Novel Methods for Calibration in Raman Spectroscopy

Raman spectroscopy can probe the chemical structure of a material providing an optical ’fingerprint’ unique to the sample. Such is the capacity of Raman spectroscopy to identify differentmaterials, it be to classify biological cells and tissue and can provide an ’optical biopsy’ for various types of disease. A key component in Raman diagnostics is the use of multivariate statistical algorithms that can be trained using datasets of known samples to classify the groups based on the subtle differences between them. Despite the great progress in this field in recent decades, Raman spectroscopy has never been adopted clinically. The key reason for this is the poor resproducibility of Raman spectroscopy across instruments; in other words the same material can produce different spectra when recorded using different spectrometers. These differences can include small movement of the Raman peaks along the wavenumber axis (wavenumber miscalibration) or modulation in the amplitude of the peaks (intensity calibration). Such changes can render a multivariate classifier trained on one instrument to be completely useless in identifying samples recorded from another instrument. The overall goal of this thesis is to develop new methods for wavenumber and intensity calibration that can help Raman spectroscopy penetrate into the clinic

Toward Learning Model-Agnostic Explanations for Deep Learning-Based Signal Modulation Classifiers

Recent advances in deep learning (DL) have brought tremendous gains in signal modulation classification. However, DL-based classifiers lack transparency and interpretability, which raises concern about model's reliability and hinders the wide deployment in real-word applications. While explainable methods have recently emerged, little has been done to explain the DL-based signal modulation classifiers. In this work, we propose a novel model-agnostic explainer, Model-Agnostic Signal modulation classification Explainer (MASE), which provides explanations for the predictions of black-box modulation classifiers. With the subsequence-based signal interpretable representation and in-distribution local signal sampling, MASE learns a local linear surrogate model to derive a class activation vector, which assigns importance values to the timesteps of signal instance. Besides, the constellation-based explanation visualization is adopted to spotlight the important signal features relevant to model prediction. We furthermore propose the first generic quantitative explanation evaluation framework for signal modulation classification to automatically measure the faithfulness, sensitivity, robustness, and efficiency of explanations. Extensive experiments are conducted on two real-world datasets with four black-box signal modulation classifiers. The quantitative results indicate MASE outperforms two state-of-the-art methods with 44.7% improvement in faithfulness, 30.6% improvement in robustness, and 44.1% decrease in sensitivity. Through qualitative visualizations, we further demonstrate the explanations of MASE are more human interpretable and provide better understanding into the reliability of black-box model decisions

Sintering Bonding Process with Ag Nanoparticle Paste and Joint Properties in High Temperature Environment

Ag nanoparticle paste is prepared based on the polyol method and subsequent concentration by centrifuging. The sintering bonding process using Ag nanoparticle paste at different bonding pressures is studied. The joint strengths are increased as the bonding pressure increases from 0 MPa to 7.5 MPa. This is due to the fact that the higher assistant bonding pressure is beneficial to the growth of neck size between the adjacent particles and forms denser sintered Ag layers. The joint strength bonded under 10 MPa is lower than that bonded under 7.5 MPa, which may be due to the residue of organic component in the sintered Ag layer. The joint properties bonded with Ag nanoparticle paste in high temperature environment are evaluated by heat treatments at temperatures ranges of 200–350°C for 50 hours. The results show that the mechanical properties of joint with Ag nanoparticle paste are better than the joint with Pb95Sn5 solder after storage at high temperatures

Clinical spectrum and gene mutations in a Chinese cohort with anoctaminopathy

Recessive mutations in anoctamin-5 (ANO5) are causative for limb-girdle muscular dystrophy (LGMD) 2L and non-dysferlin Miyoshi-like distal myopathy (MMD3). ANDS mutations are highly prevalent in European countries; however it is not common in patients of Asian origin, and there is no data regarding the Chinese population. We retrospectively reviewed the clinical manifestations and gene mutations of Chinese patients with anoctaminopathy. A total of five ANDS mutations including four novel mutations and one reported mutation were found in four patients from three families. No hotspot mutation was found. Three patients presented with presymptomatic hyperCKemia and one patient had limb muscle weakness. Muscle imaging of lower limbs showed preferential adductor magnus and medial gastrocnemius involvement. No hotspot mutation has been identified in Chinese patients to date. (C) 2019 Elsevier B.V. All rights reserved.Peer reviewe

A Comparative Study of Systolic and Diastolic Mechanical Synchrony in Canine, Primate, and Healthy and Failing Human Hearts.

Aim: Mechanical dyssynchrony (MD) is associated with heart failure (HF) and may be prognostically important in cardiac resynchronization therapy (CRT). Yet, little is known about its patterns in healthy or diseased hearts. We here investigate and compare systolic and diastolic MD in both right (RV) and left ventricles (LV) of canine, primate and healthy and failing human hearts. Methods and Results: RV and LV mechanical function were examined by pulse-wave Doppler in 15 beagle dogs, 59 rhesus monkeys, 100 healthy human subjects and 39 heart failure (HF) patients. This measured RV and LV pre-ejection periods (RVPEP and LVPEP) and diastolic opening times (Q-TVE and Q-MVE). The occurrence of right (RVMDs) and left ventricular systolic mechanical delay (LVMDs) was assessed by comparing RVPEP and LVPEP values. That of right (RVMDd) and left ventricular diastolic mechanical delay (LVMDd) was assessed from the corresponding diastolic opening times (Q-TVE and Q-MVE). These situations were quantified by values of interventricular systolic (IVMDs) and diastolic mechanical delays (IVMDd), represented as positive if the relevant RV mechanical events preceded those in the LV. Healthy hearts in all species examined showed greater LV than RV delay times and therefore positive IVMDs and IVMDd. In contrast a greater proportion of the HF patients showed both markedly increased IVMDs and negative IVMDd, with diastolic mechanical asynchrony negatively correlated with LVEF. Conclusion: The present IVMDs and IVMDd findings have potential clinical implications particularly for personalized setting of parameter values in CRT in individual patients to achieve effective treatment of HF

Language learning strategies among English majors in a Chinese technological institute : an investigation of self-reported strategy use and of six factors that may affect the results

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Novel Methods for Calibration in Raman Spectroscopy

Raman spectroscopy can probe the chemical structure of a material providing an optical ’fingerprint’ unique to the sample. Such is the capacity of Raman spectroscopy to identify differentmaterials, it be to classify biological cells and tissue and can provide an ’optical biopsy’ for various types of disease. A key component in Raman diagnostics is the use of multivariate statistical algorithms that can be trained using datasets of known samples to classify the groups based on the subtle differences between them. Despite the great progress in this field in recent decades, Raman spectroscopy has never been adopted clinically. The key reason for this is the poor resproducibility of Raman spectroscopy across instruments; in other words the same material can produce different spectra when recorded using different spectrometers. These differences can include small movement of the Raman peaks along the wavenumber axis (wavenumber miscalibration) or modulation in the amplitude of the peaks (intensity calibration). Such changes can render a multivariate classifier trained on one instrument to be completely useless in identifying samples recorded from another instrument. The overall goal of this thesis is to develop new methods for wavenumber and intensity calibration that can help Raman spectroscopy penetrate into the clinic

Novel Methods for Calibration in Raman Spectroscopy

Raman spectroscopy can probe the chemical structure of a material providing an optical ’fingerprint’ unique to the sample. Such is the capacity of Raman spectroscopy to identify differentmaterials, it be to classify biological cells and tissue and can provide an ’optical biopsy’ for various types of disease. A key component in Raman diagnostics is the use of multivariate statistical algorithms that can be trained using datasets of known samples to classify the groups based on the subtle differences between them. Despite the great progress in this field in recent decades, Raman spectroscopy has never been adopted clinically. The key reason for this is the poor resproducibility of Raman spectroscopy across instruments; in other words the same material can produce different spectra when recorded using different spectrometers. These differences can include small movement of the Raman peaks along the wavenumber axis (wavenumber miscalibration) or modulation in the amplitude of the peaks (intensity calibration). Such changes can render a multivariate classifier trained on one instrument to be completely useless in identifying samples recorded from another instrument. The overall goal of this thesis is to develop new methods for wavenumber and intensity calibration that can help Raman spectroscopy penetrate into the clinic

The complete chloroplast genome of Prunus verecunda, and phylogenetic analysis with amygdaleae species

We assembled complete chloroplast (cp) genome of Prunus verecunda based on Illumina sequencing. The cp genome of P. verecunda is 157,917 bp in length with 129 genes comprising 84 protein-coding genes, 37 tRNA genes and 8 rRNA ribosomal genes. The overall GC content of cp genome is 36.7%. A maximum likelihood phylogenetic analysis revealed that P. verecunda is sister to P. serrulata var. spontanea and P. maximowiczii

The Stress and Stiffness Analysis of Diaphragm

Diaphragm coupling with its simple structure, small size, high reliability, which can compensate for its input and output displacement deviation by its elastic deformation, is widely used in aerospace, marine, and chemical etc. This paper uses the ANSYS software and its APDL language to analysis the stress distribution when the diaphragm under the load of torque, axial deviation, centrifugal force, angular deviation and multiple loads. We find that the value of maximum stress usually appears in the outer or inner transition region and the axial deviation has a greater influence to the distribution of the stress. Based on above, we got three kinds of stiffness for axial, angular and torque, which the stiffness of diaphragm is nearly invariable. The results can be regard as an important reference for design and optimization of diaphragm coupling