esa-sceva/satcom-chunk-collection huggingface dataset:
# Methodology for Conceptual Navigational 3D Chart Assessment Based on Eye Tracking Measures
## 2 Materials and Methods
### Data Collection and Processing  
The eye-tracking experiments were conducted in a controlled laboratory environment using a Tobii Pro X3-120 eye-tracker, a commercial device with a 120 Hz sampling rate, manufactured by Tobii AB (Stockholm, Sweden). The tracker was positioned at the bottom of a 15-inch monitor with a Full HD resolution of 1920 \(\times\) 1080 pixels, where both stimuli and questionnaires were presented. Participants were seated approximately 60 cm from the screen. A standard 9-point calibration procedure was performed before each session to ensure accurate gaze tracking. All participants viewed the map scenarios under the same lighting and display conditions. Data processing and visualisation, including real-time generation of heatmaps and the application of Areas of Interest (AOIs), were carried out using iMotion software (version 10.1). Fixation and saccade data were recorded throughout the tasks and processed using the I-VT (Identification by Velocity Threshold) filter [60]. Heatmaps were generated separately for the 2D and 3D groups by averaging fixation distributions across all 15 participants in each group. These heatmaps were based on cumulative dwell time and fixation density per grid cell and visualised using a quartile-based colour scale ranging from green (low attention) to red (high attention) [61]. Heatmaps were exported in PNG format.  
AOIs were manually defined as polygons covering key regions of the maps, including Pytanie (instructional text in the form of question), Legenda (simply map legend), Mapa  
\begin{table}
\begin{tabular}{c c c} \hline
**Category** & **Count** & **Percent [\%]** \\ \hline Gender & & \\ Female & 11 & 37 \\ Male & 19 & 63 \\ Sum & 30 & 100 \\ \hline Experience & & \\ Experienced & 7 & 23 \\ Inexperienced & 23 & 77 \\ Sum & 30 & 100 \\ \hline Map & & \\
2D: & 15 & 50 \\ Female & 4 & 27 \\ Male & 11 & 73 \\ Experienced & 4 & 27 \\ Inexperienced & 11 & 73 \\
3D: & 15 & 50 \\ Female & 7 & 47 \\ Male & 8 & 53 \\ Experienced & 3 & 20 \\ Inexperienced & 12 & 80 \\ Sum & 30 & 100 \\ \hline \end{tabular}
\end{table}
Table 1: Characteristics of the testers who took part in the experiment.  
(main area of cartographic content), and Obiekt (target object), as shown in Figure 8. The Obiekt AOI was specifically used to detect gaze directed at the correct object to be found in the task. All mouse clicks were registered during the experiment, and using screen coordinates, each click was verified to determine whether it fell within the Obiekt AOI. Identification time was calculated as the duration from stimulus onset to the participant's first correct click on the object of interest. All collected data--fixation events, saccade events, timestamps, and click coordinates--were exported as CSV files to allow for further calculations of indicators.
## 2 PV Cell and PSC Modeling  
### PV Cell Modeling  
A PV cell, as illustrated in Figure 1, is made of a combination of PV cells. Various models have been proposed for a PV cell based on the single-diode model. A mathematical single-diode model of the PV cell is defined as follows:  
The PV cell current based on the mentioned model is defined by [9; 10] as follows:  
\[\mathrm{I_{pv}}\ =\ \mathrm{I_{ph}}-\mathrm{I_{o}}\times\left(\exp(\frac{\mathrm{ q}(\mathrm{V_{pv}}+\mathrm{R_{s}}\mathrm{I_{pv}})}{\mathrm{akT}}-1)\right)-\frac{( \mathrm{V_{pv}}+\mathrm{R_{s}}\mathrm{I_{pv}})}{\mathrm{R_{sh}}} \tag{1}\]  
where \(\mathrm{R_{s}}\) and \(\mathrm{R_{sh}}\) represent the ohmic values of series and parallel resistors, \(\mathrm{I_{o}}\) indicates the saturation current of the diode, \(\mathrm{I_{ph}}\) represents the current source, \(\mathrm{I_{pv}}\) and \(\mathrm{V_{pv}}\) define the current and voltage of the PV cell, k represents the Boltzmann constant, and T refers to the temperature at \({}^{\circ}\)C.
## 3 Loss Calculation of IM Driven FESS
### Mechanical Losses
#### 3.3.3 Stray Losses  
Stray losses are caused by the magnetic flux leakages of an electrical machine and can be categorised as the stator and rotor stray losses. Due to very little changes in the magnetic flux distribution of the IM stator from no load to full load, stray load losses in the stator of the IM can be neglected. Stray losses in the rotor of IM is a function of the frequency and depends on the rotor slip. In a squirrel cage induction machine (SCIM) with small slip, rotor stray losses are very small and can be neglected [72]. However, during normal operation where the IM operates at full or partial load, these losses cannot be neglected and can be estimated using Equation (27) as recommended by IEEE standards for calculating stray losses in electrical machines [73].  
\[P_{stray}=0.005\frac{P_{g}^{2}}{P_{r}} \tag{27}\]  
where \(P_{g}\) is the generated power or output power of the machine and \(P_{r}\) is the rated power.
## 2 Materials and Methods
### System Architecture
#### 2.3.1 Mechanical Infrastructure and Transmission Subsystem  
The heart of the mechanical infrastructure is represented by a commercial aluminum guideline and a plate of the same material sliding on it. The chosen architecture ensures high reliability for such a core component of the system and also ensures an easy replacement in case of failure. In addition, a custom-designed aluminum framework is bolted to the plate over the guideline. It includes a damping system consisting of two opposed springs and supports for attaching the dummy. The latter is made of transparent polycarbonate, thus ensuring both robustness and lightness and also allowing players to see incoming kicks while remaining behind the goal. The choice of making the metal parts from aluminum is due to its excellent mechanical strength vs. the reduced overall weight.  
The transmission subsystem is made of the DC motor powered by two automotive lead-acid 12 V batteries, a gear wheel, a tension pulley, and a plastic belt reinforced with steel filaments. The belt must be properly tense; otherwise, the high torque of the DC motor could cause it to slide along the pulley, and perhaps permanent damage to the mechanical components. To this aim, an adjustable tension sheave is installed; this can be released with a dedicated secure handle, if necessary. This subsystem also includes two inductive sensors  
Figure 2: Joystick movement space representation for the third mode of functioning.  
mounted near its edges and an optical encoder used by the electronic subsystem to detect the end of stroke and to track the position of the dummy, respectively.  
A computer-made scale model of the entire mechanical infrastructure, mounted in a door (3 m large and 2 m tall), is shown in Figure 2(a). The semi-transparent plastic case for protecting any mechanical and electrical part from incoming kicks is also shown. The surface area of the dummy is comparable to that of a human body with slightly open arms. Figure 2(b) shows a detailed model of the transmission subsystem.
## 5 Medical Imaging-Based Kinematics
### Magnetic Resonance Imaging (MRI)
#### 5.2.1 Tissue Tagging  
This technique, first introduced by [PERSON] et al., in 1988, was specifically designed to quantitatively assess the transmural motion of the myocardium [176]. Image markers, or tags, are created by locally perturbing the magnetization of the tissue, either by selective radiofrequency saturation sequences or through modulation of the magnetization vector by gradient fields. Tags are created on a thin section orthogonal to the image plane at diastole, then followed by regular time-resolved imaging. Electrocardiographic gating is used to consistently apply the tagging radiofrequency at diastole. Early works reported decrement of tag resolution at systole as the magnetic saturation exponentially decays over time; nevertheless, this problem is palliated with the use of larger magnetization energy [177]. [PERSON] et al. showed that tag lines were still clearly identifiable at the end of the cardiac cycle on human hearts with a 7 T MRI scan [178]. Special radio-frequency sequences, such as spatial modulation of magnetization (SPAMM) and delays alternating with nutation for transient excitation (DANTE) [179, 180], allowed the creation of 2D orthogonal tagging grids that facilitate the kinematic analysis. Tag sizes can be only as small as the pixel-size resolution (>1 mm) with typical tag spacing of about 5 mm (Figure 8b). The technique allows for 25 to 30 images per cardiac cycle, requiring about 20 s of scan time per tagging sequence [170, 181]. Multiple studies on phantoms have shown this technique to be superior to US speckle-tracking in terms of accuracy and repeatability. Due to the spatial resolution limitations of this technique, it has only been successfully applied to study the kinematics of relatively thick tissues such as the myocardium, skeletal muscle, lung tissue, and the tongue [182].
# Multibeam Wideband Transmit Beamforming Using 2D Sparse FIR Trapezoidal Filters
### Advantages of an All-Digital Approach  
We can solve many such problems by adopting a fully digital transmit beamformer. In fully digital beamformers [26; 27; 28], beam personalities including main beams and null synthesis for each independent beam are achieved using discrete domain linear and time-invariant filtering methods implemented in real time on a fast digital signal processor (DSP). Multibeam combination is also achieved in the digital domain [29; 30]. A dedicated DAC is used for each transmit chain driving the PAs so that maximum flexibility and reconfigurability are obtained.
# Optimized Wireless Sensor Network Architecture for AI-Based Wildfire Detection in Remote Areas
## 3 WSN Architecture
### Star/Circle Topology  
In the proposed WSN topology, nodes are arranged in concentric flat or pyramidal circles based on forest type (flat or mountainous), as illustrated in Figure 1. The network design considers forest density, terrain, and the use of the Zigbee protocol for node communication. Operating at 2.4 GHz, Zigbee may face interference from other wireless signals (e.g., Wi-Fi, Bluetooth), especially near urban areas. However, this is negligible in the targeted remote forests. Terrain features like hills, as well as weather conditions such as rain or fog, can further reduce signal range. Under optimal conditions, Zigbee can reach 50-100 m, but in dense vegetation, the range may drop to 10-20 m or less. These factors are accounted for in the WSN architecture and sensor node deployment.  
The WSN architecture (Figure 2) combines two topologies: star and circle. In star topology, a central sink node is surrounded by four sensing nodes aligned along its axes. Due to the distance exceeding their sensing range, these nodes cannot communicate directly with each other. Instead, they transmit data to the sink node upon detecting fire or act as intermediaries to relay data from nodes in the surrounding circular tiers.  
Figure 1: Deployment of WSN nodes in (**a**) mountainous and (**b**) flat forest scenarios.  
The circular tiers are centered around the sink node, with radii increasing by multiples of n \(\times\) r, where r is the effective sensing radius. Key nodes are placed along the axes at angles 0, \(\pi/2\), \(\pi\), and \(3\pi/2\) in each tier. The spacing between consecutive axis nodes equals the effective sensing radius, determined by forest type, density, and terrain. Within each tier, adjacent nodes are placed at distances less than or equal to r, ensuring reliable communication when needed.  
In non-dense forests, the distance between circular tiers may exceed the effective sensing radius. In this case, the system relays data between nodes along the same circle until it reaches an axis node, which then forwards it to the sink. In dense forests, tier spacing is reduced to within the maximum effective radius, enabling communication between adjacent tiers. This enables faster data transmission during fire spread and enhances responsiveness.
## 3 Results
### Differences Between BDS and GPS Position Time Series  
In order to recognize the systematic discrepancies between BDS and GPS positioning results, we present the mean and RMS of differences between BDS and GPS position time series. As an example, the mean of differences between BDS and GPS results for station YNSM is \(-0.6\), \(-1.0\), and \(-3.8\) mm for north, east, and up components, respectively. The corresponding RMS is 7.1, 8.5, and 19.4 mm, respectively. We present the summary of the mean and RMS from 44 position differential time series between BDS and GPS results in Table 2. The mean values are \(-0.8\), \(-1.5\), and \(-5.5\) mm for the north, east, and up components, respectively, and the corresponding RMS are 6.8, 7.3, and 21.7 mm, respectively. We estimated the seven parameters of coordinate transformation between BDS and GPS daily position time series by least square sense, and obtained daily seven transformation parameters. The magnitude of the mean of translation and rotation parameters is almost near zero, while the mean scale is 2.2 ppb (ppb equals \(10^{-9}\)), indicating the root cause of discrepancy between BDS and GPS results is the change of scale. The average RMS of BDS residual position time series, which is about 7 mm and 22 mm on horizontal and vertical components, respectively, are at the same level with the RMS of differential position time series. There are no systematic differences between BDS and GPS position time series.
###### Abstract  
As oil exploitation enters its middle and late stages, formation pressure drops, and crude oil degases. In production profile logging, the presence of the gas phase will affect the initial oil-water two-phase flowmeter's flow measurement results. In order to eliminate gas-phase interference and reduce measurement costs, we designed a downhole gas-liquid separator (DGLS) suitable for low flow, high water holdup, and high gas holdup. We based it on the phase isolation method. Using a combination of numerical simulation and fluid dynamic measurement experiments, we studied DGLS separation efficiency separately in the two cases of gas-water two-phase flow and oil-gas-water three-phase flow. Comparative analysis of the numerical simulation calculation and dynamic test results showed that: the VOF model constructed based on \(k-\varepsilon\) the equation is nearly identical to the dynamic test, and can be used to analyze DGLS separation efficiency; the numerical simulation results of the gas-water two-phase flow show that when the total flow rate is below 20 m\({}^{3}\)/d, the separation efficiency surpasses 90%. The oil-gas-water three-phase's numerical simulation results show that the oil phase influences separation efficiency. When the total flow rate is 20 m\({}^{3}\)/d-50 m\({}^{3}\)/d and gas holdup is low, the DGLS's separation efficiency can exceed 90%. Our experimental study on fluid dynamics measurement shows that the DGLS's applicable range is when the gas mass is 0 m\({}^{3}\)/d-15 m\({}^{3}\)/d, and the water holdup range is 50%-100%. The research presented in this article can provide a theoretical basis for the development and design of DGLSs.  
downhole gas-liquid separator (DGLS); gas-water two-phase flow; multiphase flow; separation efficiency +
Footnote †: journal: Applied Sciences
# Metabolic Potential of Halophilic Filamentous Fungi--Current Perspective
## 6 Industrial Applications of Halophilic Biocompounds
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Bioactivity** & **Halophilic Fungi** & **Compounds** & **Description** & **References** \\ \hline \multirow{6}{*}{_Aspergillus_ sp. nov. F1} & \multicolumn{2}{c}{Ergosterol} & \multirow{2}{*}{Potent cytotoxic activity to human tumor cell lines A549, Hela, BEL-7402, and RKO} & [115] \\ \cline{3-5}  & & Rosellichalasin E & & \\ \cline{3-5}  & \multicolumn{2}{c}{Cytochalasin E} & & \\ \cline{3-5}  & \multicolumn{2}{c}{SC2051} & \multirow{2}{*}{Inhibitory activity in the tyrosine kinase assay; inhibited HUVEC proliferation, migration, and tubule formation} & [117] \\ \cline{3-5}  & \multicolumn{2}{c}{Hypochromies B} & & \\ \cline{3-5}  & \multicolumn{2}{c}{New ergosterol derivative} & \multirow{2}{*}{Cytotoxicity against HL-60 and BEL-7402} & \multirow{2}{*}{[119]} \\ \cline{3-5}  & \multicolumn{2}{c}{3b-hydroxyergosta-8, 24(28)-dien-7-one} & & \\ \hline \multirow{6}{*}{_Apergillus floccolus_} & \multicolumn{2}{c}{Plectosphaeraic acid A, B} & \multirow{2}{*}{Inhibitory against indoleamine 2,3-dioxygenase (IDO)} & \multirow{2}{*}{[123]} \\ \cline{3-5}  & \multicolumn{2}{c}{} & & \\ \cline{3-5}  & \multicolumn{2}{c}{} & & \\ \end{tabular}
\end{table} 
Table 5: Cont. \begin{table}
\begin{tabular}{c c c c} \hline \hline  
Halophilic fungi can conduct decolorization of dyes and purification of colored effluent. Ligninolytic enzymes produced by marine-derived fungi (_Tinctoporellus_ sp. CBMAI 1061, _Marasniellus_ sp. CBMAI 1062, and _Peniophora_ sp. CBMAI 1063) were able to decolorize up to 100% Remazol Brilliant Blue R dye (RBBR) under both saline and non-saline conditions [50]. Extensive research on biofuels, where several processes are carried out in the presence of high concentrations of NaCl, has focused the attention of researchers on halophiles [70]. Extracellular \(\beta\)-glucosidase from _A. sydowii_ BTMFS 55 has been tested on different media for possible application in production of bioethanol, showing satisfactory results [74]. Biocompounds from halophilic fungi are promising for the pharmaceutical industry. Hydrophobins' ability to form amphipathic membranes might find applications in the pharmaceutical industry for hydrophobic drug formulation and delivery. They can replace synthetic surfactants, which are used to improve drugs solubility in an aqueous environment and which have been shown to be immunogenic in immunocompromised patients as well as to increase drug stabilization [95; 127]. Moreover, antimicrobial, anticancer, and antioxidant biological activities of secondary metabolites are expected to find applications as drugs in medicine [20]. Both melanin and MAAs are UV-absorbing compounds with antioxidant activities, and therefore, they could serve as sunscreen agents or potential anti-aging ingredients in cosmetics [52; 128]. They have been found in many halophilic fungi, especially the black yeast, such as _Hortaae werneckii_[37; 52].
# Correspondence between Multilevel Graph Partitions and Tree Decompositions
## 6 Conclusions  
We present a mapping between rooted tree decompositions and node-based multilevel graph partitions. This mapping is a bijection, if the tree decomposition fulfills some technicalities. Establishing this connection is the main contribution of our paper. Our insight allows translating results from tree decomposition research into the terminology of multilevel graph partitioning and vice versa. For example, in the PACE'2017 tree decomposition computation challenge [21], one of the top competitors [20] used our result to apply graph partitioning experience to compute tree decompositions. Our research can be used to compute small tree decompositions of large-scale graphs using graph partitioning methods. We hope that our results bring both research communities closer together.  
We have shown that there is one-to-one mapping between node-based multilevel partitions and tree decompositions. Beside node-based multilevel partitions, edge-based multilevel partitions also exist. A natural question is whether there also exists a one-to-one mapping between edge-based multilevel partitions and tree decompositions. Unfortunately, this is not the case. The proof consists of showing that there is no one-to-one mapping between edge- and node-based partitions. As there is a one-to-one mapping node-based multilevel partitions and tree decompositions, there cannot simultaneously exist a one-to-one mapping with edge-based multilevel partitions. An open question is whether a tree decomposition theory structure similar to tree decompositions exists that has a one-to-one mapping with an edge-based multilevel partition.  
**Supplementary Materials:** The following are available online at [[http://www.mdpi.com/1999-4893/12/9/198/sl](http://www.mdpi.com/1999-4893/12/9/198/sl)]([http://www.mdpi.com/1999-4893/12/9/198/sl](http://www.mdpi.com/1999-4893/12/9/198/sl)). Zip File S1: OpenStreetMap Germany graph in the format of the PACE tree decomposition challenge [21], lattice and tree decomposition in the format of the PACE tree decomposition computation challenge [21], latitude and longitude as binary files, license for the data and readme file explaining the data formats.  
**Author Contributions:** Conceptualization, M.H. and B.S.; software, B.S.; validation, B.S.; formal analysis, B.S.; investigation, B.S.; resources, B.S.; data curation, B.S.; writing--original draft preparation, B.S.; writing--review and editing, M.H. and B.S.; visualization, B.S.; and project administration, M.H. and B.S.  
**Funding:** This research was partially funded by the Deutsche Forschungsgemeinschaft (DFG) under grants WA654/19-2 and WA654/22-2. The APC was funded by the KIT-Publication Fund of the Karlsruhe Institute of Technology.  
**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
# An Analytical Survey of WSNs Integration with Cloud and Fog Computing
## 3 Related Work
A fog framework-based information obtaining an instrument, which highlights lightweight, high productivity, and constant strangely information separating calculation is proposed in [50]. Through community-oriented figuring of all WSN nodes, the approach empowers solid and proficient information securing even if there should arise an occurrence of information variation from the norm [51]. The FC layer in WSN is introduced as a response to the issues exhibited in the investigation. The temperature measurement database managed through Link Quality Routing Protocol (LQRP) is used which is based on Ad-hoc On-Demand Distance Vector (AODV) [52]. The work centers on demonstrating and investigating the association of the Fog paradigm with the plan of a CoT (Cloud of Things) foundation. The objective of the paper is to build a scientific model of three-level CoT to evaluate the relevance of the fog level with regards to the framework and to show that it is a key factor to meet the requests of time-limitation applications [53]. An adaptable processing framework that empowers more brilliant urban communities with mobile data through enormous information innovation is proposed in [54; 55]. An IoT framework and a door that enable applications to be sent nearer to the system edge and relocated to the cloud in light of the client's necessity are proposed in [55]. They focused on the identification of unanticipated sensor data collected by the various sensors or the surroundings during investigation in this paper. We offer a new method for automatically detecting anomalies in heterogeneous sensor networks that combine edge and cloud analysis of the data [56]. This topic is investigated in this work. We begin by defining the concept of scope in a multi-IoT scenario. Then, we present two formalizations of this concept that allow its values to be computed. After that, they go through two different ways and that scope can be used. Furthermore, they present a set of tests that are conducted to assess it; the final one compares range to dispersion degrees and impact degree, two characteristics that have previously been suggested in the research [57; 58]. The idea recommended in [59; 60] included the use of wireless sensors to detect the nearness of traffic close to any circle or common area and then made the traffic path easy and accessible. This development does not require any framework in vehicles so can be executed in a traffic system affordably and effectively in less time. A comparison of fog and CC is given in Table 2.