Magnetic hysteresis loop shift in NiFe(2)O(4) nanocrystalline powder with large grain boundary fraction

Magnetic properties of nanocrystalline NiFe(2)O(4) spinel mechanically processed for 350 h have been studied using temperature dependent from both zero-field and in-field (57)Fe Mossbauer spectrometry and magnetization measurements. The hyperfine structure allows us to distinguish two main magnetic contributions: one attributed to the crystalline grain core, which has magnetic properties similar to the NiFe(2)O(4) spinel-like structure (n-NiFe(2)O(4)) and the other one due to the disordered grain boundary region, which presents topological and chemical disorder features(d-NiFe(2)O(4)). Mossbauer spectrometry determines a large fraction for the d-NiFe(2)O(4) region(62% of total area) and also suggests a speromagnet-like structure for it. Under applied magnetic field, the n-NiFe(2)O(4) spins are canted with angle dependent on the applied field magnitude. Mossbauer data also show that even under 120 kOe no magnetic saturation is observed for the two magnetic phases. In addition, the hysteresis loops, recorded for scan field of 50 kOe, are shifted in both field and magnetization axes, for temperatures below about 50 K. The hysteresis loop shifts may be due to two main contributions: the exchange bias field at the d-NiFe(2)O(4)/n-NiFe(2)O(4) interfaces and the minor loop effect caused by a high magnetic anisotropy of the d-NiFe(2)O(4) phase. It has also been shown that the spin configuration of the spin-glass like phase is modified by the consecutive field cycles, consequently the n-NiFe(2)O(4)/d-NiFe(2)O(4) magnetic interaction is also affected in this process. (C) 2010 Elsevier B.V. All rights reserved.

Single-step chemical synthesis of ferrite hollow nanospheres

We report a single-step chemical synthesis of iron oxide hollow nanospheres with 9.3 nm in diameter. The sample presents a narrow particle diameter distribution and chemical homogeneity. The hollow nature of the particles is confirmed by HRTEM and HAADF STEM analysis. Electron and x-ray diffraction show that the outer material component is constituted by 2 nm ferrite crystals. Mossbauer data provide further evidence for the formation of iron oxide with high structural disorder, magnetically ordered at 4.2 K and superparamagnetism at room temperature. An unusual magnetic behavior under an applied field is reported, which can be explained by the large fraction of atoms existing at both inner and outer surfaces.

A novel MAP-MRF approach for multispectral image contextual classification using combination of suboptimal iterative algorithms

In this paper we present a novel approach for multispectral image contextual classification by combining iterative combinatorial optimization algorithms. The pixel-wise decision rule is defined using a Bayesian approach to combine two MRF models: a Gaussian Markov Random Field (GMRF) for the observations (likelihood) and a Potts model for the a priori knowledge, to regularize the solution in the presence of noisy data. Hence, the classification problem is stated according to a Maximum a Posteriori (MAP) framework. In order to approximate the MAP solution we apply several combinatorial optimization methods using multiple simultaneous initializations, making the solution less sensitive to the initial conditions and reducing both computational cost and time in comparison to Simulated Annealing, often unfeasible in many real image processing applications. Markov Random Field model parameters are estimated by Maximum Pseudo-Likelihood (MPL) approach, avoiding manual adjustments in the choice of the regularization parameters. Asymptotic evaluations assess the accuracy of the proposed parameter estimation procedure. To test and evaluate the proposed classification method, we adopt metrics for quantitative performance assessment (Cohen`s Kappa coefficient), allowing a robust and accurate statistical analysis. The obtained results clearly show that combining sub-optimal contextual algorithms significantly improves the classification performance, indicating the effectiveness of the proposed methodology. (C) 2010 Elsevier B.V. All rights reserved.

A Boolean algebra and a Banach space obtained by push-out iteration

Under the assumption that c is a regular cardinal, we prove the existence and uniqueness of a Boolean algebra B of size c defined by sharing the main structural properties that P(omega)/fin has under CH and in the N(2)-Cohen model. We prove a similar result in the category of Banach spaces. (C) 2011 Elsevier B.V. All rights reserved.

“Flipped Classroom” for Teaching Business Research in a Business Management Course

This presentation will report on a cross-department collaboration between the library and the business/economics department at Lehman College to conduct information literacy instruction as a “flipped classroom.”

The First Provenance Challenge

The first Provenance Challenge was set up in order to provide a forum for the community to understand the capabilities of different provenance systems and the expressiveness of their provenance representations. To this end, a Functional Magnetic Resonance Imaging workflow was defined, which participants had to either simulate or run in order to produce some provenance representation, from which a set of identified queries had to be implemented and executed. Sixteen teams responded to the challenge, and submitted their inputs. In this paper, we present the challenge workflow and queries, and summarise the participants contributions.

Levine Family Reunion Members, interviewed by Wendy Miller in September 2009: Transcript

The Levine family held an extensive reunion during the Summer of 2009 during which 29 DVDs of raw material were recorded for use in the creation of a Levine family mini-documentary. Many of these DVDs contain oral history interviews conducted by Wendy Miller, one of the organizers of the reunion. Although these interviews were not designed for historical research, they contain valuable historical information. Some of the family members interviewed include: Ben Arnon (4/5), Marjorie, Stephen, and Michael Kaplan (8), Glenyce Miller Kaplan (starts in 15, continues in 9; separate interview in 13), Burt, Phyllis, and Louis Shiro (9) [Burt Shiro also in 26/27], Myrt and Gordon Wolman (9), Ted and Billy Alfond (10), Barbara and Joan Alfond (10), Susan and Peter Alfond (10), Alice Emory [caregiver for Bibby] (11), Eric Bloom and Stu Cushner (11), Saralee Kaplan Bloom (11), Sarah Miller Arnon (12), Kayla and Jenna Cushner (12), Josh Soros and Eliana Miller-Kaplan (12), Sarah, Wendy, and Julie Miller (starts in 12, continues in 14), Bill Shutzer (13), Maschia and Glicka Kaplan, Sharon Kushner, Dan Hood (13), Gene, Alex, Kate Cohen (14), Ben, Jeremy, Joselyn Arnon (14), Wendy and Julie Miller at the store (15), and Eric Bloom (15).

Constructing a Structural Macroeconomic Model Using Multiple Techniques

This project constructs a structural model of the United States Economy. This task is tackled in two separate ways: first econometric methods and then using a neural network, both with a structure that mimics the structure of the U.S. economy. The structural model tracks the performance of U.S. GDP rather well in a dynamic simulation, with an average error of just over 1 percent. The neural network performed well, but suffered from some theoretical, as well as some implementation issues.