esa-sceva/satcom-chunk-collection huggingface dataset:
# PAM-UNet: Enhanced Retinal Vessel Segmentation Using a Novel Plenary Attention Mechanism
## 3 Experiments
### Evaluation Metrics  
To evaluate the performance of PAM-UNet, we selected Accuracy (Acc), Specificity (Sp), Sensitivity (Se), F1-score and AUC as evaluation metrics. The formulas for these metrics are shown in Equations (10)-(13).  
\[Acc=\frac{TP+TN}{TP+TN+FP+FN} \tag{10}\]  
\[Se=\frac{TP}{TP+FN} \tag{11}\]  
\[Sp=\frac{TN}{TN+FP} \tag{12}\]  
\[\text{F1}=\frac{2 TP}{2 TP+FN+FP} \tag{13}\]  
where TP represents the number of pixels correctly classified as vessels, TN represents the number of pixels correctly classified as background, FP represents the number of pixels incorrectly classified as background, and FN represents the number of pixels incorrectly classified as vessels. Acc represents the proportion of correctly labeled vessel and background pixels out of the total pixels in the entire image. Sp represents the proportion of pixels correctly predicted as vessels among all pixels that are actually vessels. Se represents the proportion of pixels correctly predicted as background among all pixels that are actually background. F1 can be used to evaluate a classifier in a more comprehensive  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Dataset** & **Image Size** & **Number of Images** & **Mask** & **Training/Testing** \\ \hline DRIVE & \(584\times 565\) & 40 & ✓ & 20/20 \\ \hline CHASE\_DB1 & \(999\times 960\) & 28 & ✓ & 20/8 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Detailed dataset information.  
Figure 6: Image preprocessing.  
way. The larger F1 is, the higher the quality of the model is. In addition, AUC reflects the relationship between Se and Sp and is used to characterize the predictive accuracy of vessels segmentation results.
## 3 Results and Discussion
### Effect of FNGB and FGB Ethanol Extracts on the Survival Rate and Heart Rate of Zebrafish Embryos  
In this experiment, besides observing whether the samples would affect the zebrafish embryo morphology, the percentage of deaths and malformations of zebrafish embryos caused by different concentrations should also be assessed. No significant difference in the survival rate of zebrafish embryos was observed compared with that in the control group (\(p>0.05\)) when the concentration of FNGB ethanol extract (Figure 5A) or FGB (Figure 5B) was 10-100 \(\mathrm{\SIUnitSymbolMicro g}\)/mL, and the survival rate was between 89.72-100.40%. Meanwhile, under an FNGB or FGB concentration of 250 \(\mathrm{\SIUnitSymbolMicro g}\)/mL, the survival rate of zebrafish embryos was significantly reduced by 78.97% and 68.77% (\(p<0.05\)), respectively, compared with that in the control group.  
During the sample concentration tests on zebrafish embryos, in addition to investigating whether the samples would cause death or malformations of zebrafish embryos, the impact on the heart rate was also observed to ensure the sample applicability. The results are shown in Figure 5C,D. When zebrafish embryos were incubated with FNGB or FGB ethanol extract at 10-100 \(\mathrm{\SIUnitSymbolMicro g}\)/mL, the heart rate was 93.75-102.21% and 102.12-105.93%, respectively, and there were no significant differences from that in the control group (\(p>0.05\)). However, when the sample concentration was 250 \(\mathrm{\SIUnitSymbolMicro g}\)/mL, the heart rate of zebrafish embryos was 10-100 \(\mathrm{\SIUnitSymbolMicro g}\)/mL, and the survival rate was between 89.72-100.40%. Meanwhile, under an FNGB or FGB concentration of 250 \(\mathrm{\SIUnitSymbolMicro g}\)/mL, the survival rate of zebrafish embryos was significantly reduced by 78.97% and 68.77% (\(p<0.05\)), respectively, compared with that in the control group.  
Figure 5: Effects of ethanol extracts from fermented-nongermination black soy milk and fermented-germination black soy milk on survival rate (**A**,**B**) and heart rate (**C**,**D**) in zebrafish embryos. Zebrafish embryos were treated with several concentrations’ ethanol extracts of fermented-nongermination black soy milk or fermented-germination black soy milk (10–250 \(\mathrm{\SIUnitSymbolMicro g}\)/mL) from 7 to 55 hpf. The survival rate and heart rate were determined under an inverted microscope after 48 h treatment. The data are presented as means \(\pm\) SD (\(n=3\)). Values with different uppercase letters were significantly by Duncan’s multiple range tests (\(p<0.05\)). PTU, 0.2 mM phenylthiourea; hpf, hours post fertilization; FNGB, fermented-nongermination black soy milk; FGB, fermented-germination black soy milk.  
byros decreased significantly to 67.28% and 82.63% (\(p<0.05\)) compared with that in the control group.  
In summary, when the concentration of FNGB or FGB ethanol extract was below 100 ug/mL, no malformations, death, or decreased heart rate was observed in the zebrafish embryos. Subsequent experiments would use 100 ug/mL as the upper limit concentration of the treatment group.
# A Data-Driven State Estimation Based on Sample Migration for Low-Observable Distribution Networks
## 5 Conclusions  
This study addresses a data-driven state estimation based on sample migration for low-observable distribution networks. Based on sample migration technology, knowledge from high-observable distribution networks is transferred to low-observable distribution networks, enabling effective state estimation. Considering the results from the actual distribution network, the following conclusions can be drawn.  
Figure 8: Comparison of average absolute error of state estimation results of an actual distribution network system: (**a**) comparison of average absolute error of voltage magnitude; (**b**) comparison of average absolute error of voltage angle.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Testing System**} & \multicolumn{3}{c}{**Calculation Time in One Section/s**} \\ \cline{2-4}  & **Proposed Method** & **WLS** & **WLAV** \\ \hline
10 nodes & 0.0094 & 0.0019 & 0.0038 \\
26 nodes & 0.0099 & 0.0075 & 0.0112 \\
100 nodes & 0.0105 & 0.0192 & 0.0547 \\ \hline \hline \end{tabular}
\end{table}
Table 3: The state estimation time under different algorithms.  
In low-observable distribution networks, the proposed method enhances the estimation accuracy compared to traditional methods, such as WLS and WLAV. It effectively addresses issues of low estimation accuracy and estimation failure due to insufficient measurements in traditional methods. Additionally, it improves the model's generalization ability.
2. The method demonstrates better robustness and instantaneous performance in online SE compared to traditional WLS and WLAV. By incorporating bad data into the training samples and utilizing a data-driven SE model, the proposed approach shows superior performance in handling real-time estimation tasks.  
Future work will consider system faults, variations in power sources and loads, and differences in line parameters, further extending the applicability of the proposed method.  
Conceptualization, H.J. and C.W.; methodology, L.W. and M.H.; software, Y.X. and M.H.; validation, J.C., C.W. and Y.X.; formal analysis, J.C. and Y.X.; investigation, H.J.; resources, H.J., Y.X. and L.W.; writing--original draft preparation, M.H.; writing--review and editing, H.J. and L.W.; visualization, C.W.; supervision, J.C. and Y.X.; project administration, Y.X.; funding acquisition, H.J., J.C. and Y.X. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Technology Project of State Grid Jiangsu Electric Power Co., Ltd., China [grant number: J2023007].  
No new data were created or analyzed in this study.  
Authors [PERSON], [PERSON], [PERSON] and [PERSON] are employed by the company State Grid Jiangsu Electric Power Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
###### Abstract  
The recharge efficiency during artificial groundwater recharge (AGR) is reduced primarily by clogging that is triggered by suspended particles. However, there are loopholes in the current standards of recharge-water quality for clogging control during AGR, and the threshold values of turbidity to prevent clogging have not been reasonably determined. In this study, secondary effluents from wastewater treatment plants (WWTPs) were injected into saturated sand columns to simulate the process of AGR. Batch experiments under different turbidity conditions were conducted, and the numerical modeling of particle transport and deposition was performed to assess the clogging processes. Theories of single-collector contact and interfacial interaction energy were applied to elucidate possible microcosmic mechanisms. The results showed that the diluted secondary effluent (SE) with turbidities of 0.540 \(\pm\) 0.050, 1.09 \(\pm\) 0.050, and 1.84 \(\pm\) 0.060 NTU caused considerable clogging in the porous media, which decreased the relative hydraulic conductivities (\(K/K_{0}\)) by 13.2%, 17.6%, and 83.6%, respectively. The filtered SE with a turbidity of 0.160 NTU did not cause clogging, and \(K/K_{0}\) was reduced by only 1.70%. The clogging was attributed to the deposition of suspended particles in the sand matrix because they have a high collision efficiency (0.007-1.98) and attachment efficiency (0.029-0.589 \(k_{\text{B}}\)T). Finally, this paper recommends that the turbidity of the recharge water should not exceed 0.500 NTU during AGR practices.  
artificial groundwater recharge; physical clogging; secondary effluent; suspended particles; turbidity; threshold +
Footnote †: journal: water  
0000-0002-4891-3888][PERSON]  
1 School of Environment, Northeast Normal University, No. 2555, Jingyue Street, Changchun 130117, China 1
## 1 Introduction  
Adhesive structural bonding is widely used in mechanical and aerospace industries [1]. In recent years, there has also been a growing interest in the use of the adhesive connections in the building industry [2]. In civil engineering structures, some applications of structural adhesives are of particular importance, such as the strengthening of existing concrete members [3, 4], hybrid composite-concrete beams [5] or adhesive anchors [6]. A relatively new idea is the use of structural adhesives as shear connectors in steel-concrete composite beams (e.g., [7, 8, 9]). The shear strength of adhesive joints in steel-concrete composite systems has been evaluated by many researchers (e.g., [PERSON] [10], Barnes & Mays [11], [PERSON] et al. [12], [PERSON] et al. [13], [PERSON] et al. [14], [PERSON] et al. [9], [PERSON] et al. [15], [PERSON] et al. [16], [PERSON] et al. [17]).  
With the increasing use of adhesive connections, there is a need to develop methods of non-destructive evaluation and damage detection at an early stage of degradation. One of the most efficient techniques to characterize a contact between connected components is a method utilizing the phenomenon of elastic wave propagation. Ultrasonic waves have been successfully used in the evaluation of bolted connections between metal elements [18, 19, 20], adhesive connections between metal elements [21, 22, 23] or adhesive connection between concrete substrate and repair materials [24, 25, 26]. Recently, studies of damage evaluation based on the concept of ultrasound monitoring have been reported The examples of their application include monitoring of damage in concrete samples [27],reinforced concrete beams [28; 29; 30] or in an adhesive lap joint of metal elements [31]. However, the literature on the inspection of steel-concrete adhesive joints using ultrasonic waves is limited. Only two recent papers [32; 33] concern the problem of diagnostics of interface bonding between steel and concrete. In addition, in both of them, steel-concrete specimens with artificially introduced debonding were investigated and no external load was considered. To the best of the author's knowledge, there is no research on the non-destructive testing of steel-concrete adhesive connections during mechanical degradation.  
The study presents a novel approach to the failure monitoring and condition assessment of the adhesive connection between steel and concrete. Experimental investigations are performed on nine push-out specimens consisting of a concrete cube with two adhesively bonded steel plates. The diagnostic procedure uses wave propagation signals registered during mechanical degradation and damage indices based on the Sprague and Gears metric. The influence of different failure modes on obtained results is analyzed.
## 3 Proposed Methodology
### Data Annotation Process
#### 3.2.3 Inter-Rater Agreement Evaluation  
**Cohen's Kappa:**  
After annotating the data, we conducted an examination of the inter-rater agreement. The analysis, employing Cohen's Kappa [20], revealed an impressive average value of 0.91 Kappa. This indicates very strong agreement among the annotators, as demonstrated in Table 2.  
Figure 5: Data annotation process.  
Figure 6: Top 10 most frequent vulgar words in the dataset.  
**[PERSON]'s alpha:** Using [PERSON]'s Kappa score we can see that the annotators were in almost perfect agreement. To double-check the annotation agreements, we calculated the inter-rater agreement scores using Krippendorff's alpha [21]. As a result, we achieved an average agreement value of 0.914, demonstrating a significantly high agreement among annotators (refer to Table 3).  
With the above two inter-rater agreements scores, we verified that there was a very high agreement between the annotators during the data annotation process. With the assurance of good quality guidelines and annotators with professional backgrounds, we can state that the created dataset can be considered high quality.
## 2 The Bus Synchronization Problem
### Mathematical Formulation
#### Variables
Complementary, Constraint (8) forces \(a_{r}^{h}\) to be \(0\) when a trip is scheduled with a departing time beyond the planning horizon, i.e., \(h_{r}^{h}>T\); thus, it is not  
\[\text{min}\quad FO_{c}=\sum_{h\in H}\mathcal{C}b^{h}\cdot\left( \sum_{r\in R^{h}}q_{r}^{i}\right) \tag{2}\]5 Actors and entities of a synchronization event with the path of vehicles and users indicated in dashed blue and red lines, respectively. part of the solution. To summarize, only those trips scheduled with a departing time within the planning horizon are considered valid. The trips scheduled beyond this time are unused trips for that bus line. Whenever the s-th trip of \(g\in H\) (i.e., \(s\in R^{\delta}\)) is not to be scheduled, passengers from any other trip \(r\in R^{h}\) at any zone \(b\in B\) cannot transfer to it. The last fact is captured by Constraint (9). The values for \(N_{h}\) with \(h\in H\) are the result of the QoS model in Section 2.2. For every line \(h\) in the system, Constraint (10) schedules--at least--the minimum number of trips required to statistically prevent congestion. Constraints (11) and (12) impose the time interval between two consecutive trips of the same bus line (i.e., the headway) to fall within the predefined boundaries of \(Hd_{h}^{min}\) and \(Hd_{h}^{max}\), respectively. Similarly, Constraint (13) enforces that the first trip of each bus line \(h\in H\) in the planning horizon, i.e., \(x_{1}^{h}\), departs in the interval \([0,Hd_{h}^{max}]\). Finally, Constraints (14) succinctly assert the nature of the variables. The presence of products \(z_{rsb}^{hg}(x_{r}^{h}-x_{r-1}^{h})\) in the objective function renders the formulation akin to a Mixed-Integer Quadratic Programming (MIQP) problem. Addressing non-linear programming presents a distinct challenge compared to linear problems, usually requiring a larger amount of computational resources [38; 39]. To tackle this issue, the variable transformation proposed by [40] is used. Let us define \(y_{rsb}^{hg}\) as \(z_{rsb}^{hg}(x_{r}^{h}-x_{r-1}^{h})\). After the redefinition of variables, the linear objective becomes \(\frac{\sum_{b\in B}\sum_{d\in B}\sum_{r\in R^{h}}\sum_{r\in R^{h}}\sum_{r\in R ^{h}}y_{r-1}^{hg}}{T}\). To ensure equivalence between the original objective and the modified version, two equations are added for each \(y_{rsb}^{hg}\) variable: (i) \(y_{rsb}^{hg}\leq(x_{r}^{h}-x_{r-1}^{h})\) and (ii) \(y_{rsb}^{hg}\leq Hd_{h}^{max}\cdot z_{rsb}^{hg}\). It is important to highlight that within a maximization context, variables \(y_{rsb}^{hg}\) strive to attain the highest possible value. Thus, the third restriction of method proposed by [40]--to force \(y_{rsb}^{hg}\) to adopt value \((x_{r}^{h}-x_{r-1}^{h})\) when \(z_{rsb}^{hg}=1\)--is not necessary. In this manner, the introduced variable transformation renders the problem linear, akin to Mixed Integer Linear Programming (MILP), alleviating the computational complexities associated with quadratic terms.
# Design, Experiment, and Improvement of a Quasi-Zero-Stiffness Vibration Isolation System
## 2 The QZS Vibration Isolation System  
The QZS vibration isolation platform is presented in Figure 1. It was constructed by using a negative stiffness spring with a positive stiffness spring in parallel, where the negative stiffness was produced by two axial-magnetized ring magnets.  
Figure 1: Three-dimensional structure diagram of the proposed quasi-zero-stiffness (QZS) vibration isolator.  
As shown in Figure 1, the QZS vibration isolator was mainly composed of a linear spring, an inner ring magnet, and an outer ring magnet, an object. Furthermore, other subsidiary parts were used as well, which included intermediate shaft 1, intermediate shaft 2, linear motion bearing 1, linear motion bearing 2, and the adjustable screw nut. The two linear motion bearings guaranteed a straight-line movement of the platform and reduced the friction. The two intermediate shafts connected the positive stiffness spring and the negative stiffness spring in parallel, while an adjustable screw nut was used to regulate the relative displacement. All of the parts mentioned above made up the QZS vibration isolation system.
## 5 Conclusions
The quick estimation of NRT flooding and damaged rice production should be improved when Sentinel 1B is completed and the updated GSO dataset is available for the RRD region. Finally, when flooding occurs, not only rice but also other crops are affected. The usage of remote sensing to monitor other crops under flooding will be considered. Conceptualization, A.P. and T.T.N.N. ; Methodology, A.P., C.D.M. and T.T.N.N. ; Software, A.P., D.N.H. and C.D.M. ; Validation, A.P. ; Investigation, A.P. and C.D.M. ; Resources, H.Q.B. and T.T.N.N. ; Writing--original draft preparation, A.P. and T.T.N.N. ; Writing--review and editing, A.P. and T.T.N.N. ; Visualization, A.P. and T.T.N.N. ; Supervision, C.D.M., T.T.N., H.Q.B. and T.T.N.N. ; Project administration, H.Q.B. and T.T.N.N. This work has been supported by Vietnam National University Hanoi (VNU), under Project No. QG.18.36 and Project No. QG.17.41. The authors would like to thank the anonymous reviewers for their time and their thoughtful comments and efforts towards improving our manuscript. The authors would like to thank the European Space Agency for the open data policy of Sentinel 1A data. We also thank General Statistics Office of Vietnam for providing free statistical data. The authors declare no conflict of interest.
## 3 Methods
### Optimization Algorithm
Accordingly, a trip assignment probability weight tensor (\(T_{c}\)) with only three accessible stations in its combinations remains, and the probability weights for all other stations become 0, as shown in Figure 5. This allows only three accessible stations for each combination to be included in the loss calculation and the probability weight updating process. Since the probability weight tensor does not represent a probability, it must be converted into one using a normalization process, as shown in Figure 6. A row of the probability weight tensor (\(T_{c}\)) represents a combination of zones and lines, and a probability weight sum tensor (\(T_{d}\)) is created by extending a row-wise sum of the probability weight tensor. A probability tensor (\(T_{c}\)) is calculated by dividing the previous two tensors. The following is the step used to assign the total trip from each combination of zones and lines to each station using the probability. The total trip tensor (\(T_{f}\)) is a tensor that contains the total trip information for each combination, and it is multiplied by the probability tensor (\(T_{c}\)) to obtain the assigned trip tensor (\(T_{g}\)) for the accessible stations. This is represented in Figure 7.  
Figure 5: Calculation of probability weight tensor (\(T_{c}\)). Figure 6: Calculation converting the probability weight to the probability. The boarding/alighting volume for each station must be estimated using the assigned trip tensor to calculate the loss compared with the observed volume. This is calculated by adding the entries in each column in the assigned trip tensor, as shown in Figure 8.  
The difference between the assigned sum trip tensor and the observed trip tensor is calculated with a predefined loss function. Finally, by calculating the gradient using backpropagation to reduce the loss, the probability weight tensor is updated until the end of the algorithm as shown in Figure A3. The optimization codes were implemented based on Python 3.8 and PyTorch 1.11, and the PC specifications were CPU: Intel Core i5 11400 (2.60 GHz), memory: 32 GB, and GPU: NVIDIA GeForce RTX 2070 SUPER.
## 5 Conclusions  
The mission design of a spaceborne monostatic-bistatic SAR has been presented in order to evaluate the effects of orbital configurations and pointing strategies on the performance of single-pass stereo-radargrammetric methods for DEM generation. Proposed approach can be fruitfully used to investigate overall constraints and on-orbit configurations of future SAR missions, since it accounts for all main factors affecting measurement accuracy of stereo-radargrammetric applications, such as baseline and antenna state vector knowledge, image quality, monostatic and bistatic resolutions, Doppler parameters, etc. Special emphasis has been given to the application of advanced procedures to derive antenna state vectors based on GPS.  
The sensitivity analysis carried out has shown that the so-called parallel orbit configuration offers adequate accuracy in relief reconstruction in spite of the unavoidable non perfectly parallel trajectories and limited along-track separations between monostatic and bistatic antennae due to the relative rotations between the orbital planes and between the satellites within each orbital plane. The effect of the latitude of the observed scene on measurement uncertainty has been pointed out too. Since the proposed model computes quantitatively performance in terrain height evaluation along the orbit, it allows a  
Figure 14: Height estimation error (LE90 point-to-point) as a function of target latitude for bistatic rigorous stereo SAR problem and low bistatic off-nadir angles (1/10 of an image pixel assumed as co-registration uncertainty, 0.25 m as uncertainty for monostatic antenna position error, and 0.1 m as baseline component measurement uncertainty).  
straightforward selection of the relative positions between the satellites on the ascending node, able to guarantee a higher accuracy over assigned latitude intervals.  
Realization in a near future of a dedicated spaceborne monostatic-bistatic SAR mission with large, programmable baselines seems to be compatible with the present generation spaceborne microwave sensors and the current formation flying technologies. Such mission could be able to produce DEM by means of radar-stereogrammetric techniques offering 4-5 m as height accuracy on a global scale within a wide range of surface coverage and slope characteristics. This product could be an indispensable addition of DEMs generated by SAR interferometry both for applications and for engineering goals (as an example to improve phase unwrapping procedures), thanks to the expected robustness of the radargrammetric technique, which is less sensitive to terrain characteristics and decorrelation, and can be fulfilled over larger latitude intervals with almost constant performance, as shown by the investigation.