Richard Gonzalez - US grants

The current work studies the role of promoter materials with carbon monoxide-hydrogen reactions. This work will also be extended to include bimetallic clusters, support and dispersion effects. An infrared cell is used that permits simultaneous infrared and kinetic measurements; simultaneous infrared, temperature-programmed desorption; and temperature-programmed reaction studies, surface composition measurements from experimental extinction coefficients, and surface concentrations of catalytically active species under ;itin situ;ro conditions.

This award will support Professor Richard D. Gonzalez of the University of Illinois at Chicago Circle in collaboration with Professor Ricardo Gomez of the Metropolitan University of Mexico at Iztapalapa. Studies recently completed suggest that metal-precursor-support interactions are important in determining the resulting surface composition of supported multimetallic catalysts. In particular, the presence of a mobile surface metal-precursor results in the surface enrichment of that metal in the resulting bimetallic catalyst. The investigators aim to identify the structure of these precursor-surface complexes using diffuse U.V. reflectance spectroscopy. The strength of the metal-support interactions will be measured through the use of quantitative differential scanning calorimetry and the elemental composition of the resulting bimetallic particles will be obtained through the use of dispersive x-ray spectroscopy (EDXS). EDXS will also be used to study interparticle metal phase relationships. The proposed research will be carried out simultaneously at the University of Illinois at Chicago and the Metropolitan University of Mexico at Iztapalapa. The in-situ diffuse U.V. reflectance studies, the microcalorimetric DSC studies and the catalyst charac- terization studies, including the surface composition measurements, will be carried out at the University of Illinois. The catalytic probe reactions and major portion of the EDXS studies will be performed in Mexico.

This project studies how individuals actually make decisions under uncertainty. Respondents will state cash equivalences for prospects defined over events. The project will then empirically validate recent axiomatic models of decision making which allow the separation of attitudes about consequences from attitudes about risk and uncertainty and which are defined over events that do not necessarily have a well-defined additive probability measure. The proposed research seeks to characterize risk attitudes as a function of the events(the weighting function) rather than the traditional view of characterizing risk attitudes as a function of the utility curve. Seven studies are proposed to understand people's attitudes about risk and uncertainty. The main focus of the studies will be to characterize properties of the weighting function and understand the relationship between the source of the uncertainty and the shape of the weighting function (i.e., source dependence.) Supplementing the empirical work will be a study of additional constraints, or axioms, needed to specify functional forms for the weighting function.

This Americas Program award will fund a cooperative research project, involving sol-gel processing and characterization of supported metal catalysts, between Dr. Richard D. Gonzalez of Tulane University and Professors Ricardo Gomez Romero and Tessy Lopez Goerne of the Autonomous Metropolitan University of Mexico at Iztapalapa. The focus of this proposed study will be on sol-gel processing of silica and alumina. A new series of high surface area catalysts in which the metal is in a highly dispersed state will be prepared. Sol-gel processing will lead to the formation of more homogenous-supported metal catalysts with a much more uniform distribution of particle sizes. The reforming catalysts prepared by sol-gel processing have the potential to compete favorably with industrial catalysts in use. This cooperative research project will share facilities available at Tulane University and Mexico. The synthetic procedures and catalyst characterization studies will be performed at Tulane while catalytic studies will be performed in Mexico.

ABSTRACT CTS-9530048 Funds are supplied to support a postcongress symposium on calorimetry to be held July 7-10, 1996, in Mayaguez, Puerto Rico. The symposium will follow (and be linked to) the Eleventh International Congress on Catalysis. Funds are used mainly to support travel between the Congress site in Baltimore and the symposium site in Mayaguez.

This grant provides funding to conduct a series of workshops on Interdisciplinary Design as an Instructional Discipline to be held over a 12 month period. Workshops will be held at the University of Michigan, Northwestern University, and in conjunction with the 2009 NSF CMII Grantees Conference and the 2009 ASME International Design Engineering Technical Conferences. These workshops will address issues related to supporting the emerging discipline of design through graduate education and interdisciplinary design research. Participants from a broad range of disciplines, including engineering, architecture, industrial design, visual arts, psychology, and business, among others, will be invited to attend.

Design is an integrative activity that spans many disciplines; however, our educational system often struggles to provide interdisciplinary design experiences for our undergraduate and graduate students and to recognize the significance of design research. Recently, new and innovative interdisciplinary graduate programs in design have arisen with strong ties to engineering yet structured to fully embrace and complement research from other disciplines. These graduate programs have the potential to influence the development of a new discipline of design that includes both education and research. Interdisciplinary education is a central factor in expanding and sustaining an American competitive advantage in today's global economy. Developing design as a broadly recognized and practiced instructional discipline is essential for maintaining leadership in the innovation of new products and systems. This series of workshops will bring together experts in the field of engineering design research and education and the larger design community to explore the challenges, successes, practices and future directions of interdisciplinary design graduate programs to gain insight into how to construct, grow, and sustain programs that prepare students for successful design innovation. If successful, this series of workshops will form the basis of new approaches to design education and research that fully embraces interdisciplinary collaborations within the current structure of academia.

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). The research objective of this award is to develop methods for innovation in science and engineering. The research investigates how designers use heuristics, or cognitive strategies, to identify specific solutions in the creative process, and how team collaboration may use multiple heuristics across team members as a means to generate robust designs---designs that meet user needs despite variability in consumer preferences over different consumers and changes in consumer preferences/needs over time. The goal of this research program is to understand the cognitive heuristics that support creative, innovative, and robust designs. A combination of laboratory experiments and field studies will be used to maximize control and improve generalization to real world settings. Deliverables include a new methodology for studying and identifying cognitive heuristics in design teams, software to teach and facilitate the creation of optimal and robust product designs, and tested recommendations for effective innovation in the context of multidisciplinary design teams.

If successful, the results of this research will lead to a new methodology for the creation of novel and quality designs in engineering, science and industry. By identifying the heuristics used by experts, and facilitating the use of successful cognitive heuristics by novices, we will increase creativity and innovation in design as seen in science and engineering. This will have direct consequences for industry in the development of new products. Another direct application of these research findings is improved instructional techniques in engineering design that foster creativity and innovation. These pedagogical techniques can transfer to other types of professional training (e.g., social sciences, humanities), industry and educational settings such as K-12 and higher education, thus providing new approaches to encouraging and instilling creativity and innovation in design across an array of instructional settings.

The project is investigating the impact of a systematic formal approach (Design Heuristics) for idea generation in design efforts in engineering education through a laboratory study, as well as in the context of existing engineering design courses. In one focus the team is characterizing the understanding engineering students have about concept generation, specifically how they approach it, what their goals are when they ideate, and what they believe makes it successful. In a second focus, they are assessing the solution creativity and quality and the solution set diversity of first-year engineering students when using Design Heuristics as compared to existing ideation methods (SCAMPER and Morphological Analysis) and students' own approaches. In the third focus, they are investigating the effects of Design Heuristics instruction on student ideation outcomes and conceptions of the ideation process over time using introductory engineering and senior capstone design courses that include a design project component. Finally, they are making the Design Heuristics approach and pedagogy available to engineering students and instructors through a guidebook for teaching idea generation with Design Heuristics and through a faculty workshop. The investigators are collecting data on the comparative effectiveness of the approaches and an external evaluator is reviewing the student selection and assignment, the appropriateness of the protocols, the fidelity of the interventions, and the coding, analysis, and interpretation of the data. Broader impacts include a strong dissemination plan with a faculty development workshop to inform others of the approach.

Five research-productive faculty members from the biology and physics departments at the University of San Diego will purchase, install, maintain, and manage a shared laser scanning confocal microscope to advance research in the physiological, cellular, molecular, and biophysical sciences. Confocal microscopy is essential in providing sensitive, high resolution, three-dimensional, time-resolved imaging so as to characterize: ion transporter expression in aquatic animals (Patrick, Gonzalez), reactive oxygen species in plants (Baird), serotonergic neurons in worms (Loer), intracellular trafficking in cellular migration (Prigozhina) and the intramolecular dynamics of diffusing DNA molecules. Research by the PI and co-PIs is highly integrative and requires a breadth of confocal technology that will enable imaging and data acquisition over a wide range of magnification, ranging from individual macromolecules (DNA) and real-time imaging of events in live cells, to localizing molecules in whole mounts of tissues or intact organisms. The specifications of Olympus Fluo View 1000/IX81 inverted microscope will satisfy the confocal research and training requirements of the faculty and provide opportunities for new and collaborative projects.

The NSF award will be used to purchase a confocal microscope for five faculty members in the Biology and Physics departments at USD, three of which are women faculty, including one pre-tenure, junior faculty in Physics. USD is an undergraduate institution where 58% of students are women and 20% are underrepresented ethnicities. The PI and co-PIs have a strong record of productive, collaborative research with undergraduates throughout the year. Students from Mater Dei High School (80% Latino/a and 20% from economically disadvantaged backgrounds) and San Diego City College (57% women, 70% minority status) will also benefit from gaining skills in confocal technology in summer research with USD science faculty. Integration of confocal technology into our research-based curriculum will augment several biology and physics courses and provide an opportunity to develop an interdisciplinary microscopy techniques course for the new biophysics major. This state-of-the-art instrument will enrich the research and educational experience of students in STEM areas at USD and attract highly motivated undergraduates to science careers.

This research project will create a theoretical and computational infrastructure to design new technology using creativity from crowds and individuals in combination with machine learning. A crowd could be a collection of experts within an organization, a classroom of students, or a large number of people online. Earlier research used machine learning working with individual engineers to help with simple design problems. This research will extend the earlier work to more complex configuration design problems, and will add crowd sourcing. Design representations will be graphs instead of vectors, and the design space will not be defined ahead of time. Machine learning may prove to be an important improvement over design evolution methods, and will provide insight into which design features are important. Machine learning also generates a model of subjective human judgment and preference, leading to more efficient and perhaps more innovative design synthesis.

If successful, this research will provide a platform for new models of innovation with input from multiple stakeholders: A machine supported by crowd-sourced knowledge and real-time interaction with humans will be able to produce unique and creative structures that were beyond the imagination of the humans involved. This research will also result in algorithmic advances in inference, learning, and related optimization techniques in representation learning for structured data and interactive human-machine collaboration. It will also provide a mathematical framework for innovation in massive system design problems involving thousands of designers such as the design of a jet fighter. The technology developed will be possible to implement in a variety of environments from complex engineering system design decisions to ideas for new products on commercial sites. In an educational context, this research, if successful, will allow students and teachers to experiment with design tools, individually, as part of a classroom experience, or as a national endeavor to both learn and possibly to generate new design ideas collectively.

The engineering design ability is critical in all undergraduate engineering programs. Design fixation is one of the common problems facing engineering design teams. This project is creating and evaluating tools that will help the design group avoid the design fixation problem. The work is taking a unique approach to the problem by creating 77 heuristics to help design groups avoid the fixation problem.

The technique is based on prior studies involving both student and professional teams. This prior work has demonstrated the technique is applicable to both design groups. The prior success provides a high level of confidence that this work will be successful.

Because design is included in all engineering programs and because the design heuristics are rather generic the work pre performed in this project is applicable to virtually all engineering programs nationally. As a result a successful result in this project could be a transformative innovation for engineering education.

This project is also producing instructional workshops to help instructors utilize the heuristics to enhance creativity in design courses. The workshops are not single point in time delivery of information but are distributed throughout time providing a long-term engagement of faculty. This type of prolonged engagement has proven to be more effective than other means of development and will produce excellent long term change.

? DESCRIPTION (provided by applicant): We propose a two-day workshop for Spring/Summer 2015 titled Operationalizing Affective Complexity: Measurement and Applications. Affective complexity, or the experience of more than one emotion at the same time, has been a topic of recent debate in multiple areas including subjective well-being, decision making, judgment, attitude ambivalence, socio-emotional and social cognitive development and aging, social neuroscience, and health. Examples include research on the co-occurrence of feelings, blends of same and different emotion valences, flexible and dynamic appraisals of emotions and feelings, asynchrony of behavioral reactions and subjective feelings, spillover of moods, and transitions from one emotion to another. Evidence suggests that mixed emotional states develops over childhood and may be enhanced in later life. The phenomenological experience of affective complexity extends our fundamental understanding of the meaning of emotions. It raises theoretical and empirical questions about the measurement and analysis of emotional states, experiences, and episodes that consist of more than one emotion. The resolution of these issues has implications for how we assess affective experience, a topic of increasing interest in NIA-supported international surveys related to the measurement of subjective well-being. Research about affective complexity is dispersed in multiple journals. The definitions and methods used in the various subdisciplines differ. This poses challenges for researchers in emerging fields, including research on experienced well-being, decision neuroscience, and neuroeconomics, where the measurement of emotional states and their relevance for policy analysis and decision-making requires accurate assessment of affective states in real time, appropriately linked to context. Recent advances in aging research, regarding the complexity and changes in affective experience over the life course, have not been fully integrated into this discussion. The goal of this meeting is to strengthen links between these disciplines and approaches. The workshop will engage a diverse audience of up to 100 participants from a range of fields, including psychology of aging, affective science, behavioral economics, psychiatry, and demography. The workshop will consist of short talks and discussion sessions. Each day will end in a panel-led discussion designed to integrate across talks and sessions and engage audience (live and web streaming). The meeting will establish a multidisciplinary network to share information, promote cross talk, and facilitate collaboration. Recruitment for the conference will include several society newsletters, email groups and list serves as well as contacts with existing networks involving Program Committee members and confirmed speakers. This will allow broad coverage and diversity of discipline, academic rank, and conference participants. Output from the conference will include downloadable videos of the talks, white papers, special issue of a journal, special topic symposia at relevant conferences, and infrastructure for continued collaboration after the workshop.

Novel neuroscience tools and techniques are necessary to enable insight into the building blocks of neural circuits, the interactions between these circuits that underpin the functions of the human brain, and modulation of these circuits that affect our behavior. To leverage rapid technological development in sensing, imaging, and data analysis new ground breaking advances in neuroscience are necessary to facilitate knowledge discovery using data science methods. To address this societal grand challenge, the project will foster new interdisciplinary collaborations across computing, biological, mathematical, and behavioral science disciplines together with partnerships in academia, industry, and government at multiple levels. The Big Data Neuroscience Spoke titled Midwest: Advanced Computational Neuroscience Network (ACNN) is strongly aligned with the national priority area of neuroscience and brings together a diverse set of committed regional partners to enable the Midwest region to realize the promise of Big Data for neuroscience. The ACNN Spoke will build broad consensus on the core requirements, infrastructure, and components needed to develop a new generation of sustainable interdisciplinary Neuroscience Big Data research. ACNN will leverage the strengths and resources in the Midwest region to increase innovation and collaboration for the understanding of the structure, physiology, and function of the human brain through partnerships and services in education, tools, and best practices.

The ACNN will design, pilot and support powerful neuroscientific computational resources for high-throughput, collaborative, and service-oriented data aggregation, processing and open-reproducible science. The ACNN Spoke framework will address three specific problems related to neuroscience Big Data: (1) data capture, organization, and management involving multiple centers and research groups, (2) quality assurance, preprocessing and analysis that incorporates contextual metadata, and (3) data communication to software and hardware computational resources that can scale with the volume, velocity, and variety of neuroscience datasets. The ACNN will build a sustainable ecosystem of neuroscience community partners in both academia and industry using existing technologies for collaboration and virtual meeting together with face-to-face group meetings. The planned activities of the ACNN Spoke will also allow the Midwest Big Data Hub to disseminate additional Big Data technologies resources to the neuroscience community, including access to supercomputing facilities, best practices, and platforms.

This award received co-funding from CISE Divisions of Advanced Cyberinfrastructure (ACI) and Information and Intelligent Systems (IIS).

A central challenge in natural language processing is to develop methods for determining how meanings of words relate to one another. This task is called "lexical semantics", because "lexical" means "word" and "semantics" means "meaning". Traditional dictionaries do not solve the problem of lexical semantics, because definitions are often circular or incomplete, especially for the most common words. Instead, models of lexical semantics are computed by processing large bodies of text, using the principle that pairs of words that often appear in the same contexts must have meanings that are similar along some dimensions. For example, the words "man" and "boy" would be inferred to have similar meanings along the dimensions of "human" and "gender". However, a limitation of current models is that they assume that the meaning of words is the same for all speakers of a language. This is plainly false: we know, for example, that English speakers use words differently depending, among other factors, their age, gender, field of work, and geographic location; that is, on the basis of their demographics. This project will overcome this limitation by developing methods for demographic-aware lexical semantics, where people-centric information complements language-based information. This work will help improve systems for natural language communication between people and computers, such as Siri or Alexa, as well as improve systems for automatically translating between different languages.

Recent years have witnessed significant progress in research in lexical semantics using corpus-based approaches such as distributional vector-space models and word embeddings. At the same time, the growth of Web 2.0 has led to tremendous volumes of texts, most of which are rich in explicit or implicit demographic information, such as the age, gender, industry, or location of the writer. The goal of this project is to take the next natural step at the confluence of these two trends, and develop methods for demographic-aware lexical semantics, where people-centric information complements language-based information for enhanced linguistic representations that explicitly account for the demographics and traits of the people behind the language. The project targets the following three main research objectives. First, it develops novel demographic-aware word representations models that account not only for contextual knowledge but also for people-centric information. Methods that are explored include distributional vector-space models that can be composed to create demographic-aware vector-space representations for various demographic profiles, and joint word embeddings that combine generic context-based embeddings with specialized embeddings that reflect the specifics of given demographic dimensions. Second, building upon extensive previous work in behavioral studies targeting the identification of systematic heterogeneity across groups, lab studies are devised to validate the findings from the computational models. Third, the application of these novel people-centric word representations to three core tasks in natural language processing are explored, ranging from simple to complex, namely: word associations, text similarity, and diversified news.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

The Analysis Core (AnC) will play a critical role in the activities and productivity of the Michigan Center for Contextual Factors in Alzheimer's Disease (MCCFAD). Supporting MCFADD's three priority areas of: epidemiology, health economics, and culturally sensitive care as well as the long-term goal to advance ADRD- relevant social and behavioral science research in underserved and underrepresented communities while diversifying the research workforce dedicated to healthy aging, the AnC will ensure the highest possible impact of our Center's research and discoveries. Specifically, the AnC will ensure culturally sensitive and scientifically valid cognitive, functional, and psychosocial measurement approaches; and (2) oversee methods and analysis of both primary and secondary data for AD-RCMAR Scientists. Methodological sensitivity to cultural differences in cognitive testing and in the experience of ADRD is critical for valid and reliable investigations in ADRD disparities. In collaboration with the other cores, the AnC will link AD-RCMAR Scientists to appropriate data sets and mentor in state-of-the-art research methods. AnC focus on the use of cutting-edge analytic and data visualization techniques, as well as multiple and diverse racial/ethnic groups will lead to significant contributions to the field including the development and dissemination of: new and evaluation of existing cognitive, functional, and psychosocial measures; analytic and visualization code to examine and communicate within-group variability; automation code and templates to generate registry participant feedback reports; and methodological focused publications detailing steps used to ensure cultural sensitivity and validity of measures. Corresponding to these areas of importance, the AnC proposes three Specific Aims: Aim 1: Provide an enriched environment to ensure culturally sensitive and scientifically valid measurement approaches; Aim 2: Emphasize mentoring in state-of-the-art methods and analysis: person and variable centered approaches; Aim 3: Disseminate scientific information regarding novel methodological developments, measurement approaches, and new data resources produced. The AnC will ensure thoughtful and thorough methodological approaches and provide consultations at every stage of Center-wide and AD-RCMAR Scientist projects. Moreover, they will work closely with the Research and Education Core (REC) and Community Liaison and Recruitment Core (CLRC) to assist, mentor and support AD-RCMAR Scientists to become independent investigators in ADRD- related research by providing an enriched learning environment to increase their analytic and research skills. With our multi-disciplinary and highly experienced AnC leadership team and Center faculty, the AnC is exceptionally well-equipped to ensure that the MCCFAD makes seminal contributions to innovative ADRD disparities research across the region and nationally.