esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Validation of MPY Data Through Immersion Testing of Corrosion Coupons  
The immersion test was conducted to verify the MPY values obtained from the LPR sensor by comparing them with the actual material loss measured on corrosion coupons. The coupons were immersed in a neutral 3.5% NaCl solution at 25 \({}^{\circ}\)C for up to 60 h. After the immersion period, the corroded surface profiles were analyzed using a 3D laser confocal microscope. The microscope provided detailed surface topography, measuring the difference in elevation between the masked area (non-corroded) and the corroded area, indicating the extent of metal loss due to uniform corrosion. This vertical depth difference was then converted into MPY values for comparison with the LPR sensor readings. The measured depth was converted to MPY values according to the relationship to Equation (7).  
\[MPY=um/year\times 0.03937 \tag{7}\]  
In Figure 7, the colors represent the difference in elevation between the masked area (non-corroded) and the corroded area. As shown in Figure 7, the corrosion profiles illustrate the smooth transition between the masked and corroded areas, confirming that the corrosion observed corresponds to general corrosion (uniform corrosion) rather than localized corrosion such as pitting and crevice corrosion. The measured depth ranged between 23 \(\upmu\)m and 47 \(\upmu\)m, though these specific values are not significant for analysis. Instead, the masked area serves as a stable reference point to accurately measure the vertical material loss in the corroded regions, which is more relevant for evaluating uniform corrosion behavior. The MPY values derived from these measurements were then compared with the LPR sensor readings. For example, profile (a) shows an actual CR of 119 MPY, while the LPR sensor reported 127 \(\pm\) 10 MPY, demonstrating good agreement. Similarly, in profiles (c) and (d), the actual CR values were 186 and 174 MPY, respectively, with corresponding LPR readings of 171 \(\pm\) 17 MPY and 171 \(\pm\) 7 MPY, reflecting the reliability of the sensor across multiple conditions. These results confirm that the LPR sensor provides reliable estimates of CR, even in short-term tests, with minor discrepancies attributed to surface roughness and measurement variability.  
The immersion test validates the practicality of LPR sensors for real-time corrosion monitoring, as the instantaneous MPY values closely match the material loss recorded during immersion. The consistent performance of the sensor demonstrates its capability to detect general corrosion trends effectively, making it suitable for use in environments such as marine cooling systems where continuous corrosion monitoring is essential.
## 4 Conclusions and Future Work  
In conclusion, this paper proposes a novel few-shot electrical image classification algorithm based on knowledge distillation. By leveraging the few-shot learning method and employing global and local knowledge distillation, our algorithm achieves high classification accuracy with only a limited number of image samples. The results obtained on the newly introduced EEI-100 dataset demonstrate that our method achieves a remarkable prediction accuracy of 94.12% using just 5-shot images. The lightweight and high-performance nature of our model enables its practical application in the online inspection of electrical equipment in smart grids, effectively enhancing the efficiency of detection and maintenance in the power system. Furthermore, the training and deployment of our model do not impose significant hardware requirements, making it accessible to a wide range of researchers.  
Regarding future work, we plan to explore a pre-training method to separate the foreground and background, as different backgrounds may negatively affect distillation. Additionally, we plan to use a multi-stage fusion of global and local features during the distillation process. This can provide a better understanding of the underlying structure of the complex model and the relationship between different stages of the model.  
Conceptualization, B.Z. and J.G.; methodology, B.Z.; software, C.Y.; validation, B.Z. and J.Z.; formal analysis, B.Z.; investigation, X.Z.; resources, J.Z.; data curation, X.Z.; writing--original draft preparation, B.Z.; writing--review and editing, J.G. All authors have read and agreed to the published version of the manuscript.  
This research was supported in part by the National Natural Science Foundation of China under Grant No. U2066203 and No. 61973178, and in part by the Key Research & Development Program of Jiangsu Province under Grant No. BE2021063.  
Not applicable.  
The dataset proposed in this paper can be obtained from the author with a reasonable request.  
The authors declare no conflict of interest in preparing this article.
## 2 Results and Discussion
### Protein Nutritional Quality  
Since black cherry seeds contain higher levels of protein (\(37.95\%\pm 0.16\%\)) than other seeds, their protein nutritional quality was assessed. Amino acid composition data are presented in Table 3. It is important to mention that in this experiment tryptophan was not determined.  
Another protein quality measure is digestibility. Differences among the _in vitro_ protein digestibility values of raw and toasted black cherry seeds were not significant (\(88.12\%\pm 0.72\%\) and \(89.40\%\pm 1.32\%\), respectively). These values were similar to that of almonds (\(90.15\%\pm 0.85\%\)), however they were lower than those of peanuts (\(94.06\%\pm 0.78\%\)) and casein (\(98.51\%\pm 0.82\%\)), which was used as control. It has been reported that _in vitro_ protein digestibility values greater than \(80\%\) are related to an efficient amino acid bioavailability [27]. Therefore, these results suggest that black cherry seed proteins are highly bioavailable.  
Considering these findings, the protein digestibility-corrected amino acid score (PDCAAS) was determined. This method is accepted as the most recognized approach for assessing the protein quality of foods [30]. Every essential amino acid receives a score, but the final PDCAAS value corresponds to that of the limiting amino acid. The highest PDCAAS value for a given protein is 1.0, which indicates that a protein provides adequate amounts of all the essential amino acids [31]. Table 4 shows that lysine is the limiting amino acid in _P. serotonin_ seeds, therefore, PDCAAS values for raw and toasted black cherry seeds protein are 0.13 and 0.18, respectively. These values are lower than those reported for  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Amino** & **Raw Seeds mg/g** & **Toasted Seeds mg/g** \\
**Acid** & **Protein** & **Protein** \\ \hline Asp & 112.29 & 116.97 \\ Glu & 256.84 & 273.73 \\ Ser & 32.84 & 42.11 \\ His & 21.60 & 21.29 \\ Gly & 37.43 & 38.82 \\ Thr & 52.85 & 59.16 \\ Arg & 84.24 & 87.42 \\ Ala & 41.47 & 44.06 \\ Tyr & 48.75 & 60.99 \\ Met & 8.93 & 9.83 \\ Val & 45.48 & 45.62 \\ Phe & 48.64 & 52.00 \\ Ile & 39.17 & 40.33 \\ Leu & 75.10 & 82.11 \\ Lys & 8.85 & 11.17 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Protein amino acids composition of raw and toasted black cherry seeds.  
almonds (0.23) [17] and peanuts (0.69) [32]. These results suggest that black cherry seeds could be a complementary source of proteins.
# Relief Aircraft Dispatch Strategies Based on Different Levels of Information Sharing Systems
## 6 Numerical Experiments
### Result of Numerical Experiment
#### 6.2.4 Implications for Air Rescue Operations  
From the results of the numerical experiment, we can provide the following implications for achieving more efficient operations on air rescue:  
1. The information-sharing level or communication system in air relief activities is extremely important, and the level of the information-sharing system determines the optimal aircraft dispatch strategies. Based on this numerical experiment, different agents (aircraft, airports, and shelters) and involved organizations (medical teams, fire departments, response headquarters, etc.) could be connected by an integrated information-sharing system that could improve relief efficiency.
2. To determine which strategies must be implemented, it is necessary to consider the information sharing level, demand distribution, and disaster level. Our simulation has proved that the total amount and distribution of demands could affect the result of dispatch strategies. Therefore, a suitable strategy must be employed according to different scenarios.
3. In a single relief activity, the demand distributions and communication systems could vary with the relief phases. For example, at the beginning of the relief, the information system used is \"Level one\". After communication devices recovering, the information sharing level is improved.
## 4 Results
### System Performance
The integration of an IP camera alongside the radiometers proved particularly useful in identifying these unforeseen problems and may be useful for other causes of data contamination such as boats, floating debris/vegetation, or other unusual conditions in the radiometer field of view (Figure 5) since the radiometer gives only spatially integrated information. However, image analysis is presently subjective and is not easy to automate.
## 4 Multiplexers Based on Cyclically Used Michelson Interferometeres
Finally, the \(\text{LP}_{11b}\) mode is previously obtained from a \(90^{\circ}\)-rotated \(\text{LP}_{11a}\) one emerging from the interferometer when a \(\text{LP}_{01}\) mode from a new single mode fiber is introduced into P1. In short, the final \(\text{LP}_{21a}\) mode is obtained after four passes through the interferometer: two of them to obtain the mode itself and multiplex it with the final \(\text{LP}_{01}\) mode and the last two passes to multiplex them with the other three modes. It is worth highlight that we can remove the phase plates from these systems and to replace the input single mode fibers with few mode fibers. In this case there is no mode conversion but each mode can be managed separately. So we can do the (de)multiplexing and the mode conversion (if necessary) in two different stages. For example we can drop and add a mode of a few mode fiber with two systems similar to that of Figure 5 without phase plate. The first one should act as a demultiplexer putting each mode in its respective fiber from 1 to 4 (now few mode fibers). The desired mode is extracted (drop) and the rest are coupled to the corresponding inputs of the second system which acts as a multiplexer. We can introduce a new signal (add) in the proper mode of the free input fiber of the second system. The new signal will be incorporated with the other three in the output few mode fiber. Even more, both systems can be merged into one by sharing the interferometer, doubling the number of fibers in each port and connecting them properly. Figure 5: Multiplexer similar to that of Figure 4, but cyclically using a single interferometer. Other interferometric multiplexers based on MZI can be redesigned as Michelson interferometers. However, the interferometers using two Dove prisms [12] or those based on image inversion with spherical lenses can not multiplex several pair of modes simultaneously, because the emerging beams are parallel only if the input fiber is on the optical axis. Therefore they can not be used cyclically. On the contrary, those using cylindrical lenses, for instance in order to generate an image inversion in only one direction, do can multiplex several pairs of modes since they have an invariant behavior along the perpendicular direction. Similarly the refractive Gouy phase shifters with cylindrical lenses [15] can take advantage of this cyclic use to enlarge the SDM to radial modes more economically. Their adaptation to the Michelson configuration requires two simple modifications. First, the collimating system must now generate a slightly convergent beam whose waist must be located at the reference mirror. And secondly, just the cylindrical lens must be inserted at the proper distance of the mirror of the other arm. Note that since only one reflection occurs in each arm, the interferometer is already polarization insensitive, so the Fresnel retarder is unnecessary in this case.
# Applications of Plasma Produced with Electrical Discharges in Gases for Agriculture and Biomedicine
## 2 Plasma as a Medium for Application in Agriculture and Biomedicine
### Agricultural and Soil Protection Problems
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Kind of Discharge** & **Main Applications** & **Power Supply** \\ \hline Dielectric barrier & Ozone synthesis, methane conversion, & AC voltage of mains and \\ discharges DBDs & sterilisation, biomedicine and agriculture & increased frequency \\ \hline DBDs with & Decomposition of SOx and NOx, & DC, pulse power (PP) and AC \\ dielectric/ferroelectric packing & VOCs conversion & \\ \hline Corona discharges (CDs) & Sterilisation, disinfection, & PP and DC \\ Barrier corona discharge (BCD) & medical applications & \\ \hline Atmospheric pressure plasma jet APPJ, & & \\ Plasma needles (PNs) & & \\ \hline Surface discharges (SDs) & Neutralisation of nitrogen oxides and & \\  & volatile organic substances & Increased and high-frequency AC \\ \hline Thermal arc discharges (ADs) & Chemical syntheses, & \\ Microwave discharges (MWDs) & melting, welding, & DC and AC voltage \\ Plasmatrons & surface treatment, waste incineration & radio and microwave frequency \\ Plasma torches (PTs) & and vitrification & \\ \hline  & Toxic gas neutralisation, SOx and NOx & \\ Gliding arc discharges GADs & treatment, and biomedical and & DC, PP and AC PS \\  & agricultural applications & \\ \hline \hline \end{tabular}  
* Based on [5; 9] and the authors’ own study.  
\end{table} 
Table 2: Plasma reactors, their applications, and their power supply **. have contributed to ozone layer depletion, degradation of soil and chemical residues in food. Other methods, including autoclaving (moist heat), dry heat, and microwaves have been tried as alternatives to chemical fumigation. Soil treatment using pesticides is an effective method for resisting the spread of disease in soil. However, pesticide residues in groundwater, caused by the overuse of chemicals, have become a serious issue in agriculture. From the environmental point of view, alternative methods of soil treatment are being sought. Ozone is a powerful oxidising agent and a much more effective disinfect than chlorine compounds. A mixture of water-mist with ozone produces very reactive intermediate hydroxyl free radicals, which are much stronger oxidising agents than ozone itself, and have exciting potential in soil and plant treatment, such as pest removal from agricultural soil [12; 13; 18; 19; 20; 80; 81; 82; 83; 84].
# Evolutionary Approach to the Euclidean Steiner Tree Problem in n-Space
## 1 Introduction
### Definitions
Therefore, adding the fifth vertex would be possible in five ways. Generally, adding the \(k\)-th Steiner point is possible in \(2(k-1)+1\) ways, for \(k=1,2,...,p-2\), assuming the first Steiner point connects three terminals. The number of possible full topologies increases very rapidly with \(p\) and is given by the following formula:  
\[2^{-(p-2)}\frac{(2p-4)!}{(p-2)!}\]  
This reflects the combinatorial complexity of the problem, illustrating how the space of potential solutions expands with each additional terminal. Starting from \(p=12\), this value is greater than \(p!\) (654,729,075 vs. 479,001,600). Figure 3: An example of a full Steiner topology (**top**) and its degeneracy (**bottom**) for five terminals \(t_{1}-t_{5}\) (gray circles). Additional Steiner points are \(s_{1},s_{2}\) and \(s_{3}\) (white circles).
# Experimental Study on Milling CFRP with Staggered PCD Cutter
## 5 Conclusions  
1. The wear zone of the staggered PCD cutter is mainly concentrated on the cutting edge, so the cutting-edge wear radius is introduced to characterize tool wear. With the increase of the cutting length, both the cutting-edge radius and the milling force increase gradually as effect of the abrasive wear mechanism. Nonetheless, the main cutting force increases most obviously, while the axial force varies relatively little.
2. There are obvious differences in the machining surface topography in all fiber layer regions. Fiber bundles pulling out and forming hole defects first occurs in the fiber layer region of 90\({}^{\circ}\), tiny grooves mostly appear in the fiber layer region of 0\({}^{\circ}\), and the machining surfaces in the fiber layer regions of 45\({}^{\circ}\) and 135\({}^{\circ}\) are smoother. In addition, with an increase of milling length, the surface topography in all fiber layer regions gradually gets more complex.
3. The types of surface defect change obviously as the tool wear proceeds. When the wear degree of the cutting edge is small, the fiber fracture of the surface machined with the staggered PCD cutter is relatively flat. With the intension of the cutting-edge wear, the fiber fracture topography becomes irregular, the resin coating and backfill occur locally, and defects such as fiber bundle exposure, and grooves and holes appear; thus, the surface topography deteriorates gradually.
4. Compared with the straight-teeth PCD cutter, the cutting edge of the staggered PCD milling cutter can form a sinistral-decstral inclination angle structure, which can make the workpiece bear two-way forces, inhibit delamination defects, and improve the cutting conditions, while the inclined cutting edge can increase the contact area between the tool and the workpiece, reduce the load on the unit cutting edge, and prolong the tool life. Thus, the staggered PCD cutter shows better cutting performance, and its wear resistance and machining quality have improved significantly.  
Figure 10: Comparison of the wear morphologies between the two PCD cutters: (**a**) staggered PCD cutter; (**b**) straight-teeth PCD cutter.  
**Acknowledgments:** The authors would like to acknowledge the support of the International S&T Cooperation Program of China (Grant No. 2014 DFA70400), the National Natural Science Foundation of China (Grant No. 51475125), the Natural Science Foundation of Heilongjiang Province (Grant No. E2016047), the Program for Harbin Science and Technology Innovation Talents (Grant No. 2015 RQQXJ039), and the Distinguished Young Talents Program of Harbin University of Science and Technology.  
**Author Contributions:** [PERSON] and [PERSON] designed the tool and experiment. [PERSON], [PERSON] and [PERSON] performed the experiment. [PERSON], [PERSON], [PERSON] and [PERSON] analyzed the data. [PERSON] and [PERSON] wrote the paper.  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 3 Results and Discussion
### Checking the Feasibility of a Moving-Bed RFR
The variation of the \(\eta_{\text{s}}\) and the \(\eta_{\text{G}}\) with time for both operating modes can be found in Figure A8 in Appendix A. Moreover, the phenomena of \"cavity\" and \"pinning\" may occur in a moving-bed RFR when the gas flowrate exceeds a certain value. These phenomena may lead to a reduced capture efficiency [50; 51]. A \"cavity\" can be formed between the inflow wall and sorbent, as the drag force between the gas flow and sorbent increases when the gas flow increases. Due to the formation of a cavity, the effective bed length (in the direction of the gas flow) decreases and gas can bypass part of the sorbent bed; further maldistribution of the gas flow may occur. Indeed, we observed some cavities adjacent to the inflow wall. In addition, the sorbent's downward movement was non-uniform. Decreasing the gas flow rate visually avoided the appearance of cavities, but this leads to a lower CO\({}_{2}\) supply rate and a longer effective \(\text{t}_{\text{sto}}\). When the gas flow increases further, the gas flow exerts stronger normal stress to the particle, corresponding with an increment in the frictional force between the particle and the outflow wall. The particle will be \"pinned\" to the wall if the friction force is sufficient to hold the particle weights, and the downward movement of the particle stops. We observed that the \"pinning\" appeared when the feeding gas flow was further increased beyond 200 m\({}^{3}\)/h. The phenomena discussed above make the moving-bed operation practically challenging. More work is needed to investigate whether this can be resolved by modifying the geometry or operating conditions. The time required to fill and empty the RFR is less than two minutes. In comparison with the adsorption time, this operating time loss (less than 5%) is significantly lower than the loss in working capacity when switching to continuous operation. Considering the above issues, the RFL process will used a fixed-bed RFR intermittently filled with freshly regenerated sorbent and emptied towards the desorber (after sorbent saturation) as the preferred operating method for further study.
## 4 Proposed Model Structure
The hidden layer encodes and compresses the input feature vector of the flow table according to Equation (1) [33]:  
\[encoder=W_{1}x_{i}+b_{1} \tag{1}\]  
where \(W_{1}\) is the weight connecting the input layer and the hidden layer, \(x_{i}\) is the input feature vector of the \(i\)-th flow table, and \(b_{1}\) is the bias of the hidden layer neuron. After the encoding is completed and determined on the output result of the hidden layer, the output layer is decoded and reconstructed to produce an output of the same size as the input layer neuron, using Equation (2) [33]:  
\[decoder=f(W_{2}(encoder)_{i}+b_{2}) \tag{2}\]  
where \(f\) is the activation function, \(W_{2}\) is the weight between the hidden and the output layer, \((encoder)_{i}\) is the stream table feature vector compressed by the hidden layer coding, and \(b_{2}\) is the bias of the output layer neuron. Finally, the goal of training the self-encoding model is achieved by minimizing the loss function using Equation (3) [34]:  
\[loss=\sum_{i=1}^{n}\left(x_{i}-(decoder_{i})\right)^{2} \tag{3}\]  
where \(n\) is the number of flow table feature vectors, \(x_{i}\) is the input flow table feature vector, and \((decoder_{i})\) is the flow table feature vector output by \(x_{i}\) through the self-encoding model. To achieve dimensionality reduction and feature extraction when constructing the model, we intend to use the deep stack auto-encoding model [35]. The deep stack auto-encoding model is constructed by stacking the input layer and hidden layer of self-encoding models' layer by layer. Each self-encoding model generates a hidden layer. After the flow table feature vector is learned by the first self-encoding model, the compressed abstract features are obtained in its hidden layer, and the hidden layer of the first self-encoding model is used as the input layer of the second self-encoding model. The learning of the second auto-encoding model indicates that more abstract features are obtained after further compression in its hidden layer. Then, the text of the second auto-encoding model is used to achieve the purpose of dimensionality reduction and abstract feature extraction when constructing the model. When building a deep-learning model, the use of convolutional layers of different depths will have a significant impact on the detection accuracy of the model, and training the model leads to better performance. Two models have been investigated, one based on multilayer convolutional neutral networks (CNN) with Max pooling, and the second based on bidirectional long short-term memory (BDLSTM). We intend to use a batch size of 50 for model training by default. We will test CNN models containing three convolutional layers, two max pooling layers, one flatten, and two dense layers (as described in Table 1). The BDLSTM model has one LSTM and four dense layers (the structure is provided in Table 2).