Biodiesel is an eco-friendly, renewable, and potential liquid biofuel mitigating greenhouse gas emissions. Biodiesel has been produced initially from vegetable oils, non-edible oils, and waste oils. ...However, these feedstocks have several disadvantages such as requirement of land and labor and remain expensive. Similarly, in reference to waste oils, the feedstock content is succinct in supply and unable to meet the demand. Recent studies demonstrated utilization of lignocellulosic substrates for biodiesel production using oleaginous microorganisms. These microbes accumulate higher lipid content under stress conditions, whose lipid composition is similar to vegetable oils. In this paper, feedstocks used for biodiesel production such as vegetable oils, non-edible oils, oleaginous microalgae, fungi, yeast, and bacteria have been illustrated. Thereafter, steps enumerated in biodiesel production from lignocellulosic substrates through pretreatment, saccharification and oleaginous microbe-mediated fermentation, lipid extraction, transesterification, and purification of biodiesel are discussed. Besides, the importance of metabolic engineering in ensuring biofuels and biorefinery and a brief note on integration of liquid biofuels have been included that have significant importance in terms of circular economy aspects.
The first proapoptotic caspase, CED-3, was cloned from Caenorhabditis elegans in 1993 and shown to be essential for the developmental death of all somatic cells. Following the discovery of CED-3, ...caspases have been cloned from several vertebrate and invertebrate species. As reviewed in other articles in this issue of Cell Death and Differentiation, many caspases function in nonapoptotic pathways. However, as is clear from the worm studies, the evolutionarily conserved role of caspases is to execute programmed cell death. In this article, I will specifically focus on caspases that function primarily in cell death execution. In particular, the physiological function of caspases in apoptosis is discussed using examples from the worm, fly and mammals.
The widespread existence of different organic contaminants mostly phenolic compounds, organic dyes and antibiotics in water bodies initiated by the various industrial wastes that raised great ...scientific concern and public awareness as well recently owing to their prospective capability to spread these contaminants resistant gene and pose hazard to human. In the present study, a series of nanostructured ZnO-CdO incorporated with reduced graphene oxide (ZCG nanocomposites) were successfully synthesized by a simple refluxing method and characterized by using the X-ray diffraction (XRD), Raman spectroscopy, FT-IR spectroscopy, photoluminescence spectroscopy, field emission-scanning microscope (FE-SEM) and UV–visible diffused reflectance spectroscopy (DRS) for the photocatalytic degradation of bisphenol A (BPA), thymol blue (ThB) and ciprofloxacin (CFn) with illumination of UV light. The maximum degradation and mineralization of BPA, ThB and CFn was achieved around 98.5%, 98.38% and 99.28% over the ZCG-5 nanocomposite photocatalyst after UV light irradiation for 180 min, 120 min and 75 min, respectively. The superior photocatalytic activity of ZCG-5 ascribed to enhance adsorption capacity, effective separation of charge carriers consequential for the production of more ROS after incorporation of RGO nanosheets with ZnO-CdO in photocatalyst. The conceivable photocatalytic degradation mechanism of BPA, ThB and CFn was elucidated through ROS identification and the assessment of photocatalyst stability by reusability, EEO (kwh/m3order) and UV light dose (mJ/cm2) were evaluated. The plausible photocatalytic degradation pathways were proposed for the degradation of BPA, ThB and CFn via GC-MS analysis. The present work investigates the efficient removal of BPA, ThB and CFn using ZCG nanocomposites as photocatalyst.
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•Synthesis of ZnO-CdO-RGO nanocomposites by refluxing method.•Reusability and sustainability of ZCG-5 nanocomposite as photocatalyst.•Photodegradation kinetics of Bisphenol A, Thymol blue and ciprofloxacin using ZCG nanocomposites.•Significance of ZnO-CdO and RGO nanosheets in ZCG nanocomposites and Plausible photocatalytic degradation mechanism.•Plausible photocatalytic degradation pathway of bisphenol A, thymol blue and ciprofloxacin.
Psidium guajava
L. (guava) is predominantly grown throughout the world and known for its medicinal properties in treating various diseases and disorders. The present work focuses on aqueous ...extraction of bioactive compounds from the guava leaf and its utilization in the formulation of jelly to improve the public health. The guava leaf extract has been used in the preparation of jelly with pectin (1.5 g), sugar (28 g) and lemon juice (2 mL). The prepared guava leaf extract jelly (GJ) and the control jelly (CJ, without extract) were subjected to proximate, nutritional and textural analyses besides determination of antioxidant and antimicrobial activities. GJ was found to contain carbohydrate (45.78 g/100 g), protein (3.0 g/100 g), vitamin C (6.15 mg/100 g), vitamin B3 (2.90 mg/100 g) and energy (120.6 kcal). Further, the texture analysis of CJ and GJ indicated that both the jellies showed similar properties emphasizing that the addition of guava leaf extract does not bring any change in the texture properties of jelly. GJ exhibited antimicrobial activity against various bacteria ranging from 11.4 to 13.6 mm. Similarly, GJ showed antioxidant activity of 42.38% against DPPH radical and 33.45% against hydroxyl radical. Mass spectroscopic analysis of aqueous extract confirmed the presence of esculin, quercetin, gallocatechin, 3-sinapoylquinic acid, gallic acid, citric acid and ellagic acid which are responsible for antioxidant and antimicrobial properties.
Environment friendly methods for the synthesis of copper nanoparticles have become a valuable trend in the current scenario. The utilization of phytochemicals from plant extracts has become a unique ...technology for the synthesis of nanoparticles, as they possess dual nature of reducing and capping agents to the nanoparticles. In the present investigation we have synthesized copper nanoparticles (CuNPs) using a rare medicinal plant Cissus arnotiana and evaluated their antibacterial activity against gram negative and gram positive bacteria. The morphology and characterization of the synthesized CuNPs were studied and done using UV-Visible spectroscopy at a wavelength range of 350–380 nm. XRD studies were performed for analyzing the crystalline nature; SEM and TEM for evaluating the spherical shape within the size range of 60–90 nm and AFM was performed to check the surface roughness. The biosynthesized CuNPs showed better antibacterial activity against the gram-negative bacteria, E. coli with an inhibition zone of 22.20 ± 0.16 mm at 75 μg/ml. The antioxidant property observed was comparatively equal with the standard antioxidant agent ascorbic acid at a maximum concentration of 40 μg/ ml. This is the first study reported on C. arnotiana mediated biosynthesis of copper nanoparticles, where we believe that the findings can pave way for a new direction in the field of nanotechnology and nanomedicine where there is a significant potential for antibacterial and antioxidant activities. We predict that, these could lead to an exponential increase in the field of biomedical applications, with the utilization of green synthesized CuNPs, due to its remarkable properties. The highest antibacterial property was observed with gram-negative strains mainly, E. coli, due to its thin peptidoglycan layer and electrostatic interactions between the bacterial cell wall and CuNPs surfaces. Hence, CuNPs can be potent therapeutic agents in several biomedical applications, which are yet to be explored in the near future.
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•To prepare the copper nanoparticles using novel medicinal plant Cissus arnotiana•Characterization of CuNPs by different microscopic techniques•To evaluate the antioxidant and antibacterial activity
The oral microbiome is established within a few minutes after birth and consists of stable multi‐species communities that engage in a dynamic equilibrium with the host immune system. Dental caries, ...endodontic infections and periodontal diseases are bacterially driven diseases that are caused by dysbiotic microbiomes. Over a century ago, the focal infection theory implicated these infections in the aetiology of several systemic diseases, ranging from arthritis to neurodegenerative diseases. However, a lack of concrete evidence, combined with the urgency with which clinicians embraced this approach without regard for appropriate case selection, led to its demise within 30 years. In the last decade of the 20th century, the concept of periodontal medicine was introduced to explain the correlations that were being observed between periodontitis and cardiovascular disease, rheumatoid arthritis, Alzheimer's disease, pulmonary disease, pre‐term delivery of low birth weight infants and metabolic disease. It was proposed that periodontal pathobionts played a causal role in the initiating or exacerbating certain diseases either by direct invasion or by stimulating a florid immune‐inflammatory response that extended into the systemic circulation. This review will examine the strength of current evidence in establishing a causal link between oral pathobionts and systemic disease.
The effects of bacteria associated with dental caries and periodontitis on various systemic diseases: a review of the currently available evidence.
Decarbonizing the planet is one of the major goals that countries around the world have set for 2050 to mitigate the effects of climate change. To achieve these goals, green hydrogen that can be ...produced from the electrolysis of water is an important key solution to tackle global decarbonization. Consequently, in recent years there is an increase in interest towards green hydrogen production through the electrolysis process for large-scale implementation of renewable energy-based power plants and other industrial, and transportation applications. The main objective of this study was to provide a comprehensive review of various green hydrogen production technologies especially on water electrolysis. In this review, various water electrolysis technologies and their techno-commercial prospects including hydrogen production cost, along with recent developments in electrode materials, and their challenges were summarized. Further some of the most successful results also were described. Moreover this review aims to identify the gaps in water electrolysis research and development towards the techno-commercial perspective. In addition, some of the commercial electrolyzer performances and their limitations also were described along with possible solutions for cost-effective hydrogen production Finally, we outlined our ideas, and possible solutions for driving cost-effective green hydrogen production for commercial applications. This information will provide future research directions and a road map for the development/implementation of commercially viable green hydrogen projects.
•Water electrolysis is one of the most promising methods for green hydrogen generation.•Green hydrogen provides a sustainable solution for future energy demands and decarburization.•This review summarizes various water electrolysis technologies for techno-commercial perspective and their challenges.•Finally, we outlined our ideas/recommendations for future research and developments.
•Artificial Neural Networks (ANNs) live a vital role in many areas including medical, security systems and stock market.•This paper proposed nine new integrated models for forecasting intraday stock ...price based on the potential of three ANNs.•Results proved that the PSO-BPNN model yielded the highest prediction accuracy in estimating intraday stock price.•Other models produced low performances in prediction accuracy are 97.2, 98.4, 84.0, 85.2, 84.0, 83.9, 89.9 and 78.6%.
Stock market prediction is one of the critical issues in fiscal market. It is important issue for the traders and investors. Artificial Neural Networks (ANNs) associated with nature inspired algorithms are playing an increasingly vital role in many areas including medical field, security systems and stock market. Several prediction models have been developed by researchers to forecast stock market trend. However, few studies have focused on improving stock market prediction accuracy especially when utilizing artificial neural networks to perform the analysis. This paper proposed nine new integrated models for forecasting intraday stock price based on the potential of three ANNs, Back Propagation Neural Network (BPNN), Radial Basis Function Neural Network (RBFNN), Time Delay Neural Network (TDNN) and nature inspired algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC).The developed models were named as GA-BPNN, PSO-BPNN, ABC-BPNN, GA-RBFNN, PSO-RBFNN, ABC-RBFNN, GA-TDNN, PSO-TDNN and ABC-TDNN. Nature inspired algorithms are employed for optimizing the parameters of ANNs. Technical indicators calculated from historical data are fed as input to developed models. Proposed hybrid models validated on four datasets representing different sectors in NSE. Four statistical metrics, Root Mean Square Error (RMSE), Hit Rate (HR), Error Rate (ER) and prediction accuracy were utilized to gauge the performance of the developed models. Results proved that the PSO-BPNN model yielded the highest prediction accuracy in estimating intraday stock price. The other models, GA-BPNN, ABC-BPNN, GA-RBFNN, PSO-RBFNN, ABC-RBFNN, GA-TDNN, PSO-TDNN and ABC-TDNN produced lower performance with mean prediction accuracy of 97.24%, 98.37%, 84.01%, 85.15%, 84.01%, 83.87%, 89.95% and 78.61% respectively.
The wind turbine power curve shows the relationship between the wind turbine power and hub height wind speed. It essentially captures the wind turbine performance. Hence it plays an important role in ...condition monitoring and control of wind turbines. Power curves made available by the manufacturers help in estimating the wind energy potential in a candidate site. Accurate models of power curve serve as an important tool in wind power forecasting and aid in wind farm expansion. This paper presents an exhaustive overview on the need for modeling of wind turbine power curves and the different methodologies employed for the same. It also reviews in detail the parametric and non-parametric modeling techniques and critically evaluates them. The areas of further research have also been presented.
We study the thermoelectric properties of bulk and monolayer MoSe2 and WSe2 by first-principles calculations and semiclassical Boltzmann transport theory. The lattice thermal conductivity is ...calculated using the self-consistent iterative approach as well as the single-mode relaxation time approximation. The acoustical and optical contributions to the lattice thermal conductivity are evaluated along with the influence of the phonon mean free path. The employed methodology enables a quantitative comparison of the thermoelectric properties of transition-metal dichalcogenides. In particular, WSe2 is found to be superior to MoSe2 for thermoelectric applications.
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