An experimental study of the intrinsic stability of random forest variable importance measures

BACKGROUND: The stability of Variable Importance Measures (VIMs) based on random forest has recently received increased attention. Despite the extensive attention on traditional stability of data perturbations or parameter variations, few studies include influences coming from the intrinsic randomness in generating VIMs, i.e. bagging, randomization and permutation. To address these influences, in this paper we introduce a new concept of intrinsic stability of VIMs, which is defined as the self-consistence among feature rankings in repeated runs of VIMs without data perturbations and parameter variations. Two widely used VIMs, i.e., Mean Decrease Accuracy (MDA) and Mean Decrease Gini (MDG) are comprehensively investigated. The motivation of this study is two-fold. First, we empirically verify the prevalence of intrinsic stability of VIMs over many real-world datasets to highlight that the instability of VIMs does not originate exclusively from data perturbations or parameter variations, but also stems from the intrinsic randomness of VIMs. Second, through Spearman and Pearson tests we comprehensively investigate how different factors influence the intrinsic stability. RESULTS: The experiments are carried out on 19 benchmark datasets with diverse characteristics, including 10 high-dimensional and small-sample gene expression datasets. Experimental results demonstrate the prevalence of intrinsic stability of VIMs. Spearman and Pearson tests on the correlations between intrinsic stability and different factors show that #feature (number of features) and #sample (size of sample) have a coupling effect on the intrinsic stability. The synthetic indictor, #feature/#sample, shows both negative monotonic correlation and negative linear correlation with the intrinsic stability, while OOB accuracy has monotonic correlations with intrinsic stability. This indicates that high-dimensional, small-sample and high complexity datasets may suffer more from intrinsic instability of VIMs. Furthermore, with respect to parameter settings of random forest, a large number of trees is preferred. No significant correlations can be seen between intrinsic stability and other factors. Finally, the magnitude of intrinsic stability is always smaller than that of traditional stability. CONCLUSION: First, the prevalence of intrinsic stability of VIMs demonstrates that the instability of VIMs not only comes from data perturbations or parameter variations, but also stems from the intrinsic randomness of VIMs. This finding gives a better understanding of VIM stability, and may help reduce the instability of VIMs. Second, by investigating the potential factors of intrinsic stability, users would be more aware of the risks and hence more careful when using VIMs, especially on high-dimensional, small-sample and high complexity datasets

Can understanding reward help illuminate anhedonia?

Purpose of review: The goal of this paper is to examine how reward processing might help us understand the symptom of anhedonia. Recent findings: There are extensive reviews exploring the relationship between responses to rewarding stimuli and depression. These often include a discussion on anhedonia and how this might be underpinned in particular by dysfunctional reward processing. However, there is no specific consensus on whether studies to date have adequately examined the various sub-components of reward processing or how these might relate in turn to various aspects of anhedonia symptoms. Summary: The approach to understanding the symptom of anhedonia should be to examine all the sub-components of reward processing at the subjective and objective behavioural and neural level, with well validated tasks that can be replicated. Investigating real life experiences of anhedonia and how theses might be predicted by objective lab measures is also needed in future research

Space Charge at Nanoscale: Probing Injection and Dynamic Phenomena Under Dark/Light Configurations by Using KPFM and C-AFM

International audienc

Sex dependency of inhibitory control functions

BACKGROUND: Inhibition of irrelevant responses is an important aspect of cognitive control of a goal-directed behavior. Females and males show different levels of susceptibility to neuropsychological disorders such as impulsive behavior and addiction, which might be related to differences in inhibitory brain functions. METHODS: We examined the effects of ‘practice to inhibit’, as a model of rehabilitation approach, and ‘music’, as a salient contextual factor in influencing cognition, on the ability of females and males to perform a stop-signal task that required inhibition of initiated or planned responses. In go trials, the participants had to rapidly respond to a directional go cue within a limited time window. In stop trials, which were presented less frequently, a stop signal appeared immediately after the go-direction cue and the participants had to stop their responses. RESULTS: We found a significant difference between females and males in benefiting from practice in the stop-signal task: the percentage of correct responses in the go trials increased, and the ability to inhibit responses significantly improved, after practice in females. While listening to music, females became faster but males became slower in responding to the go trials. Both females and males became slower in performing the go trials following an error in the stop trials; however, music significantly affected this post-error slowing depending on the sex. Listening to music decreased post-error slowing in females but had an opposite effect in males. CONCLUSIONC: Here, we show a significant difference in executive control functions and their modulation by contextual factors between females and males that might have implications for the differences in their propensity for particular neuropsychological disorders and related rehabilitation approaches

World guidelines for falls prevention and management for older adults: a global initiative

Background: falls and fall-related injuries are common in older adults, have negative effects on functional independence and quality of life and are associated with increased morbidity, mortality and health related costs. Current guidelines are inconsistent, with no up-to-date, globally applicable ones present. Objectives: to create a set of evidence- and expert consensus-based falls prevention and management recommendations applicable to older adults for use by healthcare and other professionals that consider: (i) a person-centred approach that includes the perspectives of older adults with lived experience, caregivers and other stakeholders; (ii) gaps in previous guidelines; (iii) recent developments in e-health and (iv) implementation across locations with limited access to resources such as low- and middle-income countries. Methods: a steering committee and a worldwide multidisciplinary group of experts and stakeholders, including older adults, were assembled. Geriatrics and gerontological societies were represented. Using a modified Delphi process, recommendations from 11 topic-specific working groups (WGs), 10 ad-hoc WGs and a WG dealing with the perspectives of older adults were reviewed and refined. The final recommendations were determined by voting. Recommendations: all older adults should be advised on falls prevention and physical activity. Opportunistic case finding for falls risk is recommended for community-dwelling older adults. Those considered at high risk should be offered a comprehensive multifactorial falls risk assessment with a view to co-design and implement personalised multidomain interventions. Other recommendations cover details of assessment and intervention components and combinations, and recommendations for specific settings and populations. Conclusions: the core set of recommendations provided will require flexible implementation strategies that consider both local context and resources

Automated Off-Body Cartesian Mesh Adaption for Rotorcraft Simulations

A new adaptive mesh refinement strategy is presented that couples feature-detection with local error-estimation. The goal is to guide refinement to key vortical features using feature detection, and to terminate refinement when a maximum acceptable error level has been reached. The feature detection scheme, which has been presented in previous related work, uses a special local normalization that allows it to properly identify regions of high vortical strength without tuning to a particular vorticity value. The newly introduced error estimation scheme applies a Richardson extrapolation-like procedure to detect local truncation error based on solutions from different grid levels. The error is then used the computed error to determine when to cut off further refinement. The paper presents a theoretical analysis of the scheme, applying it to computations of an isolated vortex and comparing to an exact solution. The scheme is implemented as part of the off-body Cartesian solver in the Helios code. Two practical cases are considered, resolution of the wake tip vortex from a NACA 0015 wing, and resolution of the wake structure of a quarter-scale V22 rotorcraft. I