Optothermal Microbubble Assisted Manufacturing of Nanogap-Rich Structures for Active Chemical Sensing

Guiding analytes to the sensing area is an indispensable step in a sensing system. Most of the sensing systems apply a passive sensing method, which waits for the analytes to diffuse towards the sensor. However, passive sensing methods limit the detection of analytes to a picomolar range on micro/nanosensors for a practical time scale. Therefore, active sensing methods need to be used to improve the detection limit in which the analytes are forced to concentrate on the sensors. In this article, we have demonstrated the manufacturing of nanogap-rich structures for active chemical sensing. Nanogap-rich structures are manufactured from metallic nanoparticles through an optothermally generated microbubble (OGMB) which is a laser-induced micron-sized bubble. The OGMB induces a strong convective flow that helps to deposit metallic nanoparticles to form nanogap-rich structures on a solid surface. In addition, the OGMB is used to guide and concentrate analytes towards the nanogap-rich structures for the active sensing of analytes. An active sensing method can improve the detection limit of chemical substances by an order of magnitude compared to a passive sensing method. The microbubble assisted manufacturing of nanogap-rich structures together with an active analyte sensing method paves a new way for advanced chemical and bio-sensing applications

Medium-to-low-speed freight rail transport induced environmental vibration and analysis of the vibration isolation effect of building slope protection piles

The environmental vibration induced by freight rail transport has become an important type of environmental pollution. The environmental vibration caused by a running freight train near a typical medium- to low- speed railway in China and in the surrounding residential area is measured and analyzed. The test result shows that in the region adjacent to the railway, the weighed vibration acceleration level as a function of time (t) in the vertical direction (VLz) is lower than 80 dB, which meets the requirements of the standard (GB10070-88); however, in the surrounding residential area, the VLz is in the range of 58-74 dB, which is 0-4 dB higher than the specified limit during the day and 0-2 dB higher than the specified limit at night. For the isolation of environmental vibration induced by the freight train, a dynamic model of the vehicle and track and a finite element model of the railway, stratum and building are constructed to analyze the feasibility of modifying the slope protection piles outside of the building to make them function as vibration isolating piles, and the vibration isolation effects of such piles in a single row and double rows are compared with the case without piles. The simulation result shows that vibration isolation piles can attenuate the vibration level in front of and behind the piles: compared with the case without piles, the VLz can be reduced by 2-4 dB within 5 m behind the piles in a single row, and can be reduced by 4-10dB behind the piles in double rows, so the double-row setup is recommended for vibration isolation. It is suggested that for residential buildings which are close to the existing medium- to low- speed freight railway lines and for which other vibration attenuation measures are impractical, satisfactory vibration isolation effects may be achieved by simply increasing the number of rows of slope protection piles

Optimization and Structural Stability of Gold Nanoparticle–Antibody Bioconjugates

Gold nanoparticles (AuNPs) bound with biomolecules have emerged as suitable biosensors exploiting unique surface chemistries and optical properties. Many efforts have focused on antibody bioconjugation to AuNPs resulting in a sensitive bioconjugate to detect specific types of bacteria. Unfortunately, bacteria thrive under various harsh environments, and an understanding of bioconjugate stability is needed. Here, we show a method for optimizing Listeria monocytogenes polyclonal antibodies bioconjugation mechanisms to AuNPs via covalent binding at different pH values, from 2 to 11, and 2-(N-morpholino)ethanesulfonic acid (MES), 3-(N-morpholino)propanesulfonic acid, NaOH, HCl conditions. By fitting Lorentz curves to the amide I and II regions, we analyze the stability of the antibody secondary structure. This shows an increase in the apparent breakdown of the antibody secondary structure during bioconjugation as pH decreases from 7.9 to 2. We find variable adsorption efficiency, measured as the percentage of antibody adsorbed to the AuNP surface, from 17 to 27% as pH increases from 2 to 6 before decreasing to 8 and 13% at pH 7.9 and 11, respectively. Transmission electron microscopy (TEM) analysis reveals discrepancies between size and morphological changes due to the corona layer assembly from antibody binding to single nanoparticles versus aggregation or cluster self-assembly into large aggregates. The corona layer formation size increases from 3.9 to 5.1 nm from pH 2 to 6, at pH 7.9, there is incomplete corona formation, whereas at pH 11, there is a corona layer formed of 6.4 nm. These results indicate that the covalent binding process was more efficient at lower pH values; however, aggregation and deactivation of the antibodies were observed. We demonstrate that optimum bioconjugation condition was determined at pH 6 and MES buffer-type by indicators of covalent bonding and stability of the antibody secondary structure using Fourier transform-infrared, the morphological characteristics and corona layer formation using TEM, and low wavelength shifts of ultraviolet–visible after bioconjugation

Octopus: A Heterogeneous In-network Computing Accelerator Enabling Deep Learning for network

Deep learning (DL) for network models have achieved excellent performance in the field and are becoming a promising component in future intelligent network system. Programmable in-network computing device has great potential to deploy DL for network models, however, existing device cannot afford to run a DL model. The main challenges of data-plane supporting DL-based network models lie in computing power, task granularity, model generality and feature extracting. To address above problems, we propose Octopus: a heterogeneous in-network computing accelerator enabling DL for network models. A feature extractor is designed for fast and efficient feature extracting. Vector accelerator and systolic array work in a heterogeneous collaborative way, offering low-latency-highthroughput general computing ability for packet-and-flow-based tasks. Octopus also contains on-chip memory fabric for storage and connecting, and Risc-V core for global controlling. The proposed Octopus accelerator design is implemented on FPGA. Functionality and performance of Octopus are validated in several use-cases, achieving performance of 31Mpkt/s feature extracting, 207ns packet-based computing latency, and 90kflow/s flow-based computing throughput

MqsR/MqsA Toxin/Antitoxin System Regulates Persistence and Biofilm Formation in Pseudomonas putida KT2440

Bacterial toxin/antitoxin (TA) systems have received increasing attention due to their prevalence, diverse structures, and important physiological functions. In this study, we identified and characterized a type II TA system in a soil bacterium Pseudomonas putida KT2440. This TA system belongs to the MqsR/MqsA family. We found that PP_4205 (MqsR) greatly inhibits cell growth in P. putida KT2440 and Escherichia coli, the antitoxin PP_4204 (MqsA) neutralizes the toxicity of the toxin MqsR, and the two genes encoding them are co-transcribed. MqsR and MqsA interact with each other directly in vivo and MqsA is a negative regulator of the TA operon through binding to the promoter. Consistent with the MqsR/MqsA pair in E. coli, the binding of the toxin MqsR to MqsA inhibits the DNA binding ability of MqsA in P. putida KT2440. Disruption of the mqsA gene which induces mqsR expression increases persister cell formation 53-fold, while overexpressing mqsA which represses mqsR expression reduces persister cell formation 220-fold, suggesting an important role of MqsR in persistence in P. putida KT2440. Furthermore, both MqsR and MqsA promote biofilm formation. As a DNA binding protein, MqsA can also negatively regulate an ECF sigma factor AlgU and a universal stress protein PP_3288. Thus, we revealed an important regulatory role of MqsR/MqsA in persistence and biofilm formation in P. putida KT2440

Deep3DSketch+: Rapid 3D Modeling from Single Free-hand Sketches

The rapid development of AR/VR brings tremendous demands for 3D content. While the widely-used Computer-Aided Design (CAD) method requires a time-consuming and labor-intensive modeling process, sketch-based 3D modeling offers a potential solution as a natural form of computer-human interaction. However, the sparsity and ambiguity of sketches make it challenging to generate high-fidelity content reflecting creators' ideas. Precise drawing from multiple views or strategic step-by-step drawings is often required to tackle the challenge but is not friendly to novice users. In this work, we introduce a novel end-to-end approach, Deep3DSketch+, which performs 3D modeling using only a single free-hand sketch without inputting multiple sketches or view information. Specifically, we introduce a lightweight generation network for efficient inference in real-time and a structural-aware adversarial training approach with a Stroke Enhancement Module (SEM) to capture the structural information to facilitate learning of the realistic and fine-detailed shape structures for high-fidelity performance. Extensive experiments demonstrated the effectiveness of our approach with the state-of-the-art (SOTA) performance on both synthetic and real datasets