esa-sceva/satcom-chunk-collection huggingface dataset:
# Low-Complexity Hybrid Optical OFDM with High Spectrum Efficiency for Dimming Compatible VLC System
## 1 Introduction
As a benefit, the symbols transmitted by the proposed DCHO-OFDM can be readily detected upon relying on a standard OFDM receiver, which significantly reduces the complexity at receiver compared to the existing advanced transmission schemes, such as HACO-OFDM and LACO-OFDM. The superiorities of the proposed DCHO-OFDM in terms of spectrum efficiency over its counterparts have been verified by our simulation results. The rest of this paper is organized as follows. Section 2 provides a review of the HACO-OFDM scheme in VLC. The detail of the proposed DCHO-OFDM regime is presented in Section 3. Our numerical results are discussed in Section 4, whilst our conclusions are drawn in Section 5.
# MpcNet: A Vision Transformer Network for Estimating Room Layouts from a Single RGB Panorama
## 1 Introduction
It is natural to think of a way to introduce ViT into 3D room layout reconstruction problems, using its shape sensitivity to better shape the layout prediction. However, drawbacks to the direct use of ViT for the 3D reconstruction of room layout remain: (1) The time complexity of calculation is high. The computation time complexity of the dot-product attention is \(O(L2)\), where \(L\) is the length of the input feature. (2) A large number of parameters. This not only makes training difficult, but also brings about the problem of gradient dissipation during gradient backpropagation. (3) Attention deficit. Although ViT has the advantage of a global receptive field, in theory, it has the problem of a limited receptive field in practice when analyzing its attention. To solve the above problems, we propose a novel neural network named MreNet. Generally speaking, to make structural inferences about an indoor layout, we introduce dot-product attention into the model and obtain a global receptive field similar to ViT. To improve the inference speed of the model, we use sparse attention instead of full attention to calculate dot-product attention. To accelerate the speed of training and the mixing of features of different granularity, we propose a feature connection mechanism to connect different layers. Finally, we propose a novel structure based on a larger convolution kernel to enhance its sensitivity to local shape and address the attention deficit. In general, the contributions of this paper are as follows:  
Figure 1: The relationships between objects and the room layout. We propose a novel neural network named MreNet, based on ViT [9], to model the structural problem of the room layout. By using this architecture, we obtain a larger receptive field than the traditional convolutional neural networks, so we obtain a better modeling effect. 2. We introduce a sparse attention mechanism to replace the traditional full attention mechanism in order to enhance the inference speed of the model and reduce the time complexity of operation. 3. We propose an assistant structure that enhances the local large receptive field and introduce it into our model to enhance the shape sensitivity of the model. 4. We propose a novel feature connection mechanism to solve the problem of the gradient disappearing in the process of training, and feature maps of different granularity can be obtained in different layers. The rest of the paper is organized as follows. A brief overview of related work is given in Section 2. Section 3 presents our proposed approach, MreNet. Section 4 presents our experimental results, and Section 5 concludes the paper.
## 2 Influence Factors of Service Performance of LSDM
### Comparative Analysis of Truss Rod Deformation in Ground and Space Environment  
To reduce the satellite's overall mass, the LSDM's truss rods usually consist of carbon fiber, which has low density, high strength, and high rigidity. However, due to their high length-to-diameter ratio, which can exceed 100, the truss rods are inevitably affected by gravity during ground assembly. In actual assembly, all truss hinges are implemented with gravity compensation, and the axial clearance between the truss rod and truss hinge is left. Therefore, the truss rod can be effectively modeled, as shown in Figure 5a.  
Figure 4: Assembly site schematic projection onto the X-O-Z plane.  
By analyzing Figure 5a, it can be seen that \(f_{1}\) and \(f_{2}\) are both \(0\), while \(F_{1}\) and are all \(-0.5G\). Based on this information, the deformation analysis of the truss rod can be performed as shown in Figure 5b, which considers the gravity \(G\) as a uniformly distributed load \(q\).  
As shown in Figure 5b, the truss rod's theoretical length is \(L\). The angle between the truss rod and the horizontal plane is \(\varphi,\varphi\in(-0.5\pi,0.5\pi)\). The truss rod bends under uniform load \(q\). The deflection can be expressed as \(\omega(l)\),where the \(l\) is the length of the rod from \(0\) to \(x\), and the value of \(l\) can be expressed as \(\frac{x}{\cos\varphi}\). Then, the actual length of the truss rod can be calculated as follows:  
\[S=\frac{l}{n}\left[\mathbbm{1}\left(\sqrt{1+\frac{G^{2}l^{4}\cos^{2}\varphi}{6 L^{2}l^{2}}}+\sqrt{1+\frac{25G^{2}l^{4}\cos^{2}\varphi}{S^{6}L^{2}l^{2}}} \right)+\sum_{i=1}^{n-1}\sqrt{1+\frac{G^{2}\cos^{2}\varphi}{4L^{2}l^{2}}\left( \frac{1}{3L^{i}l_{i}^{3}}+\frac{1}{2}l_{i}^{2}-\frac{1}{4}L^{2}\right)^{2}}\right] \tag{2}\]  
where \(E\) is the elasticity modulus which is determined by the material of the truss rod; \(l\) is the inertia moment, which is related to the cross-sectional shape of the truss rod; \(n\) denotes dividing the length \(L\) into \(n\) segments; and \(l_{i}\) can be expressed as follows:  
\[\left\{\begin{aligned} & l_{i}=l_{i-1}+\frac{L}{n}\\ & l_{0}=0\\ & l_{n}=L\end{aligned}\right. \tag{3}\]  
Figure 6 shows that the rod's length changes from the gravity environment to the service environment in space. The rod's length changes from its nominal length \(L\) on the ground to its actual length \(S\) in space. The distance between the hinges at both ends of the rod changes from \(L\) to \(S\), and the elongation \(\Delta L\) can be expressed as follows:  
\[\Delta L=S-L \tag{4}\]
# Non-Stationary Stochastic Global Optimization Algorithms
## 4 Results
### Evolutionary Strategies (es)  
#### 4.4.1 Concept  
Evolutionary Strategies (\(\mu/\rho+\lambda\))-es are a type of Evolutionary Algorithms that apply mutation, recombination, and selection operators to a population of individuals [22], see Algorithm 11. Every individual has two parts: the candidate solution (\(x\)) and the set of endogenous strategy parameters (\(s\)) used to control the mutation operator ([22]). An ES randomly initializes the population, (Line 2), and evolves both parts of the individual (Lines 5-9) up to certain ending-condition is fulfilled (Line 3). The set of endogenous parameters are exposed to evolution (Lines 6 and 8) before producing a child candidate solution (Line 7 and 9) to introduce variety. The new individual is a composition of a set of selected candidate solutions (Line 5). ES generates a new population of \(\lambda\) new individuals each generation (Line 4). Finally, ES selects a final population using two possible approaches. The (\(\mu+\lambda\))-es approach that selects the best \(\mu\) individuals among the \(\mu\) parents and \(\lambda\) children or the (\(\mu\),\(\lambda\))-es that selects the best \(\mu\) individuals from the \(\lambda\) children (notice that \(\lambda\geq\mu\) in this case). In this work, we study both of them.  
```
1:\(g=0\)
2:initialize(\(P_{q}^{(0)}\): \(=\{(y_{m}^{(0)},s_{m}^{(0)},F(y_{m}^{(0)})),m=1,\ldots,\mu\}\))
3:while\(\
eg\textsc{TerminationCondition}()\)do
4:for\(l=1\) to \(\lambda\)do
5:\(a_{l}=\textsc{Marriage}(P_{q}^{g},\rho)\)
6:\(s_{l}=\textsc{Recombination}_{s}(a_{l})\)
7:\(y_{l}=\textsc{Recombination}_{y}(a_{l})\)
8:\(s_{l}^{\prime}=\textsc{Mutation}_{s}(s_{l})\)
9:\(y_{l}^{\prime}=\textsc{Mutation}_{s}(y_{l},s_{l}^{\prime})\)
10:\(\bar{\Gamma}_{l}^{\prime}=F(y_{l}^{\prime})\)
11:\(P_{0}^{g}=\{(y_{l}^{\prime},s_{l}^{\prime},\bar{\Gamma}_{l}^{\prime}),l=1, \ldots,\lambda\}\)
12:if\((\mu,\lambda)\)then
13:\(P_{q}^{g+1}=\textsc{Selection}(P_{0}^{g},\mu)\)
14:else(\(\mu+\lambda\))
15:\(P_{q}^{g+1}=\textsc{Selection}(P_{0}^{g},P_{q}^{g},\mu)\)
16:\(g=g+1\)
```  
**Algorithm 11** Evolutionary strategies described by [22]
## 3 Results
### Human Kentinocyte Viability and Cytotoxicity  
The effect of the _Artemisia_ extracts--_Artemisia annua_ L. (AAn) _Artemisia absinthium_ L (AAb), _Artemisia dracunculus_ L. (ADr), was evaluated on HaCaT keratinocytes after a stimulation period of 72 h (Figure 2). The Control group is represented by cells treated with  
\begin{table}
\begin{tabular}{c c c c c c c} \hline
**No.** & **Compound Name** & \(\begin{array}{c}R_{\text{t}}\\ (\text{min})\end{array}\) & \(\begin{array}{c}[\text{M}-\text{H}^{\text{+}}]^{\text{+}}\\ (\text{\mu}/\text{z})\end{array}\) & \(\begin{array}{c}\text{AAn}\\ (\upmu/\text{g}\text{\,}\text{\,}\text{\,}\text{\,}\text{\,}\text{\,} \text{\  
the solvent dimethyl sulfoxide (the DMSO concentration did not exceed 0.5%). In Figure 2a, it can be observed that AAn, at concentrations ranging from 10 to 250 \(\mathrm{\SIUnitSymbolMicro\SIUnitSymbolMicro}\)/mL, produced a significant increase in cells viability. Only at higher concentrations, 500-1000 \(\mathrm{\SIUnitSymbolMicro\SIUnitSymbolMicro}\)/mL, was a decrease in cells viability noticed. A similar effect was obtained for AAb (Figure 2b) and ADr extracts (Figure 2c).  
The highest increase in keratinocytes viability was induced by the sweet wormwood, followed by the wormwood extract and last by the tarragon extract (AAn > AAb > ADr). In terms of decreasing the cells viability, the most significant reduction was obtained at the highest concentration, 1000 \(\mathrm{\SIUnitSymbolMicro\SIUnitSymbolMicro}\)/mL, for AAn--cells viability was 15.8 \(\pm\) 2.6% vs. Control; for AAb--cells viability was 22.6 \(\pm\) 0.4% vs. Control; for ADr--cells viability was 21.6 \(\pm\) 1.4% vs. Control.  
Figure 3 depicts the effect of the _Artemisia_ extracts on LDH release. At the tested concentrations, for all samples, no cytotoxic effect was observed compared to Control. Moreover, a decrease in LDH release was obtained following stimulation with the extracts. We determined the cytotoxic effect at these concentrations by analyzing the viability assay results, where an increase in cells viability was obtained and we intended to add a proof that the human keratinocytes were not affected by these extracts.
## 5 Conclusions
### Practical Impact and Future Directions
#### 5.3.2 Limitations and Mitigation  
There are three methodological limitations in this study and corresponding mitigation strategies:  
* The limited sample heterogeneity: To address this, the research team will expand the sample group to include K-12 students and special education needs groups through stratified sampling. A pilot verification project covering 12 provinces and cities has already been initiated.
* The high-cost barrier of immersive equipment: An optical transparent AR solution based on mobile terminals is under development, employing cross-platform lightweight algorithms to implement core functionalities, with the goal of controlling the single-machine cost below RMB 500 (the current prototype development cost has been reduced to RMB 780).
* The lack of longitudinal tracking for skill transfer effects: The study design includes a 36-month stepwise tracking mechanism, constructing a multidimensional skill retention database that includes cognitive behavior parameters and neurophysiological indicators. Standardized assessment tools have undergone validity and reliability testing ([PERSON]'s \(\alpha\) = 0.89).
## 3 Results  
Q-RPW model has simplified the simulation and performance evaluation of RPW system. As mentioned in previous section, it has halved the number of real random gaussian variables required to model the channel [17]. Since each symbol is received \(N_{p}\) times in RPW, this reduction translates to a high computational efficiency. Q-RPW has also improved the performance of RPW receiver by combining the signals received from two branches using quaternions. This method is superior to both SC and EGC because the orthogonality of received polarizations is conserved.  
Figure 5 shows the procedure adopted for simulation of quaternion model of RPW and BER evaluation of RP-MPSK. MATLAB simulation is performed, and the simulation parameters are shown in Table 1. The simulation results are divided into four parts: BER performance of RP-MPSK modulation, comparison of BER of RP-MPSK with other LPWAN modulation schemes, BER evaluation for recommended sampling rates (value of \(N_{p}\)) at receiver, and BER performance under interference and multipath conditions.
## 2 Material and Methods
### Sorption Study  
Sorption of metribuzin onto soil in the presence of the non-ionic surfactant Brij 35 was investigated through a soil equilibrium technique. Triplicate soil samples (1 g) were equilibrated with an aqueous solution (10 mL) of metribuzin at concentrations of (2.5, 5.0, 7.5 and 12.5 \(\mathrm{\SIUnitSymbolMicro m}^{-1}\)) in factorial combination with Brij 35 concentrations of 0, 0.5 and 5 g \(\mathrm{L}^{-1}\). All solutions contained 0.01 M CaCl\({}_{2}\) to mimic the ionic strength of groundwater [36]. The soil slurry was placed in a 50 mL centrifuge tube, and placed on a reciprocal shaker, operating at 200 rpm, for 24 h. The slurry was centrifuged at 2683 g for 20 min. Extraction and analysis of metribuzin proceeded, as described above. The proportion of metribuzin adsorbed was calculated by taking the difference between the amount initially present in solution and the amount remaining in solution, after equilibrium with the soil.  
The sorption coefficient was calculated as follows:  
\[K_{d}=\frac{C_{\mathrm{s}}}{C_{\mathrm{aq}}} \tag{1}\]  
where \(C_{\mathrm{s}}\) is the amount of metribuzin sorbed (\(\mathrm{\SIUnitSymbolMicro m}\) g\({}^{-1}\)), \(C_{\mathrm{aq}}\) is the solution concentration in \(\mathrm{\SIUnitSymbolMicro m}\)\(\mathrm{\SIUnitSymbolMicro m}^{-1}\), and \(K_{d}\) is the sorption coefficient (mL g\({}^{-1}\)).  
Organic carbon normalized coefficient values for metribuzin in the absence of surfactant and in the presence of surfactant were obtained as follows:  
\[K_{oc}=\frac{K_{d}}{f_{oc}} \tag{2}\]  
where \(f_{oc}\) is the organic carbon fraction of the soil (0.0297 g g\({}^{-1}\) for the soil used), and \(K_{oc}\) is the partition coefficient of the contaminant in the organic fraction of the soil (mL g\({}^{-1}\)).
## 2 Health Condition Monitoring
### Data Processing
#### 2.2.1 Data Preprocessing
Compared with the traditional detection method, the assumption of the program is less, and it is more suitable for the modern industrial process [26]. [PERSON] et al. proposed a data cleaning and monitoring algorithm that can screen the abnormal data caused by natural factors and human factors [27]. [PERSON] et al. presented a hybrid frame for detecting and removing extensive abnormal data [28]. The stacked auto-encoder method is widely used to monitor the contamination of abnormal values. The stacked auto-encoder has a powerful feature of functional extraction, which greatly retains the original information of the data [29]. The proposed method has superiority by comparing experiments with traditional abnormal value detection algorithms;  
Figure 2: Data preprocessing diagram. (3) Redundant data deletion  
The redundant data on the ship mainly includes two parts. One is that in the process of data acquisition and transmission, some duplicate data will be generated due to the influence of sensors, transmission networks, and other influencing factors. The other is that some data acquisition cycles are short, and the data does not change in a short time. Redundant data will increase the amount of system calculation and affect the effect of model analysis. Data preprocessing is a process to improve data quality and reduce noise. There are many sensors on the ship. The collected data has high dimensions and contains nonlinear data, which is very complex. At present, there is no general data preprocessing method suitable for all working conditions. Nowadays, most of the research methods are offline processing. More effective and stable ship real-time data processing methods are needed in the future, such as automatic data imputation and cleaning.
## 3 Results and Discussion
### Room-Temperature IL-Mediated Astaxanthin Extraction Using \(\alpha\)-Quartz NPLs  
To improve room-temperature astaxanthin extraction using [Emim]-based ILs, ultrathin \(\alpha\)-quartz NPLs were introduced to lactate the rigid cell walls of 90-day-old _H. lacustris_ cysts, based on findings from a previous report [13]. Brief incubation of the _H. lacustris_ solution for 5 min in an ultrasonic water bath facilitated sufficient contact between the algal cells and the \(\alpha\)-quartz NPLs. As a control, when the algal cysts were treated with \(\alpha\)-quartz NPLs followed by extraction with only with ethyl acetate for 2 h, the astaxanthin recovery efficiency was very low (4.7 \(\pm\) 0.1%), indicating that the cell-wall-disrupting effect of NPLs was not conducive to ethyl acetate extraction (Figure 2). Five-minute sonication of the algal solution without \(\alpha\)-quartz NPLs helped increase the astaxanthin recovery efficiency of ILs to 24.0-38.6%, irrespective of the IL type, compared to the recovery efficiency achieved with IL treatment alone (9.6-14.2%, Figure 1). This improvement is attributed to partial cell wall disruption by the high-pressure bubbles and acoustic cavitation effects and, consequently, the enhancement of IL permeability [9]. However, it should be noted that excessive sonication can lead to severe biodegradation and oxidation of bioactive astaxanthin by localized heating and free radical formation [3; 18]. In particular, free radicals readily break the hydroxyl and C=C bonds of the astaxanthin structure.  
Notably, using \(\alpha\)-quartz NPLs in room-temperature IL-mediated extraction, the astaxanthin recovery from _H. lacustris_ cysts improved significantly (49.8% for [Emim] SCN, 60.0% for [Emim] DEP, 80.7% for [Emim] HSO4, and 74.3% for [Emim] Cl) (Figure 2). These values were 4.4, 6.1, 8.4, and 5.2 times higher, respectively than obtained with the IL treatment alone (Figure 1). This finding clearly demonstrated that the cell-wall-lacerating effect of \(\alpha\)-quartz NPLs increased the cell wall permeability and astaxanthin extraction potential of the four [Emim]-based ILs from rigid _H. lacustris_ cysts. It also suggests that \(\alpha\)-quartz NPLs can be considered as effective cell-wall-disrupting tools for the applicatio  
Figure 2: Astaxanthin recovery efficiency from 90-day-old _H. lacustris_ cysts using 5-min-sonication-assisted \(\alpha\)-quartz nanoplate (NPL) pretreatment followed by treatment with four different [Emim]-based ILs with SCN, HSO4, DEP, and Cl anions for 2 h at room temperature (_ca._ 28 \({}^{\circ}\)C). As controls, the cyst cells were treated using only NPL or IL in a sonication bath for 5 min. Astaxanthin was recovered by subsequent ethyl acetate extraction at room temperature for 30 min.  
ILs in the extraction of various products, including edible oils, fragrances, biopolymers, biodiesel, bio-jet fuel, bioethanol, and biogas, using algal biorefineries [2, 20, 30, 31].
###### Abstract  
Remote sensing (RS) is a compulsory component in studying and monitoring ecosystems suffering from the disruption of natural balance, productivity, and degradation. The current study attempted to assess the feasibility of multisource RS for assessing and monitoring mountainous natural grasslands in Armenia. Different spatial resolution RS data (Landsat 8, Sentinel-2, Planet Scope, and multispectral UAV) were used to obtain various vegetation spectral indices: NDVI, NDWI, GNDVI, GLI, EVI, DVI, SAVI, MSAVI, and GSAVI, and the relationships among the indices were assessed via the Spearman correlation method, which showed a significant positive correlation for all cases (\(p<0.01\)). A comparison of all indices showed a significant high correlation between UAV and the Planet Scope imagery. The comparisons of UAV with Sentinel and Landsat data show moderate and low significant correlation (\(p<0.01\)), correspondingly. Also, trend analysis was performed to explore the spatial-temporal changes of these indices using Mann-Kendall statistical tests (MK, MKKH, MKKY, PW, TFPW), which indicated no significant trend. However, Sen's slope as a second estimator showed a decreasing trend. Generally, it could be proved that, as opensource data, Sentinel-2 seemed to have better alignment, making it a reliable tool for the accurate monitoring of the ecological state of small mountainous grasslands.  
multisource remote sensing; mountainous grasslands; UAV data; trend analysis; short-term data sets; vegetation indices; Armenia
## 4 Results and Discussion  
We tested the proposed method on one day data and calculated the three metrics to analyze the performance of the method. To further prove the performance of the algorithm, several comparison tests between our algorithm and another NILM method were conducted. Time consumption comparison of power trajectory estimation showed the estimation performance of OSVR, and estimation performance comparison between OSVR and SVR proved the improvement of the OSVR algorithm in power estimation.
# A CSAR 3D Imaging Method Suitable for Edge Computation
## 5 Conclusions  
CSAR is a typical 3D imaging mode of SAR that uses a small airborne platform to realize 3D imaging by observing targets in 360\({}^{\circ}\). However, the low efficiency of the BP 3D imaging algorithm limits its implementation for edge nodes, which is not conducive to the popularization and application of practical engineering. To fill this gap, a CSAR 3D imaging method suitable for edge calculation was proposed in this paper. By directly using image processing methods such as track ridge extraction, IRT, and Hough transform to image the target, our method replaces the phase compensation and accumulation of the azimuth-by-azimuth pulse of traditional BP imaging and greatly shortens the imaging time. The correctness and effectiveness of the proposed method were verified by the imaging results for the simulation and measured data. The proposed method can be applied to aircraft, small ground terminals, and other edge nodes to realize fast CSAR 3D imaging and provide a technical means for the efficient transmission and application of SAR perception information in the IoT.  
Conceptualization and writing--original draft, L.C.; methodology and funding acquisition, Y.M.; validation, Z.H.; formal analysis, B.L.; resources, Y.S.; writing review and editing, W.L. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Research of Military Internal Scientific Project under grant number KYSZQZL2019.  
Not applicable.  
The authors declare no conflict of interest.  
\begin{table}
\begin{tabular}{c c c} \hline
**BP (s)** & **IBP (s)** & **The Proposed Algorithm (s)** \\ \hline
23,974.43 & 8001.40 & 3809.32 \\ \hline \end{tabular}
\end{table}
Table 4: Time consumption comparison.