Biomedical subjects

Bhavik R Bakshi

Publications and source records attributed to Bhavik R Bakshi.

4 recordsLinked to original sources

PubMed2005

Flow of natural versus economic capital in industrial supply networks and its implications to sustainability.

Appreciating the reliance of industrial networks on natural capital is a necessary step toward their sustainable design and operation. However, most contemporary accounting techniques, including engineering economics, life cycle assessment, and full cost accounting, fail in this regard, as they take natural capital for granted and concentrate mainly on the economic aspects and emissions. The recently developed "thermodynamic input-output analysis" (TIOA) includes the contribution of ecological goods, ecosystem services, human resources, and impact of emissions in an economic input-output model. This paper uses TIOA to determine the throughputs of natural and economic capitals along industrial supply networks. The ratios of natural to economic capitals of economic sectors reveals a hierarchical organization of the U.S. economy wherein basic infrastructure industries are at the bottom and specialized value-added industries constitute the top. These results provide novel insight into the reliance of specific industrial sectors and supply chains on natural capital and the corresponding economic throughput. Such insight is useful for understanding the implications of corporate restructuring on industrial sustainability metrics and of outsourcing of business activities on outsourcer, outsourcee, and global sustainability. These implications are discussed from the standpoints of weak and strong sustainability paradigms. The calculated ratios can also be used for hybrid thermodynamic life cycle assessment.

Costs and Cost Analysis↗

PubMed2004

Thermodynamic accounting of ecosystem contribution to economic sectors with application to 1992 U.S. economy.

Incorporation of ecological considerations in decision-making is essential for sustainable development, but is hindered by inadequate appreciation of the role of ecosystems, and lack of scientifically rigorous techniques for including their contribution. This paper develops a novel thermodynamic accounting framework for including the contribution of natural capital via thermodynamic input-output analysis. This framework is applied to the 1992 US economy comprising 91 industry sectors, resulting in delineation of the myriad ways in which sectors of the US economy rely on ecosystem products and services. The contribution of ecosystems is represented via the concept of ecological cumulative exergy consumption (ECEC), which is related to emergy analysis but avoids any of its controversial assumptions and claims. The use of thermodynamics permits representation of all kinds of inputs and outputs in consistent units, facilitating the definition of aggregate metrics. Total ECEC requirement indicates the extent to which each economic sector relies directly and indirectly on ecological inputs. The ECEC/money ratio indicates the relative monetary versus ecological throughputs in each sector, and indicates the relationship between the thermodynamic work needed to produce a product or service and the corresponding economic activity. This ratio is found to decrease along economic supply chains, indicating industries that are higher up in the economic food chain price ecosystem contribution more than the basic infrastructure industries such as mining and manufacturing. The ratio of CEC with and without inclusion of ecosystems indicates the extent to which conventional thermoeconomic analysis underestimates the contribution of ecosystems. Such ratios, made available for the first time, provide unique insight into the importance of natural capital, and are especially useful in hybrid thermodynamic life cycle analysis of industrial systems. The approach, data compiled in this work, and the resulting insight provide a more ecologically conscious tool for environmental decision-making, and has potential applications at micro as well as macro scales.

Accounting↗

PubMed2004

Expanding exergy analysis to account for ecosystem products and services.

Exergy analysis is a thermodynamic approach used for analyzing and improving the efficiency of chemical and thermal processes. It has also been extended for life cycle assessment and sustainability evaluation of industrial products and processes. Although these extensions recognize the importance of capital and labor inputs and environmental impact, most of them ignore the crucial role that ecosystems play in sustaining all industrial activity. Decisions based on approaches that take nature for granted continue to cause significant deterioration in the ability of ecosystems to provide goods and services that are essential for every human activity. Accounting for nature's contribution is also important for determining the impact and sustainablility of industrial activity. In contrast, emergy analysis, a thermodynamic method from systems ecology, does account for ecosystems, but has encountered a lot of resistance and criticism, particularly from economists, physicists, and engineers. This paper expands the engineering concept of Cumulative Exergy Consumption (CEC) analysis to include the contribution of ecosystems, which leads to the concept of Ecological Cumulative Exergy Consumption (ECEC). Practical challenges in computing ECEC for industrial processes are identified and a formal algorithm based on network algebra is proposed. ECEC is shown to be closely related to emergy, and both concepts become equivalent if the analysis boundary, allocation method, and approach for combining global energy inputs are identical. This insight permits combination of the best features of emergy and exergy analysis, and shows that most of the controversial aspects of emergy analysis need not hinder its use for including the exergetic contribution of ecosystems. Examples illustrate the approach and highlight the potential benefits of accounting for nature's contribution to industrial activity.

Algorithms↗

PubMed2002

Multiscale and Bayesian approaches to data analysis in genomics high-throughput screening.

Tremendous amounts of data are produced by high-throughput screening methods currently employed in drug discovery and product development. A typical cDNA microarray or oligonucleotide-based gene chip experiment easily generates over 10,000 data points for each array or chip. The challenge of inferring meaningful information is formidable given the size and number of these datasets. This paper reviews the current status of statistical tools available for gene expression analysis, with emphasis on Bayesian approaches and multiscale wavelet filtering. Fundamental concepts of Bayesian and multiscale modeling are discussed from the perspective of their potential to address important issues related to the analysis of gene expression data, such as the fact that genomic data often have non-Gaussian distributions and feature localization and multiple scales in both frequency and measurement dimension. Recent publications in these areas are reviewed. Wavelet filtering and the advantages of multiscale methods are demonstrated by application to publicly available gene expression data from the National Cancer Institute (NCI). Multiscale methods, including multiscale principal component analysis (MSPCA), are applied to extract gene subsets and to visualize data in multidimensions for comparisons. Similarity in cell lines and gene selection are effectively visualized and quantitatively compared.

Animals↗