State University of New York System

About: State University of New York System is a education organization based out in Albany, New York, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 54077 authors who have published 78070 publications receiving 2985160 citations.

On Learning Vector-Valued Functions

Abstract: In this letter, we provide a study of learning in a Hilbert space of vectorvalued functions. We motivate the need for extending learning theory of scalar-valued functions by practical considerations and establish some basic results for learning vector-valued functions that should prove useful in applications. Specifically, we allow an output space Y to be a Hilbert space, and we consider a reproducing kernel Hilbert space of functions whose values lie in Y. In this setting, we derive the form of the minimal norm interpolant to a finite set of data and apply it to study some regularization functionals that are important in learning theory. We consider specific examples of such functionals corresponding to multiple-output regularization networks and support vector machines, for both regression and classification. Finally, we provide classes of operator-valued kernels of the dot product and translation-invariant type.

Pattern and variation of C:N:P ratios in China’s soils: a synthesis of observational data

Abstract: Inspired by previous studies that have indicated consistent or even well-constrained (relatively low variability) relations among carbon (C), nitrogen (N) and phosphorus (P) in soils, we have endeavored to explore general soil C:N:P ratios in China on a national scale, as well as the changing patterns of these ratios with soil depth, developmental stages and climate; we also attempted to determine if well-constrained C:N:P stoichiometrical ratios exist in China’s soil. Based on an inventory data set of 2,384 soil profiles, our analysis indicated that the mean C:N, C:P and N:P ratios for the entire soil depth (as deep as 250 cm for some soil profiles) in China were 11.9, 61 and 5.2, respectively, showing a C:N:P ratio of ~60:5:1. C:N ratios showed relatively small variation among different climatic zones, soil orders, soil depth and weathering stages, while C:P and N:P ratios showed a high spatial heterogeneity and large variations in different climatic zones, soil orders, soil depth and weathering stages. No well-constrained C:N:P ratios were found for the entire soil depth in China. However, for the 0–10 cm organic-rich soil, which has the most active organism–environment interaction, we found a well-constrained C:N ratio (14.4, molar ratio) and relatively consistent C:P (136) and N:P (9.3) ratios, with a general C:N:P ratio of 134:9:1. Finally, we suggested that soil C:N, C:P and N:P ratios in organic-rich topsoil could be a good indicator of soil nutrient status during soil development.

The Differentiation of Self Inventory: Development and Initial Validation

Abstract: Despite the importance of Bowen theory (M.Bowen, 1976,1978; M. E. KerrB Nichols & Schwartz, 1998). Indeed, Bowen theory provides a foundation for the field of family therapy that renders i t distinct from the multitude of theoretica l approaches to individual psychotherapy. At present, many of Bowen's (1976, 1978) concepts (e.g., differentiation of self, interlocking triangles , o r reactiv e emotiona l distancing ) pervade th e famil y system s literature . Despit e th e vas t attention Bowen theory has received from clinicians and theorists alike, there have been, to date, few programmatic attempts t o tes t it s validit y wit h respec t t o personalit y functioning or quality of interpersonal relations or to changes as a result of psychotherapy. To begin filling this notable gap, we developed the Differentiation o f Self Inventory, a self-report instrument for adults (ages 25+). In this article, we present psychometric support for the measure, validation studies to date, and implications for theory, research, and practice.

Two-Level Linear Programming

Abstract: Decentralized planning has long been recognized as an important decision making problem. Many approaches based on the concepts of large-scale system decomposition have generally lacked the ability to model the type of truly independent subsystems which often exist in practice. Multilevel programming models partition control over decision variables among ordered levels within a hierarchical planning structure. A planner at one level of the hierarchy may have his objective function and set of feasible decisions determined, in part, by other levels. However, his control instruments may allow him to influence the policies at other levels and thereby improve his own objective function. This paper examines the special case of the two-level linear programming problem. Geometric characterizations and algorithms are presented with some examples. The goal is to demonstrate the tractability of such problems and motivate a wider interest in their study.