esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Proposed Approach and Requirements
### Requirements  
Since this study is aiming to redefine the framework of future SATCOM in order to achieve the highest possible spectrum efficiency, we are encouraged to identify and propose which aspects of SATCOM could be enhanced to be able to support dynamic spectrum slicing and allocation. Therefore, it is not necessary that the proposed framework follows existing standards and regulations in SATCOM. Rather, if achieved results are proven to be beneficial, they can serve as a basis for adaptation of existing SATCOM standards and regulations. Based on these considerations, the following requirements are identified throughout this work:  
* A basic multi-frequency time division multiple access (MF-TDMA) medium access control (MAC) protocol is considered to be available and running in all satellite-related entities. This is the most basic enabler of spectrum slicing in its two dimensions (frequency, time) that is adopted by the broader wireless community (also in 5G) for future dynamic and spectrum efficient resource allocation. Although current satellite systems use frequency division duplexing (FDD) and further time division multiplexing (TDM) in downlink and MF-TDMA in uplink as in 2 nd Generation Interactive Digital Video Broadcasting Satellite System (DVB-RCS2) [29], such a continuous TDM stream will be a major source of interference and this approach is not sustainable with the anticipated growth of satellite density. Therefore, we consider MF-TDMA for both downlink and uplink and elaborate its benefits in terms of spectrum utilization and interference avoidance capabilities.
* For the sake of simplicity, FDMA is considered for both 5G FWA and MW links. Note that the intention here is not to simulate the full stack of the terrestrial part, but rather to consider it as the incumbent.
* There is time synchronization between all entities taking part in the MF-TDMA based DSS framework with an accuracy at least in the order of 1 up to 2 ms, requiring that the distance between two extremes of the satellite's beam, projected on the ground, is within bounds that allow the level of synchronization assumed. If terrestrial networks want to actively share spectrum in the time domain through the MF-TDMA MAC, then they also need to adhere to this time synchronization requirement.
* Each transmitter is capable of actively shifting its transmission bursts in frequency and in time in order to make sure that the receiver receives the transmission within the intended frequency range and time slot.
# Acceleration of a Production-Level Unstructured Grid Finite Volume CFD Code on GPU
## 5 Performance and Discussion
### Performance of LU-SGS Parallelization  
The performance of two LU-SGS parallelization methods was investigated using the M6 wing grid at various levels. Figure 12a shows the speed-up ratio of the single-card GPU calculation of colouring and hyperplane algorithms compared with the serial version on the CPU. These data reflect the concurrency level of the algorithm. Considering that the colouring or hyperplane method will bring additional overhead, it is necessary to compare it with the original LU-SGS algorithm to evaluate the acceleration benefits of the parallel algorithm. The result is shown in Figure 12b. Results show that the concurrency of the face colouring method is significantly higher than that of the hyperplane. Both algorithms require dividing the grid cells into different colours of groups, with each group executing in parallel. Thread initialization and synchronization are needed before and after parallel execution. Therefore, the more groups divided, the lower the degree of concurrency, and the higher the overall parallel overhead. The number of divided hyperplanes is large, and the number of grid cells between the planes is uneven. In extreme situations, one hyperplane has only one grid cell, resulting in high parallel synchronization overhead and low concurrency. As the scale of the grid increases, the problem of low concurrency will be alleviated, so the speed up gradually increases.  
Figure 11: Comparison of speed up of UpdateRHS of simulating M6 wing before and after shared memory optimization.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Grid Level**} & \multicolumn{2}{c}{**Convective Flux**} & \multicolumn{2}{c}{**Viscous Flux**} \\ \cline{2-5}  & **Original** & **Loop Fusion** & **Original** & **Loop Fusion** \\ \hline Grid 1 & 18.7 & 9.6 & 12.0 & 10.3 \\ Grid 2 & 102.1 & 48.0 & 69.4 & 50.1 \\ Grid 3 & 565.5 & 317.6 & 372.2 & 274.9 \\ Grid 4 & 1622.8 & 861.5 & 1077.2 & 801.3 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Comparison of time consumption (s) before and after loop fusion for convective flux and viscous flux.
# Effects of Auditory Pre-Stimulation on Cognitive Task Performance in a Noisy Environment
## 3 Results and Discussion
### Experiment 1
#### 3.1.2 Discussion  
In _Experiment 1_, each participant performed the three STM/WM tasks for two experimental conditions (\(P_{N}\,E_{Q}\) and \(P_{N}\,E_{F}\)) to examine the effects of a noisy environment on the performance of basic STM/WM tasks. Paired \(t\)-test results showed that the experimental condition did not affect the scores of the Corsi block-tapping and 3-back tasks and only significantly affected the Digit span task score (\(p<0.01\)). The \(P_{N}\,E_{F}\) condition showed a 15.2% smaller mean than the \(P_{N}\,E_{Q}\) condition. It can be inferred from these results that \(E_{F}\) has a greater effect on the phonological loop than on the visuospatial sketchpad and the central executive of the WM system. In other words, noise acted as a type of interference/distraction in the phonological analysis and articulatory rehearsal process during the Digit span task. The observed _field-noise_ effects on the Digit span task performance are in good agreement with the findings of other studies that showed that extraneous  
Figure 4: The mean and standard deviation values of STM/WM tasks for each experimental condition.  
Figure 5: The mean and standard deviation values of task-specific and overall mental workload ratings for each experimental condition.  
auditory stimuli/noise deteriorated task performance. [PERSON] et al. (2020) revealed that the performance on an auditory processing task requiring the phonological loop function was poorer in a noisy environment compared with a quiet environment. Similarly, [PERSON] and [PERSON] (2018) showed that the performance on a serial recall task involving phonological STM was lower in a noisy condition of 75 dB than in a quiet condition of 37 dB.  
Another notable observation from _Experiment 1_ was that the mean scores for each task-specific mental workload experienced during the Corsi block-tapping, Digit span, and 3-back tasks and the overall mental workload were significantly higher in the \(\mathbf{P_{N}}\,\mathbf{E_{\mathrm{F}}}\) condition than in the \(\mathbf{P_{N}}\,\mathbf{E_{\mathrm{Q}}}\) condition (Figure 6). These findings suggest that \(\mathbf{E_{\mathrm{F}}}\) increased the participants' mental workload, congruent with the results of other studies showing that noise increased participants' mental workloads ([PERSON], 2018; [PERSON] and [PERSON], 2018). Given that \(\mathbf{E_{\mathrm{F}}}\) was an environment in which actual field noise was provided, the results of _Experiment 1_ suggest that field noise prevalent in actual workplaces can negatively impact the worker's phonological loop function in addition to increasing the mental workload.
## 3 Results and Discussion
#### 3.1.3 Effect of Monomer Content  
Then, the (PAA-_co_-PAM)-DPNR was prepared by varying the monomer contents from 10 phr to 30 phr, which was denoted as P10-DPNR and P30-DPNR, respectively. The effect of monomer concentration was examined using a fixed concentration of initiator (1.0 phr) at a reaction temperature of 50 \({}^{\circ}\)C. The resulting product became a more viscous latex when the monomer contents increased due to a greater amount of PAA-_co_-PAM forming in the system. From Figure 3b, the monomer conversion was observed to be around 91.9-94.1% for the monomer concentration of 10-30 phr. The grafting efficiency and grafting percentage were found to increase with the increasing monomer content. The grafting efficiency and grafting percentage were in the range of 20.8-38.9% and 2.1-9.9%, respectively. The modified DPNR was also prepared by graft copolymerization with only acrylic acid (PAA-DPNR) and acrylamide (PAM-DPNR) for comparison. Unstable latex was obtained for the PAA-DPNR. The phase separation of PAA-DPNR leads to the occurrence of a creaming phenomenon. Figure S1 displays the creaming index with different storage times (see Supplementary information), which can indicate the degree of latex stability. The creaming index of PAA-DPNR increased with storage time. Although PAA had the ability to stabilize particles through electrostrict stabilization [41], high acidity in the system could deteriorate the colloidal stability of the rubber particles in an aqueous medium. When the comonomer was used at the ratio of 50:50 acrylic acid/acrylamide by weight percentage, the (PAA-_co_-PAM)-DPNR exhibited good colloidal stability over a month, as was the same for the PAM-DPNR. However, the PAM-DPNR had a low grafting percentage (6.4%) compared to the (PAA-_co_-PAM)-DPNR. The stronger interactions between the copolymers of the polyacrylic acid and polyacrylamide can lead to the formation of self-assembled structures and generate additional physical crosslinking through hydrogen bonding [42]. Therefore, the use of comonomer would be effective for preparing colloidally stable rubber particles with high grafting percentage as compared to a sole monomer.
## 2 Class-D PA for Polar-Mode Architectures  
Since the polar-mode architecture requires the RF PA to be used as a high-level amplitude modulator, it can be considered a three-port device [5; 6], as follows:  
Figure 2: Power spectral density (PSD) of the 4C-CH VDL-T signal generated by MATLAB. Main signals in a polar-mode transmitter: drive signal (\(v_{\text{DR}}\)), amplified envelope (\(v_{E}\)), and amplified RF signal at the output (\(v_{O}\)).  
* The RF drive (\(v_{DR}\)) input port, where the carrier (with phase information if required) is injected.
* The envelope (\(v_{E}\)) input port is used to modulate the PA with amplitude information.
* The amplified signal (\(v_{O}\)) is provided by the RF output port.  
The difficulty of achieving good isolation (from unwanted signal components) between ports results in some distortion problems that usually affect the amplified signal (\(v_{O}\)) envelope; this is due to the leakage from the input ports (\(v_{DR}\) and \(v_{E}\)) to the RF output port and the bandwidth limitations of the envelope input port (\(v_{E}\)).
# CFD and Experimental Comparison for Micro-Pump Performance in Space Applications: A Case Study
## 1 Introduction
It presents an integrated and rapid methodology for pump design and evaluation, combining linear predesign techniques, three-dimensional fully viscous CFD-based optimization, and precision additive manufacturing for accelerated prototyping. The proposed approach addresses the persistent challenge of reconciling the CFD results with experimental measurements at small scales--where discrepancies are often amplified due to Reynolds number effects and manufacturing tolerances. A key aspect of this work is the tight and iterative connection between simulations and experiments, in contrast to traditional sequential workflows where design, testing, and analysis are performed in separate stages. This integration supports faster refinement and validation of the pump design. The study also explores a simple empirical adjustment using two global scaling factors--for pressure and mass flow--that bring the CFD results into closer agreement with experimental data across the tested operating range. These scaling factors are purely empirical and are used to illustrate the consistent offset observed between CFD and experiment. This approach is intended as a diagnostic tool to explore potential sources of systematic deviation.
# DVCW-YOLO for Printed Circuit Board Surface Defect Detection
## 2 Methodology
### Proposed DVCW-YOLO Network  
YOLOv8 [13] is a widely utilized detector in the field of target detection. It incorporates the cross stage partial (CSP) structure within backbone network, along with the spatial pyramid pooling with factorized convolutions (SPPF) module at its output stage. The neck network features a bidirectional path aggregation network (PAN-FPN) for efficient feature integration [14]. However, the backbone and neck networks of YOLOv8 exhibit several limitations, including the restricted feature extraction capability of C2f module, high computational complexity, and a substantial number of standard convolution parameters [15]. Additionally, the complete intersection over union (CIoU) loss function does not adequately account for the characteristics of the background region, which may lead to the neglect of surrounding contextual information, consequently diminishing detection performance [16].  
To address these challenges, including the large model size in fire detection tasks and the difficulty in balancing detection accuracy with model efficiency, this paper achieves several improvements to the backbone network, neck network, and loss function based on the YOLOv8n architecture, and develops the DVCW-YOLO detection model. The overall architecture of the DVCW-YOLO model is illustrated in Figure 1. All standard convolutions in both the backbone and neck networks are replaced with the more lightweight DWConv. Additionally, we introduce the C2 fcBAM module in the backbone network, which incorporates the CBAM attention mechanism at both the input and output ends of the C2f module. This new module replaces the original C2f module, enhancing the model's ability to extract features from key areas by emphasizing salient features and suppressing less important features. Secondly, the C2f module is replaced with global structure-aware convolution (GSConv) and the more efficient VOVGSCSP module in the neck structure, reducing both the number of model parameters and the overall model complexity. Finally, the WIoU loss function is used to replace the traditional CIoU loss function. This modification ensures that the improved model focuses more on normal and high-probability samples, thereby enhancing detection accuracy.
## 3 Results
### Change Ratio
#### 3.2.1 Stride Length  
In Figure 8, we see the change values for stride length for the Base-Post and Before-After comparisons. The repeated measures ANOVA revealed a significant effect of the condition on the value (\(F=26.2;p<0.0001\)). Multiple comparison testing with Benjamini-Hochberg correction revealed significant differences between all pairs of conditions, except SI and PI (\(t(74)=1.85;p=0.08\)) and PI and PD (\(t(74)=1.46;p=0.15\)). Additionally, the change values for Base-Post were lower in magnitude than those for Before-After, which indicates a weaker carry-over effect.  
As expected, the SI condition showed increases in both the Base-Post and Before-After change values, 6.2% and 2.6%, respectively. Additionally, there was a significant difference between the two comparisons in the SI condition (\(t(36)=3.47;p=0.006\)). The PI and PD conditions both had similar increases for both Base-Post and Before-After change values. However, they were not as large and had a larger standard deviation. Additionally, they had no significant differences between the two comparisons.  
The SD condition showed the expected decreases in both the Base-Post and Before-After change values. This is the only condition with decreases in the change values. There  
Figure 8: The stride length change ratio values showing the comparison between the Base and Post sections (Base-Post) = \(\frac{\text{Post}-\text{Base}}{\text{Base}}\) and the change between the Before and After sections (Before–After) = \(\frac{\text{After}-\text{Before}}{\text{Before}}\). SI—Spatial Increase; SD—Spatial Decrease; PI—Phase Increase; PD—Phase Decrease. **—\(p<0.01\); ***—\(p<0.001\).  
was also a notable significant difference between the Base-Post and Before-After change values (\(t(36)=5.36;p=0.0003\)). The SD Before-After values had the largest difference amongst the conditions, a decrease of 12.6%, while the SD Base-Post values had the smallest one, with a decrease of only 0.8%.
###### Abstract  
EEG signals may be affected by physiological and non-physiological artifacts hindering the analysis of brain activity. Blind source separation methods such as independent component analysis (ICA) are effective ways of improving signal quality by removing components representing non-brain activity. However, most ICA-based artifact removal strategies have limitations, such as individual differences in visual assessment of components. These limitations might be reduced by introducing automatic selection methods for ICA components. On the other hand, new fully automatic artifact removal methods are developed. One of such method is artifact subspace reconstruction (ASR). ASR is a component-based approach, which can be used automatically and with small calculation requirements. The ASR was originally designed to be run not instead of, but in addition to ICA. We compared two automatic signal quality correction approaches: the approach based only on ICA method and the approach where ASR was applied additionally to ICA and run before the ICA. The case study was based on the analysis of data collected from 10 subjects performing four popular experimental paradigms, including resting-state, visual stimulation and oddball task. Statistical analysis of the signal-to-noise ratio showed a significant difference, but not between ICA and ASR followed by ICA. The results show that both methods provided a signal of similar quality, but they were characterised by different usabilities.  
artifact subspace reconstruction; EEG signal analysis; independent component analysis; automatic EEG data correction
## 2 Strength Variation of Cement-Stabilized Base Courses
### Results  
#### 2.2.1 Compactness  
Figure 1 shows the compressive strength of cement-stabilized macadam specimens with different compaction for different curing durations. The compressive strength of the base increased linearly with increasing compactness (Figure 1). When the curing time was 7 days, the compactness increased by 2% and the compressive strength increased by 0.4662 MPa on average. When the curing time was 28 days, the compactness increased by 2% and the compressive strength increased by 0.3324 MPa on average. The influence on strength was gradually reduced, and the relationship between compressive strength and compactness at different ages was linear, such as in Equations (1) and (2):  
\[7\text{d}:\ \sigma_{s}=0.231K-18.831\ \ \ \ R^{2}\ =\ 0.99, \tag{1}\]  
\[28\text{d}:\ \sigma_{s}=0.1662K-10.635\ \ \ R^{2}\ =\ 0.98. \tag{2}\]  
In the equation, \(\sigma_{s}\) is compressive strength in MPa and \(K\) is the degree of compaction %.  
Figure 2 shows the splitting strength of cement-stabilized macadam specimens with different compaction after different curing times. Splitting strength linearly decreased with decreasing compactness for specimens cured for 7 days (Figure 2). Average splitting strength decreased by 0.0266 MPa for every 2% reduction in compactness, and the variation of splitting strength with compactness for 28 days was slightly different. Splitting strength decreased by 0.02 MPa, 0.04 MPa, and 0.07 MPa when compactness decreased from 102% to 100%, 98%, and 96%, respectively, as the decreasing rate accelerated. This phenomenon occurred because the gap in the material increased with decreasing compaction degree. The interior of the material increased in weak points, thereby reducing the cohesive force and friction between particles. This kind of defect is more and more obvious with increasing age, so the base compaction must meet the requirements of the technical specification for highway road base construction.  
Figure 1: Compressive strength under different test procedures: (**a**) The relationship between compaction and compressive strength after 7 days of curing; (**b**) the relationship between compaction and compressive strength after 28 days of curing.
# A Novel Anomaly Behavior Detection Scheme for Mobile Ad Hoc Networks
## 2 Background
### Security Issues in MANETs
The classical ZRP routing protocol does not use any security mechanism; however, it is employed in many applications where security is predominantly required. As the ZRP is a hybrid protocol, it has the advantages of both preventive and reactive protocols. Researchers have proposed enhanced versions of the ZRP that incorporate security mechanisms [16; 17; 18]. Thus, from the literature insights above, it can be inferred that security enhancement in the routing protocols is essential to protect against hostile attacks.
## 5 Conclusions  
We have proposed a new approach to eigen-decomposition as an essential reconstruction method for OCTA, which is windowed-ED (wED). The wED algorithm can be used to extract blood-flow signals from repeated scanning at the same position. This algorithm can reduce motion artifacts and improve PSNR performance compared to other algorithms for OCTA. Therefore, wED can be used for both animal models and human participants, especially when motion effects occur. This study can also be served as a guide for others to utilize our new, optimized, and easy-to-deploy wED algorithm.  
Conceptualization, T.Z. and K.Z.; methodology, T.Z.; software, T.Z.; validation, T.Z., K.Z., C.L. and Z.H.; formal analysis, T.Z.; investigation, T.Z., K.Z., H.R.R. and A.P.; resources, H.R.R. and A.P.; data curation, T.Z.; writing--original draft preparation, T.Z.; writing--review and editing, W.W., Z.W., C.L. and Z.H.; visualization, T.Z.; supervision, C.L. and Z.H.; project administration, K.Z., J.L.C., C.L. and Z.H.; funding acquisition, J.L.C. and Z.H. All authors have read and agreed to the published version of the manuscript.  
The establishment of the mouse model was funded by a Wellcome Trust and Royal Society Sir [PERSON] to Dr. [PERSON] (202581/Z/16/Z), and a Chancellors Fellowship PhD studentship, which was funded through Dr. [PERSON]'s fellowship, to Dr. [PERSON].  
All animal procedures were performed under PIL I61689163 and PPL PD3147 DAB (January 2018-January 2021) and conducted with approval from the local ethical review committee at the University of Edinburgh and under UK Home Office regulations (Guidance on the Operation of Animals, Scientific Procedures Act, 1986).  
Not applicable.  
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to ethical restrictions.  
We would like to express our gratitude to [PERSON], [PERSON], and [PERSON] for their supports.  
The authors declare no conflict of interest.  
Figure 17: The comparisons of en face results from maximum intensity projection using different algorithms. (**A**) Registration from 4-time acquisitions; (**B**) SV; (**C**) aED; (**D**) bED; (**E**) wED. (All scale bars represent 500 \(\upmu\)m); SV: Speckle Variance; aED: A-scan eigen-decomposition; bED: B-scan eigen-decomposition; wED: windowed eigen-decomposition.