Optimal basis set for electronic structure calculations in periodic systems

An efficient method for calculating the electronic structure of systems that need a very fine sampling of the Brillouin zone is presented. The method is based on the variational optimization of a single (i.e., common to all points in the Brillouin zone) basis set for the expansion of the electronic orbitals. Considerations from k.p-approximation theory help to understand the efficiency of the method. The accuracy and the convergence properties of the method as a function of the optimal basis set size are analyzed for a test calculation on a 16-atom Na supercell.

Rapid forensic analysis and identification of "lilac" architectural finishes using Raman spectroscopy

The potential of Raman spectroscopy to discriminate between architectural finishes (household paint) has been investigated using a test set of 51

Hidden Conditional Random Fields for Visual Speech Recognition

In this paper we present the application of Hidden Conditional Random Fields (HCRFs) to modelling speech for visual speech recognition. HCRFs may be easily adapted to model long range dependencies across an observation sequence. As a result visual word recognition performance can be improved as the model is able to take more of a contextual approach to generating state sequences. Results are presented from a speaker-dependent, isolated digit, visual speech recognition task using comparisons with a baseline HMM system. We firstly illustrate that word recognition rates on clean video using HCRFs can be improved by increasing the number of past and future observations being taken into account by each state. Secondly we compare model performances using various levels of video compression on the test set. As far as we are aware this is the first attempted use of HCRFs for visual speech recognition.

P2Y(1) antagonists: Combining receptor-based modeling and QSAR for a quantitative prediction of the biological activity based on consensus scoring

P2Y(1) is an ADP-activated G protein-coupled receptor (GPCR). Its antagonists impede platelet aggregation in vivo and are potential antithrombotic agents. Combining ligand and structure-based modeling we generated a consensus model (LIST-CM) correlating antagonist structures with their potencies. We docked 45 antagonists into our rhodopsin-based human P2Y(1) homology model and calculated docking scores and free binding energies with the Linear Interaction Energy (LIE) method in continuum-solvent. The resulting alignment was also used to build QSAR based on CoMFA, CoMSIA, and molecular descriptors. To benefit from the strength of each technique and compensate for their limitations, we generated our LIST-CM with a PLS regression based on the predictions of each methodology. A test set featuring untested substituents was synthesized and assayed in inhibition of 2-MeSADP-stimulated PLC activity and in radioligand binding. LIST-CM outperformed internal and external predictivity of any individual model to predict accurately the potency of 75% of the test set.

Investigation of the Human Brain Metabolome to Identify Potential Markers for Early Diagnosis and Therapeutic Targets of Alzheimer’s Disease

A study combining high resolution mass spectrometry (liquid chromatography-quadrupole time-of-flight-mass spectrometry, UPLC-QTof-MS) and chemometrics for the analysis of post-mortem brain tissue from subjects with Alzheimer’s disease (AD) (n = 15) and healthy age-matched controls (n = 15) was undertaken. The huge potential of this metabolomics approach for distinguishing AD cases is underlined by the correct prediction of disease status in 94–97% of cases. Predictive power was confirmed in a blind test set of 60 samples, reaching 100% diagnostic accuracy. The approach also indicated compounds significantly altered in concentration following the onset of human AD. Using orthogonal partial least-squares discriminant analysis (OPLS-DA), a multivariate model was created for both modes of acquisition explaining the maximum amount of variation between sample groups (Positive Mode-R2 = 97%; Q2 = 93%; root mean squared error of validation (RMSEV) = 13%; Negative Mode-R2 = 99%; Q2 = 92%; RMSEV = 15%). In brain extracts, 1264 and 1457 ions of interest were detected for the different modes of acquisition (positive and negative, respectively). Incorporation of gender into the model increased predictive accuracy and decreased RMSEV values. High resolution UPLC-QTof-MS has not previously been employed to biochemically profile post-mortem brain tissue, and the novel methods described and validated herein prove its potential for making new discoveries related to the etiology, pathophysiology, and treatment of degenerative brain disorders.

Approximating Credal Network Inferences by Linear Programming

An algorithm for approximate credal network updating is presented. The problem in its general formulation is a multilinear optimization task, which can be linearized by an appropriate rule for fixing all the local models apart from those of a single variable. This simple idea can be iterated and quickly leads to very accurate inferences. The approach can also be specialized to classification with credal networks based on the maximality criterion. A complexity analysis for both the problem and the algorithm is reported together with numerical experiments, which confirm the good performance of the method. While the inner approximation produced by the algorithm gives rise to a classifier which might return a subset of the optimal class set, preliminary empirical results suggest that the accuracy of the optimal class set is seldom affected by the approximate probabilities

Investigation into DCT Feature Selection for Visual Lip-Based Biometric Authentication

This paper investigated using lip movements as a behavioural biometric for person authentication. The system was trained, evaluated and tested using the XM2VTS dataset, following the Lausanne Protocol configuration II. Features were selected from the DCT coefficients of the greyscale lip image. This paper investigated the number of DCT coefficients selected, the selection process, and static and dynamic feature combinations. Using a Gaussian Mixture Model - Universal Background Model framework an Equal Error Rate of 2.20% was achieved during evaluation and on an unseen test set a False Acceptance Rate of 1.7% and False Rejection Rate of 3.0% was achieved. This compares favourably with face authentication results on the same dataset whilst not being susceptible to spoofing attacks.

Rapid tryptophan depletion improves decision-making cognition in healthy humans without affecting reversal learning or set shifting

Rapid tryptophan (Trp) depletion (RTD) has been reported to cause deterioration in the quality of decision making and impaired reversal learning, while leaving attentional set shifting relatively unimpaired. These findings have been attributed to a more powerful neuromodulatory effect of reduced 5-HT on ventral prefrontal cortex (PFC) than on dorsolateral PFC. In view of the limited number of reports, the aim of this study was to independently replicate these findings using the same test paradigms. Healthy human subjects without a personal or family history of affective disorder were assessed using a computerized decision making/gambling task and the CANTAB ID/ED attentional set-shifting task under Trp-depleted (n=17; nine males and eight females) or control (n=15; seven males and eight females) conditions, in a double-blind, randomized, parallel-group design. There was no significant effect of RTD on set shifting, reversal learning, risk taking, impulsivity, or subjective mood. However, RTD significantly altered decision making such that depleted subjects chose the more likely of two possible outcomes significantly more often than controls. This is in direct contrast to the previous report that subjects chose the more likely outcome significantly less often following RTD. In the terminology of that report, our result may be interpreted as improvement in the quality of decision making following RTD. This contrast between studies highlights the variability in the cognitive effects of RTD between apparently similar groups of healthy subjects, and suggests the need for future RTD studies to control for a range of personality, family history, and genetic factors that may be associated with 5-HT function.

A novel diagnostic test detects a low frequency of the hemicentin Gln5345Arg variant among Northern Irish age related macular degeneration patients.

Purpose: Age related macular degeneration (AMD) is a common cause of severe vision loss. Identification of genes involved in AMD will facilitate early detection and ultimately help to identify pathways for treatment for this disorder. The A16,263G mutation in the HEMICENTIN-1 gene produces a non-conservative substitution of arginine for glutamine at codon 5345 which has been implicated in familial AMD. The aim of this study is to develop a rapid diagnostic assay for the detection of this mutation and to evaluate its frequency in a sample of AMD patients. Methods: A primer probe set was designed from exon 104 of the HEMICENTIN-1 gene to differentiate between mutant and wild type alleles. A region spanning the mutation was amplified by PCR using a LightCycler (Roche Diagnostic). The mutation was then detected by melt curve analysis of the hybrid formed between the PCR product and a specific fluorescent probe. The frequency of the mutation within the Northern Ireland population was evaluated by assaying 508 affected AMD patients, 25 possibly affected and 163 controls. Results: This assay clearly discriminates between the A16,263G mutant and wild type HEMICENTIN-1 alleles. The wild type sequence has a single base mismatch with the probe which decreases the stability of the hybrid, resulting in a lower TM (TM=51.27 °C) than that observed for the perfectly matched mutant allele (TM=59.9 °C). The mutant allele was detected in only one of the 696 subjects, an affected AMD patient. Conclusions: We describe a rapid assay for the genotyping of the Gln5345Arg mutation using real-time fluorescence PCR to facilitate rapid processing of samples through combined amplification and detection steps. These characteristics are suitable for a clinical setting where high throughput diagnostic procedures are required. The frequency of this mutation within the Northern Ireland population has been estimated at 0.2%, concurring with previous findings that this mutation is a rare variant associated with AMD. A rapid diagnostic assay will facilitate a reliable and convenient evaluation of the frequency of the Gln5345Arg mutation and its association with AMD within other populations.

Development of a rapid screening test for veterinary sedatives and the beta-blocker carazolol in porcine kidney by ELISA

Sedatives and tranquillisers are frequently used to reduce stress during the transportation of food producing animals. The most widely used classes of sedatives include the butyrophenone azaperone, the phenothiazines acepromazine, propionylpromazine, chlorpromazine and the beta-blocker, carazolol. For regulatory control purposes, tolerances for azaperone and carazolol have been set by the European Union as 100 and 25 mug kg(-1), respectively. Furthermore, the use of the phenothiazines is prohibited and therefore has a zero tolerance. A method for the detection of residues of five tranquillisers and one beta-blocker using a single ELISA plate has been developed. Kidney samples (2.5 g) were extracted with dichloromethane and applied to a competitive enzyme immunoassay using three polyclonal antibodies raised in rabbits against azaperol, propionylpromazine and carazolol conjugates. In sample matrix, the azaperol antibody cross-reacted 28.0% with azaperone and the propionylpromazine antibody cross-reacted 24.9% with acepromazine and 11.7% with chlorpromazine. In the ELISA, the detection capabilities of the six sedatives, azaperol, azaperone, carazolol, acepromazine, chlorpromazine, and propionylpromazine are 5, 15, 5, 5, 20 and 5 mug kg(-1), respectively. The proposed method is a sensitive and rapid multi-residue technique that offers a cost effective alternative to current published procedures, without any concession on the ability to detect sedative misuse.

Optimal Credit Rationing in Not-For-Profit Financial Institutions

We examine the dynamic optimization problem for not-for-profit financial institutions (NFPs) that maximize consumer surplus, not profits. We characterize the optimal dynamic policy and find that it involves credit rationing. Interest rates set by mature NFPs will typically be more favorable to customers than market rates, as any surplus is distributed in the form of interest rate subsidies, with credit rationing being required to prevent these subsidies from distorting loan volumes from their optimal levels. Rationing overcomes a fundamental problem in NFPs; it allows them to distribute the surplus without distorting the volume of activity from the efficient level.

A hierarchical physical model-based approach to predictive control of a thermal power plant for efficient plant-wide disturbance rejection

Extending the work presented in Prasad et al. (IEEE Proceedings on Control Theory and Applications, 147, 523-37, 2000), this paper reports a hierarchical nonlinear physical model-based control strategy to account for the problems arising due to complex dynamics of drum level and governor valve, and demonstrates its effectiveness in plant-wide disturbance handling. The strategy incorporates a two-level control structure consisting of lower-level conventional PI regulators and a higher-level nonlinear physical model predictive controller (NPMPC) for mainly set-point manoeuvring. The lower-level PI loops help stabilise the unstable drum-boiler dynamics and allow faster governor valve action for power and grid-frequency regulation. The higher-level NPMPC provides an optimal load demand (or set-point) transition by effective handling of plant-wide interactions and system disturbances. The strategy has been tested in a simulation of a 200-MW oil-fired power plant at Ballylumford in Northern Ireland. A novel approach is devized to test the disturbance rejection capability in severe operating conditions. Low frequency disturbances were created by making random changes in radiation heat flow on the boiler-side, while condenser vacuum was fluctuating in a random fashion on the turbine side. In order to simulate high-frequency disturbances, pulse-type load disturbances were made to strike at instants which are not an integral multiple of the NPMPC sampling period. Impressive results have been obtained during both types of system disturbances and extremely high rates of load changes, right across the operating range, These results compared favourably with those from a conventional state-space generalized predictive control (GPC) method designed under similar conditions.

Multiple Input Governor Control for a Diesel Generating Set

The paper presents a multiple input single output fuzzy logic governor algorithm that can be used to improve the transient response of a diesel generating set, when supplying an islanded load. The proposed governor uses the traditional speed input in addition to voltage and power factor to modify the fuelling requirements during various load disturbances. The use of fuzzy logic control allows the use of PID type structures that can provide variable gain strategies to account for non-linearities in the system. Fuzzy logic also provides a means of processing other input information by linguistic reasoning and a logical control output to aid the governor action during transient disturbance. The test results were obtained using a 50 kVA naturally aspirated diesel generator testing facility. Both real and reactive load tests were conducted. The complex load test results demonstrate that, by using additional inputs to the governor algorithm, enhanced generator transient speed recovery response can be obtained.

Imperfect assessment and limited information preclude optimal strategies in male-male fights in the orb-weaving spider Metellina mengei

Agonistic behaviour between male orb-web spiders Metellina mengei competing for access to female webs was examined in field experiments to test the major predictions of game theory. Winners of fights were significantly larger than losers, particularly with respect to the length of the first pair of legs, which are sexually dimorphic in this species and used extensively in agonistic encounters. The size of the winning male had no influence on contest intensity or duration, and neither did relative size. However, fight intensity and duration were both positively correlated with the size of the losing male. Resident males won significantly more contests than intruders. Winning intruders were significantly larger than winning residents and it was these winning intruders that tended to produce the longer fights. Female weight and hence reproductive value had a marked influence on fight intensity and duration of fights won by the intruder but not those won by the resident. This indicates that only the resident obtains information about the female. These data are discussed with reference to the discrepancy with theory and a failure of some contestants to obtain information on resource value and relative contestant size necessary to optimize fight strategy.