esa-sceva/satcom-chunk-collection huggingface dataset:
# The Potential of Visible and Far-Red to Near-Infrared Light in Glaucoma Neuroprotection
## 7 Existing Patents for Ocular Treatments Using Laser Red Light  
Currently, it is well known that, in vivo, LLLT leads to a significant improvement in visual acuity in adolescent and adult patients with amblyopia caused by anteropia or stragismus. This procedure is most effective when an area of the macula is irradiated through the conjunctiva from 1 cm distance for 30 s with a laser light (780 nm, 292 Hz, 1:1 duty cycle; 7.5 mW; spot area 3 mm, repeated on average 3.5 times) [60]. Moreover, two patentswere filed concerning LLLT. Specifically, the one by LumiThera describes a device and a method for non-invasive multi-wavelength photobiomodulation for ocular treatments [63] of symptoms of acute or chronic ocular syndromes, such as diabetic retinopathy, retinitis pigmentosa, glaucoma, age-related macular degeneration, central serous retinopathy, non-arteritic anterior ischemic optic neuropathy, and [PERSON]'s hereditary optic neuropathy; treatment is also provided to the eyelids, wrinkles, deratitis, viral and bacterial infections, and many more areas. Irradiance with multiple wavelengths is provided by multiple laser sources (25 nm to 900 nm pulsed at frequencies from 1 to 100 Herz, or from 100 Hz to 100 kHz for 1 millisecond up to 150 s). Furthermore, a method for treating visual system diseases is disclosed in this first patent. In the other one patent, which was sponsored by the Department of Defense Advanced Research Project Agency (USA), the aim was to restore vision after methanol toxicity. It is based on the use of LEDs developed by NASA and consists of (a) exposing a component of a patient's visual system to light treatment (wavelength between 630-1000 nm, 10-90 mW/cm for 1-3 min), and (b) observing the restoration of visual system function [64].
# Anthropometric Ratios for Lower-Body Detection Based on Deep Learning and Traditional Methods
## 4 Experimental Results
### Accuracy  
Table 5 summarizes the performance of different frameworks for lower-body detection with the proposed anthropometric ratios. It is clear that in the case of the sensitivity measure tested on the human image, the HOG-SVM framework again shows the highest performance among the traditional algorithms for detecting human images (72.22%), while \(V|_{Face}\) and \(V|_{Upper}\) can only achieve human detection with an accuracy of less than 36%. Regarding the deep learning techniques, OpenPose achieves higher sensitivity (99.73%) than the A-CNNs method (75.94%).  
On the non-human data set, all frameworks achieve a total specificity of more than 85% for detecting background images. The \(V|_{Face}\) method achieves the highest specificity (99.56%), while the specificity of HOG-SVM is the lowest (85.43%). For the deep learning methods, the specificity of A-CNNs (99.30%) is higher than that of OpenPose (86.09%). The specificity of OpenPose is decreased by its false positive detections on background images, as shown in Figure 22.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Method** & \multicolumn{3}{c}{**A-Traditional (\%)**} & \multicolumn{3}{c}{**Deep Learning (\%)**} \\ \hline Algorithm & \(V|_{Face}\) & \(V|_{Upper}\) & HOG-SVM & OpenPose & A-CNNs \\ \hline Sensitivity & 34.03 & 35.76 & 72.22 & 99.73 & 75.94 \\ \hline Specificity & 99.56 & 91.83 & 85.43 & 86.09 & 99.30 \\ \hline Accuracy & 74.09 & 70.04 & 80.30 & 95.82 & 90.14 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Performance of frameworks for lower-body detection with the proposed anthropometric ratios.  
Figure 22: Result of false positive detection using OpenPose method. Result of false positive detection using OpenPose method.  
An averaged accuracy of A-Traditonal methods is around 74.81%. The HOG-SVM algorithm also provides higher overall accuracy (80.30%) than the other traditional methods, while the accuracy of \(V|_{Face}\) is higher than that of \(V|_{Upper}\). In terms of deep learning, both the A-CNNs and OpenPose methods achieve overall accuracies of greater than 90%.
# Studies of Fracture Damage Caused by the Proppant Embedment Phenomenon in Shale Rock
## 4 Discussion  
Measurements were performed for a light ceramic proppant consisting of grains with size from 0.600 to 0.300 mm, with a low surface concentration of proppant of 2.44 kg/m\({}^{2}\) (several layers of proppant grains), and axial compression stress of 48.3 MPa for 6 hours at 70 \({}^{\circ}\)C. The average diameter of the proppant grains was 0.450 mm. The tested dry shale rock was characterized by:  
1. On the basis of the analyzed embedment profiles, it was concluded that 17.1% of the total surface was damaged by the proppant grains.
2. The total depth of proppant embedment in the fracture faces was 0.0254 mm.
3. The obtained width of the fracture was 1.489 mm, therefore 1.7% less than the maximum achievable fracture width, which could be 1.514 mm, for the specified test conditions.  
For the additionally simulated maximum fracture width (0.450 mm), corresponding to only one layer of the tested proppant, a decrease of the maximum fracture width by 5.6% was obtained. In this case, the depth of the proppant embedment of 0.0254 mm was used for the calculation. The final width of such packed fracture was 0.425 mm.  
The size of the fracture width determines the flow of hydrocarbons through the fracture packed with proppant grains to the wellbore.  
The tested dry shale rock allowed to maintain the width of the packed fracture in order for hydrocarbons to flow.  
Test results indicate that the developed method of measurement may be used for preliminary assessments when choosing the proppant type and fracturing fluid for hydraulic fracturing of unconventional reservoirs, especially shale rocks.  
Conceptualization, M.M., P.K., M.C., K.W. and R.M.; Formal analysis, M.M., P.K., M.C., K.W. and R.M.; Funding acquisition, M.M.; Investigation, M.M. and P.K.; Methodology, M.M.; Software, M.M.;  
Figure 15: Parameters of the fracture effectively packed with the proppant for shale rock packed with one layer of proppant (grains size from 0.600 to 0.300 mm).  
Supervision, P.K., M.C. and K.W.; Validation, M.M. and R.M.; Visualization, M.M.; Writing--Original Draft, M.M.; Writing--Review & Editing, P.K., M.C. and K.W.
## 4 Simulation Analysis and Performance Comparisons
system with a higher optimization method reduces the voltage drop and increases the voltage gain. The comparative analysis of existing converters with the proposed model is given in Table 4.  
The voltage and efficiency analysis of the HGBC-PVS system is represented in Figure 9a,b. The input power for the simulation analysis is varied from 10 to 100 W, with an incremental level of 10 W. The simulation outcomes are compared with the measured results. The measured results are always higher with the optimized method. As the input power increases, the respective efficiency and voltage gain of the HGBC-PVS system also increase. The converter ensures a lesser drop and higher voltage gain in all the simulation environments. Figure 8: (**a**) The voltage across switch analysis. (**b**) The voltage across diode analysis. Figure 9: (**a**) Voltage-gain analysis of the HGBC-PVS system. (**b**) Efficiency analysis of the HGBC-PVS system. The system output of the real-time system is denoted in Figure 10. The hardware components are shown, and the system uses optimized parameters. The output of the HGBC-PVS system is verified using the given high-gain DC-DC converters, reducing the system error, and the higher SoC is achieved using the optimized algorithm and parameters. The outcome is measured using Xilinx software for photovoltaic systems. The HGBC-PVS system is designed and analyzed in this section. The simulation outcomes in terms of voltage across the switch, diode, and current in the inductor, output, efficiency, and voltage gain are computed and compared with the measured results. The HGBC-PVS system with the optimization method reduces the voltage drop and current fluctuations and, thus, increases the system outcomes. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Converter** & \(\mathbf{C}\) & \(\mathbf{L}\) & \(\mathbf{D}\) & \(\mathbf{S}\) & \
\begin{tabular}{c} **Voltage** \\ **Gain** \\ \end{tabular} &
\begin{tabular}{c} **Efficiency** \\ \end{tabular} \\ \hline Boost [23] & 1 & 1 & 1 & 1 & \(\dfrac{D}{(1-D)}\) & 80\% \\ Cuk [24] & 3 & 2 & 2 & 1 & \(\dfrac{D}{(1-D)}\) & 85\% \\ SEPIC [25] & 3 & 2 & 1 & 1 & \(\dfrac{D}{(1-D)}\) & 88.82\% \\ Proposed & 4 & 4 & 3 & 1 & \(\dfrac{1+3D}{1-D}\) & 97.5\% \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Comparison with existing converters. Figure 10: System output of the real-time system.
## 4 Discussion  
Research on BPFs mainly aims for their application to wired and wireless communication systems. In addition, IPD technology is used to meet the high demands of modern communication equipment regarding micromachining. Moreover, GaAs, a high mobility material, is usually applied as a substrate because its process is more mature than most other processes, and there is no excess passivation film on the GaAs surface. Long transmission lines designed in the pattern improve processing precision, which further ensures the stability of the filter. In this study, a simple inductor-capacitor series equivalent circuit is used for analysis. Problems can be found in time in low-order circuit and be modified easily. Then, after repeated simulations and measurements, loss was reduced and a wide bandwidth was achieved. Finally, fabricated BPF was checked to confirm that there is no problem through the scanning electron microscopy images.  
Many studies have been focused on improving the performance of BPFs in recent years. Table 1 compares on-chip filters based on different processes with the proposed BPF, which provides higher performance with fewer metal layers than a low temperature co-fired ceramic BPF [8] or a glass IPD BPF [22]. The return loss above 20 dB of the proposed BPF indicates that almost no reflected signal occurs at the center frequency, and the best insertion loss was obtained among the compared BPFs [8; 21; 22; 23; 24; 25]. GaAs can provide better insulation and less signal loss than silicon substrate; in addition, the working power of GaAs is higher than glass [26]. A circular spiral pattern is used in series with the inductor, and the stability of the capacitance value is ensured by the simple structure in a limited space. A relatively high self-resonant frequency of the capacitor, which is approximately equal to 8.1 GHz, enables the capacitor to work over a wide frequency range. The overall size of fabricated chip is small, especially the circular structure that makes the short side more compact.  
Figure 5: Final processed on-chip BPF. (**a**) Scanning electron microscopy image of proposed BPF; (**b**) Simulated current density over proposed BPF.  
Figure 6: Simulation and measurement results: (**a**) Parameters S\({}_{11}\) and S\({}_{21}\); (**b**) Group delay.
## 2 Background
### ISO26262 for Road Vehicle Functional Safety  
ISO26262, published in late 2011, is an international standard concerned with functional safety of safety-related E/E systems within the automotive systems. The purpose of this standard is to constructs a framework to integrate functional safety activities into the development of safety-related E/E systems through providing guidance, recommendation and argumentation [6]. The stipulation of each new product to be state-of-the-art could be helped by putting forward suggestions on specific safety development processes and safety classifications.  
ISO26262 consists of 10 parts and the safety activities are mainly described in seven parts (from Part 3 to Part 9). Part 3 gives a clear explanation of the specific contents of the concept phase [6]:  
1. Item definition: the object of this process is to describe the functionality, interfaces between other items, the driver and the environment of an item. This step is the input of the HARA process.
2. The HARA process is made up of three steps: **(1)** Determine the hazardous events according to identified vehicle-level hazards, corresponding operational situations and operating modes. **(2)** For each identified vehicle-level hazard, the risk assessment framework of ISO26262 is applied: * The probability of exposure (E) to the operational situation is assessed. * Identify potential scenarios which can cause a crash. The severity (S) of the harm to the persons involved is assessed if the crash happened. * The controllability (C) of the vehicle and the operational situations is assessed. * Determine the automotive safety integrity level (ASIL) based on E, S and C according to ISO 26262 as shown in Figure 1. **(3)** The worst-case ASIL is assigned to the hazardous event.
3. SGs shall be determined for each identified hazardous event with its ASIL.
4. Functional safety concept: the most important objective of this step is the derivation of FSRs from the SGs, considering the system architectural design.  
Figure 1: Cont.
## 4 Calculation Results
### Exact Solution to Rotation Angle  
From Equation (47), the transcendental equation solved \(\theta_{b}\) is as follows  
\[\sqrt{\alpha}=K(\mu)-F(\phi,\mu) \tag{74}\]  
where  
\[F(\phi,\mu)=\int_{0}^{\phi}\frac{\mathrm{d}t}{\sqrt{1-\mu^{2}\sin^{2}t}} \tag{75a}\] \[K(\mu)=\int_{0}^{\pi/2}\frac{\mathrm{d}t}{\sqrt{1-\mu^{2}\sin^{2}t}} \tag{75b}\]  
\(F(\phi,\mu)\) is the first type of elliptic integral and \(K(\mu)\) is the first complete elliptic integral. Therein  
\[\phi=\arcsin\frac{1}{\sqrt{2}\mu} \tag{76}\]  
\[\mu=\sqrt{\frac{1+\sin\theta_{b}}{2}} \tag{77}\]  
According to Equations (53) and (73), the linear solution to the rotation angle at the free end with dimension \(1\) is:  
\[\Theta_{b}=\frac{\alpha}{\pi} \tag{78}\]  
It can be verified that the convergent region of the linear solution (78) is as follows if the relative error \(\Delta\leq 1\%\) is required.  
\[\alpha\in[0,0.33],\;\Theta_{b}\in[0,0.11], \tag{79}\]
Heavy metals constitute a group of elements characterized by high density and high toxicity even at low concentrations in the environment. According to the United States Environmental Protection Agency (EPA) compilation, 7 heavy metals--Pb, Cr, Zn, Cu, Cd, Hg, Ni and metalloid As--are listed to be most widespread heavy metals in the environment [8]. Simultaneously it should be underlined that Cu and Zn are essential micronutrients for plants needed for normal plant development [4]. These metals are also important for an adequate state of human health, because they play many functions in metabolic and physiological processes [20]. Therefore, often these metals are not perceived as a real threat to living organisms. However, an assessment of the potential transfer of Cu and Zn from soil to plants of consumer importance should be carried out even when the soil has an elevated metal content. According to the authors' knowledge, the current literature related to human health risk appraisal of Cu and Zn is concentrated mainly on analyses of commonly consumed food products of both plant (fruit and vegetables) and animal (meat, dairy) origin. The knowledge of metal dietary intake and potential health risks in the case of plant-origin products is limited, especially for oat and amelina--plants which are not so popular in comparison to fruits and vegetables. These plants are not directly consumed (only plant seeds are processed into food as oil or flakes), so their cultivation on soils with elevated amounts of heavy metals is allowed. Although such soils are used for agricultural purposes, simultaneously they undergo remediation processes. Consequently, the objectives of the present study were to: (1) measure contents of Cu and Zn in cultivated crops such as amelina and oat; (2) determine the total and bioavailable amounts of Cu and Zn in soil; (3) calculate the bioconcentration factors (BCF), estimated dietary intake (EDI), and health risk (HRI) indices; and (4) evaluate the effect of applied immobilizing agents (compost and fly ash) on Cu and Zn contents both in plants and soil, as well as their influence on the calculated factors and indices.
## 3 Results and Discussion
### Structural Characterization of the Ga\({}_{2}\)O\({}_{3}\)-Shell
Because the Ga\({}_{2}\)O\({}_{3}\)-shell surrounds the GaN-core, during the EDX analyses, the electron beam is transmitted through the entire NWs (GaN plus Ga\({}_{2}\)O\({}_{3}\)), then causing an overlap of the core and shell EDX signatures. The observed blue dots of oxygen in the core area is thus a visual effect specific to the NW heterostructure configuration as we have already described in [64]. The EDX mappings reveal that the \(\beta\)-Ga\({}_{2}\)O\({}_{3}\) shell surrounds continuously the GaN-core, which is of crucial importance to integrating these kinds of heterostructures in gas sensors. EDX mappings evidence also the border between the core and the shell, which expresses the ripple interface of GaN/Ga\({}_{2}\)O\({}_{3}\) similar to ones observed by STEM (Figure 6). The thickness of the oxide shell extracted from EDX mappings is around 3-5 nm, this measurement being in good agreement with our estimations performed from SEM analyses (Figure 2). Figure 5: XRD analyses using in-plane Phi scan configuration of GaN/\(\beta\)-Ga\({}_{2}\)O\({}_{3}\) NWs with the detector (2 ThetaChi) fixed at 57.8\({}^{\circ}\) (**a**), 61.1\({}^{\circ}\) (**b**) and 64.3\({}^{\circ}\) (**c**) corresponding respectively to GaN (11-20), \(\beta\)-Ga\({}_{2}\)O\({}_{3}\) (020) and \(\beta\)-Ga\({}_{2}\)O\({}_{3}\) (403) peak positions.
## 3 EUV Spectra Analysis in the Plasma Recovery
### Suppression of Runaway Electron  
Figure 8 shows the time evolution of the runaway electron flux signal of two comparable discharges conducted before and after the lithium granule injection experiment in plasma recovery. The results indicate a significant decrease in the averaged runaway electron flux signal, with both the spike frequency and amplitude experiencing a dramatical reduction after the lithium granule injection.  
Figure 7: Time traces of spectral lines intensity with lithium granule injection (#84607, recovery discharge). (a) Li II 199.28 Å, He II 303.78 Å, O III 374.0 Å, and C IV 312.4 Å, (b) O IV 238.57 Å, O V 215.245 Å, and O VI 184.117 Å, (c) C V 40.268 Å, O VII 21.6 Å, C VI 33.734 Å, and O VIII 18.97 Å, (d) runaway electrons and ECE signal. Lithium granule entered plasma at t = 3.6 s in this discharge.  
The baseline of the runaway signal was extracted, and the averaged intensity during 3.0-6.0 s (at \(\rm I_{p}\) platform) was calculated to obtain the shot-evolution of runaway electron flux signal, as shown in Figure 9. Note that the data of #84604, #84608, and #84610 are missing due to disruptions.  
The energy spectra of runaway electrons at the \(\rm I_{p}\) platform (t = 5.0 s) for #84602 and #84611 are plotted in Figure 10. The peak energy of runaway electrons was maintained at \(\sim\)0.29 MeV. The intensity of the peak energy in #84611 decreased to 68% of the original level after the lithium granule injection, suggesting an effective suppression of runaway electron by the injection.  
Figure 8: Time evolution of runaway electron flux signal in two discharges before (#84602, blue line) and after (#84611, red line) lithium granule injection.  
Figure 10: Energy spectra of runaway electron at \(\rm I_{p}\) platform before (#84602, blue line) and after (#84611, red line) lithium granule injection.  
Figure 9: The averaged runaway electron flux signal during t = 3.0–6.0 s change in the discharges during lithium granule injection (#84602–#84611).
## 4 Performance Assessment
### Experiment  
#### 4.2.1 Experimental Setup  
To further assess the validity of the proposed method, the experiment was designed and carried out in an indoor pool with four sides covered with acoustic anechoic materials. The length, width, and depth of the pool were 45 m, 6 m, and 5 m, respectively. The bottom of the pool was covered with sand, and both the surface and bottom of the pool could reflect the acoustic signal. In the experiment, the transmit sensor deployed at 1.5 m below the surface was a hemispherical transducer, and the receive sensor placed at 2 m below the surface was a spherical hydrophone. The communication distance was 6.7 m. The experiment configuration is shown in Figure 7.  
The parameters used in the experiment are the same as those shown in Table 1. The transmit signal was organized in the packet structure consisting of the probe signal, the 100 ms guard time interval, and the FMT signal. The probe signal used for frame synchronization was a 50 ms and an 8-16 kHz  
Figure 6: The output mutual information (MI) of the proposed method for \(E_{b}/N_{0}=2\)dB: (**a**) and (**c**) the output MI of equalization; (**b**) and (**d**) the output MI of decoding.  
Figure 7: Experiment configuration.  
linear frequency modulated (LFM) signal with a hamming window. The FMT signal includes 1500 symbols and ahead 100 symbols were used to train equalizer coefficients. When the 8 PSK mapping scheme is used, time domain waveforms and frequency spectrums of the LFM signal with a hamming window and the FMT signal at the transmitter and the receiver, as shown in Figure 8. Time domain waveforms and frequency spectrums of the LFM signal and the FMT signal at the receiver are also shown in Figure 8 for comparison. The SNR at the receiver is 23 dB. In Figure 8, all time domain waveforms and frequency spectrums are normalized, and the received FMT signal is processed by frame synchronization.  
Two observations can be obtained from Figure 8. Firstly, the LFM signal and the FMT signal are obviously distorted by the multipath effect after passing through the UWA channel, and therefore ISI suppression technique must be used to deal with the ISI in the received FMT signal for good communication performance. Secondly, although the distortion appears in the frequency spectrum of the received FMT signal, the adjacent subbands still keep unoverlapping, and therefore each output subsequence of the FMT demodulator can be individually processed using turbo equalization.