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Silent speech recognition (SSR) allows users to speak to the device without making a sound, avoiding being overheard or disturbing others. Compared to the video-based approach, wireless signal-based SSR can work when the user is wearing a mask and has fewer privacy concerns. However, previous wireless-based systems are still far from well-studied, e.g. they are only evaluated in corpus with highly limited size, making them only feasible for interaction with dozens of deterministic commands. In this paper, we present mSilent, a millimeter-wave (mmWave) based SSR system that can work in the general corpus containing thousands of daily conversation sentences. With the strong recognition capability, mSilent not only supports the more complex interaction with assistants, but also enables more general applications in daily life such as communication and input. To extract fine-grained articulatory features, we build a signal processing pipeline that uses a clustering-selection algorithm to separate articulatory gestures and generates a multi-scale detrended spectrogram (MSDS). To handle the complexity of the general corpus, we design an end-to-end deep neural network that consists of a multi-branch convolutional front-end and a Transformer-based sequence-to-sequence back-end. We collect a general corpus dataset of 1,000 daily conversation sentences that contains 21K samples of bi-modality data (mmWave and video). Our evaluation shows that mSilent achieves a 9.5% average word error rate (WER) at a distance of 1.5m, which is comparable to the performance of the state-of-the-art video-based approach. We also explore deploying mSilent in two typical scenarios of text entry and in-car assistant, and the less than 6% average WER demonstrates the potential of mSilent in general daily applications.

The excavation of non-circular tunnels at shallow depths is becoming increasingly common because of the need to efficiently utilize excavation spaces. However, the stress concentration is likely much greater around shallow tunnels than deep ones. This study provides an analytical solution of stresses around non-circular tunnels at shallow depths by combining the Schwartz alternating method with complex variable theory. The analytical solutions are verified by good agreement between the analytical and FEM numerical results. A parametric study is performed to investigate stress concentrations around elliptical and square tunnels and the effect of tunnels’ buried depth. The proposed analytical solutions provide great value to the conceptual understanding of the mechanical behaviour of non-circular tunnels, which are shallowly excavated in rock or medium to stiff clay, and to the verification of numerical models.

Depletion of PIG3 sensitized NSCLC cells to docetaxel. Forty eight hrs following transfection with PIG3 and control siRNAs, H460 cells were exposed to various concentrations of docetaxel. Cell proliferation was determined by CCK8 assay 48 h post treatment. The data are expressed as the mean and standard deviations from three independent experiments (** P

Loss of PIG3 inhibites cell proliferation and leads to increased outcome of misalignment chromosomes in H460 NSCLC cells. a Western blot analysis demonstrating the efficacy of PIG3 siRNA #1 in H460 cells at 48 h post-transfection. b 3× 103 cells were seeded in 96-well plates at day 0, and CCK8 assay was used to determine cell proliferation rates at indicated days (1, 2, 3, 4 and5 days). Absorbance values at 450 nm were normalized by the value measured on day 1 (* P

Overexpression PIG3 promotes NSCLC cells proliferation and increases resistance of NSCLC cells to docetaxel. a Western blot analysis demonstrating the level of PIG3 in PIG3-overexpressed and control H1299 cells. b 3× 103 cells were seeded in 96-well plates at day 0, and CCK8 assay was used to determine cell proliferation rates at indicated days (1, 2, 3, 4 and 5 days). Absorbance values at 450 nm were normalized by the value measured on day 1 (* P

The localization of PIG3 in the cells detected by immunofluorescent staining. A549 cells were treated or untreated with 4Gy Îł ray irradiation. One hour post irradiation, cells were fixed and stained using anti-PIG3, KAP-1 and phosphorylated H2AX antibody. (PPTX 1444Â kb)

Protein adsorption on nanoparticles is closely associated with the physicochemical properties of particles, in particular, their surface properties. We synthesized two batches of polyacrylic acid-coated nanoparticles under almost identical conditions except for the heating duration and found differences in the head-group structure of the polyacrylic acid. The structure change was confirmed by NMR and MS. The two batches of particles had varied binding affinities to a selected group of proteins. Computational work confirmed that the head group of the polymer on the surface of a nanoparticle could directly interact with a protein, and small structural changes in the head group were sufficient to result in a significant difference in the free energy of binding. Our results demonstrate that protein adsorption is so sensitive to the surface properties of particles that it can reveal even small variations in the structure of a nanoparticle surface ligand, and should be useful for quick assessment of nanoparticle properties.

For the first time, the possible binding site of nanoparticles on protein was revealed by cross-linking chemistry coupled with mass spectrometry. The peptides located very close to the poly(acrylic acid) (PAA)-coated Fe(3)O(4) nanoparticles (NPs) during interaction with human serum albumin (HSA) were cross-linked to the surface of NPs. Following protease digestion, the attached peptides were cleaved off the particle surface and identified by matrix-assisted laser desorption/ionization-time-of-flight-mass spectrometry (MALDI-TOF-MS). The peptides were found to be part of the so-called drug binding site 2 of HSA; and the competitive binding to HSA between the corresponding drug, ibuprofen, and the NPs was observed. Our results demonstrated that cross-linking chemistry coupled with MS was a quick and simple method for locating the possible binding sites of NPs on protein. Information on NP-protein binding interface will benefit the study of how the interactions are governed by the physicochemical properties of NPs, for guiding the design of functional bionano constructs. It can also help to predict the biological consequence of protein adsorption on NPs, for obtaining more knowledge on nanotoxicity.

Understanding nanoparticle-protein interaction could help in promoting applications of nanoparticles in the biomedical fields and reducing/preventing possible adverse effects to the biological systems caused by nanoparticles. Quantitative measurement of the biophysical parameters of nanoparticle-protein interaction will improve such understanding, which could be conveniently performed by capillary electrophoresis (CE) as demonstrated in the present study. Two interaction situations were identified. Stable nanoparticle-protein complexes were resolved from the free nanoparticles and the proteins by capillary zone electrophoresis (CZE). Transient complexes with fast association/dissociation rates showed distinct mobility change from the free nanoparticles in affinity capillary electrophoresis (ACE). Interactions of bovine serum albumin (BSA) with the Fe(3)O(4) nanoparticles (average diameters of 8 and 10 nm) and with the Au nanoparticles (average diameters of 5 and 10 nm) displayed slow and fast binding kinetics, respectively. Using the Hill equation, we could calculate the dissociation constants (K(D)) and cooperativity coefficients (n). Impacts on nanoparticle-protein interaction from the physicochemical properties of nanoparticles and the incubation buffer were evaluated on the basis of the K(D) and n values to interpret the interaction driving forces. Our study demonstrated the high simplicity and flexibility of CE in probing the interaction of proteins with diverse particles. The separation power of CE should also facilitate studies of the multicomponent interaction systems for investigating how adsorption onto nanoparticles could affect the protein-protein or protein-small molecule interactions.