esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Results and Discussion
### Serial-Parallel Register  
The serial-parallel register works in such a way that the state from the input is sent through all outputs in turn. In this way, in a register of, e.g., 4 bits, 4 outputs show subsequent states appearing at the input during the last 4 rising edges given to CLK. During the experiments, only a table describing the system consisting of 16 sets of data was allowed to obtain satisfactory results. Each of these 16 sets represented a situation consisting of 7 consecutive input and output states for each possible sequence of four bits of data fed to the input of the system. Since the entire table consists of 7*16 rows, Table 8 shows only an example of one of the 16 data sets presenting the situation when the input contains the sequence 1011 and the final 00. One of the obtained results (\(number\_columnsCGP=10\), set of functions: JK, AND, OR, NOT) represents the genotype:  
*([1]3 0 0), *([2]0 0 1), *([3]3 2 2), ([4]0 1 1), *([5]0 2 3), *([6]3 5 1), *([7]0 5 6), *([8]3 7 1), *([9]0 7 8), ([10]0 8 9), 9 7 5 2 representing the circuit shown in Figure 13. As you can see, this is a classic diagram of a 4-bit series-parallel register. For comparison, the genotype:  
[1]3 0 0), ([2]0 1 0), *([3]1 0 0), ([4]1 0 2), ([5]0 4 4), *([6]1 3 0), *([7]1 6 5), *([8]1 7 6), 8 7 6 3 shows the circuit shown in Figure 14, which was created using the parameter  
\(number\_columnsCGP=8\) and an extended set of flip-flops JK (function type 0), D (function type 1), T (function type 2) and AND gates (function type 3), OR (function type 4) and NOT(function type 5). The D flip-flop in the diagrams will be represented as a JK with a small NOT gate going from the J input to the K input. The T flip-flop in the diagrams will be represented as a JK with the J and K inputs connected. For comparison, this circuit was obtained after 117 generations and the previous one after 8236 generations. As expected, it can be seen that expanding the number of function types makes it much easier to find the correct solution. Additionally, after reducing the number of CGP columns to 6, only the result consistent with Figure 14 was obtained.  
Figure 12: Example of a layout obtained based on Table 7. This is a classic parallel register layout. All systems obtained using Table 7 and the adopted parameters were of this form.
## 2 Problem Description
### Model Conversion and Control Objective  
The nonlinear dynamic model of FAHV (1) can be written as the following matrix form:  
\[\begin{array}{l}\dot{x}\approx f(x)+g(x)u\\ y=x\\ z=Cx\end{array}. \tag{4}\]  
where \(y\) is the measurable output and \(z\) is the controlled output.  
\[f(x)=\begin{bmatrix}\frac{\overline{\eta}S(C_{T}(\alpha)+C_{T}^{2}(\eta))\cos \alpha-\overline{\eta}SC_{D,\alpha,\beta}(\alpha,\eta)}{m}-g\sin\gamma\\ \frac{\overline{\eta}SC_{L,\alpha,\beta}(\alpha,\eta)+\overline{\eta}S(C_{T}( \alpha)+C_{T}^{2}(\eta))\sin\alpha}{mV}-g\cos\gamma\\ Q-\frac{\overline{\eta}SC_{L,\alpha,\beta}(\alpha,\eta)+\overline{\eta}S(C_{T} (\alpha)+C_{T}^{2}(\eta))\sin\alpha}{mV}+g\cos\gamma\\ \frac{\overline{\eta}S(C_{T}(\alpha)+C_{T}^{2}(\eta))+\overline{\eta}SC_{M, \alpha,\beta}(\alpha,\eta)}{i\eta}\\ -2\zeta_{1}\omega_{1}\dot{\eta}_{1}-\omega_{1}^{2}\eta_{1}+N_{1}(\alpha,\eta) \\ \dot{\eta}_{2}\\ -2\zeta_{2}\omega_{2}\dot{\eta}_{2}-\omega_{2}^{2}\eta_{2}+N_{2}(\alpha,\eta) \\ \dot{\eta}_{3}\\ -2\zeta_{3}\omega_{3}\dot{\eta}_{3}-\omega_{3}^{2}\eta_{3}+N_{3}(\alpha,\eta) \end{bmatrix}\]  
\[g(x)=\begin{bmatrix}\frac{\overline{\eta}SC_{T}(\alpha)\cos\alpha}{m}&-\frac {\overline{\eta}SC_{D,\beta}(\alpha)}{m^{3}}\\ \frac{\overline{\eta}SC_{T}(\alpha)\sin\alpha}{m^{3}}&\frac{\overline{\eta}SC _{M,\beta}(\alpha)}{m^{3}}\\ 0&0\\ -\frac{\overline{\eta}SC_{T}(\alpha)\sin\alpha}{m^{3}}&-\frac{\overline{\eta} SC_{M,\beta}(\alpha)}{m^{3}}\\ \frac{\overline{\eta}SC_{T}(\alpha)}{i\eta}&\frac{\overline{\eta}SC_{M, \beta}(\alpha)}{i\eta}\\ 0&0\\ 0&N_{1}(\delta)\\ 0&0\\ 0&N_{2}(\delta)\\ 0&0\\ 0&N_{3}(\delta)\end{bmatrix},\text{and}\,C=\begin{bmatrix}1&0&0&0&0&0&0&0&0 &0&0\\ 0&0&1&0&0&0&0&0&0&0\\ \end{bmatrix}\).  
The control objective is to design a control law so that the velocity \(V\) and the altitude \(h\) of the FAHV track given reference signals when the motion model of the FAHV is completely unknown.
## 2 Formation and Stability  
Atmospheric NPAHs are formed through two processes. The first is the primary formation that occurs during the combustion of organic matter, which allows for the electrophilic nucleation with NO\({}^{+}\) to form NPAHs. This depends on the combustion temperature, and the formation yield of NPAHs from PAHs increases with increasing combustion temperature [16]. Diesel and gasoline engines, coal combustion, biomass burning, and other industrial combustion processes are considered major sources. The [NPAH]/[PAH] concentration ratios in emitted particulates differ significantly in these sources depending on combustion temperature. As described in Section 4, this fact was effectively used for the development of a new source analysis method. The second is the gas phase reaction in theatmosphere with parent PAHs in the presence of radicals such as the -OH\({}^{-}\), \(\cdot\)NO\({}_{3}\)\({}^{-}\) radicals and NO\({}_{2}\)[17]. In addition, several metal ions also play important roles in the secondary formation of NPAHs [18]. Nitration of several PAHs is accelerated in the atmosphere when the concentration of Asian dust is high [19]. Although PAHs and several derivatives were degraded by photo radiation [20; 21; 22], the stability of NPAHs in the environment is not clear.  
2-Nitrofluoranthene (2-NFR) and 2-NP are formed from fluoranthene (FR) and pyrene (Pyr), respectively, through secondary atmospheric processes. Their concentrations increase in the atmosphere, several hours later than those of their parent PAHs [23; 24]. The total concentrations of primary formation NPAHs in the air are usually much lower than those of PAHs. However, concentrations of secondary formed NPAHs are often higher than those of primary formation NPAHs. The primary and secondary formation results in nitration at differing positions on the PAH molecule. Considering that NPAHs are more mutagenic than PAHs, it is important to understand to what extent biological activity is determined by the position of nitration. Hence, source identification of NPAHs is essential to evaluate their health risks [16].  
The degradation of NPAHs in the environment is important because oxidative derivatives of PAHs, such as OHPAHs, QPAHs and hydroxy NPAHs, show different biological activities from NPAHs [4; 5; 6]. [Nap]/[1-NNap] and [Pyr]/[1-NP + 1-OHP], which significantly decrease with radiation, have been proposed as highly reliable post-emission stability indicators, showing chemical formations in the atmosphere [25]. The concentrations of secondary aerosol components, including sulphate, nitrate, and secondary organics, in aerosol particles increased sharply during heavy haze episodes in central China, suggesting these gasses and particle compounds act as the important contributors to aerosol pollution [26].
## 3 Results
### Human Fibro Blast Cell's Viability and Proliferation
(**b**) Cell proliferation rates analyzed by comparing the OD values on Days 2 and 3 (n = 3): control+ = 123.03%, control- = 58.76%, A1 = 141.43%, A2 = 140.54%, A3 = 131.10%, B1 = 141.23%, B2 = 139.18%, B3 = 143.11%, C1 = 141.62%, C2 = 146.69%, C3 = 144.28%, analyzed. Data are presented as the means \(\pm\) SDs, * \(p\) \(<\) 0.05, ** \(p\) \(<\) 0.01, *** \(p\) \(<\) 0.001. *** \(p\) \(<\) 0.0001 vs. positive control; ##### \(p\) \(<\) 0.0001 versus negative control. As the GO coating increased the surface energy and surface roughness of the PS film (Tables 2 and 3), it increased the cell culture efficiency by increasing the initial adhesion and proliferation rate of cells without requiring complex chemical treatment. Unlike the polystyrene film, the GO-coated PS film demonstrated no cytotoxicity and improved the cell compatibility with the vessel surface.
###### Abstract
This latest version of the demon algorithm, before searching for the DVF, smoothes the image by applying a Gaussian kernel at different levels, forming a blurring pyramid that eliminates noise in the voxels' intensity. Unlike the classic demon method, the updated domain is estimated at each iteration. The current transformation is measured by using a new rule that is updated between the exponential map of the updated domain and the previous estimate. The transformation describes the DVF between a fixed CT scan and another moving or displaced CT scan. To analyze the efficiency of the implementation, a moving version of the CT scan is estimated from the DVF calculated with the new version of the demon algorithm, and its similarity with the original moving CT scan is measured using performance measures. However, each DVF depends on three parameters: the variance of the smoothed kernel, the number of pyramid levels in the blur, and the number of iterations to update the domain, which must be defined each time; these parameters, in particular, have not been documented for breast CT scans. The goal of this work is to propose a contour-propagation algorithm based on demons and a heuristic algorithm based on local search, which finds the combinations of iterations, variance, and number of levels in the blur in the solution space that optimizes the performance measures: the correlation coefficient (CC) and the Dice similarity coefficients (DSC). Additionally, to show the linear relationship of the CC and DSC results. These algorithms contribute to calculating the optimal dose of radiotherapy for patients with cancer, given that a good contour avoids putting healthy organs at risk and optimizes the efficiency of the dose beam. Elastic image registration is especially challenging for volumes of interest that are large and subject to large nonrigid deformations over time. Good examples of such structures are the liver and the breast. Depending on the case, such structures might be considered to be organs at risk (that is, they are not the volumes to be treated but the dose should be calculated and minimized in such structures) or they might be considered target volumes to be treated. In any case an accurate registration is a prerequisite for an adequate radiation dose calculation. For this reason both the liver and breast are important organs in any radiotherapy treatment performed in the thoracic region. The paper is organized as follows: Section 2 describes the demon method and presents the respective parameters. Section 3 presents the results and analysis. Finally, the conclusions are presented in Section 4.
## 1 Introduction
In the present work, we used TiO\({}_{2}\) nanoparticles as a photocatalyst and studied the degradation efficiency towards single bentazon herbicide (BZ), Nile blue dye (NB), and herbicide and dye mixture (BZ + NB) under UV light and sunlight irradiation. To the best of our knowledge, this is the first work to report the high photocatalytic efficiency of TiO\({}_{2}\) towards such pollutants: with optimized conditions, 5 ppm contaminant concentration, pH 7, and catalyst loading of 20 mg, bentazon is 99% degraded in 40 min and Nile blue is degraded 100% in 160 min. The degradation of both pollutants in the BZ + NB mixture demonstrates that TiO\({}_{2}\) photocatalyst has the ability to degrade the pollutants simultaneously under UV and sunlight.
## 4 Design Optimization
### Design Space Exploration  
The sensitivity analysis provided crucial insights into the influence of design variables on valve performance. We leveraged this information to efficiently explore the design space and identify optimal configurations.  
Figure 9 illustrates the relationship between the \(R_{p}\)/\(R_{s}\) ratio and performance metrics. In Figure 9a, contact pressure reaches a maximum in the \(R_{p}\)/\(R_{s}\) range of 1.2-1.3, indicating the optimal operation window for the sealing mechanism. Simultaneously, Figure 9b  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Design Variable** & \
\begin{tabular}{c} **Influence on** \\ **Max. Contact Pressure (\%)** \\ \end{tabular} &
\begin{tabular}{c} **Influence on** \\ **Max. Equivalent Stress (\%)** \\ \end{tabular} \\ \hline \(R_{p}\) (mm) & 63.5 & 52.8 \\ \(R_{s}\) (mm) & 24.3 & 32.4 \\ \(e\) (mm) & 12.2 & 14.8 \\ \hline \hline \end{tabular}
\end{table}
Table 7: Influence of design variables on performance metrics.  
Sample #21 (\(R_{p}\)/\(R_{s}\) = 1.25) prioritized structural integrity with lower equivalent stress (164.65 MPa) at the expense of reduced contact pressure (142.80 MPa). This comparison underscores the inherent trade-off between sealing performance and durability, highlighting the importance of balancing these competing objectives in pursuit of an optimal design.  
To leverage the advantages of these design points, we conducted an optimization process utilizing kriging metamodeling. The resulting optimal design (\(R_{p}\) = 5.73 mm, \(R_{s}\) = 4.68 mm, \(e\) = 0.95 mm) features an \(R_{p}\)/\(R_{s}\) ratio of 1.22, aligning with the theoretically optimal point from a performance perspective.  
FEA validation revealed exceptional performance characteristics. As presented in Table 9, the optimal design achieved a contact pressure of 152.69 MPa and equivalent stress of 169.42 MPa, representing improvements of 3.66% and 2.07% over the metamodel predictions (147.30 MPa, 173.04 MPa), respectively. The error between metamodel predictions and FEA results remained below 5%, confirming the high accuracy of the kriging metamodel.  
The convergence of theoretical analysis and numerical results suggested that the optimal balance between low-pressure sealing performance and high-pressure durability was achieved within the \(R_{p}\)/\(R_{s}\) range of 1.2-1.25. These precise predictions and performance enhancements can be attributed to the nonlinear characteristics of Hertzian contact mechanics, effectively realizing the theoretical advantages of curved surface contact in ultra-high-pressure valve design.
# New Resorbable Membrane Materials for Guided Bone Regeneration
## 2 Collagen  
Collagen has been used as a resorbable membrane for GBR [11]. Collagen membrane has the advantages of low antigenicity, high biocompatibility, and excellent cell affinity, but pure collagen has the disadvantage of being difficult to handle due to a paucity of physical properties, and it is degraded quickly [12; 13; 14]. Cross-linking methods improve the physical properties of the collagen membrane and effectively extend the absorption time [12; 15; 16]. Among the chemical cross-linking agents, glutaraldehyde is the most widely used, but it has been reported to be cytotoxic [17; 18]. To overcome the drawbacks of this method, other cross-linking agents with low cytotoxicity have been developed. Diphenylphosphorylazide (DPPA) provides biocompatibility and good handling characteristics withoutany cytotoxic effects [19; 20]. 1-Ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC) cross-linked collagen membrane has a high resistance to enzymatic digestion and low cytotoxicity [21; 22]. Epigallocatechin-3-gallate (EGCG) cross-linked collagen membrane has better mechanical properties and anti-inflammatory effects [23; 24]. Several studies have reported changes in mechanical properties and outcomes of GBR by adding additives to collagen membrane (Table 1).
# Re-Visiting Acoustic Sounding to Advance the Measurement of Optical Turbulence
## 2 Materials and Methods
### Path Resolved Optical Turbulence Profiler for Comparative Reference  
The Delayed Tilt Anisoplanatism (DELTA) instrument shown in Figure 1 is a turbulence profiling system developed by MZA [23]. The DELTA system uses an 8-inch aperture to image a distant target onto a science camera. Images are captured at 100 frames per second. The system measures the differential motion, or tilts between pairs of feature points on the target as a function of their angular separation. The differential tilt variance between a pair of feature points is a path-weighted integral of \(C_{n}^{2}\). Figure 2 shows the target board used for DELTA measurements in the present work and weighting functions for differential tilt variances, corresponding to four different feature point separations on the target board. These weighting functions drop to zero at both ends of the path. Sub-apertureseparations have weighting functions with peaks closer to the source end of the path. Weighting functions for large separations have peaks closer to the aperture end of the path. The DELTA processing software uses the measured differential tilt variances for various separations, along with the corresponding weighting functions to generate turbulence profiles along the path. Turbulence values are typically reported in 10 bins distributed along the path. Frames captured during a three second window are used to generate a turbulence profile. Turbulence parameters such as Rytov number, Fried's coherence diameter, Scintillation index as well as crosswind speeds are calculated from this profile. The maximum operational range for a DELTA system is approximately two kilometers.  
When turbulence is strong, the feature points on the target become blurry and can no longer be tracked as points. While trying to still track feature points, DELTA measures smaller differential tilt variances due to the blurring. This leads to an underestimation of \(C_{n}^{2}\) values during periods of strong turbulence. Since DELTA measures differential motion between feature points, the whole image shift, due to changes in the large-scale refractive index gradient, does not affect the measurements.
# Radiator Enablers for Wireless Communication Evolution
## 3 Radiators' Novel Technologies, Design, and Implementation Issues
### gMIMO
#### 3.1.3 Antennas Selection  
When it comes to selecting the right configuration to apply to a certain scenario, there are certain factors to be taken into consideration. For instance, in ultra-massive MIMO (UM-MIMO) systems operating at THz frequencies, uniform linear arrays (ULAs), uniform rectangular planar arrays (URPAs), uniform hexagonal planar arrays (UHPAs), and uniform circular planar arrays (UCPAs) provide high gain and spatial resolution while addressing channel sparsity and spatial non-stationarity (ref. [33]). Intelligent reflecting and intelligent transmitting surfaces (IRS/ITS) have emerged as critical enablers for mmWave and THz systems, requiring less energy and expandability by combining active and passive antenna elements to overcome propagation losses and expand coverage (refs. [33; 34]).  
For mobile scenarios, such as fixed-to-mobile (F2M) ultra-massive MIMO channels, adaptive configurations like distributed uniform linear arrays (DULAs) excel in managing user mobility while maintaining high capacity (ref. [32]). In static multi-user environments, beamforming strategies, employing fully and partially connected hybrid architectures, provide optimized alternatives between complexity and performance, enabling effective inter-user interference management (refs. [33; 34]). Furthermore, if wider coverage is desired, we can use the modular massive MIMO (mmMIMO), which works efficiently in lower frequencies (sub-1 GHz) (ref. [35]). Modular massive MIMO provides flexibility and expandability, facilitating deployment in dense urban settings where channel conditions vary significantly (ref. [35]). This type of MIMO design will be discussed later in more detail.
## 4 Analysis of Factors Influencing Anchoring Performance
### Anchorage Length of Grout Anchor Steel Bars  
Figure 10 compares load-displacement curves for specimens with various anchorage lengths of grout anchor steel bars. The observations are as follows:  
Figure 10: Load-displacement curves of specimens with different anchorage lengths of grout steel bar. (**a**) Specimen 40-B; (**b**) Specimen 50-B; (**c**) Specimen 60-B.  
(1) For anchorage lengths of 0.4 and 0.6 L\({}_{\text{ab}}\), the specimens do not experience a pronounced yield stage; bond anchorage failure occurs prematurely, accompanied by significant steel bar slippage or pull-out. At an anchorage length of 0.8 L\({}_{\text{ab}}\), bond channel penetration and specimen failure ensue post-yield upon experiencing slippage before reaching the ultimate state. When the anchorage lengths are 1.0 and 1.2 L\({}_{\text{ab}}\), which meet or exceed the minimum code-specified lengths, the specimens undergo a complete progression of elastic deformation, yielding, strengthening, and steel bar necking. The dominant failure mode is tensile failure, and minimal slippage occurs during failure, indicating enhanced bond anchorage performance.  
(2) In the case of the 40-B and 50-B specimens, when the anchorage length is less than or equal to the basic anchorage length, an increase in ultimate load correlates with increased anchorage length, significantly boosting bond anchorage performance. When the anchorage length reaches 1.2 L\({}_{\text{ab}}\), the ultimate load escalates, but the ultimate displacement at failure diminishes during the late stages of loading, culminating in tensile failure.
# Fatigue Behavior of Prestressed Concrete Beam for Straddle-Type Monorail Tracks
## 5 Conclusions  
Based on the above experimental investigations, conclusions can be drawn as follows:  
* The PC track beam for monorail behaved within the linear-elastic stage when subjected to repeated service loadings with the upper and lower limit of 39.97 kN and 348 kN, respectively. The displacement of midspan slightly fluctuates between 13.5 mm and 13.8 mm, indicating the good stiffness performance of the beam. The displacement predicted using the 3D finite element model which ignored the change of the stiffness is reasonably accurate compared with the measured results.
* No crack was observed throughout the test, even after 6,000,000 cycles of repeated loading, indicating the good crack resistance of the beam. As a fully PC beam, the specimen was conformed to the design intention and fabricated well.
* The distribution of concrete strain remained linear during the whole process of the test, which is consistent with the assumption of plane section. The strain of reinforcement is a little different from that of concrete at the same height, and the ratio of the latter to the former ranges from 0.95 to 1.03, which indicates that the bond between concrete and reinforcement performed well throughout the test.  
Conceptualization, H.W. and H.G.; Methodology, Q.P. and H.W.; Software, H.W. and Y.B.; Validation, H.G. and Y.B.; Formal Analysis, H.W. and H.G.; Investigation, Q.P. and M.Y.; Resources, Q.P.; Data Curation, M.Y.; Writing-Original Draft Preparation, H.W.; Writing-Review & Editing, H.W. and H.G.; Visualization, H.W. and Y.B.; Supervision, H.G.; Project Administration, Q.P.; Funding Acquisition, Q.P.  
The research described in this paper was financially supported by the National Natural Science Foundation of China (Grant Nos. 51508474 and 51108382), the Sichuan Science and Technology Program (Grant No. 2018 JY0294), and the Science and Technology Research and Development Plan of China Railway Construction (Grant No. 2014-C34).  
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, and in the decision to publish the results.