Khα1,2 hypersatellites of 3d transition metals and their photoexcitation energy dependence

Hollow atoms in which the K shell is empty while the outer shells are populated allow studying a variety of important and unusual properties of atoms. The diagram x-ray emission lines of such atoms, the K-h alpha(1,2) hypersatellites (HSs), were measured for the 3d transition metals, Z=23-30, with a high energy resolution using photoexcitation by monochromatized synchrotron radiation. Good agreement with ab initio relativistic multiconfigurational Dirac-Fock calculations was found. The measured HS intensity variation with the excitation energy yields accurate values for the excitation thresholds, excludes contributions from shake-up processes, and indicates domination near threshold of a nonshake process. The Z variation of the HS shifts from the diagram line K alpha(1,2), the K-h alpha(1)-K-h alpha(2) splitting, and the K-h alpha(1)/K-h alpha(2) intensity ratio, derived from the measurements, are also discussed with a particular emphasis on the QED corrections and Breit interaction.

Simulation and graph mining tools for improving gene mapping efficiency

Gene mapping is a systematic search for genes that affect observable characteristics of an organism. In this thesis we offer computational tools to improve the efficiency of (disease) gene-mapping efforts. In the first part of the thesis we propose an efficient simulation procedure for generating realistic genetical data from isolated populations. Simulated data is useful for evaluating hypothesised gene-mapping study designs and computational analysis tools. As an example of such evaluation, we demonstrate how a population-based study design can be a powerful alternative to traditional family-based designs in association-based gene-mapping projects. In the second part of the thesis we consider a prioritisation of a (typically large) set of putative disease-associated genes acquired from an initial gene-mapping analysis. Prioritisation is necessary to be able to focus on the most promising candidates. We show how to harness the current biomedical knowledge for the prioritisation task by integrating various publicly available biological databases into a weighted biological graph. We then demonstrate how to find and evaluate connections between entities, such as genes and diseases, from this unified schema by graph mining techniques. Finally, in the last part of the thesis, we define the concept of reliable subgraph and the corresponding subgraph extraction problem. Reliable subgraphs concisely describe strong and independent connections between two given vertices in a random graph, and hence they are especially useful for visualising such connections. We propose novel algorithms for extracting reliable subgraphs from large random graphs. The efficiency and scalability of the proposed graph mining methods are backed by extensive experiments on real data. While our application focus is in genetics, the concepts and algorithms can be applied to other domains as well. We demonstrate this generality by considering coauthor graphs in addition to biological graphs in the experiments.

Dominant role of the Cu---O charge-transfer energy, electronic polarizability and associated factors in the superconductivity of cuprates

Although it is believed that there is strong hybridization between the Cu(3d) and O(2p) orbitals in the layered cuprates and that the parent compounds such as La2CuO4 are charge-transfer gap insulators, very few models consider the Cu---O charge-transfer energy, Δ, or the hybridization strength, tpd, to be the important factors responsible for the superconductivity of these materials. Based on the crucial experimental observation that the relative intensity of the features in Cu(2p) photoemission of several families of cuprates varies systematically with the hole concentration, nh, we have been able to show that both these properties vary smoothly with Δ /tpd. More importantly, we show that the electronic polarizability of the CuO2 sheets, α , is sufficiently large to favour hole pairing and that the value α also depends on Δ/tpd. Both nh and α increase smoothly with decreasing Δ /tpd. Considering that the maximum Tc in the various cuprate families containing the same number of CuO2 sheets occurs around the same nh value (e.g., nh≈ 0.2 in cuprates with two CuO2 sheets). The present study demonstrates how Δ /tpd, α and such chemical bonding characteristics have an important bearing on the superconducting properties of the cuprates.

Effect of stacking fault energy on the dynamic recrystallization during hot working of FCC metals: A study using processing maps

The influence of stacking fault energy (SFE) on the mechanism of dynamic recrystallization (DRX) during hot deformation of FCC metals is examined in the light of results from the power dissipation maps. The DRX domain for high SFE metals like Al and Ni occurred at homologous temperature below 0·7 and strain rates of 0·001 s−1 while for low SFE metals like Cu and Pb the corresponding values are higher than 0·8 and 100 s−1. The peak efficiencies of power dissipation are 50% and below 40% respectively. A simple model which considers the rate of interface formation (nucleation) involving dislocation generation and simultaneous recovery and the rate of interface migration (growth) occurring with the reduction in interface energy as the driving force, has been proposed to account for the effect of SFE on DRX. The calculations reveal that in high SFE metals, interface migration controls DRX while the interface formation is the controlling factor in low SFE metals. In the latter case, the occurrence of flow softening and oscillations could be accounted for by this model.

Madelung energy and hole location in YBa2Cu4O8

The Madelung energy of YBa2Cu4O8 has been computed for different locations of the hole in the structure. The lowest-energy configuration corresponds to partial localization of the hole on O(1) and O(11) sites.

A Novel, Balanced, and Energy-Efficient Training Method for Receive Antenna Selection

In receive antenna selection (AS), only signals from a subset of the antennas are processed at any time by the limited number of radio frequency (RF) chains available at the receiver. Hence, the transmitter needs to send pilots multiple times to enable the receiver to estimate the channel state of all the antennas and select the best subset. Conventionally, the sensitivity of coherent reception to channel estimation errors has been tackled by boosting the energy allocated to all pilots to ensure accurate channel estimates for all antennas. Energy for pilots received by unselected antennas is mostly wasted, especially since the selection process is robust to estimation errors. In this paper, we propose a novel training method uniquely tailored for AS that transmits one extra pilot symbol that generates accurate channel estimates for the antenna subset that actually receives data. Consequently, the transmitter can selectively boost the energy allocated to the extra pilot. We derive closed-form expressions for the proposed scheme's symbol error probability for MPSK and MQAM, and optimize the energy allocated to pilot and data symbols. Through an insightful asymptotic analysis, we show that the optimal solution achieves full diversity and is better than the conventional method.

Energy efficiency in India: Assessing the policy regimes and their impacts

In the recent years. India has emerged as one of the fast growing economies of the world necessitating equally rapid increase in modern energy consumption. With an imminent global climate change threat, India will have difficulties in continuing with this rising energy use levels towards achieving high economic growth. It will have to follow an energy-efficient pathway in attaining this goal. In this context, an attempt is made to present India's achievements on the energy efficiency front by tracing the evolution of policies and their impacts. The results indicate that India has made substantial progress in improving energy efficiency which is evident from the reductions achieved in energy intensities of GDP to the tune of 88% during 1980-2007. Similar reductions have been observed both with respect to overall Indian economy and the major sectors of the economy. In terms of energy intensity of GDP, India occupies a relatively high position of nine among the top 30 energy consuming countries of the world. (C) 2009 Elsevier Ltd. All rights reserved.

Energy efficient asymmetric binary search switching technique for SAR ADC

An asymmetric binary search switching technique for a successive approximation register (SAR) ADC is presented, and trade-off between switching energy and conversion cycles is discussed. Without using any additional switches, the proposed technique consumes 46% less switching energy, for a small input swing (0.5 V-ref (P-P)), as compared to the last reported efficient switching technique in literature for an 8-bit SAR ADC. For a full input swing (2 V-ref (P-P)), the proposed technique consumes 16.5% less switching energy.

Optimisation problems in wireless sensor networks

This thesis studies optimisation problems related to modern large-scale distributed systems, such as wireless sensor networks and wireless ad-hoc networks. The concrete tasks that we use as motivating examples are the following: (i) maximising the lifetime of a battery-powered wireless sensor network, (ii) maximising the capacity of a wireless communication network, and (iii) minimising the number of sensors in a surveillance application. A sensor node consumes energy both when it is transmitting or forwarding data, and when it is performing measurements. Hence task (i), lifetime maximisation, can be approached from two different perspectives. First, we can seek for optimal data flows that make the most out of the energy resources available in the network; such optimisation problems are examples of so-called max-min linear programs. Second, we can conserve energy by putting redundant sensors into sleep mode; we arrive at the sleep scheduling problem, in which the objective is to find an optimal schedule that determines when each sensor node is asleep and when it is awake. In a wireless network simultaneous radio transmissions may interfere with each other. Task (ii), capacity maximisation, therefore gives rise to another scheduling problem, the activity scheduling problem, in which the objective is to find a minimum-length conflict-free schedule that satisfies the data transmission requirements of all wireless communication links. Task (iii), minimising the number of sensors, is related to the classical graph problem of finding a minimum dominating set. However, if we are not only interested in detecting an intruder but also locating the intruder, it is not sufficient to solve the dominating set problem; formulations such as minimum-size identifying codes and locating–dominating codes are more appropriate. This thesis presents approximation algorithms for each of these optimisation problems, i.e., for max-min linear programs, sleep scheduling, activity scheduling, identifying codes, and locating–dominating codes. Two complementary approaches are taken. The main focus is on local algorithms, which are constant-time distributed algorithms. The contributions include local approximation algorithms for max-min linear programs, sleep scheduling, and activity scheduling. In the case of max-min linear programs, tight upper and lower bounds are proved for the best possible approximation ratio that can be achieved by any local algorithm. The second approach is the study of centralised polynomial-time algorithms in local graphs – these are geometric graphs whose structure exhibits spatial locality. Among other contributions, it is shown that while identifying codes and locating–dominating codes are hard to approximate in general graphs, they admit a polynomial-time approximation scheme in local graphs.

A Deterministic Optimization Approach to Protein Sequence Design Using Continuous Models

Determining the sequence of amino acid residues in a heteropolymer chain of a protein with a given conformation is a discrete combinatorial problem that is not generally amenable for gradient-based continuous optimization algorithms. In this paper we present a new approach to this problem using continuous models. In this modeling, continuous "state functions" are proposed to designate the type of each residue in the chain. Such a continuous model helps define a continuous sequence space in which a chosen criterion is optimized to find the most appropriate sequence. Searching a continuous sequence space using a deterministic optimization algorithm makes it possible to find the optimal sequences with much less computation than many other approaches. The computational efficiency of this method is further improved by combining it with a graph spectral method, which explicitly takes into account the topology of the desired conformation and also helps make the combined method more robust. The continuous modeling used here appears to have additional advantages in mimicking the folding pathways and in creating the energy landscapes that help find sequences with high stability and kinetic accessibility. To illustrate the new approach, a widely used simplifying assumption is made by considering only two types of residues: hydrophobic (H) and polar (P). Self-avoiding compact lattice models are used to validate the method with known results in the literature and data that can be practically obtained by exhaustive enumeration on a desktop computer. We also present examples of sequence design for the HP models of some real proteins, which are solved in less than five minutes on a single-processor desktop computer Some open issues and future extensions are noted.

Head-on infall of two compact objects: Third post-Newtonian energy flux

Head-on infall of two compact objects with arbitrary mass ratio is investigated using the multipolar post-Minkowskian approximation method. At the third post-Newtonian order the energy flux, in addition to the instantaneous contributions, also includes hereditary contributions consisting of the gravitational-wave tails, tails-of-tails, and the tail-squared terms. The results are given both for infall from infinity and also for infall from a finite distance. These analytical expressions should be useful for the comparison with the high accuracy numerical relativity results within the limit in which post-Newtonian approximations are valid.

Voluntary Energy Harvesting Relays and Selection in Cooperative Wireless Networks

The use of energy harvesting (EH) nodes as cooperative relays is a promising and emerging solution in wireless systems such as wireless sensor networks. It harnesses the spatial diversity of a multi-relay network and addresses the vexing problem of a relay's batteries getting drained in forwarding information to the destination. We consider a cooperative system in which EH nodes volunteer to serve as amplify-and-forward relays whenever they have sufficient energy for transmission. For a general class of stationary and ergodic EH processes, we introduce the notion of energy constrained and energy unconstrained relays and analytically characterize the symbol error rate of the system. Further insight is gained by an asymptotic analysis that considers the cases where the signal-to-noise-ratio or the number of relays is large. Our analysis quantifies how the energy usage at an EH relay and, consequently, its availability for relaying, depends not only on the relay's energy harvesting process, but also on its transmit power setting and the other relays in the system. The optimal static transmit power setting at the EH relays is also determined. Altogether, our results demonstrate how a system that uses EH relays differs in significant ways from one that uses conventional cooperative relays.

Hybrid Solar Cooking

In the existing traditional solar cookers, the cooking is performed near the collector which may be at an inconvenient location for cooking purposes. This paper proposes a hybrid solar cooking system where the solar energy is brought to the kitchen. The energy source is a combination of the solar thermal energy and the Liquefied Petroleum Gas (LPG) that is very common in kitchens. The solar thermal energy is transferred to the kitchen by means of a circulating fluid like oil. The transfer of solar heat is a two fold process wherein the energy from the collector is transferred first to an intermediate energy storage tank and then the energy is subsequently transferred from the tank to the cooking load. There are three parameters that are controlled in order to maximize the energy transfer from the collector to the load viz. the fluid flow rate from collector to tank, fluid flow rate from tank to load and the diameter of the pipes. The entire system is modeled using the bond graph approach. This paper discusses the implementation of such a system.