Lehigh University

About: Lehigh University is a education organization based out in Bethlehem, Pennsylvania, United States. It is known for research contribution in the topics: Catalysis & Fracture mechanics. The organization has 12684 authors who have published 26550 publications receiving 770061 citations.

Detection of noninteracting single domain particles using first-order reversal curve diagrams

Abstract: We present a highly sensitive and accurate method for quantitative detection and characterization of noninteracting or weakly interacting uniaxial single domain particles (UNISD) in rocks and sediments. The method is based on high-resolution measurements of first-order reversal curves (FORCs). UNISD particles have a unique FORC signature that can be used to isolate their contribution among other magnetic components. This signature has a narrow ridge along the Hc axis of the FORC diagram, called the central ridge, which is proportional to the switching field distribution of the particles. Therefore, the central ridge is directly comparable with other magnetic measurements, such as remanent magnetization curves, with the advantage of being fully selective to SD particles, rather than other magnetic components. This selectivity is unmatched by other magnetic unmixing methods, and offers useful applications ranging from characterization of SD particles for paleointensity studies to detecting magnetofossils and ultrafine authigenically precipitated minerals in sediments.

Large stocks of peatland carbon and nitrogen are vulnerable to permafrost thaw.

Abstract: Northern peatlands have accumulated large stocks of organic carbon (C) and nitrogen (N), but their spatial distribution and vulnerability to climate warming remain uncertain. Here, we used machine-learning techniques with extensive peat core data (n > 7,000) to create observation-based maps of northern peatland C and N stocks, and to assess their response to warming and permafrost thaw. We estimate that northern peatlands cover 3.7 ± 0.5 million km2 and store 415 ± 150 Pg C and 10 ± 7 Pg N. Nearly half of the peatland area and peat C stocks are permafrost affected. Using modeled global warming stabilization scenarios (from 1.5 to 6 °C warming), we project that the current sink of atmospheric C (0.10 ± 0.02 Pg C⋅y-1) in northern peatlands will shift to a C source as 0.8 to 1.9 million km2 of permafrost-affected peatlands thaw. The projected thaw would cause peatland greenhouse gas emissions equal to ∼1% of anthropogenic radiative forcing in this century. The main forcing is from methane emissions (0.7 to 3 Pg cumulative CH4-C) with smaller carbon dioxide forcing (1 to 2 Pg CO2-C) and minor nitrous oxide losses. We project that initial CO2-C losses reverse after ∼200 y, as warming strengthens peatland C-sinks. We project substantial, but highly uncertain, additional losses of peat into fluvial systems of 10 to 30 Pg C and 0.4 to 0.9 Pg N. The combined gaseous and fluvial peatland C loss estimated here adds 30 to 50% onto previous estimates of permafrost-thaw C losses, with southern permafrost regions being the most vulnerable.

Rectified Motion of Liquid Drops on Gradient Surfaces Induced by Vibration

Abstract: When a liquid drop (1−2 μL) is placed on a surface possessing a continuous gradient of wettability, it moves toward the more wettable part of the gradient with typical speeds of 1−2 mm/s. This low speed arises because the driving force due to surface tension is reduced by contact angle hysteresis. The hysteresis force acting on a drop on a gradient surface is, however, spatially asymmetricits magnitude against the gradient being larger than that along the gradient. If a periodic force is applied to a drop resting on such a gradient surface, the force against the gradient is rectified whereas it is enhanced along the gradient. This half-wave rectification of periodic force causes 1−2 μL size drops to move with enhanced speeds of 5−10 mm/s.

Interior Point Methods for Nonlinear Optimization

Abstract: Interior-point methods (IPMs) are among the most efficient methods for solving linear, and also wide classes of other convex optimization problems. Since the path-breaking work of Karmarkar [48], much research was invested in IPMs. Many algorithmic variants were developed for Linear Optimization (LO). The new approach forced to reconsider all aspects of optimization problems. Not only the research on algorithms and complexity issues, but implementation strategies, duality theory and research on sensitivity analysis got also a new impulse. After more than a decade of turbulent research, the IPM community reached a good understanding of the basics of IPMs. Several books were published that summarize and explore different aspects of IPMs. The seminal work of Nesterov and Nemirovski [63] provides the most general framework for polynomial IPMs for convex optimization. Den Hertog [42] gives a thorough survey of primal and dual path-following IPMs for linear and structured convex optimization problems. Jansen [45] discusses primal-dual target following algorithms for linear optimization and complementarity problems.Wright [93] also concentrates on primal-dual IPMs, with special attention on infeasible IPMs, numerical issues and local, asymptotic convergence properties. The volume [80] contains 13 survey papers that cover almost all aspects of IPMs, their extensions and some applications. The book of Ye [96] is a rich source of polynomial IPMs not only for LO, but for convex optimization problems as well. It extends the IPM theory to derive bounds and approximations for classes of nonconvex optimization problems as well. Finally, Roos, Terlaky and Vial [72] present a thorough treatment of the IPM based theory - duality, complexity, sensitivity analysis - and wide classes of IPMs for LO.

Alliance portfolio diversity and firm performance

Abstract: In this paper, we offer a comprehensive alliance portfolio diversity construct that includes partner, functional, and governance diversity. Grounding our work primarily with the resource- and dynamic capabilities-based views, we argue that increased diversity in partners' industry, organizational, and national background will incur added complexity and coordination costs but will provide broadened resource and learning benefits. Increased functional diversity results in a more balanced portfolio of exploration and exploitation activities that expands the firm's knowledge base while increased governance diversity inhibits learning and routine building. Hypotheses were tested with alliance portfolio and performance data for 138 multinational firms in the global automobile industry during the twenty-year period from 1985 to 2005. We found alliance portfolios with greater organizational and functional diversity and lower governance diversity were related to higher firm performance while industry diversity had a U-shaped relationship with firm performance. We suggest firms manage their alliances with a portfolio perspective, seeking to maximize resource and learning benefits by collaborating with a variety of organizations in various value chain activities while minimizing managerial costs through a focused set of governance structures. Copyright © 2010 John Wiley & Sons, Ltd.