Food recognition using neural network classifier and multiple hypotheses image segmentation

ABSTRACT

This paper proposes the multiple-hypotheses image segmentation and feed-forward neural network classifier for food recognition to improve the performance. Initially, the food or meal image is given as input. Then, the segmentation is applied to identify the regions, where a particular food item is located using salient region detection, multi-scale segmentation, and fast rejection. Then, the features of every food item are extracted by the global feature and local feature extraction. After the features are obtained, the classification is performed for each segmented region using a feed-forward neural network model. Finally, the calorie value is computed with the aid of (i) food volume and (ii) calorie and nutrition measure based on mass value. The experimental results and performance evaluation are validated. The outcome of the proposed method attains 0.947 for Macro Average Accuracy (MAA) and 0.959 for Standard Accuracy (SA), which provides better classification performance.     

Preparation of Pure Uranium,Thorium, and Yttrium Oxides from El-Garra El-Hamra Sulfate Leach Liquor

Radiochemistry - The study deals with separation of uranium, thorium, and yttrium with highest possible purity from El-Garaa El-Hamara sulfate leach liquor. From the latter, almost complete...     

Fatal Attraction: How Bacterial Adhesins Affect Host Signaling and What We Can Learn from Them

The ability of bacterial species to colonize and infect host organisms is critically dependent upon their capacity to adhere to cellular surfaces of the host. Adherence to cell surfaces is known to be essential for the activation and delivery of certain virulence factors, but can also directly affect host cell signaling to aid bacterial spread and survival. In this review we will discuss the recent advances in the field of bacterial adhesion, how we are beginning to unravel the effects adhesins have on host cell signaling, and how these changes aid the bacteria in terms of their survival and evasion of immune responses. Finally, we will highlight how the exploitation of bacterial adhesins may provide new therapeutic avenues for the treatment of a wide range of bacterial infections.     

Macrophage Immunomodulation Through New Polymers that Recapitulate Functional Effects of Itaconate as a Power House of Innate Immunity

Itaconate (ITA) is an emerging powerhouse of innate immunity with therapeutic potential that is limited in its ability to be administered in a soluble form. A library of polyester materials that incorporate ITA into polymer backbones resulting in materials with inherent immunoregulatory behavior is developed. Harnessing hydrolytic degradation release from polyester backbones, ITA polymers result in the mechanism specific immunoregulatory properties on macrophage polarization in vitro. In a functional assay, the polymer-released ITA inhibits bacterial growth on acetate. Translation to an in vivo model of biomaterial associated inflammation, intraperitoneal injection of ITA polymers demonstrate a rapid resolution of inflammation in comparison to a control polymer silicone, demonstrating the value of sustained biomimetic presentation of ITA.     

Quantum Sensing in a Physiological‐Like Cell Niche Using Fluorescent Nanodiamonds Embedded in Electrospun Polymer Nanofibers

Fluorescent nanodiamonds (fNDs) containing nitrogen vacancy (NV) centers are promising candidates for quantum sensing in biological environments. This work describes the fabrication and implementation of electrospun poly lactic‐co‐glycolic acid (PLGA) nanofibers embedded with fNDs for optical quantum sensing in an environment, which recapitulates the nanoscale architecture and topography of the cell niche. A protocol that produces uniformly dispersed fNDs within electrospun nanofibers is demonstrated and the resulting fibers are characterized using fluorescent microscopy and scanning electron microscopy (SEM). Optically detected magnetic resonance (ODMR) and longitudinal spin relaxometry results for fNDs and embedded fNDs are compared. A new approach for fast detection of time varying magnetic fields external to the fND embedded nanofibers is demonstrated. ODMR spectra are successfully acquired from a culture of live differentiated neural stem cells functioning as a connected neural network grown on fND embedded nanofibers. This work advances the current state of the art in quantum sensing by providing a versatile sensing platform that can be tailored to produce physiological‐like cell niches to replicate biologically relevant growth environments and fast measurement protocols for the detection of co‐ordinated endogenous signals from clinically relevant populations of electrically active neuronal circuits.     

Monolithically-integrated BiVO4/p+-n GaAs1-xPx tandem photoanodes capable of unassisted solar water splitting

Monolithically-integrated tandem photoanodes were fabricated on substrates consisting of epitaxial n-GaAs_1-xP_x (x ? 0.32) grown on n⁺-GaAs wafers. A p⁺-n junction photovoltaic (PV) cell was first formed by zinc diffusion into the n-GaAs_0.68P_0.32 from a deposited ZnO coating. After diffusion the ZnO serves as a transparent electrical contact to the resulting p⁺-GaAs_0.68P_0.32 surface layer. Transparent, conducting SnO₂:F provides chemical and mechanical protection for the ZnO and the underlying PV cell, and it electrically connects this cell to a top BiVO₄ photocatalyst layer. In some photoanodes, a WO₃ thin film was interposed between the SnO₂:F and BiVO₄. All oxide coatings were produced by ultrasonic spray pyrolysis except WO₃, which was spin coated. Unassisted (unbiased) solar water splitting was achieved, with a solar-to-hydrogen efficiency approaching 2%, without addition of any co-catalyst to the BiVO₄ surface. This work can provide insights to other researchers regarding scalable, low cost approaches for the planar monolithic integration of oxide photoanode materials with PV cells to create new tandem devices.