esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Experiments
### Performance Measurements  
In order to evaluate the performance of NeuroTIS+, we employ the standard performance evaluation criteria in terms of sensitivity (SN), specificity (SP), accuracy (ACC), precision (PRE), F1-score, area under the receiver operating characteristic (auROC), area under the precision recall curve (auPRC), and MCC. These metrics can be calculated as follows:  
\[SN=\frac{TP}{TP+FN}\] \[SP=\frac{TN}{FP+TN}\] \[PRE=\frac{TP}{TP+FP}\] \[ACC=\frac{TP+TN}{TP+TN+FP+FN}\] \[F1-score=\frac{2*PRE*SN}{PRE+SN}\] \[MCC=\] \[\frac{TP*TN-FP*FN}{(TP+FN)*(TP+FP)*(TN+FP)*(TN+FN)}\]  
These evaluation metrics are fundamentally derived from four basic elements: true positives (TPs, correctly classified positive instances), false positives (FPs, misclassified negative instances), true negatives (TNs, correctly classified negative instances), and false negatives (FNs, misclassified positive instances). Among them, Matthews correlation coefficient (MCC) serves as a comprehensive performance metric. While receiver operating characteristic (ROC) curves are widely adopted for binary classification assessment, precision-recall curves (PRCs) prove more reliable for imbalanced datasets. Both auROC and auPRC values are derived via trapezoidal rule integration between consecutive thresholds. Implementation details are documented in [37; 38].
# Effects of Bilberry Extract on Hepatic Cholesterol Metabolism in HepGG2 Cells
## 3 Results
### Regulation of Genes for Biliary Cholesterol Efflux by BE  
The genes involved in the canalicular cholesterol efflux were measured in HepG2 cells to examine the effects of BE on biliary cholesterol flux. The transporters present in the canalicular membrane, i.e., NPC1L1 and ABCG5/G8, are involved in biliary cholesterol efflux in hepatocytes. NPC1L1 facilitates cholesterol absorption from bile, while the heterodimer ABCG5/G8 flux cholesterol mediates free cholesterol secretion into bile. There was a significant reduction in NPC1L1 expression in BE-treated HepG2 cells. A significant upregulation of ABCG8 was observed in treatment with 100 \(\upmu\)g/mL of BE. Bile acid synthesis and secretion play essential roles in maintaining cholesterol homeostasis. There was a significant and dose-dependent increase in mRNA expression of CYP7A1, the rate-limiting enzyme for converting cholesterol to bile in BE-treated cells. Furthermore, 100 \(\upmu\)g/mL of BE treatment significantly increased the expression of ABCB11, the canalicular transporter for bile acid secretion. A significant upregulation of ABCB4, a transporter for biliary phospholipid secretion, was observed in 100 \(\upmu\)g/mL of BE-treated cells (Figure 4a). Consistent  
Figure 3: The effects of BE on the protein levels for cholesterol de novo synthesis and uptake in HepG2 cells. Cells were treated with either 50 or 100 \(\upmu\)g/mL of BE for 24 h. The representative images of Western blot are shown. \(\upbeta\)-actin served as a loading control.  
Figure 2: The effects of BE on the mRNA expression of genes involved in cholesterol de novo synthesis and uptake in HepG2 cells. Cells were treated with either 50 or 100 \(\upmu\)g/mL of BE for 24 h. The mRNA abundance was determined by qRT-PCR analysis. Bars with different letters are significantly different (\(p<0.05\)). Values are means \(\pm\) S.E.M. \(n=6\).  
with mRNA data, the protein expressions of canalicular transporters for biliary cholesterol efflux were altered by BE treatment. There was a noticeable reduction in NPC1L1 protein abundance in BE-treated HepG2 cells. The protein levels of transporters involved in biliary cholesterol secretion, i.e., ABCG8 and ABCB11, were markedly induced by BE (Figure 4b).
## 4 Results
### Review Papers and Application Fields
#### 4.6.4 MCDA and Forest Management  
Forestry decision-making is highly complex, necessitating the assessment of trade-offs between economic, environmental, and social concerns [114]. [PERSON] et al. [112] conducted a review of literature on the effectiveness of forest management organisations and concluded that DEA is the most frequently adopted approach for benchmarking. However, there is a difficulty in making the tools user-friendly, and it is necessary to provide learning workshops for prospective users in the forest sector. [PERSON] et al. [114] analysed forest operations problems and reported that MCDA is less prevalent in forestoperations compared to forest management. However, they found that MCDA applications are effective at all three levels of planning--strategic, tactical, and operational.  
[PERSON] and [PERSON] [110] reviewed the empirical applications of MCDA in forestry and concluded that, although theoretical developments have progressed faster than empirical applications, there is a growing interest in MCDA among both researchers and policymakers. Furthermore, empirical MCDA techniques are improving significantly, leading to their wider application in forestry decision-making. However, there is still significant potential to improve the use of MCDA in formulating real-world strategies. [PERSON] and [PERSON] [111] suggested that a more participatory approach should be adopted in MCDA at all stages of modelling. As such, decision-makers and other stakeholders should have the opportunity to contribute to the process.  
However, [PERSON] et al. [57] reached the conclusion that, when it comes to decisions on the sustainable use of natural resources, the hybrid approaches of MCDA can provide a better structure and support for the process, as no single method can meet the requirements of an ideal decision support process. Indeed, [PERSON] et al. [115] concentrated solely on hybrid MCDA applications in forestry and found that the hybrid approaches provide a more complete perspective of the genuine outcomes of specific decisions. They also stated that is necessary to utilise participatory modelling and consider uncertainty regarding available information; however, to date, only a limited number of applications have implemented hybrid MCDA in forest management. [PERSON] et al. [113] researched the combination of multi-attribute decision making and geographic information systems in the context of forest ecosystem services. The study concluded that easy-to-use methods enable broad and participatory involvement of non-experts in the decision-making process, with AHP being the most common method. However, experts can use more advanced techniques to produce more robust and reliable results.
# Integrated Photonics for IoT, RoF, and Distributed Fog-Cloud Computing: A Comprehensive Review
## 4 Photonic Implementations in Fog Computing Domains
### Smart Buildings and Industrial IoT (IIoT)  
Smart buildings utilize thousands of sensors to monitor parameters such as temperature, humidity, occupancy, air quality, and security. These sensors generate telemetry data, which is locally processed to enable real-time responses via actuators--for example, activating fire-suppression systems or initiating lockdowns during security breaches. Because many responses are time-sensitive, Fog computing is essential for localized processing and control. The Fog architecture can be applied hierarchically within buildings, allowing each floor, wing, or room to operate its own Fog node. These nodes perform functions such as emergency response, climate control, security, and providing localized compute and storage services for residents. Operational data can be aggregated and forwarded to the Cloud for large-scale analytics and machine learning model training. The trained models are then pushed back to the Fog layer for real-time execution, enabling intelligent, responsive, and resilient building environments [21; 22; 23].  
Example: Amazon's Greengrass and Siemens Industrial Edge integrate photonic interfaces for data-intensive tasks in smart factories. Heterogeneous PICs are also being tested for predictive maintenance in IIoT environments [28].
## 2 Material and Methods
### Qualitative Analysis of Aroma Compounds
#### 2.4.3 Compound Identification
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**No.** & **Compound** & **Exact Mass (Da)** & **RI b** & **LRI c** & **Identification d** & \multicolumn{3}{c}{**SPE**} & \multicolumn{3}{c}{**SPME**} \\ \cline{6-10}  & **Alcohols** & & & & & & **Misty** & **O’Neal** & **Misty** & **O’Neal** \\ \hline
1 & ethanol & 46,042 & 730 & 668 & MS c\({}^{*}\), RIL f & & & & & & \\
2 & 1-pentanol & 88,099 & 771 & 766 & MS c\({}^{*}\), RIL & & & & & \\
3 & 2-Methylbutana-1-ol & 88,099 & 773 & 779 & MS, RIL & & & & \\
4 & (2)-3-hexenol & 86,073 & 856 & 858 & S, MS, RIL & & & & \\
5 & (E)-2-hexenol & 86,073 & 865 & 853 & S, MS, RIL & & & & \\
6 & 2-ethyl-1-hexanol & 130,136 & 1025 & 1032 & MS, RIL & + & & & \\
7 & benzyl alcohol & 100,685 & 1029 & 1039 & S, MS, RIL & + & + & & \\
8 & phenylethyl alcohol & 122,073 & 1111 & 1111 & S, MS, RIL & ++ & ++++ & ++++ \\
9 & benzerepropanol & 136,098 & 1227 & 1231 & MS, RIL & ++ & t & \\
10 & cumulica alcohol & 150,104 & 1286 & 1284 & S, MS, RIL & & & & \\
11 & cinnaryl alcohol & 134,073 & 1301 & 1312 & MS, RIL & + & t & t \\
12 & 3-hydroxy-benzethemund & 130,686 & 1422 & - & MS MS & ++++ & ++++ \\
13 & homovanilyl alcohol & 168,079 & 1527 & 1530 & MS, RIL & + & + & \\ \hline
**Esters** & & & & & & & & \\
14 & ethyl acetate & 88,052 & 742 & 628 & S, MS, RIL & & ++ & ++ \\
15 & methyl butanoate & 102,068 & 768 & 724 & S, MS, RIL & & + & \\
16 & isobutyl acetate & 116,084 & 794 & 776 & S, MS, RIL & & & + \\
17 & methyl isovalerate & 116,084 & 795 & 765 & MS, RIL & & & + & \\
18 & ethyl butanoate & 116,084 & 811 & 804 & S, MS, RIL & & & + & \\
19 & ethyl 2-methylbutanoate & 130,099 & 851 & 849 & S, MS, RIL & & + & \\
20 & ethyl 3-methylbutanoate & 130,099 & 854 & 853 & MS, RIL & & & + & \\
21 & isomary acetate & 130,099 & 875 & 876 & S, MS, RIL & & & + & ++ \\
22 & ethyl benzoate & 141,115 & 998 & 1002 & MS, RIL & + & + & + & + \\
23 & methyl benzoate & 136,052 & 1090 & 1103 & S, MS, RIL & & ++ & ++++ \\
24 & ethyl benzoate & 150,068 & 1168 & 1185 & S, MS, RIL & + & ++ & ++++ \\
25 & phenylethyl formate & 150,068 & 1178 & 1176 & MS, RIL & & & + & + & \\
26 & diethyl succinate & 174,089 & 1183 & 1167 & S, MS, RIL & ++ & + & ++++ \\
27 & methyl silsilylate & 152,047 & 1189 & 1198 & S, MS, RIL & & & + & ++++ \\
28 & ethyl octanoate & 172,146 & 1198 & 1198 & S, MS, RIL & & & + & ++++ \\
29 & ethyl decanoate & 200,178 & 1395 & 1398 & S, MS, RIL & & & + & + & + \\
30 & methyl vallilate & 182,058 & 1513 & 1525 & S, MS, RIL & ++ & & & \\
31 & ethyl+hydroxy-hypearnedate & 180,079 & 1550 & 1559 & MS, RIL & + & t & & \\
32 & benzo acid, 3,4,5-trimethoxy-, methyl ester & 226,084 & 1718 & - & MS & + & & & \\ \hline \hline \end{tabular}
\begin{tabular}{c} **Kotens** \\ \end{tabular} 33 & 3-hydroxy-2-butanone & 88,0524 & 742 & 718 & MS, RIL & & ++++ & +++ \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Characterization and relative peak size a of the volatile compounds detected in different blueberry wines by different volatile extraction methods.
## 4 Conclusions  
Based on the proposed negative thermal-flux region in the heat collecting element (HCE), three novel HCEs (NHCEs) with different IR-reflector coatings, namely, real IR-reflector coating of transparent conductive oxide (TCO) film (IRR-I), IR-reflector with a fixed cutoff wavelength of 2.5 \(\upmu\)m (IRR-II), and IR-reflector with optimal cutoff wavelength (IRR-III), were proposed. In this framework, to observe the actual overall performance of three kinds of NHCEs, a 72 m loop PTC system with different NHCEs is numerically investigated for evaluating the outdoor energetic and exergetic efficiencies of NHCEs. The simulation results based on the established mathematical models are verified with the experimental data, it is calculated that the RMSD value remains within 6.0% and the MBE value is about \(-\)0.8%, which demonstrates that the modeled results yield a satisfactory consistence with the experimental data. Additionally, the effects of solar irradiance on the performance of NHCEs are also studied in this paper. The results are summarized as follows:  
(1) Three kinds of NHCEs possess superior heat loss performance at higher temperature. The percentages of heat loss reduction of NHCE-IRR-I, NHCE-IRR-II, and NHCE-IRR-III reach 18.7%, 25.3%, and 43.8% at the absorber temperature of 600 \({}^{\circ}\)C, respectively.  
(2) Compared with the CHCE, three kinds of NHCEs achieve great overall performance at high operating temperatures, and the NHCE-IRR-III shows greatest potential for the enhancements of energetic and exergetic efficiencies in the PTC system. The percentages of enhancements of energetic efficiency and exergetic efficiency of NHCE-IRR-III reach 25.2% and 28.1% at the inlet temperature of 580 \({}^{\circ}\)C.  
(3) Direct normal irradiance (DNI) exerts an important impact on the performance of PTC system with the NHCEs. Higher value of DNI causes lower performance enhancement of PTC system with the NHCEs.  
(4) The performance-enhanced PTC system with the NHCEs would greatly contribute to the efficient building heating and cooling systems.  
Conceptualization, Q.W. and G.P.; methodology, Q.W.; software, Q.W.; validation, Q.W., H.Y. ([PERSON]). and M.H.; formal analysis, Q.W.; investigation, Q.W., J.C.; resources, Q.W.; data curation, Q.W.; writing--original draft preparation, Q.W., H.Y. ([PERSON]). and M.H.; writing--review and editing, Q.W., M.H.; visualization, Q.W.; supervision, H.Y. ([PERSON]); project administration, Q.W.; funding acquisition, H.Y. ([PERSON]), M.H. All authors have read and agreed to the published version of the manuscript.  
Figure 14: Percentage of exergetic efficiency enhancement of NHCEs versus DNI.  
Funding:This research was funded by the National Key R&D Program of China (2018 YFD0700200), Postdoctoral Hub program of the Innovation and Technology Fund of the Hong Kong SAR Government, China, the National Science Foundation of China (51761145109, 51776193) and the China Postdoctoral Science Foundation (2019M652209).
# Advancing the Solar Radiation Pressure Model for BeiDou-3 IGSO Satellites
## 3 Results
### Performance of SRP Models for BeiDou-3 IGSO Satellites  
As mentioned earlier, due to BeiDou-3 IGSO satellites with a cuboid shape, the orbits determined with the ECOM1 model may have systematic radial orbit errors. Therefore, the performance of ECOM1, ECOM2 and ECOM1 + BW models for BeiDou-3 IGSO orbit determination is analyzed. Although all BeiDou-3 IGSOs are equipped with laser retroreflectors for Satellite Laser Ranging that allows for external accuracy assessment of orbit radial component, none of BeiDou-3 IGSOs have been tracked by the International Laser Ranging Service so far. Other than SLR, the clock estimates of high-stable satellite clocks can also be used as a quality indicator for radial orbit modeling issues because radial orbit errors are mapped to the estimated satellite clocks [9; 12; 15; 23]. Due to the PHM clocks equipped on BeiDou-3 IGSOs, the residuals of the daily estimated clocks after a second-order polynomial fitting are used as a measure of radial orbit accuracy. Of course, the orbit boundary discontinuity (DBD) [35] is also a very important index for assessing orbit quality and will be discussed in detail.
## 4 Results
### Monitoring and Assessing the 2012 Drought
Figure 9: The lack of precipitation over the Great Plains from May to October in 2012. The lower values of the three-month standard precipitation index (SPI-3) (deeper red) indicate less precipitation. Figure 11 is a map showing the reduction in the NDVI. From May to June, the spatiotemporal pattern of the decline in NDVI values was quite similar to that of SIF, indicating that during this season, the drought-induced reduction of SIF also applied to the NDVI. It has been reported that the drought-induced reduction of SIF is related to the reduction of APAR (or the fraction of absorbed photosynthetic active radiation, FAPAR), to which the NDVI is also sensitive. This may explain the similarity between Figures 10 and 11. However, there are two major distinctions between the two patterns:  
* First, Figure 10 is redder than Figure 11, which indicates that SIF declined more significantly during the drought. The saturation effect of the NDVI has been widely discussed (e.g., [46; 47]), while SIF and APAR are reported to be better indicators for vegetation production [23]. [PERSON] _et al._[46], indicated that an NDVI-driven NPP model failed to capture differences in vegetation production caused by drought stress at the beginning and end of the dry season because of the NDVI saturation effect. The results in Figures 10 and 11 suggest that SIF might be more appropriate than NDVI to precisely indicate the agricultural drought level. * Second, the spatiotemporal reduction map for the NDVI was more similar to SPI-3, especially in September and October. [PERSON] and [PERSON] [6] found that the most significant correlation between the NDVI and SPI occurred for the SPI-3, while Figures 3-6 in this study show that SIF was more sensitive to shorter-term SPIs. It has been demonstrated that the 2012 drought in the Great Plains eased in September and October. In addition, the recovery of GPP in these two months (Figure 8) also indicates an easing of the agricultural drought, although this is not obvious in Figure 11.  
These two aspects of differences may help illustrate the advantage of SIF over NDVI to indicate agricultural drought, for its timeliness and directness. Figure 10: The reduction of solar-induced chlorophyll fluorescence (SIF) from May to October in 2012.
# Compact Broadband Antenna with Vicsek Fractal Slots for WLAN and WiMAX Applications
## 2 Antenna Geometry Design  
### Antenna Geometry  
The configuration of the suggested antenna is displayed in Figure 1. It comprises an octagonal radiator loaded with the two first iterations of Vicsek fractal slot structure, and it is engraved on a 1.6-mm-thick FR-4 dielectric substrate with relative permittivity \(\varepsilon_{\mathrm{r}}\) = 4.4 and \(\tan(\delta)\) = 0.02. In addition, a partial ground plane with initial dimensions 50 \(\times\) 15 mm\({}^{2}\) is printed on the bottom side of the substrate. The antenna geometry has a complete size of 50 \(\times\) 50 \(\times\) 1.6 mm \({}^{3}\) and a 50-\(\Omega\) feed line of width \({}^{\prime}W_{f}\) and length \({}^{\prime}L_{f}\) with an inset of length \({}^{\prime}d^{\prime}\), and gap \({}^{\prime}g^{\prime}\) is used to excite the antenna. The antenna has been designed and performed using the CST MWS simulator, and the optimal dimensions of the investigated antenna are listed in Table 1.
# Secure Watermarking Schemes and Their Approaches in the IoT Technology: An Overview
## 3 The Concept of IoT  
The primary advantage of the IoT is global awareness, intelligent processing and reliable transfer of information. The key is the realisation of information's interactions between a human and a device or device-to-device. These devices consist of the embedded systems, control and automation systems, WSNs and others that share information among each other in different environments for enabling the IoT [84]. Therefore, the data can be transferred over different networks without the need for human intervention. In the real environment of IoT applications, smart city and home are the most popular fields. These applications mostly consist of three layers, which include: the perception, the network and the application [16]. Network and application layers are implemented in high-power devices that will keep data secure, while the perception layer is implemented in a low-power WSN. The WSN consists of multiple sensor nodes, which are communicating among each other by using different radio frequencies that are capable of performing various tasks of sensing, surveillance, measuring, and tracking [85]. These wireless nodes are resource-constrained devices that are characterised by their low processing power, narrow bandwidth, limited battery life, and restricted memory capacity [86]. The communication between IoT layers is depicted in Figure 10.  
Based on Figure 10, WSNs are responsible for plotting the network topology and routing table in the perception layer based on the use of different protocols [87]. After that, the WSN starts collecting data from different locations and forwards it to the network layer (edge-router). However, the WSN nodes can normally function within untrusted environments, which are not periodically monitored. This makes the WSN networks extremely vulnerable to various attacks, and therefore, valuable data can be easily disclosed to unauthorized parties resulting in serious security and privacy risks [88].
# PAGE--Practical AES-GCM Encryption for Low-End Microcontrollers
###### Abstract  
An optimized AES (Advanced Encryption Standard) implementation of Galois Counter Mode of operation (GCM) on low-end microcontrollers is presented in this paper. Two optimization methods are applied to proposed implementations. First, the AES counter (CTR) mode of operation is speed-optimized and ensures constant timing. The main idea is replacing expensive AES operations, including AddRound Key, SubBytes, ShiftRows, and MixColumns, into simple look-up table access. Unlike previous works, the look-up table does not require look-up table updates during the entire encryption life-cycle. Second, the core operation of Galois Counter Mode (GCM) is optimized further by using Karatsuba algorithm, compact register utilization, and pre-computed operands. With above optimization techniques, proposed AES-GCM on 8-bit AVR (Alf and Vegard's RISC processor) architecture from short-term, middle-term to long-term security levels achieved 415, 466, and 477 clock cycles per byte, respectively.  
AES; fast software encryption; Galois Counter Mode of operation; low-end microcontrollers; side channel attack countermeasure +
Footnote †: journal: Applied sciences
# A Location and Velocity Prediction-Assisted FANET Networking Scheme for Highly Mobile Scenarios
## 5 Simulation and Analysis
### Limitation and Applicability of the Proposal  
In the aforementioned subsection, we performed some simulations and made comparisons with the existing methods from three aspects, i.e., the network stability coefficient, ratio of changed edges, and the computational complexity. Even though our proposal presents marginal improvements regarding the latter two metrics, the limitations of our proposal should also be fully noted. Our simulation scenarios involve highly mobile scenarios without any surrounding obstacles, but with some external turbulences, which makes the nodes deviate from the predefined motion trajectories. Moreover, the turbulences get more severe with the increasing motion velocity. Consequently, the network topology changes quickly as nodes proceed forward. Based on the above analysis, our findings are applicable and can be used in some highly mobile scenarios. On one hand, the external disturbances cannot be ignored and even get stronger at higher velocities, which causes nodes to deviate from predefined trajectories severely. On the other hand, it requires a low-computational algorithm to adapt to fast time-varying scenarios. The potential application scenarios are such as UAV swarms and missile swarms, etc.