esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Preparations of the SC Ni-Mn-Ga/Polymer Composites
#### 2.4.3 Integration of Polymer Matrix and SC Ni-Mn-Ga Particles  
In the previous Sections 2.4.1 and 2.4.2, the polymers were synthesized as control specimens without the integration of the SC Ni-Mn-Ga alloys (i.e., pure polymers of epoxy and silicone). In this section, the processes for the integration of the SC Ni-Mn-Ga alloy and polymer for the fabrications of the SC Ni-Mn-Ga particles/polymer composites are described in detail.  
The SC Ni-Mn-Ga particles described in Section 2.3.1 were used as the fillers for fabricating the SC Ni-Mn-Ga particles/epoxy composites. The semi-liquid slurry of the precursor of the epoxy and hardener was mixed with the SC Ni-Mn-Ga particles in different volume percentages. In the preliminary trial, one relatively large SC Ni-Mn-Ga particle was integrated with the epoxy. The specimen is denoted as a \"one-particle/epoxy composite\", unless otherwise mentioned. Following the preliminary trial, further composites with various volume percentages (e.g., 10 and 40 vol.%) of the SC Ni-Mn-Ga particles were prepared. Please note that the volume percentage (vol.%) is described with respect to the SC Ni-Mn-Ga alloy here. The well-mixed composites were then thermally cured at RT for 24 h in an acrylic mold, with a process similar to those described in Section 2.4.1.  
Other than the aforementioned composites, the SC Ni-Mn-Ga particles described in Section 2.3.1 were also used as the fillers to fabricate a specimen of the SC Ni-Mn-Ga particles/silicone composite. The semi-liquid slurry of the precursor of the silicone rubber and hardener was mixed with the SC Ni-Mn-Ga particles in different volume percentages (i.e., 10, 20, and 40 vol.%). The composites were then thermally cured at RT for 24 h in an acrylic mold, with a process similar to those described in Section 2.4.2.  
The composites, which were prepared by integrating SC Ni-Mn-Ga particles and two different polymers (i.e., epoxy and silicone), are summarized in Table 1. In addition, the fundamental physical properties of the polymers used are also listed in Table 1.  
\begin{table}
\begin{tabular}{c c c} \hline \hline \multicolumn{1}{c}{**(a) Composites Prepared in This Study**} & **Epoxy** & **Silicone** \\ \hline \multicolumn{3}{c}{One particle} & 10 \\ Volume percentages of Ni-Mn-Ga particles (vol.\%) & 10 & 20 \\ \multicolumn{3}{c}{40} & 40 \\ \multicolumn{3}{c}{**(b) Physical Properties of Two Polymers**} & **Epoxy** & **Silicone** \\ \multicolumn{3}{c}{Density, \(\rho\) (g cm\({}^{-3}\))} & 1.10 & 1.27 \\ Young’s modulus, \(E\) (MPa) & 200–800 & 2–4 \\ Flow stress, \(\sigma\) (MPa) & 15–40 & \textless{}3 MPa \\ \hline \hline \end{tabular}
\end{table}
Table 1: (a) Composites of SC Ni-Mn-Ga particles/polymer prepared in this study and the (b) fundamental physical properties of the polymers (i.e., epoxy and silicone) used in this work.
## 1 Introduction
Other topology for the modular structure of the MPC has been proposed in Reference [34] that implements a sub-modules of a fully isolated MPC as a building block for the modular converter to enable decentralized PV/battery strings. However, it requires a large number of semiconductor switches/diodes per each sub-module that causes the power converter to be very complex. In this paper, a new multiport converter topology for interfacing PVs and batteries has been developed. The developed topology has been used as a sub-module to build a new modular multiport converter (MMPC) which removes the need for high voltage strings of PV/batteries with their related problems. It also reduces the power rating and voltage stress of the power electronics that may enhance the overall system efficiency. One of the most important merits of the propose topology is that it can perform battery charge balancing for a wide range of battery module imbalances. This is of particular interest when employing second-life batteries (SLB) which are receiving considerable attention [35; 36; 37]. The paper is organised as follows: the system level analysis of the proposed converter is presented in Section 2; the topology of the scalable power module design is discussed in Section 3; then, operation of the proposed converter is discussed in Section 4 and experimental results to verify the operation of the converter is presented in Section 5; finally, Section 6 concludes the main points of this paper.
# Ball Tracking Based on Multiscale Feature Enhancement and Cooperative Trajectory Matching
## 4 Experiments  
### Data Set and Evaluation  
#### 4.1.1 SportsTrack  
There is currently no public sports competition broadcast video data set, including basketball, soccer, or volleyball, that specifically contains object ball detection and tracking. We used a small-scale manual annotation method to build a relatively high-quality object tracking data set containing soccer, basketball, and volleyball competition broadcast videos as a supplement to the research data. The self-built data set is named SportsTrack. The competition videos used for annotation are all from professional public competition broadcast videos. On the premise of complying with the rules of video use and dissemination, 4K ultra-high-definition soccer competition videos and 1080 p high-definition basketball and volleyball competition videos were selected and downloaded as source videos. Several clips from long-range shots were intercepted from the original video; each clip was no longer than 15 s, and the complex conditions of detection and tracking were fully taken into account to increase the difficulty of the task and finally formed a video with multiple resolutions and high image quality, creating a relatively high-precision ball object tracking data set covering three sports scenes: soccer, basketball, and volleyball. It can be used for the detection and tracking tasks of soccer, basketball, and volleyball at the same time. The relevant parameter information of the self-built data set SportsTrack is shown in Table 1. Soccer has a corresponding 4K version, and basketball and volleyball have corresponding 1080 p versions.  
Compared with other sports-related tracking data sets, our self-built data set SportsTrack has the following three advantages:  
1. [leftmargin=*]
2. Contains multiple types of resolutions and higher resolutions. Soccer videos have larger stadiums, farther objects from the shooting camera, and smaller objects. The resolution of the collected competition broadcast videos reaches 4K, which can provide richer detailed information;
3. Covers multiple complex sports scenes. Our data set contains three important team ball sports: soccer, basketball, and volleyball. Compared with other previous object tracking data set scenarios, the movement form and background information of the object in the video are more complex;  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Object** & **Train** & **Test** & **Frame** & **GT** & **Pixel** & **FPS** \\ \hline Soccer & 2164 & 1196 & 3360 & 3282 & 1280 \(\times\) 720 & 30 \\ Basketball & 2196 & 1464 & 3660 & 3498 & 1280 \(\times\) 720 & 30 \\ Volleyball & 2160 & 1400 & 3600 & 3520 & 1280 \(\times\) 720 & 30 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Self-built data set SportsTrack.  
The annotation information comes from manual annotation and has undergone secondary manual quality inspection, so the annotation accuracy is high.
# STN-Homography: Direct Estimation of Homography Parameters for Image Pairs
## 5 Sequence STN-Homography  
Although the proposed hierarchical STN-homography model yields a very small mean corner error, the training of a multistage hierarchical STN-Homography model is not an end-to-end training and relies on image_a when the training or testing is conducted (image_a was warped using the prediction result of the current stage to generate image_a warp and patch_a for next stage). In this section, we proposed sequence STN-homography model that (a) can be trained in an end-to-end manner and (b) does not rely on image_a when the training or testing is conducted, i.e., sequential STN-homography takes the input image pair of patch_a and patch_b, and directly outputs the final predicted results of the homography matrix values between patch_a and patch_b (the homography matrix between image_a and image_b is the same as the homography matrix between patch_a and patch_b).
# Extraction, Characterization, and Applications of Pectins from Plant By-Products
## 3 Pectin Extraction Methods
### Traditional Methods for the Pectin Extraction
Time and temperature have a destructive effect on the plant cell wall. As a result, they facilitate solvent diffusion and pectin extraction. In the extraction process, high temperature allows the solubilization of pectins and increases the yields [46]. However, pectin extraction at very high temperatures has been related to the hydrolysis of pectin into short chains which are not precipitated by ethanol, affecting the yields [47]. High temperatures also reduce the degree of esterification of pectin [27]. From the perspective of the extraction time, it should be enough for the solvent to dissolve a sufficient amount of the target component since the extraction occurs until equilibrium is reached. On the other hand, a long extraction time can cause pectin degradation [34]. Therefore, to achieve the desired conditions, the extraction temperature and time have to be optimized [48]. The solid/liquid ratio is usually maintained between 1:10 and 1:50 for pectin extraction. When this ratio is less than 1:10, it leads to low pectin yields because the amount of solvent is not enough to dissolve and extract the pectin. An increase is found in the solid-liquid ratio (up to 1:30 \(m/v\)) increments regarding the pectin yield due to the rise in dissolution capacity. Pectin extraction yield increases following an increase in the solid to liquid ratio through an increase in the dissolution capacity [27; 34]. The surface area of the material and agitation are also effective in the pectin extraction process. Table 1 summarizes the different extraction conditions in the conventional extraction method.
# Integrated Precise Orbit Determination of Multi-Gnss and Large LEO Constellations
## 4 Result Analysis and Discussion
### Integrated POD with Full LEO Constellation
#### 4.1.1 Integrated POD with Different Numbers of LEO
Figure 6: Average 3D RMS values of BDS orbit differences for the integrated POD with different numbers of LEO satellites.
# A Study on the Roof-Cutting and Pressure Releasing Technology of Roof Blasting
###### Abstract  
The surrounding rock during a coal mine excavation is prone to significant engineering disasters such as considerable deformation and rock bursts. Pressure release can improve the stress field of a deep rock mass and prevent the occurrence of dangers such as roadway collapse and coal and gas outbursts. This paper uses the ANSYS 19.0/LS-DYNA finite element software to simulate the crush area and fracture zone of a detonation charge with different diameters under in situ stress. The stability of the surrounding rock was analyzed based on the impact stress and velocity, and was verified by field tests. The research results show that the blasting load primarily affects the damaged area near the borehole, while the in situ stress affects far-field crack propagation. The crack propagates in the direction of high surrounding rock pressure. When the uncoupling index is 1.5, the impact pressure of a 60 mm diameter cartridge is eight times that of a 20 mm diameter cartridge. The impact speed can reach two times that of the 20 mm diameter cartridge. The high-energy event at the roof is transferred to the front of the working face, the distribution is no longer concentrated, and a better pressure-relief blasting effect is achieved. The research results can help guide the prevention and control measures of rock bursts and other mining disasters.  
roof-cutting blasting; pressure-relief blasting; deep rock mass; rock burst; fracture zone
## 6 Experiments on SBS Mitigation and Parametric Amplification with a DOF  
In this section we aim at evaluating the performance of a DOF as a parametric amplifier, in terms of its SBS threshold as well as its conversion efficiency (CE). We compare the DOF's performance with a standard highly nonlinear fiber (HNLF) with a constant longitudinal dispersion profile.
# Development of Practical Design Approaches for Water Distribution Systems
## 2 Practical Design of Water Distribution Systems
### Multi-Objective Optimization Framework for Water Distribution Systems Design
#### 2.2.1 Objective Functions  
The objective of the first objective function in WDSs design is to minimize construction cost. The cost-estimation equation for network design proposed by [PERSON] and [PERSON] [18] is applied. This cost can be estimated by multiplying the cost of each commercial pipe diameter by the length of each pipe. Therefore, the sum of the cost of all pipes in the network is given by Equation (1).  
\begin{table}
\begin{tabular}{c c c} \hline \hline  & **Existing Pipe Size Continuity** & **Pipe Size Continuity Search** \\  & **Search Algorithm [10]** & **Algorithm of This Study** \\ \hline Ability to handle complex joint point & X & O \\ \hline Alleviation of calculation time & X & O \\ \hline Overlapping part of search process & O & X \\ \hline \hline \end{tabular}
\end{table}
Table 1: Functional difference between existing method and proposed method.  
Figure 3: Pipe continuity approach for water distribution systems (WDSs) design.  
\[\textit{Construction Cost}=\sum_{i=1}^{PN}C(D_{i})L_{i}+\textit{Penalty} \tag{1}\]  
where _C(D\({}_{i}\))_ is the cost function of the _i_-th pipe per unit length (m) of each pipe diameter, and _L\({}_{i}\)_ is the length (m) of the _i_-th pipe. _D\({}_{i}\)_ is the pipe diameter (mm) of the _i_-th pipe. _PN_ is the total number of pipes. _Penalty_ represents the penalty function; if the solution cannot satisfy for the constraints, the penalty function is applied.  
The secondary objective function represents system resilience [19], which defines the system's capability to create foresight, recognize, anticipate, and defend against changing risks, before adverse consequences occur. Various resilience indicators have been proposed after such an indicator was first developed by [PERSON] [19]. It was expressed as a surrogate measure for hydraulic benefits. The index is based on the concept that the total input power into a network consists of the power dissipated in the network and the power delivered at demand nodes. Moreover, less power consumed internally to overcome friction results in more surplus power at demand nodes; therefore, it has the ability to counter failure conditions. The system resilience index calculated by Equation (2) was in the range from 0 to 1, where a higher index value indicates better resilience.  
\[\text{System Resilience}=\frac{\sum_{j=1}^{N}q_{j}\Big{(}h_{j}-h_{j}^{*}\Big{)}} {\sum_{k=1}^{NR}Q_{k}H_{K}+\sum_{i=1}^{NP}Pu_{i}-\sum_{j=1}^{N}q_{j}h_{j}^{*}}+ \textit{Penalty} \tag{2}\]  
where \(N\), _NR_, and _NP_ are the number of nodes, reservoirs, and pumps, respectively, _h\({}_{j}\)_ is a head at node \(j\), _h\({}_{j}^{*}\)_ is the minimum required head at node \(j\), _H\({}_{K}\)_ is the water level of reservoir \(K\), _Q\({}_{K}\)_ is water flow of reservoir \(K\), and _Pu\({}_{i}\)_ is the power of pump \(i\).
# Risk Causal Analysis of Traffic-Intensive Waters Based on Infectious Disease Dynamics
## 2 Methodology
### Screening of Risk Factors in Traffic-Intensive Waters  
#### 2.2.1 Traffic-Intensive Waters  
Waterborne traffic accidents are characterized by suddenness, randomness, and uncertainty [36]. Ship navigation accidents occur frequently, which is affected by the coupling effect of multiple factors. Therefore, analyzing the characteristics of traffic flow in traffic-intensive waters and identifying the key vulnerability factors affecting the navigation system are conducive to deep-level mining of the causes of navigation system accidents. At present, there is no clear definition of the concept of traffic-intensive waters. It usually refers to the water areas with a large ratio of ship traffic flow to the navigation capacity (saturation) of the channel, including fishing areas, inland river dam areas, intersecting waters, narrow sections, canal sections, and so on. The navigation system in traffic-intensive waters mainly includes the following characteristics:  
1. High traffic flow and density. This will increase the uncertainties of collision avoidance action of ships in crossing situation, and thus lead to a relatively higher collision risk [37; 38].
2. When affected by external factors such as meteorological parameters and hydrological parameters, the possibility of accidents is relatively high [39].
3. When vessels are sailing in traffic-intensive waters, officer of the watch's duties and skills are demanded higher [39; 40].
4. The ship's front and rear spacing is small, and the shipping line is intricate. Hence, the ship management requirements are higher [39; 41].
# A Simple Model to Predict Machined Depth and Surface Profile for Picosecond Laser Surface Texturing
## 2 Modeling of LST and Experimental Procedures
### Modeling of LST Process  
A rectangular raster trajectory was used to fabricate micro-channels, as shown in Figure 1. A single-channel is initially created with a certain scanning speed and laser frequency. Subsequently, single-channels are overlapped by shifting a small interval to form a multi-pass micro-channel. This pattern is overscanned layer by layer to create the final micro-channel with desired depth.  
During LST process, the scanning speed and frequency determine the laser pulse center along the longitudinal direction, while the adjacent interval determines the laser pulse center along the transverse direction. In order to predict the machined depth of LST, a fine mesh is developed with dimensions slightly larger than the length and width of the created micro-channel. The depth at each mesh point is calculated using a summation of all the depths created by each individual pulse at this location, expressed as:  
\[D(x,y)=\sum_{i=1}^{m}\sum_{j=1}^{n}D_{\text{max}}(N)e^{-k(\frac{(x-x_{i})^{2}+ (y-y_{i})^{2}}{w_{0}^{2}})} \tag{4}\]  
where \(m\) and \(n\) are the number of increments in the longitudinal and transverse directions at point \((x,y)\) and \((x_{i},y_{i})\) is the laser pulse center determined by the scanning speed, frequency and adjacent interval.
# Predicting the Gap in the Day-Ahead and Real-Time Market Prices Leveraging Exogenous Weather Data
## 5 Simulation Results  
### Feature Importance  
LASSO, SVR, and Random Forest algorithms can not inherently capture temporal dependencies for sequential data; that is why day-ahead prices for a previous 48 h time horizon are added as features. Therefore, 48 new columns are created that contain the delayed values of the DAM LMP. Similarly, lagged real-time and gap values are added to the existing dataset; however, for the RTM, the most recent prices that are available are at \(t-12\) h. Consequently, only those features that are realistically available for the RTM are taken into consideration.  
In this section, the RF algorithm is procured to select the most important features. Since the RF method employs decision trees, it can be leveraged for feature selection. The RF naturally ranks by how well each decision tree improves the purity of the node. The Gini index of decision tree algorithms is leveraged to procure feature importance values. For example, the greatest decrease in impurity happens at the root of the tree, while the least decrease in impurity happens at the leaves of the tree. Consequently, pruning the tree below a particular node creates a subset of the most relevant features. In comparison to PCA, the above-described algorithm captures the non-linear dependencies of the features, while PCA only captures linear relationships between features. Table 2 presents the selected features, ranked by their importance for predictions of the price gap between the two markets. The RF algorithm renders 204 features useful for gap prediction. Note that the 13 most relevant features are shown in Table 2. The right column of Table 2 represents the importance coefficient. The importance coefficient is scaled so that the sum of all the importance coefficients is 100. It is interesting that the external features that are collected demonstrated a significant effect on predicting the price gap between the two markets. For example, the solar zenith angle has an importance coefficient of 1.0, while the DHI contributes to the prediction with a 0.39 importance score.
###### Abstract  
A satellite formation operating in low-altitude orbits is subject to perturbations associated to the higher-order harmonics of the gravitational field, which cause a degradation of the formation configurations designed based on the unperturbed model of the Hill-Clohessy-Wiltshire equations. To compensate for these effects, periodic reconfiguration maneuvers are necessary, requiring the prior allocation of a propellant mass budget and, eventually, the use of resources from the ground segment, having a non-negligible impact on the complexity and cost of the mission. Using the Hamiltonian formalism and canonical transformations, a model is developed that allows designing configurations for formation flying invariant with respect to the zonal harmonic perturbation. \(J_{n}\) invariant configurations can be characterized, selecting the drift rate (or boundedness condition) and the amplitude of the oscillations, based on four parameters which can be easily converted in position and velocity components for the satellites of the formation. From this model, a guidance strategy is developed to inject a satellite approaching another spacecraft into a bounded relative trajectory about it and the optimal time for the maneuver, minimizing the total \(\Delta V\), is identified. The effectiveness of the model and of the guidance strategy is verified on some scenarios of interest for formations operating in a sun-synchronous and a medium-inclination low Earth orbit and a medium-inclination lunar orbit.  
formation flying invariant configuration; zonal harmonic perturbation +
Footnote †: journal: Applied Physics Letters