1,038 research outputs found

    Context-specific activations are a hallmark of the neural basis of individual differences in general executive function

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    Common executive functioning (cEF) is a domain-general factor that captures shared variance in performance across diverse executive function tasks. To investigate the neural mechanisms of individual differences in cEF (e.g., goal maintenance, biasing), we conducted the largest fMRI study of multiple executive tasks to date (N = 546). Group average activation during response inhibition (antisaccade task), working memory updating (keep track task), and mental set shifting (number–letter switch task) overlapped in classic cognitive control regions. However, there were no areas across tasks that were consistently correlated with individual differences in cEF ability. Although similar brain areas are recruited when completing different executive function tasks, activation levels of those areas are not consistently associated with better performance. This pattern is inconsistent with a simple model in which higher cEF is associated with greater or less activation of a set of control regions across different task contexts; however, it is potentially consistent with a model in which individual differences in cEF primarily depend on activation of domain-specific targets of executive function. Brain features that explain commonalities in executive function performance across tasks remain to be discovered

    Modeling and Validating Chronic Pharmacological Manipulation of Circadian Rhythms

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    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/110096/1/psp4201334-sup-0010.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/110096/2/psp4201334-sup-0009.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/110096/3/psp4201334-sup-0011.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/110096/4/psp4201334-sup-0008.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/110096/5/psp4201334-sup-0005.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/110096/6/psp4201334-sup-0012.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/110096/7/psp4201334-sup-0006.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/110096/8/psp4201334-sup-0013.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/110096/9/psp4201334.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/110096/10/psp4201334-sup-0007.pd

    Evolutionary Multi-Objective Design of SARS-CoV-2 Protease Inhibitor Candidates

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    Computational drug design based on artificial intelligence is an emerging research area. At the time of writing this paper, the world suffers from an outbreak of the coronavirus SARS-CoV-2. A promising way to stop the virus replication is via protease inhibition. We propose an evolutionary multi-objective algorithm (EMOA) to design potential protease inhibitors for SARS-CoV-2's main protease. Based on the SELFIES representation the EMOA maximizes the binding of candidate ligands to the protein using the docking tool QuickVina 2, while at the same time taking into account further objectives like drug-likeliness or the fulfillment of filter constraints. The experimental part analyzes the evolutionary process and discusses the inhibitor candidates.Comment: 15 pages, 7 figures, submitted to PPSN 202

    Collaborative Deep Learning for Recommender Systems

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    Collaborative filtering (CF) is a successful approach commonly used by many recommender systems. Conventional CF-based methods use the ratings given to items by users as the sole source of information for learning to make recommendation. However, the ratings are often very sparse in many applications, causing CF-based methods to degrade significantly in their recommendation performance. To address this sparsity problem, auxiliary information such as item content information may be utilized. Collaborative topic regression (CTR) is an appealing recent method taking this approach which tightly couples the two components that learn from two different sources of information. Nevertheless, the latent representation learned by CTR may not be very effective when the auxiliary information is very sparse. To address this problem, we generalize recent advances in deep learning from i.i.d. input to non-i.i.d. (CF-based) input and propose in this paper a hierarchical Bayesian model called collaborative deep learning (CDL), which jointly performs deep representation learning for the content information and collaborative filtering for the ratings (feedback) matrix. Extensive experiments on three real-world datasets from different domains show that CDL can significantly advance the state of the art

    Toward open sharing of task-based fMRI data: the OpenfMRI project

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    The large-scale sharing of task-based functional neuroimaging data has the potential to allow novel insights into the organization of mental function in the brain, but the field of neuroimaging has lagged behind other areas of bioscience in the development of data sharing resources. This paper describes the OpenFMRI project (accessible online at http://www.openfmri.org), which aims to provide the neuroimaging community with a resource to support open sharing of task-based fMRI studies. We describe the motivation behind the project, focusing particularly on how this project addresses some of the well-known challenges to sharing of task-based fMRI data. Results from a preliminary analysis of the current database are presented, which demonstrate the ability to classify between task contrasts with high generalization accuracy across subjects, and the ability to identify individual subjects from their activation maps with moderately high accuracy. Clustering analyses show that the similarity relations between statistical maps have a somewhat orderly relation to the mental functions engaged by the relevant tasks. These results highlight the potential of the project to support large-scale multivariate analyses of the relation between mental processes and brain function

    Multiple publications: The main reason for the retraction of papers in computer science

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    This paper intends to review the reasons for the retraction over the last decade. The paper particularly aims at reviewing these reasons with reference to computer science field to assist authors in comprehending the style of writing. To do that, a total of thirty-six retracted papers found on the Web of Science within Jan 2007 through July 2017 are explored. Given the retraction notices which are based on ten common reasons, this paper classifies the two main categories, namely random and nonrandom retraction. Retraction due to the duplication of publications scored the highest proportion of all other reasons reviewed

    A Bayesian General Linear Modeling Approach to Cortical Surface fMRI Data Analysis

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    Cortical surface functional magnetic resonance imaging (cs-fMRI) has recently grown in popularity versus traditional volumetric fMRI. In addition to offering better whole-brain visualization, dimension reduction, removal of extraneous tissue types, and improved alignment of cortical areas across subjects, it is also more compatible with common assumptions of Bayesian spatial models. However, as no spatial Bayesian model has been proposed for cs-fMRI data, most analyses continue to employ the classical general linear model (GLM), a “massive univariate” approach. Here, we propose a spatial Bayesian GLM for cs-fMRI, which employs a class of sophisticated spatial processes to model latent activation fields. We make several advances compared with existing spatial Bayesian models for volumetric fMRI. First, we use integrated nested Laplacian approximations, a highly accurate and efficient Bayesian computation technique, rather than variational Bayes. To identify regions of activation, we utilize an excursions set method based on the joint posterior distribution of the latent fields, rather than the marginal distribution at each location. Finally, we propose the first multi-subject spatial Bayesian modeling approach, which addresses a major gap in the existing literature. The methods are very computationally advantageous and are validated through simulation studies and two task fMRI studies from the Human Connectome Project. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement

    Genomic determinants of organohalide-respiration in Geobacter lovleyi, an unusual member of the Geobacteraceae

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    Background Geobacter lovleyi is a unique member of the Geobacteraceae because strains of this species share the ability to couple tetrachloroethene (PCE) reductive dechlorination to cis-1,2-dichloroethene (cis-DCE) with energy conservation and growth (i.e., organohalide respiration). Strain SZ also reduces U(VI) to U(IV) and contributes to uranium immobilization, making G. lovleyi relevant for bioremediation at sites impacted with chlorinated ethenes and radionuclides. G. lovleyi is the only fully sequenced representative of this distinct Geobacter clade, and comparative genome analyses identified genetic elements associated with organohalide respiration and elucidated genome features that distinguish strain SZ from other members of the Geobacteraceae. Results Sequencing the G. lovleyi strain SZ genome revealed a 3.9 Mbp chromosome with 54.7% GC content (i.e., the percent of the total guanines (Gs) and cytosines (Cs) among the four bases within the genome), and average amino acid identities of 53–56% compared to other sequenced Geobacter spp. Sequencing also revealed the presence of a 77 kbp plasmid, pSZ77 (53.0% GC), with nearly half of its encoded genes corresponding to chromosomal homologs in other Geobacteraceae genomes. Among these chromosome-derived features, pSZ77 encodes 15 out of the 24 genes required for de novo cobalamin biosynthesis, a required cofactor for organohalide respiration. A plasmid with 99% sequence identity to pSZ77 was subsequently detected in the PCE-dechlorinating G. lovleyi strain KB-1 present in the PCE-to-ethene-dechlorinating consortium KB-1. Additional PCE-to-cis-DCE-dechlorinating G. lovleyi strains obtained from the PCE-contaminated Fort Lewis, WA, site did not carry a plasmid indicating that pSZ77 is not a requirement (marker) for PCE respiration within this species. Chromosomal genomic islands found within the G. lovleyi strain SZ genome encode two reductive dehalogenase (RDase) homologs and a putative conjugative pilus system. Despite the loss of many c-type cytochrome and oxidative-stress-responsive genes, strain SZ retained the majority of Geobacter core metabolic capabilities, including U(VI) respiration. Conclusions Gene acquisitions have expanded strain SZ’s respiratory capabilities to include PCE and TCE as electron acceptors. Respiratory processes core to the Geobacter genus, such as metal reduction, were retained despite a substantially reduced number of c-type cytochrome genes. pSZ77 is stably maintained within its host strains SZ and KB-1, likely because the replicon carries essential genes including genes involved in cobalamin biosynthesis and possibly corrinoid transport. Lateral acquisition of the plasmid replicon and the RDase genomic island represent unique genome features of the PCE-respiring G. lovleyi strains SZ and KB-1, and at least the latter signifies adaptation to PCE contamination

    Genomic determinants of organohalide-respiration in Geobacter lovleyi, an unusual member of the Geobacteraceae

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    Background Geobacter lovleyi is a unique member of the Geobacteraceae because strains of this species share the ability to couple tetrachloroethene (PCE) reductive dechlorination to cis-1,2-dichloroethene (cis-DCE) with energy conservation and growth (i.e., organohalide respiration). Strain SZ also reduces U(VI) to U(IV) and contributes to uranium immobilization, making G. lovleyi relevant for bioremediation at sites impacted with chlorinated ethenes and radionuclides. G. lovleyi is the only fully sequenced representative of this distinct Geobacter clade, and comparative genome analyses identified genetic elements associated with organohalide respiration and elucidated genome features that distinguish strain SZ from other members of the Geobacteraceae. Results Sequencing the G. lovleyi strain SZ genome revealed a 3.9 Mbp chromosome with 54.7% GC content (i.e., the percent of the total guanines (Gs) and cytosines (Cs) among the four bases within the genome), and average amino acid identities of 53–56% compared to other sequenced Geobacter spp. Sequencing also revealed the presence of a 77 kbp plasmid, pSZ77 (53.0% GC), with nearly half of its encoded genes corresponding to chromosomal homologs in other Geobacteraceae genomes. Among these chromosome-derived features, pSZ77 encodes 15 out of the 24 genes required for de novo cobalamin biosynthesis, a required cofactor for organohalide respiration. A plasmid with 99% sequence identity to pSZ77 was subsequently detected in the PCE-dechlorinating G. lovleyi strain KB-1 present in the PCE-to-ethene-dechlorinating consortium KB-1. Additional PCE-to-cis-DCE-dechlorinating G. lovleyi strains obtained from the PCE-contaminated Fort Lewis, WA, site did not carry a plasmid indicating that pSZ77 is not a requirement (marker) for PCE respiration within this species. Chromosomal genomic islands found within the G. lovleyi strain SZ genome encode two reductive dehalogenase (RDase) homologs and a putative conjugative pilus system. Despite the loss of many c-type cytochrome and oxidative-stress-responsive genes, strain SZ retained the majority of Geobacter core metabolic capabilities, including U(VI) respiration. Conclusions Gene acquisitions have expanded strain SZ’s respiratory capabilities to include PCE and TCE as electron acceptors. Respiratory processes core to the Geobacter genus, such as metal reduction, were retained despite a substantially reduced number of c-type cytochrome genes. pSZ77 is stably maintained within its host strains SZ and KB-1, likely because the replicon carries essential genes including genes involved in cobalamin biosynthesis and possibly corrinoid transport. Lateral acquisition of the plasmid replicon and the RDase genomic island represent unique genome features of the PCE-respiring G. lovleyi strains SZ and KB-1, and at least the latter signifies adaptation to PCE contamination

    Metal oxide semiconductor thin-film transistors for flexible electronics

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    The field of flexible electronics has rapidly expanded over the last decades, pioneering novel applications, such as wearable and textile integrated devices, seamless and embedded patch-like systems, soft electronic skins, as well as imperceptible and transient implants. The possibility to revolutionize our daily life with such disruptive appliances has fueled the quest for electronic devices which yield good electrical and mechanical performance and are at the same time light-weight, transparent, conformable, stretchable, and even biodegradable. Flexible metal oxide semiconductor thin-film transistors (TFTs) can fulfill all these requirements and are therefore considered the most promising technology for tomorrow's electronics. This review reflects the establishment of flexible metal oxide semiconductor TFTs, from the development of single devices, large-area circuits, up to entirely integrated systems. First, an introduction on metal oxide semiconductor TFTs is given, where the history of the field is revisited, the TFT configurations and operating principles are presented, and the main issues and technological challenges faced in the area are analyzed. Then, the recent advances achieved for flexible n-type metal oxide semiconductor TFTs manufactured by physical vapor deposition methods and solution-processing techniques are summarized. In particular, the ability of flexible metal oxide semiconductor TFTs to combine low temperature fabrication, high carrier mobility, large frequency operation, extreme mechanical bendability, together with transparency, conformability, stretchability, and water dissolubility is shown. Afterward, a detailed analysis of the most promising metal oxide semiconducting materials developed to realize the state-of-the-art flexible p-type TFTs is given. Next, the recent progresses obtained for flexible metal oxide semiconductor-based electronic circuits, realized with both unipolar and complementary technology, are reported. In particular, the realization of large-area digital circuitry like flexible near field communication tags and analog integrated circuits such as bendable operational amplifiers is presented. The last topic of this review is devoted for emerging flexible electronic systems, from foldable displays, power transmission elements to integrated systems for large-area sensing and data storage and transmission. Finally, the conclusions are drawn and an outlook over the field with a prediction for the future is provided
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