Multistate resistive switching in silver nanoparticle films.

Resistive switching devices have garnered significant consideration for their potential use in nanoelectronics and non-volatile memory applications. Here we investigate the nonlinear current-voltage behavior and resistive switching properties of composite nanoparticle films comprising a large collective of metal-insulator-metal junctions. Silver nanoparticles prepared via the polyol process and coated with an insulating polymer layer of tetraethylene glycol were deposited onto silicon oxide substrates. Activation required a forming step achieved through application of a bias voltage. Once activated, the nanoparticle films exhibited controllable resistive switching between multiple discrete low resistance states that depended on operational parameters including the applied bias voltage, temperature and sweep frequency. The films' resistance switching behavior is shown here to be the result of nanofilament formation due to formative electromigration effects. Because of their tunable and distinct resistance states, scalability and ease of fabrication, nanoparticle films have a potential place in memory technology as resistive random access memory cells

Business excellence models in UK Universities: two contrasting case studies

The overall aim of the research was to explore the reason(s) for the apparent disparity in acceptance and adoption of Business Excellence Models (BEMs) in UK universities and to identify ways to help quality assurance staff make the best use of these models. BEMs provide organisations with management frameworks based around quality and are praised for allegedly improving global competitiveness and performance. BEMs are also criticised for allegedly being fads, over-promising and contradicting the nature of HE. This study also investigated whether BEMs were seen as fads and what makes them sustainable. Two contrasting case studies in London were examined: a research-intensive Russell Group university and a teaching-focused newer (Post 92s) university. 18 semi-structured interviews were conducted with Vice Chancellors/Pro-Vice Chancellors; senior managers; heads of department and professional services/quality assurance staff. In contrast to previous literature, only one interviewee thought BEMs were fads. All the Russell Group interviewees thought BEMs were applicable to the HE sector whereas some interviewees from the newer university were more sceptical. Advocates of BEMs cited their intrinsic value as well as operational benefits. Critics said BEMs were too complicated and conflicted with academic freedom. Although all the participants agreed that effective leadership was vital for successful implementation, they disagreed on what this meant. Some emphasised motivation and inspiration but others highlighted the need to occasionally force change. Participants generated six criteria for evaluating BEMs. Four of these ((a) improved student experience; (b) adequately trained and mentored staff; (c) increased community engagement and (d) compatibility with league table requirements) are found in previous literature. Two ((a) strong personal tutoring and (b) students informing resource allocation and report generation) are not. Participants also identified seven Critical Success Factors (CSFs) that influenced their institution’s choice of BEM. Three of these (team, process and collaboration) are found in previous literature. Four (location, brand, personal tutoring and transparency) are not. Finally, a conceptual framework was developed to explain how BEMs can be sustained. Three elements of the framework match previous literature (human resource management, institutionalisation and feedback). Four (leadership, resource allocation, monitoring and collaboration with the Student Union) are new

Characterizing and Diminishing Autofluorescence in Formalin-fixed Paraffin-embedded Human Respiratory Tissue

The article of record as published may be found at http://dx.doi.org/10.1369/0022155414531549Tissue autofluorescence frequently hampers visualization of immunofluorescent markers in formalin-fixed paraffin-embedded respiratory tissues. We assessed nine treatments reported to have efficacy in reducing autofluorescence in other tissue types. The three most efficacious were Eriochrome black T, Sudan black B and sodium borohydride, as measured using white light laser confocal Ʌ² (multi-lambda) analysis. We also assessed the impact of steam antigen retrieval and serum application on human tracheal tissue autofluorescence. Functionally fitting this Ʌ² data to 2-dimensional Gaussian surfaces revealed that steam antigen retrieval and serum application contribute minimally to autofluorescence and that the three treatments are disparately efficacious. Together, these studies provide a set of guidelines for diminishing autofluorescence in formalin-fixed paraffin-embedded human respiratory tissue. Additionally, these characterization techniques are transferable to similar questions in other tissue types, as demonstrated on frozen human liver tissue and paraffin-embedded mouse lung tissue fixed in different fixatives.NIHNIAI

Learning Contextualized Semantics from Co-occurring Terms via a Siamese Architecture

One of the biggest challenges in Multimedia information retrieval and understanding is to bridge the semantic gap by properly modeling concept semantics in context. The presence of out of vocabulary (OOV) concepts exacerbates this difficulty. To address the semantic gap issues, we formulate a problem on learning contextualized semantics from descriptive terms and propose a novel Siamese architecture to model the contextualized semantics from descriptive terms. By means of pattern aggregation and probabilistic topic models, our Siamese architecture captures contextualized semantics from the co-occurring descriptive terms via unsupervised learning, which leads to a concept embedding space of the terms in context. Furthermore, the co-occurring OOV concepts can be easily represented in the learnt concept embedding space. The main properties of the concept embedding space are demonstrated via visualization. Using various settings in semantic priming, we have carried out a thorough evaluation by comparing our approach to a number of state-of-the-art methods on six annotation corpora in different domains, i.e., MagTag5K, CAL500 and Million Song Dataset in the music domain as well as Corel5K, LabelMe and SUNDatabase in the image domain. Experimental results on semantic priming suggest that our approach outperforms those state-of-the-art methods considerably in various aspects

Fighting COVID-19: What’s in a Name?

While the COVID-19 virus has infected over 3 million people in the United States of America, Asian Americans face unique unfair treatment due to COVID-19. In America, many anti-Asian incidents have been reported, and the FBI warns of increased hate crimes to Asian Americans due to COVID-19. Americans and high-level politicians use inappropriate names, such as “Chinese Virus,” for the COVID-19 virus, which fuels racism and xenophobia. In this Experience piece, we discuss the harm of referring to the COVID-19 virus based on the geographic location where it was first identified