磁控微机器人的选择性与独立控制——综述

磁驱动方法具有无线连接和高安全性的特点,是一种常见的微机器人驱动技术,适用于微流体操作以及医疗微机器人导航等应用。然而,由于微型机器人或被驱动的目标暴露在同一片磁场环境中的,使得选择性地控制单个机器人或多个目标中的某一部分变得具有挑战性。本文回顾了磁场驱动的多微型机器人或多关节微型机器人系统的选择性和独立控制方法的最新进展。这些选择性和独立的控制方法将全局磁场解码为特定配置,用于多个微型机器人的独立驱动。这些方法包括将机器人设计成具有与众不同的物理属性或者在工作空间中的不同位置产生性质各异的磁场。对选定目标的独立控制使多个微型机器人能够有效协作以完成更复杂的操作。在这篇综述中,我们提供了一个独特的视角来解释如何在磁场中操纵单个微型机器人以在小尺度机器人中实现高水平的群体智能,这有助于加速微型机器人技术在现实生活中应用的转化和发展。

Noise-like rectangular pulses in a mode-locked double-clad Er:Yb laser with a record pulse energy

Generation of noise-like rectangular pulse was investigated systematically in an Er–Yb co-doped fiber laser based on an intra-cavity coupler with different coupling ratios.When the coupling ratio was 5/95,stable mode-locked pulses could be obtained with the pulse packet duration tunable from 4.86 ns to 80 ns.The repetition frequency was 1.186 MHz with the output spectrum centered at 1.6μm.The average output power and single pulse energy reached a record 1.43 W and1.21μJ,respectively.Pulse characteristics under different coupling ratios(5/95,10/90,20/80,30/70,40/60)were also presented and discussed.

Nimbolide targeting SIRT1 mitigates intervertebral disc degeneration by reprogramming cholesterol metabolism and inhibiting inflammatory signaling

Inflammation,abnormal cholesterol metabolism,and macrophage infiltration are involved in the destruction of the extracellular matrix of the nucleus pulposus(NP),culminating in intervertebral disc degeneration(IDD).Whether nimbolide(Nim),a natural extract,can alleviate IDD is unclear.In this study,we demonstrated that Nim promotes cholesterol efflux and inhibits the activation of the nuclear factor kappa B(NF-κB)and mitogen-activated protein kinase(MAPK)signaling pathways by activating sirtuin 1(SIRT1)in nucleus pulposus cells(NPCs)during inflammation.Thus,Nim balanced matrix anabolism and catabolism of NPCs.However,the inhibition of SIRT1 significantly attenuated the effects of Nim.We also found that Nim promoted the expression of SIRT1 in RAW 264.7,which enhanced the proportion of M2 macrophages by facilitating cholesterol homeostasis reprogramming and impeded M1-like macrophages polarization by blocking the activation of inflammatory signaling.Based on these results,Nim can improve the microenvironment and facilitate matrix metabolism equilibrium in NPCs.Furthermore,in vivo treatment with Nim delayed IDD progression by boosting SIRT1 expression,modulating macrophage polarization and preserving the extracellular matrix.In conclusion,Nim may represent a novel therapeutic strategy for treating IDD.

Retinal microvasculature is a potential biomarker for acute mountain sickness

Increased cerebral blood flow resulting from altered capillary level autoregulation at high altitudes leads to capillary overperfusion and then vasogenic cerebral edema,which is the leading hypothesis of acute mountain sickness(AMS).However,studies on cerebral blood flow in AMS have been mostly restricted to gross cerebrovascular endpoints as opposed to the microvasculature.This study aimed to investigate ocular microcirculation alterations,the only visualized capillaries in the central neural system(CNS),during early-stage AMS using a hypobaric chamber.This study found that after high altitude simulation,the optic nerve showed retinal nerve fiber layer thickening(P=0.004–0.018)in some locations,and the area of the optic nerve subarachnoid space(P=0.004)enlarged.Optical coherence tomography angiography(OCTA)showed increased retinal radial peripapillary capillary(RPC)flow density(P=0.003–0.046),particularly on the nasal side of the nerve.The AMSpositive group had the largest increases in RPC flow density in the nasal sector(AMS-positive,?3.21±2.37;AMS-negative,?0.01±2.16,P=0.004).Among multiple ocular changes,OCTA increase in RPC flow density was associated with simulated early-stage AMS symptoms(beta=0.222,95%CI,0.009–0.435,P=0.042).The area under the receiver operating characteristics curve(AUC)for the changes in RPC flow density to predict early-stage AMS outcomes was 0.882(95%CI,0.746–0.998).The results further confirmed that overperfusion of microvascular beds is the key pathophysiologic change in early-stage AMS.RPC OCTA endpoints may serve as a rapid,noninvasive potential biomarker for CNS microvascular changes and AMS development during risk assessment of individuals at high altitudes.

High Arterial Oxygen Saturation in the Acclimatized Lowlanders Living at High Altitude

Blood oxygen saturation(SpO_(2))is a key indicator of oxygen availability in the body.It is known that a low SpO_(2)at high altitude is associated with morbidity and mortality risks due to physiological hypoxemia.Previously,it was proposed that the lowlander immigrants living at high altitude should have a lower SpO_(2)level compared to the highlander natives,but this proposal has not been rigorously tested due to the lack of data from the lowlander immigrants living at high altitude.In this study,we compared arterial oxygen saturation of 5929 Tibetan natives and 1034 Han Chinese immigrants living at altitudes ranging from 1120 m to 5020 m.Unexpectedly,the Han immigrants had a higher SpO_(2)than the Tibetan natives at the same high altitudes.At the same time,there is a higher prevalence of chronic mountain sickness in Han than in Tibetans at the same altitude.This result suggests that the relatively higher SpO_(2)level of the acclimatized Han is associated with a physiological cost,and the SpO_(2)level of Tibetans tends to be sub-optimal.Consequently,SpO_(2)alone is not a robust indicator of physiological performance at high altitude.

30-W supercontinuum generation based on ZBLAN fiber in an all-fiber configuration

We report an all-fiberized 30-W supercontinuum(SC) generation in a piece of ZrF4-BaF2-LaF3-AlF3-NaF(ZBLAN) fiber. The pump source is a thulium-doped fiber amplifier(TDFA) with broadband output spectrum spanning the 1.9 to 2.6 μm region. The used ZBLAN fiber has a core diameter of 10 μm, and was directly fusion-spliced to the pigtail of the TDFA without using a traditional mode field adapter(MFA) or a piece of transition fiber. Such a low-loss and robust fusion splice joint, together with a robust AlF3-fiber-based endcap,enables efficient and high-power SC generation in the ZBLAN fiber. An SC with an average power up to 30.0 W and a spectral coverage of 1.9–3.35 μm with 20-dB bandwidth of 1.92–3.20 μm was obtained. Moreover, an SC with a broader spectrum was achieved by raising the pump pulse peak power(via reducing the duty ratio of the pump laser pulse). An SC with an output power of 27.4 W and a spectral coverage of 1.9–3.63 μm(with 20-dB bandwidth of 1.92–3.47 μm) was obtained, as well as an SC with output power of 24.8 W and a spectral coverage of 1.9–3.70 μm(with 20-dB bandwidth of 1.93–3.56 μm). The power conversion efficiency was measured as>69%. To the best of the authors’ knowledge, this research demonstrates the record output power of SC lasers based on ZBLAN fibers, paving the way for broadband and efficient multi-tens-of-watts SC generation in softglass fibers.

Integrating deep learning to achieve phase compensation for free-space orbital-angular-momentum-encoded quantum key distribution under atmospheric turbulence

A high-dimensional quantum key distribution(QKD), which adopts degrees of freedom of the orbital angular momentum(OAM) states, is beneficial to realize secure and high-speed QKD. However, the helical phase of a vortex beam that carries OAM is sensitive to the atmospheric turbulence and easily distorted. In this paper, an adaptive compensation method using deep learning technology is developed to improve the performance of OAM-encoded QKD schemes. A convolutional neural network model is first trained to learn the mapping relationship of intensity profiles of inputs and the turbulent phase, and such mapping is used as feedback to control a spatial light modulator to generate a phase screen to correct the distorted vortex beam. Then an OAM-encoded QKD scheme with the capability of real-time phase correction is designed, in which the compensation module only needs to extract the intensity distributions of the Gaussian probe beam and thus ensures that the information encoded on OAM states would not be eavesdropped. The results show that our method can efficiently improve the mode purity of the encoded OAM states and extend the secure distance for the involved QKD protocols in the free-space channel, which is not limited to any specific QKD protocol.

Spectrally flat supercontinuum generation in a holmium-doped ZBLAN fiber with record power ratio beyond 3μm

A spectrally flat mid-infrared supercontinuum(MIR-SC) spanning 2.8–3.9 μm with a maximum output power of 411 mW was generated in a holmium-doped ZBLAN fiber amplifier(HDZFA). A broadband fiber-based SC covering the 2.4–3.2 μm region was designed to seed the amplifier. Benefiting from the broadband seed laser,the obtained SC had a high spectral flatness of 3 dB over the range of 2.93–3.70 μm(770 nm). A spectral integral showed that the SC power beyond 3 μm was 372 mW, i.e., a power ratio of 90.6% of the total power. This paper,to the best of our knowledge, not only demonstrates the first spectrally flat MIR-SC directly generated in fluoride fiber amplifiers, but also reports the highest power ratio beyond 3 μm obtained in rare-earth-doped fluoride fiber until now.

Handwashing quality assessment via deep learning:a modelling study for monitoring compliance and standards in hospitals and communities

Background Hand hygiene can be a simple,inexpensive,and effective method for preventing the spread of infectious diseases.However,a reliable and consistent method for monitoring adherence to the guidelines within and outside healthcare settings is challenging.The aim of this study was to provide an approach for monitoring handwashing compliance and quality in hospitals and communities.Methods We proposed a deep learning algorithm comprising three-dimensional convolutional neural networks(3D CNNs)and used 230 standard handwashing videos recorded by healthcare professionals in the hospital or at home for training and internal validation.An assessment scheme with a probability smoothing method was also proposed to optimize the neural network’s output to identify the handwashing steps,measure the exact duration,and grade the standard level of recognized steps.Twenty-two videos by healthcare professionals in another hospital and 28 videos recorded by civilians in the community were used for external validation.Results Using a deep learning algorithm and an assessment scheme,combined with a probability smoothing method,each handwashing step was recognized(ACC ranged from 90.64%to 98.87%in the hospital and from 87.39%to 96.71%in the community).An assessment scheme measured each step’s exact duration,and the intraclass correlation coefficients were 0.98(95%CI:0.97-0.98)and 0.91(95%CI:0.88-0.93)for the total video duration in the hospital and community,respectively.Furthermore,the system assessed the quality of handwashing,similar to the expert panel(kappa=0.79 in the hospital;kappa=0.65 in the community).Conclusions This work developed an algorithm to directly assess handwashing compliance and quality from videos,which is promising for application in healthcare settings and communities to reduce pathogen transmis-sion.