University of Houston
  • Houston, TX, United States
Recent publications
Background and objective The Coronavirus Aid, Relief, and Economic Security Act led to the rapid implementation of telemedicine across health care office settings. Whether this transition to telemedicine has any impact on missed appointments is yet to be determined. This study examined the relationship between telemedicine usage and missed appointments during the COVID-19 pandemic. Method This retrospective study used appointment-level data from 55 Federally Qualified Health Centre clinics in Texas between March and November 2020. To account for the nested data structure of repeated appointments within each patient, a mixed-effects multivariable logistic regression model was used to examine associations between telemedicine use and missed appointments, adjusting for patient sociodemographic characteristics, geographic classification, past medical history, and clinic characteristics. The independent variable was having a telemedicine appointment, defined as an audiovisual consultation started and finalized via a telemedicine platform. The outcome of interest was having a missed appointment (yes/no) after a scheduled and confirmed medical appointment. Results from this initial model were stratified by appointment type (in-person vs. telemedicine). Results The analytic sample included 278,171 appointments for 85,413 unique patients. The overall missed appointment rate was 18%, and 25% of all appointments were telemedicine appointments. Compared to in-person visits, telemedicine visits were less likely to result in a missed appointment (OR = 0.87, p < .001). Compared to Whites, Asians were less likely to have a missed appointment (OR = 0.82, p < .001) while African Americans, Hispanics, and American Indians were all significantly more likely to have missed appointments (OR = 1.61, p < .001; OR = 1.19, p = .01; OR = 1.22, p < .01, respectively). Those accessing mental health services (OR = 1.57 for in-person and 0.78 for telemedicine) and living in metropolitan areas (OR = 1.15 for in-person and 0.82 for telemedicine) were more likely to miss in-person appointments but less likely to miss telemedicine appointments. Patients with frequent medical visits or those living with chronic diseases were more likely to miss in-person appointments but less likely to miss telemedicine appointments. Conclusions Telemedicine is strongly associated with fewer missed appointments. Although our findings suggest a residual lag in minority populations, specific patient populations, including those with frequent prior visits or chronic conditions, those seeking mental health services, and those living in metropolitan areas were less likely to miss telemedicine appointments than in-person visits. These findings highlight how telemedicine can enable effective and accessible care by reducing missed healthcare appointments. • KEY MESSAGES • Telemedicine was associated with 13% lower odds of missed appointments. • Patients with frequent medical visits or those living with chronic diseases were less likely to miss telemedicine appointments but more likely to miss in-person appointments. • Patients seeking mental health services were less likely to miss telemedicine appointments but more likely to miss in-person appointments. • Similarly, those living in metropolitan areas were less likely to miss telemedicine appointments but more likely to miss in-person appointments.
The voltage-gated sodium channel isoform NaV1.7 is a critical player in the transmission of nociceptive information. This channel has been heavily implicated in human genetic pain disorders and is a validated pain target. However, targeting this channel directly has failed, and an indirect approach – disruption of interactions with accessory protein partners – has emerged as a viable alternative strategy. We recently reported that a small-molecule inhibitor of CRMP2 SUMOylation, compound 194, selectively reduces NaV1.7 currents in DRG neurons across species from mouse to human. This compound also reversed mechanical allodynia in a spared nerve injury and chemotherapy-induced model of neuropathic pain. Here, we show that oral administration of 194 reverses mechanical allodynia in a chronic constriction injury (CCI) model of neuropathic pain. Furthermore, we show that orally administered 194 reverses the increased latency to cross an aversive barrier in a mechanical conflict-avoidance task following CCI. These two findings, in the context of our previous report, support the conclusion that 194 is a robust inhibitor of NaV1.7 function with the ultimate effect of profoundly ameliorating mechanical allodynia associated with nerve injury. The fact that this was observed using both traditional, evoked measures of pain behavior as well as the more recently developed operator-independent mechanical conflict-avoidance assay increases confidence in the efficacy of 194-induced anti-nociception.
Flexible pressure sensors with high sensitivity are desired in the fields of electronic skins, human–machine interfaces, and health monitoring. Employing ionic soft materials with microstructured architectures in the functional layer is an effective way that can enhance the amplitude of capacitance signal due to generated electron double layer and thus improve the sensitivity of capacitive-type pressure sensors. However, the requirement of specific apparatus and the complex fabrication process to build such microstructures lead to high cost and low productivity. Here, we report a simple strategy that uses open-cell polyurethane foams with high porosity as a continuous three-dimensional network skeleton to load with ionic liquid in a one-step soak process, serving as the ionic layer in iontronic pressure sensors. The high porosity (95.4%) of PU-IL composite foam shows a pretty low Young’s modulus of 3.4 kPa and good compressibility. A superhigh maximum sensitivity of 9,280 kPa ⁻¹ in the pressure regime and a high pressure resolution of 0.125% are observed in this foam-based pressure sensor. The device also exhibits remarkable mechanical stability over 5,000 compression-release or bending-release cycles. Such high porosity of composite structure provides a simple, cost-effective and scalable way to fabricate super sensitive pressure sensor, which has prominent capability in applications of water wave detection, underwater vibration sensing, and mechanical fault monitoring.
Background Radiology serves in the diagnosis and management of many diseases. Despite its rising importance and use, radiology is not a core component of a lot of medical school curricula. This survey aims to clarify current gaps in the radiological education in Egyptian medical schools. In February–May 2021, 5318 students enrolled in Egyptian medical schools were recruited and given a 20-multiple-choice-question survey assessing their radiology knowledge, radiograph interpretation, and encountered imaging experiences. We measured the objective parameters as a percentage. We conducted descriptive analysis and used Likert scales where values were represented as numerical values. Percentages were graphed afterwards. Results A total of 5318 medical students in Egypt answered our survey. Gender distribution was 45% males and 54% females. The results represented all 7 class years of medical school (six academic years and a final training year). In assessing students’ knowledge of radiology, most students (75%) reported that they received ‘too little’ education, while 20% stated the amount was ‘just right’ and only 4% reported it was ‘too much.’ Sixty-two percent of students stated they were taught radiology through medical imaging lectures. Participants’ future career plans were almost equally distributed. Near half of participants (43%) have not heard about the American College of Radiology Appropriateness Criteria (ACR-AR), while 39% have heard about it but are not familiar with. Conclusions Radiology is a novel underestimated field. Therefore, medical students need more imaging exposure. To accomplish this, attention and efforts should be directed toward undergraduate radiology education to dissolve the gap between radiology and other specialties during clinical practice. A survey answered by medical students can bridge between presence of any current defect in undergraduate radiology teaching and future solutions for this topic.
Abstract Background There is a worldwide deficit in teaching and training in the field of radiology for undergraduate medical students. This educational gap is prominent in many medical schools as most radiology curricula are a part of other specialty trainings, usually provided by non-radiologists. After COVID-19 pandemic, there was an increased trend in online education. However, questions have been raised about the efficacy and acceptance of online education. We developed a course on the principles of radiology and medical imaging basics to target Egyptian medical students. We then assessed the impact of these educational videos through several online surveys. Our "The Principles of Radiology Online Course" was delivered to students at various Egyptian medical schools; it was a prerecorded series composed of nine sessions, and each session followed the sequence of a pre-test, video, and post-test. There was a final survey to assess the overall feedback. Finally, we analyzed the results to give insight onto how teaching radiology through online lectures can help build better physicians. Results Among various medical schools around Egypt, 1396 Egyptian medical students joined this cohort. Cohort population percentage was 56% female and 44% male. Ninety-eight percent of the students agreed that this program increased their understanding of radiology. Eighty-four percent of the students found the platform friendly and easy to use. Seventy-nine percent found these webinars were more convenient compared to in-person education. Statistical significance (p-value
Bacterial persister cells are temporarily tolerant to bactericidal antibiotics but are not necessarily dormant and may exhibit physiological activities leading to cell damage. Based on the link between fluoroquinolone-mediated SOS responses and persister cell recovery, we screened chemicals that target fluoroquinolone persisters. Metabolic inhibitors (e.g., phenothiazines) combined with ofloxacin (OFX) perturbed persister levels in metabolically active cell populations. When metabolically stimulated, intrinsically tolerant stationary phase cells also became OFX-sensitive in the presence of phenothiazines. The effects of phenothiazines on cell metabolism and physiology are highly pleiotropic: at sublethal concentrations, phenothiazines reduce cellular metabolic, transcriptional, and translational activities; impair cell repair and recovery mechanisms; transiently perturb membrane integrity; and disrupt proton motive force by dissipating the proton concentration gradient across the cell membrane. Screening a subset of mutant strains lacking membrane-bound proteins revealed the pleiotropic effects of phenothiazines potentially rely on their ability to inhibit a wide range of critical metabolic proteins. Altogether, our study further highlights the complex roles of metabolism in persister cell formation, survival and recovery, and suggests metabolic inhibitors such as phenothiazines can be selectively detrimental to persister cells.
Background Hay fever (allergic rhinitis) is a common condition that causes unpleasant respiratory symptoms. The objective of this cross-sectional study is to examine the trends of hay fever self-reported diagnosis among adults and children in the United States from 2013 to 2018 and its associations with sociodemographic characteristics. Survey data from the National Health Interview (NHIS) were used to identify children and adults with hay fever. Chi-square tests were used to evaluate the group differences by sociodemographic characteristics within each year examined. Trends in self-reported hay fever as well as trends for each sociodemographic characteristic over the study period were charted. Results All sociodemographic characteristics examined in both adults and children showed statistically significant group differences. Females were the highest risk sex group among adults while males were the highest risk sex group among children. Hay fever was more likely to be found among those with two or more races, non-Hispanics, those with higher education level and wealth, and residents from the western United States. Conclusions The findings of this study can help identify subpopulations at higher risk of hay fever, which can aid in developing targeted interventions to help individuals experiencing hay fever alleviate their symptoms and improve their quality of life.
Background Clostridioides difficile infection (CDI) is associated with high recurrence rates impacting health-related quality of life (HrQOL). However, patient-reported data are lacking particularly in the outpatient setting. We assessed changes in HrQOL over time in patients treated with bezlotoxumab at US infusion centers and determined clinical factors associated with HrQOL changes. Methods The HrQOL survey was conducted in adult patients with CDI, who received bezlotoxumab in 25 US outpatient infusion centers. The survey was adapted from the Cdiff32 instrument to assess anxiety-related changes to HrQOL and completed on the day of infusion (baseline) and at 90 days post bezlotoxumab (follow-up). Demographics, disease history, CDI risk factors, and recurrence of CDI (rCDI) at 90-day follow-up were collected. Changes in HrQOL scores were calculated and outcomes assessed using a multivariable linear regression model with P < 0.05 defined as statistically significant. Results A total of 144 patients (mean age: 68 ± 15 years, 63% female, median Charlson index: 4, 15.9% rCDI) were included. The overall mean baseline and follow-up HrQOL scores were 26.4 ± 11.5 and 56.4 ± 25.0, respectively. At follow-up, this score was significantly higher for patients who had primary CDI (34.5 ± 21.7) compared to those with multiple rCDI (24.7 ± 21.0; P = 0.039). The mean HrQOL change at follow-up was significantly higher for patients without rCDI (34.1 ± 28.8 increase) compared to patients with rCDI (6.7 ± 19.5 increase; P < 0.001), indicating improvement in anxiety. Conclusions Using the Cdiff32 instrument, we demonstrated that HrQOL worsened significantly in patients with further rCDI. These findings support the use of Cdiff32 in assessing CDI-related humanistic outcomes.
Background Depression is one of the most common psychiatric diseases. The monoamine transmitter theory suggests that neurotransmitters are involved in the mechanism of depression; however, the regulation on serotonin production is still unclear. We previously showed that Ahi1 knockout (KO) mice exhibited depression-like behavior accompanied by a significant decrease in brain serotonin. Methods In the present study, western blot, gene knockdown, immunofluorescence, dual-luciferase reporter assay, and rescue assay were used to detect changes in the Ahi1/GR/ERβ/TPH2 pathway in the brains of male stressed mice and male Ahi1 KO mice to explain the pathogenesis of depression-like behaviors. In addition, E2 levels in the blood and brain of male and female mice were measured to investigate the effect on the ERβ/TPH2 pathway and to reveal the mechanisms for the phenomenon of gender differences in depression-like behaviors. Results We found that the serotonin-producing pathway-the ERβ/TPH2 pathway was inhibited in male stressed mice and male Ahi1 KO mice. We further demonstrated that glucocorticoid receptor (GR) as a transcription factor bound to the promoter of ERβ that contains glucocorticoid response elements and inhibited the transcription of ERβ. Our recent study had indicated that Ahi1 regulates the nuclear translocation of GR upon stress, thus proposing the Ahi1/GR/ERβ/TPH2 pathway for serotonin production. Interestingly, female Ahi1 KO mice did not exhibit depressive behaviors, indicating sexual differences in depressive behaviors compared with male mice. Furthermore, we found that serum 17β-estradiol (E2) level was not changed in male and female mice; however, brain E2 level significantly decreased in male but not female Ahi1 KO mice. Further, ERβ agonist LY-500307 increased TPH2 expression and 5-HT production. Therefore, both Ahi1 and E2 regulate the ERβ/TPH2 pathway and involve sexual differences in brain serotonin production and depressive behaviors. Conclusions In conclusion, although it is unclear how Ahi1 controls E2 secretion in the brain, our findings demonstrate that Ahi1 regulates serotonin production by the GR/ERβ/TPH2 pathway in the brain and possibly involves the regulation on sex differences in depressive behaviors.
Firefighters are at increased risk for posttraumatic stress disorder (PTSD) symptoms and sleep disturbances due to occupational trauma exposure as well as the nature of their job (e.g., shift work, workplace stress). PTSD symptoms co-occur with sleep disturbances, including poor sleep quality, short sleep duration, and low sleep efficiency. No published studies have examined subgroups of firefighters based on PTSD symptoms and sleep disturbances. Thus, we used latent profile analysis to identify the best-fitting class solution to categorize firefighters based on endorsed PTSD symptoms and sleep disturbances and examined relations between the optimal class solution and health covariates (i.e., anger reactions, depression symptoms, emotion regulation difficulties, number of traumatic event types). The sample included 815 trauma-exposed firefighters (Mage = 38.63; 93.20% male). Results indicated three latent subgroups: High PTSD-Sleep Disturbances, Moderate PTSD-Sleep Disturbances, and Low PTSD-Sleep Disturbances. Multinomial logistic regression indicated that endorsing greater anger reactions, depression symptoms, and emotion regulation difficulties increased the chances of being in the more severe classes. Endorsing greater number of traumatic event types increased the chances of being in the Moderate vs. Low PTSD-Sleep Disturbances Classes. Findings improve our understanding of subgroups of firefighters based on PTSD and sleep disturbances and underscore the importance of addressing depression symptoms, anger management, and emotion regulation skills for firefighters reporting more severe PTSD symptoms and sleep disturbances.
Membrane processes such as microfiltration (MF) and ultrafiltration (UF) are known to be the best advanced technologies for water reuse application. Numerous research efforts have been conducted in areas of modifying commercial MF/UF products or synthesizing novel materials promising enhanced oil-water separation performances. Block copolymer (BCP)-based membranes have recently gained increased popularity due to their improved water permeabilities. This study applies a comprehensive testing protocol for performance evaluation of two emerging poly (styrene-block-methyl methacrylate) BCP membranes developed by the project team. Tests mimicking industrial conditions were conducted by using a representative synthetic produced water and operating repeat tests. Both BCP membranes (referred to as A & B) were found to possess high permeabilities of 5538 and 12,424 LMH/bar, respectively. Membrane B showed higher organic rejection at 79% against 74% rejection obtained for membrane A. The novel membranes were then compared to a relevant commercial product. Lower permeability at 3831 LMH/bar and slightly higher rejection performance (within ~ 10%) were obtained for the commercial membrane as compared to the BCP membranes. Test results obtained for those novel membranes being still in the development stage will be utilized in future studies investigating further optimization of the membrane structure and oil-water separation performance. Graphical Abstract
Photocatalysts based on heterostructure 2D materials show promising properties for the construction of optoelectronic devices for selective reduction of CO2 to methanol. In this sense, a fast and simple method to produce 2D hexagonal hybrid BN nanosheets (h-BNNs) doped with graphene heterostructure by van der Waals interactions was developed. The method used plasma created by a Tesla coil. The Gr/h-BNNs hybrid material obtained presented a stacking structure containing h-BNNs and graphene layers. The structure included doping of carbon atoms along the h-BN edge structures. The doping of the h-BN nanostructure with graphene sheets, conferred adaptable optical properties to the semiconductor, resulting in band gap energy values favorable to photocatalysis. The reaction promoted selective reduction of CO2 to methanol, and synthesis of other products, such as formaldehyde and formic acid, due to multielectronic transfer processes.
One of the pandemics that have caused many deaths is the Coronavirus disease 2019 (COVID-19). It first appeared in late 2019, and many deaths are increasing day by day until now. Therefore, the early diagnosis of COVID-19 has become a salient issue. Additionally, the current diagnosis methods have several demerits, and a new investigation is required to enhance the diagnosis performance. In this paper, a set of phases are performed, such as collecting data, filtering and augmenting images, extracting features, and classifying ECG images. The data were obtained from two publicly available ECG image datasets, and one of them contained COVID ECG reports. A set of preprocessing methods are applied to the ECG images, and data augmentation is performed to balance the ECG images based on the classes. A deep learning approach based on a convolutional neural network (CNN) is performed for feature extraction. Four different pre-trained models are applied, such as Vgg16, Vgg19, ResNet-101, and Xception. Moreover, an ensemble of Xception and the temporary convolutional network (TCN), which is named ECGConvnet, is proposed. Finally, the results obtained from the former models are fed to four main classifiers. These classifiers are softmax, random forest (RF), multilayer perception (MLP), and support vector machine (SVM). The former classifiers are used to evaluate the diagnosis ability of the proposed methods. The classification scenario is based on fivefold cross-validation. Seven experiments are presented to evaluate the performance of the ECGConvnet. Three of them are multi-class, and the remaining are binary class diagnosing. Six out of seven experiments diagnose COVID-19 patients. The aforementioned experimental results indicated that ECGConvnet has the highest performance over other pre-trained models, and the SVM classifier showed higher accuracy in comparison with the other classifiers. The resulting accuracies from ECGConvnet based on SVM are (99.74%, 98.6%, 99.1% on the multi-class diagnosis tasks) and (99.8% on one of the binary-class diagnoses, while the remaining achieved 100%). It is possible to develop an automatic diagnosis system for COVID based on deep learning using ECG data.
The on-demand economy (or gig economy) is touted “the future of work” characterized by heterogeneous laborers “on the cloud.” Turnover intention (TI) models have been developed to describe employees in the conventional settings and thus may be insufficient for understanding on-demand workers. This study aims to fill this important gap and beyond. We derive a model of discontinuance intention (DI) where job satisfaction is a prominent mediator of the effect of reward fairness. We further theorize and test how and why on-demand workers’ dual commitments toward their online communities arising from workers’ informal social interactions (ISI) may create boundary conditions for the mediating role of job satisfaction. Data were collected from a large sample of 1493 on-demand workers over a four-year span and facilitated the analysis of a moderated mediation model. Results indicate that job satisfaction largely mediates a negative relationship between workers’ perceptions that their rewards are just (i.e., fairness of rewards) and their intention to discontinue work for the on-demand firm. Moreover, workers’ dual commitments toward their online peer communities (OPCs) disrupted this mediating effect. More interestingly, the dual commitments did not moderate the mediation path equally. Overall, our theoretical model and empirical results delineate how discontinuance intention can be affected by a parsimonious set of antecedents in the context of the on-demand economy.
The family of Abelson interactor (Abi) proteins is a component of WAVE regulatory complex (WRC) and a downstream target of Abelson (Abl) tyrosine kinase. The fact that Abi proteins also interact with diverse membrane proteins and intracellular signaling molecules places these proteins at a central position in the network that controls cytoskeletal functions and cancer cell metastasis. Here, we identified a motif in Abi proteins that conforms to consensus sequences found in a cohort of receptor and non-receptor tyrosine kinases that bind to Cbl-tyrosine kinase binding domain. The phosphorylation of tyrosine 213 in this motif is essential for Abi degradation. Double knockout of c-Cbl and Cbl B in Bcr-Abl-transformed leukemic cells abolishes Abi1, Abi2, and WAVE2 degradation. Moreover, knockout of Abi1 reduces Src family kinase Lyn activation in Bcr-Abl-positive leukemic cells and promotes EGF-induced EGF receptor downregulation in breast cancer cells. Importantly, Abi1 depletion impeded breast cancer cell invasion in vitro and metastasis in mouse xenografts. Together, these studies uncover a novel mechanism by which the WRC and receptor/non-receptor tyrosine kinases are regulated and identify Abi1 as a potential therapeutic target for metastatic breast cancer.
Environmental policies are often chosen according to physical characteristics that disregard the complex interactions between decision-makers, society, and nature. Environmental policy resistance has been identified as stemming from such complexities, yet we lack an understanding of how social and physical factors interrelate to inform policy design. The identification of synergies and trade-offs among various management strategies is necessary to generate optimal results from limited institutional resources. Participatory modeling has been used within the environmental community to aid decision-making by bringing together diverse stakeholders and defining their shared understanding of complex systems, which are commonly depicted by causal feedbacks. While such approaches have increased awareness of system complexity, causal diagrams often result in numerous feedback loops that are difficult to disentangle without further, data-intensive modeling. When investigating the complexities of human decision-making, we often lack robust empirical datasets to quantify human behavior and environmental feedbacks. Fuzzy logic may be used to convert qualitative relationships into semi-quantitative representations for numerical simulation. However, sole reliance upon computer-simulated outputs may obscure our understanding of the underlying system dynamics. Therefore, the aim of this study is to present and demonstrate a mixed-methods approach for better understanding: 1) how the system will respond to unique management strategies, in terms of policy synergies and conflicts, and 2) why the system behaves as such, according to causal feedbacks embedded within the system dynamics. This framework is demonstrated through a case study of nature-based solutions and policymaking in Houston, Texas, USA.
A variable buoyancy system (VBS) operated by a reversible fuel cell (RFC) with feedback depth control is developed. The system varies its buoyancy by inflating or deflating a bladder via gases produced by electrolysis or consumed through fuel cells. The system has advantages in the perspective of energy efficiency since some of the energy used for the electrolysis process is recaptured by the fuel cell. Furthermore, it is noiseless and compact, facilitating smooth integration with other underwater robots requiring buoyancy control. A PDA (Proportional-Derivative-Acceleration) feedback controller is designed to regulate the electrochemical process to position and stabilize the device at a certain depth. The model describing the VBS’s motion dynamics with bounded gas rates is used to evaluate the range of motion before instability. Then, a jerk-constrained time-optimal trajectory planner is employed to generate a suboptimal trajectory to move the VBS between two known depths. Finally, the effectiveness of the controller is confirmed with experiments. The real-time experiment shows that the controller can track both sinusoidal reference and the suboptimal trajectory planned between two depths. The device can achieve fine depth control with a depth resolution of 0.06 m, which makes its application promising in bio-inspired underwater robots.
Prior research showed that corporate divestitures could help firms restore their strategic (versus financial) controls and long-term focus. This suggests that divestiture activities may have implications for firms’ commitment to corporate social responsibility (CSR) following divestitures. Drawing from the attention-based view of the firm, we examine this underexplored yet important research question. We propose that firms’ divestiture scale is positively associated with their commitment to post-divestiture CSR. However, this relationship is weakened among firms facing pre-restructuring financial decline and selling more related businesses, but strengthened among divesting firms with a new CEO. Using a longitudinal dataset of U.S. firms, we found support for most of our hypotheses. These findings suggest that corporate divestitures may offer a meaningful path to stakeholder value creation through better CSR performance.
Dielectric elastomers (DEs) deform and change shape when an electric field is applied across them. They are flexible, resilient, lightweight, and durable and as such are suitable for use as soft actuators. In this paper a physics-based and control-oriented model is developed for a DE tubular actuator using a physics-lumped parameter modeling approach. The model derives from the nonlinear partial differential equations (PDE) which govern the nonlinear elasticity of the DE actuator and the ordinary differential equation (ODE) that governs the electrical dynamics of the DE actuator. With the boundary conditions for the tubular actuator, the nonlinear PDEs are numerically solved and a quasi-static nonlinear model is obtained and validated by experiments. The full nonlinear model is then linearized around an operating point with an analytically derived Hessian matrix. The analytically linearized model is validated by experiments. Proportional–Integral–Derivative (PID) and H∞\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$H_{\infty }$$\end{document} control are developed and implemented to perform position reference tracking of the DEA and the controllers’ performances are evaluated according to control energy and tracking error.
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9,905 members
Sujash Chatterjee
  • Biology and Biochemistry/ UH Sequencing Center
Amit K Gupta
  • Department of Pharmacological and Pharmaceutical Sciences
Melisa Martinez-Paniagua
  • Department of Chemical & Biomolecular Engineering
Ali Rad
  • William A. Brookshire Department of Chemical and Biomolecular Engineering
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RENU KHATOR
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