2199 research outputs found
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Preparing a Numerical Model for Simulating Stormwater Management Scenarios: West Creek Case Study
No full texthttps://kent-islandora.s3.us-east-2.amazonaws.com/node/10084/10201-thumbnail.jpgNumerical modeling is a powerful tool for studying the effects of stormwater management in urban catchments, but numerical modeling requires high quality meteorological input data and a well-calibrated hydrological model. The main hypothesis of this research is that consideration of spatial variability in meteorological data and careful selection of calibration method and parameters will result in good performance of an urban hydrological model. The 20.63 km2, 30.3% impervious West Creek watershed in the Cleveland metropolitan area is modeled in the Personal Computer Storm Water Management Model (PCSWMM), based on an existing model provided by the Northeast Ohio Regional Sewer District (NEORSD). 5-minute rainfall data from 4 rain gauges was also obtained from NEORSD. All other meteorological parameters are from the Cleveland airport, after comparison with a station within West Creek watershed. Missing data were filled using linear regression. Identification of sensitive parameters for calibration was done with the help of existing literature and the PCSWMM SRTC tool. Snowpack parameters were manually calibrated based on available data from the Cleveland airport. Uncertainty-based automatic calibration for streamflow using Differential Evolution Markov Chain Algorithm (DREAM) is underway. The percentage of missing data of all meteorological variables varies from 0.21% – 0.61%, a substantial improvement over the single station previously used. Manual calibration of snowpack and addition of an aquifer leads to a Nash-Sutcliffe efficiency of 0.764 for 2017-2018, which will be further improved by using the DREAM algorithm. The final, well-calibrated model will be used to simulate different stormwater management scenarios.</p
Characterization of Conditioning Films on Microplastics
No full texthttps://kent-islandora.s3.us-east-2.amazonaws.com/node/10086/10203-thumbnail.jpgMicroplastics (plastic debris with diameter <5mm) are of particular concern to the environment. However, there is a scarcity of information concerning the effects of conditioning films on bacterial colonization of microplastics in freshwater ecosystems. The formation of conditioning films on substrate surfaces is a critical step in the priming of substrates for bacterial colonization in aquatic systems. Conditioning films are comprised of dissolved organic solutes that are deposited on to surfaces of substrates, which attract bacterial colonizers. Moreover, the thicknesses of conditioning films are influenced by the physicochemical properties of substrate surfaces. This study aimed to understand the effects of different conditioning films on bacterial colonization of microplastic surfaces in freshwater. Five types of conditioning films were analyzed: Bovine Serum Albumin (BSA), sodium alginate (medium and very low viscosity), humic and fulvic acid; all are components of biofilms on four types of microplastic disks (diameter <5mm): polypropylene (PP), polystyrene (PS), high-density polyethylene (HDPE), and low-density polyethylene (LDPE). The disks were analyzed for conditioning film thicknesses using AFM (atomic force microscopy) and 16S rRNA sequencing to determine compositions of bacterial communities in the presence of different conditioning films. Understanding these questions will provide insights on fates of microplastic debris in freshwater.</p
Spatial Variability of Stormwater Control Measures in Northeast Ohio: Preliminary Analysis and Additional Data Required
No full textIn urban areas, impervious surfaces and pipe networks rapidly deliver high volumes of stormwater to streams and sewer networks. Stormwater runoff causes flooding, erosion, pollution and degradation of aquatic ecosystems, and the discharge of raw sewage into the environment when combined sewers overflow. These impacts, especially in the context of increased urbanization and climate change have provoked intense interest in mitigating stormwater runoff. Yet, the impact of stormwater management practices on urban hydrology is poorly understood at the watershed scale as well as at the scale of a metropolitan area. Increased urbanization and imperviousness in urban watersheds throughout the world necessitate informed decision-making practices when implementing stormwater control measures. This study seeks to quantify how stormwater management actions modulate the influence of urbanization on flow regimes at the watershed scale. We analyze impervious surface cover and road density as measures of urbanization intensity. Based on data provided by the Cuyahoga Soil and Water Conservation District for 22 municipalities, the density of SCMs in USGS gauged watersheds is 0.31 SCMs/km2. Incomplete data means that this number is likely and underestimate of the true SCM density in the Cleveland area and we are actively seeking additional sources of SCM data from municipalities and other organizations. Using the current SCM dataset, we analyze the variability in SCM types, year of construction, and spatial distribution and compare these results to urbanization intensity. Once the SCM database is complete in the >12 USGS gaged watersheds in the Cleveland area, the next step will be to analyze the hydrologic response to precipitation with respect to urbanization intensity and stormwater management and their change over time. This research has the potential to inform municipal and watershed-scale efforts to optimize investments in stormwater infrastructure.</p
Kent State National Ceramics Invitational
No full texthttps://kent-islandora.s3.us-east-2.amazonaws.com/node/10405/10537-thumbnail.jpgExhibition ran from March 6-April 11, 2020
Curated by Peter Pincus
Works by Sanam Emami, Brooks Oliver, Adam Posnak, Hannah Thompsett</p
How Do Educators and Students Work for the Sustainable Development of China’s Fashion Industry?
No full texthttps://kent-islandora.s3.us-east-2.amazonaws.com/node/10439/10610-thumbnail.jpgSustainable development is an important issue in the global fashion industry. As the largest
clothing consumer and producer in the world, China has an unmistakable responsibility to
promote the sustainable development of fashion industry. Due to a shift in Chinese
consumers, the younger generation of consumers pays more attention to brand environmental protection and social responsibility, but the sustainable development process of the Chinese fashion industry is still relatively slow and there are some obstacles. The reason lies in the lack of sustainable fashion education, so for this study researchers conducted questionnaires and interviews with educators, students, and designers of some fashion universities in China. Taking colleges and universities as units, this paper probes the present situation of sustainable fashion education in China from cognition to existing problems and development trends and puts forward some measures and ideas for educators and students to practice sustainable fashion development. And this study combined with the regional development of China’s clothing industry imbalance, industrial clusters prominent characteristics of regional research, to explore the future of education to promote the sustainable development of a regional clothing industry.</p
Ohio History Fall 2020
No full texthttps://kent-islandora.s3.us-east-2.amazonaws.com/node/10536/OH-v127n2-thumb.jpgOHIO HISTORY
Contents for Volume 127, Number 2, Fall 2020
Contributors ...... 6
The Tensions between Continuity and Change: Early Prescriptive Literature in Ohio and the Western Reserve
Martha I. Pallante ...... 7
The 1891 McKinley-Campbell Ohio Gubernatorial Debate and the Draw That Still Splits America
Robert Klotz ...... 32
Painting the Past: History, Memory, and Community in Modern Ohio
Stuart D. Hobbs ...... 47
Nexus of Naturalists: Sharing Nature in the Columbus Dispatch Column of Edward Sinclair Thomas
Ken J. Ward ...... 92
Book and Exhibition Reviews ...... 114
On the cover: “Construction of a Modern Steel Building.” Image courtesy the Supreme Court of Ohio. David Barker, photographer.</p
Breathing Aid Devices to Support Novel Coronavirus (COVID-19) Infected Patients
No full textNovel coronavirus (COVID-19), an ongoing pandemic, is threatening the whole population all over the world including the nations having high or low resource health infrastructure. The number of infection as well as death cases are increasing day by day, and outperforming all the records of previously found infectious diseases. This pandemic is imposing specific pressures on the medical system almost the whole globe. The respiration problem is the main complication that a COVID-19 infected patient faced generally. It is a matter of hope that the recent deployment of small-scale technologies like 3D printer, microcontroller, ventilator, Continuous Positive Airway Pressure (CPAP) are mostly used to resolve the problem associated with medical equipment\u27s for breathing. This paper aims to overview the existing technologies which are frequently used to support the infected patients for respiration. We described the most recent developed breathing aid devices such as oxygen therapy devices, ventilator, and CPAP throughout the review. A comparative analysis among the developed devices with necessary challenges and possible future directions are also outlined for the proper selection of affordable technologies. It is expected that this paper would be of great help to the experts who would like to contribute in this area.</p
Machine Learning Maps Research Needs in COVID-19 Literature
No full texthttps://kent-islandora.s3.us-east-2.amazonaws.com/node/10699/88579-thumbnail.jpgAs of August 2020, thousands of COVID-19 (coronavirus disease 2019) publications have been produced. Manual assessment of their scope is an overwhelming task, and shortcuts through metadata analysis (e.g., keywords) assume that studies are properly tagged. However, machine learning approaches can rapidly survey the actual text of publication abstracts to identify research overlap between COVID-19 and other coronaviruses, research hotspots, and areas warranting exploration. We propose a fast, scalable, and reusable framework to parse novel disease literature. When applied to the COVID-19 Open Research Dataset (CORD-19), dimensionality reduction suggests that COVID-19 studies to date are primarily clinical-, modeling- or field-based, in contrast to the vast quantity of laboratory-driven research for other (non-COVID-19) coronavirus diseases. Furthermore, topic modeling indicates that COVID-19 publications have focused on public health, outbreak reporting, clinical care, and testing for coronaviruses, as opposed to the more limited number focused on basic microbiology, including pathogenesis and transmission.</p
The UK needs a sustainable strategy for COVID-19
No full textThe UK is well into the second wave of COVID-19, with 60 051 lives lost to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection to date, according to provisional data from the Office for National Statistics. Official UK Government data show that cases have been rising exponentially since late August, 2020, with increases across all regions in England in recent weeks.
As of Nov 4, 2020, the UK had 25 177 confirmed daily cases. These are almost certainly underestimates as between Oct 17 and Oct 23, 2020, England alone had 52 000 estimated daily cases.
Estimates of the effective reproduction number in England vary between 1·1 and 1·6.</p
Exploring the Relationships Between Discrepancies in Perceptions of Emotional Performance Among College Students on Self-Esteem and Psychological Distress
No full textUsing the cultural-normative perspective (Ekman [1973] 2006; Gordon 1981, 1990; Hochschild 1975, [1983] 2012) and the perceptual control emphasis in identity theory (Burke 1991, 1996; Burke and Stets 2009; Stets 2003, 2004, Social Psychology Quarterly, 68(1), 39–56 Stets 2005; Stets and Asencio 2008; Stets and Osborn 2008; Stets & Carter, Social Psychology Quarterly, 74(2), 192–215, 2011, American Sociological Review, 77(1), 120–140 2012; Stets et al. 2008b; Stets and Trettevik 2016; Stets and Tsushima 2001) I explore how college students’ perceptions of self versus others evaluations of emotional performances impact self-esteem and psychological distress. Drawing on a convenience sample of 1100 college students from a large university in the United States, I run a series of structural equation models (SEM) to examine my hypotheses. I suggest that the greater the discrepancy in the evaluation of the emotional response of happiness (or sadness) related to the student identity is related to lower self-esteem, greater depression and anxiety. Results support my hypotheses, even small discrepancies in perceptions of our emotional displays of happiness or sadness impact the self and psychological distress. I suggest ways this work can inform counselors, educators and others working within higher education to encourage integration of coping responses associated with the college student identity to be embedded in the cultural landscape of the university setting. I offer suggestions how theoretical, empirical and applied work in this tradition can enhance the lives of college students and present a number of pathways for future research.</p