esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods  
### Partial Differential Equation (PDE) Cases  
This manuscript focuses on three cases of PDEs: the 1D Allen-Cahn equation (AC equation), the 1D Burgers equation, and the 2D wave equation.  
The AC equation is a PDE that describes the phenomenon of phase transitions, and it is widely used in materials science [31]. The AC equation is used to describe the evolution of interfaces between different phases (e.g., solids and liquids) in a material. An important characteristic of the AC equation is that it is capable of modeling fuzzy regions of phase transition interfaces, rather than just well-defined boundaries. The standard form of the Allen-Cahn equation can be written as:  
\[\frac{\partial u}{\partial t}=e^{2}\
abla^{2}-W^{\prime}(u) \tag{1}\]  
where \(u(x,\ t)\) is the function that describes the state of the material, \(t\) represents time, \(x\) is the spatial coordinate and \(\epsilon\) is a small positive number referred to as the interface width parameter. The \(W(u)\) is potential energy function, \(W^{\prime}(u)\) is the derivative of \(W(u)\) with respect to \(u\). The first term \(e^{2}\
abla^{2}\) of this equation represents the diffusion term, which describes the ambiguity of the phase transition interface. The second term \(-W^{\prime}(u)\) represents the potential energy term, which describes the difference in energy of the material between phases, driving the system to tend to reach an energy minimum.  
The 1D AC equation is a special case of the Allen-Cahn equation in which only one spatial variable \(x\) is involved and can be expressed as follows:  
\[\frac{\partial u(x,t)}{\partial t}=e^{2}\frac{\partial^{2}u(x,t)}{\partial x ^{2}}-W^{\prime}(u), \tag{2}\]  
The Burgers equation integrates a nonlinear convection term and a viscous diffusion term and can be used to model a variety of complex fluid dynamics phenomena [32]. The Burgers equation is a 1D nonlinear PDE, which is expressed as follows:  
\[\frac{\partial u(x,t)}{\partial t}+u(x,t).\frac{\partial u(x,t)}{\partial x}= v\frac{\partial^{2}u(x,t)}{\partial x^{2}}, \tag{3}\]  
where \(u(x,t)\) represents the velocity field as a function of space \(x\) and time \(t\), and \(v\) is a positive constant and represents the viscous coefficient.  
The wave equation is a partial differential equation that describes the propagation and interaction of waves in space. It is widely used in physics, engineering, and mathematics to study the propagation behavior of water, sound, and light waves in a plane [29]. Equation (4) denotes the lossless two-dimensional wave equation:  
\[\frac{\partial u(x,y,z)}{\partial t^{2}}=c^{2}\left(\frac{\partial u(x,y,t)}{ \partial x^{2}}+\frac{\partial^{2}u(x,y,t)}{\partial y^{2}}\right), \tag{4}\]  
where \(u(x,y,t)\) denotes the displacement of point \((x,y)\) at time instance \(t\) for the wave in the plane, and \(c\) is the velocity of the 2D wave.
# Blockchain Applications in Forestry: A Systematic Literature Review
## 4 Blockchain Applications in the Forestry Sector
### Traceability  
Eleven included articles (52%) proposed and/or investigated the blockchain-based applications on traceability of wood (products) in forestry. These blockchain-based traceability systems have been designed to prevent illegal loggings/timbers and increase the purchaser's trust. In general, blockchain technology has been applied to traceability sys  
Figure 5: Taxonomy of blockchain applications in forestry. tems to track forest-based (woody) products--information of each timber uploaded into blockchain by actors involved in the wood supply chain. The actors in the supply chain could include, but are not limited to, forest farmers, suppliers, transportation companies, manufacturing companies, and customers. All actors can access all the data in the wood supply chain. Table 2 shows the data extracted from included articles related to the traceability of wood products. This subsection presents and analyzes the details of these blockchain applications for the traceability of forest-based products in Table 2. In Table 2, only nine of eleven included articles are listed. That is because extracted data of these two included articles [32; 33] are not suitable for this subsection. In reference [32], [PERSON] et al. analyzed the advantages, benefits, disadvantages, and dangers of blockchain in illegal wood. The included article [33] is a similar article that discussed the strengths, weaknesses, opportunities, and threats of blockchain for illegal timber trading. The data extracted from these two articles is presented and analyzed in Section 5. [PERSON], [PERSON] et al. [40] proposed a method to improve the blockchain-based wood traceability system using the AKAZE method. The study focused on improving the technology of wood product identification in the traceability system. The technology could distinguish the unique texture feature of wood products which can replace traditional image-based methods of wood product identification in the blockchain-based wood traceability system [40]. The workflow of this system has two processes: uploading and identification. The uploading process is to upload images (raw images) by workers. The workers take images of wood products and upload them to the systems. Once the image is uploaded, the AKAZE method detects the image feature's key points. Then, the dataset of key points is uploaded to the blockchain system. The identification or the matching process is processed by customers. When customers receive wood products, they could take an image of woodblock and match it with the dataset of key points downloaded from the wood blockchain system [40]. [PERSON] and [PERSON] [39] proposed a system based on blockchain technology to identify the validity of teak wood within the teak supply chain from farmers to end-users. The study presented the proposed system's workflow (physical and data). The teak wood supply
## 2 Analysis and Design of a Sun Tracking Control System
### Experimental Setup  
In the work presented in this paper, the block diagram of the experiment setup is shown in Figure 9. In the one MW HCPV demonstration power plant, the console gets the Direct Normal Irradiance (DNI) values from the DNI equipment and DC power from the grid inverter.  
The console gets the sun position sensor data through the sun tracking control system and records the data and analysis.  
Figure 8: Flow diagram of path following controller.  
Figure 9: Block diagram of experiment setup.  
Figure 11 shows the comparison between LBS control and PID control for the point where best suppression was achieved. The time traces show that between 36-66 minute, the cloud influences the sun light making the x(AZ) or y(EL) present a larger tracking error. Besides, the system is in an unstable state. The LBS control shows that between 36-66 minute, the tracking error is confined to within 30. The system is stable and bounded.  
Although the lower setpoint of the switch makes the tracking system more stable, it is also inaccurate. However, the tracking system is stable and accurate, when the optimal lower setpoint of switch(**S**) is in the range of 10.  
Figure 12 shows the comparison between LBS control (diamond point) and PID control (square point) for the output power based on the same Direct Normal Irradiance (DNI). The X axis (DNI) traces show that at 0-650 watts per cm\({}^{2}\), the cloud influences the sun light causing different DNI. The PID control shows that at 0-470 watts per cm\({}^{2}\), the output power is lower than LBS. The LBS control switches the reference tracking control to the path following control to get more power under low DNI. But in the range, 470-650 watts per cm\({}^{2}\), less cloud results in less power loss in the PID control. The output power of the PID control is almost the same as the LBS control.
## 2 Marinization Methodology  
HPUTs are typically bolted onto the outer wall of an ultrasonic bath, resulting in no contact with water, which means that there is no requirement for a marinization technique. The marinization is sub-contracted to STS Defense [17]. This is done by housing the HPUT within a Restriction of Hazardous Substances (RoHS) compliant and Mercury-free Polyurethane 3D printed enclosure (see Table 1 for material properties). This allows a marinized cable to run through the housing, which is then soldered onto the contact plates of the HPUT. Once the cable is attached to the HPUT electrodes (similarly to Figure 1), a RoHS compliant and mercury-free polyurethane potting is injected into the housing, and then filled to the opening of the housing to ensure that the contact plates and Piezoelectric elements are sealed from any water contact. The design of the 3D printed enclosure is shown in Figure 2.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Test** & **Result** \\ \hline Flammability & Not flame retardant \\ Volume Resistivity & 13–1510 ohm.cm \\ Surface Resistivity & 12.5–14.510 ohm.cm \\ Dielectric Constant & 3.1 \\ Breakdown Voltage & 20 KV/mm \\ Hardness & 70 Shore A \\ Tensile Strength & 3–4 MPa \\ Operating Temperature & \(-\)55 to 130 \({}^{\circ}\)C (application and geometry dependent) \\ Elongation at Break & 200\% \\ \hline \hline \end{tabular}
\end{table}
Table 1: Material properties of polyurethane used for marinization of the HPUT.  
Each HPUT is connected to a flame retardant, halogen-free, 6.4 mm diameter, marinized RG58 cable. A cross-section of the cable along with material descriptions are presented in Figure 3 and Table 2. The confirmed number of HPUTs found [16] undergo marinization with a 10 m long marinized cabling with a BNC connection; a summary of the marinization requirements are shown in Table 3.  
Figure 1: Example of cable connection to High-Power Ultrasonic Transducer (HPUT) using a male BNC test lead cable.  
Figure 2: Technical drawing of 3D-printed housing to encapsulate the 40 kHz HPUT.  
_HUPt Marinization Characterization_  
To characterize any changes in power delivery to the HPUTs by the addition of the marinization material, the Agilent 4294A Precision Impedance Analyzer [18] is used to measure the 40 kHz HPUTs before and after marinization. Figure 4 shows that the addition of the marinization material has increased the impedance of the HPUTs resonant frequency which also contributes to a partial shift in the resonant frequency. The anti-resonant frequency has reduced in impedance, implying that the marinization technique is dampening the HPUT components. This causes the HPUT to become more broadband.  
\begin{table}
\begin{tabular}{c c c} \hline \hline \# & **Component** & **Material** \\ \hline
1 & Central Conductor & Tanned Copper \\
2 & Dielectric & Solid Polyethylene \\
3 & Outer Conductor & Tanned Copper Wire Braid \\
4 & Inner Jacket & PVC TM2 \\
5 & Outer Jacket & Polyurethane \\ \hline \hline \end{tabular}
\end{table}
Table 2: Component and material description of marinized RG58 cable.  
Figure 3: Cross-section of marinized RG58 cable.
## 5 Simulation Study
### Impact of Varying the Number of Sink Nodes  
Network performance is closely related to the number of sink nodes in the network, so this group of experiments analyses performance of the three different protocols by varying the total number of sinks. The experimental results can be seen in Figure 10.  
We can easily verify that as the number of sink nodes increases, the delivery ratios of all protocols rise and ARP always achieves the best performance compared with the other two protocols. This is because sensor nodes have better opportunity of meeting sink nodes as the number of sink nodes increases. Thus, messages have a better chance to be delivered before they are dropped. We also find in the experiment that the locations where the sink nodes put have great impact on data delivery ratio. If the sink node is put near \"office\" marked as 3, a data delivery ratio of 60% can be achieved, but if the sink node is put near \"office\" named 3, the data delivery ratio can only reach 46.2%.  
It is also noticed that the transmission overhead of the proposed ARP, LABEL and flooding protocols all increase with the increase of the number of sink nodes, as shown in Figure 10(b). Additionally, the number of average message copies generated in the flooding protocol is much larger than that in both ARP and LABEL. This is also steme from the queue management scheme in flooding. Figure 10(c) depicts the delivery delay of all protocols decrease when the sink nodes in the network increase. This is reasonable because messages have higher opportunity of meeting the sink nodes.  
Figure 10: Impact of the number of sink nodes: **(a)** Average delivery ratio; **(b)** Average copies; **(c)** Average delay.  
Figure 9: Impact of queue length: **(a)** Average delivery ratio; **(b)** Average copies; **(c)** Average delay.
## 2 Materials and Methods  
The spatial databases used in this research are consistent with the proposed purpose of this GIS model of spatial analysis, more precisely, that of using free spatial databases and satellite imagery with high temporal extension, for the semi-automatic delineation and evaluation of the built-up area dynamics. The first stage, which aims at the rapid delimitation of the built-up areas, is based on the analysis of Landsat Level 1 satellite images by using remote-sensing spectral indices.  
The remotely sensed used in this research (Table 1) are Landsat satellite images (5-Thematic Mapper; 7-Enhanced Thematic Mapper Plus and 8-Operational Land Imager & Thermal Infrared Sensor), covering a period of 19 years, between 2000 and 2019. The images used have a very good quality, a very small amount of clouds, which are generally present, outside the study area.  
The Landsat Thematic Mapper (TM) sensor carried by Landsat-5 provides images in six spectral bands with a spatial resolution of 30 meters for Bands 1-5 and 7, and one thermal band (Band 6) acquired at 120-meter resolution, but re-sampled to 30-meter pixels.  
The Landsat Enhanced Thematic Mapper Plus (ETM+) sensor carried by Landsat-7 satellite provides image in seven spectral bands with a spatial resolution of 30-meters for Bands 1-5 and 7. The ETM+ includes additional features in comparison with Landsat-5 TM that make it a more versatile  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Capture Date** & **Scene** & **Sensor** & **Bands** & \begin{tabular}{c} **Spatial** \\ **Resolution** \\ **(m)** \\ \end{tabular} & \
\begin{tabular}{c} **Cloud** \\ **Amount** \\ **(\%)** \\ \end{tabular} &
\begin{tabular}{c} **RMSE** \\ **(m)** \\ \end{tabular} \\ \hline (a) 2000-08-22 & Landsat-7 & ETM+ & 8 & 30 & 1 & 2.323 \\ (b) 2005-10-07 & Landsat-7 & ETM+ & 7 & 30 & 0 & 5.079 \\ (c) 2010-08-26 & Landsat-5 & TM & 7 & 30 & 12 & 4.062 \\ (d) 2013-08-02 & Landsat-8 & OLI&TIRS & 11 & 30 & 3.21 & 7.477 \\ (e) 2016-08-26 & Landsat-8 & OLI&TIRS & 11 & 30 & 0.48 & 6.783 \\ (f) 2019-07-02 & Landsat-8 & OLI&TIRS & 11 & 30 & 0.01 & 7.644 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Satellite imagery used in this study.  
Figure 1: Geographic location of the study area.  
and efficient instrument for land cover change monitoring and assessment, such as: a panchromatic band (Band 8) with a 15-meter spatial resolution; on-board, full aperture, 5% absolute radiometric calibration; thermal band (Band 6) acquired at 60-meter resolution, re-sampled to 30-meter pixels; an on-board data recorder.  
Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS), two primary sensors carried by Landsat-8, generate combined images in eleven spectral bands. Seven of the eleven spectral bands are basically consistent with ETM+ found on Landsat-7. In addition, Landsat-8 provides an Ultra Blue (coastal/aerosol) and cirrus cloud detection band. Furthermore, the thermal band is acquired on two spectral channels at 100-meters (re-sampled to 30-meters) for more accurate surface temperatures [52].
# Advanced Progress of Optical Wireless Technologies for Power Industry: An Overview
## 3 Wireless Power Transfer of Power Industry Optical Wireless Communications
### Dynamic Optical Wireless Power Transfer
In recent years, optical wireless technology has become more and more important. Check the freepatantsononline website about OWC, IWOC, PLC patents, there are as many as several million in each field, enough to see that optical wireless technology is widely used in today's society, which is a research hotspot. There are also hundreds of thousands of patents related to power industry and optical wireless communication, indicating that the combination of power industry and optical wireless technology is a feasible solution. Similarly, according to CNKI statistics, there are 200 Chinese patents related to optical wireless communications from 1986 to 2020. Furthermore, Chinese patents related to visible light communication amounted to nearly 14,000, with an average of more than 1000 patents per year in the past eight years. It covers the power industry, telecommunications technology, computer software and computer applications, automation technology, radio electronics, and other multidisciplinary fields. There are also nearly 10,000 patents related to PLC, with an average of more than 800 articles per year in the past eight years. In addition, Chinese patents for the combination of visible light communications and PLC can be traced back to 2011. There are still relatively few patents on the combination of smart power and wireless optical technologies. Optical wireless and wireless optical have always been used by researches in the communication field, meanwhile power grid and smart grid belong to the categories of the power industry. Therefore, on the World Intellectual Property Organization (WIPO) official website we searched \"smart grid,\" \"optical wireless,\" \"power line,\" \"visible light communication,\" \"free space optical,\" \"power grid,\" and so on, and realized the search of related patents in the field of power optical wireless from 2012 to 2020, and obtained 45 patents with these themes, as shown in Figure 31 [125]. It can be seen from the figure that in the past five years, power industry optical wireless technologies have been more and more widely used. Therefore, exploring the power technology under optical wireless technologies has great development prospects. Figure 31: 2012–2020 statistical analysis chart based on power industry optical wireless patents from WIPO [125].
# Cascaded Regression-Based Segmentation of Cardiac CT under Probabilistic Correspondences
## 2 Materials and Methods  
### Patients  
In total, 35 cardiac CT angiography (CCTA) volumes were used for the evaluation of cardiac CT segmentation. These volumes were acquired at our institution (Cardiovascular Center, Seoul National University Bundang Hospital, Seoul, South Korea). The need for informed consent was relinquished because of the retrospective nature of this study. We used a 256-slice CT scanner (iCT256, Philips Healthcare/ Philips Medical System, Eindhoven, The Netherlands). Volumes were downsampled by an integer value two along three axes for effective execution. Therefore, the x and y dimensions were adjusted to \(256\times 256\). For evaluation, six-fold cross-validation was performed by dividing 35 cases into six-groups of [6; 6; 6; 6; 6; 5] cases. Five groups were selected as the training sets, and the remaining group was used as the test set. Two engineers with bioengineering major participated in the delineation of the LA and the inner and outer boundary of the LV by using ITKSANAP software [29]. One engineer has an experience of 10 years, and the other engineer has an experience of 3 years. The mask from the 10 years experience engineer was generated for a gold standard mask. The remaining mask was used for repeatability calculation.
# An Automated Framework for Streamlined CFD-Based Design and Optimization of Fixed-Wing UAV Wings
## 6 Optimization Case Study  
To demonstrate the power of the automated CFD framework, one aerodynamic shape optimization case study is conducted. This includes a conventional UAV wing with the goal of showcasing the adaptability and robustness of the algorithm. The objective of optimization is to maximize the lift-to-drag (\(L/D\)) while also satisfying the sensitive stability constraints. All the design variables described in Section 2 are selected, except for the dihedral angle, since it plays a minor role in the aerodynamic performance and the longitudinal stability of the UAV [6; 7].  
Bayesian Optimization (BO) was chosen for these cases, as it is a method well-suited for high-cost optimization problems [68]. BO utilizes a surrogate model, typically a Gaussian Process (GP), to map the aerodynamic behavior to inputs (i.e., the design variables). The Expected Improvement (EI) criterion drives the algorithm in balancing exploration (unseen design areas) and exploitation (refining promising regions), enabling efficient exploration of high-dimensional design spaces while minimizing the number of analyses required. Classic BO does not offer a straightforward way of incorporating constraints into the optimization formulation. To tackle this, [PERSON]. [69] introduces Constrained Bayesian Optimization (cBO), which incorporates inequality constraints by placing Gaussian Process priors on both the objective and constraint functions. This approach allows for the optimization of an expensive objective function while simultaneously considering feasibility constraints. For the CFD analyses, the AUTh HPC infrastructure was utilized, using the specifications described in Table 6.
## 2 Experimental Setup
### TCPC Models Preparation  
In order to perform bench tests, we manufactured three TCPC samples of various shapes. Their dimensions and geometry are shown in Figure 1. The finalized TCPC model is shown Figure 2C. The manufacturing process of the Fontan compound consists of several stages. ABS plastic blanks that repeat the geometry of the TCPCs were prepared via the Fortus 450 mc (Stratasys Ltd., Rehovot, Israel) 3D printer. In order to connect TCPC to the hydraulic circuit, we used fittings with an inner diameter of 6 mm (Camozzi 2601 9-1/4, Camozzi Automation S.p.A., Brescia, Italy), which were installed in a transparent plexiglass base. To visualize the fluid flow, the layout is poured with Clear Flex 50 transparent polyurethane (Smooth-On, Inc., Macungie, PA, USA). After complete hardening, the product is placed in acetone that dissolves the 3D layout, forming a cavity inside the polyurethane form. The upper and lower surfaces of the model are completely transparent and allow us to visually observe the fluid flow profile.  
The transparency of the side faces contributes to minimal loss of laser beam power when passing from the outer walls to the internal cavity of the TCPC model.  
Figure 1: Schematic of three different geometry configurations of total cavopulmonary connections (TCPCs) chosen for the research in this work. (**A**) Simple direct joint, where the inferior vena cava (IVC) and superior vena cava (SVC) are coaxially arranged (model is shown with dimensions). (**B**) Compound where the IVC and SVC are shifted by the distance of a single diameter (6 mm). This type of compound is often used in TCPC surgery. (**C**) More complex type of curvilinear connection, where IVC is divided into two vessels and connected to the left pulmonary artery (LPA) and right pulmonary artery (RPA) at an angle, directing the flow along a smoother trajectory.