Silicon Mitigates Drought Stress in Wheat (Triticum aestivum L.) Through Improving Photosynthetic Pigments,Biochemical and Yield Characters

Silicon - Feeling prone to stress differs with plant production stage, water scarcity near commencement of grain filling phase has a significant reduced grain yield through fewer endosperm and sink...     

Recent advances and developments in advanced green porous nanomaterial for sustainable energy storage application

Journal of Porous Materials - Compared with traditional battery and super capacitor materials, nanomaterials can significantly improve ion transport and electron conductivity. There are many...     

EEG‐based brain source localization using visual stimuli

Electroencephalography (EEG) is widely used in variety of research and clinical applications which includes the localization of active brain sources. Brain source localization provides useful information to understand the brain's behavior and cognitive analysis. Various source localization algorithms have been developed to determine the exact locations of the active brain sources due to which electromagnetic activity is generated in brain. These algorithms are based on digital filtering, 3D imaging, array signal processing and Bayesian approaches. According to the spatial resolution provided, the algorithms are categorized as either low resolution methods or high resolution methods. In this research study, EEG data is collected by providing visual stimulus to healthy subjects. FDM is used for head modelling to solve forward problem. The low‐resolution brain electromagnetic tomography (LORETA) and standardized LORETA (sLORETA) have been used as inverse modelling methods to localize the active regions in the brain during the stimulus provided. The results are produced in the form of MRI images. The tables are also provided to describe the intensity levels for estimated current level for the inverse methods used. The higher current value or intensity level shows the higher electromagnetic activity for a particular source at certain time instant. Thus, the results obtained demonstrate that standardized method which is based on second order Laplacian (sLORETA) in conjunction with finite difference method (FDM) as head modelling technique outperforms other methods in terms of source estimation as it has higher current level and thus, current density (J) for an area as compared to others.     

Effect of Silicone Nano,Nano/Micro and Nano/Macro‐Emulsion Softeners on Color Yield and Physical Characteristics of Dyed Cotton Fabric

The study of silicone nano‐emulsions and softeners to alter physical properties of undyed cotton fabric has recently gained a substantial interest. However, systematic investigation of silicon nano‐emulsion softeners on dyed cotton fabric has not so far been conducted. This paper deals with the application of silicone nano‐, micro‐, and macro‐emulsion softeners, and combinations of nano/micro and nano/macro, on dyed cotton fabric. We report the effect of silicon nano/micro‐ and nano/macro‐emulsion softeners on color yield and physical characteristics of dyed cotton fabric. All bleached fabrics were dyed with CI Reactive Black 5 and then treated with known concentrations of silicone softeners by the pad‐dry method. The silicone nano‐emulsion was combined with micro‐ and macro‐emulsion softeners using blending ratios of nano/micro (1:1) and nano/macro (1:1). Treated fabrics were compared in terms of physical properties such as fabric handling, wrinkle recovery angle, bending length, abrasion resistance and tensile strength. The color changes were evaluated by color yield (K/S) values and total color difference (ΔE_cmc). The results revealed that the silicon nano‐emulsion had better physical properties than micro‐, macro‐ and combination nano/micro‐ and nano/macro‐emulsion softeners. Among all treated samples, nano‐emulsion softeners showed better ΔE_cmc values. Scanning electron microscopy analysis suggests that the fiber morphology of treated fabrics was very smooth and uniform.     

Recent developments and progress of aerogel assisted environmental remediation: a review

Journal of Porous Materials - Aerogel is a special type of porous material with many outstanding physical and chemical properties, such as low density, high porosity, high surface area, and...