Inductive queries for a drug designing robot scientist

It is increasingly clear that machine learning algorithms need to be integrated in an iterative scientific discovery loop, in which data is queried repeatedly by means of inductive queries and where the computer provides guidance to the experiments that are being performed. In this chapter, we summarise several key challenges in achieving this integration of machine learning and data mining algorithms in methods for the discovery of Quantitative Structure Activity Relationships (QSARs). We introduce the concept of a robot scientist, in which all steps of the discovery process are automated; we discuss the representation of molecular data such that knowledge discovery tools can analyse it, and we discuss the adaptation of machine learning and data mining algorithms to guide QSAR experiments

Enhancement of deep epileptiform activity in the EEG via 3-D adaptive spatial filtering,

The detection of epileptiform discharges (ED’s) in the electroencephalogram (EEG) is an important component in the diagnosis of epilepsy. However, when the epileptogenic source is located deep in the brain, the ED’s at the scalp are often masked by more superficial, higher-amplitude EEG activity. A noninvasive technique which uses an adaptive “beamformer” spatial filter has been investigated for the enhancement of signals from deep sources in the brain suspected of containing ED’s. A forward three-layer spherical model was used to relate a dipolar source to recorded signals to determine the beamformer’s spatial response constraints. The beamformer adapts, using the least-mean-squares (LMS) algorithm, to reduce signals from sources distant to some arbitrarily defined location in the brain. The beamformer produces three outputs, being the orthogonal components of the signal estimated to have arisen at or near the assumed location. Simulations were performed by using the same forward model to superimpose realistic ED’s on normal EEG recordings. The simulations show the beamformer’s ability to enhance signals emanating from deep foci by way of an enhancement ratio (ER), being the improvement in signal-to-noise ratio (SNR) to that observed at any of the scalp electrodes. The performance of the beamformer has been evaluated for 1) the number of scalp electrodes, 2) the recording montage, 3) dependence on the background EEG, 4) dependence on magnitude, depth, and orientation of epileptogenic focus, and 5) sensitivity to inaccuracies in the estimated location of the focus. Results from the simulations show the beamformer’s performance to be dependent on the number of electrodes and moderately sensitive to variations in the EEG background. Conversely, its performance appears to be largely independent of the amplitude and morphology of the ED. The dependence studies indicated that the beamformer’s performance was moderately dependent on eccentricity with the ER increasing as the dipolar source and the beamformer were moved from the center to the surface of the brain (1.51–2.26 for radial dipoles and 1.17–2.69 for tangential dipoles). The beamformer was also moderately dependent on variations in polar or azimuthal angle for radial and tangential dipoles. Higher ER’s tended to be seen for locations between electrode sites. The beamformer was more sensitive to inaccuracies in both polar and azimuthal location than depth of the dipolar source. For polar locations, an ER > 1.0 was achieved when the beamformer was located within 25 of a radial dipole and 35 of a tangential dipole. Similarly, angular ranges of 37.5 and 45 , respectively, for inaccuracies in azimuthal locations. Preliminary results from real EEG records, comprising 12 definite or questionable epileptiform events, from four patients, demonstrated the beamformer’s ability to enhance these events by a mean 100% (52%–215%) for referential data and a mean 104% (50%–145%) for bipolar data

Balancing selected medication costs with total number of daily injections: a preference analysis of GnRH-agonist and antagonist protocols by IVF patients

Abstract Background During in vitro fertilization (IVF), fertility patients are expected to self-administer many injections as part of this treatment. While newer medications have been developed to substantially reduce the number of these injections, such agents are typically much more expensive. Considering these differences in both cost and number of injections, this study compared patient preferences between GnRH-agonist and GnRH-antagonist based protocols in IVF. Methods Data were collected by voluntary, anonymous questionnaire at first consultation appointment. Patient opinion concerning total number of s.c. injections as a function of non-reimbursed patient cost associated with GnRH-agonist [A] and GnRH-antagonist [B] protocols in IVF was studied. Results Completed questionnaires (n = 71) revealed a mean +/− SD patient age of 34 +/− 4.1 yrs. Most (83.1%) had no prior IVF experience; 2.8% reported another medical condition requiring self-administration of subcutaneous medication(s). When out-of-pocket cost for [A] and [B] were identical, preference for [B] was registered by 50.7% patients. The tendency to favor protocol [B] was weaker among patients with a health occupation. Estimated patient costs for [A] and [B] were $259.82 +/− 11.75 and$654.55 +/− 106.34, respectively (p  Conclusions This investigation found consistently higher non-reimbursed direct medication costs for GnRH-antagonist IVF vs. GnRH-agonist IVF protocols. A conditional preference to minimize downregulation (using GnRH-antagonist) was noted among some, but not all, IVF patient sub-groups. Compared to IVF patients with a health occupation, the preference for GnRH-antagonist was weaker than for other patients. While reducing total number of injections by using GnRH-antagonist is a desirable goal, it appears this advantage is not perceived equally by all IVF patients and its utility is likely discounted heavily by patients when nonreimbursed medication costs reach a critical level.</p

Application of the Tool for Turbine Engine Closed-loop Transient Analysis (TTECTrA) for Dynamic Systems Analysis

Systems analysis involves steady-state simulations of combined components to evaluate the steady-state performance, weight, and cost of a system; dynamic considerations are not included until later in the design process. The Dynamic Systems Analysis task, under NASAs Fixed Wing project, is developing the capability for assessing dynamic issues at earlier stages during systems analysis. To provide this capability the Tool for Turbine Engine Closed-loop Transient Analysis (TTECTrA) has been developed to design a single flight condition controller (defined as altitude and Mach number) and, ultimately, provide an estimate of the closed-loop performance of the engine model. This tool has been integrated with the Commercial Modular Aero-Propulsion System Simulation 40,000 (CMAPSS 40k) engine model to demonstrate the additional information TTECTrA makes available for dynamic systems analysis. This dynamic data can be used to evaluate the trade-off between performance and safety, which could not be done with steady-state systems analysis data. TTECTrA has been designed to integrate with any turbine engine model that is compatible with the MATLAB Simulink (The MathWorks, Inc.) environment

The Cryogenic Target for the G0^0 Experiment at Jefferson Lab

A cryogenic horizontal single loop target has been designed, built, tested and operated for the G$^0$ experiment in Hall C at Jefferson Lab. The target cell is 20 cm long, the loop volume is 6.5 l and the target operates with the cryogenic pump fully immersed in the fluid. The target has been designed to operate at 30 Hz rotational pump speed with either liquid hydrogen or liquid deuterium. The high power heat exchanger is able to remove 1000 W of heat from the liquid hydrogen, while the nominal electron beam with current of 40 $\mu$A and energy of 3 GeV deposits about 320 W of heat into the liquid. The increase in the systematic uncertainty due to the liquid hydrogen target is negligible on the scale of a parity violation experiment. The global normalized yield reduction for 40 $\mu$A beam is about 1.5 % and the target density fluctuations contribute less than 238 ppm (parts per million) to the total asymmetry width, typically about 1200 ppm, in a Q$^2$ bin.Comment: 27 pages, 14 figure

Measurement of BOLD changes due to cued eye-closure and stopping during a continuous visuomotor task via model-based and model-free approaches

As a precursor for investigation of changes in neural activity underlying lapses of responsiveness, we set up a system to simultaneously record functional magnetic resonance imaging (fMRI), eye-video, EOG, and continuous visuomotor response inside an MRI scanner. The BOLD fMRI signal was acquired during a novel 2-D tracking task in which participants (10 males, 10 females) were cued to either briefly stop tracking and close their eyes (Stop Close) or to briefly stop tracking (Stop) only. The onset and duration of eye-closure and stopping were identified post hoc from eye-video, EOG, and visuomotor response. fMRI data were analyzed using a general linear model (GLM) and tensorial independent component analysis (TICA). The GLM-based analysis identified predominantly increased blood oxygenation level dependent (BOLD) activity during eye-closure and stopping in multisensory areas, sensory-motor integration areas, and default-mode regions. Stopping during tracking elicited increased activity in visual processing areas, sensory-motor integration areas, and premotor areas. TICA separated the spatio-temporal pattern of activity into multiple task-related networks including the 1) occipito-medial frontal eye-movement network, 2) sensory areas, 3) left-lateralized visuomotor network, and 4) fronto-parietal visuomotor network, which were modulated differently by Stop Close and Stop. The results demonstrate the merits of using simultaneous fMRI, behavioral, and physiological recordings to investigate the mechanisms underlying complex human behaviors in the human brain. Furthermore, knowledge of widespread modulations in brain activity due to voluntary eye-closure or stopping during a continuous visuomotor task is important for studies of the brain mechanisms underlying involuntary behaviors, such as microsleeps and attention lapses, which are often accompanied by brief eye-closure and/or response failures

Vapour-liquid coexistence in many-body dissipative particle dynamics

Many-body dissipative particle dynamics is constructed to exhibit vapour-liquid coexistence, with a sharp interface, and a vapour phase of vanishingly small density. In this form, the model is an unusual example of a soft-sphere liquid with a potential energy built out of local-density dependent one-particle self energies. The application to fluid mechanics problems involving free surfaces is illustrated by simulation of a pendant drop.Comment: 8 pages, 6 figures, revtex

Convergence of chiral effective field theory

We formulate the expansion for the mass of the nucleon as a function of pion mass within chiral perturbation theory using a number of different ultra-violet regularisation schemes; including dimensional regularisation and various finite-ranged regulators. Leading and next-to-leading order non-analytic contributions are included through the standard one-loop Feynman graphs. In addition to the physical nucleon mass, the expansion is constrained by recent, extremely accurate, lattice QCD data obtained with two flavors of dynamical quarks. The extent to which different regulators can describe the chiral expansion is examined, while varying the range of quark mass over which the expansions are matched. Renormalised chiral expansion parameters are recovered from each regularisation prescription and compared. We find that the finite-range regulators produce consistent, model-independent results over a wide range of quark mass sufficient to solve the chiral extrapolation problem in lattice QCD.Comment: 13 pages, 13 figures; To appear in Progress in Particle and Nuclear Physics; presented at Erice School on Quarks in Hadrons and Nuclei, September 200

Pre-main-sequence Lithium Depletion

In this review I briefly discuss the theory of pre-main-sequence (PMS) Li depletion in low-mass (0.075<M<1.2 Msun) stars and highlight those uncertain parameters which lead to substantial differences in model predictions. I then summarise observations of PMS stars in very young open clusters, clusters that have just reached the ZAMS and briefly highlight recent developments in the observation of Li in very low-mass PMS stars.Comment: 8 pages, invited review at "Chemical abundances and mixing in stars in the Milky Way and its satellites", eds. L. Pasquini, S. Randich. ESO Astrophysics Symposium (Springer-Verlag

Chiral Extrapolation of Lattice Data for Heavy Baryons

The masses of heavy baryons containing a b quark have been calculated numerically in lattice QCD with pion masses which are much larger than its physical value. In the present work we extrapolate these lattice data to the physical mass of the pion by applying the effective chiral Lagrangian for heavy baryons, which is invariant under chiral symmetry when the light quark masses go to zero and heavy quark symmetry when the heavy quark masses go to infinity. A phenomenological functional form with three parameters, which has the correct behavior in the chiral limit and appropriate behavior when the pion mass is large, is proposed to extrapolate the lattice data. It is found that the extrapolation deviates noticably from the naive linear extrapolation when the pion mass is smaller than about 500MeV. The mass differences between Sigma_b and Sigma_b^* and between Sigma_b^{(*)} and Lambda_b are also presented. Uncertainties arising from both lattice data and our model parameters are discussed in detail. We also give a comparision of the results in our model with those obtained in the naive linear extrapolations.Comment: 29 pages, 9 figure