esa-sceva/satcom-chunk-collection huggingface dataset:
# The Concept of Segmented Wind Turbine Blades: A Review
## 2 Wind Turbine Blade Manufacturing  
While initially, aerospace methodologies were used, most modern wind turbine blades are manufactured from composite materials using methods derived from ship building [8; 9]. Large clamshell molds are used to manufacture separate pressure sides (PS) and suction sides (SS) and a number of shear webs. This is done using processes such as the lamination of pre-impregnated material, bladder molding, wet-layup or vacuum assisted resin transfer molding (VARTM) [10; 11; 12]. The material is currently placed manually, but can be automated [13; 14]. Most frequently, the separate components are joined together using thick adhesive bonds [15]. As the blade size increases, this leads to issues. Firstly, tolerances increase resulting in thickness variations of the adhesive bonds, which add weight and cause stress concentrations [16]. Secondly, heating and temperature control become more difficult, while very thick laminates give exothermic reactions, which can damage the blade [17]. Thirdly, defects become more severe and prevalent in larger volumes resulting in a lower strength than assumed from coupon data [18]. These defects lower the load-carrying capacity of the blade and may require scrapping the part, which is more expensive for a larger blade [19; 20]. Lastly, modern blades are often designed with a pre-curved shape, to ensure sufficient tower clearance under extreme load without using a very stiff design [21].  
Modifications have been suggested to counter the issues with manufacturing large blades. Typically, these allow production in separate components, allowing better quality of the individual pieces. Frequently, a separately cured spar structure is used [18]. Furthermore, [PERSON] [22] suggested to build the spar cap out of thin purturbed planks glued on top of each other to avoid thick laminates. [PERSON] [17] suggested producing the blade root in multiple segments for better temperature control. [PERSON] [23] suggested producing large parts of the blades separately and joining them together using adhesive bonds before transport. This approach has the advantage of manufacturing segments and avoids the difficulty of on-site assembly. Additionally, to improve the quality of the adhesive bonds at the shear webs, [PERSON] [24] advocated producing the internal spar of a blade in two pieces, of which the height can be adjusted in order to obtain the desired bond thickness.
## 2 Supervisory Control and Data Acquisition Systems
### SCADA in Water Resource Management  
Water resource management is a critical application area for SCADA systems, particularly in regions facing water scarcity, aging infrastructure, and increasing demand [11]. SCADA systems are widely used to monitor and control water supply networks, including the following: Water Treatment Plants; Monitoring chemical dosing, filtration processes, and water quality parameters [12; 13]. Distribution Networks; Tracking water flow, pressure levels, and leak detection [14]. Pumping Stations; Controlling pump operation and optimizing energy consumption [8]. Reservoirs and Storage Tanks; Managing water levels and ensuring adequate supply [11].  
The integration of SCADA systems in water management has demonstrated significant benefits, including improved operational efficiency, reduced response times to failures, and enhanced decision-making through data-driven insights [13]. However, traditional SCADA systems often rely on 2D graphical interfaces, which can limit the ability of operators to fully understand and interact with complex infrastructure [15].
# Development of a Nonlinear Piezoelectric Energy Harvester for Alternating Air Load
## 5 Simulation Analysis of Piezoelectric Patch  
The output voltage can be influenced by the size of piezoelectric patch. In order to research the relationship between the diameter of piezoelectric patch and output voltage, a simulation analysis was performed using COMSOL software (No. 5.2, COMSOL Inc., Stockholm, Sweden). The model was built and the sweep gridding was used to analyze the characteristics of power generation. Figure 4 shows the output voltage in different diameters of piezoelectric patch. \(D_{\text{p}}\) is the diameter of PZT-5H and \(D_{\text{s}}\) is the diameter of the substrate. The pressure of the compressed air load is fixed at 200 kPa. As the diameter of \(D_{\text{p}}\) increases, the output voltage is also increases.  
Figure 3: Cross section view of the piezoceramic (PZT) circular patch.  
Figure 5 shows the output voltage under different pressures. When the pressure of \(P_{x}\) increases, the output voltage also increases. When the pressure is 200 kPa the output voltage is 52.1 V. There is an axial displacement picture for which the pressure is defined as 170 kPa, as shown in Figure 5. As the common rule of different pressures, the pressure 170 kPa has been selected. The maximum displacement appears at the center of the PZT patch, which can bear the compressed air easily.  
In this section, the structure and working principle have been designed and analyzed. The theoretical analysis and simulation results show that the output voltage is proportional to the compressed air load. When the size of piezoelectric patch increases, clearly the output voltage also increases.
# An Efficient Data Retrieval Parallel Reeb Graph Algorithm
## 5 Parallelization of the Algorithm  
In this section, we give the details of our strategy to compute the Reeb graph in parallel. We describe the three stages of the parallel algorithm as follows.  
1. **The Partition Stage**. In this stage, we partition the manifold \(M\) into submanifolds, such that the vertices counts of each submanifold are approximately equal to each other.
2. **Computing the Reeb Graph for the Submanifold Stage**. Computing the Reeb graphs for each submanifold obtained from stage one concurrently.
3. **The Gluing Stage**. In this step, we glue the Reeb graphs that were obtained from stage 2.
# AI-Driven Phishing Detection: Enhancing Cybersecurity with Reinforcement Learning
## 3 Classification of Phishing Detection Strategies
### RL-Based Systems  
RL offers a dynamic, adaptive, and self-improving approach to phishing detection. Unlike traditional supervised ML models that rely on large, labeled datasets and static training, RL systems learn from interaction with their environment, making them highly effective in combating evolving phishing tactics [54]. This continuous learning capability aligns perfectly with the dynamic nature of cybersecurity threats, where new attack vectors emerge regularly as shown in Figure 2 below.  
RL components include the following:  
* Environment (E): The incoming stream of emails, websites, or network data that needs analysis;
* State (s): The current representation of features extracted from emails or websites (e.g., URL length, domain age, and sender reputation);
* Action (a): The classification decision--either phishing (1) or benign (0);  
Figure 2: Reinforcement learning agent adapts phishing detection through continuous interaction with dynamic email environments. Agent (A): the phishing detection system tasked with identifying malicious emails or URLs.  
* Reward (R): A feedback mechanism where the agent receives positive rewards for correct classifications and penalties for false positives/negatives. The goal of the RL agent is to learn an optimal policy (\(\pi^{*}\)), which maps states to actions to maximize cumulative rewards over time.
# Multidisciplinary Design Optimization of Cooling Turbine Blade: An Integrated Approach with R/ICSM
## 4 Optimization Results and Discussion  
### Comparison of Optimization Results  
Table 1 presents a comparison of performance parameters between the initial and enhanced turbine schemes. In contrast to the initial scheme, the improved scheme exhibits notable enhancements: a 0.69% increase in efficiency for the 41 st section, a 0.08% boost in total expansion ratio, a 0.04% reduction in gas flow rate, and a 0.24% increase in outlet airflow angle, aligning it closer to the axial direction. However, it is worth noting that the maximum von Mises stress on the first stage rotor blade experienced a significant 20.38% increase, nearing the boundary of the strength constraint. These results underscore the improved aerodynamic performance of the optimized turbine blade while still adhering to strength constraints. Table 2 compares the 20 design variables of the first-stage rotor blade between the initial and enhanced schemes of the high-pressure turbine. Significant changes are evident in the blade design variables. Specifically, in the middle section, the leading edge radius \(R_{q2}\) increased by 23.05%, while the inlet wedge angle \(W_{q2}\) decreased by 27.88%. Additionally, the turning angle \(\delta_{2}\) of the middle section increased by 20.03%, the turning angle \(\delta_{3}\) of the root section increased by 10.19%, the blade stagger angle \(\gamma_{1}\) of the tip section rose by \begin{table}
\begin{tabular}{c c c c c c} \hline Parameters & \(\frac{\pi_{\text{eq,max}}-\eta_{\text{max}}}{\eta_{\text{bas}}}\) & \(\frac{\pi_{\text{eq,max}}-\eta_{\text{max}}}{\tau_{\text{bas}}}\) & \(\frac{W_{41,\text{eq,max}}-W_{41,\text{bas}}}{W_{41,\text{bas}}}\) & \(\frac{\alpha_{\text{eq,max}}-\alpha_{\text{bas}}}{\omega_{\text{bas}}}\) & \(\frac{\sigma_{\text{eq,max,opt}}-\sigma_{\text{eq,max,bas}}}{\omega_{\text{ eps,max,bas}}}\) \\ \hline Value & +0.69\% & +0.08\% & \(-0.04\%\) & +0.24 & +20.38\% \\ \hline \end{tabular}
\end{table} 
Table 1: Comparison of typical performance parameters of turbine blade before and after optimization. 16.63%, the axial chord length \(S_{1}\) of the tip section increased by 13.25%, and the axial chord length \(S_{2}\) of the middle section increased by 12.23%. After optimization, the axial chord length of the blade root section remains unchanged, with minimal alteration to the blade root profile. However, there are substantial variations in the axial chord length of the middle and tip sections, leading to notable changes in the tip and middle sections, as depicted in Figure 12.
## 2 Broadband System
### Fixed-Line Broadband System
#### 2.1.2 Broadband Powerline  
Power Line Communication (PLC) is a concept that is based on the use of electrical wires for data transmission [121]. A typical BPL system is depicted in Figure 3. The main motivation for its deployment is the need for alternative means of offering broadband last-mile access in diverse areas [122; 123]. The BPL technology is relevant in this scope due to the existing connection from the power grid to different homes and offices using the grid infrastructure. This saves the need for further investment in the backbone installation [124; 125; 126]. Note that apart from being used for electrical power transmission, it can be also employed for the transmission of additional audio (speech and music) and video signals. Based on this, different applications such as in-home automation, broadband Internet access, broadband LAN connectivity, smart city, wireless power transfer, automatic remote metering, telemetry, in-vehicle communications, and other transport systems can benefit from PLC network [121; 126; 127; 128].
# Laser Finishing of Ti6 Al4V Additive Manufactured Parts by Electron Beam Melting
## 3 Results  
### Preliminary Tests  
Figure 2 depicts the preliminary results of the samples treated with three different fluences, by way of focal distance: +5, +7.5, and +10 mm on the surface of the samples. Three different states are visible:  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Profile** & **Cutoff** & **Evaluation Length** \\ \hline
**Rz (\(\upmu\)m)** & **Ra (\(\upmu\)m)** & **\(\uplambda\) (mm)** & **In (mm)** \\ \hline Up to 0.1 & Up to 0.02 & 0.08 & 0.4 \\
0.1–0.5 & 0.02–1 & 0.25 & 1.25 \\
0.5–10 & 1–2 & 0.8 & 4 \\
10–50 & 2–10 & 2.5 & 12.5 \\
50–200 & 10–80 & 8 & 40 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Recommended cut-off and evaluation length according to the UNI EN ISO 4288:2000 standard.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Control Factors** & **Labels** & **Low (–)** & **Middle (0)** & **High (+)** & **Unit** \\ \hline Scan speed & Ss & 3.6 & 9 & 18 & mm/min \\ Focal distance & Fd & 5 & – & 7.5 & mm \\ \hline \hline \end{tabular}
\end{table}
Table 3: Control factors and their levels.  
a-state--the laser track appears regular with the typical V-shape of a deep marking. This means that the adopted fluence is so high as to vaporize the little ridges and part of the bulk (Figure 2a).  
b-state--the laser track is just visible. The fluence is high enough to melt and vaporize only the little ridges while the bulk is light blue (Figure 2b).  
c-state--the laser track is not visible. Just a dark shade is visible on the ridges and no melted material (Figure 2c).  
According to these observations, the c-state was not desired for finishing purposes; consequently, focal distance (Fd) = 10 mm was excluded from the second phase.  
The screening tests show that, as expected, the fluence affects the interaction between the laser and material. When the density increases, it is possible to pass from heating up to melting or even vaporizing the material. If we consider the tracks, laser power, and treatment time, we can achieve an estimation of the adopted fluences. It is worth noting that these values differ from the theoretical ones but are more suitable for industrial applications. The measurements are reported in Table 5, while in Figure 3 the contour plot of the estimated fluence was traced vs. the track width and focal distance.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Focal Distance, Fd (mm)** & **Track Width, Tw (mm)** \\ \hline
5 & 0.57 \\
7.5 & 0.74 \\
10 & 1.04 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Width of laser tracks at different focal distances.  
Figure 2: Laser tracks on the surfaces of specimens performed at: (**a**) Fd = 5 mm, (**b**) Fd = 7.5 mm, (**c**) Fd = 10 mm.
## 2 System Model  
Figure 1 illustrates the block diagram of the OFDM receiver employing joint signal direction estimation and beamforming. In this system, signals received by the airborne platform are first converted from analog to digital (A/D) before being processed by the DOA estimation module. This module is capable of distinguishing between desired and interfering signals. Subsequently, the data along with the DOA information are sent to the beamforming module. Here, using the INCM reconstruction approach, the module computes the weight vector and executes beamforming to extract the desired signal. Finally, the original data are recovered after operations such as signal demodulation and channel decoding.  
The focus of this study is on using the Cyclic-MUSIC algorithm for DOA estimation and the INCM reconstruction method for beamforming, as indicated by the dashed box in Figure 1.
# Modulation Decoding Based on K-Means Algorithm for Bit-Patterned Media Recording
## 4 Simulation and Results
\begin{table}
\begin{tabular}{c} \hline \hline
**K-Means Algorithm in Scikit-Learn** \\ \hline from sklearn.cluster import Kmeans \\ codeword = np.array([[+1, +1, -1, -1, -1, -1, -1], [-1, -1, +1, +1, +1], [-1, -1, -1, +1], [+1, +1, +1, +1], [+1, +1, +1, -1, -1], \\ [+1, -1, +1, -1, -1, -1], [-1, +1, -1, +1, +1], [-1, +  
SNR increases, as illustrated in Figure 5b, the points for each cluster are gathered. Further, the K-means algorithm can derive centroids from the received sequences and allocate them to an appropriate cluster. Table 3 lists the centroids of the K-means decoder based on hard and soft decisions at SNR = 14 dB. For the initialization of K-means, a codeword is used as the initial centroid. When using the hard decision, since the received sequence from the Viterbi detector is a hard-decision value and information loss occurs by the hard decision, the finalized centroid with a hard decision is also similar to the codeword. It is then difficult to achieve performance gain, as shown in Figure 3. However, when using the soft decision, since the received sequence from the SOVA detector is a soft-decision value, the K-means algorithm helps to understand data patterns and characteristics. Figure 4: BER performance of the decoding schemes in accordance with TMR at SNR of 14 dB. Figure 3: BER performance of the decoding schemes according to SNR. Figure 6 shows the number of codeword errors depending on the modulation decoding schemes when the SNR is 10 dB; in other words, when \(\mathbf{c}^{l}\) is transmitted by the encoder but the decoder determines \(\mathbf{c}^{k}\) (\(l\
eq k\)), the number of codeword errors for \(\mathbf{c}^{l}\) is counted. The total number of codeword errors in the conventional and K-means decoders is 2944 and 651, respectively. Additionally, when the conventional decoder is used, many codeword errors occur in \(\mathbf{C}_{12}\) and \(\mathbf{C}_{13}\) because the isolated patterns such as \([-1,+1,-1]^{\mathrm{T}}\) and \([+1,-1,+1]^{\mathrm{T}}\) can be generated by the adjacent neighboring codewords. However, when the K-means decoder is used, the number of errors in each codeword is similar because the K-means algorithm only considers data patterns and characteristics.
## 3 Results and Discussion
### Binding Mechanism Analysis between HSP47 and Native Collagen Peptides
We found that Pro and Phe at this position bind better than Hyp, Leu, Met, and Ala, while molecular modelling of the integrin peptide 1 (GF\({}^{-4}\)OGER\({}^{0}\)) showed that Phe at position -4 could fit into a shallow surface cleft of HSP47, providing potential stabilizing interactions (Figure 3). Smaller hydrophobic residues such as Met and Leu seen in other integrin peptides could also be accommodated in this surface cleft, while the charged bulky side chain of an arginine residue could not. This readily explains why HSP47 binds tightly on integrin peptide 1 but very poorly on integrin peptide 5 (Table 1); however, there were differences between the experimental and predicted results for Ala in position -4, which was likely an outlier from the calculation by FoldX (Table 1, Figure 3). We also assessed the effects of substitutions at positions -7 and -6 in CMP (PPGP\({}^{-7}\)P\({}^{-6}\) GP\({}^{-4}\)T\({}^{-3}\)GP\({}^{-1}\)R\({}^{0}\)GPPPG), which are located at the other end of the HSP47 binding site on collagen. It appeared that all the non-Pro substitutions showed worse binding to HSP47 (Figure S4). This may be due to these positions being far away from the key anchoring Arg\({}^{0}\), while replacement of proline, which has a rigid sidechain, will increase the flexibility in this part of the triple-helical conformation, leading to lower binding activities of these peptides. Although not all of the unbound peptides with the GXR motif in toolkits II and III could be readily explained by the simple free folding energy calculation (Figure S2), the binding activities of collagen peptides towards HSP47 most likely reflect the overall cumulative effects of all of the residues involved in the HSP47-peptide binding interface. Arg\({}^{0}\) is the most critical residue in collagen, but residues at positions -3 and -4 of collagen peptides play a critical supporting role for efficient HSP47 binding. This indicates that targeting the binding surfaces of HSP47 corresponding to positions -4, -3, and 0 of collagen  
Figure 3: (**a**) Predicted total folding energies for the substitution of residues at position -4 in integrin peptide 1 (PPGP\({}^{-7}\)P\({}^{-6}\)GF\({}^{-4}\)O\({}^{-3}\)GE\({}^{-1}\)R\({}^{0}\)GPPPG) and the HSP47 complex compared to that of WT (\(\Delta\Delta\)G \(\pm\) SD, n = 5, kcal/mol). The lower energy indicates favorable binding. (**b**) The predicted binding mode between triple-helical integrin peptide 1 (shown as magenta cartoon and sticks) and HSP47 (shown on electrostatic potential surface). simultaneously would provide a more efficient approach to blocking HSP47 activity than targeting the binding surface of HSP47 at position 0 only.
## 4 Results Analysis
### Spatial Change Characteristics of the ESV  
Using the ArcGIS 10.8 platform, ESV was calculated for each grid cell, followed by interpolation analysis employing the kriging tool. Subsequently, the natural breakpoint  
Figure 7: Ecosystem services value of districts or counties in Putian from 2000 to 2020. Sources: Drawings from this study.  
method was employed to classify ESV in Putian City into five grades from low to high, as depicted in Figure 8.  
As illustrated in Figure 8, Putian City exhibited a distinct spatial pattern of ecosystem services value (ESV), with higher values concentrated in the north and lower values in the south. Low-value areas (Grade I and Grade II) represented a small fraction of the city, primarily encompassing regions with dense populations and intense human activities, such as Licheng District and Xiuyu District. Moderate-value areas (Grade III) were the most prevalent, predominantly distributed in Xianyou County and Hanjiang District. These areas were characterized by high forest cover, a substantial proportion of forest land, and relatively developed fruit and forestry industries. High-value areas (Grade IV and Grade V) were primarily concentrated in the Xinghua Plain, located in the southern and northern reaches of the lower Mulan River. These regions, endowed with abundant water resources, served as Putian's primary centers for food, vegetable, and aquatic product production. Their superior ecological conditions contributed to their elevated ecosystem services value. From an evolutionary perspective, the ecosystem services value of Grade II and Grade III remained relatively stable between 2000 and 2020, while the value of Grade I, Grade IV, and Grade V expanded. This suggests that Putian City effectively responded to the national \"Three Regions and Three Lines\" strategy, achieving notable progress in ecological conservation. However, it is noteworthy that ESV in most areas of the Licheng District and Xiuyu District gradually declined over the study period. This decline primarily stemmed from the conversion of significant portions of cultivated land and grassland into built-up land during this time, leading to a continuous decrease in provisioning services in these areas.
# Analysis of the Effect of Capillary Water Absorption on the Resistivity of Cementitious Materials
## 3 Results and Discussion
### Effect of Capillary Water Absorption on the Resistivity of Cement Mortar
Under the action of capillary water absorption, the specimen can be divided into three areas according to the distribution of water inside the specimen: the saturated area, non-saturated area, and dry area. The bottom of the specimen is a saturated area, and the pores are connected by water to form a conductive path, which  
Figure 8: The capillary water distribution in the section of 1/2 length of the specimen (after 36 days of capillary water absorption). Figure 7: Changes in water absorption and resistivity of cement mortar with different SF contents over time: (**a**) Macroscopic damage; (**b**) Partially enlarged drawing. leads to a significant decrease in the resistivity of the specimen. However, the pores in the dry zone are hardly conductive.