esa-sceva/satcom-chunk-collection huggingface dataset:
# Derivation and Validation of Bandgap Equation Using Serepentine Resonator
## 5 Conclusions  
In this study, we presented the derivation of an equation for a bandgap based on a numerical and experimental approach. A simplified model consisting of a resonator (mass-spring system) and host structure was used to derive the equation. Since the resonator was used as a serpentine resonator, the design freedom of the bandgap increased; hence, various design parameters of the simplified model were used to control the bandgap. The simplified model was simulated to verify the theoretical equation using commercial software. The resonant frequency and bandgap of the serpentine resonator were calculated and compared with the theoretical result to analyze the cause of relative error. In addition, the relative error map for each design variable was also presented to confirm the critical design variables. Experimental validation was conducted to verify the theoretical equation. The experiment was conducted using an impact hammer test, and the bandgap effect and vibration reduction on the thin beam were confirmed. The serpentine resonator reduces vibration by 5.5 dB in the bandgap frequency region and this is in agreement with the theoretical implementation and simulation. Therefore, the bandgap equation solved numerically through software in this study is mathematically derived for the first time. The derived bandgap equation can be used to control the bandgap by adjusting the design parameters, and the time used for simulation can be significantly shortened. Furthermore, if this study is limited to tortuous resonators, it is expected that it will be possible to derive bandgaps of various unit structures if developed.  
J.Y.: Conceptualization, Methodology, Software, Formal analysis, Visualization, Writing--original draft; J.J.: Conceptualization, Investigation; S.W.: Supervision, Funding acquisition. All authors have read and agreed to the published version of the manuscript.  
This study was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (NO.2021R1A2C2013259).  
**Institutional Review Board Statement:** Not applicable.  
Figure 11: Vibration measurement result.
# Situational Awareness: Mapping Interference Sources in Real-Time Using a Smartphone App
## 6 On-Field Measurement Campaigns
### Interferences in an Urban Scenario
#### 6.1.1 Case-study A: Experiment Performed in Porta Nuova Train Station  
Figure 8 shows a disturbance detected on 6 March 2017 in front of Porta Nuova train station in correspondence of the tram stop (Figure 8b). The interesting phenomenon observed is the occurrence of a very narrow-band interference each time a bus or a tram crosses the bus stop (Figure 8c). Figure 8a,b report just two of a series of recorded PSDs, where the peak always appears in the same frequency range: (1.59-1.61) MHz. This anomaly was observed for all the buses and trams passing by the stop. The TE in such cases was 12,000 (dB/Hz)\({}^{2}\), which was under threshold because the interference in this case have very narrow band and it did not affect considerably the TE value.  
Figure 8: _Cont._  
Figure 7: Live experiment test setup (**a**), screenshot of NGeneApp GUI (**b**) and real-time PSD plot (**c**).
# Multiple-Valued Logic Modelling for Agents Controlled via Optical Networks
## 1 Introduction
### Advantages of Data Protection Schemes Based on Multiple-Valued Logic  
Discrete \(k\)-valued logic calculus of Allen-Givone algebra (AGA) [29] and data coding schemes on their base [23; 30; 31; 32] have several features that are beneficial for the implementation of data verification schemes for network MASs. First of all, AGA makes the design of multiparametrical logic models easy, containing arbitrary associations of digital and symbolic parameters and aggregated by the appropriate choice of input variables and variants of functions. MVL modelling is also attractive for the integration of quantum schemes, which can be, e.g., easily described by AGA functions [32] for the quantum PU protocol [33]. The principal advantage of discrete \(k\)-valued logic is the high data capacity of AGA models, which can describe much more states in compact logic expressions [30] than Boolean logic.
## 4 Experimental Results and Analysis
### Comparison of Original Data and Model Prediction Results
Taking September as an example, in low-concentration areas such as around some parks in Qingxiu District, the model did not take into account factors such as vegetation adsorption of particulate matter and low surrounding traffic flow, resulting in overestimation of values in some low-concentration areas. The prediction results of the Prophet model are relatively fragmented. Although the values in some rural areas of Yongning District are relatively close to the true values, in the border areas such as the border with Jiangnan District, due to the complex changes in concentration gradients caused by changes in topography and human activities, the prediction deviates greatly from the actual distribution. In general, the SARIMA model has certain advantages in time series trend prediction, but in terms of actual spatial feature capture, there are certain deviations in different urban areas in different months, such as the commercial area of Xingning District and the newly developed area of Liangqing District. In general, each model has its own advantages and disadvantages in capturing and predicting the spatial distribution of PM\({}_{2.5}\) concentration at different time resolutions. In practical applications, it is necessary to comprehensively consider the changes in meteorological conditions in different time periods in the study area, such as the low temperature and calm wind period in winter, the concentrated precipitation period in summer, etc., as well as regional characteristics, such as the functional zoning of urban areas (commercial areas, industrial areas, residential areas, etc. ), topography ( mountainous areas, plains, water areas, etc.) and other factors. For areas with complex and changeable meteorological conditions and complex topography, the LightGBM model that can handle complex nonlinear relationships can be given priority. For time series with obvious seasonal and trend characteristics, the SARIMA model may be more advantageous. At the same time, the prediction accuracy of the spatial distribution of PM\({}_{2.5}\) concentration can be further improved by adjusting model parameters, such as optimizing the tree depth and learning rate of the LightGBM model, or fusing the prediction results of multiple models.
# Video Multi-Scale-Based End-to-End Rate Control in Deep Contextual Video Compression
## 4 Experimental Results
### Performance Analysis of End-to-End Rate Control
It can be observed that the RD performance of the proposed end-to-end rate control is better than the others, which indicates the effectiveness of the proposed end-to-end rate control. To summarize, the proposed end-to-end rate control can improve both objective and subjective coding performance with good control accuracies.
## 2 Materials and Methods
### Spectra Processing and Analysis
#### 2.4.2 Principal Component Analysis (PCA)  
Principal Component Analysis (PCA) was also used to identify WAMACS. The spectra were analyzed using SNV and the Savitzky-Golay second-order-derivative method before PCA analysis. PCA was performed and the loadings were calculated and used for WAMACS identification.
# Investigations of the Windage Losses of a High-Speed Shrouded Gear via the Lattice Boltzmann Method
## 3 Results and Discussion  
Based on the above real geometrical parameters of the spur gear, four groups of simulations with different lattice sizes are carried out to investigate the dependence analysis of the LBM model. The spur gear is rotating with a shroud whose radial clearance \(C_{r}\) is 16.66 mm and axial clearance \(C_{a}\) is 30.23 mm (i.e., \(\zeta_{r}=C_{r}/R_{p}=0.1009\), \(\zeta_{a}=C_{a}/b_{g}=1.0644\)). When the rotational speed is about 5100 rpm, the measured experimental windage power losses are about 500 W, as presented by [PERSON] et al. (2018). The detailed lattice sizes and numerical results of these three groups are listed in Table 2. Simulations were conducted on an AMD EPYC 7302 16-core Processor at 3.00 GHz. As shown in Table 2, all numerical windage power losses of the following models compare well with the experimental measurements. Considering the precision and accuracy of the calculation and flow field information, the finest resolution (Group 1) of these LBM models was recommended.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Number of teeth & 52 (-) \\ Module & 6.35 (mm) \\ Gear width & 28.4 (mm) \\ Pitch radius & 165.1 (mm) \\ Pressure angle & 25 (\({}^{\circ}\)) \\ Tooth profile & Standard \\ \hline \hline \end{tabular}
\end{table}
Table 1: Gear geometrical parameters.  
Figure 2: Figures of the numerical: (**a**) three-dimensional model; (**b**) lattice refinement.
## 2 Related Work
### Partition-Merge Clustering Algorithm  
Clustering algorithms based on the partition-merge strategy have gained favor among researchers for their ability to overcome the limitations of traditional clustering methods. Clustering by combining k-means with the density- and distance-based method (KMDD) [31] is a classical clustering algorithm following the partition-merge strategy, which combines both k-means and density in order to quickly find the structure of the data in the space. In the partitioning phase, KMDD uses k-means to divide the dataset into a number of smaller spherical clusters and assigns the corresponding local densities.  
In the merging phase, the initial subclusters are merged by manually selecting the cluster centers from the decision graph following the feature that the cluster core density is higher than the density of neighboring subclusters at a greater distance. KMDD accurately identifies clusters of various shapes, but the optimal k-value is a challenge for the KMDD algorithm. To address the limitations of KMDD, [PERSON] et al. [32] proposed a clustering algorithm called Beyond K-Means++, which explores clusters through local geometric information. To overcome the dependence on k, the algorithm automatically increases or decreases k starting from 1 as clusters split and merge, thereby not only avoiding k-dependence but also enhancing clustering accuracy. To address the limitations of the DPC algorithm's poor performance on popular datasets and its high dependence on the cutoff parameter, [PERSON] et al. [17] proposed a division and merging algorithm called an improved density peaks clustering algorithm based on natural neighbor with a merging strategy (IDPC-NNMS), which combines peak density and natural nearest neighbors. IDPC-NNMS adaptively obtains the local densities by accurately identifying the natural neighbors of each data and then defines a novel merging strategy to merge the subclusters. [PERSON] et al. [33] proposed a split-merge clustering algorithm, a novel projection-based split-and-merge clustering algorithm (PSM) using projection techniques, which extends projection techniques to K-means to select the initial cluster centers and then determines the distribution of clusters by the distribution of density profiles. Experiments show that PSM performs well under strict data conditions.
###### Abstract  
As LiDAR technology progressively advances, the capability of radar in detecting targets has become increasingly vital across diverse domains, including industrial, military, and automotive sectors. Frequency-modulated continuous-wave (FMCW) LiDAR in particular has garnered substantial interest due to its efficient direct velocity measurement and excellent anti-interference characteristics. It is widely recognized for its significant potential within radar technology. This study begins by elucidating the operational mechanism of FMCW LiDAR and delves into its basic principles. It discuss, in depth, the influence of various parameters on FMCW LiDAR's performance and reviews the latest progress in the field. This paper proposes that future studies should focus on the synergistic optimization detection. Frequency-modulated continuous-wave (FMCW) LiDAR represents the forefront of this technology [2].  
TOF LiDAR is often favored for its high accuracy, rapid response, and broad applicability. However, its performance may be limited within complex environments. FMCW LiDAR, however, has demonstrated significant advantages, positioning it as an advanced detection technology. Its primary benefit lies in the use of coherent detection technology, which eliminates the need for expensive single-photon detection devices and the generation of high peak power pulses. Additionally, FMCW LiDAR exhibits a high resistance to various interferences, including background illumination and ground scattering. When detecting dynamic targets, FMCW LiDAR leverages the optical Doppler frequency shift in received light signals, using the Doppler effect to instantly measure the target's velocity. This technology achieves high-resolution distance measurements while simultaneously acquiring distance and velocity information of the target in a single measurement process. The interference resistance of FMCW LiDAR denotes its capability to negate the effects of other light sources, enhancing its reliability in complex environments. With significant advantages in accurate velocity and position measurement, as well as noise suppression from light and environmental factors, FMCW LiDAR is particularly suitable for scenarios requiring target velocity information. Table 1 summarizes the advantages and disadvantages of both detection methods [3], highlighting the widespread research interest in FMCW LiDAR due to its numerous advantages.  
This paper focuses on FMCW LiDAR, emphasizing its fundamental principles. It subsequently explores the impact of several key parameters on FMCW LiDAR performance and summarizes recent research advances in the field. Future research should aim to optimize these critical parameters collaboratively to enhance the miniaturization, portability, cost-effectiveness, and longevity of FMCW LiDAR systems. This endeavor seeks to improve the performance of FMCW LiDAR systems comprehensively, providing more reliable and precise solutions for applications in autonomous driving and environmental sensing.
# Numerical Simulation on Backfilling of Buried Pipes Using Controlled Low Strength Materials
## 5 Conclusions  
1. In this study, the numerical simulation of the pipe is carried out under three conditions of loose backfill, dense backfill and CLSM backfill. It is concluded that the vertical earth pressure at 15 cm above the buried pipeline increases by 6% compared with the dense backfill. The vertical earth pressure on the pipe top and the horizontal earth pressure on the pipe side are significantly reduced. The horizontal earth pressure on the pipe side is reduced by 39.6% compared with the dense backfill. The CLSM is used for pipeline backfill, which significantly reduces the soil pressure on the pipe top and pipe side and protects the pipeline well.
2. Using CLSM to backfill the buried pipeline, the bearing force of the pipeline changes from the pipe-soil interaction to the majority of the solidified CLSM. The'soil arching effect' of pipes almost disappeared. The stress of the pipe is greatly reduced, which is conducive to the operation of the pipeline.
3. Under three different backfill conditions, the maximum radial displacement of the pipeline appears at the top of the pipe. In the case of dense backfill, the radial displacement of the pipe top is reduced, and the deformation of the buried pipe is 'heart' shaped. When the buried pipe is backfilled by CLSM, the deformation of the pipe is minimal. When the surface pressure is 200 kPa, the radial displacement of the pipe top is only 0.6 mm. Compared with the dense backfill, the radial displacement of the pipe top is reduced by 82.9%, which greatly reduces the deformation of the pipe.
4. Using CLSM to backfill buried pipeline, the circumferential strain around the pipe is greatly reduced. When the surface pressure is 200 kPa, the circumferential strain of the pipe top decreased by 84.5% and 79.7%, respectively, compared with the loose backfill and dense backfill. The strain around the pipe is very small by using CLSM backfill, and the pressure is uniformly distributed around the pipe.  
Conceptualization, H.L. and P.Z.; Data curation, H.L. and Y.X.; Formal analysis, H.L. and Y.X.; Funding acquisition, P.Z.; Investigation, H.L.; Methodology, H.L. and Y.X.; Validation, H.L. and K.L.; Visualization, P.Z.; Writing--original draft, H.L., Y.Z. and P.Z.; Writing--review & editing, H.L. and K.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Hubei Provincial Natural Science Foundation of China, grant number 2020 CFB477.  
Not applicable.  
The authors declare no conflict of interest.  
Figure 18: Circumferential strain under three backfill conditions.
# GIS Approach for Expressing Structural Landforms: Forms, Elements, and Relationships
## 2 GIS Approach for Expressing Structural Landforms
### Descriptions of Elements, Characteristics, and Relationships
\begin{table}
\begin{tabular}{c c} \hline \hline \multicolumn{1}{c}{**Morphological Types**} & \multicolumn{1}{c}{**Relationship between Elements**} \\ \hline Mesa & The **terrane *** occurrence is horizontal, the **lithology** is hard, and the **stratigraphic boundary** is parallel to the **contour line**. \\ \hline Anticlinal Mountain & The stratum in the **core of the fold** is older in age, and the **fold axis** coincides with the **ridge line**. \\ \hline Synclinal Mountain & The stratum in the **core of the fold** is younger in age, and the **fold axis** coincides with the **ridge line**. \\ \hline Anticlinal Valley & The stratum in the **core of the fold** is older in age, and the **fold axis** coincides with the **valley line**. \\ \hline Synclinal Valley & The stratum in the **core of the fold** is younger in age, and the **fold axis** coincides with the **valley line**. \\ \hline Cuesta & The **terrane** occurrence is inclined, the **lithology** is hard, and the **ridge line** coincides with the **stratigraphic boundary**. \\ \hline Hogback Mountain & The **terrane** occurrence is inclined, and the **contour line** coincide with the **stratigraphic boundary**. \\ \hline Fault Block & The fault line overlaps with the **ridge line**, and the upper and lower plates of the **fault wall** are relative displacements. \\ \hline Fault Valley & The fault line overlaps with the **valley line**, and the upper and lower plates of the **fault wall** are relative displacements. \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Relationships between the elements of each structural landform type.
# Hyperlipidemic Rabbit Models for Anti-Atherosclerotic Drug Development
## 2 Hyperlipidemic Rabbit Models
### Gene-Manipulated Rabbits
#### 2.3.2 Knockout (KO) Rabbits  
For a long time, it had been impossible to generate KO rabbits; however, the emergence of recent gene-editing technologies has dramatically changed the field of KO rabbits. Recently, apo E and LDLR KO rabbits were generated and have been used for the study of hyperlipidemia [45; 46; 47]. Apo-KO rabbits exhibited mild hyperlipidemia, with TC levels at \(\approx\)200 mg/dL, on a normal standard diet [46; 48]. When challenged with a cholesterol diet, apo E KO rabbits showed greater susceptibility to hyperlipidemia than did the wild-type rabbits, and their plasma TC and TG levels were remarkably increased, with a 6.3-fold increase in TC and a 5.7-fold increase in TG compared with those of wild-type rabbits [48]. Hyperlipidemia in apo E KO rabbits was caused by elevated remnant lipoproteins predominated by apo B-48 and rich in both apo A-I and apo A-IV contents. [PERSON] et al. generated LDLR KO rabbits and found that, similar to WHHL rabbits, LDLR deficiency markedly increased plasma TC levels (272-1013 in LDLR-KO rabbits vs. 51 mg/dL in the wild-type rabbits) on a normal standard diet. Increased plasma TC levels were mainly caused by elevated LDL-C (124-730 in LDLR-KO rabbits vs. 21 mg/dL in the wild-type rabbits) [47]. Apo E and LDLR double-KO rabbits were also generated by the same group and exhibited remarkable hyperlipidemia on a normal standard diet [49]. These KO rabbits may be useful for anti-atherosclerotic drug development in the future.
# Determining Key Parameters with Data-Assisted Analysis of Conditionally Automated Driving
## 5 Discussion
### Safety Measures  
In addition to predictions during the TO process, which focuses on monitoring the intervals between TOR and the TO, some safety performance parameters could also be monitored. If the most exposed parameters, i.e., _maximal acceleration_ (deceleration) and maximal jerk, would exceed a certain threshold, additional actions such as warnings or automatic maneuvers could be performed by the vehicle, regardless of whether the driver performs a TO or not. For example, [PERSON] and [PERSON] [103] proposed that additional warnings should be issued every time a minimal TTC (P7) drops below three seconds.  
The simple model of overall success (no collision, P8) suggests the importance of moderate braking (moderate maximal acceleration). It should be neither too strong, which could be the consequence of a late response, nor too weak, which could be a possible consequence of an inadequate response or no response at all. Separately, the analysis of off-road driving (P4) revealed that drivers with strong accelerations/decelerations also had the highest probability of off-road driving. This suggests a correlation among maximal acceleration (A29), off-road driving (P4), and overall success (P8). On the other hand, no off-road driving was observed with drivers who braked fast enough (with a larger maximal jerk), did so appropriately (not too hard), or responded correctly to the TOR.  
It seems somewhat surprising that measurements of lane deviation were not pointed out more often by our models. In contradiction to [PERSON] et al. [43] or [PERSON] et al. [55], lane deviation measurements do not seem to affect the TO quality as much as the maximal acceleration or braking reaction time do. However, maximal lateral acceleration (P6) is most strongly influenced by the fastest steering wheel rotation. The recorded fast steering wheel turns may have been the result of reckless reactions by drivers. It could be debatable whether preventing fast steering wheel turns would benefit the overall quality of a TO (e.g., by hardening the wheel, as lane-keeping systems do while manually changing lanes without signaling).  
To finally answer our primary research question (_which parameters_), the TOR-to-first-brake interval and maximal deceleration seem to have the greatest impact on the quality of a TO. Therefore, to improve the TO quality, a good TOR UI should provoke quick braking reactions (although not necessarily stronger ones, since excessive braking can negatively affect some TO quality aspects, such as off-road drive or overall success) or, even better, include a controlled automatic braking maneuver. Somewhat generalized, one could say that the best option for the driver would be gradual braking immediately after TOR to gradually reduce speed. Braking, and thereby reducing speed, reduces both the overall reaction time and the maximal lateral acceleration, as well as increases the minimal TTC. Furthermore, this could be done automatically by an automatic braking maneuver.