Characteristic of Stomatal Conductance and Optimal Stomatal Behaviour in an Arid Oasis of Northwestern China

Stomatal conductance (gs), the process that governs plant carbon uptake and water loss, is fundamental to most Land Surface Models (LSMs). With global change accelerating, more attention should be paid to investigating stomatal behavior, especially in extremely arid areas. In this study, gas exchange measurements and environmental/biological variables observations during growing seasons in 2016 and 2017 were combined to investigate diurnal and seasonal characteristics of gs and the applicability of the optimal stomatal conductance model in a desert oasis vineyard. The results showed that the responses of gs to environmental factors (photosynthesis active radiation, PAR; vapor pressure deficit, VPD; and temperature, T) formed hysteresis loops in the daytime. The stomatal conductance slope, g1, a parameter in the unified stomatal optimal model, varied in different growing seasons and correlated with the soil-to-leaf hydraulic conductance (KL). These results indicated the potential bias when using a constant g1 value to simulate gs and highlighted that the water-use strategy of oasis plants might not be consistent throughout the entire growing season. Our findings further help to achieve a better understanding of stomata behavior in responding to climate change and encourage future efforts toward a more accurate parameterization of gs to improve the modeling of LSMs.

ONTOGENETIC, BREED, AND SEASONAL FEATURES OF THE SYNTHESIS OF THYROXIN AND CORTISOL IN DOGS AND CATS

The article presents data on the breed and seasonal characteristics of the synthesis of thyroxine and cortisol in dogs of different breeds and cats that do not have a breed. It has been shown that the synthesis of thyroxine in dogs and cats depends on the breed, age and season. The functional activity of the thyroid gland in dogs decreases by 10-12, and in cats by 9-13 years of age. The highest level of thyroxine production throughout the entire research period belongs to the Griffon Petit-Brabancons. The synthesis of cortisol in dogs and cats is stable and does not undergo statistically significant changes. Seasonal dynamics of thyroxine is observed in dogs, but absent in cats. No sea-sonal dependence of cortisol synthesis has been reported in dogs and cats.

A statistics and physics-based tropical cyclone full track model for catastrophe risk modeling

Catastrophe (CAT) risk modeling of perils such as typhoon and earthquake has become a prevailing practice in the insurance and reinsurance industry. The event generation model is the key component of the CAT modeling. In this paper, a physics-based tropical cyclone (TC) full track model is introduced to model typhoons events in the western North Pacific basin. At the same time, a comprehensive test of the model is presented from the perspective of CAT risk modeling for insurance and reinsurance applications. The full track model includes the genesis, track, intensity, and landing models. Driven by the global environmental circulations, the model employs the advection and beta drift theory in atmospheric dynamics to model the track of typhoons. The proposed model is novel in the way of modeling the genesis of TCs with three-dimension kernel distributions in space and time. This enables the simulation of seasonal characteristics of TCs. By generating 10,000-year TC events, we comprehensively test the model from the standpoint of CAT insurance and reinsurance applications. The typhoon hazard model and the generated events can serve as the inputs for assessing the typhoon risk and insured loss caused by winds, rains, floods, and storm surges.

Nature-Inspired Approach Using Seasonal Comparison of Wind Speed With Spectral and Statistical Analysis

Seasonal analysis of wind speed includes elements of its evaluation and analysis for wind energy production in complex geographical areas. These analyses require wind energy systems to be set up, integrated, operated, and designed according to seasonal differences. Istanbul wind speed data were collected hourly and analyzed seasonally. When the results of the analysis are examined, no significant increase in seasonal transitions was observed, while certain changes were observed between summer and winter. Here, statistical analysis, Weibull distribution function, and signal processing-based PSD analysis for wind speed is performed. In addition, correlation analysis was made between the seasons. Although significant results were obtained in signal-based analyses, results were obtained for seasonal transitions in correlation analyses. Seasonal spectral densities were calculated in the spectral analysis of wind speed data. This study has important implications in terms of extraction of seasonal characteristics of wind speed, resource assessment, operation, investment, and feasibility.

A Panel Asymmetric Causality Between Health and Climate Change

As climate change threatens human life and health by causing severe storms, floods, temperature fluctuations and droughts, it is predicted that in the coming decades, most of the global population will be impacted and the lives of millions will be at risk. In this context, the article investigates the existence of a symmetric and asymmetric causality between climate change and health between 1990 and 2015 for European countries, including EU, EFTA member and EU candidate states. In the first stage of the analysis, health scores are estimated by cluster and discriminant analyses; in the second stage, the relationships among these scores and climate variables are examined. The country-specific findings are obtained for the health effects of climate change variables according to factors such as geographical structure and seasonal characteristics. According to the results, while the health effects of changes in temperature and greenhouse emissions differ from country to country, the reduction in precipitation for nearly half of the countries is found to have a negative effect on health.

Physical chemical and citotoxic evaluation of highly diluted solutions of Euphorbia tirucalli L. prepared through the fifty milesimal homeopathic method

Background: although Hahnemann described the fifty-milesimal (LM) method in the 6th edition of the Organon of the Medical Art, very little research has been carried out on the physical chemical properties of these homeopathic preparations. Furthermore, there is still no evidence allowing for the correlation between the alleged physical chemical properties and the biological effects of high dilutions. Aims: to evaluate physical chemical characteristics of LM preparations including electrical conductivity, pH and refraction index, and their effect on biological experimental models. Materials and methods: preparations tested for physical chemical analysis were dilutions 1 lm to 10 lm of Euphorbia tirucalli L. prepared from the latex and the juice of the plant. To rule the seasonal characteristics of this plant, 2 different populations were used, one collected in June 2007 and the other in May 2008. Furthermore, the cytotoxic effect of Euphorbia tirucalli 5 lm was tested on human breast cancer cells (MCF7) through MTT assay. Some differences among the two collections were observed. However, any clear correlation could be observed between physical chemical properties and biological activity.

Seasonal characteristics of atmospheric peroxyacetyl nitrate (PAN) in a coastal city of Southeast China: Explanatory factors and photochemical effects

Peroxyacetyl nitrate (PAN) acting as a typical indicator of photochemical pollution can redistribute NOx and modulate O3 production. Coupled with the observation-based model (OBM) and a generalized additive model (GAM), the intensive observation campaigns were conducted to reveal the pollution characteristics of PAN and its impact on O3, the contributions of influencing factors to PAN formation were also quantified in this paper. The F-values of GAM results reflecting the importance of the influencing factors showed that ultraviolet radiation (UV, F-value = 60.64), Ox (Ox = NO2+O3, 57.65), and air temperature (T, 17.55) were the main contributors in the PAN pollution in spring, while the significant effects of Ox (58.45), total VOCs (TVOCs, 21.63) and T (20.46) were found in autumn. The PAN formation rate in autumn was 1.58 times higher than that in spring, relating to the intense photochemical reaction and meteorological conditions. Without considering the transformation of peroxyacetyl radical (PA) and PAN, acetaldehyde contributed to the dominant production of PA (46 ± 4 %), followed by methylglyoxal (28 ± 3 %) and radical cycling (19 ± 3 %). The PAN formation was highly VOC-sensitive, and sufficient NOx (compared with VOCs abundance) would not be the limited factor for atmospheric photochemistry. PAN could promote or inhibit O3 formation under high or low ROx levels, respectively. The PAN promoting O3 formation mainly occurred during the periods of 11:00–16:00 (local time) when the favorable meteorological conditions (high UV and T) stimulated the photochemical reactions to offer ROx radicals, which accounted for 17 % of the whole monitoring periods in spring and 31 % in autumn. In this study, the formation mechanism of PAN and its effect on ozone were identified, which might be helpful to improve the scientific understanding of photochemical pollution in coastal areas.

A Novel Decomposition and Combination Technique for Forecasting Monthly Electricity Consumption

With the share of electricity in total final energy consumption increasing quickly, the world is becoming increasingly dependent on electricity, which makes it more and more important to improve the forecasting accuracy of electricity consumption to ensure the normal operation of economic activities. In this paper, a novel decomposition and combination technique to forecast monthly electricity consumption is proposed. First, we use STL decomposition to obtain the trend, season, and residual components of the time series. Second, we use SARIMA, SVR, ANN, and LSTM to forecast trend, season, and residual component, respectively. Third, we use time correlation principle to improve the forecasting accuracy of season component. Fourth, we integrated the residual component predicted by SARIMA, SVR, ANN, and LSTM into a new sequence to improve the forecasting accuracy of residual component. In order to verify the performance of the proposed forecast model, monthly electricity consumption data in China is introduced as an example for empirical analysis. The results show that after STL decomposition, time correlation modification, and residual modification, the forecasting accuracy of each model has been gradually improved. We believe that the proposed forecast model in this paper can also be used to solve other mid- and long-term forecasting problems with obvious seasonal characteristics.