esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### Fatty Acids  
Thermal treatments can affect FAs among the lipid compounds of meats [1], and in particular, polyunsaturated FAs (PUFAs) are more highly susceptible to oxidation during heating processes than their saturated analogues, which may change the nutritional value of cooked products [19]. The influence of heat treatments on the composition of FAs is shown in Table 3. In the decreasing order of percentage, the major FAs in beef were found to be cis elaidic (18:1 (n-9)c), palmitic (16:0), stearic (18:0), and linoleic (18:2 (n-6)c) acids. Depending on the cooking conditions, the fat extracted from RSSs contained lower levels of saturated FAs (SFA) than SSS (12.97%). Reverse searing decreased the palmitic acid (16:0) and stearic acid (18:0) content in the fat extracted from beef by 9.64% and 14.07%, respectively. As expected, unsaturated FA (UFA) contents were lower in RSSs than in SSs. However, the levels of UFAs such as arachidonic acid (20:4 (n-6)), dihomo-\(\gamma\)-linolenic acid (20:3 (n-6)), and \(\gamma\)-linolenic acid (18:3 (n-6)) were increased in RSSs (7.26%, 5.30%, and 49.53%). Several mechanisms that occur during cooking, such as lipid oxidation and water loss, can lead to changes in PUFAs [19]. All of the levels of fatty acids (SFA, MUFA, PUFA, and TFA), except for 18:3 (n-6), 20:4 (n-6), 20:3 (n-6), 20:5 (EPA), and 22:5 (DPA), were increased in SSs rather than in RSSs, possibly due to the fact that they were cooked at a high temperature. However, within the 27 FAs analyzed, no significant differences were observed, except for in arachidonic (20:0), behenic (22:0), and dihomo-\(\gamma\)-linolenic (20:3 (n-6)) acids.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Fatty Acid** & **Seared Steak** & **Reverse-Seared Steak** & **t** \\ \hline
10:0 & 6.19 \(\pm\) 0.55 & 5.54 \(\pm\) 0.36 & 1.69 \\
12:0 & 7.99 \(\pm\) 0.67 & 7.05 \(\pm\) 0.35 & 2.15 \\
14:0 & 334.18 \(\pm\) 33.88 & 300.01 \(\pm\) 18.52 & 1.53 \\
15:0 & 66.76 \(\pm\) 6.94 & 58.57 \(\pm\) 3.86 & 1.79 \\
16:0 & 2800.68 \(\pm\) 281.69 & 2530.79 \(\pm\) 160.98 & 1.44 \\
17:0 & 171.61 \(\pm\) 19.02 & 156.80 \(\pm\) 10.39 & 1.18 \\
18:0 & 2238.6 \(\pm\) 249.22 & 1923.54 \(\pm\) 131.62 & 1.94 \\
20:0 & 17.05 \(\pm\) 1.50  & 14.05 \(\pm\) 0.92  & 2.95 * \\
22:0 & 10.07 \(\pm\) 0.72  & 8.05 \(\pm\) 0.66  & 3.59 * \\  
PA) & 15.94 \(\pm\) 0.75 & 16.39 \(\pm\) 0.73 & \(-\)0.74 \\ SFA & 5663.39 \(\pm\) 591.03 & 5012.31 \(\pm\) 328.10 & 1.67 \\ MUFA & 3715.74 \(\pm\) 382.01 & 3359.34 \(\pm\) 203.76 & 1.43 \\ PUFA & 1227.34 \(\pm\) 71.54 & 1156.48 \(\pm\) 63.62 & 1.28 \\ TFA & 797.39 \(\pm\) 86.72 & 684.88 \(\pm\) 42.01 & 2.02 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Fatty acids (mg/100 g) of seared and reverse-seared steaks.
# Long-Term Effects of External Sulfate Attack on Low-Carbon Cementitious Materials at Early Age
## 4 Conclusions  
In this investigation, OPC pastes, as well as binary, ternary, and quaternary blended cement pastes, underwent long-term exposure to 15 g/L of sodium sulfate at an early age. Following comprehensive characterizations and continuous monitoring of the attacked samples, the study resulted in the following conclusions:  
* CEM I exhibits the lowest resistance to ESA when compared to blended mixes. It shows the highest mass gain, expansion, formation of ettringite and gypsum, sulfate consumption from the solution, and microstructure alteration. Additionally, during the course of this experiment, it deteriorated only after 90 weeks, whereas the blended cements maintained their structural integrity even after 120 weeks;
* blended specimens demonstrated good durability, retaining structural integrity after 120 weeks of sulfate exposure from an early age;
* incorporating a low quantity (10%) of metkaolin along with blast furnace slag emerged as the most effective substitute for clinker, outperforming other combinations based on the observed behavior of various blended mixes in sulfate exposure;  
Figure 9: Illustrative overview of research results.  
* non-invasive Raman spectroscopy emerged as a reliable method for monitoring the ESA effect by quantifying the sulfate ions left in the attacking solutions.  
Further investigations at the mortar and/or concrete scale would provide additional insights into the physical transport properties, in addition to the chemical aspects of ESA. This is particularly relevant as the current study focuses on cement paste materials that are highly porous. Moreover, further investigations are needed to explore the effects of adding metakaolin to slag as a substitute for clinker, aiming to develop highly resistant materials against ESA.  
Validation, conceptualization, methodology, writing--review, editing, and supervision O.O.M., M.M. and M.Q.; conceptualization, methodology, writing--original draft preparation, investigation, formal analysis, and editing, F.E.L.; validation, investigation, writing--review, and formal analysis, B.A. and M.H. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
Data are contained within the article.  
The authors declare no conflicts of interest.
# Network Allocation Vector (NAV) Optimization for Underwater Handshaking-Based Protocols
## 3 Optimization of NAV
### Trying to Communicate with Another Neighbor  
The propagation delays acquired during overhearing are the ones related to the source or destination only, and not the neighbors. Thus, in case a neighbor tries to communicate with another neighbor, the NAV is determined by the larger NAV out of those obtained in Sections 3.1 and 3.2.
# A Durability Prediction Method for Historical Square Rebar Reinforced Concrete Buildings
## 5 Applications of the Proposed Method  
### Two Typical Historical Square Rebar Reinforced Concrete Buildings  
Two typical historical buildings were presented as the application cases in this section. Both of them were constructed between 1930 and 1940 and used square rebars. They are the target objects of this method. Besides, they both are of typical pseudo-classic style. The form of the Songfengge Building is a double-eave hip roof, and the form of the Main Hall of the Tomb of Yu is a double-eave saddle roof. Hip roof and saddle roof were two typical roof types for traditional Chinese timber buildings, and these two styles were very popular to be used on RC buildings for decades in China history. The structure arrangements of these types of RC buildings were not similar to the current common frame structure, especially for the roofs. Both of the structural designs and concrete techniques of these two buildings were representative of that historical period. Besides, many similar types of RC buildings also existed in other Asian countries. Component importance analysis for these two buildings can also serve as a reference for buildings of comparable characteristics found in Japan, Korea, and some Southeast Asian countries. The dimensions of the ground plan of the Songfengge Building are 38.5 m \(\times\) 16.6 m, while the height of the building is 13.35 m. The data of the Main Hall of the Tomb of Yu are 24.0 m \(\times\) 21.5 m and 17.67 m. The buildings are shown in Figures 8 and 9.  
Figure 8: The picture of the Songfengge Building.
## 3 Results
### Cytotoxic Activity  
The cytotoxicity of the isolated compounds was tested on three different human cancer cell lines in a wide range of concentrations (0.1-1000 \(\upmu\)M) and compared with the cytotoxicity of ellagic acid as the standard parent compound. The three analytes decreased viability of all model cell lines in a dose-dependent manner. The standard was found to be moderately cytotoxic towards all lines investigated with the lowest IC\({}_{50}\) value at 62.3 \(\pm\) 9.7 \(\upmu\)M for melanoma cells WM 115. The cytotoxicity  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Analyte**} & \multicolumn{3}{c}{_G.__Rivale_} & \multicolumn{2}{c}{_G.__Urbanum_} \\ \cline{2-7}  & **Rhizome** & **Aerial Parts** & **Rhizome** & **Aerial Parts** \\ \hline
**1** & 2.94 \(\pm\) 0.03 & \textless{}LOQ & \textless{}LOQ & nd \\
**2** & 5.45 \(\pm\) 0.03 & \textless{}LOQ & \textless{}LOQ & nd \\ \hline \hline \end{tabular} Data presented as means \(\pm\) SD (\(n\) = 3); LOQ—limit of quantification; nd—not detected.  
\end{table}
Table 4: Content of compound **1** and **2** (mg/g dw) in investigated plant materials.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Analyte**} & \multicolumn{3}{c}{**Precision (RSD\%)a**} & \multicolumn{3}{c}{**Accuracyb**} \\ \cline{2-7}  & **Level** & **Intra-Day Variability** & **Inter-Day Variability** & **Spiked Level** & **Recovery** \\  & **[ug/mL]** & \(t_{R}\) & **Peak Area** & \(t_{R}\) & **Peak Area** & **[ug/mL]** & **(RSD [\%])** \\ \hline \multirow{4}{*}{**1**} & 149.30 & 0.61 & 0.76 & 1.13 & 1.35 & 5 & 97.76 (2.39) \\  & 59.41 & 0.53 & 0.73 & 1.34 & 1.48 & 25 & 98.64 (1.45) \\  & 14.93 & 0.64 & 1.25 & 1.32 & 2.14 & 50 & 98.34 (1.75) \\  & 157.20 & 0.65 & 0.65 & 1.25 & 1.69 & 5 & 96.55 (1.97) \\
**2** & 108.63 & 0.49 & 0.78 & 1.46 & 1.53 & 25 & 98.72 (1.60) \\  & 15.72 & 0.61 & 1.34 & 1.39 & 2.53 & 50 & 97.24 (1.43) \\ \hline \hline \end{tabular}  
* Values for the standard solution tested at 100\(\%\) and 10\(\%\) of the stock concentration and for the rhizome of _G.__rivale_ (nominal concentration of 59.41 \(\upmu\)g/mL for **1**, and 108.63 \(\upmu\)g/mL for **2**); b Spiked levels refer to the analyte amount added to the sample of the rhizome of _G.__rivale_ (nominal concentration of 59.41 \(\upmu\)g/mL for **1**, and 108.63 \(\upmu\)g/mL for **2**).  
\end{table}
Table 3: Validation parameters of precision and accuracy.  
of compounds **1** and **2** was significantly lower, with the IC\({}_{50}\) values in the range of 306.4-473.8 uM, and the highest activity was found also for the WM 115 line (Table 5). Despite this similarity, the sensitivity profile of the tested cancer cells on the sulphate derivatives was noticeably different as compared to ellagic acid. In the case of the standard, the cytotoxicity decreased significantly from the WM 115 line, through lymphoblastic leukaemia NALM-6 cell line (IC\({}_{50}\) = 124.9 \(\pm\) 50.5 uM), to promylocytic cells HL-60 (IC\({}_{50}\) = 300.6 \(\pm\) 12.3 uM), whereas the anti-cancer activity of compounds **1** and **2** was similarly low for all tested cells.
# A Survey on Pump and Dump Detection in the Cryptocurrency Market Using Machine Learning
## 5 Discussion and Research Directions
### Research Directions  
The following research directions can be explored to advance P&D detection in cryptocurrency:  
* Detecting the end of the pump phase: It would be beneficial to develop methods for detecting the end of the pump phase with a high degree of accuracy. The unavailability of this information on social media platforms makes accurate detection difficult. To address this future work, researchers can explore advanced ML algorithms that can analyze historical price patterns and social media sentiments to detect abrupt changes in market behavior, indicating the end of the pump phase;
* Fake news and coordinated advice impact: One possible future direction is to consider the factor of fake news and coordinated investment advice. Since many individual investors rely on investment websites, news channels, and investment advice channels, if enough of them buy a specific coin because of fake news or coordinated advice, it will cause the price to change quickly. To tackle this research direction, sentiment analysis can be employed to identify false information and advice. Additionally, developing a reliable system that verifies the authenticity and credibility of news sources could help mitigate the influence of false information on the market;
* Feature combinations for enhanced model training: Various combinations of input features in the data can be used to train the models, for example, by using indicators as input features for market data, such as RSI, which considers whether an asset is overbought or oversold; MACD, which tries to forecast market trends by comparing short and long-term tendencies; SMA and EMA, which represent simple and exponential moving averages of the market data, respectively. These indicators are used to improve the efficiency of the prediction process and develop the quality of the data, which could be beneficial to the performance of the trained models. Incorporating and examining the outcomes of different models using such combinations of input data could be the subject of future studies aiming to establish general guidelines for future research in this field. Researchers can address this future work by conducting an extensive feature engineering analysis to identify the most relevant indicators and combine them to enhance model training;
* Transfer learning: There are studies [20; 21; 22] that train ML models for market manipulation detection; future studies can use transfer learning to fine-tune these pre-trained models for detecting specific market manipulations like P&D.
# EAOA: Energy-Aware Grid-Based 3D-Obstacle Avoidance in Coverage Path Planning for UAVs
## 2 Related Works
For each path planned, they rely on the cost function to move from one cell to another unvisited neighboring cell. This produces changes in direction and consequently increases the number of turns. In our work, the UAV movement is parallel to the longest side of the grid (from the top view), which reduces the number of turns and the path length. As in [14], we take into consideration the percentage of the area in the cell to be covered, in order to increase the coverage rate. The work in [24] drops the whole cells that contain obstacles. Hence, if the obstacle occupies a small portion of a cell, the whole cell won't be covered, thus the area coverage rate decreases. Additionally, avoiding the whole cell increases the path length and the turning angles. Consequently, it increases the completion time and energy consumption. Authors in [14] propose an energy aware coverage path planning method. They use 2D grid partitioning to scan an area of interest. Scenarios with one drone and different regular and irregular area shapes were considered. The algorithm determines the turning positions as well as the start point and the scan direction of the area. The path is planned in an offline mode and showed efficient results in terms of energy saving, area coverage, and completion time. However, the areas of interest were without obstacles and nonflying zones. In this work, we develop an extension for this algorithm. The objective is to cover an area of interest in the presence of obstacles. Our proposed algorithm re-plans the original path by scanning the facing area which contains obstacles. We try to avoid obstacles with the shorter path possible while keeping the completion time and energy consumption to a minimum.
# A Lightweight Slice-Based Quality of Service Manager for IoT
## 5 Validation, Evaluation and Obtained Results
### Traffic Policing  
Policing can be implemented on interface _eth_I of the VM-Application, mainly because it represents the interface that deals with traffic flows entering the system from the outside. On the other hand, each created slice port represents the way out of the whole OvS system, which enables its usage for outgoing traffic shaping. Because of that, traffic policing is inevitably applied to all the gateway created slices, affecting them in a single-level fashion. Contrarily, shaping is applied to each slice independently, where rules are set and are inherent to one single virtualised network segment. Hence, it is important to mention that besides the default flow entries applied by the Ryu controller, no flows entries are applied by our proposed slice-based QoS manager. The evaluation is intended to illustrate that it affects all slices when the solution is taking advantage of it. In light of this, the clients' number was gradually increased in two simultaneously running slices whose combined bit rate was limited by 50 Mbit/s. All clients were attempting to poke the server with 1 Mbit/s, using TCP. Additionally, the defined policing burst value was set as 10 Mbit/s. The slices' aggregated bandwidth is observable in Figure 17.  
Figure 16: Comparison of two slices’ total bandwidth.  
As can be seen, both slices are being affected when their bit rates reach 25 Mbit/s. This can be explained by their aggregated bandwidth of 50 Mbit/s at a time, which is the rate limit that the traffic policing implementation imposed. The OvS documentation states that defining a burst size to be a sizeable fraction of the policing maximum limit rate enables the flow to more easily achieve the full rate. However, if the defined burst size is set to be a significant value, the client can notice an average rate slightly higher than the specified maximum one [20]. Hence, because the test defined burst value is around 20% of the maximum rate limit, the slices' aggregated bandwidth is moderately overcoming it.
## 4 Results  
### Multicollinearity Results  
The calculated VIF and TOL values indicate the existence of multicollinearity problems in specific factors (Table S1). We reached this conclusion by noticing that some tolerance values were less than 0.1, and some VIF values were higher than 10. To address this, we followed a step-by-step elimination process. Starting with the factor linked to the highest VIF value, we removed factors until we reached a point where no factors were causing multicollinearity issues. After this elimination process, we kept 23 factors, which can be seen in Table S2. The highest VIF was 7.29, and the lowest TOL was 0.14. Importantly, we found that these kept factors were suitable for use in classification processes because none of them had issues with multicollinearity.  
To reinforce the findings of the multicollinearity assessment, the Pearson's correlation coefficients among each factor were computed for the dataset. As illustrated in the Figure S1, the factor pair with the highest correlation value is DTI-DCH, registering at 0.73. Across the matrix, it is evident that the majority of factor pairs exhibit no substantial correlation, with partially correlated pairs falling below the selected threshold of 0.8.  
To sum up, two factor selection methods were employed: the correlation coefficient and the multicollinearity assessment. The latter offers a comprehensive analysis of how factors interact, complementing the relationship insights provided by the correlation coefficient. Trimming a dataset from a larger set of factors to a more focused subset, such as from 34 down to 23, is a frequent practice used to better tailor the factors to suit the ML-based classification framework. This process ensures that the resulting data suit the study region, enhancing their relevance and usability. Eliminated factors underwent careful scrutiny, ensuring key factors, such as PTF, mentioned in the literature, were retained for their importance in model performance and analysis.
## 3 Results and Discussion
### Application of the PolyHIPE Scaffolds in Cytotoxicity Evaluation of Cigarette Smoke  
Due to the high porosity, large void and connected window size, and a great promotion of cell proliferation, the polyHIPE materials prepared with a W/O ratio of 90/10 and an emulsifier amount of E/M 50% was used to construct a 3D cell cytotoxicity evaluation system, in which the cigarette smoke cytotoxicity was evaluated. For comparison, the cytotoxicity evaluations of cigarette smoke were also performed with routine 2D cell culture directly on the tissue culture plate (2D-TCP).  
Figure 9a shows the cell viability as determined by the CKK-8 assay under the smoke TPM exposure with an increased exposure dose. Using the polyHIPE scaffold-based 3D cell cytotoxicity evaluation system, the cell viability of A549 decreased after smoke TPM treatment of as low as 40 ug/mL TPM exposure. Cell viability decreased to 71.4%, 57.1% and 41.5% after 24 h exposure to 120, 200, 280 ug/mL TPM, respectively, showing a dose-dependent cytotoxicity of smoke TPM exposure. However, much lower cell viabilities were observed when using the traditional 2-D cell cytotoxicity evaluation system. For example, cell viability in the 2D platform decreased to 46.8%, 34.3% and 31.1% after 24 h exposure to 120, 200, 280 ug/mL TPM, which is much lower than that in the polyHIPE-based 3D platform, indicating that the cytotoxicity of smoke TPM against A549 is lower in the 3D cell platform than the traditional 2D system. Lactate dehydrogenase (LDH) release from cells under the smoke TPM exposure was also analyzed and the results were shown in Figure 9b. The LDH released 3.8-30.0% under the expose of smoke TPM with a dose of 40-280 ug/mL in the 3D cell cytotoxicity evaluation platform with polyHIPE scaffolds. However, a larger LDH leakage of 4.0-39.2% was observed in the 2D platform with the same exposure dose of smoke TPM. These results also indicated that the smoke cytotoxicity against A549 is lower in 3D cell platform than that of the 2D system. These results are consistent with the reported cytotoxicity evaluation results of cigarette smoke based on a self-assembling peptide nanofiber 3D cell culture system [40; 41]. The lower cytotoxicity of smoke TPM in the 3D cell system is probably due to that cells could form a 3D gradient similar to in vivo in the 3D platform, which would not only affect the transfer of nutrients and wastes, but also the permeability of TPM, benefiting a higher cell viability.  
Considering the controlled pore structure and the enhanced simulation of complex tissue architectures, the polystyrene-based polyHIPE scaffolds would be a potential candidate for 3D cell culture and application in the cytotoxicity evaluation of cigarette smoke.