esa-sceva/satcom-chunk-collection huggingface dataset:
# Development of a Two-Dimensional Hybrid Sediment-Transport Model
## 3 Numerical Method
### Solution Procedure  
All discretized equations are solved by the BiCGSTAB(\(l\)) (biconjugate-gradient stabilized method) solver [52]. At each time step, the flow and the sediment transport are coupled in the following way: (1) the flow field is calculated first based on the current bed conditions (bed elevation and bed material composition); (2) then, the sediment transport is simulated using the calculated flow field; and (3) finally, the bed changes and the bed sorting are calculated and bed elevations and sediment compositions are updated.
## 4 Wireless Transmission in WBANs
### Physical (PHY) Layer and Medium Access Control (MAC) Layer
[97] proposed a frame structure model for a self-adaptive guard band protocol based on TDMA which synchronizes the sleeping state of the nodes and the coordinator to effectively reduce the energy consumption. [PERSON] et al. [98] proposed a MAC protocol based on channel-aware polling to optimize energy efficiency by adjusting the number of polling cycles in super frames to adapt to dynamic traffic requirements and channel fluctuations.
## 7 Mechanisms of PGPB (Plant Growth Promoting Bacteria) towards Salinity Tolerance  
The key mechanisms involved in PGPR (plant growth promotion rhizobacteria) salinity tolerance include specific membrane or cell wall structures, draining ions out of the cell through salt efflux, or modification of their intracellular environment through accumulation of nontoxic organic osmolytes, and adapting enzymes and proteins to function under high solute ion concentrations [25]. The ability of PGPB to improve crop yields during salt stress includes many direct and indirect pathways such as ferrous iron minerals and inorganic phosphate solubilization, exopolysaccharides and biofilms synthesis [166], production of phytohormes [167], increased ACC (1-aminocyclopropane-1-carboxylate) deaminase activity [168], and nitrogen fixation [169]. The Figure 2 shows PGPB (Plant growth promoting bacteria) salinity resistance strategies and mechanisms of plant growth improvement under salt stress. PGP bacteria may survive high salinity via three main mechanisms (pumping out the cell, intracellular adaptation processes, and cell wall construction). These bacteria stimulate plant growth during salt stress by means of several mechanisms including  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Crops** & **PGPB** & **NaCl (mM)** & **Beneficial Effects** & **Reference** \\ \hline \multirow{2}{*}{Lettuce} & _Azotobacter dracoaccount_ & 50 and 100 & Enhanced the radiole lengths and plumule of germinated seeds & [160] \\ \cline{2-4}  & _Pseudomonas fluorescens_ & & & \\  & _CECT 378T_ & & & \\ \hline \multirow{2}{*}{Strawberry} & _Bacillus_ sp. & 35 & Ameliated fruit productivity, leaf water amount, ionic constitution, and membrane permeability & [162] \\ \cline{2-4}  & _Serratia_ sp. _SL-12_ & 150–200 & Improvement in plant increase, as determined by factors like root/shoot length, dry/fresh weight, and augmentation of photosynthetic pigment & [163] \\ \hline \multirow{2}{*}{Maize} & _Trichoderma_ & & & \\  & _harzamtum Th-6_ & 50–150 & Improves water composition and stomatal conductance, elevated pigment amounts, and increases photosynthetic performance & [164] \\ \hline \multirow{2}{*}{Barley} & _Azospirillum_ & & & \\  & _busiliense NO40_ & 250 and 350 & Mitigate photosynthetic pigments in the roots and shoots, photosynthetic effectiveness, transpiration level, stomatal conductance, agglomeration of Mg, P, K, Fe, and Ca & [165] \\ \hline \hline \end{tabular}
\end{table}
Table 1: Various roles of PGPB (Plant growth promoting bacteria) in enhancing yield and growth of different plants/crops under salt stress.  
phytohormones production, amelioration of nutrients uptake, ACC deaminase, P solubilization, EPS synthesis, biofilms formation, and N\({}_{2}\) fixation.
# A Blockchain and IoT-Enabled Framework for Ethical and Secure Coffee Supply Chains
## 3 Methodology
### System Architecture and Dataset Design for IoT-Supported Blockchain Integration  
In our proposed framework, illustrated in Figure 2, Internet of Things (IoT) technologies are integrated into the coffee supply chain architecture to enable real-world data acquisition and blockchain-based smart contract execution. To maintain our experimental focus on blockchain system performance and functionality, the IoT device data streams were simulated through the creation of structured datasets. We manually generated syn  
\begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline
**Feature** & **Our Work** & **Paper 1**[29] & **Paper 2**[20] & **Paper 3**[26] & **Paper 4**[26] & **Paper 5**[31] & **Paper 6**[4] \\ \hline
**Year** & **2025** & **2018** & **2019** & **2021** & **2022** & **2022** & **2023** \\ \hline Blockchain & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) \\ \hline Dual-Layer Architecture & \(\surd\) & \(\times\) & \(\times\) & \(\times\) & \(\times\) & \(\times\) & \(\times\) \\ \hline IoT Integration & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\times\) & \(\times\) & \(\times\) \\ \hline Environmental Sensors & \(\surd\) & \(\times\) & \(\surd\) & \(\times\) & \(\surd\) & \(\times\) & \(\times\) \\ \hline Origin Authentication & \(\surd\) & \(\times\) & \(\surd\) & \(\times\) & \(\times\) & \(\times\) & \(\times\) \\ \hline Process Verification & \(\surd\) & \(\times\) & \(\times\) & \(\times\) & \(\times\) & \(\times\) & \(\times\) \\ \hline Advanced Smart Contracts & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) \\ \hline Mobile Quality Assessment & \(\surd\) & \(\surd\) & \(\times\) & \(\times\) & \(\times\) & \(\times\) & \(\times\) \\ \hline Transaction Cost Analysis & \(\surd\) & \(\times\) & \(\times\) & \(\times\) & \(\times\) & \(\times\) & \(\times\) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparison of our work’s contribution with other recent works in similar fields.  
thetic datasets [32] to emulate realistic sensor outputs corresponding to RFID tagging [33], GPS tracking, weight measurements, environmental monitoring, and mobile-based validations, thereby effectively simulating an IoT environment without requiring physical device deployment. Each data entry was formatted to match the expected input conditions of the blockchain smart contracts and injected through Remix IDE [34] integrated with Metamask [35; 36] during system testing. This approach ensured that the blockchain transactions were validated under realistic operational scenarios while laying a detailed foundation for future experimental implementations. In subsequent work, IoT simulation platforms such as Node-RED [37] can be coupled with custom data generation scripts and used to further automate and enrich the sensor-to-blockchain data pipeline.
## 3 Results and Discussion
### Surface Roughness and Topography
In addition, the increase of MRR was also due to the spalling of the Al\({}_{2}\)O\({}_{3}\) ceramic. The reason is that the brittle materials are removed by plastic deformation and spalling during the grinding process, and the MRR associated with spalling is an order of magnitude greater than that for plastic deformation [31]. No fusing structure like irregular and spherical droplets was present on the machined surface, which means that the material removed by diamond wire sawing combined with oil film-assisted ECDM was due to mechanical failure instead of melting. \begin{table}
\begin{tabular}{c c c c c c c} \hline
**Measurement** & **Voltage** & \begin{tabular}{c} **First** \\ **Measurement** \\ \end{tabular}  & \begin{tabular}{c} **Second** \\ **Measurement** \\ \end{tabular}  & \begin{tabular}{c} **Third** \\ **Measurement** \\ \end{tabular}  & \ \begin{tabular}{c} **Mean Value** \\ \end{tabular}  & \begin{tabular}{c} **Standard Error** \\ \end{tabular}  \\ \hline \multirow{4}{*}{Parallel} & 46 & 0.454 & 0.552 & 0.448 & 0.485 & 0.033711 \\  & 49 & 0.502 & 0.583 & 0.501 & 0.529 & 0.027168 \\  & 52 & 0.594 & 0.674 & 0.679 & 0.649 & 0.027538 \\  & 55 & 0.837 & 0.750 & 0.850 & 0.812 & 0.031392 \\  & 58 & 0.865 & 0.838 & 0.966 & 0.890 & 0.038954 \\ \hline \multirow{4}{*}{Perpendicular} & 46 & 0.756 & 0.681 & 0.760 & 0.732 & 0.025693 \\  & 49 & 0.714 & 0.802 & 0.714 & 0.743 & 0.029333 \\ \cline{1-1}  & 52 & 0.751 & 0.711 & 0.810 & 0.757 & 0.028754 \\ \cline{1-1}  & 55 & 0.869 & 0.869 & 0.950 & 0.896 & 0.027 Figure 8: SEM of machined surface by (**a**) diamond wire sawing, and (**b**) diamond wire sawing, combined with oil film-assisted ECDM (46 V). Figure 9: SEM of machined surfaces by (**a**) diamond wire sawing, and diamond wire sawing combined with oil film-assisted ECDM under DC voltages of (**b**) 49 V, (**c**) 55 V, and (**d**) 58 V.  
It is known that material removal of advanced ceramics is due to the combined action of melting, evaporation and spalling. Furthermore, in ceramic materials, thermal spalling is due to sudden changes in temperature that lead to rapid shrinkage and expansion of the material, resulting in thermal stress. This causes tensile and compressive stresses sufficient to cause the material to suddenly break, resulting in the material being removed in the form of flakes [32]. There is no micro crack on the machined surfaces when DC voltage is applied and diamond wire sawing is assisted by oil film, which is different from the machined surface by EDM. An SEM image at high magnitude was obtained to make sure that no micro crack is presented on the machined surface (Figure 10). The reason could be that the spark discharge energy is insufficient to melt the Al\({}_{2}\)O\({}_{3}\) ceramic. The stresses caused by the quick variation of temperature are not large enough to generate micro cracks on the machined surface.
## 3 Results and Discussion
### Gas Temperature  
Biomedical applications of CAP first utilized plasma at thermal equilibrium, which was based on thermal energy for tissue removal, disinfection, and cauterization of thermally stable biomedical instruments. However, it is not suitable for heat-sensitive substances such as living tissues, as cells cannot tolerate such high temperatures. Recent advances in novel plasma sources, which can generate transferred CAP under atmospheric pressure in an open space at nearly room temperature, have allowed direct contact between live human cells and plasma yet avoid thermal damage. Implementation of cold plasma is essential for biological or medical treatment (Figure 4a), as only plasma with a temperature slightly higher than the body temperature which can be utilized to avoid harm and distress to patients' cells. As shown in Figure 4b,c, an infrared (IR) camera was used to confirm that the gas temperature remained near room temperature after passing through an extended silicon tube. The thermal image data (Figure 4b,c) show that the temperature in the area of the transferred CAP remained under 30 \({}^{\circ}\)C during plasma treatment. For instance, a conventional argon-based CAP with a reported temperature of 35 \({}^{\circ}\)C to 40 \({}^{\circ}\)C was utilized for melanoma cells treatment [23]. A helium-based CAP with a temperature-controlled environment was also presented for melanoma treatment [24] although using argon ismore affordable than helium gas. On the other hand, as mentioned in the introduction, using argon gas leads to a heating problem that causes a relatively high gas temperature compared to the room temperature. The treated biological cells and tissue could be damaged by heating with a temperature around 40 \({}^{\circ}\)C although there is no specific threshold temperature for heating damage [31]. In our case, during the plasma treatment, as shown in Figure 4b, the thermal image presents a gas temperature less than 30 \({}^{\circ}\)C, which is much safer for avoiding possible heating damage to biological cells and tissue.
# Distributed Localization of Non-Cooperative Targets in Non-Coplanar Rendezvous Processes
## 5 Conclusions  
This paper investigates the distributed target localization problem during rapid uncoplanar rendezvous to a non-cooperative target. A three-line-of-sight cooperative localization scheme is proposed. A distributed consensus EKF algorithm based on CE is designed. The configuration during the approach process directly influences the performance of target position estimation, prompting improvements to the NSGA-III algorithm for optimizing the approach configuration. The proposed improved NSGA-III algorithm demonstrates a wider search space and faster convergence speeds compared to traditional algorithms, resulting in a solution set that is closer to the true Pareto front. Research has shown that system observability and localization accuracy are highly influenced by the configuration of the satellites, more precisely, the angle formed by the LOS. The article believes that when the angle between LOS approaches 180 degrees or 0 degrees, observability will be minimized, leading to degraded positioning performance. Additionally, after the configuration optimization, the three-line-of-sight distributed cooperative positioning system demonstrated strong observability and robustness. The accuracy of target localization significantly improved, achieving an RMSE of only 6.7 m after filter convergence. In cases of single-satellite signal loss, the positioning performance did not significantly decrease, with a mere 0.2 m precision loss in target localization. The effectiveness of the proposed method has been confirmed.  
Conceptualization, F.Y. and Z.Z.; methodology, Z.Z.; software, Z.Z.; validation, F.Y. and Z.Z.; formal analysis, F.Y.; investigation, F.Y.; resources, F.Y.; data curation, Z.Z.; writing--original draft preparation, Z.Z.; writing--review and editing, F.Y.; visualization, Z.Z.; supervision, F.Y.; project administration, F.Y.; funding acquisition, F.Y. All authors have read and agreed to the published version of the manuscript. This research received no external funding.  
The raw data supporting the conclusions of this article will be made available by the authors on request.  
The authors declare no conflicts of interest.
## 8 Retrieval Performance
### Performance vs. SNR  
The signal-to-noise ratio (SNR) has important influence on the accuracy of GNSS-R techniques. Here, It is needed to analyze the dependence of retracking performance on the SNR. In GNSS-R, the SNR could be defined the scale of processed signal power exceeding the processed noise level as [20]  
\[SNR(\tau)=\frac{\langle|Y(\tau)|^{2}\rangle}{P_{\text{N}}} \tag{25}\]  
where \(P_{\text{N}}\) is the noise floor level which could be computed by averaging all delay waveform points before the first correlation power of the reflected signal. In the paper, the SNR refers in the proportion between the peak waveform and the noise floor, i.e., \(\max\{SNR(\tau)\}\). Here, the only differentia of simulation steps with the above is that the noise level in Equation (6) is also considered to be random to produce the delay waveform with different SNR. Figures 15 and 16 show the improving tendencies of retrieval performance using retracked waveform as the SNR increases. When the SNR is lower than 3 dB, the retrieval accuracies rapidly become worse. For wind speed, the retrieval performance using peak waveform and leading edge slope are the least and worst affected by the SNR, respectively.
# Drone SAR Imaging for Monitoring an Active Landslide Adjacent to the M25 at Flint Hall Farm
## 4 Results  
### Preliminary Results  
Figure 16 shows the drone radar system in-flight at Flint Hall Farm. The following preliminary results are noted from the fieldwork:  
* Flight duration: the drone demonstrated an average maximum flight duration of 21 min with the 3.5 kg payload attached. Any variability in the flight duration is attributed to varied atmospheric conditions, such as wind speeds and atmospheric pressure.
* Flight stability: the drone demonstrated safe and stable flight at low to medium speeds with the payload attached. The hexacopter efficiently distributes the additional weight and maintains stability in windy conditions.
# Post-Earthquake Damage Inspection of Wood-Frame Buildings by a Polarimetric GB-SAR System
## 2 Materials and Methods
### Signal Processing
#### 2.3.2 Antenna Phase Center Calibration  
After a standard VNA calibration, the reference plane, i.e., the time-zero position, is located at the antenna feeding point. However, the electromagnetic waves are radiated from an apparent reference point--i.e., antenna phase center [22]. For a Vivaldi antenna, the phase center is located neither at its feeding point nor at its aperture center, but between them on its symmetric axis, as illustrated in Figure 4. The precise knowledge of the location of the antenna phase center is important for the accurate ranging. Moreover, it is also significant for SAR processing, because it accurately simplifies an antenna as a point source [24].  
We used a multi-offset transmission measurement for locating the apparent phase center position. The details of the method and the experiment procedure are described in [24]. The phase center position of the Vivaldi antenna is estimated to be located 2.0 cm away from the antenna aperture towards the antenna feeding point. Meanwhile, the time delay at the estimated phase center relative to the feeding point is estimated to be 0.4 ns. This antenna delay is corrected and the physical antennas are simplified to be point sources in the following SAR processing.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Frequency Range** & **1 GHz–20 GHz** \\ \hline Polarimetric Combination & HH/HV/VH/VV \\ Antenna Moving Step & 5 mm \\ Scan Area & 80 cm \(\times\) 80 cm \\ \hline \hline \end{tabular}
\end{table}
Table 1: Measurement parameters of the GB-SAR system.
## 4 Discussion
### Discussion on the Load Bridging Effects and Trends by Each Significant Factor
#### 4.1.3 Effect of the Pallet Friction Coefficient on the Bending Ratio of a Board  
As can be observed in the results (Figure 12), there was an inverse relationship between the deflection ratio of the board and the pallet CoF for most scenarios studied. When the friction of the pallet deck increased, the bending of the board decreased. This trend has the potential to influence the design of plastic pallets. Pallets' safe load carrying capacities can be determined by finding the maximum deflection for safe handling or determining the load at which certain pallet components begin to fail [30,31]. Plastic pallets, given the commonly low stiffness of their structures, tend to have a maximum carrying capacity determined by their bending level under load. Affecting the resultant bending of the boards by simply increasing the friction can potentially increase the carrying capacity of a pallet. As with other factors, the interactions between the number of columns, payload height, and box friction determine the resulting effects and, therefore, it all must be studied as a system. However, unit loads carrying packages with low friction levels, such as those equivalents to returnable plastic containers (RPC), did not present such changes in board deflection, except in the case of larger boxes.  
The effect of pallet friction can be observed for commonly used unit load scenarios. Take a unit load, supported on a 1219 mm \(\times\) 1016 mm pallet, containing 340 mm \(\times\) 250 mm \(\times\) 400 mm corrugated boxes made of kraft paper (with an average box friction of 0.45), and stacked three high (having 1200 mm in total height). In this scenario, increasing the frictional forces by going from a pallet friction coefficient of 0.30 to 0.60 can decrease the bending response by 48%. Keeping the same characteristics but using smaller boxes, 170 mm \(\times\) 254 mm \(\times\) 400 mm (in six columns), and increasing the pallet friction coefficient at the same rate, only decreases the bending response by 15%.
# Fundamental Spacetime Representations of Quantum Antenna Systems
###### Abstract  
We utilize relativistic quantum mechanics to develop general quantum field-theoretic foundations suitable for understanding, analyzing, and designing generic quantum antennas for potential use in secure quantum communication systems and other applications. Quantum antennas are approached here as abstract source systems capable of producing what we dub \"quantum radiation.\" We work from within a generic relativistic framework, whereby the quantum antenna system is modeled in terms of a fundamental quantum spacetime field. After developing a framework explaining how quantum radiation can be understood using the methods of perturbative relativistic quantum field theory (QFT), we investigate in depth the problem of quantum radiation by a controlled abstract source functions. We illustrate the theory in the case of the neutral Klein-Gordon linear quantum antenna, outlining general methods for the construction of the Green's function of a source--receiver quantum antenna system, the latter being useful for the computation of various candidate angular quantum radiation directivity and gain patterns analogous to the corresponding concepts in classical antenna theory. We anticipate that the proposed formalism may be extended to deal with a large spectrum of other possible controlled emission types for quantum communications applications, including, for example, the production of scalar, fermionic, and bosonic particles, where each could be massless or massive. Therefore, our goal is to extend the idea of antenna beyond electromagnetic waves, where now our proposed QFT-based concept of a quantum antenna system could be used to explore scenarios of controlled radiation of any type of relativistic particles, i.e., effectively transcending the well-known case of photonic systems through the deployment of novel non-standard quantum information transmission carriers such as massive photons, spin-\(1/2\) particles, gravitons, antiparticles, higher spin particles, and so on.  
quantum antennas; quantum field theory; relativistic quantum mechanics; quantum radiation; propagator; Green's function; quantum engineering; quantum technologies; radiation pattern +
Footnote †: journal: Physics Letters