Fully Dynamic Connectivity in O(log⁡n(log⁡log⁡n)2)O(\log n(\log\log n)^2) Amortized Expected Time

Dynamic connectivity is one of the most fundamental problems in dynamic graph algorithms. We present a randomized Las Vegas dynamic connectivity data structure with $O(\log n(\log\log n)^2)$ amortized expected update time and $O(\log n/\log\log\log n)$ worst case query time, which comes very close to the cell probe lower bounds of Patrascu and Demaine (2006) and Patrascu and Thorup (2011)

A Novel Broad-spectrum Lipopeptide Antimicrobial Agent, Paenibacterin, against Drug-resistant Bacteria: Structural Elucidation, Biosynthesis, and mechanisms of action

Food, Agricultural, and Environmental Sciences (FAES): 3rd Place (The Ohio State University Edward F. Hayes Graduate Research Forum)The ongoing explosion of infections caused by antibiotic-resistant bacteria continues to challenge the global public health. However, the discovery and development of novel antibacterial drugs are on the decline in the past decades. Therefore, it is urgent to develop potent and safe antimicrobial agents. Here we report the chemical structure, biosynthesis and modes of action of a novel antimicrobial agent, paenibacterin, from a strain of Paenibacillus thiaminolyticus OSY-SE. The producer microorganism was isolated from a soil sample collected in Columbus, OH in 2011. The potent antimicrobial agent was extracted by acetonitrile from the producer cells and purified using HPLC. The core peptide structure of paenibacterin was elucidated by mass-spectrometry (MS) and nuclear magnetic resonance (NMR) while the lipid tail of compound was determined by GC-MS. In order to identify the biosynthetic pathway of the compound, the whole genome of the producer strain OSY-SE was sequenced using the high throughput Illumina sequencing technology. The paenibacterin gene cluster (pbt) was further identified by bioinformatic analyses and confirmed by in vitro protein functional analyses. Furthermore, the mechanisms of action of paenibacterin were studied by fluorescence microscopy, membrane integrity assays, and hydroxyl radical production assays. Paenibacterin is a broad-spectrum antimicrobial agent with potent activity against foodborne pathogens and clinical drug-resistant isolates. Paenibacterin generally yielded a minimum inhibitory concentration (MIC) at 2-8 μg/ml against Gram-negative strains, and 8-64 μg/ml against Gram-positive strains. Paenibacterin is a cyclic lipopeptide, consisting of 13 amino acids and a C15 fatty acid side chain. Among the amino acids, some are D-amino acids and non-proteinogenic amino acid (ornithine). Paenibacterin is biosynthesized by the producer strain through non-ribosomal peptide synthetases (NRPS). The biosynthetic gene cluster was identified within 52-kb region, encoding three NRPSs (PbtA, PbtB and PbtC) and two ABC-transporters (PbtD and PbtE). Paenibacterin damages bacterial cell membrane, resulting in cytoplasmic membrane deporlarization and potassium ions release. Furthermore, paenibacterin triggers radical production via Fenton reaction and subsequently leads to cell death. This study reported a unique and potent antimicrobial agent with activity against drug-resistant bacteria. The structure of the compound could serve a scaffold for designing even more potent compounds by chemical synthesis. In addition, the elucidation of the biosynthetic pathway expedites the effort to produce paenibacterin derivatives by genetic engineering. This new and potent compound is a very promising candidate for agricultural and clinical application.A five-year embargo was granted for this item

Rewriting Flash Memories by Message Passing

This paper constructs WOM codes that combine rewriting and error correction for mitigating the reliability and the endurance problems in flash memory. We consider a rewriting model that is of practical interest to flash applications where only the second write uses WOM codes. Our WOM code construction is based on binary erasure quantization with LDGM codes, where the rewriting uses message passing and has potential to share the efficient hardware implementations with LDPC codes in practice. We show that the coding scheme achieves the capacity of the rewriting model. Extensive simulations show that the rewriting performance of our scheme compares favorably with that of polar WOM code in the rate region where high rewriting success probability is desired. We further augment our coding schemes with error correction capability. By drawing a connection to the conjugate code pairs studied in the context of quantum error correction, we develop a general framework for constructing error-correction WOM codes. Under this framework, we give an explicit construction of WOM codes whose codewords are contained in BCH codes.Comment: Submitted to ISIT 201

Fuzzy control and its application to a pH process

In the chemical industry, the control of pH is a well-known problem that presents difficulties due to the large variations in its process dynamics and the static nonlinearity between pH and concentration. pH control requires the application of advanced control techniques such as linear or nonlinear adaptive control methods. Unfortunately, adaptive controllers rely on a mathematical model of the process being controlled, the parameters being determined or modified in real time. Because of its characteristics, the pH control process is extremely difficult to model accurately. Fuzzy logic, which is derived from Zadeh's theory of fuzzy sets and algorithms, provides an effective means of capturing the approximate, inexact nature of the physical world. It can be used to convert a linguistic control strategy based on expert knowledge, into an automatic control strategy to control a system in the absence of an exact mathematical model. The work described in this thesis sets out to investigate the suitability of fuzzy techniques for the control of pH within a continuous flow titration process. Initially, a simple fuzzy development system was designed and used to produce an experimental fuzzy control program. A detailed study was then performed on the relationship between fuzzy decision table scaling factors and the control constants of a digital PI controller. Equation derived from this study were then confirmed experimentally using an analogue simulation of a first order plant. As a result of this work a novel method of tuning a fuzzy controller by adjusting its scaling factors, was derived. This technique was then used for the remainder of the work described in this thesis. The findings of the simulation studies were confirmed by an extensive series of experiments using a pH process pilot plant. The performance of the tunable fuzzy controller was compared with that of a conventional PI controller in response to step change in the set-point, at a number of pH levels. The results showed not only that the fuzzy controller could be easily adjusted to provided a wide range of operating characteristics, but also that the fuzzy controller was much better at controlling the highly non-linear pH process, than a conventional digital PI controller. The fuzzy controller achieved a shorter settling time, produced less over-shoot, and was less affected by contamination than the digital PI controller. One of the most important characteristics of the tunable fuzzy controller is its ability to implement a wide variety of control mechanisms simply by modifying one or two control variables. Thus the controller can be made to behave in a manner similar to that of a conventional PI controller, or with different parameter values, can imitate other forms of controller. One such mode of operation uses sliding mode control, with the fuzzy decision table main diagonal being used as the variable structure system (VSS) switching line. A theoretical explanation of this behavior, and its boundary conditions, are given within the text. While the work described within this thesis has concentrated on the use of fuzzy techniques in the control of continuous flow pH plants, the flexibility of the fuzzy control strategy described here, make it of interest in other areas. It is likely to be particularly useful in situations where high degrees of non-linearity make more conventional control methods ineffective

Investigation of Structural Dynamics of Enzymes and Protonation States of Substrates Using Computational Tools.

This review discusses the use of molecular modeling tools, together with existing experimental findings, to provide a complete atomic-level description of enzyme dynamics and function. We focus on functionally relevant conformational dynamics of enzymes and the protonation states of substrates. The conformational fluctuations of enzymes usually play a crucial role in substrate recognition and catalysis. Protein dynamics can be altered by a tiny change in a molecular system such as different protonation states of various intermediates or by a significant perturbation such as a ligand association. Here we review recent advances in applying atomistic molecular dynamics (MD) simulations to investigate allosteric and network regulation of tryptophan synthase (TRPS) and protonation states of its intermediates and catalysis. In addition, we review studies using quantum mechanics/molecular mechanics (QM/MM) methods to investigate the protonation states of catalytic residues of β-Ketoacyl ACP synthase I (KasA). We also discuss modeling of large-scale protein motions for HIV-1 protease with coarse-grained Brownian dynamics (BD) simulations