A Better Solution for the Text of Xenophon, Symp. 4. 37

IT may be taken as a great verity of Greek syntax that ν is not construed with the present or the perfect of the indicative. Exceptions are either apparent, needing explanation, or errors in transmission, requiring correction. There are no discordant voices in the expert choir on this point, all say the same. As usual the collections of examples are most copious in Kühner-Gerth, other authorities attempting only to adduce a few new examples. Since these are so readily available there is no need to review all the pertinent passages here. The apparent exceptions are either cases of confusing word-order or anacolutha. Confusing word-order occurs for example when ν attaches itself to a verb of speaking (µαι), or to a negative when it belongs logically elsewhere in the sentence. The anacolutha are principally formulaic in character, as when kaν єi is used simply as ═ kαiє and so brings an extra ν into the sentence which may seem to belong to an indicativ

“Oscillating Between Hope and Despair”: A Narrative Case Study of Culture and Coping for Women in Engineering in Higher Education and Industry

Women in engineering in all phases (students, faculty, and industry) are traditionally underrepresented, and have been underrepresented in the field for decades (Eaton et al., 2020). The United States government has invested in STEM disciplines to address the low presence of women in STEM fields and the STEM workforce (National Academy of Sciences, 2016). Lower representation can be attributed to numerous factors, including a lack of institutional commitment, lack of representation throughout students’ upbringing, inappropriate cultural recruitment/outreach efforts, educational discrepancies throughout PK-12, and social expectations among others (Seymour & Hewitt 1997; Geisinger & Raman, 2013; Camacho et al., 2010; Smith et al., 2012). Not only is there low representation in the field of engineering, but also low retention for students, faculty, and industry due to the same factors that impact representation. The current qualitative study is a narrative case study utilizing relational interviewing. Participants included three women in the engineering field-- an undergraduate student, a professional engineer, and a faculty member and administrator. The key themes we uncovered-- Impact of Dominant Culture; Lack of Belonging/Connection; Justification of Existence; Emotional Turmoil; Coping Strategies—are woven throughout and across the narratives. Actionable change that we hope will come from this narrative study include determining ways we can make the engineering field more inclusive at all levels– in the classroom, on co-op, at universities, in academia, and on the field in industry

A multi-class framework for a pedestrian cell transmission model accounting for population heterogeneity

This work is an extension of PedCTM, an aggregate and transient cell transmission model for multidirectional pedestrian flows in which pedestrian characteristics are assumed to be homogeneous across the population considered. Critically, one fundamental diagram relating pedestrian speed and flow to local pedestrian density is employed across the entire population. This work extends the model to population heterogeneity with a multi-class approach wherein each sub-population is assigned its own characteristic fundamental diagram. The model presented requires the implementation of an update cycle to minimize numerical dis- persion of pedestrians across all classes. In addition, multi-class dynamics introduces an element of competition in determining the flow constraints of the various classes. A priority scheme is implemented that allows for static, dynamic and stochastic determination of flow priorities throughout the network over the course of simulation. An attempt was made to base the class-specific fundamental diagrams off of inference from a dataset related to the PedFlux collaboration. Ultimately, however, the implementation made use of the Kladek formula for the speed-density relation. Preliminary simulations and results are presented to serve as a proof of concept

The Delmarva Peninsula : planning for inevitable change.

Massachusetts Institute of Technology. Dept. of Urban Studies and Planning. Thesis. 1972. B.S.Bibliography: leaf 85.B.S

Modeling Elevation-Dependent Snow Sensitivity to Climate Warming in the Data Sparse Eastern Oregon Cascades

In the mountains of the Western US, shifts in the timing and magnitude of snow water equivalent (SWE) over the past century are well documented and attributed to climate warming, but the magnitude of sensitivity depends on elevation. We modeled the spatial distribution of SWE and its sensitivity to climate warming in the 1500 km² Upper Deschutes River Basin, Oregon, with a spatially distributed snowpack energy balance model forced by a gridded meteorological dataset. The forcing data, gridded at a spatial scale of 1/16°, were downscaled to a 100 m spatial-scale digital elevation model using two sets of temperature lapse rates, with and without bias-correction applied prior to downscaling. The bias-correction method adjusted the spatial patterns of temperature and precipitation in the 1/16° gridded data to match 30 arcsecond Parameter Regressions on Independent Slopes Model (PRISM) climate data. During production, the 1/16° temperature data was adjusted for the effect of elevation using a spatially uniform and temporally constant 6.5°C km⁻¹ lapse rate, whereas PRISM adjusts temperature for the effect of elevation using spatially and temporally variable lapse rates that are computed directly from regional weather station data. Thus, bias-correction implicitly adjusted the lapse rates in the 1/16° gridded data to match measured lapse rates. To test the effect of this implicit adjustment of the input data lapse rates vs. adjusting the lapse rates during downscaling, the 30 arcsecond bias-corrected data and 1/16o original data were each downscaled with 1) a spatially uniform and temporally constant 6.5°C km⁻¹ lapse rate, and 2) with monthly varying lapse rates computed from PRISM. Precipitation was downscaled with the same method for each case. This procedure produced four sets of 100 m spatial scale data used as input to the snow model. Model parameters that control empirical estimates of incoming irradiance and the partitioning of precipitation into rain and snow were estimated independently with each dataset to optimize the agreement between modeled and observed SWE. We then modeled the sensitivity (percent change) of basin SWE in response to +2°C and +4°C warming with each of the four downscaled datasets and their respective optimized parameters. Pre-calibration, modeled SWE for the historical climate period differed depending on bias correction and choice of downscaling lapse rates. Post-calibration, modeled SWE for the historical climate period did not differ depending on choice of lapse rates but substantial differences emerged between modeled SWE with the original and bias-corrected forcing data. Inter-forcing dataset differences in modeled SWE during the historical period were largely controlled by differences in estimates of longwave irradiance and temperature between datasets. For the warming scenarios, the SWE sensitivity differed significantly at all elevations between the bias-corrected and original data, but (as in the post-calibration historical period) did not depend on choice of lapse rates. At low to mid elevations, climate change impacts on snow were largely controlled by temperature-driven shifts from snowfall to rainfall, while at high elevations, precipitation variability controlled SWE sensitivity. With just a 2°C increase in temperature, peak snow accumulation occurred 20-30 days earlier and was 20-60% smaller, the length of the snow covered season decreased up to 50 days, and winter rainfall increased by 20-60%. With a 4°C increase, the shifts in timing were roughly doubled and the declines in snow and snowfall increased up to 80%. A 10% increase in precipitation had a negligible impact on basin-integrated declines, indicating that future precipitation variability has little chance of offsetting regional climate warming impacts on snow in the Oregon Cascades. These results highlight the challenges of modeling SWE in data sparse regions, the importance of bias correcting gridded meteorological forcing datasets for hydrologic modeling applications in regions of complex topography, and the strong temperature dependence of snow in the Oregon Cascades

Enhanced magnetoassociation of 6^6Li in the quantum degenerate regime

We study magnetic Feshbach resonance of ultracold $^6$Li atoms in a dipole trap close to quantum degeneracy. The experiment is carried out by linearly ramping down the magnetic field from the BCS to the BEC side around the broad resonance at $B_r=834.1$G. The Feshbach molecule formation efficiency depends strongly on the temperature of the atomic gas and the rate at which the magnetic field is ramped across the Feshbach resonance. The molecular association process is well described by the Landau-Zener transition while above the Fermi temperature, such that two-body physics dominates the dynamics. However, we observe an enhancement of the atom-molecule coupling as the Fermionic atoms reach degeneracy, demonstrating the importance of many-body coherence not captured by the conventional Landau-Zener model. We develop a theoretical model that explains the temperature dependence of the atom-molecule coupling. Furthermore, we characterize this dependence experimentally and extract the atom-molecule coupling coefficient as a function of temperature, finding qualitative agreement between our model and experimental results. Accurate measurement of this coupling coefficient is important for both theoretical and experimental studies of atom-molecule association dynamics.Comment: 6 pages, 4 figure

Factors predicting incidence of post-operative delirium in older people following hip fracture surgery: a systematic review and meta-analysis

Objective: Delirium is one of the most common complications following hip fracture surgery in older people. This study identified pre- and peri-operative factors associated with the development of post-operative delirium following hip fracture surgery. Methods: Published and unpublished literature were searched to identify all evidence reporting variables on patient characteristics, on-admission, intra-operative and post-operative management assessing incident delirium in older people following hip fracture surgery. Pooled odds ratio (OR) and mean difference (MD) of those who experienced delirium compared to those who did not were calculated for each variable. Evidence was assessed using the Downs and Black appraisal tool and interpreted using the GRADE approach. Results: 6704 people (2090 people with post-operative delirium) from 32 studies were analysed. There was moderate evidence of nearly a two-times greater probability of post-operative delirium for those aged 80 years and over (OR: 1.77; 95% CI: 1.09, 2.87), whether patients lived in a care institution pre-admission (OR: 2.65; 95% CI: 1.79, 3.92), and a six-times greater probability of developing post-operative delirium with a pre-admission diagnosis of dementia (OR: 6.07, 95% CI: 4.84, 7.62). There was no association with intra-operative variables and probability of delirium. Conclusion: Clinicians treating people with a hip fracture should be vigilant towards post-operative delirium if their patients are older, have pre-existing cognitive impairment and poorer overall general health. This is also the case for those who experience post-operative complications such as pneumonia or a urinary tract infection

Methods for detecting gene × gene interaction in multiplex extended pedigrees

Complex diseases are multifactorial in nature and can involve multiple loci with gene × gene and gene × environment interactions. Research on methods to uncover the interactions between those genes that confer susceptibility to disease has been extensive, but many of these methods have only been developed for sibling pairs or sibships. In this report, we assess the performance of two methods for finding gene × gene interactions that are applicable to arbitrarily sized pedigrees, one based on correlation in per-family nonparametric linkage scores and another that incorporates candidate loci genotypes as covariates into an affected relative pair linkage analysis. The power and type I error rate of both of these methods was addressed using the simulated Genetic Analysis Workshop 14 data. In general, we found detection of the interacting loci to be a difficult problem, and though we experienced some modest success there is a clear need to continue developing new methods and approaches to the problem