Aid, domestic and foreign direct investment in small states

Small States (SS) are economies whose population barely exceeds 1.5 million. Their small population size, small land size and location, mostly on coastal or Islands may act as a disadvantage to their rapid economic growth and makes them susceptible to the effects of external economic issues. Notwithstanding the disadvantages, some of them have enjoyed rapid growth over time and are classified as developed nations. This study examines the effect of aid, foreign direct investment (FDI) and domestic investment (DI) on economic growth in SS. Among SS, aid hurts the economic progress in underdeveloped countries. However, DI and FDI have a favourable impact on economic growth. In developed SS, aid, DI and FDI independently do not positively influence economic growth, however, aid with FDI, aid with trade openness and aid with domestic investment and FDI promoted growth. In the total sample (developed and developing SS), aid discourages economic growth, but FDI and DI enhance economic growth. Also, aid together with FDI positively affects economic growth. Policies should therefore be directed at moving from accepting ‘consumption aid’ to ‘productive aid’, increasing the amount of net FDI and increase in DI

In-Situ Spectro-Electrochemistry of Conductive Polymers Using Plasmonics to Reveal Doping Mechanisms

Conducting polymers are a key component for developing wearable organic electronics, but tracking their redox processes at the nanoscale to understand their doping mechanism remains challenging. Here we present an in-situ spectro-electrochemical technique to observe redox dynamics of conductive polymers in an extremely localized volume (<100 nm3). Plasmonic nanoparticles encapsulated by thin shells of different conductive polymers provide actively tuned scattering color through switching their refractive index. Surface-enhanced Raman scattering in combination with cyclic voltammetry enables detailed studies of the redox/doping process. Our data intriguingly show that the doping mechanism varies with polymer conductivity: a disproportionation mechanism dominates in more conductive polymers, while sequential electron transfer prevails in less conductive polymers

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Automated water source scheduling system with flow control system

Too much application of fertilizer can kill the plants and in irrigation, little by little application of fertilizer is better than one time big time fertilizing the plants. Water scarcity is also a major concern in irrigation. To solve the shortage of water sources, management and optimization of water sources is needed. The aim of this study is to develop a scheduling system of water sources: water with fertilizer, pond water, and ground water using Arduino and DS3231 Real Time Clock. Also, a flow control system is added to increase the efficiency of water use. The system was implemented in a controlled environmental chambers. Based on the result, the system design has been successfully functional and operational. © 2018 IEEE

Examining the Impact of Environmental Factors on Quality of Life Across Massachusetts

Several studies indicate that there are significant relationships among quality of life, green vegetation, and socioeconomic conditions, particularly in urban environments. The purpose of this research is twofold: (1) to compare two weighting and aggregation techniques, data envelopment analysis (DEA) and principal components analysis (PCA), in the development of a socioeconomic index; and (2) to test for and explore spatial variation in the relationship between socioeconomic index and environmental variables using geographically weighted regression (GWR). The analysis was conducted at the census block group level in Massachusetts. First, DEA and PCA were used to generate two separate socioeconomic indexes. Second, the relationship between these indexes and environmental variables including percentage impervious surface, percentage industrial land use, percentage land used for waste, and traffic density was modeled using ordinary least squares (OLS) regression and GWR. The GWR models explained more variance in the relationship than the OLS models and indicated that there is considerable spatial variation in the character and the strength of this relationship. The results of the GWR analyses were similar between the models generated using DEA- and PCA-derived indexes, indicating that the results were corroborative. The study concludes that the environmental variables are generally a strong predictor of the socioeconomic conditions at the scale of census block group; however, there is substantial geographical variation in the strength and the character of this relationship. The results of this study also suggest that various weighting and aggregation methods should be tested in every study that uses or creates composite indicators. © 2013 Copyright Taylor and Francis Group, LLC