This study addresses the challenges of human-robot interactions in real-time environments with adaptive field-programmable gate array (FPGA)-based accelerators. Predicting human posture in indoor environments in confined areas is a significant challenge for service robots. The proposed approach works on two levels: the estimation of human location and the robot's intention to serve based on the human's location at static and adaptive positions.
View Article and Find Full Text PDFPurpose: To understand the bacterial microbiome changes associated with Sjogren's syndrome (SS) and non-Sjogren's syndrome (NSS) aqueous-deficient dry eyes compared to healthy eyes.
Methods: Bacterial microbiome was generated from the deoxyribonucleic acid of tear film samples in healthy (n = 33), SS (n = 17), and NSS (n = 28) individuals. Sequencing of the V3-V4 region of the 16S rRNA gene was performed on the Illumina HiSeq2500 platform.
Conjunctival swabs (CS) are the major source of sampling for ocular microbiome studies, however collecting CS from the diseased eyes is difficult and painful. In this study, as an alternative to CS, a less invasive approach of tear collection was used to establish the bacterial microbiome in healthy eyes. Tear bacterial microbiome was generated from the DNA of tears (n = 24; male = 16 and female = 8) of healthy volunteers aged from 20 to 52 years.
View Article and Find Full Text PDF1G ethanol from sweet sorghum can be a better alternative to various other sources used for its production. The commercial feasibility is dictated by the high sugar containing varieties, their transport to ethanol plants, storage and availability of robust yeast strains for the fermentation. Eight sweet sorghum cultivars namely CSV19SS, CSV24SS, CSV27, CSV32F, PV, SSV84, RVICSH, SPV1871, SSV74 were tested for their sugar content and varieties-SSV84 and CSV24SS were containing sugar content of 170-190 g/L.
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