Design and simulation of shear-tension spring-type quasi-zero stiffness isolator

By connecting the linear compression spring (positive stiffness mechanism) in parallel with the tension spring (negative stiffness mechanism) and using the shear lever mechanism to amplify the motion of the negative stiffness mechanism, a shear-tension spring type quasi-zero stiffness isolation system is constructed, which is suitable for low-frequency and ultra-low-frequency vibration isolation, especially for small-amplitude, low-frequency vibration isolation. In addition, the vibration isolation system has adjustable function. When the mass of the isolated object changes, it is needed to adjust the linear bearing at the bottom of the vertical spring to change the length of the spring, so as to keep the isolation system in the equilibrium position of the quasi-zero state. The results show that the isolator has excellent performance in isolation of low frequency vibration with small and micro amplitude

Cardinality and Bounding Constrained Portfolio Optimization Using Safe Reinforcement Learning

Portfolio optimization is a strategic approach aiming at achieving an optimal balance between risk and returns through the judicious allocation of limited capital across various assets. In recent years, there has been a growing interest in leveraging Deep Reinforcement Learning (DRL) to tackle the complexities of portfolio optimization. Despite its potential, a notable limitation of DRL algorithms is their inherent difficulty in integrating conflicted objectives with the reward functions throughout the learning process. Typically, DRL's reward function prioritizes the maximization of returns or other performance indicators, often overlooking the integration of risk aspects. Furthermore, the standard DRL framework struggles to incorporate practical constraints, such as cardinality and bounding, into the decision process. Without these constraints, the investment strategies developed might be unrealistic and unmanageable. To this end, in this paper, we propose an adaptive and safe DRL framework, which can dynamically optimize the portfolio weights while strictly respecting practical constraints. In our method, any infeasible action (i.e., one that violates the constraints) decided by the RL agent will be mapped to a feasible region using a safety layer. The extended Markowitz Mean-Variance (M-V) model is explicitly encoded in the safety layer to ensure the feasibility of the actions from the alternative views. In addition, we utilize Projection-based Interior-point Policy Optimization (IPO) to resolve multiple objectives and constraints in the examined problem. Extensive results on real-world datasets show that our method is effective in strictly respecting constraints under dynamic market environments, in contrast to prevailing data- driven trading strategies and conventional model-based static solutions

Automatic nodule identification and differentiation in ultrasound videos to facilitate per-nodule examination

Ultrasound is a vital diagnostic technique in health screening, with the advantages of non-invasive, cost-effective, and radiation free, and therefore is widely applied in the diagnosis of nodules. However, it relies heavily on the expertise and clinical experience of the sonographer. In ultrasound images, a single nodule might present heterogeneous appearances in different cross-sectional views which makes it hard to perform per-nodule examination. Sonographers usually discriminate different nodules by examining the nodule features and the surrounding structures like gland and duct, which is cumbersome and time-consuming. To address this problem, we collected hundreds of breast ultrasound videos and built a nodule reidentification system that consists of two parts: an extractor based on the deep learning model that can extract feature vectors from the input video clips and a real-time clustering algorithm that automatically groups feature vectors by nodules. The system obtains satisfactory results and exhibits the capability to differentiate ultrasound videos. As far as we know, it's the first attempt to apply re-identification technique in the ultrasonic field

A flexible virtual sensor array based on laser-induced graphene and MXene for detecting volatile organic compounds in human breath

Detecting volatile organic compounds (VOCs) in human breath is critical for the early diagnosis of diseases. Good selectivity of VOC sensors is crucial for the accurate analysis of VOC biomarkers in human breath, which consists of more than 200 types of VOCs. In this paper, a flexible virtual sensor array (FVSA) was proposed based on a sensing layer of MXene and laser-induced graphene interdigital electrodes (LIG-IDEs) for detecting VOCs in exhaled human breath. The fabrication of LIG-IDEs avoids the costly and complicated procedures required for the preparation of traditional IDEs. The FVSA's responses of multiple parameters help build a unique fingerprint for each VOC, without a need for changing the temperature of the sensing element, which is commonly used in the VSA of semiconductor VOC sensors. Based on machine learning algorithms, we have achieved highly precise recognition of different VOCs and mixtures and accurate prediction (accuracy of 89.1%) of the objective VOC's concentration in variable backgrounds using this proposed FVSA. Moreover, a blind analysis validates the capacity of the FVSA to identify alcohol content in human breath with an accuracy of 88.9% using breath samples from volunteers before and after alcohol consumption. These results show that the proposed FVSA is promising for the detection of VOC biomarkers in human exhaled breath and early diagnosis of diseases

Bubble in the Whale: Identifying the Optical Counterparts and Extended Nebula for the Ultraluminous X-ray Sources in NGC 4631

We present a deep optical imaging campaign on the starburst galaxy NGC 4631 with CFHT/MegaCam. By supplementing the HST/ACS and Chandra/ACIS archival data, we search for the optical counterpart candidates of the five brightest X-ray sources in this galaxy, four of which are identified as ultraluminous X-ray sources (ULXs). The stellar environments of the X-ray sources are analyzed using the extinction-corrected color-magnitude diagrams and the isochrone models. We discover a highly asymmetric bubble nebula around X4 which exhibits different morphology in the H$\alpha$ and [O III] images. The [O III]/H$\alpha$ ratio map shows that the H$\alpha$-bright bubble may be formed mainly via the shock ionization by the one-sided jet/outflow, while the more compact [O III] structure is photoionized by the ULX. We constrain the bubble expansion velocity and interstellar medium density with the MAPPINGS V code, and hence estimate the mechanical power injected to the bubble as $P_w \sim 5\times10^{40}$ erg s$^{-1}$ and the corresponding bubble age of $\sim7\times 10^{5}$ yr. Relativistic jets are needed to provide such level of mechanical power with a mass-loss rate of $\sim10^{-7}\ M_{\odot}\ \rm yr^{-1}$. Besides the accretion, the black hole spin is likely an additional energy source for the super-Eddington jet power.Comment: 17 pages, 10 figures, accepted by Ap

Epidemiology of invasive group B streptococcal disease in infants from urban area of South China, 2011–2014

YesBackground: Group B Streptococcus (GBS) is a leading cause of morbidity and mortality in infants in both developed and developing countries. To our knowledge, only a few studies have been reported the clinical features, treatment and outcomes of the GBS disease in China. The severity of neonatal GBS disease in China remains unclear. Population-based surveillance in China is therefore required. Methods: We retrospectively collected data of <3 months old infants with culture-positive GBS in sterile samples from three large urban tertiary hospitals in South China from Jan 2011 to Dec 2014. The GBS isolates and their antibiotic susceptibility were routinely identified in clinical laboratories in participating hospitals. Serotyping and multi-locus sequence typing (MLST) were also conducted for further analysis of the neonatal GBS disease. Results: Total 70 cases of culture-confirmed invasive GBS infection were identified from 127,206 live births born in studying hospitals, giving an overall incidence of 0.55 per 1000 live births (95% confidence interval [CI] 0.44–0.69). They consisted of 49 with early-onset disease (EOD, 0.39 per 1000 live births (95% CI 0.29–0.51)) and 21 with late-onset disease (LOD, 0.17 per 1000 live births (95% CI 0.11–0.25)). The incidence of EOD increased significantly over the studying period. Five infants (4 EOD and 1 LOD) died before discharge giving a mortality rate of 7.1% and five infants (7.1%, 2 EOD and 3 LOD) had neurological sequelae. Within 68 GBS isolates from GBS cases who born in the studying hospitals or elsewhere, serotype III accounted for 77.9%, followed by Ib (14.7%), V (4.4%), and Ia (2.9%). MLST analysis revealed the presence of 13 different sequence types among the 68 GBS isolates and ST-17 was the most frequent sequence type (63.2%). All isolates were susceptible to penicillin, ceftriaxone, vancomycin and linezolid, while 57.4% and 51.5% were resistant to erythromycin and clindamycin, respectively. Conclusions: This study gains the insight into the spectrum of GBS infection in south China which will facilitate the development of the guidance for reasonable antibiotics usage and will provide evidence for the implementation of potential GBS vaccines in the future.Supported by medical and health science and technology projects of Health and Family Planning Commission of Guangzhou Municipality (grant number 20151A010034) and Guangdong provincial science and technology planning projects (grant number 2014A020212520)