When Models Interact with their Subjects: The Dynamics of Model Aware Systems

A scientific model need not be a passive and static descriptor of its subject. If the subject is affected by the model, the model must be updated to explain its affected subject. In this study, two models regarding the dynamics of model aware systems are presented. The first explores the behavior of "prediction seeking" (PSP) and "prediction avoiding" (PAP) populations under the influence of a model that describes them. The second explores the publishing behavior of a group of experimentalists coupled to a model by means of confirmation bias. It is found that model aware systems can exhibit convergent random or oscillatory behavior and display universal 1/f noise. A numerical simulation of the physical experimentalists is compared with actual publications of neutron life time and {\Lambda} mass measurements and is in good quantitative agreement.Comment: Accepted for publication in PLoS-ON

Intrinsic gain modulation and adaptive neural coding

In many cases, the computation of a neural system can be reduced to a receptive field, or a set of linear filters, and a thresholding function, or gain curve, which determines the firing probability; this is known as a linear/nonlinear model. In some forms of sensory adaptation, these linear filters and gain curve adjust very rapidly to changes in the variance of a randomly varying driving input. An apparently similar but previously unrelated issue is the observation of gain control by background noise in cortical neurons: the slope of the firing rate vs current (f-I) curve changes with the variance of background random input. Here, we show a direct correspondence between these two observations by relating variance-dependent changes in the gain of f-I curves to characteristics of the changing empirical linear/nonlinear model obtained by sampling. In the case that the underlying system is fixed, we derive relationships relating the change of the gain with respect to both mean and variance with the receptive fields derived from reverse correlation on a white noise stimulus. Using two conductance-based model neurons that display distinct gain modulation properties through a simple change in parameters, we show that coding properties of both these models quantitatively satisfy the predicted relationships. Our results describe how both variance-dependent gain modulation and adaptive neural computation result from intrinsic nonlinearity.Comment: 24 pages, 4 figures, 1 supporting informatio

Band-gap expansion in the surface-localized electronic structure of MoS2(0002)

The electronic band structure of MoS2 single crystals has been investigated using angle-resolved photoelectron spectroscopy and first-principles calculations. The orbital symmetry and k dispersion of these electronic states responsible for the direct and the indirect electronic band gaps have been unambiguously determined. By experimentally probing an increase of the electronic band gap, we conclude that a MoS2 (0002) surface localized state exists just below the valence band maximum at the Gamma point. This electronic state originates from the sulfur planes within the topmost layer. Our comprehensive study addresses the surface electronic structure of MoS2 and the role of van der Waals interlayer interactions.open112625Nsciescopu

Chandrasekhar-Kendall functions in astrophysical dynamos

Some of the contributions of Chandrasekhar to the field of magnetohydrodynamics are highlighted. Particular emphasis is placed on the Chandrasekhar-Kendall functions that allow a decomposition of a vector field into right- and left-handed contributions. Magnetic energy spectra of both contributions are shown for a new set of helically forced simulations at resolutions higher than what has been available so far. For a forcing function with positive helicity, these simulations show a forward cascade of the right-handed contributions to the magnetic field and nonlocal inverse transfer for the left-handed contributions. The speed of inverse transfer is shown to decrease with increasing value of the magnetic Reynolds number.Comment: 10 pages, 5 figures, proceedings of the Chandrasekhar Centenary Conference, to be published in PRAMANA - Journal of Physic

Effects of robotic-assisted laparoscopic prostatectomy on surgical pathology specimens

Background Robotic-assisted laparoscopic prostatectomy (RALP) has greatly changed clinical management of prostate cancer. It is important for pathologists and urologists to compare RALP with conventional open radical retropubic prostatectomy (RRP), and evaluate their effects on surgical pathology specimens. Methods We retrospectively reviewed and statistically analyzed 262 consecutive RALP (n = 182) and RRP (n = 80) procedures performed in our institution from 2007 to 2010. From these, 49 RALP and 33 RRP cases were randomly selected for additional microscopic examination to analyze the degree of capsular incision and the amount of residual prostate surface adipose tissue. Results Positive surgical margins were present in 28.6% RALP and 57.5% RRP cases, a statistically significant difference. In patients with stage T2c tumors, which represent 61.2% RALP and 63.8% RRP patients, the positive surgical margin rate was 24.1% in the RALP group and 58.8% in the RRP group (statistically significant difference). For other pathologic stages, the differences in positive margins between RALP and RRP groups were not statistically significant. The incidence of positive surgical margins after RALP was related to higher tumor stage, higher Gleason score, higher tumor volume and lower prostate weight, but was not related to the surgeons performing the procedure. When compared with RRP, RALP also caused less severe prostatic capsular incision and maintained larger amounts of residual surface adipose tissue in prostatectomy specimens. Conclusions In this study RALP showed a statistically significant lower positive surgical margin rate than RRP. Analysis of capsular incision and amount of prostatic surface residual adipose tissue suggested that RALP caused less prostatic capsular damage than RRP

Novel genetic analysis for case-control genome-wide association studies: quantification of power and genomic prediction accuracy

Genome-wide association studies (GWAS) are routinely conducted for both quantitative and binary (disease) traits. We present two analytical tools for use in the experimental design of GWAS. Firstly, we present power calculations quantifying power in a unified framework for a range of scenarios. In this context we consider the utility of quantitative scores (e.g. endophenotypes) that may be available on cases only or both cases and controls. Secondly, we consider, the accuracy of prediction of genetic risk from genome-wide SNPs and derive an expression for genomic prediction accuracy using a liability threshold model for disease traits in a case-control design. The expected values based on our derived equations for both power and prediction accuracy agree well with observed estimates from simulations