esa-sceva/satcom-chunk-collection huggingface dataset:
# Research on Lifespan Prediction of Cross-Linked Polyethylene Material for XLPE Cables
## 1 Introduction
### Mechanical Properties
#### 2.2.2 Hardness Testing  
The hardness test is one of the most commonly adopted methods for evaluating the aging degree of polymers with different aging times. In this paper, a Shore A durometer was used to analyze the hardness of three samples with the same aging time. The test methods for hardness are as follows.  
Six points, denoted as _a-f_, were measured to ensure the accuracy of the test results. The average hardness of six points, denoted as \(A\), was obtained for comparing the hardness among samples aged for different years, and the standard deviation of results was denoted as \(a_{A}\).  
The hardness test results are listed in Table 3.  
According to the obtained results (Table 3), with the increase in aging time, the hardness of samples gradually increases. For samples aged for 3.5 and 8 years, the hardness increases by 1.12% and 8.57%, respectively, compared with samples aged for 1 year. The reasons for this phenomenon are that thermal oxygen aging and thermal decomposition reactions occur when XLPE cables are operating in a thermal aging environment for a long time, which results in the breaking of polymer chains and the failure of the global cross-linking network. In this case, small molecules in the material are re-cross-linked, along with the hardness of the samples increasing.
# Optimization of Multi-Mission CubeSat Constellations with a Multi-Objective Genetic Algorithm
## 3 Problem and Optimization Formulation
### Multi-Objective Genetic Algorithm  
A given multi-objective problem will rise to a set of optimal solutions known as Pareto optimal solutions. These are a set of optimal solutions to the problem. If there is no additional information, one of these Pareto optimal solutions is not better than the others [21]. There are various algorithms for finding Pareto optimal solution sets. Evolutionary algorithms are frequently used to solve these problems as they can keep a diverse solution set. The genetic algorithm (GA) is a widely used global optimization method, among evolutionary algorithms, due to its ability to locate a global optimum solution for a set of nonlinear multi-objective problems [10; 22; 23].  
The multi-objective genetic algorithm is a robust multi-objective optimization technique that results in a set of Pareto optimal solutions. To solve the optimization problem with the four objectives given in Equations (1) and (7)-(9), the class of MOGA, named NSGA-II, is used. The NSGA-II algorithm can find a near-true Pareto optimal front through a fast non-dominated sorting algorithm, diversity preservation, and elitist principles [21; 22]. Because of these properties, the NSGA-II algorithm is widely used to solve multi-disciplinary nonlinear multi-objective problems. NSGA-II calculates the nondominated solution set at each generation until the maximum generation or a given convergence criterion is achieved. Several studies have used NSGA-II for constellation design optimization problems, resulting in a good performance [12; 22; 23; 24].
## 2 Materials and Methods
### Dimensionality Reduction  
As presented earlier, the two-sample Hotelling \(T^{2}\) statistic defines sample similarity used by the Kohonen neural network algorithm. However, for this statistic to be applicable, the dimension of the data must be less than the size of the samples [14]. Therefore, dimensionality reduction to satisfy this requirement must precede usage of the statistic. We performed a wavelet transform [30; 31; 32], which is often used for dimensionality reduction in pattern analysis and classification [33]. A wavelet representation retains of the data wavelet decomposition coefficients only those which correspond to a predetermined energy of the transformed signal [34; 35; 36]. A significant advantage of the wavelet representation is that a decomposition depends on the data item to describe, not on other data,in contrast to other common feature selection methods such as principal component analysis (PCA) or singular value decomposition (SVD) [37].
# Single-Parameter-Tuned Attitude Control for Quadrotor with Unknown Disturbance
## 3 Quadrotor Attitude Control System Design
### ESO Parameter Tuning with CMA-ES Algorithm
#### 3.4.5 Step-Size Control  
This section presents a simple method to control the step size \(\sigma_{g}\). We scale \(\sigma_{g}\) according to the mean value \(cost\left(m_{g}\right)\):  
\[\sigma_{g}=\begin{cases}\sigma_{max}\text{ }\frac{cost\left(m_{g}\right)}{ cost_{max}},&if\quad cost\left(\mathbf{m}_{g}\right)<cost_{max}\\ \sigma_{max},&if\quad cost\left(\mathbf{m}_{g}\right)\geq cost_{max}\end{cases} \tag{18}\]  
where \(\sigma_{max}\) is the max step-size, and \(cost_{max}\) is the max cost we set.  
Algorithm 4 lists the total algorithm:  
```
1:for\(g=1,2...g_{max}\)do
2: compute \(B\),\(\mathbf{D}\) from \(\mathbf{C}_{g}\)
3:for\(i=1,2...\lambda\)do
4: sample point \(\mathbf{x}_{i}\) with \(\mathbf{B}\),\(\mathbf{D}\) and \(\mathbf{I}\)
5: compute the cost of sample point \(cost\left(\mathbf{x}_{i}\right)\)
6:endfor
7: sort the points based on the costs: \(cost\left(\mathbf{x}_{1;\mu}\right)\leq cost\left(\mathbf{x}_{2;\mu}\right)\leq... \leq cost\left(\mathbf{x}_{\mu;\mu}\right)\)
8: update the mean value using Equation (15)
9: update the evolution path using Equation (16)
10: update the covariance matrix using Equation (17)
11: update the step-size using Equation (18)
12:endfor
```  
**Algorithm 4** Covariance matrix adaptation evolution strategy (CMA-ES) algorithm for extended state observer (ESO) parameter tuning.
## 3 System Design
### UWB Localization
#### 3.2.2 Nonlinear Least Squares for 3D Position Estimation
The Levenberg-Marquardt algorithm optimizes the tag's position by iteratively refining an initial estimate \(\mathbf{p}_{0}\). This iterative refinement ensures convergence towards a solution that minimizes the residual error, adhering to pre-established tolerance levels and maximum iteration constraints. Then, the residual \(r(\mathbf{p})\) to evaluate the quality of the position estimate uses the Root Mean Square (RMS) value of the prediction error and is calculated as follows. \[r(\mathbf{p})=\sqrt{\frac{1}{4}\sum_{i=1}^{4}\biggl{(}\sqrt{(\mathbf{a}_{i}- \mathbf{p})^{\top}(\mathbf{a}_{i}-\mathbf{p})-d_{i}}\biggr{)}^{2}}. \tag{4}\]  
A lower residual value indicates a higher accuracy of the estimated position, ensuring alignment with the measured distances from the anchors. This enhanced trilateration algorithm is particularly advantageous in environments where precision and reliability are paramount. The integration of the Levenberg-Marquardt optimization algorithm compensates for potential errors and noise in the distance measurements, delivering more-accurate and -consistent results. Applications of this refined trilateration technique span across various domains including indoor positioning, robot navigation, and satellite-based positioning systems. Its adaptability and scalability cater to the diverse and dynamic requirements of these applications, offering a robust solution for real-time, accurate 3D position estimation in complex environments.
## 3 MIPs' Applications
### MIPs as Chemical Sensors and Biosensors
Although this MIA method was found to be more cumbersome, it was cheaper and faster than that of natural antibodies. Moreover, MIPs have demonstrated remarkable stability under storage in dry state at ambient temperatures, surviving for several years without loss of recognition capability. The competitive formats of MIAs can be divided into two categories: homologous and non-homologous assays, in which analyte and probe are chemically identical or chemically different respectively. Radio-labeled MIAs were the first examples of homologous assays where the probe is just the radio-labeled form of the analyte used as template in the imprinting process. In particular, novel imprinting processes to create spherical, molecular imprinted beads were employed in radio-labeled MIAs as alternatives to conventional MIP particles preparation with several advantages such as enhanced selectivity, low cross-reactivity and a simple bead preparation. Recently, [PERSON] _et al._ synthesized (_R_,_S_)-propranolol imprinted microspherical beads by a modified precipitation polymerization and they were used in competitive radio-labeled MIAs for chiral analysis of propranolol, using (_S_)-[4-\({}^{3}\)H]Propranolol as radioactive probe. When the MIP was used in scintillation proximity assays, the binding of the radio-labeled template determined a transfer of energy from template to scintillant resulting in the generation of a fluorescence signal [161]. In another study, 17\(\upbeta\)-estradiol imprinted beads prepared by precipitation polymerization were employed in a competitive radio-labeled MIAs to obtain a stereoselectivity for 17\(\upbeta\)-estradiol over its diastereoisomer 17\(\upalpha\)-estradiol [78]. Nevertheless, the practical applications of this technology are heavily restrained due to the inherent complications of handling and disposing of radioactive materials. For this reason, fluorescent analogues of analytes were employed as alternative probes in MIAs. Conventional fluorescent-labeled MIAs is an example of non-homologous assay where the MIP is prepared using the analyte itself as template in the imprinting process and a fluorescent probe in place of the radioactive probe. However, a problem that hinders the development of this technique is due to different structures of the fluorescent probe, which has additional fluorescent groups to that of the analyte, inducing a decrease of sensitivity and selectivity. Nevertheless, in the last few years, many researchers have focused their interest on fluorescence-labeled MIAs [162, 163, 164, 165] primarily for their attractive practical features in future applications.
# Probabilistic Shaping for Finite Blocklengths: Distribution Matching and Sphere Shaping
## 5 Performance Comparison
### End-to-End Decoding Performance
We further observe that they are 0.22 and 0.23 dB more power-efficient than CCDM at rates 4 and 4.5 bit/2-D, respectively. Since SpSh and MPDM perform almost identically for the considered shaping length, we believe the implementation aspects, which are discussed next, are of significant importance in the comparison between these architectures.
## 5 Applications of Wireless EM Energy Transfer and Propagation in SCs
### Near and Onboard Living-Tissue Tools in SC Environment
#### 5.1.3 Case of Image-Assisted Medical Therapies and Interventions Tools  
Disorders in the distribution of the RF magnetic field inside of an MRI tunnel, which is image-correlated, are characteristically activated by external EMFs or by the insertion of conductive or magnetic stuff into the imager scaffold. In MRI-assisted interventions or therapies, only actuating tools fabricated from non-conductive and non-magnetic ingredients, such as piezoelectric matter, are tolerable. In general, piezoelectric actuators [69; 70; 71; 72; 73] employ for their excitation thin conductive electrodes. The positioning of such electrodes regarding the field orientation performs an important role connected to the influence of the conductive surface perpendicular to the field direction. Thus, the higher this surface, the higher the corresponding disturbance will be. Such an occurrence, which is related to the currents induced, could be exploited in the actuation context to diminish disorder in the distribution of RF magnetic field \(B_{1}\)[36]. The checking of such a field distribution could be achieved via EMC analysis by solving Equations (6)-(9) and comparing the field distributions without and with the introduced matter. Figure 3 displays the RF magnetic field \(B_{1}\) distribution (vertically directed) in the axial section of the birdcage inside the tunnel of an MRI, at 63.87 MHz (corresponding to static magnetic field \(B_{0}\) of 1.5 T), for the no material case. Figure 4 exhibits an example of a cubic piezoelectric material with relative values of (\(\mu\), and \(\varepsilon\)) and \(\sigma\) of (\(\mu_{\text{r}}\) = 1, \(\varepsilon_{\text{r}}\) = [450 990 990], \(\sigma\) = 0 S/m) coated by thin electrodes on two opposite faces with (\(\mu_{\text{r}}\) = 1, \(\varepsilon_{\text{r}}\) = 1, \(\sigma\) = 3.77 \(\times\) 10\({}^{7}\) S/m)--see Figure 4a. Figure 4b,c show the field \(B_{1}\) distributions in the two situations, where the electrodes are, respectively, perpendicular and parallel to the field direction. The effect of the conductors, in the last case (parallel to the field), is drastically reduced (Figures 3 and 4c are almost identical). The results in Figures 3 and 4 illustrate a simple qualitative example related to RA material use, avoiding adverse effects due to possible EMF noise image perturbation.  
Figure 2: RA and OH approaches involving the eco-design and use of onboard tools considering urban SC biodiversity via handling of adverse EMF effects [41].
# Comparative Study of Blockchain Hashing Algorithms with a Proposal for HashLEA
## 3 Background
### Hash Functions
#### 3.3.13 Lyra2/Lyra2 REv2  
Lyra2 is a Password Hashing Scheme (PHS) that employs a cryptographic Sponge structure to generate pseudorandom outputs, which can be used as cryptographic keys or authentication strings. Designed with a focus on sequential execution, Lyra2 resists parallelization, thereby providing strong protection against attackers employing high-performance hardware, such as GPUs or custom ASICs. Furthermore, it is straightforward to implement in software and offers flexibility for legitimate users to adjust their memory and processing costs in order to meet security requirements [83].  
The Lyra2 system represents an improvement over its predecessor, the Lyra system, in that it addresses limitations and enhances security against a range of potential attack vectors. The Lyra2 employs a two-dimensional memory structure, designated as the memory matrix, wherein cells are successively read, written, and revisited throughout the hashing process. This matrix is initially configured and traversed through a stateful combination of the Sponge's absorbing, squeezing, and duplexing operations. The stateful design guarantees that the matrix remains sequential, with its internal state carried forward rather than being reset [84].  
The Lyra2 REv2 hashing algorithm is a chain of multiple hashing functions, commonly utilized as a PoW mechanism in various cryptocurrencies. Its primary objective is to enhance the resilience of the algorithm to the use of ASICs, thereby ensuring a more level playing field for mining participants. At the core of the Lyra2 REv2 chain lies a critical component derived from a specific implementation of the general Lyra2 algorithm, which plays a crucial role in achieving the intended security and resilience properties of the algorithm. Discarding memory cells to conserve memory leads to the necessity of recomputation whenever those cells are accessed again, up to their last modification [85]. This design feature makes Lyra2 highly resistant to memory reduction attacks.
###### Abstract  
Anti-jamming communication technology is one of the most critical technologies for establishing secure and reliable communication between unmanned aerial vehicles (UAVs) and ground units. The current research on anti-jamming technology focuses primarily on the power and spatial domains and does not target the issue of intelligent jammer attacks on communication channels. We propose a game-theoretical center frequency selection method for UAV-enabled air-to-ground (A2G) networks to address this challenge. Specifically, we model the central frequency selection problem as a Stackelberg game between the UAV and the jammer, where the UAV is the leader and the jammer is the follower. We develop a formal matrix structure for characterizing the payoff of the UAV and the jammer and theoretically prove that the mixed Nash equilibrium of such a bimatrix Stackelberg game is equivalent to the optimal solution of a linear programming model. Then, we propose an efficient game algorithm via linear programming. Building on this foundation, we champion an efficacious algorithm, underpinned by our novel linear programming solution paradigm, ensuring computational feasibility with polynomial time complexity. Simulation experiments show that our game-theoretical approach can achieve Nash equilibrium and outperform traditional schemes, including the Frequency-Hopping Spread Spectrum (FHSS) and the Random Selection (RS) schemes, in terms of higher payoff and better stability.  
air-to-ground network; unmanned aerial vehicle (UAV); anti-jamming communication; Stackelberg game +
Footnote †: journal: Electronics  
0
Footnote 0: Copyright** © 2023 by the authors. Liconse MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([[https://creativecommons.org/licenses/by/](https://creativecommons.org/licenses/by/)]([https://creativecommons.org/licenses/by/](https://creativecommons.org/licenses/by/)) 4.0/).
## 3 Reducing Transmission Overhead without Compromising Throughput  
OppNet routing requires message replication techniques that maintain low transmission overhead under increasing node population and degrees of spatial locality without degrading throughput. In order to achieve this, the progress messages have made towards their respective destinations needs to be determined through means that incur low metadata transmission overhead (i.e., metadata transmission that does not increase drastically with node population, or require frequent updates) and are based on realistic assumptions (i.e., assumptions that do not require knowledge of global network parameters and are suitable for realistic human movement patterns). As observed in an earlier study [28], the optimal quota for message replication varies with the degree of spatial locality. Regulating the replication quota to suit different messages showed a better performance trade-off between transmission overhead and throughput. In particular, different messages were assigned different replication quota, depending on the distance--in terms of number of regions apart--between the home region of the source and destination nodes. In this section, we present LARep, and address the following points in the process:  
* An approach to determine the optimal quota for different messages on-the-go; and
* Achieving this with minimal metadata transmission overhead and realistic assumptions.  
By addressing these points, LARep is able to achieve the features shown in Table 2.
# Fatigue Crack Propagation Analysis of Rail Surface Under Mixed Initial Crack Patterns
## 4 Conclusions  
This study conducted numerical analyses to calculate the stress intensity factor for surface cracks in U71 Mn rails. The results were obtained using numerical methods, and the finite element method (FEM) was employed to examine the effects of various initial crack angles, lengths, and friction coefficients on crack propagation. The main conclusions are as follows:  
1. Under varying axle weight conditions, the maximum equivalent force is situated approximately 3 mm beneath the rail surface. The cracks primarily extend in the depth direction of the rail, transforming the semi-circular surface cracks into elliptical cracks with the major axis oriented along the rail's width.
2. The analysis of the stress intensity factor under varying operating conditions shows that model-\(I\) has a minimal effect on crack extension, keeping the crack surface predominantly closed. Crack propagation is primarily driven by model-II and III in the mixed shear stress modes.
3. The crack expansion rate is highest at an initial angle of 0\({}^{\circ}\) and lowest at 45\({}^{\circ}\). In other words, a smaller initial crack angle results in a faster crack expansion rate.
4. As the initial crack length increases, the equivalent stress intensity factor at the crack tip also rises, accelerating crack propagation.
5. Increasing the friction between the wheels and rails can mitigate the growth of fatigue cracks, as higher friction reduces slippage at the crack surface.  
J.L.: conceptualization, methodology, and writing--review and editing; W.Y.: formal analysis, writing--original draft preparation, and data curation; Z.W.: investigation and supervision. All authors have read and agreed to the published version of the manuscript.  
This work was funded by the National Key R&D Program of China (2021 YFF0501101), The National Natural Science Foundation of China (52272347), the National Science Fund of Hunan (2024J)7132), and the Scientific Research Project of Hunan Provincial Department of Education (22A0391).  
Not applicable.  
The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.  
The authors declare no conflicts of interest.  
Figure 13: Crack propagation at different initial crack friction coefficients: (**a**) crack propagation length; (**b**) crack propagation rate.
## 7 Evaluation
### Comparison of Area Estimation  
The KNN and Delaunay schemes are compared in terms of area estimation. Tables 1 and 2 show that KNN with and without FLANN show good performance when calculating the area of regular shapes. The error is less than 3% for all the regular shapes. The Delaunay scheme shows slightly larger errors, in the range of 6-11%.  
For irregular shapes, shown in Tables 3 and 4, the KNN without FLANN shows a maximum of 8% error. The KNN with FLANN shows a slightly larger error (up to 10%). The increase in error is due to the fact that FLANN removes some points which results in a lower granularity.  
Table 4 also shows that for irregular shapes, the error of Delaunay increases up to 31%. The increase in error is largely due to the fact that the convex mechanism is used for approximation.
###### Abstract  
Coastal municipalities and industries often discharge poorly treated wastewater into proximate marine and estuarine environments. The urban and/or effluent input can lead to eutrophication and lower water quality, as it holds high concentrations of nutrients and pollutants. One widely applied tool to increase effluent dispersion and direct it away from coastal areas, thus causing fewer impacts on human activities, is sea outfall. In Aveiro, Portugal, the Sao Jacinto sea outfall construction was completed in 1998; however, limited literature regarding the sea outfall's monitoring using satellite data is available. The methodology in this study involved collecting four years' worth (2016-2019) of satellite data to investigate visible traces of the interaction between the S. Jacinto sewage water mass and the Ria de Aveiro lagoon ecosystem using ocean color and spectral analysis, and producing new qualitative data regarding sea outfall plume dispersion monitoring through high-resolution Sentinel-2 imagery. The results showed a clear spectral signature of the sewage water mass, and a seasonal pattern was observed in which the plume was more evident in winter and autumn. Additionally, the coastal longshore current and the Aveiro lagoon's runoff were able to restrict the marine outfall's dispersion superficially. Ocean color data were revealed to be a factual and cost-effective tool to monitor the plume water. Finally, an exchange between the marine outfall water mass and Ria de Aveiro lagoon could happen in high tide under northern wind conditions. Therefore, it is important to monitor the water quality to ensure the coastal ecosystem's good environmental state.  
marie outfall; remote sensing; ocean color; eutrophication; spectral signature; sewage plume; effluent detection; Sentinel-2 2023