Enhancing Cell Proliferation and Migration by MIR-Carbonyl Vibrational Coupling: Insights from Transcriptome Profiling

Cell proliferation and migration highly relate to normal tissue self-healing, therefore it is highly significant for artificial controlling. Recently, vibrational strong coupling between biomolecules and Mid-infrared (MIR) light photons has been successfully used to modify in vitro bioreactions, neuronal signaling and even animal behavior. However, the synergistic effects from molecules to cells remains unclear, and the regulation of MIR on cells needs to be explained from the molecular level. Herein, the proliferation rate and migration capacity of fibroblasts were increased by 156% and 162.5%, respectively, by vibratory coupling of 5.6 micrometers photons with carbonyl groups in biomolecules. Through transcriptome sequencing analysis, the regulatory mechanism of infrared light in 5.6 micrometers was explained from the level of signal pathway and cell components. 5.6 micrometers optical high power lasers can regulate cell function through vibrational strong coupling while minimizing photothermal damage. This work not only sheds light on the non-thermal effect on MIR light-based on wound healing, but also provides new evidence to future frequency medicine.Comment: 20 pages, 5 figure

Privacy-Preserving Face Recognition with Learnable Privacy Budgets in Frequency Domain

Face recognition technology has been used in many fields due to its high recognition accuracy, including the face unlocking of mobile devices, community access control systems, and city surveillance. As the current high accuracy is guaranteed by very deep network structures, facial images often need to be transmitted to third-party servers with high computational power for inference. However, facial images visually reveal the user's identity information. In this process, both untrusted service providers and malicious users can significantly increase the risk of a personal privacy breach. Current privacy-preserving approaches to face recognition are often accompanied by many side effects, such as a significant increase in inference time or a noticeable decrease in recognition accuracy. This paper proposes a privacy-preserving face recognition method using differential privacy in the frequency domain. Due to the utilization of differential privacy, it offers a guarantee of privacy in theory. Meanwhile, the loss of accuracy is very slight. This method first converts the original image to the frequency domain and removes the direct component termed DC. Then a privacy budget allocation method can be learned based on the loss of the back-end face recognition network within the differential privacy framework. Finally, it adds the corresponding noise to the frequency domain features. Our method performs very well with several classical face recognition test sets according to the extensive experiments.Comment: ECCV 2022; Code is available at https://github.com/Tencent/TFace/tree/master/recognition/tasks/dctd

Developing a class of dual atom materials for multifunctional catalytic reactions

Dual atom catalysts, bridging single atom and metal/alloy nanoparticle catalysts, offer more opportunities to enhance the kinetics and multifunctional performance of oxygen reduction/evolution and hydrogen evolution reactions. However, the rational design of efficient multifunctional dual atom catalysts remains a blind area and is challenging. In this study, we achieved controllable regulation from Co nanoparticles to CoN4 single atoms to Co2N5 dual atoms using an atomization and sintering strategy via an N-stripping and thermal-migrating process. More importantly, this strategy could be extended to the fabrication of 22 distinct dual atom catalysts. In particular, the Co2N5 dual atom with tailored spin states could achieve ideally balanced adsorption/desorption of intermediates, thus realizing superior multifunctional activity. In addition, it endows Zn-air batteries with long-term stability for 800 h, allows water splitting to continuously operate for 1000 h, and can enable solar-powered water splitting systems with uninterrupted large-scale hydrogen production throughout day and night. This universal and scalable strategy provides opportunities for the controlled design of efficient multifunctional dual atom catalysts in energy conversion technologies

Research and Design on IGBT Induction Heating Power Supply

AbstractThis paper introduces a new method, using PLL and fixed angle control, to track the converter's frequency automatically. After analyzing the work state of parallel inverter, a new control method using closed-loop rectifier control of voltage and current. The commonly-happening faults in the IGBT Medium Frequency Induction Heating Power Supply is analyzed, and the corresponding protective measures and protection circuits are designed. 100kw / 8kHz Parallel induction heating power is developed, and the designed control method is verified to be scientific and effective

GPR Image Noise Removal Using Grey Wolf Optimisation in the NSST Domain

Hyper-wavelet transforms, such as a non-subsampled shearlet transform (NSST), are one of the mainstream algorithms for removing random noise from ground-penetrating radar (GPR) images. Because GPR image noise is non-uniform, the use of a single fixed threshold for noisy coefficients in each sub-band of hyper-wavelet denoising algorithms is not appropriate. To overcome this problem, a novel NSST-based GPR image denoising grey wolf optimisation (GWO) algorithm is proposed. First, a time-varying threshold function based on the trend of noise changes in GPR images is proposed. Second, an edge area recognition and protection method based on the Canny algorithm is proposed. Finally, GWO is employed to select appropriate parameters for the time-varying threshold function and edge area protection method. The Natural Image Quality Evaluator is utilised as the optimisation index. The experiment results demonstrate that the proposed method provides excellent noise removal performance while protecting edge signals

Formation of Deposition Patterns Induced by the Evaporation of the Restricted Liquid

Evaporation-induced self-assembly of colloids or suspensions has received increasing attention. Given its critical applications in many fields of science and industry, we report deposition patterns constructed by the evaporation of the restricted aqueous suspension with polystyrene particles at different substrate temperatures and geometric container dimensions. With the temperature increases, the deposition patterns transition from honeycomb to multiring to island, which is attributed to the competition between the particle deposition rate U-p and the contact line velocity U-CL, and the dimension of the geometric container has an effect on the characteristics of patterns. In this paper, the formation of an ordered multiring pattern is mainly focused on as a result of U-p keeping up with U-CL such that the entire contact line can be pinned, that is, the periodic stick-slip motion of the contact line and the particle sedimentation. Moreover, based on the Onsager principle, we develop a theoretical model to reveal the physical mechanisms behind the multiring phenomena. The position and spacing of rings are measured, which shows that the theoretical prediction agrees well with experiments. We also find that the ring spacing decays exponentially from center to edge experimentally and theoretically. This may not only help us to understand the formation of the deposition patterns but also assist future design and control in practical applications. Evaporation-induced self-assembly of colloids or suspensions has received increasing attention. Given its critical applications in many fields of science and industry, we report deposition patterns constructed by the evaporation of the restricted aqueous suspension with polystyrene particles at different substrate temperatures and geometric container dimensions. With the temperature increases, the deposition patterns transition from honeycomb to multiring to island, which is attributed to the competition between the particle deposition rate U-P and the contact line velocity U-CL, and the dimension of the geometric container has an effect on the characteristics of patterns. In this paper, the formation of an ordered multiring pattern is mainly focused on as a result of U-P keeping up with U-CL such that the entire contact line can be pinned, that is, the periodic stick-slip motion of the contact line and the particle sedimentation. Moreover, based on the Onsager principle, we develop a theoretical model to reveal the physical mechanisms behind the multiring phenomena. The position and spacing of rings are measured, which shows that the theoretical prediction agrees well with experiments. We also find that the ring spacing decays exponentially from center to edge experimentally and theoretically. This may not only help us to understand the formation of the deposition patterns but also assist future design and control in practical applications

Unsupervised SAR Despeckling by Combining Online Speckle Generation and Unpaired Training

Speckle suppression is a crucial preliminary step for synthetic aperture radar (SAR) image processing. Supervised despeckling approaches trained on synthetic datasets usually perform poorly in practice due to the unavailability of clean SAR images. Besides, the spatial correlation of speckle is rarely considered in many methods based on the fully developed speckle assumption. In this article, we propose an unsupervised despeckling method to address these issues by combining online speckle generation and unpaired training. The method consists of two branches: the stop-gradient branch and the unpaired branch. First, the stop-gradient branch learns to generate the spatially correlated speckle. Then, the unpaired branch combines the generated speckle with the unpaired optical image to form pairs of training data for network parameter updates. More specifically, in order to generate the more realistic speckle in the stop-gradient branch, we design a speckle correction module with three SAR speckle priors: the threshold prior, the unit mean prior, and the correlation prior coupled with the weighted patch-shuffle. In the unpaired training, a hybrid loss function is employed, which takes spatial smoothness and detail protection into consideration. Afterward, we combine the stop-gradient branch with the unpaired branch by the Siamese network to achieve alternate optimization of speckle generation and speckle removal. Finally, the optimization process in our method is analyzed theoretically. Qualitative and quantitative experiments demonstrate that the proposed method is comparable to the supervised despeckling approaches on synthetic datasets and outperforms several state-of-the-art unsupervised methods on real SAR datasets