First-principles study on rutile TiO2 quantum dots

The electronic structure of rutile TiO2 quantum dots (QDs) are investigated via the first-principles band structure method. We first propose a model to passivate the rutile TiO2 surfaces for the local density approximation calculations. In this model pseudohydrogen atoms are used to passivate the surface dangling bonds, which remove the localized in-cap surface states in the TiO2 QDs. As the size of the QD decreases, the band gap evolves as E-g(dot) = E-g(bulk) + 73.70/d(1.93), where E-g(dot) and d are the band gap and diameter of the QD, and E-g(bulk) is the band gap of the bulk rutile TiO2. The valence band maximum and the conduction band minimum states of the QDs are distributed mostly in the interior of the QDs, and they well inherit the atomic characteristics of those states of the bulk rutile TiO2.

Band-gap bowing and p-type doping of (Zn, Mg, Be)O wide-gap semiconductor alloys: a first-principles study

Using a first-principles band-structure method and a special quasirandom structure (SQS) approach, we systematically calculate the band gap bowing parameters and p-type doping properties of (Zn, Mg, Be)O related random ternary and quaternary alloys. We show that the bowing parameters for ZnBeO and MgBeO alloys are large and dependent on composition. This is due to the size difference and chemical mismatch between Be and Zn(Mg) atoms. We also demonstrate that adding a small amount of Be into MgO reduces the band gap indicating that the bowing parameter is larger than the band-gap difference. We select an ideal N atom with lower p atomic energy level as dopant to perform p-type doping of ZnBeO and ZnMgBeO alloys. For N doped in ZnBeO alloy, we show that the acceptor transition energies become shallower as the number of the nearest neighbor Be atoms increases. This is thought to be because of the reduction of p-d repulsion. The N-O acceptor transition energies are deep in the ZnMgBeO quaternary alloy lattice-matched to GaN substrate due to the lower valence band maximum. These decrease slightly as there are more nearest neighbor Mg atoms surrounding the N dopant. The important natural valence band alignment between ZnO, MgO, BeO, ZnBeO, and ZnMgBeO quaternary alloy is also investigated.

Trends in elasticity and electronic structure of 5d transition metal diborides: first-principles calculations

We investigate the cohesive energy, heat of formation, elastic constant and electronic band structure of transition metal diborides TMB2 (TM = Hf, Ta, W, Re, Os and Ir, Pt) in the Pmmn space group using the ab initio pseudopotential total energy method. Our calculations indicate that there is a relationship between elastic constant and valence electron concentration (VEC): the bulk modulus and shear modulus achieve their maximum when the VEC is in the range of 6.8-7.2. In addition, trends in the elastic constant are well explained in terms of electronic band structure analysis, e.g., occupation of valence electrons in states near the Fermi level, which determines the cohesive energy and elastic properties. The maximum in bulk modulus and shear modulus is attributed to the nearly complete filling of TM d-B p bonding states without filling the antibonding states. On the basis of the observed relationship, we predict that alloying W and Re in the orthorhombic structure OsB2 might be harder than alloying the Ir element. Indeed, the further calculations confirmed this expectation.

Neuromuscular-skeletal constraints on the acquisition of skill in a discrete torque production task

The organisation of the human neuromuscular-skeletal system allows an extremely wide variety of actions to be performed, often with great dexterity. Adaptations associated with skill acquisition occur at all levels of the neuromuscular-skeletal system although all neural adaptations are inevitably constrained by the organisation of the actuating apparatus (muscles and bones). We quantified the extent to which skill acquisition in an isometric task set is influenced by the mechanical properties of the muscles used to produce the required actions. Initial performance was greatly dependent upon the specific combination of torques required in each variant of the experimental task. Five consecutive days of practice improved the performance to a similar degree across eight actions despite differences in the torques required about the elbow and forearm. The proportional improvement in performance was also similar when the actions were performed at either 20 or 40% of participants' maximum voluntary torque capacity. The skill acquired during practice was successfully extrapolated to variants of the task requiring more torque than that required during practice. We conclude that while the extent to which skill can be acquired in isometric actions is independent of the specific combination of joint torques required for target acquisition, the nature of the kinetic adaptations leading to the performance improvement in isometric actions is influenced by the neural and mechanical properties of the actuating muscles.

Maximum Outage Capacity in Dense Indoor Femtocell Networks with Joint Energy and Spectrum Utilization

We consider a multiple femtocell deployment in a small area which shares spectrum with the underlaid macrocell. We design a joint energy and radio spectrum scheme which aims not only for co-existence with the macrocell, but also for an energy-efficient implementation of the multi-femtocells. Particularly, aggregate energy usage on dense femtocell channels is formulated taking into account the cost of both the spectrum and energy usage. We investigate an energy-and-spectral efficient approach to balance between the two costs by varying the number of active sub-channels and their energy. The proposed scheme is addressed by deriving closed-form expressions for the interference towards the macrocell and the outage capacity. Analytically, discrete regions under which the most promising outage capacity is achieved by the same size of active sub-channels are introduced. Through a joint optimization of the sub-channels and their energy, properties can be found for the maximum outage capacity under realistic constraints. Using asymptotic and numerical analysis, it can be noticed that in a dense femtocell deployment, the optimum utilization of the energy and the spectrum to maximize the outage capacity converges towards a round-robin scheduling approach for a very small outage threshold. This is the inverse of the traditional greedy approach. © 2012 IEEE.

Endocrine Surgery: Principles and Practice:adrenal chapter

The paired adrenal (suprarenal) glands are flattened retroperitoneal endocrine glands closely applied to the medial aspect of the superior pole of each kidney. The internal structure of these pale yellow glands are incongruous in that the adrenal gland is composed of two discrete parts, namely an outer cortex enveloping a central medulla. The adrenal cortex and medulla contain distinct endocrine tissues that secrete different hormones and are regulated by separate control systems.

Experimental and discrete element modelling of cohesive iron ore fines

In this study, the behaviour of iron ore fines with varying levels of adhesion was investigated using a confined compression test and a uniaxial test. The uniaxial test was conducted using the semi-automated uniaxial EPT tester in which the cohesive strength of a bulk solid is evaluated from an unconfined compression test following a period of consolidation to a pre-defined vertical stress. The iron ore fines were also tested by measuring both the vertical and circumferential strains on the cylindrical container walls under vertical loading in a separate confined compression tester - the K0 tester, to determine the lateral pressure ratio. Discrete Element Method simulations of both experiments were carried out and the predictions were compared with the experimental observations. A recently developed DEM contact model for cohesive solids, an Elasto-Plastic Adhesive model, was used. This particle contact model uses hysteretic non-linear loading and unloading paths and an adhesion parameter which is a function of the maximum contact overlap. The model parameters for the simulations are phenomenologically based to reproduce the key bulk characteristics exhibited by the solid. The simulation results show a good agreement in capturing the stress history dependent behaviour depicted by the flow function of the cohesive iron ore fines while also providing a reasonably good match for the lateral pressure ratio observed during the confined compression K0 tests. This demonstrates the potential for the DEM model to be used in the simulation of bulk handling applications.

Automated design of microwave discrete tuning differential capacitance circuits in Si-integrated technologies

A genetic algorithm used to design radio-frequency binary-weighted differential switched capacitor arrays (RFDSCAs) is presented in this article. The algorithm provides a set of circuits all having the same maximum performance. This article also describes the design, implementation, and measurements results of a 0.25 lm BiCMOS 3-bit RFDSCA. The experimental results show that the circuit presents the expected performance up to 40 GHz. The similarity between the evolutionary solutions, circuit simulations, and measured results indicates that the genetic synthesis method is a very useful tool for designing optimum performance RFDSCAs.

Automated synthesis procedure of RF discrete tuning differential capacitance circuits

The paper presents a RFDSCA automated synthesis procedure. This algorithm determines several RFDSCA circuits from the top-level system specifications all with the same maximum performance. The genetic synthesis tool optimizes a fitness function proportional to the RFDSCA quality factor and uses the epsiv-concept and maximin sorting scheme to achieve a set of solutions well distributed along a non-dominated front. To confirm the results of the algorithm, three RFDSCAs were simulated in SpectreRF and one of them was implemented and tested. The design used a 0.25 mum BiCMOS process. All the results (synthesized, simulated and measured) are very close, which indicate that the genetic synthesis method is a very useful tool to design optimum performance RFDSCAs.

Revisiting optimization algorithms for maximum likelihood estimation

Parmi les méthodes d’estimation de paramètres de loi de probabilité en statistique, le maximum de vraisemblance est une des techniques les plus populaires, comme, sous des conditions l´egères, les estimateurs ainsi produits sont consistants et asymptotiquement efficaces. Les problèmes de maximum de vraisemblance peuvent être traités comme des problèmes de programmation non linéaires, éventuellement non convexe, pour lesquels deux grandes classes de méthodes de résolution sont les techniques de région de confiance et les méthodes de recherche linéaire. En outre, il est possible d’exploiter la structure de ces problèmes pour tenter d’accélerer la convergence de ces méthodes, sous certaines hypothèses. Dans ce travail, nous revisitons certaines approches classiques ou récemment d´eveloppées en optimisation non linéaire, dans le contexte particulier de l’estimation de maximum de vraisemblance. Nous développons également de nouveaux algorithmes pour résoudre ce problème, reconsidérant différentes techniques d’approximation de hessiens, et proposons de nouvelles méthodes de calcul de pas, en particulier dans le cadre des algorithmes de recherche linéaire. Il s’agit notamment d’algorithmes nous permettant de changer d’approximation de hessien et d’adapter la longueur du pas dans une direction de recherche fixée. Finalement, nous évaluons l’efficacité numérique des méthodes proposées dans le cadre de l’estimation de modèles de choix discrets, en particulier les modèles logit mélangés.

Comparison of extrasystolic ECG signal classifiers using discrete wavelet transforms

This work compares and contrasts results of classifying time-domain ECG signals with pathological conditions taken from the MITBIH arrhythmia database. Linear discriminant analysis and a multi-layer perceptron were used as classifiers. The neural network was trained by two different methods, namely back-propagation and a genetic algorithm. Converting the time-domain signal into the wavelet domain reduced the dimensionality of the problem at least 10-fold. This was achieved using wavelets from the db6 family as well as using adaptive wavelets generated using two different strategies. The wavelet transforms used in this study were limited to two decomposition levels. A neural network with evolved weights proved to be the best classifier with a maximum of 99.6% accuracy when optimised wavelet-transform ECG data wits presented to its input and 95.9% accuracy when the signals presented to its input were decomposed using db6 wavelets. The linear discriminant analysis achieved a maximum classification accuracy of 95.7% when presented with optimised and 95.5% with db6 wavelet coefficients. It is shown that the much simpler signal representation of a few wavelet coefficients obtained through an optimised discrete wavelet transform facilitates the classification of non-stationary time-variant signals task considerably. In addition, the results indicate that wavelet optimisation may improve the classification ability of a neural network. (c) 2005 Elsevier B.V. All rights reserved.

First-principles simulation of elastic constants and electronic properties of GaN

The electronic and structural properties and elastic constants of the wurtzite phase of GaN, was investigated by computer simulation at Density Functional Theory level, with B3LYP and B3PW hybrid functional. The electronic properties were investigated through the analysis of the band structures and density of states, and the mechanical properties were studied through the calculus of the elastic constants: C11, C33, C44, C12, and C13. The results show that the maximum of the valence band and the minimum of the conduction band are both located at the Γ point, indicating that GaN is a direct band gap semiconductor. The following constants were obtained for B3LYP and B3PW (in brackets): C11 = 366.9 [372.4], C33 = 390.9 [393.4], C44 = 99.1 [96.9], C12 = 143.6 [155.2], and C13 = 107.6 [121.4].

Recommendations for sex/gender neuroimaging research: Key principles and implications for research design, analysis and interpretation

Neuroimaging (NI) technologies are having increasing impact in the study of complex cognitive and social processes. In this emerging field of social cognitive neuroscience, a central goal should be to increase the understanding of the interaction between the neurobiology of the individual and the environment in which humans develop and function. The study of sex/gender is often a focus for NI research, and may be motivated by a desire to better understand general developmental principles, mental health problems that show female-male disparities, and gendered differences in society. In order to ensure the maximum possible contribution of NI research to these goals, we draw attention to four key principles—overlap, mosaicism, contingency and entanglement—that have emerged from sex/gender research and that should inform NI research design, analysis and interpretation. We discuss the implications of these principles in the form of constructive guidelines and suggestions for researchers, editors, reviewers and science communicators.