Principal Investigators: Bo Zeng (Swanson School of Engineering), Na Du (School of Information Science) Alison Sanders (School of Public Health)
Abstract: Investigating how to utilize a smaller number of electric school buses, along with traditional diesel-powered ones, to transport students with better health and sustainability outcomes
Principal Investigators: William Harbert (Department of Geology and Environmental Science), Paul Ohodnicki (Swanson School of Engineering), Khurram Naeem (Swanson School of Engineering)
Abstract: Distributed fiber sensing has the potential for the extraction of thousands of measurement points from a single strand of fiber optic cable. In this proposal, a long fiber optic cable will be identified within the region of Pittsburgh, PA and an already existing interrogator unit will be used to record several weeks of data. The integrator configuration will be used as a Distributed Acoustic Sensing (DAS) geotechnical multichannel linear array with carefully modeled virtual sensor location. These data will then be analyzed and compared with the already running and fully functional three-component research seismograph UPAO (UPAO University of Pittsburgh - Allegheny Observatory) located at 40.48° N, 80.02° W and 274 meters elevation to identify local and global seismic activity, and identify non-seismic acoustic emission anomalies. As a new methodology applied to DAS, these virtual sensor DAS records will then be processed using Rayleigh wave (Passive Multichannel Analysis of Surface Waves, P-MASW) surface analysis techniques to determine a high resolution2-D map of material stiffness of the near-surface along the DAS dark fiber array length. The completed geophysical dark fiber workflows, and optimum DAS parameters (number of channels, receiver spacing, and recording parameters) will be highly useful and application of this technique to other dark fiber networks can be rapidly expanded to produce a regional material stiffness shallow subsurface map (> 30 m depth below dark fiber) in urban areas.
Principal Investigators: Morgan DiLeo (Ophthalmology), Sanford Asher (Chemistry),
Abstract: Development of an inexpensive, user-friendly sensing platform that can simplify detection of diagnostic biomarkers compared to current industry standards. The proposed work will focus on the development of a sensor that can detect brain-derive neurotrophic factor (BDNF), a biomarker for early-stage glaucoma. Such a sensor will simplify the diagnosis of early-stage glaucoma and improve visualoutcomes for patients.
Principal Investigators: Lisa Maillart (Swanson School of Engineering) and Supriya Kumar (Graduate School of Public Health
Topic: On the Allocation and Use of Paid Sick Days in Today’s Workplace: A Multidisciplinary Approach
Principal Investigators: Phil Williams (Matthew B. Ridgway Center for Security and Intelligence Studies at the Graduate School of Public and International Affairs), Thomas Congedo (Associate Director of the Stephen R. Tritch Nuclear Engineering Program) and Yu-Ru Lin (School of Information Science)
Topic: Intersections: Nuclear Smuggling, Transnational Organized Crime, and Terrorism: Enhancing Intelligence and Policy Responses
Principal Investigators: Hoda Bikhori (Swanson School of Engineering) and Keivan Sadeghzadeh
(Prediction Analysis Lab at the Massachusetts Institute of Technology’s Sloan School of Management )
Topic: Predictive Analytics for Operational Failures in Medical and Healthcare Systems
Principal Investigators: Frank Giarratani, Jean-Francois Richard, Mehmet Ali Soytas
This research presents and applies a dynamic model of monthly U.S ferrous scrap prices for the period of 1990 to 2010. Our analysis takes into account the nonlinear reaction of price changes to "excess demand" and addresses the challenge of forecasting in a market where long-standing trends are disrupted by dramatic changes in international demand. We bring modern statistical techniques to bear on analysis in a forecasting environment long dominated by predictions based on the immediate experience of industry practitioners.
Policy, Regulation and Innovation in Chinese Industry
Project Directors: Loren Brandt, Thomas G. Rawski
What drives the growing innovative capacity of Chinese industry? What is its likely trajectory? Do China's policies accelerate the accumulation of manufacturing capabilities? This project adopts a three-stage approach to answering these questions.
Project directors
Loren Brandt, University of Toronto
Thomas G. Rawski, University of Pittsburgh
Multidisciplinary teams will conduct intensive documentary and field studies of six high-priority industries. Adding firm-level data on production, finance, and trade will expand our analysis to encompass the entire industrial sector. We then focus on the prospects for key upstream technologies that emerge from the initial research. At the micro-level, our study will measure the effectiveness of multiple channels of technological upgrading; at the macro-level, it will deliver a comprehensive overview of China's national innovation system.
Participants
Michael Davidson, MIT
Douglas B. Fuller, Zhejiang University
Ravi Madhavan, University of Pittsburgh
Margaret M. Pearson, University of Maryland
Zhi Qiang, Central University of Finance and Economics, Beijing
Richard P. Suttmeier, University of Oregon
Timothy Sturgeon, MIT
Eric Thun, University of Oxford
Qingfeng Tian, Northwest Polytechnic University, Xi’an
Luhang Wang, Xiamen University
Irene S. Wu, U.S. Federal Communications Commission
Yi-chong Xu, Griffith University
Principal Investigator: Frank Giarratani
The steel industry in Pittsburgh was emblematic of the American steel industry's decline in the 1980s. Although airbrushed from the popular image of Pittsburgh's present and future, the region's signature industry has played a key positive role in Pittsburgh's widely acknowledged economic transformation. Through restructuring, the steel industry has solidified Pittsburgh's manufacturing base and helped to connect southwestern Pennsylvania to the world economy. The goal of this research is to produce a book that traces this remarkable trajectory and places Pittsburgh's modern steel industry in an historical context.
By drawing on the region's industrial history and contemporary practices of firms throughout the steel value chain, this research seeks to expose key aspects of Pittsburgh's economic resilience. The experience of steel-related firms will be used to demonstrate the vitality of the steel industry in the Pittsburgh region by explaining the ways in which innovative firms adapt to changing market conditions.
Principal Investigators: Frank Giarratani, Gene Gruver, Carey Treado
The database compiled at the Center for Industry Studies to support research on the steel industry is extensive, and it includes records related to all steel-making plants in the United States with raw steel making capacity from 1978 to 2003. Data for the steel mills is drawn from industry sources such as 33 Metal Producing and Iron & Steelmaker (I&SM), and related data on economic variables for steel producing regions are compiled from public sources. To prepare the data for use on applied modeling problems, we secured the help of database experts and have constructed a relational database using Microsoft® Access. The effort in this work has been substantial in that it required the organization of data from numerous fragmented sources. Once organized, further substantial efforts were required to document the data, prepare necessary data entry forms, and train students for implementation and use of the database. Although the database is no longer being updated, it remains a powerful tool for analyzing past trends related to steel manufacturing in the United States.
Reducing Industrial Accidents, Worker Chemical Exposure and Pollution in the Chemical Industry
PI Shanti Gamper-Rabindran and Stephen Finger
Industry self-regulation, voluntary programs and information disclosure programs have become exceedingly important in risky industries, with the decline in regulatory budgets and the increasing costs of traditional regulations. We construct a detailed database of about 3,000 chemical plants in the US over a decade, with economic, environmental and regulatory information. We find that industry self-regulation and voluntary standards, in the presence of effective liability laws, can effectively reduce industrial accidents and worker exposure to toxic chemicals, respectively.[1,2] However, when complementary liability laws are absent, self-regulation programs are not likely to reduce pollution. [3, 4] Our research also finds that mandatory pollution disclosure programs, aimed at reducing chemical factories' pollution releases into the environment, is associated with a decline in workers' exposure to chemicals inside these factories. [5]
Acknowledgement: National Science Foundation SES 1127223 and BCS 0351058, Central Research Development Fund, European Union Center for Excellence, University Center for International Studies, Center for Industry Studies.
- S. Finger and S. Gamper-Rabindran. Testing the effects of self-regulation on industrial accidents. Journal of Regulatory Economics , 43(2) 2013:115-146
- S. Finger and S. Gamper-Rabindran. Voluntary versus mandatory standards: Protecting workers from adverse chemical exposure. Center for Industry Studies WP # 36, 2012.
- S. Gamper-Rabindran. Did the EPA's voluntary Industrial Toxics program reduce plants' emissions? A GIS analysis of distributional impacts and a by-media analysis of substitution. Journal of Environmental Economics and Management 52(1) 2006:391-410.
- S. Gamper-Rabindran and S. Finger. Does self-regulation reduce pollution? Responsible Care program in the chemical industry . Journal of Regulatory Economics, 43(1) 2013: 1-30.
- S. Finger and S. Gamper-Rabindran. Mandatory disclosure of plant emissions into the environment and worker chemical exposure inside plants. Ecological Economics, 87, 2013: 124-136.
Principal Investigators: John Camillus and Bopaya Bidanda
The Business of the Humanity Project seeks to develop an economic model informed by the criterion of "humanity." The project also attempts to rethink the strategy paradigm by incorporating humanity. This requires redefining the strategy process; recognizing the significance of social networks; shifting from an emphasis on competition to "co-opetition" and alliances; incorporating multi-criteria, multiple stakeholder decision processes;responding to the wicked nature of many strategic issues; and integrating content and processes. The project develops case studies, holds conferences, and maintains an online network of managers and academics to achieve its objectives.