esa-sceva/satcom-chunk-collection huggingface dataset:
# A Critical Review of SCWG in the Context of Available Gasification Technologies for Plastic Waste
## 3 Supercritical Water Gasification (SCWG)
### Advantages and Disadvantages in The Use of SCW  
Supercritical water gasification has numerous advantages over conventional gasification:  
* Supercritical water is an active reactant which results in a high hydrogen yield ([PERSON] et al., 2019).
* In the SCWG, the drying step of feedstock is not required. This leads to greater energy efficiency especially for biomass with a high moisture content. Therefore, there is a considerable economic saving, since drying and pre-treatment of biomass add extra cost to the process economics ([PERSON] et al., 2019).
* High pressure of the gaseous product enables the transportation, usage, carbon capture, and further purification of the product gas through steam reforming or PSA (pressure swing adsorption).
* The reaction temperature is much lower than that used in conventional gasification and pyrolysis processes.
* Tar and coke formation is inhibited by a fast solution of the formed gas components in the supercritical water ([PERSON] et al., 2019).
* The gaseous product is very clean, as NO\({}_{\rm x}\) and SO\({}_{\rm x}\) are generated in very small quantities and the CO concentration is very low, especially in the presence of a catalyst to improve the water-gas shift reaction ([PERSON] et al., 2019).  
At the same time, this technique has some disadvantages that must be taken into consideration. First of all, the reactor must be made of materials resistant not only to corrosion but also to high temperatures and pressures. Furthermore, there is a considerable energy expenditure to heat up the water to the reaction temperature. This entails high investment costs.
## 4 Discussion
### Ferric Reducing Antioxidant Power Assay (FRAP)  
The results found for FRAP in all of the porcine liver enzymatic hydrolysates were lower than the activities observed in ABTS and DPPH assays. Moreover, the type of enzyme selected for hydrolysis had a significant effect (\(P<0.05\)) on the outcomes obtained. In this case, alcalase was the second most important enzyme after bromelain. The lower values of FRAP obtained in alcalase and papain could be due to the lower ability of these liver hydrolysate extracts to reduce ferric ion to its ferrous form. In contrast, other authors found that papain presented better results than those obtained for alcalase and bromelain in bovine blood and lung hydrolysates [47; 48]. In addition, the values obtained in FRAP assay showed lower values than those found in other liver hydrolysates [10].  
Large hydrolysis periods intensified the FRAP activity of the peptides released by enzyme hydrolysis. This increase of the FRAP activity with longer hydrolysis time was also reported with other protein hydrolysates obtained from meat by-products [49; 50]. This behavior was reported in the enzymes studied in the present work and in others, such as flavorzyme [47; 48]. [PERSON] et al. [10] observed that hydrolysis performed with alcalase and papain increased FRAP activity by 40.0% after 6 h of hydrolysis, while increases of about 76.0% were observed by [PERSON] et al. [50] in porcine hemoglobin hydrolysates after 10 h of hydrolysis.  
According to the results previously reported by other authors for porcine protein hydrolysates, ultrafiltration process is one of the factors that has a marked effect on the FRAP activity. In contrast with the results found by other authors [49; 51], larger size peptides obtained from the enzyme hydrolysis exhibited higher FRAP values than those obtained in extracts that contained lower molecular weight peptides. A similar trend was observed in whole porcine liver and blood hydrolysates [19; 52]. This fact confirmed that the structure and size of the peptides of the resulting hydrolysates could be responsible for these differences in antioxidant activities among hydrolysates [43].
# Optimization Methods of Compressively Sensed Image Reconstruction Based on Single-Pixel Imaging
###### Abstract  
According to the theory of compressive sensing, a single-pixel imaging system was built in our laboratory, and imaging scenes are successfully reconstructed by single-pixel imaging, but the quality of reconstructed images in traditional methods cannot meet the demands of further engineering applications. In order to improve the imaging accuracy of our single-pixel camera, some optimization methods of key technologies in compressive sensing are proposed in this paper. First, in terms of sparse signal decomposition, based on traditional discrete wavelet transform and the characteristics of coefficients distribution in wavelet domain, a constraint condition of the exponential decay is proposed and a corresponding constraint matrix is designed to optimize the original wavelet decomposition basis. Second, for the construction of deterministic binary sensing matrices in the single-pixel camera, on the basis of a Gram matrix, a new algorithm model and a new method of initializing a compressed sensing measurement matrix are proposed to optimize the traditional binary sensing matrices via mutual coherence minimization. The gradient projection-based algorithm is used to solve the new mathematical model and train deterministic binary sensing measurement matrices with better performance. Third, the proposed optimization methods are applied to our single-pixel imaging system for optimizing the existing imaging methods. Compared with the conventional methods of single-pixel imaging, the accuracy of image reconstruction and the quality of single-pixel imaging have been significantly improved by our methods. The superior performance of our proposed methods has been fully tested and the effectiveness has also been demonstrated by numerical simulation experiments and practical imaging experiments.  
Keywords:wavelet decomposition basis; sensing matrix; image reconstruction; compressive sensing; single-pixel imaging +
Footnote †: journal: Applied Physics Letters
## 2 Materials and Methods
### User Testing
#### 2.3.3 Functional Joint Center Calculation  
The functional joint center (FJC) visually indicates the prosthetic foot's center of rotation [11; 12; 22] and provides additional information to help understand the ESR deformation characteristics during the stance phase. The ankle moment and ankle angle data commonly collected during user testing describe the prosthetic foot's stiffness characteristics. In contrast, the FJC's position provides an average intersection location of the foot and tibial segments rotation during the stance phase. The FJC is an estimation of the virtual joint center and therefore enhances the interpretation of the ESR flexible leaf spring deformation during roll-over.  
The functional joint center was calculated for both machine and biomechanical tests. Marker positions were processed using the video tracking software Tema (Image Systems, Linkoping, Sweden) for machine tests. The marker positions for the biomechanical tests were exported as an average for the five users. The points coordinates were projected to the sagittal plane (Figure 5). The rigid-body assumption between markers was used for the calculation. The center of zero velocity was calculated during the stance phase using a MATLAB custom script (MathWorks, Natick MA, USA) between M1-M2 and M3-M4 segments for the test machine and between segments M\({}_{\text{k knee}}\)-M\({}_{\text{Ankle}}\) and M\({}_{\text{heel}}\)-M\({}_{\text{toe}}\) segments for the biomechanical test. The position of the instantaneous center of rotation was then averaged for the stance phase over five steps. The X and Y coordinates of the FJC were compared between the two test methods.
# A Low-Order Series Approximation of Thin-Bed PP-Wave Reflections
## 3 Approximate Formula of PP-Wave Reflections
\begin{array}{ll}B_{1}=\frac{1}{m_{1}}\left(1-\frac{a_{3}a_{3}}{d_{1}}+ja _{1}a_{5}\right)(1+A_{0})-\frac{1}{m_{1}}[l_{1}l_{2}a_{2}+(\cos q+j\sin q)a_{ 4}]B_{0}\\ +\frac{1}{m_{1}}\left[\frac{2}{r_{1}}-ja_{2}l_{1}\sin\tau+\frac{2l_{1}}{r_{2}} \frac{z_{52}}{z_{51}}(a_{1}\cos\tau-1)\right](1-A_{0})\end{array}  \tag{9b}\]  
with \(m_{1}=(z_{53}/z_{51}+1){\cos q}+j(z_{52}/z_{51}+z_{53}/z_{52}){\sin\eta}\). \(a_{6}\) is given in Appendix C.  
Considering the quadratic term of sine incidence angle in Equation (1), then \(R_{PP}=A_{0}+A_{2}{\sin^{2}\theta}\), \(T_{PP}=B_{0}+B_{2}{\sin^{2}\theta}\), \(R_{PS}=A_{1}{\sin\theta}\), \(T_{PS}=B_{1}{\sin\theta}\). Equation (1) is simplified as  
\[ \begin{array}{ll}\left(\cos\tau+j\frac{z_{P1}}{z_{P2}}\sin\tau\right)A_{2}+B _{2}=\left(b_{1}+jb_{3}\frac{z_{P1}}{z_{P2}}\right)(1+A_{0})\\ +b_{6}(1-A_{0})+\frac{j_{1}l_{2}^{2}l_{2}^{2}}{2}B_{0}+\frac{l_{1}l_{2}}{r_{3}} B_{1}\\ +\left(b_{1}+\frac{1}{r_{1}}\cos\tau+\frac{a_{3}}{r_{1}d_{1}}+j^{2}{\sin\eta} \frac{\tau}{r_{1}^{2}}\frac{z_{P1}}{z_{P2}}\right)A_{1}\end{array}  \tag{10a}\]and  
\[ \begin{array}{l}\left(\cos\tau+j\frac{z_{p1}}{z_{p2}}\sin\tau\right)A_{2}+B_{2}= \left(b_{1}+jb_{3}\frac{z_{p1}}{z_{p2}}\right)(1+A_{0})\\ +b_{6}(1-A_{0})+\frac{\hat{H}_{1}^{2}Z}{2}B_{0}+\frac{\hat{H}_{1}Z}{r_{3}}B_{1} \\ +\left(b_{1}+\frac{1}{r_{1}}\cos\tau+\frac{a_{3}}{r_{1}d_{1}}+j\frac{2\sin\tau} {r_{1}^{2}}\frac{z_{p1}}{z_{p2}}\right)A_{1}\end{array}  \tag{10b}\]  
with \(b_{1}\)-\(b_{6}\) are presented in Appendix C.  
Solving Equation (10), there is  
\[ \begin{array}{l}A_{2}=\frac{1}{m_{0}}\left[-\frac{\hat{H}_{1}^{2}}{2}\tau \sin\tau+2\frac{a_{3}\hat{H}_{1}^{2}}{\hat{r}_{2}^{2}}(d_{1}-1)+\frac{2}{r_{1} ^{2}}\cos\tau+b_{1}\frac{z_{p2}}{z_{p1}}+jb_{3}\frac{z_{p2}}{z_{p2}}\right](1+ A_{0})\\ +\frac{1}{m_{0}}\left(b_{6}\frac{z_{p2}}{z_{p1}}+\frac{2|jb_{1}}{r_{1}^{2}}+jb _{4}\frac{z_{p2}}{z_{p1}}\right)(1-A_{0})+\frac{b_{5}}{m_{0}}\left[l_{1}l_{2} \left(\frac{\hat{H}_{1}^{2}}{4}-1\right)B_{0}+\left(\frac{r_{3}}{2}-1\right)B _{1}\right]\\ +\frac{1}{m_{0}}\left[\begin{array}{c}\left(b_{1}+\frac{\cos\tau}{r_{1}} \right)\frac{z_{p2}}{z_{p1}}+\frac{2}{r_{1}}\cos\tau+l_{1}a_{3}\left(\frac{2}{ r_{1}^{2}}\frac{z_{p2}}{z_{p1}}+\frac{1}{r_{1}}\frac{z_{p2}}{z_{p2}}\right)\\ +\frac{2j\sin\tau}{r_{1}^{2}}\frac{z_{p3}}{z_{p2}}+j\frac{\sin\tau}{r_{1}}\frac {z_{p2}}{z_{p1}}-j\frac{b_{1}\hat{H}_{1}}{r_{1}}\end{array}\right]A_{1}\end{array}  \tag{11}\]  
Equations (4) with (6a) and (11) constitute the wholly second-order series approximation of thin-bed \(R_{pp}\), algorithmic steps of which are shown in Figure 3 details. The intercept and gradient of the approximate formula are dependent on frequency, which is greatly different from those of a single interface [36]. It is worthy to notice that, the approximate formula can be further simplified for ultra-thin bed cases by introducing in the approximations of \(\sin\tau\approx\tau\), \(\sin q\approx q\), \(\cos\tau\approx 1\), and \(\cos q\approx 1\).
## 4 Discussion
### Bioassays  
While the sheep wool hydrodistillate and its major component thialdine did not show any significant attractant activity against adult female _Ae. aegypti_ mosquitoes in glass tube bioassays, the baits with dynamic (vibrated) raw sheep wool were attractive to _Ae. aegypti_ compared to the static baits, or dynamic baits but without wool. Baits with sheep wool, dynamic or static, could both be sources of volatiles, but under static conditions the odor emanating from wool may not be strong enough to stimulate the mosquito's olfactory sensors. When vibrated, the volatile compounds, most probably, are released more intensively from the wool fiber, and the released volatiles, as potential attractants, increase mosquito capture. The attractant activity of vibrated raw sheep wool could be attributed to the volatile molecules from the HS extracts containing significant amounts of those aldehydes, alcohols, sesquiterpenes, alkanes, ketones, or 2-methylbutanoic acid (Tables 1 and 2) that were identified as active against mosquitoes according to the literature reports [8, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70]. On the contrary, in sheep wool hydrodistillate these compounds were present only in small amounts: e.g., \(p\)-cresol, detected by GC-MS and GC-FID/GC-MS, was present at \(\sim\)2%, 2-octanone, detected by GC-MS, was present at \(\sim\)0.9%, and hexadecane, detected by GC-FID/GC-MS, was present at \(\sim\)0.3%. The major component of the hydrodistillate, thialdine, which is product of cooking [45], was not attractive to adult female _Ae. aegypti_, according to glass tube bioassays.  
In semi-field bioassays with raw sheep wool, the following factors could be involved affecting mosquito attraction: chemical (volatiles released by wool) and visual (vibrating Vortex) signals. It should be noted that sound could also influence mosquito behavior, according to [PERSON] et al. [71], who studied _Ae. aegypti_ and _An. gambiae_ mosquitoes responses to sound stimulus; in our case, sound from the vibrating Vortex.  
Thus, the attraction of adult female _Ae. aegypti_ to vibrating sheep wool may have been a combination of the effects of olfactory, visual, and, also, acoustic cues; of which the olfactory cues should be most important as, according to a recent study on adult female _Ae. aegypti_ by [PERSON] et al. [72], olfactory cues seem to play a greater role in attracting mosquitoes to the host than their visual cues.  
According to [PERSON] et al. [7], during storage the hair could lose volatile compounds over time compared to the dynamic production from live animals, and in our semi-field experiments, we tried to create the dynamic conditions by vibrating sheep wool, which, we assume, intensified the process of releasing volatiles, that appear to be still present in stored sheep wool, and this intensive emission of volatiles considerably increased mosquito collection in the traps.
## 5 Conclusions  
In this paper, to reduce the computational burden while maintaining prediction accuracy in orbital uncertainty propagation, an adaptive Gaussian mixture model using virtual sample generation--noted as AGMM-VSG--is proposed. The splitting algorithm is applied to the dominant eigenvalue of the covariance matrix of the Gaussian components. An active sampling-based KRG algorithm is employed for generating virtual samples, and then propagations are executed based on these expense-less virtual samples.  
The performance of the active sampling-based KRG algorithm is validated using an LEO case considering the atmospheric drag. Numerical simulation shows that the proposed active sampling-based KRG algorithm can accurately approximate the orbit state using only 10 samples.  
Figure 10: PDF contours using AGMM-VSG with Monte Carlo samples for TQO case.  
Figure 9: Final uncertainty using AGMM-VSG and MC for TQO case.  
Moreover, the proposed AGMM-VSG is successfully applied to solve the orbit uncertainty propagation problem in LEO, HEO, and Tianqin orbit cases. It was demonstrated that the obtained PDF contours using AGMM-VSG are more representative of the curvature of the true distribution than the fifth-order CR method. Moreover, likelihood agreement measure tests indicate that the new approach shows close performance in approximating the propagation of uncertainty with the AGMM method, while only 100 evaluations are required. The computational cost of the proposed AGMM-VSG method is only 1/20 that of the conventional GMM method. All in all, the newly presented approach has advantages in accuracy and efficiency over competitive methods.  
Conceptualization, T.X. and Z.Z.; methodology and software, H.H. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China (Grant No. U20B2001), the National Key R&D Program of China (Grant No. 2020 YFC2201200) and the Basic Scientific Research Project (Grant No. JCKY2020903B002).  
Not applicable.  
The authors declare no conflict of interest.
# Hierarchical Coordinated Predictive Control of Multiagent Systems for Process Industries
###### Abstract  
Focusing on the requirements for efficient and accurate control in large-scale process industries with integrated \"distributed-decentralized\" characteristics, a novel hierarchical coordinated predictive control strategy for process industries is proposed with a multiagent system as the computational paradigm. This approach comprehensively considers the overall state of the system, the interactions of control actions among agents, the constraints of processes and energy consumption to solve the problems of poor flexibility of agent decision-making in the narrow consensus strategy and strong interaction of parts of the system. The proposed hierarchical control strategy requires each agent to perform three tasks at each time step. First, each agent iteratively obtains a consistent basis for closed-loop prediction in a distributed way. Then, each agent independently proposes a control scheme and determines its own priority by playing games based on the economic performance of the scheme. Next, each agent calculates its own optimal dynamic predictive control sequence in order of priority based on the system's dynamic process model. Finally, by considering the temperature-control process of heating an alumina ceramic block in a high-power microwave reactor with six microwave sources, the effectiveness of the proposed hierarchical coordinated predictive control strategy is verified under different communication topologies by comparing it with the centralized model predictive control strategy.  
multiagent system; hierarchical predictive control; coordinated control; game theory; economic performance
# Information-Centric Network-Based Vehicular Communications: Overview and Research Opportunities
## 5 ICN-Based VANET Research Opportunities
### ICN-Based VANET Caching  
ICN caching is divided into several parts, i.e., (a) off-path caching that requires extra storing devices, (b) on-path caching which is achieved opportunistically, (c) homogeneous caching where two caching nodes co-operate with each other, and (d) heterogeneous caching in which caching nodes do not co-operate with one another. For understanding the concept of these techniques, a recent survey [22] provides a detailed explanation of ICN caching strategies along with their contributions and limitations.  
In vehicular networks, caching is achieved either through RSUs or even another sensing device such as vehicle. If an RSU is deemed as a caching node and a vehicle needs to access its cached data, then it can be acquired easily [38]. However, when a vehicle covers some distance and leaves the covering area of the RSU, then it is complicated to locate the real cache position. Similarly, if another vehicle is supposed to be a caching node, then after covering distance in the opposite direction from the accessing vehicle, it is more challenging to locate that caching vehicle. Moreover, cache update is also an essential mania for avoiding traffic congestions and accidents, which may cause due to outdated cached content. Therefore, a flawless updating cache strategy accompanied by a fine-grained forwarding mechanism is the basic requirement of the ICN-based VANET environment.
# Experimental Investigation of TR-UHPC Composites and Flexural Behavior of TR-UHPC Composite Slab
## 2 Axial Tensile Performance of TR-UHPC
### Results and Analyses of Axial Tension Tests
#### 2.3.2 Impact of Fiber Type on Tensile Properties of TR-UHPC Composites  
Figure 5 shows a comparison of the stress-strain curves between various TR-UHPC tensile specimens.  
Among the TR-UHPC tensile specimens, the CFT had the greatest improvement on the axial tensile properties of UHPC due to the excellent mechanical properties of the carbon fiber, which significantly increased the initial cracking strength and tensile strength by about 18.0% and 21.7%, respectively, compared to the plain UHPC specimens. The BFT-UHPC tensile specimens showed a second-grade increase in the initial cracking strength and tensile strength by about 12.0% and 15.9%, respectively. The surface impregnation treatment enhanced the firmness of the braided junction in the BFT compared to the other fiber textiles. At the microscopic level, the difference in thickness between the braided junction and other positions was more significant, resulting in the best bond with the matrix. Compared with the plain UHPC tensile specimen, the initial cracking strength and tensile  
Figure 4: Failure modes of the axial tension tests.  
Figure 5: Comparison of the stress–strain curves of the tensile specimens.  
strength of the T-G2 specimens were improved by 9.1% and 8.0%, respectively. Though the improvement in the tensile performance of the T-G2 specimens was not obvious, there was a great improvement in ductility. It is possible that the surface treatment of CFT and GFT could enhance their interface bonding properties, resulting in more stable outcomes.
# Authenticated Multicast in Tiny Networks via an Extremely Low-Bandwidth Medium
## 1 Introduction
### Multicasting and the Problem of Shared Symmetric Keys  
As explained above, for the target networks, we are forced to use symmetric cryptography. This is not a challenge when one-to-one links have to be secured. If node \(A\) shares a key \(K\) exclusively with a node \(B\), then securing the link from \(A\) to \(B\) is not a problem; a message from \(A\) can be encrypted with a standard authenticated encryption algorithm such as ASCON [10], then \(B\) can decrypt it and check the message authentication code. If this check succeeds, \(B\) becomes convinced that the message comes from somebody that knows \(K\). The only party apart from \(B\) to know \(K\) is \(A\); thus, \(B\) concludes that the message comes from \(A\).  
As message authentication codes are recomputed by the recipient and are generated by pseudorandom functions, they can be truncated to save bandwidth. By truncation, the chances of guessing the authentication code by the adversary increases, but may be still sufficiently low (after truncating to, say, 20 bits, the adversary may succeed in guessing a correct code for a manipulated message with probability \(2^{-20}\)).  
In the networks considered in this paper, it might be useful or even necessary to use multicast mode instead of sending a message separately to each intended recipient. In that case, authenticated encryption with a shared key \(K\) is not enough to authenticate a message. Assuming that \(A\), \(B\), and \(C\) share a key \(K\), where \(A\) is the intended sender while \(B\) and \(C\) are intended recipients, if \(B\) receives a message correctly encrypted with \(K\), then they can no longer assume that it comes from \(A\), as party \(C\) could also have created it. This may happen if \(C\) is malicious or simply subverted by an adversary. We assume that the physical protection of the network nodes is limited and that they may be captured, reprogrammed or cloned, and turned against others.