Miami University

About: Miami University is a education organization based out in Oxford, Ohio, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 9949 authors who have published 19598 publications receiving 568410 citations. The organization is also known as: Miami of Ohio & Miami-Ohio.

Sexuality, Substance Use, and Susceptibility to Victimization Risk for Rape and Sexual Coercion in a Prospective Study of College Women

Abstract: An 8-month prospective study examined behavioral, personality, and psychological variables thought to increase vulnerability for college women's experience of rape and verbal sexual coercion. Participants were 276 college women who completed self-report surveys. During 1 academic year, 9.5% of women were raped and 11.7% reported verbal sexual coercion. Elevated levels of sexual concerns, dysfunctional sexual behavior, and impaired self-reference were associated with both verbal sexual coercion and rape. Alcohol and marijuana use increased risk only for rape, whereas self-criticism and depression increased risk only for verbal coercion. Findings suggest that multiple aspects of sexuality, such as shame regarding sexuality and using sex to meet nonsexual needs, may increase risk for both types of sexual victimization. Results support conclusions that rape and verbal sexual coercion have both shared and unique risk factors. Implications for future research and intervention programs are discussed.

Long-Term Integrated Studies Show Complex and Surprising Effects of Climate Change in the Northern Hardwood Forest

Abstract: Evaluations of the local effects of global change are often confounded by the interactions of natural and anthropogenic factors that overshadow the effects of climate changes on ecosystems. Long-term watershed and natural elevation gradient studies at the Hubbard Brook Experimental Forest and in the surrounding region show surprising results demonstrating the effects of climate change on hydrologic variables (e.g., evapo- transpiration, streamflow, soil moisture); the importance of changes in phenology on water, carbon, and nitrogen fluxes during critical seasonal transition periods; winter climate change effects on plant and animal community composition and ecosystem services; and the effects of anthro- pogenic disturbances and land-use history on plant community composition. These studies highlight the value of long-term integrated research for assessments of the subtle effects of changing climate on complex ecosystems. unraveling this daunting complexity is long-term studies, including those in which natural elevation gradients are exploited, as a foundation for detailed studies of critical and often unexpected climate-induced changes in forest struc- ture and function. In this article, results from the Hubbard Brook Experimental Forest (HBEF) and the surrounding region are used to illustrate how long-term studies can serve as a foundation for addressing the complex interactions that ultimately determine the effects of climate change on ecosystems. We combine data from long-term (50-year) measurements of multiple aspects of climate and ecosystem structure and function to highlight important but poorly studied inter- actions that could be critical determinants of the responses of plant and animal communities, fluxes of water, element dynamics, and services in northern hardwood forest eco- systems. Our objective is to demonstrate how a combina- tion of long-term and in-depth measurements facilitates A dominant approach in climate change research has been to focus on the effects of changes in temperature and precipitation on broadscale ecosystem properties over large areas and long periods. This body of research suggests that climate change will substantially alter the distribution of species and the function of ecosystems (e.g., Iverson and Prasad 2001), with important effects on ecosystem services. These analyses are based on well-described effects of tem- perature and precipitation on the distribution and activity of organisms. However, climate change is playing out over the complex and dynamic hydrobiogeological structure of the landscape—that is, the intertwined patterns of soils, vegetation, and hydrologic flowpaths, with a spatially variable history of land use and a wide range of current human activities and concurrent environmental changes. The climate effects on ecosystem structure and function may be modified by interactions with these patterns and histories over a range of time scales. We assert that a key approach to

Changes in undergraduate student alcohol consumption as they progress through university.

Abstract: Unhealthy alcohol use amongst university students is a major public health concern. Although previous studies suggest a raised level of consumption amongst the UK student population there is little consistent information available about the pattern of alcohol consumption as they progress through university. The aim of the current research was to describe drinking patterns of UK full-time undergraduate students as they progress through their degree course. Data were collected over three years from 5895 undergraduate students who began their studies in either 2000 or 2001. Longitudinal data (i.e. Years 1–3) were available from 225 students. The remaining 5670 students all responded to at least one of the three surveys (Year 1 n = 2843; Year 2 n = 2219; Year 3 n = 1805). Students reported consuming significantly more units of alcohol per week at Year 1 than at Years 2 or 3 of their degree. Male students reported a higher consumption of units of alcohol than their female peers. When alcohol intake was classified using the Royal College of Physicians guidelines [1] there was no difference between male and females students in terms of the percentage exceeding recommended limits. Compared to those who were low level consumers students who reported drinking above low levels at Year 1 had at least 10 times the odds of continuing to consume above low levels at year 3. Students who reported higher levels of drinking were more likely to report that alcohol had a negative impact on their studies, finances and physical health. Consistent with the reduction in units over time students reported lower levels of negative impact during Year 3 when compared to Year 1. The current findings suggest that student alcohol consumption declines over their undergraduate studies; however weekly levels of consumption at Year 3 remain high for a substantial number of students. The persistence of high levels of consumption in a large population of students suggests the need for effective preventative and treatment interventions for all year groups.

Stock market one-day ahead movement prediction using disparate data sources

Abstract: A financial expert system for predicting the daily stock movements.Knowledge base captures both traditional and online data sources.The inference engine uses three artificial intelligence techniques.Prediction accuracy of 85% is higher than the reported results in the literature.The system is hosted online and freely available for investors and researchers. There are several commercial financial expert systems that can be used for trading on the stock exchange. However, their predictions are somewhat limited since they primarily rely on time-series analysis of the market. With the rise of the Internet, new forms of collective intelligence (e.g. Google and Wikipedia) have emerged, representing a new generation of crowd-sourced knowledge bases. They collate information on publicly traded companies, while capturing web traffic statistics that reflect the publics collective interest. Google and Wikipedia have become important knowledge bases for investors. In this research, we hypothesize that combining disparate online data sources with traditional time-series and technical indicators for a stock can provide a more effective and intelligent daily trading expert system. Three machine learning models, decision trees, neural networks and support vector machines, serve as the basis for our inference engine. To evaluate the performance of our expert system, we present a case study based on the AAPL (Apple NASDAQ) stock. Our expert system had an 85% accuracy in predicting the next-day AAPL stock movement, which outperforms the reported rates in the literature. Our results suggest that: (a) the knowledge base of financial expert systems can benefit from data captured from nontraditional experts like Google and Wikipedia; (b) diversifying the knowledge base by combining data from disparate sources can help improve the performance of financial expert systems; and (c) the use of simple machine learning models for inference and rule generation is appropriate with our rich knowledge database. Finally, an intelligent decision making tool is provided to assist investors in making trading decisions on any stock, commodity or index.

Landscape change with agricultural intensification in a rural watershed, southwestern Ohio, U.S.A.

Abstract: Specialized cash grain production, emergent in the midwestern United States during the post-WWII era, typifies the Upper Four Mile Creek watershed in southwestern Ohio. This style of agriculture intensifies cropland use, with consequent increases in soil erosion and stream sedimentation - a serious problem in the lower reservoir, Acton Lake. Agricultural statistics and aerial photographs compiled between 1934 and 1984 were used to quantify agricultural dynamics and landscape change in the watershed, including land-use apportionment, diversity, and the structural configuration of forest, woodland, and old-field/brushland patches and corridors. A questionnaire sent to all land owners in the basin documented farm-level characteristics and factors that influence management decisions. Crop diversity (H′) in Preble County, Ohio decreased from 1.42 in 1934 to 1.17 in 1982, as corn and soybeans dominated the landscape mosaic. Yields rose, but net profits were reduced by declining prices per bushel and increases in fertilizer and petroleum-based subsidies. Landuse diversity in the county also declined (H′ = 1.37 in 1934 tot 0.80 in 1982) in response to cropland expansion, whereas forest land in the watershed increased from 1605 to 2603 ha. Fragmentation declined and the landscape became polarized after 1956, with a concentration of agricultural patches in the upper watershed and forest-patch coalescence in stream gullies and state park land in the lower watershed. The questionnaire (~ 29% return) further supported, at the farm-level, observed regional trends toward expansion (farm coalescence and lease contracts) and specialization (conversion toward corn and soybeans). The most important factors influencing farm size and management were better equipment and family traditions. Thus, cultural and technological factors that operate at the farm-level, coupled with meso-scale variation in the physical conditions of a catchment basin, tend to influence landscape-level patterns more than regional socioeconomics and governmental policies.