Synthesis of novel poly[(2,5-dimethoxy-p-phenylene)vinylene] precursors having two eliminatable groups: An approach for the control of conjugation length

Poly[(2,5-dimethoxy-p-phenylene)vinylene] (DMPPV) of varying conjugation length was synthesized by selective elimination of organic soluble precursor polymers that contained two eliminatable groups, namely, methoxy and acetate groups. These precursor copolymers were in turn synthesized by competitive nucleophilic substitution of the sulfonium polyelectrolyte precursor (generated by the standard Wessling route) using methanol and sodium acetate in acetic acid. The composition of the precursor copolymer, in terms of the relative amounts of methoxy and acetate groups, was controlled by varying the composition of the reaction mixture during nucleophilic substitution. Thermal elimination of these precursor copolymers at 250 degrees C, yielded partially conjugated polymers, whose color varied from light yellow to deep red. FT-IR studies confirmed that, while essentially all the acetate groups were eliminated, the methoxy groups were intact and caused the interruption in conjugation. Preliminary photoluminescence studies of the partially eliminated DMPPV samples showed a gradual shift in the emission maximum from 498 to 598 nm with increasing conjugation lengths, suggesting that the color of LED devices fabricated from such polymers can, in principle, be fine-tuned.

targetTB: A target identification pipeline for Mycobacterium tuberculosis through an interactome, reactome and genome-scale structural analysis

Background: Tuberculosis still remains one of the largest killer infectious diseases, warranting the identification of newer targets and drugs. Identification and validation of appropriate targets for designing drugs are critical steps in drug discovery, which are at present major bottle-necks. A majority of drugs in current clinical use for many diseases have been designed without the knowledge of the targets, perhaps because standard methodologies to identify such targets in a high-throughput fashion do not really exist. With different kinds of 'omics' data that are now available, computational approaches can be powerful means of obtaining short-lists of possible targets for further experimental validation. Results: We report a comprehensive in silico target identification pipeline, targetTB, for Mycobacterium tuberculosis. The pipeline incorporates a network analysis of the protein-protein interactome, a flux balance analysis of the reactome, experimentally derived phenotype essentiality data, sequence analyses and a structural assessment of targetability, using novel algorithms recently developed by us. Using flux balance analysis and network analysis, proteins critical for survival of M. tuberculosis are first identified, followed by comparative genomics with the host, finally incorporating a novel structural analysis of the binding sites to assess the feasibility of a protein as a target. Further analyses include correlation with expression data and non-similarity to gut flora proteins as well as 'anti-targets' in the host, leading to the identification of 451 high-confidence targets. Through phylogenetic profiling against 228 pathogen genomes, shortlisted targets have been further explored to identify broad-spectrum antibiotic targets, while also identifying those specific to tuberculosis. Targets that address mycobacterial persistence and drug resistance mechanisms are also analysed. Conclusion: The pipeline developed provides rational schema for drug target identification that are likely to have high rates of success, which is expected to save enormous amounts of money, resources and time in the drug discovery process. A thorough comparison with previously suggested targets in the literature demonstrates the usefulness of the integrated approach used in our study, highlighting the importance of systems-level analyses in particular. The method has the potential to be used as a general strategy for target identification and validation and hence significantly impact most drug discovery programmes.

A fuzzy logic based dynamic wave model inversion algorithm for canal regulation

A fuzzy logic based centralized control algorithm for irrigation canals is presented. Purpose of the algorithm is to control downstream discharge and water level of pools in the canal, by adjusting discharge release from the upstream end and gates settings. The algorithm is based on the dynamic wave model (Saint-Venant equations) inversion in space, wherein the momentum equation is replaced by a fuzzy rule based model, while retaining the continuity equation in its complete form. The fuzzy rule based model is developed on fuzzification of a new mathematical model for wave velocity, the derivational details of which are given. The advantages of the fuzzy control algorithm, over other conventional control algorithms, are described. It is transparent and intuitive, and no linearizations of the governing equations are involved. Timing of the algorithm and method of computation are explained. It is shown that the tuning is easy and the computations are straightforward. The algorithm provides stable, realistic and robust outputs. The disadvantage of the algorithm is reduced precision in its outputs due to the approximation inherent in the fuzzy logic. Feed back control logic is adopted to eliminate error caused by the system disturbances as well as error caused by the reduced precision in the outputs. The algorithm is tested by applying it to water level control problem in a fictitious canal with a single pool and also in a real canal with a series of pools. It is found that results obtained from the algorithm are comparable to those obtained from conventional control algorithms.

Indolic compounds in the leaves of Tecoma stans

Indole, tryptophan, tryptamine and skatole were isolated from the leaves of Tecoma stans. Anthranilic acid was also identified in its free form, in contrast to its glucoside, in Jasminum grandiflorum. The presence of both indole and anthranilic acid in the leaves of Tecoma stans indicates that they are the true substrate and product of indole oxygenase from the leaves of Tecoma stans.

On the Average Case Communication Complexity for Detection in Sensor Networks

The problem of sensor-network-based distributed intrusion detection in the presence of clutter is considered. It is argued that sensing is best regarded as a local phenomenon in that only sensors in the immediate vicinity of an intruder are triggered. In such a setting, lack of knowledge of intruder location gives rise to correlated sensor readings. A signal-space viewpoint is introduced in which the noise-free sensor readings associated to intruder and clutter appear as surfaces $\mathcal{S_I}$ and $\mathcal{S_C}$ and the problem reduces to one of determining in distributed fashion, whether the current noisy sensor reading is best classified as intruder or clutter. Two approaches to distributed detection are pursued. In the first, a decision surface separating $\mathcal{S_I}$ and $\mathcal{S_C}$ is identified using Neyman-Pearson criteria. Thereafter, the individual sensor nodes interactively exchange bits to determine whether the sensor readings are on one side or the other of the decision surface. Bounds on the number of bits needed to be exchanged are derived, based on communication complexity (CC) theory. A lower bound derived for the two-party average case CC of general functions is compared against the performance of a greedy algorithm. The average case CC of the relevant greater-than (GT) function is characterized within two bits. In the second approach, each sensor node broadcasts a single bit arising from appropriate two-level quantization of its own sensor reading, keeping in mind the fusion rule to be subsequently applied at a local fusion center. The optimality of a threshold test as a quantization rule is proved under simplifying assumptions. Finally, results from a QualNet simulation of the algorithms are presented that include intruder tracking using a naive polynomial-regression algorithm.

Performance analysis of a suprathreshold, stochastic resonance based nonlinear detector

In this paper we introduce a nonlinear detector based on the phenomenon of suprathreshold stochastic resonance (SSR). We first present a model (an array of 1-bit quantizers) that demonstrates the SSR phenomenon. We then use this as a pre-processor to the conventional matched filter. We employ the Neyman-Pearson(NP) detection strategy and compare the performances of the matched filter, the SSR-based detector and the optimal detector. Although the proposed detector is non-optimal, for non-Gaussian noises with heavy tails (leptokurtic) it shows better performance than the matched filter. In situations where the noise is known to be leptokurtic without the availability of the exact knowledge of its distribution, the proposed detector turns out to be a better choice than the matched filter.

Refinement of the thermodynamic properties of ruthenium dioxide and osmium dioxide

The standard Gibbs energies of formation of RuO2 and OsO2 at high temperature have been determined with high precision, using a novel apparatus that incorporates a buffer electrode between the reference and working electrodes, The buffer electrode absorbs the electrochemical flux of oxygen through the solid electrolyte from the electrode with higher oxygen chemical potential to the electrode with lower oxygen potential, The buffer electrode prevents polarization of the measuring electrode and ensures accurate data, The standard Gibbs energies of formation (Delta(f)G degrees) of RuO2, in the temperature range of 900-1500 K, and OsO2, in the range of 900-1200 K, can be represented by the equations Delta(f)G degrees(RuO2)(J/mol) = -324 720 + 354.21T - 23.490T In T Delta(f)G degrees(OsO2)(J/mol) = -304 740 + 318.80T - 18.444T In T where the temperature T is given in Kelvin and the deviation of the measurement is +/- 80 J/mol, The high-temperature heat ;capacities of RuO2 and OsO2 are measured using differential scanning calorimetry. The information for both the low- and high-temperature heat rapacity of RuO2 is coupled with the Delta(f)G degrees data obtained in this study to evaluate the standard enthalpy of formation of RuO2 at 298.15 K (Delta(f)H degrees(298.15K)). The low-temperature heat capacity of OsO2 has not been measured: therefore, the standard enthalpy and entropy of formation of OsO2 at 298.15 K (Delta(f)H degrees(298.15K) and S degrees(298.15K), respectively) are derived simultaneously through an optimization procedure from the high-temperature heat capacity and the Gibbs energy of formation. Both Delta fH degrees(298.15K) and S degrees(298.15K) are treated as variables in the optimization routine, For RuO2, the standard enthalpy of formation at 298.15 K is Delta fH degrees(298.15K) (RuO2) -313.52 +/- 0.08 kJ/mol, and that for OsO2 is Delta(f)H degrees(298.15K) (OSO2) = -295.96 +/- 0.08 kJ/mol. The standard entropy of OsO2 at 298.15 K that has been obtained from the optimization is given as S degrees(298.15K) (OsO2) = 49.8 +/- 0.2 J (mol K)(-1).

Nonlinear I-V characteristics of nanocrystalline SnO2

Current versus voltage characteristics (I-V) of nanocrystalline SnO2 materials have been investigated in air at room temperature. The samples were prepared by the inert gas condensation technique (IGCT) as well as by chemical methods. X-ray diffraction studies showed a tetragonal rutile structure for all the samples. Microstructural studies were performed with transmission electron microscopy. All the samples exhibited nonlinear I-V characteristics of the current-controlled negative resistance (CCNR) type. The results show that the threshold field (break down) voltage is higher for the samples prepared by the IGCT method than for those prepared by the chemical method due to the formation of a tin oxide layer over the crystalline tin. It is also found that the threshold field increases with the decrease in grain size.

Optimal Weighted Antenna Selection For Imperfect Channel Knowledge From Training

Receive antenna selection (AS) reduces the hardware complexity of multi-antenna receivers by dynamically connecting an instantaneously best antenna element to the available radio frequency (RF) chain. Due to the hardware constraints, the channels at various antenna elements have to be sounded sequentially to obtain estimates that are required for selecting the ``best'' antenna and for coherently demodulating data. Consequently, the channel state information at different antennas is outdated by different amounts. We show that, for this reason, simply selecting the antenna with the highest estimated channel gain is not optimum. Rather, the channel estimates of different antennas should be weighted differently, depending on the training scheme. We derive closed-form expressions for the symbol error probability (SEP) of AS for MPSK and MQAM in time-varying Rayleigh fading channels for arbitrary selection weights, and validate them with simulations. We then derive an explicit formula for the optimal selection weights that minimize the SEP. We find that when selection weights are not used, the SEP need not improve as the number of antenna elements increases, which is in contrast to the ideal channel estimation case. However, the optimal selection weights remedy this situation and significantly improve performance.

In vitro protection of umbilical cord blood-derived primitive hematopoietic stem progenitor cell pool by mannose-specific lectins via antioxidant mechanisms.

BACKGROUND: Earlier we reported that an oral administration of two mannose-specific dietary lectins, banana lectin (BL) and garlic lectin (GL), led to an enhancement of hematopoietic stem and progenitor cell (HSPC) pool in mice. STUDY DESIGN AND METHODS: Cord blood derived CD34+ HSPCs were incubated with BL, GL, Dolichos lectin (DL), or artocarpin lectin (AL) for various time periods in a serum- and growth factor free medium and were subjected to various functional assays. Reactive oxygen species (ROS) levels were detected by using DCHFDA method. Cell fractionation was carried out using lectin-coupled paramagnetic beads. RESULTS: CD34+ cells incubated with the lectins for 10 days gave rise to a significantly higher number of colonies compared to the controls, indicating that all four lectins possessed the capacity to protect HSPCs in vitro. Comparative analyses showed that the protective ability of BL and GL was better than AL and DL and, therefore, further experiments were carried out with them. The output of long-term culture-initiating cell (LTC-IC) and extended LTC-IC assays indicated that both BL and GL protected primitive stem cells up to 30 days. The cells incubated with BL or GL showed a substantial reduction in the ROS levels, indicating that these lectins protect the HSPCs via antioxidant mechanisms. The mononuclear cell fraction isolated by lectin-coupled beads got enriched for primitive HSPCs, as reflected in the output of phenotypic and functional assays.CONCLUSION: The data show that both BL and GL protect the primitive HSPCs in vitro and may also serve as cost-effective HSPC enrichment tools.