Renovation and revolution: a cultural history of homes in Virginia

RENOVATION AND REVOLUTION: A CULTURAL HISTORY OF HOMES IN VIRGINIA Renovation and Revolution is the first half of a book length series of linked essays exploring the history of houses in Virginia from 1607 to the present. Readers travel through the American Indian town of Paspahegh, models of waddle and daub houses excavated at James Town, Appalachian cabins, freed slave refugee camps, manor houses shipped from England, low-income garden apartments, a sprawling commune, abandoned college dorms modeled after world\u27s fair designs, and much more. This tour ultimately guides readers to a better understanding of what it means to be at home in America, a land founded on movement and innovation, yet constantly searching for its roots. This half covers pre-history through the Civil War with a few side stories foraying into the 21st century

Guest Blog: Charleston Mission Trip An Eye Opening Experience

Over fall break, Gardner-Webb went on a mission trip to Charleston, South Carolina. The mission team worked with a group in Charleston called Metanoia, which is a community development ministry.https://digitalcommons.gardner-webb.edu/gwu-today/1225/thumbnail.jp

What Poverty Means For Student Achievement and The Best Practices for Teaching Students in Poverty

In America today, there are approximately 103 million people living below the line of poverty (Edelman, p. 4). This means that 103 million people are supporting a family of three or more with less than $36,000 (p. 4). Therefore, one-third of America today lives in poverty (p. 4). Within those 103 million, there are approximately 20.5 million people in America who fall into the category of “deep poverty,” making less than$9,000 for a family of three or more (p. 5). These people make up about 6.7% of the population (p. 5). Finally, within these 20.5 million people, there are about 6 million who do not have any income at all (p. 5). Since one-third of America lives in poverty today, our future generations are likely to have even greater numbers of poverty according to the phenomenon of generational poverty. Generational poverty occurs when “a parent’s poverty permanently affects the lives of his/her children” (Getting, p.2). Living in poverty causes children to gain cognitive, behavioral, and emotional deficits, putting them at a vast disadvantage in education and in professional attainment (p. 2). This is due to the fact these children have access to fewer resources, and live in a world of disadvantage (p. 3). The living environments of these children often involve limited access to food, higher pollution rates, overcrowded and overfunded schools, and higher crime rates (p. 3). Children from poverty also often develop the attributes their parents display and lack proper role models. Therefore, they often have poor nutritional habits, a lack of self-confidence, and little reading abilities (p. 5). Additionally, children from poverty also tend to move quite frequently, causing an increased amount of stress (p. 4). In fact, adults who were raised in poverty tend to continue to exhibit problems with stress and emotional processing (p. 4). Altogether, the deficits of poverty cause children raised in these situations to be 72% more likely to raise their own children in poverty, and thus continuing the cycle of generational poverty (p. 5). The effects of poverty affect all aspects of a child’s life, but specifically cause deficits in their education. Although this puts students in poverty at a disadvantage as they begin their learning, there are many strategies and methods that teachers can use to help support these students in order to prevent them from falling behind due to reasons beyond their control. One of the best ways that educators can help students in poverty break the cycle of generational poverty is by unlocking their potential and ability to succeed in school (The Cycle, p. 16). Success in the world of education can unlock many opportunities for these students that will otherwise likely fall back into the cycle of generational poverty. This study evaluates the problems that children in poverty often face, and the strategies that teachers can use to combat these problems. In addition, this study evaluates the problems faced by students in an actual elementary setting and describes the strategies that would be effective in this setting. This research is an action research study designed to investigate what poverty means for student achievement and the best practices for teaching students in poverty

ASSOCIATING SEVERE THUNDERSTORM WARNINGS WITH DEMOGRAPHIC AND LANDSCAPE VARIABLES: A GEOGRAPHICALLY WEIGHTED REGRESSION-BASED MAPPING OF FORECAST BIAS

Severe thunderstorm warnings (SVTs) are released by meteorologists in the local forecast offices of the National Weather Service (NWS). These warnings are issued with the intent of alerting areas in the path of severe thunderstorms that human and property risk are elevated, and that appropriate precautionary measures should be taken. However, studies have shown that the spatial distribution of severe storm warnings demonstrates bias. Greater numbers of severe thunderstorm warnings sometimes are issued where population is denser. By contrast, less populated areas may be underwarned. To investigate the spatial patterns of these biases for the central and southeastern United States, geographically weighted regression was implemented on a set of demographic and land cover descriptors to ascertain their patterns of spatial association with counts of National Weather Service severe thunderstorm warnings. GWR was performed for each our independent variables (total population, median income, and percent impervious land cover) and for all three of these variables as a group. Global R2 values indicate that each individual variable as well as all three collectively explain approximately 60% of the geographical variation in severe thunderstorm warning counts. Local R2 increased in the vicinity of several urban regions, notably Atlanta, Washington, D.C., St. Louis, and Nashville. However, the independent variables did not exhibit the same spatial patterning of R2. Some cities had high local R2 for all variables. Other cities exhibited high local R2 for only one or two of these independent variables. Median income had the highest local R2 values overall. Standardized residuals confirmed significant differences among several NWS forecast offices in the number and pattern of severe thunderstorm warnings. Overall, approximately half of the influences on the distribution of severe thunderstorm warnings across the study area are related to underlying land cover and demographics. Future studies may find it productive to investigate the extent to which the spatial bias mapped in this study is an artifact of forecast culture, background thunderstorm regime, or a product of urban anthropogenic weather modification

Can the EITC and Unemployment Insurance Replace Lost Wages?

The COVID-19 pandemic has had a significant effect on all aspects of social, economic, and political life worldwide. In the United States, millions of people have tested positive for COVID-19, and over 200,000 people have died from the virus. While Ohio’s governor and director of public health have been credited for their quick decision-making in response to the pandemic, Ohio’s communities still suffered, with well over 100,000 cases and thousands of COVID-19-related deaths statewide. Policymakers aiming to reduce the spread of COVID-19 were forced to make difficult tradeoffs between public health and the economy. On March 23, 2020, Governor Mike DeWine’s stay-at-home order started. This executive order mandated only essential businesses could remain open. Consequently, many Ohioans faced lay-offs or furloughs, filing over 1.6 million unemployment claims between March and August 2020—more than the last four years combined. Cuyahoga County was not immune to this economic downturn; unemployment increased by 19 percentage points in four months. Low-wage jobs in the Accommodation and Food Services industries were hit hardest,4 meaning the county’s most economically vulnerable residents were most likely to experience lost wages. After a phase-in of re-openings, the stay-at-home order ended on May 29th. Unemployment rates, while falling, remain above those in 2019. In response to the pandemic’s economic impact, the federal government enacted landmark policy. The federal Coronavirus Aid, Relief, and Economic Security (CARES) Act aimed to reduce the financial burden and provide a safety net through the expansion of unemployment benefits, provision of stimulus payments to eligible Americans, and postponed loan payments, among other things. Most relevant to this analysis is an additional $600 per week of unemployment benefits available to individuals affected by COVID-19. These benefits were available between March 29th and July 25th, which includes nine of the ten weeks of Ohio’s stay-at-home order. This research brief provides insight into the effects of unemployment insurance (UI) benefits and the Earned Income Tax Credit (EITC) on wage replacement rates, as well as policy recommendations regarding UI and EITC in response to the COVID-19 pandemic. While we find UI and EITC benefits replaced the lost wages for most of the county’s economically vulnerable workers, we urge continued policy intervention to mitigate the consequences of the pandemic

Vampirism, Vampire Cults and the Teenager of Today

The aim of this paper is to summarize the limited literature on clinical vampirism, vampire cults and the involvement of adolescents in vampire-like behavior. The various definitions of clinical vampirism are outlined and the emergence of vampire cults from Gothic culture is examined. Further, the clinical features of cult behavior, the attraction to cults, the risk factors for cult involvement, and the clinical management of cult members are discussed. Additionally, vampire popular media is briefly introduced and a case study presented

A Study of Trihalomethane Precursors in Deer Creek Reservoir

Deer Creek Reservoir and tributaries were monitored from May to December 1983 in a study of the occurrence of trihalomethane (THM) precursors in the reservoir and nutrient dynamics of the reservoir system. Microcosms were used to study the effect of the following parameters on THM precursor production in the reservoir system: phosphorus loading, sediment, algal growth, and application of algicide. Additionally, THM precursor concentrations of interstitial water were analyzed in reservoir and microcosm sediment samples. Microcosms treated with ahigh phosphorus loading (70 ug/1) had THM precursor concentrations significantly higher than those measured in microcosms treated with a low phosphorus loading (10 ug/1). The presence of sediment in microcosms did not significantly affect THM precursor concentrations. Algae growth did result in THM production significantly aboce that measured in microcosms without algae growth. No correlation between total organic carbon and terminal total trihalomethane concentrations was found to exist in microcosms. Potassium permanganate and copper sulface were used as algicides. Applications of 0.3 mg/1 potassium permanganate and 50 ug/1 copper sulfate as Cu^+2 did not appear to affect THM precursor, total phosphorus, total suspended solids, or volatile suspended solids concentrations in the microcosms. Anoxic phosphorus release occurred in dark microcosms after the dissolved oxygen concentration dropped below approximately 3.0 mg/1. Considering all data collected, no significant difference in THM precursor concentraion could be detected between tributary and reservoir samples. THM precursor concentrations in tributaries were found to vary significantly be season. Samples collected from three depths within the reservoir were not found to have significantly different mean terminal total trihalomethane concentrations over the sampling period. No correlation between total organic carbon and terminal total trihalomethane concentrations was found to exist. Total phosphorus concentrations in tributaries were quite high, particularly in Main and Daniels Creeks

The Evolution of the Galaxy Cluster Luminosity-Temperature Relation

We analyzed the luminosity-temperature (L-T) relation for 2 samples of galaxy clusters which have all been observed by the ASCA satellite. We used 32 high redshift clusters (0.3<z<0.6), 53 low redshift clusters (z<0.3), and also the combination of the low and high redshift datasets. We assumed a power law relation between the bolometric luminosity of the galaxy cluster and its integrated temperature and redshift (L_{bol,44}=C*T^alpha*(1+z)^A). The results are consistent, independent of cosmology, with previous estimates of L$\sim$T$^3$ found by other authors. We observed weak or zero evolution.Comment: 20 pages, Latex, 11 figures, GIF forma

Nonmeteorological Influences on Severe Thunderstorm Warning Issuance: A Geographically Weighted Regression-Based Analysis of County Warning Area Boundaries, Land Cover, and Demographic Variables

Studies have shown that the spatial distribution of severe thunderstorm warnings demonstrates variation beyond what can be attributed to weather and climate alone. Investigating spatial patterns of these variations can provide insight into nonmeteorological factors that might lead forecasters to issue warnings. Geographically weighted regression was performed on a set of demographic and land cover descriptors to ascertain their relationships with National Weather Service (NWS) severe thunderstorm warning polygons issued by 36 NWS forecast offices in the central and southeastern United States from 2008 to 2015. County warning area (CWA) boundaries and cities were predominant sources of variability in warning counts. Global explained variance in verified and unverified severe thunderstorm warnings ranged from 67% to 81% for population, median income, and percent imperviousness across the study area, which supports the spatial influence of these variables on warning issuance. Local regression coefficients indicated that verified and unverified warning counts increased disproportionately in larger cities relative to the global trend, particularly for NWS weather forecast office locations. However, local explained variance tended to be lower in cities, possibly due to greater complexity of social and economic factors shaping warning issuance. Impacts of thunderstorm type and anthropogenic modification of existing storms should also be considered when interpreting the results of this study