Purdue University

About: Purdue University is a education organization based out in West Lafayette, Indiana, United States. It is known for research contribution in the topics: Population & Heat transfer. The organization has 73219 authors who have published 163563 publications receiving 5775236 citations. The organization is also known as: Purdue & Purdue-West Lafayette.

Employee Turnover: A Meta-Analysis and Review with Implications for Research

Abstract: Studies of employee turnover are reviewed using meta-analytic techniques. The findings indicate that almost all of the 26 variables studied relate to turnover. The findings also indicate that study variables including population, nationality, and industry moderate relationships between many of the variables and turnover. It is suggested that future research on employee turnover: (1) report study variables, (2) continue model testing rather than simply correlating variables with turnover, and (3) incorporate study variables into future models.

What is beautiful is good, but…: A meta-analytic review of research on the physical attractiveness stereotype.

Abstract: This review demonstrates that the physical attractiveness stereotype established by studies of person perception is not as strong or general as suggested by the often-used summary phrase what is beautiful is good. Although subjects in these studies ascribed more favorable personality traits and more successful life outcomes to attractive than unattractive targets, the average magnitude of this beauty-is-good effect was moderate, and the strength of the effect varied considerably from study to study Consistent with our implicit personality theory framework, a substantial portion of this variation was explained by the specific content of the inferences that subjects were asked to make: The differences in subjects* perception of attractive and unattractive targets were largest for indexes of social competence; intermediate for potency, adjustment, and intellectual competence; and near zero for integrity and concern for others. The strength of the physical attractiveness stereotype also varied as a function of other attributes of the studies, including the presence of individuating information.

The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements

Abstract: [1] This first paper of the two‐part series describes the objectives of the community efforts in improving the Noah land surface model (LSM), documents, through mathematical formulations, the augmented conceptual realism in biophysical and hydrological processes, and introduces a framework for multiple options to parameterize selected processes (Noah‐MP). The Noah‐MP’s performance is evaluated at various local sites using high temporal frequency data sets, and results show the advantages of using multiple optional schemes to interpret the differences in modeling simulations. The second paper focuses on ensemble evaluations with long‐term regional (basin) and global scale data sets. The enhanced conceptual realism includes (1) the vegetation canopy energy balance, (2) the layered snowpack, (3) frozen soil and infiltration, (4) soil moisture‐groundwater interaction and related runoff production, and (5) vegetation phenology. Sample local‐scale validations are conducted over the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) site, the W3 catchment of Sleepers River, Vermont, and a French snow observation site. Noah‐MP shows apparent improvements in reproducing surface fluxes, skin temperature over dry periods, snow water equivalent (SWE), snow depth, and runoff over Noah LSM version 3.0. Noah‐MP improves the SWE simulations due to more accurate simulations of the diurnal variations of the snow skin temperature, which is critical for computing available energy for melting. Noah‐MP also improves the simulation of runoff peaks and timing by introducing a more permeable frozen soil and more accurate simulation of snowmelt. We also demonstrate that Noah‐MP is an effective research tool by which modeling results for a given process can be interpreted through multiple optional parameterization schemes in the same model framework.