esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Background and International Context
### International Context  
#### 2.2.1 Inter-Agencies Working Groups  
The need for globally distributed reference data and for community-agreed Cal/Val best practices calls for strong international collaborations. The objective of these collaborations is to join forces and exploit synergies among the various Space Agencies and scientific institutions. Various inter-agency bodies are actively working in this respect. Among the various groups, we recall here those most relevant for satellite land products validation and for addressing the need of inter-sensors interoperability in the optical domain:  
* The Global Space-based Inter-Calibration System (GSICS) [28] is an international collaborative effort, initiated and promoted by the World Meteorological Organization (WMO), aiming at monitoring, improving and harmonising the quality of observations from operational weather and environmental satellites. The GSICS delivers calibration corrections needed for accurately integrating data from multiple observing systems into products, applications and services. ESA is an active contributor to the GSICS working groups' objectives in the advances and consolidation of best practices for cross-sensor intercalibration. * The CEOS Infrared and Visible Optical Sensors Subgroup (CEOS-IVOS) [29] is a sub-level working group of the CEOS-WGCV (Working Group on Calibration and Validation) aiming at fostering international collaborations in the frame of Cal/Val for optical sensors and proposing and agreeing on methodologies and standards, identifying test sites and sharing Cal/Val data among the various agencies. The ESA has been an active member of the CEOS-IVOS group for many years and actively supported the definition and implementation of advanced practices and networks for optical sensors Cal/Val. * The CEOS Land Surface Imaging Virtual Constellation (CEOS-LSI-VC) [30] is a subgroup of the CEOS Virtual Constellations (CEOS-VC), which is responsible for promoting the efficient and comprehensive collection, distribution and application of space-acquired image data of the global land surface. The CEOS-LSI-VC leads the CEOS Analysis Ready Data for Land (CARD4L) initiative [31], including the definition of the individual product family specifications, as well as the assessment process and outreach. ESA is active member of the LSI-VC working group and is currently contributing to the CARD4L initiative. * CEOS Land Product Validation (CEOS-LPV) [32] is a sub-group of the CEOS-WGCV, which is responsible for coordinating the quantitative validation of satellite-derived land products. The main objective of CEOS-LPV is to establish standardised guidelines and best practice protocols for the validation of a wide range of terrestrial Essential
## 4 Performance Evaluation
### Selected Threshold for Doppler Values  
The Doppler value threshold should be selected such that the radar receiver can extract the target information without the need for our proposed algorithm. Therefore, if the proposed module is activated and the residue is less than the specific threshold, we can still obtain target information.  
Based on the parameters listed in Table 1, the pulse width of the phase-coded waveform equals 1.3 ms. Hence, the Doppler completes one cycle during the pulse duration at 770 Hz. To avoid signal distortion, the Doppler value should be less than half of this value. To ensure good quality of the signal in the presence of the Doppler effect at the receiver end, the threshold is set to one-third of this value, approximately 256 Hz. Therefore, the Doppler value threshold is chosen to be 250 Hz.
## 4 Experiment and Analysis
### Equipment Coordination and Joint Testing  
Researchers set up automated monitoring devices at the site as depicted in Figure 5, to furnish the requisite hardware environment for subsequent testing and eventual application of the algorithm, and also to facilitate pilot experiments for extensive deployment. The core components of the automated detection system include a high-definition camera, an industrial computer, and a gateway. The high-definition camera monitors and records the entire target area, transmitting the data to the industrial computer for processing; the industrial computer then detects slope rockfalls using pre-programmed model code; the gateway provides a robust network environment for overall computation and data transmission.  
Initially, experimenters identified areas at risk of rockfall activity on the target railway based on preliminary point cloud data and aerial survey results. Cameras were used to collect data on moving rockfalls in the target area, ensuring diversity of background and breadth of targets. After preliminary data collection, an on-site survey was conducted in the target area to determine the best locations for camera installation, ensuring the detection range would adequately cover the target area. After this, equipment installation involved excavating sites for the cameras, laying reinforced concrete foundations, and mounting the cameras after the concrete had been set. Due to the unavailability of a local power supply, solar panels were used to power the devices. After connecting the power supply, the industrial computer and gateway were configured, activating the camera equipment. The cameras then monitored the target area to assess coverage detection accuracy and orientation. The industrial computer was connected to a remote server, preparing the system for algorithm integration and application.
# Image Storage in DNA by an Extensible Quaternary Codec System
###### Abstract  
Silicon-based storage technologies are increasingly failing to meet the explosively growing data storage demands of the information age. DNA-based data storage offers a promising solution due to its unparalleled storage density, long lifespan, low energy consumption, and high parallel accessibility. In this study, we propose a novel True Quadratic Codec System (ETQ) that directly encodes data into nucleotide sequences using a quaternary encoding approach. By treating A, T, C, and G as direct encoding symbols (0, 1, 2, 3), an ETQ eliminates the intermediate binary-to-ATCG conversion step, thus surpassing the theoretical storage density limit of 2 bits/nt. An ETQ is built on these three key components: (1) dividing image data into B, G, and R color channels for separate encoding and storage, (2) employing quaternary Huffman encoding to map image information directly into nucleotide sequences, and (3) integrating Reed-Solomon error correction codes to enhance data reliability and system extensibility. The ETQ framework demonstrates significant improvements in storage density and efficiency compared to conventional methods. By leveraging the inherent properties of DNA, this system offers a scalable and cost-effective solution that addresses the growing global data storage crisis.  
DNA storage; Huffman coding; RS error correction; quaternary codec system Article
## 2 Experimental and Theoretical Tools  
### High Pressure and High Temperature Rig  
The experiments were carried out in a high pressure and high temperature (HPHT) rig. Parameters such as the composition of the gas, the pressure and the temperature of the ambient gas can be controlled independently to obtain oxygen concentration between 0 and 21%, pressures up to 15 MPa and temperatures up to 1100 K. Thereby, it is possible to replicate the thermodynamic conditions of the cylinder of an internal combustion engine when the fuel is injected. Furthermore, as the temperature field is homogeneous and constant in the area of interest, this reduces the uncertainties that could be associated to engine transients. The HPHT rig has wide optical accesses, which allow the application of different visualization techniques. The installation can operate as an open circuit with air or, in order to reduce O\({}_{2}\) concentration, as a closed loop circuit with a mixture of air and Nitrogen. The regulation and control system ensures steady thermodynamic conditions during long time periods with the aim of getting reliable statistical results of many injections and combustion events. Additionally, one injection is performed every 4 s to avoid any temperature transients. The boundary conditions have been detailed widely in [21] where a full description of the facility is given.  
The common-rail used is capable to achieve injection pressures up to 230 MPa and is equipped with a solenoid-activated single-hole nozzle injector. It is worth mentioning that the injection system pump used is made by polymerizing tetrafluoroethylene material. This material has shown compatibility with oxymethylene ether fuels according to the investigation reported in [22].
# The Impact of Leveee Openings on Storm Surge: A Numerical Analysis in Coastal Louisiana
## 3 Model Results and Flux Analysis  
The storm surge model has been validated for Hurricane Isaac [2]. Surface wind fields were provided by an asymmetric parametric hurricane wind model [13]. In this study, three scenarios were carried out: (1) the base case reflecting the existing conditions, (2) the both-crossing case with the removal of levees at both the upper and the lower locations and (3) the no-levee case with the removal of all MR&T levees (see black lines in Figure 2) in the model. Four water level stations near both crossing locations (see Figure 1) from the Louisiana Coastwide Reference Monitoring System (CRMS, [[http://lacoast.gov/crms2/](http://lacoast.gov/crms2/)]([http://lacoast.gov/crms2/](http://lacoast.gov/crms2/)), accessed on 23 October 2022) were selected to further validate the model performance and to compare water level results in different scenarios. In addition, at each crossing location, a \"control box\" (see filled red rectangles in Figure 2b) was set up to analyze fluxes through its four sides (i.e., west bank, river north, east bank and river south).  
Figure 2: The model domain with computational grids (white line), boundaries (orange for water level, purple for current and yellow for Neumann) and the MR&T leveee system (black line). Green lines denote the levee removal parts; filled red rectangles denote “control box” for flux analysis. (**a**) Entire model domain. (**b**) Local enlarged model domain.
## 5 Breeding Approaches to Enhance Steviol Production  
The primary goal of stevia breeding is the genetic improvement of existing stevia varieties with the development of varieties with a greater number of leaves, higher yield of SvGls and greater resistance to biotic and abiotic stress. The main traits desired to achieve a high success rate in stevia breeding are: high leaf yield per unit area, high content of specific SvGls (RebA, RebD, Reb M) in leaves, high adaptability to a wide range of climatic conditions and self-compatibility. Several patents have been registered for newly developed stevia varieties with enhanced traits desirable for steviol synthesis [8].  
The conventional breeding approach involves two major steps: selection of genotypes and intercrossing among the genotypes with desirable traits. In the beginning, countries such as Japan, China, and Korea utilized the marker-assisted selection scheme (MAS) and reported success in their breeding programs by developing varieties with enhanced SvGls  
\begin{table}
\begin{tabular}{l l l}  & \multirow{3}{*}{[PERSON] et al., 2018 [35]} \\  & & & \\  & & \\  & & & \\  & & & \\  & & & \\  & & & \\  & & & \\  & & & \\  & & & \\  & & & \\  & & & \\  & & & \\ \end{tabular}
\end{table}
Table 1: Outline of the conventional (physical and chemical) approaches to enhance steviol glycosides concentration in _S. rebaudiana_.  
and leaf yields. Some of these varieties were very high yielding but were limited for commercialization due to self-incompatibility [8; 38]. Additionally, some findings suggested that recurrent phenotypic selection was more effective than MAS in improving quantitatively inherited characteristics in stevia--a cross-pollinated species characterized by high differentiation of a given trait within the population [39]. Further, synthetic cultivars were developed by intercrossing clones or sibbed lines derived from a breeding population through multiple cycles of recurrent selection. Synthetic varieties such as AC Black Bird and ATCC Accession No. PTA-444 are a few varieties developed with 2.5 times improved RebA-to-stevioside ratio compared to traditional stevia plants. However, these varieties also suffered from the loss of self-fertility [8].  
Recently mutagenesis is the innovative approach that has brought technical and scientific progress in stevia breeding. Ethyl methanesulfonate (EMS), gamma radiation, and neutron beams are the commonly used physical and chemical inductions used to create an alteration in DNA. The random mutagenesis does not affect the germination growth of the seedlings and has shown a 1.5-2 fold increase in RebA content in comparison to the control plants [12]. The finding suggests that the increased SvGls content was associated with the increased expression of UGT74G1 induced by EMA and gamma radiations.  
Characters of interest can only be improved through mutation breeding if the population's variability for the character in question is low. Because the leaves are the most valuable part of this crop, mutation breeding can play a significant role in stevia improvement.
# Organic Crystals for THz Photonics
## 2 Second-Order Organic Nonlinear Optical (NLO) Crystals
### NLO Effects in Organic Materials
Due to the different origin of the polarizability in organic and inorganic materials, the frequency dispersion of \(\chi^{(i)}\) (\(i=1,2\) or \(3\)) is essentially different, which is important for applications. For example, for the most well-known organic crystal DAST (4-N, \(N\)-dimethylamino-4\({}^{\prime}\)-\(N^{\prime}\)-methyl-stilbazolium toyslate), the optical refractive index along the polar axis \(a\) is about 2.1 and in the THz range it is about 2.3. The square root \(\sqrt{\epsilon^{T}}\) is also about 2.3 [22; 23], which points to the very low dispersion from the low to the optical frequencies. For the most well-known inorganic NLO crystal LiNbO\({}_{3}\), the optical refractive index along the polar \(c\) axis is about 2.2 and in the THz range it is about 5, which points to the much larger contribution of lattice vibrations to the polarizability of this crystal. This is also observed in the dispersion of the NLO susceptibility \(\chi^{(2)}\): while the electro-optic coefficient (involving quasi-static fields) is of the same order of magnitude for DAST (\(r_{111}=48\,\mathrm{pm/V}\) at \(1535\,\mathrm{nm}\)) and LiNbO\({}_{3}\) (\(r_{333}=30\,\mathrm{pm/V}\) at \(1064\,\mathrm{nm}\)), the difference is much larger for the NLO coefficient for second-harmonic generation, involving only the optical fields (\(d_{111}=290\,\mathrm{pm/V}\) at \(1535\,\mathrm{nm}\) for DAST and \(d_{333}=34\,\mathrm{pm/V}\) at \(1064\,\mathrm{nm}\) for LiNbO\({}_{3}\)) [21, 22, 24]. This shows that the origin of the linear and the nonlinear optical susceptibility in organic materials is essentially electronic and therefore extremely fast (femtoseconds). This is an important advantage for high-speed electro-optic modulation [6, 25, 26] and also for THz-wave generation and detection: due to the approximate matching of the THz and the optical refractive index, it is much easier to achieve the phase matching needed for highly efficient response, as discussed in Section 3.4.
## 4 Experiments and Results
### Ablation Study  
To compare the result of the traditional sentiment analysis classification task and our proposed method, we perform an experiment on the SemEval-2017 (without neutral class) dataset using sentence transformer and single-model machine learning classifiers.  
We have analyzed different sizes of training datasets (from 100 to 1000 samples, see the vertical axis in Figure 7) with the fixed-size testing set using 500 instances. The result shows that our proposed method can achieve almost the same and even better in most cases than sentence transformers with only a small dataset required for training.  
Figure 6: Confusion matrix of 3-class (negative, neutral and positive) classification.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **Precision** & **Recall** & **F1-Score** & **Accuracy** \\ \hline Binary classification & 0.863 & 0.908 & 0.884 & 0.873 \\
3-class classification & 0.562 & 0.627 & 0.554 & 0.627 \\ \hline \hline \end{tabular}
\end{table}
Table 8: Performance result comparison for binary and 3-class classification.  
Figure 7: Accuracy vs. number of training instances for sentence transformer + machine learning classifiers and our proposed method.
## 4 Conclusions  
HEOs and carbon/HEO composites are prepared and physicochemically characterized. In order to explore the possibility of using them as active electrode materials for the CDI of water, their capacitive behavior is evaluated in this preliminary study. To investigate the effect of the material size and morphology, spinel-structured CrMnFeCoNi-HEO NPs and NFs are prepared by the sol-gel method and electrospinningine technique, respectively. To study the influence of the HEO lattice structure and of a fibrous host carbon matrix, electrospun composite NFs are further produced with embedded spinel-structured CrMnFeCoNi- and rock-salt-structured MgCoNiCuZn-HEO grains.  
In the range scan rates investigated (5-100 mV s\({}^{-1}\)), the specific capacitance improves in the order C/(Mg\({}_{0.2}\)Co\({}_{0.2}\)Ni\({}_{0.2}\)Cu\({}_{0.2}\)Zn\({}_{0.2}\))O NFs \(\cong\) (Cr\({}_{0.2}\)Mn\({}_{0.2}\)Fe\({}_{0.2}\)Co\({}_{0.2}\)Ni\({}_{0.2}\))\({}_{3}\)O\({}_{4}\) NPs \(<\) (Cr\({}_{0.2}\)Mn\({}_{0.2}\)Fe\({}_{0.2}\)Co\({}_{0.2}\)Ni\({}_{0.2}\))\({}_{3}\)O\({}_{4}\) NFs \(<\) C/(Cr\({}_{0.2}\)Mn\({}_{0.2}\)Fe\({}_{0.2}\)Co\({}_{0.2}\)Ni\({}_{0.2}\))\({}_{3}\)O\({}_{4}\) NFs. The comparative discussion of the results of the physicochemical and electrochemical analyses indicates that the size of the HEO grains plays a relevant role. The smaller the grains, the larger the surface available for the adsorption and the higher specific capacity. In pure HEOs, the fibrous morphology favors the formation of smaller-sized HEO grains. The lattice structure of the HEO exerts an indirect influence, as it results in HEO grains with different sizes and size ranges. The carbon matrix provides a positive contribution, which can be synergistically enhanced by the incorporation of small-sized HEO grains.  
The preliminary results presented in this work suggest that C/HEO composite NFs possess great potential as low cost and eco-sustainable electrode material for CDI and further open the way to explore different HEOs and their carbon composites for a novel design concept of the CDI electrodes.  
The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/app13020721/s1](https://www.mdpi.com/article/10.3390/app13020721/s1)]([https://www.mdpi.com/article/10.3390/app13020721/s1](https://www.mdpi.com/article/10.3390/app13020721/s1)), Figure S1: Specific capacitance of C/CrMnFeCoNi-HEO NFs compared with that of C/Fe-, C/Zn-, and C/Mn-LEO NFs.  
Conceptualization, S.S.; methodology, C.T., B.P., I.R., A.A., S.G. and Y.B.; validation and formal analysis, C.T., I.R., A.A., S.G. and Y.B.; data curation C.T., I.R., A.A., S.G., Y.B. and S.S.; writing--original draft preparation C.T., M.G.M., S.S. and Y.B.; writing--review and editing, C.T. and S.S. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The data presented in this study are available on request from the corresponding author.  
The authors declare no conflict of interest.
## 5 Numerical Results
### Traffic Load Distribution
Moreover, for the two traffic load distributions under study, the throughput increased with the increase in the satellite spacing, as this generated more visible positions, allowing the system to better allocate the total channel load, thereby reducing collisions. Figure 8: Overall throughput achieved with uniform and non-uniform traffic load distributions versus the total channel load \(G_{T}\) for different spacing between \(K=2\) satellites. Figure 9: Overall throughput achieved with uniform and non-uniform traffic load distribution \(G_{T}=180\) versus \(K\) satellites in the system.
## 3 Proposed Anomaly-Based IDS for IoT Ecosystem
### Model Training  
In this phase, our machine learning models are trained. We use two different ML categories to improve the performance of the anomaly-IDS model, namely individual classifiers, and ensemble classifiers with majority voting. The models utilize the proposed hybrid feature selection technique at the training and the testing phases to generate the final set of selected features. The IoTID20 dataset containing only these features is then used to train the ML models. As we have stated above, these subsets of features are: 60% ranked features of IG, 60% ranked features of GR, 20% ranked features of IG, 20% ranked features of GR, IMF (11 features), and UMF (28 features). Specifically, the proposed anomaly-based IDS uses the following ML techniques:  
* ANN (_called_ MLP in the Weka tool) stands for artificial neural network and is a set of neuron nodes arranged in hidden layers designed to recognize patterns imitating the human brain.
* kNN (_called_ IBk or instance-based learner in the Weka Tool) stands for the k-nearest neighbor and is a simplified supervised machine learning algorithm that can be used to address classification or regression tasks. kNN depends on deriving the distance metric between a predicted sample and k-stored samples to provide the classification decision based on the maximum value of the distance of nearest neighbors.
* _C4.5_ (_called_ J48 in the Weka tool) is an ML algorithm that is used to generate a decision tree. C4.5 is an extension of the ID3 (iterative dichotomies 3) algorithm. It implements the model to consist of a root node, branch nodes, and leaf nodes. C4.5 has some advantages over ID3, including handling both continuous and discrete attributes, handling missing values without human intervention, handling attributes with various costs (i.e., loss function), and providing an optional task to prune the tree after creation.
* Bagging (bootstrap aggregating) fits well for an imbalanced dataset. It reduces variance which helps to avoid overfitting. It can be applied to a different domain. Bagging is a type of ensemble algorithm.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Approach** & **\# Features** & **Extracted Features** \\ \hline
**-** & 41 & All Feature \\
**IG** & 20 & 1, 3, 4, 5, 6, 12, 23, 25, 26, 29, 30, 31, 33, 34, 35, 36, 37, 38, 39, 40 \\
**GR** & 20 & 2, 3, 4, 5, 6, 8, 10, 11, 12, 13, 23, 25, 26, 29, 30, 33, 34, 37, 38, 39 \\
**IG \(\cap\)GR** & 15 & 3, 4, 5, 6, 12, 23, 25, 26, 29, 30, 33, 34, 37, 38, 39 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Results of ranking feature NSL-KDD.  
* Ensemble Method: The ensemble method aims to select the final best decision by using majority voting on the outputs from individual classifiers (ANN, kNN, C4.5, and Bagging). With six feature-reduced sets, we established six ensemble methods to construct the final anomaly-based IDS.
## 5 Mechanisms Used by Industrial Technologies to Improve Performance Metrics
### Channel Hopping Techniques
This hopping separation is more than the _coherence bandwidth value_--the frequency-shift by which a link has to undergo transition from deep fade-in the case of indoor multi-path interference [26]. WISA employs frequency-hopping sequences in which the consecutive hops are widely separated in frequency and the sub-band bandwidth is more than the typical bandwidth of the coherence bandwidth. WISA uses frame-by-frame frequency hopping in which the used radio channel for retransmission is independent of the previous one, so likelihood of a successful transmission increases.