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Mankato, MN, United States

Minnesota State University, Mankato , also known as Minnesota State, is a public comprehensive university located in Mankato, Minnesota. The university sits atop the bluff of the Blue Earth River valley, approximately 75 miles southwest of Minneapolis-St. Paul. Founded as Mankato Normal School in 1868, it is the second oldest member of the Minnesota State Colleges and Universities System. It also the second largest public university in the state and has over 112,000 alumni worldwide.It is an important part of the economy of South-Central Minnesota as it adds more than $377.13 million to the economy annually.Minnesota State offers 140 undergraduate programs of study, 80 graduate programs and 4 doctoral programs. Students are served by 750 full-time faculty members creating a 25:1 student to faculty ratio. In addition to the main campus, it operates two satellite campuses: one in the Twin Cities suburb of Edina and the other in Owatonna. Through the College of Extended Learning it provides bachelor's degrees at the Normandale Partnership Center and programs online through an online campus. Wikipedia.

Fugate J.E.,Mayo Medical School | Klunder A.M.,Minnesota State University, Mankato | Kallmes D.F.,Mayo Medical School
American Journal of Neuroradiology | Year: 2013

BACKGROUND: In 2003, Higashida et al proposed the Thrombolysis In Cerebral Infarction scale to evaluate angiographic intracranial flow. Our aim is to review how subsequently published studies define TICI. MATERIALS AND METHODS: We used the ISI Web of Knowledge and SciVerse Scopus databases to search for "TICI" and "thrombolysis in cerebral infarction" and for articles that cited the original TICI paper from January 2004 through May 2012. Articles were categorized according to their definition of the TICI categories, typically grades 0-4, with grade 2 (partial reperfusion) subdivided into 2a and 2b, and rate of contrast entry to the perfused area. In addition, we catalogued the type of redefinitions of TICI subcategory 2 and additions of new categories. RESULTS: Of 236 articles screened, 74 were included. Eight (11%) explicitly followed the TICI scale as originally defined. Thirty-seven (50%) cited Higashida but did not define their scale. Fifteen (21%) used and explained modified scales. Thirteen (18%) used the term TICI, but did not define the scale and did not cite Higashida. Eighteen (24%) specified a 2a subcategory. Nine defined grade 2a as <67% filling, 6 defined it as <50%, and 3 did not offer a percentage. Two studies added a 2c subcategory. Fifty-two (70%) used a cutoff level to define "successful reperfusion." Of these, 65% used TICI ≥2, 33% used TICI ≥2b, and 2% used TICI = 3. CONCLUSIONS: There is substantial variability in the definition and/or application of the TICI scale in the literature. This variability could considerably impact our understanding of results of revascularization studies.

Pettitt R.W.,Minnesota State University, Mankato
Journal of Strength and Conditioning Research | Year: 2010

Inferential statistics help the strength and conditioning specialist to determine if a team is responding to a strength and conditioning program overall; however, such statistics do not detect unusual responses among individuals such as those who may be overtraining. This article introduces the standard difference score (SDS), a new statistic for evaluating strength and conditioning programs. The SDSs are standard scores (z score) derived from a change in a raw strength and conditioning performance score. They are simple to calculate and sort, easy to plot, and can be aggregated to detect athletes exhibiting extreme performance changes from a battery of tests. Standard difference scores, when evaluated with skewness, can be substituted for conventional exploratory statistics generated with higher end statistical software programs. © 2010 National Strength and Conditioning Association.

Bockting W.O.,University of Minnesota | Miner M.H.,University of Minnesota | Swinburne Romine R.E.,University of Minnesota | Hamilton A.,Minnesota State University, Mankato | Coleman E.,University of Minnesota
American Journal of Public Health | Year: 2013

Objectives: We assessed the association between minority stress, mental health, and potential ameliorating factors in a large, community-based, geographically diverse sample of the US transgender population. Methods: In 2003, we recruited through the Internet a sample of 1093 maleto-female and female-to-male transgender persons, stratified by gender. Participants completed an online survey that included standardized measures of mental health. Guided by the minority stress model, we evaluated associations between stigma and mental health and tested whether indicators of resilience (family support, peer support, identity pride) moderated these associations. Results: Respondents had a high prevalence of clinical depression (44.1%), anxiety (33.2%), and somatization (27.5%). Social stigma was positively associated with psychological distress. Peer support (from other transgender people) moderated this relationship. We found few differences by gender identity. Conclusions: Our findings support the minority stress model. Prevention needs to confront social structures, norms, and attitudes that produce minority stress for gender-variant people; enhance peer support; and improve access to mental health and social services that affirm transgender identity and promote resilience.

Thomas P.M.,Minnesota State University, Mankato
Homicide Studies | Year: 2011

This article reviews the contributions of social disorganization, cultural, and strain perspectives to criminological understanding of the relationship between immigration and crime. In efforts to draw parallels between the theories and strands of scholarship on immigration, various hypotheses are outlined to encourage expansion of knowledge on immigration and crime, theoretical extension, revision, and perhaps integration as well. © 2011 SAGE Publications.

Agency: NSF | Branch: Standard Grant | Program: | Phase: COMPUTING RES INFRASTRUCTURE | Award Amount: 145.36K | Year: 2013

The Speech Recognition Virtual Kitchen

Performing successful research on end-to-end speech processing problems requires the integration of many individual tools (e.g. for data cleaning, acoustic model training, language modeling, data analysis, real-time audio, decoding, parsing, synthesis, etc.). It is difficult for new researchers to get started in the field, simply because a typical lab environment consists of a hodgepodge of tools suited to a particular computing set-ups. This environment is hard to recreate, because few people are experts in the theory and practice of all these fields, and can debug and replicate experiments from scratch.

This research infrastructure project creates a kitchen environment based on Virtual Machines (VMs) to promote community sharing of research techniques, and provides solid reference systems as a tool for education, research, and evaluation. We liken VMs to a kitchen because they provide an environment into which one can install appliances (e.g., toolkits), recipes (scripts for creating state-of-the art systems using these tools), and ingredients (spoken language data). The kitchen even holds reference dishes in the form of complete experiments with baseline runs, log-files, etc., together with all that is needed to recreate and modify them.

The project is developing a community and repository by (a) building pilot VMs, (b) engaging the community in using and continuing to develop them on its own, and (c) evaluating the impact of providing VMs for education and research. We envision researchers as well as students downloading a VM, reproducing the baseline experiment, implementing changes, posting their results in the community, discussing with other users who have worked on the same VM, merging improvements back into the VM, which get re-distributed, and finally publishing easily reproducible results. Work with curriculum and project development will support the creation of engaging activities to specifically encourage students at undergraduate and graduate levels.

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