esa-sceva/satcom-chunk-collection huggingface dataset:
# Privacy-Preserving Authentication Based on PUF for VANETs
## 2 Related Works
In addition, when the drivers enter the coverage of RSUs, route planning is also introduced into the proposed scheme to speed up the V2I authentication.
# Multimodal Magnetic-Plasmonic Nanoparticles for Biomedical Applications
## 2 Synthetic Methods
### Brust's Method  
[PERSON]'s method of nanoparticle synthesis involves reduction of a metal precursor in a two-phase (water-toluene) system by NaBH\({}_{4}\) in the presence of an alkane thiol, and is a good method of preparing highly stable thiol functionalised nanoparticles. The metallic clusters are grown by the simultaneous attachment of self-assembled thiol monolayers on the growing nuclei [52]. The synthesis proceeds at room temperature, and first involves the phase transfer of chloroauric acid (Au\({}^{3+}\)) from the aqueous phase to the organic phase using a phase transfer catalyst. The two phases are then separated and the organic phase is first treated with dodecanethiol to cause the reduction of Au\({}^{3+}\) to Au\({}^{1+}\). Sodium borohydride is then added to reduce the Au\({}^{1+}\) to Au\({}^{0}\), and this reduction is indicated by a colour change [53]. This method was utilised in the synthesis of Fe\({}_{3}\)O\({}_{4}\)@Au nanoparticles; in this case the Brust Schiffrin method was used to obtain 2 nm Au nanoparticles, and the shell was obtained through a modified thermally activated processing protocol [54]. While the Brust method was first used to synthesise gold nanoparticles, the methodology can be extended to other metal based systems. For example, [PERSON] method was used by [PERSON] et al. to produce bimetallic magnetic plasmonic Au/Co. nanoparticles (Figure 6) [55].  
Figure 6: STEM images showing AuCo nanoparticles in amorphous carbon. The histogram illustrates the small size distribution of the nanoparticles. Reprinted with permission from [55]. Copyright MRS, 2013.
## 4 Results
### Experiments in the Real Environment  
On the real robotic platforms we only tested the height-adaptive PID w/o predictive action, since for the predictive system to have worked we would have needed an additional means to localize the landing platform's position in global coordinates, as described in Section 3.3.2. In the simulated environment, transforming positions to a fixed global frame was straightforward. In the real world, however, this is more complex; implementing a Visual Inertial Odometry (VIO) or even a full visual Simultaneous Localization and Mapping (vSLAM) system would have been required in order to localize the drone in the scene with respect to a fixed frame.  
What we did, however, was localize the landing platform relative to the UAV's coordinate frame, which is the only input required by the non-predictive approach. Therefore, on the real robotic platforms we qualitatively tested the system that employs our novel height-adaptive PID w/o prediction.  
In particular, we performed five takeoff-tracking-landing sequences both for the linear and circular trajectory, following the same strategy as that described in Section 4.2.1. The UAV landed successfully in all five experiments for the linear trajectory and only failed once for the circular trajectory. The landing quality is visualized in Figure 14. We therefore demonstrate that the system presented in this work can be deployed on real robotic platforms. Figure 15 visualizes one of the linear trajectory experiments, and Figure 16 shows a sequence of a recovery maneuver. The complete sequences can be found in the video provided as Supplementary Material, or at [[https://youtu.be/CCrPBw_we2E](https://youtu.be/CCrPBw_we2E)]([https://youtu.be/CCrPBw_we2E](https://youtu.be/CCrPBw_we2E))  
Figure 12: Detail of the 3D trajectory for a velocity of \((v_{x}=0.7\,\mathrm{m}\,\mathrm{s}^{-1},\,w_{2}=0.07\,\mathrm{rad}\,\mathrm{ s}^{-1})\) where a re-localization maneuver takes place. The run-time interval represented is [47.79 s, 99.84 s].  
Figure 13: Error along the z axis (relative UAV-UGV distance along the z axis) during the first 200 s for both velocity conditions studied. (**b**) shows three re-localization maneuvers.  
The reader must note that the real experiments were targeted as a qualitative demonstration of how our system can be integrated into real robotic platforms. We believe that the numerous quantitative experiments presented for the simulated environment (where we have used the same UAV model as in the real tests, as well as the same UGV) can serve to demonstrate the robustness and accuracy of the system, while the qualitative tests performed on the real robots can demonstrate that our system can be deployed on the real world.
## 2 Materials and Methods
### Microbial Community Analysis  
Samples from the inoculum and the final microbial communities present in the BTFs and BFs packed with Filtralite materials (at the end of the experimentation) were withdrawn for microbial analysis. The biomass was centrifuged at 13,000\(\times\)\(g\) for 10 min. The resulting pellet was used for DNA extraction using the MasterPureTM Complete DNA Purification Kit (Epicenter Biotechnologies, Madison, USA) according to the manufacturer's instructions. DNA was quantified with Qubit dsDNA broad-range (BR) assays in a QFX Fluorometer (DENOVIX, Wilmington, DE, USA) and subsequently purified. The extracted DNA was used for sequencing by Illumina Miseq. Sequencing was performed at the Foundation for the Promotion of Health and Biomedical Research of the Valencia Region (FISABIO,Valencia Spain). Amplicon sequencing was developed targeting the 16S ribosomal DNA V3 and V4 regions using the bacterial/archaeal primers described by [PERSON] [17]. Illumina adapter overhang nucleotide sequences were added to the gene-specific sequences. After 16S rRNA gene amplification, library construction was carried out using the Nextera XT DNA Sample Preparation Kit (Illumina, San Diego, CA, USA). Libraries were then normalized and pooled prior to sequencing. Samples containing indexed amplicons were loaded onto the MiSeq reagent cartridge for automated cluster generation sequencing using a 2 \(\times\) 300 pb paired-end run (MiSeq Reagent kit v3 (MS-102-3001)) according to manufacturer's instructions (Illumina). Quality assessment and sequence joining was performed using prinseq-lite program [18] and bioinformatic analysis was done using an ad-hoc pipeline in RStatistics environment, making use of open-source libraries (gdata, vegan...). The sequence data was analyzed using qime2 software tools. Taxonomic affiliations have been assigned using the Naive Bayesian classifier integrated in quilime2 plugins. The database used for this taxonomic assignation was the Silva138 [19].
## 4 Preliminary Performance Considerations for IPDALLS
### Potential Performance Limitations
Turbulent refraction will also degenerate an initially Gaussian beam profile into spatial intensity fluctuations in the incident wave plane, characterized by a spatial correlation scale, and leading to further potential signal loss, even if [PERSON] _et al._[65] are referring to interference generated during the reflection of coherent light off a rough Lambertian target. This is of less concern to the technique described in this paper, and results off a small (essentially point) retroreflector showed a much higher bichromatic cross-correlation (0.87), albeit with relatively high variance [67]. For a retroreflector and a receiving telescope of finite apertures, the possibility of integrating over such a speckle structure or individual cells will need to be accounted for [66]. For the total power not to be fluctuating, the aperture sizes would need to be larger than the spatial correlation scale [68], which is not satisfied with the current design specifications. In particular, if the radius of a single (point) retroreflector is smaller than the intensity spatial correlation scale, fluctuations in the reflected flux will not be averaged by a receiving aperture of arbitrary size, though a larger telescope diameter would still reduce the signal variance. [PERSON] _et al._[33] show for a rough target IPDA LiDAR that speckle has a large potential to severely degrade the final SNR, and all of the above will need to be considered in a much more detailed analysis of the expected performance of our system, and validated experimentally. We can already note, however, that we expect strong constraints on the optimistic results presented in the previous section. The GOMOS transmission spectra retrievals are corrected for by anisotropic scintillation measurements from the fast photometer [60]; we expect to realize similar corrections by introducing scintillation quantification using the continuous-wave high-divergence IR beacon laser potentially required by the PAT system (see Figure 8), which would also provide the potential for gathering further science data.
## 8 Introduction to Proprietary and Standards-based Solutions
### Standards-Based Technologies
#### 8.2.6 NB-Fi  
NB-Fi (narrowband fidelity) LPWAN technology is designed for narrowband, low power, and long range bidirectional M2M communication applications [22; 36]. This solution is designed by WavIoT--an Infrastructure as a Solution (IaaS) LPWAN provider. It works in 868 MHz and 915 MHz unlicensed ISM bands as well as other sub-GHz unlicensed spectrum. NB-Fi is an open, full-stack protocol with all seven layers of the OSI reference model for robust, reliable, and energy-efficient sensor communication. To achieve improved spectral efficiency and performance in the narrow bands, it employs smart and optimized spectrum utilization algorithms based on SDR technology, neural networks, and artificial intelligence techniques. NB-Fi has a decentralized architecture, allowing base stations to perform significant operations, making it more robust and reliable in the case of network failure. It is a highly scalable solution in which one NB-Fi base station can support up to 2 million sensor nodes. As sub-1 GHz ISM bands are crowded, the gateways are designed to work with an interference avoidance algorithm. NB-Fi provides coverage up to 10 km in urban areas and up to 30 km in rural areas.
## 5 Spectroscopy Analysis
### In Situ Research for Biomaterials  
The picosecond dynamics of hydration, which could be relative to the characteristics of nucleic acid, protein, cell, and tissue, can be effectively evaluated through the dielectric properties in the THz region [70]. Besides, the THz wave is non-ionizing, which is safe for the biomedical samples. Thus, the THz-ATR system could be suitable for in situ research for biomaterials and biomedicine. Here, we reviewed research that mainly focuses on the cell samples.  
[PERSON] et al. [71; 72] determined the complex dielectric constant of cultured human cancer cells (DLD-1, HEK293, and HeLa) in the THz region. They found that the dielectric responses below 1.0 THz best characterize the particular water dynamics of cancer cells. Later in their research [59], the hydration state of an intact HeLa cell monolayer was investigated. Compared to the bulk water molecules, these intracellular hydration water molecules exhibited slowed down re-orientation dynamics relative to that of bulk water. [PERSON] et al. [73] proposed real-time measurements, which could monitor the cytoplasm leakage. The THz signal shows great sensitivity to the intracellular protein concentration. [PERSON] et al. [74] also conducted a study on the cultured living human breast epithelial cells (MCF10A). The dielectric constant and dielectric loss of cells were determined, and their evolution under oxidative stress response was discussed. The above all demonstrated that THz-ATR spectroscopy could allow in situ, noninvasive, real-time, and rapid monitoring of living cells.
## 3 Background and Related Work
### Identity Management
#### 3.1.1 Identification  
Identification is the starting point for digital identities, as the user presents proof of his or her real-world identity. Users are typically assigned unique identifiers during enrolment by organizations. These identifiers are then utilized as logins or usernames for services. According to [PERSON] et al. [11], an identity represents an entity, such as a person, an organization, or resources. It is defined for a specific context and has certain characteristics, either artificially defined or natural.  
While the process of assigning a digital identifier to a person is a standard process in many organizations, the certainty that the person is actually the person they pretend to be differs. In order to characterize these and other differences, levels of assurances (LoAs) are applied for cross-organizational contexts. One example of a LoA is the National Institute of Standards and Technology (NIST) Special Publication (SP) 800-63, where enrolment and identity proofing are described in document A [12]. The lowest level, i.e., identity assurance level (IAL) 1, has no requirements to link the applicant to a specific real-life identity. IAL 2 supports the real-world existence of the claimed identity and verifies that the applicant is associated with this real-world identity. The highest level of IAL 3 requires physical presence for identity proofing. Although identification is important in practice, it is almost not regarded in research [13]. Exceptions are the identification of users on mobile devices [14; 15], in virtual reality (VR) settings [16; 17], and across social networks [18; 19].
## 2 Materials and Methods
### Data Processing  
Each TMY-PV at any of the 33 sites in Greece consists of hourly values of ambient temperature (in \({}^{\circ}\)C), relative humidity (in %), and global horizontal and direct horizontal solar radiations (in Wm\({}^{-2}\)). As no atmospheric pressure data were included in the TMYs-PV, this parameter was adopted from the corresponding TMYs-MC. All of the above parameters refer to the station's altitude and have gone through quality-control testing during the generation process of the TMYs (see [57]).  
The original SUNAE (Sun's Azimuth and Elevation) routine, first introduced by [PERSON] [66], together with its modifications [67; 68; 69; 70] was applied to the geographical coordinates of the 33 stations at every 30 min past the hour for a complete year. To derive the hourly values of the solar altitude, \(\gamma\), needed for the calculation of \(m\) at every site for a complete year, the SUNAE algorithm was applied to each month of the site's TMY (for description see [57]). Only values of \(\gamma\) greater than or equal to 5\({}^{\circ}\) were considered (to avoid the cosine effect); thus, the corresponding \(T_{\rm L}\), \(T_{\rm UM}\), \(k^{\prime}_{\rm t}\), and \(k^{\prime}_{\rm d}\) values were discarded. Another data-quality criterion was the rejection of all \(T_{\rm L}\), \(T_{\rm UM}\), \(k^{\prime}_{\rm t}\), and \(k^{\prime}_{\rm d}\) values if \(G_{\rm e}\) or \(B_{\rm e}\) were equal to zero. On the other hand, the distinction of skies into overcast, intermediate and clear for the purposes of this work has been based on the criteria mentioned in Section 2.1.3. Furthermore, the hourly values of \(T_{\rm L}\), \(T_{\rm UM}\) have been kept in the ranges given in Sections 2.1.1 and 2.1.2, respectively.  
The derivation of \(T_{\rm L}\) and \(T_{\rm UM}\) at the 33 sites was based on necessary measured or estimated parameters (\(B_{\rm e}\), \(P_{\rm z}\) for \(T_{\rm L}\); \(B_{\rm e}\), \(RH\), \(T\) for \(T_{\rm UM}\)); their values have been taken from the available TMY datasets at the 33 locations. Therefore, one could say that the derived \(T_{\rm L}\) and \(T_{\rm UM}\) annual datasets also correspond to a TMY; thus, the notion of a TATY (Typical Atmospheric Turbidity Year) is introduced here.
# Quantum Key Distribution with Post-Processing Driven by Physical Unclonable Functions
## Appendix A The Size of the Pre-Shared Key  
In a QKD system, the pre-shared key is mainly used for authentication and encryption purposes during the post processing. The length of the pre-shared key depends strongly on the details of the post-processing, and one may wonder about the typical values. In an effort to discuss the typical lengths without deviating from the main focus of this work, we have kept this appendix as general and simple as possible. Following Refs. [10; 11], we will assume that authentication takes place only in the key sifting, the error verification, and the privacy amplification for the extraction of the final secret key, whereas encryption takes place only during error reconciliation. Let us look separately at the key cost for these processes.
# Application of Microgel as a Sorbent for Bisphenol Analysis in Liquid Food Samples
## 2 Materials and Methods
### Analysis of Food Samples  
Food samples were taken from local markets in Warsaw, Poland. The analyzed samples included the liquid part of food and drinks: coated cans (mandarin, peach, two cans of pineapple, mushroom, figs, fruits in syrup and energy drink); polycarbonate bottle (mineral water); plastic packages marked with 7 recycle codes (pickles and sour cabbage); and tap water. The liquid part of each sample was filtered (0.45 \(\upmu\)m), the pH was measured and then the liquid was kept at 4 \({}^{\circ}\)C before extraction. All the food samples were measured in their own pH (Table 1). The pH of the samples was not adjusted, as our microgel showed stability in the sorption of all bisphenol under pH 9 [28]. For each extraction, 1 mL of sample was used, and five milligrams of microgel was added. The extraction procedure was made on liquid food samples and liquid food samples spiked with a standard mixture of four bisphenols (50 \(\upmu\)g\(\cdot\)L\({}^{-1}\)). All mixtures were then shaken in a tube rotator at 20 \({}^{\circ}\)C for 30 min. After separation from the mixtures, the microgel sorbent was washed with 500 \(\upmu\)L of distilled water, and then bisphenols were eluted with 200 \(\upmu\)L of 80% methanol and water solution. Afterwards, all collected samples (the effluent, water after washing and elution solvent after preconcentration) were analyzed by LC-FLD. The recovery (\(R\)) was calculated with the following equation:  
\[R=\frac{C_{exp}}{C_{ther}}\cdot 100\%\]where \(C_{exp}\) is the experimental concentration of bisphenols after preconcentration, and \(C_{theor}\) is the theoretical concentration, which should be obtained. Extraction repeatability was calculated as the standard deviation (SD) of three replicates.
## 3 Experimental Results and Discussions
### The Measurement Error Analysis of the Multi-Electrode Sensor System
In previous studies, the corrosion rate of the Q235 carbon steel in the simulated pore solution with 3.5% NaCl added was between 0.15 mm/a and 0.28 mm/a after the breakdown of the passive film [34]. It can be used as reference data for the evaluation of the highest localized penetration rate in this test. The upper limit of the highest localized corrosion rate of the weldment may reach 1.1 mm/a based on the reference data. However, in this test, the corrosion process of the welded structure in concrete is a typical localized corrosion pattern. The reference \(I_{Micro}\) is almost four times smaller than the \(I_{Macro}\) on WE 3. The highest localized corrosion rate can be well reflected by the sensor system. This parameter is also the most concerning factor for the failure evaluation of the marine structure. Consequently, the coupled multi-electrode array sensor system can be applied as an effective method for monitoring the localized corrosion in the ocean and coastal structures.
## 2 Materials and Methods
### Methodology
#### 2.3.2 Geographic Difference Analysis and Geographic Ratio Analysis  
Both GDA and GRA can be used to reduce the difference between satellite precipitation data and rain gauge measurement data [31; 98]. In this study, we selected the validation group rain gauges (RGS) data to compare the calibration effect of GDA and GRA on downscaled data. The principle and expression are as follows:  
1. Calculate the difference/ratio between downscaled precipitation and RGS measurements: \[\mathrm{P_{ratio}^{point}}=\mathrm{RGS}/\mathrm{P_{i,d}^{1\;\mathrm{km,SAT}}}\] (10) \[\mathrm{P_{sub}^{point}}=\mathrm{RGS}-\mathrm{P_{i,d}^{1\;\mathrm{km,SAT}}}\] (11)
2. Interpolate the difference/ratio to 1 km resolution using interpolation techniques (GDA: IDW, Kriging, RBF; GRA: IDW).
3. Calibrate downscaled precipitation to obtain the final downscaled results: \[\mathrm{P_{GRA}^{1\;\mathrm{km,SAT}}} =\mathrm{P_{i,d}^{1\;\mathrm{km,SAT}}}*\mathrm{P_{ratio}^{1\; \mathrm{km}}}\] (12) \[\mathrm{P_{GDA}^{1\;\mathrm{km,SAT}}} =\mathrm{P_{i,d}^{1\;\mathrm{km,SAT}}}+\mathrm{P_{sub}^{1\; \mathrm{km}}}\] (13)  
where \(\mathrm{P_{i,d}^{1\;\mathrm{km,SAT}}}\) represents the downscaled satellite precipitation data (CMORPH, ERA5, and IMERG), \(\mathrm{P_{sub}^{1\;\mathrm{km}}}\) is the difference interpolated to a 1 km resolution, \(\mathrm{P_{ratio}^{1\;\mathrm{km}}}\) is the difference ratio interpolated to a 1 km resolution, and \(\mathrm{P_{GRA}^{1\;\mathrm{km,SAT}}}\) and \(\mathrm{P_{GDA}^{1\;\mathrm{km,SAT}}}\) are the final downscale precipitation results.
# Mechanical Performance of Concrete Made with the Addition of Recycled Macro Plastic Fibres
## 4 Results and Discussion
### Flexural Strength  
Most previous studies observed that the flexural strength of concrete increased upon the addition of PF [50, 51, 52, 36, 53, 54].  
However, as can be seen in Figure 4, the flexural strength recorded for non-notched prismatic specimens underwent a considerable reduction for mixtures made with fibres compared to the control concrete specimen (C-REF). The results also show that, as the percentage of fibre increased, a significant reduction in flexural strength followed. This is consistent with the findings of other authors [55,56], who stated that the flexural strength only improved when the concrete had a low fibre content, whereas, above a certain threshold, the flexural strength decreased (which coincides with our case).  
With respect to the values of the control concrete specimen (C-REF), the decreases were 28.45% for PFRC-REF, 39.79% for PFRC-2, 45.03% for PFRC-4, and 49.04% for PFRC-6. According to other researchers, the reduction in flexural strength may have been due to the presence of voids inside the concrete matrix [46], which depends mainly on the strength of the mix, as seen in concrete specimens with fibres compared to C-REF.  
Figure 3: Elastic modulus (E\({}_{\text{cm}}\)) values for all mixtures at 28 days, along with the standard deviation bands.