esa-sceva/satcom-chunk-collection huggingface dataset:
# Analysis of Grating Lobe Effects on GEO DSC Distributed Antennas
## 4 Suppression of Grating Lobes Using Sparse Arrays
### Distributed Antenna Array for DSC  
#### 4.2.1 Uniform Array  
As shown in Figure 11, we first considered the case of using a uniformly spaced linear array of 10 GEO DSC satellites as an array configuration for the DSC distributed antenna. According to antenna theory, the antenna pattern after arraying is equal to the array factor of the 10-element linear array layout multiplied by the array pattern of the GEO array. We took the minimum spacing of the GEO satellites to be 10 km. From the antenna pattern in Figure 12, it is not difficult to observe that there are many grating lobes present within the  
\begin{table}
\begin{tabular}{c c c c} \hline _dc_ **(m)** & \(N\) = 8 & \(N\) = 16 & \(N\) = 24 \\ \hline
100 & 1.6 & 4.54 & 6.1 \\
120 & 1.72 & 4.35 & 6.2 \\
140 & 1.80 & 4.60 & \\
160 & 1.77 & 4.37 & \\ \hline \end{tabular}
\end{table}
Table 1: Sidelobe levels (dB) of an optimized beam for different values of \(N\) and \(d_{c}\) in an array.  
When the scanning angle was \(0^{\circ}\), it could be observed from Figure 14 that the grating lobes were effectively suppressed, but the sidelobe level decreased by 2.09 dB and the beamwidth was \(1.4^{\circ}\times 10^{-5}\).  
In the following, the array was scanned and the antenna orientation diagrams are shown in Figures 15-18 when the scanning angles \(\theta\) were considered to be \(\pm 4^{\circ}\) and \(\pm 8.7^{\circ}\), respectively. The sidelobe levels and beamwidths are presented in Table 2. From the simulation results, it can be observed that in distributed satellite clusters, where antennas are placed on each satellite and the inter-satellite spacing is much larger than the operating wavelength, a single satellite can be regarded as an antenna element, while the satellites collectively form an ultra-sparse array (distributed array). If a uniform layout is adopted, numerous grating lobes will appear. To avoid grating lobes, a non-periodic arrangement can be employed. Non-periodic arrays suppress the occurrence of grating lobes, but disperse their energy into the sidelobe region, leading to an overall increase in sidelobe levels. To control the overall sidelobe level, optimization of the layout approach can be implemented.  
Figure 14: The antenna pattern of a sparse array configuration with 10 DSC satellites.  
Figure 13: The arrangement of 10 DSC satellites in a sparse linear array configuration.  
Figure 15: The antenna pattern at a scanning angle of \(4^{\circ}\).
# Evolutionary Game for Content Cache in a mm-Wave-Based Vehicular Fog
###### Abstract  
Vehicular fog computing is attractive for sharing computing resources and data for safety and infotainment of self-driving cars. Recently, the V2X communication technology using mm-Wave frequency spectrum accelerates such future mobile computing with large bandwidth and beam-forming using a directional antenna. Although the beam-forming technique requires a complicate procedure for beam alignment, it can reduce mutual interference by spatial diversity. From the beam-forming scheduling, the vehicular fog can improve network performance, which is limited by data locations. Beams toward a vehicle for the same content should be scheduled in the time domain. Instead, we propose to replicate the content to multiple vehicles nearby to diversify beam directions. However, it is a challenge for vehicles to cache the content because the content caching costs not only limited local storage, but data transmission for other vehicles. For this, we adopt evolutionary game theory in which vehicles learn an evolutionarily stable strategy (ESS) from repeated games and maximize social utility. In this paper, we contribute to modeling a road segmentation for the mm-Wave V2X communication in order to derive connectivity probability with distributed content caches for the vehicular fog, and centralized and distributed algorithms for the evolutionary content cache game. From experiments, we confirm that content cache can improve V2X connectivity and the proposed evolution algorithm leads vehicles to choose the ESS for the content cache in the vehicular fog.  
v 2020, 9, 1794; doi:10.3390/electronics911794
## 3 Results and Discussion
### Effect of Factors and Interactions  
The effect of the independent variables on protein yield is represented in Figure 2. The three factors had a positive effect on the response when they were increased. However, for the case of temperature and time, an inflection point was observed from 47.5 \({}^{\circ}\)C and 62.5 min, respectively, which may represent a decrease in the effect of these factors. On the other hand, this inflection point was not observed in the alkaline solution variable. Alkaline protein extraction from plant material is a widely studied process, and it is known that when combining higher values of pH, temperature, and time, the cell wall is disrupted, and proteins are liberated and solubilized [27; 47].  
The interactions between factors are visualized in the contour plots (Figure 3). At 30 \({}^{\circ}\)C with a time of 50 min, protein yield was the maximum (30-35%), and this value was the same for up to the maximum level of time. A temperature of 50 \({}^{\circ}\)C represented a significant increase of yield protein in just 25 min. At 60 \({}^{\circ}\)C, protein yield was 40-45% with no change with the time, while in the case of 70 \({}^{\circ}\)C, it seems that 45-50% of the response can be reached from 80 min (Figure 3A).  
As mentioned before, the values of the alkaline solution were coded as 1, 2, and 3, with pH values of 12.10, 12.29, and 12.68, respectively (Table 3). For every temperature, the response increased consistently when increasing pH value and vice versa. The pH strongly influenced protein extraction, even at a temperature as low as 30 \({}^{\circ}\)C with a pH value of 12.68, the response was 45-50% (Figure 3B). In the case of the time and alkaline solution interaction, the protein yield improved for all the times when increasing the pH value. It was observed that, at a pH of 12.68, a maximum response was achieved regardless of time level (Figure 3C).  
[PERSON] et al. (2020) carried out alkaline dry matter extraction from commercial soybean flour using NaOH solutions at different pH values generated by the electrolysis of NaCl solutions [23]. Higher extraction yields of dry matter were found at higher pH values. The highest protein content in the extract was 45.55%, obtained from a NaOH solution with a pH value of 12.75.  
Figure 2: Main effects of factors for protein yield (%).  
In the present study, suspensions of alkaline solutions with soybean flour (relation 1:20) had pH values from 8.73 to 10.85. These values were in the range of or above 8.0 to 8.5, as mentioned by [PERSON] et al. (2017) for soy protein extraction, who also mentioned that higher pH values increase protein extraction due to an improvement in protein solubility [4]. Furthermore, increasing the temperature promotes breaking the carbohydrate-protein complex, leading to improved protein extraction. On the other hand, it has been reported that protein extraction is improved with time, but after a certain period, the protein extraction is plateaued [4].
## Materials and Methods
### Preparation of Cellulose-Polytthiophene Materials
#### 2.2.4 Polythiophenes-Derivative/Cellulose Composite Materials: Conjugated Polymers Solutions  
For a better understanding of interactions between CPs and cellulose fibers, we also prepared composite materials processing CPs solutions, PEDOT:PSS and PDBProDOT, to perform a comparison on processability, roughness, and conductivity properties with in-situ prepared composite materials. A total of 2 mL of PEDOT:PSS aqueous solution was deposited on cellulose substrates either casting of spray coating processing methods. All samples were dried overnight at room temperature to evaporate solvent (Table 2). PDBProDOT cellulose composite materials were prepared through a similar procedure to PEDOT:PSS samples dissolving previously PDBProDOT in DCM by magnetic stirring during 1 h (Table 2). Additionally, Scheme 1 shows a detailed procedure for the preparation of all composite materials.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & \multicolumn{3}{c}{_In-Situ Polymerization_} \\ \hline
**Sample** & **Substrate** & **Proc. Technique** & **Oxidizing Agent** \\ \hline _PTsWCt_ & W & & \\ _PTsACt_ & A & Casting (Ct) & \\ _PTsCCT_ & C & & \\ \hline _PTsWSp_ & W & & \\ _PTsAsp_ & A & Spray (Sp) & \\ _PTSCSp_ & C & & \\ \hline _PTJWCt_ & W & & \\ _PTfACt_ & A & Casting (Ct) & \\ _PTfCCt_ & C & & \\ \hline _PTfWSp_ & W & & \\ _PTfASp_ & A & Spray (Sp) & \\ _PTfCSp_ & C & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Polythiophene-derivative/cellulose materials prepared by in-situ polymerization.  
In this work, composite materials were named by each polymer name ('PIs', 'PTf', 'PPs' and 'PPD' correspond to PEDOT:Tosylate, PEDOT:Triflate, PEDOT:PSS and PDBProDOT, respectively) followed by the substrate type by their corresponding initials: W, A and C. The sample names are completed adding at the end the processing technique, casting (Ct) or spray coating (Sp).
# Private and Secure Distribution of Targeted Advertisements to Mobile Phones
## 5 Detailed System Description
### User Meets Ad-Dealer
#### 5.4.1 Ad-Dealer Authentication and Logging  
Before logging their encounter with an Ad-Dealer, users must authenticate the Ad-Dealer. Installed within the user's client is an additional asymmetric verification (public) key \(K_{auth}\), which is the same for all clients, and it is used just for authenticating Ad-Dealers. The matching signing (private) key \(K_{sign}\) is given by the Broker to the Ad-Dealers. As shown in Figure 5, users authenticate an Ad-Dealer by sending a random nonce \(R\), which the Ad-dealer must sign with \(K_{sign}\). Since \(K_{sign}\) is kept secret among the Ad-Dealers, authentication can be achieved by attempting to verify the signature on the signed \(R\) with the use of the \(K_{auth}\).
## 2 The Basic Frame of the Geological Suitability Evaluation of Urban Underground Space (GSEUUS)
### The Collaborative Mechanism Between ESA and GSEUUS  
The synergy between ESA and GSEUUS must be achieved through multiple pathways. Firstly, ESA's sustainability goals--such as reducing carbon footprints and protecting groundwater systems--should be integrated into the evaluation indicator system of GSEUUS [6]. Specifically, indicators, like the \"avoidance rate of ecologically sensitive areas\" and the \"carbon emission intensity of underground development,\" should be incorporated as binding criteria for geological suitability assessments. For instance, automatic downgrading of development suitability should occur within ecological redline zones to ensure alignment with their objectives (Figure 1 green rectangle). Secondly, during the assessment process of GSEUUS, the screening and scoping steps of ESA should be prioritized to identifygeological units that require special protection, such as aquifers and fault zones. Additionally, both parties should share data and leverage ESA's cross-domain databases, including ecological redlines and cultural heritage distribution, to optimize GSEUUS's 3D geological models, thereby avoiding planning conflicts. Taking the groundwater vulnerability map as an example, a shared data mechanism is established to integrate the ESA data layer into the GSEUUS application scenario using methods, such as spatial overlay analysis and weight correction. Finally, by incorporating ESA's public consultation process and organizing stakeholder workshops, community acceptance of UUS development can be fostered to address social preference biases in weight allocation [65], further promoting the collaborative synergy between ESA and GSEUUS.
## 3 Results
### Effects of Temperature on Sensor Application  
The sensor's performance was tested at three different temperatures at which canine training aid kits could be frequently stored (Table 6). This experiment was evaluated through a present/not present paradigm that would reflect future end-user practice. Kits can be stored at either indoor or outdoor locations and the chosen temperatures reflect either possibility. In this experiment, no cross-contamination of 2E1H was detected by instrumental headspace analysis after three days at 25 \({}^{\circ}\)C, the average time a canine handler may leave the training aids stored between uses. Likewise, there was no change in color in the sensor for that time at that temperature. On the other hand, at 50 \({}^{\circ}\)C and 70 \({}^{\circ}\)C, cross-contamination of 2E1H was detected in the headspace of the blank jar within 48 h and 24 h, respectively; however, the sensor changed from green to blue within the first 24 h for both environments. Further analysis of the training aid kit itself showed that, at 50 \({}^{\circ}\)C, 2E1H was detected via SPME-GC-MS inside the kit after 24 h even if it was not detected inside Jar B; thus, the color change was indeed indicative of contamination within the kit.
## 3 Material and Method
### Experimental Design
#### 3.2.2 IoT-Based Monitoring System  
The monitoring system, as shown in Figure 4, was operated using a 25-volt direct current (DC) sensor and DS18B20 temperature sensor. These two sensor types were selected because of their capability to measure battery voltage and ambient temperature. The data collected by these sensors were then transmitted via HTTP over a LAN network and subsequently stored in a database for further analysis and processing.  
Figure 3: Lead acid battery predictive model.  
Figure 2: Block diagram of study.  
The acquired data were then visualized using a dedicated dashboard, which provided a comprehensive and user-friendly interface for monitoring voltage over time. The visualization in Figure 5 shows the voltage and degradation values over time in seconds, providing a real-time view of trends, which enables stakeholders to gain insights into voltage variations and patterns, ultimately aiding in the prediction and assessment of the battery voltage.
## 3 Results and Discussions
### Chemical Characterization of Pyrolytic Oil
#### 3.3.2 FTIR Analysis of the Pyrolytic Oil  
Figure 3 shows the FTIR spectra of the pyrolytic oil samples obtained from the pyrolysis of PE waste without using a catalyst [12] and using the three studied catalysts. The peaks observed in the FTIR of the oil without a catalyst were practically equal to those obtained with commercial catalysts, but absorbance values without a catalyst were higher. These variations in the absorbance intensity may be related to changes in the concentration of the compounds involved and the path length through the sample. In addition, some technical aspects, such as the pressure of the material on the ATR crystal, could also have an influence. The main peaks found were 2917 cm\({}^{-1}\) and 2850 cm\({}^{-1}\) (C-H medium stretch) for alkanes; 1714 cm\({}^{-1}\) (C=O strong stretch) for aldehydes, ketones, carboxylic acids and esters; 1642 cm\({}^{-1}\) (C=C medium and weak stretch) for alkenes; 1465 cm\({}^{-1}\) (C-H variable scissoring and bending) for alkanes; 1150 cm\({}^{-1}\) (C-O strong stretch) for alcohols, ethers, carboxylic acids and esters; 970 cm\({}^{-1}\), and 890 cm\({}^{-1}\) and 720 cm\({}^{-1}\) (C-H strong bend) for alkenes [39].  
In addition, the presence of certain compounds may be due to the origin of the plastic waste used; in this case, we used plastics that have already been processed and contain additives that have been added in the manufacturing process, as well as traces of organic and inorganic impurities [40]. In this way, since the acidity of hydrocarbons is mainly due to the presence of naphthalene acids (lineal, cyclic and aromatic carboxylic groups), the C=O and C-O bonds would be related to the slightly acid pH of liquid fractions, which increase to around 1.69% when the catalysts are used.  
[PERSON] et al. [41] studied the pyrolysis of different polymer wastes with HUSY and HZSM5 catalysts and obtained peaks similar to those determined.  
Figure 2: Simulated Distillation curves of the pyrolytic oil samples obtained by thermal (without catalyst) and catalytic cracking (HY, HUSY and HBEA).
# Differential Signalling in Free-Space Optical Communication Systems
## 8 Conclusions  
In this paper, we outlined the essentials of differential signalling based FSO systems subject to the both effects of pointing errors and turbulence. We provided a description comprehensive investigation of the system performance under different conditions of turbulence and/or pointing errors. We derived closed-form expressions for various channel conditions for the DSS based FSO system and showed predicted and simulated results for the variance of DTL and the BER for both SISO and DSS based FSO links. We showed that the DSS based link offers improved performance at higher turbulence and pointing error levels compared to the simple SISO link.  
**Author Contributions:** [PERSON] and [PERSON] carried out the mathematical analysis and simulation; [PERSON] and [PERSON] proofread and confirmed the analysis; [PERSON]-[PERSON] and [PERSON] contributed to the theory material.  
**Acknowledgments:** Portions of this work were presented at the IEEE International Conference on Communications ICC in 2016 (ICC2016), using differential signaling to mitigate pointing errors effect in an FSO communication link. One of the authors, [PERSON] was supported by the PhD studentship from Northumbria University. The work was also supported by the The European project H2020 MSC ITN no. 764461 (VISION) and CTU project SGS17/182/OHK3/3T/13.  
**Conflicts of Interest:** The authors declare no conflict of interest.  
Figure 6: Single-input single-output (SISO) and differential signaling scheme (DSS) based free-space optical (FSO) links with pointing errors (PE) and moderate to strong turbulence: (**a**) the normalised variance of detection threshold level (DTL) versus the correlation coefficient of the channels; and (**b**,**c**) bit-error-rate (BER) against signal-to-noise ratio (SNR) for different values of \(w_{eq}\) with unit of cm and \(\sigma_{R}^{2}\).
## 5 Evaluation of the Security Aspects of the Designed Protocol
### Man-in-the-Middle Attack  
In contemporary computer networks, the Man-in-the-Middle (MitM) attack is among the most perilous threats, commonly referred to as MITM, MitM, MIM, or MITMA in different publications. It is unfortunate that this kind of attack is often overlooked by users, potentially resulting in unauthorized access to a user's information. The primary objective of a MitM attacker is to intercept and manipulate the data flow between the network nodes during their communication. Moreover, the attacker has the potential to access network traffic, creating a substantial threat to the confidentiality and integrity of the data in transit. To counter this attack, encrypting information is one of the most effective solutions as it assists in safeguarding the secrecy of data during its transmission over the network. Within our suggested protocol, we use a dynamic symmetric key to secure the messages being exchanged. Additionally, multi-factor authentication mechanisms have been incorporated into our protocol procedure to ensure identity verification. Even if the attacker succeeds in obtaining the parameter K, according to ECDLP theory, they still need the server's private key, which is a significant obstacle for the attacker. Moreover, other security policies are taken into consideration:  
1. **Message Freshness:** Communication parties verify the freshness of messages, and the protocol utilizes random numbers combined with private parameters. This dynamic aspect ensures that intercepted messages become obsolete and cannot be reused.
2. **Unique AC\({}_{\text{i}}\) Parameter:** The AC\({}_{\text{i}}\) parameter used in the protocol is unique for each network entity. Consequently, when recalculating the verification parameters S\({}_{2}\), S\({}_{3}\), and A on the server side, it will not match the data manipulated by the adversary, leading to a disconnection.
3. **Session Key:** To derive the session key, the adversary would need access to the S\({}_{1}\), S\({}_{2}\), S\({}_{3}\), SA, AC\({}_{\text{i}}\), A, and N\({}_{\text{i}}\) parameters. These values are neither transmitted over the channel nor easily accessible. As previously described in the impersonation attack section, it is practically impossible for an adversary to acquire these critical values.
## 5 Parametric Analysis on the Assessment Results
### Effects of Pipe Wall Thickness and Misalignment  
In the previous subsection, the effect of the crack size on the evaluation results of the girth welds on \(\mathcal{O}813\times 17.5\) mm pipes were compared and analyzed. Based on the current internal detection accuracy control requirements and crack size control specifications, the possible maximum crack depth (\(a\)) and length (\(2c\)) of a pipe girth welding are 2.5 mm and 25 mm, respectively. At the actual position of the crack, the wall thickness and misalignment are not necessarily the same. According to relevant standards [27], the axial stress of the pipeline under normal service conditions should not exceed 0.9 times the minimum yield strength of the base metal.  
Based on this assumption, in this section, the results of axial pipeline loading with different misalignment levels and wall thickness values are analyzed under loads equal to 0.5-0.9 times the minimum yield strength. Figure 7(a) demonstrates the results of pipe girth welds with different misalignment and wall thickness values when loaded with an axial load of 0.9 times the minimum yield strength. In addition, Figure 7(b) shows the results of the \(\mathcal{O}813\times 11\) mm pipe girth welds with different misalignment when loaded with axial loads of 0.5-0.9 times the minimum yield strength.  
According to Figure 8, the smaller the pipe wall thickness, the larger the corresponding load and fracture ratios, and the greater the possibility of failure. Therefore, by increasing the pipeline wall thickness, the safety of the pipeline can be effectively improved. When there is no misalignment at the girth weld, the difference between the load ratios corresponding to different wall thickness values is not large. Nevertheless, with the increase of the misalignment level, the distance between the evaluation points corresponding to different wall thickness values increases gradually, indicating that the existence of misalignment significantly increases the stress concentration, and the greater the misalignment, the more severe the stress concentration.  
Figure 7: Effect of crack size on the evaluation results of \(\mathcal{O}813\times 17.5\) mm pipeline girth welded joints. (a) \(a\)/\(B\) = 0.3; (b) \(2c\)/\(\pi D\) = 0.07.  
By comparing the results obtained for different misalignment levels, it can be found that, when the girth well does not contain any misalignments, the evaluation results corresponding to all wall thickness values meet the safety requirements under loads equal to 0.5-0.9 times the minimum yield strength. When there is a misalignment of 1 mm or more, not all crack evaluation results under all loading conditions can pass the evaluation. This is attributed to that a high level of misalignment results in high bending stress, which makes the bearing state of the circumferential weld extremely dangerous.