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With the continuous progress of The Times, the traditional paper graphic design has been unable to meet the needs of graphic design, through the use of computer aided technology in graphic design visual aesthetics, can effectively improve the aesthetic sense of the work. In this paper, first of all, the visual aesthetics of graphic design and graphic design of the construction type and computer aided technology analysis, at the same time, the specific application of computer aided technology in graphic design, for the reader’s reference.

AbstractThe NLRP3 inflammasome is a multi-molecular complex that acts as a molecular platform to mediate caspase-1 activation, leading to IL-1β/IL-18 maturation and release in cells stimulated by various pathogen-associated molecular patterns (PAMPs) or damage-associated molecular patterns (DAMPs). This inflammasome plays an important role in the innate immunity as its activation can further promote the occurrence of inflammation, enhance the ability of host to remove pathogens, and thus facilitate the repair of injured tissues. But if the inflammasome activation is dysregulated, it will cause the development of various inflammatory diseases and metabolic disorders. Therefore, under normal conditions, the activation of inflammasome is tightly regulated by various positive and negative signaling pathways to respond to the stimuli without damaging the host itself while maintaining homeostasis. In this review, we summarize recent advances in the major signaling pathways (including TLRs, MAPK, mTOR, autophagy, PKA, AMPK, and IFNR) that regulate NLRP3 inflammasome activation, providing a brief view of the molecular network that regulates this inflammasome as a theoretical basis for therapeutic intervention of NLRP3 dysregulation-related diseases.

Object recognition in the real-world requires handling long-tailed or even open-ended data. An ideal visual system needs to recognize the populated head visual concepts reliably and meanwhile efficiently learn about emerging new tail categories with a few training instances. Class-balanced many-shot learning and few-shot learning tackle one side of this problem, by either learning strong classifiers for head or learning to learn few-shot classifiers for the tail. In this paper, we investigate the problem of generalized few-shot learning (GFSL)—a model during the deployment is required to learn about tail categories with few shots and simultaneously classify the head classes. We propose the ClAssifier SynThesis LEarning (Castle), a learning framework that learns how to synthesize calibrated few-shot classifiers in addition to the multi-class classifiers of head classes with a shared neural dictionary, shedding light upon the inductive GFSL. Furthermore, we propose an adaptive version of Castle (aCastle) that adapts the head classifiers conditioned on the incoming tail training examples, yielding a framework that allows effective backward knowledge transfer. As a consequence, aCastle can handle GFSL with classes from heterogeneous domains effectively. Castle and aCastle demonstrate superior performances than existing GFSL algorithms and strong baselines on MiniImageNet as well as TieredImageNet datasets. More interestingly, they outperform previous state-of-the-art methods when evaluated with standard few-shot learning criteria.

A convenient, fast and selective water analysis method is highly desirable in industrial and detection processes. Here a robust microporous Zn-MOF (metal–organic framework, Zn(hpi2cf)(DMF)(H 2 O)) is assembled from a dual-emissive H 2 hpi2cf (5-(2-(5-fluoro-2-hydroxyphenyl)-4,5-bis(4-fluorophenyl)-1 H -imidazol-1-yl)isophthalic acid) ligand that exhibits characteristic excited state intramolecular proton transfer (ESIPT). This Zn-MOF contains amphipathic micropores (<3 Å) and undergoes extremely facile single-crystal-to-single-crystal transformation driven by reversible removal/uptake of coordinating water molecules simply stimulated by dry gas blowing or gentle heating at 70 °C, manifesting an excellent example of dynamic reversible coordination behaviour. The interconversion between the hydrated and dehydrated phases can turn the ligand ESIPT process on or off, resulting in sensitive two-colour photoluminescence switching over cycles. Therefore, this Zn-MOF represents an excellent PL water-sensing material, showing a fast (on the order of seconds) and highly selective response to water on a molecular level. Furthermore, paper or in situ grown ZnO-based sensing films have been fabricated and applied in humidity sensing (RH<1%), detection of traces of water (<0.05% v/v) in various organic solvents, thermal imaging and as a thermometer. Fast and sensitive detection of water molecules in organic solvents and gases remains an important challenge. Here, Pan and co-workers design a metal-organic framework capable of ultrafast and reversible water sensing by photoluminescence switching via an excited state intramolecular proton transfer mechanism.

This study aims to examine the correlation between four distinct Epstein-Barr virus (EBV) antibodies (EA-D, EBNA-1, VCA-p18, and ZEBRA) and the likelihood of developing prostate cancer (PCa) using the Mendelian Randomization (MR) technique. The primary objective is to determine whether a causal relationship exists between these EBV antibodies and prostate cancer. Genome-wide association study (GWAS) data for EBV antibodies were sourced from the UK Biobank cohort, and prostate cancer data were obtained from the PRACTICAL consortium, which includes 79148 cases and 61106 controls. Univariable Mendelian Randomization (MR) analysis was conducted to evaluate the associations, while reverse Mendelian Randomization was employed to assess causality. Additionally, Multivariable Mendelian Randomization analysis was performed to identify independent risk factors. Univariable MR analysis revealed significant associations between EBV EA-D (OR = 1.084, 95% CI = 1.012-1.160, IVW_ = 0.021) and EBNA-1 (OR = 1.086, 95% CI = 1.025-1.150, IVW_ = 0.005) antibodies and an increased risk of prostate cancer. Reverse MR analysis did not establish a causal relationship. Multivariable MR analysis identified the EBV EBNA-1 antibody as an independent risk factor for prostate cancer (OR = 1.095, 95% CI = 1.042-1.151, IVW_ = 0.00036). The study highlights the association between EBV antibody levels, particularly EBNA-1, and prostate cancer risk, suggesting EBNA-1 as an independent risk factor. Future research is needed to elucidate the biological pathways linking EBV antibody levels to prostate cancer. These insights could be instrumental in developing targeted prevention strategies and therapeutic interventions for prostate cancer.

Luminescence of porous coordination polymers (PCPs) or metal–organic frameworks (MOFs) is sensitive to the type and concentration of chemical species in the surrounding environment, because these materials combine the advantages of the highly regular porous structures and various luminescence mechanisms, as well as diversified host‐guest interactions. In the past few years, luminescent MOFs have attracted more and more attention for chemical sensing of gas‐phase analytes, including common gases and vapors of solids/liquids. While liquid‐phase and gas‐phase luminescence sensing by MOFs share similar mechanisms such as host‐guest electron and/or energy transfer, exiplex formation, and guest‐perturbing of excited‐state energy level and radiation pathways, via various types of host‐guest interactions, gas‐phase sensing has its unique advantages and challenges, such as easy utilization of encapsulated guest luminophores and difficulty for accurate measurement of the intensity change. This review summarizes recent progresses by using luminescent MOFs as reusable sensing materials for detection of gases and vapors of solids/liquids especially for O2, highlighting various strategies for improving the sensitivity, selectivity, stability, and accuracy, reducing the materials cost, and developing related devices. Luminescent metal–organic frameworks are promising for chemical sensing. Compared with liquid‐phase sensing, gas‐phase sensing has its unique advantages and challenges. This review summarizes recent representative works on luminescent MOFs for non‐destructive detection of gas‐phase analytes.

White spot syndrome virus (WSSV) is an enveloped double-stranded DNA virus that has had a serious influence on worldwide shrimp farming in the last 30 years. We have demonstrated that WSSV hijacks host autophagy and lipid metabolism for reproduction in kuruma shrimp ( Marsupenaeus japonicus ). These findings revealed the mechanism by which WSSV exploits host machinery for its infection and provided serial targets for WSSV prevention and control in shrimp farming. Mindin is a secreted extracellular matrix protein that is involved in regulating cellular events through interacting with integrin. Studies have demonstrated its role in host immunity, including phagocytosis, cell migration, and cytokine production. However, the function of Mindin in the host-virus interaction is largely unknown. In the present study, we report that Mindin facilitates virus infection by activating lipid utilization in an arthropod, kuruma shrimp ( Marsupenaeus japonicus ). Shrimp Mindin facilitates white spot syndrome virus infection by facilitating viral entry and replication. By activating autophagy, Mindin induces lipid droplet consumption, the hydrolysis of triglycerides into free fatty acids, and ATP production, ultimately providing energy for virus infection. Moreover, integrin is essential for Mindin-mediated autophagy and lipid utilization. Therefore, by revealing the mechanism by which Mindin facilitates virus infection through regulating lipid metabolism, the present study reveals the significance of Mindin in the host-virus interaction. IMPORTANCE White spot syndrome virus (WSSV) is an enveloped double-stranded DNA virus that has had a serious influence on worldwide shrimp farming in the last 30 years. We have demonstrated that WSSV hijacks host autophagy and lipid metabolism for reproduction in kuruma shrimp ( Marsupenaeus japonicus ). These findings revealed the mechanism by which WSSV exploits host machinery for its infection and provided serial targets for WSSV prevention and control in shrimp farming.

Plants use nitrate and ammonium as major nitrogen (N) sources, each affecting root development through different mechanisms. However, the exact signaling pathways involved in root development are poorly understood. Here, we show that, in Arabidopsis thaliana , either disruption of the cell wall-localized ferroxidase LPR2 or a decrease in iron supplementation efficiently alleviates the growth inhibition of primary roots in response to NH 4 + as the N source. Further study revealed that, compared with nitrate, ammonium led to excess iron accumulation in the apoplast of phloem in an LPR2-dependent manner. Such an aberrant iron accumulation subsequently causes massive callose deposition in the phloem from a resulting burst of reactive oxygen species, which impairs the function of the phloem. Therefore, ammonium attenuates primary root development by insufficiently allocating sucrose to the growth zone. Our results link phloem iron to root morphology in response to environmental cues. Ammonium affects plant root development through different mechanisms than nitrate. Here, the authors show that the Arabidopsis cell wall-localized ferroxidase LPR2 is required to attenuate root growth in response to ammonium.

Considering the data collection and labeling cost in real-world applications, training a model with limited examples is an essential problem in machine learning, visual recognition, etc. Directly training a model on such few-shot learning (FSL) tasks falls into the over-fitting dilemma, which would turn to an effective task-level inductive bias as a key supervision. By treating the few-shot task as an entirety, extracting task-level pattern, and learning a task-agnostic model initialization, the model-agnostic meta-learning (MAML) framework enables the applications of various models on the FSL tasks. Given a training set with a few examples, MAML optimizes a model via fixed gradient descent steps from an initial point chosen beforehand. Although this general framework possesses empirically satisfactory results, its initialization neglects the task-specific characteristics and aggravates the computational burden as well. In this manuscript, we propose our AdaptiVely InitiAlized Task OptimizeR (Aviator) approach for few-shot learning, which incorporates task context into the determination of the model initialization. This task-specific initialization facilitates the model optimization process so that it obtains high-quality model solutions efficiently. To this end, we decouple the model and apply a set transformation over the training set to determine the initial top-layer classifier. Re-parameterization of the first-order gradient descent approximation promotes the gradient back-propagation. Experiments on synthetic and benchmark data sets validate that our Aviator approach achieves the state-of-the-art performance, and visualization results demonstrate the task-adaptive features of our proposed Aviator method.

Terahertz (THz) near-field microscopy retains the advantages of THz radiation and realizes sub-wavelength imaging, which enables applications in fundamental research and industrial fields. In most THz near-field microscopies, the sample surface must be approached by a THz detector or source, which restricts the sample choice. Here, a technique was developed based on an air-plasma dynamic aperture, where two mutually perpendicular air-plasmas overlapped to form a cross-filament above a sample surface that modulated an incident THz beam. THz imaging with quasi sub-wavelength resolution (approximately λ/2, where λ is the wavelength of the THz beam) was thus observed without approaching the sample with any devices. Damage to the sample by the air-plasmas was avoided. Near-field imaging of four different materials was achieved, including metallic, semiconductor, plastic, and greasy samples. The resolution characteristics of the near-field system were investigated with experiment and theory. The advantages of the technique are expected to accelerate the advancement of THz microscopy.A THz near-field technique was proposed based on an air-plasma dynamic aperture, which can achieve sub-wavelength THz imaging without approaching the sample with any devices.