esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract
It is necessary to examine measurement protocols that are not biased against the diversity of curved surfaces, apply various curved surface models to evaluate the measurement method, and perform numerical experiments for verification. The geometric condition of the curved surfaces should express the optical properties of the PV module and the mismatching loss [72; 73; 74; 75; 76; 77; 78]. The curved surface of PVs is also related to mechanical and geometrical issues (increasing and optimizing the packing density) [14; 62; 69; 71; 79; 80; 81; 82; 83; 84; 85; 86; 87; 88; 89; 90; 91; 92; 93]. The curved surface, generally a 3D curved surface (undevelopable), commonly seen in vehicle bodies cannot be covered by a flat plane. Namely, it cannot be covered by the flexible types of photovoltaic devices without generating wrinkles. Typically, it is covered only in the relatively flat zone of the vehicle bodies, leading to a reduced coverage of the curved surface and thus reducing the amount of power. The typical coverage ratio of a photovoltaic device in the entire roof area of a vehicle is 70%. Such a low coverage ratio is as significant as the power conversion efficiency. These factors need to be solved as a mechanical constraint optimization problem, which this study did not investigate. This article begins by describing a curved surface, aided by differential geometry. Then, we expand it to the interaction with non-uniform solar irradiance that is observed frequently in vehicles running in the valleys of buildings. For this purpose, we define a four-tensor (nested matrix) to characterize the interaction. Reducing the complexity of certain applications, such as PV devices on car roofs, is feasible. First, we do not need to consider the 3D rotation of the coordinate system (pitch, roll, and yaw); we only need to consider the vehicle's orientation. Second, the curve shape is simple convex (single peak), and we do not need to consider the hidden surface; thus, we only consider the inner product of the normal vector of the surface element and the ray vector. Third, solar cells are connected in series (single string configuration). In such cases, the calculation steps are not complex. Still, it is beyond arithmetic with trigonometric functions. The new algorithm for curved PV devices was validated using a commercial VIPV panel. It effectively explains the performance of PV modules in an outdoor environment with dramatic differences between standard and flat PV devices. The unusual behavior of curved PV devices in VIPV applications has been intensively considered and analyzed. Therefore, the modeling, measurement, analysis, and discussions of curved issues were focused on VIPVs in this study. However, they can also be applied to curved PV devices such as building-integrated photovoltaics (BIPVs), aircraft PVs, and even PV arrays installed on wavy land.
# Discrete Integral Optimal Controller for Quadrotor Attitude Stabilization: Experimental Results
## 1 Introduction
A previous exact linearization was performed on the dynamical model in order to remove the Coriolis terms and transform the rotational dynamics in the second-order differential equation depending on external torque inputs. So for control of the altitude and attitude of the UAV, four optimal controls with integral action are proposed: one for each subsystem. The controllers for rotational dynamics are synthesized using the assumption that pitch, roll and yaw are inside a bounded region around the origin, which is an equilibrium point for this aerial vehicle. The proposed optimal control strategy assumes that all state variables are available. Our proposal is experimentally tested in takeoff and altitude stabilization tasks. An Optitrack vision system is used to obtain the whole state of the vehicle, and satisfactory results are obtained when the optimal discretized controller with integral action is applied. So the main contributions of this work are:  
1. Synthesis, analysis and implementation of Optimal Integral Control (OIC) tuned under the QR approach and applied to trajectory tracking of takeoff and hover flight of UAVs. 2. Experimental validation of the OIC by real-time tests in the presence of induced crosswind disturbances applied during the trajectory tracking of takeoff and hover flight of a UAV, allowing the analysis of the robustness of the closed loop with the proposed control scheme. 3. Comparison of the kinetic and potential energy between the PID and the Optimal Integral Control when a trajectory tracking task is executed for the take-off and hover-flight phases of the UAV in the presence of induced crosswind. The paper is organized as follows: The nomenclature and symbols used throughout this document are presented in Section \"Nomenclature\", while the introduction is reported in Section 1. Moreover, Section 2 is devoted to showing the mathematical model of the UAV together with the synthesis of the proposed control law. In Section 3, the experimental platform is shown. Real-time experimental results are displayed in Section 4, and finally, the conclusion and discussion are reported in Section 5.
# Ontology-Based Framework for Cooperative Learning of 3D Object Recognition
## 3 Proposed Cloud and Ontology-Based Framework Architecture
### Motivational Example  
We illustrate our proposal with the motivational example given in Figure 1. Consider two known objects (A and B) captured by different robots with different RGBD cameras or laser scanners. The structure and appearance of each object is represented in the Point Cloud Data (PDC) format (i.e., a set of points sampled from the object's surface) as defined by the Open Perspective Foundation [31]. The PCD data are uploaded to the cloud platform through the Object Training Service, which constructs, over time, a shared training set for object detection and recognition, a set of Object Templates. We allow multiple object templates for a single object in order to handle different viewpoints for identifying asymmetric objects (e.g., object A). If we suppose that another robot wants to identify another instance of object A in a target scene X also represented by a point cloud, then the robot merely needs to submit X to the Object Detection and Recognition Service to perform matching of the target scene with the set of Object Templates specifically for object A. Multiple object template matching processes can be run in parallel on the cloud platform to reduce the time required to find the best match. Finally, the best-matching template would be returned to the robot for the purpose of identifying the position and orientation of the instance of object A in the scene and making it possible to plan manipulation strategies.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Service Robotics Feature** & \begin{tabular}{c} **Our** \\ **Frame-Work** \\ \end{tabular} & \begin{tabular}{c} **[PERSON]** \\ **et al.**[12] \\ \end{tabular} & \begin{tabular}{c} **[PERSON]** \\ **et al.**[17] \\ \end{tabular} & \begin{tabular}{c} **[PERSON]** \\ **et al.**[19; 21] \\ \end{tabular} & \
\begin{tabular}{c} **[PERSON]** \\ **et al.**[28] \\ \end{tabular} &
\begin{tabular}{c} **[PERSON] et al.** \\ [30] \\ \end{tabular} \\ \hline
1. Ontology-based & ✓ & ✓ & ✓ & ✓ & ✓ & ✓ \\
2. Enables Cooperative learning & ✓ & & & & \\
3. Provides for knowledge sharing & ✓ & & ✓ & & ✓ & \\ and management & & & ✓ & & & ✓ \\
4. Performs 3D object recognition & ✓ & ✓ & & & & ✓ \\
5. Provides information about robot & & ✓ & ✓ & ✓ & ✓ & ✓ \\ capabilities & ✓ & ✓ & & & ✓ & \\
6. Provides information about robot & ✓ & & & ✓ & & \\ physical characteristics & & & & ✓ & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparison of cloud-enabled service robot frameworks.  
Figure 1: Cooperative robot learning example scenario.
## 4 Model Validation and Results
As the extraction time prolonged, the residual gas pressure between boreholes decreased rapidly, and the pressure criterion of 0.74 MPa was reached after 284 days of extraction. The relative error of our simulation results was 5.96%, which confirmed that the current multi-scale THM model was applicable to a simulation of gas extraction from a coal seam stimulated by directional hydraulic fracturing. Figure 5: Comparison between field data and simulations results. Figure 6: Gas pressure distribution of the matrix at different times. When the gas pressure decreased over time, the permeability of the matrix also decreased, but the cleat permeability in the x- and y-directions increased, as shown in Figure 8. The matrix and cleat permeability were both controlled by dual competing mechanism of effective stress and matrix deformation. Similar, the hydraulic fracture aperture was sensitive to the change in the effective stress. The maximum aperture of hydraulic fracture decreased from 0.229 mm at 10 days to 0.186 mm at 284 days of extraction, which indicates that the increased effective stress closed the hydraulic fracture apertures and reduced permeability and heat flux in the hydraulic fracture, as shown in Figure 9.  
Figure 8: The evolution of the matrix and fracture permeability at a specific point x = 9 m and y = 5.5 m during gas drainage. Figure 7: Gas pressure evolutions in the matrix along line A.
## 3 Results
### Expression Stability Validation of the Most Reliable Reference Gene  
To verify the stability and reliability of _HIS_ (the most stable reference gene) for accurate normalization of the expression levels of _Fusarium_ wilt-related genes, we evaluated the expression of four potential resistance-related genes, including _POD_, _PAL_, _CHI_, and _DIR_, using qRT-PCR. As presented in Figure 4, the results showed that the expression patterns of the four target genes were the same during the first three time periods (0 h, 6 h, and 12 h) after inoculating; all genes showed the lowest expression at the 0 h time-point and began to significantly up-regulate in 6 h and then down-regulated again in 12 h. In the next three time periods (24 h, 48 h, and 72 h), they again showed a certain upregulation. The time period of their highest expression was not exactly the same. However, the general expression levels of the four target genes were stronger in most samples inoculated with _F. oxysporum_ than that in control samples (Figure 4).  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Comprehensive Ranking** & **Reference Genes** & **GM Values of Ranking** \\ \hline
1 & _HIS_ & 1.587 \\
2 & _CYP_ & 2.080 \\
3 & _PGK_ & 2.884 \\
4 & _UBQ_ & 4.121 \\
5 & _AQP_ & 4.309 \\
6 & _EF-1a_ & 5.192 \\
7 & _TUB_ & 6.000 \\
8 & _RPL13_ & 7.652 \\
9 & _GAPDH_ & 9.000 \\ \hline \hline \end{tabular}
\end{table}
Table 3: The comprehensive ranking of candidate reference gene stability by GM method.
## 3 Results  
The results for objective evaluation in Section 3.1 include F0 pattern evaluation and spectrum augmentation evaluation. The results of U/V analysis, F0 CC and log F0 RMSE are used to evaluate the F0 pattern. MCD and CodeAP RMSE are used to evaluate the spectrum augmentation. The results for subjective evaluation in Section 3.2 include the analysis of tone accuracy, influence of semantic information for tone accuracy, word perception error rate, MOS of intelligibility and naturalness.
## 4 Proposed Methods
### Update of \(\rho\)  
First, we focus on the precoding factor \(\rho\) within the DFRC system. With \(\mathbf{X}\) and \(\mathbf{X}_{0}\) held constant, the optimization problem Equation (11) for \(\rho\) is defined as follows  
\[\min_{\rho}\|\mathbf{S}-\rho\mathbf{H}\mathbf{X}\|_{F}^{2}+\rho^{2}ULN_{0} \tag{12}\]  
We expand the objective function in Equation (12), as follows  
\[\begin{split} G(\rho)&=\text{Tr}\Big{(}(\mathbf{S} -\rho\mathbf{H}\mathbf{X})^{H}(\mathbf{S}-\rho\mathbf{H}\mathbf{X})\Big{)}+ \rho^{2}ULN_{0}\\ &=\text{Tr}(\mathbf{S}^{H}\mathbf{S})-2\rho\,\text{Tr}(\mathbf{ S}^{H}\mathbf{H}\mathbf{X})+\rho^{2}\Big{(}\text{Tr}(\mathbf{X}^{H}\mathbf{H}^{H} \mathbf{H}\mathbf{X})+ULN_{0}\Big{)}\end{split} \tag{13}\]  
Differentiating \(G(\rho)\) and setting the derivative equal to zero, provided that the coefficient of \(\rho^{2}\) is greater than zero, allows us to obtain  
\[-2\,\text{Tr}\Big{(}\mathbf{S}^{H}\mathbf{H}\mathbf{X}\Big{)}+2\rho(\| \mathbf{H}\mathbf{X}\|_{F}^{2}+ULN_{0})=0 \tag{14}\]  
Consequently, \(\rho\) can be determined using the closed-form expression below  
\[\rho=\frac{\text{Tr}\big{(}\mathbf{S}^{H}\mathbf{H}\mathbf{X}\big{)}}{\| \mathbf{H}\mathbf{X}\|_{F}^{2}+ULN_{0}} \tag{15}\]  
Here, \(\rho\) is obtained as a closed-form solution by minimizing the MSE between the intended symbols \(\mathbf{S}\) and the scaled received signals \(\rho\mathbf{H}\mathbf{X}\). As shown in Equation (15), \(\rho\) depends on the current precoded matrix \(\mathbf{X}\) and the channel \(\mathbf{H}\). It balances the residual noise and interference, ensuring that the received symbols align closely with the desired constellation points.
## 4 Calculation Example of Slope Stability under Freeze-Thaw Conditions  
### Slope Stability Method under Freeze-Thaw  
In the analysis of slope stability under freeze-thaw, the strength reduction method is used [16]. While keeping the external load constant, the ratio of the maximum shear strength exerted by the slope to the actual shear stress generated by the external load inside the slope is the strength reduction factor [17].  
In the calculation, the shear strength parameters C (cohesive force) and \(\varphi\) (internal friction angle) of the slope are first reduced by a certain coefficient \(Fr\), which is recorded as C\({}_{\text{m}}\) and \(\varphi_{\text{m}}\), and then C\({}_{\text{m}}\) and \(\varphi_{\text{m}}\) are substituted into the ABAQUS slope model for calculation under the condition that the external load remains unchanged. We then continuously increase \(Fr\) until the slope is unstable under a certain reduction factor. The value of the reduction factor before the overall failure of the slope is recorded as the slope safety factor \(Fr\). The calculation equations of parameters C\({}_{\text{m}}\) and \(\varphi_{\text{m}}\) are as follows:  
\[\text{C}_{\text{m}}=\text{C}/Fr \tag{1}\]  
\[\varphi_{\text{m}}=\arctan(\tan\varphi/Fr) \tag{2}\]  
In the freeze-thaw environment, when the stability analysis of the slope is carried out using the strength reduction method, the standard of slope instability is generally as follows: (1) trend of displacement at the shoulder of the slope; (2) penetration of the equivalent plastic zone of the slope; and (3) failure to converge within the specified number of iterations. In the calculation of ABAQUS, it is more practical to use the convergence as the slope instability criterion. Therefore, in this paper, the slope safety factor \(Fr\) we studied was calculated based on the third criterion.
# A Review of Regional and Global Gridded Forest Biomass Datasets
## 3 Current Gridded Forest Biomass Maps
### Forest AGB Maps Generated Using GIS-Based Methods
#### 3.1.4 IIASA's Global Forest Database  
[PERSON] et al. [54] produced a global forest biomass database at 0.5\({}^{\circ}\) resolution for the year 2005 by downscaling the aggregated country-level FRA biomass, on the basis of the relationships between net primary productivity (NPP) and biomass, and between human impact and biomass. The uncertainty of estimated AGB depends heavily on the quality of the FRA, and NPP and human activity data, as well as the simple assumption of linearity in the relationship between NPP and human activity, and biomass.
## 2 Materials and Methods
### Imaging the Condyle  
The CT examinations were performed using a 64-detector 128-slice GE Revolution EVO scanner (GE Healthcare, Milwaukee, WI, USA) before and after 3 months of treatment. The scanning area was planned to cover the TMJ and the mandible. CT acquisition parameters were as follows: rotation time, 0.4 s; 80 kVp; 100 mA; slice thickness, 0.625 mm; slice interval, 0.625 mm; and pitch, 0.984. Scanning was performed using automatic tube current modulation (in three axes) and iterative reconstruction (ASIR-V) to reduce noise and dose. Acquired Digital Imaging and Communications in Medicine (DICOM) images were sent to a workstation (GE Advantage Workstation, General Electric Medical Systems, Milwaukee, WI, USA) to create three-dimensional images consisting only of bony structures.  
An initial tracing intersecting the orbitale and porion points was made to isolate the condylar image. This step was followed by tracings parallel to the first one, which extended from the top of the condyle and the bottom of the sigmoid notch. The remaining surrounding structures were removed using various shaping tools, and a three-dimensional image of the condyle was obtained (Figure 4).
# Laser Induced Aggregation of Light Absorbing Particles by Marangoni Convection
## 3 Results and Discussion
### AP Aggregation
At the liquid-air interface, the surface tension gradient, \(\
abla\gamma\), drives liquid migration from hot to cold regions. This convective flow provides a driving force to deliver colloidal particles in the liquid through Stokes' drag force, given by \(F=6\pi\eta Rv\), where \(\eta\) is the viscosity of the liquid, \(R\) is the mean radius of the particles, and \(v\) is the convective flow velocity [40]. Moreover, Marangoni convection can increase particle aggregation speed by 1-2 orders of magnitude, which enhances self-assembly and deposition of particles [42]. In our experiments, the particles accumulated quickly at the location near the laser focus when there was a gas phase in the sample cell. Therefore, we think that the Marangoni convection dominantly causes the particle aggregation at the liquid-air interface. The aggregation speed of particles under the Marangoni convection was measured. As the AP aggregates were almost monolayers, we used areas of the AP aggregates to describe the amount and accumulation speed of APs. The areas of the AP aggregates were measured at different laser powers. Figure 2: Images of forming absorbing particle (AP) aggregates. (**a**) No laser illuminating, the APs do not move. (**b–f**) The process of laser induced particles aggregation. The APs begin to accumulate when the laser begins to illuminate on a small aggregate at time = 0.6 s. The APs move to the heat center, and form a large AP aggregate. P = 18 mW at the pupil of the objective. The circle indicates the focal center of the laser beam. The thickness of the suspension layer was 70 \(\upmu\)m. Scale bar, 10 \(\upmu\)m.  
For each laser power, the initial AP aggregate was carefully selected with almost same size of beam. The experiment results are shown in Figure 3. The green pentagon represents the data at the laser power of 15 mW; the blue triangle represents the data at laser power of 22 mW; the red circle represents the data at laser power of 29 mW, and the black square represents the data at laser power of 41 mW. The results show that the areas of AP aggregates gradually increase when the laser irradiation time increases. The accumulation speed of APs mainly depends on the laser power for a suspension layer.
## 3 Results and Discussion  
### Magnetic Structure of a-Cu\({}_{2}\)P\({}_{2}\)O\({}_{7}\)  
The crystal structure of monoclinic \(\alpha\)-Cu\({}_{2}\)P\({}_{2}\)O\({}_{7}\) with \(C2/c\) space group includes two layers of pyrophosphate [P\({}_{2}\)O\({}_{7}\)] groups; the layers are parallel to the (100) plane. The optimized crystal structures for the four magnetic configurations considered in this work are shown in Figure 1 with the local magnetic moments on the four Cu atoms indicated by arrows. The primitive cell parameters for the ferromagnetic (FM) state, as calculated by PBE functional, are \(a_{p}=b_{p}=5.485\) A, \(c=9.411\) A, \(a_{p}=\beta_{p}=75.725^{\circ}\), \(\gamma_{p}=97.330^{\circ}\), \(V_{0}=260.53\) A\({}^{3}\) and \(Z=2\) (two Cu\({}_{2}\)P\({}_{2}\)O\({}_{7}\) formula units per primitive cell). The calculated (standardized, \(Z=4\)) unit cell parameters are listed in Table 1 where they are compared with some of the available theoretical and experimental data [14; 15; 22; 23]. We note that a hydrated form of nanocrystalline copper pyrophosphate exists, whose unit cell (incorporating four Cu\({}_{2}\)P\({}_{2}\)O\({}_{7}\):2H\({}_{2}\)O formula units) is bigger than that of the anhydrous form: \(a=11.466\) A, \(b=10.204\) A, \(c=6.123\) A [46]. Naturally, the molecular volume for the hydrated form, \(V_{0}=196.054\) A\({}^{3}\) per Cu\({}_{2}\)P\({}_{2}\)O\({}_{7}\):2H\({}_{2}\)O formula unit, is bigger than that for the anhydrous form, \(V_{0}=130.265\) A\({}^{3}\) per Cu\({}_{2}\)P\({}_{2}\)O\({}_{7}\) formula unit, by the volume of two H\({}_{2}\)O molecules. In copper pyrophosphate, only Cu\({}^{2+}\) ions are calculated to carry local magnetic moments corresponding to spin 1/2. Each Cu\({}^{2+}\) ion is surrounded by five O atoms forming a [CuO\({}_{5}\)] polyhedron with the volume of 6.905 A\({}^{3}\) and Cu-O bond lengths in the range 1.913-2.316 A. Besides, the shortest Cu-Cu distance (along the crystallographic direction \(b\)) is calculated to be \(\sim\)3.12 A. Importantly, for this Cu-Cu pair there are two identical Cu-O-Cu paths with a bond angle \(\angle\)Cu-O-Cu of 101.735\({}^{\circ}\), as shown in Table 2. According to previous studies on the nearest-neighbor (NN) exchange coupling, the closeness of \(\angle\)Cu-O-Cu to 90\({}^{\circ}\) indicates a sizeable ferromagnetic contribution, based on the Goodenough-Kanamori rules [12; 47; 48]. Hence, it is natural to expect the superexchange interaction to favor an antiferromagnetic order for the Cu-Cu NN pair, due to the deviation of Cu-O-Cubond angle from 90\({}^{\circ}\). The calculated Cu-Cu distance and Cu-O-Cu bond angle is in agreement with the results of previous studies, 3.05-3.33 A and 100.4-100.8\({}^{\circ}\)[12; 14; 24]. For the obtained parameters of Cu-O-Cu paths, competing exchange interactions may be expected to exist along the shortest Cu-Cu distance, giving rise to four possible magnetic configurations FM, AFM-1, AFM-2, and AFM-3 shown in Figure 1. Experimentally, \(\alpha\)-Cu\({}_{2}\)P\({}_{2}\)O\({}_{7}\) is antiferromagnetic at cryogenic temperatures [12; 23; 24; 25; 26] and Curie-Weiss
# First Lidar Campaign in the Industrial Sites of Volta Redonda-RJ and Lorena-SP, Brazil
## 4 Data Retrieval and Results  
The results retrieved in this study, based on satellite and ground-based remote sensing systems, are presented and discussed in this section. First, we present results of air quality analysis from stations installed on four cities of MRPV from 2015 to 2020, and an analysis of aerosol optical properties retrieved from CALIPSO satellite from the period of 2006 to 2020 for Volta Redonda and Lorena in order to describe an overview of air pollution impact on air quality of the region. Subsequently, we present results from two important campaigns developed in Volta Redonda and Lorena locations using the ground-based lidar. These two campaigns mainly contributed to achieving, for the first time, the monitoring of the vertical distribution of aerosol in the MRVP, detecting episodes of intense pollution within the atmospheric boundary layer and also detecting detached aerosol layers above the atmospheric boundary layer, which can indicate the possibility of long-range aerosol transportation that will be investigated using the HYSPLIT trajectory model.  
This first effort to monitor aerosol optical properties and their vertical distribution can encourage initiatives to develop a monitoring network in this region and use the measured atmospheric data to improve numerical prediction models of air quality indices.