Yogis, Ayurveda, and Kayakalpa: The Rejuvenation of Pandit Malaviya

How should we read claims about health and well-being which defy common sense? Are claims of extreme longevity to be viewed as fraudulent, or as pushing the boundaries of possibility for the human body? This article will consider the narrative and context around a particularly well-publicized incident of rejuvenation therapy, advertised as kāyakalpa (body transformation or rejuvenation), from 1938. In this year, the prominent Congress Activist and co-founder of Banaras Hindu University, Madan Mohan Malaviya (1861–1946), underwent an extreme – and very public – rejuvenation treatment under the care of a sadhu using the name of Shriman Tapasviji (c.1770?-1955). The first half of the article will explore the presentation of Malaviya’s treatment and how it inspired a focus on rejuvenation therapy within Indian medicine in the years immediately following. Exploring this mid-twentieth century incident highlight some of the themes and concerns of the historical period, just out of living memory, but in many ways similar to our own

Rejuvenation and Memory in model Spin Glasses in 3 and 4 dimensions

We numerically study aging for the Edwards-Anderson Model in 3 and 4 dimensions using different temperature-change protocols. In D=3, time scales a thousand times larger than in previous work are reached with the SUE machine. Deviations from cumulative aging are observed in the non monotonic time behavior of the coherence length. Memory and rejuvenation effects are found in a temperature-cycle protocol, revealed by vanishing effective waiting times. Similar effects are reported for the D=3$site-diluted ferromagnetic Ising model (without chaos). However, rejuvenation is reduced if off-equilibrium corrections to the fluctuation-dissipation theorem are considered. Memory and rejuvenation are quantitatively describable in terms of the growth regime of the spin-glass coherence length.Comment: Extended protocols. Accepted in Phys. Rev. B. 10 postscript figure

Aging after shear rejuvenation in a soft glassy colloidal suspension: evidence for two different regimes

The aging dynamics after shear rejuvenation in a glassy, charged clay suspension have been investigated through dynamic light scattering (DLS). Two different aging regimes are observed: one is attained if the sample is rejuvenated before its gelation and one after the rejuvenation of the gelled sample. In the first regime, the application of shear fully rejuvenates the sample, as the system dynamics soon after shear cessation follow the same aging evolution characteristic of normal aging. In the second regime, aging proceeds very fast after shear rejuvenation, and classical DLS cannot be used. An original protocol to measure an ensemble averaged intensity correlation function is proposed and its consistency with classical DLS is verified. The fast aging dynamics of rejuvenated gelled samples exhibit a power law dependence of the slow relaxation time on the waiting time.Comment: 7 pages, 6 figure

Semi-independent resampling for particle filtering

Among Sequential Monte Carlo (SMC) methods,Sampling Importance Resampling (SIR) algorithms are based on Importance Sampling (IS) and on some resampling-based)rejuvenation algorithm which aims at fighting against weight degeneracy. However %whichever the resampling technique used this mechanism tends to be insufficient when applied to informative or high-dimensional models. In this paper we revisit the rejuvenation mechanism and propose a class of parameterized SIR-based solutions which enable to adjust the tradeoff between computational cost and statistical performances

A real space renormalization group approach to spin glass dynamics

The slow non-equilibrium dynamics of the Edwards-Anderson spin glass model on a hierarchical lattice is studied by means of a coarse-grained description based on renormalization concepts. We evaluate the isothermal aging properties and show how the occurrence of temperature chaos is connected to a gradual loss of memory when approaching the overlap length. This leads to rejuvenation effects in temperature shift protocols and to rejuvenation--memory effects in temperature cycling procedures with a pattern of behavior parallel to experimental observations.Comment: 4 pages, 4 figure

Software Aging Analysis of Web Server Using Neural Networks

Software aging is a phenomenon that refers to progressive performance degradation or transient failures or even crashes in long running software systems such as web servers. It mainly occurs due to the deterioration of operating system resource, fragmentation and numerical error accumulation. A primitive method to fight against software aging is software rejuvenation. Software rejuvenation is a proactive fault management technique aimed at cleaning up the system internal state to prevent the occurrence of more severe crash failures in the future. It involves occasionally stopping the running software, cleaning its internal state and restarting it. An optimized schedule for performing the software rejuvenation has to be derived in advance because a long running application could not be put down now and then as it may lead to waste of cost. This paper proposes a method to derive an accurate and optimized schedule for rejuvenation of a web server (Apache) by using Radial Basis Function (RBF) based Feed Forward Neural Network, a variant of Artificial Neural Networks (ANN). Aging indicators are obtained through experimental setup involving Apache web server and clients, which acts as input to the neural network model. This method is better than existing ones because usage of RBF leads to better accuracy and speed in convergence.Comment: 11 pages, 8 figures, 1 table; International Journal of Artificial Intelligence & Applications (IJAIA), Vol.3, No.3, May 201

Skeletal muscle as an experimental model of choice to study tissue aging and rejuvenation.

Skeletal muscle is among the most age-sensitive tissues in mammal organisms. Significant changes in its resident stem cells (i.e., satellite cells, SCs), differentiated cells (i.e., myofibers), and extracellular matrix cause a decline in tissue homeostasis, function, and regenerative capacity. Based on the conservation of aging across tissues and taking advantage of the relatively well-characterization of the myofibers and associated SCs, skeletal muscle emerged as an experimental system to study the decline in function and maintenance of old tissues and to explore rejuvenation strategies. In this review, we summarize the approaches for understanding the aging process and for assaying the success of rejuvenation that use skeletal muscle as the experimental system of choice. We further discuss (and exemplify with studies of skeletal muscle) how conflicting results might be due to variations in the techniques of stem cell isolation, differences in the assays of functional rejuvenation, or deciding on the numbers of replicates and experimental cohorts

Tet2 Rescues Age-Related Regenerative Decline and Enhances Cognitive Function in the Adult Mouse Brain.

Restoring adult stem cell function provides an exciting approach for rejuvenating the aging brain. However, molecular mechanisms mediating neurogenic rejuvenation remain elusive. Here we report that the enzyme ten eleven translocation methylcytosine dioxygenase 2 (Tet2), which catalyzes the production of 5-hydroxymethylcytosine (5hmC), rescues age-related decline in adult neurogenesis and enhances cognition in mice. We detected a decrease in Tet2 expression and 5hmC levels in the aged hippocampus associated with adult neurogenesis. Mimicking an aged condition in young adults by abrogating Tet2 expression within the hippocampal neurogenic niche, or adult neural stem cells, decreased neurogenesis and impaired learning and memory. In a heterochronic parabiosis rejuvenation model, hippocampal Tet2 expression was restored. Overexpressing Tet2 in the hippocampal neurogenic niche of mature adults increased 5hmC associated with neurogenic processes, offset the precipitous age-related decline in neurogenesis, and enhanced learning and memory. Our data identify Tet2 as a key molecular mediator of neurogenic rejuvenation