esa-sceva/satcom-chunk-collection huggingface dataset:
# Scalp-Implanted Ultra-Wideband Circularly Polarized MIMO Antenna for Biotelemetry Systems
## 3 Results and Discussion
### Link Budget for Wireless Communications  
The scalp-implantable device aims to transmit collected data to an external receiver, making an \(LM\) analysis essential to assess the communication capability, transmission distance, and speed of data transmission. The \(LM\) is usually calculated using the following equation [28]:  
Figure 7: Two-dimensional radiation direction diagrams of (**a**) antenna-1 and (**b**) antenna-2.  
\[LM=Link\frac{c}{N_{0}}-Required\frac{c}{N_{0}} \tag{2}\]  
\[Link\frac{c}{N_{0}}=P_{t}+G_{t}-L_{f}-L_{p}+G_{r}-N_{0} \tag{3}\]  
\[Required\frac{c}{N_{0}}=\frac{E_{b}}{N_{0}}+10 lgB_{r}-G_{c}+G_{d} \tag{4}\]  
\[L_{f}=20\text{log}_{10}(\frac{4\pi d}{\lambda}) \tag{5}\]  
\[N_{0}=10\text{log}_{10}(k)+10\text{log}_{10}(T_{i}) \tag{6}\]  
\[T_{i}=T_{0}(NF-1) \tag{7}\]  
All of the variables and values utilized in the calculations are detailed in Table 2. In the link communication setup, the implanted CP MIMO antenna functions as the transmitting antenna, while an external CP dipole antenna with a gain of 2.15 dBi serves as the receiving antenna. Given that both antennas exhibit CP properties, the polarization mismatch loss is assumed to be negligible at 0 dB. Effective communication between the two antennas is ensured when the \(LM\) exceeds 0 dB. In this work, a minimum reference margin of 20 dB was used to guarantee stable and seamless communication. Figure 8 shows that, at an operating frequency of 2.45 GHz, the \(LM\) decreases as the communication distance increases. The tested data transmission rates were 1, 10, 50, and 78 Mbps, with the maximum transmission distance reaching 9.6 m at a bit rate of 78 Mbps. Therefore, the proposed ultra-wideband CP MIMO antenna is highly suitable for use in scalp-implantable devices.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Specification** & **Variable** & **Value** \\ \hline Transmitting antenna polarization & & Circular \\ Receiving antenna polarization & & Circular \\ Frequency (MHz) & & 2450 \\ Implantable antenna gain (dBi) & \(\zeta_{\text{Gt}}\) & \(-\)24.1 \\ Transmitted power(dBm) & Pt & \(-\)16 \\ Impedance mismatch losses at transmitting side (dB) & Lt & 0 \\ Distance (m) & d & 0–20 \\ Ambient temperature (K) & T0 & 293 \\ Rx noise figure & NF & 3.5 \\ System noise temperature(K) & Ti & 732.5 \\ Rx gain & Gr & 2.15 \\ Boltzmann constant & K & 1.38 \(\times\) 10\({}^{-23}\) \\ Noise power density (dB/Hz) & N0 & \(-\)199.95 \\ Data rate (Kbps) & Br & Various \\ Ideal PSK (dB) & Eb/N0 & 9.6 \\ Coding gain (dB) & Gc & 0 \\ Fixing deterioration (dB) & Gd & 2.5 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Communication link budget parameters.  
Figure 8: Link margin for different transmission rates at 2450 MHz.
## 5 Comments upon Measured Results  
The main acoustic parameters taken into consideration for the analysis of this particular space were the early decay time (EDT), reverberation time (T20), music clarity (C80), and definition (D50). The considered spectrum ranged between 125 Hz and 4 kHz. The results summarized in Figure 3 were averaged for all the source and receiver positions. The comparison includes the acoustic response measured in two specific conditions, without and with transparent acrylic panels that were 3.5 m high.  
Figure 3: Average measured results related to the garden of [PERSON]’s villa: EDT (**a**), T20 (**b**), C80 (**c**), and D50 (**d**).  
Figure 2: Equipment position during the acoustic measurements.  
Figure 3a shows that a negligible difference was revealed between the two scenarios in relation to the EDT results. The EDT results, with and without screens, fluctuated around 0.7 s at low frequencies with a slight downward trend up to 4 kHz, where the values were around 0.5 s. Overall, the screens did not contribute to a significant acoustic improvement for the early reflections, which should be increased to be close to 1.8 s, as per the criteria set for enclosed spaces [11].  
Figure 3b shows that the T20 results without screens fluctuate around 0.4 s, which is low for good acoustics of musical performances. The addition of 3.5 m screens improved marginally the reverberation, reaching 0.6 s for all the octaves and 0.8 s at 500 Hz, only.  
The clarity index, with and without screens, fluctuated around 8 dB, with an upward peak equal to 11.5 dB at 2 kHz in the absence of any screens, as shown in Figure 3c. These C80 values were highly above the upper threshold set to +2 dB, meaning that the music (both vocal and instrumental) is clearer than what should be [12].  
Figure 3d shows that the definition is around 0.4 and 0.6 at low frequencies and around 0.6 and 0.7 at high frequencies, without and with screens, respectively. These D50 values are considered suitable for musical performances [13]. The presence of screens flattened the response across the bandwidth to be more uniformly distributed without peaks at any octaves [14].
# Neither Denied nor Exposed: Fixing WebRTC Privacy Leaks
## 5 Dealing with IP Leaks  
As discussed in Section 2, a browser informs the actual WebRTC application about the location of STUN and TURN servers using the RTCPeerConnection object. The peer can later use this object to connect to the STUN server, get informed about its own IP addresses through this connection, and create SDP offers for initializing a call. It is therefore straightforward that a webpage that is not destined to execute WebRTC requests should not use by any means the RTCPeerConnection object. In that case, if a binding request to a STUN server takes place, then the user should be informed that the visited website needs to access private information (the public IP address) in order to use WebRTC.  
Taking the latest Android update as an example, a \"runtime\" permission system would be the ideal approach against such kind of actions. More precisely, a user should be informed that the webpage is trying to access their IP address information to initiate a WebRTC call and the exact time the user is placing the call. A similar type of permission request is used in some browsers, like Chrome, to inform the user that the current webpage is trying to access their location or wishes to send notifications. In such circumstances, if the user approves the request, then the browser will be able to get the appropriate user's information. Contrariwise, if the user rejects the request, the action should get blocked, also meaning they will not be able to make a call, if that is the case.  
To address the above issue and detect whether a webpage attempts to execute a STUN or TURN request, we propose two diverse kinds of solutions, which are implemented differently, but, in essence, use the same detection technique. The first approach is a browser extension, which basically uses a preload mechanism to prevent such JavaScript calls before the actual HTML Document Object Model (DOM) loading starts. The second one is using a gateway, either local or third-party, to inspect the JavaScript code the user is about to download.
## 3 Results and Discussion
### Final Particle Characteristics of Samples Obtained by SpraySyn1 and SpraySyn2
#### 3.1.2 BET and Magnetic Properties  
To examine whether average particle sizes differ among the four synthesized samples, BET measurements are conducted. This revealed the respective BET-related average mean primary particle diameter, \(d_{\text{PP,BET}}\), and the materials' \(SSA\) values. Noteworthy, the materials' \(SSA\) is of particular relevance for catalytic applications, while \(d_{\text{PP,BET}}\) is of greater relevance for superparamagnetic applications, due to the correlation of magnetism and particle size [1; 2; 3].  
By examining the samples' by BET, it is revealed that increasing the INN concentration correlates with a rising \(d_{\text{PP,BET}}\) and declining \(SSA\) value (Figure 5). This phenomenon can be attributed to the fact that larger particles emerge in the gas phase by the interplay of agglomeration and sintering at higher precursor concentrations. The BET analysis also reveals a systematic higher \(d_{\text{PP,BET}}\) for SpraySyn1 samples (Figure 5a) compared to samples from SpraySyn2 (Figure 5b). This effect can be attributed to the fact that the lifetime of particles in high-temperature fields is shorter for SpraySyn2 [23]. All samples display a Type III isotherm with slight hysteresis relative pressure regions, indicating pore-sizes in the low two-digit nm regime (Figure S1). Given the fact that synthesized particles are considerably small (\(<\)10 nm), these hysteresis observed are likely caused by voids between particle-aggregates and agglomerates.  
Figure 5: BET data for \(\gamma\)-Fe\({}_{2}\)O\({}_{3}\) particles prepared by SpraySyn1 (**a**) and SpraySyn2 (**b**). Samples: 0.1 M INN and 0.2 M INN in EtOH + EHA.  
Given the fact that \(\gamma\)-Fe\({}_{2}\)O\({}_{3}\) particles of considerable small size are obtained, all samples display superparamagnetic behavior during measurements by means of vibrational magnetometry conducted at room temperature (Figure S2). As demonstrated graphically in the supplement, no hysteresis in the magnetization functions can be observed. However, the samples display quite different magnetization strengths. In this regard, Table 2 summarizes all four saturation magnetization values (\(M_{\text{S}}\)) measured at a high-field magnetization of \(H=70\) kOe, and the data is compared to the samples' \(d_{\text{PP,BET}}\). As shown, a correlation between \(M_{\text{S}}\) and \(d_{\text{PP,BET}}\) is obtained, consistent with the theory that smaller particle sizes are accompanied by mitigation of \(M_{\text{S}}\)[1; 2; 3]. This data comparison briefly demonstrates the possibility to manipulate the \(M_{\text{S}}\) of superparamagnetic \(\gamma\)-Fe\({}_{2}\)O\({}_{3}\) by changing the burner type and/or the precursor concentration in SFS.
# Offset-Assisted Factored Solution of Nonlinear Systems
## 3 Limitations of the Factored Method When Real Negative or Complex Solutions Are Involved
### Complex Solutions  
If the starting point does not lie in the basin of attraction of a real solution, or simply when real solutions do not exist at all, the factored iterative procedure is able to converge to a complex solution. However, as it is never known in advance whether the starting point is in the basin of a positive, negative or complex solution, it is advisable to always add a sufficiently large positive offset \(m\), as discussed in the previous section. The problem of adding such a positive offset is that, when starting from a real starting point, the iterative process will not abandon the real domain unless a negative component arises by chance in \(y\), which may not happen at all. This is a consequence of the log of a positive real number being also real. Fortunately, this problem is easily solved by adding an imaginary component to the offset \(m\), as illustrated in the following example.  
**example 3**.: Consider again the simple system of the previous examples, but this time with \(p_{1}=2\) and \(p_{2}=0\), which has the real solution \(x=[-2,-2]\) and the complex conjugate solution \(x=[\pm i,1\pm i]\). Starting from \(x^{(0)}=[0,0]\), with \(m=2\), the values of \(x_{1}\) and \(x_{2}\) show initially a sustained oscillatory behavior (see Figure 2) until \(x_{1}\) becomes negative at Iteration 9. Afterwards, the imaginary component of \(x_{1}\) is non-null, and the iterative process manages to converge after 20 iterations to one of the complex conjugate solutions. For other starting points, the oscillations may persist much longer or indefinitely. However, with \(m=2+i\), the factored method quickly converges in six iterations, as shown in Figure 2.  
Figure 2: Evolution of real (\(x_{1}\)) and imag (\(x_{1}\)) as iterations progress for the simple system of Example 3 with \(m=2\) and \(m=2+i\).  
In summary, a positive real offset \(m\) is needed to prevent the iterative process from converging to complex solutions when searching for real negative solutions. Reciprocally, an imaginary component should be added to \(m\) so that complex solutions more easily pop up when real solutions do not exist or are of no interest.
# Data Analysis, Simulation and Visualization for Environmentally Safe Maritime Data
## 1 Introduction
### Factors That Raise Marine Traffic Engineering Awareness
#### 1.2.1 Sea Traffic  
The maritime traffic in the Mediterranean Sea has increased dramatically in recent years due to technological advances in vessels, which have greatly improved the speed, capacity and size. In addition, tourist cruisers choose the eastern Mediterranean for the conduct of the cruise, offering economic and tourism boom in the region. However, the shipping around the area is not thoroughly controlled and lots of dangers are lurking.  
Despite the small size of the Mediterranean Sea in relation to the area covered by the Earth, it is the home for approximately 14-18% of marine species worldwide and about \(\frac{1}{4}\) of organisms that lives in the Mediterranean considered endemic. Characterized by a large number of small islands and narrow channels, where a lot of protected species can find appropriate conditions to survive such as sea turtles, seals, marine mammals and sharks. Consequently, it is important to protect and preserve the eastern Mediterranean area from the devastating impacts of uncontrolled shipping [5].
## 6 Sugars  
Cyanobacteria are generally less tolerant to chemicals than other heterotrophic hosts such as _E. coli_ and yeast, hindering its industrialization. Therefore, as an alternative approach, cyanobacteria are engineered to produce soluble sugars that are not toxic to cyanobacteria and can be directly utilized by heterotrophs. Sucrose is a natural product produced by cyanobacteria as an osmoprotectant. Sucrose can accumulate intracellularly at a concentration of around 300 mM [85; 86], representing a large amount of potential sugar that can be produced. To facilitate sucrose transport across the cellular membrane, sucrose permease (CscB), a sucrose/proton symporter, was expressed in PCC 7942 [46]. As cyanobacteria generate proton gradient from inside of thylakoid membranes and alkalinize the environment, it facilitates removal of sucrose from cytoplasm. The expression of CscB and knockout of glycogen synthesis enabled the production of sucrose up to 2.7 g/L in engineered PCC 7942, representing a significant portion of carbon portioned into sucrose production. Glucose and fructose have also been produced by PCC 7942 [32] upon expression of invertase, which hydrolyzes sucrose.  
In another study, sucrose production through metabolic engineering of PCC 6803 has been examined [47]. It was found that the sucrose accumulation of PCC 6803 was not as high as PCC 7942. Through overexpressing sucrose synthesis genes and knocking out the genes for glucosylglycerol formation, the resulting strain produced 140 mg/L of sucrose in 10 days.  
Mannitol is a sugar alcohol used in the pharmaceutical and food industries. To produce mannitol using recombinant cyanobacteria, PCC 7002 was engineered to express mannitol-1-phosphate dehydrogenase (MtlD) and mannitol-1-phosphatase (Mlp) [45]. Together with glycogen synthesis knocked out, the resulting strain produced 1.1 g/L of mannitol. Interestingly, it was noted that mannitol was exported to the culture medium through an unknown mechanism. These relatively high flux photosynthetic sugar/sugar alcohol production studies indicated that the flux for sugar synthesis is naturally high in cyanobacteria as the overexpression of the genes related to the synthesis of upper glycolytic intermediates were not necessary.
## 5 Discussion
### Research Gaps
#### 5.1.1 Smartphone Users' Activities and Behaviors  
Smartphone users' activities have been categorized into five groups: sensors, services, physical, software, and applications. Each activity is related to several activities or behaviors linked to the sensors based on the permissions granted. Mobile sensors are fundamental in collecting, passing, and processing information within a smartphone application. The sensitive data extracted from the sensors are attractive to hackers. Due to their small capacity, low-cost sensors, and constantly \"ON\" nature, IoT devices often lack the capability to support complex security mechanisms and algorithms [192].  
User behaviors contribute to cyber attacks due to unawareness [12; 89; 90; 101; 112], limited knowledge [93; 98; 109], and unskilled employees in a business [89; 102; 104; 107], resulting in the targeting of smartphone assets such as contacts, bank information, and images. Consequently, granting permissions requested by applications exposes smartphone users to privacy risks [114]. Furthermore, the user behavior and research findings of [13] have been formalized and validated as providing comprehensive security protection and a mitigation model against APT attacks, such as spear phishing, watering holes, and malware attacks.  
Nevertheless, a major limitation of SENSATE is the limited exploration of the human behavioral context concerning intention, device usage, and tasks completed with a smartphone. Resultantly, limited studies have focused on identifying malicious behaviors while a smartphone application retrieves the user's data from sensors [12; 193].
# Numerical Modeling of Temperature Effect on Tensile Strength of Granitic Rock
## 5 Conclusions  
A numerical method to predict thermal cracking induced weakening effects in the tensile strength of granitic rock was developed and validated in this paper. The following conclusions can be drawn:  
* The nonlinear coupled problem of thermal cracking in rock due to a uniform elevated temperature field can be effectively solved with an explicitly staggered approach. The present method, based on embedded discontinuity finite elements, is computationally fast and has physically meaningful model parameters.
* Extreme mass scaling for the mechanical problem can be used in this approach due to the quasi-static nature of the slow heating of a rock sample to a uniform temperature. Particularly, a million-fold density, to increase the critical time step 1000-fold, can be used with virtually no effect on accuracy.
* In modeling, thermal cracking induced reduction of tensile strength of granitic rocks due to a uniform temperature field can be reduced to the deviant behavior of the quartz mineral. This means that it is enough to account for only the temperature dependence of the quartz thermal expansion. Moreover, homogenous and temperature-independent mechanical properties, measured for a rock sample, can thus be used. However, the initial (room temperature) tensile strength parameters should be heterogenous to correctly predict the failure mode in uniaxial tension.
* With this method, the thermal weakening effect can be replicated
## 3 Case Study
### Performance Function and Random Variables  
For simplicity, only the maximum allowable inward displacement of tunnel shotcrete lining is taken as the criterion of its stability. The performance function \(\mathcal{G}_{\text{Tunnel}}(\mathbf{X})\) is obtained using Formula (14). According to the CHTTDC, the maximum design value of the vault settlement \(u_{\text{max}}\) is taken as \(u_{\text{vmax}}=0.1\) m, and the maximum displacement convergence values \(u_{\text{max}}\) of monitoring lines AB, AC, BC, AD, and AE are taken as \(u_{\text{ABmax}}=u_{\text{ACmax}}=0.075\) m, \(u_{\text{BCmax}}=0.072\) m, and \(u_{\text{ADmax}}=u_{\text{AEmax}}=0.087\) m, respectively.  
\[G_{\text{Tunnel}}(\mathbf{X})=u_{\text{max}}-u(E,c,\varphi,\
u) \tag{14}\]  
where \(E\) is rock Young's modulus; \(\
u\) is rock Poisson's ratio; \(\varphi\) is rock friction angle; and \(c\) is rock cohesion.  
\(E\), \(\
u\), \(\varphi\) and \(c\) are taken as the basic random variables of rock with statistical properties, as shown in Table 2. The properties of initial support, second lining, and rock bolt are assumed to be deterministic.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Measuring Points/Lines** & **A** & **H** & **AB** & **AC** & **BC** & **AD** & **AE** & **DE** & **FG** \\ \hline Monitoring displacement/cm & -9.74 & 8.43 & –6.44 & –6.44 & –9.99 & –9.95 & –9.96 & –12.59 & –10.43 \\ \hline \hline \end{tabular}
\end{table}
Table 1: On-site monitoring data of a tunnel section.  
Figure 3: Schematic diagram of tunnel monitoring point layout.
# Optimized Implementation and Analysis of CHAM in Quantum Computing
## 2 Background
### Grover's Algorithm (for Key Search)  
[PERSON]'s algorithm [5] is a quantum search algorithm that derives the desired answer using the superposition and entanglement principles of quantum mechanics. When the function domain size is \(n\), using the [PERSON]'s algorithm reduces the computational complexity to \(\sqrt{n}\).  
The [PERSON]'s algorithm consists of an oracle and a diffusion operator. Among these, the oracle operator is a key component in the algorithm as it has a direct relationship with the overall performance of the algorithm. Namely, it is essential to implement oracle efficiently to optimize the performance of the algorithm.  
1. In order to make the key of \(n\)-qubit superposition states \(|\psi\rangle\), the Hadamard gates are applied to \(k\) of \(n\)-qubit. This ensures that all states of the qubits have the same amplitude: \[|\psi\rangle=H^{\otimes n}|0\rangle^{\otimes n}=\Big{(}\frac{|0\rangle+|1 \rangle}{\sqrt{2}}\Big{)}=\frac{1}{2^{n/2}}\sum_{k=0}^{2^{n}-1}|k\rangle\] (6)
2. The attack-target cipher is implemented as a quantum circuit and arranged in oracle \(f(k)\). Encrypting the known plaintexts of the superposition key produces ciphertexts \(c\) for all key values. Afterwards, if the ciphertext matches the known ciphertext, \(f(k)=1\) and \((-1)^{f(k)}|k\rangle|-\rangle\), so the sign of the solution key value is reversed. \[f(k)=\begin{cases}1\text{ if }Enc(key)=c\\ 0\text{ if }Enc(key)\
eq c\end{cases}\] (7) \[U_{f}(|\psi\rangle|-\rangle)=\frac{1}{2^{n/2}}\sum_{k=0}^{2^{n}-1}(-1)^{f(k)} |k\rangle|-\rangle\] (8)
3. In the final step, the diffusion operator amplifies the amplitude of the negative-signed solution key returned by the oracle. Usually, diffusion operators do not require special skills to implement because their design is general.