esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Distribution of the Optical Properties
[20]), the linear dependence of \(n\) and \(k\) on the position proves that they also linearly depend on the composition (\(n_{Si_{1-x}Ge_{x}}(x)=(1-x)\times n_{Si}+x\times n_{Ge}\) and \(k_{Si_{1-x}Ge_{x}}(x)=(1-x)\times k_{Si}+x\times k_{Ge}\), where \(n_{Si}=4.33\), \(n_{Ge}=5.33\), \(k_{Si}=0.46\), \(k_{Ge}=1.10\) for the wavelength of 849.7 nm). Both \(n\) and \(k\) span a wide range depending on the composition, indicating  
Figure 4: Spectra of the refractive index (\(n\), color map on the middle graph) and the extinction coefficient (\(k\), color map of the bottom graph) as a function of position along the center line of the wafer, calculated using the Tauc–Lorentz (TL) parameterization, as described in the text. The \(n\) and \(k\) spectra fitted by the TL model individually can be identified along the vertical axis of the bottom and middle maps, the values of which are color coded at the right hand side of the graphs. The composition of a-Si\({}_{1-x}\)Ge\({}_{x}\) changes from \(x=0\) to \(x=1\) over the lateral positions from \(-1\) to \(1\), as shown in the horizontal axis at the top. The zero position corresponds to the composition of \(x=0.5\). The top graph shows \(n\) and \(k\) at the wavelength of 849.7 nm. that these properties can well be controlled by properly adjusting \(x\) in the a-Si\({}_{1-x}\)Ge\({}_{x}\) composition. It is also important to emphasize that this behavior holds for a broad range of wavelengths. Note that the refractive index can also be modified by hydrogenation, which will be the target of our next study. In this work, we deal with non-hydrogenated amorphous Si and Ge (see also Ref. [26]).
## 5 Experiments
### Ablation Study
#### 5.3.1 Ablation of Descriptor Encoder  
In this experiment, we compare four different combinations of descriptor encoders. The first option is the PointNet [60] encoder, working on separate points sampled by the nearest neighbor search. The second design takes the output of descriptor decoder and performs max pooling to extract global features. We then use an MLP to embed this information into a global descriptor as the input of GAT. We refer to this descriptor as Global Desc. The third design is the one proposed by [PERSON] et al. [4] named MDGAT. This design is inspired by the USIP detector [42] and FPFH descriptor [24] to enrich the feature representation before being fed into the GAT.  
We train different networks with the above encoders. The results in Table 4 demonstrate that our descriptor with most generalized structure can achieve the best performance. The result is that the density-invariant feature descriptor inspired by DJFeat allows the network to cope with the inherent density of point cloud variations. Furthermore, the dynamic GAT with two types of attention enhances the performance of a powerful and flexible matching mechanism. For Global Desc., we can see that concatenating global information too early in the descriptor encoding process does not improve the matching efficiency but  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Matcher** & **Failure Rate** & **Inlier Ratio** \\ \hline FPFH + RANSAC & 8.37 & 18.77 \\ SHOT + RANSAC & 5.40 & 18.21 \\ USIP + RANSAC & 1.41 & 32.20 \\ MDGAT Desc. + SuperGlue & 0.58 & 36.19 \\ MDGAT (Desc. + matcher) & 1.33 & **37.54** \\
**DFGAT** & **0.117** & 34.93 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Registration performance.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Method** & **RTE (cm)** & **Standard Deviation (cm)** & **RRE (\({}^{\circ}\))** & **Standard Deviation (\({}^{\circ}\))** & **Success (\%)** \\ \hline
3 DFeat-Net & 25.9 & 26.2 & 0.57 & 0.46 & 95.97 \\ FCGF & 9.52 & 1.30 & 0.30 & 0.28 & 96.57 \\ DJFeat & **6.90** & **0.30** & **0.24** & **0.06** & 99.81 \\ SpinNet & 9.88 & 0.50 & 0.47 & 0.09 & 99.10 \\ MDGAT-matcher & 16.00 & 64.9 & 0.608 & 3.56 & 98.67 \\
**DFGAT** & 9.70 & 21.0 & **0.24** & 1.22 & **99.88** \\ \hline \hline \end{tabular}
\end{table}
Table 3: Registration results on KITTI.  
even reduces the discriminant ability. The same effect applies to PointNet, which extracts the overall interface using maximum aggregation and loses local information.
## 4 Test Results and Analysis
### Energy Dissipation Capacity  
The equivalent damping ratios--those are, \(h_{\mathrm{e}}=S_{\mathrm{(ABC+CDA)}}/(2\pi S_{\mathrm{(OBE+ODF)}})\), in which \(S_{\mathrm{(ABC+CDA)}}\) is the area of the hysteresis loop of DABCD, and \(S_{\mathrm{(OBE+ODF)}}\) is the total area of the triangles of OBE and ODF--for evaluating the energy dissipation capacity calculated from the load--displacement hysteretic loops are shown in Figure 12. The purpose was to reflect the better energy dissipation capacity of the frame proposed in this paper compared with that of the RC frame proposed by [PERSON] et al. [22]. Figure 13 gives the equivalent damping ratios versus the maximum lateral displacement corresponding to the test frame and the contrasting RC frame. It can be found that the value of \(h_{\mathrm{e}}\) increases with the increase in lateral displacement, which indicates that more energy is consumed. The reason is that the plastic hinge appears at the beam end and column end and develops continuously, which increases the energy dissipation capacity of the frame. When the lateral displacement is at the same level, the energy dissipation capacity of the RACFCST frame is better than that of RC frame. With the increase in displacement level, the gap in energy dissipation capacity between the two types of frame increases, which is mainly related to the good plastic deformation performance of the RACFCST columns in the later stage of the test. At the end of the test, the \(h_{\mathrm{e}}\) of the RC frame and RACFCST frame is 0.156 and  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{
\begin{tabular}{c} **Specimen** \\ **Name** \\ \end{tabular} } & \multirow{2}{*}{**Loading**} & \multicolumn{2}{c}{**Yield Point**} & \multicolumn{2}{c}{**Ultimate Point**} & \multicolumn{2}{c}{**Failure Point**} \\ \cline{3-8}  & & & \(\theta_{y}\) & \((\theta_{y})_{\mathrm{average}}\) & \(\theta_{u}\) & \((\theta_{u})_{\mathrm{average}}\) & \(\theta_{I}\) & \((\theta_{I})_{\mathrm{average}}\) \\ \hline RACFCST & + & 1/86 & 1/91 & 1/47 & 1/47 & 1/33 & 1/33 \\ frame & - & 1/96 & 1/47 & 1/47 & — & 1/33 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Measured displacement angle at characteristic points.  
Figure 11: Characteristic points on the load–displacement curve.  
0.276, respectively, which shows that the energy dissipation capacity of the RACFCST frame is much better than that of the RC frame.
# Variability of Water Use Efficiency Associated with Climate Change in the Extreme West of Bahia
## 3 Results  
### Spatial Distribution of GPP, ET and WUE  
In terms of the spatial mean distributions of GPP, ET, and WUE in 19 years (Figure 2), the maximum values are 580 gC/m\({}^{2}\), 3000 mm, and 3.5 gC/mm\(\cdot\)m\({}^{2}\), respectively. Gross primary productivity values were mostly between 340 and 580 gC/m\({}^{2}\) (Figure 2a), with the lowest values in the western part, on the border of the state of Bahia with the Tocantins (TO) (to the northwest-NW of the westernmost region of Bahia) and Goias (GO) (to the southwest-SW of the westernmost region of Bahia). The mean ET values had a spatial distribution similar to that of GPP (Figure 2b), with the lowest values (\(\leq\)1350 mm) in the western portion and a range of 1600 to 2100 mm.  
The highest GPP (\(\cong\) 580 gC/m\({}^{2}\)) and ET (\(\cong\) 3000 mm) values were found in the central portion of the westernmost region of Bahia, towards the north. These areas have natural vegetation, which may have promoted the highest ET and GPP. Refs. [52; 53] found that areas of dense vegetation and evergreen broadleaf forests had the highest annual total GPP.  
Figure 2c shows the distribution of mean WUE values. There was an exception, an area of exposed soil in the SW portion with zero values highlighted in red. Values between 2.0 and 2.5 gC/mm\(\cdot\)m\({}^{2}\) were predominant. The highest values, between 3.0 and 3.5 gC/mm\(\cdot\)m\({}^{2}\), were observed in the western (W) and SW portions of the Santa Maria da Vitoria microregion.
# Optimal Route Planning for Truck-Drone Delivery Using Variable Neighborhood Tabu Search Algorithm
## 4 Model Solution
### Initial Solution  
The generation of the initial solution mainly includes the following three stages:  
1. Generation of pure-truck delivery route The generation of pure-truck delivery routes uses the nearest neighbor algorithm, and the steps are as follows:  
Step 1. Create an empty route \(R_{n}\) for each truck, \(R_{n}=\varnothing\), \(\forall n\in N\).  
Step 2. Assume that the last customer point on route \(R_{n}\) is \(g\), select a customer point closest to \(g\) from all unassigned customer points and insert it into route \(R_{n}\).  
Step 3. Check whether there are unassigned customer points or not. If yes, go to step 2; otherwise, terminate the algorithm and output the final delivery route \(\{R_{n}\}\).  
(2) Generation of drone delivery route  
For any two customer points \(i\) and \(j\) on route \(R_{n}\), if customer point \(k\) satisfies: \(t_{\mathrm{L}}+t_{\mathrm{R}}+t_{ik}^{\mathrm{D}}+t_{kj}^{\mathrm{D}}+s^{ \mathrm{D}}\leq e,\ i\to k\to j\) is a feasible drone delivery route \(R_{n}^{\prime}\), and customer point \(k\) is visited by the drone.  
(3) Route update  
It is assumed that \(i\to k\to j\) is a pure-truck delivery route. If customer point \(k\) can be visited by the drone, \(k\) is removed from the route, i.e., the truck delivery route \(R_{n}\) is updated as \(i\to j\) and the drone delivery route is \(R_{n}^{\prime}\): \(i\to k\to j\). The route update process is shown in Figure 2.
# Adaptive TCP Transmission Adjustment for UAV Network Infrastructure
## 3 Asran
### How to Distinguish Transient Link Instability from Buffer Overflow
#### 3.3.2. Dealing with Buffer Overflow  
If CWND always rises rapidly in the slow-start phase, wireless link can frequently experience buffer overflow due to excessively large amount of data stream generated by overgrown CWND size. If \(ASRAN\) uses \(current\_cwnd\) to calculate \(recalculated\_ssthresh\), TCP will always increase CWND using the Slow-Start algorithm after segment loss even in the case of congestion due to buffer overflow. In order to prevent such the case, \(ASRAN\) uses the \(last\_max\_cwnd\). If \(last\_max\_cwnd\) is larger than currently reduced CWND size after segment loss, the \(ASRAN\) recovers the CWND size using slow-start until it is the same size as \(last\_max\_cwnd\). If not, the \(ASRAN\) uses the \(original\_ssthresh\) as the \(recalculated\_ssthresh\), so the TCP flow executes the congestion avoidance phase as usual TCP congestion control does. Figure 2b shows such the scenario that lets \(ASRAN\) perform congestion avoidance. In Figure 2b, on the second CWND drop, the saved \(last\_max\_cwnd\) of the previous segment loss is smaller than \(original\_ssthresh\). In this case, the value of the \(original\_ssthresh\) will be the \(recalculated\_ssthresh\) value. Because \(recalculated\_ssthresh\) is smaller than reduced CWND size, congestion avoidance algorithm is executed.
# Structural Behaviour of Concrete Deep Beams Reinforced with Aluminium Alloy Bars
###### Abstract  
Aluminium alloy (AA) bars have emerged in structural engineering applications mainly to reduce deterioration caused by corrosion. However, research on AA-reinforced concrete (RC) beams has been limited, despite RC beams reinforced with AA bars providing a study area with great potential. Therefore, this study mainly aims to investigate the behaviour of AA RC deep beams. The investigated parameters include concrete strength, tension reinforcement ratio, beam size, a/d ratio, and transverse reinforcement ratio, most of which have not yet been thoroughly studied. A finite element (FE) model was developed to obtain accurate predictions. The developed FE model predicted the actual load-bearing capacity with a mean value of 1.00. The findings indicated a clear trend in which shear force capacity increased from 124.1 to 181.4 kN with increasing concrete compressive strength from 20 to 40 MPa. A strong relationship between the reinforcement ratio and failure mode was obtained. The shear strength decreased from 2.95 to 2.1 MPa as the effective depth increased from 175 to 350 mm. An increase in transverse reinforcement ratio instigated an enhancement in shear force capacity. Finally, the applicability of the design models in the current literature was evaluated. The design formulations gave accurate predictions with an error of 3%.  
aluminium alloy; concrete beams; finite element; shear Article
# Design Methodology and Application Dynamics of Compact Quasi-Zero Stiffness Isolators
## 3 Compact Design of QZS Isolation
### Special Spring Type
#### 3.1.4 Transverse Notch Springs  
[PERSON] et al. [46] constructed and investigated a prototype QZS isolator with negative stiffness provided by two pairs of transverse notch springs. Figure 7a illustrates the model diagram. Compared with coil springs, the transverse notch springs have the advantages of compact structure and designability. They analyzed the stiffness characteristics, dynamic response, vibration isolation performance, and the influence of parameters of the structure theoretically and designed the prototype and tested the force-displacement curves. The experimental data for Figure 7b show that the structure has a good vibration isolation effect  
Figure 5: WQZS isolator proposed by [PERSON] et al. [44]: (**a**) Front section view of the isolator; (**b**) Displacement transmissibility.  
Figure 6: The planar spring structure proposed by [PERSON] et al. [45].  
under the excitation of the 3-15 Hz frequency band, which further confirms the feasibility and effectiveness of transverse notch springs in the design of QZS isolators.  
In summary, the special spring has a compact structure, which has a significant advantage in space utilization efficiency compared to the QZS isolation constructed with conventional coil springs. A large stiffness coefficient is the key to the compact design. The high stiffness coefficient effectively suppresses the displacement of the vibration isolation object, which significantly expands the working area of the vibration isolator and enhances the stability and reliability of the vibration isolation effect. However, special springs face many difficulties in the design and processing process. Due to their special structure and performance requirements, accurate mechanical calculations and simulation analysis are indispensable, and in-depth investigation of the non-linear factors introduced by the special structure is needed to investigate the mechanism of the overall performance; in the processing and manufacturing process, the complexity of special springs requires very high processing accuracy, and the slightest deviation may result in a significant reduction in the performance of the springs, which in turn affects the isolation performance of the vibration isolator.
# Combining Higher-Order Statistics and Array Techniques to Pick Low-Energy P-Seismic Arrivals
## 3 Methodology
### Single-Trace Stage
As noted in the previous work by [6], the optimal picking performance occurs when the actual onset matches the earliest part of the characteristic function's increase; this corresponds to the case when the very beginning of the sought signal accesses the time window for HOS calculation, leading to a small increase in HOS. The value of the threshold that optimally catches this increase depends on the dataset and receiver setup. In this study, we identify the final onset with the first potential onset \(o_{1}\) (related to the threshold \(\theta_{1}=0.1\)), as Section 4 indicates that this is the best choice in our case. From \(\{o^{k}\}\), an estimate of the uncertainty on the arrival can be assigned as the standard deviation \(\sigma_{o}\). Specifically, we assign a weight to the P-onset ranging between 0 and 3 based on the ratio \(\sigma_{o}/\sigma_{\text{max}}\), as reported in Table 2.  
For example, considering the statistics \(\gamma_{4}\) in the cases displayed in Figure 3, the standard deviation among the set \(\{o_{k}\}\) is calculated using the case in the left panel, which is equal to \(4\cdot 10^{-3}\) s. In contrast, the traces in the central and right panels exhibit standard deviations of about 0.1 s and 0.2 s, respectively. The choice \(\sigma_{\text{max}}=75\) ms, for example, would correspond to the assignment of a weight of 0 (the largest reliability) to the left case and to reject the onsets on the other cases. Similar outcomes can be obtained considering the 6 th-order statistic. \begin{table}
\begin{tabular}{c c} \hline \hline
**P-Weight** & \(\sigma_{o}/\sigma_{\text{max}}\) \\ \hline
0 & \(\leq\)0.25 \\
1 & \(>\)0.25 \& \(\leq\)0.50 \\
2 & \(>\)0.50 \& \(\leq\)0.75 \\
3 & \(>\)0.75 \& \(\leq\)1.00 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Correspondence between the \(\sigma_{o}/\sigma_{\text{max}}\) and weight assignment method of STS. The assigned weights reflect the uncertainty levels of the respective P-wave arrival times. Lower weights correspond to lower uncertainty levels (e.g., a weight equal to 0 indicates maximum reliability).
## 1 Introduction
Similarly, the availability of remote operators 24/7 might be an issue. Moreover, the CAVs are expected to generate approximately 10 gigabytes (GB) of data every minute [11], suggesting that even advanced networks such as 5G will require optimisation [10]. Network latency or delay is one of the major challenges that can cause disruptions in communication systems [1; 3; 7; 8; 9; 10; 12]. Latency can affect the quality of sensory data from the vehicle to the remote station and control command data from the station to the vehicle, in turn degrading the operator's and teleoperation performance. It can also cause over- and under-steering of the remote vehicle. Moreover, longer and variable (time-varying) latency is an even more significant problem, making the control problem very challenging. The remote operators can tolerate latency up to a threshold beyond which it becomes unmanageable. For example, during vehicle teleoperation, [PERSON] [3] states that a constant latency of less than 170 milliseconds (ms) has a minor impact and is easily manageable whilst the operator can adapt to latency below 300 ms. However, latencies (with less variance) between 300 ms to 500 ms become challenging and significant for the operator to handle the vehicle (at slow speeds). Latencies above 700 ms make it nearly impossible for the teleoperator to interact with the vehicle in a timely manner.
## 1 Introduction
The other method combines the binding properties of MIPs (plastic antibodies) with a competitive fluorescence assay, similar to fluorescence ELISA [2; 40; 41; 42]. For example, our research group designed a novel fluorescent MIP sensor involving direct competitive binding between triazine herbicide and 5-(4,6-dichlorotriazinyl)aminofluorescein on MMIPs for atrazine detection in tap water [2]. Based on the above, we designed a novel magnetic dummy molecularly imprinted polymer (MDMIP) for fluorescence detection of melamine in milk. The principle is based on competitive absorption between a melamine molecule and a fluorescein isothiamate (FITC)-melamine (FITC-Mel) conjugate on the surface active sites of the MDMIPs. The MDMIPs were prepared on the surfaces of Fe\({}_{3}\)O\({}_{4}\)@SiO\({}_{2}\) to absorb specifically melamine molecules. The MDMIPs were characterized, and their adsorption capacity was evaluated based on their static adsorption and Scatchard analysis. Competitive binding between FITC-Mel and melamine was used for quantitative detection of melamine in spiked milk samples. Compared to the above-mentioned melamine detection methods, the detection method established in this paper needs no sophisticated experimental procedure and instruments. In addition, the present competitive fluorescence assay based on MDMIP is simpler than current Quantum Dots-MIP (QDs-MIP) fluorescent sensors with embedding of fluorescent QDs into the MIPs.
# Dynamic Stability Finite Difference Time Domain Analysis of Landfill Based on Hypergravity Test
## 3 Establishment of Computational Model
### Mechanical Damping Settings  
In dynamic analysis, commonly used forms of mechanical damping include Rayleigh damping, local damping, and hysteresis damping. Rayleigh damping and local damping are set based on the model's natural frequency or critical damping ratio, while hysteresis damping can be set using the shear modulus dynamic attenuation relationship curve, which can better reflect the nonlinear characteristics under dynamic loading. The damping ratio of MSW under an earthquake increases with cumulative strain, while the shear modulus decreases with cumulative strain, showing significant nonlinear characteristics. Based on the modulus attenuation curve of MSW obtained from experiments [11; 12; 13; 14], this study introduces hysteresis damping to simulate its dynamic characteristics. In dynamic calculation analysis, the total energy dissipation of the model in one cycle is represented by the energy dissipation corresponding to the constitutive model and hysteresis damping.  
\[\Delta E=\Delta E_{HD}+\Delta E_{M-C} \tag{8}\]  
where \(\Delta E_{HD}\) represents the energy dissipation caused by hysteresis damping in a cycle, and \(\Delta E_{M-C}\) represents the energy dissipation corresponding to the Mohr-Coulomb model in a cycle.
## 5 Conclusions  
A planar antenna array with a wide bandwidth and narrow beamwidth for an IR-UWB radar application is proposed in this paper. The design of the proposed antenna is considered on the entire integrated-circuit four-layer stack-up with the signal processing portion. Compared to a single antenna, implementing the proposed 2 \(\times\) 2 array in the same footprints offers beamwidth reduction while maintaining the wideband impedance matching. More specifically, the measured S11 \(<\) \(-\)10 dB fractional bandwidth is 10.7%, which is two times broader than a conventional patch antenna, and the measured HPBW is less than 50\({}^{\circ}\) in both E- and H-planes, with the antenna gain more than 6 dBi over the target frequency range. Thus, the proposed antenna array is preferable for an IR-UWB radar application that generates a pulse with a duration of a few nanoseconds in a limited azimuth boresight thanks to its wide bandwidth and narrow beamwidth.  
Conceptualization, V.-T.N.; Data curation, V.-T.N.; Formal analysis, V.-T.N.; Project administration, J.-Y.C.; Supervision, J.-Y.C.; Writing--original draft, V.-T.N. All authors have read and agreed to the published version of the manuscript.  
This work was supported in part by the Basic Science Research Program through NRF, funded by the Ministry of Education (NRF-2019R1A6A1A03032119), and in part by the NRF funded by the Korean government (MSIT) (no. 2021R1A2C1095134).  
Not applicable.  
The authors declare no conflict of interest.