This handbook covers basic concepts in mechanical engineering and mechatronics, including stress and strain, mechanics of solids, internal combustion engines, refrigeration, fluid mechanics, control ...systems, actuation, robotics, electro-mechanical systems, hydraulics, and more. --
Alzheimer's disease (AD) is the most devastating neurodegenerative disorder that affects the aging population worldwide. Endogenous and exogenous factors are involved in triggering this complex and ...multifactorial disease, whose hallmark is Amyloid-β (Aβ), formed by cleavage of amyloid precursor protein by β- and γ-secretase. While there is no definitive cure for AD to date, many neuroprotective natural products, such as polyphenol and carotenoid compounds, have shown promising preventive activity, as well as helping in slowing down disease progression. In this article, we focus on the chemistry as well as structure of carotenoid compounds and their neuroprotective activity against Aβ aggregation using molecular docking analysis. In addition to examining the most prevalent anti-amyloidogenic carotenoid lutein, we studied cryptocapsin, astaxanthin, fucoxanthin, and the apocarotenoid bixin. Our computational structure-based drug design analysis and molecular docking simulation revealed important interactions between carotenoids and Aβ via hydrogen bonding and van der Waals interactions, and shows that carotenoids are powerful anti-amyloidogenic molecules with a potential role in preventing AD, especially since most of them can cross the blood-brain barrier and are considered nutraceutical compounds. Our studies thus illuminate mechanistic insights on how carotenoids inhibit Aβ aggregation. The potential role of carotenoids as novel therapeutic molecules in treating AD and other neurodegenerative disorders are discussed.
Abstract
High quality silver (Ag) decorated CeO
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nanoparticles were prepared by a facile one-step chemical method. The samples were characterized by X-ray diffraction (XRD), scanning electron ...microscopy (SEM), High resolution transmission electron microscopy (HR-TEM), fourier transform infrared spectrometer (FT-IR), electron paramagnetic resonance (EPR), X-ray photoelectron spectroscopy (XPS), UV–Visible absorption (UV–Vis), photoluminescence (PL) and thermogravimetric analysis. The decoration of Ag on CeO
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surface was confirmed by XRD, EPR and HR-TEM analysis. Harmful textile pollutant Rose Bengal dye was degraded under sunlight using the novel Ag decorated CeO
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catalyst. It was found that great enhancement of the degradation efficiency for Ag/CeO
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compared to pure CeO
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, it can be ascribed mainly due to decrease in its band gap and charge carrier recombination rate. The Ag/CeO
2
sample exhibited an efficient photocatalytic characteristic for degrading RB under visible light irradiation with a high degradation rate of 96% after 3 h. With the help of various characterizations, a possible degradation mechanism has been proposed which shows the effect of generation of oxygen vacancies owing to the decoration of Ag on the CeO
2
surface.
► Review of methods for trend detection in the presence of serial correlation. ► Identification of temporal and spatial changes in maximum and minimum temperature over India. ► More than one method ...should be used to detect temporal changes satisfactorily. ► Substantial change in minimum temperature during 1970–2003 over India. ► Significant temporal changes in temperature are found over North Central region of India.
Present study performs the spatial and temporal trend analysis of annual, monthly and seasonal maximum and minimum temperatures (tmax, tmin) in India. Recent trends in annual, monthly, winter, pre-monsoon, monsoon and post-monsoon extreme temperatures (tmax, tmin) have been analyzed for three time slots viz. 1901–2003, 1948–2003 and 1970–2003. For this purpose, time series of extreme temperatures of India as a whole and seven homogeneous regions, viz. Western Himalaya (WH), Northwest (NW), Northeast (NE), North Central (NC), East coast (EC), West coast (WC) and Interior Peninsula (IP) are considered. Rigorous trend detection analysis has been exercised using variety of non-parametric methods which consider the effect of serial correlation during analysis. During the last three decades minimum temperature trend is present in All India as well as in all temperature homogeneous regions of India either at annual or at any seasonal level (winter, pre-monsoon, monsoon, post-monsoon). Results agree with the earlier observation that the trend in minimum temperature is significant in the last three decades over India (Kothawale et al., 2010). Sequential MK test reveals that most of the trend both in maximum and minimum temperature began after 1970 either in annual or seasonal levels.
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•A hybrid short-term wind speed prediction model for high accuracy is proposed.•The Ensemble Empirical Mode Decomposition algorithm is adopted to decompose the original wind speed ...data.•The Adaptive Wavelet Neural Network is developed to predict the wind time series data.•Results from a real-world case study in India are reported along with comprehensive comparison.•Attained high accuracy, less uncertainty and low computational burden in forecasts by the proposed method for the first time.
Wind energy is one of the emerging sustainable sources of electricity. Wind is intermittent in nature. The typical grid operation of wind energy is complex. The significance of wind energy generation and integration with the grid is increasing day by day. An accurate wind speed forecasting method will help the utility planners and operators to meet the balance of supply and demand by generating wind energy. In this paper, a statistical-based wind speed prediction is implemented without utilizing the numerical weather prediction inputs. This analytical study proposes a hybrid short-term prediction approach that can successfully preprocess the original wind speed data to enhance the forecasting accuracy. The most efficient signal decomposition algorithm, Ensemble Empirical Mode Decomposition is used for preprocessing. This ensemble empirical mode decomposition technique decomposes the original wind speed data. Each decomposed signal is regressed to forecast the future wind speed value by utilizing the Adaptive Wavelet Neural Network model. The proposed hybrid approach is subsequently investigated with respect to the wind farm of South India. The results from a real-world case study in India are reported along with comprehensive comparison. The prediction performance delivered high accuracy, less uncertainty and low computational burden in the forecasts attained. The developed hybrid model outperforms the six other benchmark models such as persistence method, back propagation neural network, radial basis function neural network, Elman neural network, Gaussian regression neural network, and wavelet neural network.
Magnetic chitosan composites (MCCs) are a novel material that exhibits good sorption behavior toward various toxic pollutants in aqueous solution. These magnetic composites have a fast adsorption ...rate and high adsorption efficiency, efficient to remove various pollutants and they are easy to recover and reuse. These features highlight the suitability of MCCs for the treatment of water polluted with metal and organic materials. This review outlines the preparation of MCCs as well as methods to characterize these materials using FTIR, XRD, TGA and other microscopy-based techniques. Additionally, an overview of recent developments and applications of MCCs for metal and organic pollutant removal is discussed in detail. Based on current research and existing materials, some new and futuristic approaches in this fascinating area are also discussed. The main objective of this review is to provide up-to-date information about the most important features of MCCs and to show their advantages as adsorbents in the treatment of polluted aqueous solutions.
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•Outline of preparation, characterization and properties of magnetic chitosan adsorbents•Inorganic and organic pollutant removal from water using MCCs has been reviewed.•Adsorption kinetics and equilibrium isotherm models were reviewed.•Magnetic separation and adsorption mechanism have been discussed.•The outlook for potential applications and limitations was also discussed.
Copper nanowires (Cu NWs) are of particular interest for application as transparent and flexible conducting electrodes in 'see-through' and/or 'deformable' future electronics due to their excellent ...electrical, optical, and mechanical properties. It is necessary to develop reliable and facile methods to produce well-defined Cu NWs prior to their full exploitation. Among the wide variety of methods available to generate Cu NWs, solution-based synthesis routes are considered to be a promising strategy because of several advantages including fewer constraints on the selection of precursors, the solvent and reaction conditions, and the feasibility of large-scale low-cost production. Here, we provide a thorough review of various recently developed synthetic methodologies to obtain Cu NWs, with particular emphasis on wet chemical synthesis approaches including a hydrothermal route, reduction of metal precursors, and catalytic synthesis. The emerging applications of Cu NWs including transparent electrodes and flexible/stretchable electronics are also discussed, followed by brief comments on the remaining challenges and future research perspectives.
This review summarizes the wet chemical synthesis strategies, properties, and applications of copper nanowires.
•The survey of machine learning algorithms for WSNs from the period 2014 to March 2018.•Machine learning (ML) for WSNs with their advantages, features and limitations.•A statistical survey of ...ML-based algorithms for WSNs.•Reasons to choose a ML techniques to solve issues in WSNs.•The survey proposes a discussion on open issues.
Wireless sensor network (WSN) is one of the most promising technologies for some real-time applications because of its size, cost-effective and easily deployable nature. Due to some external or internal factors, WSN may change dynamically and therefore it requires depreciating dispensable redesign of the network. The traditional WSN approaches have been explicitly programmed which make the networks hard to respond dynamically. To overcome such scenarios, machine learning (ML) techniques can be applied to react accordingly. ML is the process of self-learning from the experiences and acts without human intervention or re-program. The survey of the ML techniques for WSNs is presented in 1, covering period of 2002–2013. In this survey, we present various ML-based algorithms for WSNs with their advantages, drawbacks, and parameters effecting the network lifetime, covering the period from 2014–March 2018. In addition, we also discuss ML algorithms for synchronization, congestion control, mobile sink scheduling and energy harvesting. Finally, we present a statistical analysis of the survey, the reasons for selection of a particular ML techniques to address an issue in WSNs followed by some discussion on the open issues.
The contemporary environmental-stewardship programmes primarily aimed at curbing the global warming potential by adopting a multidisciplinary approach. Manipulating the feeding strategies has great ...potential in reducing the environmental footprints of livestock production. This study intends to assess the effect of soybean meal (SBM) replacement with varying levels of coated urea (SRU) on both zoo-technical (nutrient digestibility, heat increment, and physio-biochemical parameters) and environmental attributes. The coated urea was used to replace the SBM at 0, 25, 50, and 75 percent levels. Eight adult rams (43.02 ± 0.76) maintained in a conventional shed were used in a replicated 4 x 4 Latin square design. Not all the physiological parameters viz. rectal temperature, pulse rate, and respiratory rate were affected (P>0.05)f by varying levels of SRU incorporation. The SRU fed animals had higher (P<0.05) crude protein digestibility compared to SBM fed animals; however, the replacements did not affect the nutrient digestibility coefficients of DM, OM, NFC, NDFap, ADF, and hemicellulose components. The SRU did not affect various biochemical parameters such as serum glucose, total protein, albumin, globulin, urea, creatinine, ALT, AST, Ca, P and T3, and T4 levels; however, post-prandial serum urea N (SUN) values showed a diurnal quadratic pattern (P<0.05) with a dose-dependent relationship. Further, the SBM replacements had no effect on the calcium excretion, while the SRU incorporation decreased the faecal phosphorous content, thereby abating the eutrophication phenomenon. Although the SBM replacements did not affect in vivo water variables and faecal solid fractions, they managed to decrease the land and virtual water requirement along with global warming potential (GWP) of the entire trial. The GWP-perceptual map unveils the fact that replacement of conventional feed ingredients with NPN compounds aids in eco-friendly livestock production. Further, the conjectural analysis of the carbon footprint methodology revealed that agricultural by-products consideration could cause a huge increase in the GWP share of feed consumed, thus compelling the importance of research pertaining to feed production perspective as equal as ruminal methane amelioration.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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