Some experiments on human memory and a new neural model

An associative memory with parallel architecture is presented. The neurons are modelled by perceptrons having only binary, rather than continuous valued input. To store m elements each having n features, m neurons each with n connections are needed. The n features are coded as an n-bit binary vector. The weights of the n connections that store the n features of an element has only two values -1 and 1 corresponding to the absence or presence of a feature. This makes the learning very simple and straightforward. For an input corrupted by binary noise, the associative memory indicates the element that is closest (in terms of Hamming distance) to the noisy input. In the case where the noisy input is equidistant from two or more stored vectors, the associative memory indicates two or more elements simultaneously. From some simple experiments performed on the human memory and also on the associative memory, it can be concluded that the associative memory presented in this paper is in some respect more akin to a human memory than a Hopfield model.

Composition tunable memory and threshold switching in Al20As xTe80− x semiconducting glasses

I-V studies indicate a composition dependent switching behavior (Memory or Threshold) in bulk Al20AsxTe80−x glasses, which is determined by the coordination and composition of aluminum. Investigations on temperature and thickness dependence of switching and structural studies on switched samples suggest thermal and electronic mechanisms of switching for the memory and threshold samples, respectively. The present results also show that these samples have a wider composition range of threshold behavior with lower threshold voltages compared to other threshold samples.

TURBULENT PUMPING OF MAGNETIC FLUX REDUCES SOLAR CYCLE MEMORY AND THUS IMPACTS PREDICTABILITY OF THE SUN'S ACTIVITY

Prediction of the Sun's magnetic activity is important because of its effect on space environment and climate. However, recent efforts to predict the amplitude of the solar cycle have resulted in diverging forecasts with no consensus. Yeates et al. have shown that the dynamical memory of the solar dynamo mechanism governs predictability, and this memory is different for advection- and diffusion-dominated solar convection zones. By utilizing stochastically forced, kinematic dynamo simulations, we demonstrate that the inclusion of downward turbulent pumping of magnetic flux reduces the memory of both advection- and diffusion-dominated solar dynamos to only one cycle; stronger pumping degrades this memory further. Thus, our results reconcile the diverging dynamo-model-based forecasts for the amplitude of solar cycle 24. We conclude that reliable predictions for the maximum of solar activity can be made only at the preceding minimum-allowing about five years of advance planning for space weather. For more accurate predictions, sequential data assimilation would be necessary in forecasting models to account for the Sun's short memory.

Design and Implementation of a Flexible and Memory Efficient Operating System for Sensor Nodes

Sensor network nodes exhibit characteristics of both embedded systems and general-purpose systems.A sensor network operating system is a kind of embedded operating system, but unlike a typical embedded operating system, sensor network operatin g system may not be real time, and is constrained by memory and energy constraints. Most sensor network operating systems are based on event-driven approach. Event-driven approach is efficient in terms of time and space.Also this approach does not require a separate stack for each execution context. But using this model, it is difficult to implement long running tasks, like cryptographic operations. A thread based computation requires a separate stack for each execution context, and is less efficient in terms of time and space. In this paper, we propose a thread based execution model that uses only a fixed number of stacks. In this execution model, the number of stacks at each priority level are fixed. It minimizes the stack requirement for multi-threading environment and at the same time provides ease of programming. We give an implementation of this model in Contiki OS by separating thread implementation from protothread implementation completely. We have tested our OS by implementing a clock synchronization protocol using it.

Primary Microcephaly Gene MCPH1 Shows Signatures of Tumor Suppressors and Is Regulated by miR-27a in Oral Squamous Cell Carcinoma

Mutations in the MCPH1 (microcephalin 1) gene, located at chromosome 8p23.1, result in two autosomal recessive disorders: primary microcephaly and premature chromosome condensation syndrome. MCPH1 has also been shown to be downregulated in breast, prostate and ovarian cancers, and mutated in 1/10 breast and 5/41 endometrial tumors, suggesting that it could also function as a tumor suppressor (TS) gene. To test the possibility of MCPH1 as a TS gene, we first performed LOH study in a panel of 81 matched normal oral tissues and oral squamous cell carcinoma (OSCC) samples, and observed that 14/71 (19.72%) informative samples showed LOH, a hallmark of TS genes. Three protein truncating mutations were identified in 1/15 OSCC samples and 2/5 cancer cell lines. MCPH1 was downregulated at both the transcript and protein levels in 21/41 (51.22%) and 19/25 (76%) OSCC samples respectively. A low level of MCPH1 promoter methylation was also observed in 4/40 (10%) tumor samples. We further observed that overexpression of MCPH1 decreased cellular proliferation, anchorage-independent growth in soft agar, cell invasion and tumor size in nude mice, indicating its tumor suppressive function. Using bioinformatic approaches and luciferase assay, we showed that the 3'-UTR of MCPH1 harbors two non-overlapping functional seed regions for miR-27a which negatively regulated its level. The expression level of miR-27a negatively correlated with the MCPH1 protein level in OSCC. Our study indicates for the first time that, in addition to its role in brain development, MCPH1 also functions as a tumor suppressor gene and is regulated by miR-27a.

A study on fear memory retrieval and REM sleep in maternal separation and isolation stressed rats

As rapid brain development occurs during the neonatal period, environmental manipulation during this period may have a significant impact on sleep and memory functions. Moreover, rapid eye movement (REM) sleep plays an important role in integrating new information with the previously stored emotional experience. Hence, the impact of early maternal separation and isolation stress (MS) during the stress hyporesponsive period (SHRP) on fear memory retention and sleep in rats were studied. The neonatal rats were subjected to maternal separation and isolation stress during postnatal days 5-7 (6 h daily/3 d). Polysomnographic recordings and differential fear conditioning was carried out in two different sets of rats aged 2 months. The neuronal replay during REM sleep was analyzed using different parameters. MS rats showed increased time in REM stage and total sleep period also increased. MS rats showed fear generalization with increased fear memory retention than normal control (NC). The detailed analysis of the local field potentials across different time periods of REM sleep showed increased theta oscillations in the hippocampus, amygdala and cortical circuits. Our findings suggest that stress during SHRP has sensitized the hippocampus amygdala cortical loops which could be due to increased release of corticosterone that generally occurs during REM sleep. These rats when subjected to fear conditioning exhibit increased fear memory and increased, fear generalization. The development of helplessness, anxiety and sleep changes in human patients, thus, could be related to the reduced thermal, tactile and social stimulation during SHRP on brain plasticity and fear memory functions. (C) 2014 Elsevier B.V. All rights reserved.

An efficient design of serial and parallel memory using Quantum dot cellular automata

Quantum cellular automata (QCA) is a new technology in the nanometer scale and has been considered as one of the alternative to CMOS technology. In this paper, we describe the design and layout of a serial memory and parallel memory, showing the layout of individual memory cells. Assuming that we can fabricate cells which are separated by 10nm, memory capacities of over 1.6 Gbit/cm2 can be achieved. Simulations on the proposed memories were carried out using QCADesigner, a layout and simulation tool for QCA. During the design, we have tried to reduce the number of cells as well as to reduce the area which is found to be 86.16sq mm and 0.12 nm2 area with the QCA based memory cell. We have also achieved an increase in efficiency by 40%.These circuits are the building block of nano processors and provide us to understand the nano devices of the future.

Stress-induced phase transformation and pseudo-elastic/pseudo-plastic recovery in intermetallic Ni-Al nanowires

Extensive molecular dynamics (MD) simulations have been performed in a B2-NiAl nanowire using an embedded atom method (EAM) potential. We show a stress induced B2 -> body-centered-tetragonal (BCT) phase transformation and a novel temperature and cross-section dependent pseudo-elastic/pseudo-plastic recovery from such an unstable BCT phase with a recoverable strain of similar to 30% as compared to 5-8% in polycrystalline materials. Such a temperature and cross-section dependent pseudo-elastic/pseudo-plastic strain recovery can be useful in various interesting applications of shape memory and strain sensing in nanoscale devices. Effects of size, temperature, and strain rate on the structural and mechanical properties have also been analyzed in detail. For a given size of the nanowire the yield stress of both the B2 and the BCT phases is found to decrease with increasing temperature, whereas for a given temperature and strain rate the yield stress of both the B2 and the BCT phase is found to increase with increase in the cross-sectional dimensions of the nanowire. A constant elastic modulus of similar to 80 GPa of the B2 phase is observed in the temperature range of 200-500 K for nanowires of cross-sectional dimensions in the range of 17.22-28.712 angstrom, whereas the elastic modulus of the BCT phase shows a decreasing trend with an increase in the temperature.

Technological-forecasting and research inputs in area of birth-control technology

Technological forecasting, defined as quantified probabilistic prediction of timings and degree of change in the technological parameters, capabilities desirability or needs at different times in the future, is applied to birth control technology (BCT) as a means of revealing the paths of most promising research through identifying the necessary points for breakthroughs. The present status of BCT in the areas of pills and the IUD, male contraceptives, immumological approaches, post-coital pills, abortion, sterilization, luteolytic agents, laser technologies, and control of the sex of the child, are each summarized and evaluated in turn. Fine mapping is done to identify the most potentially promising areas of BCT. These include efforts to make oral contraception easier, improvement of the design of the IUD, clinical evaluation of the male contraceptive danazol, the effecting of biochemical changes in the seminal fluid, and researching of immunological approaches and the effects of other new drugs such as prostaglandins. The areas that require immediate and large research inputs are oral contraception and the IUD. On the basis of population and technological forecasts, it is deduced that research efforts could most effectively aid countries like India through the immediate production of an oral contraceptive pill or IUD with long-lasting effects. Development of a pill for males or an immunization against pre gnancy would also have a significant impact. However, the major impediment to birth control programs to date is attitudes, which must be changed through education.