A robust lower order mixed finite element method for a strain gradient elasticity model

A robust nonconforming mixed finite element method is developed for a strain gradient elasticity (SGE) model. In two and three dimensional cases, a lower order $C^0$-continuous $H^2$-nonconforming finite element is constructed for the displacement field through enriching the quadratic Lagrange element with bubble functions. This together with the linear Lagrange element is exploited to discretize a mixed formulation of the SGE model. The robust discrete inf-sup condition is established. The sharp and uniform error estimates with respect to both the small size parameter and the Lam\'{e} coefficient are achieved, which is also verified by numerical results. In addition, the uniform regularity of the SGE model is derived under two reasonable assumptions.Comment: 25 page

The Value of CT Enhancement Degree in Prognosis of Pancreatic Cancer

Objective: To explore the prognostic value of CT enhancement degree of pancreatic cancer in pancreatic cancer. Methods: From January 2019 to January 2022, 50 patients with pancreatic cancer who came to our hospital for pathological confirmation were selected. Prior to surgery, use multiphase CT of the pancreas to complete enhanced scans. After surgery, the patient's survival period, clinical treatment effectiveness, and imaging data are used as research variables. In the scanning diagnosis, it is necessary to collect the patient's age, gender, tumor location and size, differentiation process, CT value, etc. Create a mathematical model based on the collected data and complete the experimental research work. Results: Univariate analysis showed that the prognosis of pancreatic cancer patients with higher enhancement degree in each stage (P<0.05 in each stage) was better. Multivariate analysis showed that tumor differentiation (P=0.0118), TNM staging (P=0.004), and portal vein enhancement (P<0.001) can be independent predictors of patient prognosis. Conclusion: The lower the CT enhancement degree of pancreatic cancer, the worse the prognosis

Automatic Liver Segmentation Using an Adversarial Image-to-Image Network

Automatic liver segmentation in 3D medical images is essential in many clinical applications, such as pathological diagnosis of hepatic diseases, surgical planning, and postoperative assessment. However, it is still a very challenging task due to the complex background, fuzzy boundary, and various appearance of liver. In this paper, we propose an automatic and efficient algorithm to segment liver from 3D CT volumes. A deep image-to-image network (DI2IN) is first deployed to generate the liver segmentation, employing a convolutional encoder-decoder architecture combined with multi-level feature concatenation and deep supervision. Then an adversarial network is utilized during training process to discriminate the output of DI2IN from ground truth, which further boosts the performance of DI2IN. The proposed method is trained on an annotated dataset of 1000 CT volumes with various different scanning protocols (e.g., contrast and non-contrast, various resolution and position) and large variations in populations (e.g., ages and pathology). Our approach outperforms the state-of-the-art solutions in terms of segmentation accuracy and computing efficiency.Comment: Accepted by MICCAI 201

Improved Federated Learning for Handling Long-tail Words

Automatic speech recognition (ASR) machine learning models are deployed on client devices that include speech interfaces. ASR models can benefit from continuous learning and adaptation to large-scale changes, e.g., as new words are added to the vocabulary. While federated learning can be utilized to enable continuous learning for ASR models in a privacy preserving manner, the trained model can perform poorly on rarely occurring, long-tail words if the distribution of data used to train the model is skewed and does not adequately represent long-tail words. This disclosure describes federated learning techniques to improve ASR model quality when interpreting long-tail words given an imbalanced data distribution. Two different approaches - probabilistic sampling and client loss weighting - are described herein. In probabilistic sampling, the federated clients that include fewer long-tail words are less likely to be selected during training. In client loss weighting, incorrect predictions on long-tail words are more heavily penalized than for other words

Research Progress of Superhydrophobic Materials in the Field of Anti-/De-Icing and Their Preparation: A Review

Accumulated ice has brought much damage to engineering and people’s lives. The accumulation of ice can affect the flight safety of aircraft and lead to the failure of cables and power generation blades; it can even cause damage to human life. Traditional anti-icing and de-icing strategies have many disadvantages such as high energy consumption, low efficiency, or pollution of the environment. Therefore, inspired by animal communities, researchers have developed new passive anti-icing materials such as superhydrophobic material. In this paper, the solid surface wetting phenomenon and superhydrophobic anti-icing and de-icing mechanism were introduced. The methods of fabrication of superhydrophobic surfaces were summarized. The research progress of wear-resistant superhydrophobic coatings, self-healing/self-repairing superhydrophobic coatings, photothermal superhydrophobic coatings, and electrothermal superhydrophobic coatings in the field of anti-icing and de-icing was reviewed. The current problems and challenges were analyzed, and the development trend of superhydrophobic materials was also prospected in the field of anti-icing and de-icing. The practicality of current superhydrophobic materials should continue to be explored in depth

Controlling electron motion with attosecond precision by shaped femtosecond intense laser pulse

We propose the scheme of temporal double-slit interferometer to precisely measure the electric field of shaped intense femtosecond laser pulse directly, and apply it to control the electron tunneling wave packets in attosecond precision. By manipulating the spectra phase of the input femtosecond pulse in frequency domain, one single pulse is split into two sub-pulses whose waveform can be precisely controlled by adjusting the spectra phase. When the shaped pulse interacts with atoms, the two sub-pulses are analogous to the Young's double-slit in time domain. The interference pattern in the photoelectron momentum distribution can be used to precisely retrieve the peak electric field and the time delay between two sub-pulses. Based on the precise characterization of the shaped pulse, we demonstrate that the sub-cycle dynamics of electron can be controlled with attosecond precision. The above scheme is proved to be feasible by both quantum-trajectory Monte Carlo simulations and numerical solutions of three-dimensional time-dependent Schr\"{o}dinger equation.Comment: 10 pages,4 figure

Electron dynamics in laser-driven atoms near the continuum threshold

Strong-field ionization and Rydberg-state excitation (RSE) near the continuum threshold exhibit two phenomena that have attracted a lot of recent attention: the low-energy structure (LES) just above and frustrated tunneling ionization just below the threshold. The former becomes apparent for longer laser wavelengths, while the latter has been especially investigated in the near infrared; both have been treated as separate phenomena so far. Here we present a unified perspective based on electron trajectories, which emphasizes the very important role of the electron-ion Coulomb interaction as expected in this energy region. Namely, those trajectories that generate the LES can also be recaptured into a Rydberg state. The coherent superposition of the contributions of such trajectories with different travel times (each generating one of the various LES peaks) causes an oscillation in the intensity dependence of the RSE yield, which is especially noticeable for longer wavelengths. The theory is illustrated by RSE experiments at 1800 nm, which agree very well with the theory with respect to position and period of the oscillation. The wavelength scaling of the RSE oscillation is also discussed. Our work establishes a solid relationship between processes below and above the threshold and sheds new light on atomic dynamics driven by intense laser fields in this critical energy region