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Institution

Miami University

EducationOxford, Ohio, United States
About: Miami University is a(n) education organization based out in Oxford, Ohio, United States. It is known for research contribution in the topic(s): Population & Poison control. The organization has 9949 authors who have published 19598 publication(s) receiving 568410 citation(s). The organization is also known as: Miami of Ohio & Miami-Ohio.
Papers
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Journal ArticleDOI
Marjorie M. Cowan1Institutions (1)
TL;DR: The current status of botanical screening efforts, as well as in vivo studies of their effectiveness and toxicity, are summarized and the structure and antimicrobial properties of phytochemicals are addressed.
Abstract: The use of and search for drugs and dietary supplements derived from plants have accelerated in recent years. Ethnopharmacologists, botanists, microbiologists, and natural-products chemists are combing the Earth for phytochemicals and “leads” which could be developed for treatment of infectious diseases. While 25 to 50% of current pharmaceuticals are derived from plants, none are used as antimicrobials. Traditional healers have long used plants to prevent or cure infectious conditions; Western medicine is trying to duplicate their successes. Plants are rich in a wide variety of secondary metabolites, such as tannins, terpenoids, alkaloids, and flavonoids, which have been found in vitro to have antimicrobial properties. This review attempts to summarize the current status of botanical screening efforts, as well as in vivo studies of their effectiveness and toxicity. The structure and antimicrobial properties of phytochemicals are also addressed. Since many of these compounds are currently available as unregulated botanical preparations and their use by the public is increasing rapidly, clinicians need to consider the consequences of patients self-medicating with these preparations.

6,996 citations


Journal ArticleDOI
TL;DR: The use (and misuse) of GLMMs in ecology and evolution are reviewed, estimation and inference are discussed, and 'best-practice' data analysis procedures for scientists facing this challenge are summarized.
Abstract: How should ecologists and evolutionary biologists analyze nonnormal data that involve random effects? Nonnormal data such as counts or proportions often defy classical statistical procedures. Generalized linear mixed models (GLMMs) provide a more flexible approach for analyzing nonnormal data when random effects are present. The explosion of research on GLMMs in the last decade has generated considerable uncertainty for practitioners in ecology and evolution. Despite the availability of accurate techniques for estimating GLMM parameters in simple cases, complex GLMMs are challenging to fit and statistical inference such as hypothesis testing remains difficult. We review the use (and misuse) of GLMMs in ecology and evolution, discuss estimation and inference and summarize 'best-practice' data analysis procedures for scientists facing this challenge.

6,380 citations


Journal ArticleDOI
Asru K. Sinha1Institutions (1)
TL;DR: A simple colorimetric assay for catalase activity has been described using K2Cr2O7/acetic acid reagent to determine values of different enzyme sources and compared with the values obtained by titrimetric methods.
Abstract: A simple colorimetric assay for catalase activity has been described using K2Cr2O7/acetic acid reagent. Kat. f values of different enzyme sources were determined by the colorimetric method and compared with the values obtained by titrimetric methods.

4,341 citations


Journal ArticleDOI
Rob J. Hyndman1, Anne B. Koehler2Institutions (2)
Abstract: We discuss and compare measures of accuracy of univariate time series forecasts. The methods used in the M-competition as well as the M3-competition, and many of the measures recommended by previous authors on this topic, are found to be degenerate in commonly occurring situations. Instead, we propose that the mean absolute scaled error become the standard measure for comparing forecast accuracy across multiple time series.

3,116 citations


Journal ArticleDOI
Abstract: Highly emphasized in entrepreneurial practice, business models have received limited attention from researchers. No consensus exists regarding the definition, nature, structure, and evolution of business models. Still, the business model holds promise as a unifying unit of analysis that can facilitate theory development in entrepreneurship. This article synthesizes the literature and draws conclusions regarding a number of these core issues. Theoretical underpinnings of a firm’s business model are explored. A six-component framework is proposed for characterizing a business model, regardless of venture type. These components are applied at three different levels. The framework is illustrated using a successful mainstream company. Suggestions are made regarding the manner in which business models might be expected to emerge and evolve over time.

2,185 citations


Authors

Showing all 9949 results

NameH-indexPapersCitations
Krzysztof Matyjaszewski1691431128585
James H. Brown12542372040
Mark D. Griffiths124123861335
Hong-Cai Zhou11448966320
Donald E. Canfield10529843270
Michael L. Klein10474578805
Heikki V. Huikuri10362045404
Jun Liu100116573692
Joseph M. Prospero9822937172
Camillo Ricordi9484540848
Thomas A. Widiger9342030003
James C. Coyne9337838775
Henry A. Giroux9051636191
Martin Wikelski8942025821
Robert J. Myerburg8761432765
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202214
2021902
2020903
2019820
2018772
2017814