1,721,817 research outputs found
Cesium Copper Iodide Tailored Nanoplates and Nanorods for Blue, Yellow, and White Emission
No full textInorganic metal halide perovskite nanocrystals (NCs) are promising materials for emission-based applications; however, the inclusion of toxic lead may limit their commercial viability. This paper describes two cesium cupriferous iodides as nontoxic alternatives to lead containing perovskites. These nanocrystals were synthesized with tailored composition and morphology by a hot-injection colloidal route to produce hexagonal nanoplates (NPs) of blue-emitting Cs3Cu2I5 and nanorods (NRs) of yellow-emitting CsCu2I3. Phase purity was confirmed by Rietveld refinement of X-ray powder diffraction patterns and solid state 133Cs MAS NMR with both compounds exhibiting high thermal stability suitable for optoelectronic technologies. Phase mixing allows linear tuning of Commission Internationale de l’Eclairage (CIE) coordinates from (0.145, 0.055) to (0.418, 0.541) such that a 1:8 molar ratio of Cs3Cu2I5 NPs and CsCu2I3 NRs yields white emission, while the 133Cs MAS NMR demonstrates that these photophysical effects are not attributed to any changes in the Cu oxidation state
Kartavya Vashishtha/Librarian-1.0.4
No full textCode snapshot for manuscript submission of Librarian: A quality control tool to analyse sequencing library compositions
(10.12688/f1000research.125325.
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Book Review: Sonalde Desai, Prem Vashishtha and Omkar Joshi, Mahatma Gandhi National Rural Employment Guarantee Act: A Catalyst for Rural Transformation
No full text Sonalde Desai, Prem Vashishtha and Omkar Joshi, Mahatma Gandhi National Rural Employment Guarantee Act: A Catalyst for Rural Transformation. New Delhi: NCAER, 2015, 191 pp., price not mentioned. </jats:p
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Multi-Modal Brain Tumor Segmentation Model to solve Mutual Inhibition between Modes
No full textFaculty Advisor: Ju SunMedical image segmentation has become a key research area in the machine learning community with brain tumor segmentation as one of the most challenging problems in the field. Brain tumor segmentation using machine learning models can help in diagnosing, treating, and monitoring of brain tumors which would significantly improve the medical care of patients.
The aim of this research is to develop a network that could solve the problem of mutual inhibition in multi-modal image segmentation for brain tumors. Specifically, multi-modal image segmentation represents the true day-to-day scenario of brain tumor imaging which will be automated using machine learning networks. Contribution to the multi-modal brain tumor segmentation problem will allow for the fast detection and classification of brain tumors which will lead to improved medical care to patients.This research was supported by the Undergraduate Research Opportunities Program (UROP). Special word of thanks to Group of Learning, Optimization, Vision, healthcarE and X (GLOVEX) whose guidance and expertise made this UROP possible. For more information on the Group of Learning, Optimization, Vision, healthcarE and X (GLOVEX) , please visit https://glovex.umn.edu/Vashishtha, Shridhar. (2023). Multi-Modal Brain Tumor Segmentation Model to solve Mutual Inhibition between Modes. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/259170
Numerical investigation of the impact of injectors location on fuel mixing in the HIFiRE 2 Scramjet combustor
Get PDFIn scramjets, the position and direction of the injectors plays a crucial role for fuel/air mixing and combustion efficiency. Fuel injection is still a potential topic of research to be addressed, in fact an effective fuel injection strategy is critical for increasing the streamwise vorticity that has been found to be the main responsible for the fuel-air mixing in compressible flows. In fact, the position and the direction of the fuel injectors, the presence of a cavity scramjet has a critical influence on the density and pressure gradients, and consequently on the baroclinic term that is a source of vorticity. In this regard, this research wants to investigate the nature of the mixing in supersonic flows, investigating the contribution between the streamwise and stretching component for the vorticity. Numerical modelling of supersonic combustion using Large Eddy Simulations was carried out in HIFiRE 2 Scramjet to better understand the physics of the combustion and mixing
Meta-Learning for Monitoring Environment Systems Across the Globe
Get PDFPhD student mentor: Arvind Renganathan
Faculty mentor: Vipin KumarData sparsity is a key challenge in monitoring climate because of the lack of quality data, problems in sensors, lack of historical data, or financial constraints in certain parts of the world. Thus, monitoring the environment using machine learning becomes a difficult task because classic machine learning algorithms’ main objective is to train a model that uses input features to learn classes. This paradigm requires huge datasets which makes it difficult to train models in tasks where data is sparse.
Meta-learning, or learning-to-learn is a learning paradigm which provides an alternative methodology to classic machine learning algorithms. Meta-learning uses machine learning models in various learning episodes and uses this experience to learn in new learning environments. Thus, meta-learning can be used to monitor environment systems by training in scenarios where data is available and leveraging that information in data sparse tasks.This research was supported by the Undergraduate Research Opportunities Program (UROP).Vashishtha, Shridhar. (2024). Meta-Learning for Monitoring Environment Systems Across the Globe. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/263210
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