基于灰色关联度与TOPSIS模型分析不同配伍比例的知母对石膏中6种无机元素溶出的影响

目的基于灰色关联度和逼近理想解排序(TOPSIS)法探讨配伍不同比例的知母对石膏中钾(K)、钛(Ti)、锶(Sr)、钡(Ba)、钙(Ca)、镁(Mg)6种无机元素溶出的影响,为临床提供一定参考。方法建立电感耦合等离子体质谱(ICP-MS)法同时分析石膏-知母药对中K、Ti、Sr、Ba、Ca、Mg 6种无机元素含量,并用灰色关联度法和TOPSIS综合分析,与不同比例知母配伍前后,石膏中6种无机元素溶出的变化。结果ICP-MS法测定石膏-知母药对中无机元素的线性、精密度、重复性和稳定性试验结果良好,平均加样回收率为81.78%~104.13%,RSD为2.10%~4.62%(n=6)。与不同比例知母配伍后石膏中6种无机元素的溶出均显著高于石膏单煎(P<0.05),石膏-知母30∶9配伍比例时石膏中6种无机元素溶出得分最高。结论ICP-MS法灵敏度高、准确性好,可用于石膏-知母药对中K、Ti、Sr、Ba、Ca、Mg等6种无机元素的溶出量测定。石膏-知母最佳配伍比例为30∶9时,可有效提高石膏中6种无机元素的溶出,为两者进一步的配伍研究提供依据。

Intelligent risk identification of gas drilling based on nonlinear classification network

During the transient process of gas drilling conditions,the monitoring data often has obvious nonlinear fluctuation features,which leads to large classification errors and time delays in the commonly used intelligent classification models.Combined with the structural features of data samples obtained from monitoring while drilling,this paper uses convolution algorithm to extract the correlation features of multiple monitoring while drilling parameters changing with time,and applies RBF network with nonlinear classification ability to classify the features.In the training process,the loss function component based on distance mean square error is used to effectively adjust the best clustering center in RBF.Many field applications show that,the recognition accuracy of the above nonlinear classification network model for gas production,water production and drill sticking is 97.32%,95.25%and 93.78%.Compared with the traditional convolutional neural network(CNN)model,the network structure not only improves the classification accuracy of conditions in the transition stage of conditions,but also greatly advances the time points of risk identification,especially for the three common risk identification points of gas production,water production and drill sticking,which are advanced by 56,16 and 8 s.It has won valuable time for the site to take correct risk disposal measures in time,and fully demonstrated the applicability of nonlinear classification neural network in oil and gas field exploration and development.

General anesthesia mediated by effects on ion channels

Although it has been more than 165 years since the first introduction of modern anesthesia to the clinic, there is surprisingly little understanding about the exact mechanisms by which general anesthetics induce unconsciousness. As a result, we do not know how general anesthetics produce anesthesia at different levels. The main handicap to understanding the mechanisms of general anesthesia is the diversity of chemically unrelated compounds including diethyl ether and halogenated hydrocarbons, gases nitrous oxide, ketamine, propofol, benzodiazepines and etomidate, as well as alcohols and barbiturates. Does this imply that general anesthesia is caused by many different mechanisms? Until now, many receptors, molecular targets and neuronal transmission pathways have been shown to contribute to mechanisms of general anesthesia. Among these molecular targets, ion channels are the most likely candidates for general anesthesia, in particular γ-aminobutyric acid type A, potassium and sodium channels, as well as ion channels mediated by various neuronal transmitters like acetylcholine, amino acids amino-3-hydroxy-5-methyl-4-isoxazolpropionic acid or N-methyl-D-aspartate. In addition, recent studies have demonstrated the involvement in general anesthesia of other ion channels with distinct gating properties suchas hyperpolarization-activated, cyclic- nucleotide-gated channels. The main aim of the present review is to summarize some aspects of current knowledge of the effects of general anesthetics on various ion channels.

Ophthalmic Syndrome Differentiation System and Digital Chinese Medicine

In traditional Chinese medicine(TCM),ophthalmic syndrome differentiation is an ophthalmology-specific method for identifying syndromes based on the“Five Orbiculi”theory.It was devised by Professor Qing-Hua PENG through an unprecedented combination of syndrome element differentiation and ophthalmic clinical practices,based on the Clinical Terminology of Chinese Medical Diagnosis and Treatment-Syndromes of the National Standards of the People's Republic of China.This approach integrates an ophthalmic syndrome differentiation system with digital Chinese medicine(DCM),and proposes the extraction of syndrome elements of ophthalmic diseases from research on DCM.These elements are then quantified and organized to form a model of digital diagnosis and treatment specific to ophthalmology,which should help to achieve synergistic development of the ophthalmic syndrome differentiation system and DCM.

Assessing performance of augmented reality-based neurosurgical training

This paper presents a novel augmented reality(AR)-based neurosurgical training simulator which provides a very natural way for surgeons to learn neurosurgical skills.Surgical simulation with bimanual haptic interaction is integrated in this work to provide a simulated environment for users to achieve holographic guidance for pre-operative training.To achieve the AR guidance,the simulator should precisely overlay the 3D anatomical information of the hidden target organs in the patients in real surgery.In this regard,the patient-specific anatomy structures are reconstructed from segmented brain magnetic resonance imaging.We propose a registration method for precise mapping of the virtual and real information.In addition,the simulator provides bimanual haptic interaction in a holographic environment to mimic real brain tumor resection.In this study,we conduct AR-based guidance validation and a user study on the developed simulator,which demonstrate the high accuracy of our AR-based neurosurgery simulator,as well as the AR guidance mode’s potential to improve neurosurgery by simplifying the operation,reducing the difficulty of the operation,shortening the operation time,and increasing the precision of the operation.

A Bright Single-Photon Source from Nitrogen-Vacancy Centers in Diamond Nanowires

Single-photon flux is one of the crucial properties of nitrogen vacancy （NV） centers in diamond for its application in quantum information techniques. Here we fabricate diamond conical nanowires to enhance the single-photon count rate. Through the interaction between tightly confined optical mode in nanowires and NV centers, the single-photon lifetime is much shortened and the collection efficiency is enhanced. As a result, the detected single-photon rate can be at 564 kcps, and the total detection coefficient can be 0.8%, which is much higher than that in bulk diamond. Such a nanowire single-photon device with high photon flux can be applied to improve the fidelity of quantum computation and the precision of quantum sensors.

SSL Depth: self-supervised learning enables 16× speedup in confocal microscopy-based 3D surface imaging [Invited]

In scientific and industrial research, three-dimensional (3D) imaging, or depth measurement, is a critical tool that provides detailed insight into surface properties. Confocal microscopy, known for its precision in surface measurements, plays a key role in this field. However, 3D imaging based on confocal microscopy is often challenged by significant data requirements and slow measurement speeds. In this paper, we present a novel self-supervised learning algorithm called SSL Depth that overcomes these challenges. Specifically, our method exploits the feature learning capabilities of neural networks while avoiding the need for labeled data sets typically associated with supervised learning approaches. Through practical demonstrations on a commercially available confocal microscope, we find that our method not only maintains higher quality, but also significantly reduces the frequency of the z-axis sampling required for 3D imaging. This reduction results in a remarkable 16×measurement speed, with the potential for further acceleration in the future. Our methodological advance enables highly efficient and accurate 3D surface reconstructions, thereby expanding the potential applications of confocal microscopy in various scientific and industrial fields.

Learning the imaging mechanism directly from optical microscopy observations

The optical microscopy image plays an important role in scientific research through the direct visualization of the nanoworld,where the imaging mechanism is described as the convolution of the point spread function(PSF)and emitters.Based on a priori knowledge of the PSF or equivalent PSF,it is possible to achieve more precise exploration of the nanoworld.However,it is an outstanding challenge to directly extract the PSF from microscopy images.Here,with the help of self-supervised learning,we propose a physics-informed masked autoencoder(PiMAE)that enables a learnable estimation of the PSF and emitters directly from the raw microscopy images.We demonstrate our method in synthetic data and real-world experiments with significant accuracy and noise robustness.PiMAE outperforms DeepSTORM and the Richardson–Lucy algorithm in synthetic data tasks with an average improvement of 19.6%and 50.7%(35 tasks),respectively,as measured by the normalized root mean square error(NRMSE)metric.This is achieved without prior knowledge of the PSF,in contrast to the supervised approach used by DeepSTORM and the known PSF assumption in the Richardson–Lucy algorithm.Our method,PiMAE,provides a feasible scheme for achieving the hidden imaging mechanism in optical microscopy and has the potential to learn hidden mechanisms in many more systems.

Picotesla fiberized diamond-based AC magnetometer

Portable quantum sensors are crucial for developing practical quantum sensing and metrology applications.Fiberized nitrogen-vacancy(NV)centers in diamonds have emerged as one of the most promising candidates for compact quantum sensors.Nevertheless,due to the difficulty of coherently controlling the ensemble spin and noise suppression in a large volume,it often faces problems such as reduced sensitivity and narrowed bandwidth in integrated lensless applications.Here,we propose a fluorescence signal treatment method for NV spin ensemble manipulation by the exponential fitting of spin polarization processes,instead of integrating the photon emission.This enables spin state readout with a high signal-to-noise ratio and applies to the pulse sensing protocols for large-volume NV spins.Based on this,we further developed a fiberized diamond-based AC magnetometer.With an XY8-N dynamical decoupling pulse sequence,we demonstrated a T_(2)-limited sensitivity of 8pT/√Hz and T_(1)-limited frequency resolution of 90 Hz over a wide frequency band from 100 kHz to 3 MHz.This integrated diamond sensor leverages quantum coherence to achieve enhanced sensitivity in detecting AC magnetic fields,making it suitable for implementation in a compact and portable endoscopic sensor.

Electroacupuncture alleviates postoperative pain through inhibiting neuroinflammation via stimulator of interferon genes/type-1 interferon pathway

Objective This work explores the impact of electroacupuncture(EA)on acute postoperative pain(APP)and the role of stimulator of interferon genes/type-1 interferon(STING/IFN-1)signaling pathway modulation in the analgesic effect of EA in APP rats.Methods The APP rat model was initiated through abdominal surgery and the animals received two 30 min sessions of EA at bilateral ST36(Zusanli)and SP6(Sanyinjiao)acupoints.Mechanical,thermal and cold sensitivity tests were performed to measure the pain threshold,and electroencephalograms were recorded in the primary somatosensory cortex to identify the effects of EA treatment on APP.Western blotting and immunofluorescence were used to examine the expression and distribution of proteins in the STING/IFN-1 pathway as well as neuroinflammation.A STING inhibitor(C-176)was administered intrathecally to verify its role in EA.Results APP rats displayed mechanical and thermal hypersensitivities compared to the control group(P<0.05).APP significantly reduced the amplitude ofθ,αandγoscillations compared to their baseline values(P<0.05).Interestingly,expression levels of proteins in the STING/IFN-1 pathway were downregulated after inducing APP(P<0.05).Further,APP increased pro-inflammatory factors,including interleukin-6,tumor necrosis factor-αand inducible nitric oxide synthase,and downregulated anti-inflammatory factors,including interleukin-10 and arginase-1(P<0.05).EA effectively attenuated APP-induced painful hypersensitivities(P<0.05)and restored theθ,αandγpower in APP rats(P<0.05).Meanwhile,EA distinctly activated the STING/IFN-1 pathway and mitigated the neuroinflammatory response(P<0.05).Furthermore,STING/IFN-1 was predominantly expressed in isolectin-B4-or calcitonin-gene-related-peptide-labeled dorsal root ganglion neurons and superficial laminae of the spinal dorsal horn.Inhibition of the STING/IFN-1 pathway by intrathecal injection of C-176 weakened the analgesic and anti-inflammatory effects of EA on APP(P<0.05).Conclusion EA can generate robust analgesic and anti-inflammatory effects on APP,and these effects may be linked to activating the STING/IFN-1 pathway,suggesting that STING/IFN-1 may be a target for relieving APP.

High-sensitivity and wide-bandwidth fiber-coupled diamond magnetometer with surface coating

Mapping magnetic fields from different materials and structures can provide a powerful means for broad applications of activity probe and feature analysis.Here,we present a high-sensitivity and wide-bandwidth fiber-based quantum magnetometer at the scale of a few hundred micrometers.We propose a fiber-coupled diamond magnetometer.Tracking a pulsed optically detected magnetic resonance spectrum allows a magnetic field sensitivity of 103 pT∕■and a bandwidth of 2.6 k Hz.Additionally,with an approach of coating the diamond surface with silver reflective film,both the fluorescence collection and excitation efficiency are significantly enhanced,and the sensitivity and bandwidth are expected to be further improved to 50 pT∕■and 4.1 k Hz,respectively.Finally,this fiber-based quantum magnetometer is applied as a probe to successfully map the magnetic field induced by the current-carrying copper-wire mesh.Such a stable and compact magnetometer can provide a powerful tool in many areas of physical,chemical,and biological researches.

High resolution imaging with anomalous saturated excitation

The nonlinear fluorescence emission has been widely applied for high spatial resolution optical imaging.Here,we studied the fluorescence anomalous saturating effect of the nitrogen vacancy defect in diamond.The fluorescence reduction was observed with high power laser excitation.It increased the nonlinearity of the fluorescence emission,and changed the spatial frequency distribution of the fluorescence image.We used a differential excitation protocol to extract the high spatial frequency information.By modulating the excitation laser’s power,the spatial resolution of imaging was improved approximately 1.6 times in comparison with the confocal microscopy.Due to the simplicity of the experimental setup and data processing,we expect this method can be used for improving the spatial resolution of sensing and biological labeling with the defects in solids.