Experimental investigation on the flexural behavior of concrete reinforced by various types of steel fibers

The benefit of steel fiber on the mechanical behaviors of concrete has been well accepted. The flexural behavior of steel fiber reinforced concrete (SFRC) is complicated which depends on many factors, such as matrix properties, fiber material properties, fiber geometries, fiber volume contents, and interface properties. Thus, the investigations on the flexural behavior of SFRC are needed to be expanded. In this study, the effects of fiber type with varying shapes and aspect ratios on the flexural performance of SFRC were investigated. Five steel fibers were adopted in this study: milled fiber (M), corrugated fiber (C) and three hooked fibers with aspect radios of 45 (HA), 55 (HB), and 65 (HC). Two volume fractions (0.4% and 1.0%) of steel fiber and two compressive strengths (normal and high strengths) of matrix were considered. The load-deflection curves, energy absorption capacity and equivalent flexural strength were discussed. The results show that the flexural behavior of SFRC beams reinforced by 1.0% fibers is significantly higher than that of the beams reinforced by 0.4% fibers. Hooked fiber reinforced beams performed the best flexural load-deflection response compared to the beams reinforced by milled fiber and corrugated fiber reinforced, and exhibited an increasing trend of flexural performance as the fiber aspect ratio increased. The differences between specimens with different fibers for high strength matrix are more obvious compared to the normal strength matrix

The value of VI-RADS combined with tumor contact length in the detection of muscle-invasive bladder cancer

Background and purpose: The value of Vesical Imaging-Reporting and Data System (VI-RADS) based on multiparametric magnetic resonance imaging (MRI) in the preoperative assessment of bladder cancer muscle-invasive is increasingly recognized. However, there is still a high number of false positives when the diagnostic cut-off value is 3 points. Tumor size has certain auxiliary diagnostic value in the assessment of tumor infiltration. Therefore, this study mainly explored the diagnostic performance of VI-RADS combined with tumor size in assessing bladder cancer muscle-invasive. Methods: The preoperative bladder multiparametric MRI and clinical data of 119 patients with bladder cancer confirmed by surgery and pathology (a total of 159 lesions) who were treated in Fudan University Shanghai Cancer Center from November 2019 to February 2022 were retrospectively collected. VI-RADS score and tumor contact length (TCL) measurements were performed independently for each lesion by two radiologists. Lesions with differences in score or size were given consistent results following discussion by two physicians. The receiver operating characteristic (ROC) curve was used to analyze the diagnostic performance of VI-RADS, TCL and their combined models for muscle invasion, and the corresponding area under curve (AUC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and diagnostic accuracy were compared. Results: Postoperative pathology confirmed that there were 75 and 84 lesions of non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC), respectively. The mean TCL of MIBC group (6.15-6.23 cm) was significantly different from that of NMIBC group (2.26-2.35 cm), and the difference was statistically significant (P<0.05). The specificity, PPV and diagnostic accuracy of VI-RADS combined with TCL in predicting bladder cancer muscle-invasive were significantly higher than those of VI-RADS with a diagnostic threshold of 3 points alone (P<0.05), whereas there was no statistically significant difference in the sensitivity and NPV (P>0.05). There was no significant difference in AUC between TCL (AUC = 0.89), VI-RADS (AUC = 0.90) and VI-RADS combined with TCL (AUC = 0.91) (P>0.05). Conclusion: VI-RADS combined with TCL can reduce the false positive rate of VI-RADS 3-point lesions in the evaluation of bladder cancer muscle-invasive to a certain extent, which is beneficial for avoiding overtreatment

Head and Neck Cancer Tumor Segmentation Using Support Vector Machine in Dynamic Contrast-Enhanced MRI

Objective. We aimed to propose an automatic method based on Support Vector Machine (SVM) and Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) to segment the tumor lesions of head and neck cancer (HNC). Materials and Methods. 120 DCE-MRI samples were collected. Five curve features and two principal components of the normalized time-intensity curve (TIC) in 80 samples were calculated as the dataset in training three SVM classifiers. The other 40 samples were used as the testing dataset. The area overlap measure (AOM) and the corresponding ratio (CR) and percent match (PM) were calculated to evaluate the segmentation performance. The training and testing procedure was repeated for 10 times, and the average performance was calculated and compared with similar studies. Results. Our method has achieved higher accuracy compared to the previous results in literature in HNC segmentation. The average AOM with the testing dataset was 0.76 ± 0.08, and the mean CR and PM were 79 ± 9% and 86 ± 8%, respectively. Conclusion. With improved segmentation performance, our proposed method is of potential in clinical practice for HNC

Paralellized ensemble Kalman filter for hydraulic conductivity characterization

[EN] The ensemble Kalman filter (EnKF) is nowadays recognized as an excellent inverse method for hydraulic conductivity characterization using transient piezometric head data. Its implementation is well suited for a parallel computing environment. A parallel code has been designed that uses parallelization both in the forecast step and in the analysis step. In the forecast step, each member of the ensemble is sent to a different processor, while in the analysis step, the computations of the covariances are distributed between the different processors. An important aspect of the parallelization is to limit as much as possible the communication between the processors in order to maximize execution time reduction. Four tests are carried out to evaluate the performance of the parallelization with different ensemble and model sizes. The results show the savings provided by the parallel EnKF, especially for a large number of ensemble realizations. (c) 2012 Elsevier Ltd. All rights reserved.The first author acknowledges the financial support from China Scholarship Council (CSC). Financial support to carry out this work was also received from the Spanish Ministry of Science and Innovation through project CGL2011-23295, and from the Universitat Politecnica de Valencia through project PERFORA.Xu, T.; Gómez-Hernández, JJ.; Li ., L.; Zhou ., H. (2013). Paralellized ensemble Kalman filter for hydraulic conductivity characterization. Computers and Geosciences. 52:42-49. https://doi.org/10.1016/j.cageo.2012.10.007S42495

Initial LDH level can predict the survival benefit from bevacizumab in the first-line setting in Chinese patients with metastatic colorectal cancer

BACKGROUND: Markers to predict the efficacy of bevacizumab treatment have been not fully validated in most cancers, including metastatic colorectal cancer (mCRC). The aim of this study was to investigate the potential role of lactate dehydrogenase (LDH) in predicting the survival benefit from first-line bevacizumab treatment, in Chinese patients with mCRC. METHODS: All the patients were diagnosed with mCRC at the Sun Yat-sen University Cancer Center from 2003 to 2013. The study group and the control group were classified by receiving bevacizumab or not. The serum LDH value of all the patients had been detected before the first-line treatment. The primary end point was progression-free survival (PFS). RESULTS: The median PFS of the study and the control group (patients who received bevacizumab or not) was 11.3 and 9.1 months, respectively (P=0.004). In the control group, the median PFS of the high LDH level and the low LDH level groups was 6.9 and 10.2 months, respectively (P<0.001). However, in the study group, the corresponding median PFS was 9.9 and 11.9 months, respectively (P=0.145). In addition, for the low LDH level group, the median PFS was 11.9 and 10.2 months for patients who received bevacizumab or not, respectively (P=0.066); however, the median PFS of patients receiving bevacizumab or not was significantly different in the high LDH level group (9.9 and 6.9 months, respectively) (P=0.012). CONCLUSION: The addition of bevacizumab in the first-line treatment setting could improve the PFS of mCRC patients notably. However, the benefit could only be potentially reflected on patients with high serum LDH level

Rare Copy Number Variants Identify Novel Genes in Sporadic Total Anomalous Pulmonary Vein Connection

Total anomalous pulmonary venous connection (TAPVC) is a rare congenital heart anomaly. Several genes have been associated TAPVC but the mechanisms remain elusive. To search novel CNVs and candidate genes, we screened a cohort of 78 TAPVC cases and 100 healthy controls for rare copy number variants (CNVs) using whole exome sequencing (WES). Then we identified pathogenic CNVs by statistical comparisons between case and control groups. After that, we identified altogether eight pathogenic CNVs of seven candidate genes (PCSK7, RRP7A, SERHL, TARP, TTN, SERHL2, and NBPF3). All these seven genes have not been described previously to be related to TAPVC. After network analysis of these candidate genes and 27 known pathogenic genes derived from the literature and publicly database, PCSK7 and TTN were the most important genes for TAPVC than other genes. Our study provides novel candidate genes potentially related to this rare congenital birth defect (CHD) which should be further fundamentally researched and discloses the possible molecular pathogenesis of TAPVC

The Power of Transient Piezometric Head Data in Inverse Modeling: An Application of the Localized Normal-score EnKF with Covariance Inflation in a Heterogenous Bimodal Hydraulic Conductivity Field

The localized normal-score ensemble Kalman filter (NS-EnKF) coupled with covariance inflation is used to characterize the spatial variability of a channelized bimodal hydraulic conductivity field, for which the only existing prior information about conductivity is its univariate marginal distribution. We demonstrate that we can retrieve the main patterns of the reference field by assimilating a sufficient number of piezometric observations using the NS-EnKF. The possibility of characterizing the conductivity spatial variability using only piezometric head data shows the importance of accounting for these data in inverse modeling.The first author acknowledges the financial support from the China Scholarship Council (CSC). Financial support to carry out this work was also received from the Spanish Ministry of Science and Innovation through project CGL2011-23295.Xu, T.; Gómez-Hernández, JJ.; Zhou, H.; Li, L. (2013). The Power of Transient Piezometric Head Data in Inverse Modeling: An Application of the Localized Normal-score EnKF with Covariance Inflation in a Heterogenous Bimodal Hydraulic Conductivity Field. Advances in Water Resources. 54:100-118. https://doi.org/10.1016/j.advwatres.2013.01.006S1001185

Taxonomic identification and antagonistic activity of Streptomyces luomodiensis sp. nov. against phytopathogenic fungi

Banana wilt caused by Fusarium oxysporum f. sp. cubense tropical race 4 (Foc TR4) is a devastating fungal disease. Biocontrol strategies hold immense potential for inhibiting the spread of Foc TR4. Here, 30 actinobacteria were isolated from soils and screened for their antagonistic activity against Foc TR4. Strain SCA4-21T was selected due to its strongest antagonistic activity against Foc TR4. Strain SCA4-21T also exhibited strong antagonistic activity against the other eight phytopathogenic fungi. The strain was identified as the genus Streptomyces according to its physiological, biochemical, and phenotypic characteristics. The phylogenetic trees of 16S rRNA sequences demonstrated that strain SCA4-21T formed a subclade with S. iranensis HM 35T and/or S. rapamycinicus NRRL B-5491T with low bootstrap values. Considering that 16S rRNAs did not provide sufficient resolution for species-level identification, the whole genome of strain SCA4-21T was sequenced. Multilocus sequence analysis (MLSA) based on five housekeeping gene alleles (atpD, gyrB, recA, rpoB, and trpB) revealed that strain SCA4-21T clustered into S. hygroscopicus subsp. hygroscopicus NBRC 13472T with 100% of bootstrap value. The analysis of the genome-based phylogeny also approved the results. Average nucleotide identity (ANI) and digital DNA–DNA hybridization (dDDH) were 91.26 and 44.30%, respectively, with values below the respective species level threshold of 95 and 70%. Hence, strain SCA 4–21T represented a novel species within the genus Streptomyces, named Streptomyces luomodiensis sp. nov. The type strain is SCA4-21T (=GDMCC4.340T = JCM36555T). By the CAZymes analysis, 348 carbohydrate-active enzymes (CAZymes) were detected, including 15 chitinases and eight β-1,3-glucanases. The fermentation broth of strain SCA4-21T, exhibiting strong antagonistic activity against Foc TR4, demonstrated high activities of chitinase and β-1,3-glucanase, which might be involved in antifungal activity. Our results showed an innovative potential biocontrol agent for managing plant fungal diseases, specifically banana fusarium wilt

Long-Term Exposure to Silica Dust and Risk of Total and Cause-Specific Mortality in Chinese Workers: A Cohort Study

A retro-prospective cohort study by Weihong Chen and colleagues provides new estimates for the risk of total and cause-specific mortality due to long-term silica dust exposure among Chinese workers

Modeling transient groundwater flow by coupling ensemble Kalman filtering and upscaling

The ensemble Kalman filter (EnKF) is coupled with upscaling to build an aquifer model at a coarser scale than the scale at which the conditioning data (conductivity and piezometric head) had been taken for the purpose of inverse modeling. Building an aquifer model at the support scale of observations is most often impractical since this would imply numerical models with many millions of cells. If, in addition, an uncertainty analysis is required involving some kind of Monte Carlo approach, the task becomes impossible. For this reason, a methodology has been developed that will use the conductivity data at the scale at which they were collected to build a model at a (much) coarser scale suitable for the inverse modeling of groundwater flow and mass transport. It proceeds as follows: (1) Generate an ensemble of realizations of conductivities conditioned to the conductivity data at the same scale at which conductivities were collected. (2) Upscale each realization onto a coarse discretization; on these coarse realizations, conductivities will become tensorial in nature with arbitrary orientations of their principal components. (3) Apply the EnKF to the ensemble of coarse conductivity upscaled realizations in order to condition the realizations to the measured piezometric head data. The proposed approach addresses the problem of how to deal with tensorial parameters, at a coarse scale, in ensemble Kalman filtering while maintaining the conditioning to the fine-scale hydraulic conductivity measurements. We demonstrate our approach in the framework of a synthetic worth-of-data exercise, in which the relevance of conditioning to conductivities, piezometric heads, or both is analyzed.The authors acknowledge Wolfgang Nowak and three anonymous reviewers for their comments on the previous versions of the manuscript, which helped substantially to improve it. 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