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Little Rock, AR, United States

University of Arkansas at Little Rock is a metropolitan public research university located in Little Rock, Arkansas. Established as Little Rock Junior College by the Little Rock School District in 1927, the institution became a private four-year university under the name Little Rock University in 1957. It returned to public status in 1969 when it merged with the University of Arkansas System under its present name.Located on 250 acres, the UALR campus encompasses more than 56 buildings, including the Center for Nanotechnology Integrative science, the Emerging Analytics Center, and the Sequoyah Research Center, and the Ottenheimer Library Ottenheimer library. Additionally, UALR houses special learning facilities that include a learning resource center, art galleries, KUAR public radio station, University Television, cyber café, speech and hearing clinic, and a campus-wide wireless network. Because of the university's location in the state capital, UALR students benefit from close contact with leaders in government, business, industry, medicine , information technology, and arts and culture. As the state's only metropolitan university and as a member of the Coalition of Urban and Metropolitan Universities, UALR provides a strategic focus on the needs of the community by creating active links between the campus, community, and commerce.The Center for Integrative Nanotechnology science is a state-of-the-art facility focused on faculty and student research, education, and economic development. The center advances the science of nanotechnology through research and outreach, along with accelerating technological innovations into applications for society. In 2013, the Emerging Analytics Center opened to provide advanced visualization and interactive technologies enhance economic development in Arkansas and around the world. Dr. Carolina Cruz-Neira, globally recognized as an international pioneer in the areas of virtual reality and interactive visualization, directs the center, which is creating exciting collaborative endeavors to bring faculty, students, and industry professionals toward transforming innovative ideas into tangible research and development projects. Wikipedia.


Zhao W.,University of Arkansas at Little Rock
Journal of Physical Chemistry Letters | Year: 2011

The third-order nonlinear resonant electronic and Raman susceptibilities of length-sorted DNA-encased single-walled carbon nanotubes have been measured by the interferometric method of nondegenerate four-wave mixing spectroscopy. The four-wave mixing is predominantly resonant with the first interband transition E 11 of (10,5) nanotubes at 1275 nm. Large electronic third-order susceptibilities have been determined with a real part XRe (3) = -3.0 ×10 -8 esu and an imaginary part XIm (3) = 2.9 ×10 -8 esu. The G band Raman third-order susceptibility was simultaneously determined with a large value of X (3) = 3.3 ×10 -8 esu, or 4.1 ×10 -12 esu per six-membered aromatic ring, which is ∼60 times larger that of 992 cm -1 benzene ring breathing mode. Such large X (3) values suggest promising carbon nanotube applications in photonics and optical sensing. © 2011 American Chemical Society. Source


A gene delivery concept based on ethylenediamine-functionalized single-walled carbon nanotubes (f-SWCNTs) using the oncogene suppressor p53 gene as a model gene was successfully tested in vitro in MCF-7 breast cancer cells. The f-SWCNTs-p53 complexes were introduced into the cell medium at a concentration of 20 μg mL(-1) and cells were exposed for 24, 48, and 72 hours. Standard ethidium bromide and acridine orange assays were used to detect apoptotic cells and indicated that a significantly larger percentage of the cells (approx 40%) were dead after 72 hours of exposure to f-SWCNTs-p53 as compared to the control cells, which were exposed to only p53 or f-SWCNTs, respectively. To further support the uptake and expression of the genes within the cells, green fluorescent protein-tagged p53, attached to the f-SWCNTs was added to the medium and the complex was observed to be strongly expressed in the cells. Moreover, caspase 3 activity was found to be highly enhanced in cells incubated with the f-SWCNTs-p53 complex, indicating strongly induced apoptosis. This system could be the foundation for novel gene delivery platforms based on the unique structural and morphological properties of multi-functional nanomaterials. Source


Cui J.,University of Arkansas at Little Rock
Materials Characterization | Year: 2012

ZnO nanowires (NWs) have attracted much interest in the past decade because of their various remarkable physical properties and potential applications in a number of emerging areas such as low-voltage and short-wavelength optoelectronics, photonics, actuators, and solar cells. As a promising compound semiconductor, ZnO has a number of advantages over other materials such as low cost and efficient excitonic emission. Tremendous effort has been made in recent years, however, high quality ZnO NWs with well controlled structure and property, especially doping with p-type conductivity, is still unavailable for device fabrication. This paper reviews some of the fundamental aspects of ZnO NW research and showcases the importance of ZnO NWs with proper properties for future applications. It includes the synthesis and patterned growth, the challenge for p-type doping, basic properties of ZnO NWs, and their potential applications. It concludes with future prospects of this exciting material. © 2011 Elsevier Inc. All rights reserved. Source


Drawve G.,University of Arkansas at Little Rock
Justice Quarterly | Year: 2016

There are numerous hot spot mapping techniques that can be used in research and in practice for predicting future crime locations. Due to differences in the varying techniques, metrics were developed to compare the accuracy and precision of these techniques. The predictive accuracy index (PAI) and recapture rate index (RRI) were used to assess six different hot spot techniques. Spatial and Temporal Analysis of Crime, Nearest Neighbor Hierarchical, Kernel Density Estimation, and Risk Terrain Modeling were the general techniques compared in relation to their PAI and RRI values for short-term and long-term prediction of robberies. The results of the study were discussed with an emphasis on the utility of using multiple techniques jointly for analysis. © 2014 Academy of Criminal Justice Sciences. Source


Liu X.,University of Arkansas at Little Rock
International Journal of Electrical Power and Energy Systems | Year: 2012

In this paper, an optimization model is developed for a system consisting of both combined heat and power units and wind turbines. The analysis is conducted in the scope of economic dispatch. In the present model, the probability (rather than the average) of stochastic wind power is considered as a constraint. This approach avoids the probabilistic infeasibility appearing in conventional approaches. It is shown that the effects of wind speed on the generated power and heat can be readily assessed in terms of reliability. © 2012 Elsevier Ltd. All rights reserved. Source

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