esa-sceva/satcom-chunk-collection huggingface dataset:
# A Survey on Physical Layer Techniques and Challenges in Underwater Communication Systems
## 2 UWAC Physical Layer Techniques
### Spatial Modulation Techniques
So far, numerous other progressive methods have been projected using the operational mechanism of these methods.
## 4 Results and Discussion
### Simulation of Different Construction Distances  
#### 4.2.1 Simulation of Different Horizontal Construction Distances  
Simulations were carried out for cases involving a horizontal distance of 3 m, 4 m, 5 m, 6 m, 7 m and 8 m, respectively, to explore the affected laws of oil and gas pipelines under different horizontal distances.  
As shown in Figure 17, at varying horizontal construction distances, the displacement and X-direction stress cloud distribution exhibit similarities, with the peak displacement and axial stress manifesting at the center of the pipeline, nearest to the pile foundation. With a reduction in distance, the pipeline's displacement and peak stress progressively escalate. The maximum horizontal displacement escalates from 0.26 mm to 2.17 mm, and the peak axial stress rises from 0.53 MPa to 2.59 MPa. Additionally, the extent of the maximum stress progressively diminishes, leading to a pronounced stress concentration phenomenon.  
Figure 17: Cont.  
Monitoring points are established on the surface of the pipeline nearest to the pile foundation to track the horizontal displacements and stresses. The outcomes observed are then compiled and represented by a curve, as shown in Figure 18.  
The graph clearly demonstrates that with a decrease in the horizontal construction distance, there is a noticeable increase in both the horizontal displacement and the axial stress experienced by the pipeline. In the displacement aspect, a linear increase is observed from the 8 m to 5 m interval, with a marked increase in the curve's slope from 5 m to 3 m, highlighting a distinct acceleration in the rate of displacement. The enhancement in the horizontal displacement per meter of reduction from 6 m to 3 m is quantified at 38.4%, 55.6% and 57.1%, respectively. The stress variation curve mirrors this trend, but with greater intensity; negligible changes occur within the 8 m to 5 m span, followed by a steep incline between 3 m to 5 m. At a horizontal construction distance of 3 m, the induced stress on the pipeline is approximately 2.5 times greater than that at 4 m, with the stress escalation per meter of reduction from 6 m to 3 m being 15.8%, 45.5% and 131.3%,  
Figure 17: Pipeline X-direction displacement and stress cloud for different horizontal construction distances: (**a**) 3 m; (**b**) 4 m; (**c**) 5 m; (**d**) 6 m; (**e**) 7 m; (**f**) 8 m.  
respectively. Consequently, both the horizontal displacement and axial stress on adjacent oil and gas pipelines during pile foundation construction exhibit a negative correlation with the construction distance, with a more pronounced increase in displacements and stresses at distances less than 5 m. Therefore, it is imperative to intensify the control over construction impacts when undertaking pile foundation construction within 5 m of oil and gas pipelines buried at a depth of 3 m, selecting suitable pile foundation construction techniques and impact mitigation measures in compliance with the designated design criteria.
## 4 Results and Discussion  
### Health Trend Prediction  
In this case study, predictors were forecasted using the PLSR to construct the prediction models. As a preliminary step, the changing health trends were analyzed using RHP-EWS for the Maria event. We collected data for health prediction during the period of July 10 to July 13, 2018. When the collected data were input into RHP-EWS, the HI, IBI, and WQI prediction values per one-hour step over the event period were obtained and the changing health trends of each sub-catchment or reach were predicted and are shown in the prediction thematic maps. Figure 5a is a bar chart thematic map, which illustrates the changing HI trends of all reaches during the Maria event from 1:00 a.m., July 10 to 11:00 p.m., July 13. When one of the charts is clicked, the detailed trend features are presented as a trend line chart. For instance, when we click the bar chart located in Zhaoshandu Reservoir, its detailed HI trend feature is shown as Figure 5b. Figure 5b shows that HI reached the lowest value of 0.62 at 1:00 p.m. on July 12. Before this time, the HI decreased, and after that, the HI trend episode began to rise and reached a constant approximately 3 days later. Thus, the trend analysis yielded a remarkable advance by forecasting upcoming severe situations days earlier than the original measurements.  
Figure 5: _Cont._
## 2 Materials and Methods
### Remote Sensing Data
#### 2.3.2 UAV Data
Once this conversion factor (\(F_{i,\lambda}\)) is determined, the reflectance at wavelength \(\lambda\) (\(\rho_{\lambda}\)) for the image can be calculated by multiplying the spectral radiance by the conversion factor, as shown in Equation (3):  
\[\rho_{\lambda}=L_{sen_{\lambda}}\times F_{i_{\lambda}} \tag{3}\]  
After radiometric calibration, MS images were orthorectified using geodetic coordinates from Real Time Kinect GPS GNSS RTK (Emlid, Reach RS2) using the control ground points obtained on the edge of plots, using the georeference tool from QGIS 3.36 software [58]. The pixel resolution of the processed images was 2.0 cm.
## 2 Materials and Methods
### Study Area  
Several environmental and technical factors influence the choice of navigation methodology: temperature, illumination, communication with Earth, and Lunar topography. The Moon's position in the solar system and its relationship with the Earth and the Sun open an important topic on the selection of regions for future settlement. Therefore, the area around the South Pole is the most attractive location for Lunar exploitation [34]. The orientation of the Moon's rotation axis, which is tilted \(1.5^{\circ}\) from the ecliptic plane, makes the Lunar poles mainly Permanently Shadowed Regions (PSRs), meaning that the floors of some craters from these regions never receive sunlight. Consequently, the temperature in these characteristic craters allows the sustainability of Lunar ice. This confirms a hypothesis based on evidence of the potential existence of water on the Moon, thus guaranteeing the possibility of living and working on the Moon [35]. However, regions which never receive direct solar illumination still receive sunlight coming to them indirectly, scattered, with the addition of starlight. This issue is elaborated in several statistics on measured quantities of solar power supply in all regions, including the polar ones [36; 37; 38].  
Important conclusions on the South Pole area are drawn from results of processing topographical, geological, and environmental datasets collected by diverse Lunar missions (Apollo, Luna, Molnya, Chandrayaan, Chang'e, Lunar Reconnaissance Orbiter (LRO), Clementine [36; 39], SELENE [40], etc.), making this area the best candidate for permanent Lunar settlement. Figure 1 introduces the polar-based region, where high attention is given to Shackleton Crater, located inside the rim of the South Pole Aitken (SPA) Basin [36; 39; 41; 42].  
Furthermore, communication with the Earth plays an important role in site selections. That is why the potential sites in the South Pole region based near the Shackleton Crater rim and Mons Malapert crater fulfill the requested parameters. They are noted as the best areas for a relay station due to high altitude, topographic characteristics, and visibility with the Earth [43]. In the case of simultaneous establishment of the laser relay on the North Pole, communication with the Earth will be 100% covered. Two separate systems per pole with 100 km distance between them will enable robust local wireless communication coverage [36].  
Concluding on the selection of the study area for this research, the analysis of the discussion on the Moon's South Pole region characteristics showed that Shackleton Crater fulfills all technical and environmental requirements. Therefore, simulation and statistical analysis of positioning accuracy will be carried out using Shackleton Crater as a case study. The presented methodology is replicable to other regions as well as other celestial bodies.
## 3 Applications of the Tactile Internet
### eHealth  
eHealth is a significant concern for human health and safety. A large portion of the TI sector is networked wirelessly to propel and provide proper services to humans. An efficient way could be found where information-based healthcare services can make superior use of information to upgrade patient security. Furthermore, competencies such as efficiency, robustness and reliability of the healthcare system's services in teleservices (rehabilitation, surgery, and diagnosis), TI infrastructure and IEEE wireless standards need  
Figure 4: The platooning of self-driven vehicles maintaining a fixed distance ’D’ between them.  
Figure 5: An automated production assembly line where the user is giving instructions wirelessly on a tablet in industry.  
improvement [25]. It is observed that any delay in a non-real-time system can prompt a mistake in patient behaviour in the case of remotely assisted (robotic) telepresence surgery [26].  
To overcome distant geographic places and increment access to medical services, telemedicine uses the TI infrastructure with wireless communication. A time could come when medical experts could be present (virtually) anywhere and without paying attention to doctors' location using advanced tele-diagnostic tools. Hence and so forth, without a doctor physically present at the patient's location, a telerobot can treat the patient operated by a doctor (remotely). Additionally, audio and visual information will be provided, along with haptic feedback. This will improve the possible future application of TI in health care which will incorporate telediagnosis, telesurgery and telerehabilitation.  
It is fundamental to see that the capabilities of machines are growing. Therefore, the TI should give aid to humans rather than finding a replacement for them. This emergence of the TI should facilitate new options that enable humans by providing a hike in their career based on yields. Figure 6 illustrates robotic telesurgery with a master (operator) and slave (patient), which are physically present in remote locations. The operator's location will be equipped with a high-quality camera and controlling devices with haptic feedback. Therefore, the user (doctor) would feel being physically present in the patient's location.
# Analysis of Hydrological Characteristics of Blue Nile Basin, Nishe Watershed
## 3 Results and Discussion
### Hydrological Water Balance of the Watershed  
The determination of water balance is one of the most essential variables addressed when determining whether the model is suitable for any particular application in the watershed. The SWAT model was used effectively for assessing the relevant components of water balance of the catchment. The investigation of water balance components was computed at the outlet of the watershed by using the SUFI-2 algorithm since it is slightly better than the other algorithms. Precipitation, surface runoff, lateral flow, base flow and evapotranspiration are the most essential components of the water balance of the watershed [9; 46]. A water balance equation is used to quantify the major hydrological processes. This study investigated the model findings by establishing season-based water balance to explain the watershed behavior for the wet season, short rain season and dry season. For seasonal analysis, seasons in Ethiopia were classified into three seasons in the year based on the rainfall magnitudes.  
The short rain season occurs between February and May, followed by the wet season between June to September. The other season is the dry season between October to January  
Figure 8: Monthly observed and simulated stream flow using PSO.  
and which can be characterized generally over the majority of the country. The results show that the watershed receives around 19%, 69%, and 12% of precipitation during the short, long and dry seasons respectively. The received precipitation was lost due to evapotranspiration by 29%, 34% and 37% for each season, respectively. The surface runoff contributes to the catchment by 5%, 86% and 9% during the respective seasons. The catchment contribute high surface runoff on the northwestern and downstream of the watershed (Figure 9). The sub-basins that contribute high ground water were mostly upstream of the catchment. The monthly and annual water balance of the Nashe watershed were shown generally in Figures 10 and 11 respectively. The summary of the average monthly spatial distribution of water balance components of the watershed is presented in Figure 9.  
Figure 10: Monthly average water balance of the study area.  
Figure 9: Spatial distribution of hydrologic components of the Nashe watershed.
## 3 Results and Discussion
### Controlled Release  
Figure 5 shows the release behaviors of the Pyr@M15, Pyr@M100, Pyr@M200, and Pyr. A certain proportion of ethanol is usually added to increase the solubility of pesticides due to the poor solubility of most pesticides. In order to completely dissolve the Pyr in the release medium, 20% PBS aqueous ethyl alcohol solution was used as the release medium. In vitro lab studies revealed that in comparison with Pyr@M15, Pyr@M100, Pyr@M200, and Pyr showed a better release of up to 400 h. After 400 h, the cumulative release rates of Pyr from the Pyr@M in the medium reached more than 60%. On the other hand, Pyr dissolved slowly at only 40%, due to its poor water-solubility. This suggested that the nanoparticles increased the solubility of insoluble drugs, which promoted the release of pesticides. It was mentioned in Section 3.1 that the average particle size of Pyr@M15, Pyr@M100, and Pyr@M200 was about 15, 100, and 200 nm, respectively, and the particle size Pyr in technical material (TC) was about 3 \(\upmu\)m, much larger than the nanoparticles. As the particles size decreased, particle number and surface area would increase, which improved the solubility of the active ingredient. From Figure 5, the release curves of different particle sizes almost coincide, this indicated that size had no clear difference impact on the release rate. The effect of particle size on release, however, was found to be minimal.  
To further clarify the release principle, the Pyr release data from Pyr@M15, Pyr@M100, and Pyr@M200 were fitted using the Ritger-Peppas equation [40], M\({}_{t}\)/M\({}_{\infty}\) = k\({}^{\text{tn}}\), where M\({}_{t}\)/M\({}_{\infty}\) is the accumulative release (%) of Pyr from the nanoparticles at time t; k is the kinetic constant; n is the release exponent; the fitting plots are shown in Figure 5b. The kinetic parameters obtained from this fitting are summarized in Table 4, The n value indicated the type of release mechanism. It was observed that all n values exceeded 0.45 but were lower than 0.89, indicating a non-Fickian transport [41]. The release results demonstrated that the different sizes of carbon quantum dots-MSN loading pesticide did not change the release mechanism.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Carrier Material** & **Solvent** & **Mass Ratio a** & **Loading Content (\%) b** \\ \hline M100 & Acetonitrile & 2:1 & 4.25 \(\pm\) 0.68 \\ M100 & Methanol & 2:1 & 5.86 \(\pm\) 1.66 \\ M100 & Dichloromethane & 2:1 & 18.86 \(\pm\) 0.61 \\ \hline M15 & Dichloromethane & 2:1 & 8.8 \(\pm\) 0.07 \\ M100 & Dichloromethane & 2:1 & 18.86 \(\pm\) 0.61 \\ M200 & Dichloromethane & 2:1 & 23.06 \(\pm\) 0.43 \\ \hline M15 & Dichloromethane & 5:1 & 23.43 \(\pm\) 0.42 \\ M100 & Dichloromethane & 3:1 & 22.63 \(\pm\) 0.23 \\ M200 & Dichloromethane & 2:1 & 23.06 \(\pm\) 0.43 \\ \hline \hline \end{tabular}  
* Mass ratio of Pyr to carbon quantum dots-MSN. b Loading content values are mean \(\pm\) SD of the three replicates.  
\end{table}
Table 3: Results of the loading content of Pyr into carbon quantum dots-MSN with different sizes.
## 1 Introduction
In addition, the integrated QoE is consistently high with the implementation of Ac-VHO. The main contributions and innovations that we have made are as follows:  
* Our proposed Ac-VHO scheme, based on a VLC-RF heterogeneous networking environment, introduces VHO decision making for each of the three types of RTA encountered by MTs for the first time. Additionally, it determines the activation status of an RTA. * The Ac-VHO scheme incorporates separate user-specific psychological tolerance time intervals for different types of RTA. This approach enhances the flexibility and inclusiveness of the VHO residence time. * Our scheme makes VHO decisions by considering various factors such as VLC link quality degradation and the activity of different types of RTA. It combines elements from the D-VHO, dynamic D-VHO, and HA-VHO schemes, resulting in a reduced number of unnecessary handovers. * For an MT moving randomly within an indoor space, we optimize the handover dwell time by taking into account the MT's RTA usage requirements and the impact of \begin{table}
\begin{tabular}{c c} \hline \hline
**Environmental Requirement** & **Special Scenario** \\ \hline Anti-electromagnetic interference & Hospitals, mines, and laboratories \\ Confidentiality & Military academies, military bases, \\  & air defense offices \\ High communication efficiency and capacity & Commercial office space and indoor smart \\  & home environments \\  & Large coverage area & Underground parking lots and buried shelters \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Special Scenarios for VLC heterogeneous networking. movement speed on the QoE. This optimization ensures a stable and highly integrated QoE even when the MT's speed changes.
# Ionospheric Narrowband and Wideband HF Soundings for Communications Purposes: A Review
## 2 Ionosphere Characteristics
### Technical Procedures and Metrics to Analyze the Ionospheric Variations
#### 2.4.2 Narrowband and Wideband Techniques: SNR, Availability and Time and Frequency Dispersion  
Narrowband sounding is commonly used to monitor the channel and gather information on the reliability of HF communications. For instance, the reception of WWV Standard Frequency transmissions can be used to estimate the range of frequencies with good availability, to study its relationship with the sunspot number and even characterize the channel during disturbed periods when the ionosphere is under the effect of a geomagnetic storm. When assessing the effect of a disturbance on a communication system it is not sufficient to consider only signal strength. The nature of the signal must also be considered and hence the depth and rate of fading and the time and frequency spreading of the signal must be studied. Wideband sounding is then used to describe these distortion effects that suffer the transmitted signals on a given bandwidth.  
There are many techniques to sound the channel and to collect the required propagation parameters needed to design a communication link. Reference [27] revises several techniques to sound a radio channel (i.e., single-tone continuous wave, spaced tone waveform, pulse waveform, pulse compression waveform and coded pulse signals). All of them use different kind of waveforms designed to detect the prevailing propagation conditions. Furthermore, several architectures and methodology have been proposed in the literature [28; 29; 30] to obtain the key parameters of the ionospheric channel, such as the following: (i) Frequency and temporal dispersion by means of the scattering function, (ii) Time of flight, (iii) Signal to noise ratio, (iv) Link power attenuation, (v) Phase stability, (vi) Angle of arrival and (vii) Independent measurements for ordinary and extraordinary rays.
## 3 Data and Methods
### Deriving Monthly Net Primary Production (NPP) Data Set  
The conversion from the GIMMS3g NDVI into estimated NPP was done from per-pixel correlations between the 11 overlapping years of monthly GIMMS3g NDVI and MODIS NPP (2000-2010) data. The per-pixel strength of the linear relationship between these two data sets was determined by calculating the Pearson correlation coefficient for the 11-year monthly observations (Figure 3). Meanwhile, the significance value of each pixel was used to assess the confidence of its corresponding correlation coefficient. The 11 overlapping years were split into two periods: 7 years for model calibration and 4 years for model validation. A bootstrapping regression model was used for the model calibration, with the pixels of significant and positive correlation coefficient with the monthly MODIS NPP (2000-2006) as the dependent variable and the monthly NDVI as the independent variable. The bootstrapping regression model is a nonparametric approach to statistical inference  
Figure 2: Map of land cover for the Okavango, Kwando, and upper Zambezi (OKZ) catchment.  
which is more general and robust than traditional distributional assumptions [32]. The outputs, including per-pixel mean slope and intercept, were then used to validate and predict the per-pixel NPP time series. Figure 4 illustrates the outputs of the bootstrapping regression model for one example pixel (Lat: \(-15.44^{\circ}\)S; Lon: \(23.25^{\circ}\)E). As such, a monthly time series of estimated NPP pixel level values were created for the GIMMS3g NDVI data, for the entire study area from 1982 to 2010. These data are then utilized in the model evaluation (2007-2010) and the remaining analyses. The eddy covariance data from the CarboAfrica database were used to validate the MODIS NPP dataset which is the benchmark of our estimates. There are two eddy covariance flux sites of savannas within our study area: the Botswana site (Maun, \(19.9165^{\circ}\)S, \(23.5603^{\circ}\)E) and the Zambian site (Mongu, \(15.4388^{\circ}\)S, \(23.2525^{\circ}\)E). The former is covered by typical propane woodland, while the vegetation of the latter is broadleaf deciduous miombo woodland. Both vegetation types are representative in our study area. The Level-4 records are available with GPP on varying time intervals including hourly, daily, weekly, and monthly. Although there was still much uncertainty of NPP/GPP ratios of different ecosystem types, here a value of 60% was used to estimate NPP fluxes from Level 4 estimates of GPP based on the empirical relationship from [PERSON] _et al._[33].  
Figure 3: Spatial pattern of correlation coefficient between Moderate-resolution Imaging Spectroradiometer (MODIS) monthly net primary production (NPP) and third generation Global Inventory Monitoring and Modeling System (GIMMS3g) monthly normalized difference vegetation index (NDVI) from 2000 to 2010.