esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Optimal AOS/Gelatin Concentration for Stable Foam Generation  
The optimum concentrations of AOS and the stabilizer (gelatin) were determined by measuring the half-life period of the foam. As shown in Figure S2A, the foam stability (in terms of half-life) gradually increased with increasing AOS concentration. The foam half-life increased from 10 min to 32 min when the AOS concentration was increased from 0.05 to 0.20%. However, a further increase in the AOS concentration did not increase the half-life, resulting in constant foam stability.  
The influence of gelatin concentration (0.05, 0.10, 0.15, 0.20, 0.25, 0.30, 0.35, and 0.40%) on the foam half-life was also investigated in the system by adding a predetermined concentration of AOS (i.e., 0.2%). As shown in Figure S2B, the foam stability sharply increased from 37 min to 120 min when the gelatin concentration increased from 0.05 to 0.30%. A further increase in gelatin concentration up to 0.40% did significantly increase foam stability, which remained virtually constant with a half-life of only 122 min. Therefore, 0.3% was selected as the optimal concentration of gelatin. Thus, this study selected the optimal concentration of AOS and gelatin as 0.2% and 0.3%, respectively, with a half-life of 2 h.  
Gelatin is an effective foam stabilizer, and during its use, the surfactant binding ratio of the foam usually becomes smaller than normal. Refs. [34; 35] identified a surfactant and stabilizer with similar compositions to our experiment (0.86 g of AOS was stabilized with 1 g of protein). A further increase in the stabilizer concentration smears out or distorts the weak bonds, such as intra- and intermolecular hydrogen connections of polymers, which further loosens (uncoils) the polymer chain. The combination of AOS and gelatin does not negatively affect biocompatibility; AOS is popular because of its superior biocompatibility and physio-chemical properties, along with its excellent foaming characteristics. Furthermore, AOS is resistant to the hardness of water and other metallic ions and is stable over a wide pH range.
## 3 The Proposed System's Architecture  
The proposed system aims to provide an adaptation of the course material based on the knowledge level of a student, in which a topic should be delivered, which topic needs revision, and which topic has been learned. This system is able to identify and update the knowledge level (KL) of a student, allowing each individual student to finish the e-learning course at his/her own pace and provide feedback and hints for an individual student. The basic architecture of FB-ITS, as presented in Figure 1, is based on the classical architecture of ITSs [41]. The importance of the developed FB-ITS is that it is a web-based system which can be used anywhere at any time. This system has been tested in Google Chrome, Mozilla Firefox, Microsoft Edge, and Internet Explorer browsers. Therefore, it allows a multitude of learners to access the FB-ITS from different platforms.  
This ITS was implemented in the Microsoft Visual Studio 2015 development environment using ASP.net, an open-source server-side web application framework designed for developing dynamic web applications. The functionality of the system was written using VB.net, which is a multi-paradigm, object-oriented programming language, implemented on the. NET Framework. Since an FB-ITS is a web-based system, there should be some mechanism for representing, storing and retrieving data related to the components of the system (the knowledge domain model and the student model) and any data related to the student-system interaction in order to provide adaptation. Microsoft SQL Server 2014 was used to create and manage the database. Microsoft SQL Server is compatible with ASP.net and they interact with each other properly.  
Three versions of the ITS were developed and implemented in this research based on the architecture presented in Figure 1. These versions have the same components except for the student model. The student model in the first version was created using the Bayesian network, only according to the Bayesian student model. In the second version, it was created using fuzzy logic only, and in the third version, the student model was created using a combination of the Bayesian network and fuzzy logic, named FB-ITS, to meet the objectives of this study. The purpose of creating these three versions is to answer the research questions and to demonstrate that combining the Bayesian network and fuzzy logic technology increases the performance of the ITS, compared to using fuzzy logic and Bayesian networks separately.
## 2 Set-Up and Hardware Description
### Dual-Polarized Antenna  
A novel, dual-circularly-polarized (shortly 2 pol) antenna has been developed in the project. It relies on a concept that is currently implemented in an RHCP geodetic-grade antenna supporting all GNSS signals in L band [18; 19]. Within the framework of the FANTASTIC project, a novel feed network enabling wideband dual-mode operation was developed and, additionally, optimizations in terms of efficiency and beam width were performed. The antenna is illustrated in Figure 0(a) and its main characteristic are listed in Figure 0(b). Figures 2 and 3 show the measured radiation patterns for both the RHCP and LHCP, respectively.  
Figure 1: Developed 2 pol antenna within the framework of the FANTASTIC project (**a**) and its main characteristics (**b**).  
Figure 3: Measured radiation patterns (normalized) of the LHCP output of the 2 pol antenna prototype. (Red) RHCP gain and (blue) LHCP gain.  
Figure 2: Measured radiation patterns (normalized) of the RHCP output of the 2 pol antenna prototype. (Red) RHCP gain and (blue) LHCP gain.  
It can be seen that the plots for the co-pol and cross-pol components are almost identical and nearly optimal in terms of multipath suppression and ability to receive signals from satellites at low elevation angles. The antenna provides high polarization purity in all directions of interest with a cross polarization discrimination (XPD: difference between co-pol and cross-pol gain) of at least 10 dB (axial ratio 5.6 dB). This is the minimum value for XPD the antenna will provide, particularly for low elevation angles. For the major part of the specified covering region (higher elevations, directions of interest) the values are greater than 15 dB, being the value in the zenith not worse than 16 dB (axial ratio of 3 dB). It should be noted that a high XPD is very important for the approach described here because of the navigation performance targets, avoiding spill-over of LHCP multipath components into the RHCP line-of-sight signal. It is worth pointing out that the requirement of 16 dB for the XPD is very difficult to achieve at all frequencies and angles of interest. Just for reference, the high-quality antenna Polant MC (not dual circularly polarized) from AeroAntenna, the main competitor due its excellent performance in terms of accuracy, exhibits even worse performance than the FANTASTIC antenna: XPD \(>\) 9 dB.
# Modeling of the Drying Process of Apple Pomace
## 4 Conclusions  
The process of drying apple pomace may be modeled by means of Page equation. The estimation results were consistent with the experimental results.  
As expected, the results of the research also confirmed the fact that the temperature of drying air had the greatest impact on drying time. The increase in temperature resulted in a shortening of the drying time and in the increase in intensity of moisture release by the pomace.  
Despite the essence of kinetics, modeling of drying of materials is indispensable for understanding the basic mechanism of transport, and is a precondition for successful simulation or for the increase in the scale of the whole process in order to optimize it or control working conditions. Simple models are effective for engineering purposes. Mathematical modeling of dehydration process is an inherent part of design, development and optimization of drying equipment.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Type of Drying**} & \multicolumn{6}{c}{**Equation Coefficient**} \\ \cline{2-6}  & \(\mathsf{b}\) & \(\mathsf{k_{0}}\) & \(\mathsf{N}\) & \(\mathsf{K}\) & \(\mathsf{n}\) \\ \hline \multicolumn{6}{c}{Models of external and internal heat and mass transfer} \\ \hline Forced & 0.200668 & 0.0533 & 1.03 & 0.0258 & - \\ convection 40\({}^{\circ}\) & 0.196212 & 0.19986 & 4.60 & 0.0837 & - \\ Forced & 0.200260 & 0.0868 & 1.18 & 0.1078 & - \\ \hline \multicolumn{6}{c}{Page model} \\ \hline Forced & - & 0.021995 & - & - & 1.01 \\ convection 40\({}^{\circ}\) & - & 0.069859 & - & - & 1.02 \\ Forced & - & 0.069859 & - & - & 1.02 \\ convection 80\({}^{\circ}\) & - & 0.069859 & - & - & 1.02 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Coefficients of equations that describe the kinetics of drying depending on the method and parameters of the process.  
Present expectations of consumers regarding higher quality foodstuffs result in research intensification and improvement of drying technology. The observed differences in kinetics of drying and initial processing need to be taken into account when choosing the best conditions of drying in order to improve the quality of the finished product. Consumption of energy and economic viability of the process of drying apple pomace also require consideration.  
Conceptualization, W.T. and S.G.; methodology, W.T. and S.G.; formal analysis, W.T.; investigation, W.T.; resources, W.T.; data curation, W.T.; writing--original draft preparation, W.T.; writing--review and editing, W.T. and S.G.; visualization, W.T.; supervision, S.G.; project administration, S.G. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The data presented in this study are available on request from the corresponding author.  
The authors declare no conflict of interest.
# Tie-System Calibration for the Experimental Setup of Large Deployable Reflectors
## 2 Experimental Settings for Calibration
### Rear Node Determination  
In the event that only the co-ordinates of the nodes of the front net are known by measurement, before implementing the algorithm described above, the rear node co-ordinates have to be estimated. Their co-ordinates are initialized with the design data and System (1) is implemented for each free node of the front and rear net. Note the dualism between the two methods: In the former, the unknowns are the construction lengths; in the latter, they are the rear node co-ordinates. Next, the construction lengths are obtained as a consequence of using the Euclidian norm. We checked that both methods lead to the same results (except for negligible errors) if the experimental configuration is not too distant from the design one.
## 4 Simulation Results
### Influence of the Number of RIS Units on Asymptotic Capacity  
To investigate the influence of the number of RIS units on the asymptotic capacity, we set several simulations by changing the number of RIS units while retaining the other parameters unchanged. The RIS units cannot be too small due to the fact that the system model of indoor parallel MIMO VLC is derived based on the point source hypothesis [22]. Consequently, we assume that the area of the RIS unit is \(10\ \mathrm{cm}\ \times\ 10\ \mathrm{cm}\), and for fairness, the center point of RIS is constant when the number of RIS units increases (i.e., the RIS units are deployed on the wall evenly centered on the center point we set).  
Figure 4 shows the influence of the number of RIS units on the asymptotic capacity with the assignment scheme derived by the proposed algorithm. From the figure, we can obtain that the growth rate of the asymptotic capacity improves steadily with the increase of the number of RIS units. However, the slope of the growth rate decreases with the increase of the number of RIS units. This is due to the marginal benefit and the constraints on the RIS design. This reminds us that the RIS needs to be further developed in the future to overcome the technical bottleneck (e.g., much smaller physical area of the RIS units).  
Figure 3: Asymptotic capacity versus different SNR with different assignment schemes, \(K=100\).  
Meanwhile, it is observed that the growth rate decreases when the SNR increases. This is because a higher SNR means a larger primal asymptotic capacity, and hence the growth rate decreases with the increase of the SNR.
###### Abstract  
Satellite remote sensing has been widely recognized as an effective tool for estimating fire severity. Existing indies predominantly rely on broad-spectrum multispectral data, limiting the ability to elucidate the intricate relationship between fire severity and spectral response. To address this challenge, the optimal spectral bands and indices for fire severity assessment were explored using ZY-1 hyperspectral data, which captured pre- and post-fire conditions of a forest fire site in Yuxi City, Yunnan Province, China. Separability contrast and threshold segmentation methods were applied to perform a sensitivity analysis on the original spectral bands and constructed indices derived from surface reflectance of the post-fire image and the pre- and post-fire image combination, respectively. The findings indicate the following: (1) The spectral bands of the post-fire image exhibited superior spectral separability and classification capabilities compared to the pre- and post-fire difference image, with the highest forest fire severity classification accuracy of 78.99% achieved at the 800 nm central wavelength. (2) The difference of normalized difference index category for the pre- and post-fire image combination outperformed the vegetation indices of the post-fire image and the other vegetation indices using the pre- and post-fire image combination, with the highest forest fire severity classification accuracy of 83.39% achieved with the combination of 2048 nm and 1106 nm central wavelength. (3) Unburned areas exhibited strong separability, facilitating effective segmentation, but burned areas showed poor separability between fire severities, particularly between low and moderate-high severity, which remains the primary limitation in fire severity assessment. In conclusion, this study advances the understanding of fire severity and spectral response by leveraging the narrow-band advantages. It aims to enhance the accuracy of satellite-based fire severity estimation, offering valuable technical guidance and theoretical insights for assessing forest fire impacts and vegetation recovery.  
hyperspectral data; forest fire; fire severity; spectral index; sensitivity analysis +
Footnote †: journal: Physics Letters  
Article Exploration of Suitable Spectral Bands and Indices for Forest Fire Severity Evaluation Using ZY-1 Hyperspectral Data  
[PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], L. Exploration of Suitable Spectral Bands and Indices for Forest Fire Severity Evaluation Using ZY-1 Hyperspectral Data
# A Low-Ambiguity Signal Waveform for Pseudolite Positioning Systems Based on Chirp
###### Abstract  
Signal modulation is an essential design factor of a positioning system, which directly impacts the system's potential performance. Chirp compressions have been widely applied in the fields of communication, radar, and indoor positioning owing to their high compression gain and good resistance to narrowband interferences and multipath fading. Based on linear chirp, we present a modulation method named chirped pseudo-noise (ChPN). The mathematical model of the ChPN signal is provided with its auto-correlation function (ACF) and the power spectrum density (PSD) derived. The ChPN with orthogonal chirps is also discussed, which has better resistance to near-far effect. Then the generation and detection methods as well as the performances of ChPN are discussed by theoretical analysis and simulation. The results show that, for ChPN signals with the same main-lobe bandwidth (MLB), generally, the signal with a larger sweep bandwidth has better tracking precision and multipath resistance. ChPN yields slighter ACF peaks ambiguity due to its lower ACF side-peaks, although its tracking precision is a little worse than that of a binary offset carrier (BOC) with the same MLB. Moreover, ChPN provides better overall anti-multipath performance than BOC. For the ChPN signals with the same code rate, a signal with a larger sweep bandwidth has better performance in most aspects. In engineering practice, a ChPN receiver can be implemented by minor modifications of a BOC receiver. Thus, ChPN modulation shows promise for future positioning applications.  
chirp; low-ambiguity; high-precision; navigation; pseudolite +
Footnote †: journal: Sensors
## 6 Discussion  
Our primary objective was to ensure that the dataset adequately represents the unique characteristics of each language (Japanese, English, and Hungarian), including the alphabets, most frequently used characters, writing styles, and common vocabulary. This allows the OCR system to learn and recognize the distinctions and combinations between or among language scripts effectively. The dataset that was used in the experiments contains high-quality, clean, and accurate text samples from well-known and recent sources to train the OCR system effectively. This ensured that the model learned to recognize characters and words--as well as hybrid languages--accurately, improving its overall performance in real-time OCR tasks. The training dataset prepared incorporated samples with various degrees of noise, such as occlusions, distortions, or low-quality images, to train the OCR system to be robust and tolerant to noise in real-world scenarios. During experiments and the dataset preparation workflow optimization process, we included a wide variety of text samples, such as different fonts, writing styles, and contexts, which helped the OCR system generalize better and adapt to various scenarios. This diversity in data enables the model to handle a wide range of text inputs from different sources. We established that a \"balanced dataset\" is essential to prevent the model from being biased towards a particular language or character set. As a future outcome, this involves the \"equal\" representation of each language and the mitigation of class imbalances, enabling the OCR system to recognize characters and words from all three languages equally well. It was ensured that the training dataset included samples that reflect the contextual variations of each language and their variations (e.g., English acronyms or technical terms in Hungarian or English phrases). This allows the OCR system to understand and interpret texts or phrases within different contexts, such as formal, informal, technical, or colloquial settings. We incorporated domain-specific data for each language to support the OCR system in specialized fields or use cases, such as legal, IT, medical, engineering, or technical contexts. This adaptation allows the model to recognize and interpret domain-specific vocabulary and jargon more accurately. In order to allow for further expandability, a specific dataset was designed to allow for easy integration of additional languages or new data samples in the future or to be ported to a HPC environment. This facilitates the ongoing improvement and expansion of the OCR system to cater to new requirements and evolving language trends.
# A Trusted Routing Scheme Using Blockchain and Reinforcement Learning for Wireless Sensor Networks
## 4 Experimental Analysis and Evaluation
### Efficiency
#### 4.3.2 Token Transaction Energy Consumption  
In Ethereum networks, \"gas\" is a special unit used to measure how much \"work\" an action or a series of actions of a miner has. It is determined by the number of computer instructions operated by the Ethereum transaction (e.g., the length of the code in the smart contract), and the gas fluctuation does not change much. For example, to calculate a Keccak256 encryption hash value, every time computing the hash will need 30 gas. Ethereum platform trading or contract execution of every operation needs a certain amount of gas, and the more computational resources operation we need, the more gas costs. Then the gas will be converted into corresponding ether currency to pay the blockchain miner. We take the gas consumption as the main evaluation index of the system energy consumption and the experimental results are shown below.  
As can be seen from the experimental results in Figure 9, the gas consumption of the average transaction is very stable as the arrival rate \(\lambda\) increases, and since the computing resources required are the same that the consumption of the two systems is approximately equal. With the increase of the arrival rate, the average token transaction gas consumption of the two blockchain systems was finally stable around 35,660 gas which cost only 0.0007132 ether (\(\approx\)0.0613 USD) at the gas price of 0.02 ether per million gas. In private Ethereum networks, the economic costs will be less and such a consumption tradeoff is small and acceptable.  
Figure 8: Average transaction latency of proof of authority (PoA) and proof of work (PoW) blockchain systems.  
Figure 9: Average transaction consumption of PoA and PoW blockchain systems.
# Yeast-Based Magnetic Biocomposite for Efficient Sorption of Organic Pollutants
## 1 Introduction
Biological methods are characterized by a diversity of biological materials. Some fungi, bacteria, and algae are used. A biosorption process can also be employed, wherein the microorganisms utilized possess a specific sorption surface area and the capability to absorb dyes without altering the chemical structure. To observe the good effectiveness of dye removal using biological methods and to increase its efficiency, it is necessary to select microorganisms that have a high affinity for the class of dyes being removed [12]. [PERSON] et al. reported that the removal efficiency of methylene blue using _Bacillus subtilis_ could reach 91.68% [13]. Removing many of the dyes present in water using microorganisms is a cost-effective and environmentally friendly approach. Microbiological processes in free-cell cells are slow, and the use of free cells in the purification of pollutants on an industrial scale is limited [14]. To overcome these drawbacks, microorganisms can be immobilized on biochar enriched with magnetic particles and used to remove complex, hazardous organic substances on an industrial scale. In this research, the process of removing methylene blue from the liquid phase using a magnetic bioccomposite was carried out. The bioccomposite was obtained by incorporating magnetite particles into biochar obtained from dried lotus pods and then immobilizing _Yarrowia lipolytica_ yeast on the biochar thus obtained. This yeast has been successfully used in the removal process of bromocresol purple, safranin, bromothymol blue, and phenol red [15]. In addition, this species of yeast is used in the bioremediation of soil pollution, for the disposal of oil and fish residues, and in soil fertilization (due to its ability to stimulate the germination of cereal grains) [16]. Giving magnetic properties to the bioccomposite makes the process of removing the sorbent from the liquid phase after the process much easier, because it is enough to use an external source of magnetic field, which eliminates the required complex separation process, such as filtration. The combination of all common advantages of the individual components of the bioccomposite reduces the risk of agglomeration of magnetic particles by immobilizing them on the biochar, and the use of yeast cells enhances the effect of the biocomposite through the use of the bioremediation process. Research on the removal of methylene blue with the use of biocomposite was carried out in a periodic system. The impact of various factors, such as temperature, process time, and initial dye concentration, was investigated. The obtained results allowed for the assessment of adsorption capacity, identification of kinetic and equilibrium models, and thermodynamic analysis.