Using Bad Learners to find Good Configurations

Finding the optimally performing configuration of a software system for a given setting is often challenging. Recent approaches address this challenge by learning performance models based on a sample set of configurations. However, building an accurate performance model can be very expensive (and is often infeasible in practice). The central insight of this paper is that exact performance values (e.g. the response time of a software system) are not required to rank configurations and to identify the optimal one. As shown by our experiments, models that are cheap to learn but inaccurate (with respect to the difference between actual and predicted performance) can still be used rank configurations and hence find the optimal configuration. This novel \emph{rank-based approach} allows us to significantly reduce the cost (in terms of number of measurements of sample configuration) as well as the time required to build models. We evaluate our approach with 21 scenarios based on 9 software systems and demonstrate that our approach is beneficial in 16 scenarios; for the remaining 5 scenarios, an accurate model can be built by using very few samples anyway, without the need for a rank-based approach.Comment: 11 pages, 11 figure

Automated multi-objective calibration of biological agent-based simulations

Computational agent-based simulation (ABS) is increasingly used to complement laboratory techniques in advancing our understanding of biological systems. Calibration, the identification of parameter values that align simulation with biological behaviours, becomes challenging as increasingly complex biological domains are simulated. Complex domains cannot be characterized by single metrics alone, rendering simulation calibration a fundamentally multi-metric optimization problem that typical calibration techniques cannot handle. Yet calibration is an essential activity in simulation-based science; the baseline calibration forms a control for subsequent experimentation and hence is fundamental in the interpretation of results. Here, we develop and showcase a method, built around multi-objective optimization, for calibrating ABSs against complex target behaviours requiring several metrics (termed objectives) to characterize. Multi-objective calibration (MOC) delivers those sets of parameter values representing optimal trade-offs in simulation performance against each metric, in the form of a Pareto front. We use MOC to calibrate a well-understood immunological simulation against both established a priori and previously unestablished target behaviours. Furthermore, we show that simulation-borne conclusions are broadly, but not entirely, robust to adopting baseline parameter values from different extremes of the Pareto front, highlighting the importance of MOC's identification of numerous calibration solutions. We devise a method for detecting overfitting in a multi-objective context, not previously possible, used to save computational effort by terminating MOC when no improved solutions will be found. MOC can significantly impact biological simulation, adding rigour to and speeding up an otherwise time-consuming calibration process and highlighting inappropriate biological capture by simulations that cannot be well calibrated. As such, it produces more accurate simulations that generate more informative biological predictions

Classic and recent advances in understanding amnesia

Neurological amnesia has been and remains the focus of intense study, motivated by the drive to understand typical and atypical memory function and the underlying brain basis that is involved. There is now a consensus that amnesia associated with hippocampal (and, in many cases, broader medial temporal lobe) damage results in deficits in episodic memory, delayed recall, and recollective experience. However, debate continues regarding the patterns of preservation and impairment across a range of abilities, including semantic memory and learning, delayed recognition, working memory, and imagination. This brief review highlights some of the influential and recent advances in these debates and what they may tell us about the amnesic condition and hippocampal function

A morphological study of retinal changes in unilateral amblyopia using optical coherence tomography image segmentation.

OBJECTIVE: The purpose of this study was to evaluate the possible structural changes of the macula in patients with unilateral amblyopia using optical coherence tomography (OCT) image segmentation. PATIENTS AND METHODS: 38 consecutive patients (16 male; mean age 32.4+/-17.6 years; range 6-67 years) with unilateral amblyopia were involved in this study. OCT examinations were performed with a time-domain OCT device, and a custom-built OCT image analysis software (OCTRIMA) was used for OCT image segmentation. The axial length (AL) was measured by a LenStar LS 900 device. Macular layer thickness, AL and manifest spherical equivalent refraction (MRSE) of the amblyopic eye were compared to that of the fellow eye. We studied if the type of amblyopia (strabismus without anisometropia, anisometropia without strabismus, strabismus with anisometropia) had any influence on macular layer thickness values. RESULTS: There was significant difference between the amblyopic and fellow eyes in MRSE and AL in all subgroups. Comparing the amblyopic and fellow eyes, we found a statistically significant difference only in the thickness of the outer nuclear layer in the central region using linear mixed model analysis keeping AL and age under control (p = 0.032). There was no significant difference in interocular difference in the thickness of any macular layers between the subgroups with one-way between-groups ANCOVA while statistically controlling for interocular difference in AL and age. CONCLUSIONS: According to our results there are subtle changes in amblyopic eyes affecting the outer nuclear layer of the fovea suggesting the possible involvement of the photoreceptors. However, further studies are warranted to support this hypothesis

The gender dimension of intergenerational transfers in Europe

This paper analyses the gender dimension of intergenerational transfers in 15 European countries using National Transfer Accounts (NTA) data on age- and gender-specific transfers in 2010. We combine NTA data with information from life tables to derive measures of gender-specific net transfers over the whole life course and by life stages. The analysis distinguishes between public and private transfer flows, and accounts for transfers of services produced by unpaid work. Furthermore, we analyse public transfers in more detail by decomposing public old-age benefits into yearly averages and the number of years that individuals can expect to be net recipients. In all analysed countries, men contribute more to public transfers and finance a larger proportion of consumption needs of children, compared to women. By contrast, women provide most of the transfers of services produced by unpaid work, such as childcare and household work. While yearly net public benefits in old age are considerably smaller for women in most countries, total public benefits over the whole retirement period are higher for women due to their higher life expectancy

The gender dimension of intergenerational transfers in Europe

The intergenerational transfers system is characterised by a range of gender inequalities. Men provide more resources for the consumption by children and the elderly population, while women provide most of the intergenerational transfer via unpaid housework and childcare. Consequently, women contribute less to the public pension system and therefore receive considerably lower yearly pensions. However, their higher life expectancy makes women net recipients of transfers for a considerably longer time than men. This paper analyses the gender dimension of intergenerational transfers in European countries using National Transfer Accounts data on age- and gender-specific transfers in 2010. It takes into account public and private transfers, considering contributions as well as benefits. The results show that the yearly net public benefits in old age are considerably smaller for women. However, because of the higher female life expectancy, the total amount of net public benefits over the course of the retirement period is higher for women in most countries

The evolution of language: a comparative review

For many years the evolution of language has been seen as a disreputable topic, mired in fanciful "just so stories" about language origins. However, in the last decade a new synthesis of modern linguistics, cognitive neuroscience and neo-Darwinian evolutionary theory has begun to make important contributions to our understanding of the biology and evolution of language. I review some of this recent progress, focusing on the value of the comparative method, which uses data from animal species to draw inferences about language evolution. Discussing speech first, I show how data concerning a wide variety of species, from monkeys to birds, can increase our understanding of the anatomical and neural mechanisms underlying human spoken language, and how bird and whale song provide insights into the ultimate evolutionary function of language. I discuss the ‘‘descended larynx’ ’ of humans, a peculiar adaptation for speech that has received much attention in the past, which despite earlier claims is not uniquely human. Then I will turn to the neural mechanisms underlying spoken language, pointing out the difficulties animals apparently experience in perceiving hierarchical structure in sounds, and stressing the importance of vocal imitation in the evolution of a spoken language. Turning to ultimate function, I suggest that communication among kin (especially between parents and offspring) played a crucial but neglected role in driving language evolution. Finally, I briefly discuss phylogeny, discussing hypotheses that offer plausible routes to human language from a non-linguistic chimp-like ancestor. I conclude that comparative data from living animals will be key to developing a richer, more interdisciplinary understanding of our most distinctively human trait: language

Elemental spatial and temporal association formation in left temporal lobe epilepsy

The mesial temporal lobe (MTL) is typically understood as a memory structure in clinical settings, with the sine qua non of MTL damage in epilepsy being memory impairment. Recent models, however, understand memory as one of a number of higher cognitive functions that recruit the MTL through their reliance on more fundamental processes, such as “self-projection” or “association formation”. We examined how damage to the left MTL influences these fundamental processes through the encoding of elemental spatial and temporal associations. We used a novel fMRI task to image the encoding of simple visual stimuli, either rich or impoverished, in spatial or spatial plus temporal information. Participants included 14 typical adults (36.4 years, sd. 10.5 years) and 14 patients with left mesial temporal lobe damage as evidenced by a clinical diagnosis of left temporal lobe epilepsy (TLE) and left MTL impairment on imaging (34.3 years, sd. 6.6 years). In-scanner behavioral performance was equivalent across groups. In the typical group whole-brain analysis revealed highly significant bilateral parahippocampal activation (right > left) during spatial associative processing and left hippocampal/parahippocampal deactivation in joint spatial-temporal associative processing. In the left TLE group identical analyses indicated patients used MTL structures contralateral to the seizure focus differently and relied on extra-MTL regions to a greater extent. These results are consistent with the notion that epileptogenic MTL damage is followed by reorganization of networks underlying elemental associative processes. In addition, they provide further evidence that task-related fMRI deactivation can meaningfully index brain function. The implications of these findings for clinical and cognitive neuropsychological models of MTL function in TLE are discussed