esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
### The Development of New Photosensitive Systems
The current efforts result in an amazing series of proposals of new PISs [27; 28; 29; 30; 31; 32; 33; 34; 35; 36; 37; 38; 39; 40; 41; 42; 43; 44; 45; 46; 47; 48; 49; 50; 51; 52; 53; 54; 55; 56; 57; 58; 59; 60; 61; 62; 63; 64; 65; 66; 67; 68; 69; 70; 71; 72; 73; 74; 75; 76]. For example, we have recently introduced PISs ([51; 52; 53; 54; 55; 56; 57; 58; 59; 60; 61; 62; 63; 64; 65; 66; 67; 69; 70; 71; 72; 73; 74; 75; 76]) exhibiting really novel absorption properties (red-shift absorptions, multicolor absorptions, enhanced molar extinction coefficients, \(\varepsilon\)): e.g., colored substituted or functionalized ketones [60], modified organometallic derivatives [70; 71; 72; 73; 74; 75; 76; 77; 78; 79; 80; 81; 82; 83; 84; 85; 86; 87; 88; 89; 90; 91; 92; 93; 94; 95; 96; 97; 98; 99; 100; 101; 102; 103; 104; 105; 106; 107] (ruthenium-, iridium-, platinum-, zirconium- and zinc-based complexes, titanocene derivatives...), various series of dye-based skeletons [61; 62; 63; 65; 66; 67; 68; 74; 75; 76] (e.g., phenylenediamine, polystilbene, polyazine, violanthrone, acridinedione, 2,7-di-tert-butyldimethyldihydropyorene, bodipy, boranyl, thiophene, perylene bis-dicarboximide, hydrocarbons, pyrromethene, pyridinium salt...), di- and _tri_-functional architectures of photo initiators [64], light harvesting compounds [57; 58] (where a strong molecular orbital coupling occurs, leading to \(\varepsilon\) huge values) and push-pull and multicolor photoinitiators (novel chromophores; donor-\(\pi\)-acceptor arrangements; unusual broad absorptions from the blue to the red wavelengths...).
## 3 Validation with Data from International GNSS Service
### Performance of Ambiguity Fixing  
In this study, the DD ambiguity candidates are defined over baselines shorter than a distance of 3500 km and at least with 15 min common observations. For reliable fixing, we excluded DD ambiguities with a standard deviation (STD) larger than 0.15 cycles or a fractional part larger than 0.25 cycles. The fixing rate, defined as the ratio of the number of the fixed and that of all independent DD ambiguities, can be a very efficient indicator to judge the fixing performance. There is an average of 35,013, 51,145, 43662, 39,810 and 65,505 daily independent DD ambiguity candidates can be used with GPS, GR, GE, GC and GREC observations, respectively. We can see that the addition of GLONASS, Galileo and BDS can enhance the estimation of the float solutions, therefore a higher fixing rate can be achieved.  
Obviously, the WL fixing does not have any differences for PPP and POP since it is independent of the analysis model and only code and carrier phase observations are applied. Therefore, we only compare the performance of NL fixing.  
The fixing percentages with single-, dual- and four-system observations are analyzed. The results are displayed in Figure 4. The average fixing percentage of PPP is 88.4% with GPS-only observations which is generally lower than that of the static processing [6; 15] because kinematic stations are involved for fixing. The fixing percentages of POP with GPS, GLONASS and Galileo observations are slightly higher than the corresponding PPP solutions, while the improvement is significant with the BDS observations because of the reduced impact of the orbit errors.  
Figure 3: The distribution of GLONASS stations selected for integer ambiguity fixing. The red diamonds denote the SEPT POLARX5 receivers, the blue dots denote the TRIMBLE NETR9 receivers, the yellow squares denote the JAVAD TRE_G3 TH DELTA receivers and the green triangles denote the LEICA GR25 receivers. The firmware versions for different types of receivers are ignored in this study.  
With the addition of other GNSS observations, a higher fixing rate can be achieved than the GPS-only solution, that is most likely because multi-GNSS enhances the float solution. The average fixing percentages of PPP GC and GREC solutions are only about 86.8 and 89.5%, which are even 5.0 and 2.3% lower than its GR solutions. The major reason is the problem of BDS fixing because of its relatively poor orbit and clock quality. However, the POP can resist such effect, while its GR, GE and GC solutions show almost the same fixing percentage and is higher than that of GPS-only; meanwhile, its GREC solution represents the highest fixing rate of about 92.7%.  
Comparing the ambiguity fixing of PPP and POP solutions using GC or GREC observations, the advantage of the POP approach is confirmed that the orbit biases can be absorbed by clock parameters for better estimates of float ambiguities and consequently better fixing performance.
# Performance Evaluation of Multi-UAV Network Applied to Scanning Rocket Impact Area +
## 4 Proposed System
### Software Architecture  
In order to enable proper information exchange, a system was developed using the client server model capable of exchanging messages between the network nodes and the BS. The communication requirements of the application include the transmission of images processed by the computer vision subsystem; text messages to obtain the aircraft position; the chronology of events; verification of the transmitted data integrity and confirmation of received data. The software is designed to meet the requirements imposed by the image processing subsystem and operate on a network composed of XBee sensors. This architecture can be used in other communication protocols or network architectures for UAV area scanning, where it is necessary to fragment and send data safely to ensure the receipt of all packets. Based on the aforementioned requirements, the system has three types of messages:  
* Type 1: control messages (CtrM), which are periodically transmitted from the network to the BS containing data on telemetry and the swept area;
* Type 2: data messages (DM), which are scanned transmitted from a UAV to the BS when a boat is found, containing the image of the target;
* Type 3: confirmation messages (CnfM), which correspond to the response sent from the BS to a UAV to confirm the receipt of a data message.  
Figure 8: Sequence of steps of the proposed algorithm.
###### Abstract  
The birth of synchrotron radiation (SR) facilities and X-ray free electron lasers (XFELs) has led to the development of new characterization tools that use X-rays and opened frontiers in science and technology. Ultrafast X-ray absorption fine structure (XAFS) spectroscopy for photocatalysts is one such significant research technique. Although carrier behavior in photocatalysts has been discussed in terms of the band theory and their energy levels in reciprocal space (k-space) based on optical spectroscopic results, it has rarely been discussed where photocarriers are located in real-space (r-space) based on direct observation of the excited states. XAFS provides information on the local electronic and geometrical structures around an X-ray-absorbing atom and can address photocarrier dynamics in the r-space observed from the X-ray-absorbing atom. In this article, we discuss the time dependent structure change of tungsten trioxide (WO\({}_{3}\)) and bismuth vanadate (BiVO\({}_{4}\)) photocatalysts studied by the ultrafast pump-probe XAFS method in the femtosecond to nanosecond time scale with the Photon Factory Advanced Ring (PF-AR) and the SPring-8 Angstrom Compact free-electron LASer (SACLA). WO\({}_{3}\) shows a femtosecond decay process of photoexcited electrons followed by a structural change to a metastable state with a hundred picosecond speed, which is relaxed to the ground-state structure with a nanosecond time constant. The Bi L\({}_{3}\) edge of BiVO\({}_{4}\) shows little contribution of the Bi 6s electron to the photoabsorption process; however, it is sensitive to the structural change induced by the photoexcited electron. Time-resolved XAFS measurements in a wide range time domain and with varied wavelengths of the excitation pump laser facilitate understanding of the overall details regarding the photocarrier dynamics that have a significant influence on the photocatalytic performance.  
pump-probe XAFS; XFEL; photocatalyst; arrival timing monitor 2020 10 7818; doi:10.3390/app10217818
## 3 Results
### Pore Size Distributions (PSDs)  
The MIP method has been widely used to analyze pore throats with incremental intrusion plots [34]. PSDs of macro- and mesopores of coal, shale, and tight sandstone samples were obtained using MIP (Figure 7). As shown in Figure 7, coal, shale, and tight sandstone samples show various pore volumes and PSDs. It should be noted that coal samples and tight sandstone samples show significant volumes and multimodal distributions in macro- and mesopore size ranges, while shale samples are dominated by macropores within this range.  
Figure 6: Microreservoir space of nano–micro pores in tight sandstone reservoirs. (**a**) RIPs and ICPs under high-resolution microscope; (**b**) GDPs under high-resolution microscope; (**c**) ICPs under high-resolution microscope; (**d**) RIPs, GDPs and ICPs under FESEM; (**e**) GDPs under FESEM; (**f**) ICPs under FESEM; (**g**) RIPs and secondary quartz under SEM; (**h**) RIPs and ICPs under SEM; (**i**) ICPs and authigenic kaolinite under SEM.  
PSDs of absorption pores (micro- and mesopores) with diameters smaller than 100 nm were obtained using LP-N\({}_{2}\)GA. PSDs of transitional pores and micropores of coal, shale, and tight sandstone samples using LP-N\({}_{2}\)GA are illustrated in Figure 8. All samples have shown the bimodal PSD characteristics of two major peaks. It can be observed that high-rank coal, shale, and tight sandstone have similar pore size peaks at 20 nm and 40 nm. However, most of the tight sandstone samples have larger pore volumes than coal and shale. It is notable that shale samples have another minor but prominent peak at the pore size range between 1 and 4 nm, especially in samples of S-1 and S-5.  
Figure 7: MIP incremental pore volume plots of macropores and mesopores of coal, shale, and tight sandstone samples. (**a**) Macro- and mesopore size distribution in high-rank coal samples. (**b**) Macro- and mesopore size distribution in shale samples. (**c**) Macro- and mesopore size distribution in tight sandstone samples.  
Figure 8: Transitional and micropores coal, shale and tight sandstone samples via LP-N\({}_{2}\)GA. (**a**) Transitional pores and micropores of shale samples via LP-N\({}_{2}\)GA. (**b**) Transitional pores and micropores of high-rank coal samples via LP-N\({}_{2}\)GA. (**c**) Transitional pores and micropores of tight sandstone samples via LP-N\({}_{2}\)GA.
## 2 Numerical Model Development and Experimental Validation
### Numerical Model  
A FEM model of SLJ was developed and simulated using the software Abaqus (Dassault Systemes, Velizy-Villacoublay, France). To create the simulation model, the values of most parameters were chosen based on the existing literature. The mesh size of 1.5 mm was selected, as this is the largest allowable value still below half the LW wavelength, as suggested by the works of [PERSON] et al. [11]. Along the thickness of the substrates, another approach was taken, with the mesh size being governed by the number of layers rather than by the overall size of each element. The value chosen was four layers in each part thickness in order to have enough elements on the thickness to allow the wave to transverse it while still maintaining a reasonable simulation time, which on average corresponded to 1 h per case. A dynamic explicit simulation was chosen due to the temporal flow intrinsic to the problem at hand, while the element type chosen was C3D8R.
# TAB Series-Resonant DC-DC Converter and Multi-Phase-Shift Based Global Optimization Modulation
## 2 Analysis of Topology and Characteristics  
### Topology and Modulation  
Figure 1 shows the topology of the proposed isolated TAB resonant dc-dc converter. It contains three H-bridge converters as the basic power conversion unit at each port. The three ports are connected via a three-winding high-frequency transformer and the turn ratio of the transformer is \(n_{1}\): \(n_{2}\): \(n_{3}\). Two resonant tanks are set at port 1 and 2 to temporarily store energy and realize power adjustment. Compared with the standard series-resonant three-port converter, the proposed converter adds a resonant capacitor on port 3 to construct a resonant tank with the leakage inductor \(L_{\text{k3}}\) of the transformer on port 3. The resonant tank on port 3 is used to realize the power decoupling between port 1 and 2 at the topology level.  
For the two-port converter, the triple-phase-shift modulation has been applied and the minimum transformer current is realized by controlling cooperatively the three phase shifts. However, there is the coupling of the two ports on \(D_{3}\), which causes the optimized modulation in the two-port converter not to be directly applied in the proposed converter.  
Next, the power characteristics of the proposed converter are analyzed and then the power decoupling method is proposed. Furthermore, the principle of the multi-phase-shift modulation to minimize the RMS value of the transformer current is analyzed and the process of how to obtain the final relationship among the various phase shifts is derived in detail.
## 4 Simulation Results
### Simulation Scenarios  
The high-mobility multipath channel is assumed to have \(P=4\) Rayleigh faded paths with exponential power delay profile (PDP) with a decaying time constant of \(10\)\(\upmu\)s and a maximum delay of \(10\)\(\upmu\)s. We consider two different case studies corresponding to different scenarios:  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Cost Function** & **Equation (19)** & **RCF** \\ \hline Multiplications & \((MN+1)(i^{2}+i)\) & \(2 MN+1\) \\ \hline Additions & \((MN-1)(i^{2}+i)+i^{2}-1\) & \(2(MN-1)\) \\ \hline Total number of operations & \(2 MN(i^{2}+i)+i^{2}-1+\mathcal{O}(i^{3})\) & \(4 MN\) \\ \hline \hline \end{tabular}
\end{table}
Table 2: Comparison of computational complexity of cost functions.  
1. _Low-IPI Regime_: Propagation delays and Doppler shifts assume fractional values but the paths are far enough to guarantee low IPI. Thus, all paths are separable in the DD domain. The delays and Doppler shifts of the paths are \(\boldsymbol{\tau}=[0\;\;0.86\tau_{\text{res}}\;\;2.11\tau_{\text{res}}\;\;3.2 \tau_{\text{res}}]\) s, \(\boldsymbol{\
u}=[-1.87\tau_{\text{res}}\;\;2.24\tau_{\text{res}}\;\;-3\tau_{ \text{res}}\;\;1.3\tau_{\text{res}}]\) Hz, respectively.
2. _High-IPI Regime_: Propagation delays and Doppler shifts assume fractional values, and the paths are close enough to create high IPI. The propagation delays of the paths are \(\boldsymbol{\tau}=[0\;\;2.3\;\;3.15\;\;7.7]\) us. The maximum user equipment (UE) speed is \(v_{UE}=190\;\frac{\text{m}}{\text{s}}(684\frac{\text{km}}{\text{s}})\), resulting in a maximum Doppler spread of \(v_{\text{max}}=\frac{v_{UE}}{c}f_{c}=3.23\) kHz, where \(c=3\cdot 10^{8}\;\frac{\text{m}}{\text{s}}\) is the speed of light. The Doppler shifts of all paths are generated assuming Jakes' Doppler power spectrum (DPS) using \(v_{i}=v_{\text{max}}cos(\theta_{i})\) where \(\theta_{i}\sim\mathcal{U}[0,2\pi]\). An example of a pilot frame received in both regimes is provided in Figure 1.
# Energy-Efficient De-Duplication Mechanism for Healthcare Data Aggregation in IoT
## 7 Conclusions  
In this article, the proposed scheme provides a robust solution for improving data transmission within the heterogeneous healthcare environment. The sensors generate patient data readings in different formats. When data readings lie in the normal range, the proposed scheme transmits the Boolean digit 0 for them at the very initial level. Only irregular data readings are transmitted in full form. The key findings are that the proposedsolution reduces data size and improves the performance by eliminating duplicate data and reducing the load on CHs. It further increases the aggregation factor and reduces energy consumption during data transmission. Apart from this, communication and storage costs are also reduced. The stored data on Fog servers and the cloud is demanded to be very precise to help medical professionals focus on only critical readings. EE-FDAS streamlines data transmission processes to improve patient care, particularly for individuals in rural or underserved areas. The proposed scheme is simulated by using NS 2.35 and EE-FDAS has outperformed as compared to existing schemes. Results show that aggregation factor is 0.81, 0.85 and 0.87 in FDAS, EHDA and EE-FDAS. The packet drop ratio remains in FDAS, DICA, DICA\({}_{\text{EXTENSION}}\), EHDA and EE-FDAS is 73%, 87%, 80%, 53% and 43%. In the context of transmission slots, FDAS, DICA, DICA\({}_{\text{EXTENSION}}\), and EHDA require 450, 630, 600, and 250, whereas EE-FDAS dominates by taking only 230 transmission slots. In future, energy-efficient compression techniques will be implemented for critical readings without compromising on data quality.  
Conceptualization, M.N.U.K. and Z.T.; data curation, M.N.U.K. and Z.T.; funding acquisition, Z.T. and W.C.; investigation, Z.T., W.C. and W.P.; methodology, Z.T., A.U. and M.N.U.K.; project administration, M.N.U.K., A.U. and W.P.; software, M.N.U.K., A.U. and W.P.; supervision, Z.T. and W.C.; validation, M.N.U.K. and Z.T.; visualization, M.N.U.K. and A.U.; writing--original draft, M.N.U.K.; writing--review and editing, M.N.U.K., Z.T. and A.U. All authors have read and agreed to the published version of the manuscript.  
This study was supported by the Natural Science Foundation of Guangxi Province under grant 2021 GXNSFAA220010.  
The data presented in this study are available in this article.  
The authors would like to acknowledge Guilin University of Electronic Technology for their valuable support.  
The authors declare no conflicts of interest.
# Magnetic Nanoparticles as Mediators for Magnetic Hyperthermia Therapy Applications: A Status Review
## 3 Results and Discussion
### X-ray Diffraction Analysis
The XRD patterns in Figure 6 show three characteristic broad peaks at 2\(\theta\) = 44.57\({}^{\circ}\), 51.94\({}^{\circ}\), and 76.51\({}^{\circ}\). The as-prepared MNPs were amorphous, and upon heating with an elevated temperature, the size of the crystallites or crystallinity increased [107]. The composition of CrNi MNPs (microemulsion technique) was following the [Cr\({}^{3+}\)]-[Ni\({}^{2+}\)] = 20:80 molar ratio used for the synthesis. The microemulsion technique for the synthesis of NiCr nanoparticles also proved not to be the best, as extremely amorphous nanoparticles were obtained without thermal homogenization. At the same time, the XRD results also show a peak at 37\({}^{\circ}\), indicating the formation of NiO despite the inert atmosphere throughout the synthesis process. Only with the help of homogenization at elevated temperatures did we obtain crystalline nanoparticles that grew with increasing temperature. Unfortunately, homogenization leads to agglomeration of nanoparticles and at some locations also to larger grains in the form of platelets, which was confirmed by TEM analysis. In Figure 7, we see the XRD results showing the formation of Cr\({}_{x}\)Ni\({}_{1-x}\) alloy using mechanical milling [107]. With increasing Ni content (in %), a progressive diffraction angle was observed in both cases (111) and (200). NiCr samples prepared using mechanical milling were also milled for 20 h in the same manner as NiCu. Figure 7 shows that the Bragg peaks in both cases (111) and (200) shift to higher diffraction angles with increasing Ni content. The lattice constant and interplanar distance \(d_{111}\) also increase with increasing chromium content. In the microemulsion method, particles with a size of up to 25 nm were obtained, while in mechanical milling the particles were micrometer in size, which were comprised of nanocrystallites.
## 4 Results and Discussion
### Advantages and Limitations of Using the DEA Method  
DEA technique has several merits over the conventional regression-based production function approach. A few of them are as follows [102; 103; 104] quotes as it is in Table 4:  
* DEA can deal with multiple inputs and outputs with a series of units.
* It does not need any assumption of a functional form relating inputs to outputs.
* It sets targets for risk DMUs to make them efficient.
* It estimates a single risk score, identifies input excesses and output, and provides benchmarks to monitor the performance of risky road segments.
* It is free from the unit concept.
* Relative changes in data in case of homogeneous DMUs do not effects on the output generated by DEA.
* Selection of inputs and outputs play major role in calculation of efficiency and risk.
* There may be any question about the application of DEA model but through proper application in accordance with its weak points it can be applied widely following the rules and regulations.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Advantages** & **Limitations** \\ \hline \(\bullet\) & DEA can deal with multiple inputs and outputs with a series of units. & \(\bullet\) \\ \(\bullet\) & It does not need any assumption of a functional form relating inputs to outputs. & \(\bullet\) \\ \(\bullet\) & It sets targets for risk DMUs to make them efficient. & \(\bullet\) \\ \(\bullet\) & It estimates a single risk score, identifies input excesses and output, and provides benchmarks to monitor the performance of risky road segments. & \(\bullet\) \\ \(\bullet\) & It is free from the unit concept. & \(\bullet\) \\ \(\bullet\) & Relative changes in data in case of homogeneous DMUs do not effects on the output generated by DEA. & \(\bullet\) \\ \(\bullet\) & Selection of inputs and outputs play major role in calculation of efficiency and risk. & \(\bullet\) \\ \(\bullet\) & There may be any question about the application of DEA model but through proper application in accordance with its weak points it can be applied widely following the rules and regulations. & \(\bullet\) \\ \hline \hline \end{tabular}
\end{table}
Table 4: Advantages and limitations of using the DEA method.