Circuit design issues affecting present and future deep sub-micron ferroelectric random-access memories

Abstract

The basic architecture of ferroelectric memories (FeRAMs) is known to be very similar to that of DRAM. Consequently, many design issues for FeRAM are already known from DRAM and have been solved by applying prior DRAM solutions. However, there are also a number of issues that are unique to FeRAM. Often these issues become critical design problems that require innovative circuit-level solutions^[1]. This paper discusses some of the most relevant issues affecting present and future deep sub-micron FeRAMs. In addition, new problems that have to be solved for future FeRAMs are presented.     

The utility of the Revised NEO Personality Inventory in an outpatient, drug rehabilitation context.

This study evaluated the psychometric properties of the Revised NEO Personality Inventory (NEO–PI–R) in a mostly African American clinical sample and determined if these qualities provided useful information about their motivational characteristics that were germane to treatment. Eighty-two men and 50 women entered a 6-week outpatient drug rehabilitation program, completed the NEO–PI–R, and received counselor ratings of personality at admission. The 99 who finished the program completed a 2nd NEO–PI–R. Counselors provided ratings of treatment responsiveness. The cross-observer, cross-method, cross-time correlations indicated that the NEO–PI–R can be a useful tool for organizing clinical information about clients. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Agricultural research in flux : Experiments in university-industry ties

Dramatic advances in agricultural technology and management are changing the institutional structure of agricultural research in business, academia and government. A range of “experiments” aimed at improving the transfer of information from academia to industry are being run; some will work and some will not. Overall, these experiments are facilitating information exchange, and enhance—rather than pose a threat to—openness.     

Socioeconomic determinants of health. The contribution of nutrition to inequalities in health

Social class differences in health are seen at all ages, with lower socioeconomic groups having greater incidence of premature and low birthweight babies, heart disease, stroke, and some cancers in adults. Risk factors including lack of breast feeding, smoking, physical inactivity, obesity, hypertension, and poor diet are clustered in the lower socioeconomic groups. The diet of the lower socioeconomic groups provides cheap energy from foods such as meat products, full cream milk, fats, sugars, preserves, potatoes, and cereals but has little intake of vegetables, fruit, and wholewheat bread. This type of diet is lower in essential nutrients such as calcium, iron, magnesium, folate, and vitamin C than that of the higher socioeconomic groups. New nutritional knowledge on the protective role of antioxidants and other dietary factors suggests that there is scope for enormous health gain if a diet rich in vegetables, fruit, unrefined cereal, fish, and small quantities of quality vegetable oils could be more accessible to poor people.     

Melatonin administration does not affect isoproterenol-induced LVH.

Left ventricular hypertrophy (LVH), a common sequella of hypertension, is associated with increased incidence of sudden cardiac death. The study reported herein measured the effect of melatonin on the heart in the setting of direct cardiac myocyte stimulation with isoproterenol, thus minimizing the role of autonomic output from the suprachiasmatic nucleus (SCN) and clarifying the effect of melatonin on LVH, an outcome of chromic hypertensions. Results show that daily injections of high dosages of melatonin do not affect heart weight:body weight or heart weight:tibia length ratios in the setting of isoproterenol-induced hypertrophy, suggesting that the cardiovascular effects of melatonin observed by others are not due primarily to a direct effect of melatonin on cardiac myocytes but to another mechanism, possibly melatonin modulation of SCN output. Melatonin has no effect on isoproterenol-induced LVH, suggesting that its cardiovascular effects are not due to a direct effect on cardiac myocytes. Melatonin has been found to have a significant effect on hypertension; however, in this study, one effect of extended hypertension, cardiac hypertrophy, which can ultimately lead to cardiac failure, was not affected, even by very large doses of melatonin in a chemically induced hypertrophy mouse model. It has been suggested that the effect of melatonin on hypertension is comparable to common antihypertensive agents.     

Comparison of approximate solution methods for the solid phase diffusion equation in a porous electrode model

Approximation methods are often used in porous electrode models to eliminate the need to solve the local solid phase diffusion equation. These methods include Duhamel's superposition method, a diffusion length method and a polynomial approximation method which have long been used in the literature. The pseudo steady state (PSS) method is a method that has been used recently to develop a solution to the diffusion equation in a spherical particle with time dependent boundary conditions, but the PSS method has not been used in a porous electrode model. These methods are compared to each other in a dimensionless analysis study, and they are used in a porous electrode model to predict the discharge curves for a LiCoO₂ electrode. Simulation results presented here indicate that the PSS method or the high order polynomial method should be used in a porous electrode model to obtain accuracy and save computation time.     

Classification by ensembles from random partitions of high-dimensional data

A robust classification procedure is developed based on ensembles of classifiers, with each classifier constructed from a different set of predictors determined by a random partition of the entire set of predictors. The proposed methods combine the results of multiple classifiers to achieve a substantially improved prediction compared to the optimal single classifier. This approach is designed specifically for high-dimensional data sets for which a classifier is sought. By combining classifiers built from each subspace of the predictors, the proposed methods achieve a computational advantage in tackling the growing problem of dimensionality. For each subspace of the predictors, we build a classification tree or logistic regression tree. Our study shows, using four real data sets from different areas, that our methods perform consistently well compared to widely used classification methods. For unbalanced data, our approach maintains the balance between sensitivity and specificity more adequately than many other classification methods considered in this study.     

Spiritual Transcendence as a Predictor of Psychosocial Outcome From an Outpatient Substance Abuse Program.

Does the Spiritual Transcendence Scale (STS; R. L. Piedmont, 1999) predict psychosocial outcomes from an outpatient substance abuse program? Self-report data on symptoms, personality, and coping resources were obtained for 73 consecutive admissions (57 men and 16 women; ages 19-66 years) at intake and again from the 56 (47 men and 9 women) who completed treatment. Controlling for relevant demographic variables, pretreatment STS scores were significantly related to self-ratings at posttreatment. The STS predicted treatment outcomes over and above the contribution of the five-factor model of personality. Significant partial correlations between pretreatment STS scores and therapist ratings of treatment outcome were also obtained. Spiritual Transcendence, especially the facets of Universality and Connectedness, appears to play a significant role in substance abuse recovery. (PsycINFO Database Record (c) 2010 APA, all rights reserved)