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This study was undertaken to ascertain ovarian function under the conditions of ethanol withdrawal and continued ethanol treatment to distinguish between a temporary delay in ovarian activity and a permanent suppression of ovarian function. Immature rats were fed the following diets for 16 weeks: a liquid diet containing 5% ethanol, a liquid diet without ethanol (pair-fed controls), a liquid diet with 5% ethanol for eight weeks followed by laboratory chow and water for eight weeks, or chow and water ad lib. Vaginal patency was significantly delayed in both groups of ethanol-treated rats compared to controls. The duration of an estrous cycle for the rats in the ad lib group was 5.0 +/- 0.3 days, while a "regular" estrous cycle was four to six days in duration. The rats which received ethanol for 16 weeks exhibited more irregular estrous cycles (both less than 4 and greater than 6 days) than the rats with other treatments and the cycles were significantly longer. After 16 weeks of treatment, the rats were mated; ethanol was not given during pregnancy. The average number of pups per litter and body weight of the offspring were similar for all groups. These data show that although ethanol alters normal cyclic activity, it does not totally suppress ovarian function since alcohol-treated rats were capable of mating and delivering viable offspring.

Abstract With impending economical concerns and fuel crisis, biodiesel produced from microalgae has been proposed as a potential substitute for petroleum fuel. But experimental characterisation of combustion, performance and emission behaviour of biofuel operating under different operating conditions would be resource consuming. Even numerical modelling using computational fluid mechanics methods would be computationally consuming when combinatorics of all operating conditions are considered. In this study, we append empirical modelling to numerical modelling to derive industry feasible solutions. An artificial neural network was trained with responses at limited operating conditions obtained from a software Diesel-RK. Various variables representing combustion, performance and emission behaviour of IC engine were predicted accurately with average r-value of 0.9801 ± 0.0146 for operating conditions defined by blending, loading and fuel injection pressure. Redundancy amongst the system variables was also observed thus indicating to possible reduced empirical models.

Moss-associated N2 fixation by epiphytic microbes is a key biogeochemical process in nutrient-limited high-latitude ecosystems. Abiotic drivers, such as temperature and moisture, and the identity of host mosses are critical sources of variation in N2 fixation rates. An understanding of the potential interaction between these factors is essential for predicting N inputs as moss communities change with the climate. To further understand the drivers and results of N2 fixation rate variation, we obtained natural abundance values of C and N isotopes and an associated rate of N2 fixation with 15N2 gas incubations in 34 moss species collected in three regions across Alaska, USA. We hypothesized that δ15N values would increase toward 0‰ with higher N2 fixation to reflect the increasing contribution of fixed N2 in moss biomass. Second, we hypothesized that δ13C and N2 fixation would be positively related, as enriched δ13C signatures reflect abiotic conditions favorable to N2 fixation. We expected that the magnitude of these relationships would vary among types of host mosses, reflecting differences in anatomy and habitat. We found little support for our first hypothesis, with only a modest positive relationship between N2 fixation rates and δ15N in a structural equation model. We found a significant positive relationship between δ13C and N2 fixation only in Hypnales, where the probability of N2 fixation activity reached 95% when δ13C values exceeded - 30.4‰. We conclude that moisture and temperature interact strongly with host moss identity in determining the extent to which abiotic conditions impact associated N2 fixation rates.

Climate change is increasing overall temporal variability in precipitation resulting in a seasonal water availability, both increasing periods of flooding and water scarcity. During low water availability periods, the concentration of leachates from riparian vegetation increases, subsequently increasing dissolved organic matter (DOM). Moreover, shifts in riparian vegetation by land use changes impact the quantity and quality of DOM. Our objective was to test effects of increasing DOM concentrations from Eucalyptus grandis (one of the most cultivated tree species in the world) leachates on the metabolism (respiration, R; gross primary productivity, GPP) and extracellular enzyme activities (EEAs) of freshwater biofilms. To test effects of DOM concentrations on freshwater biofilm functions, we incubated commercial cellulose sponges in a freshwater pond to allow biofilm colonization, and then exposed biofilms to five different concentrations of leaf-litter leachates of E. grandis for five days. To test if responses to DOM concentrations varied with colonization stage of biofilms, we measured treatment effects on biofilms colonizing standard substrates after one, two, three and four weeks of colonization. Increases in leachates concentrations enhanced biofilm heterotrophy, increasing R rates and decreasing GPP. Leachate concentrations did not affect biofilm EEAs, and changes in biofilm metabolism were not explained by treatment-induced changes in biofilm biomass or stoichiometry. We detected the lowest production:respiration ratios, i.e. more heterotrophic assemblages, with the most concentrated leachate solution and the most advanced biofilm colonization stages. Shifts in quantity of dissolved organic matter in freshwaters may further influence ecosystem metabolism and carbon processing.

Abstract Power-to-gas (PtG), as a promising technology proposed to store surplus renewable energy (RE), can hardly be commercialized for its low profitability. In this paper, three approaches are proposed in this paper to enhance the profitability of the PtG. Firstly, a cooperative union containing PtG is proposed and its sustainability analysis is undertaken based on Shapley Value method. Secondly, the PtG reaction heat, as an essential by-product of PtG which is valuable and therefore requires further study, is fully exploited for district heating in the operation of regional integrated energy system, which is solved by an improved SOCP method. Thirdly, a symbiosis cooperation mode is designed for wind power and PtG to enhance the benefit of PtG through optimization-based trading strategy, which is a MINLP model and solved by Big-M method. The results show that the daily profit of PtG is significantly increased with the cooperative union as the symbiosis cooperation mode can produce a 15.1% profit lift, meanwhile, exploitation of reaction heat can produce an 8.6% profit lift. Finally, our study reveals the conflict of interest between wind power and the cogeneration. A sensitivity study on the proportion of reaction heat used for district heating is performed to verify the mutually beneficial relation between PtG and the cogeneration. The findings of this paper can guide the commercialization of PtG.

Rats of the selectively bred alcohol-preferring P and alcohol-nonpreferring NP lines were evaluated using three different behavioral measures of anxiety. Compared with NP rats, P rats (1) showed greater footshock-induced suppression of operant responding in an approach-avoidance conflict test; (2) spent less time in the open arms of an elevated plus maze; and (3) took longer in a passive avoidance test to step down from a platform to a grid floor where footshock was received 24 hours earlier. These findings indicate a greater degree of anxiety in the P than in the NP line of rats in these situations. Pretreatment with intraperitoneal (IP) ethanol (0.5-1.0 g/kg) injections produced anticonflict or anxiolytic effects in P but not in NP rats. However, the anticonflict effects of ethanol were small relative to those produced by chlordiazepoxide (CDP, 7.5 mg/kg) in both lines. The results demonstrate that selective breeding for divergent oral ethanol preference has produced associated differences between the P and NP lines of rats in behavioral tests of anxiety and in the anxiolytic effects of ethanol.

<div class="section abstract"><div class="htmlview paragraph">A study has been conducted into icephobic properties of some highly durable “off-the-shelf” elastomer materials using a rotating ice adhesion test rig installed in the NRC’s Altitude Icing Wind Tunnel. This enabled the formation of ice at environmental conditions similar to those experienced during in-flight icing encounters. Initially, the tests indicated some very positive results with ice adhesion shear stress as low as 8KPa. On further examination, however, it became apparent that the test preparation process, in which the samples were cleaned with an ethanol alcohol solution, influenced the results due to absorption and prolonged retention of the cleaning fluid. The uptake of the ethanol alcohol solution by the elastomer was found to be a function of the surface temperature and remained absorbed into the coating during the ice accretion process changing the characteristics of the coating in such a way that led to a reduction in the ice/surface bond strength.</div></div>

Ground based sky imaging and irradiance sensors are used to quantitatively evaluate the impact of cloud transmittance and cloud velocity on the accuracy of short-term direct normal irradiance (DNI) forecasts. Eight representative partly-cloudy days are used as an evaluation dataset. Results show that incorporating real-time sky and cloud transmittances as inputs reduces the root mean square error (RMSE) of forecasts of both the Deterministic model (Det) (16.3%∼ 17.8% reduction) and the multi-layer perceptron network model (MLP) (0.8% ∼ 6.2% reduction). Four computer vision methods: the particle image velocimetry method, the optical flow method, the x-correlation method and the scale-invariant feature transform method have accuracies of 83.9%, 83.5%, 79.2% and 60.9% in deriving cloud velocity, with respect to manual detection. Analysis also shows that the cloud velocity has significant impact on the accuracy of DNI forecasts: underestimating the cloud velocity magnitude by 50% results in 30.2% (Det) and 24.2% (MLP) increase of forecast RMSE; a 50% overestimate results in 7.0% (Det) and 8.4% (MLP) increase of RMSE; a ±30∘ deviation of cloud velocity direction increases the forecast RMSE by 6.2% (Det) and 6.6% (MLP).