Highly selective and efficient hydrogenation of carboxylic acids to alcohols using titania supported Pt catalysts

Selective hydrogenation of carboxylic acids to alcohols and alkanes has been achieved under remarkably mild reaction temperatures and H-2 pressures (333 K, 0.5 MPa) using Pt/TiO2 catalyst.

Power Efficient Dynamic-Range Utilisation for DSP On FPGA

A power and resource efficient ‘dynamic-range utilisation’ technique to increase operational capacity of DSP IP cores by exploiting redundancy in the data epresentation of sampled analogue input data, is presented. By cleverly partitioning dynamic-range into separable processing threads, several data streams are computed concurrently on the same hardware. Unlike existing techniques which act solely to reduce power consumption due to sign extension, here the dynamic range is exploited to increase operational capacity while still achieving reduced power consumption. This extends an existing system-level, power efficient framework for the design of low power DSP IP cores, which when applied to the design of an FFT IP core in a digital receiver system gives an architecture requiring 50% fewer multipliers, 12% fewer slices and 51%-56% less power.

Power Efficient DSP Datapath Configuration Methodology for FPGA

Exploiting the underutilisation of variable-length DSP algorithms during normal operation is vital, when seeking to maximise the achievable functionality of an application within peak power budget. A system level, low power design methodology for FPGA-based, variable length DSP IP cores is presented. Algorithmic commonality is identified and resources mapped with a configurable datapath, to increase achievable functionality. It is applied to a digital receiver application where a 100% increase in operational capacity is achieved in certain modes without significant power or area budget increases. Measured results show resulting architectures requires 19% less peak power, 33% fewer multipliers and 12% fewer slices than existing architectures.

Efficient Evaluation of Multidimensional Time-Varying Density Forecasts

We propose two simple evaluation methods for time varying density forecasts of continuous higher dimensional random variables. Both methods are based on the probability integral transformation for unidimensional forecasts. The first method tests multinormal densities and relies on the rotation of the coordinate system. The advantage of the second method is not only its applicability to any continuous distribution but also the evaluation of the forecast accuracy in specific regions of its domain as defined by the user’s interest. We show that the latter property is particularly useful for evaluating a multidimensional generalization of the Value at Risk. In simulations and in an empirical study, we examine the performance of both tests.