esa-sceva/satcom-chunk-collection huggingface dataset:
# Advanced and Potential Methods for Extraction of Bioactive Compounds from Avocado Peel--A Review
## 4 Advanced Methods for Extraction of Bioactive Compounds from Avocado Peel
### Natural Deep Eutectic Solvents (NaDESs) Extraction  
Deep eutectic solvents (DESs) are an extraction method that increasingly uses solvents as a greener alternative to ionic liquids. DESs are solvents formed by mixing two or more compounds at an exact ratio corresponding to the eutectic point [44]. NaDES deserves special attention because of its characteristics, which make it very promising for future applications. Recently, NaDES has been identified as an ecological and green solvent that has attracted significant attention from the scientific community. NaDES has several beneficial physicochemical properties, including a liquid state across a wide temperature range, low volatility, chemical and thermal stability, nonflammability, and nontoxicity of constituent elements [45]. In addition, NaDES solvents are widely available in nature, easy to obtain, and renewable [46]. Furthermore, NaDES is made up of non-toxic ingredients that are found naturally in foods and can be employed directly in food compositions. The solvent purification phase is not required after the extraction process, and the extract can be used directly in food-grade applications, lowering production costs compared to the standard organic solvent extraction procedure [45]. Nevertheless, a disadvantage of NaDESs compared to standard organic or aqueous solvents is that NaDESs have relatively high viscosity. The high viscosity of NADESs would make extracting food extremely challenging. The difficulty, however, has been handled; it has been shown that adding water to NaDESs can reduce its viscosity [47]. This approach makes applying this technology in the industry more feasible. [PERSON] et al. [48] reported that NaDES has been successfully used to extract bioactive phenolic compounds from avocado peels. From five selected DESs, it was found that the best extraction results were obtained with choline chloride-acetic acid and -lactic acid, the extraction efficiency of which was higher than that of ethanol. The avocado peel extract obtained by NaDES exhibited high antioxidant and antimicrobial activity, particularly against _Staphylococcus aureus_, _Streptococcus dysgalacticiae_, _Escherichia coli_, and Pseudomonas putida.
## 5 Results and Discussions
### Comparative Analysis of Unknown Objects  
The CeRDE approach has the fastest performance, with values for the five objects ranging from 1.735 ms (truck) to 1.807 ms (bicycle), as shown in Figure 29. In comparison, the PbyP and proposed CoRDE approaches take considerably longer. GCRDE proposed another approach, showing moderate times with values from 4.43 ms (bicycle) to 27.64 ms (car). In summary, the CeRDE approach is significantly faster compared to the proposed approaches.  
PbyP offers varying levels of accuracy across objects, with the highest accuracy for person (96.59%) and the lowest for truck (2.21%), as shown in Figure 30. The accuracy of CoRDE is generally lower than that of PbyP, with its highest accuracy for person (88.83%) and the lowest for Truck (1.85%). On the other hand, CeRDE achieves impressive accuracy for person (93.88%) and car (93.97%), making it a more accurate method overall, especially for specific objects like person and car. GCRDE performs quite well, indicating that it is the best-performing method for certain cases. Overall, CeRDE and GCRDE provide higher accuracy than PbyP, but the performance varies across different objects.  
The PbyP approach shows relatively high RMSE values, ranging from 1.60 m (person) to 18.237 m (bus), which indicates less precision in depth extraction. CoRDE has worse RMSE values than other approaches, ranging from 1.785 m (person) to 18.328 m (bus). However, CeRDE shows a substantial improvement in precision, with RMSE values ranging from 1.116 m (bus) to 6.892 m (truck), highlighting its superior performance in terms of  
Figure 28: This comparison shows depth extraction RMSE (in meters) at occlusion Levels 2 for the traditional approach: PbyP (Point-by-Point) and our proposed approaches: CoRDE (Complete Region Depth Extraction), CeRDE (Central Region Depth Extraction), and GCRDE (Grid Central Region Depth Extraction).  
Figure 29: This comparison shows mean depth extraction time (in milliseconds) at occlusion Levels 3 for the traditional approach: PbyP (Point-by-Point) and our proposed approaches: CoRDE (Complete Region Depth Extraction), CeRDE (Central Region Depth Extraction), and GCRDE (Grid Central Region Depth Extraction).  
depth accuracy. GCRDE, with RMSE values ranging from 1.392 m (bus) to 7.481 (car), also offers lower RMSE than PbyP and CoRDE, making it a promising approach for better depth precision. CeRDE emerges as the most precise method in this analysis, particularly for objects, where its RMSE is significantly lower than other methods, as shown in Figure 31.  
In conclusion, the CeRDE approach is the fastest and offers very good accuracy and precision. The GCRDE method strikes a balance between speed, accuracy, and precision, offering moderate performance across all three aspects. The PbyP method, while faster and more accurate than CoRDE, does not consistently outperform CoRDE in terms of RMSE. Based on the analysis, GCRDE and CeRDE are the most promising methods for applications requiring high accuracy and precision, while CeRDE is suitable for situations where speed is the primary concern.
## 3 Web3 and Metaverse
### Appropriate Translation and Continuous Synchronization to the Real World
#### 3.3.1 Spatial Computing  
The ability to map and understand physical space and objects in the real world is called spatial computing [61]. In the context of Web3, spatial computing can be used to create decentralized and immersive virtual experiences that can be accessed through theWeb3 ecosystem. AR (Augmented Reality) and MR (Mixed Reality) are technologies that could be used for a variety of purposes, such as an object or facial recognition, plane detection, and movement tracking. An example is doctors using such technologies in environments such as digital operation theatres, where everyone can watch live patient medical operations [14]. According to many sources [62; 63; 64], the following are the key technology elements in spatial computing in Web3:  
* Augmented Reality (AR): AR technology allows users to overlay digital information and objects onto the real world, creating a more immersive and interactive experience.
* 3D modeling and mapping: 3D modeling and mapping technologies are used to create detailed and realistic virtual environments that can be accessed through Web3.
* Location-based services: Location-based services can be used to provide contextually relevant information and experiences to users based on their physical location.
* Edge computing: Edge computing allows for the processing and storage of data closer to the point of user interaction, reducing latency and increasing the responsiveness of spatial computing applications.
* 6G wireless communications: 6G wireless communications technology enables faster and more reliable data transfer, which is necessary for the real-time interactions that are required for spatial computing applications.
## 2 Methods
### Computational Complexity
#### 2.5.2 Space Complexity Analysis  
At the beginning of the algorithm, it needs to be in free space \(X_{free}\). Generate a set of sample points internally. Each sample point needs to store its coordinates in space, which is usually proportional to the dimension (d) of the problem. Therefore, the space required to store all sample points is \(O(nd)\). However, when analyzing the overall spatial complexity, it is common to consider (d) as a constant, thus simplifying the spatial complexity of sample point storage \(O(n)\). The FMT algorithm constructs a path by checking the potential connections between sample points, which requires storing connection information between point pairs. In the worst-case scenario, if each point is connected to all other points, the number of connections may be close to \(O(n^{2})\). However, due to the fact that the FMT algorithm uses a radius-based neighborhood search, not all pairs of points will form a connection, which determines whether points can be connected. In fact, as the number of sample points increases, the average number of connections at each point is influenced by the choice of connection radius, but it does not increase in a square relationship with the number of points. The spatial complexity of improving FMT* satisfies Equation (20):  
\[O(n)<O<O(n^{2}) \tag{20}\]
## 5 Clinical Applications
### Functional Cine Imaging  
Since the FRF is fully motion-resolved in both the cardiac and respiratory dimensions, 3D images of every cardiac phase or respiratory motion state can be reconstructed. Typically, the cardiac cycle is segmented into cardiac phases with a 50 ms bin width, while the respiratory motion is divided into four motion states. However, the FRF with its CS reconstruction has the capability of retrospectively and flexibly selecting the temporal resolution for image reconstruction. After reconstructing a static 3D image for each cardiac phase and motion state, multiple static 3D images can be played after each other to create a 3D cine image (i.e., x-y-z-cardiac). Although this can be performed in both the cardiac and respiratory dimensions, the former is mostly used and widely recognized as cardiac cine imaging for the assessment of cardiac volumes and function. Given these powerful capabilities of the FRF, anatomical imaging, coronary angiography, and cardiac cine imaging can all be performed using a single MRI acquisition of 5-10 min, depending on the required spatial resolution, without ECG and during free-breathing.  
Recent work, although unpublished yet, focussed on how much the acquisition time for cardiac cine imaging using the FRF could be shortened while still obtaining comparable cardiac volumes and ejection fraction compared to reference standard 2D breath-hold cine imaging. When comparing acquisition durations between 1 and 6 min, durations as short as  
Figure 6: Panel (**A**) Diastolic and systolic coronary reformats of paediatric patients after ferumoxytol injection under general anaesthesia and intubation, and under sedation and free-breathing. Data were collected using the 5D free-running framework. The orange arrowheads indicate the right coronary artery (RCA), while the blue arrowheads indicate the left main (LM) and left anterior descending (LAD) coronary arteries. It can be observed that image quality and vessel conspicuity appear similar in the two indicated cardiac phases, as well as that image quality is comparable between intubated and free-breathing subjects. Panel (**B**) Coronary reformats for three intubated and one free-breathing paediatric subjects for simultaneous visualisation of the RCA cesium (orange arrowheads) and LM artery ostium (blue arrowheads). The arrowheads with a red glow highlight anomalous coronary vessel anatomy. Figure created using the original source images by [PERSON] et al. [29] with author permission.  
1 min still led to comparable quantitative measures, albeit with significantly noisier images and therefore lower observer confidence (Figure 7). These results underline the importance of focusing on improving efficiency and obtaining comparable clinical measures, instead of only striving for the highest image quality. The FRF therefore holds promise as an alternative to standard 2D cine imaging to improve workflow efficiency, simplicity, and patient comfort.
# Comparative Study on Vibration Characteristics of Biaxial Carbon/Glass Hybrid Wind Turbine Blades
## 2 Research Theory
### Modal Analysis  
The overall dynamic balance equation of a free vibration structure is as follows:  
\[[M]\big{\{}\ddot{u}\big{\}}+[C]\big{\{}\ddot{u}\big{\}}+[K]\big{\{}u\big{\}}=0 \tag{16}\]  
where \([M]\) is the mass matrix, \(\big{\{}\ddot{u}\big{\}}\) is the node acceleration vector, \([C]\) is the damping matrix, \(\big{\{}\dot{u}\big{\}}\) is the node velocity vector, \([K]\) is the Stiffness matrix, and \(\big{\{}u\big{\}}\) is the node displacement vector.  
The modal analysis under the action of no damping or external force can be changed from the above equation as follows:  
\[[M]\big{\{}\ddot{u}\big{\}}+[K]\big{\{}u\big{\}}=0. \tag{17}\]  
For a linear system:  
\[\{u\}=\big{\{}\phi\big{\}}_{i}\cos w_{i}t. \tag{18}\]  
In the formula, \(\big{\{}u\big{\}}\) is the vibration mode eigenvector corresponding to the i-th mode, \(\big{\{}\phi\big{\}}_{i}\) is the natural frequency of the i-th mode, and \(t\) is time.  
Substituting Equation (7) into Equation (6) yields  
\[([K]-[M]w_{i}^{2})\big{\{}\phi\big{\}}_{i}=0 \tag{19}\]where \(w_{i}\) is the vibration frequency, \(\{\phi\}\) is the modal shape, and \([K]\) is the stiffness matrix.  
In modal analysis, the size of the stiffness matrix \([K]\) is related to the elastic modulus and Poisson's ratio of the structure, while the size of the mass matrix depends on the density of the structure. Therefore, just knowing the elastic modulus, Poisson's ratio and density of the structure, we can build constant stiffness matrix \([K]\) and mass matrix, and calculate the modal frequency and mode shape of the structure.
###### Abstract  
A timing recovery algorithm is introduced that operates with less than two samples per symbol and provides an enormous complexity reduction. The complexity reduction is due to a synergy with the already existing Fourier transforms in a coherent receiver, an avoidance of terms that are dominated by noise, and a complete elimination of multiplications. A simulation and an experiment with a single carrier modulation format show that the inherent timing jitter is, despite of the significant complexity reduction, comparable with the state of the art, and in particular outperforms the Godard algorithm for low roll-off factors. In addition, it is one of the few algorithms that operates with less than two samples per symbol in the frequency domain, and thus enables the lowest complexity in a receiver.  
Keywords:optical communication; timing recovery; sampling phase estimation; field-programmable gate array (FPGA)-based real-time processing +
Footnote †: journal: Applied Sciences
## 4 Simulation Results and Discussion
### Effectiveness of the Proposed Control Scheme under DoS Attacks  
To validate the performance of the proposed secondary control scheme under DoS attacks, the communication link between DG1 and DG4 is supposed to be subject to the attacks after \(t=1\) s. The simulation results are illustrated in Figures 11-13.  
Figure 11: Performance of the proposed control scheme under DoS attacks: (**a**) DG output voltages; (**b**) evolution of the estimated average value of voltage \(V^{AVE}\);(**c**) DG output reactive power; (**d**) evolution of the estimated average value of reactive power \(Q^{AVE}\).  
Figure 10: Performance of the proposed control scheme under plug-and-play operation: (**a**) DG output voltages; (**b**) evolution of the estimated average value of voltage \(V^{AVE}\); (**c**) DG output reactive power; (**d**) evolution of the estimated average value of reactive power \(Q^{AVE}\).  
The simulation results in Figure 11 show that the proposed secondary control scheme is able to accurately estimate the average value of voltage and reactive power of overall DGs under DoS attacks, hence achieving the control objectives of voltage restoration and reactive power sharing. Compared with Figure 6, it can be known that DoS attacks weaken the control functions of each agent which increases the convergence time of the proposed strategy. Figure 12 shows that the DoS attacks can block the data transmissions on the communication link between DG1 and DG4. At the triggering time instants, communication attempts between agents are denied by the attack, which leads to the changes of the control inputs for \(V^{AVE}\) and \(Q^{AVE}\). Figure 13 illustrates the triggering time instants of DG1 and DG4 under DoS attacks. When DoS attack shifts to a sleep period, the ACK-based monitoring mechanism can detect that the communication link returns to normal, thus the successful communication attempt can be achieved. Our method ensures the immediate update of the control signals and consensus can be ultimately reached. It can be concluded that the control objectives of voltage restoration and reactive power sharing can still be implemented even under DoS attacks.
## 6 Safety Mechanisms Enabled by AI Agents
### Fault Detection and Predictive Maintenance  
Maintaining operational integrity in autonomous maritime systems requires the early identification of malfunctions before they escalate into critical failures. In this context, AI  
Figure 4: AI-Driven collision avoidance process (own elaboration).  
agents serve as proactive guardians of vessel health, detecting anomalies, diagnosing faults, and initiating corrective measures in real time.  
Using unsupervised learning techniques such as clustering algorithms, autoencoders, and statistical thresholding, AI agents continuously monitor vast streams of sensor data from propulsion systems, engine temperatures, fuel flow, steering angles, and more [111]. They create dynamic baselines for \"normal\" operational behavior and immediately flag deviations that could indicate mechanical issues, sensor degradation, or external interferences.  
For instance, a gradual increase in engine vibration detected during long-haul navigation might not trigger immediate alarms. However, the AI agent--trained on historical vibration profiles--identifies this as a precursor to potential bearing failure. It not only logs the anomaly but recommends maintenance within 72 h, avoiding costly emergency repairs.  
Beyond anomaly detection, AI agents are empowered with diagnostic reasoning capabilities. Through decision trees, Bayesian networks, or neural-symbolic hybrid models, they can identify root causes, suggest mitigation plans, and even initiate predefined failover actions, such as switching to redundant systems or reducing engine load to prevent escalation [112].  
This functionality extends into predictive maintenance, where historical trends and real-time telemetry are used to forecast failures before they happen. The agent analyzes wear patterns, operation hours, and micro-anomalies to optimize maintenance windows, balancing safety with fuel use, component lifespan, and mission schedules.  
In this sense, the agent acts as both a mechanic and a risk manager, preserving operational continuity while reducing unscheduled downtime and maintenance costs.  
Crucially, this proactive safety logic often operates in the background, with human operators only alerted when human intervention is needed. Unlike conventional maintenance protocols, which rely on fixed schedules or reactive repairs, maritime AI agents support a shift toward resilient, data-driven vessel management, which is especially important for long voyages without immediate access to port services.
# Remote Sensing Analysis of Geologic Hazards
## 5 Volcanoes  
The work of [PERSON] and [PERSON] [37] concerned the mapping of lava and ash deposits using PlanetScope optical images. This study introduced an object-oriented classification for mapping lava flows in vegetated and unvegetated areas during several eruptive phases of three Indonesian volcanoes. A change detection investigation was combined with the analysis of variations in texture and brightness, with hydrological runoff modelling and with analysis of thermal anomalies derived from Sentinel-2 or Landsat-8. The results showed good agreement with the reports of the Global Volcanism Program and showed the benefits of PlanetScope images for volcano daily monitoring and eruption risk assessment.
# Secure Aviation Control through a Streamlined ADS-B Perception System
## 5 Analysis and Discussion
### Discussion  
The study's primary goal is to identify binary classification to detect injected ADS-B messages and try to counter path modification, ghost aircraft injection, and velocity drift attacks. By identifying the sort of assault that was launched, we can better prepare our  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**RFC** & **MLPC** & **kNN** \\ \hline \hline \multicolumn{4}{c}{A training set of 10\% of the dataset} \\ \hline Accuracy & 98.18\% & 93.87\% & 84.25\% \\ Precision & 97.94\% & 93.10\% & 82.84\% \\ Recall & 97.65\% & 93.48\% & 85.21\% \\ F1-Score & 97.79\% & 93.29\% & 83.42\% \\ MCC & 0.970 & 0.902 & 0.762 \\ \hline \hline \end{tabular}
\end{table}
Table 8: Performance of the top three ML models.  
defenses. Below is a full examination of the findings using the proposed model compared to the related literature.
* The authors in [4] used radio frequency transmitters to attack ADS-B communication channels. They used 36 different ADS-B in message configurations (13 hardware devices and 22 software). They attacked them using BladeRF and HackRF as attacking devices. They achieved 90% accuracy in detecting spoofed messages and showed that their method could help distinguish the different ADS-B messages.
* [PERSON] et al. [21] proposed a detection model that detects malicious messages by fingerprinting wireless radio signals. Still, even though their proposed method is unfamiliar, only 50 percent of the malicious signals were detected.
* The authors of [38] proposed employing multiple variants of the SVM algorithm to detect and classify attacks on ADS-B messages and then compare the results. They produced the dataset used to test our proposed model.
* [PERSON] et al. [39] proposed a model utilizing supervised deep learning to detect attacks on ADS-B messages using a fake data generator.  
Now, after showcasing the results of the proposed system with a set of different attributes, we produced the following table, Table 6, which compares the proposed model with other existing models in a similar study field. Table 9 compares other state-of-the-art models. The comparison was based on the following performance factors: analysis algorithm, accuracy, F1-score, and Matthews correlation coefficient (MCC).  
Our results show that it is possible to build precise detection models for this kind of data that can operate across various stages of the life cycle of these messages by relying on the analysis of transmitted signals. The suggested detection model outperformed the majority of those in the literature in terms of results. This section reviewed the experiment results, evaluated the suggested approach, and compared the output with previous pioneering work in this field. The experimental results are outstanding and impactful in the field. However, further improvements can be made to improve the quality of these results.