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.`

According to the CDC, obesity has increased from 30.5% to 42.4% over the past 18 years. Western diets (WDs) consist of large portions in high fats, high carbohydrates, excess sugar and high-glycemic foods that can cause metabolic complications and mitochondrial dysfunction. Diet-induced obesity can lead to changes in muscle metabolism and muscle fiber phenotypes, which in turn lead to metabolic complications. Muscle fiber phenotype is determined protein isoform-content of myosin heavy chain (MHC). Regular exercise alters mitochondrial content and fat oxidation and shifts MHC proportions under healthy circumstances. However, diet and exercise-driven fiber type shifts in diet-induced obesity are less understood. We designed our experiment to better understand the impact of diet and/ or exercise on fiber type content of gastrocnemius muscle in diet-induced obese mice. Exercise and genistein may be used as a treatment strategy to restore the MHC proportions in obese subjects to that of the lean subjects. We hypothesized that genistein and exercise would have the greatest MHC I change in muscle fiber phenotype of mouse gastrocnemius muscles. Further, we also hypothesized that a standard diet would reverse the expected increase in fast fiber phenotype (MHC IIb). Lastly, we also hypothesized that exercise would also reduce the abundance of MHC IIb. Gastrocnemius muscles were collected from mice, homogenized, run through gel electrophoresis and stained to give muscle fiber proportions. Paired sample t-tests were conducted for differences between the MHC isoforms compared to the lean (LN) and high-fat diet (HFD) control groups. The results showed that genistein and exercise significantly increased the abundance of MHC I muscle fibers (19%, p<0.05). Additionally, diet and exercise restored the muscle fiber phenotype to that of lean control. As expected, HFD obese mice exhibited elevated fast twitch fibers compared to only 3% slow twitch fibers. These findings show the potential for exercise and supplementation of genistein as a strategy to combat diet induced obesity. Future research should aim to understand the mechanisms that genistein acts on to make these changes, and aim to replicate these data in humans with obesity.

Bats are a highly diverse mammal species with a dense virome and fascinating immune system. The following project utilizes metagenomics in order to identify DNA viruses present in populations of silver-haired bats and Mexican free-tailed bats from southern Arizona. A significant number of DNA viruses and novel viruses were identified in the Cressdnaviricota phylum and Microvirdae family.

In this research, I surveyed existing methods of characterizing Epilepsy from Electroencephalogram (EEG) data, including the Random Forest algorithm, which was claimed by many researchers to be the most effective at detecting epileptic seizures [7]. I observed that although many papers claimed a detection of >99% using Random Forest, it was not specified “when” the detection was declared within the 23.6 second interval of the seizure event. In this research, I created a time-series procedure to detect the seizure as early as possible within the 23.6 second epileptic seizure window and found that the detection is effective (> 92%) as early as the first few seconds of the epileptic episode. I intend to use this research as a stepping stone towards my upcoming Masters thesis research where I plan to expand the time-series detection mechanism to the pre-ictal stage, which will require a different dataset.

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.