34 research outputs found
Differential Effect of Cholesterol and Its Biosynthetic Precursors on Membrane Dipole Potential
AbstractDipole potential is the potential difference within the membrane bilayer, which originates due to the nonrandom arrangement of lipid dipoles and water molecules at the membrane interface. Cholesterol, a representative sterol in higher eukaryotic membranes, is known to increase membrane dipole potential. In this work, we explored the effects of immediate (7-DHC and desmosterol) and evolutionary (ergosterol) precursors of cholesterol on membrane dipole potential, monitored by the dual wavelength ratiometric approach utilizing the probe di-8-ANEPPS. Our results show that the effect of these precursors on membrane dipole potential is very different from that observed with cholesterol, although the structural differences among them are subtle. These results assume relevance, since accumulation of cholesterol precursors due to defective cholesterol biosynthesis has been reported to result in several inherited metabolic disorders such as the Smith-Lemli-Opitz syndrome. Interestingly, cholesterol (and its precursors) has a negligible effect on dipole potential in polyunsaturated membranes. We interpret these results in terms of noncanonical orientation of cholesterol in these membranes. Our results constitute the first report on the effect of biosynthetic and evolutionary precursors of cholesterol on dipole potential, and imply that a subtle change in sterol structure can significantly alter the dipolar field at the membrane interface
Earth observation and geospatial data can predict the relative distribution of village level poverty in the Sundarban Biosphere Reserve, India
There is increasing interest in leveraging Earth Observation (EO) and geospatial data to predict and map aspects of socioeconomic conditions to support survey and census activities. This is particularly relevant for the frequent monitoring required to assess progress towards the UNs' Sustainable Development Goals (SDGs). The Sundarban Biosphere Reserve (SBR) is a region of international ecological importance, containing the Indian portion of the world's largest mangrove forest. The region is densely populated and home to over 4.4 million people, many living in chronic poverty with a strong dependence on nature-based rural livelihoods. Such livelihoods are vulnerable to frequent natural hazards including cyclone landfall and storm surges. In this study we examine associations between environmental variables derived from EO and geospatial data with a village level multidimensional poverty metric using random forest machine learning, to provide evidence in support of policy formulation in the field of poverty reduction. We find that environmental variables can predict up to 78% of the relative distribution of the poorest villages within the SBR. Exposure to cyclone hazard was the most important variable for prediction of poverty. The poorest villages were associated with relatively small areas of rural settlement (<∼30%), large areas of agricultural land (>∼50%) and moderate to high cyclone hazard. The poorest villages were also associated with less productive agricultural land than the wealthiest. Analysis suggests villages with access to more diverse livelihood options, and a smaller dependence on agriculture may be more resilient to cyclone hazard. This study contributes to the understanding of poverty-environment dynamics within Low-and middle-income countries and the associations found can inform policy linked to socio-environmental scenarios within the SBR and potentially support monitoring of work towards SDG1 (No Poverty) across the region.</p
Linking IPCC AR4 & AR5 frameworks for assessing vulnerability and risk to climate change in the Indian Bengal Delta
The International Panel on Climate Change (IPCC) AR5 (Fifth Assessment Report, 2014) conceptual approach and terminology is aligned with a concept of risk which differs from the previous framework (AR4). This study draws links between the AR5 concept of risk with the previous concept of vulnerability (AR4). The most significant difference between the results of the AR4 and AR5 approaches is the change in sub-district level relative rankings. Findings show that Basanti, in the Bengal Delta, is the most vulnerable sub-district using the AR4 approach, whereas Gosaba is found to be highly exposed to risk using the AR5 approach.UK Government's Department for International Development (DFID
Assessment and attribution of mangrove forest changes in the Indian Sundarbans from 2000 to 2020
The Indian Sundarbans, together with Bangladesh, comprise the largest mangrove forest in the world. Reclamation of the mangroves in this region ceased in the 1930s. However, they are still subject to adverse environmental influences, such as sediment starvation due to migration of the main river channels in the Ganges–Brahmaputra delta over the last few centuries, cyclone landfall, wave action from the Bay of Bengal—changing hydrology due to upstream water diversion—and the pervasive effects of relative sea-level rise. This study builds on earlier work to assess changes from 2000 to 2020 in mangrove extent, genus composition, and mangrove ‘health’ indicators, using various vegetation indices derived from Landsat and MODIS satellite imagery by performing maximum likelihood supervised classification. We show that about 110 km 2 of mangroves disappeared within the reserve forest due to erosion, and 81 km 2 were gained within the inhabited part of Sundarbans Biosphere Reserve (SBR) through plantation and regeneration. The gains are all outside the contiguous mangroves. However, they partially compensate for the losses of the contiguous mangroves in terms of carbon. Genus composition, analyzed by amalgamating data from published literature and ground-truthing surveys, shows change towards more salt-tolerant genus accompanied by a reduction in the prevalence of freshwater-loving Heiritiera, Nypa, and Sonneratia assemblages. Health indicators, such as the enhanced vegetation index (EVI) and normalized differential vegetation index (NDVI), show a monotonic trend of deterioration over the last two decades, which is more pronounced in the sea-facing parts of the mangrove forests. An increase in salinity, a temperature rise, and rainfall reduction in the pre-monsoon and the post-monsoon periods appear to have led to such degradation. Collectively, these results show a decline in mangrove area and health, which poses an existential threat to the Indian Sundarbans in the long term, especially under scenarios of climate change and sea-level rise. Given its unique values, the policy process should acknowledge and address these threats
Assessment and Attribution of Mangrove Forest Changes in the Indian Sundarbans from 2000 to 2020
The Indian Sundarbans, together with Bangladesh, comprise the largest mangrove forest in the world. Reclamation of the mangroves in this region ceased in the 1930s. However, they are still subject to adverse environmental influences, such as sediment starvation due to migration of the main river channels in the Ganges–Brahmaputra delta over the last few centuries, cyclone landfall, wave action from the Bay of Bengal—changing hydrology due to upstream water diversion—and the pervasive effects of relative sea-level rise. This study builds on earlier work to assess changes from 2000 to 2020 in mangrove extent, genus composition, and mangrove ‘health’ indicators, using various vegetation indices derived from Landsat and MODIS satellite imagery by performing maximum likelihood supervised classification. We show that about 110 km2 of mangroves disappeared within the reserve forest due to erosion, and 81 km2 were gained within the inhabited part of Sundarbans Biosphere Reserve (SBR) through plantation and regeneration. The gains are all outside the contiguous mangroves. However, they partially compensate for the losses of the contiguous mangroves in terms of carbon. Genus composition, analyzed by amalgamating data from published literature and ground-truthing surveys, shows change towards more salt-tolerant genus accompanied by a reduction in the prevalence of freshwater-loving Heiritiera, Nypa, and Sonneratia assemblages. Health indicators, such as the enhanced vegetation index (EVI) and normalized differential vegetation index (NDVI), show a monotonic trend of deterioration over the last two decades, which is more pronounced in the sea-facing parts of the mangrove forests. An increase in salinity, a temperature rise, and rainfall reduction in the pre-monsoon and the post-monsoon periods appear to have led to such degradation. Collectively, these results show a decline in mangrove area and health, which poses an existential threat to the Indian Sundarbans in the long term, especially under scenarios of climate change and sea-level rise. Given its unique values, the policy process should acknowledge and address these threats
Awareness programs control infectious disease - multiple delay induced mathematical model
We propose and analyze a mathematical model to study the impact of awareness programs on an infectious disease outbreak. These programs induce behavioral changes in the population, which divide the susceptible class into two subclasses, aware susceptible and unaware susceptible. The system can have a disease-free equilibrium and an endemic equilibrium. The expression of the basic reproduction number and the conditions for the stability of the equilibria are derived. We further improve and study the model by introducing two time-delay factors, one for the time lag in memory fading of aware people and one for the delay between cases of disease occurring and mounting awareness programs. The delayed system has positive bounded solutions. We study various cases for the time delays and show that in general the system develops limit cycle oscillation through a Hopf bifurcation for increasing time delays. We show that under certain conditions on the parameters, the system is permanent. To verify our analytical findings, the numerical simulations on the model, using realistic parameters for Pneumococcus are performed
Effect of Ligand Attachment on the C–I Bond Dissociation Process on Aluminum Nanoclusters: A DFT Investigation
The
influence of the ligand attachment on the activation process
of carbon halogen bond on small sized aluminum nanoclusters are investigated
using density functional theory. Attaching suitable ligand to metal
clusters is among the widely popular techniques often used by experimentalists
in order to stabilize metastable clusters. In depth theoretical investigations
have shown that based on the jellium configuration of the cluster,
attaching an electron withdrawing ligand can either make a cluster
more reactive toward the C–I dissociation or may convert the
cluster relatively inert. The alteration of the activation barriers
and other associated parameters due to ligand attachment are included
in this paper along with additional calculations and explanations.
The study also shows that even the reaction parameters of specific
magic clusters can be significantly altered via ligand attachment.
The activation process of small molecules on metal clusters are of
crucial importance for the development of material science and cluster
chemistry. The present investigation will therefore be useful for
better understanding of the properties of the ligated clusters as
well as may also aid the experimentalists toward controlling the reactivity
of a specific cluster as required
Pump power induced instability and hysteresis in an all-normal dispersion linear mode-locked fiber laser
In this manuscript, experimental studies on the instability and hysteresis in an all-normal dispersion (ANDi) fiber laser have been presented. The laser was mode-locked by using a semiconductor saturable absorber mirror and a chirped fiber Bragg grating in linear cavity configuration and under the stable conditions it delivered stationary dissipative soliton pulses with characteristic rectangular-shaped steep-edged spectrum. With increasing the pump power, the laser transits to a non-stationary state with a near trapezoidal-shaped spectrum with significant temporal instabilities. The hysteresis associated with the state transition and variations in spectral characteristics has been studied including dispersive Fourier transform based analysis. Pump power induced state transition in an ANDi linear cavity with a physical saturable absorber without the influence of any physical polarization controller or apparent limitation due to spectral filtering is the key observation presented in this paper
Generation of stable Q-switched pulses at 1566 nm by using a segment of erbium-doped fiber as saturable absorber
In this manuscript, the performance of a passively Q-switched fiber laser has been presented, where a segment of un-pumped erbium-doped fiber (EDF) is used as the saturable absorber (SA). We have taken an erbium and ytterbium (Er/Yb) co-doped double cladding fiber as the gain media for efficient pump absorption and checked the potential of the laser by changing the length of the in-house fabricated erbium-doped fiber saturable absorber (EFSA). For a fixed length of EFSA, variation of important system parameters such as output power, repetition rate, pulse width, etc, with the change of the pump power has also been reported. The laser has delivered pulses of a minimum duration of 1.35 mu s with maximum energy of 2.8 mu J. The repetition rate varies in the range from 24.8 kHz to 47 kHz with alteration of the length of the SA. The central wavelength of the output spectra is 1566 nm