esa-sceva/satcom-chunk-collection huggingface dataset:
# Blind Image Separation Method Based on Cascade Generative Adversarial Networks
## 3 Experiments
### Experimental Results of the Remote Sensing Image Dataset  
Compared with the natural image, the remote sensing image contains more detailed ground information. In the process of acquiring the remote sensing image, due to the atmospheric environment and other reasons, the acquired images are covered by haze and other related shadows; how the images are contaminated is unknown. Therefore, remote sensing image dehaze is an application of BIS.  
Qualitative comparisons of the remote sensing image results are shown in Figure 6. The results show that CAP can only reduce part of the haze but cannot remove the haze completely. Especially, the details of the remote sensing image cannot be restored well. The dehazing results of GDCP, MOF and GCANet show that the obtained images have different degrees of spectral distortion, and the original image cannot be accurately restored by the three methods. When compared with other algorithms, the proposed method can better recover the ground truth of the remote sensing image from haze images without spectral distortion.  
To further explore the processing of other particles in the atmosphere by the separation method, a comparative removal experiment was performed on the remote sensing image with thin clouds. In contrast to the haze, the clouds had multiple distribution types and different thicknesses. The uncertainty of cloud distribution, thickness, and other information conformed to the characteristics of the blind images [31; 32]. Therefore, cloud removal from the remote sensing images was also an image separation problem in the field of BIS. The experimental results are shown in Figure 7. The proposed method effectively reconstructed the information from the clouds and shadows. From the perspective of visual results, it was significantly better than the comparison methods.  
A quantitative comparison of the results of dehazing and cloud removal is shown in Table 2. The results show that our method achieves the best values of all comparison methods. Compared to the previous most effective technique, our method achieves a 0.21 improvement in SSIM and 0.18 dB in PSNR in the RICE-II dataset, and achieves a 1.41 dB improvement in PSNR in the RICE-I dataset. This demonstrates that the proposed method better enhances the visibility of the separation scenes under the same mixing components. Therefore, it is suitable for the separation of remote sensing images.  
Figure 5: Result of image separation for synthesized images.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**PSNR (dB)/SSIM** & **NMF** & **FastICA** & **NES** & **Yang [22]** & **Ours** \\ \hline Yellow haze images & 15.02/0.42 & 12.67/0.15 & 19.75/0.63 & 15.70/0.45 & 25.92/0.89 \\ Synthesized images & 23.79/0.70 & 14.70/0.55 & 20.56/0.78 & 21.37/0.71 & 23.84/0.88 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Shoe and bag image results (PSNR, SSIM).
## 2 Literature Review
### Motivation and Research Contributions  
Analysis of the introduction and literature review sections revealed that ML models are a useful technique for CRA systems. However, imbalance in the datasets used for credit risk can lead to various problems. One of the effective methods to solve these problems is resampling using the SMOTE technique. In our study, we aimed to contribute to the literature by using the SMOTE method specifically in a multi-class dataset.  
When the literature was examined, it was seen that one of the biggest deficiencies in CRA systems is a real and up-to-date dataset. Previous studies have mostly used publicly available traditional datasets. These datasets consist of only past credit or credit card data and two classes. The dataset we use in our study is the \"bill payment habits\" dataset obtained from bill payments made at a payment institution in Turkey. The label feature is the real credit score obtained from the credit assessment institution. In addition, unlike other studies in the literature, the label feature is not a two-class feature, but a multi-class feature consisting of 10 classes. When viewed from these perspectives, the dataset stands out as a unique and real source.  
Although ML models are used effectively in CRA, they are not transparent. In terms of legal obligations and compliance, financial institutions must clearly explain how decision-making processes are carried out and the parameters involved in these processes. ML models that are not transparent and explainable can be difficult to verify and can be prone to error and bias. XAI techniques are a technology that makes black box ML models, which have become more complex in recent years, more transparent and interpretable. In our study, a transparent model output was produced on both an instance and class basis by using the LIME and SHAP methods.  
In our study, we aim to contribute to the literature by proposing a hybrid method that combines and evaluates ML and XAI steps for CRA.  
This study made the following contributions to the literature:  
* An alternative credit score estimate was made for people without a credit score.
* For CRA, the real bill payment habits data was combined with the real credit score. A similar dataset is not available in the literature.
* The importance and effectiveness of pre-processing steps such as data cleaning and feature selection in ML studies were shown.
* SMOTE, a resampling technique, was used in our multi-class and imbalanced dataset.
* The EXT algorithm, which is not widely preferred in the literature, was shown to be effective in CRA systems.
* The black box ML model was transformed into an explainable and interpretable form with the LIME and SHAP methods, providing a transparent and hybrid solution.
## 2 Results and Discussion
### Optimization of MSPE Conditions
#### 2.3.3 Desorption Conditions  
The desorption time and elution solvent, which are the main parameters for the desorption process, were optimized. Experiments with desorption times in the range of 10-60 min were carried out, as shown in Figure 7c. The recoveries of OFL increased with increasing desorption time from 10 to 40 min. Therefore, 40 min was selected as the optimal desorption time.  
Various proportions of acetic acid-methanol were investigated to obtain satisfactory recoveries. As shown in Figure 7d, 10% acetic acid-methanol (\(v/v\)) was found to be the most effective eluent for OFL. The recoveries increased as the proportion of acetic acid increased from 1% to 10%. However, the MMIPs may be destroyed at higher concentrations of acetic acid [28]. Thus, 5 mL of 10% acetic acid-methanol was adopted for the desorption of OFL.
# Microstructural and Corrosion Properties of Burnished 6060 Aluminum Alloy
## 3 Results
### Corrosion Test
#### 3.2.1 Potentiodynamic Polarization Tests  
Potentiodynamic curves of the samples treated at room temperature and at 50 \({}^{\circ}\)C are shown in Figure 11. The corrosion potential Ecorr and corrosion current density icorr, graphically extrapolated from the curves according to [PERSON]'s law, are reported in Tables 4 and 5.  
Figure 11: Potentiodynamic polarization curves for the samples treated in solution 1 at 50 \({}^{\circ}\)C (**a**) and for the samples treated in solution 2 at ambient temperature (**b**). Test electrolyte: commercial solution that simulates cleaning product \(\bullet\).  
Figure 10: SEM analysis of sample section blackened with solution 2 for 100 min.  
Considering the results obtained with solution 1 (Figure 11a and Table 4) the formed black layer was characterized by a corrosion current density with the same order of magnitude as that of the samples obtained with 15, 30, 75, and 90 min of treatment time. The same order of magnitude of the current was also observed for the untreated sample (as received AR). The black coating obtained with a blackening immersion time of 50 min presented a corrosion current density an order of magnitude higher than that of the other samples. This result shows that the corrosion rate, directly linked to the corrosion current density, was higher for the sample treated with 50 min immersion time than the other samples. Furthermore, for solution 1, the sample obtained with an immersion time of 50 min exhibited lower corrosion resistance.  
Considering the samples obtained with solution 2 (Figure 11b and Table 5), it is possible to observe that the corrosion current density for all the samples (treated and untreated) had the same order of magnitude. The same result appeared for the corrosion potential. So it can be concluded that potentiodynamic polarization tests in the alkaline commercial solution did not show a significant difference in terms of corrosion resistance for the samples blackened at room temperature.  
Comparing the two blackening solutions, is possible to observe that the corrosion current density had the same order of magnitude for all the samples, except for the one treated at 50 \({}^{\circ}\)C for 50 min. To get more significant results in terms of corrosion behavior of the burnished layer with the two baths, EIS measurements were employed.
## 3 Results
### Characterization of PRGF-Modified Collagen Membranes by FTIR Spectroscopy  
ATR FTIR spectra of commercial collagen membranes before and after immersion in PRGF are presented in Figure 2. The vibrational details of the spectra revealed the fingerprints of collagen as an intact triple helix conformation: amide I at 1630 cm\({}^{-1}\) (C=O stretching), amide II at 1580 cm\({}^{-1}\) (N-H in  
\begin{table}
\begin{tabular}{l l l} \hline \hline
**Component** & **Whole Blood/Normal Range** & **PRGF** \\ \hline Leukocytes (\(\times 10^{-3}/\mu\)L) & 5.9 \(\pm\) 0.2/4–10 & 0.4 \(\pm\) 0.1 \\ Erythrocytes (\(\times 10^{-6}/\mu\)L) & 4.5 \(\pm\) 0.4/3.8–5 & 0.01 \(\pm\) 0.01 \\ Platelets (\(\times 10^{-3}/\mu\)L) & 210 \(\pm\) 20/150–300 & 655 \(\pm\) 85 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Hematology parameters of whole blood and PRGF fraction.  
Figure 1: Whole blood separation upon centrifugation at 580 G for 8 minutes at room temperature (**a**) and subsequent platelets rich in growth factor (PRGF) separation by pipetting (**b**); membrane immersion in PRGF (**c**).  
plane deformation and C-N stretching), and amide III at 1235 cm\({}^{-1}\) (C-N stretching and N-H bending vibration from amide linkages). These fingerprints were very well preserved after PRGF treatment, which demonstrates that no specific interaction between collagen and PRGF components occurred [24].  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Growth Factor Content** & **Value** \\ \hline Transforming growth factor TGFB1—enhances the proliferative activity of fibroblasts and stimulates the biosynthesis of collagen and fibronectin & 43 ng/mL \(\pm\) 8.2 \\ Vascular endothelial growth factor VEGF—induces angiogenesis via migrating endothelial cells Insulin-like growth factor IGF-1—a primary mediator of the effects of growth hormone; can also regulate cellular DNA synthesis & 220 pg/mL \(\pm\) 20 \\ Platelet-derived growth factor PDGR—enhances collagen synthesis and bone cell proliferation & 105 ng/mL \(\pm\) 15.5 \\ RANTES chemokine (CCL5)—role in regulating T-cell responses and immunity during chronic & 14 ng/mL \(\pm\) 3.5 \\ Interleukin IL-1ß cytokine—regulates and initiates inflammatory responses & 520 pg/mL \(\pm\) 100 \\ Monocyte chemotactic proteins (MCP-1)—regulates the expression of cell surface antigens; can induce the proliferation and activation of killer cells & 400 pg/mL \(\pm\) 80 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Quantitative assessment of the main growth factors, cytokines, and chemokines in PRGF fraction.  
Figure 2: ATR FTIR (Attenuated Total Reflection Fourier Transform Infrared) spectra of commercial collagen membranes for bone-guided regeneration before and after PRGF treatment. Legend: Biocellogen® = MCP; \(\text{CovaTM}\text{Max}\) = MPP; Jason® = MC.
# Spatio-Temporal Distribution of Ground Deformation Due to 2018 Lombok Earthquake Series
## 1 Introduction
It was followed by a 7.0 Mw mainshock on 5 August 2018, then a 6.2 Mw aftershock on 9 August 2018, and finished by an earthquake of 6.9 Mw on 19 August 2018 (Figure 1). In between and after these four days of strong motion occurrence, there were at least 818 minor earthquakes until 31 August 2018 at 18:00 Western Indonesian Time. This led to 560 deaths, 396,032 evacuated people, and 83,392 destructed houses (Figure 2). Such a great number of destructed houses due to the high magnitude of consecutive earthquakes in a short period of time would be caused by the abrupt change in local topography. This is well-known as ground deformation which may involves uplift and/or subsidence. The aims of this study are to measure ground deformation due to the 2018 Lombok earthquake series and to map its spatio-temporal distribution. This would be important to local authorities to evaluate the earthquake's impacts which still exist now and mitigate future disasters related to earthquake-induced ground displacement.
# The Applications and Challenges of Digital Twin Technology in Smart Grids: A Comprehensive Review
## 4 Critical Applications
### Disaster Response and Recovery
#### 4.3.3 Enhancing Recovery Efforts  
In the wake of disasters, Digital Twins prove indispensable for guiding the recovery and restoration of critical systems like smart grids. By virtually replicating the current state of the physical grid, Digital Twins pinpoint severely impacted areas, allowing utilities to prioritize recovery initiatives for essential services and vulnerable populations. Their true strength lies in integrating diverse data--from field crews, drones, satellite imagery and more--into a unified view of the damage and restoration progress. This convergence empowers precise resource allocation, the efficient execution of recovery actions, and swift, safe power restoration. The studies discussed in this section exemplify how Digital Twins enhance situational awareness, enable proactive decision-making, and facilitate coordinated responses during this crucial recovery phase.  
For instance, the paper in [36] proposes a multi-tiered framework leveraging Digital Twins to enhance both the preventative measures and incident response of Critical Cyber Infrastructures (CCIs). The proposed model includes three distinct sections: a foundational layer focused on technical systems, an intermediary layer managing operational processes, and an overarching layer facilitating external collaborations. The study also highlights the importance of situational awareness (SA) and Common Operating Picture (COP) in enabling coordinated actions; the goal is to streamline response efforts and improve the overall system resilience. While the proposed model shows promise, its broader use across varied infrastructure contexts remains to be examined through practical implementation and testing. The study in [41] proposes the application of DT to enhance fault tolerance in small-scale power networks, particularly focusing on a Battery Energy Storage System (BESS). The proposed model includes four interconnected components: the physical device, its digital counterpart, an adaptive decision-making module, and a communication interface. The DT uses state prediction models, generating error vectors to identify unaccounted-for impacts on the physical BESS. The intelligent module interprets these vectors to guide responses, such as IEEE Std. 1547-2018 ride-through actions or operational mode switches [93]. The study demonstrates this approach with a BESS voltage source converter (VSC) simulation, presenting error vector outcomes under various fault scenarios. However, the research is limited to this specific component, without exploring the scalability to broader nanogrid applications. The intelligent module's implementation details and decision-making processes remain underdeveloped. Moreover, the framework's effectiveness in enhancing system recovery and ride-through capabilities during simultaneous faults lacks quantitative comparisons with existing methods.
# Cladding-Pumped Erbium/Ytterbium Co-Doped Fiber Amplifier for C-Band Operation in Optical Networks
###### Abstract  
Space-division multiplexing (SDM) attracts attention to cladding-pumped optical amplifiers, but they suffer from a low pump power conversion efficiency. To address this issue, ytterbium (Yb\({}^{3+}\)) and erbium (Er\({}^{3+}\)) co-doping is considered as an effective approach. However, it changes the gain profile of Er\({}^{3+}\)-doped fiber amplifiers and induces the gain difference between optical wavelengths in the C-band, significantly limiting the effective band of the dense wavelength-division multiplexed (DWDM) system. This paper is devoted to a detailed study of a cladding-pumped Er\({}^{3+}\)/Yb\({}^{3+}\) co-doped fiber amplifier (EXDFA) through numerical simulations aiming to identify a configuration, before assembling a similar EXDFA in our laboratory premises that ensures the desired performance. The simulation model is based on a commercial double cladding EXDF whose parameters are experimentally extracted and fed to the EXDFA setup for the system-level studies. We investigate the wavelength dependence of the amplifier's characteristics (absolute gain, gain uniformity, noise figure) and bit error rate (BER) performance for several DWDM channels and their optical power. The obtained results show that a 7 m long EYDF and co-propagating pump direction is preferable for the EXDFA with a 3 W pump source at 975 nm and with the given gain medium characteristics for WDM applications. For instance, it ensures a gain of 19.7-28.3 dB and a noise figure of 3.7-4.2 dB when amplifying 40 DWDM channels with the input power of \(-\)20 dBm per channel. Besides, we study EXDFA gain bandwidth and the maximum output power when operating close to the saturation regime and perform a sensitivity analysis showing how the doped fiber's absorption and emission cross-sections impact the amplification process through energy transfer from Yb\({}^{3+}\) to Er\({}^{3+}\). Finally, we quantify the power penalty introduced by the EXDFA; the results show that it is not higher than 0.1 dB when amplifying 40 \(\times\) 10 Gbps non-return-to-zero on-off keying signals from \(-\)20 dBm/channel.  
bit error rate; cladding-pumped optical amplifier; doped fiber amplifiers; erbium/ytterbium co-doping; optical fiber network; simulation; wavelength division multiplexing
# Geometric Spherical Surfaces Emulating the Geostationary Orbit at Any Latitude with Zenith Links
## 4 Discussion and Conclusions
It is assumed that the frequency band and worldwide communication service type are the same for all systems. the satellite enters or leaves the local service area. The connections among the satellites are easier to establish because of the constant positions along an orbital plane or adjacent planes, although with variable distances. The number of satellites is much less than that of a current large constellation proposal (Starlink). The main drawback is the large number of satellites crowding at high latitudes, a problem, however, that could be eased by slightly changing the polar orbits inclination. Because the GeoSurf constellation design can be applied to any orbit altitude, we could design a large number of GeoSurf constellations, by varying the altitude. We have presented some particular and popular orbit altitudes, just to show what could be done and to orient readers. Lower altitudes could also be used, such as, for example, 600 km, suitable for the very small cube satellites [17; 18]. Of course, any satellite of the GeoSurf constellation could be linked to a real geostationary satellite and many architectures are possible. The same overall design could be considered for future large--scale human settings on Mars. In conclusion, GeoSurf constellations could effectively replace most of the actual constellations for Internet applications. However, as any new complex satellite constellation design, its possible implementation requires many feasibility studies, especially from the point of view of space companies, a task well beyond this theoretical paper. This research received no external funding. The author declares no conflict of interest.
# Challenge-Response Pair Mechanisms and Multi-Factor Authentication Schemes to Protect Private Keys
## 5 Discussion: Recovery Protocols in Real-Life Implementation
### Extreme Case: A Physical Threat  
One of the extreme cases feared by users of crypto wallets is a direct physical threat from an opponent. Very few schemes can protect a user against this type of attack besides triggering a warning signal to a service provider connected to the terminal device. The suggested protocols with multiple layers of authentication slow down the recovery process of the private key; the user needs to enter their password, plug in the token, place their face in front of the camera, and retrieve the virtual token. One of the following protocols could automatically generate a warning signal that could be intercepted by a service provider:  
* The password could incorporate the warning signal.
* A change in facial expression can be detected by the CRP mechanism generating the CT-Bio that is presented in Section 2. The user could, for example, smile during the enrollment cycle in such a way that a recovery process without a smile could trigger an abnormal rate of errors in the CT-bio, and a warning signal.
* The retrieval of the virtual token could incorporate the warning signal.
* The MFA factors could be entered out of a pre-arranged sequence, thereby sending the warning signal.  
Some of the warning signals described here could be the result of a mistake, triggering a false alarm that could be managed separately.
Due to their agricultural and domestic uses, the presence of pesticides and personal care products in river waters and effluents from wastewater treatment plants has been described worldwide [32; 33]. Chlorpyrifos (CPS) is an organophosphate insecticide widely used both in agriculture and gardening. The World Health Organization considers it to be a compound of moderate toxicity for humans [34], and its use is now forbidden in Europe. CPS is included as a priority substance in the Water Framework Directive (WFD) [35], with an environmental quality standard (EQS) of 0.03 \(\upmu\)g L\({}^{-1}\). Triclosan (TCS) is commonly used as a bacteriostatic, fungistatic, mildewstat, and deodorizer. As a preservative material, TCS is used in many products, including adhesives, fabrics, vinyl, plastics, floor wax emulsions, and textiles, among others. TCS is not biodegradable and can accumulate in soil and surface water, attached to suspended sediments and affecting aquatic organisms and is regarded as an emerging pollutant [36; 37]. Tonalide (AHTN) is a component used in non-alcoholic perfumes. It is the most produced synthetic polycyclic musk and can be found in a large variety of consumer products, including cosme, detergents, toiletties, and cigarettes. AHTN is not properly eliminated in conventional wastewater treatment plants (WWTPs) and enters rivers and bioaccumulates in the same way as TCS [38; 39]. It has been demonstrated that absorption by MWCNT is an efficient technique for the removal of these compounds [29; 40; 41]. In this study, we investigate for the first time the use of MWCNTs embedded in a polymeric film to perform TFME of three organic pollutants, namely CPS, TCS, and AHTN. The behaviour of a 10% MWCNT-containing film is compared with a film prepared with 30% dibutyl sebacate (DBS) as the plasticizer. Our aim was to explore whether the use of the plasticizer can be avoided in the preparation of the film, thereby improving the chromatographic analysis and the green characteristics of the TFME method.