esa-sceva/satcom-chunk-collection huggingface dataset:
# Effect of Diagonal Pattern Training on Trunk Function, Balance, and Gait in Stroke Patients
## 1 Introduction  
The sitting balance and gait performance with trunk control is one of the important prognostic indicators for the functional outcome of stroke patients. Thus, restoring the sitting balance and gait performance is a major goal of rehabilitation after stroke [1; 2; 3].  
It is observed that trunk control disability frequently occurs after a stroke [4; 5; 6; 7]. Additionally, trunk control disability after stroke causes reduced trunk muscle activity [7], decreased contractility [4], reduced trunk control performance [6], changes in the position sense [5], and decreased pelvic movements [8]. Moreover, the trunk control ability of stroke patients significantly alters their sitting balance and gait ability [9; 10]. Specifically, as the thoracic and pelvic movements occur together due to the lack of the trunk motion that separates the thorax and pelvis during walking, stroke patients walk with a pathologically increased trunk movement [11]. Trunk control impairment in stroke patients not only shows spinal problems which can be seen in the sagittal plane, but also shows asymmetric changes in the pelvis [12]. Therefore, these impairments alter the balance and gait performance causing pathological movement.  
Diagonal pattern training has been conducted for trunk control rehabilitation in several studies for the selective movement of the spine and pelvis in stroke patients [13; 14; 15]. Diagonal pattern training is one of the trunk rehabilitation training methods that improve the movement, trunk asymmetry, flexibility, and strength provided by various planes [13]. It produces greater adaptive plasticity as the neural recruitment increases and dorsolateral prefrontal cortex and the primary motor cortex changes when compared to single plane movements [16]. Diagonal pattern movement can also rotate the trunk diagonally, separate the thorax and pelvis, and include repetitive weight movements to promotethe facilitation of trunk muscles [13]. Although diagonal pattern training provides well-matched intervention in patients with trunk disability by stroke, the effect of trunk control ability for balance and gait relationship has not been verified yet.  
Therefore, the purpose of this study was to investigate the effect of diagonal pattern training in the sitting position to improve trunk control ability for balance and gait in stroke-affected patients.
# Efficient Security Scheme for Disaster Surveillance UAV Communication Networks
## 6 Security Analysis
### Information Availability  
To guarantee the efficiency and reliability of the surveillance UAV Network operation, the information aggregated from the disaster area should be available to \(CS\) whenever \(CS\) asked for it. Our proposed scheme allows redundancy in the readings, as several drones are monitoring the same subarea and sending their versions of the scanning data to \(CS\) via cluster heads and relays. If some drones in the same group or same subarea are not available, the remaining units still send their data to \(CS\). If \(\mathcal{A}\) compromises a certain number of drones, \(CS\) still can guarantee the correctness of each reading value by receiving redundant values for the same information from other drones.  
Moreover, \(CS\) reduces the probability of attacks by eliminating the suspicious drones. If \(CS\) does not receive the expected messages from certain groups, or if units that forward the group's messages to \(CS\) are not the current chosen cluster heads, \(CS\) blocks these malicious heads and checks the whole group, i.e., \(CS\) realizes that these nodes are compromised by \(\mathcal{A}\).  
In case of a regular drone malfunction, other drones in the group are still sending their information. If a cluster head fails or malfunctions, \(CS\) receives the data from the other head. Even if the whole group failed, other groups are supplying \(CS\) by the required information. Thus, the data availability is guaranteed and drone malfunction does not have an effect on the rescue operation's efficiency.
## 4 Conclusions  
The results of the simulation of the SHE effect have revealed that with a gate length of less than 40 nm, a greater influence on the resulting temperature was exerted on the considered structures of the transistor (see case 1 and case 2) than the influence of the gate oxide and the BOX materials. Furthermore, it was observed that SHE is sensitive to gate length for all combinations of gate and back oxide materials in the transistor, while the DIBL effect is more sensitive to gate length for transistors with combinations 3 and 4.  
Moreover, our simulation results revealed that the choice of gate and BOX oxide materials to ensure the highest possible immunity against degradation effects, such as SHE and DIBL effects, is an optimization task in 2D MoS2-based MOSFETs. The electrical and thermal properties of the back oxide material have been shown to have a major influence on the SHE and DIBL effects in 2D MoS2-based MOSFETs. Indeed, the use of the BOX material with a relative dielectric constant between 3.9 and 25 and a thermal conductivity between 1.4 and 2.3 W/(K\(\cdot\)m) makes it possible to obtain optimum immunity against degradation effects, such as SHE and DIBL effects, in 2D MoS2-based MOSFETs. Finally, it was observed that the gate oxide material has almost no considerable impact on the SHE effect as well as the DIBL effect.  
Conceptualization, A.E.A.; methodology, A.E.A. and A.Y.; software, K.S.S.; validation, A.E.A. and K.S.S.; formal analysis, J.C.C. and A.Y; investigation, K.S.S.; resources, K.S.S.; data curation, K.S.S.; writing--original draft preparation, A.E.A.; writing--review and editing, A.E.A. and J.C.C.; visualization, J.C.C. and A.Y.; supervision, A.E.A.; project administration A.E.A.; funding acquisition, A.E.A. All authors have read and agreed to the published version of the manuscript. This research was funded by the Ministry of Innovation Development of the Republic of Uzbekistan, grant number Ind-Uzb-2021-80.  
Not applicable.  
Data availability Statement: Data is unavailable due to privacy.  
The authors declare no conflict of interest.
# Conductive Textiles for Signal Sensing and Technical Applications
## 2 Materials Used to Impart Conductivity on Textiles
### Deposition Method  
The deposition is an effective way of applying a thin coating on textile substrates. Metals or non-metals and intrinsically conductive polymers (ICPs) can be deposited on a suitable substrate by following three steps: (a) scatter or vapor deposition, (b) employing sol precursor, and (c) sintering the substrate to start a sol-to-gel transformation [137].
## 1 Introduction
\begin{table}
\begin{tabular}{l c c c c} \hline \hline
**Authors** & **Year** & **Refs.** & **Dataset** & **Method** & **Model** \\ \hline [PERSON] et al. & 2019 & [6] & VCC2018 & VAE with cycle loss & RNNT \\ [PERSON] et al. & 2020 & [7] & VCC2018 & Ref. [6] with multiple decoders & CNN \\ [PERSON] et al. & 2018 & [8] & VCC2016 & GAN with cycle loss & CNN \\ [PERSON] et al. & 2019 & [9] & VCC2018 & Improved [8] by modifying loss and models & CNN \\ [PERSON] et al. & 2020 & [10] & VCC2018 & Improved [9] by applying TFAN norm & CNN \\ [PERSON] et al. & 2021 & [11] & VCC2018 & Improved [9] by masking input feature & CNN \\ [PERSON]. [PERSON] et al. & 2022 & [12] & In-house & Flow-based model & LSTM \\ [PERSON] et al. & 2016 & [17] & VCC2016 & Direct waveform modification & Diff VC \\ [PERSON] et al. & 2019 & [18] & In-house & Applied [17] to a singing voice conversion task & Diff VC \\ [PERSON] et al. & 2018 & [19] & VCC2018 & Open-source implementation of [17] & Diff VC \\ [PERSON] et al. & 2020 & [20] & TIDIGITS & Translation-based method using a transformer & Transformer \\ [PERSON] et al. & 2022 & [21] & VCTK & Content and speaker disentanglement & CNN \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Summary of the conventional voice conversion methods. Figure 1: Analysis–mapping–reconstruction steps of a conventional voice conversion system. \(w^{A}\) and \(s^{A}\) represent the waveform and the feature vectors of speaker \(A\), respectively. Similarly, \(w^{A\to B}\) and \(s^{A\to B}\) represent the waveform and the feature vectors of the converted speech from speaker \(A\) to speaker \(B\). start from the traditional mel-spectrogram extraction method and gradually optimize the parameters, thereby achieving efficient learning and flexible parameter adjustment. Second, the difficulties of training the GAN models in the proposed wav2 wav method are addressed using pre-training and two-phase training techniques. This allowed us to train the proposed wav2 wav model reliably on small datasets, such as VCC2018 [23]. To verify the performance of the proposed method, objective and subjective evaluations were performed using the mel-cepstral distance (MCD) metric and the mean opinion score (MOS) metric, respectively. The contributions of this paper are as follows:  
* We propose a novel wave-to-wave voice conversion architecture that jointly trains analysis-mapping-reconstruction modules for high-quality voice conversion. * We provide an efficient training algorithm so that the proposed GAN-based integrated model can be reliably trained with very small amounts of training data, such as VCC2018. * The supervised learning process of standalone vocoders were modified to accommodate unsupervised learning in the end-to-end learning of the integrated model. * We demonstrate the usefulness of the proposed method using both objective and subjective measures. The rest of the paper is organized as follows. In Section 2, relevant previous studies are reviewed. Section 3 describes the proposed wav2 wav model. Section 4 analyzes the experimental results. Finally, Section 5 concludes the paper.
## 3 The Proposed Method
### Constructing Graphs from Time Series  
The creation of weighted graphs is imperative for accurately representing the interactions between samples. Figure 4 demonstrates the step-by-step process for constructing weighted graphs, which involves data normalization of the original time series with a certain signal length. Subsequently, the time series data can be normalized as follows:  
\[X^{N}=NOR(X) \tag{13}\]  
where \(X^{N}\) represents the normalized time series. NOR (\(\cdot\)) refers to different normalization methods, and the maximum-minimum normalization method is employed [23].  
Once data normalization is complete, the resulting values can be segmented into data samples of predetermined subsample lengths or dimensions \(d\). This process yields a dataset that is ideal for further analysis and modeling:  
\[\left\{\begin{array}{l}M=\left(x_{1}^{Nol},x_{2}^{Nol},\ldots,x_{n}^{Nol} \right),x_{n}^{Nol}\in X^{Nol}\\ n=floor\left(\frac{d}{d}\right)\end{array}\right. \tag{14}\]  
where \(M\) is the constructed subsample set, \(x_{n}^{Nol}\) denotes subsamples, \(n\) is the total number of subsamples, \(floor\) represents rounding to negative infinity, and \(d\) is the size of the subsamples.  
Figure 3: The attention-based readout module.  
To mitigate the effects of environmental noise generated by axial piston pumps on graph features, we conducted fast Fourier transform (FFT) on each subsample, and viewed the resulting spectrum as a distinct sample. This process can be illustrated as follows:  
\[\widetilde{x}_{i}=FFT\Big{(}x_{i}^{Nol}\Big{)},i=1,2\ldots n. \tag{15}\]  
The _FFT_ refers to the process of converting subsamples to the frequency domain and then extracting the resultant frequencies. By assigning identical labels to each sample, a labeled dataset can be obtained:  
\[D=\Big{[}\Big{(}\widetilde{x}_{1},y_{1}\Big{)},\Big{(}\widetilde{x}_{2},y_{1} \Big{)},\ldots\Big{(}\widetilde{x}_{n},y_{n}\Big{)}\Big{]} \tag{16}\]  
where \(D\) is the labeled dataset.  
To determine the top-k nearest neighbor for every node, a weighted graph can be generated using the aforementioned dataset. The resulting neighbors of node \(x_{i}\) can then be written as follows:  
\[Ne(x_{i})=KNN\big{(}k^{\prime},x_{i},\zeta\big{)} \tag{17}\]  
where \(k^{\prime}\) is taken as 5 in this paper. \(\zeta=[x_{i+1},x_{i+2},\ldots,x_{i+m}]\) is a subset with \(m\) samples, and \(Ne(x_{i})\) represents the nearest neighbor of node \(i\). The edge weights between nodes in a weighted graph can be estimated using the Gaussian kernel weight function. This function is defined as follows:  
Figure 4: The process of creating time series weighted graphs.  
\[e_{ij}=\exp\left(-\frac{\left\|\left(x_{i},x_{j}\right)\right\|^{2}}{2\delta^{2}} \right),\ x_{j}\in Ne(x_{i}) \tag{18}\]  
where \(e_{ij}\) represents the edge weight between node \(x_{i}\) and node \(x_{j}\), while \(\delta\) denotes the bandwidth of the Gaussian kernel.
# Active Tunable Elastic Metasurface for Abnormal Flexural Wave Transmission
## 4 Conclusions  
In the present study, a tunable metasurface consisting of adaptive unit cells attached with piezoelectrical actuators and sensors was achieved by applying the negative proportional feedback control strategy. The flexural motion of the metasurface was derived based on the equivalent parameters of the adaptive unit cells. Employing the TMM, the analytical model was established to predict the transmittance and the phase shift of flexural waves propagating through the metasurface, and the validity was verified by comparing the results to those from FEM simulations. Based on the generalized Snell's law, a metasurface with 40 adaptive unit cells was designed. The passively modulated metasurface was constructed by changing the proportion of the adaptive unit cell occupied by sub-cells, and abnormal modulation flexural waves were achieved at 6 kHz. With the fixed geometrical parameters of the passively modulated metasurface, different phase gradients were generated by adjusting the negative proportional feedback system control gain. Full-wave simulations were performed in finite elements, and the metasurface achieved functions such as the abnormal transmission of multiple angles and the planar lensing of multiple positions at different operating frequencies. A comparison of the theoretical design and finite element simulations shows that this study is reproducible and reliable, which proves the feasibility of the design structure and method. The introduction of a negative proportional positive feedback control strategy provides an active method for adjusting the phase gradient to modulate flexural waves.  
Conceptualization, B.L. and J.L.; methodology, B.L. and J.L.; software, B.L. and J.L.; validation, B.L., J.L. and W.L.; formal analysis, B.L. and J.L.; investigation, J.L., W.L. and Q.M.; resources, B.L. and J.L.; data curation, B.L. and J.L.; writing--original draft preparation, B.L. and J.L.; writing--review and editing, B.L. and J.L.; visualization, B.L., J.L., W.L. and Q.M.; supervision, J.L.; project administration, J.L.; funding acquisition, J.L. All authors have read and agreed to the published version of the manuscript.  
Figure 10: The out-of-plane displacement diagrams of the transforming guided wave at (**a**) \(f\) = 6 kHz and (**b**) 7 kHz.  
**Funding:** This research was funded by the National Natural Science Foundation of China, grant number 52365009, the Natural Science Foundation of Hainan Province, grant number 122 MS004, and the Fundamental Research Funds for the Central Universities, grant number 3072022]C2601.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The data presented in this study are available on request from the corresponding author due to privacy reasons.  
**Conflicts of Interest:** The authors declare no conflicts of interest.
# Structural Designing of Supersonic Swirling Devices Based on Computational Fluid Dynamics Theory
## 2 Structural Design Method of Supersonic Swirling Separator for Natural Gas Liquefaction
### Design of Swirl Generator  
To control the expansion waves and oblique shockwaves easily and to improve the pressure recovery capability of the supersonic separator, a radial swirl generator (Figure 2) was installed in front of the stabilization section of the nozzle inlet to generate swirling gas flow.  
The generator consists of several circular arc vanes arranged evenly along the direction of the nozzle inlet cross-section. The ends of the vanes were tangential to the nozzle inlet. The design parameters are as follows: height of the swirl generator \(H\), outer diameter \(D\), inner diameter \(d\), minimum distance between the vanes \(w\), vane thickness \(b\), vane angle \(\theta\), vane arc radius \(R\), and number of vanes \(n_{\text{sb}}\). The vane arc radius \(R\) and vane angle \(\theta\) are important parameters to be considered when designing vanes. Generally, the inner diameter \(d\) of the swirl generator is the same as the inner diameter of the stabilization section of the inlet of the supersonic nozzle. When \(n_{\text{sb}}\), \(w\), and \(b\) are known, \(R\) can be obtained using geometric methods. As shown in Figure 3, \(O_{1}\) and \(O_{2}\) are the centers of the inner circle of the radial swirl generator and arc vanes, respectively. \(A\) and \(D\) are two points on the inner circle, \(r_{\text{nei}}\) is the radius of the inner circle, \(BD\) is the vane thickness, \(C\) is the intersection of the \(O_{2}C\) extended line and vane, and \(BC\) is the distance between points \(B\) and \(C\). \(O_{1}D=O_{1}A=r_{\text{nei}}\), \(O_{2}C=R\), \(BD=b\), and \(BC=w\). \(\beta\) is the angle between the ends of two adjacent vanes: \(\beta=360^{\circ}/n_{sb}\) and \(\alpha=180^{\circ}-\beta\).  
According to the law of cosines, the following relationship can be obtained from triangle \(O_{1}BO_{2}\) (Figure 3):  
\[|O_{2}B|^{2}=\Big{|}O_{1}B^{2}\Big{|}+|O_{1}O_{2}|^{2}-2\cos\alpha|O_{1}B| \cdot|O_{1}O_{2}|, \tag{4}\]  
and  
\[(R-w)^{2}=(r_{\text{nei}}+b)^{2}+(R-r_{\text{nei}})^{2}-2\cos\alpha(r_{\text {nei}}+b)\cdot(R-r_{\text{nei}}). \tag{5}\]  
From Equation (5), the expression for the vane arc radius can be obtained as:  
\[R=\frac{2r_{\text{nei}}(1+\cos\alpha)(r_{\text{nei}}+b)+b^{2}-w^{2}}{2[r_{ \text{nei}}-w+\cos\alpha(r_{\text{nei}}+b)]}. \tag{6}\]  
Figure 2: Schematic of the radial swirl generator.  
The vane arc angle \(\theta\) is related to the number of vanes; the larger the number of vanes, the smaller is the angle.  
Once the inlet pressure and size of the supersonic nozzle are determined, the swirling intensity of the gas flow inside the supersonic nozzle can be fixed by adjusting the minimum flow area of the swirl generator, \(A_{\text{min}}\).  
\[Asb_{min}. \tag{7}\]
## 1 Introduction
### The Challenge of Monitoring the Development of Crater Rows  
The accessibility and visibility conditions at an active volcano are often challenging and obscured due to the emission of ash, steam, and volcanic gasses, which, combined with rapidly changing weather conditions, make direct and close observations hazardous. This is also why successful monitoring of active volcanoes with passive optical remote-sensing satellites such as Landsat, Pleiades, SPOT, or Sentinel-2 rarely provide a temporal or spatial resolution sufficient for change detection. On the other hand, active sensors such as synthetic aperture radar (SAR) transmit their own radio signal and measure the amount of energy backscattered by the object, making them independent of sunlight and atmospheric conditions. Furthermore, SAR collects information in the longer wavelengths, specifically in the microwave part of the electromagnetic spectrum, thus is allowing visibility through clouds, volcanic gasses, ash, and steam [20; 21]. In this study, we have used X-band radar amplitude signal images acquired from the COSMO-SkyMed (Constellation of small Satellites for Mediterranean basin Observation) SAR satellites to track surface changes and analyze the development of new eruption vents. The analysis of X-band amplitude signal has already provided results at other volcanoes, e.g., at Merapi in Indonesia [21], Soufriere Hills on Montserrat Island [22; 23], or Cotopaxi in Ecuador [24].  
Volcanic structures and edifices can display rapid changes during volcanic activity, and interpretation of many of these variations requires visual confirmation. Therefore, video and time-lapse camera records helped to monitor volcanic surface changes [24]. Time-lapse cameras have been used to elaborate on the transition from fissure eruptions to formations of crater rows and associated topographic changes [14; 15]. It was shown that dike intrusions feed a long and continuous fissure eruption in the first hours to days, which then evolve into several aligned eruption vents with the formation of craters [14].  
It is likely that the distinct craters at the surface are connected to multiple deeper dikes along finger-like conduits also during a later stage of the eruption. However, the geometric details of this connection are debated [25]. While the erupting craters grow in depth and dimension, their location often remains stable throughout the eruption [14]. This differs from observations made at La Palma, where the feeder dike opened multiple new eruptive events during the 85 days of the 2021 eruption. At first, vents were aligned in a clear profile facilitating the monitoring of the lava fountains; however, they disaggregated during the later stages of the eruption. The details of such a deviation of crater rows from an idealized chain alignment have not been studied in previous works. In this study, we combine SAR and optical camera time-lapse data to trace craters, to locate crater positions and lava fountain activity, further comparing the results to a seismic catalogue.