Model-free adaptive nonlinear control of the absorption refrigeration system

This work is supported by the National Natural Science Foundation of China (Grant Nos. 61773282, 61873181, and 61922062).Peer reviewedPostprin

Foundational Certification of Code Transformations Using Automatic Differentiation

Automatic Differentiation (AD) is concerned with the semantics augmentation of an input program representing a function to form a transformed program that computes the function's derivatives. To ensure the correctness  of the AD transformed code, particularly for safety critical applications, we aim at certifying the algebraic manipulations at the heart of the AD process. We have considered a WHILE-language and have shown how such proofs can be constructed by using an appropriate relational Hoare logic.In particular, we have shown how such inference rules can be constructed for both the forward and reverse mode AD by using an abductive logical reasoning

PgtE Enzyme of Salmonella enterica Shares the Similar Biological Roles to Plasminogen Activator (Pla) in Interacting With DEC-205 (CD205), and Enhancing Host Dissemination and Infectivity by Yersinia pestis

Yersinia pestis, the cause of plague, is a newly evolved Gram-negative bacterium. Through the acquisition of the plasminogen activator (Pla), Y. pestis gained the means to rapidly disseminate throughout its mammalian hosts. It was suggested that Y. pestis utilizes Pla to interact with the DEC-205 (CD205) receptor on antigen-presenting cells (APCs) to initiate host dissemination and infection. However, the evolutionary origin of Pla has not been fully elucidated. The PgtE enzyme of Salmonella enterica, involved in host dissemination, shows sequence similarity with the Y. pestis Pla. In this study, we demonstrated that both Escherichia coli K-12 and Y. pestis bacteria expressing the PgtE-protein were able to interact with primary alveolar macrophages and DEC-205-transfected CHO cells. The interaction between PgtE-expressing bacteria and DEC-205-expressing transfectants could be inhibited by the application of an anti-DEC-205 antibody. Moreover, PgtE-expressing Y. pestis partially re-gained the ability to promote host dissemination and infection. In conclusion, the DEC-205-PgtE interaction plays a role in promoting the dissemination and infection of Y. pestis, suggesting that Pla and the PgtE of S. enterica might share a common evolutionary origin.Peer reviewe

Optimal Design and Operation of Multi-Period Water Supply Network with Multiple Water Sources

A water supply network is an essential part of industrial and urban water systems. The water intake in a conventional water supply network varies periodically over time, depending on the amount of available water resources and the demand at water sinks or water-using units. This paper establishes a super-structural mathematical model for the optimal design and operation of a multi-period water supply network with multiple water sources. It considers the flow rate fluctuation of raw water availability and the demand of water sinks during different periods. The influence of multi-period demand variation on technology and the capacity selection of desalination water stations is examined, which affects the overall cost of the water supply network. The operating cost penalty factor is introduced, which quantitatively clarifies how the network operating status influences the operating costs. The comparison results of three scenarios considering with and without multi-period variation of water demand verify the validity of the proposed model, i.e., for a municipal water price of 4 CNY·t−1 and penalty factor of 0.3, one reverse osmosis desalination unit of capacity 800 t·h−1 is selected. However, in the multi-period case, two reverse osmosis desalination units with capacities of 500 t·h−1 and 300 t·h−1 are selected. In both cases, the operating costs are different because of the different operating status of the network. The work can guide the design and operation of industrial and urban water supply networks

DINet: Deformation Inpainting Network for Realistic Face Visually Dubbing on High Resolution Video

For few-shot learning, it is still a critical challenge to realize photo-realistic face visually dubbing on high-resolution videos. Previous works fail to generate high-fidelity dubbing results. To address the above problem, this paper proposes a Deformation Inpainting Network (DINet) for high-resolution face visually dubbing. Different from previous works relying on multiple up-sample layers to directly generate pixels from latent embeddings, DINet performs spatial deformation on feature maps of reference images to better preserve high-frequency textural details. Specifically, DINet consists of one deformation part and one inpainting part. In the first part, five reference facial images adaptively perform spatial deformation to create deformed feature maps encoding mouth shapes at each frame, in order to align with input driving audio and also the head poses of input source images. In the second part, to produce face visually dubbing, a feature decoder is responsible for adaptively incorporating mouth movements from the deformed feature maps and other attributes (i.e., head pose and upper facial expression) from the source feature maps together. Finally, DINet achieves face visually dubbing with rich textural details. We conduct qualitative and quantitative comparisons to validate our DINet on high-resolution videos. The experimental results show that our method outperforms state-of-the-art works

DPC-MSGATNet : dual-path chain multi-scale gated axial-transformer network for four-chamber view segmentation in fetal echocardiography

Echocardiography is essential in evaluating fetal cardiac anatomical structures and functions when clinicians conduct early treatment and screening for congenital heart defects, a common and intricate fetal malformation. Nevertheless, the prenatal detection rate of fetal CHD remains low since the peculiarities of fetal cardiac structures and the variousness of fetal CHD. Precisely segmenting four cardiac chambers can assist clinicians in analyzing cardiac morphology and further facilitate CHD diagnosis. Hence, we design a dual-path chain multi-scale gated axial-transformer network (DPC-MSGATNet) that simultaneously models global dependencies and local visual cues for fetal ultrasound (US) four-chamber (FC) views and further accurately segments four chambers. Our DPC-MSGATNet includes a global and a local branch that simultaneously operates on an entire FC view and image patches to learn multi-scale representations. We design a plug-and-play module, Interactive dual-path chain gated axial-transformer (IDPCGAT), to enhance the interactions between global and local branches. In IDPCGAT, the multi-scale representations from the two branches can complement each other, capturing the same region’s salient features and suppressing feature responses to maintain only the activations associated with specific targets. Extensive experiments demonstrate that the DPC-MSGATNet exceeds seven state-of-the-art convolution- and transformer-based methods by a large margin in terms of F1 and IoU scores on our fetal FC view dataset, achieving a F1 score of 96.87% and an IoU score of 93.99%. The codes and datasets can be available at https://github.comQiaoSiBo/DPC-MSGATNet

Low-dose imaging denoising with one pair of noisy images

Low-dose imaging techniques have many important applications in diverse fields, from biological engineering to materials science. Samples can be protected from phototoxicity or radiation-induced damage using low-dose illumination. However, imaging under a low-dose condition is dominated by Poisson noise and additive Gaussian noise, which seriously affects the imaging quality, such as signal-to-noise ratio, contrast, and resolution. In this work, we demonstrate a low-dose imaging denoising method that incorporates the noise statistical model into a deep neural network. One pair of noisy images is used instead of clear target labels and the parameters of the network are optimized by the noise statistical model. The proposed method is evaluated using simulation data of the optical microscope, and scanning transmission electron microscope under different low-dose illumination conditions. In order to capture two noisy measurements of the same information in a dynamic process, we built an optical microscope that is capable of capturing a pair of images with independent and identically distributed noises in one shot. A biological dynamic process under low-dose condition imaging is performed and reconstructed with the proposed method. We experimentally demonstrate that the proposed method is effective on an optical microscope, fluorescence microscope, and scanning transmission electron microscope, and show that the reconstructed images are improved in terms of signal-to-noise ratio and spatial resolution. We believe that the proposed method could be applied to a wide range of low-dose imaging systems from biological to material science.Published versionThis work was funded by National Key Research and Development Program of China (2021YFB3602604); National Natural Science Foundation of China (61975205,62075221, 62131011); Fusion Foundation of Research and Education of CAS; University of Chinese Academy of Sciences; Fundamental Research Funds for the Central Universities; Funded Project of Hebei Province Innovation Capability Improvement Plan, China (20540302D)

The Protection of C-O Bond of Pine Lignin in Different Organic Solvent Systems

The methods of extraction and degradation of lignin from biomass are very important for obtaining high value-added chemical precursors. In this paper, pine wood powder was selected as the feedstock to investigate the effect of different organic solvent systems (ethanol, ethylene glycol, 1, 4-butanediol and acetone) on the lignin extraction using different radio of H2SO4 and acetic acid. The extraction yields were calculated, the solvent lignin structure was analyzed by SEM, Elemental Analyzer, GPC, FT-IR, HSQC and the organosolv lignin was depolymerized over NaOH and Pd/C in ethanol. The results showed that the molecular weight of all lignin extracted from biomass by different organic solvents were lower than 2000 g mol(-1). Among the organic solvents, acetic acid and glycol could react with the gamma and & x251; position of the beta-O-4 bond in lignin, which protect the C-O bond during the extraction treatment. The analysis of depolymerization products suggested that the ethylene glycol had the best ability of retaining the structures of lignin and dissolution. About 17.74 wt. % aromatic compounds were obtained from the ethylene glycol lignin in 2 MPa H-2 at 240 degrees C, which were mainly phenyl alcohol compounds. Ethylene glycol lignin could give more aromatic hydrocarbon compounds and phenols than the other two kinds of lignin. Ethylene glycol and 1,4-butanediol was also found in the depolymerization product respectively. The protection of the C-O bond offers effective strategies for directional depolymerization design

Non-Uniform Synthetic Aperture Radiometer Image Reconstruction Based on Deep Convolutional Neural Network

When observing the Earth from space, the synthetic aperture radiometer antenna array is sometimes set as a non-uniform array. In non-uniform synthetic aperture radiometer image reconstruction, the existing brightness temperature image reconstruction methods include the grid method and array factor forming (AFF) method. However, when using traditional methods for imaging, errors are usually introduced or some prior information is required. In this article, we propose a new IASR imaging method with deep convolution neural network (CNN). The frequency domain information is extracted through multiple convolutional layers, global pooling layers, and fully connected layers to achieve non-uniform synthetic aperture radiometer imaging. Through extensive numerical experiments, we demonstrate the performance of the proposed imaging method. Compared to traditional imaging methods such as the grid method and AFF method, the proposed method has advantages in image quality, computational efficiency, and noise suppression

WTAP-mediated m6A modification of FRZB triggers the inflammatory response via the Wnt signaling pathway in osteoarthritis

Abstract Osteoarthritis (OA) is the most common form of arthritis. However, the exact pathogenesis remains unclear. Emerging evidence shows that N6-methyladenosine (m6A) modification may have an important role in OA pathogenesis. This study aimed to investigate the role of m6A writers and the underlying mechanisms in osteoarthritic cartilage. Among m6A methyltransferases, Wilms tumor 1-associated protein (WTAP) expression most significantly differed in clinical osteoarthritic cartilage. WTAP regulated extracellular matrix (ECM) degradation, inflammation and antioxidation in human chondrocytes. Mechanistically, the m6A modification and relative downstream targets in osteoarthritic cartilage were assessed by methylated RNA immunoprecipitation sequencing (MeRIP-seq) and RNA sequencing, which indicated that the expression of frizzled-related protein (FRZB), a secreted Wnt antagonist, was abnormally decreased and accompanied by high m6A modification in osteoarthritic cartilage. In vitro dysregulated WTAP had positive effects on β-catenin expression by targeting FRZB, which finally contributed to the cartilage injury phenotype in chondrocytes. Intra-articular injection of adeno-associated virus-WTAP alleviated OA progression in a mouse model, while this protective effect could be reversed by the application of a Wnt/β-catenin activator. In summary, this study revealed that WTAP-dependent RNA m6A modification contributed to Wnt/β-catenin pathway activation and OA progression through post-transcriptional regulation of FRZB mRNA, thus providing a potentially effective therapeutic strategy for OA treatment