Greensboro, NC, United States
Greensboro, NC, United States

The University of North Carolina at Greensboro , also known as UNC Greensboro, is a public research university in Greensboro, North Carolina, United States and is a constituent institution of the University of North Carolina system. However, UNCG, like all members of the UNC system, is a stand alone university and awards its own degrees. UNCG is accredited by the Southern Association of Colleges and Schools Commission on Colleges to award baccalaureate, masters, specialist and doctoral degrees.The university offers more than 100 undergraduate, 61 master's and 26 doctoral programs. The university's academic schools and programs include the College of Arts & science, the Joseph M. Bryan School of Business & Economics, the School of Education, the School of Health and Human science, the Joint School of Nanoscience & Nanoengineering , the School of Music, Theatre & Dance , the School of Nursing, Continual Learning, Graduate School, Warren Ashby Residential College and Lloyd International Honors College. The university is also home to the nationally renowned Weatherspoon Art Museum, which features one of the largest and most impressive collections of modern American art in the country.The university holds two classifications from the Carnegie Foundation for the Advancement of Teaching, as a “research university with high research activity” and for “community engagement” in curriculum, outreach and partnerships. Wikipedia.


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Beaty R.E.,University of North Carolina at Greensboro
Neuroscience and Biobehavioral Reviews | Year: 2015

Researchers have recently begun to examine the neural basis of musical improvisation, one of the most complex forms of creative behavior. The emerging field of improvisation neuroscience has implications not only for the study of artistic expertise, but also for understanding the neural underpinnings of domain-general processes such as motor control and language production. This review synthesizes functional magnetic resonance imagining (fMRI) studies of musical improvisation, including vocal and instrumental improvisation, with samples of jazz pianists, classical musicians, freestyle rap artists, and non-musicians. A network of prefrontal brain regions commonly linked to improvisatory behavior is highlighted, including the pre-supplementary motor area, medial prefrontal cortex, inferior frontal gyrus, dorsolateral prefrontal cortex, and dorsal premotor cortex. Activation of premotor and lateral prefrontal regions suggests that a seemingly unconstrained behavior may actually benefit from motor planning and cognitive control. Yet activation of cortical midline regions points to a role of spontaneous cognition characteristic of the default network. Together, such results may reflect cooperation between large-scale brain networks associated with cognitive control and spontaneous thought. The improvisation literature is integrated with Pressing's theoretical model, and discussed within the broader context of research on the brain basis of creative cognition. © 2015 Elsevier Ltd.All rights reserved.


Patent
University of North Carolina at Greensboro and Duke University | Date: 2016-04-21

A method of determining the susceptibility to ventricular arrhythmias in a subject, the method including determining a reserve of refractoriness (RoR) and a reserve of memory (RoM) and combining the reserve of refractoriness (RoR) and the reserve of memory (RoM) to produce a metric of stability-of-propagation reserve (SoPR) in the subject, a higher value of SoPR indicating lower susceptibility to ventricular arrhythmias in the subject. Systems and apparatus for carrying out the method are also described.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: BIOPHOTONICS, IMAGING &SENSING | Award Amount: 306.00K | Year: 2015

PI: Wei, Jianjun
Proposal: 1511194

The goal is to develop a novel platform that incorporates an optical transmission sensing scheme with an automated size-dependent sample delivery system in a single nanoscale unit. The results will lead to a chip-based, point-of-care (POC) technology for early diagnosis of cardiovascular disease (CVD).


This project will investigate a plasmonic nano-optofluidic (PNOF) platform to demonstrate its utility and versatility of in-situ cell separation and delivery of small molecules to the sensing area, and discriminative, sensitive quantitation of protein biomarkers in whole blood. Unique metal film structures will be used as plasmonic waveguides to tune the spectrum that enables ultrasensitive and high signal-to-noise (S/N) ratio detection. The array will be utilized to integrate with a microfluidic network to realize in-situ separation of cells and size-exclusive delivery biomarkers. The researchers will then adopt the immunoassay format and demonstrate delivery and discrimination of selected biomarkers in human blood.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: MATHEMATICAL BIOLOGY | Award Amount: 203.83K | Year: 2015

This project is an integration of mathematical modeling and experimental analysis of an invertebrate predator-prey system to explore the effects of habitat fragmentation, conditional dispersal, predation, and interspecific competition on herbivore population dynamics from the patch level to the landscape level. It represents a unique collaboration between two mathematicians, and ecologist, and undergraduate and PhD students. This project is expected to provide much-needed information in population ecology on the consequences of conditional dispersal to population dynamics of species in fragmented landscapes. Results from this project will answer several key ecological questions such as will the presence of density dependent dispersal help to moderate potentially detrimental factors as habitat fragmentation or worse, exacerbate their effects. The project will also provide a significant contribution towards the analysis of elliptic boundary value problems with nonlinear boundary conditions, as new mathematical tools will be developed to better understand the dynamics of these population models. Finally, the project will provide clear guidelines for how empirical studies should be constructed to evaluate the presence and consequences of density dependent dispersal in light of the predictions of these theoretical models. The investigators will disseminate the results of this project to both the ecological and mathematical communities through various media including peer-reviewed mathematical and ecological journals, talks at national and international conferences, and a user-friendly website showcasing the research. An important aspect of this project will involve the training of graduate and undergraduate students through workshops hosted by the investigators and mentorship of independent research projects. Moreover, a population dynamics curriculum covering basic population ecology through mathematical tools and interesting examples for exploring population models related to density dependent dispersal will be developed targeting undergraduate and advanced level high school students and freely available to the public via the projects website.

The purpose of this collaborative project between will be an integration of modeling of population dynamics via reaction diffusion models, mathematical analysis, and experimental analysis of an invertebrate system to explore the effects of habitat fragmentation, conditional dispersal, predation, and interspecific competition on herbivore population dynamics from the patch level to the landscape level. This study will help answer important biological questions such as 1) what patch level effects can be expected from density dependent dispersal, specifically of positive, negative or U-shaped density dependent dispersal, 2) does density dependent dispersal moderate or even exacerbate the effects of habitat fragmentation, Allee effects, interspecific competition, or predation on local or regional stability/persistence of a population, and 3) how should empirical studies be constructed to evaluate the presence and consequences of density dependent dispersal in light of the predictions of these theoretical models. A more comprehensive understanding of the patch and landscape level consequences of density dependent dispersal in the presence of such complicating factors as predation, interspecific competition, and habitat fragmentation is important by itself, but may also lead to the development of better population management strategies, especially in an environment where populations face diverse ecological challenges due to predation, habitat fragmentation, and global climate change. This project is expected to be significant by providing much-needed information in population ecology on the consequences of conditional dispersal (i.e., as a function of the density of conspecifics, interspecific competitors, and predators) to population dynamics of species in fragmented landscapes. The research is novel because, to date, theoretical and empirical studies in fragmented systems have ignored other forms of density dependent dispersal (negative or U-shaped) that are commonly found in nature. Results from this project will answer several key ecological questions as to whether the presence of negative or U-shaped density dependent dispersal helps to moderate potentially detrimental factors as habitat fragmentation or worse, exacerbate their effects. The project will also provide a significant contribution towards the analysis of elliptic boundary value problems with nonlinear boundary conditions, as new mathematical tools will be developed to better understand the dynamics of these population models. Further, development of a true landscape level modeling framework built on reaction diffusion equations will serve as a foundation for enhanced study of landscape dynamics in theoretical models. The investigators plan to disseminate the results of this project to both the ecological and mathematical communities through various media including: the ArXiv, peer-reviewed mathematics, mathematical biology, and ecology journals, and in talks at mathematical biology and ecological conferences.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: S-STEM:SCHLR SCI TECH ENG&MATH | Award Amount: 999.94K | Year: 2017

The project STAMPS: Science, Technology and Math Preparation Scholarships is serving the national interest by supporting academically talented and financially needy students, including minority, women and first-generation college students, in their efforts to complete their college degrees in the STEM disciplines (Natural, Physical, Earth and Computer Sciences). The project is providing financial, academic, mentoring and advising support to talented students in the STEM disciplines to increase their retention rates and better prepare students for science and technology-based careers or for advance study in professional (e.g., medical, dental, pharmacy, graduate) schools. By doing so, the project is increasing the pool of talented individuals for highly skilled jobs or careers in science and technology. The project is also developing best practices on how to support and train students for a skilled workforce that is shared with other universities.

STAMPS enrolls a diverse group of first year STEM students into a yearlong integrated science course, designed to create a cohort, supported by faculty and peer mentors and services. STAMPS students have opportunities for research, interacting with STEM speakers, travel, and facilitated shadowing at the Joint School for Nanoscience and Nanoengineering. The goals are to 1) matriculate and then graduate STAMPS scholars into STEM careers or graduate school; 2) identify and support a diverse community of STEM learners; 3) create a supportive and self-sustaining environment for STAMPS scholars; and 4) discover what works and why and share this knowledge to a broad audience.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: IUSE | Award Amount: 299.94K | Year: 2016

Increasing the number of US university students who successfully complete degrees in science, technology, engineering, and mathematics (STEM) and enter the STEM workforce is of national importance. However, this has proven to be surprisingly difficult, especially with women and underrepresented minorities. A primary reason is that the students most likely to drop out of STEM disciplines, and therefore most in need of help, benefit least from innovations that merely address teaching quality or curriculum content. Research shows that we must influence students self-efficacy: their belief in their own ability to overcome setbacks and ultimately succeed. This project will develop, test, document, and publicize a practical, inexpensive, single-session intervention to improve students self-efficacy. It is suitable for inclusion in any university STEM course. Our test population will be 440 STEM majors taking introductory physics at UNCG and NCA&T, both universities having particularly large minority and/or female enrollments.

The project builds on two strong, but previously separate, lines of research into attitudinal/affect variables that influence student success. The first is attributional retraining, in which students learn to attribute their successes and failures to internal rather than external factors. The second is mindset about fixed vs. growable intelligence, in which students learn that the brain remains plastic throughout life and that they can, with conscious effort and attention to thinking skills and strategies, become smarter. Interventions of demonstrated efficacy exist for each of these two, but none exist that address both concurrently, and none are suitable and practical for widespread use in university-level STEM instruction. In addition to developing a disseminable intervention and documenting its effectiveness, this project will develop procedures for efficiently and reliably gauging STEM students self-efficacy (with extant instruments), and will advance our theoretical understanding of self-efficacy, its components, and its growth dynamics.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: | Award Amount: 450.00K | Year: 2014

For this project, Professor Mitchell P. Croatt in the Department of Chemistry and Biochemistry at the University of North Carolina at Greensboro is funded by the Chemical Structure, Dynamics and Mechanisms B Program of the Chemistry Division to investigate the synthesis and reactions of cyanocarbenes made from alkynes and azides. The goal of the project is to use readily available compounds, have them undergo previously unexplored reaction mechanisms, and generate products with significantly increased molecular complexity. An educational goal of this project is to develop a program to help students learn organic chemistry better and more quickly train them to visualize molecules as if they were experienced organic chemists. The program is designed to create a game-like atmosphere to make learning organic chemistry fun while also helping students to learn the material more efficiently. Finally, training of underrepresented minority researchers will actively take place through a variety of methods including a series of discussion panels.

This project explores the conversion of electrophilic alkynes and nucleophilic azides to cyanocarbenes and then studies their subsequent reactivity. The electrophilic alkynes, hypervalent iodonium alkynyl triflates, are isolable. However, this project will form them in situ and allow them to react with azide anions. A series of reactive intermediates, including vinylidene carbenes and alkynyl azides, are formed, and eventually cyanocarbenes are generated. These electrophilic carbenes will be allowed to react with a variety of nucleophiles to produce additional reactive intermediates which can undergo extensive rearrangement before producing stable molecules with significantly increased molecular complexity.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: INFRASTRUCTURE PROGRAM | Award Amount: 31.73K | Year: 2016

This award will support the UNCG Regional Mathematics and Statistics Conference annually for three years, beginning in November of 2016. The main goal of the University of North Carolina Greensboro (UNCG) Regional Mathematics and Statistics Conference is to provide a venue for students at all levels to share and experience research in the field of mathematics and statistics. The opportunity for personal interaction among students and, between students and faculty is a hallmark of our conference. These interactions enhance the research infrastructure and are essential for the success of student research and for training a new generation of mathematicians and statisticians. Moreover, due to the funding of NSF the principal investigators will be able to focus support on those currently underrepresented in mathematical research. Students from underrepresented groups accounted for about half of the supported participants in prior years.

This conference started as an annual undergraduate student conference in 2005 and has now expanded to include graduate researchers since 2009. The research sessions concentrate on topics in statistics, mathematical biology, graph theory, and computational biology but are open to other topics as well. The conference will entail a faculty development workshop to provide training for faculty to increase their effectiveness at mentoring undergraduate researchers. The conference has established a tradition of attracting active student researchers and their faculty mentors from North Carolina and Virginia. The NSF support will allow the conference to attract participants from the entire Southeastern Atlantic region. The conference website is: http://www.uncg.edu/mat/rmsc/.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: I-Corps | Award Amount: 49.47K | Year: 2016

As modern technology has made the collection of vast amounts of data of all kinds extremely cheap and easy, new approaches to analyzing such information are required for this type of technology to be truly useful. In particular, the advent of affordable and portable electrocardiogram (ECG) measurement devices has enabled collection and storage of hours of detailed information about patients? personal cardiovascular system. However, the untrained individuals limited ability to interpret this raw information limits the revolutionary healthcare potential of such technology. Consequently, there is no decrease in required face-to-face visits with a physician, and many ethical questions arise regarding storage, transmission and responsibility of the doctor to monitor such information. In this project, this I-Corps team outlines a strategy for taking such technology to the next level of personalization by incorporating a novel metric for cardiovascular health into currently available portable ECG measurement devices.

The ability to extract meaningful information from a large set of data is of paramount importance in the digital age. At its core, the proposed technology isolates the degrees of freedom within the cardiovascular system that govern a particular aspect of the hearts response to external stresses including pollutants. By enabling real-time measurement of the cardiac muscle physical ability to recover from a single contraction through the so-called reserve of refractoriness (RoR), the door to non-invasive assessment of exposure to arbitrary types of potential pollutants is opened. A remarkable feature of introduced metric is its lack of sensitivity to the inherent noise in low-resolution, single-lead ECG measurement devices. Such a stiffness makes the proposed refractoriness metric an ideal method for analyzing the cardiovascular system in a variety of practical contexts. Specifically, the proposed technology demonstrates how it may be rewarding for the medical industry, companies with concern for occupational or environmental hazards, as well as for the vast fitness industry.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: MSPA-INTERDISCIPLINARY | Award Amount: 275.95K | Year: 2014

Many animals live in populations whose internal structure reflects multiple factors, for example, the interplay between territorial behavior between conspecifics and the spatial arrangement of the physical environment or other interactions demonstrated within the context of a social hierarchy established by dominance or kinship. This project will develop a unified mathematical framework for structured models of animal territoriality and social interactions. Using evolutionary graph theory, student researchers will study and classify the distribution of finite populations moving and interacting across a network of distinct sites under different models of interaction. Among several questions that will be explored, the participants will seek to understand the effect that the existing population structure has on the level of aggressiveness between conspecifics.

This project will provide an understanding for the natural emergence of the ways in which animal populations and social groups organize and partition themselves into cooperative or antagonistic factions. The participants will endeavor to create a generalizable framework which could provide insight in multiple fields such as ecology, evolution, and the behavioral sciences. Many STEM fields are undergoing dynamic changes as a consequence of cross-disciplinary interactions, and this project will develop a diverse cadre of new scientists capable of working across traditional academic and scientific boundaries. This REU Site project trains undergraduate students to work at the interface of mathematics and the biological sciences. Each year, eight undergraduate students will participate in a ten week summer program and will be integrated into research teams lead by faculty members. The participants will be trained in pertinent mathematical techniques and biological concepts and they will engage in original research. This REU experience will improve participants quantitative, analytical, and scientific communication skills and will prepare them for graduate school and scientific careers.

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