esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results  
The extraction processes of _Ganoderma lucidum_ spores gave oily residues, as reported in experimental section. The extracts weights obtained by extraction with \(n\)-hexane, in Soxhlet apparatus with \(n\)-hexane and reflux extraction with chloroform are, respectively, 5.3 \(\pm\) 0.31 g (yield = 26.43%), 32.7 \(\pm\) 0.24 g (yield = 32.65%) and 0.27 \(\pm\) 0.02 g (yield = 26.83%). The oily extracts were submitted to spectroscopic investigations via NMR. The \({}^{1}\)H NMR spectra showed typical signals of triglycerides containing chains of saturated and unsaturated fatty acids [24]. Moreover, even in the commercially available liquid extract of \(G\). _lucidum_. In fact, their proton spectra showed the signals related to fatty acid residues at 8: 5.46-5.33 (m, -**CH**=**CH**-); 2.78 (brt, \(J\) = 6.6, Hz, =CH-CH**2**-CH**=); 2.37-2.29 (m, -O-CO-CH**2**); 2.16-1.70 (m, **CH**2-CH**=CH**-); 1.67-1.62 (m, -O-CO-CH**2**-CH**-); 1.39-1.21 (m, -(**CH**2)_n-); 0.93-0.88 (m, **CH**3 CH**2-) and of residue of glycerols triesterified at 8: 5.28 (tt, \(J\) = 4.0, 6.0 Hz, ROCH\({}_{2}\)-CHOR\({}^{\prime}\)-CH\({}_{2}\)OR\({}^{\prime\prime}\)); 4.30 (dd, \(J\) = 4.0, 12.0 Hz, ROCH\({}_{2}\)-CHOR\({}^{\prime}\)-CH\({}_{2}\)OR\({}^{\prime\prime}\)); 4.15 (dd, \(J\) = 6.0, 12.0 Hz, ROCH\({}_{2}\)-CHOR\({}^{\prime}\)-CH\({}_{2}\)OR\({}^{\prime\prime}\)) (Figure 1). Triglycerides in the oily extracts of \(G\). _lucidum_ were subjected to a common transesterification reaction, called alcoholysis. In transesterification, triglycerides react with methanol in the presence of a basic catalyst to form a mixture of glycerol and fatty acid methyl esters (FAMEs) [18]. FAMEs were identified and quantified via GC-MS in all samples. For accurate identification and quantification of FAMEs, the GC-MS method was optimized for the best peak resolution and minimum run time using a 37-components FAMEs standard mixture. As can be seen from Figure 2, the optimized method (reported in a previous section) provides separation on  
Figure 1: \({}^{1}\)H NMR spectra recorded at 400 MHz in CDCl\({}_{3}\) of extracts obtained from _Ganoderma lucidum_ spores: (**A**) commercial liquid extract, (**B**) by \(n\)-hexane; (**C**) by \(n\)-hexane in Soxhlet apparatus; (**D**) by reflux in CHCl\({}_{3}\). the base line of all components of the standard FAMEs mixture. In Table 1 are exposed retention data both in the form of retention times (t\({}_{\text{r}}\)) and Kovats retention indices (KI) of the twelve FAMEs obtained from _G. lucidum_ spores. For quantification of detected FAMEs, the internal standard calibration method (ISTD) was employed, as is usual in quantitative GC-MS work. To this end, the standard FAMEs mixture was diluted with \(n\)-hexane to prepare five calibration solutions containing accurately known concentrations of each target analyte. Furthermore, each calibration solution was made 122.4 mg L\({}^{-1}\) of methyl ester of nonanoic acid internal standard (IS).
## 6 Conclusions  
In this paper, we proposed a novel method for narrowband interference (NBI) cancellation in SC-FDE systems. The proposed technique aligns the interference frequency with the FFT grid frequency using a fine frequency shifting process, followed by interference removal through FFT nulling. This approach combines the simplicity of the FFT nulling method with enhanced BER performance by minimizing the impact on the desired signal. Simulation results demonstrate that the proposed method effectively cancels NBI even under conditions of very strong interference. Furthermore, when combined with DSSS, the method achieves BER performance that is nearly identical to interference-free scenarios, underscoring its robustness and effectiveness. These findings indicate that the proposed interference cancellation technique is not only suitable for scenarios with unintentional interference but also highly effective in military communication systems that must withstand intentional jamming attacks. Moreover, the method's versatility enables its application in both mobile and satellite communication systems. Its ability to maintain low distortion of the desired signal makes it particularly beneficial for communication environments requiring high sensitivity and robust interference cancellation. This contribution has the potential to significantly advance reliable communication in both commercial and military applications.  
Conceptualization, S.-M.Y. and E.-R.J.; methodology, E.-R.J.; software, S.-M.Y.; validation, Y.-B.R., D.-H.S. and E.-R.J.; formal analysis, E.-R.J.; investigation, D.-H.S.; resources, Y.-B.R.; data curation, E.-R.J.; writing--original draft preparation, S.-M.Y.; writing--review and editing, E.-R.J.; visualization, S.-M.Y.; supervision, E.-R.J.; project administration, D.-H.S.; funding acquisition, Y.-B.R. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Korea Research Institute for defense Technology planning and advancement (KRIT) grant funded by the Korea government (DAPA(Defense Acquisition Program Administration)) (No. KRIT-CT-22-079(2), On Board Processor Payload of LEO Communication Satellite, 2022).  
Figure 13: BER performance with interference cancellation under ETU channel and SIR = 0 dB (solid: spreading gain 1, dashed: spreading gain 4).  
Data Availability Statement: The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.  
The authors have no acknowledgments to declare.  
The authors declare no conflicts of interest.
# Digital Twin Technology-Based Networking Solution in Low Earth Orbit Satellite Constellations
###### Abstract  
Digital twin technology provides a reliable paradigm to address the high trial-and-error costs and limited perception capabilities in satellite networking. However, the dynamic constellation topology and real-time twin applications remain significant challenges in satellite network design. This paper proposes a network topology simulation approach that dynamically analyzes the inter-satellite topology based on pre-calculated ephemeris and orbital information. Furthermore, the paper introduces a digital twin algorithm based on network virtualization, cloud platform management, and software-defined networking to validate and analyze the twin requirements at different stages. Finally, a low Earth orbit (LEO) constellation twin validation environment is constructed to verify the networking protocols at various stages. The experimental results demonstrate the performance of the proposed twin systems at different stages.  
low-orbit constellation; digital twin; system construction; network optimization Article
## 2 Mathematical Description of the Proposed Hybrid System Components
### BESS System  
The battery energy storage system (BESS) is a mandatory element for the isolated hybrid systems. BESS is charged in the periods of power excess and discharged when the load increases. The capacity of the BESS is expressed as follows [25]:  
\[C_{bat}=\frac{E_{I}\times AD}{DOD\times\eta_{inv}\times\eta_{b}} \tag{8}\]  
where \(E_{I}\) is the load demand, \(AD\) represents the autonomy daily of the battery, \(DOD\) is the depth of discharge of the battery system, \(\eta_{inv}\) and \(\eta_{b}\) are the battery and inverter efficiency, respectively.
###### Abstract  
Efficient energy utilization and network life prolongation are primary objectives to be considered when designing a Wireless Sensor Network. Cluster-based routing protocols are most suitable for achieving such goals. Energy and Optimal Inter Cluster Head Distance (EOICHD) is a cluster-based hierarchical routing protocol inspired by the Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol. EOICHD resolves the problems associated with LEACH protocol, such as selecting cluster head nodes in close proximity. By carefully selecting the cluster head nodes based on residual energy and optimal inter-cluster head distance, EOICHD ensures that selected cluster head nodes are separated by a certain optimal distance. This approach ensures uniform distribution of cluster head nodes across the entire network. The study of the EOICHD protocol presented so far is not sufficient. Hence, in this paper, we propose three variants of EOICHD protocol to understand its behavior in a better manner. A comparative analysis of all three EOICHD variants, LEACH and LEACH-central constrained (LEACH-C) protocol, is performed by considering comparative parameters such as alive nodes, cumulative network energy, data packets arrived at the base station, and stability of the network.  
cluster head node; EOICHD; energy efficiency; cluster distance +
Footnote †: journal: Applied System  
**Authors**
## 3 Results and Discussion
### Quantification of Compounds by HPLC
However, the maximum concentration at this temperature for kaempfer was obtained at the lowest exposure time (E:75\(-\)10), which may forecast the degradation of this compound upon more prolonged exposure at higher temperatures, owing to its thermal sensitivity [87]. In general, prolonged exposure negatively affects the yields of the studied compounds (Figure 3). [PERSON] et al. [21] also showed the complexity of the chromatograms obtained for red propolisils extracts from the equivalent geographic region, and they confirmed the occurrence of isoflavoids, including formononetin and the flavonoid kaempfer. [PERSON] et al. [17] also identified and quantified formononetin in Brazilian red propolisils extracts from the equivalent geographic region that were processed with ultrasound technology at room temperature (25 \({}^{\circ}\)C), with exposure for 1 h, and they observed lower values for this compound when compared with sample E:50\(-\)20 (25% lower), which may indicate that a temperature of 50 \({}^{\circ}\)C is optimal for extracting this component. [PERSON] et al. [27] also identified formononetin as the main compound in Brazilian red propolisils extracts from the same geographic region. Kaempfer is a compound with high antioxidant activity, but it is present at low concentrations in red propolisis [27]. [PERSON] et al. [88] detected kaempfer in only three European propolis samples among the twenty studied, with a concentration range between 0.0697 and 0.2931 mg\(\cdot\)g\({}^{-1}\). Importantly, this compound was not identified in samples of Cuban red propolisils extracts from different regions [20]. Results similar to those in this work were described by other authors when comparing the yields of the chemical species of interest from several natural matrices when ultrasound and conventional extraction were applied, showing that extraction with ultrasound pretreatment is more selective and thus generates products with higher biological value [89; 90; 91; 92; 93]. Therefore, among the parameters evaluated in this study, although it does not show the highest antioxidant activity, sample E:50\(-\)20 was the sample that presented the highest content of the formononetin and kaempfer (the compounds of interest), thus showing the greater biological potential of this extract when it was obtained under the tested conditions. It should be noted that different studies indicate that formononetin presents different important biological activities, e.g., acting in a positive manner against distinct tumor cell lines [94; 95]. Thus, the antioxidant property of an extract cannot be related only with the occurrence of phenolic compounds and/or flavonoids, since other classes of compounds can also support this activity [96].
# A Hybrid Deep Learning Approach for Cotton Plant Disease Detection Using BERT-ResNet-PSO
## 3 The Proposed Hybrid Deep Learning Approach
### BERT-Based Encoder for Image Segmentation Dataset
#### 3.2.5 Final Classification and Ensemble Learning  
To improve the robustness of classification, predictions from multiple models optimized through PSO are combined into an ensemble. The ensemble formulation is expressed as:  
\[\hat{y}=\text{model}(\hat{y}_{1},\hat{y}_{2},\dots,\hat{y}_{k}) \tag{14}\]  
where \(\hat{y}_{k}\) is the prediction from the \(k^{th}\) model in the ensemble, and \(\hat{y}\) is the final ensemble prediction.  
Alternatively, a weighted voting scheme can be applied, where models with higher accuracy on a validation set have a greater influence on the final prediction. This weighted ensemble voting is represented as:  
\[\hat{y}=\sum_{i=1}^{k}\omega_{i}\hat{y}_{i} \tag{15}\]  
where \(\omega_{i}\) are the weights allocated to each model's prediction based on validation accuracy.
# Research on Hybrid Relay Protocol Design and Cross-Layer Performance Based on NOMA
## 6 Conclusions  
In this paper, the physical layer and MAC layer of a wireless and power line communication hybrid relay system based on NOMA are studied comprehensively. By determining the optimal power allocation factor, the comprehensive performance of the combined normalized throughput and packet loss probability is optimized. Simulation results show that the cross-layer algorithm in this paper can achieve the best system performance by analyzing the relationship between transmitting power and performance index more comprehensively and accurately, so as to select the optimal total transmitting power at the source end and the power allocated to different users according to channel quality. The relevant conclusions can provide necessary theoretical support for the application of wireless and power line hybrid relay communication technology. However, the stations at the source of this paper compete based on the CSMA access scheme, and users use random user pairing when sending data, so the fairness and reliability of the system need to be further improved. In the future, we can continue to study the protocol improvement of the MAC layer and user pairing problems based on NOMA technology, so as to improve the transmission reliability and user fairness of the physical layer and further improve the overall performance of the system.  
Figure 8: Comparison of optimization target of different algorithms with SNR.  
Figure 9: Comparison of delay of different algorithms with SNR.  
**Author Contributions:** Conceptualization, Z.C.; formal analysis, T.C.; methodology, Z.C.; software, P.W.; validation, P.W.; writing--original draft, T.C.; writing--review & editing, J.F. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by the National Natural Science Foundation of China Youth Fund Project, grant number 61601182, and the Central University Research Fund Project, grant number 2023 MS113.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The data that support the findings of this study are available from the corresponding author upon reasonable request.  
**Conflicts of Interest:** The authors declare no conflicts of interest.
# The Applications and Challenges of Digital Twin Technology in Smart Grids: A Comprehensive Review
## 2 Methodology
### Study Selection Process  
The paper selection process was designed to capture the most relevant studies demonstrating practical Digital Twin implementations or significant theoretical contributions to smart grid applications. Selection was conducted in three stages:  
Stage 1: Initial Screening (520 \(\rightarrow\) 180 papers): Papers were screened based on title and abstract review. This stage identified papers with clear focus on Digital Twin applications in power systems, eliminating papers with only peripheral mentions of the technology.  
Stage 2: Full-Text Assessment (180 \(\rightarrow\) 95 papers): Detailed review of full texts focused on technical content and implementation details. Key papers emerged in several areas:  
* Grid intelligence enhancement frameworks [16; 17; 21].
* Energy management implementations [17; 18; 20].
* Security testing frameworks [21; 23; 24].
* Novel application architectures [21].  
Stage 3: Final Selection (49 papers): we applied our quality assessment criteria to the 95 papers; this resulted in 49 papers for detailed analysis. In this final stage, we prioritized papers demonstrating robust methodology, comprehensive validation, and significant contribution to the field. These papers formed the core foundation for our subsequent analysis of DT applications in smart grids.  
A flow diagram showing the complete selection process with numbers at each stage and filtering criteria applied is shown in Figure 4.  
The selection process used the following criteria:  
* Papers presenting original Digital Twin implementations in smart grids.
* Studies with clear validation of proposed solutions.
* Works demonstrating integration with emerging technologies.
* Papers with comprehensive security considerations.  
Figure 4: PRISMA flow diagram.  
* Studies reporting real-world deployment results. Exclusion Criteria:
* General IoT papers without specific Digital Twin focus.
* Papers lacking technical implementation details.
* Duplicate studies covering the same implementation.
* Non-peer-reviewed technical reports.
* General blogs without technical contributions.
## 4 Performance Evaluation
### Performance Comparison  
According to [25; 26], the average SE and average EE requirements for 5G mobile systems are 27-37 bps/Hz and \(3\times 10^{-6}\) Joules/bit, respectively. It is expected that the future 6G mobile systems will require 10 times average the SE [1] (i.e., 270-370 bps/Hz) and 10 times the average EE [2] (i.e., \(0.3\times 10^{-6}\) Joules/bit) of 5G mobile systems. Here, \(\sigma_{\rm SE}^{\rm 6G}\) and \(\sigma_{\rm EE}^{\rm 6G}\) denote the average SE and average EE requirements for 6G mobile systems, respectively, such that \(\sigma_{\rm SE}^{\rm 6G}=\) 270-370 bps/Hz and \(\sigma_{\rm EE}^{\rm 6G}=\) \(0.3\times 10^{-6}\) Joules/bit. Now, using Equations (22)-(23), the required values of \(\varepsilon_{\rm RF}\) and \(L\) for the system-level average SE \(\sigma_{\rm SE}^{\rm sys}\) and average EE \(\sigma_{\rm EE}^{\rm sys}\) to satisfy the corresponding requirements for 6G mobile systems are given in Table 3. From Table 3, it can be found that both the average SE and average EE requirements for 6G mobile systems can easily be satisfied by all possible 3D spatial reuse factors with cluster sizes of 4, 9, and 16 for multistory buildings, with each building containing 10 floors with 18 apartments per floor, which is achieved by reusing the same 28 and 60 GHz mmWave spectra, with small-cell building \(L\) values of just 3, 2, and 1, respectively. It is noted that with no 3D spatial reuse of mmWave spectra (i.e., \(\varepsilon_{\rm RF}=\) 1), a large number of small-cell buildings with \(L=\) 30 are needed to satisfy the requirements (particularly, the average SE requirement) for 6G mobile networks.  
Figure 5: (**a**) Average spectral efficiency (SE) and (**b**) average energy efficiency (EE) responses for different values of \(L\) with the variation in 3D spatial reuse factor per building.  
\begin{table}
\begin{tabular}{c c c c c} \hline \multirow{2}{*}{\(\varepsilon_{\rm RF}\)} & \multirow{2}{*}{\(|\Theta_{\rm 3D}^{*}(\varepsilon_{\rm F})\)} & \multicolumn{2}{c}{_L (to Satisy Both Average SE and EE Requirements for 6G Mobile Networks)_} \\ \cline{3-5}  & & \(\sigma_{\rm SE}^{\rm sys}\)\(\geq\)\(\sigma_{\rm SE}^{\rm 6G}\) & \(\sigma_{\rm EE}^{\rm sys}\)\(\leq\)\(\sigma_{\rm EE}^{\rm 6G}\) & max(\(\sigma_{\rm SE}^{\rm sys}\)\(\sigma_{\rm EE}^{\rm sys}\)) \\ \hline
1 & 180 & 30 & 1 & 30 \\
11 & 16 & 1 & 1 & 1 \\
20 & 9 & 2 & 1 & 2 \\
35 &
## 3 Results  
### Plasma Biochemistry and Leukocyte Profile  
Results of plasma parameters analysis and leukocyte profile are presented in Table 2. Statistical analyses showed significant differences between the wild-caught and the farmed fish for almost all measured parameters, with the exception of plasma concentrations of GLU, CHOL, and URE. The levels of TRIG, TP, ALB, GLOB, TBIL, CRE, CK, and SOD were significantly higher, while A/G ratio, Ca and P concentrations, ALP, and GPx activities were significantly lower in the farmed, compared to the wild-caught, turbot. The analysis of white blood cells points to significant differences in neutrophil percentage and N:L ratio, with higher values observed in wild population. Although lymphocytes and monocyte percentages were higher in the farmed group, the observed differences were insignificant.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Genes** & **Primers Sequence (5’-3’)** & **Size (bp)** & **Reaction Condition** \\ \hline s18 & FW: ACTGAGG
## 4 SLA Specification for the Fog Storage Services
### SLA Parameters  
SLA parameters, as already mentioned, are observable service properties that are used to define the SLOs. The SLA parameters are initially used as input parameters in the Pareto decision-making process to determine optimal storage nodes and then are continuously monitored during the runtime of the application. The selection of SLA parameters in this work is based on in-depth research undertaken by several H2020 research and innovation projects. The baseline information used for the selection of SLA parameters is based on:  
* Analysis of the various public Cloud providers and their currently offered SLA contracts (e.g., AWS S3 availability SLA ([[https://aws.amazon.com/s3/sla/](https://aws.amazon.com/s3/sla/)]([https://aws.amazon.com/s3/sla/](https://aws.amazon.com/s3/sla/)), accessed on 5 January 2022));
* Information gathered from a detailed analysis of the available literature related to SLA contracts for Cloud storage and wider SLAs related to Cloud computing (e.g., WSLA [38], CSLA [9], SYBL [47], Contrail [48] and SLA@SOI [49]);
* Analysis of the monitoring and control possibilities for SLA parameters, which can be implemented as a monitoring system.  
In this research, the following SLA parameters are chosen for Fog storage services: availability, throughput and cost. In the following paragraphs, each of the selected parameters is defined and described.
# Clustering-Based Data Dissemination Protocol Using the Path Similarity for Autonomous Vehicles
## 4 Results
### Cluster Robustness Evaluation  
The survivability of the cluster is confirmed as follows. At the first road in the lattice-shaped experimental environment, 5620 cars start simultaneously. It then stores the first connected cluster members and the number of cluster members that are disconnected each time they cross an intersection.  
The number of cluster members that have not been missed is then divided by the number of cluster members that were initially connected to each time they crossed the intersection. Because there are seven intersections in this experimental environment, we measure every seven iterations.  
The results are shown in Figure 19. The number of cluster members in the CPB decreased sharply in the experimental environment with many intersections. In contrast, the PCDP showed that the number of members consisted of the first members, even after the intersections were steadily maintained.  
Only 64.5% of the CPB maintained the first cluster on the entire network, even after the first iteration, and only 4.632% after the last iteration was the same as the first cluster member.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Variable** & **Value** & **Unit** \\ \hline Area Size & 36,000 & m\({}^{2}\) \\ Grid Size & 1000 & m\({}^{2}\) \\ Size of Grid & 6 \(\times\) 6 & \\ Maximum Speed & 80 & km/h \\ Number of Nodes Per Route & 5 & \\ Number of Routes & 924 & \\ Simulation Time & 18,000 & S \\ Bitrate & 6 & Mbps \\ Signal Strength & \(-\)20 & dBm \\ \hline \hline \end{tabular}
\end{table}
Table 2: Simulation Variables.  
Figure 19: Cumulative Survived Cluster Member Rate.  
However, the percentage of PCDP in the same cluster after the first iteration reached 92.5%, and 57.92% remained after the last iteration.