esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Computational Algorithm  
The numerical solution of the nonstationary, two-dimensional, radiation-gasdynamic model developed in the work is based on the method of splitting into physical processes and spatial directions. The developed computational codes use a multiblock, multigrid technology for calculations on nonorthogonal, structured grids. To solve the gasdynamic part of the system of equations, a nonlinear, quasi-monotone, compact-polynomial difference scheme of increased order of accuracy [23] is used, as well as the spatial splitting of the Reynolds equations [15], written in an arbitrary curvilinear coordinate system (\(\xi,\eta\)). When calculating the flux vectors at the boundaries of the computational cell, the procedure for calculating the decay of the discontinuity developed in [24] was used. Other details of the nonlinear, quasi-monotone, compact-polynomial difference scheme are given in [24; 25]. The rigid part of the system of equations of the \(q-\omega\) Coakley model was solved using the implicit Rosenbrock method.  
The method for calculating the transfer of broadband radiation is considered on the basis of the multigroup diffusion approximation [17; 18]. To find a numerical solution to the diffusion approximation of the radiation transfer equation, a modified, alternating triangular method was applied using a three-layer iterative scheme, in which the iterative timestep is found using the method of conjugate directions [26]. The timestep \(\Delta t\) necessary for the integration of the above difference scheme is selected from the condition of the Courant-Friedrichs-Levy stability criterion.  
The hyperbolic (convective) part of the computer model was tested on a one-dimensional version of the Riemann problem (Soda problem) on the decay of an unstable discontinuity of a given configuration. A comparison of the exact and approximate solutions showed that the difference is no more than a percent [23; 27]. Verification calculations (in order to assess the degree of attenuation of the system of reflected shock waves) were carried out for experimental conditions. The calculations performed in [28] showed that the calculation error is within the experimental accuracy of the results and can reach a level of \(10\%\). These results are also in good agreement [23] with the indicated calculations. (The relative error is \(0.4\%\).)  
The parabolic (thermal) part of the model was tested on some problems that admit exact analytical solutions: heating of a continuous medium [27; 29] filling a flat semi-bounded space \(r>0\) by a heat flux through the left fixed boundary \(r=0\). (The relative error is less \(1\%\).)
# Fail-Safe Topology Optimization Using Damage Scenario Filtering
## 2 Theory of Fail-Safe Structural Topology Optimization  
In this section, the fundamental principles of fail-safe topology optimization are discussed. For the topological optimization of linear elastic materials, the Young's modulus \(E_{e}\) can be obtained through the modified Solid Isotropic Material with Penalization (SIMP) [39; 40; 41], as illustrated in Equation (1).  
\[E_{e}=E_{\text{min}}+\rho_{e}^{p}(E_{0}-E_{\text{min}}) \tag{1}\]  
where the design domain of the continuous structure, \(\Omega\), is discretized into N finite elements, each associated with the relative density variable \(\rho_{e}\), which varies within the [0, 1] range. Here, \(E_{0}\) represents the elastic modulus of the solid material, \(p\) is the penalization factor for the void material, and \(\eta\) serves as the design variable in the optimization problem, representing the unit density. Additionally, \(E_{\text{min}}\) denotes the elastic modulus of the void material, serving the purpose of mitigating the singularity and non-zero entries in the finite element stiffness matrix.
## 6 Conclusions  
In this work, we proposed TS-CGANet, a two-stage complex and real dual-path sub-band fusion network for full-band speech enhancement. We introduced the convolution-augmented gated attention unit into the full-band speech enhancement method and employed spectrum splitting to process full-band speech. This approach enabled better handling of the global and local information of low-frequency speech and provided external knowledge guidance when processing high-frequency speech. Moreover, we proposed a complex CGAU that enhanced the interaction between the real and imaginary parts of speech, improved the performance of the decoupling phase compensation method, and enhanced speech quality. Experiments on the Voice Bank + DEMAND dataset showcased the notable performance improvements of our proposed TS-CGANet model over the base  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Method** & **PESQ** & **CSIG** & **CBAK** & **COVL** & **STOI** \\ \hline
**TS-CGANet** & **3.30** & 4.31 & **3.69** & **3.82** & **0.95** \\ LB-Net (full) & 3.16 & 4.24 & 3.64 & 3.71 & 0.95 \\ LB-Net (with real CGAU) & 3.11 & 4.22 & 3.61 & 3.68 & 0.95 \\ LB-Net (w/o phase enhancement) & 2.81 & 3.24 & 3.04 & 3.01 & 0.94 \\ TS-CGANet (with real CGAU) & 3.24 & **4.37** & 3.69 & 3.82 & 0.95 \\ TS-CGANet (w/o phase enhancement) & 3.18 & 4.33 & 3.62 & 3.77 & 0.95 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Results of the ablation study.  
line models of the same category. In the future, we will further explore other methods for full-band speech enhancement.  
Conceptualization, H.C.; funding acquisition, X.Z.; methodology, H.C.; project administration, X.Z.; software, H.C.; validation, H.C.; writing--original draft, H.C. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China (No.: 61172017).  
Not applicable.  
A publicly available dataset (Voice Bank + DEMAND) was analyzed in this study. The Voice Bank + DEMAND dataset can be found here: [[https://datashare.ed.ac.uk/handle/10283/2791](https://datashare.ed.ac.uk/handle/10283/2791)]([https://datashare.ed.ac.uk/handle/10283/2791](https://datashare.ed.ac.uk/handle/10283/2791)) (accessed on 17 December 2021).  
The authors would like to thank all the anonymous reviewers for their helpful comments and suggestions to improve the manuscript.  
The authors declare no conflict of interest.
## 5 Iwoa-Iga--Enhanced WOA Algorithm Featuring Improved Genetic Mechanism
### Iwoa-Iga: Modified Iwo Algorithm Featuring IGA Characteristics
The resulting optimized mapping was executed on the NoC using the unified simulation framework known as ENoCTweak, which was used to simulate and analyze critical NoC system characteristics such as latency, throughput, energy, and power. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Benchmarks** & **Nodes** & **Edges** & **Mesh Size** \\ \hline PIP & 8 & 8 & \(3\times 3\) \\ MPEG-4 & 12 & 26 & \(4\times 4\) \\ MWD & 12 & 13 & \(4\times 4\) \\
263 encMP3 dec & 12 & 12 & \(4\times 4\) \\
263 decMP3 dec & 14 & 15 & \(4\times 4\) \\ Mp3 EncMp3 Dec & 13 & 14 & \(4\times 4\) \\ VOPD & 16 & 21 & \(4\times 4\) \\ CAVLC & 16 & 22 & \(4\times 4\) \\ MMS & 25 & 38 & \(5\times 5\) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Standard NoC benchmarks with 2D mesh sizes. ### Performance-Based Comparative Analysis

As the main aim of this study was to enhance the communication cost, which represents the overall cost associated with running a particular application on NoC (depicted by Equation (1)), the communication cost for both the IWOA and IWOA-IGA were first evaluated based on real-world and TGFF-based graphs. #### 6.2.1 Performance Analysis Based on Standard Benchmark Instances

Both of the developed techniques were tested using real-world applications as well as TGFF-based graphs (presented in the next section). A comparison of the IWOA and IWOA-IGA with other advanced heuristic algorithms and with the exact mathematical solution was carried out. Table 3 depicts the performance comparison in terms of communication cost for various standard benchmark applications. When it comes to estimation of communication cost, ILP (Integer Linear Programming) is regarded as the optimal solution [3]. The results demonstrate that the proposed modified IWOA and its genetically integrated version obtained optimal results derived from real-world instances. \begin{table}
\begin{tabular}{c c} \hline \hline
**Configuration** & **Detail** \\ \hline Network Type & Mesh \\ Type of Platform & Embedded \\ Applications & VOPD, MP3 encMp3 dec, MPEG4, MWD, 263 encMp3 dec, \\  & 263 decMp3 dec \\ Mapping Algorithm & IWOA, IWOA, ISA, PSO \\ PacketDeliveryMode & Without ACK \\ SendingACKPolicy & Send ACK Optimally \\ Packet Distribution & Exponential \\ Fixed Packet Length & 10 (flits) moment \\ Flitin InjectionRate & 0.1 (flits/cycle/node) \\ Type of Router & Wormhole-Pipeline \\ Routing Algorithm & XY DIMENSION-ORDER \\ OutputChannelSelection & XY-ORDER \\ BufferSize & 1 (flit) \\ Pipeline Type & 8 \\ StagesOfPipeline & 4 \\ InputVoltage & 1 (V) \\ Operating Clock Frequency & 100,000 (MHz) \\ Warm-Uptime & 20,000 cycles \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Simulation setup details.
## 3 Testing Results  
### Determination of the Shear Modulus and Damping Ratio  
As a multiphase material, the interaction between mineral particles, such as stilbite, actinolite, and quartz, as well as the dynamic reorganization of the microstructure, significantly influences the shear modulus. Under cyclic loading conditions, the relative positions and contact states between particles alter, leading to the transfer and redistribution of stress concentration areas. Such changes may lead to variations in the trend of the shear modulus. Specifically, the shifting of stress concentration, changes in the contact state, microstructural reorganization, damage accumulation, and changes in the inter-particle forces significantly affect the shear modulus of rocks.  
In cyclic loading and unloading tests, the loading and unloading curves do not coincide and usually form a hysteresis loop, indicating irreversible mechanical actions that lead to energy dissipation [28; 29] during a single cyclic loading cycle. The shear modulus and damping ratio are usually determined from the stress-strain curves of rock specimens, reflecting the nonlinearity and hysteresis of the material [30]. In this test, the modulus of elasticity E is defined as the ratio of the stress difference (the peak stress minus the minimum stress during the loading stage) to the strain difference (the strain corresponding to the peak stress minus the strain corresponding to the minimum stress during the loading stage), calculated over a single cycle. The damping ratio relates to the hysteresis loop formed by the stress-strain curve, and the magnitude of this ratio intuitively reflects the material's energy dissipation under loading effects due to damping. The dynamic shear modulus G and damping ratio \(\lambda\) are calculated as follows:  
\[\mathrm{E}=\frac{(\sigma_{\mathrm{max}}-\sigma_{\mathrm{min}})}{(\varepsilon_ {\mathrm{max}}-\varepsilon_{\mathrm{min}})} \tag{1}\]  
where \(\sigma_{max}\) is the maximum stress in a single cycle, \(\varepsilon_{max}\) is the strain corresponding to the maximum stress, \(\sigma_{min}\) is the minimum stress during unloading in this cycle, and \(\varepsilon_{min}\) is the strain corresponding to the minimum stress.  
\[\mathrm{G}=\frac{\mathrm{E}}{2(1+\
u)} \tag{2}\]  
where \(\
u\) is Poisson's ratio.  
\[\lambda=\frac{\mathrm{A_{R}}}{4\pi\mathrm{A_{S}}} \tag{3}\]  
where \(A_{R}\) is the area of ABCDA, and \(A_{S}\) is the area of AOE. The horizontal coordinate in Figure 6 is \(\varepsilon_{d}\), and the vertical coordinate is the stress \(\sigma_{d}\).  
Figure 5: Cyclic loading path diagram: (**a**) mode 1; (**b**) mode 2; (**c**) mode 3; (**d**) mode 4.
## 1 Introduction
Similarly, the rise of low-cost (and possibly open-source) electronics is an evolution that is increasingly attracting the attention of both research groups and public agencies across the world. For example, this trend can be identified also in the technical development and history of the \"Swift drifters\" family, among others, which are also advancing towards open-source, low-cost, \"do it yourself\" technical solutions [53; 54; 55], focusing on measuring waves in the open ocean. Another example of this trend is visible in recent works that focus on building small, inexpensive, biodegradable surface drifters [46]. Similarly, the Defense Advanced Research Projects Agency (DARPA) is actively pursuing similar efforts with its \"Ocean of Things\" project [56], which aims at \"deploying thousands of low-cost, environmentally friendly, intelligent floats that drift as a distributed sensor network\" (quote from the Ocean of Things project webpage, accessed December 2021). This paper is organized as follows. First, we discuss the general design and features of the instrument v2021. Then, we present a detailed validation of the instrument v2021: (i) in a preliminary deployment, aimed at validating the general concept of the instrument and the power efficiency of the design; (ii) in laboratory experiments that tested the noise threshold of the waves measurements; (iii) in a full-scale deployment in the Russian Arctic; (iv) in a full-scale deployment in the Caribbean. Finally, we offer a few words of conclusion and present a road map for future development. All hardware blueprints, embedded software, postprocessing codes, and detailed instructions are released as open source on Github, as indicated in the Appendix A.
## 2 Materials and Methods
### Microwaves in the Medical Field  
The main benefit of utilizing MW energy resides in the fundamentally different method of transferring energy from the source to the sample. By directly delivering energy to MW-absorbing materials, conventional challenges such as long heating periods, establishing thermal gradients, and energy lost to the system's environment can be avoided. Furthermore, the penetrating phenomenon of MW allows for the volumetric heating of samples.  
The ability to heat specific materials depends on their dielectric properties. MWs are inherently unable to heat a combination of materials uniformly since different human tissues (e.g., liver and bones) all present different dielectric properties. Tissues that contain pathological areas, such as cancer, will also present different dielectric properties relative to the normal surrounding tissue. The unique attributes of MW energy have made the technology very attractive in medical applications as an alternative to conventional methods such as thermal heating or surgical ablations.  
The goal of the technique is one of hyperthermia, where MW's heat to cytotoxic conditions diseased tissues over healthy one. Natural blood flow serves as the basic cooling mechanism to avoid thermal diffusion to healthy tissues. Some applications of thermal ablation can be found in angioplasty, atrial fibrillation, benign prostatic hyperplasia, other urology-related disorders [35], dielectric blood coagulometry, stroke diagnostics [36], and drug efficiency enhancement.  
In most cases, the utilization of MW energy has produced improved results compared to conventional methods while reducing heating time or reaction temperature. MW energy at 2.45 GHz is becoming the prime candidate for medical applications over 915 MHz and RF.  
Until now, MW-assisted technology development has sought uniform heating--which is against the natural behaviour of MWs--and thus, efforts have mostly been devoted to developing \"mechanical solutions\", which involve medical devices that remove the natural selective heating abilities of MWs [37]. No information relating to the development of dielectric-based methods and apparatus can therefore be found in the open access literature. However, the concept is beginning to make inroads. The goal of this research was to design better and more efficient dielectric-based heating strategies. As stated, it aims to make use of and capitalize on the unique selective heating characteristics of MWs by making use of microwave susceptors that are inert to human tissues and possess dielectric properties, such that enhanced temperature gradients will be created locally, while focusing the electric fields in the tissues to be treated. This is also important in the era of precision medicine, as each treatment can therefore be tailored to each patient.
# Potential of Advanced Consolidants for the Application on Sandstone
## 1 Introduction
The oft-used thermal treatment, especially of sandstone, causes physico-chemical changes, such as binder hardening, that render such treated materials unsuitable for consolidation tests. The freeze-thaw cycles are unsuitable for large-scale testing. Additionally, salt crystallization and/or acid attack make it difficult to interpret the consolidation performance. Concerning quarried stone (third option), the test material must be very carefully selected so that it accurately mimics the real weathered one. The Czech Republic is particularly suitable in this respect because it is rich in sandstone quarries, meaning that a wide range of samples differing in texture and mechanical properties are available. Our previous studies have shown that sandstone from the Mene quarry in Central Bohemia is suitable for the evaluation of consolidation performance because it is characterized by high-porosity and relatively low mechanical strength [11; 13; 14]. This sandstone is characterized by high-purity (over 95% of quartz and a small amount of binder), homogeneity and a well-defined monomodal porous system with a narrow pore-size distribution. Moreover, this stone was used as a construction material for extremely important historical monuments in Prague, such as St. Vitus's Cathedral, Charles Bridge, the Old Town Hall and several government buildings. The third fundamental aspect, besides the selection of stone substrate to be tested and the choice of consolidant, is the methodology as to how the success of consolidation will be evaluated. From the practical point of view, the long-term durability of the consolidation effect is more pivotal than the initial level of consolidation. When there is a fast loss of the consolidation effect, such consolidation technology would not be suitable for application. Therefore, in this study, we focus on the aspect of durability and use it as a criterion for the assessment of the consolidation outcome. Specifically, we consolidate Czech-quarried sandstone by various consolidant formulations, including two TEOS-based commercial products (Remmers KSE OH, SurfaPore FX SB), a self-developed TEOS-based PMC consolidant [11], and two self-developed phosphate-based consolidants. Afterwards, we artificially weather the treated samples and determine the durability of each type of sandstone consolidation by performing mechanical tests on a micro- (nanoindentation) and macroscale (drilling resistance measurements). To evaluate the cohesion of the consolidant xerogels, both before and after incorporation into the sandstone pores, sorption experiments are carried out in the gas phase.
# On Analyzing Beamforming Implementation in O-RAN 5G
## 4 O-RAN Beamforming
### Open Research Issues  
The new applications identified in the 5G charter may face challenges in latency with the current O-RAN structure, specifically in the ultra-reliable low-latency communication (URLLC) scenarios such as vehicle-to-everything and boundless XR (e-health), which demand ultra-low latency. The problem lay in determining whether the front-haul open interface (communicating the O-DU and O-RU) is capable of meeting strict requirements for ultra-low latency applications, which implies practically zero interferences in the interface.  
In order to avoid interferences, we propose to implement beamforming by using the channel information method combined with the zero-forcing algorithm. The O-DU will estimate the channel information between O-RU and users and pass this information on as channel matrix information to O-RU through the C-Plane. The implementation of this method is based on Split 7-2x Category B, where the precoding will implement in O-RU in the case that the precoder output streams are over 8.
###### Abstract  
Leveraging technological advancements such as containers, microservices, and service mesh, cloud-native edge computing (CNEC) has become extensively discussed and applied in both academia and industry. The integration of mobile edge computing and communication is crucial for the future communication architecture in order to fully utilize distributed and fragmented communication resources and computing power. The potential for cloud-native integration can help merge mobile edge computing and communication, enhancing network flexibility and resource utilization. This paper investigates the implementation plan for extending cloud-native capabilities to integrated computing and communication (INCCOM) in the satellite-terrestrial network. We construct an experimental verification platform called ComEdge in a real-world setting. Subsequently, we analyze the architecture, functional characteristics, and deployment of the platform in a real-world environment. Furthermore, we explore the solution of deep reinforcement learning in the deployment of cloud-native core network and conduct a preliminary verification of the platform's potential to enable artificial intelligence in a real production environment, which will provide guidance to both academic and industry sectors. Finally, we conduct an analysis on the challenges and opportunities encountered by the cloud-native INCCOM network system.  
satellite-terrestrial network; cloud-native edge computing; integrated computing and communication; deep reinforcement learning; core network +
Footnote †: journal: Electronics Electronics  
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