esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Conclusions and Future Work  
In this paper, we propose a hazard analysis approach for the SOTIF in the IRDAS. This involves the extended STPA method for identifying SOTIF-related hazardous factors, as well as a complex network-based approach for the quantitative evaluation of the identified hazardous factors. The extension of the feedback part in the STPA control structure is helpful for the deeper understanding of the situational awareness process of the IRDAS. Based on that, the hazardous factor classification is beneficial for safety practitioners to identify more comprehensive hazardous factors specified in the SOTIF domain. The hazardous factors network and the customized topological indexes explore the complexity of the identified hazardous factors. This can help find the key factors and make targeted hazard control strategies. The usefulness of the proposed approach is validated on the TIDS. A total of 162 SOTIF-related hazardous factors of three hazards are identified, among which the hazardous factors that play the most important roles in the hazard causation paths are found. Based on that, some practical hazard control strategies are designed and validated for enhancing the safety of the TIDS. The proposed approach has the potentiality to be used in the hazard analysis and the hazard control strategy formulation of the railway autonomous operation systems.  
The extension of STPA in this approach emphasizes the feedback part of the system to analyze the problems of the improper system behavior and the reasonably foreseeable driver misuse. In future work, we plan to study the cognitive process of the driver in complex driving processes, to find a way to form a more systematic mental model of the driver. This could provide more insights into the analysis of driver misuses. In addition, after a long period of operation, if sufficient operational data can be collected, the statistical quantitative strengths of cause-effect relationships in the HFN can be calculated. Then, the HFN can be changed into a weighted network, within which more targeted hazard control strategies can be developed.  
Conceptualization, S.Z., J.L. and T.T.; methodology, S.Z. and J.L.; writing--original draft preparation, S.Z.; writing--review and editing, S.Z., J.L., and T.T.; supervision, T.T. All authors have read and agreed to the published version of the manuscript.  
This work is co-supported by the Fundamental Research Funds for the Central Universities (No. 2021 QY007), and the National Natural Science Foundations of China (No. 61803019, No. 61803020).  
Not applicable.  
The authors declare no conflict of interest.
## 4 Adsorption Study
### Effect of pH on the Removal of RB  
The adsorption of RB dye onto CC biochars is greatly influenced by the pH of the solution. Thus, the charge in the adsorbent surface, the degree of ionization, and the nature of the dye solution are affected by the pH. The pH regulates the electrostatic interactions between the functional groups available on the CC biochar surfaces and the RB dye solution. The effect of the initial pH on the removal of RB from an aqueous solution (60 mg/L RB amount) is investigated through the change in pH from 2 to 12 at room temperature (27 \(\pm\) 2 \({}^{\circ}\)C). It can be seen that a removal of 99.5, 100, and 100% is obtained with CCB500, CCB600, and CCB700, respectively, at pH 2 (Figure 4).  
The RB dye is negatively charged (sulfonate-rich); thus, the positively charged acidic solution favours its adsorption due to the high electrostatic attraction forces between adsorbent and adsorbate. Further, the adsorption capacity is high at a low pH and decreases with an increasing pH due to the repulsive interactions between negative sulfonate groups and negatively charged biochars (CCB500 and CCB600) at a high basic pH.  
Furthermore, the adsorbent's surface is positively charged at a low pH, which attracts RB dye (anionic dye). Under acidic conditions, the functional groups on the surface of the adsorbent become polarized, adding electrostatic interactions to -H bonding and the Van der Walls force [38]. In addition, as the biochar surface is negatively charged under alkaline conditions (pH > 7), the anionic RB molecules are repelled, resulting in a decrease in dye removal efficiency [39]. It can be seen, however, that the adsorption performance of CCB700 remains good for high pH values, probably due to its high surface area, mineral composition, and high pore volume [11].  
The influence of the RB dye solution pH on adsorption efficiency could also be investigated by looking at the pH\({}_{\text{PZC}}\). As shown in Figure 5, the determination of the pH\({}_{\text{PZC}}\) at the intersection of two plots reveals that the adsorbent surface has a zero charge at a pH of 11, 11.35, and 12.53 for CCB500, CCB600, and CCB700, respectively. In this way, the surface sites of the CC biochars are positively charged with the loose protons at pH values below pH\({}_{\text{PZC}}\) (pH < pH\({}_{\text{PZC}}\)), which favours the uptake of anionic dyes due to an electrostatic attraction force [31; 35]. These results are in line with the pyrolysis tempera  
Figure 4: Effect of contact time, initial concentration, dose, and pH of biochar on RB removal.  
ture, which increases the pH\({}_{\text{IPZC}}\) and biochar mineral content (Table 1), in particular, the Ca concentration.
## 3 Contextual Received Signal Strength Approach
### CRSS Approach  
#### 3.4.1 Analysis from Spatial Data  
A complete spatial randomness (csr) is synonymous with a homogeneous Poisson process in \(\mathbb{R}^{d}\). (\"This process has the property that, conditional on \(N(A)\). The number of events in a bounded region \(A\subset\mathbb{R}^{d}\), the events of the process are independently and uniformly distributed over \(A\). That is, given \(N(A)=n\), the ordered \(n\) tuple of events \((s_{1},...,s_{n})\) in \(A^{n}\) satisfies \(Prob(s_{1}\in B_{1},...,s_{n}\in B_{n})=\prod_{i=1}^{n}(|B_{i}|/\left|A\right|),B_{1},...,B_{n}\subset A^{n})\)[33] (p. 586). Distances may be measured between sample and nearest events. For a completely spatial process, i.e., a homogeneous Poisson process, the distribution theory for nearest neighbor distances is well known [34], where the density of the positive random variable \(W\) in \(\mathbb{R}^{2}\) is  
\[g(W)=2\pi\lambda we^{(-\pi\lambda w^{2})}. \tag{6}\]  
Theoretical calculations show that, under csr in \(\mathbb{R}^{2}\), the probability \(G(r)\) that the distance from a chosen event to its nearest event is less than or equal to \(r\) can be expressed by  
\[G(r)=1-e^{(-\lambda\pi r^{2})}, \tag{7}\]  
where \(\lambda\) is the intensity of the homogeneous point process. For the homogeneous Poisson process, the probability that there are no events within distance \(x\) for an arbitrary point is \(e^{(-\lambda\pi x^{2})}\). Hence, the distribution function of the point to the nearest event distance is \(1-e^{(-\lambda\pi x^{2})},x>0\).
# Performance Evaluation of CF-MMIMO Wireless Systems Using Dynamic Mode Decomposition
## 3 Channel Estimation
### Channel Estimation Using PiDMD  
If we know beforehand that the correlation structure follows a Toeplitz matrix form, we can employ PiDMD to generate a matrix with the desired structure using the empirical information available. Figure 10 illustrates the calculated correlation matrix under the specified simulation scenario.  
The resulting Toeplitz matrix is not sufficiently satisfactory in terms of the eigenvalues obtained compared to the theoretical values. At this stage, following the proposed algorithm, DMD is initially used to reduce the order of the system, and subsequently, PiDMD values are applied to the resulting system. Figure 11 illustrates the outcome of the successive application of DMD and PiDMD.  
Figure 11: The matrix **R** obtained from empirical data through the successive application of DMD and PiDMD.  
Figure 10: PiDMD is used to obtain a Toeplitz matrix from empirical data.
## 6 Limitations and Future Work  
The design heuristic presented in this article is limited in range and granularity. In the simulation study in Section 4 we investigated a design space of 2-5 pads and 6-12 gates which shows linear behaviour according to the design heuristic. This might allow for extrapolation beyond the limits of the studied design space, but the consistency is unknown. Furthermore, we looked at 1000, 1500 and 2000 daily passengers, which is a rather coarse resolution; more granularity would allow for more precise application of the design heuristic. Another limitation worth mentioning is that we assumed uniform characteristics across all agents (e.g., all passengers have the same walking speed). While both passengers and vehicles will have varying characteristics in the real world, it was shown in a related study that this effect plays a negligible role [24].  
Future work, as indicated in Section 3.5, should entail a more detailed analysis of peaks and imbalances of demand. Staying below the defined thresholds of \(PHCAP=264\) and \(PICAP=33\) guarantees low delays; but exceeding the thresholds does not necessarily lead to high delays (see also Figure 9). We propose future work on demand peaks to include not only the tip of a peak, but also the breadth. In this way statements can be made about how long the capacity threshold is exceeded. Similarly, we propose future work on imbalances to not only include the maximum imbalance, but also how long a high imbalance is maintained.  
Another aspect worth considering is vehicle down-time at the gates or stands (e.g., for charging). Currently, the vertiport simulation operates in a touch-and-go fashion, meaning that vehicles are available for their next mission right after de-boarding is finished. In future real world operations, this assumption will only be true of some vertiports, while a down-time exceeding the boarding process can be expected for most vertiports. How this impacts vertiport operations needs to be investigated in the future.  
Conceptualization, L.P. and M.H.; methodology, L.P.; software, L.P.; resources, M.H.; data curation, L.P.; writing--original draft preparation, L.P.; writing--review and editing, L.P. and M.H.; visualization, L.P.; supervision, M.H. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research received no external funding.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Conflicts of Interest:** The authors declare no conflicts of interest.
# Verifying Mutual Exclusion Algorithms with Non-Atomic Registers
###### Abstract  
The work described in this paper develops a formal method for modeling and exhaustive verification of mutual exclusion algorithms. The process is based on timed automata and the Uppaal model checker. The technique was successfully applied to several mutual exclusion algorithms, mainly under the atomic memory model, when the read and write operations on memory cells (registers) are atomic or indivisible. The original contribution of this paper consists of a generalization of the approach to support modeling mutual exclusion algorithms with non-atomic registers, where multiple read operations can occur on a register simultaneously to a write operation on the same register, thus giving rise to the _flickering_ phenomenon or multiple write operations can occur at the same time on the same register, hence determining the _scrambling_ phenomenon. The paper first clarifies some consistency rules of non-atomic registers. Then, the developed Uppaal-based method for specifying and verifying mutual exclusion algorithms is presented. The method is applied to the correctness assessment of a sample mutual exclusion solution. After that, non-atomic register consistency rules are rendered in Uppaal to be embedded in the specification methodology. The paper goes on by presenting different mutual exclusion algorithms that are studied using non-atomic registers. Algorithms are also investigated in the context of a tournament tree organization that can provide standard and efficient mutual exclusion solutions for \(N>2\) processes. The paper compares the proposed techniques for handling non-atomic registers and reports about their application to many other mutual exclusion solutions.  
mutual exclusion algorithms; model checking; atomic registers; non-atomic registers; flickering; scrambling; timed automata; Uppaal
## 2 Materials and Methods
### Data Collection Equipment  
Participant anthropometric measurements included body mass and height, which were measured using an InBody 230 (Biospace, Seoul, Republic of Korea) and a Seca 206 stadiometer (seca, Hamburg, Germany), respectively.  
A motion capture system was employed to record full-body movements during side hopping. The system consisted of eight Miqus Video Cameras (Qualisys AB, Gothenburg, Sweden), operating at a sampling frequency of 100 Hz and a resolution of 720 p. Prior to data collection, a 2.0 \(\times\) 2.0 \(\times\) 2.0 m performance volume was calibrated with an error \(<\) 0.50 mm. Two 60 \(\times\) 40 cm force platforms (Bertec Inc., Columbus, OH, USA) positioned side by side and fixed to the ground were used to record ground reaction forces at a 2000 Hz sampling frequency and in synchrony with the motion capture system. The Qualisys Track Manager version 2024.2 (Qualisys AB, Gothenburg, Sweden) software was employed to collect both video and force data.  
After arriving at the laboratory, participants were given an informed consent form that provided additional details about the planned experimental procedures. If they agreed to participate, they signed the form and were asked to change into more comfortable garments (i.e., shorts and a T-shirt) while remaining barefoot. The Tegner Activity Scale (TAS) was applied to the participants in the case group prior to the beginning of the experimental procedures [32].  
A researcher provided a verbal explanation of the side-hop exercise, followed by the demonstration of the movement: stand on one foot (right or left) on a force platform and then hop side to side, alternating between platforms while using the same foot, without performing double taps, for a duration of 15 s. The participant was allowed to try the movement once with each foot. After a rest period of 3 min, data collection was initiated. Three repetitions of side-to-side hopping were recorded for each foot.
# DNN Beamforming for LEO Satellite Communication at Sub-THz Bands
## 3 Numerical Results
The sample number denotes samples selected from the generated data set that is reserved for testing. As we can observe, the DNN is able to track the performance as desired with a TTD beamformer at a given AoA \(\theta_{0}\) with very high accuracy. The MSE performance of the implemented DNN beamformer is shown in Figure 4 for the train, test and validation set. We can observe that the mean square (MSE) is very low thus showing that DNN is able to match the performance of a TTD beamformer as the AoA changes at the antenna array receiver. The best performance was obtained in 184 epochs with a very low mean square error as indicated in Figure 4. The MSE performance for the training, test and validation set was observed to be \(9.73\times 10^{-13}\), \(10.005\times 10^{-13}\) and \(9.64\times 10^{-13}\) respectively. Thus, as we can observe that for a wideband LEO satellite communication system, it is feasible to design a DNN beamformer that will replace the use of costly and non-ideal phase shifters for the beamforming of massive number of antenna array elements. The DNN is able to match the performance as expected by a TTD beamformer for a wideband LEO satellite communication system. Figure 4: MSE Performance of proposed DNN Beamformer over the training, test and the validation dataset. The best MSE performance obtained at 184 epochs is indicated with a circle. Figure 3: Output signal voltage predicted by the DNN beamformer and that of a true time delay beamformer for the test set at different angle of arrival \(\theta_{0}\) between 0–80\({}^{\circ}\) for the considered frequency range of 99–101 GHz. In order to compare and show the performance relative to the phase shifter implementation for a wideband signal, we show the signal voltage of the trained DNN, TTD and PSB beamformer at different frequencies in Figure 5 for the elevation angle in the range of 10-90\({}^{\circ}\). The output of TTD is the ideal response that is desired for a wideband signal. It can be observed that for signal frequency of 100 GHz, the PSB also gives exact output as expected by a TTD beamformer but as the signal frequency deviates, the performance degrades severely. As pointed out earlier, this happens as the phase shifter is designed to provide specific delay at a given center frequency and as the frequency deviates, the phase response in not able to provide the constructive interference at the output. The spacing between the antenna elements at the center frequency is taken to be 0.5\(\lambda_{0}\). We note that the trained DNN beamformer is able to match the ideal performance as expected by a TTD beamformer as the elevation angle is varying in the range of 10-90\({}^{\circ}\). As for massive number of array elements, the beamwidth of receiver antenna will be narrower and thus the effect of beam-squint can be severe.
## 5 Conclusions  
In summary, it has been shown that it is possible to determine the statistical properties and the configurational entropy related to the size changes of a population of magnetic skyrmions according to a 2D model basing on the fact that magnetic skyrmions are planar structures. The analogy with the 3D MB distribution for the ideal gas is not anymore so stringent as occurred within the 3D model of a population of skyrmions but it can still be applied, without loss of generality, in the region of skyrmion metastability studied in this work. The analysis was carried out discussing the comparison of the results obtained according to the 2D model with the ones derived within the 3D model. It has been shown that both the 2D and 3D models lead to similar quantitative results related to skyrmions distribution statistical properties such as the skyrmion average size as a function of the temperature. Instead, some quantitative discrepancies regarding the configurational entropy calculation have been found being \(S^{\text{2D}}\) almost one order of magnitude less than \(S^{\text{3D}}\). These discrepancies are not surprising because the two models lead to a different power dependence of \(S^{\text{2D}}\) and \(S^{\text{3D}}\) on the thermal energy. In addition, within the 3D description, there is also an explicit dependence on the thickness of the ferromagnetic material that gives a further contribution to the entropy. According to some physical arguments related to the estimation of the average energy and the entropy contribution to the Helmholtz free energy that should be comparable in a thermodynamic system such as the one studied, and taking into account some micromagnetic observations, the results regarding the thermodynamic properties of the 3D model are preferable. However, a final confirmation could come from the measurement of the entropy and the heat exchanged using, for example, calorimetric techniques.  
Finally, a qualitative description of an entropy data communication system has been given for a future possible application of magnetic skyrmions as temperature and magnetic field dependent information entropy carriers. This was proposed exploiting the strong analogy between [PERSON]'s statistical entropy and [PERSON] continuous version of [PERSON]'s information entropy. It has been shown that the magnetic skyrmion at room temperature carries more entropy information than at low temperature and that, under an external bias field, at fixed temperature the encapsulated information entropy reduces with increasing the magnetic field amplitude.  
This research received no external funding.  
The author acknowledges support by Gruppo Nazionale per la Fisica Matematica (GNFM) and Istituto Nazionale di Alta Matematica (INdAM) \"[PERSON]\" The author wish to give a special thanks to [PERSON] and [PERSON] for fruitful discussions.  
The author declares no conflict of interest.
## 3 Results  
When the filter method was used to minimize the dimensionality of the ML model, where the defined MI metric was used to sequentially delete the least significant features, the results did not always translate into the model's best possible performance on an unknown testing set. Figure 4 depicts the relationship between the model's training, testing, and overall accuracy as the dimensionality is reduced. This relationship is illustrated using four different types of machine learning models: (a) Simple Tree, (b) RBF SVM, (c) Linear SVM, and (d) kNN. The wrapper method is applied as a consequence of these benchmark results, which are covered in depth in the discussion portion of this paper.  
The findings indicate that the overall performance of the final ML model obtained the best possible outcome by utilizing the embedded wrapper approach. As is evident from Figure 5, we were able to create a feature set optimization algorithm that guides the formation of the ML model to the state with the highest potential for generalization. Figure 5 shows that, the dimensionality is reduced to 53 features, there is a strong relationship between the optimization fit-value (fitness-function) and the individual outputs of the ML model (training, testing, and overall accuracy). The final state of the GA optimization achieves 100% overall accuracy after 893 epochs.  
The importance of these results is examined and evaluated thoroughly in the following section.  
Figure 4: Filter method (benchmark): Four machine learning algorithms evaluated with respect to sequential dimensionality reduction using the mutual information relevance metric. (**a**) Simple Tree, (**b**) Radial Basis Function kernel Support Vector Machine, (**c**) Linear Support Vector Machine, (**d**) \(k\)-Nearest Neighbor. Data: \(N=\textit{Overall}=56\)\((p=32,n=24),\ R=\textit{Train}=38\)\((p=23,n=15),\ E=\textit{Test}=18\)\((p=9,n=9)\).