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.`

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.

We develop a general framework to analyze the controllability of multiplex networks using multiple-relation networks and multiple-layer networks with interlayer couplings as two classes of prototypical systems. In the former, networks associated with different physical variables share the same set of nodes and in the latter, diffusion processes take place. We find that, for a multiple-relation network, a layer exists that dominantly determines the controllability of the whole network and, for a multiple-layer network, a small fraction of the interconnections can enhance the controllability remarkably. Our theory is generally applicable to other types of multiplex networks as well, leading to significant insights into the control of complex network systems with diverse structures and interacting patterns.

Dynamical processes occurring on the edges in complex networks are relevant to a variety of real-world situations. Despite recent advances, a framework for edge controllability is still required for complex networks of arbitrary structure and interaction strength. Generalizing a previously introduced class of processes for edge dynamics, the switchboard dynamics, and exploit- ing the exact controllability theory, we develop a universal framework in which the controllability of any node is exclusively determined by its local weighted structure. This framework enables us to identify a unique set of critical nodes for control, to derive analytic formulas and articulate efficient algorithms to determine the exact upper and lower controllability bounds, and to evaluate strongly structural controllability of any given network. Applying our framework to a large number of model and real-world networks, we find that the interaction strength plays a more significant role in edge controllability than the network structure does, due to a vast range between the bounds determined mainly by the interaction strength. Moreover, transcriptional regulatory networks and electronic circuits are much more strongly structurally controllable (SSC) than other types of real-world networks, directed networks are more SSC than undirected networks, and sparse networks are typically more SSC than dense networks.

Synthetic cathinones, colloquially referred to as “bath salts,” are derivatives of the psychoactive alkaloid cathinone found in Catha edulis (Khat). Since the mid-to-late 2000s, these amphetamine-like psychostimulants have gained popularity amongst drug users due to their potency, low cost, ease of procurement, and constantly evolving chemical structures. Concomitant with their increased use is the emergence of a growing collection of case reports of bizarre and dangerous behaviors, toxicity to numerous organ systems, and death. However, scientific information regarding the abuse liability of these drugs has been relatively slower to materialize. Recently we have published several studies demonstrating that laboratory rodents will readily self-administer the “first generation” synthetic cathinones methylenedioxypyrovalerone (MDPV) and methylone via the intravenous route, in patterns similar to those of methamphetamine. Under progressive ratio schedules of reinforcement, the rank order of reinforcing efficacy of these compounds is MDPV ≥ methamphetamine > methylone. MDPV and methylone, as well as the “second generation” synthetic cathinones α-pyrrolidinovalerophenone (α-PVP) and 4-methylethcathinone (4-MEC), also dose-dependently increase brain reward function. Collectively, these findings indicate that synthetic cathinones have a high abuse and addiction potential and underscore the need for future assessment of the extent and duration of neurotoxicity induced by these emerging drugs of abuse.

The maternal separation (MS) paradigm is an animal model of early life stress. Animals subjected to MS during the first 2 weeks of life display altered behavioral and neuroendocrinological stress responses as adults. MS also produces altered responsiveness to and self-administration (SA) of various drugs of abuse including cocaine, ethanol, and amphetamine. However, no studies have yet examined the effects of MS on methamphetamine (METH) SA. This study was performed to examine the effects of MS on the acquisition of METH SA, extinction, and reinstatement of METH-seeking behavior in adulthood. Given the known influence of early life stress and drug exposure on epigenetic processes, we also investigated group differences in levels of the epigenetic marker methyl CpG binding protein 2 (MeCP2) in the nucleus accumbens (NAc) core. Long–Evans pups and dams were separated on postnatal days (PND) 2–14 for either 180 (MS180) or 15 min (MS15). Male offspring were allowed to acquire METH SA (0.05 mg/kg/infusion) in 15 2-h daily sessions starting at PND67, followed by extinction training and cue-induced reinstatement of METH-seeking behavior. Rats were then assessed for MeCP2 levels in the NAc core by immunohistochemistry. The MS180 group self-administered significantly more METH and acquired SA earlier than the MS15 group. No group differences in extinction or cue-induced reinstatement were observed. MS15 rats had significantly elevated MeCP2-immunoreactive cells in the NAc core as compared to MS180 rats. Together, these data suggest that MS has lasting influences on METH SA as well as epigenetic processes in the brain reward circuitry.

Recent works revealed that the energy required to control a complex network depends on the number of driving signals and the energy distribution follows an algebraic scaling law. If one implements control using a small number of drivers, e.g. as determined by the structural controllability theory, there is a high probability that the energy will diverge. We develop a physical theory to explain the scaling behaviour through identification of the fundamental structural elements, the longest control chains (LCCs), that dominate the control energy. Based on the LCCs, we articulate a strategy to drastically reduce the control energy (e.g. in a large number of real-world networks). Owing to their structural nature, the LCCs may shed light on energy issues associated with control of nonlinear dynamical networks.

Given a complex geospatial network with nodes distributed in a two-dimensional region of physical space, can the locations of the nodes be determined and their connection patterns be uncovered based solely on data? We consider the realistic situation where time series/signals can be collected from a single location. A key challenge is that the signals collected are necessarily time delayed, due to the varying physical distances from the nodes to the data collection centre. To meet this challenge, we develop a compressive-sensing-based approach enabling reconstruction of the full topology of the underlying geospatial network and more importantly, accurate estimate of the time delays. A standard triangularization algorithm can then be employed to find the physical locations of the nodes in the network. We further demonstrate successful detection of a hidden node (or a hidden source or threat), from which no signal can be obtained, through accurate detection of all its neighbouring nodes. As a geospatial network has the feature that a node tends to connect with geophysically nearby nodes, the localized region that contains the hidden node can be identified.

Locating sources of diffusion and spreading from minimum data is a significant problem in network science with great applied values to the society. However, a general theoretical framework dealing with optimal source localization is lacking. Combining the controllability theory for complex networks and compressive sensing, we develop a framework with high efficiency and robustness for optimal source localization in arbitrary weighted networks with arbitrary distribution of sources. We offer a minimum output analysis to quantify the source locatability through a minimal number of messenger nodes that produce sufficient measurement for fully locating the sources. When the minimum messenger nodes are discerned, the problem of optimal source localization becomes one of sparse signal reconstruction, which can be solved using compressive sensing. Application of our framework to model and empirical networks demonstrates that sources in homogeneous and denser networks are more readily to be located. A surprising finding is that, for a connected undirected network with random link weights and weak noise, a single messenger node is sufficient for locating any number of sources. The framework deepens our understanding of the network source localization problem and offers efficient tools with broad applications.

Background: 5-HT1B receptor agonists enhance cocaine intake during daily self-administration sessions but decrease cocaine intake when tested after prolonged abstinence. We examined if 5-HT1B receptor agonists produce similar abstinence-dependent effects on methamphetamine intake.

Methods: Male rats were trained to self-administer methamphetamine (0.1 mg/kg, i.v.) on low (fixed ratio 5 and variable ratio 5) and high (progressive ratio) effort schedules of reinforcement until intake was stable. Rats were then tested for the effects of the selective 5-HT1B receptor agonist, CP 94,253 (5.6 or 10 mg/kg), or the less selective but clinically available 5-HT1B/1D receptor agonist, zolmitriptan (10 mg/kg), on methamphetamine self-administration both before and after a 21-day forced abstinence period during which the rats remained in their home cages.

Results: The inverted U-shaped, methamphetamine dose-response function for intake on the fixed ratio 5 schedule was shifted downward by CP 94,253 both before and after abstinence. The CP 94,253-induced decrease in methamphetamine intake was replicated in rats tested on a variable ratio 5 schedule, and the 5-HT1B receptor antagonist SB 224,289 (10 mg/kg) reversed this effect. CP 94,253 also attenuated methamphetamine intake on a progressive ratio schedule both pre- and postabstinence. Similarly, zolmitriptan attenuated methamphetamine intake on a variable ratio 5 schedule both pre- and postabstinence, and the latter effect was sustained after each of 2 more treatments given every 2 to 3 days prior to daily sessions.

Conclusions: Unlike the abstinence-dependent effect of 5-HT1B receptor agonists on cocaine intake reported previously, both CP 94,253 and zolmitriptan decreased methamphetamine intake regardless of abstinence. These findings suggest that 5-HT1B receptor agonists may have clinical efficacy for psychostimulant use disorders.