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The development of a cost structure for energy storage systems (ESS) has received limited attention. In this study, we developed data-intensive techno-economic models to assess the economic feasibility of ESS. The ESS here includes pump hydro storage (PHS) and compressed air energy storage (CAES). The costs were developed using data-intensive bottom-up models. Scale factors were developed for each component of the storage systems. The life cycle costs of energy storage were estimated for capacity ranges of 98-491 MW, 81-404 MW, and 60-298 MW for PHS, conventional CAES (C-CAES), and adiabatic CAES (A-CAES), respectively, to ensure a market-driven price can be achieved. For CAES systems, costs were developed for storage in salt caverns hard rock caverns, and porous formations. The results show that the annual life cycle storage cost is $220-400 for PHS, $215-265 for C-CAES, and $375-480 per kW-year for A-CAES. The levelised cost of electricity is $69-121 for PHS, $58-70 for C-CAES, and $96-121 per MWh for A-CAES. C-CAES is economically attractive at all capacities, PHS is economically attractive at higher capacities, and A-CAES is not attractive at all. The developed information is helpful in making investment decision related to large energy storage systems.

Almost all research output includes tables, diagrams, photographs and even sketches, and papers within HCI typically take advantage of including these figures in their files. However the space given to non-diagrammatical or tabular figures is often small, even in papers that primarily concern themselves with visual output. The reason for this might be the publishing models employed in most proceedings and journals: Despite moving to a digital format which is unhindered by page count or physical cost, there remains a somewhat arbitrary limitation on page count. Recent moves by ACM SIGCHI and others to remove references from the maximum page count suggest that there is movement on this, however images remain firmly within the limits of the text. We propose that images should be celebrated – not penalised – and call for not only the adoption of the Pictorials format in CHI, but for images to be removed from page counts in order to encourage greater transparency of process in HCI research.

Improving measurements of water vapour in the upper troposphere and lower stratosphere (UTLS) is a priority for the atmospheric science community. In this work, UTLS water vapour profiles derived from Atmospheric Chemistry Experiment (ACE) satellite measurements are assessed with coincident ground-based measurements taken at a high Arctic observatory at Eureka, Nunavut, Canada. Additional comparisons to satellite measurements taken by the Atmospheric Infrared Sounder (AIRS), Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), Microwave Limb Sounder (MLS), Scanning Imaging Absorption Spectrometer for Atmospheric CHartography (SCIAMACHY), and Tropospheric Emission Spectrometer (TES) are included to put the ACE Fourier transform spectrometer (ACE-FTS) and ACE Measurement of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation (ACE-MAESTRO) results in context. Measurements of water vapour profiles at Eureka are made using a Bruker 125HR solar absorption Fourier transform infrared spectrometer at the Polar Environment Atmospheric Research Laboratory (PEARL) and radiosondes launched from the Eureka Weather Station. Radiosonde measurements used in this study were processed with software developed by the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) to account for known biases and calculate uncertainties in a well-documented and consistent manner. ACE-FTS measurements were within 11 ppmv (parts per million by volume; 13 %) of 125HR measurements between 6 and 14 km. Between 8 and 14 km ACE-FTS profiles showed a small wet bias of approximately 8 % relative to the 125HR. ACE-FTS water vapour profiles had mean differences of 13 ppmv (32 %) or better when compared to coincident radiosonde profiles at altitudes between 6 and 14 km; mean differences were within 6 ppmv (12 %) between 7 and 11 km. ACE-MAESTRO profiles showed a small dry bias relative to the 125HR of approximately 7 % between 6 and 9 km and 10 % between 10 and 14 km. ACE-MAESTRO profiles agreed within 30 ppmv (36 %) of the radiosondes between 7 and 14 km. ACE-FTS and ACE-MAESTRO comparison results show closer agreement with the radiosondes and PEARL 125HR overall than other satellite datasets – except for AIRS. Close agreement was observed between AIRS and the 125HR and radiosonde measurements, with mean differences within 5 % and correlation coefficients above 0.83 in the troposphere between 1 and 7 km. Comparisons to MLS at altitudes around 10 km showed a dry bias, e.g. mean differences between MLS and radiosondes were −25.6 %. SCIAMACHY comparisons were very limited due to minimal overlap between the vertical extent of the measurements. TES had no temporal overlap with the radiosonde dataset used in this study. Comparisons between TES and the 125HR showed a wet bias of approximately 25 % in the UTLS and mean differences within 14 % below 5 km.

The sweet-basil (Ocimum basilicum L.) fruit/pericarp produces mucilage that engulfs the fruit and seed within minutes of hydration. Seed mucilage is produced by plant species that have adapted to arid, sandy soils. This study was conducted to determine how basil-seed mucilage improves ecological fitness. A second objective was to find ways to remove mucilage, which may interfere with commercial planting. Basil fruit/seeds were examined using light and environmental scanning electron microscopy. Columnar structures of basil mucilage rapidly unfolded from the pericarp upon initial hydration. Dilute hydrochloric acid removed the mucilage, which decreased the water content four-fold but did not inhibit seed germination in a laboratory test. Nondestructive Fourier-transform mid-infrared (FTIR) spectroscopy confirmed that the mucilage was primarily composed of hemicellulose that anchored the basil seed to resist movement. The fully hydrated seeds approached zero water potential, so the mucilage did not interfere with hydration. The seeds that were planted in growing media with mucilage had from 12 to 28% higher seedling emergence and survival percentages after 10 days than seeds without mucilage. Basil-fruit/seed mucilage provides a reservoir of loosely bound water at high water potential for seed germination and early seedling development, thus improving survivability under low moisture. Published version

Introduction Multimodality monitoring of patients with severe traumatic brain injury (TBI) is primarily performed in neurocritical care units to prevent secondary harmful brain insults and facilitate patient recovery. Several metrics are commonly monitored using both invasive and non-invasive techniques. The latest Brain Trauma Foundation guidelines from 2016 provide recommendations and thresholds for some of these. Still, high-level evidence for several metrics and thresholds is lacking. Methods Regarding invasive brain monitoring, intracranial pressure (ICP) forms the cornerstone, and pressures above 22 mmHg should be avoided. From ICP, cerebral perfusion pressure (CPP) (mean arterial pressure (MAP)-ICP) and pressure reactivity index (PRx) (a correlation between slow waves MAP and ICP as a surrogate for cerebrovascular reactivity) may be derived. In terms of regional monitoring, partial brain tissue oxygen pressure (PbtO(2)) is commonly used, and phase 3 studies are currently ongoing to determine its added effect to outcome together with ICP monitoring. Cerebral microdialysis (CMD) is another regional invasive modality to measure substances in the brain extracellular fluid. International consortiums have suggested thresholds and management strategies, in spite of lacking high-level evidence. Although invasive monitoring is generally safe, iatrogenic hemorrhages are reported in about 10% of cases, but these probably do not significantly affect long-term outcome. Non-invasive monitoring is relatively recent in the field of TBI care, and research is usually from single-center retrospective experiences. Near-infrared spectrometry (NIRS) measuring regional tissue saturation has been shown to be associated with outcome. Transcranial doppler (TCD) has several tentative utilities in TBI like measuring ICP and detecting vasospasm. Furthermore, serial sampling of biomarkers of brain injury in the blood can be used to detect secondary brain injury development. Conclusions In multimodal monitoring, the most important aspect is data interpretation, which requires knowledge of each metric's strengths and limitations. Combinations of several modalities might make it possible to discern specific pathologic states suitable for treatment. However, the cost-benefit should be considered as the incremental benefit of adding several metrics has a low level of evidence, thus warranting additional research.

The Optical Spectrograph and Infra-Red Imager System (OSIRIS) and the Atmospheric Chemistry Experiment (ACE) have been taking measurements from space since 2001 and 2003, respectively. This paper presents intercomparisons between ozone and NO2 measured by the ACE and OSIRIS satellite instruments and by ground-based instruments at the Polar Environment Atmospheric Research Laboratory (PEARL), which is located at Eureka, Canada (80° N, 86° W) and is operated by the Canadian Network for the Detection of Atmospheric Change (CANDAC). The ground-based instruments included in this study are four zenith-sky differential optical absorption spectroscopy (DOAS) instruments, one Bruker Fourier transform infrared spectrometer (FTIR) and four Brewer spectrophotometers. Ozone total columns measured by the DOAS instruments were retrieved using new Network for the Detection of Atmospheric Composition Change (NDACC) guidelines and agree to within 3.2%. The DOAS ozone columns agree with the Brewer spectrophotometers with mean relative differences that are smaller than 1.5%. This suggests that for these instruments the new NDACC data guidelines were successful in producing a homogenous and accurate ozone dataset at 80° N. Satellite 14–52 km ozone and 17–40 km NO2 partial columns within 500 km of PEARL were calculated for ACE-FTS Version 2.2 (v2.2) plus updates, ACE-FTS v3.0, ACE-MAESTRO (Measurements of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation) v1.2 and OSIRIS SaskMART v5.0x ozone and Optimal Estimation v3.0 NO2 data products. The new ACE-FTS v3.0 and the validated ACE-FTS v2.2 partial columns are nearly identical, with mean relative differences of 0.0 ± 0.2% and −0.2 ± 0.1% for v2.2 minus v3.0 ozone and NO2, respectively. Ozone columns were constructed from 14–52 km satellite and 0–14 km ozonesonde partial columns and compared with the ground-based total column measurements. The satellite-plus-sonde measurements agree with the ground-based ozone total columns with mean relative differences of 0.1–7.3%. For NO2, partial columns from 17 km upward were scaled to noon using a photochemical model. Mean relative differences between OSIRIS, ACE-FTS and ground-based NO2 measurements do not exceed 20%. ACE-MAESTRO measures more NO2 than the other instruments, with mean relative differences of 25–52%. Seasonal variation in the differences between NO2 partial columns is observed, suggesting that there are systematic errors in the measurements and/or the photochemical model corrections. For ozone spring-time measurements, additional coincidence criteria based on stratospheric temperature and the location of the polar vortex were found to improve agreement between some of the instruments. For ACE-FTS v2.2 minus Bruker FTIR, the 2007–2009 spring-time mean relative difference improved from −5.0 ± 0.4% to −3.1 ± 0.8% with the dynamical selection criteria. This was the largest improvement, likely because both instruments measure direct sunlight and therefore have well-characterized lines-of-sight compared with scattered sunlight measurements. For NO2, the addition of a ±1° latitude coincidence criterion improved spring-time intercomparison results, likely due to the sharp latitudinal gradient of NO2 during polar sunrise. The differences between satellite and ground-based measurements do not show any obvious trends over the missions, indicating that both the ACE and OSIRIS instruments continue to perform well.

Within the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water), long-term tropospheric water vapour isotopologue data records are provided for ten globally distributed ground-based mid-infrared remote sensing stations of the NDACC (Network for the Detection of Atmospheric Composition Change). We present a new method allowing for an extensive and straightforward characterisation of the complex nature of such isotopologue remote sensing datasets. We demonstrate that the MUSICA humidity profiles are representative for most of the troposphere with a vertical resolution ranging from about 2 km (in the lower troposphere) to 8 km (in the upper troposphere) and with an estimated precision of better than 10%. We find that the sensitivity with respect to the isotopologue composition is limited to the lower and middle troposphere, whereby we estimate a precision of about 30‰ for the ratio between the two isotopologues HD16O and H216O. The measurement noise, the applied atmospheric temperature profiles, the uncertainty in the spectral baseline, and the cross-dependence on humidity are the leading error sources. We introduce an a posteriori correction method of the cross-dependence on humidity, and we recommend applying it to isotopologue ratio remote sensing datasets in general. In addition, we present mid-infrared CO2 retrievals and use them for demonstrating the MUSICA network-wide data consistency. In order to indicate the potential of long-term isotopologue remote sensing data if provided with a well-documented quality, we present a climatology and compare it to simulations of an isotope incorporated AGCM (Atmospheric General Circulation Model). We identify differences in the multi-year mean and seasonal cycles that significantly exceed the estimated errors, thereby indicating deficits in the modeled atmospheric water cycle.

Natural selection on floral scent composition is a key element of the hypothesis that pollinators and other floral visitors drive scent evolution. The measure of such selection is complicated by the high-dimensional nature of floral scent data and uncertainty about the cognitive processes involved in scent-mediated communication. We use dimension reduction through reduced-rank regression to jointly estimate a scent composite trait under selection and the strength of selection acting on this trait. To assess and compare variation in selection on scent across species, time and space, we reanalyse 22 datasets on six species from four previous studies. The results agreed qualitatively with previous analyses in terms of identifying populations and scent compounds subject to stronger selection but also allowed us to evaluate and compare the strength of selection on scent across studies. Doing so revealed that selection on floral scent was highly variable, and overall about as common and as strong as selection on other phenotypic traits involved in pollinator attraction or pollen transfer. These results are consistent with an important role of floral scent in pollinator attraction. Our approach should be useful for further studies of plant–animal communication and for studies of selection on other high-dimensional phenotypes. In particular, our approach will be useful for studies of pollinator-mediated selection on complex scent blends comprising many volatiles, and when no prior information on the physiological responses of pollinators to scent compounds is available. peerReviewed

In immediate serial recall, a canonical short-term memory task, it is well established that performance is affected by several sublexical, lexical, and semantic factors. One factor that receives a growing interest is valence, whether a word is categorised as positive (e.g., happy) or as negative (e.g., pain). However, contradictory findings have recently emerged. Tse and Altarriba in two experiments with one set of stimuli and fixed lists concluded that valence affects serial recall performance, while Bireta et al. in three experiments with three sets of stimuli and randomised lists concluded that valence does not affect serial recall performance. Two experiments assessed the experimental discrepancy between Tse and Altarriba and Bireta et al. For both experiments, in one block, every participant saw the exact same lists as those used in Tse and Altarriba, and in the other block, each list was randomly constructed for each participant, as was done in Bireta et al. In Experiment 1, with concrete words varying in valence, we replicated the results of Tse and Altarriba with fixed lists and the results of Bireta et al. with randomised lists. In Experiment 2, with abstract words with both fixed and randomised lists, we replicate the absence of effect valence like Tse and Altarriba and Bireta et al. Overall, we conclude that valence does not affect serial recall and the discrepancy was attributed to the peculiarity of the fixed lists used by Tse and Altarriba. The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by a discovery grant from the Natural Sciences and Engineering Research Council of Canada (NSERC) to Jean Saint-Aubin. While working on this article, Dominic Guitard was supported by a postdoctoral fellowship from NSERC. Natural Sciences and Engineering Research Council of Canada (NSERC); NSERC Published version