Experimental evolution for generalists and specialists reveals multivariate genetic constraints on thermal reaction norms

Theory predicts the emergence of generalists in variable environments and antagonistic pleiotropy to favour specialists in constant environments, but empirical data seldom support such generalist–specialist trade-offs. We selected for generalists and specialists in the dung fly Sepsis punctum (Diptera: Sepsidae) under conditions that we predicted would reveal antagonistic pleiotropy and multivariate trade-offs underlying thermal reaction norms for juvenile development. We performed replicated laboratory evolution using four treatments: adaptation at a hot (31 °C) or a cold (15 °C) temperature, or under regimes fluctuating between these temperatures, either within or between generations. After 20 generations, we assessed parental effects and genetic responses of thermal reaction norms for three correlated life-history traits: size at maturity, juvenile growth rate and juvenile survival. We find evidence for antagonistic pleiotropy for performance at hot and cold temperatures, and a temperature-mediated trade-off between juvenile survival and size at maturity, suggesting that trade-offs associated with environmental tolerance can arise via intensified evolutionary compromises between genetically correlated traits. However, despite this antagonistic pleiotropy, we found no support for the evolution of increased thermal tolerance breadth at the expense of reduced maximal performance, suggesting low genetic variance in the generalist–specialist dimension.

A critical evaluation of the ability of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) thermal infrared red-green-blue rendering to identify dust events: theoretical analysis

Using a combination of idealized radiative transfer simulations and a case study from the first field campaign of the Saharan Mineral Dust Experiment (SAMUM) in southern Morocco, this paper provides a systematic assessment of the limitations of the widely used Spinning Enhanced Visible and Infrared Imager (SEVIRI) red-green-blue (RGB) thermal infrared dust product. Both analyses indicate that the ability of the product to identify dust, via its characteristic pink coloring, is strongly dependent on the column water vapor, the lower tropospheric lapse rate, and dust altitude. In particular, when column water vapor exceeds ∼20–25 mm, dust presence, even for visible optical depths of the order 0.8, is effectively masked. Variability in dust optical properties also has a marked impact on the imagery, primarily as a result of variability in dust composition. There is a moderate sensitivity to the satellite viewing geometry, particularly in moist conditions. The underlying surface can act to confound the signal seen through variations in spectral emissivity, which are predominantly manifested in the 8.7μm SEVIRI channel. In addition, if a temperature inversion is present, typical of early morning conditions over the Sahara and Sahel, an increased dust loading can actually reduce the pink coloring of the RGB image compared to pristine conditions. Attempts to match specific SEVIRI observations to simulations using SAMUM measurements are challenging because of high uncertainties in surface skin temperature and emissivity. Recommendations concerning the use and interpretation of the SEVIRI RGB imagery are provided on the basis of these findings.

Thermal and pressure stability of myrosinase enzymes from black mustard (Brassica nigra L. W.D.J Koch. var. nigra), brown mustard (Brassica juncea L. Czern. var. juncea) and yellow mustard (Sinapsis alba L. Subsp Maire) seeds

This study investigates the effects of temperature and pressure on inactivation of myrosinase extracted from black, brown and yellow mustard seeds. Brown mustard had higher myrosinase activity (2.75 un/mL) than black (1.50 un/mL) and yellow mustard (0.63 un/mL). The extent of enzyme inactivation increased with pressure (600-800 MPa) and temperature (30-70 °C) for all the mustard seeds. However, at combinations of lower pressures (200-400 MPa) and high temperatures (60-80 °C), there was less inactivation. For example, application of 300 MPa and 70 °C for 10 minutes retained 20%, 80% and 65% activity in yellow, black and brown mustard, respectively, whereas the corresponding activity retentions when applying only heat (70 °C, 10min) were 0%, 59% and 35%. Thus, application of moderate pressures (200-400 MPa) can potentially be used to retain myrosinase activity needed for subsequent glucosinolate hydrolysis.

The role of copper in the thermal conductivity of thermoelectric oxychalcogenides: do lone pairs matter?

Understanding the underlying mechanisms that suppress thermal conduction in solids is of paramount importance for the targeted design of materials for thermal management and thermoelectric energy conversion applications. Bismuth copper oxychalcogenides, BiOCuQ (Q = Se, Te), are highly crystalline thermoelectric materials with an unusually low lattice thermal conductivity of approx. 0.5 Wm-1K-1, a value normally found in amorphous materials. Here we unveil the origin of the unusual thermal transport properties of these phases. First principles calculations of the vibrational properties combined with analysis of in-situ neutron diffraction data, demonstrate that weak bonding of copper atoms within the structure leads to an unexpected vibrational mode at low frequencies, which is likely to be a major contributor to the low thermal conductivity of these materials. In addition, we show that anharmonicity and the large Grüneisen parameter in these oxychalcogenides are mainly related to the low frequency copper vibrations, rather than to the Bi3+ lone pairs.

Temporally stable feature clusters for maritime object tracking in visible and thermal imagery

This paper describes a new approach to detect and track maritime objects in real time. The approach particularly addresses the highly dynamic maritime environment, panning cameras, target scale changes, and operates on both visible and thermal imagery. Object detection is based on agglomerative clustering of temporally stable features. Object extents are first determined based on persistence of detected features and their relative separation and motion attributes. An explicit cluster merging and splitting process handles object creation and separation. Stable object clus- ters are tracked frame-to-frame. The effectiveness of the approach is demonstrated on four challenging real-world public datasets.

Stereochemistry and thermal stability of tartaric acid on the intrinsically chiral Cu{531} surface

Intrinsically chiral metal surfaces provide enantiospecific reaction environments without the need of coadsorbed modifiers. Amongst the intrinsically chiral copper surfaces, Cu{531} has the smallest unit cell and the highest density of chiral sites. XPS, NEXAFS and TPD were employed to investigate the adsorption and decomposition behaviour of the two chiral enantiomers of tartaric acid on this surface. The results obtained from XPS and NEXAFS show that at saturation coverage both enantiomers of tartaric acid adsorb in a μ4 configuration through the two carboxylic groups,which are rotatedwith respect to each other by 90°±≈15°within the surface plane. At intermediate coverage the R,R enantiomer adopts a similar configuration, but the S,S enantiomer is different and shows a high degree of dissociation. Growth of multilayers is observed at high exposures when the sample is kept at below 370 K. TPD experiments show that multilayers desorb between 390 K and 470 K and decomposition of the chemisorbed layer occurs between 470 K and 600 K. The desorption spectra support a two-step decomposition mechanism with a O_C_C_O or HO–HC_CH–OH intermediate that leads to production of CO2 and CO. Enantiomeric differences are observed in the desorption features related to the decomposition of the chemisorbed layer.

Robust future changes in temperature variability under greenhouse gas forcing and the relationship with thermal advection

Recent temperature extremes have highlighted the importance of assessing projected changes in the variability of temperature as well as the mean. A large fraction of present day temperature variance is associated with thermal advection, as anomalous winds blow across the land-sea temperature contrast for instance. Models project robust heterogeneity in the 21st century warming pattern under greenhouse gas forcing, resulting in land-sea temperature contrasts increasing in summer and decreasing in winter, and the pole-to-equator temperature gradient weakening in winter. In this study, future monthly variability changes in the 17 member ensemble ESSENCE are assessed. In winter, variability in midlatitudes decreases while in very high latitudes and the tropics it increases. In summer, variability increases over most land areas and in the tropics, with decreasing variability in high latitude oceans. Multiple regression analysis is used to determine the contributions to variability changes from changing temperature gradients and circulation patterns. Thermal advection is found to be of particular importance in the northern hemisphere winter midlatitudes, where the change in mean state temperature gradients alone could account for over half the projected changes. Changes in thermal advection are also found to be important in summer in Europe and coastal areas, although less so than in winter. Comparison with CMIP5 data shows that the midlatitude changes in variability are robust across large regions, particularly high northern latitudes in winter and mid northern latitudes in summer.

Thermal aspects of satellite downscaling

The strong trend toward nanosatellites creates new challenges in terms of thermal balance control. The thermal balance of a satellite is determined by the heat dissipation in its subsystems and by the thermal connections between them. As satellites become smaller, heat dissipation in their subsystems tends to decrease and thermal connectivity scales down with dimension. However, these two terms do not necessarily scale in the same way, and so the thermal balance may alter and the temperature of subsystems may reach undesired levels. This paper focuses on low-Earth-orbit satellites. We constructed a generalized lumped thermal model that combines a generalized low-Earth-orbit satellite configuration with scaling trends in subsystem heat dissipation and thermal connectivity. Using satellite mass as a scaling parameter, we show that subsystems do not become thermally critical by scaling mass alone.

Modelling personal thermal sensations using C-Support Vector Classification (C-SVC) algorithm

The personalised conditioning system (PCS) is widely studied. Potentially, it is able to reduce energy consumption while securing occupants’ thermal comfort requirements. It has been suggested that automatic optimised operation schemes for PCS should be introduced to avoid energy wastage and discomfort caused by inappropriate operation. In certain automatic operation schemes, personalised thermal sensation models are applied as key components to help in setting targets for PCS operation. In this research, a novel personal thermal sensation modelling method based on the C-Support Vector Classification (C-SVC) algorithm has been developed for PCS control. The personal thermal sensation modelling has been regarded as a classification problem. During the modelling process, the method ‘learns’ an occupant’s thermal preferences from his/her feedback, environmental parameters and personal physiological and behavioural factors. The modelling method has been verified by comparing the actual thermal sensation vote (TSV) with the modelled one based on 20 individual cases. Furthermore, the accuracy of each individual thermal sensation model has been compared with the outcomes of the PMV model. The results indicate that the modelling method presented in this paper is an effective tool to model personal thermal sensations and could be integrated within the PCS for optimised system operation and control.

A study of adaptive thermal comfort in a well-controlled climate chamber

This paper aims to critically examine the application of Predicted Mean Vote (PMV) in an air-conditioned environment in the hot-humid climate region. Experimental studies have been conducted in a climate chamber in Chongqing, China, from 2008 to 2010. A total of 440 thermal responses from participants were obtained. Data analysis reveals that the PMV overestimates occupants' mean thermal sensation in the warm environment (PMV > 0) with a mean bias of 0.296 in accordance with the ASHRAE thermal sensation scales. The Bland–Altman method has been applied to assess the agreement of the PMV and Actual Mean Vote (AMV) and reveals a lack of agreement between them. It is identified that habituation due to the past thermal experience of a long-term living in a specific region could stimulate psychological adaptation. The psychological adaptation can neutralize occupants’ actual thermal sensation by moderating the thermal sensibility of the skin. A thermal sensation empirical model and a PMV-revised index are introduced for air-conditioned indoor environments in hot-humid regions. As a result of habituation, the upper limit effective thermal comfort temperature SET* can be increased by 1.6 °C in a warm season based on the existing international standard. As a result, a great potential for energy saving from the air-conditioning system in summer could be achieved.

Daily thin-ice thickness maps from modis thermal infrared imagery

Accurate knowledge of ice-production rates within the marginal ice zones of the Arctic Ocean requires monitoring of the thin-ice distribution within polynyas. The thickness of the ice layer controls the heat loss and hence the new-ice formation. An established thinice algorithm using high-resolution MODIS data allows deriving the ice-thickness distribution within polynyas. The average uncertainty is ±4.7 cm for ice thicknesses below 0.2 m. In this study, the ice-thickness distributions within the Laptev Sea polynya for the two winter seasons 2007/08 and 2008/09 are calculated. Then, a new method is applied to determine a daily MODIS thin-ice product.

Evaluation of a polynya flux model by means of thermal infrared satellite estimates

We test the ability of a two-dimensional flux model to simulate polynya events with narrow open-water zones by comparing model results to ice-thickness and ice-production estimates derived from thermal infrared Moderate Resolution Imaging Spectroradiometer (MODIS) observations in conjunction with an atmospheric dataset. Given a polynya boundary and an atmospheric dataset, the model correctly reproduces the shape of an 11 day long event, using only a few simple conservation laws. Ice production is slightly overestimated by the model, owing to an underestimated ice thickness. We achieved best model results with the consolidation thickness parameterization developed by Biggs and others (2000). Observed regional discrepancies between model and satellite estimates might be a consequence of the missing representation of the dynamic of the thin-ice thickening (e.g. rafting). We conclude that this simplified polynya model is a valuable tool for studying polynya dynamics and estimating associated fluxes of single polynya events.

Increasing thermal plant flexibility in a high renewables power system

Thermal generation is a vital component of mature and reliable electricity markets. As the share of renewable electricity in such markets grows, so too do the challenges associated with its variability. Proposed solutions to these challenges typically focus on alternatives to primary generation, such as energy storage, demand side management, or increased interconnection. Less attention is given to the demands placed on conventional thermal generation or its potential for increased flexibility. However, for the foreseeable future, conventional plants will have to operate alongside new renewables and have an essential role in accommodating increasing supply-side variability. This paper explores the role that conventional generation has to play in managing variability through the sub-system case study of Northern Ireland, identifying the significance of specific plant characteristics for reliable system operation. Particular attention is given to the challenges of wind ramping and the need to avoid excessive wind curtailment. Potential for conflict is identified with the role for conventional plant in addressing these two challenges. Market specific strategies for using the existing fleet of generation to reduce the impact of renewable resource variability are proposed, and wider lessons from the approach taken are identified.

Different strategies for improving summer thermal comfort in heavyweight traditional buildings

In order to exploit the passive energy potential of the building envelope, it is important to provide a right combination of insulation thickness, heat capacity and night-time ventilation. In this paper, this issue will be tackled with reference to an historic building in Catania (Southern Italy). The building was built at the end of the XIX century, and its opaque envelope is entirely made with lava stones, which is typical of traditional architecture in this area. Starting from the current configuration of the building, many hypotheses for refurbishment are considered, combined with different strategies for passive cooling, such as night-time ventilation, use of shading devices and adoption of highly-reflective coatings. The effectiveness of each solution in terms of summer thermal comfort is evaluated through dynamic thermal simulations carried out with EnergyPlus. The results show the synergic effect of these strategies, as well as their individual impact, and allow to draw some general conclusions about the behaviour of heavyweight buildings under moderately hot weather conditions.

Proper evaluation of the external convective heat transfer for the thermal analysis of cool roofs

Cool materials are characterized by high solar reflectance and high thermal emittance; when applied to the external surface of a roof, they make it possible to limit the amount of solar irradiance absorbed by the roof, and to increase the rate of heat flux emitted by irradiation to the environment, especially during nighttime. However, a roof also releases heat by convection on its external surface; this mechanism is not negligible, and an incorrect evaluation of its entity might introduce significant inaccuracy in the assessment of the thermal performance of a cool roof, in terms of surface temperature and rate of heat flux transferred to the indoors. This issue is particularly relevant in numerical simulations, which are essential in the design stage, therefore it deserves adequate attention. In the present paper, a review of the most common algorithms used for the calculation of the convective heat transfer coefficient due to wind on horizontal building surfaces is presented. Then, with reference to a case study in Italy, the simulated results are compared to the outcomes of a measurement campaign. Hence, the most appropriate algorithms for the convective coefficient are identified, and the errors deriving by an incorrect selection of this coefficient are discussed.