esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### SERS Applications
#### 3.2.2 Detection of Naphthalene through SERS  
Polycyclic aromatic hydrocarbons (PAHs), which are extensively studied due to their environmental significance, are generally thought to have a low affinity for Au and Ag surfaces because they are uncharged, lacking electrostatic attraction, and do not contain functional groups like amines or thiols, which usually facilitate adsorption to metal surfaces. As a typical example, naphthalene signals were not detected when using aggregated Ag colloids as enhancing materials, even at a high concentration of \(10^{-3}\) M, with SERS spectra only showing background peaks [45]. However, the situation is dramatically changed if silver is replaced by gold, being reported that naphthalene can be detected on citrate-reduced Au colloids at concentrations as low as \(10^{-8}\) M. It was suggested that in this case, \(\pi\)-metal interactions between the analyte and the Au surface could be a crucial factor governing adsorption. Furthermore, it was suggested that since the citrate surface capping agent has a much lower affinity toward Au than toward Ag, it can be displaced much more easily from the surface of aggregated AuNPs compared with AgNPs [45]. Indeed, using citrate-reduced Au colloids, we obtained strong SERS signals for naphthalene, as shown in Figure 10a, together with the Raman spectrum of the molecule, for comparison. The major peaks in the SERS spectrum of naphthalene were recorded at 509 cm\({}^{-1}\), 754 cm\({}^{-1}\), 1016 cm\({}^{-1}\), 1376 cm\({}^{-1}\), and 1558 cm\({}^{-1}\).  
Due to the hydrophobic nature of the CD cavity, we considered that CD-capped NPs could avoid these difficulties. In Figure 10b, we present the SERS spectra of naphthalene to the micromolar range, obtained using AgNPs, reduced with \(\beta\)-CDs in the ultrasound field. Some vibration bands are slightly shifted compared with AuNPs, these differences could be related to the different nature of the two metals. On the other hand, the relative intensity of the peak landscape is different between the two metals. These differences might be related also to the orientation of the molecules toward the metallic surface. Assuming the interaction of Au with the \(\pi\) electrons, the molecule should lie flat on the Au surface. In  
Figure 9: SERS spectra of MB: (**a**) using a citrate-reduced gold colloid (obtained according to ref. [44]) without and with 0.1 M NaOH. The new vibrational bands that appeared in basic pH conditions are highlighted with dashed rectangles; (**b**) using cyclodextrin-reduced gold colloids reduced at room temperature; no new vibrational bands can be detected after the addition of NaOH in the case of cyclodextrin-reduced colloids.  
the case of CD-capped AgNPs, naphthalene approaches the metallic surface through the CD cavity having a perpendicular conformation. Nevertheless, one can notice that in the case of CD-capped AgNPs, other vibration peaks can also be detected.
## 1 Introduction  
The flavor, aroma, and appearance are the basic sensory components of green tea [1]. Green tea is consumed by many people living in Asia for its flavor, cultural connotations, and health benefits. Recently, western countries are embracing green tea as a beverage because of the possible health benefits [2]. In addition to the health effects of green tea, researchers have studied the flavors of green tea using descriptive sensory methods [3; 4; 5; 6]. Recently, a green tea lexicon was developed evaluating over 100 green tea samples [7]. The aromatic volatile composition of green tea also has been studied extensively by researchers [8; 9; 10; 11; 12; 13; 14; 15].  
While the results of this previous research have been valuable, the researchers evaluated only the first brews of green tea. It is generally believed in Asia that a high quality green tea can be brewed multiple times. A Chinese poet sang about tea drinking and mentioned the first through the seventh brew [1]. Many premium and high end products suggest brewing their tea multiple times (up to five times) in the infusion directions. [PERSON] [16] suggested that green tea can be brewed up to three times. However, some of the literature on the multiple brewing of green tea is contradictory. Several researchers recommended using fresh leaves or a new tea bag when wanting more tea instead of using already brewed tea leaves or a tea bag and stated that used leaves do not provide much more than a little bitterness [17]. This may be true for green tea bags because such products are processed specifically to increase the surface area to extract the flavor and nutrients quickly. But no such study has been made on the similar properties of green tea that is brewed from tea leaves.  
A limited number of researchers have reported on teas that have been brewed more than once [18; 19]. The concentrations of caffeine, theobromine, and theophylline were measured in tea samples brewed three times [18]. The percentage of caffeine released in each brew of tea decreased as they were brewed repeatedly. However, the flavor and aroma changes of green tea as it is brewed repetitively were not discussed in the research literature. Recent research showed that brewing methods impact green tea flavor, but those authors did not test multiple brewing [20].  
Investigating the aroma and flavor characteristics of green teas liquors that have been brewed repetitively can help determine how many times green teas can be brewed for consumption. No literature was found indicating how the aromatic volatile compounds and the flavor characteristics change when green tea is brewed multiple times. Thus, the objectives of this study were to: (1) determine how the flavor changes as green tea is brewed multiple times, (2) determine how the aromatic volatile compounds change as green tea is brewed multiple times, (3) relate the descriptive flavor analysis of green tea flavors to the aromatic volatile compounds data at each brew, and (4) suggest the number of times that green tea leaves can be brewed and still maintain their major flavor notes.
# A Game Theory-Based Model for the Dissemination of Privacy Information in Online Social Networks
## 2 Related Work
[PERSON] and [PERSON] extended the SIR (susceptible infective removal) model to analyze the influence of user's privacy awareness on the dissemination of privacy information [22] and how neighbor nodes would affect the dissemination of privacy information in OSNs [23]. However, most of the previous research on OSNs has been focused on the spread of information and rumors in OSNs, and the research on private messages has not adequately considered user's micro-influence. Meanwhile, the game theory model incorporated in the social networks is a pure strategy game scenario of a single mode. At present, there is hardly any research on mixed games between the sender and the receiver. Based on the influencing factors of the relationships between users, it is possible to determine the probability that a user will spread privacy information after receiving it. It is also important to determine to which receivers to send the information, making the game suitable for the strategic choice of both users in a specific scenario. The model should microscopically express the user's psychology and can thus be used to determine to which neighboring users the privacy information should be sent. Consequently, this paper applies the game theory to develop a model to facilitate the study of the dissemination of privacy information in OSNs based on the influencing factors of relationships between users and analyzes the main factors that would affect the dissemination of privacy information in OSNs from different perspectives.
# Experimental and Numerical Research on End-Wall Flow Mechanism of High-Loading Tandem Stators
## 5 Corner Stall of Tandem Stators  
The stall occurred in the tandem rotor for the tandem blade stage measured by the above model, and the stall flow coefficient was about 0.43. There was still no corner stall in the tandem stator at the flow coefficient. In order to study the flow characteristics associated with corner stall phenomena in tandem stators, the tandem rotor was replaced by an optimized rotor in this section, while the tandem stator remained unchanged. The  
Figure 22: Schematic diagram of blade surface pressure rise distribution for tandem and conventional stators.  
small flow coefficient of the rotor was 0.39, and the tandem stator stalled when the flow coefficient was 0.41.  
In Figure 23, the variation of the total pressure loss coefficient for the FB and RB was depicted with respect to the flow coefficient. The total pressure loss coefficient of the RB was calculated based on the dynamic pressure head of the RB inlet. When the corner stall occurred in the tandem stator, the total pressure loss coefficient in the FB root region exceeded 0.20, and the loss in the RB root and mid-span regions also increased sharply. Figure 24 illustrates the limit streamline at the corner stall condition, providing a clear visualization of the flow behavior during this phenomenon. For comparative purposes, the limit streamline of the single FB corner stall was also depicted in the figure. It became evident that the presence of the RB did not affect the form of the corner stall. With the increase in the incidence and load of the FB, corner stall occurred in the FB. However, as described in Section 4.1, the corner stall of the tandem stator was developed from one corner stall zone, which caused weaker blockage than that of the single FB.  
The low-energy fluid resulting from the corner stall of the FB accumulated in the root region, forming a large blockage area. When the stalled flow cluster in the corner region entered the RB channel, the blocking region migrated to the mid-span region under the influence of secondary flow dynamics. In addition, the reverse pressure gradient of the  
Figure 23: Variation of the total pressure loss coefficient for FB and RB of the tandem stator with the flow coefficient.  
Figure 24: Limit streamlines of suction surface for single FB and tandem blade at corner stall condition.  
rear blade further expanded the blocking area of the low-energy fluid. The velocity field contours at the exit of the tandem FB and RB were shown in Figure 25, revealing that the FB corner stall fluid indeed caused significant blockage within the RB channel. This blockage reduced the RB load and inhibited the development of the corner separation, so the RB corner region was relatively weak. Distinctively, unlike the conventional blade corner stall, the FB corner stall in the tandem stators caused more fluid to be involved in the stalled cluster influenced by the RB, resulting in greater loss. Therefore, in the design of tandem blades, more attention is needed to explain how to delay the occurrence of corner stalls.
# Time-Division Color Holographic Projection in Large Size Using a Digital Micromirror Device +
## 2 Methods  
In a holographic projection, a random phase is added to the original image to diffuse the object light widely. Then, the CGH is generated using propagation calculation. Given the complex amplitude of the original image \(u_{o}(x_{i},y_{i})\), the random phase \(u_{i}(x_{i},y_{i})\), the complex amplitude of the CGH \(u_{h}(x_{h},y_{h})\), the propagation distance \(z\), and the light propagation operator \(\text{Prop}_{z}[\cdot]\), the CGH calculation is expressed by  
\[u_{h}(x_{h},y_{h})=\text{Prop}_{z}[u_{o}(x_{i},y_{i})u_{i}(x_{i},y_{i})]. \tag{1}\]  
As a DMD is used in this study, only the real part of Equation (1) is extracted and binarized to generate binary CGH. In the binarization, we use one if the real part is positive, and zero otherwise.  
Figure 1 shows the simulated results of the reconstructed image when the size of the original image is twice larger than the CGH. Table 1 shows the simulation condition. We used only the red wavelength in this simulation. Figure 1a shows the original image. Without the random phase, only the part with the same size as the CGH is reconstructed, as shown in Figure 1b. However, by adding a random phase, the entire original image is reconstructed as shown in Figure 1c. This causes speckle noise in the reconstructed image. There are methods to reduce these speckle noises, such as the multi-random phase and pixel separation methods.  
In the following subsections, we explain the multi-random phase and pixel separation methods. Further, the proposed methods, a combination of multi-random and pixel separation methods, and the correction method for color unevenness are explained.  
Figure 1: Original and simulated reconstructed images: (**a**) original image, (**b**) reconstructed image without random phase, (**c**) reconstructed image with random phase.
## 5 Results
### Risk Assessment Under Different Rainfall Conditions
The evaluation results show that there are a total of 349 residential slope units in the town, of which 37 are high-risk, 174 are medium-risk, and 138 are low-risk. Based on the geological hazard risk assessment, a geological hazard prevention zoning plan was carried out for Huangshi Town, dividing the entire area into 4 key prevention zones with a total area of 18.55 km\({}^{2}\), 6 secondary key prevention zones with a total area of 25.78 km\({}^{2}\), and 3 general prevention zones with a total area of 65.48 km\({}^{2}\). Additionally, based on different rainfall conditions, prevention zoning work was conducted for the key investigation areas. In the key investigation areas, 33 key prevention zones were delineated, covering an area of 0.884 km\({}^{2}\), 176 secondary key prevention slope units were identified, covering an area of 4.917 km\({}^{2}\), and 146 general prevention slope units were defined. The analysis results under different rainfall scenarios indicate a clear trend of risk concentration with increasing rainfall intensity. Under the 24-h 100 mm rainfall condition, the high-risk zone includes 22 slope units, covering an area of 0.556 km\({}^{2}\), which accounts for 34.86% of the total area of the key investigation area; the medium- and low-risk zones together account for 65.14% of the area. In contrast, under the 24-h 250 mm and 72-h 240 mm rainfall conditions, the extremely high and high-risk zones combined include 61 slope units, covering a total area of 1.537 km\({}^{2}\), representing over 96% of the total area. This demonstrates that as rainfall intensity increases, slope units originally classified as moderate-risk are extensively transformed into high-risk zones. At the same time, the number of geological hazard risk points increases significantly under high rainfall scenarios, reflecting a heightened level of hazard activity. Spatially, high-risk zones are significantly concentrated in the southeastern and southwestern parts of Huangshi Town, indicating a localized sensitivity to extreme rainfall. This trend highlights the importance of dynamic zoning and emergency planning tailored to different rainfall scenarios in geological hazard prevention and mitigation efforts.
###### Abstract
Techniques such as time-series analysis, sliding windows, and feature engineering can be applied to transform raw sensor data into a format suitable for analysis. Once extracted, these features can be utilized in various deep learning models, including long short-term memory (LSTM) networks [29; 30] and 1D convolutional neural networks (1-D CNNs) [31; 32], which are inherently designed to handle sequential data. The shift from singular value features to sequential features represents a significant advancement in the field of tool wear classification. By fully exploiting the temporal information contained within sensor data, sequential features provide a more accurate and detailed understanding of tool wear dynamics, leading to better predictive models and more effective maintenance strategies. As technology and data analysis methods continue to evolve, the potential for further improvements in this area remains vast, promising even greater gains in manufacturing efficiency and tool life optimization. A recent study by [PERSON] et al. (2024) underscores the effectiveness of data-driven approaches in predicting the remaining useful life (RUL) of tools. They applied a hybrid model combining bidirectional long short-term memory (BLSTM) and convolutional neural networks (CNNs) for metal-forming processes. The CNN-based WearNet was retrained to classify the wear states of workpiece surfaces, and these classifications were then used as inputs for a BLSTM-based regression model to estimate RUL. Their approach achieved high accuracy and low root mean square error (RMSE), highlighting the robustness of data-driven techniques in tool wear prediction [33]. The primary objective of this article is to present a novel, sensor-based diagnostic system designed for the real-time monitoring and classification of tool wear in chipboard milling processes based on sequential features. By leveraging advanced deep learning techniques, specifically 1-D convolutional neural networks (CNNs) and long short-term memory (LSTM) networks, this study aims to enhance the accuracy and efficiency of tool condition monitoring. By providing an in-depth analysis of sequential features derived from a comprehensive set of sensors, this research seeks to not only improve the predictive capabilities of tool wear classification but also to significantly reduce downtime and operational costs in manufacturing settings. Furthermore, this work contributes to the body of knowledge by offering insights into the practical implementation of deep learning models in industrial applications, thereby paving the way for more intelligent and autonomous manufacturing processes.
## 5 Results and Discussion
### Mold Model Test Results
#### 5.2.2 Effects of Moisture Content and Compaction (Case 1 vs. Case 2)  
It is noticeable that Case 2 (OMC clay) exhibited a very high bearing capacity compared to all other cases. The OMC clay was very stiff, thus tensions occur at the surface around the piston during penetration. The experimental results showed a local shear failure on the OMC clay sample as manifested by a soil bulging (soil heave) at the surface around the piston and the smooth load-settlement curve in Figure 12. Considering only Case 1 and Case 2 have full clayey soil (Figure 12), Case 2 exhibited an extremely large bearing capacity, which shows that well-compacted clay at OMC is high strength clay capable of sustaining loads up to 6,500 kPa at 0.25\(B\). This strength is very desirable for actual construction. However, it is very difficult to implement on the construction site and would entail too much effort and a long period of time. Thus, clayey soil with a high water content is more likely to be used. In this study, the clay with high water content (Case 1) exhibited the least load of 50 kPa. The NMC clay (Case 1) is soft and has negligible tensions at the surface around the piston during the penetration. The experimental results showed a punching shear failure during the penetration as shown by the straight load-settlement curve in Figure 12. From this, it can be inferred that clay with a higher moisture content has a lower bearing capacity.  
Figure 12: The comparison of the bearing capacity of NMC clay (Case 1) and OMC clay (Case 2).  
Therefore, water content is a crucial factor, which significantly influences the strength of the soil. It is said that water serves as a lubricant, reducing friction between soil particles, making compaction easier, and creating a good sealer for engineered barriers. However, water saturates the soil, which increases its plasticity and, at the same time, reduces soil unit weight, thus reducing bearing capacity [4; 22; 23; 24].
###### Abstract  
Xylo-oligosaccharides are sugar oligomers with 2-7 xylose units considered non-digesible fibers that can be produced from biodegradable and low-cost biomass like wheat straw. An integrated approach consisting of hydrothermal pretreatment, alkaline treatment, enzymatic treatment and the combinations thereof was applied to overcome the recalcitrance structure of the wheat straw and allow selective fractioning into fermentable sugars and xylo-oligosaccharides. The hydrolyses and processed solids were chemically characterized by High-performance liquid chromatography and Ion chromatography, and the results were expressed as function of the severity factor and statistically interpreted. The concentration of fermentable sugars (glucose, xylose, arabinose) was the highest after the combination of alkaline and enzymatic treatment with xylanase (18 g/L sugars), while xylo-oligosaccharides (xylotriose and xylotetraose) were released in lower amounts (1.33 g/L) after the same treatment. Refining experiments were carried out to obtain a purified fraction by using anion and cation exchange chromatography. The polymer adsorber resin MN-502 showed efficient removal of salts, phenols andfuran derivatives. However, the xylo-oligosaccharides yields were also slightly reduced. Although still requiring further optimization of the treatments to obtain higher purified oligomer yields, the results provide information on the production of xylo-oligosaccharides and fermentable sugars from wheat straw for potential use in food applications.  
a Article  
Chemical and Enzymatic Synthesis of Biobased Xylo-Oligosaccharides and Fermentable Sugars from Wheat Straw for Food Applications  
1 Faculty of Food Science and Technology, Institute of Life Sciences, University of Agricultural Sciences and Veterinary Medicine, 400372 Cluj-Napoca, Romania; [EMAIL_ADDRESS]  
2 Leibniz Institute for Agricultural Engineering & Bioeconomy, Max-Eyth-Allee 100, 14460 Potsdam, Germany; [EMAIL_ADDRESS] (J.V.); [EMAIL_ADDRESS] (M.H.); [EMAIL_ADDRESS] (R.S.)  
3 Department of Exact Sciences, Horticulture Faculty, University of Agricultural Sciences and Veterinary Medicine, Cluj-Napoca, Calea Manistur 3-5, 400372 Cluj-Napoca, Romania; [EMAIL_ADDRESS]  
4 Correspondence: [EMAIL_ADDRESS]; Tel.: +40.747-341-881