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

Bayesian log-Gaussian Cox process regression: applications to meta-analysis of neuroimaging working memory studies

Working memory (WM) was one of the first cognitive processes studied with functional magnetic resonance imaging. With now over 20 years of studies on WM, each study with tiny sample sizes, there is a need for meta-analysis to identify the brain regions that are consistently activated by WM tasks, and to understand the interstudy variation in those activations. However, current methods in the field cannot fully account for the spatial nature of neuroimaging meta-analysis data or the heterogeneity observed among WM studies. In this work, we propose a fully Bayesian random-effects metaregression model based on log-Gaussian Cox processes, which can be used for meta-analysis of neuroimaging studies. An efficient Markov chain Monte Carlo scheme for posterior simulations is presented which makes use of some recent advances in parallel computing using graphics processing units. Application of the proposed model to a real data set provides valuable insights regarding the function of the WM

Study of trap states in zinc oxide (ZnO) thin films for electronic applications

The electrical properties of ZnO thin films grown by pulsed laser deposition were studied. Field-effect devices with a mobility reaching 1 cm2/V s show non-linearities both in the current–voltage and in the transfer characteristics which are explained as due to the presence of trap states. These traps cause a reversible threshold voltage shift as revealed by low-frequency capacitance–voltage measurements in metal insulator semiconductor (MIS) capacitors. Thermal detrapping experiments in heterojunctions confirm the presence of a trap state located at 0.32 eV

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

Advocacy in the tail: Exploring the implications of ‘climategate’ for science journalism and public debate in the digital age

This paper explores the evolving practices of science journalism and public debate in the digital age. The vehicle for this study is the release of digitally stored email correspondence, data and documents from the Climatic Research Unit at the University of East Anglia in the weeks immediately prior to the United Nations Copenhagen Summit (COP-15) in December 2009. Described using the journalistic shorthand of ‘climategate’, and initially promoted through socio-technical networks of bloggers, this episode became a global news story and the subject of several formal reviews. ‘Climategate’ illustrates that media literate critics of anthropogenic explanations of climate change used digital tools to support their cause, making visible selected, newsworthy aspects of scientific information and the practices of scientists. In conclusion, I argue that ‘climategate’ may have profound implications for the production and distribution of science news, and how climate science is represented and debated in the digitally-mediated public sphere

Mastering tricyclic ring systems for desirable functional cannabinoid activity

There is growing interest in using cannabinoid receptor 2 (CB2) agonists for the treatment of neuropathic pain and other indications. In continuation of our ongoing program aiming for the development of new small molecule cannabinoid ligands, we have synthesized a novel series of carbazole and γ-carboline derivatives. The affinities of the newly synthesized compounds were determined by a competitive radioligand displacement assay for human CB2 cannabinoid receptor and rat CB1 cannabinoid receptor. Functional activity and selectivity at human CB1 and CB2 receptors were characterized using receptor internalization and [35S]GTP-γ-S assays. The structure–activity relationship and optimization studies of the carbazole series have led to the discovery of a non-selective CB1 and CB2 agonist, compound 4. Our subsequent research efforts to increase CB2 selectivity of this lead compound have led to the discovery of CB2 selective compound 64, which robustly internalized CB2 receptors. Compound 64 had potent inhibitory effects on pain hypersensitivity in a rat model of neuropathic pain. Other potent and CB2 receptor–selective compounds, including compounds 63 and 68, and a selective CB1 agonist, compound 74 were also discovered. In addition, we identified the CB2 ligand 35 which failed to promote CB2 receptor internalization and inhibited compound CP55,940-induced CB2 internalization despite a high CB2 receptor affinity. The present study provides novel tricyclic series as a starting point for further investigations of CB2 pharmacology and pain treatment.Fil: Petrov, Ravil R.. University Of Montana; Estados UnidosFil: Knight, Lindsay. Indiana University; Estados UnidosFil: Chen, Shao Rui. University Of Texas; Estados UnidosFil: Wager Miller, Jim. Indiana University; Estados UnidosFil: McDaniel, Steven W.. University Of Montana; Estados UnidosFil: Diaz, Fanny. University Of Montana; Estados UnidosFil: Barth, Francis. Sanofi-aventis R&D; FranciaFil: Pan, Hui Lin. University Of Texas; Estados UnidosFil: Mackie, Ken. Indiana University; Estados UnidosFil: Cavasotto, Claudio Norberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación en Biomedicina de Buenos Aires; ArgentinaFil: Diaz, Philippe. University Of Montana; Estados Unido

Neurodegeneration and Epilepsy in a Zebrafish Model of CLN3 Disease (Batten Disease)

The neuronal ceroid lipofuscinoses are a group of lysosomal storage disorders that comprise the most common, genetically heterogeneous, fatal neurodegenerative disorders of children. They are characterised by childhood onset, visual failure, epileptic seizures, psychomotor retardation and dementia. CLN3 disease, also known as Batten disease, is caused by autosomal recessive mutations in the CLN3 gene, 80–85% of which are a ~1 kb deletion. Currently no treatments exist, and after much suffering, the disease inevitably results in premature death. The aim of this study was to generate a zebrafish model of CLN3 disease using antisense morpholino injection, and characterise the pathological and functional consequences of Cln3 deficiency, thereby providing a tool for future drug discovery. The model was shown to faithfully recapitulate the pathological signs of CLN3 disease, including reduced survival, neuronal loss, retinopathy, axonopathy, loss of motor function, lysosomal storage of subunit c of mitochondrial ATP synthase, and epileptic seizures, albeit with an earlier onset and faster progression than the human disease. Our study provides proof of principle that the advantages of the zebrafish over other model systems can be utilised to further our understanding of the pathogenesis of CLN3 disease and accelerate drug discovery

Evaluation of outreach services for primary care and mental health; assessing the impact

Objectives: This paper reports an evaluation, carried out for London Health Libraries, of the impact of outreach services to primary care and mental health workers in thirteen different settings. The main aims of the project were to identify the impact being made by the service, and to produce best practice guidelines for outreach services in this kind of ‘difficult’ community setting. Methods: Methods used were: analysis of documents (all 13 services); analysis of any evaluation already performed by or for the service (all 13 services); interviews with outreach librarians (11 services); questionnaire survey of a representative sample of users (8 services, with 66 returned questionnaires, 35% response rate). The services evaluated were very diverse, in terms of setting, structure, functions and activities, and extent and nature of self-evaluation and reporting. The evaluation was therefore largely qualitative, in order to deal with the lack of a consistent ‘template’ for analysis. Emphasis was placed on trying to identify critical incidents , where it could be shown unambiguously that the outreach services made a difference to practice. Study limitations included the difficulty of summarising and comparing very different situations and diverse services, difficulty in identifying critical incidents, and an inability to study ‘non-users’. Findings: Service recipients felt better informed, more up- to-date, more aware of resources, more confident and supported in their work, and saved time. Services contributed to a richer information environment. Direct impacts, demonstrably improved patient care, cost savings etc., were more difficult to establish

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