ASU Scholarship Showcase

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.`

The termites evolved eusociality and complex societies before the ants, but have been studied much less. The recent publication of the first two termite genomes provides a unique comparative opportunity, particularly because the sequenced termites represent opposite ends of the social complexity spectrum. Zootermopsis nevadensis has simple colonies with totipotent workers that can develop into all castes (dispersing reproductives, nest-inheriting replacement reproductives, and soldiers). In contrast, the fungus-growing termite Macrotermes natalensis belongs to the higher termites and has very large and complex societies with morphologically distinct castes that are life-time sterile. Here we compare key characteristics of genomic architecture, focusing on genes involved in communication, immune defenses, mating biology and symbiosis that were likely important in termite social evolution. We discuss these in relation to what is known about these genes in the ants and outline hypothesis for further testing.

The estimation of energy demand (by power plants) has traditionally relied on historical energy use data for the region(s) that a plant produces for. Regression analysis, artificial neural network and Bayesian theory are the most common approaches for analysing these data. Such data and techniques do not generate reliable results. Consequently, excess energy has to be generated to prevent blackout; causes for energy surge are not easily determined; and potential energy use reduction from energy efficiency solutions is usually not translated into actual energy use reduction. The paper highlights the weaknesses of traditional techniques, and lays out a framework to improve the prediction of energy demand by combining energy use models of equipment, physical systems and buildings, with the proposed data mining algorithms for reverse engineering. The research team first analyses data samples from large complex energy data, and then, presents a set of computationally efficient data mining algorithms for reverse engineering. In order to develop a structural system model for reverse engineering, two focus groups are developed that has direct relation with cause and effect variables. The research findings of this paper includes testing out different sets of reverse engineering algorithms, understand their output patterns and modify algorithms to elevate accuracy of the outputs.

Small and medium office buildings consume a significant parcel of the U.S. building stock energy consumption. Still, owners lack resources and experience to conduct detailed energy audits and retrofit analysis. We present an eight-steps framework for an energy retrofit assessment in small and medium office buildings. Through a bottom-up approach and a web-based retrofit toolkit tested on a case study in Arizona, this methodology was able to save about 50% of the total energy consumed by the case study building, depending on the adopted measures and invested capital. While the case study presented is a deep energy retrofit, the proposed framework is effective in guiding the decision-making process that precedes any energy retrofit, deep or light.

Commercial buildings’ consumption is driven by multiple factors that include occupancy, system and equipment efficiency, thermal heat transfer, equipment plug loads, maintenance and operational procedures, and outdoor and indoor temperatures. A modern building energy system can be viewed as a complex dynamical system that is interconnected and influenced by external and internal factors. Modern large scale sensor measures some physical signals to monitor real-time system behaviors. Such data has the potentials to detect anomalies, identify consumption patterns, and analyze peak loads. The paper proposes a novel method to detect hidden anomalies in commercial building energy consumption system. The framework is based on Hilbert-Huang transform and instantaneous frequency analysis. The objectives are to develop an automated data pre-processing system that can detect anomalies and provide solutions with real-time consumption database using Ensemble Empirical Mode Decomposition (EEMD) method. The finding of this paper will also include the comparisons of Empirical mode decomposition and Ensemble empirical mode decomposition of three important type of institutional buildings.

There are many data mining and machine learning techniques to manage large sets of complex energy supply and demand data for building, organization and city. As the amount of data continues to grow, new data analysis methods are needed to address the increasing complexity. Using data from the energy loss between the supply (energy production sources) and demand (buildings and cities consumption), this paper proposes a Semi-Supervised Energy Model (SSEM) to analyse different loss factors for a building cluster. This is done by deep machine learning by training machines to semi-supervise the learning, understanding and manage the process of energy losses. Semi-Supervised Energy Model (SSEM) aims at understanding the demand-supply characteristics of a building cluster and utilizes the confident unlabelled data (loss factors) using deep machine learning techniques. The research findings involves sample data from one of the university campuses and presents the output, which provides an estimate of losses that can be reduced. The paper also provides a list of loss factors that contributes to the total losses and suggests a threshold value for each loss factor, which is determined through real time experiments. The conclusion of this paper provides a proposed energy model that can provide accurate numbers on energy demand, which in turn helps the suppliers to adopt such a model to optimize their supply strategies.

Eusocial insects, mostly Hymenoptera, have evolved unique colonial lifestyles that rely on the perception of social context mainly through pheromones, and chemoreceptors are hypothesized to have played important adaptive roles in the evolution of sociality. However, because chemoreceptor repertoires have been characterized in few social insects and their solitary relatives, a comprehensive examination of this hypothesis has not been possible. Here, we annotate ∼3,000 odorant and gustatory receptors in recently sequenced Hymenoptera genomes and systematically compare >4,000 chemoreceptors from 13 hymenopterans, representing one solitary lineage (wasps) and three independently evolved eusocial lineages (ants and two bees). We observe a strong general tendency for chemoreceptors to expand in Hymenoptera, whereas the specifics of gene gains/losses are highly diverse between lineages. We also find more frequent positive selection on chemoreceptors in a facultative eusocial bee and in the common ancestor of ants compared with solitary wasps. Our results suggest that the frequent expansions of chemoreceptors have facilitated the transition to eusociality. Divergent expression patterns of odorant receptors between honeybee and ants further indicate differential roles of chemoreceptors in parallel trajectories of social evolution.

Epigenetic inheritance plays an important role in mediating alternative phenotype in highly social species. In order to gain a greater understanding of epigenetic effects in societies, we investigated DNA methylation in the termite Zootermopsis nevadensis. Termites are the most ancient social insects, and developmentally distinct from highly-studied, hymenopteran social insects. We used replicated bisulfite-sequencing to investigate patterns of DNA methylation in both sexes and among castes of Z. nevadensis. We discovered that Z. nevadensis displayed some of the highest levels of DNA methylation found in insects. We also found strong differences in methylation between castes. Methylated genes tended to be uniformly and highly expressed demonstrating the antiquity of associations between intragenic methylation and gene expression. Differentially methylated genes were more likely to be alternatively spliced than not differentially methylated genes, and possessed considerable enrichment for development-associated functions. We further observed strong overrepresentation of multiple transcription factor binding sites and miRNA profiles associated with differential methylation, providing new insights into the possible function of DNA methylation. Overall, our results show that DNA methylation is widespread and associated with caste differences in termites. More generally, this study provides insights into the function of DNA methylation and the success of insect societies.

Gut-associated microbiota of ants include Rhizobiales bacteria with affiliation to the genus Bartonella. These bacteria may enable the ants to fix atmospheric nitrogen, but no genomes have been sequenced yet to test the hypothesis. Sequence reads from a member of the Rhizobiales were identified in the data collected in a genome project of the ant Harpegnathos saltator. We present an analysis of the closed 1.86 Mb genome of the ant-associated bacterium, for which we suggest the species name Candidatus Tokpelaia hoelldoblerii. A phylogenetic analysis reveals a relationship to Bartonella and Brucella, which infect mammals. Novel gene acquisitions include a gene for a putative extracellular protein of more than 6,000 amino acids secreted by the type I secretion system, which may be involved in attachment to the gut epithelium. No genes for nitrogen fixation could be identified, but genes for a multi-subunit urease protein complex are present in the genome. The urease genes are also present in Brucella, which has a fecal-oral transmission pathway, but not in Bartonella, which use blood-borne transmission pathways. We hypothesize that the gain and loss of the urease function is related to transmission strategies and lifestyle changes in the host-associated members of the Rhizobiales.

Background: The molecular mechanisms of variations in individual longevity are not well understood, even though longevity can be increased substantially by means of diverse experimental manipulations. One of the factors supposed to be involved in the increase of longevity is a higher stress resistance. To test this hypothesis in a natural system, eusocial insects such as bees or ants are ideally suited. In contrast to most other eusocial insects, ponerine ants show a peculiar life history that comprises the possibility to switch during adult life from a normal worker to a reproductive gamergate, therewith increasing their life expectancy significantly.

Results: We show that increased resistance against major stressors, such as reactive oxygen species and infection accompanies the switch from a life-history trait with normal lifespan to one with a longer life expectancy. A short period of social isolation was sufficient to enhance stress resistance of workers from the ponerine ant species Harpegnathos saltator significantly. All ant groups with increased stress resistances (reproducing gamergates and socially isolated workers) have lower catalase activities and glutathione levels than normal workers. Therewith, these ants resemble the characteristics of the youngest ants in the colony.

Conclusions: Social insects with their specific life history including a switch from normal workers to reproducing gamergates during adult life are well suited for ageing research. The regulation of stress resistance in gamergates seemed to be modified compared to foraging workers in an economic way. Interestingly, a switch towards more stress resistant animals can also be induced by a brief period of social isolation, which may already be associated with a shift to a reproductive trajectory. In Harpegnathos saltator, stress resistances are differently and potentially more economically regulated in reproductive individuals, highlighting the significance of reproduction for an increase in longevity in social insects. As already shown for other organisms with a long lifespan, this trait is not directly coupled to higher levels of enzymatic and non-enzymatic antioxidants.