esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Results and Validation  
### Field Boundary Delineation  
Field boundary delineation has a great impact on further analysis. Two main causes of poor image segmentation are over-segmentation and under-segmentation. The cadastral data provided by land administration in Jiashan County is used as the reference boundary dataset to validate our field boundary delineation. A confusion matrix consisted of 10,000 samples, with 5000 edge samples selected randomly within 10 m of reference boundaries and 5000 non-edge samples randomly selected more than 10 m away from the reference boundaries. Accuracy metrics calculated from the confusion matrix are commission error (CE), omission error (OE), Kappa coefficient, and overall accuracy (OA). The OE indicates how well the extracted edges are in line with reference edge, and a high OE means under-segmentation. The CE measures false edges within fields, and a high OE means over-segmentation. Besides metrics obtained from the confusion matrix, the intersection over union (IoU) score is also used. IoU is a metric to quantify the percentage of overlap between the reference fields and our extracted fields (prediction), which is calculated as:  
\[\text{IoU}=\frac{\text{reference}\cap\text{prediction}}{\text{reference} \cup\text{prediction}}\]  
Figure 8: (**a**) is the distribution of stratified samples for points from the MCD12Q1 land cover map, farm POIs, and field photos; (**b**) is an example of a square AOI for one sample; (**c**) is an example of geo-referenced field photo acquired from (**d**) the site ([[http://www.eomf.ou.edu/photos/](http://www.eomf.ou.edu/photos/)]([http://www.eomf.ou.edu/photos/](http://www.eomf.ou.edu/photos/)) (accessed on 1 March 2021)).  
Accuracy metrics in Table 2 shows that the field boundary delineation achieves satisfying OA (0.898). The CE and OE are acceptable. Detailed inspections on the prediction results reveal that substantial OEs occur in edges between fields planted with the same crops with similar crop progress, and some CEs are contributed by linear features within the same fields (e.g., irrigation canals and ditches) which are not recorded in cadastral data. As such under-segmentation (the merge of rice fields with similar crop progress) and over-segmentation (caused by irrigation system) will not significantly obscure rice recognition, those fields in reference fields are correspondingly merged and split before calculating IoU score. The IoU score calculated using around four hundred randomly sampled reference fields is 0.718.
# Internet of Spacecraft for Multi-Planetary Defense and Prosperity
## 6 Conclusions  
In this paper, a comprehensive review of space exploration, space colonization, space threats, extinction events, space observatory, and space defense has been given, followed by a detailed presentation of related research and projects on milestones in human history. Furthermore, a summary and a prediction are made for humanity's future evolution path: terraforming other celestial bodies for extra-terrestrialization. As a result, multi-planet-based communications and defense networks will be critically necessary, and a framework named the Solar Communication and Defense Networks (SCADN) is proposed and analyzed. The distributed and intelligent features of the proposed SCADN framework can provide high reliability in coping with the potentially hazardous space objects in emergent situations and serve other purposes of space exploration and astronomical survey. Eventually, it is envisioned that founding such an enormous framework may require unprecedented resources and efforts across many nations and entities on a long-term basis for human living and prosperity. To utilize such a framework to serve the entire human race's common interest under international treaties, strict legislation, scientific implementation, and public supervision will play a crucial role.
## 4 Blockchain and Fog Based Architecture
### Data Transfer  
The target application such as SIoT, has a large amount of data to transfer and this size grows regularly at a fast pace. This also raises the requirement of network bandwidth, data storage, and processing speed. Data is transferred from local storage, web and IoT devices. Data manipulation is applied as per the protocol of the organization such as cleaning, filtering and integrating.  
Here, the cloud is employed at the last layer to process the metadata. The FN (an edge or dew computing) analyses the data and make metadata abstract. The proposed BFAN architecture enhances the mobility of IoE applications users with FN and dew computing, further security is provided through Blockchain, which disables the anonymous users' entry in the IoE devices. FN and dew computing provide the application services with the storage on the work for the IoE devices. The communication takes place in the following order:  
* The communication between the local devices with sensing and processing capability is known as primary or inter primary communication. These devices can be sensors, laptops, touch-screen devices and computers used for P2P communications. Wi-Fi is used to communicate between IoE devices, where the distance is medium. The inter primary communication takes place with ZigBee and Bluetooth, while the short distance uses TCP/IP medium for inter primary communications.
* The communication between dew computing and Fog Nodes takes place with wireless or wired media. The optic fiber, CAT-5/6 is used for TCP/IP for end-to-end connection.  
The local wireless connection is used to communicate inter primary and primary communication. There are direct and indirect connection types of communication. The direct hoping system is applied to communicate between FNs. This makes the proposed BFAN architecture minimize the latency rate.  
Multi-casting is supported for secondary communication. The characteristics of the communication system are described in Table 2. The inter primary and primary communication QoS improves with high-speed communication, with low latency. As compared to other communication systems, BFAN supports the applications of stream type/pervasive, heterogeneity with secondary connections.  
The storage devices, servers, and other components are shown in Figure 2. The fog components are connected with the particular server, as shown in Figure 3. The secondary and primary communication is isolated from each other as per the distance of components. The scalability of FNs can be grown or reduced. Primary communication is handled with the local connection while the secondary communication's responsibility is given to external connections. The t2t relationship is a subcategory of primary communication. Blockchain is used to authenticate and authorize the applications. IoE layer of BFAN over the safe communication path is used to avoid congestion. Similarly, this process is followed by for tFNt communication.
# Integrity Monitoring of GNSS Constellations with Only LEO-PNT Satellites +
## 3 User-Based Integrity with LEO-PNT Formulation (Option 2)
### LEO-PNT Error Budget  
The LEO-PNT's barrier performance relies on the quality of the MEO observables collected by the LEO satellites and the geometry that the LEO constellation provides to the user.  
Table 4 presents the LEO Equivalent Ranging Error (LERE) budget. The first two terms (A and B) are the LEO satellite's position and synchronization. The next two terms (C and D) are the phase and code noise for the iono-free combination. Finally, these terms are added quadratically to derive the phase and code LERE in rows E and F, respectively. The more conservative values in brackets are used in the simulations to account for some uncertainties not considered in this simple budget, such as multipath errors.
# Applying Vision-Based Pose Estimation in a Telerehabilitation Application
## 2 Materials and Methods
### ExerPlayer Module
#### 2.2.3 ExerPlayer Game Mode
For the placement of the targets in any of the four games, the therapist can select one of the predefined distributions for each game or can design a specific distribution for each prescribed session. After each game, a score is given so that the patient has immediate feedback about their performance. It is important to note that in game mode, the patient has greater freedom of movement and rather than perfectly repeat a certain movement, the idea is to foment the exercise of a certain part of the body.
## 4 Case Studies
### Three-Dimensional Point Cloud of San Nicola in Montedoro Church
#### 4.2.4 Photogrammetry of the Internal Part of the Structure Using a Fisheye Lens  
For the interior of the church, since there are also frescoes of great historical and cultural value and considering the rather restricted environment, a photogrammetric survey was carried out using a Nikon D5000 DSLR camera with a calibrated fisheye lens (focal length 10 mm). The fisheye is a wide-angle photographic lens that allows a wide scene to be observed. This type of lens has been used successfully in the photogrammetry field, as shown in [PERSON] and [PERSON], 2006 [22], especially in narrow spaces.  
Figure 5: Image acquisition by unmanned aerial vehicle (UAV): (**a**) Parrot Anafi and Parrot Sky-controller; (**b**) acquisition step; (**c**) an aerial image acquired by UAV platform.  
In self-calibration mode, the dataset of the 22 images was processed in Agisoft Metashape software. The total error, i.e., standard deviation evaluated on 6 GCPs, was 0.003 m.  
Considering the high value of the frescoes and the architecture of the small altars inside the structure, orthophotos of each single facade and floor were taken. In order to carry out this task, it was necessary to build a mesh of the interior of the structure. Subsequently, identifying the planes of the single facade, the orthophotos with a geometric resolution of 0.1 mm of the interior of the church were built (Figure 6).
# Antioxidant Properties of _Jatropha curcas_ L. Seed Shell and Kernel Extracts
## 1 Introduction  
Plant-derived bioactive compounds have received considerable attention because of their therapeutic potential as anti-inflammatory, anticancer, and antioxidant substances [1]. _Jatropha curcas_ L. is a tropical and subtropical plant that has multiple uses and considerable economic potential [2; 3; 4]. It belongs to the Euphorbiaceae family [5], whose aqueous and organic extracts have been traditionally used as laxatives, scavengers, emetics, and therapeutics [6]. Although _J. curcas_ is toxic, some of its parts are suitable for therapeutic uses [7]. For example, its root and latex, which contain phenolic and flavonoid compounds, exhibit notable antioxidant, antihypertensive, antiplatelet, and anti-inflammatory activities [8]. The methanolic extract of leaves has anticrustacean and antiviral activities [9]. The stem and root barks have antibacterial properties and can be a source of antibacterial compounds [10]. The root contains curcusone A-E [11], which can be used for the treatment of many diseases [12]. Curcusone A and B, which are found in the stem, have anticancer activity. Moreover, curcusone B effectively suppresses metastatic processes [12]. The main source of toxicity in seeds is the kernel [13]. However, no information exists regarding the toxicity of the seed shell.  
The seed extract of _J. curcas_ exhibits significant antioxidant activity, and the hydroalcoholic extract of _J. curcas_ exhibits potent activity for protecting against oxidant and free radical injuries [14]. The kernel of _J. curcas_ has a high total phenolic content and exhibits strong antioxidant activity [15]. The extract of _J. curcas_ seed shells has a high phenolic content and exhibits relatively strong bioactivity. _J. curcas_ seed shells are a new natural antioxidant source and can be used in the industry [16]. The kernels of _J. curcas_ contain nitrogen, phosphorous, and potassium and can be used as fertilizers [16; 17].  
To the best of our knowledge, the antioxidant capacity of _J. curcas_ seed shells and kernels has rarely been studied. Water, methanol, and ethanol are suitable extraction solvents for polyphenolic compounds to optimize the antioxidant capacity of _J. curcas_ seed shell and kernel extracts [18]. Studies have been conducted on different solvent extractions [16]; however, the differences in ethanol extraction at a series of concentration have been less studied. Therefore, this study investigated the in vitro antioxidant activity of the seed shell and kernel extracts of _J. curcas_ by using five types of ethanol solutions with different polarities.
## 4 Trends and Challenges
### Lunar and Deep Space Exploration  
China has made significant strides in SAR technology for deep space exploration, advancing from technical groundwork to engineering applications. In the upcoming Phase IV of the Lunar Exploration Program, the Chang'e-7 (CE-7) orbiter will be equipped with a Pol-SAR for the first time, focusing on high-resolution imaging and water ice detection in the lunar polar regions. By analyzing polarimetric scattering characteristics, this payload can penetrate permanently shadowed areas to retrieve terrain and material information, addressing a technological gap in China's deep space SAR capabilities and providing essential data for lunar resource exploration. In addition, the \"China Fuyan\" deep space radar system, developed by Beijing Institute of Technology, has entered its initial operational phase. The system consists of four distributed radar units, each with a 16 m aperture, and has successfully produced the first 3D radar image of a lunar impact crater, demonstrating the feasibility of distributed aperture radar imaging for deep space. By coordinating multiple small radar antennas, the system can actively image the Moon, near-Earth asteroids, and other planetary targets, enabling large-aperture observations of distant objects.  
China's deep space SAR research is expanding toward higher resolution, multi-platform coordination, and novel observation modes. The Pd-SAR system under development is expected to achieve 0.5 m resolution, enabling the detailed surface characterization of deep space targets. Proposed concepts such as the GCOLB-SAR system envision Earth observation from a stable lunar platform, offering ultra-wide swath coverage of up to 6500 km and providing a new paradigm for global change studies [125]. Concurrently, breakthroughs in multi-platform coordinated imaging and onboard real-time data processing are accelerating, addressing deep space data transmission bottlenecks and improving detection efficiency.  
These developments demonstrate that China is actively advancing SAR technologies through independent innovation, enabling key applications in lunar base construction, planetary geological research, and deep space resource exploration.
## 3 Calculation Results
### Parameters of the Neutron Source  
Estimates of the maximum neutron yield for the volumetric fusion neutron source in the DEMO-FNS project with 40 MW of fusion power [39, 40] give 1.42 \(\times\) 10\({}^{19}\) s\({}^{-1}\). At the same time, calculations by the ASTRA code did not provide [8, 13] such values for neutron power and yield. Calculations showed that, in the working window of densities and confinement parameters, the achievable fusion power is \(>\)35 MW, which is higher than calculated earlier (see Figure 13). The achievable power increases with increasing plasma density.  
It was already noted [13, 41] that the total fusion power \(P_{fus}\) is formed by the plasma-plasma and beam-target components and the ratio of these values depends substantially on the plasma and beam compositions. Since, to date, the most promising variant is that using the deuterium NBI, calculations were carried out for this. The obtained dependences of neutron yield \(S_{neut}\) on \(f_{core}\)\({}^{T}\) (see Figure 14) are in relatively good agreement with the earlier obtained results [13]. The maximum values of neutron flow can be obtained at \(f_{core}\)\({}^{T}\) = 0.7 for the D\({}^{0}\) beam. In the considered case with \(f_{core}\)\({}^{T}\) = 0.5, the neutron yield turns out to be approximately 10% lower than expected, similar to the total fusion power. The dependence of neutron yield \(S_{neut}\) on plasma parameters: density \(<\)\(n_{e}\)\(>\) and confinement parameter \(\tau_{p}\)\(/\)\(\tau_{E}\) is shown in Figure 13. It is seen that, in the considered working window, the values are quite uniform.
# Performance Analysis of D2D Communication with Retransmission Mechanism in Cellular Networks
###### Abstract  
In this paper, we focus on the performance analysis of device-to-device (D2D) underlay communication in cellular networks. First, we develop a spatiotemporal traffic model to model a retransmission mechanism for D2D underlay communication. The D2D users in backlogged statuses are modeled as a thinned Poisson point process (PPP). To capture the characteristics of sporadic wireless data generation and limited buffer, we adopt queuing theory to analyze the performance of dynamic traffic. Furthermore, a feedback queuing model is adopted to analyze the performance with retransmission strategy. With the consideration of interference and channel fading, the service probability of the queue departure process is determined by the received signal-to-interference-plus-noise ratio (SINR). Then, the embedded Markov chain is employed to depict the queuing status in the D2D user buffer. We compute its steady-state distribution and derive the closed-form expressions of performance metrics, namely the average queue length, average throughput, average delay, and dropping probability. Simulation results show the validity and rationality of the theoretical analysis with different channel parameters and D2D densities. In addition, the simulation explores the dropping probability of a D2D user with and without the retransmission strategy for different D2D links in the system. When the arrival rate is comparatively high, the optimal throughput is reached after fewer retransmission attempts as a result of the limited buffer.  
device-to-device (D2D) communication; spatiotemporal model; feedback queuing model; embedded Markov chain +
Footnote †: journal: Applied Soft
## 3 Methodology
### Sizing Analysis  
The size of heat exchangers is determined by calculating the \(UA\) coefficient, which is related to investment, operating, and maintenance costs [11]. Due to the significant variation in the thermodynamic properties of S-CO\({}_{2}\), it is important to divide the heat exchanger into \(N\) layers to calculate the \(UA\) coefficient accurately. The \(UA\) is calculated for the pre-cooler, low-temperature recuperator, high-temperature recuperator, and intermediate heat exchanger.  
The size parameter (\(SP\)) is used to estimate the dimensions and associated costs of the turbo components [27]. The equations pertaining to the size parameter for the turbine, main compressor and recompression compressors, respectively, are represented by Equations (12)-(14).  
\[SP_{T}=\frac{\sqrt{\dot{m}_{\text{CO}_{2}}v_{3s}}}{\sqrt[4]{h_{2}-h_{3s}}} \tag{12}\]  
\[SP_{MC}=\frac{\sqrt{\dot{m}_{\text{CO}_{2}}(1-SR)v_{6}}}{\sqrt[4]{h_{7s}-h_{6}}} \tag{13}\]  
\[SP_{RC}=\frac{\sqrt{\dot{m}_{\text{CO}_{2}}SRv_{5}}}{\sqrt[4]{h_{9s}-h_{5}}} \tag{14}\]  
Storage tanks are the main component of the thermal energy storage. The volume of the storage system in the literature [3] is often associated with the temperature difference of the heat transfer fluid (HTF) between the inlet and outlet of the solar receiver. In this study, the volume required to store the thermal energy needed by the power block for one hour is used as a representative parameter for the size of the storage system. This approach will also account for the different densities and the specific heat capacities of both types of molten salts. The volume of the storage tanks required for the cycle to operate at full load for one hour is expressed by Equation (15).  
\[V_{HTF}=\frac{\dot{m}_{HTF}\cdot 3600}{\dot{\rho}_{HTF}(T_{hot})+\dot{\rho}_{HTF} (T_{cold})} \tag{15}\]  
where \(\dot{\rho}_{HTF}(T_{cold})\) is the density of the molten salts at the temperature of the cold tank and \(\dot{\rho}_{HTF}(T_{hot})\) is the density of the molten salts at the temperature of the hot tank. Since it is assumed that the tank's heat losses are negligible, both temperatures coincide with the inlet and outlet temperatures of the solar receiver.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Component** & **Fuel Exergy** & **Product Exergy** \\ \hline Solar system & \(\dot{E}x_{s}\) & \(\dot{E}x_{13}-\dot{E}x_{14}\) \\ IHE & \(\dot{E}x_{13}-\dot{E}x_{14}\) & \(\dot{E}x_{2}-\dot{E}x_{1}\) \\ T & \(\dot{E}x_{2}-\dot{E}x_{3}\) & \(\dot{W}_{T}\) \\ HTR & \(\dot{E}x_{3}-\dot{E}x_{4}\) & \(\dot{E}x_{1}-\dot{E}x_{10}\) \\ LTR & \(\dot{E}x_{4}-\dot{E}x_{5}\) & \(\dot{E}x_{8}-\dot{E}x_{7}\) \\ RC & \(-\dot{W}_{RC}\) & \(\dot{E}x_{9}-\dot{E}x_{5}\) \\ MC & \(-\dot{W}_{MC}\) & \(\dot{E}x_{7}-\dot{E}x_{6}\) \\ PC & \(\dot{E}x_{5}-\dot{E}x_{6}\) & \(\dot{E}x_{12}-\dot{E}x_{11}\) \\ M & \(\dot{E}x_{8}+\dot{E}x_{9}\) & \(\dot{E}x_{10}\) \\ \hline \hline \end{tabular}
\end{table}
Table 5: Exergy rate of fuel and product definition for each component.
# Predicting Freeway Travel Time Using Multiple-Source Heterogeneous Data Integration
## Data Collection and Preprocessing  
### Data Description  
Data for this study was collected from Freeway G5513 that runs from Changsha to Yiyang, Hunan Province, starting from the Changsha toll station and ending at Yiyang toll station. This is a standard freeway with a two-way four lane speed of 100 km/h and a roadbed width of 26 m. The total length is approximately 63 km, the daily average flow reached 58,000 vehicles, and the peak flow during holiday or festival was up to 96,600 vehicles. Because of heavy traffic, the freeway has been rated as one of the six most congested sections in the Hunan Province. There are nine toll stations along the road, from east to west, which are Changsha West, Youren, Guanshan, Jinzhou, Ningxiang, Xiangjiang West, Quanjiao, Chaoyang, and YiyangNorth, illustrated in Figure 1.  
The main data set collected in this study includes:  
* Toll data of all toll stations along G5513 in February 2018 (vehicles entering and leaving toll station), with a total of 561,081 data items, including the name of the toll station, the time of vehicle entering and leaving the toll station, vehicle type and weight.
* Weather data of Meteorology monitoring stations, which was collected from the Chinese Weather Network in February 2018, with a total of 672 data items, including 24 h daily weather, temperature, relative humidity, precipitation, and wind direction.
* Freeway blockage record statistics, which was obtained from the freeway's management department, a total of 260 freeway blockage information reports were collected in February, March, April, and May, including blockage location, reasons for the blockage, blockage start time, and blockage end time.
* Freeway traffic control measures report, which was obtained from the Traffic Police Department, with a total of seven data items collected on 5 April Qingming Traditional National Festival, May 1 International Labor Day, and other holiday control information.