esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Wave Equations and Theoretical Wave Velocities
### Zero Permeability  
For the case of zero permeability, there is no relative motion between the pore fluid and the solid skeleton. The strong viscous coupling makes the P2 wave attenuate to zero rapidly. Because \(w\) is equal to zero, the fluid relative velocity \(\tilde{w}\) and acceleration \(\tilde{w}\) are equal to zero, and the terms of permeability in Equations (5) and (6) are ignored. Equations (5) and (6) is simplified as:  
\[(\lambda+G)\
abla\
abla\cdot\mathbf{u}+G\
abla^{2}\mathbf{u}-\alpha\
abla p-\rho\tilde {\mathbf{u}}=\mathbf{0} \tag{35}\]  
\[\alpha\
abla^{T}\tilde{\mathbf{u}}+\frac{1}{Q_{b}}\dot{p}-\mathbf{0} \tag{36}\]  
Referring to the method in the literature [35], Equation (36) is substituted into Equation (35). Two uncoupled equations about only the displacements are shown below:  
\[\left\{\begin{array}{l}\rho\frac{\partial^{2}u_{r}}{\partial t^{2}}=\big{(} \lambda+2G+\alpha^{2}Q_{b}\big{)}\bigg{(}\frac{\partial^{2}u_{r}}{\partial r ^{2}}+\frac{1}{r}\frac{\partial u_{r}}{\partial r}-\frac{u_{r}}{r^{2}}\bigg{)} \\ \rho\frac{\partial^{2}u_{\theta}}{\partial t^{2}}=G\bigg{(}\frac{ \partial^{2}u_{\theta}}{\partial r^{2}}+\frac{1}{r}\frac{\partial u_{\theta} }{\partial r}-\frac{u_{\theta}}{r^{2}}\bigg{)}\end{array}\right. \tag{37}\]  
In two dimensional cylindrical coordinates, the displacement potential functions, respectively, are expressed by the radial and tangential components:  
\[\left\{\begin{array}{l}u_{r}=\frac{\partial\varphi}{\partial r}\\ u_{\theta}=\frac{\partial\varphi}{\partial r}\end{array}\right. \tag{38}\]Equation (38) is substituted into Equation (37), and the wave equations of the displacement potential functions are obtained:  
\[\frac{\partial^{2}\varphi}{\partial t^{2}}=C_{P1}^{2}\bigg{(}\frac{\partial^{2} \varphi}{\partial r^{2}}+\frac{1}{r}\frac{\partial\varphi}{\partial r}\bigg{)} \tag{39}\]  
\[\frac{\partial^{2}\psi}{\partial t^{2}}=C_{S}^{2}\bigg{(}\frac{\partial^{2} \psi}{\partial r^{2}}+\frac{1}{r}\frac{\partial\psi}{\partial r}\bigg{)} \tag{40}\]  
where the velocities of P1 and S waves, respectively, are:  
\[\left\{\begin{array}{l} C_{P1}=\sqrt{\frac{\lambda+2G+\alpha^{2}Q_{b}}{ \rho}}\\ C_{S}=\sqrt{\frac{G}{\rho}}\end{array}\right. \tag{41}\]  
Equation (39) and Equation (40), respectively, are the wave equations of P1 and S waves under the zero-permeability condition.
## 4 Results
For qualitative comparison, Figures 8-11 were evaluated qualitatively by 36 subjects. The subjects assessed the resulting images generated by the previous methods and our approach by assigning a score from 1 (poor) to 5 (good). Table 4 shows the average scores of the resulting images for the approaches. The average scores of HDRCNN [10], DrTMO [8], ExpandNet [14], SingleHDR [11], and the proposed approach were 3.25, 3.26, 3.74, 3.86, and 3.63, respectively. Our approach was better than HDRCNN and DrTMO, but slightly worse than ExpandNet and SingleHDR. Hence, the proposed approach can maintain a certain quality for reconstructing comparable HDR images. \begin{table}
\begin{tabular}{c c} \hline \hline \multicolumn{2}{c}{**Average Score**} \\ \hline HDRCNN [10] & 3.25 \\ DrTMO [8] & 3.26 \\ ExpandNet [14] & 3.74 \\ SingleHDR [11] & 3.86 \\ The Proposed Approach & 3.63 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Qualitative evaluation. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Input Image** & **Stage 1** & **Stage 2** \\ \hline PSNR & 14.218 & 19.314 & 19.587 \\ SSIM & 0.560 & 0.711 & 0.724 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: PSNR and SSIM evaluation results of original images and the resulting images of the two stages on tone-mapped images. \begin{table}
\begin{tabular}{c c c} \hline \hline  & **PSNR** & **SSIM** \\ \hline HDRCNN [10] & 17.782 & 0.683 \\ DrTMO [8] & 18.515 & 0.731 \\ ExpandNet [14] & 20.387 & 0.729 \\ SingleHDR [11] & 21.895 & 0.774 \\ The Proposed Approach & 19.587 & 0.724 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Comparison of the proposed approach with the previous methods. Figure 8: The visual comparison of the proposed approach with the previous methods. (**a**) Input image, (**b**) HDRCNN, (**c**) DrTMO, (**d**) ExpandNet, (**e**) SingleHDR, and (**f**) the proposed approach. Figure 9: The visual comparison of the proposed approach with the previous methods. (**a**) Input image, (**b**) HDRCNN, (**c**) DrTMO, (**d**) ExpandNet, (**e**) SingleHDR, and (**f**) the proposed approach.
# Jet Noise in Airframe Integration and Shielding
### Jet--Pylon Interactions  
When an aircraft engine is mounted to the wing, the engine pylon provides an aerodynamic shape around the rod support that connects the engine's core housing to the wing structure. In the conventional aircraft designs, where the engine is placed under the wing, installation effects due to the pylon can modify the flow. These asymmetries in the flow field caused by the pylon affect the exhaust plume, and as a result, change the far-field acoustics. In general, the pylon increases the OASPL in the far-field [2].  
[PERSON] [3] carried out experiments on a bypass ratio five separate flow nozzle to measure the effect of the pylon relative to the baseline axisymmetric nozzle. The effect of adding the pylon was found to increase the EPNdB relative to the baseline, from 1 to 3 EPNdB at different power settings. [PERSON] and [PERSON] [4] performed experimental studies to investigate acoustic effects of jet-pylon interaction for separate flow and chevron nozzles of both a bypass ratio five and eight. They concluded that, for the bypass ratio eight configuration, the effect of adding a pylon to the baseline nozzle is to slightly increase the noise for the case with a core chevron. Figure 1 shows the pylon installed on the separate exhaust nozzle, along with the perceived noise level (PNL) directivity.  
The model shown in Figure 1a corresponds to an approximate scale factor of nine used in the wind tunnel tests reported in [4]. One of the challenges in these investigations was the existence of several mechanisms responsible for noise generation, and since no specific pylon size or shape exists, it was difficult to quantify the individual mechanisms of noise generation. However, the effects of different pylons on an engine's exhaust flow are qualitatively similar. These effects include both modifications  
Figure 1: (**a**) Pylon installed on the separate exhaust nozzle (scale factor of 9). (**b**) perceived noise level as a function of the directivity angle for baseline, and with pylon (Ref. [4]).  
to the exhaust flow field, as well as acoustic changes due to waves reflecting from surface near the noise sources.  
One of the mechanisms responsible for modifications of the flow field due to the presence of the pylon is the deflection of the core flow. The viscous forces of the core stream cause the flow to resist separation from the pylon shelf, and consequently, the core flow is turned upwards toward the pylon. This process is generally known as the \"Coanda effect\". The other mechanism that is known as \"rooster tail effect\" follows this deviation of the core flow. The upward velocity component of the core flow cuts against the fan flow and is sucked to fill the void below the core flow, resulting in two strong counter-rotating vortices shed from the pylon. Figure 2 illustrates both the Coanda effect and the rooster tail effect.
# Evaluation of Fire Blight Resistance of Eleven Apple Rootstocks Grown in Kazakhstan Fields
###### Abstract  
Clonal rootstocks of apple trees are one of the main components of intensive horticulture, and they play an important role in regulating tree growth, yield, fruit quality, and resistance to biotic and abiotic stresses. In the two-year monitoring survey reported here, eleven rootstocks mainly used for cultivar grafting in Kazakhstan were assessed for fire blight resistance, taking genetic background into consideration. The loci FB_F7 on LG7 and FB_MR5 and RLP1 on LG3 were analyzed on the basis of SCAR and SNP markers. The rootstocks 'Geneva 41', 62-396', and 'Geneva16', bearing resistant alleles for five markers (AH0)FXM, AH21B92, AH4 AAGA, AH518 MI, and AH6R6 SQ, four markers (AH0)FXM, AH21B92, AH4 AAGA, and AH518 MI), and one (AH4 AAGA) SNP marker, respectively, were not infected during the monitoring period despite weather conditions in 2022 being favorable for the development and spread of _Erwinia amylcorora_. No connection was identified between the presence of a resistant allele for the AE10-375 marker and fire blight resistance responses. This is the first study to evaluate the fire blight resistance of foreign and local rootstocks grown in the Kazakhstan southern region.  
apple; rootstock; fire blight; loci; SNP; SCAR Article
## 5 Factors That Influence the Effectiveness of In-Vehicle Messaging
### Characteristics of Vehicle Automation  
Vehicles with Level 3 or 4 automation can monitor and maintain control of driving tasks with the expectation that a human will take over control. Levels 1 or 2 vehicle automation still require the human to maintain control of the vehicle for the majority of time [26]. These different levels (or modes) of automation create a set of factors that could potentially impact the development of in-vehicle messaging content. Specifically, automation reliability is crucial to ensuring safe and effective use of new technologies. Automation reliability is necessary to minimize demands on driver vigilance over extended periods of time when there are limited opportunities for physical engagement in vehicle control. Reliability is also necessary to offset driver performance decrements when boredom and vigilance decrements occur [117]. However, reliable automation comes with its own set of pitfalls. As the level of highly reliable automation increases, there is an increased chance of performance impairment when the automation fails. This is particularly true for Levels 2 and 3 vehicle automation, as the driver is disengaged from a significant part of the driving task but is still expected to takeover vehicle control when needed. As automation handles vehicle control and simple road hazards, drivers become disengaged [46], and their skills to handle takeovers in the event of automation failures degrade, especially for more complex situations [118].  
One possible function for in-vehicle messaging is to serve as a mitigation of automation-induced vigilance problems by providing a secondary task that might prevent the onset of boredom during an automated drive; however, there is no empirical evidence of this relationship. Proper tuning of the timing, type and amount of information is necessary to ensure messaging is helpful without resulting in increased workload on the driver in information processing. Another concern regarding characteristics of messaging displays is the amount of feedback that is provided by the automated system. As a result of the driver being disengaged from the driving task, recovery of control can differ in quality depending on the design of warnings [119, 120, 46]. Informative feedback could potentially alleviate the negative consequences of higher levels of automation by keeping the driver regularly apprised of information relevant to the driving task. However, drivers may experience some frustration with frequent messaging notifications from the vehicle for no acute reason. A potential method is to establish specific messaging intervals depending on the criticality of the message. However, this design approach requires further investigation for effectiveness.
## 4 Simulation Validation and Results Analysis  
In this paper, the whole simulation is carried out under MATLAB and Autonomie. MATLAB is a mathematical calculation software for numerical analysis, matrix operation, algorithm development, etc. Autonomie, developed by the Argonne National Laboratory, is an intelligent vehicle simulation software based on MATLAB and Simulink [22,23].  
In order to compare the optimization results, the default CD/CS strategy and the DP algorithm are applied as the benchmark. In the CD mode, the parallel PHEV is driven by the battery when the engine is off. In the CS mode, the engine will be turned on when the driveline power demand is more than the engine-on power threshold and the parallel PHEV is driven by the engine and the battery together. The engine will be turned on when the battery maximum power cannot satisfy the driveline power demand [1,6]. When the engine is on, the engine power should also consider the battery balance control, which means that if the battery SOC is lower than the pre-set value, the battery needs to be charged. The detailed CD/CS strategy can be formulated,  
Figure 8: The calculation process of simulated annealing (SA) algorithm method.  
\[P_{bat}=\left\{\begin{array}{ll}P_{o}&SOC\geq 36\%\\ \min(25317.8,P_{o})&33\%\leq SOC<36\%\\ \min(25317.8\cdot(SOC-0.3)/0.03,P_{o})&30\%\leq SOC<33\%\\ \max(-30717.3\cdot(SOC-0.3)/0.03,P_{o})&P_{o}<0,27\%\leq SOC<30\%\\ \max(-30717.3\cdot(SOC-0.3)/0.03,P_{o}-P_{eng\_max})&P_{o}>0,27\%\leq SOC<30 \%\\ \max(-30717.3,P_{o})&P_{o}<0,SOC<27\%\\ \max(-30717.3,P_{o}-P_{eng\_max})&P_{o}>0,SOC<27\%\end{array}\right. \tag{20}\]  
where \(P_{eng\_max}\) indexes the maximum power of engine. Based on (20), the battery power is calculated according to the current SOC. In the CD mode, the vehicle is only powered by the battery if the battery SOC is more than 0.36. In the CS mode, the engine is turned on and the battery is charged to hold the SOC near 0.3. In order to verify the control performances more widely, different initial SOC values are considered. We select the initial SOC of 0.9, 0.8 and 0.7 to verify the controlling performances.
# Bot-Based Emergency Software Applications for Natural Disaster Situations
## 3 Bot-Based Applications for Natural Disasters
### Rimay Application  
Rimay ([[https://citiaps.usach.cl/portafolio/rimay](https://citiaps.usach.cl/portafolio/rimay)]([https://citiaps.usach.cl/portafolio/rimay](https://citiaps.usach.cl/portafolio/rimay)), accessed on 28 January 2022) manages and coordinates groups of volunteers using the Telegram bot. Each group of volunteers has a leader who receives tasks from one or more coordinators or administrators. Coordinators can use a web page to easily manage tasks and collect statistics. Figures 5 and 6 show some screenshots of the Rimay bot.  
Figure 5: Screenshots of Rimay’s Front-end application: (**a**) login web page, (**b**) information about users.  
Figure 6: Screenshots of Rimay’s Front-end application: (**a**) statistics report on events and (**b**) reports.  
The application supports the following tasks:  
1. Enrollment: Users request to register as volunteers. When the coordinator accepts the request, the data associated with the volunteer are stored in the system. In addition, the coordinator can assign the coordinator role to new users (Figure 5a,b).
2. Create event: The coordinator creates an event such as a forest fire. In addition, the coordinator can create tasks for each event, such as distributing face masks. Tasks have information such as where the face masks are stored and a job description. Volunteers can accept or decline assignments. Volunteers can also finish assignments when they are completed. The coordinator can also finish the event when it is complete. (Figure 6a).
3. Delete user: The coordinator can delete users from the system.
4. Send file: The coordinator can send a file to the volunteers.
5. Help/Status: Reports the status of volunteers.
6. Send report: Volunteers can send a report (attached file) to the coordinator. See Figure 6b.  
Figure 7 shows the steps executed during the execution of different tasks on the Rimay application. In particular, in this example, the coordinator sends the command \"newTask\" to the Telegram bot to create a new task. The bot asks for the name of the task. After the coordinator answers, the bot asks if he/she wants to upload a file. The coordinator uploads an image file. Then, the bot asks if he/she want to add a GPS location and the coordinator responds by sharing a geolocation. The bot displays a menu showing the existing volunteers. Then, the coordinator selects a volunteer who will receive the new task. Finally, the coordinator sends a request to the Back-end component to verify the information and to store it in a database. The boxes \(S_{i}\) with \(i=1,2,3,4,5\) represent the time it takes for the person to respond. The boxes \(Tbot_{i}\) with \(i=1,2,3,4,5\) represent the processing times of the bot. \(Tbe_{1}\) represents the processing time of the Back-end. Notice that during the execution time \(Tbe_{1}\), the bot thread is free until it gets the response. Figure 5 shows screenshots of the login web page and the information provided the Rimay application running on the Front-end.
## 3 Proof of P3P for the Stereo Camera System
Given the coordinates of the three points, we can calculate vectors as follows: the vector \(\overrightarrow{P_{1}P_{2}}=(X_{2}^{C}-X_{1}^{C},Y_{2}^{C}-Y_{1}^{C},Z_{2}^{C }-Z_{1}^{C})\), and the vector \(\overrightarrow{P_{1}P_{3}}=(X_{3}^{C}-X_{1}^{C},Y_{3}^{C}-Y_{1}^{C},Z_{3}^{C }-Z_{1}^{C})\). The unit vector \(\overset{\rightarrow}{n}\) which is perpendicular to the plane formed by these three points, can be expressed as: \[\overset{\rightarrow}{n}=\frac{\overrightarrow{P_{1}P_{2}}\times\overrightarrow {P_{1}P_{3}}}{\left|\overrightarrow{P_{1}P_{2}}\times\overrightarrow{P_{1}P_ {3}}\right|}\] (1)  
Here, \(\times\) denotes the cross product. Figure 4: P2P problem with a stereo camera system. All potential cartesian systems are located on the circle plotted in red. Figure 5: P3P Problem with a stereo camera system. The angles between \(\stackrel{{\rightarrow}}{{n}}\) and XYZ axes of the coordinate system can be expressed as follows:  
\[\cos(\theta_{x})=\stackrel{{\rightarrow}}{{n}}\cdot\stackrel{{ \rightarrow}}{{i}} \tag{2}\]  
\[\cos(\theta_{y})=\stackrel{{\rightarrow}}{{n}}\cdot\stackrel{{ \rightarrow}}{{j}} \tag{3}\]  
\[\cos(\theta_{z})=\stackrel{{\rightarrow}}{{n}}\cdot\stackrel{{ \rightarrow}}{{k}} \tag{4}\]  
where \(\theta_{x}\), \(\theta_{y}\) and \(\theta_{z}\) are the angles between \(\stackrel{{\rightarrow}}{{n}}\) and the unit vectors in the X, Y, and Z directions, denoted as \(\stackrel{{\rightarrow}}{{i}}\), \(\stackrel{{\rightarrow}}{{j}}\), and \(\stackrel{{\rightarrow}}{{k}}\), respectively. Therefore, with the direction \(\stackrel{{\rightarrow}}{{n}}\) fixed in space, the orientations of each axis of the coordinate system can be computed uniquely. According to the P1P problem, the origin of the coordinate system must lie on the surface of a sphere centered at \(P_{1}\) with radius \(=\sqrt{{X_{1}^{C}}^{2}+{Y_{1}^{C}}^{2}+{Z_{1}^{C}}^{2}}\) as depicted in Figure 2:0 Each coordinate system established with a different origin point on the surface of this sphere results in a unique configuration of the axis orientations. Therefore, as the orientations of the axes are defined in space, the position of the frame (or the position of the origin) is also uniquely defined. In conclusion, the P3P problem is sufficient to solve the PnP problem for a stereo camera system. **Proof concluded \(\square\)**  
This proposition indicates that to uniquely determine the full six DoFs of the stereo camera, at least three points (or nine 2D features) are required to match in the image-based visual servoing control.
# Diabetic Retinopathy and Ocular Melanoma: How Far We Are?
## 2 Angiogenesis and Anti-Angiogenic Therapy  
Neovascularisation or angiogenesis is mediated by vascular endothelial growth factors (VEGFs), and these mediators are also found in retinal alterations affecting its vasculature, such as those caused by diabetes mellitus, retinal vascular occlusion, and ocular malignancies [23, 24, 25]. Vascular endothelial growth factor/receptor (VEGF/VEGF) influences tumour neovascularization significantly, being self-secreted and by surrounding stroma [26, 27]. While certain treatments such as radiotherapy also increase the secretion of VEGF by the tumour [28, 29], it has been anticipated that anti-angiogenic treatment may enhance uveal melanoma's response to radiotherapy, regulating blood vessels and consequently tissue oxygenation [30, 31]. Hypoxia is a trigger for the initiation of angiogenesis and results from a cascade of cellular signalling leading to vasodilation via release of nitric oxide, increased vascular network permeability by VEGF and angiopoetin-2 (Ang-2), and also due to vascular basement membrane decomposition via extracellular matrix by matrix metalloproteinases (MMPs) [32, 33, 34, 35]. In a hypoxic environment, pericytes secrete VEGF and are involved as mediators of numerous processes related to tumour metastasis and angiogenesis. Pericytes are vascular mural cells located in the basement membrane of microvessels that also contribute to endothelial cell proliferation [36]. Although their impact in angiogenesis therapy is still unclear, it is well known that they are crucial in tumour progression. [PERSON] et al. have described the molecular aspects of tumour angiogenesis, predicted anti-angiogenic therapy, and also demonstrated that tumour blood suspension influences metastatic growth [37]. The appearance of VEGF was first detailed by [PERSON] et al. [38]. Indeed, this growth factor is crucial in angiogenesis as it controls vasopermeability and endothelial cell propagation and dispersion [39]. The serum VEGF levels are a useful biological marker of various tumours, their invasiveness and possible metastases [40]. In this review, we discuss diabetic retinopathy and  
Figure 1: Main features of diabetic retinopathy (**left**) and ocular melanoma (**right**).  
ocular melanoma, their relationship with angiogenesis and also current anti-angiogenic therapies for their treatment.