Aflatoxins and food pathogens: impact of biologically active aflatoxins and their control strategies

Globally disease outbreaks as a result of the consumption of contaminated food and feedstuffs are a regular primary problem. The foremost elements contributing to contamination are microorganisms, particularly fungi, which produce low‐molecular weight secondary metabolites, with demonstrated toxic properties that are referred to as mycotoxins. Aflatoxins contaminate agricultural commodities and may cause sickness or fatality in humans and animals. Moreover, poor conditions of storage and a deficiency in regulatory measures in food quality control aggravate the main issue. For that reason, mycotoxin‐related illness of nutrition represents a major health hazard for local populations. Government policies should make regulations aiming to avoid the entry of aflatoxins into food stuffs. For consumer safety, control and management strategies should be developed and implemented by regulatory authorities. There is the need for attention from farmers, scientists, government and collaborative minds throughout the country to ensure aflatoxin‐free food. The present review is informative not only for health‐conscious consumers, but also for relevant authorities with respect to paving the way for future research aiming to fill the existing gaps in our knowledge with regard to mycotoxins and food security. © 2016 Society of Chemical Industry     

Accelerating Multiresolution Gabor Feature Extraction for Real Time Vision Applications

Multiresolution Gabor filter banks are used for feature extraction in a variety of applications as Gabor filters have shown to be exceptional feature extractors with a close correspondence to the simple cells in the primary visual cortex (V1) of the brain. Yet applying the Gabor filter is a computationally intensive task. Most applications that utilize the Gabor feature space require real time results; however, the large quantity of computations involved has hindered systems from achieving real time performance. The natural solution for such compute intensive tasks is parallelization. FPGAs have emerged as attractive platforms for compute intensive signal processing applications due to their massively parallel computation resources as well as low power consumption and affordability. We present a configurable architecture for Gabor feature extraction on FPGA that enhances the resource utilization of the FPGA hardware fabric while maintaining a streaming data flow to yield exceptional performance. The increased resource utilization resulting from configurability, optimizations, and resource sharing allows for higher levels of parallelism to achieve real time feature extraction of high resolution images. Two architectures are introduced. The first is an architecture for multiresolution feature extraction with extensive resource sharing for enhanced resource utilization. The second is an architecture for many-orientation applications using a coarse to fine grain method to enhance resource utilization by reducing the number of filters applied at different orientations. Our results show that our multiresolution implementation achieves real-time performance on 2048?×?1526 images and exhibits 6X speed up over a GPU implementation while exhibiting energy efficiency with 0.4fps/W compared to the GPU that achieves 0.036fps/W.[1] The implementation for many-orientation applications using the coarse to fine grain method exhibits resource saving of at most \( 2\sqrt{O} \) for O number of orientations and higher, compared to a fully parallel architecture and 25× speedup compared to a GPU implementation for 16 orientations.     

Electrostatic Limit of Detection of Nanowire‐Based Sensors

Scanning gate microscopy is used to determine the electrostatic limit of detection (LOD) of a nanowire (NW) based chemical sensor with a precision of sub‐elementary charge. The presented method is validated with an electrostatically formed NW whose active area and shape are tunable by biasing a multiple gate field‐effect transistor (FET). By using the tip of an atomic force microscope (AFM) as a local top gate, the field effect of adsorbed molecules is emulated. The tip induced charge is quantified with an analytical electrostatic model and it is shown that the NW sensor is sensitive to about an elementary charge and that the measurements with the AFM tip are in agreement with sensing of ethanol vapor. This method is applicable to any FET‐based chemical and biological sensor, provides a means to predict the absolute sensor performance limit, and suggests a standardized way to compare LODs and sensitivities of various sensors.     

Fault Aware Dynamic Resource Manager for Fault Recognition and Avoidance in Cloud

Fault tolerance (FT) schemes are intended to work on a minimized and static amount of physical resources. When a host failure occurs, the conventional FT frequently proceeds with the execution on the accessible working hosts. This methodology saves the execution state and applications to complete without disruption. However, the dynamicity of open cloud assets is not seen when taking scheduling choices. Existing optimization techniques are intended in dealing with resource scheduling. This method will be utilized for distributing the approaching tasks to the VMs. However, the dynamic scheduling for this procedure doesn’t accomplish the objective of adaptation of internal failure. The scheme prefers jobs in the activity list with the most elevated execution time on resources that can execute in a shorter timeframe, but it suffers with higher makespan; poor resource usage and unbalance load concerns. To overcome the above mentioned issue, Fault Aware Dynamic Resource Manager (FADRM) is proposed that enhances the mechanism to Multi-stage Resilience Manager at an application-level FT arrangement. Proposed FADRM method gives FT a Multi-stage Resilience Manager (MRM) in the client and application layers, and simultaneously decreases the over-head and degradations. It additionally provides safety to the application execution considering the clients, application and framework necessities. Based on experimental evaluations, Proposed Fault Aware Dynamic Resource Manager (FADRM) method 157.5 MakeSpan (MS) time, 0.38 Fault Rate (FR), 0.25 Failure Delay (FD) and improves 5.5 Performance Improvement Ratio (PIR) for 25, 50, 75 and 100 tasks and 475 MakeSpan (MS) time, 0.40 Fault Rate (FR), 1.30 Failure Delay (FD) and improves 6.75 improves Performance Improvement Ratio (PER) for 100, 200, 300 and 500 Tasks compare than existing methodologies.     

Influence of process variables on the characteristics of friction‐stir‐welded polyamide 6,6 joints

This paper aims to study the feasibility of friction stir welding of thermoplastic material polyamide 6,6. The maximum joint strength achieved through the optimized process variables is 41 MPa. The maximum temperature rise of 126 °C is achieved and the weld nugget exhibits a hardness of 69 D on Shore hardness scale. Fractography analysis reveals that the fracture followed a continuous plastic flow comprising less prominent fibrillation and more elongated voids. An increase in glass transition temperature T_g is observed in the weld specimen. The impact of the welding process variables on the frequency and band shift of the functional groups of the polymer is also discussed.     

Influence of Industrial and Agricultural by-Products as Cementitious Blends in Self-Compacting Concrete – A Review

Silicon - Globally, the annual generation of industrial and agricultural by-products is exceeding a thousand million tons and forecasted to tremendously inflate in the future. The by-products are...     

Investigation of N–S-based graphene quantum dot on sodium alginate with ammonium thiocyanate (NH4SCN) biopolymer electrolyte for the application of electrochemical devices

Journal of Materials Science: Materials in Electronics - The development of high ion conducting membrane is in need of present time for efficient battery. The aim of this study is to develop a...     

Mechanical and Thermal Properties Modeling,Sorption Characteristics of Multiscale (Multiwalled Carbon Nanotubes/Glass Fiber) Filler Reinforced Polypropylene Composites

The present work was aimed to investigate the individual and hybrid reinforcement effect of multiscale fillers [glass fibers (GF)/multiwalled carbon nanotubes (MWCNTs)] in polypropylene (PP) matrix. The MWCNT content in the hybrid composites was varied from 0.5 to 5 wt%, and glass fiber fraction was fixed as 20 wt%. The morphology of nano and hybrid composite revealed reasonable dispersion of MWCNTs and glass fibers in the matrix. At a MWCNT content of 3 wt%, the optimum tensile properties for the hybrid composites were achieved and beyond which it declined due to agglomeration effects as revealed by transmission electron microscopy. A comparative study of the experimental and predicted values of moduli of nano, micro, and hybrid composites using various micromechanical models was conducted. The simultaneous incorporation of MWCNTs and glass fibers in PP restricted the mobility of polymer chains as indicated by the increase in storage modulus and rise in glass transition temperature obtained by dynamic mechanical analysis. The differential scanning calorimetry studies indicated that the inclusion of 2 wt% of MWCNTs increased the crystallinity of PP from 58.2 to 69.1% in hybrid composites. The Avrami and Mo models were used to explore nonisothermal crystallization kinetics, and Mo model was in close agreement with the experimental results. The sorption behavior of the composites revealed that the formation of immobilized regions developed by the simultaneous inclusion of micro and nano fillers delayed the transport of the solvent. J. VINYL ADDIT. TECHNOL., 25:E94–E107, 2019. © 2019 Society of Plastics Engineers     

An automatic plant leaf disease identification using DenseNet-121 architecture with a mutation-based henry gas solubility optimization algorithm

Neural Computing and Applications - Farmers are struggling to provide the fast-growing population with sufficient agricultural products, while plant diseases result in devastating food loss. The...