esa-sceva/satcom-chunk-collection huggingface dataset:
# FEM-Based Compression Fracture Risk Assessment in Osteoporotic Lumbar Vertebra L1
## 3 Numerical Results and Discussion
### Estimation of the Fracture Risk  
The risk of fracture of the lumbar vertebra can be estimated by the Monte Carlo method as a probability \(Pr_{f}=Pr(Z\leq 0)\), where \(Z=Y_{p,R}-X_{p,E}\) and \(X_{p,E}\) and \(Y_{p,R}\) are external pressure \(p\) imposed on the vertebra and the load-bearing capacity of the vertebra random variables respectively. It is assumed that the load-bearing capacity of the vertebra \(p_{R}\) equals the minimum pressure \(p\) at which the maximum von Mises stresses equal the yield stress \(\sigma_{Y}\), that is, for the given \(\delta\) and \(\beta\), the load-bearing capacity r.v. \(p_{R}=min\{p:g_{FEM}(\delta,\beta,p)\geq\sigma_{Y}\}\). It is assumed that \(X_{p,E}\) and \(Y_{p,R}\) are independent random variables. To evaluate the fracture risk \(Pr_{f}\), the random numbers of the acting pressure random variable \(X_{p,E}\) can be generated directly, while the generation of the random numbers of the load-bearing capacity \(Y_{p,R}\) is more complicated since it is known that the cortical shell thickness and BV/TV are dependent random variables. In addition, the load-bearing capacity function of the lumbar vertebra \(p_{R}=h(\delta,\beta,\sigma_{Y},...)\) dependent of all variables must be known. Then, the r.v. of the load-bearing capacity \(Y_{p,R}\) can be obtained as a transformation \(Y_{p,R}=h(X_{\delta},X_{\beta},X_{\sigma,Y},...)\), where \(X_{\delta}\), \(X_{\beta}\), \(X_{\sigma,Y},...\) are random variables affecting the load-bearing capacity of the lumbar vertebra: for example, the cortical shell thickness, BV/TV ratio, the yield stress, geometry, and so on. It is evident that it is not possible to generate the sample of the realizations of the load-bearing capacity r.v. \(Y_{p,R}\) directly by calculating each random number by FEM. Therefore, in the present article, another approach is adopted: to approximate the maximum von Mises stresses of the vertebra by the polynomial \(\hat{g}\) and then, by solving this polynomial as an equation \(\sigma_{Y}=\hat{g}(\delta,\beta,p)\), to obtain the pressure \(p\) that corresponds to the given variables \(\delta\), \(\beta\), and the maximum von Mises stress \(\sigma_{Y}\).
# Accurate Energy Consumption Modeling of IEEE 802.15.4e TSCH Using Dual-Band OpenMote Hardware
## 4 Measurements
### Device State Current Consumption  
The consumption of the OpenMote-CC2538 connected to the OpenUSB was measured during all possible device states. Since the CPU and radio are the two components responsible for the majority of the current consumption, these device states are all combinations between CPU and radio modes. Instead of measuring the consumption of the CPU and radio separately, we measured the consumption of the entire device. The result is that any current consumption not related to the CPU or radio (e.g., SPI or timers) are measured as part of the CPU usage. This allows for a slightly more accurate prediction of the charge drawn compared to models that ignore these other components.
## 3 Hybrid Model Verification: Experimental Results and Discussion
Second, the model does not take into account a diffraction phenomenon (Figure 9c), which takes place when the real laser beam is propagating through the optical path (Figure 9d). In the experiment, as a result of diffraction, the focal spots on the Shack-Hartmann sensor in the central part of the beam are displaced from the centers of corresponding sub-apertures at high scatterer concentrations, which leads to additional defocusing. This effect was not observed in the model. For this reason, the experimental curve on Figure 8 increases faster than the model curve at high concentrations. Third, in addition to the centrally symmetric aberrations in the average wavefront, there were also other distortions (in particular, coma aberration) in the experiment (Figure 9f), which could not exist in the model (Figure 9e) in principle due to the symmetry of the nature of Mie scattering on spherical particles. This was due to the fact that the walls of the glass cuvette were not plane-parallel. We have also examined this problem in detail; the results can be found in [79]. We made the measurements and determined that the cuvette walls were not absolutely parallel. The deviation was not huge, but in conjugation with the impact of the scattering medium, it led to an overall tilt and, finally, coma aberration. Thus, an additional slope was introduced into the laser beam and, as a result, the coma aberration. It can be observed from Figure 8 that there is one more data point in the model curve (for a concentration of the order of \(10^{6}\) mm\({}^{-3}\)). This is due to the fact that when a laser beam propagates through a scattering medium with a particles' concentration of the order of \(10^{6}\) mm\({}^{-3}\), only fractions of a percent of the initial radiation energy level reach the sensor aperture. The traditional, most popular, and widespread CCD cameras have insufficient quantum efficiency and a limited exposure range to detect radiation of such a low power. Regarding the numerical simulation, we could use any concentration values, since with a statistically sufficient number of simulated photons, it is possible to obtain an image of focal  
Figure 9: Initial intensity distribution of the simulated (**a**) and real, experimental (**b**) laser beam; schematical representation of laser beam propagation without diffraction (**c**) and with diffraction (**d**); reconstructed interference pattern with symmetrical distortions only (**e**) obtained in the simulation and with both symmetrical and non-symmetrical distortions (**f**) obtained in the real experiment. spot field. We displayed this data point to show that the model curve does not move far away from the experimental curve even with an increase in the concentration of scatterers. Thus, the data obtained in the developed model and, subsequently, in a laboratory experiment showed that with an increase in the concentration of scattering particles in the range from \(10^{5}\) to \(10^{6}\) mm\({}^{-3}\), the amplitude of distortions of the average wavefront of radiation propagating through the layer of the scattering medium increases.
# Computing a Clique Tree with the Algorithm Maximal Label Search
## 2 Preliminaries
### Clique Minimal Separators and Atom Trees  
The atoms of a graph \(G\) are the subsets of \(V\) obtained by clique minimal separator decomposition. The reader is referred to [15; 18; 19] for full details on the decomposition by clique separators and by clique minimal separators. An atom of a connected graph \(G\) is a subset of \(V\) inducing a connected subgraph having no clique separator and being inclusion-maximal for this property. The atoms of a chordal graph are its maximal cliques. The atoms of a graph can be organized into an atom tree in the same way as the maximal cliques of a chordal graph are organized into a clique tree [20].  
Definition 2: [20] Let \(G=(V,E)\) be a connected graph. An atom tree of \(G\) is a tree \(T=(V_{T},E_{T})\) such that \(V_{T}\) is the set of atoms of \(G\) and for any vertex \(x\) of \(G\); the set of nodes of \(T\) containing \(x\) induces a subtree of \(T\).  
Definition 2: [20] Let \(G\) be a connected graph; let \(T\) be an atom tree of \(G\); and let \(S\) be a set of vertices of \(G\); then \(S\) is a clique minimal separator of \(G\) if and only if there is an edge \(A_{1}A_{2}\) of \(T\), such that \(S=A_{1}\cap A_{2}\).
###### Abstract  
To address the problem of harmonic pollution in power systems, a harmonic and interharmonic detection method based on the adaptive order and the dominant factor algorithms is proposed. The proposed method greatly improves the accuracy and precision of harmonic detection, overcoming the notorious problem of high sensitivity to noise of the traditional Prony algorithm that often leads to unsatisfactory detection results. In the proposed method, the \"adaptive order determination\" algorithm is first used to determine the optimal order of Singular Value Decomposition (SVD) denoising, resulting in a more accurate distinction between signal and noise components. Then, signal reconstruction is carried out to effectively remove noise components to enhance the denoising ability of SVD. This mitigates the Prony algorithm's high sensitivity to noise and greatly reduces the amplitude of false components in the fitting results. Finally, the dominant factor algorithm is applied to accurately screen out the non-false components in Prony's fitting results. Simulation results show that the proposed method can effectively reduce signal noise in different noise environments with noise intensities ranging from 5 dB to 30 dB, achieving an average signal-to-noise ratio improvement of around 20 dB. Meanwhile, the identification and screening results of harmonic and interharmonic components in the signal are accurate and reliable, with detection errors in amplitude, frequency, and phase at around 0.5%, 0.01%, and 0.5%, respectively. Overall, the proposed method is well suited for detecting harmonics and interharmonics in power systems under various noise environments.  
harmonic detection; Singular Value Decomposition (SVD); signal denoising; Prony algorithm +
Footnote †: journal: 2023, 13, 7558, [[https://doi.org/10.3390/app13137558](https://doi.org/10.3390/app13137558)]([https://doi.org/10.3390/app13137558](https://doi.org/10.3390/app13137558))
## 6 Conclusions  
To describe the mechanical behavior of rocks under high temperature more accurately, based on the Zienkiewicz-Pande yield criterion, a secondary development was carried out on the Flac\({}^{\text{3D}}\) 5.0 software by introducing the high-temperature-load coupled damage variable Dc. The research results are as follows:  
1. Based on the Zienkiewicz-Pande yield criterion, by introducing the damage variable \(D_{c}\) coupled with high-temperature and mechanical load, and according to the incremental numerical algorithm in Flac\({}^{\text{3D}}\), the detailed derivation of the augmented elastic-plastic constitutive model for high-temperature-load coupled damage was presented. The quantitative iterative equation and the calculation process were developed by virtue of Visual Studio C++ and compiled into the corresponding dynamic link library file, which was successfully applied in numerical simulation of rocks using Flac\({}^{\text{3D}}\) software.
2. By adjusting the shape function, the Z-P constitutive model degenerated into an M-C constitutive model. The simulation results of an ideal circular tunnel using Flac\({}^{\text{3D}}\) manifested that the calculation results of the degenerated Z-P constitutive model were similar to those of the M-C constitutive model built in Flac\({}^{\text{3D}}\). Compared to the computed outcomes of the model, the average relative error of the hoop stress was 0.485%, and the radial stress appeared an average relative error of 1.246%, which conformed to the accuracy requirements and verified the correctness of the secondary development program.
3. Through conducting uniaxial compression test simulations on granite at various high temperatures, the obtained stress-strain curves in the numerical simulation were compared with experimental data from the existing literature. The comparison revealed a similar trend between the numerical simulation and test results under different high temperatures. Additionally, the discrepancy between the peak stress and peak strain values was found to be within 6.5%. This outcome validated the rationality of the proposed high-temperature-load coupled damage model based on the Zienkiewicz-Pande yield criterion, and demonstrated its ability to accurately depict the mechanical behavior of rocks subjected to high-temperature treatment. Furthermore, it was recommended to choose the value range of \(\alpha\) for thermal damage parameters as (0.001, 0.01), and the value range of \(\beta\) as [0.1, 0.5].
## 4 Simulation Verification and Analysis
### Steady-State Operational Validation  
In order to verify the rationality of the simulation model, the simulation waveform of the system running in the steady-state condition was as follows. The reference value of the active power of the wind farm controller was reduced to 0.9 p.u. (\(P_{\textit{nf}}\) = 252 MW) at 5 s, and the reference value of active power was restored to 1.0 p.u. at 7 s.  
Figure 6 depicts the outcomes of the system's steady-state operation. The turbines' output power adjusted in response to variations in the active power reference value. The MMC-HVDC system ensured the stable transmission of the wind farm's input power. Notably, despite fluctuations in DC voltage accompanying changes in transmission power during operation, the DC voltage controller maintained it within the rated range.  
\begin{table}
\begin{tabular}{c c c c} \hline
**Component** & **Parameter** & **Symbol** & **Values** \\ \hline \multirow{3}{*}{Grid} & AC voltage & \(U_{\text{ac}}/\text{KV}\) & 230 \\  & Leakage reactance & \(L_{\text{ac}}/\text{H}\) & 0.2 \\  & Current limiting resistor & \(R/\Omega\) & 100 \\  & Number of SMs per arm & \(N_{\text{mmc}}\) & 50 \\ \multirow{3}{*}{MMC converter} & SM capacitor & \(C/\mu\text{F}\) & 3000 \\  & The rated voltage of SMs & \(U_{\text{c}}/\text{KV}\) & 8 \\  & Bridge arm reactor & \(L_{0}/\text{H}\) & 0.0076 \\ \multirow{3}{*}{Wind turbine (PMSG)} & Rated power & \(P_{\text{unit}}/\text{MW}\) & 2 \\  & Rated voltage & \(U_{\text{G}}/\text{KV}\) & 0.69 \\ \multirow{3}{*}{Wind farm} & Aggregated number & \(N_{\text{agg}}\) & 140 \\  & Total rated power & \(P_{\text{total}}/\text{MW}\) & 280 \\ \hline \end{tabular}
\end{table}
Table 1: MMC-HVDC-system-related parameter setting.  
Interaction Analysis and Protection Strategy Verification of Offshore Wind Farms Connected with the MMC-HVDC System Under Fault Conditions  
Once a short circuit fault occurs on the AC side of the GSMMC, the power transmission capability of the MMC-HVDC system will be greatly reduced. However, at the moment of failure, because the wind farm cannot immediately make a load reduction response, the wind farm will continue to inject power into the MMC-HVDC system. The continuous accumulation of unbalanced energy at the input and output terminals of the MMC-HVDC system will cause the DC voltage to rise rapidly to a safe limit (within tens of milliseconds to hundreds of milliseconds). To ensure the safety of power electronics, the system will trigger overvoltage protection and block the converter, which will have a great impact on the entire system. In severe cases, the DC overvoltage caused by unbalanced energy will lead to a large area of wind farms being off-grid. Based on the simulation model of an offshore wind farm connected with an MMC-HVDC system, interaction analyses of different short-circuit fault types on the AC side of the GSMMC are carried out in this section. In addition, a corresponding protection and control scheme is proposed so that the system can continue to operate safely and stably during the AC fault at the receiving end.
## 3 Materials and Methods
### Traditional YOLOv4 Architecture  
The following section describes the architecture of the traditional YOLOv4. YOLOv4, which [PERSON] and the other researchers introduced, integrates the most powerful optimization approaches in the CNN domain in recent years with the traditional YOLO series. It compromises detection speed and precision, which is noticeably better than YOLOv3. Three network components comprise the traditional YOLOv4 model: backbone, neck, and head. The \"backbone\" network component, which performs the role of a feature extractor, consists of an activation function, a standardization layer, and a convolutional layer. VGG16 [84], ResNet-50 [85], EfficientNet [86], CSPREsNeXt50 [87], and CSPDarknet53 [87] are currently more popular backbone detectors. We used CSPDarknet53 for our approach because it provided a greater frame rate than the others. It greatly expands the receptive field, isolates the most important context characteristics, and results in nearly no reduction in network operating speed [65]. CSPDarknet53 is composed of 29 convolutional layers, a 725 \(\times\) 725 receptive field, and 26.6 M parameters.  
The \"neck\" of the object detector is used to gather feature maps between the backbone and the head. After the CSPDarknet53, we add Spatial Pyramid Pooling or SPP [88] blocks to enhance the receptive field. It isolates the most critical context characteristics and has a negligible impact on network performance. The pooling cores have a diameter of 5 \(\times\) 5, 9 \(\times\) 9, and 13 \(\times\) 13, respectively. We use Path Aggregation Networks or PANet [89] to aggregate parameters from various backbone levels for various detector levels. In the initial version of PANet, the current layer's information is combined with that of a previous layer to create a new vector. In YoloV4 implementation, the input vector and the vector from the preceding layer are combined to form a new vector.  
The \"head\" of a single-stage object detector is utilized for prediction. According to the output data, the bounding box and its confidence for the identified category can be established. Using anchor boxes, it generates output vectors with class probabilities, objectness scores, and bounding boxes. It runs seven anchors since it is a single-stage detector without an area proposal module. A single-stage object detector is quicker but has inferior performance compared to a two-stage detector.  
Figure 4: Visualization of the Distribution for Dataset.
## 6 Conclusions  
In this paper, we have reported on the comparative characterization between two leading classes of multimode planar optical waveguide, namely graded index polymer waveguides produced using the Mosquito and Photo-addressing methods, and planar graded index glass waveguides produced using an ion diffusion method. The insertion loss measurements at the key communications wavelengths of 850 nm and 1310 nm showed a consistent reciprocal relationship between the two waveguide material types with respect to wavelength, with polymer waveguides showing lower insertion loss at 850 nm than at 1310 nm, and glass waveguides showing lower insertion loss at 1310 nm than at 850 nm. Signal integrity and bit error rate measurements on both waveguide classes indicated low added signal distortion at their respective optimal wavelengths and a bit error rate of less than \(10^{-12}\). The waveguides were incorporated into an optically enabled data center platform and system level characterization was carried out showing negligible performance disruption from any of the waveguides at 850 nm. The fact that the state-of-the-art in embedded graded index waveguides of both classes has been validated in the prototype platform paves the way for widespread deployment of both emerging classes of embedded graded index waveguide in future optically enabled data center systems.  
The research reported herein was carried out as part of the EU H2020 project \"COSMICC\" (grant agreement No. 688516) and EU FP7 project \"PhoXTrot\" (grant agreement No. 318240), for which it has received funding from the European Union.  
[PERSON], [PERSON], [PERSON] and [PERSON] conceived and designed the experiments. [PERSON], [PERSON] and [PERSON] performed the experiments and analysed the data. [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] wrote the paper.  
The authors declare no conflict of interest.  
Figure 19: Optically enabled data storage system performance in terms of error-free data transfers per data block size with different waveguides connected to the system. (**a**) reference measurement with fiber only system, (**b**) Keio mosquito waveguide channel 5 operating at 850 nm, (**c**) Sumitomo Bakelite waveguide channel 1 operating at 850 nm, (**d**) IZM glass waveguide set 7 channel 12 at 850 nm.
## 3 Failure Mechanism and Common Improvement Solutions  
### The Drilling Parameter Matching of the DTH Hammer Bit  
As above mentioned, the DTH hammer bit mainly relies on the impact action to break the rock. The button of the percussive bit has strong impact resistance, but the shear resistance is relatively weak. Therefore, the drilling parameters of the DTH hammer bit, such as the hole diameter, the rotation speed, the percussive frequency, and the bit buttons, are required to match well.  
The drilling parameter matching for the DTH hammer bit has been studied deeply. In the early stage, based on the practice of down-the-hole hammer drilling, for the small diameter drilling with a diameter less than 150 mm, the American Water Well Association Camber proposed that the drilling tool rotation of 11 degrees per impact was the \"optimal angle\", and the arc length of the edge buttons travel \(\Delta\)S between the adjacent two impacts was 14.4 mm, as shown in Figure 4. In order to meet the needs of the ever-expanding drilling diameter, some scholars [28] proposed the concept of \"reasonable impact interval or moving arc length \(\Delta\)S\" based on the relationship of an \"optimal angle\". In addition to impact frequency, the influence of the ball buttons diameter and bit diameter on bit rotation speed are also considered. For example, impact bits with a ball buttons diameter of 14-15 mm are used. The bit is struck 32 times per revolution. If the impact frequency is 25 Hz, the bit rotation speed must not exceed 48 rpm. However, for drilling in large-diameter hard rock formations, the rotation speed is lower and the diameter of the PDC ball buttons is small. The actual rotation speed of the spindle (bit) is difficult to match with the frequency of the DTH hammer and the diameter of the ball buttons, especially for the traditional rotary table drill drilling in large-diameter hard rock holes.  
Figure 4: The arc distance under different rotation speed and the diameter of edge buttons.
# Integrated Microwave Photonics for Wideband Signal Processing
## 7 Conclusions  
Photonic signal processing offers the advantages of high bandwidth capabilities to overcome inherent electronic limitations and finds uses not only for radar and defense applications, but also recently in communications and sensing systems. The field of integrated microwave photonics, which is a booming technology driven by the rapid demand for compact, lightweight, and low power consumption devices, has now become one of the most active areas of research. Thanks to the significant research interest in this area, we have witnessed an impressive leap in knowledge and technology developed in the last decade alone, evidenced by the overwhelming volume of papers being published in this area. Recent developments in integrated MWP for wideband signal processing have been presented at both the device and subsystem level, which include phase shifters, true time delay lines, and frequency tunable microwave filters as MWP building blocks, monolithic integration for broadband wireless, and cascaded MWP functions for photonic links. The many varieties of integration platforms and the ongoing investigation of new materials provides an optimistic outlook for the future of microwave photonics to eventually find an optimal solution in integrated photonics, be it a hybrid or a single monolithic approach.  
The authors would like to thank the funding support from Australian Department of Defence and Australian Research Council.  
This review article was jointly written by and proof-read by all authors, where [PERSON] and [PERSON] contributed the premier part of the paper. All authors contributed in various degrees to the research concept, theory and the experimental study. [PERSON] was the chief investigator for this project. [PERSON] and [PERSON] performed a great part of the analysis and experimental study. [PERSON], [PERSON], [PERSON] and [PERSON] worked on the design and structures. [PERSON], [PERSON] and [PERSON] contributed to the research concept. All authors participated in revising the article critically for important intellectual content.  
The authors declare no conflict of interest.