esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### Intercomparison between UTOPIA and NOAH Simulations Initialized with GLDAS
#### 3.3.1 Net Radiation (RNET)  
The values of RNET estimated by NOAH (Tables 12-14 and Supplementary Figures S9-S11) show daily mean and median values larger than those evaluated by UTOPIA (by about 40-50 W m\({}^{-2}\)). In addition, maxima and minima are higher for NOAH (by about 30-50 W m\({}^{-2}\) the former and 20-30 W m\({}^{-2}\) the latter). In previous section EXP1,2,3a show that, compared with the observations, UTOPIA maxima are too low, while minima are consistent, with discrepancies of a similar magnitude, and comparable with the accuracy of solar radiation measurements. Here, UTOPIA and NOAH values differ by about 20-30 W m\({}^{-2}\), the former being lower than the latter, for both GLDAS2.0 and GLDAS2.1. Regarding value distribution, the most frequent for NOAH are in the class 150-200 W m\({}^{-2}\), while for UTOPIA they are around 0 W m\({}^{-2}\). As a conclusion, it seems that both models (UTOPIA and NOAH) can give a sufficiently good representation of the net radiation (NOAH overestimating the minima, and UTOPIA underestimating the maxima). We also notice that the initializations with GLDAS-2.0 (EXP3b and EXP5) show the smallest ranges for both models, because minima are higher and maxima smaller, and in EXP5 minima are never negative in all sites, while observed minima in vineyards at CO (Table 13) are negative and correctly captured by UTOPIA (EXP1,2,3a). Thus, it seems that GLDAS-2.1 gives more correct boundary conditions for RNET to LSMs.
# Real-Time Indoor Positioning Approach Using iBeacons and Smartphone Sensors
## 4 Experiment
The accuracy is between 2 and 4 m. Similar to the results in Table 1, the main error occurs in the heading direction (the column 'RMSE X(m)'). A conclusion of the experimental results is that the orientation filter cannot independently improve location accuracy of the PDR. Although it can partially improve the direction and location estimates, it cannot reduce systematic errors. Instead, the proposed fusion positioning workflow can curb systematic errors.
# Named Data Networking Based Disaster Response Support System over Edge Computing Infrastructure +
## 4 Implementation
### NDN Network Deployment  
NDN routers are deployed using pre-configured yaml files. This information helps NDN routers can automatically create NDN connections with other NDN nodes in the network. An example of an NDN router's yaml file is shown in Figure 10. In this file, information about the deployed NDN router's name (ALIAS, SITENAME), neighbor nodes (NEIGHBOR_IP, NEIGHBOR_HOSTNAME, NEIGHBOR_SITE_ROUTE), pre-advertised prefixes (AD_PREFIXE), NLRS configuration (NLSR_LIFETIME, NLSR_HELLOTIME, NLSR_FIRST_HELLOTIME), Delay-Tolerant Networking [33] (DTN) configuration (DTN_SUPPORT, DTN_DEFAULT_PUREFIX) and targeted edge node (kubernete.io/hostname) is  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Entity** & **Hardware** & **Software** \\ \hline Cloudcore & CPU: Intel® Xeon 2.4 GHz, RAM: 256 GB, HDD: 1.8 TB & Ubuntu server 18.04 \\  & CPU: Intel® Xeon 2.4 GHz, KubeEdge Cloudcore v1.4 \\  & RAM: 256 GB, HDD: 1.8 TB & NDN, NFD v0.6.5 \\  & & NLSR v0.5 \\ \hline Normal Edgecore & CPU: Intel® Xeon 1.5 GHz, RAM: 64 GB, HDD: 440 GB & NDNcox, NFD v0.6.5 \\  & & NLSR v0.5 \\  & & lbrdtn v1.0.1 \\ \hline Border Edgecore & CPU: Intel® Core i3.17 GHz, RAM: 8 GB, HDD: 120 GB & Ubuntu 16.04 \\  & CPU: Intel® Dual Core, RAM: & NDNcox, NFD v0.6.5 \\  & 8 GB, HDD: 128 GB & NLSR v0.5 \\  & & lbrdtn v1.0.1 \\ \hline End-user & CPU: Intel® Dual Core, RAM: 8 GB, HDD: 128 GB & NDNcox, NFD v0.6.5 \\  & & NLSR v0.5 \\  & & lbrdtn v1.0.1 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Detailed implementation configuration.  
Figure 9: Cross-regional NDN network topology in the implementation.  
defined in environment variables. Based on these variables, once being deployed, NDN routers can automatically start up and link with their neighbor nodes to create NDN network between them. Pre-advertised prefixes will be advertised by NLSR engine so that information can be delivered immediately through the deployed routers. Moreover, NDN mobility handling and edge device management software are pre-installed inside the image.
## 7 Applications
### Google Maps Driving Directions  
As discussed in Section 1, we apply our results to the Google Maps Driving Directions application. Note that the evaluation metric for balanced partitioning of the world graph is the expected percentage of cross-shard queries over the total number of queries. More specifically, this objective function can be captured as follows: we first estimate the number of times each edge of graph may be part of the shortest path (or the driving direction) from the source to destination across all the query traffic. This produces an edge-weighted graph in which the weight of each edge is proportional to the number of times we expect this edge appearing in a driving direction and our goal is to partition the graph into a small number of pieces and minimize the total weight of the edges cut. We can estimate edge weights based on historical data and use it as a proxy for the number of times the edge appears on a driving direction on the real data. This objective is aligned with minimizing the weighted cut and we can apply our algorithms to solve this problem.  
Before deciding about our live experiments, we realized it might be suitable to use an imbalance factor in dividing the graph and as a result, we first examined the best imbalance factor for our cut-optimization technique. The result of this study is summarized in Figure 10. In particular, we observe that we can reduce cross-shard queries by 21% when increasing the imbalance factor from 0% to 10%.  
The two methods that we examined via live experiments were (i) a baseline approach based on the Hilbert-curve embedding and (ii) one method based on applying our cut-optimization postprocessing techniques. Note that both these algorithms first compute an embedding of nodes into a line, which results in a much simpler system to identify the corresponding shards for the source and destination of each query at serving time. Finally, by running live experiments on the real traffic, we observe that the number of multi-sharded queries from our cut-optimization techniques is almost 40% less than the number of multi-sharded queries compared to the naive Hilbert embedding technique.  
\begin{table}
\begin{tabular}{l c c c c} \hline \hline
**Graph** & \(|\mathbf{V}|\) & \(|E|\) & **Max Degree** & **Running Time** \\ \hline RMAT 20 & 650 K & 31 M & 65 K & 100\% \\ RMAT 22 & 2.4 M & 130 M & 160 K & 110\% \\ RMAT 24 & 8.9 M & 525 M & 400 K & 133\% \\ RMAT 26 & 32.8 M & 2.1 B & 1 M & 160\% \\ RMAT 28 & 120 M & 8.5 B & 2.5 M & 402\% \\ \hline \hline \end{tabular}
\end{table}
Table 5: General statistics (size) about the RMAT graphs as well as the relative running times of balanced-partitioning algorithm on these graphs.
# Effect of Post-Weld Heat Treatment on the Solid-State Diffusion Bonding of 6061 Aluminum Alloy
## 4 Conclusions  
This paper has presented the feasibility of solid-state diffusion bonding of AA 6061 joints and the effects of PWHT on the mechanical properties and fracture mechanisms of the bonded AA 6061 specimens. The morphological analysis and the evolution tendency of the corresponding joint strengths on the samples diffusion bonded under various bonding conditions revealed that the two dominant factors were bonding temperature and holding time, in close similarity to the solid solution type of diffusion bonding in metals. The average bonding shear strength could reach 71.2 MPa at 510 \({}^{\circ}\)C for 240 min, which is comparable to the strengths achieved by brazing or TLP bonding. The highest joint shear strengths were 89.15 MPa at bonding temperature of 500 \({}^{\circ}\)C for 240 min. After T6 heat treatment, the average bonding shear strengths of the AA6061 joint bonded at 500 and 530 \({}^{\circ}\)C for 240 min increased from 70.31 to 101.04 MPa and 64.41 to 105.11 MPa, respectively. The SEM fractographs revealed morphological differences in the fracture surfaces of strong and weak joints, in which elongated dimples were indications of excellent bonding. Furthermore, PWHT of the diffusion bonded AA 6061 specimens enhanced the joint strengths by around 40-50%. This result can be mainly attributed to T6-PWHT as the favorable interdiffusion condition provided by the artificial aging of T6 could eliminate the cracks that resulted from the previous quenching process (T4), and the lower aging temperature also led to a smaller grain size and finer precipitates within the AA 6061 material, as confirmed by fractography analysis.  
Conceptualization, C.-H.C., Y.-K.S., Y.-C.L., S.-Y.C. and T.-H.C.; data curation, Y.-K.S., Y.-C.L. and S.-Y.C.; investigation, C.-H.C., Y.-K.S. and Y.-C.L.; methodology, Y.-K.S. and T.-H.C.; writing--original draft, C.-H.C., Y.-K.S. and T.-H.C.; writing--review and editing, C.-H.C., S.-Y.C. and T.-H.C. All authors have read and agreed to the published version of the manuscript.  
This study was sponsored by the industrial and academic cooperation program of Plus Metal Tech., Co. LTD. and the Ministry of Science and Technology, Taiwan, under Grant No. MOST 109-2622-E-002-030.  
Not applicable.  
The authors declare no conflict of interest.
# Actuating Performance Analysis of a New Smart Aggregate Using Piezoceramic Stack
###### Abstract  
A new type of smart aggregate using piezoceramic stack (SAPS) was developed for improved output, as compared with a conventional smart aggregate with a single piezoceramic patch. Due to the better output, the proposed smart aggregate is preferred where the attenuating effect is strong. In this research, lead zirconate titanate (PZT) material in the form of discs was used due to its strong piezoelectric performance. For analysis, the proposed SAPS was simplified to a one-dimensional axial model to investigate its electromechanical and displacement output characteristics, and an experimental setup was designed to verify the simplified model. Moreover, the influence of the structural parameters, including the number of the PZT discs, the dimensions of the PZT disc, protective shell, and copper lids, and the elastic modulus of the epoxy on the electromechanical and displacement output performance of SAPSs, were numerically studied by using the one-dimensional axial model. The numerical analysis results indicate that the structural dimension of the PZT discs has a greater effect on the electromechanical performance of SAPSs than that of the protective shell and copper lids. Moreover, the results show that the number of the PZT discs and the outer diameter of the protective shell have a much greater influence on the displacement output of SAPSs than other parameters. The analysis results of SAPSs with different elastic moduli of the epoxy demonstrate that the SAPSs' first resonance frequency, first electromechanical coupling factor, and displacement output change less than 1.79% when the epoxy's elastic modulus changes from 1.28 GPa to 5.12 GPa, which indicates that the elastic modulus of the epoxy has a limited influence on the property of SAPSs, and it will be helpful for their fabrication. This study provides an approach to increasing the output of SAPS and also develops a method to design the structure of SAPSs.  
s +
Footnote †: journal: Applied Sciences  
amt aggregate; smart aggregate using piezoceramic stack (SAPS); lead zirconate titanate (PZT) disc; transducers
## 3 Graph to Metric Space Transformation
### Graph to Metric Space Algorithm
#### 3.1.2 Function Selection  
The function selection module determines the metric for a pair of nodes. The function selector \(\phi\) converts a similarity function (Pearson coefficient (\(\sigma_{PC}\)), Spacerman coefficient (\(\sigma_{SC}\)) or cosine similarity (\(\sigma_{CS}\))) into a distance matrix. In general, the similarity function satisfies the positivity and similarity condition of the metric, but not the triangle inequality. \(\phi\) is a metric-preserving (\(\phi(d(x_{i},x_{j})=d_{\phi}(x_{i},x_{j}))\), concave and monotonically-increasing function. The three conditions above are referred to as the chord condition. The \(\phi\) function is chosen to have minimum internal area with the chord.
# Multi-Temporal Sentinel-1 Backscatter and Coherence for Rainforest Mapping
## 2 Background
### Temporal Decorrelation Model  
The temporal decorrelation quantifies the amount of decorrelation between the interferometric pair caused by changes on ground, occurred during the time span between the acquisitions. Since the effects on repeat-pass SAR data may impair the magnitude of the complex coherence, in the last decade different analytical formulations have been proposed to model temporal changes, due, for example, to wind-induced decorrelation or biological growth of vegetation. Such models take into account Brownian motion and birth-and-death processes [11; 12; 13]. In [7], a minimum mean square error analysis based on Sentinel-1 experimental observations suggested the development of an improved temporal decorrelation model, by combining the concepts of long-term coherence [14] together with the squaring of the term in the exponential decay, proposed in [12]. Hence, the temporal decorrelation \(\rho_{\text{temp}}(t)\) can be expressed as:  
\[\rho_{\text{temp}}(t)=\left(1-\rho_{\text{LT}}\right)e^{-\left(\frac{t}{ \tau}\right)^{2}}+\rho_{\text{LT}}, \tag{1}\]where \(\tau\) is defined as the temporal decorrelation constant, a factor regulating the exponential decay, and \(\rho_{\rm LT}\) is the long-term coherence, representing the asymptotic value of the coherence after a time much greater than the constellation revisit time.
# A Review of Electrochemical Sensors for the Detection of Glyated Hemoglobin
###### Abstract  
Glyocated hemoglobin (HbA1c) is the gold standard for measuring glucose levels in the diagnosis of diabetes due to the excellent stability and reliability of this biomarker. HbA1c is a stable glycated protein formed by the reaction of glucose with hemoglobin (Hb) in red blood cells, which reflects average glucose levels over a period of two to three months without suffering from the disturbance of the outside environment. A number of simple, high-efficiency, and sensitive electrochemical sensors have been developed for the detection of HbA1c. This review aims to highlight current methods and trends in electrochemistry for HbA1c monitoring. The target analytes of electrochemical HbA1c sensors are usually HbA1c or fructosyl valine/fructosyl valine histidine (FV/FVH, the hydrolyzed product of HbA1c). When HbA1c is the target analyte, a sensor works to selectively bind to specific HbA1c regions and then determines the concentration of HbA1c through the quantitative transformation of weak electrical signals such as current, potential, and impedance. When FV/FVH is the target analyte, a sensor is used to indirectly determine HbA1c by detecting FV/FVH when it is hydrolyzed by fructosyl amino acid oxidase (FAO), fructosyl peptide oxidase (FPOX), or a molecularly imprinted catalyst (MIC). Then, a current proportional to the concentration of HbA1c can be produced. In this paper, we review a variety of representative electrochemical HbA1c sensors developed in recent years and elaborate on their operational principles, performance, and promising future clinical applications.  
electrochemical sensor; HbA1c sensor; fructosyl valine sensor; diabetes; cyclic voltammetry; electrochemical impedance spectroscopy +
Footnote †: journal: Physics Letters B
# Path Planning Strategy for Implementing a Machine Control System in Grader Operations
## 3 Path Generation Algorithm for Graders
### Work Path Generation Algorithm
#### 3.3.5 Create Work Path  
The work path was generated using these values after determining the repeated rate and the effective width. The work path is created by translating the list of coordinates for the outer boundary lines. When the list of coordinates for the outer boundary lines is considered, with the left side as df1 and the right side as df2 based on the direction of the road, the list of coordinates (x1, y1) is stored in df1 and the list of coordinates (x2, y2) is stored in df2. Next, a direction vector V is calculated from the first coordinate of df1 to the first coordinate of df2 (see Figure 11), and the unit vector U is computed:  
\[\overset{\rightarrow}{V}=(x2-x1,y2-y1) \tag{3}\]  
Figure 10: Work section and set work direction.  
\[\overset{\rightarrow}{U}=\overset{\rightarrow}{V}/|\overset{\rightarrow}{V}| \tag{4}\]  
Next, the coordinates (x1, y1) are translated in the direction of unit vector \(U\). In the first translation, the coordinates were shifted by half the blade width, and in subsequent translations, they were shifted by the effective width:  
\[\text{Direction and distance of the first parallel shift}:\overset{\rightarrow}{U}\times W_{a} \tag{5}\]  
\[\text{Direction and distance of subsequent parallel shift}:\overset{\rightarrow}{U}\times W_{e} \tag{6}\]  
Using the same method as the parallel shift, all the coordinates of df1 generate the path. Finally, by deciding and applying the line-changing method, a grader's work path was created.
# Applications of Cement-Based Smart Composites to Civil Structural Health Monitoring: A Review
## 4 Discussion and Open Issues
### Fabrication  
Several dispersion procedures depending on the filler typology have been introduced. For CFs and SFs, as well as CB, mechanical stirring is generally applied. Conversely, if CNTs are used as conductive filler, sonication or ultrasonication are systematically carried out often coupled with the use of surfactant (LS or SBDS, in particular). Therefore, CNT-based CSCs are typically of limited dimensions, since the adoption of methods such as sonication or chemical reaction cannot be performed at large scale due to practical limits as well as economic reasons, whereas large scale CSCs can be obtained by using fiber-shaped filler. Acid functionalized fillers in CSCs have been also investigated by some Authors, showing high sensing performance. Hybrid solutions given by the combination of different filler types provide several benefits in terms of reduction of dispersion complexity; moreover, the use of additives, such as fly ash or silica fume, allows to reduce internal pores. Cement paste is typically used as a matrix due to the easier filler dispersion and lower concentration of conductive material with respect to mortar and concrete. The latter is adopted only if fiber-shaped filler is used. w/c ratio values range between 0.33 and 0.50, depending on filler type and additives.  
Appropriate spacing of electrodes must be ensured in order to obtain accurate resistivity measurements. In this regard, a minimum value commonly assumed for the distance between two consecutive electrodes is 5 mm. About electrode material and installation, different options have been investigated (copper or steel, embedded or externally pasted) but negligible influence on CSCs performance has been reported. Less systematic studies focused on curing procedures have been found in the literature; most of them are based on laboratory or standard condition (i.e., with almost constant temperature and humidity). In a few cases, oven- or air-dry processes have been performed in order to improve the sensing performance by the elimination of the internal residual moist water; however, duration and imposed temperature value vary from case to case, and no firm conclusion on the effect of temperature or moisture is drawn for CSCs applied to structural prototypes. Nevertheless, a very recent study [62] highlighted the significant influence of hourly temperature variations on the electrical resistivity, whereas changes in moisture yielded only secondary effects.
## 4 Simulations and Discussion
### FH Signal Sorting  
In this section, the performance of FH signal sorting is analyzed. The performance of separation is evaluated in terms of the average signal-to-interference ratio (SIR).  
\[SIR=10\log_{10}\left(\frac{\sum\limits_{n=1}^{N}E\Big{[}s_{n}^{2}(t)\Big{]}}{ \sum\limits_{n=1}^{N}E\Big{(}(s_{n}(t)-\hat{s}_{n}(t))^{2}\Big{]}}\right) \tag{23}\]  
where \(s_{n}(t)\) is the source signal, and \(\hat{s}_{n}(t)\) is the separated signal, which is an estimation of \(s_{n}(t)\). The higher the SIR, the more similar the separated signal to the source, which means better performance.  
Figure 8 shows the performance of FH signal sorting. In the present study, the number of sources is three. For our system, the number of sub-channels is set as \(m=50\) and each sub-channel contains two pairs of sub-bands for signal tracking, and \(Ls=256\), \(\beta=8\), \(\gamma=10\%\). Compared with the subspace-based algorithm [3], the proposed algorithm performs better. As the subspace-based algorithm is based on calculating a mixing matrix and comparative power, the error of matrix estimation will lead to amplitude fluctuation of the separated signals. The proposed algorithm can avoid the influence of sub-bands that do not contain signals and filter the noise out of the band. In Figure 8, the orthogonal matching pursuit (OMP) algorithm [31] for recovery is taken as a reference. The performance of OMP does not involve separation. It is shown here as a performance upper bound under ideal conditions.  
Figure 7: Performance of the support set estimation by dynamic programming.  
The single hop is considered long enough as a stationary signal. The SIR performance of the proposed algorithm is a little worse than the OMP recovery method, because the noise of the sub-bands is amplified. The performance improves at high SNR and gets closer to recovery, because the noise is no longer the main cause of performance degradation. Our method has the advantages of fewer calculation requirements and adjustability.  
Figure 9 shows the performance of FH signal separation against number of sources \(N\)s. In the present study, the number of sub-channels is set as \(m=50\) and each sub-channel contains two pairs of sub-bands for signal tracking; \(Ls=256\), \(\beta=8\) and\(\gamma=10\%\). It can be concluded that with more sources, the SIR for separated signals decreases, because the signals interfere with each other and the estimation of relative power degrades. Thus, the sparsity of signals should be considered in the application of CS systems.  
Furthermore, FH code sequences always have the characteristic of a wide gap. The probability of two adjacent hops in different channels can be relatively high. It is beneficial for our system to sense changes in the hops.  
Figure 8: Performance comparison against SNR.  
Figure 9: Performance of separation against number of source.