Merging multiple precipitation sources for flash flood forecasting

We investigated the effectiveness of combining gauge observations and satellite-derived precipitation on flood forecasting. Two data merging processes were proposed: the first one assumes that the individual precipitation measurement is non-bias, while the second process assumes that each precipitation source is biased and both weighting factor and bias parameters are to be calculated. Best weighting factors as well as the bias parameters were calculated by minimizing the error of hourly runoff prediction over Wu-Tu watershed in Taiwan. To simulate the hydrologic response from various sources of rainfall sequences, in our experiment, a recurrent neural network (RNN) model was used. The results demonstrate that the merged method used in this study can efficiently combine the information from both rainfall sources to improve the accuracy of flood forecasting during typhoon periods. The contribution of satellite-based rainfall, being represented by the weighting factor, to the merging product, however, is highly related to the effectiveness of ground-based rainfall observation provided gauged. As the number of gauge observations in the basin is increased, the effectiveness of satellite-based observation to the merged rainfall is reduced. This is because the gauge measurements provide sufficient information for flood forecasting; as a result the improvements added on satellite-based rainfall are limited. This study provides a potential advantage for extending satellite-derived precipitation to those watersheds where gauge observations are limited. © 2007 Elsevier B.V. All rights reserved

Satellite-based precipitation estimation using watershed segmentation and growing hierarchical self-organizing map

This paper outlines the development of a multi-satellite precipitation estimation methodology that draws on techniques from machine learning and morphology to produce high-resolution, short-duration rainfall estimates in an automated fashion. First, cloud systems are identified from geostationary infrared imagery using morphology based watershed segmentation algorithm. Second, a novel pattern recognition technique, growing hierarchical self-organizing map (GHSOM), is used to classify clouds into a number of clusters with hierarchical architecture. Finally, each cloud cluster is associated with co-registered passive microwave rainfall observations through a cumulative histogram matching approach. The network was initially trained using remotely sensed geostationary infrared satellite imagery and hourly ground-radar data in lieu of a dense constellation of polar-orbiting spacecraft such as the proposed global precipitation measurement (GPM) mission. Ground-radar and gauge rainfall measurements were used to evaluate this technique for both warm (June 2004) and cold seasons (December 2004-February 2005) at various temporal (daily and monthly) and spatial (0.04 and 0.25) scales. Significant improvements of estimation accuracy are found classifying the clouds into hierarchical sub-layers rather than a single layer. Furthermore, 2-year (2003-2004) satellite rainfall estimates generated by the current algorithm were compared with gauge-corrected Stage IV radar rainfall at various time scales over continental United States. This study demonstrates the usefulness of the watershed segmentation and the GHSOM in satellite-based rainfall estimations

Watershed rainfall forecasting using neuro-fuzzy networks with the assimilation of multi-sensor information

The complex temporal heterogeneity of rainfall coupled with mountainous physiographic context makes a great challenge in the development of accurate short-term rainfall forecasts. This study aims to explore the effectiveness of multiple rainfall sources (gauge measurement, and radar and satellite products) for assimilation-based multi-sensor precipitation estimates and make multi-step-ahead rainfall forecasts based on the assimilated precipitation. Bias correction procedures for both radar and satellite precipitation products were first built, and the radar and satellite precipitation products were generated through the Quantitative Precipitation Estimation and Segregation Using Multiple Sensors (QPESUMS) and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS), respectively. Next, the synthesized assimilated precipitation was obtained by merging three precipitation sources (gauges, radars and satellites) according to their individual weighting factors optimized by nonlinear search methods. Finally, the multi-step-ahead rainfall forecasting was carried out by using the adaptive network-based fuzzy inference system (ANFIS). The Shihmen Reservoir watershed in northern Taiwan was the study area, where 641 hourly data sets of thirteen historical typhoon events were collected. Results revealed that the bias adjustments in QPESUMS and PERSIANN-CCS products did improve the accuracy of these precipitation products (in particular, 30-60% improvement rates for the QPESUMS, in terms of RMSE), and the adjusted PERSIANN-CCS and QPESUMS individually provided about 10% and 24% contribution accordingly to the assimilated precipitation. As far as rainfall forecasting is concerned, the results demonstrated that the ANFIS fed with the assimilated precipitation provided reliable and stable forecasts with the correlation coefficients higher than 0.85 and 0.72 for one- and two-hour-ahead rainfall forecasting, respectively. The obtained forecasting results are very valuable information for the flood warning in the study watershed during typhoon periods. © 2013 Elsevier B.V

Comparison of dimensional accuracies of stereolithography and powder binder printing

This paper presents a comparative experimental investigation of the dimensional accuracies of two widely used rapid prototyping (RP) processes: stereolithography (SLA) and powder binder printing (PBP). Four replicates of a purpose-designed component using each RP process were fabricated, and the measurements of the internal and external features of all surfaces were performed using a general-purpose coordinate measurement machine. The results showed that in both cases, the main cause of dimensional variations was the volumetric change inherent in the process. The precision of SLA was far better than that of PBP. The dimensional accuracy of SLA was better in the z direction, whereas PBP produced better dimensional accuracy in the x–y plane. In both RP processes, the height error consisted of two components: constant error and cumulative error. The constant error component was equal to the datum surface error. SLA yielded an average datum surface error that was 68 % higher than in PBP. The height error of SLA improved with the increase in nominal height, whereas it deteriorated in PBP

Significance of Aurora B overexpression in hepatocellular carcinoma. Aurora B Overexpression in HCC

<p>Abstract</p> <p>Background</p> <p>To investigate the significance of Aurora B expression in hepatocellular carcinoma (HCC).</p> <p>Methods</p> <p>The <it>Aurora B </it>and <it>Aurora A </it>mRNA level was measured in 160 HCCs and the paired nontumorous liver tissues by reverse transcription-polymerase chain reaction. Mutations of the <it>p53 </it>and <it>β-catenin </it>genes were analyzed in 134 and 150 tumors, respectively, by direct sequencing of exon 2 to exon 11 of <it>p53 </it>and exon 3 of <it>β-catenin</it>. Anticancer effects of AZD1152-HQPA, an Aurora B kinase selective inhibitor, were examined in Huh-7 and Hep3B cell lines.</p> <p>Results</p> <p><it>Aurora B </it>was overexpressed in 98 (61%) of 160 HCCs and in all 7 HCC cell lines examined. The overexpression of <it>Aurora B </it>was associated with <it>Aurora A </it>overexpression (<it>P </it>= 0.0003) and <it>p53 </it>mutation (<it>P </it>= 0.002) and was inversely associated with <it>β</it>-<it>catenin </it>mutation (<it>P </it>= 0.002). <it>Aurora B </it>overexpression correlated with worse clinicopathologic characteristics. Multivariate analysis confirmed that <it>Aurora B </it>overexpression was an independent poor prognostic factor, despite its interaction with Aurora A overexpression and mutations of <it>p53 </it>and <it>β</it>-<it>catenin</it>. In Huh-7 and Hep3B cells, AZD1152-HQPA induced proliferation blockade, histone H3 (Ser10) dephosphorylation, cell cycle disturbance, and apoptosis.</p> <p>Conclusion</p> <p><it>Aurora B </it>overexpression is an independent molecular marker predicting tumor invasiveness and poor prognosis of HCC. Aurora B kinase selective inhibitors are potential therapeutic agents for HCC treatment.</p

Evidence for Impaired CARD15 Signalling in Crohn's Disease without Disease Linked Variants

BACKGROUND:Sensing of muramyl dipeptide (MDP) is impaired in Crohn's disease (CD) patients with disease-linked variants of the CARD15 (caspase activation and recruitment domain 15) gene. Animal studies suggest that normal CARD15 signalling prevents inflammatory bowel disease, and may be important for disease development in CD. However, only a small fraction of CD patients carry the disease linked CARD15 variants. The aim of this study was thus to investigate if changes could be found in CARD15 signalling in patients without disease associated CARD15 variants. METHODOLOGY/PRINCIPAL FINDINGS:By mapping the response to MDP in peripheral monocytes obtained from CD patients in remission not receiving immunosuppresives, an impaired response to MDP was found in patients without disease linked CARD15 variants compared to control monocytes. This impairment was accompanied by a decreased activation of IkappaB kinase alpha/beta (IKKalpha/beta), the initial step in the nuclear factor kappaB (NFkappaB) pathway, whereas activation of mitogen-activated protein (MAP)-kinases was unaffected. MDP additionally stimulates the inflammasome which is of importance for processing of cytokines. The inflammasome was constitutively activated in CD, but unresponsive to MDP both in CD and control monocytes. CONCLUSIONS/SIGNIFICANCE:These results suggest that inhibited MDP-dependent pathways in CD patients not carrying the disease-associated CARD15 variants might be of importance for the pathogenesis of CD. The results reveal a dysfunctional immune response in CD patients, not able to sense relevant stimuli on the one hand, and on the other hand possessing constitutively active cytokine processing

Thermal Properties of Graphene, Carbon Nanotubes and Nanostructured Carbon Materials

Recent years witnessed a rapid growth of interest of scientific and engineering communities to thermal properties of materials. Carbon allotropes and derivatives occupy a unique place in terms of their ability to conduct heat. The room-temperature thermal conductivity of carbon materials span an extraordinary large range - of over five orders of magnitude - from the lowest in amorphous carbons to the highest in graphene and carbon nanotubes. I review thermal and thermoelectric properties of carbon materials focusing on recent results for graphene, carbon nanotubes and nanostructured carbon materials with different degrees of disorder. A special attention is given to the unusual size dependence of heat conduction in two-dimensional crystals and, specifically, in graphene. I also describe prospects of applications of graphene and carbon materials for thermal management of electronics.Comment: Review Paper; 37 manuscript pages; 4 figures and 2 boxe

An experimental investigation into the dimensional error of powder-binder three-dimensional printing

This paper is an experimental investigation into the dimensional error of the rapid prototyping additive process of powder-binder three-dimensional printing. Ten replicates of a purpose-designed part were produced using a three-dimensional printer, and measurements of the internal and external features of all surfaces were made using a general purpose coordinate measuring machine. The results reveal that the bases of all replicates (nominally flat) have a concave curvature, producing a flatness error of the primary datum. This is in contrast to findings regarding other three-dimensional printing processes, widely reported in the literature, where a convex curvature was observed. All external surfaces investigated in this study showed positive deviation from nominal values, especially in the z-axis. The z-axis error consisted of a consistent positive cumulative error and a different constant error in different replicates. By compensating for datum surface error, the average total height error of the test parts can be reduced by 25.52 %. All the dimensional errors are hypothesised to be explained by expansion and the subsequent distortion caused by layer interaction during and after the printing process

Utilization of IκB–EGFP Chimeric Gene as an Indicator to Identify Microbial Metabolites with NF-κB Inhibitor Activity

NF-κB regulates several important expressions, such as cytokine release, anti-apoptosis, adhesion molecule expression, and cell cycle processing. Several NF-κB inhibitors have been discovered as an anti-tumor or anti-inflammatory drug. The activity of NF-κB transcription factor is negatively regulated by IκB binding. In this study, IκB assay system was established and IκB–EGFP fusion protein was used as an indicator to monitor the effects of substances on the IκB degradation. The results indicated that the chosen hydroquinone could inhibit the IκB degradation and cause the cell de-attachment from the bottom of culture plate. In addition, this system could also monitor the IκB degradation of microbial metabolite of natural mixtures of propolis. Thus, the IκB assay system may be a good system for drug discovery related to microbial metabolite

Roles of cysteines Cys115 and Cys201 in the assembly and thermostability of grouper betanodavirus particles

The virus-like particle (VLP) assembled from capsid subunits of the dragon grouper nervous necrosis virus (DGNNV) is very similar to its native T = 3 virion. In order to investigate the effects of four cysteine residues in the capsid polypeptide on the assembly/dissociation pathways of DGNNV virions, we recombinantly cloned mutant VLPs by mutating each cysteine to destroy the specific disulfide linkage as compared with thiol reduction to destroy all S–S bonds. The mutant VLPs of C187A and C331A mutations were similar to wild-type VLPs (WT-VLPs); hence, the effects of Cys187 and Cys331 on the particle formation and thermostability were presumably negligible. Electron microscopy showed that either C115A or C201A mutation disrupted de novo VLP formation significantly. As shown in micrographs and thermal decay curves, β-mercaptoethanol-treated WT-VLPs remained intact, merely resulting in lower tolerance to thermal disruption than native WT-VLPs. This thiol reduction broke disulfide linkages inside the pre-fabricated VLPs, but it did not disrupt the appearance of icosahedrons. Small dissociated capsomers from EGTA-treated VLPs were able to reassemble back to icosahedrons in the presence of calcium ions, but additional treatment with β-mercaptoethanol during EGTA dissociation resulted in inability of the capsomers to reassemble into the icosahedral form. These results indicated that Cys115 and Cys201 were essential for capsid formation of DGNNV icosahedron structure in de novo assembly and reassembly pathways, as well as for the thermal stability of pre-fabricated particles