Rheological and functional properties of Roselle (Hibiscus sabdariffa) leaves puree

Pureed form of leaves (Hibiscus sabdariffa L. (Roselle)) was taken for physicochemical and rheological analysis at temperatures and TSS range of 278 K - 318 K and 3 - 5 °Brix respectively. The steady-state rheological analysis was performed with a shear rate of 1 - 100 s-1. Different rheological models are tried; Power-law was best fitted with the experimental data (R2 ≥0.98). Temperature dependence of viscosity was found out using an Arrhenius-type relationship at a shear rate of 10, 50, 100 s-1 IR analysis was done to know the influence of functional groups on rheological properties of purees. Consistency index (K) of puree increases with increase in TSS content but at a fixed TSS, there is a decrease in K with an increase in temperatures but the opposite was observed for flow behavior index (n). Puree showed a shear thinning behavior with an increment in temperature level and puree having 5 °Brix (8.37) has higher activation energy (kJ.mol-1) than 3 °Brix (6.32). 

Utilizing Radiomic Feature Analysis For Automated MRI Keypoint Detection: Enhancing Graph Applications

Graph neural networks (GNNs) present a promising alternative to CNNs and transformers in certain image processing applications due to their parameter-efficiency in modeling spatial relationships. Currently, a major area of research involves the converting non-graph input data for GNN-based models, notably in scenarios where the data originates from images. One approach involves converting images into nodes by identifying significant keypoints within them. Super-Retina, a semi-supervised technique, has been utilized for detecting keypoints in retinal images. However, its limitations lie in the dependency on a small initial set of ground truth keypoints, which is progressively expanded to detect more keypoints. Having encountered difficulties in detecting consistent initial keypoints in brain images using SIFT and LoFTR, we proposed a new approach: radiomic feature-based keypoint detection. Demonstrating the anatomical significance of the detected keypoints was achieved by showcasing their efficacy in improving registration processes guided by these keypoints. Subsequently, these keypoints were employed as the ground truth for the keypoint detection method (LK-SuperRetina). Furthermore, the study showcases the application of GNNs in image matching, highlighting their superior performance in terms of both the number of good matches and confidence scores. This research sets the stage for expanding GNN applications into various other applications, including but not limited to image classification, segmentation, and registration

Consortium on Vulnerability to Externalizing Disorders and Addictions (cVEDA):A developmental cohort study protocol

Background: Low and middle-income countries like India with a large youth population experience a different environment from that of high-income countries. The Consortium on Vulnerability to Externalizing Disorders and Addictions (cVEDA), based in India, aims to examine environmental influences on genomic variations, neurodevelopmental trajectories and vulnerability to psychopathology, with a focus on externalizing disorders. Methods: cVEDA is a longitudinal cohort study, with planned missingness design for yearly follow-up. Participants have been recruited from multi-site tertiary care mental health settings, local communities, schools and colleges. 10,000 individuals between 6 and 23 years of age, of all genders, representing five geographically, ethnically, and socio-culturally distinct regions in India, and exposures to variations in early life adversity (psychosocial, nutritional, toxic exposures, slum-habitats, socio-political conflicts, urban/rural living, mental illness in the family) have been assessed using age-appropriate instruments to capture socio-demographic information, temperament, environmental exposures, parenting, psychiatric morbidity, and neuropsychological functioning. Blood/saliva and urine samples have been collected for genetic, epigenetic and toxicological (heavy metals, volatile organic compounds) studies. Structural (T1, T2, DTI) and functional (resting state fMRI) MRI brain scans have been performed on approximately 15% of the individuals. All data and biological samples are maintained in a databank and biobank, respectively. Discussion: The cVEDA has established the largest neurodevelopmental database in India, comparable to global datasets, with detailed environmental characterization. This should permit identification of environmental and genetic vulnerabilities to psychopathology within a developmental framework. Neuroimaging and neuropsychological data from this study are already yielding insights on brain growth and maturation patterns.</p

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

A New design using CLRCL Full Adder Logic in 180 nm Technology

Abstract — This article explains a low complexity full adder design using 10 transistors having higher computing speed, lower operating voltage and lower energy consumption. The simulation results, based on 0.18um process models indicate that the proposed de sign has the lowest working Vdd and highest working frequency. Apart from this, the performance edge of the proposed design in terms of speed and energy consumption become even more significant as the word length of the adder increases

Comparative Analysis of 8-Bit Adder Cells Using CLRCL Full Adder Logic

In this paper, we propose a modified low power 10-T Adder design using 10 transistors & 12 transistors featuring higher computing speed, lower operating voltage, and lower energy consumption compared with peer designs. The simulation results, based on 0.18um process models, indicate that the proposed design has the lowest working Vdd and highest working frequency among all designs using 10 transistors & 12 transistors. It also features the lowest energy consumption per addition among these designs. In addition, the performance edge of the proposed design in both speed and energy consumption becomes even more significant as the word length of the adder increases