Henry Volkening to Mrs. Motley (7 November 1962)

https://egrove.olemiss.edu/mercorr_pro/2187/thumbnail.jp

Comentarios al margen a la tragedia Axel del conde Villiers de L’isle-Adam

Volkening escribió para su amigo Nicolás Gómez Dávila,  "Comentarios al margen a la tragedia Axel del conde Villiers de L’isle-Adam”, traducido por David Alvarado-Archila, una muestra de un contacto epistolar en el que se pueden ver algunas de las perspectivas críticas características de quien fue uno de nuestros principales críticos literarios.Volkening escribió para su amigo Nicolás Gómez Dávila,  "Comentarios al margen a la tragedia Axel del conde Villiers de L’isle-Adam”, traducido por David Alvarado-Archila, una muestra de un contacto epistolar en el que se pueden ver algunas de las perspectivas críticas características de quien fue uno de nuestros principales críticos literarios

Flow dynamics of an accumulation basin: a case study of upper Kahiltna Glacier, Mount McKinley, Alaska

We interpreted flow dynamics of the Kahiltna Pass Basin accumulation zone on Mount McKinley, Alaska, USA, using 40, 100 and 900 MHz ground-penetrating radar profiles and GPS surface velocity measurements. We found dipping, englacial surface-conformable strata that experienced vertical thickening as the glacier flowed westward from a steep, higher-velocity (60 m a–1) region into flat terrain associated with a 908 bend in the glacier and lower velocities (15 m a–1) to the south. Stratigraphy near the western side of the basin was surface-conformable to 170 m depth and thinned as flow diverged southward, down-glacier. We found complex strata beneath the conformable stratigraphy and interpret these features as buried crevasses, avalanche debris and deformed ice caused by up-glacier events. We also suggest that basin dimensions, bed topography and the sharp bend each cause flow extension and compression, significantly contributing to conformable and complex strata thickness variations. Our findings show that surface-conformable stratigraphy continuous with depth and consistent strata thicknesses cannot be assumed in accumulation basins, because local and upglacier terrain and flow dynamics can cause structural complexities to occur under and within surfaceconformable layers

Melt regimes, internal stratigraphy, and flow dynamics of three glaciers in the Alaska Range

We used ground-penetrating radar (GPR), GPS and glaciochemistry to evaluate melt regimes and ice depths, important variables for mass-balance and ice-volume studies, of Upper Yentna Glacier, Upper Kahiltna Glacier and the Mount Hunter ice divide, Alaska. We show the wet, percolation and dry snow zones located below 2700 m a.s.l., at 2700 to 3900 m a.s.l. and above 3900 m a.s.l., respectively. We successfully imaged glacier ice depths upwards of 480 m using 40–100 MHz GPR frequencies. This depth is nearly double previous depth measurements reached using mid-frequency GPR systems on temperate glaciers. Few Holocene-length climate records are available in Alaska, hence we also assess stratigraphy and flow dynamics at each study site as a potential ice-core location. Ice layers in shallow firn cores and attenuated glaciochemical signals or lacking strata in GPR profiles collected on Upper Yentna Glacier suggest that regions below 2800 m a.s.l. are inappropriate for paleoclimate studies because of chemical diffusion, through melt. Flow complexities on Kahiltna Glacier preclude ice-core climate studies. Minimal signs of melt or deformation, and depth–age model estimates suggesting 4815 years of ice on the Mount Hunter ice divide (3912 m a.s.l.) make it a suitable Holocene-age ice-core location

Topological data analysis of zebrafish patterns

Self-organized pattern behavior is ubiquitous throughout nature, from fish schooling to collective cell dynamics during organism development. Qualitatively these patterns display impressive consistency, yet variability inevitably exists within pattern-forming systems on both microscopic and macroscopic scales. Quantifying variability and measuring pattern features can inform the underlying agent interactions and allow for predictive analyses. Nevertheless, current methods for analyzing patterns that arise from collective behavior only capture macroscopic features, or rely on either manual inspection or smoothing algorithms that lose the underlying agent-based nature of the data. Here we introduce methods based on topological data analysis and interpretable machine learning for quantifying both agent-level features and global pattern attributes on a large scale. Because the zebrafish is a model organism for skin pattern formation, we focus specifically on analyzing its skin patterns as a means of illustrating our approach. Using a recent agent-based model, we simulate thousands of wild-type and mutant zebrafish patterns and apply our methodology to better understand pattern variability in zebrafish. Our methodology is able to quantify the differential impact of stochasticity in cell interactions on wild-type and mutant patterns, and we use our methods to predict stripe and spot statistics as a function of varying cellular communication. Our work provides a new approach to automatically quantifying biological patterns and analyzing agent-based dynamics so that we can now answer critical questions in pattern formation at a much larger scale