esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Theoretical Background
### Parametric Lifetime Models
#### 2.4.3 Other Parametric Distributions  
There are several other parametric distributions, such as normal distribution, logistic distribution, lognormal distribution, gamma distribution, beta distribution, loglogistic distribution, Gumbel distribution, etc. [13; 17; 19]. For the exponential, Weibull, gamma, lognormal and loglogistic distributions, there is a location-shifting parametrization using the gamma \(\gamma\) parameter [13].  
Some distributions are preferred to others, depending on the scientific context of the advantages and disadvantages [19]. Exponential distribution is a memoryless distribution and is used to model the lifetime of electronic and electrical equipment that fails randomly [17]. It considers that the past history of the component has no effect on its future lifetime [17]. The normal distribution is capable of describing some dynamic component failures or failures that occur in a specific period of time, including some deviations [17]. The graphical plot of the logistic distribution is analogous to the normal distribution [17]. The failures that happen at the beginning of the life cycle in projects, startups, installations, or operations are mostly represented by the lognormal distribution [17]. It can model both random and wear-and-tear failure mechanisms. The loglogistic distribution and lognormal distributions have the same shape [17]. The Weibull distribution is frequently used to model the lifetime of components that fail due to wear and tear, and it depends on parameters of exponential, lognormal, or normal distributions [17]. The Weibull distribution is flexible and can be used to model increasing and decreasing failure rates [17]. When the data are right-skewed and the failure rate decreases over time, then the gamma distribution can be used for modeling [17]. The component failures that occur at the end-of-life cycle of pipelines, vessels, and towers, etc. can be represented by the Gumbel distribution [17].
## 3 The Hybrid Distributed Topology Control Scheme (HDTC)
### Phase III: Reforming the Communication/Routing Group
#### 3.3.1 Communication Group \(G_{u}\)  
Let the upper bound _UB_and the lower bound _LB_represent the constraints of the group size for managing the topology change. When the group size is over the upper bound _UB_ (_i.e._, \(|G_{u}|\geq UB\)), update \(G_{u}\) and \(R_{u}\); while \(LB\leq|G_{u}|<UB\), monitor and update \(R_{u}\) if necessary; when the group size is under the lower bound _LB_, reform the communication group and go to Phase I. Thus, each group size is adjusted autonomously.  
Accordingly, vehicle \(u\) may include its new neighbors when the group size constraint is satisfied. On the other hand, when a vehicle leaves a group, this link down event can be detected by not receiving periodical broadcasting messages, and the neighboring vehicles can update the knowledge of their neighborhood. This phase performs the group reformation, which aims to maintain topology stability. The reformation conditions are:  
Figure 7: Flow diagram of Phase II: Determining the routing group members.  
1. If \(|G_{u}|\geq UB\), update \(G_{u}\) and \(R_{u}\).
2. If \(UB>|G_{u}|\geq LB\), go to Phase II, monitoring and updating the routing group members \(R_{u}\).
3. If \(|G_{u}|<LB\), increase \(\theta\) and go to Phase I (_i.e._, reforming \(G_{u}\)).  
Notice that since the neighbor vehicle properties depends on the type of mobility occurring in the network, the upper bound _UB_ and the lower bound _LB_ of the group size are given according to the number of vehicles and issues on the mobility model.
# Multivariate Algorithmics for Finding Cohesive Subnetworks
## 3 Distance-Based Clique Relaxations
### Sets of Vertices Connected by Short Paths: \(s\)-Cliques  
In a related clique relaxation, it is allowed that the short paths between group members use vertices that are not part of the group.  
**Definition 8**.: A set \(S\subseteq V\) is an \(s\)_-clique_ in a graph \(G=(V,E)\) if every \(u\in S\) and every \(v\in S\) have distance at most \(s\) in \(G\).  
\(s\)-Clique  
**Input:**: An undirected graph \(G\) and an integer \(k\).
**Question:**: Does \(G\) contain an \(s\)-clique of size at least \(k\)?For example, a known heuristic for \(s\)-Club is to first compute a maximum \(s\)-clique and then to find a maximum \(s\)-club \(S^{\prime}\subseteq S\)[46]. Hence, algorithmic improvements for \(s\)-Clique may yield improved algorithms for \(s\)-Club. In this context, it is of interest that being an \(s\)-clique is hereditary: to determine whether a set \(S\) is an \(s\)-clique, one considers simply each pair \(u\) and \(v\) of vertices and evaluates a predicate that depends only on \(G\), \(u\) and \(v\) and not on other vertices in \(S\). Hence, removing any vertex from an \(s\)-clique \(S\) yields another \(s\)-clique. Thus, one may, for example, solve \(s\)-Clique by deciding whether or not \(G\) contains an \(s\)-clique of size _exactly_\(k\).  
Most tractability results that have been achieved for \(s\)-Club transfer easily to \(s\)-Clique. For example, Observation 3 is also valid if we replace \(s\)-club by \(s\)-clique. It also holds trivially that every \(s\)-clique of a graph \(G\) is a subset of \(N_{s}[v]\) for some vertex \(v\). These two facts give immediately the following tractability results.  
For \(s>1\), \(s\)-Clique is fixed-parameter tractable with respect to \(k\) and also with respect to \((\Delta,s)\).  
Concerning the dual parameter \(\ell:=n-k\), one can exploit once more the close connection to Vertex Cover to obtain fixed-parameter tractability.  
For all \(s\), \(s\)-Clique can be solved in \(O(1.28^{\ell}+\ell n+nm)\) time.  
Proof.: First, compute in \(O(nm)\) time the \(s\)-th power \(G^{s}\) of the input graph \(G\). Then, use the fact that a set \(S\) is an \(s\)-clique in \(G\) if and only if it is a clique in \(G^{s}\). To this end, compute whether \(G^{s}\) has a clique of size at least \(k\) by finding a vertex cover of size at most \(\ell\) in \(\bar{G^{s}}\), the complement graph of \(G^{s}\). The running time bound follows from the running time of the current-best Vertex Cover algorithm for the parameter solution size [22].  
Proposition 6 shows that a SETH-based lower bound as it is known for \(s\)-Club parameterized by \(\ell\) is unlikely for \(s\)-Clique. Of course, it would be interesting to obtain faster algorithms by exploiting that the input graphs for the Vertex Cover instance are not arbitrary graphs, but powers of other graphs. Maybe it could be more interesting to find situations where the complexity of \(s\)-Clique and \(s\)-Club are really different. For example, the complexity of \(s\)-Clique for the two remaining parameters is open.
# A Vector Sensor-Based Acoustic Characterization System for Marine Renewable Energy
## 3 Results
### Flow Noise Removal
The in-phase components \(\textbf{C}_{\text{ij}}\)(x,\(\omega\)), termed the active intensity, represent the net power being propagated by the acoustic field. The quadrature component, \(\textbf{Q}_{\text{ij}}\)(x,\(\omega\)), termed the reactive intensity, relates pressure and particle velocity components that are orthogonal to each other, and it represents spatially heterogeneous power flow [17]. Non-acoustic contamination may be evaluated through the reactive intensity components of the cross-power spectral density matrix. For example, a metric to evaluate the contribution of the non-acoustic component on the x-particle velocity channel can be defined [18] that arises from the relationship between the particle velocity cross-spectra and active and reactive intensity vectors. \[M_{21}=\frac{\left|Q_{34}(\omega)\right|-\left|\left(\frac{C_{\text{i}2,34}( \omega)\times\textbf{Q}_{\text{i}2,34}(\omega)}{S_{\text{i}1}(\omega)}\right) _{x}\right|}{\left|Q_{34}(\omega)\right|+\left|\left(\frac{C_{\text{i}2,34}( \omega)\times\textbf{Q}_{\text{i}2,34}(\omega)}{S_{\text{i}1}(\omega)}\right) _{x}\right|}. \tag{1}\]  
The notation \(\textbf{X}_{\text{i}[2,3,4]}\) represents the off-diagonal elements of the matrix **X**, arranged as a vector, and \(\times\) is the vector cross-product. Values of \(M_{\text{i}2}\) that deviate significantly from zero are considered to be a flag of non-acoustic contamination. Similar to \(M_{21}\), metrics for the other particle velocity channels (\(M_{22}\), \(M_{23}\)) can be defined. The probability distribution of \(M_{21}\) (Equation 1) was computed for NoiseSpotter VSA data collected at MSL over a 30-min period during each tidal cycle, as shown in Figure 7. A marked contrast is seen in the distributions with and without the flow shields. Distributions with the flow shield (right half of Figure 7) are seen to cluster around zero between 0 and 250 Hz, and no significant deviations toward higher values are observed. In contrast, the \(M_{\text{i}2}\) distributions without the flow shield (left half of Figure 7) are seen to cluster toward a value of 1 over much of the 0-500 Hz range shown, indicating the presence of non-acoustic signal contamination.
## 5 Conclusions  
The application effects of date palm waste biochar derived from two different production processes on evaporation, moisture distribution, infiltration, sorptivity (Sp), saturated hydraulic conductivity (\(\mathrm{K_{sat}}\)), and water holding capacity (WHC) were examined in a soil column experiment. The findings demonstrated that in comparison to untreated soils, increasing the application of date palm waste biochar (macro and nanoparticles) decreased daily and cumulative evaporation. As a result, with the addition of biochar in the topsoil surface, soil water conservation increased. Moreover, adding date palm waste biochar with nanoparticles at a depth of 5-10 cm was more effective on the water that is retained in soils. The application of biochar significantly reduced the infiltration rate, cumulative infiltration, \(\mathrm{K_{sat}}\), and WHC compared to untreated soils. Additionally, it was found that untreated soils showed the highest evaporation, infiltration, and \(\mathrm{K_{sat}}\) rates while having the lowest soil water conservation, soil moisture distribution, and WHC. It would be reasonable to conclude that date palm waste biochar, particularly when added at the nanoscale particle size, is beneficial for modifying the hydro-physical characteristics of sandy soils, and thus has great impact on the growth of the field crops and vegetables.  
This research received no external funding.  
Not applicable.  
Data Availability Statement: Data are available from the authors upon request.  
This project was funded by the National Plan for Science, Technology, and Innovation (MAARIFAH), King Abdulaziz City for Science and Technology, Kingdom of Saudi Arabia, Award Number (13-AGR1104-02).  
The authors declare no conflict of interest.  
Figure 7: Saturated hydraulic conductivity \(\mathrm{K_{sat}}\) of macro-biochar and nanoparticles in relation to sandy soils.
# Biodeterioration of Salon de Reinos, Museo Nacional del Prado, Madrid, Spain
## 3 Results and Discussion
### Metabolic Activities of Bacterial and Fungal Isolates  
Trovao and Portugal [5] described the importance of using plate assays for identifying the deteriorative abilities of microorganisms in order to evaluate the potential risks to mural paintings. The isolation of microorganisms and plate assays are widely used by microbiologists in deterioration studies to provide insight into their attack on different types of materials [5; 52; 53; 54; 14; 55; 13; 26]. Table 5 presents the metabolic activities of the isolates and their role in the hydrolysis of gelatin, casein, and lipids, the solubilization of gypsum and calcite, and acid production (Figure 3). The most conspicuous activities, with a greater number of positive strains, were the hydrolysis of casein and lipids, and to a lesser extent, the hydrolysis of gelatin and the production of acids and alkalis. The activity of _Penicillium chrysogenum_ stands out, with six out of seven strains hydrolyzing casein, in addition to the _Penicillium fuscoglaucum_ strain. All the other fungal strains were negative for casein hydrolysis. Among the bacteria, five out of the nine _Bacillus_ strains also hydrolyzed casein, as well as _Cytobacillus oceanisediminis_, _Streptomyces thinghiensis_, and _Stagnosporopsis lupini_. The degradation of lipids is important in the _Bacillus_ strains, of which six out of nine presented lipolytic activity, while only two out of the nine of _Penicillium chrysogenum_ showed such activity, in addition to _Penicillium fuscoglaucum_ and _Botryotrichum domesticum_. It should be noted that only the two strains of _Bacillus paralicheniformis_ were capable of hydrolyzing gelatin. Acid/alkali production was found in only five _Bacillus_ strains. Calcite solubilization was very limited in the isolated strains and showed only in one strain of _Penicillium chrysogenum_ and _Penicillium fuscoglaucum_. Gypsum solubilization was present in only three _Bacillus_ strains. _Bacillus_ species generally produce enzymes such as lipases, proteases, xylanases, and others that allow for the breakdown of casein, gelatin, and lipids. Specifically, _Bacillus cereus_ produces these types of enzymes. However, the strain isolated from _Salon de Reinos_ does not possess these capacities, since it did not show hydrolytic activity against casein and lipids. In light of the obtained data, the species with potential biodeterioration properties mainly belong to the genera _Bacillus_, _Pristia_, _Cladosporium_, and _Penicillium_, as described in other reports [2; 3; 4; 5]. In addition, it should be noticed that airborne microorganisms, commonly isolated from plants, are able to use lipids and casein from mural paintings as nutrient sources and therefore represent a risk for mural paintings.
## 3 Application of Integrated Transducer Arrays for Generation of Sound Waves
### Experimental Investigations
#### 3.3.1 Laser Doppler Vibrometry  
To assess the mechanical wave induced by the actuators, a series of experiments using the scanning laser Doppler vibrometer (type PSV-400 produced by Polytec GmbH, Waldbrunn, Germany) were conducted. The application of a contactless measurement system guarantees that the mechanical properties of the investigated object are not distorted by the additional mass of typical vibration sensors.  
Since the output signal of the laser scanning vibrometer is directly proportional to the velocity of the targeted surface along the laser beam direction, the LDV has been positioned normal to the analyzed plate. In order to assure to high reflection of the laser light and, hence, a high signal-to-noise ratio, a large section on the plate surface was covered with a reflective spray paint. A regular spatial distribution of 55 \(\times\) 97 discrete measuring points in approximately 2 mm distance has been selected to guarantee reliable capturing of the wave's spatial and time development. The investigated plate was hung vertically using a thin light rope (Figure 12).  
The actuators were excited with a typical burst signal as it can be used for different measurement tasks. Based on the plate dimensions and the array setup a center frequency of 35 kHz was chosen. The signal consists of a four-periods-long sinusoidal signal which was windowed with a Hann window to limit the bandwidth. The triggered 2.5 ms long time series of out-of-plane velocities were recorded  
Figure 11: Organic sheet, _eProform_ with TPM pattern, and conductors (thermally stapled).  
Figure 12: Experimental setup for the determination of propagation of induced mechanical and acoustical waves.  
20 times in every point and subsequently averaged to reduce the noise content in the acquired signals. The time resolution of the LDV was set to 4.883 us to assure at least five samples per measured signal period.
# Semi-Global Stereo Matching Algorithm Based on Multi-Scale Information Fusion
## 3 Experimental Design and Results Analysis  
In this Section, experimental design is first introduced with Middlebury datasets to examine the effectiveness of the proposed method. Then, experimental results of our method are compared with those of some typical methods available in the literature.
# Image Watermarking between Conventional and Learning-Based Techniques: A Literature Review
## 2 Image Watermarking Background
### Embedding Phase
#### 2.1.1 Additive Method  
The additive approach consists of adding the watermark to the image's components using one of the mathematical equations listed below [32]:  
\[\left\{\begin{array}{l}I_{w}=I_{0}+\alpha\times W\\ I_{w}=I_{0}(1+\alpha\times W)\\ I_{w}=I_{0}\times e^{\alpha\times W}\end{array}\right. \tag{1}\]  
where \(\alpha\) controls the watermark insertion strength to maintain the balance between the imperceptibility and robustness requirements. Watermarks can be added directly to the pixels of the original image or to the frequency components after image transformation, such as discrete wavelet transforms [33], discrete Fourier transforms [34; 35], discrete cosine transforms [36], etc. Figure 5 shows the principle of additive insertion.  
Figure 4: General scheme of digital watermarking.
# A Collocation Method for the Numerical Solution of Nonlinear Fractional Dynamical Systems
## 2 Materials and Methods
### The Cardinal B-Splines  
The cardinal B-splines are piecewise polynomials with breakpoints on integer knots. Given the sequence of simple integer knots \(\mathcal{I}=\{0,1,\dots,n+1\}\), the Cardinal B-spline of integer degree \(n\geq 0\) can be defined by applying the divided difference operator to the truncated power function \(t_{+}^{n}:=\max(t,0)^{n}\) on the knots \(\mathcal{I}\):  
\[B_{n}(t) := (n+1)[0,1,\dots,n+1](x-t)_{+}^{n}=\] \[= (n+1)\,\frac{\left|M\left(\begin{array}{c}1,x,x^{2},\cdots,x^{n },(x-t)_{+}^{n}\\ 0,1,2,\cdots,n,n+1\end{array}\right)\right|}{\left|M\left(\begin{array}{c}1,x,x^{2},\cdots,x^{n},x^{n+1}\\ 0,1,2,\cdots,n,n+1\end{array}\right)\right|}=\frac{1}{n!}\,\Delta^{n+1}\,t_{+} ^{n}\,,\]  
where  
\[M\left(\begin{array}{cccc}f_{1}(x),&f_{2}(x),&\cdots,&f_{n}(x)\\ x_{1},&x_{2},&\cdots,&x_{n}\end{array}\right)=\left[\begin{array}{cccc}f_{1} (x_{1})&f_{n}(x_{1})&\cdots&f_{n}(x_{1})\\ f_{1}(x_{2})&f_{n}(x_{2})&\cdots&f_{n}(x_{2})\\ \cdots&\cdots&\cdots&\cdots\\ f_{1}(x_{n})&f_{n}(x_{n})&\ldots&f_{n}(x_{n})\end{array}\right]\]  
is the collocation matrix of the function system \(\{f_{1}(x),f_{2}(x),\dots,f_{n}(x)\}\) on the nodes \(\{x_{1},x_{2},\dots,x_{n}\}\) and  
\[\Delta^{n}\,f(t)=\sum_{k=0}^{n}\,(-1)^{k}\,\begin{pmatrix}n\\ k\end{pmatrix}f(t-k)\]  
is the backward finite difference operator.  
We recall that \(B_{n}(t)\) is compactly supported on \([0,n+1]\), is positive in \((0,n+1)\) and belongs to \(C^{n-1}(\mathbb{R})\). For details and further properties on polynomial B-splines, see, for instance, [19].
# Effects of Pretreatment on the Volatile Composition, Amino Acid, and Fatty Acid Content of Oat Bran
## 3 Results and Discussion
### Effects of Heating Methods on Fatty Acids of Oat Bran
#### 3.5.2 Correlation Analysis of Fatty Acids and Flavor Components in the Pretreated Oat Bran  
The correlation analysis demonstrated that linoleic acid (C18:2) displayed a significant positive correlation with VFC23, VFC45, VFC19, and VFC40 (\(p<0.05\)), whereas oleic acid (C18:1) and palmitic acid (C16:0) displayed a significant negative correlation with those substances (Figure 4, Table 2) (\(p<0.01\)). The constituents were detected only in S-OB. Oleic acid (C18:1) exhibited an extremely significant positive correlation with VFC13, VFC28, VFC33, VFC42, VFC34, VFC43, and VFC26 (\(p<0.01\)). The constituents were (E, E)-2,4-decadienal, 1-octen-3-ol, (Z)-4,5-dimethylhept-2-en-3-ol,4,4,6-trimethyl-cyclohex-2-en-1-ol, acetic acid, 4-ethylcyclohex-1-ol, octanoic acid, and decanoic acid ethyl ester, respectively. Linoleic acid (C18:2) exhibited an extremely significant positive correlation with VFC31, VFC56, VFC32, VFC39, and VFC14 (\(p<0.01\)). The components comprised mainly aldehydes and alcohols. The products of lipoxygenase detected in oats were 2-Pentyfuran, 1-octen-3-ol, (E)-hept-2-enal, hexanal, and 2-heptanone. However, the action of oat lipoxygenase on linoleic acid produces mostly hexanal and 2-nonenal. Different processing methods alter the release of volatile compounds by affecting the correlation between factors involved in amino acid and fatty acid metabolism.  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Fatty Acid Composition** & \multicolumn{4}{c}{**Fatty Acid Composition (\% of Total Fatty Acids)**} \\  & **OB** & **S-OB** & **M-OB** & **HA-OB** \\ \hline Palmitic acid (C16:0) & 17.28 \(\pm\) 0.04 a  & 16.96 \(\pm\) 0.05 b  & 17.38 \(\pm\) 0.08 a  & 17.24 \(\pm\) 0.02 a  \\ Stearic acid (C18:0) & 1.60 \(\pm\) 0.01 b  & 1.60 \(\pm\) 0.01 b  & 1.65 \(\pm\) 0.01 a  & 1.63 \(\pm\) 0.01 ab  \\ Saturated fatty acid & 18.88 \(\pm\) 0.05 a  & 18.56 \(\pm\) 0.06 b  & 19.03 \(\pm\) 0.08 a  & 18.87 \(\pm\) 0.03 a  \\ Oleic acid (C18:1) & 46.98 \(\pm\) 0.15 a  & 45.97 \(\pm\) 0.04 b  & 46.49 \(\pm\) 0.15 a  & 46.58 \(\pm\) 0.13 a  \\ Linoleic acid (C18:2) & 31.38 \(\pm\) 0.14 b  & 32.69 \(\pm\) 0.11 a  & 31.65 \(\pm\) 0.07 b  & 31.76 \(\pm\) 0.16 b  \\ linoleic acids (C18:3) & 0.96 \(\pm\) 0.01 a  & 0.94 \(\pm\) 0.00 a  & 0.96 \(\pm\) 0.01 a  & 0.96 \(\pm\) 0.01 a  \\ Unsaturated fatty acid & 79.32 \(\pm\) 0.31 b  & 79.60 \(\pm\) 0.16 a  & 79.11 \(\pm\) 0.22 b  & 79.30 \(\pm\) 0.30 b  \\ \hline \end{tabular}
\end{table}
Table 4: Composition and content of fatty acids in oat bran after different pretreatments.  
Figure 4: Correlation heat map between fatty acids and flavor substances in pretreated oat bran. Red represents positive correlation, blue represents negative correlation, * represents \(p\) < 0.05, ** represents \(p\) < 0.01.
# 3D Gravity Inversion on Unstructured Grids
## 1 Introduction
Subsequently, two mechanisms of depth weighting are compared and analyzed in detail: (1) a regularization-based strategy: applying a depth weighting to the regularization term [9; 11; 14; 16]; and (2) gradient-based strategy: applying a depth weighting to the gradient of data misfit [21; 22]. The comparative analysis indicates that the second method would improve gravity depth resolution more directly and effectively, and this improvement is less influenced by regularization parameters. Moreover, the regularization terms will have a restraining effect at all depths. Besides, we develop an improved fuzzy c-means clustering method combined with spatial constraints. Compared with previous works [17; 18; 19; 20], it measures property distribution of inverted models in both the spatial domain and parameter domain, and it can provide a more continuous distribution of properties on unstructured grids. To demonstrate the effectiveness of our algorithm, we tested both on a synthetic and a field dataset from the Vinton salt dome by Bell Geospace. The forward modeling is accomplished with the algorithm of Okabe [4] based on unstructured grids, which has been used in gravity researches [17; 23; 24]. We use TetGen [25] to generate tetrahedral grids. TetGen is an open-source software that generates the tetrahedral and Voronoi grids as required. The algorithms of TetGen are Delaunay-based, which ensures high quality for the whole grids by maximizing the minimum dihedral angle in the grids. The results show that the problem in gravity inversion with the anomaly concentration to the surface is largely solved. The inverted models show sharp boundaries and true positions.