4,671 research outputs found

    Proteinopathy, oxidative stress and mitochondrial dysfunction: cross talk in alzheimer’s disease and parkinson’s disease

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    Alzheimer's disease and Parkinson's disease are two common neurodegenerative diseases of the elderly people that have devastating effects in terms of morbidity and mortality. The predominant form of the disease in either case is sporadic with uncertain etiology. The clinical features of Parkinson's disease are primarily motor deficits, while the patients of Alzheimer's disease present with dementia and cognitive impairment. Though neuronal death is a common element in both the disorders, the postmortem histopathology of the brain is very characteristic in each case and different from each other. In terms of molecular pathogenesis, however, both the diseases have a significant commonality, and proteinopathy (abnormal accumulation of misfolded proteins), mitochondrial dysfunction and oxidative stress are the cardinal features in either case. These three damage mechanisms work in concert, reinforcing each other to drive the pathology in the aging brain for both the diseases; very interestingly, the nature of interactions among these three damage mechanisms is very similar in both the diseases, and this review attempts to highlight these aspects. In the case of Alzheimer's disease, the peptide amyloid beta (A beta) is responsible for the proteinopathy, while alpha-synuclein plays a similar role in Parkinson's disease. The expression levels of these two proteins and their aggregation processes are modulated by reactive oxygen radicals and transition metal ions in a similar manner. In turn, these proteins - as oligomers or in aggregated forms - cause mitochondrial impairment by apparently following similar mechanisms. Understanding the common nature of these interactions may, therefore, help us to identify putative neuroprotective strategies that would be beneficial in both the clinical conditions

    Low Energy Nuclear Bursts of Cosmic Rays at Sea Level

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    Dynamics of magnetic modulation of ferrofluid droplets for digital microfluidic applications

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    Active control of droplet generation in a microfluidic platform attracts interest for development of digital microfluidic devices ranging from biosensors to micro-reactors to point-of-care diagnostic devices. The present paper characterizes, through an unsteady three-dimensional Volume of Fluid (VOF) simulation, the active control of ferrofluid droplet generation in a microfluidic T-junction in presence of a non-uniform magnetic field created by an external magnetic dipole. Two distinctly different positions of the dipole were considered – one upstream of the junction and one downstream. While keeping the ferrofluid flow rate fixed, a parametric variation of the continuous phase capillary number, dipole strength, and dipole position was carried out. Differences in the flow behaviour in terms of dripping or jetting and the droplet characteristics in terms of droplet formation time period and droplet size were studied. The existence of a threshold dipole strength, below which the magnetic force was not able to influence the flow behaviour, was identified. It was also observed that, for dipoles placed upstream of the junction, droplet formation was suppressed at some higher dipole strengths, and this value was found to increase with increasing capillary number. Droplet time period was also found to increase with increasing dipole strength, along with droplet size, i.e. an increase in droplet volume

    System-level Impact of Non-Ideal Program-Time of Charge Trap Flash (CTF) on Deep Neural Network

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    Learning of deep neural networks (DNN) using Resistive Processing Unit (RPU) architecture is energy-efficient as it utilizes dedicated neuromorphic hardware and stochastic computation of weight updates for in-memory computing. Charge Trap Flash (CTF) devices can implement RPU-based weight updates in DNNs. However, prior work has shown that the weight updates (V_T) in CTF-based RPU are impacted by the non-ideal program time of CTF. The non-ideal program time is affected by two factors of CTF. Firstly, the effects of the number of input pulses (N) or pulse width (pw), and secondly, the gap between successive update pulses (t_gap) used for the stochastic computation of weight updates. Therefore, the impact of this non-ideal program time must be studied for neural network training simulations. In this study, Firstly, we propose a pulse-train design compensation technique to reduce the total error caused by non-ideal program time of CTF and stochastic variance of a network. Secondly, we simulate RPU-based DNN with non-ideal program time of CTF on MNIST and Fashion-MNIST datasets. We find that for larger N (~1000), learning performance approaches the ideal (software-level) training level and, therefore, is not much impacted by the choice of t_gap used to implement RPU-based weight updates. However, for lower N (<500), learning performance depends on T_gap of the pulses. Finally, we also performed an ablation study to isolate the causal factor of the improved learning performance. We conclude that the lower noise level in the weight updates is the most likely significant factor to improve the learning performance of DNN. Thus, our study attempts to compensate for the error caused by non-ideal program time and standardize the pulse length (N) and pulse gap (t_gap) specifications for CTF-based RPUs for accurate system-level on-chip training

    Uranium series inequilibrium and the geochemical processes occurring on the surface of coastal sediments

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    Remarkable anomaly has been observed between U238 and U234 in the marine environment by a number of workers in the field. But little information is available regarding the U238^ U235 and U^^^ activities in coastal sediments. The present work deals with the ratio of the activities of U23</U238 and Ui35/U238 from the coastal sediments of the west coast of India from Bombay (19°N, 73°E) to the southern tip of India up to Kottilppad near Manavalakurichi (8°N, 77°E) in the monazite bearing area of Kerala State. The sediment samples are leached with ammonium carbonate solution so as not to attack the mineral core of the sediment and to get the leachable uranium activities from the surface of the particles. In all the sediment samples U234 activity is about 12 to 14% higher than the equilibrium value indicating that there is disequilibrium between U^^B and U^34. The U235/U238 activity ratios lie in the range of 0.045 to 0.048 thereby showing that there is no significant fractionation between 0^38 and U235

    Peculiarities of the hidden nonlinear supersymmetry of Poschl-Teller system in the light of Lame equation

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    A hidden nonlinear bosonized supersymmetry was revealed recently in Poschl-Teller and finite-gap Lame systems. In spite of the intimate relationship between the two quantum models, the hidden supersymmetry in them displays essential differences. In particular, the kernel of the supercharges of the Poschl-Teller system, unlike the case of Lame equation, includes nonphysical states. By means of Lame equation, we clarify the nature of these peculiar states, and show that they encode essential information not only on the original hyperbolic Poschl-Teller system, but also on its singular hyperbolic and trigonometric modifications, and reflect the intimate relation of the model to a free particle system.Comment: 10 pages, typos corrected; to appear in J. Phys.
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