Global warming and recurrent mass bleaching of corals

During 2015–2016, record temperatures triggered a pan-tropical episode of coral bleaching, the third global-scale event since mass bleaching was first documented in the 1980s. Here we examine how and why the severity of recurrent major bleaching events has varied at multiple scales, using aerial and underwater surveys of Australian reefs combined with satellite-derived sea surface temperatures. The distinctive geographic footprints of recurrent bleaching on the Great Barrier Reef in 1998, 2002 and 2016 were determined by the spatial pattern of sea temperatures in each year. Water quality and fishing pressure had minimal effect on the unprecedented bleaching in 2016, suggesting that local protection of reefs affords little or no resistance to extreme heat. Similarly, past exposure to bleaching in 1998 and 2002 did not lessen the severity of bleaching in 2016. Consequently, immediate global action to curb future warming is essential to secure a future for coral reefs

A review of a strategic roadmapping exercise to advance clinical translation of photoacoustic imaging: From current barriers to future adoption

Photoacoustic imaging (PAI), also referred to as optoacoustic imaging, has shown promise in early-stage clinical trials in a range of applications from inflammatory diseases to cancer. While the first PAI systems have recently received regulatory approvals, successful adoption of PAI technology into healthcare systems for clinical decision making must still overcome a range of barriers, from education and training to data acquisition and interpretation. The International Photoacoustic Standardisation Consortium (IPASC) undertook an community exercise in 2022 to identify and understand these barriers, then develop a roadmap of strategic plans to address them. Here, we outline the nature and scope of the barriers that were identified, along with short-, medium- and longterm community efforts required to overcome them, both within and beyond the IPASC group

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

Synthesis of cannabinoids

Provided are synthesis processes and intermediates for preparing cannabinoids and analogs

Synthesis of cannabinoids

Provided are synthesis processes and intermediates for preparing cannabinoids and analogs

Synthesis of cannabinoids

Provided are synthesis processes and intermediates for preparing cannabinoids and analogs

A study of emissions from domestic solid-fuel stove combustion in Ireland

Solid-fuel stoves are at the heart of many homes not only in developing nations, but also in developed regions where there is significant deployment of such heating appliances. They are often operated inefficiently and in association with high emission fuels like wood. This leads to disproportionate air pollution contributions. Despite the proliferation of these appliances, an understanding of particulate matter (PM) emissions from these sources remains relatively low. Emissions from five solid fuels are quantified using a “conventional” and an Eco design stove. PM measurements are obtained using both “hot filter” sampling of the raw flue gas, and sampling of cooled, diluted flue gas using an Aerosol Chemical Speciation Monitor and AE33 aethalometer. PM emissions factors (EF) derived from diluted flue gas incorporate light condensable organic compounds; hence they are generally higher than those obtained with “hot filter” sampling, which do not. Overall, the PM EFs ranged from 0.2 to 108.2 g GJ−1 for solid fuels. The PM EF determined for a solid fuel depends strongly on the measurement method employed and on user behavior, and less strongly on secondary air supply and stove type. Kerosene-based firelighters were found to make a disproportionately high contribution to PM emissions. Organic aerosol dominated PM composition for all fuels, constituting 50−65% of PM from bituminous and low-smoke ovoids, and 85−95% from torrefied olive stone (TOS) briquettes, sod peat, and wood logs. Torrefied biomass and low-smoke ovoids were found to yield the lowest PM emissions. Substituting these fuels for smoky coal, peat, and wood could reduce PM2.5 emissions by approximately 63%