esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### Multilayer Perceptron (MLP) Model
The confusion matrices, shown in Table 9, illustrate the predictive performance of the model, which compares the predicted values against the actual outcomes to determine whether VHI scores improved. Out of twenty-six cases, the model predicted that VHI scores would not improve in three instances; among these, two cases were correctly identified as having no improvement (true negative, TN), while in one instance, the model incorrectly predicted no improvement when there actually was improvement (false negative, FN). Additionally, the model predicted improvement in VHI scores for 23 cases; of these, 22 cases were correctly identified as having improved (true positive, TP), while the model incorrectly predicted improvement when there was none in the one remaining case (false positive, FP). Table 10 shows the performance metrics of the model, which achieved an accuracy of 84.61%, indicating that it correctly classified 84.61% of all cases. The model's precision is 0.95, signifying that 95% of the instances predicted as positive were indeed positive; its specificity is 0.67, indicating that the model accurately identified 67% of true-negative cases; its recall, or sensitivity, is 0.86, demonstrating that the model correctly detected 86% of the actual positive cases; its F score is 0.90, representing a high level of harmonic balance between precision and recall; finally, its AUC is 0.87, reflecting the model's strong capacity to distinguish between positive and negative outcomes. Figure 7 presents a bar graph illustrating the relative importance of various parameters. Each bar represents the significance of a specific parameter, with the horizontal axis indicating the relative magnitude of importance. According to the graph, surgery status is the most influential parameter, followed by voice user status, gender, smoking status, alcohol consumption, coffee consumption, voice training status, and comorbidity, in descending order of importance. The relative importance of each parameter increases  
Figure 6: ROC curves of MLP modeling. \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{4}{c}{**Reference**} \\ \hline  & & **VHI (\(-\))** & **VHI (\(+\))** & **Total** \\ \hline \multirow{3}{*}{Predicted} & VHI (\(-\)) & 2 & 1 & 3 \\  & VHI (\(+\)) & 3 & 20 & 23 \\ \cline{1-1}  & Total & 3 & 23 & 26 \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Confusion matrices of MLP model. towards the right side of the graph, indicating that the parameters further to the right have a greater impact on the model.
# Long Term Effects of Forest Liming on the Acid-Base Budget
## 2 Materials and Methods
### Calculation of Acid-Base Budgets  
The input-output budgets for the forest soil were calculated based on element fluxes (cf. [14; 26]) on a yearly basis for 24 years, from 1989 to 2012. The inputs to the soil-internal element cycle are total deposition and elements released by mineral weathering. The element loss by seepage water is an output from the forest soil. Lime and fertilizers are treated as part of the soil and not as an additional input.  
The acid load based on the budgets of NH\({}_{4}\)\({}^{+}\), H\({}^{+}\), Mn\({}^{2+}\), Al\({}^{3+}\), Fe\({}^{3+}\), SO\({}_{4}\)\({}^{2-}\), NO\({}_{3}\)\({}^{-}\), organic anions (Org\({}^{-}\)), Ca\({}^{2+}\), K\({}^{+}\), Mg\({}^{2+}\), and Na\({}^{+}\) was calculated for each subplot after [PERSON] [26; 38]. Dissolved organic carbon (DOC) was measured in the water samples and converted to Org\({}^{-}\), as described in [PERSON] et al. [39] with the updated conversion factor of ICP Forests [40]. P was not included because of uncertainties in the input-outputbudgeting. The element fluxes at 60 cm depth were taken as an output from the ecosystem and subtracted from the accordant element input by TD.  
In the original approach by [PERSON] [26], mineral weathering and the acid load by biomass increment are not calculated separately but instead included in the element budgets. Positive budgets of NH\({}_{4}\)+, H+, Mn\({}^{2+}\), Al\({}^{3+}\), or Fe\({}^{3+}\) account for a net input of acidity into the ecosystem because these ions count as potential proton donors [14]. Moreover, positive budgets of Ca\({}^{2+}\), K+, Mg\({}^{2+}\), and Na\({}^{+}\) add to the acid load, because it is assumed that these M\({}_{\rm b}\) cations are incorporated into the biomass increment or are bound to exchange sites of the mineral soil and releasing M\({}_{\rm a}\) cations that lead to proton production. Negative budgets of SO\({}_{4}\)\({}^{2-}\), NO\({}_{3}\)\({}^{-}\) or Org\({}^{-}\) represent the dissolution of aluminum sulfates, nitrification, or the dissociation of dissolved organic acids and contribute also to the acid load. Opposing results of the element budgets lead to proton consumption by acid base reactions like dissolution of M\({}_{\rm b}\) and M\({}_{\rm a}\) oxides, cation exchange, mineralization, or the formation of aluminum sulfates [26].  
Because of the decision to treat the added lime and fertilizer as part of the soil, the M\({}_{\rm b}\) cation budgets of the liming treatments are more negative in comparison to the control plots. Lime and fertilizer could also be treated as an additional input, which would lead to positive M\({}_{\rm b}\) cation budgets and therefore adding to the acid load for all liming treatments. This acid load originating from the M\({}_{\rm b}\) cation input by liming would have to be balanced by protonation of HCO\({}_{3}\)\({}^{-}\), which would complicate the calculations as well as the presented tables, without adding additional insights.
## 5 Conclusions  
This study demonstrated that VNIR spectroscopy can be used to estimate Cd, Cr, and Pb content in soils under phytoremediation. First-order differential, second-order differential, and reciprocal logarithmic transformations were performed on the pre-processed original spectra and utilized to reduce the influence of external factors. Among them, differential transformation helped to improve the correlation between the heavy metal content and spectral reflectance of the soil, and the use of higher correlation bands significantly improved the stability and predictability of the model. The optimal spectral estimation models for Cd, Cr, and Pb heavy metal elements were established by the BPNN, MEA-BPNN, and PLSR models. The best spectral model established by the MEA-BPNN model was better and had higher precision than those of the other models, and could realize the rapid prediction of three heavy metal elements. Cr exhibited the highest modeling accuracy and a perfect prediction effect, reflected by statistical analysis values of R\({}^{2}\) = 0.884 and RPD = 3.000. The modeling effects of Cd and Pb were good, with R\({}^{2}\) values of 0.873 and 0.857, respectively, and RPD values of 2.114 and 2.560, respectively. Therefore, in the future, the use of spectroscopy to estimate heavy metal content will be the main method for the rapid monitoring of soil heavy metal content and soil remediation assessment.  
[PERSON] made substantial contributions toward the collection, processing, analysis, and interpretation of data and assisted with manuscript preparation; [PERSON] and [PERSON] collected the data and assisted in the revision of the manuscript; [PERSON] provided his experience and was responsible for the proofreading of the manuscript; [PERSON] and [PERSON] were mainly responsible for the content verification; [PERSON] designed and performed the experiments; and [PERSON] was responsible for the estimation model. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the National Natural Science Foundation of China (51874307).  
The authors declare no conflict of interest.
# Recent Research Progress in Surface Ligand Exchange of PbS Quantum Dots for Solar Cell Application
## 3 Solution-Phase Ligand Exchange
### Directly Usable PbS CQD Inks by Solution-Phase Ligand Exchange  
Inorganic ligands, such as halide anions, have significantly developed PbS CQD PVs [35; 36; 37]; however, such approaches that have been conducted by solid-state ligand exchange require a large amount of material and are time consuming. Therefore, solution-phase ligand exchange using halide can provide numerous merits. [PERSON] et al. reported PbS CQD PVs based on a halide ligand-capped PbS CQD ink prepared via the solution-phase ligand exchange [34]. To produce the PbS CQD ink, the PbS CQDs dispersed in a nonpolar solvent such as octane, and iodide salts dissolved in dimethylformamide (DMF) are vortexed vigorously. They are then kept static until the phase separation. After eliminating the top octane solvent, the PbS CQDs are washed using a polar solvent to eliminate residual organic debris. Finally, toluene is added to precipitate PbS CQD, and after following centrifugation and redispersion in butylamine, PbS CQD ink can be obtained (Figure 6a). This enables a direct and simple fabrication of thick PbS CQD film with an approximately 300 nm thickness, as well as minimize waste of materials (Figure 6b,c). The resultant PbS CQD films exhibited an \(n\)-type characteristic which is suitable for PbS CQD PVs. With this new class of \(n\)-type PbS CQD film, 6% \(PCE\) has been achieved. This work is the first demonstration of PbS CQD PVs using PbS CQD ink prepared via solution-phase ligand exchange, and the trend of PbS CQD research has begun to change from solid-state to solution-phase ligand exchange.
# Analysing and Computing the Impact of Geometric Asymmetric Coils on Transformer Stray Losses
## 2 Modelling and Considerations  
### Geometric Model of Column-Type Transformers  
Additional losses in all structural components in the transformer sometimes represent more than 20% of the load losses if they are not controlled [21]. Most of the additional losses occur in the tank, so this work lays more emphasis on this part and its control through magnetic shunts. Additional losses in core clamps or yoke beams are also considered, but the analysis of these losses in structural parts such as guides and flitch plates was discarded. Figure 1a shows the actual arrangement of the transformer tank being analysed, equipped with magnetic shunts. Figure 1b shows the geometric model used for the analysis, covering the structural components and their positioning. In particular, tank details are omitted to improve clarity of magnetic shunts and visualisation of core clamps. It is important to highlight that in this model the core is represented as a solid piece, without considering laminations. This simplification arises from the fact that the main focus of the research is the analysis and calculation of losses in the magnetic shunts and the tank. Figure 1c represents an overhead view of a cross section that includes the tank walls: front wall (Fw), left wall (Lw), rear or back wall (Bw), and right wall (Rw). The top (Tw) and the bottom (Gw) tank walls are also considered. The separation of tank walls allowed us to analyse in greater detail the amount of stray magnetic flux in each of the walls. Other parameters include primary winding height (hp) and thickness (wp), secondary winding height (hs) and thickness (ws), and magnetic shunt height (hsh).
###### Abstract  
Genotoxicity is the ability of specific substances to cause DNA damage, affecting development, physiology, and reproduction. This is often mediated by induction of oxidative stress. This _in vitro_ study aims to test the ability of two antioxidants, ellagic acid (EA, 100 \(\mu\)M) and curcumin (Cur, 40 \(\mu\)M) to protect zebrafish blood cells from the genotoxic action of benzene (10 \(\mu\)L/mL). Cells were treated for 30, 60, and 90 min with EA or Cur alone and in combination with benzene. The antigenotoxic role of antioxidants was evaluated in terms of cytotoxicity by trypan blue dye, genome stability by RAPD-PCR technique, DNA fragmentation and percentage of apoptotic cells using Comet and Diffusion assay, respectively. The results did not show statistical differences in terms of cell viability, genome stability, DNA damage and apoptosis between cells treated with antioxidants. When zebrafish blood cells were co-incubated with individual antioxidants and benzene, a significant improvement of these parameters was observed in comparison with cells incubated in benzene. Our results suggested that EA and Cur are able to protect zebrafish blood cells against DNA damage and apoptosis caused by mutagenic substance, and laid the foundation for future studies investigating their antigenotoxic potential in DNA oxidative damage therapy.  
Keywords:antioxidants; curcumin; ellagic acid; genotoxic stress; oxidative stress Authors Authors
# Evolutionary Optimization of Spiking Neural P Systems for Remaining Useful Life Prediction
## 6 Conclusions  
Spiking Neural P (in short, SN P) systems are a bio-inspired computing tool that incorporates the idea of spiking neurons into membrane systems called P systems. These systems have been used for a variety of applications, but so far, they have been handcrafted by human experts for each application. In this paper, we employed a custom neuro-evolutionary algorithm, based on NEAT, to automatically design SN P systems for a given task, with little or no domain knowledge. The proposed method was applied to an RUL prediction task for predictive maintenance, where so far, traditional neural networks have been mainly used. Then, we compared our method to methods from the literature, e.g., based on MLPs and CNNs. The comparative evaluation was based not only on the CMAPSS dataset, which is the de facto standard benchmark in the area of RUL prediction, but also on the N-CMAPSS dataset, which is one of the most up-to-date benchmarks in this area. In the experiments on CMAPSS, we observed that our approach was able to produce SN P systems that are competitive in terms of prediction error but with a much smaller number of trainable parameters. Moreover, in the experiments on the N-CMAPSS dataset, although our approach was not able to outperform the deep neural networks when considering the RMSE, it produced once again much smaller structures (in terms of number of parameters). Overall, our approach provides a reasonable trade-off between performance and number of trainable parameters, so that the proposed SN P systems with optimized structure and parameters can be used as an efficient RUL prediction tool in industrial applications that require finding a compromise between the prediction accuracy and the number of parameters, which in turns correlates with memory consumption (which is a crucial aspect e.g., in embedded systems) and computing time.  
[PERSON] and [PERSON] contributed equally to this work and are listed in alphabetical order. [PERSON] ran part of the experiments and performed part of the numerical analysis. [PERSON] conceptualized and supervised the study. All authors have read and agreed to the published version of the manuscript.  
This research was partially supported by Trentino Sviluppo. We gratefully acknowledge the support of NVIDIA Corporation with the donation of the TITAN Xp GPU used for this research.  
Not applicable.  
The data are available upon request.  
The authors declare no conflict of interest.
## 5 Conclusions  
(1) The nanoscale pores of high-rank coal are mainly organic matter pores. The nanoscale pore types in the shale are complex, the connectivity is poor, and the overall pore development degree is low--mainly clay intergranular pores and OM nano-pores. Mineral-related pores, such as intercrystalline pores, in clay minerals occupy the major reservoir space in tight sandstone.  
(2) The mesopores of shale and coal are poorly developed compared to tight sandstone. The nanopores of tight sandstone have lower proportion of reservoir space than shale and coal. Significant differences in connectivity and storage performance, as well as stability of structural characteristics between different samples (heterogeneity), lead to pore systems with different physical properties and gas-bearing capacities.  
(3) According to the comprehensive analysis of pore structure, heterogeneity, and other factors, coal is a better reservoir in strata that have stronger storage capacities and hydrocarbon generation capacities. A tight sandstone reservoir has a higher degree of pore development, which is an important potential factor for better overall gas-bearing properties in the strata. The pore structure and heterogeneity characteristics of shale determine that it is more likely to become an interlayer between gas-bearing subsystems. Continuously developed shale of a specific thickness is more likely to grow into interlayers between gas-bearing systems.  
(4) From the point of view of pore system and heterogeneity, the study of the difference comparison of different lithological intervals in coal measures can provide a scientific basis for the study of the formation mechanism of multi-superposed gas systems. It can be concluded that in addition to the pore structure characteristics of the sample itself, the differences and heterogeneity between samples can also be important evaluation and research parameters.  
Conceptualization, D.Z. and W.J.; Methodology, D.Z.; Validation, Q.W. and Y.L.; Formal analysis, D.Z. and Q.W.; Investigation, D.Z. and X.G.; Data curation, J.Z. and X.Z.; Writing--original draft, D.Z., X.G. and W.J.; Writing--review & editing, X.G. and D.Z.; Visualization, D.L.; Supervision, G.W. and Y.G.; Project administration, D.Z., G.W. and Y.G. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Natural Science Foundation of Jiangsu Province (No. BK20210521), the science and technology research program of Chongqing Municipal Education Commission (No.KJZD-K202103201), the Fundamental Research Funds for the Central Universities (No. 2021 QN1061) and Provincial Innovation Training Plan for College Students of Jiangsu Province (202210290394H).  
Not applicable.  
All data needed to evaluate the conclusions in the paper are present in the paper. Additional data related to this paper are available from the authors upon request.  
The author [PERSON] appreciates the QIHANG Project of China University of Mining and Technology for its help. The authors appreciate [PERSON] and [PERSON] for their help in language editing.  
The authors declare no conflict of interest.
# Enhancing Healthcare Security: A Unified RBAC and ABAC Risk-Aware Access Control Approach
## 4 Implementation of Proposed Model in Healthcare Scenario
### Role-Based Access Control Implementation
From the MC Children's Hospital scenario that we discussed earlier, we recognize five primary identities: doctors, nurses, administrators, social workers, and police officers [12; 35]. The admin will be able to access all the file types, while other actors will only be allowed to access medical records. To simplify the implementation process regarding data types in the healthcare scenario, a singular data type called medical records was assumed to grant simultaneous access to all users across roles. Table 2 demonstrates the data type permissions corresponding to different user roles.
# Spectrogram Classification Using Dissimilarity Space
## 2 Proposed Approach
### Support Vector Machine Training and Prediction  
A Support Vector Machine (SVM) is a supervised learning model with can be used to perform classification or regression. An SVM model represents each training example as a data point in space and is trained to construct one or more hyperplanes that divide the space in two, separating data points belonging to different classes (function trainSVM). The model will predict (function predictSVM) the class of a new pattern mapped in the space according to the side of the hyperplane the data point falls into. The hyperplane found by an SVM is defined as follows:  
\[D(x)=w*x-b, \tag{2}\]  
where \(D(x)\) is the hyperplane, \(x\) is the data point vector, \(w\) is the hyperplane's normal vector, and the \(\frac{b}{||w||}\) ratio is the hyperplane's distance from the origin. The optimal hyperplane is the one that maximizes the distance to the nearest data point of any class, defined as \(\frac{2}{||w||}\), which is also called the _margin_. The \(i\)-th point \(x_{i}\) will be assigned to the first class when \(D(x_{i})\geq+1\) and to the second class when \(D(x_{i})\leq-1\). The points that lie on the margin line, defined by the equation \(D(x_{i})=\pm 1\), completely describe the solution to the problem and are called _support vectors_. An example of an optimal hyperplane with highlighted support vectors is shown in Figure 2.  
Because SVMs use hyperplanes to discriminate data, they do not work well with data that is not linearly separable in its original space. This problem can be solved using kernel functions, which map data into a much higher dimensional space, presumably to make the separation easier in that space. To keep the computational complexity to an acceptable level, the kernel function of choice has to be computationally efficient.  
Being binary classifiers, SVMs can only determine the separation surface between two classes of data; however, it is possible to apply SVMs to multi-label problems by training an ensemble of SVMs and combining them. In this work, the _One-Against-All_ approach is used, where for each class an SVM is trained to discriminate between a given class and all the other classes put together. The pattern is then assigned to the class that gives the higher confidence score.
## 2 Background
### Discussion on the Security of Stream Cipher Algorithms  
In terms of network transmission security, as far as we understand, vulnerabilities that may be exploited in the system primarily exist in the standards and protocols of the applied encryption algorithms. Taking RC4 as an example, it is a stream cipher algorithm that has become part of some commonly used standards and protocols. For instance, it has been included in the IEEE 802.11 standard [41], pertaining to the network link layer protocols Wired Equivalent Privacy (WEP) and Wi-Fi Protected Access (WPA) [42]. It has also been incorporated into the IETF-RFC standard, relating to the network transport layer protocols Secure Sockets Layer (SSL) and Transport Layer Security (TLS). Due to concerns about potential vulnerabilities [43], IETF-RFC-7465 announced the discontinuation of the use of the RC4 encryption algorithm in TLS [44]. However, based on our understanding, the vulnerabilities that may be exploited in the system primarily lie within the operationsof encryption protocol (i.e., WEP), rather than the applied encryption algorithm itself (i.e., RC4). Therefore, this paper focuses on using the RC4 algorithm just as a Pseudo Random Number Generator (PRNG), coupled with the OTP\({}^{3}\) non-repeating key mechanism to realize an efficient streaming encryption mechanism suitable for the IoT environment. The relevant results will be explained in the Section 5 \"Experimental Results\" and Section 6 \"Discussion and Conclusions\".