esa-sceva/satcom-chunk-collection huggingface dataset:
# A Multilevel Switched Capacitor Inverter with Reduced Components and Self-Balance
## 4 Topology Extension and Comparison  
### Topology Extension  
One of the main benefits of the proposed 13-level topology is that it allows for modular extensions. As illustrated in Figure 7, each L-type unit (LTU) contains a capacitor, three power switches, and a diode. It can be learned from a previous analysis that capacitor \(C_{\rm 3}\) is charged in series with the capacitors \(C_{\rm 1}\) and \(C_{\rm 2}\) through switches \(S_{\rm 10}\) and \(S_{\rm 12}\). Theoretically, \(n\) LTUs can be integrated into the proposed switched-capacitor multilevel inverter. For the \(n\)-th LTU, capacitor \(C_{\rm n+2}\) can be charged to (\(3\times 2^{\rm n-1}\)) \(V_{\rm dc}\) through series connection with the capacitors \(C_{\rm 1}\)-\(C_{\rm n+1}\), since the voltage levels and boost factor will be increased by connecting multiple L-type units.  
The extended inverter consists of \(n\) number of LTU, the switch count \(N_{\rm switch}\), the diode count \(N_{\rm diode}\), the switched capacitor count \(N_{\rm capacitor}\), the voltage levels \(N_{\rm level}\), and the boost factor \(G\) can be expressed as:  
\[N_{\rm switch} =3n+9, \tag{26}\]  
\[N_{\rm diode}=n+1, \tag{27}\]  
\[N_{\rm capacitor}=n+2, \tag{28}\]  
\[N_{\rm level} =3\times 2^{n+1}+1, \tag{29}\]  
\[G =3\times 2^{n}. \tag{30}\]  
Figure 7: Extended structure with n LTUs.  
The THD of the proposed inverter can be further reduced with the increase in output levels, while the control of switches will be more complex, and the demand for carriers will also increase significantly, which is twice as much as voltage gain. Therefore, reasonable output levels and voltage gain can be chosen according to application requirements.
# Development of an Online Detection Setup for Dissolved Gas in Transformer Insulating Oil
## 5 Conclusions  
In this paper, an online detection system for dissolved gases in transformer insulating oil based on modified headspace degassing and tunable laser absorption spectroscopy, was proposed. The oil-gas separation system degassed large-volume oil samples using low pressure, constant temperature, and low-frequency stirring as working conditions. An oil-gas separation experiment showed that the equipment can degas a 650 mL oil sample in 1 h. The optical coupler and time-division multiplexing (TDM) technology were used to form a common optical path to improve the structural strength of the optical system. By analyzing the absorption spectra, the near-infrared center wavelengths of six target gases (carbon dioxide 1579.57 nm, carbon monoxide 1579.74 nm, methane 1684.04 nm, ethylene 1683.35 nm, ethane 1683.1 nm, acetylene 1532.83 nm) are determined. Three lasers (1569, 1684, 1532 nm) are used to detect those six gases, respectively. Laser (1684 nm) is adopted to detect three gases (methane, ethylene, ethane), laser (1579 nm) for two gases (carbon dioxide, carbon monoxide), and laser (1532 nm) for acetylene. The detection sensitivity of the target gases achieved by the gas detection experiment were 5.1 mV/\(\mu\)L\(\cdot\)L\({}^{-1}\) for methane, 6.4 mV/\(\mu\)L\(\cdot\)L\({}^{-1}\) for ethylene, 4.6 mV/\(\mu\)L\(\cdot\)L\({}^{-1}\) for ethane, 3.4 mV/\(\mu\)L\(\cdot\)L\({}^{-1}\) for carbon monoxide, 1.6 mV/\(\mu\)L\(\cdot\)L\({}^{-1}\) for carbon dioxide, and 12.8 mV/\(\mu\)L\(\cdot\)L\({}^{-1}\) for acetylene. The experimental results of the detection of dissolved gases in insulating oil demonstrate that the setup described in this paper conforms to the standards required by the electric power industry. In addition, the six kinds of gases detected can analyze additional transformer status information. Therefore, the system developed in this paper is a relatively accurate online detection setup for determining the transformer status.  
Conceptualization and writing original draft preparation, Y.C.; methodology, Y.C.; software, Y.C. and Z.L.; validation, J.D.; formal analysis, Z.L.; investigation, H.Z. and Z.W.; resources, J.D. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The data presented in this study are available on request from the corresponding author.  
The authors declare no conflict of interest.
# A Probabilistic Hyperspectral Imagery Restoration Method
## 5 Experimental Results and Analysis
### Evaluation on Real Dataset  
We further verify the proposed method on real data. Specifically, we use terrain and urban datasets in the experiments, which can be downloaded from [[http://www.tec.army.mil/hypercube](http://www.tec.army.mil/hypercube)]([http://www.tec.army.mil/hypercube](http://www.tec.army.mil/hypercube)).  
We restore terrain data on all bands with VBM3D, Godec, SLrank, and the proposed low-rank based method. Figures 8 and 9 illustrate the experimental results on bands 1 and 4, where two areas of interest are zoomed. These bands are influenced by Gaussian noise, stripes and dead lines. The real image band is given in (a). The restoration results of VBM3D, Godec, SLrank, and the proposed method are illustrated in (b)-(e). It can be seen that the proposed low-rank method has better performance compared with other competing methods. The stripes and dead lines are well addressed and the details of HSI are well preserved. The dead lines and stripes still remains for VBM3D based method.  
Figure 8: Visual results on band 1 of terrain dataset: (**a**) Captured actual band, (**b**) Restoration results of VBM3D based method, (**c**) Restoration results of Godec based method, (**d**) Restoration results of SLrank based method, (**e**) Restoration results of the proposed method.
# A Study on the Amplitude Comparison Monopulse Algorithm
## 3 Least-Squares-Based Amplitude Comparison Monopulse Algorithm
### Sum-Difference Measurement-Based Algorithm
\right]\delta S \tag{34}\]  
which means that the first iterative step in least-squares estimation gives the following target location estimate:  
\[\left[ \begin{array}{c}\hat{\theta}_{az}^{full}\\ \hat{\theta}_{cl}^{full}\end{array} \right]\approx\frac{\theta_{3 dB}^{2}}{8 \sqrt{2}\log 2\;\theta_{s}\;{g(\theta_{s})}A}\left[ \begin{array}{c}\Delta_{ az}\\ \Delta_{el}\end{array} \right] \tag{35}\]  
For the case of the sum-difference measurement-based algorithm, a similar analysis is possible. With the assumption of \(\theta_{az}^{2}+\theta_{cl}^{2}\approx 0\), the matrix \(\Big{(}H_{sd}^{T}H_{sd}\Big{)}^{-1}\) of Equation (32) is approximately computed by  
\[\Big{(}H_{sd}^{T}H_{sd}\Big{)}^{-1}\approx\frac{\theta_{3 dB}^{4}}{128\;{(\log 2 )}^{2}\;\theta_{s}^{2}\;{(g(\theta_{s}))}^{2}A^{2}}\;I_{2} \tag{36}\]  
With the nominal values of \(\theta_{az0}=0\) and \(\theta_{el0}=0\), the sum-difference measurement-based algorithm given by Equation (32) becomes approximately  
\[\delta\hat{\theta}^{sd}\approx\frac{\theta_{3 dB}^{2}}{8\sqrt{2}\log 2\;\theta_{s}\; {g(\theta_{s})}A}\left[ \begin{array}{ccc}0&1&0\\ 0&0&1\end{array} \right]\delta Z \tag{37}\]  
which means that the first iterative step in least-squares estimation gives the following target location estimate:  
\[\left[ \begin{array}{c}\hat{\theta}_{az}^{sd}\\ \hat{\theta}_{el}^{sd}\end{array} \right]\approx\frac{\theta_{3 dB}^{2}}{8\sqrt {2}\log 2\;\theta_{s}\;{g(\theta_{s})}A}\left[ \begin{array}{c}\Delta_{ az}\\ \Delta_{el}\end{array} \right] \tag{38}\]  
Note that this equation is the same as Equation (35) of full measurement-based algorithm. To compare the least-squares-based estimate algorithm with the conventional one, Equations (6) and (12) are applied to Equations (15) and (16), and, then,  
\[ \begin{array}{c}\hat{\theta}_{az}^{c}=\frac{\theta_{3 dB}^{2}}{8\sqrt{2}\log 2 \;\theta_{s}\;{g_{0}}A}\Delta_{xz}\\ \hat{\theta}_{el}^{c}=\frac{\theta_{3 dB}^{2}}{8\sqrt{2}\log 2\;\theta_{s}\;{g_{0}}A} \Delta_{el}\end{array}  \tag{39}\]Equation (39) is also the same as Equations (35) and (38), since \(g(\theta_{s})\approx g_{0}\) is already assumed in Equation (7), which means that the conventional monopulse algorithm provides the same target location estimate as the least-squares-based algorithms with the first iterative step. Eventually, it turns out that the three monopulse algorithms are nominally the same. We can expect that performing multistep iterations with least-squares-based algorithm can provide better target location estimation than the conventional one, since the accuracy of the first-order Taylor expansion is improved.
# Research on Bandwidth Improvement of Fine Tracking Control System in Space Laser Communication
## 1 Introduction
### Main Contributions  
In this paper, we set up an experimental platform for the fine tracking system, verify the accuracy of the rate-dependent hysteresis model, and analyze the advantages of the compound control method based on the rate-dependent hysteresis model. Finally, we test the effectiveness of this control method in improving the error suppression bandwidth of the fine tracking system.
# Shear Capacity of Textile-Reinforced Concrete Slabs without Shear Reinforcement
## 2 Experimental Investigation on Shear Capacity
### Cementitious Matrix  
The cementitious matrix utilized in this study was specifically designed within the C\({}^{3}\) project to meet the requirements of textile reinforced concrete [70]. The mixture was based on [70], but adapted with locally available aggregates. Details can be found in Table 3. The maximum diameter of the crushed quartz aggregate (4 mm) matched the size of the grid openings. The high content of fine particles in the cementitious binder compound and the fine sand paired with the high-performance superplasticizer led to self-compacting properties of the fresh mix. During production, no external or internal compaction was required to achieve a dense matrix without cavities or gravel pockets.  
According to DIN EN 206 [71], the mixture was no standard concrete due to its small aggregate size and its high content of fine particles. As it was produced and applied just like concrete as matrix, the term \"concrete\" is used in this paper and generally in the context of textile reinforced concrete for new constructions. This allows a distinction to be made from repair and retrofitting, where the term mortar is more common.  
The hardened concrete exhibited high strength, both in compression and in tension. The bending tensile strength was determined on prism specimens (40 \(\times\) 40 \(\times\) 160 mm), according to the standard  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Characteristic** & **Unit** & **Warp Direction (0\({}^{\circ}\))** & **Weft Direction (90\({}^{\circ}\))** \\ \hline Modulus of elasticity & [MPa] & 244,835 & 243,828 \\ Mean ultimate stress & [MPa] & 3221 (\(n=204\) tests) & 3334 (\(n=218\) tests) \\
5\% quantile ultimate stress & [MPa] & 2737 & 2762 \\ Mean ultimate strain & [\%] & 13.2 & 13.7 \\ Axial spacing of yarns & [mm] & 38 & 38 \\ Cross-sectional area per yarn \({}^{1}\) & [mm\({}^{2}\)] & 3.62 \({}^{1}\) & 3.62 \({}^{1}\) \\ Cross-sectional area per meter \({}^{1}\) & [mm\({}^{2}\)/m] & 95 \({}^{1}\) & 95 \({}^{1}\) \\ \hline \hline \end{tabular} \({}^{1}\)Filament area without epoxy-impregnation.  
\end{table}
Table 2: Reinforcement characteristics for solidian Grid Q95/95-CCE-38 (properties of one individual yarn, from [64] with test setup according to [65]).  
test method for mortar [72]. The mean value of all experiments (age 27 to 32 days) was 15.1 MPa with a coefficient of variation (COV) of 21.6%. The mean modulus of elasticity of the cementitious matrix was tested on cylindrical specimens (d/h = 150/300 mm) to 44595 MPa (COV 2.1%) with the method described in [73]. The mean compressive strength reached 127.6 MPa (COV 4.2%) for 150 mm cubes [74], 105.4 MPa (COV 4.7%) for cylinders (d/h = 150/300 mm, [74]), and 122.5 MPa (COV 5.1%) for the prism halves [72]. Due to the high strength of the cementitious matrix, cracks usually ran through the aggregates. The ultimate compressive strain of this concrete has been determined on two cylinders with external concrete strain gauges to 2.92% at the age of 28 days.
# Error Characteristic Analysis of Fluid Momentum Law Test Apparatus
## 2 Experimental Device and Numerical Model
### Numerical Model and Parameters  
In the process of experimental investigation, a water jet is generated by the jet generator (4) and the water jet impacts the flat model (5) under the action of inertia. During this process, the water jet is greatly deformed under the block of the flat model, and the momentum of the jet changes, forming a jet impact force. The flat model produces displacement and deformation under the action of the jet impact force. This process is a typical water jet impacting solid. The SPH-FEM method is suitable for the numerical solution of this experiment. During the experiment, the verification of the law of fluid momentum under different jet velocity states was achieved by changing the flow of the system. Combining the actual operation of the experiment, this article intends to analyze the characteristics of the jet impact process and the momentum law test apparatus under five common flow conditions, as shown in Table 1. The jet generator of the experiment platform produces a circular cross-section equal-diameter water jet with a diameter of 8 mm. The jet impact position is the center of the plate, the target distance is 2 mm, and gravity is ignored; the impact calculation time is set to 30 ms.  
The numerical model of the experimental device is shown in Figure 2. The material and element properties of each part of the model are shown in Table 2. The basic properties of the materials PMMA (Polymethyl-methacrylate, abbreviated as PMMA) and STEEL [25] are shown in Table 3; the EOS of the jet (WATER) equation of state selects US-UP, and the specific parameters are also shown in Table 3. According to the experimental conditions, the classical formula of the momentum theorem is used to calculate that the jet impact force is less than 20N, and the materials PMMA and STEEL of the structure are in the elastic deformation zone without plastic deformation.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**No**} & **Flow Rate** & **Speed of Jet** & **Initial Momentum of Jet** & **Increment of Jet** \\  & **(m\({}^{3}\)/h)** & **(m/s)** & **(kg:m/s)** & **(kg:m/s)** \\ \hline
1 & 2.2 & 12.16 & 7.43 & 0 \\
2 & 2.4 & 13.26 & 8.84 & 1.41 \\
3 & 2.6 & 14.37 & 10.38 & 1.54 \\
4 & 2.8 & 15.48 & 12.04 & 1.66 \\
5 & 3.0 & 16.58 & 13.82 & 1.78 \\ \hline \hline \end{tabular}
\end{table}
Table 1: The distribution of jet velocity.
# Caching Transient Contents in Vehicular Named Data Networking: A Performance Analysis
## 6 Performance Evaluation
### Highway Scenario  
The second set of results, in Figure 6, focuses on the highway scenario, when varying the Zipf skewness parameter \(\alpha\) in the range 1, 1.5, 2, 2.5.  
The same trends can be observed already seen for the urban scenario. First, the proposed solution, FDC, outperforms the benchmark schemes, under all settings. Second, performance gets better for all  
Figure 5: Performance metrics in the urban scenario, when varying the number of consumers (\(\alpha=1.5\)).  
schemes as the \(\alpha\) parameter increases. The main difference regarding the previous scenario is that all solutions exhibit slightly worse performance. For instance, in Figure 5(b), it can be seen that the lowest retrieval delay is 6.1s for FDC when \(\alpha=2.5\), while it was about 3s in the urban scenario in the same settings. This has to be ascribed to the topology and the higher vehicle speed which make contact times among vehicles shorter, hence also reducing the caching events. As a result, the number of hops increases as well as the delay in retrieving contents which entails the exchange of more Data packets.  
As shown in Figure 7, the increasing number of consumers affects the achieved performance, similarly to the urban scenario. However, the trend of the experienced improvements in terms of both cache hit ratio and retrieval delay gets steeper as the number of consumers increases, compared to the urban scenario. Indeed, less congestion is experienced in this topology, due to the higher volatile nature of connectivity and the smaller size of the one-hop neighborhood per vehicle.  
Figure 6: Performance metrics in the highway scenario, when varying the Zipf skewness parameter \(\alpha\) (number of consumers equal to 20).
## 4 Conclusions  
In summary, we have confirmed that electrospray technology facilitates the introduction of cisplatin, an anticancer drug, into cancer cells and discovered that electrospray at 6 kV is the proper voltage for delivery of the drug to the target. Compared with the group treated only with cisplatin, the 6 kV CDES-treated group effectively inhibited cell proliferation and induced apoptosis of cancer cells. Additionally, after ES treatment, the plasma membrane permeability was measured at regular intervals. This result indirectly showed that CDES increased the influx of the drug by increasing the permeability of the cell membrane. If this technology is further improved with additional in vivo studies, we expect it could be advanced to local anticancer treatment to apply the drugs selectively to tumor sites only. With our research, another anticancer delivery system fundamental for local treatment has been established.  
The following are available online at [[https://www.mdpi.com/article/10.3390/app11073203/s1](https://www.mdpi.com/article/10.3390/app11073203/s1)]([https://www.mdpi.com/article/10.3390/app11073203/s1](https://www.mdpi.com/article/10.3390/app11073203/s1)), Figure S1: Components of CDES system, Figure S2: Cell viability after electrospray (ES) at various voltage, Figure S3: Comparison of cell viability at various voltage CDES.  
Conceptualization, M.C.L., S.P. ([PERSON]), H.S. ([PERSON]) and J.H.C.; methodology, M.C.L. and J.W.L.; validation, [PERSON], M.C.L., [PERSON] ([PERSON]), [PERSON] ([PERSON]) and [PERSON] ([PERSON]); formal analysis, M.C.L., J.W.L. and S.P. ([PERSON]); investigation, M.C.L., [PERSON] ([PERSON]), [PERSON], [PERSON] ([PERSON]), [PERSON] ([PERSON]) and J.E.K.; resources, [PERSON] ([PERSON]); data curation, [PERSON] ([PERSON]) and J.W.L.; writing--original draft preparation, [PERSON], [PERSON] ([PERSON]) and [PERSON]; writing--review and editing, [PERSON] ([PERSON]), M.C.L., P.G. and [PERSON]; visualization, [PERSON] and [PERSON]; supervision, [PERSON] ([PERSON]), [PERSON] and [PERSON]; funding acquisition, [PERSON] and [PERSON]. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (NRF-2020R1F1A1067439 and NRF-2020R1I1A1A01068262), Korea Institute of Energy Technology Evaluation and Planning (KETEP) and the Ministry of Trade, Industry & Energy (MOTIE) of the Republic of Korea (20194210100230), and the Ministry of Trade, Industry & and BK21 FOUR, Global Smart Farm Educational Research Center, Seoul National University, Seoul, Korea.  
Not applicable.  
The authors declare no conflict of interest.
# A Node Placement Algorithm Utilizing Mobile Nodes in WSN and IoT Networks +
## 4 The Node Placement Algorithm
### Dynamic Node Placement (Locally-Significant Paths)
#### 4.1.2 Calculation of Extra Resources  
In this step, the _Additional Resources_ are calculated based on the average number of packets per time unit (seconds) that the defective node receives and is not able to forward. This parameter defines the excess traffic the mobile node will require to accommodate.  
In particular, for a _defective node_\(i\), the _Additional Resources_ rate \(AR(i)\) is calculated by the equation:  
\[AR(i)=\frac{Recv(i)-Tran(i)}{t-t_{0}} \tag{1}\]  
where  
\(Recv(i)\) is the number of packets that \(i\) has received from its neighbors,  
\(Tran(i)\) is the number of packets that \(i\) has transmitted,  
\(t\) is the current time, and  
\(t_{0}\) is the time that \(i\) started transmitting packets.  
Based on this equation, the mobile node that will move close to the problematic area should be able to receive and forward the excess traffic load that cannot be forwarded by the defective node. Thus, the defective node will receive just the traffic it can accommodate, and the problem will be alleviated.  
Below a more detailed description of each step is presented.
## 3 Results and Discussions
### Research on the Relationship between the Extent of Damage Intensity Index and Mining Impacts  
The purpose of this study was to see if there was a significant relationship between the damage intensity index of buildings \(w_{u}\) and their components \(w_{ui}\), and mining impacts in the form of:  
* Continuous ground deformations, described by maximum values of horizontal deformations \(\varepsilon_{max}\),
* Mining tremors, which were measured using two indices \(PGA_{H}\) and \(a_{sg}\).  
They were determined individually for each building. In the case of \(PGA_{H}\), all tremors which occurred in the analysed periods of the building existence were taken into account, that is from the date of construction to 2002, in 2003-2007 and 2008-2012. In the case of \(a_{sg}\), the basis was the increments of the index over the reported time intervals.  
Figure 6: Average \(a_{sg}\) values of the studied buildings (**a**) and average number of N tremors with \(a_{p}\geq 0.12\) m/s\({}^{2}\) (**b**).  
[PERSON]'s linear correlation test was used. In addition to the correlation coefficient R, the significance level \(p\) of the obtained result was also calculated. The critical level was taken as \(p=0.05\).  
The results of the conducted research for large-block buildings are summarized in Table 5, while those for large-panel buildings in Table 6. The cases where significant positive correlations were found are highlighted.