esa-sceva/satcom-chunk-collection huggingface dataset:
# Thermal Conductivity and Thermal Behavior of Mortar Containing Wood Shavings and Sawdust
## 4 Conclusions  
Based on the results presented, the following conclusions can be drawn:  
* The density of fresh mortar containing wood shavings or sawdust decreases as the wood shavings content increases.
* The thermal conductivity coefficient decreases as the replacement increases, both for wood shavings and wood sawdust. The utilization of construction materials having lower thermal conductivity in buildings may help in improving the energy efficiency of the building.
* Compressive and flexural strength decreases as the replacement percentage of conventional aggregates increases, but the mix design and the use of not high percentages of replacement of conventional aggregates could compensate for this reduction in strength. The use of 30% replacement of conventional aggregates by wood shavings and 20% replacement of conventional aggregates by wood sawdust would give acceptable mixes of mortar, depending on their use and the use's requirements.
* Flexural and compressive strength exponentially decrease as exposure temperature increases. This behavior aligns with the progressive thermal degradation of wood components (hemicellulose, cellulose and lignin) beginning around 200-250 \({}^{\circ}\)C, leading to loss of cohesion and increased porosity in the composite matrix.
* In addition to the specific findings of this study, the results related to density, ultrasonic pulse velocity and mechanical properties contribute valuable data that can be combined with existing literature to enable future meta-analyses comparing different types of wood aggregates, binder compositions and mortar mix designs.  
Further study is needed to cover all physical and mechanical properties of mortars and concrete containing wood shavings or sawdust, in order to assess their uses. Then, testing of a full-scale application using the selected compositions is needed. To further quantify the sustainability impact of the developed mixtures, a life cycle assessment (LCA) should be carried out to compare their environmental performance against conventional mortars. This assessment should consider the specific application context and the mechanical requirements, particularly compressive strength. Additionally, the lower thermal conductivity of the developed mortars may contribute to reduced heating and cooling demands in buildings, offering long-term energy savings, so this should also be considered in LCA.  
Conceptualization, A.S.; methodology, S.G. and N.N.; resources, A.S.; investigation, S.G. and N.N.; writing--original draft preparation, S.G. and T.K.G.; writing--review and editing, S.G.; supervision, S.G. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.  
The authors declare no conflicts of interest.
# Distributed Consensus for Global Matrix Formation in the Principal Component Pursuit Scenario
## 6 Conclusions  
An algorithm to recover a low-rank and a sparse matrix in an undirected static graph is proposed and validated. The consensus mechanism in static undirected graphs was coupled with a principal component pursuit problem, where there is a global noisy and corrupted matrix \(M\) and each agent knows a part of this matrix, with possible redundant observations between agents. Reaching a consensus, they agree on the global original \(M\). To overcome the difficulties that are caused by redundant data, each agent updates only a subset of its own entries. This consensus scheme converges exponentially fast, given the properties of the connected graph described in the associated adjacency matrix \(A\).  
Each agent performs convex relaxation of the optimization problem, where an alternate direction method is employed to find the low-rank and sparse matrices of \(M\). This alternate direction method speeds up the calculation since the sub-problems (when either L or S is fixed) are significantly more manageable than the coupled problem. Under some weak assumptions, these convexification and uncoupling processes recover the exact solution.  
An application of distributed image recovery from a corrupted global matrix is shown, along with a method to handle colored images. A low-rank matrix is employed to recover the corrupted entries of the matrix found by the consensus.  
A brief comparison of random, strongly connected networks of different sizes shows a faster convergence with a higher number of agents. However, for very dense networks, the performance declines. For a fixed number of agents, a lower edge density improves the convergence speed.  
Conceptualization, G.S. and J.D.V.; methodology, G.S. and J.D.V.; software, G.S.; validation, G.S. and J.D.V.; formal analysis, G.S. and J.D.V.; investigation, G.S. and J.D.V.; resources, G.S. and J.D.V.; data curation, J.D.V.; writing--original draft preparation, G.S. and J.D.V.; writing--review and editing, G.S. and J.D.V.; visualization, G.S.; supervision, G.S. and J.D.V.; project administration, J.D.V.; funding acquisition, J.D.V. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Institucion Universitaria Pascual Bravo.  
Not applicable.  
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy.  
The authors declare no conflicts of interest.
## 4 Conclusions  
New configurations of 2-D phased arrays were presented in this paper for reducing the number of phase shifters. The methodology was based on the use of a novel 4 \(\times\) 9 CORPSs block for 2-D phased arrays. Then, two new antenna systems for 2-D phased arrays were studied and analyzed applying CORPSs blocks of four inputs and nine outputs. The CORPSs feeding blocks were applied in a convenient manner to feed planar antenna arrays by generating the required phase plane and reducing the number of phase shifters. Full-wave simulation results were provided using an interesting antenna element for the proposed 2-D array systems. These results illustrated a great reduction of the phase shifters, providing a good design compromise in terms of scanning range and side lobe level performance.  
Furthermore, the full-wave simulation results illustrated a maximum reduction capability in the number of phase shifters of 81%, considering a scanning range of \(\pm 30^{\circ}\) in azimuth and \(\pm 30^{\circ}\) in elevation. A raised cosine distribution was applied to reach side lobe levels of \(-19\) dB for \(\pm 18^{\circ}\) and \(-17\) dB for \(\pm 30^{\circ}\). The results were compared with respect to other works previously published. The proposed cases for 2-D phased array systems provided a design solution that reaches the highest reduction of phase shifters with respect to previous work. These benefits could be of interest to designers of phased array systems.  
Conceptualization, M.A.P.; methodology, G.C.; software, G.C.; validation, G.C. and C.d.R.; formal analysis, G.C. and E.J.; investigation, G.C. and A.R.; resources, M.A.P.; writing--original draft, A.R. and G.C.; writing--review and editing, C.d.R. and A.R.; supervision, M.A.P.; project administration, E.J.; funding acquisition, M.A.P. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The original contributions presented in the study are included in the article; further inquiries can be directed to the corresponding author.  
The authors declare no conflicts of interest.
## 3 Results and Discussion
### Biomechanical Stress Analysis  
Finite element analysis is an important tool that topology optimization is based on, and it is necessary to simulate highly complicated biomechanical problems. Using the exact same finite element procedure that was initially used to create the topology-optimized plate is a key aspect to validate the results of topology optimization [47; 41]. In this paper, a stress analysis study was performed to validate the topology optimization designs by monitoring the stresses at the fracture planes when fixated with the initial and optimized designs. Figure 5 presents the von Mises stress distribution in the region of interest of fracture plane 1 of the eight bone-plate construct FE models for both screw configurations. Table 3 shows the resulting average change in von Mises stresses at the region of interests for all considered bone-plate constructs. In the average stress at the fracture planes, the INT-BP plate under SC1 resulted in 3.98 MPa, while under SC2 it resulted in 13.79 MPa. This is mostly due to the change in the interfragmentary motion of the fracture and the stabilization technique [48]. The reason why this is happening when fixing the distal tibia plate to treat a 43A1.1 fracture with SC1 is due to the bone being stabilized absolutely, while fixing under SC2 results in relative fracture stability, with more interfragmentary motion.  
\begin{table}
\begin{tabular}{c c c} \hline  & \multicolumn{2}{c}{**Equivalent Bending Stiffness Change (\%)**} \\ \hline
**Initial Design** & \multicolumn{2}{c}{**14.13 \(\pm\) 1.7 N.m\({}^{2}\)**} \\ \hline
**Volume Reduction, \%** & **Plates SC1** & **Plates SC2** \\ \hline
25 & \(-\)22.29\% & \(-\)20.99\% \\ \hline
50 & \(-\)32.74\% & \(-\)27.83\% \\ \hline
75 & \(-\)76.24\% & \(-\)73.38\% \\ \hline \end{tabular}
\end{table}
Table 2: The equivalent bending stiffness change percentage in comparison to INT-BP plate.  
\begin{table}
\begin{tabular}{c c c} \hline \hline \multirow{2}{*}{**Plate**} & \multicolumn{2}{c}{**Von Misses Stress Change (\%)**} \\ \cline{2-3}  & **SC1** & **SC2** \\ \hline TO25-BP & 0.16 & 0.09 \\ \hline TO50-BP & 2 & 5 \\ \hline TO75-BP & 13 & 13 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Average change in the von Mises stresses at the fracture planes of the topology-optimized plates based on the initial designs (INT-BP for SC1 is 3.98 \(\pm\) 0.23 MPa and INT-BP for SC2 is 13.79 \(\pm\) 0.19 MPa).  
Figure 5: The von Mises stresses at fracture plane 1 for the eight bone-plate models.
## 5 Discussion of Numerical Simulation Results
### The Influence of the Opening Angle of Outer Ring Pipe on the Weak Area  
Taking the arrangement of the outer ring pipe in this paper as an example, the axial opening angles of C2 are changed to 8.5\({}^{\circ}\), 13.5\({}^{\circ}\), 18.5\({}^{\circ}\), 23.5\({}^{\circ}\), and 28.5\({}^{\circ}\), respectively, and the opening angle of C1 remains unchanged at 13.5\({}^{\circ}\). The temperature distribution of the weak points of C2C1 center on each frozen section of different models when analyzing the different axial opening angles of the outer ring pipe C2 is shown in Figure 13. The C1C2 distance under different C2 opening angles is shown in Table 5.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Extension Length of Outer Ring Pipe (m)** & **Closure Time (d)** \\ \hline
3.53 & 121 \\
4.00 & 108 \\
4.50 & 98 \\
4.99 & 93 \\
5.47 & 88 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Closure time of the control section C.  
Figure 13: The influence of outer circle angle on the temperature of weak points.  
It can be seen from Figure 15 that the temperature of the weak point increases approximately linearly as the angle coefficient increases. And the temperature of the weak point increases by 3.3 \({}^{\circ}\)C for an increase of 1 of the angle coefficient. By analyzing the reasons, the influence of changing the opening angle on the \"boundary point\" temperature is finally attributed to the influence of the spacing between adjacent freezing pipes. As shown in Figure 16, with C1 as the center of the circle and C1C2 as the radius, C2 moves outward along the OC2 ray when the axial opening angle of C2 increases. At this time, the distance of C1C2 increases gradually, so the temperature of the freezing weak point in the center gradually decreases. Therefore, in the construction of similar projects, reducing the axial angle near the weak link of the outer ring hole to a certain extent will improve the stability of the weak link. At the same time, it will also help to reduce the total length of the freezing pipe and reduce the loss of cooling capacity when the horizontal length of the outer ring pipe is certain. The distance of C1C2 under different C2 opening angles has been calculated from Table 5.
###### Abstract  
In the present work, a comparative study of two major non-intrusive polynomial chaos methods, Point-Collocation Non-Intrusive Polynomial Chaos (NIPC) and Non-Intrusive Spectral Projection (NISP), was conducted for the transitional \(\gamma-R_{\theta}\) transitional model. Three multiple model coefficients, \(\text{C}_{a2}\), \(\text{C}_{c1}\), and \(\text{C}_{c2}\) were considered with multiple random inputs with the assumption of uniform distributions with \(\pm 10\%\) deviation. The target transitional flows were one around a flat plate and Aerospatiate A-airfoil. Deterministic solutions were obtained by employing the open source software OpenFOAM. The results of two methods were compared to the results of Monte Carlo simulation with 500 runs. The order convergence of the mean value and the standard deviation (STD) were compared in terms of the quantities of interest, drag and lift coefficients. Further, the most effective model coefficient for each transitional flow could be found through the calculation of the Sobol index.  
point collocation; spectral projection; non-intrusive polynomial chaos; CFD; uncertainty quantification; transition model +
Footnote †: journal: Applied Physics Letters B
# Anomalous Vehicle Recognition in Smart Urban Traffic Monitoring as an Edge Service +
## 1 Introduction
This paper is an extension based on one of our earlier conference publications [22], which was inspired by the excellent performance of the SSA algorithms in change point detection in time series [24]. The mSSA algorithm is creatively adopted to catch the differences in the dimension of characteristics of vehicles on the road by reformatting the abnormal vehicle detection problem as a change point detection problem. Instead of depending on pre-defined abnormal behavior patterns, we catch different/suspicious behaviors and then recognize this behavior. The mSSA approach reduces the amount of data to be transmitted to either a fog or a cloud layer. On top of [22], the major contributions of this paper are:  
* A novel framework is proposed to detect and recognize abnormal vehicle behaviors by leveraging the mSSA algorithm and Capsules Networks at the edge;
* A new cascaded Capsules Network structure is introduced with a new routing agreement for abnormal vehicle behavior recognition; and
* Extensive experimental studies have been conducted with real-world traffic data that validated the effectiveness of SurMon scheme. The rest of this paper is organized as follows: Section 2 briefly presents the related work. An overall introduction of the SurMon architecture is given in Section 3. The anomalous vehicle behavior detection procedure using mSSA is discussed in Section 4 and the behavior interpretation scheme using the cascaded Capsules Network architecture is presented in Section 5. Experimental results are reported in Section 6, and Section 7 concludes this paper with some discussions and the future work.
## 3 Effects of Storage and Maintenance Modes on Battery Performance  
In the experimental studies, the effects of different storage and maintenance modes on the battery capacity could be evaluated by the change of charge retention rate and capacity recovery rate, and the effects of different storage and maintenance modes on the power performance were evaluated by the change rate of charge-discharge power. The efficiency of battery module was evaluated by the change rate of charge-discharge efficiency.  
The charge retention rate and capacity recovery rate can be calculated according to the following equations:  
\[\varphi_{1}=C_{1}/C_{0}\times 100\%, \tag{11}\]  
\[\varphi_{2}=C_{2}/C_{0}\times 100\%, \tag{12}\]  
where \(\varphi_{1}\) is the charge retention rate, \(\varphi_{2}\) is the capacity recovery rate, \(C_{0}\) is the capacity before storage, \(C_{1}\) denotes the residual capacity after storage, and \(C_{2}\) represents the capacity that the battery module can regain after storage.  
The change rate of charge-discharge power can be computed using the following equations:  
\[\varphi_{c1}=(P_{c2}-P_{c1})/P_{c1}\times 100\%, \tag{13}\]  
\[\varphi_{d1}=(P_{d2}-P_{d1})/P_{d1}\times 100\%, \tag{14}\]  
where \(\varphi_{c1}\) is the change rate of charge power, \(\varphi_{d1}\) is the change rate of discharge power, \(P_{c1}\) and \(P_{c2}\) are the charge powers of the performance initial test and performance retest, and \(P_{d1}\) and \(P_{d2}\) are the discharge powers of the performance initial test and performance retest.  
The change rate of charge-discharge efficiency can be computed using the following equations:  
\[\varphi_{c2}=(\eta_{c2}-\eta_{c1})/\eta_{c1}\times 100\%, \tag{15}\]  
Figure 4: Charge–discharge efficiency test flow of Ni-MH battery modules: (a) charge efficiency test; (b) discharge efficiency test.  
\[\varphi_{d2}=\left(\eta_{d2}-\eta_{d1}\right)/\eta_{d1}\times 100\%, \tag{16}\]  
where \(\varphi_{c2}\) is the change rate of charge efficiency, \(\varphi_{d2}\) is the change rate of discharge efficiency, \(\eta_{c1}\) and \(\eta_{c2}\) denote the charge efficiencies of the performance initial test and performance retest, and \(\eta_{d1}\) and \(\eta_{d2}\) represent the charge efficiencies of the performance initial test and performance retest.  
Note that in the following experimental results, the \"\(-\)\" sign represents \"reduction\", as opposed to \"negative value\".
## 3 Basic Concepts
### Software-Defined Networks and CPPs  
Software-defined networks (SDNs) are a new network technology that is controlled centrally and intelligently. In this type of network, the management and tracing of packets are entirely the responsibility of the controlling part of it. The main issue of the network's controlling plane occurs when the network size is large, as in this case, just one controller will not be able to cover the entire network. Therefore, the main challenge in this scenario is finding the right amount and location for the controllers. Clustering is one of the most reasonable viewpoints that can succeed in the complicated management process of large networks and can guarantee load balancing. Using the concept of clustering, a large network is divided into multiple subnetworks in a manner that there will be a controller for each subnetwork. Some matters such as the delay between controllers, load balancing, and reliability are also important considerations in addition to decreasing the delay between the switch and the controller.
## 1 Introduction
### Background and Scope  
The approach conducts here the determination of safety assessment of aged-concrete gravity dam (aged-CGD) by a key term reliability index, which is usually expressed either by Damage Probability Matrixes (DPM) or probabilistic failure consequences. [PERSON] et al. [1] illustrated the relationship between the structural redundancy and reliability index of RC frames where the ultimate result shows a result increase of reliability index with increasing the structural redundancy. In this study for determiningthe reliability index of the aged-CGD, the selected CGD is calibrated by the well-established Response Surface Methodology (RSM) [2], and experimental selection for the parameters is carried out by the Central Composite Design method (CCD) [3]. [PERSON] and [PERSON] [4], [PERSON] et al. [5] and [PERSON] and [PERSON] [6] explained that the RSM is a mathematical and statistical method to solve the uncertainties elapsed in an epistemic manner in the real structure.  
According to the performance-based earthquake engineering (PBEE) framework, the reliability index comes through the development of the fragility analysis and mean annual frequency of exceedance. The lognormal distribution acted well to develop the seismic fragility for CGDs by expressing only the median seismic fragility, which includes the randomness and uncertainties [7].Among several methods, the incremental dynamic analysis (IDA) scall the ground motion (GM) to some extent [8], and this manuscript follows the IDA to make the fragility curve.  
The CGD safety evaluation depends on the determination of the risk assessment, which can be textualized as a measure of the probable adverse effect on the surrounding environment. According to [PERSON] et al. [9], risks are also thought about because of the intentional interaction with uncertainties. The dam safety depends on the specific mode of failure due to the different load scenarios such as static, seismic, hydrologic, geologic, mechanical, etc. Here, for this target, the seismic load has been considering by determining the seismic hazard analysis of the specific site, where the risk is evaluated by the multiplication with the structural failure responses. The software PSHRisk-tool developed by the same authors of this manuscript has been used to evaluate the seismic hazard analysis of the specific sites (dam location) in Korea analyzed considered four seismic models [10].  
Even though there are several studies in safety evaluation of the CGD, very few types of research have been done on the determination of the safety range using the reliability analysis. The rare part is the aging effect considering the hygro-chemo-mechanical model of the aged-CGD, and it shows the time-varying aging effect on the safety evaluation. Finally, the safety index of aged-CGD will inform at what stage the specific CGD will fail to fulfill the target reliability range. The novelty of this proposed approach gives an idea to the dam operator and researcher to safety check of the aged-CGD for the potential earthquake levels.
## 3 Method
### Derivation of the Weighted Reliability Score
If we were to know the correct label \(cl(x)\) for each case \(x\), then we would simply set \(a\hat{c}c_{i}(x)=\mathbb{1}_{r_{i}(x)=cl(x)}\). However, this is usually not possible, and we would need to resort to a probabilistic estimate of the rater's accuracy. This latter can be set either on the basis of the empirical accuracy of the rater estimated on another dataset sample, which would however provide the same value \(a\hat{c}c_{i}\) for each \(x\), or on the basis of a model-based estimation, such as the Rasch model [30]. In this latter case, assuming that for each case \(x\), an assessment of its complexity \(diff(x)\) is available, the value of \(a\hat{c}c_{i}(x)\) can be estimated as follows:  
\[a\hat{c}c_{i}=\frac{e^{exp_{i}-diff(x)}}{1+e^{exp_{i}-diff(x)}} \tag{5}\]  
where \(exp_{i}\) is an estimate of rater \(i\)'s ability or expertise. Thus, having an estimate of each rater's accuracy on each case, we can quantify the probability that an observed agreement is right (i.e., equal to the true, unknown label) as:  
\[P(r_{i}(x),r_{j}(x)\text{ correct})=\frac{a\hat{c}c_{i}*a\hat{c}c_{j}}{a\hat{c}c _{i}a\hat{c}_{j}+(1-a\hat{c}c_{i})(1-a\hat{c}c_{j})} \tag{6}\]  
From the degree of concordance, we can then define a composite reliability measure, the so-called weighted reliability score, or \(\varrho\), which also takes into account the accuracy of the raters and is defined at both the single case and whole dataset level:  
\[\varrho(x,R) =\binom{m}{2}^{-1}\sum_{r_{i}\
eq r_{j}\in R}G\,A_{x}(r_{i},r_{j} )\cdot P(r_{i}(x),r_{j}(x)\text{ correct}) \tag{7}\] \[\varrho(S,R) =\frac{1}{|S|}\sum_{x\in S}\varrho(x,R) \tag{8}\]