esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Conclusions  
We conclude that exposure assessments based on spot measurements can serve as a practical proxy to evaluate personal RF-EMF exposure, whether using a static probe or a portable PEM. The developed methodology offers a reliable and efficient approach to characterizing personal exposure levels, enabling continuous monitoring and the detection of potential changes over time. The result of the different proportionality factors obtained is shown in Table 4.  
The application of correction factors, particularly the differentiation between LOS and NLOS conditions, significantly improves the accuracy of PEM measurements, bringing them closer to those obtained with BBMs. This highlights the importance of accounting for the line of sight to antennas when estimating exposure levels, as direct exposure to base stations considerably affects measurement accuracy due to body shielding effects. By applying appropriate correction factors, the inherent limitations of PEMs, such as underestimating exposure levels in LOS conditions, can be mitigated.  
Moreover, using genetic algorithms to optimize these corrections further enhances the precision of the exposure maps, demonstrating that this method can be a valuable tool in urban RF-EMF monitoring. The ability to generate accurate spatial exposure distributions through PEMs makes this methodology more accessible and cost effective, especially in large-scale studies where deploying multiple BBMs might not be feasible.  
Nevertheless, further validation is needed in various environments to refine the correction models and ensure broader applicability. Future studies should focus on refining these algorithms and exploring other factors that could influence exposure, such as linearity, urban infrastructure, and signal interference. Despite these challenges, the methodology developed in this study represents a significant advancement in RF-EMF exposure assessment, offering a flexible and scalable approach to creating consistent EMF exposure maps using PEMs.  
Conceptualization, R.C.-d.-C.; Methodology, A.N. and P.-L.L.-E.; Software, R.S.-M. and J.G.-P.; Validation, J.G.-R. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the University of Alcala and Comunidad de Madrid (grant numbers CM/JIN/2021-032, UAH INFR. B 2021-012 and CM/JIN/2019-036). These research projects are founded by the University of Alcala and Comunidad de Madrid (Government of Madrid Region) in a competitive concurrence and external evaluation basis.  
Not applicable.  
The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.  
The authors declare no conflict of interest.
# A Risk Assessment Analysis to Enhance the Security of OT WAN with SD-WAN
## 2 Related Works
### Analysis  
While the above- mentioned studies offer valuable insights that contribute to today's research, there is a significant gap in comprehensively analyzing SD-WAN and assessing its effectiveness as a security solution for OT infrastructure, rather than merely viewing it as a network device. Moreover, the existing research primarily employs simulations using various tools to analyze SD-WAN. This paper will evaluate whether SD-WAN is sufficiently efficient as a security solution for OT networks through a security risk assessment, considering the advantages and disadvantages of an extended OT infrastructure in a cloud environment. Additionally, this paper includes a systematic evaluation of selecting a risk management framework tailored to OT, which will be used to test multiple WAN security solutions and identify key variables to consider when choosing a network security solution to enhance the OT WAN infrastructure and bolster security for ICS and CPS.
## 4 Discussion
### Limitations of the LUE-Based Model  
The basis of the LUE-based models is the initial linear relationship between the GPP and APAR of the canopy [63]. However, this relationship is not linear at the individual leaf level and is characterized by temporal heterogeneity associated with the variation of illumination levels [95]. Photosynthesis in sunlit leaves is often light-saturated and limited by the level of Rubisco activity related to leaf nutrient conditions and the ambient temperature [18], which results in a lower LUE, while photosynthesis in shaded leaves is often not light-saturated and essentially has a linear response to APAR, which results in a higher LUE [13; 96; 97; 98; 99]. In the LUE-based MuSyQ-GPP algorithm, LUE is determined by assigning a constant maximum value of \(LUE_{0}\) and adjusting downward based on temperature and water conditions. Daily variability in the sunlit and shaded leaf fractions cannot be represented in this model. Consequently, the internal physiological processes of these two leaf groups are substantially different and the LUE of the shaded leaves is generally higher than that of the sunlit leaves [95]. As GPP can vary greatly in space and time as a result of the variability between sunlit and shaded leaf fractions, we argue that scaling the \(LUE_{0}\) without considering the difference between the sunlit and shaded leaf groups can significantly limit the performances of the LUE-based models. There are some literature suggests that the LUE models underestimate GPP at high productivity and overestimate GPP at low productivity [96], and the underestimation is consistent with our research. However, the overestimation cannot be clearly shown in our analysis. These results are not contradictory since our data at low productivity is limited. In addition, the \(LUE_{0}\) used in the LUE-based models is usually defined as a constant value for each broadly defined plant functional type (PFT). For our study, we used a constant value of 0.60 gC mol\({}^{-1}\) PPFD from the study by [PERSON] [69], which was conducted at the same site as our study. However, other literature has suggested that \(LUE_{0}\) for maize at different sites can be assigned as 1.50 gC mol\({}^{-1}\) PPFD [67; 100], 0.93 g C mol\({}^{-1}\) PPFD [101], or 1.22 g C mol\({}^{-1}\) PPFD [101]. Therefore, \(LUE_{0}\) varies among vegetation types and study sites and should be calibrated before using in the LUE-based approach. Moreover, the MuSyQ-GPP algorithm deploys two down-regulating factors to represent the effects of temperature and water conditions while scaling the \(LUE_{0}\). Although various strategies have been developed to characterize the impacts of temperature and water stresses [8; 9; 10; 11], the descriptions of their influences in the LUE-based approaches are still empirical, which may introduce some uncertainties, especially for the water stress scalar. For the MuSyQ-GPP algorithm, a calculation of evapotranspiration is conducted to represent water availability. Predictably, the uncertainties existing in the evapotranspiration estimation would lead to significant deviations in the final GPP estimation.
# Power Control and Link Selection for Wireless Relay Networks with Hybrid Energy Sources
## 3 Optimal Control for Expected Total Rewards
### Parameter Analysis  
Figure 2 demonstrates the total rewards with different number of battery levels at different time slots. In any slot, the total rewards increase with the number of battery levels rises. Actually, the energy between two adjacent levels is expressed by the lower level, and the interval of two adjacent levels is smaller as the number of levels becomes larger. At this point, the error between the true value and the expressed value will be smaller, which makes a more accurate result. When the number of battery levels reach 80 and 160, their rewards are close and maximal. Consequently, for reducing the computational complexity, M = 80 is used for simulation analysis in the follow-up.  
We assume that \(d_{SD}=d_{SR}+d_{RD}=80m\), and the total rewards vary with \(d_{SD}\) is shown in Figures 3 and 4. As \(d_{SD}\) increases, the rewards of all algorithms become larger first and then decrease. When \(d_{RD}\) is small, \(d_{SR}=80-d_{RD}\) is large, and the path loss between the source node and relay is high. In this case, the source node delivers a few bits to relay with high grid energy consumption, which leads to low total rewards. As \(d_{RD}\) increases, the path loss between the source node and relay decreases, and the total rewards rise. Once \(d_{RD}\) is larger than a certain threshold, the path loss between the relay and destination is high, the number of bits that can be transmitted by relay is lower than that by source node. In this case, the total reward is gradually reduced as the throughput of relay tapers off.  
Figure 2: Total reward vs. time slots for different number of the battery intervals, \(\omega_{t}=1\), \(d_{SD}=d_{SR}+d_{RD}=40m\).  
In addition, the JPLA-F and BIBAoSE-F achieve the maximum value near \(d_{RD}^{*}=40\) m in both Figures. Meanwhile, the PCA, JPLA and BIBAoSE obtain the maximum value at different \(d_{RD}^{*}\) in two Figures. Unlike the JPLA-F and BIBAoSE-F, the other three algorithms are affected by the energy harvesting intensity. The energy that the relay needed for data transmission grows larger as \(d_{RD}\) increases. Therefore, when the energy is more sufficient, the total rewards will be closer to optimal result. The total rewards reach the maximum value at \(d_{RD}=40\). Thus, we choose \(d_{RD}=40\) for subsequent simulations to better observe the improvement of system performance in the absence of energy.
# Cooperative Power-Domain NOMA Systems: An Overview
## 3 Types of NOMA
### Power Domain NOMA  
Different PD-NOMA versions employed in 5G as shown in Figure 7 are discussed in this section. PD-NOMA is a method for simultaneously serving many users by differentiating power levels. This method is most commonly used in 5G to enhance energy efficiency, spectral efficiency, and latency. The subsections that follow provide a thorough explanation of each PD-NOMA variation.
# Affordable Broadband with Software Defined IPv6 Network for Developing Rural Communities
## 3 Affordable Broadband for Rural Communities
### Wireless and Satellite Communications  
In the mountainous regions where a wired network is not possible, wireless communication such as Wi-MAX and 3G/LTE/4G technologies and the use of TVWS for long distance wireless coverage has to be established. Additionally, some places require satellite communications. Geostationary Earth Orbit satellites are comparatively simple and cost effective compared with other constellations [17]. Focusing on the unserved and underserved communities, Low Earth Orbit (LEO) satellites provide low latency and high-speed broadband services to rural communities. The LEO satellite system is becoming the global communication service provider's counterpart to local terrestrial paging, cellular, and fiber networks. Telesat, OneWeb, SpaceX [32; 33], and Amazon [34] have initiated LEO satellites to establish low cost, affordable, and sustainable global communications.
# Atmospheric Effects on Satellite-Ground Free Space Uplink and Downlink Optical Transmissions
## 2 Uplink and Downlink Channels in Satellite-Ground FSO Communications  
In uplink and downlink satellite-ground communications, the optical signal propagates through the Earth's atmosphere and loses power due to a variety of factors such as the geographic environment, time of day, and weather. Environmental factors, such as clouds, snow, fog, rain, and haze, cause significant attenuation in the optical signal. Unlike radio communications, optical communications cannot pass through most types of cloud cover [17]. In addition, atmospheric turbulence in the daytime is comparatively more than at night [18]. The responsibility of an FSO system designer is to carefully examine the design requirements to minimize signal attenuation due to the atmosphere. Atmospheric attenuation factors in both satellite-ground and ground-satellite communications are discussed in this section.
## 3 Results and Discussion
### FT-IR Analysis  
The FT-IR spectra for the precursors (PVP, LaMnO\({}_{3}\):Ag, and LaMnO\({}_{3}\):Pd) and the two hybrid materials (LaMnO\({}_{3}\):Ag/PVP (P11), LaMnO\({}_{3}\):Pd/PVP (P14)) are shown in Figure 2.  
The FT-IR spectrum of pure PVA exhibits the following significant absorption bands: 3453 cm\({}^{-1}\) related to O-H stretching, 2950 cm\({}^{-1}\) corresponding to asymmetric C-H\({}_{2}\) stretching [4; 36], 1493-1421 cm\({}^{-1}\) assigned to C-H\({}_{2}\) deformations [37], 1286 cm\({}^{-1}\) attributed to C-N bending vibration from the pyrrolidone structure [38].  
A strong absorption peak located at 1652 cm\({}^{-1}\) can be assigned to the C=O stretching vibration in the pyrrolidone group [4; 36; 38; 39]. However, [PERSON] et al. [37] supported the assignment of the peak at \(\sim\)1660 cm\({}^{-1}\) as amide I rather has a carbonyl stretch.  
All the major functional groups of the host polymer can be found in the spectra of the hybrid materials. The FT-IR spectra of the hybrid materials show certain differences regarding the position of the absorption bands corresponding to PVP and increased intensities.  
The C-H stretching vibration peaks blue-shift to 2953 cm\({}^{-1}\) for sample P11, and 2952 cm\({}^{-1}\) for sample P14, respectively. The broad band around 3600-3200 cm\({}^{-1}\) corresponding to O-H stretching vibration is centered at \(\sim\)3453 cm\({}^{-1}\) in PVP spectra, while in both hybrid materials, it is centered at 3418 cm\({}^{-1}\).  
Figure 1: XRD patterns for the precursors and hybrid materials: (**a**) LaMnO\({}_{3}\):Ag, PVP, and LaMnO\({}_{3}\):Ag/PVP (P11); (**b**) LaMnO\({}_{3}\):Pd, PVP, and LaMnO\({}_{3}\):Pd/PVP (P14).  
Figure 2: The FT-IR spectra of the precursors and hybrid materials: (**a**) LaMnO\({}_{3}\):Ag, PVP, and LaMnO\({}_{3}\):Ag/PVP (P11); (**b**) LaMnO\({}_{3}\):Pd, PVP, and LaMnO\({}_{3}\):Pd/PVP (P14).  
The C=O stretching band is shifted from 1652 cm\({}^{-1}\) to lower wavenumbers in both hybrid materials (1646 cm\({}^{-1}\) for sample P11, and 1647 for sample P14). This red shift could be explained by the coordination between metallic species and carbonyl oxygen from PVP [39; 40; 41].  
The band shifting and their variation in intensities in the FT-IR spectrum indicate the formation of new hybrid materials. The bands of both perovskites are not visible in the spectra of the hybrid materials in the 4000-600 cm\({}^{-1}\) range, probably due to the large amount of PVP used compared to the amount of perovskite materials.
# Using Acoustic Emission Methods to Monitor Cement Composites during Setting and Hardening
## 4 Conclusions  
The acoustic emission method seems to be a suitable complementary instrument for determining the incidence of new formations and later micro-cracks during the setting and hardening of cement composites. Identifying a particular source of acoustic emissions in cement composites containing aggregate is usually more difficult than in the case of cement pastes, especially during the stage of setting and early hardening [39]. In many cases, there are parallel phenomena which contribute to the overall progress of composites' internal structure formation. Generally, the higher number of new formations and micro-cracks appear, the more acoustic emission events are generated. It may be stated that the higher the AE signal amplitude values are recorded, or AE signal energy is released, the more significant structural changes occur in the form of new formations or damage in the existing structure [40]. The number and size of micro-cracks in a cement composite significantly affects its final mechanical properties (i.e., strength, elastic modulus, durability, etc.). The application of the AE method to continuous monitoring of cement composites during setting and hardening may be an instrument suitable for timely detection of micro-damage. However, at this stage of technological progress, the application of the AE method may be rather complicated. The sensors cannot be placed on the specimen surface without having them embedded. Therefore, the use of waveguides seems to be better suited for observing the setting of a fresh mixture. Fixing the sensor to the waveguide improves the sensor's sensitivity so the waves (signals) received become more stable due to the shape and length of the waveguide and are more easily detectable. Based on the characteristics of recorded signals (duration, amplitude, energy) the significance of the recorded AE events may be defined. In the ongoing investigation of materials' structural changes, the AE measurements will be supplemented with the microscopic analysis, which allows the quantification of these micro-changes.  
This outcome has been achieved with the financial support of the Czech Science Foundation under project no. 17-143025 \"Experimental analysis of the early-age volume changes in cement-based composites\" and the project no. LO1408 \"AdMaS UP--Advanced Materials, Structures and Technologies\", supported by Ministry of Education, Youth, and Sports under the \"National Sustainability Programme I\".  
[PERSON] and [PERSON] conceived, designed, and performed the experiments; [PERSON], [PERSON], and [PERSON] analysed the data and wrote the paper; and [PERSON] and [PERSON] supervised the research and revised the manuscript.  
The authors declare no conflict of interest.  
Figure 8: Energy of AE signals measured during the first 68 h of specimen aging.
# Disguised Full-Duplex Covert Communications
## 3 Problem Formulation  
In this work, we aim to identify the optimal public data rate and transmit power of the FD destination node that maximizes the covert rate at the hidden receiver as  
\[\text{(P1):}\max_{P_{D}\
eq P}r_{C,R},\] (17a) subject to: \[r_{P}\leq\bar{r}_{P,R}, \tag{17b}\] \[r_{P}\leq\bar{r}_{P,D},\] (17c) \[r_{P}\geq\bar{r}_{P},\] (17d) \[\Pr(\text{error})\big{|}_{\tau=\tau^{\star}}\geq\varepsilon,\] (17e) \[\zeta\rho_{W}^{2}\geq|h_{DW}|^{2}P_{D}+\frac{1}{\zeta}\sigma_{W} ^{2},\] (17f) \[0\leq P_{D}\leq\bar{P}_{D}. \tag{17g}\]  
Constraint (17b) guarantees that the hidden receiver successfully decodes and eliminates a public message prior to decoding a covert message, and (17c) indicates the achievable public data rate up to which the destination node can notify the source node to adjust. A minimum quality of service \(\bar{r}_{P}\) for the public transmission is considered in (17d), and (17e) with (17f) assures the non-zero minimum DEP for \(0\leq\varepsilon\leq 0.5\). Lastly, (17g) shows the power budget \(\bar{P}_{D}\) at the disguised FD destination node.
## 3 The Consecutive Iteration Based on Signal Cancellation (SCCI) Algorithm
### Adaptive Variable Convergence Factor
#### 3.2.3 Performance Comparison of Algorithms  
A comparison of the adaptive variable convergence factor in the SCCI algorithm with the fixed convergence factor in the SCCME algorithm was simulated. The system sampling points were 500, and each curve was the average result of 100 independent simulations. The fixed convergence factors in the SCCME algorithm were 0.1, 0.05, and 0.01, respectively. The simulation results are shown in Figure 4.  
From Figure 4, it can be observed that the convergence speed and steady-state error performance of the SCCI algorithm are significantly higher than those of the SCCME algorithm with different convergence factor values. For the SCCME algorithm, the smaller the convergence factor value, the better the steady-state error performance, but the slower the convergence speed. Through the analysis above, it can be seen that compared to the SCCME algorithm with a fixed convergence factor, the SCCI algorithm has obvious advantages in convergence speed, a lower steady-state error, and stronger adaptability to external systems.  
Here is a summary of the SCCI algorithm process, as shown in Figure 5, with detailed steps outlined in Table 1.  
Figure 4: Convergence curves of each algorithm.  
Figure 5: Flow chart of SCCI algorithm.
## 4 Discussion
### Free Radical Scavenging Using DPPH Assay  
Antioxidants play an important role in protecting cell tissues from free radicals, thus protecting the living organism against infections and degenerative diseases such as cancer. The antioxidant activity of the extracts indicates the presence of compounds that can interact with free radicals and act as electron donors [46]. DPPH is a well-known compound that has been used extensively as a free radical to evaluate the radical scavenging abilities of natural compounds [55]. DPPH is a stable free radical that has a strong absorption band centered at about 517 nm, which is diminished in the presence of antioxidants capable of reducing it to its hydrazine form by hydrogen/electron donation [56]. In the present finding, all tested microalgae extract scavenged DPPH at different levels. Observing the phenolic content data, a positive correlation between total phenolic content and antioxidant activity was noted. Therefore, high scavenging activity in BCM extract could be probably due to its higher content of phenolic compounds compared to BBM and ANM extracts. On the other hand, [57] in their study on antioxidant activity of three edible seaweeds from two areas in South East Asia, reported a similar correlation after using the DPPH radical scavenging assay. These authors found a decrease in IC\({}_{50}\) with an increase in the total phenolic content level. Investigations revealed that the high amount of polyphenic compounds present in the seaweed were capable of functioning as free radical scavengers. Our findings are in agreement with [21], who presented results of DPPH radical-scavenging activity of \(96.8\pm 0.07\) % in a red alga, _Polysiphonia vacculata_ crude extract, using an ascorbic acid solvent fraction. On the other hand, the current results differ from the findings of [58] who found the highest radical scavenging ability of \(70.3\pm 0.6\) % in _Nannochloropsisulata_ hexane extracts. This difference might be due to the differences in the chemical nature of the compounds that contribute to antioxidant responses within the cellular structure of these species [24].