Porträt Johann Gottfried Tempel (Gutsbesitzer, Abgeordneter des Sächsischen Landtages 1857-1868), aufgenommen von Carl Engelmann in Dresden, um 1857/1858. Albuminpapier auf Karton; 9,8 x 6,1 cm
aus ...Papier in schwarzweiß, hoch
Portrait Johann Gottfried Temple (landowner, deputy of the Saxon Landtag 1857-1868), taken by Carl Engelmann in Dresden, circa 1857/1858. Albumin paper on cardboard; 9.8 x 6.1 cm
The fracture of polycrystalline graphene is explored by performing molecular dynamics simulations with realistic finite-grain-size models, emphasizing the role of grain boundary ends and junctions. ...The simulations reveal a ∼50% or more strength reduction due to the presence of the network of boundaries between polygonal grains, with cracks preferentially starting at the junctions. With a larger grain size, a surprising systematic decrease of tensile strength and failure strain is observed, while the elastic modulus rises. The observed crack localization and strength behavior are well-explained by a dislocation-pileup model, reminiscent of the Hall–Petch effect but coming from different underlying physics.
An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of ...the brain. One increasingly popular and successful approach is to take inspiration from inference and learning algorithms used in deep neural networks. However, the workhorse of deep learning, the gradient descent Gradient Back Propagation (BP) rule, often relies on the immediate availability of network-wide information stored with high-precision memory during learning, and precise operations that are difficult to realize in neuromorphic hardware. Remarkably, recent work showed that exact backpropagated gradients are not essential for learning deep representations. Building on these results, we demonstrate an event-driven random BP (eRBP) rule that uses an error-modulated synaptic plasticity for learning deep representations. Using a two-compartment Leaky Integrate & Fire (I&F) neuron, the rule requires only one addition and two comparisons for each synaptic weight, making it very suitable for implementation in digital or mixed-signal neuromorphic hardware. Our results show that using eRBP, deep representations are rapidly learned, achieving classification accuracies on permutation invariant datasets comparable to those obtained in artificial neural network simulations on GPUs, while being robust to neural and synaptic state quantizations during learning.
•Ti0.47V0.46Mn and Ti0.50V0.51Mn alloys were produced by arc melting.•Compositional differences led to different unit cell volumes for the C14 Laves phase.•Change in composition caused a significant ...change in plateau pressure and hysteresis.
Two Ti–V–Mn BCC-Laves phase alloys with the nominal composition Ti0.5V0.5±xMn (x=−0.04 and 0.01), were synthesised by arc melting. This compositional difference resulted in different compositions and unit cell volumes for the C14 Laves phase. Ti0.47V0.46Mn and Ti0.50V0.51Mn demonstrated reversible hydrogen sorption capacities of 1.53 and 1.56±0.05wt.% (at 120bar H2 at 303K) respectively, however, the change in composition results in a small change in the enthalpy of hydride decomposition, and a significant change in plateau pressure and hysteresis. This may allow for the plateau pressure to be tuned to meet the requirements of different solid-state hydrogen storage applications.
Polypeptide toxins have played a central part in understanding physiological and physiopathological functions of ion channels. In the field of pain, they led to important advances in basic research ...and even to clinical applications. Acid-sensing ion channels (ASICs) are generally considered principal players in the pain pathway, including in humans. A snake toxin activating peripheral ASICs in nociceptive neurons has been recently shown to evoke pain. Here we show that a new class of three-finger peptides from another snake, the black mamba, is able to abolish pain through inhibition of ASICs expressed either in central or peripheral neurons. These peptides, which we call mambalgins, are not toxic in mice but show a potent analgesic effect upon central and peripheral injection that can be as strong as morphine. This effect is, however, resistant to naloxone, and mambalgins cause much less tolerance than morphine and no respiratory distress. Pharmacological inhibition by mambalgins combined with the use of knockdown and knockout animals indicates that blockade of heteromeric channels made of ASIC1a and ASIC2a subunits in central neurons and of ASIC1b-containing channels in nociceptors is involved in the analgesic effect of mambalgins. These findings identify new potential therapeutic targets for pain and introduce natural peptides that block them to produce a potent analgesia.
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