Yan Chen - US grants

proteins; enzymes; biomedical resource; biological products;

This award will support a theoretical and experimental study on the dynamic stability of Nash-efficient public goods mechanisms. The theoretical investigation will evolve around developing a new family of supermodular Nash mechanisms that implement Lindahl allocations. The experimental research will study the stability of variants from the same new family of mechanisms in a laboratory setting with real human subjects. The data will enable the investigator to study the effects of institutions/mechanisms on the resulting learning dynamics adopted, to calibrate and compare the performance of different learning rules, and to refine and improve on existing learning models in light of the data. Previous theoretical work on Nash implementation has mainly focused on establishing the static properties of Nash equilibria. The few exceptions have been using specific dynamic learning rules to study the stability of different mechanisms, such as Cournot best response or the gradient adjustment process. Based on previous experimental findings and its robust theoretical properties, the investigator proposes to use supermodularity as a reasonable stability criterion for Nash-efficient mechanisms. This provides a fresh perspective on implementation theory and contributes to the public goods mechanism literature. The new family of mechanisms will be the first Nash-efficient public goods mechanisms which implement Lindahl allocations and also have a robust stability property. The experimental study will contribute to the ongoing research on learning and implementation. The PI is an assistant professor who is in an early stage of building up a career that combines theoretical and experimental research in mechanism design. She is in her fourth year at Michigan where tenure in the field of economics is difficult to achieve. The POWRE award will assist her at a critical career stage.

School choice is one of the hottest topics in education. It means giving parents the opportunity to choose the schools their children will attend. Since it is not possible to assign each student to her top choice school, a central issue in school choice is the design of a student assignment mechanism. By now several cities including Boston, Cambridge, Little Rock, San Jose, and Seattle have adopted school choice plans. While each of these plans has its protocol and guidelines for the assignment of students, none of them has a rigorous procedure. The lack of rigorous procedures offers opportunities to manipulation and results in appeals by parents who are unsatisfied by the school assignments of their children. This project introduces a new class of indivisible goods allocation problems that model public school choice, proposes a mechanism for rigorously assigning students to schools, and analyzes it. The project also studies the allocation of housing with existing tenants. The main application is on-campus housing, although the model has other applications such as public housing, office space allocation, and parking space allocation. Existing allocation mechanisms are shown to have serious shortcomings including inefficiency. An alternative mechanism is shown to overcome these shortcomings. Additional properties of this mechanism are studied and experiments are conducted to test the theoretical results that compare the performances of this mechanism and a widely used common real-life mechanism. Both of these projects deal with design and analysis of mechanisms for real-life indivisible goods allocation problems.

The objective of this proposal is to finish validation of a unique transgenic mouse model for applications in preclinical toxicology and risk assessment. The K6/ODC mouse overexpresses the enzyme ornithine decarboxylase in skin and internal organs and is exquisitely sensitive to topically applied carcinogens. The specific aims of the application are to determine the tumor response of K6/ODC mice to systemically administered chemicals and to continue characterization of the response to UV irradiation. Use of this model for carcinogen detection will reduce the time, cost, and number of animals required for regulatory purposes as compared to existing models. In addition, the enhanced sensitivity of the model allows agents to be tested at low doses typical of human exposure levels. PROPOSED COMMERCIAL APPLICATIONS: An in vivo transgenic mouse model will be further developed for testing the carcinogenic potential of drugs, environmental chemicals, dietary constituents, and UV light. Because the model is extremely sensitive, chemicals can be tested at low doses, comparable to human exposure levels.

This program of research in experimental economics incorporates bounded rationality and learning into the mechanism design framework. The project has two parts. The first consists of three experimental studies of incentive-compatible public goods mechanisms. The presence of public goods seriously challenges traditional or "natural" solutions for the allocation of private goods. Incentive-compatible mechanisms align individual self-interests with the group interest. The investigator's previous work and others' work have shown that among these incentive compatible mechanisms those which are supermodular, i.e., when players' strategies are strategic complements, converge robustly well to the Nash equilibrium prediction, and those which are not supermodular do not converge as well. This project examines whether the degree of strategic complementarity could have a significant effect on the convergence of a mechanism, i.e., whether the process is gradual. Experiments are conducted on three supermodular mechanisms for public goods provision with varying degrees of strategic complementarity to study this effect. Convergence is an important criterion for selecting a mechanism to solve a particular problem because at the end of the learning process we would like the mechanism to yield the desired outcome.

The second part consists of two experimental studies of mechanism design in distributed systems, such as the Internet, which are characterized by asynchronicity and limited information. In a wide variety of real world situations a group of agents share a common production process transforming input into output. A salient example is provided by the Internet, which has becoming increasingly important in global telecommunications. In the context of several agents sharing a network link, the cost to be shared is congestion experienced. In the network context, traditional solution concepts such as Nash equilibrium or the serially undominated set might not apply. Friedman and Shenker (1998) propose new solution concepts for distributed systems. This project runs experiments to examine these new solution concepts. The project also conducts experiments to study the average cost pricing and the serial cost sharing mechanisms under complete information and synchronous moves, as well as distributed settings with limited information and varying degrees of asynchrony. This study will provide information on what types of mechanisms should be selected in distributed systems.

DESCRIPTION (provided by applicant): The purpose of the proposed research is to develop fluorescence correlation spectroscopy into an effective, reliable tool for in vivo characterization of dynamic processes. This technology has enormous potential for biomedical applications, such as in vivo drug screening. Fluorescence correlation spectroscopy (FCS) studies the fluorescence fluctuations of a small number of molecules inside the focal spot of a laser with statistical analysis tools. Among the unique information provided by FCS is the absolute fluorophore concentration and kinetic parameters, such as the diffusion coefficient and chemical reaction coefficients. FCS delivers dynamic information with submicron spatial resolution and without the need to apply an external perturbation rendering it especially attractive for in vivo measurements. Another recently developed analysis technique based on the photon counting histogram will be employed to extract additional information on brightness heterogeneity from FCS data. A careful experimental examination of the in vivo properties of green fluorescent protein (GFP) will be conducted, while explicitly considering the influence of the cellular environment on FCS measurements. In addition, GFP tagged retinoid receptors will be used to perform an in vivo study to resolve their molecular oligomerization state in the presence and absence of ligands.

Despite extensive experience, eliciting contributions in an on-line community is still largely a matter of trial and error. This project will develop theory to predict contribution behavior in on-line communities and will help transfer that theory into practice by using it to develop a set of on-line community design guidelines. The project brings together three teams of researchers (from the University of Michigan, Carnegie-Mellon and the University of Minnesota) with diverse areas of expertise (including economics, social psychology, and on-line recommender systems). The research team will start with existing theories of voluntary contribution to collective efforts, conduct a set of experiments to test the validity of these theories in the domain of on-line communities, and develop a new, synthesized theory. The experiments will be conducted in the MovieLens community with thousands of active users and an average of 30 new users joining each day. The key scientific significance of this work lies in using Social Science theory to guide design. An interesting broader impact of that approach is the development of a cadre of graduate students with interdisciplinary research experience who will be ready to guide the next generation of on-line community research.

This project will use experimental and simulation methods to examine matching theories and their applications to school choice, labor markets, and marriage markets.

When a public school district adopts "school choice", generally some schools attract many more applications than they can accept. How to match students to schools is therefore an important question for public policy. The experimental studies will focus on three algorithms that could be used to match students to schools. The first, the Boston mechanism, is one of the most commonly used and prominent in current use. There are two alternatives to the Boston mechanism that have superior theoretical properties - the Gale-Shapley mechanism and the top trading cycles mechanism. The goal is to evaluate which mechanism is likely to do a better job in the real world. The project will use lab experiments and extensive computer simulations to analyze both the basic school choice problem and the "controlled choice" problem when schools must meet goals for their enrollment characteristics (for example, including a certain percentage of low-income or minority students in their enrollment). Data from the experiment will provide the first rigorous evaluation of the Boston mechanism, as well as an evaluation of the Gale-Shapley mechanism and the top trading cycles mechanism used in the school choice context. As more states have passed legislation mandating intra- or inter-district school choice, it is urgent to evaluate the Boston mechanism as well as alternative mechanisms in order to make meaningful policy recommendations. The results of this study will be immediately useful to policymakers.

The rest of the project will conduct experimental studies of three mathematical models that have proven to be a useful tool in labor economics, macroeconomics and monetary theory. These are also "matching" models; they each consider a decentralized matching process with search frictions. The experimental studies will test whether the theoretical models are robust when the perfect rationality assumption is relaxed. They will also examine factors affecting equilibrium selection, as well as the effects of taxes and subsidies on search and matching in these models. The models have been used to predict how people match to available jobs and how people find marriage partners. The results of this part of the project should therefore improve our understanding of how taxes and subsidies will affect occupational and marriage choices.

This demonstration project will identify barriers and develop alternative incentive mechanisms for data producers to deposit archive-ready data sets in an archive. Archive-ready means data sets that meet an archive's deposit requirements and submission guidelines. Archives rely heavily on data producers to provide complete and accurate documentation when they deposit data and to comply with other requirements, such as file structures and formats, transfer media, and requirements for protection of privacy and confidentiality. The entire enterprise of digital archiving assumes some degree of cooperation between producers of digital information and archives. When data producers do not comply with submission guidelines, archives incur additional costs in preparing the data for preservation and dissemination, experience delays between ingest and release, and assume risks if data that do not meet quality assurance standards are released. The research literature and years of experience with data deposits at the Inter-university Consortium for Political and Social Research (ICPSR) indicate that, as a rule, current incentives are insufficient to overcome the obstacles that data producers report. This multi-disciplinary team of experts in digital archiving, social science research, and experimental economics and ICPSR will investigate ways to increase cooperation between producers and archives. With a government partner, the National Institute of Justice, the team will use multiple methods (surveys and experiments) to identify barriers to compliance, revise guidelines and
responsibilities, and develop and test alternative incentive mechanisms.

Intellectual Merit

This award will examine legal, social and economic impediments to archiving by analyzing problems that producers encounter when preparing data for deposit and by developing and field testing alternative incentive mechanisms. The project will enhance understanding of curatorial processes and work flow, especially when work is distributed between the data creator and the archive. It will develop metrics for the contributions expected of data producers. Contributions will also be made to our understanding of incentive mechanisms for public goods.

Broader Impacts

The results of research with social scientists will produce better models for sharing responsibility for archiving between data producers and archives. The models and incentive mechanisms will have broad applicability to other types of data producers who are mandated to deposit data by funding agencies or as a condition of publication. Ultimately, more cooperation between data producers and archives will reduce the costs of archiving, accelerate the release of data, and improve its quality. The research will also inform development of standards and guidelines for producer-archive relationships.

Culture sits between institutions and economic or political achievement, affecting performance. Whether looking horizontally across countries or vertically through time, one lesson is clear: the efficacy of institutions such as markets, democracies, and legal systems hinges upon behavior, particularly on the tendency for people to cooperate with and trust one another. A theory of institutional performance, therefore, must come to grips with culture. We meet this challenge with a modification of the traditional game-theoretic approach. Game theory, the preferred formal framework for analyzing institutions, assumes isolated, context-free strategic environments and optimal behavior within them. Thus, game theory would seem to be at a loss to explain the patterned, contextual, and sometimes suboptimal behavior we think of as culture, let alone its emergence and persistence across space and time. We have developed a method to examine how people respond to multiple institutional environments---games---simultaneously (hence the games theory moniker). Preliminary models suggest that when purposeful, incentive-driven agents confront multiple strategic situations simultaneously and when cognitive effort is costly, culturally distinct behavior may emerge and be unavoidable. Therefore, a second goal is to uncover how the addition of new institutions---including timing and combinations with other institutions---may affect culture, creating a more profitable and peaceful climate.

The proposed research consists of four parts. First, the researchers construct agent based and game theoretic models that produce cultural behavior. Second, they conduct experiments with human subjects to corroborate those agent based models. Third, they define a classification to clarify and refine what is meant by path dependence, highlighting a distinction between processes that depend on the path of history and processes that depend only on the set of historical events but not their order. Fourth, they construct an agent based model that tests whether path dependence emerges that they then also test with human subjects. This research effort brings together a political scientist trained in the study of institutions, a complex systems scholar who connects mathematical and agent based models, and an experimental and theoretical economist who specializes in learning and public economics. All three investigators are well versed in game theory which will serve as a translating language between the various methodologies applied.

Aleksandar Kuzmanovic
Pollution Resilience for Internet Caches
Northwestern University
0627715

Abstract

The majority of requests for the Domain Name System (DNS) entries, web,
or even peer-to-peer (p2p) content in today's Internet are not served
by origin servers, but rather by intermediate caches. As such, they
pose an attractive target for malicious attackers. This project will
address the problem of cache-targeted DoS attacks on a broad front:
(i) by developing and studying a new generation of large-scale
cache-targeted pollution attacks, (ii) by designing fundamental
knowledge in creating deployable anti-pollution mechanisms, and
(iii) by designing and implementing counter-DoS solutions for three
imminent threats: web, p2p, and local DNS cache-targeted pollution
attacks.

The proposed pollution attacks pose a challenging problem for the
entire Internet community: (i) they are capable of degrading overall
network performance without flooding network resources; (ii) they
possess a dangerous level of indirection; (iii) they pollute the cache
with unpopular, rather than bogus files; (iv) they may operate at much
longer time-scales than classical DoS attacks operate and are thus
invisible for state-of-the-art counter-DoS schemes.
By leveraging data streaming computation techniques, our goal is to
attain a scalable solution by significantly reducing the amount of
state needed to maintain, and to make the detection system itself
resilient to DoS attacks. The involvement of industrial partners in
this project will accelerate the transfer of the research results
into operation. In particular, we will collaborate closely with the
UltraDNS Corporation which provides DNS services for over 20\% of
the world domains, including top-level domains as well as numerous
private organizations.

Yan Chen
Northwestern University
0627751
Panel: P060969

Abstract


Attacks are commonplace in today's networks, and identifying them
rapidly and accurately is critical for large network/service
operators. Most existing intrusion detection systems (IDSes) are
signatures-based. But such signatures are usually generated manually
or semi-manually, a process too slow for defending against
self-propagating malicious codes, or worms. To evade detection by
signatures, attackers may also employ polymorphic worms which change
their byte sequence at every successive infection.

In order to thwart a zero-day worm attack, it is essential to design
an automatic signature generation system against polymorphic worms
which may be deployed at the network gateways/routers and satisfy
the following requirements: network-based, noise-tolerant,
attack-resilient, and having efficient signature matching.

None of the existing work satisfy all the requirements above. Thus
the PIs design NAPOLEON( Network-based Attack-resilient
POLymophic-worm signaturE generatiON), a network-based automatic
signature generation system with all the aforementioned properties.
NAPOLEON has two components which complement each other: TOken-based
Signature Generator (called TOSG) and LEngth-based Signature
Generator (called LESG).

This project combines theoretical computer science with practical
network security research. The PI has extensive experience on
network anomaly/intrusion detection. The co-PI's expertise is in
theoretical computer science and algorithms and has a track record
of applying them to various applications including security.

This interdisciplinary research will have a strong impact. For
example, during the PIs' collaboration, they have found that certain
algorithmic techniques in bioinformatics are directly or indirectly
applicable to worm detection problems.

Exponential decreases in computation and communication costs induce marvelous new Internet services and social opportunities. However, new forms of social engagement also create new problems. This Integrative Graduate Education and Research Traineeship (IGERT) renewal will advance a principled, multi-disciplinary research method well-suited to make the Internet a place that is safe, fun and sustainable, with corresponding potential for improved social, economic, and political interaction. Incentive-centered design is a science that aligns participants' incentives with system or social goals. Distributed and collaborative system performance depends critically on strategic choices that users make when interacting with the system or each other, yet mismatch between individual interests and system goals is pervasive. This program takes a broad view of individual motivations, drawing on economic, psychological, and sociological theories, and combines these with the design and engineering sciences of artificial intelligence, software and networking.

The broader impacts go beyond research contributions to the design of socially-valuable Internet communities and services. The joint Ph.D. program at the University of Michigan and Wayne State University (a metropolitan comprehensive institution) will train future scholars and teachers from a diverse array of socio-economic and cultural backgrounds. In addition it includes a summer program for undergraduates from underrepresented groups, who in teams together with the IGERT trainees will develop submissions to international research competitions. This program will increase the pool of students from underrepresented groups who are prepared for and motivated to pursue graduate education. IGERT is an NSF-wide program intended to meet the challenges of educating U.S. Ph.D. scientists and engineers with the interdisciplinary background, deep knowledge in a chosen discipline, and the technical, professional, and personal skills needed for the career demands of the future. The program is intended to catalyze a cultural change in graduate education by establishing innovative new models for graduate education and training in a fertile environment for collaborative research that transcends traditional disciplinary boundaries.

This project advances knowledge in both the fields of psychology and economics by integrating understanding of the psychological processes associated with social identity (e.g. ingroup bias, group norms) with understanding of individual decision-making in the economic domain (e.g. social preferences, mechanism design and equilibrium selection). To date, research in social psychology has developed a broad base of knowledge about the influence of social identity on attitudes and behaviors; however, little is known about the economic consequences of these processes. Similarly, standard economic theories have explicated processes underlying individual preferences but have no systematic empirical foundation which incorporates group identity into individual preferences. This project draws on the theory and methods developed in social psychology and experimental economics to bridge the two bodies of work and inform us of the relationship between social identity and social preferences. Thus, the results of the studies will extend our knowledge in both these fields of study. The PIs will first explicitly measure the effects of social identity on social preferences. Based on the outcome of this research, a second research stream will be initiated examining the effects of group identity and, in particular, a common identity, on contract design and public goods productions. Finally, the PIs will examine the effects of group identity on equilibrium selection, an important unresolved issue in game theory.

Broader Impact: As the world becomes more integrated, managing diversity
becomes an increasingly important issue to understand. For instance, organizations are more frequently encountering the issue of integrating a diverse workforce, and motivating members coming different backgrounds to work towards a common goal. The results of the proposed research can inform us about the role of social identity in eliciting decisions from individuals to maximize social-welfare, to prioritize organizational goals above self-interest, and to exert more effort. From the perspective of the organizations, this research will provide insights on whether an organization should invest resources to create and enforce a common identity among its workers.

NSF Proposal 0831508: CT-ISG High-Speed Network Defense with Massive and Diverse Vulnerability Signatures

PI: Yan Chen, Northwestern University

Given the ever-increasing sophisticated Internet attacks, network-based Intrusion Detection/Prevention Systems (IDS/IPS) are of critical importance. Such systems mainly have two important metrics: accuracy and throuput. Accuracy is of particular importance, especially for IPSes which are inline devices that throttle connections when they are identified as malicious via signature-matching. The latest works assume that regular expressions (RE) are the right choice for signature formatting. However, there are polymorphic and metamorphic variations that can evade the RE-based detection. The fundamental problem of RE signatures is that in many cases it cannot capture the vulnerability conditions.

In this project, we design a next-generation semantic based network IDS/IPS system (called NetShield) which contains thousands of vulnerability signatures with rich diversity, including protocol, file and web semantic signatures. While offering much better accuracy, NetShield provides high throughput comparable to that of the state-of-the-art regular expression based IDS. We design algorithms for 1) efficient protocol parsing and 2) massive protocol semantic signature matching. Furthermore, we extend the parsing and matching solutions to Web and file semantic signatures.

This project has the potential for significant broad impact. The research component will produce fundamental knowledge that will advance the state-of-the-art in the network IDS/IPS systems. Our wide collaboration with industry researchers will facilitate such technology transfer. In addition, we plan to disseminate our work through timely releases of software/hardware, traces, and benchmarks to the open source community for broader usage. This research agenda is complemented by a strong and tightly integrated educational and outreach component.

Intellectual Merit:
This REU Site award to the University of Michigan's School of Information is dedicated to furthering undergraduate intellectual growth and preparing them for careers at the intersection of the social sciences and information technology in incentive-centered design for cyberinfrastructure. They will conduct research in some of the country's leading information laboratories. Performance of distributed and collaborative systems critically depends on interactions, yet such interactions are often ineffective and inefficient. this training will address these inefficiencies.
Broader Impact:
Partnerships with various organizations and with Wayne State will assist in recruitment of women, underrepresented minorities and students from institutions with limited research programs.

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).

Much of the Internet's growth occurs in domains beyond the reach of current measurement techniques and platforms, such as behind NAT boxes and firewalls or in regions of the Internet not exposed by public BGP feeds. This work is motivated by the observation that, collectively, peers in large-scale P2P systems have a unique and valuable perspective on network conditions, one to which today's researchers, operators and users have limited or no access. P2P systems are an ideal vehicle for accessing these views, being among the largest services and covering most of the Internet. As passive monitors of the Internet, different P2P systems can provide different, complementary views of the network, over partially overlapping space and time domains. The goal of this effort is to explore the potential for reusing such valuable view, investigating techniques for gathering, sharing, and exploiting it. The work focuses on: identifying useful metrics regarding network conditions collected by these peers and evaluating their potential for reuse (over time and across multiple systems' perspectives), designing approaches for maintaining this information and making it accessible to other large-scale distributed systems in a decentralized manner while preserving the privacy of the participating peers, and exploring potential applications that could benefit from this information.

Access to end-host views of the network will help in the understanding and characterization of the underlying network and address the needs of new emergent Internet services and applications.

This proposal requests a three-year grant to support a program of research in matching theory and experiments at the University of Michigan and Carnegie-Mellon University. Part of the proposed research will be conducted in China, in collaboration with Xiangdong Qin at Shanghai Jiao Tong University and Zongkai Shi at Tsinghua University. This program is an extension of work
that has been supported by NSF grant SES-0720943 and university funds. The proposed research is likely to have direct impact on the school choice reform in the U.S. and college admissions reform in China.

(1) Intellectual merit: The PIs propose to conduct theoretical and experimental studies of a family of matching mechanisms applied to the school choice problem: the Boston mechanism, which is one of the most commonly used and prominent school choice algorithms in practice, and two alternatives which have superior theoretical properties ? the Gale-Shapley mechanism and the modified Boston mechanism. Data from the experiment will provide a rigorous evaluation of the family of mechanisms in the school choice context. The PIs then propose experimental studies of the college admissions mechanisms, with variants used in China. Both the theoretical and the experimental studies of these mechanisms are essential to advancing knowledge. Mechanisms cannot be evaluated purely on theoretical grounds, because people may not use them as intended. Nor can they be evaluated as used in the real world, because we do
not have access to people?s true preferences. Experiments are vital to understanding how mechanisms will perform. It is important to note that the findings will guide both theory and practice regardless of whether the hypotheses are confirmed or rejected.

(2) Broader impacts: School choice has been one of the most important and most widely debated topics in the past twenty years. In the current debate on school reform, choice has moved to the top of the national agenda. The Boston mechanism is a prominent algorithm used in several cities pioneering the school choice program, but its performance has not been thoroughly evaluated. As more states have passed legislation mandating intra- or inter-district choice, it is urgent to evaluate this mechanism as well as alternative mechanisms in order to make meaningful policy recommendations. Similarly, college admissions mechanisms in China present a new class of matching problems which influence the education and labor market outcomes of more than 10 million high school seniors every year. The research proposal has the potential to benefit society by influencing the method by which students are matched with schools and colleges. The successful and timely completion of the proposed experimental program is only possible with the involvement of undergraduate and graduate students. Chen has been working with undergraduate
students through the Undergraduate Research Opportunities Program at the University of Michigan since 1999 and the NSF REU program. The PIs will continue to include 1-2 undergraduate students in this research project every year. New undergraduate students will have the opportunity to become involved in most phases of the project, including literature review, assistance in conducting experiments and preliminary data analysis. Analysis of large data sets requires the hard work and dedication of graduate students. Therefore, the PIs plan to get one graduate student research assistant for each year of the project. Graduate students are encouraged to participate in conferences and workshops to present their research to the research community. Graduate students will learn the entire process of experimental research, from experimental design, execution, data analysis to writing and presentation.

PROJECT SUMMARY The long term goal of the Applicant's research program is to explore the molecular mechanisms underlying the etiology of age-related macular degeneration (AMD) and develop novel target-based therapeutic strategies. This K99/R00 grant will facilitate the transition for the Applicant to become an independent investigator at the Vanderbilt Eye Institute, which has a rich environment of scientific collaboration and nurturing career development of junior scientists. AMD is the leading cause of blindness in elderly Americans. The majority of AMD patients has atrophic (dry) form of the disease and has only limited treatment options at the present time. Atrophic AMD is likely resulted from gene/environmental interaction causing progressive degeneration of the retinal pigment epithelium (RPE). Aging is the most well defined environmental risk factor of AMD. We hypothesize that the mammalian target of rapamycin (mTOR)-mediated signaling pathway plays key roles in controlling the aging process of the RPE. The hypothesis is supported by recent literature data suggesting that mTOR plays key roles in integrating various environmental signals and linking them to altered tissue function and organism's life span. In our preliminary studies, we found that rapamycin reversed the senescent phenotype of primary human RPE cells in vitro. To further test our hypothesis, we have proposed three specific aims in this application. Aim 1 is to determine how the aging process regulates mTOR pathways in the RPE. Aim 2 is to determine how modulating the mTOR signaling affects RPE aging in vitro by a potential mechanism of regulating autophagy. Aim 3 is to determine whether mTOR regulates aging of the RPE in vivo using SOD1 knockout mice which develop AMD-like phenotype in the retina. During the mentored phase, the Applicant will conduct the proposed experiments under the supervision of a mentoring committee, which is consisted of mentors with expertise in AMD etiology and pathogenesis (Dr. Paul Sternberg), animal models of neurodegeneration in the retina (Dr. David Calkins) and mTOR/autophagy (Dr. Lu Bo). Members of the committee will meet regularly, monitor the research progress and assist the Applicant to advance her career towards independence. Research at the R00 phase will test the potential therapeutic effects of mTOR inhibitors in an animal model relevant to AMD. Results from these studies will provide novel mechanistic information on aging and age-related degeneration of the RPE and retina.

This project represents an interdisciplinary research effort to investigate the effects of social identity on lender behavior in an online microfinance community (kiva.org) and the selection of social identities. Social identity research in economics predicts that a salient group identity and group competition increases individual contribution to public goods.

The researchers will apply social identity and social preference theory to analyze the Kiva lending data at the individual and team level. Results from the analysis will yield insights to one of the most important yet unresolved problems in social identity research, the selection of identity and the formation of norms within a social group. This work represents the first attempt to bridge text and network data mining techniques with social identity theory. Novel text mining and machine learning models will be developed that advance the state-of-the-art of mining of online communities.

More than one billion people globally live in absolute poverty, most also excluded from the formal banking sector. To alleviate poverty, microfinance programs emerge in many parts of the world to provide small loans to the poor. Currently about 10 million households are served by microfinance programs. This research investigates incentives to increase lender participation and lending activities on Kiva. Preliminary analysis indicates that the lending teams program is effective in increasing loan activities. Results from the analysis will benefit Kiva and other microfinance programs. Increased participation and lending activities will help realize the World Bank's goal of serving 100 million poor households.

IIP 1134684
University of Cincinnati; Lee

IIP 1134676
University of Michigan; Ni

IIP 1134721
Missouri University of Science and Technology; Sarangapani

The NSF Industry/University Cooperative Research Center (I/UCRC) on Intelligent
Maintenance Systems (IMS) was established in 2001. This proposal builds upon the accomplishments of the previous ten years and seeks funding to continue supporting a three campus operation among the University of Cincinnati (leading institution), the University of Michigan, and Missouri Univ. of S&T.

The Center addresses the underlying issues in machine degradation modeling and prediction as well as develops the transformational technology in advanced prognostics. Over the past 10 years, the Center has developed systematic methodology and tools that made evident impacts to a number of member companies including Toyota, G.M., Boeing, P&G, and National Instruments, amongst others. Over the next five years, the Center intends to advance the scientific base as well as to validate the developed tools to further accelerate the deployment and commercialization of the developed technologies. The center also plans to have international sites in Singapore, Brazil and Spain. In addition, the Center plans to develop spin-off companies with a compelling Marketing Plan in order to commercialize its tools through its member company, National Instruments, in 2011.

The IMS IUCRC fills an important niche to maintain industry global competiveness by continuous improvement of manufacturing effectiveness and efficiency. The center educates students and its membership through an extensive system of internship and scholar exchanges as well as international workshops and courses. IMS has developed and continues to execute an effective system for innovation and IP generation. The Center plans to develop spin-off companies with a compelling Marketing Plan in order to commercialize its tools through its member company, National Instruments, in 2011.

There are two approaches to preventing localized bottlenecks in datacenter networks: 1) building an over-provisioned network capable of supporting worse-case dataflows, or 2) providing rapid (microseconds to millisecond) on-demand provisioning of links, usually optical, between communication hotspots in the datacenter. This projects studies and prototypes the second approach via a novel interconnect design for datacenter networks (DCNs) with good fault-tolerance and scalability features, termed WaveCube. In particular, optical wavelength selective switch (WSS) technology is used to achieve cost savings while implementing multipathing and dynamic bandwidth scheduling for improved performance. The WaveCube topology is a multi-dimension cube with fiber carrying multiple wavelengths (Wavelength Division Multiplexing or WDM). WDM dramatically cuts down on the number of fibers needed in a datacenter but gives rise to a wavelength assignment problem. Thus the project will study wavelength assignment algorithms needed to provide connections via multiple WSSs taking into account fault-tolerance and performance. The project will compare WaveCube wiring complexity to that of other suggested approaches. The project will also study the performance of WaveCube-based data centers under a variety of processing loads, some derived from actual measurements and some synthetic.

Broader Impact:
The PI will create undergraduate datacenter networking courses. The PI also describes a plan to increase participation of underrepresented minorities and women in the proposed research activities and had previous demonstrations of such outreach via work with programs such as AGEP, REU, CRA CREW. The PI's are collaborating with an industrial organization.

The proposed work seeks to investigate event-based modeling to deal with high-dimensional and heterogeneous data environments in order to enhance prognostics design with adaptive control of data collection and rapid maintenance decision-making to apply data analytics to the software development process. The event-based approach is explored given its potential to reduce temporal redundancy while preserving the machine dynamics. Event-based approaches have not been fully explored for prognostics applications with continuous signal inputs, such as sensor measurements. The proposed approach represents a paradigm shift in data modeling prognostic system design and holds the potential to help address the fundamental issues of big data in the areas of volume, velocity and variety. Results will be validated using various data collected from a fleet of electric vehicles.

The outcomes of the proposed work have the potential for significant impact in the manufacturing sector in the area of prognostics and health monitoring. The resulting approach has the potential to create more efficient systems that can more rapidly adapt and respond to critical issues. The work is supported by the Industry Advisory Board as well as individual industry members of the center and has the potential to extend the centers portfolio through expansion into the area of event-driven modeling, big data reduction and mining for improved industrial efficiency. The center will involve graduate students and undergraduates in the work.

The adoption of smartphones has steadily increased in the past few years, and smartphones have become the tool with which millions of users handle confidential information, such as financial and health-related data. As a result, these devices have become attractive targets for cybercriminals, who attempt to violate the trust assumptions underlying the smartphone platform in order to compromise the security and privacy of users.

This research effort provides a novel framework to model the trust relationships between users, the smartphone platform, and the surrounding ecosystem, including smartphone apps and app markets. This model allows for the systematic exploration of trust-violation weaknesses (i.e., situations in which trust is misplaced and trust
assumptions can be violated). In a complementary fashion, the model also supports the design of security mechanisms that address the identified weaknesses (i.e., techniques to prevent, or detect and mitigate trust violations).

The results of this research have the potential of impacting the lives of millions of smartphone users, providing protection against attacks that might harm their well-being. Though this project focuses on the Android platform, its results are general and applicable to other smartphone platforms. The analysis techniques that have been developed as part of this research are made available to the public through a web portal that allows users to submit smartphone applications and obtain reports on possible trust weaknesses based on the static and dynamic analysis of the application and its interaction with other applications, the network, and other components in the Android platform.

Mobile advertising is a large and quickly growing market, driven by the movement of viewing traffic and advertising dollars from other media to mobile. In 2014, mobile worldwide ad spending is about $40 billion and it's expected to top nearly $200 billion in 2019. Among all the hundreds of thousands of app developers operating today, 90% of which offer free apps that create revenues through "in-app" advertising: they get paid when a user clicks on an ad embedded in their apps. Nowadays, these app developers have to play banner ad in their apps, which is a small-sized ad form that usually runs at the bottom of the screen, attracting littler user attention
and thus reducing developers' revenues. The proposed technology "AdsProphet" is a novel mobile ads library that is based on the observation that when user using apps, a lot of time has been wasted on waiting for the app to load remote data and such 'freezing time' has not been fully taken advantage of. AdsProphet can find these valuable windows and displays full-screen ads, which attracts user attention 25 times higher than what banner ads can achieve. This I-Corps team assumes app developers can use AdsProphet to display full-screen ads at a rate of 10% of banner ads, then AdsProphet is expected to double developers' revenue without affecting user experiences.

The key technique behind AdsProphet is a novel real-time user-perceived delay prediction system on mobile device. It's challenging to propose such a system: first, during each networking delay,only a portion of it is user-perceived delay when user can do nothing but to wait. There is no built-in event for it in any systems. This I-Corps team proposes a novel approach that is able to intelligently
detect user-perceived delay by combing techniques of network behavior manipulation, image similarity comparison algorithms and user behavior model. Second, the networking condition varies dramatically and frequently on a mobile device: users move their phones from place to place and connect to different networks such as WIFI or cellular network all the time. Moreover, the prediction process must decide whether or not to play ads in real-time; otherwise, it wastes the time to play full-screen ads and affect developers? revenues. The team first proposes an approach to predict user-perceived delay by designing a novel algorithm to efficiently estimate bandwidth as
well as round trip time to target servers, both of which serve as the most essential indicators of current networking condition. Then, to further accelerate the proposed prediction system, the team proposes a networking history model based on user's history.

Languages vary in how they use the pitch of voice to convey meaning. In a tone language, pitch is used to differentiate word meanings. For example, in Mandarin Chinese, the syllable ma said with a steady high tone means 'mother', but said with a falling tone it means 'to scold'. Tone languages represent 60%-70% of the world's 6,000 languages; about 20% of them have tones that sound very similar to each other and are difficult for non-native speakers to distinguish. More and more people around the world are learning tone languages because of globalization, international business, migration, and cross-cultural communications. In the United States, the number of college students studying Chinese alone was over 61,000 as of 2013, and the number is likely to surpass 134,000 by 2050. As the economy of the United States has become increasingly international, the demand for foreign language proficiency is stronger and stronger, and many less commonly taught tone languages such as Vietnamese and Thai have attracted a large number of learners. However, learning a tone language is challenging. Research has shown that, in general, people have difficulties distinguishing and pronouncing tones in a foreign language and that this hinders cross-cultural communication, as miscommunication arises due to mispronunciation. Thus, better learning of tone languages would help the American business community in trade with China and other areas where tone languages are spoken.

The focus of this project is the process for learning tones in Cantonese, a language with tones that are difficult for non-native speakers to distinguish. Specifically, this project aims to investigate whether non-native speakers can benefit from providing tone marks, a set of symbols to show pitch contour, in learning to distinguish and produce Cantonese tones. The research will be conducted in 3 locations: the United States, Thailand and Hong Kong, where native speakers of American English, Mandarin, Thai, and Cantonese are easily found. In the United States, native speakers of American English and native speakers of Mandarin will participate in a listening-based tone learning experiment to learn to hear and produce the contrasts of Cantonese tones with or without the help of tone marks. Although both Cantonese and Mandarin are varieties of Chinese, they have different tone systems. While Mandarin has four tones (high, mid rising, low-dipping and high falling), Cantonese has six (high, mid, low, high-rising, low-rising and low falling). Studies have shown that Mandarin speakers have difficulties learning Cantonese tones. The same experiment will be conducted in Thailand with native speakers of Thai. Native speakers of Cantonese in Hong Kong will participate in the experiment to provide a comparison case. The investigators will assess whether the addition of tone marks can result in substantial improvement in distinguishing and producing Cantonese tones by the non-native speakers. The investigators will also assess whether people from different language backgrounds exhibit different learning patterns and whether they can achieve native-like results. The findings from this research will provide insight into how foreign language learners integrate visual and auditory information during non-native sound learning. The results will also show how human beings use visual and auditory information in speech processing in general. This study will also have the potential to improve the teaching of tone languages. If tone marks are proven to be helpful, they can easily be included in teaching materials and used as a teaching method for better tone-learning outcomes.

The long-term goal of this project is to elucidate the mechanisms by which membrane trafficking is regulated in retinal pigment epithelium (RPE) cells, and to understand the role of defects in this regulation in retinal diseases including age-related macular degeneration (AMD). The RPE is responsible for the removal of daily shed photoreceptor outer segments (POS) by phagocytosis, which activates tightly controlled processes of membrane trafficking and organelle transport. In our published and preliminary studies, we found that phagocytosis activated signaling pathway mediated by the mechanistic target of rapamycin (mTOR). Under physiological conditions, mTOR activation was transient. Aging and degeneration, however, rendered mTOR activation to become prolonged after morning burst. In our newly developed murine model of RPE-specific deletion of mTORC1 upstream suppressor TSC1, constitutively high mTOR activity led to RPE and photoreceptor degeneration, likely caused by deregulated membrane trafficking and delayed POS degradation. We further identified VPS11, a key component of the membrane tethering complexes, was downregulated in TSC1-deficient RPE cells possibly due to inhibition on the transcription factor EB (TFEB). Based on those novel findings, we hypothesize that hyperactivation of mTORC1 can cause RPE and photoreceptor degeneration due to defective membrane trafficking. Enhancing TFEB-mediated expression of RPE trafficking proteins can restore the cellular functions and prevent the degenerative phenotype in retina of TSC1?RPE mice. The hypothesis will be tested by three specific aims. Aim 1 is to further characterize the retinal phenotype of mice with conditional knockout of TSC1 in the RPE. Aim 2 is to determine whether overactivation of mTOR inhibits RPE intracellular trafficking and membrane fusion by inhibiting TFEB-mediated VPS11 expression. Aim 3 is to determine whether TFEB gene therapy can prevent or rescue RPE degeneration. Results from the proposed studies are expected to further establish the critical roles of mTOR in controlling the RPE and photoreceptor interaction. Although anti-VEGF therapy has achieved unprecedented success, the majority of AMD patients have the atrophic form of the disease whose etiology is still largely unknown and treatment options are very limited. Identifying novel targets downstream of mTOR in degenerating RPE cells can facilitate the design of therapeutic strategies to prevent or at least delay the disease progression at early stage of AMD.