esa-sceva/satcom-chunk-collection huggingface dataset:
# Research Progress on Flexible Oxide-Based Thin Film Transistors
## 2 Device Fundamental Concept and Conventional Configuration
### Typical Device Configurations  
By depositing a gate, an oxide semiconductor and drain/source electrodes in different ways and in different orders, five different types of device configurations can be formed, namely ES, BCE, TG, DG, and CP structure, as shown in Figure 1.  
In Figure 1a, the BCE configuration is shown, which is applied in most commercial applications (e.g., cellphone, TV) due to its simple photolithography process and low cost. As oxide semiconductors are very weak in most of the wet etchants, dry etching needs to be employed to etch the S/D electrodes. A downside of dry-etching, however, is that the TFT devices can become ion-damaged by plasma bombardment during the dry etching process [145]. To avoid these effects, the ES configuration shown in the Figure 1b and contains an added ES layer formed and patterned on the active layer to protect the channel during the etching of the S/D electrodes [146]. However, it makes the processes more complicated and increases the cost. Figure 1c shows the TG structure, where the passivation is replaced by the top gate insulator and electrode to protect the active layer [147]. Nonetheless, the stability of negative bias illumination stress of the top gate structure TFTs still needs to be improved. By combining the TFTs (Figure 1a-c), the DG structure with a top gate, a bottom gate is obtained, which presents a high performance for driving pixel circuits, gate driver circuits, and other integrated circuits, as shown in Figure 1d. However, it is observed that the overlap between the gate and source/drain electrodes in Figure 1a-d causes a high parasitic capacitance. This capacitance is proportional to the overlap areaand induces a resistance-capacitance (RC) delay in the TFT arrays and integrated circuits. To reduce this RC delay effect, coplanar structures of TFTs called CP TFTs are presented in Reference [148], as shown in Figure 1e. In CP TFTs, the overlap between the G and S/D electrodes is negligible so that the parasitic capacitance can be remarkably reduced.
# Lyndon Factorization Algorithms for Small Alphabets and Run-Length Encoded Strings +
## 2 Basic Definitions  
Let \(\Sigma\) be a finite ordered alphabet of \(\sigma\) symbols and let \(\Sigma^{*}\) be the set of words (strings) over \(\Sigma\) ordered by lexicographic order. In this paper, we use the terms string, sequence, and word interchangeably. The empty word \(\varepsilon\) is a word of length \(0\). Let \(\Sigma^{+}\) be equal to \(\Sigma^{*}\setminus\{\varepsilon\}\). Given a word \(w\), we denote with \(|w|\) the length of \(w\) and with \(w[i]\) the \(i\)-th symbol of \(w\), for \(0\leq i<|w|\). The concatenation of two words \(u\) and \(v\) is denoted by \(uv\). Given two words \(u\) and \(v\), \(v\) is a substring of \(u\) if there are indices \(0\leq i,j<|u|\) such that \(v=u[i]...u[j]\). If \(i=0\) (\(j=|u|-1\)) then \(v\) is a prefix (suffix) of \(u\). The substring \(u[i]...u[j]\) of \(u\) is denoted by \(u[i..]\), and for \(i>j\)\(u[i..j]=\varepsilon\). We denote by \(u^{k}\) the concatenation of \(k\)\(u\)'s, for \(u\in\Sigma^{+}\) and \(k\geq 1\). The longest border of a word \(w\), denoted with \(\beta(w)\), is the longest proper prefix of \(w\) which is also a suffix of \(w\). Let \(lcp(w,w^{\prime})\) denote the length of the longest common prefix of words \(w\) and \(w^{\prime}\). We write \(w<w^{\prime}\) if either \(lcp(w,w^{\prime})=|w|<|w^{\prime}|\), i.e., if \(w\) is a proper prefix of \(w^{\prime}\), or if \(w[lcp(w,w^{\prime})]<w^{\prime}[lcp(w,w^{\prime})]\). For any \(0\leq i<|w|\), \(\textsc{rot}(w,i)=w[i..|w|-1]w[0..i-1]\) is a rotation of \(w\). A Lyndon word is a word \(w\) such that \(w<\textsc{rot}(w,i)\), for \(1\leq i<|w|\). Given a Lyndon word \(w\), the following properties hold:  
1. \(|\beta(w)|=0\);
2. either \(|w|=1\) or \(w[0]<w[|w|-1]\).  
Both properties imply that no word \(a^{k}\), for \(a\in\Sigma\), \(k\geq 2\), is a Lyndon word. The following result is due to [PERSON], [PERSON] and [PERSON] [11]:  
**Theorem 1**.: _Any word \(w\) admits a unique factorization \(CFL(w)=w_{1},w_{2},\ldots,w_{m}\), such that \(w_{i}\) is a Lyndon word, for \(1\leq i\leq m\), and \(w_{1}\geq w_{2}\geq\ldots\geq w_{m}\)._  
The interval of positions in \(w\) of the factor \(w_{i}\) in \(CFL(w)=w_{1},w_{2},\ldots,w_{m}\) is \([a_{i},b_{i}]\), where \(a_{i}=\sum_{j=1}^{i-1}|w_{j}|\), \(b_{i}=\sum_{j=1}^{i}|w_{j}|-1\), for \(i=1,\ldots,m\). We assume the following property:  
**Property 1**.: _The output of an algorithm that, given a word \(w\), computes the factorization \(CFL(w)\) is the sequence of intervals of positions of the factors in \(CFL(w)\)._  
The run-length encoding (RLE) of a word \(w\), denoted by \(\textsc{rle}(w)\), is a sequence of pairs (runs) \(\langle(c_{1},l_{1}),(c_{2},l_{2}),\ldots,(c_{\rho},l_{\rho})\rangle\) such that \(c_{i}\in\Sigma\), \(l_{i}\geq 1\), \(c_{i}\
eq c_{i+1}\) for \(1\leq i<\rho\), and \(w=c_{1}^{l_{1}}c_{2}^{l_{2}}\ldots c_{\rho}^{l_{\rho}}\). The interval of positions in \(w\) of the run \((c_{i},l_{i})\) is \([a_{i}^{\textsc{rle}},b_{i}^{\textsc{rle}}]\) where \(a_{i}^{\textsc{rle}}=\sum_{j=1}^{i-1}l_{j}\), \(b_{i}^{\textsc{rle}}=\sum_{j=1}^{i}l_{j}-1\).
## 2 Materials and Methods
### Treatment Methods and Reaction Mechanisms  
In this study, deionized water and ethanol were chosen as solvents for the hydrolysis reaction of SCA. In addition, to determine the optimal concentration of SCA, conductivity was chosen as a measure to assess the effect of concentration on the degree of SCA hydrolysis. This is because the conductivity of SCA and deionized water is very low, while the conductivity of the hydrolysis products of SCA is high. In addition, in the solution proportioning, there is no effect on the conductivity of the system because ethanol always makes up 50% of the total solution volume in the solution proportion. Therefore, the degree of hydrolysis of the SCA can be confirmed through conductivity measurements. As shown in Figure 1, the conductivity increased significantly when the SCA concentration was increased from 2% to 5%. However, as the SCA concentration continued to increase, the conductivity did not increase; instead, it showed a decreasing trend. The results indicate that the hydrolysis of SCA is highest when the concentration of SCA is 5%. Therefore, the optimal ratio of the SCA mixture solution is SCA:deionized water:ethanol = 5:45:50.  
The RCA treatment method and modification mechanism are shown in Figure 2. First, the SCA mixed solution (SCA:distilled:ethanol = 5:45:50) was stirred at 60 \({}^{\circ}\)C for 30 min to promote the hydrolysis reaction of SCA. Then, the RCA was immersed in an SCA mixture for 30 min to ensure a sufficient reaction between the SCA and RCA. Finally, the RCA was dried at a high temperature of 160 \({}^{\circ}\)C for 60 min to undergo a dehydration condensation reaction. During the entire process, the methoxy group (\(-\)OCH3) in the molecular structure of SCA (KH550) can hydrolyze into the alkoxy group (\(-\)SiOH) of silanol in a mix of ethanol and water. Then, under high temperature conditions, the alkoxy group undergoes a dehydration condensation reaction with the hydroxyl group on the RCA surface to form Si-O-Si bonds [47].  
Figure 1: Conductivity of SCA mixed solutions at various concentrations.  
\begin{table}
\begin{tabular}{l c} \hline \hline
**Prefix** & **Full Name** \\ \hline RCA & Recycled concrete aggregate \\ RCA1 & Discarded cement column (30 \(\times\) 30 \(\times\) 30 mm) \\ RCA2 & Recycled concrete aggregate (13.2–19 mm) \\ C-S-H & Calcium silicate hydrate \\ SCA & Silane coupling agent \\ SEM & Scanning electron microscopy \\ SARA & Saturates, aromatics, resins, and asphaltenes \\ \hline \hline \end{tabular}
\end{table}
Table 3: All prefixes in this paper.
## 1 Introduction
### Motivation and Contributions  
SAGIN-driven future network communications have three main use cases: enhanced mobile broadband (eMBB), ultra-reliable low-latency communication (URLLC), and massive machine-type communication (mMTC). These impose strict requirements on UAV  
Figure 1: Architectural diagram of UAV-Assisted SAGIN. Subfigure (**a**) demonstrates the hierarchical architecture of SAGIN, where different network layers are primarily interconnected through wireless links. Subfigures (**b,c**) present application scenarios of SAGIN. In (**b**), a large UAV serves as an aerial base station collaborating with a small UAV communication relay to provide connectivity services for remote devices. Subfigure (**c**) highlights operational advantages of UAVs, while functioning as base stations, they can simultaneously execute other specialized missions. SAGIN integrates terrestrial and maritime environments through this architecture, enabling ubiquitous interconnection. assisted SAGINs to improve quality of service (QoS) metrics in terms of (1) stability, (2) throughput, (3) latency, and (4) security. In recent years, researchers have developed numerous UAV-assisted SAGIN studies, covering areas such as (1) system architecture, (2) path planning, (3) routing and scheduling, (4) resource allocation and energy management, and (5) the deployment of drones. These research achievements are highly significant for the development of SAGINs. However, there is currently no comprehensive review of the important stage of research results on UAV-assisted SAGINs. According to the survey results in Table 1, existing surveys on UAV-assisted SAGINs have summarized key aspects such as security [9], resource allocation [10; 11; 12], routing protocols [13], path planning [14], and UAV deployment [14; 15]. In addition, the review [6] analyzes routing algorithms driven by artificial intelligence (AI). Some surveys focus on specific areas while neglecting others, and although review [2] provides a comprehensive overview, it offers only general viewpoints. Therefore, a thorough review of the current research progress on these key technologies is essential and would provide valuable guidance for future studies and technological development. The contributions of this paper are as follows:  
1. We provide a comprehensive and detailed description of the network architecture and technical features of UAV-assisted SAGINs.
## 8 Conclusions  
This research has explored kinetic energy harvesting technologies for locations with high pedestrian traffic, specifically targeting sustainable energy solutions for the Al-Haram Mosque. This study demonstrated how piezoelectric, triboelectric, and hybrid energy-harvesting systems could effectively transform pedestrian foot traffic into usable electrical power. Individually, energy-harvesting technologies such as piezoelectric transducers embedded in floor tiles produce limited power; however, they become significantly more effective when integrated into hybrid systems. Combined kinetic and solar energy harvesting exhibits strong potential for providing stable and reliable power sources, suitable for low-energy applications such as LED lighting, IoT devices, and environmental sensors.  
Materials such as PVDF and BaTiO\({}_{3}\), along with novel composite materials including MXene-based and cellulosic substances, emerge as promising candidates because of their enhanced energy conversion efficiency and mechanical durability under repeated mechanical stress. Additionally, this study highlights various design innovations--from series-parallel configurations of piezoelectric cells to foldable and modular energy mats--emphasizing the critical importance of optimizing both material choices and structural designs for high-density pedestrian areas.  
Nevertheless, several significant challenges persist. These include insufficient energy production from individual energy-harvesting units, sensitivity to environmental variations, and integration difficulties within existing structures without compromising aesthetic or functional standards. Enhancing durability and establishing effective maintenance procedures for harsh environments such as that of the Al-Haram Mosque necessitates ongoing research and development efforts.  
The reviewed studies reveal transformative potential, even though current technologies fall short of meeting large-scale energy demands independently. Advances in materials science, combined with the development of hybrid systems, remain crucial for extending the practical applicability of these energy-harvesting solutions. Aligned with Saudi Arabia's Vision 2030 and its commitment to renewable energy, future research efforts should prioritize enhancing energy-generation capabilities, reducing costs, and ensuring sustained performance. Implementing a unified strategy will reduce reliance on conventional energy sources, significantly contributing to sustainable energy infrastructures in heavily visited public spaces.  
Conceptualization, F.A. and M.K.; methodology, F.A.; software, F.A.; validation, M.K.; formal analysis, F.A.; investigation, M.K.; resources, F.A.; data curation, F.A.; writing--original draft preparation, F.A.; writing--review and editing, M.K.; visualization, F.A.; supervision, M.K.; project administration, M.K. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
No new data is created.  
The authors declare no conflicts of interest.
# Decision-Maker's Preference-Driven Dynamic Multi-Objective Optimization
## 5 Conclusions
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline
**DMOOP** & \(\mathbf{n_{t}}\) & \(\mathbf{\tau_{t}}\) & **PM** & **PPA** & **DPA** & **RSTFRA** & **PM** & **PPA** & **DPA** & **RSTFRA** \\ \hline fda5 & 10 & 4 & nNVD & 39.5000 & **50.0333** & 45.3000 & sNVD & **0.1175** & 0.0966 & 0.1008 \\ fda5 & 10 & 4 & nNVD & 57.1667 & 67.3333 & **68.4333** & sNVD & **0.0906** & 0.0791 & 0.0726 \\ fda5 & 10 & 4 & nNVD & 63.5000 & **74.6333** & 63.1333 & sNVD & **0.1100** & 0.0915 & 0.0962 \\ fda5 & 10 & 4 & nNVD & 71.9000 & **72.9333** & 58.8667 & sNVD & 0.1237 & 0.1122 & **0.1245** \\ \hline fda5 & 10 & 5 & nNVD & 42.0000 & **49.9667** & 27.4000 & sNVD & **0.1652** & 0.1327 & 0.1010 \\ fda5 & 10 & 5 & nNVD & **72.0667** & 70.2000 & 35.0667 & sNVD & **0.1105** & 0.1015 & 0.0915 \\ fda5 & 10 & 5 & nNVD & **74.4333** & 65.4667 & 36.4000 & sNVD & **0.1089** & 0.1005 & 0.0940 \\ fda5 & 10 & 5 & nNVD & **79.0667** & 60.1667 & 34.0333 & sNVD & 0.1017 & **0.1079** & 0.1059 \\ \hline fda5 & 10 & 2 & nNVD & **12.2667** & 11.8333 & 2.9333 & sNVD & **0.2712** & 0.2546 & 0.0040 \\ fda5 & 10 & 2 & nNVD & **13.1667** & 9.1000 & 1.5667 & sNVD & 0.1928 & **0.2910** & 0.0032 \\ fda5 & 10 & 2 & nNVD & **19.3000** & 8.8000 & 2.6333 & sNVD & 0.2200 & **0.3729** & 0.0005 \\ fda5 & 10 & 2 & nNVD & **41.5667** & 33.8000 & 2.6000 & sNVD & 0.1413 & **0.1716** & 0.0062 \\ \hline fda5 & 1 & 4 & nNVD & **12.9667** & 12.7000 & 9.6333 & sNVD & 0.1967 & **0.2117** & 0.0279 \\ fda5 & 1 & 4 & nNVD & **32.4667** & 18.6667 & 12.3667 & sNVD & **0.2258** & 0.1087 & 0.0253 \\ fda5 & 1 & 4 & nNVD & **13.6667** & 12.9667 & 9.3667 & sNVD & **0.2683** & 0.2654 & 0.0122 \\ fda5 & 1 & 4 & nNVD & **29.2333** & 28.9000 & 16.5333 & sNVD & **0.2238** & 0.0853 & 0.0124 \\ \hline fda5 & 1 & 5 & nNVD & 19.4000 & **23.2000** & 21.7333 & sNVD & **0.0897** & 0.0592 & 0.0568 \\ fda5 & 1 & 5 & nNVD & 35.8333 & 34.2000 & **67.6333** & sNVD & **0.0946** & 0.0687 & 0.0368 \\ fda5 & 1 & 5 & nNVD & 21.0333 & **23.4333** & 21.0333 & sNVD & **0.1374** & 0.1011 & 0.0651 \\ fda5 & 1 & 5 & nNVD & 39.1 & 33.6333 & **62.8333** & sNVD & **0.0757** & 0.0693 & 0.0407 \\ \hline fda5 & 1 & 2 & nNVD & 22.1667 & 23.6333 & **26.4333** & sNVD & **0.1600** & 0.1365 & 0.0837 \\ fda5 & 1 & 2 & nNVD & **20.8667** & 17.8667 & 6.6000 & sNVD & 0.0726 & **0.0964** & 0.0577 \\ fda5 & 1 & 2 & nNVD & **18.8000** & 17.5000 & 17.4333 & sNVD & 0.2013 & **0.2357** & 0.1891 \\ fda5 & 1 & 2 & nNVD & **20.2667** & 18.0333 & 11.4667 & sNVD & 0.0617 & **0.0747** & 0.0391 \\ \hline \hline \end{tabular}
\end{table} 
Table 10: hvr and react for each DMOA for FDA5 with various frequency and severity of change.
## 2 Mission and Satellite Design  
The S-STEP is defined as a spaceborne SAR microsatellite technology demonstration program by developing an engineering qualification model of the SAR payload. The fundamental mission objective of the S-STEP is the continuous near-real-time monitoring of the Earth's surface using high-resolution SAR images through an affordably developed 80 kg class microsatellite SAR constellation. This constellation operates within an average revisit cycle of half an hour. These images can be employed in civil, scientific, military, and commercial applications. In military surveillance, these images are used to detect time-critical targets such as TELs, and in maritime surveillance, these are used to detect illegal fishing vessels (dark vessels). The S-STEP mission aims to develop a faster, better, smaller, and lighter 80 kg class SAR satellite in accordance with the NSP.
## 3 Results and Discussion
### TEM Analysis and DLS  
The shape of the synthesized AgNPs was spherical and the diameter of biosynthesized AgNPs, as characterized by TEM, were in the range of 15 to 80 nm with a narrow size distribution pattern (Figure 4A,B). This confirms the findings obtained by our SEM analysis and  
\begin{table}
\begin{tabular}{c c c} \hline
**Aw-AgNPs Wave Number (cm\({}^{-1}\))** & **Probable Functional Group** & **Compound Class** \\ \hline
3420 & N-H Stretch & Amines \\
2854 & C-H Stretch & Alkanes \\
2985 & C-H Stretch & Alkanes \\
1030 & C-O stretch & Ester \\
1019 & C-4-OH stretch & Typical for glucose residue of disaccharides \\
668 & C=C stretch & Alkene \\ \hline \end{tabular}
\end{table}
Table 1: FTIR analysis and probable functional groups.  
Figure 3: Characterization of AgNPs. (**A**) SEM image of AgNPs; (**B**) EDAX spectrum of AgNPs; (**C**) quantitative results obtained by EDAX from Ajwa date extract.  
are similar to those observed by [PERSON] et al. who determined the size of biosynthesized date fruit AgNPs to be in a range between 25 and 60 nm [2]. The particle size distribution of AgNPs of Ajwa in relation to intensity (percent) was monitored through Dynamic light scattering analysis (Figure 4C). From this figure we concluded that the inconsistency in the size of AgNPs is because of few agglomerations in sample. Supporting studies were done to determine mean size of nanoparticles in aqueous solutions utilizing Dynamic light scattering. TEM is one of the most powerful methods for obtaining direct structural and size information of nanoparticles.
# UVsq-Sat NG, a New CubeSat Pathfinder for Monitoring Earth Outgoing Energy and Greenhouse Gases
## 1 Introduction
Furthermore, Uvsq-Sat NG has a high-definition camera (focal length of 70.5 mm, F/2.2, spectral range transmission from 390 to 690 nm, complementary metal oxide semiconductor (CMOS) sensor of 2048 \(\times\) 1536 pixels, pixel size of 3.2 \(\upmu\)m, field of view of 13\({}^{\circ}\)) to acquire images of observed scenes in the visible spectrum. The post-processing of the images should enable high-precision geolocation, which is necessary for analyzing Uvsq-Sat NG NIR Spectrometer observations and interpreting GHG concentration maps. This camera will also be used to observe the Earth at the limb. Uvsq-Sat NG is a SmallSat belonging to the International Satellite Program in Research and Education (INSPIRE) series of satellite missions. The INSPIRE program is a collaborative effort among multiple universities aimed at creating a constellation of SmallSats for pioneering space and Earth science research. This initiative also encompasses the establishment of a global ground station network and educational programs encompassingspacecraft design, systems engineering, operations and data analysis. The advancements achieved through the Uvsq-Sat NG program contribute also to enhancing our educational curriculum (SIMIS Professional Bachelor (Mantes-en-Yvelines, France), Master NewSpace Paris-Saclay (Guyancourt, France), etc. ), enabling the training of students in space technology, as well as space sciences. The general objective of this paper is to present the Uvsq-Sat NG mission and logic and to describe the instruments including the NIR Spectrometer and its data processing. Section 2 explains the scientific purposes of the mission. Section 3 describes the Uvsq-Sat NG nanosatellite, its current status, its Calibration and Validation (Cal/Val) process, and its Concept of Operations (ConOps). Section 4 presents an initial analysis of the expected results on GHG retrieval from future Uvsq-Sat NG observations based on numerical simulations. A radiative model is used to relate the observed transmittance functions to the concentrations of the atmospheric gases. A Levenberg-Marquardt algorithm iteratively adjusts the gas concentrations and inputs to the model, to minimize the differences between measured and simulated transmittance functions depending on assumed environmental parameters. The estimation of gases concentrations (CO\({}_{2}\), CH\({}_{4}\), O\({}_{2}\), H\({}_{2}\)O) and their associated uncertainties is largely based on a Monte Carlo approach, performing multiple simulations with randomized model inputs within specified uncertainty bounds.
# Design and Analysis of Pattern Reconfigurable Antenna Based on RF MEMS Switches
## 4 Measurement and Results
Place the reconfigurable antenna to be tested near the gain reference antenna, place the gain reference antenna on a slide that can move at a constant speed, and slide the gain reference antenna up and down to measure the power \(P_{ref}\) of the electromagnetic wave received in space due to reflection with the gain reference antenna;  
Figure 12: The graph of the return loss of the reconfigurable antenna. (**a**) Simulated return loss. (**b**) Measured return loss. The gain value \(G_{AUT}\) of the pattern reconfigurable antenna at this point and angle can be calculated by formula (8), where \(G_{ref}\) is the gain of the gain reference antenna, and the values here are expressed in logarithms: \[G_{AUT}=G_{ref}+\left(P_{AUT}-P_{ref}\right);\] (8)
5. By measuring the gain values at multiple angles and frequency points using the above method, we can obtain the pattern and gain of the pattern reconfigurable antenna to be tested. Figure 14 is the picture of microwave anechoic chamber and the test results are shown in Figure 15. The test results show that the antenna can switch among three working modes; the main lobe radiation directions of the three working modes are \(-0.6^{\circ}\), \(-7.9^{\circ}\), \(8.0^{\circ}\). Therefore, the reconfigurable antenna designed in this paper can achieve directional pattern switching of the main lobe to the left (about \(-8^{\circ}\)), middle (about \(0^{\circ}\)), and right (about \(+8^{\circ}\)). The performance comparison between the reconfigurable antenna developed in this paper and other reconfigurable antennas is shown in Table 3. From Table 3, it can be seen that we designed a MEMS pattern reconfigurable antenna that can dynamically adjust the antenna radiation direction at a working frequency of 35 GHz. Moreover, we designed the antenna and MEMS switch integrated design and fabrication technology, which makes the whole antenna more compact and easy to integrate and apply. The comparison data show that the pattern reconfigurable antenna designed and presented in this paper can effectively achieve the purpose of device miniaturization while ensuring good radio frequency performance parameters and improving the flexibility and adaptability of the antenna. Figure 14: Microwave anechoic chamber. Figure 13: Principle block diagram of comparative law method for measuring the gain of reconfigurable antenna.