Geomorphology reveals active decollement geometry in the central Himalayan seismic gap

The similar to 700-km-long ``central seismic gap'' is the most prominent segment of the Himalayan front not to have ruptured in a major earthquake during the last 200-500 yr. This prolonged seismic quiescence has led to the proposition that this region, with a population >10 million, is overdue for a great earthquake. Despite the region's recognized seismic risk, the geometry of faults likely to host large earthquakes remains poorly understood. Here, we place new constraints on the spatial distribution of rock uplift within the western similar to 400 km of the central seismic gap using topographic and river profile analyses together with basinwide erosion rate estimates from cosmogenic Be-10. The data sets show a distinctive physiographic transition at the base of the high Himalaya in the state of Uttarakhand, India, characterized by abrupt strike-normal increases in channel steepness and a tenfold increase in erosion rates. When combined with previously published geophysical imaging and seismicity data sets, we interpret the observed spatial distribution of erosion rates and channel steepness to reflect the landscape response to spatially variable rock uplift due to a structurally coherent ramp-flat system of the Main Himalayan Thrust. Although it remains unresolved whether the kinematics of the Main Himalayan Thrust ramp involve an emergent fault or duplex, the landscape and erosion rate patterns suggest that the decollement beneath the state of Uttarakhand provides a sufficiently large and coherent fault segment capable of hosting a great earthquake.

Imaging cellular signalling: many `moving tales' in MAP kinase odyssey

Cellular signalling events are at the core of every adaptive response. Signalling events link environmental changes to physiological responses, consequently allowing cellular and organismal sustenance and survival. Classical approaches to study cellular signalling have relied on a variety of cell disruptive techniques which yield limited kinetic information, while the underlying events are much more complex. In this article, we discuss how modern live cell imaging microscopy has found increasing utilization in revealing spatio temporal dynamics of various signalling pathways. Utilizing the well studied mitogen-activated protein kinase (MAPK) signalling cascade as a template, the design, construction and utilization of `mobile' (translocation proficient) biosensors, suitable for studying MAPK signalling in living cells are described in detail. Experimental setup and results obtained from these biosensors, based on different proteins involved in the MAPK signalling cascade, have been described along with the setup of a microscope optimal for live cell imaging applications. Utilizing the ability to activate or deactivate signalling pathways using defined activators and specific pharmacological inhibitors, we also show how these sensors can yield unique spatial and temporal kinetic information of signalling in living cells.

Seismic intensity map of South India for estimated future earthquakes

In this study, an attempt has been made to prepare the seismic intensity map for south India considering the probable earthquakes in the region. Anbazhagan et al. (Nat Hazards 60:1325-1345, 2012) have identified eight probable future earthquake zones in south India based on rupture-based seismic hazard analysis. Anbazhagan et al. (Eng Geol 171:81-95, 2014) has estimated the maximum future earthquake magnitude at these eight zones using regional rupture character. In this study, the whole south India is divided into several grids of size 1(o) x 1(o) and the intensity at each grid point is calculated using the regional intensity model for the maximum earthquake magnitude at each of the eight zones. The intensity due to earthquakes at these zones is mapped and thus eight seismic intensity maps are prepared. The final seismic intensity map of south India is obtained by considering the maximum intensity at each grid point due to the estimated earthquakes. By looking at the seismic intensity map, one can expect slight to heavy damage due to the probable earthquake magnitudes. Heavy damage may happen close to the probable earthquake zones.

Intrinsic large gap quantum anomalous Hall insulators in LaX (X = Br,Cl,I)

We report a theoretical prediction of a new class of bulk and intrinsic quantum anomalous Hall (QAH) insulators LaX (X=Br, Cl, and I) via relativistic first-principles calculations. We find that these systems are innate long-ranged ferromagnets which, with the help of intrinsic spin-orbit coupling, become QAH insulators. A low-energy multiband tight-binding model is developed to understand the origin of the QAH effect. Finally, integer Chern number is obtained via Berry phase computation for each two-dimensional plane. These materials have the added benefit of a sizable band gap of as large as similar to 25 meV, with the flexibility of enhancing it to above 75 meV via strain engineering. The synthesis of LaX materials will provide the impurity-free single crystals and thin-film QAH insulators for versatile experiments and functionalities.

Photometric metallicity map of the Large Magellanic Cloud

We have estimated a metallicity map of the Large Magellanic Cloud (LMC) using the Magellanic Cloud Photometric Survey (MCPS) and Optical Gravitational Lensing Experiment (OGLE III) photometric data. This is a first of its kind map of metallicity up to a radius of 4 degrees-5 degrees, derived using photometric data and calibrated using spectroscopic data of Red Giant Branch (RGB) stars. We identify the RGB in the V, (V - I) colour-magnitude diagrams of small subregions of varying sizes in both data sets. We use the slope of the RGB as an indicator of the average metallicity of a subregion, and calibrate the RGB slope to metallicity using spectroscopic data for field and cluster red giants in selected subregions. The average metallicity of the LMC is found to be Fe/H] = -0.37 dex (sigmaFe/H] = 0.12) from MCPS data, and Fe/H] = -0.39 dex (sigmaFe/H] = 0.10) from OGLE III data. The bar is found to be the most metal-rich region of the LMC. Both the data sets suggest a shallow radial metallicity gradient up to a radius of 4 kpc (-0.049 +/- 0.002 dex kpc(-1) to -0.066 +/- 0.006 dex kpc(-1)). Subregions in which the mean metallicity differs from the surrounding areas do not appear to correlate with previously known features; spectroscopic studies are required in order to assess their physical significance.

SYNGAP1: Mind the Gap

A cardinal feature of early stages of human brain development centers on the sensory, cognitive, and emotional experiences that shape neuronal-circuit formation and refinement. Consequently, alterations in these processes account for many psychiatric and neurodevelopmental disorders. Neurodevelopment disorders affect 3-4% of the world population. The impact of these disorders presents a major challenge to clinicians, geneticists, and neuroscientists. Mutations that cause neurodevelopmental disorders are commonly found in genes encoding proteins that regulate synaptic function. Investigation of the underlying mechanisms using gain or loss of function approaches has revealed alterations in dendritic spine structure, function, and plasticity, consequently modulating the neuronal circuit formation and thereby raising the possibility of neurodevelopmental disorders resulting from synaptopathies. One such gene, SYNGAP1 (Synaptic Ras-GTPase-activating protein) has been shown to cause Intellectual Disability (ID) with comorbid Autism Spectrum Disorder (ASD) and epilepsy in children. SYNGAP1 is a negative regulator of Ras, Rap and of AMPA receptor trafficking to the postsynaptic membrane, thereby regulating not only synaptic plasticity, but also neuronal homeostasis. Recent studies on the neurophysiology of SYNGAP1, using Syngapl mouse models, have provided deeper insights into how downstream signaling proteins and synaptic plasticity are regulated by SYNGAP1. This knowledge has led to a better understanding of the function of SYNGAP1 and suggests a potential target during critical period of development when the brain is more susceptible to therapeutic intervention.

SYNGAP1: Mind the Gap

A cardinal feature of early stages of human brain development centers on the sensory, cognitive, and emotional experiences that shape neuronal-circuit formation and refinement. Consequently, alterations in these processes account for many psychiatric and neurodevelopmental disorders. Neurodevelopment disorders affect 3-4% of the world population. The impact of these disorders presents a major challenge to clinicians, geneticists, and neuroscientists. Mutations that cause neurodevelopmental disorders are commonly found in genes encoding proteins that regulate synaptic function. Investigation of the underlying mechanisms using gain or loss of function approaches has revealed alterations in dendritic spine structure, function, and plasticity, consequently modulating the neuronal circuit formation and thereby raising the possibility of neurodevelopmental disorders resulting from synaptopathies. One such gene, SYNGAP1 (Synaptic Ras-GTPase-activating protein) has been shown to cause Intellectual Disability (ID) with comorbid Autism Spectrum Disorder (ASD) and epilepsy in children. SYNGAP1 is a negative regulator of Ras, Rap and of AMPA receptor trafficking to the postsynaptic membrane, thereby regulating not only synaptic plasticity, but also neuronal homeostasis. Recent studies on the neurophysiology of SYNGAP1, using Syngapl mouse models, have provided deeper insights into how downstream signaling proteins and synaptic plasticity are regulated by SYNGAP1. This knowledge has led to a better understanding of the function of SYNGAP1 and suggests a potential target during critical period of development when the brain is more susceptible to therapeutic intervention.

Spatio-temporal Map Formation Based on a Potential Function

We revisit the problem of temporal self organization using activity diffusion based on the neural gas (NGAS) algorithm. Using a potential function formulation motivated by a spatio-temporal metric, we derive an adaptation rule for dynamic vector quantization of data. Simulations results show that our algorithm learns the input distribution and time correlation much faster compared to the static neural gas method over the same data sequence under similar training conditions.

Visualisation of charge-transfer excitations in donor-acceptor molecules using the particle-hole map: a case study

Charge-transfer (CT) excitations are essential for photovoltaic phenomena in organic solar cells. Owing to the complexity of molecular geometries and orbital coupling, a detailed analysis and spatial visualisation of CT processes can be challenging. In this paper, a new detail-oriented visualisation scheme, the particle-hole map (PHM), is applied and explained for the purpose of spatial analysis of excitations in organic molecules. The PHM can be obtained from the output of a time-dependent density-functional theory calculation with negligible additional computational cost, and provides a useful physical picture for understanding the origins and destinations of electrons and holes during an excitation process. As an example, we consider intramolecular CT excitations in Diketopyrrolopyrrole-based molecules, and relate our findings to experimental results.