esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Related Works
### Satellite Images
#### 2.1.1 Training a Customized CNN with Satellite Images  
[PERSON] et al. [8] predicted path loss in a campus environment (suburban) from a model that integrated satellite image input with other numerical data features. The satellite images are passed through five convolutional layers, and the numerical data are passed through fully connected layers. The outputs of the two networks are concatenated and passed onto an output neural network composed of two fully connected layers and a single node output layer. The data used in training and testing were measurements at 811 and 2630 MHz, with a fixed transmitting antenna height of 30 m and receiving antenna height of 1.5 m. The deep learning model performed better than 3D Ray Tracing and the empirical model. A similar architecture was developed to predict signal strength at 811 and 2630 MHz, but with reduced complexity in the CNN, whereby four convolutional layers were used with a reduced number of filters. A modification was also made to the numerical features used, such that latitude and longitude were removed, the frequency was included, and data from different environments were considered [23]. The model was upgraded in [24] by the addition of the receiver position side view image. [PERSON] et al. modified the model in [23] such that the model predicts signal strength corrections of a 3 GPP empirical model at 3.5 GHz. The final signal strength is obtained by the addition of the corrections to the signal strength computed using the 3 GPP empirical model [25]. However, the image of the receiver position is not sufficient to describe the path of the signal from the transmitter to the receiver position.
## 5 Design of the Antenna Pointing Control System
### Control Frequency of Antenna Driving Control System  
The control frequency required for antenna driving control system can be calculated from the required antenna pointing accuracy and the attitude angular velocity of the fixed-wing UAV, as shown in Equation (25) [22]. Therefore, the calculation results are shown in Figure 18.  
\[\theta_{\rm am}\geq\frac{\omega_{\rm UAV}}{2\pi f_{\rm A}} \tag{25}\]  
The average absolute values of the attitude angular velocities of the fixed-wing UAV are 4 deg./s for roll angular velocity, 7 deg./s for pitch angular velocity, and 4 deg./s for yaw angular velocity.  
Therefore, the control frequency of the antenna driving control system was set to 10 Hz to be satisfied these.
# Progressive Poling of Large Area, High r\({}_{33}\) Electro-Optic Polymer SEO100c
## 3 Waveguide Fabrication  
The first step in the fabrication process was using e-beam deposition to deposit 10 nm of chrome adhesion layer followed by 100 nm of gold on a silicon wafer to form the bottom electrode. A 4.3 \(\upmu\)m layer of Norland Products NOA 73 was spun on using a static spinning technique, then UV cured for 30 min with low intensity UV to form a smooth bottom cladding layer.  
To create the core layer, a vial with 0.5 g of SEO100c had 7.45 g of dibromomethane added. The solution was then mixed on a rotator at 35 rpm for 8.5 h. Once mixed, the SEO100c was passed through a 0.2 \(\upmu\)m nylon filter and allowed to settle for 30 min. After settling, the SEO100c was deposited by a static spinning process with a spin speed of 1000 rpm for 40 s producing a 2.7 \(\upmu\)m-thick core layer. The wafer was then baked in a vacuum oven at 75 \({}^{\circ}\)C for 18 h.  
A layer of Futurrex's PR1-1000a photoresist was spun on, photolithography was performed to define 6 \(\upmu\)m wide rib waveguides, and the wafer was developed in Futurrex's RD6. The PR-1 photoresist was used because it was known to not chemically damage the SEO100c core layer [14]. Following development, it was etched for 125 s in an O\({}_{2}\) environment using a reactive ion etching process. The etched structures were measured at an etch depth of 667 nm. Using harsher chemicals such as acetone or resist remover potentially degrade the EO-polymer, therefore the PR-1 was removed by flood exposure to UV followed by development in RD6.  
A second 4.3 \(\upmu\)m cladding layer of NOA73 was spun on and UV cured for 30 min. The top electrode was formed by e-beam deposition of 10 nm of chrome followed by 100 nm of gold. PR-1 was spun on, and the top electrodes were patterned using photolithography. The top electrodes were then wet etched using type TFA gold etchant and CR7 chrome etchant to etch the layers of the top electrode. The PR-1 was again exposed to UV light and developed in RD6. A shadow mask was placed over the wafer and the bottom electrodes were accessed by RIE in an O\({}_{2}\) environment. Etching through the polymer layers was performed by alternating periods of etching with cool off periods to prevent the wafer from overheating. The completed stack is shown in Figure 1.  
Devices were then diced apart in single passes using a nickel bonded blade with a spindle speed of 30,000 RPM with a feed rate of 40 mils/s. These dicing parameters were selected to produce clean and consistent end faces.
## 4 Practical Application  
### Application Target and Experimental Setup  
In sequence, the developed sensor is applied to evaluate the joint structure of an existing balanced-arm lamp: IKEA TERTIAL lamp. Several commercial balanced-arms utilize gravity compensation mechanisms composed of parallelograms and springs [31]. If the balancing structure is not designed with proper calculation, then the supporting ability of the balanced-arm is not likely to perform well. For example, the lamp on the distal part of the balanced-arm may not be fixed in the desired position and may go up or down. On the other hand, a properly designed structure can successfully support the distal end against gravity. The joint of the balanced-arm used in this experiment is expected to show completely different torque measurement results depending on the presence of the balancing springs. After the measurement, a method capable of improving the joint structure can be proposed.  
Figure 11 shows how the experimental equipment is installed. The balanced-arm consists of four joints: the 1 st base yaw joint, the 2 nd lower parallelogram joint, the 3 rd upper parallelogram joint, and the 4 th neck pitch joint; among them, the two intermediate joints are not strictly perfect parallelograms. Each parallelogram joint has two balancing springs, and the target of this measuring experiment is the upper parallelogram joint. As shown in the figure, one hinge joint constituting  
Figure 10: The measured load output by the sinusoidal torque input according to three different moment arm length of the load cell. Black dash-dotted lines represent fitted sine curves. The rotation angle range is (**a**,**b**) between 0\({}^{\circ}\) and 720\({}^{\circ}\), and (**c**,**d**) between 1\({}^{\circ}\) and 179\({}^{\circ}\).  
the upper parallelogram is connected to the developed torque sensor through a transmission shaft. Therefore, as the joint angle changes according to the rotation of the motor incorporated in the sensor, the torque required to move is continuously measured. The lower parallelogram linkage of the balanced-arm is fixed to be perpendicular to the ground, while the upper parallelogram linkage is horizontal to the ground in the neutral position. The posture reference of the parallelogram joints is based on their inner linkages.
# Energy-Efficient Wireless Communication Strategy for Precision Agriculture Irrigation Control
## 2 Precision Irrigation Control System
### State Space Model  
The hydrological balance model describes the dynamics of an irrigation system where the soil moisture changes in the root zone \(\dot{\theta}\) were obtained from the sum of water inflows and outflows. If we consider a plain field (no water runoff) in a dry area (no rainfall and no water capillary rise), as stated by [37], then the system behavior is expressed as  
\[\dot{\theta}(t)=a_{1}ir(t-\tau)-K_{c}eto(t)-a_{2}\theta(t), \tag{1}\]  
where \(ir\) is the applied irrigation, _eto_ is the reference evapotranspiration, and \(a_{1}\), \(K_{c}\), and \(a_{2}\) are constants that, respectively, denote the irrigation efficiency, evapotranspiration coefficient to incorporate crop characteristics, and soil moisture proportionality to estimate deep percolation. In addition, \(\tau\) is the time delay required by the water to reach the crop roots, which usually requires several minutes.  
Since a discrete model is required, Euler approximation is used to discretize Equation (1) with a sampling period \(h\), and then  
\[\theta(kh+h)=c_{1}\theta(kh)+c_{2}ir(kh-\tau)+c_{3}eto(kh), \tag{2}\]  
where \(c_{1}\), \(c_{2}\), and \(c_{3}\) are discrete coefficients that absorb the previous continuous coefficients and signs.  
The model is enhanced by considering soil moisture variations as a second state variable; therefore, \(\delta\), defined as  
\[\delta(kh+h)=\theta(kh)-\theta(kh-h), \tag{3}\]  
represents the relative moisture dynamics and indicates the changes detected in the root zone. Now, the state-space model for an irrigation system is specified as a second order system in the general form of  
\[\begin{split} x(kh+h)&=\Phi x(kh)+\Gamma u(kh)\\ y(kh)&=Cx(kh),\end{split} \tag{4}\]  
where the state and input and output vectors are defined, respectively, as  
\[x(kh)=\begin{bmatrix}\theta(kh)\\ \delta(kh)\end{bmatrix},u(kh)=\begin{bmatrix}ir(kh-\tau)\\ eto(kh)\end{bmatrix},y(kh)=\begin{bmatrix}\theta(kh)\end{bmatrix}, \tag{5}\]  
while the discrete matrices \(\Phi\in\mathbb{R}^{2\times 2}\), \(\Gamma\in\mathbb{R}^{2\times 2}\), and \(C\in\mathbb{R}^{1\times 2}\) define the process dynamics coefficients to be identified.
# Development of the First Portuguese Radar Tracking Sensor for Space Debris
## 3 System Expected Capabilities  
Given the technical specifications of the current system, it is possible to make estimates on how it will perform. These estimates are not only useful for predicting the systems applicability but also to identify its limitations and guide to future upgrades.
# Review on the Recent Numerical Studies of Liquid Atomization
## 6 Multi-Fluid and Multi-Scale Eulerian Method
### Application Cases  
A fully Eulerian-based MFMS method has been applied in the simulation of gas-liquid flow in a pipe [76], liquid column impinging into a free surface [77], a dam break [78], and boiling flow in a heated pipe [79]. The simulations were usually conducted on the commercial code CFX, utilizing the inhomogeneous MUlti-Slze Group (iMUSIG) model, which is a kind of discrete population balance model. Except the theories shown in Section 6.1, multiple sub-grid turbulence models and turbulence dumping need to be included since avoiding using LES or DNS is the aim of MFMS, intended for applications in practical and efficient engineering design.  
Application of MFMS on jet flow is rare in the literature. The authors of the present paper have performed a simulation of an air jet injected into water [80], with air as the dispersed gas phase and water as the continuous liquid phase, both in a Eulerian framework. Since the bubble sizes were observed ranging from 1 to 10 mm, much velocity discrepancy was expected, and the dispersed phase was divided into two velocity groups and six size groups, thus forming a three-phase Eulerian simulation. The distribution of bubble size as well as the gas volume fraction were in better agreement with the electricity probe measurement than the mono-dispersed or homogeneous MUSIG methods.  
For the simulation of jet atomization, we also developed a three-phase Eulerian method, which contains continuous gas, continuous liquid, and dispersed liquid [81]. Nine groups of droplet size from 10 um to 160 um were assumed for the dispersed liquid phase. An RMS turbulence model and the turbulence criteria shown in equations from (38) to (40) were adopted for obtaining the transition rates from continuous liquid to dispersed liquid. The computational domain with a length of 0.5 m was meshed by two million cells, which is more acceptable than the interface capturing method for practical engineering usage. The comparison with the experiment reveals reasonable agreement in aspects such as jet spreading, droplet coalescence, and distribution of droplet sizes. However, this study only serves as a primary exploration, and it is necessary to adjust the parameters of the droplet collision model or to develop a new model to take care of the secondary evolvement of the droplets and hence better predict the droplet size distribution downstream. To realize this, more experimental measures must be carried out for validation purposes.
## 4 Numerical Experiments
### Model Analyses  
The single-period model under the rolling horizon framework is tested on all instances with three and seven planning cycles, respectively. We first study the robust solution and the deterministic solution on three planning cycles, where the robust solution is proposed by this work and the deterministic solution is solved by the average demands \(\bar{d}\). Then the planning horizon crossing strategy is studied on instances with three and seven planning cycles. All gaps are calculated by  
\[\text{Gap}=\frac{\text{Obj}_{\text{other}}-\text{Obj}_{\text{baseline}}}{\text {Obj}_{\text{baseline}}}\times 100\%. \tag{30}\]  
Table 2 shows the total cost of the robust solution and the deterministic solution when the real demands are \(d=\bar{d}\) or \(d=\bar{d}+\bar{d}\). The baseline is the robust solution. The gap between the robust solution and the deterministic solution when the real demands are \(\bar{d}\) is only 1.12%. This gap is so small that we can hardly use more times experiments to exclude the influence of solution errors on the results. Because the solution is solved by the meta-heuristic algorithm and we cannot evaluate the gap between the obtained best solution and the optimal solution. It can explain why the robust solution is better than the deterministic solution in a few instances. When the real demands are the worst case (\(d=\bar{d}+\bar{d}\)), the robust solution outperforms the deterministic solution 49.86% on average.  
To evaluate the performance of our planning horizon crossing strategy, we test with and without this strategy on instances with three planning cycles and seven planning cycles. The baseline is the solution with planning horizon crossing strategy. Note that the planning horizon in the first and the last planning cycle are not crossing (\(H=T\)).  
\begin{table}
\begin{tabular}{l c c c c c c} \hline \hline \multirow{2}{*}{**Instances**} & \multicolumn{3}{c}{**Average Demands**} & \multicolumn{3}{c}{**Maximum Demands**} \\ \cline{2-7}  & **Robust** & **Deterministic** & **Gap** & **Robust** & **Deterministic** & **Gap** \\ \hline n32 & 163,211.08 & 162,561.91 & \(-\)0.40\% & 593,052.13 & 1,061,567.47 & 79.00\% \\ n33a & 163,960.52 & 160,677.23 & \(-\)2.00\% & 654,320.31 & 1  
As shown in Table 3, the gap between the model with and without planning horizon crossing in three cycles and seven cycles are 6.31% and 15.21%, respectively. The result shows that the planning horizon crossing strategy can balance short-term decisions and long-term decisions, and reduce the out-of-stock cost before replenishment arrives in each planning cycle.
# Design and Implementation of LoRa Based IoT Scheme for Indonesian Rural Area  
[PERSON]  
1 Department of Electronic and Computer Engineering (ECE), National Taiwan University of Science and Technology, Taipei City 106, Taiwan; d10702804@mail.  
several sensors through the specifically proposed platform committed for agricultural-based applications. For instance, the monitoring scheme to measure soil conditions as well as the current weather is discussed. They also introduced the use of a cloud-based system for the entire IoT solution.  
In Indonesia, most farmers are located in rural areas where the communication network is not stable enough for IoT construction [6]. In reality, we need to overcome the availability of network resources. To solve the problem, we proposed the development of an IoT scheme based on Long Range Wide Area (LoRa) communication to send the data to the cloud or remote server. As we know, LoRa is the pioneering of long-range connections with low power consumption and can be one of the solutions for limited resources [7; 8].  
Therefore, using the LoRa based approach, we can reach long-range communication compared to Bluetooth or other wireless communications [9]. Additionally, not only can it address long distances, but LoRa can also save on power consumption. Comparing to other conventional wire or wireless communications, LoRa is beneficial to be employed in areas with very limited access to the ideal infrastructure. For example, as listed in [8], LoRa has a wide coverage area and supports a private deployment compared to NB-IoT and Sigfox that need licensed spectrum, which may limit the flexibility of the deployment. Furthermore, compared to WiFi, Zigbee, and Bluetooth, LoRa has a relatively low power consumption [8]. Then, several contributions of using our approach can be listed as follows. First, the scheme to implement low power and long-distance communication for the agricultural sector in the Indonesian rural area is designed. Then, we also provide an affordable monitoring solution for Indonesian farmers. Eventually, we conduct an analysis of some factors affecting the performance of LoRa-based communications in a real environment in agricultural fields. The rest of our paper is written as follows. Related work discusses several studies and approaches for IoT solutions implemented in the agricultural sector. After that, the explanation of the proposed scheme is elaborated in design and implementation. Thus, we analyze the experimental results of our study. Finally, future work and the conclusion are stated in the last section.
# Design, Synthesis, and Cell Lines Studies of Oleanolic Acid--Hydrogen Sulfide Donor Hybrids
## 3 Results and Discussion
### The Antiproliferative Activities of Compounds in Different Cancer Cell Lines
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & \multicolumn{3}{c}{**IC\({}_{50}\) (\(\mu\)M) \({}^{\text{a}}\)**} \\ \hline
**12a** & \(41.6\pm 4.3\) & \(38.1\pm 3.7\) & \(54.2\pm 3.5\) \\
**12b** & \(39.7\pm 5.2\) & \(31.5\pm 2.1\) & \(48.7\pm 5.9\) \\
**14a** & \(35.4\pm 5.3\) & \(47.5\pm 2.4\) & \(85.2\pm 7.7\) \\
**14b** & \(31.5\pm 4.2\) & \(41.9\pm 3.6\) & \(74.2\pm 8.6\) \\
**14c** & \(37.8\pm 5.1\) & \(52.8\pm 4.1\) & \(89.9\pm 7.8\) \\
**18a** & \(28.7\pm 3.5\) & \(29.8\pm 2.3\) & \(45.9\pm 4.5\) \\
**18b** & \(25.7\pm 3.1\) & \(27.5\pm 2.9\) & \(41.2\pm 3.3\) \\
**18c** & \(21.5\pm 2.9\) & \(19.7\pm 1.5\) & \(31.4\pm 2.1\) \\
**18d** & \(13.6\pm 2.5\) & \(11.8\pm 1.1\) & \(19.10\pm 1.9\) \\
**18e** & \(31.2\pm 2.8\) & \(25.1\pm 3.1\) & \(38.8\pm 3.5\) \\
**18f** & \(29.7\pm 2.7\) & \(21.9\pm 2.3\) & \(32.6\pm 1.7\) \\
**OA** & \(75.2\pm 6.7\) & \(113.6\pm 4.7\) & \(>\)200 \\
3-oxooleanolic acid & \(41.8\pm 3.4\) & \(96.8\pm 3.6\) & \(137.5\pm 5.6\) \\ oxaliplatin & \(12.77\pm 1.88\) & \(13.00\pm 1.23\) & \(14.62\pm 0.78\) \\ \hline \hline \end{tabular} \({}^{\text{a}}\) At least three independent experiments were conducted to express results as the mean \(\pm\) SD by the MTT assay.  
\end{table} 
Table 1: _Cont._  
Figure 1: The structures of three kinds of H\({}_{2}\)S donors. A549 cell lines. Especially, the cytotoxicities of **18c** and **18d** against A549 were higher than those of other cell lines, which may be due to the expression of PepT1 in A549, but not in other cells. On the basis of the above results, the most promising compounds, **18c** and **18d**, were evaluated for possible cytotoxicity towards normal human liver cells (LO2) to investigate whether the prodrugs have a tumor-cell-selecting activity. Interestingly, the growth of LO2 cell lines was not significantly affected by **18c** and **18d**, indicating that **18c** and **18d** selectively inhibit the growth of tumor cells (Table 3).
# Compact SOI Dual-Mode (De)multiplexer Based on the Level Set Method
## 5 Conclusions  
In conclusion, we designed and demonstrated a dual-mode (de)multiplexer device on an SOI platform. The device has a compact footprint of 9.4 \(\upmu\)m \(\times\) 2.9 \(\upmu\)m and features a simply connected structure with a minimum feature size exceeding 200 nm, ensuring stable fabrication. The experimental results indicate that the device exhibited low IL (<0.89 dB) and low CT (<\(-\)24 dB) for both TE\({}_{0}\) and TE\({}_{1}\) modes within the wavelength range of 1530-1570 nm. With a fabrication deviation of 40 nm, the results of IL increased to 1.5 dB and CT to \(-\)13 dB, demonstrating sufficient robustness in fabrication. The device's exceptional performance, ultra-compactness, and stable fabrication characteristics make it a promising candidate for large-scale and highly integrated on-chip mode-division-multiplexing systems.  
Conceptualization, S.Y. and Y.Y.; methodology, H.Z. and S.Y.; software, H.Z., S.Y. and Y.Y.; validation, S.Y. and L.Z.; formal analysis, S.Y. and Y.Y.; investigation, L.Z.; resources, S.Y. and Y.Y.; data curation, H.Z.; writing--original draft preparation, H.Z. and S.Y.; writing--review and editing, H.Z., S.Y. and Y.Y.; visualization, H.Z. and S.Y.; supervision, L.Z.; project administration, Y.Y.; funding acquisition, Y.Y. All authors have read and agreed to the published version of the manuscript.  
This work was funded by the National Natural Science Foundation of China (62174128, 61975198); State Key Laboratory of Information Photonics and Optical Communications (IPOC2021 ZT11); Fundamental Research Funds for the Central Universities (XJSJ23177); and Xian City Science and Technology Plan Project (22)BGS-QCY4-0006).  
Not applicable.  
Data underlying the results presented in this paper are not publicly available at this time due to privacy but may be obtained from the authors upon reasonable request.  
The authors declare no conflicts of interest.
###### Abstract  
This study proposes a simplified approach for the experimental dynamic characterization of the historic Messina Bell Tower (northeastern Sicily) using passive seismic single-station surveys. The Horizontal-to-Vertical Spectral Ratio (HVSR) analysis identified a site resonance frequency of approximately 1.06 Hz, while the Multichannel Analysis of Surface Waves (MASW) survey contributed to the characterization of the shear wave velocity profile, providing a coherent geophysical framework useful for structural dynamic analysis. Spectral ratios analysis revealed four distinct vibration modes, including a fundamental rocking mode (~1.4 Hz), a torsional mode (3.5 Hz), and two higher-frequencies flexural modes. The structure's dynamic behavior, notably its sensitivity to torsion and rocking, is attributed to the deformable subsoil. Damping ratios estimated via the Random Decrement Method (RDM) were below 1%, consistent with the expected linear elastic response under ambient vibrations. The results show strong agreement with previous long-term monitoring, validating the effectiveness of passive seismic techniques for rapid, non-invasive assessment. This study demonstrates that streamlined, time-efficient methodologies are capable of delivering modal parameters consistent with those obtained from more extensive and resource-intensive monitoring campaigns, thereby providing a reliable and practical approach for the seismic vulnerability assessment of heritage structures.  
Keywords:passive seismic survey; simplified dynamic characterization; vibration frequencies; mode shapes; HVSR; MASW Article