Low inherent nitrogen (N), phosphorus (P), and potassium (K) contents of smallholder farms limit maize grain yield. Maize grain yield response to N, P, and K mineral fertilizer application and economically optimal rates for nitrogen (EORN), phosphorus (EORP), and potassium (EORK) were evaluated on a Ferric Acrisol within the semi-deciduous forest zone of Ghana. The nutrient rates evaluated were N (0, 30, 60, 90, and 120 kg N ha-1), P (0, 30, 60, and 90 kg ha-1 P2O5), and K (0, 30, 60 and 90 kg ha-1 K2O). The treatments were arranged in a randomized complete block with three replications using an incomplete factorial design. Nutrient responses were determined using asymptotic quadratic-plus plateau functions. The best nitrogen rate for all P and K levels was 60 kg ha-1, which gave grain yield of 5 t ha-1. Nitrogen uptake, N agronomic and N recovery efficiencies peaked at 60 kg N ha-1 while N partial factor productivity declined with increasing N application rate. Cost to grain price ratios (CP) were 1.29, 1.65, and 1.65 for N, P, and K, respectively. https://www.selleckchem.com/products/ver155008.html The EORN was 61 kg ha-1, 32% less than the recommended 90 kg N ha-1 for maize production in the semi-deciduous forest zone of Ghana. Nitrogen application had the lowest CP ratio, making its application economically profitable than P and K. The findings suggest that the application of N at 61 kg N ha-1 to maize is economically profitable than at higher application rates. However, further studies should be conducted on farmers' fields to validate the results obtained.According to both professional journalists and news users, news should be relevant. While a great deal of research that treats relevance as co-constructed starts from the text of news stories, this paper asks how news users explicitly construct the (ir)relevance of particular news reports, taking a language-centered lens to open-ended survey responses. This paper makes a methodological argument in favor of a language-centered approach to open-ended survey data. Given the ubiquity of online surveys in many social science disciplines, the present paper provides an example of how this approach can deepen our understanding of survey responses. We find that news users construct relevance at varying scales, using a number of linguistic strategies of self-reference. Those who said they found the story they saw relevant used pronouns with a different distribution than those who did not, and these differences exceeded chance. In general, those who referred to themselves as members of larger collectivities were more likely to say they found a news story relevant, suggesting that relevance is discursively constructed in part through practices of self-reference.This paper argues for a specific urban planning perspective on smart governance that we call "smart urban governance," which represents a move away from the technocratic way of governing cities often found in smart cities. A framework on smart urban governance is proposed on the basis of three intertwined key components, namely spatial, institutional, and technological components. To test the applicability of the framework, we conducted an international questionnaire survey on smart city projects. We then identified and discursively analyzed two smart city projects-Smart Nation Singapore and Helsinki Smart City-to illustrate how this framework works in practice. The questionnaire survey revealed that smart urban governance varies remarkably As urban issues differ in different contexts, the governance modes and relevant ICT functionalities applied also differ considerably. Moreover, the case analysis indicates that a focus on substantive urban challenges helps to define appropriate modes of governance and develop dedicated technologies that can contribute to solving specific smart city challenges. The analyses of both cases highlight the importance of context (cultural, political, economic, etc.) in analyzing interactions between the components. In this, smart urban governance promotes a sociotechnical way of governing cities in the "smart" era by starting with the urban issue at stake, promoting demand-driven governance modes, and shaping technological intelligence more socially, given the specific context.The objective of this study was to understand the impacts of COVID-19 crisis in agriculture and food systems in Nepal and assess the effectiveness of measures to deal with this crisis. The study draws policy implications, especially for farming systems resilience and the achievement of SDGs 1 and 2. The findings are based on (i) three panel discussions over six months with policy makers and experts working at grassroots to understand and manage the crisis, (ii) key informants' interviews, and (iii) an extensive literature review. Results revealed that the lockdown and transport restrictions have had severe consequences, raising questions on the achievement of SDGs 1 and 2, especially in the already vulnerable regions dependent on food-aid. This crisis has also exposed the strengths and limitations of both subsistence and commercial farming systems in terms of resiliency, offering important lessons for policy makers. Traditional subsistence farming appears to be somewhat resilient, with a potential to contribuoving the productivity through quality inputs and by diversifying, promoting and protecting the indigenous food system, while the latter through sustainable intensification by building reliant supply network linking farming with markets and guarantying the supply of inputs.There is increasing interest in CO2 emissions inequality between and within countries, and concerns about the impacts of COVID-19 on vulnerable groups. In this study, the CO2 emissions inequality based on the different consumption category data of disaggregated income groups in eight developing countries is analyzed with the application of input-output model. We further examine the effects of the COVID-19 outbreak on CO2 emissions inequality based on the hypothetical extraction method, and the results reveal that the outbreak has decreased the CO2 emissions inequality and emissions over time. However, the shared socioeconomic pathway scenario simulation results indicate that long-term CO2 emissions inequality will persist. Targeted poverty elimination measures improve the utility of the low- and lowest-income groups and reduce CO2 emissions inequality. Reducing the excessive consumption on the demand side as well as improving the energy efficiency and increasing the share of renewable energy in the energy consumption on the supply side will provide more informed options to achieve multiple desirable outcomes, such as poverty elimination and climate change mitigation.