esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion
Conversely, the NPV increases with higher AHI thresholds, reaching its peak at AHI \(\geq\) 10 (89% [95% CI 87; 91]), meaning that 89% of children who have negative ODI3 at overnight oximetry will not actually have OSA. This trend indicates that a negative test result is increasingly likely to be correct as the severity of OSA increases. This is important to provide an indication of the ability to rule out more severe forms of OSA, reducing unnecessary follow-ups and diagnostic procedures. Our findings can be considered consistent with the trends observed in the literature, such as in [PERSON] et al. [17], who reported a similar range of sensitivity and specificity for ODI4 when assessing moderate-to-severe OSA in children, and in the study by [PERSON] et al. [8], in which oximetry yielded the highest specificity against two validated questionnaires used for the screening of pediatric OSA. However, the pooled sensitivity and specificity in our results appears slightly lower compared to those by [PERSON] et al. [9], which reported higher values for moderate pediatric OSA. This difference might reflect variations in the population characteristics or the specific methodological approaches used across studies. This comparison suggests that while oximetry parameters, particularly ODI3, are useful for identifying pediatric OSA, sensitivity and specificity can vary significantly depending on the AHI threshold and the study population, highlighting the importance of context in interpreting these diagnostic tools. There are some limitations in this systematic review that warrant consideration. A substantial proportion of the included primary studies were conducted in sleep centers or involved patients presenting with snoring or respiratory symptoms, which may have inflated the observed prevalence of OSA within the sample. Additionally, the heterogeneity in age, health status, and ethnicity across the primary studies could restrict the generalizability of the findings to the broader pediatric population. Furthermore, many studies did not explicitly report whether consecutive or random samples of eligible children were selected, raising concerns about potential selection biases and the applicability of the results. The lack of blinding between oximetry and PSG results in several studies may also have introduced bias in the interpretation of findings. Other notable limitations include the lack of information regarding the influence of age on the accuracy of overnight oximetry for detecting pediatric OSA, as well as the absence of clear data on how many children were excluded from analysis due to technical issues or other factors such as artifacts. Variability in the implementation and interpretation of oximetry, combined with inconsistent reporting of criteria for high-quality sleep studies, further complicates the precision of the diagnostic estimates. To enhance clinical relevance, future research should focus on standardizing oximetry execution and interpretation methods, while also addressing the methodological shortcomings identified in the primary studies included in this review.
# High-Power, High-Beam-Quality, Long-Pulse-Width 532 nm Laser Based on a 4f Optical System
## 3 Experimental Setup
Mirror M\({}_{3}\) is placed symmetrically with respect to the crystal rod, with a distance l\({}_{1}\) of 600 mm from mirror M\({}_{1}\). The experimental setup of the long-pulse-width 532 nm acousto-optic Q-switched laser is shown in Figure 3. By moving mirror M\({}_{1}\) further from the laser cavity, the cavity is extended, doubling the total length. A pair of spherical lenses is added to the extended cavity to show the previous positions of the mirrors compared to the new positions. Thus, despite the significantly longer and highly asymmetric cavity, its performance resembles that of a shorter cavity with stable laser characteristics and consistent stability parameters over the entire pump power range. The lenses L\({}_{1}\) and L\({}_{2}\), with a focal length of f = 150 mm, form a 4f optical system. The distance between the output mirror M\({}_{3}\) and the virtual position M\({}_{1}\)' is l\({}_{1}\) = 600 mm, and the distance between the virtual position and the back mirror M\({}_{1}\) is l\({}_{2}\) = 600 mm. The distance between lenses L\({}_{1}\) and L\({}_{2}\) is twice the focal length of the lenses, i.e., 300 mm.
# The Application of Nano Titanium Dioxide for Hydrogen Production and Storage Enhancement
## 2 Titanium Dioxide
### Hydrogen Production Exploiting TiO\({}_{2}\) under Visible and Solar Light  
Water splitting is an uphill reaction that needs the standard Gibbs free energy change of 237 kJ mol\({}^{-1}\)[2]. It consists of two half reactions [3]:  
\[2\mathrm{H}^{+}+2\mathrm{e}^{-}\rightarrow\mathrm{H}_{2} \tag{1}\]  
\[2\mathrm{H}_{2}\mathrm{O}+4\mathrm{h}^{+}\rightarrow\mathrm{O}_{2}+4\mathrm{H} ^{+} \tag{2}\]  
Therefore, the overall reaction is [2]:  
\[\mathrm{H}_{2}\mathrm{O}\rightarrow\mathrm{H}_{2}+1/2\,\mathrm{O}_{2} \tag{3}\]  
In order for a semiconductor to function as a photocatalyst for water splitting, it is imperative that the bottom of its conduction band exhibits a more negative potential than the reduction potential of H\({}^{+}\)/H\({}_{2}\) at 0 V versus the normal hydrogen electrode (NHE).  
Simultaneously, the top of its valence band should possess a more positive potential than the oxidation potential of O\({}_{2}\)/H\({}_{2}\)O at 1.23 V versus NHE. Therefore, for efficient water splitting, the band gap of the semiconductor should exceed 1.23 eV; conversely, to harness visible light, the band gap should be less than 3.0 eV [29]. Accordingly, a band gap falling within the range of (1.23-3.0) eV is a necessary requisite. In addition, photocatalytic H\({}_{2}\) generation is influenced by some factors such as surface area and particle size, band gap energy, corrosion resistance, and the presence of a sacrificial agent [3] such as glycerol [1], triethanolamine (TEOA) [10], ethanol [30], or methanol [11].  
For H\({}_{2}\) production, the performance of TiO\({}_{2}\) is generally limited by the high recombination rate of the photogenerated electrons and holes, an inability to utilize visible light, and fast backward reactions [31]. Loading TiO\({}_{2}\) with noble metals such as Pt, Au [32; 33; 34], or Pd [35] allows the photocatalytic efficiency of TiO\({}_{2}\) to be enhanced by reducing the fast recombination of photogenerated charge carriers [11] and allows the TiO\({}_{2}\) response to the entire visible light spectral range to be extended [3]. However, the use of noble metals is expensive, and their availability is limited; consequently, their use is unsuitable for large-scale energy production [11]. For these reasons, other strategies have been optimized to improve the photocatalytic efficiency of TiO\({}_{2}\), such as employing non-noble metals, metal oxides, cadmium sulfide (CdS), and molybdenum disulfide (MoS\({}_{2}\)).  
Below, different TiO\({}_{2}\) modification strategies that have been evaluated under visible and solar light are presented.
## 3 Data  
### Remotely Sensed Data  
We acquired six TSX stripmap HH polarization images with 3 m spatial resolution (Table 1). The scenes were acquired during the 2009 growing season between 20 July and 20 September (Figure 1). The image product was received in Multi Look Ground Range Detected (MGD) format with reduced speckle and approximately square resolution cells [50].  
To derive NDVI, we utilized a terrain corrected Landsat-5 TM (L1T) scene with 30 m spatial resolution, the best available optical remote sensing data overlapping with our SAR dataset from the growing season of the year 2009 (Table 1). The dataset was received from the United States Geological Survey (USGS) Earth Resources Observation Systems (EROS) center. The image was acquired on 13 July 2009, around the time of mid-growing season when plant growth has reached sufficient levels and NDVI allows better differentiation of vegetation status [51,52]. We further investigated the surface properties of DTLBs by visually analyzing high resolution oblique aerial photographs of several of the DTLBs and a few available Quickbird and Ikonos images. Aerial photographs were collected in June of 2010 and 2011, whereas the Quickbird and Ikonos images were acquired in the growing season of the year 2006 and 2007.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Scenes** & **Acquisition Date** & **Spatial Resolution** & **Incidence Angle** & **Orbit Direction** & **Polarization** \\ \hline TerraSAR-X 1 & 07/20/2009 & 3 m & 35.3\({}^{\circ}\) & Descending & HH \\ TerraSAR-X 2 & 08/16/2009 & 3 m & 31.0\({}^{\circ}\) & Descending & HH \\ TerraSAR-X 3 & 08/27/2009 & 3 m & 28.8\({}^{\circ}\) & Descending & HH \\ TerraSAR-X 4 & 08/29/2009 & 3 m & 31.1\({}^{\circ}\) & Ascending & HH \\ TerraSAR-X 5 & 09/09/2009 & 3 m & 33.2\({}^{\circ}\) & Ascending & HH \\ TerraSAR-X 6 & 09/20/2009 & 3 m & 35.3\({}^{\circ}\) & Ascending & HH \\ Landsat-5 TM & 07/13/2009 & 30 m & - & - & - \\ \hline \hline \end{tabular}
\end{table}
Table 1: Satellite images used in the study.
# Design, Analysis, and Experiment of a Wheel-Legged Mobile Robot
## 4 Results
### Simulation Settings  
As shown in Figure 17a, a virtual prototype and terrain were created. The simulation environment was composed of two types of terrain: flatland and slope. The flatland width was 800 mm, the slope angle was 30 degrees, and the slope height was 240 mm. The length of the prototype was 110.5 mm, and the width was 84 mm. The movement process of the robot is shown in Figure 17b-d. The movement includes movement on the flatland and rolling on the slope. Given these two situations, ADAMS was used for dynamics analysis.  
Figure 16: Structure of the wheel-leg. (**a**)Wheel-leg; (**b**) wheel-leg rack; and (**c**) wheel-leg rod.  
Figure 17: Curling process of the wheel-legged robot. (**a**) Prototype and the terrain. (**b**) Motion on flatland. (**c**) Initial state before rolling. (**d**) End state after rolling.  
The dynamic equations were established using the widely used [PERSON]'s equation with ADAMS. The three coordinates of the barycenter of each rigid body in the inertial reference system and the three Euler angles of the rigid body were selected to determine the Cartesian generalized coordinates. [PERSON]'s equation with multipliers was used to process the complete or incomplete constrained system of multiple coordinates. To avoid over-complexity of the calculations, default values were used for some of the parameters without affecting the results [39]. Then, a kinematics equation with Cartesian generalized coordinates as variables was derived. The calculation program of the software uses the gear rigid integration algorithm and sparse matrix, which greatly improves the calculation efficiency.  
The purpose of the simulation is to analyze the influence of wheel-leg stiffnesses, ground friction, and wheel-leg rotation speed on the torque of the driving motor. Based on the analysis result, the appropriate wheel-leg cover material was determined. Nylon, rubber, and acrylic were used as alternatives. The ground stiffness was set to that of steel. The remaining parameters are shown in Table 2.
## 2 Materials and Methods
### Data Analysis  
Since data from the HandyGym mobile application could not be exported, the average force and power data for the concentric and eccentric phases of each repetition were manually recorded in an Excel matrix. As the app expresses force in equivalent kilograms, these values were converted to Newtons by multiplying by 9.80. To obtain comparable summary data from the criterion method, raw data (200 Hz) for time, position, force, and velocity from the Muscle Lab sensors were downloaded using MuscleLab Software v.10. The raw data were processed using a custom routine in the open-source R statistical software (v. 4.4.1; R Core Team 2024, Vienna, Austria) for Windows [46]. This routine sequentially calculated instantaneous power by multiplying velocity and force values at each time point automatically detected at the start and end of each phase (concentric-eccentric) based on extreme position data from the linear encoder and calculated the average force and power for each phase of every repetition. All data from both systems were consolidated into a single Excel matrix, including volunteer ID, load configuration, repetition number, phase, and the force and power values from both systems for subsequent statistical analysis.
## 5 Application Case
### Platform Application Effect  
According to the actual service environment and on-site requirements of petrochemical enterprises, the service platform of key materials, the post-evaluation criteria and safety assessment model of the supplementary and accelerated tests, and the safety assessment and risk management system were carried out. Based on the application framework proposed in this paper, the following functions are mainly completed in the petrochemical platform:  
1. Established a petrochemical material service that can realize multi-user sub-rights and scalable network data management through integration of service conditions, test data, production process data, corrosion monitoring data and literature data.
2. Constructed a production data management system for petrochemical enterprises that can realize real-time monitoring of on-site data, and real-time monitoring and analysis of corrosion monitoring data.
3. Developed the safety assessment and risk management system of key materials, which realized the evaluation of the risk of corrosion cracking in petrochemical enterprises, and provided support for the formulation of risk control strategies.  
At present, the research results have been applied to the production of a petrochemical enterprise to protect the safety of production.
# Advances in Remote Sensing-Based Disaster Monitoring and Assessment
###### Abstract  
Extreme weather/climate events have been increasing partly due to on-going climate change. Such events become disasters where people live. In a sustainable society, the rapid detection and monitoring of natural disasters are required. Remote sensing techniques are suitable for dealing with natural disasters that have various characteristics in multiple spatial and temporal domains. Continued efforts in finding ways to operationally-monitor and assess disastrous events such as heavy rains, floods, drought, heatwave, and forest fires are consistently rewarded by integrating advanced remote sensing. However, the development of robust disaster monitoring and assessment methods from regional to national scales of disasters is still challenging as disastrous events typically result from complex mechanisms. A multitude of data from visible to microwave remote sensing have been used for conducting comprehensive monitoring and assessment solutions for disasters. Disaster monitoring and assessment are the areas that have benefited most by recent advances in satellite, airborne, and ground remote sensing. Novel techniques in image analysis and the scheduled launch of a series of new sensors with enhanced specifications are also promising for disaster monitoring and assessment, which aims at reducing the risks caused by disasters. This special issue aims at finding novel approaches using various satellite-based images and airborne/ground instruments for the monitoring and assessment of natural disasters including floods, droughts, cyclones, landslides, and land subsidence.
## 3 Results and Discussion
### Mip  
Figure 6 (see also appendix Table A1) show the MIP results of the FSW and SSW samples at 7 and 28 days.  
As shown in Figure 6a, the FSW sample at 7 and 28 days has similar values of total porosity (i.e., an insignificant reduction of total porosity). However, in Figure 6b, the pore-size distributions display notable differences between 7 and 28 days in two size ranges: (1) 200-500 nm, and (2) below 30 nm. Pores with sizes of 200-500 nm have decreased while pores smaller than 30 nm increased from 7 to 28 days. Thus, the FSW sample had a pore-size refinement.  
In contrast, the SSW sample demonstrates a great reduction in total porosity from 0.08 to 0.03 mL/g, as shown in Figure 6c. The SSW sample also shows a substantial pore-size refinement (see Figure 6d). For instance, the pores larger than 0.1 um at 7 days mostly disappeared at 28 days, while the pores smaller than 0.005 um increased. The simultaneous reduction of pore size and total volume are advantageous to improve impermeability to chloride ingression.  
Figure 5: Detailed XRD figure of the SSW sample in 8–15\({}^{\circ}\) 20 at 7 and 28 days with reference patterns of Cl-hydrocalumite and Cl-hydrotalcite.  
Figure 6: _Cont._
# Combined Navigation and Tracking with Applications to Low Earth Orbit Satellites +
## 3 Xona PULSAR(tm) Demonstration Platform
### XL Signal Tracking Startup  
The Xona XL is a modern dual-component signal (data + pilot) designed for the L-Band, with the carrier at 1260 MHz, a chip rate of 5 Mcps, and a data rate of 500 bps [1; 3]. For the scenarios under test, Xona Space Systems provided both the simulated PULSAR  
Figure 7: Approximate orbit propagation: LEO vs. MEO.  
demonstration signals and the full satellite orbit parameters. Simulated scenarios were generated using Safran's GSG-8 simulator and Skydel simulation engine.  
Under nominal steady-state conditions, the FLL is configured to track the pilot component with a 4-quadrant atan2() discriminator, a coherent period of 20 ms, and the number of incoherent accumulations in the range of 4-10 for a total dwell time of 80-200 ms. High dwell times are selected at low signal strengths (CN0) to guarantee good sensitivity. To reach this condition, a signal candidate must pass through a sequence of processing to reduce its code-phase and frequency uncertainties. This procedure is sometimes referred to as handover to emphasize the transfer of the signal candidate from acquisition to tracking specific hardware.  
In cold start conditions, i.e., without any prior assistance information, the Xona XL signal is acquired using a dedicated time-domain correlation engine over a frequency range of 60 kHz. The acquired correlation peak is then passed to a tracking channel, which performs a code-phase and frequency grid refinement. Initial tracking is performed with a wide bandwidth, while at the same time, a pilot secondary code phase is acquired [14]. Finally, secondary code wipe-off is applied, tracking bandwidth is reduced, and additional correlation resources are allocated to the data component for navigation message decoding.  
After handover completion, loop aiding can start. Orbit parameters and receiver coordinates are needed to compute LOS quantities as from (1). Satellite ephemerides are downloaded and extracted regularly from the decoded navigation bits, and, alternatively, they can be obtained offline and injected into the receiver through serial links.  
In our demonstration receiver, all the described procedures did not change very much between MEO and LEO, especially when MEO modernized dual-component signals are compared. Clearly, LEO orbit dynamics had in proportion a bigger effect on the operation of the control loops and increased the signal search space.
## 3 Results and Discussion
### Effect of Infill Pattern on Flexural Properties
#### 3.2.2 Edgewise Testing  
The edgewise testing of infill patterns yielded different results compared to the in-plane testing, as presented in Figure 11. Table 5 shows that the highest edgewise flexural modulus was obtained for the quarter-cubic pattern, i.e., 0.38 \(\pm\) 0.01 GPa, while the lowest flexural modulus of 0.26 \(\pm\) 0.02 GPa was shown by the tri-hexagon pattern. A similar trend was noticed for the maximum flexural load. A maximum load of 29.1 \(\pm\) 1.01 N was carried by a quarter-cubic pattern, whereas the tri-hexagon withstood a maximum flexural load of only 11.1 \(\pm\) 0.90 N. A percentage difference comparison between the two shows that the quarter-cubic pattern outperforms the tri-hexagon pattern by 89% and 37%  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Pattern** & **Max. Flexural Load (N)** & **Flexural Modulus (GPa)** & **Flexural Strength (MPa)** & **Fracture Strain (\%)** \\ \hline Line & 62.7 \(\pm\) 2.14 & 1.06 \(\pm\) 0.01 & 33.4 \(\pm\) 1.08 & 7.36 \(\pm\) 0.60 \\ Triangular & 64.3 \(\pm\) 2.12 & 1.26 \(\pm\) 0.04 & 32.4 \(\pm\) 1.07 & 4.95 \(\pm\) 0.40 \\ Grid & 65.3 \(\pm\) 0.32 & 1.21 \(\pm\) 0.02 & 33.0 \(\pm\) 0.16 & 5.95 \(\pm\) 0.69 \\ Tri-hexagon & 69.0 \(\pm\) 2.77 & 1.23 \(\pm\) 0.03 & 36.7 \(\pm\) 1.22 & 5.99 \(\pm\) 0.35 \\ Quarter-cubic & 63.3 \(\pm\) 3.19 & 1.17 \(\pm\) 0.03 & 31.9 \(\pm\) 1.60 & 6.03 \(\pm\) 0.51 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Experimental results for in-plane flexural properties at different infill patterns.  
Figure 10: (**a**) In-plane force-extension; (**b**) stress–strain behavior of different infill patterns; (**c**) comparison of in-plane flexural strengths for different infill patterns.  
in terms of flexural load and modulus, respectively. The trend was also similar for the remaining two parameters, as given in Table 5. This could be possible due to the high degree of bonding between the layers of the quarter-cubic pattern and the higher stiffness demonstrated by the individual cubic cells formed in the quarter-cubic pattern, which has been discussed in detail with the help of SEM micrographs presented in the next section. Moreover, quarter-cubic exhibited a ductile behavior among the tested patterns, as illustrated in Figure 11b.
# Sensitivity Analysis of Multi-Temporal Sentinel-1 SAR Parameters to Crop Height and Canopy Coverage
## 2 Materials and Methods
### Sentinel-1 Dual Polarimetric SAR Data Statement and Processing  
We used Single Look Complex (SLC) Sentinel-1A interferometric wide swath (IW) data in descending pass direction (Table 2). Sentinel-1 satellites are equipped with C-band sensor with an incidence angle range between 29.1\({}^{\circ}\) and 46.0\({}^{\circ}\) at 5405 MHz radar frequencies. The satellite obtains data with dual polarization (VV and VH) backscatter where electromagnetic waves have polarized vertically (V) for transmission and H/V for reception [21]. Data can be acquired in both ascending and descending orbit pass directions, which means that any object on the earth surface can be evaluated as two independent sights. The difference is that due to steeper incident angle of the ascending orbit therefore the mean backscatter values are rather higher in compare with descending orbit [22]. For time series analysis of SAR backscatter, four C-band polarimetric SAR data during the growth stages of the selected crops from mid-June to late August were acquired for investigation of the sensitivity of Sentinel-1 data to the crops.  
Figure 6: BBCH-scale relationship with crop height (**a–c**), and Correlation between canopy coverage (CC) and crop height (**d–f**) for maize, sunflower, and wheat.