Zoo Tools Pro V2.2.4 For Maya 2021
Introducing all-new tools that let you fine-tune and finish your renders without needing an extra app. Composite render layers, make color corrections, and instantly adjust lighting in the new V-Ray Frame Buffer.
Zoo Tools Pro V2.2.4 For Maya
Repetition suppression paradigms allow a more detailed look at brain functioning than classical paradigms and have been applied vigorously in adult cognitive neuroscience. These paradigms are well suited for studies in the field of developmental cognitive neuroscience as they can be applied without collecting a behavioral response and across all age groups. Furthermore, repetition suppression paradigms can be employed in various neuroscience techniques, such as functional magnetic resonance imaging (fMRI), functional near-infrared spectroscopy (fNIRS), electroencephalography (EEG) and magnetoencephalography (MEG). In the present article we review studies using repetition suppression paradigms in developmental cognitive neuroscience covering the age range from infancy to adolescence. Our first goal is to point out characteristics of developmental repetition suppression effects. In doing so, we discuss the relationship of the direction of repetition effects (suppression vs enhancement) with developmental factors, and address the question how the direction of repetition effects might be related to looking-time effects in behavioral infant paradigms, the most prominently used behavioral measure in infant research. To highlight the potential of repetition suppression paradigms, our second goal is to provide an overview on the insights recently obtained by applying repetition paradigms in neurodevelopmental studies, including research on children with autism spectrum disorders (ASDs). We conclude that repetition suppression paradigms are valuable tools for investigating neurodevelopmental processes, while at the same time we highlight the necessity for further studies that disentangle methodological and developmental factors. Copyright 2016 Elsevier Ltd. All rights reserved.
Repetitive DNA sequences are a major component of eukaryotic genomes and may account for up to 90% of the genome size. They can be divided into minisatellite, microsatellite and satellite sequences. Satellite DNA sequences are considered to be a fast-evolving component of eukaryotic genomes, comprising tandemly-arrayed, highly-repetitive and highly-conserved monomer sequences. The monomer unit of satellite DNA is 150-400 base pairs (bp) in length. Repetitive sequences may be species- or genus-specific, and may be centromeric or subtelomeric in nature. They exhibit cohesive and concerted evolution caused by molecular drive, leading to high sequence homogeneity. Repetitive sequences accumulate variations in sequence and copy number during evolution, hence they are important tools for taxonomic and phylogenetic studies, and are known as "tuning knobs" in the evolution. Therefore, knowledge of repetitive sequences assists our understanding of the organization, evolution and behavior of eukaryotic genomes. Repetitive sequences have cytoplasmic, cellular and developmental effects and play a role in chromosomal recombination. In the post-genomics era, with the introduction of next-generation sequencing technology, it is possible to evaluate complex genomes for analyzing repetitive sequences and deciphering the yet unknown functional potential of repetitive sequences. Copyright 2014 The Authors. Production and hosting by Elsevier Ltd.. All rights reserved.
In an ageing world population more citizens are at risk of cognitive impairment, with negative consequences on their ability of independent living, quality of life and sustainability of healthcare systems. Cognitive neuroscience researchers have identified behavioral anomalies that are significant indicators of cognitive decline. A general goal is the design of innovative methods and tools for continuously monitoring the functional abilities of the seniors at risk and reporting the behavioral anomalies to the clinicians. SmartFABER is a pervasive system targeting this objective. A non-intrusive sensor network continuously acquires data about the interaction of the senior with the home environment during daily activities. A novel hybrid statistical and knowledge-based technique is used to analyses this data and detect the behavioral anomalies, whose history is presented through a dashboard to the clinicians. Differently from related works, SmartFABER can detect abnormal behaviors at a fine-grained level. We have fully implemented the system and evaluated it using real datasets, partly generated by performing activities in a smart home laboratory, and partly acquired during several months of monitoring of the instrumented home of a senior diagnosed with MCI. Experimental results, including comparisons with other activity recognition techniques, show the effectiveness of SmartFABER in terms of recognition rates. Copyright 2016 Elsevier B.V. All rights reserved.
Most of the fastest-growing string collections today are repetitive, that is, most of the constituent documents are similar to many others. As these collections keep growing, a key approach to handling them is to exploit their repetitiveness, which can reduce their space usage by orders of magnitude. We study the problem of indexing repetitive string collections in order to perform efficient document retrieval operations on them. Document retrieval problems are routinely solved by search engines on large natural language collections, but the techniques are less developed on generic string collections. The case of repetitive string collections is even less understood, and there are very few existing solutions. We develop two novel ideas, interleaved LCPs and precomputed document lists , that yield highly compressed indexes solving the problem of document listing (find all the documents where a string appears), top- k document retrieval (find the k documents where a string appears most often), and document counting (count the number of documents where a string appears). We also show that a classical data structure supporting the latter query becomes highly compressible on repetitive data. Finally, we show how the tools we developed can be combined to solve ranked conjunctive and disjunctive multi-term queries under the simple [Formula: see text] model of relevance. We thoroughly evaluate the resulting techniques in various real-life repetitiveness scenarios, and recommend the best choices for each case.
Prader-Willi syndrome (PWS) is a genetically determined neurodevelopmental disorder presenting with behavioral problems including hyperphagia, emotional aberration, and compulsion-like behaviors. This combination of behavioral problems is likely to be caused by damage to the orbitofrontal cortices and anterior temporal lobes or to circuits involving them. To investigate the prevalence of eating and non-eating behavioral disturbances in PWS by using assessment tools developed originally for patients with frontotemporal dementia and with frontal lobe injury. The questionnaire consisted of 35 questions related to three categories of behavior: eating behaviors (including four domains: appetite, food preference, eating habits, and other oral behaviors), stereotypy (including four domains: roaming, speaking, movements, and daily rhythm), and collecting behaviors. It was administered in Japan to the parents of 250 individuals aged 1-42 years with a clinical diagnosis of PWS. The prevalence rates of symptoms in all categories were high. Each domain involved in eating behaviors was significantly correlated with stereotypy and collecting behaviors. The prevalence rates and severity scores of some eating and non-eating behaviors were higher in the older groups. Abnormal eating behaviors, stereotyped behaviors, and collecting behaviors were common in the PWS subjects. There was also a potential link between abnormal eating and non-eating behaviors related to frontal behavioral syndromes. It is likely that these behavioral abnormalities reflect dysfunction of the orbitofrontal cortices and anterior temporal lobes.