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Quincy, MA, United States

The Eastern Nazarene College is a private, coeducational college of the liberal arts and science in Quincy, Massachusetts, near Boston, in the New England region of the United States. It is known for its religious affiliation, liberal arts core curriculum, and its science and religion education. Its academic programs are primarily undergraduate, with some professional graduate education offered. The residential campus, in Wollaston Park near Quincy Bay, is served by the Wollaston MBTA station, and was once the summer home of Boston mayor Josiah Quincy, Jr. Established as a holiness college in Saratoga Springs, New York, in 1900, it was relocated to Massachusetts in 1919. Wikipedia.

This review is a salute to Monty Kier's creativity. Emphasis is placed on creative aspects in the development of the representation of molecular topological structure information and the resultant formalisms: Molecular connectivity and electrotopological state (E-State). Less attention is given to detailed analysis of individual papers and the generally well known books and book chapters. This discussion reveals creative paths that led to the concept of the atomic descriptors, simple connectivity delta, encoding local topology, and valence delta value which encodes valence electron information. The fundamental developments that led to the creation of molecular connectivity chi indices are described along with extensions to different chi and delta chi formalisms. Continued thinking about structure in the topological sense led to the development of the only valence state electronegativity formalism based entirely on structure, Kier-Hall electronegativity (KHE). That creation further inspired the development of the electronegativity/topology-based atomic intrinsic state along with perturbation terms that together give electrotopological state indices (E-State). Further creation led to atom and bond type E-State descriptors. All these developments are briefly illustrated with examples in QSAR, chemical similarity, and database searching. © 2012 Bentham Science Publishers. Source

Zhang X.,Harbin Institute of Technology | Zhang X.,Heilongjiang Institute of Technology | Hu L.,Harbin Institute of Technology | Zhang L.,Eastern Nazarene College
Neurocomputing | Year: 2013

In this paper, we address a regression problem for economic data forecasting by using multiple-kernel learning (MKL) and propose a novel two-step multiple-kernel regression (MKR) method. The proposed MKR method firstly reformulates learning from linear convex combination of the basis kernels as a maximum eigenvalue problem. The optimal weights of basis kernels in the combination can be conveniently derived from solving the maximum eigenvalue problem by eigenvalue decomposition instead of solving complicated optimization like most existing MKR algorithms. By means of SVR optimization routine, finally, we can learn from basis kernels which have different predictive ability so as to improve prediction performance. More significantly, the way to address MKR problem can make sense of the weights and the correspondingly optimal kernel in terms of interpretability. To evaluate performance, the proposed MKR method is compared with the state-of-the-art methods on three real sets of economics data. The experimental results prove that the proposed two-step MKR method outperforms the other methods in terms of prediction performance and model selection, and demonstrates satisfied efficiency. © 2013 Elsevier B.V. Source

Kao Y.,Harbin Institute of Technology | Kao Y.,Qingdao University | Wang C.,Harbin Institute of Technology | Zhang L.,Eastern Nazarene College
Neural Processing Letters | Year: 2013

This paper is devoted to investigating delay-dependent robust exponential stability for a class of Markovian jump impulsive stochastic reaction-diffusion Cohen-Grossberg neural networks (IRDCGNNs) with mixed time delays and uncertainties. The jumping parameters, determined by a continuous-time, discrete-state Markov chain, are assumed to be norm bounded. The delays are assumed to be time-varying and belong to a given interval, which means that the lower and upper bounds of interval time-varying delays are available. By constructing a Lyapunov-Krasovskii functional, and using poincarè inequality and the mathematical induction method, several novel sufficient criteria ensuring the delay-dependent exponential stability of IRDCGNNs with Markovian jumping parameters are established. Our results include reaction-diffusion effects. Finally, a Numerical example is provided to show the efficiency of the proposed results. © 2012 Springer Science+Business Media New York. Source

Rinehart J.P.,U.S. Department of Agriculture | Yocum G.D.,U.S. Department of Agriculture | Leopold R.A.,U.S. Department of Agriculture | Robich R.M.,Eastern Nazarene College
Journal of Medical Entomology | Year: 2010

A major expenditure in vector biology laboratories is the rearing of mosquitoes. Most mosquito colonies require substantial effort to maintain, including frequent bloodmeals for optimal performance. Successful cryopreservation of mosquitoes continues to be elusive. Although using diapause as a storage mechanism is an option for mosquito preservation, several obstacles include the lack of a well-characterized diapause or the inability of some species to enter diapause. Thus, other options for preservation are needed. To address this issue, we investigated the use of long-term low-temperature storage in the absence of diapause for adults of the northern house mosquito, Culex pipiens L. Our results indicate that although male longevity is not substantially increased by cold storage, female longevity is dramatically increased by storage at lower temperatures. When mated before storage, females remain reproductively viable after at least 10 wk of storage, although at reduced levels. These results indicate that cold storage without diapause induction is a viable option for colony maintenance in vector biology laboratories. Source

Hall L.M.,Hall Associates Consulting | Hall L.H.,Eastern Nazarene College | Kertesz T.M.,University of Connecticut | Hill D.W.,University of Connecticut | And 6 more authors.
Journal of Chemical Information and Modeling | Year: 2012

The goal of many metabolomic studies is to identify the molecular structure of endogenous molecules that are differentially expressed among sampled or treatment groups. The identified compounds can then be used to gain an understanding of disease mechanisms. Unfortunately, despite recent advances in a variety of analytical techniques, small molecule (<1000 Da) identification remains difficult. Rarely can a chemical structure be determined from experimental "features" such as retention time, exact mass, and collision induced dissociation spectra. Thus, without knowing structure, biological significance remains obscure. In this study, we explore an identification method in which the measured exact mass of an unknown is used to query available chemical databases to compile a list of candidate compounds. Predictions are made for the candidates using models of experimental features that have been measured for the unknown. The predicted values are used to filter the candidate list by eliminating compounds with predicted values substantially different from the unknown. The intent is to reduce the list of candidates to a reasonable number that can be obtained and measured for confirmation. To facilitate this exploration, we measured data and created models for two experimental features; MS Ecom50 (the energy in electronvolts required to fragment 50% of a selected precursor ion) and HPLC retention index. Using a data set of 52 compounds, Ecom50 models were developed based on both Molconn and CODESSA structural descriptors. These models gave r 2 values of 0.89 to 0.94 depending on the number of inputs, the modeling algorithm chosen, and whether neutral or protonated structures were used. The retention index model was developed with 400 compounds using a back-propagation artificial neural network and 33 Molconn structure descriptors. External validation gave a v2 = 0.87 and standard error of 38 retention index units. As a test of the validity of the filtering approach, the Ecom50 and retention index models, along with exact mass and collision induced dissociation spectra matching, were used to identify 1,3-dicyclohexylurea in human plasma. This compound was not previously known to exist in human biofluids and its elemental formula was identical to 315 other candidate compounds downloaded from PubChem. These results suggest that the use of Ecom50 and retention index predictive models can improve nontargeted metabolite structure identification using HPLC/MS derived structural features. © 2012 American Chemical Society. Source

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