esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Simulation Results
### Single Objective Optimization
#### 3.1.1 Without Considering the Limitations of Power Exchange with Upstream Grid
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Time**} & \multicolumn{6}{c}{**Generation**} \\  & **MT (\&W)** & **FC (\&W)** & **PV (\&W)** & **WT (\&W)** & **Storage (\&W)** & **Grid (\&W)** \\ \hline
1 & 6 & 3 & 0 & 0 & 0 & \(-10\) & 53 \\
2 & 6.01 & 3 & 0 & 0 & 10 & 31 \\
3 & 6 & 3.03 & 0 & 0 & \(-10\) & 50.87 \\
4 & 6 & 3 & 0 & 0.05 & 10 & 31.93 \\
5 & 6 & 3.02 & 0 & 0 & \(-10\) & 57.97 \\
6 & 6 & 3 & 0 & 0 & 10 & 42.99 \\
7 & 6 & 30 & 0 & 0.14 & \(-10\) & 43.86 \\
8 & 6 & 30 & 0.16 & 0.03 & 0.11 & 37.66 \\
9 & 30 & 30 & 0 & 1.43 & \(-0.1\) & 14.88 \\
10 & 30 & 30 & 6.02 & 2.47 & 9.98 & 0.54 \\
11 & 30 & 30 & 8.36 & 7.02 & 10 & \(-7.38\) \\
12 & 30 & 30 & 9.56 & 8.33 & 10 & \(-12.89\) \\
13 & 30 & 30 & 0 & 3.13 & \(-10\) & 18.87 \\
14 & 30 & 30 & 16.84 & 1.9 & 10 & \(-17.74\) \\
15 & 30 & 30 & 0 & 0 & 10 & 6 \\
16 & 29.98 & 30 & 0 & 0 & \(-0.55\) & 22.42 \\
17 & 30 & 30 & 0 & 0 & 0 & 25.22 \\
18 & 30 & 30 & 0 & 0 & \(-7.71\) & 31.99 \\
19 & 6 & 29.99 & 0 & 0 & \(-10\) & 64.01 \\
20 & 6 & 30 & 0 & 0 & \(-3.37\) & 57.94 \\
21 & 30 & 30 & 0 & 1.04 & 10 & 5.96 \\
22 & 30 & 29.93 & 0 & 0 & 9.99 & 1.1 \\
23 & 6 & 30 & 0 & 0 & \(-10\) & 38.99 \\
24 & 6 & 3 & 0 & 0.48 & \(-10\) & 58.51 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Distributing power to reduce costs without considering the limitations of upstream network power exchange. Figure 2: Cost convergence diagram in different methods without considering the limitations of power exchange with upstream network. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Time**} & \multicolumn{6}{c}{**Generation**} \\  & **MT (kW)** & **FC (kW)** & **PV (kW)** & **WT (kW)** & **Storage (kW)** & **Grid (kW)** \\ \hline
1 & 6 & 3 & 0 & 1.43 & \(-9.88\) & 51.32 \\
2 & 6 & 3.03 & 0 & 0 & 5.3 & 31.7 \\
3 & 6 & 3 & 0 & 1.
###### Abstract  
This paper takes the ZF3806 working face of Shuiliandong Coal Mine in Birxian County, Shaanxi Province as the engineering background. Aiming at the problems of the development of surrounding rock cracks and roof breakage encountered in the process of roadway excavation and support and based on the composite beam theory, the method of layered grouting reinforcement of roadways is proposed according to the deformation and failure of the roadway roof and the internal drilling conditions. At the same time, combined with the splitting grouting mechanism, the roadway is strengthened and supported by layered grouting of \"shallow bolt grouting + deep cable grouting\". The \"shallow\" and \"deep\" form a complete and stable composite beam support structure. After grouting, the bending moments of \"shallow\" and \"deep\" support beams decrease by \(20.78\times 10^{6}\) N\(\cdot\)m and \(26.50\times 10^{6}\) N\(\cdot\)m, respectively. The support scheme is applied to the field test, and the grouting effect is analyzed and monitored. The research results show the layered grouting support scheme of \"shallow bolt grouting + deep cable grouting\" can significantly improve the structural integrity of the roadway roof. The displacement of the two sides is within the controllable range, and the support role of the bolt and cable is entirely played through grouting. The roof displacement of the roadway is reduced by \(65\%\) on average, and the bolt failure and steel belt fracture are significantly reduced, which effectively controls the deformation and damage of the roadway and reduces the maintenance cost of the roadway while ensuring safe mining. The study's findings could be useful in treating broken surrounding rock in other coal mine roadways.  
factured coal; roadway support; composite beam; layered grouting; stress gradient Article
# Within and Across-Language Comparison of Vocal Emotions in Mandarin and English
## 3 Results
### Across-Language Comparison of Vocal Emotions: Mandarin versus English
#### 3.2.2. Phonation Cues for Encoding Emotions in Mandarin and English  
Figure 4 illustrates the effects of Emotion and Language on comprehensive spectral cues. It is clear that the mean differences of CPP, H4 and H1-H2 among four emotions are greater in Mandarin than in English. The results of mixed-repeated measures ANOVAs showed that Emotion had a significant main effect on CPP and H2. Language had no significant main effect on all spectral cues. The interaction between Emotion and Language was significant on CPP, meaning that the two languages had different CPP patterns. To be specific, the difference of CPP between anger and neutral in both Mandarin and English was small since the mean values were close to 0. The CPP of fear and sadness in both languages was smaller than neutral emotion and that of happiness was greater than neutral emotion. This result indicated that fear and sadness were less periodic with increased spectral noise in both languages and Mandarin had a greater degree of changes compared to neutral emotion. The pattern of H1 was similar to that of mean pitch, where anger and happiness increased their H1; whereas, sadness lowered its H1 in Mandarin. The changes of H2 were similar in Mandarin and English. Anger and happiness increased H2. Sadness and fear reduced H2.  
To comprehend the physiological mechanisms of vocal emotions in Mandarin and English, three EGG cues were analysed. Figure 5 displays the effects of Emotion and Language on these EGG cues. As can be seen from the figure, the mean differences of these three cues among four emotions are greater in Mandarin than in English. In terms of Emotion, there were significant differences among  
Figure 4: Phonation-related acoustic measures of four emotions in Mandarin and English. Points indicate mean values and error bars 95% confidence intervals (Adapted from Figure 2 in Reference [31]).  
four emotions on CQ (F(3,24) = 20.77, \(p\) < 0.001), SQ (F(3,24) = 20.41, \(p\) < 0.001) and marginal significant difference on PIC (F(3,24) = 2.93, \(p\) = 0.054). However, the main effects of Language on these three cues were not significant. The interaction between Emotion and Language was significant on CQ (F(3,24) = 9.52, \(p\) < 0.001) and SQ (F(3,24) = 11.03, \(p\) < 0.001). Specifically, CQ showed a greater degree of variation among four emotions compared to neutral emotion in Mandarin than that of English. Anger and happiness increased CQ from neutral emotion, whereas fear decreased its CQ in both languages. However, the CQ of sadness was lower than neutral emotion in Mandarin but raised a little in English. Similarly, the changes of PIC in four emotions in English were close to 0 but greatly increased in Mandarin. For SQ, fear showed a significant increase in Mandarin, suggesting that fear had more symmetrical EGG waveforms.
# Accelerating Xinomavro Red Wine Flavor Aging Using a Pulsed Electric Field and Various Wood Chips
## 3 Results and Discussion
### Sensory Evaluation
The results with apple wood chips were particularly interesting, with PEF-2 and PEF-4 mitigating aggressive notes, resulting in a smoother, more palatable profile. The introduction of grassy and sweet elements implies a potential modulation of undesirable characteristics through PEF, providing a promising avenue for refining the flavor profile of Xinomavro red wine. Common oak wood chips, especially under PEF-3 and PEF-4, displayed a substantial enhancement in rustic and spicy elements, contributing to a more complex flavor profile. The extended afterstate observed in these treatments suggests that PEF might have facilitated the extraction of compounds contributing to the wine's sensory attributes. Chestnut wood chips presented a mixed response, with PEF-1 showing improvements in body and a dry finish, while PEF-2 and PEF-3 presented challenges with aggressive and rough elements. This variation highlights the delicate balance required when applying PEF to wines with certain wood types. The aggressive and dry characteristics observed in PEF-3 suggest a potential over-extraction of undesirable compounds, emphasizing the need for careful parameter optimization. Apricot wood chips, particularly under PEF-1, PEF-3, and PEF-4, exhibited a diverse array of flavors, including toasty notes, marmalade, and a well-balanced sweetness. The versatility of PEF in introducing these elements suggests a dynamic interaction between apricot wood and PEF, contributing to a rich and multi-layered sensory profile. Based on the above sensory attributes, the use of cherry wood chips and apple wood chips was found to be the most favorable, and, as such, was further investigated. Overall, the results emphasize the importance of tailored approaches when implementing PEF in Xinomavro red wine production. The variations observed across wood chip types and PEF treatments underscore the importance of tailoring the wood characteristics, PEF parameters, and the resultant sensory outcomes. The promising enhancements seen in certain treatments, particularly PEF-3 and PEF-4, suggest that application of PEF could expedite the aging process and enrich the flavor profile of Xinomavro red wine. However, there is need for further research to optimize further PEF parameters and wood chip combinations to achieve consistent and desirable sensory outcomes. This comprehensive understanding contributes to the broader discourse on innovative winemaking practices and opens avenues for future investigations in the realm of PEF applications in wine production.
# Recommendation System for a Delivery Food Application Based on Number of Orders
## 4 Proposed Recommendation System
### Clients' Preferred Restaurants  
The recommendation process is explained with a hypothetical example (see Table 2) of six clients (\(x,\)\(o,\)\(p,\)\(q,\)\(r,\) and \(s\)) and four restaurants (\(a,\)\(b,\)\(c,\) and \(d\)). First, we calculate all the clients' normalized vectors (see Equation (3)). Entries of normalized vectors correspond to the percentage of orders. All values in those vectors altogether must sum to 1.0 (see the rows in Table 2). The minimum percentage of orders, \(pmin\), was used to determine the preferred restaurants for each client. Suppose the percentage of orders of client \(x\) to a specific restaurant, \(a\), is more than \(pmin\). In that case, we consider that restaurant \(a\) is inside the preferences of client \(x\). We recommend using \(pmin=0.1\), meaning that restaurants with more than 10% of the orders are preferred. In the next section, we experiment with different values of \(pmin\). In our example (see Table 2), using \(pmin=0.1\), the preferred restaurants to client \(x\) are \(a\) and \(b\) since the percentage of orders are 0.19 and 0.80, respectively. A real example is shown in Appendix A.
# Cell-Free Massive MIMO Power Consumption with Serial Front-Hauls
## 2 System Model and Problem Statement  
### System Model  
A cell-free massive MIMO system, where \(M\) APs are deployed, is considered. A CPU connects to all the APs via a front-haul network that consists of \(N\) links. Figure 0(a) shows a generic cell-free massive MIMO deployment.  
If \(N=M\), there will be a dedicated front-haul link for each AP (see Figure 0(b)). Otherwise, if \(N<M\), there will be two APs or more serially connected. In the case of \(N=1\), this means that the front-haul is fully serialized (see Figure 0(c)). Additionally, \(K\) users are uniformly distributed in the scenario and served simultaneously.
# CFD-DEM Simulation of Dust Deposition on Solar Panels for Desert Railways
###### Abstract
[17] used Reynolds-averaged Navier-Stokes equations to simulate the three-dimensional flow field around a solar panel fixed on the ground, and the results showed that the pressure coefficient was basically consistent with the wind tunnel results proposed by [PERSON] [18]. [PERSON] et al. [19] studied the flow field around a roof solar panel by means of a wind tunnel experiment and a Reynolds-averaged simulation method, and the results showed that the simulation results were in good agreement with the wind tunnel experiment. [PERSON] et al. [20] found that the tilt angle of a solar panel will affect the amount of dust deposition, resulting in a change in power loss with the tilt angle. [PERSON] et al. [21; 22] used the CFD-DPM method to study the flow field and dust deposition around a solar panel installed on the ground, which simulated the trajectory of the sand particles but it was difficult to accurately reflect the rebound, capture and sliding process of the sand particles on the solar panel. [PERSON] et al. [23] investigate the dust deposition behavior around a ground-mounted solar PV panel with a discrete phase model in CFD simulations, and the influence of the wind speed, dust particle size and dust material on the sand deposition rate were investigated. In order to understand the law of particle deposition on photovoltaic panels and then to develop efficient dust removal technology, the deposition process of real dust particles on solar panels and the interaction between the dust particles and the panel surface must be simulated accurately, which can be realized by the CFD-DEM method. This method has been applied to some fields [24; 25] to simulate the dynamic contact process of individual particles. Therefore, this paper intended to introduce this method to analyze the deposition of atmospheric particles on photovoltaic panels. This paper is arranged as follows. Section 2 describes the detailed formulas of the CFD-DEM method and the computation conditions. Section 3 introduces the numerical simulation results of the deposited states of the clay and fine particles with different wind speeds and cohesion parameters and the non-uniform concentration distribution of the fine sand particles deposited on the solar panel due to the rolling movement of sand particles on its surface. Section 4 gives the conclusion. Through the simulation of wind flow and the dust trajectories around the solar panel, the number of deposits could be calculated based on the statistics of the number of particles with zero speed on the solar panel. Then, the deposition difference in the clay and fine sand on the solar panel under different wind speeds was obtained, and the non-uniformity of dust deposition on solar panels was also firstly reported.
## 4 Conclusions  
In this research, the effects of the tool overlapping and the tool path strategies were experimentally investigated on the surface roughness, surface morphology, MRR and profiles of the pockets machined on alumina (Al\({}_{2}\)O\({}_{3}\)) ceramic by using RUM. The conclusions were as follows:  
* The tool overlapping had significant effects on the surface roughness of the milled pockets. The surface roughness decreased with the increasing of tool overlapping percentage.
* Like roughness, the surface morphology varied considerably with the change of the tool overlapping. SEM images show that the smooth surface morphology was found at the higher levels of tool overlapping percentage (20-25%).
* The tool path strategies played an important role in surface Ra, Rt and MRR. The best values of Ra = 0.155 \(\upmu\)m and Rt = 1.432 \(\upmu\)m could be achieved by employing a mix of uni-directional and zigzag tool path strategy (Mix-2), along with the tool overlapping of 20%.
* The maximum MRR (0.49 mm\({}^{3}\)/min) could be attained at the spiral and Mix-1 milling strategies. This was because the surface area of the machined pockets was fully machined (with no un-machined regions) while applying these two path strategies.
* In general, it was inferred that RUM could be used for fabricating pockets in Al\({}_{2}\)O\({}_{3}\) with smooth surface finish and high dimensional accuracy.
* Several tool wear types were observed during RUM including bond fracture, rounding of the tool edge and plastic deformation.  
[PERSON] conceived the idea, designed and performed the experiments, analyzed the data and wrote the paper; [PERSON] edited the paper and provided critical advices on the research strategy; [PERSON]-[PERSON] and [PERSON] supervised the project. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Deanship of Scientific Research at King Saud University through research group no. RG-1439-009.  
The authors extend their appreciation to the Deanship of Scientific Research at King Saud University for funding this work through research group no. RG-1439-009.  
The authors declare no conflict of interest.
# Research on Thermal and Heat Insulation Properties of Aerogel Heat-Insulating Reflective Coatings
## 2 Experimental Studies  
### Specim Preparation  
There were three specimens tested in this test; the first board was a 10 mm thick plasterboard coated with a 1 mm thick ordinary white exterior wall coating called blank board; the second board was covered with a 1 mm thick aerogel coating on the surface of the plasterboard following the aerogel coatings' construction process, which is called aerogel board; the third board refers to the external thermal insulation construction practice, using the unique adhesive of Guerch building thermal insulation material to paste the 20 mm thick XPS thermal insulation board on the surface of the plasterboard, called XPS board. XPS is an extruded polystyrene board with the advantages of being lightweight, having low thermal conductivity, and being easy to construct. At present, XPS has been widely used in building exterior wall insulation. We chose XPS boards as a comparison because XPS has a lower thermal conductivity than similar insulation boards and is more accessible for us to cut. Here we need to explain that there are some unavoidable dimensional deviations in the fabrication process of the specimens. Figure 2 shows the designed thickness of each sample, and Table 1 shows the actual measured data of each sample. We will use the actual dimensions for later calculations.
# Ankle Joint Dynamic Stiffness in Long-Distance Runners: Effect of Foot Strike and Shoes Features
## 2 Materials and Methods
### Data Analysis  
Three-dimensional kinematics and kinetic data were analysed in Visual3D software (C-Motion, Inc, Rockville, MD, USA). A digital low-pass Butterworth filter (4 th order, zero lag) was used to smooth raw kinematic and kinetic data with cut-off frequency of 15 and 35 Hz, respectively. The ankle joint angle was calculated as the relative angle between the foot and the shank longitudinal axes, and subtracted to the ankle joint angle computed during subject's standing calibration posture (reference angle). Joint moments were computed around the ankle flexion/extension axis (the axis connecting the medial and lateral malleoli) using Newton-Euler inverse dynamics approach and normalized to body mass. Stance time was defined by gait events of initial and terminal foot contact (IC and TC) that were determined by a vertical ground reaction force threshold of 20 N. Stance time was normalised to 101 data points. The ankle (internal) moment was plotted as a function of the corresponding ankle angle (moment-angle plot), and the resultant curve was subdivided into three functionally relevant phases: early rising (ERP), late rising (LRP) and descending-phase (DP), similar to Crenna and Frigo [12]. The ERP was defined as the period between an ascending threshold of 0.2 peak plantar flexion moment and the first identified abrupt change in the statistical properties of the signal (i.e., mean and slope) going forward. The LRP was defined as the period between a threshold of 0.95 ascending moment to the first change in the statistical properties of the signal (i.e., mean and slope) going backwards.  
The slope of the best regression line interpolating the angle-moment curve in each phase represents the average ankle joint stiffness (\(\mathrm{K_{ankle}}\)) in each functionally relevant phase (Figure S1). The area under the rising component and the descending component of the curve was integrated using a trapezoidal approximation. This gives the work absorbed (\(\mathrm{W_{abs}}\), during the loading phase) and the work produced (\(\mathrm{W_{prod}}\), during the unloading phase), respectively. The net work (\(\mathrm{W_{net}}\)) produced was computed as the difference between \(\mathrm{W_{prod}}\) and \(\mathrm{W_{abs}}\). Finally, the work ratio (\(\mathrm{W_{ratio}}=\mathrm{W_{abs}}/\mathrm{W_{prod}}\)) was computed and was considered as a measure of muscle efficiency.
# Steering Mirror System with Closed-Loop Feedback for Free-Space Optical Communication Terminals
## 2 Steering Mirror Design and Trade-Offs
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Metric** & **Electrostatic MEMS** & **Voice Coil** & **Piezo-Stack** & **Stick-Slip Kinematic** \\ \hline Power Consumption & Low & High & High & Moderate \\ (active) & Low & High & Moderate & Zero \\ \hline Power Consumption & Low & High & Moderate & Zero \\ (stationary) & Low & High & Low & High \\ \hline Marror Size & Low & Moderate & Moderate & High \\ \hline Resolution & Moderate & Low & High & High \\ \hline Optical Power Handling & Low & High & High & High \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Qualitative comparison of fine steering mirrors [12]. Figure 2: Rendering of a steering mirror assembly, showing a top-down and side view. The assembly uses a bespoke kinematic mount, with a spherical joint enabling motion in the desired axis, controlled by two piezoelectric inertia actuators. The position of the spherical joint is marked in blue, with the positions of the actuators marked in red. The actuators are positioned 82 mm horizontally from the pivot point, and 30 mm vertically on either side of the pivot plane. The mirror has an aperture measuring 130 \(\times\) 90 mm. range. A significant advantage of these actuators is that they are self-locking when at rest, eliminating the need for constant power to maintain a set pointing angle. This characteristic is valuable in applications with tight power budgets, such as in CubeSats. The limitations of these actuators are the relatively slow travel speeds of around 3.5 mm/min, and the piezo hysteresis requiring external feedback for precise positioning.