Non-parametric models in the monitoring of engine performance and condition: Part 2: non-intrusive estimation of diesel engine cylinder pressure and its use in fault detection

An application of the radial basis function model, described in Part 1, is demonstrated on a four-cylinder DI diesel engine with data from a wide range of speed and load settings. The prediction capabilities of the trained model are validated against measured data and an example is given of the application of this model to the detection of a slight fault in one of the cylinders

Neuronal Activity in the Human Subthalamic Nucleus Encodes Decision Conflict during Action Selection

The subthalamic nucleus (STN), which receives excitatory inputs from the cortex and has direct connections with the inhibitory pathways\ud of the basal ganglia, is well positioned to efficiently mediate action selection. Here, we use microelectrode recordings captured during\ud deep brain stimulation surgery as participants engage in a decision task to examine the role of the human STN in action selection. We\ud demonstrate that spiking activity in the STN increases when participants engage in a decision and that the level of spiking activity\ud increases with the degree of decision conflict. These data implicate the STN as an important mediator of action selection during decision\ud processes.\u

Know-how, intellectualism, and memory systems

ABSTRACTA longstanding tradition in philosophy distinguishes between knowthatand know-how. This traditional “anti-intellectualist” view is soentrenched in folk psychology that it is often invoked in supportof an allegedly equivalent distinction between explicit and implicitmemory, derived from the so-called “standard model of memory.”In the last two decades, the received philosophical view has beenchallenged by an “intellectualist” view of know-how. Surprisingly, defenders of the anti-intellectualist view have turned to the cognitivescience of memory, and to the standard model in particular, todefend their view. Here, I argue that this strategy is a mistake. As it turns out, upon closer scrutiny, the evidence from cognitivepsychology and neuroscience of memory does not support theanti-intellectualist approach, mainly because the standard modelof memory is likely wrong. However, this need not be interpretedas good news for the intellectualist, for it is not clear that theempirical evidence necessarily supp..

A Rebound Effect After Stereotype Threat?

Two studies investigated a potential cognitive mediator for stereotype threat, a phenomenon whereby the mere threat of confirming a negative stereotype results in a performance deficit. It was hypothesized that people attempt to suppress stereotypes in memory during threatening situations, consuming cognitive resources, but that the suppression is released after the threatening situation has ended. This results in a “rebound effect” and a subsequent increase in stereotyped thought. The experiments failed to find a significant stereotype threat effect when examined individually, but when the data from the experiments were aggregated aggregated, a performance deficit was found. However, because of the failure to find a significant performance deficit in any one experiment, the results to not directly bear on any potential rebound effect

Emergent Medical Data: Health Information Inferred by Artificial Intelligence

Artificial intelligence (AI) can infer health data from people’s behavior even when their behavior has no apparent connection to their health. AI can monitor one’s location to track the spread of infectious disease, scrutinize retail purchases to identify pregnant customers, and analyze social media to predict who might attempt suicide. These feats are possible because, in modern societies, people continuously interact with internet-enabled software and devices. Smartphones, wearables, and online platforms monitor people’s actions and produce digital traces, the electronic remnants of their behavior. In their raw form, digital traces might not be very interesting or useful; one’s location, retail purchases, and internet browsing habits are relatively mundane data points. However, AI can enhance the value of digital traces by transforming them into something more useful—emergent medical data (EMD). EMD is health information inferred by artificial intelligence from otherwise trivial digital traces. This Article describes how EMD-based profiling is increasingly promoted as a solution to public health crises such as the COVID-19 pandemic, gun violence, and the opioid crisis. However, there is little evidence to show that EMD-based profiling works. Even worse, it can cause significant harm, and current privacy and data protection laws contain loopholes that allow public and private entities to mine EMD without people’s knowledge or consent. After describing the risks and benefits of EMD mining and profiling, the Article proposes six different ways of conceptualizing these practices. It concludes with preliminary recommendations for effective regulation. Potential options include banning or restricting the collection of digital traces, regulating EMD mining algorithms, and restricting how EMD can be used once it is produced

Racism and Redistribution in the United States: A Solution to the Problem of American Exceptionalism

The two main political parties in the United States put forth policies on redistribution and on issues pertaining directly to race. We argue that redistributive politics in America can be fully understood only by taking account of the interconnection between these issues, and the effects of political competition upon the multi-dimensional party platforms. We identify two mechanisms through which racism among American voters decreases the degree of redistribution that would otherwise obtain. Many authors have suggested that voter racism decreases the degree of redistribution due to an anti-solidarity effect: that (some) voters oppose government transfer payments to minorities whom they view as undeserving. We point to a second effect as well: that some voters who desire redistribution nevertheless vote for the anti-redistributive party (the Republicans) because that party's position on the race issue is more consonant with their own, and this, too, decreases the degree of redistribution. We call this the policy bundle effect. The effect of voter racism on redistribution is the sum of these two effects. We propose a formal model of multi-dimensional political competition that enables us to estimate the magnitude of these two effects, and estimate the model for the period 1976-1992. We numerically compute that during this period voter racism reduced the income tax rate by 11-18 percentage points; the total effect decomposes about equally into the two sub-effects. We also find that the Democratic vote share is 5-38 percentage points lower than it would have been, absent racism.racism, distribution,endogenous parties, party unanimity Nash equilibrium, anti-solidarity effect

Illusory correlation: interplay of evaluative group impression and item-specific episodic memory

Illusory Correlation (IC) is the perception that two events are associated with each other, when in reality they are not. The current study tested predictions of the Multiple Component Model (MCM) regarding the role different types of information (i.e., evaluative and item-specific information) play in producing the IC effect. The current study extended previous experiments on IC, particularly that by Van Rooy, Vanhoomissen and Van Overwalle (2013), in using two independent trait dimensions (i.e., Common Trait and Rare Trait), rather than the traditionally used one evaluative dimension (i.e., frequent, desirable vs. infrequent, undesirable behaviours). The MCM predicted that, judgements based on evaluative information, would result in an association between the majority group and the common trait (Majority-Common Trait), whereas the minority group would be associated with the rare trait (Minority-Rare Trait). For judgements based on item-specific ! episodic memory, the MCM predicted enhanced memory amongst participants for Minority-Rare Trait statements. Partial support was found for both predictions: Participants did develop a Majority-Common Trait association, but no particular association was formed with the minority group. Additionally, participants did show enhanced memory for Minority-Rare Trait statements. However, they also showed unexpected enhanced memory for Majority-Rare Trait statements. Together, the current results further elucidate the interplay of evaluative and item-specific information when reporting judgments on a majority and minority group respectively. The finding of a Majority-Rare Trait association however, implies the need for further studies to examine the exact nature (i.e., evaluative or episodic) of this association and its implications in causing IC