Omaha, NE, United States

University of Nebraska at Omaha

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Omaha, NE, United States
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Domestic dogs (Canis familiaris) have been suggested as a natural model for human social cognition, possessing social skills that are in many ways functionally analogous to those of young humans. Researchers have debated the origins of dogs’ human-like social competence and the underlying cognitive mechanisms, but only recently have researchers begun to explore their neurobiological underpinnings. In this review, findings from behavioral studies are integrated with what is known about the biological basis of dogs’ human-directed social competence, with an emphasis on how stress-mediating systems, particularly the hypothalamic-pituitary-adrenal (HPA) axis, interact with oxytocin and underlying neural systems to facilitate dogs’ interspecific social-cognitive abilities. The working model presented in this paper offers a biological explanation for many of the inconsistent findings from past work on social cognition in dogs and generates questions for future research in the field of canine social competence. © 2016 Elsevier Ltd


Peterson M.P.,University of Nebraska at Omaha
Lecture Notes in Geoinformation and Cartography | Year: 2015

Application Programmer Interfaces (APIs) support multi-scale panable (MSP) maps from the major online map providers. A mapping API consists of a series of functions that control the scale and location of the map, and any added information in the form of points, lines or areas. Raster layers can also be overlaid to totally obscure the underlying map. Available since 2005, the use of APIs has proliferated and now represents the most common cloud mapping technique. Soon after the release of the Google Maps API, Microsoft and Yahoo soon followed with their own versions. Eventually, MapQuest and OpenStreetMap also released APIs. While similar, all of these APIs used specific functions and objects. The MapStraction open source project attempts to create a single API that can be used with all of these mapping sources. Additional APIs have since been introduced by Nokia and Leaflet. The purpose here is to examine the major mapping APIs and provide a basis for evaluation. © Springer International Publishing Switzerland 2015.


Hughes L.A.,University of Nebraska at Omaha
Criminology | Year: 2013

Data from Short and Strodtbeck's (1965) study of gangs in Chicago, 1959-1962, are used to examine the association between intragang friendship networks and violent and delinquent behaviors among 248 boys from 11 different gangs (9 Black and 2 White). Contrary to expectations of tightly connected gangs being the most dangerous, estimates from multilevel overdispersed Poisson regression models showed significantly increased mean levels of violence among gangs with relatively low group cohesion. No relationship was observed between delinquency and gang cohesiveness, regardless of the specific network measure employed. At the individual level, popular boys were at a significantly increased risk for both delinquency and violence, suggesting a link between prestigious positions within the structure of gang friendship networks and conformity with group processes. The implications of these findings for detached worker intervention are discussed. © 2013 American Society of Criminology.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: | Award Amount: 1.20M | Year: 2014

In a partnership between the Omaha Public Schools (OPS) and the University of Nebraska at Omaha (UNO), this Noyce Scholarship Track Phase I program will address the national need for more underrepresented STEM talent who pursue careers in teaching. The initiative is building upon momentum from ongoing STEM Education initiatives at both institutions. The Omaha Noyce Partnership represents a new UNO initiative that aligns with NebraskaMATH, a statewide partnership that works to improve achievement in mathematics for all students and to narrow the STEM achievement gaps of at-risk populations. The Omaha Noyce Partnership will recruit a diverse pool of new teachers and provide much needed funding to support economically disadvantaged students. The partnership will strengthen and expand the pipeline for preparing mathematics teachers at UNO to better meet the high demand for teachers in local school districts, particularly in districts with high-need schools.

The Omaha Noyce Partnership scholarship program is designed to develop highly skilled secondary mathematics teachers who are committed to teaching in high-need schools by providing targeted support for students enrolled in and graduating from UNOs Bachelor of Science in Mathematics/Teacher Preparation program. The program includes new coursework and complements existing pathways that were developed by the UNO mathematics and education faculty in collaboration with school district partners. The projects evaluation activities will inform and advance ongoing collaborative research initiatives related to the effectiveness of inquiry-based learning in teaching mathematical concepts and in preparing students to be effective secondary mathematics teachers. All of the students supported by the Omaha Noyce Partnership will be enrolled in this new program and will receive focused training and extensive fieldwork in the Omaha Public Schools to prepare them for teaching careers in high need schools, including instruction in inquiry-based learning and other culturally responsive pedagogies.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: Exploiting Parallel&Scalabilty | Award Amount: 146.53K | Year: 2015

The goal of SPANDAN project is to create a novel architecture-independent framework
for designing efficient, portable and scalable parallel algorithms for analyzing
large-scale dynamic networks. SPANDAN will not only provide an intuitive methodology
for efficiently translating sequential algorithms into scalable parallel algorithms
for dynamic networks, but also provide mechanisms for their analytical evaluation and
serve as a mediatory layer between applications and system level tuning. To evaluate
the effectiveness of SPANDAN framework in real-world applications, the PIs will
collaborate with social scientists and biologists. They will also integrate research
findings into various courses such as network analysis, parallel algorithms, and
bioinformatics. They will further collaborate with high schools to develop summer courses
with the goal of encouraging women and minority students to pursue IT-related careers.


As the underlying methodology, the SPANDAN framework will exploit graph sparsification
techniques to divide the network into sparse subgraphs (certificates) that form the
leaves of a sparsification tree. This innovative approach will lead to the design and
analysis of efficient parallel algorithms for updating dynamic networks, and reduction
of memory latency associated with parallelizing unstructured data. Specifically parallel
algorithms will be designed for maintaining network topological characteristics, and
updating influential vertices and communities. To demonstrate portability and performance,
the developed algorithms will be implemented on the distributed memory clusters, shared
memory multicores, and massively multithreaded CRAY-XMT.

For further information see the project web site at:
http://cs.mst.edu/labs/crewman/projects/SPANDAN/


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: BD Spokes -Big Data Regional I | Award Amount: 99.96K | Year: 2016

Bridges across the U.S. continue to deteriorate at an alarming rate and the American Society of Civil Engineers estimate a cost of over $76 billion to improve the countrys functionally obsolete or structurally deficient bridges. This indicates a significant demand for innovative bridge health monitoring solutions that can strategically guide management, maintenance and replacement programs without risking public safety. Unfortunately, the need to improve how our bridges are managed and repaired or replaced faces similar issues and demands as the rest of the U.S. transportation network: continuously shrinking resources and governing bodies who do not have the necessary insights from bridge health data to find a workable solution.

To discuss how to address these critical problems, researchers, practitioners, and individuals representing public and private sectors (transportation infrastructure and built environment owners, operators, designers and maintainers) convened with Big Data technology and analytics experts participated at the inaugural BRIDGE-ing Big Data Workshop hosted by the University of Nebraska in October 2015. During this workshop, it became clear that Big Data technology could assist with providing a timely solution. It also was apparent that past efforts focusing on utilizing bridge health monitoring and big data techniques as part of the management and maintenance/replacement processes are fragmented, and resulting datasets are not deemed trustworthy and are under-utilized. This project will (1) catalog datasets including sources, copyrights, license, collection procedures, and expected access controls from private sector, academia, and government agencies, (2) obtain commitments from stakeholders and host collaboration workshops with small working groups to discuss, import/export, and share bridge structural health monitoring data, and (3) solicit proposals from businesses/researchers to develop innovative applications that integrate disparate and voluminous data sources. It is anticipated that this projects findings will benefit the Midwest Big Data Hub transportation spoke and potentially inform similar activities for highways, buildings, power distribution networks and other civil infrastructure entities. Findings from this project will be promoted to national and international technical organizations, to directly impact workforce development, education and research programs. Combined, this project will make a direct impact on our countrys ability to efficiently maintain the health and safety of its bridges.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: Secure &Trustworthy Cyberspace | Award Amount: 290.04K | Year: 2016

Quantum cryptography is a subject that is typically difficult to learn. One possible reason is that students are treated as passive recipients with linear and fragmented teaching presentations that provide no opportunity for learning the holistic nature of the discipline. Further, quantum cryptographic equipment is expensive and beyond the reach of most universities. At the same time, project-based learning environments are proven more likely to meet educational objectives compared to traditional lectures. QuaSim is a pedagogical game-based simulator that allows students an interactive experience to improve learning by transforming subject-based lectures in quantum cryptography into project-based virtual simulations.

The knowledge components in QuaSim are codified in a highly expressive first-order logic augmented with abductive reasoning to generate explanations for user interactions and solutions. A continual adaptive framework generates customized scenarios and mine responses to measurably improve learning. While a user who is repeatedly able to solve problems without hints is led to harder and/or timed problems, a user repeatedly performing erroneous interactions is fed into pre-defined and automatically learned error models to identify the responsible knowledge component and prescribed scenarios with hints to address knowledge gaps. QuaSim is perhaps the first game-based simulator for quantum cryptography that incorporates abductive theorem proving along with data analysis to continuously adapt game scenarios based on user performance to measurably improve learning. Such adaptations enable instructors to empirically and quantifiably relate student performance to knowledge components and design lesson plans. QuaSim is expected to improve the quality and efficiency of undergraduate and graduate STEM education.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: ENVIRONMENTAL ENGINEERING | Award Amount: 100.00K | Year: 2016

1644595
Kolok

The Mississippi River basin, from Lake Itasca, Minnesota to the Gulf of Mexico, stretches over 2,300 miles and travels through or along the border of 10 different states. The river receives major inputs of water, sediment and nutrients from four major sub-watersheds: the Upper Mississippi River, the Missouri River, the Ohio River and the Arkansas/Red River. It is thought that water quality is responsible for the low oxygen concentrations in the Gulf of Mexico, known as the Dead Zone, near where the Mississippi discharges into the Gulf. Relative to this watershed, public participation in scientific research can be a valuable resources for data collection. Samples which are repeated and simultaneously taken in different locations can estimate the temporal variability of a compounds occurrence at specific priority sites. Second, since the sampling is mobile, sampling can be adjusted quickly if the environmental conditions change. Therefore, the long-term goal of this project is to build a national citizen science network that can monitor for contaminants in water across geographical scales that are too large to be efficiently sampled using traditional methods.

This research is novel, as it can provide large amounts of simultaneously collected data across a wide geography. Such data collection would not be possible with standard methods and technologies. To fulfill this objective, it will be necessary to satisfy the following specific aims: 1) Evaluate the capacity for citizen scientists to collect repeatable and quantitative data on nutrients and turbidity. 2) To leverage information technology using mobile devices (e.g., smartphones) to capture the data and validate the data integrity for further analysis. 3) To conduct a citizen science campaign within the Mississippi River watershed that will produce spatially and temporally robust quantitative data sets on water quality parameters across the region. The citizen scientists will be provided with commercially available assessment test strips for phosphate, nitrate, and atrazine and will be given a device to estimate turbidity. They will then submit their data via an interactive IT data management system currently under development. To address data integrity, a series of laboratory trials, focusing on experts, as well as experienced and naive citizen scientists, will evaluate the accuracy and reproducibility of water quality data obtained from citizen scientists. It is anticipated that by the end of the study, a series of protocols will be developed to assure data quality and reliability from the citizen scientists collecting data on nutrients, agrichemicals and turbidity. This project can be a model that other scientists, both nationally and internationally, can use to develop monitoring programs that use citizens to collect quality data. In addition to the collection of the data, by partnering with the Nebraska Watershed Network on this project, citizen science participation will bring awareness of environmental issues by bringing science education to life among the Omaha, Nebraska community, to the state of Nebraska, and to the Midwestern United States as a whole. Furthermore, personal visits to K-12 classes, presentations to the public, and information distributed via social media (including two webpages, two Facebook pages, and a listserv) are all being used to leverage the results from a social media campaign into community education and awareness.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: ITEST | Award Amount: 1.14M | Year: 2015

The SPARCS project will support 72 teachers of grades 7-9 to integrate computer science into their science and math instruction. Because the world is adopting computational tools quickly, students need to learn about how computational technology can be leveraged to make informed decisions. This project will help teachers integrate computational thinking and computer science principles into their teaching through these tools, by engaging students in projects that analyze data. The question of how to support secondary teachers to integrate computer science and real world related applications into their STEM instruction is on the cutting edge. This project will inform this issue.

Teachers will participate in a summer institute, online courses in computer science, monthly meetings during the school year, and mentorship with industry professionals. During the summer institute, teachers will work in small teams to create activities within a problem-based learning (PBL) framework, which they will implement in their classrooms during the school year. These activities will be informed by existing curricular resources, publicly available electronic data, and advice from industry experts and project staff. The efforts of these teachers will be documented through several forms of data, including elaborate teacher portfolios, observations, interviews, and student achievement results. These data will support refinement of the project from year 1 to year 3, and will be designed to communicate to other educators how to implement similar efforts in other schools.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: Research Coordination Networks | Award Amount: 499.94K | Year: 2015

The University of Nebraska at Omaha has received a Research Coordination Network - Undergraduate Biology Education award for their project entitled Network for Integrating Bioinformatics into Life Sciences Education (NIBLSE). The long-term goal of this project is to establish bioinformatics as an essential component of undergraduate life sciences curricula nationwide. The field of bioinformatics, which uses techniques from computer science to store, manage, and analyze large biological data sets, has arisen to meet the challenges associated with such large data sets. It is now an important interdisciplinary field that is central to studying many aspects of biology, yet it is not an integral part of most biology curricula nationwide. The current project is informed by the results of the successful conference held by the PI team for their RCN-UBE Incubator project (DBI-134559).

In order to achieve full integration of bioinformatics into undergraduate life sciences education, NIBLSE is establishing a permanent network of investigators committed to this goal. The Leadership Team and Steering Committee are using the literature and their collective expertise to identify, vet, and refine a set of bioinformatics core competencies for inclusion in life sciences curricula. They are also identifying and vetting assessment tools that align with the core competencies and that will facilitate educational research related to the integration of bioinformatics into biology curricula. Finally, they are developing systems to organize and simplify dissemination of curricular materials, assessment tools, and professional development resources. The materials and resources developed by the network are having a broad impact on undergraduate education in the life sciences by enabling educators nationwide to effectively apply bioinformatics knowledge and skills to their teaching and research. This project is funded jointly by the Directorate for Biological Sciences, Division of Biological Infrastructure and the Directorate for Education and Human Resources, Division of Undergraduate Education in support of efforts to address the challenges posed in Vision and Change in Undergraduate Education: A Call to Action http://visionandchange.org/finalreport/.

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