esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Experimental Validation
### Improved BIT* Algorithm with Adaptive Parameter Optimization for Optimal Path Planning
#### 4.1.3 Analysis of Visualized Results for the Improved Algorithm  
We utilized a 200,000 \(\times\) 200,000 map with 100% CPU utilization, offloading the third and fourth thread tasks to CUDA. Consequently, both the CPU and GPU employed a multi-threaded A* algorithm for parallel path searching. The CPU and GPU utilization data before and after optimization in this experiment are presented in Table 3.  
As can be observed from Table 1, offloading a portion of the planning workload to the GPU effectively alleviates the burden on the CPU, which is constrained by the limitations of the computer hardware. In conclusion, these results demonstrate that the optimized algorithm exhibits an enhanced capacity for handling large-scale map planning tasks while maintaining a high level of goal attainment performance.  
Figure 10: Path planning time comparison: single-thread vs. four-thread.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **Map Size (Grid** & **Reached** & **Obstacle Avoidance** & **CPU Usage** & **GPU Utilization (\%)** \\  & **Cells** & **Destination?** & ** Successful?** & **(Clock Speed)** & **GPU Utilization (\%)** \\ \hline Before Optimization & 2 \(\times\) 104 & Yes & Yes & 4.25 GHz & 0 \\ After Optimization & 2 \(\times\) 104 & Yes & Yes & 3.59 GHz & 56\% \\ \hline \hline \end{tabular}
\end{table}
Table 3: CPU and GPU utilization data.
# Multi-Scale Residual Depthwise Separable Convolution for Metro Passenger Flow Prediction
## 2 Methodology
### Construction of Relationship Graphs between Metro Stations  
In this section, we explore the relationship between metro stations from two perspectives. One is the track connectivity of adjacent stations, and the other is the correlation of passenger flow patterns between different stations. Considering the station-to-station relevant information from the network map and historical passenger flow, network structure correlation graph and passenger flow similarity graph are constructed to fully explore the complex inter-station correlations.
## 6 Conclusions  
The subsequent conclusions may be taken from the findings of the experimental and analytical investigations to suggest two novel ways to enhance the bond between the GFRP laminates and the concrete's surface.  
1. The geopolymer paste with and without short glass fibers outperformed epoxy in the strengthened beams. No debonding was observed between the GFRP laminate and the concrete surface, which is the most significant issue that frequently limits the strengthening of structures using GFRP laminate. On the other hand, compared with epoxy, geopolymer paste with and without short glass fibers reduced adhesive materials costs by more than 90%.
2. The failure loads of beams B1-0-GPP, B2-0.60-GPP, and B3-1.2-GPP were greater than control beam B0-Control by approximately 20.80%, 25.60%, and 31.40%, respectively, whereas the failure loads of beams B4-0-EP, B5-0.6-EP, and B6-1.2-EP were greater than the control beam B0-Control by approximately 16.90%, 26.90%, and 26.10%, respectively. The results showed that increasing the SGF ratio in the GPP had a clear effect on raising the capacity of the beam due to the enhanced interfacial bond shear strength. In addition, the GPP had a great effect on increasing the failure load capacity of the tested beams.
3. Based on the experimental results, no debonding occurred for laminates when using GPP as adhesive material with different SGF ratios. On the contrary, there was a debonding when using EP as adhesive material.
4. The maximum deflection of the tested beams B1-0-GPP, B2-0.6-GPP, and B3-1.2-GPP was less than the control beam by approximately 14.60%, 6.90%, and 6.20%, respectively, whereas the maximum deflection of the tested beams B4-0-EP, B5-0.6-EP, and B6-1.2-EP was less than the control beam by approximately 19.30%, 5.92%, and 17.10%, respectively. This showed that the GPP as adhesive material pastes enhanced the maximum beam's deflections better than EP.
5. The ductility factor of beams B1-0-GPP, B2-0.6-GPP, and B3-1.2-GPP was larger than corresponding beams B4-0-EP, B5-0.6-EP, and B6-1.2-EP by approximately 5.80%, 13.60%, and 21.40%, respectively. This showed that the GPP as adhesive material pastes enhanced the beam's ductility factor more than EP.
6. The experimental findings and FE predictions are shown to be in good agreement. Due to the complexity of using the cohesive model in modeling the GFRP laminate-concrete interface, there was a slight variation in the results.
# Methods for Aggregation and Remuneration of Distributed Energy Resources
## 1 Introduction
### Background  
Although the term aggregator usually only refers to the manager of consumers, at the same time, this entity can also be a virtual power plant, i.e., a manager of multiple generators or an aggregator of producers [1; 2; 3].  
An aggregator of producers usually deals with the management of distributed generation, which is defined in the European electricity directive (2009/72/EC) as \"generation plants connected to a distribution system\".  
Aggregators can be of several types, for which different responsibilities are assumed [4]:  
* Parallel Aggregator--can participate at the same time in distinct markets (electricity, water, heat);
* Large-scale Aggregator--can aggregate large dimension production units that are connected in HV or VHV;
* Micro Aggregator--aggregates small production units;
* Global Aggregator--aggregates both production and consumption units.  
In this paper, it is considered that the aggregator is of a micro and global type, dealing with small production and consumption resources.  
The aggregator's role starts with the scheduling of its resources. However, the main features are the aggregation and remuneration, namely, on which basis these are performed [5,6]. The aggregation process defines how the resources are joined together and thus the final energy scheduled per group. The aggregator can then use this energy in an auction in energy markets, giving the possibility of negotiation at the level of larger resources when comparing with individual consumers or distributed generators [7,8].  
The goal of an electric power system is always to provide electricity to its consumers, taking into account certain levels of security and quality. For the aggregator, the consumers are seen as a double-faced resource, since they have to be supplied by a given amount, but can provide flexibility regarding that consumption [9,10]. This gives robustness to the aggregator's operation, allowing him several options of scheduling and load management [11, 12, 13]. Distributed generators allow a similar flexibility, because of the penetration of renewable energy sources they provide. These resources are more easily placed in and out of the network's operation, with reduced costs for the aggregator, when compared with thermal or other major power plants.
###### Abstract  
This study investigates the potential increase in flood hazard in the city of Elblag. Poland, due to the climate-induced intensification of wind surges in the Vistula Lagoon. Using the HEC-RAS 2D (version 6.6) model--typically applied to riverine systems but here adapted for wind-driven lagoon dynamics--we simulate both historical and hypothetical storm events to evaluate water level changes under varying wind speeds. Model validation was performed using the January 2019 surge event, demonstrating strong agreement with observed water levels (NSE > 0.93). Subsequent simulations using synthetic wind scenarios show that extreme NE winds of 35 m\(\cdot\)s\({}^{-1}\) could raise water levels above 3.5 m asl, significantly surpassing warning and alarm thresholds. The results reveal a non-linear response between wind speed and water accumulation, underscoring the elevated hazard for low-lying areas such as Zuawy Elblaskie. The novelty of this study lies in the innovative application of HEC-RAS to a wind-driven lagoon environment and in the generation of synthetic surge scenarios for climate resilience planning. These findings provide critical insight for improving flood risk assessment and infrastructure adaptation in the face of ongoing climate change.  
Vistula Lagoon; Elblag; wind surge; flood hazard; climate change; HEC-RAS Article
# _Photonics_
## 2 Basic Theory  
_Design and Simulation_  
Two field components are there for an electromagnetic wave reflected from a metasurface; one of the same polarization is known as a co-polarized reflected field, and the second one is known as a cross-polarized reflected field orthogonal to the incident polarization. The isotropic reflective metasurfaces of low cross-polarized and co-polarized reflection components are widely applied for electromagnetic wave absorption. By breaking the symmetry of the isotropic unit cell, the cross-polarized coefficient is increased due to the anisotropic impact imposed by the geometry. Hence, it describes the conversion of electromagnetic waves from y-polarized to x-polarized or vice versa. Using a similar concept, based on a stair-like unit cell, we designed an ultra-wideband and extremely effective reflective metasurface. The proposed metasurface comprises three resonators. Each resonator is composed of the joining of five copper patches of the same length and width in a stair-like pattern. The gap between the right and left resonators from the middle resonator is 0.1 mm from their top sides, as shown in Figure 1, where P = 6.2 mm, a = 1.5 mm, b = 1.3 mm, c = 0.5 mm, d = 1 mm, e = 0.2 mm, f = 0.5 mm, g = 1 mm, h = 1.6 mm, and i = 0.5 mm are the physical dimensions of a unit cell. Three layers comprise the suggested unit cell: the middle layer comprises FR4 with a thickness of h = 1.6 mm, a dielectric constant, and a loss tangent of \(\varepsilon_{r}\) = 4.3 and tan\(\delta\) = 0.025, respectively, while the top and bottom layers are made of copper and have a thickness of 0.035 mm and an electrical conductivity of 5.80107 S/m. The CST Microwave Studio (2021) simulation platform is used for analyzing and designing the proposed polarization converter. The simulation of the unit cell is run by a built-in frequency domain solver.
## 5 Simulation
### Varying Packet Generation Rate
#### 5.2.2 Average Packet Loss  
As shown in Figure 15, the average packet loss of WEAMR is lower than AODV and AOMDV. WEAMR is capable of handling a higher throughput hence the result for variable number of connections and variable packet rate are similar. Hotline topology enhances the packet success ratio manifolds as compared to traditional _ad hoc_ wireless routing, as shown in Figure 15.
## 2 Proposed FP-AFPMG and Optimization Process
### Optimization of Rotor Poles  
To reduce the THD of the AFPMG, [15] proposes the modification of the permanent magnet by adding an arc height facing the air gap. From their study, the THD of the generated voltage (\(E_{f}\)) can be decreased by 26.3% because of more sinusoidal flux density in the air gap when compared to the conventional model. Besides arc height, in this study, the pole width to pole pitch ratio (\(\alpha_{i}\)) and the slot opening width (\(s_{o}\)) depicted in Figure 8a,b, respectively, are also modified. Four different \(\alpha_{i}\) of 0.8, 0.85, 0.9, 0.95 and four different \(s_{o}\) of 4.5 mm, 7 mm, 9.5 mm, 12 mm are proposed in this study. The results of THD obtained from a transient solution type by connecting the generator with a resistive load are tabulated in Table 2.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \multirow{2}{*}{\(\alpha_{i}\)} & \multirow{2}{*}{\(s_{o}\)} & \multicolumn{8}{c}{**Harmonic Order**} & \multirow{2}{*}{**THD (\%)**} \\ \cline{3-3} \cline{5-8}  & & **1** & **3** & **7** & **9** & **11** & **13** \\ \hline \multirow{4}{*}{0.8} & 4.5 & 39.3687 & 8.308 & 0.1955 & 0.4424 & 0.0317 & 0.0872 & 21.1401 \\  & 7 & 38.6705 & 8.7878 & 0.2238 & 0.4597 & 0.0187 & 0.0846 & 22.76435 \\ \cline{1-1}  & 9.5 & 37.6329 & 9.1347 & 0.2907 & 0.4261 & 0.045 & 0.0316 & 24.31228 \\ \cline{1-1}  & 12 & 36.3404 & 9.3068 & 0.42 & 0.3252 & 0.0554 & 0.0071 & 25.6522 \\ \hline \end{tabular}
\end{table}
Table 2: Harmonic magnitude of the combination between \(\alpha_{i}\) and \(s_{o}\).  
Figure 8: Proposed optimization of rotor pole. (**a**) Pole width to pole pitch ratio (\(\alpha_{i}\)), (**b**) stator slot opening width (\(s_{o}\)).  
Figure 7: Five-phase stator winding configuration. (**a**) Star of slot, (**b**) armature winding arrangement in the stator slot.  
From Table 2, the 5 th harmonic is eliminated because the generator is connected in a star connection, and the 3 rd harmonic is more dominant compared to the 7 th, 9 th, 11 th, and 13 th. Equation (6) is formulated to calculate the THD.  
\[\text{THD}=\frac{\sqrt{V_{2}^{2}+V_{3}^{2}+V_{4}^{2}+\ldots}}{V_{1}^{2}} \tag{6}\]  
In Equation (6), \(V_{n}\) is the nth harmonic of the terminal voltage (\(V_{t}\)) and \(V_{1}\) is the fundamental harmonic of \(V_{t}\). From Table 2, because the combination of \(\alpha_{i}\) = 0.95 and \(s_{o}\) = 12 mm gives the smallest THD of 1.55%, this combination is chosen to be the optimal rotor pole combination in this case.
# Vehicle Lane Change Models--A Historical Review
## 2 Vehicle Lane Change Models
### Physical Models of Lane Change  
The physical models of lane change are mainly based on the characteristics of the vehicle kinematics and dynamics to describe lane change behavior. In the physical models of lane change, factors such as vehicle speed, acceleration, and position are considered, and the motion state and trajectory change of the vehicle are described using mathematical equations. The common physical models of lane change are mainly divided into three types: kinematic, dynamic, and vehicle control.
## 4 State of Art
### Hybrid Sensors  
This type of device tries to explore the combination of the optical fiber sensors and the conventional current transducers. The main advantage is that as the insulation is provided by the fiber optic itself, and the cost of the insulation needed for a conventional current transducer would be greatly reduced [1]. Sensing systems using hybrid devices consist mainly of a conventional electrical or electronic current sensor, a current transformer (such as Rogowski coil) or a photo-electronic device, but interrogated by an optical fiber system. The principal element of this combination is an electro-optic converter which transforms electrical current modulation into optical modulation [1].  
To control the sensing configurations, diverse optical modulation schemes have been reported in recent years, such as optical phase modulation [85], intensity modulation [86], frequency modulation [87], polarization modulation [1] and chromatic modulation [88]. Figure 17 shows an experimental configuration for this type of sensor.  
Figure 17: Typical setup of a hybrid sensor configuration.  
Figure 16: Structure diagram of magnetic filled HC PCF FP sensor proposed by [PERSON] _et al_. [83].
# Recent Advances in Volatiles of Teas
## 7 Determination of Tea Volatiles  
Determination of tea volatiles is very important in assessing tea quality, and it involves volatile extraction and instrumental analysis. The extraction methods can be categorized into solvent extraction, distillation sampling and headspace solids-phase microextraction (HS-SPME). There are great differences in volatile composition and concentration between various extraction methods. During solvent extraction, tea leaves are directly extracted in organic solvents, such as diethyl ether, pentane, hexane and ethyl acetate. Solvent extraction gives a complete profile of volatiles [31], but it always contains pigments and lipids, which interfere with the analytic instruments. Simultaneous distillation and extraction (SDE) is the most commonly-used distillation method for sampling tea volatiles [40]. SDE gives a high yield of volatiles, but its disadvantage is the presence of artifacts formed during the distillation process due to thermal reactions, oxidation and degradation [40]. To minimize  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Processing Stage 2** & **A** & **B** & **C** \\ \hline \multirow{2}{*}{_Trans-_2-hexenal_} & Green tea & 52.619 \(\pm\) 3.284 & 0.482 \(\pm\) 0.139 & 0.205 \(\pm\) 0.111 \\  & Black tea & 52.619 \(\pm\) 3.284 & 60.906 \(\pm\) 4.969 & 14.261 \(\pm\) 0.235 \\ \hline \multirow{2}{*}{Geraniol} & Green tea & 13.997 \(\pm\) 2.845 & 0.982 \(\pm\) 0.039 & 0.844 \(\pm\) 0.05 \\  & Black tea & 13.997 \(\pm\) 2.845 & 14.885 \(\pm\) 0.425 & 15.05 \(\pm\) 0.297 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Effect of processing on the concentration of partial volatiles in black tea and green tea 1.  
the thermal reactions, steam distillation under reduced pressure (SDRP) at low temperature was developed to replace SDE [61]. HS-SPME is based on the adsorption and desorption of volatiles on SPME fibers coated with various adsorbents, such as 65-um polydimethylsiloxane divinylbenzene. The SPME fiber was exposed to the headspace of the dry tea or tea liquor sample for about 60 min and then directly inserted into the GC/MS injector for desorption and testing [38]. The results of HS-SPME are closely related to sensory assessments, but are greatly influenced by sampling temperature and time. Therefore, it is crucial to maintain consistency in these factors.  
GC/MS is usually used to analyze the volatile samples. Owing to the lack of the full set of authentic reference substances, the tested volatiles are commonly tentatively identified by the MS method and the concentration levels are always expressed as the ratio of the peak area of the detected volatile to that of an internal standard substance [55]. Therefore, the results from different sources are not comparable.
## 4 Analysis Example and Methods
### Results from the BHP Vibration Experiment
#### 5.3.3 Vibration Experiment Results for the BHP with Different Elastic Layer Thicknesses  
The radial acceleration amplitude for the pipe wall at the middle node (point P) in each BHP is shown in Figure 20.  
Figure 19: Flow pulsation curve for the BHP outlet. (**a**) RTV as the elastic layer; (**b**) RTV-SWCNTs composite as the elastic layer.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**No.**} & \multirow{2}{*}{**Length (mm)**} & **RTV** & **RTV-SWCNTs Composite Materials** & \multirow{2}{*}{**Pulsation Reduction (\%)**} \\ \cline{3-3} \cline{5-5}  & & **The Standard Deviation for Flow Pulsation** & & \\ \hline
1 & 130 & 0.319 & 0.248 & 22.3 \\
6 & 180 & 0.301 & 0.216 & 28.2 \\
7 & 230 & 0.2702 & 0.1779 & 34.16 \\
8 & 280 & 0.1824 & 0.1296 & 28.9 \\
9 & 330 & 0.128 & 0.0913 & 28.7 \\ \hline \hline \end{tabular}
\end{table}
Table 9: The absorption effect of flow pulsation in the BHPs with different lengths of pipeline.  
The radial acceleration amplitude at point P in the two-layer BHP with RTV as the elastic layer and the three-layer BHP with RTV-SWCNTs composite as the elastic layer decreases as the thickness of the elastic layer increases. This indicates that elastic materials (RTV or RTV-SWCNTs composites) can suppress pipeline vibration by absorbing the flow pulsation. With the increase in the elastic layer thickness, the effect of the vibration suppression is more obvious.  
In reference to Section 5.2.1, Figure A4 (Appendix C) compares the amplitude of the radial acceleration at point P in the BHPs with RTV or RTV-SWCNTs composite as the elastic layer when the thickness of the elastic layer is the same.  
In Figure A4, it can be seen that the radial acceleration at point P in the three-layer BHP with RTV-SWCNTs composite material as the elastic layer is significantly lower than that of double-layer BHP with RTV as the elastic layer. The data on the vibration suppression effect in the BHP with different thicknesses of the elastic layer is shown in Table 10.  
It can be seen that the standard deviation for the radial acceleration in the three-layer BHP with SWCNTs is significantly lower than that of double-layer BHP with RTV as the elastic layer. As the thickness increases, the standard deviation for the radial acceleration decreases, and the effect of the pulsation absorption increases. When the thickness of the elastic layer is 15 mm, the percentage of the pulsation reduction is the largest, and the vibration suppression effect in the BHP is the best. This conclusion lays the experimental foundation for the further optimization of BHPs.
## 4 Results
### Condition 1  
Figures 15-17 represent the frequency variation, inter-tie-line power change and ACE, respectively, for the three different areas due to a 0.1 per unit (0.001 MW) change in step load demand in area 1. An increment of 0.1 per unit (0.001 MW) step load in all areas applied under four different cases was investigated. It was found that frequency variation, tie-line power and ACE rapidly returned to zero using the type-2 fuzzy PI approach. The performance for the above case study is illustrated numerically in Table 2. Its obvious from Table 2 that type-2 fuzzy outperformed fuzzy PI and conventional PI approaches. In this table, \(\Delta\)f\({}_{1}\), \(\Delta\)f\({}_{2}\) and \(\Delta\)f\({}_{3}\) are changes in frequency; \(\Delta\)ACE\({}_{1}\), \(\Delta\)ACE\({}_{2}\) and \(\Delta\)ACE\({}_{3}\) are area control errors; \(\Delta\)P\({}_{\text{tie1}}\), \(\Delta\)P\({}_{\text{tie2}}\) and \(\Delta\)P\({}_{\text{tie3}}\) are tie-line power fluctuations in areas 1, 2 and 3, respectively. Figure 24: Frequency variations of (**a**) area 1, (**b**) area 2 and (**c**) area 3 using IT2 FLC fuzzy-PI, fuzzy-PI and PI controller due to step load change of 0.1 p.u. in all three areas. Figure 25: Tie-line power variations (\(\Delta\)P\({}_{\text{tie}}\)) of (**a**) area 1, (**b**) area 2 and (**c**) area 3 using IT2 FLC fuzzy-PI, fuzzy-PI and PI controller due to step load change of 0.1 p.u. in all three areas. Figure 26: ACE variations of (**a**) area 1, (**b**) area 2 and (**c**) area 3 using IT2 FLC fuzzy-PI, fuzzy-PI and PI controller due to step load change of 0.1 p.u. in all three areas.