Clarkson University

About: Clarkson University is a education organization based out in Potsdam, New York, United States. It is known for research contribution in the topics: Particle & Turbulence. The organization has 4414 authors who have published 10009 publications receiving 305356 citations. The organization is also known as: Thomas S. Clarkson Memorial School of Technology & Thomas S. Clarkson Memorial College of Technology.

Uniform, optimal signal processing of mapped deep-sequencing data

Abstract: Optimized algorithms from the field of electrical-signal processing improve the identification of genomic signals from diverse high-throughput sequencing experiments, such as ChIP-seq, DNase-seq and FAIRE-seq. Despite their apparent diversity, many problems in the analysis of high-throughput sequencing data are merely special cases of two general problems, signal detection and signal estimation. Here we adapt formally optimal solutions from signal processing theory to analyze signals of DNA sequence reads mapped to a genome. We describe DFilter, a detection algorithm that identifies regulatory features in ChIP-seq, DNase-seq and FAIRE-seq data more accurately than assay-specific algorithms. We also describe EFilter, an estimation algorithm that accurately predicts mRNA levels from as few as 1–2 histone profiles (R ∼0.9). Notably, the presence of regulatory motifs in promoters correlates more with histone modifications than with mRNA levels, suggesting that histone profiles are more predictive of cis-regulatory mechanisms. We show by applying DFilter and EFilter to embryonic forebrain ChIP-seq data that regulatory protein identification and functional annotation are feasible despite tissue heterogeneity. The mathematical formalism underlying our tools facilitates integrative analysis of data from virtually any sequencing-based functional profile.

Review: Recent Developments in Enzyme-Based Biosensors for Biomedical Analysis

Abstract: The need for simple, rapid, cost-effective, and portable screening methods has boosted the development of practical biosensors with applications in clinical monitoring, and diagnosis of disease. Compared with traditional analytical methods, enzyme-based bioanalytical devices have several distinct advantages such as high sensitivity and specificity, portability, cost-effectiveness, and the possibilities for miniaturization and mass production. Additionally, they can be developed for point-of-care diagnostic testing. This paper reviews recent advances in the development of enzyme biosensors, design characteristics, performances, and applications with a focus on electrochemical and optical sensors. Recent emerging technologies and innovative biosensing designs, such as nanosensors, paper based-sensors, lab-on-a-chip, biochips, and microfluidic devices are discussed. Specific applications in bioanalysis, clinical diagnosis, and pharmacology are discussed.

Optimal Traffic-Power Flow in Urban Electrified Transportation Networks

Abstract: This paper conducts an interdisciplinary study on the coordinated operation of both transportation system and power system. We consider an electrified transportation network enabled by wireless power transfer technology and coupled with a power distribution network (PDN) in the future city. The independent system operator, which is a public entity, is eligible to manage generation assets and charge congestion tolls (CTs) on electrified roads with the purpose of minimizing social cost. The route choices of electric vehicles are amenable to the Wardrop user equilibrium (UE) principle, such that no one can reduce his travel cost by changing route unilaterally. The traffic UE pattern further influences the spatial distribution of the electrical loads of the PDN. The power flow of the PDN is modeled through Dist-Flow equations. To find out the best generation schedule and CTs, we propose an optimal traffic-power flow model, which is a mixed integer nonlinear program with traffic UE constraints and further reformulated as a mixed integer second-order cone program, whose global optimal solution is accessible with reasonable computation effort. Case studies corroborate the benefits from the joint operation of the coupled networks, and demonstrate that ignoring the interdependency between the two critical infrastructures may lead to an insecure operation.

Effects of activator characteristics on the reaction product formation in slag binders activated using alkali silicate powder and NaOH

Abstract: The influence of different levels of alkalinity, expressed using the Na2O-to-source material ratio (n) and activator SiO2-to-Na2O ratio (Ms), on the compressive strength development of, and reaction product formation in sodium silicate and NaOH powder activated slag binder systems is discussed. Higher n value mixtures are found to exhibit higher early and later age compressive strengths. An increase in Ms results in reduced early age and slightly increased later age strengths. Compositional coefficients, which are functions of n and Ms are proposed, that relate to the early and later age strengths of the activated slag binders as well as to the shift in the FTIR spectra. The reaction product formation in these systems as a function of the total alkalinity is explained using the shifts of the dominant peak in the FTIR spectra. Fundamental changes in reaction products of powder activated binders as a function of alkalinity is observed. The deductions from the peak shifts are substantiated using the FTIR spectra of the pastes before and after salicylic acid–methanol (SAM) attack.