Field-Induced Formation and Growth of Pillars on Films of Bisphenol-A-Polycarbonate

An electric field is used to construct pillars on films of bisphenol-A-polycarbonate (BPAPC) between two parallel electrodes. Both the size and density of the pillars are dependent on the film thickness. For the same experimental conditions, thicker films will lead to the formation of pillars of larger sizes and smaller densities. The time dependence of the average diameter of the pillars is found to be a linear function of the square root of the difference between the annealing time and incubation time. The temperature dependence of the temporal evolution of the pillars follows the Arrhenius relation with an activation enthalpy of 121.5 kJ mol−1. Increasing the film thickness and electric field intensity leads to the decrease of the characteristic wavenumber for the surface patterns at the same annealing temperature. There is a larger change in the film thickness for a thinner film than that of a thicker film after the formation of pillars under the same experimental conditions

Efficient XAI Techniques: A Taxonomic Survey

Recently, there has been a growing demand for the deployment of Explainable Artificial Intelligence (XAI) algorithms in real-world applications. However, traditional XAI methods typically suffer from a high computational complexity problem, which discourages the deployment of real-time systems to meet the time-demanding requirements of real-world scenarios. Although many approaches have been proposed to improve the efficiency of XAI methods, a comprehensive understanding of the achievements and challenges is still needed. To this end, in this paper we provide a review of efficient XAI. Specifically, we categorize existing techniques of XAI acceleration into efficient non-amortized and efficient amortized methods. The efficient non-amortized methods focus on data-centric or model-centric acceleration upon each individual instance. In contrast, amortized methods focus on learning a unified distribution of model explanations, following the predictive, generative, or reinforcement frameworks, to rapidly derive multiple model explanations. We also analyze the limitations of an efficient XAI pipeline from the perspectives of the training phase, the deployment phase, and the use scenarios. Finally, we summarize the challenges of deploying XAI acceleration methods to real-world scenarios, overcoming the trade-off between faithfulness and efficiency, and the selection of different acceleration methods.Comment: 15 pages, 3 figure

Virus-like particle secretion and genotype-dependent immunogenicity of dengue virus serotype 2 DNA vaccine

Dengue virus (DENV), composed of four distinct serotypes, is the most important and rapidly emerging arthropod-borne pathogen and imposes substantial economic and public health burdens. We constructed candidate vaccines containing the DNA of five of the genotypes of dengue virus serotype 2 (DENV-2) and evaluated the immunogenicity, the neutralizing (Nt) activity of the elicited antibodies, and the protective efficacy elicited in mice immunized with the vaccine candidates. We observed a significant correlation between the level of in vitro virus-like particle secretion, the elicited antibody response, and the protective efficacy of the vaccines containing the DNA of the different DENV genotypes in immunized mice. However, higher total IgG antibody levels did not always translate into higher Nt antibodies against homologous and heterologous viruses. We also found that, in contrast to previous reports, more than 50% of total IgG targeted ectodomain III (EDIII) of the E protein, and a substantial fraction of this population was interdomain highly neutralizing flavivirus subgroup-cross-reactive antibodies, such as monoclonal antibody 1B7-5. In addition, the lack of a critical epitope(s) in the Sylvatic genotype virus recognized by interdomain antibodies could be the major cause of the poor protection of mice vaccinated with the Asian 1 genotype vaccine (pVD2-Asian 1) from lethal challenge with virus of the Sylvatic genotype. In conclusion, although the pVD2-Asian 1 vaccine was immunogenic, elicited sufficient titers of Nt antibodies against all DENV-2 genotypes, and provided 100% protection against challenge with virus of the homologous Asian 1 genotype and virus of the heterologous Cosmopolitan genotype, it is critical to monitor the potential emergence of Sylvatic genotype viruses, since vaccine candidates under development may not protect vaccinated humans from these viruses

Methods for in vitro CRISPR/CasRx-Mediated RNA Editing

Specific changes in the genome have been accomplished by the revolutionary gene-editing tool known as clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) system. The advent of programmable RNA editing CRISPR/Cas nucleases has made this gene-editing tool safer and more precise. Specifically, CasRx, a family member of the Cas13d family, has shown great therapeutic potential. Here, we describe the in vitro methods of utilizing this powerful RNA editing platform and determine the RNA editing efficiencies for CasRx with different forms of guide RNAs (also known as gRNA or sgRNA)

Physion++: Evaluating Physical Scene Understanding that Requires Online Inference of Different Physical Properties

General physical scene understanding requires more than simply localizing and recognizing objects -- it requires knowledge that objects can have different latent properties (e.g., mass or elasticity), and that those properties affect the outcome of physical events. While there has been great progress in physical and video prediction models in recent years, benchmarks to test their performance typically do not require an understanding that objects have individual physical properties, or at best test only those properties that are directly observable (e.g., size or color). This work proposes a novel dataset and benchmark, termed Physion++, that rigorously evaluates visual physical prediction in artificial systems under circumstances where those predictions rely on accurate estimates of the latent physical properties of objects in the scene. Specifically, we test scenarios where accurate prediction relies on estimates of properties such as mass, friction, elasticity, and deformability, and where the values of those properties can only be inferred by observing how objects move and interact with other objects or fluids. We evaluate the performance of a number of state-of-the-art prediction models that span a variety of levels of learning vs. built-in knowledge, and compare that performance to a set of human predictions. We find that models that have been trained using standard regimes and datasets do not spontaneously learn to make inferences about latent properties, but also that models that encode objectness and physical states tend to make better predictions. However, there is still a huge gap between all models and human performance, and all models' predictions correlate poorly with those made by humans, suggesting that no state-of-the-art model is learning to make physical predictions in a human-like way. Project page: https://dingmyu.github.io/physion_v2

DiscoverPath: A Knowledge Refinement and Retrieval System for Interdisciplinarity on Biomedical Research

The exponential growth in scholarly publications necessitates advanced tools for efficient article retrieval, especially in interdisciplinary fields where diverse terminologies are used to describe similar research. Traditional keyword-based search engines often fall short in assisting users who may not be familiar with specific terminologies. To address this, we present a knowledge graph-based paper search engine for biomedical research to enhance the user experience in discovering relevant queries and articles. The system, dubbed DiscoverPath, employs Named Entity Recognition (NER) and part-of-speech (POS) tagging to extract terminologies and relationships from article abstracts to create a KG. To reduce information overload, DiscoverPath presents users with a focused subgraph containing the queried entity and its neighboring nodes and incorporates a query recommendation system, enabling users to iteratively refine their queries. The system is equipped with an accessible Graphical User Interface that provides an intuitive visualization of the KG, query recommendations, and detailed article information, enabling efficient article retrieval, thus fostering interdisciplinary knowledge exploration. DiscoverPath is open-sourced at https://github.com/ynchuang/DiscoverPath

Evaluation of the Kinetic Change of the Immunogenicity of Dengue-2 DNA Vaccine in Mice Administered by Different Administration Routes

A plasmid DNA vaccine is able to induce both humoral and cellular immune responses; however, the kinetic change of the Th1/Th2 response, antibody avidity, cytokine secretion, and neutralization activity after different priming and boosting strategies have not been evaluated. A plasmid DNA, designated pCBD2 and previously shown to efficiently induce an immune response very similar to that by a wild type virus, was evaluated kinetically in this study. Our results suggest that a DNA vaccine delivered by the gene gun (gg) route produced higher and longer DENV-2-specific anti-body titers than those induced through the intramuscular (im) route. Although the gg group induced a Th2 response and im delivery induced a Th1 response, priming by gg delivery, followed by a boosting by im delivery, did not shift the immune response from a Th2 to Th1 response. Furthermore, the antibody avidity (AI) measured by ELISA demon-strated a gradual increase of AI from low (AI range from 6.8% - 9.6%) on day 42 to high (AI value > 30) on day 119 in all but the gene-gun immunization group, in which an AI value of 23 was observed. Although there was lower avidity in the gg group, the mice sera from all three groups of mice demonstrated significant neutralization activity. This is the first report about the kinetics of immunogenicity of a DNA vaccine through different administration strategies, which suggests that gene gun delivery of a DNA vaccine can induce an immune response containing both neutralizing and nonneutralizing antibodies at high titers important for neutralization

Breast Cancer Immunohistochemical Image Generation: a Benchmark Dataset and Challenge Review

For invasive breast cancer, immunohistochemical (IHC) techniques are often used to detect the expression level of human epidermal growth factor receptor-2 (HER2) in breast tissue to formulate a precise treatment plan. From the perspective of saving manpower, material and time costs, directly generating IHC-stained images from hematoxylin and eosin (H&E) stained images is a valuable research direction. Therefore, we held the breast cancer immunohistochemical image generation challenge, aiming to explore novel ideas of deep learning technology in pathological image generation and promote research in this field. The challenge provided registered H&E and IHC-stained image pairs, and participants were required to use these images to train a model that can directly generate IHC-stained images from corresponding H&E-stained images. We selected and reviewed the five highest-ranking methods based on their PSNR and SSIM metrics, while also providing overviews of the corresponding pipelines and implementations. In this paper, we further analyze the current limitations in the field of breast cancer immunohistochemical image generation and forecast the future development of this field. We hope that the released dataset and the challenge will inspire more scholars to jointly study higher-quality IHC-stained image generation.Comment: 13 pages, 11 figures, 2table

Matched sizes of activating and inhibitory receptor/ligand pairs are required for optimal signal integration by human Natural Killer cells

It has been suggested that receptor-ligand complexes segregate or co-localise within immune synapses according to their size, and this is important for receptor signaling. Here, we set out to test the importance of receptor-ligand complex dimensions for immune surveillance of target cells by human Natural Killer (NK) cells. NK cell activation is regulated by integrating signals from activating receptors, such as NKG2D, and inhibitory receptors, such as KIR2DL1. Elongating the NKG2D ligand MICA reduced its ability to trigger NK cell activation. Conversely, elongation of KIR2DL1 ligand HLA-C reduced its ability to inhibit NK cells. Whereas normal-sized HLA-C was most effective at inhibiting activation by normal-length MICA, only elongated HLA-C could inhibit activation by elongated MICA. Moreover, HLA-C and MICA that were matched in size co-localised, whereas HLA-C and MICA that were different in size were segregated. These results demonstrate that receptor-ligand dimensions are important in NK cell recognition, and suggest that optimal integration of activating and inhibitory receptor signals requires the receptor-ligand complexes to have similar dimensions

NTIRE 2023 Quality Assessment of Video Enhancement Challenge

This paper reports on the NTIRE 2023 Quality Assessment of Video Enhancement Challenge, which will be held in conjunction with the New Trends in Image Restoration and Enhancement Workshop (NTIRE) at CVPR 2023. This challenge is to address a major challenge in the field of video processing, namely, video quality assessment (VQA) for enhanced videos. The challenge uses the VQA Dataset for Perceptual Video Enhancement (VDPVE), which has a total of 1211 enhanced videos, including 600 videos with color, brightness, and contrast enhancements, 310 videos with deblurring, and 301 deshaked videos. The challenge has a total of 167 registered participants. 61 participating teams submitted their prediction results during the development phase, with a total of 3168 submissions. A total of 176 submissions were submitted by 37 participating teams during the final testing phase. Finally, 19 participating teams submitted their models and fact sheets, and detailed the methods they used. Some methods have achieved better results than baseline methods, and the winning methods have demonstrated superior prediction performance