esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Information Leakage Analysis of Merkle Tree-Based Authentication Schemes
### Previous Schemes and Their Vulnerabilities
#### Merkle Tree-Based Authentication of Encrypted Data  
[PERSON] et al. [30] and [PERSON] et al. [31] independently investigated data authentication of encrypted data in the context of proof-of-ownership (PoW). Their strategy is to encrypt the data first, then to perform authentication over the encrypted data based on a Merkle tree to guarantee data confidentiality and verify the complete possesion of the underlying plain data. In combination with a secure encryption algorithm, the underlying plain content can be hidden from unauthorized users, including malicious service providers.  
Even if their schemes preserve data confidentiality by encrypting data itself, however, they are vulnerable to the side-channel attacks we found due to the inherent property of Merkle tree. In other words, even if the plaintext corresponding to the encrypted data is not known, the information about the Merkle tree generated from the ciphertext can be obtained by eavesdropping, so the authentication coverage falls with repeated authentication attempts. As with the Merkle tree-based authentication of unencrypted data, the size of the underlying (encrypted) data can still be inferred.
## 4 Results
### Regression Analysis
#### 4.1.1 Data Preparation and Transformation  
The dataset comprised results from 84 simulation scenarios, encompassing variations in towing speed, squat ratio, time, and floating object bow types. To meet the assumptions of linear regression regarding normality and homoscedasticity, a Box-Cox transformation was applied to the dependent variable--the suspended sediment concentration (S, in kg/m\({}^{3}\)). This transformation serves to stabilize variance and approximate normal distribution, thereby enhancing the reliability and validity of the regression model.  
Additionally, the independent variables were scrutinized for multicollinearity using Variance Inflation Factor (VIF) analysis. Variables exhibiting high VIF values, indicative of strong multicollinearity, were iteratively removed to optimize model stability and interpretability. The final set of predictors included the Froude number (_Fr_), squat ratio (_Sq_), squared time (_t_2), and floating object type (_Obj_T_), along with relevant interaction terms such as _Fr_\(\times\)_Obj_T_, _Sq_\(\times\)_Obj_T_, and _t_\({}^{2}\)\(\times\)_Obj_T_.
## 2 Experimental Test
### Generalization of Thermal Stratification  
Based upon previous studies, thermal stratification influences the effect of TCC mostly. However, it is complicated owing to a variation of the topography and climates of a reservoir. To generalize the most representative thermal stratification, five hydraulic engineering projects which have the low-temperature released water problems were selected. They are all river-type reservoirs, with the dam heights more than 150 m, including Sanbanxi, Nuozhadu, Ertan, and Xiluodu projects in China and the Glen Canyon Dam in America. As shown in Figure 2a, May and August were chosen to represent the spring and summer, respectively, when the lower RWT was obvious.  
The thermal stratification characteristics of these reservoirs can be generalized into two types: single thermocline and double thermocline. Single thermocline (S1) distribution refered to a clear vertical thermal stratification with a three-layer structure, comprising an upper mixed layer, a middle thermocline layer, and the hypolimnion layer at the bottom of the reservoir. This stratification was more stable and the thermocline had uniform temperature gradients. Double thermoclines (S2) included two thermoclines, upper and lower. There was a mixed layer between the two areas with more sharp gradients.  
Considering the size of tank, two curves with the characteristics of S1 and S2 stratification were designed, respectively, and the curves were shown in Figure 2b. Through adjusting the depth and location of high-power electric heat tubes, the vertical temperature measured in the tank at the beginning of tests were almost the same as the designed curves (Figure 2b).  
Figure 1: Arrangement of experimental test.
# Passive Location for 5G OFDM Radiation Sources Based on Virtual Synthetic Aperture
###### Abstract  
Passive location technology has been greatly developed because of its low power consumption, long detection distance, good concealment, and strong anti-interference ability. Orthogonal frequency-division multiplexing (OFDM) is an efficient multi-carrier transmission technology, which is an important signal form of 5G communication. Researching passive locations for OFDM signals can realize the location of base stations, which is of great significance in the military. Space-borne passive location technology has a contradiction between wide coverage and high precision. Therefore, a single-satellite passive location algorithm for OFDM radiation sources based on the virtual synthetic aperture is proposed. The algorithm introduces virtual synthetic aperture technology, using antenna movement to accumulate data coherently over a long time period and synthesizing a long azimuth virtual aperture. In addition, it utilizes fast Fourier transform (FFT) to extract phase information at a specific frequency based on the multi-carrier modulation technology of the OFDM signal. Pilot technology of the communication system is used for phase compensation and noise reduction. Thus, the azimuth linear frequency modulation (LFM) signal containing the location information of the radiation source is obtained. The radiation source location can be obtained by range searching and azimuth focusing. Simulation results verify the effectiveness of the algorithm and show that the algorithm can realize high-precision and wide-coverage location for the OFDM radiation sources using a single antenna, turning the hardware structure into software to reduce the cost and complexity of the system.  
OFDM signal; passive location; virtual synthetic aperture; data coherent accumulation pacs: **2023**, _15_, 1695. [[https://doi.org/10.3390/rs15061695](https://doi.org/10.3390/rs15061695)]([https://doi.org/10.3390/rs15061695](https://doi.org/10.3390/rs15061695))
# Securing Wireless Sensor Networks Using Machine Learning and Blockchain: A Review
## 9 BC and Cyberattack Prevention
### BC Challenges in WSNs
Time consistency during time synchronization between sensor nodes requires exchanging a number of messages depending on synchronization frequency. * Computation Overhead: heterogeneous IoT devices have different processing capabilities for running encryption and decryption, which leads to variations in processing time. Integrating a BC into the sensor network enables a logical peer-to-peer network to validate and store transactions locally, which is straightforward for personal computers or workstations; however, it might be difficult for tiny sensors with limited computational resources. * Complexity and Energy Wastage: most widely employed BCs use PoW as a consensus mechanism, where the network participants must solve a mathematical problem or cryptographic puzzle in order to validate and authenticate transactions. PoW uses a significant amount of computational resources, causing energy losses; therefore, it is not practically suitable for IoT networks [30; 111]. In addition, severe latency affects WSN stability in delay-sensitive applications [132]. * Guaranteeing Security: many malicious activities target IoT and WSNs. A single attack can harm a large number of devices or be used to destroy another system, as monitor nodes can be turned into malicious nodes to launch further attacks. The network's ability to manage advanced cyberattacks is degraded due to the constrained resources of IoT devices. However, a BC relies on sophisticated hash functions, which require heavy computation and consensus mechanisms that consume network bandwidth. * Compatibility and Standardization: standardization for BC security applications is needed in to ensure that devices meet a reasonable set of standards and have fundamental security and privacy capabilities and to diminish risks associated with cyberattacks against IoT devices [133]. BC in WSN and IoT may never become a reality unless the storage, battery life, computation power, and bandwidth availability of sensor devices are improved [134]. Securing a network using a BC with resource-constrained devices remains challenging [111], and researchers are currently seeking lightweight mechanisms that can solve problem of excessive resources consumption by sensor networks when using BC to secure WSN and IoT networks against possible attacks such as data manipulation and tampering.
# Post-Quantum Digital Signature: Verkle-Based HORST
## 1 Introduction
While HORST adds a Merkle tree to compress public keys and increase performance, HORS uses a subset of secret keys for each signature to minimize key sizes. Nevertheless, HORST continues to rely on Merkle proofs, which increase in size as the tree height increases, and due to its \"few-times\" nature, its security deteriorates as the number of signatures increases. In this paper, we present Verkle-based HORST, a new framework that uses a Verkle tree--a cryptographic structure that uses vector commitments to obtain constant-sized proofs--instead of the Merkle tree in HORST [12]. Verkle trees employ polynomial commitments (such as KZG commitments) to provide proofs of constant size (\(O\) (1)), in contrast to Merkle trees, which demand proofs that increase logarithmically with the number of leaves (\(O\) (\(\log n\))). This invention increases the scheme's scalability and drastically lowers the quantity of data needed for verification. We present a formal security proof for Verkle-based HORST, showing that it preserves the collision resistance of the underlying hash function and the unforgeability guarantees of classical HORST under the discrete logarithm assumption. Our method does without logarithmic-sized proofs while retaining the same level of security by substituting Verkle trees for Merkle trees. To assess the usefulness of our method, we perform a thorough efficiency comparison between classic HORST and Verkle-based HORST. Important variables like proof size, verification time, and storage needs are the main focus of our investigation. The findings show that Verkle-based HORST is a scalable and useful approach for post-quantum digital signatures, providing notable efficiency gains.
# Corrosion Monitoring Techniques in Subcritical and Supercritical Water Environments
## 3 Invasive Corrosion Monitoring Techniques
### Electrochemical Noise
At the same time, the electrochemical noise technique can also be applied to coating performance evaluation and corrosion inhibitor screening, providing a powerful technique for studying material corrosion problems, protection, and surgical support. Some scholars at home and abroad have adopted electrochemical noise techniques to investigate corrosion issues in high-temperature and high-pressure water systems. [PERSON] et al. [121] found a linear relationship between the weight loss rate of 304 SS in high-temperature water and the reciprocal of noise resistance, consistent with the research results in room-temperature systems. [PERSON] et al. studied the corrosion behavior of 304 SS [122] and 08 CH18N10T steel [123] in high-temperature water. They found that during the initial soaking stage, the noise resistance increased first and finally became stable. The average corrosion rate calculated using the experimentally obtained noise resistance is consistent with the EIS results. [PERSON] et al. [124] performed the EN monitoring for stainless steel and carbon steel pipelines in the laboratory and industrial sites. They found that as the temperature increased, the measured noise resistance showed  
Figure 10: EN monitoring results of Q235B steel exposed to Tianjin urban atmosphere over 20 days. (**a**) electrochemical potential noise; (**b**) electrochemical current noise; (**c**) relative humidity; (**d**) temperature; (**e**) noise resistance; (**f**) ECN standard deviation; (**g**) EPN standard deviation Reprinted from Ref. [116]. 2017, SAGE journals. a decreasing trend, and the value of the noise resistance corresponded to the rust on the surface of the pipeline. Another critical piece of research in the exploratory stage focuses on the online monitoring of EN signals for environmentally assisted cracking. Preliminary research has indicated that electrochemical noise signals are more sensitive to crack propagations, during which both the current signal's increase and the voltage signal's decrease can be monitored simultaneously [125,126]. If the crack propagation is discontinuous, a potential reduction with a long time interval will occur, accompanied by a significant increase in current. Suppose the crack rapidly expands and the surface oxide film does not have time to undergo re-passivation. In that case, it will decrease the potential signal and cause a continuous increase in the current signal [126]. However, due to the weak noise signals generated during the initiation and early propagation stages of cracks and the high interference of background noise, it is challenging to study the initial stage of environmentally assisted cracking using the EN technique.
## 3 Results and Discussion
### Analytical Application
#### 3.2.3 Analytical Performance of the Recommended Procedure  
The plot of Cu(II) concentration versus absorbance is linear over a range of 0.7-25 \(\mathrm{\SIUnitSymbolMicro m}\)\(\mathrm{L}^{-1}\). The linear equation that describes the calibration curve of our developed method is:  
\[\mathrm{A}=0.18\,\mathrm{C}-0.009\qquad\text{(R${}^{2}$ = 0.992, $n=10$)} \tag{3}\]  
where, A and C are absorbance, and concentration of copper(II) solution, respectively. [PERSON]'s factor, and the molar absorptivity (\(\varepsilon\)) of the proposed method are 0.003 \(\mathrm{\SIUnitSymbolMicro m}\)\(\mathrm{\SIUnitSymbolMicro m}\)\(\mathrm{\SIUnitSymbolMicro m}\)\(\mathrm{\SIUnitSymbolMicro m}\ \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Analysis Technique** & **pH** & **LOD, ug/mL** & **Concentration Range, ug/mL** & **Interferences** & **Ref.** \\ \hline Micro SPE-AAS & 3 & 0.022 & 0.05–1 & Fe\({}^{3+}\)Ni\({}^{2+}\),Co\({}^{2+}\),Zn\({}^{+}\) & [5] \\ AAS with high resolution continuum source & Acidic medium & 0.021–14 \({}^{*}\) & 0.07–100 \({}^{*}\) & [6] \\ Potentiometry using modified carbon paste electrode & 3 & 9.2\(\times 10^{-5}\) & 22.2\(\times 10^{-4}\),-635 & H\({}_{2}^{2+}\),Cd\({}^{2+}\),Ag\({}^{+}\) & [7] \\ Potentiometry using modified carbon paste electrode & 4.5–8.5 & 0.057 & 0.081–812 & Fe\({}^{3+}\),Cd\({}^{2+}\),Al\({}^{3+}\),Ca\({}^{2+}\),Cr\({}^{3+}\) & [8] \\ Voltammetry using modified carbon paste electrode & 1.4 & 0.017 & 0.1–1 & H\({}_{2}^{2+}\),Cd\({}^{2+}\),Pb\({}^{2+}\) & [9] \\ AAS combined with SPE & 5 & NM & 0.15–2 & Al\({}^{3+}\),Sn\({}^{2+}\),Ni\({}^{2+}\),Mn\({}^{2+}\) & [37] \\ AAS combined with SPE & 5 & 0.01 & 0.01–0.34 & There is no interference cut:10M ratio & [38] \\ AAS combined with SPE & 5.6 & 0.3 & NM & Fe\({}^{2+}\),Co\({}^{2+}\) & [39] \\ Direct spectrophotometry & 4–6 & 0.011 & 0.7–25 & Mn\({}^{2+}\),Al\({}^{3+}\) & PW \\ \hline \hline \end{tabular}  
* Depending on the used atomic lines.  
\end{table} 
Table 6: Comparison between the proposed method and various previously published analytical techniques to estimate Cu(II).
# Algorithm-Based Real-Time Analysis of Heart Rate Measures in HIIT Training: An Automated Approach
###### Abstract
The rate of increase in heart rate during work intervals (ascending slope) and the rate of decrease during recovery (descending slope) offer particularly valuable metrics for assessing cardiovascular fitness and adaptation to training [23; 24]. However, the manual identification of these features is labor-intensive, subject to human error, and impractical during real-time training sessions [20], highlighting the need for automated approaches that can process physiological data with greater consistency and efficiency [25]. Automated algorithmic analysis of physiological data presents a solution to these challenges by providing real-time, objective, and consistent evaluation of heart rate responses during HIIT without requiring constant expert supervision [26]. The application of algorithmic approaches to physiological signal processing has advanced considerably in recent years [27], yet there remains a notable gap in the literature regarding automated real-time analysis of heart rate data specifically for HIIT applications. In this sense, we found a notable gap in the automated analysis of heart rate dynamics during HIIT protocols, indicating a significant opportunity for methodological innovation through specialized algorithms that can automatically detect and analyze heart rate behavior in exercise, recreation, and fitness. Therefore, the present study addresses this gap by proposing a novel algorithm for the automated real-time detection of key heart rate parameters during HIIT sessions. Our algorithm is designed to identify maximum and minimum heart rate signals and calculate additional metrics, including ascending and descending slopes and intermediate averages between these values. These parameters provide comprehensive insights into cardiovascular response and recovery efficiency, enabling an objective assessment of an athlete's performance and adaptation to HIIT protocols without the experts being involved in the continuous supervision of the heart rate of the exercisers.
## 4 MAC Protocol Design
### Adaptive Slot Allocation Method  
As mentioned earlier, the ISWN is expected to achieve both strict delay performance of partial nodes and overall operating efficiency. To further achieve energy savings, an inactive period is included in the superframe. The beacon indicates the superframe boundary, while the sub-beacons separate the different periods. Note that the TDMA period has a fixed length, while the length of CSMA period is adaptive. Thus the second sub-beacon changes with traffic load.  
As shown in Figure 8, in order to gather the traffic status, a queue counter is added at the beginning of the data payload. For a slave node, the queue counter carries the number of the data packets in its buffer zone. With the queue information carried by data packets, the host node can calculate the real-time network traffic. Also, in the host node, an array \(F[M][N]\) is maintained to store the slot allocation in the TDMA period, in which \(M\) represents the number of the slots and \(N\) the nodes. The value of \(F[m][n]\) (\(1<m<M\), \(1<n<N\)) represents the slot occupation status. If the slot \(m\) is occupied by nodes \(n\), then the value of \(F[m][n]\) will be 1, otherwise it will be 0. Obviously, the sum of the elements value in the array will be less than or equal to \(M\). By checking array \(F\), the slot that vacated by the sleeping node is known to the host node. In this section, an adaptive slot allocation method is proposed, which includes two basic strategies. It is designed such to mantain good performance under different traffic load. The strategies are described as follows.
## 3 Results and Discussion
These depth maps are given in Figure 2. In these depth maps, it is seen that the EMT process distorts the adherent form of the cells within the first 24 h. An important observation that can be made from these depth maps is that the variations in the shape of the mesenchymal cells are much more limited than their epithelial counterparts. For each cell line, the epithelial cells tend to be more elongated and flat. As they gained a more mesenchymal characteristic they gained a more rounded shape. An accurate measurement of this characteristic is the eccentricity value that is a measure of the circularity of a given shape. For each cells line, the mesenchymal cells had a lower eccentricity value. Along with eccentricity, the cell base surface area, cell height, and cell volume was measured for each sample as can be seen in Figure 2. A comparison of these parameters before and after the EMT process are given in Figure 3. The extracted morphological features indicate that each cell line transforms into a more spherical shape. The eccentricity value, which is calculated as the ratio of the largest and smallest lengths along the cells' axes, decreased for each cell line after the treatment. A similar yet less significant decrease was observed in the cell surface areas. The surface area of a cell is one of the most important measures of its adhesive properties. This decrease indicates a significant drop in the adhesion capabilities of cells. In addition, the variation in the eccentricity and surface area values decreased. An increase in the measured cell height values was observed, however the variance also increased for these parameters. No significant change was observed in the cell volume parameter. Figure 2: A reconstruction of the depth maps for each cell line throughout a 48 h period in 6 h intervals. This figure show exemplary depth maps from (**a**) HCT-116, (**b**) HUVEC, (**c**) ONOCO-DG1, and (**d**) MDA-MB-231 cell lines for 0, 6, 12, 18, 24, 30, 36, 42, and 48 h intervals respectively from left to right. All units of the axis scales are in \(\upmu\)m. For each cell line, we observed a transformation to a more spherical shape, which indicates a decrease in the adherent characteristic of the cells. For each sample, A is the surface area of the cell in \(\upmu\)m\({}^{2}\), h is cell height in \(\upmu\)m, and E is the eccentricity value which is unitless.
###### Abstract  
Few mode optical fibers are a promising way to continue increasing the data rate in optical communications. However, an efficient method to launch and extract separately each mode is essential. The design of a interferometric spatial mode (de)multiplexer for few mode optical fibers is presented. It is based on a single Michelson-like interferometer which consists of standard optical elements and has a reflective image inverter in one arm. Particular care has been taken in its design so that both polarizations behave the same. Moreover, this interferometer can process several pairs of modes simultaneously. The multiplexer also consists of: a phase plate, focusing optics at both ports of the interferometer and elliptical core fibers to recirculate some outputs. It can multiplex ten spatial and polarization modes and it presents low losses and no intrinsic crosstalk between modes. Additionally, it is polarization insensitive, achromatic, compact and inexpensive. The same system can work as a demultiplexer when used in reverse. In this case, both the losses and the crosstalk remain very low. Similar designs that perform other functions, like an add-drop mode multiplexing, are also suggested.  
optical fibers; space division multiplexing; few mode fibers; mode sorting; interferometers 25 October 2020; Accepted: 26 November 2020; Published: 30 November 2020