esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Nano-Morphological Parameters and Technical Indexes of Aged Bitumen  
### Nano-Morphological Parameters Test Results of Aged Bitumen  
The A-90 bitumen samples with different ageing time were tested by AFM. The three-dimensional nanoscopic images of A-90 bitumen under different ageing time are shown in Figure 9.  
With the ageing time prolonging, the number of the bitumen bee-like structure decreases gradually, but the bee-like structures aggregate with each other to form larger bee-like structures. Relevant studies have shown that the existence of asphaltene is an important cause of the formation of the bee-like structure. During the bitumen ageing process, some light components volatilize, some aromatics change into resins, and some resins are converted into asphaltenes. The asphaltenes will move closer together and agglomerate due to the increase in the proportion of asphaltenes, thereby, the number of bee-like structures will reduce and the volume will increase. These phenomena also indicate that ageing can promote the development of the bee-like structure [46; 47; 48; 49]. The relationship between nano-morphological parameters and ageing time is shown in Figure 10.  
Figure 8: The maximum amplitude.  
Figure 10: The relationship between nano-morphological parameters and ageing time. (**a**) the area ratio of bee-like structure; (**b**) the roughness; (**c**) the maximum amplitude.  
Figure 9: The three-dimensional nanoscopic images of A-90 bitumen under different ageing time. (**a**) 0 h; (**b**) 2.5 h; (**c**) 5 h; (**d**) 7.5 h; (**e**) 10 h; (**f**) 15 h; (**g**) 20 h.  
Figure 10 shows that as the ageing time is prolonged, the area ratio of the bee-like structure increases gradually and tends to be stable after ageing time is longer than 15 h. The surface roughness increases with ageing time and tends to be stable after ageing time is longer than 15 h. The maximum amplitude has a similar regular pattern and does not increase after ageing for 10 h. The change of nano-morphological parameters indicates that the bee-like structure has been further developed during the ageing process. It can be concluded that ageing has an effect on the nano-morphology of asphalt. During the ageing of the bitumen, the composition continuous changes. Saturate and aromatic are continuously volatilized and partially converted into the resin, some of which are converted into asphaltenes. Also, asphaltenes aggregate with each other.
# Path Algorithms for Contact Sequence Temporal Graphs +
## 2 Materials and Methods
### Complexity of Algorithms  
In this section, we perform a complexity comparison between OSE, TRG_Wu and TRG_Ours. The time complexities for the OSE algorithms and the TRG_Wu algorithms (except for minhop) are taken from [8]. Note, that in their complexity analysis, [PERSON] et al. [8] assume that \(|V|<|E|\), and therefore, drop all the \(|V|\) terms. We do not make such an assumption and add the \(|V|\) terms to their complexities. As noted earlier, the algorithms for acyclic TRG_Wu are similar to those used for acyclic TRG_Ours and have similar time complexities. Table 1 contains the complexities of the various algorithms. The notation used here is the same as in Section 2.1. \(d_{max}\) is the maximum in-degree among all the original contact sequence temporal graph nodes. Although [8] does not give an algorithm for the min-hop paths problem, their OSE and TRG_Wu algorithms for shortest paths are easily modified to compute min-hop paths. We do not compare with TRG_Zschoche as this data structure requires that all edges in the temporal contact sequence graph have an integer weight and be >0. Further, for contact sequence temporal graphs that satisfy these requirements, TRG_Zschoche is expected to have more vertices and edges than TRG_Wu most of the time. A particular case when the reverse is true is when all edge weights are 1.  
Based on Table 1, we expect that the algorithms for cyclic TRGs will perform better using TRG_Ours than TRG_Wu as our analysis of Section 2.1 shows that \(|V^{\prime}|\) and \(|E^{\prime}|\) will be larger than \(|V^{\prime\prime\prime}|\) and \(|E^{\prime\prime\prime}|\) in most cases. To compare the OSE algorithms and those for cyclic TRG graphs using TRG_Ours, we replace \(|V^{\prime\prime\prime}|\) with its upper bound derived in inequality (3) and \(|E^{\prime\prime\prime}|\) with 2\(|E|\) as per inequality (4). The resulting complexities of TRG_Ours will be \(O(V+3|E|)\) which simplifies to \(O(V+|E|)\) for both the fastest and minhop algorithms. Whether or not TRG_Our performs better than OSE depends on \(|T_{out}(s)|\) and \(d_{max}\). However, we do not expect improvements for the shortest and foremost path algorithms.  
For acyclic TRG graphs, we expect that using TRG_Ours will result in better performance than using TRG_Wu because we expect \(|V^{\prime}|\) and \(|E^{\prime}|\) to be larger than \(|V^{\prime\prime\prime}|\) and \(|E^{\prime\prime\prime}|\) in most cases. We also expect the acyclic TRG algorithms to outperform their counterparts for cyclic TRGs. This is for the algorithms whose asymptotic complexity is the same for cyclic and acyclic graphs, as the latter algorithms have a more negligible overhead. Also, since the asymptotic complexity of the acyclic TRG algorithms is superior to that of the OSE algorithms except for the foremost paths problem, we expect the acyclic TRG algorithms to outperform their OSE counterparts except for the foremost paths problem. The OSE algorithm for the foremost paths problem has very low overhead and we do not expect any improvement from using acyclic TRGs.
## 3 Results
### Results of the First Experimental Phase  
At the end of the first set of tests, after the selection and location of the peak stress points, maps were provided for each driver involved in the test, as shown in Figure 10.  
Figure 9: Subdivision in homogeneous zones of the route for the second experimental phase (QGIS elaboration of Google Maps).  
Three main results were achieved, as follows:  
* Some of the points identified during the tests were stressful for both involved drivers. Even on the basis of two tests only, it was, therefore, possible to highlight road areas for which it would be advisable to investigate the causes of an increase in stress, so as to carry out possible interventions;
* A correlation between stress points and accident points was found. By creating a buffer of 60 m in diameter around the points in which the accident occurred, 50% of the recorded stress points were located within this buffer. On the contrary, considering the same buffer around stress points, the 56% of the points in which the accident occurred were within the defined area. Even considering the limited number of tests, the recorded corresponding values appear as an initial interesting element for the validation of the method. Figures 11 and 12 show two examples of results, whereby incidental points are displayed in red and stress peaks in blue. The buffers highlighted in yellow show the areas in which there was a correspondence between stress condition and accidents, while the various dimensions of red and blue points are associated with the different number of accidents or with the different level of stress encountered (low, medium, or high);
* The data elaboration highlighted the relevant effect related to the presence of construction sites, road works, and detours along the path investigated. In fact, it emerged that many of the points defined as stressful were located in areas with unclear indications of deviations or with bottlenecks due to the presence of road works.  
Figure 11: Example of a route—accidents identified in red, and stress points in blue. Circles indicate the buffer around accidental points (QGIS elaboration of Google Maps).  
Figure 10: Location of the peak stress points (QGIS elaboration of Google Maps).
# Application Research of Multi-Mode Relay in Future Heterogeneous Networks
## 1 Introduction
This makes us consider that emission powers of different kinds of BSs are different  
Figure 1: Multi-mode relay (MMR) running in the modes of picocell BS and femtocell BS. Accordingly, we provide equipment that can produce different powers to cater to different levels of HHWN. Multi-Mode Relay (MMR), in brief, has different modes of emission powers, which is out of ordinary relay at present. We may consider that the base station in the picocell and femtocell, which is at the edge of the macrocell, could be represented as relays, as shown in Figure 1. Because of the different transmission power in the base stations of different layers, the relay must use more than two modes if it wants to integrate the picocell station and the femtocell station. In other words, the relay is not only the picocell BS, but also the femtocell BS. Consequently, the different coverage area of the cell served by MMR leads to the different transmitting power required. Then, unequal relay power problems need to be studied with extreme urgency. Literature [13] indicated the system performance of equal relay power, because the serving nodes are considered in same layer of wireless network. However, in heterogeneous networks, especially in HHWN system, the powers of relay to UE nodes are usually different, since UE nodes are in different layer of HHWN, as mentioned above. Therefore, the main contribution of this paper is that we propose the unequal transmitting power structure in a HHWN system and derive the expression of outage probability in this structure. We also apply our expression to the system-level simulation to research system performance of future heterogeneous networks with unequal relay powers to each UE nodes. The following parts of the paper are organized as follows. Section 2 describes the system model of a heterogeneous hierarchical wireless networks (HHWN) with multi-mode relay system model, defines the two amplify-and-forward (AF) factors for different transmission power of MMR, sets up the comparison of SINRs \(f_{AB}\) and \(f_{BA}\), and analyzes the relationship with the MMR power, which is the key point of performance analysis. In Section 3, we consider the system with unequal relay emission powers situations, get the mathematic computation formulas of outage error probability with channel estimation errors with the conditions of different relay powers and channel state information, and give theoretical analysis. In Section 4, we present the theory computation and simulation demonstrations.
## 4 Experimental Results and Analysis
### Main Results
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Images**} & \multirow{2}{*}{**Method**} & **Execution Time** & \multirow{2}{*}{**Iteration Time**} & **Segmentation** \\  & & **(s)** & & **Accuracy (\%)** \\ \hline \multirow{3}{*}{Original image a} & K-means & 5.324 & 320 & 65.634 \\  & Mean shift & 10.328 & 450 & 70.286 \\  & Our method & 4.473 & 140 & 79.548 \\ \hline \multirow{3}{*}{Original image b} & K-means & 5.475 & 290 & 67.983 \\  & Mean shift & 11.076 & 410 & 71.612 \\  & Our method & 4.469 & 105 & 81.673 \\ \hline \multirow{3}{*}{Original image c} & K-means & 6.038 & 380 & 70.845 \\  & Mean shift & 10.871 & 510 & 76.732 \\  & Our method & 5.679 & 160 & 84.975 \\ \hline \multirow{3}{*}{Original image d} & K-means & 5.804 & 360 & 63.781 \\  & Mean shift & 10.936 & 480 & 67.742 \\ \cline{1-1}  & Our method & 5.026 & 150 & 74.657 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Algorithm performance comparisons. Figure 6: Iteration times of different algorithms.
# Accelerate Incremental TSP Algorithms on Time Evolving Graphs with Partitioning Methods
## 3 Algorithms
### Graph Partitioning Constraints  
In this paper, we have mapped different partitioning methods to our problem definition and implemented them to compare which method can give better results for the TSP algorithm on TEG. To better understand our partitioning methods, we have considered Figure 3 as our example, which is a fully connected graph comprising of six vertices. The adjacency list for the graph is also shown. The three partitioning constraints used in this paper are as follows:  
* Vertex size attribute partitioning (NP-TSP): The vertex size is defined as the total weight of outgoing edges from a vertex. This method focuses on balancing the partitions. The vertices in a partition are added in such a way that the difference between the total weight of each partition is minimum. For example, in Figure 5, the total difference between both the partitions is less than the edge attribute method. This is the baseline partitioning method without any constraint.
* Edge attribute partitioning (EP-TSP): In this method, the graph is partitioned in such a way that the total weight of edges across the partitions will be minimum. The intuition behind this method is to minimize the cost of connecting the sub-tours when the number of partitions is higher. For example, in Figure 5, the total weight of edges across the partition is 320. Therefore, this method can save computation cost for graphs with a higher number of partitions because if the weight across the partition  
Figure 4: The process of combining TSP tours of different partitions. The red color is partition 1 and the blue color is partition 2. The solid line is used to connect intermediate vertices, and the dotted line is used to connect the head vertex of the TSP tour of the red partition to the tail vertex of the tour of the blue partition.  
Figure 3: The left graph is a fully connected six-vertex graph. The right table shows the adjacency matrix to represent the cost of traveling between two vertices.  
is already minimized, then the probability of getting a nearly optimal tour increases. This partitioning strategy avoids a higher cost edge in the partition.
* k-means partitioning (KP-TSP): The k-means method is an iterative partitioning algorithm where k random vertices are placed as a centroid in different partitions. In each partition, the vertices close to centroids are added iteratively. The intuition behind this method is to keep closer vertices together. This method is also useful for a larger graph with a higher number of partitions. In Figure 4, the centroids for both partitions are randomly chosen as 1 and 4, respectively. Partition 1 contains vertices 2 and 5 because they are closer to vertex 1, and partition 2 contains vertices 0 and 3 because they are closer to vertex 4.
## 3 Results
### Accuracy Analyses of Experimental Results
#### 3.2.3 Analysis of the Average Accuracies of the ERP Components  
Table 7 shows the average accuracies of the three ERP components using NN analysis. The average accuracy of using the N2P3 component to discriminate the data from the same electrodes is better than that obtained using the P300 or N200 components. Each electrode gained the same results, as shown in Table 8. As expected, after the computer calculates the results, the average accuracy using the NN analysis is better than that of each electrode as well.  
We also verify whether the difference among average accuracies of three components calculated by the NN technology (Table 7) reaches significance, as shown in Table 9.
## 3 SiN for Coarse Wavelength Division Multiplexing (CWDM) Optical Transceivers in the O-Band  
CWDM is a standard providing a channel spacing of 20 nm that is large enough to tolerate the possible wavelength deviation of the lasers. It is, therefore, an attractive solution to increase the data rate of optical transceivers while using uncooled laser, which limits the power-consumption of the transceiver. However, for a 4-channel CWDM transceiver, the optical bandwidth of the circuit reaches 80 nm, making the waveguide-to-fiber coupling difficult with a Si grating. Thanks to its low optical index, an SiN-based grating presents a larger bandwidth, which is helpful for CWDM circuit testing [38]. In this section, we present a CWDM SiN multiplexer with a low thermal sensitivity and a SiN-based grating coupler for broadband fiber coupling.
# Fatigue Reliability Analysis of Rib-To-Deck Joints Using Test Data and In-Situ Measurements
## 1 Introduction
Apart from the fatigue strength, the vehicle-induced stress ranges are of the same importance in determining fatigue performance. In most codes of practice [20; 21; 22], the stress ranges are represented by an equivalent stress range solved by the deterministic analysis with standard fatigue truck models. Obviously, this type of method is simple and straightforward, but it may cause notable errors in fatigue life prediction since the random feature of fatigue is not explicitly considered [23]. Alternatively, reliability analysis can be applied to predict the fatigue life of welded joints under an assumed target reliability [24], with the consideration of uncertainties in both fatigue strength and action. At the same time, with the rapid improvement in structural health monitoring (SHM) [25], the measurement-based structural analysis gradually becomes available and applicable. For instance, in [26], in-situ monitoring data were utilized to predict the fatigue life of bridge suspenders through reliability analysis. With respect to TEUs, numerical evaluations have been previously conducted on the fatigue performance of rib-to-deck joints in OSDs using TEUs and the joints in OSDs using CUs [27]. The result suggested that the fatigue life of RD joints can be prolonged by 141% to 161% when using TEUs. In the numerical study, the fatigue strength of RD joints was determined after the existing S-N curves and some preliminary results obtained from the limited test data. However, it is worth noting that the numerical fatigue evaluation was performed in a deterministic way to some degree, even if the stress spectra of RD joints were derived based on a stochastic traffic model. The aim of the present study was to evaluate the fatigue performance of rib-to-deck (RD) joints in orthotropic steel decks (OSDs) using TEUs under a reliability-based framework incorporating test data and in-situ measurements. Based on the preliminary experimental studies of 11 full-scale specimens in [10; 18], a series of fatigue tests was first carried out with a total of 7 full-scale specimens. Through the test data of the above 18 specimens, probability-stress-life (P-S-N) curves were established for RD joints through statistical analysis. Meanwhile, a typical OSD bridge was selected as the prototype and the traffic data from in-situ measurements were considered. On this end, a novel reliability-based evaluation approach was proposed to incorporate the fatigue test result and in-situ measurement data. In the approach, numerous studies have been employed to establish the stress spectra of RD joints from the traffic data through large-scale sampling. Based on the proposed approach, fatigue reliability analysis was performed for the RD joint in OSDs using TEUs and the one in OSDs using CUs. With the assumed target reliability, the fatigue life of RD joints in the above two deck systems were predicted and compared, indicating the superiority of TEUs over CUs in OSDs.
## 2 Materials and Methods
### Sensory Profiling  
QDA was employed to describe the sensory characteristic of the CPCO samples according to ISO 13299:2016 [35]. The sensory training was performed by 10 well-selected panelists (eight females and two males, ages 25-42) according to ISO 8586-1:1996 [36]. Assessors were selected, trained, and monitored according to guidelines in this international standard [36]. Selected assessors are chosen for their ability to perform a sensory test. They were asked to identify basic tastes described in ISO 3972 (2011) [37] and participated in the odor recognition test based on ISO 5496 (2006) [38]. Before participating in the sensory analysis, the assessor had gained tremendous experience and knowledge of sensory descriptors for oils and fats products. Moreover, sensory training about specific attributes present in CPCO was conducted before assessments. Panelist training was divided into three phases: (1) lectins generation (5 sessions), (2) training on attributes recognition and understanding definition (15 sessions), and (3) panel performance checking (3 sessions). During the first phase, elections of oils pressed from _Camelina sativa_ seeds were developed by presenting 10 commercial CPCO samples collected from the marketplace. The sensory lexicon of CPCO, including nine attributes, was developed: one taste attribute (bitter), six flavor attributes (overall flavor intensity (OFI), cabbage-like, nutty-like, mustard-like, fruity-like, woody-like), and two attributes of mouth feeling category (astringency and persistence). Descriptors for CPCO, their definitions, and the used reference standards are presented in Table 1.  
During the second training phase, panelists were trained to recognize and quantify the intensity of each attribute with an intensity rating scale from 0-10, where 0--attribute not detected and 10--attribute extremely strong. Reference samples for each attribute listed in Table 1 were presented to the panelist and were crucial for the achievement of consensus regards to the definition. Some reference samples were taken from the ASTM E1627-94:2004 [39] for sensory evaluation of edible oils and fats. Phase 2 was successfully finished when a consensus among panelists was reached. During the last phase, the performance panel was checked (repeatability, reproducibility, discrimination), and only the assessors who showed good repeatability of the results were selected.
# A New Methodology for Estimating Surface Albedo in Heterogeneous Areas from Satellite Imagery
## 3 Materials  
In order to obtain surface albedo results with good spatial resolution, this paper focuses on the use of Landsat 8 satellite data. In addition, this work uses as reference values for comparison: (1) the indirect estimations of surface albedo from satellite products generated through the ABOVE mission, and (2) the direct measurements of the Surface Radiation budget monitoring (SURFAD) network, so that a double comparison of the results of the methodology developed is provided.