24 research outputs found
WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing
Self-supervised learning (SSL) achieves great success in speech recognition,
while limited exploration has been attempted for other speech processing tasks.
As speech signal contains multi-faceted information including speaker identity,
paralinguistics, spoken content, etc., learning universal representations for
all speech tasks is challenging. To tackle the problem, we propose a new
pre-trained model, WavLM, to solve full-stack downstream speech tasks. WavLM
jointly learns masked speech prediction and denoising in pre-training. By this
means, WavLM does not only keep the speech content modeling capability by the
masked speech prediction, but also improves the potential to non-ASR tasks by
the speech denoising. In addition, WavLM employs gated relative position bias
for the Transformer structure to better capture the sequence ordering of input
speech. We also scale up the training dataset from 60k hours to 94k hours.
WavLM Large achieves state-of-the-art performance on the SUPERB benchmark, and
brings significant improvements for various speech processing tasks on their
representative benchmarks. The code and pre-trained models are available at
https://aka.ms/wavlm.Comment: Submitted to the Journal of Selected Topics in Signal Processing
(JSTSP
Multicolor-Encoded Reconfigurable DNA Nanostructures Enable Multiplexed Sensing of Intracellular MicroRNAs in Living Cells
Despite
the widespread utilization of gold nanoparticles and graphene
for in vivo applications, complex steps for the preparation and functionalization
of these nanomaterials are commonly required. In addition, the cytotoxicity
of such materials is currently still under debate. In this work, by
taking the significant advantages of DNA in terms of biocompatibility,
nontoxicity, and controllability as building blocks for DNA nanostructures,
we describe the construction of a reconfigurable, multicolor-encoded
DNA nanostructure for multiplexed monitoring of intracellular microRNAs
(miRNAs) in living cells. The DNA nanostructure nanoprobes containing
two fluorescently quenched hairpins can be obtained by simple thermal
annealing of four ssDNA oligonucleotides. The presence of the target
miRNAs can unfold the hairpin structures and recover fluorescent emissions
at distinct wavelengths to achieve multiplexed detection of miRNAs.
Importantly, the DNA nanostructure nanoprobes exhibit significantly
improved stability over conventional DNA molecular beacon probes in
cell lysates and can steadily enter cells to realize simultaneous
detection of two types of intracellular miRNAs. The demonstration
of the self-assembled DNA nanostructures for intracellular sensing
thus offers great potential application of these nanoprobes for imaging,
drug delivery and cancer therapy in vivo
Experimental Study of Influence of Different Parameters on Flow Field Structures Around an Airfoil Covered with Rough Ice
Rough ice can change the leading edge of airfoil and affect the aerodynamic characteristics. Studying the influence of rough ice caused by supercooled water droplets can provide reference for anti-icing design of aircrafts. A detailed experimental study was conducted to measure the flow field structure of an airfoil model with rough ice in a low-speed wind tunnel by using particle image velocimetry. The parameters include Reynolds number, roughness of rough ice, and angle of attack. The results show that with the increase of Reynolds number, the range and value of spanwise vorticity at the wake of the airfoil with ice increased, while the normalized Reynolds stress decreased slightly. The presence of rough ice reduced the airflow velocity near the airfoil, increased the vorticity of wake, and seriously affected the shear stress distribution. Compared with the clean airfoil, the rough ice caused the air flow to separate earlier and the velocity in the separation bubble fluctuated more violently
Ultrasensitive Assay for Telomerase Activity via Self-Enhanced Electrochemiluminescent Ruthenium Complex Doped MetalâOrganic Frameworks with High Emission Efficiency
Here,
an ultrasensitive âoffâonâ electrochemiluminescence
(ECL) biosensor was proposed for the determination of telomerase activity
by using a self-enhanced ruthenium polyethylenimine (RuâPEI)
complex doped zeolitic imidazolate framework-8 (RuâPEI@ZIF-8)
with high ECL efficiency as an ECL indicator and an enzyme-assisted
DNA cycle amplification strategy. The RuâPEI@ZIF-8 nanocomposites
were synthesized by self-enhanced RuâPEI complex doping during
the growth of zeolitic imidazolate framework-8 (ZIF-8), which presented
high ECL efficiency and excellent stability. Furthermore, owing to
the porosity of RuâPEI@ZIF-8, the self-enhanced RuâPEI
complex in the outer layer and inner layer of self-enhanced RuâPEI@ZIF-8
could be excited by electrons causing the utilization ratio of the
self-enhanced ECL materials to be remarkably increased. To further
improve the sensitivity of the proposed biosensor, the telomerase
activity signal was converted into the trigger DNA signal which was
further amplified by an enzyme-assisted DNA recycleâamplification
strategy. The proposed ECL biosensor presented great performance for
telomerase activity detection from 5 Ă 10<sup>1</sup> to 10<sup>6</sup> Hela cells with a detection limit of 11 cells. Moreover,
this method was applied in the detection of telomerase activity from
cancer cells treated with an anticancer drug, which indicated the
proposed method held potential application value as an evaluation
tool in anticancer drug screening
Tetraphenylethylene-doped covalent organic frameworks as a highly efficient aggregation-induced electrochemiluminescence emitter for ultrasensitive miRNA-21 analysis
MicroRNAs (miRNAs) as a well-known kind of cancer marker are closely associated with the formation and metastasis of tumors. Here, a novel tetraphenylethylene (TPE)-doped covalent organic frameworks (TPE-COFs) with strong aggregation-induced electrochemiluminescence (AIECL) response was synthesized and introduced to construct an ultrasensitive biosensor for the detection of miRNA-21. The strong aggregation-induced emission (AIE) response was obtained because the molecular motion of TPE was restricted by COFs which had the porosity and highly ordered topological structure. Meanwhile, the porous structure of COFs allowed TPE to react with electrochemiluminescence (ECL) coreactants more effectively. Furthermore, COFs significantly improved the electron transport efficiency of the entire ECL system. All of these endowed the TPE-COFs with superior AIECL performance. Then, a TPE-COFs based ECL resonance energy transfer (ECL-RET) system was constructed for ultrasensitive miRNA-21 biosensing with differential signal readout. The proposed assays exhibited excellent sensitivity with a wide dynamic range from 10 aM to 1Â pM and a low detection limit of 2.18 aM. Therefore, these indicated that doping TPE in COFs was a creative way to develop functional COFs and provided an effective way for enhancing AIECL. Furthermore, this work boarded the application of AIECL in analytical chemistry
Ultrasensitive Cytosensor Based on Self-Enhanced Electrochemiluminescent Ruthenium-Silica Composite Nanoparticles for Efficient Drug Screening with Cell Apoptosis Monitoring
The self-enhanced electrochemiluminescence
(ECL) with high sensitivity
could be an effective method for anticancer drug screening with cell
apoptosis monitoring. Here we reported an ultrasensitive ECL cytosensor
for cell apoptosis monitoring by using self-enhanced electrochemiluminescent
rutheniumâsilica composite nanoparticles (RuâNâSiNPs)
labeled annexin V as signal probes. The RuâNâSiNPs were
first synthesized through simple hydrolysis of a novel precursor containing
luminescent and intracoreactant groups in one molecule, which presented
higher emission efficiency and enhanced ECL intensity due to the shorter
electron-transfer path and less energy loss. Moreover, the as-proposed
ECL cytosensor was successfully used to investigate efficiency of
paclitaxel toward MDA-MB-231 breast cancer cell in the range from
1 nM to 200 nM with a detection limit of 0.3 nM and a correlation
coefficient of 0.9917. The improved accuracy and excellent dynamic
range revealed the potential applications in biomolecules diagnostics
and cells detections, especially in living and complex systems
Table1_Application of yeast in plant-derived aroma formation from cigar filler leaves.PDF
Introduction: There are various degrees of defects of cigar filler leaves after air drying.Methods: In order to improve the quality and plant-derived aroma content of cigar filler leaves, nine aroma-producing yeasts were applied in artificially solid-state fermentation of cigar filler leaves in this study. The differences with various yeasts application were compared by chemical composition and GC-MS analysis.Results and discussion: The results showed that 120 volatile components were identified and quantified in cigar filler leaves after fermentation, including aldehydes (25 types), alcohols (24 types), ketones (20 types), esters (11 types), hydrocarbons (12 types), acids (4 types) and other substances (23 types). Based on the analysis of odor activity value (OAV), the OVA of fruity and floral aroma components were higher. It was found that floral aroma are the representative aroma types of cigar filler leaves treated with Clavispora lusitaniae, Cyberlindera fabianii, Saccharomycosis fibuligera and Zygosaccharomyces bailii R6. After being inoculated with Hanseniaspora uvarum J1, Hanseniaspora uvarum J4 and Pichia pastoris P3, the OAV of fruity aroma in cigar filler leaves was the highest, followed by tobacco aroma and woody aroma. The correlation between volatile components of cigar filler leaves with different yeasts was revealed after PCA analysis. It was concluded that the quality of cigar filler leaves was improved, and cigar filler leaves fermented with different yeasts showed different flavor.</p