esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Development History of Navigation Signal Authentication Technology
### Authentication Architecture for BDS  
Facing the construction of the next-generation BDS, a BDS signal authentication service system is built that integrates high-medium-low mixed constellation, and standard positioning service and augmented services. The architecture is shown in Figure 8. The BDS medium orbit and high orbit broadcasts navigation and augmentation signals, and adds signal authentication functions in the existing signal system framework to provide message integrity and signal source identity verification capabilities; low-orbit satellites can broadcast both navigation signals and communication signals. Its navigation authentication signal is similar to that of the medium and high orbits, and the communication signal has a two-way communication link with the terminal, which can provide large-capacity communication resources.  
Beidou navigation satellites will provide both navigation message authentication and a spreading code authentication service; BDSBAS will provide message authentication. Low-orbit navigation augmentation satellites can broadcast navigation ranging signals, and high-precision navigation messages, and transmit communication signals. Thus, on the one hand, the low-orbit navigation satellite provides two-way communication authentication, and on the other hand, it assists the BDS satellites or the BDSBAS satellites to complete the broadcast signal authentication and realize positioning authentication based on the spot beam. In addition, a third-party navigation signal authentication service can be provided using the terrestrial communication network.  
Figure 8: Authentication service architecture for BDS.
# Fusion Network for Change Detection of High-Resolution Panchromatic Imagery
## 5 Conclusions  
This paper presented a robust fusion network for detecting changed/unchanged areas in high-resolution panchromatic images. The proposed method learns and identifies the changed/unchanged areas by combining front- and back-end neural network architectures. The dual outputs are efficiently incorporated for low- and high-level differential features with a modified loss function that combines the contrastive and weighted binary cross entropy losses.  
Figure 10: Detection results for three areas when using an individual network output and the proposed algorithms: (**a**) \(D\), (**b**) \(O\), (**c**) Mean, (**d**) SOFN, and (**e**) the proposed fusion network with a two-stage decision.  
In addition, a post-processing step was applied to enhance the sensitivity and specificity from false changes/unchanged detections based on the neighboring information. We found through qualitative and quantitative evaluations that the proposed algorithm can yield a higher sensitivity and specificity compared to the existing algorithms, even under noisy conditions such as geometric distortions and different viewing angles  
For further work, the proposed algorithm can be extended for other modalities such as multi-spectrum images, Pan-sharpening, and SAR data. In addition, the proposed algorithm requires expensive time complexity caused by pixel-wise detection with a two-stage decision. To accelerate run-time complexity, block-wise prediction design would also be a focus of future work.  
All authors contributed to the writing of the manuscript. [PERSON] and [PERSON] conceived, designed the algorithm, and analyzed the data. [PERSON] developed it and conducted the experiments and analyzed the data. [PERSON] supervised the study.  
This research was supported by the Ministry of Science and ICT (MSIT), Korea, under the Information Technology Research Center (ITRC) support program (IITP-2018-2016-0-00288) supervised by the Institute for Information & communications Technology Promotion (IITP) and Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (NRF-2018R1A2B2008238).  
The authors declare no conflicts of interest.
## 4 Experiments
### Ablation Study  
To validate the functionality of individual components within the ICP-BGCN model, this paper devises three distinct ablation studies as follows:  
1. w/o BiPS: The bidirectional propagation graph module is removed. An undirected propagation graph is used to represent the propagation path, which only considers the structure of event propagation and does not consider its direction.
2. w/o Ps: Removed the information propagation graph. Without considering the influence of tweet propagation structure on detection, only the content semantic features of source tweets and response posts are used for false information detection.
3. w/o Text: Removed textual semantic information. The semantic features of the source tweet and the response post were removed, and the model only contained the bidirectional graph structure of the propagation relationship.  
The experimental results are shown in Tables 7 and 8. Analyzing these, it can be found that each module plays a unique role, and removing or replacing any of the components will  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Methods** & **Accuracy** & **Macro-F1** \\ \hline HiTPLAN [10] & 0.571 & 0.581 \\ MTL2-hierarchical transformer [50] & 0.643 & 0.657 \\ Coupled hierarchical transformer [50] & 0.678 & 0.680 \\ HCD-MGN [51] & 0.767 & 0.754 \\ ICP-BGCN & 0.785 & 0.792 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Comparative experimental results on SemEval-17 dataset.  
affect the overall performance of the ICP-BGCN method. When the undirected propagation graph is used to replace the bidirectional propagation graph model, the accuracy of the model on the two datasets is decreased by 2.8% and 2.8%, respectively, indicating that the topology structure combining propagation and diffusion can more effectively capture and model the propagation characteristics of events and enhance the event detection rate. Furthermore, only considering the propagation structure or relying on semantic information alone for false information detection will lead to a significant decrease in the accuracy of the model, which indicates that the propagation structure and semantic information have significant effects on false information detection respectively. Concurrently, the integration of both elements significantly enhances the precision of disinformation detection.
## 1 Introduction
### Multispectral LiDAR Systems
In a previous work conducted by the authors on land/water discrimination, we defined three normalized difference feature indexes (_NDFIs_) based on the intensity data acquired at the three wavelengths by the Optech Titan sensor [43] as follows:  
\[NDF\textsubscript{I}\textsubscript{C3}-\textsubscript{C2}\frac{\textsubscript{I} \textsubscript{C3}-\textsubscript{I}\textsubscript{C2}}{\textsubscript{I} \textsubscript{C3}+\textsubscript{I}\textsubscript{C2}} \tag{1}\]  
\[NDF\textsubscript{I}\textsubscript{C3}-\textsubscript{C1}\frac{\textsubscript{I} \textsubscript{C3}-\textsubscript{I}\textsubscript{C1}}{\textsubscript{I} \textsubscript{C3}+\textsubscript{I}\textsubscript{C1}} \tag{2}\]  
\[NDF\textsubscript{I}\textsubscript{C2}-\textsubscript{C1}\frac{\textsubscript{I} \textsubscript{C2}-\textsubscript{I}\textsubscript{C1}}{\textsubscript{I} \textsubscript{C2}+\textsubscript{I}\textsubscript{C1}} \tag{3}\]  
where \(\textsubscript{I}\textsubscript{C1}\), \(\textsubscript{I}\textsubscript{C2}\), and \(\textsubscript{I}\textsubscript{C3}\) are the intensity from the C1, C2, and C3, respectively. The results showed that the NDFIs could not be directly used for land/water discrimination. This is because of the recorded intensity values of vegetation and water are very close in each channel. Consequently, water points are misclassified as vegetation points [43]. The green wavelength has the ability to penetrate water bodies, allowing it to detect water surfaces and/or benthic layers [12; 13; 14; 15], while the infrared wavelengths can detect the water surface. This adds a new capability to the LiDAR system, especially at the land/water interface. Therefore, the dual-wavelength or multispectral airborne LiDAR system, including the green wavelength, is expected to aid in the automation of the land/water discrimination process. Also, to the best of the authors' knowledge, there is a lack of studies using dual-wavelength or multispectral LiDAR data in discrete returns format for land/water discrimination. In this research, we aim to (1) evaluate a set of point features, derived from the LiDAR data based on geometric and radiometric attributes, for discriminating water body from land objects; and (2) present an unsupervised land/water discrimination method based on a seeded region growing algorithm using discrete return multispectral LiDAR data.
## 2 Results and Discussion
### Results
#### 2.1.5 KEGG (Kyoto Encyclopedia of Genes and Genomes) Pathway Annotation  
To identify the active biological pathways and for further understanding the biological functions and interactions of genes, 71,095 all-unigenes were analyzed to the KEGG pathway database. In total, 32,200 unigenes having significant matches in the database were assigned to 5 categories (level 1), 19 sub-categories (level 2) and 128 pathways (level 3) (Table S3). In level 3, \"metabolic pathways\" had the largest number of unigenes (7137; 22.16%) followed by \"biosynthesis of secondary metabolites\" (3419; 10.62%). The \"metabolism\" category under level 2 contained 11 sub-categories, of  
Figure 3: Histogram presentation of gene ontology (GO) functional classification. The results are summarized in three GO ontologies: biological process, cellular component and molecular function. The right y-axis indicates the number of unigenes in a category and the left y-axis indicates the percentage in the same category.  
which the large four are \"global map\", \"carbohydrate metabolism\", \"lipid metabolism\" and \"amino acid metabolism\" (Figure 5A). In the \"biosynthesis of other secondary metabolites\" sub-category, 1280 uninges were classified into 13 pathways and most of them were mapped to \"phenylpropanol biosynthesis\", \"flavonoid biosynthesis\", \"stilbenoid, diarylheptanoid and gengerol biosynthesis\" and \"flavone and flavonoid biosynthesis\" (Figure 5B). Many enzymes mapped to unigenes in KEGG pathways indicate that the active metabolic processes were underway in _P. ginseng_ adventitious roots and a variety of metabolites were synthesized as well.
# A Comprehensive Study on EDFA Characteristics: Temperature Impact
## 3 Results and Discussion  
A variety of evaluation parameters such as maximum peak gain, optimum fiber length, Lopt, saturation signal power, Psat, and saturation pump power, Psat, are investigated. Each parameter is tested for several other related parameters such as the change of the driven input signal power, Psat, fiber length, L, and driven pump power, Psat. The effect of temperature on each parameter is then tested, and the results are graphically displayed.  
In this paper, all of the investigations are made on an Al/P-Silica EDFA at room temperature (27 \({}^{\circ}\)C) [34] using the parameters shown in Table 1[21]. To calculate the EDFA gain, first, the rate equations, Equations (3)-(5), are solved together. The effect of temperature on cross-sections is carried out using the McCumber relation, Equation (1), and the overlap factor is calculated from Equations (5)-(7). Then, the propagation equations are solved together from Equation (9) using a forward explicit Euler's method. Here, the effect of temperature is presented in this set of equations through both the cross-sections and the Boltzmann factor. For the sake of comparison, we have chosen the temperature range from \(-40\)\({}^{\circ}\)C to \(+80\)\({}^{\circ}\)C such as in the work of [PERSON] et al., [PERSON] et al., [PERSON] et al., [PERSON] et al., and [PERSON] at al. [19; 20; 23; 35; 36]. The value of \(\Delta\)E\({}_{2}\) was chosen to be 200 cm\({}^{-1}\) for simplicity [14]. Some boundary conditions are taken into account. First, we consider that the amplified spontaneous emission (ASE) power in the forward direction, P\({}_{\text{ASE}}^{+}\), is zero at the entry of the EDFA. Also, ASE power in the backward direction, P\({}_{\text{ASE}}^{-}\), is considered to be zero at its end.  
The values of all of the needed parameters in the simulation are shown in Table 1. The used absorption and emission cross-sections at room temperature are extracted from the work of Miniscalco [34], and are typical for Al/P-Silica erbium-doped glasses.  
We validate the accuracy of the used analytical model in our work to the study concerning the optimum fiber length, which was calculated already and introduced by [PERSON] et al. [15]. The procedure is accomplished by setting \(\beta=1\), and the obtained values are found in a complete agreement with that mentioned and simulated in Figure 5 in the work of [PERSON] et al. [15]. Another check was accomplished using the given parameters by [PERSON] [21], where again a fair agreement was found between the obtained results and already simulated results in Figure 2 by [PERSON] [21].
## 2 Applications of Chiral Nanoparticles
### Biomedicine
[PERSON] and colleagues also investigated the chiral recognition and subsequent release of IMC by two using concealed-body chiral mesoporous silica nanoparticles (Cb-L(D)-MSNs) prepared with either L- or D-tartaric acid [75]. Both Cb-D-MSN and Cb-L-MSN significantly improved IMC dissolution, oral bioavailability, and anti-inflammatory effects compared to achiral MSN and, even more interestingly, the two chiral MSNs showed different chiral recognition behavior, with the Cb-D-MSNs showing higher affinity for the drug and sodium-dependent glucose transporter (SLGT) (Figure 7). Figure 7: Enantioselective recognition and release of indomethacin (IMC) by means of concealed-body chiral MSNs prepared with either L- or D-tartaric acid. Reprinted with permission from [75], Copyright Elsevier, 2018. Similar results were obtained by [PERSON] et al. with on-off chiral mesoporous silica nanoparticles (On-Off-D-CMSN and On-Off-L-CMSN) [76]. The two IMC-loaded On-Off-L(D)-CMSNs exerted different chiral recognition functions with on-off mechanism in an in vitro chiral environment; however, this time the L enantiomer yielded a higher anti-inflammatory effect than the D enantiomer, probably because the NPs could trigger chirality of the biological environment, thus achieving on or off chiral recognition functions. In order to investigate different geometries, twisted rod-like chiral MSNs were employed for solubilizing ibuprofen by using L- and D-alanine derivatives as templates to obtain chiral helical structures [77]. MSNs with different chirality were able to effectively encapsulate the drug, with the D enantiomer being more efficient, as well as being able to achieve drug release differentiation and enhance the dissolution of ibuprofen in simulated gastric fluid, depending on the pH of the medium and on the pore size of the MSNs. Despite using a different metallic core, [PERSON] et al. synthetized CdS NPs in anodic aluminum oxide (AAO) nanochannels and functionalized their surface with cysteine for binding BSA. They noted that the L enantiomer was able to bind more strongly the protein, thus enhancing the response sensitivity of BSA transport [78].
## 3 Proposed Algorithmic Approach
### Initial Default Route  
Because there is not enough information available to execute any algorithm, it is necessary to configure an initial default route that connects all the nodes in a linear manner, which causes a separation of 15 cm between them. Once each node has the necessary information for the controller to run the algorithm, a push button is used to transmit each node's neighbor tables. When activated, it generates a frame that jumps from node to node until it reaches the controller, as shown in Figure 8.  
The transmission times between nodes when communicating through the initial default route were measured to compare algorithms and determine the most efficient. Con  
Figure 8: Communication between nodes and the controller through initial default route (uplink).  
Figure 7: Example of default routes.  
sidering the separation distance and the initial configuration of the default route, the nodes communicate linearly, with a separation distance of 15 cm between them. Measurements of the initial default route reveal that a frame originating from the node furthest from the controller (node 1) takes 42 milliseconds, considering 6 relay nodes in which the source node is included and a delay time in each node of 6 msec, to reach the controller node. Each node's average retransmission time, totaling six milliseconds, encompasses propagation time, frame transmission time (TF), frame processing (\(T_{FP}\)) time, backoff time (\(T_{BO}\)), time to switch from receiver to transmitter (\(T_{TA}\)), and the duration required to detect a busy channel (\(T_{CA}\)), as depicted in Figure 9. Notably, propagation time is significantly shorter compared to the other time components, and the average values obtained account for various backoff times in scenarios where two nodes seek access to the channel.  
The time recorded by the sniffer denotes the moment when the frame arrives and is stored for processing, excluding the duration from when the frame departs the source node and the propagation time. It is important to note that the subsequent measurements at the next node encompass these times, including the frame's departure from the source node and the propagation time. This consistency is maintained across all retransmissions due to the test scenario.  
The measurement of the transmission time of a frame traveling through the initial default path is considered a reference to compare the performance of the nodes with and without the application of the algorithm.
# A Methodology Linking Tamping Processes and Railway Track Behaviour
## 3 Principles of Tamping Processes
### Compactness of the Ballast  
A well-compacted ballast bed is an important factor for the quality and durability of the track geometry [36; 37; 38; 39; 40; 41; 42]. Different methods have been proposed to assess the compactness of the track ballast. These methods can be summarised as direct measurements, indirect assessments, and computer models and simulations. Direct measurements of the ballast compactness were conducted by [PERSON] et al. [43] and [PERSON] et al. [40] in the form of the water-filling method. This approach allows a precise calculation of the compactness and its change during tamping (by repeating the experiment afterwards) but implies a disturbance of the ballast matrix at the examination point. Indirect assessments of the ballast compactness were conducted by [PERSON] et al. [44] and [PERSON] et al. [39]. The former analysed measurement data recorded by sensors attached to the tamping tines of a tamping machine, from which they derived parameters indicating the plastic deformation of the ballast matrix, which correlates with the compaction. The latter employed the seismic method, which makes use of the dependence of the wave propagation velocity of an acoustic signal on the compactness of granular matter. Both studies delivered promising results and proofed the applicability of the respective concept. [PERSON] et al. [39] note that the quality of the ballast compaction can also be estimated (i.e., indirectly assessed) by the stability of the track geometry (Section 2.2). Computer models and simulations enable sophisticated analyses of the interaction between tamping tools and the bedding. [PERSON] et al. [45] created a model coupling the discrete element method and multibody dynamics.  
The model allowed analyses of the ballast compactness in different areas of the track cross section and clearly showed the positive effects of tamping in that regard.
# Exploration of Floral Volatile Organic Compounds in Six Typical _Lycoris_ taxa by GC-MS
###### Abstract  
_Lycoris_, which is known as the 'Chinese tulip,' has diverse flower colors and shapes, and some species have a delicate fragrance. However, limited studies have reported the volatile organic compounds (VOCs) of _Lycoris_. In this study, headspace solid-phase microextraction combined with gas chromatography-mass spectrometry was used to analyze the floral VOCs of six typical _Lycoris_ taxa. Thirty-two VOCs were identified, including terpenoids, alcohols, esters, aldehydes, ketones, and phenols. The aldehyde and terpenoid contents in _Lycoris aurea_ were higher than in the other taxa, and the ester and alcohol contents in _L. sprengeri_ were the highest compared to all taxa tested. Compared with other species and cultivars, _L. longituba_ and _L. longituba_ var. _flava_ were the two most scented taxa and the VOCs were dominated by terpenoids and esters. _L. radiate_ and _L. chinensis_ were two unscented taxa and, accordingly, the VOC content was weak. A partial least squares discriminate analysis of the floral VOCs among the six _Lycoris_ taxa showed that the six taxa could be successfully separated. Moreover, the VOCs of _L. longituba_ and _L. longituba_ var. _flava_ clustered together. \(\beta\)-Ocimene was verified as the most important aroma compound, as determined via the calculation of the variable importance in projection values and significance analysis. \(\beta\)-Ocimene and its trans isomer, _trans_-\(\beta\)-ocimene, had a high relative content in _L. longituba_, _L. longituba_ var. _flava_, _L. aurea_, and _L. chinensis_ but were not detected in _L. sprengeri_ and _L. radiata_. These results indicate that floral VOCs might be selected during the evolutional processes of _Lycoris_, and \(\beta\)-ocimene could be the most typical VOC among the different _Lycoris_ taxa.  
_Lycoris_; tepal; aroma; GC-MS; volatile organic compounds +
Footnote †: journal:plants
# GPSR: Gradient-Prior-Based Network for Image Super-Resolution
## 3 Method  
Most SR methods suffer from blindly recovering high-frequency details, resulting in their reconstructed images lacking sharp edge and texture details, along with undesired geometric distortion and artifical artifacts [34; 35]. Particularly, this problem becomes more severe as the scaling factor increases. To address the problem, we propose a Gradient-Prior-based Super-Resolution network (GPSR), which is able to reconstruct sharp edge and texture details in SR tasks with large scaling factors (i.e., \(\times\)4 and \(\times\)8). In this section, we first introduce the overall architecture of our GPSR, followed by a detailed description of the detail-preserving Gradient-Guided Strategy (GGS) and the Residual Spatial Attention Adaptive Aggregation Module (RS3 AM).