Energy-dependence of nitrate reductase induction in Candida-Utilis

The requirement of a suitable energy source during the induced synthesis of nitrate reductase in Image was investigated. The levels of nitrate reductase induced were shown to be energy-dependent, and to vary in response to the type of carbon source provided. Glycerol, fructose, ethanol, glucose, and sucrose served as efficient energy sources. Growth rate of the yeast and the induced level of nitrate reductase were dependent on the ratio of carbon to nitrogen in the induction medium, and ratio of 2 being optimal. Induction of nitrate reductase was inhibited by uncouplers, 2,4-dinitrophenol (DNP), dicumarol and carbonyl cyanide Candida-Utilis -trifluoromethoxy phenyl hydrazone (CCCP), and by cyanide and azide, indicating an absolute energy-dependency. The facilitation of induction of a high level of nitrate reductase by exogenously added ATP as sole source of energy confirmed the obligate requirement of ATP for the synthesis of nitrate reductase in Candida-Utilis.

Metallo crown porphyrins as ionophores-metal dependent uncoupling of mitochondrial energy potential

Porphyrins appended with crown ether moieties function as efficient uncouplesrs of oxidative phorphorylation in rat liver mitochondria. Permeation of these highly organized porphyrins decrease the respiratory coefficient index (RCI) values. Lowering of the RCI values parallels the number of K+ chelating crown ether groups attached to the porphyrins. The inhibitory effect upon the oxidative phorphorylation reaction depends on the nature of divalent metal ions, VO, Co, Cu and Zn in the porphyrin cavity and related to their relative tendency to complex intracellular K+ ions.

A design approach to innovation in the Australian energy industry

Electricity businesses across Australia are facing many market disruptions, such as the increasing demand from the rapid uptake of domestic air conditioners and the contrasting problematic generation from solar power connections to the grid. In this context, the opportunity to proactively leverage forthcoming technological advances in battery storage and electric vehicles to address the steeply rising cost of electricity supply has emerged. This research explores a design approach to support a business to navigate such disruptions in the current market.This study examines a design-led approach to innovation conducted over a ten month action research study within a large, risk-averse firm in the Australian energy sector. This article presents results describing a current foresight gap within the business; the response of the business to using design-led innovation to address this issue; and the tools, approaches and processes used. The business responses indicate their perception of the value of qualitative customer engagement as a path to addressing, and potentially benefiting from, disruptive innovation. It is anticipated that these results will further business model development within the company, and assist in leveraging disruptive innovations for this industry participant, thus limiting future increases in the cost of electricity supply for customers in Australia.

Metallo crown porphyrins as ionophores-metal dependent uncoupling of mitochondrial energy potential

Porphyrins appended with crown ether moieties function as efficient uncouplesrs of oxidative phorphorylation in rat liver mitochondria. Permeation of these highly organized porphyrins decrease the respiratory coefficient index (RCI) values. Lowering of the RCI values parallels the number of K+ chelating crown ether groups attached to the porphyrins. The inhibitory effect upon the oxidative phorphorylation reaction depends on the nature of divalent metal ions, VO, Co, Cu and Zn in the porphyrin cavity and related to their relative tendency to complex intracellular K+ ions.

Efficient eucalypt cell wall deconstruction and conversion for sustainable lignocellulosic biofuels

In order to meet the world’s growing energy demand and reduce the impact of greenhouse gas emissions resulting from fossil fuel combustion, renewable plant-based feedstocks for biofuel production must be considered. The first-generation biofuels, derived from starches of edible feedstocks, such as corn, create competition between food and fuel resources, both for the crop itself and the land on which it is grown. As such, biofuel synthesized from non-edible plant biomass (lignocellulose) generated on marginal agricultural land will help to alleviate this competition. Eucalypts, the broadly defined taxa encompassing over 900 species of Eucalyptus, Corymbia, and Angophora are the most widely planted hardwood tree in the world, harvested mainly for timber, pulp and paper, and biomaterial products. More recently, due to their exceptional growth rate and amenability to grow under a wide range of environmental conditions, eucalypts are a leading option for the development of a sustainable lignocellulosic biofuels. However, efficient conversion of woody biomass into fermentable monomeric sugars is largely dependent on pretreatment of the cell wall, whose formation and complexity lend itself toward natural recalcitrance against its efficient deconstruction. A greater understanding of this complexity within the context of various pretreatments will allow the design of new and effective deconstruction processes for bioenergy production. In this review, we present the various pretreatment options for eucalypts, including research into understanding structure and formation of the eucalypt cell wall.

Efficient probabilistic contingency analysis through a stability measure considering wind perturbation

The integration of stochastic wind power has accentuated a challenge for power system stability assessment. Since the power system is a time-variant system under wind generation fluctuations, pure time-domain simulations are difficult to provide real-time stability assessment. As a result, the worst-case scenario is simulated to give a very conservative assessment of system transient stability. In this study, a probabilistic contingency analysis through a stability measure method is proposed to provide a less conservative contingency analysis which covers 5-min wind fluctuations and a successive fault. This probabilistic approach would estimate the transfer limit of a critical line for a given fault with stochastic wind generation and active control devices in a multi-machine system. This approach achieves a lower computation cost and improved accuracy using a new stability measure and polynomial interpolation, and is feasible for online contingency analysis.

A Search for Energy Minimized Sequences of Proteins

In this paper, we present numerical evidence that supports the notion of minimization in the sequence space of proteins for a target conformation. We use the conformations of the real proteins in the Protein Data Bank (PDB) and present computationally efficient methods to identify the sequences with minimum energy. We use edge-weighted connectivity graph for ranking the residue sites with reduced amino acid alphabet and then use continuous optimization to obtain the energy-minimizing sequences. Our methods enable the computation of a lower bound as well as a tight upper bound for the energy of a given conformation. We validate our results by using three different inter-residue energy matrices for five proteins from protein data bank (PDB), and by comparing our energy-minimizing sequences with 80 million diverse sequences that are generated based on different considerations in each case. When we submitted some of our chosen energy-minimizing sequences to Basic Local Alignment Search Tool (BLAST), we obtained some sequences from non-redundant protein sequence database that are similar to ours with an E-value of the order of 10(-7). In summary, we conclude that proteins show a trend towards minimizing energy in the sequence space but do not seem to adopt the global energy-minimizing sequence. The reason for this could be either that the existing energy matrices are not able to accurately represent the inter-residue interactions in the context of the protein environment or that Nature does not push the optimization in the sequence space, once it is able to perform the function.

A Nonlinear Approach for Re-entry Guidance of Reusable Launch Vehicles Using Model Predictive Static Programming

A nonlinear suboptimal guidance scheme is developed for the reentry phase of the reusable launch vehicles. A recently developed methodology, named as model predictive static programming (MPSP), is implemented which combines the philosophies of nonlinear model predictive control theory and approximate dynamic programming. This technique provides a finite time nonlinear suboptimal guidance law which leads to a rapid solution of the guidance history update. It does not have to suffer from computational difficulties and can be implemented online. The system dynamics is propagated through the flight corridor to the end of the reentry phase considering energy as independent variable and angle of attack as the active control variable. All the terminal constraints are satisfied. Among the path constraints, the normal load is found to be very constrictive. Hence, an extra effort has been made to keep the normal load within a specified limit and monitoring its sensitivity to the perturbation.

Single atom (Pd/Pt) supported on graphitic carbon nitride as efficient photocatalyst for visible-light reduction of carbon dioxide

Reducing carbon dioxide (CO2) to hydrocarbon fuel with solar energy is significant for high-density solar energy storage and carbon balance. In this work, single palladium/platinum (Pd/Pt) atoms supported on graphitic carbon nitride (g-C3N4), i.e. Pd/g-C3N4 and Pt/g-C3N4, acting as photocatalysts for CO2 reduction were investigated by density function theory (DFT) calcu-lations for the first time. During CO2 reduction, the individual metal atoms function as the active sites, while g-C3N4 provides the source of hydrogen (H*) from hydrogen evolution reaction. The complete, as-designed photocatalysts exhibit excellent activity in CO2 reduction. HCOOH is the preferred product of CO2 reduction on the Pd/g-C3N4 catalyst with a rate-determining barrier of 0.66 eV, while the Pt/g-C3N4 catalyst prefers to reduce CO2 to CH4 with a rate-determining barrier of 1.16 eV. In addition, depositing atom catalysts on g-C3N4 significantly enhances the visible light absorption, rendering them ideal for visible light reduction of CO2. Our findings open a new avenue of CO2 reduction for renewable energy supply.

Two-Phase Thermodynamic Model for Efficient and Accurate Absolute Entropy of Water from Molecular Dynamics Simulations

Presented here is the two-phase thermodynamic (2PT) model for the calculation of energy and entropy of molecular fluids from the trajectory of molecular dynamics (MD) simulations. In this method, the density of state (DoS) functions (including the normal modes of translation, rotation, and intramolecular vibration motions) are determined from the Fourier transform of the corresponding velocity autocorrelation functions. A fluidicity parameter (f), extracted from the thermodynamic state of the system derived from the same MD, is used to partition the translation and rotation modes into a diffusive, gas-like component (with 3Nf degrees of freedom) and a nondiffusive, solid-like component. The thermodynamic properties, including the absolute value of entropy, are then obtained by applying quantum statistics to the solid component and applying hard sphere/rigid rotor thermodynamics to the gas component. The 2PT method produces exact thermodynamic properties of the system in two limiting states: the nondiffusive solid state (where the fluidicity is zero) and the ideal gas state (where the fluidicity becomes unity). We examine the 2PT entropy for various water models (F3C, SPC, SPC/E, TIP3P, and TIP4P-Ew) at ambient conditions and find good agreement with literature results obtained based on other simulation techniques. We also validate the entropy of water in the liquid and vapor phases along the vapor-liquid equilibrium curve from the triple point to the critical point. We show that this method produces converged liquid phase entropy in tens of picoseconds, making it an efficient means for extracting thermodynamic properties from MD simulations.

A Wavelet based Teager Energy Operator for Spike Detection in Microelectrode Array Recordings

Spike detection in neural recordings is the initial step in the creation of brain machine interfaces. The Teager energy operator (TEO) treats a spike as an increase in the `local' energy and detects this increase. The performance of TEO in detecting action potential spikes suffers due to its sensitivity to the frequency of spikes in the presence of noise which is present in microelectrode array (MEA) recordings. The multiresolution TEO (mTEO) method overcomes this shortcoming of the TEO by tuning the parameter k to an optimal value m so as to match to frequency of the spike. In this paper, we present an algorithm for the mTEO using the multiresolution structure of wavelets along with inbuilt lowpass filtering of the subband signals. The algorithm is efficient and can be implemented for real-time processing of neural signals for spike detection. The performance of the algorithm is tested on a simulated neural signal with 10 spike templates obtained from [14]. The background noise is modeled as a colored Gaussian random process. Using the noise standard deviation and autocorrelation functions obtained from recorded data, background noise was simulated by an autoregressive (AR(5)) filter. The simulations show a spike detection accuracy of 90%and above with less than 5% false positives at an SNR of 2.35 dB as compared to 80% accuracy and 10% false positives reported [6] on simulated neural signals.

Multi power port converter for hybrid electric vehicles using multi phase bidirectional fly-back topology

For hybrid electric vehicles the batteries and the drive dc-link may be at different voltages. The batteries are at low voltage to obtain higher volumetric efficiencies and the dc-link is at higher voltage to have higher efficiency on the motor side. Therefore a power interface between the batteries and the drive's dc-link is essential. This power interface should handle power flow from battery to motor, motor to battery, external genset to battery and grid to battery. This paper proposes a multi power port topology which is capable of handling multiple power sources and still maintains simplicity and features like obtaining any gain, wide load variations, lower output current ripple and capability of parallel battery energy due to the modular structure. The development and testing of a bi-directional fly-back DC-DC converter for hybrid electric vehicle is described in this paper. Simple hysteresis voltage control is used for DC link voltage regulation. The experimental results are presented to show the working of the proposed converter.

Photophysics of conjugated polymers: interplay between Forster energy migration and defect concentration in shaping a photochemical funnel in PPV

Recent single molecule experiments have suggested the existence of a photochemical funnel in the photophysics of conjugated polymers, like poly[2-methoxy-5-(2'-ethylhexyl)oxy-1,4-phenylenevinylene] (MEH-PPV). The funnel is believed to be a consequence of the presence of conformational or chemical defects along the polymer chain and efficient non-radiative energy transfer among different chromophore segments. Here we address the effect of the excitation energy dynamics on the photophysics of PPV. The PPV chain is modeled as a polymer with the length distribution of chromophores given either by a Gaussian or by a Poisson distribution. We observe that the Poisson distribution of the segment lengths explains the photophysics of PPV better than the Gaussian distribution. A recently proposed version of an extended particle-in-a-box' model is used to calculate the exciton energies and the transition dipole moments of the chromophores, and a master equation to describe the excitation energy transfer among different chromophores. The rate of energy transfer is assumed to be given here, as a first approximation, by the well-known Forster expression. The observed excitation population dynamics confirms the photochemical funneling of excitation energy from shorter to longer chromophores of the polymer chain. The time scale of spectral shift and energy transfer for our model polymer, with realistic values of optical parameters, is in the range of 200-300 ps. We find that the excitation energy may not always migrate towards the longest chromophore segments in the polymer chain as the efficiency of energy transfer between chromophores depends on the separation distance between the two and their relative orientation.

Joint Power Control, Scheduling and Routing for Multihop Energy Harvesting Sensor Networks

We study wireless multihop energy harvesting sensor networks employed for random field estimation. The sensors sense the random field and generate data that is to be sent to a fusion node for estimation. Each sensor has an energy harvesting source and can operate in two modes: Wake and Sleep. We consider the problem of obtaining jointly optimal power control, routing and scheduling policies that ensure a fair utilization of network resources. This problem has a high computational complexity. Therefore, we develop a computationally efficient suboptimal approach to obtain good solutions to this problem. We study the optimal solution and performance of the suboptimal approach through some numerical examples.

Pd Supported on Titanium Nitride for Efficient Ethanol Oxidation

The excellent metal support interaction between palladium (Pd) and titanium nitride (TiN) is exploited in designing an efficient anode material. Pd-TN, that could be useful for direct ethanol fuel cell in alkaline media. The physicochemical and electrochemical characterization of the Pd-TiN/electrolyte interface reveals an efficient oxidation of ethanol coupled with excellent stability of the catalyst under electrochemical conditions. Characterization of the interface using in situ Fourier transform infrared spectroscopy (in situ FITR) shows the production CO2 at low overvoltages revealing an efficient cleaving of the C-C bond. The performance comparison of Pd supported on TiN (Pd-TiN) with that supported on carbon (Pd-C) clearly demonstrates the advantages of TiN support over carbon. A positive chemical shift of Pd (3d) binding energy confirms the existence of metal support interaction between pd and TiN, which in turn helps weaken the Pd-CO synergetic bonding interaction. The remarkable ability of TiN to accumulate -OH species on its surface coupled with the strong adhesion of Pd makes TiN an active support material for electrocatalysts.