esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction  
The environmental pollution phenomenon has a significant impact on the construction buildings, especially on the cultural heritage ones, causing important damages, which require complex maintenance or repair interventions, involving significant material and economic cost [1]. Therefore, the development of the new materials capable of providing efficient treatments for the heritage buildings remain an important objective [2].  
The literature data reveals that graphene oxide (GO), resulting from the graphite oxidation, is a versatile material, that can be successfully used in several activity fields, such as electronics, environment, biomedicine and why not, in construction [2, 3, 4]. The functional groups containing oxygen, i.e., hydroxyl (-OH), epoxy (-C-O-C), carbonyl (-C=O), carboxyl (-COOH), which are present both on the surface of GO sheets and on their edges [5, 6, 7, 8], allow the GO functionalization. The silanization of GO, by functionalizing its reactive groups with organosilanes, can lead to an improvement of the properties of the construction materials in which they are introduced [9, 10].  
According to the literature data, GO also has a good antibacterial activity due to its ability to generate reactive oxygen species (ROS) but also due to the shape edges of the GO sheets, which are able to penetrate the cell membranes of the bacteria, thus leading to their death. Moreover, the functionalization of GO sheets with ZnO might improve the antibacterial effect of the materials in which they are introduced because ZnO generates ROS, while the accumulation of Zn nanoparticles in the cytoplasm can inhibit the cell loads. On the other hand, the addition of the Ag nanoparticles can accelerate the destruction of bacteria causing constant cell membrane damages, leading to increased permeability and disruption of the bacterial DNA replication [11].  
The aim of the present study was to synthetize and characterize various powders of graphene oxide (GO), GO combined with silver (GO-Ag) or Zn oxide (GO-ZnO). The powders were silanized with (3-aminopropyl) triethoxysilane (APTES). The non-silanized powders (GO, GO-Ag and GO-ZnO), as well as the silanized ones (GO-APTS, GO-Ag-APTES and GO-ZnO-APTES) were characterized by Fourier Transform Infrared Spectrometry (FTIR) and Scanning Electron Microscopy (SEM) before and after the silanization process. The GO, AG-GO, GO-ZnO, GO-Ag-APTES and GO-ZnO-APTES powders were also investigated by Thermogravimetric Analysis (TG/DTA) and Ultraviolet-Visible Spectroscopy (UV-Vis). Furthermore, the antibacterial activity of all synthesized powders against _Streptococcus mutans_, _Porphyromonas gingivalis_, _Enterococcus faecalis_, _Escherichia coli_ and _Staphylococcus aureus_ was also evaluated.  
These materials are intended to be used in a future work as additives for preparing hydraulic mortars with improved adhesion to the original support materials and with antibacterial properties that could be effectively applied for the heritage buildings [12].
# Route Availability as a Communication Quality Metric of a Mobile Ad Hoc Network
###### Abstract  
Using ad hoc communication between mobile terminals, MANETs (mobile ad hoc networks) are independent of any communication infrastructure but their communication quality can degrade because, as terminals move about in the service area, routes are constantly disconnected and then re-established. There has been no proposal for a quality metric that models this unstable state, i.e., route nonuniformity. This paper proposes a new concept of route availability (RA) as a metric of route nonuniformity in a MANET and verifies how effectively it represents the quality of service (QoS) of a network or the quality of experience (QoE) of video streaming. We have built an environment that emulates a MANET capable of video streaming, and developed a method of measuring RA for two representative MANET routing methods: AODV (Ad hoc On-Demand Distance Vector) and OLSR (Optimized Link State Routing). We have examined the relationship between RA and conventional network QoS metrics: packet loss rate and throughput. We have also checked RA using a subjective quality assessment test.  
MANETs; route availability; communication quality metrics; QoS; QoE; video streaming +
Footnote †: journal:  
_Future Internet_**2018**, _10_, 41; doi:10.3390/610050041
## 3 Study Area and Data
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Parameter** & **Product** & **Spatial Resolution** & **Temporal Resolution** \\ \hline LAI & MCD15 & 1 km & 4 days \\ Black-sky albedo & MCD43 & 1 km & 16 days \\ White-sky albedo & MCD43 & 1 km & 16 days \\ Land cover & MCD12 & 1 km & Yearly \\ \(k\) & Calculated by direct and total PAR & 1 km & Hourly \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Input data for FPAR inversion. Figure 3: Schematic of the SunScan canopy analysis system. _Remote Sens._**2015**, \(7\)  
\[L_{con}\downarrow\ =\ L_{\
u}+L_{con}\uparrow+L_{s} \tag{22}\]  
\[L_{s}\ =\ L_{sol}\downarrow-L_{sol}\uparrow \tag{23}\]  
Then, the vegetation canopy FPAR can be expressed as Equation (24):  
\[FPAR\ =\ \frac{L_{\
u}}{L_{con}\downarrow} \tag{24}\]  
Long time observation are helpful in obtaining measured canopy FPAR data under different weather conditions and at different times and is also important for the analysis of FPAR characteristics. However, using the SunScan canopy analysis system to obtain a long time of canopy FPAR is time consuming and laborious. The PAR Quantum Sensor is designed to provide accurate, continuous PAR measurements. Therefore, upward and downward photon flux sensors (PQS1) were erected on crop, forest and meadow land surfaces (Figure 4) in the Heihe River Basin. The sensors can observe upward PAR (PAR\(\uparrow\)) and downward PAR (PAR\(\uparrow\)):  
\[PAR\downarrow-PAR\uparrow\ =\text{APAR}_{\text{plant}}+\text{APAR}_{\text{soil}} \tag{25}\]  
\[APAR_{plant}\ =\ FPAR_{plant}\times PAR\downarrow \tag{26}\]  
where \(APAR_{plant}\) is the PAR absorbed by the plant canopy and \(APAR_{soil}\) is the PAR absorbed by the soil background. These observed \(APAR\) data were used as indirect validation data for the DnD model.
# Safety Effects of Freeway Hard Shoulder Running
## 2 Methodology
### Empirical Bayes Method  
The aim of this study was to evaluate the safety effect of HSR by applying the EB methodology [40; 41] to crash data from South Korea for before and after HSR trials. The EB method is commonly used by transportation safety analysts for conducting different types of safety analyses, such as before-after studies and hotspot analyses [42; 43; 44; 45]. It enables researchers to control for several critical factors such as regression-to-the-mean effect, long-term trends, and exogenous changes in traffic volume [47].  
In order to apply the EB method, we need to develop a safety performance function. The negative binomial model is selected because of the presence of overdispersion in the data. The general form of the negative binomial model is given below:  
\[p(Y_{i}=y_{i})=\frac{\Gamma\big{(}y_{i}+a^{-1}\big{)}}{y!\Gamma(a^{-1})}\left( \frac{a\mu_{i}}{1+a\mu_{i}}\right)^{y_{i}}\left(\frac{1}{1+a\mu_{i}}\right)^{a ^{-1}} \tag{1}\]  
\[\mu_{i}=\exp(\beta_{0}+\beta_{1}x_{i1}+\beta_{2}x_{i2}+\ldots+\beta_{k}x_{ik}), \tag{2}\]  
where  
\(y_{i}\) is the crash count at site \(i\);  
\(\mu_{i}\) is the expected number of crashes at site \(i\);  
\(\beta_{0}\), \(\beta_{1}\), \(\beta_{k}\) are the parameters to be estimated;  
\(x_{i1}\),..., \(x_{ik}\) are the explanatory variables for neighborhood \(i\);  
\(\alpha\) is the dispersion parameter.  
The EB method is then applied to determine the expected crash occurrences:  
\[\mathrm{k}=\lambda\mathrm{w}+(1-\mathrm{w})\,\mathrm{K} \tag{3}\]  
\begin{table}
\begin{tabular}{c c c c} \hline
**Variable** & **Description** & **Mean** & **Std Dev** \\ \hline A & Annual average daily traffic (veh/day) & 80,792.97 & 55,698.64 \\ T & Daily average truck volume (veh/day) & 4373.10 & 3267.31 \\ V & Average speed (km/h) & 98.41 & 7.45 \\ N & Number of lanes & 2.86 & 0.91 \\ L & Length of site (km) & 7.98 & 4.75 \\ LW & Lane width (m) & 3.60 & 0.03 \\ SW & Shoulder width (m) & 3.62 & 0.05 \\ \hline \end{tabular}
\end{table}
Table 2: Summary statistics of reference sites.  
\[\text{w}=1/(1+\lambda\ \alpha)\]  
where  
**k** is the expected number of crashes before treatment;  
**\(\lambda\)** is the model-predicted number of crashes before treatment;  
**w** is the weight given to the model-predicted number of crashes;  
**K** is the recorded number of crashes before treatment.
## 3 Proposed Method  
### Improved Transfer Component Analysis  
#### 3.1.1 Dispersion Factor  
Any sample is mixed with noise to a greater or lesser extent. When feature transfer occurs, noisy features are easily amplified, causing the mapped samples to diverge. It is necessary to improve the intraclass aggregation of the mapped samples to reduce the impact of noise and facilitate classification. Based on this, according to the idea of variance, the dispersion factor \(S\) is proposed to measure the aggregation degree of the intraclass samples. The calculation of the dispersion factor \(S\) is shown in Equation (12).  
\[S=\frac{1}{n}\sum_{j=1}^{C}\sum_{i=1}^{m_{j}}d_{i}^{j} \tag{12}\]  
where \(n\) represents the total number of samples, \(C\) represents the number of categories, \(m_{j}\) represents the number of samples in class \(j\), and \(d_{i}^{j}\) represents the Euclidean distance between the \(i\)th sample in class \(j\) and the cluster center of the corresponding category. The calculation of the Euclidean distance is shown in Equation (14).
# Hierarchical Resource Management for Mega-LEO Satellite Constellation
## 1 Introduction
For spectrum planning at the NCC, spectrum data mining methods based on causal regression, LSTM prediction, and anomaly detection are presented, and spectrum planning based on game theory, anomaly algorithms, machine learning, and knowledge graphs is summarized. Service area planning needs to comprehensively consider multiple parameters, which can be obtained by multiple algorithms, such as satellite coverage area calculation, interference avoidance calculation, and residual time calculation, etc. Then, a heuristic beam scheduling algorithm is studied for beam-hopping satellite systems. * In this study, we provide an assessment of effectiveness and efficiency, along with the primary performance indicators. These metrics are essential for evaluating the overall performance of our proposed system. We conduct some simulations to validate the effectiveness and efficiency of our architecture, approaches, and algorithms. The organization of this paper is presented as follows: In Section 2, we discuss related works on resource management in satellite communication systems and SINs. Section 3 examines the correlation and influencing factors of resource management in the MLSCS. Section 4 proposes a three-layer architecture for implementing system resource management. Detailed functions and procedures are described in Section 5. In Section 6, we depict the approaches and algorithms for each component and procedure. Section 7 presents performance assessments and indicators. Finally, Section 8 concludes the paper and outlines future work.
# CFD-Simulink Modeling of the Inflatable Solar Dryer for Drying Paddy Rice
## 3 Results
### Validation of the Drying Model  
#### 3.2.1 Simulation of the Air Temperature during the Drying Process  
Figure 10 presents the solar radiation, the ambient temperature, and the relative humidity during the three experimental batches of solar drying of paddy rice in the ISD. The solar radiation during the rainy season shows higher variations due to clouds and sudden rainfall. When the sun rises, the ambient relative humidity declines gradually and keeps to a minimum value of 55% at around noon. This corresponds to the maximum temperature of 36 \({}^{\circ}\)C. The ambient temperature during nighttime reaches about 22 \({}^{\circ}\)C, while the relative humidity increases to 88%.  
Figure 8: Contour plots of the simulated and experimental airflow distribution at the height of 0.08 m across the ISD.  
Figure 9: Simulated and experimental air velocity along the centerline at the height of 0.08 m over the ISD length.  
The simulated temperature was validated against the experimental paddy rice data, as shown in Figure 11. It can be observed that the temperature increase in the drying area was well reproduced throughout the drying process. During the daytime, the average drying air temperatures varied from 5 to 25 \({}^{\circ}\)C above the ambient temperature. The highest experimental and simulated drying temperatures were 63.7 and 60.2 \({}^{\circ}\)C at 13:05 and 12:00, respectively. The high fluctuation of weather conditions such as cloudiness or sudden showers influenced the temperature in the ISD. This phenomenon can be also observed from the simulated temperature. Therefore, the simulation was in good agreement with experimental data.  
Figure 10: The variation of ambient temperature, relative humidity, and solar radiation for the three experimental batches during rainy season.
## 2 Materials and Methods
### Data Collection  
The experiential walk and on-site questionnaire survey were conducted on sunny days with an Air Quality Index of less than 60 and wind speed below 5 m/s in July 2021.  
To avoid individual perceptive differences that may have been caused by differences in age [68], educational background [69] and state of being alone or with company [70], 20 young adults aged between 20 and 30 years old were recruited from a local university to participate in the experiential walk and on-site questionnaire. The recruited subjects all had normal or corrected-to-normal visual acuity, normal colour vision and hearing. The ratio of male to female subjects was controlled at 1:1. The survey was ethically approved, and informed consent was obtained from each subject in advance. Necessary training and introduction were also provided before the survey was formally taken.  
The 30 recruited subjects were divided into four groups, and each group was led by one researcher, travelling through the five UGSs in different orders. Subjects were asked to walk along the designated routes in each site alone for at least one round trip, and the time taken to experience each route needed to be over three minutes. The questionnaire survey was completed afterwards. Each of the 30 subjects filled out a questionnaire for each of the 14 experiential routes. A total of 420 responses were thus collected. Noise data, such as an incomplete questionnaire or questionnaires with the same ratings for every indicator, were manually removed. The number of valid responses was 279 (approximately 20 per route). The sample size was in line with previous similar studies, which stated that the total number of valid responses should be over 100 [71].
# A New COVID-19 Detection Method Based on CSK/QAM Visible Light Communication and Machine Learning
## 2 State-of-the-Art Techniques  
This section presents the state-of-the-art techniques used for the application of VLC in underground channels. This is followed by the presentation of a model of a channel based on colour shift keying with quadrature Amplitude modulation (CSK/QAM) mapping, the use of the Galois Field Mapping/Galois Fields Demapping interface between the human side of the machine and the signal processing communication channel, and finally, AI-based procedures to replace human processing. Note that COVID-19 and pathogens in general are most likely to spread rapidly in indoor settings, such as hospitals or industrial settings like mine tunnels. As evidenced by events of the last three years, this can result in a decrease in a country's GDP and crippling of its economy.
## 4 Results  
### Photogrammetry and Mass Balance  
The photogrammetrically calculated model of the hillslope debris flow is shown in Figure 3. The model allows measuring the precise runout and displaced masses (Figure 4b). Since photogrammetrically-created DEM cannot be effectively filtered for vegetation, densely vegetated areas were discarded in order to solely compare real ground points (Figure 4a; vegetation marked in grey). Security measures and clean-up work were carried out at various locations compared to the in situ photos immediately taken after the debris flow (Figure 1). Nevertheless, the fissure, runout and deposits were mostly unaltered and are clearly recognizable in the model, showing a lasting effect on slope morphology.  
Figure 4: **(A) Photogrammetrically-calculated model of the hillslope debris flow with overlying true-color mesh; densely vegetated areas marked in grey. (B) Elevation difference between the photogrammetrically-generated DEM from 2 February 2022 and an ALS-generated DEM from 2018. (C) Elevation change in the drawn transect (yellow line in B) with distinct morphological markers shown as 2D graph.**The total length of the hillslope debris flow from the initiation point to the outermost deposition layer is 184 m. The resulting scar in the initiation area is 15 m wide on average with a maximum depth of 6 m. This widely exceeds the assumed depth for unconsolidated parent material (or sediment cover) at this location. Such underestimated sediment covers are a typical feature that was observed to be associated with numerous mass movements triggered by the torrential rainfall event of 14 July 2021 in the Eifel region [2].  
Based on a comparison with the airborne LiDAR Survey (ALS) from 2018, we can show that approximately 1350 m\({}^{3}\) of material moved downslope in the scar. In order to stabilize the forest path, an earth wall with a height of 2.50 m was built at the end of the scar, partially using debris flow material. Below the path, material was re-dumped into the erosion channel on an area of 87 m\({}^{2}\).  
The runout track is 130 m long with a maximum incision of 1.5 m (Figure 4C; cf Figure 1B). For an event of this magnitude, this incision throughout the runout track is relatively low and could be attributed to a moderate flow velocity. The deposition area behind the affected house is 238 m\({}^{2}\) in size. In the course of shoring works, it was leveled up to 2 m above the original ground surface. In total, the mass balance of the whole debris flow runout suggests that 1090 m\({}^{3}\) of material was relocated during the event, including post-event anthropogenic measures.
# Numerical Analysis on Self-Propulsion of a Waterjet-Propelled Ship with Different Propulsion Models
## 2 Numerical Model
### Grid System and Boundary Conditions  
Considering the symmetry of the geometry and flow, half of the model composed of a half hull and a waterjet system is used for self-propulsion simulations, and the bare hull simulations are accomplished via a half hull. Figure 3 shows the computational domain and boundary conditions. With respect to the computational coordinate system, a Cartesian Earth-fixed coordinate system O-XYZ is used and defined as follows: the origin O is on the symmetry plane (y = 0) of the ship located at the intersection of the calm waterline and midship section in the longitudinal direction; the positive directions of the \(X\)/\(Y\)/\(Z\) axis are the directions from the stern to the bow, mid-ship to the port side and bottom of the ship to its deck, respectively. Body-fitted O-type grids are generated around the hull geometry, and mesh refinement strategies are applied near the hull and the gas-liquid interface areas, which is consistent in either bare hull or self-propulsion simulations in particular. Figure 4 exhibits the computational grid system of the waterjet-propelled ship model. For self-propulsion simulations, the computational domain is divided into static and rotational regions, separated by interface boundaries. The mesh of waterjet system is shown in Figure 5, and the mesh refinement is implemented for the tip clearance between impeller blade and impeller shroud.  
Figure 4: Computational grid system of the waterjet-propelled ship model.  
Figure 3: Computational domain and boundary conditions.  
The velocity inlet is located ahead of the bow, with a distance of \(L_{pp}\). Additionally, the pressure outlet is situated \(3L_{pp}\) behind the stern to completely develop the wake field. To avoid wave reflection, the damping length is set to \(0.5L_{pp}\). The side, top, and bottom are far-field boundary conditions, the mid-ship section is a symmetry boundary condition, and all solid surfaces are no-slip wall boundaries.
###### Abstract
Specifically, UAVs can collect the traffic density information and the state of vehicles connectivity on the ground and exchange them with vehicles through the vehicle-to-everything (V2X) communications. The MEC architecture can reduce the computational delay, reduce energy requirement, and improve the computation ability by distributing the latency-sensitive tasks to MEC servers around the vehicles, which can be widely used in the automatic drive, the multimedia entertainment service, the intelligent traffic management, and the geographic information service. The main contributions are summarized as follows. * We propose an MEC-enabled UAV-assisted VANET to provide vehicles with the low latency and reliable computing services through UAVs. Specifically, we adopt comprehensive task processing delay as the optimization objective by jointly considering the transmission model and the security assurance model from the vehicle to the MEC server on UAV, and the task computation model of the local vehicle and the edge UAV. * We design a network optimization scheme by jointly considering the task offloading, the resource allocation, and the security assurance for VANETs. Moreover, to fully exploit the advantages of the MEC-enabled UAV-assisted VANET architecture, we use UAVs for boosting VANETs communications to improve VANETs' computation ability. Furthermore, we propose an efficient iterative algorithm based the relax-and-rounding method and the Lagrangian method, which can effectively solve the joint optimization problem. * We conduct simulations to evaluate the performance of our proposed scheme. The simulation results indicate that our designed MEC-enabled UAV-assisted VANET architecture is superior to the traditional ground-based VANETs. In addition, our proposed scheme can achieve significant performance superiority compared with other schemes in the successful task processing ratio and the task processing delay. This paper is organized as follows. Section 2 overviews the related works. In Section 3, we introduce the considered system model and problem formulation. Section 4 describesthe proposed scheme. Simulation results are presented in Section 5, after which a discussion is presented in Section 6. Finally, we conclude our paper in Section 7.