esa-sceva/satcom-chunk-collection huggingface dataset:
# Unbiased Isotonic Regression Tree for Discovering Hidden Heterogeneity in Monotonicity Constraints
###### Abstract
Patients with more severe conditions might require higher doses to show the same recovery improvement as patients with less severe conditions. In this case, IRT can detect such heterogeneity in medication effectiveness by categorizing patients into two subgroups based on the patient's condition. From two isotonic regressions that are fitted for each subgroup, heterogeneous recovery patterns in response to medication are observed. The example demonstrates the significance of partitioning data into subgroups to identify different degrees of monotonically increasing patterns. Such partitioning not only enhances the model's fit but also determines covariates that contribute to the heterogeneity in increasing patterns. Inspired by this example, this study has two major contributions as follows:  
* This study investigates the possibility of the selection bias problem for a split in IRT. For the split variable selection, IRT determines the split variable and its cutpoint following the same approach used in the Classification and Regression Tree (CART). CART selects the split variable and its cutpoint simultaneously, but the simultaneous process introduces selection bias through the split (i.e., variables with more conceivable cutpoints have a higher chance of being selected) [24; 25]. Given that IRT is inherited from CART for selecting split variables, IRT might be vulnerable to selection bias for a split. Such bias would lead to misleading subgrouping due to splitting with inappropriate covariates, ultimately impacting subsequent predictions or decisions derived from the model. * This study proposes the isotonic regression tree with unbiased split variable selection. To remove selection bias in IRT, this study proposes a statistical hypothesis test for selecting split variables. A simulation study and real data analysis were carried out to validate the unbiasedness of the proposed split variable selection method. The case study validates the fact that the proposed unbiased isotonic regression tree produces meaningful subgroups with heterogeneous monotonically increasing patterns. Compared with its competitors, the proposed tree additionally excels in model performance. Hereafter, this study calls the proposed tree an unbiased isotonic regression tree (UIRT). The remainder of this paper is organized as follows. Section 2 reviews the literature on regression trees and how constraints are accommodated in trees. Section 3 describes the proposed unbiased isotonic regression tree. A simulation study and empirical data analysis are presented in Section 4 to investigate the selection bias in the conventional IRT and validate the unbiased split variable selection of the proposed method. Section 5 applies the proposed model to the wind turbine dataset. Section 6 concludes the paper and discusses future research directions.
## 4 Discussion
### Design Challenges and Trade-Offs
#### 4.1.1 Balancing Decentralization with Usability  
In decentralized platforms, the user experience can often be complex due to the need for users to manage their own private keys, interact with blockchain networks, and handle decentralized storage systems. Balancing the inherent complexity of decentralized technologies with the need for a seamless, intuitive user experience is a significant challenge.  
* _Security vs. usability_: To achieve true decentralization, users need to control their private keys, which can be difficult for non-technical users. Managing keys and cryptographic signatures can be cumbersome but is essential for maintaining security. Offering simplified solutions, such as dedicated wallets or social recovery systems, can improve usability but may introduce centralization risks. In SPARK-IT, we opted for a decentralized blockchain-based solution, where the centralized components assist in interaction flows. The essential data are stored encrypted in IPFS, and proof-of-data is anchored in blockchain. Moreover, the user can choose any digital wallet solution as long as it is compatible with an Ethereum blockchain.
* _Speed vs. decentralization:_ Decentralized systems can introduce latency, particularly when dealing with blockchain-based interactions or IPFS file retrieval. Optimizing for speed (e.g., using centralized servers or content delivery networks) might decrease decentralization, as centralized components may become single points of failure. In SPARK-IT, we use dedicated in-memory caches to make the overall system as responsive as possible. However, if these fail, the front-end client applications, for both innovator and experts, have a fallback alternative that goes directly to the decentralized components (blockchain and IPFS). Moreover, we opted for a POS (proof-of-stake) permissioned blockchain that can process a high number of transactions per second.
* _Complexity of interactions_: Decentralized platforms often require users to engage with more steps, such as verifying transactions on-chain, interacting with smart contracts, or managing encrypted data. While a decentralized system gives more control to the user, simplifying these processes without losing the core decentralized nature is not an easy task. Designing intuitive front-end systems that abstract away the complexities of blockchain and IPFS interactions while still ensuring underlying security and decentralization is crucial. In SPARK-IT, we streamline the workflows for the users so that the interactions with the employed decentralized technologies, blockchain and IPFS, as well as the entire process of encrypting/decrypting data, are seamless. Our system provides a straightforward wallet integration and guided workflows for on-chain actions. The front-end applications contain JavaScript libraries that perform the heavy-lifting tasks of connecting and interacting with the blockchain and IPFS.
# Imaging Characteristics of Disturbance Flow Field Surrounding a Hypersonic Target
## 1 Introduction
Subsequently, the correlation between imaging blurring, imaging deviation, and the orbit height, pixel size, and focal length of the space-based imaging detection system was established. The results demonstrate that the presence of perturbed flow fields leads to a varying degrees of visually perceptible blurring effects and indiscernible deviation effects in the background image under different flight conditions. The profiles of the disturbance field were successfully extracted from the deviated image, demonstrating the feasibility of detecting hypersonic targets through the disturbance flow field. This approach holds promise as an alternative scheme in situations where infrared and radar detection methods are not available. The remainder of this paper is organized as follows. In Section 2, the research method of imaging characteristics of the disturbance flow field surrounding a hypersonic target based on Fourier Optics and Background-Oriented Schlieren was analyzed. In Section 3, the results of the imaging blurring and imaging deviation caused by the disturbance flow field were demonstrated, and the influence mechanism of the relevant parameters was analyzed. In Section 4, the conclusions drawn from the study were presented.
# Nonlocal and Size-Dependent Dielectric Function for Plasmonic Nanoparticles
###### Abstract  
We develop a theoretical approach to investigate the impact that nonlocal and finite-size effects have on the dielectric response of plasmonic nanostructures. Through simulations, comprehensive comparisons of the electron energy loss spectroscopy (EELS) and the optical performance are discussed for a gold spherical dimer system in terms of different dielectric models. Our study offers a paradigm of high efficiency compatible dielectric theoretical framework for accounting the metallic nanoparticles behavior combining local, nonlocal and size-dependent effects in broader energy and size ranges. The results of accurate analysis and simulation for these effects unveil the weight and the evolution of both surface and bulk plasmons vibrational mechanisms, which are important for further understanding the electrodynamics properties of structures at the nanoscale. Particularly, our method can be extended to other plasmonic nanostructures where quantum-size or strongly interacting effects are likely to play an important role.  
Keywords:EELS; plasmons vibrational modes; nanoparticles; nonlocal and size-dependent dielectric +
Footnote †: journal: Applied Physics Letters B
# Optical Frequency Comb Expansion Using Mutually Injection-Locked Gain-Switched Lasers
## 3 Results and Discussion
### Comb Line Characterization
#### 3.2.2 Phase Correlation  
Finally, the phase correlation between the MIL-GS OFC lines is assessed by characterizing the resultant RF beat tone of selected pairs of comb lines. Two consecutive 3.125 GHz FSR comb lines are filtered and heterodyned on a 50 GHz photodetector to generate an RF beat tone as shown in Figure 8a. The phase correlation between the two lines cancels the optical phase noise, thus resulting in a generation of narrow beat tone with a 3 dB line width of 33 Hz (ESA setting: VBW = 30 Hz; RBW = 30 Hz). A beat tone with a line width of the order of tens of Hz reflects the phase property of RF source used for the OFC generation, thus proves a high degree of phase correlation between the comb lines. Subsequently, the measurement is repeated for pairs of comb lines separated by multiples of FSR (up to 40 GHz due to the limited bandwidth of the ESA). Consistently, a beat line width of 33 Hz is measured, as shown in Figure 8b for MIL-GS OFC with FSR of the 3.125 GHz and 6.25 GHz. The results prove a high degree of phase correlation is maintained even between tones that originated from two different GS lasers (OFC 1 and 2).  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & \multicolumn{2}{c}{**Phase Noise**} & \multicolumn{2}{c}{**RIN**} \\ \cline{2-4}  & **6.25 GHz** & **3.125 GHz** & **6.25 GHz** & **3.125 GHz** \\ \hline Master laser & \(\sim\)30 kHz & \(\sim\)30 kHz & \(\sim\)\(-\)157.2 dB/Hz & \(\sim\)\(-\)157.2 dB/Hz \\ Comb line (middle) & \(\sim\)40 kHz & \(\sim\)42 kHz & \(\sim\)\(-\)152.1 dB/Hz & \(\sim\)\(-\)152.8 dB/Hz \\ Comb line (right) & \(\sim\)47 kHz & \(\sim\)49 kHz & \(\sim\)\(-\)152.7 dB/Hz & \(\sim\)\(-\)152.5 dB/Hz \\ Comb line (left) & \(\sim\)45 kHz & \(\sim\)47 kHz & \(\sim\)\(-\)152.6 dB/Hz & \(\sim\)\(-\)152.5 dB/Hz \\ \hline \hline \end{tabular}
\end{table}
Table 4: Summary of the MIL-GSL OFC phase noise and RIN characterization.  
Figure 6: FM noise spectrum for MIL-GS OFC lines at FSR of (**a**) 6.25 GHz; (**b**) 3.125 GHz; (**c**) plot of measured optical linewidths of different comb tone (FSR = 6.25 GHz).  
Figure 7: Relative intensity noise measurements for MIL-GS OFC of FSR (**a**) 6.25 GHz; (**b**) 3.125 GHz.
## 1 Introduction
[9] showed that trunk control in the weeks after stroke is a key predictor of long-term functional results. Early trunk control improvement improves functional recovery, suggesting that trunk-specific exercises in the early phases of rehabilitation may affect long-term autonomy. Robust evidence indicates that trunk control and core stability exercise enhance sitting and standing balance, mobility, trunk control, and neuromuscular integration [23,24], hence positively impacting daily activities [25, 26, 27]. The use of technology represents a great opportunity for rehabilitation. Robotic devices represent a wide range of tools, capable of performing gesture-specific, repetitive, and high-intensity activities: they can be used considering patients' residual abilities and can provide different feedback (e.g., visual, auditory, haptic) on performance in real time. Robotic rehabilitation represents an innovative tool and is being used in various populations [28; 29; 30]. Recently, the only article that investigated the effect of robotic trunk rehabilitation in chronic stroke patients was that of [PERSON] et al. [31]. The authors emphasized the impact of a robotic rehabilitation program on trunk balance and stability, particularly on dynamic balance and proprioceptive activities, resulting in improved trunk control and reduced compensatory methods. After a cerebrovascular incident, trunk control rehabilitation is crucial, greatly impacting autonomy and quality of life, but it requires a comprehensive approach that combines traditional rehabilitation methods with cutting-edge technology and other advanced systems. Given the literature and little scientific evidence on robotic trunk rehabilitation for patients with sABI, this study aims to examine the effects of technological rehabilitation via the humova(r) robotic platform on sitting balance, trunk control, fatigue and quality of life.
## 4 Conclusions  
In an underwater environment with nonlinear and unpredictable characteristics, establishing an accurate mathematical model using conventional control theory is difficult. Therefore, this study used the FLC method with its high adaptability and tolerance of partial uncertainty to control a UUV's motion.  
According to the experimental results, the ROV with the FLC and sonar sensor exhibited the following performances for heading control and obstacle avoidance:  
* For heading control in the experiment, the FLC system directly commanded the ROV's motion according to the data sensed in the environment. It reduced dependence by using the vehicle's motion and environment models.
* Implementation of the heading control was more difficult because of the evident hydrodynamic force generated by the ROV's motors, which caused a yaw phenomenon. The FLC required time to stabilize the ROV.
* In the obstacle avoidance experiment, the sonar sensor with optimum value computing combined with fuzzy logic control allowed for efficient avoidance of the obstacles and movement to the target destination. This would be helpful for the navigation control of UUVs.  
In this study, the performance of the external sensor on the ROV was evaluated using an experiment that provided a basis for further development of AUV design.  
**Author Contributions:** [PERSON] conceived the experiments and drafted the manuscript; [PERSON] reviewed and revised the manuscript; [PERSON] and [PERSON] provided experimental data. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by Ministry of Education Taiwan under grant numbered 1090023205C.  
**Acknowledgments:** The authors would like to acknowledge the CAD/CAM team's members in NDU who contributed and helped in the experiment.  
**Conflicts of Interest:** The authors declare no conflict of interest.  
Figure 15: Side view images of the experiment.
## 4 Results
### Study 1
#### 4.1.1 Participants  
A total of 80 out of 161 participants (31 female, 48 male, and 1 divers) completed the online survey and were included in the data analysis. Participants' ages ranged from 19 to 77 years (\(M\) = 30.62, \(SD\) = 13.69). The participants had diverse educational backgrounds and came from seven different nationalities. Occupations of participants included (N = 1) each in natural sciences, healthcare, and crafts; (N = 2) each in law and administration; (N = 3) each in management and social work; (N = 5) in services; (N = 20) in other professions; and (N = 42) in engineering. Twenty-five participants reported having foot conditions, with sixteen of these in the past and nine currently. In total, 14 had chronic issues and eleven had acute conditions. Overall, 21 participants reported wearing orthopedic aids, including insoles (N = 11), bandages (N = 5), high-leg orthoses (N = 4), and short-leg orthoses (N = 1). In response to the question of whether the participants had previously heard of the term \"smart orthoses\", 51 responded \"no\", and 29 responded \"yes\". Twenty-nine participants were aware of generative AI image generation, twenty-eight had actively used it, and twenty-three had no prior knowledge of the technology.  
To investigate whether participant demographics influenced the results, we conducted an ART ANOVA, which showed no statistically significant main or interaction effects of gender, prior AI knowledge, or past orthopedic conditions on SCM, WEAR, and Likert scores (all \(p>0.05\)). These results show that demographic factors did not systematically influence the ratings of the participants.
# Quantum Perspective on Digital Money: Towards a Quantum-Powered Financial System
## 6 Impact of Quantum Money on the Banking System
### Quantum Money as a Constraint on Money Creation  
Quantum money introduces a paradigm shift by ensuring that every unit of currency is represented by a specific quantum state. Due to the no-cloning theorem [7], quantum money cannot be duplicated, preventing the arbitrary expansion of the money supply. If banks were required to hold actual quantum money before issuing loans, they would no longer be able to create deposits purely through accounting. This would enforce a fundamental constraint:  
\[M_{new}\leq M_{quantum}, \tag{15}\]  
where \(M_{quantum}\) represents the total supply of quantum money, directly controlled by the central bank.  
This shift would restore full monetary control to the central bank, ensuring that money issuance is explicitly tied to tangible, non-replicable quantum assets. With this approach, only the central bank or other authorized and properly equipped institutions would be able to generate certified quantum states representing legitimate money. These quantum states, recognized as a legal means of payment, could then be transferred to recipients via quantum teleportation.
## 4 Numerical Results
### Application for Real-World Engineering Problems
#### 4.2.1 Problem 1: Sonic Boom Uncertainty Quantification  
In this application, sonic boom uncertainty quantification with four uncertain variables is performed to show the success of the methods on low-dimensional engineering problems. The effect of angle of attack, Mach number, reflection factor and ground elevation uncertainties on the ground noise level have been examined, and the statistics of the uncertain variables are shared in Table 4.  
The accuracy metrics of the surrogate models are demonstrated in Figure 13. As can be observed in Figure 13, an accurate surrogate model was not obtained by PCE and MF-PCE methods using few high-fidelity analyses. With a small number of high-fidelity analyses, an accurate surrogate model is constructed with the LRA and MF-LRA method, and for the low-dimensional problem, there is no great difference between the LRA and MF-LRA surrogate model accuracy metrics. In general, the accuracy value obtained by using 40 high-fidelity simulations with the PCE and MF-PCE methods could be obtained by using only 10 high-fidelity simulations with the LRA and MF-LRA methods.  
Using the considered surrogate models, the probability density functions (PDF) are calculated and the results are visualised in Figure 14. In addition, the PDF value calculated by using 100 high-fidelity analysis results is also demonstrated in Figure 14 as the reference solution. As observed in the figure, the MF-LRA method gives very close results to the reference result with a small number of high-fidelity analyses. Although the success of the LRA and MF-LRA methods are similar in surrogate model accuracy metrics, it is observed that the PDF obtained by the LRA method is somewhat different from the reference result.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Variable** & **Statistics** \\ \hline Angle of attack, (\({}^{\circ}\)) & \(\mathcal{N}(3.07,0.1)\) \\ Mach & \(\mathcal{N}(1.6,0.0016)\) \\ Reflection factor & \(\mathcal{U}(1.8,2)\) \\ Ground elevation, (ft) & \(\mathcal{U}(0,5000)\) \\ \hline \hline \end{tabular}
\end{table}
Table 4: Statistics of random variables.  
Figure 13: Surrogate model error metrics for sonic boom problem 1 (\(N_{lf}=70\)).  
PCE and MF-PCE methods, on the other hand, have low success rates when few HF simulation results are used.  
In order to make numerical comparisons, the results of the uncertainty quantification are shared in Table 5. If the results obtained from different methods are generally compared with the reference result, the mean, standard deviation, skewness, and kurtosis values estimated from the single- and multi-fidelity LRA methods are close to the reference results. However, if the results obtained with the single- and multi-fidelity PCE method are examined, the mean and standard deviation values are in good agreement with the reference result, while the skewness and kurtosis values have a higher error rate compared to the results obtained by the reference result.
###### Abstract  
This work describes the advances on a micro-newton torsional thrust balance for ionic liquid electrospray thruster (ILET) being developed in the National University of Defense Technology. The torsional thrust balance adopts an asymmetric pendulum arm about a flexural pivot, and an electrostatic comb device is used for calibration, which makes the balance compact and allows the measurement of the micro-newton level thrust with high accuracy. To minimize the influence of gravity on the measurement results, a two-dimensional adjustable counterweight mechanism is adapted to balance the entire arm and make its mass center close to the pivot axis. Mechanical oscillations are passively damped with an eddy current damper. A series of experimental studies are carried out in a vacuum chamber; the results provide validation that the balance has good linearity in the range of 2-30 uN, with the resolution better than 0.21 uN and the settling time to a step force is less than 7 s, which can meet the thrust measurement requirements of the ILET operating in the mode of alternating work voltage polarity. In addition, we find that the electrostatic force generated by the power supply wire has a non-negligible influence on thrust measurement results, which needs to be considered in the actual thrust measurement.  
electrospray thruster; micro thrust measure; torsional thrust balance +
Footnote †: journal: Aerospace  
FootnoteThere are many thrust stands that have been proposed and developed for steady state micro thrust measurement. According to their structural topology, they can be divided into pendulum, inverted pendulum type, and torsion pendulum three major types. All these topologies are variations of the spring-mass-damper system, and the primary difference is the influence of the gravity on the dynamic response characteristics of the system [4]. The thrust generated by a single ILET is in the range of several \(\upmu\)N to 10 s \(\upmu\)N, which is small compared with the mass of the thruster and pendulum arm. Gravity acts as a restoring force in the hanging pendulum and applied force in the inverted pendulum, respectively, which will significantly influence the thrust measurement results. However, in the ideal torsional pendulum, gravity has no effect on thrust measurement due to the motion plane of the arm being always perpendicular to the gravity vector. Therefore, a torsional thrust balance with a thrust measurement range of 2-30 \(\upmu\)N is developed for directly measuring ILET thrust. The detailed design and performance of the thrust balance are presented in this paper.