Motilal Nehru National Institute of Technology

Nanomedicine and nano delivery systems are a relatively new but rapidly developing science where materials in the nanoscale range are employed to serve as means of diagnostic tools or to deliver therapeutic agents to specific targeted sites in a controlled manner. Nanotechnology offers multiple benefits in treating chronic human diseases by site-specific, and target-oriented delivery of precise medicines. Recently, there are a number of outstanding applications of the nanomedicine (chemotherapeutic agents, biological agents, immunotherapeutic agents etc.) in the treatment of various diseases. The current review, presents an updated summary of recent advances in the field of nanomedicines and nano based drug delivery systems through comprehensive scrutiny of the discovery and application of nanomaterials in improving both the efficacy of novel and old drugs (e.g., natural products) and selective diagnosis through disease marker molecules. The opportunities and challenges of nanomedicines in drug delivery from synthetic/natural sources to their clinical applications are also discussed. In addition, we have included information regarding the trends and perspectives in nanomedicine area.

The present study investigates ameliorative effect of nitric oxide (NO) against zinc oxide nanoparticles (ZnONPs) phytotoxicity in wheat seedlings. ZnONPs exposure hampered growth of wheat seedlings which was coincided with reduced photosynthetic efficiency (Fv/Fm and qP) due to increased accumulation of zinc (Zn) in xylem and phloem saps. However, SNP supplementation has partially mitigated the ZnONPs-mediated toxicity by modulation of photosynthetic activity and Zn accumulation in xylem and phloem sap. Further, the results reveal that ZnONPs treatments enhanced level of hydrogen peroxide (H2O2) and hence lipid peroxidation (as malondialdehyde; MDA) due to severely inhibited activities of the ascorbate-glutatione cycle (AsA-GSH) enzymes: ascorbate peroxidase (APX), glutathione reductase (GR), monodehydroascorbate reductase (MDHAR) and dehydroascorbate reductase (DHAR), and its associated metabolites: reduced ascorbate and glutathione. In contrast to this, the addition of SNP together with ZnONPs maintained the cellular functioning of the AsA-GSH cycle properly, hence lesser damage was noticed in comparison to ZnONPs treatments alone. The protective effect of SNP against ZnONPs toxicity on fresh weight (growth) can be reversed by 2-(4carboxy-2-phenyl)-4,4,5,5-tetramethyl- imidazoline-1-oxyl-3-oxide, a NO scavenger, suggesting role of NO released from SNP in ameliorating ZnONPs toxicity. Overall the results of the present study have shown about implication of NO in the reducing ZnONPs toxicity through the regulation of accumulation of Zn, and functioning of the AsA-GSH cycle.

Agricultural productivity is something on which economy highly depends. This is the one of the reasons that disease detection in plants plays an important role in agriculture field, as having disease in plants are quite natural. If proper care is not taken in this area then it causes serious effects on plants and due to which respective product quality, quantity or productivity is affected. For instance a disease named little leaf disease is a hazardous disease found in pine trees in United States. Detection of plant disease through some automatic technique is beneficial as it reduces a large work of monitoring in big farms of crops, and at very early stage itself it detects the symptoms of diseases i.e. when they appear on plant leaves. This paper presents an algorithm for image segmentation technique which is used for automatic detection and classification of plant leaf diseases. It also covers survey on different diseases classification techniques that can be used for plant leaf disease detection. Image segmentation, which is an important aspect for disease detection in plant leaf disease, is done by using genetic algorithm.

Abiotic stress is one of the severe stresses of environment that lowers the growth and yield of any crop even on irrigated land throughout the world. A major phytohormone abscisic acid (ABA) plays an essential part in acting towards varied range of stresses like heavy metal stress, drought, thermal or heat stress, high level of salinity, low temperature and radiation stresses. It also finds its role in various developmental processes including seed germination, seed dormancy, and closure of stomata. Abscisic acid acts by modifying the expression level of gene and subsequent analysis of cis- and trans-acting regulatory elements of responsive promoters. It also interacts with the signaling molecules of processes involved in retorting to stresses and development of seeds. On the whole, the stress to a plant can be susceptible or tolerant by taking into account the coordinated activities of various stress-responsive genes. Numbers of transcription factor are involved in regulating the expression of abscisic acid responsive genes by acting together with their respective cis‑acting elements. Hence, for improvement in stress-tolerance capacity of plants, it is necessary to understand the mechanism behind it. On this ground, this article enlightens the importance and role of ABA signaling with regard to various stresses as well as regulation of abscisic acid biosynthetic pathway along with the transcription factors for stress tolerance.

Second-generation bioethanol can be produced from various lignocellulosic biomasses such as wood, agricultural or forest residues. Lignocellulosic biomass is inexpensive, renewable and abundant source for bioethanol production. The conversion of lignocellulosic biomass to bioethanol could be a promising technology though the process has several challenges and limitations such as biomass transport and handling, and efficient pretreatment methods for total delignification of lignocellulosics. Proper pretreatment methods can increase concentrations of fermentable sugars after enzymatic saccharification, thereby improving the efficiency of the whole process. Conversion of glucose as well as xylose to bioethanol needs some new fermentation technologies to make the whole process inexpensive. The main goal of pretreatment is to increase the digestibility of maximum available sugars. Each pretreatment process has a specific effect on the cellulose, hemicellulose and lignin fraction; thus, different pretreatment methods and conditions should be chosen according to the process configuration selected for the subsequent hydrolysis and fermentation steps. The cost of ethanol production from lignocellulosic biomass in current technologies is relatively high. Additionally, low yield still remains as one of the main challenges. This paper reviews the various technologies for maximum conversion of cellulose and hemicelluloses fraction to ethanol, and it point outs several key properties that should be targeted for low cost and maximum yield.

Mobile payment solutions (MPSs) are experiencing growth and popularity across the globe because of their convenience and other benefits in performing transactions. However, despite these circumstances and the benefits offered, MPSs are still suffering from challenging situations related to their adoption and usage. The main challenge MPSs have faced in retail is because of the presence of consumer resistance toward their use. The present study investigates the different consumer barriers toward the intentions to use and recommend MPSs. The current study examines the adoption and usage of MPSs through the lens of innovation resistance. We developed the research model based on the innovation resistance theory (IRT) and tested it using a large cross-sectional study with 1256 MPS users. The study findings suggest that usage, risk, and value barriers are negatively associated with intentions to use MPSs. On the other hand, only usage and value barriers have a negative association with users’ intention to recommend MPSs. In comparison, the tradition and image barriers did not share any association with the user intentions. The study offers different implications for practitioners and researchers.

Abstract In the fast changing global business, knowledge management (KM) has emerged as an integral part of business strategy. Many business organizations have implemented KM and many are in the process of its implementation. KM implementation is adversely affected by few factors which are known as KM barriers. The objective of this paper is to develop the relationships among the identifiedKMbarriers. Further, this paper is also helpful to understand mutual influences of barriers and to identify those barriers which support other barriers (driving barrier) and also those barriers which are most influenced by other barriers (dependent barriers). The interpretive structural modeling (ISM) methodology is used to evolve mutual relationships among these barriers. KM barriers have been classified, based on their driving power and dependence power. The objective behind this classification is to analyze the driving power and dependence power of these barriers.

Heavy metals (HMs) exists in the environment in both forms as essential and non-essential. These HM ions enter in soil biota from various sources like natural and anthropogenic. Essential HMs such as cobalt (Co), copper (Cu), iron (Fe), manganese (Mn), molybdenum (Mo), nickel (Ni), and zinc (Zn) plays a beneficial role in plant growth and development. At optimum level these beneficial elements improves the plant’s nutritional level and also several mechanisms essential for the normal growth and better yield of plants. The range of their optimality for land plants is varied. Plant uptake heavy metals as a soluble component or solubilized them by root exudates. While their presence in excess become toxic for plants that switches the plant’s ability to uptake and accumulate other nonessential elements. The increased amount of HMs within the plant tissue displays direct and indirect toxic impacts. Such direct effects are the generation of oxidative stress which further aggravates inhibition of cytoplasmic enzymes and damage to cell structures. Although, indirect possession is the substitution of essential nutrients at plant’s cation exchange sites. These ions readily influence role of various enzymes and proteins, arrest metabolism, and reveal phytotoxicity. On account of recent advancements on beneficial HMs ions Co, Cu, Fe, Mn, Mo, Ni, and Zn in soil-plant system, the present paper: overview the sources of HMs in soils and their uptake and transportation mechanism, here we have discussed the role of metal transporters in transporting the essential metal ions from soil to plants. The role played by Co, Cu, Fe, Mn, Mo, Ni, and Zn at both low and high level on the plant growth and development and the mechanism to alleviate metal toxicity at high level have been also discussed. At the end, on concluding the article we have also discussed the future perspective in respect to beneficial HM ions interaction with plant at both levels.

Nanotechnology is a cutting-edge field of science with the potential to revolutionize today's technological advances including industrial applications. It is being utilized for the welfare of mankind; but at the same time, the unprecedented use and uncontrolled release of nanomaterials into the environment poses enormous threat to living organisms. Silver nanoparticles (AgNPs) are used in several industries and its continuous release may hamper many physiological and biochemical processes in the living organisms including autotrophs and heterotrophs. The present review gives a concentric know-how of the effects of AgNPs on the lower and higher autotrophic plants as well as on heterotrophic microbes so as to have better understanding of the differences in effects among these two groups. It also focuses on the mechanism of uptake, translocation, accumulation in the plants and microbes, and resulting toxicity as well as tolerance mechanisms by which these microorganisms are able to survive and reduce the effects of AgNPs. This review differentiates the impact of silver nanoparticles at various levels between autotrophs and heterotrophs and signifies the prevailing tolerance mechanisms. With this background, a comprehensive idea can be made with respect to the influence of AgNPs on lower and higher autotrophic plants together with heterotrophic microbes and new insights can be generated for the researchers to understand the toxicity and tolerance mechanisms of AgNPs in plants and microbes.

Abstract Groundwater is an important source for drinking water supply in hard rock terrain of Bundelkhand massif particularly in District Mahoba, Uttar Pradesh, India. An attempt has been made in this work to understand the suitability of groundwater for human consumption. The parameters like pH, electrical conductivity, total dissolved solids, alkalinity , total hardness, calcium, magnesium, sodium, potassium, bicarbonate, sulfate, chloride, fluoride, nitrate, copper, manganese, silver, zinc, iron and nickel were analysed to estimate the groundwater quality. The water quality index (WQI) has been applied to categorize the water quality viz: excellent, good, poor, etc. which is quite useful to infer the quality of water to the people and policy makers in the concerned area. The WQI in the study area ranges from 4.75 to 115.93. The overall WQI in the study area indicates that the groundwater is safe and potable except few localized pockets in Charkhari and Jaitpur Blocks. The Hill-Piper Trilinear diagram reveals that the groundwater of the study area falls under Na + -Cl − , mixed Ca 2+ -Mg 2+ -Cl − and Ca 2+ - $${\text{HCO}}_{3}^{ - }$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msubsup> <mml:mtext>HCO</mml:mtext> <mml:mrow> <mml:mn>3</mml:mn> </mml:mrow> <mml:mo>-</mml:mo> </mml:msubsup> </mml:math> types. The granite-gneiss contains orthoclase feldspar and biotite minerals which after weathering yields bicarbonate and chloride rich groundwater. The correlation matrix has been created and analysed to observe their significant impetus on the assessment of groundwater quality. The current study suggests that the groundwater of the area under deteriorated water quality needs treatment before consumption and also to be protected from the perils of geogenic/anthropogenic contamination.

This paper reports the structural and optical properties and comparative photocatalytic activity of TiO2 and Ag-doped TiO2 nanoparticles against different bacterial strains under visible-light irradiation. The TiO2 and Ag-doped TiO2 photocatalysts were synthesized by acid catalyzed sol-gel technique and characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM), UV-vis spectroscopy and photoluminescence (PL). The XRD pattern revealed that the annealed sample of TiO2 has both anatase and rutile phases while only an anatase phase was found in Ag-doped TiO2 nanoparticles. The decreased band-gap energy of Ag-doped TiO2 nanoparticles in comparison to TiO2 nanoparticles was investigated by UV-vis spectroscopy. The rate of recombination and transfer behaviour of the photoexcited electron-hole pairs in the semiconductors was recorded by photoluminescence. The antimicrobial activity of TiO2 and Ag-doped TiO2 nanoparticles (3% and 7%) was investigated against both gram positive (Staphylococcus aureus) and gram negative (Pseudomonas aeruginosa, Escherichia coli) bacteria. As a result, the viability of all three microorganisms was reduced to zero at 60 mg/30 mL culture in the case of both (3% and 7% doping) concentrations of Ag-doped TiO2 nanoparticles. Annealed TiO2 showed zero viability at 80 mg/30 mL whereas doped Ag-TiO2 7% showed zero viability at 40 mg/30 mL culture in the case of P. aeruginosa only.

Abstract Landslide, one of the most critical natural hazards, is caused due to specific compositional slope movement. In the past decades, due to inflation of urbanized area and climate change, a compelling expansion in landslide prevalence took place which is also termed as mass/slope movement and mass wasting, causing extensive collapse around the world. The principal reason for its pursuance is a reduction in the internal resistance of soil and rocks, classified as a slide, topple, fall, and flow. Slopes can be differentiated based on earth material and the nature of its movements. The downward flow of landslides occurs due to excessive rainfall, snowmelt, earthquake, volcanic eruption, and so on. This review article revisits the conventional approaches for identification of landslides, predicting future risk, associated with slope failures, followed by emphasizing the advantages of modern geospatial techniques such as aerial photogrammetry, satellite remote sensing images (ie, panchromatic, multispectral, radar images), Terrestrial laser scanning, and High‐Resolution Digital Elevation Model (HR‐DEM) in updating landslide inventory maps. Machine learning techniques like Support Vector Machine, Artificial neural network, deep learning has been extensively used with geographical data producing effective results for assessment of natural hazard/resources and environmental research. Based on recent studies, deep learning is a reliable tool addressing remote sensing challenges such as trade‐off in imaging system producing poor quality investigation, in addition, to expedite consequent task such as image recognition, object detection, classification, and so on. Conventional methods, like pixel and object‐based machine learning methods, have been broadly explored. Advanced development in deep learning technique like CNN (Convolutional neural network) has been extensively successful in information extraction from an image and has exceeded other traditional approaches. Over the past few years, minor attempts have been made for landslide susceptibility mapping using CNN. In addition, small sample sizes for training purpose will be major drawback and notably remarkable while using deep learning techniques. Also, assessment of the model's performance with diverse training and testing proportion other than commonly utilized ratio, that is, 70/30 needs to be explored further. The review article briefly highlights the remote sensing methods for landslide detection using machine learning and deep learning.

In recent decades, demand for sustainable materials in place of low cost and high strength materials has been trigged globally, which has motivated researchers towards biocomposites/green composites. The PLA has been the most promising matrix material for suistanable biocomposites owing to its biodegradability, good availability, eco-friendliness, antibacterial property, and good mechanical and thermal properties. The PLA-based biocomposites are economical, full/partial biodegradable depends upon types of reinforcement, light in weight, and also offer good thermal and mechanical properties. A number of research works have been performed on PLA and its biocomposites to explore their potential for sustainable products. However, no comprehensive review with up-to-date research data on PLA and its biocomposites are reported so far. This fact motivated to summerize the reported studies on PLA and its biocomposites. The aim of present review is to highlight the current and past trends in the research of PLA and its biocomposites. This review article covers current and past efforts reported by researchers on the synthesis and sustainability of PLA, processing, characterization, applications and future scope of its biocomposites. This study observed that PLA-based composites are the most emerging materials that can replace existing non-biodegradable and non-renewable synthetic materials. The PLA-based biocomposites could be considered as the best source of sustainable products. PLA's mechanical and thermal properties can be enhanced by reinforcing the nano and micro sizes of natural fibers and cellulose.

A review on the mechanical properties of hybrid fibers-reinforced polymer composite is presented in this article. Fiber-reinforced polymer composite has a lot of advantages such as high strength, low density, and ease of processing. Fiber-reinforced polymer composite has been used in many areas such as aerospace, automotive, and construction. Incorporation of two or more fibers into a single polymer matrix leads the development of hybrid composite. Hybridization can improve the mechanical properties of single fiber-reinforced polymer composite. This study shows that mechanical properties of natural fiber-reinforced polymer composite increase due to incorporation of comparably high elongation fibers.

In this age of globalization, to survive, organizations need a good capacity to retain, develop, organize and utilize their knowledge assets. The knowledge of an organization comprises of professional intellect, such as know‐how, know‐why, and self‐motivated creativity; as also the experience, concepts, values, beliefs and ways of working that can be shared and communicated. Knowledge Management (KM) is described as the management of an organization’s knowledge through the processes of creating, sustaining, applying, sharing and renewing knowledge to enhance organizational performance and create value. Interpretive Structual Modeling (ISM) is a methodology for identifying and summarizing relationships among specific elements, which define an issue or problem. It provides a means by which order can be imposed on the complexity of such elements. In the present paper the important elements (also referred to as variables) for the implementation of KM in engineering industries have been analyzed to obtain an ISM, which shows the inter‐relationships of the variables and their levels. These variables have also been categorized depending on their driving power and dependence.

In this paper, comparative study between wavelet transform (WT) and <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">S</i> -transform (ST) based on extracted features for detection of islanding and power quality (PQ) disturbances in hybrid distributed generation (DG) system is presented. The hybrid system consists of DG resources like photovoltaic, fuel cell, and wind energy systems connected to grid. The negative sequence component of the voltage signal is used in islanding detection of these resources from the grid. Voltage signal extracted directly at the point of common coupling is considered for detection of PQ disturbances. Further, the effect of variation of grid impedances on islanding and PQ disturbances and effect of islanding on the coherency between the energy resources is also presented in this paper. The study for different scenarios of DG system is presented in the form of time-frequency analysis. The energy content and standard deviation of ST contour and WT signal is also reported in order to validate the graphical results. The results demonstrate the advantages of <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">S</i> -transform over WT in detection of islanding and different disturbances under noise-free as well as noisy scenarios.

Abstract The increasing use and effectiveness of social media influencers in marketing have intrigued both academic scholars and industry professionals. To shed light on the foundations and trends of this contemporary phenomenon, this study undertakes a systematic literature review using a bibliometric-content analysis to map the extant literature where consumer behavior, social media, and influencer marketing are intertwined. Using 214 articles published in journals indexed by the Australian Business Deans Council (ABDC), Chartered Association of Business Schools (CABS), and Web of Science (WOS) from 2008 to 2021, this study unpacks the articles, journals, methods, theories, themes, and constructs (antecedents, moderators, mediators, and consequences) in extant research on social media influencer marketing. Noteworthily, the review highlighted that the major research streams in social media influencer marketing research involve parasocial interactions and relationships, sponsorship, authenticity, and engagement and influence. The review also revealed the prominent role of audience-, brand-, comparative-, content-, influencer-, social-, and technology-related factors in influencing how consumers react to social media influencer marketing. The insights derived from this one-stop, state-of-the-art review can help social media influencers and marketing scholars and professionals to recognize key characteristics and trends of social media influencer marketing, and thus, drive new research and social media marketing practices where social media influencers are employed and leveraged upon for marketing activities.

The remediation of polluted sites has become a priority for society because of increase in quality of life standards and the awareness of environmental issues. Over the past few decades there has been avid interest in developing in situ strategies for remediation of environmental contaminants, because of the high economic cost of physicochemical strategies, the biological tools for remediation of these persistent pollutants is the better option. Major foci have been considered on persistent organic chemicals i.e. polyaromatic hydrocarbons (PAHs) due to their ubiquitous occurrence, recalcitrance, bioaccumulation potential and carcinogenic activity. Rhizoremediation, a specific type of phytoremediation that involves both plants and their associated rhizospheric microbes is the creative biotechnological approach that has been explored in this review. Moreover, in this review we showed the significance of rhizoremediation of PAHs from other bioremediation strategies i.e. natural attenuation, bioaugmentation and phytoremediation and also analyze certain environmental factor that may influence the rhizoremediation technique. Numerous bacterial species were reported to degrade variety of PAHs and most of them are isolated from contaminated soil, however few reports are available from non contaminated soil. Pseudomonas aeruginosa , Pseudomons fluoresens , Mycobacterium spp., Haemophilus spp., Rhodococcus spp., Paenibacillus spp. are some of the commonly studied PAH-degrading bacteria. Finally, exploring the molecular communication between plants and microbes, and exploiting this communication to achieve better results in the elimination of contaminants, is a fascinating area of research for future perspective.

ABSTRACT Chitin and chitosan are versatile polymers, where the interest in chitosan is due to the large variety of useful forms that are commercially available or can be made available. Chitin basically is obtained from prawn/crab shells; chemical treatment of chitin produces chitosan. This article surveys applications of chitin and chitosan in various industrial and biomedical fields.

Gold nanoparticles (AuNPs) have been widely explored and are well-known for their medical applications. Chemical and physical synthesis methods are a way to make AuNPs. In any case, the hunt for other more ecologically friendly and cost-effective large-scale technologies, such as environmentally friendly biological processes known as green synthesis, has been gaining interest by worldwide researchers. The international focus on green nanotechnology research has resulted in various nanomaterials being used in environmentally and physiologically acceptable applications. Several advantages over conventional physical and chemical synthesis (simple, one-step approach to synthesize, cost-effectiveness, energy efficiency, and biocompatibility) have drawn scientists' attention to exploring the green synthesis of AuNPs by exploiting plants' secondary metabolites. Biogenic approaches, mainly the plant-based synthesis of metal nanoparticles, have been chosen as the ideal strategy due to their environmental and in vivo safety, as well as their ease of synthesis. In this review, we reviewed the use of green synthesized AuNPs in the treatment of cancer by utilizing phytochemicals found in plant extracts. This article reviews plant-based methods for producing AuNPs, characterization methods of synthesized AuNPs, and discusses their physiochemical properties. This study also discusses recent breakthroughs and achievements in using green synthesized AuNPs in cancer treatment and different mechanisms of action, such as reactive oxygen species (ROS), mediated mitochondrial dysfunction and caspase activation, leading to apoptosis, etc., for their anticancer and cytotoxic effects. Understanding the mechanisms underlying AuNPs therapeutic efficacy will aid in developing personalized medicines and treatments for cancer as a potential cancer therapeutic strategy.