CO2 concentrating mechanism and signal transduction pathway associated with limiting CO2 acclimation in Chlamydomonas reinhardtii

Many aquatic photosynthetic organisms exhibit a variety of acclimation responses to limiting CO2 availability, including induction of CO2 concentrating mechanisms (CCMs), which represent adaptations to environments with changing and, at times, limiting CO2 availability. Although the characteristics and regulation of limiting CO2 acclimation, including the CCM, in the green alga Chlamydomonas reinhardtii have been well demonstrated by physiological and biochemical studies, much less information is available at the molecular level with regard to the components involved in the CCM and other parts of the limiting CO2 acclimation response. We have applied insertional mutagenesis and genetic approaches in an effort to identify the components of the CCM, other pathways essential to limiting CO2 acclimation and of the regulatory pathways controlling limiting CO2 acclimation responses. Many mutants defective in acclimation to limiting CO2 environments were generated by gene tagging, and, although all the identified mutants are phenotypically high-CO2-requiring, they can be distinguished by differences in their ability to survive under various levels of CO2, by differences in heterotrophic growth, and by differences in the gene expression patterns of CO2 responsive genes. Using the insertional tags, several mutant genes have been identified or confirmed, including the transcription factor Cia5, 2-oxoglutarate dehydrogenase (Ogd2), heat shock proteins and LciB , which encodes an unknown protein apparently involved in inorganic carbon transport. The identity of defective genes in the mutants suggests that they are located in various metabolic or regulatory pathways, including the CCM, mitochondrial respiration, chloroplast photoprotection and some not yet identified regulatory pathways. In addition, it has become evident that analysis of insertional mutants in C. reinhardtii is rarely straightforward, even when there is a single insert that co-segregates with the mutant phenotype. We hope that this endeavor will continue to provide information useful in elucidating the networks associated with the limiting CO2 acclimation response and its regulation

Evaluation of Ocean Forecasting in the East China Sea

The accuracy of the initial condition of a global ocean forecasting system and its prediction skill was evaluated against in situ temperature, salinity and satellite salinity observations during the winter of 2015 and the summer of 2016 for the East China Sea. The ocean forecasting system demonstrates better skill for the Yangtze River estuary and the East China Sea during winter time than during summer time. During winter time, the root-mean-square error (RMSE) of the initial fields of the system for salinity is 1.90 psu, and the correlation is 0.56. The model has a salty bias of 0.29 psu. The salinity RMSE reduces with increasing distance from the coast. In contrast, the RMSE for temperature is 0.76°C, and the correlation is as high as 0.95. There is no bias between model temperature and observation. During summer time, the accuracy and forecast skill of the global ocean forecasting system are very poor. The RMSE for salinity is 3.14 psu, and the correlation is 0.28. The model has a salty bias of 0.95 psu. The RMSE for temperature is 7.22°C, and the model has a warm bias as high as 5.52°C

Research on measuring method of large-caliber gun muzzle vibration

In this paper, a measuring system based on binocular vision is developed for the research on large-caliber gun muzzle vibration. The system is consisted of two high-speed cameras and other equipment. The two-step calibration method based on radial constraint is adopted in order to complete the calibration, the inter-frame differential multiplication method is used to detect the centroid of moving target accurately, the improved Kalman filter tracking algorithm is used to obtain the motion trajectory of the muzzle identification point. The system is applied to practice for a type of muzzle vibration measurement and meaningful original data is acquired

Research on friction parameter identification under the influence of vibration and collision

Vibration and collision in the process of friction will cause large deviation of identification result with the actual situation. In this paper, friction process with the influence of vibration and collision as well as data collection of this process are implemented; to eliminate influence of vibration and collision in the aspect of the original data, sine filter is introduced into friction model according to the theory of Fourier series; ideas of simulated annealing is introduced into genetic algorithm to form hybrid algorithm, friction parameter can be identified combined with model and test data. The numerical results demonstrate the proposed method has effective identification results for friction process under the influence of the vibration and collision

A Decision-Framework for Building Portfolios Towards Enhanced Resilience and Sustainability of Communities Under Natural Hazards

In recent years, communities in the U.S. and other countries have experienced several catastrophic natural hazards (e.g. Hurricane Katrina in 2005 and the Christchurch Earthquake in 2011). The unproportioned social, political impact and economic loss from these events and the fact that such events will continue to occur have highlighted the vulnerability of typical communities, and more importantly, emphasized the significance of considering the performance of communities as a whole under extreme natural and man-made events over a long-time horizon. The physical built environment and the decision-making on them plays a critical role in determining the extent to which the community will perform immediately after the hazard events, the recovery trajectory afterward as well as the long-term financial health, environmental protection, and prosperity. Some communities in the U.S. began or about to implement large-scale, community-level engineering strategies. However, such strategies generally suffer from lacking quantitative support. While some studies have been done to explore the large-scale decision-making, they might be not sufficient to address the problem systematically. A uniform decision support framework for various strategies across different stages of infrastructure systems must be developed. This dissertation focuses on developing a risk-informed decision-making framework for building portfolios under the threat of natural hazards, with particular emphasis on exploring optimal strategies supporting the engineering enhancement measures in different stages of building portfolios over their lifetime. In this study, three categories of large-scale engineering strategies are discussed in depth: new construction, pre-hazard retrofitting, and post-hazard reconstruction that communities may adopt to enhance the performance of the residential building cluster, and thus the whole community in future hazards. Decision-making is explored under seismic and tornado hazards as examples and reveals that communities can and must make engineering decisions from the perspective of the resilience performance of communities and simultaneously consider the sustainability requirements (by employing the economic metric of life-cycle cost as an example). The study demonstrates that the resilience and sustainability goals could be achieved at the same time without compromising one or the other. The proposed decision-making framework could assist community leaders in designing mandatory/voluntary policies or financial incentives to let owners invest in an organized manner and collectively enable the community to achieve its pre-defined resilience and sustainability goals in the long-term

Research on damping parameter identification of elastomer buffer

The object of this paper is the changing process of damping force as the falling weight impacting the elastomer buffer. The whole mechanical system is built up through practical test and simulation. According to the type of elastomer buffer and the experimental process in shock environment, velocity damping force identification model was established. Wavelet denoising and least square method were used for parameter identification of damping force. Considering the data saturation problem in the traditional least square method, the limited memory least square method was obtained to improve the identification method. The results of parameter identification of damping force based on limited memory method proved that the limited memory method was superior to least square method. The numerical results demonstrate the effectiveness of the identification model