Equalisation of time variant multipath channels using amplitude banded LMS algorithms

For the purpose of equalisation of rapidly time variant multipath channels, we derive a novel adaptive algorithm, the amplitude banded LMS (ABLMS); which implements a nonlinear adaptation based on a coefficient matrix. Then we develop the: ABLMS algorithm as the adaptation procedure for a linear transversal equaliser (LTE) and a decision feedback equaliser (DFE) where a parallel adaptation scheme is deployed. Computer simulations demonstrate that with a small increase of computational complexity, the ABLMS based parallel equalisers provide a significant improvement related to the conventional LMS DFE and the LMS LTE in the case of a second order Markov communication channel model.

Noise resilience and entanglement evolution in two nonequivalent classes of quantum algorithms

The speedup provided by quantum algorithms with respect to their classical counterparts is at the origin of scientific interest in quantum computation. However, the fundamental reasons for such a speedup are not yet completely understood and deserve further attention. In this context, the classical simulation of quantum algorithms is a useful tool that can help us in gaining insight. Starting from the study of general conditions for classical simulation, we highlight several important differences between two nonequivalent classes of quantum algorithms. We investigate their performance under realistic conditions by quantitatively studying their resilience with respect to static noise. This latter refers to errors affecting the initial preparation of the register used to run an algorithm. We also compare the evolution of the entanglement involved in the different computational processes.

Analysis of Receiver Algorithms for LTE SC-FDMA Based Uplink MIMO Systems

This letter derives mathematical expressions for the received signal-to-interference-plus-noise ratio (SINR) of uplink Single Carrier (SC) Frequency Division Multiple Access (FDMA) multiuser MIMO systems. An improved frequency domain receiver algorithm is derived for the studied systems, and is shown to be significantly superior to the conventional linear MMSE based receiver in terms of SINR and bit error rate (BER) performance.

Revealing differences in gene network inference algorithms on the network level by ensemble methods

Motivation: The inference of regulatory networks from large-scale expression data holds great promise because of the potentially causal interpretation of these networks. However, due to the difficulty to establish reliable methods based on observational data there is so far only incomplete knowledge about possibilities and limitations of such inference methods in this context.

Results: In this article, we conduct a statistical analysis investigating differences and similarities of four network inference algorithms, ARACNE, CLR, MRNET and RN, with respect to local network-based measures. We employ ensemble methods allowing to assess the inferability down to the level of individual edges. Our analysis reveals the bias of these inference methods with respect to the inference of various network components and, hence, provides guidance in the interpretation of inferred regulatory networks from expression data. Further, as application we predict the total number of regulatory interactions in human B cells and hypothesize about the role of Myc and its targets regarding molecular information processing.

Heterogeneous mixed-layer clays from the Cretaceous greensand, Isle of Wight, southern England

The sea-cliffs of the Isle of Wight were deposited during a period of overall sea-level rise starting in the Barremian (Lower Cretaceous) and continuing into the Aptian and Albian. They consist of fluvial, coastal and lagoonal sediments including greensands and clays. Numerous episodes of erosion, deposition and faunal colonization reflect condensation and abandonment of surfaces with firmgrounds and hardgrounds. This study focused mainly on shallow marine cycles where variations in clay mineralogy would not be expected, because overall system composition, sediment source, and thermal history are similar for all the samples in the studied section. Instead we found a wide variety of clay assemblages even in single samples within a 200 in interval.

Molecular diagnosis for heterogeneous genetic diseases with high-throughput DNA sequencing applied to retinitis pigmentosa

BACKGROUND:
The genetic heterogeneity of many Mendelian disorders, such as retinitis pigmentosa which results from mutations in over 40 genes, is a major obstacle to obtaining a molecular diagnosis in clinical practice. Targeted high-throughput DNA sequencing offers a potential solution and was used to develop a molecular diagnostic screen for patients with retinitis pigmentosa.
METHODS:
A custom sequence capture array was designed to target the coding regions of all known retinitis pigmentosa genes and used to enrich these sequences from DNA samples of five patients. Enriched DNA was subjected to high-throughput sequencing singly or in pools, and sequence variants were identified by alignment of up to 10 million reads per sample to the normal reference sequence. Potential pathogenicity was assessed by functional predictions and frequency in controls.
RESULTS AND CONCLUSIONS:
Known homozygous PDE6B and compound heterozygous CRB1 mutations were detected in two patients. A novel homozygous missense mutation (c.2957A?T; p.N986I) in the cyclic nucleotide gated channel ß1 (CNGB1) gene predicted to have a deleterious effect and absent in 720 control chromosomes was detected in one case in which conventional genetic screening had failed to detect mutations. The detection of known and novel retinitis pigmentosa mutations in this study establishes high-throughput DNA sequencing with DNA pooling as an effective diagnostic tool for heterogeneous genetic diseases.

CsF and alumina: A mixed homogeneous-heterogeneous catalytic system for the transesterification of sunflower oil with methanol

The activity and nature (i e heterogeneous and/or homogeneous) of catalysts based on CsF supported on alpha-Al2O3 were investigated for the transesterification of vegetable oil with methanol. The effect of the activation temperature, CsF loading and the reusability in a recirculating reactor were first studied CsF/alpha-Al2O3 exhibited the highest activity for a CsF loading of 0 6 mmol/g and when activated at 120 degrees C An important aspect of this study is the effect of CsF leaching into the reaction mixture, which is attributed to the high solubility of CsF in methanol, leading to a complete loss of activity after one run It was Identified that the activity of the catalyst resulted from a synergy between alumina and dissolved CsF, the presence of both compounds being absolutely necessary to observe any conversion The use of an alumina with a higher surface area resulted in a far greater reaction rate, showing that the concentration of surface site on the oxide (probably surface hydroxyl) was rate-limiting in the case of the experiments using the low surface area alpha-Al2O3 This work emphasizes that combined homogeneous-heterogeneous catalytic systems made from the blending of the respective catalysts can be used to obtain high conversion of vegetable oil to biodiesel. Despite the homogeneous/heterogeneous dual character, such a catalytic system may prove valuable in developing a simple and cost-effective continuous catalytic process for biodiesel production (C) 2010 Elsevier B V All rights reserved

TESTING FOR STATIONARITY IN HETEROGENEOUS PANEL DATA IN THE CASE OF MODEL MISSPECIFICATION

This paper investigates the performance of the tests proposed by Hadri and by Hadri and Larsson for testing for stationarity in heterogeneous panel data under model misspecification. The panel tests are based on the well known KPSS test (cf. Kwiatkowski et al.) which considers two models: stationarity around a deterministic level and stationarity around a deterministic trend. There is no study, as far as we know, on the statistical properties of the test when the wrong model is used. We also consider the case of the simultaneous presence of the two types of models in a panel. We employ two asymptotics: joint asymptotic, T, N -> infinity simultaneously, and T fixed and N allowed to grow indefinitely. We use Monte Carlo experiments to investigate the effects of misspecification in sample sizes usually used in practice. The results indicate that the assumption that T is fixed rather than asymptotic leads to tests that have less size distortions, particularly for relatively small T with large N panels (micro-panels) than the tests derived under the joint asymptotics. We also find that choosing a deterministic trend when a deterministic level is true does not significantly affect the properties of the test. But, choosing a deterministic level when a deterministic trend is true leads to extreme over-rejections. Therefore, when unsure about which model has generated the data, it is suggested to use the model with a trend. We also propose a new statistic for testing for stationarity in mixed panel data where the mixture is known. The performance of this new test is very good for both cases of T asymptotic and T fixed. The statistic for T asymptotic is slightly undersized when T is very small (