esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
The addition of lime is used in applications of soil loess stabilization, e.g., [23]. The lime improves the cation exchange of the soil and  
Figure 3: (**A**) Resistance to load of stabilized Loess soil with different contents of Metakaolin (MK, 0–30%) in an activation solution containing sodium silicate and NaOH (Group 1, Table 2). (**B**) Resistance to load of stabilized Loess soil with calcium oxide (CaO) as a substitute for NaOH in the activation solution (Group 2, Table 2). The results are CaO at the same amount as the NaOH (X1), which was used in the geopolymer presented Figure 3A, and with enlarged amount of CaO up to 20-times (X5-X20). The content of the Metakaolin was 30% for all samples in Figure 3B. Figure 2: PM10 concentrations recorded during the laboratory wind tunnel experiment on the diverse dust control products under wind velocities 6.5 (**right** side) and 9.5 m s\({}^{-1}\) (**left** side). Note, the “control” is the Loess soil with no treatment. The background level measured in the wind tunnel before the test was \(\sim\)0.020 mg m\({}^{-3}\). absorbs water, which lowers the pH. Adding lime also affects the structure of the soil through the soil ability to absorb water. The results of the test for soil samples stabilized by the geopolymer with different amounts of CaO in the activation solution are presented in Figure 3b. The MK content of 30% was constant for all the samples. The resistance increased as the concentration of the lime was higher. This was true up to lime concentration that is 15 (X15) times that of the original concentration (X1). At the highest concentration (X20), the resistance was lower (peak at 6450 N) than in X15 (peak at 7400 N). This can be explained by a rapid and unsteady solidification of the material, which does not allow us to pour the soil mixture into the molds. However, the results of the NaOH in the activation solution (Figure 3a) are significantly higher than those of the replacement base (CaO) with 30% MK (Figure 3a). The results in Figures 2 and 3 show the potential of the clay-based geopolymer examined in this study to suppress dust emission and to stabilized loess soil. The application of the geopolymer for dust control in loess soil in comparison with common products (prime, bitumen, PVA) resulted in no dust emission. As a soil stabilizer, the geopolymer tested in this study provides remarkably good results in the tensile test. The most successful composition of the geopolymer, which is activation solution of sodium silicate and NaOH together with an addition of 30% MK, obtained soil strength of 23,900 N after 28 days. The attempt to replace NaOH with CaO in the activation solution was far inferior to the original composition. The factor of relatively rapid firming of the soil after seven days (strength of 15,510 N) is very important in stabilizing unpaved roads.
# Application of Acoustic Emission Technique in Landslide Monitoring and Early Warning: A Review
## 2 Current Landslide Monitoring Methods
### Geophysical Methods
AE monitoring can provide insights into the accumulation of preparatory damage before surface displacements become detectable, particularly after surpassing specific thresholds [72]. This method effectively captures internal micro-event emissions, reducing signal attenuation. By combining datasets from various scales and domains, a comprehensive understanding of landslide evolution can be achieved, ultimately leading to improved early warning systems. Table 3 summaries the strengths and limitations of geophysical methods.
###### Abstract
Nevertheless, the lack of a consistent pulmonary response across studies evidenced the poor aerosol delivery efficiency in neonates managed with NRS. Since then, the emergence of the vibrating-membrane nebulizer technology and increased awareness of the intrinsic (e.g., low lung volumes and small airways) and the extrinsic (e.g., NRS modality and bias flow, nebulizer type, and position) factors that influence aerosol lung deposition in neonates [12; 21] has led to the development of customized aerosol delivery strategies for this patient population [13; 22; 23; 24]. In this regard, recently published clinical trials on surfactant nebulization have reported encouraging results [25; 26]. Unfortunately, the clinical benefits of nebulized surfactant (i.e., the reduction in intubation) were only observed for the most mature neonates (GA > 31 weeks). While CPAP has been almost exclusively used in all clinical studies, a recent single-center, Phase II trial on nebulized surfactant has reported the use of HFNC in a subgroup of neonates [27]. Nevertheless, to the best of our knowledge, neither the lung surfactant dose nor the effect of nebulized surfactant delivered via HFNC has been yet addressed in benchmark studies or animal models of respiratory distress. Therefore, the present study was designed to investigate the lung dose and the in vivo efficacy of nebulized surfactant delivered with the investigational eFlow Neos vibrating-membrane nebulizer during HFNC. First, we tested the compatibility of different commercially available NCs commonly used in the neonatal intensive care units (NICUs) with our in vivo setting (spontaneously breathing adult rabbits). After that, we conducted a benchmark study with compatible NCs to compare the nebulized surfactant lung dose under simulated neonatal HFNC. Finally, the effect of nebulized surfactant delivered via HFNC was investigated in spontaneously breathing rabbits with induced respiratory distress.
## 5 Emerging Paradigms and Future Directions
### Quantum-Enhanced Architectures  
Quantum computing holds transformative potential for high-dimensional optimization, yet its integration with PINNs remains nascent. Parameterized quantum circuits encode differential operators as Hamiltonians:  
\[H=\sum_{i=1}^{n}\sigma_{z}^{i}+\sum_{i<j}J_{ij}\sigma_{x}^{i}\sigma_{x}^{j} \tag{14}\]  
enabling parallel evolution in \(N\)-dimensional spaces with circuit depths \(D=O(\log N)\). In Equation (14), \(H\) represents the Hamiltonian, which describes the energy of the quantum system, \(\sigma_{z}^{i}\) is the Pauli Z operator acting on the \(i\)-th qubit. It is a matrix that represents a rotation about the \(z\)-axis in quantum mechanics, \(J_{ij}\) represents the coupling strength between qubits \(i\) and \(j\), often associated with interaction terms in quantum systems, \(\sigma_{x}^{j}\) is the Pauli X operator acting on the \(i\)-th qubit, which represents a rotation about the \(x\)-axis in quantum mechanics, \(\sigma_{x}^{i}\sigma_{x}^{j}\) is the tensor product of Pauli X operators acting on qubits \(i\) and \(j\), describing the interaction between these qubits. Early IBM Quantum experiments demonstrate 8\(\times\) speedups for 10D Poisson equations, but noise-induced errors limit scalability beyond 20 qubits [40].  
Co-designing quantum-native PINN architectures with error-mitigation strategies--such as dynamical decoupling and randomized compiling--could suppress decoherence in high-dimensional parameter spaces. Collaborative initiatives like the Quantum-PINN Alliance are curating benchmark datasets (e.g., 50-qubit plasma simulations) to quantify quantum advantage under realistic noise models.  
Figure 3 evaluates the maturity of key directions through a computational physics lens:  
* Neuro-symbolic PINNs (TRL-5): Laboratory validation in turbulence/closures; requires hardware acceleration for real-time deployment.
* Federated PINNs (TRL-4): Pilot studies in healthcare; needs standardization of cross-domain encryption protocols.
* Quantum-PINNs (TRL-3): Proof-of-concept simulations; dependent on error-corrected qubit architectures.  
Bridging these gaps demands coordinated efforts across academia and industry. For instance, the OpenPINN Consortium has established interoperability standards for hybrid numerical-neural models, while NSF-funded initiatives like PhySense are developing IoT-edge frameworks for federated geophysical monitoring.
## 2 The Generation Mechanism and Propagation Route of Flow-Induced Noise
With the decrease of the available net positive suction head (NPSHa), the periodic fluctuations characteristics of sound pressure disappear gradually and the sound pressure intensity at inlet and outlet pipes decreases and increases, respectively [30]. Figure 3 shows the frequency response characteristics of power spectral density (PSD) signal of sound pressure at the outlet pipe. With the decrease of NPSHa, the frequency response characteristics that are dominated by characteristic frequencies weaken gradually in low frequency band, which means that the cavitation could inhibit the rotor-stator interaction to some extent [31]. When the frequency is higher than 1000 Hz, the PSD signal oscillation intensifies significantly. In summary, the flow-induced noise of centrifugal pumps is associated with various flow phenomena. There have been great achievements in the analysis of the generation mechanism and  
Figure 3: Frequency response characteristics of power spectral density (PSD) signal of sound pressure at outlet pipe with different available net positive suction head (NPSHa). (a) 0–1000 Hz; (b) 1000–4000 Hz [30]. frequency response characteristics of the noise induced by rotor-stator interaction and cavitation; meanwhile, the control strategy of the two kinds of noise has also been developed [19; 32; 33; 34; 35]. However, there are few studies concentrating on the analysis of the generation, distribution and control strategy of the noise induced by other factors with inconspicuous characteristics, which include turbulence, back flow, rotating stall and water hammer. Actually, during various operating conditions, the turbulence phenomenon exists in centrifugal pumps. The back flow, rotating stall and water hammer also appear in the process of condition regulation. Therefore, it is necessary to pay more attention to these kinds of noise in follow-up studies, to deepen the comprehensive understanding of the generation mechanism and distribution characteristics of flow-induced noise and to further promote the development of the noise control strategy. (3) The noise propagation route  
The centrifugal pump system consists of the inlet pipe, centrifugal pump and outlet pipe. The flow-induced noise will not only propagate to the inlet and outlet pipes, namely the internal flow noise, but will also propagate to the external environment, namely the external radiation noise [36].
# Factors Affecting the Efficiency of Hydrophobic Coatings--Experience from Application on Sandstone
## 3 Results
### Results of the Water Absorption Tests  
3.2.1. Efficiency of the Antipluviol S  
The progress of the WAC tests in time is expressed in Figure 7 where all types of samples are represented: untreated and impregnated ones. Each series of samples is characterized by one representative line (an average of three to four tested samples). Raw data of this plot can be found in Table S1.  
The untreated Horice sandstone showed a very high absorption by capillarity. Within 1 h, WAC reached the value of 8100 g\(\cdot\)m\({}^{-2}\), and the saturation continued with slower rate, reaching 10,923 g\(\cdot\)m\({}^{-2}\) after 30 days.  
As expected from the visual tests of the coating's penetration, the coating was not water-resistant enough after 2 days of curing. From the first moment of contact with water it started dissolving or diluting, and samples 2x/2d showed WAC close to 8000 g\(\cdot\)m\({}^{-2}\) after 2 days in water when their test was stopped. In contrast, sample groups 2x/2w and 3x/2w show identical behavior, with very slow increase of WAC, reaching only 1100 g\(\cdot\)m\({}^{-2}\) at the end of the test (after 30 days). Based on this experience, 2 weeks proved to be an advisable curing time for the Antipluviol S coating which guarantees sufficient protection with a coating efficiency of 89.8% after 30 days in contact with water.  
Results of \(N_{WAC}\) are compared to \(N_{WAI}\) in Table 3. Because the data sets were too small for statistics (only 3 to 4 data per set), calculation of the standard deviation or other statistical parameters was irrelevant except the average. The efficiency of the coating is quantitatively expressed by the coefficient \(C_{\mathit{ef}}\). It is apparent that the coatings that were only cured for 2 days markedly lost their protective effect; those samples reached lower values of \(N_{WAI}\) than the untreated sandstone, but considerably higher values than the longer cured ones.  
Figure 7: WAC curves—samples with Antipluviol S coatings compared to untreated ones.  
After the test of water absorption by complete immersion, samples were dried and their mass was checked once again. This weighing showed the mass increase of 0.23 g for the samples 2x/2w and 0.22 g for 3x/2w compared to their initial dry mass before the treatment with Antipluviol S (Table 4). This additional mass can be attributed to the hydrophobic coating that resisted the leaching effect of the water. Despite a small loss of the coating's mass, the protection from water is still effective, as reflected by \(N_{WAI}\) in Table 3.
## 2 Integrated Circuit under Study  
This work employs the gallium nitride high electron mobility transistor (GaN-HEMT) power amplifier IC as an example, which operates on frequency range of 2-4 GHz (S-band of electromagnetic spectrum). This IC possess the current advancements in frequency and power, which makes it a potential candidate to study the effect of EMI in this work. To illustrate the methodology developed here, we use a hypothetical 3D-IC where we stack up two and three of this same IC to form the 3D-IC in this work, and the severity of EMI in the stacked dies is also computed.  
An optical image of the power amplifier IC under study at 1600\(\times\) magnification is shown in Figure 2. Its input power (Pin) is 28 dBm and the corresponding output power (Pout) is 30.3 dBm. Drain to source voltage (VDS) of the transistors is 26 V with the gate to source voltage (VGS) of \(-\)2.8 V. The dimensions of the IC are 1700 \(\upmu\)m \(\times\) 1400 \(\upmu\)m \(\times\) 107.92 \(\upmu\)m.
## 3 Results and Discussion
### Phenolic Compound Identification by HPLC/ESI/MS  
The extraction yields of bioactive compounds obtained for the hydroethanol extract were, 11.53% for Cardon, 16.92% for Xoconoste 'Ulapa', 12.18% for Xoconoste 'Cuaresmeno' rosado and 27.23% for Pitaya. It was possible to detect 28 total compounds, of which 19 compounds were unique. The main compounds identified were flavonoids, flavones, anthocyanins, catechins, hydroxybenzoic acids, hydroxycinnamic acids, methoxyflavones, methoxycinnamic acids, methoxyflavonols, lignans, and proanthocyanidin trimers. Table 4 shows the tentative identification of phenolic compounds, where the peaks separated by HPLC/ESI/MS were identified according to their molecular weight using the VARIIAN Work Station database (version 2.0). In Figure 1, the chromatographic profiles of phenolic compounds separated by HPLC are presented. Figure 1: Chromatographic profiles of the main phenolic compounds of cactus flowers from Hidalgo, Mexico. (**a**) _Cylindroputtia rosea_ (CA): (1, 10, 15) hydroxcinnamic acids, (5) anthocyanins, (2, 3, 4, 6, 12) flavonoids, (7, 11, 14) hydroxbenzoic acids, (13) methoxyflavones, (9) proanthocyanidin trimers. (**b**) _Oynutin oligacantha_ (XU): (1, 2, 3) methoxycinnamic acids, (4, 10) methoxyflavones, (6) flavonoids, (7, 8) methoxyflavonols. (**c**) _Oynutin matudae_ (XC): (1, 2) methoxycinnamic acids, (4) lignans, (5) methoxyflavones, (8) flavonoids, (9, 10) methoxyflavonols, (12) anthocyanins. (**d**) _Echinoccreus cinarcscens_ (PI): (1, 2) catechins, (3, 4, 5) flavanols, (7) methoxyflavonols. The presence of 15 compounds was detected in CA, while 10, 12 and 17 compounds were discovered in XU, XC, and PI, respectively. All elutions were recorded at 280 nm. According to the chromatogram, the main compounds detected in the CA flowers were identified as flavanols (peak 12, with Rt 54.47 min and \(m/z\) 301, identified as quercetin), followed by hydroxybenzoic acids (peak 14, with Rt 56.59 min and \(m/z\) 315, identified as protocatechu acid 4-O-glucose), and methoxyflavones (peak 13, with Rt 55.73 and \(m/z\) 283, identified as Geraldone). In the flowers of XU and XC, the main compounds detected were identified as isorham-netin 3-O-glucose methoxyflavonols (peak 8, with Rt 37.63 and \(m/z\) 476.9 in XU, and peak 10, with Rt 37.67 min and \(m/z\) 476.9 in XC), followed by isorhametin 3-O-glucose 7-O-hamnoside (peak 7, with Rt 36.67 and \(m/z\) 622.9 in XU, and peak 9, with Rt 37.73 and \(m/z\) 622.9 in XC), andflavanols such as quercetin 3-O-glucose (peak 6, with Rt 35.24 and
## 5 Experimental Study and Results
### In-Silico Results and Evaluation  
The in-silico analyses of the GRU and LSTM-based models are presented in Figure 13. In Figure 13a, a comparison of the slave robot's original and final response for a traveling distance of 150 mm with a scalar value (\(\sigma\)) of 1.0 mm is shown. Although the original error rose to 40% (2.0 mm) of the input command for some steps, the minimum and maximum final errors were 0.001 mm and 0.1 mm (2% of the input command) per step. The figure shows that the GRU-based controller could predict the expected slave robot response and then utilize this to regress the initial position error. Similarly, in Figure 13b, we present the performance of the LSTM model when the slave robot actuates under a uniform motion for a distance of 150 mm with a scalar value of 1.5 mm. The model predicted values indicate that the LSTM-based controller makes a good prediction of the slave robot response for a typical displacement of 5.0 mm, with a resultant final error of 1.25 mm. Compared with Table 1, the neural-based models ensure higher precision and accuracy of master-slave position-tracking capability. Overall, the models are suitable for position prediction and error compensation within RCSs.  
Figure 12: The slave device assembly and translational motion simulation in CoppeliaSim.
# D-Limonene: Promising and Sustainable Natural Bioactive Compound
## 5 Anthellmitic Activity and Insecticidal Activity of D-Limonene
### Anthellmitic and Insecticidal Activity  
It is reported that low concentrations of D-limonene can kill _Aondiella aurntni_[139], the LC\({}_{50}\) for adult _Stiophilus oryzae_ was 36.85 \(\upmu\)L/L [140], and the percentage of death in _Rhipiccephalus sanguineus_ treated with D-limonene at 0.1 \(\upmu\)L/L was 82.6% [141]. The use of oil-in-water nanoemulsions made of D-limonene (8.9% \(w/w\)), water (30.2% \(w/w\)), Tween 20 (36.9% \(w/w\)), propylene glycol (15.1% \(w/w\)), and ethanol (8.9% \(w/w\)) were highly toxic to larvae of _Culex pipiens molestus_ and _Aedes albopictus_ and the toxicity effect was stronger than that of the unencapsulated D-limonene solution; this is probably due to the increased surface to volume ratio of nanoencapsulated D-limonene, which is beneficial to penetration, making it easier to pass through the insect's exoskeleton and protect the active substances within it from inactivation and degradation. After treatment, the larvae have a fragile appearance, with a wrinkled body surface and changes to the head, thorax, siphon, and abdominal cuticle, indicating potential for application in integrated pest control [142], and for _Aedes aegypti_ and _Aedes albopictus_ eggs, D-limonene causes morphological damage to the outer villous cuticle and blocks stomata, leading to respiratory distress [143]. Of note, D-limonene exhibited low toxicity to the natural enemies of this mosquito, _Poecilia lattipima_ and _Poecilia reticulata_, suggesting that it has potential for biological control.  
[PERSON] et al. [144] showed that D-limonene directly affected the development of the adults, larvae, and pupae of _Haematobia irritans irritans_ and that D-limonene at a concentration of 5.8% rendered _H. irritans irritans_ immobile and significantly interfered with the fecundity and egg hatchability of the insect, but the mechanism was not clear. Interestingly, D-limonene was present in salivary gland extracts of _Ceratitis capitita_[145] and D-limonene had an attractive effect on _H. irritans irritans_ at concentrations below 0.1%, indicating that D-limonene has potential application in trapping these insects [144]. In addition, D-limonene not only inhibited the fecundity activity of _Bactrocera dorsalis_ but also showed a significant toxic effect on adults and pupae and exhibited a dose-dependent killing effect on larvae [146]. However, [PERSON] et al. [147] found that D-limonene exhibited acute toxicity to the insect at high concentrations but promoted its survival and reproduction at low concentrations, probably due to the hormetic-like effect of D-limonene.
###### Abstract  
Machine learning (ML) algorithmic developments and improvements in Earth and planetary science are expected to bring enormous benefits for areas such as geospatial database construction, automated geological feature reconstruction, and surface dating. In this study, we aim to develop a deep learning (DL) approach to reconstruct the subsurface discontinuities in the subsurface environment of Mars employing the echoes of the Shallow Subsurface Radar (SHARAD), a sounding radar equipped on the Mars Reconnaissance Orbiter (MRO). Although SHARAD has produced highly valuable information about the Martian subsurface, the interpretation of the radar echo of SHARAD is a challenging task considering the vast stocks of datasets and the noisy signal. Therefore, we introduced a 3D subsurface mapping strategy consisting of radar echo pre-processors and a DL algorithm to automatically detect subsurface discontinuities. The developed components the of DL algorithm were synthesized into a subsurface mapping scheme and applied over a few target areas such as mid-latitude lobate debris aprons (LDAs), polar deposits and shallow icy bodies around the Phoenix landing site. The outcomes of the subsurface discontinuity detection scheme were rigorously validated by computing several quality metrics such as accuracy, recall, Jaccard index, etc. In the context of undergoing development and its output, we expect to automatically trace the shapes of Martian subsurface icy structures with further improvements in the DL algorithm.  
shallow subsurface radar; lobate debris aprons; polar deposits; discontinuity; subsurface feature +
Footnote †: journal: Applied Sciences  
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