1,139 research outputs found
Collaborative Deep Learning for Recommender Systems
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
Evolutionary Multi-Objective Design of SARS-CoV-2 Protease Inhibitor Candidates
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
Multiple publications: The main reason for the retraction of papers in computer science
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
Toward open sharing of task-based fMRI data: the OpenfMRI project
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
Metal oxide semiconductor thin-film transistors for flexible electronics
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
Ethical and methodological issues in engaging young people living in poverty with participatory research methods
This paper discusses the methodological and ethical issues arising from a project that focused on conducting a qualitative study using participatory techniques with children and young people living in disadvantage. The main aim of the study was to explore the impact of poverty on children and young people's access to public and private services. The paper is based on the author's perspective of the first stage of the fieldwork from the project. It discusses the ethical implications of involving children and young people in the research process, in particular issues relating to access and recruitment, the role of young people's advisory groups, use of visual data and collection of data in young people's homes. The paper also identifies some strategies for addressing the difficulties encountered in relation to each of these aspects and it considers the benefits of adopting participatory methods when conducting research with children and young people
Hypnotic analgesia reduces brain responses to pain seen in others.
Brain responses to pain experienced by oneself or seen in other people show consistent overlap in the pain processing network, particularly anterior insula, supporting the view that pain empathy partly relies on neural processes engaged by self-nociception. However, it remains unresolved whether changes in one's own pain sensation may affect empathic responding to others' pain. Here we show that inducing analgesia through hypnosis leads to decreased responses to both self and vicarious experience of pain. Activations in the right anterior insula and amygdala were markedly reduced when participants received painful thermal stimuli following hypnotic analgesia on their own hand, but also when they viewed pictures of others' hand in pain. Functional connectivity analysis indicated that this hypnotic modulation of pain responses was associated with differential recruitment of right prefrontal regions implicated in selective attention and inhibitory control. Our results provide novel support to the view that self-nociception is involved during empathy for pain, and demonstrate the possibility to use hypnotic procedures to modulate higher-level emotional and social processes
Context-specific activations are a hallmark of the neural basis of individual differences in general executive function
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
Impact Factor: outdated artefact or stepping-stone to journal certification?
A review of Garfield's journal impact factor and its specific implementation
as the Thomson Reuters Impact Factor reveals several weaknesses in this
commonly-used indicator of journal standing. Key limitations include the
mismatch between citing and cited documents, the deceptive display of three
decimals that belies the real precision, and the absence of confidence
intervals. These are minor issues that are easily amended and should be
corrected, but more substantive improvements are needed. There are indications
that the scientific community seeks and needs better certification of journal
procedures to improve the quality of published science. Comprehensive
certification of editorial and review procedures could help ensure adequate
procedures to detect duplicate and fraudulent submissions.Comment: 25 pages, 12 figures, 6 table
Modeling and Validating Chronic Pharmacological Manipulation of Circadian Rhythms
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
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