esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 CCFD Self-Interference Suppression Performance
### RF-Domain Self-Interference Suppression  
Spatial-domain self-interference suppression has certain limitations and cannot eliminate SIS. The residual SIS remains stronger than the desired signal, necessitating further suppression in the RF domain [48]. RF-domain self-interference suppression involves processing at the RF front-end, where the idea is to estimate the residual SIS and remove it from the received RF signal, thereby preventing saturation of nonlinear components in the RF receiver chain [49].  
Based on current research, RF-domain self-interference suppression techniques can be broadly categorized into three types: direct RF coupling interference suppression [50], digitally assisted RF interference suppression [33], and high-isolation device design. Table 3 summarizes the status of RF-domain self-interference suppression. For received signals  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Reference** & **Year** & \
\begin{tabular}{c} **Central** \\ **Frequency/GHz** \\ \end{tabular} & **Bandwidth/MHz** & **Suppression Method** &
\begin{tabular}{c} **Best Suppression** \\ **Effect/dB** \\ \end{tabular} \\ \hline
[40] & 2020 & 19.7–21 & \(\backslash\) & Orthogonal polarization & 45 \\
[41] & 2020 & 21.5 & \(\backslash\) & Parasitic patches & 52.7 \\
[42] & 2021 & 28 & 80 & Cross-polarization & 57 \\
[43] & 2021 & 28 & 500 & Linear patch & 100 \\
[44] & 2022 & 24.125 & 500 & Feed structure decoupling & 70 \\
[45] & 2022 & 26–27 & 100 & Orthogonal polarization & 77 \\  & & & Electromagnetic bandgap & 109.1 \\
[46] & 2023 & 26.5 & 200 & structures & \\
[47] & 2024 & 17.7–21.4 & \(\backslash\) & Matching network design & 67 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Status of spatial-domain self-interference suppression for array antennas.  
Figure 3: Schematic diagram of self-interference suppression locations in CCFD systems.  
within the central frequency range of 20 GHz to 30 GHz, current techniques such as multi-tap channel reconstruction and the development of high-isolation devices can achieve RF-domain self-interference suppression exceeding 35 dB.
# YOLOv5-Sewer: Lightweight Sewer Defect Detection Model
## 2 YOLOv5-Sewer Network Design
### YOLOv5-Sewer Network Architecture  
The challenges posed by the complexity of sewer environments, homogenized images, and features such as medium- to long-distance dimness [29] present difficulties in sewer defect detection. These characteristics contribute to visual similarity, impacting the accuracy of defect detection and adding complexity to the network.  
In response to these challenges, this paper proposes enhancements to YOLOv5s, a lightweight model known for its outstanding performance in object classification and detection. The objective is to tailor this model to the swift and effective detection of defects within sewer systems. The framework of the proposed model, YOLOv5-Sewer, is depicted in Figure 1. This framework aims to address the unique challenges posed by sewer environments, providing a robust and efficient solution for defect detection in such complex scenarios.  
The enhancements to the YOLOv5s network in the proposed YOLOv5-Sewer model are as follows.  
1. The original backbone of the YOLOv5s network is substituted with MobileNetV3 block stacking. This modification is aimed at reducing the network's complexity.
2. The C3 module is upgraded to the C3-Faster module, incorporating partial convolutions. This adjustment focuses the network on crucial regions of the feature map, enhancing its ability to capture relevant information.
3. To counteract the reduction in detection accuracy resulting from the lightweight design, a convolutional block attention module (CBAM) and channel attention (CA) modules are integrated. These attention mechanisms help the network to adapt to the challenging visual characteristics of sewer environments.
4. The Efficient Intersection over Union (EIOU) localization loss function is introduced, replacing the original Complete Intersection over Union (CIOU) loss function. This adaptation allows the model to effectively handle multi-scale sewer defects.  
The improved YOLOv5-Sewer model demonstrates robust capabilities in detecting pipeline defects. It successfully mitigates the impact of dim backgrounds in severe environments, leading to enhanced accuracy in defect detection. Furthermore, the lightweight design reduces redundant computations, thereby lowering the training costs. This makes the model well suited for rapid defect detection in sewers on-site, particularly on low-configuration computing devices, owing to its optimized model size, computational efficiency, and detection speed.
# A Survey on Cyber Risk Management for the Internet of Things
## 4 Cyber Risk Assessment for IoT Survey Results  
IoT cyber risk management strategies assess and determine IoT risk based on risk _assessment_, which uses data from risk _identification_ processes. According to ISO [18], risk assessment can be broken down into three major processes, risk identification, risk analysis, and risk evaluation. Within the identification phase, the context of the system is built, with all entities that need to be protected being identified, as well as the potential threats to each entity. This information is then used to analyse risk, assessing probability and impact, with the risk evaluation being used to determine whether risk is tolerable. Therefore, the goal of carrying out cyber risk assessments is to formulate a risk acceptance criteria, perform a risk assessment, and produce results that are meaningful [18].  
For IoT cyber risk assessment, additional challenges different to traditional IT are present, with IoT breaches having been well documented within the vast number of environments that harness IoT, with one of the most notable being the Mirai botnet DDoS attacks affecting OVHcloud, Dyn, and Krebs on Security [37]. Overall, the identification and calculation of IoT risk must consider integral differences to become sufficient, with the surveyed papers discussed in this section showing the commonalities and differences in how these processes are undertaken; an overview of the results is found within Table 1.  
Figure 3: The proposed taxonomy of IoT cyber risk management concepts surveyed and the number of applicable papers. Each arrow signifies the filtering of surveyed papers that apply to each category.
###### Abstract  
The detection of adrenaline (Adr) is essential for monitoring physiological and clinical conditions, including stress response, cardiovascular health, and neurological disorders. We present a novel glass-nanopipet electrode sensor based on a non-redox ion-transfer approach using ion transfer across two immiscible electrolyte solutions (ITIES). Two ionophores, dibenzo-24-crown-8 ether (DB24C8) and dibenzo-18-crown-6 ether (DB18C6), were evaluated for their ability to facilitate Adr transfer across aqueous/dichloroethane interfaces. Among these, DB24C8 demonstrated superior stability, attributed to its larger ring size and stronger complexation with Adr. We systematically studied Adr transfer in various media, including KCl, DI water, Millipore DI water, and Tris buffer, and constructed calibration curves based on peak potential shifts that follow a power-law relationship with Adr concentration. The sensor achieved a detection limit of 5 pM in Tris buffer using DB24C8 and 50 pM with DB18C6, both significantly lower than the physiological concentration of Adr. Furthermore, the effects of pH and ionic strength on the peak shifts were analyzed, revealing that pH changes had a more substantial impact compared to ionic strength variations. Importantly, while DB24C8 and DB18C6 are known to facilitate the transfer of other cations, such as potassium and calcium, our findings confirm that these cation transfers do not interfere with Adr detection. This innovativeITIES-based sensing platform offers ease of fabrication, robustness, and excellent potential for real-time, in vivo applications. It represents a significant advancement in electrochemical detection technologies, paving the way for practical applications in clinical and physiological settings.  
adrenaline; ion transfer;ITIES; glass nanopipet; electrochemical sensing Article
# Impact of Mega Constellations on Geospace Safety
## 5 Discussion and Conclusions
The increase in frequency of avoidance operation after considering Starlink results in the increase of \(\Delta V\), and the change of \(\Delta V\) supports the huge avoidance consumption of target satellites after considering Starlink from the level of result. Starlink has a huge impact on the target satellite. (4) When avoidance is not performed in advance, the lifetime of the three satellites is shortened by 56.21%, 99.09%, and 99.82% after taking Starlink into account, and when avoidance is performed in advance, the lifetime of the three satellites is shortened by 10 revolutions without taking Starlink into account, assuming that the satellites can detect and avoid each warning event in advance. The lifetimes of the three target satellites can be extended by 380%, 502.6%, and 493.12%, respectively, but in the case of Starlink, the lifetime of the other two target satellites is extended by 155.44%, and the lifetimes of other two target satellites are shortened by 92.166%, 91.99%, respectively, according to the characteristics of the three target satellites combined with the data. According to the characteristics of the three target satellites and the data, the orbital altitudes of the target satellites change more after being affected by Starlink, so the effects of Starlink should be considered more thoroughly for some satellites with orbital altitudes in specific areas. We can see from the calculated values that taking Starlink into account makes the geospace environment of the three target satellites harsher, but some features cause a bigger impact than others. Of the three features considered in this paper, orbital altitude constitutes the biggest impact, followed by area and inclination. According to the findings, increasing the frequency of avoidance control after considering Starlink does not improve the risk situation, the results from avoidance control do not improve, and the deterioration of the geospace environment is irreversible. Given an orbital altitude higher than YAOGAN-3 SC, CORVUS BC5, and in advance, Starlink has significantly less effect on JILIN-01 GAOFEN 2D. Given early avoidance control, Starlink is guaranteed to not result in any impact on its mission lifetime, but for the first two, even with early avoidance control, less than 10 percent of the mission lifetime remains. Conceptualization, H.T., X.L., Q.Z. and X.C. ; methodology, H.T. and X.C. ; software, H.T. ; validation, H.T., W.M., Z.Z. and G.Z. ; formal analysis, H.T. ; investigation, H.T. ; resources, X.L., Q.Z. and X.C. ; writing--original draft preparation, H.T. ; writing--review and editing, H.T. and X.C. ; visualization, H.T. ; supervision, X.L. and Q.Z. ; All authors have read and agreed to the published version of the manuscript. **Funding:** This research received no external funding. **Data Availability Statement:** Not Applicable. **Acknowledgments:** The authors wish to thank the anonymous reviewers for their valuable suggestions. **Conflicts of Interest:** The authors declare no conflict of interest.
## 4 Experiment
### Hyperparameter Analysis  
We conduct a series of experiments on PEMS04 to analyze the impact of hyperparameter tuning. The investigated hyperparameters are the number of encoder and decoder layers of the temporal autoformer, the number of spatial-temporal blocks, and the learning rate decay. Table 7 exhibit the results. The hyperparameter settings are the same as depicted in Section 4.2 except for the investigated changes. We can see that the proposed model is not sensitive to the number of encoder and decoder layers of temporal autoformer and is relatively sensitive to the number of spatial-temporal blocks.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Model** & **MAE** & **MAPE (\%)** & **RMSE** \\ \hline MSSTTN & 18.64/18.97/19.44/20.05 & 13.16/13.41/13.69/14.29 & 30.17/30.81/31.54/32.39 \\ MSSTTN-attn & 19.93/21.21/22.45/23.91 & 14.17/15.03/15.89/17.02 & 31.17/33.06/34.80/36.70 \\ MSSTTN-single-3 & 19.03/19.46/19.99/20.76 & 13.44/13.75/14.21/14.92 & 30.53/31.29/32.09/33.09 \\ MSSTTN-single-5 & 18.70/19.06/19.49/20.07 & 13.22/13.53/13.89/14.46 & 30.21/30.87/31.56/32.36 \\ MSSTTN-single-7 & 18.68/19.00/19.45/20.04 & 13.08/13.30/13.67/14.24 & 30.28/30.89/31.61/32.40 \\ MSSTTN-GCN & 18.69/19.02/19.46/20.11 & 13.05/13.30/13.67/14.40 & 30.42/31.04/31.76/32.63 \\ MSSTTN-fixed & 18.63/18.98/19.43/20.04 & 13.16/13.48/13.82/14.37 & 30.19/30.86/31.58/32.41 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Comparison of ablation models.
# Dynamic Analysis and Security Characteristics of Carrier-Based Aircraft Arresting in Yaw Condition
## 5 Calculation and Analysis
### The Influence of Yaw Angle on the Tension of Arresting Cable  
The maximum yaw angle was taken as 9 degrees, and the variation trend of the tension of the unilateral arresting cable when the yaw angle was 0, 3, 5, 7, and 9 degrees was analyzed. The results are shown in Figures 12 and 13.  
The results of the maximum belt tension on the left side and the maximum belt tension on the right side under different yaw angles are listed in Table 3 for comparative analysis.  
Figure 12: The port tape tension.  
Figure 13: The starboard tape tension.  
It can be seen from the results that with the increase of the yaw angle, the cable tension of the left-side arresting system increases gradually compared with that of the centering arresting system, and the maximum belt tension of the left side with the yaw angle of 9 degrees is 445.31 kN. The belt tension of the right-side arresting system decreases gradually compared with that of the centering arresting system, and the maximum belt tension of the right side with the yaw angle of 9 degrees is 349.50 kN.  
The change trend of the tension of the two sides of the arresting belt was then analyzed, when the yaw angle was 0, 3, 5, 7, and 9 degrees. The results are shown in Figure 14.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Parameters** & **Centering** & **Yaw 3\({}^{\circ}\)** & **Yaw 5\({}^{\circ}\)** & **Yaw 7\({}^{\circ}\)** & **Yaw 9\({}^{\circ}\)** \\ \hline Port maximum & & & & & \\ belt tension & 373.76 & 381.63 & 397.25 & 420.06 & 445.31 \\ (kN) & & & & & \\ Starboard & & & & & \\ maximum belt & 373.76 & 365.74 & 360.35 & 354.93 & 349.50 \\ tension (kN) & & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 3: Comparison of the port and starboard maximum belt tensions of different eccentricity.  
Figure 14: The comparison of port and starboard tape tensions: (**a**) when yaw angle is 0\({}^{\circ}\); (**b**) when yaw angle is 3\({}^{\circ}\); (**c**) when yaw angle is 5\({}^{\circ}\); (**d**) when yaw angle is 7\({}^{\circ}\); (**e**) when yaw angle is 9\({}^{\circ}\).  
It can be seen from Figure 14 that with the increase of yaw angle, the tension difference between the two side belts is larger, and the tension of the left-side belt is larger than that of the right-side belt. Compared with the centering arresting, due to the different elongation of the arresting cables on the left and right sides, the speed of the pistons on either side is different, and the tension of the arresting belts on either side is different. The upper limit of cable tension is 784 kN, and yaw arrest does not cause drag to exceed this limit.
# Adaptive Beamformer Combined with Phase Coherence Weighting Applied to Ultrafast Ultrasound
## 2 Materials and Methods
### Gaussian Phase Coherence Factor (gPCF)  
The PCF is originally defined by the standard deviation of the phases of echo signals received by individual transducer elements [31] and used for weighting the beamformed echo signals to suppress echoes with focusing errors. In our previous study, the gPCF was proposed to enhance the effect of the PCF [36]. The gPCF is expressed as follows:  
\[\mathrm{gPCF}=\exp\left\{\rho\times\left(\frac{\sigma}{\sigma_{0}}\right)^{2} \right\}, \tag{16}\]  
where \(\rho\) is the control parameter, which was set at 3 in the present study [36]. Also, \(\sigma_{0}\) is the nominal standard deviation of \(\pi/3^{0.5}\) of the uniform distribution between \(-\pi\) and \(\pi\)[31], and \(\sigma\) is the standard deviation among phases of delay-compensated echo signals received by individual transducer elements or outputs from sub-aperture beamformers. When an echo is coming from the receiving focal point and sound speed in medium is homogeneous, no focusing error occurs and the gPCF is estimated to be 1. On the other hand, when an echo is coming from the out-of-focal point, phase variance increases and the gPCF falls to 0. In our previous study, the outputs of the sub-aperture beamformers were prepared and, then, the phase variance was estimated using outputs of the sub-apertures to suppress interferences from the out-of-focus echoes [35]. In the present study, the gPCF is estimated using the output \(y_{k}\) of each sub-aperture defined in Equation (8) (i.e., output signals before applying the adaptive beamformer weights).
## 3 Results and Discussion
### Direct Impacts of Gasifier Uptake on Household Livelihoods
#### 3.2.3 Reducing Time Spent on Cooking  
Fifty percent of the households using the gasifier reported spending less time cooking compared to three stone open fire [23]. This was mostly for the fast-cooking food types which did not need fuel refilling. Foods that took longer to cook required more of the cook's time because fuel reloading was necessary at some point during the cooking process. Use of a larger TLUD gasifier by rural households in Kenya was reported to save 18% of time that would have been spent on cooking if using the three-stone open fire [20]. In Idifu village in Tanzania, the time spent on cooking was reduced by 20% when an improved cook stove was used instead of a three-stone fire [30]. However, arranging fuel in the canister and lighting fuel takes more time than with three stone open fire.
## 4 Results and Discussion
### Gradient Tensor Analysis of Bou Azzer Inlier
The application of this method extends to both synthetic and real data. Its effectiveness is assessed by comparing it to other contour detection methods found in previous literature that rely on derivatives. The black lines (Figures 3 and 5) and the colored lines (Figure 7) demonstrate the undeniable effectiveness of our method in accurately indicating the location of the boundaries of causative bodies, even for anomalies caused by numerous intrusive sources. It is worth noting that the northern contact between serpentinites and basic rocks in the uplifted block shows a straight alignment, as does the southern contact. However, we must then emphasize that the most significant deposits are located on the southern interaction among quartz diorite and serpentinite. The application of GTA in the Bou Azzer uplifted block has yielded effective results. Thus, Figure 4 displays the amplitude maxima of horizontal invariants along the edges of the ophiolitic complex, marked by a tectonic contact with the surrounding rocks. In this case, regarding Figure 5, it becomes easy to identify the geological lineaments with theta map, enabling a better comprehension of the area's tectonic history. The effect of depth has been observed in the extension of the ophiolitic complex in the north-western part of the uplifted block. From a structural standpoint, the major Anti-Atlas fault-oriented WNW-ESE is more clearly visible on the gradient tensor maps (Figure 3), snaking through the northern portion of the aforementioned ophiolitic complex. We emphasize that the contact between the basic magmatism of Jbel Boho and the surrounding rocks is subcircular (Figure 4). Therefore, we recall that the northern contact is marked by the presence of dolomitic beds from the lower Adoudounian, while the southern contact is marked by the presence of dolomites. For the Foum Zguid dyke, we note that the maxima are located on either side of the center of said dyke [28]. Then said maxima show an elongation along the NE-SW direction.
## 2 Active Magnetic Bearing Rotor System Model
The electromagnetic force of four active magnetic bearings is written in matrix form, as shown in Equation (6). \[ \begin{bmatrix}f_{ax}\\ f_{bx}\\ f_{ay}\\ f_{by}\end{bmatrix} = \begin{bmatrix}k_{i}&0&0&0\\ 0&k_{i}&0&0\\ 0&0&k_{i}&0\\ 0&0&0&k_{i}\end{bmatrix}\begin{bmatrix}i_{ax}\\ i_{bx}\\ i_{ay}\\ i_{by}\end{bmatrix} + \begin{bmatrix}k_{x}&0&0&0\\ 0&k_{x}&0&0\\ 0&0&k_{x}&0\\ 0&0&0&k_{x}\end{bmatrix}\begin{bmatrix}x_{a}\\ x_{b}\\ y_{a}\\ y_{b}\end{bmatrix}  \tag{6}\]  
In the equation, \(F= \begin{bmatrix}f_{ax}&f_{bx}&f_{ay}&f_{by}\end{bmatrix} ^{T}\) is the electromagnetic force matrix, \(diag(k_{i},k_{i},k_{i},k_{i})\) is the current stiffness matrix, \(diag(k_{x},k_{x},k_{x},k_{x})\) is the displacement stiffness matrix, \(i= \begin{bmatrix}i_{ax}&i_{bx}&i_{ay}&i_{by}\end{bmatrix} ^{T}\) is the coil current matrix and \(q= \begin{bmatrix}x_{a}&x_{b}&y_{a}&y_{b}\end{bmatrix} ^{T}\) is the displacement matrix. The equation of motion of the four-degrees-of-freedom AMB rotor system can be obtained by bringing Equations (2) and (6) into Equation (4), as shown in Equation (7). \[MT\ddot{q}+G\dot{q}=BF \tag{7}\]  
When the AMB rotor is slender and the working speed is low, the distribution characteristics of the rotor's moment of inertia substantially reduce the contribution of gyroscopic torque to the system's dynamic response. Meanwhile, the angular momentum rate under low-speed operating conditions is insufficient to excite significant gyroscopic effects. Based on this physical characteristic, the gyro coupling term can be ignored. Therefore, Equation (7) can be simplified to Equation (8). \[q=T^{-1}M^{-1}BF \tag{8}\]  
Equation (8) is expanded into Equation (9). \[ \begin{bmatrix}x_{a}\\ x_{b}\\ y_{a}\\ y_{b}\end{bmatrix} =\begin{bmatrix}\frac{1}{m}+\frac{\dot{q}_{x}}{y}&\frac{1}{m} -\frac{\dot{q}_{x}l_{b}}{l_{x}}&0&0\\ \frac{1}{m}-\frac{\dot{q}_{x}}{y}&\frac{1}{m}+\frac{\dot{q}_{y}}{y}&0&0\\ 0&0&\frac{1}{m}+\frac{\dot{q}_{x}}{l_{x}}&\frac{1}{m}-\frac{\dot{q}_{x}l_{b}}{ l_{x}}\\ 0&0&\frac{1}{m}-\frac{\dot{q}_{x}l_{b}}{l_{x}}&\frac{1}{m}+It can be seen from Equation (10) that the movement of the AMB rotor in the _x (y)_ direction is independent of the force in the _y (x)_ direction. The movement of one end of the AMB rotor in the _x (y)_ direction is little affected by the force in the _x (y)_ direction at the other end of the rotor. Therefore, for a rigid rotor, it can be considered that the motion of the AMB rotor in the four degrees of freedom is decoupled, and the four degrees of freedom can be decoupled.