Structure and realization of pole-shared switched-current complex wavelet filter

A pole-shared switched-current complex wavelet filter structure with follow-the-leader feedback configuration is proposed for synthesizing the real and imaginary approximation functions with the same poles. The double-sampling fully-balanced SI bilinear integrator and current mirror are employed as the building cells. By sharing the implementation circuit for approximation poles of the real and the imaginary part, the proposed structure only has the same circuit complexity as that of real-valued wavelet filter, which is very suitable for small-size and low-power application. The complex Morlet wavelet is selected as an example to elaborate the design procedure. Simulation results confirm that the presented complex wavelet filter structure can generate the real and imaginary coefficients of complex wavelet transform accurately with simple synthesis method and explicit design formulas.Peer reviewedFinal Accepted Versio

Design of Gm-C wavelet filter for on-line epileptic EEG detection

Copyright © 2019 The Institute of Electronics, Information and Communication EngineersAnalog filter implementation of continuous wavelet transform is considered as a promising technique for on-line spike detection applied in wearable electroencephalogram system. This Letter proposes a novel method to construct analog wavelet base for analog wavelet filter design, in which the mathematical approximation model in frequency domain is built as an optimization problem and the genetic algorithm is used to find the global optimum resolution. Also, the Gm-C filter structure based on LC ladder simulation is employed to synthesize the obtained analog wavelet base. The Marr wavelet filter is designed as an example using SMIC 1V 0.35μm CMOS technology. Simulation results show that the proposed method can give a stable analog wavelet filter with higher approximation accuracy and excellent circuit performance, which is well suited for the design of low-frequency low-power spike detector.Peer reviewe

Realization of Analog Wavelet Filter using Hybrid Genetic Algorithm for On-line Epileptic Event Detection

© 2020 The Author(s). This open access work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/.As the evolution of traditional electroencephalogram (EEG) monitoring unit for epilepsy diagnosis, wearable ambulatory EEG (WAEEG) system transmits EEG data wirelessly, and can be made miniaturized, discrete and social acceptable. To prolong the battery lifetime, analog wavelet filter is used for epileptic event detection in WAEEG system to achieve on-line data reduction. For mapping continuous wavelet transform to analog filter implementation with low-power consumption and high approximation accuracy, this paper proposes a novel approximation method to construct the wavelet base in analog domain, in which the approximation process in frequency domain is considered as an optimization problem by building a mathematical model with only one term in the numerator. The hybrid genetic algorithm consisting of genetic algorithm and quasi-Newton method is employed to find the globally optimum solution, taking required stability into account. Experiment results show that the proposed method can give a stable analog wavelet base with simple structure and higher approximation accuracy compared with existing method, leading to a better spike detection accuracy. The fourth-order Marr wavelet filter is designed as an example using Gm-C filter structure based on LC ladder simulation, whose power consumption is only 33.4 pW at 2.1Hz. Simulation results show that the design method can be used to facilitate low power and small volume implementation of on-line epileptic event detector.Peer reviewe

Effects of HBsAg carriers on pregnancy complications in pregnant women: a retrospective cohort study

ObjectiveHepatitis B virus (HBV) infection is a major health threat worldwide, especially in developing countries. We aimed to investigate the impact of hepatitis B carrier on pregnancy complications in pregnant women, in China.MethodsThis retrospective cohort study was conducted by using data from the EHR system of Longhua District People’s Hospital in Shenzhen, China, from January 2018 to June 2022. Binary logistic regression was used to evaluate the relationship between HBsAg carrier status and pregnancy complications and pregnancy outcomes.ResultsThe study included 2095 HBsAg carriers (exposed group) and 23,019 normal pregnant women (unexposed group). Pregnant women in the exposed group were older than the pregnant women in the unexposed group (29 (27,32) vs. 29 (26,32), p < 0.001). In addition, the incidence of some adverse pregnancy complications in the exposure group was lower than that in the unexposed group, including hypothyroidism of pregnancy (adjusted odds ratio [aOR], 0.779; 95% confidence interval [CI], 0.617–0.984; p = 0.036), hyperthyroidism of pregnancy (aOR, 0.388; 95% CI, 0.159–0.984; p = 0.038), pregnancy induced hypertension (aOR, 0.699; 95% CI, 0.551–0.887; p = 0.003), antepartum hemorrhage (aOR, 0.294; 95% CI, 0.093–0.929; p = 0.037). However, compared with the unexposed group, the exposed group had a higher risk of lower birth weight (aOR, 1.12; 95% CI, 1.02–1.23; p = 0.018) and intrahepatic cholestasis of pregnancy (aOR, 2.888, 95% CI, 2.207–3.780; p < 0.001).ConclusionThe prevalence rate of HBsAg carriers in pregnant women in Longhua District of Shenzhen was 8.34%. Compared with normal pregnant women, HBsAg carriers have a higher risk of ICP, a lower risk of gestational hypothyroidism and PIH, and a lower birth weight of their infants

Assessing the causal relationship between genetically determined inflammatory biomarkers and low back pain risk: a bidirectional two-sample Mendelian randomization study

BackgroundObservational studies have suggested an association between inflammatory markers and low back pain (LBP), but the causal relationship between these factors remains uncertain.MethodsWe conducted a bidirectional two-sample Mendelian randomization analysis (MR) study to investigate whether there is a causal relationship between inflammatory markers and low back pain. We obtained genetic data for CRP, along with its upstream inflammatory markers IL-6, IL-8, and IL-10, as well as low back pain from publicly available genome-wide association studies (GWAS). We applied several MR methods, including inverse variance weighting, weighted median, MR-Egger, Wald Ratio, and MR-PRESSO, to test for causal relationships. Sensitivity analyses were also conducted to assess the robustness of the results.ResultsOur analyses utilizing the Inverse Variance Weighted (IVW) method, the MR-Egger method, and the weighted median method indicated that IL-6 may be associated with an increased risk of LBP (Effect Size: -0.009, 95% Confidence Interval: -0.013–0.006, p = 9.16e-08); however, in the reverse direction, there was no significant causal effect of LBP on inflammatory markers.ConclusionOur study used a Mendelian randomization approach and found that elevated IL-6 levels may reduce the risk of LBP

Switched-current filter structure for synthesizing arbitrary characteristics based on follow-the-leader feedback configuration

This document is the Accepted Manuscript version of the following article: Wenshan Zhao, Yigang He, and Yichuang Sun, ‘Switched-current filter structure for synthesizing arbitrary characteristics based on follow-the-leader feedback configuration’, Analog Integrated Circuits and Signal Processing, (2015), Vol. 82 (2): 479-486. The version of record is available online at doi: 10.1007/s10470-014-0477-8 © Springer Science+Business Media New York 2015Peer reviewedFinal Accepted Versio

PyPose: A Library for Robot Learning with Physics-based Optimization

Deep learning has had remarkable success in robotic perception, but its data-centric nature suffers when it comes to generalizing to ever-changing environments. By contrast, physics-based optimization generalizes better, but it does not perform as well in complicated tasks due to the lack of high-level semantic information and the reliance on manual parametric tuning. To take advantage of these two complementary worlds, we present PyPose: a robotics-oriented, PyTorch-based library that combines deep perceptual models with physics-based optimization techniques. Our design goal for PyPose is to make it user-friendly, efficient, and interpretable with a tidy and well-organized architecture. Using an imperative style interface, it can be easily integrated into real-world robotic applications. Besides, it supports parallel computing of any order gradients of Lie groups and Lie algebras and $2^{\text{nd}}$-order optimizers, such as trust region methods. Experiments show that PyPose achieves 3-20$\times$ speedup in computation compared to state-of-the-art libraries. To boost future research, we provide concrete examples across several fields of robotics, including SLAM, inertial navigation, planning, and control

Predictors of failure of early neurological improvement in early time window following endovascular thrombectomy: a multi-center study

Background and objectiveEndovascular thrombectomy (EVT) has become the gold standard in the treatment of acute stroke patients. However, not all patients respond well to this treatment despite successful attempts. In this study, we aimed to identify variables associated with the failure of improvements following EVT.MethodsWe retrospectively analyzed prospectively collected data of 292 ischemic stroke patients with large vessel occlusion who underwent EVT at three academic stroke centers in China from January 2019 to February 2022. All patients were above 18 years old and had symptoms onset ≤6 h. A decrease of more than 4 points on the National Institute of Health Stroke Scale (NIHSS) after 24 h compared with admission or an NIHSS of 0 or 1 after 24 h was defined as early neurological improvement (ENI), whereas a lack of such improvement in the NIHSS was defined as a failure of early neurological improvement (FENI). A favorable outcome was defined as a modified Rankin scale (mRS) score of 0–2 after 90 days.ResultsA total of 183 patients were included in the final analyses, 126 of whom had FENI, while 57 had ENI. Favorable outcomes occurred in 80.7% of patients in the ENI group, in contrast to only 22.2% in the FENI group (p < 0.001). Mortality was 7.0% in the ENI group in comparison to 42.1% in the FENI group (p < 0.001). The multiple logistic regression model showed that diabetes mellitus [OR (95% CI), 2.985 (1.070–8.324), p = 0.037], pre-stroke mRS [OR (95% CI), 6.221 (1.421–27.248), p = 0.015], last known well to puncture time [OR (95% CI), 1.010 (1.003–1.016), p = 0.002], modified thrombolysis in cerebral infarction = 3 [OR (95% CI), 0.291 (0.122–0.692), p = 0.005], and number of mechanical thrombectomy passes [OR (95% CI), 1.582 (1.087–2.302), p = 0.017] were the predictors of FENI.ConclusionDiabetes mellitus history, pre-stroke mRS, longer last known well-to-puncture time, lack of modified thrombolysis in cerebral infarction = 3, and the number of mechanical thrombectomy passes are the predictors of FENI. Future large-scale studies are required to validate these findings

Simulation Study on Natural Ventilation Performance in a Low-Carbon Large-Space Public Building in Hot-Summer and Cold-Winter Region of China

Recently, climate governance has entered a new phase of accelerating decarbonization. In order to achieve low-carbon buildings, natural ventilation has been widely used as it requires no fan power. However, there are great challenges for achieving effective natural ventilation in large-space public buildings especially in areas characterized by hot-summer and cold-winter climatic regions, due to empirically unsuitable ambient temperatures and theoretically complex joint effect of wind pressure and thermal buoyancy. Therefore, this numerical study was conducted on the performance of a natural ventilation strategy in a large-space public building in a hot-summer and cold-winter region by using computational fluid dynamics (CFD) methods. Simulations were performed by applying FLUENT software for obtaining airflow distributions within and around a typical low-carbon public building. The temperature distribution in the atrium of the building was simulated particularly for analyzing the natural ventilation performance in a large-space area. Results demonstrated that thermal pressure was dominant for the large-space building in the case study. The average indoor airflow velocities on different floors ranged from 0.43 m/s to 0.47 m/s on the windward side which met indoor ventilation requirements. Most areas of wind velocities could meet ventilation requirements. The natural ventilation performance could be improved by increasing the relative height difference between the air inlets and air outlets. These findings could help provide references and solutions for realizing natural ventilation in low-carbon large-space public buildings in hot-summer and cold-winter regions