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Functional polymeric materials with electrical bi-stable states possess significant potential for high-density data storage due to their nanoscale memory site, three-dimensional-stacking ability and intrinsic flexibility. Aromatic polyimides bearing donor-acceptor (D-A) skeleton could form charge transfer complex (CTC) under electrical field, leading to their feasibility as memory materials. Three novel porphyrinated polyimides DATPP-DSDA, Zn-DATPP-DSDA and Mn-DATPP-DSDA were designed and synthesized for information memory applications. Metal ions with different electron configurations at 3d orbital have a determining influence on memory behaviors of polyimides: nonvolatile write-once-read-many-times memory (WORM) for DATPP-DSDA, volatile static random access memory (SRAM) for Zn-DATPP-DSDA, but no memory performance for Mn-DATPP-DSDA. By comparing the contribution of orbital transition and hole-electron distribution of charge-transfer excited states, roles of metal ions in regulating memory types were discussed. Molecular simulation results indicate that the Zn ion could play a bridge role in paving the route for excited electrons from a D to an A, while a trap role for the Mn ion in hindering this process. This study proves the feasibility of the strategy for modulating the memory behaviors of porphyrinated polyimides by varying the central metal ion and provides the exact effects of various metal ions on regulating charge transfer processes.

The coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has precipitated a global health crisis of unprecedented proportions. Because of its severe impact, multiple COVID-19 vaccines are being rapidly developed, approved and manufactured. Among them, mRNA vaccines are considered as ideal candidates with special advantages to meet this challenge. However, some serious adverse events have been reported after their application, significantly increasing concerns about the safety and efficacy of the vaccines and doubts about the necessity of vaccination. Although several fertility societies have announced that COVID-19 mRNA vaccines are unlikely to affect fertility, there is no denying that the current evidence is very limited, which is one of the reasons for vaccine hesitancy in the population, especially in pregnant women. Herein, we provide an in-depth discussion on the involvement of the male and female reproductive systems during SARS-CoV-2 infection or after vaccination. On one hand, despite the low risk of infection in the male reproductive system or fetus, COVID-19 could pose an enormous threat to human reproductive health. On the other hand, our review indicates that both men and women, especially pregnant women, have no fertility problems or increased adverse pregnancy outcomes after vaccination, and, in particular, the benefits of maternal antibodies transferred through the placenta outweigh any known or potential risks. Thus, in the case of the rapid spread of COVID-19, although further research is still required, especially a larger population-based longitudinal study, it is obviously a wise option to be vaccinated instead of suffering from serious adverse symptoms of virus infection.

The coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has currently spread worldwide, leading to high morbidity and mortality. As the putative receptor of SARS-CoV-2, angiotensin-converting enzyme 2 (ACE2) is widely distributed in various tissues and organs of the human body. Simultaneously, ACE2 acts as the physiological counterbalance of ACE providing homeostatic regulation of circulating angiotensin II levels. Given that some ACE2 variants are known to cause an increase in the ligand-receptor affinity, their roles in acquisition, progression and severity of COVID-19 disease have aroused widespread concerns. Therefore, we summarized the latest literature and explored how ACE2 variants and epigenetic factors influence an individual’s susceptibility to SARS-CoV-2 infection and disease outcome in aspects of ethnicity, gender and age. Meanwhile, the possible mechanisms for these phenomena were discussed. Notably, recombinant human ACE2 and ACE2-derived peptides may have special benefits for combating SARS-CoV-2 variants and further studies are warranted to confirm their effects in later stages of the disease process. As the uncertainty regarding the severity and transmissibility of disease rises, a more in-depth understanding of the host genetics and functional characteristics of ACE2 variants will not only help explain individual clinical differences of the disease, but also contribute to providing effective measures to develop solutions and manage future outbreaks of SARS-CoV-2.

Background: Papillary thyroid carcinoma (PTC) accounts for the majority of thyroid cancer and affects a large number of individuals. The pathogenesis of PTC has not been completely elucidated thus far. Metabolic reprogramming is a common feature in tumours. Our previous research revealed the reprogramming of lipid metabolism in PTC. Further studies on lipid metabolism reprogramming may help elucidate the pathogenesis of PTC. Methods: Clinical samples of PTC and para-tumour tissue were analysed using lipidomic, proteomic, and metabolomic approaches. A multi-omics integrative strategy was adopted to identify the important pathways in PTC. The findings were further confirmed using western blotting, tissue microarray, and bioinformatics. Findings: The differentially expressed substances included 146 lipids, 2975 proteins, and 217 metabolites in PTC samples. Multi-omics data and the results of integrated analysis revealed that the three steps of fatty acid metabolism (hydrolysis, transportation, and oxidation) were significantly enhanced in PTC. The key enzymes in the three steps, namely LPL, FATP2, and CPT1A, respectively, were overexpressed. Moreover, their expression was strongly associated with the TNM stage, lymph node metastasis, and PTC prognosis. In addition, the levels of several types of phospholipids and sphingolipids increased significantly in PTC. Interpretation: Our data suggested that enhanced fatty acid metabolism supplied additional energy and substrates for tumour growth, invasion, and metastasis in PTC. This may help elucidate the mechanism underlying PTC pathogenesis and identify the potential therapeutic targets for PTC. Funding Information: Work in the authors' laboratory is supported by grants from National Natural Science Foundation of China (No. 81702647, NO. 81972819), Taishan Scholar Foundation of Shandong Province (No. tspd20181201), Collaborative Innovation Center of Technology and Equipment for Biological Diagnosis and Therapy in Universities of Shandong, Natural Science Foundation of Shandong Province (No. ZR201702190483, No. ZR2020YQ57), Key Technology Research and Development Program of Shandong (No. 2016GSF201161). Declaration of Interests: The authors declare no competing interests. Ethics Approval Statement: This prospective study was approved by the institutional ethical committee of Qilu Hospital of Shandong University, Shandong Province, China. All the specimens were collected in the Qilu Hospital of Shandong University. The participants provided written informed consent for the use of thyroid tissue specimens for research.

Face recognition system performance is affected by face image quality. In this paper, a face matching score, instead of a subjective perceptual score, is used as the image quality label to build a face image quality database; therefore, the ground truth quality achieved high accordance with the recognition performance. The database contains five common practical application distortion types for 19 people and three to five collection scenes for each. In addition, a face image quality algorithm based on a local gradient is proposed to judge the image quality. Making use of the fact that face landmarks can locate contour areas that have rich gradient information, a new mask based on human visual characteristics is designed to evaluate the image quality by using the local gradient information of landmark neighborhoods; this method was used to control for the influence of the image content and background. Our algorithm does not rely on a large amount of training data, and it has low computational complexity. The experimental results show that the algorithm is effective and efficient for evaluating image quality and improving the performance of face recognition systems.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death worldwide. Lipogenesis has been considered as a critical player in HCC initiation and progression. However, the underlying mechanism is still not fully understood. METHODS: ZHX2 overexpression and knockdown were introduced into HCC cell lines. BODIPY staining and D-Glucose- 13C6 labeled lipid mass spectrometry were involved to estimate lipogenesis in HCC cell lines. Colony formation and cell proliferation assays were used to determine HCC development. Hepatocytes specific Zhx2 knockout mice (Zhx2-KOhep) were included to induce spontaneous liver tumor. qRT-PCR, western blotting and dual luciferase assays were used to detect gene regulation. FINDINGS: Ectopic expression of ZHX2 significantly inhibited de novo lipogenesis in HCC cells and decreased expression of FASN, ACL, ACC and SCD1. In accordance, ZHX2 was negatively associated with SREBP1c, the master regulator of de novo lipogenesis, in HCC cell lines and human specimens. Further studies demonstrated that ZHX2 inhibited de novo lipogenesis and consequent HCC progression via repression of SREBP1c. Furthermore, treatment with SREBP1c inhibitor, fatostatin, dampened the spontaneous tumor formation in Zhx2-KOhep mice. Mechanically, ZHX2 transcriptionally increased expression of miR-24-3p, which targets on SREBP1c. INTERPRETATION: ZHX2 inhibits de novo lipogenesis in HCC cells by down-regulating the expression of SREBP1c via miR-24-3p, and further inhibits the development of HCC. These new findings may provide a new strategy for the treatment of HCC. FUNDING STATEMENT: This work was supported by grants from the National Science Foundation of China (Key project 81830017 and 81902443,81702647,81902051,81972819), Taishan Scholarship (No.tspd20181201), National Key Research and Development Program (2018YFE0126500), National Science Foundation for Distinguished Young Scholars of China (81425012), Shandong Provincial Key Innovation project (No.2018FYJH0503), Collaborative Innovation Center of Technology and Equipment for Biological Diagnosis and Therapy in Universities of Shandong, Key Research and Development Program of Shandong (2019GSF108238) . DECLARATION OF INTERESTS: All authors declare no potential conflicts of interest. ETHICS APPROVAL STATEMENT: The Medical Ethics Committee of Shandong University approved the use of human specimens in accordance with the Helsinki Declaration. All mice were housed under conditions free of specific pathogens and euthanized according to regulations established by the Animal Care Committee of Shandong University.

In this paper, an efficient method for single image dehazing is proposed based on haze density estimation. We provide two forms of haze density estimation in different color spaces, which are called scene-based haze density estimation in HSV color space and pixel-based haze density estimation in RGB color space. The attenuation model of pixel-level transmission is established based on the two haze density estimations by an exponential function. Guided filtering is applied to smooth the transmission map and maintain the local edges. Global atmospheric light is obtained adaptively by smoothed transmission. A series of experiments on different types of hazy images are implemented, and the results reveal that the proposed method can obtain high-quality haze-free images along with abundant details, high color fidelity, and few halo artifacts.

Self-compacting concrete could be poured under the action of gravity, without vibration, and has good working performance. It could reduce the noise during production, and reduce the labor of workers. In recent years, more and more scholars begin to study the concrete. In this paper, ABAQUS finite element software is used to simulate the self-compacted concrete prestressed T-beam under different parameters, using the self-compacting concrete constitutive model. The cooling method is used to simulate the prestress applying, and the performance of beam is analyzed. It is found that the bearing capacity of the member improves with the increasing of the reinforcement ratio, the prestress increases the stiffness of the member, and reduces the deflection of the member, but the ductility is reducing with the increasing of prestress.

The emergence of mobile augmented reality children’s puzzle games conforms to the development of the information age. One augmented reality game named “Baby Running” was researched and developed, based on Unity engine and the Vuforia, which improves the interaction between the game and the player, and exercises the child’s concentration and reaction. The paper will discuss the game planning, game system design, key technologies, game testing, and the system’s conclusion and some future directions.

BACKGROUND The aim of this study was to investigate the value of the mean platelet volume to platelet count (MPV/P) ratio for predicting in-hospital and long-term cardiac mortality in older non-ST elevation-acute coronary syndrome (NSTE-ACS) patients after primary percutaneous coronary intervention (PCI). METHODS We retrospectively reviewed 452 older NSTE-ACS patients who received primary PCI. The patients were divided into two groups based on MPV/P ratios: high MPV/P group (N.=150) defined as a value in the third tertile (>0.056628) and low MPV/P group (N.=302) in the lower two tertiles (≤0.056628). Clinical outcomes included non-fatal reinfarction, heart failure, and cardiac mortality. RESULTS Multivariate analyses showed that high MPV/P and MPV values were independent predictors of cardiac mortality. The in-hospital cardiac mortality of the high MPV/P group was higher than the low MPV/P group (1.3% vs. 14.7%, P

This paper present an efficient real time rectangle speed limit sign recognition system. The system design considers computation load and hardware resources for driver assistant system. First multi-scale overlapping LBP features are used to train AdaBoost cascade classifier for speed limit sign object detection. Then a simple linear prediction method is used to do tracking task. At the recognition stage, a novel efficient algorithm is used to correct rotation angle, and then integral image based adaptive threshold algorithm is adopted to segment the speed limit number. The clustering based binary tree of linear support vector machine is adopted for classification task. The system is tested on real road scene video sequences. It achieves 98.3% recognition rate with approximate 16fps frame rate on laptop