Global Minnesota

TanSat is China’s first greenhouse gases observing satellite. In recent years, substantial progresses have been achieved on retrieving column-averaged CO2 dry air mole fraction (XCO2). However, relatively few attempts have been made to estimate terrestrial net ecosystem exchange (NEE) using TanSat XCO2 retrievals. In this study, based on the GEOS-Chem 4D-Var data assimilation system, we infer the global NEE from April 2017 to March 2018 using TanSat XCO2. The inversion estimates global NEE at −3.46 PgC yr-1, evidently higher than prior estimate and giving rise to an improved estimate of global atmospheric CO2 growth rate. Regionally, our inversion greatly increases the carbon uptakes in northern mid-to-high latitudes and significantly enhances the carbon releases in tropical and southern lands, especially in Africa and India peninsula. The increase of posterior sinks in northern lands is mainly attributed to the decreased carbon release during the nongrowing season, and the decrease of carbon uptakes in tropical and southern lands basically occurs throughout the year. Evaluations against independent CO2 observations and comparison with previous estimates indicate that although the land sinks in the northern middle latitudes and southern temperate regions are improved to a certain extent, they are obviously overestimated in northern high latitudes and underestimated in tropical lands (mainly northern Africa), respectively. These results suggest that TanSat XCO2 retrievals may have systematic negative biases in northern high latitudes and large positive biases over northern Africa, and further efforts are required to remove bias in these regions for better estimates of global and regional NEE.

I review the relationship between natural resource endowment type and economic growth in developing countries. Certain types of natural resources, such as oil and minerals, tend to exhibit concentrated production and revenue patterns, while revenue flows from other resources such as agriculture are more diffuse. Most developing countries that export products from the first group have been prone to growth failure in recent times. The most important channels are political economy mechanisms, where there are negative relationships between natural resource rents and institutional development. An explicit model of growth collapse with micro-foundations in rent-seeking contests that have increasing returns in rent-seeking outlays is presented.

Sentiment analysis (SA) is an enduring area for research especially in the field of text analysis. Text pre-processing is an important aspect to perform SA accurately. This paper presents a text processing model for SA, using natural language processing techniques for twitter data. The basic phases for machine learning are text collection, text cleaning, pre-processing, feature extractions in a text and then categorize the data according to the SA techniques. Keeping the focus on twitter data, the data is extracted in domain specific manner. In data cleaning phase, noisy data, missing data, punctuation, tags and emoticons have been considered. For pre-processing, tokenization is performed which is followed by stop word removal (SWR). The proposed article provides an insight of the techniques, that are used for text pre-processing, the impact of their presence on the dataset. The accuracy of classification techniques has been improved after applying text pre-processing and dimensionality has been reduced. The proposed corpus can be utilized in the area of market analysis, customer behaviour, polling analysis, and brand monitoring. The text pre-processing process can serve as the baseline to apply predictive analysis, machine learning and deep learning algorithms which can be extended according to problem definition.

Cloud Computing is the hottest research area today because of its ability to reduce costs associated with computing while increasing scalability and flexibility for computing services. Cloud computing is Internet based computing because it provides on demand dynamically to consumers by sharing resources and providing information to the software. Cloud Computing is one of the fastest growing technology IT trade for business. Cloud computing security has become a major cause of hindrance in its development. Cloud computing security is set of policies, procedure, controls, roles, permissions and technologies that work together to protect cloud based system and data. Cloud computing security has become a latest topic in academic research and industry because Cloud users have to save their data in the cloud so lack of security in the cloud cans loss the user’s trust. This paper discusses review of security in cloud computing. The study is based on all the levels of SaaS (Software as a Service), PaaS (Platform as a Service) and IaaS (Infrastructure as a Service) and the deployment model (Private, Public, Hybrid, and community cloud.

The initiative to explore the moon has always been a necessity for deep space exploration to humans. But exploration needs mobility, and whether you are on Earth or the moon, you need sensible tires to induce your vehicle from one place to another. But exploring an unknown extra-terrestrial land is a demanding task. This paper presents a survey on the lunar environment, the design requirements for a lunar rover wheel and has analyzed different rover wheels. Wheels contacting with the surface of the moon must be able to withstand the moon’s harsh environment. The wheel is required to have much terrain ability as possible in the lunar surface, which includes soft regolith and slopes to boulders/steps and craters to achieve robust teleoperation. Various kinds of wheels, such as rigid, elastic, flexible, and wire meshed concepts, have been discussed, and a qualitative analysis shows which wheel would be efficient for specific missions.