esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
Only one older numerical FEA study [30] was found to make a limited distinction between brittleness and ductileness for the root canal filling, but without further development. Most of the recent FEA studies [28; 29; 30; 31; 32; 33; 34; 35; 36; 37; 38; 39; 40; 41; 43; 44; 45; 46; 47; 48; 49; 50; 51] employed the hydrostatic pressure criterion (specially designed for liquids, with no shear stress), maximum principal S1 tensile stress, and minimum principal S3 compressive stress (for brittle-like materials) for the study of PDL (a ductile-like material), while the reported results invariably exceeded MHP even for light orthodontic forces (suggesting ischemic and resorptive risks that contradict clinical data). The bone-implant [19; 20; 21; 22; 23; 24; 25; 26; 44] and bone-tooth [29; 43; 44] FEA studies employed S1-S3 (brittle-like) and [PERSON] (ductile-like) failure criterion but without any discussion about the above-mentioned issues. Most of the above FEA studies employed included boundary conditions isotropy, linear elasticity, and homogeneity, despite the anatomical tissues being none of these, without addressing their suitability, adequacy, and influence over the results accuracy issues. Moreover, the applied forces were higher than 1.2 N (despite the above boundary conditionsbeing correct only for small displacements and applied forces), while the investigated models were artificially created and anatomically simplified (i.e., lower number of nodes and elements with a higher global element size) [19; 20; 21; 22; 23; 24; 25; 26; 27; 28; 29; 30; 31; 32; 33; 34; 35; 36; 37; 38; 39; 40; 41; 42; 43; 44; 45; 46; 47; 49; 50]. It must be emphasized that, from a biomechanical point-of-view, linear elasticity and isotropy assumptions are correctly employed only if the applied forces are up to 1 N, and the non-homogeneity of materials is considered and addressed using the Tresca criterion. There is no available data on the above issues for higher applied forces in dental tissues and no studies, except for our previous studies [2; 3; 5; 6; 9; 10; 16; 48], acknowledged and addressed these issues. Herein, the study aimed to individually assess the biomechanical absorption-dissipation ability of dental tissues in intact periodontitis under 0.6 N, 1.2 N, and 2.4 N during the five most used orthodontic movements, as well as the changes produced by the reduction in supporting tissues during a gradual horizontal periodontal breakdown of 1-8 mm. Additionally, we investigated the suitability and biomechanical behavioral correctness of the frequently employed boundary conditions (isotropy, linear elasticity, and homogeneity) under increasing loads.
# Robust Estimators in Geodetic Networks Based on a New Metaheuristic: Independent Vortices Search
## 2 Classical and Robust Approaches  
The adjustment of geodetic networks is generally conducted by employing a Least Squares (LS) method, which is the best linear unbiased estimator when only random errors are present in the observations [9]. When this assumption does not comply, the estimation fails, distributing errors over many parameters. Other techniques can be applied when one suspects the presence of outliers, such as robust estimators (REs). We present a brief explanation of the methods covered in this study below.
# Smart Grid Data Management in a Heterogeneous Environment with a Hybrid Load Forecasting Model
## 5 Results and Discussion (Case Study 1)
### Case Study 1: Data Management  
The data were produced by the Iraqi Ministry of Electricity (MOELC) [59]. It is available on the Iraqi ministry of electricity's main website. The original consumption dataset included 9 months of monthly aggregated reading values (one read per month/per subscriber) for a total of 5,189,000 mechanical meters. Each meter also provides nine (9) subscription information parameters. The data covers insights from the four seasons, as it starts from winter (January-February) to spring (March-May), summer (June-August), and the beginning of autumn (September). The summary of the dataset is referred to in Table 2.  
The information obtained from the mechanical meters lacks detailed information, where it only includes reading value per month as a dynamic parameter and lacks important time-series (timestamps) or cluster information. These can be considered as a limitation in the current case study, but using PIAS, other objectives can still be achieved. Moreover, any database design should consider the ability to deal with heterogeneous data types resulting from current mechanical meters and the possibility of having smart meters soon. The presence of heterogeneous data leads to the need to go through a delicate transition phase, i.e., processing the current mechanical meter data, while the gradual replacement takes place on and shifts to smart meters in the future. This process can take many years and can be considered as another limitation in the current study. In addition to that, the nature of the data and its dimensions are different, as the smart meters possess an average of 20 to 30 different pieces of information about power consumption over time, while the mechanical meter only has reading value and date of physical data.
## 2 Methods--Data Processing
### Data Processing
#### 2.2.4 Target Encoding  
Two targets were simultaneously predicted with the reasoning that this might give gradients with richer information and thus could benefit convergence (Section 3.3.6 for details of how the loss was calculated). The first target was an ETA to the final known position. It has to be kept in mind that this could also be a point along the route where a short journey ends and does not necessarily have to be the final stop on the trajectory. This is expressed as minutes from the last data transmission. The second target is the next position along the trajectory, which is equivalent to a fraction along the route and can be decoded to give exact GPS coordinates. As noted previously, reducing the prediction space improves the final prediction. Therefore, the target was expressed as the distance along the trajectory from the last known position, which can be simply added to the previous distance to give a location along the trajectory. This enforces a forward prediction and is more useful, as a vehicle should never change direction in the middle of a journey. The combination of the two targets is an example which is more applicable, as network operators will in most cases be interested in ETA predictions and more accurate vehicle locations.
# Dynamic Response of Electro-Mechanical Properties of Cement-Based Piezoelectric Composites
###### Abstract  
By employing ordinary Portland cement as a matrix and PZT-5H piezoelectric ceramic as the functional body, 1-3 and 2-2 cement-based piezoelectric composites were prepared. Quasistatic compression tests were performed along with dynamic impact loading tests to study the electro-mechanical response characteristics of 1-3 and 2-2 cement-based piezoelectric composites. The research results show that both composites exhibit strain rate effects under quasi-static compression and dynamic impact loading since they are strain-rate sensitive materials. The sensitivity of the two composites has a non-linear mutation point: in the quasi-static state, the sensitivity of 1-3 and 2-2 composites is 157 and 169 pC/N, respectively; in the dynamic state, the respective sensitivity is 323 and 296 pC/N. Although the sensitivity difference is not significant, the linear range of the 2-2 composite is 24.8% and 61.3% larger than that of the 1-3 composite under quasi-static compression and dynamic impact loading, respectively. Accordingly, the 2-2 composite exhibits certain advantages as a sensor material, irrespective of whether it is subjected to quasi-static or dynamic loading.  
electro-mechanical response; cement-based piezoelectric composites; impact loading; sensitivity +
Footnote †: journal: Applied Sciences
# A Beam Hopping Scheme Based on Adaptive Beam Radius for LEO Satellites
## 3 Model
### Computational Complexity Analysis  
In step 1, we find the non-hotspot cell by traversing the macro cell service traffic. Therefore, the algorithmic computational complexity of step 1 is \(\mathcal{O}(M)\), \(M\) is the number of large cells.  
In step 2, we partition \(M\) cells into four clusters, thus, the algorithm's computational complexity is \(\mathcal{O}(M)\).  
In step 3, if there are available service beams, they will be utilized to serve medium or micro cells. Therefore, the algorithm complexity is \(\mathcal{O}(N*I))\), where \(N\) is the number of medium cells and \(I\) is the number of micro cells.  
In general, due to the significantly smaller number of large-beam cells compared to medium- and small-beam cells within the same coverage area, the product of \(N\) and \(I\) is much larger than \(M\). Therefore, the algorithm's computational complexity is denoted as \(\mathcal{O}(N*I)\).
# LoRa Architecture for V2X Communication: An Experimental Evaluation with Vehicles on the Move
## 6 Outdoor Testing and Analysis of the Prototypes
### Statistical Analysis of Proposed System
Therefore, the position of RSU and its interaction with vehicle speed do not have any significant effect on the number of data packets received by any of the RSUs. The \(p\)-value of the VS is less than the assumed \(\alpha\) which suggests rejecting the null hypothesis. This implies that different vehicle speeds have effects on the number of data packets received by RSUs which is obvious. Thus, these results clearly imply the statistical significance of the performed tests and collected data. The aim of the statistical analysis in this work was to show that the position and order of the RSU do not adversely affect the number of data packets received by those RSUs but it might be affected by the speed of the vehicles going along the road. That said, if the vehicle does not change the speed and it goes alongside multiple RSUs for equal time or distances for each one of them, then every RSU will get an equal number of data packets.
# Ambiguity-Resolved Model Tests for Carrier-Phase GNSS
## 3 The AF and AK Tests
### The Ambiguity-Float Test  
The AF test statistic is obtained from (4) by replacing \(a_{0}\) and \(a\) by their BLUEs under \(\mathcal{H}_{0}\) and \(\mathcal{H}_{a}\), respectively. This gives, with the help of Lemma 1,  
\[\underline{T}(\underline{\hat{a}}_{0},\underline{\hat{a}})=||\underline{\hat{ e}}_{0}||^{2}_{Q_{yy}}-||\underline{\hat{e}}_{a}||^{2}_{Q_{yy}}=||\underline{ \hat{e}}||^{2}_{Q_{zz}} \tag{6}\]  
It is distributed under \(\mathcal{H}_{0}\) and \(\mathcal{H}_{a}\) as  
\[\underline{T}(\underline{\hat{a}}_{0},\underline{\hat{a}})\left\{\begin{array} []{ll}\mathcal{H}_{0}&\chi^{2}(q,0)\\ \mathcal{H}_{a}&\chi^{2}(q,\lambda_{\text{AF}})\end{array}\right. \tag{7}\]  
with noncentrality parameter \(\lambda_{\text{AF}}=||c||^{2}_{Q_{zz}}\).  
A special case occurs when, under the alternative hypothesis, the mean of \(\underline{y}\) is allowed to vary freely over the whole of \(\mathbb{R}^{m}\), i.e., when \(\mathcal{R}(A,B,C)=\mathbb{R}^{m}\). Then, \(\underline{\hat{e}}_{a}\equiv 0\) and (6) reduces to  
\[\underline{T}(\underline{\hat{a}}_{0},\underline{\hat{a}})=||\underline{\hat{ e}}_{0}||^{2}_{Q_{yy}} \tag{8}\]  
This is the test statistic that is used for AF _detection_, i.e., for testing the ambiguity-float null hypothesis against the most relaxed alternative hypothesis.
## 1 Introduction  
Light scattering by pure water or pure seawater is a fundamental quantity in aquatic optics. Because of hydrogen bonding, many bulk properties of water exhibit anomalous behavior with temperature that is unlike any other liquids [1,2]. For example, liquid water has a maximum density near 4 \({}^{\circ}\)C [3], a minimum isothermal compressibility near 46 \({}^{\circ}\)C [4] and a maximum refractive index near 0 \({}^{\circ}\)C [5]. The scattering seems to behave \"anomalously\" too [6]. [PERSON] and [PERSON] [6] measured the scattering at 436 and 546 nm by pure water at temperatures from 5 to 65 \({}^{\circ}\)C, and found a scattering minimum at approximately 22 \({}^{\circ}\)C that is consistent with their theoretical estimate using the Einstein-Smoluchowski equation and the temperature variation of the isothermal compressibility. Using the same Einstein-Smoluchowski equation, with inputs re-evaluated using newer experimental results, [PERSON] et al. [7] improved the estimate of light scattering by pure water, which showed a better agreement with the spectral values measured by [PERSON] [8]. However, their model predicts a maximum scattering at 15 \({}^{\circ}\)C, which differs from [PERSON] and [PERSON] [6] not only in value but in the behavior as well. To the best of our knowledge, few other studies have explored the temperature behavior of scattering by water. In addition, it is still unknown whether and how this temperature dependence of scattering by water would vary in the presence of sea salts.
###### Abstract  
This study numerically analyzes and investigates the effects of the bearing design parameters of a tilting pad journal bearing (TPJB) on the pad-pivot friction-induced nonlinear rotordynamic phenomena and bifurcations. The bearing parameters were set to the pad preload, pivot offset, spherical pivot radius, and bearing length to diameter (L/D) ratio. The Stribeck curve model (SCM) model was applied at the contact surface between the pad and the pivot, which varied to the boundary-mixed-fluid friction state depending on the friction condition. The rotor-bearing model was set up with a symmetrical five-pad TPJB system supporting a Jeffcott type rigid rotor. The fluid repelling force generated in the oil film between each pad and the shaft was calculated using a finite element method. The simulation recurrently conducted the transient numerical integration to obtain the Poincare maps and phase states of the journal and pad with various bearing design variables, then the nonlinear properties of each condition were analyzed by expressing the bifurcation diagrams. As a result, the original findings of this study are: (1) The pad preload and pivot offset significantly influenced the emergence of Hopf bifurcations and the associated limit cycles. In contrast, (2) the pivot radius and L/D ratio contributed relatively less to the friction-induced instability. Resultantly, (3) all the effects diminished when the rotor operated under the larger mass eccentricity of the disc.  
p 2020 10 5406 10.3390/app10165406
# Rician Beamforming: Despeckle Method via Coarray Projection Stochastic Analysis
## Appendix A RiB First-Order Cumulative Distribution Functions  
Let \(\mathsf{X}\) be a random process for which first-order probability distribution matches Rician distribution with parameters \(\varepsilon\) and \(\sigma\),  
\[f_{X}\left(x|\varepsilon,\sigma\right)=\frac{x}{\sigma^{2}}\exp\left[-\frac{x^ {2}+\varepsilon^{2}}{2\sigma^{2}}\right]\cdot I_{0}\left(\frac{x\varepsilon}{ \sigma^{2}}\right) \tag{11}\]  
We define \(\rho=\varepsilon/\sigma\), essentially being a signal-to-noise ratio, and introduce the corresponding cumulative distribution function, defined as  
\[F_{X}\left(x|\varepsilon,\sigma\right)=\exp\left[\frac{-\rho^{2}}{2}\right] \int_{-\infty}^{x}\frac{y}{\sigma^{2}}\exp\left[-\frac{y^{2}}{2\sigma^{2}} \right]\cdot I_{0}\left(\frac{y\rho}{\sigma}\right)\ \mathrm{d}y=\exp\left[\frac{-\rho^{2}}{2}\right]G_{X} \left(x|\varepsilon,\sigma\right) \tag{12}\]  
On this general form, one may look into particular cases described in terms of distribution parameters, and interpret the RiB definition in (4). Penalties corresponding to the Rician distribution are depicted in Figure 11. This is, the difference between DAS and RiB outputs. Parameter \(\kappa\) significantly affects low SNR values, while it preserves high SNR inputs.
# _CoVSCode_: A Novel Real-Time Collaborative Programming Environment for Lightweight IDE
## 6 Prototype Implementation and Evaluations
### Experimental Evaluations
#### 6.3.1 Performance of Local and Remote Editing Operation Processing  
In a real-time collaboration session, whenever a local editing operation is performed, it will be detected (by the listener), processed (by the operational transformation controller) and propagated to the server; and whenever a remote editing operation arrives, it will be transformed and replayed. The processing times of these local and remote editing operations are key factors of user experience. To this end, we conducted 24 sets of experiments with two and three collaborating programmers (the most common scenarios) working on the six selected projects, respectively. During each experiment, we asked the participating programmers to concurrently edit the same source code file for at least five minutes, measured the processing times of at least 200 local or remote editing operations during the process, and finally calculated the average values. In terms of configuration, the experimental PC was equipped with an Intel Core i7 @ 2.2 GHz processor and 16 GB of RAM, and the operating system was macOS 10.14.6 (18G87).  
Table 3 presents the experimental results, including the average processing times of local editing operations in the two-collaborator sessions (2C sessions) and three-collaborator sessions (3C sessions), and the average processing times of remote editing operations in the 2C and 3C sessions. It can be observed that the processing of local editing operations was very efficient (less than one millisecond for each operation), which demonstrates the high local responsiveness of the client system. The processing of remote editing operations was also efficient, which contributes to the instant replay of remote editing operations, and also implies that the duration from an operation's generation (at its original site) to its remote replay (at a remote site) mainly depends on its transmission over the network, rather than its processing upon arrival.
## 2 Results and Discussion
### Detailed iPC-APPJ Device and Optical, Electronical, and Discharge Characteristics
The films with better performance in electric conductivity were located in these peak regions [14]. These related peaks confirm the successful formation of PANI. This observation suggests that the produced pPANI films are more likely in the emeraldine base form. Figure 5: Transmission electron microscopy (TEM) images of pPANI nanoparticles thin film prepared via iPC-APPJ. (**a–d**) The different magnifications; the inset in (c) is the selected area electron diffraction (SAED) pattern of pPANI nanoparticles. Scale bar = 2 nm. Figure 6: Fourier transform infrared spectroscopy (FTIR) spectrum of pPANI NwN thin film prepared using iPC-APPJ. Figure 7 shows the total ion count chromatogram of the pPANI NwN thin film obtained using solid-phase microextraction (SPME) GC-MS. As shown in Figure 7, the peaks at 10.468 min and 16.926 min were related to benzenamine and benzonitrile, respectively. The peak at 23.751 min was related to N=N bending vibration of azobenzene. FT-IR and GC-MS analysis show the characteristic polyaniline peaks, with evidence that some quinone and benzene rings were broken in the recombination region due to the intensive plasma jet. It also notes that our pPANI nanofibers and nanoparticles have an insulating state with the emeraldine base form, partially oxidized, with a few N-H groups in the main chain. However, emeraldine can easily change from insulator to conductor when it is protonated with a proton donor, such as HCl and iodine (I\({}_{2}\)) [13; 14; 34; 35; 53; 54]. Table 1 summarizes the weight average MW (\(M_{w}\)) of the aniline monomer and \(M_{w}\), number average MW (\(M_{n}\)), and polydispersity index (PDI) of the pPANI NwN thin film synthesized using the iPC-APPJ technique. As shown in the GPC results of Table 1, the synthesized pPANI showed high molecular weights (\(M_{w}\)) of about 533 kDa and an excellent PDI of about 1.9. Consequently, these experimental results confirm that the proposed iPC-APPJ device, driven by the sinusoidal voltage waveform, can obtain high molecular weight and ultra-fast (during just 10-30 min) pPANI films and NwN. Furthermore, we expect that our pPANI NwN can provide a unique advantage for optoelectronics, molecular electronics, and bionanotechnology applications. In addition, this proposed device is expected to be used for plasma polymerization with various monomers. Figure 7: Total ion count chromatogram of pPANI NwN thin film obtained using solid-phase microextraction gas chromatography-mass spectrometry (SPME-GC-MS) prepared using iPC-APPJ.
## 2 Materials and Methods
### Design and Fabrication of the LOC Test Device
In the next step, TiO\({}_{2}\) films with a thickness of 15 nm were deposited onto the surfaces of the gold nanoparticles using ALD equipment (CN1 Atomic Classic, Gyeonggi  
Figure 4: (**a**) Fabrication process of the PDMS mold and PDMS, (**b**) 3D diagram of the LOC test device, and (**c**) the fabrication process of the TiO\({}_{2}\)/Au nanocomposite film on a quartz substrate. do, Republic of Korea), employing alternating pulses of tetrakisdimethylamido titanium (TDMATi) and H\({}_{2}\)O as precursors in an Ar atmosphere [33; 34]. When the deposition temperature was 150 \({}^{\circ}\)C, the thickness of TiO\({}_{2}\) deposited per cycle was approximately 0.57 A, and 270 deposition cycles generated TiO\({}_{2}\) films with a thickness of 15 nm. For comparison, pure TiO\({}_{2}\) films with a thickness of 15 nm were also deposited on a quartz substrate using the same method. Finally, the deposited TiO\({}_{2}\) film was annealed at 500 \({}^{\circ}\)C for 1 h to transform its crystal structure into the anatase phase, characterized by high photocatalytic performance [35; 36; 37]. The pressure applied during the high-temperature annealing process for the aforementioned materials was standard atmospheric pressure. After prefabricating the TiO\({}_{2}\)/Au nanocomposite film and PDMS, a thin mixed liquid coating of PDMS polymer base and curing agent was prepared through the spin-coating method. The PDMS was then placed on the coating and dipped in thin layer of the mixed liquid before bonding with the TiO\({}_{2}\)/Au nanocomposite film. Finally, the PDMS and TiO\({}_{2}\)/Au nanocomposite film were baked at 70 \({}^{\circ}\)C for 2 h to enhance the bonding between them, yielding the LOC test device. The three-dimensional (3D) diagram of the fabricated LOC device is shown in Figure 4b, and its layered structure is shown in Figure 5. The device consists of four parts: a quartz substrate at the bottom, PDMS with microfluidic channels at the top, and a metal-doped and photocatalyst layer in the middle.
## 3 Experimental Results and Discussion
### Effect of Cutting Direction and Joint Spacing on Cutting Performance
#### 3.2.1 Effect of Cutting Direction
Figure 18 presents the mean values and standard deviations of the \(s/p_{\text{opt}}\) for intact rock specimens and different cutting directions in jointed rock mass specimens. The \(s/p_{\text{opt}}\) in jointed rock mass was smaller than that in intact rock, with the smallest value observed in the parallel cutting direction to the joint plane. This can be attributed to the differences in crack formation characteristics between jointed rock mass and intact rock. With the penetration of the cutting tool, in intact rock, cracks are generated only under the tool tip. On the other hand, in jointed rock mass, the majority of cracks are generated on the joint plane, contributing to the rock breaking [21; 35]. As a result, efficient rock breakage can still be achieved even at smaller spacings due to the interaction of cracks with joint planes. Furthermore, in the cutting direction parallel to the joint plane, the joint plane acts as a barrier, restricting the propagation of cracks generated by the pick and interfering with the interaction between successive cuts. Consequently, the optimal spacing is further reduced. Figure 17: Jointed rock mass specimen with a joint spacing of 60 mm after cutting (\(p=12\) mm and \(s=48\) mm). Figure 18: Variation in \(s/p_{\text{opt}}\) with \(\alpha\).