Resilience of Supervised Learning Algorithms to Discriminatory Data Perturbations

Discrimination is a focal concern in supervised learning algorithms augmenting human decision-making. These systems are trained using historical data, which may have been tainted by discrimination, and may learn biases against the protected groups. An important question is how to train models without propagating discrimination. In this study, we i) define and model discrimination as perturbations of a data-generating process and show how discrimination can be induced via attributes correlated with the protected attributes; ii) introduce a measure of resilience of a supervised learning algorithm to potentially discriminatory data perturbations, iii) propose a novel supervised learning algorithm that inhibits discrimination, and iv) show that it is more resilient to discriminatory perturbations in synthetic and real-world datasets than state-of-the-art learning algorithms. The proposed method can be used with general supervised learning algorithms and avoids inducement of discrimination, while maximizing model accuracy.Comment: 17 pages, 10 figures, 1 tabl

Obesity Induces Hypothalamic Endoplasmic Reticulum Stress and Impairs Proopiomelanocortin (POMC) Post-translational Processing

It was shown previously that abnormal prohormone processing or inactive proconverting enzymes that are responsible for this processing cause profound obesity. Our laboratory demonstrated earlier that in the diet-induced obesity (DIO) state, the appetite-suppressing neuropeptide -melanocyte-stimulating hormone ( -MSH) is reduced, yet the mRNA of its precursor protein proopiomelanocortin (POMC) remained unaltered. It was also shown that the DIO condition promotes the development of endoplasmic reticulum (ER) stress and leptin resistance. In the current study, using an in vivo model combined with in vitro experiments, we demonstrate that obesity-induced ER stress obstructs the post-translational processing of POMC by decreasing proconverting enzyme 2, which catalyzes the conversion of adrenocorticotropin to -MSH, thereby decreasing -MSH peptide production. This novel mechanism of ER stress affecting POMC processing in DIO highlights the importance of ER stress in regulating central energy balance in obesity.Fil: Cakir, Isin. Brown University; Estados UnidosFil: Cyr, Nicole E.. Brown University; Estados UnidosFil: Perello, Mario. Brown University; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Litvinov, Bogdan Patedakis. Brown University; Estados UnidosFil: Romero, Amparo. Brown University; Estados UnidosFil: Stuart, Ronald C.. Brown University; Estados UnidosFil: Nillni, Eduardo A.. Brown University; Estados Unido

Adaptively Optimised Adaptive Importance Samplers

We introduce a new class of adaptive importance samplers leveraging adaptive optimisation tools, which we term AdaOAIS. We build on Optimised Adaptive Importance Samplers (OAIS), a class of techniques that adapt proposals to improve the mean-squared error of the importance sampling estimators by parameterising the proposal and optimising the $\chi^2$-divergence between the target and the proposal. We show that a naive implementation of OAIS using stochastic gradient descent may lead to unstable estimators despite its convergence guarantees. To remedy this shortcoming, we instead propose to use adaptive optimisers (such as AdaGrad and Adam) to improve the stability of the OAIS. We provide convergence results for AdaOAIS in a similar manner to OAIS. We also provide empirical demonstration on a variety of examples and show that AdaOAIS lead to stable importance sampling estimators in practice.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Physiological Measures of Risk Perception in Highly Automated Driving

Highly automated driving will likely result in drivers being out-of-the-loop during specific scenarios and engaging in a wide range of non-driving related tasks. Manifesting in lower levels of risk perception to emerging events, and thus affect drivers' availability to take-over manual control in safety-critical scenarios. In this empirical research, we measured drivers' (N = 20) risk perception with cardiac and skin conductance indicators through a series of high-fidelity, simulated highly automated driving scenarios. By manipulating the presence of surrounding traffic and changing driving conditions as long-term risk modulators, and including a driving hazard event as a short-term risk modulator, we hypothesised that an increase in risk perception would induce greater physiological arousal. Our results demonstrate that heart rate variability features are superior at capturing arousal variations from these long-term, low to moderate risk scenarios. In contrast, skin conductance responses are more sensitive to rapidly evolving situations associated with moderate to high risk. Based on this research, future driver state monitoring systems should adopt multiple physiological measures to capture changes in the long and short term, modulation of risk perception. This will enable enhanced perception of driver readiness and improved availability to safely deal with take-over events when requested by an automated vehicle.</p

Using fNIRS to Verify Trust in Highly Automated Driving

Trust in automation is crucial for the safe and appropriate adoption of automated driving technology. Current research methods to measure trust mainly rely on subjective scales, with several intrinsic limitations. This empirical experiment proposes a novel method to measure trust objectively, using functional near-infrared spectroscopy (fNIRS). Through manipulating participants’ expectations regarding driving automation credibility, we have induced and successfully measured opposing levels of trust in automation. Most notably, our results evidence two separate yet interrelated cortical mechanisms for trust and distrust. Trust is demonstrably linked to decreased monitoring and working memory, whereas distrust is event-related and strongly tied to affective (or emotional) mechanisms. This paper evidence that trust in automation and situation awareness are strongly interrelated during driving automation usage. Our findings are crucial for developing future driver state monitoring technology that mitigates the impact of inappropriate reliance, or over trust, in automated driving systems

Effects of Local Weather Variation on Water-column Stratification and Hypoxia in the Western, Sandusky, and Central Basins of Lake Erie

Hypoxia, low dissolved oxygen (DO) concentrations (<2 mg/L), has been a major issue in Lake Erie for decades. While much emphasis has been placed on biological factors, particularly algal blooms, contributing to hypolimnetic oxygen depletion, there has been little focus on the role of weather. For this study, we monitored water temperature and DO concentrations at sites in the western, central, and Sandusky basins in Lake Erie during June and July 2010–2012. We then compared trends in stratification and DO concentrations to weather patterns during that period. We found that during those three years, there was significant variation in weather patterns, particularly decreased ice coverage and increased storm events in 2012. These weather patterns corresponded to 2012 having the warmest water temperatures, some of the lowest DO concentrations, and a deeper and thinner hypolimnion (especially in the central basin) than the previous years. We found a relationship between weather and hypoxia, providing further evidence for why these basins are susceptible to low DO conditions during summer months. The role of weather in hypoxia is another indication that the lake is vulnerable to effects of climate change and should be considered in management strategies

Visualizing Poiseuille flow of hydrodynamic electrons

Hydrodynamics is a general description for the flow of a fluid, and is expected to hold even for fundamental particles such as electrons when inter-particle interactions dominate. While various aspects of electron hydrodynamics were revealed in recent experiments, the fundamental spatial structure of hydrodynamic electrons, the Poiseuille flow profile, has remained elusive. In this work, we provide the first real-space imaging of Poiseuille flow of an electronic fluid, as well as visualization of its evolution from ballistic flow. Utilizing a scanning nanotube single electron transistor, we image the Hall voltage of electronic flow through channels of high-mobility graphene. We find that the profile of the Hall field across the channel is a key physical quantity for distinguishing ballistic from hydrodynamic flow. We image the transition from flat, ballistic field profiles at low temperature into parabolic field profiles at elevated temperatures, which is the hallmark of Poiseuille flow. The curvature of the imaged profiles is qualitatively reproduced by Boltzmann calculations, which allow us to create a 'phase diagram' that characterizes the electron flow regimes. Our results provide long-sought, direct confirmation of Poiseuille flow in the solid state, and enable a new approach for exploring the rich physics of interacting electrons in real space

Differential Subplastidial Localization and Turnover of Enzymes Involved in Isoprenoid Biosynthesis in Chloroplasts

Plastidial isoprenoids are a diverse group of metabolites with roles in photosynthesis, growth regulation, and interaction with the environment. The methylerythritol 4-phosphate (MEP) pathway produces the metabolic precursors of all types of plastidial isoprenoids. Proteomics studies in Arabidopsis thaliana have shown that all the enzymes of the MEP pathway are localized in the plastid stroma. However, immunoblot analysis of chloroplast subfractions showed that the first two enzymes of the pathway, deoxyxylulose 5-phosphate synthase (DXS) and reductoisomerase (DXR), can also be found in non-stromal fractions. Both transient and stable expression of GFP-tagged DXS and DXR proteins confirmed the presence of the fusion proteins in distinct subplastidial compartments. In particular, DXR-GFP was found to accumulate in relatively large vesicles that could eventually be released from chloroplasts, presumably to be degraded by an autophagy-independent process. Together, we propose that protein-specific mechanisms control the localization and turnover of the first two enzymes of the MEP pathway in Arabidopsis chloroplasts

Obesity Induces Hypothalamic Endoplasmic Reticulum Stress and Impairs Proopiomelanocortin (POMC) Post-translational Processing

It was shown previously that abnormal prohormone processing or inactive proconverting enzymes that are responsible for this processing cause profound obesity. Our laboratory demonstrated earlier that in the diet-induced obesity (DIO) state, the appetite-suppressing neuropeptide -melanocyte-stimulating hormone ( -MSH) is reduced, yet the mRNA of its precursor protein proopiomelanocortin (POMC) remained unaltered. It was also shown that the DIO condition promotes the development of endoplasmic reticulum (ER) stress and leptin resistance. In the current study, using an in vivo model combined with in vitro experiments, we demonstrate that obesity-induced ER stress obstructs the post-translational processing of POMC by decreasing proconverting enzyme 2, which catalyzes the conversion of adrenocorticotropin to -MSH, thereby decreasing -MSH peptide production. This novel mechanism of ER stress affecting POMC processing in DIO highlights the importance of ER stress in regulating central energy balance in obesity.Fil: Cakir, Isin. Brown University; Estados UnidosFil: Cyr, Nicole E.. Brown University; Estados UnidosFil: Perello, Mario. Brown University; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Litvinov, Bogdan Patedakis. Brown University; Estados UnidosFil: Romero, Amparo. Brown University; Estados UnidosFil: Stuart, Ronald C.. Brown University; Estados UnidosFil: Nillni, Eduardo A.. Brown University; Estados Unido

Ghrelin Indirectly Activates Hypophysiotropic CRF Neurons in Rodents

Ghrelin is a stomach-derived hormone that regulates food intake and neuroendocrine function by acting on its receptor, GHSR (Growth Hormone Secretagogue Receptor). Recent evidence indicates that a key function of ghrelin is to signal stress to the brain. It has been suggested that one of the potential stress-related ghrelin targets is the CRF (Corticotropin-Releasing Factor)-producing neurons of the hypothalamic paraventricular nucleus, which secrete the CRF neuropeptide into the median eminence and activate the hypothalamic-pituitary-adrenal axis. However, the neural circuits that mediate the ghrelin-induced activation of this neuroendocrine axis are mostly uncharacterized. In the current study, we characterized in vivo the mechanism by which ghrelin activates the hypophysiotropic CRF neurons in mice. We found that peripheral or intra-cerebro-ventricular administration of ghrelin strongly activates c-fos – a marker of cellular activation – in CRF-producing neurons. Also, ghrelin activates CRF gene expression in the paraventricular nucleus of the hypothalamus and the hypothalamic-pituitary-adrenal axis at peripheral level. Ghrelin administration directly into the paraventricular nucleus of the hypothalamus also induces c-fos within the CRF-producing neurons and the hypothalamic-pituitary-adrenal axis, without any significant effect on the food intake. Interestingly, dual-label immunohistochemical analysis and ghrelin binding studies failed to show GHSR expression in CRF neurons. Thus, we conclude that ghrelin activates hypophysiotropic CRF neurons, albeit indirectly