Advanced nonlinear analysis of masonry arch bridges

This research investigates the nonlinear response up to collapse of masonry arches and arch bridges using advanced numerical descriptions. Past research has shown that the mesoscale modelling approach for brick-masonry, where bricks and mortar joints are modelled separately, may offer a realistic representation of the mechanical behaviour of masonry components. However, because of the significant computational cost, thus far the use of this modelling strategy has been mainly restricted to 2D analysis of masonry arches and arch bridges. In some cases this may lead to a crude representation of the response which is inherently three-dimensional, especially when the analysed structure is subjected to eccentric loading or is characterised by a complex geometry (e.g. skew arches). In this work, masonry arches and arch bridges are analysed using a partitioned mesoscale approach, which enables the use of a detailed model for describing material nonlinearity at structural scale. This is combined with a partitioned approach allowing for parallel computation which guarantees computational efficiency. In the 3D mesoscale description, brick units and mortar interfaces are modelled separately accounting for the actual texture and arrangement of masonry. 3D elastic continuum solid elements are used to model brick units while mortar interfaces are modelled by means of 2D nonlinear interface elements. In analysing masonry bridges, the backfill material is modelled as an elasto-plastic continuum, while the physical interface between the continuum and mesoscale domain for masonry is represented by nonlinear zero-thickness interface elements allowing separation and plastic sliding. The proposed modelling approach has been applied to the analysis of multi-ring square and skew arches and masonry arch bridges. The numerical results, which also include numerical-experimental comparisons, confirm the accuracy of the adopted numerical strategy. Moreover numerical simulations have been performed to investigate the effects of the arch geometry, loading positions, material characteristics and potential settlements at the supports. The results obtained offer important information and a detailed description on the complex response of these critical structural systems under different loading and boundary conditions.Open Acces

Two-and-a-half Order Score-based Model for Solving 3D Ill-posed Inverse Problems

Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are crucial technologies in the field of medical imaging. Score-based models have proven to be effective in addressing different inverse problems encountered in CT and MRI, such as sparse-view CT and fast MRI reconstruction. However, these models face challenges in achieving accurate three dimensional (3D) volumetric reconstruction. The existing score-based models primarily focus on reconstructing two dimensional (2D) data distribution, leading to inconsistencies between adjacent slices in the reconstructed 3D volumetric images. To overcome this limitation, we propose a novel two-and-a-half order score-based model (TOSM). During the training phase, our TOSM learns data distributions in 2D space, which reduces the complexity of training compared to directly working on 3D volumes. However, in the reconstruction phase, the TOSM updates the data distribution in 3D space, utilizing complementary scores along three directions (sagittal, coronal, and transaxial) to achieve a more precise reconstruction. The development of TOSM is built on robust theoretical principles, ensuring its reliability and efficacy. Through extensive experimentation on large-scale sparse-view CT and fast MRI datasets, our method demonstrates remarkable advancements and attains state-of-the-art results in solving 3D ill-posed inverse problems. Notably, the proposed TOSM effectively addresses the inter-slice inconsistency issue, resulting in high-quality 3D volumetric reconstruction.Comment: 10 pages, 13 figure

Genetic Diversity, Population Structure, and Linkage Disequilibrium of an Association-Mapping Panel Revealed by Genome-Wide SNP Markers in Sesame

The characterization of genetic diversity and population structure can be used in tandem to detect reliable phenotype–genotype associations. In the present study, we genotyped a set of 366 sesame germplasm accessions by using 89,924 single-nucleotide polymorphisms (SNPs). The number of SNPs on each chromosome was consistent with the physical length of the respective chromosome, and the average marker density was approximately 2.67 kb/SNP. The genetic diversity analysis showed that the average nucleotide diversity of the panel was 1.1 × 10-3, with averages of 1.0 × 10-4, 2.7 × 10-4, and 3.6 × 10-4 obtained, respectively for three identified subgroups of the panel: Pop 1, Pop 2, and the Mixed. The genetic structure analysis revealed that these sesame germplasm accessions were structured primarily along the basis of their geographic collection, and that an extensive admixture occurred in the panel. The genome-wide linkage disequilibrium (LD) analysis showed that an average LD extended up to ∼99 kb. The genetic diversity and population structure revealed in this study should provide guidance to the future design of association studies and the systematic utilization of the genetic variation characterizing the sesame panel

Reduced expression of miR-22 in gastric cancer is related to clinicopathologic characteristics or patient prognosis

OBJECTIVE: Involvements of microRNA-22 (miR-22) in cancer development have attracted much attention, but its role in tumorigenesis of gastric cancer is still largely unknown. Therefore, the aim of this study was to investigate the expression patterns and clinical implications of miR-22 in gastric cancer. METHODS: Quantitative RT-PCR was performed to evaluate the expression levels of miR-22 in 98 pairs of gastric cancer and normal adjacent mucosa. RESULTS: Compared with normal adjacent mucosa, miR-22 expression was significantly downregulated in gastric cancer tissues (P < 0.001). Of 98 patients with gastric cancer, 58 (59.2%) were placed in the low miR-22 expression group and 40 (40.8%) were placed in the high miR-22 expression group. In addition, tumors with low miR-22 expression had greater extent of lymph node metastasis (P = 0.02) and distant metastasis (P = 0.01), and were at a worse stage (P = 0.01) than the tumors with high miR-22 expression. Moreover, the gastric cancer patients with low miR-22 expression had shorter overall survival than those with high miR-22 expression (P = 0.03). MiR-22, determined by multivariate analysis, was an independent prognostic factor for patients with gastric cancer. CONCLUSION: Our data offer the convincing evidence that the reduced expression of miR-22 was significantly associated with malignant development of gastric cancer and may be a novel prognostic marker of this disease. miR-22 might have potentials in the application of cancer therapy for patients with gastric cancer

On Effectively Learning of Knowledge in Continual Pre-training

Pre-trained language models (PLMs) like BERT have made significant progress in various downstream NLP tasks. However, by asking models to do cloze-style tests, recent work finds that PLMs are short in acquiring knowledge from unstructured text. To understand the internal behaviour of PLMs in retrieving knowledge, we first define knowledge-baring (K-B) tokens and knowledge-free (K-F) tokens for unstructured text and ask professional annotators to label some samples manually. Then, we find that PLMs are more likely to give wrong predictions on K-B tokens and attend less attention to those tokens inside the self-attention module. Based on these observations, we develop two solutions to help the model learn more knowledge from unstructured text in a fully self-supervised manner. Experiments on knowledge-intensive tasks show the effectiveness of the proposed methods. To our best knowledge, we are the first to explore fully self-supervised learning of knowledge in continual pre-training

Differential expressed genes in ECV304 Endothelial-like Cells infected with Human Cytomegalovirus

Background: Human cytomegalovirus (HCMV) is a virus which has the potential to alter cellular gene expression through multiple mechanisms.Objective: With the application of DNA microarrays, we could monitor the effects of pathogens on host-cell gene expression programmes in great depth and on a broad scale.Methods: Changes in mRNA expression levels of human endothelial-like ECV304 cells following infection with human cytomegalovirus AD169 strain was analyzed by a microarray system comprising 21073 60-mer oligonucleotide probes which represent 18716 human genes or transcripts.Results: The results from cDNA microarray showed that there were 559 differential expressed genes consisted of 471 upregulated genes and 88 down-regulated genes. Real-time qPCR was performed to validate the expression of 6 selected genes (RPS24, MGC8721, SLC27A3, MST4, TRAF2 and LRRC28), and the results of which were consistent with those from the microarray. Among 237 biology processes, 39 biology processes were found to be related significantly to HCMV-infection. The signal transduction is the most significant biological process with the lowest p value (p=0.005) among all biological process which involved in response to HCMV infection.Conclusion: Several of these gene products might play key roles in virus-induced pathogenesis. These findings may help to elucidate the pathogenic mechanisms of HCMV caused diseases.Keywords: Human cytomegalovirus, microarray, Gene expression profiling; infectomicsAfrican Health Sciences 2013; 13(4): 864 - 87

Skewed X-chromosome inactivation in patients with esophageal carcinoma

ABSTRACT: Skewed X-chromosome inactivation (SXCI) was found in some apparently healthy females mainly from Western countries. It has been linked to development of ovarian, breast and pulmonary carcinomas. The present study aimed to observe the SXCI frequencies in apparently healthy Chinese females and patients with esophageal carcinoma. DNA was extracted from the peripheral blood cells from 401 Chinese females without a detectable tumor and 143 female patients with esophageal carcinoma. Exon 1 of androgen receptor (AR) gene was amplified, and the products of different CAG alleles were resolved on denaturing polyacrylamide gels and visualized after silver staining. The corrected ratios (CR) of the products before and after HpaII digestion were calculated. As to the healthy females, when CR ≥ 3 was used as a criterion, SXCI was found in two (4.3%) of the 46 neonates, 13 (7.8%) of the 166 younger adults (16–50 years) and 37 (25.7%) of the 144 elderly females (51–96 years), with the frequency higher in the elderly subjects than in the two former groups (P < 0.05). When a more stringent criterion (CR ≥ 10) was used, SXCI was found in one (2.2%), two (1.2%) and 16 (11.1%) of the subjects in the three age groups, respectively, itsfrequency being higher in the elderly than in the younger age groups (P < 0.05). Occurrence of SXCI was detected in both the patients and controls at similar frequencies. However, the phenomenon, as defined as CR ≥ 3, was more frequent in the patients aging <40 years (35.7%) compared to the corresponding reference group (7.6%, P = 0.006). When CR ≥ 10 was adopted, the frequencies were 7.1% and 1.2%, respectively. Their difference did not attain statistical significance (P = 0. 217). SXCI also occurs in apparently healthy Chinese females, and is associated with age. It may be considered as a predisposing factor for the early development of esophageal carcinoma. VIRTUAL SLIDES: The virtual slide(s) for this article can be found here http://www.diagnosticpathology.diagnomx.eu/vs/154236433792765