esa-sceva/satcom-chunk-collection huggingface dataset:
# Passive Microwave Imagers, Their Applications, and Benefits: A Review
###### Abstract  
Passive Microwave Imagers (PMWIs) aboard meteorological satellites have been instrumental in advancing the understanding of Earth's atmospheric and surface processes, providing invaluable data for weather forecasting, climate monitoring, and environmental research. This review examines the relevance, applications, and benefits of PMWI data, focusing on their practical use and benefits to society rather than the specific techniques or algorithms involved in data processing. Specifically, it assesses the impact of PMWI data on Tropical Cyclone (TC) intensity and structure, global precipitation and extreme events, flood prediction, the effectiveness of tropical storm and hurricane watches, fire severity and carbon emissions, weather forecasting, and drought mitigation. Additionally, it highlights the importance of PMWIs in hydrometeorological and real-time applications, emphasizing their current usage and potential for improvement. Key recommendations from users include expanding satellite networks for more frequent global coverage, reducing data latency, and enhancing resolution to improve forecasting accuracy. Despite the notable benefits, challenges remain, such as a lack of direct research linking PMWI data to broader societal outcomes, the time-intensive process of correlating PMWI use with measurable societal impacts, and the indirect links between PMWI and improved weather forecasting and disaster management. This study provides insights into the effectiveness and limitations of PMWI data, stressing the importance of continued research and development to maximize their contribution to disaster preparedness, climate resilience, and global weather forecasting.  
passive microwave imager; societal impact; hydrometeorological application; environmental monitoring; climate monitoring; disaster management +
Footnote †: journal: Remote Sensing  
**2025**, 17, 1654
## 3 Results and Discussion
### Transport Properties along the Layers
From the temperature dependence of the Fermi level, which for a parabolic c-band is related with the concentration of the carriers as  
\[n_{C}=4\pi\left(\frac{2m^{*}kT}{h^{2}}\right)^{3/2}F_{1/2}\left(\frac{\mu}{kT} \right), \tag{5}\]  
the Fermi integral was calculated, and the chemical potential was determined for a set of temperature points. With the significant compensation of donors, the following equation takes place:  
\[\mu=kT\ln\frac{N_{D}-N_{A}}{N_{C}+gN_{A}e^{E_{D}/kT}} \tag{6}\]  
This equation contains two unknown parameters, \(N_{D}\) and \(E_{D}\), related by the expression:  
\[N_{A}=\frac{n_{dep}-N_{C}e^{\mu/kT}}{ge^{\frac{p+E_{D}}{kT}}} \tag{7}\]  
By taking the spin degeneracy factor to be \(g=2\) and writing the expression for \(N_{A}\) at two significantly different temperatures, we obtain a corresponding difference equation that contains the only unknown parameter \(E_{D}\), which is obtained from a fitting procedure. Thus, for the intercalated sample 2 we obtain that \(E_{D}=90.4\) meV, \(N_{D}=5.38\cdot 10^{15}\) cm\({}^{-3}\), and \(N_{A}=3.30\cdot 10^{15}\) cm\({}^{-3}\). Note that in our case \(E_{D}\) is the depth of the potential well and its value is close to those observed in [36] (0.09-0.14 eV). To define the nature of the additional interlayer defects which appeared after the insertion of RbNO\({}_{3}\), it is necessary to carry out detailed studies. Here, we assume that the intercalation leads to the formation of additional interlayer planar defects and potential wells. For such samples, one can expect a decrease in the \"vertical\" conductivity and high values for the anisotropy ratio at low temperatures.
## 3 Results and Discussion
### Regeneration Studies  
From industrial and technological points of view, it is desirable to recover and reuse the adsorbed material. The effective reuse of adsorbent materials directly affects the cost factor, so its practicability  
Figure 4: XRD patterns of (**a**) L1, (**b**) L2, (**c**) L2-Eu.  
Figure 5: FT-IR spectra of (**a**) L1, (**b**) L2, (**c**) L2-Eu.  
in continuous batch adsorption process is important [43; 44]. In this work, the regeneration of the used EDTA-LDH adsorbent was investigated. The desorption efficiency of the exhausted adsorbent is shown in Figure 6, and the removal efficiency of the regenerated L2 adsorbent is shown in Figure 7. From Figure 6, the desorption by HNO\({}_{3}\) shows good desorption efficiency for both La(III) and Eu(III).  
The optimum concentration was 200 mmol-L\({}^{-1}\). The desorption efficiency of La(III) was found to be 95.67%, whereas that of Eu(III) was slightly lower; this may be due to the fact that the stability constant of Eu-EDTA (17.4) is higher than that of La-EDTA (15.5). Figure 7 shows the better reuse performance of L2 after three cycles. The hydrogen ions may destroy the structure during the desorption process, which results in the decrease of the removal efficiency after the fourth or fifth cycle.
# Remote Sensing and Bio-Geochemical Modeling of Forest Carbon Storage in Spain
###### Abstract  
This study simulates annual net primary production (NPP) of forests over peninsular Spain during the years 2005-2012. The modeling strategy consists of a linked production efficiency model based on the Monteith approach and the bio-geochemical model Biome-BGC. Recently produced databases and data layers over the study area including meteorological daily series, ecophysiological parameters, and maps containing information about forest type, rooting depth, and growing stock volume (GSV), were employed. The models, which simulate forest processes assuming equilibrium conditions, were previously optimized for the study area. The production efficiency model was used to estimate daily gross primary production (GPP), while Biome-BGC was used to simulate growth (\(R_{\text{G}}\)) and maintenance (\(R_{\text{M}}\)) respirations. To account for actual forest conditions, GPP, \(R_{\text{G}}\), and \(R_{\text{M}}\) were corrected using the ratio of the remotely-sensed derived actual to potential GSV as an indicator of the actual state of forests. The obtained results were evaluated against current annual increment observations from the Third Spanish Forest Inventory. Coefficients of determination ranged from 0.46 to 0.74 depending on the forest type. A simplified dataset was produced by applying regular increments in air temperature and reductions in precipitation to the original 2005-2012 daily series with the goal of covering the range of variation of the climate projections corresponding to the different climate change scenarios reported in the literature. The modified meteorological series were used to simulate new GPP, \(R_{\text{G}}\), and \(R_{\text{M}}\) through Biome-BGC and corrected using GSV. Precipitation was confirmed as the main limiting factor in the study area. In the regions where precipitation was already a limiting factor during 2005-2012, both the increment in air temperature and the reduction in precipitation contributed to a reduction of NPP. In the regions where precipitation was not a limiting factor during 2005-2012, the increment in air temperature led to an increment of NPP. This study is therefore relevant to characterize the growth of Spanish forests both in current and expected climate conditions.  
forest; NPP; Monteith; Biome-BGC; Spain 2020 12 1356 doi:10.3390/rs12091356
## 3 Beamforming Techniques  
The beamforming technique opens a new window in the arena of antenna array by using a weighting vector. The weighting vector is a robust technique that puts null in the direction of the unwanted signal. As a result, it is named after robust techniques that can detect the false signal and cancel the noise. Fixed diagonal loading (FDL), optimal diagonal loading (ODL), and variable diagonal loading (VDL) are mostly used. An optimal technique is also applied in this research. A new variable loading (NVL) technique is proposed in this paper.
# Traffic Aware Scheduler for Time-Slotted Channel-Hopping-Based IPv6 Wireless Sensor Networks
## 4 Design of the Subtree-Size and Traffic Aware Scheduler
### Deallocation Phase  
The cells are deallocated when the number of remaining packets in the queue is below the deallocation_threshold for five consecutive times. Based on analysis of simulations of RBS Orchestra in different traffic situations, we concluded that, when the traffic rate is 1 or 2 packets per minute, the number of remaining packets in the queues for the root's children rarely reaches 2 packets. Thus, the deactivation_threshold is set to 2. When the condition for deallocating cells is met, the activation flag is set to false and inserted in the following unicast packets. Upon receiving a unicast packet from one of its children with the activation flag set to false, the root removes the additional Rx cells. In the deallocation phase, the Tx cells are removed first, followed by the Rx cells, to avoid sending packets in a cell that does not have a corresponding receive cell on the root's side.  
Figure 7 summarizes the allocation and deallocation phases. The algorithm for allocating and deallocating Tx cells for the root's children is presented in Figure 7a. Whenever a packet is sent, each root child checks its queue. If the number of remaining packets is above the activation_threshold five times (denoted \"a\" in Figure 7a) and the new schedule is not already activated, the corresponding number of Tx cell is added after 1s. We check the activation condition \"a\" times to avoid reacting too soon and increasing the duty cycle in case the high number of packets is related to control traffic or a burst with a duration shorter than the reaction time of our algorithm. The same reasoning is applied when deallocating Tx cells, with the difference that we do not wait before removing the Tx cells.  
In Figure 7b, the algorithm for allocating and deallocating Rx cells for the root is described. Whenever a data packet is received, we evaluate the activation flag. If it is true and the schedule is not already activated, we proceed with allocating Rx cells. If the activation flag is false and the schedule is active, we deallocate the Rx cells.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Threshold** & **Value** \\ \hline subtree\_lower\_threshold & 3 \\ \hline subtree\_upper\_threshold & 5 \\ \hline M & 2 \\ \hline N & 3 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Values of the thresholds used for exemplifying the allocation of additional time slots.  
Figure 6: Example of allocation of Rx and Tx slots with the new scheduler. (**a**) The placement of nodes results in a topology with 3 children for the root. Each child has a different subtree size. (**b**) Allocation of Tx and Rx slots based on the topology in (**a**).
# Application of the MiL and HiL Simulation Techniques in Stewart Platform Control Development
## 4 Hardware-in-the-Loop (HiL) Simulation of the Stewart Platform
Graphs show that transient responses are slightly oscillating, which is the reason the actual position and orientation of the moving plate is oscillating as well. The steady state values are comparable to the MiL scenario with the exception of the first linear actuator where a small error in magnitude is visible, which must result in an error in position and orientation of the moving plate. Authors assume this discrepancy is caused by one of the issues mentioned at the end of this chapter. Figure 17: Moving plate position and orientation (HiL). (**a**) Actual (\(\varphi_{y}\), \(\vartheta_{y}\), \(\Psi_{y}\)) orientation of the moving plate; (**b**) Actual (\(\chi_{y}\)) positon of the moving plate in the \(X_{\text{b}}\) axis; (**c**) Actual (\(\chi_{y}\)) position of the moving plate in the \(Y_{\text{b}}\) axis; (**d**) Actual (\(\chi_{y}\)) position of the moving plate in the \(Z_{\text{b}}\) axis. Figure 18: Actual piston rod extensions of the Stewart platform linear actuators (HiL). In Figure 19 the acting forces \(F_{a}\) of the linear actuators, that are equivalent to the action value inputs \(u\), are shown. It can be seen that the acting forces slightly oscillate and that the peak values and steady states are similar to the MiL simulation results. Even though the obtained data cannot be directly compared to the MiL scenario, from the graphs it is obvious that the dynamics of the system is very similar. The main discrepancy in the MiL and HiL scenario is in the oscillation of the transient responses and the error in the magnitude of the first piston rod extension. These discrepancies can be caused by multiple issues such as different sampling periods of the controller and the simulated plant, connection of the real controller and the associated conversion of quantities from numerical format to voltage signal, quantization of signals during A/D and D/A conversions, rounding errors and also slight time delay. However, since most of the mentioned issues also occur during the control of the real system, the obtained results might represent the real control conditions. From this perspective, it is important that the control shows stability, required dynamics and accuracy which also depends on the type and parameters of the used controller. The HiL technique allowed us to get acquainted with properties and behaviour of the Stewart platform in real-time scenario with an actual real controller design. It also allowed us to experiment with the system in the virtual environment and therefore we avoided the potential risk of destroying or damaging the real equipment. This scenario also possibly allows us to investigate the synchronization of the individual linear actuators which must be precise in high-precision Stewart platform applications.
###### Abstract
The complex effects of ions in ion-exchange polymers include the factors that contribute to the selectivity of ion separation [30; 31; 32], which are considerably intricate yet summarized as a single coefficient. A crucial application of this is the formation of the Donnan-Manning model [11; 12], which combines the Donnan equilibrium theory to predict the thermodynamic separation ratio of different ions in ion-exchange polymers, a topic that has been widely reported [33; 34; 35]. Notably, among the results of these experiments, the Donnan-Manning model accurately captures the varying affinities of counterions with the same valence for ion-exchange polymers through counterion condensation, predicting their competitive distribution in mixed solutions [36; 37; 38]; However, the applicable concentration range remains limited. One potential solution is to gather experimental ion partitioning data, which allows for adaptive fitting of [PERSON]'s model based on the data. Once calibrated in this manner, accurate ion activity coefficients in ion-exchange polymers can still be derived from the fitted model, even if prior predictions are inadequate. In this work, aminated cross-linked polystyrene anion-exchange membranes (AEM) were synthesized, and the solvent and ion concentration distributions in the electrolyte solution were measured as a function of external salt concentration. The ion activity coefficients in the membrane were predicted by [PERSON]'s Counterion Condensation Theory [10; 11; 12; 13] and compared with experimental values. To enhance the applicability of [PERSON]'s model, simple improvements and modifications based on experimental data were implemented to increase accuracy and provide a feasible reference scheme for calculating and modeling ion activity coefficients in an ion-exchange polymer.
## 2 Related Work and Comparisons between the Methods
### Further Discussion on Histogram Modification-Based Approaches
Since human eyes are more sensitive to the changes in lower intensity pixels than higher ones, this approach divide the intensity levels into four groups of equal size and embed less bits in the low intensity pixels for less conceived distortion of the stego-image so that the visual imperceptibility is improved. * Pixel Value Ordering (PVO). [PERSON] et al. [20] proposed the pixel value ordering (PVO) technique which is an advancement of PEE. When the cover images are divided into blocks, PVO first sorts pixel values in each block and then computes minimum, maximum, second-minimum and second maximum pixels which are used for data embedding depending on the minimum and maximum prediction errors in the blocks. PVO changes the pixel values only by at most 1; hence, it generates high quality stego-images. [PERSON] et al. [54] propose RDH technique using PVO and pairwise PEE to improve EC while retain the quality of the stego image. The embedding strategy is performed in two-phases on three-pixel blocks. Pixels are traversed in a zig-zag way and then sorted based on their rhombus means. The key of PVO for increasing EC is that smaller prediction errors are derived after pixels are sorted. [PERSON] et al. [55] also considered RDH based on PVO for roughly texture images. For more thorough survey on RDH approaches based on PVO can refer to the survey in [54].
## 2 Principle and Intensity of Effective Stress of Unsaturated Soil
### Strain Characteristics of Unsaturated Soil in the Stress Field  
A large number of tests have shown that the strain hardening curves for different types of unsaturated soil have different trends under the same confining pressure. As shown in Figure 2, the deviatoric stresses of the three curves are the same at the time of destruction, which means that the three curves have the same Mohr's stress circle. Therefore, the hardening capacity of the three strain hardening curves must be reflected in order to distinguish the engineering properties of the soil.  
Since soil is a typical viscoelastic material, the fractional calculus theory is introduced to effectively describe the strain hardening and viscoelasticity of unsaturated soil. The differential operators from fractional calculus and the stress history of memory materials are widely used to describe the mechanical properties of viscoelastic materials. According to the Riemann-Liouville fractional calculus operator theory, the integral of function \(f(t)\) of order \(\alpha\) is defined as:  
\[\frac{\text{d}^{-\alpha}f(t)}{\text{d}t^{-\alpha}}=_{t0}D_{t}^{-\alpha}f(t)\ =\ \frac{1}{\Gamma(\alpha)}\int_{a}^{t}(t-x)^{\alpha-1}f(x)dx \tag{11}\]  
The fractional order differentiation is defined as:  
\[_{t0}D_{t}^{\alpha}f(t)\ =\ \frac{\text{d}^{\alpha}f(t)}{\text{d}t^{\alpha}}\ =\ \frac{\text{d}^{\alpha}}{\text{d}t^{\alpha}}\Big{[}D^{-(n-\alpha)}f(t)\Big{]} \tag{12}\]  
where \(0<\alpha\) is the fractional order. \(\Gamma(*)\) is a Gamma function defined as: \(\text{Re}(z)>0\), \(\Gamma(\tau)\ =\ \int_{0}^{\infty}e^{-x}t^{\tau-1}dx\).  
Figure 2: Stress–strain curves of different unsaturated soil under the same confining pressure.  
Therefore, the strain hardening relationship of unsaturated soil can be derived from the fractional calculus theory as the following:  
\[\sigma(t)\ =\ E_{0}D^{\alpha}\varepsilon(t) \tag{13}\]  
where \(E_{0}\) denotes the initial elastic modulus, 0 \(<\alpha<\) 1 and a larger \(\alpha\) means a smaller strain hardening capacity of the soil,  
Generally, constant strain rate loading is adopted in unsaturated soil shear tests, and the strain-time relationship is:  
\[t\ =\ \frac{\varepsilon}{v_{0}} \tag{14}\]  
where the constant \(v_{0}\) denotes the strain rate.  
Bringing Equation (14) into Equation (13), the strain hardening viscoelasticity model in the triaxial test is obtained as follows:  
\[\sigma\ =\ E_{0}v_{0}^{\alpha}\frac{\varepsilon^{(1-\alpha)}}{\Gamma(2-\alpha)} \tag{15}\]
## 4 Results
### Lossless dielectric scatterer  
Next, a lossless dielectric scatterer was considered, with radius \(\rho=3\lambda\), arc displacement \(d=0.5\rho=1.5\lambda\), relative permittivity \(\varepsilon_{r}=2.56\), incidence angle \(\varphi_{inc}=0\), inner and outer auxiliary  
Figure 5: Plots of \(E\) field boundary condition error for a perfectly electric conducting (PEC) scatterer with initial \(\rho_{aux}=\rho-0.075\lambda\) using: (**a**) the standard, conformal auxiliary surface; and (**b**) the deformed auxiliary surface.  
Figure 6: Plots of \(E\) field boundary condition error for a PEC scatterer with initial \(\rho_{aux}=\rho-0.15\lambda\) using: (**a**) the standard, conformal auxiliary surface; and (**b**) the deformed auxiliary surface.  
surface radius \(\rho_{aux\ in}=\rho-0.3\lambda\) and \(\rho_{aux\ out}=\rho+0.45\lambda\), and, originally, 160 CPs (hence 160 inner and 160 outer ASs). Like in the PEC case, the efficiency of MAS was initially tested using a conformal auxiliary surface and the extracted results of the BC error are presented in Figure 7a, where the upper subplot depicts the quantified error for the \(E\) field (\(\Delta E\) %) and the lower one for the \(H\) field (\(\Delta H\) %), both being relatively significant near the wedge tips.  
Afterwards, the improvement of the BC was examined by employing the aforementioned deformation scheme with the following parameters, obtained through multiple trials: the portion of ASs to be displaced was \(1/5\) for the inner and \(1/8\) for the outer ones, with a proximity factor of \(s=0.75\) and \(s=0.65\), respectively, while all of them were densified with \(D_{start}=0.80\). The addition of extra ASs offered no further refinement and was skipped once more. Figure 7b depicts the considerably decreased quantified BC error, and the corresponding radar cross section (RCS) is displayed in Figure 7c.
# A Hybrid Bio-Optical Transformation for Satellite Bathymetry Modeling Using Sentinel-2 Imagery
## 2 Materials and Methods
### Data Acquisition  
#### 2.2.1 The Field Data  
The training and validation bathymetry used in the Hybrid Bio-optical Transformation (HBT) model implementation was extracted from the nautical chart No. 423/2 (scale 1:20,000), published in June 1989 by the Hellenic Navy Hydrographic Service. This data originates from hydrographic surveys performed between 1982 and 1987, categorized as CATZOC A2 (Category Zone Confidence A2), with horizontal accuracy of the depicted depths of \(\pm\)20.0 m and vertical accuracy of \(\pm\)1.6 m.
## 4 Challenges and Future Research Directions
### THz and mmWave Communication Challenges  
The utilization of THz waves for wireless communication faces a significant challenge due to its substantial free space path loss (FSPL). Thus, THz/mmWave provides limited wireless coverage or transmission distance. However, larger lenses and antennas could potentially reduce FSPL issues, but they are not ideal because they conflict with the crucial design parameter of maintaining a compact form factor for indoor network components [124].  
Additionally, the high directivity of the link makes it susceptible to blockage issues [125]. To address these challenges, beam-forming technology can be employed to mitigate blockage vulnerability. However, reliable non-line-of-sight (NLOS) wireless communication can be ensured by relay/IRS. It is essential to find potential solutions that overcome the major challenges of IRS/relay, such as beamforming, signal reception, location, etc., for the successful implementation of THz wave-based wireless communication systems.