esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 System Model  
We will consider an end-to-end system model for compute and forward, as shown in Figure 1. There are \(L\) sources and a single destination node, \(D\). The \(L\) sources communicate with the destination via a single relay node, \(R\). For the proposed precoding-based CF, transmission occurs in two phases: phase I, during which the sources transmit simultaneously to \(R\), followed by phase II, during which \(R\) transmits to \(D\).
## 3 Driving Force Distribution and Control Strategy  
### Hierarchical Control Scheme  
In this paper, vehicle motion control was implemented through a driving force distribution and control algorithm. There are two layers of processing in the hierarchical scheme: the upper layer controller and the lower layer controller, as shown in Figure 5. In the parsing layer, the desired state, including the desired longitudinal speed and the desired yaw rate, is obtained by parsing the inputs from the remote control. In the tire force estimation, the tire lateral forces are estimated by referring to [35]. In order to track the desired input state of the vehicle, an upper layer controller is proposed for calculating the desired resultant force and the desired resultant yaw moment. Since the desired resultant force and the desired resultant yaw moment are generated by the interaction between the six tires and the road, a lower layer controller was designed to distribute the driving force or torque of the six motors.  
Figure 4: Longitudinal force and lateral force in combined slip circumstances; the slip rate is from 0 to 0.6, and the sideslip angle is from 0\({}^{\circ}\) to 30\({}^{\circ}\). (**a**) Longitudinal force; (**b**) Lateral force.  
Figure 5: Schematic diagram of the controller.
_Applied_  
_sciences_  
_Mdpi_  
_PMAA Intraocular Lenses Changes after Treatment_  
_with Nd:Yag Laser: A Scanning Electron Microscopy_  
_and X-ray Spectrometry Study_  
**[PERSON] 1**, **[PERSON] 1**, **[PERSON] 1**, **[PERSON] 1**, **[PERSON] 1**, **[PERSON] 1**, **[PERSON] 1**, **[PERSON] 2**, **[PERSON] 3,* and **[PERSON] 1**  
1 Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Via Consolare Valeria 1, 98125 Messina, Italy; [EMAIL_ADDRESS] (A.M.); [EMAIL_ADDRESS] (A.A.S.); [EMAIL_ADDRESS] (A.D.M.); [EMAIL_ADDRESS] (P.P.); [EMAIL_ADDRESS] (G.A.); [EMAIL_ADDRESS] (B.T.); [EMAIL_ADDRESS] (D.P.); [EMAIL_ADDRESS] (A.G.M.)  
2 Department of Veterinary Sciences, University of Messina, Annunziata University Pole, Viale Annunziata, 98168 Messina, Italy; [EMAIL_ADDRESS]  
3 Department of Biomedical and Dental Sciences and Morphofunctional Imaging, Regional Referral Center for the Ocular Surface Diseases, University of Messina, Via Consolare Valeria 1, 98125 Messina, Italy  
* Correspondence: [EMAIL_ADDRESS]; Tel.: +39-90-221-2401; Fax: +39-90-221-3958  
Received: 30 July 2020; Accepted: 9 September 2020; Published: 11 September 2020  
**Featured Application: The clinical relevance of this experiment is to demonstrate that PMMA lenses have a moderate resistance to laser treatment if they are hit by a low number of spots, but significant structural changes occur when a higher number of spots reach their surface. The effect of multiple laser spots on IOLs is relevant even because this is what may happen in procedures carried out by residents at their early stages of training.**  
**Abstract:** Neodymium:yttrium-aluminum-garnet (Nd:YAG) laser may cause intraocular lenses (IOLs) damages. Therefore, the effects of Nd:YAG laser on IOLs were evaluated. Twenty-four IOLs (copolymer of 2-hydroxyethylmethacrylate and 2-ethoxyylmethylmethacrylate) were used. For scanning electron microscope (SEM), twelve IOLs were divided into three groups: Group 1, controls; Group 2, IOLs treated with two laser spots (YC-1800 Nidek Nd:YAG laser set at 1.2 m)); and Group 3, IOLs treated with six laser spots. All IOLs were critical point dried in CO\({}_{2}\) and viewed in a Zeiss EVO LS10 SEM. For Energy Dispersive X-ray spectrometry (EDX), four IOLs of each group were examined with a Jeol JMC-6000 SEM. With SEM, Group 1 IOLs showed well-preserved size, shape and surface. Group 2 IOLs exhibited normal shape and margins, a peripheral furrow with irregular blebs, straight clefts and holes on the wrinkled surface. Group 3 IOLs were swollen and broken into two or three parts. With SEM and EDX, Group 1 and the undamaged surfaces of Groups 2 and 3 showed evident carbon and oxygen peaks, while, in the damaged areas, both atoms were significantly reduced. Nd:YAG laser induced evident changes in IOLs morphology and organic alterations in their chemistry: great care during posterior capsule opacification treatment is required.  
**Keywords:** intraocular lens; Nd:YAG laser; Energy Dispersive X-ray spectrometry; critical point drying; scanning electron microscopy
# A Review of Wireless Positioning Techniques and Technologies: From Smart Sensors to 6G
## 3 Wireless Technologies
### Cellular
#### 3.2.3 Fifth Generation (5G)
Specifically, the 3 GPP radio access network (RAN) release 18 enhances the 5G with artificial intelligence and machine learning technologies. The new radio (NR) in release 15 addresses numerous scenarios, such as enhanced mobile broadband (eMBB) and massive machine-type communications (mMTC) and release 16 introduces numerous improvements, such as multiple-input multiple-output (MIMO) and beamforming enhancements, as well as the enhanced support of industrial IoT. Furthermore, in release 17, the multicast and broadcast service (MBS) and non-terrestrial networks (NTNs) are introduced. One of the major improvements in release 18 are the network energy savings, which makes 5G NR significantly more energy efficient, compared to previous generations. It also introduces the conditional handover for the user equipment (UE) receivers. Furthermore, regarding positioning, it was first supported in release 15 and enhanced in release 16 using both downlink-based and uplink-based positioning methods. Additional enhancements for reducing latency for time-critical applications, such as short distance positioning, were included in release 17, while further improvements in accuracy, integrity, and power efficiency were investigated in release 18 [82].
## 5 Result and Discussion
### Analysis Results of AHP and Rough AHP  
Figure 2 shows that C1 (access to all areas) and C2 (order characteristics) are the most critical criteria based on the importance levels provided by all the decision-makers. On the other hand, the least important criteria according to all decision-makers based on weight were C6 (material handling) and C5 (placement of the product). The average weights of the criteria are also presented in Table 6. The method implemented was the rough set theory using AHP, which could determine a better CI quickly and could analyze the complex problem. These rough sets are generally utilized for conditions with multiple decision-makers. In this case, some inconsistency may occur using only AHP methods, so for better judgment, the rough method was considered. Moreover, with the aforementioned series of steps and computations of weights based on decision-maker judgments, the C2 (order characteristic), C3 (frequency of product), and C4 (storage area) are consistent, C5 (placement of boxes) and C6 (material handling) have the least weighting, and C1 (access to all areas) has the most influence (Figure 3). These criteria affect the space utilization of the warehouse, as shown in Figure 3.
## 4 Proposed Antenna Codebook and MAB Approach
### Proposed Nested Two-Stage MAB Approach
#### 4.2.1 Proposed Nested Two-Stage TS Algorithm  
TS is based on a pure Bayesian strategy [16], where prior/posterior distributions are considered for the arms' rewards. The parameters of the assumed probabilistic model are initialized for each arm at the beginning of the algorithm. Then, random samples are taken from the constructed distributions, and the arm related to the highest random sample is selected and played. After obtaining the rewards corresponding to the played arm, its parameters are updated for the posterior distribution of the next round of the MAB game. In the proposed TS algorithm, normal distributions are considered for the spectral efficiency corresponding to each value of \(\mathbf{\Phi}\) and \(\mathbf{f}\) at time \(t\), i.e., \(\mathbf{\psi}_{\mathbf{\Phi}_{i}\mathbf{f}_{j_{t}}}\), where \(1\leq i\leq|\mathcal{R}|\), \(1\leq j\leq|\mathcal{F}|\).
## 4 Discussion
### Impact Resistance Index (IRI)  
The IRI values of the briquettes higher than 100% were found in treatments T7 (0:67:33) and T2 (0:100:0), where no large sawdust particles were used; values higher than 90% were found in treatments T3 (0:0:100), T4 (33:33:33), and T9 (33:67:0). Values for the treatments T8 (0:33:67), T0(12:71:17) (control), and T6 (67:0:33) were higher than 76.5%, which, according to [PERSON] [48], is the minimum requirement established by the Wood Pellet Association of Canada. The hardness results were based on briquettes produced by mechanical piston presses and screw presses, and hard enough to be transported in trucks over considerable distances without degrading [38].  
The impact resistance of the briquettes showed an inverse relationship to the size of the particles, as the briquettes with smaller particles have a larger surface area, which increases shock absorption at the drop and improves bonding, similarly to the behavior presented by [PERSON] et al. [23] and [PERSON] et al. [13]. The main factors that contribute to the formation of a stronger bond between particles during densification may be the mechanical interlocking and the adhesive force between biomass particles. However, it is often difficult to provide an acceptable result with this index because the ratio of test results and reality has not been thoroughly studied [38]. According to the response surface and contour graphs (Figure 7), the highest impact resistance values (>100%) were obtained with mixtures containing percentages of medium particles approaching 100% and large and small particles approaching 0%, while decreasing the percentages of medium particles from 100 to 70% and increasing the percentages of both large (0-5%) and small (0-30%) particles reduced the impact resistance values by up to 90%.
# Application of a DC Distribution System in Korea: A Case Study of the LVDC Project
###### Abstract  
With the rapid expansion of renewable energy and digital devices, there is a need for direct current (DC) distribution technology that can increase energy efficiency. As a result, DC distribution research is actively underway to cope with the sudden digitization and decentralization of load environment and power supply. To verify the possibility of DC distribution, Korea Electric Power Corporation (KEPCO) Research Institute made a DC distribution system connected with a real power system in Gwangju. The construction of the demonstration area mainly includes design of protection and grounding systems, operating procedures of insulation monitoring device (IMD), and construction of power converters. Furthermore, this paper goes beyond the simulation and the lab testing to apply DC distribution to a real system operation in advance. It is designed as a long-distance low-loaded customer for rural areas and operated by the DC distribution. In addition, safety and reliability are confirmed through field tests of DC distribution elements such as power conversion devices, protection and grounding systems. In particular, to improve the reliability of non-grounding system, the insulation monitoring device was installed and the algorithms of its operational procedures are proposed. Finally, this paper analyzes the problems caused by operating the actual DC distribution and suggests solutions accordingly.  
DC distribution system; AC/DC converter; protection; grounding system; insulation monitoring device (IMD) +
Footnote †: journal: Applied Sciences
## 5 Results
The influence of the color levels of the feature maps on performance is shown in Figure 19. This variational study was carried out for all models, where the lower limit of the color scale was varied using offsets of \(-30\) (least details), \(-50\), and \(-70\) (most details) with regard to the maximum color value. Here, the CAE and CNN show the best performance and higher robustness to color level variations, whereas the RNN-based methods are more strongly affected, with the GRU showing the strongest effects. The results indicate that the color levels have a significant impact on classification accuracy. Considering the stochastic effects of training, the optimum threshold in this study probably lies between \(-50\) and \(-70\). The influence of the compression ratios of the feature maps on performance is shown in Figure 20. Using three different compression ratios, i.e., \(100\%\), \(67\%\), and \(50\%\), a study was carried out for all models. According to the results, the performance of all models, except for the GRU, shows high robustness to information loss caused by compression, with the CAE achieving the best results, followed by the CNN and Bi-LSTM. In practice, this means that even with a halved data size, the models are able to achieve similar performance. It should  
Figure 16: Loss and accuracy during training and confusion matrix for Bi-LSTM (RNN)-based classification. Figure 17: Loss and accuracy during training and confusion matrix for GRU (RNN)-based classification. be noted that the model-specific performance deviations in the investigated cases were caused by the stochastic nature of the learning algorithm and the dataset batching process. From the results, we can confirm that CNN-based classification achieved better performance in comparison to the investigated RNN-based methods. The reason for this is that the derived feature maps of CNNs have the ability to extract locally distributed spatial features in a hierarchical manner and, therefore, can recognize typical patterns, whereas RNN-based methods memorize temporal sequences of single features. This ability also applies to CAEs, but the tendency for overfitting is much higher, so tuning, e.g., through better regularization, is necessary. Regarding the underlying type of input, namely images, RNN-based networks are suboptimal due to the lack of scalability and the absence of the ability to memorize spatial properties. Figure 19: Accuracy by different lower color value limits used for threshold filtering for the selected models. Figure 18: Loss and accuracy during training and confusion matrix for CAE-based classification. Further, it can be revealed that the classification of coarse-grained activities led to better results. Higher magnitudes of the reflected radar signal, which were assigned to large-scale movements, led to distinct characteristic properties in the micro-Doppler maps, which improved performance.
## 2 Materials and Methods
### Comparison with Other Satellite Data  
In our model-data workflow, we derived the aboveground biomass and net primary productivity (NPP) values for the forests in the Amazon (among other things). We compared these values with maps from other sources: the aboveground biomass map for forests from [PERSON] et al. (radar remote sensing) [32] and the NPP map from MODIS (optical remote sensing) [33].  
The aboveground biomass map contains data from 2018 with a resolution of 100 m. The NPP map from MODIS contains data from 2000 to 2010 with a resolution of approximately 1000 m. Both maps were adapted to the grid of the forest/non-forest map used in this study (50 m). This made it possible to distinguish the biomass and NPP values for the forest edge and core areas. We used R for the calculations.
# A Novel Particulate Matter 2.5 Sensor Based on Surface Acoustic Wave Technology
## 2 Design and Simulation
### Particle Separation  
The sampling principle of the VI is based on the different inertia of particles of different diameters [15; 16]. The VI is composed of two coaxial nozzles, shown in Figure 3. The upper nozzle is the acceleration nozzle, and the lower nozzle is the collection probe. The geometric parameters are the width of inlet \(W\), the angle of inlet \(\theta_{0}\), the width of acceleration nozzle \(W_{0}\), the length of acceleration nozzle \(L_{0}\), the nozzle-to-probe distance \(S\), the width of collection probe \(W_{1}\) and the height of microchannel \(h\) (perpendicular to the cross-sectional view).  
When the air flows into the nozzle, the high-speed airflow is divided into two. One part of it, occupying 90% of the total flow, changes direction with an angle of 90 degrees and flows into the side passage. This part is called major flow. Another part of airflow, occupying 10% of the total flow, enters the collection probe directly. This part is called minor flow. Meanwhile, particles of small diameter have small inertia and are easy to move with the major flow to the side passage. On the other hand, large particles have large inertia and are easy to break away from the deflecting airflow, entering the collection probe. The inertia based separation property of particles is characterized by a parameter, namely the Stokes number (Stk) [17]. If the particles with a certain diameter that 50% of which flow into the side passage and another 50% of which flow into the collection probe, the certain diameter is called the cut-off diameter (\(D_{50}\)). The corresponding Stokes number is Stk\({}_{50}\). The \(D_{50}\) and Stk\({}_{50}\) satisfy  
Figure 3: Cross-sectional view of the virtual impactor.  
Figure 2: Exploded view of the detecting probe.  
the Stokes equation (Equation (1)), which is influenced by the fluid properties and the VI geometric parameters. In Equation (1), \(\mu\) is the dynamic viscosity of the fluid, \(\rho_{8}\) is the particle density, \(Q_{0}\) is the total flow and \(C\) is the Cunningham slip correction.  
\[D_{50}=\sqrt{\frac{9\mu HW_{0}^{2}\text{St}k_{50}}{\rho_{8}Q_{0}\text{C}}} \tag{1}\]  
First, the value of \(\text{St}k_{50}\) was assumed to be 0.55 and the \(D_{50}\) was set to 2.5 \(\upmu\)m. According to Equation (1), the total flow \(Q_{0}\) = 13.5 mL/min, the height \(h\) = 200 \(\upmu\)m and the width \(W_{0}\) = 290 \(\upmu\)m were determined. Then, the other geometric parameters were obtained in succession referring to [18]. Lastly, the proposed design of the microchannel was further adjusted by using the FEM software COMSOL to deduce the collection efficiency. The collection efficiency is the ratio of the particles collected in the minor flow to the particles supplied to the inlet. By using the Laminar Flow and the Particle Tracing for Fluid Flow packages in COMSOL, the velocity field distribution and the collection efficiency curve of the VI were obtained, shown in Figures 4 and 5 respectively. The maximum velocity is 7.16 m/s and the cut-off diameter is 2.5 \(\upmu\)m.
# Design of Positioning Mechanism Fit Clearances Based on On-Orbit Re-Orientation Accuracy
## 5 Conclusions  
In this paper, the re-orientation accuracy of an on-orbit replaceable optical unit was studied. Based on the angular displacement vector, the mathematical models of the relationship between fit clearances and theoretical rotation angle limits were deduced. When the relative position relationship of the positioning mechanisms was known, the fit clearances of positioning mechanisms as the key factor of re-orientation accuracy were designed using a matrix. This was a simple method to design the fit clearances. The rotation angle measurement method by the theodolites was introduced and error analysis was carried out. The analysis results showed that the differences between the measurement angles and the real angles were within limits. The experiment was designed and the gravity of the optical unit model was unloaded. The experimental results showed that the rotation accuracy around the \(x\)-axes of the optical unit was \(6.4^{\prime\prime}\) (by theodolite1) and \(6.2^{\prime\prime}\) (by theodolite2), the accuracy around the \(y\)-axes was \(5.7^{\prime\prime}\), and the accuracy around the \(z\)-axes was \(8.5^{\prime\prime}\). The results were within the index range, and there were some acceptable errors, which accorded with the theoretical deduction. The correctness of designing the fit clearances by mathematical models was proved. This study provides a reference for the design of the fit clearances of on-orbit replaceable units.  
Project administration, W.Z.; methodology, L.Y. and Q.L.; experiment and analysis, L.Y.; Q.L. and Z.S.; writing--Original draft, Q.L.; writing--Review and editing, Z.L.  
This research was funded by the Strategic Priority Research Program of Chinese Academy of Sciences, grant number XDA17010205.  
The authors declare no conflicts of interest.
## 5 Simulation Results
### Performance Comparison of RBD and Proposed Scheme  
The enhancement of the BER performance which is obtained by diversity gain and normalized throughput of the proposed scheme are shown in Figures 4 and 5, respectively. The number of data streams for RBD is \(N_{R}\) and QPSK is used at RBD. In proposed scheme, \(\frac{N_{R}}{2}\) data streams are transmitted and 16 QAM is used to achieve same data rate with RBD. In other words, since the number of data streams for the proposed scheme is reduced to the half number of the data streams for RBD to obtain the diversity gain, modulation level is increased to 16 QAM. The number of data streams for the proposed scheme is 4 in Figures 4 and 5.  
The BER performances are shown in Figure 4 with \(N_{T}=N_{R}=8\). The proposed scheme has better performance compared to RBD in spite of the higher modulation level at the proposed scheme. Since the proposed scheme can achieve the transmit diversity gain by reducing the number of total data streams, the BER of the proposed scheme is better than RBD in Figure 4. The proposed scheme has especially steep slope from 5 dB to 20 dB due to diversity gain. In a short range with small transmit power, the proposed scheme shows lower BER performance than RBD due to high modulation level. The BER performance of the proposed scheme decreases gradually from 20 dB.  
The normalized throughput performances are shown in Figure 5 with \(N_{T}=N_{R}=8\). The throughput performances are normalized according to maximum throughput. The proposed scheme reduces the number of the data streams for achieving the transmit diversity. Thus, the modulation level of the proposed scheme is increased to 16 QAM to achieve same data rate with RBD. Figure 5 shows that the maximum throughput performances of the proposed scheme and the RBD are same even though the proposed scheme transmits fewer data streams. Since the proposed scheme has better BER performance by obtaining transmit diversity, the proposed scheme can achieve maximum throughput with relatively lower transmit power. In other words, the proposed scheme which has lower computational complexity has maximum throughput with relatively lower transmit power compared to RBD.
# Analysis of Slope Stability in Ion-Adsorption Rare Earth Mine Under In Situ Leaching Condition
## 2 Methodology
### Stability Grade of Rare Earth Slope  
This study utilizes the safety factor obtained from the limit equilibrium method built upon finite element analysis to assess the stability of ion-adsorption rare earth mine slopes. According to the Chinese standard DZ/T0218-2006 [37], stability is classified into four levels: unstable, slightly stable, basically stable, and stable (Table 2). Here, F\({}_{\text{s}}\) represents the safety factor calculated from the profile, and F\({}_{\text{st}}\) denotes the allowable safety factor. This paper adopts F\({}_{\text{st}}\) = 1.1 as the allowable safety factor for slope stability under in situ leaching conditions to ensure the slope's stability and economic efficiency [23].  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Safety Factor** & **F\({}_{\text{s}}\) < 1.00** & **1.00 < F\({}_{\text{s}}\)\(\leq\) 1.05** & **1.05 < F\({}_{\text{s}}\)\(\leq\) F\({}_{\text{st}}\)** & **F\({}_{\text{s}}\)\(\geq\) F\({}_{\text{st}}\)** \\ \hline Stability State & Unstable & Marginally Stable & Substantially Stable & Stable \\ \hline \end{tabular}
\end{table}
Table 2: Grading of slope stability levels [37].