A self-learning rule base for command following in dynamical systems

In this paper, a self-learning Rule Base for command following in dynamical systems is presented. The learning is accomplished though reinforcement learning using an associative memory called SAM. The main advantage of SAM is that it is a function approximator with explicit storage of training samples. A learning algorithm patterned after the dynamic programming is proposed. Two artificially created, unstable dynamical systems are used for testing, and the Rule Base was used to generate a feedback control to improve the command following ability of the otherwise uncontrolled systems. The numerical results are very encouraging. The controlled systems exhibit a more stable behavior and a better capability to follow reference commands. The rules resulting from the reinforcement learning are explicitly stored and they can be modified or augmented by human experts. Due to overlapping storage scheme of SAM, the stored rules are similar to fuzzy rules

Intimate Partner Violence and Population Mental Health: Why Poverty and Gender Inequities Matter

Alexander Tsai discusses a new research study by Karen Devries and colleagues, and comments on the possible impact on public health of the study's insights regarding the relationship between intimate partner violence and mental health

Mental health spillovers and the Millennium Development Goals: The case of perinatal depression in Khayelitsha, South Africa

Mental illness currently ranks among the top ten causes of burden of disease in low-income countries. In the African region specifically, neuropsychiatric disorders account for approximately 5% of disability-adjusted life years lost, with nearly one-quarter of this burden attributable to unipolar depressive disorders

A Simple Model for Deglacial Meltwater Pulses

Evidence from radiocarbon dating and complex ice sheet modeling suggests that the fastest rate of sea level rise in Earth's recent history coincided with collapse of the ice saddle between the Laurentide and Cordilleran ice sheets during the last deglaciation. In this study, we derive a simple, two‐equation model of two ice sheets intersecting in an ice saddle. We show that two conditions are necessary for producing the acceleration in ice sheet melt associated with meltwater pulses: the positive height‐mass balance feedback and an ice saddle geometry. The amplitude and timing of meltwater pulses is sensitively dependent on the rate of climate warming during deglaciation and the relative size of ice sheets undergoing deglaciation. We discuss how simulations of meltwater pulses can be improved and the prospect for meltwater pulses under continued climate warming

Nano-Pervaporation Membrane with Heat Exchanger Generates Medical-Grade Water

A nanoporous membrane is used for the pervaporation process in which potable water is maintained, at atmospheric pressure, on the feed side of the membrane. The water enters the non-pervaporation (NPV) membrane device where it is separated into two streams -- retentate water and permeated water. The permeated pure water is removed by applying low vapor pressure on the permeate side to create water vapor before condensation. This permeated water vapor is subsequently condensed by coming in contact with the cool surface of a heat exchanger with heat being recovered through transfer to the feed water stream

HDAC2 expression in parvalbumin interneurons regulates synaptic plasticity in the mouse visual cortex

An experience-dependent postnatal increase in GABAergic inhibition in the visual cortex is important for the closure of a critical period of enhanced synaptic plasticity. Although maturation of the subclass of parvalbumin (Pv)-expressing GABAergic interneurons is known to contribute to critical period closure, the role of epigenetics on cortical inhibition and synaptic plasticity has not been explored. The transcription regulator, histone deacetylase 2 (HDAC2), has been shown to modulate synaptic plasticity and learning processes in hippocampal excitatory neurons. We found that genetic deletion of HDAC2 specifically from Pv interneurons reduces inhibitory input in the visual cortex of adult mice and coincides with enhanced long-term depression that is more typical of young mice. These findings show that HDAC2 loss in Pv interneurons leads to a delayed closure of the critical period in the visual cortex and supports the hypothesis that HDAC2 is a key negative regulator of synaptic plasticity in the adult brain.National Institute of Neurological Diseases and Stroke (U.S.) (Grant NS078839)National Institute on Aging (Grant NS078839

Harnessing Poverty Alleviation to Reduce the Stigma of HIV in Sub-Saharan Africa

Alexander Tsai and colleagues highlight the complex relationship between poverty and HIV stigma in sub-Saharan Africa, and discuss possible ways to break the cycle. Please see later in the article for the Editors' Summar

Quantifying Bias in Measuring Insecticide-treated Bednet Use: Meta-analysis of Self-reported vs Objectively Measured Adherence

Background Insecticide-treated bednets (ITNs) are recommended for use by 3.4 billion people at risk of malaria world-wide. Policy makers rely on measurements of ITN use to optimize malaria prevention efforts. Self-reports are the most common means of assessing ITN use, but self-reports may be biased in a way that reduces their reliability as a proxy for ITN adherence. This meta-analysis compared self-reported and two methods which are more objective measures of ITN use to explore whether self-reports overestimate actual ITN adherence. Methods A comprehensive search of electronic databases and hand searching reference lists resulted in screening 2885 records and 202 articles were read in full. Sixteen articles with comparable data were chosen for the meta-analysis. Comparable data was defined as self-reported and objectively measured ITN use (observation of a mounted ITN or surprise visits confirming use) at the same unit of analysis, covering the same time period and same population. A random effects model was used to determine a weighted average risk difference between self-reported and objectively measured ITN use. Additional stratified analyses were conducted to explore study heterogeneity. Results Self-reported ITN use is 8 percentage points (95% confidence interval CI: 3 to 13) higher than objectively measured ITN use, representing a 13.6% overestimation relative to the proportion measured as adherent to ITN use by objective measures. Wide variations in the discrepancies between self-reports and objective measures were unable to be explained using stratified analyses of variables including location, year of publication, seasonality and others. Conclusions Self-reports overestimate ITN adherence relative to objectively measured ITN use by 13.6% and do so in an unpredictable manner that raises questions about the reliability of using self-reported ITN use alone as a surveillance tool and a guide for making policy decisions