esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 LED Equalization  
As previously mentioned, the speed of transmission is limited to the LEDs low modulation bandwidth. Practically, the bandwidth is limited far beyond the theoretical 2 GHz [25] due to the lifetime of minority carriers in LEDs. In a previous work [24], we proposed a pre-equalization circuit (and blue filtering) that can extend the phosphorescent white LED bandwidth from 3 MHz to 325 MHz. The pre-equalization circuit is added to the LEDs driving circuit. A simplified VLC system block diagram, Figure 7, shows the placement of the circuit and blue filter. After carefully studying and analyzing the limitations of the circuit presented in Reference [24], it is observed that further bandwidth enhancement can be achieved.  
In this section, we first introduce the affiliated pre-equalization circuit, followed by our proposed design and its evaluation.  
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \multirow{2}{*}{
\begin{tabular}{c} **Bit** \\ **Rate** \\ \end{tabular} } & \multirow{2}{*}{\(\varnothing_{1/2}\)} & \multicolumn{2}{c}{**4 Arrays Model**} & \multicolumn{2}{c}{**9 Arrays Model**} & \multicolumn{2}{c}{**16 Arrays Model**} & \multicolumn{2}{c}{**25 Arrays Model**} & \multicolumn{2}{c}{**36 Arrays Model**} \\ \cline{3-11}  & & **BER** & **SNR** & **BER** & **SNR** & **BER** & **SNR** & **BER** & **SNR** & **BER** & **SNR** \\ \hline
30 & \(30^{\circ}\) & \(5.0\times 10^{-17}\) & 69.0 & \(2.7\times 10^{-17}\) & 70.2 & \(2.3\times 10^{-16}\) & 65.9 & \(6.1\times 10^{-17}\) & 68.6 & \(7.5\times 10^{-17}\) & 68.2 \\ Mb/s & \(70^{\circ}\) & \(1.6\times 10^{-15}\) & 62.1 & \(4.9\times 10^{-16}\) & 64.5 & \(1.7\times 10^{-15}\) & 62.0 & \(7.9\times 10^{-16}\) & 63.5 & \(9.0\times 10^{-16}\) & 63.3 \\ \hline
300 & \(30^{\circ}\) & \(1.3\times 10^{-12}\) & 49.0 & \(6.7\times 10^{-13}\) & 50.3 & \(6.0\times 10^{-12}\) & 46.0 & \(1.5\times 10^{-12}\) & 48.6 & \(1.9\times 10^{-12}\) & 48.2 \\ Mb/s & \(70^{\circ}\) & \(4.2\times 10^{-11}\) & 42.1 & \(1.3\times 10^{-11}\) & 44.5 & \(4.4\times 10^{-11}\) & 42.1 & \(2.0\times 10^{-11}\) & 43.6 & \(2.3\times 10^{-11}\) & 43.3 \\ \hline
3 & \(30^{\circ}\) & \(3.6\times 10^{-8}\) & 29.0 & \(1.9\times 10^{-8}\) & 30.2 & \(1.8\times 10^{-7}\) & 25.9 & \(4.5\times 10^{-8}\) & 28.6 & \(5.5\times 10^{-8}\) & 28.2 \\ Gb/s & \(70^{\circ}\) & \(1.3\times 10^{-6}\) & 22.1 & \(3.8\times 10^{-7}\) & 24.4 & \(1.4\times 10^{-6}\) & 22.0 & \(6.2\times 10^{-7}\) & 23.5 & \(7.1\times 10^{-7}\) & 23.3 \\ \hline \end{tabular}
\end{table}
Table 9: Minimum bit error rate (BER) and its corresponding signal to noise ratio (SNR) for the five configurations.  
Figure 7: The simplified visible light communication (VLC) system block diagram.
Application-Oriented Study of Next-Generation Alternant Codes over Gaussian Integers for Secure and Efficient Communication  
[PERSON]  
1 NUTECH School of Applied Science and Humanities, National University of Technology, Islamabad 44000, Pakistan 1  
2 Department of Electrical Engineering, College of Engineering, Qassim University,  
Buraydah 52571, Saudi Arabia 2  
additional algebraic tools such as norms, divisors, and Euclidean algorithms. Their structure enables more adaptable encoding mechanisms, particularly suitable for high-reliability systems such as satellite communication, the IoT, and 5G networks. Despite these prospects, the literature lacks a concrete coding framework for alternant codes over \(\mathbb{Z}_{n}[i]\), where \(n\) is a positive integer.  
This paper addresses this gap by proposing a construction method for alternant codes over Gaussian integer residue rings, evaluating their structural properties, and analyzing their effectiveness in correcting errors across moderately sized block lengths.
## 2 Background and Core Technologies
### Geographic Information Systems (GISs)  
A GIS stands for a Geographic Information System. It is a system intended to catch, store, manipulate, analyze, and manage current geographical data [16], as illustrated in Figure 1.  
The term \"Geographic Information System\" (GIS) refers to both a generic method for organizing and analyzing large amounts of geographical data and a computer system that gathers, stores, organizes, analyzes, displays, and applies geographic information [17].
###### Abstract  
The degree of monomer conversion (DC) values of three different dental composites were examined using three different methods: surface microhardness (ratio of bottom/top), Fourier-transform infrared (FT-IR), and differential scanning calorimetry (DSC). Two of the dental composites included in the study were nanohybrid (Dentsply Neo Spectra ST HV and Omnichroma), and one was a microhybrid-labeled newly marketed composite containing nanoparticles (Dentac Myra). Composite discs were prepared according to the methodology for all methods and analyzed (2 mm thickness \(\times\) 5 mm diameter). Surface microhardness values were measured in Vickers Hardness Number (VHN), while FT-IR and DSC values were obtained in percentage (%). Significant differences were observed in both bottom/top surface microhardness values and DC values obtained from FT-IR. However, there was no statistical difference in the ratio of bottom/top microhardness values. Neo Spectra ST HV exhibited superior performance in both microhardness and monomer conversion compared to the other two composites. Newly marketed Myra showed values close to Omnichroma. It was found that the values obtained by the DSC method were parallel to those obtained by FT-IR. In conclusion, the structure of dental composites leads to different mechanical properties. Additionally, DSC measurements and FTIR spectra were found to be complementary techniques for characterizing monomer conversion values.  
Keywords:dental composite; degree of conversion; differential scanning calorimeter; monomer; nanohybrid; surface microhardness +
Footnote †: journal: Applied sciences
## 1 Introduction
used a camera and laser radar for joint calibration, fusing the image and point cloud data. The experimental positioning error was within 10 mm [23]. The ranging method was the same as that of the RGB-D camera, which was based on the active measurement of 3D space by structured light to obtain the depth information. Although RGB-D camera has good positioning accuracy, strong illumination easily affects the performance of the camera sensor in a natural environment [24], and binocular camera has strong anti-interference ability to light, it is applicable in an orchard's natural environment. To ensure the imaging quality and positioning accuracy, a _C. oleifera_ fruit detection and positioning method based on a binocular stereo vision system is proposed in this study to solve the above problems. The main contributions of our work are summarized as follows:  
* Two industrial cameras are set up to form a binocular stereo vision system for recognizing and locating _C. oleifera_ fruits. * A robust detection model is obtained by using the YOLOv7 neural network to train the dataset of _C. oleifera_ fruits. * A binocular vision localization algorithm based on image matching with local binary patterns (LBP) maps is proposed.
## 5 Analysis of Results
### Future Prospects  
With the development of urban underground space to deeper and denser development, shield tunnel grouting control and settlement inhibition technology will face higher precision requirements. Intelligent regulation of grouting parameters based on multi-physical field coupling is the core breakthrough direction: on the one hand, it is necessary to establish a real-time feedback model of the evolution of grouting pressure-diffusion radius-soil stiffness, combined with distributed optical fiber and microseismic monitoring data, to achieve the dynamic evaluation of grouting effect; on the other hand, artificial intelligence-driven grouting decision-making systems (such as parameter optimization based on an LSTM network) can break through the limitations of traditional empirical formulas and achieve a settlement prediction error of <5% in complex strata. In addition, the development of low-viscosity and high-strength quick-consolidation grouting materials (e.g., nano-silica modified slurry) is expected to improve the uniformity of reinforcement while reducing injection resistance, and 3D printing directional grouting technology may accurately repair the weak areas of the soil body. Future research should focus on the synergistic innovation of construction-monitoring-materials technology and achieve whole-life-cycle settlement control through a digital twin platform to provide theoretical support for the construction of smart tunnels.
# Adaptive PI Control Strategy for Optimal Microgrid Autonomous Operation
## 7 Conclusions  
This research presents a novel PI controller optimum design based on EBSABA. To improve MGD efficiency, the proposed approach considers 12 PI controller gains. Two PI controllers are used for each DGR in the control approach. The simulation outcomes show the controller scheme's sanity, obtained using the PSCAD/EMTDC software. Furthermore, the results show that the suggested controller can maintain active and reactive powers while efficiently regulating the voltage profile. The outcomes data further indicated fast damping in the transient responses as well as a rapid Tst and a minor Est under multiple MGD operative Incidents: (1) removing the MGD from the utility (islanding mode); (2) load variations under islanding mode; and (3) a three-phase fault under islanding mode. To verify the proposed technique, several simulations are run to demonstrate the effectiveness of the proposed EBSABA in the system's transient responses over LMSRE-based adaptive control and specific other optimization strategies, such as the SFO and PSO approaches. More specifically, the EBSABA reduced the voltage MPUST by 75%, 78.3%, and 85.4% relative to the LMSRE, PSO, and SFO approaches. In Incident 2, when the MGD experienced a sudden change in the load under islanding mode, the proposed approach reduced Tst to zero seconds.  
The future study will improve the proposed EBSABA to employ it in various applications such as power systems, energy storage techniques, and smart-grid, achieving the most satisfactory results in the clean energy schemes.  
A.M.H. and J.K.: conceptualization and methodology; A.A. and M.A.: validation, formal analysis; H.M.H. and M.T.-V.: investigation, visualization, supervision; R.A.T. and F.J.: review and editing. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Researchers Supporting Project number (RSP2022R467), King Saud University, Riyadh, Saudi Arabia.  
The authors declare no conflict of interest.
## 3 Results and Discussion
For example, the conductivity of (La\({}_{2-x}\)Ca\({}_{3}\))Zr\({}_{2}\)O\({}_{7-\delta}\) (\(x\) = 0.05) in wet air is 7 \(\times\) 10\({}^{-4}\) S/cm at 600 \({}^{\circ}\)C while that of (Nd\({}_{2+}\)Ca\({}_{3}\))Zr\({}_{2}\)O\({}_{7-\delta}\) (\(x\) = 0.05) is 2.5 \(\times\) 10\({}^{-4}\) S/cm at 600 \({}^{\circ}\)C) and that of (Sm\({}_{2-x}\)Ca\({}_{3}\))Zr\({}_{2}\)O\({}_{7-\delta}\) (\(x\) = 0.05) is 7.5 \(\times\) 10\({}^{-4}\) S/cm at 600 \({}^{\circ}\)C [41; 42; 43; 44; 45]. The comparison of the proton conductivity of the Ca-doped zirconates and \"stuffed\" hafnate pyrochlores indicates that the higher basicity of cations around an oxygen vacancy in position 48f as a result of Ca-substitution, a more basic cation, for the lanthanide increases the hydration at this position and, as a result, proton conductivity rises by almost two orders of magnitude [41; 42; 43; 44; 45; 46; 47; 48]. Another factor contributing to the decrease in the conductivity of the \"stuffed\" hafnate pyrochlores is the presence of more covalent and strong Hf-O bonds in hafnates relative to zirconates [32]. Figure 5: Total conductivity of La\({}_{2}\)(Hf\({}_{1.9}\)La\({}_{0.1}\))O\({}_{6.95}\) in dry and wet air and N\({}_{2}\).
# Sensitivity Analysis of P-Wave Polarization Direction and Velocity Gradient Inversion
## 3 Sensitivity Analysis of Polarization Direction to Relative Velocity Gradient
If \(\delta\varphi_{e}^{\pi^{\pm}}\) is larger, the opposite displacement required to reposition the ray endpoint back to the position of the receiver will also be larger. Since the change \(\delta\varphi_{e}^{\pi^{\pm}}\) is dependent on the change in the ray exit direction \(\delta\alpha\), a larger opposite displacement requires a larger negative adjustment in the ray exit direction to reposition the ray endpoint back to the receiver position. Combining this with the previous conclusion, the farther the position of the relative velocity gradient change is from the receiver, the greater the variation in the ray endpoint position caused by this change. Therefore, it can be inferred that the closer the position of the relative velocity gradient change is to the receiver, the smaller its influence on the ray endpoint position, and thus the smaller the adjustment required to the ray exit direction to bring the ray endpoint back to the receiver position. Based on the above two steps, the change in polarization direction caused by variations in the relative velocity gradient can be expressed as  
\[\delta\beta_{e}\approx\delta\beta_{e}^{g}+\delta\beta_{e}^{a}. \tag{20}\]  
Regardless of where the relative velocity gradient changes, the first term on the right-hand side of Equation (20) is the same. However, the farther the location of the relative velocity gradient change is from the receiver, the smaller the second term on the right-hand side of Equation (20) becomes. Therefore, we can conclude that the sensitivity of P-wave polarization direction data to the relative velocity gradient is related to the distance of the relative velocity gradient from the receiver. The farther the relative velocity gradient is from the receiver, the lower the sensitivity.
## 2 Results
### A Central Binding Groove in LAIR-1 Common for C1q and Generic Collagen Recognition
Such substitution might induce a slight steric hindrance on the interaction surface, so we decided to introduce it in LAIR-1 (I102L) in order to investigate possible steric impact at that position. Isoleucine 102 was also replaced by a bulkier tyrosine residue (I102Y) in order to enhance the steric effect on collagen interaction. Interaction studies using SPR showed that, when isoleucine 102 is replaced by a slightly longer residue (I102L), the interaction with C1q is partially hampered and it is abolished in the case of the larger I102Y substitution (Figure 7B). However, the interaction with the control collagen peptide is only affected by the I102Y mutation (Figure 7B, lower part). This highlights that the isoleucine 102 position is prone to steric conflict for C1q binding, revealing that  
Figure 5: LAIR-1 R59 and E61 are central collagen binding residues, conserved in LAIR-2 and GPVI. (**A**) Sequence alignment of LAIR-1, LAIR-2 and GPVI Ig-like domains. The \(\beta\)-strands forming the collagen interaction groove in LAIR-1 are indicated with grey arrows and the N-glycosylation site (N69) is indicated with a purple star. The LAIR-1 mutated residues are colored in red for the central collagen binding site and in green and orange for the identified distal residues. LAIR-1 conserved and different residues in LAIR-2 and GPVI sequences are colored in light orange and black, respectively. (**B**) Alignment of the crystal structure of the Ig-like domains of LAIR-1 (in blue, PDB code: 3 KGR) and GPVI (in green) in complex with a collagen peptide (in yellow) (PDB code: 5 OU8). LAIR-1 R59 and E61 and the GPVI homologous residues are colored in red. LAIR-1 N69 is labeled in purple. The remarkable W109 in LAIR-1, close to the collagen ligand, is labeled in cyan. (**C**) NanoDSF experiments of LAIR-1 WT (in blue), R59A (in green) and E61A (in red), alone (dashed lines) or in the presence of a positive collagen peptide control (solid lines). the collagen residue placed in front of the I102 of LAIR-1 should be small enough to accommodate LAIR-1 binding without introducing steric conflict. Figure 6: LAIR-1 R59A and E61A mutations abrogate the interaction with C1q and its variants. LAIR-1 WT (blue curves), R59A (green curves) and E61A (red curves) were injected at a concentration of 10 \(\upmu\)M over immobilized sC1q (**A**), C1 qCLR_nc2 (**B**) and C1 qstem_nc2 (**C**).
## 5 Empirical Analysis and Results
### Assessment of Measurement Model
#### 5.2.3 Convergent Validity  
The measurement model was also examined for convergent validity [60], which refers to the extent to which items truly represent the intended latent construct and indeed correlate with other measures of the same latent construct ([PERSON] et al., 2010). The indicators were evaluated using Average Variance Extracted (AVE) as suggested by [57]. Ref. [61] recommended that the AVE of each la tent construct should be 0.50 or more, and in this study they AVE showed high loadings (>0.50) (see Table 3).
## 1 Introduction
Ordinary differential equation application for mathematical modeling purposes via the mixing problem is important in high-volume manufacturing supply chains. In the context of dynamic SC, inventory management (IM) presents an important role in the operation and management sciences. In this research work, our aim is to present a systemic analysis regarding the reasons why IM for dynamic SC is important by applying systems theory and model-based control approaches. The main goal is to explore the dynamic nature of SC via the development of ordinary differential equations (linear and nonlinear). By definition, inventory management is part of the SCM, which plans, implements, and controls the forward and reverse flow of goods and services (as well as storage) between the point of origin and the point of consumption to meet customer requirements. Inventories, by their nature, are present all along the supply chain (SC), and inventory control is a crucial activity by a company's management [12]. Presenting appropriate inventory levels is a crucial task for a company [13], considering that quick and positive response to customers is related to high inventory levels (which increase the cost), while low inventory levels might cause scarcity. In general, for manufacturing firms, inventory usually represents from 20% to 60% of the total assets [14]. The coordination of inventory policies in IM for SCM between suppliers, manufactures, and distributors is a major task. Furthermore, it smooths material flow and minimizes costs while meeting customer demands [15]. Based on this, the following research questions are formulated: (1) Are dynamic supply chains suitable to be mathematically modeled via the mixing problem? (2) Do optimal control and high-volume manufacturing have an impact at operational level of dynamic SC? The rest of the paper is organized as follows: Section 2 presents an analysis on dynamic SC and the role of optimal control theory in supply chains. Section 3 presents a discussion of the mixing problem theory. A mathematical modeling description of the problem, as well as a sensitivity and stability analysis for the system, are present in Section 4. In Section 5, a model-based optimal control for a composed energy performance index is presented. In Section 6, a discussion on the results is presented. Finally, conclusions and future work are discussed in Section 7.
# A Survey of Analog-to-Digital Converters for Operation under Radiation Environments
## 4 Data Analysis
### COTS within the Selection
\begin{table}
\begin{tabular}{c l l l l l l l l l} \hline \hline \multicolumn{2}{c}{**Application**} & \multicolumn{1}{c}{**BF**} & \multicolumn{1}{c}{**CS**} & \multicolumn{1}{c}{**DAC**} & \multicolumn{1}{c}{**GOLD**} & \multicolumn{1}{c}{**DIS**} & \multicolumn{1}{c}{**4P**} & \multicolumn{1}{c}{**QS**} & \multicolumn{1}{c}{**1P**} & \multicolumn{1}{c}{**S**} \\ \hline \multirow{6}{*}{satellite communications} & collider experiments & \(\checkmark\checkmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & & \\  & discrete-time control & & \(\checkmark\checkcheckmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & & \\  & earth observation & & & & \(\checkmark\) & & & \(\checkmark\) & \\  & house-keeping & & & \(\checkmark\) & \(\checkmark\) & & & \(\checkmark\) & \\ \hline \multirow{3}{*}{satellite communications} & base-band & \(\checkmark\checkmark\) & \(\checkmark\) & & & \(\checkmark\) & \(\checkmark\) & & \\  & DDC & \(\checkmark\checkmark\) & \(\checkmark\) & & & \(\checkmark\) & \(\checkmark\) & & \\ \hline \multirow{3}{*}{sensor acquisition} & thermistor & & & & \(\checkmark\) & & & \(\checkmark\) & \\  & gauge & & & & \(\checkmark\) & & & \(\checkmark\) & \\  & magnetometer & & & & \(\checkmark\) & & & \(\checkmark\) & \\ \hline \multirow{3}{*}{satellite communications} & star-tracker & & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & & \\  & sun sensor & & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \\ \hline \multirow{3}{*}{satellite communications} & fast dynamics & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & & \\  & slow dynamics & & & & \(\checkmark\) & & & \(\checkmark\) & \\ \hline \multirow{3}{*}{sensor acquisition} & video & & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \\  & & & & & & \(\checkmark\) & & \(\checkmark\) & \\ \hline \multirow{3}{*}{satellite communications} & star-tracker & & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \\  & sun sensor & & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \\ \hline \multirow{3}{*}{satellite communications} & fast dynamics & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & & \\  & slow dynamics & & & & \(\checkmark\) & & & \(\checkmark\) & \\ \hline \multirow{3}{*}{satellite communications} & video & & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \\ \cline{1-1}  & video & & & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \(\checkmark\) & \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Suitability of ADC soft error test methods for applications in radiation environments.