Understanding learning in fruit flies (D. melanogaster) can lead to many important discoveries about learning in humans due to the large overlap of shared DNA and the appearance of the same diseases in both species. Fruit flies have already been test subjects for many influential research experiments, some of which earned Nobel Prizes. This study seeks to investigate inhibitory conditioning in a way that differs from the traditional forward pairing inhibitory conditioning. Specifically, this experiment aims to establish inhibitory learning in fruit flies using backward association. The results show that when fruit flies are trained using backward conditioning as opposed to forward conditioning, there is a pattern of preference that differs substantially from the results showing an aversion to the associated odor in forward conditioning. When comparing the data using Two-Factor ANOVA of forward versus backward conditioning, it clearly indicates that the results are significant. Simply by altering the temporal placement of an unconditioned stimulus and a conditioned stimulus, the fruit flies learn significantly differently, switching from an aversion to the paired odor to a preference. Based on these results, fruit flies can be considered capable of inhibitory learning via backward pairing. Further research will consider whether responses become stronger after more repetitions of the training, and summation and retardation tests can be done in order to confirm that the response is, in fact, due to inhibitory conditioning and not just habituation.

Cities in the Global South face rapid urbanization challenges and often suffer an acute lack of infrastructure and governance capacities. Smart Cities Mission, in India, launched in 2015, aims to offer a novel approach for urban renewal of 100 cities following an area‐based development approach, where the use of ICT and digital technologies is particularly emphasized. This article presents a critical review of the design and implementation framework of this new urban renewal program across selected case‐study cities. The article examines the claims of the so‐called “smart cities” against actual urban transformation on‐ground and evaluates how “inclusive” and “sustainable” these developments are. We quantify the scale and coverage of the smart city urban renewal projects in the cities to highlight who the program includes and excludes. The article also presents a statistical analysis of the sectoral focus and budgetary allocations of the projects under the Smart Cities Mission to find an inherent bias in these smart city initiatives in terms of which types of development they promote and the ones it ignores. The findings indicate that a predominant emphasis on digital urban renewal of selected precincts and enclaves, branded as “smart cities,” leads to deepening social polarization and gentrification. The article offers crucial urban planning lessons for designing ICT‐driven urban renewal projects, while addressing critical questions around inclusion and sustainability in smart city ventures.`

Attitudes and habits are extremely resistant to change, but a disruption of the magnitude of the COVID-19 pandemic has the potential to bring long-term, massive societal changes. During the pandemic, people are being compelled to experience new ways of interacting, working, learning, shopping, traveling, and eating meals. Going forward, a critical question is whether these experiences will result in changed behaviors and preferences in the long term. This paper presents initial findings on the likelihood of long-term changes in telework, daily travel, restaurant patronage, and air travel based on survey data collected from adults in the United States in Spring 2020. These data suggest that a sizable fraction of the increase in telework and decreases in both business air travel and restaurant patronage are likely here to stay. As for daily travel modes, public transit may not fully recover its pre-pandemic ridership levels, but many of our respondents are planning to bike and walk more than they used to. These data reflect the responses of a sample that is higher income and more highly educated than the US population. The response of these particular groups to the COVID-19 pandemic is perhaps especially important to understand, however, because their consumption patterns give them a large influence on many sectors of the economy.