An ant colony-based semi-supervised approach for learning classification rules

Semi-supervised learning methods create models from a few labeled instances and a great number of unlabeled instances. They appear as a good option in scenarios where there is a lot of unlabeled data and the process of labeling instances is expensive, such as those where most Web applications stand. This paper proposes a semi-supervised self-training algorithm called Ant-Labeler. Self-training algorithms take advantage of supervised learning algorithms to iteratively learn a model from the labeled instances and then use this model to classify unlabeled instances. The instances that receive labels with high confidence are moved from the unlabeled to the labeled set, and this process is repeated until a stopping criteria is met, such as labeling all unlabeled instances. Ant-Labeler uses an ACO algorithm as the supervised learning method in the self-training procedure to generate interpretable rule-based models—used as an ensemble to ensure accurate predictions. The pheromone matrix is reused across different executions of the ACO algorithm to avoid rebuilding the models from scratch every time the labeled set is updated. Results showed that the proposed algorithm obtains better predictive accuracy than three state-of-the-art algorithms in roughly half of the datasets on which it was tested, and the smaller the number of labeled instances, the better the Ant-Labeler performance

The Effect of Learning to Drum on Behaviour and Brain Function in Autistic Adolescents

There is an acknowledged need for improved service provision in the context of autism spectrum disorders. Previous studies have demonstrated the positive role drum training can play in improving behavioral outcomes for children and adolescents with emotional and behavioral difficulties. However, to date, none of these studies has explored how these behavioral changes translate at the neural level. Our study provides strong evidence that drumming not only reduces hyperactivity and inattention in autistic adolescents but also strengthens functional connectivity in brain regions responsible for inhibitory control and action outcome monitoring

Enrichment and characterization of ammonia-oxidizing archaea from the open ocean : phylogeny, physiology and stable isotope fractionation

Author Posting. © The Author(s), 2011. This is the author's version of the work. It is posted here by permission of Nature Publishing Group for personal use, not for redistribution. The definitive version was published in The ISME Journal 5 (2011): 1796–1808, doi:10.1038/ismej.2011.58.Archaeal genes for ammonia oxidation are widespread in the marine environment, but direct physiological evidence for ammonia oxidation by marine archaea is limited. We report the enrichment and characterization of three strains of pelagic ammonia-oxidizing archaea (AOA) from the north Pacific Ocean that have been maintained in laboratory culture for over three years. Phylogenetic analyses indicate the three strains belong to a previously identified clade of water column-associated AOA and possess 16S rRNA genes and ammonia monooxygenase subunit a (amoA) genes highly similar (98-99% identity) to those recovered in DNA and cDNA clone libraries from the open ocean. The strains grow in natural seawater-based liquid medium while stoichiometrically converting ammonium (NH4 +) to nitrite (NO2 -). Ammonia oxidation by the enrichments is only partially inhibited by allylthiourea at concentrations known to inhibit cultivated ammonia-oxidizing bacteria. The three strains were used to determine the nitrogen stable isotope effect (15εNH3) during archaeal ammonia oxidation, an important parameter for interpreting stable isotope ratios in the environment. Archaeal 15εNH3 ranged from 13- 41‰, within the range of that previously reported for ammonia-oxidizing bacteria. Despite low amino acid identity between the archaeal and bacterial Amo proteins, their functional diversity as captured by 15εNH3 is similar.This work was supported by a Woods Hole Oceanographic Institution (WHOI) Postdoctoral Scholar fellowship to AES and the WHOI Ocean Life Institute

Variability and magnitude of brain glutamate levels in schizophrenia: a meta and mega-analysis

Glutamatergic dysfunction is implicated in schizophrenia pathoaetiology, but this may vary in extent between patients. It is unclear whether inter-individual variability in glutamate is greater in schizophrenia than the general population. We conducted meta-analyses to assess (1) variability of glutamate measures in patients relative to controls (log coefficient of variation ratio: CVR); (2) standardised mean differences (SMD) using Hedges g; (3) modal distribution of individual-level glutamate data (Hartigan’s unimodality dip test). MEDLINE and EMBASE databases were searched from inception to September 2022 for proton magnetic resonance spectroscopy (1H-MRS) studies reporting glutamate, glutamine or Glx in schizophrenia. 123 studies reporting on 8256 patients and 7532 controls were included. Compared with controls, patients demonstrated greater variability in glutamatergic metabolites in the medial frontal cortex (MFC, glutamate: CVR = 0.15, p < 0.001; glutamine: CVR = 0.15, p = 0.003; Glx: CVR = 0.11, p = 0.002), dorsolateral prefrontal cortex (glutamine: CVR = 0.14, p = 0.05; Glx: CVR = 0.25, p < 0.001) and thalamus (glutamate: CVR = 0.16, p = 0.008; Glx: CVR = 0.19, p = 0.008). Studies in younger, more symptomatic patients were associated with greater variability in the basal ganglia (BG glutamate with age: z = −0.03, p = 0.003, symptoms: z = 0.007, p = 0.02) and temporal lobe (glutamate with age: z = −0.03, p = 0.02), while studies with older, more symptomatic patients associated with greater variability in MFC (glutamate with age: z = 0.01, p = 0.02, glutamine with symptoms: z = 0.01, p = 0.02). For individual patient data, most studies showed a unimodal distribution of glutamatergic metabolites. Meta-analysis of mean differences found lower MFC glutamate (g = −0.15, p = 0.03), higher thalamic glutamine (g = 0.53, p < 0.001) and higher BG Glx in patients relative to controls (g = 0.28, p < 0.001). Proportion of males was negatively associated with MFC glutamate (z = −0.02, p < 0.001) and frontal white matter Glx (z = −0.03, p = 0.02) in patients relative to controls. Patient PANSS total score was positively associated with glutamate SMD in BG (z = 0.01, p = 0.01) and temporal lobe (z = 0.05, p = 0.008). Further research into the mechanisms underlying greater glutamatergic metabolite variability in schizophrenia and their clinical consequences may inform the identification of patient subgroups for future treatment strategies

Event and scenario recognition in a video surveillance system for radiotherapy treatments

International audiencePurpose/Objective: We propose a module to monitor a treatment room using video cameras in order to assist and reassure the radiation therapist and to record the sequence of events during the treatment delivery process. This module will complement other existing quality assurance systems by adding external information on the patient and the elements surrounding him or her (people and objects). Such information is today rarely taken into account and may be acquired by means of a global viewing scheme. This system may be used to help minimize errors such as patient's identity, detection of involuntary movements, positioning relatively to a unique referential, presence of treatment accessorizes (bolus, ..) and presence of staff or undesired elements during irradiation, etc

Association Between the Probability of Autism Spectrum Disorder and Normative Sex-Related Phenotypic Diversity in Brain Structure

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White matter development and early cognition in babies and toddlers

The normal myelination of neuronal axons is essential to neurodevelopment, allowing fast inter-neuronal communication. The most dynamic period of myelination occurs in the first few years of life, in concert with a dramatic increase in cognitive abilities. How these processes relate, however, is still unclear. Here we aimed to use a data-driven technique to parcellate developing white matter into regions with consistent white matter growth trajectories and investigate how these regions related to cognitive development. In a large sample of 183 children aged 3 months to 4 years, we calculated whole brain myelin volume fraction (VF(M)) maps using quantitative multicomponent relaxometry. We used spatial independent component analysis (ICA) to blindly segment these quantitative VF(M) images into anatomically meaningful parcels with distinct developmental trajectories. We further investigated the relationship of these trajectories with standardized cognitive scores in the same children. The resulting components represented a mix of unilateral and bilateral white matter regions (e.g., cortico-spinal tract, genu and splenium of the corpus callosum, white matter underlying the inferior frontal gyrus) as well as structured noise (misregistration, image artifact). The trajectories of these regions were associated with individual differences in cognitive abilities. Specifically, components in white matter underlying frontal and temporal cortices showed significant relationships to expressive and receptive language abilities. Many of these relationships had a significant interaction with age, with VF(M) becoming more strongly associated with language skills with age. These data provide evidence for a changing coupling between developing myelin and cognitive development. Hum Brain Mapp 35:4475–4487, 2014