esa-sceva/satcom-chunk-collection huggingface dataset:
## Evaluation and Results
### Random Network Formation
#### 5.5.4 Summary  
As with the more controlled grid topology, a significant improvement in energy consumption is again evident when MADCAL is implemented. However, in this more random scenario there is improvement across all speeds, even as the interference range reduces. As such, compared to the controlled grid topology, the improvements in network lifetime are greater, especially so at faster sink speeds. When considering frame delivery, there are no significant improvements when using MADCAL other than at 10 mps. However, frame delivery improves slightly or stays roughly the same and is generally consistent across all speeds once MADCAL is in use. As such MADCAL can be seen as improving energy consumption considerably, whilst generally improving frame reception to the point where sink speed is mostly negated.
# Continuous-Wave THz Imaging for Biomedical Samples
###### Abstract  
In the past few decades, the applications of terahertz (THz) spectroscopy and imaging technology have seen significant developments in the fields of biology, medical diagnosis, food safety, and nondestructive testing. Label-free diagnosis of malignant tumours has been obtained and also achieved significant development in THz biomedical imaging. This review mainly presents the research status and prospects of several common continuous-wave (CW) THz medical imaging systems and applications of THz medical imaging in biological tissues. Here, we first introduce the properties of THz waves and how these properties play a role in biomedical imaging. Then, we analyse both the advantages and disadvantages of the CW THz imaging methods and the progress of these methods in THz biomedical imaging in recent ten years. Finally, we summarise the obstacles in the way of the application of THz bio-imaging application technology in clinical detection, which need to be investigated and overcome in the future.  
t +
Footnote †: journal: Medical Imaging  
1 Faculty of Science, College of Physics and Optoelectronics, Beijing University of Technology, Beijing 100124, China; [EMAIL_ADDRESS] (Y.Z.); [PERSON]L_ADDRESS] (S.W.)  
2 Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China; [EMAIL_ADDRESS] (S.W.)  
3 Department of Electronic Engineering, Tsinghua University, Haidian District, Beijing 100084, China; [EMAIL_ADDRESS] (B.H.); [EMAIL_ADDRESS] (Y.Z.)  
4 Beijing Engineering Research Center of Precision Measurement Technology and Instruments, Beijing 100124, China;  
5 Academy of Medical Science, Peking Union Medical College, Beijing 100730, China  
* Correspondence: [EMAIL_ADDRESS] (D.W.); [EMAIL_ADDRESS] (L.R.); [EMAIL_ADDRESS] (Y.Z.); Tel.: +86-010-67391741 (D.W.); +86-010-67391741 (L.R.); +86-010-69152830 (Y.Z.)  
These authors contributed equally to this work.
## 4 Settings, Results and Discussion
### Comparisons with State-of-the-Arts
#### 4.3.1 Performance on VQA-CP v2  
**Setting.** The authors of this paper combine LBSD with LMH and name it LBSD-LMH. For fair comparisons, the authors of this paper choose the debiased method based on UpDn. According to the principles of reducing language bias, the authors of this paper divide the methods into groups: (1) Strengthening visual information [24; 25]. (2) Weakening language priors [29; 31; 32]. (3) Using various data enhancement and data balance [36; 68].  
Since LBSD improves the performance by enabling the model to focus more on visual information and difficult samples (the model cannot answer based on language bias), the authors of this paper compare other methods with those in the first and second groups. Moreover, according to the experiment settings of CSS [36], the authors of this paper test and calculate the gap index as an auxiliary index on VQA v2 to verify the robustness of the model.  
**Results.** Comparisons are reported in Table 6. As shown in Table 6, compared with other methods with UpDn as the standard VQA model, LBSD improves the performance on VQA-CP v2. The gap index has also been improved (\"All\" and \"Other\"). The results show that the proposed LBSD can reduce language bias in VQA. For individual items, such as Num, yes/no and others, CFVQA is slightly higher than our method in num index; it is an ensemble method based on causal inference. Similar to boosting, CFVQA uses more  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Model** & **Overall** & **Yes/No** & **Num** & **Other** \\ \hline Bias Product * & 39.86 & 41.96 & 12.59 & 46.25 \\ +**LBSD**-with & 40.06 & 43.31 & 12.41 & 45.94 \\ LMH & & & & \\ +**LBSD**-same & **40.47** & 44.28 & 12.28 & 46.21 \\ stu & 40.02 & 45.09 & 12.30 & 44.96 \\ +**LBSD**-with & 40.60 & 44.92 & 12.56 & 46.03 \\ LMH & **41.28** & 47.07 & 12.30 & 46.20 \\ stu & 52.05 & 69.81 & 44.46 & 45.54 \\ +**LBSD**-with & 53.89 & 75.25 & 43.58 & 45.52 \\ Bayesian product +**LBSD**-with & 53.82 & 75.56 & 41.79 & 45.73 \\ Reweight & **54.27** & 75.49 & 44.02 & 45.96 \\ \hline \hline \end{tabular}
\end{table}
Table 5: VQA-CP v2: Heterogeneous student networks. * indicates the results from our reimplementation using officially released codes.  
ensemble networks as additional information than ours. Therefore, it is unfair to compare directly on small indices.
## 5 Conclusions and Limitations  
### Major Work and Conclusions  
This investigation presents a comprehensive analysis of China's railway transportation network resilience through the integration of resilience theory and complex network analysis methodologies. Through the construction of dual-layer network models encompassing both physical infrastructure and service operations, this study has systematically identified critical vulnerabilities and evaluated the efficacy of various recovery strategies under diverse disturbance scenarios.  
The empirical results demonstrate that targeted disruptions (external attacks and passenger/freight flow fluctuations) induce significantly more severe degradation of network performance compared to stochastic disturbances (natural disasters and technical failures), particularly when nodes with high betweenness centrality are compromised. The simulation analyses reveal differentiated resilience characteristics across the three dimensions examined:  
1. Accessibility: The network exhibits pronounced vulnerability to targeted attacks directed at hub stations, resulting in accelerated deterioration of connectivity metrics. Conversely, stochastic disturbances permit the maintenance of essential functional connections for extended periods, as evidenced by the gradual decline in reachable node pairs.
2. Invulnerability: The cascade failure model elucidates that perturbation events exceeding certain critical thresholds can precipitate system-wide failures through load redistribution mechanisms. Statistical analysis indicates that the network's capacity to withstand cascading failures diminishes exponentially once key nodes are compromised.
3. Restorability: Comparative analysis of recovery strategies demonstrates the statistical superiority of betweenness-based approaches over both degree-based and random methodologies, with recovery efficiency improvements of 36.2% and 78.5%, respectively, in targeted attack scenarios.  
These empirical findings have several significant implications for railway infrastructural planning and operational management:  
Infrastructural Planning: The implementation of topological redundancy for stations exhibiting high betweenness centrality values represents a critical strategy for mitigating single-point vulnerabilities within the network architecture.  
Emergency Response Frameworks: Railway administration entities should establish differentiated response protocols calibrated to the disturbance typology, with expedited intervention mechanisms specifically designed for targeted disruption scenarios.  
Recovery Resource Allocation: The optimization of maintenance and restoration resource allocation should prioritize nodes based primarily on betweenness centrality metrics rather than solely on degree centrality or geographical considerations.
## 1 Introduction
demonstrated a fixed-time extended state observer (FTESO) for marine surface vessel trajectory tracking [30]. In [31], fixed-time neuroadaptive practical tracking control based on an extended state observer was proposed for a quadrotor unmanned aerial vehicle with external disturbances and time-varying parameters. It can be concluded that ZNNs have not been applied to mobile robot dynamic control, since its application faces unsolved challenges. One is that unmeasured velocities encountered in practice lead to failure in building a ZNN control framework. The other is how to achieve noise suppression and fast convergence simultaneously. To address the above challenges, a novel activation function with fixed-time convergence and noise suppression is introduced. Then, an FTESO is employed to estimate the unmeasured velocities and quickly construct a ZNN model. Finally, a fixed-time-convergence ZNN model (FXZNN) based on the FTESO is proposed in this paper to achieve the fast tracking of the desired velocity, as well the trajectory, even with unmeasured velocities and external disturbances. To the best of our knowledge, this is the first ZNN control framework based on an observer for TMR tracking control. The main contributions of this paper are as follows:  
1. An FTESO is designed to estimate the TMR's unmeasured velocity as well the lumped disturbances in the system. 2. An FTESO-based FXZNN model is proposed to improve the desired velocities, convergence speed and tracking control performance of the system with the novel activation function adopted. 3. The velocity estimation error between the estimation and the actual values is adopted for constructing the error function of the proposed ZNN model. This paper is organized as follows: Section 2 presents the modified TMR kinematic and dynamic model. Section 3 describes the tracking problem of the TMR. In Section 3, we demonstrate the design of the FXZNN model based on an FTESO for the TMR and present the corresponding stability analysis of the model using Lyapunov theory. Simulation results of the proposed model are given in Section 4, followed by the conclusion in Section 5.
# Cost-Effective Satellite Ground Stations in Real-World Development for Space Classrooms
## 4 Optimizing Ground Station Systems Through Numerical Design
### The Parameters for Calculating the Capabilities of the Ground Station  
The key parameters for designing a ground station to receive signals from satellites in orbit are explained in detail under each subsection as follows.
## 4 Experiments and Results  
### System Hardware  
Calibration experiments were carried out to verify the proposed method using the developed DPMD measurement system, as illustrated in Figure 7. The setup consisted of a CCD camera, two LCD screens, a beam splitter plate, and a mirror with a matrix of hollow ring markers. The camera was the model ECO655 CVGE from SVS (Bremen, Germany), and had a resolution of 2448 \(\times\) 2048 pixels. Two small size LCD screens were used in the DPMD system. The two LCD screens were the model LP097 QX2 from LG (Seoul, Korea) and had a resolution of 2048 \(\times\) 1536 pixels. However, they were low quality and the flatness was not so good. The three angular displacement platforms had a minimum readout of 5\({}^{\prime}\) from Micro-nano Optics Automation Equipment Cooperation (Beijing, China). The mirror with the matrix of hollow ring markers and the beam splitter plate were manufactured by Jiaite Photoelectric Corporation (Shenzhen, China) to match the experimental requirements.
## 3 Results and Discussion
### Optimization of the LHTES Geometries for a Solar Absorption Chiller Application
Therefore, this methodology is ideal for generating a quick and reliable preliminary design before running into detailed CFD simulations and mechanical assessments. Future work could evaluate the operational cost of an LHTES unit together with the energy system that is equipped with the LHTES unit, and analyze the effect of different designs on the overall performance of the downstream equipment and the whole energy system. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **PCM \#1** & **PCM \#2** & **PCM \#3** \\ \hline Fixed variables & & & \\ \hline TES power, \(Q\) [kW] & 1.42 & 1.42 & 1.42 \\ HTT mass flow rate, \(\dot{m}\) [kg\(\cdot\)s\({}^{-1}\)] & 0.139 & 0.139 & 0.139 \\ HTF inlet temperature, \(T_{\mathrm{in}}\) [\({}^{\circ}\)C] & 68.0 & 68.0 & 68.0 \\ Tube outer diameter, \(Dt\) [m] & 0.0172 & 0.0172 & 0.0172 \\ Operation time, \(t\) [h] & 3.7 & 3.7 & 3.7 \\ Shell material & Stainless steel & Stainless steel & Stainless steel \\ Tube material & Stainless steel & Stainless steel & Stainless steel \\ \hline Properties of the material selected & & & \\ \hline PCM melting point, \(T_{\mathrm{mp}}\) [\({}^{\circ}\)C] & 54.0 & 65.0 & 64.0 \\ PCM latent heat, \(dH\) [k\(\cdot\)kg\({}^{-1}\)] & 170 & 120 & 220 \\ \hline Optimized geometric variables & & & \\ \hline Tube length, \(L\) [m] & 6.69 & 5.57 & 5.79 \\ Number of tubes, \(N\) [-] & 26 & 115 & 88 \\ PCM cost, \(C_{\mathrm{PCM}}\) [USD] & 1112 & 1575 & 859 \\ Total purchase cost, \(C_{\mathrm{tot}}\) [USD] & 30856 & 37975 & 35041 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Optimized cases for three PCMs with varying tube length and number of tubes.
## 4 Case Studies  
To verify the capability of the intelligent fault detection networks proposed in this article, two practical case studies were carried out. In case study 1, a comparative experiment of diagnosis performance under diverse working conditions was conducted, and case study 2 compared the diagnosis performance of the proposed method with conventional methods under various label proportions.
# Linear Parameter-Varying Model Predictive Control of AUV for Docking Scenarios
## 3 AUV Control System
### Control System Architecture  
The proposed control system structure is shown in Figure 2. The nonlinear AUV system, including sensors and actuators (blue block) as described in the previous section, is affected by the tidal current (green block) speed \(v_{T}\) and the control system (grey block). The controller is composed of three main algorithms: a predictive control algorithm, an estimator and an allocation algorithm.  
The Model Predictive Control (MPC, yellow block) computes the virtual control signals (forces and moments) \(\tau_{V}\) by solving an optimal control problem given the estimated state vector \(\hat{x}_{AUV}\) and the control reference set-point signal vector \(r_{SP}\). A Kalman Filter (KF, orange block) is used to estimate the AUV system state \(\hat{x}_{AUV}\), by using the measured output signals \(y_{AUV}\) and the virtual control signals \(\tau_{V}\). The Thrust Allocation algorithm (TA, red block) converts the virtual control \(\tau_{V}\), to a set of signals driving the actuators \(u_{A}\) such that these provide a set of forces and moments minimizing the difference with \(\tau_{V}\) given the actuator limits and physical properties.  
Predictive control methods normally involve a MPC algorithm to solve a single optimization problem, which computes the vector of future controls. This solution provides the sequence of control signals driving the actuators. It requires a single MPC design model involving the vehicle and actuator dynamics, and the actuator thruster allocation algorithm. This approach was investigated but an alternative route was taken to obtain a design that was more practical to implement.  
In the following, a different control architecture was used to simplify the optimal problem by introducing two sub-problems, instead of one large optimization problem. This has the advantage that it provides a simpler (reduced number of optimization variables and control action constraints) optimization problem for the MPC. The TA policy also involves a simpler resources allocation problem that is to be solved only for the actual time instant. The controller structure avoids input and output constraints in the predictive controller, so that the MPC for this application is an unconstrained optimization problem that can be solved with a reduced computational effort with respect to other, constrained MPC problem solutions [12].
## 4 Genetic Diagnosis of VCP-MSP  
The diagnosis of VCP-MSP is confirmed by the identification of a pathogenic mutation in _VCP_ using genetic testing. Diagnosis of VCP-MSP should be considered in patients having one or more of the clinical presentations described in Table 1. In the presence of an autosomal dominant family history, the likelihood of diagnosing a genetic disorder is much greater. However, cases without family history may still be caused by _VCP_ mutations due to variations in disease penetrance and expressivity, attribution of alternate diagnoses, or presence of de novo mutations. When interviewing patients for family  
Figure 1: Pathogenic mutations represented on the 3D model of VCP. **(A)** Three-dimensional representation of the VCP hexamer. We have color-coded individual domains from a single VCP monomer for ease of reference in subsequent images: Green for the N-terminal domain, blue for the N-D1 linker, yellow for the D1 domain, purple for the D1-D2 linker, light blue for the D2 domain, yellow for the C-terminal domain, with grey lines representing the other 5 structural oligomers. In red, we have represented the locations of pathogenic variants in VCP, showing the positions in the N-terminal domain (**B**), linker domain (**C**), D1 domain (**D**), and D2 domain (**E**). This figure was generated using open source material available from Swiss model [108] and PyMOL [109] based on the proposed structure of the VCP hexamer [110].  
history, it is important to consider the above-mentioned clinical variability and ask about muscle weakness, bone disease, dementia and ALS, since phenotypes may vary and do not correlate with genotype. As mentioned above, the exception is Charcot-Marie-Tooth disease type 2Y, which appears to be correlated to particular _VCP_ mutations [44; 45; 51]. Parkinson disease and Alzheimer disease have been associated with _VCP_ mutations, although it is important to be aware that these conditions are also common in the aged population. Some specific phenotypes may have higher likelihood for a diagnosis with VCP-MSP, for example, ALS is a relatively common disease compared with the prevalence of VCP-MSP; therefore, the likelihood of identifying a _VCP_ mutation in a sporadic case of ALS is low. Myopathy with onset in adulthood is extensively heterogeneous with a low likelihood of obtaining any genetic diagnosis; therefore, isolated myopathy on its own would not suggest a high likelihood of identifying VCP-MSP. However, myopathy is the most common presentation of VCP-MSP and it is possible that some cases of VCP-MSP are misdiagnosed as sporadic inclusion body myositis based on reactivity to NT5C1A antibodies [118]. Early-onset FTD is very rare and may portend a higher likelihood of identifying a causative gene mutation.
# Smart Poly(acrylic acid)/Poly(acrylamide) Microgels with Interpenetrating Polymer Network Structure
## 3 Results
### Temperature Responsiveness of IPN MGs  
Diffusion-ordered NMR spectroscopy (DOSY) was used to study the temperature-responsiveness of PAA/PAAM IPN MGs. Diffusion NMR spectroscopy based on Pulsed Field Gradient NMR (PFG NMR) is a convenient non-destructive method for the investigation of translational molecular motion at the micrometer scale, allowing for the measurement of the translational diffusion coefficient of particles. DOSY has been recognized as a useful approach for the analysis of complex mixtures. The method exploits the differences in diffusion coefficients and particle sizes to separate the signals from the different components in a mixture. The DOSY spectrum is a two-dimensional map with a horizontal dimension representing the chemical shifts and a vertical dimension representing the diffusion coefficients, usually in a logarithmic format. The determined translational diffusion coefficient could be further used to calculate the size of the particles by applying an appropriate shape model. In this study, we used the Stokes-Einstein equation to calculate the apparent hydrodynamic radius, R\({}_{\text{h}}\), of the MG, assuming spherical-shaped particles (see Section 2). As an example, Figure 6 shows the DOSY spectrum of sample PC66, measured in D\({}_{2}\)O at 311K and pD = 5.27.  
The temperature dependence of R\({}_{\text{h}}\) for PC66, calculated from the translational diffusion coefficients determined by DOSY measurements as a function of temperature at two different pD values, is presented in Figure 7.  
The NMR data indicate that the R\({}_{\text{h}}\) of the PC66 MGs slightly increased linearly with increasing temperature and that the particle size was larger in alkaline media; however, the IPN MGs did not show temperature sensitivity in either acidic or alkaline pH in the studied temperature range (Figure 7). This result, obtained by NMR, was confirmed by  
Figure 5: TEM images of PAA/PAAM IPN MGs with two different compositions: (**A**,**B**) PC75 and (**D**,**E**) PC25, with their respective schematical representations (**C**,**F**) (PAA (black) and PAAM (red)).  
DLS measurements made in distilled water at pH = 7 (Figure 8). This reveals that no real temperature responsiveness was observed for any of the IPN MGs at neutral pH.  
However, at pH-5, both methods, NMR and DLS, registered an upper critical solution temperature (UCST) for the PC66 MGs (Figure 9). The abrupt volume increase in the IPN MGs at the UCST was due to the disruption of the hydrogen bonds between PAA and PAAM. Both methods registered similar values for UCST around 37 \({}^{\circ}\)C, which deems these MGs appropriate for drug delivery.  
Figure 8: Temperature responsiveness of PAA/PAAM IPN MGs with different compositions in distilled water, as revealed by DLS.  
Figure 6: DOSY spectrum of PC66 at 311 K and pD = 5.27.  
Figure 7: Hydrodynamic radius (R\({}_{\rm h}\)) temperature dependence at two pD values as revealed by DOSY for sample PC66.
# Research on Interference Mechanism of 25 Hz Phase Sensitive Track Equipment from Unbalanced Current
## 2 Cause Analysis of Abnormal Red Ribbon
### Generation Mechanism of Unbalanced Traction Current
#### 2.1.1 Impedance Unbalance of Traction Current Circuit  
From the traction current wheel-rail circuit shown in Figure 1, it can be seen that, after the traction current flows through the electric locomotive transformer, it finally flows into the track through the contact between the wheel and rail. The unbalance phenomenon caused by unequal impedance in the current loop is the essence of unbalanced traction current.  
The differences in site environment and track conditions will cause inconsistent rail contact impedance. At the same time, the contact area and pressure between wheel-rail and rail are constantly changing during vehicle driving, which affects the contact impedance between wheel-rail and rail. Therefore, the unbalanced wheel-rail contact impedance and rail impedance in the current loop are the main causes of the unbalanced traction current.