esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Assessing the Health Risks Associated with the PTEs
#### 3.4.2 Carcinogenic Risks to Humans
\begin{table}
\begin{tabular}{c c c c c c c} \hline  & & **As** & **Cd** & **Cr** & **Ni** & **Pb** \\ \hline \multirow{4}{*}{CDI\({}_{\mathrm{ingestion}}\)} & \multicolumn{1}{c}{**Median**} & **Median** & **Median** & **Median** & **Median** \\  & Children & \(1.35\times 10^{-5}\) & \(1.54\times 10^{-7}\) & \(1.55\times 10^{-5}\) & \(4.20\times 10^{-5}\) & \(2.77\times 10^{-5}\) \\  & Adults & \(7.70\times 10^{-6}\) & \(8.79\times 10^{-8}\) & \(8.84\times 10^{-6}\) & \(2.40\times 10^{-5}\) & \(1.58\times 10^{-5}\) \\  & Children & \(3.78\times 10^{-16}\) & \(4.31\times 10^{-18}\) & \(4.34\times 10^{-16}\) & \(1.18\times 10^{-15}\) & \(7.78\times 10^{-16}\) \\  & Adults & \(1.13\times 10^{-9}\) & \(1.29\times 10^{-11}\) & \(1.30\times 10^{-9}\) & \(3.53\times 10^{-9}\) & \(2.33\times 10^{-9}\) \\  & Children & \(2.16\times 10^{-8}\) & \(2.46\times 10^{-10}\) & \(2.47\times 10^{-8}\) & \(6.72\times 10^{-8}\) & \(4.44\times 10^{-8}\) \\  & Adults & \(2.35\times 10^{-7}\) & \(2.68\times 10^{-9}\) & \(2.70\times 10^{-7}\) & \(7.32\times 10^{-7}\) & \(4.83\times 10^{-7}\) \\  & Children & \(2.02\times 10^{-5}\) & - & \(7.73\times 10^{-6}\) & - & - \\  & Adults & \(1.15\times 10^{-5}\) & - & \(4.42\times 10^{-6}\) & - & - \\  & Children & \(5.67\times 10^{-15}\) & \(2.72\times 10^{-17}\) & \(1.82\times 10^{-14}\) & \(9.89\times 10^{-16}\) & \(3.27\times 10^{-16}\) \\  & Adults & \(1.70\times 10^{-8}\) & \(8.14\times 10^{-11}\) & \(5.46\times 10^{-8}\) & \(2.96\times 10^{-9}\) & \(9.79\times 10^{-10}\) \\  & Children & \(7.89\times 10^{-8}\) & - & - & - & - \\  & Adults & \(8.59\times 10^{-7}\) & - & - & - & - \\  & Children & \(2.03\times 10^{-5}\) & \(2.72\times 10^{-17}\) & \(7.73\times 10^{-6}\) & \(9.89\times 10^{-16}\) & \(3.27\times 10^{-16}\) \\  & Adults & \(1.24\times 10^{-5}\) & \(8.14\times 10^{-11}\) & \(4.47\times 10^{-6}\) & \(2.96\times 10^{-9}\) & \(9.79\times 10^{-10}\) \\  & Children & & & \(2.90\times 10^{-5}\) & & \\  & Adults & & \(1.74\times 10^{-5}\) & & & \\ \hline \end{tabular} Note: “-” not available.  
\end{table} 
Table 8: Median values of carcinogenic risk indictors to humans from soil PTEs. risk. The PTEs in the soil around mining areas demonstrate considerable non-carcinogenic and carcinogenic risks for local inhabitants, and this has been verified by a previous study by analysis of a large number of soil data around the mining area [5]. Figure 8: The distribution of counter maps of the carcinogenic risks (TCR) and cumulative carcinogenic risk (CTCR) determined by inverse distance-weighted (IDW) interpolation.
## 1 Introduction
However, in the V2G distributed network, there is no such entity as all the involved entities (EVs) are of the same role. In order to sort out this issue, [PERSON] _et al._[22] presented the simultaneous existence of multiple vehicles as a whole group is verified by an aggregator (AG), while \"WINSmartEV\" project tracks-on the charging usage and the preference of EVs by a RFID-based scheme [23]. Thus, researchers must first observe the difference of the V2G system with other wireless networks when they design a protocol for the V2G system. In this paper, we provide a comprehensive overview of various security and privacy issues in the SG with focuses on mutual authentication, access control, and secure integration. The existing survey paper by [PERSON] _et al._[24] provides a comprehensive overview on device issues, networking issues, dispatching and management, and anomaly detection. Different from the existing survey, we also take into account the authentication issues in the HAN and the V2G network. Furthermore, we present the state of the art solutions to secure access control and integration in the SG. The following is a summary of our contribution in this work:  
1. We organize the requirements of mutual authentication and privacy preservation among various SG entities (devices, user, and network) and highlight the objectives for developing an efficient and secure authentication protocol for the SG. 2. We perform a critical analysis of the existing work. We observe that there is no such protocol that provides mutual authentication among HAN environments, energy providers (EP) and GW, and AMI network. 3. We discuss the V2G communication (using DR technology) requirement in comparison with VANET and RFID technology. Further, we perform a careful evaluation of existing literature in terms of efficiency and security. 4. We also summarize and explain the secure integration and authorization that is essential to further enhance the secure communication in the SG system. The rest of the paper is organized as follows: Section 2 discusses the requirement of mutual authentications in the SG network along with the existing authentication protocols. Section 3 discusses various available protocols for the V2G network. The existing authentication protocols considering authorization and integration in the SG are presented in Section 4 and Section 5, respectively. Section 6 highlights the current issues and future directions. Finally, Section 7 provides the conclusion of this work.
# Design and Multi-Objective Optimization of Fiber-Reinforced Polymer Composite Flywheel Rotors
## 3 Modeling
### Analytical Stress Calculation and Failure Prediction  
#### 3.4.1 Load Cases  
Rotor stresses are induced by rotation, temperature differences and press fits. During operation all of these effects together determine the total stress state in the rotor. Note that examining only the load case for operation is not sufficient. Therefore, as proposed in [13], three load cases are considered separately.  
The first load case represents residual stresses due to the curing process. Residual stresses can have a significant impact on the maximum allowable speed and are therefore not negligible. The larger the temperature difference between curing and operation the higher these stresses will be. Residual stresses also become increasingly critical for a rising ratio of the outer to inner rim radius. Rims that are thinner in radial direction are therefore preferable in order to lower the effect of residual stresses.  
The second load case considers stresses caused during press fit assembly. A press fit causes radial compressive stresses which counteract tensile stresses induced at high rotational speeds. This is generally a positive effect. By only determining the stresses during operation; however, it is not considered that rims can fail due to too high compressive stresses through the assembly process.  
Finally, the third load case describes the rotor stresses during operation.
## 6 TTL Estimation
### Results under \(L\)-Type Offset
#### 6.2.2 Impact of Lateral Offset  
Estimation results of different lateral offsets are shown in Figure 12 and Table 7, where the pointing angle noise level was set to \(0.1\,\mathrm{\SIUnitSymbolMicro rad}/\mathrm{Hz}^{1/2}\) and the angle biases we used are the same as in the previous subsection.  
It can be seen in Figure 12 that the levels of estimation error (black) of the four cases are similar except at high frequencies, similar to the corresponding results under the S-type offset in Figure 9. Therefore, similar conclusion can be drawn that the lateral offset is not of great significance for TTL estimation even if the longitudinal offsets are large when the angle noise level is as low as \(0.1\,\mathrm{\SIUnitSymbolMicro rad}/\mathrm{Hz}^{1/2}\).  
\begin{table}
\begin{tabular}{l c c c c c c} \hline \hline \multirow{2}{*}{**Lateral Offset**} & \multicolumn{6}{c}{**Coupling Factor**} \\ \cline{2-7}  & \(p_{\text{x,1}}\) (mm/rad\({}^{2}\)) & \(p_{\text{y,1}}\) (\(\SIUnitSymbolMicro\)/rad) & \(p_{\text{z,1}}\) (\(\SIUnitSymbolMicro\)/rad) & \(p_{\text{z,2}}\) (mm/rad\({}^{2}\)) & \(p_{\text{y,2}}\) (\(\SIUnitSymbolMicro\)/rad) & \(p_{\text{z,2}}\) (\(\SIUnitSymbolMicro\)/rad) \\ \hline (a) \(100\,\mathrm{\SIUnitSymbolMicro\SIUnitSymbolMicro m}\) & \(1475.1\pm 14.8\) & \(365.7\pm 2.7\) & \(-630.2\pm 14.7\) & \(1600.1\pm 12.7\) & \(-1257.3\pm 12.9\) & \(768.3\pm 9.7\) \\ (b) \(500\,\mathrm{\SIUnitSymbolMicro m}\) & \(1474.7\pm 14.8\) & \(-33.7\pm 2.7\) & \(-232.4\pm 14.7\) & \(1597.3\pm 12.8\) & \(-1654.1\pm 12.9\) & \(1162.8\pm 9.7\) \\ (c) \(2000\,\mathrm{\SIUnitSymbolMicro m}\) & \(1467.2\pm 15.3\) & \(-1532.1\pm 2.8\) & \(1271.4\pm 15.2\) & \(1580.5\pm 13.2\) & \(-3134.4\pm 13.3\) & \(2646.1\pm 10.0\) \\ (d) \(5000\,\mathrm{\SIUnitSymbolMicro m}\) & \(1447.4\pm 18.4\) & \(-4532.7\pm 3.3\) & \(4281.0\pm 18.3\) & \(1638.7\pm 15.9\) & \(-6186.3\pm 16.0\) & \(5669.5\pm 12.0\) \\ \hline \hline \end{tabular}
\end{table}
Table 7: Estimated TTL coupling factors under different lateral offsets (L-Type offsets).  
Figure 12: Input and estimated TTL error as well as their difference under different lateral offsets. (a) \(0.1\,\mathrm{mm}\); (b) \(0.5\,\mathrm{mm}\); (c) \(2.0\,\mathrm{mm}\); (d) \(5.0\,\mathrm{mm}\).
# Analytical Calculation Model of the TV3-117 Turboshaft Working Regimes Based on Experimental Data
## 7 Conclusions  
The objective of this paper is to provide a version of an analytical calculation model of working regimes and performance analysis for a free turbine turboshaft, useful for gas turbine engine education and several propulsion experimental applications. The paper work presents an analytical calculation model to determine the particular operating regimes of the TV3-117 MT turboshaft, at which are only known certain performances and some main engine parameters from the takeoff regime. The paper presents a first version of working regime model calculation, based on a limited data library, with relevant experimental data, from three different types of engines, as is the TV2-117A turboshaft, AI-20K turboprop, and the Viper 632-41 turbojet, following the engines run on the test bench. This current analytical calculation model, compared to some simulation software, does not require knowing the dimensional parameters or the performance map of the compressor and turbine, and does not work with kinematic parameters and works only with experimental parameters from engine regime variation analysis. The analytical calculation model has a validity rate of around 97% for regimes above 80% engine speed and a validity rate of around 85% for regimes between idle and 80% engine speed. The validity rate was determined by comparison of the calculated data with the engine manual data, which are the main reference. Similarity parameters have an approximate validity rate of around 90% because they do not have fixed constant values across different regimes. Experimental data processing demonstrated that they vary within narrow limits, which can be eventually reduced to constant values. In conclusion, by improving the data library, by adding more experimental data, and other extra similarly calculated coefficients, this model will be a powerful tool for performance prediction and off-design analysis.  
Conceptualization, R.M.C.; methodology, R.M.C.; software, R.M.C.; validation, R.M.C.; formal analysis, R.M.C.; investigation, R.M.C.; resources, R.M.C.; data curation, R.M.C.; writing--original draft preparation, R.M.C.; writing--review and editing, G.D.; visualization, G.D.; supervision, G.D.; project administration, R.M.C.; moreover, preparing the engines, instrumentation, the acquisition of parameters and testing, R.M.C. All authors have read and agreed to the published version of the manuscript.  
The Research was carried out under the \"Nucleu\" Program through The National Plan for Research, Development and Innovation 2022-2027, funded by the Romanian Ministry of Research, Innovation and Digitalization (MCID), Grant no. 31N/2023. The APC was funded by the Romanian Ministry of Research, Innovation and Digitalization (MCID) through project number PN23.12.01.02.  
Not applicable.  
Data Availability Statement: Data is contained within the article and in referenced papers.  
The authors declare no conflict of interest.
# Low-Power Wireless Data Transfer System for Stimulation in an Intracritical Visual Prosthesis
## 7 Conclusions  
The downlink for delivering stimulation data to a visual prosthesis was experimentally demonstrated. Commercial off-the-shelf coils were used, showing sufficient bandwidth. Power consumption at the implanted receiver was reduced by lowering the clock frequency by skipping redundant bits in the digitized received signal. The system meets the specified requirements.  
Although the system was demonstrated on a scaled-down version on a circuit board, the experimental results show everything is in order from a system point of view for a more compact, integrated design, together with the uplink system in future. This will wirelessly enable the visual prosthesis in a low-power and robust way.  
[PERSON] designed the communication system and circuits, performed the experiments, and wrote the paper. [PERSON] provided the initial idea of this research and is the project leader. [PERSON] revised and gave recommendations on the manuscript. All of the authors read and approved the final version of this paper.  
This research was funded by the Dutch Technology Foundation STW, which is part of the Netherlands Organization for Scientific Research (NWO), project 5 of the NESTOR program (P15-42).  
Not applicable.  
Data Availability Statement: Data is contained within the article tables and figures and are available on request.  
This research is supported by the Dutch Technology Foundation STW, which is part of the Netherlands Organization for Scientific Research (NWO), project 5 of the NESTOR program (P15-42).  
The authors declare no conflict of interest.  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l} ISM & Industrial, Scientific, and Medical \\ IC & Integrated Circuit \\ SAR & Specific Absorption Rate \\ NESTOR & NEuronal STimulation for Recovery of Function \\ BPSK & Binary Phase Shift Keying \\ PLL & Phase Locked Loop \\ FSK & Frequency Shift Keying \\ ASK & Amplitude Shift Keying \\ BER & Bit Error Rate \\ CMOS & Complementary Metal-Oxide-Semiconductor \\ SPST & Single Pole Single Throw \\ ADC & Analog to Digital Converter \\ \end{tabular}
## 4 Discussion
All patients underwent arthroscopic debridement and antibiotic treatment; additionally, most patients (8 patients) were treated with constant irrigation drains left in the joint for 4-7 days, and two patients underwent additional lavage [6]. Radiographic examination showed osteophyte formation in three patients, and joint space narrowing of the medial compartment in two others. To the best of our knowledge, our study is the first to report complex clinical, isokinetic and MRI evaluations of patients with SA after ACL-R treated with arthroscopic debridement and drainage, where the results were related to the other, healthy knee. To our knowledge, this is the first comprehensive isokinetic study to evaluate knee function after SA following ACL-R treatment in the available literature. Observations indicate that, due to the positive subjective evaluation of the treatment outcome, patients are not willing to engage in intensive and diligent exercise and rehabilitation to fully restore quadriceps and flexor muscle strength, despite a long follow-up period. Furthermore, studies have shown significant deficits in selected isokinetic parameters that may remain non-normalized throughout the patient's life. However, previous reports by [PERSON] indicate that with consistent rehabilitation and isokinetic training, normalization of function and strength of both flexor and quadriceps muscles is entirely possible [49]. The results of gait analysis further revealed that there are differences in dynamic and static loading of the operated limb, which should be considered as an independent risk factor for the early development of degenerative changes. Our experience indicates the high usefulness of monitoring body temperature, which is a reliable signal of infection development, provided the regime of avoidance of anti-inflammatory drugs that may falsify the measurement results. There are several limitations to this study that should be considered. The relatively small size of the study group did not allow for more precise statistical analysis. The complications studied are very rare, and it is difficult to collect an appropriate number of patients in a single center. Moreover, for a proper analysis of long-term outcomes, the evaluation should be performed at similar endpoints for each patient. The second limitation of our analysis may be the lack of a control group of patients who underwent primary ACL-R without SA. This would allow for more complete clinical and functional assessments and analyses. However, the main goal of our study was to demonstrate the positive effect of the proposed treatment of SA after ACL-R and its influence on reducing hospitalization time, cost of treatment and cartilage thickness changes in MRI evaluation. Although the number of patients studied prevented us from drawing far-reaching conclusions, the prospective nature of the study and the extent of comprehensive clinical assessment and MRI may be a valuable addition to our knowledge regarding the therapeutic options for SA after ACL-R and the prognosis of long-term outcomes.
## 3 Results and Discussions
### The Effect of Gravity and Device Orientation on Flow and Heat Transfer
These effects can be looked at from the point of view of temperature profiles shown in Figure 28. It can be seen that the orientation changes the temperature field depending on the location of the HHX, the direction of flow, and the resulting temperature-driven buoyancy effect. When the flow is moving in the positive direction (\(\phi 9\)), the effect of device orientation on the temperature profiles is more pronounced at the CHX. When the flow reverses (\(\phi 19\)), the effect appears to be more obvious at the location of the HHX. Natural convection effect at \(\phi 19\) for HHX is stronger than that at \(\phi 9\) for CHX because the 'hot plume' appears next to the HHX (as seen in Figure 13). This is congruent with the weak gravity effects on the heat flux at the CHX compared to the HHX as seen in Figure 27. Of course, at an orientation of \(270^{\circ}\) (dashed line), when the HHX is located below the CHX, the temperature between both the HHX and CHX increases due to the temperature-driven buoyancy effect. At an orientation of \(90^{\circ}\), presented by a dashed-dotted line, the temperature between the plates and hence the wall heat flux is lower because heat is driven away from the plates of the heat exchanger by the buoyancy effect. Figure 26: The effect of gravity and device orientation on the velocity profiles at a location \(15\) mm from the joint above the cold (CHX) and hot (CHX) plates for phases (**a**) \(\phi 19\) and (**b**) \(\phi 9\).
# Transmission Line Fault-Cause Identification Based on Hierarchical Multiview Feature Selection
###### Abstract  
Fault-cause identification plays a significant role in transmission line maintenance and fault disposal. With the increasing types of monitoring data, i.e., micrometeorology and geographic information, multiview learning can be used to realize the information fusion for better fault-cause identification. To reduce the redundant information of different types of monitoring data, in this paper, a hierarchical multiview feature selection (HMVFS) method is proposed to address the challenge of combining waveform and contextual fault features. To enhance the discriminant ability of the model, an \(\epsilon\)-dragging technique is introduced to enlarge the boundary between different classes. To effectively select the useful feature subset, two regularization terms, namely \(l_{21}\)-norm and Frobenius norm penalty, are adopted to conduct the hierarchical feature selection for multiview data. Subsequently, an iterative optimization algorithm is developed to solve our proposed method, and its convergence is theoretically proven. Waveform and contextual features are extracted from yield data and used to evaluate the proposed HMVFS. The experimental results demonstrate the effectiveness of the combined used of fault features and reveal the superior performance and application potential of HMVFS.  
fault-cause identification; transmission line; sparse learning; multiview learning; feature selection +
Footnote †: journal: Applied Sciences  
1
## 3 Experiments and Analysis
### Baseline Methods and Experimental Setup  
In this study, STFD was compared against several state-of-the-art methods, including single-frame local contrast-based methods (DNGM [17], TLLCM [18]), low-rank sparse decomposition-based methods (IPI [22], IMNNLWEC [23]), a temporal-based method (TVF [34]), a spatial temporal method (SSTLCM [37]), a segmentation-based method (FKRW [8]), and a deep learning-based method (UIUNet [33]). These eight methods represent a diverse array of detection strategies and have demonstrated strong performance in their respective domains, serving as a comprehensive benchmark for evaluating the effectiveness of STFD.  
All experiments were performed on an Ubuntu 20.04 system with an Intel Core i9-13900K CPU (5.8 GHz), 64 GB of RAM (Intel, Santa Clara, CA, USA), and an NVIDIA RTX 4090 GPU with 24 GB of memory (NVIDIA, Santa Clara, CA, USA).
## 4 Results
### Optimized Key Factors for Landslides  
Initially, the potential factors were reclassified in ArcGIS utilizing the natural breakpoint method, which was then overlaid with 80% of the slides and debris flows, respectively, to ascertain the key factors based on the \(Z_{CF}\) value (Table 1). The key factors for slides included elevation, slope, groundwater, LS factor, TWI, valley depth, and maximum precipitation, as evidenced by their \(Z_{CF}\) values exceeding 0. The regions with positive \(CF\) values had elevations below 3412 m, slopes between 10 and 40\({}^{\circ}\), groundwater yields >1 L/S, TWI values ranging from 7.3 to 8.7, 10.4 to 12.3, and 14.9 to 18.5, LS factors from 3.7 to 12.4 and 16.1 to 19.8, and maximum precipitation > 24 mm. Elevation, slope, relative relief, aspect, LS factor, distance to the river, and maximum temperature were the key factors for debris flows. Positive \(CF\) values were found in places with elevations between 4598 and 5523 m, slopes ranging from 30 to 60\({}^{\circ}\), relative reliefs from 34 to 79 m/km\({}^{2}\), north and northeast aspects, LS factor > 16.1, distance to rivers < 177.6 m, and maximum temperatures between 9 and 15 \({}^{\circ}\)C.  
Furthermore, the created random point tool was used to generate 200 non-slides and non-debris flows in the study area, which were then mixed with 80% of the slides and debris flows to produce slide and debris flow samples for the LR model. The key factors of the slides and debris flows were analyzed using a binary LR model of the SPSS-20.0 software ([[https://www.ibm.com/spss](https://www.ibm.com/spss)]([https://www.ibm.com/spss](https://www.ibm.com/spss)), accessed on 18 September 2024). The Sig values of the key factors were all less than 0.05, indicating that the binary LR model results met the 95% significance level test and were statistically significant (Table 1).  
Figure 6: Maximum temperature, maximum precipitation, and landslide distribution.