Classification with Asymmetric Label Noise: Consistency and Maximal Denoising

In many real-world classification problems, the labels of training examples are randomly corrupted. Most previous theoretical work on classification with label noise assumes that the two classes are separable, that the label noise is independent of the true class label, or that the noise proportions for each class are known. In this work, we give conditions that are necessary and sufficient for the true class-conditional distributions to be identifiable. These conditions are weaker than those analyzed previously, and allow for the classes to be nonseparable and the noise levels to be asymmetric and unknown. The conditions essentially state that a majority of the observed labels are correct and that the true class-conditional distributions are "mutually irreducible," a concept we introduce that limits the similarity of the two distributions. For any label noise problem, there is a unique pair of true class-conditional distributions satisfying the proposed conditions, and we argue that this pair corresponds in a certain sense to maximal denoising of the observed distributions. Our results are facilitated by a connection to "mixture proportion estimation," which is the problem of estimating the maximal proportion of one distribution that is present in another. We establish a novel rate of convergence result for mixture proportion estimation, and apply this to obtain consistency of a discrimination rule based on surrogate loss minimization. Experimental results on benchmark data and a nuclear particle classification problem demonstrate the efficacy of our approach

The logic of recurrent circuits in the primary visual cortex

Recurrent cortical activity sculpts visual perception by refining, amplifying or suppressing visual input. However, the rules that govern the influence of recurrent activity remain enigmatic. We used ensemble-specific two-photon optogenetics in the mouse visual cortex to isolate the impact of recurrent activity from external visual input. We found that the spatial arrangement and the visual feature preference of the stimulated ensemble and the neighboring neurons jointly determine the net effect of recurrent activity. Photoactivation of these ensembles drives suppression in all cells beyond 30 µm but uniformly drives activation in closer similarly tuned cells. In nonsimilarly tuned cells, compact, cotuned ensembles drive net suppression, while diffuse, cotuned ensembles drive activation. Computational modeling suggests that highly local recurrent excitatory connectivity and selective convergence onto inhibitory neurons explain these effects. Our findings reveal a straightforward logic in which space and feature preference of cortical ensembles determine their impact on local recurrent activity

Selenoprotein gene nomenclature

The human genome contains 25 genes coding for selenocysteine-containing proteins (selenoproteins). These proteins are involved in a variety of functions, most notably redox homeostasis. Selenoprotein enzymes with known functions are designated according to these functions: TXNRD1, TXNRD2, and TXNRD3 (thioredoxin reductases), GPX1, GPX2, GPX3, GPX4 and GPX6 (glutathione peroxidases), DIO1, DIO2, and DIO3 (iodothyronine deiodinases), MSRB1 (methionine-R-sulfoxide reductase 1) and SEPHS2 (selenophosphate synthetase 2). Selenoproteins without known functions have traditionally been denoted by SEL or SEP symbols. However, these symbols are sometimes ambiguous and conflict with the approved nomenclature for several other genes. Therefore, there is a need to implement a rational and coherent nomenclature system for selenoprotein-encoding genes. Our solution is to use the root symbol SELENO followed by a letter. This nomenclature applies to SELENOF (selenoprotein F, the 15 kDa selenoprotein, SEP15), SELENOH (selenoprotein H, SELH, C11orf31), SELENOI (selenoprotein I, SELI, EPT1), SELENOK (selenoprotein K, SELK), SELENOM (selenoprotein M, SELM), SELENON (selenoprotein N, SEPN1, SELN), SELENOO (selenoprotein O, SELO), SELENOP (selenoprotein P, SeP, SEPP1, SELP), SELENOS (selenoprotein S, SELS, SEPS1, VIMP), SELENOT (selenoprotein T, SELT), SELENOV (selenoprotein V, SELV) and SELENOW (selenoprotein W, SELW, SEPW1). This system, approved by the HUGO Gene Nomenclature Committee, also resolves conflicting, missing and ambiguous designations for selenoprotein genes and is applicable to selenoproteins across vertebrates

Pervasive Eclogitization Due to Brittle Deformation and Rehydration of Subducted Basement: Effects on Continental Recycling?

The buoyancy of continental crust opposes its subduction to mantle depths, except where mineral reactions substantially increase rock density. Sluggish kinetics limit such densification, especially in dry rocks, unless deformation and hydrous fluids intervene. Here we document how hydrous fluids in the subduction channel invaded lower crustal granulites at 50–60 km depth through a dense network of probably seismically induced fractures. We combine analyses of textures and mineral composition with thermodynamic modeling to reconstruct repeated stages of interaction, with pulses of high‐pressure (HP) fluid at 650–670°C, rehydrating the initially dry rocks to micaschists. SIMS oxygen isotopic data of quartz indicate fluids of crustal composition. HP growth rims in allanite and zircon show uniform U‐Th‐Pb ages of ∼65 Ma and indicate that hydration occurred during subduction, at eclogite facies conditions. Based on this case study in the Sesia Zone (Western Italian Alps), we conclude that continental crust, and in particular deep basement fragments, during subduction can behave as substantial fluid sinks, not sources. Density modeling indicates a bifurcation in continental recycling: Chiefly mafic crust, once it is eclogitized to >60%, are prone to end up in a subduction graveyard, such as is tomographically evident beneath the Alps at ∼550 km depth. By contrast, dominantly felsic HP fragments and mafic granulites remain positively buoyant and tend be incorporated into an orogen and be exhumed with it. Felsic and intermediate lithotypes remain positively buoyant even where deformation and fluid percolation allowed them to equilibrate at HP

Entrepreneurial growth and ownership under market socialism in China: a longitudinal case study of small business growth

How firms grow is still a mystery and a definitive explanation remains elusive. This is especially the case for emerging economies, where the development of research into business growth has been notably slow whilst emerging business ventures are developing at hyper speed. Since most empirical studies have focused on the quantitative differences in growth across firms, this paper adopts a longitudinal case study approach to explore the qualitative differences in terms of how various types of firm achieve their growth outcomes in the organisational development process over a prolonged period of time. Through a theoretical lens which focuses on growth process approaches, this study not only demonstrates that entrepreneurial processes take different forms and dimensions in different contexts, but it also provides insights into the interactions of various organisational factors underpinning the strategies and changes that lead to contrasting growth outcomes. Case study findings assert that the ownership factor is a key contingent factor that shapes management structure and resources which, in turn, affect particular entrepreneurial outcomes. Furthermore, a combination of leadership style and the approach to knowledge management also play critical roles in the learning process which, tends to determine the strategy choice of either high or low value added product strategy. The findings of this research are that small firms with a low value product strategy can improve their survival chances and growth through the vertical broadening of a product portfolio in synchrony with increasing production and technology advancement. The case study companies show a tendency to reinforce their industry position by adopting contrasting choices for growth. The paper addresses the challenges and managerial implications for Western company managers in different growth contexts

Physiological Correlates of Volunteering

We review research on physiological correlates of volunteering, a neglected but promising research field. Some of these correlates seem to be causal factors influencing volunteering. Volunteers tend to have better physical health, both self-reported and expert-assessed, better mental health, and perform better on cognitive tasks. Research thus far has rarely examined neurological, neurochemical, hormonal, and genetic correlates of volunteering to any significant extent, especially controlling for other factors as potential confounds. Evolutionary theory and behavioral genetic research suggest the importance of such physiological factors in humans. Basically, many aspects of social relationships and social activities have effects on health (e.g., Newman and Roberts 2013; Uchino 2004), as the widely used biopsychosocial (BPS) model suggests (Institute of Medicine 2001). Studies of formal volunteering (FV), charitable giving, and altruistic behavior suggest that physiological characteristics are related to volunteering, including specific genes (such as oxytocin receptor [OXTR] genes, Arginine vasopressin receptor [AVPR] genes, dopamine D4 receptor [DRD4] genes, and 5-HTTLPR). We recommend that future research on physiological factors be extended to non-Western populations, focusing specifically on volunteering, and differentiating between different forms and types of volunteering and civic participation

Doctor of Philosophy

dissertationAstrocytes are glial cells that make up 50% of brain volume, with each one wrapping around thousands of synapses. In the presence of neuronal activity, astrocytes exhibit calcium transients, hinting that these cells may be playing an active role in regulating brain activity. Evidence suggests that astrocytes are involved in synaptic plasticity, buffering of extracellular ions, and several neurological disorders. However, the underlying mechanisms of their calcium signals and how they lead to these functions remain unclear. We begin by examining the data collected by our collaborators, in which they evoked calcium responses via brief stimulant applications. Even in this controlled setup, calcium transients exhibit a vast range of amplitudes and durations, with some presenting multiple peaks after one stimulus. We develop a computational model that captures the diversity of responses and use it to propose a classification system for the types of transients observed. Further, we demonstrate that calcium activity in an astrocyte can influence neuronal activity by affecting extracellular ion concentrations. We show that variability in the time course of the signaling molecule IP3 is enough to create the variability of the observed calcium responses. We investigate the source of this variability through a novel stochastic process in which n particles are diffusing and interacting with receptors. We derive mathematical results related to this process by considering our system in several ways: as a spatial diffusion process with recharging receptors; as a continuous-time Markov process approximating the original system; and as a system of ODEs in a mean-field approximation. We prove that by accounting for the finite recharge time that occurs between binding events, the expected number of captured particles has an upper-bound of order log(n). Thus, only a small number of molecules are binding to receptors, leading to more variability than previously expected. Further, we find that through ensheathment (how tight an astrocyte wraps a synapse), astrocytes can tune the time course of neurotransmitters in the synaptic cleft, and thus the strength of neuronal connections. Lastly, we discuss preliminary work on incorporating these results into a new type of neuronal network that includes the effects of astrocytes