Soft Carrier Multiplications by Hot Electrons in Graphene

By using Boltzmann formalism, we show that carrier multiplication by impact ionization can take place at relatively low electric fields during electronic transport in graphene. Because of the absence of energy gap, this effect is not characterized by a field threshold unlike in conventional semiconductors, but is a quadratic function of the electric field. We also show that the resulting current is an increasing function of the electronic temperature, but decreases with increasing carrier concentration

3D Depthwise Convolution: Reducing Model Parameters in 3D Vision Tasks

Standard 3D convolution operations require much larger amounts of memory and computation cost than 2D convolution operations. The fact has hindered the development of deep neural nets in many 3D vision tasks. In this paper, we investigate the possibility of applying depthwise separable convolutions in 3D scenario and introduce the use of 3D depthwise convolution. A 3D depthwise convolution splits a single standard 3D convolution into two separate steps, which would drastically reduce the number of parameters in 3D convolutions with more than one order of magnitude. We experiment with 3D depthwise convolution on popular CNN architectures and also compare it with a similar structure called pseudo-3D convolution. The results demonstrate that, with 3D depthwise convolutions, 3D vision tasks like classification and reconstruction can be carried out with more light-weighted neural networks while still delivering comparable performances.Comment: Work in progres

Establishing the impact of luminous AGN with multi-wavelength observations and simulations

Cosmological simulations fail to reproduce realistic galaxy populations without energy injection from active galactic nuclei (AGN) into the interstellar medium (ISM) and circumgalactic medium (CGM); a process called `AGN feedback'. Consequently, observational work searches for evidence that luminous AGN impact their host galaxies. Here, we review some of this work. Multi-phase AGN outflows are common, some with potential for significant impact. Additionally, multiple feedback channels can be observed simultaneously; e.g., radio jets from `radio quiet' quasars can inject turbulence on ISM scales, and displace CGM-scale molecular gas. However, caution must be taken comparing outflows to simulations (e.g., kinetic coupling efficiencies) to infer feedback potential, due to a lack of comparable predictions. Furthermore, some work claims limited evidence for feedback because AGN live in gas-rich, star-forming galaxies. However, simulations do not predict instantaneous, global impact on molecular gas or star formation. The impact is expected to be cumulative, over multiple episodes.Comment: Accepted for publication in IAU Symposium 378 Conference Proceedings "Black Hole Winds at all Scales

Improvement of Grazing Lands for Better Livestock Production--A Case Study from Chitradurga District in India

Chitradurga is a highly drought prone district in the central dry zone of Karnataka, India, with a normal rainfall of 530 mm per annum. Over 85 per cent of cultivable area is rainfed and the livestock plays a vital role in rural income generation in this district. Improper management and overgrazing have resulted in most of the grazing resources declining to a poor, degraded condition. Regeneration of pasture land was vital in the villages due to three reasons - a) people\u27s livelihood dependency on livestock was considerable b) small ruminants played a vital role for landless farmers and c) lack of adequate fodder was a prime factor for low livestock productivity. To improve the livelihood of livestock farmers, a few interventions were made under World Bank funded National Agricultural Innovation Project through consortium approach in 10 project villages. Frequent interactions were held with the local livestock farmers to discuss about the importance of increasing the fodder resources in the villages to improve the income and to sustain their livelihood. They realized the importance of fodder and came forward to take up cultivation of perennial fodders and also, for the revitalization of grazing lands, locally known as kavals. The primary survey in the villages indicated that about 90 to 96 per cent of the small ruminant holders are dependent on these common property grazing resources for the fodder needs. The High Level Panel of Experts on food security and nutrition, constituted by FAO, has emphasized the importance of extending appropriate technologies and inputs, providing the needed credit and ensuring assured and remunerative marketing opportunities to the smallholders (HLPE, 2013). Such measures are also essential for revitalizing the degraded grasslands in this region

Few-Shot Single-View 3-D Object Reconstruction with Compositional Priors

The impressive performance of deep convolutional neural networks in single-view 3D reconstruction suggests that these models perform non-trivial reasoning about the 3D structure of the output space. However, recent work has challenged this belief, showing that complex encoder-decoder architectures perform similarly to nearest-neighbor baselines or simple linear decoder models that exploit large amounts of per category data in standard benchmarks. On the other hand settings where 3D shape must be inferred for new categories with few examples are more natural and require models that generalize about shapes. In this work we demonstrate experimentally that naive baselines do not apply when the goal is to learn to reconstruct novel objects using very few examples, and that in a \emph{few-shot} learning setting, the network must learn concepts that can be applied to new categories, avoiding rote memorization. To address deficiencies in existing approaches to this problem, we propose three approaches that efficiently integrate a class prior into a 3D reconstruction model, allowing to account for intra-class variability and imposing an implicit compositional structure that the model should learn. Experiments on the popular ShapeNet database demonstrate that our method significantly outperform existing baselines on this task in the few-shot setting

3D-printing: An emerging and a revolutionary technology in pharmaceuticals

© 2018 EDIZIONI MINERVA MEDICA. One of the novel and progressive technology employed in pharmaceutical manufacturing, design of medical device and tissue engineering is three-dimensional (3D) printing. 3D printing technologies provide great advantages in 3D scaffolds fabrication over traditional methods in the control of pore size, porosity, and interconnectivity. Various techniques of 3D-printing include powder bed fusion, fused deposition modeling, binder deposition, inkjet printing, photopolymerization and many others which are still evolving. 3D-printing technique been employed in developing immediate release products, various systems to deliver multiple release modalities etc. 3D printing has opened the door for new generation of customized drug delivery with built-in flexibility for safer and effective therapy. Our mini-review provides a quick snapshot on an overview of 3D printing, various techniques employed, applications and its advancements in pharmaceutical sciences

Evaluation of the IS6110 PCR assay for the rapid diagnosis of tuberculous meningitis

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