Richardson, TX, United States
Richardson, TX, United States

The University of Texas at Dallas is a public research university in the University of Texas System. The main campus is in Richardson, Texas, Telecom Corridor, 18 miles north of downtown Dallas. The institution, established in 1961 as the Graduate Research Center of the Southwest and later renamed the Southwest Center for Advanced Studies , began as a research arm of Texas Instruments. In 1969 the founders bequeathed SCAS to the state of Texas and Governor Preston Smith signed the bill officially creating the University of Texas at Dallas.UTD offers over 133 academic programs across its seven schools and hosts more than 50 research centers and institutes. With a number of interdisciplinary degree programs, its curriculum is designed to allow study that crosses traditional disciplinary lines and to enable students to participate in collaborative research labs. Entering freshmen average math and critical reading SAT scores are among the highest of the public universities in Texas and 1261 for 2013. The Carnegie Foundation classifies UT Dallas as a "comprehensive doctoral research university" and a "high research activity institution". Research projects include the areas of space science, bioengineering, cybersecurity, nanotechnology, and behavioral and brain science.The school has a Division III athletics program in the American Southwest Conference and fields 13 intercollegiate teams. The university recruits worldwide for its chess team and has a nationally recognized debate team. For the spring 2013 commencement the university granted 1,557 bachelor's degrees, 1,380 master's degrees and 87 PhDs for a total of 3,024 degrees. Wikipedia.

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Vidyasagar M.,University of Texas at Dallas
Annual Review of Pharmacology and Toxicology | Year: 2015

This article reviews several techniques from machine learning that can be used to study the problem of identifying a small number of features, from among tens of thousands of measured features, that can accurately predict a drug response. Prediction problems are divided into two categories: sparse classification and sparse regression. In classification, the clinical parameter to be predicted is binary, whereas in regression, the parameter is a real number. Well-known methods for both classes of problems are briefly discussed. These include the SVM (support vector machine) for classification and various algorithms such as ridge regression, LASSO (least absolute shrinkage and selection operator), and EN (elastic net) for regression. In addition, several well-established methods that do not directly fall into machine learning theory are also reviewed, including neural networks, PAM (pattern analysis for microarrays), SAM (significance analysis for microarrays), GSEA (gene set enrichment analysis), and k-means clustering. Several references indicative of the application of these methods to cancer biology are discussed. ©2015 by Annual Reviews. All rights reserved.

Grundy S.M.,University of Texas at Dallas
Journal of the American College of Cardiology | Year: 2012

Pre-diabetes represents an elevation of plasma glucose above the normal range but below that of clinical diabetes. Pre-diabetes can be identified as either impaired fasting glucose (IFG) or impaired glucose tolerance (IGT). The latter is detected by oral glucose tolerance testing. Both IFG and IGT are risk factors for type 2 diabetes, and risk is even greater when IFG and IGT occur together. Pre-diabetes commonly associates with the metabolic syndrome. Both in turn are closely associated with obesity. The mechanisms whereby obesity predisposes to pre-diabetes and metabolic syndrome are incompletely understood but likely have a common metabolic soil. Insulin resistance is a common factor; systemic inflammation engendered by obesity may be another. Pre-diabetes has only a minor impact on microvascular disease; glucose-lowering drugs can delay conversion to diabetes, but whether in the long run the drug approach will delay development of microvascular disease is in dispute. To date, the drug approach to prevention of microvascular disease starting with pre-diabetes has not been evaluated. Pre-diabetes carries some predictive power for macrovascular disease, but most of this association appears to be mediated through the metabolic syndrome. The preferred clinical approach to cardiovascular prevention is to treat all the metabolic risk factors. For both pre-diabetes and metabolic syndrome, the desirable approach is lifestyle intervention, especially weight reduction and physical activity. When drug therapy is contemplated and when the metabolic syndrome is present, the primary consideration is prevention of cardiovascular disease. The major targets are elevations of cholesterol and blood pressure. © 2012 American College of Cardiology Foundation.

Agency: NSF | Branch: Standard Grant | Program: | Phase: COGNEURO | Award Amount: 543.56K | Year: 2016

The United States is an aging society. Presently, about 9% of the population is aged 70 years or older. This proportion will have grown to around 15% by 2030, bringing with it a dramatic increase in the economic and social costs of age-related cognitive and physical impairment, and fuelling an urgent need for research in aging. Advancing age is associated with an accelerating trajectory of decline in several important cognitive abilities, including episodic memory, the ability to accurately recollect the details of a recent event. Importantly, age-related decline in memory accuracy is not always accompanied by a decline in memory confidence, the strength of our conviction that a memory is accurate. This increases their risk of basing important choices and decisions on erroneous information. The present research aims to understand why a mismatch between the feeling that a memory is accurate and its actual accuracy is more common in older than in younger people. The findings will shed new light on why older people are prone to make inaccurate, confident memory judgments and will contribute to the development of interventions that ameliorate this tendency. The research will also provide training in the cognitive neuroscience of aging for masters and PhD students, and for postdoctoral trainees. An important additional broader impact will be the contribution of the research to the outreach and education activities of the Center for Vital Longevity at the University of Texas at Dallas. These activities include frequent talks on age-related research by Center members (including trainees) to a wide range of community organizations, public lectures, and a biennial international scientific conference.

The research will use functional magnetic resonance imaging (fMRI) to monitor the brain activity of older (65-75 yrs.) and younger (aged 18-30 yrs.) people. The research is motivated by findings that although accuracy of episodic memory is highly age-sensitive, the subjective experience of remembering is less affected. Thus, older individuals are more likely to report a strong sense of recollection in concert with an inaccurate memory judgment than are young individuals. We will examine two possible accounts of this age-related dissociation between objective and subjective measures of episodic memory. The first account proposes that the dissociation reflects age differences in the precision of recollection. Experiment 1 will assess this account by using multi-voxel pattern analyses to examine whether the fidelity with which information about a study event is reinstated in the cerebral cortex is lower in older people. The second account proposes that older individuals are as capable of recollecting detailed information as young individuals, but are less able to control recollection so as to align its content with the goal of the retrieval attempt.

Agency: NSF | Branch: Standard Grant | Program: | Phase: Big Data Science &Engineering | Award Amount: 519.60K | Year: 2016

Understanding the structure and dynamics of social networks is crucial for detecting any anomalous behavior and for managing its impacts. Most existing approaches view a network as a series of snapshots, where a snapshot represents the state of a network in a given time period. Therefore, different network operations need to be individually performed over each snapshot. In reality, online social networks are continuously evolving and therefore, network operations should be automatically performed as networks evolve and need to be done efficiently and reliably. Viewing the problem from this perspective allows us to create a solution that supports advanced, real-world use cases such as tracking the neighborhood of a given node or tracking how network connections evolve in time to determine effective marketing campaigns. These examples indicate the need for efficient computing techniques for important network statistics as the large networks evolve over time. To address this problem, the researchers in this project complement existing distributed evolving social graph analysis techniques with bootstrap and other statistical re-sampling based approaches. The ultimate goal is to develop novel data-driven tools so that when needed, not only certain estimates of statistical network models could be computed efficiently but their estimation errors are reliably quantified.

This project primarily targets development of new efficient and robust methods for anomaly and outlier detection on large sparse networks. The resulting methodology provides the following functions: 1) a computationally efficient finite sample inference for an extensive range of network topology statistics; 2) a flexible data-driven characterization of network structure and dynamics, and 3) comprehensively quantifying uncertainty in modeling and estimation of large networks, without imposing restrictive conditions on network model specification. The expected advances are both in research methods - new approaches to data-driven nonparametric inference for large sparse networks and in substantial enhancement of knowledge of network dynamics and formation in the era of digital communication. The project can significantly benefit students by providing a broad exposure to interdisciplinary applications of large network and fostering awareness of interdisciplinary relationships -- hence enhancing their capacity for critical thinking and opening up new career paths.

Agency: NSF | Branch: Standard Grant | Program: | Phase: Secure &Trustworthy Cyberspace | Award Amount: 528.22K | Year: 2016

The Intel Software Guard Extensions (SGX) is a new technology introduced to make secure and trustworthy computing in a hostile environment practical. However, SGX is merely just a set of instructions. Its software support that includes the OS support, toolchain and libraries, is currently developed in a closed manner, limiting its impact only within the boundary of big companies such as Intel and Microsoft. Meanwhile, SGX does not automatically secure everything and it still faces various attacks such as controlled-side channel and enclave memory corruption.

This research investigates how to enable application developers to securely use the SGX instructions, with an open source software support including a toolchain, programming abstractions (e.g., library), and operating system support (e.g., kernel modules). In addition, this research systematically explores the systems and software defenses necessary to secure the SGX programs from the enclave itself and defeat the malicious use of SGX from the underlying OS.

Agency: NSF | Branch: Standard Grant | Program: | Phase: DEVELOP& LEARNING SCIENCES/CRI | Award Amount: 515.00K | Year: 2016

In the US, over 31 million children (42%) are from low socioeconomic status (SES) homes. On average these children have significantly smaller vocabularies than their middle SES peers. This vocabulary gap appears early in development, increases during the school years and has life-long academic and economic implications. Although research has identified some possible reasons for lower vocabulary in low SES toddlers, it is not clear how or why the deficit continues to increase during the school years. The present project will study how well-documented SES differences in semantic knowledge, reading abilities and working memory may contribute to word learning deficits at the behavioral and brain levels in school-aged children. The outcomes of this research will help to identify directions for intervention to increase the likelihood of academic success within this at-risk population.

This project will use a relatively new analysis technique, Time Frequency Analysis, to study changes in electrophysiological processes of school-aged children (8-15 years) as they learn new words. These neuronal responses will be studied in relation to childrens word learning abilities, family background (mothers level of education and needs-to-income ratio) and cognitive abilities (reading abilities, vocabulary and working memory). In this way, the proposed work will clarify the mechanisms by which SES influences the behavioral and neural processes contributing to childrens word learning during the school years.

Agency: NSF | Branch: Standard Grant | Program: | Phase: EARS | Award Amount: 596.74K | Year: 2016

This EARS (Enhancing Access to the Radio Spectrum) program was founded in response to the 2010 Presidential Memorandum on Unleashing the Wireless Broadband Revolution mandated by Congress as part of the National Broadband Plan. It was referenced in 2010 State of the Union and later on the Middle Class Tax Relief and Job Creation Act of 2012 (More than 1/3 of the bill deals with radio spectrum), the PCAST 2012 Report [Presidents Council of Advisors on Science and Technology] (which calls for vastly increased use of spectrum sharing) and the 2013 Presidential memo (Expanding Americas Leadership in Wireless Innovation). The aim of this program is to identify bold new concepts with the potential to contribute to significant improvements in the efficiency of radio spectrum utilization, protection of passive sensing services, and in the ability for traditionally underserved Americans to benefit from current and future wireless-enabled goods and services. The impact is large on the economics of the Nation as seen on the last FCC bidding of 65MHz of the spectrum for over $45 billion early in 2015. It will enable access to science, engineering, industry, civilian and military users of the radio frequency (RF) spectrum.

Active wireless systems (which transmit and receive RF signals) such as cellular wireless communications have generated numerous advancements in our society and tremendous impacts on the national economy. Passive wireless systems (which only receive usually very faint signals) such as radio astronomy and earth exploration remote sensing have provided economically and scientifically important observations of Earths environment, our solar system and the cosmos (e.g., weather forecasting, observation of solar flares which could affect infrastructure and lives on Earth). Both types of systems play crucial roles for the growth of humanity, thus their advancements need to be accommodated. However, their spectrum requirements are growing and conflicting to a large degree, and radio frequency interference (RFI) from active systems to passive systems is an increasing concern. This calls for a new paradigm of spectrum access and sharing that can cope with the futures needs. This project proposes such a paradigm between cellular wireless communications (CWC) and radio astronomy systems (RAS).

The project develops a novel time and frequency division spectrum access between CWC and RAS, which not only resolves the spectrum requirement conflict but also enhances spectrum access opportunities for both systems. Instead of relying on the geographical isolation of RAS telescopes to avoid RFI, the project introduces a geographical coexistence paradigm between CWC and RAS through the use of a large number of distributed auxiliary radio telescopes (DARTs). The very large scale DARTs will suppress the RFI issue and potentially enable a quantum leap in RASs capabilities. In addition, the project develops novel adaptive circuitry and signal processing algorithms to handle the RFI issue efficiently. In brief, this project develops an interdisciplinary and mutually-beneficial technical solution and framework for spectrum access of CWC and RAS through coordination between them. CWC could gain more spectrum access opportunities which will enable more wireless services/applications and new business opportunities, thus expanding and enriching the national economy. RAS will secure more spectrum access opportunities and enhanced astronomical observation capabilities, thus accelerating its contributions to the fundamental science, knowledge of the universe, and protection of lives on Earth through space environmental information.

Agency: NSF | Branch: Continuing grant | Program: | Phase: BIOMATERIALS PROGRAM | Award Amount: 100.00K | Year: 2017

This CAREER award by the Biomaterials program in the Division of Materials Research to University of Texas at Dallas is to study protein-based nanoparticles using non-infectious and non-toxic virus capsids as scaffolding materials for possible drug delivery applications. Nanoparticle-based drug delivery systems have traditionally focused on using nanoparticles derived from metals, silica, polymers, etc. However, some of these materials have encountered roadblocks in their applications. For instance, nanoparticles based on inorganic and polymeric materials typically take a long time in clearing by the body, and possible accumulation in different organs. One possible solution is to make nanoparticles from proteins using non-infectious and non-toxic virus particles as a scaffolding. Conceptually, viruses are ideal for drug delivery system as they have been evolutionarily endowed with all the resources and properties needed to deliver a cargo to specific cells. However, one of the issues holding back in the use of protein-based nanoparticles for drug delivery is the lack of synthetic chemistries under conditions that dont cause unfolding or a denaturation of the proteins of the virus particles during their preparation. One of the thrusts of this proposal is in developing several new reaction methods and building a tool kit for future applications. These new reactions would enable to look at new approaches for drug release from protein-based nanoparticles, including the use of external trigger sources like pulsed laser light. To accomplish this, this project will functionalize the protein nanoparticles with photo-thermal antennae that when struck by the appropriate wavelength of light, will result in the rupture of the capsids and release of their contents (cargo, drugs, etc.) into the cell. An important benefit of this research is that this study is multidisciplinary in nature, and readily lends itself to creating a collaborative environment for student teaching and training. These efforts will be harnessed by giving these students opportunities in creating a web-based comics program, which are expected not only to educate, but also entertain school-aged K-12 children and their parents by telling stories on how nanomaterials interact with the body, and how they could help bring about future drug delivery systems for many biomedical applications.

The main objective of this CAREER award is to synthesize thermally responsive protein-based nanoscopic molecular drug delivery system prepared from virus derived nanoparticles that are non-infectious and non-toxic. Many of the current approaches for releasing contents of nanoparticles - either macromolecular or small molecule - depend on exploiting the cellular environment. The significant part of this award is to expand the variety and scope of reactions available for the functionalization of protein-based nanoparticles from virus-like particles QB (VLPs QB). Additionally, this award will study novel approaches in seeking the development of a method to permit cargo release using external sources of radiation - in particular optical radiation. To these ends, this project will focus on two objectives: 1) using a virus-like particles derived from QB as a model, this award will develop bioconjugation chemistries focusing on the disulfide groups found in viral capsid surfaces without significantly undermining the thermal stability of viral particle; and 2) introducing photothermally active receptors (antennae) on the surface of the proteinaceous surface of QB virus particles, and these modified viral particles when exposed to pulsed laser irradiation will cause rapid heating and cooling of the nano carriers resulting in the ruptue of the particles, and this in turn will result in the release of cargo/drug stored inside the VLP. This project, in addition, will demonstrate concurrent bilayer membrane disruption with cargo release as an alternate approach to escape from endosome capture, which in general would result in the degradation of the cargo. The students working in this project, which combines biochemical, physical, and synthetic chemistry, will gain experience and interdisciplinary learning, and these students will be engaging in creating high quality on-line and freely available science oriented and web-based comic strips aimed at K-12 students. These comic strips will be used to promote scientific literacy, and to encourage students and their parents to engage and discuss the ideas and concepts emerging from contemporary research. To that end, the project will take advantage of the unique diversity available at the campus to create multi-lingual comics to engage people from all over the world in the research that is being funded through this award.

Agency: NSF | Branch: Standard Grant | Program: | Phase: IntgStrat Undst Neurl&Cogn Sys | Award Amount: 800.00K | Year: 2016

Qin, Zhenpeng

Understanding how the brain controls behavior requires advanced tools to manipulate brain activity. Inspired by recent progress in optogenetics (i.e., a technique to control selected types of brain cells with genetic modification and light stimulation), this project seeks to develop a new set of tools that will allow localized and ultrafast control of brain activity to influence behavior in freely-moving animals. This will be achieved by using light stimulation to rapidly release compounds that are encapsulated in tiny nanometer-sized particles. The ultrafast feature of this novel compound technology is ideally suited to manipulate brain activity that typically occurs on the scale of milliseconds. Importantly, this new technology is suited to packaging and releasing a wide range of chemical and biological compounds, as well as combinations of such compounds. The projects success will have a number of broader impacts. Scientifically, this project will generate a new technology to better understand how the brain works, and thus new knowledge about the brain and behavior. The ultrafast compound release method can potentially develop into a platform technology for other research areas, including the nervous system outside the brain. The collaborative environment of this project will provide interdisciplinary training opportunities for two graduate students with cutting-edge technologies in the fields of engineering and neuroscience. Finally, this project will promote STEM education both in the lab and through community outreach programs.

Advances in methodologies and tools for neuroscience research often lead to fundamental insights into the function of the central and periphery nervous system. Currently available methods for drug infusions using relatively large metal cannulas are not ideal for studies in freely behaving animals, because drug delivery is slow and the cannulas often destroy the brain area under study and/or overlying brain areas. New methods are needed to perform drug infusion or local release in a minimally invasively manner in freely moving animals. Inspired by recent developments in optogenetics, the PIs will develop a versatile optically-triggered system for sub-millisecond compound burst release for the real-time study of brain activity and behavior. Plasmonic liposomes, i.e. liposomes coated with a gold shell layer, can encapsulate a wide range of molecular compounds and be deposited locally in the brain. Due to the small width and poor clearance of the extracellular space in the brain, the plasmonic liposomes can be designed to stay in the injected area for prolonged periods of time. The encapsulated compound can then be quickly burst-released by a near-infrared pulsed laser via an implanted optical fiber. The encapsulated compounds can be designed to release by repeated triggers, allowing multiple on-demand drug release events over an extended period for behavioral studies. In this project, an integrated approach will be developed to deliver and release the encapsulated compounds, and to study the resulting brain activity and behavior change in real-time utilizing Pavlovian fear conditioning. Successful development of this sub-millisecond optically-triggered burst release technique will represent a major technological advancement that addresses the limitations of current techniques for behavioral research. Specifically, improved bio-compatibility and reduced invasiveness are anticipated by the by one-time nanoparticle infusion and on-demand light-triggered drug release. The fast release feature of the new technique will provide sufficient speed to study neuronal communication in neuroscience research. Furthermore, this technique will find wide applications in neuropharmacology research where targeted delivery and localized rapid release are currently unavailable.

Agency: NSF | Branch: Standard Grant | Program: | Phase: SNM - Scalable NanoManufacturi | Award Amount: 1.25M | Year: 2017

Low-density, high strength composites play a critical role in a wide range of technological areas including aerospace, defense, sports, transportation, and renewable energy. One of the most important classes of low-density materials is polymer matrix composites, which are now used as primary structural materials for large airliners, and in other applications, such as wind turbines and ship structures. The use of nanostructured reinforcements in composites has been shown to improve strength, resulting in structural weight reduction, thereby leading to fuel savings and reduced ecological impact. There is an increasing interest and a strong need for nanomanufacturing technologies for making the nanostructured reinforcement materials and their composites that are scalable in throughput and quantity. Through this Scalable NanoManufacturing (SNM) award, an interdisciplinary research team will work with industry to develop a continuous nanomanufacturing process to fabricate light-weight, high-strength structural composites. Nanometer thick carbon nanotube fabric will be wrapped around individual fibers to create fuzzy carbon fibers to enhance their bonding strength with the surrounding polymer. The nanostructured composites will be tested to evaluate their performance under service environments. The use of the carbon nanotube fabric wrapped carbon fiber composites can potentially reduce the structural weight of aircraft, increase energy efficiency and reduce travel time. This project will make an important contribution to the continued success of the NanoExplorer program. A large number of high school and college students will be involved in all aspects of this multi-disciplinary project. Efforts will be made to recruit students from minority and under-represented groups.

In this project, a continuous nanomanufacturing line will be designed, built and assembled to wrap individual fibers with carbon nanotube fabric, without degrading in-plane carbon fiber properties. The concept of false twist will be employed to scale-up the wrapping process and make it fully automatic. The individually wrapped fuzzy fibers will be subsequently consolidated to form a tow of fibers. The fiber tows will be impregnated in polymer to form prepregs, which will then be stacked and fully cured to prepare composite laminates. The laminates will be characterized for thermal stability and mechanical behavior. The nanomanufacturing process as well as the material preparation configurations will be investigated through computer simulations and models. The successful completion of the project will provide a unique scalable nanomanufacturing process to provide composites with significantly enhanced interfacial shear and compressive strength without degrading fiber tensile properties.

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