University of Nebraska Omaha

About: University of Nebraska Omaha is a education organization based out in Omaha, Nebraska, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 4526 authors who have published 8905 publications receiving 213914 citations. The organization is also known as: UNO & University of Omaha.

Advancing Creativity Theory and Research: A Socio‐cultural Manifesto

Abstract: This manifesto, discussed by 20 scholars, representing diverse lines of creativity research, marks a conceptual shift within the field. Socio-cultural approaches have made substantial contributions to the concept of creativity over recent decades and today can provide a set of propositions to guide our understanding of past research and to generate new directions of inquiry and practice. These propositions are urgently needed in response to the transition from the Information Society to the Post-Information Society. Through the propositions outlined here, we aim to build common ground and invite the community of creativity researchers and practitioners to reflect up, study, and cultivate creativity as a sociocultural phenomenon.

FAMCDM: A fusion approach of MCDM methods to rank multiclass classification algorithms

Abstract: Various methods and algorithms have been developed for multiclass classification problems in recent years. How to select an effective algorithm for a multiclass classification task is an important yet difficult issue. Since the multiclass algorithm selection normally involves more than one criterion, such as accuracy and computation time, the selection process can be modeled as a multiple criteria decision making (MCDM) problem. While the evaluations of algorithms provided by different MCDM methods are in agreement sometimes, there are situations where MCDM methods generate very different results. To resolve this disagreement and help decision makers pick the most suitable classifier(s), this paper proposes a fusion approach to produce a weighted compatible MCDM ranking of multiclass classification algorithms. Several multiclass datasets from different domains are used in the experimental study to test the proposed fusion approach. The results prove that MCDM methods are useful tools for evaluating multiclass classification algorithms and the fusion approach is capable of identifying a compromised solution when different MCDM methods generate conflicting rankings.

Tuning Electronic and Magnetic Properties of Early Transition Metal Dichalcogenides via Tensile Strain

Abstract: We have performed a systematic first-principles study of the effect of tensile strains on the electronic properties of early transition-metal dichalcogenide (TMDC) monolayers MX2 (M = Sc, Ti, Zr, Hf, Ta, Cr; X = S, Se, and Te). Our density-functional theory (DFT) calculations suggest that the tensile strain can significantly affect the electronic properties of many early TMDCs in general and the electronic bandgap in particular. For group IVB TMDCs (TiX2, ZrX2, HfX2), the bandgap increases with the tensile strain, but for ZrX2 and HfX2 (X=S, Se), the bandgap starts to decrease at strain 6% to 8%. For the group-VB TMDCs (TaX2), the tensile strain can either induce the ferromagnetism or enhance the existing ferromagnetism. For the group-VIB TMDCs (CrX2) the direct-to-indirect bandgap transition is seen upon application of the tensile strain, except CrTe2 whose bandgap decreases with the tensile strain even though the direct character of its bandgap is retained. Lastly, for the group-IIIB TMDCs (ScX2) in the T metallic phase, we find that the tensile strain has little effect on their electronic and magnetic properties. Our study suggests that strain engineering is an effective approach to modify electronic and magnetic properties of most early TMDC monolayers, thereby opening an alternative way for future optoelectronic and spintronic applications.

Finding cycles in synchronous Boolean networks with applications to biochemical systems

Abstract: This paper is an analytical study of Boolean networks. The motivation is our desire to understand the large, complicated and interconnected pathways which comprise intracellular biochemical signal transduction networks. The simplest possible conceptual model that mimics signal transduction with sigmoidal kinetics is the n-node Boolean network each of whose elements or nodes has the value 0 (off) or 1 (on) at any given time T = 0, 1, 2, …. A Boolean network has 2n states all of which are either on periodic cycles (including fixed points) or transients leading to cycles. Thus one understands a Boolean network by determining the number and length of its cycles. The problem one must circumvent is the large number of states (2n) since the networks we are interested in have 100 or more elements. Thus we concentrate on developing size n methods rather than the impossible task of enumerating all 2n states. This is done as follows: the dynamics of the network can be described by n polynomial equations which describe the logical function which determines the interaction at each node. Iterating the equations one step at a time finds all fixed points, period two cycles, period three cycles, etc. This is a general method that can be used to determine the fixed points and moderately large periodic cycles of any size network, but it is not useful in finding the largest cycles in a large network. However, we also show that the network equations can often be reduced to scalar form, which makes the cycle structure much more transparent. The scalar equations method is a true "size n" method and several examples (including nontrivial biochemical systems) are examined.

Genomic analyses reveal global functional alterations that promote tumor growth and novel tumor suppressor genes in natural killer-cell malignancies.

Abstract: Natural killer (NK)-cell malignancies are among the most aggressive lymphoid neoplasms with very poor prognosis. We performed array comparative genomic hybridization analysis on a number of NK cell lines and primary tumors to gain better understanding of the pathogenesis and tumor biology of these malignancies. We also obtained transcriptional profiles of genes residing in these regions and compared them with normal and activated NK cells. Only 30-50% of the genes residing in the gained or deleted regions showed corresponding increased or decreased expression. However, many of the upregulated genes in regions of gain are functionally important for the proliferation and growth of the neoplastic population. Genes downregulated in regions of loss included many transcription factors or repressors, tumor suppressors or negative regulators of the cell cycle. The minimal common region of deletion in 6q21 included three known genes (PRDM1, ATG5 and AIM1) showing generally low expression. Mutations resulting in truncated PRDM1 and changes in conserved amino-acid sequences of AIM1 were detected. Highly methylated CpG islands 5' of PRDM1 and AIM1 correlated with low expression of the transcripts. Reversal of methylation by Decitabine induced expression of PRDM1 and cell death. In conclusion, we have shown a general tumor-promoting effect of genetic alterations and have identified PRDM1 as the most likely target gene in del6q21. ATG5, an essential gene for autophagy and AIM1, a gene implicated in melanoma, may also participate in the functional abnormalities.