抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

介绍了Kirk—Othmer Encyclopedia of Chemical Technology（化工技术百科全书）（第五版）电子图书网络版数据库，并对该数据库使用方法和检索途径作出了说明，且结合实例简单地介绍了该数据库的检索方法。

Kirk-Othmer Encyclopedia of Chemical Technology数据库介绍及实例

Carbon capture and storage (CCS) is broadly recognised as having the potential to play a key role in meeting climate change targets, delivering low carbon heat and power, decarbonising industry and, more recently, its ability to facilitate the net removal of CO2 from the atmosphere. However, despite this broad consensus and its technical maturity, CCS has not yet been deployed on a scale commensurate with the ambitions articulated a decade ago. Thus, in this paper we review the current state-of-the-art of CO2 capture, transport, utilisation and storage from a multi-scale perspective, moving from the global to molecular scales. In light of the COP21 commitments to limit warming to less than 2 °C, we extend the remit of this study to include the key negative emissions technologies (NETs) of bioenergy with CCS (BECCS), and direct air capture (DAC). Cognisant of the non-technical barriers to deploying CCS, we reflect on recent experience from the UK's CCS commercialisation programme and consider the commercial and political barriers to the large-scale deployment of CCS. In all areas, we focus on identifying and clearly articulating the key research challenges that could usefully be addressed in the coming decade.

/pdf/carbon-capture-and-storage-ccs-the-way-forward-11rgsqyer0.pdf

Carbon capture and storage (CCS): the way forward

The State of Food and Agriculture

Many scientific papers have been written concerning gas sensors for different sensor applications using several sensing principles. This review focuses on sensors and sensor systems for gaseous ammonia. Apart from its natural origin, there are many sources of ammonia, like the chemical industry or intensive life-stock. The survey that we present here treats different application areas for ammonia sensors or measurement systems and different techniques available for making selective ammonia sensing devices. When very low concentrations are to be measured, e.g. less than 2 ppb for environmental monitoring and 50 ppb for diagnostic breath analysis, solid-state ammonia sensors are not sensitive enough. In addition, they lack the required selectivity to other gasses that are often available in much higher concentrations. Optical methods that make use of lasers are often expensive and large. Indirect measurement principles have been described in literature that seems very suited as ammonia sensing devices. Such systems are suited for miniaturization and integration to make them suitable for measuring in the small gas volumes that are normally available in medical applications like diagnostic breath analysis equipment.

/pdf/ammonia-sensors-and-their-applications-a-review-35hg34lbf3.pdf

Ammonia sensors and their applications - a review

Unprecedented high volumes of data are becoming available with the growth of the advanced metering infrastructure. These are expected to benefit planning and operation of the future power systems and to help customers transition from a passive to an active role. In this paper, we explore for the first time in the smart grid context the benefits of using deep reinforcement learning, a hybrid type of methods that combines reinforcement learning with deep learning, to perform on-line optimization of schedules for building energy management systems. The learning procedure was explored using two methods, Deep Q-learning and deep policy gradient, both of which have been extended to perform multiple actions simultaneously. The proposed approach was validated on the large-scale Pecan Street Inc. database. This highly dimensional database includes information about photovoltaic power generation, electric vehicles and buildings appliances. Moreover, these on-line energy scheduling strategies could be used to provide real-time feedback to consumers to encourage more efficient use of electricity.

On-Line Building Energy Optimization Using Deep Reinforcement Learning

This work estimates the energy embedded in wasted food annually in the United States. We calculated the energy intensity of food production from agriculture, transportation, processing, food sales, storage, and preparation for 2007 as 8080 ± 760 trillion BTU. In 1995 approximately 27% of edible food was wasted. Synthesizing these food loss figures with our estimate of energy consumption for different food categories and food production steps, while normalizing for different production volumes, shows that 2030 ± 160 trillion BTU of energy were embedded in wasted food in 2007. The energy embedded in wasted food represents approximately 2% of annual energy consumption in the United States, which is substantial when compared to other energy conservation and production proposals. To improve this analysis, nationwide estimates of food waste and an updated estimate for the energy required to produce food for U.S. consumption would be valuable.

http://pubs.acs.org/doi/pdf/10.1021/es100310d

Wasted food, wasted energy: the embedded energy in food waste in the United States.

Clustering analysis of residential electricity demand profiles

As the need for alternative transportation fuels increases, it is important to understand the many effects of introducing fuels based upon feedstocks other than petroleum. Water intensity in “gallons of water per mile traveled” is one method to measure these effects on the consumer level. In this paper we investigate the water intensity for light duty vehicle (LDV) travel using selected fuels based upon petroleum, natural gas, unconventional fossil fuels, hydrogen, electricity, and two biofuels (ethanol from corn and biodiesel from soy). Fuels more directly derived from fossil fuels are less water intensive than those derived either indirectly from fossil fuels (e.g., through electricity generation) or directly from biomass. The lowest water consumptive (<0.15 gal H2O/mile) and withdrawal (<1 gal H2O/mile) rates are for LDVs using conventional petroleum-based gasoline and diesel, nonirrigated biofuels, hydrogen derived from methane or electrolysis via nonthermal renewable electricity, and electricity deri...

Water intensity of transportation.

Understanding the nexus between energy and water - water used for energy and energy used for water - has become increasing important in a changing world. As growing populations demand more energy supplies and water resources, research aims to analyze the interconnectedness of these two resources. Our study sought to quantify the energy-water relationship in Texas, specifically the relationship between electricity generation and water resources as it pertains to policy and society. We examined the water requirements for various types of electricity generating facilities, for typical systems both nationwide and in Texas. We also addressed the energy requirements of water supply and wastewater treatment systems, comparing national averages with Texas-specific values. Analysis of available data for Texas reveals that approximately 595,000 megaliters of water annually - enough water for over three million people for a year - are consumed by cooling the state's thermoelectric power plants while generating approximately 400 terawatt-hours of electricity. At the same time, each year Texas uses an estimated 2.1 to 2.7 terawatt- hours of electricity for water systems and 1.8 to 2.0 terawatt-hours for wastewater systems - enough electricity for about 100,000 people for a year. In preparing our analysis, it became clear that substantially more site-specific data are necessary for a full understanding of the nature of the energy-water nexus and the sustainability of economic growth in Texas. We recommend that Texas increase efforts to collect accurate data on the withdrawal and consumption of cooling and process water at power plants, as well as data on electricity consumption for public water supply and wastewater treatment plants and distribution systems. The overarching conclusion of our work is that increased efficiency advances the sustainable use of both energy and water. Improving water efficiency will reduce power demand, and improving energy efficiency will reduce water demand. Greater efficiency in usage of either energy or water will help stretch our finite supplies of both, as well as reduce costs to water and power consumers.

/pdf/the-energy-water-nexus-in-texas-1myrfxbdwk.pdf

Michael E. Webber

Papers

On-Line Building Energy Optimization Using Deep Reinforcement Learning

Wasted food, wasted energy: the embedded energy in food waste in the United States.

Clustering analysis of residential electricity demand profiles

Water intensity of transportation.

The energy-water nexus in Texas