esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Data and Methodology
### Formosat-3/cosmic  
FORMOSAT-3/COSMIC, a joint project of Taiwan and the United States, is a constellation of six small satellites [45] that probe the Earth's atmosphere using the GPS radio occultation (GPSRO) technique [22]. The mission was launched in 2006, and it provided observational data up to May 2020. The COSMIC \"atmprf\" dataset provides the dry temperature data in the stratosphere, and version 2.0 data are analysed in the current study. COSMIC data sampling is random and spatially non-uniform as it depends on the position of the COSMIC and the GPS satellites. COSMIC satellites make observations of the radio signals transmitted by the GPS satellites as they set or rise behind the Earth's horizon [22]. Hence, the observations are very random. [PERSON] et al. [14] have shown that a window size of \(\pm 10\) days is suitable for retrieving short-term tidal variability from such observations, and it also reduces the aliasing. For appropriate comparisons, CMAM30 and ERA-Interim data are also analysed using a window of \(\pm 10\) days.  
The least square fitting method is used to investigate the short-term variability of the tides in the stratosphere during 2007 to 2010 using COSMIC data. All migrating and non-migrating diurnal tides are extracted along with the mean temperature variation and SPW components [14]. The following function is fit to the two-dimensional temperature data, \(T\), a function of universal time, \(t\), and longitude, \(\lambda\), at a given latitude and altitude, to include (a) mean temperature (\(T_{0}\)) (b) tides and (c) SPWs.  
\[T(t,\lambda)=T_{0}+\sum_{i=1}^{3}\sum_{j=-4}^{4}T_{ij}\cos(2\pi f_{i}t+2\pi s_{ j}\lambda-\phi_{ij})+\sum_{k=1}^{3}T_{k}\cos(2\pi s_{k}\lambda-\phi_{k}) \tag{2}\]  
where \(T_{ij}\) and \(\phi_{ij}\) are the amplitudes and phases of tides with frequency, \(f_{i}\), taking values from 1 to 3 for diurnal, semi-diurnal, ter-diurnal tides and wavenumber, \(s_{j}\), ranging from \(-4\) to \(+4\), where negative (positive) wavenumbers denote eastward (westward) propagating tides. \(T_{k}\) and \(\phi_{k}\) are the amplitudes and phases of the SPW with wavenumbers, \(s_{k}\), ranging from 1 to 3. As already mentioned, a window size of \(\pm 10\) days is used to extract the short-term wave variability, i.e., data over \(\pm 10\) days are combined to obtain the wave features and are attributed to the central day [14]. The process is repeated at each altitude from 15 to 50 km at all latitudes from 70\({}^{\circ}\) S to 70\({}^{\circ}\) N. COSMIC data have been validated, and it has been found that they are reliable up to approximately 45 km [46].
## 4 Case Study
### Case Study 5: Step Response via the LADRC by Introducing ATD  
In this part, tracking control of the radar position servo system via LADRC1, which contains the proposed ATD, is simulated as compared with LADRC2 without the ATD under the same conditions. The input signal turns into a step signal, which steps to 2 at 5 s. The parameters of the LADRC1 are given as: \(h=0.001\), \(K=300\), \(L=120\),\(\sigma_{1}=3.5\), \(\sigma_{2}=10.25\), \(w_{0}=180\), \(k_{p}=15\), and \(k_{d}=10\).  
The step responses of LADRC1 and LADRC2 are shown in Figure 22. As shown in Figure 22, ADRC1 has faster tracking performance with an acceptable overshoot of 2.73%. The control signals of LADRC1 and LADRC2 are shown in Figure 23. As seen, the LADRC1 consumes less energy compared with LADRC2, which smoothly eliminates the excessive control gain in order to track the change of input signal immediately, and the peak value of the control signal has been greatly reduced, which reduces the spike impact on the actuator. Thus, the LADRC1 containing the proposed ATD has more practical application value.  
Figure 21: Tracking error of the DRNN-LADRC for the new radar servo system.  
Figure 22: Step responses from the LADRC with ATD and LADRC without ATD.
# Explainable Artificial Intelligence: Advancements and Limitations
## 4 Visual Explanations
### Pixel Attribution
#### 4.2.1 Backpropagation-Based Saliency Mapping
Backpropagation-based XAI methodologies have been pivotal in unravelling the inner workings of complex neural networks. They offer a relatively efficient way to link input features to model predictions, enabling practitioners to gain insights into model behaviour and hence increase trustworthiness. These methods are particularly appealing due to their simplicity and adaptability across various neural architectures. However, their limitations are equally noteworthy. One key issue is their lack of precision, as they often produce coarse, blurry visualisations that highlight large, indistinct regions of the image, making it difficult to pinpoint exactly what features the model is focusing on. This can be particularly problematic when interpreting decisions in tasks like medical imaging or autonomous driving, where fine-grained details are critical. These methodologies also often suffer from instability and lack of robustness, with explanations being sensitive to minor input perturbations. They may also struggle to capture global model behaviour, instead focusing on local feature importance, which can lead to misleading or incomplete interpretations. Furthermore, the ones that employ gradients may be vulnerable to vanishing gradients and susceptible to noise. Additionally, saliency maps by backpropagation-based methodologies tend to be post hoc explanations, meaning they provide insights only after a decision is made, which might not always reflect the true reasoning process of the model. In summary, these shortcomings reduce the effectiveness of backpropagation-based methodologies in providing clear, consistent, and trustworthy interpretations, especially in high-stakes applications, which underline the need for complementary XAI approaches that provide more consistent and comprehensive explanations.
# Polycaprolactone Blended Cosmetic Microneedle for Transdermal Hispidin Delivery System
## 3 Results and Discussion
### Hispidin Delivery Test  
To observe the delivery effects due to MN skin permeability, we replicated the system using in vitro agarose gels. The amounts of hispidin delivered to the agarose gel were calculated using UV-Vis calibration standard curves. The pristine hispidin showed the highest absorbance at a wavelength of 358 nm, and we estimated the absorbance of each concentration (0.12, 0.1, 0.08, 0.06, 0.04, and 0.02 wt.% of hispidin) (Figure 2a). For the delivery layers, amounts of PLA and PCL were also calculated using UV-Vis calibration standard curves at 282 nm and 290 nm (Figure 2b,c). After applying MNs to agarose gel (3 g) for 5 min, the amounts of delivered hispidin were observed. Compared to hispidin-only delivery layers, hispidin with PLA/PCL blended polymer delivery layers exhibited higher absorption peaks at 358 nm (Figure 2d). According to the UV-Vis calibration standard curves, 0.03 mg of hispidin was contained on the MN surface and 0.0036 mg (12.13%) was delivered from the coated MNs to the agarose gel. When we developed delivery layers with PLA/PCL blends, the delivered hispidin increased to 18.36%. This result indicates that the high-strength biodegradable polymer offers an effective physical drug delivery system for hispidin and many other related molecules.  
Figure 1: Microstructure and mechanical strength of microneedles (MNs). (**a**) Fabrication process of MNs. (**b**) SEM image of casted pristine polylactic acid (PLA)/polycaprolactone (PCL) MNs. (**c**) Stress–strain graph of various PLA/PCL blended structures. (**d**) SEM image of MNs after coating of hispidin delivery layer. (**e**) SEM image of MNs after coating of hispidin with PLA/PCL blended polymer delivery layer.
## 4 Conclusions  
In this paper, a STIL system that combines TDC and streak camera ranging mechanism is proposed. Moreover, a ground test was proposed to assess the ranging accuracy of the developed method. The assessment shows a ranging time accuracy of 0.65 ns for a building target at a horizontal distance of 6 km. The results indicate that the designed STIL system achieves a high ranging accuracy of 0.1 m at 6 km, thereby verifying the system's long-range ranging capability. In future work, we will analyze and verify the scanning accuracy of the STIL system and further study the streak camera's imaging characteristics of long-distance laser echoes. Building on the foundation of high ranging accuracy, we aim to further improve the efficiency and precision of the STIL system in long-distance 3D detection.  
Conceptualization, R.F.; Methodology, Z.C.; Software, X.W.; Formal analysis, L.C.; Investigation, Z.F. and Z.D.; Data curation, P.H.; Writing--original draft, C.D.; Supervision, D.C. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the National Natural Science Foundation of China, with No. 62305085 and No. 62192774.  
Not applicable.  
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to confidentiality agreements and concerns regarding data privacy.  
The authors declare no conflicts of interest.  
Figure 7: Normalized histogram of \(t_{range}^{s}\), with an average measurement time of 38,785.6 ns (d* = 5817 m) and a standard deviation of 0.65 ns (\(\sigma_{\text{d}}\) = 0.1 m).
## 2 Related Work
### Facility Location Problems  
Facility location determination is a critical strategic business decision. There are several factors that determine facility location, including competition, costs, and associated impacts. The facility location decision has a profound impact on tactical and operational operations. For dealing with this strategic decision, the Facility Location Problem (FLP) was introduced to the field of operations research in the 1960s [28] and was initially called the Plant Location Problem.  
FLPs consist of determining the optimal location for one or more facilities to serve a range of demand points. The importance of the optimal location depends on the nature of the problem in terms of the constraints and optimality criteria considered for the site [29]. FLPs are useful for determining the location of facilities such as hospitals, fire stations, bus stops, train stations, truck terminals, gas stations, blood bank centers, retail stores, neighborhoods, libraries, parks, post offices, airports, and landfills. The FLP can be seen as a generalization of the vehicle routing problem with fixed costs for the installation of facilities. An exhaustive review and discussion of the FLPs is provided in [30].  
In a basic formulation, the FLP consists of a number of potential plant locations at which a plant can be opened and a number of demand points that must be served. The aim is to determine what subset of facilities needs to be opened in order to minimize the total costs of delivering goods to customers plus the sum of the facility opening costs. A simple example of a classic FLP instance is shown in Figure 2, where each customer (blue circle) is assigned to the nearest open facility (red square) via an active connection.  
One of the most frequently investigated discrete location problems is the uncapacitated facility location problem (UFLP). The UFLP is the problem of determining the best location for a given facility--or the best locations for a given group of facilities--given some limitations on the environment in which it can be placed. This contrasts with the capacitated FLP, where facilities limit the number of customers they can serve. In the uncapacitated version, there is no such limitation. Some applications of FLP in UL context are presented in [31; 32; 33; 34; 35; 36; 37; 38].
## 4 Experimental Evaluation
### Comparison between Different Approaches  
This subsection discusses the results of comparative experiments with different optimization algorithms, including the PSO, the GA, and their combined algorithms. Based on experience and repeated experiments, the parameters of the GA are set as follows: the crossover probability is 0.7, the mutation probability is 0.1, the population size is 50, and the number of iterations depends on the size of the optimization problem. The parameters of the PSO are set as follows: \(w=0.7298,c1=c2=1.4962\), the number of populations is 50, and the number of iterations depends on the size of the optimization problem. Three sets of parameter combinations were designed to validate these algorithms for the 2D space, and finally, their performances were compared. Three sets of different parameter combinations are shown in Table 1.  
For each parameter combination, the average running time, average coverage, and standard deviation of the coverage are recorded in Table 2. It can be seen that the combined algorithm consistently produces the best optimization results, and the standard deviations are all smaller than the other two algorithms, which indicates that the combined algorithm produces better and more stable optimization results. In addition, the average running time of the combined algorithm is between that of the PSO and the GA, with a significant reduction in running time compared to the GA. Among the three algorithms, PSO has always had the lowest running time, as well as the lowest coverage, and the optimization results are unstable, probably because PSO can easily fall into a local optimum and cannot obtain the global optimal solution.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline  & **Space** & \(\mathbf{fov}\) & \(\mathbf{dof}\) & **N** & \(\mathbf{\Delta_{b}}\) & \(\mathbf{\Delta_{m}}\) & \(\mathbf{s_{\varphi}}\) & **Objective** \\ \hline
1 & 60 \(\times\) 60 & 35 & 60 & 4 & 5 & 5 & 4 & 1-coverage \\ \hline
2 & 80 \(\times\) 80 & 90 & 80 & 2 & 5 & 5 & 4 & 1-coverage \\ \hline
3 & 80 \(\times\) 60 & 60 & 60 & 6 & 5 & 5 & 4 & 2-coverage \\ \hline \end{tabular}
\end{table}
Table 1: Different parameter combinations for comparison of the different approaches.
# On the Properties of WC/SiC Multilayers
## 1 Introduction
A pair of MLLs prepared from these materials was used to demonstrate imaging at 16.3 keV with sub-10 nm focused beam with over 60% diffraction efficiency [8]. In general, high-NA MLLs consist of many thousands of bilayers. For example, the two aforementioned MLLs consist of 5100 and 3326 bilayers. The high NA and high efficiency make such MLLs ideally suited for focusing highly coherent X-ray beams from synchrotrons or X-ray Free Electron Lasers (XFELs). Based on our experience with intense synchrotron beams WC/SiC-based MLLs maintain performance over long periods of time. However, under XFELs beam these lenses would be subjected to more extreme X-ray intensities and potentially damaging conditions. Hence, knowledge of the thermal stability of these MLLs is required to help select materials and design lenses to be used at such sources. Typically, only materials with low atomic number (Z), low density, high melting point and high thermal stability are considered for XFEL optical coatings and elements. For example, diamond-based Fresnel zone plates were used to successfully focus a hard X-ray FEL beam [12]. However, in XFEL experiments, where the damage of single films [13] and multilayers [14] consisting of high Z elements were studied, higher than expected damage thresholds in grazing incidence geometries were observed. Thus, it may be possible to use MLLs consisting of WC/SiC multilayers with XFEL beams. To the best of our knowledge no thermal stability data were reported for WC/SiC multilayers, and W/SiC systems were only explored at a temperature range below 300 \({}^{\circ}\)C [15]. Here we report on WC/SiC and W/SiC multilayers, in particular the study of their properties (interface roughness, microstructure, chemical composition, stoichiometry and stress) as a function of multilayer period. Their stability as a function of temperature and annealing time is investigated as well.
## 6 Results and Discussion
### Security Analysis  
Mobile users A and B calculate \(S_{1}\) and \(S_{2}\) respectively as the short authentication string for mutual authentication and then, they apply hash function for the shared key.  
We assume that another device E is launching a Man In The Middle Attack by pretending to [PERSON] to be [PERSON]. First, it listens on the wireless channel and collects \(g\) and \(p\), known as The key pair. It selects \(e\) and calculates \(g^{e}modp\). Next, it sends the hash value to B. After receiving [PERSON]'s answer (hash value of \(g^{e}modp\)), [PERSON] cannot edit hash value and resend it to A. Thus, in the mutual authentication step, A and B compare \(H(S_{1})=H(g^{ab}modp)\) with \(H(S_{2})=H(g^{ab}modp)\) but \(S_{3}\) is different from \(S_{1}\) and \(S_{2}\).  
As a result, the key exchange scenario has been performed correctly. To provide confidentiality of all transmitted messages, the calculated shared secret is used to ensure AES encryption generating the symmetric key with a size of 128 bits that is hard to be broken by adversaries.
## 3 Results and Discussion
### Strength and Analysis of Fracture Surface
* With a decrease in sintering temperature from 1550 to 1450 \({}^{\circ}\)C, for the 3 YSZ ceramic the area fractions of 0.3-0.6 \(\upmu\)m and 0.6-0.9 \(\upmu\)m grains increased from 4 to 21.5% and from 18 to 59%, respectively; untypically high area fractions (up to 15%) were observed for large grains in the 3 YSZ ceramic, namely 2.4-2.7 \(\upmu\)m and >2.7 \(\upmu\)m grain sizes in the case of sintering temperature of 1550 \({}^{\circ}\)C (Figure 4a);
* With a decrease in sintering temperature from 1550 to 1450 \({}^{\circ}\)C, for the 6 YSZ ceramic, the area fraction of 0.3-0.6 \(\upmu\)m grains (the smallest grains, Figure 4b) increased from 24 to 37%; this material exhibited finer microstructure compared to other conditions; for 6 YSZ ceramics sintered at 1500 \({}^{\circ}\)C and 1450 \({}^{\circ}\)C, increased area fractions were revealed for larger grains, >2.4 \(\upmu\)m and >1.5 \(\upmu\)m grain sizes, respectively;
* It was revealed for the 3 YSZ ceramic sintered at 1500 \({}^{\circ}\)C (Figure 10a) that the total percentage of relatively small cleavage facets (2-10 \(\upmu\)m\({}^{2}\)) exceeds 90%, whereas this of relatively large cleavage facets (>10 \(\upmu\)m\({}^{2}\)) is less than 10%; with both the increase in the sintering temperature to 1550 \({}^{\circ}\)C and decrease to 1450 \({}^{\circ}\)C, shifts in the fractions of cleavage facets towards large values are observed; fracture along boundaries of separate clusters occurred in the 3 YSZ ceramic sintered at 1450 \({}^{\circ}\)C, and no recrystallized zirconia grain was identified; thus, the cleavage facets identified for this material condition cannot be associated with \"classic\" transgranular fracture;
* A gradual decrease in fractions of cleavage facets (from 31.5% to 16%) in the size range from 2 to 10 \(\upmu\)m was observed in the 6 YSZ ceramic sintered at 1550 \({}^{\circ}\)C, and a small fraction (about 6%) was found for larger cleavage facets (Figure 10b); the total fraction of large cleavage facets of >10 \(\upmu\)m\({}^{2}\) was much higher (from 20% to about 29%) for sintering temperatures of 1450 \({}^{\circ}\)C and 1500 \({}^{\circ}\)C than for 1550 \({}^{\circ}\)C;
* The above-mentioned differences in the void size distribution shapes may be related to the complex nature of the void formation, as some voids could grow from pre-existing pores and others might have formed in the high-density parts of the volume. This should be taken into account when characterizing the fracture evolution based on the fracture void imaging.
## 2 Materials and Methods
### Data Analysis  
For each study, a two-by-two contingency table was constructed, including the TP, FP, TN, and FN for the index tests. If these values were not reported in the manuscript, they were calculated from the data extracted from each study (sample size, number of participants with the target condition, estimates of sensitivity and specificity, or estimates of PPV and NPV), following the recommendations of the Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy for the calculation of TP, FP, TN, and FN results [48]. Approximations and rounding were made, if necessary. Calculations were double-checked and cross-checked against the accuracy measures presented in the study.  
For the meta-analysis, we used hierarchical random-effects models and Receiver Operating Characteristic (ROC) analysis. Hierarchical Summary Receiver Operating Characteristics (HSROC) models were implemented for the estimation of a Summary Receiver Operating Characteristic (SROC) curve. This method provides information on the test performance, describing variations in sensitivity and specificity [43; 49], considering the recommendations of the Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy [39].  
A SROC plot was developed, presenting the results of each study in the ROC space, the Summary ROC (SROC) curve, the summary estimates of sensitivity, and the false positive rate (1--specificity), with 95% confidence and 95% predictive regions.  
A sensitivity analysis was performed by removing the studies of paper-based digital solutions and displaying the Summary ROC (SROC) curves, summary estimates of sensitivity, and the false positive rate (1--specificity), with 95% confidence and 95% predictive regions, in a SROC plot.  
Data were subdivided into two subgroups considering the type of index test used: (i) paper-based digital solutions; (ii) innovative digital solutions. A SROC plot was also developed for each index test subgroup. The estimate of the summary points and confidence intervals (CI) for sensitivity and specificity were calculated.  
To perform the meta-analysis, a web application developed in R (R Core Team, Vienna) using Shiny, the MetaDTA, was used [50; 51]. Among other features, MetaDTA allows to incorporate the data obtained by the QUADAS-2 tool into the graphical representation.