Indian Institute of Technology Jodhpur

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.

Metal oxide semiconductors-based gas sensors have been extensively explored due to their high sensing response, cost-effectivity, long-term stability, and simple fabrication. However, their utilization at low operating temperature is still challenging. Thus, reduction in power consumption is highly essential for long-term usage of gas sensors. ZnO nanostructures-based gas sensors are one of the most eligible candidates where a real-time detection of explosive and toxic gases is needed. On this subject, numerous efforts have been made to improve the sensing response at reduced working temperature with the assistance of various methods. In this report, several techniques related to the synthesis of ZnO nanostructures and their efficient performance in sensing are reviewed. The report primarily focuses on different means of improving the sensing properties, such as functionalization of noble metal nanoparticles, doping of metals, inclusion of carbonaceous nanomaterials, using nanocomposites of different MOx, UV activation, and post-treatment method of high-energy irradiation on ZnO nanostructures, with their possible sensing mechanisms. This study will therefore shed light on future proposals of ZnO-based gas sensors showing high sensitivity even at low operating temperature.

This paper performs an extensive review on control schemes and architectures applied to dc microgrids (MGs). It covers multilayer hierarchical control schemes, coordinated control strategies, plug-and-play operations, stability and active damping aspects, as well as nonlinear control algorithms. Islanding detection, protection, and MG clusters control are also briefly summarized. All the mentioned issues are discussed with the goal of providing control design guidelines for dc MGs. The future research challenges, from the authors' point of view, are also provided in the final concluding part.

Two-dimensional materials have gained considerable attention in chemical sensing owing to their naturally high surface-to-volume ratio. However, the poor response time and incomplete recovery at room temperature restrict their application in high-performance practical gas sensors. Herein, we demonstrate ultrafast detection and reversible MoS2 gas sensor at room temperature. The sensor’s performance is investigated to NO2 at room temperature, under thermal and photo energy. Incomplete recovery and high response time of ∼249 s of sensor are observed at room temperature. Thermal energy is enough to complete recovery, but it is at the expense of sensitivity. Further, under photo excitation, MoS2 exhibits an enhancement in sensitivity with ultrafast response time of ∼29 s and excellent recovery to NO2 (100 ppm) at room temperature. This significant improvement in sensitivity (∼30%) and response time (∼88%) is attributed to the charge perturbation on the surface of the sensing layer in the context of NO2/MoS2 interaction under optical illumination. Moreover, the sensor shows reliable selectivity toward NO2 against various other gases. These unprecedented results reveal the potential of 2D MoS2 to develop a low power portable gas sensor.

We present a simple and eco-friendly biosynthesis of silver nanoparticles using Coriandrum sativum leaf extract as reducing agent. The aqueous silver ions when exposed to leaf extract were reduced and resulted in silver nanoparticles whose average size is 26 nm. The silver nanoparticles were characterized by UV-Visible, X-ray diffraction (XRD), Fourier transform infra-red spectroscopy (FT-IR) and transmission electron microscopy (TEM) techniques. Nonlinear optical properties of silver nanoparticles were studied using Z-scan technique with 6 ns pulse duration at 532 nm. The nonlinear refractive index and third-order susceptibility 3 were measured to be ∼ 6 0×10−13 cm2/W and 1 38×10−9 esu, respectively. Silver nanoparticles were found to exhibit strong reverse saturable absorption (RSA). RSA was identified as the main mechanism responsible for optical limiting.

Abstract Recent years have witnessed a resurgence of novel, efficient and practical protocols for radical‐mediated cross‐coupling reactions involving N ‐(acyloxy)phthalimides (NHPI esters) as redox‐active esters. After the initial discovery of the redox‐active properties of NHPI esters, exciting examples of SET‐based cross‐coupling reactions under thermal or photolytic conditions leading to diverse C–X (X=C, B, Si, Se, S) bonds have been published. The operational simplicity and broad applicability exhibited in redox‐active NHPI ester‐based cross‐couplings bode well for their widespread adoption. The review presented herein covers all the recent developments in the field of redox‐active ester (RAE)‐based cross‐couplings since the initial discovery. Depending on the conditions employed the reactions have been categorized into photoinduced and non‐photoinduced cross‐couplings with representative examples and insightful mechanistic discussions. magnified image

Amyloids are a class of protein with unique self-aggregation properties, and their aberrant accumulation can lead to cellular dysfunctions associated with neurodegenerative diseases. While genetic and environmental factors can influence amyloid formation, molecular triggers and/or facilitators are not well defined. Growing evidence suggests that non-identical amyloid proteins may accelerate reciprocal amyloid aggregation in a prion-like fashion. While humans encode ~30 amyloidogenic proteins, the gut microbiome also produces functional amyloids. For example, curli are cell surface amyloid proteins abundantly expressed by certain gut bacteria. In mice overexpressing the human amyloid α-synuclein (αSyn), we reveal that colonization with curli-producing Escherichia coli promotes αSyn pathology in the gut and the brain. Curli expression is required for E. coli to exacerbate αSyn-induced behavioral deficits, including intestinal and motor impairments. Purified curli subunits accelerate αSyn aggregation in biochemical assays, while oral treatment of mice with a gut-restricted amyloid inhibitor prevents curli-mediated acceleration of pathology and behavioral abnormalities. We propose that exposure to microbial amyloids in the gastrointestinal tract can accelerate αSyn aggregation and disease in the gut and the brain.

Inflammation in the brain accompanies several high-impact neurological diseases including multiple sclerosis (MS), stroke, and Alzheimer’s disease. Neuroinflammation is sterile, as damage-associated molecular patterns rather than microbial pathogens elicit the response. The inflammasome, which leads to caspase-1 activation, is implicated in neuroinflammation. In this study, we reveal that lysophosphatidylcholine (LPC), a molecule associated with neurodegeneration and demyelination, elicits NLRP3 and NLRC4 inflammasome activation in microglia and astrocytes, which are central players in neuroinflammation. LPC-activated inflammasome also requires ASC (apoptotic speck containing protein with a CARD), caspase-1, cathepsin-mediated degradation, calcium mobilization, and potassium efflux but not caspase-11. To study the physiological relevance, Nlrc4−/− and Nlrp3−/− mice are studied in the cuprizone model of neuroinflammation and demyelination. Mice lacking both genes show the most pronounced reduction in astrogliosis and microglial accumulation accompanied by decreased expression of the LPC receptor G2A, whereas MS patient samples show increased G2A. These results reveal that NLRC4 and NLRP3, which normally form distinct inflammasomes, activate an LPC-induced inflammasome and are important in astrogliosis and microgliosis.

Abstract Dengue is considered as a major health issue which causes a number of deaths worldwide each year; tropical countries are majorly affected by dengue outbreaks. It is considered as life threatening issue because, since many decades not a single effective approach for treatment and prevention of dengue has been developed. Therefore, to find new preventive measure, we used immunoinformatics approaches to develop a multi-epitope based subunit vaccine for dengue which can generate various immune responses inside the host. Different B-cell, T C cell, and T H cell binding epitopes were predicted for structural and non-structural proteins of dengue virus. Final vaccine constructs consisting of T C and T H cell epitopes and an adjuvant (β-defensin) at N-terminal of the construct. Presence of B-cell and IFN-γ inducing epitopes confirms the humoral and cell mediated immune response developed by designed vaccine. Designed vaccine was not found allergic and was potentially antigenic in nature. Modeling of tertiary structure and the refined model was used for molecular docking with TLR-3 (immune receptor). Molecular docking and dynamics simulation confirms the microscopic interactions between ligand and receptor. In silico cloning approach was used to ensure the expression and translation efficiency of vaccine within an expression vector.

Room-temperature gas sensors have aroused great attention in current gas sensor technology because of deemed demand of cheap, low power consumption and portable sensors for rapidly growing Internet of things applications. As an important approach, light illumination has been exploited for room-temperature operation with improving gas sensor's attributes including sensitivity, speed and selectivity. This review provides an overview of the utilization of photoactivated nanomaterials in gas sensing field. First, recent advances in gas sensing of some exciting different nanostructures and hybrids of metal oxide semiconductors under light illumination are highlighted. Later, excellent gas sensing performance of emerging two-dimensional materials-based sensors under light illumination is discussed in details with proposed gas sensing mechanism. Originated impressive features from the interaction of photons with sensing materials are elucidated in the context of modulating sensing characteristics. Finally, the review concludes with key and constructive insights into current and future perspectives in the light-activated nanomaterials for optoelectronic gas sensor applications.

The past decade has witnessed the emergence of N-(acyloxy)phthalimides (NHPI esters) and its derivatives at the forefront of synthetic methods facilitating the construction of diverse molecular frameworks from the readily available carboxylic acid feedstock. The NHPI esters are predisposed to undergo reductive fragmentation via a single electron transfer (SET) process under thermal, photochemical, or electrochemical conditions to generate the corresponding carbon- or nitrogen-centered radicals that participate in a multitude of synthetic transformations to forge carbon–carbon and carbon–heteroatom bonds. The chemistry involving NHPI esters has received broad applicability not only in well-designed cascade annulations but also in medicinal chemistry and natural product synthesis. This comprehensive Review, broadly categorized according to the nature of the bond formation, details the progress made in this field since the initial discovery by providing representative examples with mechanistic details, with an emphasis on challenges and future directions.

We demonstrated an ultrahigh-performance and self-powered β-Ga2O3 thin film solar-blind photodetector fabricated on a cost-effective Si substrate using a high-temperature seed layer (HSL). The polycrystalline β-Ga2O3 thin film deposited with HSL shows high performance in the solar-blind region in comparison to the amorphous Ga2O3 thin film deposited without HSL. The zero-bias digitizing sensor prototype with an HSL produces a digitized output bit with deep UV (DUV) light that exhibits a high on/off (I254 nm/Idark) ratio of >103, a record-low dark current of 1.43 pA, and high stability and reproducibility over 100 cycles even after >2100 h. The photodetector shows minimum persistent photoconductivity and fast response in milliseconds. The photodetector yields a responsivity of 96.13 A W–1 with an external quantum efficiency of 4.76 × 104 at 5 V for 250 nm monochromatic light. The photodetector shows a high response to even a rare weak signal of DUV (44 nW/cm2). These values are the highest reported to date for a planar β-Ga2O3 thin film based photodetector despite the use of the cost-effective substrate. The asymmetric I–V curve indicates a dissimilar Schottky barrier height at the two ends of the MSM photodetector, which is discussed as the main reason for the high response even at zero bias. This work provides the guidelines to develop a β-Ga2O3-based cost-effective, self-powered, high-performance, and fast DUV photodetector that possesses a high potential for next-generation practical solar-blind photodetector application.

Abstract In gas sensor technology, current research efforts are focused on developing a high performance miniaturized gas sensor operating at room temperature. In recent years, layered semiconducting material MoS 2 has gained vast attention in sensing field owing to the detection of a variety of analytes at room temperature, high surface‐to‐volume ratio, and also provided substantial advantages in emerging flexible and wearable sensing field. Herein, a state‐of‐art overview of the utilization of burgeoning MoS 2 research in gas sensing applications is provided. The synthesis of some exciting different nanostructures and hybrids of the MoS 2 on a rigid as well as flexible substrate is summarized, as they play an important role in tuning the gas sensing characteristic of the MoS 2 . The gas sensing performance of the MoS 2 sensors with proposed mechanisms is discussed in the context of a wide range of different morphologies/nanostructures, nanocomposites, van der Waals heterostructures, and photoactivation effects. Moreover, rapid advances and growing significance of the MoS 2 on the emerging flexible gas sensing platform are also highlighted. Finally, some insights into new challenges and future perspectives in the promising MoS 2 research for gas sensing applications are presented.

Abstract The usage of the gas sensor has been increasing very rapidly in the industry and in daily life for various potential applications. In the recent years, metal oxide semiconductors (MOS) become the primary choice for designing highly sensitive, stable, and low‐cost real‐life applications‐based gas sensors due to their inherent physical and chemical properties. Researchers have proposed numerous sensing mechanisms to explain the functionality of MOS‐based gas sensors. In this review, we have comprehensively covered different sensing mechanisms used for MOS. We have also discussed different parameters affecting the sensitivity and selectivity of the gas sensors. Moreover, the different techniques used to enhance the gas sensing response of MOS‐based sensors are also extensively covered. And finally, we give our prospective on recent opportunities and challenges on the future applications of MOS‐based gas sensors.

Resolving momentum degrees of freedom of excitons, which are electron-hole pairs bound by the Coulomb attraction in a photoexcited semiconductor, has remained an elusive goal for decades. In atomically thin semiconductors, such a capability could probe the momentum-forbidden dark excitons, which critically affect proposed opto-electronic technologies but are not directly accessible using optical techniques. Here, we probed the momentum state of excitons in a tungsten diselenide monolayer by photoemitting their constituent electrons and resolving them in time, momentum, and energy. We obtained a direct visual of the momentum-forbidden dark excitons and studied their properties, including their near degeneracy with bright excitons and their formation pathways in the energy-momentum landscape. These dark excitons dominated the excited-state distribution, a surprising finding that highlights their importance in atomically thin semiconductors.

Heater plates or sheets that are visibly transparent have many interesting applications in optoelectronic devices such as displays, as well as in defrosting, defogging, gas sensing and point-of-care disposable devices. In recent years, there have been many advances in this area with the advent of next generation transparent conducting electrodes (TCE) based on a wide range of materials such as oxide nanoparticles, CNTs, graphene, metal nanowires, metal meshes and their hybrids. The challenge has been to obtain uniform and stable temperature distribution over large areas, fast heating and cooling rates at low enough input power yet not sacrificing the visible transmittance. This review provides topical coverage of this important research field paying due attention to all the issues mentioned above.

This review aims at providing a comprehensive summary of the current advancements in 2D/metal-oxide based heterostructures as gas sensors.

In this paper we introduce a large-scale hand pose dataset, collected using a novel capture method. Existing datasets are either generated synthetically or captured using depth sensors: synthetic datasets exhibit a certain level of appearance difference from real depth images, and real datasets are limited in quantity and coverage, mainly due to the difficulty to annotate them. We propose a tracking system with six 6D magnetic sensors and inverse kinematics to automatically obtain 21-joints hand pose annotations of depth maps captured with minimal restriction on the range of motion. The capture protocol aims to fully cover the natural hand pose space. As shown in embedding plots, the new dataset exhibits a significantly wider and denser range of hand poses compared to existing benchmarks. Current state-of-the-art methods are evaluated on the dataset, and we demonstrate significant improvements in cross-benchmark performance. We also show significant improvements in egocentric hand pose estimation with a CNN trained on the new dataset.

In this letter, a compact octagonal shaped fractal ultrawideband multiple-input-multiple-output antenna is presented, and its characteristics are investigated. In order to achieve the desired miniaturization and wideband phenomena, self-similar and space filling properties of Koch fractal geometry are used in the antenna design. These fractal monopoles are placed orthogonal to each other for good isolation. Moreover, grounded stubs are used in the geometry to provide further improvement in the isolation. The band rejection phenomenon in wireless local area network band is achieved by etching a C-shaped slot from the monopole of the antenna. The proposed antenna has compact dimensions of 45 mm × 45 mm and exhibits quasi-omnidirectional radiation pattern. In addition, it shows an impedance bandwidth (S <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">11</sub> <; -10 dB ) from 2 to 10.6 GHz with isolation better than 17 dB over the entire ultra-wideband range. Diversity performance is also evaluated in terms of envelope correlation coefficient and capacity loss. The measured results show good agreement with the simulated ones.

Proteins are the essential biological macromolecules required to perform nearly all biological processes, and cellular functions. Proteins rarely carry out their tasks in isolation but interact with other proteins (known as protein-protein interaction) present in their surroundings to complete biological activities. The knowledge of protein-protein interactions (PPIs) unravels the cellular behavior and its functionality. The computational methods automate the prediction of PPI and are less expensive than experimental methods in terms of resources and time. So far, most of the works on PPI have mainly focused on sequence information. Here, we use graph convolutional network (GCN) and graph attention network (GAT) to predict the interaction between proteins by utilizing protein's structural information and sequence features. We build the graphs of proteins from their PDB files, which contain 3D coordinates of atoms. The protein graph represents the amino acid network, also known as residue contact network, where each node is a residue. Two nodes are connected if they have a pair of atoms (one from each node) within the threshold distance. To extract the node/residue features, we use the protein language model. The input to the language model is the protein sequence, and the output is the feature vector for each amino acid of the underlying sequence. We validate the predictive capability of the proposed graph-based approach on two PPI datasets: Human and S. cerevisiae. Obtained results demonstrate the effectiveness of the proposed approach as it outperforms the previous leading methods. The source code for training and data to train the model are available at https://github.com/JhaKanchan15/PPI_GNN.git .