Plant cells orchestrate an array of molecular mechanisms for maintaining plasmatic concentrations of essential heavy metal (HM) ions, for example, iron, zinc and copper, within the optimal functional ...range. In parallel, concentrations of non‐essential HMs and metalloids, for example, cadmium, mercury and arsenic, should be kept below their toxicity threshold levels. Vacuolar compartmentalization is central to HM homeostasis. It depends on two vacuolar pumps (V‐ATPase and V‐PPase) and a set of tonoplast transporters, which are directly driven by proton motive force, and primary ATP‐dependent pumps. While HM non‐hyperaccumulator plants largely sequester toxic HMs in root vacuoles, HM hyperaccumulators usually sequester them in leaf cell vacuoles following efficient long‐distance translocation. The distinct strategies evolved as a consequence of organ‐specific differences particularly in vacuolar transporters and in addition to distinct features in long‐distance transport. Recent molecular and functional characterization of tonoplast HM transporters has advanced our understanding of their contribution to HM homeostasis, tolerance and hyperaccumulation. Another important part of the dynamic vacuolar sequestration syndrome involves enhanced vacuolation. It involves vesicular trafficking in HM detoxification. The present review provides an updated account of molecular aspects that contribute to the vacuolar compartmentalization of HMs.
Spatial and temporal metal homeostasis is of fundamental importance for plant life and fitness. A set of heavy metal and metalloid ion transporters of high complexity resides at the tonoplast and orchestrates the dynamic deposition and mobilization of essential metal nutrients and detoxification of non‐essential metal ions in plant organs such as root and leaves. This becomes particularly obvious in metal hyperaccumulators, but is a principle in all.
•We present a multi-objective reliability optimization problem using intuitionistic fuzzy optimization.•Reliability is considered as a triangular fuzzy number during formulation.•Exponential ...membership and quadratic nonmembership functions are used for defining their fuzzy goals.•We utilize the PSO algorithm to the solve the optimization problem.•Examples are shown to illustrate the method.
In designing phase of systems, design parameters such as component reliabilities and cost are normally under uncertainties. This paper presents a methodology for solving the multi-objective reliability optimization model in which parameters are considered as imprecise in terms of triangular interval data. The uncertain multi-objective optimization model is converted into deterministic multi-objective model including left, center and right interval functions. A conflicting nature between the objectives is resolved with the help of intuitionistic fuzzy programming technique by considering linear as well as the nonlinear degree of membership and non-membership functions. The resultants max–min problem has been solved with particle swarm optimization (PSO) and compared their results with genetic algorithm (GA). Finally, a numerical instance is presented to show the performance of the proposed approach.
A thin endometrium is encountered infrequently (2.4%) in assisted reproductive technology cycles. When it does occur it is a cause of concern as it is associated with lower implantation rate and ...pregnancy rate. Though pregnancies have been reported at 4 and 5 mm it is apparent that an endometrial thickness <6 mm is associated with a trend toward lower probability of pregnancy. Hormone replacement therapy - frozen embryo transfer (FET) cycles appear to give better results due to an improvement in endometrial receptivity (ER). The etiology of thin endometrium plays a significant part in its receptivity. A number of treatments have been tried to improve endometrial growth, but none has been validated so far. Confirming ER of a thin endometrium by an ER array test before FET offers reassurance.
Cloud computing provides infinite resources and various services for the execution of variety of applications to end users, but still it has various challenges that need to be addressed. Objective of ...cloud users is to select the optimal resource that meets the demand of end users in reasonable cost and time, but sometimes users pay more for short time. Most of the proposed state-of-the-art algorithms try to optimize only one parameter at a time. Therefore, a novel compromise solution is needed to make the balance between conflicting objectives. The main goal of this research paper is to design and develop a task processing framework that has the decision-making capability to select the optimal resource at runtime to process the applications (diverse and complex nature) at virtual machines using modified particle swarm optimization (PSO) algorithm within a user-defined deadline. Proposed algorithm gives non-dominance set of optimal solutions and improves various influential parameters (time, cost, throughput, task acceptance ratio) by series of experiments over various synthetic datasets using Cloudsim tool. Computational results show that proposed algorithm well and substantially outperforms the baseline heuristic and meta-heuristic such as PSO, adaptive PSO, artificial bee colony, BAT algorithm, and improved min–min load-balancing algorithm.
The present study attempts to explore and compare the seasonal variability in chemical composition and contributions of different sources of fine and coarse fractions of aerosols (PM2.5 and PM10) in ...Delhi, India from January 2013 to December 2016. The annual average concentrations of PM2.5 and PM10 were 131 ± 79 μg m−3 (range: 17–417 μg m−3) and 238 ± 106 μg m−3 (range: 34–537 μg m−3), respectively. PM2.5 and PM10 samples were chemically characterized to assess their chemical components i.e. organic carbon (OC), elemental carbon (EC), water soluble inorganic ionic components (WSICs) and heavy and trace elements and then used for estimation of enrichment factors (EFs) and applied positive matrix factorization (PMF5) model to evaluate their prominent sources on seasonal basis in Delhi. PMF identified eight major sources i.e. Secondary nitrate (SN), secondary sulphate (SS), vehicular emissions (VE), biomass burning (BB), soil dust (SD), fossil fuel combustion (FFC), sodium and magnesium salts (SMS) and industrial emissions (IE). Total carbon contributes ∼28% to the total PM2.5 concentration and 24% to the total PM10 concentration and followed the similar seasonality pattern. SN and SS followed opposite seasonal pattern, where SN was higher during colder seasons while SS was greater during warm seasons. The seasonal differences in VE contributions were not very striking as it prevails evidently most of year. Emissions from BB is one of the major sources in Delhi with larger contribution during winter and post monsoon seasons due to stable meteorological conditions and aggrandized biomass burning (agriculture residue burning in and around the regions; mainly Punjab and Haryana) and domestic heating during the season. Conditional Bivariate Probability Function (CBPF) plots revealed that the maximum concentrations of PM2.5 and PM10 were carried by north westerly winds (north-western Indo Gangetic Plains of India).
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•Simultaneous sampling of PM2.5 and PM10 was carried out for 4 years (2013–2016).•Seasonal variations in composition and sources of PM2.5 and PM10 are studied in Delhi.•Secondary inorganic aerosol accounts for 21% of PM10 and 27% of PM2.5 mass with contrasting seasonal variations.•Traffic emission contributes greatly to PM10 while biomass burning to PM2.5, both being maximum in winters.•Maximum concentrations of PM2.5 and PM10 were coming from North West direction of Delhi (CBPF plots).
The present work explores the temporal and seasonal variabilities in composition and contributions of different sources to fine and coarse fractions of particulate matter over Delhi.
Inuit in Nunavut (NU) and Inuvialuit in the Northwest Territories (NWT), Canada, were traditionally nomadic peoples whose culture and lifestyle were founded on hunting and gathering foods from the ...local environment, primarily land and marine mammals. Lifestyle changes within the last century have brought about a rapid nutrition transition, characterised by decreasing consumption of traditional foods and an associated increase in the consumption of processed, shop-bought foods. This transition may be attributed to a multitude of factors, such as acculturation, overall food access and availability, food insecurity and climate change. Obesity and risk for chronic disease are higher in the Canadian Arctic population compared with the Canadian national average. This present review describes the study population and methodologies used to collect data in order to study the nutrition transition amongst Aboriginal Arctic populations and develop Healthy Foods North (HFN), a novel, multi-institutional and culturally appropriate programme that aims to improve dietary adequacy and reduce risk of chronic disease. Included in this special issue of the Journal of Human Nutrition and Dietetics are papers describing dietary intake patterns, physical activity levels, dietary behaviours, chronic disease prevalence and psychosocial factors that potentially mediate behaviour. A further paper describes how these data were utilised to inform and develop Healthy Foods North.
A new theory of coherent structure in wall turbulence is presented. The theory is the first to predict packets of hairpin vortices and other structure in turbulence, and their dynamics, based on an ...analysis of the Navier–Stokes equations, under an assumption of a turbulent mean profile. The assumption of the turbulent mean acts as a restriction on the class of possible structures. It is shown that the coherent structure is a manifestation of essentially low-dimensional flow dynamics, arising from a critical-layer mechanism. Using the decomposition presented in McKeon & Sharma (J. Fluid Mech., vol. 658, 2010, pp. 336–382), complex coherent structure is recreated from minimal superpositions of response modes predicted by the analysis, which take the form of radially varying travelling waves. The leading modes effectively constitute a low-dimensional description of the turbulent flow, which is optimal in the sense of describing the resonant effects around the critical layer and which minimally predicts all types of structure. The approach is general for the full range of scales. By way of example, simple combinations of these modes are offered that predict hairpins and modulated hairpin packets. The example combinations are chosen to represent observed structure, consistent with the nonlinear triadic interaction for wavenumbers that is required for self-interaction of structures. The combination of the three leading response modes at streamwise wavenumbers
$6, ~1, ~7$
and spanwise wavenumbers
$\pm 6, ~\pm 6, ~\pm 12$
, respectively, with phase velocity
$2/ 3$
, is understood to represent a turbulence ‘kernel’, which, it is proposed, constitutes a self-exciting process analogous to the near-wall cycle. Together, these interactions explain how the mode combinations may self-organize and self-sustain to produce experimentally observed structure. The phase interaction also leads to insight into skewness and correlation results known in the literature. It is also shown that the very large-scale motions act to organize hairpin-like structures such that they co-locate with areas of low streamwise momentum, by a mechanism of locally altering the shear profile. These energetic streamwise structures arise naturally from the resolvent analysis, rather than by a summation of hairpin packets. In addition, these packets are modulated through a ‘beat’ effect. The relationship between Taylor’s hypothesis and coherence is discussed, and both are shown to be the consequence of the localization of the response modes around the critical layer. A pleasing link is made to the classical laminar inviscid theory, whereby the essential mechanism underlying the hairpin vortex is captured by two obliquely interacting Kelvin–Stuart (cat’s eye) vortices. Evidence for the theory is presented based on comparison with observations of structure in turbulent flow reported in the experimental and numerical simulation literature and with exact solutions reported in the transitional literature.
The experimental observation of Peregrine solitons in a multicomponent plasma with the critical concentration of negative ions is reported. A slowly amplitude modulated perturbation undergoes ...self-modulation and gives rise to a high amplitude localized pulse. The measured amplitude of the Peregrine soliton is 3 times the nearby carrier wave amplitude, which agrees with the theory. The numerical solution of the nonlinear Schrödinger equation is compared with the experimental results.
CNT nanoparticles have high tensile strength, excellent thermal transfer properties, and optimal chemical and physical stability. The lack of CNT stable dispersion in most of the fluids limits its ...industrial exploitation in heat transfer applications. Researchers are constantly making efforts for preparing stable dispersions of CNT. Luckily, the unique
π
-electron-rich structures of CNT open a variety of possibilities for modifications in their structure leading to alterations in their chemical and electronic properties. Normally, chemical and physical methods are used for CNT surface properties alterations to make it dispersible in various base fluids. This review provides a comprehensive survey of chemical and physical methods used to prepare stable CNT nanofluid as well as methods used to analyse CNT nanofluid stability. Chemical modifications are either done by covalent or non
-
covalent methods. Covalent methods utilized by researchers include reaction with acids, bases, organic and inorganic molecules, metals, metal complexes, polymers, etc. In non-covalent method, surfactants, biomolecules and natural products, polymers, IL and DES, polymers, etc. are used. Physical methods discussed herein include techniques like homogenization, crushing, etc. that deagglomerate CNT bundles. The application of extreme forces on CNT leads to distortion in electronic framework of CNT. Therefore, to avoid excess of physical and chemical treatments
,
a blend of techniques in appropriate ratio is proposed for CNT dispersion. The techniques that are used to analyse the stability of nanofluid such as UV–vis, TEM, SEM, turbiscan, zeta, and DLS are also reviewed. It could be concluded that there is need for development of low-cost and fast method for prediction of the stability of CNT nanofluid.
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