esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Continuous Model
### Dimensionless Equation of Motion  
By introducing the following non-dimensional quantities:  
\[\dot{v}=\dfrac{v}{I},\quad\dot{s}=\dfrac{s}{I},\quad\dot{t}=t\Omega,\quad \Omega:=\dfrac{1}{I}\sqrt{\dfrac{T_{0}}{m}} \tag{6}\]  
and parameters:  
\[\varrho^{2}:=\dfrac{E_{b}I_{b}}{I^{2}T_{0}},\quad\Lambda^{2}:=(kl)^{2}\, \dfrac{E_{c}A_{c}}{T_{0}},\quad\dot{\eta}_{\alpha}=\eta_{a}\Omega,\quad\dot{c }_{\alpha\alpha}=c_{\alpha\alpha}\dfrac{\Omega l^{2}}{T_{0}},\quad\ddot{b}_{i }=b_{i}\dfrac{\Omega^{2}l^{3}}{T_{0}},\quad u=\dfrac{U}{\Omega l} \tag{7}\]  
the equations of motion are recast in non-dimensional form:  
\[\begin{split}&\varrho^{2}\left(1+\eta_{b}\partial_{t}\right)v^{ \prime\prime\prime}-\left(1+\eta_{c}\partial_{t}\right)v^{\prime\prime}+ \Lambda^{2}\left(1+\eta_{c}\partial_{t}\right)\int\limits_{-1/2}^{1/2}\!vds+ \dot{v}+\left(c_{e}+b_{1}u\right)\dot{v}+b_{3}\dfrac{1}{u}\dot{v}^{3}+b_{5} \dfrac{1}{u^{3}}\dot{v}^{5}=0\\ & v\left(-1/2,t\right)=0,\quad\varrho^{2}\left(1+\eta_{b} \partial_{t}\right)v^{\prime\prime}\left(-1/2,t\right)=0\\ & v\left(1/2,t\right)=0,\quad\varrho^{2}\left(1+\eta_{b}\partial_{t }\right)v^{\prime\prime}\left(1/2,t\right)=0\end{split} \tag{8}\]In Equation (8), prime and dot denote differentiation with respect to non-dimensional space and time, respectively, and the tilde is dropped for convenience. It is noticed that nonlinearities are only due to aerodynamics.  
The dimensionless parameter \(\Lambda^{2}\) is the well-known Irvine-Caughey parameter [3], accounting for geometric and mechanical properties of the cable. The dimensionless parameter \(\rho^{2}\) (also used in [13, 47, 48] and others), describes the beam-to-cable stiffness ratio. For long bridges, it tends to zero, so that such bridges behave as a cable with an appended mass. However, still in this case, the \(\rho^{2}\) parameter causes the occurrence of boundary layers close to the constraints and the point-loads, where the flexural behavior cannot be neglected. In this paper, attention will be devoted to bridges of medium length, in which the role of the beam is not negligible, as it will be discussed soon. A parametric study about the influence of both parameters on the free dynamic of the bridge is carried out in [18].
## 5 Discussion
### Limitations of This Study  
We acknowledge several limitations and offer future research directions. First, while diverse stakeholders, including end-users, employees, regulators, and technicians, will be in the AT industry, this study focused merely on the perspective of freight transport operators. Second, the time horizon represents the most significant constraint of this study. Because we were looking ahead, a significant amount of our data was derived from external estimations, which could shift as more time passes. Third, since only the expenses that are directly associated with transportation have been explored, a future study should analyze the entire process of logistics, such as warehousing operations, and loading and unloading the goods. Fourth, although the results may change according to the market penetration rates of ATs, this study did not consider this aspect in the cost estimates. Fifth, in a subsequent study, it should also be an objective to differentiate between the various levels of automation of ATs. Sixth, this study focused solely on one mode of transportation (i.e., trucks), while ruling out other transportation modes in logistics, such as rail, air, and marine vehicles. Seventh, since this study conducted a case study in South Korea, the findings based on this analysis with a limited geographic scope may not be generalizable. Eighth, this research disregarded one of the most significant contributors to the operating expenses of freight transportation companies--namely, investments in AT technology. Also, the potential expenditures for new infrastructure that would be necessary to enable ATs were not included in the cost estimation of this study because it is unclear whether such infrastructure would be required and what precise specifications and costs should be included in the calculations. Even more critically, the rebound effect may very well reverse the gains in cost-efficiency that have been achieved. For instance, major employment losses may result, and in level 4 automation, the drivers' responsibilities are minimized to include just straightforward activities. Nevertheless, we did not consider the impact of these adverse effects on the TCO estimation.
## 5 Summary and Conclusions  
A comprehensive analysis was conducted to understand the direct impact on NovAtel receivers and their positioning engines under scintillation. The events of 2023-2024 were studied by characterizing scintillation using the amplitude scintillation index (S4) values in an equatorial region. Furthermore, the scintillation effect on the receivers was assessed through the analysis of C/N0, lock breaks, double differences and other indicators. Substantial data were collected at 20\({}^{\circ}\) latitude, where high solar activity occurs, enabling the analysis of the positioning performance of RTK and PPP.  
The experimental results show that the lower-frequency GNSS signals are impacted more than those of a higher frequency. This is observed in the loss of tracking lock statistics and depth of the fade. It was also observed that the amplitude scintillation intensity is higher than the phase scintillation. It was also discovered that the during scintillation, the ionosphere delay varies with higher magnitude compared to during calm ionosphere conditions. The experiments also revealed the superior performance of PPP compared to RTK under scintillation.  
[PERSON] processed the data sets; [PERSON], A.B. and S.K. contributed to, read and agreed to the published version of the manuscript. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
Data availability StatementData are not available publicly.  
Authors [PERSON], [PERSON] and [PERSON] were employed by Hexagon I NovAtel. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest.
# Policy Similarity Measure for Two-Player Zero-Sum Games
## 5 Experiments
### Ablation Studies  
To investigate the individual contributions of the Gaussian and cosine similarity components in our proposed PSM-PSRO framework, we perform an ablation study by systematically removing each of these components. Specifically, we evaluate two variants of our approach: PSM-PSRO w/o. cosine, where the cosine similarity component is removed, and PSM-PSRO w/o. Gaussian, where the Gaussian similarity component is excluded.  
As illustrated in Figures 4a and 6, both PSM-PSRO w/o. Gaussian and PSM-PSRO w/o. cosine exhibit higher exploitability than the full method, underscoring the critical role of each similarity measure in mitigating exploitability. Figures 2a and 4b further demonstrate that removing either similarity component increases PSM values, indicating a rise in redundant policies within the population. Simultaneously, Figure 2b shows that the absence of either similarity component results in a decline in UDM values, reflecting a relative reduction in overall policy diversity. Moreover, the heatmaps in Figures 7 and 8 reveal that the full PSM-PSRO consistently yields a more heterogeneous and well-distributed policy population, whereas the removal of either similarity measure leads to greater policy clustering.  
Overall, these findings highlight that Gaussian and cosine similarity capture complementary aspects of policy redundancy, and their combination is essential for ensuring a well-distributed and strategically diverse policy population. While each component individually improves diversity to some extent, only their joint application effectively mitigates both magnitude- and direction-based redundancy, leading to lower exploitability and a more diverse population.  
Figure 6: Non-transitive mixture model ablation experiment: exploration trajectories during training. The final exploitability \(\times 100\) (Exp) for each method is reported at the bottom. The bold values in the figure represent the best-performing results.  
Figure 7: Non-transitive mixture model ablation experiment: similarity matrix heatmaps of policy populations after 50 PSRO iterations. The heatmaps display the pairwise similarity between policies, with red indicating higher similarity.
## 4 Materials and Test Methods  
### Materials  
The constituents utilized in this investigation comprised (1) cement, (2) aggregates, (3) water, (4) superplasticizer, and (5) silica fume. Type II cement, sourced from the Hegmatan Cement Factory (Hamadan, Iran) and conforming to the ASTM C150 [56] standard, was utilized. The properties of the employed cement are delineated in Table 1. The silica fume (SF) was produced by the Ferroalloys Company (Tehran, Iran) according to the ASTM C1240 [57] standard. The specifications of the SF are presented in Table 2. River sand, which was sieved through #30 mesh (finer than 600 microns) in compliance with ASTM C778 [58], was utilized in the fabrication of the designated concrete. Table 3 delineates the characteristics of the sand employed. The superplasticizer, denoted as M200R and manufactured by Shimisakhteman Company (Tehran, Iran), conformed to the ASTM C494 [59] standard. The properties of the superplasticizer are listed in Table 4.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multicolumn{2}{c}{**Chemical Properties**} & \multicolumn{3}{c}{**Physical Properties**} \\ \hline SiO\({}_{2}\) & 21.27 & \multirow{2}{*}{Compressive strength (MPa)} & 3 days & 20.1 \\ \cline{1-1} \cline{5-5} Al\({}_{2}\)O\({}_{3}\) & 1.12 & & 7 days & 28.2 \\ \cline{1-1} \cline{5-5} Fe\({}_{2}\)O\({}_{3}\) & 4.03 & & 28 days & 40.3 \\ \cline{1-1} \cline{5-5} CaO & 62.95 & \multirow{2}{*}{Setting time (min)} & Initial & 154 \\ \cline{1-1} \cline{5-5} MgO & 1.55 & & Final & 195 \\ \cline{1-1} \cline{5-5} SO\({}_{3}\) & 2.26 & \multirow{2}{*}{Longitudinal expansion} & \multirow{2}{*}{1.5 mm-0.08\%} \\ \cline{1-1} \cline{5-5} Na\({}_{2}\)O & 0.49 & & & \\ \cline{1-1} \cline{5-5} K\({}_{2}\)O & 0.65 & \multirow{2}{*}{Specific surface (cm\({}^{2}\)/gr)} & \multirow{2}{*}{2910} \\ \cline{1-1} \cline{5-5} C\({}_{3}\)A & 6.30 & & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Chemical and physical characteristics of the cement.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multicolumn{2}{c}{**Chemical Properties**} & \multicolumn{3}{c}{**Physical Properties**} \\ \hline SiO\({}_{2}\) & 89.26 & Physical state & amorphous \\ \hline Al\({}_{2}\)O\({}_{3}\) & 4.95 & & \\ \hline Fe\({}_{2}\)O\({}_{3}\) & 1.8 & Particle size (typical) & \textless{1} \(\mu\)m \\ \hline CaO & 0.87 & & \\ \hline MgO & 1.1 & Color & Light gray \\ \hline Na\({}_{2}\)O & 0.5 & & \\ \hline K\({}_{2}\)O & 0.66 & Specific surface (cm\({}^{2}\)/gr) & 21,000 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Chemical and physical characteristics of the silica fume.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multicolumn{2}{c}{**Sieve Size**} & \multirow{2}{*}{**ASTM C778 [58]**} & \multirow{2}{*}{**This Study**} \\ \hline
**mm** & **No.** & & \\ \hline
1.18 & 16 & 100 & 100 \\ \hline
0.6 & 30 & 100 & 96–100 \\ \hline
0.425 & 40 & 67.5 & 65–75 \\ \hline
0.3 & 50 & 28 & 20–30 \\ \hline
0.15 & 100 & 3.5 & 0–4 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Sand grading.
## 3 Results
### The Results of Instrumental Color Measurement and Nitrosylmyoglobin Content
In turn, SBC was characterized by the slightly higher lightness at 10 and 20 days compared to the SK sample. The same redness values (a*) was maintained throughout the time in all batches (SK (7.78-9.34), SCH1 (8.08-9.97), SCH2 (7.73-10.09), SBC1 (5.73-7.69), and SBC2 (4.42-6.47)). The sausages with the addition of black cumin presented the lowest a* at any of the days, whereas the sausages elaborated with chia seeds had the greatest redness value. Even the control sample had similar value of a* parameter compared to the sausages with chia seeds. Regarding yellowness (b*), this parameter decreased progressively with time in all samples, except for SCH2, SBC1, and SBC2, where they showed the same degree of b* from days 20 to 30 (SK (9.27-5.01), SCH1 (10.13-5.48), SCH2 (10.64-6.05), SBC1 (7.95-4.29), and SBC2 (7.55-3.91)). In case of the b* parameter, the same trend as for a* parameter was observed. The SBC samples showed the lowest b* values, while samples with chia seed were characterized by the highest b* color parameter values. The color differences (\(\Delta\)E) between control and test samples showed that the greatest color changes took place at Day 20. At this day, the color changes for the samples ranged from 6.91 to 11.37. The greatest color changes were shown between the control and SCH2 sample. The values \(\Delta\)E higher than 5 mean that an observer notices two different colors for samples. The content of nitrosylmyoglobin increased with time, leading to the greatest amount on the last day (Table 2) with the exception of the SCH2 samples. The samples with chia seed were characterized by the highest content of nitrosylmyoglobin at Day 20 (45.68 mg kg\({}^{-1}\)). No differences among the sausages were observed during the first day. SK sample showed the lowest content of this compound on any of the days studied (11.74, 13.97, 25.81, and 28.56 mg kg\({}^{-1}\) at 1, 10, 20, and 30 days), whereas the SBC samples showed the highest values. Slightly more concentration was reached in the sausages with 2% of black cumin seeds (18.17 vs. 16.57, 44.03 vs. 39.34, 62.35 s. 52.49, and 66.55 vs. 58.24 mg kg\({}^{-1}\) at 1, 10, 20, and 30 days).
# Conserved Plastid Genomes of _Pourthiaea_ Trees: Comparative Analyses and Phylogenetic Relationship
## 4 Discussion
### Characteristics and Comparison of the Pourthiaea Plastomes
The plastome sequences of the 13 _Pourthiaea_ species showed low divergence in general, as indicated by mVISTA, Pi, and genetic distance analyses, similar to other woody species genera [63; 65; 78]. The three most divergent non-coding regions (_trn_H-GUG_-_psbA_, _psbZ-trn_G-GCC, and _trn_R-UCU-_atp_A) were identified as the mutational hotspots. Among them, _trn_H-GUG_-_psbA_ is the universal DNA barcode of land plants [79]. The _psbZ-trn_G-GCC and _trn_R-UCU-_atp_A were identified as the mutational hotspots in the genera of _Quercus_ [63], _Sanciula_ [77], _Rehmannia_ [80], _Argentina_ [81], and _Castanea_ [82]. Therefore, these regions could be good candidate DNA barcodes to discriminate _Pourthiaea_ species. A study based on 101 complete plastomes showed that the large single-copy (LSC) region can serve as a highly effective DNA marker for accurately identifying medicinal _Dendrobium_ species [83]. We may be able to collect more plastomes of _Pourthiaea_ species in the future to determine the efficiency of LSC regions in the species delimitation of this genus. In short, our findings offered a precious reference for developing DNA barcodes for _Pourthiaea_. The pattern of dN/dS is a very crucial marker in gene evolution studies. The dN/dS \(<1\) represents purifying selection (especially less than 0.5), dN/dS = 1 represents neutral evolution, and dN/dS \(>1\) represents positive selection [84]. The great mass of protein-coding genes in our study held low dN/dS values, suggesting a strong purifying selection and the conservatism of plastid protein-coding genes in _Pourthiaea_. We identified that the _rbc_L gene was under positive selection in _Pourthiaea_. The _rbc_L gene is essential for photosynthesis as it encodes the large subunit of the RuBisCO [23; 85]. Positive selection on this gene has been observed in other plant groups, for instance Lamiales [86], _Amphilophium_ [87], and tribe Selineae [71]. In fact, compared with aquatic plants, bacteria, and algae, positive selection on the _rb_CL gene is often observed in terrestrial plants [88]. This may be because the thermal and water regime of the aquatic habitat is more stable, while the habitat of terrestrial plants is more variable, and therefore requires positive selection to regulate the activity of the RuBisCO [89]. The identification of positive selection on the _rb_CL gene suggests that _Pourthiaea_ may have undergone adaptive changes, which warrants further investigation to understand their relation to environmental pressures.
## 5 Non-Iterative BER-Driven DDM Synthesis
### Results: Synthesis Example  
Let us consider the compact multimode antenna proposed in [37]. This radiating structure can perform the functions of a four-element array while generating a radiation pattern with a single maximum that can be steered freely in any direction in the XY plane. A drawback of this antenna is the high side lobes of the radiation pattern, which may compromise security in those observation angles (Figure 7). This performance can be improved with DDM.  
A QPSK modulation will be transmitted along the secure observation angle \(\phi_{0}=180^{\circ}\) with BER(\(180^{\circ}\)) = 3.43 \(\times\) 10\({}^{-5}\). Figure 8 depicts the typical curve of BER as a function of \(SNR\) for a QPSK modulation under the assumption of AWGN and conventional Gray coding [36], so we determine \(SNR_{av}(180^{\circ})\)= 12 dB and, considering (3), \(N_{AWGN}=-12\) dB.  
In order to improve the security of the transmission, let us suppose that we are interested in lowering BER in side lobes (BER(\(111^{\circ}\)) \(\approx\) 10\({}^{-1}\)) and narrowing the information beam width (BER(\(190^{\circ}\)) \(\approx\) 10\({}^{-3}\)). From Figure 8, we obtain \(SNR_{av}(111^{\circ})\)= 2 dB and \(SNR_{av}(190^{\circ})\)= 9.8 dB, and, using (12) the power of the artificial noise to be injected gives \(rp_{av\_W}(111^{\circ})=-4.5\) dB and \(rp_{av\_W}(190^{\circ})=-16.3\) dB. In this example, conditions (13) and (14) are satisfied in no observation angle; therefore, the total noise will approximately behave as a zero mean Gaussian distribution even if the artificial noise is non-Gaussian.  
Figure 9 shows the interference radiation patterns generated with the antenna weights \(\mathbf{C}_{1}\) and \(\mathbf{C}_{2}\) also interfering the secure observation angle (\(180^{\circ}\)). Therefore, these antenna weights need to be modified to steer a null of the interference radiation pattern along 180\({}^{\circ}\). The interference radiation patterns obtained using the antenna weights \(\mathbf{A}_{1}\) and \(\mathbf{A}_{2}\) are  
also plotted in Figure 9. It must be noted that, after (16), we find a null at 180\({}^{\circ}\), but the interference pattern maximum is not necessarily at 111\({}^{\circ}\) (190\({}^{\circ}\)). Next, we apply (18) to obtain \(G_{1}=5.1\) dB and \(G_{2}=-1.6\) dB, and finally, we determine \(\textbf{B}_{mp\_DDM}\) through (17).  
Figure 8: BER for QPSK modulation and Gray coding as a function of SNR.  
Figure 7: Compact antenna of [37]. QPSK modulation, \(\phi_{0}=180^{\circ}\), SNR(\(\phi_{0}\)) = 12 dB, \(PE_{DDM}\) = 100% (conventional). Average radiation pattern (**a**) and BER (**b**) in the XY plane.  
The average radiation patterns obtained after our synthesis and the BER computed with our approach compared to the BER evaluated through the transmission of \(10^{6}\) symbols can be found in Figure 10.
# Rolling Bearing Incipient Fault Detection Based on a Multi-Resolution Singular Value Decomposition
## 1 Introduction
The background noise, the harmonic interference, and the periodic shock vibration have different singular value characteristics after the singular value decomposition (SVD). In contrast to the above frequency-separation-based methods, a new SVD-based preprocessing method, that is, multi-resolution singular value decomposition (MRSVD) [46], is introduced in this study with the objective of extracting the periodic shock vibration from the raw vibration signal which is acquired at the incipient failure stage of a rolling bearing. Multi-resolution singular value decomposition (MRSVD) is a new signal decomposition method that has been proposed in recent years. Inspired by the multi-resolution analysis idea of wavelet analysis and the construction principle of matrix dichotomy recursion, MRSVD decomposes the analytic signal into a number of approximate and detail signals with different resolutions via the SVD method. As shown in the theoretical analysis in Section 3.1, in the MRSVD decomposition results of a mixed-signal that contains strong background noise, harmonic disturbances, and a periodic shock vibration, the first detail signal is mainly composed of noise, and the last approximate signal is mainly composed of harmonic disturbances. Therefore, the MRSVD method is used to preprocess the rolling bearing vibration signal to remove the background noise signal and the harmonic interference signal. The simulation analysis and the application examples show that the MRSVD method can effectively extract the periodic impact components caused by a bearing fault, even under the influence of strong background noise and harmonic disturbances. Furthermore, the proposed method does not require any prior knowledge about the resonance band. Hence, the MRSVD method has a good application prospect for the initial fault detection of a rolling bearing.
# A New Road Damage Detection Baseline with Attention Learning
## 3 China Road Damage Detection Dataset  
Existing datasets can be divided into wide-view and top-view according to their shooting perspective. Damage captured from top-view images has no distortion and is easier to recognize. However, collecting top-view images needs UAVs and other professional equipment. This limits it to single acquisition areas, which makes it impossible for it to access the intelligent road damage detection system on a large scale. It may be more suitable for dangerous or inaccessible sections. Wide-view images can be easily obtained by smartphones or ordinary cameras. The shooting angle of wide-view images is free and changeable, and such images have obvious perspective relationships. Moreover, this kind of image usually contains interference items, such as buildings, vehicles or pedestrians, which makes it more difficult to detect road damage compared to top-view images. These datasets, no matter what perspective, have greatly fostered the development of ADRD.  
However, the published parts of these datasets are collected from foreign roads. Further, there is a variety of data distribution within them due differences in acquisition equipment and shooting perspectives. This makes it difficult to establish a scientific cross-domain bridge by transfer learning. In order to solve these problems, this paper puts forward a CNRDD dataset that may become the standard for road damage detection. It adopts unified collection and annotation according to the actual situation of roads in China. This can facilitate subsequent expansion and cross-domain transfer learning, which will help the model improve the generalization ability for road damage detection.  
The CNRDD dataset has the following three advantages over existing datasets: (1) Data collection adopts a professional onboard camera, and the image size is unified, which is conducive to the access of ADRD to intelligent road maintenance system in the future. (2) Classification meets the evaluation standards of China's highway technical status, and the damage categories are richer, which can provide data support for the application and promotion of ADRD algorithms. (3) The dataset has high damage density in single images and provides damage degree classification, which is more challenging for the damage detection algorithm. The specific introduction of dataset classification statistics and evaluation indicators is as follows.