esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion
### Usage Effects on the Flight Trajectories of the Balls  
The simulations of the flight trajectories of the soccer balls show that in powerful long kicks (initial speed 30 m/s, release angle 20\({}^{\circ}\)), the flight distance (horizontal) differs depending on the ball type. In particular, the new Telstar18 and Merlin reach farther distances compared to the used ones. However, the flight distance of the new Derbystar was approximately 1 m shorter than the used one. Furthermore, the simulations of free kicks (initial speed 20 m/s, release angle 15\({}^{\circ}\)) show that the vertical positions (height)  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Airflow Velocity** & **Type** & **Telstar18** & **Merlin** & **Derbystar** \\ \hline \(Re=3.5\times 10^{5}\) & Used ball & 0.22 (about 10\% up) & 0.15 (about 7\% up) & 0.18 (about 20\% up) \\ \cline{2-5} (about 23 m/s) & New ball & 0.20 & 0.14 & 0.15 \\ \hline \(Re=5.0\times 10^{5}\) & Used ball & 0.21 (about 15\% up) & 0.17 (about 15\% up) & 0.15 (about 7\% down) \\ \cline{2-5} (about 33 m/s) & New ball & 0.18 & 0.15 & 0.16 \\ \hline \hline \end{tabular}
\end{table}
Table 1: \(C_{D}\) values of the new and used balls used in this experiment.  
of the ball impact point at the net placed at 20 m from the kick position differed by approximately 0.2 m depending on the ball type. These differences are approximately comparable to the size of a soccer ball and are therefore significant from the goalkeeper's position. Furthermore, depending on the ball type, the difference in height between the used and new balls varied significantly from 0.03 m (Derbystar) to 0.09 m (Merlin). These results are similar to the variations in the flight trajectories depending on the ball type reported in previous studies [9,19]. However, in these tests, the computation results were obtained using the \(C_{D}\) values from the wind tunnel tests. Further studies are necessary to determine the flight trajectories of used balls through a launching device such as a kicking robot.  
The differences in the flight distances may be attributed to the worn surface of the kicked ball, the ball type, and the properties of the leather used for the balls (Figure 8). The Telstar18 and Merlin balls are manufactured using rubber-based synthetic leather and adhesive bonds, while the Derbystar balls are manufactured using artificial leather-based synthetic leather and hand-stitching. However, a detailed study on this topic using a super-microscope is necessary for the future.  
In summary, the surface conditions (roughness, worn and torn leather materials) of the modern soccer balls change with usage, causing variations in the airflow around the balls, which affect the aerodynamics and flight trajectories of the balls. Based on the variations of the aerodynamic forces acting on the ball depending on the surface structure, we assumed that the surface conditions of the ball are essential to study their aerodynamics in addition to the number and shape of panels, ball orientation, and surface structure reported in previous studies [6,8,18].
# Recent Advances of MXene-Based Electrochemical Immunosensors
## 3 Electrochemical Immunosensors Based on MXenes
### MXenes as Electrode-Modified Nanomaterials in Electrochemical Immunosensors
Since massive amino terminals of PAMAM provided abundant active sites, AuNPs were subsequently self-assembled to construct AuNPs/MXene@PAMAM 3D heterogeneous nanoarchitecture. Benefiting from the structural and functional advantages of the AuNPs/MXene@PAMAM, the resulting immunosensor showed desirable stability, high specificity and good sensitivity for cTnT detection, with a LOD of 0.069 ng mL\({}^{-1}\). MXene-based immunosensors for detecting sweat biomarkers have also been reported. A wearable microfluidic-integrated impedimetric immunosensor was developed for cortisol detection in human sweat, based on a Ti\({}_{3}\)C\({}_{2}\)T\({}_{x}\) MXene-laser-burned graphene (LBG) electrode [55]. The strategy of depositing highly conductive Ti\({}_{3}\)C\({}_{2}\)T\({}_{x}\) MXenes onto LBG electrode addressed the problem of inter-flake disconnection caused by burning and transferring, thereby improving the electrical properties of the LBG electrode. Integrated with a  
Figure 3: Schematic illustration of the fabricating procedure of the immunosensor for Apo–A1 and NMP 22 detection. Adapted with permission from Ref. [53]. 2020, Wiley–VCH GmbH. microfluidic system, the prepared patch immunosensor showed good selectivity, as well as a low LOD of 3.88 pM. Based on L-cys/AuNPs/MXene modified conductive thread electrode, a label-free immunosensor was fabricated for non-invasive detection of sweat cortisol (Figure 4) to identify adrenal gland disorders [56]. Since L-cys-/AuNPs/MXene not only enhanced the electrochemical conductivity of the conductive thread electrode, but also increased the surface area for antibody immobilization, the immunosensor achieved high sensitivity, good reproducibility and long-term storage stability. Moreover, the immunosensor was successfully applied for cortisol detection in artificial sweat, with satisfactory performance. [PERSON] et al. [57] reported a sandwich-type immunosensor for the detection of PCT, a key biomarker of septicemia. In their report, glassy carbon electrode (GCE) was modified with AuNPs/d-S-Ti\({}_{3}\)C\({}_{2}\)T\({}_{\rm X}\) (gold nanoparticles functionalized sulfur-doped MXene) to increase surface conductivity and the amount of capture antibody. The c-g-C\({}_{3}\)N\({}_{4}\) (carboxylated graphitic carbon nitride) was used to label detection antibody via a strong interaction between -COOH of c-g-C\({}_{3}\)N\({}_{4}\) and -NH\({}_{2}\) of monoclonal detection antibody, thus achieving stable signal amplification. The resulting immunosensor realized an ultrasensitive detection of PCT, with a LOD of 2.0 fg mL\({}^{-1}\).
# Privacy Framework for the Development of IoT-Based Systems
## 4 Related Work
### Comparative Analysis of Existing Approaches  
Several approaches have been introduced to address security and privacy concerns in IoTSs. Traditional security mechanisms focus on mitigating vulnerabilities across system layers--such as using blockchain for secure communication--but often neglect the integration of privacy-by-design principles and offer limited guidance for developers during the system lifecycle [25; 26].  
AI-based techniques, including machine learning, deep learning, and federated learning, have shown promise in detecting threats like botnets and malware [31; 32]. However, their direct applicability to the IoTS development process remains limited.  
Zero Trust models represent a shift from implicit trust to continuous verification [35], yet their implementation in resource-constrained IoT environments presents significant challenges.  
Existing frameworks and guidelines provide valuable insights and domain-specific recommendations [37], but often lack a systematic, developer-centric approach to embedding privacy across all stages of IoTS development.  
Privacy-by-Design frameworks--such as those by [PERSON] et al. [22]--offer structured guidance for incorporating privacy, yet typically fall short in terms of tooling support and full lifecycle integration.  
Our proposed framework seeks to bridge these gaps by delivering a systematic, lightweight, and developer-oriented approach that incorporates Privacy by Design principles throughout the IoTS development lifecycle. It emphasizes practical privacy require  
\begin{table}
\begin{tabular}{l l} \hline
**Guideline Name** & \\ \hline
1-Minimize data acquisition & 16-Distributed data storage \\
2-Minimize the number of data sources & 17-Knowledge discovery-based \\
3-Minimize raw data intake & aggregation \\
4-Minimize knowledge discovery & 18-Geography-based aggregation \\
5-Minimize data storage & 19-Chain aggregation \\
6-Minimize data retention period & 20-Time period-based aggregation \\
7-Hidden data routing & 21-Category-based aggregation \\
8-Data anonymization & 22-Information disclosure \\
9-Encrypted data communication & 23-Control \\
10-Encrypted data processing & 24-Logging \\
11-Encrypted data storage & 25-Auditing \\
12-Data granularity reduction & 26-Open source \\
13-Query response & 27-Data flow diagrams \\
14-Repeated query blocking & 28-Certification \\
15-Distributed data processing & 29-Standardisation \\ \hline \end{tabular}
\end{table}
Table 1: PbD guidelines (adapted from [PERSON] et al. [22]).  
ment extraction, workflow support, and adaptive privacy risk management, making it particularly suitable for resource-constrained IoTS environments.  
Table 2 summarizes and compares key characteristics of these approaches, highlighting their main focus areas and limitations:
# An Early Investigation of the HHL Quantum Linear Solver for Scientific Applications
## 5 Scientific Applications and Evaluation
### Power Flow Problem in Power Grid
#### 5.1.2 Performance Evaluations  
The sparsity of all tested coefficient matrices is \(84.375\%\) after the expansion, with condition numbers in the range of \([5.950,5.970]\). The minimums of the magnitude of eigenvalues are in the range of \([12.263,12.506]\), and the maximums are \([73.209,74.659]\). Figure 3b,c provide illustrative evidence of the use of a less precise linear solver in the iterative method like the N-R method. Although the N-R method with an HHL subroutine converges slower than a classical linear solver in MATLAB, all methods converge under the same criteria and obtain a similar solution. A trade-off between convergence speed and complexity of linear system solving exists in our experiments.  
On the other hand, if we compare the values of normalized error \(\parallel\left|x\right>-\left|x\right>_{HHL}\parallel_{2}\), when \(n_{c}=4,5,6,7\), using more clock qubits indeed leads to lower error from the HHL algorithm itself. However, increasing \(n_{c}\) does not imply less error on the solution vectors, \(\vec{x}_{HHL}\), nor faster convergence by looking at the values of \(\parallel\vec{x}-\vec{x}_{HHL}\parallel_{2}\) and \([\Delta\vec{P}^{T}\ \Delta\vec{Q}^{T}]^{T}\) in Figure 3. The HHL algorithm with \(n_{c}=5\) gives the fastest convergence, which is smaller than the default value, \(6\), from Equation (3).
# Ephemeral Node Identifiers for Enhanced Flow Privacy
## 5 Discussion  
Overall, the use of eNIDs makes it impossible for an attacker to perform a flow correlation from using source address values, which is an attack that is easily realised today. Additionally, there are other possible security benefits from use of eNIDs.
## 1 Introduction
The number of grooves that is involved in diffraction is 2000, giving a pulse-front tilt of 40 \(\mu\)m, _i.e._, 130 fs, that cannot be neglected for few-femtosecond pulses. Nevertheless, it is possible to realize grating monochromators that do not alter the temporal duration of ultrashort pulses by using two gratings in a time-delay compensated configuration, where the second grating compensates for the time and spectral spread introduced by the first one [11; 12; 13; 14]. Pulses as short as 8 fs have been measured at the output of a double-grating monochromator at 35 nm (H23 of Ti:Sa laser) [15]. The main drawback of these configurations is the use of two gratings that increase the complexity and reduce the efficiency. Let us analyze the conditions to have the minimum temporal broadening from a single grating. Once the output bandwidth \(\Delta\lambda\) has been defined the minimum number of grooves \(\mathrm{N}_{\mathrm{min}}\) that have to be illuminated to support such a bandwidth is \(|m|\mathrm{N}_{\mathrm{min}}=\lambda/\Delta\lambda\)[16]. The corresponding minimum pulse front-tilt at half-width that can be obtained by a single grating, \(\Delta\tau_{\mathrm{G,min}}\), is:  
\[\Delta\tau_{G,\mathrm{min}}\equiv\frac{0.5}{c}\big{|}m\big{|}\lambda N_{ \mathrm{min}}=\frac{0.5}{c}\frac{\lambda^{2}}{\Delta\lambda} \tag{2}\]  
that is close to the Fourier limit given by Equation 1. Therefore, a single grating may be used for the spectral selection of ultrashort pulses without altering in a significant way the pulse duration, provided that the number of illuminated grooves at first diffraction order is equal to the actual resolution. In this paper, we analyze two configurations for the spectral selection of ultrashort pulses: the classical-diffraction mount and the off-plane mount. We discuss the advantages and drawback of both mountings and present a configuration, where the two geometries are joined in a new and innovative design, which overcomes the limits of the two single configurations. The design allows us to realize a broad-band grazing-incidence single-grating monochromator with either ultrafast time response with low spectral resolution or a longer time response with higher resolution.
# Weak-Edge Extraction of Nuclear Plate Fuel Neutron Images at Low Lining Degree
## 3 Edge Extraction Algorithm
### Image Preprocessing  
Subject to the imaging system characteristics and various external noises (e.g., \(\gamma\) white spot noise, Gaussian-Poisson mixed noise, and electronic noise), the obtained neutron images are characterized by a low SNR, poor contrast, and blurred edges. Thus, it is necessary to preprocess neutron images.  
First, 10 neutron images (sample/background) were superimposed and averaged, respectively, to reduce the noise generated by the CCD device. Then, we chose adaptive median filtering to remove the obvious impulse noise, like salt and pepper. Next, the background image, after superimposed averaging, was divided by the sample image and then taken logarithmically to achieve a normalized image. Due to the normalized neutron image's low contrast and blurred edges, the method based on the visual characteristics was adopted to enhance the edge and local information details. This method uses a three-Gaussian model to simulate the receptive fields of retinal ganglion cells and convolves it with the image to improve image quality and facilitate subsequent edge detection. Finally, after edge sharpening, we used bilateral filtering [23] to smooth the image, combining spatial domain information (spatial proximity) and numerical domain information (pixel grayscale similarity) to smooth out noise while protecting the edges. The kernel size of the bilateral filter is a user-defined parameter that balances edge localization and noise rejection, and a standard \(7\times 7\) kernel was used in this paper.  
Appropriately preprocessing the fuel plate neutron image reduced the influence of background areas and noise for edge extraction while improving the quality of the image to prominently display the outside edge information of its aluminum cladding for subsequent operations.
# Hybrid LSTM Model to Predict the Level of Air Pollution in Montenegro
## 3 Implementation Methodology
### Performance Evaluation  
In order to provide a baseline for comparative analysis and to assess the proposed model's performance, four standard evaluation metrics were applied: Mean Square Error (MSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Coefficient of Determination \(R^{2}\).  
MSE is a measure used to quantify the extent of deviation between the predicted values (\(\widehat{z_{i}}\)) and measured values (\(z_{i}\)). A lower MSE value indicates a smaller deviation. The MSE value is computed using Equation (17):  
\[MSE=\frac{1}{n}\sum_{i=1}^{n}(z_{i}-\widehat{z}_{i})^{2}. \tag{17}\]  
MAE measures the extent of error between the predicted value and the measured value. The MAE value can be obtained by Equation (18):  
\[MAE=\frac{1}{n}\sum_{i=1}^{n}|z_{i}-\widehat{z}_{i}|. \tag{18}\]  
MAPE quantifies the error between the predicted and measured values as a percentage of the measured values. The MAPE value is computed based on Equation (19):\[MAPE=\frac{1}{n}\sum_{i=1}^{n}\left|\frac{z_{i}-\widehat{z_{i}}}{\widehat{z_{i}}} \right|100\%. \tag{19}\]  
The \(R^{2}\) measure indicates how well the air pollutant values in a regression model explain the variation in the CAQI value. It quantifies the proportion of the total variation in the CAQI values that can be accounted for by the air pollutants. The \(R^{2}\) value ranges from 0 to 1, and a higher \(R^{2}\) value indicates a better fit, meaning that a larger proportion of the variation in the CAQI values is captured by the air pollutants. The \(R^{2}\) measure is calculated as shown in Equation (20):  
\[R^{2}=1-\frac{\sum_{i=1}^{n}(z_{i}-\widehat{z_{i}})^{2}}{\sum_{i=1}^{n}(z_{i} -\overline{z})^{2}}, \tag{20}\]  
where \(\overline{z}\) represents the mean of the measured values and \(n\) is the number of samples.  
The issue of bias can arise in performance validation when the dataset is split, trained, and tested only once [26]. This implies that the validity of the results obtained from the testing dataset may be affected when the testing subset is altered. To address this problem, each model in our work was rebuilt five times using different random subsets of training and testing samples, while maintaining a consistent splitting proportion of 75:25.
# Communication Architecture in Mixed-Reality Simulations of Unmanned Systems
## 5 The Proposed Architecture Design  
Several topologies can be identified to fit the requirements of the communication system for the MR simulation that is defined in the previous section, and the most relevant topologies are depicted in Figure 2. A possible suitable topology uses two different networks (the network of HWEs and network of SWEs) with one bridge to relay the messages between them (labeled as _MSG routing_ in Figures 2 and 3). This bridge is represented by the simulation platform, i.e., which is most commonly the GCS. SWEs can be modeled either centrally within the GCS machine (as shown in Figure 2a), or individually in a separate machine that is connected to the GCS via TCP/UDP sockets to distribute the computational load on the simulation platform (as shown in Figure 2b). These topologies require only one communication modem to provide the simulation of all the SWEs; thus, they provide cheaper and less error-prone testbeds for high fidelity system validation. On the other hand, they require an addressing mechanism for routing in both the networks mentioned in the previous section. Further, they have to address the accuracy-based aspects of the communication model discussed in Section 6.  
The second most related communication system topology uses a separate modem for each entity in the simulation (both SWEs and HWEs), so it creates one common network (as depicted in Figure 2c) with no need for any message routing and special addressing. Using RF modems for all entities also deals with the effect of using a single relay point on the bandwidth of the HWE-SWE connection discussed in Section 6.2. On the other hand, this topology requires an additional modem for every SWE in the system, so it decreases the scalability of the simulations and increases the cost. Modems are also susceptible to hardware-related errors, so this topology can be considered more error-prone compared to the previous case. Moreover, this topology breaks the concept of the purely virtual entities since the SWEs, in this case, could be considered as entities with the hardware-deployed communication layer. For these reasons, only the topologies with two communication networks are considered hereafter.  
Figure 2: Various communication system architectures—(**a**) virtual entities within a ground control station (GCS); (**b**) virtual entities apart from the GCS that use it for message relay; and (**c**) separated modems for all entities.
# The Design and Investigation of Hybrid a Microfluidic Micromizer
## 1 Introduction
Moreover, it has also been examined that much less work has been conducted on the hybrid approach in which the combination of active and passive approaches is used for mixing applications. A hybrid microfluidic approach might offer numerous advantages to generate more versatile and efficient microfluidic systems, such as increasing the control and precision of the flowing fluid, reducing energy consumption, flexibility, and versatility, enhancing mixing performance, etc. In addition, the hybrid microfluidics micromixer may effectively solve the backflow issues and achieve robust backflow-free micromixing due to its precise mixing control, making this study more attractive in the point-of-care testing (POCT) application. Thus, there is great potential exists in using a hybrid approach in the design, development, and research of microfluidic systems for controlling and manipulating fluid particles, especially for mixing applications. The main objective of this research work is to numerically evaluate the mixing performance of the microfluidic micromixer with different micropillar shapes and different micropillar gaps using the hybrid actuation approach. The nature of acoustic streaming velocity, acoustic velocity, and acoustic pressure were also investigated in the presence \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Year**} & \multirow{2}{*}{**Goal**} & **Microchannel** & **Microfluidic** & \multirow{2}{*}{**Microchannel Design**} & **References** \\  & & **Type** & **Type** & & \\ \hline \multirow{8}{*}{2022} & Investigation of & & & & \\  & different operational & & & & \\  & parameters by & & & & \\  & combining the fractal & & & & \\  & principle with the & Cantor fractal & & & \\  & multi-objective genetic & & & & \\  & algorithm and the & & micromixers & & \\  & multi-objective & & & & \\  & optimisation of cantor & & & & \\  & fractal baffle & & & & \\  & micromixers. & & & & \\ \hline \multirow{8}{*}{2019} & Design and & & & & & \\  & optimisation of an & & & & \\  & active-based & & Microchannel & & & \\  & microchannel & with & & & \\  & incorporated with & & micropillars & & \\  & micropillars. & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: _Cont._of micropillars with different gaps at different Reynolds numbers. Subsequently, based on these characteristics, mixing performance was evaluated due to acoustic streaming and its impact on species transport. The findings from this study also demonstrated how the proposed hybrid microfluidic micromixer can enhance the mixing index between two different heterogeneous species. The results obtained in this study can be extremely helpful for the design and modifications of microfluidic micromixers for the high-quality mixing of fluids.
# VSFCM: A Novel Viewpoint-Driven Subspace Fuzzy C-Means Algorithm
## 4 Experimental Results  
In this section, we validate the clustering ability of the proposed VSFCM algorithm through a series of experiments. In the comparative experiment section, five relevant algorithms are selected, including V-FCM, SCAD, ESSC, FRFCM, and DVPFCM. Among the two algorithms of SCAD, the structure of the first one is more complex and closer to the algorithm in this paper, so we chose it to compare with ours. In terms of initialization methods, we compare our algorithm with the HDCCI algorithm and present it visually.  
The testing data sets include two artificial data sets, 10 UCI machine-learning data sets, and the Olivetti face database. The artificial data sets DATA1 and DATA2 are composed of Gaussian distribution points obtained by generation tools. The tested UCI data sets [34]include Iris, Wireless Indoor Localization, Wine, Breast Cancer Wisconsin, Seeds, Letter Recognition (A, B), Ionosphere, SPECT heart data, Aggregation, and Zoo. These UCI data sets are popular and representative of the field of machine learning. The Olivetti face database corresponds to a collection of 40 people and 10 pictures per person. We select 200 pictures corresponding to 20 people from it, with a total of 1024 attributes.  
Table 2 counts the basic information of two artificial data sets and 10 UCI machine learning data sets, which include a total number of instances, features, and reference clusters. For all experiments, the default values are selected for the parameters, and the specific settings are as follows: \(m=2,\ t=2,\ \varepsilon=10^{-5}\). For convenience, the selection of \(cd\) in the CDCI algorithm is calculated based on (12).