Nitric oxide (NO) is just one member of a new class of gaseous signalling molecules with fundamental actions in biology. In higher vertebrates it has key roles in maintaining haemostasis and in smooth muscle (especially vascular smooth muscle), neurons and the gastrointestinal tract. It is intimately involved in regulating all aspects of our lives from waking, digestion, sexual function, perception of pain and pleasure, memory recall and sleeping. Finally, the way it continues to function in our bodies will influence how we degenerate with age. It will likely play a role in our deaths through cardiovascular disease, stroke, diabetes and cancer. Our ability to control NO signalling and to use NO effectively in therapy must therefore have a major bearing on the future quality and duration of human life.

Nitric oxide physiology and pathology.

Anthropogenic sources of VOC in a football stadium: Assessing human emissions in the atmosphere

Quantifying volatile organic compounds (VOCs) in cigarette smoke is necessary to establish smoke-related exposure estimates and evaluate emerging products and potential reduced-exposure products In response to this need, we developed an automated, multi-VOC quantification method for machine-generated, mainstream cigarette smoke using solid-phase microextraction gas chromatography–mass spectrometry (SPME-GC–MS) This method was developed to simultaneously quantify a broad range of smoke VOCs (ie, carbonyls and volatiles, which historically have been measured by separate assays) for large exposure assessment studies Our approach collects and maintains vapor-phase smoke in a gas sampling bag, where it is homogenized with isotopically labeled analogue internal standards and sampled using gas-phase SPME High throughput is achieved by SPME automation using a CTC Analytics platform and custom bag tray This method has successfully quantified 22 structurally diverse VOCs (eg, benzene and associated monoaro

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Simultaneous analysis of 22 volatile organic compounds in cigarette smoke using gas sampling bags for high-throughput solid-phase microextraction.

This paper reviews the NTIRE 2022 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The task of the challenge was to super-resolve an input image with a magnification factor of ×4 based on pairs of low and corresponding high resolution images. The aim was to design a network for single image super-resolution that achieved improvement of efficiency measured according to several metrics including runtime, parameters, FLOPs, activations, and memory consumption while at least maintaining the PSNR of 29.00dB on DIV2K validation set. IMDN is set as the baseline for efficiency measurement. The challenge had 3 tracks including the main track (runtime), sub-track one (model complexity), and sub-track two (overall performance). In the main track, the practical runtime performance of the submissions was evaluated. The rank of the teams were determined directly by the absolute value of the average runtime on the validation set and test set. In sub-track one, the number of parameters and FLOPs were considered. And the individual rankings of the two metrics were summed up to determine a final ranking in this track. In sub-track two, all of the five metrics mentioned in the description of the challenge including runtime, parameter count, FLOPs, activations, and memory consumption were considered. Similar to sub-track one, the rankings of five metrics were summed up to determine a final ranking. The challenge had 303 registered participants, and 43 teams made valid submissions. They gauge the state-of-the-art in efficient single image super-resolution.

NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results

A coupling between a cigarette smoking simulator and a time-of-flight mass spectrometer was constructed to allow investigation of tobacco smoke formation under simulated burning conditions. The cigarette smoking simulator is designed to burn a sample in close approximation to the conditions experienced by a lit cigarette. The apparatus also permits conditions outside those of normal cigarette burning to be investigated for mechanistic understanding purposes. It allows control of parameters such as smouldering and puff temperatures, as well as combustion rate and puffing volume. In this study, the system enabled examination of the effects of “smoking” a cigarette under a nitrogen atmosphere. Time-of-flight mass spectrometry combined with a soft ionisation technique is expedient to analyse complex mixtures such as tobacco smoke with a high time resolution. The objective of the study was to separate pyrolysis from combustion processes to reveal the formation mechanism of several selected toxicants. A purposely designed adapter, with no measurable dead volume or memory effects, enables the analysis of pyrolysis and combustion gases from tobacco and tobacco products (e.g. 3R4F reference cigarette) with minimum aging. The combined system demonstrates clear distinctions between smoke composition found under air and nitrogen smoking atmospheres based on the corresponding mass spectra and visualisations using principal component analysis.

Pyrolysis and combustion of tobacco in a cigarette smoking simulator under air and nitrogen atmosphere.

A sampling system has been set up to monitor a group of volatile smoke analytes (nitric oxide, acetaldehyde, acetone, benzene, toluene, 1,3 butadiene, isoprene and carbon dioxide) from mainstream cigarette smoke on a puff-resolved basis. The system was able to record gas evolution profiles during puffing and interpuff periods without interruption (e.g. taking clearing puffs). Gas phase smoke analytes were sampled as close to the mouth end of the cigarette filter as possible in order to minimise any dead volume effect. The results revealed that, for some volatile species, a significant fraction (e.g. up to 30% for benzene) in the cigarette mainstream smoke had been generated during the preceding smoulder period. These species were trapped or absorbed within the cigarette rod and then subsequently eluted during the puff. The identification of the two sources of the mainstream smoke, a smouldering source and a puffing source, has not been reported before. The observation contributes to the fundamental knowledge of the cigarette smoke formation and may have implications on wider smoke chemistry and associated effects.

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New insights into the formation of volatile compounds in mainstream cigarette smoke

This paper reviews the challenge on constrained high dynamic range (HDR) imaging that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conjunction with CVPR 2022. This manuscript focuses on the competition set-up, datasets, the proposed methods and their results. The challenge aims at estimating an HDR image from multiple respective low dynamic range (LDR) observations, which might suffer from under-or over-exposed regions and different sources of noise. The challenge is composed of two tracks with an emphasis on fidelity and complexity constraints: In Track 1, participants are asked to optimize objective fidelity scores while imposing a low-complexity constraint (i.e. solutions can not exceed a given number of operations). In Track 2, participants are asked to minimize the complexity of their solutions while imposing a constraint on fidelity scores (i.e. solutions are required to obtain a higher fidelity score than the prescribed baseline). Both tracks use the same data and metrics: Fidelity is measured by means of PSNR with respect to a ground-truth HDR image (computed both directly and with a canonical tonemapping operation), while complexity metrics include the number of Multiply-Accumulate (MAC) operations and runtime (in seconds).

S. Feng

Papers

New insights into the formation of volatile compounds in mainstream cigarette smoke

NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results