esa-sceva/satcom-chunk-collection huggingface dataset:
# Bonding of Selected Hardwoods with PVAc Adhesive
## 3 Results and Discussion
### Density, Cold Water Extract, pH Value, Roughness, and Wettability of Hardwoods
The smaller water contact angles, which usually result from the rougher and more polar characteristics of wood surfaces, indicate deeper penetration of the water-based adhesive into the wood structure [16; 59]. When comparing the roughness parameters and the wettability parameters of 13 hardwoods (Tables 2 and 3), it is evident that there was not always a more apparent connection between these two groups of parameters. For example, the macaranduba and meranti \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Wood** & \multicolumn{3}{c}{**Roughness Parallel with Grain (\(\mu\)m)**} & \multicolumn{3}{c}{**Roughness Perpendicular to Grain (\(\mu\)m)**} \\ \cline{2-7}
**Species** & \(Ra\) & \(Rz\) & \(R_{Sm}\) & \(Ra\) & \(Rz\) & \(R_{Sm}\) \\ \hline Bangkirai & 10.4 (3.0) & 68.4 (18.5) & 698.4 (193.6) & 17.1 (3.6) & 131.9 (19.7) & 560.5 (89.5) \\ Beech & 6.0 (1.8) & 41.2 (12.6) & 673.9 (142.9) & 8.2 (1.9) & 63.7 (12.8) & 408.5 (56.7) \\ Black locust & 5.8 (2.7) & 40.5 (19.3) & 572.4 (121.8) & 9.6 (2.7) & 86.7 (20.7) & 565.5 (149.7) \\ Bubinga & 6.5 (3.6) & 44.9 (22.8) & 591.4 (150.1) & 7.0 (3.1) & 69.3 (22.2) & 688.5 (233.6) \\ Ipe & 7.9 (4.6) & 51.5 (25.8) & 737.1 (197.5) & 9.3 (3.8) & 77.2 (20.5) & 572.4 (105.9) \\ Iroko & 7.1 (1.8) & 51.6 (13.7) & 580.5 (134.8) & 10.0 (3.2) & 82.5 (24.7) & 661.1 (256.5) \\ Macaranduba & 3.6 (1.5) & 26.7 (8.7) & 555.1 (104.7) & 4.2 (0.9) & 46.8 (13.5) & 643.9 (213.3) \\ Meranti & 9.9 (5.1) & 60.8 (27.3) & 655.0 (179.8) & 17.6 (4.6) & 126.6 (21.3) & 760.2 (197.7) \\ Oak & 9.4 (6.4) & 59.5 (35.2) & 574.5 (195.2) & 16.8 (5.1) & 123.4 (33.7) & 534.5 (119.5) \\ Palisander & 4.7 (1.3) & 34.3 (10.1) & 679.2 (239.1) & 5.9 (2.1) & 57.6 (14.7) & 555.7 (138.8) \\ Sapelli & 7.3 (2.8) & 52.8 (19.4) & 565.1 (109.0) & 10.2 (2.3) & 87.6 (11.1) & 533.8 (93.0) \\ Wengé & 5.4 (3.3) & 39.2 (20.0) & 545.6 (145.7) & 9.8 (2.7) & 78.5 (17.8) & 712.1 (174.5) \\ Zebrano & 7.1 (3.2) & 50.3 (22.4) & 588.5 (159.5) & 9.5 (3.3) & 81.6 (21.7) & 622.5 (195.1) \\ \hline \hline \end{tabular} Note: Mean values are determined from 90 values (15 different measuring spots on 6 replicates). Standard deviations are in parentheses.  
\end{table} 
Table 2: Roughness parameters \(Ra\), \(Rz\), and \(R_{Sm}\) of the hardwood surfaces. woods, characterized by totally different values for the density (Table 1) and the parameters of roughness (Table 2), had comparable values for the water contact angles (Table 3).
# Optimizing Rural Highway Maintenance Scheme with Mathematical Programming
## 5 Findings and Research Extensions
### Limitations and Future Research Directions  
While the proposed model offers valuable insights, there are several limitations and opportunities for future research:  
Non-Synchronous Maintenance Periods: The current model assumes synchronous maintenance periods, where all selected road segments are maintained simultaneously. Exploring non-synchronous maintenance schedules could potentially lead to more efficient solutions, although it would introduce additional complexity.  
Dynamic Traffic Demand: The model assumes a fixed traffic demand, whereas real-world traffic patterns can fluctuate significantly. Incorporating dynamic traffic demand models could enhance the realism and effectiveness of the maintenance strategies.  
Environmental Impact: While the model considers fuel consumption as an indirect measure of the environmental impact, a more comprehensive analysis incorporating other environmental factors, such as emissions and noise pollution, would be beneficial.  
Multi-Modal Transportation Systems: The current model focuses on rural highway networks. Future research could explore the extension of the model to multi-modal transportation systems, incorporating different modes of transportation and their interactions.
## 3 Results and Discussion
### Development of Hybrid Mixes
#### 3.3.2 Compressive Strength  
The variation of the hybrid SCC samples' compressive strength with curing age is shown in Figure 18. Multiple samples were tested at different intervals ranging between 3 and 56 days, with the average compressive strength being reported. At 3 and 7 days of curing, the hybrid mixes had a lower compressive strength compared to the benchmark SCC mix. Afterwards, H01 began to overtake the benchmark SCC mix and continued to do so until 56 days. Meanwhile, H02 and H03 exhibited similar trends (compressive strength and rate of strength gain) to each other. H02 met the benchmark SCC mix's final compressive strength while H01 and H03 exceeded it, with the final compressive strengths being 95.6, 92.1, and 94.7 MPa for H01, H02, and H03, respectively. The hybrid mixes had a maximum standard deviation of 4.20 MPa and a maximum variance coefficient of 5.25%.
## 4 Multimodal Interaction
### Interaction Based on the Auditory Channel  
One modality consists of using sounds or pre-recorded texts, where in some cases the speech can be automatically and dynamically generated by a text-to-speech engine. Often it is proposed a spoken natural language interface as a usable way of interaction. Such a vocal interface requires a robust speech recognition system and the analysis and comprehension of the recognized text. However, it can give inaccurate results in over-crowded environments and therefore demands specific requirements, such as the use of accurate microphones. The MAGA system exploits a chatbot interface and radio frequency identification (RFID) tags attached to points of interest [33]. Users used a PDA running the MAGA client application able to process the data of RFID tags. Every time a tag is detected, the RFID Module communicates the position to a chatbot, that, as a consequence, starts the interaction providing information about the detected item and waiting for user requests. An application for character-based guided tours on mobile devices has been introduced in [34]. The system has been designed to play the role of a guide in a historical site and is based on a virtual character, named \"[PERSON]\" who is a spider having an anthropomorphic aspect. It uses the DramaTour methodology for information presentation that is based on the assumption that a character acting in first person and sharing with the user both the location and the time of the visit can provide a strong effect of physical and emotional presence. The content is presented to the visitor in a location-aware manner and the elementsof the presentation are labelled with metadata associated to both their content and their communicative function.  
A robotic system capable of interacting with human users in order to inform them about issues regarding the cultural heritage domain in an engaging and amusing manner has been illustrated in [35]. The system is capable of interacting in natural language with the user to explore a knowledge base both in a traditional, rule-based manner and also making sub-symbolic associations between the user queries and the concepts stored in the Knowledge base. Two different and complementary AI approaches, namely sub-symbolic and symbolic, have been implemented and combined to reach these capabilities. Furthermore, when the required information is not available, the robot tries to find it on Internet.
## 4 Analysis and Verification of Rolling Bearing Fault Diagnosis Tests
### Additional Validation Experiments
\begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Model**} & \multicolumn{8}{c}{**Running Time/s**} & \multirow{2}{*}{**Avg/s**} \\ \cline{2-2} \cline{4-13}  & **1** & **2** & **3** & **4** & **5** & **6** & **7** & **8** & **9** & **10** \\ \hline
1-VMD-PE-LSTM & 10.13 & 11.16 & 10.13 & 10.29 & 10.11 & 10.44 & 10.36 & 10.17 & 10.57 & 10.16 & 10.35 \\
2-VMD-PE-IGTO-LSTM & 10.26 & 11.30 & 10.26 & 10.42 & 10.24 & 10.57 & 10.49 & 10.30 & 10.70 & 10.29 & 10.48 \\
3-GTO-VMD-PE-LSTM & 10.39 & 11.45 & 10.39 & 10.56 & 10.37 & 10.71 & 10.63 & 10.43 & 10.84 & 10.42 & 10.62 \\
4-IGTO-VMD-PE-LSTM & 11.56 & 12.74 & 11.56 & 11.74 & 11.54 & 11.91 & 11.82 & 11.61 & 12.06 & 11.59 & 11.81 \\
5-IGTO-VMD-PE-GW-LSTM & 15.17 & 16.71 & 15.17 & 15.41 & 15.14 & 15.64 & 15.52 & 15.23 & 15.83 & 15.22 & 15.50 \\
6-IGTO-VMD-PE-PSO-LSTM & 13.51 & 14.88 & 13.51 & 13.72 & 13.48 & 13.92 & 13.81 & 13.56 & 14.09 & 13.55 & 13.80 \\
7-IGTO-VMD-PE-IGTO-LSTM & 13.20 & 14.55 & 13.20 & 13.41 & 13.18 & 13.61 & 13.50 & 13.25 & 13.78 & 13.24 & 13.49 \\
8-IGTO-VMD-PE-CDO-LSTM & 12.21 & 13.45 & 12.21 & 12.40 & 12.19 & 12.58 & 12.49 & 12.26 & 12.74 & 12.25 & 12.48 \\
9-GWO-VMD-PE-IGTO-LSTM & 16.05 & 15.38 & 13.96 & 14.18 & 13.94 & 14.39 & 14.28 & 14.02 & 14.57 & 14.01 & 14.48 \\
10-PSO-VMD-PE-IGTO-LSTM & 14.28 & 13.68 & 12.42 & 12.62 & 12.40 & 12.80 & 12.70 & 12.47 & 12.96 & 12.46 & 12.88 \\
11-GTO-VMD-PE-IGTO-LSTM & 15.66 & 15.04 & 13.65 & 13.86 & 13.62 & 14.07 & 13.96 & 13.70 & 14.24 & 13.69 & 14.15 \\
12-CDO-VMD-PE-IGTO-LSTM & 13.87 & 13.29 & 12.07 & 12.26 & 12.04 & 12.43 & 12.34 & 12.11 & 12.59 & 12.10 & 12.51 \\
13-IGTO-VMD-PE-IGTO-LSTM & 15.39 & 14.75 & 13.39 & 13.60 & 13.36 & 13.80 & 13.69 & 13.44 & 13.97 & 13.43 & 13.88 \\ \hline \hline \end{tabular}
\end{table} 
Table 11: Running time for each model. Figure 13: Boxplot of test phase accuracy for each model.
###### Abstract  
This paper is concerned with the state estimation problem based on non-fragile set-membership filtering for a class of measurement-saturated memristive neural networks (MNNs) with unknown but bounded (UBB) noises, mixed time delays and missing measurements (MMs), subject to cyber-attacks under the framework of weighted try-once-discard protocol (WTOD protocol). Considering bandwidth-limited open networks, this paper proposes an improved set-membership filtering based on WTOD protocol to partially solve the problem that multiple sensor-related problems and multiple network-induced phenomena influence the state estimation performance of MNNs. Moreover, this paper also discusses the gain perturbations of the estimator and proposes an improved non-fragile estimation framework based on set-membership filtering, which enhances the robustness of the estimation approach. The proposed estimation framework can effectively estimate the state of MNNs with UBB noises, estimator gain perturbations, mixed time-delays, cyber-attacks, measurement saturations and MMs. This paper first utilizes mathematical induction to provide the sufficient conditions for the existence of the desired estimator, and obtains the estimator gain by solving a set of linear matrix inequalities. Then, a recursive optimization algorithm is utilized to achieve optimal estimation performance. The effectiveness of the theoretical results is verified by comparative numerical simulation examples.  
weighted try-once-discard protocol; memristive neural networks; state estimation; non-fragile set-membership filtering; network-induced phenomenon Article
# Research on Construction Sequencing and Deformation Control for Foundation Pit Groups
## 2 Materials and Methods  
This section integrates experimental and numerical approaches to systematically investigate excavation sequencing effects in foundation pit groups. The physical model tests were designed based on typical engineering scenarios in the Nanjing Jiangbei New District Phase II project, where segmented and adjacent pit configurations face challenges of asymmetric stress redistribution and cumulative deformations under spatial constraints. The scaling principles (1:100) adhere to the similarity laws for geotechnical centrifuge modeling, ensuring kinematic consistency between model and prototype behaviors. Material selections (e.g., uniform sand) were validated against the Quaternary alluvial sands dominant in the Yangtze River Delta region, as characterized in Section 2.1.3.
## 2 Materials and Methods
### Measurement Procedure  
After guided surgery, postoperative CBCT scans were taken of each side of the pig jaw with the same settings as the preoperative scans. Using the software BlueSkyPlan 4 (BlueSkyBio, Libertyville, IL, USA), the drill path was automatically segmented via a slice-by-slice method and transformed into a three-dimensional virtual model. As a next step, STL files of the drill path and initial planning were superimposed using 3 Shape Implant Studio by aligning the crowns of each tooth. The CBCT analysis used a specific algorithm to minimize the relative distance according to an interactive process of the files matching, guaranteeing accurate and repeatable overlaying. Following the alignment process, a mean error value was calculated using the distance of the points between the two surfaces (from the STL and the DICOM files), which were considered acceptable when less than 0.1-0.15 mm.  
To compare the result of the osteotomy with the plan in terms of the deviation of the principal axes, the deviation of each drill path created with the SMGs and initial planning was measured in 3 dimensions. To calculate the Euclidean distances, the following formula was used:  
\[\sqrt{x^{2}+y^{2}+z^{2}}\]  
where \(x,y,\) and \(z\) are the sagittal, coronal, and axial distances between the end of the drill path created with the SMGs and the end of the preplanned virtual implant, respectively (Figure 4a-e). The angular deviation was defined as the angle closed by the principal axes of the aligned models in degrees. All measurements were repeated three times.  
Figure 4: Determination of the measurement deviation calculation and angular deviation at the level of the apex. (**a**) The preoperative 3D reconstruction of the pig jaw shows the virtual implants in direction of the targeted root apices. (**b**) The illustration shows the calculation of the apical deviation of the tip of the virtual implant in comparison with the actual drilled path. (**c**) Sagittal view, (**d**) coronal view, and (**e**) axial view of the superposition between the virtual planned implant (green) and the actual drill path (orange).The green circle represents the implant’s safety zone. The blue line shows the main axis of the implant. The dark green line represents the panoramic curve.
# Effect of Buildings on the Radiation Characteristics of MF Broadcast Antennas
## 2 Materials and Methods
### Scattering from a Wire Grid  
A point-matching solution to the problem of scattering by a wire-grid model has already been developed by [PERSON] [27]. A brief outline of this solution is given below.  
The elementary scatterer is a short, thin wire segment of length \(\Delta\). By assuming that \(\Delta\ll\lambda\), the current density may be taken as uniform over the surface of each segment. The electric field intensity of this source, i.e., the scattered field of each segment, may be expressed as a surface integral over the surface of the wire. Subsequently, we enforce the boundary conditions: the tangential electric field intensity should vanish everywhere on the surface of each PEC segment. However, if the wire is thin, it is sufficient to zero the tangential electric field at just one point at the center of each segment. The end result of the analysis described above is a set of \(N\) linear equations, where \(N\) is the total number of segments:  
\[\sum_{j=1}^{N}S_{ij}I_{j}=-E_{i}^{inc},\quad i=1,2,\ldots,N \tag{2}\]  
In Equation (2), \(S_{ij}\) represents the scattering coefficient, i.e., the tangential component of the electric field intensity radiated by segment \(j\) (with unit current) when the observation point is at the center of segment \(i\), \(I_{j}\) stands for the (unknown) current induced on segment \(j\), and \(E_{i}^{inc}\) is the tangential component of the incident electric field intensity at the center of segment \(i\). The scattering coefficients \(S_{ij}\) are calculated in the Appendix of [27]; the explicit expression for \(S_{ij}\) is given by Equation (24) in [27] and is omitted for the sake of brevity.  
The system (2) may be solved numerically in order to obtain the unknown currents, provided that \(E_{i}^{inc}\) is known. Herein, the latter is actually the field intensity radiated by  
Figure 2: The orientation of a building with reference to the antenna. The building is modeled as a wire-grid rectangular parallelepiped.  
an antenna, and it is discussed in Section 2.5. Subsequently, the vector potential \(A_{i}\) is calculated from:  
\[A_{i}=A_{i}\hat{i}=\frac{\mu s_{i}l_{i}}{4\pi r}\exp[-jkr+jk(x_{i}\sin\theta\cos \varphi+y_{i}\sin\theta\sin\varphi+z_{i}\cos\theta)]\hat{i} \tag{3}\]  
The unit vector \(\hat{i}\) in Equation (3) denotes the direction parallel to segment \(i\), \(s_{i}\) is the length of segment \(i\), which is equal to \(\Delta\) for the case examined herein, and \((x_{i}y_{i},z_{i})\) are the Cartesian coordinates of the center of segment \(i\). Finally, the distant scattered field is found as follows:  
\[E_{\theta}^{sca}=-j\omega\sum_{i=1}^{N}[\cos\theta\cos a_{i}(\cos\varphi\cos b _{i}+\sin\varphi\sin b_{i})+\sin\theta\sin a_{i}]A_{i} \tag{4a}\] \[E_{\varphi}^{sca}=j\omega\sum_{i=1}^{N}(\sin\varphi\cos b_{i}-\cos\varphi\sin b _{i})A_{i}\cos a_{i} \tag{4b}\]  
The angles \(a_{i}\) and \(b_{i}\), in Equation (4), denote the orientation of segment \(i\) according to: \(\hat{i}=\hat{x}\cos a_{i}\cos b_{i}+\hat{y}\cos a_{i}\sin b_{i}-\hat{z}\sin a_ {i}\).
## 2 Monochromator Design and Realization
### Parameter Selection  
The design has been demonstrated in the 12-50 eV region. Two gold-coated gratings manufactured by Newport-Richardson Gratings\({}^{TM}\) were used, respectively, with 600 gr/mm (\(G_{1}\)) and 1200 gr/mm (\(G_{2}\)), both of them with 5.2\({}^{\circ}\) nominal blaze angle. The coma-correction energies \(E_{C}=hc/\lambda_{C}\) were 20.6 eV (60 nm) and 41.3 eV (30 nm), respectively, for \(G_{1}\) and \(G_{2}\). The subtended angle at \(E_{C}\) was selected equal to 156\({}^{\circ}\).  
Further parameters, such as the grating output arm \(q_{G}\), the mirror-to-grating distance \(D\), and the CM incidence angle \(\alpha_{M}\) were selected to satisfy both spectral bandwidth (Section 3.3) and compact realization requirements. Monochromator parameters are reported in Table 1.  
Once the geometrical design was defined, the subtended angles (reported in Figure 3) and the FWHM energy bandwidth \(\Delta E_{FWHM}=E\Delta\lambda_{FWHM}/\lambda\) were calculated, from Equations (2) and (6), respectively, for the entire spectral range of the two gratings.  
The entrance slit width was set to about 35 \(\pm\) 3 \(\upmu\)m, which is the typical width of a HHs source, with the laser focused tightly to reach sufficient intensity to ionize the gas [22].  
\begin{table}
\begin{tabular}{c c|c c|c c} \hline \hline \multicolumn{2}{c}{**Entrance Slit Dimensions**} & \multicolumn{3}{c}{**35 \(\upmu\)m \(\times\) 1 mm**} \\ \hline \multicolumn{2}{c|}{**Focusing Mirror**} & \multicolumn{2}{c|}{**Gratings \(G_{1}\)\(-\)\(G_{2}\)**} & \multicolumn{2}{c}{**Plane Mirror**} \\ \hline \(p_{M}\) & 675 mm & \(p_{G}\) & 363 mm & \(q_{1}\) range & 60–200 mm \\ \(q_{M}\) & 478 nm & \(q_{G}\) & 2070 mm & \(q_{2}\) range & 1870–2010 mm \\ \(\alpha_{M}\) & 87\({}^{\circ}\) & \(k\) range & 149\({}^{\circ}\)–158\({}^{\circ}\) & \(\alpha_{D}\) & 77.5\({}^{\circ}\)–82\({}^{\circ}\) \\ \(R_{M}\) (tang. radius) & 10,700 mm & \(G_{1}\) groove density & 600 gr/mm & & \\  & & \(G_{1}\) energy range & 12–25 eV & & \\  & & \(G_{2}\) groove density & 1200 gr/mm & & \\  & & \(G_{2}\) energy range & 25–50 eV & & \\  & & \(D\) & 115 mm & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Parameters of the monochromator.
## 5 Conclusions  
Aiming at the problems of asynchronous multi-parameter acquisition and high cost in the crop phenotype platform, this paper introduced the PTP and built a low-cost and practical crop phenotype parameter acquisition system, realizing the time synchronization of multiple sensors at the ns level, providing an advanced technical means for crop phenotype research. The paper draws the following three conclusions:  
The system developed in this paper built the PTP between the MAC and physical layers, which can realize the high-precision time synchronization of digital cameras, infrared cameras, and laser point cloud devices. The results of the 72 h time synchronization test experiment show that the root mean square errors of the time differences between the system real-time clocks of each timing board and the PTP clock of timing board 1 (the master clock) are 129.17, 128.87, and 120.47 ns, respectively, indicating that the system has high time synchronization accuracy.  
The results of the stability test experiment (taking peppers as an example) show that the system achieved a 100% acquisition success rate in 133 consecutive acquisitions. The average point number difference and coordinate error of the acquired data were both about 3%, the DSSIM was about 0.96, the Charm distance was about 1.14 mm, and the Hausdorff distance was about 5 mm, proving that the system developed in this paper has good stability.  
Without considering the public network transmission delay, the response time of the system developed in this paper reaches the microsecond level, which can not only meet the needs of the fast mobile crop phenotype system to carry multiple sensors for synchronous acquisition but also provide hardware support for improving the accuracy of data registration.  
Conceptualization, R.S. and M.Z.; methodology, R.S.; software, R.S. and H.L.; validation, H.L. and Y.H.; investigation, R.S. and H.L.; resources, W.S.; data curation, R.S.; writing--original draft preparation, R.S.; writing--review and editing, M.Z. and W.S.; visualization, R.S.; supervision, W.S.; project administration, W.S.; funding acquisition, W.S. All authors have read and agreed to the published version of the manuscript.  
This research was funded by [National Key Research and Development Program of China] grant number [SQ2022 YFD2000004].  
Not applicable.  
**Data Availability Statement:** The data used to support the findings of this study are available from the corresponding author upon request.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# Hybrid Engineered Water-Polymer Flooding in Carbonates: A Review of Mechanisms and Case Studies
## 4 Hybrid Engineered Water-Polymer Flooding (EWFF)
### Recovery Mechanisms
#### 4.2.1 Wettability Modification Using Engineered Water  
One of the two governing mechanisms of the hybrid process is the effect of ion-adjusted, low-salinity water, which changes the wettability of carbonate rock from oil-wet or intermediate-wet to water-wet by disturbing the initial equilibrium of the formation of the water-oil-rock system [168]. In this way, the EW plays its part in enhancing the microscopic sweep efficiency via desorption of oil  
Figure 6: Capillary desaturation curves (CDCs) showing the higher microscopic efficiency of LSPF compared to conventional PF based on coreflood studies. VEPF: viscoelastic polymer flooding.  
from the rock. It is important to consider various factors when designing the EW for a particular OWR system and polymer type. For example, the selection of PDIs is very critical and must be decided based on the specific rock type (limestone, chalk, and dolomite) under study. The pH of the injection brine is also a critical parameter that must be considered in the design process. The factors that govern the wettability modification mechanism of EWPF are briefly discussed below.