esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Results and Discussion
### Validation of the Simulation
#### 4.1.2 Comparison of Aerodynamic Coefficients  
Tables 2 and 3 present the comparison of the simulation results from the transition model and the standard \(k\)-\(\varepsilon\) model for the drag and lift coefficients at the six AoAs and the experimental results [26; 29]. The numerical lift and drag coefficients calculated from mixed laminar/turbulent flows obtained with the semi-transition model by [29] are also presented. The transition calculations in the present study show a very good agreement with the measured data even at AoAs higher than 9.22\({}^{\circ}\). The exceptions to this are the drag coefficients at 14.24\({}^{\circ}\) and 20.15\({}^{\circ}\), which are underpredicted by 33% and 38%, respectively. This is primarily due to the sharp truncated trailing edge on the airfoil, where the drag is underpredicted [34]. Slight underpredictions for the drag coefficient of 8% and 9% are observed at 0\({}^{\circ}\) and 1.02\({}^{\circ}\), whereas lift coefficient overpredictions between 7.3% and 21.1% are observed at AoAs higher than 9.22\({}^{\circ}\). On the other hand, the simulation results by the standard \(k\)-\(\varepsilon\) model are largely overpredicted or underpredicted in the range of 389% to 36%. Accordingly, the transition results show considerably better predictions than the standard \(k\)-\(\varepsilon\) model. In addition, the transition simulations are found to be more accurate than the mixed laminar/turbulent flows obtained with the semi-transition model suggested in [29]. In particular, the semi-transition model was applied by splitting the computational region into laminar and turbulent domains and specifying laminar and turbulent zones using the standard \(k\)-\(\varepsilon\) model in each domain. However, the accuracy of the semi-transition model depends strongly on the transition location. Owing to the known transition location from the experimental report [26; 29], it is expected that the semi-transition model results provide a reasonable match with the experimental results. Therefore, the semi-transition model has a notable disadvantage in that the TO point from the experiment should be suggested in advance, prior to the simulation. Hence, this methodology is not currently useful for predicting the LS on an airfoil. Overall, comparison of the \(\gamma\)-\(Re_{\theta}\) transition model results with the experimental data demonstrated a good agreement. Accordingly, the subsequent LSB analysis is considered to be of sufficient accuracy.  
Figure 6: Comparison between the experiment and the simulation results of the pressure coefficient (C\({}_{\rm p}\)) with different turbulence models at selected angles of attack (AoAs) of 0\({}^{\circ}\) (**a**), 1.02\({}^{\circ}\) (**b**), 5.13\({}^{\circ}\) (**c**), 9.22\({}^{\circ}\) (**d**), 14.24\({}^{\circ}\) (**e**), and 20.15\({}^{\circ}\) (**f**) for the S809 airfoil (Re = \(2\times 10^{6}\)).
## 5 Outlook and Perspective
### Comparing Obtained Results with Prior Available Data

Table 1: Intercomparison between the results obtained in the current research and prior available data. There are other studies that providing practical approaches for predicting erosion induced by cavitation bubbles, as well as examining cavitation thermodynamics, lengths, and regimes [46; 47; 48; 54; 55]. The erosive power method [54], which predicts cavitation erosion on propellers based on computational fluid dynamics [56], is a suitable strategy for investigating the effects of materials and surface morphology. However, some nanoscale phenomena present in reality may be lost in this approach. Venturi-type cavitation reactors can also be used successfully to investigate cavitation thermodynamics, lengths, and regimes [46; 47; 48; 55]. These reactors, equipped with high-speed video or particle image velocimetry methods using the suppression techniques of hydrodynamic cavitation and thermodynamic effects, can accurately monitor periodic single-cloud cavitation, aperiodic multi-cloud cavitation, cavitation dynamics, lengths, and regimes under different temperature and pressure conditions. However, these methods have not reported fingerprints of erosion and corrosion. In sum, the intercomparison and review of the data provided in Table 1 reveal that material, surface morphology, and thermodynamic conditions can affect erosion induced by cavitation bubbles [9; 10; 17; 49; 50; 51; 52; 53]. Additionally, various experimental setups can offer more details regarding cavitation [46; 47; 54]. However, it is difficult to precisely determine the effects of surface morphology and material on the mitigation of erosion because all of these data were obtained under different conditions. To address these issues, the current study compares the effects of Al and brass materials, with and without riblets, on the mitigation of erosion under similar conditions. This strategy enables an accurate comparison of the material and surface morphology for erosion resistance applications. The results show that brass, both with and without riblets, provides greater erosion resistance compared to that of Al.
## 1 Introduction
The attachment of graphene oxide and MnFe\({}_{2}\)O\({}_{4}\) to form MnFe\({}_{2}\)O\({}_{4}\)/graphene oxide nanocomposite has enhanced properties over its counterparts such as high removal efficiency, magnetic separation, and reusability that can be perfect adsorbent for the elimination of neutral red dye and lead ions from wastewater. Various studies have been reported the combination of carbon-based materials and magnetic nanoparticles [36; 37; 38] for water treatment. Moreover, hierarchically porous reduced graphene oxide decorated with manganese ferrite (MrGO) was used to uptake methylene blue and malachite green dyes with high efficiency [39]. This study aimed to synthesize and characterize a novel nanocomposite of MnFe\({}_{2}\)O\({}_{4}\)/graphene oxide to absorb neutral red dye and lead ions from wastewater. The effect of different factors like contact time, adsorbent dosage, and pH on the adsorption process was investigated and discussed. The separation of the selected nanocomposite for reusability was determined. In a similar previous study, MnFe\({}_{2}\)O\({}_{4}\)/graphene oxide was synthesized for the removal of Pb\({}^{2+}\), As\({}^{3+}\), and As\({}^{5+}\) from water [40]. As the synthesis method, conditions, and phase ratios in the composite affect the surface area of the adsorbent and, consequently, affect the nanocomposite's adsorption capacity. Therefore, the current study clarifies the suitable method and conditions of MnFe\({}_{2}\)O\({}_{4}\)/graphene oxide synthesis for more effective pollutants removal and determining the applicability of this nanocomposite for the removal of additional pollutants.
## 4 Ensemble Learning IDS for IoV: Research Trends and Gaps
### Ensemble Learning IDS for IoV Taxonomy
#### 4.1.1 Based on Deployment Strategy  
The deployment of ensemble learning techniques in IDS for IoV involves two prominent strategies: centralized and distributed. These strategies address different aspects of the research problem by balancing scalability, real-time efficiency, and data privacy.
## 3 Results
### Risk Reduction Outcomes
#### 3.2.2 Property and Business Continuity Benefits  
In addition to its contributions to life safety, the proposed fire response system offers marked improvements in property preservation and operational continuity. Conventional sprinkler-based suppression, while effective in extinguishing flames, often results in substantial collateral damage due to widespread water dispersion--posing significant risksto sensitive electronic systems, archival materials, and high-value infrastructure. In contrast, the proposed system utilizes a residue-free clean extinguishing agent deployed in a targeted, non-destructive manner. This selective approach not only mitigates direct fire damage but also minimizes secondary losses, thereby supporting uninterrupted operations and reducing post-incident recovery costs.  
Experimental results in Section 3.1.3 showed that the suppression system achieved complete flame extinguishment within 13.2 s on average, using a localized spray pattern confined to a 2.5 m radius. This precise deployment, guided by edge-based fire localization, prevented over-application and reduced the risk of damage to adjacent equipment or furnishings. No electrical shorting, corrosion, or residue was observed post-discharge, confirming the system's suitability for data centers, control rooms, and commercial interiors.  
From an operational standpoint, rapid smoke extraction (Section 3.1.2) and minimal agent cleanup requirements enabled faster re-occupancy and reduced downtime. Under simulated continuity scenarios, the proposed system supported recovery and partial operation within 6 h, compared to estimated 48-72 h for sprinklered zones requiring drainage, drying, and equipment replacement. Furthermore, integration with SmartThings Edge and building management systems (BMS) allowed for immediate remote diagnostics and predictive maintenance scheduling, further expediting restoration workflows.  
Overall, the proposed solution demonstrates strong alignment with modern facility risk management objectives--protecting assets, minimizing downtime, and enabling faster recovery after fire incidents--thereby offering both functional and economic value to building operators and insurers.
# Current Status of HbA1c Biosensors
## 2 HbA1c Biosensors
### Antibody-Modified Biosensors
#### 2.2.2 Immobilization of a Glycated Pentapeptide as HbA1c Analogon  
Similar to the ARS/PBS competitive inhibition assay mentioned in the boronic affinity section, an immunoenzymatic assay for HbA1c detection has been developed based on the competitive binding of the HbA1c analyte and the surface-bound glycated pentapeptide (GPP) epitope to a known amount of anti-HbA1c antibody [42]. The enzymatic activity of glucose oxidase-antibody conjugate  
Figure 2: Schematic illustration of construction of HbA1c immunosensor by using (**A**) DOCA or Hp; (**B**) GPP; and (**C**) 3-MPA, PPy-Au NPs, and Mixed SAMs for HbA1c recognition.  
measured by absorbance spectroscopy is proportional to the amount of surface-bound anti-HbA1c antibody for GPP, but in an inverse relationship to HbA1c concentration. The synthetic GPP analogon shares the same amino acid sequence of the first five residues of the N-terminal \(\beta\)Hb. Compared to one time usage of the protein-modified cellulose membrane, the GPP-modified surface exhibits very good reproducibility and can be repetitively regenerated more than 20 times without loss of the binding affinity.  
[PERSON] and coworkers constructed a series of electrochemical immunosensors based on the competitive inhibition assay in which HbA1c competes with surface-bound GPP for binding to anti-HbA1c antibody. There are several key features of the electrode fabrication for those biosensors: (i) the GCE surface is coated with a mixed layer of oligo(phenylethylene) molecular wire (MW) and oligo(ethylene glycerol) (OEG) [43] or with AuNP-diazonium salt modified interface [44; 45]; (ii) in the amperometric immunosensor, the redox probe of 1,10-di(aminomethyl) ferrocene (FDMA) is covalently bound to the modified interface followed by the immobilization of GPP; (iii) Ru(NH3)6\({}^{3+}\)/Ru(NH3)6\({}^{2+}\) redox couple is used in the EIS immunosensor based on AuNP-diazonium salt modified interface; (iv) the OEG molecules work as the insulator to prevent nonspecific protein binding on the electrode surface; (v) in the amperometric mode, the relative current increases with the increase of HbA1c concentration; (vi) in the impedenmetric mode, the change of electron transfer resistance shows an inverse linear correlation with the increase of HbA1c concentration in the sample. The dynamic range of HbA1c detection of those three types of electrochemical immunosensor covers the physiological range of HbA1c level from 4.5-15%.
# Iterated Orthogonal Simplex Cubature Kalman Filter and Its Applications in Target Tracking
## 6 Conclusions  
A new iterated orthogonal simplex cubature Kalman filter (IOSCKF) is proposed to improve the nonlinear system filtering accuracy in target tracking. The new cubature points are determined using the orthogonal matrix after being modified using the spherical simplex-radial rule and the second-order Gauss-Laguerre quadrature rule. This lowers the high-order error terms. The Gauss-Newton iteration is used to maximize the posteriori state and covariance in the measurement update process until the iteration is finished. Target tracking simulations, including CV target tracking and spacecraft orbit tracking, are used to examine the performance of the proposed method, and the results reveal that the IOSCKF can achieve greater accuracy compared to the CKF, SCKF, and OSCKF. In spacecraft orbit tracking simulation, compared with the SCKF, the position tracking accuracy and velocity tracking accuracy of the OSCKF are increased by 2.21% and 1.94%, respectively, which indicate that the orthogonal transformation can improve the tracking accuracy. Furthermore, compared with the OSCKF, the position tracking accuracy and velocity tracking accuracy of the IOSCKF are increased by 2.71% and 2.97%, respectively, which indicate that the tracking accuracy can be effectively improved by introducing iterative calculation into the measurement equation, thus verifying the effectiveness of the method presented in this paper.  
Methodology, Z.L. and H.C.; Software, Z.L. and X.Y.; Investigation, X.Y. and L.L.; Resources, L.L.; Data curation, L.L.; Writing--original draft, Z.L. and H.C.; Funding acquisition, H.C. All authors have read and agreed to the published version of the manuscript.  
This research was funded by National Natural Science Foundation of China (Grant 62005320).  
Not applicable.  
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.  
This work was supported by the National Natural Science Foundation of China (Grant 62005320).  
The authors declare no conflicts of interest.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Filters** & **Position RMSE/m** & **Velocity RMSE/(m/s)** \\ \hline SCKF & 24.86 & 0.103 \\ OSCKF & 24.31 & 0.101 \\ IOSCKF & 23.65 & 0.098 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Spacecraft tracking RMSE of the various filters.
## 3 Results
### Regulation of DC-DC Signals  
Comparisons among the circuits working with CIL, CPL, and CIL-CPL are performed, starting with the voltage regulation value \(v_{cref}=32\) DC volts. The results shown below are simulated in discrete time and the parameters are given in Table 1; besides, voltage and current are measured with a sampling frequency in a fixed step equal to 5 kHz, a resolution of 12 bits, and a delay time of 1/5000 s. The chosen parameters of the \(LC\) filter are \(L=53\) mH, \(C=938\) uF, and the switching frequency \(Fc=5\) kHz, which cause a slower response time of the system; however, it maintains the voltage regulation within the limits with an error close to 3%. Figure 5 shows the behavior of the output voltage \(v_{c}\) and error for the different loads. Figure 5a shows that the voltage follows the reference signal \(v_{cref}=32\) V for the loads, and an overshoot of 12.5% is observed for the signal \(v_{c}\) when the load is CPL: 9.5% for CIL and 9% for CIL-CPL. The settling times are similar for the three signals and the steady-state errors are similar and lower than 1.5%, as shown in Figure 5b. These curves were created with the factor \(k=4\) and voltage reference \(v_{cref}=32\) V.  
Figure 6 shows the inductor currents for the three loads and transient behavior. The three currents have similar behavior in the transient and steady-state operations, changing only the final magnitude of the current as they vary according to the load.  
The regulation of the DC-DC signals with various reference values allows for the identification of how the control system works and is a good indicator to compare and find similitude among the different loads. Figure 7a,b show the output signal \(v_{c}\) for the different loads plotted against time. The tests were performed considering various steps in the reference signals as \(v_{cref}=10\) V at times between 0.05 and 0.1 s; \(v_{cref}=20\) V at times between 0.1 and 0.2 s; and \(v_{cref}=30\) V at times between 0.2 and 0.3 s. These figures show that the regulation is similar for cases when the reference signal is increased or reduced. There are some small differences in the response times and the maximum peaks of the signal, having a longer settling time for the system with a CPL load. In the steady-state for the three tests, the error is lower than 4%. Figure 7b shows that the error is increased when the reference signal is close to zero. Therefore, the three tests in this research show that signals have similar regulation behaviors.  
Figure 5: Simulated tests with \(k=4\) and voltage regulation of \(v_{cref}=32\) for loads CIL, CPL, and CIL-CPL.  
Figure 6: Inductor currents for the three loads.
## 3 Results
### Results of X-ray Diffraction
#### 3.3.2 Results of Wear Testing  
Figure 4 shows the results of wear rate with varied weight percentages of Fe\({}_{2}\)O\({}_{3}\) and with a constant weight percentage of Ag for Al/Fe\({}_{2}\)O\({}_{3}\)+ Ag hybrid nano-composites by changing loads by 2, 4, 6, 8 and 10N with a constant sliding velocity of 750 rpm. Wear rate minimizes with increases in the weight percentage of Fe\({}_{2}\)O\({}_{3}\) nanoparticles, and the improving of the wear resistance of Al/Fe\({}_{2}\)O\({}_{3}\) + Ag nano-composites is a result of good chemical bonding at the interfaces between Fe\({}_{2}\)O\({}_{3}\) ceramic nanoparticles and Ag with the Al matrix. Moreover, strain fields are formed around Fe\({}_{2}\)O\({}_{3}\) because of the difference in the thermal expansion coefficient of Fe\({}_{2}\)O\({}_{3}\) and Al. These strain fields make networks of dislocations at the interfaces between the Fe\({}_{2}\)O\({}_{3}\) and Al matrix, which in turn constrains the propagation of cracks. The uniform dispersion of Fe\({}_{2}\)O\({}_{3}\) and Ag nanoparticles into the Al matrix improves the Orwan strengthening of the product [19]. Therefore, the wear resistance of Al/Fe\({}_{2}\)O\({}_{3}\) + Ag nano-composites is improved and, in turn, enhances the tribological characteristics between the pin (Al/Fe\({}_{2}\)O\({}_{3}\) + Ag nano-composites) and the hardened steel disc, which reduces shear stresses between them. The preferred low wear rate for Al/12 Fe\({}_{2}\)O\({}_{3}\) + 1 Ag is a result of the same reasons mentioned for the micro-hardness and compressive tests. This is agreed with in [20].  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Sample No.** & **Fe\({}_{2}\)O\({}_{3}\) + 1 Ag (wt.\%)** & **Micro-Hardness (HV)** & **STD Error Bars** \\ \hline
1 & 0 & 17.13 & 3.14 \\ \hline
2 & 3 & 23.01 & 3.61 \\ \hline
3 & 6 & 26.23 & 3.95 \\ \hline
4 & 9 & 31.04 & 4.17 \\ \hline
5 & 12 & 34.19 & 4.47 \\ \hline
6 & 15 & 30.22 & 4.10 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Micro-hardness values of the samples of Al/Fe\({}_{2}\)O\({}_{3}\) + 1 wt.%Ag.  
Figure 3: The variation of micro-hardness with different wt.% of Fe\({}_{2}\)O\({}_{3}\).
# An Evaluation of the Effects of a Virtual Museum on Users' Attitudes towards Cultural Heritage
## 5 Discussion  
In this study, we evaluated the impact of the PC version of the virtual museum on users' attitudes towards cultural heritage and towards visiting physical museums, using contemporary theories on attitude change and presence as measuring factors.  
As a control, we developed an interactive website where users can visualize historical pieces as 3D objects, including the same information and functionalities as the virtual museum. The development process was successful in porting the virtual reality experience to a PC version, thanks to the Unity 3D game engine and to scalable and modular programming.  
The results showed that a virtual museum and an interactive website do not have main effects on attitudes toward heritage (except for a virtual visit). Specific results can be observed as a function of interactive effects of either thoughts, experience, or presence. As a consequence, we draw different conclusions depending on the type of object that we want to evaluate. If general attitudes are the focus, a virtual museum reduces the negative impact of negative thoughts, leading to positive attitudes, especially when high presence is perceived. However, if it is not possible to have a virtual museum, an interactive website can be useful regardless of presence if it is designed to generate mostly positive thinking at the beginning with a simple instruction as a pop-up page (e.g., Why do you think that museums exist?). If a specific attitude is the focus, other conclusions are possible. For example, attitudes toward heritage are affected by presence and thought direction with main and interactive effects, regardless of the multimedia experience. Therefore, we recommend both as generating positive thoughts and creating high presence environments.  
Another conclusion can be derived from face-to-face or virtual visits. A virtual museum leads to positive attitudes regardless of thought direction, but an interactive website can have positive consequences as a function of high presence and positive thinking. However, for virtual visits, the opposite is observed. Interaction via thinking and high presence are useful in developing positive attitudes, but no interactive or main effects seem to be critical for the case of the interactive website. Therefore, according to the conducted experiments, which technological product to develop should be chosen depending on the attitude one wants to promote in potential users.
# Satellite-Derived Bathymetry for Selected Shallow Maltee Coastal Zones
## 2 DataSets
### In Situ Data  
For the very nearshore coastal area up to depths of 100 m, where dynamic sediment transport was expected to alter the bathymetry regularly, in situ bathymetric data were collected via the PowerDolphin, a remote surface vehicle (RSV) manufactured by PowerVision [33]. This instrument is a surface water drone which works with PowerSeeker to automatically scan the specified waters and produce bathymetric maps containing accurate underwater information shown in both a visual and digital manner [34]. Moreover, depth values further offshore were obtained from the lidar survey carried out by the Malta Planning Authority in 2018 [35]. This dataset was only used for regions with depths between 10 m and 35 m. Although the measurements were taken a few years prior to this study, due to the nature of the seabed, the values are assumed to have remained constant. Obtaining data from two different in situ techniques were essential to cover the entire region of interest.  
Through the use of GIS software, a subset of the in situ data collected by the PowerDolphin and by the lidar data was grouped to obtain points spread over the satellite image (Figure 2).  
Figure 2: In-situ data points obtained by lidar and sonar techniques.