Physical Sciences and Mathematics Commons^™

Offline Reinforcement Learning With Causal Structured World Models, Zheng-Mao Zhu, Xiong-Hui Chen, Hong-Long Tian, Kun Zhang, Yang Yu

Machine Learning Faculty Publications

Model-based methods have recently shown promising for offline reinforcement learning (RL), aiming to learn good policies from historical data without interacting with the environment. Previous model-based offline RL methods learn fully connected nets as world-models to map the states and actions to the next-step states. However, it is sensible that a world-model should adhere to the underlying causal effect such that it will support learning an effective policy generalizing well in unseen states. In this paper, We first provide theoretical results that causal world-models can outperform plain world-models for offline RL by incorporating the causal structure into the generalization error …

5th Annual Innovation And Technology Law Conference: Deep Innovation Dives, Steven W. Bender

SITIE Symposiums

Steven W. Bender, Seattle University School of Law Professor and organizer of the SITIE Symposium series, details the history of the SITIE symposiums and the 2022 proceedings. He discusses how this year's symposium builds on themes and issues raised in previous symposiums and looks ahead to the 2023 SITIE symposium.

Legacy Lead In Urban Garden Soils: Communicating Risk And Limiting Exposure, Anna Paltseva, Zhongqi Cheng, Murray Mcbride, Maha Deeb, Sara Perl Egendorf, Peter M. Groffman

Advanced Science Research Center

Lead (Pb) exposure has long been recognized as a hazard to human health. Urban garden soils often contain elevated levels of Pb, mainly from legacy sources, which is a main barrier for urban gardening. The capacity of gardeners to access, understand, and act on scientific data related to soil contamination is also variable. This synthesis paper briefly summarizes the current scientific knowledge on soil Pb in urban gardens. Our objective is to produce clear recommendations about assessing actual risks and limiting exposure. First, we synthesize the nature and extent of soil contamination with Pb, and then describe how the bioavailability …

Synthesis, Physicochemical Characterization, And Catalytic Evaluation Of Fe3+-Containing Ssz-70 Zeolite, Christopher M. Lew, Cong Yan Chen, Gary J. Long, Fernande Grandjean, Andrew S. Ichimura, Dan Xie, Nicolás A. Grosso-Giordano, Khetpakorn Chakarawet, Howard S. Lacheen, Kurt O. Jensen, Abraham Martinez, Alexander Katz, Bi Zeng Zhan, Stacey I. Zones

Chemistry Faculty Research & Creative Works

Whereas one-dimensional, 10-membered ring zeolites are typically used for hydroisomerization, Fe3⁺-containing SSZ-70 (Fe-SSZ-70) shows remarkable isomerization selectivity for a zeolite containing 12- and partially blocked 14-membered rings, in addition to 10-membered rings. Fe-SSZ-70 was compared to Al3⁺-containing SSZ-70 (Al-SSZ-70) in constraint index and n-decane hydrocracking tests. Fe-SSZ-70 exhibited a 74% total isomer yield (64% yield of monobranched isomers and 10% cracking yield) at 85% conversion compared to 49% total isomer yield (41% yield of monobranched isomers and 36% cracking yield) for Al-SSZ-70 at the same conversion. The selectivity to isomerization is attributed to the weaker acid …

Noncanonical Amino Acid Mutagenesis In Response To Recoding Signal-Enhanced Quadruplet Codons, Yan Chen, Xinyuan He, University Of Nebraska-Lincoln, Kun Liu, Tian Gao, Wei Niu, Jiantao Guo

Department of Chemistry: Faculty Publications

While amber suppression is the most common approach to introduce noncanonical amino acids into proteins in live cells, quadruplet codon decoding has potential to enable a greatly expanded genetic code with up to 256 new codons for protein biosynthesis. Since triplet codons are the predominant form of genetic code in nature, quadruplet codon decoding often displays limited efficiency. In this work, we exploited a new approach to significantly improve quadruplet UAGN and AGGN (N = A, U, G, C) codon decoding efficiency by using recoding signals imbedded in mRNA. With representative recoding signals, the expression level of mutant proteins containing …

Magnetic-Field-Dependent Stimulated Emission From Nitrogen-Vacancy Centers In Diamond, Felix A. Hahl, Lukas Lindner, Xavier Vidal, Tingpeng Luo, Takeshi Ohshima, Shinobu Onoda, Shuya Ishii, Alexander M. Zaitsev, Marco Capelli, Brant C. Gibson, Andrew D. Greentree, Jan Jeske

Publications and Research

Negatively charged nitrogen-vacancy (NV) centers in diamond are promising magnetic field quantum sensors. Laser threshold magnetometry theory predicts improved NV center ensemble sensitivity via increased signal strength and magnetic field contrast. Here, we experimentally demonstrate laser threshold magnetometry. We use a macroscopic high-finesse laser cavity containing a highly NV-doped and low absorbing diamond gain medium that is pumped at 532 nm and resonantly seeded at 710 nm. This enables a 64% signal power amplification by stimulated emission. We test the magnetic field dependency of the amplification and thus demonstrate magnetic field-dependent stimulated emission from an NV center ensemble. This emission …

Geochronological And Geochemical Investigation Into Rhyolite Volcanism Of The High Lava Plains And Columbia River Basalt Group Provinces Of Eastern Oregon, Usa, Vanessa Marie Swenton

Dissertations and Theses

Voluminous and widespread bimodal volcanism has significantly impacted the Pacific Northwest, USA, throughout the Miocene to present day. The two primary volcanic provinces of eastern Oregon include the Columbia River Basalt Group (CRBG) province and the High Lava Plains (HLP) trend. The magmatic and tectonic processes responsible for generating bimodal volcanism, and particularly rhyolites of the ~17-15 Ma CRBG and 12-0 Ma HLP provinces has recently been a popular topic of debate. Rhyolite volcanism of the HLP province has been ascribed to either buoyancy-driven westward plume spreading or to slab rollback and mantle convection spanning from southeast Oregon to Newberry …

Collaborative Research: Surface-Specific Aerosol Chemistry: Direct Observations, Kinetics, And Environmental Impact, Yi Rao

Funded Research Records

No abstract provided.

A Raft To Coastal Resilience: Odu Researchers Collaborate To Help Rural Communities Combat Flooding Impacts, News @ Odu

News Items

No abstract provided.

Monotonicity Properties Of Functionals Under Ricci Flow On Manifolds Without And With Boundary, Paul Bracken

School of Mathematical & Statistical Sciences Faculty Publications

In this paper, the idea of the Ricci flow is introduced and its significance and importance to related problems in mathematics had been discussed. Several functionals are defined and their behavior is studied under Ricci flow. A unique minimizer is shown to exist for one of the functionals. This functional evaluated at the minimizer is strictly increasing. The results for the first functional considered are extended to manifold with boundary. Finally, two physically motivated examples are presented.

All-Sky, All-Frequency Directional Search For Persistent Gravitational-Waves From Advanced Ligo's And Advanced Virgo's First Three Observing Runs, R. Abbott, T. D. Abbott, F. Acernese, K. Ackley, C. Adams, Teviet Creighton, Mario C. Diaz, Francisco Llamas, Soma Mukherjee, Volker Quetschke, Wenhui Wang

Physics & Astronomy Faculty Publications

We present the first results from an all-sky all-frequency (ASAF) search for an anisotropic stochastic gravitational-wave background using the data from the first three observing runs of the Advanced LIGO and Advanced Virgo detectors. Upper limit maps on broadband anisotropies of a persistent stochastic background were published for all observing runs of the LIGO-Virgo detectors. However, a broadband analysis is likely to miss narrowband signals as the signal-to-noise ratio of a narrowband signal can be significantly reduced when combined with detector output from other frequencies. Data folding and the computationally efficient analysis pipeline, PyStoch, enable us to perform the radiometer …

Using Hospital Bed Capacity Prediction During Covid-19 To Determine Feature Importance, Helene Barrera, Justin Ehly, Blake Freeman, Chris Papesh, Brad Blanchard

SMU Data Science Review

The COVID-19 pandemic has exacerbated existing hospital capacity limitations in the United States, causing hospitals in certain regions to hit maximum capacity. The purpose of this study is to investigate key features of COVID-19 related admissions to help create a higher level of public understanding and help guide healthcare management professionals and governments when considering preventive measures. The introduction of preventative measures and new regulations during the pandemic have led to the generation of multiple types of models and feature selection methods in the field of Machine Learning that are increasingly complicated. This study focuses on the exploration of feature …

A Machine Learning Approach To Revenue Generation Within The Professional Hair Care Industry, Alexander K. Sepenu, Linda Eliasen

SMU Data Science Review

The cosmetic and beauty industry continues to grow and evolve to satisfy its patrons. In the United States, the industry is heavily science-driven, innovative, and fast-paced, suggesting that to remain productive and profitable, companies must seek smart alternatives to their current modus operandi or risk losing out on this multi-billion-dollar industry to fierce competition. In this paper, the authors seek to utilize machine learning models such as clustering and regression to improve the efficiency of current sales and customer segmentation models to help HairCo (pseudonym for confidentiality), a professional hair products manufacturer, strategize their marketing and sales efforts for revenue …

Analysis Of The Electric Power Outage Data And Prediction Of Electric Power Outage For Major Metropolitan Areas In Texas Using Machine Learning And Time Series Methods, Renfeng Wang, Venkata Leela 'Mg' Vanga, Zachary B. Zaiken, Jonathan Bennett

SMU Data Science Review

With growing energy usage, power outages affect millions of households. This case study focuses on gathering power outage historical data, modifying the data to attach weather attributes, and gathering ERCOT energy market conditions for Dallas-Fort Worth and Houston metropolitan areas of Texas. The transformed data is then analyzed using machine learning algorithms including, but not limited to, Regression, Random Forests and XGBoost to consider current weather and ERCOT features and predict power outage percentage for locations. The transformed data is also trained using time series models and serially correlated models including Autoregression and Vector Autoregression. This study also focuses on …

Web Page Multiclass Classification, Brian Gaither, Antonio Debouse, Catherine Huang

SMU Data Science Review

As the internet age evolves, the volume of content hosted on the Web is rapidly expanding. With this ever-expanding content, the capability to accurately categorize web pages is a current challenge to serve many use cases. This paper proposes a variation in the approach to text preprocessing pipeline whereby noun phrase extraction is performed first followed by lemmatization, contraction expansion, removing special characters, removing extra white space, lower casing, and removal of stop words. The first step of noun phrase extraction is aimed at reducing the set of terms to those that best describe what the web pages are about …

Anomaly Detection Methods To Improve Supply Chain Data Quality And Operations, Ana E. Glaser, Jake P. Harrison, David Josephs

SMU Data Science Review

Supply chain operations drive the planning, manufacture, and distribution of billions of semiconductors a year, spanning thousands of products across many supply chain configurations. The customizations span from wafer technology to die stacking and chip feature enablement. Data quality drives efficiency in these processes and anomalies in data can be very disruptive, and at times, consequential. Developing preventative measures that automate the detection of anomalies before they reach downstream execution systems would result in significant efficiency gain for the organization. The purpose of this research is to identify an effective, actionable, and computationally efficient approach to highlight anomalies in a …

Adjusting Community Survey Data Benchmarks For External Factors, Allen Miller, Nicole M. Norelli, Robert Slater, Mingyang N. Yu

SMU Data Science Review

Abstract. Using U.S. resident survey data from the National Community Survey in combination with public data from the U.S. Census and additional sources, a Voting Regressor Model was developed to establish fair benchmark values for city performance. These benchmarks were adjusted for characteristics the city cannot easily influence that contribute to confidence in local government, such as population size, demographics, and income. This adjustment allows for a more meaningful comparison and interpretation of survey results among individual cities. Methods explored for the benchmark adjustment included cluster analysis, anomaly detection, and a variety of regression techniques, including random forest, ridge, decision …

The Importance Of Understanding And Developing Identification Techniques In Wildlife Crime, Savannah Nguyen

D.U.Quark

Wildlife crime continues to grow annually and globally, impacting several species and ecosystems. New advancements of technologies and techniques can track criminals and aid the affected victims. Highlighting the complexity of conservation and the development of identification techniques helps tackle this widespread dilemma. New developing techniques in wildlife forensics can differentiate an animal between wild and poached to pave the way for further advancement in understanding wildlife crimes. Hence, though the wildlife forensics field is still new, emphasizing the need for intricate identification techniques can help save threatened species.

Empowering You: Environment, Water, Rivers And You, League Of Women Voters Of The Greater Dayton Area, David Bodary

Rivers Institute Publications

Host David Bodary talks about "Environment, Water, Rivers and You" with guest Leslie King, director of the Rivers Institute at the University of Dayton Fitz Center for Leadership in Community and University of Dayton junior Tessa O'Halloran, a River Steward.

Preliminary Planning For Mars Sample Return (Msr) Curation Activities In A Sample Receiving Facility (Srf), Kimberly T. Tait, Francis M. Mccubbin, Caroline L. Smith, Carl B. Agee, Henner Busemann, Barbara Cavalazzi, Viciane Debaille, Aurore Hutzler, Tomohiro Usui, Gerhard Kminek, Michael A. Meyer, David W. Beaty, Brandi L. Carrier, Timothy Haltigin, Lindsay E. Hays, Charles S. Cockell, Daniel P. Glavin, Monica M. Grady, Ernst Hauber, Bernard Marty, Lisa M. Pratt, Aaron B. Regberg, Alvin L. Smith, Roger E. Summons, Timothy D. Swindle, Nicholas J, Tosca, Arya Urdry, Michael A. Velbel, Meenakshi Wadhwa, Frances Westall, Maria-Paz Zorzano

Geoscience Faculty Research

The Mars Sample Return Planning Group 2 (MSPG2) was tasked with identifying the steps that encompass all the curation activities that would happen within the MSR Sample Receiving Facility (SRF) and any anticipated curation-related requirements. An area of specific interest is the necessary analytical instrumentation. The SRF would be a Biosafety Level-4 facility where the returned MSR flight hardware would be opened, the sample tubes accessed, and the martian sample material extracted from the tubes. Characterization of the essential attributes of each sample would be required to provide enough information to prepare a sample catalog used in guiding the preparation …

Science And Curation Considerations For The Design Of A Mars Sample Return (Msr) Sample Receiving Facility (Srf), Brandi L. Carrier, David W. Beaty, Aurore Hutzler, Alvin L. Smith, Gerhard Kminek, Michael A. Meyer, Timothy Haltigin, Lindsey E. Hays, Carl B. Agee, Henner Busemann, Barabara Cavalazzi, Charles S. Cocksell, Vinciane Debaille, Daniel P. Glavin, Monica M. Grady, Ernst Hauber, Bernard Marty, Francis M., Lisa M. Pratt, Aaron B. Regberg, Caroline L. Smith, Roger E. Summons, Timothy D. Swindle, Kimberly T. Taiit, Nocholas J. Tosca, Arya Urdry, Tomohiro Usui, Michael A. Velbel, Meenakshi Wadhwa, Frances Westall, Maria-Paz Zorzano

Geoscience Faculty Research

The most important single element of the “ground system” portion of a Mars Sample Return (MSR) Campaign is a facility referred to as the Sample Receiving Facility (SRF), which would need to be designed and equipped to receive the returned spacecraft, extract and open the sealed sample container, extract the samples from the sample tubes, and implement a set of evaluations and analyses of the samples. One of the main findings of the first MSR Sample Planning Group (MSPG, 2019a) states that “The scientific community, for reasons of scientific quality, cost, and timeliness, strongly prefers that as many sample-related investigations …

The Scientific Importance Of Returning Airfall Dust As A Part Of Mars Sample Return (Msr), Monica M. Grady, Roger E. Summons, Timothy D. Swindle, Frances Westall, Gerhard Kminek, Michael A. Meyer, David W. Beaty, Brandi L. Carrier, Timothy Haltigin, Lindsay E. Hays, Carl B. Agee, Henner Busemann, Barabara Cavalazzi, Charles S. Cockell, Vinciane Debaille, Daniel P. Galvin, Ernst Hauber, Aurore Hutzler, Bernard Marty, Francis M. Mccubbin, Lisa M. Pratt, Aaron B, Regberg, Alvin L. Smith, Caroline L. Smith, Kimberly T. Tait, Nicholas J. Tosca, Arya Udry, Tomohiro Usui, Michael A. Velbel, Meenakshi Wadhwa, Maria-Paz Zorzano

Geoscience Faculty Research

Dust transported in the martian atmosphere is of intrinsic scientific interest and has relevance for the planning of human missions in the future. The MSR Campaign, as currently designed, presents an important opportunity to return serendipitous, airfall dust. The tubes containing samples collected by the Perseverance rover would be placed in cache depots on the martian surface perhaps as early as 2023–24 for recovery by a subsequent mission no earlier than 2028–29, and possibly as late as 2030–31. Thus, the sample tube surfaces could passively collect dust for multiple years. This dust is deemed to be exceptionally valuable as it …

Time-Sensitive Aspects Of Mars Sample Return (Msr) Science, Nicholas J. Tosca, Carl B. Agee, Charles S. Cockell, Daniel P. Glavin, Aurore Hutzler, Bernard Marty, Francis M. Mccubbin, Aaron B. Regberg, Michael A. Velbel, Gerhard Kminek, Michael A. Meyer, David W. Beaty, Brandi L. Carrier, Timothy Haltigin, Lindsay E. Hays, Henner Baumann, Barbara Cavalazzi, Vinviane Debaille, Monica M. Grady, Ernst Hauber, Lisa M. Pratt, Alvin L. Smith, Caroline L. Smith, Roger E. Summons, Timothy D. Swindle, Kimberly T. Tait, Arya Udry, Tomohiro Usui, Meenakshi Wadhwa, Frances Westall, Maria-Paz Zorzano

Geoscience Faculty Research

Samples returned from Mars would be placed under quarantine at a Sample Receiving Facility (SRF) until they are considered safe to release to other laboratories for further study. The process of determining whether samples are safe for release, which may involve detailed analysis and/or sterilization, is expected to take several months. However, the process of breaking the sample tube seal and extracting the headspace gas will perturb local equilibrium conditions between gas and rock and set in motion irreversible processes that proceed as a function of time. Unless these time-sensitive processes are understood, planned for, and/or monitored during the quarantine …

Planning Implications Related To Sterilization-Sensitive Science Investigations Associated With Mars Sample Return (Msr), Michael A. Velbel, Charles S. Cockell, Daniel P. Glavin, Bernard Marty, Aaron B. Regberg, Alvin L. Smith, Nicholas J. Tosca, Meenakshi Wadhwa, Gerhard Kminek, Michael A. Meyer, David W. Beaty, Brandi Lee Carrier, Timothy Haltigin, Lindsay E. Hays, Carl B. Agee, Henner Busemann, Barbara Cavalazzi, Vinciane Debaille, Monica M. Grady, Ernst Hauber, Aurore Hutzler, Francis M. Mccubbin, Lisa M. Pratt, Caroline L. Smith, Roger E. Summons, Timothy D. Swindle, Kimberly T. Tait, Arya Udry, Tomohiro Usui, Frances Westall, Maria-Paz Zorzano

Geoscience Faculty Research

The NASA/ESA Mars Sample Return (MSR) Campaign seeks to establish whether life on Mars existed where and when environmental conditions allowed. Laboratory measurements on the returned samples are useful if what is measured is evidence of phenomena on Mars rather than of the effects of sterilization conditions. This report establishes that there are categories of measurements that can be fruitful despite sample sterilization and other categories that cannot. Sterilization kills living microorganisms and inactivates complex biological structures by breaking chemical bonds. Sterilization has similar effects on chemical bonds in non-biological compounds, including abiotic or pre-biotic reduced carbon compounds, hydrous minerals, …

Final Report Of The Mars Sample Return Science Planning Group 2 (Mspg2), Michael A. Meyer, Gerhard Kminek, David W. Beaty, Brandi L. Carrier, Timothy Haltigin, Lindsay E. Hays, Carl B. Agree, Henner Busemann, Barbara Cavalazzi, Charles S. Cockell, Vinciane Debaille, Daniel P. Glavin, Monica M. Grady, Ernst Hauber, Aurore Hutzler, Bernard Marty, Francis M. Mccubbin, Lisa M. Pratt, Aaron B. Regberg, Alvin L. Smith, Carolina L. Smith, Roger E. Summons, Timothy D. Swindle, Kimberly T. Tait, Nicholas J. Tosca, Arya Udry, Tomohiro Usui, Michael A. Velbel, Meensakshi Wadhwa, Frances Westall, Maria-Paz Zorzano

Geoscience Faculty Research

The Mars Sample Return (MSR) Campaign must meet a series of scientific and technical achievements to be successful. While the respective engineering responsibilities to retrieve the samples have been formalized through a Memorandum of Understanding between ESA and NASA, the roles and responsibilities of the scientific elements have yet to be fully defined. In April 2020, ESA and NASA jointly chartered the MSR Science Planning Group 2 (MSPG2) to build upon previous planning efforts in defining 1) an end-to-end MSR Science Program and 2) needed functionalities and design requirements for an MSR Sample Receiving Facility (SRF). The challenges for the …

Rationale And Proposed Design For A Mars Sample Return (Msr) Science Program, Timothy Haltigin, Ernst Hauber, Gerhard Kminek, Michael A. Meyer, Carl B. Agee, Henner Busemann, Brandi L. Carrier, Daniel P. Glavin, Lindsay E. Hays, Bernard Marty, Lisa M. Pratt, Arya Udry, Maria-Paz Zorzano, David W. Beaty, Barbara Cavalazzi, Charles S. Cockell, Vinciane Debaille, Monica M. Grady, Aurore Hutzler, Francis M. Mccubbin, Aaron B. Regberg, Alvin L. Smith, Caroline L. Smith, Roger E. Summons, Timothy D. Swindle, Kimberly T. Tait, Nicholas J. Tosca, Tomohiro Usui, Michael A. Velbel, Meenakshi Wadhwa, Frances Westall

Geoscience Faculty Research

The Mars Sample Return (MSR) Campaign represents one of the most ambitious scientific endeavors ever undertaken. Analyses of the martian samples would offer unique science benefits that cannot be attained through orbital or landed missions that rely only on remote sensing and in situ measurements, respectively. As currently designed, the MSR Campaign comprises a number of scientific, technical, and programmatic bodies and relationships, captured in a series of existing and anticipated documents. Ensuring that all required scientific activities are properly designed, managed, and executed would require significant planning and coordination. Because there are multiple scientific elements that would need to …

Spotlight Report #6: Proffering Machine-Readable Personal Privacy Research Agreements: Pilot Project Findings For Ieee P7012 Wg, Noreen Y. Whysel, Lisa Levasseur

Publications and Research

What if people had the ability to assert their own legally binding permissions for data collection, use, sharing, and retention by the technologies they use? The IEEE P7012 has been working on an interoperability specification for machine-readable personal privacy terms to support this ability since 2018. The premise behind the work of IEEE P7012 is that people need technology that works on their behalf—i.e. software agents that assert the individual’s permissions and preferences in a machine-readable format.

Thanks to a grant from the IEEE Technical Activities Board Committee on Standards (TAB CoS), we were able to explore the attitudes of …

Investigation Of The Association Of Exposures To Fire-Related Hazards With Pulmonary Function Of Firefighters, David G. Goldfarb

Dissertations and Theses

Background. Firefighters are habitually exposed to hazardous toxicants which place them at an elevated risk for numerous adverse health outcomes. An example of this is the associations observed in other works between inhalation of combustion byproducts from urban structural fires and both acute and chronic pulmonary dysfunction. To-date, the characterization of firefighters’ exposures to dangerous chemicals in smoke from non-wildfire incidents, both directly through personal monitoring and indirectly from work-related records is scarce. Prior works investigating the association between routine firefighting and pulmonary function have relied on crude metrics such as years of service and numbers of responses to …

Methodologies For Quantum Circuit And Algorithm Design At Low And High Levels, Edison Tsai

Dissertations and Theses

Although the concept of quantum computing has existed for decades, the technology needed to successfully implement a quantum computing system has not yet reached the level of sophistication, reliability, and scalability necessary for commercial viability until very recently. Significant progress on this front was made in the past few years, with IBM planning to create a 1000-qubit chip by the end of 2023, and Google already claiming to have achieved quantum supremacy. Other major industry players such as Intel and Microsoft have also invested significant amounts of resources into quantum computing research.

Any viable computing system requires both hardware and …

A Bayesian Latent Scale Model For Multivariate Longitudinal Data, Kruti Pandya

Dissertations and Theses

In order to understand the entire course of slow progressing diseases like Alzheimer's dementia or multiple sclerosis, it is essential to characterize long term disease dynamics from a healthy stage to a late disease stage. Cohort studies typically recruit subjects at different stages of the disease and then follow them for a relatively short period of time. In this dissertation, we propose a novel Bayesian nonlinear mixed effects model with latent time scale to characterize long term disease dynamics using the observed short term longitudinal data from cohort studies without relying on clinical diagnosis. This model can accommodate noisy longitudinal …