esa-sceva/satcom-chunk-collection huggingface dataset:
# Physical Layer Definition for a Long-Haul HF Antarctica to Spain Radio Link
## 3 System Description
### Hardware of the Transmitter
#### 3.1.2 Antenna and Antenna Tuner  
One of the requirements of a system operating in Antarctica is the low environmental impact, thus, a simple antenna with the maximum of radiation towards the horizon would be desirable. The monopole is one of the most useful antennas waiting this kind of scenario, but an antenna tuner is needed to transmit throughout the whole HF band. Thus, we installed a monopole for signal transmission purposes.  
However, when using amateur radio antenna tuners, sometimes the adaptation is not perfect mainly at the lower frequencies of the HF band and one may get high values of Voltage Standing-Wave Ratio (VSWR) with a significant amount of reflected power. Moreover, the monopole is subject to strong winds and extreme weather conditions, so its behavior degrades over time.  
Figure 4: Complete block diagram of (**a**) the transmitter and (**b**) the receiver.  
In order to lower the main radiation lobes of the monopole to maximize the gain, we had to improve the conductivity of the ground plane. In Antarctic regions, due to the permafrost found when soil is at or below freezing point, conductivity is far from the ideal value.  
Several simulations were conducted to evaluate the change in the gain in elevation angles lower than \(11^{\circ}\) from the horizon, depending on the number and the length of the radials of the monopole, and also of the type of terrain. The radial characteristics do not change the adaptation of the antenna tuner, but as the voltage is higher when performing with radials, a more detailed design has to be done to avoid system malfunction.  
The simulation software used were 4 NEC2 [19] and EZNEC+ [20], both simulation methods for wire antennas, using NEC2 as standard simulation technique, originally developed as NEC by Lawrence Livermore Laboratory [21]. Several simulations were conducted using the classical paradigm of simulation, measuring the change in the gain modifying only one of the simulation parameters (either the number of radials, the length, the section, the type of terrain or the frequency).  
Simulations conducted for different types of terrain or frequency did not modify substantially the gain results; the parameters associated to the radial design had a clearer influence in the gain variations. The results, which led us to conclude the best radial characteristics, are shown in Figure 5. They compare the gain at 15 MHz with an elevation of \(5^{\circ}\) without and with radials. The results show that the gain increased from \(-10.7\) dB without the radials to \(-8.6\) dB with the radials. Nearly 2 dB of gain obtained only by choosing 32 radials of 15 m length and 2.5 mm\({}^{2}\) section.  
That means an increment of the voltage drop at the antenna terminals, and some additional isolation was needed to avoid the electric arc.
# High-Efficiency Triple-Band RF-to-DC Rectifier Primary Design for RF Energy-Harvesting Systems
## 2 Radio Frequency Energy-Harvesting Design  
### Rectenna System Design  
The rectifying antenna (rectenna) is a joint system of an antenna and an RF-to-DC rectifier. The antenna is responsible for capturing the ambient RF electromagnetic energy, whereas the rectifier converts the input AC voltage into DC voltage, able to feed low-power electronic devices. In many cases, an impedance-matching network intervenes between the RF-to-DC rectifier and the antenna, to adjust the impedance between these two elements. [PERSON] [22] invented the first rectenna in the early 1960s. Since then, the technological revolution has encouraged researchers to design and fabricate more efficient and sophisticated circuits. Figure 1 illustrates the basic block diagram of a rectenna system.
# Online Street View-Based Approach for Sky View Factor Estimation: A Case Study of Nanjing, China
## 5 Conclusions  
This study presents the development of BMapSVF, and the source code, demo, and models are publicly available at [[https://github.com/Voyagerlemon/BMapSVF](https://github.com/Voyagerlemon/BMapSVF)]([https://github.com/Voyagerlemon/BMapSVF](https://github.com/Voyagerlemon/BMapSVF)) (accessed on 12 December 2023). It is a novel tool for easily obtaining SVF information from the massive BSV panorama database in developed cities in China. The tool is demonstrated through a complex environmental scenario in the Qinhuai District, aiming to enable fast computation of the SVF for large urban areas and further analysis of the spatial distribution of the SVF.  
In all sampling points within the Qinhuai District, SVF estimation occurs through methods based on both 3D urban building models and BMapSVF, resulting in an RMSEof 0.3445, an MBE of \(-\)0.2816, and an R of 0.5972. At sampling points with limited tree coverage, the RMSE of the SVF estimates from both methods is 0.0442, the MBE is \(-\)0.0339, and the R is 0.9784. Conversely, at sampling points with substantial tree coverage, the RMSE of the SVF estimates from both methods is 0.7699, the MBE is 0.4642, and the R is 0.6894.  
Within the complexities of urban settings, BMapSVF excels in delivering more refined estimations of the SVF. However, it is imperative to consider spatial uncertainty factors, particularly in the context of tree obstructions. This consideration may result in a decline in SVF values estimated through BMapSVF, further illustrating that the spatial structure of this region is more diversified than that of other urban areas.  
In general, BMapSVF efficiently extracts the SVF using online map data resources, resolving limitations in online, large-scale, and rapid SVF estimation capabilities. Given that this tool has undergone testing solely in existing scenarios, users may need to assess its applicability under diverse conditions. Furthermore, the tool incorporates the intelligent retrieval of other urban spatial data, offering users flexibility based on their specific requirements.  
Conceptualization, H.L.; Data curation, H.X. and S.L.; Formal analysis, H.X.; Methodology, H.X., H.L. and S.L.; Software, H.X.; Supervision, H.L.; Validation, H.X.; Writing--original draft, H.X.; Writing--review and editing, H.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, grant number 41478324.  
Not applicable.  
The study did not report any publicly archived datasets, please refer to the GitHub repository provided in this paper for specific details.  
The authors declare no conflicts of interest.
## 3 Results
### Influencing Factors of the Communication Elements
For example, from the \"communication intention\" of an \"alarm/process parameters/status surveillance\", the resulting \"act of communication\" might be (1) an \"announcement\", when the speaker announces the readings on the display, (2) \"self-judgment\", when the speaker adds his/her opinion, (3) \"repeating known information\", when one of the speaker's tasks is to repeat certain information periodically, although there is no change, or (4) a \"warning\", when the announcements are ignored and the speaker finds the situation is becoming dangerous, or other acts of communication. The \"communication content type\" categorizes \"communication utterances\" based on the content, resembling a speech-act coding scheme. The difference between an \"act of communication\" and \"communication content type\" is that in the latter, no context is assumed or known, whereas an \"act of communication\" is the product of the communication intention of the speaker. The speaker's identity and task provide a context for the resulting \"act of communication\". While some of the content types might be similar to the others, in the current research, we gathered the findings from the reference papers as comprehensively as possible.
# Estimation of Chlorophyll Fluorescence at Different Scales: A Review
## 3 Chlorophyll Fluorescence Detection near the Ground
### Passive Chlorophyll Fluorescence Measurement
#### 3.2.1 Spectral Fitting Method (SFM)
\begin{table}
\begin{tabular}{l l} \hline \hline \multicolumn{1}{c}{**Parameter**} & \multicolumn{1}{c}{**Meaning**} \\ \hline \(L(\lambda)\) & The canopy radiance \\ \(L_{\text{measure}}(\lambda)\) & Measured canopy radiance \\ SIF(\(\lambda\)) & Fluorescence radiance \\ \(\rho(\lambda)\) & Canopy reflectance \\ \(E^{g}(\lambda)\) & The integral of incoming radiance over hemisphere in the bottom of atmosphere \\ \(c_{fi}\) & Coefficients of basis spectra of fluorescence \\ \(c_{rj}\) & Coefficients of basis spectra of reflectance \\ \(\phi_{fi}(\lambda)\) & Basis spectra of fluorescence \\ \(\phi_{rj}(\lambda)\) & Basis spectra of reflectance \\ NF & The number of basis spectra of fluorescence \\ Nr & The number of basis spectra of reflectance \\ \(b_{0}\), \(b_{1}\), \(b_{2}\), \(b_{3}\), \(b_{4}\), \(b_{5}\) & Coefficients of the expressions of solar-induced fluorescence (SIF) and reflectance \\ \(SIF_{\text{FSR}}\) & The full SIF spectrum \\ \(c_{1}\), \(c_{2}\), \(c_{3}\) & Coefficients of basis spectra \\ \(v_{1}\), \(v_{2}\), \(v_{3}\) & Basis spectra of full SIF spectrum \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Parameters used in the Equations (1)–(6). the basis spectra of the full SIF spectrum by singular value decomposition (SVD), and the full SIF spectrum is written as follows [81]:  
\[SIF_{FSR}=c_{1}\cdot v_{1}+c_{2}\cdot v_{2}+c_{3}\cdot v_{3} \tag{5}\]  
In Equation (5), \(c_{1}\), \(c_{2}\) and \(c_{3}\) are the coefficients of basis spectra, and are determined with the optimization process at five absorption bands. The FSR method only uses the information at five absorption bands of the SIF spectrum. Based on this idea, [PERSON] et al. proposed an aFSR (advanced FSR) method which uses the full information of the SIF spectrum. The upwelling radiance is expressed as follows [84]:  
\[L(\lambda)=\sum_{i=1}^{Nf}c_{fi}\phi_{fi}(\lambda)+\frac{E^{g}(\lambda)}{\pi} \sum_{i=1}^{Nr}c_{ri}\phi_{rj}(\lambda) \tag{6}\]  
in which, the parameter descriptions are shown in Table 1. With respect to Equation (6), the linear least squares method is used to obtain the coefficients by computing the residual between the measured upwelling radiance and the modeled upwelling radiance in the range of 640-850 nm. In the last, the full fluorescence spectrum is constructed. The F-SFM method proposed by [PERSON] et al. has a similar idea with the aFSR method [82]. In the F-SFM method, the reflectance is written as a first-order linear expression, and the basis spectra of the SIF spectrum is generated by principal components analysis (PCA).
# Comparative Technical-Economical Analysis of Transient Stability Improvements in a Power System
## 4 Improved System Description  
The improvement solutions, described in Parag. II, are now connected to the IEEE 9 bus system. See Figure 1 in order to analyze their effects on the rotor angle stability. The main features of such systems are:  
* SVC device of \(\pm\)50 MVAr connected to the load bus 8. The SVMSO1 model is used to implement the SVC in the PowerWorld Simulator. The block diagram model and the modified parameters are listed in Table 3 (the other parameters are set to default values);
* STATCOM device of \(\pm\) 50 MVAr connected to load bus 8. To implement the STATCOM in the PowerWorld Simulator, the SVMSO3 model is used. The block diagram of the model and the modified parameters are shown in Table 3 (the other parameters are fixed at default values);
* Fast-acting exciters. The standard IEEET1 exciter of the three generators is replaced by the EXST4B fast-acting exciter model (IEEE ST4B). The block diagram model and the main differences between IEEET1 and EXST4B in terms of parameters are listed in Table 4 (all parameters are set to the default values for both models);
* The transmission line runs parallel to the already existing line between buses 5 and 7.  
Figure 2: Rotor angles of three generators, FCT = 0.35 s.
## 2 Results and Discussion
### Analytical Performances  
Analytical performance of the proposed HS-SPME-GC-FID strategy was assessed by obtaining analytical figures of merit, including linear dynamic ranges (LDR), limit of detection (LOD), limit of quantification (LOQ), and relative standard deviation (RSD). Calibration curve was linear over the range of 5-40,000 ng\(\cdot\)g\({}^{-1}\), with a correlation coefficient of 0.994. LOD and LOQ were obtained as 0.01 and 0.4 ng\(\cdot\)g\({}^{-1}\), respectively. To evaluate the repeatability of the method, RSD was calculated based on six repeated analyses of 2 \(\mu\)g\({}^{-1}\) of the analyte. It was found to be 8.4%. Inter-day RSD (reproducibility) was calculated 19% by repeating an experiment in six different days, at the same conditions. The inter-fiber reproducibility was also obtained (26%). The big intra-fiber RSD is probably due to the nature of electropolymerization process, with different affecting variables. For further demonstrating the superiority of the developed HS-SPME-GC-FID method with PPy@MIL-101(Cr) nanosorbent, its analytical performances were compared with some similar procedures that are reported in the literature [25; 26; 27; 28; 29; 30; 31; 32]. The results are summarized in Table 1. As is clear from the results, the HS-SPME-GC analysis using PPy@MIL-101(Cr)-coated fiber has wider linear range than all other cited methods. Its LOD and RSD are bigger or comparable with the mentioned procedures. However, it should be considered that this strategy is capable for direct analysis of complicated solid samples, while other methods have been applied in water media and some of them have used MS as much sensitive detection system.
###### Abstract  
The federated recommender system (FRS) employs federated learning methodologies to create a recommendation model in a distributed environment, where clients share locally updated data with the server without exposing raw data and achieving privacy preservation. However, varying communication capabilities among devices restrict the participation of only a subset of clients in each round of federated training, resulting in slower convergence and requiring additional training rounds. In this work, we propose a novel federated recommendation framework, called FedRecI2C, which integrates communication and computation resources in the system. This framework accelerates convergence by utilizing not only communication-capable clients for federated training but also communication-constrained clients to leverage their computation and limited communication resources for further local training. This framework offers simplicity and flexibility, providing a plug-and-play architecture that effectively enhances the convergence speed in FRSs. It has demonstrated remarkable effectiveness in a wide range of FRSs when operating under diverse communication conditions. Extensive experiments are conducted to validate the effectiveness of FedRecI2C. Moreover, we provide in-depth analyses of the FedRecI2C framework, offering novel insights into the training patterns of FRSs.  
federated recommender system; convergence rate; communication resources; computation resources +
Footnote †: journal:
## 2 Materials and Methods  
### MR Data and Acquisition Protocols  
We analysed a 2D multi-slice dataset of abdominal CSE-MRI, obtained from 209 subjects using a 1.5 T Philips Achieva scanner (Philips Healthcare, Best, The Netherland). Part of this dataset had been previously reported [20; 21], and the study was approved by the local Ethics Committee. Among the 209 subjects, 189 were suspected of having MASLD based on ultrasound findings, while the remaining 20 were healthy volunteers. For each subject, 16 to 28 axial slices were acquired to capture the entire pancreas and liver, resulting in a total of 4640 axial abdominal images.  
To acquire the images, the MR scan protocol used uniformly spaced echo times (TEs) to minimise the scan time, considering the use of a 4-channel abdomen coil and a voxel size of 0.89 \(\times\) 0.89 \(\times\) 10.00 mm. The scan parameters that were used are shown in Table 1: multi-slice images were acquired at six different echo times, with the first echo time (TE\({}_{1}\)) at 1.3 ms and an echo spacing (\(\Delta\)TE) of 2.1 ms. For each sample, we computed reference water-fat images and their respective \(R_{2}^{*}\) and \(\phi\) quantitative maps using the graph-cut method with 6 echoes. In a subset of volunteers (N = 18), we also acquired three-echo images with the same TE\({}_{1}\) and \(\Delta\)TE but with the shortest possible repetition time (TR) determined by the scanner (13-47 ms). This was performed to test DL models trained to process three-echo images, which were trained using the first three echoes of the training data. For comparison purposes, we also performed water-fat separation using graph cut and only three echoes.
# Fault Analysis and Protection Principle for the Distribution Networks Integrated with PV and BESS
## 2 Fault Characteristics of the Distribution Networks with PV and BESS
### Negative Sequence Impedance Characteristics of the Network During Asymmetric Faults
At this time, the PV and BESS need to output more positive sequence active current and absorb more negative sequence reactive current, and it is very likely to reach the reactive current limit, thus making the negative sequence impedance of the PV and the BESS greater than the value in Equation (3). Figure 2: (**a**) Composite sequence network when two-phase short-circuit faults occur at \(f_{3}\). (**b**) Composite sequence network when two-phase short-circuit faults occur at \(f_{4}\). When the fault location is the same, the smaller the transition resistance, the smaller the positive sequence voltage at bus C and the larger the negative sequence voltage. Similarly, in this case, it is also easier to reach the reactive current limit, making the negative sequence impedance of the PV and BESS greater than the value in Equation (3). In conclusion, the negative sequence impedance of the PV and the BESS is the largest when the system is in the minimum operation mode and a forward outlet metallic two-phase short-circuit fault occurs.
# Biosorption of Heavy Metals by the Bacterial Exopolysaccharideaccharide FucoPol
## 3 Results and Discussion
### Effect of pH in Pb\({}^{2+}\) Removal by FucoPol  
The pH affects the metal's solubility and the functional groups responsible for the metal-binding capacity since it determines their ionization state (protonated/deprotonated) [1; 38; 40; 42; 43]. The influence of this parameter in the metal-binding ability of FucoPol (5 g/L) was evaluated for pH values between 2.5 to 4.3 (the latter was the pH value of the original metal solution), using an initial Pb\({}^{2+}\) concentration of 10 mg/L (Figure 4). It was not possible to test higher pH-values due to the occurrence of chemical precipitation of the metal above pH 6 [1; 44].  
As shown in Figure 4, FucoPol had a higher removal efficiency at the maximal pH value tested (4.3). A reduction in pH (3.3 and 2.5) led to a considerable decrease in metal removal (\(39.8\pm 2.8\%\) and \(7.3\pm 2.7\%\), respectively). These results were probably due to the fact that the acidic groups of FucoPol were protonated, decreasing the negative charges available to interact with Pb\({}^{2+}\) cations [23; 35]. A similar trend was described for other anionic EPS, including the EPS produced by _A. macedoii_ subsp _fijiensis_ that demonstrated a low binding capacity at pH values below 4, and optimal stable metal uptake values when the pH was between 4.5 and 6 [33]; and for the EPS produced by _B. firmus_ MS-102, which optimal Pb\({}^{2+}\) uptake was found at pH 4.5 [21]. As can be seen in Table 1, these EPSs had polyanionic character due to their presence of uronic acids and acyl substituents in their composition. On the other hand, the EPS that did not present these groups in their composition seemed to be more efficient at neutral pH. Examples include the EPS produced by _P. peoriae_, a fructose  
Figure 3: Removal of Pb\({}^{2+}\) (\(C_{i}\) 10 mg/L) with different FucoPol concentrations. Results presented in terms of metal uptake (\(q\), \(\bullet\)) and removal efficiency (\(M\), \(\blacksquare\)) (pH 4.3, temperature 21 \({}^{\circ}\)C, incubation time 24 h).  
homopolysaccharide [23]; and the EPS produced by a mixed culture of _R. radiolobacter_ F2 and _B. sphaeicus_ F6 that was only composed of neutral sugars (Table 1) [38].
# An Accurate Probabilistic Model for TVWS Identification
## 2 Background
Based on our analysis of the above mentioned works, we propose that at least three parameters should be considered in each geographical location to evaluate a TV channel, namely, the real instantaneous noise signal, the composite signal consisting of users' signal and noise, and the energy detected in each reading. These parameters ensure the accuracy of the detected channels and can be used to apply or adapt the IEEE 802.22 standard in current CR systems.
# Enhancing Image Dehazing with a Multi-DCP Approach with Adaptive Airlight and Gamma Correction
## 5 Evaluations  
The proposed method is assessed using the Real-World Task-Driven Testing Set (RTTS) obtained from the Realistic Single Image Dehazing (RESIDE) benchmark [15]. The RTTS is specifically curated to consist solely of images depicting natural haze, ensuring the authenticity and relevance of the evaluation. This dataset comprises 4322 images characterized by diverse dimensions and a wide range of haze intensities and environmental conditions.  
In our evaluation, we utilize the Dehazing Quality Index (DHQI) [14], a metric designed to assess the effectiveness of dehazing algorithms specifically on images affected by fog or hazy weather, rather than evaluating overall noise reduction.