Learning a Unified Control Policy for Safe Falling

Being able to fall safely is a necessary motor skill for humanoids performing highly dynamic tasks, such as running and jumping. We propose a new method to learn a policy that minimizes the maximal impulse during the fall. The optimization solves for both a discrete contact planning problem and a continuous optimal control problem. Once trained, the policy can compute the optimal next contacting body part (e.g. left foot, right foot, or hands), contact location and timing, and the required joint actuation. We represent the policy as a mixture of actor-critic neural network, which consists of n control policies and the corresponding value functions. Each pair of actor-critic is associated with one of the n possible contacting body parts. During execution, the policy corresponding to the highest value function will be executed while the associated body part will be the next contact with the ground. With this mixture of actor-critic architecture, the discrete contact sequence planning is solved through the selection of the best critics while the continuous control problem is solved by the optimization of actors. We show that our policy can achieve comparable, sometimes even higher, rewards than a recursive search of the action space using dynamic programming, while enjoying 50 to 400 times of speed gain during online execution

Asymmetry to symmetry transition of Fano line-shape: Analytical derivation

An analytical derivation of Fano line-shape asymmetry ratio has been presented here for a general case. It is shown that Fano line-shape becomes less asymmetric as \q is increased and finally becomes completely symmetric in the limiting condition of q equal to infinity. Asymmetry ratios of Fano line-shapes have been calculated and are found to be in good consonance with the reported expressions for asymmetry ratio as a function of Fano parameter. Application of this derivation is also mentioned for explanation of asymmetry to symmetry transition of Fano line-shape in quantum confined silicon nanostructures.Comment: 3 figures, Latex files, Theoretica

Operational mesoscale atmospheric dispersion prediction using a parallel computing cluster

An operational atmospheric dispersion prediction system is implemented on a cluster supercomputer for Online Emergency Response at the Kalpakkam nuclear site. This numerical system constitutes a parallel version of a nested grid meso-scale meteorological model MM5 coupled to a random walk particle dispersion model FLEXPART. The system provides 48-hour forecast of the local weather and radioactive plume dispersion due to hypothetical airborne releases in a range of 100 km around the site. The parallel code was implemented on different cluster configurations like distributed and shared memory systems. A 16-node dual Xeon distributed memory gigabit ethernet cluster has been found sufficient for operational applications. The runtime of a triple nested domain MM5 is about 4h for a 24h forecast. The system had been operated continuously for a few months and results were ported on the IMSc home page. Initial and periodic boundary condition data for MM5 are provided by NCMRWF, New Delhi. An alternative source is found to be NCEP, USA. These two sources provide the input data to the operational models at different spatial and temporal resolutions using different assimilation methods. A comparative study on the results of forecast is presented using these two data sources for present operational use. Improvement is noticed in rainfall forecasts that used NCEP data, probably because of its high spatial and temporal resolution

Populating the swampland: the case of U(1)^496 and E_8 x U(1)^248

For d=10 N=1 SUGRA coupled to d=10 N=1 SYM, anomaly cancellation places severe constraints on the allowed gauge groups. Besides the ones known to appear in string theory, only U(1)^496 and E_8 x U(1)^248 are allowed. There are no known theories of quantum gravity that reduce in some limit to these two last supergravity theories, and in this note I present some evidence that those quantum theories might not exist. The first observation is that, upon compactification, requring that the quantum theory possesses a moduli space with finite volume typically implies the existence of singularities where the 4d gauge group is enhanced, but for these two theories that gauge enhancement is problematic from the 10d point of view. I also point out that while these four supergravity theories present repulson-type singularities, the known mechanism that repairs those singularities for the first two - the non-Abelian enhancon - is not available for the last two theories. In short, these two supergravity theories might be too Abelian for their own good.Comment: 12 page

Complexity without chaos: Plasticity within random recurrent networks generates robust timing and motor control

It is widely accepted that the complex dynamics characteristic of recurrent neural circuits contributes in a fundamental manner to brain function. Progress has been slow in understanding and exploiting the computational power of recurrent dynamics for two main reasons: nonlinear recurrent networks often exhibit chaotic behavior and most known learning rules do not work in robust fashion in recurrent networks. Here we address both these problems by demonstrating how random recurrent networks (RRN) that initially exhibit chaotic dynamics can be tuned through a supervised learning rule to generate locally stable neural patterns of activity that are both complex and robust to noise. The outcome is a novel neural network regime that exhibits both transiently stable and chaotic trajectories. We further show that the recurrent learning rule dramatically increases the ability of RRNs to generate complex spatiotemporal motor patterns, and accounts for recent experimental data showing a decrease in neural variability in response to stimulus onset

Disease progression in Plasmodium knowlesi malaria is linked to variation in invasion gene family members.

Emerging pathogens undermine initiatives to control the global health impact of infectious diseases. Zoonotic malaria is no exception. Plasmodium knowlesi, a malaria parasite of Southeast Asian macaques, has entered the human population. P. knowlesi, like Plasmodium falciparum, can reach high parasitaemia in human infections, and the World Health Organization guidelines for severe malaria list hyperparasitaemia among the measures of severe malaria in both infections. Not all patients with P. knowlesi infections develop hyperparasitaemia, and it is important to determine why. Between isolate variability in erythrocyte invasion, efficiency seems key. Here we investigate the idea that particular alleles of two P. knowlesi erythrocyte invasion genes, P. knowlesi normocyte binding protein Pknbpxa and Pknbpxb, influence parasitaemia and human disease progression. Pknbpxa and Pknbpxb reference DNA sequences were generated from five geographically and temporally distinct P. knowlesi patient isolates. Polymorphic regions of each gene (approximately 800 bp) were identified by haplotyping 147 patient isolates at each locus. Parasitaemia in the study cohort was associated with markers of disease severity including liver and renal dysfunction, haemoglobin, platelets and lactate, (r = ≥ 0.34, p =  <0.0001 for all). Seventy-five and 51 Pknbpxa and Pknbpxb haplotypes were resolved in 138 (94%) and 134 (92%) patient isolates respectively. The haplotypes formed twelve Pknbpxa and two Pknbpxb allelic groups. Patients infected with parasites with particular Pknbpxa and Pknbpxb alleles within the groups had significantly higher parasitaemia and other markers of disease severity. Our study strongly suggests that P. knowlesi invasion gene variants contribute to parasite virulence. We focused on two invasion genes, and we anticipate that additional virulent loci will be identified in pathogen genome-wide studies. The multiple sustained entries of this diverse pathogen into the human population must give cause for concern to malaria elimination strategists in the Southeast Asian region

Branch Mode Selection during Early Lung Development

Many organs of higher organisms, such as the vascular system, lung, kidney, pancreas, liver and glands, are heavily branched structures. The branching process during lung development has been studied in great detail and is remarkably stereotyped. The branched tree is generated by the sequential, non-random use of three geometrically simple modes of branching (domain branching, planar and orthogonal bifurcation). While many regulatory components and local interactions have been defined an integrated understanding of the regulatory network that controls the branching process is lacking. We have developed a deterministic, spatio-temporal differential-equation based model of the core signaling network that governs lung branching morphogenesis. The model focuses on the two key signaling factors that have been identified in experiments, fibroblast growth factor (FGF10) and sonic hedgehog (SHH) as well as the SHH receptor patched (Ptc). We show that the reported biochemical interactions give rise to a Schnakenberg-type Turing patterning mechanisms that allows us to reproduce experimental observations in wildtype and mutant mice. The kinetic parameters as well as the domain shape are based on experimental data where available. The developed model is robust to small absolute and large relative changes in the parameter values. At the same time there is a strong regulatory potential in that the switching between branching modes can be achieved by targeted changes in the parameter values. We note that the sequence of different branching events may also be the result of different growth speeds: fast growth triggers lateral branching while slow growth favours bifurcations in our model. We conclude that the FGF10-SHH-Ptc1 module is sufficient to generate pattern that correspond to the observed branching modesComment: Initially published at PLoS Comput Bio

Review on Shaka Varga w.s.r. to Bruhatrayee

The vegetables are grouped under Shaka Varga in Ayurvedic classics. The Bruhatrayees are the most important books of Ayurveda classics. They are Charaka Samhita, Sushruta Samhita and Astanga Hridaya/Astanga Sangraha. Most of the plants under Shaka Varga are of controversial botanical identity and some are unidentified. The Bruhatrayees included Shaka Varga under Ahara(food). The Shaka Varga includes Patra Shaka (leafy vegetables), Kanda Shaka (stem vegetables), Phala Shaka (vegetable fruits), Pushpa Shaka (flower vegetables) etc. Consumption of these vegetables helps to maintain the health in the healthy individual and helps in curing the diseases. Certain vegetables are Pathya (suitable) and Apathya (not suitable) for consumption. The vegetables are consumed for the nutrition and as the best calorie diet. The medicinal herbs are used in the small quantities and have huge medicinal properties. The present study is to review on the number of plants with their botanical identification and the Karma of Shaka Varga Dravyas (plants belonging to vegetable category) in Bruhatrayees

In silico-designed lignin peroxidase from Phanerochaete chrysosporium shows enhanced acid stability for depolymerization of lignin

Background: The lignin peroxidase isozyme H8 from the white-rot fungus Phanerochaete chrysosporium (LiPH8) demonstrates a high redox potential and can efficiently catalyze the oxidation of veratryl alcohol, as well as the degradation of recalcitrant lignin. However, native LiPH8 is unstable under acidic pH conditions. This characteristic is a barrier to lignin depolymerization, as repolymerization of phenolic products occurs simultaneously at neutral pH. Because repolymerization of phenolics is repressed at acidic pH, a highly acid-stable LiPH8 could accelerate the selective depolymerization of recalcitrant lignin. Results: The engineered LiPH8 was in silico designed through the structural superimposition of surface-active site-harboring LiPH8 from Phanerochaete chrysosporium and acid-stable manganese peroxidase isozyme 6 (MnP6) from Ceriporiopsis subvermispora. Effective salt bridges were probed by molecular dynamics simulation and changes to Gibbs free energy following mutagenesis were predicted, suggesting promising variants with higher stability under extremely acidic conditions. The rationally designed variant, A55R/N156E-H239E, demonstrated a 12.5-fold increased half-life under extremely acidic conditions, 9.9-fold increased catalytic efficiency toward veratryl alcohol, and a 7.8-fold enhanced lignin model dimer conversion efficiency compared to those of native LiPH8. Furthermore, the two constructed salt bridges in the variant A55R/N156E-H239E were experimentally confirmed to be identical to the intentionally designed LiPH8 variant using X-ray crystallography (PDB ID: 6A6Q). Conclusion: Introduction of strong ionic salt bridges based on computational design resulted in a LiPH8 variant with markedly improved stability, as well as higher activity under acidic pH conditions. Thus, LiPH8, showing high acid stability, will be a crucial player in biomass valorization using selective depolymerization of lignin