Black Single Parent Families: Coping and Functioning

The University Archives has determined that this item is of continuing value to OSU's history.Presenter: Jacquelyn Wallace Gorum, D.S.W., Director of Undergraduate Program, School of Social Welfare, Health Science Center, SUNY/Stoney Brook, Stoney Brook, New York - "Black Single Parent Families: Coping and Functioning".The Ohio State University College of Social Wor

Wisdom From the Collard Field: Exploring Agrarian Community in Twenty and Twenty-first Century American Literature

This dissertation surveys agrarian literature written by American writers since World War II. It compares the Southern Agrarians of Vanderbilt University and New Agrarians such as Wendell Berry, Wes Jackson, and Gene Logsdon to examine their understanding of place and home. I begin my inquiry with a personal frame story of time I have spent in and around the sustainable agriculture movement. Drawing on various forms of literature, including memoirs, cookbooks, novels, reportage, and other scholarship, I explore American ideals since World War II relating to the production and consumption of food. I begin my opening chapter with a reassessment of the Southern Agrarians of Vanderbilt University as a starting off point in a defense of small-scale agriculture, organic farming, and the local food movement as antidotes for the excess of industrial capitalism. I put three members of the erstwhile group in conversation with green critics Lawrence Buell and Murray Bookchin as a way to wring emancipatory power from their argument and assess what can be reclaimed in the twenty-first century. In my second chapter, I question the New Agrarian call to stay home, examining the idea of drudgery in farming by comparing Paul Shephard’s Nature and Madnessto Wendell Berry, Gene Logsdon, Wes Jackson, and Joel Salatin’s defense of agriculture. The chapter continues with examples of small-scale agricultural practices that exemplify a more correct relationship with nature, such as seed saving, by exploring the traditional practices of Gary Nabhan, Janisse Ray, Bill Best, before turning to Ruth Ozeki’s All Over Creation. My last chapter continues with an assessment of various people in the contemporary agrarian movement in a discussion of privilege, equity, and accessibility. Next, I look to agrarian traditions of the past by appraising what was lost in the Great Migration through Harriette Arnow’s The Dollmakerand Edna Lewis’s cookbook, The Taste of Country Cookingbefore concluding the chapter with a discussion of present-day Detroit

Rapid mapping of forested landslide from ultra-high resolution unmanned aerial vehicle data

2018 Geoinformation for Disaster Management Conference, Gi4DM 2018 -- 18 March 2018 through 21 March 2018 -- -- 135177The Black Sea Region is one of the most landslide prone area due to the high slope gradients, heavy rainfall and highly weathered hillslope material conditions in Turkey. The landslide occurrences in this region are mainly controlled by the hydro-climatic conditions and anthropogenic activities. Rapid regional landslide inventory mapping after a major event is main difficulties encountered in this densely vegetated region. However, landslide inventories are first step and necessary for susceptibility assessment since considering the principle that the past is the key to the future thus, future landslides will be more likely to occur under similar conditions, which have led to past and present instability. In this respect, it is important to apply rapid mapping techniques to create regional landslide inventory maps of the area. This study presents the preliminary results of the semi-automated mapping of landslides from unmanned aerial vehicles (UAV) with object-based image analysis (OBIA) approach. Within the scope of the study, ultra-high resolution aerial photographs were taken with fixed wing UAV system on Aug 17, 2017 in the landslide zones which are triggered by the prolonged heavy rainfall event on August 12-13, 2016 at Bartin Kurucaşile province. 10 cm resolution orthomosaic and Digital Surface Model (DSM) data of the area were produced by processing the obtained photographs. A test area was selected from the overall research area and semi-automatic landslide detection was performed by applying object-based image analysis. OBIA has been implemented in three steps: image segmentation, image object metric calculation and classification. The accuracy of the resulting maps is assessed by comparisons with expert based landslide inventory map of the area. As a result of the comparison, 80% of the 240 landslides in the area were detected correctlyFirat University Scientific Research Projects Management Unit: 1608F607This study was supported by Anadolu University Scientific Research Projects Commission under the grant number 1608F607. The authors would like to thank İsmail Bulut from General Directorate of Combating Desertification and Erosion for his valuable suggestions on the site-selection

Sinkhole development in the Sivas gypsum karst, Turkey

The extensive gypsum karst of Sivas, Turkey is one of the most outstanding examples of bare gypsum karst in the world. It displays a number of remarkable geomorphic features, including: (1) two stepped planation surfaces cut-across folded gypsum developed during an initial phase of slow base level deepening punctuated by periods of stability; (2) unusual deeply entrenched gypsum canyons related to a subsequent phase of rapid fluvial incision and water table lowering; (3) a polygonal karst of superlative quality mainly developed in the upper surface; (4) relict valleys disrupted by sinkholes in the lower erosional surface; (5) a large number of bedrock collapse sinkholes mostly associated with the lower surface; and (6) numerous cover subsidence sinkholes developed in the valley floors. This work analyses the spatial distribution, characteristics and evolution of the sinkholes within the broad Plio-Quaternary geomorphological and paleohydrological evolution of the epigene karst system dominated by autogenic recharge. A cartographic sinkhole inventory has been produced in an area covering 2820 km(2) with morphometric data and including 295 bedrock collapse sinkholes and 302 cover subsidence sinkholes. The different sinkhole types show a general spatial zonation controlled by the hydrogeological functioning of the different sectors: (1) solution sinkholes (polygonal karst) in the upper recharge area; (2) bedrock collapse sinkholes in the lower denudation surface and close to the base level, where well developed caves are inferred; and (3) cover subsidence sinkholes, with high densities probably associated with areas of preferred groundwater discharge. The morphology of the bedrock collapse sinkholes, varying from small cylindrical holes to large and deep tronco-conical depressions with gentle slopes reflect to geomorphic evolution of these sinkholes that reach exceptionally large hectometre-scale diameters. Their evolution, involving substantial enlargement and deepening, is attributed to the solutional removal as solute load of large volumes of gypsum by downward vadose flow. This type of morphological evolution with significant post-collapse solutional denudation differs from that observed in carbonate rocks characterised by lower solubility and erodibility. The analysis of historical imagery reveals that bedrock collapse sinkholes currently have a very low probability of occurrence and that buried cover subsidence sinkholes are used for urban development creating risk situations. (C) 2021 The Author(s). Published by Elsevier B.V

From ground motion simulations to rockfall hazard scenarios:A look into cascading effects from the 2023 Turkish earthquakes

In the last decade the interest in understanding or assessing the susceptibility of earthquake induced landslides has considerably increased in the scientific literature. In this context rockfalls present a challenge due to the difficulty to collect information on fallen boulders following an earthquake emergency. The data obtained is often biased, as it is usually recorded only when it causes damage to buildings or road networks. Important aspects for future studies, such as the identification of source areas, are generally overlooked.This study aims to develop a coseismic rockfall analysis based on the Turkish scenario, where two massive earthquakes of magnitude 7.8 and 7.5 struck on February 6, 2023, triggering approximately 3,673 landslides, the majority of which were rockfalls. The approach combines data collection and statistical analysis to obtain the key input data needed for forecasting rockfall trajectories caused by future earthquakes.The well-timed collection of post-event high resolution ortho-images allowed to realize a thorough coseismic rockfall inventory of the area affected by the earthquakes. This inventory will serve to train both the source area susceptibility model and the trajectories simulation model.This information allows the application of an occurrence probability model based on ground motion predictive equations and the estimated peak ground acceleration for a potential earthquake along the left-lateral East Anatolian Fault, focusing on the identification of future source areas susceptible to rockfall. From these sources, some rockfall trajectories will be simulated to assess the hazard zonation along the main infrastructures like road, pipelines and villages

Speech-recognition in landslide predictive modelling:A case for a next generation early warning system

Traditional landslide early warnings are based on the notion that intensity-duration relations can be approximated to single precipitation values cumulated over fixed time windows. Here, we take on a similar task being inspired by modeling architectures typical of speech-recognition tasks. We aim at classifying the Turkish landscape into 5 km grids assigned with dynamic landslide susceptibility estimates. We collected all available national information on precipitation-induced landslide occurrences. This information is passed to a Long Short-Term Memory equipped with the whole rainfall time series, obtained from daily CHIRPS data. We test this model: 1) by randomizing the presence/absence data to represent the slope instability over Turkey and over 13 years under consideration (2008–2020) and 2) by assessing the effect of different time windows used to pass the rainfall signal to the neural network. Results show that the inclusion of the full precipitation signal rather than its scalar approximation leads to a substantial increase in prediction power (approximately 20%). This may potentially pave the road for a new generation of speech-recognition-based landslide early warning systems.</p