Detection Limit for Optically Sensing Specific Protein Interactions in Free-solution

Optical molecular sensing techniques are often limited by the refractive index change associated with the probed interactions. In this work, we present a closed form analytical model to estimate the magnitude of optical refractive index change arising from protein-protein interactions. The model, based on the Maxwell Garnett effective medium theory and first order chemical kinetics serves as a general framework for estimating the detection limits of optical sensing of molecular interactions. The model is applicable to situations where one interacting species is immobilized to a surface, as commonly done, or to emerging techniques such as Back-Scattering Interferometry (BSI) where both interacting species are un-tethered. Our findings from this model point to the strong role of as yet unidentified factors in the origin of the BSI signal resulting in significant deviation from linear optical response.Comment: 7 Page Manuscript + 14 Page Supplementary Informatio

Addressing the Node Discovery Problem in Fog Computing

In recent years, the Internet of Things (IoT) has gained a lot of attention due to connecting various sensor devices with the cloud, in order to enable smart applications such as: smart traffic management, smart houses, and smart grids, among others. Due to the growing popularity of the IoT, the number of Internet-connected devices has increased significantly. As a result, these devices generate a huge amount of network traffic which may lead to bottlenecks, and eventually increase the communication latency with the cloud. To cope with such issues, a new computing paradigm has emerged, namely: fog computing. Fog computing enables computing that spans from the cloud to the edge of the network in order to distribute the computations of the IoT data, and to reduce the communication latency. However, fog computing is still in its infancy, and there are still related open problems. In this paper, we focus on the node discovery problem, i.e., how to add new compute nodes to a fog computing system. Moreover, we discuss how addressing this problem can have a positive impact on various aspects of fog computing, such as fault tolerance, resource heterogeneity, proximity awareness, and scalability. Finally, based on the experimental results that we produce by simulating various distributed compute nodes, we show how addressing the node discovery problem can improve the fault tolerance of a fog computing system

Count-Based Exploration in Feature Space for Reinforcement Learning

We introduce a new count-based optimistic exploration algorithm for Reinforcement Learning (RL) that is feasible in environments with high-dimensional state-action spaces. The success of RL algorithms in these domains depends crucially on generalisation from limited training experience. Function approximation techniques enable RL agents to generalise in order to estimate the value of unvisited states, but at present few methods enable generalisation regarding uncertainty. This has prevented the combination of scalable RL algorithms with efficient exploration strategies that drive the agent to reduce its uncertainty. We present a new method for computing a generalised state visit-count, which allows the agent to estimate the uncertainty associated with any state. Our \phi-pseudocount achieves generalisation by exploiting same feature representation of the state space that is used for value function approximation. States that have less frequently observed features are deemed more uncertain. The \phi-Exploration-Bonus algorithm rewards the agent for exploring in feature space rather than in the untransformed state space. The method is simpler and less computationally expensive than some previous proposals, and achieves near state-of-the-art results on high-dimensional RL benchmarks.Comment: Conference: Twenty-sixth International Joint Conference on Artificial Intelligence (IJCAI-17), 8 pages, 1 figur

Labour Cost and Export Behaviour of Firms in Indian Textile and Clothing Industry

The implementation of the Agreement on Textile and Clothing (ATC) of the World Trade Organization (WTO) renders both threats and opportunities to India’s Textile and Clothing (T&C) industry in the wake of liberal international trade in the sector. Firms acquire greater international competitiveness through various cost cutting and efficiency enhancing strategies. The question we try to ponder on is, what route does Indian firms take to join the international export market in T&C. Empirical analysis, using Tobit estimation techniques, supported the view that increasing the share of low cost labour was an important route through which export performance of the Indian firms in T&C was enhanced. Further, the use of this means to perform better in the international market aggravated in the period after the implementation of the ATC. On the other hand, capital and technology based factors did not have any perceptive effect on the export performance of Indian firms in the international market. This endorses the view that the Indian T&C firms by and large utilized the low road to competitiveness, rather than the other. Also the importance of the import intensity in export performance suggests that Indian T&C is increasingly getting integrated within the global value chain.Export performance; Textile and clothing industry; Labour cost; Tobit Model; Agreement on Textile and Clothing

Radiation and non-​Darcy effects on convection in porous media

Combined conduction , convection and radiation heat transfer in a gray fluid-​satd. sparsely packed porous medium is analyzed for the case of marginal convection by using linear stability anal. The effects of boundaries and inertia that are absent in the usual Darcy model are considered. The Milne-​Eddington approxn. is employed to det. the solns. valid for transparent and opaque media that absorb and emit thermal radiation. The nature of the bounding surfaces and radiation affect the crit. Rayleigh and wave nos. The mechanism for suppressing or augmenting convection is discussed. The results obtained by using the Galerkin technique are compared with the existing results of the Darcy model and of nonradiating systems, and agreement is found

Effect of packing density and habitat material on the survival and duration of Penaeus indicus post larvae during oxygen-packed transportation.

The survival and duration of the Indian white shrimp. Penaeus indicus postlarvae (PL.) packed with oxygen under uniform water quality conditions were studied at packing densities of 200,300,400 and 500PL/L. with and without habitat material which was in the form of hollow 10-15 mm bits of transluscent plastic straw at a ratio of 1 bit: 2 PL. The effect of packing density on the cumulative percentage survival was significant. The duration of obtaining 100% survival which was taken as the 'safe duration of transport' was significantly different at all the packing densities tried