esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### EEG Analysis Results
#### 3.2.1 Individual Participant EEG Data Analysis  
We compared the relationship between the magnitude of the mean alpha wave value per electrode for 30 individual subjects while watching the videos of the two schemes (see Table 8), and the results showed that, on 12 groups of electrodes, more than half of the subjects watched the free-form landscape video with a higher alpha value than they watched the regulated landscape video, 7 groups of electrodes did not have a significant difference in the alpha value, and 13 groups of electrodes tended to be in favor of the regular-form landscape. From the above, both free-form and regularized landscapes can produce more \(\alpha\)-waves on a larger number of electrodes and are more capable of eliciting physiological comfort. However, we further found that the two landscape schemes affect different brain regions differently.  
Figure 5 shows the distribution of electrode locations for the 32 groups and their propensity for free-form or regular-form landscape. The results showed that more than half of the people who viewed D1 produced high alpha waves in the left frontal lobe (Fp1, Fp3), the left temporal lobe (Fc5, C3), and the central region electrodes (Fz, FC2, Cz), and that more people were more comfortable in this region for physiological perception of free-form landscape; when viewing the regular-form landscape, more people produced high alpha waves in the right frontal lobe (Fp2, F4, F8), the left parietal lobe (CP5, P3, CP1), and occipital electrodes (Pz, POz, O1), which means that the regular-form landscape is more likely to induce physiological comfort in these regions (see Figure 6). At the same time, we noticed that, similar to the F3 electrode in subject 7, there was no significant change in the \(\alpha\) value before and after the video stimulation of the two sets of landscapes and, due to the different individual differences, we can only preliminarily determine the effect of the two sets of protocols on the physiological comfort in different brain regions from the perspective of the number of individuals.  
Figure 4: EEG data processing flow.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Electrode**} & \multicolumn{2}{c}{**Subject1**} & \multicolumn{2}{c}{**Subject2**} & \multicolumn{2}{c}{**Subject3**} & \multicolumn{2}{c}{**Subject4**} & \multicolumn{2}{c}{**Subject5**} & \multicolumn{2}{c}{**Subject6**} & \multicolumn{2}{c}{**Subject7**} \\ \cline{2-10}  & & **M** & **M** & **M** & **M** & **M** & **M** \\ \hline \multirow{5}{*}{FP1} & D1 & 0.30 & \(-\)0.21 & 0.34 & 0.40 & \(-\)1.60 & \(-\)0.57 & \(-\)0.07 \\  & D
## 6 Conclusions  
To deeply understand the impact of the airfoil angle of attack on the output performance of valveless piezoelectric pumps with airfoil baffles, this study experimentally investigated the output characteristics of valveless piezoelectric pumps with airfoil baffles at various angles of attack, and performed simulation calculations for the entire flow field of the piezoelectric pump. The experimental results indicate that as the airfoil angle of attack increases, both the maximum output flow rate and the maximum output back pressure of the piezoelectric pump decrease. At a 0\({}^{\circ}\) angle of attack for the Clark Y airfoil, the maximum output flow rate of the pump is 200.7 mL/min, with a maximum output back pressure of 784.4 Pa. The flow field simulation results show that with an increase in the airfoil angle of attack, the entropy production within the piezoelectric pump also gradually increases, with turbulence dissipation entropy production and wall entropy production constituting a larger proportion compared to viscous entropy production. Notably, regions of high turbulence dissipation entropy production within the pump are primarily located at the pump chamber inlet, the trailing edge of the airfoil in the inlet pipe, the trailing edge of the airfoil in the outlet pipe, and the outlet bend. As the angle of attack of the airfoil baffle increases, the complexity of the vortex core structure in the flow field also increases. The areas of high wall entropy production are mainly concentrated in the outlet bend component.  
Conceptualization, J.H. and B.Z.; methodology, J.H., H.A., M.K. and J.X.; software, H.A. and M.K.; validation, H.A., M.K., J.X. and S.Z.; formal analysis, S.Z.; investigation, J.H. and H.A.; resources, B.Z.; data curation, M.K. and J.X.; writing--original draft preparation, J.H.; writing--review and editing, B.Z.; visualization, M.K.; supervision, B.Z.; project administration, B.Z.; funding acquisition, J.H. and B.Z. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China, grant number 51605200.  
Not applicable.  
The raw data supporting the conclusions of this article will be made available by the authors upon request.  
The authors declare no conflicts of interest.
## 2 State of the Art
### VR Applications for General Training  
VR techniques can represent realistic workplace situations and provide text-free interfaces to better engage users in the training [4]. Specifically, VR provides an alternate modality that allows workers to receive accurate training in hazard recognition and avoidance, such as learning to follow mine evacuation routes and safe procedures without exposing themselves to danger [5].  
VR technologies have been broadly utilized in various fields for training. [PERSON] et al. developed a training system for fire emergency evacuation; the system was tested for its robustness and functionality against the development requirements, and the results showed promising potential to support more effective emergency management [6]. [PERSON] et al. presented a tower crane dismantlement training VR system, and the results indicate that the trainees of the proposed system generally learned better than those using the traditional method [7]. As a potential reference for users, [PERSON] et al. provided a comparative study on virtual construction by using the CAVE system, head-mounted Oculus VR and Cardboard VR. This study can potentially contribute to formalizing selection and integration of appropriate VR environments in support of construction project management [8]. [PERSON] et al. also integrated a traditional VR visualization system with 3D object manipulation and adjustment functions for a collaborative and interactive VR system for architectural design education. It will promote the education of architectural design [9]. In the language learning field, [PERSON] et al. improved vocabulary acquisition by introducing VR technology in English as a Foreign Language (EFL) for middle school students [10].  
Specifically in the architecture, engineering and construction (AEC) domains, VR technology has been rapidly accepted for education and training in recent years due to the superiority of the engaging, immersive environment feature [11]. The tread analysis by [PERSON] et al. showed a significant increase in AR/VR utilization in the AEC industry, including residential, commercial, institutional and transportation sectors [12]. [PERSON] et al. adopted the VR technology for AEC procedures, in which 112 participants showed statistically enhanced performance comparable to that in a physical environment [13]. VR technology enables spatial cognition for the immersive review of 3D design [14], which further enables civil engineering (CE) students to gain practical experience without being present at a construction site [15].
# A Review of Double-Walled and Triple-Walled Carbon Nanotube Synthesis and Applications
## 2 Synthesis and Characterization of DWNTs
### The Catalytic Chemical Vapor Deposition Method  
The catalytic chemical vapor deposition (CCVD) method has been used for the preparation of SWNTs, DWNTs and MWNTs. The main idea of the CCVD method is as follows: decompose the carbon precursor into small carbon species by applying heat (either by self-thermal decomposition or by catalytic dehydration at the catalyst surface); carbon species adsorb onto the catalyst surface, diffuse onto the surface of a catalyst metal nanoparticle, followed by the formation of a solid solution; saturated carbons precipitate from the catalyst metal nanoparticle and then simultaneously form a cap structure as the initiation of the CNT growth; the structure changes from the cap to a cylinder as the growth continues. This CCVD method involves various reactions; thus, usually, amorphous carbons,SWNTs and MWNTs are found as impurities besides DWNTs. Although the system for CCVD growth is quite simple, it is found that there are many parameters that can be controlled from the catalyst preparation all the way through the CCVD reaction. It was found that small variations in the details of these growth parameters sensitively change the catalytic reaction, as well as the resulting CNT structure. Therefore, selective growth of CNTs is still challenging. There are two different methods, which correspond to the \"supported catalyst\" method and the \"floating catalyst\" method for CCVD growth. To achieve selective growth of CNTs with a certain number of walls, the diameter of the metal nanoparticle needs to be precisely controlled prior to the synthesis reaction, since the catalyst metal nanoparticles with different diameters yield CNTs with different diameters and numbers of layers, depending on the CNT diameter. The desired addition of promoter is another way to control the layer number of CNTs. The highly selective growth of DWNTs has also been reported by several groups using different synthesis conditions (Table 1).
## 3 Results and Discussion
### Optical Properties
The alignment of energy levels facilitates the migration of photogenerated electrons from the conduction band of g-C\({}_{3}\)N\({}_{4}\) to that of CdS, while the  
Figure 6: UV-Vis DRS of (**a**) porous g-C\({}_{3}\)N\({}_{4}\), CdS, and CdS/g-C\({}_{3}\)N\({}_{4}\)-2 and hv estimates of (**b**) porous g-C\({}_{3}\)N\({}_{4}\), CdS, and CdS/g-C\({}_{3}\)N\({}_{4}\)-2.  
photogenerated holes remain confined within the valence band of g-C\({}_{3}\)N\({}_{4}\). [40], effectively enhancing charge separation. Consequently, CdS functions as an electron acceptor or \"sink\", facilitating the sustained dissociation of photogenerated carriers and increasing their usability in light-induced reactions [41]. The observed reduction in PL emission intensity aligns with improved photocatalytic performance, substantiating the critical role of heterojunction formation in optimizing charge separation efficiency. Notably, although there are slight discrepancies in excitation wavelengths between this study (350 nm) and referenced studies on CdS (300 nm), the consistent trend of diminished PL intensity in the CdS/g-C\({}_{3}\)N\({}_{4}\)-2 composite emphasizes the heterojunction's function in mitigating e\({}^{-}\)-h\({}^{+}\) recombination. Furthermore, the weak emission peaks detected in the 400-500 nm range for CdS/g-C\({}_{3}\)N\({}_{4}\)-2 point to the existence of oxygen vacancies or defect states, which create localized energy levels that facilitate electron migration and further diminish the likelihood of direct e\({}^{-}\)-h\({}^{+}\) recombination. In brief, the reduced PL intensity and enhanced photocatalytic efficiency observed in CdS/g-C\({}_{3}\)N\({}_{4}\)-2 emphasize the pivotal role of heterojunctions in facilitating charge separation. The integration of CdS alters the band alignment in g-C\({}_{3}\)N\({}_{4}\), enabling directional charge transfer and suppressing recombination through interfacial interactions. Additionally, defect states assist in electron migration, collectively extending the lifespan of charge carriers and enhancing the involvement in light-driven degradation. These combined mechanisms underpin the observed improvement in photocatalytic activity.
## 3 The Proposed Method
### Verification of Quiet Zone  
According to ISO standard a Quiet Zone is defined as \"a region 4X wide which shall be free of all other markings, surrounding the symbol on all four sides\". So, it must be checked if there are only white points in the image in the rectangular areas wide 1\(MW\) which is parallel to line segments defined by FP\({}_{1}\)-FP\({}_{2}\) and FP\({}_{2}\)-FP\({}_{3}\) (Figure 11). For fast scanning of the rectangle points [PERSON]'s line algorithm is utilized [20].  
QR Code candidates which do not have quiet zones around are rejected. Rejected are also QR Code candidates whose outer bounding box (larger) contains outer bounding box (smaller) of another QR Code candidate.
# Strain Measurement Distributed on a Ground Anchor Bearing Plate by Fiber Optic OFDR Sensor
## 4 Anchor Tension Test with the Bearing Plate
In addition, strains were selected one by one in each of the five sensing fiber lines at a 10 cm vertical position where the compression load of the anchor head is dominant; these are labelled (a) in Figure 12.  
As the anchor load increases, group (a), which has a large influence on the bending load, has a large strain variation, but the difference between the respective strains is smaller than for group (b). In addition, the strains of group (b), which have a large effect of the anchor compressive load, are smaller than those of the group (a) due to the increase of the load, but the difference between the strains increases due to the increase of the load. As shown in Figures 10-12, such bending deformation is a phenomenon caused by bending of the base plate of the fixing jig. If the bending rigidity of the fixing jig base plate is increased, compression deformation due to the anchor head will predominantly appear. The bearing plate of a typical anchor head also undergoes bending deformation, but it is considered to occur in a symmetrical form with respect to the center. It was also considered that the complicated strain distribution of such a bearing plate can be seen in reality. Therefore, it was found  
Figure 11: Strain distribution on the bearing plate from OFDR sensor under 10 t loading. Figure 12: Strains on the bearing plate from OFDR sensor due to loading. that the deformation behavior of the bearing plate should be considered when measuring the strain of the bearing plate in order to monitor the anchor load. That is, when the strain distribution of the bearing plate does not have a point symmetric distribution due to the anchor load, it cannot be simply converted to the load of the anchor by measuring one point of strain at an arbitrary location.
## 2 System Model
### Sparse Delay-Doppler Domain Channel Model  
To implement channel estimation, we place \(L=(2k_{max}+2Q+1)(l_{max}+1)\) pilot symbols \(x_{p}[k,l]\) in the DD domain. The greatest delay \(\tau_{max}\) and Doppler \(\
u_{max}\) related to the delay and Doppler taps are defined as \(k_{max}\) and \(l_{max}\). In addition, we formulate Equation (7) in a different form, as follows:  
\[y[k,l]=\sum_{k^{\prime}=-k_{max}-Q}^{k_{max}+Q}\sum_{l^{\prime}=0}^{l_{max}}h \left[k^{\prime},l^{\prime}\right]x\left[k-k^{\prime},l-l^{\prime}\right] \tag{8}\]  
After a series of formula calculations, we finally obtain the matrix form of the formula as  
\[\mathbf{y}=\mathbf{\Phi}\mathbf{h}+\mathbf{V} \tag{9}\]where  
\[\mathbf{h}=\begin{bmatrix}\mathbf{h}[0]\\ \vdots\\ \mathbf{h}[l_{max}]\end{bmatrix} \tag{10}\]  
\[\mathbf{h}[l^{\prime}]=\begin{bmatrix}h[-k_{max}-Q_{\cdot}l^{\prime}]\\ \vdots\\ h[k_{max}+Q_{\cdot}l^{\prime}]\end{bmatrix}\] (10a) where \(l^{\prime}\in[0,l_{max}]\)  
\[\Phi =\sum_{l^{\prime}=0}^{l_{max}}\mathbf{x}_{k,l-l^{\prime}}^{T}\] \[=\sum_{l^{\prime}=0}^{l_{max}}\left[\begin{matrix}\mathbf{x}[k-(-k_{ max}-Q),l-l^{\prime}]\\ \vdots\\ \mathbf{x}[k-(k_{max}+Q),l-l^{\prime}]\end{matrix}\right] \tag{11}\] \[=\begin{bmatrix}\mathbf{X}_{\mathbf{k^{\prime}},\mathbf{l-0}}^{T}\\ \vdots\\ \mathbf{X}_{\mathbf{k^{\prime}},\mathbf{l-I_{max}}}^{T}\end{bmatrix}=\begin{bmatrix}\mathbf{X }_{\mathbf{k^{\prime}},\mathbf{l^{\prime}}}^{T}\\ \vdots\\ \mathbf{X}_{\mathbf{k^{\prime}},\mathbf{l^{\prime}}}^{T}\end{bmatrix}\]  
where \(\mathbf{\Phi}\in\mathbb{C}^{5\times L}\), \(\mathbf{h}\in\mathbb{C}^{L\times 1}\), and \(\mathbf{V}\in\mathbb{C}^{5\times 1}\) are the received signal, transmitted signal. and Gaussian noise in the DD domain, respectively. \(S\) is the size of the channel estimation area. A simple proof is provided in Appendix A.
## 3 Results and Discussion
### Color Measurement of Burger Samples  
Because of the important influence of food colors on the consumers acceptance, the surface color of carp and barbel burgers have been interpreted into values of color indices (L*, a*, b*) that can explain the difference between different treatments using a standard illuminant light source (Table 5).  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multicolumn{1}{c}{**Functional**} & \multirow{2}{*}{**Fish Burger Types**} & \multirow{2}{*}{**Burger Formulations**} \\ \cline{2-3} \multicolumn{1}{c}{**Characteristics**} & & & Control burger & 1\% _Spirulina_ fish burger \\ \hline \multirow{3}{*}{**SWC (mL/g DW)***} & CB & 3.13 \(\pm\) 0.115 & 3.56 \(\pm\) 0.110 ** \\ \cline{2-3} \cline{2-3}  & BB & 2.99 \(\pm\) 0.03 & 3.43 \(\pm\) 0.02  \\ \hline \multirow{3}{*}{**OHC (g/g DW)***} & CB & 0.85 \(\pm\) 0.07 & 0.90 \(\pm\) 0.017 ** \\ \cline{2-3} \cline{2-3}  & BB & 0.86 \(\pm\) 0.014 & 1.06 \(\pm\) 0.056  \\ \hline \multirow{3}{*}{**WHC (g/g DW)***} & CB & 2.31 \(\pm\) 0.135 & 2.78 \(\pm\) 0.162 ** \\ \cline{2-3} \cline{2-3}  & BB & 2.12 \(\pm\) 0.042 & 2.52 \(\pm\) 0.042  \\ \hline \hline \end{tabular} CB: carp burgers and BB: Barbel burgers. \({}^{*}\) Results are expressed as means \(\pm\) SD (n = 3). Control burgers _vs._Spirulina_-fortified burgers: a \(p<0.001\).  
\end{table}
Table 4: Functional parameters of control and _Spirulina_-fortified fish burgers.  
The L* value measures the brightness of food samples, ranging from 0 (black) to 100 (white) [40]. In cooked burgers, lightness (L*) decreased when _Spirulina_ was added. Statistically significant differences (\(p<0.001\)) were found between the 1% _Spirulina_-fortified samples and the control samples and this is due to the darker colors obtained from _Spirulina_. We speculate that reducing sugars derived from the hydrolysis of _Spirulina_ polysaccharides during the burgers production may elicit the Maillard reaction to form brown melanoidins [46]. Further, this decrease could be attributed to differences in composition, resulting in different amounts of pigments (chlorophylls and phycocyanin) and water, which is a determining element in the resulting color product [40]. These results indicate that _Spirulina_ has no tendency to lighten the burger's color. Indeed, these results are consistent with those obtained by [PERSON] et al. [47]. Moreover, carp and barbel burgers fortified with 1% of _Spirulina_ powder were characterized by significantly low a* and b* values (\(p<0.001\)), which shows that the yellow color diminished to a greenish color (Table 5). This could be mainly explained by the fact that _Spirulina_ is rich in chlorophylls. These data could be useful in predicting the effect of _Spirulina_ on the conventional color of the products where it will be used. In addition, we can argue that _Spirulina_ pigments could also be useful as natural dyes in fishery products.
# ErrorExplainer: Automated Extraction of Error Contexts from Smart Contracts
## 10 Conclusions  
Diagnosing transaction failures is critical for both users and developers in Web3. However, the absence of standardized error messages and the structural complexity of smart contracts make the task challenging. In particular, non-standardized error outputs leave users guessing the causes of failures and appropriate remedies without a clear explanation.  
I presented ErrorExplainer, a client-side framework that links low-level revert data to source-level context, providing clear, human-readable explanations. Its lightweight static pipeline extracts every transaction-reverting statement into a uniform error context, including the error message, the location of the error, and the error condition. Extensive experiments on the real-world SC-Bench dataset show that ErrorExplainer locates 6284 of the transaction-reverting statements, and correctly matches 96.99% out of 1161 injected changes, achieving an information completeness of 0.952 and a matching fitness of 0.954 (function-level) and 0.604 (trace-level).  
Despite its effectiveness, ErrorExplainer currently relies on static analysis of verified Solidity source code. The lifting rules need to be extended to support other languages or blockchains. Applying dynamic execution states to evaluate the triggering conditions in the error context can improve the matching fitness. However, the runtime overhead of this dynamic analysis should be considered.  
In future work, we plan to incorporate data-flow analysis to support filtering via guard conditions and extend error-context patterns to recognize inline assembly reverts. We are also exploring LLM prompts that translate the extracted context into natural-language advice. These enhancements will move ErrorExplainer closer to a universal, real-time error-explanation layer for Web3.  
This research received no external funding.  
Not applicable.  
Data Availability Statement: Data are contained within this article.  
The author declares no conflicts of interest.
# Recent Advances in Black Silicon Surface Modification for Enhanced Light Trapping in Photodetectors
## 3 Dry Methods for Black Silicon Fabrication
### Ion Implantation Process  
Ion implantation represents another frequently utilized technique for generating BSi [61]. This approach utilizes high-voltage pulsed direct current (DC) or pure DC power to accelerate ions toward an appropriate substrate independent of plasma dependence.  
Ion implantation has been used to fabricate sulfur (S)-doped Si nanowire arrays, referred to as BSi [62]. This work explored how the morphology of Si nanowires influences absorption across the complete wavelength range of 0.3-2.5 \(\upmu\)m and examined the impacts of thermal annealing on below-bandgap absorption. It was revealed that S-doped BSi demonstrates enhanced absorbance across the complete wavelength spectrum of 0.3 to 2.5 \(\upmu\)m when contrasted with undoped Si nanowire arrays and flat Si. Meanwhile, a study by [PERSON] et al. successfully employed PIII using \(SF_{6}\) and O\({}_{2}\) to fabricate polycrystalline BSi [63]. Subsequently, a defect removal etching process was implemented under a range of conditions, with the objective of diminishing surface recombination by decreasing surface area and alleviating damage from plasma etching. The researchers investigated the surface microstructures, reflectance, and internal quantum efficiency of the BSi utilizing an FESEM, a spectrophotometer, and a quantum efficiency measurement apparatus, respectively. Their studies indicated improvements in all these aspects. SEM images revealed that, with increased defect removal etching (DRE) process time, the height and density of nano-hills on the BSi surface decreased, which corresponded to a reduction in surface reflectance.  
Ion implantation is a promising and suitable technique for boron doping in next-generation c-Si solar cells, but its application has been traditionally limited by the necessity for high activation annealing temperatures, typically around 1050 \(\mathrm{\SIUnitSymbolCelsius}\). In their study, [PERSON] et al. utilized PIII with a diborane (B\({}_{2}\)H\({}_{6}\)) gas precursor, successfully reducing the required annealing temperature to as low as 950 \(\mathrm{\SIUnitSymbolCelsius}\)[64]. This modification not only preserved a high quality of emitters but also substantially enhanced the efficiency of n-type passivated emitter rear totally diffused solar cells, achieving a performance level of 20.8%. These findings are vital for reducing manufacturing costs and enhancing the viability of ion implantation in large-scale solar cell production.