Structural organization of cholera toxin gene and its expression in an environmental non-pathogenic strain of Vibrio cholerae

Non-pathogenic, environmental strain ofVibrio cholerae, ELTOR Ogawa EW6 carries a copy of the cholera toxin gene in its chromosome. Restriction enzyme digestion followed by Southern blot analysis revealed that the structure of the cholera toxin gene in this organism is different from that found in the virulent strains. The xbaI site which has been found to be conserved in the cholera toxin of the virulent strains examined so far, is absent here. Results of the RNA dot blot analysis indicated that the cholera toxin gene in EW6 is transcribed much less efficiently compared to the cholera toxin gene present in the virulent strainVibrio cholerae classical Inaba 569B

Dynamics of spatial heterogeneity in a landfill with interacting phase densities:a stochastic analysis

A landfill represents a complex and dynamically evolving structure that can be stochastically perturbed by exogenous factors. Both thermodynamic (equilibrium) and time varying (non-steady state) properties of a landfill are affected by spatially heterogenous and nonlinear sub-processes that combine with constraining initial and boundary conditions arising from the associated surroundings. While multiple approaches have been made to model landfill statistics by incorporating spatially dependent parameters on the one hand (data based approach) and continuum dynamical mass-balance equations on the other (equation based modelling), practically no attempt has been made to amalgamate these two approaches while also incorporating inherent stochastically induced fluctuations affecting the process overall. In this article, we will implement a minimalist scheme of modelling the time evolution of a realistic three dimensional landfill through a reaction–diffusion based approach, focusing on the coupled interactions of four key variables –solid mass density, hydrolysed mass density, acetogenic mass density and methanogenic mass density, that themselves are stochastically affected by fluctuations, coupled with diffusive relaxation of the individual densities, in ambient surroundings. Our results indicate that close to the linearly stable limit, the large time steady state properties, arising out of a series of complex coupled interactions between the stochastically driven variables, are scarcely affected by the biochemical growth–decay statistics. Our results clearly show that an equilibrium landfill structure is primarily determined by the solid and hydrolysed mass densities only rendering the other variables as statistically “irrelevant”inthis (largetime) asymptotic limit. The other major implication of incorporation of stochasticity in the land- fill evolution dynamics is in the hugely reduced production times of the plants that are now approximately 20–30 years instead of the previous deterministic model predictions of 50 years and above. The predictions from this stochastic model are in conformity with available experimental observations

Nanomaterials for Supercapacitors: Uncovering Research Themes with Unsupervised Machine Learning

Identification of important topics in a text can facilitate knowledge curation, discover thematic trends, and predict future directions. In this paper, we aim to quantitatively detect the most common research themes in the emerging supercapacitor research area, and summarize their trends and characteristics through the proposed unsupervised, machine learning approach. We have retrieved the complete reference entries of article abstracts from Scopus database for all original research articles from 2004 to 2021. Abstracts were processed through a natural language processing pipeline and analyzed by a latent Dirichlet allocation topic modeling algorithm for unsupervised topic discovery. Nine major topics were further examined through topic-word associations, Inter-topic distance map and topic-specific word cloud. We observed the greatest importance is being given to performance metrics (28.2%), flexible electronics (8%), and graphene-based nanocomposites (10.9%). The analysis also points out crucial future research directions towards bio-derived carbon nanomaterials (such as RGO) and flexible supercapacitors

Graph Coloring via Degeneracy in Streaming and Other Space-Conscious Models

We study the problem of coloring a given graph using a small number of colors in several well-established models of computation for big data. These include the data streaming model, the general graph query model, the massively parallel computation (MPC) model, and the CONGESTED-CLIQUE and the LOCAL models of distributed computation. On the one hand, we give algorithms with sublinear complexity, for the appropriate notion of complexity in each of these models. Our algorithms color a graph $G$ using about $\kappa(G)$ colors, where $\kappa(G)$ is the degeneracy of $G$: this parameter is closely related to the arboricity $\alpha(G)$. As a function of $\kappa(G)$ alone, our results are close to best possible, since the optimal number of colors is $\kappa(G)+1$. On the other hand, we establish certain lower bounds indicating that sublinear algorithms probably cannot go much further. In particular, we prove that any randomized coloring algorithm that uses $\kappa(G)+1$ many colors, would require $\Omega(n^2)$ storage in the one pass streaming model, and $\Omega(n^2)$ many queries in the general graph query model, where $n$ is the number of vertices in the graph. These lower bounds hold even when the value of $\kappa(G)$ is known in advance; at the same time, our upper bounds do not require $\kappa(G)$ to be given in advance.Comment: 26 page

Technologies used at advanced dairy farms for optimizing the performance of dairy animals: A review

Superior germplasm, better nutrition strategies, health care facilities and improved dairy husbandry practices have boosted milk yield and its quality with a rapid rate. Per cow productivity has risen up sharply with considerable increase in the population of dairy animals. Recent era has witnessed the extension of large dairy farms around the world. Demand for high quality and increased quantity of milk is of the prime concern for all the dairy farms. With an increase in the size of animals in a farm, the labour requirement also rises up. Availability of skilled labour at low wage rate is becoming difficult. In last couple of decades, the cost of microprocessors has been reduced to an affordable level. The economic availability of engineered processors, artificial intelligence, improved data statistics combined with expert suggestions has created a revolution in livestock farming. Advanced engineered devices have become alternative to reduce high labour cost. This review focuses on latest knowledge and emerging developments in animal’s welfare focused biomarker activities and activity-based welfare assessment like oestrus, lameness and others. Use of enhanced sensors and data technologies with expert based solutions is anticipated to bring out a substantial improvement in existing dairy farming practices

Effect of vaccine dose intervals:Considering immunity levels, vaccine efficacy, and strain variants for disease control strategy

In this study, we present an immuno-epidemic model to understand mitigation options during an epidemic break. The model incorporates comorbidity and multiple-vaccine doses through a system of coupled integro-differential equations to analyze the epidemic rate and intensity from a knowledge of the basic reproduction number and time-distributed rate functions. Our modeling results show that the interval between vaccine doses is a key control parameter that can be tuned to significantly influence disease spread. We show that multiple doses induce a hysteresis effect in immunity levels that offers a better mitigation alternative compared to frequent vaccination which is less cost-effective while being more intrusive. Optimal dosing intervals, emphasizing the cost-effectiveness of each vaccination effort, and determined by various factors such as the level of immunity and efficacy of vaccines against different strains, appear to be crucial in disease management. The model is sufficiently generic that can be extended to accommodate specific disease forms

Laws of Black Hole Mechanics from Holst Action

The formulation of Weak Isolated Horizons (WIH) based on the Isolated Horizon formulation of black hole horizons is reconsidered. The first part of the paper deals with the derivation of laws of mechanics of a WIH. While the zeroth law follows from the WIH boundary conditions, first law depends on the action chosen. We construct the covariant phase space for a spacetime having an WIH as inner boundary for the Holst action. This requires the introduction of new potential functions so that the symplectic structure is foliation independent. We show that a precise cancellation among various terms leads to the usual first law for WIH. Subsequently, we show from the same covariant phase space that for spherical horizons, the topological theory on the inner boundary is a U(1) Chern-Simons theory.Comment: References added, Minor Corrections 25 pages 1 fi