Genome Mining and Evaluation of the Biocontrol Potential of Pseudomonas fluorescens BRZ63, a New Endophyte of Oilseed Rape (Brassica napus L.) against Fungal Pathogens

Endophytic bacteria hold tremendous potential for use as biocontrol agents. Our study aimed to investigate the biocontrol activity of Pseudomonas fluorescens BRZ63, a new endophyte of oilseed rape (Brassica napus L.) against Rhizoctonia solani W70, Colletotrichum dematium K, Sclerotinia sclerotiorum K2291, and Fusarium avenaceum. In addition, features crucial for biocontrol, plant growth promotion, and colonization were assessed and linked with the genome sequences. The in vitro tests showed that BRZ63 significantly inhibited the mycelium growth of all tested pathogens and stimulated germination and growth of oilseed rape seedlings treated with fungal pathogens. The BRZ63 strain can benefit plants by producing biosurfactants, siderophores, indole-3-acetic acid (IAA), 1-aminocyclopropane-1-carboxylate (ACC) deaminase, and ammonia as well as phosphate solubilization. The abilities of exopolysaccharide production, autoaggregation, and biofilm formation additionally underline its potential to plant colonization and hence biocontrol. The effective colonization properties of the BRZ63 strain were confirmed by microscopy observations of EGFP-expressing cells colonizing the root surface and epidermal cells of Arabidopsis thaliana Col-0. Genome mining identified many genes related to the biocontrol process, such as transporters, siderophores, and other secondary metabolites. All analyses revealed that the BRZ63 strain is an excellent endophytic candidate for biocontrol of various plant pathogens and plant growth promotion.     

Dietary mycotoxins binders: a strategy to reduce aflatoxin m1 residues and improve milk quality of lactating Beetal goats

Aflatoxin M1 (AFM1) is a metabolite of aflatoxin B1 (AFB1) and secreted in milk of animals that are kept on a moldy diet. AFB1 is produced by several toxigenic species of fungi. In this study, the comparative efficacy of two mycotoxin binders was evaluated in terms of reducing excretion of AFM1, total viable bacterial count and somatic cell count in milk obtained from goats fed with AFB1 contaminated diet. A total of 32 lactating Beetal goats were reared and divided into 4 equal groups: Animals of group A were kept as control, while those in groups B, C, and D were individually fed with AFB1 at 40 µg alone, 40 µg AFB1 along with mycotoxin binder Toxfin^® at 3 g kg^?1 of cotton seed cake, and 40 µg AFB1 along with mycotoxin binder Elitox^® at a dose rate of 1 g kg^?1 of cotton seed cake, respectively. Toxfin^® significantly decreased the excretion of AFM1 in goats’ milk by 49.57 % while Elitox^® non-significantly reduced the excretion of AFM1 in goats’ milk by 19.49 %. Total viable bacterial count in milk samples of group C and D, and somatic cell count in milk samples of group C did not reduce significantly. However, somatic cell count in milk samples of group D reduced significantly. We conclude that the addition of Toxfin^® in the moldy diet significantly reduce the excretion of AFM1 in animals’ milk and minimize the risk of mycotoxin toxicity to public health.     

Modern Drifts in Conjugated Polymers and Nanocomposites for Organic Solar Cells: A Review

In this article, various aspects of photovoltaic, organic solar cell and working principle involved have been reviewed. Moreover, different generations of solar cell, and use of an important class of organic materials, i.e., conjugated polymers and polymer-based nanocomposites and their properties were discussed. Convincingly, organic materials have vast future potential in solar cell to enhance its efficiency and durability of devices. In the review, current understandings of mechanisms that rule the photocurrent creation steps and define seek for alternate materials and device structure, have been focused. Foremost research efforts must focus cell efficiency improvement to speed up new material commercialization.     

A neural circuit with transcendental energy function for solving system of linear equations

A feedback neural network based circuit to solve a system of simultaneous linear equations is presented. The circuit has an associated transcendental energy function that ensures fast convergence to the exact solution while enjoying reduction in hardware complexity over existing schemes. The proof of the energy function has been given and it is shown that the gradient network converges exactly to the solution of the system of equations. PSPICE simulation results are presented for linear systems of equations of various sizes and are found to agree exactly with the algebraic solution. Hardware implementation for small sized problems further confirm the circuit operation.     

BilKristal 2.0: A tool for pattern information extraction from crystal structures

We present a revised version of the BilKristal tool of Okuyan et al. (2007). We converted the development environment into Microsoft Visual Studio 2005 in order to resolve compatibility issues. We added multi-core CPU support and improvements are made to graphics functions in order to improve performance. Discovered bugs are fixed and exporting functionality to a material visualization tool is added.     

Data center network architecture in cloud computing： review,taxonomy, and open research issues＊

The data center network （DCN）, which is an important component of data centers, consists of a large number of hosted servers and switches connected with high speed communication links. A DCN enables thc deployment of resources centralization and on-demand access of the information and services of data centers to users. In recent years, the scale of the DCN has constantly increased with the widespread use of cloud-based services and the unprecedented amount of data delivery in/between data centers, whereas the traditional DCN architecture lacks aggregate bandwidth, scalability, and cost effectiveness for coping with the increasing demands of tenants in accessing the services of cloud data centers. Therefore, the design of a novel DCN architecture with the features of scalability, low cost, robustness, and energy conservation is required. This paper reviews the recent research findings and technologies of DCN architectures to identify the issues in the existing DCN architectures for cloud computing. We develop a taxonomy for the classification of the current DCN architectures, and also qualitatively analyze the traditional and contemporary DCN architectures. Moreover, the DCN architectures are compared on the basis of the significant characteristics, such as bandwidth, fault tolerance, scalability, overhead, and deployment cost. Finally, we put forward open research issues in the deployment of scalable, low-cost, robust, and energy-efficient DCN architecture, for data centers in computational clouds.     

Effect of growth factors on the production of mycelium-based biofoam

Clean Technologies and Environmental Policy - Mycelium-based biofoam has the potential to become an alternative to petroleum-polymeric based-foam by utilising fungal mycelium and lignocellulosic...     

An amorphous model for morphological processing in visual comprehension based on naive discriminative learning.

A 2-layer symbolic network model based on the equilibrium equations of the Rescorla–Wagner model (Danks, 2003) is proposed. The study first presents 2 experiments in Serbian, which reveal for sentential reading the inflectional paradigmatic effects previously observed by Milin, Filipovi? ?ur?evi?, and Moscoso del Prado Martín (2009) for unprimed lexical decision. The empirical results are successfully modeled without having to assume separate representations for inflections or data structures such as inflectional paradigms. In the next step, the same naive discriminative learning approach is pitted against a wide range of effects documented in the morphological processing literature. Frequency effects for complex words as well as for phrases (Arnon & Snider, 2010) emerge in the model without the presence of whole-word or whole-phrase representations. Family size effects (Moscoso del Prado Martín, Bertram, H?iki?, Schreuder, & Baayen, 2004; Schreuder & Baayen, 1997) emerge in the simulations across simple words, derived words, and compounds, without derived words or compounds being represented as such. It is shown that for pseudo-derived words no special morpho-orthographic segmentation mechanism, as posited by Rastle, Davis, and New (2004), is required. The model also replicates the finding of Plag and Baayen (2009) that, on average, words with more productive affixes elicit longer response latencies; at the same time, it predicts that productive affixes afford faster response latencies for new words. English phrasal paradigmatic effects modulating isolated word reading are reported and modeled, showing that the paradigmatic effects characterizing Serbian case inflection have crosslinguistic scope. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Determination of phenol in the Bangsai River water of Bangladesh by gas chromatography-mass spectrometry

A simple, sensitive and rapid gas chromatography-mass spectrometry (GC-MS) method is proposed for the analysis of some environmentally important highly toxic phenols in water. The concentration level of phenol was determined in water at the sampling stations of Savar, Dhaka Export Processing Zone (DEPZ) and Bank Colony of the Bangsai River, Bangladesh. Water samples were collected from different depth of the sampling stations. The phenolic compounds were extracted with dichloromethane, which was further preconcentrated by evaporation. Different concentrations of toxic phenol were obtained in the river water at the various sampling stations. The concentration of highly toxic phenol was found in the range of 0.01–0.998 μg L⁻¹. This method could permit the analysis of water for phenol as well as phenolic derivatives with detection limit as low as 100 ng L⁻¹.