esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Conclusions  
In this paper, we propose a smart washer and prestressing force index for monitoring the prestressing force of steel strands. The problem of energy saturation was effectively mitigated by installing a smart anchor washer on the anchor. During prestress tension tests,  
Figure 11: The index H\({}_{5\text{-}\text{Shannon}}\) for prestress monitoring: (**a**) entire frequency range (0–1000 kHz), (**b**) low-frequency range (0–600 kHz), (**c**) high-frequency range (600–1000 kHz), and (**d**) average value of the high-frequency range.  
PZT patches were used on the upper and lower annular cylinders to excite and receive signals transmitted through the contact interface. The received signals were quantized using wavelet packet decomposition. It is evident from the results that as the tension force increases, the energy of the received signal also increases. This finding aligns with the theory that relates the passing wave to the contact area. The degree of prestressing force was successfully evaluated by using Shannon entropy extracted from the signal as the prestressing force index. The proposed method is low-cost, simple, and feasible, and it allows for the monitoring of prestressing force in steel strands. It should be noted that the method presented here is only applicable to anchored prestressing force in post-tensioned anchorage systems and is not applicable to any general location along the layout of prestressing tendons. The significant variation in test results may be attributed to the control of tension force during the test and the design precision of the smart anchor washer. Based on the method proposed in this paper, the testing accuracy is expected to be further improved in the future. Furthermore, the research will focus on analyzing the difference in prestress in each steel strand using an array of PZT transducers.  
Conceptualization, L.W. and L.Z.; methodology, L.W.; software, L.W.; validation, L.W., L.Z. and D.M.; formal analysis, D.M.; investigation, L.W.; resources, X.W.; data curation, D.M.; writing--original draft preparation, L.W.; writing--review and editing, L.W.; visualization, L.W.; supervision, L.Z.; project administration, X.W.; funding acquisition, L.Z. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
All data that support the findings of this study are included within the article.  
The authors declare no conflicts of interest.
## 2 Reliability Analysis and Reliability-Based Design Optimization
### Reliability Analysis Using the First-Order Reliability Method
Several search algorithms [38,39,40] integrating multiple design points have been proposed as an effort to improve the accuracy of reliability analysis.
# Transfer Learning-Based Classification of Maximly Sinus Using Generative Adversarial Networks
###### Abstract
GANs serve an important function in producing synthetic pictures, which enrich the dataset and improve the performance of CNN models. The use of GANs in medical imaging, particularly for sinus diseases, adds a new dimension to image synthesis and data augmentation [12]. GANs help to overcome dataset size limits, improving the generalization power of deep learning models. This work investigates the use of GANs to resolve imbalances in sinusitis datasets, resulting in a more complete and diversified dataset for training. The purpose of this study is to create customized CNN models that can not only detect sinusitis but also assess its severity using CT scans. The customized CNNs are tuned to the unique characteristics of sinus-related illnesses, allowing for a more precise and nuanced diagnosis. This study's contribution is the unique use of GANs for data balancing and the building of CNN models specialized in severity evaluation, which advances the capabilities of deep learning in the area of sinus-related medical imaging. The contributions of this research are outlined as follows:  
* Implement generative adversarial networks (GANs) to address data imbalance issues and enhance the dataset by generating synthetic samples, ensuring a more robust and balanced representation of various cases. * Develop and customize convolutional neural network (CNN) models specifically tailored for the diagnosis of the severity in CT images related to sinus-related pathologies, providing a targeted and optimized approach for accurate assessment and classification. The rest of this study is structured as follows: Section 2 introduces the relevant studies. Section 3 elaborates on the proposed framework, dataset, and experimental design. Section 4 demonstrates model evaluation and experimental results. In Section 5, the conclusion and future work are discussed.
## 4 Discussion  
### The Effects of Different Additives on the Nutritional Quality of Corn Straw Silage  
During the silage process, the nutritional quality of the silage material undergoes changes due to a series of biological activities, influenced by both the raw material itself and the microorganisms involved [29; 30]. In this study, after 60 days of ensiling, the crude protein (CP) content in the additive-treated groups was significantly higher than that in the control (CK) group. This finding aligns with the results of [PERSON] et al. [31], who examined the effect of cellulase on whole-plant corn silage. The improvement in CP content may be attributed to cellulase accelerating the breakdown of cellulose, which provides additional fermentation substrates for lactic acid bacteria. These bacteria, in turn, produce more lactic acid (LA), lowering the pH, inhibiting proteinases from hydrolyzing proteins, and suppressing the growth of harmful microorganisms that also degrade proteins [32]. As a result, the fermentation quality of the corn straw silage is enhanced. [PERSON] et al. [33] reported that the addition of cellulase and xylanase to barley straw silage significantly reduced the acid detergent fiber (ADF) content. In the present study, after 60 days of silage, the ADF content in samples treated with both low and high concentrations of cellulase was significantly lower than in the CK group. This result is consistent with previous studies and may be attributed to cellulase degrading the cell walls of corn straw, leading to the release of more soluble sugars. In terms of nutritional quality, the group treated with xylanase showed the best results.
## 4 Experiments and Results
### Case Study
#### 4.5.2 Example 2  
In this second example the following user preferences are considered:  
* **Price**: very high.
* **Cuisine**: grill, barbecue, bar.
* **Special Diets**: no gluten, vegetarian.
* **Meals**: dinner, drinks, late night.
* **Features**: private dining, serves alcohol, table service, free WiFi, credit cards, outdoor seating, parking, full bar.
* **Distance**: restaurants in the city centre are preferred.  
We keep the same weight for all criteria and the same ELECTRE thresholds as in the previous example. The utility values of the domain criteria are shown in Figure 10 and the ranking results of the two cases (without and with the social-based criteria) are shown in Figure 11. As we can see, there are clear differences in the two ranking graphs. For example, the alternative \"La Caleta\" changes from the third to the first position. On the other hand, the alternative \"Les Coques\" is downgraded from position 1 to position 8 and \"AQ\" is downgraded from position 2 to position 7. The analysis of the domain performance table for this example, depicted in Figure 10, shows that the more relevant criteria are price, distance to the city centre and features, in this order.  
Changes similar to those reported in the first example may also be noted here. For example, the restaurant \"Les Coques\", which was the best in terms of domain criteria, goes down to the middle of the ranking when users' opinions are considered.  
Given all that, we can conclude that the incorporation of the social-based criteria adds more constraints to the ranking process. However, we believe that the integration of the users' reviews with the decision-maker preferences needs more investigation to improve the results. The next section discusses this point in more detail.  
Figure 10: Profile 2: the domain performance-table. The colour indicates the degree of satisfaction, and colours range from green, the worst, to red, the best.  
Figure 11: Profile 2: ranking result.
## 2 Results and Discussion
### Physical Properties and Fabrication Process of PFGI-POF
#### 2.1.2 Measurement of the Numerical Aperture (NA)  
The evolution of the PFGI-POF numerical aperture (far field measurement according to the standardized procedures [15,16]) is reported in Figure 7. A mean value (measured at 5% of the maximum intensity) close to #0.18 has been exhibited for the four, PFGI-POF which is near the datasheets values. This value is lower than the NA values of the glass multimode fibers (NA\({}_{\mathrm{glass}}\)\(\sim\) 0.2). This measurement is effectively important particularly for producing the best optical coupling efficiency between the used laser and the PFGI-POF. In our case, most of this study complies with the use of a vertical cavity surface emitting laser, having a NA close to 0.3. It can be noted that the NA value of a PMMA based POF is close to 0.5.  
\begin{table}
\begin{tabular}{|c|c|c|c|c|c|c|} \hline  & **IEC** & \begin{tabular}{c} **Core/cladding** \\ **diameters (\(\upmu\)m)** \\ \end{tabular} & \begin{tabular}{c} **\(\upalpha\)at 850 nm** \\ **(dB/km)** \\ \end{tabular} & \
\begin{tabular}{c} **\(\upalpha\)at 1,300 nm** \\ **(dB/km)** \\ \end{tabular} &
\begin{tabular}{c} **Modal bandwidth at** \\ **850 nm (MHz km)** \\ \end{tabular} & **NA** \\ \hline Lucina & A4g & 120/490 & 18 & 18 & 350 & 0.185 \\ \hline Lucina-X & A4g & 120/490 & 18 & 18 & 350 & 0.185 \\ \hline GigaPOF-50 SR & & 50/490 & 40 & 40 & 300 & 0.19 \\ \hline GigaPOF-62 SR & A4h? & 62.5/490 & 40 & 40 & 300 & 0.19 \\ \hline GigaPOF-120 SR & A4g & 120/490 & 40 & 40 & 300 & 0.185 \\ \hline \end{tabular}
\end{table}
Table 1: Overview of the commercially available POF.
## 5 Conclusions  
For the long-term safety of a near-surface disposal facility, concrete-designed barriers are still sufficient safety features. The simulation of concrete degradation in this study attempted to prove this assertion. The findings showed that even in their most deteriorated form, concrete structures do not cause a significant release of radionuclides into the environment. The most degraded condition IV of the concrete emitted a maximum dose of 1.4 \(\times\) 10\({}^{-8}\) mSv/yr in drinking water drawn from a hypothetical well 300 m from a disposal site. Aside from being significantly lower than the regulatory limit of 0.1 mSv/yr, the most degraded state of concrete poses no significant radiation exposure risk, as the bulk of radionuclide activity will have decreased by the time the concrete reaches its worst-case condition of degradation. Certain key variables were subjected to a sensitivity analysis (Kd, Ds and density) and radionuclide concentration in well water was found to be inversely related to distribution coefficient (Kd) and density, but directly proportional to diffusion coefficient (Ds). The findings of this study also highlight the importance of radionuclide sorption in designing barriers to preventing their migration to the environment. The general view is that engineered features with higher sorption properties will increase the safety of disposal facilities.  
Conceptualization, A.M. and J.K.; methodology, A.M. software, A.M.; validation, A.M. and J.K.; formal analysis, A.M.; investigation, J.K. and A.M.; resources, J.K. and A.M.; data curation, A.M.; writing-original draft preparation, A.M.; writing-review and editing, J.K.; visualization, A.M.; supervision, J.K.; project administration, J.K.; funding acquisition, J.K. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Korea Institute of Energy Technology Evaluation and Planning (KETEP) grant funded by the Korean government (MOTIE) (No. 20203210100060, Development of High Performance Cement Materials and Solidification Technology for Immobilization of Liquid Radioactive Wastes). This research was also supported by the 2022 Research Fund of the KEPCO International Nuclear Graduate School (KINGS), the Republic of Korea.  
Not applicable.  
The data that support the findings of this study are available on request from the corresponding author.  
The authors declare that they have no conflict of interest.
# A Multi-Path Semantic Segmentation Network Based on Convolutional Attention Guidance
## 4 Experiment  
### Datasets and Experimental Setup  
Our network is evaluated on three popular datasets: ADE20K [29], Cityscapes [30] and COCO-Stuff [31]. ImageNet [32] stands out as the most renowned image classification dataset, featuring 1000 categories. Following a common practice in segmentation methods, this study uses ImageNet to pre-train the main path (MP) of the MCAG encoder.  
ADE20K [29] is a challenging dataset with 150 semantic classes, consisting of 20,210/2000/ 3352 images for training, validation and testing sets, respectively. Cityscapes [30] focuses on urban scenes, presenting 5000 high-resolution images with 19 categories. The dataset is divided into 2975/500/1525 images for training, validation and testing. COCO-Stuff [31] is another challenging dataset, encompassing a total of 172 semantic classes and 164,000 images.  
The experiments in this paper were conducted using PyTorch [33] and the mmsegmentation library [34]. The main route of the segmentation model's encoder was pretrained on the ImageNet-1K dataset [32]. The mean intersection over union (mIoU) was employed as the segmentation evaluation metric. All models were trained on nodes equipped with two RTX 3090 GPUs.  
For the pre-training on ImageNet, the data augmentation methods and training settings were consistent with DeiT [35]. Common data augmentation techniques, including random horizontal flipping, random scaling (from 0.5 to 2) and random cropping, are applied for segmentation experiments. The batch size for the Cityscapes dataset is set to 4, while for the other datasets, it is set to 8. The AdamW optimizer [36] is used for training. The initial learning rate is set to 0.00006, and a multi-learning rate decay strategy is employed. The ADE20K model is trained for 160K iterations, and the Cityscapes and COCO-Stuff models are trained for 80K iterations.
# Microsphere Polymers in Molecular Imprinting: Current and Future Perspectives
## 4 Green Aspects in Molecularly Imprinted Microspheres  
In developing an economic, reliable, sustainable, and environmentally friendly approach, the reusability and stability of the imprinted material plays an important role. It is well-known that polymer degradation products can also contaminate the sample during its application. There are four main factors that affect the reusability and stability of MIP, namely the crosslinker, crosslinking degree, condition template extraction and functional monomer. These factors were investigated by [PERSON] et al. [144] using eleven different \(\upiota\)-phenylalanine methyl ester (ME)-imprinted polymers in various compositions. Their study conducted an evaluation of long-term stability and reusability via performing adsorption-regeneration cycles up to 100 times. In terms of the crosslinking degree, DVB-based polymers showed a great result where DVB-based polymers can be reused at least 100 times without losing its template affinity under acidic and basic conditions and elevated temperature (65 \({}^{\circ}\)C). In contrast with DVB-base polymers, the crosslinking degree of acrylamide and methacrylate-based polymers decreased in both acidic and basic conditions due to their irreversible degradation. As discussed above, both the acrylamide and methacrylate crosslinker are commonly used in MIM preparation. This can be a challenge for future research in developing a long-term stable and reusable formulation of MIMs.  
Reducing the use of solvents and energies could also have a significant impact. These aspects were deeply discussed by several studies [145; 146; 147]. According to these studies, alternative approaches that can be considered include the use of green templates, green monomers, green solvents such as porogens and template removal solvents, green crosslinkers and initiators, energy efficiency, incorporation of ultrasound and microwaves in promoting reaction rates, miniaturized techniques, and the use of computational tools for optimizing both the polymer and synthesis process. Energy efficiency is crucial, since higher energy needs cause significant impacts for the environment, such as global warming. As mentioned above, all CRPP techniques can be carried out at mild temperature conditions, which is beneficial in terms of the environmental aspect.
# Design and Analysis of High-Capacity MIMO System in Line-of-Sight Communication
## 5 Applications
### Applications in Inter-Satellite Communication  
The above theory can be applied not only to short-distance LoS coupling train communication, but also to inter-satellite communication in a non-scattering LoS environment. In inter-satellite communication, the distance of transceiver antennas is relatively farther, which means that the aspect ratio \(\xi\) is large. In order to ensure the proper spacing of the antenna elements, the signal transmission frequency needs to be increased. However, the frequency of satellite communication is primarily focused on the Ka frequency range (26-40 GHz) and frequencies will be higher in the future. The \(2\times 2\) MIMO inter-satellite communication system is shown in Figure 12.  
The proper array element spacing \(d_{s}\) and the signal frequency \(f\) can be determined at a long distance \(d\) of transceiver antennas according to Equation (35) to obtain the largest channel capacity. Table 5 provides recommendations for antenna configurations in inter-satellite communication.  
As shown in Table 5, when the signal wavelength \(\lambda\) is constant, the larger the array element spacing \(d_{s}\) is, the longer the transmission distance \(d\) will be. In other words, we can choose an appropriate signal wavelength \(\lambda\) according to the propagation distance \(d\) and the array element spacing \(d_{s}\). In inter-satellite communication, due to the long distance between the transmitting and receiving antennas, it is necessary to appropriately increase the distance between the antenna elements and the signal frequency to obtain the maximum channel capacity.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \(f\) (GHz) & \(\lambda\) (m) & \(d\) (m) & \(d_{s}\) (m) \\ \hline
2.6 & 0.1154 & 10 & 0.8779 \\
2.6 & 0.1154 & 20 & 1.2409 \\
3.5 & 0.0857 & 10 & 0.7565 \\
3.5 & 0.0857 & 20 & 1.0694 \\
5.6 & 0.0536 & 10 & 0.5979 \\
5.6 & 0.0536 & 20 & 0.8453 \\
28 & 0.0107 & 10 & 0.2673 \\
28 & 0.0107 & 20 & 0.3780 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Recommendations for \(3\times 3\) MIMO system of virtual coupling train.  
Figure 12: The \(2\times 2\) MIMO inter-satellite communication system.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \(f\) (GHz) & \(\lambda\) (m) & \(d\) (m) & \(d_{s}\) (m) & \(\xi\) \\ \hline
30 & 0.01 & 50 & 0.05 & 100 \\
30 & 0.01 & 5000 & 0.5 & 1000 \\
40 & 0.
# Six Sigma-Based Frequency Response Analysis for Power Transformer Winding Deformation
## 5 Conclusions  
This study introduced FRA6\(\sigma\), a novel framework integrating frequency response analysis with Six Sigma statistical tools to enhance the objectivity and precision of transformer fault diagnosis. By applying control charts and process capability indices (\(C_{p}\) and \(C_{pk}\)), the method quantifies deviations in response signatures, enabling the early detection of winding deformation, insulation degradation, and other mechanical anomalies. Validation across three transformer case studies demonstrated that FRA6\(\sigma\) improved diagnostic sensitivity by 31.25% and identified faults earlier than traditional FRA or physical inspection. The method's ability to link frequency deviations to specific fault types across defined bands ensures structured, repeatable condition assessment. FRA6\(\sigma\) transforms FRA interpretation from a subjective, experience-based task to a data-driven, statistically grounded process. Its adoption can strengthen predictive maintenance strategies, reduce unexpected failures, and extend transformer lifespan.  
Moving forward, future research should focus on expanding the dataset to include a broader range of transformer types, operational stressors, and environmental conditions to further validate the methodology. Additionally, automation of statistical control charts and integration with machine learning algorithms could enhance the predictive accuracy of FRA6\(\sigma\), making it a fully automated fault diagnosis tool for real-time transformer monitoring. Further field trials across utility-scale transformers will also be instrumental in confirming the long-term effectiveness and reliability of the methodology in diverse grid conditions.  
This research received no external funding.  
**Institutional Review Board Statement**: Not applicable.  
**Informed Consent Statement**: Not applicable.  
**Data Availability Statement**: The raw data supporting the conclusions of this article will be made available by the authors on request.  
**Conflicts of Interest**: The author declares no conflicts of interest.
# A Survey of Wi-Fi 6: Technologies, Advances, and Challenges
## 5 SR in Wi-Fi 6
### Challenges with SR in Legacy Wi-Fi  
With SR, different BSSs utilize the same channel via the CSMA/CA protocol. When BSSs overlap and use overlapping channels, they cause more collisions [110] and a poor data rate. This leads to problems with legacy Wi-Fi that we illustrate in the following figure Figure 13.  
Figure 12: Two overlapping BSSs: the smartphone and the laptop are in the hearing range of both access points.  
The NAV is a timer that helps to block stations during an ongoing transmission. The backoff is paused during the NAV, forbidding the competing stations to start their transmission. In legacy Wi-Fi, only a single NAV exists and is updated after overhearing any transmissions. Thus, it may cause collisions if two different BSSs have parallel transmissions with different durations. A node may be a neighbor of the two transmitters that belong to two different BSSs. This neighbor will overhear the first RTS/CTS reservation and update its NAV. Then, the same neighbor will overhear the second RTS/CTS from the second BSS and will overwrite the existing NAV with those contained in the new RTS. If the second NAV value is short enough, the neighbor may create a collision since it will consider erroneously that the medium has been released.  
If a station receives an RTS with a weak signal strength, the sender is far away from the receiver station. Then, the upcoming transmission will not be impaired by a potential transmission of the receiver. In that case, setting the NAV by the receiver station is not needed. This unnecessarily prevents the receiver station from sending, which is a waste of transmission resources.