Exploiting Evolution for an Adaptive Drift-Robust Classifier in Chemical Sensing

Gas chemical sensors are strongly affected by drift, i.e., changes in sensors' response with time, that may turn statistical models commonly used for classification completely useless after a period of time. This paper presents a new classifier that embeds an adaptive stage able to reduce drift effects. The proposed system exploits a state-of-the-art evolutionary strategy to iteratively tweak the coefficients of a linear transformation able to transparently transform raw measures in order to mitigate the negative effects of the drift. The system operates continuously. The optimal correction strategy is learnt without a-priori models or other hypothesis on the behavior of physical-chemical sensors. Experimental results demonstrate the efficacy of the approach on a real problem

H2O2 Enables Convenient Removal of RAFT End-Groups from Block Copolymer Nano-Objects Prepared via Polymerization-Induced Self-Assembly in Water

RAFT-synthesized polymers are typically colored and malodorous due to the presence of the sulfur-based RAFT end-group(s). In principle, RAFT end-groups can be removed by treating molecularly dissolved copolymer chains with excess free radical initiators, amines, or oxidants. Herein we report a convenient method for the removal of RAFT end-groups from aqueous dispersions of diblock copolymer nano-objects using H2O2. This oxidant is relatively cheap, has minimal impact on the copolymer morphology, and produces benign side products that can be readily removed via dialysis. We investigate the efficiency of end-group removal for various diblock copolymer nano-objects prepared with either dithiobenzoate- or trithiocarbonate-based RAFT chain transfer agents. The advantage of using UV GPC rather than UV spectroscopy is demonstrated for assessing both the kinetics and extent of end-group removal

Dynamical aspects of mean field plane rotators and the Kuramoto model

The Kuramoto model has been introduced in order to describe synchronization phenomena observed in groups of cells, individuals, circuits, etc... We look at the Kuramoto model with white noise forces: in mathematical terms it is a set of N oscillators, each driven by an independent Brownian motion with a constant drift, that is each oscillator has its own frequency, which, in general, changes from one oscillator to another (these frequencies are usually taken to be random and they may be viewed as a quenched disorder). The interactions between oscillators are of long range type (mean field). We review some results on the Kuramoto model from a statistical mechanics standpoint: we give in particular necessary and sufficient conditions for reversibility and we point out a formal analogy, in the N to infinity limit, with local mean field models with conservative dynamics (an analogy that is exploited to identify in particular a Lyapunov functional in the reversible set-up). We then focus on the reversible Kuramoto model with sinusoidal interactions in the N to infinity limit and analyze the stability of the non-trivial stationary profiles arising when the interaction parameter K is larger than its critical value K_c. We provide an analysis of the linear operator describing the time evolution in a neighborhood of the synchronized profile: we exhibit a Hilbert space in which this operator has a self-adjoint extension and we establish, as our main result, a spectral gap inequality for every K>K_c.Comment: 18 pages, 1 figur

Correlation inequalities for classical and quantum XY models

We review correlation inequalities of truncated functions for the classical and quantum XY models. A consequence is that the critical temperature of the XY model is necessarily smaller than that of the Ising model, in both the classical and quantum cases. We also discuss an explicit lower bound on the critical temperature of the quantum XY model.Comment: 13 pages. Submitted to the volume "Advances in Quantum Mechanics: contemporary trends and open problems" of the INdAM-Springer series, proceedings of the INdAM meeting "Contemporary Trends in the Mathematics of Quantum Mechanics" (4-8 July 2016) organised by G. Dell'Antonio and A. Michelangel

Mineralogy and geochemistry of atypical reduction spheroids from the Tumblagooda Sandstone, Western Australia

Funding Information: This research was supported by a CSIRO Mineral Resources studentship, a Curtin University student scholarship and a Minerals Research Institute of Western Australia scholarship. The editors of Sedimentology and three anonymous reviewers are acknowledged for their assistance in improving the manuscript. We would also like to thank Mike Paxman and the Parks and Wildlife Service for permission to sample in Kalbarri National Park. Finally, the authors would like to pay tribute to the memory of Professor Nigel Trewin, whose work laid much of the foundation for this study and many others on the Tumblagooda Sandstone.Peer reviewedPostprin

Climate change refugia for the flora and fauna of England

A variety of evidence suggests that species have, in the past, been able to withstand the effects of climatic change in localised environments known as refugia, where specific environmental conditions acted as a buffer against broader-scale climatic changes. Therefore, an important question for conservation is whether refugia might exist under current and future anthropogenic climate change. If there are areas that are likely to remain relatively climatically stable and so enable species to persist despite climate change making surrounding areas unsuitable, identifying and protecting these places will be an important part of future conservation strategies. This report is part of a project that is investigating this question. The report was commissioned to identify the characteristics of potential refugia, to investigate evidence for the existence of contemporary refugia by analysing patterns of local persistence and disappearance of over 1000 species across a range of taxa, and to identify sites in England with the potential to function as refugia for different taxonomic groups at a range of spatial scales

Functional diversity of chemokines and chemokine receptors in response to viral infection of the central nervous system.

Encounters with neurotropic viruses result in varied outcomes ranging from encephalitis, paralytic poliomyelitis or other serious consequences to relatively benign infection. One of the principal factors that control the outcome of infection is the localized tissue response and subsequent immune response directed against the invading toxic agent. It is the role of the immune system to contain and control the spread of virus infection in the central nervous system (CNS), and paradoxically, this response may also be pathologic. Chemokines are potent proinflammatory molecules whose expression within virally infected tissues is often associated with protection and/or pathology which correlates with migration and accumulation of immune cells. Indeed, studies with a neurotropic murine coronavirus, mouse hepatitis virus (MHV), have provided important insight into the functional roles of chemokines and chemokine receptors in participating in various aspects of host defense as well as disease development within the CNS. This chapter will highlight recent discoveries that have provided insight into the diverse biologic roles of chemokines and their receptors in coordinating immune responses following viral infection of the CNS