esa-sceva/satcom-chunk-collection huggingface dataset:
# Research on Performance Metrics and Environmental Conditions for 5G MIMO OTA
## 4 Conclusions  
This paper analyzes the performance of TRMS and MARSS based on the MIMO OTA measurement among 10 commercial smartphones on the Chinese market. Two new FoMs, i.e., Peak-Null and Variance, have been compared to analyze the performance of 12 azimuth positions. The impact of different channel models on UE MIMO OTA throughput performance as well as the variance per azimuth positions are compared.  
Figure 9: A comparison between the different average manners for (**a**) the UMi and (**b**) the UMa channel model under CTIA interference-limited environmental condition (MARSS raw data).  
Peak-Null can better reflect the difference between the 12 azimuth positions than Variance. TRMS under UE noise-limited environmental condition has a stronger ability to distinguish between good and bad performing DUTs than MARSS under CTIA interference-limited environmental condition. This discrepancy comes from environmental condition itself. Meanwhile, different channel models present nearly the same UE performance trends under 3 GPP UE noise-limited condition. On the contrary, MARSS performance presents highly dependence on channel models. In conclusion, it is proposed to adopt TRMS under UE noise-limited environmental condition as the unique or baseline test condition in 5G FR1 MIMO OTA. Peak-Null can be considered as a secondary FoM to characterize the variance per azimuth.  
Conceptualization, S.S.; methodology, M.Q.; investigation, Z.C. and X.L.; writing--original draft preparation, M.Q.; writing--review and editing, S.S.; visualization, M.Q. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Key Research and Development Project of Guangdong Province (2020B0101080001) and the Fundamental Research Funds for the Central Universities (CUC210B012).  
The authors declare no conflict of interest.
## 2 Materials and Methods
### Sensitivity Analysis  
To investigate the effects of ALS scan angles on the estimation accuracy of the four forest component proportions, we analyzed the root mean square errors (RMSEs) between ALS- and 3 DSMax-based four forest component proportions in plots WPA-P2 (32 scan angles) and WPA-P4 (13 scan angles). In terms of ALS flight path design, we analyzed the effect of crossed and parallel flight paths on the accuracy of the four forest component proportions based on plots PC-P2 (i.e., crossed) and PC-P3 (i.e., parallel). To find the optimum scan angle range for estimating the four forest component proportions, we compared the RMSEs of the ALS- and 3 DSMax-based four forest component proportions in plots WPA-P3 (i.e., -26\({}^{\circ}\) - -16\({}^{\circ}\), -10\({}^{\circ}\) - 10\({}^{\circ}\), 18\({}^{\circ}\) - 28\({}^{\circ}\)). According to the two-side field-of-view ALS configuration with positive (0\({}^{\circ}\)\(\sim\)30\({}^{\circ}\)) and negative (0\({}^{\circ}\)\(\sim\) -30\({}^{\circ}\)) scan angle ranges, we set up six combinations of scan angle ranges including negative-small (i.e., -10\({}^{\circ}\)-0\({}^{\circ}\)), negative-large (i.e., -26\({}^{\circ}\) - -16\({}^{\circ}\)), negative-small and large (i.e., -10\({}^{\circ}\) - 0\({}^{\circ}\), -26\({}^{\circ}\) - -16\({}^{\circ}\)), small negative and positive (i.e., -10\({}^{\circ}\) - 10\({}^{\circ}\)), large negative and positive (i.e., -26\({}^{\circ}\) - -16\({}^{\circ}\), 18\({}^{\circ}\) - 28\({}^{\circ}\)) and all (i.e., -26\({}^{\circ}\) - -16\({}^{\circ}\), -10\({}^{\circ}\) - 10\({}^{\circ}\), 18\({}^{\circ}\) - 28\({}^{\circ}\)). Moreover, we investigated the effects of voxel size on the estimation accuracy of the four forest component proportions by changing the voxel size from 0.1 m to 2.0 m with an interval of 0.1 m in forest plots WPA-P2 and PC-P1. Furthermore, to explore the effects of the comprehensiveness of sampled ground points on the estimation of the four forest component proportions, we restored all missing ground points using the inverse distance weighted method [55].
## Abstract  
The effects of post-annealing on the crystal structure, microstructure, and microwave dielectric properties for Ba(Co\({}_{0.7}\)Zn\({}_{0.3}\))\({}_{1/3}\)Nb\({}_{2/3}\)O\({}_{3}\) ceramics were investigated. The as-prepared materials were characterized by X-ray diffraction, scanning electron microscopy and energy dispersive spectroscopy. The microwave dielectric properties are measured at 6 GHz using a network analyzer. Ba\({}_{5}\)Nb\({}_{4}\)O\({}_{15}\) and/or Ba\({}_{6}\)(Co\({}_{2}\)Zn)\({}_{1}\)Nb\({}_{6}\)O\({}_{24}\) secondary phases were found on the surface according to sintering conditions due to volatilization of some Zn and Co elements. The experimental results show that the beneficial effect of the annealing steps to improved the microwave dielectric properties. Excellent microwave dielectric properties were achieved for the coarse-grained microstructures by a higher sintering temperature and with a shorter holding time followed by annealing steps at lower temperatures with a longer holding time. This improvement can be attributed to 1:2 cation ordering within the crystal, which is taking place during annealing process. The Ba(Co\({}_{0.7}\)Zn\({}_{0.3}\))\({}_{1/3}\)Nb\({}_{2/3}\)O\({}_{3}\) ceramic could be used successfully for realization of dielectric microwave resonators, since it has a high quality factor \(Q_{f}\) value of 123,700 GHz, a high dielectric constant \(\varepsilon_{r}\) value of 34.5 and a temperature coefficient of the resonant frequency \(\tau_{f}\) of 0 ppm/\({}^{\circ}\)C.  
ceramics; microstructure; X-ray diffraction; dielectric properties 29 October 2015; Accepted: 3 December 2015; Published: 22 December 2015  
Academic Editor: [PERSON]
## 2 Methodology
### Recovery of Precise Satellite Orbit/Clock with PPP-B2b  
The information provided by the PPP-B2b service includes the orbit and satellite clock offset corrections of broadcast products in the satellite-fixed frame (radial, along, and cross directions), which cannot be used directly in positioning. Thus, to apply the corrections in PPP, the precise orbit and clock offsets need to be recovered. The satellite positions computed by broadcast ephemeris are given in the Earth-Centered Earth-Fixed reference (ECEF) frame (\(e\)-frame). Therefore, the orbit corrections must be transformed into the ECEF frame by [32]  
\[\begin{bmatrix}\delta O_{x}\\ \delta O_{y}\\ \delta O_{z}\end{bmatrix}=\begin{bmatrix}e_{radial}&e_{along}&e_{cross} \end{bmatrix}\begin{bmatrix}\delta O_{radial}\\ \delta O_{along}\\ \delta O_{cross}\end{bmatrix} \tag{1}\]  
With  
\[\begin{cases}e_{radial}=r/|r|\\ e_{cross}=(r\times\dot{r})/|r\times\dot{r}|\\ e_{along}=e_{radial}\times e_{cross}\end{cases} \tag{2}\]  
where \(\begin{bmatrix}\delta O_{radial}&\delta O_{cross}&\delta O_{along}\end{bmatrix}^ {T}\) is the orbit correction vector in the satellite-fixed frame; \(\begin{bmatrix}\delta O_{x}&\delta O_{y}&\delta O_{z}\end{bmatrix}^{T}\) represents the orbit correction vector in the \(e\)-frame; \(r\) is the satellite position vector and \(\dot{r}\) represents the satellite velocity vector, which can be computed by broadcast ephemeris.  
By applying the corrections in Equation (1) to broadcast ephemeris, precise satellite positions can be calculated by  
\[\begin{bmatrix}X\\ Y\\ Z\end{bmatrix}_{prec,B2b}=\begin{bmatrix}X\\ Y\\ Z\end{bmatrix}_{brtc}-\begin{bmatrix}\delta O_{x}\\ \delta O_{y}\\ \delta O_{z}\end{bmatrix} \tag{3}\]  
where \(\begin{bmatrix}X&Y&Z\end{bmatrix}_{prc,B2b}^{T}\) denotes the vector of precise satellite positions after using the corrections provided by PPP-B2b service; \(\begin{bmatrix}X&Y&Z\end{bmatrix}_{brtc}^{T}\) is the vector of satellite positions calculated by broadcast ephemeris.  
PPP-B2b service also provides the correction of satellite clock offset. The precise clock offsets can be obtained by  
\[dt_{prec,B2b}^{s}=dt_{brtc}^{s}-\frac{C_{0}}{c} \tag{4}\]  
where \(dt_{prec,B2b}^{s}\) is the precise clock offset calculated by using the clock offset derived from broadcast ephemeris (\(dt_{brtc}^{s}\)) and the PPP-B2b clock correction parameter (\(C_{0}\)); \(c\) denotes the velocity of light.
# Automated Detection of Misinformation: A Hybrid Approach for Fake News Detection
## 3 Methodology
### Customization of Naive Bayes Classifier  
In this section, we delve into the customization of naive Bayes classifiers tailored specifically for fake news detection. We enable users to adjust three key parameters: 'alpha', 'fit_prior', and 'class_prior', offering flexibility and control over model performance.  
**The Value of 'Alpha'**: 'Alpha' is a smoothing parameter used to address zero probabilities and enhance model robustness, particularly crucial for handling unseen words in fake news detection tasks. By applying Laplace smoothing, we ensure non-zero probabilities for all words, mitigating overfitting and increasing model generalization.  
**The Impact of 'Fit_prior'**: 'Fit_prior' determines whether the model learns class prior probabilities from the data or uses a uniform prior. This parameter is essential for adapting to imbalanced class distributions, a common scenario in fake news datasets. Adjusting 'fit_prior' based on the dataset's specific distribution optimizes the classifier's predictive ability.  
**The Influence of 'Class_prior'**: 'Class_prior' allows users to specify prior probabilities of classes, offering flexibility in scenarios where domain knowledge diverges from the training set distribution. This parameter empowers users to incorporate external information about class distributions, enhancing the model's adaptability and performance.  
In summary, by customizing these parameters, we empower users to tailor the naive Bayes classifier to suit the unique challenges of fake news detection. This flexibility enables the development of more effective and reliable models, contributing to the ongoing efforts to combat misinformation.
# Enhanced Control Strategy for Three-Level T-Type Converters in Hybrid Power-to-X Systems
## 3 Three-Phase T-Type Bidirectional Converter  
Bidirectional multilevel converters are a combination of DC voltage sources/DC loads and switching power electronic components (IGBT, SiC MOSFET, etc.) connected to an AC loads/AC source through filter, \(L\) or \(LC\) or \(LCL\) filter, as shown in Figure 2, where a three-phase T-type converter is employed. Bidirectional multilevel converters play a significant role in the hybrid operation of P2X systems, as shown in Figure 3. T-type, as employed in this paper, and NPC topologies are the most common of three-phase three-level converters, widely used in high power applications such as P2X (10 kVA-100 kVA).  
This paper focuses on three-phase three-level T-type filtered converter which is powered by a DC voltage source \(V_{DC}\), representing by energy source such as PV renewable energy source, battery storage, fuel cell, which are all connected through a DC/DC converter as shown in Figure 3, or wind power connected through an AC/DC converter. The converter acts as a DC/AC converter, connected to an AC load or to the grid. Figure 4 shows _LCL_ filter implantation for the T-type converter employed in this paper. \(L_{1X}\) is the inverter side inductor, where \(x\) refers to the phases \(a\), \(b\), or \(c\). \(C_{x}\) is the filter capacitor of each phase, and \(L_{2x}\) is the grid/load side inductor of each phase. The proposed control regulates the voltage across the capacitor voltage and the current injected from the inverter to the grid or to an AC load, maintaining stable voltage levels and fast current regulation to enhance the dynamic response to changes in load and generation.  
Figure 5 presents a single-phase representation of the controlled converter in order to simplify the control methodology. \(v_{O}\) and \(v_{C}\) represent the output voltage across the filter capacitance and the grid voltage, respectively, and \(d\) is the controller output. The inverter side inductor \(L_{1}\) current is \(i_{L1}\), and the grid/output side inductor \(L_{2}\) current is represented by \(i_{L2}\).  
Figure 4: Three-level three-phase T-type converter with the _LCL_ filter.  
Figure 3: T-type converter employed in the hybrid system.  
Figure 2: Bidirectional three-level three-phase T-type converter.
## 2 Methods
### Low-Orbit Satellite Constellation Model  
The first step is to establish the low-orbit satellite constellation model. In this work, a typical LEO satellite constellation is considered, including 324 satellites in 18 orbit planes at 1200 km with inclination of \(88^{\circ}\) and additional 576 satellites in 24 orbit planes at 960 km with inclination of \(55^{\circ}\). The satellites in the same orbital plane are uniformly distributed. As shown in Figure 1, the satellite constellation is modeled in a coordinate system with relatively stationary Earth and the GEO data relay satellite. Then, the multi-beam coverage is modeled in the perspective of the GEO satellite. The coverage of a certain beam is modeled with the half-cone angle and the beam center in terms of the azimuth and elevation degrees. Finally, the coordinates of a certain satellite are projected into the multi-beam coverage area to check the service access toward a certain beam. It is worth noting that the Earth as an obstruction should be taken into account to check the line-of-sight propagation between the object and the GEO data relay satellite.
## 3 Results and Discussion
### Scientific Mapping
#### 3.2.11 Communication Difficulties between Teams  
The authors of [52] identified that virtual-reality-based design reviews of complex CAD data often suffer from communication issues between virtual reality users and team members who observe the virtual reality scene from an outside perspective (e.g., a TVscreen). As a consequence, spoken descriptions are often insufficient to express a specific detail about a machinery component.  
The authors of [52] also discovered that in the virtual environment, participants voiced less affect, and [20] found that the social exclusion of virtual reality users sharing the same physical space as colleagues during a design review session has a negative impact on communication and cooperation among team members.
## 3 Results and Discussion
### Effect of Process Parameters
#### 3.1.5 Effect of Extraction Temperature  
Figure 7 shows the effects of the different temperatures (i.e., 20, 25, 30, 40 and 50 \({}^{\circ}\)C) on the extraction yield of quercetin and rutin. As can be seen, when the extraction temperature changes, a significant change has occurred in the extraction yield. That is, the extraction yield rapidly increased with increasing of temperature from 20 to 30 \({}^{\circ}\)C. If a higher temperature was applied, however, the yield obviously decreased. This phenomenon can be explained that higher temperature is not beneficial for ultrasonic-assisted extraction, since high temperature may induce the extracted quercetin and rutin to oxide and decompose during the extraction process. Therefore, extraction temperature is a  
Figure 5: Effect of extraction time using 60% concentration of ethanol solution with 40 mL/g of ratio and 80 kHz at 30 \({}^{\circ}\)C and 200 W on the extraction of quercetin and rutin.  
Figure 6: Effect of ultrasonic power using 60% concentration of ethanol solution with 40 mL/g of ratio at 30 \({}^{\circ}\)C and 80 kHz for 30 min on the extraction of quercetin and rutin.  
very sensitive process parameter for the extraction of quercetin and rutin. Through the above analysis, 30 \({}^{\circ}\)C is chosen as the optimal extraction temperature.
# Recent Advances in Black Silicon Surface Modification for Enhanced Light Trapping in Photodetectors
## 3 Dry Methods for Black Silicon Fabrication
### Reactive Ion Etching (RIE)
The samples were diffused with a phosphorus oxychloride (POCl3) and O2 ratio of 450/600, respectively, in order to minimize the phosphorous atoms in the Si. This led to decreasing dopant surface concentrations. Through applying corona charges, the emitter recombination factor quality has been improved significantly close to the industrial standards in the order of \(\sim\)30 fA/cm\({}^{2}\). Additionally, BSi was fabricated using the RIE method under various parameter conditions to investigate the effects of roughness on the samples [55]. The applied pressure in the process showed a linear relationship with the surface topologies. Furthermore, the RIE technique demonstrated superior surface roughness in comparison to alternative methodologies, including Plasma Immersion Ion Implantation (PIII) and wet etching processes.
###### Abstract  
In this paper, we report the preparation of molecularly imprinted polymer coatings on quartz chips for selective solid-phase microextraction and fluorescence sensing of the auxin, indole-3-butyric acid. The multiple copolymerization method was used to prepare polymer coatings on silylated quartz chips. The polymer preparation conditions (e.g., the solvent, monomer, and cross-linker) were investigated systematically to enhance the binding performance of the imprinted coatings. Direct solid-phase fluorescence measurements on the chips facilitated monitoring changes in coating performance. The average binding capacity of an imprinted polymer coated chip was approximately 152.9 \(\upmu\)g, which was higher than that of a non-imprinted polymer coated chip (60.8 \(\upmu\)g): the imprinted coatings showed the highest binding to IBA among the structural analogues, indicating that the coatings possess high selectivity toward the template molecule. The developed method was used for the determination of the auxin in mung bean extraction, and the recovery was found to be in the range of 91.5% to 97.5%, with an RSD (n = 3) of less than 7.4%. Thus, the present study provides a simple method for fabricating a fluorescent sensor chip for selective analysis.  
Keywords:indole-3-butyric acid; polymer coating; molecularly imprinted polymer; fluorescence detection; molecularly imprinted polymer; sensor chip +
Footnote †: journal: Sensors
# Detection of RINEX-2 Files With Mixed GPS L2P(Y)/L2C Carrier Phase Observations
## 3 Detection Algorithms  
As shown in the previous section, L2 quarter cycle biases are detected best by analyzing fractional widelane ambiguities. In this section, three detection algorithms are presented. The first two make use of estimated widelane ambiguities, either in PPP or in baseline mode. The third algorithm compares corresponding RINEX-2 and RINEX-3 observation files.
## 3 Results and Discussion
### FFA, PV and TBARS  
The FFA content of traditional cooked tilapia (control) was 1.42 g/100 g lipids, whereas the FFA content of all SV-cooked tilapia was significantly lower, accounting for 0.37-0.76 g/100 g of total lipids (\(p<0.05\)), as shown in Figure 1c. Among all SV-cooked samples, samples processed at 60 \({}^{\circ}\)C had higher FFA content, compared with samples processed at 50 \({}^{\circ}\)C at all processing times (\(p<0.05\)), indicating lipid hydrolysis occurring at the higher level when applied with more severe SV conditions. Hydrolysis of glycerol-fatty acid esters can occur because of lipase and phospholipase being liberated from fish muscle, digestive organs as well as from microorganisms during heating, thus, resulting in the accumulation of FFA [7]. Generally, FFAs are susceptible to lipid oxidation. With increasing FFA during the process, lipid oxidation could proceed more rapidly and affect to cooked meat quality, particularly the odor/flavor to some extent.  
PV and TBARS values, which represented the primary and secondary lipid oxidation products, of various SV-cooked tilapia, are presented in Figure 1d,e, respectively. Among all samples, 50-30 had the lowest PV, accounting for 0.40 mg cumene/kg sample, whereas the highest PV was obtained in the 60-60 sample and the control (0.90 and 0.92 mg cumene/kg sample, respectively). It was found that PV increased as cooking temperature or processing time increased (\(p<0.05\)). Our results were in accordance with the results reported by [PERSON] et al. [9], who stated that higher and longer cooking temperatures and times of SV can tremendously increase the rate of lipid oxidation, as indicated by the increase in PV of cooked beef. In this experiment, the result suggested SV cooking of tilapia at 50-60 \({}^{\circ}\)C can accelerate the propagation stage of lipid oxidation but occur at the lower level if compared to traditional boiled fish. The highest TBARS value was also obtained in the control (0.97 mg MDA/kg sample), whereas all SV-cooked samples did not show significantly different TBARS values, which were in the range of 0.76-0.80 mg MDA/kg sample (\(p>0.05\)). In fact, SV treatments are characterized by the absence of oxygen; thus, SV had been supposed to show lower lipid oxidation in comparison with traditional cooking. However, a close correlation between TBARS and sensory properties, particularly off-odor/flavor, has been noted in aquatic products [23]. The generally acceptable limit of TBARS is less than 2 mg MDA/kg sample, and higher than the limit is considered rancid [24]. In this experiment, the TBARS value of all samples was in the range of the limit; thus, it could be inferred that all samples may not owe their off-odor/racidity to lipid oxidation.
# Neural Network Based Approach to Recognition of Meteor Tracks in the Mini-EUSO Telescope Data
## 4 Results
### Active Pixel Selection
The last line of the table shows the false negative rate calculated for pixels containing meteor signals. Two things can be easily noticed. First, the MLP did not properly recognize 18 out of 5395 active pixels, i.e., FNR (pxl) \(\approx\) 0.33%. In this sense the accuracy can be estimated as 99.67% in average. On the other hand, the worst result was obtained for the test run on data from session 8 with FNR (pxl) \(\approx\) 0.75% so that the accuracy for this particular session equals 99.25%. We have tried to address the same task with a few other machine learning methods, among them logistic regression, K nearest neighbors, the random forest, and XGBoost. We have failed to outperform results demonstrated with the MLP with any of them.
In addition, the binding capacities after 1 h of contact showed binding capacities of 1.250 and 4.600 \(\mathrm{m}\mathrm{g}\)/\(\mathrm{g}\) for As(III) and As(V) for Fe\({}_{2}\)O\({}_{3}\). The Fe\({}_{3}\)O\({}_{4}\) nanomaterial showed binding capacities of 8.196 and 6.711 \(\mathrm{m}\mathrm{g}\)/\(\mathrm{g}\) for the binding of As(III) and As(V), respectively. In the present study, ZnO was synthesized through a precipitation method. The synthesized ZnO nanoparticles were characterized using XRD, SEM and Raman spectroscopy to determine crystallinity, phase, and morphology. In addition, the samples were analyzed using XRD and Raman spectroscopy after reaction with the As(III) and As(V) ions to determine if any changes in the material phase or the presence of reaction products could be observed. Batch studies were performed to determine the effects of pH, temperature, time, and binding capacity on the As(III) and As(V) binding. The batch isotherm studies, and time dependency studies were performed to investigate the thermodynamic parameters of the binding and the time dependency of the binding process. ZnO was selected as the adsorbent to be investigated because of its properties, especially its cost-effective synthesis. The favorable synthesis properties did not require the need of surfactants, aqueous solution chemistry, and nor the need to calcine or convert the product at high temperatures. In fact, there is a potential for ZnO to be widely used for the removal of As(III) and As(V) from aqueous solution.