Phage Displayed Short Peptides against Cells of Candida albicans Demonstrate Presence of Species, Morphology and Region Specific Carbohydrate Epitopes

Candida albicans is a commensal opportunistic pathogen, which can cause superficial infections as well as systemic infections in immuocompromised hosts. Among nosocomial fungal infections, infections by C. albicans are associated with highest mortality rates even though incidence of infections by other related species is on the rise world over. Since C. albicans and other Candida species differ in their susceptibility to antifungal drug treatment, it is crucial to accurately identify the species for effective drug treatment. Most diagnostic tests that differentiate between C. albicans and other Candida species are time consuming, as they necessarily involve laboratory culturing. Others, which employ highly sensitive PCR based technologies often, yield false positives which is equally dangerous since that leads to unnecessary antifungal treatment. This is the first report of phage display technology based identification of short peptide sequences that can distinguish C. albicans from other closely related species. The peptides also show high degree of specificity towards its different morphological forms. Using fluorescence microscopy, we show that the peptides bind on the surface of these cells and obtained clones that could even specifically bind to only specific regions of cells indicating restricted distribution of the epitopes. What was peculiar and interesting was that the epitopes were carbohydrate in nature. This gives insight into the complexity of the carbohydrate composition of fungal cell walls. In an ELISA format these peptides allow specific detection of relatively small numbers of C. albicans cells. Hence, if used in combination, such a test could help accurate diagnosis and allow physicians to initiate appropriate drug therapy on time.

Formation of a G-quadruplex at the BCL2 major breakpoint region of the t(14;18) translocation in follicular lymphoma

The t(14;18) translocation in follicular lymphoma is one of the most common chromosomal translocations. Most breaks on chromosome 18 are located at the 3'-UTR of the BCL2 gene and are mainly clustered in the major breakpoint region (MBR). Recently, we found that the BCL2 MBR has a non-B DNA character in genomic DNA. Here, we show that single-stranded DNA modeled from the template strand of the BCL2 MBR, forms secondary structures that migrate faster on native PAGE in the presence of potassium, due to the formation of intramolecular G-quadruplexes. Circular dichroism shows evidence for a parallel orientation for G-quadruplex structures in the template strand of the BCL2 MBR. Mutagenesis and the DMS modification assay confirm the presence of three guanine tetrads in the structure. 1H nuclear magnetic resonance studies further confirm the formation of an intramolecular G-quadruplex and a representative model has been built based on all of the experimental evidence. We also provide data consistent with the possible formation of a G-quadruplex structure at the BCL2 MBR within mammalian cells. In summary, these important features could contribute to the single-stranded character at the BCL2 MBR, thereby contributing to chromosomal fragility.

New Approximation Algorithms for Minimum Cycle Bases of Graphs

We consider the problem of computing an approximate minimum cycle basis of an undirected non-negative edge-weighted graph G with m edges and n vertices; the extension to directed graphs is also discussed. In this problem, a {0,1} incidence vector is associated with each cycle and the vector space over F-2 generated by these vectors is the cycle space of G. A set of cycles is called a cycle basis of G if it forms a basis for its cycle space. A cycle basis where the sum of the weights of the cycles is minimum is called a minimum cycle basis of G. Cycle bases of low weight are useful in a number of contexts, e.g. the analysis of electrical networks, structural engineering, chemistry, and surface reconstruction. Although in most such applications any cycle basis can be used, a low weight cycle basis often translates to better performance and/or numerical stability. Despite the fact that the problem can be solved exactly in polynomial time, we design approximation algorithms since the performance of the exact algorithms may be too expensive for some practical applications. We present two new algorithms to compute an approximate minimum cycle basis. For any integer k >= 1, we give (2k - 1)-approximation algorithms with expected running time O(kmn(1+2/k) + mn((1+1/k)(omega-1))) and deterministic running time O(n(3+2/k) ), respectively. Here omega is the best exponent of matrix multiplication. It is presently known that omega < 2.376. Both algorithms are o(m(omega)) for dense graphs. This is the first time that any algorithm which computes sparse cycle bases with a guarantee drops below the Theta(m(omega) ) bound. We also present a 2-approximation algorithm with expected running time O(M-omega root n log n), a linear time 2-approximation algorithm for planar graphs and an O(n(3)) time 2.42-approximation algorithm for the complete Euclidean graph in the plane.

Load balancing algorithms for an extended hypercube

Reduction of the execution time of a job through equitable distribution of work load among the processors in a distributed system is the goal of load balancing. Performance of static and dynamic load balancing algorithms for the extended hypercube, is discussed. Threshold algorithms are very well-known algorithms for dynamic load balancing in distributed systems. An extension of the threshold algorithm, called the multilevel threshold algorithm, has been proposed. The hierarchical interconnection network of the extended hypercube is suitable for implementing the proposed algorithm. The new algorithm has been implemented on a transputer-based system and the performance of the algorithm for an extended hypercube is compared with those for mesh and binary hypercube networks

Absolutely expedient algorithms for learning Nash equilibria

This paper considers a multi-person discrete game with random payoffs. The distribution of the random payoff is unknown to the players and further none of the players know the strategies or the actual moves of other players. A class of absolutely expedient learning algorithms for the game based on a decentralised team of Learning Automata is presented. These algorithms correspond, in some sense, to rational behaviour on the part of the players. All stable stationary points of the algorithm are shown to be Nash equilibria for the game. It is also shown that under some additional constraints on the game, the team will always converge to a Nash equilibrium.

Formation of a G-quadruplex at the BCL2 major breakpoint region of the t(14;18) translocation in follicular lymphoma

The t(14;18) translocation in follicular lymphoma is one of the most common chromosomal translocations. Most breaks on chromosome 18 are located at the 3'-UTR of the BCL2 gene and are mainly clustered in the major breakpoint region (MBR). Recently, we found that the BCL2 MBR has a non-B DNA character in genomic DNA. Here, we show that single-stranded DNA modeled from the template strand of the BCL2 MBR, forms secondary structures that migrate faster on native PAGE in the presence of potassium, due to the formation of intramolecular G-quadruplexes. Circular dichroism shows evidence for a parallel orientation for G-quadruplex structures in the template strand of the BCL2 MBR. Mutagenesis and the DMS modification assay confirm the presence of three guanine tetrads in the structure. 1H nuclear magnetic resonance studies further confirm the formation of an intramolecular G-quadruplex and a representative model has been built based on all of the experimental evidence. We also provide data consistent with the possible formation of a G-quadruplex structure at the BCL2 MBR within mammalian cells. In summary, these important features could contribute to the single-stranded character at the BCL2 MBR, thereby contributing to chromosomal fragility.

Growing pseudo-eigenmodes and positive logarithmic norms in rotating shear flows

Rotating shear flows, when angular momentum increases and angular velocity decreases as functions of radiation coordinate, are hydrodynamically stable under linear perturbation. The Keplerian flow is an example of such a system, which appears in an astrophysical context. Although decaying eigenmodes exhibit large transient energy growth of perturbation which could govern nonlinearity in the system, the feedback of inherent instability to generate turbulence seems questionable. We show that such systems exhibiting growing pseudo-eigenmodes easily reach an upper bound of growth rate in terms of the logarithmic norm of the involved non-normal operators, thus exhibiting feedback of inherent instability. This supports the existence of turbulence of hydrodynamic origin in the Keplerian accretion disc in astrophysics. Hence, this answers the question of the mismatch between the linear theory and experimental/observed data and helps in resolving the outstanding question of the origin of turbulence therein.

Stochastic Approximation Algorithms for Constrained Optimization via Simulation

We develop four algorithms for simulation-based optimization under multiple inequality constraints. Both the cost and the constraint functions are considered to be long-run averages of certain state-dependent single-stage functions. We pose the problem in the simulation optimization framework by using the Lagrange multiplier method. Two of our algorithms estimate only the gradient of the Lagrangian, while the other two estimate both the gradient and the Hessian of it. In the process, we also develop various new estimators for the gradient and Hessian. All our algorithms use two simulations each. Two of these algorithms are based on the smoothed functional (SF) technique, while the other two are based on the simultaneous perturbation stochastic approximation (SPSA) method. We prove the convergence of our algorithms and show numerical experiments on a setting involving an open Jackson network. The Newton-based SF algorithm is seen to show the best overall performance.

Study Of Acoustic Source Localization Algorithm For Planar Arrays

The source localization algorithms in the earlier works, mostly used non-planar arrays. If we consider scenarios like human-computer communication, or human-television communication where the microphones need to be placed on the computer monitor or television front panel, i.e we need to use the planar arrays. The algorithm proposed in 1], is a Linear Closed Form source localization algorithm (LCF algorithm) which is based on Time Difference of Arrivals (TDOAs) that are obtained from the data collected using the microphones. It assumes non-planar arrays. The LCF algorithm is applied to planar arrays in the current work. The relationship between the error in the source location estimate and the perturbation in the TDOAs is derived using first order perturbation analysis and validated using simulations. If the TDOAs are erroneous, both the coefficient matrix and the data matrix used for obtaining source location will be perturbed. So, the Total least squares solution for source localization is proposed in the current work. The sensitivity analysis of the source localization algorithm for planar arrays and non-planar arrays is done by introducing perturbation in the TDOAs and the microphone locations. It is shown that the error in the source location estimate is less when we use planar array instead of the particular non-planar array considered for same perturbation in the TDOAs or microphone location. The location of the reference microphone is proved to be important for getting an accurate source location estimate if we are using the LCF algorithm.

Heuristic algorithms for scheduling of a batch processor in automobile gear manufacturing

In this paper we address a scheduling problem for minimising total weighted tardiness. The motivation for the paper comes from the automobile gear manufacturing process. We consider the bottleneck operation of heat treatment stage of gear manufacturing. Real life scenarios like unequal release times, incompatible job families, non-identical job sizes and allowance for job splitting have been considered. A mathematical model taking into account dynamic starting conditions has been developed. Due to the NP-hard nature of the problem, a few heuristic algorithms have been proposed. The performance of the proposed heuristic algorithms is evaluated: (a) in comparison with optimal solution for small size problem instances, and (b) in comparison with `estimated optimal solution' for large size problem instances. Extensive computational analyses reveal that the proposed heuristic algorithms are capable of consistently obtaining near-optimal solutions (that is, statistically estimated one) in very reasonable computational time.

Cooperative Spectrum Sensing Algorithms For OFDM Systems with Frequency Selective Channels

This paper considers the problem of spectrum sensing in cognitive radio networks when the primary user employs Orthogonal Frequency Division Multiplexing (OFDM). We specifically consider the scenario when the channel between the primary and a secondary user is frequency selective. We develop cooperative sequential detection algorithms based on energy detectors. We modify the detectors to mitigate the effects of some common model uncertainties such as timing and frequency offset, IQ-imbalance and uncertainty in noise and transmit power. The performance of the proposed algorithms are studied via simulations. We show that the performance of the energy detector is not affected by the frequency selective channel. We also provide a theoretical analysis for some of our algorithms.

Critical exponent of the electrical conductivity in the paracoherence region of a thin film of YBa2Cu3O7?x

Critical exponent of the electrical conductivity in the paracoherence region (gamma) of the high temperature superconductor YBa2Cu3O7-x (YBCO) has been estimated for high quality thin film on ZrO2 substrate prepared by high pressure oxygen sputtering. High energy ion irradiation was carried out using 100 MeV O-16(7+) ions at liquid nitrogen to see the effects of disorder on the value of the exponent. The critical exponent from a value of about 2 to 1.62 upon irradiation. Studies were also carried film to see the effect of ageing and annealing.

Genetic algorithms: a survey

Genetic algorithms provide an alternative to traditional optimization techniques by using directed random searches to locate optimal solutions in complex landscapes. We introduce the art and science of genetic algorithms and survey current issues in GA theory and practice. We do not present a detailed study, instead, we offer a quick guide into the labyrinth of GA research. First, we draw the analogy between genetic algorithms and the search processes in nature. Then we describe the genetic algorithm that Holland introduced in 1975 and the workings of GAs. After a survey of techniques proposed as improvements to Holland's GA and of some radically different approaches, we survey the advances in GA theory related to modeling, dynamics, and deception

Managing interprocessor delays in distributed recursive algorithms

For a class of distributed recursive algorithms, it is shown that a stochastic approximation-like tapering stepsize routine suppresses the effects of interprocessor delays.

Characterization of aerosol black carbon over a tropical semi-arid region of Anantapur, India

Black carbon (BC) aerosol mass concentrations measured using an aethalometer at Anantapur, a semi-arid tropical station in the southern part of peninsular India, from August 2006 to July 2007 are analyzed. Seasonal and diurnal variations of BC in relation to changes in the regional meteorological conditions have been studied along with the mass fraction of BC to the total aerosol mass concentration (M-t) and fine particle mass (FPM) concentration in different months. The data collected during the study period shows that the annual average BC mass concentration at Anantapur is 1.97 +/- 0.12 mu g m(-3). Seasonal variations of BC aerosol mass concentration showed high during the dry (winter and summer) seasons and low during the post-monsoon followed by the monsoon seasons. Diurnal variations of BC aerosols attain a gradual build up in BC concentration from morning and a sharp peak occurs between 07:00 and 09:00 h almost an hour after local sunrise and a broad nocturnal peak from 19:00 to 21:00 h with a minimum in noon hours. The ratio of BC to the fine particle mass concentration was high during the dry season and low during the monsoon season. The regression analysis between BC mass concentration and wind speed indicates that, with increase in wind speeds the BC mass concentrations would decrease and vice-versa. Aerosol BC mass concentration shows a significant positive correlation with total mass concentration (M-t) and aerosol optical depth (ACID, tau(p)) at 500 nm. (C) 2010 Elsevier B.V. All rights reserved.