esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
VS has shown success, particularly with FDM ABS parts, utilising Acetone vapour treatment to enhance the surface finish [55; 56; 57; 58; 59; 60]. The chemical vapours enhance the surface finish of ABS replicas by softening the external layer. Acetone breaks the secondary bonds between ABS polymer chains, enabling the chains to slide past one another and settle into more stable positions. Specifically, on the surface of the ABS part, acetone erodes material from the upper surface, prompting a re-flow process that effectively fills the air gaps created during the layer-by-layer fabrication of the part [61]. However, there is no research that demonstrates a cold embossing (temperature between 18 and 21 \({}^{\circ}\)C) process for ABS 3D-printed parts after the VS stage. Numerous studies shown the potential for significant improvement in the surface finish. Within this process there is a post-processing opportunity to further modify the surface using micropattern tooling. By utilising polymer re-flow in the HE processes, it is possible to modify the surface of ABS parts at room temperature, thereby negating the T\({}_{\text{e}}\). Using a developed VS post-processing chamber and integrating it into an automation cell with a 6-axis robot, this research will demonstrate a production line for micro-texturing of an ABS substrate with a Fresnel lens design. The imprinting process will be automated, and then the quality of the lens replication will be compared to the master tool pattern. The paper is organised as follows: Section 2 discusses the experimental setup, as well as the test apparatus and methodology adopted to investigate the capability of the replication process. Next, in Section 3, the design of experiments for conducting the research is discussed together with the approach adopted for analysing the results. The experimental results are presented and the relationship between VS process parameters and replication quality is analysed. Section 4 discusses the results of the experiment design. Finally, in Section 5, the main conclusions from the conducted study and recommendations for improved automation of the VS cold embossing process is presented.
## 4 Conclusions  
The results of antioxidant, antimicrobial and antib biofilm activity analysis of _G. hederacea_ extracts obtained via SC-CO\({}_{2}\) under different conditions of the process using methanol as a co-solvent show that the temperature of extraction affects the biological activity of the tested product. Overall, the results indicate that the SC-CO\({}_{2}\) extracts are characterized by high TPC values that differ depending on the extraction conditions. The high TPC values correlate with high antioxidant properties, as well as antimicrobial (excluding filamentous fungi) and antib biofilm activity (the prevention of biofilm formation). Among the tested extracts, the most promising results were obtained for the extract obtained at 40 \({}^{\circ}\)C, including the highest TPC value, as well as the best-performing antimicrobial and antioxidant properties. All tested extracts were effective in controlling biofilm formation of the studied bacteria at MIC concentration, but only the extract obtained at 60 \({}^{\circ}\)C efficiently removed formed biofilm. _G. hederacea_ extracts obtained using SC-CO\({}_{2}\) could have promising applications at different stages of food production, as well as in the industry as a safe alternative to chemical preservatives or disinfectants due to their demonstrated properties.  
The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/app12073572/s1](https://www.mdpi.com/article/10.3390/app12073572/s1)]([https://www.mdpi.com/article/10.3390/app12073572/s1](https://www.mdpi.com/article/10.3390/app12073572/s1)), Figure S1: The fungistatic activity of obtained _G. hederacea_ CO\({}_{2}\) extracts against (a) _F. graninearum_, (b) _F. cultorum_, (c) _A. alternata_, (d) _B. cinerea_ and (e) _S. scleroorum_, expressed as MIC and MFC values. C--control; M--methanol; GH 40--G. hederacea_ CO\({}_{2}\) extract (extraction conditions: 40 \({}^{\circ}\)C/250 bar); GH 50--G. hederacea_ CO\({}_{2}\) extract (extraction conditions: 50 \({}^{\circ}\)C/250 bar); GH 60--_G. hederacea_ CO\({}_{2}\) extract (extraction conditions: 60 \({}^{\circ}\)C/250 bar); Cp--percentage concentration of CO\({}_{2}\) extracts.  
Conceptualization, D.G., K.M., K.J. and A.W.; methodology, D.G., K.J., K.M., P.A.U., S.F. and A.W.; validation, K.J., S.F. and A.W.; formal analysis, K.M., D.G., R.G. and A.W.; investigation, D.G., K.J., P.A.U., S.F., K.M. and A.W.; resources, D.G., K.M., K.J., R.G. and A.W.; data curation, K.J. and A.W.; writing--original draft preparation, D.G., K.M., K.J., P.A.U., S.F., R.G. and A.W.; writing--review and editing, D.G., K.M. and K.J.; visualization, D.G., K.J., P.A.U., S.F. and K.M.; supervision, D.G. and A.W.; project administration, R.G. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Polish National Science Centre, grant number 2018/31/B/N29/03485.  
Not applicable.  
**Data Availability Statement:** Publicly archived datasets are not available.  
The authors declare no conflict of interest.
## 4 Simulation Evaluation
### Comparison with Other Methods
#### 4.3.2 Result in the Mobile Sink Scenario  
Table 7 shows the simulation results of the three methods in the mobile sink scenario. The results on network lifetime when the number of nodes is 100 and 300 are shown in Figure 10.  
Table 7 indicates that as the number of data collection points increases, the maximum energy consumption decreases. As a result, the network's lifetime is prolonged. The network's lifetime is the longest when collecting at four points using SC-Sched regardless of the number of nodes. In WuR-TDMA, as mentioned in Section 4.3.1, energy consumption due to receiving routing and transmission timing information is large, and the amount of routing and transmission timing information increases in proportion to the number of nodes. Therefore, the improvement in network lifetime is higher in SC-Sched than in WuR-TDMA, and the difference increases with the number of nodes. These results are also visually shown in Figure 10.  
Compared with the result in Figure 8, the difference in network lifetime between SC-Sched and WuR-TDMA may seem less than expected. This is because the difference in Figure 8 only occurs during the data-collection process without considering the power consumption in the long sleep period. In the mobile sink scenario, the sink node collects data 24 times during 24 h, and the energy consumption in the sleep state accounts for the majority of the total energy consumption. Hence, the power difference between WuR-TDMA and SC-Sched in the data-collection process is not very obvious and has little impact on network lifetime. Because WuR-TDMA imple  
Figure 9: Data collection time in the four methods under different numbers of sensor nodes.  
of SC-Sched, this also confirms the effectiveness of SC-Sched. When the data collection frequency increases, the percentage of power consumption due to data collection will increase and SC-Sched will show more superiority.  
In SC-Sched, the improvement in network lifetime in times of 300 nodes is higher than that in times of 100 nodes. This means that the higher the number of nodes, the higher the effect of traffic load balancing by sink movement.
# SBNN: A Searched Binary Neural Network for SAR Ship Classification
###### Abstract
Nowadays, NAS can break through the limitation of subjective understanding and has been considered as an automatic way to design neural networks. To obtain an accurate CNN for SAR ship classification, we construct a super-net and iteratively solve the corresponding bi-level optimization problem under the guide of NAS. However, we observe that pooling operations and Skip Connection acquire large weights through experiments. The searched cells which are nearly filled by weight-free operations lead a decreased feature extraction capability of the corresponding target network. To improve the performance, weight-free candidate operations are ignored when searching the target CNN for SAR ship classification. 3. A novel method to construct an efficient binary network for SAR ship classification is proposed. The searched CNN with the excellent accuracy is too complex to be implemented on mobile or embedded devices. With the development of binary networks, the gap between binary networks and floating-point networks is narrowing. With the help of binary technology including distribution reshaping and binary blocks, we construct binary cells replacing the floating-point cells. After binarization and scaling, the 1-bit network, SBNN, strikes a good trade-off between accuracy and efficiency. Compared with its floating-point prototype, SBNN only requires 0.37 M MAdds with a 2% lower accuracy than the searched CNN. Meanwhile, thanks to the integration of NAS, our proposed SBNN outperforms binary neural networks from computer vision by 2% for the accuracy while nearly achieving a 3\(\times\) reduced number of MAdds. 4. A patch shift processing is proposed to enhance the learning of SBNN. SAR images usually have a poorer quality than natural optical images, which lays stress on the necessity of learning the feature distribution for a binary networks. The existing binary network technology reshapes the feature distribution channel-wisely without touching the spatial level. Recently, research about spatial attention has shown that processing the spatial information has a positive effect on performance. Hence, we divide feature maps into several patches. Each patch of each channel is adjusted by a learnable parameter. This processing enhances the performance of our binary network by reducing the local noise and the information irrelevant to the targets. Experimental results show our proposed processing further increases the accuracy of SBNN. The rest of this paper is organized as follows: Section 2 reviews the related work. In Section 3, SBNN is presented with details. The results of experiments and ablation studies are shown in Section 4. Section 5 concludes this paper.
# Path Planning for Localization of Radiation Sources Based on Principal Component Analysis
## 3 Experiments
### Simulations
#### 3.1.3 Condition (c) Multiple Radiation Sources Dispersed
At the 11 th measurement point, the impact of radiation source 1 was  
Figure 14: Simulation results of dispersed multiple radiation sources: (**a**) The results obtained when the threshold was set to 5000 (**b**) The results obtained when the threshold was set as 2500. It was confirmed that the measurement path significantly depends on the setting of the threshold required to switch the principal component vector. significantly greater than that of radiation source 2. Accordingly, a path was generated to solely surround radiation source 1. In an environment where multiple radiation sources were dispersed, it was confirmed that path planning significantly depends on the setting of the threshold required to switch the principal component vector. This challenge can be addressed by devising a procedure for adopting the proposed method. In the initial stage, the location of the radiation sources is approximately estimated by setting the threshold to a small value. If a specific location of radiation sources is required, an additional investigation can be performed by increasing the threshold value. To address this challenge, additional simulations were conducted under the same conditions. In the initial stage, the robot moved and measured gamma rays with the threshold set to 1000. The movement distance of the mobile robot at each time step between the measurement points was set to 1 m. Figure 15a presents the determined path and the reconstructed distribution map with the proposed method in the initial stage. The red dots denote the two radiation sources, and the black line represents the determined path with the proposed method. It was confirmed that a path primarily surrounding the two radiation sources was generated. By setting a small threshold value, measurement points away from the sources were determined. It was confirmed that two location around the sources showed high values; however, there was no clear distinction between these locations. To perform a more specific investigation, the threshold value was changed from 1000 to 3000. The robot started from the initial stage end point and continued the investigation. The movement distance of the mobile robot at each time step between the measurement points remained unchanged. Figure 15b depicts the determined path and the reconstructed distribution map with the proposed method. The red line denotes the determined path in the second stage. It was confirmed that the robot passed between the two sources and circumnavigated one source at a short distance. Through this additional investigation, the distribution map was updated, and the area around the two sources was clearly divided. These results confirm that an additional investigation can be performed by increasing the threshold value if a more specific investigation is required.
## 3 Methods
### Metrics  
The effectiveness of SAM 2's segmentation results will be evaluated using the Jaccard index (\(JCI\)) Equation (1) and the Dice score (\(DSC\)) Equation (2). These metrics are widely employed to assess the similarity between \(A\) and \(B\) images.  
\[JCI(A,B)=\frac{|A\cap B|}{|A\cup B|}, \tag{1}\]  
\[DSC(A,B)=\frac{2|A\cap B|}{|A|+|B|}. \tag{2}\]  
[PERSON] et al. (2019) argue that both the Jaccard index and the Dice score are reliable and accurate metrics for evaluating the automatic segmentation of medical images. The Dice score offers a balanced perspective by considering both recall and precision. At the same time, the Jaccard index imposes a stricter penalty for under- or over-segmentation, making it particularly valuable when a high level of segmentation accuracy is essential. More information about these metrics can be found in ([PERSON] et al., 2018).  
Figure 5: Spatial distribution of segmentation metrics using SAM, with emphasis on the central slice.  
```
0: video exists
0: video\(frames>0\) \(half_{1},half_{2}\gets SplitVideo(video)\) \(results_{1}\gets ProcessVideo(half_{1})\) \(results_{2}\gets ProcessVideo(half_{2})\) \(result\gets JointResults(results_{1},results_{2})\) functionSplitVideo(\(video\)) \(frames\gets length(video)\) \(seed\)\(frame\leftarrow\lfloor\frac{frames}{2}\rfloor\)  copy frames 0 to \(seed\)\(frame\) to \(half_{1}\)  reverse frame order in \(half_{1}\)  copy frames \(seed\)\(frame\) to end to \(half_{2}\) endfunctionfunctionProcessVideo(\(video\)) \(prompts\gets GetPrompts(seed\)\(frame)\)  segment \(seed\)\(frame\) with \(prompts\)  propagate segmentation through \(video\)  save results endfunction functionJoinResults(\(results_{1},results_{2}\))  reverse results order in \(results_{1}\)  delete \(seed\)\(frame\) results in \(results_{1}\)  join \(results_{1}\) and \(results_{2}\) endfunction
```  
**Algorithm 1** Video processing algorithm.
## 2 Materials and Methods
### Field Tests  
Field tests were carried out on saline silty-clayey soils with a content of readily soluble salts up to 3% and carbonates up to 27% for the object: \"Retaining wall on Mount Koktobe in Almaty\" (Figure 4). According to the data of engineering-geological surveys carried out at the site with soil sampling to a depth of 20 m, the geological structure of the site's soils is represented by silty clays interlayered with clayey soils. The content of carbonates in loans is up to 27%, and easily and medium-soluble salts up to 3%. The toposoil layer is 0.3 m. The degree of aggressiveness of soils in relation to the impact on reinforced concrete structures varies from average on Portland cements to strong on sulfate-resistant brands of cement. The physical and mechanical properties of saline silty-clayey soils of the base of the test site are shown in Table 1.  
To study the effect of the desalination processes on the bearing capacity of the piles, it was decided to install a friction pile with prolonged wetting, as well as a control pile without wetting. To determine the real behavior of the \"pile-shell-soil\" system, static load tests were carried out with piles in a protective and load-bearing shell for vertical indentation load: in the natural state and during leaching under flooding conditions. Six testing zones were observed during the installation of bored friction piles with a diameter of 400 mm and a length of 4 m. The allocation of the tested piles in each of the sections is presented in Figure 5. For a comparative analysis of the bearing capacity, near each experimental pile in the soil shell treated with silica solution (hereinafter referred to as \"protective shell\"),  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Engineering** & & & & & & **Soil Properties** & \\
**Geological** & **Description of Soils** & **Layer Thickness, m** & & & & \\
**Element** & & & & & & \\ \hline \multirow{2}{*}{\(1\)} & Silty clays (with & & & & \\ soil wetting) & 20 & 10.8 & 21 & 26 & 1.98 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Physical and mechanical properties of saline silty-clayey soils test site.  
Figure 4: Construction site “Retaining wall on Mount Koktobe” in Almaty.  
ordinary bored piles without a protective shell (hereinafter referred to as \"ordinary pile\") were casted.  
Thus, the tests were carried out for:  
Six bored piles with a protective shell, without soil wetting;  
Six ordinary bored piles, without soil wetting;  
Six bored piles with a protective shell, after wetting the soil;  
Six ordinary bored piles, after wetting the soil.  
Wetting of the soil mass around the pile continued for six months by pumping water into special drainage wells, 0.2 m in diameter, 3.5 m long, located at a distance of 1 m from the edge of the experimental pile (Figure 5). At the end of the wetting, significant desalination was achieved near the pile soil massif as a result of suffusion processes and the partial migration of clay particles into the holes of the drainage tubes.
###### Abstract  
Shadow in remote sensing images can obscure important details of land features, making shadow detection crucial for enhancing the accuracy of subsequent analyses and applications. Current shadow detection methods primarily rely on the spectral information of images, which can often result in shadow misdetection due to the phenomenon of spectral confusion of different objects. To mitigate this issue, we propose a method that combines topography and spectra (CTS). Firstly, we introduce a new DEM-based shadow coarse detection method to obtain the DEM rough shadow mask, which uses a relationship between the magnitude of terrain height angle and solar elevation angle to determine shadow properties. Then, we use the MC3 (modified C3 component) index-based shadow fine detection method to obtain an MC3 mean map, which includes image enhancement with a stretching process and multi-scale superpixel segmentation. We then derive the Shadow pixel Proportion Map (SPM) by counting the DEM rough shadow mask in terms of superpixels. The Joint Shadow probability Map (JSM) is obtained by combining the SPM and the MC3 mean map with specific weights. Finally, a multi-level Otsu threshold method is applied to the JSM to generate the shadow mask. We compare the proposed CTS method against several state-of-the-art algorithms through both qualitative assessments and quantitative metrics. The results show that the CTS method demonstrates superior accuracy and consistency in detecting true shadows, achieving an average overall accuracy of 95.81% on mountainous remote sensing images.  
remote sensing images; shadow detection; method that combines topography and spectra (CTS); DEM; multi-scale superpixel segmentation +
Footnote †: journal: Applied sciences
[5] noted, existing studies often focus on single aspects, such as interface design or functional development, lacking a framework that integrates human needs, interaction design, and technical implementation. This fragmented research approach struggles to effectively address the overall challenges of elderly technology use. Secondly, intergenerational interaction design principles lack systematic empirical support. While [PERSON] et al. [15] and [PERSON] and [PERSON] [16] affirm the value of intergenerational interaction, there remains a lack of large-scale, long-term empirical studies validating specific mechanisms for the design and implementation of intergenerational interaction. Thirdly, effective long-term benefit evaluation mechanisms are lacking. Most existing research focuses on evaluating the short-term usage effects, as seen in [PERSON] and [PERSON]'s [17] study, primarily concerning initial acceptance. However, systematic evaluation research on elderly technology products' sustained usage, long-term social impacts, and health promotion effects remains largely absent. Based on these research gaps, this study aimed to develop and validate a seamless technology framework for elderly-centered interactive systems. The research objectives were threefold: (1) to establish an integrated design framework that transforms human needs into concrete design elements, (2) to develop innovative intergenerational interaction models, and (3) to validate the framework's effectiveness through systematic field studies. This study introduces a new design--the \"Pillow Fight\" intergenerational interactive system [18; 19; 20]--which received global recognition at the 2019 Stanford Center on Longevity Design Challenge. The system's development can be traced back to interactive memory product design research in digital fabrication [21], demonstrating continuous exploration in integrating technology with human needs. This study's innovative contribution is manifested in three aspects. Firstly, in terms of design thinking, we propose the concept of \"seamless technology\", extending [PERSON]'s [22] vision of ubiquitous computing. This concept emphasizes (a) hiding technological components within daily objects to reduce users' resistance, (b) maintaining the original user experience and emotional connection, and (c) achieving seamless integration between technological functions and natural behaviors. Secondly, in terms of technical application, we have developed a soft sensing technology based on the Nielsen Norman Group's [23] design guidelines, combined with [PERSON] et al. 's [24] sensing technology application principles. Thirdly, in terms of practical validation, we present a two-phase field study, which was conducted across 34 sites with 1997 participants, employing both quantitative tools (SUS usability scale) and qualitative methods (observations and interviews), to evaluate the system's effectiveness.