esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 The Influence of Structural Parameters on Synchronization and Stability  
In Section 3, the theoretical results regarding the synchronization and stability criterions of three CRs and an exciter were presented in their simplified form. Section 4 would serve to give numerical results on these points. This section focuses on the influence of the structure parameters on the synchronization and stability of the proposed vibrating system. For the vibrating system, the parameters are: \(m=360\) kg, \(r=0.05\) m, \(J_{m}=38.5\) kgm\({}^{2}\), \(k_{x}=254.5\) kN/m, \(f_{x}=1.366\) kN s/m, \(k_{y}=203.2\) kN/m, \(f_{y}=1.22\) kN\(\cdot\)s/m, \(k_{\psi}=183\) kN\(\cdot\)m/rad, \(f_{\psi}=0.375\) kN\(\cdot\)s/rad; for the induction motor (50 Hz, 380 V, 6 \(-\) pole, 0.2 kW, rated speed 980 rpm), the parameters are: \(R_{s}=40.4\)\(\Omega\), \(L_{s}=1.212\) H, \(R_{r}=12.5\)\(\Omega\), \(L_{r}=1.222\) H, \(L_{m}=1.116\) H, \(T_{\rm eN1}=2.01\) N\(\cdot\)m, \(f_{1}=0.005\).
## 4 Conclusions  
A series of NIR OPTs with distinct active layer configurations were manufactured. The absorption spectrum of the organic films and the electrical characteristics and air stability of the devices were measured. The results demonstrated that (i) the bilayer PHJ devices (Dev-B and Dev-C) have far superior photosensitive performance to the single layer ones (Dev-A) due to higher carrier mobility and light absorption of Dev-B and Dev-C than Dev-A; (ii) the bilayer PHJ ones with p-type channel (Dev-B) exhibit equivalent photosensitive properties to those with n-type channel (Dev-C) owing to stronger NIR absorption but lower exciton dissociation efficiency of Dev-B than Dev-C; (iii) Dev-B demonstrates much better air stability than Dev-C due to far superior stability of pentacene to C\({}_{60}\) in air; (iv) the tri-layer PHJ ones (Dev-D) possess better photosensitive properties (\(R\) of 1415 mA/W and \(P_{\rm max}\) of 1.2 \(\times\) 10\({}^{4}\)) than the bilayer PHJ ones with p-type channel (Dev-B), and the overall excellent photosensitive performance of Dev-D receives benefits from the merits of tri-layer PHJ structure including high light absorption, carrier mobility and exciton dissociation efficiency; and (v) the air stability of Dev-D is better than that of Dev-B; this can be ascribed to the passivation of the top-level C\({}_{60}\) layer, and the C\({}_{60}\) layer can effectively block O\({}_{2}\) and H\({}_{2}\)O molecules from permeating into the PbPc layer.  
Conceptualization, Y.H., Y.L. and Y.W.; methodology, Y.H. and Y.L.; software, Y.H. and L.Z.; validation, Y.H., Y.L. and Y.W.; investigation, Y.H.; writing--original draft preparation, Y.H.; writing--review and editing, Y.H. and Y.L.; visualization, Y.H. and L.Z.; supervision, Y.W. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the development of high photoelectric conversion efficiency Si_PEDOT:PSS: PSS heterojunction solar cells, Youth Science Foundation of Lanzhou Jiaotong University, grant number 2021025.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Data are contained within the article.  
Figure 6: Energy level diagram of (**a**) Dev-B and (**b**) Dev-D. Here, S and D are short for source and drain, respectively.  
**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.
## 3 HGV Tracking with Multiple Model Algorithms
### HGMM Tracking Algorithm  
Stimulated by the idea that adding a new model set which is close to the true model will improve the performance of multiple-model estimation [33], the HGMM estimator is developed using the hybrid grid to cover a large continuous mode space with a relatively small number of models at a given accuracy level.  
If the true mode is known and added to the model set, the estimator will converge to the true mode with probability 1, and the optimal state estimate can be obtained [34]. However, the true model is unknown actually, and a common way is to add the optimal mode estimate, which is statistically close to the true mode [35].  
In HGMM algorithm the model set about attack angle is a combination of a fixed coarse grid and an adaptive fine grid. Denote by \(A_{k}\) the adaptive fine grid and by \(M\) the fixed coarse subset. One cycle of HGMM algorithm consists of three steps: first, obtain the state estimate \(\widehat{X}\) based on \(M\); second, obtain the fine subset using the state estimate \(\widehat{X}\); and, third, run VSMM.  
Then the HGMM tracking algorithm can be demonstrated as follows:
## 3 Results  
The results of the study are presented as mean and standard deviation of torque, velocity and power of hamstring muscles during MIHE, MVHE, MIKF, and MVKF motor tasks. Table 2 reports the measurements of the maximum values of torque, velocity, and power obtained by averaging three successive trial values during the hamstring muscles exercises, as DINABANG gives the maximum value of these measurements for each motor task instance.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **Male** & **Female** & **Male + Female** \\ \hline
**Motor Task** & **Dominant** & **Non-Dominant** & **Dominant** & **Non-Dominant** & **Dominant and Non-Dominant** \\ \hline \hline  & \multicolumn{4}{c}{Maximum Torque (Nm/kg)} \\ \hline MIHE & 3.07 (0.75) & 2.90 (0.74) & 2.87 (0.62) & 2.77 (0.56) & 2.93 (0.68) \\ MVHE & 2.46 (0.57) & 2.34 (0.61) & 2.48 (0.49) & 2.42 (0.51) & 2.42 (0.54) \\ MIKF & 1.25 (0.33) & 1.19 (0.33) & 1.21 (0.15) & 1.16 (0.14) & 1.21 (0.27) \\ MVKF & 1.10 (0.29) & 1.06 (0.28) & 1.06 (0.14) & 1.03 (0.13) & 1.07 (0.23) \\ \hline  & \multicolumn{4}{c}{Maximum Velocity (\({}^{\circ}\)/s)} \\ \hline MVHE & 214.64 (40.56) & 212.38 (48.65) & 222.17 (29.09) & 218.16 (37.88) & 215.96 (39.69) \\ MVKF & 418.17 (86.38) & 408.52 (67.67) & 437.80 (41.28) & 414.16 (69.84) & 452.56 (79.72) \\ \hline  & \multicolumn{4}{c}{Maximum Power (\({}^{\circ}\)Nm/s.kg)} \\ \hline MVHE & 553.59 (227.55) & 527.81 (263.50) & 553.86 (141.43) & 535.30 (164.20) & 542.13 (209.27) \\ MVKF & 471.17 (236.65) & 438.38 (204.59) & 464.88 (77.49) & 432.65 (109.73) & 452.56 (179.73) \\ \hline \hline \end{tabular} Note 1: Values are given as mean (standard deviation). Note 2: Knee flexion motor tasks (MIKF and MVKF) involve only a concentric hamstring effort, while hip extension with an extended knee (MIHE and MVHE) involves hamstring and agonist muscles in a concentric effort. Torque and Power values are normalized by body mass in Nm/kg and \({}^{\circ}\)Nm/s.kg.  
\end{table}
Table 2: Normalized torque, velocity, and power of the hamstring muscles.  
Table 3 is the result of a multiple linear regression analysis of all data collected for this paper. Three dependent variables are displayed column wise, whereas the independent variables are shown line wise: gender, age, lateral dominancy, type of motor task and inclusion of agonist muscles in the movement.
# Artificial Intelligence-Based Autonomous UAV Networks: A Survey
## 3 Autonomous Features in UAV Networks
### Multiple Access and Routing Protocols
Another group of researchers focused on using code division multiple access (CDMA) [62; 63; 64]. On the other hand, orthogonal frequency division multiple access (OFDMA) is explored by some researchers [47; 65; 66], while some other research studies are conducted exploring space division multiple access (SDMA) [67; 68; 69; 70; 71; 72]. As we can only have a limited number of orthogonal communication channels, spectrum efficiency is reduced using this approach. To overcome the above-stated limitation of orthogonal multiple access techniques, much work is being performed using non-orthogonal techniques, mainly using joint optimization of the base stations (BSs), including power [73; 74; 75], trajectory [76; 77; 78], and placement [79; 80]. Although non-orthogonal multiple access techniques can perform better by covering many users with non-orthogonal yet correlated channels, however, there is a case when its performance can degrade exponentially, i.e., when the number of antennas is greater than the number of users scheduled. To avoid such circumstances, another effective technique is explored. Rate-splitting multiple access techniques for UAVs seem to overcome the problems of both orthogonal and non-orthogonal multiple access. Hence, many research studies have been conducted to explore what we can achieve using this technique. Most of the work in this area is based on the concept of the proposal of a joint rate among multiple UAVs to achieve the most optimal network solutions [81; 82; 83; 84; 85; 86].
## 1 Introduction
To broaden the energy harvest band and improve the energy harvest effect, the common methods are either to introduce magnetic nonlinearity or to combine two or more energy harvest mechanisms [32; 33; 34]. [PERSON] et al. [35] proposed a nonlinear magnetically coupled flutter energy harvester with a low wind velocity (about 1.0 m/s) and good energy harvesting characteristics in the low wind velocity range (1.0 m/s to 2.9 m/s). [PERSON] et al. [36] designed an energy harvester that combined the flutter energy harvest mechanism and electromagnetism into a single unit with a maximum output power of 0.550 uW. [PERSON] et al. [37] proposed a piezoelectric-electromagnetic composite energy harvester with a cylindrical blunt body fixed at the end of a piezoelectric cantilever beam, and a more compact and efficient energy harvest system by using the space inside the cylindrical blunt body to embed the magnetic coil. [PERSON] et al. [38] designed a new type of bluff body with rounded and folded corners to combine the vortex excitation and galloping vibration phases. The experimental results show that when the bluff body is half cuboid and half cylinder, its voltage output reaches 14.6 V. [PERSON] et al. [39] proposed a composite energy harvester that can capture vortex excitation and flutter energy at the same time. When the wind velocity is 14.48 m/s, its power density is 2.41 uW/cm\({}^{2}\). [PERSON] et al. [40] designed a composite electromagnetic energy harvester that uses cylindrical bluff body to induce wind belt vibration to capture energy, and experimentally studied the influence of Karman Vortex Street generated by different diameters and positions of cylindrical bluff body on wind belt vibration frequency and amplitude. The maximum output voltage of the energy harvester is 6 V.  
Vortex-excited flutter is currently a hot research topic for energy harvest using wind energy, but there are still problems of complex structure and low efficiency. The nonlinear energy harvester of Cylindrical blunt vortex excitation was investigated by [PERSON] et al. [41]. It was found that a maximum unrectified power of 0.21 mW could be obtained when the flow velocity was approximately 1.6 m/s. A hybrid energy harvesters containing two airfoil components have been investigated by [PERSON] et al. [27; 42]. Based on our previous works, the further investigation of a vortex-excited and flutter composite energy harvester is carried out. In this paper, an energy harvester with a cylindrical bluff body and two symmetrically distributed airfoil components attached to the end of a cantilever beam is proposed, which can simultaneously harvest energy for both vortex-induced vibration and flutter. The coupling effect between the two is investigated by conducting several groups of wind tunnel experiments to improve the output performance of the composite energy harvester.
## 4 Discussion
### Limitations and Strengths  
The main limitation of this study is that wrestlers were tested at the end of the competition season, and testing during different points of the season could lead to different results. Thus, a similar testing procedure should be conducted at several main points during the competition season (e.g., beginning, mid-season, and end of the season among the same wrestlers). Additionally, we included only male participants, so the results and conclusions from this study cannot be generalized to female participants. Moreover, the relatively small sample size does not warrant generalizations of the results, which means that similar future studies should try to include a larger number of athletes. Also, more direct parameters such as muscle oxygenation, maximal oxygen uptake, mitochondrial respiration, liver function test for determining the lactate clearance, and pulmonary function test, which could improve the understanding of the observed issue, were not conducted in this research, but are suggested to be evaluated in future studies.  
The main strength of this study is that cardiac, metabolic, and performance variables were recorded at several time points during the testing procedure, which helps to track the response of the athletes to the given effort. In this way, it was possible to determinein detail which parameters are decisive for optimal performance and which are the most important parameters for competitive success. Also, the strength of this research is that competitive-level wrestlers were included, as it is always challenging for researchers to include elite athletes.
## 4 Computational Validation
### Simulations Using the Quasi-Newton Formulation  
To demonstrate the effectiveness of the proposed bipolar power flow formulation based on the hyperbolic approximation of the relation between the voltage and power relations in the power balance equation, here, we use an approximated solution method known as the quasi-Newton approach, which consists of calculating the Jacobian matrix only one time and keeping it constant during the entire iteration process. To implement the quasi-Newton method, the power flow Formulas (15) and (26) take the following structures:  
\[V_{d}^{pn,t+1}=-\Big{[}G_{\text{exp}}^{pn}\left(V_{d}^{pn,0}\right)\Big{]}^{- 1}\begin{bmatrix}G_{ds}^{pn}V_{s}^{pn}+2\operatorname{diag}^{-1}\!\left(V_{d} ^{pn,t}\right)P_{d}^{pn}-\\ 2\operatorname{diag}^{-1}\!\left(\left(\mathbf{J}-\mathbf{M}\right)V_{d}^{pn,t}\right)P_{d}^{pn-np}\end{bmatrix}, \tag{27}\]  
where  
\[G_{\text{exp}}^{pn}\Big{(}V_{d}^{pn,0}\Big{)}=\begin{bmatrix}G_{dd}^{pn}- \operatorname{diag}^{-2}\!\left(V_{d}^{pn,0}\right)\operatorname{diag}\! \left(P_{d}^{pn}\right)-\\ \operatorname{diag}^{-2}\!\left(\left(\mathbf{J}-\mathbf{M}\right)V_{d}^{pn,0}\right)\operatorname{diag}\!\left(P_{d}^{pn-np}\right)\!\left(\mathbf{J}- \mathbf{M}\right)\end{bmatrix}\]  
and,  
\[V_{d}^{pon,t+1}=-\Big{[}G_{\text{exp}}^{pn}\Big{(}V_{d}^{pon,0}\Big{)}\Big{]} ^{-1}\begin{bmatrix}G_{ds}^{pn}V_{s}^{pon}+2\operatorname{diag}^{-1}\!\left( \mathbf{X}V_{d}^{pon,t}\right)P_{d}^{p}+\\ 2\operatorname{diag}^{-1}\!\left(\mathbf{Y}V_{d}^{pon,t}\right)P_{d}^{n}+2 \operatorname{diag}^{-1}\!\left(\mathbf{Z}V_{d}^{pon,t}\right)P_{d}^{p-n} \end{bmatrix}, \tag{28}\]  
Figure 6: Voltage behavior for the 85-bus grid considering a solidly grounded or non-grounded neutral wire.  
where  
\[G_{\text{exp}}^{pon}\left(V_{d}^{pon,0}\right)=\begin{bmatrix}G_{dd}^{pon}-\text{ diag}^{-2}\left(\mathbf{X}V_{d}^{pon,0}\right)\text{diag}\left(P_{d}^{p}\right) \mathbf{X}-\\ \text{diag}^{-2}\left(\mathbf{Y}V_{d}^{pon,0}\right)\text{diag}\left(P_{d}^{n} \right)\mathbf{Y}-\\ \text{diag}^{-2}\left(\mathbf{Z}V_{d}^{pon,0}\right)\text{diag}\left(P_{d}^{p- n}\right)\mathbf{Z}\end{bmatrix}\]  
The main advantage of keeping the Jacobian matrix constant for the solidly and non-solidly grounded cases corresponds to the possibility of calculating it and storing it to be used in the recursive power flow formula without making inversions each time, which makes the processing times required to solve the power flow problem minor in comparison with the time taken by the original power flow formulation. One of the main advantages of keeping the Jacobian matrix constant for the cases studied here (solidly and non-solidly grounded cases) corresponds to the possibility of calculating it one time and storing it as a constant in order to be used in the recursive power flow formula without making inversions at each iteration; this approach reduces the processing times required to solve the power flow problem, but it increases the number of iterations required for the convergence of the algorithm.
## 2 Theoretical Framework and Hypothesis Development
### Data Analysis  
The data analysis process consisted of two primary steps. First, Confirmatory Factor Analysis (CFA) and Structural Equation Modelling (SEM) were conducted using Jeffrey's Amazing Statistics Program 19.3.0 (JASP) to evaluate the measurement model's validity and reliability, and then structural relationships were examined, including mediation effects. Second, the IBM Statistical Package for the Social Sciences 23.0 (SPSS) was utilised to conduct descriptive statistics, including age, study level, and previous experience with HMD-VR technology.  
Measurement and structural model fit were assessed using multiple indices, following established guidelines [87; 88; 89]. The chi-square (\(\chi^{2}\)) test was used to evaluate the absolute model fit, with a non-significant result indicating an adequate fit. The relative chi-square (\(\chi^{2}\)/df) was deemed acceptable if below 3. Comparative Fit Index (CFI) and Tucker-Lewis Index (TLI) values above 0.90 indicate acceptable fit, with values above 0.95 indicating excellent fit. A Root Mean Square Error of Approximation (RMSEA) value below 0.08 suggests an acceptable fit, while values below 0.05 indicate a good fit. A Standardised Root Mean Square Residual (SRMR) value below 0.08 generally indicates a good model fit. With 11 items and a sample size of 84, the item-to-sample ratio was approximately 7.6:1, which is deemed adequate [90].  
Internal consistency was evaluated using Cronbach's alpha (\(\alpha\)) [91] and McDonald's omega (\(\omega\)) [92]. Cronbach's alpha values above 0.7 are considered acceptable, and values above 0.80 indicate good reliability. McDonald's omega values above 0.70 also indicate good reliability. All standardised item loadings should be statistically significant and exceed the minimum acceptable threshold of 0.5 [90].  
Convergent validity was assessed through Average Variance Extracted (AVE) and composite reliability (CR). AVE values above 0.5 indicate that the construct explains more than half of the variance in its indicators, while CR values above 0.70 suggest acceptable composite reliability [93; 94]. Discriminant validity was assessed using the Heterotrait-Monotrait Ratio (HTMT) criterion, where HTMT values below 0.85 suggest adequate discriminant validity [95]. Following the validation of the measurement model, SEM was employed to assess the relationship among latent constructs and examine the potential mediation effect.
## 4 Simulated and Measured Results
### Scattering Parameters  
Figure 13a shows the simulated and measured reflection coefficients at ports 1, 2, 3, and 4 for the 28 GHz and 38 GHz bands, while Figure 13b shows the transmission coefficients (mutual coupling) at all ports for the same bands. Good agreement is seen between the simulated and measured results for the four-element QMSIW antenna used for MIMO operation. The measured 10 dB return loss bandwidth at 28 GHz is approximately 2 GHz (26.5-28.5 GHz), and 1 GHz at 38 GHz (37.5-38.5 GHz). Figure 13b shows the lowest isolation levels among antenna elements, which are excellent at around 25 dB due to the use of the orthogonal arrangement of elements as well as the shorting vias between elements.  
Figure 14 shows the scattering parameter results of a four-element QMSIW antenna at 0.13 THz obtained using two different numerical methods: the finite difference time domain (FDTD) method using CST Microwave Studio and the finite element (FEM) method using Ansys HFSS. The results in Figure 14a are in good agreement, and the achieved impedance bandwidth of 10 dB is about 3 GHz (0.128-0.131 THz). Figure 14b shows that the isolation levels are above 20 dB for the 0.13 THz band without the use of any additional decoupling circuits. For brevity, only the strongest levels of mutual coupling parameters are presented in Figure 14b.  
Figure 12: Fabricated prototype of the proposed antenna. (**a**) Prototype before assembling connectors. (**b**) Prototype after assembling connectors.  
Figure 13: Scattering parameters at 28 GHz and 38 GHz. (**a**) Reflection parameters (**b**) Isolation parameters.  
Finally, Figure 15 shows the measured and simulated reflection parameters on the Port 5 antenna at 5.5 GHz. The measured reflection parameter has a wider bandwidth, which may be due to additional lengths of the SMA connectors that were not included during the calibration process. The simulation result shows a 10 dB impedance bandwidth of about 200 MHz (5.4-5.6 GHz), sufficient for 5.5 GHz WiFi applications. It is worth mentioning that the level of mutual coupling between the MMw four-port antenna and the Mw open-loop antenna (Port 5) is below \(-40\) dB, but these results are not presented for brevity. As a result, the isolation between the five antennas is high enough to allow them to radiate independently and simultaneously. Therefore, it can be concluded that this proposed antenna is potentially valid to work as a shared-aperture reuse-structure antenna based on the QMSIW cavity.
# Mechanical Properties of Cement Composites Using Modified Plastics by Gamma Irradiation
## 2 Materials and Method  
### Material properties  
#### 2.1.1 Physical Performance of Plastics  
In this study, a cement composite was manufactured by using ISO standard yarn for a basic aggregate and replacing plastic pellets in the form of aggregate. The plastic aggregates used for the experiment were shown in Figure 1, and it was supplied by the Korea Plastics Single Material Association. Based on previous studies, among plastic aggregate types, the reason of choosing PP is the occurrence of decomposition effects and, in the case of PE, a crosslinking phenomenon that occurs while there is no change in ABS when gamma-ray irradiation was applied. Each plastic has the lowest specific gravity of 0.92 in the case of PP, PE has a specific gravity of 0.94, and ABS has a high specific gravity of 1.04.