esa-sceva/satcom-chunk-collection huggingface dataset:
# Application of Reflectance Indices for Remote Sensing of Plants and Revealing Actions of Stressors
## 4 Problems of Measurement and Analysis of Reflectance Indices
### Changeability of Illumination Parameters  
The changeability of the illumination parameters is a very important problem for the measurement of RIs [17; 39]. In laboratory conditions, the geometry of the plant illumination in experiments is controlled and corresponds to the aim of the investigation. However, even in this case, the heating of the lamps in the light source, which causes changes in the illumination spectrum, or the blinking of these lamps can negatively influence the reflectance measurements. This changeability of the illumination parameters can be strongly increased under the environmental conditions; e.g., clouds cause illumination blinking and increase light scattering in the atmosphere. The problem of the changeability of light parameters can be solved by periodical calibrations using white and black cards, which serve as standards of absolute reflectance and absorption, respectively [22]. For example, the atmospheric influence can cause up to 50% of the difference between NDVI without corrections and NDVI corrected by using white and black cards [141]. This influence of the light parameters can be corrected using Equation (1) [141]:  
\[Reflectance=\frac{I-I_{B}}{I_{W}-I_{B}} \tag{1}\]  
where \(I\), \(I_{W}\), and \(I_{B}\) are intensities of light reflected from plant, white standard, and black one, respectively.  
Effects of the illumination parameters can also be minimized by averaging spectra [145]. However, this method is limited by plant variability and influence of atmosphere and soil, which can be complex and non-linear.  
On the other hand, normalized RIs can be corrected on the basis of only the white standard in accordance with Equation (2) [155]:  
\[RI=\frac{I_{1}-I_{2}\Big{(}\frac{I_{W1}}{I_{W2}}\Big{)}}{I_{1}+I_{2}\Big{(} \frac{I_{W1}}{I_{W2}}\Big{)}} \tag{2}\]  
where \(I_{1}\) and \(I_{2}\) are intensities of the reflected light in plant at wavelengths one and two, respectively; \(I_{W1}\) and \(I_{W2}\) are intensities of the reflected light in the white standard at wavelengths one and two, respectively.  
Finally, the influence of the parameters of the changeable background light can be eliminated on the basis of the active illumination of the investigated plant by pulses of the measuring light [17; 39]. In this case, two images are used (the image measured under only the background light, and the image measured under combination of the background light and measuring light with the standard spectrum). The intensity of the reflected light is calculated as the difference between these images. This method allows to exclude periodic calibration of the reflected light [139]. However, the method can be used at only small distances from plant objects and can be relatively slow because two images should be measured; moreover, short-term fluctuations in the intensity of the light can cause errors when using this method.
## 3 Microbial Interactions in Plant Microbiomes
### Composition and Dynamics of Microbial Communities in the Rhizosphere and Endosphere  
The plant microbiome is a community of microorganisms that live in and around plants, forming a dynamic microbial ecosystem [13]. Like the human microbiome, it plays a crucial role in supporting its host by interacting with the surrounding soil, air, and water. Plant-associated microorganisms include bacteria, fungi, viruses, and some algae, and these are found in all plant tissues. Microbe-microbe and microbe-plant interactions occurring from the microbial presence in plants are involved in regulating plant health and vigor [14].  
The plant microbiome is divided into three main domains--the endosphere, rhizosphere, and phyllosphere. The endosphere consists of microorganisms living inside plant tissues, either within or between cells [15], and includes the plant's vasculature and seeds. The phyllosphere consists of microbes that inhabit the plant's aerial parts, such as leaves and stems [16]. The rhizosphere is the region in the soil surrounding the plant's roots, where microbes interact closely with plant and soil components [7]. The microbes survive within the plant as endophytes or on outer surfaces as epiphytes [17], and colonization involves the formation of biofilms of different genera and species. The composition of a plant's microbiome is influenced by factors such as species, age, health, genetics, and soil conditions. Even two plants of the same species can host different microbial communities based on their environment [18; 19; 20]. These microbial colonization zones differ in terms of their environmental factors, such as nutrient sources from the plant's metabolites and exposure to environmental conditions [21; 22; 23]. These variations partly explain the differences in microbial composition, diversity, and abundance between the different plant habitats.
## 1 Introduction
* Scalability: The architecture is designed to be scalable, thus making it capable of accommodating the growing number of connected vehicles and diverse data transactions within VANETs, thereby making it suitable for the expanding scope of smart city projects. Together, these contributions form a comprehensive solution that addresses the ongoing challenges related to security, privacy, and reliability in VANETs. Going forward, the rest of this document is organized as follows:  
* Section 2 provides a critique of the current solutions and underscores their limitations. This section delves into the myriad of security challenges in VANETs, thereby elucidating the predominant types of attacks that these networks are susceptible to. Additionally, it explores a range of proposed security measures designed to mitigate such attacks, thus presenting an insightful overview of the security landscape in VANETs [25]. In addition, this section offers a detailed taxonomy of the security solutions tailored for VANETs, thereby dissecting various types of security measures that have been proposed. It thoroughly evaluates the advantages and drawbacks of these solutions, thereby providing an extensive guide for researchers and practitioners in the field [26]. These mechanisms include various trust management methods in VANETs, thus elucidating their respective strengths and weaknesses and offering a balanced perspective on the topic [27]. * Section 3 dives into our proposed system, thus offering a detailed overview of the algorithm, methodology, and its unique benefits. It discusses the shortcomings of the existing systems and demonstrates how our proposal effectively addresses them. * Section 4 provides a comprehensive evaluation of our prototype, thus examining its performance and scalability metrics. * Section 5 concludes the paper by recapping the key contributions and exploring potential directions for future research.
## 4 Problem Formulation  
Let \(D_{uf}(X)\) represent the average content \(f\) access delay for user \(u\) from its serving SBS \(s\) for caching strategy \(X\). At least \(T_{uf}(X)\) time slots are required for successful transmission of content \(f\). Thus, the minimum number of time slots for successful data transmission from the serving SBS \(s\) to the user \(u\) is determined as  
\[T_{uf}=\arg\min\biggl{\{}T:R_{\mu}(X,s)\geq\frac{|f|}{\Delta t}\biggr{\}}, \tag{5}\]  
where \(\Delta t\) represents time duration of a complete time slot. Thus, for user \(u\), average delay of receiving content \(f\) is determined as  
\[D_{uf}(X)=\mathbb{E}\Big{\{}T_{uf}(X)\Big{\}}\Delta t. \tag{6}\]  
The delay experienced by user \(u\) in obtaining content \(f\) from serving SBS \(s\) is evaluated as  
\[D_{uf}=\frac{|f|}{\mathbb{E}[R_{\mu}]}, \tag{7}\]  
When content \(f\) is not cached by serving SBS \(s\), then first content \(f\) is fetched from the core network through a backhaul link before transferring content \(f\) towards the demanding user.  
\[D_{uf}=D^{\prime}+\frac{|f|}{\mathbb{E}[R_{\mu}]}, \tag{8}\]  
where \(D^{\prime}\) represents extra delay of data transmission from core network to serving SBS \(s\). According to [33], \(D^{\prime}\) is much larger than \(\frac{|f|}{\mathbb{E}[R_{\mu}]}\) and the impact of \(X\) on \(D^{\prime}\) is negligible. Therefore, the average delay \(D^{\prime}\) is fixed and can be determined by the average time of content \(f\) downloading from core network to the serving SBS \(s\) of user \(u\).  
In this work, our objective is network delay minimization while taking into account evolving users' data preferences. Here, we formulate our objective function as  
\[\min_{\left\{x_{uf}\right\}}D(X)=\frac{1}{U}\sum_{u=1}^{U}\sum_{f=1}^{F}\theta _{f}D_{uf}(X) \tag{9}\]  
\[s.t.\quad\sum_{f=1}^{F}x_{uf}\leq C, \tag{10}\]  
\[x_{uf}\in\{0,1\},\quad\forall f\in\mathcal{F}, \tag{11}\]  
where constraint (10) sets a cache capacity constraint on the SBS. Our problem is NP-hard. Hence, it is challenging to find an optimal caching solution. Therefore, we utilize a machine learning approach known as reinforcement learning (RL) to optimize data caching in wireless networks while taking into account limited cache capacity and users' diverse data demands.
## 1 Introduction
Research and development involving typical satellite and payload architectures will provide experience with respect to the use and applications of nanosatellite technology. Within this context, this paper provides an overview of the AlfaCrux mission and early achievements obtained so far by the satellite operation. It is intended to describe the methods and materials used to achieve the mission goals, that is, an educational platform for science, technology, engineering, and mathematics (STEM) training and learning within the aerospace field, exploring active methodologies with early in-orbit experiences. It also describes the framework built to explore its scientific capabilities gathered around the topic of digital twin (DT) modeling, which includes, for instance, on-board data handling, data processing and visualization, attitude determination and reconstruction, environment modeling, orbit dynamics, and space weather impact in the communication system. The scientific and engineering assessments conducted during the early orbit phase with the AlfaCrux operations were important not only to check and validate the health of the satellite, but also its functional characteristics for the proposed digital twin architecture. Digital twin for CubeSat applications is still an incipient topic that is driving the development and application of different methods to improve our knowledge based on digital models. A simple example of a first result is provided, but due to the initial stage of operation, detailed comparisons and performance analyses are still to come. The first step was to build, integrate, and run a pilot digital twin architecture for the AlfaCrux kinematics reconstruction, described in the paper, and as the knowledge database increases, successive refinements and performance improvements are implemented, increasing the quality of the proposed model.
# SMARTEN--A Sample-Based Approach towards Privacy-Friendly Data Refinement
###### Abstract  
Two factors are crucial for the effective operation of modern-day smart services: Initially, IoT-enabled technologies have to capture and combine huge amounts of data on data subjects. Then, all these data have to be processed exhaustively by means of techniques from the area of big data analytics. With regard to the latter, thorough data refinement in terms of data cleansing and data transformation is the decisive cornerstone. Studies show that data refinement reaches its full potential only by involving domain experts in the process. However, this means that these experts need full insight into the data in order to be able to identify and resolve any issues therein, e.g., by correcting or removing inaccurate, incorrect, or irrelevant data records. In particular for sensitive data (e.g., private data or confidential data), this poses a problem, since these data are thereby disclosed to third parties such as domain experts. To this end, we introduce SMARTEN, a sample-based approach towards privacy-friendly data refinement to smarten up big data analytics and smart services. SMARTEN applies a revised data refinement process that fully involves domain experts in data pre-processing but does not expose any sensitive data to them or any other third-party. To achieve this, domain experts obtain a representative sample of the entire data set that meets all privacy policies and confidentiality guidelines. Based on this sample, domain experts define data cleaning and transformation steps. Subsequently, these steps are converted into executable data refinement rules and applied to the entire data set. Domain experts can request further samples and define further rules until the data quality required for the intended use case is reached. Evaluation results confirm that our approach is effective in terms of both data quality and data privacy.  
privacy; data refinement; data cleansing; data transformation; human-in-the-loop Article
_Article_  
**Corrosion and Tribocorrosion Behaviors for TA3**  
**in Ringer's Solution after Implantation of Nb Ions**  
**[PERSON] 1,2, [PERSON] 1,2,*, [PERSON] 1,2,3\({}^{\copyright}\), [PERSON] 1,2, [PERSON] 1,2 and [PERSON] 1,2**  
Received: 1 November 2020; Accepted: 21 November 2020; Published: 24 November 2020  
**Featured Application: A potential application of this work is in the corrosion and tribocorrosion behaviors of Ti alloys after surface modification.**  
**Abstract:** Ti alloys are prone to corrosion and wear due to the hostile environment in bodily fluids, but the Ti-45 Nb alloy is considered to be a promising titanium alloy with excellent biocompatibility and resistance to physiological corrosion. In this study, Nb ions were implanted into a TA3 alloy and the effect on the biological corrosion as well as tribocorrosion behavior of TA3 in Ringer's solution was systematically investigated. The surface microstructure and XRD results revealed that the implanted samples showed a smoother surface due to the sputtering and radiation damages, and the Nb ions mainly existed in the alloy as the solid solution element. The electrochemical polarization tests showed that the implantation of Nb ions can increase the corrosion potential of the samples, showing a better thermodynamic stability. The tribocorrosion tests showed that the implanted samples exhibited a better thermodynamic stability in a corrosive environment accompanied by wear behavior, and the worn surface showed fewer pitting pits, indicating a better corrosion resistance. However, the abrasive wear and oxidation wear degree of the sample increased because of partial softening of the surface and brittle passivation film.  
**Keywords:** TA3; ion implantation; corrosion resistance; tribocorrosion resistance; Ringer's solution
## Permeate
### Membrane-Based MFCs and Membrane bioreactor-Microbial Fuel Cells
This percentage of COD removal is similar (90%) to that in another study in which the MFC-MBR system was used for COD removal [38]. The sludge was reformed as a result of a decrease in sludge production. The reformed sludge was 5.1% greater than the sludge produced in traditional MBRs. The integrated setup of MFC-MBR was cheaper and more effective than the most available techniques for the management of contaminated water and the production of electricity [39]. The reactor was assembled using low-cost materials and was able to generate 1.9 mA and 6 W/m\({}^{3}\) incessant and steady electricity for over 40 days. When a tubular membrane was installed in the MFC-MBR-integrated setup [20], a power output of 40 mW/m\({}^{2}\) was attained. The setup ran for 30 days, and it was capable of achieving 94% elimination of organic matter and 80% removal of ammonia nitrogen. Another setup was assembled where an EMBR was integrated with an MFC, and the PEM was substituted with a quartz sand compartment [33]. This system achieved remarkable results with regard to the elimination of ammonia nitrogen (93%), phosphorus (50%), and organic matter (97%). The generation of electricity was also improved simultaneously. The MFC-MBR setup was examined as a sensor for an MBR. The competence of the system as a sensor was determined based on an undeviating relationship with a COD of up to 1 g/L. One more MFC-EMBR integration was used for methyl red decolorization and the simultaneous generation of electricity [17]. This system was able to achieve a COD elimination efficacy of 89.3% and 100% decolorization efficiency. To explore the influence of implementing a process control on petroleum refinery wastewater treatment, a two-stage MFC-MBR-integrated system was built by [PERSON] et al. [40]. Chemical oxygen demand (COD), ammonium nitrogen (NH\({}_{4}\)+-N), and total nitrogen (TN) extraction efficiency in the MFC-MBR system were 96.3%, 92.4%, and 86.6%, respectively, compared with 74.7%, 71.2%, and 64.7% in the control system. Further, the use of this system as a biosensor was examined. The two-stage combined MFC-aerobic membrane bioreactor (MBR)-based wastewater treatment method along with the use of ruthenium/activated carbon (Ru/AC) as a cathode catalyst was studied in another experiment by [PERSON] et al. [41]. The maximum volumetric power density and coulombic efficiency of the MFC-MBR system with Ru/AC as a cathode catalyst (2.7 Wm\({}^{-3}\) and 12.8 \(\pm\) 1.2%, respectively) were almost 1.4 and 1.5 times higher than those of the control MFC-MBR system without Ru/AC (2.0 Wm\({}^{-3}\) and 8.2 \(\pm\) 0.6%). Furthermore, these integrated MFC-MBR systems removed more than 96% of chemical oxygen demand (COD) from synthetic wastewater with an initial COD of roughly 1 g\(\cdot\)L\({}^{-1}\). This integrated MFC-MBR system has a lot of potential for being developed into a full-scale application that can provide efficient wastewater treatment and bio-energy recovery.
## 3 Design of Quadcopter and Simulation Environment Setup
### Design of the Simulation Environment (Virtual Location)  
For the MR simulation, it was essential to design a virtual location in X-Plane similar to the location of the real quadcopter. In this work, a drone airfield was chosen in the permissible east part of Seoul, South Korea. Figure 4 illustrates the chosen airfield location (Hangang Drone Park) in Seoul, South Korea. Note that X-Plane has only the sceneries of major airports, there is no scenery available  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Quadcopter Specifications** & **Model/Values** \\ \hline Flight controller & Pixhawk 2.4.8 \\ Total mass (including battery) & 2 kg \\ Frame diagonal length & 450 mm \\ Propellers dimension and pitch & 10 \(\times\) 3.8 \\ No of blade & 2 \\ Motor (brushless) & 2212–920 KV \\ Motor turn rate & 4000–9000 RPM \\ Radio telemetry & 433 MHZ \\ \hline \hline \end{tabular}
\end{table}
Table 1: Specifications of the F450 spider quadcopter.  
Figure 3: Fully designed virtual quadcopter.  
for the chosen airfield location (Hangang Drone Park). To overcome this lacuna, a new scenery of the chosen airfield location was designed at the same geographic location using WorldEditor (version: 1.7.2). WorldEditor is a software, which is used to create and edit the scenery for X-Plane.  
Note that the small runway in the Hangang Drone Park (see Figure 4) was taken as the initial reference point of the real quadcopter. Therefore, we created a virtual runway similar to the real runway in Hangang Drone Park. In WorldEditor, first, we chose the \"create airport\" option. After selecting the create airport option, we could see several design tools on WorldEditor, including runway, helipad, objects, forest, sealane, and facades. Here, we used the \"runway\" tool to build the runway. According to latitude, longitude, heading, and a few other known design parameters highlighted in Figure 5, the virtual location was built similar to the chosen airfield location. Note that the coordinates of the virtual and actual locations needed to be exactly the same, which we achieved; otherwise, an error would occur during the MR simulation.  
Figure 4: Airfield location (Hangang Drone Park) in Seoul, South Korea.  
The designed virtual location was placed in the X-Plane environment (see Figure 6). Therefore, it was possible to fly the virtual quadcopter from the designed virtual location. Figure 7 illustrates the real and the virtual quadcopters in the real and the virtual environments, respectively (before MR simulation). In the following section, the interface between the real and the virtual quadcopters are presented.  
Figure 5: Design parameters of virtual location (on WorldEditor).
## 5 Numerical Analysis  
To assess the performance of the optimized SMA base isolator, the SMA wires with a radius of 3.5 mm were added to the LRBs of the benchmark bridge. Then, the nonlinear time history dynamic analysis was conducted. The behavior of the isolated structure under near-field earthquakes was different from its behavior under far-field earthquakes. The near-field records may include pulses with larger periods. Therefore, because of the long period of the isolated structure, the occurrence of resonance is probable. For this reason, the behavior of the bridge was evaluated during both far-field and near-field earthquakes, and their responses are tabulated in Tables 6 and 7, respectively. In these tables, the responses of the current study are denoted as SRB.  
For comparison, the responses of the nonlinear damper (N.D) derived from the research conducted by [PERSON] et al. (2016), the passive damper device with SMA (Cu.D) obtained from the works carried out by [PERSON] et al. (2017), and the new negative stiffness device (NSD) proposed by [PERSON] et al. (2019) are also listed in Tables 6 and 7. It should be mentioned that various devices were studied by [PERSON] et al. (2009). The results corresponding to the device compatible with the current research are presented. This device has no additional damping, and it works in the temperature of 23 \({}^{\circ}\)C. Moreover, a graphical demonstration of the four evaluation criteria resulted from the above four passive control systems is shown in Figure 9.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \multirow{2}{*}{**Criteria**} & \multicolumn{4}{c}{**North Palm Springs**} & \multicolumn{4}{c}{**El Centro**} \\ \cline{2-10}  & **SRB** & **NSD** & **N.D** & **Cu.D** & **SRB** & **NSD** & **N.D** & **Cu.D** \\ \hline
**J1** & 1.24 & 1.01 & 1.06 & 1.40 & 1.08 & 0.57 & 0.62 & 1.28 \\
**J2** & 1.39 & 1.08 & 1.10 & 1.61 & 1.06 & 0.55 & 0.61 & 1.20 \\
**J3** & 0.74 & 0.75 & 0.87 & 0.83 & 0.40 & 0.45 & 0.50 & 0.41 \\
**J4** & 1.64 & 1.19 & 1.17 & 1.67 & 1.28 & 1.09 & 1.09 & 1.62 \\
**J5** & 0.71 & 0.78 & 0.88 & 0.78 & 0.39 & 0.57 & 0.49 & 0.41 \\
**J6** & 1.39 & 1.08 & 1.10 & 1.61 & 0.83 & 0.55 & 0.61 & 1.20 \\
**J7** & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
**J8** & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
**J9** & 1.36 & 1.11 & 1.19 & 1.25 & 1.08 & 0.64 & 0.61 & 1.53 \\
**J10** & 1.39 & 1.13 & 1.21 & 1.28 & 1.06 & 0.63 & 0.60 & 1.53 \\
**J11** & 0.51 & 0.96 & 1.02 & 0.53 & 0.28 & 0.73 & 0.59 & 0.41 \\
**J12** & 1.29 & 0.95 & 0.91 & 1.52 & 1.37 & 0.94 & 0.95 & 1.74 \\
**J13** & 0.59 & 0.89 & 1.03 & 0.56 & 0.27 & 0.74 & 0.62 & 0.43 \\
**J14** & 1.39 & 1.16 & 1.21 & 1.28 & 1.06 & 0.86 & 0.60 & 1.53 \\
**J15** & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 \\
**J16** & 0.75 & 0.71 & 0.88 & 0.78 & 0.41 & 0.5 & 0.49 & 0.41 \\ \hline \end{tabular}
\end{table}
Table 6: Nonlinear dynamic analysis results of the benchmark bridge equipped with SMA-LRB isolators under far-field earthquakes.