Consumer Willingness to Pay and Marketing Opportunities for "Quality Guaranteed Tree-Ripened Peaches" in New York State

This study identifies consumer characteristics associated with willingness to pay a higher price for quality guaranteed tree-ripened peaches, with a focus on evaluating factors important to consumers when making decisions to purchase tree-ripened peaches. Telephone interviews were conducted with consumers in New York State in summer, 2002. Seventy-eight percent of the 258 survey respondents reported that they were willing to pay a higher price. A logistical regression model of willingness to pay was estimated. The empirical results indicated that willingness to pay was positively affected by the existence of previous experiences in purchasing tree-ripened peaches and by consumer dissatisfaction with peaches consumed in the past. An analysis of consumer experiences and consumer dissatisfaction showed that consumers in the two identified segments had mutually exclusive characteristics that present marketing opportunities for high quality New York-grown peaches.Consumer/Household Economics,

Quasilocal Center-of-Mass for Teleparallel Gravity

Asymptotically flat gravitating systems have 10 conserved quantities, which lack proper local densities. It has been hoped that the teleparallel equivalent of Einstein's GR (TEGR, aka GR${}_{||}$) could solve this gravitational energy-momentum localization problem. Meanwhile a new idea: quasilocal quantities, has come into favor. The earlier quasilocal investigations focused on energy-momentum. Recently we considered quasilocal angular momentum for the teleparallel theory and found that the popular expression (unlike our ``covariant-symplectic'' one) gives the correct result only in a certain frame. We now report that the center-of-mass moment, which has largely been neglected, gives an even stronger requirement. We found (independent of the frame gauge) that our ``covariant symplectic'' Hamiltonian-boundary-term quasilocal expression succeeds for all the quasilocal quantities, while the usual expression cannot give the desired center-of-mass moment. We also conclude, contrary to hopes, that the teleparallel formulation appears to have no advantage over GR with regard to localization.Comment: 12 pages, to appear in the proceedings of the 10th Marcel Grossman meeting (Rio de Janeiro, 2003

Improving Instruction in Universities: A Case Study of the Ontario Universities Program for Instructional Development (OUPID)

In the late I960's and 1970's, universities established programs, projects, and offices to improve the quality of undergraduate teaching. One of these, the Ontario Universities Program for Instructional Development (OUPID), was created to develop teaching in Ontario's 16 universities. It employed two methods, individual grants and institutional grants, to fulfill its mandate. The Program's limited impact on teaching was attributed to the amount of money, $2,500,000 earmarked for OUPID during its seven years of operation (1973-80) and to the lack of a plan. When examined closely, these reasons only partially explain OUPID's limited influence on teaching. It is more illuminating to consider the Program in relation to what most academics and universities value. This reveals that OUPID's methods neither reflected the way academics view good teaching and teaching improvement nor the way the universities believe excellence is fostered. These findings suggest that interventions which seek to change university teaching must agree with and then extend academic and university values. This conclusion has implications for the response universities make as they address the recent concern for the quality of undergraduate education.À la fin des années 60 et dans les années 70, les universités ont mis en place des programmes, des projets et des services afin d'améliorer la qualité de l'enseigne-ment dans le premier cycle universitaire. L'un de ceux-ci, le Programme de développement de l'instruction dans les universités ontariennes (O UPID : Ontario Universities Program for Instructional Development) fut créé dans le but de promouvoir l'enseignement dans 16 universités en Ontario. Pour atteindre son objectif, le programme faisait appel à deux méthodes: celle des bourses individuelles et celle des bourses institutionnelles. L'impact limité du programme sur l'enseignement fut attribué, d'une part, à l'insuffisance de la somme de 2500000 dollars allouée à OUPID durant les 7 années d'application (73-80), d'autre part à l'absence de plan concerté. En y regardant de plus près, ces raisons n'expliquent que partiellement l'influence du plan OUPID sur l'enseignement. Il est plus éclairant de considérer le programme par rapport à ce que beaucoup d'universitaires et d'universités préconisent avant tout. Il en ressort que les méthodes d'OUPID ne reflètent ni la façon dont les universitaires envisagent un bon enseignement et son amélioration, ni la façon dont les universités estiment que la qualité est favorisée. Ces résultats suggèrent que les interventions visant à modifier l'enseignement universitaire doivent s'accorder et donc s'étendre aux valeurs scolaires et universitaires. Cette conclusion a des répercussions sur la réaction des universités lorsqu'elles répondent à la préoccupation récente concernant la qualité de l'éducation en premier cycle universitaire

Thoracic Disease Identification and Localization with Limited Supervision

Accurate identification and localization of abnormalities from radiology images play an integral part in clinical diagnosis and treatment planning. Building a highly accurate prediction model for these tasks usually requires a large number of images manually annotated with labels and finding sites of abnormalities. In reality, however, such annotated data are expensive to acquire, especially the ones with location annotations. We need methods that can work well with only a small amount of location annotations. To address this challenge, we present a unified approach that simultaneously performs disease identification and localization through the same underlying model for all images. We demonstrate that our approach can effectively leverage both class information as well as limited location annotation, and significantly outperforms the comparative reference baseline in both classification and localization tasks.Comment: Conference on Computer Vision and Pattern Recognition 2018 (CVPR 2018). V1: CVPR submission; V2: +supplementary; V3: CVPR camera-ready; V4: correction, update reference baseline results according to their latest post; V5: minor correction; V6: Identification results using NIH data splits and various image model