esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Production of Plant Secondary Metabolites Using Natural Hosts
### Enhancing the Yield of Plant In Vitro Culture Systems by Process Optimization  
Due to the close connection between primary and secondary metabolism in plants, any factor that affects primary metabolism may also influence secondary metabolism. Therefore, adjusting the growth environment can further enhance the yield of secondary metabolites. This can include optimizing the types and concentrations of nutrients and plant hormones in the culture medium, as well as optimizing aeration rate, pH, and inoculum size [4]. Additionally, the addition of precursors, elicitors, and immobilization techniques may also further increase production [106]. In particular, methods that mimic biotic stress have been widely applied [107; 108]. For example, jasmonic acid and its methyl derivative, methyl jasmonate (MeJA), which are important plant stress signaling molecules, can induce the biosynthesis of defensive compounds [109]. Secondary metabolites secreted into the culture medium may be degraded by metabolic enzymes in the medium, and the accumulated secondary metabolites themselves could be harmful to plant cells and/or to the feedback inhibition of biosynthesis. Therefore, various methods, such as in situ adsorption and two-phase culture, should be employed to remove the products from the culture medium promptly [106; 110; 111].  
The successful commercial production of plant-based secondary metabolites depends on the scaling up of the process from shake flasks to bioreactors. Stirred-tank reactors and airlift reactors are widely used in cell suspension cultures [112]. The former are known for their simple scalability, strong oxygen supply, and uniform mixing, but they have the disadvantage of high shear forces [113]. The latter are easy to scale up, have low operating costs and contamination rates, and generate low shear forces. However, they suffer from poor oxygen mass transfer, non-uniform mixing, and a propensity for foaming [114]. The cultivation of root tissues primarily involves the use of mist bioreactors [115] and balloon-type bubble bioreactors [116]. The research group led by [PERSON] in South Korea successfully used a balloon-type bubble bioreactor to scale up the cultivation of _Panax ginseng_ hairy roots to volumes ranging from 10,000 to 20,000 L [117]. Temporary immersion bioreactors and root zone immersion bioreactors are suitable for explant culture. Rotating drum bioreactors can be used for the culture of suspension cells, root tissues, and explants, but they face challenges when scaling up, and their heat transfer performance is low. Other reactor types, such as disposable reactors, membrane bioreactors, and wave bioreactors, are challenging to scale up due to their specific characteristics and are primarily suitable for small-scale cultivation [112; 118]. More information on the structure and design of plant bioreactors can be found in the article by [PERSON] et al. [119].
## 5 Deposition Methods
### Pulsed Laser Deposition (PLD)  
Pulsed laser deposition (PLD) is another useful deposition technique for creating GST. Like in sputtering, it enables stoichiometric transfer of target material, and the possibility of achieving congruent deposition [53; 85; 111]. As can be seen in Figure 19a, the GST target is irradiated by a focused laser beam through a UV-transparent window. A plasma plume forms from the irradiation spot. Both the GST target and the substrates need to be rotated during the ablation in order to avoid damaging to the target, and ensure a thickness homogeneity of the deposited films. A variety of growth conditions can be modified in a PLD system to modify the fabricated film properties, such as the temperature of heat-treatment, working pressure and laser energy. Among them, [PERSON] et al. studied the effect from the temperature of heat-treatment on the composition of GST nano-particles [111], as shown in Figure 19b. It is interesting to know the arriving species during the deposition. Therefore, researchers have been explored the dissociation of GST in the plasma by using mass spectroscopy [112; 113]. Their finding shows the formations of single elements, binary Ge-Te, and Sb-Te compounds, and ternary non-Ge\({}_{2}\)Sb\({}_{2}\)Te\({}_{5}\) compounds, and there may also exist other larger clusters which may lie outside the detection range of the mass spectrometer.  
Figure 19: **(a)** Schematic of the laser ablation technique for GST thin film deposition. **(b)** Atomic ratio as a function of heat treatment temperature of GST nanoparticles. Adapted with permission from Reference [111]. ©2005 Elsevier.  
Figure 18: **(a)** Schematic of the sputtering technique for creating GST-225 films. **(b)** Electrical resistivity as a function of temperature for samples prepared at different argon pressures. The samples prepared at higher pressures show a decrease of their crystallization temperature. Adapted with permission from Reference [109]. ©2005 Elsevier.
## 4 Numerical Examples  
Different design restrictions may be applied depending on the application type for which the arch is used. To approach a general perspective of the problem, two general cases have been analyzed: In the first one, the height of the arch \(H\) is fixed, while the parameters \(H^{\prime},B,h\), and \(t_{a}\) change within a range. For the second scenario, the span of the arch \(B\) is constant, and the parameters \(H,H^{\prime},h\), and \(t_{a}\) are set for respective ranges of values. The search for the best arch shape is based on the optimization of the functional given by Equation (10). Thus, the maximum absolute bending moment is reduced whilst the airspace of the arch is increased. Note that in this work, the reduction of the bending moment has been set as the most important objective as it implies some benefits, such as in terms of the construction cost (the amount of material used for its construction is reduced). Moreover, the thickness of the arch may be reduced, thus increasing its slenderness, which is an important aspect in many cases, as in leisure applications. If the importance of the airspace (or another parameter which can be included in the functional expression) is comparable with the bending moment, a normalization of the expressions should be addressed to guarantee that the airspace weight is clearly represented in the functional value.  
There are two main restrictions in the problem. The first one is inherent to the numerical calculation. As nonlinear analysis is developed, some of the solutions may not converge, thus discarding the proposed solution. The second one is based on Equation (11). If that condition is not achieved either for linear and nonlinear analysis, the arch shape is not considered.  
The results illustrate how the combined use of the curve parameterization and the CRO-SL leads to optimal solutions. In addition, the importance of considering the nonlinear effects in the arch design is also evaluated. The CRO-SL parameters are based on trial and error tests. They are shown in Table 1.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameter** & **Description** & **Value** \\ \hline Reef & Reef size & 100 \\ \(\rho_{0}\) & Fraction of reef capacity initially occupied & 80\% \\ \(F_{b}\) & Frequency of broadcast spawning & 97\% \\ \(F_{a}\) & Percentage of asexual reproduction & 5\% \\ \(F_{dep}\) & Fraction of corals for depredation & 5\% \\ \(P_{d}\) & Probability of depredation & 10\% \\ \(\alpha\) & Maximum number of iterations & 50 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Parameters values used the CRO-SL.  
The Young's modulus of the arch material is \(E=27\),664.49 MPa and the Poisson's ratio has been chosen to be \(\
u=0.2\) (uncracked concrete) [60], with a density \(\rho_{h}=2400\) kg/m\({}^{3}\). The self-weight of the arch structure is considered in the analysis.
## 3 Results and Discussion
### Spectrally-Resolved Intensity Autocorrelation Measurements  
The cross-correlation results show that the picosecond-order exponential decay of the optical pulses can be attributed to the group delay due to the dispersion compensation optics, and to pulse broadening. However, the broadening of the cross-correlation trace cannot be explained only by the effects of the dispersion-compensation optics. Thus, we measured intensity autocorrelations for different spectral components with a spectral bandwidth narrower than that in our previous report [11]. Figure 6 shows optical spectra measured after the BPF, where the different transmission wavelength was changed by varying the incidence angle. The figure also shows the corresponding autocorrelation traces. As the cross-correlation traces in Figure 4c become broader with the increase in the wavelength, the pulse duration in Figure 6b increases with increasing transmission wavelength. The typical peak power of the optical pulses after the BPF was about 1.2 W at 398.8 nm, 3.0 W at 400.3 nm and 3.0 W at 401.0 nm. The resulting time-bandwidth product is plotted in Figure 7 as a function of wavelength. At wavelengths of about 399-400 nm, the time-bandwidth product is about 0.4, close to the Fourier-transform limited value, but it increases rapidly at wavelengths longer than 400 nm. The femtosecond optical pulses shown in Figure 2a obtained by spectral filtering correspond to the spectral region with the minimum time-bandwidth products.  
Figure 6: **(a)** Spectral components after the BPF with different transmission wavelengths and average power after the BPF; **(b)** Intensity autocorrelation traces corresponding to the spectral components after the BPF with pulse durations assuming sech\({}^{2}\) pulse shape.
# The Current Development Status of Agricultural Machinery
## 5 Summary and Future Perspectives
### Cooperative Control Algorithm Optimization
#### 5.2.2 Deep Integration of Powertrains and Energy-Efficiency Optimization  
Agricultural operations in hilly and mountainous regions encounter high energy consumption and significant fluctuations in power demand, rendering conventional single-power-source systems inadequate for meeting energy-efficiency requirements. Current technologies predominantly rely on hybrid powertrains (petrol-electric), which dynamically allocate power between engines and motors through algorithms that recognize operating conditions. However, existing systems still suffer from suboptimal energy management strategies and inefficient power coupling.  
Future solutions may involve the development of a multi-level energy system that integrates fuel cells, lithium batteries, and supercapacitors, combined with dynamic energy management strategies to provide instantaneous power compensation under high-torque steep slope conditions. This approach aims to enhance operational endurance. Furthermore,the adoption of advanced materials such as carbon fiber composites can reduce overall machine weight while maintaining structural integrity, thereby improving energy utilization efficiency and increasing the dynamic response speed of control systems--ultimately bolstering stability during slope operations.  
With advancements in domestically developed high-precision actuators and ongoing optimization of intelligent algorithms, deeply integrated powertrain technologies are poised to offer robust technical support for agricultural mechanization in hilly regions. This progress will drive the industry toward greater efficiency, intelligence, and sustainability.
# Sunspot Detection Using YOLOv5 in Spectroheliograph H-Alpha Images
## 3 Related Work
### Deep Learning for Automatic Recognition of Magnetic Type in Sunspot Groups  
[PERSON] et al. [25] developed a deep learning algorithm to detect magnetic type in sunspot groups. Although the article focuses on the recognition of magnetic fields, a recognition of the sunspots themselves was needed. The authors constructed three models, which differ in the input content, that consist of the following:  
* **Model A:** magnetograms, images built from the detection of the intensity and polarity of the magnetic fields over the solar surface, where the sunspots are also detected but with the extra information on the polarity of the magnetic field;
* **Model B:** SDO/HMI continuum images;
* **Model C:** two-channel pictures.  
The datasets used in the study consist of images collected by SDO/HMI (Solar Dynamics Observatory/Helioseismic and Magnetic Imager) and SHARP (Spaceweather HMI Active Region Patch) data, taken between May 2010 and May 2017. The data include magnetograms and continuum images with the time period of 12 min and location range of \(\pm 75\) heliolongitude degrees from the solar disk center, in order to reduce the influence of projection [25]. In the active region, in order to ensure sufficient variations between the nearest images, the data are obtained every 96 min.  
This way, the gray value of the pixel point with magnetic field strength greater than or equal to the maximum (800.0) obtains the value of 255; on the other hand, the gray value of the pixel point with a magnetic field lower than or equal to \(-800.0\) is given the value of zero [25]. The resulting pictures are interpolated into a uniform size of 160 \(\times\) 80 pixels, to match the input size required by the CNN. After data processing, the CNN is trained using the dataset.  
The CNN has good performance in the identification of the active region magnetic types. The overall accuracy of all three models is over 87%, and the total accuracy reaches over 95%. The accuracy for the Alpha type reaches 98% and the recognition accuracy for the Beta type always has values above 88%.
# The Opto-Electronic Functional Devices Based on Three-Dimensional Lead Halide Perovskites
## 3 The LHP Based Functional Devices
### Photodetectors  
Photodetectors are devices that convert optical signals to electrical signals, which are one of the key components used in areas including communication, sensing, imaging, and computation. People have proposed photodetectors by combining LHP with 2D and 1D materials to realize high performance and broad working range. As presented in Figure 6, bending of the electronic band at the interface is the key to realize high performance photodetection. By combining LHP with the other species of material, enhancement in the effective absorption coefficient and/or absorption bandwidth could be achieved. The device performances for some of the recent LHP photodetectors are presented in Figure 7, and the parameters are summarized in Table 2.  
Figure 6: (**a**) The bending of energy band at the interface of the LHP based photodetector. Reprinted with the permission from [9]. Copyright 2018 American Chemistry Society. (**b**) Schematic illustration of a hybrid photodetector by combining perovskite with the 2D PdSe\({}_{2}\). Reproduced with permission from [91]; published by Wiley, 2019. (**c**) The fabrication process for a LHP/TiO\({}_{2}\) nanotubes (NTs) photodetector. Reproduced with permission from [81]; published by Wiley, 2017.  
Figure 7: Device performance of LHP photodetectors. (**a**) Responsivity (R) and detectivity (D*) of the WS\({}_{2}\)/perovskite photodetector and (**b**) the corresponding time-dependent photocurrent response showing a stable operation. Reproduced with permission from [92]; published by Wiley, 2016. (**c**) Comparison on the absorption of the Si NWs array/Cs\(-\)doped FAPbI\({}_{3}\) heterostructure and pure Si NWs array; (**d**) The fast response of the device. Reprinted with the permission from [9]. Copyright 2018 American Chemistry Society. (**e**) Comparison on R of the MAPbI\({}_{3}\) and MAPbI\({}_{3}\)/PDPP3T composite photodetectors in the ultraviolet\(-\)visible\(-\)near infrared (UV\(-\)vis\(-\)NIR) region indicating an improved performance of the hybrid structure. (**f**) R versus bending curvature radium of the MAPbI\({}_{3}\)/PDPP3T composite photodetector demonstrating a good flexibility of the device. Reproduced with permission from [93]; published by Wiley, 2016.
## 3 Results
### Throughput for Fixed Modulation--Without Interference  
In this case, the available bandwidth of 51.28 MHz for the WFI camera is limited to 51.28 Mbps. Note that the throughput (\(T_{hr}\)) depends on the duration of the satellite pass in visibility with the ERG. By considering an average time of approximately 12 min [34], we have:  
\(T_{hr}=36.922\) Gbits (which represents the minimum throughput for WFI transmission).
# An Efficient Local Search Heuristic for Earth Observation Satellite Integrated Scheduling
## 4 An Efficient Local Search Heuristic for Earth Observation Satellite Integrated Scheduling
### An Efficient Heuristic for EOS Integrated Scheduling
#### 4.3.3 The Improvement Procedure  
The aim of the improvement procedure is to attain a local optimum solution (as good as possible) in a given neighborhood. In this paper, we propose to use an _Insertion_ neighborhood, which is induced by a _Insertion_ operator. It can also be regarded as a hill-climbing process [26; 27; 28].  
* Insertion: insert a window (VTW or DW) into a schedule. Constraint violation is allowed and the amount of violation is evaluated when this occurs.  
The pseudo-code of the improvement procedure is shown in Algorithm 2. The algorithm repeatedly considers all possible insertions and chooses the best one. Such a greedy strategy can help the solution achieve better quality at the current stage. The algorithm continues until no improvements can be found (improvement is evaluated according to Equation (17)).  
```
0: P: An AEOS scheduling problem; \(\sigma\): a solution for improvement; \(c\): a violation multiplier;
0: The local optimum solution \(\sigma^{*}\)
1:while True do
2: Collect all windows that are not included in \(\sigma\) and denote the set as \(S\);
3: bestScore \(\leftarrow\) 0;
4:for each window \(v\) in \(S\)do
5: Insert \(v\) into \(\sigma\) and the new solution is \(\sigma^{\prime}\);
6:if\(\mathit{Eva}(\sigma^{\prime},c)-\mathit{Eva}(\sigma,c)\) > bestScore then
7: bestScore \(\leftarrow\mathit{Eva}(\sigma^{\prime},c)-\mathit{Eva}(\sigma,c)\);
```  
**Algorithm 2****The Improvement Procedure*** **end if**
* **end for**
* **if** bestScore > 0 then**
* **Insert the window with the best score;**
* **else**
* **Break;**
* **end if**
* **end while**
* **return**\(\sigma^{*}\);
# An Efficient System for Automatic Blood Type Determination Based on Image Matching Techniques
###### Abstract
In addition to the limitations discussed for each group of the studies above, all of them used a small number of blood samples and did not provide an objective evaluation of accuracy. As discussed earlier, traditional blood typing is performed manually as follows: (1) taking a blood sample from the patient, (2) mixing it with different antibodies on a slide, (3) observing the agglutination, and (4) determining the blood type. In this paper, we proposed a system to automate the last two steps, (3) and (4). The system can handle a large number of input images captured by a mobile phone camera minimizing human error. Such a system has the ability to handle difficult cases that are ambiguous even for manual inspection by people who might fail to detect agglutination and/or blood type while using state-of-the-art approaches. Our contribution can be summarized as follows:  
* The ORB matching algorithm was adopted to provide an accurate, fast, and automated blood typing system. * The system is able to detect various agglutination patterns regardless of variations in photos brightness. * The system was evaluated using 1500 images of blood spots that cover all possible agglutination patterns. * The evaluation includes detailed analysis for the accuracy and processing time of different approaches. We begin this paper by providing an overview of the blood typing process, problem statement, and challenges, which are explained thoroughly in Section 2. The principle of operation of the used image matching techniques is reviewed thoroughly in Section 3. The experimental setup, including blood image capturing and analysis, is provided in Section 4. Results and their analysis are provided in Section 5. Finally, conclusions are drawn in Section 6.
## 3 Methodology
### Dataset Description
#### 3.2.2 Data for Hurricane Damage Prediction  
The data used in this study are extracted from the satellite images of the Greater Houston Area after Hurricane Harvey [45]. All the satellite images are labeled as \"damaged\" or \"undamaged\" in the building damage assessment dataset. The label \"damage\" indicates the images of the affected building due to the hurricane, and the label \"no damage\" indicates the images of the non-affected buildings. The dataset has the attributes such as the path of the image, damage status, location, and latitude and longitude. For damage prediction, a total of 5000 images are used as training data for the no damage category and 5000 images are used for the damage category. For validation and testing, 1000 files for each category were chosen for prediction. Image preprocessing is done using the packages in Keras. Good quality images are retained, and the images that are fully black or with very poor quality are automatically discarded. Simple data transformations are done using APIs to convert the string data type to float.
## 4 Discussion  
The inhalation of aerosols and droplets emitted by infected individuals is the predominant route of respiratory virus transmission for viruses such as SARS-CoV-2. The spread of these droplets is affected by their size and the surrounding environmental conditions.  
In this study, fluid-dynamics simulations were employed to examine the dispersion of particles emitted by an infectious individual. Additionally, mathematical models were utilized to assess the infection potential for susceptible individuals. A real scenario has been modeled, and the risk of infection has been proved to be significant.  
Two CFD modeling approaches were used: the Lagrangian and Eulerian approaches. The Lagrangian method, which tracks the motion of individual particles within the study environment, provides the detailed descriptions necessary to evaluate the deactivation effect of the E4 Shield when the particles have travelled for a short time from mouth to mouth, which characterizes the direct route of the contagion. The Eulerian method is an alternative computational approach, the results of which showed a good agreement with the Lagrangian approach at a much lower computational costs, which allows for longer transient simulations. Nonetheless, the approach lacks detailed descriptions of short distance phenomena.  
To estimate the risk of infection with the introduction of an E4 Shield sanitizing device into the environment, a series of preliminary electromagnetic simulations has been conducted. The E4 Shield device utilizes microwave irradiation to inactivate the respiratory virus responsible for airborne COVID-19 transmission. The microwaves emitted by this device are compatible with the presence of humans, therefore this device can be used in these kinds of scenarios.  
Our investigations involved evaluating the electromagnetic field emitted by the device, which was then integrated with fluid-dynamic studies, the ARIA contamination risk model, and experimentally obtained inactivation rates. Two different positions of the E4 Shield device were studied, both of which ensured a substantial reduction in the estimated risk of infection thanks to the virucidal effect achieved by the electromagnetic waves. The reduction in risk between these two positions is not significant. This is because, in both scenarios, the device is positioned between the two individuals who are facing each other. Nevertheless, the risk of infection is drastically lowered by the inclusion of the device.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Environment** & **ARIA Model** & **ARIA Model** & **ARIA Model** \\
**Configuration** & **Risk** & **Risk—E4 Shield** & **Risk—E4 Shield on** \\  & & **on Table** & **Wall** \\ \hline Lab Office: mixed radiant & & & \\ ceiling and primary air & 32\% & 6–7\% & 7–8\% \\ system, summer case & & & \\ \hline \hline \end{tabular}
\end{table}
Table 6: Summary of E4 Shield system de-activation results on the considered scenarios.