esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Experimental Setup  
Figure 1 schematically illustrates the experimental setup utilized in the current study. As shown, the OHPs used here are fabricated by bending the pyrex glass capillaries into the interconnected meandering manner, forming 10 U-turns and parallel vertical tubes. The pyrex glass capillaries have external diameter of \(D_{\rm o}\) = 6.0 mm and inner diameters \(D_{\rm i}\) = 1.0, 2.0, 3.0 mm, respectively. As depicted in Figure 1b, the OHP with the dimensions of 400 mm \(\times\) 185 mm is set vertically and heated at the bottom, which includes evaporator, adiabatic section and condenser with corresponding lengths of 100 mm, 25 mm and 275 mm. Before the experiment, the OHP is baked at 100 \({}^{\circ}\)C, evacuated to be 4.0 \(\times\) 10\({}^{-4}\) torr for 8 h by a vacuum pump, and then filled with methanol as the working fluid. The filling ratio is maintained at \(\phi\) = 47% in this work. For the evaporator, the Ni-Cr wire with diameter of 0.25 mm is wrapped on the outer tube wall to supply the uniform heating load for the OHP. The whole evaporator and adiabatic section are embedded into the insulation box stuffed with the aluminum silicate insulation fibers, so as to ensure the relative error of heating load \(Q\) within 4.9%. The whole experiment is conducted in an environment with a constant temperature of 15 \(\pm\) 0.5 \({}^{\circ}\)C, and thus the condenser of OHP can be cooled by the forced convection of the surrounding air via a cooling fan. By using an NEC TH9260 infrared camera (NEC Corporation, Tokyo, Japan) and the corresponding software, the infrared thermal images of the condenser during the operation of OHP are monitored, recorded and analyzed. The infrared camera possesses operation wavelength of 8-14 \(\upmu\)m and noise equivalent temperature difference (NETD) of \(\pm\)0.08 \({}^{\circ}\)C, as well as thermal image resolution of 640 \(\times\) 480 pixels. The emissivity of the condenser surface is corrected before the experiment via comparing temperature signals measured by the infrared camera and the K-type thermal couple with a measuring error of \(\pm\)0.1 \({}^{\circ}\)C. By checking the emissivity of condensation section, the deviation between the tested result of the condenser temperature and its real value via the infrared camera is less than 2.3 \({}^{\circ}\)C. The temperature of evaporator is measured by the thermocouples (diameter of 0.25 mm, OMEGA K-type with measuring error of \(\pm\)0.1 \({}^{\circ}\)C, Omega Engineering, Santa Ana, CA, USA) fixed at the bottom of the evaporator, as marked in Figure 1b. The evaporator temperature are read and recorded by an Agilent 34970A data acquisition switch unit (Agilent Technologies, Santa Clara, CA, USA) with 6.5-digit accuracy, which has a maximum relative error of 0.5%.
## 2 Material and Method
### Statistical Analysis  
The significance of differences in VIs and measured and modeled LAI caused by manipulation were tested by one-way analysis of variance (ANOVA) for every measurement day and each site separately. The \(t\)-test was performed to investigate the significance of differences between two sites for each day separately. Coefficients of determination (r\({}^{2}\)) for each couple of variables as well as root mean square error (RMSE) for modeled and measured SIF were derived from linear regression. All statistical analysis was performed in RStudio version 2022.02.0+443 (RStudio Inc., Boston, MA, USA).
## 3 Results and Discussion  
### Effect of Reaction Temperature and Time  
Reaction temperature plays a critical role in determining the yields of the depolymerized lignin products formed during the hydrothermal depolymerization process. Hence, the effect of reaction temperature on the depolymerization of KL using the (ChCl:ZnCl\({}_{2}\)) DES was evaluated. These experiments were conducted with a KL:DES ratio of 1:1 at various temperatures of 110, 130, 150, 170, 190, and 210 \({}^{\circ}\)C, each for a duration of 8 h (Figure 3A). At 110 \({}^{\circ}\)C, the yield of the liquid phase was 31%, while that of the RL was 69%. As the temperature increased to 130, 150, and 170 \({}^{\circ}\)C, the liquid phase yields increased to 36.2%, 38%, and 43.06%, respectively, while the RL yields correspondingly decreased to 63.8%, 62%, and 54.94%. Interestingly, at 190 \({}^{\circ}\)C, the liquid yield dramatically increased to 54.44%, while the RL yield decreased to 45.56%, indicating that higher reaction temperatures favor lignin depolymerization. This is because the elevated temperatures lead to a reduction in the viscosity of the DES [33], thus minimizing mass transfer limitations and consequently enhancing interactions between the DES and lignin. However, at 210 \({}^{\circ}\)C, the liquid yield substantially decreased to 26.33%, while the RL yield increased to 73.67%, suggesting the simultaneous occurrence of depolymerization and repolymerization, with repolymerization predominating at this temperature [34]. Hence, to maximize the liquid product yield, further reactions were conducted at 190 \({}^{\circ}\)C, as this temperature yielded the highest amount of the liquid product. To assess the impact of reaction time on lignin depolymerization, reactions were conducted at 190 \({}^{\circ}\)C for durations ranging from 4 to 10 h (Figure 3B). The reaction conducted at 190 \({}^{\circ}\)C for 4 h resulted in liquid and RL yields of 37% and 63%, respectively. Extending the reaction time to 6 h substantially increased the liquid product yield to 42.22% and decreased the RL yield to 57.78%. After 8 h, the liquid product yield increased dramatically to a peak value of 54.44%, while the RL yield dropped to 45.56%. However, after 10 h, the liquid phase yield declined to 38.70%, while the RL yield increased to 61.30%, likely due to the repolymerization of the degraded products. These results indicate that prolonged reaction times can hinder lignin degradation [35].
###### Abstract  
In the present work, green-composites have been developed from a partially biobased epoxy resin reinforced with flaxseed flour wastes. The attractive aesthetic appearance, similar to wood, and the balanced overall properties of the obtained composites may be interesting for use in sectors such as decoration, furniture or automotive industry.  
In the present work, green-composites from a partially biobased epoxy resin (BioEP) reinforced with lignocellulosic particles, obtained from flax industry by-products or wastes, have been manufactured by casting. In this study, the flaxseed has been crushed by two different mechanical milling processes to achieve different particle sizes, namely coarse size (CFF), and fine size (FFF) particle flaxseed flour, with a particle size ranging between 100-220 \(\upmu\)m and 40-140 \(\upmu\)m respectively. Subsequently, different loadings of each particle size (10, 20, 30, and 40 wt%) were mixed with the BioEP resin and poured into a mold and subjected to a curing cycle to obtain solid samples for mechanical, thermal, water absorption, and morphological characterization. The main aim of this research was to study the effect of the particle size and its content on the overall properties of composites with BioEP. The results show that the best mechanical properties were obtained for composites with a low reinforcement content (10 wt%) and with the finest particle size (FFF) due to a better dispersion into the matrix, and a better polymer-particle interaction too. This also resulted in a lower water absorption capacity due to the presence of fewer voids in the developed composites. Therefore, this study shows the feasibility of using flax wastes from the seeds as a filler in highly environmentally friendly composites with a wood-like appearance with potential use in furniture or automotive sectors.  
Fax seed; biobased epoxy; green-composite; waste valorization; size particle +
Footnote †: journal: Applied Soft. 2020, 10, 3688; doi:10.3390/app10113688
# 3D Reconstruction Based on Iterative Optimization of Moving Least-Squares Function
## 6 Conclusions  
We present a novel 3D reconstruction method based on iterative optimization of the Moving Least-Squares function. Our method employs an adaptive octree partitioning scheme and a GRU-based feature-optimization module to generate smooth and detailed 3D surfaces from point clouds, which solves the problem of generating accurate 3D surfaces from sparse point clouds. Extensive experiments on benchmark datasets demonstrate that our method is superior to several deep-learning methods in terms of reconstruction accuracy and visual quality. Ablation studies confirm the effectiveness of both the adaptive octree partitioning and GRU modules. Our method provides a valuable tool for generating high-quality 3D surfaces from point clouds.  
In future work, we aim to explore a more optimal shape-partitioning method that is resistant to noise interference, as, in some cases, existing adaptive octree partitioning methods unnecessarily partition the voxels of noisy point clouds, resulting in jagged 3D surfaces generated in noisy environments. Then, we will set different weights for different losses in the calculation of total losses to achieve better experimental results. Additionally, we will introduce the neural nuclear field to improve the network's generalization ability.  
Conceptualization, S.L. and J.S.; methodology, S.L.; validation, S.L. and J.S.; writing--original draft preparation, S.L.; writing--review and editing, S.L., J.S., G.J., Z.H. and X.Z. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Natural Science Foundation of Xiamen, China No. 350Z202373036, the National Natural Science Foundation of China No. 62006096 and No. 42371457; the Natural Science Foundation of Fujian Province No. 2022J01337 and 2022J01819, the Open Competition for Innovative Projects of Xiamen, 350Z20231038.  
We used publicly available datasets for all the experiments carried out in this paper. The ShapeNet dataset is available at [[https://shapenet.org/](https://shapenet.org/)]([https://shapenet.org/](https://shapenet.org/)) (accessed on 10 May 2024). The ABC dataset is available at [[https://deep-geometry.github.io/abc-dataset/](https://deep-geometry.github.io/abc-dataset/)]([https://deep-geometry.github.io/abc-dataset/](https://deep-geometry.github.io/abc-dataset/)) (accessed on 10 May 2024). The Famous dataset is available at [[https://github.com/[PERSON]/points2](https://github.com/[PERSON]/points2) surf]([https://github.com/[PERSON]/points2](https://github.com/[PERSON]/points2) surf) (accessed on 10 May 2024).  
The authors are very thankful to the editor and referees for their valuable comments and suggestions for improving the paper.  
The authors declare no conflicts of interest.
## 5 Discussion on Generation and Stability of Various Soliton Molecules
### Stability of Soliton Molecules  
The short-time stability of bound states can be characterized by measuring RF spectra. It is found that RF spectra of these bound solitons have almost the same signal-to-noise ratio (SNR, larger than 60 dB when 1 kHz span and 1 Hz resolution were set) at the fundamental mode-locking frequency as a single soliton. However, different bound states have different stabilities as far as long-term immunity to environmental perturbation is concerned. Some bound states could only preserve themselves for several minutes before they transformed to unbound states or other bound states. For comparison, some other bound states were able to maintain for at least half an hour or more under perturbations of the lab environment (change of temperature, fluctuation of pump power, etc.).  
Generally speaking, soliton molecules with smaller pulse separation have better long-term stabilities (Figure 21 as an example). It is easily understood, as smaller pulse separation guarantees stronger direct mutual interaction between solitons. This can be supported in theory that lower-energy-level (smaller separation) bound states have larger binding energy [7]. However, regarding bound states with similar separation but distinct phase differences, it is rather complicated to foresee which kind (\(\pi\), 0, \(\pi\)/2, or \(-\pi\)/2) is the most stable one. In some situations, the transformation of phase difference from \(-\pi\)/2 to 0 was observed (also see Figure 21), while in other situations seemingly endless mutual transformation between \(-\pi\)/2 and \(-\pi\) was observed.  
The spectral transition from one soliton-molecule state to the other is of great interest and very instructive. Experimentally, transformation from \(-\pi\)/2 to 0 was accompanied by overall blue-shift of the envelope of the modulated optical spectrum, while transformation from \(-\pi\)/2 to \(-\pi\) (from \(-\pi\) to \(-\pi\)/2) was accompanied by overall red-shift (blue-shift) of the envelope of the spectrum. These intriguing phenomena imply that transformation of bound states is closely related to slight  
Figure 21: Sequential spectral evolution from (**a**) to (**d**) of a two-soliton bound state under the lab environment without intentional change of experimental conditions. Evolution from (**a**) to (**c**) took several minutes; and (**d**) was stable for at least half an hour. Modulation period, pulse separation and phase difference are marked in the figures. (Reproduced with permission from [28]. © The Optical Society of America (Washington, DC, USA), 2013).  
change of optical spectra, which stems from change of gain spectrum of the active fibre under fluctuations of ambient temperature [72; 73]. Change of phase differences shows good flexibility of bound states to adapt to the environment. Note that phase differences of bound states were not rigorously equal to \(\pi\), \(0\) and \(\pm\pi/2\) in most cases. As we have shown in the simulation, high-order effects might play a vital role in the complex nonlinear dynamics.
# A Multi-Agent Deep Reinforcement Learning System for Government Interoperability
## 3 Methodology  
This study integrates multi-agent systems (MASs) with the Java Agent Development Framework (JADE) for agent-based modeling, employing deep reinforcement learning (DRL) to enhance governmental interoperability. The proposed system addresses the complexity of cross-departmental coordination by simulating interactions among various municipal administrative units, leveraging DRL capabilities to improve learning, decision making, and adaptability in administrative processes [16]. Furthermore, the integration of JADE with Python-based DRL provides a robust framework for strategic collaboration and agent interaction [17]. The following subsections detail the system's architecture, agent roles, communication protocols, and use case scenarios that form the basis of its development.
# Patch-Font: Enhancing Few-Shot Font Generation with Patch-Based Attention and Multitask Encoding
## 5 Experimental Results
### Computational Efficiency
#### 5.3.2 Results and Analysis  
Table 3 presents the proposed method's and baseline methods' computational efficiency results. Our method achieves a balanced trade-off between training and inference efficiency while maintaining competitive performance in font generation quality. Specifically, Patch-Font requires 74 h of training time, which is 49% less than FM-GAN and 14% less than MX-FONT, while maintaining comparable GPU memory usage (18 GB). In terms of inference time, Patch-Font performs second-best at 0.11 s per image, closely following FUNIT. These results highlight the resource optimization and practical applicability of the proposed method for real-world deployments.  
We excluded VQ-FONT and LF-FONT from this evaluation because they rely on separate multistage training processes, which are not compatible with the single-stage training setup of this evaluation. Their inclusion would require different experimental settings, making direct comparisons with the other methods unsuitable.
## 4 Results and Discussion  
### Story Drift Performance  
Figure 6a-c shows with thin lines the maximum inter-story drifts normalised by the story height \(h_{i}\) and expressed as a percentage (drift ratios) for each prototype under each near-fault ground motion. Also plotted in Figure 6 are the mean and mean plus/minus one standard deviation (SD). Comparing these maximum drifts with those obtained for prototypes N3 and N6 under far-field ground motions scaled for the same energy input (i.e., for the same values of \(V_{D}\)) in previous studies [9], it is found that the maximum drift in the upper stories remains basically the same, whereas the maximum drift in the first story increases significantly. More precisely, the mean value increases by about 30% and the mean plus one SD up to 35%. In spite of this, the performance of the structure is satisfactory, as discussed next.  
Figure 7 shows the cumulative distribution functions obtained by assuming a log-normal distribution of the maximum inter-story drift ratio. It can be seen that the probability of not exceeding the operational performance level (\(O_{\text{PL}}\)) defined in Structural Engineers Association of California SEAOC [32] is 78%, 73% and 87%, respectively, for prototypes N3, N6 and N9. This means that the retrofitted frames performed well, i.e., within the expected limits of current standards. Figure 8 shows another important parameter to consider: the residual drift ratio after the earthquake. As can be seen, the residual drift in the first story falls in most cases below the limiting drift of 0.2% proposed in FEMA-P-58 [33], again meaning a satisfactory performance of the retrofitted frame.  
Figure 6: Maximum inter-story drift ratios of prototypes N3 (**a**), N6 (**b**) and N9 (**c**).  
Figure 7: Cumulative distributions for prototypes N3 (**a**), N6 (**b**) and N9 (**c**).
## 3 Results
### Plasma Actuator Case
#### 3.2.1 Plasma Actuator Location  
The results based on the plasma actuator showed that the flow separation and the overall flowfield were changed due to plasma based control. Moreover, a reduction in flow separation was observed for the plasma located at \(x/c=0.66\). To test the plasma effect without changing its electric field strength or applied voltage frequency, additional analyses were completed by changing the plasma actuator location. The effect of changing the plasma actuator location is described in Figure 21 using the skin friction coefficient. Two specific locations were chosen: (1) upstream of the baseline separation point, i.e., \(x/c=0.63\), and (2) downstream of the baseline separation point, i.e., \(x/c=0.70\).  
In Figure 21, the skin friction coefficient for three different plasma locations is compared. For the skin friction in both cases with the plasma actuator located at \(x/c=0.63\) and \(x/c=0.66\), the line clearly crossed \(C_{f}=0\), thus demonstrating flow separation and flow reattachment. However, the line for \(x/c=0.7\) was different than those two positions, so it showed better flow quality in terms of flow separation. This was because the baseline flow separation was substantial at that location, and the plasma actuator positioned at \(x/c=0.66\) and \(x/c=0.63\) failed to eliminate the flow separation  
Figure 20: Plasma-induced instantaneous U-velocity at different time steps.  
completely. However, an improvement in reducing the separated flow was evident when the plasma actuator was located downstream of the baseline flow separation location.
# Density Functional Theory Study on the Adsorption of Co(II) in Aqueous Solution by Graphene Oxide
## 4 Study on the Mechanism of GO Adsorption Process
### Influence of External Environment on Adsorption
#### 4.2.1 pH
\begin{table}
\begin{tabular}{c c} \hline
**The Type of [GO...Co]** & **Binding Energy/Hartree** \\ \hline
[GO(COO)...Co]\({}^{+}\) & 0.5283 \\
[GO(O)s...Co]\({}^{+}\) & 0.4997 \\
[GO(O)..Co] & 0.2725 \\ \hline \end{tabular}
\end{table} 
Table 2: Adsorption energy of Co\({}^{2+}\) by GO containing different functional groups. The larger the binding energy value, the more energy released during the adsorption process, the easier the reaction will be, and the better the adsorption effect will be. It can be inferred from the simulation calculation results in Table 2 that under weakly acidic conditions, the carboxyl group on GO and the hydroxyl group on the base level have certain electronegativity, and electrostatic adsorption is the main force in the binding process with Co\({}^{2+}\). The epoxy group is more likely to bind to Co\({}^{2+}\) through coordination.
# M-Emu: A Platform for Multicast Emulation
## 3 Implementation
### Service-Forwarding Architecture
#### 3.1.3 Analysis of Service-Forwarding Architecture  
M-Emu's Service-Forwarding Architecture effectively solves the deficiency of NS4 architecture. The service module can create and monitor the cache queue so that the data plane of NS4 can process multiple packets at the same time, thus, supporting the emulation of packet scheduling. The algorithm of the service module is written in C++, which overcomes the deficiency of p4 language and enables the data plane of NS4 to deploy complex multicast protocols and algorithms. The Service-Forwarding Architecture provides sufficient centralized algorithm interfaces on the control plane and distributed algorithm interfaces on the data plane, which reduces the workload of emulations.
## 4 Results and Discussion
### Performance under Dark Conditions
#### 4.2.2 Anti-Fouling Performance under Dark Conditions  
In order to investigate the anti-fouling performance of the membranes in relatively long-term and dark conditions, each membrane was tested in the cross-flow apparatus. The fouling effect is quantified by the relative flux (\(J_{i}/J_{0}\)) and shown in Figure 5. It was found that, in the initial stage, the fluxes of the neat membrane and the membrane modified by polydopamine, decrease more rapidly than the others. This rapid flux decline is attributed to the relatively large contact angles. Following this, the flux of each membrane reaches its equilibrium. The membrane modified by TiO\({}_{2}\) using the polydopamine binding method reaches an equilibrium value of 95% after 30 min of filtration. The fluxes of the membranes modified by polydopamine and self-assembled TiO\({}_{2}\) stabilize at around 85% of the initial value after 2 h of filtration. After 8 h of filtration, the neat membrane retains around 75% of the initial flux. This fouling behavior is following the trend in the static BSA adhesion test (Section 4.1.3, Table 2): the membrane with good static BSA adhesion resistance has better anti-fouling filtration performance. The reasons for the fouling behavior are also consistent with the discussion in Section 4.1.3.  
When comparing the initial anti-fouling performance of the membranes modified by TiO\({}_{2}\) with both self-assembly and polydopamine methods, it can be found that the robust binding of TiO\({}_{2}\) as shown in our previous work [28], is crucial for maintaining a constant and good anti-fouling performance. A large fraction of the self-assembled TiO\({}_{2}\) can be removed by the water flow in the first hour of filtration [40]. A lower quantity of TiO\({}_{2}\) results in lower hydrophilicity and worse protein adhesion resistance. Figure 5 shows that the unstable bound TiO\({}_{2}\) cannot retain the same performance when the filtration time increases, although the membrane modified by self-assembled TiO\({}_{2}\) has a good anti-fouling performance in the initial 30 min of filtration. When further increasing the filtration time, the quantity of TiO\({}_{2}\) gradually decreases [40], which leads to a reduction in hydrophilicity and the loss of protein adhesion resistance. On the contrary, the polydopamine binding method can successfully overcome this limitation, maintaining a constant and good anti-fouling performance.