Certifying and removing disparate impact

What does it mean for an algorithm to be biased? In U.S. law, unintentional bias is encoded via disparate impact, which occurs when a selection process has widely different outcomes for different groups, even as it appears to be neutral. This legal determination hinges on a definition of a protected class (ethnicity, gender, religious practice) and an explicit description of the process. When the process is implemented using computers, determining disparate impact (and hence bias) is harder. It might not be possible to disclose the process. In addition, even if the process is open, it might be hard to elucidate in a legal setting how the algorithm makes its decisions. Instead of requiring access to the algorithm, we propose making inferences based on the data the algorithm uses. We make four contributions to this problem. First, we link the legal notion of disparate impact to a measure of classification accuracy that while known, has received relatively little attention. Second, we propose a test for disparate impact based on analyzing the information leakage of the protected class from the other data attributes. Third, we describe methods by which data might be made unbiased. Finally, we present empirical evidence supporting the effectiveness of our test for disparate impact and our approach for both masking bias and preserving relevant information in the data. Interestingly, our approach resembles some actual selection practices that have recently received legal scrutiny.Comment: Extended version of paper accepted at 2015 ACM SIGKDD Conference on Knowledge Discovery and Data Minin

The A2B adenosine receptor modulates the epithelial- mesenchymal transition through the balance of cAMP/PKA and MAPK/ERK pathway activation in human epithelial lung cells

The epithelial-mesenchymal transition (EMT) is a complex process in which cell phenotype switches from the epithelial to mesenchymal one. The deregulations of this process have been related with the occurrence of different diseases such as lung cancer and fibrosis. In the last decade, several efforts have been devoted in understanding the mechanisms that trigger and sustain this transition process. Adenosine is a purinergic signaling molecule that has been involved in the onset and progression of chronic lung diseases and cancer through the A2Badenosine receptor subtype activation, too. However, the relationship between A2BAR and EMT has not been investigated, yet. Herein, the A2BAR characterization was carried out in human epithelial lung cells. Moreover, the effects of receptor activation on EMT were investigated in the absence and presence of transforming growth factor-beta (TGF-β1), which has been known to promote the transition. The A2BAR activation alone decreased and increased the expression of epithelial markers (E-cadherin) and the mesenchymal one (Vimentin, N-cadherin), respectively, nevertheless a complete EMT was not observed. Surprisingly, the receptor activation counteracted the EMT induced by TGF-β1. Several intracellular pathways regulate the EMT: high levels of cAMP and ERK1/2 phosphorylation has been demonstrated to counteract and promote the transition, respectively. The A2BAR stimulation was able to modulated these two pathways, cAMP/PKA and MAPK/ERK, shifting the fine balance toward activation or inhibition of EMT. In fact, using a selective PKA inhibitor, which blocks the cAMP pathway, the A2BAR-mediated EMT promotion were exacerbated, and conversely the selective inhibition of MAPK/ERK counteracted the receptor-induced transition. These results highlighted the A2BAR as one of the receptors involved in the modulation of EMT process. Nevertheless, its activation is not enough to trigger a complete transition, its ability to affect different intracellular pathways could represent a mechanism at the basis of EMT maintenance/inhibition based on the extracellular microenvironment. Despite further investigations are needed, herein for the first time the A2BAR has been related to the EMT process, and therefore to the different EMT-related pathologies

Causal evidence that intrinsic beta frequency is relevant for enhanced signal propagation in the motor system as shown through rhythmic TMS

Correlative evidence provides support for the idea that brain oscillations underpin neural computations. Recent work using rhythmic stimulation techniques in humans provide causal evidence but the interactions of these external signals with intrinsic rhythmicity remain unclear. Here, we show that sensorimotor cortex precisely follows externally applied rhythmic TMS (rTMS) stimulation in the beta-band but that the elicited responses are strongest at the intrinsic individual beta-peak-frequency. While these entrainment effects are of short duration, even subthreshold rTMS pulses propagate through the network and elicit significant cortico-spinal coupling, particularly when stimulated at the individual beta-frequency. Our results show that externally enforced rhythmicity interacts with intrinsic brain rhythms such that the individual peak frequency determines the effect of rTMS. The observed downstream spinal effect at the resonance frequency provides evidence for the causal role of brain rhythms for signal propagation

The temporal sensitivity to the tactile-induced double flash illusion mediates the impact of beta oscillations on schizotypal personality traits

The coherent experience of the self and the world depends on the ability to integrate vs. segregate sensory information. Optimal temporal integration between the senses is mediated by oscillatory properties of neural activity. Previous research showed reduced temporal sensitivity to multisensory events in schizotypy, a personality trait linked to schizophrenia. Here we used the tactileinduced Double-Flash-Illusion (tDFI) to investigate the tactile-to-visual temporal sensitivity in schizotypy, as indexed by the temporal window of illusion (TWI) and its neural underpinnings. We measured EEG oscillations within the beta band, recently shown to correlate with the tDFI. We found individuals with higher schizotypal traits to have wider TWI and slower beta waves accounting for the temporal window within which they perceive the illusion. Our results indicate reduced tactile-to-visual temporal sensitivity to mediate the effect of slowed oscillatory beta activity on schizotypal personality traits. We conclude that slowed oscillatory patterns might constitute an early marker for psychosis proneness

Bottom-up vs. top-down connectivity imbalance in individuals with high-autistic traits: An electroencephalographic study

Brain connectivity is often altered in autism spectrum disorder (ASD). However, there is little consensus on the nature of these alterations, with studies pointing to either increased or decreased connectivity strength across the broad autism spectrum. An important confound in the interpretation of these contradictory results is the lack of information about the directionality of the tested connections. Here, we aimed at disambiguating these confounds by measuring differences in directed connectivity using EEG resting-state recordings in individuals with low and high autistic traits. Brain connectivity was estimated using temporal Granger Causality applied to cortical signals reconstructed from EEG. Between-group differences were summarized using centrality indices taken from graph theory (in degree, out degree, authority, and hubness). Results demonstrate that individuals with higher autistic traits exhibited a significant increase in authority and in degree in frontal regions involved in high-level mechanisms (emotional regulation, decision-making, and social cognition), suggesting that anterior areas mostly receive information from more posterior areas. Moreover, the same individuals exhibited a significant increase in the hubness and out degree over occipital regions (especially the left and right pericalcarine regions, where the primary visual cortex is located), suggesting that these areas mostly send information to more anterior regions. Hubness and authority appeared to be more sensitive indices than the in degree and out degree. The observed brain connectivity differences suggest that, in individual with higher autistic traits, bottom-up signaling overcomes top-down channeled flow. This imbalance may contribute to some behavioral alterations observed in ASD

Experimental and Numerical Performance Survey of a MW-Scale Supercritical CO2 Compressor Operating in Near-Critical Conditions

Closed power cycles based on carbon dioxide in supercritical conditions (sCO2 in the following) are experiencing a growing scientific, technical and industrial interest, due to the high energy conversion efficiency and components compactness. Despite these advantages, the use of a working fluid operating in proximity to the critical point, especially for the compressor, entails multidisciplinary challenges related to the severe non-ideality of the supercritical fluid, which includes the potential onset of phase change at the impeller intake. On the technical and industrial grounds, the phase-transition might dramatically affect the aerodynamics, the performance and the rangeability of the compressor. On the scientific ground, the modelling of two-phase flows in transonic/supersonic conditions still remains an open issue that demands a thorough experimental assessment. This work illustrates the results of a wide experimental campaign focused on the evaluation of the operative map of a MW-scale high-load sCO2 compressor operating in plant-representative conditions, i.e. in proximity to the critical point (P = 79.8 bar, T = 33°C), designed in the frame of the sCO2Flex project, EU Horizon 2020 funded program (grant agreement #764690). In the design process, the machine had been object of a thorough computational investigation, performed by using a homogeneous equilibrium model equipped with a barotropic equation of state, which revealed a significant impact of the phase change on the compressor aerodynamics and on its rangeability for flow rates higher than the design one. Such phenomena are connected to the sudden drop of the speed of sound, originated when the fluid thermodynamic condition crosses the saturation line, and they weaken as the compressor loading reduces. Experiments carried out on a first of a kind 5 MW sCO2 prototype compressor manufactured and tested by Baker Hughes in 2021 remarkably well matched the predicted compressor performance and, especially, the anticipated and sudden choking of the compressor at nominal peripheral Mach number. Results demonstrates experimentally, for the first time ever, the effects of the phase-change on the operation of a realistic sCO2 compressor, also providing significant insights on the predictive capabilities of the physical models employed for the calculation of two-phase flows in this class of machines

Rhythmic TMS as a Feasible Tool to Uncover the Oscillatory Signatures of Audiovisual Integration

Multisensory integration is quintessential to adaptive behavior, with clinical populations showing significant impairments in this domain, most notably hallucinatory reports. Interestingly, altered cross-modal interactions have also been reported in healthy individuals when engaged in tasks such as the Sound-Induced Flash-Illusion (SIFI). The temporal dynamics of the SIFI have been recently tied to the speed of occipital alpha rhythms (IAF), with faster oscillations entailing reduced temporal windows within which the illusion is experienced. In this regard, entrainment-based protocols have not yet implemented rhythmic transcranial magnetic stimulation (rhTMS) to causally test for this relationship. It thus remains to be evaluated whether rhTMS-induced acoustic and somatosensory sensations may not specifically interfere with the illusion. Here, we addressed this issue by asking 27 volunteers to perform a SIFI paradigm under different Sham and active rhTMS protocols, delivered over the occipital pole at the IAF. Although TMS has been proven to act upon brain tissues excitability, results show that the SIFI occurred for both Sham and active rhTMS, with the illusory rate not being significantly different between baseline and stimulation conditions. This aligns with the discrete sampling hypothesis, for which alpha amplitude modulation, known to reflect changes in cortical excitability, should not account for changes in the illusory rate. Moreover, these findings highlight the viability of rhTMS-based interventions as a means to probe the neuroelectric signatures of illusory and hallucinatory audiovisual experiences, in healthy and neuropsychiatric populations

The Role of Alpha Oscillations among the Main Neuropsychiatric Disorders in the Adult and Developing Human Brain: Evidence from the Last 10 Years of Research

Alpha oscillations (7–13 Hz) are the dominant rhythm in both the resting and active brain. Accordingly, translational research has provided evidence for the involvement of aberrant alpha activ- ity in the onset of symptomatological features underlying syndromes such as autism, schizophrenia, major depression, and Attention Deficit and Hyperactivity Disorder (ADHD). However, findings on the matter are difficult to reconcile due to the variety of paradigms, analyses, and clinical phenotypes at play, not to mention recent technical and methodological advances in this domain. Herein, we seek to address this issue by reviewing the literature gathered on this topic over the last ten years. For each neuropsychiatric disorder, a dedicated section will be provided, containing a concise account of the current models proposing characteristic alterations of alpha rhythms as a core mechanism to trigger the associated symptomatology, as well as a summary of the most relevant studies and scientific con- tributions issued throughout the last decade. We conclude with some advice and recommendations that might improve future inquiries within this field

Fairness-enhancing interventions in stream classification

The wide spread usage of automated data-driven decision support systems has raised a lot of concerns regarding accountability and fairness of the employed models in the absence of human supervision. Existing fairness-aware approaches tackle fairness as a batch learning problem and aim at learning a fair model which can then be applied to future instances of the problem. In many applications, however, the data comes sequentially and its characteristics might evolve with time. In such a setting, it is counter-intuitive to "fix" a (fair) model over the data stream as changes in the data might incur changes in the underlying model therefore, affecting its fairness. In this work, we propose fairness-enhancing interventions that modify the input data so that the outcome of any stream classifier applied to that data will be fair. Experiments on real and synthetic data show that our approach achieves good predictive performance and low discrimination scores over the course of the stream.Comment: 15 pages, 7 figures. To appear in the proceedings of 30th International Conference on Database and Expert Systems Applications, Linz, Austria August 26 - 29, 201