esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### Characterization of Polymer Beads  
The polymer beads were carefully characterized to validate this preparation concept. Figure 2 displays TEM images of the CdTe QDs and the NAC-QD complex. The diameters of the NAC-QDs were much larger than those of the original QDs, indicating a successful introduction of the NAC and formation of the NAC-QD complex. The morphology and size of the MIPs and NIPs were characterized by SEM (see Figure 3a,b). Both the MIPs and NIPs exhibited a uniform spherical structure with a particle diameter of about 200 \(\upmu\)m. Furthermore, the surface of the MIPs was rough and irregular due to their imprinted cavity; the NIPs were relatively smooth. These results were confirmed via magnified SEM images, which can be seen in Figure 3c,d. A large number of effective and tailor-made imprinted sites were found on the surface of the MIPs; there were none on the NIP surfaces.  
FT-IR spectra were used to analyze the surface groups of the MIPs and NIPs. The remarkable peaks at 1633 cm\({}^{-1}\) and 1463 cm\({}^{-1}\) were attributed to C=C stretching vibrations and the benzene ring vibration of DVB, respectively [36; 37]. Strong bands were observed near 1160 cm\({}^{-1}\) and 1720 cm\({}^{-1}\) which corresponded to the C-O-C stretch and C=O vibration from cross-linking TRIM [38]. Furthermore, there was no significant difference between the FT-IR spectra of the MIPs and NIPs, confirming that the template was removed completely.  
Figure 3f shows the optical properties of the QDs, NAC-QDs, MIPs, and NIPs. Compared with the emission peak of the pure QDs, the spectra peak position of the NAC-QDs had a slight red-shift to \(\sim\)340 nm due to the aggregation of QDs during the self-assembly of the NAC-QDs [39]. The fluorescence intensity of the NAC-QDs was much higher than those of the pure QDs because of the surface passivation of the QDs [40]. However, the comparative blue shift in the emission peaks of the MIPs and NIPs was obvious. This might be because of the reduction in the surface charge of the QDs because of electrostatic interactions, leading to a smaller Stokes shift.  
Figure 1: Optical images of emulsions obtained by shaking the oil-water mixture of (**a**) MIPs and (**b**) non-imprinted polymers (NIPs).  
Figure 2: Transmission electron microscopy (TEM) images of (**a**) quantum dots (QDs) and (**b**) the NAC-QD complex.
## 4 Conclusions  
The influence of porosity on the propagation of longitudinal guided waves in a liquid-filled pipe embedded in a finite porous medium was investigated. The filling-liquid was assumed to be water, which is simulated by a linearized Navier-Stokes equation. A porous medium was assumed as the medium outside the pipes and was simulated by the modified Biot theory. This study of the longitudinal guided wave of a water-filled pipe embedded in infinite and finite porous media has led to the following conclusions:  
1. The presence of a porous medium outside the pipe has no significant effect on the phase velocity of a water-filled pipe, compared with a water-filled pipe embedded in an infinite elastic medium;
2. The number of modes in a water-filled pipe embedded in a finite porous medium is more than that of a water-filled pipe embedded in an infinite porous medium in the dispersion curves;
3. The effect of the finite medium surrounding the liquid-filled pipe has been shown by the appearance of several modes (L(0,\(m\))\({}_{P}\), \(m\) = 1,2,3,...), and by the dependence of the phase velocity and displacement amplitude on an outer medium. A good agreement is thus obtained between the dispersion results, time-domain waveform, and attenuation;
4. The attenuation in a water-filled pipe when it is embedded in a finite porous medium is significantly less than that in a water-filled pipe embedded in an infinite porous medium;
5. The low attenuation L(0,1)\({}_{P}\) mode is easily excited and detected, and it is strongly influenced by porosity. As the porosity increases, the phase velocity and displacement amplitude gradually decrease. This explains why, in practice, the pore content in the medium outside the liquid-filled pipe can indirectly indicate a pipeline leak, and provide a certain theoretical support for nondestructive testing.  
With the model of a liquid-filled pipe embedded in infinite and finite porous media established in this paper, the porosity leads to a new aspect of optimization theory for pipeline leak detection, but the sound propagation characteristics still require refinement. In addition, future efforts will be directed toward the following aspects: (1) experimenta  
Figure 11: Attenuation curves of guided waves in water-filled pipe embedded in (**a**) infinite porous medium and (**b**) finite porous medium. The thickness of finite porous medium is \(d\) = 0.05 m. Black, red, and blue lines represent the porosity values of \(\beta\) = 0.1, 0.2, and 0.3, respectively.  
tion with the theoretical model to achieve mutual verification of theory and practice; (2) simulation of complicated pipe systems; and (3) investigation of other parameters, such as the pressure and viscosity coefficient.
# Experimental Design of a Mobile Landing Platform to Assist Aerial Surveys in Fluvial Environments
## 3 Materials and Methods
### Embedded System and On-Board Electronics  
The USV was equipped with a central control unit and a perception system. These components were chosen to comply with the minimum cost requirement and enable different navigation modes. The sensors that made up the perception system are detailed bellow and shown in Figure 6:  
* **HC SR04 ultrasonic sensors** for obstacle detection, with a range of 4 m.
* **IMU GY-85.** Inertial measurement unit with nine degrees of freedom since it features three axis acceleration, gyroscopic and magnetic field measurements. The IMU is used to obtain the acceleration (and speed), the attitude and the heading of the vessel. The speed of the vessel is obtained through integration of the filtered acceleration values obtained by the IMU. It is in a separate box, outside the electronics box to suppress the disturbances that might be caused by the influence of the motor's magnetic field. Attached to the surface through a sponge to absorb vibrations.
* **GPS GY-NE06 MV2**, for obtaining the platform position. The GPS module was placed at the top of the platform, and includes: the GPS module, a ceramic antenna, and a voltage divider to enable the Arduino ADC reading.  
An outline of how the control unit elements are organized and interconnected is presented in Figure 6. Figure 7 shows the system architecture used for the system. The on-board elements marked in the figure are listed below and labeled in the figure:  
Figure 6: On-board electronics and embedded system. The watertight box with the central control unit was placed in the under the landing pad. The enumerated elements in the figure list the on-board elements present in the system. The GPS was placed in the top of the platform, while the compass was placed underneath.
## 4 Discussion
#### Pros and Cons of the Proposed Study  
The simulation results of the PECR algorithm are compared with standard and recent novel algorithms. The comparison shows its competitive behavior and significant improvement in terms of energy management. The proposed PECR algorithm has advantages over existing studies due to its energy consumption model and MCH. The blend of the PECR scheme reduces the traffic overhead at the BS, reserves energy, and ultimately extends the network lifetime. In cases of huge traffic, the PECR algorithm can create a burden on the MCH to some extent. It can be improved in the future by adding more than one MCH or a moveable BS.
# Life Cycle Cost Analysis and Deterioration Patterns of Limestone Paving
## 2 Standard Requirements for Pedestrian Design--Review  
The structural design requirements for natural stone pedestrian pavements are outlined in [32]. The specific mechanical, physical, petro-physical, and durability requirements for natural stone paving slabs are detailed in [33]. Various national and international standards describe the test methods used to evaluate stone properties [34; 35; 36; 37; 38; 39; 40; 41; 42; 43; 44; 45].  
The fundamental properties that influence the performance of stone pavements include apparent density, water absorption, compressive strength, flexural strength, and abrasion resistance [1; 46; 47; 48; 49]. While the European and American standards do not prescribe limits for these properties, the Israeli regulations are more prescriptive. However, the Israeli requirements need to be validated against long-term durability data [50; 51]. Combining accelerated testing with reference service life data can provide a reliable basis for service life prediction and planning [52; 53]. The typical values of limestone properties are summarized in Table 1.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Property** & **Typical Values for Limestone [1; 48]** & **Requirements for Building Stones [50; 51]** \\ \hline Bulk density & 1.9–2.65 & Sample \textgreater{} 2.46; Average \textgreater{} 2.6 \\ \(\times\) [10\({}^{3}\) kg/m\({}^{3}\)] & 1.9–2.65 & Sample \textgreater{} 2.46; Average \textgreater{} 2.6 \\ \hline Total water absorption [mass \%] & \textless{}1\%—20\% & \textless{}1.5\% \\ \hline \hline \end{tabular}
\end{table}
Table 1: Typical values of properties of limestone and standards requirements for building stones’ properties.
# Combination of Models to Generate the First PAR Maps for Spain
## 3 Results
### Developing PAR Maps  
The PAR model developed in this study was then used to develop, for the first time, monthly and annual PAR models in mainland Spain. First, the monthly and annual averages of the daily PAR estimates were calculated using the PAR model. To do that, the monthly and annual averages of the CM-SAF and MODIS datasets were calculated. As the resolution of both datasets is different (0.1\({}^{\circ}\)\(\times\) 0.1\({}^{\circ}\) in the CM-SAF case and 5 km \(\times\) 5 km in the MODIS case), the CM-SAF grid was resized to have the same resolution in both grids. This resolution makes this model suitable to conduct generalized or large studies, but not adequate for more detailed studies. In this way, it was possible to obtain the average daily PAR estimate for each point on the grid, for every calendar month and for a year. Next, these estimates were represented on the surface of mainland Spain, as illustrated in Figures 6 and 7.  
Figure 6: Daily PAR estimates for each month of the year.
# A Novel Technosol Formulation for Sustainable Landfill Top Covers Using Non-Hazardous Wastes
## 2 Materials and Methods
### Technosol Formulation  
A two-tiered, waste-derived Technosol system is proposed as a sustainable approach for developing landfill topsoil covers. This Technosol consists of an 80 cm thick protective layer overlaid by a 20 cm horizon designed to facilitate plant growth (Figure 1).  
To construct the protective layer, the inorganic wastes (WFS and WAS) were thoroughly blended in controlled ratios to achieve a composite material with optimal geotechnical properties, capable of forming a reinforced barrier against infiltration and erosion. Three formulation ratios were evaluated for the protective layer: (a) 90 WFS/10 WAS, meaning 90% waste foundry sand and 10% waste aggregate sludge on a dry weight basis; (b) 80 WFS/20 WAS; and (c) 70 WFS/30 WAS. Given the finer grain size and more plastic nature of WAS, there was a concern about its potential impact on the long-term stability of the engineered material. Therefore, the proportion of fine-grained particles (less than 0.080 mm) in the mixture was limited to a maximum of 30% by dry weight, thus ensuring long-term performance and compliance with established civil engineering requirements for embankment fillings.  
Among the tested formulations, the blend that exhibited the most optimal geotechnical properties, including high compaction, adequate bearing capacity, and appropriate hydraulic conductivity, was selected for further enhancement. To foster plant establishment and growth within the uppermost 20 cm layer of the landfill top cover, CBS was incorporated into the chosen formulation.  
The amended topsoil cover was thoroughly homogenized by hand and then moistened with distilled water. It was then placed in polypropylene containers at room temperature for 14 days for equilibration before being transferred to pots (15 cm depth and diameter) and planted with _Brassica juncea_ (brown mustard). This species was selected for its rapid growth rate and adaptability to diverse climatic conditions and soil types [20]. The pots were placed in a glasshouse environment and received regular irrigation with tap water to maintain optimal moisture levels for plant growth.  
Following the pot experiment, a leaching test was conducted in accordance with European Standard EN-12457-4 [21] to measure the concentrations of potentially toxic trace elements leached from the Technosol. The leach solutions were analyzed for pH, Eh, and electrical conductivity, and their trace element contents were determined by inductively coupled plasma mass spectrometry (ICP-MS) with an Agilent 7700 instrument. Prior to analysis, the solutions were filtered through a 0.45 \(\upmu\)m membrane filter and acidified with dilute nitric acid. For quality control, replicates, blank analysis, and standard reference material (SRM 1640a) were used. The analytical data exhibited an accuracy and reproducibility better than 8% RSD for most elements reported.
## 2 Spectral UAV Sensors
### Pushbroom Spectrometers  
The pushbroom sensor records a line of spectral information at each exposure. By repeating the recording of individual lines during flight, a continuous spectral image over the object is obtained. Each pixel represents the spectral signature of the objects within its instantaneous FOV (IFOV) [32]. The pushbroom design has been the'standard' design for large airborne imaging spectrometers for many years; however, miniaturization for small UAVs has only recently been achieved.  
[PERSON] et al. [33] demonstrated the use of narrow-band indices acquired from a UAV platform for water stress detection in an orchard using a Headwall micro-Hyperspec VNIR pushbroomscanner [34] with a FWHM of 3.2 nm or 6.4 nm, depending on the slit used. In addition, pushbroom scanners have been used to detect plant diseases [35], estimate gross primary production (GPP) by means of physiological vegetation indices [36], and retrieve chlorophyll fluorescence by means of the Fraunhofer line depth method with three narrow spectral bands around the O2-A absorption feature at 760 nm [35; 36]. Pushbroom sensors have also been flown together with light detection and ranging (LiDAR) systems to fuse spectral and 3D data [37]. Most of these studies were carried out with fixed-wing UAVs at flying altitudes of 330-575 m above ground level (AGL), resulting in a ground sampling distance (GSD) of 0.3-0.4 m. Pushbroom systems have also been mounted on multi-rotor UAVs, flying lower and slower, resulting in ultra-high ground sampling distances (<10 cm pixel size). [PERSON] et al. [38] and [PERSON] et al. [39] achieved resolutions of up to 4 cm to map the health of Antarctic moss beds.  
State-of-the-art pushbroom sensors for UAVs weigh between 0.5-4 kg (typically \(\sim\)1 kg) including the lens. However, due to the large amount of data captured by such a sensor, a mini-computer with considerable storage capacity has to be flown together with the sensor, which increases the payload (Section 3.2). [PERSON] et al. [40] built a hyperspectral mapping system based on off-the-shelf components. Their total system included a pushbroom spectrometer, global navigation satellite system (GNSS) receiver and inertial measurement unit (IMU), a red-green-blue (RGB) camera, and a Raspberry PI to control the system and acting as a data sink. The total weight of the system was 2 kg [40]. Recently, companies that formerly focused on full-size aircraft systems have also attempted to miniaturize their sensors for UAVs and provide self-contained systems including the sensor, GNSS/IMU, and control and storage devices (e.g., [41]).  
The benefits of pushbroom devices include their high spatial and spectral resolution, and the ability to provide spatially resolved images. Compared to the point spectrometers, they are heavier and require more powerful on-board computers. Similar to point spectrometers, pushbroom systems need additional equipment on-board the UAV to enable accurate georeferencing of the data (c.f. Section 3.2).
# Shared eHMI: Bridging Human-Machine Understanding in Autonomous Wheelchair Navigation
## 4 Results and Discussion  
### Questionnaire for Wheelchair Users  
Figure 7 shows the SUS questionnaire results from 20 participants, with a mean score of 63. Most scores are between 60 and 80, indicating general acceptance of the proposed shared eHMI system, although not ideal. Notably, seven participants voted below 60, who were then the focus of in-depth study of interview materials. Item analysis found that aspects related to the complexity of the projection interaction, and the consistency of graphics and interactions with habits and expectations, received slightly negative feedback.  
The users' attitude questionnaire results in Figure 8 reveal that most participants were positive about the smart projection wheelchair, showing openness to new technology. However, some had practicality concerns. Many users were worried about the reliability of entrusting their safety to the wheelchair and preferred to retain control, reflecting a need to build trust in fully ADS technology. Despite some risk concerns, the majority were willing to try the smart wheelchair, believing it might outperform their manual operation skills with traditional electric wheelchairs.  
The UEQ-S questionnaire results reveal that the pragmatic quality is 1.2, the hedonic quality is 1.7, and the overall score is 1.45. Users gave positive feedback on both its pragmatic and hedonic quality, but pragmatic quality scored lower, indicating that users experienced more positive emotional responses during use, but the functionality could be improved.  
Figure 7: SUS scores for each participant.
## 4 Proposed Algorithm
### Optimization of Transmission Power Based on a Gradient Method  
In Algorithm 1, by the RRH switching operation according to the traffic of the cell, the interference on the UEs from the other RRHs was minimized. In this section, we use the gradient method to optimize the transmission power for an increased total-energy efficiency. The optimization of the transmission power is performed by the following steps within the upper and lower bounds of the transmission power.  
In order to find the optimal transmission power \(p_{t}^{s}\), we iteratively calculate the transmission power at which the derivative of Equation (8) is zero. We denote the derivative of \(p_{t}^{s}\) in Equation (8) as \(\eta(p_{t}^{s})\):  
\[\begin{array}{ll}\eta(p_{t}^{s})&=\frac{\partial EE(p_{t}^{s})}{\partial p_ {t}^{s}}\\ &=\frac{B\sum_{u\in U}\left(\frac{1}{\tilde{u}}(p_{t}^{s})+N_{0}-\frac{p_{t}^{ s}}{\left(\tilde{u}_{u}\left(p_{t}^{s}\right)+N_{0}\right)^{2}}\right)}{\ln 2(1+SINR_{u}^{s}) \cdot P}-\frac{\sum_{u\in U}\ln(1+SINR_{u}^{s})}{\ln 2(P)^{2}}\,\end{array} \tag{13}\]  
where \(l_{u}^{i}\left(p_{t}^{i}\right)\) is the interference on UE \(u\) from other RRH \(i\
eq s\) and \(l_{u}^{i}\left(p_{t}^{i}\right)=\sum_{i\
eq s}p_{t}^{i}\delta_{u}^{i}\). We use a positive step size \(\alpha\) for gradual convergence and multiply it by the derivative \(\eta(p_{t}^{s})\). We update \(p_{t}^{s}\) by:  
\[p_{t}^{s}=p_{t}^{s}+\alpha\cdot\eta(p_{t}^{s}). \tag{14}\]  
After updating the transmission power, we calculate the energy efficiency and compare it to that before the update. If the energy efficiency has increased, we set the updated transmission power as the optimal transmission power \(p_{t}^{s}\). This method is repeated up to the maximum number of iterations \(K\) or until the difference in energy efficiency is smaller than a given convergence condition \(\epsilon\); further details are presented in Algorithm 2. The step size \(\alpha\) is set to be smaller at the iterations, enabling a faster convergence. The proposed optimization method is summarized in Algorithm 2.  
```
1: set the maximum iteration number \(K\) and convergence condition \(\epsilon\)
2: set the positive step size \(\alpha\)
3: set \(p_{t}^{k}=p_{t}^{s}\), \(p_{t}^{k+1}=0\), \(k=1\), \(p_{t}^{s}=p_{t}^{k}\) calculate \(EE\left(p_{t}^{k}\right)\) using Equation (8)
4: for \(1\leq k\leq K\) do
5: set \(k=k+1\)
6:\(p_{t}^{k+1}=p_{t}^{k}+\alpha\cdot\eta^{k}\left(p_{t}^{k}\right)\)
7: if \(EE\left(p_{t}^{k+1}\right)>EE\left(p_{t}^{k}\right)\) then
8:\(p_{t}^{s}=p_{t}^{k+1}\).
9: else if \(EE\left(p_{t}^{k+1}\right)-EE\left(p_{t}^{k}\right)\leq\epsilon\) then
10: break
11: end if
12: set \(\alpha=\alpha/k\)
13: end for
```  
**Algorithm 2**Optimization of the transmission power based on the gradient method.
## 3 Results and Discussion
### Multivariate Analysis
#### 3.3.2 Hierarchical Cluster Analysis
The lowest correlation coefficients were calculated between the FRAP and DPPH as well as the F-C and DPPH methods (r = 0.92, \(p\) < 0.01). [PERSON] et al. [28] observed comparable [PERSON]'s correlation coefficients (r = 0.95-0.99) that described the high linear relationships between antioxidant properties of the examined black seed, spices, and herbs determined by the same analytical methods (DPPH, ABTS, FRAP, and F-C). In contrast, significantly lower correlation coefficients (r = 0.47-0.63) assessed the association between these methods  
Figure 6: [PERSON]’s correlation coefficients (r) between the antioxidant capacity (AC) determined by the DPPH, ABTS, and FRAP methods and total phenolic content (TPC) analyzed using the F-C assay. All correlation coefficients were statistically significant at \(p\) < 0.01.  
as found by [PERSON] et al. [39]. The strong positive correlations between DPPH and ABTS assays suggested that compounds capable of neutralizing free radicals were present in the spice extracts. It also indicated the possibility that the polyphenols contributing to the free radical scavenging activity were similar compounds with analogous hydrophilicity [40]. The significant positive correlations of FRAP with DPPH and ABTS results suggest that the compounds in the plant extracts that could scavenge DPPH and ABTS free radicals also had the capacity to reduce ferric ions.