esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Analysis of SMA-Compensated Torque Performance
### Total Torque of the Composite Transmission Drive  
By adding the MR torque and SMA compensation torque at different temperatures, the total torque of the composite transmission drive can be obtained as  
\[M=M_{\rm m}+M_{\rm f} \tag{18}\]  
Figure 17 shows the relationship between the MR torque, SMA compensation torque, and total torque of the composite transmission device with temperature when the current \(I=3\) A. From Figure 17, it can be seen that the torque transferred by the MRF decreased as the temperature increased, but the trend of the SMA compensation torque was the opposite. The compensation torque provided by the SMA spring was low at temperatures from 20 to 45 \({}^{\circ}\)C. When the temperature was in the range of 45 to 80 \({}^{\circ}\)C, the compensation torque increased more rapidly from 3.216 N\(\cdot\)m to 25.727 N\(\cdot\)m, with a maximum compensation torque of 27.69 N\(\cdot\)m.  
Figure 16: Schematic diagram of hydraulic friction.  
The total torque of the high-temperature MRF and SMA spring friction composite transmission device was finally maintained at 82.627 N\(\cdot\)m, which is basically the same as that of the MR torque at 20 \({}^{\circ}\)C.  
To facilitate the measurement of the torque performance of the transmission device, the torque fluctuation rate \(\beta\) of the composite transmission device was defined as  
\[\beta=\frac{M-82.627}{M}\times 100\% \tag{19}\]  
The torque fluctuation curve in Figure 17 shows that the total torque of the transmission device changes smoothly, the fluctuation in the torque is the largest when the temperature is 77 \({}^{\circ}\)C, and the total torque is 88.711 N\(\cdot\)m, which is 8.16% higher than the MR torque at 20 \({}^{\circ}\)C. When the temperature is 53 \({}^{\circ}\)C, the fluctuation in the torque is the smallest, the total torque is 82.141 N\(\cdot\)m, and the torque error is only 0.15%.  
In summary, the compensating torque of the shape memory alloy at high temperatures is exactly equal to the torque lost as a result of the MRF's degradation. That is, the torque of the composite drive can be basically maintained at a stable level.
## 2 Materials and Methods
### Antioxidant Activity Analysis
#### 2.6.2 ABTS (3-ethylbenzothazoline-6-sulfonicacid) Radical Scavenging Assay  
The ABTS radical scavenging ability was evaluated using an assay kit. To prepare the ABTS working solution, 5 mL of ABTS solution (7 mmol/L) and 88 \(\mu\)L of potassium persulfate solution (140 mmol/L) were thoroughly mixed and incubated for 12 h in darkness at 4 \({}^{\circ}\)C. Before use, the working solution was diluted with ethanol to achieve an absorbance value of 0.70 \(\pm\) 0.05 nm at 734 nm for the ABTS working solution (30 \({}^{\circ}\)C). Subsequently, 50 \(\mu\)L of the oil sample was combined with 950 \(\mu\)L of the ABTS working solution and allowed to react in darkness for 6 min at room temperature. The absorbance was then measured at 734 nm, with an ethanol solution used as a control. A standard curve (Y = 0.4365X + 1.2067; R\({}^{2}\) = 0.9973) was prepared using the different concentrations of Trolox standard solutions (0, 20, 40, 60, 80, 100 \(\mu\)g/mL). The ABTS radical scavenging abilities of the oil samples were calculated using the following formulas:  
\[\text{ABTS radical scavenging ability}(\%)=[1-(\text{A}_{1}-\text{A}_{2})/\text{A}_{3 }]\times 100 \tag{3}\]  
\[\text{ABTS radical scavenging ability}(\text{$\mu$g Trolox}/\text{mL})=(\text{Y}- 1.2067)/0.4365\times\text{A}_{4} \tag{4}\]  
In the formulas, A\({}_{1}\), A\({}_{2}\), and A\({}_{3}\) represent the absorbance values of the oil sample, control, and blank, respectively; Y denotes the ABTS radical scavenging ability (%); A\({}_{4}\) signifies the dilution factor.
## 2 Materials and Methods
### Measurement of Sensitivities to UV Irradiation  
Sensitivities to UV irradiation were determined as bactericidal activity using a colony-forming assay. _V. parahaemolyticus_ strains were collected by centrifugation (7740\(\times\)_g_, 2 min, 25 \({}^{\circ}\)C) and washed three times with sterile phosphate-buffered saline (PBS). Then, 15 min before UV irradiation, the bacterial cells were treated with or without 20 mM L-serine (Supplementary Material Figure S2). The WT or the mutant strains were both adjusted to 10\({}^{9}\) CFU/mL in PBS. The irradiant fluences of UVA, UVB, and UVC were 126, 0.27, and 0.063 kJ/m\({}^{2}\), respectively. After UV irradiation, bacterial suspensions were diluted appropriately, plated on LB agar plates with or without 20 mM L-serine, and incubated at 37 \({}^{\circ}\)C for 18 h. Following the incubation, the colonies were counted, and the log of the survival ratio was calculated as follows:  
\[\text{Log survival ratio}=\text{log}_{10}\ (N_{t}/N_{0}), \tag{1}\]  
where \(N_{t}\) is the colony count of the UV-irradiated sample, and \(N_{0}\) is the colony count of the sample that had not undergone UV irradiation.
## 5 Conclusions  
From the results of this study, we can draw the following conclusions.  
1. All the factors (adhesive application method, TC period, and adhesive system) significantly influenced the SBS values in SE mode (\(p<0.001\)).  
All the factors (adhesive application method, TC period, and adhesive system) significantly influenced the SBS values in ER mode (\(p<0.001\)).
3. Although the application method and adhesive systems significantly influenced the thickness of the adhesive layer (\(p<0.001\)), the etching mode did not have any influence (\(p=0.974\)).
4. Although GU and OX showed significantly higher SBS values in ER mode than in SE mode at 24 h, no significant differences in the SBS values of the three adhesives were observed between the SE and ER modes at TC 30,000 in Group III.
5. The application method in Group II, which conformed to the manufacturers' recommendations, resulted in an adhesive layer that was approximately 40-60 \(\upmu\)m in thickness and appeared to be optimal for effective enamel bonding, regardless of the type of adhesive system or etching mode.
6. Within the limitations of this study, the new-generation two-step SE adhesive, which adopts a universal adhesive-derived primer and a hydrophobic bonding agent, showed superior bond performance to the conventional two-step adhesive systems.  
[PERSON] and [PERSON] conceived and designed the experiments; [PERSON], [PERSON] and [PERSON] conducted the experiments; [PERSON] analyzed the data; [PERSON] wrote the paper; [PERSON] and [PERSON] proofread the manuscript and contributed to the discussion. All authors have read and agreed to the published version of the manuscript.  
This work was supported in part by Grants-in-Aid for Scientific Research, Nos. 19K10158, 21K16975, 21K16977, and 21K09900 from the Japan Society for the Promotion of Science. This project was also supported in part by the Sato Fund (2021) and by a grant from the Dental Research Center of the Nihon University School of Dentistry (2021), Japan.  
The authors of this manuscript certify that they have no proprietary, financial, or other personal interest of any nature or kind in any product, service, and/or company that is presented in this article.
## 3 Results and Discussion
### Gas Recovery Efficiency and Interlayer Compatibility
#### 3.3.3 Commingled Production Compatibility  
The aforementioned analysis clearly indicates that the interlayer pressure difference plays a pivotal role in determining the extent of interlayer interference and its impact on gas production and recovery. Therefore, it serves as a fundamental indicator for evaluating the compatibility of commingled multilayer production.  
Of the existing six interlayers, the middle four ones (i.e., layers H8, S1, S2, and TY) are found to be suitable for commingled production. The gas contribution ratios of each layer for commingled three-layer production of the three scenarios are illustrated in Figure 9a-c. It can be observed that the H8, S1, S2, and TY layers demonstrate minimal interlayer differences, small interference indices, and comparable production contribution ratios during commingled production. Consequently, this leads to a prolonged stable production duration and favorable compatibility in commingled production.  
The Q5 and BX layers are not suitable for commingled production with the other layers. Due to the lower pressure of the layer Q5, a significant interlayer interference arises during commingled production, resulting in an extended period of interference and a shortened phase of stable production, ultimately leading to a reduction in overall gas production. The high permeability and initial pressure of the BX layer result in interference with the other layers. Due to the limited initial reserves of the BX layer, however, there is a rapid decline in both the gas production rate and production contribution ratio, leading to a shortened gas production period and stable production stage. Consequently, this ultimately results in an overall reduction in gas production compared to single-layer extraction.  
Figure 9: Production contribution ratio curves for the commingled production: (**a**) Q5 + S2 + TY layers; (**b**) H8 + S2 + TY layers; and (**c**) S2 + TY + BX layers.
## 6 Conclusions  
This paper presents the design of a power system using a HESS with an SC module and a bidirectional converter to deliver the required power according to the load requirements. The DSP controls the presented system, which offers much flexibility in this application. The SC module was calculated and designed according to the specifications with a final capacitance of 10 F. After selecting the bidirectional DC/DC converter, the interconnect board was designed to properly connect the DC/DC converter, SC module, accumulator, and load. The measurement circuits were added to this board to monitor all required parameters. Finally, the presented setup was verified in the practical scenario with the help of the four-quadrant power supply simulating sink/source load. The measurement results clearly show that the proposed solution works perfectly and meets all the required criteria of the application. The dynamic test of the SC module shows a small amount of heat generated, but this test was designed to test the thermal limits of the module, and these conditions never arise in practical applications.  
One possible improvement is increasing the number of series supercapacitors to increase the overall SC module voltage. This results in a lower current through the SC  
Figure 19: Temperatures of tested SC module after 10 cycles of defined profile (top view on the left, side view on the right).  
Figure 18: Initial temperature of tested SC module (top view).  
module and the DC/DC converter. This leads to lower conduction losses, thus improving efficiency. This step leads to higher SC module prices at the expense of slightly enhanced efficiency. The improved control algorithm can use progressive decision techniques to store and deliver energy stored in the SC module properly. This can lead to optimal energy storage and its availability in different scenarios.  
Future work will focus on verifying this concept with the final profile using the SMPM drive, which can dynamically sink or source power based on external conditions.  
Conceptualization, P.R., S.K. and M.P.; methodology, M.P. and S.K.; software, P.R.; validation, S.K. and P.R.; formal analysis, S.K.; investigation, M.P. and P.R.; resources, M.P.; data curation, P.R.; writing--original draft preparation, P.R., S.K. and M.P.; writing--review and editing, S.K. and P.R.; visualization, M.P.; supervision, M.P.; project administration, P.R. and S.K.; funding acquisition, M.P. All authors have read and agreed to the published version of the manuscript.  
This work was supported by projects APVV-22-0330, \"Research of a system for active and optimal management of electrical energy using battery storage system\" and VEGA 1/0314/24, \"Research of a system for active management of electrical energy using battery storage system\".  
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.
# Optimal Energy Integration and Off-Design Analysis of an Amine-Based Natural Gas Sweetening Unit
## 4 Results and Discussion
### ORC Integration  
In contrast to direct energy integration, which was found to lead to considerable savings through all the investigated domains, secondary waste heat recovery exhibited a different behavior. As presented previously in Figure 6, the waste heat quantity and quality remaining after the first step were found to vary, respectively, between 10 and 50 MW and 90 and 120 \({}^{\circ}\)C. Consequently, the ORC net energy output varied considerably in the studied domain. The highest ORC performance is achieved at a low CO\({}_{2}\) content and high compression ratio, which is a consequence of the availability of relatively high-quality waste heat from the background process as well as an excess of energy from the first integration.  
Figure 6: Mapping of waste heat quantity and quality before (**a**) and after integration (**b**).  
In contrast, at a low CO\({}_{2}\) content and low compression ratio, the poor quality of available waste heat drastically reduces the energy conversion efficiency of the ORC system and results in very low power production.  
Moreover, the results reveal that the region with larger CO\({}_{2}\) content also presents high potential for secondary waste heat recovery via ORC integration. This feature can be seen in Figure 8, where the ORC net power output increases at CO\({}_{2}\) contents larger than 6% in the case of a pressure ratio of 2.66. In these conditions, due to the increase in the amine flow requirement and, by consequence, its waste heat potential, the sweetening process emerges as an additional source of waste heat along with the compressed NG.  
Figure 9 compares for one specific scenario the contributions of each waste heat source to the ORC power. The same trend was noticed for all other scenarios, where results show that the compression unit is the major contributor at low CO\({}_{2}\) content, whereas the amine unit is the major source of waste heat at high CO\({}_{2}\) content. This is explained by the fact that at higher CO\({}_{2}\) content, all the waste heat from the compression unit is harnessed in direct integration.  
Figure 8: ORC net power output at several conditions using R600a as working fluid.  
Figure 7: Evolution of heating requirements with CO\({}_{2}\) content before and after first integration at different compression ratios.
## 2 Materials and Methods
### Flocculation Activity  
Flocculation activity was quantified according to [18] (2019) using a kaolin clay suspension of 4 g/L. Kaolin suspension (50 mL) was aliquoted into 250 mL Erlenmeyer flasks and mixed with 1.5 mL of CaCl2 (1% \(w/v\)) and 1 mL of crude biofloculant sample. A control was prepared the same way but with the biofloculant being replaced by a sterile biofloculant production medium. The mixture was swirled and transferred into a 50 mL glass measuring cylinder. This mixture was left standing for 5 min at ambient temperature to settle. A sample of the top layer was withdrawn, and its optical density was read at 550 nm using a spectrophotometer (Jenway 7305 Spectrophotometer, Bibby Scientific Ltd., Staffordshire, UK). The flocculation activity was calculated using Equation (1), with the quantification being conducted in duplicates, and the average was used for reporting results.  
\[\%\textit{Floculation Activity}=\frac{\textit{A}-\textit{B}}{\textit{A}}*100 \tag{1}\]  
where:  
* \(A=\) absorbance of control, and
* \(B=\) absorbance of sample.
## 2 Theoretical Foundation and Sybil Attack Landscape
### Sybil Detection Algorithms
Such a table becomes the foundation for each node's assessment of whether its neighbor node is a Sybil. Such a table includes the signal strength measurements for the surrounding nodes. This information enables the algorithm to classify the investigated node. The data accumulated in such tables are obtained during direct node-to-node communication or even when an indirect node is engaged. [PERSON] et al. conducted two experiments to discern distinctive behaviors between Sybil and legitimate nodes. In experiment 1, they focused on distinguishing between the behaviors of Sybil and legitimate nodes, which was achieved by monitoring a node's RSS over time. A legitimate node typically enters another node's range gradually, strengthening its RSS as it becomes closer to the intended connections. Conversely, as it moves farther away, the RSS weakens. Figure 2 depictsthe RSS progression values over time for both Sybil and legitimate nodes. For legitimate nodes naturally entering and exiting a network, the plot generates a bell-shape RSS curve (Figure 2A) versus a Sybil node, which exhibits a higher RSS compared to a legitimate node, as depicted in Figure 2B, resulting in a constant line followed by a negatively sloping curve, signifying that the nodes enter with consistently high RSS values that diminish as the node departs the network. In the second experiment, the pace at which nodes entered the network significantly influenced the establishment of the threshold RSS value. It becomes crucial to ascertain the extent to which a node can traverse a specific node's range before being detected. To investigate the relationship between node speed, penetration distance, and RSS value, [PERSON] et al. [41] experimented on node \(X\) and \(Y\), where \(Y\)'s movement initiated away from \(X\) at varying speeds, while recording RSS values. Their findings revealed that a higher rate of movement allows nodes to penetrate into the range of other nodes while undetected. Such insights established the system threshold, assuming that no node could surpass a predetermined maximum speed.
## 4 Clutter Suppression Method
### Identification of Clutter Position
The cross-correlation coefficient \(r(s_{1i},s_{2i^{\prime}})\) of \(s_{1i}\) and \(s_{2i^{\prime}}\) can be calculated as  
\[r(s_{1i},s_{2i^{\prime}})=\frac{\text{cov}(s_{1i},s_{2i^{\prime}})}{\sqrt{D(s _{1i})}\sqrt{D(s_{2i^{\prime}})}}, \tag{16}\]  
where \(\text{cov}(\cdot)\) denotes covariance calculation and \(D(\cdot)\) represents variance computation. The clutter and background noise are independent of each other and uncorrelated with the  
Figure 8: Composition of echo signals in through-wall scenarios. echo from the human target. Cross-correlation coefficient \(r(s_{1i},s_{2i^{\prime}})\) can be equated to the correlation coefficient of clutter \(r(x_{1i},x_{2i^{\prime}})\), namely  
\[r(s_{1i},s_{2i^{\prime}})=\frac{\text{cov}(x_{1i},x_{2i^{\prime}})}{\sqrt{D(x_{1 i})}\sqrt{D(x_{2i^{\prime}})}}=r(x_{1i},x_{2i^{\prime}}). \tag{17}\]  
The specific operation is shown in Figure 9 using the position of the inner wall as the dividing line. The two pairs of bands, consisting of red and blue dots, represent two sets of symmetric clutter located on either side of the dividing line. The distance between them and the dividing line is labeled in the figure. In the calculated correlation matrix, the red dot represents the correlation coefficient of the two red bands, while the blue dot represents the correlation coefficient of the two blue bands. They signify the correlation between the front and back clutter originating from the same echo, so their values are situated near the maximum value. The orange dots denote the correlation between the left and right clutter from different echoes. Their values are not the largest but larger than the mean value.
# Onboard Processing in Satellite Communications Using AI Accelerators
## 3 Onboard AI Applications
### Use Cases
#### 3.1.2 FEC in Regenerative Payload
Hidden layer outputs are used as inputs of the delay layer, and those of the delay layer and the outputs of the delay layer are used as part of the inputs of the hidden layer the next time. Due to this structure, the RNN makes it possible to obtain outputs considering the inputs at a given time and the relationship between its inputs and those of the previous time step. These properties of the RNN suggest that the RNN can correct errors in the time series data flow by referring to the contexts obtained by supervised training. We can use the RNN as an FEC algorithm in the time series data.
# Life Cycle Assessment on a Biorefinery Approach to Pyrosis Oil for Wood Modification Treatment
###### Abstract
Therefore, little is known on the sustainability of using pyrolysis oil for material applications based on data originating from a demoplant scale operation. This study aims to determine the sustainability of replacing fossil creosote by biobased pyrolysis oil fractions for wood modification via an LCA methodology. This allows for the determination of the sustainability of this particular biobased application, as well as validating previous sustainability assessments on pyrolysis oil using real factory data. With the expectation that many more biobased products will be developed using pyrolysis oil or pyrolysis oil fractions, this study provides the principle of the pyrolysis oil platform and useful data from future sustainability assessments. In order to assess the sustainability of the process, an LCA methodology was applied. LCA is a structured, standardized method that has been widely accepted to determine the impact of processes or services on humans, the environment and the depletion of resources [19]. Limitations of the LCA methodology are that different practitioners may have variations in practices. Therefore, the modeling choices, study boundaries and assumptions made in this LCA are clearly presented in the materials and methods section. The sustainability of pyrolysis oil applications is likely to depend on the type of biomass feedstock. An alternative feedstock to the forestry residues that are commonly used in large scale pyrolysis processes could be maize digestate. Maize digestate is formed as a side product from the anaerobic digestion of maize and manure, a common practice to produce renewable energy in countries such as Germany [20]. This study investigates the use of maize digestate compared to forestry residues as feedstock for pyrolysis oil production and investigates the application of the sugar fraction from pyrolysis oil as a wood preservative treatment. In this application, the pyrolytic sugars that are be obtained by separating the pyrolysis oil fractions are intended to replace creosote. This article presents the results of the environmental impact evaluation, which consists of an LCA to compare the environmental impacts of the supply chain from biomass origin, pyrolysis oil production, pyrolysis fractionation to produce pyrolytic sugars, wood preservative treatment, use of the treated wood and the end of life of the treated wood. The LCA contains an analysis of 17 different environmental impacts clustered around three end points: Damage to human health, damage to ecosystems and damage to resources. The LCA provides quantitative insight in the environmental performance and possible environmental risks of the use of maize digestate for fast pyrolysis bio oil (FPBO), and the use of FPBO for wood preservative treatment. Finally, the results are brought into the context of other studies and life cycle assessments on fast pyrolysis. In particular, studies on the use of residual biomass [17; 21], the use of woody biomass [14; 16] and the production of bio-fuel and chemicals [15; 16; 22; 23] are applied.