esa-sceva/satcom-chunk-collection huggingface dataset:
# Visual-Inertial Navigation System Based on Virtual Inertial Sensors
## 3 Virtual Inertial Navigation System Based on Deep Learning
### Zero-Velocity Update-Based Optimization of Virtual Inertial Sensor Data  
This paper improves the accuracy of the pose estimation system of the virtual inertial sensor by incorporating the ZUPT method to reduce the cumulative errors in the inertial navigation estimation process.  
To reduce the cumulative errors in the inertial navigation estimation process, the interval zero-velocity search algorithm is used for the error update. This algorithm uses the acceleration data to detect the motion state of the robot when it is still and segments the searching units by filtering the angular velocity. The angular velocity is smoothed by the  
Figure 4: DenseNet-GRU hybrid model structure diagram.  
Figure 3: DeepConvGRU neural network model structure diagram.  
Figure 2: Flowchart of constructing virtual inertial sensors.  
sliding window average method. When the system detects zero velocity during movement, the Kalman filter is triggered to estimate and correct the output error of the system, and the rotation matrix is updated accordingly to eliminate the cumulative errors [18].  
Because the distribution of zero-velocity intervals varies in different motion modes of the quadruped robot, it can affect the accuracy of the ZUPT. The system reduces the misjudgment rate of the zero-velocity interval by adding gait classification constraints and adjusts the filtering parameters according to the motion mode to improve the accuracy of the ZUPT, as shown in Figure 5.
## 4 Analysis and Verification
### Map Building Experiment  
The building diagram is shown in Figure 7. By adding cartons as obstacles, the basic experiment environment in the laboratory was built, as is shown in Figure 7a. The height of obstacle A was lower than the installation height of the vehicle-mounted LiDAR. In practical applications, since the information obtained by the two-dimensional LiDAR is affected by the installation location, the depth camera will be affected by the ambient light, and thus there will be obstacles that are missed and the environmental information will be missing, resulting in low accuracy of the constructed environmental map information. Therefore, a map construction experiment was carried out in a simulated environment to verify the reliability of the method proposed in this paper. Figure 7b maps the environment using only LiDAR. It can be seen from the figure that due to the influence of the installation position of the LiDAR, the obstacle A cannot be detected, and therefore the ground information obtained by scanning was incomplete, resulting in low mapping accuracy. Figure 7c maps the environment using only the depth camera. Figure 7d maps the environment after data fusion. When a depth camera is used for map construction, more environmental  
Figure 6: (**a**) ROS intelligent vehicle platform; (**b**) system framework diagram.  
information can be obtained than LiDAR. However, the detection accuracy of the depth camera is easily affected by ambient light, resulting in poor target detection accuracy and blurred map construction.  
Through the method in this paper, the detection data of the depth camera and the LiDAR were fused to construct a map; the map after data fusion is shown in Figure 7d. Through the comparison, it can be found that after the fusion of the data of the two sensors, the limitation of the environment detection by a single sensor was able to be effectively compensated for. The interference of the complex environment can be overcome through the complementarity between the sensors, so that the constructed map information is more complete and accurate, and the environment map is closer to the real environment.
## 5 Discussion
### Limitations of Our Method  
Although our method achieved the best synthetic image performance, especially when synthesizing normal liver images, it still has some limitations. For example, our model is sensitive to the prediction and reconstruction of certain liver images with large lesions, such as advanced cancer and large occupying lesions. Because our method uses liver vessels to synthesize liver images, these images with particularly large lesion areas often have a large number of structures in the vessels that may have been lesioned, and the synthesis results were relatively poor compared to normal images. Meanwhile, the number of these samples was also very small, which limits the model's performance. For liver samples with only minor lesions, our model was insensitive and performed better, because the vascular structures corresponding to such diseases are often not clearly distinguishable from normal liver images.  
In addition, manually labelled vascular labels were still visually disconnected after 3D reconstruction, indicating that it was still difficult to obtain accurate vascular structure labels. This shows that clear vascular structural information is indispensable to synthesize 3D liver images. To enable the proposed method to be extended to clinical applications, we need to collect imaging data from different patients in the future. Furthermore, we plan to build a database of liver vascular images. In addition to this, we need to explore whether other anatomical structures can be generated in the liver.
## 3 Results and Discussion
### Ultrasonic Fields
To detect a more accurate thickness, a temperature-dependent method was applied, in which the ultrasonic wave velocity is not a constant and calculated by:  
\[\mathbf{v}=\sqrt{G/\rho} \tag{11}\]  
Here, \(G\) is shear modulus and \(\rho\) is density, and they both vary with temperature. Wave velocity was calculated by Equation (11), and it was used in the ultrasonic testing device to obtain the thickness at different temperatures. As shown in Figure 13, thickness predicted with the temperature-dependent wave velocity is close to the theoretical data. It indicates that the temperature-dependent method can achieve high precision detection at high temperatures. The above research shows that the heat transfer model is useful to optimize the waveguide structure, and the designed ultrasonic-guided wave testing device is able to accurately measure the thickness of metals at high temperatures. Compared with the measurement at normal temperature, ultrasonic wave velocity varies with temperature so that the common measuring method with a constant wave velocity will cause a big error at high temperatures. The proposed temperature-dependent method, which considers the correlation of wave velocity and temperature, is necessary to achieve high precision detection at high temperatures. The research demonstrates its value in the thickness detection of high temperature objects. Figure 11: Self-developed ultrasonic-guided wave testing device. Figure 12: Received wave signals and envelope curves.
## 4 Discussion
In this case, however, the use of a single connector is pointless because it does not create a stable mechanical construct in the form of a complete frame structure, as is the case with the use of two connectors. Considering the huge forces counteracting the correction of the spine during its fixation with the use of implants (caused by, among other factors, the tension of the muscular system), the use of a frame structure can have a significant impact on maintaining the effects of correction until the spinal column is fully fused. On the other hand, the use of transverse connectors in the fixation of spinal fractures is not fully justified. Based on the conducted research using digital image correlation and numerical simulation, it was noted that total displacements obtained on the rods are comparable between two configurations--without transverse connectors and with two connectors. This result indicates that while the use of one connector may, in justified cases, affect the fixation effect, the use of two connectors is not justified and may only contribute to the prolongation of the surgical procedure. The observed values of strain on the rod surfaces are higher when using transverse connectors (LSF4 TC1 and LSF4 TC2) than in four-segment fixation without connectors (LSF4). Such changes in the strain state are justified due to the appearance of additional rigid attachment points changing the load transfer system. It was also shown that the distribution of stresses and strains reduced according to the Huber-von Mises hypothesis and obtained on the rods for both configurations (LSF4 and LSF4 TC2) are practically the same, which again indicates that there is no justification for the use of transverse connectors, especially in the frame structure (two connectors). In addition, the obtained maximum stress values are within the strength limits of the rod material [42]. Based on the conducted research, preliminary conclusions can be drawn that the use of transverse connectors is not necessary in a PFS design in the case of surgical treatment of a vertebral compression fracture. The rods are joined with transverse elements towards the end of a several-hour-long, complicated open surgery, which further prolongs the operation time. The elimination of transverse elements may contribute to a shorter procedure time or a less invasive and percutaneous procedure (minimally invasive surgery). In addition, the insertion of transverse connectors is often associated with damage to the spinous processes and interspinous ligaments, depending on the place where they must be inserted. Due to the fact that the posterior spinal column plays an important role during the transmission of loads, damage to articular processes and ligaments may contribute to increased mobility of the segments, as confirmed by the conducted research. Based on the clinical and numerical studies performed, other authors also point out that the use of minimally invasive surgery offers major advantages, including reduced damage to muscle and nerve tissues, decreased intraoperative bleeding, and faster patient convalescence after surgery [39,43].
# Comparative Analysis of Target Displacements in RC Buildings for 2023 Turkiye Earthquakes
## 1 Introduction
In this manner, it will be clearly shown whether the earthquake hazard is properly represented for these provinces using the last two earthquake hazard maps in the country. At the same time, an attempt was made to accurately determine the magnitude of the earthquakes. Another key objective of the study is to examine the effect of predicted and measured PGAs on target displacement values. Target displacements are a fundamental factor determining the earthquake reliability and resistance of structures in earthquake performance analyses used to determine the effects of seismic events on structures. Whether or not structures provide their predicted earthquake performance depends on the accurate calculation of displacement limits. Therefore, target displacement analyses in earthquake engineering are essential for assessing structural performance. Target displacements, which are used to determine the level of damage to structures, are essential in assessing the seismic performance of structures. Earthquake performance analysis usually requires a displacement-based assessment. Most earthquake codes require structures to keep target displacements within certain limits. In this approach, the displacements of structures are directly considered as safety and performance criteria. Exceeding these limits indicates that the expected performance levels of the structure will not be achieved. Therefore, it is necessary to accurately determine the displacement targets of structures to ensure the correct seismic performance. In this context, this study reveals whether the target displacements are sufficient for eleven different provinces in the earthquake region. The key factor that sets this study apart from others is that it is the first detailed study conducted on eleven different provinces in the earthquake region. It is believed that this comprehensive study, which covers both earthquake hazards and target displacements, will serve as a valuable resource for the development of seismic design codes and earthquake hazard maps. By presenting the earthquake hazard in a realistic and sufficient manner, the target displacements used to assess the seismic performance of structures will be determined with much greater accuracy. As a result, this study will be one of the first studies to comparatively examine earthquake hazard and structural analyses for the entire region affected by the 2023 Kahramanmaras earthquakes. It will reveal the need to update seismic hazard analyses, especially for settlements where earthquake hazard is not adequately represented. At the same time, recommendations were made considering the causes of damage in RC structures.
## 2 Materials and Methods
### Computation of the Observed Signals  
Estimation of the sound speed distribution from the observed signals is an inverse problem. Hence, it is necessary to obtain observed signals corresponding to the sound speed distribution produced in the previous section for the dataset. The observed signals are obtained by solving the forward problem of scattering of sound waves. This section describes how to discretise the Helmholtz equation and solve the forward problem. The scattering of sound waves in a sound speed inhomogeneous medium is represented by the Helmholtz equation as follows.  
\[\left(\
abla^{2}+\frac{\omega^{2}}{c^{2}}\right)p=-s, \tag{2}\]  
where \(c\) is the sound speed, \(p\) is the pressure field, \(s\) is the wave source, and \(\omega\) is the angular frequency. Let \(N_{\mathrm{x}}\) and \(N_{\mathrm{y}}\) be the number of grids in the x and y directions in the two-dimensional space, the discretized Helmholtz equation can then be expressed by the following equation.  
\[AP=-S, \tag{3}\]  
where \(A\) is the (\(N_{\mathrm{x}}N_{\mathrm{y}}\times N_{\mathrm{x}}N_{\mathrm{y}}\)) matrix of discretized coefficients in parentheses on the left side of Equation (3) that considers the absorbing boundary conditions, \(P\) is a discretized pressure field vector with (\(N_{\mathrm{x}}N_{\mathrm{y}}\times 1\)) components, and \(S\) is a (\(N_{\mathrm{x}}N_{\mathrm{y}}\times 1\)) matrix representing a wave source. An example row of \(A\) is shown in the following expressions: Formulas (4) and (5). Note that in this example, for simplicity, the second-order difference in the spatial direction is implemented with second-order precision.  
Let \(\ell=i+jN_{\mathrm{x}}\), the formula for \(\ell\)-th row of \(A\) on Equation (3) is expressed as follows.  
\[\sum_{m=1}^{N_{\mathrm{x}}N_{\mathrm{y}}}A_{\ell,m}P_{m}=-S_{\ell}. \tag{4}\]  
\(A_{\ell,m}\) is expressed as follows.  
\[A_{\ell,m}=\left\{\begin{aligned} &\frac{1}{\Delta x^{2}},& \text{for }m=(i-1)+jN_{\mathrm{x}},\;(i+1)+jN_{\mathrm{x}},\;i+(j-1)N_{ \mathrm{x}},\;i+(j+1)N_{\mathrm{x}}\\ &\left(\frac{-4}{\Delta x^{2}}+\frac{\omega^{2}}{c(ij)^{2}} \right),&\text{for }m=i+jN_{\mathrm{x}}\\ & 0,&\text{otherwise}\end{aligned}\right\}, \tag{5}\]  
where \(\ell=i+jN_{\mathrm{x}}\) and \(c(i,j)\) is the sound speed at the point \((i,j)\). In this study, the terms corresponding to the second-order partial derivatives in the spatial direction of \(A\) were implemented using fourth-order central difference discretization, and the absorbing boundary conditions were implemented using perfectly matched layers. The pressure field \(P\) was obtained by LU-decomposition of \(A\) and inverting it for the system of equations.
## 3 Results and Discussion
### BLUF Modules in Association with the Effector Domains
#### 3.3.5 B\({}_{12}\) Binding Domain
The selected protein sequence (ABP71929.1) containing the B\({}_{12}\) domain was analyzed for a protein-protein interaction using String (version 11).The observation showed several interacting partners involved in the regulation of different signaling pathways (Figure S7d). The protein-protein interaction analysis revealed the interaction of the B\({}_{12}\) domain with the prephenate dehydatase enzyme (Rsph17025_0524; Figure S7d), which catalyzes the conversion of prephenate to phosphoenolpyruvate (PEP), water, carbon dioxide [101], and is generally involved in phenylalanine, tyrosine and tryptophan biosynthesis [102; 103]. The selected protein also interacted with tyrosl-tRNA synthetase (TyrS), an enzyme that catalyzes the attachment of tyrosine to tRNA in a two-step reaction. The interaction of the B\({}_{12}\) domain-containing protein with a transmembrane protein PA-phosphatase-like phosphodieserase (Rsph17025_2732), a SARP family transcriptional regulator and a DNA mismatch repair protein, MutL, was also revealed through the protein-protein interaction analysis (Figure S7d). The BLUF-B\({}_{12}\) binding domain containing protein also interacted with the TonB protein, which communicates with outer membrane receptor proteins and drives the energy-dependent uptake of various substrates (such as iron citrate, enterochelin, aerobactin, etc.) into the periplasmic space [104].
# Comparison of Disturbance Compensators for a Discrete-Time System with Parameter Uncertainty
## 2 Closed-Loop Stability Analysis
### Traditional Stability Analysis  
Found in most previous works, like [6; 7; 8; 9; 10; 11; 12; 13; 14; 15], a lumped disturbance is introduced to denote the combined effect of the parameter uncertainty and external disturbance. Hence, the system model Equation (1) can be rewritten as Equation (2):  
\[x(k+1)=\Phi x(k)+\Gamma u(k)+f(k) \tag{2}\]  
where \(f(k)=\Delta\Phi x(k)+d(k)\) is the lumped disturbance.  
Using the help of state transformation \(z(k)=\mathrm{Tx}(k)\), where \(\mathrm{T}\in R^{n}\), a controllable canonical form of Equation (2), is expressed as Equation (3):  
\[z(k+1)=\overline{\Phi}z(k)+\overline{\Gamma}u(k)+\overline{f}(k) \tag{3}\]where  
\[\overline{\Phi}=T\Phi T^{-1}=\left[\begin{array}{ccccc}0&1&0&\cdots&0\\ 0&0&1&\cdots&0\\ \vdots&\vdots&\vdots&\ddots&\vdots\\ 0&0&0&\cdots&1\\ -a_{1}&-a_{2}&-a_{3}&\cdots&-a_{n}\end{array}\right]\ \overline{\Gamma}=T\Gamma=\left[ \begin{array}{c}0\\ 0\\ \vdots\\ 0\\ 1\end{array}\right] \tag{4}\]  
with \(a_{i}\) (\(i=1,\,2,\,\ldots,\,n\)) is the model coefficient, and \(\overline{f}(k)\ =Tf(k)\).  
Adopting the commonly used discrete-time sliding mode control (DSMC) reaching law [16], the control law \(u(k)\) can be represented as Equation (5):  
\[u(k)=-\big{(}\overline{CT}\big{)}^{-1}\big{[}\overline{C\Phi}z(k)-(1-q)s(k)+ \xi\text{sign}(s(k))\big{]} \tag{5}\]  
where \(q\) and \(\xi\) are the control parameters. \(s(k)\ =\ \overline{C}z(k)\ =\ Cx(k)\) is the switching function. \(\overline{C}=[c_{1},\,c_{2},\,\ldots,\,1]\) is the gain vector of the switching function. Substituting Equation (5) into Equation (3) yields Equation (6):  
\[z(k+1)=\bigg{[}\overline{\Phi}-\overline{\Gamma}\big{(}\overline{CT}\big{)}^{ -1}\big{(}\overline{C\Phi}-(1-q)\overline{C}\big{)}\bigg{]}z(k)+\overline{f}(k) \tag{6}\]  
where \(\overline{f}(k)=\overline{f}(k)-\overline{\Gamma}\big{(}\overline{CT}\big{)} ^{-1}\xi\text{sign}(s(k))\). The characteristic equation of the closed-loop system Equation (6) is Equation (7):  
\[\lambda^{n}+(c_{n-1}-(1-q))\lambda^{n-1}+\ldots+(c_{1}-(1-q)c_{2})\lambda-(1-q )c_{1}=0 \tag{7}\]
## 3 Results and Discussion
### Volatiles Analysis
#### 3.4.2 Changes in Volatiles of HHP-Treated Kiwifruit Pulp Beverage during 40-Day Storage
Heat treatment (85 °C for 10 min) (**\(\blacksquare\)**), HHP (high hydrostatic pressure, 400-600 MPa for 5-15 min): 400 MPa/5 min (**\(\blacktriangledown\)**), 400 MPa/10 min (**\(\blacktriangle\)**), 400 MPa/15 min (**\(\blacktriangle\)**), 500 MPa/5 min (**\(\blacklozenge\)**), 500 MPa/10 min (**\(\blacklozenge\)**), 500 MPa/15 min (**\(\blacklozenge\)**), 600 MPa/5 min (**\(\blacklozenge\)**), 600 MPa/10 min (**\(\bullet\)**), 600 MPa/15 min (**\(\square\)**). All data were expressed as means \(\pm\) SD, \(n=3\). steadily and remained stable over 20 days, which revealed that HHP at 500 MPa for 10 min was more conducive to the retention of alcohols and ketones than HT. During storage, heat-treated samples showed lower total content of esters and acids than HHP-treated samples. Additionally, the total content of acids in samples processed by 400 MPa for 15 min was higher than those of HT and other HHP treatments at the initial time and on the 40 th day. Obviously, HHP showed a greater retention of esters and acids than heat treatment. Analysis of volatiles in kiwifruit pulp beverage during 40-day storage clearly showed that HHP at 400-500 MPa showed better aroma retention effect when compared with HT. It is generally known that aldehydes such as hexanal and _(E)_-2-hexenal, which are volatiles associated with the odor of grass, leaf and fruit, contribute a lot to the aroma of kiwifruit. By contrast, the content of hexanal and _(E)_-2-hexenal as well as the total aldehydes content in HHP-treated samples (500 MPa/15 min) remained stable at a high value over 40 days, indicating that this treatment is conducive to the retention of important characteristic volatiles in kiwifruit pulp beverage. Furthermore, HHP treatment caused more intense fruity and grassy notes of the kiwifruit pulp beverage.
# Visible Light Communication System Technology Review: Devices, Architectures, and Applications
## 7 Challenges
### Point-to-Point Communication Based on a Single Transmitter and Detector  
Multiple light sources are needed to accomplish uniform lighting and elevate the data rate in a mesh multiple-point network. Nevertheless, spatial multiplexing (SMP) is the most commonly used MIMO scheme that is restricted by channel correlation, causing difficulties for receivers to distinguish a single data stream. In 2020, a novel odd-order 32-QAM constellation scheme for 2 \(\times\) 2 MIMO VLC systems by superposing two independent signals modulated with 4-QAM and 8-QAM was illustrated by [PERSON] et al. as a promising candidate for mitigating the channel correlation of SMP MIMO VLC system [138].