esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Methods  
This study employed a scoping review methodology to evaluate the effectiveness of tDCS and tMS as alternative or adjunctive treatments for MDD, particularly in patients resistant to conventional therapies. By analyzing evidence from both clinical studies and animal models, the study seeks to assess the potential of these neuromodulation techniques in improving treatment outcomes, cognitive function, and neuroplasticity in individuals with MDD.  
Research Objectives:  
1. To investigate the neurobiological mechanisms through which tDCS and tMS modulate brain activity in the treatment of MDD.
2. To explore findings from animal models and their translational relevance to clinical applications for MDD treatment.
3. To provide recommendations for integrating tDCS and tMS into personalized treatment approaches for patients with treatment-resistant depression.  
Our review was guided by the following research question:  
RQ. How do tDCS and tMS modulate brain activity and improve treatment outcomes in patients with MDD, particularly those resistant to conventional therapies?  
The scoping review methodology was chosen to provide a broad synthesis of existing research, particularly in both animal models and human clinical studies, based on the criteria outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for scoping reviews.  
For the paper extracted for this review, we considered the following criteria: (1) Our study includes preclinical animal models and human patients diagnosed with MDD. The clinical studies evaluated include participants with treatment-resistant depression and those undergoing tDCS/tMS as monotherapy or combined with antidepressants or psychotherapy. (2) We considered peer-reviewed journal articles, clinical trials, and preclinical studies investigating the therapeutic use of tDCS and tMS in MDD. Both standalone and combination interventions were included. (3) The primary outcomes analyzed include efficacy in symptom reduction (measured through depression rating scales such as HDRS, MADRS, and BDI), cognitive function improvements, and neuroplasticity-related biomarkers (e.g., neuroimaging and neurophysiological data).  
Inclusion criteria. Studies published in peer-reviewed journals that assess the effectiveness of tDCS or tMS in MDD, including clinical trials, systematic reviews, meta-analyses, and animal model research.  
Exclusion criteria. Studies lacking primary data, case reports, studies on neuromodulation methods other than tDCS/tMS, and non-English publications.  
Search strategy and replicability. While this study follows a scoping review approach, we adhered to a structured literature search strategy using PubMed, Scopus, and Web of Science databases. The search terms included \"transcranial direct current stimulation\", \"transcranial magnetic stimulation\", \"Major Depressive Disorder\", and \"neuromodulation\". No restrictions were placed on the publication year to capture the full scope of available literature.
###### Abstract  
The impact of different photovoltaic models for a combined solar array and pumped hydro storage system was investigated. Al-Wehda dam located in Harta city in the northern of Jordan was used to validate the approach. The two-diode (TD), single-diode (SD), and ideal single-diode (ISD) solar models were evaluated in terms of the solar array size, reliability, and ecological effects. The impoundment of Al-Wehda dam was taken as the upper reservoir of the pumped hydro facility of the proposed renewable energy system. It was found that the PV power is more accurately modelled by considering the recombination loss in the TD solar model. This leads to a more realistic sizing and precise system evaluation. Results were obtained using the particle swarm optimization (PSO) algorithm and the whale optimization algorithm (WOA) for validation purposes. For instance, the PSO results showed that the realistic TD model is reliable, with an index of reliability of 98.558%. Further, it is the most ecological solution with an annual emissions reduction of 21.5198 Gg. The optimized values are 44,840 solar panels and 65.052 M.m\({}^{3}\) of the lower reservoir volume for the TD model. The number of PV panels are reduced by 16.67% and 7.93%, respectively, with the ISD and SD relative to the TD model.  
two-diode PV model; reliability improvement; recombination PV model; realistic PV model; particle swarm optimization; whale optimization algorithm; pumped hydro storage; renewable energy system optimization; emissions reduction; uncertainty analysis 2020 10 3650 10.3390/app10103650
# Future Is Unlicensed: Private 5G Unlicensed Network for Connecting Industries of Future
## 4 Challenges and Research Directions
### Challenge 6: Coexistence of Asynchronous Access and Synchronous Access Systems  
The unlicensed and shared band provides a simple, time-based spectrum access rule that is technology-neutral, fair to all spectrum users, and does not favor any unlicensed technology. However, when we consider the coexistence of asynchronous access systems with synchronized access systems for NR-U in the shared spectrum, synchronous systems can starve, as asynchronous systems could access the medium at any point in time and prevent equal access by synchronized access systems.  
This problem can be eliminated entirely by using a dedicated spectrum band for the synchronous and asynchronous access systems, but for global adoption, this is quite infeasible. Hence, one of the possible approaches that can be used is conditional relaxation of the maximum channel occupancy time (COT). The conditional relaxation specifies the maximum COT for the asynchronous and synchronous system. In this approach, the maximum COT for asynchronous access systems is kept fixed while the COT for synchronous access systems is variable, i.e., the COT can be extended beyond the nominal value (only if the medium is utilized by synchronizing medium access during sync time). As shown in Figure 7, the extension of COT can be made shorter or longer to increase the efficiency of resources and to maintain fairness among the systems. On top of this mechanism, we also can use the multi-domain coexistence approach stated in Challenge 6 and the SON approach stated in Challenge 3 for COT optimization purposes.
## 4 Results and Discussion
### Comparative Analysis
In real-world scenarios, particularly those involving iterative development, frequent updates, or time-sensitive analysis, a several-day wait time may be considered excessive. In contrast, [PERSON] et al. [38] achieved a 2.56 speedup factor when employing a multi-core processing configuration with five CPU cores on a standard personal computer. While this result implies an acceptable level of parallel efficiency, it also highlights limitations in scalability and parallel job distribution. This result shows that the algorithm's intrinsic serial components limit its capacity to scale efficiently over several cores. Furthermore, the utilization of only five cores, while feasible for a consumer-grade setup, raises the question of how well the approach would function on systems with more parallel capacity. A key factor influencing the performance of MPI-based implementations is the number of communications required, which is directly dependent on the number of processed chains, as each process generates chains independently, unlike the referenced paper's [10] approach. In the referenced implementation, there are additional communications related with tasks distribution, which are eliminated in our proposed implementation. Our approach eliminates this communication overhead by avoiding explicit task distribution and as a result reduces the bottleneck in the master process. This comparison highlights the importance of efficient process management and communication strategies in parallel computing. Our results confirm that a carefully designed parallel implementation can deliver excellent performance, even in environments with limited computational resources. In Table 4, we present the summary of the comparative analysis, covering six aspects of all implementations. Those aspects include the problem addressed in each paper, the parallelization model, number of computing nodes (or CPU cores) used for execution of experiments, performance improvement as reported in the respective papers, execution time and the strategy to handle chain merges.
## 2 Methods
### Finite Element Method Analysis
#### 2.3.2 Galerkin Method of Weighted Residuals  
The Galerkin method of weighted residual is employed to derive the system equations from the governing differential Equations (8) and (9).  
1. Multiply both sides of Equation (8) by \(\delta\mathbf{A}\), and then perform integration over the entire study domain, as follows: \[\int_{\mathrm{v}}\left[\
abla\times\frac{\
abla\times\mathbf{A}}{\mu_{r}}-i \omega\mu_{0}\widetilde{\sigma}(\mathbf{A}+\
abla\phi)\right]\cdot\delta \mathbf{Adv}=0.\] (14) where \(\mathrm{v}\) denotes the entire study domain. Taking into consideration the vector identity given in Equation (15) and the divergence theorem stated in Equation (16), \[(\
abla\times\phi)\cdot\psi=\
abla\cdot(\phi\times\psi)+(\
abla\times\psi)\cdot\phi\] (15) \[\int_{\mathrm{v}}\
abla\cdot\mathbf{B}\;\mathrm{dv}=\int_{\Gamma}\mathbf{B} \cdot\mathrm{d}\Gamma.\] (16) Then, the first term of Equation (14) can be rewritten as, \[\int_{\mathrm{v}}\
abla\times\left(\frac{1}{\mu_{r}}\
abla\times\mathbf{A} \right)\cdot\delta\mathbf{Adv}=\int_{\mathrm{v}}\
abla\times\delta\mathbf{A} \cdot\frac{\
abla\times\mathbf{A}}{\mu_{r}}\mathrm{dv}+\int_{\Gamma}\left( \frac{\
abla\times\mathbf{A}}{\mu_{r}}\right)\times\delta\mathbf{A}\cdot \mathrm{d}\Gamma.\] (17)  
Subsequently, substituting Equation (17) into Equation (14), while considering the counteraction of the surface integral, leads to a modification of Equation (16), as follows:  
\[\int_{\mathrm{v}}\left[\
abla\times\delta\mathbf{A}\cdot\frac{\
abla\times \mathbf{A}}{\mu_{r}}\mathrm{dv}-i\omega\mu_{0}\widetilde{\sigma}(\mathbf{A}+ \
abla\phi)\right]\cdot\delta\mathbf{Adv}=0. \tag{18}\]  
2. Considering the divergence theorem (Equation (19)),  
Figure 1: Mixed nodal and edge-based elements, along with their respective local coordinate systems.  
\[\
abla\cdot(\phi\mathbf{B})=\phi(\
abla\cdot\mathbf{B})+\mathbf{B}\cdot(\
abla\phi) \tag{19}\]  
After multiplying both sides of Equation (9) by \(\phi\phi\) and integrating the equation over the entire study domain, Equation (20) is derived, as follows:  
\[\oint_{\mathrm{s}}i\omega\mu_{0}\widetilde{\sigma}\delta\phi(\mathbf{A}+\
abla \phi)\mathrm{d}\mathrm{s}-\int_{\mathrm{v}}\
abla\delta\phi\cdot i\omega\mu_{0} \widetilde{\sigma}(\mathbf{A}+\
abla\phi)\mathrm{d}\mathrm{v}=0 \tag{20}\]  
Similarly, the first integral of Equation (20) remains zero; thus, Equation (20) transforms into,  
\[-\int_{\mathrm{v}}\
abla\delta\phi\cdot i\omega\mu_{0}\widetilde{\sigma}( \mathbf{A}+\
abla\phi)\mathrm{d}\mathrm{v}=0 \tag{21}\]  
The system equations for this element are obtained by combining Equations (18) and (21), while considering that \(\delta\mathbf{A}\) and \(\delta\phi\) can take any value and incorporating the boundary conditions. This leads to the final equation system, as follows:  
\[\mathbf{Ku}=\mathbf{b}. \tag{22}\]  
where \(\mathbf{K}\) is the global matrix, \(\mathbf{u}\) is the unknown electric field vector, and \(\mathbf{b}\) is the right-hand vector.  
After solving Equation (22), the potentials of \(\mathbf{A}\) and \(\phi\) are obtained.
# Evaluation of Multi-Source High-Resolution Remote Sensing Image Fusion in Aquaculture Areas
## 2 Materials and Methods
### Raff Culture Zone Fusion Evaluation  
The applied fusion techniques have improved the spatial information in the floating raft areas of the GF-1, GF-2, and WV-2 data. The rafts can be clearly seen in each of the fused images and the outline of the breeding area can be easily distinguished. However, the contrast is poor between the floating rafts and the bodies of water, which are connected in the breeding area. The number of rafts cannot be identified, primarily because the resolution of the GF-1 data is lower than that of the GF-2 and WV-2 images. Each fused image has maintained its spectrum, resembling the color of the original multispectral data, for the GF-1 (see Figure 8), GS and PCA fusion results are closer to the original images. Water in the NNDiffuse results appears dark green, which is more prominent than the  
Figure 7: \(CQ_{max}\) of fusion results in the enclosure seine culture area.  
floating raft cultures in the image. For the GF-2 (see Figure 9), the color and texture of the image after GS and NNDiffuse fusion is closest to the original multispectral images. The contrast is also higher and some brighter spots have been added to the edges of the floating rafts in the NNDiffuse results. In comparison, the PCA fusion result is dark and the contrast is poor between floating rafts and water, which is not conducive to object identification or extraction. For the WV-2 (see Figure 10), the color in the GS and PCA fusion images is brighter. The water is dark blue in the GS results and light blue in the PCA results. The color in the NNDiffuse images is closest to the original multispectral data, with high contrast between the water and the floating rafts.  
Figure 8: Comparison of fusion effects for GF-1 data for floating raft culture.  
Figure 9: Comparison of fusion effects for GF-2 data for floating raft culture.
###### Abstract
In this context, the use of RNs presents several advantages, such as a reduction in total transmission power, a decrease in network capacity dispersion, the elimination of penetration losses in outdoor-to-indoor scenarios, and an increase in network coverage that combined with the access link in millimeter bands can lead to a notable improvement in network operation [11; 12]. Furthermore, RN techniques have been studied and considered for standardization by the 3 GPP [13]. The most common strategies are Amplify-and-Forward (A&F) and Decode-and-Forward (D&F) [14], which have been considered in the LTE technology together mmWave MIMO techniques. However, the mmWave MIMO RNs have not been deeply studied in the new scenarios proposed by 3 GPP [15]. In these scenarios, 5G New Radio (NR) Networks using RNs [16] are expected to provide higher performance and solve some of the issues for deployment in these scenarios. Motivated by the above issues, in this paper, we implemented a mmWave MIMO Relay cooperative network, where signals with 5G features were considered. The major contributions of this paper are summarized as follows:  
* A two-hop architecture using out-of-band RNs in mmWave frequencies and with MIMO capabilities is presented. In the simulated architecture, the NR 5G signal features: DL-SCH transport channel coding, PDSCH generation, and SS Burst generation, were used. The relay assists the communication in the outdoor-to-indoor environment between the gNodeB and User Equipment (UE). * Two relaying strategies, Amplify-and-Forward (A&F) and Decode-and-Forward (D&F) were implemented. Besides, two alternatives of D&F protocol were considered. The first takes into account the channel knowledge and the second performs the channel estimation through the Least Square (LS) estimator and Bi-Cubic Interpolate (BCI), both in the Backhaul Link of the architecture proposal. * Analytical expressions for both A&F and D&F relaying strategies of the proposed two-hop mmWave MIMO Relay cooperative system were derived. * A mmWave transmitter and receiver chains were designed using off-the shelf components. Furthermore, extensive simulations were taken into account and carried out with the MathlabTM and SimulinkTM tools, considering the non- linearity of mmWave subsystems. The remainder of this paper is organized as follows. In Section 2, the system model of the two-hop MIMO mmWave NR-RN is presented. Then, the network model of the mmWave NR-RN cooperative system in an outdoor-to-indoor scenario is detailed in Section 3, as well as the implementation of the Decode-and-Forward NR-RN and the mmWave transmitter and receiver chains. In Section 4, the numerical results of the designed architecture are presented and discussed. Conclusions are drawn in Section 5.
# Dielectric Slabs-Based Lens for Millimeter-Wave Beamforming
## 1 Introduction
The metallic lens also behaves as anisotropic and cannot be manufactured for elevation and azimuthal planes in the same design. In addition, they are expensive and complex. Therefore, there is a crucial need for designing a dielectric-based lens, which is simple in manufacturing and can be modified easily. GRIN lens using 3D printing technology were presented in [18; 19; 20]. A-holes/voids in the lens design were included to lower the limit on the available refractive index range. These lenses were a good approximation to semi-spherical lenses for the lower frequencies where the cell size is enough to make a hole in. Therefore this approximation will not be valid for the extreme case of a solid dielectric block and dielectric blocks with very small holes, especially for high frequencies. A GRIN-like dielectric slab lens was also studied in [21]. The researchers used dielectric slabs with different widths and equal thicknesses, separated by equal air gaps. The concentration of the number of gaps varies radially and makes the dielectric slab a smoothly graded-index media, which gives it focusing or diverging properties. This lens is more efficient for the higher frequencies, but it is still needed to connect these slabs together as a whole lens. In addition, the air gap size can have a significant effect on the performance of the lens, especially on the focal distance. The limitation related to the air-gabs was solved in [22]. Researchers in this recently published paper utilized dielectric slabs that have the same widths, different thicknesses, and different lengths. In this paper, a dielectric slabs-based lens is designed for millimeter-wave beamforming in both azimuth and elevation planes. This lens is created by discretizing the semi-spherical lens to several slabs based on the effective medium theory concept. These slabs can be fabricated with a circular shape with different radii and the same thickness not exceeding a quarter of the operating wavelength to keep on the similar effective refractive index of the original semi-spherical lens. The effect of air/epoxy materials within the dielectric slabs, maximum gain, sidelobe levels, and HPBW are investigated to test the performance of the designed lens. The millimeter-wave beamforming capabilities based on the proposed lens are also demonstrated by using 16 switchable horn antennas.
# Effect of Wing Membrane Material on the Aerodynamic Performance of Flexible Flapping Wing
## 3 Data Acquisition and Deformation Measurement
### Deformation Measurement  
The rotation angles of three different wing sections (25%, 50%, and 75% of the wingspan) are measured to obtain the wing's deformation. As shown in Figure 5a, the white-colored markers with a diameter of about 2 mm are placed at the leading edge and corresponding trailing edge. The flapping process is filmed with two synchronized high-speed cameras (Phantom VEO-E 340L) with a resolution of 1280 \(\times\) 960 pixels at 2000 fps. As presented in Figure 5b, the cameras are arranged approximately orthogonally to clearly capture the marked points. The position of the markers was tracked manually in each frame using the open-source digitizing tool, DLTdv8, developed by [PERSON] [26], and based on the direct linear transformation method. Meanwhile, two additional markers were placed on the steel bar fixed at the wing root, which were tracked as a reference to calculate the rotation angle.  
As seen in Figure 6, the chord line is the line connecting the leading and trailing edge at a specified wingspan section. The rotation angle \(\theta\) is defined as the angle between the chord line and the vertical line, which is parallel to the flapping axis. The angle of attack \(\alpha\) is defined as the angle between the incoming flow and the chord line. According to the geometric relationship, the angle of attack \(\alpha\) can be expressed as:  
\[\alpha=\pi/2-\theta \tag{6}\]  
Figure 5: Deformation measurement setup. (**a**) Markers on the wing; (**b**) The experimental layout for the deformation measurement.  
Figure 6: Definition of the flapping angle variables.
# Exploiting Outage and Error Probability
## 3 System Performance Analysis and Our Proposed Cooperative Routing Protocols
### Proposed Scheme 2: E-Ace
#### Data Transmission Phase  
Till 2 nd retransmission, this phase is similar to ACE's data transmission phase. However, if BER is not acceptable after retransmission from R2, R3 does data retransmission and the process continues till all the retransmission nodes are expired or acceptable BER is achieved as shown in Figure 6d. Figure 7 presents data transmission flow chart of a single packet for E-ACE.
# A Survey on Change Detection and Time Series Analysis with Applications
## Conflicts of Interest: The authors declare no conflict of interest. Abbreviations  
The following abbreviations are for the time series analysis methods mentioned herein:  
\begin{tabular}{l l} ALFT & Anti-Leakage Fourier Transform \\ ALLSSA & Anti-Leakage Least-Squares Spectral Analysis \\ ASFT & Arbitrary Sampled Fourier Transform \\ BFAST & Breaks For Additive Seasonal and Trend \\ CCDC & Continuous Change Detection and Classification \\ CLSSA & Constrained Least-Squares Spectral Analysis \\ CWT & Continuous Wavelet Transform \\ XWT & Cross Wavelet Transform \\ DBEST & Detecting breakpoints and Estimating Segments in Trend \\ DFT & Discrete Fourier Transform \\ DTFT & Discrete-Time Fourier Transform \\ DWT & Discrete Wavelet Transform \\ EMD & Empirical Mode Decomposition \\ EWMACD & Exponentially Weighted Moving Average Change Detection \\ EWT & Empirical Wavelet Transform \\ HHT & Hilbert-Huang Transform \\ IMAP & Interpolation by MAtching Pursuit \\ JUST & Jumps Upon Spectrum and Trend \\ LSCWA & Least-Squares Cross Wavelet Analysis \\ LSSA & Least-Squares Spectral Analysis \\ LSWA & Least-Squares Wavelet Analysis \\ MALLSSA & Multichannel Anti-Leakage Least-Squares Spectral Analysis \\ MIMAP & Multichannel Interpolation by MAtching Pursuit \\ OLS & Ordinary Least-Squares \\ OLS-MOSUM & Ordinary Least-Squares Residuals-Based Moving Sum \\ STFT & Short-Time Fourier Transform \\ WWA & Weighted Wavelet Amplitude \\ WWZ & Weighted Wavelet Z-Transform \\ \end{tabular}  
Figure A3: A flowchart of the IMAP algorithm in matrix form.  
Figure A4: A flowchart of the ALLSSA algorithm.  
Figure A5: A flowchart of the LSWA algorithm.