Design of Deep Convolution Neural Networks for categorical signature classification of raw panchromatic satellite images

Multimedia Tools and Applications - Remote Sensing categorical signature classification has gained significant implications on spatial resolution image analysis due to differences in the...     

A Hybrid Analytic Model for the Effective Prediction of Different Stages in Chronic Kidney Ailments

Wireless Personal Communications - Chronic kidney disease (CKD) is a gradual loss of kidney function over the period of time and it is irrevocable once functionality reaches the critical state....     

α-Glucosidase, α-amylase inhibition kinetics,in vitro gastro-intestinal digestion,and apoptosis inducing abilities of Ficus microcarpa L. f. and Ficus racemosa L. fruit polysaccharides

Food Science and Biotechnology - A rich source of nutrients, figs have a number of clinically validated benefits. This study aimed to evaluate the in vitro simulated gastrointestinal digestion, and...     

Influence of Titanium Excess in a Ti–Si Reaction Mixture on the Synthesis of a Composite in a Combustion Wave

Theoretical Foundations of Chemical Engineering - On the basis of the classic concepts of the theory of solid-phase combustion, for the first time, a model with a detailed scheme of chemical...     

Effects of high-pressure-modified soy 11S globulin on the gel properties and water-holding capacity of pork batter

The effects of high-pressure-modified soy 11S globulin (0.1, 200, and 400 MPa) on the gel properties, water-holding capacity, and water mobility of pork batter were investigated. The high-pressure-modified soy 11S globulin significantly increased (P < 0.05) the emulsion stability, cooking yield, hardness, springiness, chewiness, resilience, cohesiveness, the a^* and b^* values, and the G′ and G′′ values of pork batter at 80 °C, compared with those of 0.1 MPa-modified globulin. In contrast, the centrifugal loss and initial relaxation time of T_2b, T₂₁, and T₂₂ significantly decreased (P < 0.05). Meanwhile, the microstructure was denser, and the voids were smaller and more uniform compared with those of 0.1 MPa-modified globulin. In addition, the sample with 11S globulin modified at 400 MPa had the best water-holding capacity, gel structure, and gel properties among the samples. Overall, the use of high-pressure-modified soy 11S globulin improved the gel properties and water-holding capacity of pork batter, especially under 400 MPa.     

Low light enhancement algorithm for color images using intuitionistic fuzzy sets with histogram equalization

Multimedia Tools and Applications - In this work, a new fuzzy logic-based algorithm is proposed for the enhancement of low light color images. A generalization of a fuzzy set known as an...     

Low Temperature Characteristics of the Metal–Superconductor NIS Tunneling Thermometer

We discuss the temperature dependence of a common low temperature local thermometer, a tunnel junction between a superconductor and a normal metal (NIS junction). Towards the lowest temperatures its characteristics tend to saturate, which is usually attributed to selfheating effects. In this technical note, we reanalyze this saturation and show that the temperature independent subgap current of the junction alone explains in some cases the low temperature behavior quantitatively.

     

Designing optical glasses by machine learning coupled with a genetic algorithm

Engineering new glass compositions have experienced a sturdy tendency to move forward from (educated) trial-and-error to data- and simulation-driven strategies. In this work, we developed a computer program that combines data-driven predictive models (in this case, neural networks) with a genetic algorithm to design glass compositions with desired combinations of properties. First, we induced predictive models for the glass transition temperature (T_g) using a dataset of 45,302 compositions with 39 different chemical elements, and for the refractive index (n_d) using a dataset of 41,225 compositions with 38 different chemical elements. Then, we searched for relevant glass compositions using a genetic algorithm informed by a design trend of glasses having high n_d (1.7 or more) and low T_g (500 °C or less). Two candidate compositions suggested by the combined algorithms were selected and produced in the laboratory. These compositions are significantly different from those in the datasets used to induce the predictive models, showing that the used method is indeed capable of exploration. Both glasses met the constraints of the work, which supports the proposed framework. Therefore, this new tool can be immediately used for accelerating the design of new glasses. These results are a stepping stone in the pathway of machine learning-guided design of novel glasses.     

Effect of Drosophila suzukii on Blueberry VOCs: Chemical Cues for a Pupal Parasitoid,Trichopria anastrephae

Journal of Chemical Ecology - Biocontrol agents such as parasitic wasps use long-range volatiles and host-associated cues from lower trophic levels to find their hosts. However, this chemical...