Authenticity is one of the most important evaluation factors of images for photography competitions or journalism. Unusual compression history of an image often implies the illicit intent of its author. Our work aims at distinguishing real uncompressed images from fake uncompressed images that are saved in uncompressed formats but have been previously compressed. To detect the potential image JPEG compression, we analyze the JPEG compression artifacts based on the tetrolet covering, which corresponds to the local image geometrical structure. Since the compression can alter the structure information, the tetrolet covering indexes may be changed if a compression is performed on the test image. Such changes can provide valuable clues about the image compression history. To be specific, the test image is first compressed with different quality factors to generate a set of temporary images. Then, the test image is compared with each temporary image block-by-block to investigate whether the tetrolet covering index of each 4×4 block is different between them. The percentages of the changed tetrolet covering indexes corresponding to the quality factors (from low to high) are computed and used to form the p-curve, the local minimum of which may indicate the potential compression. Our experimental results demonstrate the advantage of our method to detect JPEG compressions of high quality, even the highest quality factors such as 98, 99, or 100 of the standard JPEG compression, from uncompressed-format images. At the same time, our detection algorithm can accurately identify the corresponding compression quality factor.
Objective To enhance the immunogenicity of the COOH terminal peptide of beta human chorionic gonadotropin(βhCG CTP) using molecular engineering. Methods Based on the analysis of protein epitope and principles of immune recognition, a chimerical peptide comprised of the beta 8 and beta 9 epitopes of hCG and a “promiscuous ” T cell epitope from the fusion protein of measles virus (MVF) was devised, synthesized and then purified. Rabbits were immunized with the chimerical peptide. The COOH terminal peptide of beta human chorionic gonadotropin coupled to diphtheria toxoid provided by WHO was served as control. Antibody titers were determined by enzyme linked immunosorbent assay (ELISA). Results The synthesized chimerical peptide elicited a much higher antibody response against intact native human chorionic gonadotropin than the control. Conclusion The synthesized chimerical peptide is more immunogenic and there fore it is possible to enhance the immunogenicity of beta hCG CTP via molecular engineering, which may be a promising approach for the making of an efficient vaccine for human fertility control.
Objective To understand the epidemiological characteristics of hemorrhagic fever with renal syndrome (HFRS), the distribution, density and virus carriage of host animals in Zhejiang province, and provide scientific basis for the formulation of prevention and control measures. Methods The incidence data of HFRS in Zhejiang from 2016 to 2020 were collected for a descriptive epidemiological analysis to understand its time, place and population distributions. The host animals were investigated at 5 surveillance areas in Zhejiang, the capture rate was investigated by the night method, and rat-shaped animal lungs and blood were collected for the hantavirus antigen and antibody detections, and analysis on the distribution and virus carriage of rodents in Zhejiang were conducted. Results The annual reported case numbers and incidence rate of HFRS in Zhejiang were 349 and 0.62/100 000 in 2016, 353 and 0.63/100 000 in 2017, 327 and 0.59/100 000 in 2018, 369 and 0.63/100 000 in 2019, and 260 and 0.46/100 000 in 2020. From 2016 to 2020, a total of 14 068 rat traps were deployed in residential areas, and 622 rodents were captured, the capture rate was 4.42%, and a total of 31 875 rat traps were deployed in the field, and 2 112 rodents were captured, the capture rate was 6.63% in the 5 surveillance areas. The differences in rodent density in the filed among the 5 surveillance areas were significant (F=2.941, P=0.046). A total of 3 065 rodents were captured in the 5 surveillance areas. The predominant rodent species in the field was Apodemus agrarianus, (1 830, 59.71%); the predominant rodent species in residential areas was Rattus norvegicus (330, 10.77%), the difference was significant (χ2=1675.401, P＜0.001). A total of 3065 rodent serum samples were tested, and the antibody positive rate was 8.7% (236/2808), and a total of 3065 rodent lung specimens were tested, the antibody positive rate was 3.66% (103/2815), and the differences in rodent species which were antibody positive among the 5 surveillance areas were significant (χ2=235.762, P＜0.001); and the differences in rodent species which were antigen positive among the 5 surveillance areas were significant (χ2=116.195, P＜0.001). Conclusion The density and virus carrying rate of rodents were high in the areas with high incidence of HFRS in Zhejiang. It is necessary to take targeted prevention and control measures in key areas for the better prevention and control of HFRS.
Abstract The COVID-19 pandemic is spreading rapidly, highlighting the urgent need for an efficient approach to rapidly develop therapeutics and prophylactics against SARS-CoV-2. We describe here the development of a phage-displayed single-domain antibody library by grafting naïve CDRs into framework regions of an identified human germline IGHV allele. This enabled the isolation of high-affinity single-domain antibodies of fully human origin. The panning using SARS-CoV-2 RBD and S1 as antigens resulted in the identification of antibodies targeting five types of neutralizing or non-neutralizing epitopes on SARS-CoV-2 RBD. These fully human single-domain antibodies bound specifically to SARS-CoV-2 RBD with subnanomolar to low nanomolar affinities. Some of them were found to potently neutralize pseudotyped and live virus, and therefore may represent promising candidates for prophylaxis and therapy of COVID-19. This study also reports unique immunogenic profile of SARS-CoV-2 RBD compared to that of SARS-CoV and MERS-CoV, which may have important implications for the development of effective vaccines against SARS-CoV-2.
The presence of white matter hyperintensities (WMH) on T2 fluid-attenuated inversion recovery (FLAIR) magnetic resonance images (MRI) is common in older adults over 65 years old. WMH lesions are even more extensive in those with vascular or Alzheimer's disease (AD) type of dementia when compared with cognitively normal older adults, suggesting its role in dementia pathogenesis and neurocognitive dysfunction. Prior methods in characterizing age-related white matter hyperintensity (WMH) lesions on T2 fluid-attenuated inversion recovery (FLAIR) magnetic resonance images (MRI) have mainly been limited to the understanding of the sizes of, and occasionally the locations of WMH lesions. Systematic morphological characterization has been missing. In this work, we proposed innovative methods to fill this knowledge gap. High-quality T2 FLAIR images containing clearly identifiable WMH lesions (Fig. 1) with various sizes from six cognitively normal older adults were used in our method development. We developed an innovative and proof-of-concept method to characterize and quantify the shape (based on Zernike transformation) and texture (based on fuzzy logic) of WMH lesions. We have also developed a multi-dimension feature vector approach to cluster WMH lesions into distinctive groups based on their shape and then texture features. We then developed an approach to calculate the potential growth index (PGI) of WMH lesions based on the image intensity distributions at the edge of the WMH lesions (penumbra) using a region-growing algorithm. Fig. 2 shows the WHM lesion classification based on shape. Fig. 3 shows the WMH lesion classification based on texture. Fig. 4 shows the voxels potentially grow based on our edge characterization algorithm. Our one-way Analyses of Variance (ANOVAs) showed significant differences in PGI among WMH group clusters in terms of either the shape (P = 3×10−3) or the texture (P < 1×10−16) features.
Overall Listing is to point to a company will be the main assets and business to a joint stock company overall reform listed practice. Liaoning Publish Media choose overall listing not only has the profound policy background, China is the inevitable development of media capital management. Overall listing to detachment from the discard of the listing, stripping listed inevitably caused a lot of related transaction, and not fair trade association of media risks listed companies. Take Liaoning Publish Media as an example, this essay is to analyzes its listed before and after the financial data, and with the A shares of the listed company of media of other financial data comparison analysis, found that Liaoning Publish Media overall listing, in the business performance has improved, and produced the effective market effect, Liaoning Publish Media in the capital operation performance is better than other media companies listed on the media plate. This paper also makes a vista of the overall listing to the media, and points out that the media is only for the overall listing to resolve their own system mechanism provides a platform, overall listing after the enterprise how to use media capital market mechanism change the original low efficiency phenomenon, effectively solve the corporate governance problems, still needs further research.
Duplicate Question Identification (DQI) improves the processing efficiency and accuracy of large-scale community question answering and automatic QA system. The purpose of DQI task is to identify whether the paired questions are semantically equivalent. However, how to distinguish the synonyms or homonyms in paired questions is still challenging. Most previous works focus on the word-level or phrase-level semantic differences. We firstly propose to explore the asking emphasis of a question as a key factor in DQI. Asking emphasis bridges semantic equivalence between two questions. In this paper, we propose an attention model with multi-fusion asking emphasis (MFAE) for DQI. At first, BERT is used to obtain the dynamic pre-trained word embeddings. Then we get inter- and intra-asking emphasis by summing inter-attention and self-attention, respectively; the idea is that, the more a word interacts with others, the more important the word is. Finally, we use eight-way combinations to generate multi-fusion asking emphasis and multi-fusion word representation. Experimental results demonstrate that our model achieves state-of-the-art performance on both Quora Question Pairs and CQADupStack data. In addition, our model can also improve the results for natural language inference task on SNLI and MultiNLI datasets. The code is available at https://github.com/rzhangpku/MFAE.
Composite images (CIs) typically combine various elements from different scenes, views, and styles, which are a very important information carrier in the era of mixed media such as virtual reality, mixed reality, metaverse, etc. However, the complexity of CI content presents a significant challenge for subsequent visual perception modeling and compression. In addition, the lack of benchmark CI databases also hinders the use of recent advanced data-driven methods. To address these challenges, we first establish one of the earliest visual redundancy prediction (VRP) databases for CIs. Moreover, we propose a multi-visual effect (MVE)-driven incremental learning method that combines the strengths of hand-crafted and data-driven approaches to achieve more accurate VRP modeling. Specifically, we design special incremental rules to learn the visual knowledge flow of MVE. To effectively capture the associated features of MVE, we further develop a three-stage incremental learning approach for VRP based on an encoder-decoder network. Extensive experimental results validate the superiority of the proposed method in terms of subjective, objective, and compression experiments.
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