University of South Florida

About: University of South Florida is a education organization based out in Tampa, Florida, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 34231 authors who have published 72644 publications receiving 2538044 citations. The organization is also known as: USF.

Handbook of energy efficiency and renewable energy

Abstract: Global energy system / D. Yogi Goswami, Frank Kreith -- Energy policy -- Economics methods / Rosalie Ruegg, Walter Short -- Environmental impacts and costs of energy / Ari Rabl, Joseph V. Spadaro -- Distributed generation and demand-side management -- Generation technologies through the year 2025 -- Outlook for U.S. energy consumption and prices in the midterm / Andy S. Kydes -- Transportation systems / Beth Isler -- Infrastructure risk analysis and security -- Electrical energy management in buildings / Craig B. Smith, Kelly E. Parmenter -- Heating, ventilating, and air conditioning control systems / Jan F. Kreider, David E. Claridge, Charles H. Culp -- Energy efficient technologies -- Compact heat exchangers : recuperators and regenerators / Ramesh K. Shah -- Industrial energy efficiency and energy management / Craig B. Smith, Barney L. Capehart, Wesley M. Rohrer Jr. -- Process energy efficiency : pinch technology -- Energy audits for buildings / Moncef Krarti -- Cogeneration / W. Dan Turner -- Energy storage, transmission, and distribution -- Availability of renewable resources -- Solar thermal energy conversion -- Concentrating solar thermal power / Manuel Romero-Alvarez, Eduardo Zarza -- Wind energy conversion / Dale E. Berg -- Photovoltaics fundamentals, technology, and application -- Waste-to-energy combustion / Charles O. Velzy, Leonard M. Grillo -- Biomass conversion processes for energy recovery -- Geothermal power generation / Kevin Kitz -- Hydrogen energy technologies / S.A. Sherif, F. Barbir, T.N. Veziroglu, M. Mahishi, S.S. Srinivasan -- Fuel cells / Xianguo Li -- Appendices / Nitin Goel.

Esophageal and esophagogastric junction cancers, version 1.2015.

Abstract: Esophageal cancer is the sixth most common cause of cancer deaths worldwide. Adenocarcinoma is more common in North America and Western European countries, originating mostly in the lower third of the esophagus, which often involves the esophagogastric junction (EGJ). Recent randomized trials have shown that the addition of preoperative chemoradiation or perioperative chemotherapy to surgery significantly improves survival in patients with resectable cancer. Targeted therapies with trastuzumab and ramucirumab have produced encouraging results in the treatment of advanced or metastatic EGJ adenocarcinomas. Multidisciplinary team management is essential for patients with esophageal and EGJ cancers. This portion of the NCCN Guidelines for Esophageal and EGJ Cancers discusses management of locally advanced adenocarcinoma of the esophagus and EGJ.

Improving evidence-based care for heart failure in outpatient cardiology practices: primary results of the Registry to Improve the Use of Evidence-Based Heart Failure Therapies in the Outpatient Setting (IMPROVE HF).

Abstract: Background— A treatment gap exists between heart failure (HF) guidelines and the clinical care of patients. The Registry to Improve the Use of Evidence-Based Heart Failure Therapies in the Outpatient Setting (IMPROVE HF) prospectively tested a multidimensional practice-specific performance improvement intervention on the use of guideline-recommended therapies for HF in outpatient cardiology practices. Methods and Results— Performance data were collected in a random sample of HF patients from 167 US outpatient cardiology practices at baseline, longitudinally after intervention at 12 and 24 months, and in single-point-in-time patient cohorts at 6 and 18 months. Participants included 34 810 patients with reduced left ventricular ejection fraction (≤35%) and chronic HF or previous myocardial infarction. To quantify guideline adherence, 7 quality measures were assessed. Interventions included clinical decision support tools, structured improvement strategies, and chart audits with feedback. The performance imp...

Modeling the choice continuum: An integrated model of residential location, auto ownership, bicycle ownership, and commute tour mode choice decisions

Abstract: The integrated modeling of land use and transportation choices involves analyzing a continuum of choices that characterize people’s lifestyles across temporal scales. This includes long-term choices such as residential and work location choices that affect land-use, medium-term choices such as vehicle ownership, and short-term choices such as travel mode choice that affect travel demand. Prior research in this area has been limited by the complexities associated with the development of integrated model systems that combine the long-, medium- and short-term choices into a unified analytical framework. This paper presents an integrated simultaneous multi-dimensional choice model of residential location, auto ownership, bicycle ownership, and commute tour mode choices using a mixed multidimensional choice modeling methodology. Model estimation results using the San Francisco Bay Area highlight a series of interdependencies among the multi-dimensional choice processes. The interdependencies include: (1) self-selection effects due to observed and unobserved factors, where households locate based on lifestyle and mobility preferences, (2) endogeneity effects, where any one choice dimension is not exogenous to another, but is endogenous to the system as a whole, (3) correlated error structures, where common unobserved factors significantly and simultaneously impact multiple choice dimensions, and (4) unobserved heterogeneity, where decision-makers show significant variation in sensitivity to explanatory variables due to unobserved factors. From a policy standpoint, to be able to forecast the “true” causal influence of activity-travel environment changes on residential location, auto/bicycle ownership, and commute mode choices, it is necessary to capture the above-identified interdependencies by jointly modeling the multiple choice dimensions in an integrated framework.