esa-sceva/satcom-chunk-collection huggingface dataset:
# First Retrieval of Sea Surface Currents Using L-Band SAR in Satellite Formation
## 1 Introduction
Therefore, it is challenging to remove the cross-track baseline phase component solely based on the satellite's onboard navigation system parameters. In response to the characteristics of LuTan-1 distributed InSAR system, this study proposes an easily implementable two-step strategy. The key aspect of this approach is the use of a parameterized model for baseline error correction, which provides a clear physical interpretation compared to the commonly used polynomial fitting methods. This model enables the complete removal of phase components induced by an across-track baseline, thereby facilitating high-accuracy ocean current inversion. For the first time, based on \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Satellite Platform** & \begin{tabular}{c} **Frequency** \\ **Band** \\ \end{tabular} & \
\begin{tabular}{c} **AT** \\ **Baseline** \\ **Length** \\ \end{tabular} &
\begin{tabular}{c} **Orbit** \\ **Altitude** \\ \end{tabular} & **Accuracy @ Grid Size** \\ \hline SRTM [8; 9; 10; 11; 12] & X & 7 m & \(\sim\)233 km & 0.2 m/s @ 1 km\({}^{2}\) \\ TerraSAR-X [6; 13; 14] & X & 1.15 m & \(\sim\)514 km & 0.1 m/s @ 1 km\({}^{2}\) \\ RADARSAT-2 [15; 16] & C & 3.75 m & \(\sim\)798 km & 0.1 m/s @ 800 m\({}^{2}\) \\ Gaofen-3 [17] & C & 3.75 m & \(\sim\)755 km & 0.2 m/s @ 1 km\({}^{2}\) \\ TerraSAR-X/TanDEM-X [18; 19; 20] & X & 20\(\sim\)30 m & \(\sim\)514 km & 0.1 m/s @ 33 m\({}^{2}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Spaceborne ATI platforms and their specifications. LuTan-1, the inversion of sea surface currents was implemented in this study using the L-band satellite formation ATI technique, and its feasibility was evaluated. The remainder of this report is organized as follows: Section 2 presents the fundamental principles of InSAR measurements. Section 3 provides an overview of the experimental datasets, including the LuTan-1 satellite data and the reference data. Sections 4 and 5 describe the data processing procedure and retrieved results, respectively. Finally, the main conclusions are summarized in Section 6.
## 5 Recent Experiments
### Relation between the Enthalpies of Relaxation, Crystallization and Melting  
According to the general IT approach discussed above (Section 2), the interstitial-type defects in glass are inherited from the melt. Provided that the melt quenching rate is big enough, one can expect that the defect concentrations in the glass and melt are nearly equal, \(c_{glass}\approx c_{melt}\). The quantity \(c_{glass}\) determines the whole excess heat content (enthalpy) of the glass. Subsequent structural relaxation below \(T_{g}\) leads to a decrease of this concentration by \(\Delta c_{rel}\) that results in a growth of the shear modulus from \(G\) up to \(G_{rel}=G\ exp(\alpha\beta\Delta c_{rel})\) and corresponding release of the enthalpy \(\Delta H_{rel}\). Upon crystallization, the remaining defect concentration \(c_{melt}-\Delta c_{rel}\approx c_{cryst}\) drops down to zero (the defects disappear), the shear modulus increases up to its value \(\mu\) in the crystalline state with simultaneous release of the enthalpy \(\Delta H_{cryst}\). The whole heat release of the initial glass after  
Figure 7: Dependence of the relative density change on the quantity \(ln(G/G_{0})\), where \(G_{0}\) is the initial room-temperature shear modulus and \(G\) is the room-temperature shear modulus after annealing of bulk glassy \(Pd_{40}Cu_{30}Ni_{10}P_{20}\) at \(T=533\) K [57]. With permission from Elsevier, 2019.  
crystallization is then given by Equation (5), where \(\Delta U\approx\Delta H_{crystal}\), as discussed above (Section 3.5). Since the defect concentration quenched-in from the melt is \(c_{melt}\approx\Delta c_{rel}+c_{crystal}\), the heat absorbed upon melting should be approximately equal to the total heat release upon structural relaxation and crystallization, i.e., in terms of the corresponding enthalpy changes,  
\[\Delta H_{melt}\approx-\left(\Delta H_{crystal}+\Delta H_{rel}\right). \tag{13}\]  
The result of a specially designed experiment [64] aimed at the verification of this relationship is reproduced in Figure 8, which shows that the data taken on eleven Zr-, Pd- and La-based MGs can be approximated by a straight line with the unity slope. Thus, the relationship in Equation (13) is indeed valid within the experimental error (about 10%) confirming the idea on a connection between the defects occurring upon melting of the maternal crystal and those disappearing upon structural relaxation and crystallization of the glass.
## 4 Major Worldwide Cyberattacks Against Energy Systems
### Iran Nuclear Power Plant  
The Iranian authorities acknowledged that the Natanz nuclear power station had been targeted in 2011. This complex attack was accomplished by a malicious code called Stuxnet. PLCs, which are commonly used to automate business operations and power systems, were the main target of this sophisticated computer malware. Stuxnet is a unique type of malware since it is the most intricate, sophisticated, and potent malware to date. It was created to attack certain SCADA systems utilizing a number of operating system flaws, and as a result, it destroyed more than a thousand Iranian nuclear centrifuges. The attack's primary goal was to shorten the lifetime of centrifuges in order to eliminate Iran's nuclear program. Given how destructive a cyber weapon can be, this attack on Iran's nuclear power plants highlighted the significance of cybersecurity. It established itself as the first malware capable of directly harming a crucial energy infrastructure through the manipulation of control systems [70].  
The cyberattack was accomplished on the physical layer of the plant's control system through manipulating the centrifuge rotors' weaknesses and changing their speed and pressure. It was carried out using zero-day exploits and was physically delivered by a human using a USB storage device. The sophisticated level of the attack and a thorough investigation has led to the assumption that it was sponsored by nation-state hackers from the US and Israel in order to limit Iran's nuclear program. At the early stages, attackers infected Iranian critical infrastructure management facilities with the Stuxnet, which gathered real-time data from industrial systems. Later, they made the uranium centrifuges spin erratically and severely disrupt the entire plant electrical grid. As a result, centrifuges used to refine nuclear material were physically destroyed due to the rotors' overspinning and increase in pressure [65].
# Monitoring the Health and Residence Conditions of Elderly People, Using LoRa and The Things Network
## 5 Discussion and Results
### Predictive Model  
The WEKA software [40] was used to create the predictive model for detecting user position, including falls. This software was used to develop predictive models, being relatively easy, intuitive to use, and proven to be robust and reliable in determining predictive models, using data mining.  
The algorithm that best fit the study's objectives was the J48 (J48 is an open-source Java implementation of the C4.5), an algorithm of decision trees. The data obtained directly from the accelerometer represent integer values between a maximum (positive) and a minimum (negative) value for the x, y, and z axes, which generally require prior calibration as explained previously. However, the CayenneLPP format present in the TTN uses these values divided by one thousand. Therefore, in terms of database data representation, it is performed on the values obtained by TTN. Concerning the obtained values and because the decision process is carried out on the integer values processed in the MCU ESP32, the predictive model is received on this order of magnitude and not on the values divided by one thousand. The list of data prepared for the creation of the model is shown in Figure 8.  
For creating the training model, 2066 occurrences of readings of the direct accelerometer data applied in the prototype were used. Some rules were established initially, particularly the fact that the vertical position is represented by negative values close to the minimum and is naturally dependent on the position of the sensor in the electronic circuit.  
The application of algorithm J48 after parameterization to maximize effectiveness produced the following decision tree model (Figure 9).  
Figure 8: Data fields definition for test on the WEKA model.  
was 50% (Figure 10) with an accuracy of 99.73%, which is very relevant from the point of view of benchmarking and validating the model.  
Another tool that allows us to assess and validate the model is the confusion matrix (Figure 11).  
The confusion matrix shows that all expected normal (vertical) position occurrences were correctly classified, with only three cases incorrectly classified, which is not very significant. Thus, it can be said that the model is quite well adjusted to reality. Later, the decision tree model was applied to a test group, with the unknown classification variable (represented by the symbol \"7\" in Figure 12), and very consistent results were obtained.  
Figure 11: Confusion matrix.  
Figure 10: Statistical and precision analysis of the model.
## 2 Finite Element Modeling and Verification
### Bridge Section  
CSlbridge commercial software was applied to determine the responses of a skewed bridge subjected to vehicle loads. This software benefits from a vehicle load wizard that automatically draws an influence line along the path of a moving vehicle. This allows the maximum response and critical position of the vehicle to be determined conventionally.  
In order to investigate the capacity of bridge components under vehicle loads, only the superstructure was modeled, neglecting the effect of the bending [14; 27]. The three-dimensional (3D) finite element (FE) model of the superstructure consisted of a four-node shell element with six degrees of freedom (DOF) at each node. The effects of steel reinforcing and cracking of the RC slab were neglected. Longitudinal and transverse girders were modeled by means of 3D frame elements. The connection between the frame elements and the concrete slabs that they were supporting (shell elements) was provided automatically by the body constraint, vertical rigid links, defined in the CSIbridge software. Due to this assumption, no relative displacements and rotations were allowed between corresponding nodes [28].  
The X-type intermediate diaphragms (bracing system) were modeled using four-node shell elements spaced at a distance at 7.5 m from each other. Double L-shaped angular profile brace members were described by means of frame elements hinged at the ends. The parapets were modeled as a single frame element with the connecting nodes of the parapets located at the centroid of the barrier section. The connection between the composite deck and the parapets utilized a series of rigid links to consider the contribution of parapet's stiffness to the structural behavior [29].  
The sizes of the mesh elements in the finite element modeling were determined based on the analysis efficiency, with a good expectation ratio for all elements. Simple (pin) bearings that could rotate but were fixed against translational moments in all directions were used to model the boundary conditions at the first abutment, while a roller bearing was applied to represent the end abutment and piers, where only vertical transitional movement was restricted [1; 19]. A typical model of a skewed prototype bridge is shown in Figure 2.
## 2 Materials and Methods  
### Contrast Discrimination of Low-Spatial-Frequency Illusions  
The experimental task was a contrast discrimination of low-spatial-frequency (LSF) illusions (Figure S1). The illusions were flickering sinusoidal gratings with a spatial frequency of two cycles per degree, (2 cpd) and a high temporal frequency of counter-phase flicker of 15 Hz. The 'frequency-doubling' illusion effect, where a low-spatial-frequency sinusoidal grating appears to have twice its actual spatial frequency, arises when the grating is counter-phase flickered at a high temporal frequency. The experimental task investigated how the perceived spatial frequency of sinusoidal gratings changes when presented at two different contrast levels. The detection threshold was determined in a previous psychophysical procedure with a two-alternative forced-choice design [16; 17; 18]. The perceived contrasts of low-spatial-frequency (LSF) illusions were evaluated using stimuli presented at six and twelve times the respective detection threshold. The low- and high-contrast conditions of the discrimination task were presented in 40 realizations (20 realizations per condition) in a pseudorandomized sequence with an interstimulus interval of 1.5-3.5 s. These stimuli maximally activate magnocellular cells [19; 20]. Each realization begins with a fixation white cross for 100 ms on a gray background. After 200 ms, the illusion appears for 200 ms in the center of a square noise field (11 cm \(\times\) 11 cm) on a screen [14] (60 Hz refresh rate, pixels of 1920 \(\times\) 1080), located at a distance of 210 cm. The child discriminates the two contrast illusions by pressing a button with the left hand for a low-contrast and with the right hand for a high-contrast illusion. A short beep signaled the end of each realization. Correct responses and corresponding reaction times were included in the statistics, excluding reaction times less than 0.100 s and greater than 1.5 s as outliers. The numbers of correct trials for each condition were 525 for controls and 772 for children with DD in the LSF illusion.
# The Role of PET and SPECT Imaging in Prostate Cancer Targeted Alpha Therapy: When and How?
## 2 Molecular and Metabolic Imaging with PET and SPECT Technology
### Technologic Progress  
The use of WB-SPECT/CT has recently been introduced [26], in which the precision of the CT is added to the function of the SPECT [27; 28]. In recent years, digital PET has been introduced through the implementation of silicon photomultipliers (SiMP)-based detectors [29]. This innovative PET detection technology ensures significant improvements over analog technology in terms of better sensitivity and increased spatial and contrast resolution [30; 31]. All this technological progress allows for ever more personalized medicine.
## 2 Materials and Method  
Because the state of research concerning studies comparing several stimulus presentations and the associated visual search strategies or eye movements is low and inconsistent, neither a systematic review nor a theoretical, qualitative meta-synthesis was implemented [22]. The literature search was conducted and documented based on the PRISMA guidelines using a narrative approach [23] without quantitative analysis. The review overviews the differences between stimulus presentation types (in situ, video-based, and VR) when examining eye movements (via eye-tracking).  
Studies published from January 1990 up to September 2020 were searched in several ways. First, we searched the PubMed, ScienceDirect (Web of Science), IEEE Xplore, and SURF (national database) databases using relevant keywords in titles or abstracts of English-language journals. The search was restricted to the period from 1990 because of technical standards of eye-tracking equipment. The following keywords were used for literature search: (a) for perception: perceptual expertise, visual search, gaze behavior, eye movements, eye-tracking, and (b) for stimulus presentation and test design: test design, in-situ, VR, video presentation, simulation, visual cues, task specificity, task constraint, response. Furthermore, we searched on the website of relevant venues such as ETRA and identified articles' references. Studies were included if they compared different stimulus presentations, gaze behavior, or the search strategy was recorded (except the study with implementing VR) and if the article was written in English.
## 4 Design of a Reinforced-Concrete Conical Foundation
### Settlement Estimation  
Elastic settlement \(s\) in the case of saturated clayey soils:  
\[s=\frac{q\cdot B\cdot\left(1-v^{2}\right)\cdot I_{B}}{E} \tag{8}\]  
\(s\)--elastic settlement of the foundation (m or mm);  
\(q\)--uniform applied pressure/load on the foundation (kPa or N/m\({}^{2}\));  
\(B\)--width (or diameter) of the foundation in the direction of loading (m);  
\(\
u\)--[PERSON]'s ratio of the soil (dimensionless);  
\(E\)--[PERSON]'s modulus (modulus of elasticity) of the soil (kPa or N/m\({}^{2}\));  
\(I_{B}\)--influence factor (dimensionless), which depends on the shape and rigidity of the foundation, embedment depth, and type of load (values typically range from 0.8 to 1.2 for surface footings).  
\[s=\frac{312.3\cdot 0.85\cdot\left(1-0.3^{2}\right)\cdot 0.85}{21,800}=0.00944\text { m}=9.44\text{ mm}\]  
The following assumptions were made in the calculation: homogeneous, linearly elastic and isotropic soil; the foundation is flexible and round; the load is applied centrally and vertically; there are no time-dependent effects (i.e., it is instantaneous).  
Consolidation Settlement \(s_{c}\):  
\[s_{c}=\frac{C_{c}\cdot H}{1+e_{0}}\cdot log_{10}\frac{(\sigma_{0}+\Delta\sigma )}{\sigma_{0}} \tag{9}\]  
\(s_{c}\)--primary consolidation settlement (m or mm);  
\(C_{c}\)--compression index (dimensionless), obtained from oedometer tests;  
\(H\)--thickness of the compressible clay layer (m);  
\(e_{0}\)--initial void ratio of the soil (dimensionless);  
\(\sigma_{0}\)--initial effective vertical stress in the soil layer before loading (kPa);  
\(\Delta\sigma\)--increase in vertical stress, due to the applied load (kPa);  
\[s_{c}=\frac{0.05\cdot 1.2}{1+0.55}\cdot log_{10}\frac{(12.72+312.3)}{12.72}=0.0546 \text{ m}=54.6\text{ mm}\]  
Then, the total settlement would be 64 mm.  
It is assumed that consolidation occurs mostly under the cone-top, and 1.2 m (the same as the pile shaft length) was used as an approximation of this compressible zone beneath the loaded base--not the entire pile length. This is because the cone-top pile base sits at \(\approx\)1.61 m depth. The load is transferred downward, so stress dissipates mainly below the cone. The vertical extent of the pressure bulb under the base is the depth of soil significantly affected by the load. For shallow foundations or pile tips, this zone is roughly \(H\) = \(B\dots 2B\), where B is a cone base diameter \(\approx\) 0.85 m at the intersection with the ground. Using a vertical-stress distribution model (like Boussinesq or 2:1 spread), stress becomes negligible at 1.5 \(\times\) B (\(\approx\)1.2-1.3 m) below the base.  
The vertical load of 177.55 kN acts on the upper inverted conical base, transferring stress to the surrounding soil. The load spreads along the side surface of the cone and the pile shaft, creating both side friction resistance and a downward base pressure. The applied vertical stress does not exceed the ultimate strength of the soil around the cone, so extrusion or local failure is excluded.
## 5 Performance Analysis
### Summary of the Analysis  
Throughout the extensive analysis results, asynchronous transmission on STR outperformed other DCF schemes of course. This is because the asynchronous transmission on STR could operate independently on each link, which made better use of time resources. When it came to the non-STR case, the throughput of MLA-L generally exceeded the throughputs of other DCFs. Since MLD's attempts to access a channel could increase the congestion of all links, it seems reasonable to reduce MLD's attempts to access a channel through MLA-L.  
Specifically, the advantages and disadvantages of each synchronous multi-link DCFs could be identified. RTS/CTS exchange could provide single-link devices with robustness against MLD's aggressive channel access with a smaller contention window, so channel access for MLDs in an aggressive manner, i.e., MLA-S, was more efficient in terms of network throughput without reducing the single-link devices' throughput. However, there is concern that MLDs adopting MLA-S could be over-prioritized. The SLA method performed moderate throughput and fairness between MLDs and single-link devices among the specified DCFs without modifying the existing IEEE 802.11 channel access method. MLA-L had the advantage of relatively high throughput when the number of terminals was large and RTS/CTS exchange was off. Furthermore, single-link devices could exhibit comparable performance to MLDs. However, overall throughput was worse than any other competitive schemes. For MLA-A, it exhibited better performance regardless of the RTS/CTS exchange, especially when the PPDU duration was long. Recalling that the length of the PPDU was always the maximum value with the help of frame aggregation, MLA-A could exhibit good throughput performance, particularly in saturation conditions.
# Communication System Based on Magnetic Coils for Underwater Vehicles
## 1 Introduction
### Radio Frequency Communication  
This technology is intended for communication and data transmission over long distances and is commonly used in telephones, radios, televisions, etc. These communication systems use electromagnetic waves. However, seawater has a strong conductivity (4 S/m on average) that increases especially with salinity. This is reflected in a greater attenuation(\(\sim\)1 dB/m), which causes a shorter range and significantly reduces the usefulness of underwater radio frequency communications [7].  
An example of the application of this type of technology is low-frequency RFID (radio frequency identification) systems (120-134.2 kHz). These can be used in commercial devices for the identification and monitoring of aquatic species and has been particularly tested in salmon [8]. Another application is the use of global positioning system (GPS) and satellite communications, which have been used to follow the trajectory of marine species that travel long distances, such as dolphins, turtles, and whales. However, due to the great attenuation of electromagnetic signals, the system is only able to operate when the species is on the surface [9].
# A New Engine Fault Diagnosis Method Based on Multi-Sensor Data Fusion
## 3 The Proposed Method for Fault Diagnosis
### BPA Determination  
The determination of BPA is a key step in the application of D-S evidence theory. In the application of data fusion based on D-S evidence theory, the BPAs generated from different attributes will be combined to make a decision. While how to determine BPA from multi-sensor data fusion system is still an open issue, much research has been carried out [53; 73]. The BPA determination method in [53] utilized the relationship between test data and Gaussian distribution model generated by training data. However, the method of determining BPA with single measurement values can not cover the fuzziness of sensors in complex working environments. Taking this fact into consideration, a BPA determination method based on multiple measurements value is proposed in this section.  
Assuming the equipment in Figure 1 may have \(M\) faults occur, a total of \(N\) (\(N\)\(>\)\(L\)) attributes are extracted from \(L\) sensors. The frame of discernment should be \(\Theta=\left\{F_{1},F_{2},\ldots F_{i},\ldots,F_{M}\right\}\). For a certain attribute \(k\) (\(k\) = 1, 2,...,\(N\)), the test model under attribute \(k\) is put into its corresponding \(M\) fault models under attribute \(k\) to determine \(BPA_{k}\).  
Let \(\mu_{F_{i}}(x)\), \(\bar{X_{i}}\), \(\sigma_{i}\) be the function curve, mean value, standard deviation of generated model of fault \(F_{i}\) (\(i\) = 1, 2, 3,..., \(M\)) under attribute \(k\), respectively. Let \(\mu_{T}(x)\), \(\bar{X_{T}}\), \(\sigma_{T}\) be the function curve, mean value and standard deviation of generated model using observation under attribute \(k\), respectively. The \(BPA_{k}\) calculation procedures are as the following: the proposition support degree calculation method is given in Sections 3.3.1-3.3.3. \(BPA_{k}\) is obtained by normalizing all obtained support degrees to propositions, which is shown in Section 3.3.4.