esa-sceva/satcom-chunk-collection huggingface dataset:
# The Effect of Non-Transferred Plasma Torch Electrodes on Plasma Jet: A Computational Study
## 2 Computational Modeling
### Geometry and Mesh  
In our previous work, computational results from the EDI model were validated against temperature measurements obtained via emission spectroscopy. These comparisons confirmed that the temperature profile at the plasma torch outlet is symmetric [9]. Based on this, a 2D axisymmetric geometry was used for the current simulations, as shown in Figure 2. The overall length of the plasma torch is 70 mm, the inlet radius is 2.5 mm, the outlet diameter for a cylindrical anode is 6 mm, and the stepped anode is 8 mm. Furthermore, the overall length of the cathode is 9.1 mm, the bottom diameter is 9 mm, and the top diameter is a maximum of 6 mm. However, for some cathode shapes, the diameter is smaller than 6 mm because of the curved surface. Although the overall dimensions of the torch remained constant in all case studies, the cathode and anode shapes were varied. Figure 3 presents the different cathode designs used in the analysis (with a cylindrical anode), while Figure 2 (bottom) illustrates the stepped anode paired with a flat cathode for the anode geometry study.  
The cathode tip is made of tungsten, while the remainder of the cathode and the entire anode are composed of copper. Nitrogen was selected as the working gas for all simulations. Its properties, such as transport and thermodynamic characteristics under equilibrium discharge conditions, were defined in COMSOL, as described in detail in the thermal plasma book and our earlier publication [9; 29].  
Figure 3: Different cathode shapes used in non-transferred plasma torch for the case studies. (**a**) Conical tip, (**b–d**) tapered tip, and (**e,f**) flat tips.  
Figure 2: Geometries with measurements of cylindrical anode (**top**) and stepped anode (**bottom**) with a flat cathode.  
A triangular mesh was used for all geometries. The number of mesh elements varied based on the specific cathode and anode configurations, as shown in Table 1. Boundary layers were not included, since the EDI model does not accurately capture near-wall physics. The associated near-wall property variations are discussed in our prior work [9].
## 3 Results and Discussion
Concerning the samples incorporating the phycobilproteins, it was found that, although the R-PE/PVA sample lost around 50% of its initial \(\eta\) value in the first 120 min (poor result compared to that found previously concerning R-PE dispersed in gelatin [18]), the \(\eta\) value remained constant after that, reinforcing the suitability of PVA as a host matrix. Although the previous results were somehow promising, the C-PC/PVA sample lost all its emission after the 960 min of AM1.5G exposure, suggesting aggregation or UV-induced molecular degradation. \begin{table}
\begin{tabular}{c c c c} \hline
**Sample** & \(\mathbf{\lambda_{\text{exc}}}\) **(nm)** & \(\mathbf{\eta}\) & \(\mathbf{\tau}\) **(ns)** \\ \hline R-PE/PVA & 498 & 0.11 \(\pm\) 0.01 & 3.74 \(\pm\) 0.03 \\ C-PC/PVA & 580 & 0.09 \(\pm\) 0.01 & 4.30 \(\pm\) 0.04 \\ FX/PVA & 610 & 0.10 \(\pm\) 0.01 & 6.68 \(\pm\) 0.02 \\ \hline \end{tabular}
\end{table} 
Table 1: Absolute emission quantum yield (\(\eta\)) for the indicated excitation wavelengths (\(\mathbf{\lambda_{\text{exc}}}\)) and emission lifetime values (\(\tau\)), calculated from the best fit of the decay curves shown in Figures S9–S11 in Supplementary Materials. We note that very few works report the incorporation of nature-based molecules in solid matrices for application in LSCs. Nevertheless, works reporting the incorporation of phycobiliproteins in acrylamide [13] and gelatin hosts [18] resulted in materials with lower \(\eta\) values (-50% drop) than those of the phycobiliproteins dispersed in a liquid medium. Additionally, photostability studies under AM1.5G continuous exposure showed similar behavior to that in Figure 4 for phycobiliproteins [18]. Other molecules such as GFP [17] and chlorophyll [16] were incorporated into solid organic-inorganic matrices. For the case of chlorophyll, the \(\eta\) values were analogous to that measured for the diluted chlorophyll solution, pointing out that the incorporation did not contribute to an emission quenching and that the optical properties of the extract were well preserved in the solid state [16]. This was not the case with the GFP-doped organic-inorganic hybrid, which revealed a -35% drop in the \(\eta\) values compared to that of the GFP aqueous solution [17]. The incorporation of chlorophyll in the solid matrices yielded photostable materials which showed a minor relative variation in the short-circuit current of coupled PV cell of -1% upon 40 h of AM1.5G exposure [16]. The GFP is known for being a photostable molecule [5,17] and thus, in both cases, resulting materials were found to be photostable.
# Mapping Smallholder Yield Heterogeneity at Multiple Scales in Eastern Africa
## Materials and Methods
### Satellite Based Yield Estimation  
We tested two approaches to estimate yield using satellite images. The first approach, referred to as the \"calibrated\" approach, related VIs to yield measurements with a simple linear regression model:  
\[\textit{Yield}_{i}=\beta_{0}+\sum_{t=1}^{N}\beta_{t}\times VI_{it}+\beta_{N+1 }\times\ W+\epsilon_{i} \tag{1}\]  
Figure 2: Land cover classification of the study area. Map was generated using Sentinel-2 imagery with a spatial resolution of 10 m.  
where \(i\) indicates a specific field or administration unit, \(t\) is the satellite observing date, \(N\) is the number of image dates, \(W\) is the weather variable, and \(\varepsilon\) is the residual error. Here, we used the mean temperature (\(T_{avg}\)) from May through July; precipitation and vapor pressure deficit were not significant at both the B-K sub-region and the 1 AF region based on our preliminary analysis, thus, were excluded from the model. The second approach, referred to as the \"uncalibrated\" approach, used a well-validated crop model to generate pseudo-observations of yields and VIs to derive the regression coefficients of \(\beta\) in Equations (1) [6,7]. In this way, ground-measured yield was no longer required for calibration. Weather data for the \"calibrated\" approach and crop simulations were from aWhere database, while MODIS temperature data were used for the 1 AF regional yield estimation.
# Study of RF Stray Currents in ITER Neutral Beam Test Facilities
## 2 Spider Electrical System
### Transmission Line  
The 23.5 m long (in-axis) multiconductor transmission line transmits the power from ISEPS and AGPS to the beam source. The transmission line is air-insulated, and it is interfaced to the beam source by means of a high-voltage ceramic bushing. The transmission line components considered for this study are:  
* RF coaxial transmission lines: four rigid 3\(\frac{1}{8}\) inches coaxial lines deliver power from ISRF to the RF drivers in the beam source. The outer conductor of the rf coaxial line is referred to the plasma source potential. Only one RF coaxial line is represented in Figure 1.
* Plasma Grid busbars: two actively cooled busbars are used to transmit power from ISPG to the PG. Depending on their potential reference, they are identified as PGFE (connected to the negative terminal of ISEG in HVD) and PGFB (connected to the positive terminal of ISBI in HVD).
* Bias busbar: a busbar is used to connect the beam source to the negative terminal of ISBI in HVD.
* Extraction Grid cable: an insulated and screened cable is used to connect the EG to ISEG. The central conductor of the cable, which is connected to the EG, is referred to HVD.
* High-Voltage Screen (HVS): all the previous conductors (RF coaxial lines, PG busbars, BI busbar and EG cable) are surrounded by a cylindrical screen, referred to the PG potential.
* Distributed Core Snubber (DCS): ten ferromagnetic cores, which envelope the HVS, are installed along the transmission line. They are used to dampen the transients, which develop as a consequence of breakdown between grids.
* Outer Conductor: the square-section outer conductor of the transmission line consists of two sandwich copper panels isolated from one another, the inner and outer screens. Their purpose is the minimization of Electromagnetic Interference (EMI) generated in the surrounding environment during breakdown between grids. In Figure 1, for simplicity, only the outer screen, referred to the beam source, and its connections are represented.
# An Empirical Study on Ensemble of Segmentation Approaches
## 3 Results
### Datasets and Testing Protocols
#### 3.1.1 Polyp Segmentation (POLYP)  
Polyp segmentation from colonoscopy is a challenging task requiring a two-class classification between the low contrast colon background and polyp foreground pixels.  
We present experimental results according to a very popular benchmark [6] available on GitHub ([[https://github.com/james128333/HarDNet-MSEG](https://github.com/james128333/HarDNet-MSEG)]([https://github.com/james128333/HarDNet-MSEG](https://github.com/james128333/HarDNet-MSEG)), (accessed on 20 April 2022)), and including five datasets for polyp segmentation (i.e., Kvasir [37], ColonDB [38], CVC-T [39] and ETIS [40], ClinicalDB [41]): the training set is made by 1450 images (from the most large dataset, i.e., 900 images from Kvasir and 550 images from ClinicalDB); the other are for the test sets (100 images from Kvasir, 380 from ColonDB, 60 from CVC-T,196 from ETIS, and 62 from ClinicalDB), as is usually done in the literature. In these datasets, we use resized training images of size \(352\times 352\).
## 5 Conclusions  
This paper has presented a novel A2A channel model, which incorporates the propagation mechanisms of direct transmission, specular reflection, and diffuse scattering. Based on the Gaussian scatter density, a closed-form PDF that jointly describes the zenith and azimuth angles of diffuse rays has been proposed. The power of diffuse rays has been obtained considering the path loss, reflection coefficient, and scattering radiation pattern of the channel. Additionally, UAV vibrations have been considered and modeled using stochastic sinusoidal processes. The utility of the model has been validated by comparing the statistics with measurement results. Statistics including the spatial-temporal CCF, Doppler PSD, and coherence time have been obtained. The findings suggest that the scattering effect exhibits a pronounced dependence on the UAV altitudes. A large vibration amplitude or frequency significantly amplifies the Doppler spread and diminishes the temporal correlation and coherence time of the channel. For a given strength of UAV vibration, the adverse effects of UAV vibrations increase with the carrier frequency, posing a great challenge for UAV communications in high-frequency bands.  
Conceptualization, W.Q. and J.B.; methodology, W.Q. and J.B.; software, Z.W.; formal analysis, Z.W.; investigation, W.Q. and J.B.; resources, Z.W.; writing--original draft preparation, Z.W.; writing--review and editing, W.Q., J.B. and W.L.; visualization, Z.W.; supervision, W.Q. and J.B.; project administration, W.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China (NSFC), grant number 62101311.  
Data Availability Statement: Data are contained within the article.  
Conflicts of Interest: Authors [PERSON] and [PERSON] were employed by the State Grid Shandong Electric Power Company Zibo Power Supply Company. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.  
Figure 13: The coherence times of the proposed A2A channel model with different degrees of UAV vibrations and carrier frequencies.
###### Abstract  
The benefits of using hybrid drying are increasingly remarked. Microwave-convective drying (MW-CD) links the advantages of both microwave and convective drying methods and allows the negative phenomena that appear when the methods are used separately to diminish. Most importantly, reduced specific energy consumption and relatively short drying time are observed, which can be additionally decreased by the application of various preliminary treatments, e.g., pulsed electric field (PEF). Thus, the purpose of this study was to determine the impact of PEF pretreatment on the MW-CD of apples and its chosen physicochemical properties. This research was designed using response surface methodology (RSM). The first variable was microwave power (100, 200, and 300 W), and the second was specific energy input (1, 3.5, and 6 kJ/kg). Optimization responses were assumed: drying time to MR = 0.02, water activity, hygroscopicity after 72 h, rehydration ratio, relative dry matter content, total phenolic content, ability to scaveng ABTS* radical cations, and DPPH* radicals based on the \(EC_{50}\) values. The most optimal parameters were comprised of specific energy intake of 3.437 kJ/kg and microwave power of 300 W (desirability equalled 0.624), which provided the most minimized drying time and obtaining of apples with the most desired properties.  
PEF; microwave-convective drying; hybrid drying; hygroscopicity; rehydration; colour; polyphenols; antioxidant activity; RSM +
Footnote †: journal: Applied Sciences
# Optimization Techniques for Design Problems in Selected Areas in WSNs: A Tutorial
## 12 Joint Routing and Scheduling in WSNs with Multiple Sinks having Different Location Possibilities
### Reformulation: Pattern Based Formulation  
As was mentioned for the time-based formulation in [7], the life-time variable \(T\) is connected to the rest of the variables through the energy constraint by integrating over time. This constraint complicates the problem and makes it difficult to solve according to [7]. Therefore a reformulation was performed to obtain an easier problem which discretized the time parameter into different durations to give an easier problem which has no integration in any of the constraints. For each duration, a placement pattern can be assigned such that the amount of energy expended over all time durations is within the initial available energy level of each node. The life time of the network is hence equivalent to the aggregate discretized time durations. In each time duration, an assigned pattern should satisfy all the constraint sets that were explained for the time-based formulation. The energy constraint in a given time duration \(t_{p}\) for placement pattern \(p\) becomes a linear constraint in the flow variables \(g_{i,j}^{p}\) and \(g_{i,o}^{p}\). The elements of the reformulated problem are [7]:  
* Decision variables: 1. the continuous variables \(t_{p}\) which represent the assigned time durations for the possible patterns \(p\), 2. continuous variables \(e_{i}^{p}\) for the energy consumption rate for node \(i\) in pattern \(p\) for all nodes and patterns, 3. binary decision variables \(x_{s,o}^{p}\), tell whether sink node \(s\) is assigned to location \(o\) in the pattern placement \(p\) for all nodes, sinks and patterns, 4. continuous variables \(g_{i,o}^{p}\) for the data rate flow from node \(i\) to the sink position \(o\) in pattern \(p\) for all nodes, sinks and patterns, 5. continuous variables \(g_{i,j}^{p}\) for the data flow rate on the link between the nodes \(i\) and \(j\) in pattern \(p\) for all nodes and patterns.
* Objective function: Maximizes the aggregate durations assigned to the patterns which in [7], was stated to be equivalent to the lifetime of the network, i.e., \(max\;\;T=\sum_{p\in P}t_{p}\).
* Constraint sets: The same constraint sets for the time-based formulation should be satisfied for each pattern, the energy constraints however are replaced by two constraint sets for each pattern, one is linear and the other is bilinear quadratic. The linear one is an equality constraint that links the energy expended by the node in a given placement pattern with the flow variables \(g_{i,j}^{p}\) and \(g_{i,o}^{p}\). The bilinear constraint set guarantees that all the energies expended by every node in all pattern durations do not exceed their initial battery energies.
###### Abstract  
Microalgae are promising candidate resources from marine ecology for health-improving effects. Metabolite profiling of the microalgal diatom, _Chaetoceros calcitrans_ was conducted by using robust metabolomics tools, namely 1H nuclear magnetic resonance (NMR) spectroscopy coupled with multivariate data analysis (MVDA). The unsupervised data analysis, using principal component analysis (PCA), resolved the five types of extracts made by solvents ranging from polar to non-polar into five different clusters. Collectively, with various extraction solvents, 11 amino acids, cholesterol, 6 fatty acids, 2 sugars, 1 osmolyte, 6 carotenoids and 2 chlorophyll pigments were identified. The fatty acids and both carotenoid pigments as well as chlorophyll, were observed in the extracts made from medium polar (acetone, chloroform) and non-polar (hexane) solvents. It is suggested that the compounds were the characteristic markers that influenced the separation between the clusters. Based on partial least square (PLS) analysis, fucoxanthin, astaxanthin, violaxanthin, zeaxanthin, canthaxanthin, and lutein displayed strong correlation to 2,2-diphenyl-l-picrylhydrazyl (DPPH) free radical scavenging and nitric oxide (NO) inhibitory activity. This metabolomics study showed that solvent extractions are one of the main bottlenecks for the maximum recovery of bioactive microalgal compounds and could be a better source of natural antioxidants due to a high value of metabolites.  
_Chaetoceros calcitrans_; metabolite profiling; 1H nuclear magnetic resonance (NMR) spectroscopy; antioxidant; nitric oxide inhibitory
###### Abstract  
The light use efficiency (LUE) model has been widely used in regional and global terrestrial gross primary productivity (GPP) estimation due to its simple structure, few input parameters, and particular theoretical basis. As a key input parameter of the LUE model, the maximum LUE (\(\mathcal{E}_{\max}\)) is crucial for the accurate estimation of GPP and to the interpretability of the LUE model. Currently, most studies have assumed \(\mathcal{E}_{\max}\) as a universal constant or constants depending on vegetation type, which means that the spatiotemporal dynamics of \(\mathcal{E}_{\max}\) were ignored, leading to obvious uncertainties in LUE-based GPP estimation. Using quality-screened daily data from the FLUXNET 2015 dataset, this paper proposed a photosynthetically active radiation (PAR)-regulated dynamic \(\mathcal{E}_{\max}\) (_PAR_-\(\mathcal{E}_{\max}\), corresponding model named PAR-LUE) by considering the nonlinear response of vegetation photosynthesis to solar radiation. The PAR-LUE was compared with static \(\mathcal{E}_{\max}\)-based (MODs) and EC-LUE) and spatial dynamics \(\mathcal{E}_{\max}\)-based (D-VPM) models at 171 flux sites. Validation results showed that (1) R\({}^{2}\) and RMSE between PAR-LUE GP and observed GPP were 0.65 (0.44) and 2.55 (1.82) g C m\({}^{-2}\) M\({}^{-1}\) d\({}^{-1}\) at the 8-day (annual scale, respectively; (2) GPP estimation accuracy of PAR-LUE was higher than that of other LUE-based models (MODIS, EC-LUE, and D-VPM), specifically, R\({}^{2}\) increased by 29.41%, 2.33%, and 12.82%, and RMSE decreased by 0.36, 0.14, and 0.34 g C m\({}^{-2}\) M\({}^{-1}\) d\({}^{-1}\) at the annual scale; and (3) specifically, compared to the static \(\mathcal{E}_{\max}\)-based model (MODIS and EC-LUE), PAR-LUE effectively relieved the underestimation of high GPP. Overall, the newly developed _PAR_-\(\mathcal{E}_{\max}\) provided an estimation method utilizing a spatiotemporal dynamic \(\mathcal{E}_{\max}\), which effectively reduced the uncertainty of GPP estimation and provided a new option for the optimization of \(\mathcal{E}_{\max}\) in the LUE model.  
Keywords:gross primary production (GPP); light use efficiency (LUE); photosynthetically active radiation (PAR); dynamic maximum LUE +
Footnote †: journal: Remote Sens.
# Low Power Multi-Hop Networking Analysis in Intelligent Environments
## 5 Discussion of the Results
### Multi-Hop Communications with Bluetooth Park Low Power Mode
After that, the models were validated with the measurements through a graphical comparison as well as the R\({}^{2}\) statistical factor and the mean squared error (MSE). R\({}^{2}\) is used in the context of a statistical model which pretends to predict future results or to test a hypothesis. It determines the quality of the model to replicate the results and the part of the variation of the results that can be explained with the model [49]. On the other hand, the MSE  
Figure 5: Latency (vertical, seconds) vs. inactivity interval (horizontal, milliseconds). Links always in _park_ mode. From two to six hops: (**a**) _master-to-slave_ communication; (**b**) _slave-to-master_ communication. is a measure of the quality of an estimator that measures the average of the squares of the errors or deviations, i.e., the difference between the estimator and what is estimated [50]. Taking into account the dependences shown in Figures 4 and 5, the end-to-end latency when gateways nodes are in the park mode can be defined as in Equation (1), which considers the time contributions described in [48] and includes the delay time of the first hop (\(t_{1 park}\)), the amount of hops (\(N\)), the latency contribution per hop (\(\delta_{1}\)), the latency addition in each hop (\(2\ \delta_{2}\)), the inactivity period of the mode (\(T_{park}\)), and the ratio of inactivity period affecting the latency (\(\beta\)):  
\[\delta_{park}=t_{1 park}+\sum_{i=2}^{N}\Big{(}\delta_{1}+\beta\cdot T_{park}+2 \cdot\delta_{2}\cdot(i-1)\Big{)} \tag{1}\]  
Then, the values for the coefficients in Equation (1) were calculated through linear regression to define the curves that best fit to the results of the measurements for the park mode. The values are summarized in Table 1 for both the multi-hop communication from master to slave and from slave to master when links are in the park mode. Table 1 also includes the results of the validation with R\({}^{2}\) statistical datum and the results for the MSE. As a summary, the upper limit of the latency in asynchronous links of Bluetooth multi-hop networks can be defined with just one equation for each one of the directions, i.e., master-to-slave and slave-to-master communication in park low power mode. Furthermore, the models were validated with the R\({}^{2}\) statistical parameter and the MSE.