esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Simulation Results
The corresponding pulse information including the evolution map, AC trace, and optical spectrum of two-bound soliton are presented in Figure 9b1-b3, respectively. These simulated results indicated that SA with saturable absorption effect could induce the formation of CS pulse. \begin{table}
\begin{tabular}{c c c c c} \hline
**WDM** & **EDF** & **SMF** & **OC** & **SA** \\ \hline \(\beta_{2}\) = 4.5 ps\({}^{2}\)/km & \(\beta_{2}\) = 15.54 ps\({}^{2}\)/km & \(\beta_{2}\) = \(-12.2\) ps\({}^{2}\)/km & 10\% output & \(\alpha_{\mathrm{ss}}\) = 15\% \\ \(\Gamma\) = \(1.1\times 10^{-3}\) m\({}^{-1}\)W\({}^{-1}\) & \(\Gamma\) = \(3.0\times 10^{-3}\) m\({}^{-1}\)W\({}^{-1}\) & \(\Gamma\) = \(3.0\times 10^{-3}\) m\({}^{-1}\)W\({}^{-1}\) & i.e., T = 90\% & \(\alpha_{s}\) = * \\ L\({}_{\mathrm{WDM}}\) = 0.5 m & L\({}_{\mathrm{EDF}}\) = 0.5 m & L\({}_{\mathrm{SMF1}}\) = 0.5 m & Isat = * \\  & \(\Omega\)g = 40 nm & L\({}_{\mathrm{SMF2}}\) = 0.5 m & B = * \\  & g0 = * & L\({}_{\mathrm{SMF3}}\) = 4.5 m & & \\  & Psat,g = 2.3 W & & & \\ \hline \end{tabular}
\end{table} 
Table 1: Constant and variable parameters in the simulation. Figure 9: Numerical simulation of CS output pulse characteristics as a function of pump power using the ML CNT-SA parameters. **(a)** Single CS pulse evolution; **(b)** two-bound soliton state evolution; **(a1)**–**(a3)** are the simulated time evolution, AC trace and optical spectrum of the CS; **(b1)**–**(b3)** are the simulated time evolution, AC trace and optical spectrum of the two-bound soliton, respectively. To simulate the BL CNT-SA, two primary factors should be considered: the introduction of reverse absorption coefficient (\(\beta\) was set as 0.0015 W\({}^{-1}\)) and higher value of normal dispersion (\(-\)0.3D from Equation (5)). Stable mode-locking NLP pulse evolution generated in the fiber laser is demonstrated in Figure 10, with various gain coefficients (g\({}_{0}\) = 70 W\({}^{-1}\), 100 W\({}^{-1}\), and 150 W\({}^{-1}\), respectively). By increasing the gain coefficient from 70 to 150 W\({}^{-1}\), the NLP envelope broadens while the NLP spike remains nearly unchanged. These simulation results are in accordance with experimental results, illustrating the critical effect of reverse absorption in the NLP pulse operation state formation.
## 2 Materials and Methods
### Evaluation: Platform, Data Sets, Methods, and Metrics
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Data Set** & **Positive** & **Negative** \\ \hline moonInRing2U1 & 255 & 4122 \\ moonInRing2U2 & 147 & 3248 \\ moonInSemiRing2U1 & 56 & 2920 \\ moonInSemiRing2U2 & 169 & 3897 \\ twoMoonsMirror2U1 & 129 & 3746 \\ twoMonosMirror2U2 & 246 & 4538 \\ twoSemiRings2U1 & 72 & 2551 \\ twoSemiRings2U2 & 144 & 3391 \\ moonInRing2 NU1 & 484 & 4398 \\ moonInRing2 NU2 & 122 & 3952 \\ moonInSemiRing2 NU1 & 235 & 3809 \\ moonInSemiRing2 NU2 & 207 & 2747 \\ twoMoonsMirror2 NU1 & 194 & 3363 \\ twoMoonsMirror2 NU2 & 400 & 4135 \\ twoSemiRings2 NU1 & 315 & 4169 \\ twoSemiRings2 NU2 & 294 & 4178 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The numbers of positives and negatives objects in individual data sets. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Data Set** & **Temperature** & **Humidity** & **Light** & **CO2** &
\begin{tabular}{c} **Humidity** \\ **Ratio** \\ \end{tabular} \\ \hline occupancy\_12 & + & + & & & \\ occupancy\_13 & + & + & & \\ occupancy\_14 & + & & + & \\ occupancy\_15 & + & & & + \\ occupancy\_23 & + & + & & \\ occupancy\_24 & + & & + & \\ occupancy\_25 & + & & + & + \\ occupancy\_34 & & & + & + \\ occupancy\_35 & & & + & + \\ occupancy\_45 & & & & + & + \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Two-dimensional data sets consisting of the attributes used in the original occupancy data set. Figure 4: The flowchart of the geometrical divide of data particle belonging to two-dimensional feature space, extended by the introduced lemma and the new selection strategy of data particle to be divided. Information concerning the classification result of each sample was registered in the confusion matrix (CM) consisting of the following elements: TP--true positive, TN--true negative, FP--false positive, and FN--false negative. Expressing the efficiency of the classifier applied to the binary classification of imbalanced data sets required the use of a metric that would provide relevant information about the quality of prediction model. In accordance with that, the precision, recall, and F-measure were applied. Precision is expressed as \(\text{P}=\text{TP}/(\text{TP}+\text{FP})\), recall is described by formula \(\text{R}=\text{TP}/(\text{TP}+\text{FN})\), whereas F-measure uses both of them and is expressed by equation \(\text{F}=2\times\text{P}\times\text{R}/(\text{P}+\text{R})\).
# Metrics for Polyphonic Sound Event Detection
## 3 Intermediate Statistics and Averaging Options
### Averaging Options in Calculating Metrics  
Intermediate statistics can be aggregated in different ways: globally-irrespective of classes, or in two steps: first class-wise, then as an average over the results of the individual classes [33]. Highly unbalanced classes or individual class performance can result in very different overall performance when calculated with the two averaging methods.  
_Instance-based averaging_ or micro-averaging gives equal weight to each individual decision. In this case, each sound event instance (in event-based metrics) or active instance per segment (in segment-based metrics) has equal influence on the system performance. The number oftrue positives (\(TP\)), the number of false positives (\(FP\)) and the number of false negatives (\(FN\)) are aggregated over the entire test data, and the metrics are calculated based on the overall values. This results in performance values that are mostly affected by the performance on the larger classes in the considered problem.  
_Class-based averaging_ or macro-averaging gives equal weight to each class. Performance of the system on individual classes has equal influence on the overall system performance--in this case, the intermediate statistics are aggregated separately for each event class over the test data. Aggregated class-wise counts (\(TP\), \(FP\), \(FN\)) are used to calculate class-wise metrics. The overall performance is then calculated as the average of class-wise performance. This results in values that emphasize the system behavior on the smaller classes in the considered problem.
# Discerning Reality through Haze: An Image Dehazing Network Based on Multi-Feature Fusion
## 2 Related Work
### Attention Mechanism  
The attention mechanism, a computational model that imitates the pattern of human attention, primarily addresses the issue of selective attention in information processing. It allows neural networks to concentrate on essential parts of the information being processed while neglecting insignificant or irrelevant parts. To date, the attention mechanism has been widely applied in multiple deep-learning domains such as natural language processing, computer vision, and speech recognition, including classic structures like SE-Net [28], ECA-Net [32], CBAM [33], and SAM [34]. [PERSON] et al. [35] were the first to employ the attention mechanism for the resolution of computer vision problems in 2015, laying a solid foundation for the mechanism's development within computer vision. Since then, the application field of the attention mechanism has continually expanded, making it an indispensable technology in deep-learning tasks.  
In the task of single-image dehazing, the attention mechanism is utilized to compute the weights of different regions of the hazy image, enabling the network to focus on the areas most severely affected by haze. Moreover, the attention mechanism assists the network in striking a balance between global and local considerations. Global attention helps the network focus on overall features to restore the overall clarity of the image. In contrast, local attention emphasizes the recovery of details in local areas, enhancing the image's detailed effects, taking into consideration that both global and local attention can yield superior dehazing results. GridDehazeNet [36], inspired by SE-Net, introduced a multi-scale estimation method based on channel attention. This method effectively mitigated the bottleneck problem traditional multi-scale networks encounter due to information flow restrictions in the hierarchical structure, providing the network with more flexible information exchange and aggregation abilities. [PERSON] et al. [27] proposed a feature fusion attention network (FFA-Net) in 2020, addressing the issue of uneven haze density in different areas of hazy images by constructing a feature attention module combining channel and pixel attention mechanisms. However, FFA-Net does not perform well when processing images with large areas of color blocks, causing blurry image details and potential double-image effects. Moreover, the repeated invocation of the feature attention module leads to excessivecomputational resource consumption. [PERSON] et al. [37] were the first to propose a generic low-level visual U-Net backbone network based on MLP, combined with residual channel attention for image dehazing. While the attention mechanism played a pivotal role in enhancing dehazing effects, a balance must still be struck between computational resource consumption and improvements in dehazing results. Therefore, finding a more efficient attention mechanism to reduce computational resource demand and improve algorithm generalizability remains a significant challenge.
## 2 Materials and Methods
### Mixture Design  
To investigate the effect of the particle gradation (particularly particle size) of aggregate on the performance of AN-LAC, seven different gradation types of concrete, including three single-particle size gradation groups and four combined-particle size gradation groups, were designed according to the three basic particle size ranges of NSLA and the particle gradation based on GB/T 17431.1-2010 [30]. The gradation designs in numerical value and mixture proportions of the seven gradation types of AN-LAC are listed in Tables 3 and 4, respectively.  
The method for preparing concrete was based on GB/T 50081-2019 [31]. Before mixing, NSLA with high water absorption needed to be pre-wetted for 24 h (saturated water absorption state). Then, NSLA was rolled back and forth on a wet towel 8 to 10 times to make the surface dry and saturated. The manufactured sand and NSLA were first stirred for 1 min in the mixer, after which the slag was added and stirred for 2 min. Then, the alkali activator was added to the mixer and stirred for 2 min. Subsequently, the mixture was poured into molds and vibrated. The detailed process is exhibited in Figure 2.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Group**} & \multirow{2}{*}{**Slag**} & \multirow{2}{*}{**Sand**} & \multicolumn{2}{c}{**NSLA**} & \multirow{2}{*}{**NaOH**} & \multirow{2}{*}{**Water Glass**} & \multirow{2}{*}{**Water**} & \multirow{2}{*}{**Water**} \\ \cline{3-4} \cline{6-7}  & & & & **3-5 mm** & & & **6-10 mm** & **11-15 mm** \\ \hline AN-LAC-1 & 520 & 672 & 780 & - & - & 21.4 & 170.9 & 129.4 & 0.5 \\ AN-LAC-2 & 520 & 672 & - & 780 & - & 21.4 & 170.9 & 129.4 & 0.5 \\ AN-LAC-3 & 520 & 672 & 390 & 390 & - & 21.4 & 170.9 & 129.4 & 0.5 \\ AN-LAC-5 & 520 & 672 & 390 & - & 390 & 21.4 & 170.9 & 129.4 & 0.5 \\ AN-LAC-6 & 520 & 672 & - & 390 & 390 & 21.4 & 170.9 & 129.4 & 0.5 \\ AN-LAC-7 & 520 & 672 & 260 & 260 & 260 & 21.4 & 170.9 & 129.4 & 0.5 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Mixture proportions of AN-LAC (kg/m\({}^{3}\)).  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Particle** & **Bulk Density** & **Apparent** & **Cylinder Compressive** & **24 h Water** \\
**Size (mm)** & **(kg/m\({}^{3}\))** & **Density (kg/m\({}^{3}\))** & **Strength (MPa)** & **Absorption (\%)** \\ \hline
3–5 & 1215 & 2153 & 12.9 & 9.8 \\
6–10 & 1190 & 2093 & 10.8 & 12.1 \\
11–15 & 1163 & 2001 & 8.6 & 15.4 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Physical properties of NSLA.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Group**} & \multicolumn{3}{c}{**Gradation and Proportion (\%)**} & **Average Particle** \\ \cline{2-5}  & **2.36–4.75 mm** & **4.75–9.5 mm** & **9.5–16 mm** & **Size (mm)** \\ \hline AN-LAC-1 & 100 & 0 & 0 & 4 \\ AN-LAC-2 & 0 & 87 & 13 & 8 \\ AN-LAC-3 & 0 & 0 & 100 & 13 \\ AN-LAC-4 & 49 & 42 & 9 & 6.5 \\ AN-LAC-5 & 50 & 0 & 50 & 9.6 \\ AN-LAC-6 & 0 & 41 & 59 & 10.5 \\ AN-LAC-7 & 34 & 27 & 39 & 9 \\ \hline \hline \end{tabular}
\end{table}
Table 3: The sieving data and average particle size of each group of gradations.
## 3 Results and Discussion  
### Femtosecond Laser Irradiates Ag Nanoparticles Solder  
Figure 2 shows the SEM images of Ag solders before and after the femtosecond laser irradiation. The laser fluence are 29.25 mJ/cm\({}^{2}\), 42.25 mJ/cm\({}^{2}\), 55.25 mJ/cm\({}^{2}\), and 68.25 mJ/cm\({}^{2}\), respectively, and the irradiation time is 30 s in Figure 2a-h. Figure 2a-d shows the morphology of Ag solders before irradiation. Figure 2e,f shows that each of the nanoparticle's edges in the nano-solder appear to be slightly melted and blurry after irradiation. When the femtosecond laser irradiates the Ag nanoparticles, plasmon oscillation is generated on the surface of the nanoparticles. The intensity of the electromagnetic field surrounding Ag nanoparticles is increased, exhibiting nonlinear absorption of incident photons. The plasmon resonance enhances the photothermal effect to produce multiple \"hot spots\" around the Ag nanoparticles, leading to melting and deformation of the Ag nanoparticles' edge. However, the overall melting phenomenon in Figure 2e,f is not obvious. This is attributed to the low laser fluence and the weak plasmon photothermal effect between the nanoparticles. In Figure 2g, a large melting deformation between the nanoparticles is apparent, and the blurring phenomenon of the Ag particles edges has vanished. This results from the higher fluidity of the locally molten metal material under the higher laser fluence. The gap between the nanoparticles is filled gradually. The flowing molten solder acts as a bridge to connect the individual nanoparticles, thus achieving good bonding. In Figure 2h, the nanoparticles exhibit significant melting deformation as well as even overall fracture and shrinkage, which can be explained by the high laser fluence and the significant photothermal effect of plasma excitation resonance. The large melt deformation of the nanoparticles may cause the displacement of solders and poor nanowire-solder contact during the soldering process, which is detrimental to nanowire soldering. Through the comparison of melting morphologies of Ag nanoparticles solders, optimized melting of Ag solders can be obtained under a laser fluence of 55.25 mJ/cm\({}^{2}\).  
Figure 1: Schematic diagram of the femtosecond laser irradiation system.
## 2 Aims and Objectives
### Thermal System Aims and Objectives  
The thermal system is designed to ensure temperatures throughout the structure do not reach extremes which are greater than the operating ranges of the selected components [10]. This will ensure safe operation of the CubeSat and help minimize the risk of mission failure. Throughout its orbit the CubeSat will absorb large amounts of incident radiation, especially when exposed to direct solar radiation from sunlight [20]. This exposure will cause heating of the CubeSat therefore material selection is vital to minimize this heating effect. The background temperature of space is approximately 3 K. When in an area of eclipse this extremely low temperature is below the operating range of many of the components, particularly batteries which can only survive around 5 \({}^{\circ}\)C typically [21]. It may be necessary to incorporate a method of cooling and insulating components, to prevent these extreme temperatures affecting operation. Material consideration should also be taken into account, especially regarding the emissivity and absorptivity of the outer materials which act as a thermal interface with the incoming radiation [10].  
Thermal System Objectives
* Research existing thermal management systems and material selections for successful CubeSat flights.
* Investigate heat dissipation of internal electrical components and its impact upon the thermal system.
* Quantify the incoming radiation incident to the CubeSat and corresponding maximum and minimum temperatures.
* Develop thermal load cases for various configurations, identifying advantages and disadvantages.
* Calculate the time period of orbit around Earth at 600 km and the time spent in eclipse.
# Probabilistic Seismic Hazard Assessment of the Southwestern Region of Saudi Arabia
## 2 Methodology
### Ground Motion Prediction Equations
The coherence and compatibility of the three selected GMPEs were systematically assessed through a structured approach. Initially, the chosen attenuation models were standardized to operate on the Mw scale consistently. Subsequently, all selected models were adjusted to utilize the same definition for the distance term (Rrup), thus obviating the need for additional conversions of magnitude or distance. Ultimately, using the Vs,30 value, two soil classes were developed to describe the characteristics of the soil conditions. These classifications, which represented average Vs,30 values of 760 and 560 m/s, respectively, correlate with the B/C and C NEHRP site classes. These classifications distinguish from dense soils to soft rocks (class C) and extremely dense soils (class B/C boundary). Crucially, every one of the chosen GMPEs describes the site conditions in terms of Vs,30; so, no additional adjustments to this parameter are required.
# Plant Exosomal Vesicles: Perspective Information Nanocarriers in Biomedicine
## 5 Functions of Plant Nanovesicles  
The extracellular vesicles were previously believed to be mainly needed for cellular waste removal and do not have any important function. However, recent studies have shown that exosomes mediate intercellular communication by transporting various biologically active molecules in the organism. This issue is currently actively investigated in various animal and human models. Their exosomes play important roles in the regulation of developmental processes, activation of the immune system, and protective mechanisms in response to stresses, maintaining the pluripotency of embryonic stem cells, and in many other functions [63].  
The functions of nanovesicles in plants are mostly considered in terms of their protective function in the system of plant-pathogen interactions. The ability of plants to quickly respond to various pathogens is essential for their survival. Restructuring the signaling pathways, cytoskeleton, and cell wall, as well as increased synthesis of the defense compounds, lead to the formation of physical (modification of plant cell wall) and biochemical (defense-related molecules) barriers that are designed to resist infection [64]. Such changes can be carried out through the rapid and targeted delivery of the necessary molecules by vesicles. It has been shown that the fungal infection enhances the rapid accumulation of exosomes between the plasma membrane and cell wall in plant cells, indicating their important role in the immune response [41; 65]. For example, the vesicular structures containing polyphenic metabolites and hydrogen peroxide prevented infection of the barley leaves by the powdery mildew fungus _Blumeria graminis_[66]. During the infection of _Arabidopsis_ by a biotrophic fungus _Golovinomyces onothi_, the PEN1 and PEN3 proteins were transported by the exosomes and incorporated into the cell wall, acting as a protective barrier [67]. The transfer of miRNAs from the host plant to the pathogen, causing silencing of virulence genes, has also been described in the plant pathogens, such as cotton/_Verticillium dahliae_ and wheat/_Fusarium graminearum_[57; 58]. At the same time, pathogens can transport their own miRNAs in the invaded area, contributing to the suppression of the immune response and defense systems of their host plant [39]. The grain yellow rust pathogen _Puccinia striiformis_ produces miRNA-like RNA that suppresses the expression of defense genes in wheat [68]. The transfer of specific miRNAs of _Hyalopernospora arabidopsis_ and _Botrytis cinerea_ into the cells of _Arabidopsis thaliana_ suppresses the expression of AGO1 protein, thus disrupting the loading of the plant nanovesicles with protective miRNAs [69]. Notably, the plant pathogenic fungi also widely utilize the extracellular vesicles to transport the effectors through host barriers aiming to suppress the plant immunity [40].
# Mechanical Properties of Desert Sand-Based Fiber Reinforced Concrete (DS-FRC)
## 1 Introduction
However, desert sand from different regions may show significant differences, such as in physical properties and mineral compositions. It is essential to further study intrinsic effects of different desert sands on the mechanical properties of FRC. The cubic compression and the splitting mechanical properties of undisturbed desert sand-based fiber reinforced concrete (DS-FRC) were investigated by our research team [46; 47]. In these studies, the control groups without desert sand have been considered by orthogonal experiment. The results showed that compared with the river sand-based FRC, the compression and splitting strengths of DS-FRC slightly decreased with the increase of desert sand replacement rate (DSSR), especially when DSSR exceeds 40%. However, there is a lack of uniaxial tests to evaluate the mechanical properties and deformation performances of DS-FRC, and the components of matrices could be further optimized. Based on all of the above, this paper further studied the uniaxial mechanical properties of DS-FRC, aiming at promoting the full application of desert sand. The uniaxial tension and compression tests were conducted to investigate the effects of W/B, S/B and DSRR on the mechanical properties and deformation performances of DS-FRC cured for 28 d. In order to provide a better understanding about the action mechanism of desert sand and the microstructural change of DS-FRC, the chemical composition and the microscopic morphology of DS-FRC were analyzed. This research will provide valuable information to the uniaxial properties development of DS-FRC and make a foundation for future studies.