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Grambling, LA, United States

Grambling State University is a historically black, public, coeducational university, located in Grambling, Louisiana. The university is the home of late head football coach Eddie Robinson, and is listed on the Louisiana African American Heritage Trail. The University is a member-school of the Thurgood Marshall College Fund. Wikipedia.

Quick Q.,Grambling State University | Skalli O.,Louisiana State University Health Sciences Center
Experimental Cell Research | Year: 2010

α-Actinin is a prominent actin filament associated protein for which different isoforms exist. Here, we have examined whether the two highly homologous non-muscle α-actinin isoforms 1 and 4 exhibit functional differences in astrocytoma cells. The protein levels of these isoforms were differentially regulated during the development and progression of astrocytomas, as α-actinin 1 was higher in astrocytomas compared to normal brains whereas α-actinin 4 was elevated in high-grade astrocytomas compared to normal brains and low grade astrocytomas. RNAi demonstrated contrasted contributions of α-actinin 1 and 4 to the malignant behavior of U-373, U-87 and A172 astrocytoma cells. While α-actinin 1 appeared to favor the expansion of U-373, U-87 and A172 astrocytoma cell populations, α-actinin 4 played this role only for U-373 cells. On the other hand, downregulation of α-actinin 4, but not 1, reduced cell motility, adhesion, cortical actin, and RhoA levels. Finally, in the three astrocytoma cell lines examined, α-actinin 1 and 4 had contrasted biochemical properties as α-actinin 4 was significantly more abundant in the actin cytoskeleton than α-actinin 1. Collectively, these findings suggest that α-actinin 1 and 4 are differentially regulated during the development and progression of astrocytomas because each of these isoforms uniquely contributes to distinct malignant properties of astrocytoma cells. © 2010. Source

Reddy Y.B.,Grambling State University
Sensors and Transducers | Year: 2012

Secure data transfer with minimum overhead is essential. Currently, the secure data transfer in sensor networks uses cryptography, authentication, and probability based approaches. Recently, collaborative trust-based packet transfer technique was used in wireless sensor networks. Further, Sporas formula helps to update the node's trust value in a repeated packet transfer. In the proposed research, the trust level of a node is recommended as the average value generated through Sporas formula and repeated trust calculations. If the trust value of a forwarding node is below the threshold (expected value), the node is suspected as malicious and communicates the status to its neighbor nodes. Further, the neighbor nodes calculate their own trust of a suspicious node using their trust value plus trust factor received from their neighbor. The cooperative and collaborative approach helps to eliminate the suspicious node from the communication path. The proposed technique was analyzed, and simulations were provided. Copyright © 2012 IFSA. Source

Dutta S.,Grambling State University
Journal of Theoretical and Applied Information Technology | Year: 2012

Using the Theory of Planned Behavior and Rogers's Innovation Diffusion Theory a systematic model is developed to predict consumer intention to pay for online content. Results of data analyzed through structural equation modeling suggest that consumer attitude and subjective norms are significant predictors of such intention whereas perceived behavioral control is not. Implications of the results are discussed. © 2005 - 2012 JATIT & LLS. All rights reserved. Source

Norman J.,Grambling State University
The ABNF journal : official journal of the Association of Black Nursing Faculty in Higher Education, Inc | Year: 2012

Simulation-based learning is an educational intervention which creates an environment that is conducive to experiential learning. Despite the prevalence of research on the influence of simulation on nursing education, there is a dearth of literature on the effectiveness of simulation-based learning. This systematic review examines literature on simulation outcomes in nursing education from the years 2000-2010. The electronic databases reviewed for the systematic review of the literature included: CINAHL Plus, Medline, Health Source: Nursing/Academic Education, Google Scholar, and Digital Dissertations and Theses through ProQuest. The MeSH search terms included "simulation outcomes measurement" and "nursing education". Seventeen studies were included in the review of the literature. The literature was categorized into three themes; internal outcomes, external outcomes, and clinical evaluation. The available literature on simulation and nursing education provides evidence that that simulation is useful in creating a learning environment which contributes to knowledge, skills, safety, and confidence. This systematic review of the literature revealed a gap in the literature pertaining to the transfer of these outcomes to the clinical setting, and lays a foundation for further research on outcomes specific to simulation and nursing education. Source

Bouchaffra D.,Grambling State University
IEEE Transactions on Neural Networks | Year: 2010

Hidden Markov models (HMMs) and their variants are capable to classify complex and structured objects. However, one of their major restrictions is their inability to cope with shape or conformation intrinsically: HMM-based techniques have difficulty predicting the n-dimensional shape formed by the symbols of the visible observation (VO) sequence. In order to fulfill this crucial need, we propose a novel paradigm that we named conformation-based hidden Markov models (COHMMs). This new formalism classifies VO sequences by embedding the nodes of an HMM state transition graph in a Euclidean vector space. This is accomplished by modeling the noise contained in the shape composed by the VO sequence. We cover the one-level as well as the multilevel COHMMs. Five problems are assigned to a multilevel COHMM: 1) sequence probability evaluation, 2) statistical decoding, 3) structural decoding, 4) shape decoding, and 5) learning. We have applied the COHMMs formalism to human face identification tested on different benchmarked face databases. The results show that the multilevel COHMMs outperform the embedded HMMs as well as some standard HMM-based models. © 2006 IEEE. Source

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