Shape optimization of superconducting transmon qubit for low surface dielectric loss

Surface dielectric loss of superconducting transmon qubit is believed as one of the dominant sources of decoherence. Reducing surface dielectric loss of superconducting qubit is known to be a great challenge for achieving high quality factor and a long relaxation time ($T_{1}$). Changing the geometry of capacitor pads and junction wire of transmon qubit makes it possible to engineer the surface dielectric loss. In this paper, we present the shape optimization approach for reducing Surface dielectric loss in transmon qubit. The capacitor pad and junction wire of the transmon qubit are shaped as spline curves and optimized through the combination of the finite-element method and global optimization algorithm. Then, we compared the surface participation ratio, which represents the portion of electric energy stored in each dielectric layer and proportional to two-level system (TLS) loss, of optimized structure and existing geometries to show the effectiveness of our approach. The result suggests that the participation ratio of capacitor pad, and junction wire can be reduced by 16% and 26% compared to previous designs through shape optimization, while overall footprint and anharmonicity maintain acceptable value. As a result, the TLS-limited quality factor and corresponding $T_{1}$ were increased by approximately 21.6%

Curve Your Attention: Mixed-Curvature Transformers for Graph Representation Learning

Real-world graphs naturally exhibit hierarchical or cyclical structures that are unfit for the typical Euclidean space. While there exist graph neural networks that leverage hyperbolic or spherical spaces to learn representations that embed such structures more accurately, these methods are confined under the message-passing paradigm, making the models vulnerable against side-effects such as oversmoothing and oversquashing. More recent work have proposed global attention-based graph Transformers that can easily model long-range interactions, but their extensions towards non-Euclidean geometry are yet unexplored. To bridge this gap, we propose Fully Product-Stereographic Transformer, a generalization of Transformers towards operating entirely on the product of constant curvature spaces. When combined with tokenized graph Transformers, our model can learn the curvature appropriate for the input graph in an end-to-end fashion, without the need of additional tuning on different curvature initializations. We also provide a kernelized approach to non-Euclidean attention, which enables our model to run in time and memory cost linear to the number of nodes and edges while respecting the underlying geometry. Experiments on graph reconstruction and node classification demonstrate the benefits of generalizing Transformers to the non-Euclidean domain.Comment: 19 pages, 7 figure

Quantitative Sasang Constitution Diagnosis Method for Distinguishing between Tae-eumin and Soeumin Types Based on Elasticity Measurements of the Skin of the Human Hand

The usefulness of constitutional diagnoses based on skin measurements has been established in oriental medicine. However, it is very difficult to standardize traditional diagnosis methods. According to Sasang constitutional medicine, humans can be distinguished based on properties of the skin, including its texture, roughness, hardness and elasticity. The elasticity of the skin was previously used to distinguish between people with Tae-eumin (TE) and Soeumin (SE) constitutions. The present study designed a system that uses a compression method to measure the elasticity of hand skin and evaluated its measurement repeatability. The proposed system was used to compare the skin elasticity between SE and TE subjects, which produced a measurement repeatability error of <3%. The proposed system is suitable for use as a quantitative constitution diagnosis method for distinguishing between TE and SE subjects with an acceptable level of uncertainty

CardioGuard: A Brassiere-based Reliable ECG Monitoring Sensor System for Supporting Daily Smartphone Healthcare Applications

We propose CardioGuard, a brassiere-based reliable electrocardiogram (ECG) monitoring sensor system, for supporting daily smartphone healthcare applications. It is designed to satisfy two key requirements for user-unobtrusive daily ECG monitoring: reliability of ECG sensing and usability of the sensor. The system is validated through extensive evaluations. The evaluation results showed that the CardioGuard sensor reliably measure the ECG during 12 representative daily activities including diverse movement levels; 89.53% of QRS peaks were detected on average. The questionnaire-based user study with 15 participants showed that the CardioGuard sensor was comfortable and unobtrusive. Additionally, the signal-to-noise ratio test and the washing durability test were conducted to show the high-quality sensing of the proposed sensor and its physical durability in practical use, respectively

Replenishment of microRNA-188-5p restores the synaptic and cognitive deficits in 5XFAD Mouse Model of Alzheimer’s Disease

MicroRNAs have emerged as key factors in development, neurogenesis and synaptic functions in the central nervous system. In the present study, we investigated a pathophysiological significance of microRNA-188-5p (miR-188-5p) in Alzheimer’s disease (AD). We found that oligomeric Aβ(1-42) treatment diminished miR-188-5p expression in primary hippocampal neuron cultures and that miR-188-5p rescued the Aβ(1-42)-mediated synapse elimination and synaptic dysfunctions. Moreover, the impairments in cognitive function and synaptic transmission observed in 7-month-old five familial AD (5XFAD) transgenic mice, were ameliorated via viral-mediated expression of miR-188-5p. miR-188-5p expression was down-regulated in the brain tissues from AD patients and 5XFAD mice. The addition of miR-188-5p rescued the reduction in dendritic spine density in the primary hippocampal neurons treated with oligomeric Aβ(1-42) and cultured from 5XFAD mice. The reduction in the frequency of mEPSCs was also restored by addition of miR-188-5p. The impairments in basal fEPSPs and cognition observed in 7-month-old 5XFAD mice were ameliorated via the viral-mediated expression of miR-188-5p in the hippocampus. Furthermore, we found that miR-188 expression is CREB-dependent. Taken together, our results suggest that dysregulation of miR-188-5p expression contributes to the pathogenesis of AD by inducing synaptic dysfunction and cognitive deficits associated with Aβ-mediated pathophysiology in the disease

Sinabro: A Smartphone-Integrated Opportunistic Electrocardiogram Monitoring System

In our preliminary study, we proposed a smartphone-integrated, unobtrusive electrocardiogram (ECG) monitoring system, Sinabro, which monitors a user’s ECG opportunistically during daily smartphone use without explicit user intervention. The proposed system also monitors ECG-derived features, such as heart rate (HR) and heart rate variability (HRV), to support the pervasive healthcare apps for smartphones based on the user’s high-level contexts, such as stress and affective state levels. In this study, we have extended the Sinabro system by: (1) upgrading the sensor device; (2) improving the feature extraction process; and (3) evaluating extensions of the system. We evaluated these extensions with a good set of algorithm parameters that were suggested based on empirical analyses. The results showed that the system could capture ECG reliably and extract highly accurate ECG-derived features with a reasonable rate of data drop during the user’s daily smartphone use

Local electronic density of states of a semiconducting carbon nanotube interface

The local electronic structure of semiconducting single-wall carbon nanotubes was studied with scanning tunneling microscopy. We performed scanning tunneling spectroscopy measurement at selected locations on the center axis of carbon nanotubes, acquiring a map of the electronic density of states. Spatial oscillation was observed in the electronic density of states with the period of atomic lattice. Defect induced interface states were found at the junctions of the two semiconducting nanotubes, which are well-understood in analogy with the interface states of bulk semiconductor heterostructures. The electronic leak of the van Hove singularity peaks was observed across the junction, due to inefficient charge screening in a one-dimensional structure.open111

Hypovigilance Detection for UCAV Operators Based on a Hidden Markov Model

With the advance of military technology, the number of unmanned combat aerial vehicles (UCAVs) has rapidly increased. However, it has been reported that the accident rate of UCAVs is much higher than that of manned combat aerial vehicles. One of the main reasons for the high accident rate of UCAVs is the hypovigilance problem which refers to the decrease in vigilance levels of UCAV operators while maneuvering. In this paper, we propose hypovigilance detection models for UCAV operators based on EEG signal to minimize the number of occurrences of hypovigilance. To enable detection, we have applied hidden Markov models (HMMs), two of which are used to indicate the operators&apos; dual states, normal vigilance and hypovigilance, and, for each operator, the HMMs are trained as a detection model. To evaluate the efficacy and effectiveness of the proposed models, we conducted two experiments on the real-world data obtained by using EEG-signal acquisition devices, and they yielded satisfactory results. By utilizing the proposed detection models, the problem of hypovigilance of UCAV operators and the problem of high accident rate of UCAVs can be addressed