Emotional distress and affective knowledge representation one year after the COVID-19 outbreak.

This study examines whether the detrimental effects of the COVID-19 pandemic on the affectivity of the population extend one year after the outbreak. In an online-mobile session, participants completed surveys (i.e.

Two-step interpretable modeling of ICU-AIs.

We present a novel methodology for integrating high resolution longitudinal data with the dynamic prediction capabilities of survival models. The aim is two-fold: to improve the predictive power while maintaining the interpretability of the models. To go beyond the black box paradigm of artificial neural networks, we propose a parsimonious and robust semi-parametric approach (i.

Beyond simple laboratory studies: Developing sophisticated models to study rich behavior.

Psychology and neuroscience are concerned with the study of behavior, of internal cognitive processes, and their neural foundations. However, most laboratory studies use constrained experimental settings that greatly limit the range of behaviors that can be expressed. While focusing on restricted settings ensures methodological control, it risks impoverishing the object of study: by restricting behavior, we might miss key aspects of cognitive and neural functions.

Learning models for classifying Raman spectra of genomic DNA from tumor subtypes.

An early and accurate detection of different subtypes of tumors is crucial for an effective guidance to personalized therapy and in predicting the ability of tumor to metastasize. Here we exploit the Surface Enhanced Raman Scattering (SERS) platform, based on disordered silver coated silicon nanowires (Ag/SiNWs), to efficiently discriminate genomic DNA of different subtypes of melanoma and colon tumors. The diagnostic information is obtained by performing label free Raman maps of the dried drops of DNA solutions onto the Ag/NWs mat and leveraging the classification ability of learning models to reveal the specific and distinct physico-chemical interaction of tumor DNA molecules with the Ag/NW, here supposed to be partly caused by a different DNA methylation degree.

Humans account for cognitive costs when finding shortcuts: An information-theoretic analysis of navigation.

When faced with navigating back somewhere we have been before we might either retrace our steps or seek a shorter path. Both choices have costs. Here, we ask whether it is possible to characterize formally the choice of navigational plans as a bounded rational process that trades off the quality of the plan (e.

Mapping the mental space of emotional concepts through kinematic measures of decision uncertainty.

Emotional concepts and their mental representations have been extensively studied. Yet, some ecologically relevant aspects, such as how they are processed in ambiguous contexts (e.g.

Evidence for entropy maximisation in human free choice behaviour.

The freedom to choose between options is strongly linked to notions of free will. Accordingly, several studies have shown that individuals demonstrate a preference for choice, or the availability of multiple options, over and above utilitarian value. Yet we lack a decision-making framework that integrates preference for choice with traditional utility maximisation in free choice behaviour.

Physics captured by data-based methods in El Niño prediction.

On average once every four years, the Tropical Pacific warms considerably during events called El Niño, leading to weather disruptions over many regions on Earth. Recent machine-learning approaches to El Niño prediction, in particular, Convolutional Neural Networks (CNNs), have shown a surprisingly high skill at relatively long lead times. In an attempt to understand this high skill, we here use data from distorted physics simulations with the intermediate-complexity Zebiak-Cane model to determine what aspects of El Niño physics are represented in a specific CNN-based classification method.

The road towards understanding embodied decisions.

Most current decision-making research focuses on classical economic scenarios, where choice offers are prespecified and where action dynamics play no role in the decision. However, our brains evolved to deal with different choice situations: "embodied decisions". As examples of embodied decisions, consider a lion that has to decide which gazelle to chase in the savannah or a person who has to select the next stone to jump on when crossing a river.

Unsupervised inference approach to facial attractiveness.

The perception of facial attractiveness is a complex phenomenon which depends on how the observer perceives not only individual facial features, but also their mutual influence and interplay. In the machine learning community, this problem is typically tackled as a problem of regression of the subject-averaged rating assigned to natural faces. However, it has been conjectured that this approach does not capture the complexity of the phenomenon.

CollHaps: a heuristic approach to haplotype inference by parsimony.

Haplotype data play a relevant role in several genetic studies, e.g., mapping of complex disease genes, drug design, and evolutionary studies on populations.

Haplotyping for disease association: a combinatorial approach.

We consider a combinatorial problem derived from haplotyping a population with respect to a genetic disease, either recessive or dominant. Given a set of individuals, partitioned into healthy and diseased, and the corresponding sets of genotypes, we want to infer "bad'' and "good'' haplotypes to account for these genotypes and for the disease. Assume e.

The approximability of the String Barcoding problem.

The String Barcoding (SBC) problem, introduced by Rash and Gusfield (RECOMB, 2002), consists in finding a minimum set of substrings that can be used to distinguish between all members of a set of given strings. In a computational biology context, the given strings represent a set of known viruses, while the substrings can be used as probes for an hybridization experiment via microarray. Eventually, one aims at the classification of new strings (unknown viruses) through the result of the hybridization experiment.

1001 optimal PDB structure alignments: integer programming methods for finding the maximum contact map overlap.

Protein structure comparison is a fundamental problem for structural genomics, with applications to drug design, fold prediction, protein clustering, and evolutionary studies. Despite its importance, there are very few rigorous methods and widely accepted similarity measures known for this problem. In this paper we describe the last few years of developments on the study of an emerging measure, the contact map overlap (CMO), for protein structure comparison.

Haplotyping as perfect phylogeny: a direct approach.

A full haplotype map of the human genome will prove extremely valuable as it will be used in large-scale screens of populations to associate specific haplotypes with specific complex genetic-influenced diseases. A haplotype map project has been announced by NIH. The biological key to that project is the surprising fact that some human genomic DNA can be partitioned into long blocks where genetic recombination has been rare, leading to strikingly fewer distinct haplotypes in the population than previously expected (Helmuth, 2001; Daly et al.

Algorithmic strategies for the single nucleotide polymorphism haplotype assembly problem.

With the consensus human genome sequenced and many other sequencing projects at varying stages of completion, greater attention is being paid to the genetic differences among individuals and the abilities of those differences to predict phenotypes. A significant obstacle to such work is the difficulty and expense of determining haplotypes--sets of variants genetically linked because of their proximity on the genome--for large numbers of individuals for use in association studies. This paper presents some algorithmic considerations in a new approach for haplotype determination: inferring haplotypes from localised polymorphism data gathered from short genome 'fragments.

Toward fully automated genotyping: genotyping microsatellite markers by deconvolution.

Dense genetic linkage maps have been constructed for the human and mouse genomes, with average densities of 2.9 cM and 0.35 cM, respectively.

Nimodipine in acute ischemic stroke: a double-blind controlled study.

Nimodipine (BAY e 9736), a new dihydropyridine derivative, has been shown to reduce neurological deficits and mortality induced by acute cerebral ischemia in experimental studies. We investigated the effects of this calcium antagonist in patients with acute ischemic stroke through a randomized, double-blind, parallel-designed trial in which nimodipine was compared with placebo. Forty-one of 54 screened cases were found to fulfil the inclusion criteria (sudden occurrence of a focal neurological deficit secondary to an acute ischemic event in the carotid area diagnosed after a complete neurological work-up) and entered the study.