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Capillaric strain sensors (CSSs) operate based on the volume expansion of closed microfluidic networks in response to linear strain and have tunable directionality and sensitivity in a large range. The unique advantages of CSSs for integrated sensor development can simplify the human movement recognition by eliminating the need for intensive computational power and reliance on machine learning algorithms. We borrowed strategies from electrical digital circuits for the integration of CSSs in OR and AND configurations. We have fabricated devices according to these strategies. To validate their functionality, we first performed tests on a benchtop model. We have mapped the strain field on the sensors using digital image correlation and used it in combination with a mathematical procedure that we have developed to accurately predict the response of the integrated CSSs (iCSSs). Finally, we have skin mounted the iCSS patches (2 × 2 cm 2 ) and conducted tests on a human subject. The results demonstrate that skin-strain-field mapping will be an enabling tool for iCSS design toward the recognition of human movements. 

In India, the second-largest sugarcane producing country in the world, accurate mapping of sugarcane land is a key to designing targeted agricultural policies. Such a map is not available, however, as it is challenging to reliably identify sugarcane areas using remote sensing due to sugarcane’s phenological characteristics, coupled with a range of cultivation periods for different varieties. To produce a modern sugarcane map for the Bhima Basin in central India, we utilized crowdsourced data and applied supervised machine learning (neural network) and unsupervised classification methods individually and in combination. We highlight four points. First, smartphone crowdsourced data can be used as an alternative ground truth for sugarcane mapping but requires careful correction of potential errors. Second, although the supervised machine learning method performs best for sugarcane mapping, the combined use of both classification methods improves sugarcane mapping precision at the cost of worsening sugarcane recall and missing some actual sugarcane area. Third, machine learning image classification using high-resolution satellite imagery showed significant potential for sugarcane mapping. Fourth, our best estimate of the sugarcane area in the Bhima Basin is twice that shown in government statistics. This study provides useful insights into sugarcane mapping that can improve the approaches taken in other regions. 

Abstract Sugar is the second largest agro-based industry in India and has a major influence on the country’s water, food, and energy security. In this paper, we use a nexus approach to assess India’s interconnected water-food-energy challenges, with a specific focus on the political economy of the sugar industry in Maharashtra, one of the country’s largest sugar producing states. Our work underscores three points. First, the governmental support of the sugar industry is likely to persist because policymakers are intricately tied to that industry. Entrenched political interests have continued policies that incentivize sugar production. As surplus sugar has been produced, the government introduced additional policies to reduce this excess and thereby protect the sugar industry. Second, although the sugar economy is important to India, sugar policies have had detrimental effects on both water and nutrition. Long-standing government support for sugarcane pricing and sales has expanded water-intensive sugarcane irrigation in low-rainfall areas in Maharashtra, which has reduced the state’s freshwater resources and restricted irrigation of more nutritious crops. Despite its poor nutritional value, empty-calorie sugar has been subsidized through the public distribution system. Third, the Indian government is now promoting sugarcane-based ethanol production. This policy has the benefit of providing greater energy security and creating a new demand for surplus sugar in the Indian market. Our analysis shows that a national biofuel policy promoting the production of ethanol from sugarcane juice versus directly from molasses may help reduce subsidized sugar for human consumption without necessarily expanding water and land use for additional production of sugarcane.