Design of an ultra-sensitive bimetallic anisotropic PCF SPR biosensor for liquid analytes sensing.

In this research work, an anisotropic photonic crystal fiber (PCF) biosensor working on a refractive index (RI) variation and based on surface plasmon resonance (SPR) is presented. Liquid analytes (LA) having a RI within the range of 1.340 to 1.380 RIU are investigated from the proposed biosensor. Spectroscopy analysis of LA having RI values of 1.340 RIU, 1.360 RIU, and 1.380 RIU is performed from the developed sensing setup for modeling an ultrasensitive biosensor. The numerical analysis of the sensing parameters for the proposed sensor presents a maximum wavelength sensitivity (WS) of 20000 nm/RIU for x- polarization (x - pol.) and 18000 nm/RIU for y- polarization (y - pol.), respectively, using the wavelength interrogation technique. Maximum amplitude sensitivity (AS) of 2158 RIU-1 and 3167 RIU-1 is obtained for x - pol. and y - pol., respectively, using the amplitude interrogation technique. Maximum sensor resolution (SR) of 5.00 × 10-6RIU and 5.55 × 10-6RIU is obtained for x - pol. and y - pol., respectively. The linear relationship of the resonant wavelength (RW) with the RI produces R2 =  0.9972 and R2 = 0.9978, corresponding to a degree (2) for x - pol. and y - pol., respectively. The figure of merit (FOM) for x - pol. and y - pol. are 93.45 RIU-1 and 105.88 RIU-1, respectively. The sensing parameters have obtained the maximum value for the LA having a RI value of 1.375 RIU.

Modeling of texture quantification and image classification for change prediction due to COVID lockdown using Skysat and Planetscope imagery.

This research work models two methods together to provide maximum information about a study area. The quantification of image texture is performed using the "grey level co-occurrence matrix ( GLCM )" technique. Image classification-based "object-based change detection ( OBCD )" methods are used to visually represent the developed transformation in the study area. Pre-COVID and post-COVID (during lockdown) panchromatic images of Connaught Place, New Delhi, are investigated in this research work to develop a model for the study area. Texture classification of the study area is performed based on visual texture features for eight distances and four orientations. Six different image classification methodologies are used for mapping the study area. These methodologies are "Parallelepiped classification ( PC )," "Minimum distance classification ( MDC )," "Maximum likelihood classification ( MLC )," "Spectral angle mapper ( SAM )," "Spectral information divergence ( SID )" and "Support vector machine ( SVM )." GLCM calculations have provided a pattern in texture features contrast, correlation, ASM , and IDM . Maximum classification accuracy of 83.68 % and 73.65 % are obtained for pre-COVID and post-COVID image data through MLC classification technique. Finally, a model is presented to analyze before and after COVID images to get complete information about the study area numerically and visually.

Correction to: Multinational Consensus: Insulin Initiation with Insulin Degludec/Aspart (IDegAsp).

Unfortunately, the fifth author name was incorrectly published in the original publication. The correct name should read as 'Ozgur Demir'.

Multinational Consensus: Insulin Initiation with Insulin Degludec/Aspart (IDegAsp).

Insulin degludec/aspart (IDegAsp) is the first soluble insulin co-formulation, combining a long-acting insulin degludec (IDeg) and rapid-acting insulin aspart (IAsp). In type 2 diabetes patients with oral antidiabetes agent (OAD) inadequacy, insulin initiation with IDegAsp once daily provides superior long-term glycemic control compared to insulin glargine, with similar fasting plasma glucose (FPG) and insulin doses, and numerically lower rates of overall and nocturnal hypoglycemia. Furthermore, in patients with uncontrolled type 2 diabetes previously treated with insulins, IDegAsp twice daily effectively improves glycated hemoglobin and FPG, with fewer hypoglycemic episodes versus premix insulins and basal bolus therapy. In patients with type 1 diabetes mellitus, IDegAsp once daily with two doses of IAsp is a convenient, yet effective, regimen as compared to the conventional 4-5 injection-based basal bolus therapy. IDegAsp is an appropriate and reasonable option for initiation of insulin therapy in both type 1 and type 2 diabetes.