esa-sceva/satcom-chunk-collection huggingface dataset:
# A Review of Photothermal Detection Techniques for Gas Sensing Applications
## 3 Fiber-Based Photothermal Gas Sensors
### PTS Signal Enhancement using Multipass Cells  
According to the equation \(\Delta\Phi=(2\pi\Omega\)n)/\(\lambda\), the registered signal is linearly dependent on the length of the interaction between the gas sample and the beam that excites the molecules--similarly to standard absorption techniques. Therefore, a straightforward way to increase the sensitivity of a PTS sensor would be to maximize the this parameter. In Reference [32], a first demonstration of using commercially available multipass gas absorption cells to increase the gas-laser interaction length was presented. The layout of the setup is presented in Figure 6.  
The base of the multipass-cell-assisted PTS sensor was a fiber-based Mach-Zehnder interferometer designed based on telecom wavelength components (1.55 \(\upmu\)m). To increase the gas-laser interaction length, and thus achieve a higher PTS signal, a Herriot multipass cell was incorporated into the measurement arm of the interferometer. The Authors used a 50 mW quantum cascade laser (QCL) [33] as a _pump_ source and targeted a strong absorption line of methane located in the v\({}_{4}\) band near 1389 cm\({}^{-1}\). The _pump_ beam was spatially overlapped with the _probe_ beam and launched into the multipass (MP) cell. The optical path in the MP cell was changed in steps, achieving 19 cm, 83 cm and 364 cm (1, 7 and 33 passes, respectively, obtained through axial rotation of the exit mirror). The results of the  
Figure 6: **(a)** Schematic of the experimental layout incorporating a multi-pass cell for interferometric detection of a PA signal. X0/Y0—fiber couplers with specified splitting ratio, DM—dichroic mirror, F—filter, FC—fiber collimator, PD—photodiode, QCL—quantum cascade laser, DFB—distributed feedback telecom laser diode. **(b)**_2\(f\) PTS signal amplitude in function of the laser-gas interaction length. Reprinted with permission from [32].  
measurements presented as an inset in Figure 6 clearly demonstrated that the PTS signal scaled linearly with the increasing interaction length. Additionally, spherical mirrors used in the MP cell assured that both beams are traveling co-linearly (any misalignment would result in one of the beams not exiting the MP cell due to improper angular alignment) and are periodically re-focused in the center of the MP cell, thus keeping optimal beam spots of both the _pump_ and the _probe_ beams.  
Interestingly, although the registered PTS signal was enhanced by the longer gas-laser interaction length, the sensitivity of the sensor estimated based on the Allan deviation plot was limited to an NEC of 10 ppmv of CH\({}_{4}\). According to the research, the main limitation of the MP cell-assisted PTS gas sensor was connected with mechanical and acoustic noise. In this configuration, the constructed MZ interferometer readout acts as a traditional vibrometer, picking-up all unwanted background signals. To fully exploit the multipass-cell-assisted enhancement of the PT signal, a different technique of detecting the RI modulation has to be adopted.
# A Review on Vibration Control Using Piezoelectric Shunt Circuits
## 4 Modeling of Dynamical Systems with Piezoelectric Shunt Circuits
### Lumped-Parameter Systems
It is helpful to first look at a chart that shows a variety of shunt circuits frequently used in control applications before diving into a thorough literature analysis of the various control strategies used in vibration damping. Table 1 shows some of the common circuit configurations utilized in passive control systems with their total electrical impedance \(Z_{total}\). \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Circuit Name** & **Circuit Configuration** & **Total Impedance** & & **Characteristics** & **References** \\ \hline R circuit & & R & \(Z_{total}=\frac{R\cdot C_{p}\cdot\mathrm{s}}{\big{(}R\cdot C_{p}\cdot\mathrm{s} +1\big{)}}\) & & \(\bullet\) & Passive control \\  & & R & \(Z_{total}=\frac{R\cdot C_{p}\cdot\mathrm{s}}{\big{(}R\cdot C_{p}\cdot\mathrm{s} +1\big{)}}\) & & \(\bullet\) & It behaves similarly to a \\  & & & & & viscoelastically damped \\  & & & & & system \\ \hline RL circuit in series & & R & \(\bullet\) & Passive control \\  & & R & \(\bullet\) & Single mode \\  & & & & \(\bullet\) & It creates an electrical \\  & & & & & frequency that can be \\  & & & & & tuned to the structure’s \\  & & & & natural frequency to \\  & & & & induce antiresonance \\ \hline RL Circuit in parallel & & R & L & \(Z_{total}=\frac{R\cdot L\cdot\mathrm{s}}{\big{(}R+R\cdot L\cdot C_{p}\cdot\mathrm{s} ^{2}+L\cdot\mathrm{s}\big{)}}\) & \(\bullet\) & Passive control \\  & & & & \(\bullet\) & Single mode \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Common shunt circuits and their impedance.
# Similarity Analysis for Time Series-Based 2D Temperature Measurement of Engine Exhaust Gas in TDLAT
## 4 Statistical-Based Mean Difference Test and Similarity Analysis
### [Step 2] Similarity Analysis
#### 4.2.4 Results of Similarity Analysis in [Step 2]
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Cycles**} & \multicolumn{10}{c}{**Time (s)**} & \multicolumn{10}{c}{**Total**} \\ \cline{2-10}  & **1** & **2** & **3** & **4** & **5** & **6** & **7** & **8** & **9** & \\ \cline{2-10}  & & \multicolumn{10}{c}{**RMSE**} & & & **RMSE** & **Rank** \\ \hline
31 & 8.487 & 8.039 & 10.325 & 8.441 & 12.622 & 7.869 & 7.320 & 5.887 & 5.887 & 8.578 & 18 \\
51 & 5.514 & 5.592 & 6.370 & 5.994 & 7.759 & 4.776 & 6.912 & 5.526 & 5.526 & 6.049 & 17 \\
71 & 6.269 & 4.497 & 5.404 & 6.334 & 5.316 & 6.007 & 6.028 & 4.420 & 4.420 & 5.538 & 16 \\
91 & 4.879 & 3.775 & 4.331 & 5.559 & 3.894 & 5.921 & 5.073 & 3.620 & 3.620 & 4.822 & 15 \\
11 & 4.702 & 3.860 & 4.282 & 5.046 & 3.580 & 5.265 & 4.156 & 3.496 & 3.496 & 4.393 & 14 \\
151 & 3.755 & 3.129 & 4.216 & 4.833 & 3.564 & 2.957 & 4.314 & 4.065 & 4.065 & 3.918 & 13 \\
201 & 3.177 & 2.978 & 3.349 & 3.376 & 2.900 & 2.529 & 3.810 & 3.736 & 3.736 & 3.199 & 12 \\
251 & 3.024 & 3.063 & 3.496 & 3.400 & 2.338 & 3.166 & 3.243 & 2.755 & 2.755 & 3.120 & 11 \\
301 & 2.603 & 2.884 & 3.159 & 2.961 & 2.749 & 2.844 & 2.541 & 2.267 & 2.267 & 2.809 & 10 \\
351 & 2.056 & 2.733 & 2.799 & 2.686 & 2.955 & 3.333 & 2.529 & 2.099 & 2.099 & 2.703 & 9 \\
401 & 1.951 & 2.583 & 2.641 & 2.451 & 2.849 & 3.149 & 2.546 & 2.456 & 2.456 & 2.584 & 4 \\
451 & 2.047 & 2.909 & 2.662 & 2.403 & 2.785 & 3.439 & 2.512 & 2.156 & 2.156 & 2.641 & 7 \\
501 & 2.433 & 2.580 & 2.703 & 2.278 & 2.894 & 3.543 & 2.433 & 2.140 & 2.140 & 2.
# Along-Track Multistatic Synthetic Aperture Radar Formations of Miniatellites
###### Abstract  
The paper analyses an along-track multistatic Synthetic Aperture Radar (SAR) formation. The formation aims at achieving a high azimuth resolution maintaining at the same time a large swath width. The case with one transmitting sensor and all receiving is analyzed (Single Input Multiple Output, SIMO). An effective and novel reconstruction, in the two-dimensional frequency domain is introduced that is able to keep low the azimuth ambiguity and achieve a recombination gain close to the theoretical one. Degradation of the system performance due to the loss of the control of formation position is analyzed using probabilistic considerations. Moreover, some innovative methods to mitigate the loss of optimality are introduced and evaluated using simulations. Finally, considerations on the impact of the across-track non zero baseline are discussed.  
synthetic aperture radar; bistatic SAR; multistatic, SAR; satellite formation; miniSatellites; inversion +
Footnote †: journal: remote sensing  
_Article_
# Advanced Cooperative Formation Control in Variable-Sweep Wing UAVs via the MADDPG-VSC Algorithm
## 3 Cooperative Control of Variable-Sweep Wing UAV via MADDPG
### Optimization of the MADDPG-VSC Algorithm for Control Design
#### 3.2.3 Convergence and Stability  
The MADDPG-VSC algorithm significantly improves training stability through the introduction of a soft update mechanism and the use of target networks. Given that the environment model and the state transition probability \(P\) are unknown, these aspects present challenges in reinforcement learning, particularly when dealing with complex and dynamic environments.  
To address these challenges, the MADDPG-VSC algorithm utilizes a soft update approach, which gradually integrates new information into the model, ensuring that updates are smooth and that they do not destabilize the learning process. This method involves the construction of a policy network \(\mu(s|\theta^{\mu})\), a \(Q\) network \(Q(s,a|\theta^{Q})\), and their respective target networks \(\mu^{\prime}\Big{(}s|\theta^{\mu^{\prime}}\Big{)}\) and \(Q^{\prime}\Big{(}s,a\Big{|}\theta^{Q^{\prime}}\Big{)}\). The soft update mechanism is expressed as  
\[\left\{\begin{aligned} \theta^{\mu^{\prime}}=\tau\theta^{\mu}+(1- \tau)\theta^{\mu^{\prime}}\\ \theta^{Q^{\prime}}=\tau\theta^{Q}+(1-\tau)\theta^{Q^{\prime}}\end{aligned}\right. \tag{26}\]  
This gradual update method mitigates risks such as gradient explosion or vanishing, stabilizing the training process of the MADDPG-VSC algorithm. It allows the algorithm to progressively approach the optimal policy with enhanced stability, making it particularly effective in the complex and continuously changing environments encountered by variable-sweep wing UAVs.
# Research on Dynamic Modeling and Vibration Characterization of Integrated Bearings
## 2 Integrated Bearing Dynamic Performance Analysis
### Impact of Operating Conditions on Vibration of Integrated Bearings
#### 2.3.1 Impact of Axial Preload on the Vibration of Integrated Bearings  
Under the operating conditions of a shaft speed of 50,000 r/min, a radial load of 200 N in the Y-direction, and a radial load of 0 N in the Z-direction, the relationship between axial preload and bearing vibration is illustrated in Figure 13. As shown, applying a certain level of axial preload to the integrated bearing effectively reduces its vibration. Furthermore, with increasing axial preload, the bearing vibration initially decreases and then begins to increase. The optimal vibration characteristics of the integrated bearing occur when the ratio of axial preload to the bearing's rated dynamic load is between 0.5% and 0.8%.
## 2 Related Works
[PERSON] et al. [26] proposed an anticipated Rife (An-Rife) interpolation algorithm to improve the correction judgment rate of the interpolation direction. They improved Rife's original single-discrimination method using frequency-shifting technology and recalculated the frequency-shifted spectrum. Then, they estimated the final frequency by judging the correctness of the interpolation direction. They increased the estimation stability of the algorithm in an arbitrary frequency range but used the frequency shifting technique many times, which significantly increased the complexity of the algorithm. For the problem that ordinary frequency domain estimation was unsuitable for estimating two adjacent frequency components, [PERSON] et al. [27] changed the spectral main lobe estimation to side lobe estimation and proposed a frequency estimation based on the first sidelobe method. They found that the inter-spectral interference of the side lobes is smaller than that of the main lobe, from which the main lobe peak could be inferred. Unfortunately, due to the influence of the fence effect, the accurate side lobe peak could not be obtained by directly performing the FFT of the signal. Therefore, before the FFT, they zero-padded the sequence, increased the monitoring time, and accurately estimated the frequency. The improved frequency estimation algorithm proposed by [PERSON] et al. also padded the samples with zeros [28]. Unlike the Rife algorithm, the ratio of the real part of the maximum spectrum to the real part of the sub-maximum spectrum was used for interpolation estimation. The above two algorithms improved the search accuracy of frequency quantization points to varying degrees. Still, the amount of calculation was increased due to the artificial growth of the sample length. The above several improved algorithms for Rife all optimized the performance of frequency estimation in different ways. However, some algorithms sacrificed the amount of computation, and some only balanced the estimation accuracy of the Rife algorithm at each frequency point. The difference is that our proposed algorithm changed the interpolation method and used the phase angle to estimate the frequency deviation, which improved the algorithm's accuracy and made the frequency estimation error closer to CRLB.
# High-Resolution, Broad-Range Detection Setup for Polarimetric Optical Fiber Sensors
## 5 Conclusions  
A common-path polarization interferometer using a Wollaston prism and an area detector for the measurement of retardation or optical path difference was demonstrated. The measurement range of this interferometer is approximately 1350 rad at 515 nm and 786 rad at 830 nm, and it can be altered by using a Wollaston prism with a different splitting angle or a camera with a different pixel size.  
The resolution of this interferometer was investigated in a test setup using a Soleil-Babinet compensator or a quarter-wave plate to change the retardation. Based on the experimental results, it can be concluded that the minimum detectable phase change is 0.002 rad. The resolution can be further improved by using a better camera and pre-processing the acquired images more carefully. Using better-quality polarizers and lenses should also result in an improvement in resolution and accuracy.  
The presented interferometer offers a measurement resolution comparable with that of the setups described in [36], as well as measurement range of around 1000 rad, which was unattainable for these setups.  
Until quite recently, this interferometer was capable of operation only in the spectral range from approximately 400 nm to 1000 nm, limited by the spectral sensitivity characteristics of silicon CCD/CMOS detectors, excluding its use in sensors operating in 1310 nm and 1550 nm bands. At present, the commercial availability of InGaAs image sensors and cameras allows for the presented interferometer to also work in the spectral range from 700 nm to 1700 nm. However, its operation in the mid-infrared range, where sensing fibers are being developed [48; 49], will not soon be possible due to the lack of array detectors that are sensitive in that range.  
This research received no external funding.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.
# A Review of Innovative Electromagnetic Technologies for a Totally Artificial Heart
## 2 Main TAH Projects
The importance of innovative technologies, especially based on the introduction of novel electromagnetic devices, is recognizable in Table 1, which reports the main data of some significant TAH projects, approved or in the development stage. All projects except the SinCardia are electrically driven by an implanted motor, allowing for better control capability, reliability, and compactness of the supply system than the pneumatic actuator. Despite the rather scattered distribution and some difficulty in retrieving reliable data, the CF schemes indicatively appear to be the most convenient for the weight and volume, allowing similar performances of the other type at the same time. The only exception is related to the SynCardia TAH, which is, however, penalized by the heavy external equipment. Data on the input power and overall efficiency are more difficult to retrieve and are hardly comparable due to the different supply equipment. Moreover, such values are heavily affected by the load condition. However, percutaneous systems generally exhibit higher efficiency than TET, since the supply of implanted electrical and electronic devices by direct connection implies fewer losses than in contactless transcutaneous power transfer. \begin{table}
\begin{tabular}{c c c c c c c c} \hline
**TAH** & **Type** & **Mass** & **Volume** & **Power** & **Output** & **Input Power** & **Total Efficiency** \\  & & **(g)** & **(mL)** & **Supply** & **(l/min)** & **(W)** & **(\%)** \\ \hline Aeson CARMAT [18] & FD & 900 & 750 & Percutaneous & 2–9 & N.A. & N.A. \\ BiVACOR [35; 36; 37] & CF & 650 & N.A. & Percutaneous & 3–12 & 15.5 & N.A. \\ Cleveland [38; 39] & CF & 486 & 160 & Percutaneous & 7.4 & 12.9 & 13.3 \\ OregonHeart [40] & CF & N.A. & 130 & Percutaneous & 7.5 & 10.0 & 17.5 \\ Realheart [41] & EM & 800 & 1.790 & TET & 2.7–8.2 & N.A. & N.A. \\ ReinHeart [29; 30; 31; 32] & EM & 940 & 550 & TET & 5.5 & 12.5 & 10 \\ RollingHeart [42] & EM & N.A. & 704 & Percutaneous & 5.3 & 14.0 & 14.1 \\ SynCardia 70 cc [14] & FD & 240 & 400 & Percutaneous & 9.5 & N.A. & N.A. \\ HybridHeart [43] & FD & \textless{}900 & N.A. & TET & 2–8 & 34 & 6.7 \\ \hline \end{tabular}
\end{table} 
Table 1: Main data from approved or under development TAH projects.
# Linewidth Measurement of a Narrow-Linewidth Laser: Principles, Methods, and Systems
## 3 Research Progress
### The Heterodyne Method  
In 2013, [PERSON] et al. proposed a spiral resonator for on-chip laser frequency stabilization and used a Pound-Drever-Hall (PDH) locking system to lock two fiber lasers onto the spiral resonator [86]. The locked laser measures the beat frequency signal through a heterodyne linewidth, achieving linewidth measurements less than 100 Hz.  
In 2018, [PERSON] et al. proposed a narrow-linewidth continuous-wave laser with self-injection locking onto a whispering corridor (WGM) resonant cavity and used a narrow-linewidth tunable fiber laser as a reference laser to construct a heterodyne linewidth measurement system [87], obtaining a Lorentz linewidth of 340 Hz and a Gaussian linewidth of 1.7 kHz.  
The heterodyne method offers higher resolution and sensitivity than spectrometers and F-P etalon but is limited by the strict performance requirements of reference light sources, resulting in complex testing systems and higher costs.
# A Manycore Vision Processor for Real-Time Smart Cameras +
## 6 Conclusions  
In this work, we developed a Smart Camera system based on a manycore architecture for real-time image processing and computer vision applications. The main contribution of this work is a novel manycore architecture specially designed for the IP/CV application domain. All design decisions were made considering the domain-specific needs, which resulted in a refined and efficient hardware/software architecture.  
Figure 13: Power consumed for different algorithms and architecture sizes.  
Our approach makes use of _Region-based_ and operation level parallelism to optimize the processing time. Additionally, we designed a pixel distribution and control unit using an embedded ARM processor and AXI bus scheme. All subsystems are addressed and explained with construction details, focusing on matching application-specific needs. As a proof-of-concept, we implemented some IP/CV algorithms: the motion estimation, Harris corner detector, Sobel edge detector, and convolution filters. The results show that our architecture is capable of overcoming similar real-time architecture depending on the manycore size and application demands. The architecture is also flexible and easy to scale for higher numbers of tiles.  
The manycore architecture proposed was compared to state-of-art approaches based on highly specialized FPGA implementations, reaching a good performance, while providing an application-agnostic solution. In comparison to embedded GPUs (commercial and academic ones), our solution is more efficient on parallelism exploration. GPUs are directly programmed in C/C++. Our architecture does not yet have a C/C++ compiler; however, it is almost as programmable as the GPU solutions.  
In future works, we envision the utilization of a higher frame rate sensor to reach the full potential of the architecture. The proposed system is heterogeneous: we can implement the IP/CV algorithms in different architectures (direct FPGA, manycore, ARM processor). A mapping tool to obtain the algorithm description and divide it optimally over the system would also be beneficial. In addition, the other cores of the ARM processor could also be used to perform control and processing separately, as well as to run an embedded Linux operating system, bringing even more application possibilities to our Smart Camera system.  
Conceptualization, J.A.-G., M.H. and J.Y.; methodology, B.A.d.S., M.H. and J.Y.; codification, B.A.d.S. and A.M.L.; supervision, J.A.-G., M.H. and J.Y.; experiments, B.A.d.S., A.M.L. and J.Y.; data analysis, all authors; writing--original draft preparation, B.A.d.S., A.M.L. and J.Y.; writing--review and editing, all authors. All authors have read and agreed to the published version of the manuscript.  
This study was financed in part by the following institutions: Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior, Brasil (CAPES)--Finance Code 001; Fundacao de Apoio a Pesquisa do Distrito Federal (FAPDF); National Council for Scientific and Technological Development (CNPq).  
Not applicable.  
The authors declare no conflict of interest.
## 4 Simulation Experiments  
To investigate the performance of the proposed MCMC method to sample from the posterior in (12), we consider simulated data of identically manufactured LED systems. Test data generation is described in Section 4.1. The test datasets are used to address different experimental scenarios that are commonly encountered in applications:  
* Issue 1: Production and application variability (Section 4.2). In practice, we are primarily interested in the variability within the thermal resistances across the sample of \"identically\" manufactured LED systems due to material (production) and setup (application) variability. Thus, inference focuses on the estimation of the hyperparameters \(\mathbf{\theta}_{R_{\text{th}}}=(\mu_{R_{\text{th}}},\sigma_{R_{\text{th}}})\) which determine the variability in \(R_{\text{th}_{i}}\). The thermal resistances themselves are not of immediate interest and are considered nuisance. Analyses on this default issue are based on data from experiment E1.
* Issue 2: Measurement uncertainty (Section 4.3) deals with a modification of Issue 1 by considering unknown residual variances \(\sigma_{\epsilon}^{2}\). The default model is extended to additionally estimate the variance parameter. The same datasets as in Issue 1 are used for implementation of Issue 2.
* Issue 3: Uncertain experimental conditions (Section 4.4). In addition to the default setting in Issue 1, we also consider varying operational conditions by assuming that the realized forward currents \(I_{f,i}\) vary between the LED systems; see prior type 2a in Section 3.2.2. The primary aim here is to quantify the impact of this uncertainty on the quantities of interest \(\mathbf{\vartheta}_{R_{\text{th}}}=(\mu_{R_{\text{th}}},\sigma_{R_{\text{th}}})\). Modifications of the algorithm proposed for Issue 1 are straightforward. Experiment E3 points out different strategies in dealing with uncertain conditions.
## 3 Results and Discussion
### Water Absorption  
The next stage of the study involved testing water absorption. For the control series MS, water absorption was at a level of 8.1% (Figure 6). In mortars modified with MSWI-FA waste (MSWI-FA-10, MSWI-FA-15, and MSWI-FA-20) and CKD waste (CKD-10, CKD-15, and CKD-20), a gradual increase in water absorption was observed, ranging from 7.8% to 10.0% and 7.8% to 9.8%, respectively. This suggests that increasing the amount of waste impacts this parameter. The series where both wastes were used together (MSWI-FA-CKD) showed the highest values, reaching a maximum of 11.1%, indicating a synergistic effect of these components. The greatest variability was noted in the MSWI-FA-CKD group, which may reflect diverse reactions to the tested conditions. Overall, the results demonstrate the significant impact of the combined parameters on the increase in measured water absorption values.  
Figure 5: Volumetrits density of individual cement mortar series.  
Figure 6: Water absorption of individual cement mortar series.