The evolution and retreat features of the summer monsoon over India

The motivation for this study stems from the fact that there are no uniform criteria to identify the onset of the summer monsoon at a particular location. Furthermore, proper understanding of the events that culminate in the onset of the monsoon is crucial to allow its prediction over various time scales. An attempt is made to elucidate the characteristics of the onset and retreat of the monsoon using a global data assimilation and forecast system. For this purpose, the time series of net tropospheric large-scale budgets of kinetic energy, heat and moisture are examined over the Arabian Sea, Bay of Bengal and some land locations in India. The study makes use of daily data comprising operational analysis (0000 UTC) and forecasts (day1 through day5) produced by the National Centre for Medium Range Weather Forecasting, India, for the summer season of 1994. The sequence of events associated with the advent of the monsoon is noticeably different at various locations. The horizontal fluxes of heat and moisture produce a divergence regime prior to the evolution and change to convergence during the onset of monsoon over the Arabian Sea. Similarly, intense diabatic cooling is noticed prior to the onset of mansoon and changes to heating subsequently. On the other hand, heat and moisture fluxes remain in the convergence regime well before the arrival of the monsoon over the Bay of Bengal. In turn, diabatic heating is noticed prior to the onset here. Onset characteristics at Bombay and Nagpur are similar to those of the Arabian Sea. However, features at Calcutta are identical to those over the Bay of Bengal. Further, the budgets of kinetic energy, heat and moisture depict monotonic decrease at various land locations corresponding to the retreat. Interestingly, the signature of retreat is very similar at the various locations considered here. These changes are observed in the analysis and further corroborated by the model forecasts. Despite the systematic biases, the model captures the essential signature of the onset at various forecast ranges

Recognizing recurrent neural networks (rRNN): Bayesian inference for recurrent neural networks

Recurrent neural networks (RNNs) are widely used in computational neuroscience and machine learning applications. In an RNN, each neuron computes its output as a nonlinear function of its integrated input. While the importance of RNNs, especially as models of brain processing, is undisputed, it is also widely acknowledged that the computations in standard RNN models may be an over-simplification of what real neuronal networks compute. Here, we suggest that the RNN approach may be made both neurobiologically more plausible and computationally more powerful by its fusion with Bayesian inference techniques for nonlinear dynamical systems. In this scheme, we use an RNN as a generative model of dynamic input caused by the environment, e.g. of speech or kinematics. Given this generative RNN model, we derive Bayesian update equations that can decode its output. Critically, these updates define a 'recognizing RNN' (rRNN), in which neurons compute and exchange prediction and prediction error messages. The rRNN has several desirable features that a conventional RNN does not have, for example, fast decoding of dynamic stimuli and robustness to initial conditions and noise. Furthermore, it implements a predictive coding scheme for dynamic inputs. We suggest that the Bayesian inversion of recurrent neural networks may be useful both as a model of brain function and as a machine learning tool. We illustrate the use of the rRNN by an application to the online decoding (i.e. recognition) of human kinematics

Pre-transplant CDKN2A expression in kidney biopsies predicts renal function and is a future component of donor scoring criteria

CDKN2A is a proven and validated biomarker of ageing which acts as an off switch for cell proliferation. We have demonstrated previously that CDKN2A is the most robust and the strongest pre-transplant predictor of post- transplant serum creatinine when compared to “Gold Standard” clinical factors, such as cold ischaemic time and donor chronological age. This report shows that CDKN2A is better than telomere length, the most celebrated biomarker of ageing, as a predictor of post-transplant renal function. It also shows that CDKN2A is as strong a determinant of post-transplant organ function when compared to extended criteria (ECD) kidneys. A multivariate analysis model was able to predict up to 27.1% of eGFR at one year post-transplant (p = 0.008). Significantly, CDKN2A was also able to strongly predict delayed graft function. A pre-transplant donor risk classification system based on CDKN2A and ECD criteria is shown to be feasible and commendable for implementation in the near future

A novel approach to quantify random error explicitly in epidemiological studies

The most frequently used methods for handling random error are largely misunderstood or misused by researchers. We propose a simple approach to quantify the amount of random error which does not require solid background in statistics for its proper interpretation. This method may help researchers refrain from oversimplistic interpretations relying on statistical significance

Performance of Glass Woven Fabric Composites with Admicellar-Coated Thin Elastomeric Interphase

Adequate stress transfer between the inorganic reinforcement and surrounding polymeric matrix is essential for achieving enhanced structural integrity and extended lifetime performance of fiber-reinforced composites. The insertion of an elastomeric interlayer helps increase the stress-transfer capabilities across the fiber/matrix interface and considerably reduces crack initiation phenomena at the fiber ends. In this study, admicellar polymerization is used to modify the fiber/matrix interface in glass woven fabric composites by forming thickness-controlled poly(styrene-co-isoprene) coatings. These admicellar interphases have distinct characteristics (e.g., topology and surface coverage) depending on the surfactant/monomer (S/M) ratios used during the polymerization reaction. Overall, the admicellar coatings have a positive effect on the mechanical response of resin transfer molded (RTM), E-glass/epoxy parts. For instance, ultimate tensile strength (UTS) of composites with admicellar sizings improved 50 to 55% over the control desized samples. Interlaminar shear strength (ILSS) also showed increases ranging from 18 to 38% over the same control group. Interestingly, the flexural properties of these composites proved sensitive to the type of interphase formed for various admicellar polymerization conditions. Higher surface coverage and film connectedness in admicellar polymeric sizings are observed to enhance stress transfer at the interfacial region.Ye

Predictive coding and representationalism

According to the predictive coding theory of cognition (PCT), brains are predictive machines that use perception and action to minimize prediction error, i.e. the discrepancy between bottom–up, externally-generated sensory signals and top–down, internally-generated sensory predictions. Many consider PCT to have an explanatory scope that is unparalleled in contemporary cognitive science and see in it a framework that could potentially provide us with a unified account of cognition. It is also commonly assumed that PCT is a representational theory of sorts, in the sense that it postulates that our cognitive contact with the world is mediated by internal representations. However, the exact sense in which PCT is representational remains unclear; neither is it clear that it deserves such status—that is, whether it really invokes structures that are truly and nontrivially representational in nature. In the present article, I argue that the representational pretensions of PCT are completely justified. This is because the theory postulates cognitive structures—namely action-guiding, detachable, structural models that afford representational error detection—that play genuinely representational functions within the cognitive system

Components of acquisition-to-acquisition variance in continuous arterial spin labelling (CASL) imaging

<p>Abstract</p> <p>Background</p> <p>Images of perfusion estimates obtained with the continuous arterial spin labelling technique are characterized by variation between single acquisitions. Little is known about the spatial determinants of this variation during the acquisition process and their impact on voxel-by-voxel estimates of effects.</p> <p>Results</p> <p>We show here that the spatial patterns of covariance between voxels arising during the acquisition of these images uncover distinct mechanisms through which this variance arises: through variation in global perfusion levels; through the action of large vessels and other, less well characterized, large anatomical structures; and through the effect of noisy areas such as the edges of the brain.</p> <p>Conclusions</p> <p>Knowledge of these covariance patterns is important to experimenters for a correct interpretation of findings, especially for studies where relatively few acquisitions are made.</p

Using Whole Genome Sequences to Investigate Adenovirus Outbreaks in a Hematopoietic Stem Cell Transplant Unit

A recent surge in human mastadenovirus (HAdV) cases, including five deaths, amongst a haematopoietic stem cell transplant population led us to use whole genome sequencing (WGS) to investigate. We compared sequences from 37 patients collected over a 20-month period with sequences from GenBank and our own database of HAdVs. Maximum likelihood trees and pairwise differences were used to evaluate genotypic relationships, paired with the epidemiological data from routine infection prevention and control (IPC) records and hospital activity data. During this time period, two formal outbreaks had been declared by IPC, while WGS detected nine monophyletic clusters, seven were corroborated by epidemiological evidence and by comparison of single-nucleotide polymorphisms. One of the formal outbreaks was confirmed, and the other was not. Of the five HAdV-associated deaths, three were unlinked and the remaining two considered the source of transmission. Mixed infection was frequent (10%), providing a sentinel source of recombination and superinfection. Immunosuppressed patients harboring a high rate of HAdV positivity require comprehensive surveillance. As a consequence of these findings, HAdV WGS is being incorporated routinely into clinical practice to influence IPC policy contemporaneously

PGF2α-F-prostanoid receptor signalling via ADAMTS1 modulates epithelial cell invasion and endothelial cell function in endometrial cancer

<p>Abstract</p> <p>Background</p> <p>An increase in cancer cell invasion and microvascular density is associated with a poorer prognosis for patients with endometrial cancer. In endometrial adenocarcinoma F-prostanoid (FP) receptor expression is elevated, along with its ligand prostaglandin (PG)F_2α, where it regulates expression and secretion of a host of growth factors and chemokines involved in tumorigenesis. This study investigates the expression, regulation and role of a disintegrin and metalloproteinase with thrombospondin repeat 1 (ADAMTS1) in endometrial adenocarcinoma cells by PGF_2αvia the FP receptor.</p> <p>Methods</p> <p>Human endometrium and adenocarcinoma tissues were obtained in accordance with Lothian Research Ethics Committee guidance with informed patient consent. Expression of ADAMTS1 mRNA and protein in tissues was determined by quantitative RT-PCR analysis and immunohistochemistry. Signal transduction pathways regulating ADAMTS1 expression in Ishikawa cells stably expressing the FP receptor to levels seen in endometrial cancer (FPS cells) were determined by quantitative RT-PCR analysis. In vitro invasion and proliferation assays were performed with FPS cells and human umbilical vein endothelial cells (HUVECs) using conditioned medium (CM) from PGF_2α-treated FPS cells from which ADAMTS1 was immunoneutralised and/or recombinant ADAMTS1. The role of endothelial ADAMTS1 in endothelial cell proliferation was confirmed with RNA interference. The data in this study were analysed by T-test or ANOVA.</p> <p>Results</p> <p>ADAMTS1 mRNA and protein expression is elevated in endometrial adenocarcinoma tissues compared with normal proliferative phase endometrium and is localised to the glandular and vascular cells. Using FPS cells, we show that PGF2α-FP signalling upregulates ADAMTS1 expression via a calmodulin-NFAT-dependent pathway and this promotes epithelial cell invasion through ECM and inhibits endothelial cell proliferation. Furthermore, we show that CM from FPS cells regulates endothelial cell ADAMTS1 expression in a rapid biphasic manner. Using RNA interference we show that endothelial cell ADAMTS1 also negatively regulates cellular proliferation.</p> <p>Conclusions</p> <p>These data demonstrate elevated ADAMTS1 expression in endometrial adenocarcinoma. Furthermore we have highlighted a mechanism whereby FP receptor signalling regulates epithelial cell invasion and endothelial cell function via the PGF_2α-FP receptor mediated induction of ADAMTS1.</p

Reinforcement learning or active inference?

This paper questions the need for reinforcement learning or control theory when optimising behaviour. We show that it is fairly simple to teach an agent complicated and adaptive behaviours using a free-energy formulation of perception. In this formulation, agents adjust their internal states and sampling of the environment to minimize their free-energy. Such agents learn causal structure in the environment and sample it in an adaptive and self-supervised fashion. This results in behavioural policies that reproduce those optimised by reinforcement learning and dynamic programming. Critically, we do not need to invoke the notion of reward, value or utility. We illustrate these points by solving a benchmark problem in dynamic programming; namely the mountain-car problem, using active perception or inference under the free-energy principle. The ensuing proof-of-concept may be important because the free-energy formulation furnishes a unified account of both action and perception and may speak to a reappraisal of the role of dopamine in the brain