27 research outputs found
Highly sensitive detection of CYFRA21-1 with a SERS sensing platform based on the MBs enrichment strategy and antibody-DNA-mediated CHA amplification
Laryngeal carcinoma (LC) is the second most common malignant tumor of the head and neck. Due to its insidious nature, most patients have developed to the middle and late stages by the time they are diagnosed, missing the best treatment period. Thus, early detection, diagnosis and treatment are crucial to improve the prognosis of LC and enhance the quality of life of patients. In this study, a surface-enhanced Raman (SERS) sensing platform was developed by combining the magnetic beads (MBs) enrichment strategy and the antibody-DNA-mediated catalytic hairpin self-assembly (CHA) signal amplification technology. 4-Mercaptobenzoic acid (4-MBA) and hairpin DNA 1 (hpDNA1) were modified onto the surface of gold nanobipyramids (GNBPs) as SERS nanotags. Hairpin DNA 2 (hpDNA2) modified MBs were used as capture nanoprobes. Under the action of CHA and magnet-induced MBs enrichment, GNBPs can be assembled on the surface of MBs, forming high-density “hot spots” for the SERS signal enhancement. The results showed that the SERS sensing platform has the advantages of high sensitivity, high specificity and high reproducibility, with the limit of detection (LOD) low to pg/mL level. The expression level of CYFRA21-1 in serum of LC patients and healthy controls was successfully detected by the SERS sensing platform. The accuracy of the SERS results was verified by enzyme linked immunosorbent assay (ELISA). Therefore, this SERS sensor can be used for the detection of CYFRA21-1 in serum, providing a simple and reliable new method for the early diagnosis of LC
Fast and Accurate Prediction of Light Scattering from Plasmonic Nanoarrays in Multiple Directions
The method of moments (MoM) is an efficient electromagnetic numerical method for the accurate prediction of light scattering from plasmonic nanostructures. In practice, the light-scattering properties in different incident directions are often concerning. However, traditional MoM generally resorts to the iterative method, which suffers from the problems of convergence rate and redundant computations for multiple incident excitations. Nanoarray structures will further aggravate these problems due to a large number of unknowns. In this article, an efficient numerical method based on MoM and a hierarchical matrix (H-matrix) algorithm is proposed to solve these problems. Numerical experiments demonstrate the efficiency and accuracy of the proposed method for the prediction of light scattering from plasmonic nanoarrays in multiple directions
Industrial Process Monitoring Based on Knowledge–Data Integrated Sparse Model and Two-Level Deviation Magnitude Plots
Thermo-Hydrodynamic Lubricating Behaviors of Upstream Liquid Face Seals with Ellipse Dimples
In order to obtain the leakage characteristics of an upstream pumping face seal with inclined ellipse dimples under high-temperature and high-speed liquid lubricating conditions, a thermo-hydrodynamic lubricating model is developed. The novelty of this model is that it takes the thermo-viscosity effect and cavitation effect into account. The influence of operating parameters, such as rotational speed, seal clearance, seal pressure, ambient temperature and structural parameters, such as dimple depth, inclination angle, slender ratio and dimple number on the opening force and leakage rate, is numerically calculated. The results obtained show that the thermo-viscosity effect makes the cavitation intensity decrease noticeably, leading to an increase in the upstream pumping effect of ellipse dimples. Moreover, the thermo-viscosity effect may make both the upstream pumping leakage rate and opening force increase by about 10%. It can also be found that the inclined ellipse dimples can produce an obvious upstream pumping effect and hydrodynamic effect. Based on the reasonable design of the dimple parameter, not only can the sealed medium achieve zero leakage, but the opening force can also increase by more than 50%. The proposed model has the potential to provide the theoretical basis for and guide the future designs of upstreaming liquid face seals
Just-in-Time Selection of Principal Components for Fault Detection: The Criteria Based on Principal Component Contributions to the Sample Mahalanobis Distance
Comparison of Different Types of Corneal Foreign Bodies Using Anterior Segment Optical Coherence Tomography: A Prospective Observational Study
Purpose. The present study highlighted the value of anterior segment optical coherence tomography (AS-OCT) for different types of corneal foreign bodies in humans. Methods. This study was a prospective observational study. The patients included were divided into two groups. If the patients were directly diagnosed based on eye injury history and slit-lamp examination, then they were assigned to Group A. Otherwise, the patients were assigned to Group B. We compared and described the characteristics of the corneal foreign body in both groups using AS-OCT. Results. From October 2017 to January 2020, 36 eyes of 36 patients (9 females and 27 males) with a mean age of 37.8 ± 11.7 years were included in the study. Patients in Group A were the majority and accounted for 72.2% (26/36). High signals on AS-OCT images were the main constituent and accounted for 92.3% (24/26) in Group A and 70.0% (7/10) in Group B. Most of the patients in Group A, 96.2% (25/26), had clear boundaries. A blurred boundary was observed in 70.0% (7/10) of the patients in Group B. The foreign bodies on AS-OCT images had key characteristics of a high signal followed by a central zone shadowing effect and a low signal followed by a marginal zone shadowing effect. Further, all of the lesions could be directly located in Group B, and 92.3% (24/26) of the patients in Group A did not have directly located lesions. Six representative cases are described in detail. Conclusions. AS-OCT is a valuable tool in the diagnosis and management of corneal foreign bodies, especially for unusual corneal foreign body
A Machine Olfaction-Based Overheating Diagnosis Method for Electrical Equipment
Achieving early warning of electrical fires is of great importance in preventing their occurrence. The overheating diagnosis of electrical equipment by detecting volatiles is an effective way to achieve early warning of electrical fires. This paper proposes a machine olfaction-based overheating diagnosis method for electrical equipment. First, the primary materials commonly used for non-metallic elements in electrical equipment are determined. Second, a semiconductor oxide sensor array is designed based on the volatiles generated by these materials during overheating. Next, the output curves of the sensor array at different heating temperatures for these materials are obtained through experiments. Subsequently, the output data of the sensor array at multiple moments in the period of each output curve entering the plateau are extracted to construct the output vectors of the sensor array. Then, the Principal Component Analysis (PCA) algorithm and Linear Discriminant Analysis (LDA) algorithm are used to extract the characteristic quantities in the output vectors to construct the feature vectors. Finally, a second-order BP neural network model is designed based on the feature vector to determine whether the electrical equipment is overheated and what the overheated material is. The experimental results show that the accuracy of the proposed overheating diagnosis method can reach 94.58%
Investigation on Structural Behaviors of Reactor Pressure Vessel With the Effects of Critical Heat Flux and Internal Pressure
Reporting quality of economic evaluations of the negotiated Traditional Chinese Medicines in national reimbursement drug list of China: A systematic review
Abstracts: Background: Traditional Medicine (TM) has a wide uptake in most countries. In China, Traditional Chinese Medicine (TCM) is a common kind of primary health because of its beneficial effects. This review aimed to appraise the publication reporting quality of economic evaluations for selective TCM in the National Reimbursement Drug List (NRDL), Version 2020, based on the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement. Methods: Electronic databases were searched for economic evaluation that supported the TCM negotiations in NRDL (2020 version) published from 2001 to 2021, including PubMed, Web of Science, Embase, CNKI, WanFang, and SinoMed. The CHEERS statement was used to appraise the reporting quality of included TCM economic evaluations. Results: A total of 360 articles were retrieved, but only 38 economic evaluations met the inclusion criteria. None of the articles reported all items in the CHEERS checklist. The mean score of included articles is low at 10.93±2.62, with an average scoring rate of 51.31±10.53%. The least reported items included: “Characterizing heterogeneity,” “Conflicts of interest”, “Discount rate,” and “Study perspective,” with a reporting rate of 0.00%, 5.26%, 7.89%, and 15.79%, respectively. Conclusion: An upward trend occurred in the quantity and quality of the economic evaluation publications of TCM in China. TCM economic evaluations are still at an early stage, with an urgent need for improving reporting quality. It may result from research experiences or different ideas between TCM and Western Medicine. Adhering to reporting guidelines like CHEERS and educating economic evaluation investigators can improve TCM economic evaluations’ reporting quality