esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion
Taking account of an averaged estimation above for \(\left|\mathbf{E}_{\text{enh}}\right|^{2}/\left|\mathbf{E}_{0}\right|^{2}\), the ratio \(\gamma_{\text{R,enh}}(\mathbf{K})/\gamma_{\text{R,0}}(\mathbf{K})\) can take a value of approximately 50, if we assume that the quantum yield does not change significantly. Such a non-negligible value of the ratio \(\gamma_{\text{R,enh}}(\mathbf{K})/\gamma_{\text{R,0}}(\mathbf{K})\) is consistent with the experimental observations of the prominent FL-spectrum changes in Figure 3. We note that the ratio of \(\gamma\) includes the ratio of electric-field intensity at the FL-emitting wavelength; therefore, strong localization of resonant electric fields outside the Si rods are suitable to attain large EFs. Indeed, Figures 5-7 show the electric-field localization at the outmost surface of the Si rods. In this sense, electric-dipole type resonance is considered to be unsuitable for large FL enhancement in this experiment. Also, note that the ratio depends on the outgoing vector \(\mathbf{K}\), being sensitive to directional emittance of the metasurfaces; thus, the emittance control is a key factor to obtain large EFs. Overall, the FL enhancement found in this study requires full consideration represented with Equation (1). The present metasurfaces exhibit high capability of FL-intensity enhancement. Therefore, they are expected to be practical platforms for FL sensing. By incorporating proper immobilization techniques, a very low limit of detection for FL-labeled biomolecules can be assumed, as was conducted in the metallic metasurfaces [47]. In this study, FL signals are solely enhanced on the Si-rod-array metasurfaces. By contrast, the FL molecules dispersed on metallic metasurfaces tend to exhibit both FL and Raman-scattering signals in the metal-molecule direct contact configuration [49]. This is a distinct difference between dielectric and metallic metasurfaces. When self-assembled monolayers (SAMs) or other spacers are introduced onto the metallic metasurfaces, it was observed that the Raman-scattering signals disappear. Therefore, metal-molecule direct contact is most likely to affect electronic transition in the dispersed molecules. In the dielectric metasurfaces, such interplay does not take place. Very recently, hot electrons from metallic metasurfaces were reported to substantially contribute to the PL process in semiconductor QDs [61]. Thus, we suggest that hot electrons play a role in the metal-molecule contacting system. So far, metallic (in particular, gold) metasurfaces have been considered to be one of the best candidates in the development of a practical FL-sensing platform. However, the present results strongly suggest that the dielectric metasurfaces can be a good candidate for these platforms. The dielectric metasurfaces with high-FL-enhancing capability will become a strong competitor to the metallic metasurfaces when a surface-improving protocol, such as SAMs, is established. The present metasurfaces have the advantage of a lower cost compared to the metallic metasurfaces, because of their gold-free structure.
# A Fault Section Location Method for Distribution Networks Based on Divide-and-Conquer
## 6 Conclusions  
The existing distribution network fault section location model contains a large number of logic operations and does not meet the requirements of rapidity and accuracy of fault diagnosis. Therefore, a fault location method based on divide-and-conquer is proposed in this paper. In addition, through a simulated test, the following conclusions can be drawn.  
* DAC reduces the operational dimension of fault location to have a linear level of time complexity, which improves the computational efficiency of fault location more significantly. The test results show that for distribution networks with a scale of 33 and 69 nodes, the computational efficiency of the algorithm in this paper is below 20 ms and 50 ms, respectively, which is more than eight times faster than the traditional intelligent optimization algorithms.
* The algorithm in this paper does not contain random search operation; thus, it has strong numerical stability. The test results show that the accuracy of the algorithm in this paper is not affected by the size of the network, and it is more than 19.25% higher than the traditional intelligent optimization algorithm.
* The numerical calculation model of fault location proposed in this paper uses the redundancy of fault information in the whole network to tolerate the distorted information, which can accurately locate the fault with a small amount of distortion in the fault information.  
This paper was based on the fault alarm information uploaded by FTU to locate distribution network faults, which has the advantages of clear and simple information link and convenient implementation. However, when the amount of fault information distortion exceeds the acceptable amount of redundancy, misjudgment could occur. Future research could be conducted on the fault criterion of multi-source information fusion to further improve the accuracy of distribution network fault location.  
Conceptualization, Z.W.; methodology, Q.Z.; software, Q.Z.; validation, Q.Z.; formal analysis, X.L.; investigation, G.L.; resources, Z.W.; data curation, Y.W.; writing--original draft preparation, Q.Z.; writing--review and editing, G.L.; visualization, X.L.; supervision, Z.W.; project administration, Z.W.; funding acquisition, Z.W. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors declare no conflict of interest.
# Multimode Tree-Coding of Speech with Pre-/Post-Weighting +
## 5 Backward Pitch Predictor
### Backward Pitch Coefficients Calculation  
After obtaining the pitch period \(d_{k}\), the pitch coefficients can be calculated as follows. The initial pitch coefficients of each block are calculated using a Wiener-Hopf equation [27; 28]:  
\[\left(\begin{array}{c}\beta_{-1}\\ \beta_{0}\\ \beta_{+1}\end{array}\right)=\left(\begin{array}{cc}(1+\mu)R_{ee}(0)&R_{ee }(1)&R_{ee}(2)\\ R_{ee}(1)&(1+\mu)R_{ee}(0)&R_{ee}(1)\\ R_{ee}(2)&R_{ee}(1)&(1+\mu)R_{ee}(0)\end{array}\right)^{-1}\left(\begin{array} []{c}R_{ee}(d-1)\\ R_{ee}(d)\\ R_{ee}(d+1)\end{array}\right), \tag{13}\]  
where \(\mu=0.001\). When pitch coefficients of each block are initialized, other pitch coefficients are recursively adapted using the equation:  
\[\beta_{i}(k)=\lambda\beta_{i}(k-1)+\frac{\alpha}{\sigma_{u}(k)\sigma_{e}(k)}u (k)e(k-d_{k}-i),\,i=-1,0,+1, \tag{14}\]  
where \(\lambda=1-2^{-7}\) and \(\alpha=2^{-7}\), \(u(k)\) is the output of inverse quantizer, \(\sigma_{u}^{2}\) is the estimate of the variance of \(u(k)\), and \(\sigma_{e}^{2}\) is the estimate of the variance of the output of pitch predictor \(e(k)\). The estimated variances are calculated using Equation (10).
# Aerospace
## 4 Single Small Satellite to Mars Orbit as Secondary Payload  
To illustrate the use of B-plane targeting to insert satellites into multiple orbits from a single interplanetary trajectory, delivery of a single small satellite as a secondary payload is first presented. This section provides a detailed mission analysis of the aerocapture  
Figure 4: Stowed and deployed configurations of the ADEPT SR-1 flight test article. Reproduced from the work by [PERSON] et al./NASA [34]. The scaled-up version of the SR-1 article used in this study has a stowed diameter of 0.5 m and a deployed diameter of 1.5 m.  
trajectory of a single satellite and the deflection maneuver to target a different approach trajectory, which will later be extended to targeting multiple satellites at different orbits. The high-level mission objective is to deliver a small satellite to a near-equatorial Mars orbit as a secondary payload on a Mars polar orbiter mission. A few days prior to arrival at Mars, the host orbiter releases the small spacecraft on its approach trajectory for aerocapture. The host then performs a small deflection maneuver to target its approach trajectory for propulsive orbit insertion at periapsis. The mission requirements defined for this concept are arbitrarily selected for the study but illustrate how B-plane targeting maneuvers and aerocapture enable a small spacecraft to be inserted to a different inclination, low-circular orbit compared to that of the host, which goes into a highly-elliptical capture orbit.
## 2 Implementation of the Frequency-Domain-Based Bit Flipping Controller  
Since this control strategy is based on the cancellation of certain frequency contents of the input sequence of the sigma delta modulator, it only requires a frequency detector [16; 17; 18] to detect the resonance frequencies of the input sequence of the sigma delta modulator, a neural-network-based controller for finding the solution of the integer programming problem [19; 20; 21], the buffers and the combinational logic gates as well as an inverter for implementing the proposed control strategy. The block diagram of the proposed method is shown in Figure 1.  
First, the frequency detector detects the existence of the resonance frequencies in the input sequence. Here, the resonance frequencies relate to those eigenvalues of \(\mathbf{A}\) lying on the unit circle. To detect the resonance frequencies, it is equivalent to test whether \(\sum\limits_{n\geq 0}u[n]d_{i}^{-n}\) is bounded or not with \(|d_{i}|=1\) for those \(i\in[0,\cdots,P-1]\). However, as the length of the signal is infinite, the implementation involves the infinite sum. This has an implementation difficulty. To address this issue, a buffer is employed to preload a block of signal and the summation is evaluated only over the points in the block. Now, a simple accumulator is employed for computing the summation of the real part of the points in the block. Similarly, another simple accumulator is employed for computing the summation of the imaginary part of the points in the block. Finally, two comparators are employed to test whether both the absolute values of the summed real part and the summed imaginary part of the points in the block are larger than a threshold value or not.  
Second, the loop filter is implemented via the direct form structure. Here, only the delay cells, the multipliers and the adders are required for the implementation. The state variables of the digital filter are stored in the delay cells.  
Figure 1: Block diagram of the proposed system.  
Third, the quantizer is implemented via the comparators. The output of the loop filter is compared to the quantization levels of the quantizer via the comparators. Finally, the quantizer gives the output which is the output of the corresponding comparator.  
Fourth, the controller implements the integer programming algorithm via a neural network. The decision vector of the optimization problem is the weight vector of the neural network. The update of the decision vector is implemented via the update of the weight vector of the neural network. Once the update of the weight vector is converged, the converged weight vector is used to control the inverter.  
Finally, the bit streams of the output of the quantizer is compared to the converged weight vector of the neural network. If the bit streams of the output of the quantizer are different from the converged weight vector of the neural network, then the corresponding bit is inverted by the inverter. Otherwise, the bit streams of the output of the quantizer remain unchanged.
# Biosynthesis of Rubbellins in _Ramularia collo-cysni_--Genetic Basis and Pathway Proposition
## 3 Discussion  
### Identification of the Putative Core Gene in Rubellin Biosynthesis  
The phylogenetic analysis carried out on the three NR-PKSs previously identified in the genome of _R. collo-cygni_ strongly supports the role of _RccG_ as the core gene in the rubellin biosynthetic pathway, as previously suggested by [PERSON] et al. [26]. Both _Pks2_ and _Pks3_ are unlikely to be involved in rubellin biosynthesis. RccPks3, the protein encoded by _Pks3_, is related to NR-PKSs involved in the biosynthesis of meroterpenoids such as MpaC, Trt4, and AndM, responsible for the biosynthesis of mycophenolic acid, terretonin, and antidimin in _P. brevicompactum_, _A. terreus_, and _A. stellatus_, respectively [31; 33; 34]. Therefore, _Pks3_ is likely to be involved in the biosynthesis of a meroterpenoid SM. The protein encoded by _Pks2_ in _R. collo-cygni_ appears to be related to proteins involved in the biosynthesis of secondary metabolites belonging to the perylenequinone family, which are structurally very different from anthraquinone. RccG appears to be closely related to other enzymes involved in the biosynthesis of anthraquinone-derived SMs, such as cladofulvin and monodictyphenone in _C. fulvum_ and _A. nidulans_, respectively. Taken together, these results suggest that the gene encoding RccG in _R. collo-cygni_ may be the best candidate for the early steps of rubellin biosynthesis. Although all the NR-PKSs present in the clade containing RccG are involved in diverse biosynthetic pathways, all these pathways appear to rely on the formation of common intermediates. Compounds such as atrochrysone carboxylic acid **10** or emodin **8** can be found during the biosynthesis of SMs structurally related to rubellins such as monodictyphenone, agnestins, and cladofulvin in _A. nidulans_, _P. divariatus_, and _C. fulvum_, respectively [23; 25; 42]. Similarly, chrysophanol **7** and chrysophanol hydroquinone are intermediate in the biosynthesis of agnestins and cladofulvin, respectively. Based on structural similarity between rubellins and cladofulvin being a dimer of nataloe emodin and rubellin being a dimer of chrysophanol **7**, the biosynthetic pathways of these two SMs are expected to share several intermediates. Interestingly, [PERSON] et al. [44] have previously shown the presence of chrysophanol **7** in the culture of _R. collo-cygni_, suggesting that this intermediate could be involved in the biosynthesis of rubellin.  
Figure 5: Lesions induced by rubellin D **4** and chrysophanol **7** following infiltration in leaves of _A. thaliana_. (**A**) Relative lesion size in leaves infiltrated with rubellin D **4**, chrysophanol **7**, or MgCl\({}_{2}\) (control) measured after 24 h. Data show the average mean relative lesion size \(\pm\) standard error of three independent experiments of at least 10 leaves each. Significant differences are shown by different letters. (**B**) Representative pictures of lesions observed after 24 h following infiltrations.
## 1 Introduction  
The demand for underwater wireless communication has increased tremendously with expected acceleration in the near future [1]. The multicarrier modulation techniques have become a hot research area in the last two decades. Orthogonal frequency divisional multiplexing (OFDM) is a multicarrier modulation technique that is popular in underwater acoustic (UWA) communication systems for transferring data [2]. However, an OFDM communication system has a major lack of high peak to average power ratio (PAPR). This results in lower power efficiency, creating problems while implementing UWA communication [3]. Besides this, there are several other limitations, such as characteristics of noise, multipath delay, and Doppler shift. These limitations bring great difficulties to the research and implementation of UWA communication [4, 5]. Energy efficiency matters, particularly in UWA communication, for batteries deployed in underwater acoustic transceivers. Nowadays, a key driving factor is the growing energy cost of network operations, which can make up as much as 50% of the total operational cost [6]. By increasing the efficiency of a high-power amplifier (HPA), it can reduce energy costs. However, the HPA's performance is directly linked to the input signal's PAPR. Particularly in OFDM multicarrier transmissions, which are applied in many important wireless standards such as the Long-Term Evolution Advanced (LTE-A) Third Generation Partnership Project (3 GPP) [7, 8], the PAPR problem still prevents the adoption of OFDM in the uplink of mobile communication standards. It also affects the output power in the downlink coverage. It is necessary to find different methods to reduce the PAPR to a lesser value for a more powerful HPA, resulting in longer battery life and better efficiency [9]. For underwater acoustic sensing networks, there is the deployment of battery-powered modems in the water [4]. To maintain a sustainable network operation, it is necessary to reduce the PAPR of the OFDM signal [8]. For many applications, the problem of the PAPR can outweigh all the potential advantages of the OFDM communication system [10]. A variety of promising methods for the reduction of the PAPR has been proposed in the literature at the cost of BER, increment in transmission signal power, and computational complexity of the overall system. Therefore, in this paper, the PAPR of the underwater acoustic OFDM system is researched to design a nonlinear PA model with the help of a deep learning algorithm. Finally, we propose a receiver-based nonlinearity distortion mitigation method when the transmitting side has enough computation power. A nonlinear PA model is projected with the help of a modern deep learning algorithm; we call it FFB (frequentative decision feedback).
# Critical Review of Basic Methods on DoA Estimation of EM Waves Impinging a Spherical Antenna Array
## 1 Introduction
The major novelty of our work as compared with [PERSON] and [PERSON] [11] is that we particularly extended the DoA methods to the antenna array rather than the microphone array, backed with experimental data in electromagnetics vis-a-vis a spherical antenna array, which is, in the end, the ground truth to test and evaluate any method. This is the major contribution of our work. The rest of this paper is organized as follows. Section 2 present a general description of the SAA configuration. In Section 3, mathematical formulations for EM signals in free space, the space domain, spherical harmonic decomposition, and SAA with spherical harmonic decomposition (SHD) are derived. In Section 4, five DoA estimation methods are analyzed: MUSIC, PWD, WSF, and deterministic (D) ML and stochastic (S) ML methods. The numerical experimental tests, results, and discussion are presented in Section 5, and finally, conclusions based on the findings are given in Section 6.
# Predicting Choices Driven by Emotional Stimuli Using EEG-Based Analysis and Deep Learning
## 5 Experiment Implementation
### Choice Classification with DL
#### 5.5.1 CNN Architecture  
The CNN architecture employed in this work is shown in Figure 4. The CNN model consists of two convolutional (conv1d) blocks, both with 32 filters. Then, a 0.3 dropout regularization is used to improve the performance of the model via a modest regularization effect, followed by a third conv1d layer with 64 filters. The kernel size of all conv1d filters is 3 \(\times\) 3, with zero padding and stride, and we used the Rectified Linear Units (Relu) as the activation function due to its unity gradient, where the maximum amount of error is passed during backpropagation.  
Next, a maximum subsampling layer (max pooling layer) of a 2 \(\times\) 2 subwindow was applied, followed by a flattening layer. Then, a fully connected dense layer with 128 units was applied to have nonlinearity properties, followed by a 0.3 dropout regularization. The network ends with a connected dense layer fed with a sigmoid activation function for binary classification.
###### Abstract  
The primary objective of the presented paper is the numerical and experimental investigation related to developing a useful diagnostic method, which can be used for determining the site and size of damage in laminated shells of wind turbine blades. The described detection technique is based on the analysis of low frequencies bending vibrations mode shapes of rotor blades. The authors used the commonly applied statistics methods that have been adapted to detect edges of damage, including the normalized determination coefficient fit, which is a measure of the absolute fit between two curves. The research was conducted for a scaled-down blade of a three-bladed horizontal-axis wind turbine with 36 m diameter rotor. The study was divided into two parts. The first stage included numerical calculations using the finite element method, which were supplemented in the second stage by measurements under laboratory conditions of the specially manufactured composite blade. The forms of natural vibrations for intact and damaged blade were determined using Laser Doppler Scanning Vibrometry. The results of the presented research confirm the effectiveness of the modal analysis combined with statistic calculation in damage detection. The method points out the location of relatively small damage.  
Keywords:modal analysis; non-destructive damage detection; wind turbines blade; vibration based methods; statistic; laser vibrometry +
Footnote †: journal: Applied Physics Letters
# Susceptibility to Expansive Reactions of a _Greener_ Uhpc: Micro to Macro-Scale Study
## 2 Materials and Methods
### Raw Materials and Mix Design
#### 2.2.3 Resistance to External Sulphates  
UHPC resistance to external sulphate attack was evaluated according to the Portuguese specification E\(-\)462 [57], which aims to assess the cement susceptibility of external sulphates. Even though Portuguese specification E\(-\)462 suggested a mixture proportion, the UHPC mix proportions described previously (see Table 2) were used. Thus, six-bar specimens (1, 2, 3, 4, 5, and 6) with dimensions of 16 \(\times\) 16 \(\times\) 160 mm\({}^{3}\) were cast. All of the UHPC bar specimens remained in the mold for 24h and then were immersed in saturated calcium hydroxide solution for 28 days in a controlled environment (T = 20 \(\pm\) 2 \({}^{\circ}\)C). At 28 days, linear length measurements along the four side faces of each specimen were performed and taken as the initial length (\(L_{0}\)). The UHPC bar specimens 2, 4, and 6 were then transferred to a sodium sulphate solution (16g/L SO\({}_{4}\)\({}^{2-}\)), and the others (1, 3, and 5) were kept in calcium hydroxide saturated solution. The length change measurements of all UHPC bars were taken every two weeks for 26 weeks. At each length measurement, the sulphate solution was renewed. The expansion of each specimen in day \(x\) was calculated as:  
\[exp^{Ca(OH)_{2}}(x)=\frac{L_{x}-L_{0}}{1600}\;(\%) \tag{1}\]  
where \(exp^{Ca(OH)_{2}}(x)\) is the expansion of specimens kept in saturated calcium hydroxide solution (specimens 1, 3 and 5) at day \(x\)  
\[exp^{SO_{4}Na_{2}}(x)=\frac{L_{x}-L_{0}}{1600}\;(\%) \tag{2}\]  
where \(exp^{SO_{4}Na_{2}}(x)\) is the expansion of specimens kept in sodium sulphate solution (specimens 2, 4, and 6) at day \(x\).  
Thus, the expansion due to external sulphate is:  
\[exp_{sulphate}(x)=exp^{SO_{4}Na_{2}}(x)-exp^{Ca(OH)_{2}}(x)\;(\%) \tag{3}\]  
The length of each sample was measured using a digital indicator with an accuracy of 0.0001 mm.