esa-sceva/satcom-chunk-collection huggingface dataset:
# Dynamic Monitoring of the Water Flowing Fractured Zone during the Mining Process under a River
## 2 Survey Area  
### Geological Conditions  
The Selian No. 1 coal mine lies in the Dongsheng District of Ordos, Inner Mongolia (39\({}^{\circ}\)53\({}^{\prime}\)52.85\({}^{\prime\prime}\) N, 109\({}^{\circ}\)52\({}^{\prime}\)37.49\({}^{\prime\prime}\) E). Characterized by a fluctuating surface, the terrain of this area is high in the north and low in the south (Figure 1). The gullies are widely developed in and around this area, and the rivers are seasonal. The recorded maximum flood peak of the around area is 2580 m\({}^{3}\)/h. The 8101 longwall face is the first longwall face in this coal mine in which the 2-2\({}^{1}\) coal seam is mined. The strike length and the inclined length of the 8101 longwall face are 1780 m and 280 m, respectively. The ground elevation is 1382-1442 m, and the floor elevation is 1250-1264 m. The average depth is approximately 170 m, and the thickness of the coal seam ranges from 2.5 to 5.0 m, with an average of 4.0 m. There is a river (dry at that time) passing through the surface of the 8101 longwall face, beneath which the buried depth of the 2-2\({}^{1}\) coal seam is approximately 125 m.  
The overburden strata are shown in Figure 2. There are four main aquifers: the Quaternary loose pore phreatic aquifer with low-medium water abundance and strong permeability, the K\({}_{\rm 1 zh}\) unconfined aquifer in the lower series of the Cretaceous with low-medium water abundance, the middle Jurassic clastic rock type aquifer with low water abundance and poor permeability, and the Yan'an formation clastic rock type confined aquifer of the middle-lower Jurassic with low water abundance. Therefore, the main aquifers that pose a threat to the extraction of the 8101 longwall face are the K\({}_{\rm 1 zh}\) unconfined aquifer and the middle Jurassic coarse sandstone aquifer. The K\({}_{\text{Lzh}}\) unconfined aquifer is closely related to the river and has strong transmissivity and storage capacity. The water level of the unconfined aquifer is greatly affected by climatic conditions and seasonal changes. The water level of this aquifer rises with the rainy spring and summer, and drops with the less rainy winter. Due to its high water transmissivity and lateral recharge capacity, the drop in water level in some areas will cause the water recharge from other areas of the aquifer. Therefore, in order to ensure the mining safety of 8101 longwall face, it is necessary to study the developmental mechanisms of the WFFZ.
## 2 Study Area and Datasets
### Determination of Input Remote Sensing Data
#### 2.2.3 Land Surface Albedo  
Land surface albedo was estimated as a linear combination of ASTER waveband reflectances. Due to deficient shortwave infrared channels since 2008, we computed the surface albedo only using the visible and near infrared channels according to the method proposed by [PERSON] (2000) [44]. The non-snow/ice surface albedo computation formulation was given as following:  
\[\alpha=0.0771\alpha_{1}+0.3652\alpha_{2}+0.4086\alpha_{3}+0.0178 \tag{6}\]  
where \(\alpha_{1}\), \(\alpha_{2}\) and \(\alpha_{3}\) are the surface albedos of the visible and near infrared channels, respectively. The ASTER broadband albedo showed good agreement with the ground observations for the 19 sites where the four-component radiometers were installed (Figure 2), with a mean bias (overestimate) of 0.004, a mean absolute percent difference of 2.6% and an RMSE value of 0.013. This result supports the use of the ASTER broadband albedo for the \(T\)-\(\alpha\) space method.
# Advanced Medical Image Segmentation Enhancement:
## 2 Related Works
### Particle Swarm Optimization (PSO) in Image Analysis  
Particle swarm optimization (PSO) has emerged as a versatile and innovative optimization technique, with applications spanning various domains, including image analysis [62; 63]. Initially conceived as an optimization method inspired by collective swarm behavior, PSO's adaptability, effectiveness, and problem-solving capabilities make it an increasingly influential tool in image analysis [64; 65]. Within the broader context of image analysis, PSO excels at tasks such as feature selection [66], image registration [67], image segmentation [68; 69; 70], and object tracking [71]. Its capacity to navigate complex search spaces and avoid local optima positions it as an attractive choice for researchers.  
In medical image analysis, our research takes a pioneering step by extending the application of PSO to the specific realm of medical image segmentation [59]. This strategic extension capitalizes on PSO's inherent strengths in exploring intricate search spaces: aligning seamlessly with the complexities often encountered in medical images, which are marked by noise, non-uniform illumination, and intricate structures [72]. Understanding the pivotal role of PSO in image analysis forms the cornerstone of our research, wherein weharness its unique optimization capabilities to refine and enhance the accuracy of medical image segmentation as outlined in \"AMISE: PSO-Based HE Approach\".
# Phase Center Corrections for BDS IGSO and MEO Satellites in IGb14 and IGSR3 Frame
## 1 Introduction
In this study, we aim firstly to evaluate whether the terrestrial scale derived from released BDS PCOs is consistent with that obtained by Galileo-released PCOs, and secondly, to obtain the PCO estimates for BDS in IGb14 and IGSR3 frame for preparing BDS for IGS repro3 and legacy analysis. The paper is organized as follows. Section 2 provides the basic information on the status of the BDS constellation as well as ground tracking stations. Section 3 describes the processing strategy, whereas results are presented and analyzed in Section 4. In Section 4, we also demonstrate how the station coordinates and the orbit consistency benefit from the satellite antenna PCO and PCV estimates. Finally, this contribution will be summarized in Section 5.
## 3 Results and Discussion  
As expected, a pure inoculation of _H. occidentalis_ did not result in a complete fermentation of the Muscaris must, as approximately 188 \(\pm\) 4 g/L of total sugar were still present at the end of the fermentation. Interestingly, only 4 g/L of fructose was utilized during the fermentation duration of 25 days by the pure inoculation of _H. occidentalis_. A previous study also showed _H. occidentalis_ had a higher consumption rate of glucose to fructose (in minimal media), but not to the same extent as shown here [30]. This could allude to strain heterogeneity regarding sugar preference. Based on the weight-loss curves (Figure 1), inoculation of _H. occidentalis_ had little to no effect on the fermentative behavior of the Revelacion wine yeast. This is in concurrence with other mixed-culture fermentations using _Hansenispora_ spp., where no noteworthy effect on the fermentative capability of _S. cerevisiae_ was observed [31]. With the analysis of the chemical composition of the Muscaris wine, clear differences were seen with the addition of _H. occidentalis_ (Tables 1-3). Table 1 shows the main parameters of the wines and, interestingly, an almost complete consumption of the malic acid was observed with the addition of _H. occidentalis_. A slight but significant increase in acetic acid levels was also measured--a feature of _Hansenispora_ additions. The modulations of these acid components could explain the significant deacidification of the wine. Table 2 shows the main aroma constituents of the wines. A three-fold increase in ethyl acetate was observed with the addition of _H. occidentalis_, which is 25-times more than its odor threshold of 12.3 mg/L, as determined in red wines [27]. The fruity esters, namely isoamyl acetate and active amyl acetate, were higher in the \(H\). _occidentalis_-initiated samples, yet their amounts are below the significance threshold of the _t_-test, likely due to a large variance in the measured concentrations. As with \(H\). _osmophila_ and \(H\). _vineae_-initiated fermentations, an increase in 2-phenylethyled acetate was measured. An interesting observation was the two-fold increase in the ethyl ester ethyl propionate, an aroma compound imparting a pineapple-like aroma, although none of the other ethyl esters were significantly improved. \begin{table}
\begin{tabular}{c c c c c} \hline
**Parameter** & **Sc** & **Ho + Sc** & _p-Value_1  
Muscaris is a fungal-resistant white grape variety relative of the Muscat family of grapes known to be rich in terpenes. As all members of the _Hanseniuspora_ genus are capable of growing on cellobiose [32], suggestive of \(\beta\)-glucosidase action, their use in a terpenerich must could enable more release of terpenes bound to sugar moieties. The addition of _H. occidentalis_ did lead to a significant increase of both species of rose-oxide (Table 3), but no other terpen were meaningfully affected. Whether the increase in rose-oxide was caused by releasing action or by the modification of non-sugar precursors remains unclear [33].
## 2 Theoretical Background
### VR and Impact on Learning  
Previous studies have highlighted VR's positive effects on the teaching and learning experience, including increased learning and problem-solving abilities [35]. VR has also been shown to enhance the learning experience in dentistry classes and support proper positioning in physical exercises [34; 58]. Additionally, it has been found to improve understanding of flat and three-dimensional geometric figures [59] and foster greater creativity in elementary school students [60]. Specifically in engineering education, VR has shown positive learning outcomes compared to traditional teaching methods. Such outcomes include an increased understanding of automation [61], a focus on visualizing projects and systems [62], improved learning in software engineering development training compared to traditional methods [63], and greater understanding in classes on mechanical testing [64]. Specifically for engineering software development, VR may lead to more than 100% improvement in learning [65].  
Conversely, certain studies indicate that VR may have a less significant impact on student learning, particularly in areas related to product development [25]. However, in the field of robotics, the findings suggest a greater understanding of certain topics when VR is utilized [26]. While VR is commonly employed in educational settings with various learning outcomes, there are instances where the results are not optimistic. Various studies have evaluated the impact of knowledge retention, although to a lesser extent and with varying results. For example, in laparoscopy surgery training, no differences in skills and knowledge were observed between groups using traditional teaching methods versus VR support after one month [66]. However, there are conflicting findings, with one study showing significant retention of learning by children [67], while another study found that students using VR achieved 80% retention compared to 25% retention for those using traditional teaching methods [68].
## 2 Materials and Methods
### Meshing  
The impeller utilized in this study contains 24 blades and the vanned-diffuser consists of 19 vanes. Only one single passage of the impeller and the vanned-diffuser is meshed by a multi-block structured grid using conjunct blocks. We employed a multi-block structured mesh with an O4H topology scheme. The grid independency was examined by the co-authors in this present study [26]. The mesh with 998,994 nodes was built for a final grid of the compressor, which is represented in Figure 7. The impeller and the diffuser separately contain 559,680 and 439,314 nodes, respectively. The number of grid points in the streamwise, spanwise and pitchwise direction is 118, 73 and 43 nodes for the impeller as well as 74, 73, 74 nodes for the diffuser, respectively. The maximum expansion ratio in the impeller and diffuser is below 3, while the minimum skewness angles are \(16.8^{\circ}\) and \(37.1^{\circ}\), respectively. All the tip clearance through the compressor passages is set as 5.6% of exit blade height. This value of the tip clearance leads to a small scalar averaged y+ for the whole compressor. The small scalar averaged y+ is set to have adequate boundary layer resolution for the Spalart-Allamaras (SA) model. Figure 8 shows that y+ is around 1.6, with the maximum value below 10 for all the solid walls at the design and off-design conditions. This is acceptable for the Spalart-Allamaras model to obtain valid conclusions. The mesh size and topology are all the same for all studied cases in this present work. The same meshing is used for unsteady simulations.  
Figure 7: Single passage mesh: (**a**) Impeller part; (**b**) Diffuser part.
# A Maximum-Entropy Fuzzy Clustering Approach for Cancer Detection When Data Are Uncertain
## 3 Model and Algorithm
### Entropy-Based Fuzzy Clustering Algorithm  
In the following, we show the algorithm for the EFC-ID model. Fixed \(p\) (_degree of fuzzy entropy_), \(k\) (the number of clusters) and \(maxiter\) (the maximum number of iterations), and set iter = 0, the EFC-ID Algorithm 1 is composed of the following steps:  
```
1:Randomly generate the membership matrix \(\mathbf{U}^{iter}\) subject to constraints shown in (4);
2:iter = iter+1
3:Given \(\mathbf{U}^{iter-1}\), compute the centroids for the centers and radii \(\mathbf{C}^{iter-1}\) and \(\mathbf{R}^{iter-1}\);
4:Compute \(w^{iter-1}\) according Equation (12);
5:Update the membership matrix \(\mathbf{U}^{iter}\) according Equation (11);
6:if\(\|\mathbf{U}^{iter}-\mathbf{U}^{iter-1}\|>e\) & iter \(<\) maxiter ;
7:go to step 2.
8:else
9:exit loop.
10:Return: the membership matrix \(\mathbf{U}\), the centroids for the centers and radii \(\mathbf{C}\) and \(\mathbf{R}\), the weight \(w\), the number of iteration iter.
```  
**Algorithm 1** Entropy-based fuzzy clustering algorithm.  
Notice that, given the constraints on \(\mathbf{U}\), the algorithm can be expected to be rather sensitive to _local optima_. For this reason, it is recommended the use of some randomly started runs to find the best solution.
## 2 Electronic Band Structure
More specifically, the analysis of the orbital content of the set of bands containing the first four conduction bands and the first seven valence bands, which cover an energy window from \(-7\) to 5 eV around the Fermi level, approximately, reveals that these bands are dominated by the five \(4d\) (\(5d\)) orbitals of the metal Mo (\(W\)) and the six (three for each layer) \(3p\) (\(4p\)) orbitals of the chalcogen S (Se), totaling to up to 93% of the total orbital weight [35]. Single-layer TMDs are direct gap semiconductors, with the gap located at the two inequivalent K and K' points of the Brillouin zone (Figure 3). The main orbital character at the edge of the valence band is due to a combination of \(d_{x^{2}-y^{2}}\) and \(d_{xy}\) orbitals of the metal \(M\), which hybridize with \(p_{x}\) and \(p_{y}\) orbitals of the chalcogen \(X\). On the other hand, the edge of the conduction band is formed by \(d_{3z^{2}-r^{2}}\) orbital of \(M\), plus some contribution of \(p_{x}\) and \(p_{y}\) orbitals of \(X\)[35]. Contrary to single-layer samples, multi-layer compounds are indirect gap semiconductors. The edge of the valence band lies at the \(\Gamma\) point of the BZ, having a major contribution from \(d_{3z^{2}-r^{2}}\) and \(p_{z}\) orbitals of \(M\) and \(X\) atoms, respectively. The edge of the conduction band in multi-layer samples is placed at the Q point of the BZ. It is important to notice that the Q point is not a high symmetry point of the Brillouin zone, and therefore its exact position depends on the number of layers and on the specific compound. The orbital character at the Q point originates mainly from the \(d_{xy}\) and \(d_{x^{2}-y^{2}}\) orbitals of the metal \(M\), plus \(p_{x}\) and \(p_{y}\) orbitals of the chalcogen \(X\), plus a non negligible contribution of \(p_{z}\) and \(d_{3z^{2}-r^{2}}\) of \(X\) and \(M\) atoms, respectively. Figures 4 and 5 and Figures 11-13 represent these relative orbital weights in detail for the different compounds. The extremely rich orbital contribution to the relevant bands that occur in semiconducting TMDs complicates the derivation of a minimal TB model, valid in the whole  
Figure 2: Two-dimensional Brillouin zone (BZ) of \(MX_{2}\). The high symmetry points \(\Gamma=(0,0)\), \(\text{K}=4\pi/3a(1,0)\) and M\(=4\pi/3a(0,\sqrt{3}/2)\) are shown. The Q points (which are not high symmetry points) indicate the position of the edges of the conduction band in multi-layer samples. Brillouin zone. Another important feature of TMDs is that they present a strong SOC, which leads to a large splitting of the valence band at the K and K' points of the BZ (see Figure 3). The splitting is bigger for W than for Mo compounds, due to the heavier mass of the former. SOC also leads to a splitting of the conduction band at the K point, as well as at the minimum at the Q point [37; 48]. Figure 3: Electronic band structure of single-layer \(MX_{2}\) from Density Functional Theory (DFT) calculations (**black** lines) and from tight-binding (TB) (**red** lines).
## 4 Body-to-Body Communication and Connectivity
### Impact of Routing Protocols on Connectivity  
In BBN networks, implemented routing protocols refer to various classes. Indeed, recent research tends to evaluate and implement ad hoc routing networks: proactive, reactive, geographic-based and gradient-based [6] in BBN communications. Moreover, context-aware protocols were proposed with regards to the implementation context (i.e, health-care, emergency, operational assistance, military, etc.). Routing protocols consist of the mechanisms that carry data from source to destination which have key role in BBN connectivity. Indeed, routing decisions are based on certain metrics depending on the use case. With regards to the study and experiments conducted by [PERSON] et. al in [37], it is claimed that connectivity depends on the networking model (unicast, multicast or broadcast). Ad hoc networks, implemented in the disaster context application, use broadcast for neighbor discovery, and unicast/multicast for routing data. Based on our recent experiment [12], the network performance increases with the accurate end-to-end link quality estimations and real link conditions.
# Study on Frost Resistance of the Carbon-Fiber-Reinforced Concrete
## 3 Results and Discussion
### Effect of Carbon Fiber Content on Compressive Strength
A large number of fibers would be evenly distributed in the concrete as the fine reinforcement, which could effectively share the tensile stress of the concrete resulting from the deformation, and it could also effectively constrain the shrinkage of the concrete and reduce the number and scale of the cracks in the concrete, thus improving the performance of the concrete in all aspects [22; 23; 24]. However, fibers induce interface defects into the composite material, and these defects have a harmful impact on the mechanical properties of concrete [2]. The influence of fibers on the crack propagation in concrete is controlled by factors such as the fiber amount, fiber distance, drawing strength, interfacial bonds between the fiber and the matrix material, and the strength of the matrix [25; 26]. Of these, the interfacial bonding between the fibers and the cement matrix is the most important influencing factor [25; 26]. Carbon fibers, as a kind of ductile material, are combined to a concrete matrix by mainly bond forces. Given that stress is transmitted through the interfacial transition zone (ITZ) between the fibers and the matrix, the structure and properties of the ITZ are the key points that determine the performance of a CFRC. According to the research of [PERSON] [18], the increase in the solid volume caused by cement hydration is about 1.13, and the pore around the fiber is about 2.5 times that of the cement matrix. Thus, the ITZ near a fiber surface will have a high porosity, lower hardness, low strength, and more defects [27; 28; 29; 30]. When the fiber content is increased, the induction of cracks by the ITZ will be more evident, which will lead to a reduction in the reinforcement effect of the fibers on the concrete, and even a negative effect can appear [31; 32; 33]. As long as the fiber orientation is inconsistent with the direction of the principal stress, cracks will be induced, thus affecting the overall mechanical behavior of the concrete [34; 35; 36]. Figure 4: Effect of carbon fiber content on the compressive strength. CF, carbon fiber; PC, plain concrete. As shown in this study, at first the fiber content was not sufficient to resist plastic shrinkage, and more weak planes were introduced into the concrete, so the compressive strength of CFRC was reduced. When the carbon fiber content increased, a large number of plastic deformation cracks that formed in the concrete were eliminated, and the positive effect was greater than the introduced weak area. Moreover, the effect of preventing and bridging makes the compressive strength of the concrete increase rapidly, showing an approximately linear strength growth. With the increase in the fiber content, the pores and weak plane reduced the strength significantly. As a result, the compressive strength stopped increasing and even declined.
## 3 System Description
### Combined Total Flow and Single Flash (TF-SF) System  
As described above, the total-flow turbine with curved nozzle is able to accomplish both the flashing and power generating tasks, it is designed to be coupled with the single flash system by replacing the flashing process. Further, in comparison with previous geothermal energy usage, instead of directly reinjecting the condensed water to geothermal reservoirs or discharging it to the environment in the form of co-produced brine and/or uncondensed steam, the desalinized freshwater during condensation is wholly recovered in the proposed three systems.  
The proposed geothermally sourced combined power and freshwater generation TF-SF system is configured and shown in the left half of Figure 2, and corresponding temperature-entropy diagrams of the system are is shown in the right half of Figure 2. Firstly, the wellhead geofluid is introduced to the total-flow turbine for two phase expansion (point 1-point 2). Secondly, the vapor (point 3) and liquid (point 4) at the outlet of total-flow turbine is separated, and the vapor is introduced into the steam turbine of the original single-flash system to go through the second stage expansion (point 4-point 5). Finally, the whole fluid at turbine outlet of point 5 will be fully condensed (point 5-point 6) and recovered as freshwater because no other chemicals are contained.  
Figure 2: Configurations and temperature-entropy diagrams of TF-SF system.