Novel cooling strategies for improved protection of gas turbine blades

Modern gas turbines are operating at peak turbine inlet temperature well beyond the maximum endurable temperature of turbine blade material. As a result, hot gas-contacting blades or vanes have to be cooled intensively by using various cooling technologies, such as film cooling and internal cooling, in order to increase the fatigue lifetime of the engine. In the present study, a series of experimental investigations were conducted to explore innovative cooling strategies for improved exterior and interior cooling of gas turbine blades. For the exterior cooling, the effectiveness of novel film cooling designs with coolant injection from Barchan-Dune-Shaped ramp (BDSR) and Barchan-Dune-Shaped injection compound (BDSIC) were evaluated in great detail, in comparison to that of conventional circular holes. While a high-resolution Particle Image Velocimetry (PIV) system was used to conduct detailed flow field measurements to quantify the dynamic mixing process between the coolant streams and the mainstream flows over the test plates, Pressure Sensitive Paint (PSP) technique was used to map the corresponding adiabatic film cooling effectiveness on the surface of interest based on a mass-flux analog to traditional temperature-based cooling effectiveness measurements. The measured effectiveness maps were correlated with the characteristics of the flow structures revealed from the detailed PIV measurement in order to elucidate underlying physics to explore/optimize design paradigms for a better protection of the critical components of turbine blades. Beside exploration of novel cooling designs for film cooling, an experiment was performed to examine the compressibility effect on film cooling effectiveness by using PSP and PIV technique. The experimental studies were conducted in a transonic, open-circuit wind tunnel located at Iowa State University. The measured effectiveness revealed that the mainstream compressibility has limited effect on film effectiveness, and the effectiveness of transonic speed flow can be studied in a relative low-speed wind tunnel. Pertinent to interior cooling of turbine blades, finally, an experimental investigation was also conducted to quantify the characteristics of the turbulent boundary layer flows over a dimpled surface. Many interesting flow features over the dimpled surfaces, such as the separation of incoming boundary layer flow at the dimple front rim, the formation and shedding of unsteady Kelvin-Helmholtz vortices over the dimple cavity, the impingement of the high-speed incoming flow onto the back rim of the dimple, and the generation of strong upwash flow over the back rim of dimple, were revealed clearly and quantitatively. This was found to correlate well with the enhanced heat transfer performance of dimpled surface design reported in previous studies

Transcriptome and Comparative Gene Expression Analysis of Sogatella furcifera (Horváth) in Response to Southern Rice Black-Streaked Dwarf Virus

BACKGROUND: The white backed planthopper (WBPH), Sogatella furcifera (Horváth), causes great damage to many crops by direct feeding or transmitting plant viruses. Southern rice black-streaked dwarf virus (SRBSDV), transmitted by WBPH, has become a great threat to rice production in East Asia. METHODOLOGY/PRINCIPAL FINDINGS: By de novo transcriptome assembling and massive parallel pyrosequencing, we constructed two transcriptomes of WBPH and profiled the alternation of gene expression in response to SRBSDV infection in transcriptional level. Over 25 million reads of high-quality DNA sequences and 81388 different unigenes were generated using Illumina technology from both viruliferous and non-viruliferous WBPH. WBPH has a very similar gene ontological distribution to other two closely related rice planthoppers, Nilaparvata lugens and Laodelphax striatellus. 7291 microsatellite loci were also predicted which could be useful for further evolutionary analysis. Furthermore, comparative analysis of the two transcriptomes generated from viruliferous and non-viruliferous WBPH provided a list of candidate transcripts that potentially were elicited as a response to viral infection. Pathway analyses of a subset of these transcripts indicated that SRBSDV infection may perturb primary metabolism and the ubiquitin-proteasome pathways. In addition, 5.5% (181 out of 3315) of the genes in cell cytoskeleton organization pathway showed obvious changes. Our data also demonstrated that SRBSDV infection activated the immunity regulatory systems of WBPH, such as RNA interference, autophagy and antimicrobial peptide production. CONCLUSIONS/SIGNIFICANCE: We employed massively parallel pyrosequencing to collect ESTs from viruliferous and non-viruliferous samples of WBPH. 81388 different unigenes have been obtained. We for the first time described the direct effects of a Reoviridae family plant virus on global gene expression profiles of its insect vector using high-throughput sequencing. Our study will provide a road map for future investigations of the fascinating interactions between Reoviridae viruses and their insect vectors, and provide new strategies for crop protection

VideoDreamer: Customized Multi-Subject Text-to-Video Generation with Disen-Mix Finetuning

Customized text-to-video generation aims to generate text-guided videos with customized user-given subjects, which has gained increasing attention recently. However, existing works are primarily limited to generating videos for a single subject, leaving the more challenging problem of customized multi-subject text-to-video generation largely unexplored. In this paper, we fill this gap and propose a novel VideoDreamer framework. VideoDreamer can generate temporally consistent text-guided videos that faithfully preserve the visual features of the given multiple subjects. Specifically, VideoDreamer leverages the pretrained Stable Diffusion with latent-code motion dynamics and temporal cross-frame attention as the base video generator. The video generator is further customized for the given multiple subjects by the proposed Disen-Mix Finetuning and Human-in-the-Loop Re-finetuning strategy, which can tackle the attribute binding problem of multi-subject generation. We also introduce MultiStudioBench, a benchmark for evaluating customized multi-subject text-to-video generation models. Extensive experiments demonstrate the remarkable ability of VideoDreamer to generate videos with new content such as new events and backgrounds, tailored to the customized multiple subjects. Our project page is available at https://videodreamer23.github.io/

Experimental Study of the Effects of Marrow Mesenchymal Stem Cells Transfected with Hypoxia-Inducible Factor-1α Gene

Objective. To construct the eukaryotic expression vector hypoxia-inducible factor 1α-pcDNA3.1 and to investigate its transfective efficiency into mesenchymal stem cells (MSCs) in vitro and the expression of HIF-1α gene in MSCs. Methods. mRNA of Wistar Rats' myocardial cells was extracted, and cDNA was synthesized with Reverse Transcription Kit, HIF-1α was amplified by polymerase chain reaction (PCR), and constructed into pcDNA3.1. Transfected HIF-1α-pcDNA3.1 into MSCs by liposome mediated method. The expression of HIF-1α in the cells was detected by Western Blot Analysis and ELISA. Results. Eukaryotic expression vector HIF-1α-pcDNA3.1 was constructed successfully. Analyzed by flow cytometer, The MSCs' surfaces mark were CD44+, SH3(CD73)+, CD34−, CD45− and the CD44+ cells and SH3(CD73)+ cells were 94.7% and 97.3%, respectively, showing the high purity of the cultured MSCs. After inducing, the cultured MSCs can differentiate into osteoblasts and adipocytes successfully. In HIF-1α gene transfected MSCs, the expression of HIF-1α mRNA and HIF-1α protein were both increased obviously. Conclusion. HIF-1α was cloned successfully. HIF-1α-pcDNA3.1 can be transfected into MSCs by liposome-mediated method effectively and which resulting stable expression of HIF-1α in transfected MSCs

Revisiting Adversarial Attacks on Graph Neural Networks for Graph Classification

Graph neural networks (GNNs) have achieved tremendous success in the task of graph classification and its diverse downstream real-world applications. Despite the huge success in learning graph representations, current GNN models have demonstrated their vulnerability to potentially existent adversarial examples on graph-structured data. Existing approaches are either limited to structure attacks or restricted to local information, urging for the design of a more general attack framework on graph classification, which faces significant challenges due to the complexity of generating local-node-level adversarial examples using the global-graph-level information. To address this "global-to-local" attack challenge, we present a novel and general framework to generate adversarial examples via manipulating graph structure and node features. Specifically, we make use of Graph Class Activation Mapping and its variant to produce node-level importance corresponding to the graph classification task. Then through a heuristic design of algorithms, we can perform both feature and structure attacks under unnoticeable perturbation budgets with the help of both node-level and subgraph-level importance. Experiments towards attacking four state-of-the-art graph classification models on six real-world benchmarks verify the flexibility and effectiveness of our framework.Comment: 13 pages, 7 figure

Weighted SimCO: a novel algorithm for dictionary update

Algorithms aiming at solving dictionary learning problem usually involve iteratively performing two stage operations: sparse coding and dictionary update. In the dictionary update stage, codewords are updated based on a given sparsity pattern. In the ideal case where there is no noise and the true sparsity pattern is known a priori, dictionary update should produce a dictionary that precisely represent the training samples. However, we analytically show that benchmark algorithms, including MOD, K-SVD and regularized SimCO, could not always guarantee this property: they may fail to converge to a global minimum. The key behind the failure is the singularity in the objective function. To address this problem, we propose a weighted technique based on the SimCO optimization framework, hence the term weighted SimCO. Decompose the overall objective function as a sum of atomic functions. The crux of weighted SimCO is to apply weighting coefficients to atomic functions so that singular points are zeroed out. A second order method is implemented to solve the corresponding optimization problem. We numerically compare the proposed algorithm with the benchmark algorithms for noiseless and noisy scenarios. The empirical results demonstrate the significant improvement in the performance