Birla Institute of Technology, Mesra

Flavonoids, a group of natural substances with variable phenolic structures, are found in fruits, vegetables, grains, bark, roots, stems, flowers, tea and wine. These natural products are well known for their beneficial effects on health and efforts are being made to isolate the ingredients so called flavonoids. Flavonoids are now considered as an indispensable component in a variety of nutraceutical, pharmaceutical, medicinal and cosmetic applications. This is attributed to their anti-oxidative, anti-inflammatory, anti-mutagenic and anti-carcinogenic properties coupled with their capacity to modulate key cellular enzyme function. Research on flavonoids received an added impulse with the discovery of the low cardiovascular mortality rate and also prevention of CHD. Information on the working mechanisms of flavonoids is still not understood properly. However, it has widely been known for centuries that derivatives of plant origin possess a broad spectrum of biological activity. Current trends of research and development activities on flavonoids relate to isolation, identification, characterisation and functions of flavonoids and finally their applications on health benefits. Molecular docking and knowledge of bioinformatics are also being used to predict potential applications and manufacturing by industry. In the present review, attempts have been made to discuss the current trends of research and development on flavonoids, working mechanisms of flavonoids, flavonoid functions and applications, prediction of flavonoids as potential drugs in preventing chronic diseases and future research directions.

Since discovery of the first antibiotic drug, penicillin, in 1928, a variety of antibiotic and antimicrobial agents have been developed and used for both human therapy and industrial applications. However, excess and uncontrolled use of antibiotic agents has caused a significant growth in the number of drug resistant pathogens. Novel therapeutic approaches replacing the inefficient antibiotics are in high demand to overcome increasing microbial multidrug resistance. In the recent years, ongoing research has focused on development of nano-scale objects as efficient antimicrobial therapies. Among the various nanoparticles, silver nanoparticles have gained much attention due to their unique antimicrobial properties. However, concerns about the synthesis of these materials such as use of precursor chemicals and toxic solvents, and generation of toxic byproducts have led to a new alternative approach, green synthesis. This eco-friendly technique incorporates use of biological agents, plants or microbial agents as reducing and capping agents. Silver nanoparticles synthesized by green chemistry offer a novel and potential alternative to chemically synthesized nanoparticles. In this review, we discuss the recent advances in green synthesis of silver nanoparticles, their application as antimicrobial agents and mechanism of antimicrobial mode of action.

High-energy consumption in our day-to-day life can be balanced not only by harvesting pollution-free renewable energy sources, but also requires proper storage and distribution of energy. In this regard, lithium ion batteries are currently considered as effective energy storage devices and are involved in the most active research.

In the past few decades, polymeric nanocarriers have been recognized as promising tools and have gained attention from researchers for their potential to efficiently deliver bioactive compounds, including drugs, proteins, genes, nucleic acids, etc., in pharmaceutical and biomedical applications. Remarkably, these polymeric nanocarriers could be further modified as stimuli-responsive systems based on the mechanism of triggered release, i.e., response to a specific stimulus, either endogenous (pH, enzymes, temperature, redox values, hypoxia, glucose levels) or exogenous (light, magnetism, ultrasound, electrical pulses) for the effective biodistribution and controlled release of drugs or genes at specific sites. Various nanoparticles (NPs) have been functionalized and used as templates for imaging systems in the form of metallic NPs, dendrimers, polymeric NPs, quantum dots, and liposomes. The use of polymeric nanocarriers for imaging and to deliver active compounds has attracted considerable interest in various cancer therapy fields. So-called smart nanopolymer systems are built to respond to certain stimuli such as temperature, pH, light intensity and wavelength, and electrical, magnetic and ultrasonic fields. Many imaging techniques have been explored including optical imaging, magnetic resonance imaging (MRI), nuclear imaging, ultrasound, photoacoustic imaging (PAI), single photon emission computed tomography (SPECT), and positron emission tomography (PET). This review reports on the most recent developments in imaging methods by analyzing examples of smart nanopolymers that can be imaged using one or more imaging techniques. Unique features, including nontoxicity, water solubility, biocompatibility, and the presence of multiple functional groups, designate polymeric nanocues as attractive nanomedicine candidates. In this context, we summarize various classes of multifunctional, polymeric, nano-sized formulations such as liposomes, micelles, nanogels, and dendrimers.

Metallic nanoparticles such as silver nanoparticles (AgNPs) have gained lots of attention due to the continuous upsurge in microbial infections and diseases, and also inefficient treatment. Also, due to rapid intensification in the antibiotic resistance in this period has revived the consideration of the researchers and scientists to explore the therapeutic abilities of silver and its nanoparticulate systems as potential antimicrobial agents. Indeed, numerous studies suggested that AgNPs have exhibited significant antimicrobial actions, specifically against the bacterial infections. Ample of studies have been performed to evaluate and estimate the antibacterial potentials of silver and its associated products, and it was noticed that the they these Ag-particles triggers the oxidative stress, protein dysfunction, membrane and DNA damage, leading to microbial cell damage. Although it has exhibited antimicrobial activities, but its adverse effects over human health has been a major concern. Further, in this review we have summarized the significance of silver and AgNPs, various approaches for the preparation of AgNPs, antibacterial mechanism and probable toxicity in the cell environment. Furthermore, this review has been focused to consider the major mechanisms behind the bactericidal actions of the silver and silver nanoparticles-based systems, followed by comprehensive ideas related to their toxic potentials. This review would open new robust possibilities to develop silver nanoparticle-based antimicrobial systems with desired properties for effective treatment of bacterial infections in humans.

Lean and Six Sigma are two widely acknowledged business process improvement strategies available to organisations today for achieving dramatic results in cost, quality and time by focusing on process performance. Lately, Lean and Six Sigma practitioners are integrating the two strategies into a more powerful and effective hybrid, addressing many of the weaknesses and retaining most of the strengths of each strategy. Lean Sigma combines the variability reduction tools and techniques from Six Sigma with the waste and non-value added elimination tools and techniques from Lean Manufacturing, to generate savings to the bottom-line of an organisation. This paper proposes a Lean Sigma framework to reduce the defect occurring in the final product (automobile accessories) manufactured by a die-casting process. The proposed framework integrates Lean tools (current state map, 5S System, and Total Productive Maintenance (TPM)) within Six Sigma DMAIC methodology to enhance the bottom-line results and win customer loyalty. Implementation of the proposed framework shows dramatic improvement in the key metrics (defect per unit (DPU), process capability index, mean and standard deviation of casting density, yield, and overall equipment effectiveness (OEE)) and a substantial financial savings is generated by the organisation.

In the fast-paced modern world, psychological health issues like anxiety, depression and stress have become very common among the masses. In this paper, predictions of anxiety, depression and stress were made using machine learning algorithms. In order to apply these algorithms, data were collected from employed and unemployed individuals across different cultures and communities through the Depression, Anxiety and Stress Scale questionnaire (DASS 21). Anxiety, depression and stress were predicted as occurring on five levels of severity by five different machine learning algorithms – because these are highly accurate, they are particularly suited to predicting psychological problems. After applying the different methods, it was found that classes were imbalanced in the confusion matrix. Thus, the f1 score measure was added, which helped identify the best accuracy model among the five applied algorithms as the Random Forest classifier. Furthermore, the specificity parameter revealed that the algorithms were also especially sensitive to negative results.

Stress is an escalated psycho-physiological state of the human body emerging in response to a challenging event or a demanding condition. Environmental factors that trigger stress are called stressors. In case of prolonged exposure to multiple stressors impacting simultaneously, a person's mental and physical health can be adversely affected which can further lead to chronic health issues. To prevent stress-related issues, it is necessary to detect them in the nascent stages which are possible only by continuous monitoring of stress. Wearable devices promise real-time and continuous data collection, which helps in personal stress monitoring. In this paper, a comprehensive review has been presented, which focuses on stress detection using wearable sensors and applied machine learning techniques. This paper investigates the stress detection approaches adopted in accordance with the sensory devices such as wearable sensors, Electrocardiogram (ECG), Electroencephalography (EEG), and Photoplethysmography (PPG), and also depending on various environments like during driving, studying, and working. The stressors, techniques, results, advantages, limitations, and issues for each study are highlighted and expected to provide a path for future research studies. Also, a multimodal stress detection system using a wearable sensor-based deep learning technique has been proposed at the end.

Surfactants are a group of amphiphilic molecules (i.e., having both hydrophobic and hydrophilic domains) that are a vital part of nearly every contemporary industrial process such as in agriculture, medicine, personal care, food, and petroleum. In general surfactants can be derived from (i) petroleum-based sources or (ii) microbial/plant origins. Petroleum-based surfactants are obvious results from petroleum products, which lead to petroleum pollution and thus pose severe problems to the environment leading to various ecological damages. Thus, newer techniques have been suggested for deriving surfactant molecules and maintaining environmental sustainability. Biosurfactants are surfactants of microbial or plant origins and offer much added advantages such as high biodegradability, lesser toxicity, ease of raw material availability, and easy applicability. Thus, they are also termed "green surfactants". In this regard, this review focused on the advantages of biosurfactants over the synthetic surfactants produced from petroleum-based products along with their potential applications in different industries. We also provided their market aspects and future directions that can be considered with selections of biosurfactants. This would open up new avenues for surfactant research by overcoming the existing bottlenecks in this field.

Over 30 million people in India are suffering from diabetes and many others are under the risk. Thus, early diagnosis and treatment is required to prevent diabetes and its associated health problems. This study aims to assess the risk of diabetes among individuals based on their lifestyle and family background. The risk of Type 2 diabetes was predicted using different machine learning algorithms as these algorithms are highly accurate which is very much required in the health profession. Once the model will be trained with good accuracy, then individuals can self-assess the risk of diabetes. In order to conduct the experiment, 952 instances have been collected through an online and offline questionnaire including 18 questions related to health, lifestyle and family background. The same algorithms were also applied to the Pima Indian Diabetes database. The performance of Random Forest Classifier is found to be most accurate for both datasets.

The biodiversity of wheat-associated bacteria from the northern hills zone of India was deciphered. A total of 247 bacteria was isolated from five different sites. Analysis of these bacteria by amplified ribosomal DNA restriction analysis (ARDRA) using three restriction enzymes, Alu I, Msp I and Hae III, led to the grouping of these isolates into 19–33 clusters for the different sites at 75 % similarity index. 16S rRNA gene based phylogenetic analysis revealed that 65 %, 26 %, 8 % and 1 % bacteria belonged to four phyla, namely Proteobacteria, Firmicutes, Actinobacteria and Bacteroidetes, respectively. Overall, 28 % of the total morphotypes belonged to Pseudomona s followed by Bacillus (20 %), Stenotrophomonas (9 %), Methylobacterium (8 %), Arthrobacter (7 %), Pantoea (4 %), Achromobacter , Acinetobacter , Exiguobacterium and Staphylococcus (3 %), Enterobacter , Providencia , Klebsiella and Leclercia (2 %), Brevundimonas , Flavobacterium , Kocuria , Kluyvera and Planococcus (1 %). Representative strains from each cluster were screened in vitro for plant growth promoting traits, which included solubilisation of phosphorus, potassium and zinc; production of ammonia, hydrogen cyanide, indole-3-acetic acid and siderophore; nitrogen fixation, 1-aminocyclopropane-1-carboxylate deaminase activity and biocontrol against Fusarium graminearum , Rhizoctonia solani and Macrophomina phaseolina . Cold-adapted isolates may have application as inoculants for plant growth promotion and biocontrol agents for crops growing under cold climatic conditions.

Steel is the material of choice for a large number and very diverse industrial applications. Surface qualities along with other properties are the most important quality parameters, particularly for flat-rolled steel products. Traditional manual surface inspection procedures are awfully inadequate to ensure guaranteed quality-free surface. To ensure stringent requirements of customers, automated vision-based steel surface inspection techniques have been found to be very effective and popular during the last two decades. Considering its importance, this paper attempts to make the first formal review of state-of-art of vision-based defect detection and classification of steel surfaces as they are produced from steel mills. It is observed that majority of research work has been undertaken for cold steel strip surfaces which is most sensitive to customers' requirements. Work on surface defect detection of hot strips and bars/rods has also shown signs of increase during the last 10 years. The review covers overall aspects of automatic steel surface defect detection and classification systems using vision-based techniques. Attentions have also been drawn to reported success rates along with issues related to real-time operational aspects.

The present study has been undertaken to delineate the groundwater potential zones in the hard rock terrain of Palamu district, Jharkhand using the advanced applications of remote sensing, geographical information systems and analytic hierarchy process techniques. The integration and analyses of various thematic databases viz., geomorphology, lithology, soil, slope, lineament density, weathered zone thickness, drainage density and rainfall proved useful in the delineation of GWP zones. The study indicates that only 136 km2 of the study area exhibit excellent groundwater potential, 248 km2 has very good groundwater potential, whereas 36.89 and 38.23% are under poor and very poor groundwater potential zones, respectively. Hence, only a total of 11.6% of the area (490 km2) is classified as high to excellent groundwater potential. The final groundwater prospect map obtained was classified as excellent potential, very good potential, good potential, moderate potential, poor potential and very poor potential zone.

Flavonoids comprise a large group of structurally diverse polyphenolic compounds of plant origin and are abundantly found in human diet such as fruits, vegetables, grains, tea, dairy products, red wine, etc. Major classes of flavonoids include flavonols, flavones, flavanones, flavanols, anthocyanidins, isoflavones, and chalcones. Owing to their potential health benefits and medicinal significance, flavonoids are now considered as an indispensable component in a variety of medicinal, pharmaceutical, nutraceutical, and cosmetic preparations. Moreover, flavonoids play a significant role in preventing cardiovascular diseases (CVDs), which could be mainly due to their antioxidant, antiatherogenic, and antithrombotic effects. Epidemiological and in vitro/in vivo evidence of antioxidant effects supports the cardioprotective function of dietary flavonoids. Further, the inhibition of LDL oxidation and platelet aggregation following regular consumption of food containing flavonoids and moderate consumption of red wine might protect against atherosclerosis and thrombosis. One study suggests that daily intake of 100 mg of flavonoids through the diet may reduce the risk of developing morbidity and mortality due to coronary heart disease (CHD) by approximately 10%. This review summarizes dietary flavonoids with their sources and potential health implications in CVDs including various redox-active cardioprotective (molecular) mechanisms with antioxidant effects. Pharmacokinetic (oral bioavailability, drug metabolism), toxicological, and therapeutic aspects of dietary flavonoids are also addressed herein with future directions for the discovery and development of useful drug candidates/therapeutic molecules.

Gesture recognition is essential for human - machine interaction. In this paper we propose a method to recognize human gestures using a Kinect <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">®</sup> depth camera. The camera views the subject in the front plane and generates a depth image of the subject in the plane towards the camera. This depth image is then used for background removal, followed by generation of the depth profile of the subject. In addition to this, the difference between subsequent frames gives the motion profile of the subject and is used for recognition of gestures. These allow the efficient use of depth camera to successfully recognize multiple human gestures. The result of a case study involving 8 gestures is shown. The system was trained using a multi class Support Vector Machine.

This paper proposes a novel cancer sensor based on dual core photonic crystal fiber for the detection of cancer cells in cervical, breast, and basal parts. The samples are taken in fluid form and infiltrated into the farmed cavity using selective infiltration method. Each fluid form has its own refractive index values which give the various responses in the transmission and loss spectrum. The spectral shift is obtained by inducing the coupling mechanism between silica core and cancer cell core for its launching input optical field which is investigated by finite element method. The proposed structure is also optimized with its structural dimensional property for enhancing the sensitivity. The sensing performances for the cervical cancer cell are obtained as high as 7916 nm/RIU for x-polarization and 10625 nm/RIU for y-polarization with the detection limit of 0.024. The sensitivity to breast cancer cells for xand y-polarization is 5714.28 and 7857.14 nm/RIU, respectively, with detection limit of 0.014. Similarly, the sensitivity to basal cells can also reach 4500 nm/RIU for x-polarization and 6000 nm/RIU for y-polarization. To the best of our knowledge, such sensitivities are the highest reported thus so far.

The usage of Information Technology has expanded dramatically in today’s homes, business organizations and Government departments Technology has become an inevitable part of human life. Researchers have come up with various models and theories to investigate factors that influence the extent to which humans use computers and its applications. Unified Theory of Adoption and Use of Technology (UTAUT) is the latest model which has been conceived to understand the nature of technology usage and has been applied in various domains like education, banking, health care etc. Gender has been attributed as a significant variable in explaining the technology acceptance behaviour of humans. The objective of this study is to review the existing literature on the technology usage and intention to use technology from the gender perspective. It has been observed from the review that in few contexts, gender plays a significant role in determining the intention of accepting new technology and there are cases where gender differences cannot be discerned.

Abstract. We examine the distribution of aerosols and associated optical/radiative properties in the Gangetic-Himalayan region from simultaneous radiometric measurements over the Indo-Gangetic Plains (IGP) and the foothill/southern slopes of the Himalayas during the 2009 pre-monsoon season. Enhanced dust transport extending from the Southwest Asian arid regions into the IGP, results in seasonal mean (April–June) aerosol optical depths of over 0.6 – highest over Southern Asia. The influence of dust loading is greater over the Western IGP as suggested by pronounced coarse mode peak in aerosol size distribution and spectral single scattering albedo (SSA). Transported dust in the IGP, driven by prevailing westerly airmass, is found to be more absorbing (SSA550 nm&lt;0.9) than the near-desert region in Northwestern (NW) India suggesting mixing with carbonaceous aerosols in the IGP. On the contrary, significantly reduced dust transport is observed over eastern IGP and foothill/elevated Himalayan slopes in Nepal where strongly absorbing haze is prevalent, as indicated by lower SSA (0.85–0.9 at 440–1020 nm), suggesting presence of more absorbing aerosols compared to IGP. Additionally, our observations show a distinct diurnal pattern of aerosols with characteristic large afternoon peak, from foothill to elevated mountain locations, associated with increased upslope transport of pollutants – that likely represent large-scale lifting of absorbing aerosols along the elevated slopes during pre-monsoon season. In terms of radiative impact of aerosols, over the source region of NW India, diurnal mean reduction in solar radiation fluxes was estimated to be 19–23 Wm−2 at surface (12–15% of the surface solar insolation). Furthermore, based on limited observations of aerosol optical properties during the pre-monsoon period and comparison of our radiative forcing estimates with published literature, there exists a general spatial heterogeneity in the regional aerosol forcing, associated with the absorbing aerosol distribution over northern India, with both diurnal mean surface forcing and forcing efficiency over the IGP exceeding that over Northwestern India. Finally, the role of the seasonal progressive buildup of aerosol loading and water vapor is investigated in the observed net aerosol radiative effect over Northwestern India. The radiative impact of water vapor is found to amplify the net regional aerosol radiative forcing suggesting that the two exert forcing in tandem leading to enhanced surface cooling. It is suggested that water vapor contribution should be taken into account while assessing aerosol forcing impact for this region and other seasonally similar environments.

is curcumin and has gained importance in various treatments of various disorders such as antibacterial, antiprotozoal, cancer, obesity, diabetics and wound healing applications. Several techniques had been exploited as reported by researchers for increasing the therapeutic potential and its pharmacological activity. Here, the dictum is the new room for the development of physicochemical, as well as biological, studies for the efficacy in target specificity. Here, we discussed nanoformulation techniques, which lend support to upgrade the characters to the curcumin such as enhancing bioavailability, increasing solubility, modifying metabolisms, and target specificity, prolonged circulation, enhanced permeation. Our manuscript tried to seek the attention of the researcher by framing some solutions of some existing troubleshoots of this bioactive component for enhanced applications and making the formulations feasible at an industrial production scale. This manuscript focuses on recent inventions as well, which can further be implemented at the community level.

OBJECTIVE: In this study, attempt has been focused to prepare a nanoemulsion (NE) gel for topical delivery of amphotericin B (AmB) for enhanced as well as sustained skin permeation, in vitro antifungal activity and in vivo toxicity assessment. MATERIALS AND METHODS: A series of NE were prepared using sefsol-218 oil, Tween 80 and Transcutol-P by slow spontaneous titration method. Carbopol gel (0.5% w/w) was prepared containing 0.1% w/w AmB. Furthermore, NE gel (AmB-NE gel) was characterized for size, charge, pH, rheological behavior, drug release profile, skin permeability, hemolytic studies and ex vivo rat skin interaction with rat skin using differential scanning calorimeter. The drug permeability and skin irritation ability were examined with confocal laser scanning microscopy and Draize test, respectively. The in vitro antifungal activity was investigated against three fungal strains using the well agar diffusion method. Histopathological assessment was performed in rats to investigate their toxicological potential. RESULTS AND DISCUSSION: The AmB-NE gel (18.09 ± 0.6 µg/cm(2)/h) and NE (15.74 ± 0.4 µg/cm(2)/h) demonstrated the highest skin percutaneous permeation flux rate as compared to drug solution (4.59 ± 0.01 µg/cm(2)/h) suggesting better alternative to painful and nephrotoxic intravenous administration. Hemolytic and histopathological results revealed safe delivery of the drug. Based on combined results, NE and AmB-NE gel could be considered as an efficient, stable and safe carrier for enhanced and sustained topical delivery for AmB in local skin fungal infection. CONCLUSION: Topical delivery of AmB is suitable delivery system in NE gel carrier for skin fungal infection.