esa-sceva/satcom-chunk-collection huggingface dataset:
# Extension of DBSCAN in Online Clustering: An Approach Based on Three-Layer Granular Models
## 4 Methodology of the Proposed Three-Layer Granule Models
### Granulating in the Input Space
#### 4.1.2 Determination of the Granule Size  
Generally, IGs are designed as hyperrectangles in the high-dimensional input space [16]. Expanding around a selected prototype, \(z_{i}\), the corresponding granule in the input space could be built as a hyperrectangle, \(B_{hi}=[I_{hi},\,\mathbf{u}_{hi}]\). Considering that all data are normalized, the constraint of boundary is also satisfied, namely \(I,\,\mathbf{u}\in[0,1]^{n}\).  
Data points are partitioned into different granules by membership matrix, but the obtained information granules are fuzzy. Therefore, the performance of granule construction will be directly affected by the size of the granules. In general, two indicators can be proposed to construct and evaluate IG's performance: coverage and specificity [22].  
Coverage is an indicator representing the amount of data points covered in an IG, so it can be simply defined as below:  
\[Cov=\frac{1}{N}\sum\limits_{k=1}^{N}incl\left(t_{k}\in\gamma_{k}\right) \tag{6}\]where \(Y_{k}\) represents the cluster; \(t_{k}\) is the output; and _incl_(*) is a Boolean function. When \(t_{k}\in Y_{k}\), the value of _incl_(*) is \(1\).  
Specificity is the other indicator. Generally, it requires a high value when the granule size is small. Therefore, we can define a simple function as below:  
\[Spe=\frac{1}{N}\sum_{k=1}^{N}\exp(-\alpha*size(Y_{k})) \tag{7}\]  
where _scale_(\(Y_{k}\)) is the IG size; _exp_(*) is a selected function expressing the negative correlation between IG size and specificity, and \(\alpha\) is a slope control factor. For example, information granules are designed as hyperrectangles in this paper, and the selected points are prototypes. Thus, the size of the information granules could be decided by a vector, \(S\), as shown in (8):  
\[S=[\epsilon_{1}^{+},\epsilon_{1}^{-},\epsilon_{2}^{+},\epsilon_{2}^{-},\cdots,\epsilon_{n}^{+},\epsilon_{n}^{-}] \tag{8}\]  
where \(\epsilon_{i}^{+}\) and \(\epsilon_{i}^{-}\) are the distances of \(z\) to the upper bounder, \(u_{i}\), and lower bounder, \(l_{i}\), respectively.  
For example, a two-dimensional granule is shown in Figure 3a. A good information granule usually requires high coverage and high specificity. However, there exists a conflict to reach the highest values of both the indicators, as shown in Figure 3b.  
In order to address this multi-objective problem, an alternative design is to consider a product of these two indicators, defined in (9):  
\[V(S)=Cov*Spe \tag{9}\]  
where \(V(S)\) is defined as a new indicator determining the granule size, \(S\).
## 4 Working Mechanism of ESRVR
### Data Transmission and Void-Hole Detection and Mitigation
#### 4.3.4 Holding Time  
In the scenario when a source node is completely neighborless and has data packets or when a sensor node just receives packets from other nodes, the packets are held for a unique time known as holding time, which is computed as:  
\[T_{H}=D\frac{\left(\frac{P}{P_{i}}\right)}{N_{b}v} \tag{1}\]  
where \(D\), \(\frac{P_{i}}{P_{i}}\), and \(N_{b}\) represent the depth in meters, current to initial power ratio of the battery, and number of packets in the buffer of the node that holds the packet, respectively. The acoustic speed in water is \(v\) in meters per second. The above relation shows that nodes with a low depth hold the packets for a short time, which avoids congestion of packets with such nodes because these nodes are close to the water surface (low depth) and, therefore, enhances reliable information advancement to the sea surface. Similarly, a node for which the ratio \(\frac{P_{i}}{P_{i}}\) is smaller has low power left in the battery. Therefore, such a node holds the packet for a short time interval so that it may further transfer the packet before it completely drains its battery. The ratio \(\frac{P_{i}}{P_{i}}\) is initially unity when the current power and the initial power both are the same and nodes have not yet started operation. As time passes and nodes start their operation, the current power left in the battery decreases from the original initial amount in the battery, and therefore, the ratio \(\frac{P_{i}}{P_{i}}\) decreases and becomes zero when no power is left in the battery of the nodes.
## 3 Results and Discussion
### Acidogenic Substrate as Carbon (ASC)  
In order to obtain a more detailed interpretation of when the process failed (see Section 2.4), the indirect parameters ASC and DAC were calculated since they allowed a better understanding of the origin of the distortions [8]. The study of the ASC parameter, which represented the hydrolyzed and solubilized organic matter that had not been degraded to VFAs, permitted to interpret the appearance of the inhibitory effects in acidogenesis stage [34]. A transitory accumulation of ASC denoted the existence of some type of limitations in acidogenesis because the hydrolysis stage was normally the rate-limiting step of the anaerobic degradation of solid wastes [32]. Figure 5 shows the evolution of these parameters in all reactors.  
Figure 4: Specific accumulated methane production for the different mixtures tested.  
Figure 5: Evolution of dissolved organic carbon (DOC), dissolved acid carbon (DAC), and acidogenic substrate as carbon (ASC) in each reactor. (**a**) Reactor 0:100; (**b**) Reactor 10:90; (**c**) Reactor 25:75; (**d**) Reactor 50:50, and (**e**) Reactor 100:0.  
It could be observed that the ASC was not accumulated in any test. In fact, ASC reached rapidly the final level for this parameter, indicating that this value represented the concentration of the organic carbon that could not be transformed into VFAs. This behavior was observed for all tests, including the mixture 100:0 (ESBP alone). Moreover, the increase of organic matter added to the medium, when the ESBP proportion in the mixture increased, led to an increase in the maximum TVFA obtained. Therefore, it could be deduced that the inhibition of the acidogenic stage did not occur and that the hydrolytic and acidogenic stages were well-coupled in all reactors. However, the acidogenic and methanogenic stages were not coupled in the determined periods in each test. In these periods, the acidogenesis rate was higher than that of methanogenesis and, hence, an accumulation of VFA was observed. The decoupling periods were longer in reactors with high proportions of ESBP in the mixtures. Indeed, the decoupling period covered the entire test for the mixture 100:0 (ESBP alone), due to the inhibition of the acetoclastic metanogenic population, as a response of the excessively high level of TVFA.
###### Abstract
To manufacture such systems, the active ingredient must be mixed into the matrix material before the MTS fabrication or attached to the microneedles [11]. The potential of MSLA and DLP is enhanced by the ability to mix additives into photocurable resins that behave like hydrogels [12]. Previous research has explored various composites with a photocurable resin matrix, including acrylates with hollow glass microspheres [13] or a matrix of acrylated epoxidized soybean oil and carbon nanotubes [14]. Resin-based composites are also used in the production of ceramic or metallic sinters by a UV-exposing resin mixed with inorganic particles [15; 16]. In the pharmaceutical field, resins loaded with drugs such as 5-fluorouracilacil [17] or biocompatible resins with acetyl-hexapeptide-3 [18] have been developed for biomedical applications, including transdermal systems. For certain substances and fillers, additional agents are required to disperse or dissolve the filler, especially when the particles aggregate easily or differ in physicochemical properties from the matrix material. Acetone or ethanol can be used for this purpose [14; 15; 19]. However, solvents, cosolvents, and dispersion aids significantly impact the properties of the final products by affecting the resin polymerization process, particularly radical polymerization [20]. Evaporating the solvent can reduce its impact but introduces additional procedures that increase energy consumption and costs. Moreover, distillation may evaporate other resin components with similar vapor pressures, which is undesirable. Agomelatine, an antidepressant drug, requires a cosolvent for mixing into acrylic resin. Although it is lipophilic, it is difficult to dissolve directly in a resin without a cosolvent. The oral administration of agomelatine affects the gastrointestinal tract, including the liver, and is limited by the first-pass effect, reducing its bioavailability, which transdermal administration can bypass [21]. Therefore, this study investigates how ethanol, a cosolvent for dissolving agomelatine and other lipophilic substances in a resin, affects the properties of the products, including mechanical strength, dimensional stability, and mass stability. The research aims to determine the maximum alcohol content that maintains the desired properties of the final products, thus establishing the maximum amount of agomelatine for potential microneedle transdermal systems.
# Optical Response of an Interacting Polaron Gas in Strongly Polar Crystals
## 2 Many-Polaron Optical Conductivity  
We consider an electron-phonon system with the following Hamiltonian in the momentum representation:  
\[H =\sum_{\lambda}\sum_{\mathbf{k}}\varepsilon_{\lambda}\left( \mathbf{k}\right)\sum_{\sigma=\pm 1/2}a_{\mathbf{k},\sigma,\lambda}^{\dagger}a_{ \mathbf{k},\sigma,\lambda}+\sum_{\mathbf{q},j}\hbar\omega_{\mathbf{q},j}\left( b_{\mathbf{q},j}^{\dagger}b_{\mathbf{q},j}+\frac{1}{2}\right)\] \[+\sum_{\mathbf{q},j}V_{\mathbf{q},j}\left(b_{\mathbf{q},j}+b_{- \mathbf{q},j}^{\dagger}\right)\sum_{\lambda}\sum_{\mathbf{k}}\sum_{\sigma=\pm 1 /2}a_{\mathbf{k}+\mathbf{q},\sigma,\lambda}^{\dagger}a_{\mathbf{k},\sigma, \lambda}, \tag{1}\]  
where \(\varepsilon_{\lambda}\left(\mathbf{k}\right)\) is the electron energy with the momentum \(\hbar\mathbf{k}\) in the \(\lambda\)-th subband of the conduction band, \(a_{\mathbf{k},\sigma,\lambda}^{\dagger}\) and \(a_{\mathbf{k},\sigma,\lambda}\) are, respectively, creation and annihilation fermionic operators for an electron with the spin projection \(\sigma\), \(\omega_{\mathbf{q},j}\) is the phonon frequency for the momentum \(\hbar\mathbf{q}\) and the phonon branch \(j\), \(b_{\mathbf{q},j}^{\dagger}\) and \(b_{\mathbf{q},j}\) are, respectively, phonon creation and annihilation operators. The electron-phonon interaction amplitudes \(V_{\mathbf{q},j}\) are used here neglecting their possible dependence on the electron momentum and the subband number. This dependence can only be non-negligible when high-energy electrons bring an important contribution to the many-polaron response, which is not believed to be the case for strontium titanate. For the many-polaron optical response, we start from the Kubo formula,  
\[\sigma_{xx}\left(\Omega\right) =\frac{1}{Vz}\left[\frac{1}{\hbar}\int_{0}^{\infty}dt\;e^{izt} \left\langle\left[J_{x}\left(t\right),J_{x}\left(0\right)\right]\right\rangle+ i\mathcal{Z}\right] \tag{2}\] \[\left(\beta=\frac{1}{k_{B}T},\;z=\Omega+i\delta,\;\delta\to+0\right)\]  
where \(V\) is the system volume, \(e\) is the electronic charge, and the constant \(\mathcal{Z}\) is determined by the current-current correlator:  
\[\mathcal{Z}=\frac{1}{\hbar}\int_{0}^{\hbar\beta}d\tau\left\langle J_{x}\left( \tau\right)J_{x}\left(0\right)\right\rangle, \tag{3}\]  
and \(J_{x}\) is the current operator determined by:  
\[J_{x}=-ev_{x}=-\frac{e}{\hbar}\sum_{\lambda}\sum_{\mathbf{k}}\sum_{\sigma=\pm 1 /2}\frac{\partial\varepsilon_{\lambda}\left(\mathbf{k}\right)}{\partial k_{x}} a_{\mathbf{k},\sigma,\lambda}^{\dagger}a_{\mathbf{k},\sigma,\lambda}. \tag{4}\]  
The constant \(\mathcal{Z}\) can be calculated explicitly.
# Predicting C/N0 as a Key Parameter for Network RTK Integrity Prediction in Urban Environments
## 1 Introduction
Other works from this group consider 3 DMA GNSS positioning in urban environments [22; 23; 24]. Commercial product \"Sim3D\" by Spinert [25] simulates the C/N\({}_{0}\) considering multipath and NLOS situations by incorporating different 3D objects as desired by the user, e.g., building, tree, car, etc. The 3 DMA technique has been used in the \"PosNav\" research group of the Institut fur Erdmessung at Leibniz University Hannover to investigate the NLOS and multipath effect in urban environments [11; 26; 27; 28]. Current work basically takes advantage of [26], in which the multipath effects are modelled specifically for the carrier phase by developing compact expressions. In order to guarantee a navigation service for a specific trajectory with predefined quality (e.g., accuracy, integrity), performance prediction can be incorporated into the path planning step. The overall work aims to predict integrity, namely position error and protection level, in NRTK positioning useful for autonomous driving in urban environments [29; 30]. For this purpose, it is necessary to first identify the driving parameters for integrity of the RTK positioning and predict their evolution for different trajectories, environments and satellite sky distributions. By predicting the signal availability and C/N\({}_{0}\), we can put one step further towards predicting integrity. Prediction of satellite visibility in urban environments has become possible due to 3D building models of the cities. For cities located in mountainous areas, the terrain model should also be considered. This technique is known as 3D-mapping-aided (3 DMA) GNSS [12]. For predicting the C/N\({}_{0}\), in addition to signal visibility, the status of visibility should also be known. The visibility status can be line-of-sight (LOS), non-line-of-sight (NLOS), multipath or blocked [31]. The NLOS situation itself can be divided into reflection or diffraction. The signal propagation in space and attenuation interacting with the environment for any visibility status until being received by the receiving antenna should be considered (Section 4). The remainder of the paper is structured as follows. In Section 2, the real-world kinematic experiment is explained, which has been conducted to gather real observations from geodetic-grade GNSS receivers. In Section 3, we see that the solution quality can deviate from the ideal RTK solution underlining the importance of C/N\({}_{0}\). In Section 4, the signal strength prediction is investigated. In addition to a ray tracing algorithm, information is given regarding signal propagation in space and also interaction of the signal with the environment to calculate the corresponding fading of the signal in each visibility status. In Section 5, results from C/N\({}_{0}\) prediction are shown and discussed. Conclusions are given in the last section.
## 4 Result and Discussion
### Long-Term Observation and the System Stability Analysis
Measurements were taken on a total of \(53\) days from December 2019 to January 2021. **(a)** Gain and **(b)** Aperture efficiency. Figure 9: The annual variation of daily mean beamwidth. The markers are observed daily mean and minus are standard deviation. Measurements were taken on a total of 53 days from December 2019 to January 2021. **(a)** H-plane and **(b)** E-plane. pattern of a radiometer in operation and its pointing. On the other hand, we need to check whether the performance of an antenna in-field operation complies with the design specification. The traditional method for antenna performance measurement needs an anechoic chamber, which is complex in order to construct a special environment without wave reflections from the ground and surrounding area. Furthermore, in case the antenna is very large or the final assembly occurs at the installation site, the traditional method is extremely difficult [28]. Especially, the chamber method cannot be used to measure the antenna pattern of a radiometer in-field operation. Therefore, it is a simple and effective method to measure antenna pattern by using solar observation. Due to the spatial variations of the cloud and the horizontal inhomogeneity of the water vapor, a large observation uncertainty is produced under cloudy-sky condition, specially the middle and low cloud. According to our experiment, the effect is smaller for high cloud. Therefore, this method is feasible under the high-cloud condition.
### Contributions and Objectives  
Several works have been developed to improve algorithms such as PRM, GVD, and APF. Improvements often use modifications or optimization algorithms to tune parameters for collision avoidance paths. Despite these efforts, the literature lacks approaches that explore homotopy classes of trajectories to estimate a topological path at the SCARA workspace. Furthermore, there is no evidence about the performance of mathematical morphology (MM) in constraining these trajectories. We hypothesize that an MM-based strategy used to thin the regions between the obstacles at the SCARA workspace reaches groups of homotopic trajectories to draw a deterministic topological path toward the robot's target.  
This paper proposes an algorithm based on mathematical morphology operations such as dilation and erosion to create topological paths around obstacles, thus planning a collision-free path for an SCARA manipulator. We experimentally show that topological path planning (TPP) is better suited for collision avoidance and trajectory planning for an SCARA robot manipulator.  
This paper presents the following contributions:  
* A path planning with collision avoidance algorithm based on a mathematical morphology framework.
* The performance evaluation of path planning algorithms based on the dynamics of the acceleration of the manipulator joints.
* A trajectory planning suitable for collaborative manipulators.  
This paper is organized as follows. Section 2 presents the background on the SCARA manipulator and PRM. Section 3 presents the methodology of the proposed method, the scenarios used for the implementation of the algorithms, and the evaluation metrics. Section 4 presents the results of this research. In Section 5, a discussion is carried out about the results. Finally, conclusions and future work are mentioned in Section 6.
# Carbon Nanocomposites in Aerospace Technology: A Way to Protect Low-Orbit Satellites
## 3 Importance of Carbon Nanomaterials for the Corrosion Mitigation
### Carbon Quantum Dots (CQDs)  
Carbon quantum dots (CQDs) are another form of carbon nanomaterials that were studied for their potential to provide corrosion resistance under different conditions. CQDs can be incorporated into polymer-based coatings to enhance their mechanical properties and provide a barrier against corrosive species. Additionally, CQDs can act as electron acceptors and help mitigate electrochemical corrosion. The effect of nitrogen-doped carbon nanomaterials in resisting corrosion were studied by [PERSON] et al. and [PERSON] et al. [89; 90]. These studies suggested that the N-CQDs were shown to improve the performance of protective coatings by inhibiting both cathodic and anodic reactions in the corrosion process. The nitrogen atoms in the quantum dots affect the electronic structure of the metal surface, altering the reaction pathways and reducing the rate of corrosion. Additionally, the nitrogen-doping of CQDs was shown to improve their stability and reduce the risk of leaching, which is important in applications where long-term stability is required [87; 91]. Interestingly, graphene could be promising for solar sails [92].  
Figure 11: Understanding the interaction of \(AO\) with graphene: Schematic of the bonding conditions of the sites that \(AO\) fly by after the impact on \(C\) atom site with \(\varphi\) values (**a**) 0\({}^{\circ}\), (**b**) 30\({}^{\circ}\), (**c**) 90\({}^{\circ}\). \(AO\) could be both scattered and adsorbed by graphene after impacting the \(C\) atom site. Reprinted with permission from [PERSON] et al., 2023 [56] © 2019 Elsevier.  
Figure 12: Graphene/SiO\({}_{2}\) nanoparticles composite to enhance atomic oxygen corrosion resistance. (**a**) Schematic of the mechanism that (**a**) graphene flakes and (**b**) graphene flakes/SiO\({}_{2}\) nanoparticles composite mitigate atomic oxygen corrosion of polyimide. (**c**) Barrier and bonding effects between graphene flakes and atomic oxygen. (**d**) Mass loss of graphene flakes/SiO\({}_{2}\) nanoparticles composite film after atomic oxygen exposure. Reprinted with permission from [PERSON] et al., 2021 [88] © 2021 Elsevier.
## 2 Location of the Study Area and Regional Geology Setting  
The scope of the study is limited to one national road (R523) located in the Thulamela Municipality, Limpopo province, and South Africa. The Thulamela Municipality is a Category B municipality situated within the Vhembe District in the far north of the Limpopo province as shown in Figure 1.  
The Kruger National Park forms its eastern boundary while the southern and south-western side is bordered by the Makhado Municipality.  
As the smallest of the four municipalities in the district, Thulamela is spread over about 2642 km\({}^{2}\). It is, however, the largest in the province in terms of population size [22].  
The R523 road identified for this research is situated in the rugged topography of the Southpansberg Group. This geological group is partially buried beneath sedimentary and volcanic rocks of different thicknesses. The group is dominated by large faults and joints thereby creating a discrete and blocky rock mass especially in Thulamela [23; 24; 25; 26]. Furthermore, a conjugate fault and joint set has been evidenced in the northwest-southeast and northeast-southwest directions with quartz vein filling the brecciated joints and faults (see Figure 1). It is these geological features that have led to high rockfalls and slope stability problems on the roadside. An attempt is made to understand these phenomena with the help of computer-based simulation tools built around the FEM framework.  
This road is the bloodline between villages and surrounding townships. Safety is therefore critical when one considers the fact that they were excavated by the blasting of very sloppy and unstable terrain [14]. The road also passes through several rivers [15]. Intensive summer rainfall and human activities in the study area also make roads susceptible to frequent slope failure.  
Several remedial measures have been suggested and implemented but rockfalls and slope instability are still reported at an alarming rate. For example, [PERSON] [15] analyzed the stability of cut-slope along the R523 road between Thathe Vondo and Khalavha. First, geological structures, properties of the soil, and groundwater regime were surveyed. Then, conventional analytical methods were used to classify the type of soil and produce slope stability charts. Finally, two types of failure occurring close to the road were identified from the findings: rotational slump failure and rockfall in the form of toppling. The qualitative findings, however, could not be used to comprehensively describe the underlying mechanism of landslide, occurrence, and deposition. That is what the present research is attempting to explore.  
Figure 1: Locality map of the study area.