Ornamental plants: annual reports and research reviews, 2002

Ohio State University Extension Nursery, Landscape, and Turf Team directory: 2003 / Jack Kerrigan -- Floriculture Industry Roundtable of Ohio: 2003 / Charles Behnke -- Ohio State University Extension 2002 Buckeye Yard and Garden Line evaluation survey / Amy K. Stone and James A. Chatfield -- Weather, environmental, and cultural problems of ornamental plants in Ohio: 2002 / Pamela J. Bennett -- Infectious disease problems of ornamental plants in Ohio: 2002 / James A. Chatfield, Nancy A. Taylor, Erik A. Draper, and Joseph F. Boggs -- A biological calendar for predicting pest activity: six years of plant and insect phenology in Secrest Arboretum / Daniel A. Herms -- Biological suppression of foliar diseases of ornamental plants with composted manures, biosolids, and Trichoderma hamatum 382 / Harry A. J. Hoitink, Carol A. Musselman, Terry L. Moore, Leona E. Horst, Charles R. Krause, Randy A. Zondag, and Hannah Mathers -- Growth and water use by four leguminous tree species in containers on a gravel surface or embedded in mulch / Michael Knee, Daniel K. Struve, Michael H. Bridgewater, and Joseph W. Phillips -- The effects of sprayer configuration on efficacy for the control of scab on crabapple / Charles R. Krause, Richard C. Derksen, Leona E. Horst, Randall Zondag, Ross D. Brazee, Michael G. Klein, and Michael E. Reding -- Update on honeylocust knot / Pierluigi Bonello, Maria Bellizzi, and Harry A. J. Hoitink -- Control of phytophthora and other major diseases of Ericaceous plants / Harry A. J. Hoitink, Steven T. Nameth, and James C. Locke -- Is your landscape mulch going up in smoke? / Larry G. Steward, T. Davis Sydnor, and Bert Bishop -- IR-4 ornamental trials conducted by USDA-ARS in Ohio: 2002 / Betsy A. Anderson, Michael E. Reding, Michael G. Klein, and Charles R. Krause -- Research on black vine weevil and white grubs in ornamental nurseries-in Ohio by USDA-ARS / Michael E. Reding, Michael G. Klein, Ross D. Brazee, and Charles R. Krause -- Herbaceous ornamental field trial results in Clark County, Ohio – 2002 / Pamela J. Bennett -- Results of annual trial gardens at the Cincinnati Zoo and Botanical Garden for 2002 / Dave Dyke -- Ohio State University Learning Garden annual cultivar trials / Monica M. Kmetz-Gonzalez and Claudio C. Pasian -- A collection of crabapple knowledge from Secrest Arboretum: 1993-2002 / Erik A. Draper, James A. Chatfield, and Kenneth D. Cochran -- Key results of the 2001 Ohio Green Industry Survey / Gary Y. Gao, John J. Smith, James A. Chatfield, Joseph F. Boggs, Erik A. Draper, and Hannah Mathers -- The USDA/Agricultural Research Service research weather network in Lake County, Ohio - 2002 update / R. D. Brazee, R. C. Derksen, C. R. Krause, K. A. Williams, D. Lohnes, M. G. Klein, M. Reding, R. Lyons, W. Hendricks, R. Zondag, R. D. Fox, and D. Herms -- The OSU Chadwick Arboretum Learning Gardens / Dr. Steven Still and Annette Duetz -- Choosing soil testing labs / Gary Y, Gao, Maurice E. Watson, Joseph F. Boggs, and James A. Chatfield -- Top horticultural references for a green industry professional's library / Gary Y. Gao and Pamela J. Bennett -- The maples of Secrest Arboretum / Gary W. Graham, James A. Chatfield, and Kenneth D. Cochran -- Deck the halls with boughs from Ollie! / Kenneth D. Cochran and James A. Chatfiel

ART: A machine learning Automated Recommendation Tool for synthetic biology

Biology has changed radically in the last two decades, transitioning from a descriptive science into a design science. Synthetic biology allows us to bioengineer cells to synthesize novel valuable molecules such as renewable biofuels or anticancer drugs. However, traditional synthetic biology approaches involve ad-hoc engineering practices, which lead to long development times. Here, we present the Automated Recommendation Tool (ART), a tool that leverages machine learning and probabilistic modeling techniques to guide synthetic biology in a systematic fashion, without the need for a full mechanistic understanding of the biological system. Using sampling-based optimization, ART provides a set of recommended strains to be built in the next engineering cycle, alongside probabilistic predictions of their production levels. We demonstrate the capabilities of ART on simulated data sets, as well as experimental data from real metabolic engineering projects producing renewable biofuels, hoppy flavored beer without hops, and fatty acids. Finally, we discuss the limitations of this approach, and the practical consequences of the underlying assumptions failing

Multiple dimensions of health locus of control in a representative population sample: ordinal factor analysis and cross-validation of an existing three and a new four factor model

<p>Abstract</p> <p>Background</p> <p>Based on the general approach of locus of control, health locus of control (HLOC) concerns control-beliefs due to illness, sickness and health. HLOC research results provide an improved understanding of health related behaviour and patients' compliance in medical care. HLOC research distinguishes between beliefs due to Internality, Externality powerful Others (POs) and Externality Chance. However, evidences for differentiating the POs dimension were found. Previous factor analyses used selected and predominantly clinical samples, while non-clinical studies are rare. The present study is the first analysis of the HLOC structure based on a large representative general population sample providing important information for non-clinical research and public health care.</p> <p>Methods</p> <p>The standardised German questionnaire which assesses HLOC was used in a representative adult general population sample for a region in Northern Germany (N = 4,075). Data analyses used ordinal factor analyses in LISREL and Mplus. Alternative theory-driven models with one to four latent variables were compared using confirmatory factor analysis. Fit indices, chi-square difference tests, residuals and factor loadings were considered for model comparison. Exploratory factor analysis was used for further model development. Results were cross-validated splitting the total sample randomly and using the cross-validation index.</p> <p>Results</p> <p>A model with four latent variables (Internality, Formal Help, Informal Help and Chance) best represented the HLOC construct (three-dimensional model: normed chi-square = 9.55; RMSEA = 0.066; CFI = 0.931; SRMR = 0.075; four-dimensional model: normed chi-square = 8.65; RMSEA = 0.062; CFI = 0.940; SRMR = 0.071; chi-square difference test: p < 0.001). After excluding one item, the superiority of the four- over the three-dimensional HLOC construct became very obvious (three-dimensional model: normed chi-square = 7.74; RMSEA = 0.059; CFI = 0.950; SRMR = 0.079; four-dimensional model: normed chi-square = 5.75; RMSEA = 0.049; CFI = 0.965; SRMR = 0.065; chi-square difference test: p < 0.001). Results were confirmed by cross-validation. Results based on our large community sample indicated that western general populations separate health-related control-beliefs concerning formal and informal assistance.</p> <p>Conclusions</p> <p>Future non-clinical HLOC studies in western cultures should consider four dimensions of HLOC: Internality, Formal Help, Informal Help and Chance. However, the standardised German instrument needs modification. Therefore, confirmation of our results may be useful. Future research should compare HLOC structure between clinical and non-clinical samples as well as cross-culturally.</p

Generation of flavors and fragrances through biotransformation and de novo synthesis

Flavors and fragrances are the result of the presence of volatile and non-volatile compounds, appreciated mostly by the sense of smell once they usually have pleasant odors. They are used in perfumes and perfumed products, as well as for the flavoring of foods and beverages. In fact the ability of the microorganisms to produce flavors and fragrances has been described for a long time, but the relationship between the flavor formation and the microbial growth was only recently established. After that, efforts have been put in the analysis and optimization of food fermentations that led to the investigation of microorganisms and their capacity to produce flavors and fragrances, either by de novo synthesis or biotransformation. In this review, we aim to resume the recent achievements in the production of the most relevant flavors by bioconversion/biotransformation or de novo synthesis, its market value, prominent strains used, and their production rates/maximum concentrations.We would like to thank the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469 unit, COMPETE 2020 (POCI-01-0145FEDER-006684), and BiotecNorte operation (NORTE-01-0145FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020—Programa Operacional Regional do Norte.info:eu-repo/semantics/publishedVersio