Dual enzyme responsive microcapsules simulating an ``OR'' logic gate for biologically triggered drug delivery applications

Hollow microcapsules capable of disintegrating in response to dual biological stimuli have been synthesized from two FDA approved drug molecules. The capsules fabricated from protamine and chondroitin sulphate disintegrate in the presence of either trypsin or hyaluronidase enzymes, which are documented to be simultaneously over-expressed under some pathological conditions.

Gene expression programming-fuzzy logic method for crop type classification

Crop type classification using remote sensing data plays a vital role in planning cultivation activities and for optimal usage of the available fertile land. Thus a reliable and precise classification of agricultural crops can help improve agricultural productivity. Hence in this paper a gene expression programming based fuzzy logic approach for multiclass crop classification using Multispectral satellite image is proposed. The purpose of this work is to utilize the optimization capabilities of GEP for tuning the fuzzy membership functions. The capabilities of GEP as a classifier is also studied. The proposed method is compared to Bayesian and Maximum likelihood classifier in terms of performance evaluation. From the results we can conclude that the proposed method is effective for classification.

Delineation of seismic source zones based on seismicity parameters and probabilistic evaluation of seismic hazard using logic tree approach

The delineation of seismic source zones plays an important role in the evaluation of seismic hazard. In most of the studies the seismic source delineation is done based on geological features. In the present study, an attempt has been made to delineate seismic source zones in the study area (south India) based on the seismicity parameters. Seismicity parameters and the maximum probable earthquake for these source zones were evaluated and were used in the hazard evaluation. The probabilistic evaluation of seismic hazard for south India was carried out using a logic tree approach. Two different types of seismic sources, linear and areal, were considered in the present study to model the seismic sources in the region more precisely. In order to properly account for the attenuation characteristics of the region, three different attenuation relations were used with different weightage factors. Seismic hazard evaluation was done for the probability of exceedance (PE) of 10% and 2% in 50 years. The spatial variation of rock level peak horizontal acceleration (PHA) and spectral acceleration (Sa) values corresponding to return periods of 475 and 2500 years for the entire study area are presented in this work. The peak ground acceleration (PGA) values at ground surface level were estimated based on different NEHRP site classes by considering local site effects.

Interplay Between Optimal Selection Scheme, Selection Criterion, and Discrete Rate Adaptation in Opportunistic Wireless Systems

An opportunistic, rate-adaptive system exploits multi-user diversity by selecting the best node, which has the highest channel power gain, and adapting the data rate to selected node's channel gain. Since channel knowledge is local to a node, we propose using a distributed, low-feedback timer backoff scheme to select the best node. It uses a mapping that maps the channel gain, or, in general, a real-valued metric, to a timer value. The mapping is such that timers of nodes with higher metrics expire earlier. Our goal is to maximize the system throughput when rate adaptation is discrete, as is the case in practice. To improve throughput, we use a pragmatic selection policy, in which even a node other than the best node can be selected. We derive several novel, insightful results about the optimal mapping and develop an algorithm to compute it. These results bring out the inter-relationship between the discrete rate adaptation rule, optimal mapping, and selection policy. We also extensively benchmark the performance of the optimal mapping with several timer and opportunistic multiple access schemes considered in the literature, and demonstrate that the developed scheme is effective in many regimes of interest.

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.

Active yaw control of a vehicle using a Fuzzy logic algorithm

Yaw rate of a vehicle is highly influenced by the lateral forces generated at the tire contact patch to attain the desired lateral acceleration, and/or by external disturbances resulting from factors such as crosswinds, flat tire or, split-μ braking. The presence of the latter and the insufficiency of the former may lead to undesired yaw motion of a vehicle. This paper proposes a steer-by-wire system based on fuzzy logic as yaw-stability controller for a four-wheeled road vehicle with active front steering. The dynamics governing the yaw behavior of the vehicle has been modeled in MATLAB/Simulink. The fuzzy controller receives the yaw rate error of the vehicle and the steering signal given by the driver as inputs and generates an additional steering angle as output which provides the corrective yaw moment. The results of simulations with various drive input signals show that the yaw stability controller using fuzzy logic proposed in the current study has a good performance in situations involving unexpected yaw motion. The yaw rate errors of a vehicle having the proposed controller are notably smaller than an uncontrolled vehicle's, and the vehicle having the yaw stability controller recovers lateral distance and desired yaw rate more quickly than the uncontrolled vehicle.

Threshold-Independent QRS Detection Using the Dynamic Plosion Index

Detection of QRS serves as a first step in many automated ECG analysis techniques. Motivated by the strong similarities between the signal structures of an ECG signal and the integrated linear prediction residual (ILPR) of voiced speech, an algorithm proposed earlier for epoch detection from ILPR is extended to the problem of QRS detection. The ECG signal is pre-processed by high-pass filtering to remove the baseline wandering and by half-wave rectification to reduce the ambiguities. The initial estimates of the QRS are iteratively obtained using a non-linear temporal feature, named the dynamic plosion index suitable for detection of transients in a signal. These estimates are further refined to obtain a higher temporal accuracy. Unlike most of the high performance algorithms, this technique does not make use of any threshold or differencing operation. The proposed algorithm is validated on the MIT-BIH database using the standard metrics and its performance is found to be comparable to the state-of-the-art algorithms, despite its threshold independence and simple decision logic.

How Many Initiator tRNA Genes Does Escherichia coli Need?

Multiple copies of a gene require enhanced investment on the part of the cell and, as such, call for an explanation. The observation that Escherichia coli has four copies of initiator tRNA (tRNA(i)) genes, encoding a special tRNA (tRNA(fMet)) required to start protein synthesis, is puzzling particularly because the cell appears to be unaffected by the removal of one copy. However, the fitness of an organism has both absolute and relative connotations. Thus, we carried out growth competition experiments between E. coli strains that differ in the number of tRNA(i) genes they contain. This has enabled us to uncover an unexpected link between the number of tRNA(i) genes and protein synthesis, nutritional status, and fitness. Wild-type strains with the canonical four tRNA(i) genes are favored in nutrient-rich environments, and those carrying fewer are favored in nutrient-poor environments. Auxotrophs behave as if they have a nutritionally poor internal environment. A heuristic model that links tRNA(i) gene copy number, genetic stress, and growth rate accounts for the findings. Our observations provide strong evidence that natural selection can work through seemingly minor quantitative variations in gene copy number and thereby impact organismal fitness.

How Does Effectual Logic Impact Survival of High-tech Startups in an Emerging Economy? - Evidence from 99tests.com Case Study

During the early stages of operation, high-tech startups need to overcome the liability of newness and manage high degree of uncertainty. Several high-tech startups fail due to inability to deal with skeptical customers, underdeveloped markets and limited resources in selling an offering that has no precedent. This paper leverages the principles of effectuation (a logic of entrepreneurial decision making under uncertainty) to explain the journey from creation to survival of high-tech startups in an emerging economy. Based on the 99tests.com case study, this paper suggests that early stage high-tech startups in emerging economies can increase their probability of survival by adopting the principles of effectuation.

Belief propagation for minimum weight many-to-one matchings in the random complete graph

In a complete bipartite graph with vertex sets of cardinalities n and n', assign random weights from exponential distribution with mean 1, independently to each edge. We show that, as n -> infinity, with n' = n/alpha] for any fixed alpha > 1, the minimum weight of many-to-one matchings converges to a constant (depending on alpha). Many-to-one matching arises as an optimization step in an algorithm for genome sequencing and as a measure of distance between finite sets. We prove that a belief propagation (BP) algorithm converges asymptotically to the optimal solution. We use the objective method of Aldous to prove our results. We build on previous works on minimum weight matching and minimum weight edge cover problems to extend the objective method and to further the applicability of belief propagation to random combinatorial optimization problems.

A coat of many scents: Cuticular hydrocarbons in multitrophic interactions of fig wasps with ants

The fig fig wasp system of Ficus racemosa constitutes an assemblage of galler and parasitoid wasps in which tritrophic interactions occur. Since predatory ants (Oecophylla smaragdina and Technomyrmex albipes) or mostly trophobiont-tending ants (Myrmicaria brunnea) were previously shown to differentially use volatile organic compounds (VOCs) from figs as proximal cues for predation on fig wasps, we examined the response of these ants to the cuticular hydrocarbons (CHCs) of the wasps. CHC signatures of gallers were distinguished from those of parasitoids by the methyl-branched alkanes 5-methylpentacosane and 13-methylnonacosane which characterised trophic group membership. CHC profiles of wasp predator and wasp prey were congruent suggesting that parasitoids acquire CHCs from their prey; the CHC composition of the parasitoid Apocrypta sp 2 clustered with that of its galler host Apocryptophagus fusca, while the CHC profile of the parasitoid Apocryptophagus agraensis clustered with its galler prey, the fig pollinator Ceratosolen fusciceps. In behavioural assays with ants, parasitoid CHC extracts evoked greater response in all ant species compared to galler extracts, suggesting that parasitoid CHC extracts contain more elicitors of ant behaviour than those of plant feeders. CHCs of some wasp species did not elicit significant responses even in predatory ants, suggesting chemical camouflage. Contrary to earlier studies which demonstrated that predatory ants learned to associate wasp prey with specific fig VOCs, prior exposure to fig wasp CHCs did not affect the reaction of any ant species to these CHCs. (C) 2015 Elsevier Masson SAS. All rights reserved.

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.

Ultra-sensitive pressure dependence of bandgap of rutile-GeO2 revealed by many body perturbation theory

The reported values of bandgap of rutile GeO2 calculated by the standard density functional theory within local-density approximation (LDA)/generalized gradient approximation (GGA) show a wide variation (similar to 2 eV), whose origin remains unresolved. Here, we investigate the reasons for this variation by studying the electronic structure of rutile-GeO2 using many-body perturbation theory within the GW framework. The bandgap as well as valence bandwidth at Gamma-point of rutile phase shows a strong dependence on volume change, which is independent of bandgap underestimation problem of LDA/GGA. This strong dependence originates from a change in hybridization among O-p and Ge-(s and p) orbitals. Furthermore, the parabolic nature of first conduction band along X-Gamma-M direction changes towards a linear dispersion with volume expansion. (C) 2015 AIP Publishing LLC.

Event-triggered Sampling and Reconstruction of Sparse Real-valued Trigonometric Polynomials

We propose data acquisition from continuous-time signals belonging to the class of real-valued trigonometric polynomials using an event-triggered sampling paradigm. The sampling schemes proposed are: level crossing (LC), close to extrema LC, and extrema sampling. Analysis of robustness of these schemes to jitter, and bandpass additive gaussian noise is presented. In general these sampling schemes will result in non-uniformly spaced sample instants. We address the issue of signal reconstruction from the acquired data-set by imposing structure of sparsity on the signal model to circumvent the problem of gap and density constraints. The recovery performance is contrasted amongst the various schemes and with random sampling scheme. In the proposed approach, both sampling and reconstruction are non-linear operations, and in contrast to random sampling methodologies proposed in compressive sensing these techniques may be implemented in practice with low-power circuitry.

Many-Body Localization in the Presence of a Single-Particle Mobility Edge

In one dimension, noninteracting particles can undergo a localization-delocalization transition in a quasiperiodic potential. Recent studies have suggested that this transition transforms into a many-body localization (MBL) transition upon the introduction of interactions. It has also been shown that mobility edges can appear in the single particle spectrum for certain types of quasiperiodic potentials. Here, we investigate the effect of interactions in two models with such mobility edges. Employing the technique of exact diagonalization for finite-sized systems, we calculate the level spacing distribution, time evolution of entanglement entropy, optical conductivity, and return probability to detect MBL. We find that MBL does indeed occur in one of the two models we study, but the entanglement appears to grow faster than logarithmically with time unlike in other MBL systems.