esa-sceva/satcom-chunk-collection huggingface dataset:
# Improving Bundle Routing in a Space DTN by Approximating the Transmission Time of the Reliable LTP
###### Abstract  
Because the operation of space networks is carefully planned, it is possible to predict future contact opportunities from link budget analysis using the anticipated positions of the nodes over time. In the standard approach to space delay-tolerant networking (DTN), such knowledge is used by contact graph routing (CGR) to decide the paths for data bundles. However, the computation assumes nearly ideal channel conditions, disregarding the impact of the convergence layer retransmissions (e.g., as implemented by the Licklider transmission protocol (LTP)). In this paper, the effect of the bundle forwarding time estimation (i.e., the link service time) to routing optimality is analyzed, and an accurate expression for lossy channels is discussed. The analysis is performed first from a general and protocol-agnostic perspective, assuming knowledge of the statistical properties and general features of the contact opportunities. Then, a practical case is studied using the standard space DTN protocol, evaluating the performance improvement of CGR under the proposed forwarding time estimation. The results of this study provide insight into the optimal routing problem for a space DTN and a suggested improvement to the current routing standard.  
delay-tolerant networking; space communications; interplanetary networking; routing; reliability; performance modeling +
Footnote †: journal:  
0
## 6 Experiments and Results
### Experiment Environments and Parameter Setting
#### 6.1.4 Data Recovery Parameters Setup
To get proper rank estimation, we implement many times data recovery experiments with different rank. In addition, the data recovery results are computed by the above metric. The results of simulative and real networks are shown in Figure 7. According to the results, we choose different rank for the data recovery. In the simulated networks, the appropriate rank is assigned to 10 according to the experimental results shown in Figure 7a. In real network, the appropriate rank is assigned to 5 according to the experimental results shown in Figure 7b.
# Image Retrieval Method Based on Image Feature Fusion and Discrete Cosine Transform
## 2 Related Work
### Svd  
SVD is a factorization of a real or complex matrix that generalizes the eigendecomposition of a normal square matrix to any \(m\times n\) matrix \(M\) via an extension of the polar decomposition. The singular value decomposition has many practical uses in statistics,signal processing, and pattern recognition. The SVD of an \(m\times n\) matrix is often denoted as \(\mathbb{U}\Sigma\mathbb{V}^{\mathrm{T}}\), where \"U\" is an \(m\times m\) unitary matrix, \"\(\Sigma\)\" is an \(m\times n\) rectangular diagonal matrix with non-negative real numbers on the diagonal, and V is an \(n\times n\) orthogonal square matrix. The singular values \(\delta_{i}=\Sigma_{ii}\) of the matrix are generally chosen to form a non-increasing sequence:  
\[\delta_{1}\geq\delta_{2}\geq\cdots\geq\delta_{N}\geq 0 \tag{18}\]  
The number of non-zero singular values is equal to the rank of \(M\). The columns of U and V are called the left-singular vectors and right-singular vectors of \(M\), respectively. A non-negative real number \(\sigma\) is a singular value for \(M\) if and only if there exist unit-length vectors \(u\) in \(K^{m}\) and \(v\) in \(K^{n}\):  
\[Mv=\sigma u\ \&\ M^{*}u=\sigma v \tag{19}\]  
where the \(M^{*}\) denotes the conjugate transpose of the matrix \(M\). The Frobenius norm of \(M\) coincides with:  
\[\|M\|_{2}=\sqrt{\sum_{ij}\left|m_{ij}\right|^{2}}=\sqrt{trace(M*M)}=\sqrt{ \sum_{i=1}^{\min\{m,n\}}\sigma_{i}^{2}}(M) \tag{20}\]
## 2 Battery Model Settings
### The Batteries
#### 2.1.3 Vanadium Redox Flow Battery (VRFB)  
Vanadium flux batteries are flow batteries based on the redox reaction, which exploits the ability of vanadium to exist in solution in four different oxidation states. The electrolytes, which are stored in tanks and flow into the batteries, are two solutions of vanadium ions in water and sulfuric acid. The main advantage of this cell is that it can obtain an unlimited capacity by using tanks of different sizes. In addition, downtime periods do not cause degradation. Two of the main disadvantages are the low energy density and the rather complex nature of the system. Other peculiarities of this technology are the long durability (over 20 years), the good efficiency, and the low maintenance costs. The battery can undergo overloads of up to 400% for over 10 s, and thanks to its chemical neutrality, there is no risk of fire since the electrolyte solution works autonomously as a refrigerant, limiting overheating issues.  
As said, the energy density of the VRFB is rather limited, between 10-75 Wh kg\({}^{-1}\). In addition, the costs of electrolytes and membranes significantly affect the final price of the battery, which is therefore relatively high [26].
## 5 Silicon Accumulation Improves Plant Disease Resistance
### Application of Si in Plant Diseases  
The role of Si in enhancing plant resistance to various disease stresses has been confirmed, indicating that Si can be used as a conventional fertilizer in most plants. The solid and liquid form of Si fertilizer enhances plant resistance to various pathogens. Liquid potassium silicate or sodium silicate can be applied to soil irrigation or foliar application, while solid calcium silicate fertilizers are integrated into the soil. In a field study, 15 kg of Si fertilizer per 100 m\({}^{2}\) significantly reduced the average incidence of fusarium wilt [103]. Application of calcium silicate at a rate of 5 metric tons ha-1 reduced the incidence and severity of ryegrass rice blast by 39.5% and 47.3%, respectively [77]. The application of Si in the substrate and foliar spraying of Si reduce the severity of bacterial spots and the area under the disease curve in melon [104]. A 2 mM concentration potassium silicate foliar spray applied to common bean plants decreased anthracose disease severity by 34% [105]. In field trials, the application of solid Si fertilizer, Si foliar fertilizer, and both significantly reduce the incidence and disease index of Sclerotinia sclerootomy rot, with no negative effects on major agronomic traits and seed quality [106]. Soluble Si could be a useful tool in integrated management against fusarium head blight pathogens by reducing the disease development on wheat [107]. The external application of Si can effectively reduce the disease index and incidence of sugarcane disease caused by Xanthomonas albilineans [108]. The application of slag-based fertilizer to Si-deficient paddy soil is necessary for improving both rice productivity and brown spot resistance [109].
## 2 Results and Discussion
### Pearson's correlation Analysis and HCA
According to a previous study, soluble free protocatechuic acid and vanillic acid might act as precursors or accelerants in the anthocyanin biosynthesis pathway [26]. According to another study, cyanidin-3-glucose is deglycosylated upon heating, with subsequent formation of protocatechuic acid upon degradation of deglycosylated cyanidin [27]. Furthermore, vanillic acid might be generated from peonidin-3-glucoside via the same mechanism [28]. Consequently, protocatechuric acid, vanillic acid, and anthocyanins are positively correlated. These observations were also consistent with the PLS-DA loading plot and OPLS-DA VIP plot analysis (Figures 1 and 2). Almost all terpen, including monoterpenes, triterpenenes, and tetraterpenes, were placed together in cluster 3, except for \(\beta\)-tocopherol, \(\gamma\)-tocopherol, \(\gamma\)-tocotrienol, \(\gamma\)-tepinene, and \(\alpha\)-cymene. Most volatiles were placed together in cluster 4, except for \(\alpha\)-pinene, \(p\)-cymene, D-limonene, ethylbenzene, and 2-acetyl-1-pyrrololine, which clustered together in cluster 3. Monoterpenes in cluster 3, such as \(\alpha\)-pinene, \(p\)-cymene, and D-limonene, were strongly correlated.
## 6 Conclusions  
The influence of the membrane tension has been evaluated by means of a FEM study and the main finding can be summarize as follows:  
* The range where the classic theories are applicable has been obtained. A significant transition zone where neither plate theory nor membrane theory can be applied has been identified. It has been quantified for a reference case.
* It has been proven the validity of the theory of Wah [30] to describe the behaviour of part of that transition zone. It has been completed with FEM results for a wider range of values, connecting with the extreme results (plate and membrane theory).
* There has been identified some geometric ratios with significant hypersensitivity to very low tension. Some of these configurations are present in practical problems. One of them is in the different mammals hearing systems (including the human).  
The main consequence from these findings is the need to consider this effect when modelling membrane problems with low tension. It implies a double difficulty. On the one hand a proper estimation of the value of the pre-strain effect must be done. This is not easy to do, and, in most cases, there is no information to properly establish the value. On the other hand, once it has been obtained, it must be incorporated in the model and as it has been stated, small deviation provides significant response changes.  
One of the fields where this effect is relevant is the mechanics of hearing. Among researcher in this field, it is commonly accepted that the tympanic membrane presents a low level of tension, so this effect has been considered negligible in numerical model. According to these results, this effect should be evaluated and taken into account.  
Another situation is the manufacturing of micro devices with membrane elements. In this case, the presence of pre-strain is due to effects present during the different manufacturing steps. It can be caused for different reasons: temperature change, material shrinkage, etc. that are difficult to clarify and quantify.  
Finally, it must be pointed out a potential application of these results. The complete correlation obtained among pre-strain and natural frequencies opens an experimental option to determinate the level of pre-strain of a membrane system. By fitting experimental and numerical modal frequencies, using model update techniques, an estimation of the level of tension can be made. In this case, the model uncertainties (in term of mechanical properties and geometry) must be limited in order to establish a proper correlation among experimental and numerical results.  
Conceptualization, [PERSON] and [PERSON]; format analysis, [PERSON]; investigation, [PERSON], [PERSON] and [PERSON]; methodology, [PERSON] and [PERSON]; software, [PERSON] and [PERSON]; validation, [PERSON] and [PERSON]; writing--original draft preparation, [PERSON] and [PERSON]; writing--review and editing, [PERSON] and [PERSON].  
The authors acknowledge the financial support provided to this work by Junta de Andalucia from Operational Program FEDER 2014-2020 as a part of the research project UMA18-FEDERJA-214.  
The authors declare no conflict of interest.
# Testing of Indoor Obstacle-Detection Prototypes Designed for Visually Impaired Persons
## 2 Materials and Methods
### Prototypes Modules Material and Software
#### 2.1.1 Functionality Module  
The main function of the prototypes is to detect indoor obstacles placed in the path of the user. For this function, on the hardware part, a HC-SR04 ultrasonic sensor was chosen [13]. With a 4 m maximum range, a 15 degree measuring angle, easy use, easy maintenance, and cost-effectiveness, ultrasonic was the perfect candidate for this prototype. On the software part, the distance between the obstacles and the prototypes is calculated using two methods. The first method calculates the distance based on the algorithm described in Figure 1.  
The second method adjusts this distance based on data attained while calibrating the prototypes, as shown in Figure 2.
## 5 Problem Statement
For simplicity, consider the case where there are four wavelength channels on link 2\(\rightarrow\)3. Channels #3 and #4 are used as QCh and PCh, respectively; the remaining two channels, #1 and #2, can only provide data transmission for two service requests. When R1, R2, and R3 arrive at the same time, we try to assign wavelength channels to them. At this time, two wavelength channels need to meet the data transmission requirements of three services; thus, wavelength conflicts will occur. Then, one service request must be blocked, such as the request R3, as shown in Figure 5c. Therefore, to improve the success rate of requests, we should avoid potential wavelength conflicts in the resource allocation process. Figure 4: An example of routing assignment for the six-node network topology. **(a)** Static routing: fixed parameters such as link lengths are used as weights; **(b)** Dynamic routing: the real-time remaining number of resources is used as weights. To summarize, which scheme to allocate limited wavelength resources and rare quantum keys to in order to reduce wavelength conflicts and blocking probability is an important research topic in short-distance QKDON.
## 3 Results and Discussion
### Transmission Coefficient  
The transmission coefficient for three ports of the KAYI MIMO antennas is presented in Figure 9. The S\({}_{12}\), S\({}_{13}\) are the mutual coupling curves between the adjacent antennas. The results show that the antennas are well-isolated from each other. The isolation of MIMO is below \(-20\) dB in the entire frequency band.
## 4 Operationalization of the XR Framework for Safety Management
### Implementation Examples
#### 4.1.5 Terrain and Physical Environment Models  
As part of the construction planning process, but also as part of the design stage, 'terrain and physical environment' models consider the topography and surroundings of the construction site. Depending on the tools with which they were obtained, these can consist of contour lines with simple discrete points (a traditional topography) or more robust point cloud models obtained by drones using photogrammetry or laser scanners. These can be integrated directly into BIM environments (allowing integrated work in those environments in the initial design stages) or later in XR development environments. Considering the weight of this type of file, simple models (with less graphic quality) can be incorporated in the initial stages of the project or according to the requirements, and others with more detail can be used in stages where better graphic quality is required (for example, for the XR immersion). Figure 11 shows an example of a 3D environment reconstructed using photogrammetric techniques with images captured by drones. In this case, the model is used for construction planning. However, more simplified models (e.g., contour lines) will be required for the initial design.  
To provide context to the building site within a virtual or mixed environment, models of the environment can be incorporated. Figure 12 shows how a city environment has been implemented in Unity 3D. To make the generated scenario more realistic, the virtual environment should be similar to the real one. Based on the topography, an environment can be generated with elements of nature (mountains, vegetation), urban elements, buildings and streets, among others. It is important to consider that these elements add weight to the simulation; therefore, their graphic quality and properties should consider their level of interaction. For example, nearby streets and pavements can be implemented with a high level of development (e.g., where a worker will enter the construction site) and distant elements can be empty or be meshes for simple visualisation. Elements may be modelled or incorporated from free or paid 3D city model databases.  
Figure 11: Example of construction site point cloud.
## 4 Discussion
### Dataset and Methodology Limitations  
The 2012 and 2013 SeaSWIR dataset (field turbidity and water hyperspectral reflectance measurements) was used in this study to obtain relationships between water turbidity and water reflectance in the Green, Red and NIR spectral bands of satellite sensors, with \(\rho\) values (\(\rho=Rrs^{*}\pi_{\
u}\), dimensionless) ranging from 0.09 to 0.19, 0.09 to 0.22 and 0.01 to 0.15, respectively, in the Green, Red and NIR bands, and turbidity values ranging from 57.9 to 1484.7 NTU.  
This dataset covers well the ranges observed in the Pleiades satellite data in test site 1 (central part of the estuary: the most turbid waters) but has some limitations in test site 2 (the less turbid waters of the mouth area) where turbidity values typically range from \(\sim\)3 to \(\sim\)100 NTU [21]. The turbidity retrieval algorithm was therefore mainly designed for test site 1 in the present study, which certainly explains the very satisfactory results obtained in terms of validation in this area (Figure 8b, Table 4). Such validation could not be performed in test site 2. In the near future, additional in situ measurements of water reflectance and turbidity will be carried out in the mouth area (test site 2) where a new MAGEST station (located in Le Verdon) is about to provide continuous turbidity field data notably for the calibration of algorithms and validation of satellite products.  
The differences between Pleiades-1A and Pleiades-1B radiometric specifications was not taken into account in the present study, but these sensors have quite similar Relative Spectral Responses at Blue, Green, Red and NIR wavebands (Figure 3), resulting in very limited differences (MAPE of 0.9%, 1.6% and 3%, respectively, for the Green, Red and NIR bands) in terms of simulated water reflectances, based on the SeaSWIR dataset.
# Flavor and Functional Analysis of _Lactobacillus plantarum_
## 3 Results and Discussion
### Variable Changes in Volatile Substances during Fermentation of Apricot Juice  
The sensory characteristics and consumer acceptance of fermented apricot juice depend on the composition and concentration of volatile flavors. The composition and types of volatile flavors in fermented apricot juice are shown by a Venn diagram in Figure 3A. The volatile flavors were dynamically monitored by HS-SPME-GC-MS during all the stages of fermentation. In total, 50 volatile compounds were determined (Figure S5 and Table S2) including terpen (11), alcohols (8), ketones (8), aldehydes (7), esters (6), acids (4) and other compounds (6). Terpenes accounted for 52-61% of the total volatile matter, followed by alcohols (31-34%) and aldehydes (2-9%), esters, ketones, acids and other compounds accounted for 8-16% (Figure S4).  
A scatter plot showing the results of principal component analysis (PCA) of volatile compounds in seven fermentation stages of fermented apricot juice is shown in Figure 3B. Each stage was clustered according to the concentration and type of substances. The PCA showed that apricot juice had different flavors and metabolic characteristics in different stages of fermentation [53]. The volatile compounds were low at the initial stages (at 0, 2 or  
Figure 3: Venn diagram (**A**) and principal component analysis (PCA) (**B**) of volatile compounds from apricot juice during seven fermentation periods. S0, S2, S4, S6, S8, S10 and S12 represent fermentation for 0 h, 2 h, 4 h, 6 h, 8 h, 10 h and 12 h.  
Figure 2: VIP value diagram (**A**) and correlation diagram (**B**) of antioxidant capacity and phenolic compounds in seven fermentation stages of apricot juice. Each node represents phenolic compounds or antioxidant capacities. The green solid line and purple solid line represent positive and negative correlation, respectively. In addition, line width indicates the strength of correlation.  
4 h) and then rapidly increased after 4 h of fermentation. At 6 h, the contents of volatile compounds such as \(\alpha\)-terpineol, nerol, \(\beta\)-pinene and terpinene increased to the highest. At 8 h, the contents of volatile compounds such as (E, E)-2,4-heptadiene aldehyde, limonene, \(\gamma\)-decanolactone and 2,5-dimethylfuran were the highest. At 10 h, volatile compounds such as 3-hydroxy-2-butanone, 2-nonanone, \(\beta\)-ionone, 3-carene and methyl salicate were the highest, and the types of volatile compounds were the most in the whole fermentation period. At 12 h, the volatile compounds showed a slight decrease, which may be due to the reduced growth of LAB. The total amount of volatile compounds in wheat sourdough increased by 7- to 100-folds after fermentation [54]. Esters and ketones significantly improve the flavor of fermented products [55]. The change in flavor compounds of apricot juice was consistent with the change in the number of viable bacteria (Figure 1), indicating the importance of fermentation.
## 2 Data Quality Parameters and Related Work in OSM
### Completeness  
The completeness of map data is the most important data quality element next to positional accuracy. Completeness of spatial data describes the existence of features [21; 35; 36; 37] as compared to ground reality. [PERSON] et al. [35] have stated that the completeness of data focuses on the errors of omission and commission, whereas model completeness is an aspect of the fitness-of-use described under'semantic accuracy' [38]. Further, completeness is divided into two parts: feature and attribute completeness [32; 37]. Feature completeness presents the relative completeness of the percentage of features present in comparison to a reference dataset. Attribute completeness measures the relative completeness of attributes (e.g., the comparison of the road name in OSM to a reference dataset) in OSM and the reference dataset. Furthermore, the incompleteness of attributes has an impact on attribute accuracy, positional accuracy and logical consistency depending on their domains (geometric, topological, thematic, temporal, etc.).  
For assessing the completeness, an established procedure is used to compare test data with reference data. The method requires external data that can be used as the ground truth, and for this reason, its measurement tends to be extrinsic. In this, the relative completeness of a road network is determined by calculating the total length of the roads of the test dataset within a predefined area and that is then compared to a reference dataset for the same area [39; 40; 41; 42; 43; 44; 45; 46; 47; 48; 49; 50; 51; 52; 53; 54; 55; 56; 57; 58; 59; 60; 61; 62]. However, due to issues discussed earlier in Section 1, such comparisons are limited [18]. Therefore, suitable alternatives are necessary to assess completeness, based on intrinsic indicators, such as the OSM tags and their data's history [6; 63]. In the context of internal completeness quality analysis, [PERSON] et al. [64] have discussed meta-data and motivated developing and analyzing metadata [64; 65]. Metadata in OSM are the count of tags,  
Figure 1: Year-wise research publication data.  
the current maximum version for each tag, etc. [29]. Further, information about contributors who upload and edit the map is also metadata. Researchers [6; 27; 39; 40; 66; 67; 68; 69] have used various methods to assess the completeness of the OSM using various intrinsic indicators as discussed in Table 1.