esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Mechanical Analysis and Numerical Simulation of Roadway Wall Rock
### Wall Rock Support System and Its Mechanical Analysis
(3) Calculation of wall rock pressure in the 7900 mining area belt roadway  
The section of the belt roadway in the 7900 mining area of a mine is rectangular, and its relevant parameters are shown in Figure 1:0 The maximum wall rock pressure of the roadway is calculated based on the above-mentioned PU's equilibrium arch theory and [PERSON]'s theory. Based on PU's equilibrium arch theory, the maximum span \(2a_{1}\) of the natural equilibrium arch was 8.54 m according to Formula (2), the maximum rise height \(b_{1}\) of the natural equilibrium arch was 1.423 m according to Formula (1), and the maximum wall rock pressure \(Q\) of the roadway was 0.0355 MPa according to Formula (3). Based on [PERSON]'s theory, the width \(2b\) of the sliding block was calculated as 8.54 m by Equation (4), and the cohesive force of the loose soil is usually 0.2 MPa. Regardless of the surface additional load \begin{table}
\begin{tabular}{c c} \hline \hline
**Roadway Parameters** & **Values** \\ \hline Height: \(h\) & 3.5 m \\ Span: \(2a\) & 4.5 m \\ Cross-sectional area: \(S\) & 15.75 m\({}^{2}\) \\ Burial depth: \(L\) & 60 m \\ Average weight density of rock mass: \(\gamma\) & 25 KN/m\({}^{3}\) \\ Rock firmness coefficient: \(f_{p}\) & 3 \\ Lateral pressure coefficient: \(k_{0}\) & 1 \\ Internal friction angle of rock mass: \(\varphi_{c}\) & 30\({}^{\circ}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Parameters of 7900 mining area belt roadway. \(P_{0}\), the maximum wall rock pressure \(Q\) of the roadway was calculated as 0.032 MPa by Equation (13). In order to ensure the safety and effectiveness of the temporary support and ensure that the temporary support can provide a sufficient support force for the wall rock of the roadway, the larger value of 0.0355 MPa calculated by PU's equilibrium arch theory and [PERSON]'s theory was taken as the maximum wall rock pressure of the roadway as the basis for subsequent calculations.
# Output Filter Design for a Novel Dual-Input PV-Wind Power Converter by Energy Balance Principle
## 2 Characteristics of Proposed Converter  
Figure 1 shows the circuit configuration of the proposed DIPWC in this paper, which mainly consists of two coupled inductors, four power MOSFETs, four capacitors, ten diodes, and an LC filter. The proposed DIPWC can conceptually be regarded as the integrating of two double-ended forwards with voltage multipliers. This structure can recycle the energy stored in the leakage inductors, \(L_{k,wind}\) and \(L_{k,pv}\), to their corresponding power inputs. By controlling the appropriate power switches with pulse-width modulation (PWM), the DIPWC can draw renewable energy and then feed power to the DC bus. The input renewable energy can come from either a PV panel, a wind turbine or both. During a switch cycle, when all the switches are in an off state, the output inductor \(L_{0}\) has to release energy to the DC bus to continually provide power. A renewable generation system--to deal with the high power rating--will accompany a high level of output current. As a result, the DIPWC should operate in continuous conduction mode (CCM) to lower current stresses of semiconductor devices. This reason has revealed the importance of the design relating to output-filter inductance.
## 4 Intra-Layer Contact Plan Design
### Intra-Layer Contact Plan for Satellite Layer  
Taking into account the time-varying characteristics of the topology in the satellite network, a classic algorithm named as DVTR [39] is employed to schedule the contacts within the satellite layer. Like the HAP layer, the algorithm also reserves multiple shortest paths. Once the preferred next node is occupied, the available next node of another shortest path is selected to establish the contact. Besides, in order to improve the arrival rate of data, the contact which is closer to the destination node will be given higher priority to be established.
# Acoustic Impact of Hybrid-Electric DEP Aircraft Configuration at Airport Level
## 1 Introduction  
The Italian research project PROSIB (PROpulsione e Sistemi IBridi per velivoli ad ala fissa e rotante) [1], is a national project whose scope is the exploration of the impact of innovative propulsion technologies on regional aircraft and rotary wing platforms.  
The future of aircraft propulsion is leading to electric configurations, not only using fully electric technology, but also considering hybrid electric approaches. Engineering solutions will have the goal of finding the best strategies for optimizing all available energy sources on the aircraft, both electrical and classical. Electric propulsion systems are characterised by zero emissions, but we need to also take into account the noise levels produced by the system as a whole. The noise emitted by these propulsion systems is expected to be different from classical general aviation aircraft noise, particularly relevant to populated areas around the airports.  
The present work is focused on the evaluation of the acoustic impact resulting from a regional aircraft (ATR42 pax) equipped with new propulsion technologies and new configurations.  
Though noise impacts on the ground are usually evaluated with experimental test campaigns [2], this is not feasible when exploring a novel configuration. We propose a computational chain to assess the acoustic performances of aircraft in the preliminary phases of design. As a first step, to evaluate the real gain in terms of noise reduction it is important to characterize the aircraft as a noise source and then assess the impacts of its operation. Its noise field can be computed using the results of aerodynamic performance simulations. Then, a database of aircraft operations, in terms of noise levels, can be produced using the Noise-power-distance (NPD) approach [3].  
Noise-power-distance (NPD) databases play a central role in conducting noise impact assessments for any type of aircraft. This is even more important when considering new configurations, such as those equipped with brand new hybrid/electric engines. As reported in [4], the Federal Aviation Administration, Office of Environment and Energy (FAA-AEE)developed an Aviation Environmental Design Tool AEDT that uses NPD results as a source term in evaluating aircraft noise and emissions for airport environmental studies.  
Following the procedure described above, CIRA setup a computational chain consisting of the following main steps:  
1. The evaluation of the aerodynamic pressures on the full configuration via a medium-fidelity aerodynamic solver;
2. The evaluation of aeroacoustic performances and hemispheric noise fields, using the Ffowcs Williams and Hawkings (FW-H) approach;
3. Generation of noise-power-distance database through a ray-tracing approach;
4. Acoustic impact at airport level evaluation with Aviation Environmental Design Tool (AEDT) procedure.
# On the Utilization of Reversible Colour Transforms for Lossless 2-D Data Compression
## 3 Reversible Colour Transforms (RCTs)  
Prior conversion of data from imaging domain to another can produce better compression results by the BWCA. [PERSON] et al. utilized Discrete Wavelet Transform (DWT), a lossless wavelet transform in conjunction with Huffman encoder, and achieved higher compression. DWT for lossless compression has been utilized in methodologies proposed by [PERSON] and [PERSON] in [31] and [PERSON] et al. in [32]. [PERSON] et al. in [33] employed Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) showing that the DWT outperformed the DCT in terms of lossless compression. [PERSON] et al. in [34] used automatic selection of colour transforms for efficient coding, either lossy or lossless. It was 2 percent more efficient in the case of lossless coding. In [PERSON]'s earlier work in [35], various RCTs have been developed for efficient compression. By not fixing the RCT for image regions, better compression was achieved. Colour space transformation refers to the conversion of image information from one colour domain to another. Multiple linear along with the non-linear transformations of the true colour image is utilized for the definition of a colour image in terms of luminance and colour [16; 36; 37; 38; 39]. RCTs have been utilised to boost compression of the RGB images by increasing data redundancy in other colour spaces [39; 40]. Totally reversible integer colour transform transforms the imaging data into various colour spaces [29; 41] and has been utilized for lossless image compression by JPEG 2000 [29; 42; 43; 44]. Figure 3: Overview of the Bi-level Burrows–Wheeler Compression Algorithm (BBWCA) [14]. This colour conversion helps in achieving high compression by reducing an image's entropy prior to encoding [38; 39]. Researchers have proposed various RCTs in the fields including the methodologies presented in [16; 29; 37; 38; 42; 44; 45; 46; 47]. This research focuses on the evaluation and investigation of the new and efficient RCT proposed by [PERSON] in [45]. RDgDb, LDgDb, RDgEb, LDgEb, YA2 UA2 VA2, YA6 UA6 VA6, YA7 UA7 VA7 were listed as some of the few lossless transforms utilized and a comparative analysis has been drawn with RCTs of JPEG-2000, JPEG-XR and JPEG-LS etc. Each transform offers it advantages e.g., RDgDb has a requirement of subtraction of two integers per image pixel thus having lesser computational complexity [45] while LDgDb lossless colour transform offers a better estimation of the analog transformation in human vision system thus outperforming the YCoCg-R transform. Table 1 lists various RCTs used in image processing. Forward and Reverse RCT equations are listed as well.
# Design and SAR Analysis of a Dual Band Wearable Antenna for WLAN Applications
## 2 Design Methodology
### Metamaterial Based Approach
#### 2.2.2 Electromagnetic Band-Gap Array  
Surface wave suppression is one of the most important properties of EBG structures. Suppression of surface waves improves the gain, directivity and other parameters of the antenna, while it minimizes side and back lobes [37]. The scattering parameters of the  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Type** & **lu (mm)** & **g1 (mm)** & **g2 (mm)** & **h (mm)** & **r (mm)** & **1 (mm)** & **w (mm)** & **Periodicity** \\ \hline Mushroom-like & & & & & & & & \\ EBG unit cell & 32.5 & 2 & 1.5 & 3 & 1.5 & & & 32.5 \\ \hline Plus-shaped slot & & & & & & & & \\ EBG unit cell & 26.5 & 0.5 & 1.1 & 3 & & 13 & 3 & 26.5 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Summary of the EBG unit cells dimensions.  
Figure 3: In-phase reflection of EBG unit cells. (**a**) Mushroom-like unit cell. (**b**) Unit cell with plus-shaped slots.  
Figure 2: EBG unit cells. (**a**) Mushroom-like EBG unit cell. (**b**) Unit cell with plus-shaped slots.  
two EBG surfaces are achieved by the use of two port transmission line techniques, as depicted in Figure 4. Out of the two ports, the one to the left side is supposed as the source of excitation, and the other to the right side is supposed as a matched load. The mushroom-like EBG array has a total size of 176.5 mm \(\times\) 176.5 mm, while the second EBG array with plus-shaped slots is 136 mm \(\times\) 136 mm.  
The reflection and transmission coefficients of the two EBG structures are depicted in Figure 5. It shows that in the case of each EBG, the S21 is lower than \(-\)15 dB at both frequencies (2.5 GHz and 5.196 GHz). Therefore, both EBG structures have the ability to suppress surface waves in the desired frequency bands (2.5 GHz and 5.196 GHz). However, the second EBG structure with plus-shaped slots is about 22.94% more compact than the conventional mushroom-like EBG array.
# Linomycin-Induced Transcriptional Alterations in the Green Alga _Raphidocelis subcapitata_
###### Abstract  
Lincomycin (LIN), as a waterborne contaminant, may pose a threat to algal health and may affect the provision of ecosystem services. In addition, the molecular mechanisms of limomycin in algae are still unknown. Here, we attempted to use the transcriptome analysis to elucidate for the first time the potential impact of LIN at an environmentally relevant concentration on the algal growth, and verify the hypothesis that limomycin can disrupt algal protein synthesis by combining with its subunits of ribosome at high-LIN level. In this study, 7-day growth inhibition tests and RNA-seq sequencing were conducted in _Raphidocelis subcapitata_ (_R. subcapitata_) in response to a LIN at the concentrations of 0.5 \(\mathrm{\SIUnitSymbolMicro g}\) L\({}^{-1}\) (low), 5 \(\mathrm{\SIUnitSymbolMicro g}\) L\({}^{-1}\) (medium), and 400 \(\mathrm{\SIUnitSymbolMicro g}\) L\({}^{-1}\) (high) treatment groups. A negligible influence on algal growth and merely 21 (21 up- and 0 downregulated) differentially expressed genes (DEGs) was observed at low concentration of LIN, and medium groups showed a 13.4% inhibition and 92 (64 up- and 48 downregulated) DEGs, while high-LIN dosing caused 65.4% reduction in algal growth and 2514 (663 up- and 1851 downregulated) DEGs. In 0.5 and 5 \(\mathrm{\SIUnitSymbolMicro g}\) L\({}^{-1}\) groups, LIN upregulated the genes in the process of photosynthesis consisting of photosynthesis-antenna proteins, and porphyrin and chlorophyll metabolism pathways, suggesting that photosynthesis at low LIN exposure was more sensitive than algal growth. Whereas DEGs in the 400 \(\mathrm{\SIUnitSymbolMicro g}\) L\({}^{-1}\) group were mostly enriched in carbohydrate, carbon fixation in photosynthetic organisms, and nucleotide metabolism pathways. Furthermore, genes involved in detoxification processes were nearly downregulated in high-LIN group. In addition, genes encoding the antioxidant enzymes in the peroxisome pathway such as superoxide dismutase (_sod2_), peroxin-2 (_pex2_), 2,4-dienoyl-CoA reductase ((3E)-enoyl-CoA-producing) (_decr2_) were upregulated, which are responsible for deleting extra intracellular reactive oxygen species (ROS) caused by LIN to protect algal health, suggesting the occurrence of oxidative stress. Taken together, this is the first meticulous study unraveling the molecular mechanism of antibiotics in algae.  
RNA-seq; antioxidant system; detoxification; carbon fixation; growth inhibition +
Footnote †: journal: Applied Sci. 2020, 10, 8565; doi:10.3390/app10238565
## 3 Results and Discussion
At small distances/early times, there might, however, be an additional contribution from long-range interactions during Auger decay, which can have a distance-dependent effect on the DOFS, even at separations of several angstroms substantially beyond the van der Waals radii [16]. Future experiments with improved time resolution can easily investigate this early phase of photofragmentation. This should allow us to follow the reduction in DOFS during separation of the fragments in real-time and provide important information about the nature of the fragmentation process. \begin{table}
\begin{tabular}{c c c c c} \hline
**Delay (fs)** & **Peak 1, Distance** & **Peak 2, Distance** & **Peak 3, Distance** & **Model, Distance** \\  & **(Å)** & **(Å)** & **(Å)** & **(Å)** \\ \hline
380 & - & - & 21 \(\pm\) 3 & 17 \\
580 & - & - & 36 \(\pm\) 9 & 27 \\
770 & 48 \(\pm\) 16 & 24 \(\pm\) 4 & 48 \(\pm\) 16 & 35 \\
960 & 72 \(\pm\) 36 & 72 \(\pm\) 36 & 144 \(\pm\) 144 & 44 \\ \hline \end{tabular}
\end{table} 
Table 1: Fragment distances calculated based on the transient peak shifts in the Auger electron spectra and a Coulomb interaction. The confidence intervals are calculated assuming a constant error in relative peak position of 0.1 eV. For comparison, the expected distances under the model assumption of one-dimensional fragmentation that the entire absorbed excess energy is transformed into kinetic energy are included.
###### Abstract  
We propose a method to reconstruct a 3D coordinate system and a vascular map for the operation of magnetic medical robots (MMRs) controlled by a magnetic navigation system (MNS) using two 2D X-ray images and four corners of an MNS. Utilizing the proposed method, we calculated the relative rotation angle of a C-arm considering its rotational precision error. We derived the position information and 3D coordinate system of an MNS workspace in which the magnetic fields are generated and controlled by an MNS. The proposed method can also be utilized to reconstruct vascular maps. Reconstructed vascular maps are in the 3D coordinate system of the C-arm and can be transformed into the 3D coordinate system of an MNS workspace to generate the magnetic flux density with the desired direction and magnitude at the position of the MMR. The proposed method allows us to remotely and precisely control the MMR inserted into the vessel by controlling the external magnetic field. The proposed method was validated through in vitro experiments with an MNS mock-up and a vascular jig. Finally, the proposed method was applied to in vivo experiments where the MMR was inserted into the superficial femoral artery of a mini pig to remotely control the motion of the MMR. This research will enable precise and effective control of MMRs in various medical procedures utilizing an MNS.  
3D real-world coordinate; C-arm X-ray device; endovascular intervention; magnetic medical robot; magnetic navigation system Article
## 4 Numerical Simulations and Discussions
### Communication Process with Noise  
In this section, the noise is added with \(A=50\) and \(D=0.5+0.1j\). The CMPDFS process is demonstrated in Figure 7. The actual transmitted signal \(s^{\prime}(t)\) can entirely cover up the message signal \(H(t)\), and \(H_{g}(t)\) is recovered without distortion. The projection diagrams of \(L1\) and \(L2\) are presented in Figure 8 and the state variables are presented in Figure 9.  
For comparison, the same noise was added using the same parameters and processed with traditional chaotic masking based on CS. The process is presented in Figure 10. Here,  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**D** & \(max(Dy_{1})^{r}\) & \(max(Dy_{1})^{i}\) & \(10,000*E_{H^{r}}\) & \(10,000*E_{H^{i}}\) \\ \hline \(10+10j\) & 119.2935 & 615 & 6.7627 & 92.8656 \\ \(10+j\) & 211.2523 & 392.0710 & 7.6200 & 46.0385 \\ \(10+0.1j\) & 244.3068 & 369.7529 & 10.8091 & 42.2822 \\ \(1+j\) & **11.9294** & 61.5253 & **0.1927** & 2.4379 \\ \(1+0.1j\) & 21.1252 & 39.2071 & 0.3279 & 1.7356 \\ \(0.5+0.1j\) & 8.7262 & 20.8434 & 0.2395 & 1.1375 \\ \(0.1+0.1j\) & 1.1929 & 6.1525 & 0.2062 & 0.7844 \\ \(0.1+0.02j\) & 1.7452 & 4.1687 & 0.2184 & 0.7573 \\ \(0.01+0.02j\) & 0.4866 & **0.8632** & 0.2128 & **0.6959** \\ \hline \hline \end{tabular}
\end{table}
Table 2: The sum of error square with different \(D\).  
Figure 6: The CMPDFS process without noise when \(D=0.1+0.1j\).
## 3 The Proposed Optimization Hybrid Algorithm
### OPF Problem Solution in the Presence of WT and PV Units
#### 4.2.2 Case 8: Minimizing Generation Cost in the Presence of WT and PV Units with the Carbon Tax  
Carbon tax (\(C_{tax}\)) is assumed on emissions, so the application of clean energy like WT and PV units is encouraged. The emission cost can be mathematically expressed as follows [19]:  
\[C_{E}=C_{tax}E \tag{54}\]  
\[J_{8}=J_{7}+C_{tax}E \tag{55}\]  
\(C_{tax}\) is estimated to be USD 20 per tonne [19].  
Table 12 lists the OPF results obtained by estimating the output power of WT and PV units while considering a carbon tax. As one can be observed, the suggested TLTFWO gives more suitable solutions and results than both TFWO and TLBO. In the case of applying the carbon tax, both WT and PV units produce higher amounts of output power.  
Figure 11: Convergence trends for Case 7.  
Moreover, Figure 12 illustrates the convergence characteristics of the discussed methods. As is seen, the suggested TLTFWO is superior to other algorithms in terms of convergence to the global optima with less number of iterations than TFWO and TLBO. So, one can choose TLTFWO for more complicated OPF problems when stochastic variables like intermittent output power of WT and PV generating units are considered.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Variables** & **TFWO** & **TLBO** & **TLTFWO** \\ \hline \(P_{G1}\) (MW) & 123.11028 & 123.50416 & 123.32853 \\ \(P_{G2}\) (MW) & 31.9607 & 33.0291 & 32.5297 \\ \(P_{us1}\) (MW) & 45.4523 & 46.0158 & 45.7041 \\ \(P_{G3}\) (MW) & 10 & 10 & 10 \\ \(P_{us2}\) (MW) & 38.2959 & 38.7483 & 38.5267 \\ \(P_{ss}\) (MW) & 39.8618 & 37.4806 & 38.629 \\ \(V_{G1}\) (p.u.) & 1.0696 & 1.071 & 1.0697 \\ \(V_{G2}\) (p.u.) & 1.0561 & 1.0514 & 1.0561 \\ \(V_{G5}\) (p.u.) & 1.035 & 1.1 & 1.0954 \\ \(V_{G8}\) (p.u.) & 1.0686 & 1.1 & 1.0402 \\ \(V_{G11}\) (p.u.) & 1.1 & 1.1 & 1.0985 \\ \(V_{G13}\) (p.u.) & 1.0514 & 1.0594 & 1.054 \\ \(Q_{G1}\) (MVAR) & \(-3.21843\) & 12.1278 & \(-2.96534\) \\ \(Q_{G2}\) (MVAR) & 10.7334 & \(-20\) & 4.09265 \\ \(Q_{us1}\) (MVAR) & 22.2319 & 35 & 35 \\ \(Q_{G3}\)(MVAR) & 40 & 40 & 32.6276 \\ \(Q_{us2}\) (MVAR) & 30 & 30 & 30 \\ \(Q_{ss}\) (MVAR) & 15.9599 & 18.8826 & 16.9538 \\ Fuelvlvcost (USD/h) & 424.8316 & 429.4076 & 427.2849 \\ Wind gen cost (USD/h) & 256.9048 & 260.5086 & 258.6126 \\ Solar gen cost (USD/h) & 112.2470 & 103.7997 & 107.3181 \\ Total Cost (USD/h) & 793.9835 & 793.7159 & 793.2156 \\ Emission (t/h) & 0.87057 & 0.89030 & 0.88144 \\ \(J_{8}\) & 811.3949 & 811.5219 & 810.8444 \\ Power losses (MW) & 5.2809 & 5.3780 & 5.3180 \\ V.D. (p.u.) & 0.46214 & 0.49157 & 0.47299 \\ Carbon tax (USD/h) & 17.4114 & 17.806 & 17.6288 \\ \hline \hline \end{tabular}
\end{table}
Table 12: The variables’ optimal values obtained for Case 8.
## 4 Validation and Error Analysis of Extracting Transmission Characteristics
### Experiment Validation
#### 4.1.2 Multi-Traces Validation  
A multi-trace structure is shown in Figure 13. There are six traces printed on a 1.6 mm thick FR4 (\(\varepsilon_{r}=4.3\)) substrate board. On the bottom of the substrate board, a ground was placed, forming microstrips with the upper traces. The board is 100 mm \(\times\) 100 mm in size. Six through-hole SMA connectors with an equal interval of 8.8 mm were soldered at both edges of the board and connected by parallel corners traces, respectively. A coupling zone in the center of the board was formed by traces routed side-by-side with 0.5 mm of clearance, and the width of each trace was 0.76 mm. When the board was placed on the test platform shown in Figure 6, various signals were injected through the ports on one side, creating an interference environment.  
Figure 11: The compared results between the transmission characteristics of a corner trace and a via trace with the proposed method and those obtained using a VNA.  
Figure 12: The extracted transmission characteristics of a corner trace and a via trace measured using proposed method and their trends compared with those obtained using a VNA.  
To analyze the issue simply, we selected three traces for signal injection. Trapezoidal waveforms of 70 MHz, 200 MHz, and 130 MHz were injected into the printed traces through port 3, port 5, and port 7, respectively. The probe was positioned 0.5 mm vertically above port 6; the transmission characteristics from port 5 to port 6 were calculated. Firstly, the fundamental frequencies were obtained by using the method introduced in Section 3.2. Secondly, we scanned the three traces to determine which fundamental frequency had the highest amplitude when the probe was above port 6, and then we identified the signal transmitted on the trace. Finally, the transmission characteristic was calculated according to the identified signal by the proposed method. Figure 14 shows the spectrum measured above port 6, as well as the harmonics of signal transmitted from port 5 to port 6. The transmission characteristic of the trace from port 5 to port 6 obtained by the proposed method and smoothed by wavelet packet were compared with measured by a VNA in Figure 15. The analysis results indicate that the calculation results of this paper are in good agreement with the VNA data. The mean variation and maximum error are 2.78 dB and 4.22 dB at 10.4 GHz, respectively.  
Figure 14: The spectrum measured above port 6 and the harmonics of signal transmitted from port 5 to port 6.  
Figure 13: The multi-trace-validated structure.