Topology combined machine learning for consonant recognition

In artificial-intelligence-aided signal processing, existing deep learning models often exhibit a black-box structure, and their validity and comprehensibility remain elusive. The integration of topological methods, despite its relatively nascent application, serves a dual purpose of making models more interpretable as well as extracting structural information from time-dependent data for smarter learning. Here, we provide a transparent and broadly applicable methodology, TopCap, to capture the most salient topological features inherent in time series for machine learning. Rooted in high-dimensional ambient spaces, TopCap is capable of capturing features rarely detected in datasets with low intrinsic dimensionality. Applying time-delay embedding and persistent homology, we obtain descriptors which encapsulate information such as the vibration of a time series, in terms of its variability of frequency, amplitude, and average line, demonstrated with simulated data. This information is then vectorised and fed into multiple machine learning algorithms such as k-nearest neighbours and support vector machine. Notably, in classifying voiced and voiceless consonants, TopCap achieves an accuracy exceeding 96% and is geared towards designing topological convolutional layers for deep learning of speech and audio signals

AutoConv: Automatically Generating Information-seeking Conversations with Large Language Models

Information-seeking conversation, which aims to help users gather information through conversation, has achieved great progress in recent years. However, the research is still stymied by the scarcity of training data. To alleviate this problem, we propose AutoConv for synthetic conversation generation, which takes advantage of the few-shot learning ability and generation capacity of large language models (LLM). Specifically, we formulate the conversation generation problem as a language modeling task, then finetune an LLM with a few human conversations to capture the characteristics of the information-seeking process and use it for generating synthetic conversations with high quality. Experimental results on two frequently-used datasets verify that AutoConv has substantial improvements over strong baselines and alleviates the dependence on human annotation. In addition, we also provide several analysis studies to promote future research.Comment: Accepted to ACL 2023 Main Conference (Short

A High-Phosphorus-Content Polyphosphonate with Combined Phosphorus Structures for Flame Retardant PET

A high-phosphorus-content polyphosphonate (PBDA), containing two phosphorus-based structures: phosphaphenanthrene (DOPO) and phenyl phosphonate groups, was synthesized and used in flame retardant polyethylene terephthalate (PET). Good self-extinguishing property (high UL 94 grade and LOI value), superior flame retardancy (lower heat/smoke release), and high quality retention (high carbon residue) were endowed to PET by PBDA. When 10 wt% PDBA was added, the peak heat release rate (pHRR), total heat release (THR), and total smoke rate (TSR) of PDBA/PET were found to be significantly reduced by 80%, 60.5%, and 21%, respectively, compared to the pure PET, and the LOI value jumped from 20.5% for pure PET to 28.7% with a UL-94 V-0 rating. The flame-retardant mode of action in PET was verified by thermogravimetric analysis-Fourier transform infrared (TGA-FTIR), pyrolysis gas chromatography/mass spectrometry (Py-GC/MS), real-time FTIR, and scanning electron microscopy (SEM). Phosphaphenanthrene and phosphonate moieties in PDBA decomposed in sequence during heating, continuously releasing and keeping high-content PO· and PO2· radicals with a quenching effect and simultaneously promoting the formation of viscous crosslinked char layers causing a high barrier effect. PDBA mainly acted in the gas phase but the condensed-phase flame retardant function was also considerable

Development of ciprofloxacin-loaded contact lenses using fluorous chemistry

In this work, we developed a simple method to load drugs into commercially available contact lenses utilizing fluorous chemistry. We demonstrated this method using model compounds including fluorous-tagged fluorescein and antibiotic ciprofloxacin. We showed that fluorous interactions facilitated the loading of model molecules into fluorocarbon-containing contact lenses, and that the release profiles exhibited sustained release. Contact lenses loaded with fluorous-tagged ciprofloxacin exhibited antimicrobial activity against Pseudomonas aeruginosa in vitro, while no cytotoxicity towards human corneal epithelial cells was observed. To mimic the tear turnover, we designed a porcine eye infection model under flow conditions. Significantly, the modified lenses also exhibited antimicrobial efficacy against Pseudomonas aeruginosa in the ex vivo infection model. Overall, utilizing fluorous chemistry, we can construct a drug delivery system that exhibits high drug loading capacity, sustained drug release, and robust biological activity

Hypoxia-Inducible Factor-1α: A Potential Factor for the Enhancement of Osseointegration between Dental Implants and Tissue-Engineered Bone

Introduction: Tissue-engineered bones are widely utilized to protect healthy tissue, reduce pain, and increase the success rate of dental implants. one of the most challenging obstacles lies in obtaining effective os-seointegration between dental implants and tissue-engineered structures. Deficiencies in vascularization, osteogenic factors, oxygen, and other nutrients inside the tissue-engineered bone during the early stages following implantation all inhibit effective osseointe-gration. Oxygen is required for aerobic metabolism in bone and blood vessel tissues, but oxygen levels inside tissue-engineered bone are not suf-ficient for cell proliferation. HIF-1α is a pivotal regulator of hypoxic and ischemic vascular responses, driving transcriptional activation of hundreds of genes involved in vascular reactivity, angiogenesis, arteriogenesis, and osteogenesis.The hypothesis: Hypoxia-Inducible Factor-1α seems a potential factor for the enhancement of osseointegration between dental implants and tissue-engineered bone.Evaluation of the hypothesis: Enhancement of HIF-1α protein expression is recognized as the most promising approach for angiogenesis, because it can induce multiple angiogenic targets in a coordinated manner. Therefore, it will be a novel potential therapeutic methods targeting HIF-1α expression to enhance osseointegration be-tween dental implants and tissue-engineered bone

The Characterization of Laser-Induced Particles Generated from Aluminum Alloy in High Power Laser Facility

Aerosol particle contamination in high-power laser facilities has become a major cause of internal optical component damage resistance and service life reduction. In general, contaminating particles primarily originate from stray light; therefore, it is crucial to investigate the mechanism and dynamics of the dynamic contaminating particle generation to control the cleanliness level. In this study, corresponding research was conducted on experiments and theory. We investigated the particle generation and surface composition modification under the action of a laser. We employed various surface analytical methods to identify the possible variations in the aluminum alloy surface during laser irradiations. A theoretical model for particle ejection from aluminum alloy surfaces was established by taking the adhesion force and laser cleaning force (due to thermal expansion) into account. The results show that the threshold energies for contamination particle generation and damage are around 0.1 and 0.2 J/cm2, respectively. Subsurface impurities are the primary source of particles, and particle adhesion density is related to surface roughness. Pollution particle generation and splashing processes include temperature increases, phase changes, impact diffusion, and adhesion. The results provide a reference for the normal operation of high-energy laser systems. The results also suggest that the laser irradiation pretreatment of aluminum alloy surfaces is essential to improve the cleanliness level