esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 PSA in a DOF
### DOF with Multiple Frequency of Dispersion Modulation  
One impediment to the use of the high-order gain sidebands of a DOF-based PSA for amplification purposes is its narrow bandwidth. However, using of multiple closely spaced frequencies of dispersion modulation can alleviate this restriction to some degree [18]. Note that different dispersion modulation frequencies will inevitably have their individual gain band centers at different frequencies and hence the combined effect will lead to a wider gain band. Thus we consider the case where modulation of the fiber core diameter is given by a superposition of three sinusoidal functions:  
\[a(z)=\bar{a}+\bar{a}_{1}\sin\left(\frac{2\pi}{z_{m1}}z\right)+\bar{a}_{2}\sin \left(\frac{2\pi}{z_{m2}}z-1.1\right)+\bar{a}_{3}\sin\left(\frac{2\pi}{z_{m3}}z \right), \tag{28}\]  
where \(\bar{a}=2.1\) um, \(\bar{a}_{1}=0.08\) um, \(\bar{a}_{2}=0.1\) um, \(\bar{a}_{3}=0.04\) um, \(z_{m1}=40\) m, \(z_{m2}=40.5\) m, and \(z_{m3}=41.5\) m. The amplitudes and phases of the sine functions are selected so as to provide a uniform amplification in the band from \(\Omega_{ps}(2\pi)^{-1}=1.28\) THz to \(\Omega_{ps}(2\pi)^{-1}=1.32\) THz. The corresponding calculated dispersion parameters are shown in Figure 6a.  
Figure 6b,c show the signal gains calculated for \(q=1\) and \(q=2\) respectively for multi-frequency modulation for different pump input phases. For \(q=1\), the gain bandwidth is found to be 40 GHz with a gain ripple of 1 dB for \(\theta=2\) rad. This is a significant improvement over the DOF with a single dispersion modulation frequency [see Figure 5a,c] where the gain bandwidth was 22 GHz. Nevertheless, an increase in bandwidth for the multi-frequency modulation is accompanied by a decrease in the peak gain of about 15 dB.  
To investigate this further we plot in Figure 7 the full gain spectrum dependence of the system on the input pump phase \(\theta\) for \(q=1\) and \(q=2\). The signal gain is found to be a periodic function of \(\theta\), as is expected in a traditional PSA. The positive and negative gains with an extinction of about 24 dB indicate a strong squeezing of the signal and idler modes [45]. While for \(q=1\), the peak of the gain band corresponds to \(\theta=-1\pm\pi\), \(-1\pm 2\pi,\dots\), for \(q=2\) the peak gain corresponds to a different value \(\varphi_{0}=-1.87\pm\pi\), \(-1.87\pm 2\pi,\dots\). This feature of the gain profile is associated with the dependence of the gain on the modulation phase of the different dispersion modulation components.  
Figure 6: (a) Fiber dispersion parameters as a function of the propagation length. (b,c) Plot of gain of the signal as a function of the pump-signal frequency separation for different values of the initial phase of the pump wave \(\theta\). \(q=1\) in (b) and \(q=2\) in (c). Fiber length \(L=1.4\) km, \(\gamma=9.44\) (W km)\({}^{-1}\). Other fiber parameters are provided in text.
## 5 Conclusions  
A thorough investigation of Newtonian heating in addition to slip effects on the unsteady magnetohydrodynamic (MHD) flow of an Oldroyd-B fluid near an infinitely long plate was analyzed in this research. The exact expressions of the analytical solution to non-dimensional equations of velocity and temperature were explored by employing the Laplace integral transformation under slipping boundary conditions under Newtonian heating. Many graphs were portrayed to examine the effects of various physical parameters such as the time relaxation parameter, \(\lambda_{1}\), magnetic number \(M\), Prandtl number \(Pr\), Grashof number \(Gr\) and the time retardation parameter \(\lambda_{2}\). The graphical demonstration for the temperature profile and velocity field for several connected parameters under slip conditions and under no-slip conditions. The obtained results are summarized as:  
* The temperature graphs show that the temperature profile decreases for higher values of \(Pr\).
* The graphs for the velocity field under slip conditions as well as the velocity field under no-slip conditions show that the effects of \(\lambda_{1}\) and \(\lambda_{2}\) on the velocity contour are quite the opposite.
* From the graphs, one can see that the elevated values of \(M\) and \(Pr\) reduced the velocity curve.
* The velocity profile was stimulated in function of the increasing values of \(Gr\).
* It can be observed that the velocity profile for no-slip flow is lower than the velocity profile for slip flow.
* It was analyzed that for both functions \(f(t)=e^{at}\) and \(f(t)=sint\), the velocity field represents the same curve pattern for all the involved system parameters.  
M.B.R.: Conceptualization, Investigation, Methodology, Software and final editing. J.A.: Data Curation, Data Anaysis, Project administration, Validation, Supervision, Formal analysis. A.U.R.: Validation, Investigation Writing, Reviewing and Editing, Initial writing, Visualization. All authors have read and agreed to the published version of the manuscript.  
The work in this paper has been supported by the Polish National Science Centre under the grant OPUS 14 No. 2017/27/B/ST8/01330.  
Not Applicable.  
During the current study, no data sets were developed or investigated. Thus, no data sharing is applicable to this article.  
Figure 12: Velocity field under slip conditions as well as the velocity field under no-slip conditions for different \(\lambda_{2}\) values when \(f(t)=sint\), \(t=1.5\), \(Gr=3.5\), \(\lambda_{1}=0.6\), \(Pr=0.71\), \(M=2\).
## 4 Results
### Influence of the Air-Gap Length between Adjacent Magnets
The influence of the shrouding effect is less significant to axial force than to torque. As well as for torque, the influence of the shrouding effect on the maximum axial force is more significant with the increasing air-gap length. Analysis of the influence of air-gap length between adjacent magnets showed that for the case of the coupling with ferromagnetic backings, the air-gap length has minor impact on torque in the investigated range of the air-gap length when the total volume of the magnets remained constant. The maximum torque of the coupling with non-ferromagnetic backings is more sensitive when compared to the torque of the coupling with ferromagnetic backings to the air gap length. On the contrary, the maximum axial force is more sensitive to the air-gap length for the case of the coupling with ferromagnetic backings.
# Prestack Seismic Inversion via Nonconvex L\({}_{1-2}\) Regularization
## 2 Method
### Construction of the Inversion Objective Function  
According to Bayesian inversion theory and the definition of the L\({}_{1-2}\) regularized prior distribution function, the inversion objective function that simultaneously satisfies the P impedance, S impedance, and density constraints is expressed as (see Appendix A for details):  
\[\hat{\mathbf{m}}=\arg\min\left\{\frac{1}{2}\|\mathbf{W}\mathbf{C}\mathbf{r}- \mathbf{s}\|_{2}^{2}+\frac{\beta}{2}\|\mathbf{\Phi}\mathbf{r}-\mathbf{\zeta}\|_{2}^{2 }+\lambda(\|\mathbf{r}\|_{1}-\|\mathbf{r}\|_{2})\right\} \tag{12}\]  
where \(\beta\) is the weight coefficient for the low-frequency P impedance, S impedance, and density models and \(\lambda\) is the regularization tuning parameter that controls the sparsity of the parameters that will be used as input values in the inversion.  
If we define \(\mathbf{G}=\left[\begin{array}{c}\mathbf{W}\mathbf{C}\\ \sqrt{\beta}\mathbf{\Phi}\end{array}\right]\) and \(\mathbf{b}=\left[\begin{array}{c}\mathbf{S}\\ \sqrt{\beta}\mathbf{\xi}\end{array}\right]\), then Equation (12) can be further simplified into a nonconvex L\({}_{1-2}\) regularization criterion:  
\[\hat{\mathbf{r}}=\arg\min\left\{\frac{1}{2}\|\mathbf{G}\mathbf{r}-\mathbf{b}\| _{2}^{2}+\lambda(\|\mathbf{r}\|_{1}-\|\mathbf{r}\|_{2})\right\} \tag{13}\]
## Results and Discussion
### Biological Evaluation
#### 3.2.2 Antiproliferative Activity of 6a-j  
The antiproliferative activity of compounds 6a-j are listed in Table 1 as values of IC\({}_{50}\). All the tested compounds displayed excellent antiproliferative activity against non-small cell lung cancer cell lines 'A549' and human cervical cancer cells lines 'HeLa' tested. Among them, compound 6c displayed the highest antiproliferative activity against the cell lines 'A549' (4.35 uM) and 'Hela' (4.09 uM). Whereas positive control gefitinib showed less antiproliferative activity against the cell lines 'A549' (15.23 uM) and 'Hela' (7.35 uM). Besides compound 6c, another three bromo derivatives of \(N\)-benzylisatin-aryl hydrazones (6d, 6f and 6g) showed excellent antiproliferative activity, which is comparable to the control gefitinib. Detail explanations and SARs study are given below.  
Data represent means \(\pm\) SD obtained from three different experiments. Cell lines used as follows, non-small cell lung cancer cell lines 'A549' and human cervical cancer cells lines 'HeLa'. Gefitinib was used as positive controls.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & & & \\ \hline
4 & – & 14 \(\pm\) 2.15 & 46 \(\pm\) 1.30 \\
6a & 4-N(CH\({}_{3}\))\({}_{2}\) & 23.7 \(\pm\) 0.69 & 25.1 \(\pm\) 0.95 \\
6b & 4-Cl & 22 \(\pm\) 1.11 & 14.8 \(\pm\) 0.94 \\
6c & 4-OH & 4.35 \(\pm\) 0.05 & 4 \(\pm\) 0.09 \\
6d & 2-Br & 7.3 \(\pm\) 0.52 & 6.7 \(\pm\) 0.17 \\
6e & 3-Br & 41 \(\pm\) 1.20 & 9.1 \(\pm\) 0.35 \\
6f & 4-Br & 7.30 \(\pm\) 0.03 & 7.4 \(\pm\) 0.20 \\
6g & 2-CH\({}_{3}\) & 7.5 \(\pm\) 0.11 & 7.7 \(\pm\) 0.21 \\
6h & 3-CH\({}_{3}\) & 8.4 \(\pm\) 0.25 & 13.4 \(\pm\) 0.35 \\
6i & 4-CH\({}_{3}\) & 17 \(\pm\) 0.70 & 18.5 \(\pm\) 0.65 \\
6j & 4-SCH\({}_{3}\) & 14.6 \(\pm\) 0.53 & 9 \(\pm\) 0.86 \\
**Gefitinib** & – & 15.2 \(\pm\) 0.48 & 7.3 \(\pm\) 0.42 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Antiproliferative activity of \(N\)-benzylisatin-aryl hydrazones (6a-j).
# Scaled Model Simulation and Experimental Verification of Submarine Flexible Pipeline Laying System
## 1 Introduction
The mechanical properties of the pipeline-laying process are investigated using a scaled-down model of the submarine pipeline-laying system and experimental conditions that simulate the loads of the marine environment. From the overall scheme of the flexible pipe-laying system, the forces during the flexible pipe-laying process are studied, a scale model is established using the similarity principle, a scale model of the laying tower is established using the similarity principle, and indoor tests are conducted on the dangerous area of the tower during the laying of the pipeline through model tests to verify the safety of the laying tower.
# Low-Light Photodetectors for Fluorescence Microscopy
###### Abstract  
Over the years, fluorescence microscopy has evolved and has become a necessary element of life science studies. Microscopy has elucidated biological processes in live cells and organisms, and also enabled tracking of biomolecules in real time. Development of highly sensitive photodetectors and light sources, in addition to the evolution of various illumination methods and fluorophores, has helped microscopy acquire single-molecule fluorescence sensitivity, enabling single-molecule fluorescence imaging and detection. Low-light photodetectors used in microscopy are classified into two categories: point photodetectors and wide-field photodetectors. Although point photodetectors, notably photomultiplier tubes (PMTs), have been commonly used in laser scanning microscopy (LSM) with a confocal illumination setup, wide-field photodetectors, such as electron-multiplying charge-coupled devices (EMCCDs) and scientific complementary metal-oxide-semiconductor (sC-MOS) cameras have been used in fluorescence imaging. This review focuses on the former low-light point photodetectors and presents their fluorescence microscopy applications and recent progress. These photodetectors include conventional PMTs, single photon avalanche diodes (SPADs), hybrid photodetectors (HPDs), in addition to newly emerging photodetectors, such as silicon photomultipliers (SiPMs) (also known as multi-pixel photon counters (MPPCs)) and superconducting nanowire single photon detectors (SSPDs). In particular, this review shows distinctive features of HPD and application of HPD to wide-field single-molecule fluorescence detection.  
low-light photodetectors; fluorescence microscopy; time-resolved fluorescence microscopy; hybrid photodetector (HPD); single-molecule fluorescence detection +
Footnote †: journal: Applied  
19 February 2021  
Accepted: 17 March 2021  
Published: 19 March 2021
# Device-to-Device (D2D) Multi-Criteria Learning Algorithm Using Secured Sensors
## 4 Simulation Setup  
This section presents the simulation configuration to evaluate the performance of the proposed algorithm. We experimented with the proposed algorithm, CTEER [25], and QL-MAC [27] solutions in terms of energy consumption, packet delivery ratio, packet disturbance, data latency, and computational complexity. The experiments were performed under varying rounds and the varying number of nodes using NS-3. Initially, nodes have homogeneous energy levels of 5 joules. The transmission range was set to 10 m. We deployed varying sensor nodes in the field of 300 \(\times\) 300 m with a static sink. Sensor nodes are mobile with an installed GPS. Additionally, we assumed the number of malicious nodes to be 10. The data traffic between connected devices is a type of Constant Bit Rate (CBR).  
We assumed the energy model as discussed in [34; 35]. Equations (10) and (11) define the energy consumption by exploiting the transmitted and received data bits:  
\[E_{tx}(k,d)=\left\{\begin{array}{l}E_{elect}*k+k*E_{fs}*d^{2}\;if\;d<d_{0}\\ E_{elect}*k+k*E_{amp}*d^{4}\;if\;d\;\geq\;d_{0}\end{array}\right. \tag{10}\]  
\[E_{rx}(k)=E_{elect}*k \tag{11}\]  
where \(E_{tx}\) and \(E_{rx}\) are the transmitting and receiving energy, \(k\) is data bits, \(d\) is the distance among sensor nodes, \(E_{elect}\) is the amount of consumed energy per data bit, and the energy of the transmitting amplifier is denoted by \(E_{fs}\). Table 3 illustrates the parameters for simulation configuration.
# Simplified Vibration PSD Synthesis Method for MIL-STD-810
## 2 Fatigue Damage Spectrum (FDS)  
### FDS in General  
Fatigue Damage Spectrum represents the cumulative damage due to the random responses of a series of Single Degree of Freedom (SDOF) systems, with varying natural frequency, excited by random acceleration, both in the time and frequency domain [5]. So, the calculation of FDS is based on the response of SDOF system, which is the virtual specimen, to the input vibration. It has been shown that the velocity response is proportional to stress [7; 8]. Once a stress time history is given, a stress histogram can be derived by the various counting methods and then damage index can be calculated for each stress level in case the slope of S-N (stress-number) curve in log-log plot is given and finally the total damage can be simply summed thanks to the cumulative damage law. The FDS of the frequency range of interest is derived by changing the resonant frequency of the virtual specimen and repeating the entire process as shown in Figure 1.  
Figure 1: Flowchart of fatigue damage spectrum (FDS) calculations, (**a**) input acceleration, (**b**) Single Degree of Freedom (SDOF) system which is the virtual specimen, (**c**) velocity response, (**d**) stress waveform which is obtained by multiplying k to the velocity response, (**e**) stress counting and idealized stress–number (S-N) curve, (**f**) accumulation of damage index, (**g**) FDS.  
The concept of FDS was explained in time domain above, but a lot of researchers calculate FDS in frequency domain. The paper cited in many FDS literature is that of [PERSON] (1986). This is an article on the structural fatigue of aircraft, which describes the basic concept well, but the input is not vibrations but aerodynamic forces. The most extensive book on vibration fatigue is the [PERSON]'s five-volume books [PERSON] (1980), which presents generalized formulas for accurate calculations and simplified equation based on some assumptions. [PERSON] described the application of FDS based on the pseudo-velocity response of the SDOF systems [PERSON] (1980). [PERSON] et al. discussed FDS to represent the cumulative fatigue damage caused by relative displacement response not velocity or pseudo velocity [PERSON] (1980). MIL-STD-810 describes the synthesis process of vibration conditions in detail from 'G w/Change1' version published in 2014 [PERSON] et al. (2014). The DP (Damage Potential) formula used in the standard is from the paper by [PERSON] and [PERSON] [PERSON] and [PERSON] (1980). They simplified the FDS formula and proposed the DP formula to compare the power spectral density and test duration of different excitation test specifications in terms of fatigue damage [PERSON] and [PERSON] (1980). In case of the NATO environmental test specification, AECTP-200 (2006) [PERSON] et al. (2014) uses [PERSON]'s formula and AECTP-240 (2009) [PERSON] and [PERSON]'s Damage Potential.
## 3 Results
### Semantics Capabilities for Information Consistency  
The system allows the establishment of a highly controlled CIMP where the project leaders and editorial team are allowed to generate any semantic structure or form based on the existing terminologies already incorporated in the system. Once the need for a concept that is not included in the existing terminologies is identified, the coordinator is required to be contacted for additions. This will ensure that all data items collected will be consistent with the terminologies approved and well known in an organization.  
The system includes simplified functionality for post-coordinating multiple terminology concepts. This allows us to define semantic structures based on pre-coordinated terminology concepts that are post-coordinated when they are implemented as screen forms. This is a very relevant point as semantic structures based on pre-coordinated concepts are able to support a larger number of clinical scenarios with easier management of semantics to support aggregation and compatibility for data exploitation and interoperability. On the other hand, clinicians prefer to use post-coordinated terms when they are working on a specialized domain since it reduces the number of items that need to be recorded in the form. Current initiatives such as CIMI WG are working with a similar approach defining iso-semantic transformation from the precoordinated CIM to each specific scenario implemented.  
A library was developed containing generic CIMs complemented with educational material about how to manage with consistency negation, thresholds, indexes and calculation questionnaires, as well as options for others in multiple option questions.
## 4 Results and Discussion  
### Binder Testing Results and Discussion  
#### 4.1.1 Complex Modulus Master Curves  
The complex shear modulus of different binders is shown in Figure 5. The binder stiffness increases with the inclusion of binder modification. The greatest increase is observed in the binder with 4%EMAA, followed by the 4%EMAA/3%SBR-modified binder. It should be noted that there is no significant difference between the complex modulus of virgin and 3%SBR-modified binder; specifically, the complex modulus values are very close at low frequencies (high temperatures). Interestingly, with 3%SBR added into the 4%EMAA modified asphalt, the stiffness of the 4%EMAA/3%SBR compound-modified binder decreases, indicating that SBR is not able to improve the high-temperature properties of binder.
# Secure Audio-Visual Data Exchange for Android In-Vehicle Ecosystems
## 2 Setup and Methodology
### Software Implementation
Before the key is emitted or after the key is received, both the Emitter and Recorder classes use the SymbolFrequencyConvertor class to translate the values to keys and vice versa. Moreover, the Recorder class uses the FFTHandler to compute the recorded sound (even if it is during the seed or the key extraction, the operation is the same). For brevity, some class functionalities, methods or members have been left apart from the figure, e.g., file handling, conversion from 8 to 6 bits and vice versa or the mapping between frequencies and values, but some of these are nonetheless presented in what follows. The left side of Figure 6 shows how the signals are encoded in each frame. There are 4 frequencies, and for synchronization purposes, the fifth is a predefined StartOfFrame frequency. Also, to mark the start of transmission, we will use a special frequency. The shared key is reconstructed from 64 symbols. Each symbol is carried by a tone with a frequency in the 16.85-20 kHz range at 50 Hz resolution. One of our primary objectives was to use the highest frequency that we could so that the discomfort for the users would be minimal. For this we mapped one frequency to a 6 bit value and we set the distance between frequencies at 50 Hz. Consequently, in order to be able to send all the data, we needed a total bandwidth of 3200 Hz as it can be seen on the right of Figure 6. This means that we could emit a message in a range starting from 16.7 kHz (inaudible for most people) up to 20 kHz. This upper frequency of 20 kHz was used because for sampling audio signals Android recommends a sampling of 44.1 kHz or 48 kHz ([[https://developer.android.com/ndk/guides/audio/sampling-audio](https://developer.android.com/ndk/guides/audio/sampling-audio)]([https://developer.android.com/ndk/guides/audio/sampling-audio](https://developer.android.com/ndk/guides/audio/sampling-audio)), accessed on 10 August 2021) and according to the Nyquist-Shannon sampling theorem we could not use frequencies higher than 22.05 kHz to avoid sampling issues. Also, during the experiments, the results for frequencies above 20 kHz were not very good due to the limited power of the signal, so we chose 20 kHz as the maximum frequency in our application. Figure 6: Frame structure (**left**) and symbol encoding as a tone (**right**). In Figure 7 we show the 160 bit key when emitted by a device with carrier frequencies between 16.7 kHz and 20 kHz, the representation is in the time domain (left) and in the frequency domain with use of the Fast Fourier Transform (FFT) on the audio signal (right). To extract the correct frequencies in real-time by the recording device and to avoid device synchronization problems we split each window corresponding to a tone in another 5 windows. The same procedure is useful in removing the influences of the silence periods appearing at the transitions between tones. We compute the Fast Fourier Transform for each new window and then we apply a majority voting to extract the correct frequency.