esa-sceva/satcom-chunk-collection huggingface dataset:
# Passive Microwave Imagers, Their Applications, and Benefits: A Review
## 2 PMWI Applications and Impact Areas
### Applications and Benefits of PMWIs
#### 2.1.6 Sea Surface
Another example of using microwaves to retrieve sea surface parameters is the Compact Ocean Wind Vector Radiometer (COWVR) instrument. The primary goal of COWVR was to assess the performance of its simpler sensor design compared to more complex instruments like WindSat and determine whether this simplified design could match WindSat's wind vector performance [97]. In a comparison, [PERSON] et al. evaluated WindSat and COWVR across their shared channels and concluded that both instruments demonstrate a strong wind direction signal, enabling COWVR data to retrieve Ocean Surface Vector Winds (OSVWs) with accuracy comparable to WindSat. Moreover, they reported that COWVR shows greater sensitivity to wind direction at wind speeds exceeding 14 m/s. However, it should be noted that the authors conducted an indirect comparison between WindSat and COWVR data, as COWVR was launched a year after WindSat's operation ended [98]. Beyond wind direction and speed retrievals, COWVR data have also been successfully combined with TEMPEST Tb into the NRL Ocean Surface Flux System (NFLUX) to produce swath-level ocean surface air temperature and specific humidity for clear and cloudy conditions [97].
# Assessing the Added Value of Sentinel-1 PolSAR Data for Crop Classification
## 2 Materials  
### Study Area  
The study area extends across a small agricultural area of the Navarre district, located in the northeastern part of Spain (Figure 1). The area of interest surrounds the city of Pamblona, the capital of Navarre, and occupies approximately 215 km\({}^{2}\) that comprises 12,329 crop fields. Navarre's province is covered by irrigated valleys and forested mountains, with its northern part being dominated by the Pyrenees mountain range. The agricultural zone of interest is characterised by significant fragmentation, resulting in lower yields compared to the rest of the country [95]. At the same time, the rates of artificial fertilizers' use in the region exceeds the national average rate [95]. The 10 most dominant crop types of the area were taken into account: soft wheat, barley, oats, rapeseed, shrub grass, sunflower, maize, broad beans, vineyards, and cherry trees. The average area of a field was approximately 2 ha.
# Experimental Investigation on Jet Vector Deflection Jumping Phenomenon of Coanda Effect Nozzle
## 2 Experimental Setup and Methods
### Dynamic Mode Decomposition  
For the flow field change information \(\{\mathbf{u}_{1}\), \(\mathbf{u}_{2}\),..., \(\mathbf{u}_{N}\}\), it was assumed that there was a matrix \(\mathbf{A}\), so that there was a linear transformation relationship between adjacent time layers:  
\[\mathbf{u}_{i+1}=\mathbf{A}\mathbf{u}_{i} \tag{8}\]  
Definitions \(\mathbf{\psi}_{0}=\{\mathbf{u}_{1}\), \(\mathbf{u}_{2}\),..., \(\mathbf{u}_{N-1}\}\) and \(\mathbf{\psi}_{1}=\{\mathbf{u}_{2}\), \(\mathbf{u}_{3}\),..., \(\mathbf{u}_{N}\}\) could give the following relation:  
\[\mathbf{\psi}_{1}=\mathbf{A}\mathbf{\psi}_{0}=[\mathbf{A}\mathbf{u}_{1},\mathbf{A}\mathbf{u}_{2},\ldots, \mathbf{A}\mathbf{u}_{N-1}] \tag{9}\]  
For finding matrix \(\mathbf{A}\), DMD used a low\(-\)dimensional optimal approximation matrix \(\tilde{\mathbf{A}}\) to replace \(\mathbf{A}\). Solving \(\tilde{\mathbf{A}}\) required a singular value decomposition of \(\mathbf{\psi}_{0}\):  
\[\mathbf{\psi}_{0}=\mathbf{U}\mathbf{\Sigma}\mathbf{W}^{H} \tag{10}\]  
where \(\mathbf{U}\) was a left orthogonal matrix, \(\mathbf{\Sigma}\) was a singular value diagonal matrix, \(\mathbf{W}\) was a right orthogonal matrix, and H was a complex conjugate transpose [25]. The approximation matrix could be expressed as:  
\[\widetilde{\mathbf{A}}=\mathbf{U}^{H}\mathbf{\psi}_{1}\mathbf{W}\mathbf{\Sigma}^{-1} \tag{11}\]  
The next step involved finding the eigenvalue \(\tilde{\mathbf{A}}\mathbf{\Lambda}_{j}=\lambda_{j}\mathbf{\Lambda}_{j}\) for \(\tilde{\mathbf{A}}\), where \(\mathbf{\Lambda}_{j}\) was the eigenvector corresponding to the eigenvalue \(\lambda_{j}\). Where DMD mode was \(\mathbf{\Phi}_{j}=\mathbf{U}\mathbf{\Lambda}_{j}\), the mode amplitude was \(\alpha_{j}=\mathbf{\Lambda}_{j}{}^{-1}\mathbf{U}^{H}\mathbf{u}_{1}\), and the mode growth rate was \(g_{j}=\text{Re}[\text{ln}\lambda_{j}/\Delta t]\). The reconstructed flow field could be expressed as:  
\[\mathbf{u}_{j}\approx\sum_{i=1}^{N}\mathbf{\phi}_{i}(\lambda_{i})^{j-1}\alpha_{i} \tag{12}\]  
where \((\lambda_{i})^{j-1}\alpha_{i}\) was the modal coefficient.  
The residual corresponding to the maximum difference between the sample data matrix \(A\) and the reconstructed data matrix \(A^{\prime}\) was:  
\[R=\max_{\begin{array}{c}1\leq i\leq n\\ 1\leq j\leq m\end{array}}\left|A_{i,j}-A^{\prime}_{i,j}\right| \tag{13}\]  
In which \(A_{i,j}\) and \(A^{\prime}_{i,j}\) were the elements of the \(A\) and \(A^{\prime}\) matrices, respectively [28, 29].
# Bayesian Filtering Multi-Baseline Phase Unwrapping Method Based on a Two-Stage Programming Approach
## 1 Introduction
[PERSON] and [PERSON] [25] proposed Kalman filtering to solve the problem of PU for the first time. The Kalman filter PU method has attracted wide attention because of its better noise robustness. [PERSON] et al. [26] proposed an extended Kalman filter (EKF) PU method. [PERSON] [27] introduced a particle filter (PF) to the PU method. [PERSON] [28] proposed a cubature Kalman filter (CKF) PU method. The Bayesian filtering PU methods are not only applied in the SBPU method but also in MBPU methods. For example, [PERSON] [25] presented an MBPU method based on 3-D Kalman filtering. [PERSON] [29] proposed an extended particle filtering (EPF) MBPU algorithm based on an amended matrix pencil model and quantized path-following strategy. However, these Bayesian filtering MBPU methods start at the shortest baseline and proceed to longer and longer baselines. Strictly speaking, these methods do not completely eliminate the limitation of the PCA. [PERSON] [30] proposed a refined TSPA of PU for MB InSAR data using the unscented Kalman filter (TSPAUKF). This method uses the first step of TSPA for gradient estimation, so that TSPAUKF PU can completely get rid of the limitations of the PCA. In this paper, three MBPU methods base on TSPA with better noise robustness are proposed. This paper transplantsEKF, CKF, and an unscented information filter (UIF) to the MBPU domain. More meaningfully, based on these methods, we propose a framework of Bayesian filtering MBPU methods based on TSPA. The framework of the MBPU method proposes a gradient estimation method based on TSPA, and uses median filtering method to slightly filter the estimated phase gradients. Finally, the Bayesian filtering method unwraps the pixels, one by one, using an effective quality map based on heapsort. In this paper, we use several sets of simulated data and real data experimental analysis. The results show that the TSPA-based Bayesian filtering methods have better noise robustness, and the framework provides a basis for the introduction of other Bayesian filtering methods to the MBPU method. The rest of this paper is organized as follows. In Section 2, the MBPU theory and phase gradient estimation method are provided. In Section 3, several TSPA-based Bayesian filtering methods are introduced. In Section 4, we compare and analyze TSPA and TSPA-based Bayesian filtering methods through experiments. A summary and conclusions are provided in Section 5.
## 4 Discussion  
The proposed metasurface is highly efficient for harvesting EM energy in the Wireless Local Area Network (WLAN) band. The simulated and experimental results show that the metasurface has the properties of polarization insensitivity and high efficiency over a wide range of incidence angles. With square-shaped metal via rings around the unit cell and one harvesting via near the center, this metasurface solves the problem of operation frequency shifts of the maximum efficiency when the incidence angle increases. This metasurface can harvest energy with a higher efficiency over an oblique incidence in both TE and TM polarizations. This work still maintains limitations in that the efficiency decreases unequally for TE and TM polarizations when the incidence angle increases,  
Figure 11: Measured harvesting efficiency at different incidence angles for (**a**) TE and (**b**) TM polarized incident waves.  
which could be solved in future work. Nevertheless, the metasurface can efficiently harvest complex environmental EM energy, and it is expected to be applied in wireless energy charging for low-power electronic devices.  
Conceptualization, F.Y.; methodology, F.Y. and G.-Q.H.; validation, F.Y.; formal analysis, F.Y.; investigation, F.Y. and G.-Q.H.; writing-original draft preparation, F.Y.; writing-review and editing, F.Y., X.-X.Y., J.D., S.G. and G.-Q.H.; supervision, X.-X.Y.; funding acquisition, X.-X.Y. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China, grant number 61931009.  
The authors declare no conflict of interest.
## 4 Multihoming and Interworking
### Issues with Classic IPv6 Nodes  
As explained in Section 3.2, transport layer protocols use source and destination IP addresses including port numbers to map packets to flows. Moreover, bidirectional transport protocols or applications expect that packets flowing in the reverse direction (responses) have just interchanged source and destination IP addresses relative to packets flowing in the forward direction (requests) because receivers just swap these addresses when responding. In case of multihoming, this property can be  
Figure 7: A malicious GLI-gateway sends spoofed mobility update messages to two communicating GLI-nodes and intercepts their conversation.  
easily violated as we observed in Section 3.4.2. When addresses of returning packets differ from the addresses used by the sender that initiated the connection, these packets cannot be mapped to the existing communication session. This is not a problem for upgraded GLI-nodes, as only identifier addresses are used on the transport layer, and changes on the network layer do not affect existing transport connections. However a classic IPv6 node sees these changes on the transport layer and, hence, mechanisms are required to ensure that the addresses do not change when different paths are used.
## 3 Results and Discussion
### Biological Assays  
#### 3.5.1 Cytotoxicity  
Of the publications analysed, 88% used biological assays to assess the cytotoxicity of the nanohybrids against either ovarian cancer cell lines (2) or breast cancer cell lines (13). Studies included the assessment of cell viability with the unloaded nanocarrier, as well as the DOX-loaded composite, to assess the biocompatibility. Graphene itself has been shown to be a relatively safe biomaterial yet has a time, concentration, size, and shape-dependent toxicity [24; 94]. As mentioned previously, functionalisation can greatly improve the biocompatibility of the nanocarrier; in general, the results show the unloaded  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Paper**} & \multirow{2}{*}{**Nanocarrier and Release Condition**} & **Zero-Order** & **First-Order** & **Higuchi** & **Weibull** \\ \cline{3-6}  & \(R^{2}\) & \(R^{2}\) & \(R^{2}\) & \(R^{2}\) & \(R^{2}\) \\ \hline \multirow{4}{*}{14} & GO-PEG-FA-SH (pH 4) & 0.9831 & 0.9920 & 0.9983 & 0.9911 \\  & GO-PEG-FA-SH (pH 7.4) & 0.9473 & 0.9542 & 0.9902 & 0.9958 \\  & GO-PEG-FA/GNPs (pH 4) & 0.9906 & 0.9975 & 0.9970 & 0.9872 \\  & GO-PEG-FA/GNPs (pH 7.4) & 0.9899 & 0.9943 & 0.9948 & 0.9786 \\  & GO (pH 5) & 0.9360 & 0.9440 & 0.9887 & 0.9976 \\
15 & GO (pH 7.2) & 0.7671 & 0.7705 & 0.9034 & 0.9491 \\  & GO (pH 9) & 0.8733 & 0.8778 & 0.9597 & 0.9742 \\  & GO@Ag (NIR laser) & 0.9674 & 0.9868 & 0.9931 & 0.9885 \\
16 & GO@Ag (No NIR laser) & 0.9909 & 0.9912 & 0.9831 & 0.9943 \\  & GO-PEG-Fol (pH 5.5) & 0.8911 & 0.9003 & 0.9735 & 0.9933 \\
17 & GO-PEG-Fol (pH 7.4) & 0.9944 & 0.9947 & 0.9636 & 0.9220 \\ \hline \hline \end{tabular}
\end{table}
Table 2: \(Cont.\)nanocarriers were not toxic to normal or cancerous cells. In addition, the DOX-loaded nanocarriers showed increased cytotoxicity towards breast and ovarian cancer cell lines compared to free DOX.  
The different cell lines used are displayed in Table S4; they included ovarian cancer cells SKOV-3, and breast cancer cell lines including MCF-7 and MDA-MB-231. In several publications, DOX-resistant MCF-7 cells were also utilised to understand if the DOX-loaded nanocarrier was more efficacious than free DOX against resistant cell lines.  
Only 20% of the papers used in vivo experiments to assess cytotoxicity. These studies used mice to evaluate the tumour-killing efficiency of the DOX-loaded nanocarriers. Each of these three studies showed that the introduction of the nanocarrier with the loaded drug accumulated at the tumour site and efficiently suppressed the growth of the tumour. Further in vivo studies throughout the publications would be beneficial for understanding the cytotoxicity in living systems and enhancing the clinical translatability.
# New Satellite Selection Approach for GPS/BDS/GLONASS Kinematic Precise Point Positioning
## 4 Test and Analysis
### Positioning Accuracy of the NSS Model
#### 4.2.1 The MGEX Data
It is clear that the GPS/BDS/GLONASS kinematic PPP with NSS model has a centimeter-level accuracy when the simulated kinematic data at the MGEX stations is used. Table 2 shows the average percentages of the number of selected satellites with respect to all visible satellites at five MGEX stations on DOY 239, 2017. It can be known that about 45.5% and 46.6% visible satellites will be selected in NSS model and optimal DOP method, respectively. Table 3 is the RMSs of position errors at five MGEX stations. The position accuracy of original solution, NSS model, and optimal DOP algorithm is 3.0, 7.8, and 7.3 cm, respectively. Compared with the original solution, more than half of the satellites are removed in the NSS model. Additionally, the NSS model has similar position accuracy with the optimal DOP method. Table 4 shows the computing time of daily data processing using the original PPP and NSS model, respectively. From Table 4, we can know that the  
Figure 8: The satellite number and geometric position dilution of precision (GDOP) of kinematic PPP using the original PPP, NSS model, and Optimal DOP algorithm at the DARW station. Figure 9: Position residuals of PPP using different satellite selection solutions at DARW station. mean computing time of the original PPP and NSS model is 107.637 and 58.272 s, respectively. About 45.9% is improved in computing time. Thus, the centimeter-level positioning error can be accepted when it comes to the GPS/BDS/GLONASS kinematic PPP. This is because the NSS model solution reduces the computational complexity and excessive redundant information greatly at the same time.
## 1 Introduction
### Motivation and Problem Statement
In [24], the authors monitored anomalous traffic as an illustrative use case of ML tasks within network operations; moreover, the authors developed formulations for transmission latency, bandwidth congestion, and the accuracy of ML tasks while incorporating edge-cloud collaboration. The proposed method optimized the data preprocessing ratio between edge servers and cloud servers, considering network bandwidth constraints and congestion, as well as the real-time function of anomalous traffic detection. Additionally, the domain of prediction modelling has acknowledged the effectiveness of modified or optimized long short-term memory (LSTM) techniques [25; 26]. Within the context of communication networks, the motivations behind employing LSTM can be categorized into three main perspectives, including sequential dependencies with variable/temporal patterns, adaptive learning, and enhanced prediction accuracy with proactive capability. In [27], the authors presented the problem of massive traffic and proposed a novel approach to network traffic prediction using LSTM and transfer learning. By transferring knowledge from a source domain to a target domain, the method enhanced predictions in low-data scenarios, addressing overfitting and data scarcity. The LSTM-based approach extended transfer learning's application, established a prediction architecture, and improved accuracy, even with limited time series datasets. Furthermore, the LSTM-based approach is also studied in throughput prediction for minimizing the delay of mission-critical services [28]. The authors investigated ML and DL integration for accurate throughput prediction and introduced a modified LSTM-based prediction system with an attention mechanism. The system used TCP log data traces and achieved lower loss in predicting throughput compared with existing methods (e.g., LSTM without attention).
# Investigation of Biochars in Terms of Vitamin E Adsorption Capacity
## 3 Results and Discussions
### Mesopore Analysis
#### 3.2.1 Influence of Biomass  
In view of the high surface area and mesopore volume of biochars D and E, and in view of the fact that the pore volume increases with increasing mesopore class, the assumption can be made that the biomass prior to pyrolysis might have had a high initial porosity [58]. Moreover, this leads to the conundrum that, on the one hand, the pore volume is higher for higher mesopore classes, which could have been caused by a high initial porosity of the biomass [58] and low pyrolysis temperatures, but, on the other hand, the pyrolysis temperature could have been responsible for a high pore volume [68; 69]. Considerably, the range of the mesopore classes varies from 0.64 to 9.75 nm, which consequently results in a higher potential surface area and mesopore volume in, e.g., the mesopore class ranging from 10.26 to 20.01 nm. However, smaller pore classes need to be differentiated more precisely,as these occur due to increased pyrolysis [68; 69] and are mandatory for fixation of the adsorptive [32]. This is underlined by the high surface area in the small mesopore classes.  
Figure 2: Barrett–Joyner–Halenda surface area (**A**) and pore volume (**B**) and their dependence on the mesopore class of biochars A to J (\(n=2\)). Different small letters (abcde) indicate significant differences between biochars for each mesopore class, and different capital letters (ABCDEF) indicate significant differences between mesopore classes for each biochar, determined by One-Way ANOVA and [PERSON]’s post hoc test (\(p<0.05\)), even if the normality test and/or the equal variance test failed (\(p>0.05\)). * indicates that only one result is available.  
Considering these results with respect to the biomasses (Table 1), no difference between the high surface area or pore volume of biochars D and E and the low pore volume of biochar H is obvious, as these biochars consist of wood chips and/or beech and spruce. Thus, the statement that the pore volume depends on biomass [70; 71] does not necessarily apply in this study. These findings underline that the use of softwood does not necessarily result in a larger surface area than the use of hardwood. Biochar I, the only biochar made of softwood, has a rather small pore volume in comparison to the other biochars. This is contrary to [PERSON] et al.'s [72] statement that the less dense composition of softwood results in more pores and vesicles. Studies have also shown that pyrolyzed hardwood does not necessarily result in a similar pore volume: biochar made from beech had a pore volume of 0.0028 cm\({}^{3}\)/g and a surface area of 70.2 m\({}^{2}\)/g [73], whereas biochar made from oak had a pore volume of 0.6011 cm\({}^{3}\)/g and a specific surface area of 945 m\({}^{2}\)/g [74], although both biochars were pyrolyzed at 800 \({}^{\circ}\)C. In biochars A, G, and J, oak was only pyrolyzed together with beech, which resulted in a medium pore volume in comparison to the other analysed biochars.
## 3 Results and Discussion
### Functionalization of Aliphatic Amine
#### 3.1.4 Effect of Reaction Time onto Amine Density  
The effect of reaction time had been analyzed on the assimilation reaction of amine functional group onto GMA-g-NWF. The reaction time was 15, 30, 45, 60, 90, and 120 min. The results achieved are shown in Table 4. The AD increases considerably with reaction time but reaches almost plateau around 30 min, and thereafter insignificant gain was observed in AD as the reaction increases further. Other amines show a similar trend. EDA had gained an AD of 2.89 mmol/g-ad at 15 min of reaction time, which increases to 3.80 mmol/g-ad around 30 min, but the final gain of AD recorded was around 3.91 mmol/g-ad after 120 min complete reaction course. Exhaustion of epoxy sites present on GMA-g-NWF is responsible for the insignificant gain in AD after 30 min [20]. Correspondingly, EDA had gained the highest AD which decreases uniformed as the aliphatic amine chains growth longer. The observation still sustained with the progress in reaction time. EDA, the most straightforward and smallest structure, showed a promising amine to attain high AD to produce effective adsorbent.
# Dynamic Divide Grouping Non-Orthogonal Multiple Access in Terrestrial-Satellite Integrated Network
###### Abstract  
Non-orthogonal multiple access (NOMA) has been extensively studied to improve the performance of the Terrestrial-Satellite Integrated Network (TSIN) on account of the shortage of frequency band resources. In this paper, the terrestrial network and satellite network synergistically provide complete coverage for ground users, and based on the architecture, we first formulate a constrained optimization problem to maximize the sum rate of the TSIN under the limited spectrum resources. As the terrestrial networks and the satellite network will cause interference to each other, we first investigate the capacity performance of the terrestrial networks and the satellite networks separately, in which the optimal power control factor expression is derived. Then, by constructing the relationship model between user elevation angle, beam angle and distance, we develop a dynamic group pairing schemes to ensure the effective pairing of NOMA users. Based on the user pairing, to obtain the optimal resource allocation, a joint optimization algorithm of power allocation, beam channel and base station channel resource is proposed. Finally, simulation results are provided to evaluate the user paring scheme as well as the total system performance, in comparison with the existing works.  
t +
Footnote †: journal: 16 September 2021  
0000-0001-998-2218-6199  
0000-0001-998-2218-6199