DenseBAM-GI: Attention Augmented DeneseNet with momentum aided GRU for HMER

The task of recognising Handwritten Mathematical Expressions (HMER) is crucial in the fields of digital education and scholarly research. However, it is difficult to accurately determine the length and complex spatial relationships among symbols in handwritten mathematical expressions. In this study, we present a novel encoder-decoder architecture (DenseBAM-GI) for HMER, where the encoder has a Bottleneck Attention Module (BAM) to improve feature representation and the decoder has a Gated Input-GRU (GI-GRU) unit with an extra gate to make decoding long and complex expressions easier. The proposed model is an efficient and lightweight architecture with performance equivalent to state-of-the-art models in terms of Expression Recognition Rate (exprate). It also performs better in terms of top 1, 2, and 3 error accuracy across the CROHME 2014, 2016, and 2019 datasets. DenseBAM-GI achieves the best exprate among all models on the CROHME 2019 dataset. Importantly, these successes are accomplished with a drop in the complexity of the calculation and a reduction in the need for GPU memory

Bounded PCA based Multi Sensor Image Fusion Employing Curvelet Transform Coefficients

The fusion of thermal and visible images acts as an important device for target detection. The quality of the spectral content of the fused image improves with wavelet-based image fusion. However, compared to PCA-based fusion, most wavelet-based methods provide results with a lower spatial resolution. The outcome gets better when the two approaches are combined, but they may still be refined. Compared to wavelets, the curvelet transforms more accurately depict the edges in the image. Enhancing the edges is a smart way to improve spatial resolution and the edges are crucial for interpreting the images. The fusion technique that utilizes curvelets enables the provision of additional data in both spectral and spatial areas concurrently. In this paper, we employ an amalgamation of Curvelet Transform and a Bounded PCA (CTBPCA) method to fuse thermal and visible images. To evidence the enhanced efficiency of our proposed technique, multiple evaluation metrics and comparisons with existing image merging methods are employed. Our approach outperforms others in both qualitative and quantitative analysis, except for runtime performance. Future Enhancement-The study will be based on using the fused image for target recognition. Future work should also focus on this method’s continued improvement and optimization for real-time video processing

Spy Bot

In various situations, there are times when a person is unable to physically check or provide assistance, leaving a specific action undone. However, with the use of robots, such issues can be resolved, and lives can be saved. To address this need, we have proposed the development of a surveillance robot that can stream real-time videos, transfer audio, and navigate around obstacles. Our aim is to design a system that allows us to wirelessly send commands to the robot, which it will follow accordingly.This proposed system consists of three main parts: the transmitter, receiver, and live streaming section. In the transmitter section, individuals can provide commands to the robot through various means such as gesture or motion tracking. In the receiver section, signals are received and decoded before being sent to the controller, which then directs the robot. Finally, the system is designed to allow for live video streaming to the person monitoring the robot. To achieve this, a common network, such as Wi-Fi, a laptop, and Arduino Uno, will be utilized to enable the surveillance feature for the user. With the implementation of this proposed system, individuals will have access to a reliable and efficient way of remotely checking and assisting in situations where physical presence is not possible. This will provide an effective solution to various problems and, most importantly, save lives

A comprehensive review on nutraceutical potential of underutilized cereals and cereal-based products

Cereals provide nutrients such as lipids, carbs, proteins, minerals, and vitamins and make up the majority of human nutrition. Some cereals also contain a significant quantity of dietary fiber (soluble and insoluble). Cereals, when consumed as a whole or in coloured varieties, are the source of bioactive components with functional properties. Dietary fiber in whole grains has a unique blend of bioactive components such as resistant starch, vitamins, minerals, phytochemicals, and antioxidants that provide different health benefits. Traditionally, whole grains were consumed, but currently, most foods are derived from refined fractions of cereal and pulse crops. Minimal processing of cereals increases both nutrient bioavailability and health benefits. The bioactive compounds present in whole cereals ultimately fight against diseases and prevent or control some diseases in the body, such as cardiovascular risk, reducing the risk of cancer, type-2 diabetes, hypertension, and high blood pressure, improving gastrointestinal health, etc. The consumer demands minimally processed foods, which are essential for maintaining health and improving metabolism. Therefore, developing products using whole cereals or millet to improve the health and safety of humans is of great interest. The present review discusses the nutraceutical potential of cereals and their products, their impact on gut microbiota, and consumer acceptability. The potential for future research in the processing of such healthy cereals in combination with other pseudocereals is identified and discussed

Nanosensor detection of synthetic auxins in planta using corona phase molecular recognition

Synthetic auxins such as 1-naphthalene acetic acid (NAA) and 2,4-dichlorophenoxyacetic acid (2,4-D) have been extensively used in plant tissue cultures and as herbicides because they are chemically more stable and potent than most endogenous auxins. A tool for rapid in planta detection of these compounds will enhance our knowledge about hormone distribution and signaling and facilitate more efficient usage of synthetic auxins in agriculture. In this work, we show the development of real-time and nondestructive in planta NAA and 2,4-D nanosensors based on the concept of corona phase molecular recognition (CoPhMoRe), to replace the current state-of-the-art sensing methods that are destructive and laborious. By designing a library of cationic polymers wrapped around single-walled carbon nanotubes with general affinity for chemical moieties displayed on auxins and its derivatives, we developed selective sensors for these synthetic auxins, with a particularly large quenching response to NAA (46%) and a turn-on response to 2,4-D (51%). The NAA and 2,4-D nanosensors are demonstrated in planta across several plant species including spinach, Arabidopsis thaliana (A. thaliana), Brassica rapa subsp. chinensis (pak choi), and Oryza sativa (rice) grown in various media, including soil, hydroponic, and plant tissue culture media. After 5 h of 2,4-D supplementation to the hydroponic medium, 2,4-D is seen to accumulate in susceptible dicotyledon pak choi leaves, while no uptake is observed in tolerant monocotyledon rice leaves. As such, the 2,4-D nanosensor had demonstrated its capability for rapid testing of herbicide susceptibility and could help elucidate the mechanisms of 2,4-D transport and the basis for herbicide resistance in crops. The success of the CoPhMoRe technique for measuring these challenging plant hormones holds tremendous potential to advance the plant biology study.Agency for Science, Technology and Research (A*STAR)National Research Foundation (NRF)Singapore-MIT Alliance for Research and Technology (SMART)This research was supported by the National Research Foundation (NRF), Prime Minister's Office, Singapore, under its Campus for Research Excellence and Technological Enterprise (CREATE) program. The Disruptive & Sustainable Technology for Agricultural Precision (DiSTAP) is an interdisciplinary research group of the Singapore-MIT Alliance for Research and Technology (SMART) Center. T.T.S.L. was supported on a graduate fellowship by the Agency of Science, Research and Technology, Singapore. M.P. is grateful for the support of the Samsung scholarship. A.D. was supported on the Singapore-MIT undergraduate research fellowship

Phase III Pivotal comparative clinical trial of intranasal (iNCOVACC) and intramuscular COVID 19 vaccine (Covaxin®)

Abstract One of the most preferable characteristics for a COVID-19 vaccine candidate is the ability to reduce transmission and infection of SARS-CoV-2, in addition to disease prevention. Unlike intramuscular vaccines, intranasal COVID-19 vaccines may offer this by generating mucosal immunity. In this open-label, randomised, multicentre, phase 3 clinical trial (CTRI/2022/02/40065; ClinicalTrials.gov: NCT05522335), healthy adults were randomised to receive two doses, 28 days apart, of either intranasal adenoviral vectored SARS-CoV-2 vaccine (BBV154) or licensed intramuscular vaccine, Covaxin®. Between April 16 and June 4, 2022, we enrolled 3160 subjects of whom, 2971 received 2 doses of BBV154 and 161 received Covaxin. On Day 42, 14 days after the second dose, BBV154 induced significant serum neutralization antibody titers against the ancestral (Wuhan) virus, which met the pre-defined superiority criterion for BBV154 over Covaxin®. Further, both vaccines showed cross protection against Omicron BA.5 variant. Salivary IgA titers were found to be higher in BBV154. In addition, extensive evaluation of T cell immunity revealed comparable responses in both cohorts due to prior infection. However, BBV154 showed significantly more ancestral specific IgA-secreting plasmablasts, post vaccination, whereas Covaxin recipients showed significant Omicron specific IgA-secreting plasmablasts only at day 42. Both vaccines were well tolerated. Overall reported solicited reactions were 6.9% and 25.5% and unsolicited reactions were 1.2% and 3.1% in BBV154 and Covaxin® participants respectively