esa-sceva/satcom-chunk-collection huggingface dataset:
# Continuous-Wave THz Imaging for Biomedical Samples
## 2 CW THz Single-Point Scanning Imaging
### CW-THz Transmission Single-Point Scanning Imaging
The veins in the leaf had low transmissivity to the THz radiation and were represented as dark regions in the THz image. The results revealed minute details of the leaf vein structure with a submillimeter resolution. In 2012, [PERSON] et al. designed a confocal microscopic imaging system based on a 2.9 THz QCL [25]. The size of the first pinhole was 200 \(\upmu\)m as a spatial filter to obtain the point source, and the size of the pinhole was 300 \(\upmu\)m in front of the detector. Lateral and axial resolutions of 70 \(\upmu\)m and 400 \(\upmu\)m were detected. The size of the focus beam spot was 132 \(\upmu\)m by using the scanning knife-edge method. A fresh leaf was imaged at a step of 50 \(\upmu\)m within the selected local detection area of 200 \(\times\) 200 pixels. In 2014, [PERSON] et al. performed transmission single-point confocal imaging with dried spiders and ants at 2.52 THz [34], the CW THz experiment setup used the SIFIR 50 THz laser and emitted 2.52 THz with average output power was above 50 mW. The scanning step was 0.1 mm, and the spatial resolution was 145 \(\upmu\)m. In 2012, [PERSON] et al. used a horn antenna to replace the pinhole in front of the sample [35] and improved the resolution by increasing the transmission power. CW radiation at 0.2 THz was generated by the Gunn oscillator, and a Schottky diode as detector was used to scan red ginseng point by point, obtaining a THz image with a resolution of 500 \(\upmu\)m.  
Although the transmission mode imaging system has high resolution and good contrast, it is more restricted with fresh biological samples of moderate absorption, which is caused by the THz radiation being strongly absorbed by water. Unfortunately, the preparation of thin specimens with exact thicknesses is difficult. So, the reflection mode imaging is more common for biological tissues of strongly absorbing or scattering samples.
## 3 Rational for Optimization in WSNs
### Domains of Optimizations in Wireless Sensor Networks
#### 3.2.2 QoS and Security  
Security and QoS are two critical network issues in WSNs. Security mechanisms are used to maintain confidentiality, integrity, and availability of the services provided by WSNs. On the other hand, in real time applications QoS enables the sensed data to be delivered within a bounded delay period. QoS research has focused for several years on problems such as packet loss rate, throughput, bandwidth guarantees, jitter, delay, and other performance-related parameters when transmitting data over a specific network. But interestingly the issue of security is rarely mentioned. In fact, the earlier approaches were such that, if someone wants QoS and network performance for the data traffic, security cannot be part of the equation.  
So the question is still out there, whether the network QoS and security are still orthogonal to each other or should one consider security as another QoS parameter and integrate it with the performance-related QoS parameters. So, the main question is, \"Can QoS and security coexist or not\"? Our conjecture is that network QoS and security can coexist if correct security policies are used in the right places.  
The mechanisms of security and QoS are interdependent. Security mechanism choices impact the effectiveness of QoS and _vice versa_. QoS requires security mechanisms to ensure appropriate service assignment. A poor level of security measurement selection can massively jeopardize the performance of the network. Both services are necessary for safe and sound network operations. If we do not have information about QoS requirements, a poor choice of encryption endpoints may reduce the effectiveness of QoS performance. On the other hand, without information on security requirements, a poor assignment of QoS performance parameters may lead to denial of service for vital but low bandwidth data.So lack of good understanding of these interactions and inappropriate service level selection can leak extra information about the importance of packets in the traffic stream, but clever manipulation of QoS parameters like data freshness/timeliness might even help to reduce leakage of information through channels. Therefore, both services must be considered together when designing and implementing a network infrastructure to achieve the best possible security and QoS levels.
# MANET Routing Protocols' Performance Assessment Under Dynamic Network Conditions
## 4 Methodology
### Scenarios and Discussion
#### 4.3.4 Scenario 4: 500 Nodes  
In the most complex scenario with 500 nodes, the routing protocols were thoroughly tested. Performance metrics indicated significant differences in protocol efficiency.
# An Optimal Authentication Scheme through Dual Signature for the Internet of Medical Things
## 5 Proposed Dual Signature Scheme  
Our proposed dual signature scheme can be made by utilizing the following five sub-phases. All the symbols used in the proposed dual signature scheme are explained in Table 1. Figures labelled Appendices A and B depict formal validation of proposed protocol utilizing Scyther.  
\begin{table}
\begin{tabular}{c c c} \hline \hline \multicolumn{1}{c}{S. No} & \multicolumn{1}{c}{**Symbols**} & **Description** \\ \hline
1 & \(PB_{\text{IoMT}}\) & Public key of IoMT device \\ \hline
2 & \(\varphi_{\text{IoMT}}\) & Private key of IoMT device \\ \hline
3 & \(\mathcal{D}\) & Divisor on hyper elliptic curve \\ \hline
4 & \(F^{n}\) & A finite field of hyper elliptic curve \\ \hline
5 & \(PB_{\text{PDA}}\) & Public key of PDA \\ \hline
6 & \(\varphi_{\text{PDA}}\) & Private key of PDA \\ \hline
7 & \(PB_{\text{AP}}\) & Public key of AP \\ \hline
8 & \(\varphi_{\text{AP}}\) & Private key of AP \\ \hline
9 & \(m\) & Plaintext that contains patient health information \\ \hline
10 & \(C\) & Cipher text that contains patient health information in encrypted form \\ \hline
11 & \(\mathcal{L}\) & Used as a hash function \\ \hline
12 & \(n\) & Represents a large number and its value as \(n\geq 2^{80}\) \\ \hline
13 & DS & Represents a dual signature \\ \hline \hline \end{tabular}
\end{table}
Table 1: Symbols used in the proposed scheme.  
Figure 2: Proposed scheme.
## 3 Reliability Modelling and Evaluation
### Reliability Modelling and Evaluation under Trigger Mechanism 2
** \\ \hline
1 & \(0\leq u_{2}<n-1,0\leq w_{2}<k_{2}-1\) & \(p\left\{Y_{h_{2}}=(u_{2},0)|Y_{h_{2}-1}=(u_{2},w_{2})\right\}\) & \(q_{2}\) \\
2 & \(0\leq u_{2}<n-1,0\leq w_{2}<k_{2}-1\) & \(p\left\{Y_{h_{2}}=(u_{2}+1,0)|Y_{h_{2}-1}=(u_{2},w_{2})\right\}\) & \(p\) \\
3 & \(0\leq u_{  
where \(\mathbf{P}_{2_{(\gamma-1)\times(\gamma-1)}}\) is a transition probability matrix between each transient state, \(\mathbf{Q}_{2_{(\gamma-1)\times 1}}\) is the column matrix from each transient state to the absorption state, \(\mathbf{0}_{2_{1\times(\gamma-1)}}\) is a zero matrix, which is the transition probability matrix from the absorption state to transient state, and \(\mathbf{E}_{2_{1\times 1}}\) is an identity matrix representing the probability from the absorption state to the absorption state. Let \(N_{2}\) be the total number of shocks before the system failure. We can derive some reliability indices related to the shock numbers \(N_{2}\) by the following expressions. The distribution function of \(N_{2}\) is  
\[P\{N_{2}\leq l\}=\sum\limits_{j=1}^{l}\boldsymbol{\alpha}_{2}\mathbf{P}_{2}{}^ {j-1}\mathbf{e^{\prime}}_{2_{\gamma-1}}=1-\boldsymbol{\alpha}_{2}\mathbf{P}_{2 }{}^{l}\mathbf{e^{\prime}}_{2_{\gamma-1}}, \tag{8}\]  
where \(\boldsymbol{\alpha}_{2}=(1,0,\ldots,0)_{1\times(\gamma-1)}\), and \(\mathbf{e}_{2_{\gamma-1}}=(1,\ldots,1)_{1\times(\gamma-1)}\). The probability mass function of the shock numbers \(N_{2}\) is  
\[P\{N_{2}=l\}=\boldsymbol{\alpha}_{2}\mathbf{P}_{2}{}^{l-1}\mathbf{Q}_{2}. \tag{9}\]  
The expected shock number \(E(N_{2})\) is  
\[E(N_{2})=\boldsymbol{\alpha}_{2}(\mathbf{I}_{2}-\mathbf{P}_{2})^{-1}\mathbf{ e^{\prime}}_{2_{\gamma-1}}. \tag{10}\]  
We can derive the probability density function of \(T\) when \(N_{2}=n\):  
\[f_{2}(t)= \begin{cases}\lambda^{n}t^{n-1}\exp(-\lambda t)/(n-1)!,&t\geq 0\\ 0,&t<0.\end{cases}  \tag{11}\]  
In addition, we can obtain the probability density function of \(T\) by using the Law of Total Probability:  
\[f_{2}(t)= \begin{cases}\sum\limits_{l=1}^{\infty}\Big{[}\Big{(}\lambda^{l}t^{l- 1}\exp(-\lambda t)/(l-1)!\Big{)}\times P\{N_{2}=l\}\Big{]},&t\geq 0\\ 0,&t<0.\end{cases}  \tag{12}\]  
The expected system life \(E(T_{2})\) is  
\[E(T_{2})=\int\limits_{0}^{\infty}tf_{2}(t)dt. \tag{13}\]  
Then, we can show the reliability function of the system as  
\[ \begin{split} R_{2}(x)&=P\{T>x\}\\ &=P\Big{\{}\sum\limits_{i=1}^{N_{2}}X_{i}>x\}\\ &=1-\int_{0}^{x}\sum\limits_{l=1}^{\infty}\Big{[}\Big{(}\lambda^{l}t^{l- 1}\exp(-\lambda t)/(l-1)!\Big{)}\times P\{N_{2}=l\}\Big{]}dt.\end{split}  \tag{14}\]
# Harnessing Digital Twins for Sustainable Agricultural Water Management: A Systematic Review
## 2 Background
### DT Architecture
#### 2.3.2 Collection and Integration of Data from Multiple Sources  
Researchers have measured soil moisture using various methods, including soil moisture sensors, thermal imaging, and remote sensing techniques [52; 53; 54]. Sensors and remote sensing data can be integrated with DTs to continuously gather data from the physical environment [55; 56]. These real-time data keep the DT updated and enhances decision-making.  
The Internet of Things (IoT) is the network of linked physical devices equipped with sensors, an IoT platform, and user interfaces, allowing them to gather and share data over the internet autonomously, without human intervention [57]. The adoption of IoT technology in the agriculture sector is growing rapidly [58]. This technology enhances efficiency, reduces waste, and supports sustainable farming practices [59]. IoT-based smart sensors collect data on soil moisture, temperature, wind, and humidity, which are then analyzed to assess the soil's water needs.  
Recent advancements in sensor technologies have greatly improved the quality and accessibility of remote sensing data. These data play a key role in monitoring floods, managing water resources, and in soil and water conservation efforts in agriculture. Satellite-based remote sensing technologies enable the near-real-time provision of spatio-temporal information for fields. Irrigation, as the primary consumer of agricultural water, benefits significantly from these developments. Unlike IoT sensors, which provide point-source soil moisture data and may not capture the variability across a diverse agricultural environment, remote sensing offers a broader solution. With high-resolution imagery, it can deliver pixel-level data, representing conditions across small areas and plants. Earth observation satellites offer an innovative and efficient method for monitoring soil moisture and other field variables like evapotranspiration [60]. Indices like Normalized Difference Vegetation Index (NDVI) are commonly applied with crop coefficients (Kc), essential for determining crop water requirements [61]. Furthermore, Surface Energy Balance (SEB) methods are used to provide more accurate soil moisture estimates [62]. Satellite imagery also aids in mapping landscape features like soil type and slope, which are useful for soil moisture [63]; when combined with IoT sensor data, it enhances the accuracy. ML tech niques analyze data by automating data processing, segmentation, and feature extraction. This advanced method streamlines the analysis of large datasets, enabling an efficient and accurate identification of key features and patterns within the data, ultimately enhancing decision-making processes [64]. Now, estimating evapotranspiration [65] and soil moisture [66] using remote sensing is a well-established method in agricultural water management. This approach leverages satellite and aerial imagery to monitor and assess water needs, ensuring efficient irrigation practices and optimizing water use for improved crop health and yield.
# Selecting a Proper Microsphere to Combine Optical Trapping with microsphere-Assisted Microscopy
###### Abstract  
Microsphere-assisted microscopy serves as an effective super-resolution technique in biological observations and nanostructure detections, and optical trapping is widely used for the manipulation of small particles like microspheres. In this study, we focus on the selection of microsphere types for the combination of the optical trapping and the super-resolution microsphere-assisted microscopy, by considering the optical trapping performances and the super-resolution imaging ability of index-different microspheres in water simultaneously. Finally, the polystyrene (PS) sphere and the melamine formaldehyde (MF) sphere have been selected from four typical index-different microspheres normally used in microsphere-assisted microscopy. In experiments, the optically trapped PS/MF microsphere in water has been used to achieve super-resolution imaging of a 139 nm line-width silicon nanostructure grating under white light illumination. The image quality and the magnification factor are affected by the refractive index contrast between the microspheres and the immersion medium, and the difference of image quality is partly explained by the photonic nanojet. This work guides us in selecting proper microspheres, and also provides a label-free super-resolution imaging technique in many research fields.  
optical trapping; super-resolution microscopy; microsphere; photonic nanojet +
Footnote †: journal: Applied Physics Letters
## 4 Analysis And Assessment
### Experimental Strategy
#### 4.1.2 Availability of Multi-Frequency Models  
Not all BDS/GPS satellites have third frequency signals. The number of BDS/GPS satellites with dual-frequency data is not equal to the number of BDS/GPS satellites with triple-frequency data. We illustrate the number of BDS or GPS satellites with dual-frequency or triple-frequency in DOY 100, 2018, which are shown in Figures 2 and 3, respectively.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Setting** \\ \hline Rinex file & xxxx1000.18o \\ Precise orbit product & gbm19962.sp3 \\ Precise clock product & gbm19962.clk \\ Pole shift/ut1-utc & gbm19962.erp \\ Antenna phase center & igs14.atx \\ Positioning mode & static \\ Estimation algorithm & Standard Kalman Filter \\ Reference coordinate & gbm19962.clk \\ Sample rate & 30 s \\ Elevation cutoff angle & \(5^{\circ}\) \\ \hline \hline \end{tabular}
\end{table}
Table 4: Parameter settings.  
Figure 1: Distribution of the stations used in this experiment.  
Figure 2: The number of BDS/GPS satellite with dual-frequency observation data.  
The results show that the number of GPS satellites with triple-frequency data is less than five on most of the time. Except the triple-frequency GPS-only, the triple-frequency BDS/GPS, the triple-frequency BDS-only, the dual-frequency BDS/GPS, the dual-frequency BDS-only, and the dual-frequency GPS-only can be used to realize daily precise point positioning. The triple-frequency data causes IFB bias and the BDS/GPS combination causes ISB bias. Before we process data by using different observation models, we analyzed the influence of ISB and IFB on positioning errors.
## 6 Conclusions  
Lamb-wave attenuation coefficients were determined for fourteen sheet and plate materials using ultrasonic transducer excitation and point-contact receivers. Sample materials ranged from steel, Al, and silicate glass with low attenuation to polymers and a fiber composite with much higher attenuation. Experimentally obtained Lamb-wave attenuation coefficients, \(\alpha\)-S and \(\alpha\)-A, for symmetric and asymmetric modes were mostly for the zeroth mode. Plots of \(\alpha\)-S\({}_{\rm o}\) and \(\alpha\)-A\({}_{\rm o}\) values against frequency were found to coincide reasonably well to theoretically calculated curves, which utilized the Disperse program and a parametric method based on Disperse calculations. The Disperse calculations used bulk-wave attenuation coefficients as input parameters, which were previously published  
Figure 20: A cross-plot of longitudinal and transverse attenuation coefficients, \(\alpha_{\rm L}\) and \(\alpha_{\rm T}\), of 159 various solids. Solid blue line: \(\alpha_{\rm T}=2.79\ \alpha_{\rm L}\), dotted blue line: \(\alpha_{\rm T}=\alpha_{\rm L}\). Data are from [14; 45].  
or newly measured. Although further refinements are needed, this study confirmed that the Disperse program predicts Lamb-wave attenuation coefficients for elastically isotropic materials within the limitation of contact ultrasonic techniques used.  
The calculated \(\alpha\)-S and \(\alpha\)-A values were found to be dominated by the \(\alpha_{\mathrm{T}}\) contribution. Often \(\alpha\)-A\({}_{\mathrm{o}}\) coincided with \(\alpha_{\mathrm{T}}\). This was in Viktorov calculations and in Disperse results, which were separated into the contributions from \(\alpha_{\mathrm{L}}\) and \(\alpha_{\mathrm{T}}\) by the use of the Disperse-based parametric method. The physical origin of this effect is unknown.  
Displacement measurements were quantified using Rayleigh wave calibration, and peak displacements after 200-mm propagation were found to range from 10 pm to 1.5 nm. The point-contact sensor was capable of detecting 1-pm displacement with a 40 dB signal-to-noise ratio with signal averaging and had equivalent noise of 4.3 fm/\(\surd\)Hz.  
Approximate expressions for \(\alpha\)-S\({}_{\mathrm{o}}\) and \(\alpha\)-A\({}_{\mathrm{o}}\) are obtained and a correlation was found between bulk-wave attenuation coefficients, i.e., \(\alpha_{\mathrm{T}}\) = 2.79 \(\alpha_{\mathrm{L}}\), for over 150 materials.  
The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/app12136735/s1](https://www.mdpi.com/article/10.3390/app12136735/s1)]([https://www.mdpi.com/article/10.3390/app12136735/s1](https://www.mdpi.com/article/10.3390/app12136735/s1)), A-B parameters table.xlsx.  
This research received no funding.  
Not applicable.  
The author is grateful to [PERSON] for conducting most of the Disperse calculations, to [PERSON] for applying extraordinary Disperse procedures to resolve difficulty encountered in a highly attenuating medium, and to [PERSON] for attempting to extract solutions to Viktorov equations.  
The author declares no conflict of interest.
# An Efficient Advantage Distillation Scheme for Bidirectional Secret-Key Agreement
## 2 Original Two-Way Wiretap Channel  
### Transmission Scheme  
A TWWC between [PERSON] and [PERSON] was described in [18], in which the channel from [PERSON] to [PERSON] was considered to be error-free due to the powerful Low Density Parity Check (LDPC) codes. In this paper, we consider an original TWWC model shown in Figure 2, in which both main channel and eavesdropper channel are not error free. The notations used throughout this paper are given in Table 1. In the conventional TWWC, to initiate a secure communication, [PERSON] first transmits a random sequence \(Q\) to [PERSON]. For \(i=1,2,\cdots,l\), the raw keys are \(M^{i}_{ab}\) and \(M^{i}_{ba}\), the error vectors of the main channel and the eavesdropper's channel are \(E^{i}_{ab}\), \(E^{i}_{ba}\), \(E^{i}_{ae}\), and \(E^{i}_{be}\). \(E^{0}_{ba}\) denotes the error vector of the main channel and \(E^{0}_{be}\) denotes the error vector of the eavesdropper's channel. The superscript \(0\) represents the process where [PERSON] sends a random sequence \(Q\) to [PERSON] and \(i\) represents that a raw key \(M\) is transmitted in the \(i\)-th round. The subscripts \(ab\), \(ba\) and \(ae\), \(be\) denote sequences transmitted from [PERSON] to [PERSON], from [PERSON] to [PERSON] and sequences wiretapped from [PERSON] to [PERSON], and from [PERSON] to [PERSON]. We assume that the length of each sequence is \(n\), so that the received sequences of [PERSON] and [PERSON] are  
\[T_{1}=E^{0}_{ba}\oplus Q, \tag{1}\] \[TA_{1}=E^{0}_{be}\oplus Q, \tag{2}\]  
respectively, where the binary operator \(\oplus\) denotes exclusive OR (XOR) operation [20]. Then, [PERSON] uses the received sequence \(T_{1}\) to calculate  
\[U_{1}=T_{1}\oplus M^{1}_{ab}. \tag{3}\]  
Figure 2: Advantage Distillation Scheme based on the original two-way wiretap channel. [PERSON] transmits \(U_{1}\) to [PERSON] through the main channel and [PERSON] may wiretap this \(U_{1}\) through the eavesdropper's channel. [PERSON] and [PERSON] can receive the noisy version of \(U_{1}\), respectively, as  
\[V_{1}=U_{1}\oplus E_{ab}^{1}, \tag{4}\] \[W_{1}=U_{1}\oplus E_{ae}^{1}. \tag{5}\]  
Since [PERSON] knows the random sequence \(Q\), he can XOR \(Q\) to \(U\) as  
\[\bar{M}_{ab}^{1}=V_{1}\oplus Q=M_{ab}^{1}\oplus E_{ba}^{0}\oplus E_{ab}^{1}. \tag{6}\]  
[PERSON] only knows \(TA_{1}\), which is the noisy version of \(Q\), and she can only XOR \(TA_{1}\) to \(W_{1}\) as  
\[Z_{ae}^{1}=W_{1}\oplus TA_{1}=M_{ab}^{1}\oplus E_{ba}^{0}\oplus E_{be}^{0} \oplus E_{ae}^{1}. \tag{7}\]  
As shown in Figure 3, the raw key \(M\) is transmitted unidirectionally from [PERSON] to [PERSON] in the original TWWC. By comparing \(\bar{M}_{ab}^{1}\) and \(Z_{ae}^{1}\), [PERSON] has one more noisy term than [PERSON]. Therefore, as long as the main channel is not worse than the passive eavesdropper's channel (the weight of \(E_{ba}^{0}\) is not higher than that of \(E_{bc}^{0}\) and \(E_{ae}^{1}\)), it is guaranteed that [PERSON] is unable to arrive at the same sequence as
# Two-Wire Power Line Microwave Communication Using Low-Loss Modes
###### Abstract  
A closed-form solution for the common and differential modal currents induced on a pair of infinitely long parallel conductors by a source, field coupled to a power line, is derived. For lossy conductors, the current consists of a continuous spectrum of radiation modes and (for the common mode) a modified low-loss Sommerfeld-Goubau (SG) mode and (for the differential mode) a quasi-TEM mode. This model is used to investigate the influence of a parallel conductor on microwave power line communication systems. When the complete current spectrum is used, it is shown that the SG mode is not the primary reason why low-loss communication is possible on power lines for distances on the order of 100 m. Nevertheless, and consistent with previous research, microwave communication using power lines has advantages over free space communication, and for typical parameters, the performance of these systems can be enhanced if the power line contains more than one conductor.  
power line communication; electromagnetic propagation +
Footnote †: journal: Applied Sciences