University of Central Florida
  • Orlando, Florida, United States
Recent publications
The simply supported slab bridge is a typical perfricated reinforced concrete bridge. Under the influence of increasing vehicle loads and natural environmental erosion, the hinge joints between slabs suffer from damage that cannot be easily evaluated, which brings negative effects on the load carrying capacity of bridges. In the present study, a hybrid method for damage detection and condition assessment of hinge joints in hollow slab bridges using physical models and vision-based measurements was proposed. The stiffness reduction of hinge joints is taken as the damage degree and condition level of the inspected hinge joints. An analytical model of a simplified spring-mass system was firstly built to demonstrate the applicability of using the relative displacement ratio as the damage index of hinge joints. The relationship between the relative displacement ratio and the stiffness reduction of hinge joints was then studied thoroughly through a parametric study on finite element models considering different damage levels of hinge joints. Thresholds of the relative displacement ratio were defined to classify the damage states of hinge joints. The damage index of target hinge joints can be calculated from the actual data provided by using computer vision-based multi-camera and multi-point displacement measurements. Lastly, the application of a real-life bridge under normal traffic was demonstrated to verify the feasibility of the quantitative evaluation of the service status of joints in hinged-slab bridges. It indicated that the proposed method could evaluate the damage degree of joints quantitatively, effectively and economically.
Target detection in infrared imagery is a particularly challenging problem due to the presence of terrain clutter. The TCRNet-2 CNN architecture was introduced to combat this issue and has been shown to perform better than conventional networks such as faster RCNN and YOLOv3. In this paper, we evaluate the performance of the Boosted 2-Stream TCRNet in detail (including robustness to range variations, performance under day and night conditions) and compare it with that of YOLOv5. A MWIR dataset released by DSIAC is used for training and testing the network. We also propose the MWIR target classifier that recognizes the 10 classes in the NVESD dataset and achieves an accuracy of 65.72% which is state-of-the-art to date.
As Structural Health Monitoring (SHM) being implemented more over the years, the use of operational modal analysis of civil structures has become more significant for the assessment and evaluation of engineering structures. Machine Learning (ML) and Deep Learning (DL) algorithms have been in use for structural damage diagnostics of civil structures in the last couple of decades. While collecting vibration data from civil structures is a challenging and expensive task for both undamaged and damaged cases, in this paper, the authors are introducing Generative Adversarial Networks (GAN) that is built on the Deep Convolutional Neural Network (DCNN) and using Wasserstein Distance for generating artificial labelled data to be used for structural damage diagnostic purposes. The authors named the developed model “1D W-DCGAN” and successfully generated vibration data which is very similar to the input. The methodology presented in this paper will pave the way for vibration data generation for numerous future applications in the SHM domain.
This article presents the development and assessment of the Multidimensional Dispositional Greed Assessment (MDGA) scores, designed to measure adults’ dispositional greed. We present two studies detailing (a) the construction and administration of the MDGA to an initial sample of adults (study 1, exploratory factor analysis [EFA]; N = 875), and (b) the administration of the MDGA to a validating sample of adults (confirmatory factor analysis [CFA]; N = 922) and examining evidence of convergent validity (study 2). The EFA results identified a 21-item MDGA exploratory model, accounting for 73.97% of the variance and encompassing three factors, including Insatiable Pursuit for More at all Costs, Desire for More, and Retention Motivation. The CFA results validated a three-factor oblique 20-item MDGA model, accounting for 59.1% of the variance, and evidence of convergent validity. The MDGA is a promising self-report measure for scholars investigating the construct of dispositional greed.
Background: The evidence-based practice (EBP) process was challenged during the early phase of the COVID-19 pandemic by factors such as a novel disease, rapidly changing guidelines, shortage of personal protective equipment, and other health care supplies. Objectives: Our aims were to (1) explore sources of evidence sought by critical care nurses during a pandemic and (2) explore nurses' perceptions of EBP. Methods: A qualitative exploratory study was conducted using deidentified data from the American Association of Critical-Care Nurses (ACCN) open-access Facebook page, January 28 to April 30, 2020. Results: Two major themes were identified: (1) "sharing and seeking evidence," that is, nurses used both formal and informal sources to explore evidence supporting evolving clinical practices, and (2) "concerns about evidence," that is, nurses expressed concerns about lack of evidence and mistrust of evolving evidence. Discussion: Initially, there was a mismatch in nurses' expectations of the American Association of Critical-Care Nurses Facebook page. A major limitation of Facebook is the lack of a repository for quick retrieval of information. Despite these limitations, and fear and mistrust of changing guidelines, social media was used to communicate, collaborate, and share evidence to support clinical practice. Critical care nurses seemed to value evidence to support patient management and their personal safety during this evolving health crisis. Conclusions: Social media played a large role in dissemination of timely evidence-based information during the early pandemic. Our results show that current EBP models should be revised to prepare for future crises and include direction for dealing with limited health care resources, and lack of and/or rapidly changing evidence.
Introduction Thrombolysis for acute ischemic stroke (AIS) with alteplase is the currently approved therapy for patients who present within 4.5 h of symptom onset and meet criteria. Recently, there has been interest in the thrombolytic tenecteplase, a modified version of alteplase, due to its lower cost, ease of administration, and studies reporting better outcomes when compared to alteplase. This systematic review compares the efficacy of tenecteplase vs. alteplase with regard to three outcomes: (1) rate of symptomatic hemorrhage, (2) functional outcome at 90 days, and (3) reperfusion grade after thrombectomy to compare the efficacy of both thrombolytics in AIS Methods The search was conducted in August 2021 in PubMed, filtered for randomized controlled trials, and studies in English. The main search term was “tenecteplase for acute stroke.” Results A total of 6 randomized clinical trials including 1675 patients with AIS was included. No one’s study compared alteplase to tenecteplase with all three outcomes after acute ischemic stroke; however, by using a combination of the results, this systematic review summarizes whether tenecteplase outperforms alteplase. Conclusions The available evidence suggests that tenecteplase appears to be a better thrombolytic agent for acute ischemic stroke when compared to alteplase.
Background: There is an alarming shortage of addiction psychiatrists in the United States. To promote interest in addiction psychiatry (ADP), it is essential to maximize resources available through ADP fellowship websites. The aim of this study was to investigate the perceived adequacy and accessibility of content on ADP fellowship websites and discover what further information is considered important among trainees interested in becoming addiction specialists. Methods: Three virtual focus groups were conducted between January and February 2021 among medical students and residents in diverse geographic regions. Participants were asked about the availability of information on ADP fellowship program websites and other material they would like to see available. Focus groups were recorded, with data transcribed and coded using NVivo 11 and Dedoose. A coding scheme was deductively developed based on the core research questions. Results: The majority of participants (N = 27) identified areas of dissatisfaction with the content currently available on ADP websites. The sample was highly representative of racial and ethnic minoritized trainees (n = 12) and genderqueer/non-binary participants (n = 3). Three major themes were identified and durable across all focus groups: lack of emphasis on diversity/health equity, lack of portrayal of everyday life and activities of fellows, and inadequate representation of curricula. Overwhelmingly, participants identified a dedication to health equity (for example, working with minoritized populations) as a key deciding factor in whether to apply to a particular ADP fellowship. Conclusions: ADP fellowship websites are perceived to have considerable variability in the amount and quality of information. Many do not appear to provide the full spectrum of content desired by diverse potential applicants, such as information regarding current fellows and community-centered initiatives. This is concerning, as it suggests ADP fellowships may be interfacing poorly with burgeoning leaders, especially those from race and gender minoritized backgrounds, neglecting potential opportunities to develop future addiction specialists.
Individual atomic defects in 2D materials impact their macroscopic functionality. Correlating the interplay is challenging, however, intelligent hyperspectral scanning tunneling spectroscopy (STS) mapping provides a feasible solution to this technically difficult and time consuming problem. Here, dense spectroscopic volume is collected autonomously via Gaussian process regression, where convolutional neural networks are used in tandem for spectral identification. Acquired data enable defect segmentation, and a workflow is provided for machine-driven decision making during experimentation with capability for user customization. We provide a means towards autonomous experimentation for the benefit of both enhanced reproducibility and user-accessibility. Hyperspectral investigations on WS 2 sulfur vacancy sites are explored, which is combined with local density of states confirmation on the Au{111} herringbone reconstruction. Chalcogen vacancies, pristine WS 2 , Au face-centered cubic, and Au hexagonal close-packed regions are examined and detected by machine learning methods to demonstrate the potential of artificial intelligence for hyperspectral STS mapping.
Liquid crystal displays (LCDs) and photonic devices play a pivotal role to augmented reality (AR) and virtual reality (VR). The recently emerging high-dynamic-range (HDR) mini-LED backlit LCDs significantly boost the image quality and brightness and reduce the power consumption for VR displays. Such a light engine is particularly attractive for compensating the optical loss of pancake structure to achieve compact and lightweight VR headsets. On the other hand, high-resolution-density, and high-brightness liquid-crystal-on-silicon (LCoS) is a promising image source for the see-through AR displays, especially under high ambient lighting conditions. Meanwhile, the high-speed LCoS spatial light modulators open a new door for holographic displays and focal surface displays. Finally, the ultrathin planar diffractive LC optical elements, such as geometric phase LC grating and lens, have found useful applications in AR and VR for enhancing resolution, widening field-of-view, suppressing chromatic aberrations, creating multiplanes to overcome the vergence-accommodation conflict, and dynamic pupil steering to achieve gaze-matched Maxwellian displays, just to name a few. The operation principles, potential applications, and future challenges of these advanced LC devices will be discussed.
The complex future power plants require digital twin (DT) architecture to achieve high reliability, availability and maintainability at lower cost. The available research on DT for power plants is limited and lacks details on DT comprehensiveness and robustness. The main focus of the present study is to propose a comprehensive and robust DT architecture for power plants that can also be used for other similar complex capital-intensive large engineering systems. First, overviews are conducted for DT key research and development for power plants and related energy savings applications to provide current status, guidelines and research gaps. Then, the requirements and rules for the power plant DT are established and the major DT components are determined. These components include the physics-based formulations; the statistical analysis of data from the sensor network; the real-time data; the pre-performed localized in-depth simulations to predict activities of the corresponding physical twin; and the system Genome with a digital thread that connects all these components together. Recommendations and future directions are made for the power plant DT development including the need for real data and physical description of the overall system focusing on each component individually and on the overall connections. Data-driven algorithms with capabilities to predict the system’s dynamic behavior still need to be developed. The data-driven approach alone is not sufficient and a low-order physics based model should operate in tandem with the updated latest system parameters to allow interpretation and enhancing the results from the data-driven process. Discrepancies between the dynamic system models (DSM) and anomaly detection and deep learning (ADL) require in-depth localized off-line simulations. Furthermore, this paper demonstrates the advantages of the developed ADL algorithm approach and DSM prediction of the DT using vector autoregressive model for anomaly detection in utility gas turbines with data from an operational power plant.
Nano-displacement sensing based on an extrinsic hybrid fiber Fabry-Perot interferometer is proposed and demonstrated. The lead-in fiber tip of such an interferometer consists of a strongly-coupled multicore fiber section fusion spliced to a single-mode fiber. The referred lead-in fiber tip is placed in front of a microscope slide, whose rear surface is coated with a high reflecting layer. The gap between the end-face of the fiber tip and the layer is composed of an air cavity in series with a glass one. Light exiting from the lead-in fiber tip is partially reflected at the fiber-air and air-glass interfaces and the reflecting layer generating three beams that are recoupled into the multicore fiber and combined with supermode interference. By making the optical path length of the air cavity slightly different from the glass one, it is possible to generate an envelope in the interference spectra with a larger period. Thus, by tracking the shift of such an envelope, displacements of 0.47 nm can be resolved. The nano-displacement sensing approach reported here is easy to implement; moreover, the sensitivity, resolution, and dynamic range can be reconfigured by an appropriate selection of the glass cavity.
Introduction Elderly undertriage rates are estimated up to 55% in the United States. This study examined risk factors for undertriage among hospitalized trauma patients in a state with high volumes of geriatric trauma patients. Materials and methods This is a population–based retrospective cohort study of 62,557 patients admitted to Florida hospitals between 2016 and 2018 from the Agency for Healthcare Administration database. Severely injured trauma patients were defined by American College of Surgeons definitions and an International Classification of Disease Injury Severity Score <0.85. Undertriage was defined as definitive care of these severely injured patients at any Florida hospital other than a state-designated trauma center (TC). Univariate analyses were used to identify risk factors associated with inpatient mortality and undertriage. Multiple variable regression was used to estimate risk-adjusted odds of mortality after admission to either a designated or nondesignated TC. Results Undertriaged patients were more likely to have isolated traumatic brain injuries, lower International Classification of Disease Injury Severity Scores, multiple comorbidities, and older age. Trauma patients aged 65 and older were more than twice as likely to be undertriaged (34% versus 15.7%, P < 0.0001). Undertriaged patients of all ages were also more likely to suffer from pneumonia, urinary tract infection, arrhythmias, and sepsis. After risk adjustment, severely injured trauma patients admitted to non-TC were also more likely to be at risk for mortality (adjusted odds ratio, 1.27; 95% confidence interval, 1.17-1.38). Conclusions Age and multiple comorbidities are significant predictors of mortality among undertriage of trauma patients. As a result, trauma triage guidelines should account for high-risk geriatric trauma patients who would benefit from definitive treatment at designated TCs.
Acculturative stress is unique among immigrants and refers to the stress associated with maintaining cultural values and traditions in the host country. Immigrant parents confront psychosocial variables such as acculturative stress, anxiety, and depression that might result in intergenerational negative consequences on their infants. Measurement of hair cortisol concentration (HCC), an outcome of neuroendocrine dysregulation, is one relatively noninvasive approach to gauge stress in infants. No published studies have evaluated associations among parents’ psychosocial variables and infants’ HCC among immigrant families. Therefore, the purpose of this study was to: (1) examine the relationship between maternal and paternal psychosocial stress variables; and (2) examine the association between psychosocial variables of both parents (acculturative stress, anxiety, and depression) and infants’ HCC among immigrant Arab American families. A sample of 31 immigrant Arab American triads (mother–father–infant) was recruited. During one home visit, each parent completed the study questionnaires separately when the baby was 6–24 months old and a hair sample was collected from the infant for HCC. Parents reported significant symptoms of anxiety (33% mothers; 45% fathers) and depression (33% mothers; 35.5% fathers). Paternal acculturative stress, anxiety, and depressive symptoms were significantly correlated to infants’ HCC. Acculturative stress, anxiety, and depressive symptoms were significantly correlated between mother–father dyads. Future research should continue to focus on immigrant families and include both parents to better understand and improve infant health.
Aim This study explored relationships between enteral feeding and tracheal pepsin A. Background Mechanically ventilated (MV) patients receiving enteral feeding are at risk for microaspiration. Tracheal pepsin A, an enzyme specific to gastric cells, was a proxy for microaspiration of gastric secretions. Methods Secondary analysis of RCT data from critically ill, MV adults was conducted. Microaspiration prevention included elevated head of bed, endotracheal tube cuff pressure management, and regular oral care. Tracheal secretions for pepsin A were collected every 12 h. Microaspiration was defined as pepsin A ≥ 6.25 ng/mL. Positive pepsin A in >30 % of individual tracheal samples was defined as abundant microaspiration (frequent aspirator). Chi-squared, Fisher's Exact test, and generalized linear model (GLM) were used. Results Tracheal pepsin A was present in 111/283 (39 %) mechanically ventilated patients and 48 (17 %) had abundant microaspiration. Enteral feeding was associated with tracheal pepsin A, which occurred within 24 h of enteral feeding. Of the patients who aspirated, the majority received some enteral feeding 96/111 (86 %), compared to only 15/111 (14 %) who received no feeding. A greater number of positive pepsin A events occurred with post-pyloric feeding tube location (55.6 %) vs. gastric (48.6 %), although significant only at the event-level. Frequent aspirators (abundant pepsin A) had higher pepsin A levels compared to infrequent aspirators. Conclusions Our findings confirmed the stomach as the microaspiration source. Contrary to other studies, distal feeding tube location did not mitigate microaspiration. Timing for first positive pepsin A should be studied for possible association with enteral feeding intolerance.
We study the economic analysis of a single server Markovian queueing system with positive and negative customers and multiple working vacations. Both positive and negative customers arrive in the system according to a Poisson process. Upon arrival, positive customers acquire some system information and decide whether to join or to balk the system based on the acquired information and a linear cost-reward structure. Negative customers on arrival break the server and kill the positive customer in service. The server is immediately sent for repair, and no customers are allowed during a repair. The server takes multiple working vacations after serving all the positive waiting customers. We obtain the equilibrium strategies and social benefit of positive customers under four different information situations. Numerical experiments are presented to show the effects of model parameters and information levels on the equilibrium joining behavior of positive customers.
Objectives Longitudinal data offer many advantages to criminological research yet suffer from attrition, namely in the form of sample selection bias. Attrition may undermine reaching valid inferences by introducing systematic differences between the retained and attrited samples. We explored (1) if attrition biases correlates of recidivism, (2) the magnitude of bias, and (3) how well methods of correction account for such bias.Methods Using data from the LoneStar Project, a representative longitudinal sample of reentering men in Texas, we examined correlates of recidivism using official measures of recidivism under four sample conditions: full sample, listwise deleted sample, multiply imputed sample, and two-stage corrected sample. We compare and contrast the results regressing rearrest on a range of covariates derived from a pre-release baseline interview across the four sample conditions.ResultsAttrition bias was present in 44% of variables and null hypothesis significance tests differed for the correlates of recidivism in the full and retained samples. The bias was substantial, altering effect sizes for recidivism by a factor as large as 1.6. Neither the Heckman correction nor multiple imputation adequately corrected for bias. Instead, results from listwise deletion most closely mirrored the results of the full sample with 89% concordance.Conclusions It is vital that researchers examine attrition-based selection bias and recognize the implications it has on their data when generating evidence of theoretical, policy, or practical significance. We outline best practices for examining the magnitude of attrition and analyzing longitudinal data affected by sample selection.
The Dufour and Soret impacts on magnetohydrodynamic Carreau nanoliquid past a nonlinearly stretching sheet are investigated. Variations in viscosity, heat conductivity, and convective boundary conditions are considered. Suitable similarity conversions are utilized to design the governing equations nondimensional. The Optimal Homotopy Analysis Method is employed to resolve the dimensionless equations. Graphs and tables are utilized to illustrate the impacts of the relevant factors over velocity, temperature, concentration, and streamlines. For the variations of different parameters, numerical values for Nusselt number, Sherwood number, and skin friction are provided in a table. The observed results are in good agreement with the previous literature findings. Furthermore, the current research shows that when the Dufour number increases, the temperature distributions get narrower. However, with increasing Soret number, the concentration distribution has the opposite effect. One of the important outcomes of the current study is that by increasing the Weissenberg number for shear‐thinning fluids, one can improve the velocity field.
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12,007 members
Frederick Carrick
  • College of Medicine
Jorge Ridderstaat
  • Rosen College of Hospitality Management
Su-I Hou
  • Department of Health Management and Informatics
Lee Chow
  • Department of Physics
Abdelkader Kara
  • Department of Physics
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