esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Masked Addressing  
Because unreliable ID bits may lead to identification errors, some method for ensuring reliable identification is required. One obvious possibility would be to simply exclude all chips that have unreliable ID bits from use, but this would significantly reduce the yield, particularly in systems employing large numbers of ID bits.  
An alternative is to record which ID bits of a particular chip are reliable, and then exclude the unreliable ID bits from use during identification. This is accomplished by recording two numbers for every chip: an \(N\)-bit ID code \(C\), and an \(N\)-bit code mask \(M\). Each bit \(M_{i}\) is equal to \"1\" if the corresponding ID code bit \(C_{i}\) is reliable, and equal to \"0\" if \(C_{i}\) is unreliable. The values of \(C_{i}\) and \(M_{i}\) can be determined from the reliability tests as indicated in Table 1.  
To identify a particular chip \(A\), an external reader transmits both \(C_{A}\) and \(M_{A}\). Every chip receives this code and activates its ID generator, which produces a generated code, \(G\), and then tests the following equality  
\[C_{A}\ \ \&\ \ M_{A}=G\ \ \&\ \ M_{A} \tag{11}\]  
If this equality is true, the chip can determine it is being addressed. Because the generated code, \(G_{A}\), will only vary from \(C_{A}\) among the bits excluded by the mask, \(M_{A}\), this will ensure reliable identification. The protocols for initial chip characterization and subsequent chip identification are given below.
## 4 Conclusions  
An experimental study was initiated to assess the SD technology efficiency in textile wastewater treatment with bentonite added in it by investigating the colour and the suspended solids removals and to establish the influence of effluent flowrate and disc rotational speed on the process. For the investigated disc rotational speed and flowrate values, the highest suspended solids removal values ranged from 50% up to 61.13% and, for the discoloration, from 33.16% up to 49.64%, which indicates a satisfactory efficiency of the SD technology within the laboratory setup. Furthermore, these maximum values pertain to increasing trends, which indicates that even higher values may be obtained, given longer working time periods.  
After applying an active central composite rotatable 2\({}^{3}\) design, the mathematical models with three independent variables (WW flowrate, rotational speed, working time) for suspended solids removal (\(Y_{1}\)) and discoloration degree (\(Y_{2}\)) were proposed, associated with their optimal values. For short period of SD setup working, meaning no more than 24 min, the values of removal were relatively good in the case of suspended solids (33.706-45.344%) and low for discoloration (13.819-25.644%), considering that no other treatment process (physical, chemical, or biological ones) was applied.  
Figure 9: Variation in the WW suspended solids removal (\(Y_{1}\)) vs. one independent variable (\(X_{i}\)) (two variables were constant at the basic value): (**a**) \(Y_{1}\) = \(Y\)(\(X_{1}\),0,0); (**b**) \(Y_{1}\) = \(Y\)(0,\(X_{2}\),0); (**c**) \(Y_{1}\) = \(Y\)(0,0,\(X_{3}\)); and (**d**) variation of WW discoloration (\(Y_{2}\)) vs. one independent variable (\(X_{1}\)).  
This modeling and optimization study represents a pertinent application of the SD technology in the textile wastewater treatment for suspended solids and color removal.  
This research is prone to other improvements by additional chemical processes (e.g., advanced oxidation by Fenton oxidation), especially for organics removal from textile wastewaters.  
The contribution of both authors is equal. Both authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors declare no conflict of interest.
## 3 Results
### Effect of Extract on Cell Viability
#### 3.6.1 Effects of Leaf Extract on Inflammatory Markers in RAW 264.7 Cells Stimulated by LPS  
As a strong pro-inflammatory cytokine, TNF-\(\alpha\) exhibits a substantial role in the immune system during inflammatory process [33]. In this study, the inhibitory role of the extract was investigated on the release of proinflammatory cytokines such as TNF-\(\alpha\) and IL-6 in RAW 264.7 cells. Treatment of RAW 264.7 macrophages with LPS caused a noteworthy increase in IL-6 and TNF-\(\alpha\) in the supernatants. However, the extract significantly decreased the LPS-induced production of TNF-\(\alpha\) and IL-6 in a concentration-dependent manner (Figure 6). These results designate that the extract shows anti-inflammatory activity through a decrease in pro-inflammatory cytokines TNF-\(\alpha\) and IL-6 in LPS-stimulated RAW 264.7 cells.  
Figure 5: Effects of extract on cell viability in RAW 264.7 macrophages. The cells were treated with the extract (0, 100, 200, 400, 600, 800 and 1000 \(\mathrm{\SIUnitSymbolMicro g}\)/mL) in the presence of LPS (1 \(\mathrm{\SIUnitSymbolMicro g}\)/mL) for 20 h. MTT assay was used to examine the cell viability. Data are presented as mean \(\pm\) SD (\(n=3\)). Mean values denoted by (*) are significantly different (\(p<0.05\)).  
Figure 6: Anti-inflammatory extract on LPS-induced RAW 264.7 macrophages. Cells were pre-treated with various concentrations of extract for 1 h and treated with LPS for an additional 20 h. IL-6 and TNF-\(\alpha\) were measured by an enzyme-linked immunosorbent assay (ELISA) kit. The data are presented as means \(\pm\) SD (\(n=3\)). (*, \(p<0.05\) LPS group vs. extract group).  
3.6.2 Effects of the Extract on in the Total Number of Cells, Neutrophils and Macrophage Cell Counts  
After 24 h of LPS administration, neutrophils, macrophages and total number of cells were counted in different groups in the bronchial alveolar lavage fluid (BALF). LPS meaningfully increased the total number of cells (18.3 \(\times\) 10\({}^{5}\) /mL), neutrophils (12.2 \(\times\) 10\({}^{5}\) /mL) and macrophages (0.38 \(\times\) 10\({}^{5}\) /mL) compared to the control group. However, extract pretreatment of the LPS administration showed a substantial decrease in the total number of cells (12.2 \(\times\) 10\({}^{5}\) /mL and 8.4 \(\times\) 10\({}^{5}\) /mL), neutrophils (7.3 \(\times\) 10\({}^{5}\) /mL and 6.4 \(\times\) 10\({}^{5}\) /mL) and macrophages (0.28 \(\times\) 10\({}^{5}\) /mL and 0.22 \(\times\) 10\({}^{5}\) /mL) (Figure 7).
## 3 Design Consideration for g-C\({}_{3}\)N\({}_{4}\)/CQDs-Based Nanocomposites
### g-C\({}_{3}\)N\({}_{4}\)/CQDs-Based Nanocomposites for Different Antibiotic Degradation
The absorption range of CdIn\({}_{2}\)S\({}_{4}\) was simultaneously increased by the introduction of CQDs, whereas light absorption spectrum was found to be weaker for ternary g-C\({}_{3}\)N\({}_{4}\)/CQDs/CdIn\({}_{2}\)S\({}_{4}\) due to the shielding effect of g-C\({}_{3}\)N\({}_{4}\), along with a band gap of 2.26 eV. Although photostability of the hybrid influences photoactivity, other parameters, such as change migration resistance and charge pairs separation efficiency, also played an important role in the degradation process. Thus, photoluminescence and transient photocurrent density analysis suggested the rate of recombination of charge pairs. The photocurrent responses were found to be greater for g-C\({}_{3}\)N\({}_{4}\)/CQDs/CdIn\({}_{2}\)S\({}_{4}\) photocatalysts than bare CdIn\({}_{2}\)S\({}_{4}\), owing to the fast photoexcited transport of charges from CQDs and, finally, the photocatalytic performance was increased. From photoluminescence spectra showed intense peak for CdIn\({}_{2}\)S\({}_{4}\) at 562 nm was attributed to strong recombination between charge pairs, while, with addition of CQDs, the intensity peak was lowered and negligible peak was found for the ternary g-C\({}_{3}\)N\({}_{4}\)/CQDs/CdIn\({}_{2}\)S\({}_{4}\) composite. These characteristic techniques results indicated that g-C\({}_{3}\)N\({}_{4}\)/CQDs was responsible for the improved charge separation efficiency. Furthermore, [PERSON] et al., investigated a novel CQDs and reduced graphene oxide (rGO)-altered g-C\({}_{3}\)N\({}_{4}\)-CQDs/rGO-g-C\({}_{3}\)N\({}_{4}\) composites for chloramphenicol degradation under solar light irradiation [73]. The optimized g-C\({}_{3}\)N\({}_{4}\)-CQDs/rGO-g-C\({}_{3}\)N\({}_{4}\) composite achieved outstanding photocatalytic activity in chloramphenicol degradation, which was about 92.4% within 120 min and 99.1% within 90 min under sunlight and visible-light illumination, respectively. This excellent photoactivity of all the photocatalysts was owed to their sufficient charge pairs separation efficacy through the migration of charge carriers among the band potentials, CQDs and rGO. Here, CQDs had shifted the type-II heterostructure into direct Z-scheme routes and improved the photodegradation efficacy by 10-fold, i.e., 0.0810 min\({}^{-1}\), in comparison to pristine g-C\({}_{3}\)N\({}_{4}\) 0.00802 min\({}^{-1}\). Additionally, the amount of \({}^{\bullet}\)O\({}_{2}\)\({}^{-}\) and \({}^{\bullet}\)OH radical generation was increased after Z-scheme formation, rather than individual-doped photocatalysts, which promoted the photocatalytic activity. The overview of g-C3N4/CQDs based photocatalyst for pollutant degradation has been given in Table 1.
## 1 Introduction
For instance, operators may exhibit faster and more decisive movements when relying on visual and/or audio feedback from the guidance system. Although an increase in productivity is anticipated, there remains a lack of empirical research and field testing specifically quantifying improvements in operator activity under machine guidance. To understand the mechanisms through which machine guidance enhances operator efficiency, micro-level analysis comparing manual and machine-guided excavation is necessary. Previous studies demonstrating significant productivity increases using 30 min comparative trials were limited by variations in excavator specifications, manufacturers, and operators' skill levels, thus confounding the results [7]. Therefore, this study included a controlled experiment to compare the differences in operator activity between manual and machine-guided excavator operations. For this purpose, an excavator was deployed on a real construction site where actual footing foundation excavation was performed. To investigate the efficiency of operational tasksand changes in operator activity, in-depth analysis was conducted, encompassing metrics such as excavation duration, cycle time, and movement of the boom arm and tracks, and quantitative scoring of bucket fill factors. Through this analysis, the current study aimed to quantify the extent of behavioral modification induced by machine guidance and provide empirical evidence of the system's impact on operators' actions. The results will not only contribute to a deeper understanding of the man-machine interaction in the context of advanced construction equipment but also offer insights into how to encourage more proactive utilization of machine guidance by operators, ultimately enhancing its effectiveness in practical settings.
# Effect of Control Measures on Wheel/Rail Noise When the Vehicle Curves
## 3 Results and Discussions
### Effect of Wheel/Rail Friction Coefficients on Wheel/Rail Noise under Lateral Excitation  
This section investigates the effect of friction coefficient between wheel and rail on vibration and wheel/rail noise under lateral excitation. The friction coefficient of 0.012-0.3 are chosen for analysis because they cover the range of common friction coefficients. The value of 0.3 represents dry friction coefficient. The value of 0.012 represents the friction coefficient considering the third medium--oil between wheel/rail interface. The values of 0.1 and 0.05 represent friction coefficients between dry status and oil status.  
Figure 13a,b give the lateral accelerations of leading wheel with different friction coefficients in time domain and frequency domain. It can be seen that the acceleration decreases obviously at curve squeal frequencies as the friction coefficient increase. Figure 14a,b give the SPLs with different friction coefficients in time domain and frequency domain. It can be seen that SPLs also have a good reduction in significant peaks after reducing the friction coefficient. The sound reduction (SPL) of wheel considering lubricant can reduce 10-25 dB corresponding to the friction coefficient of 0.012-0.05, compared with the SPL of friction coefficient of 0.3. Therefore, it suggests that proper lubrication between the wheel and rail interface can reduce squeal noise effectively.  
Figure 13: Accelerations with different friction coefficients in (**a**) time domain and (**b**) frequency domain (simulation results).
# Sensitivity Analysis of Multi-Temporal Sentinel-1 SAR Parameters to Crop Height and Canopy Coverage
###### Abstract  
The Polarimetric Synthetic Aperture Radar technique has provided various opportunities and challenges in agricultural activities mainly on crop management. The aim of this study is to investigate the sensitivity of 10 parameters derived from multi-temporal Sentinel-1 Synthetic Aperture Radar (SAR) data, to crop height and canopy coverage (CC) of maize, sunflower, and wheat. The correlation coefficient values indicate a high correlation for maize during the early growing stage. The coefficient determinations (R\({}^{2}\)) of 0.82 and 0.81 indicate that there is a strong relationship between the maize height and SAR parameters including VV + VH and VV, respectively. The maize CC is well correlated with VV parameter (R\({}^{2}\) = 0.73), but it is observed that at the later growing stage the correlation became weaker. This means that the sensitivity decreases with increasing vegetation cover growth. Compared to maize, the sensitivity of SAR parameters to wheat variables is often good at the early stage. However, the highest correlation with wheat height represented by Alpha (\(\alpha\)) decomposition parameter (R\({}^{2}\) = 0.67). The sunflower height has an insignificant correlation with the majority of SAR parameters and only VH polarization shows low sensitivity (R\({}^{2}\) = 0.31). The sunflower CC shows relatively higher correlation with VV polarization (R\({}^{2}\) = 0.46) at the early stage while no considerable correlation is observed at the later stage. It is found that Sentinel-1 has a high potential for estimation of crop height and CC of the maize as a broad-leaf crop. The same is not true for sunflower as another broad-leaf crop.  
PolSAR; Sentinel-1 dual polarimetric SAR; scattering coefficient; agricultural monitoring; crop variables +
Footnote †: journal: Applied Sciences
# Concealed Object Detection and Recognition System Based on Millimeter Wave FMCW Radar
## 2 Materials and Methods
### Synthetic Aperture Radar (SAR) and Multiple-Input Multiple-Output (MIMO) Radar Antennas Technique
#### 2.2.3 Image Resolution  
The resolution of reconstructed image depends on wavelength, scan length and target distance. For two-dimensional imaging, the horizontal (\(X\)-axis) and longitudinal (\(Y\)-axis) resolutions are estimated to be [2; 16]:  
\[\delta_{x}=\frac{\lambda z_{0}}{2D_{x}}\,\ \delta_{y}=\frac{\lambda z_{0}}{2D_{y}} \tag{3}\]  
where \(D_{x}\) and \(D_{y}\) are the physical lengths of the two-dimensional scan length. According to \(Z_{0}=90\) mm, \(D_{x}=90\) mm, \(D_{y}=98.67\) mm, \(\lambda=3.798\) mm. The image resolution in \(X\) and \(Y\) directions are \(\delta_{x}=1.90\) mm and \(\delta_{y}=1.73\) mm.
# Crowd Evacuation Guidance Based on Combined Action Reinforcement Learning
## 3 Results
### Experimental Results and Analysis
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Method** & **Period Reward** & **Evacuation Time (s)** \\ \hline Static sign & \(-206.77\) & \(41.35\) \\ Dynamic shortest path & \(-160.92\) & \(32.18\) \\ CA-DQN-mean & \(-158.25\) & \(31.65\) \\ CA-DQN-max & \(-160.40\) & \(32.08\) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparison of evacuation times using different methods. Figure 6: Six moments in a typical evacuation process. In Figure 6d,e, the congestion at the left exit has been relieved. The right exit is expected to have more people being evacuated; consequently, the agent will lead the remaining people in the lower-left area to the left exit. Notice the first and third signs in the upper channel of Figure 6e seem to be unexpected. This phenomenon is because jamming will slow down the crowd in the simulation environment. The agent learned this feature and tries to delay part of the crowd to avoid exit congestion. Finally, in Figure 6f, the crowd is evacuated from both sides of the exit simultaneously, indicating that the crowd evacuation guide agent has maximized the crowd evacuation efficiency. The signs of empty areas in Figure 6f will not affect the evacuation efficiency, and the agent cannot learn from feedback; therefore, the signs in these areas are uncertain. The number of people initialized in the simulation scene was changed, and 100 cycles of evacuation simulation were run. A comparison of the evacuation effects of different methods is shown in Figure 7. When the number of people was small, each channel could remain unobstructed, and the static guidance method was effective. When the number of people increased, the static guidance method was affected more, while CA-DQN and the dynamic shortest path method avoided crowd congestion. When the number of people increased to more than 80, the three dynamic methods' evacuation effect was better than the static method. The CA-DQN-mean method, which used the average value of TD errors in each dimension to define the sample priority according to Formula (13), performed better than the dynamic shortest path method. The effect of the CA-DQN-max method, which was defined by Formula (12), was equivalent to that of the dynamic Dijkstra shortest path method. The experimental results show that, compared with static signs that cannot perceive crowd distribution information, the proposed CA-DQN reinforcement-learning-based crowd evacuation guidance method can dynamically adjust the display signals of the guidance signs, and effectively improve the efficiency of crowd evacuation. Compared with the dynamic Dijkstra shortest path method that is based on topological map modeling, the proposed method demonstrated higher evacuation guidance efficiency, while avoiding the workload and potential manual errors of artificial topology map construction.
# Inertial and Flexible Resistive Sensor Data Fusion for Wearable Breath Recognition
###### Abstract
* The inherent sensitivity of flex sensor data to nonbreathing activities was addressed, a primary drawback of body motion signals was mitigated, and the device's reliability was enhanced in diverse usage scenarios. * We introduced a cost-effective wearable device consisting of an off-the-shelf IMU and flex sensor that can accurately measure breathing rates, even in the presence of body motion resulting from physical activity. * The system was tested against gold-standard spirometry data across six participants (three males and three females) and showed consistent accuracy across various breathing patterns. * The noninvasive and compact nature of this device ensures improved patient compliance and comfort, making it a valuable tool for continuous monitoring in both clinical and home environments.
## 5 Fatigue Life Calculation of Jiangyin Bridge Based on the Stress Integration Approach
### Grinding Treatment
#### 6.2.2 Influence of Grinding Radius  
Figure 23 shows the finite element models with different grinding radii of GT2 under WT-4. In Figure 23, 12 mm is the maximum grinding radius to ensure that both the deck and the rib are not weakened. For WT-1, WT-2, WT-3, WT-4 and WT-5, the maximum grinding radius is 6 mm, 8 mm, 14 mm, 12 mm and 14 mm, respectively. After the grinding treatment, all the welds meet the requirements in the code that the height of the weld throat is not less than the thickness of the rib [38].  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Grinding Type** & \(r\) **(mm)** & \(d\) **(mm)** & \(\varphi\) **(o)** & \(S_{s}\) **(MPa)** & \(N_{a}\) **(years)** \\ \hline Non-grinding & — & — & — & 55.35 & 84 \\ GT1 & 3 & 0.5 & 70 & 58.53 & 63 \\ GT2 & 3 & 0 & 50 & 54.31 & 92 \\ \hline \hline \end{tabular}
\end{table}
Table 8: The effects of different grinding types on fatigue life.  
Figure 22: Grinding type. (**a**) Grinding type 1. (**b**) Grinding type 2.  
According to the fatigue life calculation steps in Section 5.4, the variation of the fatigue life with the grinding radius for GT2 under different weld types is shown in Figure 24.  
In this figure:  
(1) A comparison of WT-1, WT-2 and WT-3 shows that when the grinding radius changes from 0 to 2 mm, the fatigue life of WT-1, WT-2 and WT-3 increases by 14%, 5% and \(-\)1.5%, respectively. This indicates that the grinding treatment has an obvious effect on increasing fatigue life when the angle \(\alpha_{2}\) between the deck and the weld is large.  
(2) When the grinding radius is greater than 2 mm, the curves of the fatigue life as they vary with the grinding radius under different weld types are almost parallel, which indicates that when the grinding radius is large, the influence of the grinding radius on the fatigue life has little relation to the weld type.  
(3) For different weld types, when the grinding radius is greater than 2 mm, the fatigue life at the weld toe increases with the increase of the grinding radius. The fatigue life increases by approximately 5% when the grinding radius increases by 2 mm.  
(4) A larger grinding radius is conducive to improving the bridge fatigue life, but at the same time, it can increase the weakening of the weld seam itself, which may lead to cracks in the weld throat. Therefore, further experimental research is needed to select an appropriate grinding radius which both ensures fatigue cracks do not appear in the weld throat and maximizes the fatigue life at the weld toe.