Florida International University
  • Miami, FL, United States
Recent publications
Neighborhood effects have an important role in evacuation decision-making by a family. Owing to peer influence, neighbors evacuating can motivate a family to evacuate. Paradoxically, if a lot of neighbors evacuate, then the likelihood of an individual or family deciding to evacuate decreases, for fear of crime and looting. Such behavior cannot be captured using standard models of contagion spread on networks, e.g., threshold, independent cascade, and linear threshold models. Here, we propose a new threshold-based graph dynamical system model, 2mode-threshold, which captures this dichotomy. We study theoretically the dynamical properties of 2mode-threshold in different networks, and find significant differences from a standard threshold model. We build and characterize small world networks of Virginia Beach, VA, where nodes are geolocated families (households) in the city and edges are interactions between pairs of families. We demonstrate the utility of our behavioral model through agent-based simulations on these small world networks. We use it to understand evacuation rates in this region, and to evaluate the effects of modeling parameters on evacuation decision dynamics. Specifically, we quantify the effects of (1) network generation parameters, (2) stochasticity in the social network generation process, (3) model types (2mode-threshold vs. standard threshold models), (4) 2mode-threshold model parameters, (5) and initial conditions, on computed evacuation rates and their variability. An illustrative example result shows that the absence of looting effect can overpredict evacuation rates by as much as 50%.
In this paper we provide a method for constructing new Riesz bases on separable Hilbert spaces and we use it to prove sufficient conditions for the existence of exponential Riesz bases on domains of Rd\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${ {\mathbb {R}} }^d$$\end{document}. We also apply our results to the construction of weighted exponential Riesz bases on [0, 1].
From the perspective of service science and its core concept of value co-creation, promoting learner engagement is critical for learning outcomes in a non-formal online learning environment. To promote online learning performance, we study how multidimensional learner engagement affects both instrumental and experiential learning outcomes. By incorporating the service-dominant logic perspective into the research model, we designed an online survey to investigate the impact of platform value co-creation on learners’ engagement outcomes. By employing a partial least squares-structural equation modeling (PLS-SEM), the results show that behavioral engagement, cognitive engagement, and emotional engagement have a significant impact on learning outcomes through the mediating effect of platform value, a second-order hierarchical latent variable. This study has multiple theoretical contributions and practical implications. First, we found new evidence that pursuing good learning outcomes in a non-formal online learning setting is not just a technological architecture or pedagogic guidelines, but also a “win–win” value co-creation process. Second, our results confirm the posited direct and indirect effects, thus evidencing functional value, emotional value, social value, and personalized value as components of the platform value construct, and it as a driver and mediator for better online learning outcomes. Third, our results underscore the importance of platform value in studying the impact of learner engagement on learning outcomes and provide a sharper theoretical lens to evaluate online learning platform value from the perspective of online learners.
Applications of blockchain technology (BCT) are scaling globally, especially in developing countries, where the opportunities that they exploit are often most prevalent. Achieving scale is vital for BCT ventures, which rely on network effects. BCT ventures seeking to scale employ innovative methods for scaling and also provide interesting insights on entrepreneurial scaling. We draw attention to three approaches that support scaling – promoting technology platforms, leveraging collective action, and navigating institutional contexts– and identify theoretically-grounded strategies for scaling related to these three approaches. We also build from the practical experience of cLabs, a BCT venture seeking to scale Celo, a mobile-first cryptocurrency blockchain platform focused on the developing world. We examine what BCT proponents like cLabs need to do to scale quickly and synthesize key insights, strategies for BCT ventures in developing contexts, and opportunities for future research.
Buongiorno’s two-phase model is adopted to study the impacts of the thermophoresis effect and Brownian motion on an unsteady nanofluid flow through an irregular channel due to a stretching sheet in the presence of magnetic field. The copper oxide nanoparticles are dispersed in the base solution (i.e., water) and the nanofluid thus developed is considered as an operating fluid. The thermophysical properties such as density, thermal conductivity, viscosity, heat capacitance and thermal expansion of the considered nanofluid are determined using established laws and mixture theory. The flow and heat transfer are described by the boundary layer equations that correspond to the flow field, temperature, and concentration, and associated boundary conditions are solved numerically by employing an effective and optimized finite difference technique. The convergence criteria of the developed numerical algorithm for the obtained solutions are verified. The significant features of momentum, temperature, and concentration distributions are due to the influence of key parameters which are of physical interest such as magnetic parameter, the amplitude of a wavy channel, particle-density increment parameter, Brownian diffusion coefficient, nanoparticle Lewis number are analyzed in detail. Dissecting the impact of the wavy wall, magnetic field, Brownian motion, and thermophoresis effect are a few core objectives of the study. The substantial findings are that the enhancement in the amplitude of the wavy wall impacts the flow markedly and it increases the shear stress, heat, and mass transfer rates. The strength of the magnetic field boosts the friction factor and heat transfer rate. The Brownian motion and thermophoresis effects are to increase the momentum and heat transfer rate in the boundary layer while the concentration field is noticed to be decreasing. The fluid mechanisms behind these physical reasons are discussed in detail.
The spiny lobster fishery in Florida uses live, sublegal-size lobsters as bait in the approximately 450,000 traps currently permitted in the fishery. Live baits increase the catch of traps, yet confinement in traps compromises lobster health and causes mortality. We conducted a field experiment to test the suitability of traps fitted with escape gaps to address a priority need for reducing catch and mortality of sublegal-size lobsters and other species in Florida’s spiny lobster trap fishery. We then modeled the potential effect of escape gaps on the Florida commercial spiny lobster trap fishery (via a Monte Carlo simulation technique) to identify the effect on fishery harvest. We measured catch rates and mortality of lobsters in traps with or without a 54 mm escape gap and baited with either a live sublegal-size lobster, a live legal-size lobster, or left unbaited. The relationship between catch in traps fitted with escape gaps vs. catch in control traps determined from the field experiment was applied to commercial fishery landings data from 2010 to 2018 and used to model changes in harvest as result of implementing escape gaps and baiting with a legal-size lobster. We found that traps with escape gaps nearly eliminated catch of sublegal-size lobsters in traps, which would lower mortality caused by such confinement and potentially allow hundreds of thousands of lobsters to remain in the population. Alternatively, replacing live bait lobsters every two weeks reduced bait mortality by half in our field experiment; thus, mortality of sublegal-size lobsters used as bait in the fishery could be reduced through frequent release of bait lobsters. Escape gaps also reduced fish bycatch, including some in the snapper-grouper management complex. Traps with escape gaps and baited with legal-size lobsters caught ~27% ± 16% fewer legal-size lobsters than control lobster traps baited with a sublegal-size lobster. However, these traps caught as many legal-size lobsters as control lobster traps baited with sublegal-size lobsters when lobster abundance was high, demonstrating that self-baiting of traps is density dependent. Although traps with escape gaps caught fewer legal-size lobsters per trap, fishery modeling indicated that increased survival of sublegal-size lobsters could increase landings by the second to fourth year after implementation of escape gaps, depending on which model assumptions are used to predict landings.
Latent heat thermal energy storage (LHTES) systems are attractive for bridging the energy supply and demand gap. In such systems, reducing storage time is critical, especially for solar applications. Accordingly, this study mainly aims to employ various nano-additives, including metal (Ag and Cu) and metal-oxide (Al2O3, CuO, and TiO2) nanoparticles and carbon-based nanomaterials (GNP, MWCNT, SWCNT), to improve the thermophysical properties of pure phase change materials (PCM) to accelerate the melting process. For this purpose, the energy storage performance was numerically analyzed in a vertical shell and tube LHTES unit where D-mannitol was utilized as the PCM on the shell side. Dynalene-ht was employed as a heat transfer fluid (HTF) in the tube. Using computational fluid dynamics (CFD) modeling, transient variations in liquid fraction, PCM temperature, and total melting time were investigated under the impact of the following parameters: the thermophysical properties and volume fraction of nanomaterials, Re and the inlet temperature of HTF. In addition, a methodology based on Bayesian inference was adopted by coding the Bayesian MCMC simulation to create proper models for predicting the melting time. The numerical results showed that adding carbon-based nanomaterials to pure PCM reduced the melting time by about 50%, while metal nanoparticles impaired the melting performance. It was also observed that adding metal oxide nanoparticles did not add any essential advantage to the LHTES system. This research will help design TES applications in the operating temperature range of 160–200 °C, especially in solar cooling systems.
Wind gusts and rainfall from tropical cyclones can heavily damage forest canopies, leading to abrupt changes in forest structure and tree demography. Although many studies have shown that successive tropical cyclones can interact with each other through residual effects, the role of past disturbances is unclear because they may lead to damage amplification of the second cyclone because of weakened forest structure, or damage reduction of the second cyclone because of previous damage to susceptible trees. We investigated the interaction between consecutive cyclones between 2001 and 2017 for five well-conserved forests in Taiwan, which experiences an average of 1.75 typhoons annually. Using MODIS imagery, we computed the typhoon-induced change of a canopy vegetation index, the Normalized Difference Infrared Index (NDII). The effects of successive typhoons were assessed separately for typhoons occurring within a single year (annual analysis) and within two consecutive years (biennial analysis). We used mixed effect models of reductions in NDII, a measurement of canopy damage, in relation to target and past typhoon characteristics and damage magnitude. NDII reduction induced by preceding typhoons was slightly more important and statistically significant in explaining the variation in NDII reduction associated with the target typhoon in the annual than in the biennial analysis, where the effect was non-significant. Canopy damage did not always decrease across typhoons occurring within the same season, however, for most successive typhoons in the biennial analysis, the second cyclone caused equal or less canopy damage (16 out of 21 typhoon pairs). These results support the idea that residual interactive effects of previous typhoons decrease quickly over time and rarely last for several typhoon seasons for Taiwanese forests, contributing to their high resistance to frequent typhoon disturbance.
Marburgvirus (MARV), a member of the Filovirus family, causes severe hemorrhagic fever in humans. Currently, there are no approved vaccines or post exposure treatment methods available against MARV. With the aim of identifying vaccine candidates against MARV, we employ different sequence-based computational methods to predict the MHC-I and MHC-II T-cell epitopes as well as B-cell epitopes for the complete MARV genome. We analyzed the variations in the predicted epitopes among four MARV variants, the Lake Victoria, Angola, Musoke, and Ravn. We used a consensus approach to identify several epitopes, including novel epitopes, and narrowed down the selection based on different parameters such as antigenicity and IC50 values. The selected epitopes can be used in various vaccine constructs that give effective antibody responses. The MHC-I epitope-allele complexes for GP and NP with favorably low IC50 values were investigated using molecular dynamics computations to determine the molecular details of the epitope-allele complexes. This study provides information for further experimental validation of the potential epitopes and the design and development of MARV vaccines.
Autistic individuals who are also people of color or from lower socioeconomic strata are historically underrepresented in research. Lack of representation in autism research has contributed to health and healthcare disparities. Reducing these disparities will require culturally competent research that is relevant to under-resourced communities as well as collecting large nationally representative samples, or samples in which traditionally disenfranchised groups are over-represented. To achieve these goals, a diverse group of culturally competent researchers must partner with and gain the trust of communities to identify and eliminate barriers to participating in research. We suggest community-academic partnerships as one promising approach that results in high-quality research built on cultural competency, respect, and shared decision making.
Introduction The aim of this study is to investigate the gender distribution of first and senior authors in the most highly cited original research studies published in the top 10 surgical journals from 2015 to 2020 to identify disparities and changes over time. Methods A retrospective study analyzing the gender distribution of first and senior authors in the top 10 most cited studies from the top 10 surgical journals from 2015 to 2020. The genders of the first and senior authors of each study were assessed using National Provider Identifier (NPI) numbers or pronouns from institutional biographies or news articles. Results The genders of 1200 first and senior authors from 600 original research studies were assessed. First author gender distribution consisted of 71.8% men, 22.3% women, 0% non-binary, and 5.8% unknown. Senior author gender distribution was 82.3% men, 14.3% women, 0% non-binary, and 3.3% unknown. Studies published by first authors who are women received more citations than those published by first authors that are men in 2015 (169.1 versus 112.9, P = 0.002) and 2016 (144.2 versus 101.5, P = 0.011). There was an increase in first authorship among men from 2015 to 2020 (P = 0.035). Conclusions Men represent a significantly higher proportion of both first and senior authorships in top surgical research and the gap has widened from 2015 to 2020. However, studies written by women first authors received significantly more citations than those written by men.
Introduction A growing percentage of the US population is over the age of 65, and geriatrics account for a large portion of trauma admissions, expected to reach nearly 40% by 2050. Cognitive status is important for operative management, especially in elderly populations. This study aims to investigate preoperative and postoperative cognitive function assessment tools in geriatric patients following acute trauma and associated outcomes, including functional status, postdischarge disposition, mortality, and hospital length of stay (H-LOS). Methods A literature search was conducted using Medline/PubMed, Google Scholar, Embase, JAMA Networks, and Cochrane databases for studies investigating the use of cognitive assessment tools for geriatric patients with acute trauma. The last literature search was conducted on November 13, 2021. Results Ten studies were included in this review, of which five focused on preoperative cognitive assessment and five focused on postoperative. The evidence suggests patients with preoperative cognitive impairment had worse functional status, mortality, and postdischarge disposition along with increased LOS. Acute trauma patients with postoperative cognitive impairment also had worse functional status, mortality, and adverse postdischarge disposition. Conclusions Preoperative and postoperative cognitive impairment is common in geriatric patients with acute trauma and is associated with worse outcomes, including decreased functional status, increased LOS, and adverse discharge disposition. Cognitive assessment tools such as MMSE, MoCA, and CAM are fast and effective at detecting cognitive impairment in the acute trauma setting and allow clinicians to address preoperative or postoperative cognitive impairments to improve patient outcomes.
Previous studies have characterized the impact of substance use on cerebral structure and function in adolescents. Yet, the great majority of prior studies employed a small sample, presented cross‐sectional findings, and omitted potential sex differences. Using data based on 724 adolescents (370 females) curated from the NCANDA study, we investigated how gray matter volumes (GMVs) decline longitudinally as a result of alcohol and cannabis use. The impacts of alcohol and cannabis co‐use and how these vary across assigned sex at birth and age were examined. Brain imaging data comprised the GMVs of 34 regions of interest and the results were evaluated with a Bonferroni correction. Mixed‐effects modeling showed faster volumetric declines in the caudal middle frontal cortex, fusiform, inferior frontal, superior temporal (STG), and supramarginal (SMG) gyri, at −0.046 to −0.138 cm3/year in individuals with prior‐year alcohol and cannabis co‐use, but not those engaged in alcohol or cannabis use only. These findings cannot be explained by more severe alcohol use among co‐users. Further, alcohol and cannabis co‐use in early versus late adolescence predicted faster volumetric decline in the STG and SMG across assigned sex at birth. Findings highlight the longitudinal impact of alcohol and cannabis co‐use on brain development, especially among youth reporting early adolescent onset of use. The volumetric decline was noted in cortical regions in support of attention, memory, executive control, and social cognition, suggesting the pervasive effect of alcohol and cannabis co‐use on brain development. Mixed‐effects modeling showed faster volumetric declines in the caudal middle frontal cortex, fusiform, inferior frontal, superior temporal (STG), and supramarginal (SMG) gyri, at −0.046 to −0.138 cm3/year in individuals with prior‐year alcohol and cannabis co‐use, but not those engaged in alcohol or cannabis use only. These findings cannot be explained by more severe alcohol use among co‐users. Further, alcohol and cannabis co‐use in early versus late adolescence predicted a faster volumetric decline in the STG and SMG across biological sex.
Using a community based participatory research framework and ecological systems theory we explored the experiences of reproductive health among Inuit women living in a remote Northwestern settlement in Greenland to understand the multiple diverse factors that influence their pregnancy outcomes. We conducted 15 in depth interviews with Inuit women between the ages of 19 and 45. Key factors influencing women’s pregnancy decision making were: 1) precursors to pregnancy; 2) birth control use; 3) adoption and abortion; and 4) access to reproductive health care. Our results highlight the need to identify pathways through research, policy, health promotion, and health care practice that can support Inuit women in Greenland to be reproductively healthy and make informed decisions about pregnancy that resonate with their cultural beliefs as well as the realities of their everyday lives. We recommend the integration of cultural messaging into interdisciplinary approaches for preventive reproductive health care with women living in remote Arctic communities.
Noncoding RNAs are important regulators of mucoinflammatory response, but little is known about the contribution of airway long noncoding RNAs (lncRNAs) in COVID-19. RNA-seq analysis showed a more than four-fold increased expression of IL-6, ICAM-1, CXCL-8, and SCGB1A1 inflammatory factors; MUC5AC and MUC5B mucins; and SPDEF, FOXA3, and FOXJ1 transcription factors; in COVID-19 patient nasal samples compared to uninfected controls. A lncRNA on antisense strand to ICAM-1 or LASI was induced two-fold in COVID-19 patients and its expression was directly correlated with viral loads. A SARS-CoV-2 infected 3D-airway model largely recapitulated these clinical findings. RNA microscopy and molecular modeling indicated a possible interaction between viral RNA and LASI lncRNA. Notably, blocking LASI lncRNA reduced the SARS-CoV-2 replication and suppressed MUC5AC mucin levels and associated inflammation, and select LASI-dependent miRNAs (e.g., let-7b-5p and miR-200a-5p) were implicated. Thus, LASI lncRNA represents an essential facilitator of SARS-CoV-2 infection and associated airway mucoinflammatory response.
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13,268 members
Upal Roy
  • Department of Immunology
Lynne Webb
  • Communication
Shimelis Setegn
  • Environmental Health Sciences
Jay P. Sah
  • Institute of Environment
Imran Ahmad
  • CSHTM - Food & Bev. Science
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