Reuse, recycle to de-bloat software

Most Java programmers would agree that Java is a language that promotes a philosophy of “create and go forth”. By design, temporary objects are meant to be created on the heap, possibly used and then abandoned to be collected by the garbage collector. Excessive generation of temporary objects is termed “object churn” and is a form of software bloat that often leads to performance and memory problems. To mitigate this problem, many compiler optimizations aim at identifying objects that may be allocated on the stack. However, most such optimizations miss large opportunities for memory reuse when dealing with objects inside loops or when dealing with container objects. In this paper, we describe a novel algorithm that detects bloat caused by the creation of temporary container and String objects within a loop. Our analysis determines which objects created within a loop can be reused. Then we describe a source-to-source transformation that efficiently reuses such objects. Empirical evaluation indicates that our solution can reduce upto 40% of temporary object allocations in large programs, resulting in a performance improvement that can be as high as a 20% reduction in the run time, specifically when a program has a high churn rate or when the program is memory intensive and needs to run the GC often.

Positional Consensus of Multi-Agent Systems Using Linear Programming Based Decentralized Control with Rectilinear Decision Domain

In this paper we develop a Linear Programming (LP) based decentralized algorithm for a group of multiple autonomous agents to achieve positional consensus. Each agent is capable of exchanging information about its position and orientation with other agents within their sensing region. The method is computationally feasible and easy to implement. Analytical results are presented. The effectiveness of the approach is illustrated with simulation results.

Positional Consensus in Multi-Agent Systems using a Broadcast Control Mechanism

In this paper a strategy for controlling a group of agents to achieve positional consensus is presented. The proposed technique is based on the constraint that every agents must be given the same control input through a broadcast communication mechanism. Although the control command is computed using state information in a global framework, the control input is implemented by the agents in a local coordinate frame. We propose a novel linear programming formulation that is computationally less intensive than earlier proposed methods. Moreover, we introduce a random perturbation input in the control command that helps us to achieve perfect consensus even for a large number of agents, which was not possible with the existing strategy in the literature. Moreover, we extend the method to achieve positional consensus at a pre-specified location. The effectiveness of the approach is illustrated through simulation results.

Gossypol-induced hypokalemia and role of exogenous potassium salt supplementation when used as an antispermatogenic agent in male langur monkey

In our earlier study, we have observed that hypokalemia in langur monkeys, following gossypol acetic acid (GAA) treatment (5 mg dose level) when used as an antispermatogenic agent, and potassium salt supplementation partially maintained body potassium level of the animals. The aims of the present investigation was to confirm further occurrence of hypokalemia in the monkey (comparatively at two higher dose levels) and the role of potassium salt in preventing occurrence of gossypol-induced hypokalemia. Highly purified gossypol acetic acid alone at two dose levels (7.5 and 10 mg/animal/day; oral) and in combination with potassium chloride (0.50 and 0.75 mg/animal/day; oral) was given for 180 days. Treatment with gossypol alone as well as with the supplementation of potassium salt resulted in severe oligospermia and azoospermia. Animals receiving gossypol alone showed significant potassium deficiency with signs of fatigue at both dose levels. Enhanced potassium loss through urine was found in potassium-deficient animals, whereas animals receiving gossypol acetic acid plus potassium salt showed normal serum potassium with a less significant increase in urine potassium level during treatment phases. Other parameters of the body remained within normal range except gradual and significant elevation in serum transaminases activity. The animals gradually returned to normalcy following 150 and 180 days of termination of the treatment.

Model Predictive Static Programming: A Computationally Efficient Technique For Suboptimal Control Design

Combining the philosophies of nonlinear model predictive control and approximate dynamic programming, a new suboptimal control design technique is presented in this paper, named as model predictive static programming (MPSP), which is applicable for finite-horizon nonlinear problems with terminal constraints. This technique is computationally efficient, and hence, can possibly be implemented online. The effectiveness of the proposed method is demonstrated by designing an ascent phase guidance scheme for a ballistic missile propelled by solid motors. A comparison study with a conventional gradient method shows that the MPSP solution is quite close to the optimal solution.

An Iron Complex of Dipyridophenazine as a Potent Photocytotoxic Agent in Visible Light

Ternary iron(III) complexes (FeL(B)] (1-3) of a trianionic tetradentate phenolate-based ligand (L) and henanthroline base (B), namely, 1,10-phenanthroline (phen, 1), dipyridoquinoxaline (dpq, 2), and dipyridophenazine (dppz, 3), have been prepared and structurally characterized and their DNA binding, cleavage, and photocytotoxic properties studied. The complexes with a FeN3O3 core show the Fe(III)/Fe(II) redox couple near -0.6 V in DMF, a magnetic moment value of similar to 5.9 mu(B), and a binding propensity to both calf thymus DNA and bovine serum albumin (BSA) protein. They exhibit red-light-induced DNA cleavage activity following a metal-assisted photoredox pathway forming HO center dot radicals but do not show any photocleavage of BSA in UV-A light. Complex 3 displays photocytotoxicity in the human cervical cancer cell line (HeLa) and human keratinocyte cell line (HaCaT) with respective IC50 values of 3.59 mu M and 6.07 mu M in visible light and 251 nM and 751 nM in UV-A light of 365 nm. No significant cytotoxicity is observed in the dark. The photoexposed HeLa cells, treated prior with complex 3, have shown marked changes in nuclear morphology as demonstrated by Hoechst 33258 nuclear stain. Generation of reactive oxygen species has been evidenced from the fluorescence enhancement of dichlorofluorescein upon treatment with 3 followed by photoexposure. Nuclear chromatin cleavage has been observed in acridine orange/ethidium bromide dual staining of treated HeLa cells and from alkaline single-cell gel electrophoresis. Caspase 3/7 activity in HeLa cells has been found to be upregulated by only 4 fold after photoirradiation, signifying the fact that cell death through a caspase 3/7 dependent pathway may not be solely operative.

Programming an FPGA to Emulate the Dynamics of DC Machines

This paper presents the programming an FPGA (Field Programmable Gate Array) to emulate the dynamics of DC machines. FPGA allows high speed real time simulation with high precision. The described design includes block diagram representation of DC machine, which contain all arithmetic and logical operations. The real time simulation of the machine in FPGA is controlled by user interfaces they are Keypad interface, LCD display on-line and digital to analog converter. This approach provides emulation of electrical machine by changing the parameters. Separately Exited DC machine implemented and experimental results are presented.

A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data

Background: A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN) from transcript profiling data. Results: The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting) problem and solved finally by formulating a Linear Program (LP). A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known regulatory associations. In each S. cerevisiae LP-SLGN, the number of nodes with a particular degree follows an approximate power law suggesting that its degree distributions is similar to that observed in real-world networks. Inspection of these LP-SLGNs suggests biological hypotheses amenable to experimental verification. Conclusion: A statistically robust and computationally efficient LP-based method for estimating the topology of a large sparse undirected graph from high-dimensional data yields representations of genetic networks that are biologically plausible and useful abstractions of the structures of real genetic networks. Analysis of the statistical and topological properties of learned LP-SLGNs may have practical value; for example, genes with high random walk betweenness, a measure of the centrality of a node in a graph, are good candidates for intervention studies and hence integrated computational – experimental investigations designed to infer more realistic and sophisticated probabilistic directed graphical model representations of genetic networks. The LP-based solutions of the sparse linear regression problem described here may provide a method for learning the structure of transcription factor networks from transcript profiling and transcription factor binding motif data.

Ion beam processing of oriented CuO films deposited on (100) YSZ by laser ablation

A systematic study of Ar ion implantation in cupric oxide films has been reported. Oriented CuO films were deposited by pulsed excimer laser ablation technique on (1 0 0) YSZ substrates. X-ray diffraction (XRD) spectra showed the highly oriented nature of the deposited CuO films. The films were subjected to ion bombardment for studies of damage formation, Implantations were carried out using 100 keV Arf over a dose range between 5 x 10(12) and 5 x 10(15) ions/cm(2). The as-deposited and ion beam processed samples were characterized by XRD technique and resistance versus temperature (R-T) measurements. The activation energies for electrical conduction were found from In [R] versus 1/T curves. Defects play an important role in the conduction mechanism in the implanted samples. The conductivity of the film increases, and the corresponding activation energy decreases with respect to the dose value.

NMR spectra of oriented biologically important molecules - The structure of and the internal rotation in N,N'-dimethyluracil

From the proton NMR spectra of Nfl-dimethyluracil oriented in two different nematic solvents, the internal rotation of the methyl groups about the N-C bonds is studied. It has been observed that the preferred conformation of the methyl group having one carbonyl in the vicinity is the one where a C-H bond is in the ring plane pointing toward the carbonyl group. The results are not sensitive to the mode of rotation of the other methyl group. These data are interpreted in terms of the bond polarizations.

Uniformity in Bias Tilt for Nematics Oriented by Polyvinyl Alcohol Surface Layers

Uniformity in bias tilt, for the polyvinyl alcohol(PVA)surface layer induced orientation of nematic liquid crystals, could be achieved for large area display panels, if one of the transparent electrodes is first directionally rubbed with fine abrasive; then both the electrodes coated with PVA, followed by directionally buffing the chemisorbed layers in the same direction. Uniformity may be due to increased 'train' configuration of the adsorbed macromolecule by falling on to microgrooves and maintaining the same sense of asymmetry for the looped segments.

NMR Investigations on Di- and Tri-Azanaphthalenes Oriented in Liquid Crystals

Proton NMR spectra of 1,3-diazanaphthalene and 1,2,4-triazanaphthalene have been investigated in the nematic phase of three liquid crystals. The spectral analysis provided direct dipole-dipole couplings which have been used to derive the molecular structure. Geometry of the phenyl ring in both the molecules deviates from the regular hexagonal structure. Signs of the order parameter of the largest magnitude are opposite in liquid crystals with positive diamagetic anisotropies.

Parallel parsing of programming languages

A new method of specifying the syntax of programming languages, known as hierarchical language specifications (HLS), is proposed. Efficient parallel algorithms for parsing languages generated by HLS are presented. These algorithms run on an exclusive-read exclusive-write parallel random-access machine. They require O(n) processors and O(log2n) time, where n is the length of the string to be parsed. The most important feature of these algorithms is that they do not use a stack.

Electrochemical Reduction of Oriented Graphene Oxide Films: An in Situ Raman Spectroelectrochemical Study

Graphene oxide (GO) is assembled on a gold substrate by a layer-by-layer technique using a self-assembled cystamine monolayer. The negatively charged GO platelets are attached to the positively charged cystamine monolayer through electrostatic interactions. Subsequently, it is shown that the GO can be reduced electrochemically using applied DC bias by scanning the potential from 0 to -1 V vs a saturated calomel electrode in an aqueous electrolyte. The GO and reduced graphene oxide (RGO) are characterized by Raman spectroscopy and atomic force microscopy (AFM). A clear shift of the G band from 1610 cm-1 of GO to 1585 cm-1 of RGO is observed. The electrochemical reduction is followed in situ by micro Raman spectroscopy by carrying out Raman spectroscopic studies during the application of DC bias. The GO and RGO films have been characterized by conductive AFM that shows an increase in the current flow by at least 3 orders of magnitude after reduction. The electrochemical method of reducing GO may open up another way of controlling the reduction of GO and the extent of reduction to obtain highly conducting graphene on electrode materials.

Focused Prefetching: Performance Oriented Prefetching Based On Commit Stalls

Loads that miss in L1 or L2 caches and waiting for their data at the head of the ROB cause significant slow down in the form of commit stalls. We identify that most of these commit stalls are caused by a small set of loads, referred to as LIMCOS (Loads Incurring Majority of COmmit Stalls). We propose simple history-based classifiers that track commit stalls suffered by loads to help us identify this small set of loads. We study an application of these classifiers to prefetching. The classifiers are used to train the prefetcher to focus on the misses suffered by LIMCOS. This, referred to as focused prefetching, results in a 9.8% gain in IPC over naive GHB based delta correlation prefetcher along with a 20.3% reduction in memory traffic for a set of 17 memory-intensive SPEC2000 benchmarks. Another important impact of focused prefetching is a 61% improvement in the accuracy of prefetches. We demonstrate that the proposed classification criterion performs better than other existing criteria like criticality and delinquent loads. Also we show that the criterion of focusing on commit stalls is robust enough across cache levels and can be applied to any prefetcher without any modifications to the prefetcher.