A Comparison of 7Q10 Low Flow between Rural and Urban Watersheds in Eastern United States

Abstract: Increased runoff peaks and volumes from urbanizing watersheds have been well documented where watershed hydrology becomes modified after 10 to 25% of land area is developed. Lowering of baseflow has also been reported to be modified from urbanization; however hydrology thresholds related to percentage of land area developed are not well quantified. In this study, 100 watersheds in eastern USA were investigated to examine the potential effects of urbanization on low flows. The low flow metric chosen for this analysis is the 7Q10. Historical flow records were obtained from the USGS stream gauges, in which a minimum of 10 years of data were used for computing the 7Q10. Corresponding with flow data records, USGS Seamless land cover images for years 1992 and 2001 were used to quantify the percent land area urbanized. Using ArcGIS, land cover data for these two years were used to estimate percentage of urbanization by summing the land cover areas for industry, commercial, and high-density residential and dividing by the total watershed area above the USGS gauging station. Differences in 7Q10 values between the two periods were statistically analyzed using the Wilcoxon signed rank test. Results showed a significant decrease in low flow due to increased urbanization percentage from 0 to 11%. Decreases in low flows were sporadic as urbanization percentage increased from 11 to 23%, but for urbanization percentage more than 23% the increment of low flow were not significantly different

System size reduction in stochastic simulations of the facilitated diffusion mechanism.

BACKGROUND: Site-specific Transcription Factors (TFs) are proteins that bind to specific sites on the DNA and control the activity of a target gene by enhancing or decreasing the rate at which the gene is transcribed by RNA polymerase. The process by which TF molecules locate their target sites is a key component of transcriptional regulation. Therefore it is essential to gain insight into the mechanisms by which TFs search for the target sites.Research in this area uses experimental and analytical approaches, but also stochastic simulations of the search process. Previous work based on stochastic simulations focussed only on short sequences, primarily for reasons of technical feasibility. Many of these studies had to disregard possible biases introduced by reducing a genome-wide system to a smaller subsystem. In particular, we identified crucial parameters that require adjustment, which were not adequately changed in these previous studies. RESULTS: We investigated several methods that adequately adapt the parameters of stochastic simulations of the facilitated diffusion, when the full sequence space is reduced to smaller regions of interest. We found two methods that scale the system accordingly: the copy number model and the association rate model. We systematically compared the results produced by simulations of the subsystem with respect to the original system. Our results confirmed that the copy number model is adequate only for high abundance TFs, while for low abundance TFs the association rate model is the only one that reproduces with high accuracy the results of the full system. CONCLUSIONS: We propose a strategy to reduce the size of the system that adequately adapts important parameters to capture the behaviour of the full system. This enables correct simulations of a smaller sequence space (which can be as small as 100 Kbp) and, thus, provides independence from computationally intensive genome-wide simulations of the facilitated diffusion mechanism.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Structure-Property Relationships of Polymer Gels and Concentrated Suspensions Modified with Anisotropic Nanoparticles

Soft materials are ubiquitous in every aspect of our daily life. These materials composed of a wide range of subfields including surfactants, foams, emulsions, pastes, slurries, polymers, gels, and colloidal suspensions. In recent years, there has been a great interest focusing on the understanding of the macroscopic properties of various types of soft materials as a function of their microstructures. For example, the structure-property relationship of physically-associating triblock copolymer gels can be controlled by selecting different types of solvents and changing the temperature. In these systems, gelation occurs due to the significant changes in the solubility of one or more of the blocks with temperature compared to the other blocks. Therefore, changing the temperature can lead to the structural transitions and macroscopic properties. The other strategy that can be used to modify the macroscopic performance of polymer gels is through the incorporation of nanoparticles, such as graphene nanoplatelets and nanotubes. The addition of nanoparticles can also affect the mechanical properties of concentrated suspensions in which, understanding the structure/flow properties is vital for processing and manufacturing of a product. Despite significant advances in the field of soft materials, our understanding in linking the structure-property relationships of polymer gels and concentrated suspensions is incomplete. With this perspective, in this dissertation, shear-rheometry and scattering techniques were used to understand the structural changes of the self-assembled triblock copolymer gels over a wide length-scale and broad temperature-range. Graphene nanoplatelets have been incorporated into this system to investigate the self-assembly behavior and mechanical properties as a function of graphene concentration. On the other hand, in concentrated suspensions of functionalized nanoparticles in a low-molecular- weight polymeric media, the effect of nanoparticles on the rheological properties were investigated. The present work provides a better understanding of the nanoparticles’contributions on microstructure and mechanical behavior of soft materials

GRiP: a computational tool to simulate transcription factor binding in prokaryotes

Motivation: Transcription factors (TFs) are proteins that regulate gene activity by binding to specific sites on the DNA. Understanding the way these molecules locate their target site is of great importance in understanding gene regulation. We developed a comprehensive computational model of this process and estimated the model parameters in (N.R.Zabet and B.Adryan, submitted for publication)

Pole-placement Predictive Functional Control for over-damped systems with real poles

This paper gives new insight and design proposals for Predictive Functional Control (PFC) algorithms. Common practice and indeed a requirement of PFC is to select a coincidence horizon greater than one for high-order systems and for the link between the design parameters and the desired dynamic to be weak. Here the proposal is to use parallel first-order models to form an independent prediction model and show that with these it is possible both to use a coincidence horizon of one and moreover to obtain precisely the desired closed-loop dynamics. It is shown through analysis that the use of a coincidence horizon of one greatly simplifies coding, tuning, constraint handling and implementation. The paper derives the key results for high-order and non-minimum phase processes and also demonstrates the flexibility and potential industrial utility of the proposal

Facilitated diffusion buffers noise in gene expression.

Transcription factors perform facilitated diffusion [three-dimensional (3D) diffusion in the cytosol and 1D diffusion on the DNA] when binding to their target sites to regulate gene expression. Here, we investigated the influence of this binding mechanism on the noise in gene expression. Our results showed that, for biologically relevant parameters, the binding process can be represented by a two-state Markov model and that the accelerated target finding due to facilitated diffusion leads to a reduction in both the mRNA and the protein noise.The following article has been published by Physical Review E. It can be found at: https://journals.aps.org/pre/abstract/10.1103/PhysRevE.90.032701. Copyright 2014 American Physical Society

An Alternative for PID control: Predictive Functional Control - A Tutorial

PFC (Predictive Function Control) can be considered as a bridge between PI(D) and complex MPC. PI(D) control can have problems handling dead time and constraints. PFC handles these cases and is often better than using a Smith predictor. PFC is a simple realizable MPC which thus uses prediction and preview of key variables. PFC can be implemented via simple program code and thus has cheap license costs. The tutorial introduces the basic idea of PFC and algorithms for typical processes. Simulations illustrate its effectiveness and advantages over PI(D) and Smith predictors

Homotypic clusters of transcription factor binding sites: A model system for understanding the physical mechanics of gene expression.

The organization of binding sites in cis-regulatory elements (CREs) can influence gene expression through a combination of physical mechanisms, ranging from direct interactions between TF molecules to DNA looping and transient chromatin interactions. The study of simple and common building blocks in promoters and other CREs allows us to dissect how all of these mechanisms work together. Many adjacent TF binding sites for the same TF species form homotypic clusters, and these CRE architecture building blocks serve as a prime candidate for understanding interacting transcriptional mechanisms. Homotypic clusters are prevalent in both bacterial and eukaryotic genomes, and are present in both promoters as well as more distal enhancer/silencer elements. Here, we review previous theoretical and experimental studies that show how the complexity (number of binding sites) and spatial organization (distance between sites and overall distance from transcription start sites) of homotypic clusters influence gene expression. In particular, we describe how homotypic clusters modulate the temporal dynamics of TF binding, a mechanism that can affect gene expression, but which has not yet been sufficiently characterized. We propose further experiments on homotypic clusters that would be useful in developing mechanistic models of gene expression.This is the published version of the manuscript. It was first published by Elsevier in Computational and Structural Biotechnology Journal here: http://www.sciencedirect.com/science/article/pii/S2001037014000142

Response study of canola (Brassica napus L.) cultivars to multi-environments using genotype plus genotype environment interaction (GGE) biplot method in Iran

To study the interaction of genotype and environment in canola crop, a study was carried out in 2010. Ten genotypes (Modena, Okapi, Hyola 401, Licord, Opera, Zarfam, RGS 003, SLM046, Sarigol, and Hyola 308) of canola were studied under normal conditions of irrigation in four locations (Karaj, Birjand, Shiraz, and Kashmar) using randomized complete block design with three replications. Using GGE biplot method, grain yield was investigated for each cultivar. According to analysis of variance, there was a very significant difference among the regions. According to the yield average and genotype stability, Licord, Hyola 308, Modena and Zarfam were the best cultivars. The graphs obtained from GGE biplot software indicated that Hyola 401, Opera, and Sarigol were better than the rest of the genotypes based on stability and yield performance. At location Shiraz, none of the genotype had appropriate stability or yield. Four locations were divided into three mega-environments including Karaj, Kashmar (first mega-environment), Birjand (second mega-environment), and Shiraz (third mega-environment). Moreover, Karaj was recognized as the best region of the classification and ranking of genotypes. The study indicated that the highest and lowest genotypic reaction rates belonged to Licord and SLM 046 cultivars, respectively.Keywords: Canola, genotype environment interaction, grain yield, GGE biplot

Practical applications of multi-agent systems in electric power systems

The transformation of energy networks from passive to active systems requires the embedding of intelligence within the network. One suitable approach to integrating distributed intelligent systems is multi-agent systems technology, where components of functionality run as autonomous agents capable of interaction through messaging. This provides loose coupling between components that can benefit the complex systems envisioned for the smart grid. This paper reviews the key milestones of demonstrated agent systems in the power industry and considers which aspects of agent design must still be addressed for widespread application of agent technology to occur