Showing papers by "Indian Institute of Technology Guwahati published in 2021"

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)

Abstract: In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

Rotate to Attend: Convolutional Triplet Attention Module

Abstract: Benefiting from the capability of building interdependencies among channels or spatial locations, attention mechanisms have been extensively studied and broadly used in a variety of computer vision tasks recently. In this paper, we investigate light-weight but effective attention mechanisms and present triplet attention, a novel method for computing attention weights by capturing crossdimension interaction using a three-branch structure. For an input tensor, triplet attention builds inter-dimensional dependencies by the rotation operation followed by residual transformations and encodes inter-channel and spatial information with negligible computational overhead. Our method is simple as well as efficient and can be easily plugged into classic backbone networks as an add-on module. We demonstrate the effectiveness of our method on various challenging tasks including image classification on ImageNet-1k and object detection on MSCOCO and PASCAL VOC datasets. Furthermore, we provide extensive insight into the performance of triplet attention by visually inspecting the GradCAM and GradCAM++ results. The empirical evaluation of our method supports our intuition on the importance of capturing dependencies across dimensions when computing attention weights. Code for this paper can be publicly accessed at https://github.com/LandskapeAI/triplet-attention.

Impact of COVID-19 pandemic on mobility in ten countries and associated perceived risk for all transport modes.

Abstract: The restrictive measures implemented in response to the COVID-19 pandemic have triggered sudden massive changes to travel behaviors of people all around the world. This study examines the individual mobility patterns for all transport modes (walk, bicycle, motorcycle, car driven alone, car driven in company, bus, subway, tram, train, airplane) before and during the restrictions adopted in ten countries on six continents: Australia, Brazil, China, Ghana, India, Iran, Italy, Norway, South Africa and the United States. This cross-country study also aims at understanding the predictors of protective behaviors related to the transport sector and COVID-19. Findings hinge upon an online survey conducted in May 2020 (N = 9,394). The empirical results quantify tremendous disruptions for both commuting and non-commuting travels, highlighting substantial reductions in the frequency of all types of trips and use of all modes. In terms of potential virus spread, airplanes and buses are perceived to be the riskiest transport modes, while avoidance of public transport is consistently found across the countries. According to the Protection Motivation Theory, the study sheds new light on the fact that two indicators, namely income inequality, expressed as Gini index, and the reported number of deaths due to COVID-19 per 100,000 inhabitants, aggravate respondents' perceptions. This research indicates that socio-economic inequality and morbidity are not only related to actual health risks, as well documented in the relevant literature, but also to the perceived risks. These findings document the global impact of the COVID-19 crisis as well as provide guidance for transportation practitioners in developing future strategies.

Prospects for beyond the Standard Model physics searches at the Deep Underground Neutrino Experiment: DUNE Collaboration.

Abstract: The Deep Underground Neutrino Experiment (DUNE) will be a powerful tool for a variety of physics topics. The high-intensity proton beams provide a large neutrino flux, sampled by a near detector system consisting of a combination of capable precision detectors, and by the massive far detector system located deep underground. This configuration sets up DUNE as a machine for discovery, as it enables opportunities not only to perform precision neutrino measurements that may uncover deviations from the present three-flavor mixing paradigm, but also to discover new particles and unveil new interactions and symmetries beyond those predicted in the Standard Model (SM). Of the many potential beyond the Standard Model (BSM) topics DUNE will probe, this paper presents a selection of studies quantifying DUNE’s sensitivities to sterile neutrino mixing, heavy neutral leptons, non-standard interactions, CPT symmetry violation, Lorentz invariance violation, neutrino trident production, dark matter from both beam induced and cosmogenic sources, baryon number violation, and other new physics topics that complement those at high-energy colliders and significantly extend the present reach.

Single-Phase Step-Up Switched-Capacitor-Based Multilevel Inverter Topology With SHEPWM

Abstract: Multilevel inverter (MLI) topologies play a crucial role in the dc–ac power conversion due to their high-quality performance and efficiency. This article aims to propose a new switched-capacitor-based boost multilevel inverter topology (SCMLI). The proposed topology consists of nine power semiconductor switches with one dc voltage source and two capacitors, capable of generating a nine-level output voltage waveform with twice voltage gain. With the addition of two switches, the proposed topology can be used for higher voltage-gain applications. Other features of the proposed topology include the self-voltage balancing of the capacitors, parallel operation of the capacitors, lower voltage stress across the switches, along with the inherent polarity changing capability. To obtain the high-quality output waveform, a selective harmonic elimination pulsewidth modulation technique is applied. In this technique, the detrimental low-order harmonics can easily be regulated and eliminated from the output voltage of MLI. The proposed topology is compared with the recently introduced SCMLI topologies considering various parameters to set the benchmark of the proposed topology. The performance of the proposed MLI is investigated through various experimental results using a laboratory prototype setup.

Development of Active Lower Limb Robotic-Based Orthosis and Exoskeleton Devices: A Systematic Review

Abstract: The basic routine movements for elderly people are not easily accessible due to the weak muscles and impaired nerves in their lower extremity In the last few years, many robotic-based rehabilitation devices, like orthosis and exoskeletons, have been designed and developed by researchers to provide locomotion assistance to support gait behavior and to perform daily activities for elderly people However, there is still a need for improvement in the design, actuation and control of these devices for making them cost-effective in the worldwide market In this work, a systematic review is presented on available lower limb orthosis and exoskeleton devices, to date The devices are broadly reviewed according to joint types, actuation modes and control strategies Furthermore, tabular comparisons have also been presented with the types and applications of these devices Finally, the needful improvements for realizing the efficacy of lower limb rehabilitation devices are discussed along with the development stage This review will help the designers and researchers to develop an efficient robotic device for the rehabilitation of the lower limb

Sustainable materials for 3D concrete printing

Abstract: This paper explores the sustainability aspects of binders used in concrete 3D concrete printing. Firstly, a prospective approach to conduct sustainability-assessment based on the life cycle of 3D printed structures is presented, which also highlights the importance of considering the functional requirements of the mixes used for 3D printing. The potential of the material production phase is emphasized to enhance the sustainability potential of 3DCP by reducing the embodied impacts. The literature on the different binder systems used for producing 3D printable mixtures is reviewed. This review includes binders based on portland cement and supplementary cementing materials (SCMs) such as fly ash, silica-fume and slag. Also, alternative binders such as geopolymer, calcium sulfo-aluminate cement (CSA), limestone calcined clay cement (LC3) and reactive magnesium oxide systems are explored. Finally, sustainability assessment by quantifying the environmental impacts in terms of energy consumed and CO2 emissions of mixtures is illustrated with different binder systems. This paper underlines the effect of using SCMs and alternative binder systems for improving the sustainability of 3D printed structures.

Outage Probability Analysis of IRS-Assisted Systems Under Spatially Correlated Channels

Abstract: This letter investigates the impact of spatial channel correlation on the outage probability of intelligent reflecting surface (IRS)-assisted single-input single-output (SISO) communication systems. In particular, we derive a novel closed-form expression of the outage probability for arbitrary phase shifts and correlation matrices of the indirect channels. To shed light on the impact of the spatial correlation, we further attain the closed-form expressions for two common scenarios met in the literature when the large-scale fading coefficients are expressed by the loss over a propagation distance. Numerical results validate the tightness and effectiveness of the closed-form expressions. Furthermore, the spatial correlation offers significant decreases in the outage probability as the direct channel is blocked.

The Number of Confirmed Cases of Covid-19 by using Machine Learning: Methods and Challenges.

Abstract: Covid-19 is one of the biggest health challenges that the world has ever faced. Public health policy makers need the reliable prediction of the confirmed cases in future to plan medical facilities. Machine learning methods learn from the historical data and make predictions about the events. Machine learning methods have been used to predict the number of confirmed cases of Covid-19. In this paper, we present a detailed review of these research papers. We present a taxonomy that groups them in four categories. We further present the challenges in this field. We provide suggestions to the machine learning practitioners to improve the performance of machine learning methods for the prediction of confirmed cases of Covid-19.

Microalgae: Sustainable resource of carbohydrates in third-generation biofuel production

Abstract: Microalgae have gained interest over the century due to numerous intrinsic attributes surpassing higher plants, making them a potential feedstock for third-generation biofuel production. The current state of art technologies produces biodiesel from microalgal biomass attributed to high intrinsic neutral-lipid contents. However, persisting hurdles in terms of techno-economic feasibility have impeded commercial-scale operations. The latent qualities of microalgae towards the accumulation of multiple high-value products ranging from animal feed to pharmaceuticals adds up to the economic feasibility. Alternatively, the high abundant carbohydrate contents of microalgal strains are used as low-cost substrates for the growth of commercially important microbes to synthesize biofuels. Novel carbohydrate enhancement strategies such as two-stage cultivation, phytohormones, starvation strategies, combinatorial stress strategies, etc., are frequently emerging to mitigate the challenges. Therefore, this study targets to review the recent trends in tuning the microalgal metabolism for increased carbohydrates and associated biofuel generation to attain process feasibility and sustainability. According to recent reports, nitrogen limitation, phosphate limitation, the optimal light intensity with reduced dissolved oxygen, limited inorganic carbon, optimal organic carbon levels, and indole-3-acetic acid augmented the carbohydrate productivity in different microalgal strains. Further analysis on different pretreatment methods highlighted electric-based physical treatment strategies with high efficiencies and less energy requirements of 13.3 kJ to 1.5 MJ per kg biomass. The production cost for microalgae-based bioethanol varies from US$ 1.67 to 31.36 per gallon for different process scenarios, which needs further attention.

Blockchain-Based Adaptive Trust Management in Internet of Vehicles Using Smart Contract

Abstract: In the Internet of Vehicles (IoV), vehicles communicate wirelessly with other vehicles, sensors, pedestrians, and roadside units. IoV is aimed at improving road safety, driving comfort, and traffic efficiency. However, IoV is exposed to a range of threats to security and privacy. The presence of dishonest and misbehaving peers in the system is of a major concern, which may put lives in danger. Thus, establishing trust among these probable untrusted vehicles is one of the most significant challenges of such a network. The critical pitfalls of existing and traditional mechanisms are scalability, a single point of failure, maintaining the quality of service, verification, and revocation and dealing with sparsity, consistency, availability, efficiency, robustness, privacy concerns are some of the biggest challenges to be addressed. Blockchain technology, with its great success in applications like cryptocurrencies and smart contracts, is considered as one of the potential candidates to build trust in IoV. In this paper, we propose a blockchain-based decentralized trust management scheme using smart contracts. Specifically, we introduce the concept of blockchain sharding for reducing the load on the main blockchain and increasing the transaction throughput. Our proposal has two key contributions: blockchain to maintain and update reliable and consistent trust values across the network and incentive scheme to encourage peers to perform well. We also conduct extensive experiments, which demonstrate the implementation feasibility of proposed mechanisms in the real world.

Use of immobilized bacteria for environmental bioremediation: A review

Abstract: Bioremediation is traditionally carried out using ‘free’ bacterial cells; however, in recent years, utilization of ‘immobilized’ bacterial cells has gained attention as a promising technique due to multifarious benefits. This review collates a vast amount of existing literature on the myriad contaminants treated using immobilized bacteria. We also discuss various mechanistic aspects of using immobilized cells for environmental remediation applications, with special attention on cells encapsulated in hydrogels and their implementation in detoxifying harmful contaminants and environmental cleanup. We examine different methods/techniques for immobilizing viable bacterial cells in various supporting matrices, use of single- and multi-species bacterial communities, various growth substrates, and factors affecting the remediation process including mass transfer, kinetic processes and bioreactor configurations used in pilot and field-scale applications. The advantages and limitations associated with the use of immobilized bacteria in a bioreactor for contaminated water treatment are also discussed. From a sustainable futures perspective, resource recovery and retrieval of value-added products along with bioremediation could be an added benefit of the immobilized cell-based treatment system, making it a more cost-effective and viable treatment strategy as well as one that is amenable to the principles of circular economy.

Selenium in soil-microbe-plant systems: Sources, distribution, toxicity, tolerance, and detoxification

Abstract: Selenium is an essential micronutrient required for natural biological systems such as anti-oxidative systems. Despite such beneficial aspect, contamination of selenium and its subsequent bioaccumu...

Supernova neutrino burst detection with the Deep Underground Neutrino Experiment

Abstract: The Deep Underground Neutrino Experiment (DUNE), a 40-kton underground liquid argon time projection chamber experiment, will be sensitive to the electron-neutrino flavor component of the burst of neutrinos expected from the next Galactic core-collapse supernova. Such an observation will bring unique insight into the astrophysics of core collapse as well as into the properties of neutrinos. The general capabilities of DUNE for neutrino detection in the relevant few- to few-tens-of-MeV neutrino energy range will be described. As an example, DUNE's ability to constrain the $ u_e$ spectral parameters of the neutrino burst will be considered.

Antimicrobial Peptides and Proteins: From Nature's Reservoir to the Laboratory and Beyond.

Abstract: Rapid rise of antimicrobial resistance against conventional antimicrobials, resurgence of multidrug resistant microbes and the slowdown in the development of new classes of antimicrobials, necessitates the urgent development of alternate classes of therapeutic molecules. Antimicrobial peptides (AMPs) are small proteins present in different lifeforms in nature that provide defense against microbial infections. They have been effective components of the host defense system for a very long time. The fact that the development of resistance by the microbes against the AMPs is relatively slower or delayed compared to that against the conventional antibiotics, makes them prospective alternative therapeutics of the future. Several thousands of AMPs have been isolated from various natural sources like microorganisms, plants, insects, crustaceans, animals, humans, etc. to date. However, only a few of them have been translated commercially to the market so far. This is because of some inherent drawbacks of the naturally obtained AMPs like 1) short half-life owing to the susceptibility to protease degradation, 2) inactivity at physiological salt concentrations, 3) cytotoxicity to host cells, 4) lack of appropriate strategies for sustained and targeted delivery of the AMPs. This has led to a surge of interest in the development of synthetic AMPs which would retain or improve the antimicrobial potency along with circumventing the disadvantages of the natural analogs. The development of synthetic AMPs is inspired by natural designs and sequences and strengthened by the fusion with various synthetic elements. Generation of the synthetic designs are based on various strategies like sequence truncation, mutation, cyclization and introduction of unnatural amino acids and synthons. In this review, we have described some of the AMPs isolated from the vast repertoire of natural sources, and subsequently described the various synthetic designs that have been developed based on the templates of natural AMPs or from de novo design to make commercially viable therapeutics of the future. This review entails the journey of the AMPs from their natural sources to the laboratory.