esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Conclusions  
We were able to readily isolate and identify 75 strains of bacteria from tallgrass prairie soil contaminated up to 10 years prior with crude oil, a combination of brine and crude oil, or adjacent uncontaminated sites. Fifty-four of these strains proved capable of reducing nitrate and/or nitrite. The strains were affiliated with a variety of different taxonomic groups, with some indication of selection for halotolerant taxa in the primarily brine-contaminated soils and of Gammaproteobacteria in the oil-contaminated soils. However, around 82% of strains shown to reduce nitrate/nitrite would not be identified as NR or DN bacteria by the battery of the functional NR and DN PCR primers used. This low % detection by currently used PCR primers suggests caution in inferring numbers of NR/DN based on PCR amplification. It also attests to the value of a culture-first approach, in which a variety of bacteria are first screened for the ability to reduce nitrate /nitrite, followed by molecular analyses of their functional genes.  
The following supporting information can be downloaded at [[https://www.mdpi.com/article/10.3390/microorganisms12101981/s1](https://www.mdpi.com/article/10.3390/microorganisms12101981/s1)]([https://www.mdpi.com/article/10.3390/microorganisms12101981/s1](https://www.mdpi.com/article/10.3390/microorganisms12101981/s1)), Table S1: Summary of primers used to detect denitrification functional genes; Table S2: Site, site type, dilution origin, and phenotype, for 75 strains; Table S3: Genbank accession numbers for 165 rRNA gene sequence and functional genes for nitrate reducing and denitifying genes; Table S4: Summary of nitrate reducing/ denitrification genes from isolates (Accession number \"in bold\"/Closed GenBank match accession # (% similarity)).  
Conceptualization, S.M.A. and K.E.D.; methodology, S.M.A. and K.E.D.; software, S.M.A., F.Z.N. and K.E.D.; validation, S.M.A., K.E.D. and F.Z.N.; formal analysis, S.M.A. and K.E.D.; investigation, S.M.A. and K.E.D.; resources, S.M.A. and K.E.D.; data curation, S.M.A. and K.E.D.; writing--original draft preparation, S.M.A. and K.E.D.; writing--review and editing, S.M.A. and K.E.D.; visualization, S.M.A. and K.E.D.; supervision, K.E.D.; project administration, K.E.D.; funding acquisition, K.E.D. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the U.S. Environmental Protection Agency, Grant Number R830633C009.  
The raw data supporting the conclusions of this article will be made available by the authors on request.  
We thank [PERSON] for assistance in MOTHUR software ver1.23. We are grateful to [PERSON] for his leadership of bioremediation projects in the TPP.  
The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.
## 2 Materials and Methods
### Sensor Positions and Sensor Types  
Many fall-detection studies [43] utilize an accelerometer as the primary sensor to determine falls. [PERSON] [43] evaluates the importance of different sensors in a multisensory scheme, concluding that the most relevant features are derived from two particular acceleration components (Z and Y). A gyroscope is considered computationally expensive and is less useful in improving our understanding of the dynamics of falling [4; 44; 45]. In contrast to this, [PERSON] et al. [46] report that a sensing module (including a gyroscope and an accelerometer) consumes only about 3% more power when both sensors are active compared to only measuring the acceleration magnitudes when only one sensor is activated.  
Furthermore, the choice of sensors to use depends on the type of dataset (whether it contains near-fall activities or not). Using only acceleration measurements can result in many false positives and false negatives caused by near-fall activities, such as sitting down fast on a mattress. Near-fall and fall activities have almost the same vertical signal variation, making them difficult to differentiate. False positives and false negatives caused by near-fall activities can be reduced significantly by using the gyroscope's angular velocity measurements. Our paper compares an accelerometer-based algorithm and a gyroscope-based algorithm intended for fall detection. The results indicate that the performance of the algorithm that uses gyroscope signals is more effective when the dataset contains near-fall activities.  
We collected data from sixteen different positions: the head, pelvis, upper and lower thoracic, upper and lower arms (wrists), hand, thigh, shank, and foot. Most studies in the literature review on fall recognition have been conducted using a single wearable device without taking into account the device's location on the user's body. The position information provided by the wearable device can, however, assist in improving the performance of the fall-detection system. Several body locations are compared in this study to determine the most optimal location of the sensors for fall-detection systems.
## 2 Technical Background
**Definition 5** (Undirected graph). : _An undirected graph \(G\) associated with the given \(n\times n\) incomplete pairwise comparison matrix is defined as_  
\[G\coloneqq(V,E), \tag{3}\]  
_where \(V=\{1,2,\ldots,n\}\) denotes the set of vertices (nodes) and \(E\) denotes the set of undirected edges \(\{i,j\}\) (pairs of vertices) corresponding to the already assigned comparisons, \(E=\{\{i,j\}|\,a_{ij}\text{ is known},i,j=1,2,\ldots,n\,;i\
eq j\}\)._  
This means that if the matrix entry \(a_{ij}\) is already known, the edge is allocated from node \(i\) to node \(j\) or from node \(j\) to node \(i\), with the exception of the diagonal entries. No edge will be assigned to unknown entries. **Theorem 1** ([15], Theorem 2). : _The optimal completion of the incomplete PCM \(\mathbf{A}\) is unique if and only if the graph \(G\) corresponding to the incomplete PCM \(\mathbf{A}\) is connected._  
Note that the matrix \(\mathbf{A}\) plays a role which is similar to that of the adjacency matrix of graph \(G\). The connectedness of graph (3) will be an important property for our study. In fact, we only consider incomplete PCMs corresponding to connected graphs. Let us briefly justify this assumption. If an incomplete \(n\times n\) PCM corresponds to a non-connected graph, this simply means that at least two non-empty subsets of elements of the reference set exist, such that no element of the first subset is compared (directly or indirectly) with any element of the second subset. For practical purposes, this is clearly an irrelevant problem and we did not consider it. \begin{table}
\begin{tabular}{c c c c c c c} \hline Matrix size \(n\) & 4 & 5 & 6 & 7 & 8 & 9 & 10 \\ \hline Random index \(RI_{n}\) & 0.8816 & 1.1086 & 1.2479 & 1.3417 & 1.4057 & 1.4499 & 1.4854 \\ \hline \end{tabular}
\end{table} 
Table 1: Random index \(RI_{n}\) values [32]. **Definition 6** (Simplex). : _A simplex \(S\) in \(\mathbb{R}^{k}_{+}\) is defined as the convex hull of \(k+1\) vertices \(\mathbf{x}_{1},\ldots,\mathbf{x}_{k},\mathbf{x}_{k+1}\in\mathbb{R}^{k}_{+}\). For example, a simplex in \(\mathbb{R}_{+}\) is a line segment, a simplex in \(\mathbb{R}^{2}_{+}\) is a triangle, and a simplex in \(\mathbb{R}^{3}_{+}\) is a tetrahedron._
# Effects of Diverging Nozzle Downstream on Flow Field Parameters of Rotating Detonation Combuster
###### Abstract  
In this study, three-dimensional numerical studies have been performed to investigate the performance of a rotating detonation combuster with a diverging nozzle downstream. The effects of a diverging nozzle on the formation and propagation process of a detonation wave and typical flow field parameters in a rotating detonation combuster are mainly discussed. The results indicate that the diverging nozzle downstream is an important factor affecting the performance and design of a rotating detonation combuster. The diverging nozzle does not affect the formation and propagation process of the rotating detonation wave, while the time of two key wave collisions are delayed during the formation process of the detonation wave. With increases of the diverging angle, the rotating detonation combuster with the diverging nozzle can still maintain a certain pressure gain performance. Both the diverging nozzle and diverging angle have great influence on the flow field parameters of the rotating detonation combuster, including reducing the high pressure and temperature load, making the distribution of the outlet parameters uniform, and changing the local supersonic flow at the outlet. Among them, the outlet static pressure is reduced by up to 88.32%, and the outlet static temperature is reduced by up to 32.12%. This evidently improves the working environment of the combuster while reducing the thermodynamic and aerodynamic loads at the outlet. In particular, the diverging nozzle does not affect the supersonic characteristics of the outlet airflow, and on this basis, the Mach number becomes coincident and enhanced.  
rotating detonation combuster; diverging nozzle; formation and propagation process; flow field parameters; numerical study +
Footnote †: journal: Applied Sciences
# Secure and Transparent Space Exploration Data Management Using a Hybrid Blockchain Model
## 3 Proposed Model
### Limitations of Existing Oracle-Based Integration Methods  
Prior approaches to connecting public and private blockchains have primarily relied on oracle mechanisms, which act as external data relays to feed verified off-chain or private-chain data into smart contracts. However, this approach presents several technical limitations.  
First, traditional oracles are often centralized, operating through a single trusted data provider. This contradicts the decentralized trust model of blockchain systems and introduces a single point of failure. Furthermore, validating the authenticity of oracle-fed data is non-trivial, as malicious actors can manipulate or delay data delivery. These risks undermine the security guarantees that blockchain is intended to provide.  
Another limitation is related to data synchronization latency. Oracle-based systems typically require polling or manual triggers to initiate data transfer, which adds verification time. This results in delayed updates between private and public chains, a critical issue for real-time applications such as mission control systems or space telemetry synchronization.  
To address these challenges, we adopt the cross-chain interoperability protocol, developed by Chainlink. CCIP is a decentralized messaging protocol that supports event-driven, smart contract-based communication between heterogeneous blockchain networks. Rather than relying on a polling model, CCIP allows the private blockchain to generate a signed message containing a data hash whenever new information is recorded. This message is then automatically transmitted to the public blockchain, where it is verified using on-chain logic. To ensure the integrity and authenticity of cross-chain messages transmitted via CCIP, each message is digitally signed by the sending smart contract and verified by the receiving contract before acceptance. This signature verification ensures that messages cannot be forged or tampered with during transmission. Furthermore, Merkle proofs can optionally be embedded within CCIP payloads to provide compact verifiable evidence of data inclusion in a block, further enhancing trust in message validity. This design aligns with recent proposals on trustless cross-chain communication protocols for secure blockchain interoperability [17].  
This method improves both reliability and speed. While public blockchains such as Ethereum typically require 12-15 s for block confirmation, private blockchains using Practical Byzantine Fault Tolerance consensus can achieve sub-second finality. CCIP bridges these systems by enabling near-instantaneous data consistency between chains without sacrificing decentralization or auditability.  
By employing CCIP, the proposed model eliminates the bottlenecks associated with traditional oracles and ensures secure, real-time synchronization of critical data across blockchain layers.
# Benefit Analysis of Grid-Connected Floating Photovoltaic System on the Hydropower Reservoir
## 2 Environmental, Technical, Financial Specifications of the Plant
### Specifications  
A direct grid-connected PV plant includes the components described in Figure 2:  
PV module: each photovoltaic panel consists of many photovoltaic cells (PV cells) connected together; the photovoltaic panels will be connected in series (string) and parallel (array) to achieve the required DC output power.  
Inverter: a power electronic device that converts DC current into AC current suitable for connection to the power grid.  
Mounting system: with the solution of installing panels on the water, the rack system is replaced by a floating float system.  
Step up transformers: depending on the capacity scale and regional utility grid conditions, the voltage level can be changed appropriately (for example 22 kV, 35 kV, 110 kV, 220 kV... ). With high voltage levels, the electricity will need to go through 2 levels of transformers.  
Infrastructure for grid connection: specifically, here is the substation, including protection, metering, and control equipment.
## 3 Signal Processing and Artificial Intelligence for DT Development
### Signal Processing for DT Development
Then, they computed the Hamming distance as a similarity criterion between the classes of real and simulated faults across different operating modes. Refs. [22; 85] highlight that the discrete wavelet transform is computationally expensive, particularly for measured and real signals, in addition to requiring a careful selection of the mother wavelet. Refs. [81; 83; 84; 87] point out that the use of frequency analysis for adaptation limits this approach in non-stationary regimes. Such a technique must always be preceded by a detection step before proceeding to diagnosis. Refs. [23; 82] note that VMD often requires a careful choice of parameters, which has not been clearly specified, and is frequently combined with an optimization algorithm. Ref. [82] explains that envelope analysis is limited to detecting high-amplitude faults, as low-signature faults are often filtered out by the envelope. Ref. [70] states that EMD, as a decomposition method, has demonstrated its effectiveness in handling mixed modes compared to VMD. However, this drawback reduces its utility for combined faults. Refs. [86; 89] propose methods based on Lifting Wavelets and Markov Transform, which are relatively difficult to implement and require a prior study of the wave characteristics before processing. Ref. [90] bases its bearing condition monitoring on a statistical indicator, which, despite its effectiveness, remains sensitive to operational variations such as changes in operating modes. Table 1 provides an overview of previous frameworks for gearbox monitoring based on DTs and SP, highlighting their respective advantages and limitations. \begin{table}
\begin{tabular}{p{42.7 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Study** & **Methodology** & **Contributions** & **Strengths** & **Limitations** \\ \hline \multirow{3}{*}{[22]} & DWT, feature selection & Distinguish between real and simulated bearing faults & Effective fault discrimination & High computational cost, sensitive to mother wavelet choice \\ \cline{2-5}  & & Validate the fidelity of the DT of a helical gear & Similarity criterion for model adaptation & Limited performance in non-stationary regimes, requires fault detection step \\ \hline \multirow{3}{*}{[82]} & VMD, phase correlation, envelope analysis & Match experimental and simulated signals & Realistic signal integration, noise reduction & VMD requires parameter tuning, envelope filters out weak faults \\ \cline{2-5}  & Synchronous averaging, DFT & Adapt virtual and real signals, calculate indicators & Noise reduction, fault severity estimation & Limited in non-stationary conditions \\ \hline \multirow{3}{*}{[84]} & Basic spectral analysis & Detect fault and meshing frequencies & Simple and direct method & Ineffective for complex signals \\ \cline{2-5}  & EMD, energy entropy & Mode selection for signal denoising & Effective in handling mixed modes & Less useful for combined faults \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Overview of DT approaches using SP.
## 2 Proposed Scheme
### Data Extraction and Image Recovery  
After receiving the encrypted stego image, the pixels located at the corner positions in the \(3\times 3\) interpolation image block are retrieved to obtain the original \(2\times 2\) reconstructed encrypted blocks. As long as all \(2\times 2\) reconstructed encrypted blocks are collected, a reconstructed encrypted image is derived. With the reconstructed encrypted image, the recipient can obtain the original image or extract the hidden data depending on which key s/her holds. The recipient who holds the encryption key can obtain the original image by conducting decryption with the encryption key on the reconstructed encrypted image. If the recipient holds the data hiding key, s/he can extract the secret data by following the operations. With the encrypted stego image, the recipient extracts the 16-bit secret data from the interpolated pixels for each interpolated image block of \(3\times 3\) pixels as  
\[b^{\prime}_{k}=\text{mod}\left(\left\lfloor\frac{C^{\prime}(i,\,j)}{2^{k-1}} \right\rfloor,2\right),\text{ for }1\leq k\leq 4 \tag{8}\]  
where \(C^{\prime}(i,j)\in\{C^{\prime}(0,1)\), \(C^{\prime}(1,0)\), \(C^{\prime}(1,2)\), \(C^{\prime}(2,1)\}\) is the stego pixel and \(b_{k^{\prime}}\) is the extracted secret bit.  
Moreover, our proposed scheme can verify the image's authenticity, confirming that it has not been altered or tampered with during transmission or storage. For each block of \(3\times 3\) pixels, we compute the authentication data \(\{a_{1},a_{2},a_{3}\}\) by using Equation (6). Then, we extract the 3-bit authentication data from the central interpolated stego pixel \(C^{\prime}(1,1)\) by  
\[a^{\prime}_{k}\ =\ \text{mod}\left(\left\lfloor\frac{C^{\prime}(1,1)}{2^{k-1}} \right\rfloor,2\right),\text{ for }1\leq k\leq 3 \tag{9}\]  
where \(a_{k^{\prime}}\) is the extracted authentication data. We compare whether \(a_{k}\) and \(a_{k^{\prime}}\) are the same. If they are not equal, mark this \(3\times 3\) block invalid.  
To further improve detection results, we propose a second-layer detection strategy. We further marked a valid 3 \(\times\) 3 block as invalid if its neighboring 3 \(\times\) 3 blocks on both sides of the diagonal are invalid blocks, as shown in Figure 3. Our tamper detection process ensures the image's integrity and verifies its authenticity. It confirms that the image has not been altered or forged and the image originates from a trusted source. Therefore, our proposed scheme is a security process where an image is both encrypted and authenticated to ensure its integrity and confidentiality.
## 2 Numerical Methodology
### Optimization Approach
Meanwhile, CO, UHC, and NOx emissions are selected as the constraints. Five independent operational parameter variables were optimized simultaneously, including rpm, diesel fuel mass, methane mass, SOI, and the duration of diesel fuel, in addition to two dependent variables of nitrogen (N\({}_{2}\)) and oxygen (O\({}_{2}\)) percentages. For the present work, the operational parameters, objectives, and constraints are shown in Table 4. For the optimization study, the simulation was run from the intake valve closed IVC to the exhaust valve open EVO for the entire cylinder; since the piston bowl is non-axisymmetric, the amount of N\({}_{2}\) and O\({}_{2}\) that represents air inside the cylinder will be mixed with premixed fuel, which is the methane in this study under specific conditions; these gases represent 1% when initializing the cylinder region in the CFD model. The following equations show objectives, constraints, and the dependent and independent variables initialized in the cylinder. \[P_{\text{CH}_{4}}+P_{\text{N}_{2}}+P_{\text{O}_{2}}=1 \tag{9}\]  
\[P_{\text{O}_{2}}=(1-P_{\text{CH}_{4}})\times 0.233 \tag{10}\]  
\[P_{\text{N}_{2}}=(1-P_{\text{CH}_{4}})\times 0.767 \tag{11}\]  
where \(P_{\text{CH}_{4}}\) is the independent variable that represents the percentage of methane initialized in the cylinder, which varies according to the algorithm. \(P_{\text{N}_{2}}\) and \(P_{\text{O}_{2}}\) are the variables that are dependent on \(P_{\text{CH}_{4}}\), representing the percentage of nitrogen and oxygen initialized in the cylinder. \[CO=\frac{\left(\frac{m_{\text{CO}_{2}}}{h}\right)(\text{g}/\text{h})}{P(\text {kW})} \tag{12}\]  
\[HC=\frac{\left(\frac{m_{\text{HC}}}{h}\right)(\text{g}/\text{h})}{P(\text{kW})} \tag{13}\]  
\[NO_{x}=\frac{\left(\frac{m_{\text{NO}_{x}}}{h}\right)(\text{g}/\text{h})}{P( \text{kW})} \tag{14}\]  
\[ISFC=\frac{\left(\frac{\left(m_{\text{CH}_{4}}+m_{4}\right)}{h}\right)(\text {g}/\text{h})}{P(\text{kW})} \tag{15}\]where \(m_{\text{CO}}\), \(m_{\text{HC}}\), \(m_{\text{NO}_{\text{x}}}\), \(m_{\text{CH}_{\text{4}}}\), and \(m_{d}\) are the quantities of CO, HC, NO\({}_{\text{X}}\), CH\({}_{\text{4}}\), and diesel, respectively, at EVO, and \(P\) is the power. \[\lambda=\phi^{-1}=\frac{\sum_{j}\sum_{i}N_{i}\eta_{\text{CO},i}}{\sum_{j}2\sum _{i}N_{i}\eta_{\text{C},i}+\frac{1}{2}\sum_{i}N_{i}\eta_{\text{H},i}} \tag{16}\]  
where \(N_{i}\) denotes the mole number of species \(i\), while \(j\) represents the total number of cells in the field. Additionally, \(\eta_{\text{O},i}\), \(\eta_{\text{H},i}\), and \(\eta_{\text{C},i}\) correspond to the number of oxygen (O), hydrogen (H), and carbon (C) atoms, respectively, for species \(i\).
## 2 Materials and Methods  
### Materials  
PMPentene films with crystallinity degree (\(X_{c}\)) of 0.69 were used. The polymer for the film was made by suspension polymerization of 4-methyl-1-pentene in the A.V. Topchiev Institute of Petrochemical Synthesis, Russian Academy of Sciences (TIPS RAS). The PMPentene film (laboratory sample) was obtained by the film extrusion method in laboratory 'Polymer composites and adhesives' in TIPS RAS. The sample thickness was \(50\pm 2\)\(\upmu\)m. The chemical structure of poly (4-methyl-1-pentene) is shown in Figure 1.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{4}{c}{**Permeability \(p\), Barres**} \\ \hline
**Polymer** & **H\({}_{2}\)** & **He** & **N\({}_{2}\)** & **O\({}_{2}\)** & **CO\({}_{2}\)** & **CH\({}_{4}\)** \\ \hline PMPentene (25 \({}^{\circ}\)C) [present work] & 125 (35 \({}^{\circ}\)C) [4] & 80.2 & 7.6 & 27.5 & 84.0 & 12.7 \\ PMPentyne (35 \({}^{\circ}\)C) [11] & 3500 & 2500 [12] & 800 & 1700 & 7500 & 2000 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Permeability coefficients of PMPentene and PMPentyne in relation to certain gases.  
Figure 1: Repeating unit of PMPentene.  
PMPentyne films used for the study were also developed in TIPS RAS. Figure 2 shows the chemical structure of poly (4-methyl-2-pentyne). It should be noted that PMPentyne possesses _cis/trans_ microstructure. In our case _cis/trans_ relation was 40/60% [11]. The permeability coefficients of certain gases through PMPentyne are set out in Table 1. PMPentyne films were prepared by casting from a polymer solution in high-purity cyclohexane (99.9%). The thickness of the films was approximately 41 \(\pm\) 3 \(\upmu\)m. The experimental study began on the 90 th day after film preparation, in order to avoid the strong effect of aging on the membrane properties and to achieve stable results.  
The gases studied were used directly from the pressure cylinders, without any primary treatment. The gases studied had a purity higher than 99%. Nitrogen (99.999%), helium (99.999%), methane (99.9%), and n-butane (99.75%) were manufactured by Monitoring LLC (Zelenograd, Russia), ethane (99.9%) by Scott Specialty Gases (Breda, the Netherlands) and propane (99.9%) by Linde Gas (Balashikha, Russia).