Implementation of Two-Dimensional Polycrystalline Grains in Object Oriented Micromagnetic Framework

In response to the growing need for a more accurate micromagnetic model to understand switching phenomenon in nanoscale magnets, we developed the capability to simulate two-dimensional polycrystalline grains using the Object Oriented Micromagnetic Framework (OOMMF). This addition allows users full flexibility in determining the magnetocrystalline anisotropy and axe in each grain as well as the inter- and intragranular exchange coupling strength.     

Design of a RFID case-based resource management system for warehouse operations

In the past, the selection of resources to execute various warehouse operation services was done solely by experts. In this paper, a RFID-based Resource Management System (RFID-RMS) is designed to help users to select the most suitable resource usage packages for handling warehouse operation orders by retrieving and analysing useful knowledge from a case-based data warehouse for solutions in both time saving and cost effective manner. In addition, a pure integral-linear programming model using a branch and bound algorithm to define the optimum travel distance of forklifts is also developed and embedded in the proposed system. The proposed system, which is suitable for usage in a warehouse operation environment, enhances the effectiveness in formulating resource usage package and managing resource operation by integrating the Radio Frequency Identification (RFID), case-based reasoning (CBR) technologies and the programming model for forklift route optimization. Through applying RFID-RMS in the GENCO Distribution System, a multinational logistics company, the utilization of warehouse resources is expected to be maximized while work efficiency will be greatly enhanced.     

GLLS for optimally sampled continuous dynamic system modeling: theory and algorithm

The original generalized linear least squares (GLLS) algorithm was developed for non-uniformly sampled biomedical system parameter estimation using finely sampled instantaneous measurements (D. Feng, S.C. Huang, Z. Wang, D. Ho, An unbiased parametric imaging algorithm for non-uniformly sampled biomedical system parameter estimation, IEEE Trans. Med. Imag. 15 (1996) 512-518). This algorithm is particularly useful for image-wide generation of parametric images with positron emission tomography (PET), as it is computationally efficient and statistically reliable (D. Feng, D. Ho, Chen, K., L.C. Wu, J.K. Wang, R.S. Liu, S.H. Yeh, An evaluation of the algorithms for determining local cerebral metabolic rates of glucose using positron emission tomography dynamic data, IEEE Trans. Med. Imag. 14 (1995) 697-710). However, when dynamic PET image data are sampled according to the optimal image sampling schedule (OISS) to reduce memory and storage space (X. Li, D. Feng, K. Chen, Optimal image sampling schedule: A new effective way to reduce dynamic image storage space and functional image processing time, IEEE Trans. Med. Imag. 15 (1996) 710-718), only a few temporal image frames are recorded (e.g. only four images are recorded for the four parameter fluoro-deoxy-glucose (FDG) model). These image frames are recorded in terms of accumulated radio-activity counts and as a result, the direct application of GLLS is not reliable as instantaneous measurement samples can no longer be approximated by averaging of accumulated measurements over the sampling intervals. In this paper, we extend GLLS to OISS-GLLS which deals with the fewer accumulated measurement samples obtained from OISS dynamic systems. The theory and algorithm of this new technique are formulated and studied extensively. To investigate statistical reliability and computational efficiency of OISS-GLLS, a simulation study using dynamic PET data was performed. OISS-GLLS using 4-measurement samples was compared to the non-linear least squares (NLS) method using 22-measurement samples, GLLS using 22-measurement samples and OISS-NLS using 4-measurement samples. Results demonstrated that OISS-GLLS was able to achieve parameter estimates of equivalent accuracy and reliability in comparison to NLS or GLLS using finely sampled measurements (22-measurement samples), or OISS-NLS using optimally sampled measurements (4-measurement samples). Further more, as fewer measurement samples are used in OISS-GLLS, this algorithm is computationally faster than NLS or GLLS. Therefore, OISS-GLLS is well-suited for image-wide parameter estimation when PET image data are recorded according to the optimal image sampling schedule.     

Screw-fastened joints for thermal contact at low temperatures

Electrical resistance measurements at 4.2 K on simple screw-fastened joints between two pieces of bare copper, between two pieces of gold-plated copper, and between two pieces of silver indicate the potential usefulness of such joints for thermal contact down to millikelvin temperatures.     

Novel lipidic enaminones from a C18 keto-allenic ester

Primary amines (ammonia, methyl, propyl, octyl, octadecyl, phenyl, benzyl, phenethyl) including methyl esters of amino acids (glycine, dl-alanine, l-valine, l-leucine, L-tyrosine, and l-methionine), and secondary amines (dimethyl, diethyl, dipropyl, diisopropyl, dioctyl, and diphenyl) attack regiospecifically the central carbon atom of the allene system of methyl 12-keto-9,10-octadecadienoate (1) to give the corresponding lipidic enaminone derivatives (2–21) with an average yield of 77%. The E- and Z-configuration of the enaminone system of these novel lipid derivatives was confirmed by infrared and nuclear magnetic resonance spectroscopic techniques. Primary amines furnished Z-enaminones, while secondary amines gave E-enaminones.     

Genetic and environmental influences on interpersonal cognitions and associations with depressive symptoms in 8-year-old twins.

Less is known about depression in children than in adults. This study integrates fields by combining cognitive and interpersonal research investigating childhood depression symptoms through the use of a genetic framework. Three research questions are addressed. First, what are the associations among interpersonal cognitions, anxiety, and depression? Second, what are the relative magnitudes of genetic and environmental influences on interpersonal cognitions? Third, to what extent do genetic and environmental influences explain associations between interpersonal cognitions and depression? Three hundred pairs of 8-year-old twins reported on symptoms of depression and anxiety by completing the Children's Depression Inventory and the Screen for Childhood Anxiety-Related Emotional Disorders. The authors examined interpersonal cognitions with the Children's Expectation of Social Behaviors and the Perceptions of Peers and Self Questionnaires. Interpersonal cognitions were more strongly correlated with depression (mean r = .35) than with anxiety (mean r = .13). Genetic influence on interpersonal cognitions was small (M = 3%), and associations between interpersonal cognitions and depression were mainly explained by environmental influences. These latter findings may result from interpersonal cognitions in young children, reflecting life experiences as opposed to trait-like cognitive biases. (PsycINFO Database Record (c) 2010 APA, all rights reserved)