Catalytic contribution of flap-substrate hydrogen bonds in "HIV-1 protease" explored by chemical synthesis

An analogue of "HIV-1 protease" was designed in which the ability to donate important water-mediated hydrogen bonds to substrate was precisely and directly deleted. Chemical ligation of unprotected peptide segments was used to synthesize this "backbone-engineered" enzyme. The functionally relevant amide -CONH- linkage between residues Gly49-Ile50 in each flap of the enzyme was replaced by an isosteric thioester -COS- bond. The backbone-engineered enzyme had normal substrate specificity and affinity (Km). However, the catalytic activity (kcat) was reduced approximately 3000-fold compared to the native amide bond-containing enzyme. Inhibition by the reduced peptide bond substrate analogue MVT-101 was unaffected compared with native enzyme. By contrast, the normally tight-binding hydroxyethylamine inhibitor JG-365 bound to the backbone-engineered enzyme with an approximately 2500-fold reduction in affinity. The reduced catalytic activity of the -Gly49-psi(COS)-Ile50-backbone-engineered enzyme analogue provides direct experimental evidence to support the suggestion that backbone hydrogen bonds from the enzyme flaps to the substrate are important for the catalytic function of the HIV-1 protease.     

Quasiparticle tunneling through rare earth trihydroxide barriers

Symmetric tunneling junctions with 4000-Å-thick Pb electrodes and polycrystalline insulating barriers of Lu(OH)₃, Er(OH)₃, and Ho(OH)₃ have been fabricated. In bulk, these three rare earth trihydroxides are nonmagnetic, antiferromagnetic (T _N<1.1 K), and ferromagnetic (T_c=2.54 K), respectively. Tunneling resistances ranged from 600 to greater than 40,000 with a junction area of 6.25×10^–2 cm². Single-particle tunneling characteristics of these junctions were always broadened relative to the characteristics of Pb-PbO-Pb junctions, although the ratio of the zero-bias tunneling resistance to the normal tunneling resistance in some instances was of the order of 1000. A threefold splitting of the conductance peak at the gap was observed only in junctions with Ho(OH)₃ barriers. The gap peak of junctions with Er(OH)₃ barriers was broadened significantly relative to that of junctions with Lu(OH)₃ barriers. From measurements of the temperature and magnetic field dependences of the tunneling conductance it is argued that the splitting in junctions with Ho(OH)₃ barriers is consistent with the existence of a peak in the electronic density of states at an energy below that of the gap of each of the electrodes. This peak is believed to be the signature of a bound state near the barrier where the pair potential is depressed by virtue of the exchange coupling between the spins of the superconducting electrons and the localized spins of the barrier. Qualitative interpretations of the data support the view that the observed structure in Ho(OH)₃ barrier junctions is neither a consequence of intrinsic gap anisotropy in Pb nor of inelastic magnon-assisted tunnelling.     

Data encodings and their costs

Summary This paper is devoted to developing and studying a precise notion of the encoding of a logical data structure in a physical storage structure, that is motivated by considerations of computational efficiency. The development builds upon the notion of an encoding of one graph in another. The cost of such an encoding is then defined so as to reflect the structural compatibility of the two graphs, the (externally specified) costs of implementing the host graph, and the (externally specified) set of intended usage patterns of the guest graph. The stability of the constructed framework is demonstrated in terms of a number of results; the faithfulness of the formalism is argued in terms of a number of examples from the literature; and the tractability of the model is hinted at by several results and by further references to the literature.     

A heterogeneous modular robotic design for fast response to a diversity of tasks

This paper describes a heterogeneous modular robot system design which attempts to give a quick solution to a diversity of tasks. The approach is based on the use of an inventory of three types of modules i.e., power and control module, joint module and specialized module. Each module type aims to balance versatility and functionality. Their design permits rapid and cost effective design and fabrication. They are interchangeable in different ways to form different robot or system configurations. Depending on the task, the operator decides what type of robot can provide the best performance within the mission. A spherical joint module is described and used to build different robots, hence, forward and inverse kinematics models are obtained. Finally, from the modules described in this work, several robot configurations such as robotic arms, leg-based robots and wheel-based robots are assembled to demonstrate the execution of manipulation and locomotion tasks.     

A mobility constraint model to infer sensor behaviour in forest fire risk monitoring

Wireless sensor networks (WSNs) play an important role in forest fire risk monitoring. Various applications are in operation. However, the use of mobile sensors in forest risk monitoring remains largely unexplored. Our research contributes to fill this gap by designing a model which abstracts mobility constraints within different types of contexts for the inference of mobile sensor behaviour. This behaviour is focused on achieving a suitable spatial coverage of the WSN when monitoring forest fire risk. The proposed mobility constraint model makes use of a Bayesian network approach and consists of three components: (1) a context typology describing different contexts in which a WSN monitors a dynamic phenomenon; (2) a context graph encoding probabilistic dependencies among variables of interest; and (3) contextual rules encoding expert knowledge and application requirements needed for the inference of sensor behaviour. As an illustration, the model is used to simulate the behaviour of a mobile WSN to obtain a suitable spatial coverage in low and high fire risk scenarios. It is shown that the implemented Bayesian network within the mobility constraint model can successfully infer behaviour such as sleeping sensors, moving sensors, or deploying more sensors to enhance spatial coverage. Furthermore, the mobility constraint model contributes towards mobile sensing in which the mobile sensor behaviour is driven by constraints on the state of the phenomenon and the sensing system.     

Implementing molecular dynamics on hybrid high performance computers – Particle–particle particle-mesh

The use of accelerators such as graphics processing units (GPUs) has become popular in scientific computing applications due to their low cost, impressive floating-point capabilities, high memory bandwidth, and low electrical power requirements. Hybrid high-performance computers, machines with nodes containing more than one type of floating-point processor (e.g. CPU and GPU), are now becoming more prevalent due to these advantages. In this paper, we present a continuation of previous work implementing algorithms for using accelerators into the LAMMPS molecular dynamics software for distributed memory parallel hybrid machines. In our previous work, we focused on acceleration for short-range models with an approach intended to harness the processing power of both the accelerator and (multi-core) CPUs. To augment the existing implementations, we present an efficient implementation of long-range electrostatic force calculation for molecular dynamics. Specifically, we present an implementation of the particle–particle particle-mesh method based on the work by Harvey and De Fabritiis. We present benchmark results on the Keeneland InfiniBand GPU cluster. We provide a performance comparison of the same kernels compiled with both CUDA and OpenCL. We discuss limitations to parallel efficiency and future directions for improving performance on hybrid or heterogeneous computers.     

Drinking patterns as predictors of alcohol withdrawal reactions in DBA/2J mice

Individually housed DBA/2J mice were fed a liquid diet in which ethanol supplied 33% of the calories. The level of physical dependence that developed was estimated by scoring convulsions, elicited by handling the mice, after discontinuing the alcohol diet. The severity of the withdrawal reaction increased progressively with duration (5-12 days) of alcohol administration. A 2-day period on the diet produced no withdrawal reaction. Pretreatment of the mice with alcohol in their drinking water slightly increased the subsequent intake of the liquid diet. "Effective" alcohol intake was defined as uninterrupted alcohol consumption above 10 g/kg/day. Withdrawal scores correlated better with effective intake than with total intake under a variety of conditions. We interpret this to mean that brief interruptions in drinking (1 day) may allow the accrued physical dependence to disappear. On the basis of their effective alcohol intake, mice could be assigned to nondependent, moderately dependent or severely dependent groups for further study of the nature of physical dependence.     

Patent evolution in relation to public/private R&D investment and corporate profitability: Evidence from the United States

Summary In this paper we analyze the (historical) co-evolution of technological development and economic progress (by relating public and private R&D investment, patenting, and corporate profitability). We relate to the work ofSchmookler(1966),Griliches(1990),Pakes&Griliches(1980) andPakes(1986) who all have studied the techno-economic interplay by considering patents as in indicator of technological performance. We use United States industry and government data over the period 1953-1998 (45 years). Co-evolution analysis over this period reveals a strong interdependency among the variables. Patent evolution is strongly related to the development of private R&D and corporate profitability; the levels of public and private R&D expenditure in combination with the level of technological output (i.e. patents) have a strong predictive and explanatory power towards corporate profitability (R² value of 94.9%). Causality tests reveal a joint determination between R&D investment and corporate profitability (L=2; p<0.01).     

FDTD simulation of the nonlinear gain dynamics in active optical waveguides and semiconductor microcavities

We use the finite-difference time-domain (FDTD) solution of the full-wave vectorial Maxwell-Bloch equations for a two-level quantum system developed earlier , to investigate the nonlinear gain spatio-temporal dynamics of active optical waveguides and semiconductor microcavities. The numerical model has been successfully validated against density matrix theory of gain saturation in homogeneously broadened two-level quantum systems for optical waveguides containing resonant gain nonlinearities. The semiclassical equations have been extended employing the Langevin formalism to account for the quantum noise and the spontaneous emission. We have numerically demonstrated the time evolution of the coherent oscillations build up at the output laser facet identifying the lasing threshold and the fast relaxation oscillations until the settlement of a steady-state emission. Our simulation predictions of the lasing wavelength in a number of vertical-cavity surface-emitting laser geometries, when the spontaneous emission is the only source of radiation, agree very well with standard results and, thus, allow us to infer and subsequently optimize important emission characteristics, such as the spontaneous emission rate, the laser line shape, and the relaxation oscillation frequencies and decay rates.