reviews on patient preferences, suggesting increasing interest in conducting preference-eliciting studies and systematic reviews of these studies. Therefore, PPMSDB infrastructure could be helpful to monitor the currentness and validity of the evidence.  
Open access to PPMSDB data and metadata would provide pre-existing research with a usable and sustainable future. For example, extracted metadata and coding could be used to update a meta-analysis or even conduct another meta-analysis on a similar subject with an overlap in the relevant literature. This is crucial for several reasons. First, accumulating science and keeping evidence updated is a cooperative task, and participation in this task must be supported and incentivised, in addition to the single classical publication. Second, an open-access PPMSDB would enable the application of state-of-the-art statistical procedures to existing data and test these effects on the meta-analytic results. Third, open access to existing meta-data provides other researchers with research questions the opportunity to use subsets of the pre-existing meta-analytic data.  
The ongoing accumulation of evidence would inform the researchers about the latest findings in a specific research area; for example, they could estimate when the results are robust enough to justify further research investment. When multiple preference-eliciting studies are done, a systematic review of these studies may then be needed to synthesise and summarise the study findings.  
Some limitations must be acknowledged. This project requires continuous funding and support, not only in the development and implementation phase but also afterwards, to ensure maintenance and updating.  
Another limiting factor could be the wide variability of PPSs. In a preliminary phase, precise guidelines should be drafted for the requirements for the inclusion of PPSs into the PPMSDB. In drawing up these guidelines, however, we can refer to those issued by the Innovative Medicines Initiative-Patient Preferences (IMI-PREFER) and the Health Preference Research-International Health Economics Association [37, 38] for the design and conduct of PPSs. Moreover, having guidelines that can uniquely unite PPSs may increase the quality standards of such studies.
# An Improved Hilbert-Huang Transform for Vibration-Based Damage Detection of Utility Timber Poles
## 1 Introduction
This technique is employed on signals associated with three serviceable and three unserviceable timber poles. Selection of mother wavelet is important for the WPT. Maximum energy to Shannon entropy ratio is adopted to select the best mother wavelet function. Using WPT, the captured vibration signal is decomposed into different frequency bands and wavelet coefficients are reconstructed in the dominant frequency bands as new signal for performing further decomposition using EMD. Furthermore, a screening technique is applied to select the dominant IMFs produced from EMD to eliminate the undesirable IMFs by computing the correlation coefficients of the IMFs and the raw analysed signal. Later, Hilbert Transform is applied to those dominant IMFs in order to generate the instantaneous frequency plot. The effectiveness of the improved HHT is verified for six poles data collected from real field. Sudden changes in the instantaneous frequencies are observed in the analysed signal to determine some vital features related to the health state of timber pole. HHT with the WPT as pre-processor has been successfully used by [PERSON] et al. [36; 37] for roller bearing fault diagnosis, nevertheless there is still no report on the implementation of this technique in vibration based damage detection of utility timber poles.
# Analysis and Identification of Nonlinear Acoustic Damping in Miniature Loudspeakers
###### Abstract  
Nonlinear acoustic damping is a key nonlinearity in miniature loudspeakers when the air velocity is at a high amplitude. Measurement of nonlinear acoustic damping is beneficial for predicting and analyzing the performance of miniature loudspeakers. However, the general measuring methods for acoustic impedance, such as the standing-wave tube method or the impedance tube method, are not applicable in this scenario because the nonlinear acoustic damping in miniature loudspeakers is coupled with other system nonlinearities. In this study, a measurement method based on nonlinear system identification was constructed to address this issue. The nonlinear acoustic damping was first theoretically analyzed and then coupled in an equivalent circuit model (ECM) to describe the full dynamics of miniature loudspeakers. Based on the ECM model, the nonlinear acoustic damping was identified using measured electrical data and compared with theoretical calculations. The satisfactory agreement between the identification and theoretical calculations confirms the validity of the proposed identification method.  
nonlinear acoustic damping; nonlinear system identification; miniature loudspeaker; equivalent circuit model +
Footnote †: journal: Applied Sciences
# Metachrylate-Based Polymeric Sorbents for Recovery of Metals from Aqueous Solutions
## 7 Adsorption on Amino-Functionalized Glycidyl Methacrylate-Based Polymers
The Cr(VI) and Cu(II) sorption were much slower from their binary solutions (the sorption half time for Cr(VI) and Cu(II) were \(11\) and \(45\) min) than from single-component solutions (observed sorption half time for Cr(VI) and Cu(II) were \(0.5\) and \(3\) min) presumably due to the competition of metal ions for the active sites on the copolymer surface. As a result of kinetics analysis, it was concluded that the best fit for investigated heavy metals sorption by PGME-en and PGME-eta provides pseudo-second-order kinetics. [PERSON] et al. tested macroporous PGME functionalized with hexamethylene diamine (PGME-HD) as Cr(VI) oxyanion sorbent from aqueous solutions [89]. Kinetic data were analyzed using chemical reaction particle and diffusion models kinetic models (pseudo-first order, pseudo-second-order, Elovich), intraparticle diffusion, Bangham, Boyd, and McKay). The monolayer sorption Langmuir model was the most suitable to fit the experimental equilibrium data. Calculated thermodynamic parameters suggested that Cr(VI) adsorption onto PGME-HD was spontaneous and endothermic. In addition, PGME-HD was found to be easily regenerated with \(0.1\) M NaOH and reusable in four sorption/desorption cycles, with up to \(90\%\) recovery. PGME-eta was studied as a potential recovery agent for molybdenum, Mo(VI) oxyanions, by varying pH, time, initial concentration, and temperature [111; 130]. Calculated thermodynamic parameters revealed that both chemical adsorption and intraparticle diffusion were rate-controlling, with chemisorption as predominant. This could be the consequence of the transition metal nature of molybdenum. Namely, during the sorption process, d orbitals become filled with free electron pairs from amino or hydroxy groups of PGME-eta. Among seven chemical-reaction and particle-diffusion kinetic models (pseudo-first-order, pseudo-second-order, Elovich, intraparticle diffusion, Bangham, Boyd and McKay), the best fit was observed with pseudo-second-order, with the considerable effect of intraparticle diffusion. The maximum Mo(VI) sorption capacity for PGME-eta was \(3.58\) mmol/g at \(343\) K.
## 4 Experiments and Results
### Distributed Control Strategy Comparison Experiments  
The distributed flocking control strategy based on IDGCNs is obtained by learning from the expert template. To verify the effectiveness and scalability of the strategy, the fully distributed APF strategy (16) and a distributed learning strategy based on Delayed Aggregation Graph Neural Networks (DAGNNs) [38] are selected for comparison.
# Study of the Critical Speed of Ultra-High-Speed Diamond Drilling Technology in Marble
## 3 Simulation and Discussion
### Effect of Rock Breaking Mechanism by Ultra-High Speed
To further elucidate the impact of speed on the rock-crushing process, we delve into the equivalent plastic strain of the crushed rock. In Figure 14, we compare the equivalent plastic strain values of rock crushing under two different rotational speeds, 2 m/s and 9 m/s, using the equivalent plastic deformation curves of the diamond that contacts the rock nodes (as seen in Figure 15). The residual equivalent plastic strain of the rock under ultra-high-speed conditions is significantly reduced. Specifically, the equivalent plastic strain value of the rock fluctuates around 0.028 at 2 m/s, while the corresponding value at 9 m/s is approximately 0.026. This indicates a 7.14% reduction in equivalent plastic strain at 9 m/s compared to 2 m/s. The rationale behind this shift in the proportion of elastic-plastic damage of the rock under ultra-high-speed conditions may be attributed to the rock experiencing a higher frequency of cutting forces and elevated stress values. In rock breaking, brittle crushing plays a pivotal role in enhancing the efficiency of drilling teeth for crushing rocks. When attempting to break the same volume of rock, ultra-high rotational speeds can significantly bolster drilling efficiency. Stage III, marked by a rotational speed of 9 m/s, stands out as the point where the equivalent plastic strain value of rock crushing reaches its minimum. This juncture can be deemed as the optimal speed for efficient rock crushing. However, as the speed exceeds 9 m/s, the equivalent plastic strain begins to exhibit an upward trend once more. Examining the variation curve of the crushing pit width at different speeds in Figure 11, we observe that the diamond-cutting  
Figure 6:0 Nephogram of equivalent plastic strain under different speed: (**a**) equivalent plastic strain at 2 m/s; (**b**) equivalent plastic strain at 9 m/s. width and the volume of crushed rock both decrease after the speed surpasses 9 m/s. The additional kinetic energy generated by the RPM increase does not significantly impact rock crushing; instead, more energy is diverted towards frictional energy dissipation between the rear face of the blade and the rock. Optimal speed range selection can effectively mitigate energy dissipation and elevate rock-crushing efficiency.
## 4 Experiment and Analysis
### Discussion  
For SAR images with coherent imaging mechanisms, we used the SAR-SIFT algorithm as the algorithm benchmark. The SAR-SIFT algorithm replaces the construction of the SIFT scale space with a multi-scale Harris space based on the ROEWA multiplicative operator to handle the severely interfering speckle noise in SAR images, achieving very good matching results. However, the computational complexity of SAR-SIFT is linearly related to image size, and it is very time-consuming to process matching in multiple SAR image mosaic tasks, which does not have practical engineering application value. Therefore, based on the SAR-SIFT algorithm, this article proposes improvement points from two aspects: Firstly, accelerate the GPU by constructing the most time-consuming multi-scale Harris space and feature descriptors for SAR-SIFT. Then, for the matching task of multiple SAR images, a  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Parallelization Strategy** & **5 Scenes** & **10 Scenes** & **15 Scenes** & **21 Scenes** \\ \hline Single node CPU & 932.56 & 1848.73 & 3484.66 & 5268.59 \\ \hline Single node GPU & 34.73 & 68.99 & 125.43 & 189.98 \\ \hline Single node GPU optimization & 27.49 & 52.85 & 98.49 & 147.49 \\ \hline Four nodes GPU optimization & 8.62 & 13.21 & 27.09 & 51.45 \\ \hline Sixteen nodes CPU optimization & 2.93 & 4.77 & 9.35 & 13.62 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Record of SAR Image Matching Parallel Experiment Results.  
Figure 7: SAR Image Matching Parallel Strategy Optimization Comparison Chart.  
joint acceleration strategy based on multi-node GPUs is proposed to further improve the processing efficiency of the matching algorithm in large-scale tasks.  
Of course, for our current algorithm, there are still the following shortcomings: due to the need to construct multi-scale Harris space on the GPU, a large amount of graphics memory is required to process large and wide SAR images. For example, for an \(M\times N\) SAR image, assuming the scale is \(S\), a space of \(2\times M\times N\times S\times sizeof\ (float)\) is required. For the test data in the experiment, it actually requires more than 20 G of graphics memory, which has certain requirements for GPU configuration, it does not have the ability to migrate to edge computing devices. Later, we will further study how to reduce the consumption of GPU video memory by the algorithm and further improve the processing efficiency of the algorithm.
# On the Optimum Linear Soft Fusion of Classifiers
## 3 The Improvement Factor  
For notation convenience, let us consider that \(MSE_{1}\geq MSE_{2}\geq\ldots\geq MSE_{D}\) so that \(\min(MSE_{d})=MSE_{D}\). The improvement in terms of \(MSE\) can be computed by comparing \(MSE_{f}\) with the _MSE_ provided by the best of all the individual classifiers. So, let us define the _MSE_ improvement factor \(I_{f}=\frac{MSE_{D}}{MSE_{f}}\). It can be demonstrated by reduction ad absurdum that \(I_{f}\geq 1\): if \(I_{f}\) was smaller than 1, then there would be a solution to (6), namely \(w_{1}=0\ w_{2}=0\ldots w_{D-1}=0\ w_{D}=1\) providing a mean square error \(MSE_{D}<MSE_{f}\), but by definition, \(MSE_{f}\) is the minimum achievable mean square error. Therefore, the first conclusion is that the optimal linear fusion of classifiers, as previously defined, will be at least as good (in the _MSE_ sense) as the best of the individual classifiers. Furthermore, the specific value of \(I_{f}\) depends exclusively on \(\mathbf{M}_{s}\). Hence, we can obtain sets of scores from previously trained individual classifiers, so that we can use (5) to obtain a sample estimate, \(\hat{\mathbf{M}}_{s}\), from sample estimates of the covariance matrices, the bias vectors, and the priors: \(\hat{\mathbf{C}}_{s/1}\), \(\hat{\mathbf{b}}_{s/1}\), \(\hat{\mathbf{C}}_{s/0}\), \(\hat{\mathbf{b}}_{s/0}\), \(\hat{\mathbf{\rho}}_{0}\), \(\hat{\mathbf{\rho}}_{1}\). Then, \(I_{f}\) can be estimated from (7).  
\[\hat{I}_{f}=\frac{M\hat{S}E_{D}}{M\hat{S}E_{f}}=\hat{\mathbf{M}}_{s}(D,D)\cdot \mathbf{1}^{T}\hat{\mathbf{M}}_{s}^{-1}\mathbf{1}. \tag{9}\]  
With the intention of achieving a better understanding of the essential elements that affect \(I_{f}\), we now consider some simple yet relevant models, by considering simplified forms of \(\mathbf{M}_{s}\).
## 3 Experimental Results  
To test the experimental conditions set, in terms of the ability to detect and separate the twenty selected molecules, each analyte was individually analyzed. Specifically, 50 ng of each compound was added to a previously conditioned TD tube, according to the procedure described (Section 2.1). The analysis of each standard VOC was repeated five times and the retention time (RT) of each molecule was recorded (Table 3); moreover, for each compound, the characteristic fragment ions at m/z (mass-to-charge) ratios were employed for its quantification in the XICs mode from the SCAN chromatogram. Only acetonitrile was quantified from the SCAN chromatogram. At the end of each analysis, the conditioning procedure for each used TD tube was repeated and the relative chromatogram was acquired, to verify that the cleaning method carried out was successful. Thus, each cleaned TD tube was capped, sealed, and stored as described (Section 2.1). The optimized analytical conditions were tested using a linear regression analysis of the peak area versus the analyte amount, adding the TD tubes with aliquots of each standard molecule in quantities between 5 and 100 ng. Each measurement was repeated three times. Table 4 shows the linear ranges, the equations of the obtained calibration curves, and the LOD and LOQ for all the selected VOCs. \begin{table}
\begin{tabular}{c c c} \hline _Common Compound Name_ & _RT (min.)_ & _m/z_ \\ \hline
2-butanone & 13.8 \(\pm\) 0.2 & 72, 57, 43 \\ \hline
3-heptanone & 22.9 \(\pm\) 0.2 & 114, 85, 72 \\ \hline
1-Octine & 18.4 \(\pm\) 0.2 & 95, 81, 67 \\ \hline Acetonitrile & 11.4 \(\pm\) 0.3 & - \\ \hline Benzaldehyde & 25.5 \(\pm\) 0.3 & 106, 77, 51 \\ \hline Butanoic acid & 16.7 \(\pm\) 0.3 & 88, 73, 60 \\ \hline Butanol & 15.5 \(\pm\) 0.2 & 56, 43, 41 \\ \hline Decan & 26.2 \(\pm\) 0.3 & 142, 85, 57 \\ \hline Dichloromethane & 13.2 \(\pm\) 0.2 & 84, 49 \\ \hline Dimethyl sulfoxide & 25.0 \(\pm\) 0.2 & 78, 63, 45 \\ \hline Dodecane & 28.3 \(\pm\) 0.3 & 170, 85, 57 \\ \hline Ethyl ether & 8.4 \(\pm\) 0.4 & 74, 59, 43 \\ \hline Ethylenediamine & 12.2 \(\pm\) 0.4 & 60, 59, 43 \\ \hline Hexanal & 19.6 \(\pm\) 0.2 & 82, 72 \\ \hline Hexanoic acid & 22.4 \(\pm\) 0.2 & 87, 60 \\ \hline Octanal & 20.8 \(\pm\) 0.2 & 84, 57 \\ \hline Octanol & 28.0 \(\pm\) 0.3 & 84, 70 \\ \hline Propanal & 17.9 \(\pm\) 0.2 & 59, 57 \\ \hline Propylamine & 10.7 \(\pm\) 0.2 & 59, 41 \\ \hline Toluene & 17.5 \(\pm\) 0.2 & 91, 65 \\ \hline \end{tabular}
\end{table} 
Table 3: Selected VOCs RTs and _m/z_ ratios. The reproducibility of the investigated analytical procedure was evaluated in terms of intraday (_n_ = 3) and interday (_n_ = 3, over 7 days) RSD %, using standard solutions of the considered analytes at amount levels equal to five, ten, and twenty times the respective LOQs values. Experimental results are presented in Table 5.