Iterative methods for tomographic image reconstruction often converge slowly. Preconditioning methods can often accelerate gradient-based iterations. Previous preconditioning methods for PET reconstruction have used e...
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Iterative methods for tomographic image reconstruction often converge slowly. Preconditioning methods can often accelerate gradient-based iterations. Previous preconditioning methods for PET reconstruction have used either diagonal or Fourier-based preconditioners. Fourier-based preconditioners are well suited to problems with near-circulant Hessian matrices. However, due to the nonuniform Poisson noise variance in PET, the circulant approximation to the Hessian is suboptimal. This paper shows that a particular combined diagonal/Fourier preconditioner yields a more accurate approximation to the Hessian and gives significantly faster convergence rates than does either preconditioner used alone.
We present GranatumX,a next-generation software environment for single-cell RNA sequencing(scRNA-seq)data *** is inspired by the interactive webtool *** enables biologists to access the latest scRNA-seq bioinformatics...
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We present GranatumX,a next-generation software environment for single-cell RNA sequencing(scRNA-seq)data *** is inspired by the interactive webtool *** enables biologists to access the latest scRNA-seq bioinformatics methods in a web-based graphical *** also offers software developers the opportunity to rapidly promote their own tools with others in customizable *** architecture of GranatumX allows for easy inclusion of plugin modules,named Gboxes,which wrap around bioinformatics tools written in various programming languages and on various *** can be run on the cloud or private servers and generate reproducible *** is a community-engaging,flexible,and evolving software ecosystem for scRNA-seq analysis,connecting developers with bench *** is freely accessible at http://***/granatumx/app.
We present a technique for information-theoretic optimization of computational imaging systems demonstrated in snapshot 3D microscopy. By directly evaluating measurement quality and decoupling optimization from downst...
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Background: Many recent studies have investigated modularity in biological networks, and its role in functional and structural characterization of constituent biomolecules. A technique that has shown considerable prom...
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Background: Many recent studies have investigated modularity in biological networks, and its role in functional and structural characterization of constituent biomolecules. A technique that has shown considerable promise in the domain of modularity detection is the Newman and Girvan (NG) algorithm, which relies on the number of shortest-paths across pairs of vertices in the network traversing a given edge, referred to as the betweenness of that edge. The edge with the highest betweenness is iteratively eliminated from the network, with the betweenness of the remaining edges recalculated in every iteration. This generates a complete dendrogram, from which modules are extracted by applying a quality metric called modularity denoted by Q. This exhaustive computation can be prohibitively expensive for large networks such as Protein-Protein Interaction Networks. In this paper, we present a novel optimization to the modularity detection algorithm, in terms of an efficient termination criterion based on a target edge betweenness value, using which the process of iterative edge removal may be terminated. Results: We validate the robustness of our approach by applying our algorithm on real-world protein-protein interaction networks of Yeast, *** and Drosophila, and demonstrate that our algorithm consistently has significant computational gains in terms of reduced runtime, when compared to the NG algorithm. Furthermore, our algorithm produces modules comparable to those from the NG algorithm, qualitatively and quantitatively. We illustrate this using comparison metrics such as module distribution, module membership cardinality, modularity Q, and Jaccard Similarity Coefficient. Conclusions: We have presented an optimized approach for efficient modularity detection in networks. The intuition driving our approach is the extraction of holistic measures of centrality from graphs, which are representative of inherent modular structure of the underlying network, and the applic
We present a deep-learning method based on Wiener filters and U-Nets that performs image reconstruction in systems with spatially-varying aberrations. We train on simulated microscopy measurements and test on experime...
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Nucleic acid amplification and quantification via polymerase chain reaction(PCR)is one of the most sensitive and powerful tools for clinical laboratories,precision medicine,personalized medicine,agricultural science,f...
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Nucleic acid amplification and quantification via polymerase chain reaction(PCR)is one of the most sensitive and powerful tools for clinical laboratories,precision medicine,personalized medicine,agricultural science,forensic science and environmental *** multiplex PCR,characterized by low power consumption,compact size and simple operation,is ideal for timely diagnosis at the point-of-care(POC).Although several fast/ultrafast PCR methods have been proposed,the use of a simple and robust PCR thermal cycler remains challenging for POC ***,we present an ultrafast photonic PCR method using plasmonic photothermal light-to-heat conversion via photon–electron–phonon *** demonstrate an efficient photonic heat converter using a thin gold(Au)film due to its plasmon-assisted high optical absorption(approximately 65%at 450 nm,the peak wavelength of heat source light-emitting diodes(LEDs)).The plasmon-excited Au film is capable of rapidly heating the surrounding solution to over 150℃ within 3 *** this method,ultrafast thermal cycling(30 cycles;heating and cooling rate of 12.7960.93℃ s^(-1) and 6.660.29℃ s^(-1),respectively)from 55℃(temperature of annealing)to 95℃(temperature of denaturation)is accomplished within 5 *** photonic PCR thermal cycles,we demonstrate here successful nucleic acid(λ-DNA)*** simple,robust and low cost approach to ultrafast PCR using an efficient photonic-based heating procedure could be generally integrated into a variety of devices or procedures,including on-chip thermal lysis and heating for isothermal amplifications.
This paper proposes an efficient method to implement RSA decryption algorithm. RSA cryptosystem is the most attractive and popular security technique for many applications, such as electronic commerce and secure inter...
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Developing on-chip functional devices requires reliable fabrication methods with high resolution for miniaturization,desired components for enhanced performance,and high throughput for fast prototyping and mass ***,la...
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Developing on-chip functional devices requires reliable fabrication methods with high resolution for miniaturization,desired components for enhanced performance,and high throughput for fast prototyping and mass ***,laser-based bubble-pen lithography(BPL)has been developed to enable sub-micron linewidths,in situ synthesis of custom materials,and on-demand patterning for various functional components and *** exploits Marangoni convection induced by a laser-controlled microbubble to attract,accumulate,and immobilize particles,ions,and molecules onto different *** years have witnessed tremendous progress in theory,engineering,and application of BPL,which motivated us to write this ***,an overview of experimental demonstrations and theoretical understandings of BPL is ***,we discuss the advantages of BPL and its diverse applications in quantum dot displays,biological and chemical sensing,clinical diagnosis,nanoalloy synthesis,and *** conclude this review with our perspective on the challenges and future directions of BPL.
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