Montclair State University is a public university located in the Upper Montclair section of Montclair, the Great Notch area of Little Falls, and the Montclair Heights section of Clifton, in the U.S. state of New Jersey. As of October 2014, there were 20,022 total enrolled students: 15,885 undergraduate students and 4,137 graduate students. Montclair State currently sizes at approximately 500 acres , inclusive of the New Jersey School of Conservation, which attracts students statewide. More than 250 majors, minors and concentrations are offered.The university is a member of such professional organizations as the American Association of State Colleges and Universities, American Council on Education, Association of American Colleges and Universities and the Council of Graduate Schools. Wikipedia.
Montclair State University | Date: 2015-03-30
Provided herein is a method, a programmed computer and an article of manufacture for predicting a prenatal, neonatal, obstetric or childhood clinical event, disease or disorder, as well as a method for generating in-utero fetal and placental growth curves, using a continuous recursive algorithm housed in a computer and data periodically collected during pregnancy.
Agency: NSF | Branch: Standard Grant | Program: | Phase: LAW AND SOCIAL SCIENCES | Award Amount: 166.66K | Year: 2017
Despite widespread dissemination of best-practice standards for conducting forensic interviews, many jurisdictions lack the expertise to skillfully investigate crimes involving child witnesses. An efficient way to ensure that all jurisdictions have access to highly trained child interviewers is to conduct remote (live-streaming video) forensic interviews. Remote interviewing could reduce investigative response time, spare investigative resources, and accelerate case disposition. However, the ability of remote interviewing to elicit eyewitness evidence from children has not been sufficiently tested and, therefore, will certainly prompt challenges regarding children?s testimonial reliability. The current project is a comprehensive and theoretically grounded evaluation of the effectiveness of remote interviewing of child witnesses. Results will be disseminated to scientists and forensic professionals through publications and presentations, thereby informing policies and guidelines for the use of remote forensic interviews with children. Because remote interviewing increases access to specialized expertise, project results will also impact how children are questioned by electronic means in non-forensic contexts. The project will provide research training to dozens of students at two research sites and promote greater awareness of evidence-based practice through outreach to practitioners who work with child witnesses.
Using an established paradigm that produces salient touching experiences, individual children at two sites (ages 4 to 8 years) will be told that a male assistant can no longer touch their skin when he delivers a germ education program. The assistant will touch each child once and realize an impending mistake before he completes a second touch. Afterward, children will hear a story from their parents that contains misinformation about the experience, including narrative about a nonexperienced touch. During interviews conducted in traditional face-to-face or remote formats, children will answer questions about the germ education event and answer a series of questions that tests their ability to distinguish experienced from suggested events. By comparing the completeness and accuracy of children?s testimonies across formats, this study will determine whether remote interviewing elicits testimony that is comparable in quality to the testimony elicited by face-to-face interviewing. Measures of behavioral inhibition and executive function will determine whether remote interviewing is beneficial for children who are behaviorally inhibited or contraindicated for typically-developing children who have poor cognitive control.
Agency: NSF | Branch: Standard Grant | Program: | Phase: Systematics & Biodiversity Sci | Award Amount: 136.45K | Year: 2016
Combining data from living species and the fossil record provides a rich perspective for understanding the evolutionary processes responsible for generating the biodiversity observed in nature. Although methods for combining these data have made significant advances, these approaches still do not consider the completeness and sampling of the fossil record or the geographical distributions of living and fossil species. For this project, the investigators will integrate statistical models for describing how fossils are sampled over time and where species are found. These models for estimating species relationships will be developed in widely used software packages, making them broadly accessible to other researchers. These new methods will be tested using both simulated and real datasets. Specifically, two vertebrate groups with rich fossil records will be studied: penguins and crocodyliforms (crocodiles, alligators, gharials, and extinct relatives). This work will help to uncover how rates of speciation and extinction have changed over time for these species. The methods developed as part of this project will be taught in workshops for evolutionary biologists. Additionally, results from analyses of data from living and fossil penguins will be contributed to a public museum exhibit at the Bruce Museum in Greenwich, CT.
In recent years, advances in phylogenetic inference methods have provided ways to integrate fossil and extant taxa. These approaches allow simultaneous estimation of the divergence times and phylogenetic relationships of extant and fossil species, thus making full use of morphological and temporal data, rather than just molecular sequence data from living species. Approaches combining fossil and extant taxa have opened the door for fully integrative phylogenetic methods that use more sources of biological data, including stratigraphy, sampling, and biogeography. Thus, there is a need for comprehensive statistical models and methods that accommodate this information. The investigators will develop new, Bayesian statistical models, extensions of stochastic birth-death processes, that will integrate information about the fossil record and biogeography for use in phylogenetic methods that consider both extant and fossil taxa. The new models will be implemented in the program RevBayes. The performance and adequacy of new and previously described models will be evaluated using simulated and empirical datasets. New methods will be used to investigate macroevolutionary patterns in two exemplar clades: Sphenisciformes (penguins) and Crocodyliformes, addressing key hypotheses about phylogenetic relationships, lineage diversification, and biogeography.
Agency: NSF | Branch: Standard Grant | Program: | Phase: ENVIRONMENTAL ENGINEERING | Award Amount: 320.18K | Year: 2016
The proposed work leverages a recent key discovery, the existence of highly functional contaminated soils, that is, where bacterial communities have adapted to the contaminants. Liberty State Park, a brownfield site in Northern New Jersey, is one example. Understanding the underlying science of enhanced biochemical function within a contaminated site is an essential step in maximizing restoration potential. The goal of this project is to better understand the high enzymatic activity which has developed and apply this knowledge to optimize functional soil treatment and inform engineering solutions in a cost effective, sustainable manner
First, finding the mechanistic basis for the high enzymatic activities will be a novel and exciting contribution to ecological engineering with far reaching implications for the restoration of contaminated sites. Second, the proposed experiments will use a factorial design to determine whether: 1. the abiotic properties of the soil itself, or, 2. the microbial communities of the soils are more important to improved function. Third, this work employs targeted microbial communities originating from contaminated, undisturbed soils, in soil restoration. Measurements of extracellular enzyme activity serve as a proxy for overall soil health and function. The specific objectives of this project are: 1. Elucidate the factors driving enzymatic activity in contaminated soil by studying contaminated soils with unusually high enzyme activity in comparison to less functional, contaminated soils, and, 2. Determine the ability of microbial inocula to improve the functionality of contaminated, low functioning soils, and characterize the time course of functional transformation. Understanding the mechanisms behind the unusually high enzymatic activities will guide efforts to find functional and metal-resistant microbial communities. This will facilitate soil seeding and have direct applications to a highly cost-effective approach in restoration ecology and phytoremediation. The findings of this research and the predictive model will inform practitioners and engineers about successful microbial community compositions and time to functional transformation. The PIs will use the opportunity to extend their mentorship and expertise in training to the Liberty Science Center, situated next to Liberty State Park. As part of this grant, the PIs will work with education colleagues at the Science Center to develop workshops and outreach activities for student visitors.
Agency: NSF | Branch: Standard Grant | Program: | Phase: MAJOR RESEARCH INSTRUMENTATION | Award Amount: 497.06K | Year: 2016
This project, acquiring a high-performance computing (HPC) cluster covering areas in computational science, aims to support a wide range of current and emerging investigations and educational activities that include: 1. Development and testing of novel approaches for spectral image processing; 2. Realistic simulation of magnetic fluid flows to model magnetic drug targeting and other biomedical applications; 3. Functional genomics analysis of DNA sequence data; 4. Computational identification of ligands bind to proteins; 5. Simulation of chemical reaction pathways important in the chemistry of air pollution; 6. Development of simulated censorship systems as a test bed for censorship circumvention; 7. Automatic machine recognition of idiomatic and deceptive language; 8. Inference of subsurface ocean waves from seismic data; 9. Modeling and simulation shoreline evolution; and 10. Modeling, simulation and control of stochastic dynamics.
As shown by the extent and diversity of the projects, the use of HPC is an integral part of the overall research activity at the institution. The instrumentation is specified to meet the critical computing needs of the participating investigators? research programs and the number and diversity of projects included is expected to ensure full and efficient use of the system to be acquired which includes a set of identical nodes with infiniband connectivity for low-latency, highly parallel computing, as well as a large-memory with a shared file server all organized as a single, integrated system that will serve as a resource and focal point for HPC computational science for faculty, their research students, and collaborators at other institutions. Thus, the HPC capacity acquired will leverage and magnify the merit in each of these respective research programs. The acquisition of computing capacity, not otherwise available, that matches current and future challenges, is expected to be transformative in moving each line of research to the leading-edge of its respective field. Moreover, these advances have applications to partner disciplines and related technological developments. By providing a common focus, the HPC equipment stimulates the coalescence of a cross-cutting, multidisciplinary, and integrated Computational Research Group, composed of researchers from various disciplines (including computer science, mathematical sciences, biological sciences, chemistry, earth and environmental sciences, linguistics, and social sciences) as well as the creation of a computational science learning environment that includes undergraduate and graduate students.
Agency: NSF | Branch: Standard Grant | Program: | Phase: IUSE | Award Amount: 299.70K | Year: 2016
The goal of Creativity in Mathematics and Science (CMS) is to develop and test an innovative model of instruction that highlights the role of creative thought in science, technology, engineering, and mathematics (STEM), and that engages students in thoughtful and creative approaches to scientific and mathematical practices. This project will (i) develop course modules on creative thinking for science and non-science majors, (ii) provide a two-year engaged student experience for CMS Scholars, (iii) conduct research on student achievement and changes to students perceptions about STEM learning, and (iv) transfer the successful elements to local high schools and a community college. All elements of the CMS project are collaborative and interdisciplinary. For example, students will work in teams with mentors from multiple disciplines, and faculty members will collaborate with leaders from high schools, community colleges, and industry to develop, deliver, and transfer effective instructional practices. The project will to add to the literature on the role of creative instruction in effective undergraduate STEM education.
CMS will encourage the rethinking of undergraduate STEM education by deliberately exposing students to the creative explorations that drive the STEM fields. The project will address the documented need to provide students with authentic learning experiences and to have them engage in activities that model the work of STEM professionals. Students will experience the natural creativity in STEM and become more science-literate citizens. The development, implementation, assessment, and refinement cycle will allow for the identification of the successful elements of the project, thus informing its adoption in other STEM disciplines and academic settings. The project and its outcomes will contribute to the research on teaching and learning in STEM by introducing new learning materials and teaching techniques, disseminating results of learning under this innovation, and generating evidence regarding the role of creativity as a motivator in undergraduate STEM education.
Agency: NSF | Branch: Continuing grant | Program: | Phase: S-STEM:SCHLR SCI TECH ENG&MATH | Award Amount: 604.00K | Year: 2015
This National Science Foundation (NSF) Scholarships in Science, Technology, Engineering, and Mathematics (S-STEM) project at Montclair State University in New Jersey will provide scholarships for talented students with demonstrated financial need pursuing Master of Science degrees in Chemistry, and Biochemistry. The program is called Opening Pathways, Engaging, and Networking in Chemistry in Northern New Jersey (OPEN-NJ). The program will provide pathways for supporting Biology B.S. graduates to transition into M.S. degree programs in Chemistry and Biochemistry. Program graduates are expected to contribute to the continued success of the chemical, pharmaceutical and biotechnology industries located in Northern New Jersey. Scholarships for academically strong students, who may not otherwise be able to afford college, will increase the number of graduates prepared to support national, regional, and local companies. The success of the program will produce a well-trained workforce that will contribute to the economic growth of New Jersey and the nation.
OPEN-NJ will award approximately 51 yearly scholarships to students admitted to the M.S. programs in Chemistry, Chemistry with a concentration in Biochemistry, and Pharmaceutical Biochemistry. The program will serve as a model for enabling Biology B.S. graduates to transition into M.S. degree programs in Chemistry and Biochemistry. Many recent biology B.S. graduates would like to pursue M.S. degrees in Chemistry or Biochemistry at MSU. However transitioning to Chemistry and Biochemistry from other STEM fields is difficult because these are fields where topics build on prior knowledge and a solid foundation is critical for success. The OPEN-NJ program creates a solution to this problem by creating a practical and easy-to-adopt track for biology graduates (and other related majors) to enter Chemistry and Biochemistry M.S. programs. OPEN-NJ will offer students support services including review of general chemistry during summer orientation, dedicated tutoring services, dedicated faculty mentors, and a learning community. OPEN-NJ program will enable students to move between disciplines and in the process come to chemistry with a new perspective, understand applications and make connections, and apply what they learn. Students will learn about careers and explore their interests via weekly exchanges with a mentor. Students will take part in a set of workshops on resume preparation, interviews, and on different aspects of professional skills development. The lessons learned, as determined through the program evaluation, will provide useful data for other field-to-field transitions within STEM. Effective practices that emerge from the program evaluation data will be disseminated widely to the STEM education community and help increase widespread understanding of the attributes and practices of successful student scholarship and support programs.
Agency: NSF | Branch: Continuing grant | Program: | Phase: LIGO RESEARCH SUPPORT | Award Amount: 57.45K | Year: 2017
The detections of gravitational waves in 2015 by the NSF-funded Laser Interferometer Gravitational-wave Observatory (LIGO) have confirmed the last prediction of Einsteins theory of general relativity and opened up a new era in observational astronomy and fundamental physics. Future observations by LIGO and its international partners will discover many more merging black hole pairs. These observations will help us understand how these systems formed and will let us test general relativity in the ultra-strong gravity region produced by these coalescing black holes. The work funded here is primarily concerned with: (i) improving our ability to model the signals LIGO will detect from black hole mergers; (ii) developing techniques to model and detect a component of gravitational-wave signals that can shed light on the nonlinear nature of gravity, the matter and energy ejected by supernovae, or the dynamics of compact stars that experience close flybys; and (iii) exploring science objectives that could be achieved by the next generation of gravitational-wave experiments. The educational components of this work include: (i) training undergraduate and masters degree students at a regional public university serving a wide range of socio-economic backgrounds; (ii) developing and making available instructional materials and hands-on kits that teach LIGO science; (iii) engaging the broader public through lectures, outreach exhibits, and the continued development of the Sounds of Spacetime website (which explains gravitational-wave science via an analogy with sound waves).
The science objectives of this work are focused on (i) improving models of merging binary systems with elliptical (eccentric) orbits and (ii) the gravitational-wave memory effect. Elliptical binaries: LIGO currently has many signal models to analyze circular-orbit binaries, but few for elliptical binaries. The group will develop new signal models to handle eccentric orbits and investigate the implications for parameter estimation and testing general relativity. If present in LIGO signals, eccentricity will have implications for compact object binary formation models and constraining possible deviations from general relativity (which could be biased if eccentricity is neglected). Memory effect: The memory effect refers to a non-oscillatory component of the gravitational-wave signal. It is produced by gravitational two-body scattering, ejected matter or neutrinos in supernovae, and nonlinear interactions during black hole mergers. The effort will improve existing models of the memory effect. It will also develop, test, and execute a search for memory bursts using LIGO data. This will broaden the class of signals that LIGO investigates and could provide a new way to test general relativity.
Agency: NSF | Branch: Standard Grant | Program: | Phase: COMPUTATIONAL MATHEMATICS | Award Amount: 98.25K | Year: 2016
Advances in the synthesis of Ferrofluids (engineered fluids that respond to magnetic fields and have a number of well-established industrial applications) have increased the scope of potential applications of these fluids to new areas. Emerging applications of ferrofluids include: magnetic targeting of drugs, cell sorting in biomedical systems and magnetically driven contaminant removal. In each of these applications the use of ferrofluids enables new techniques that depend on the use of magnetic fields for remote control of the ferrofluid. However, the realization of such technologies is hampered by complexities in the simulation of these systems for further development and design. The proposed research program includes the development of effective, robust computational tools that will enable such simulations. In particular, the computing codes will include the particular magnetic physics of ferrofluids as well as the forces resulting from the magnetic fields, which serve as the means of control in these applications. The development of these effective simulation tools will support and accelerate innovation in these emerging technologies. Moreover, the proposed program of code development, simulations and integrated physical experiments will serve as a proof-of-concept for the inclusion of realistic multiphysics fluid simulations for complex scientific and engineering applications. The proposed research program will involve undergraduate and masters-degree students in leading-edge research, including students who are members of groups under-represented in STEM disciplines such as women and first-generation college students.
In magnetic drug targeting, a ferrofluid whose constituent nanoparticles have been functionalized to carry theraputic drugs is directed to a tumor or other localized site (e.g., in the eye); sorting of(nonmagnetic) biological cells by immersion in a ferrofluid so that the force of an applied magnetic field depends on cell size; purification of a polluted fluid by adsorption of contaminants to magnetic nanoparticles, which are then separated from the fluid by magnetic forces. However, advances in these applications are stymied by the complex, multi-scale and multi-physics nature of the fluid-dynamical systems in which they occur. In particular, because contemporary fluid-dynamics codes are not designed to incorporate the additional physics of magnetic-fluid systems, effective simulation with these codes is difficult. The proposal describes a plan to develop and test a new parallel, multi-phase code for fully three-dimensional flows. This project will lead to a flexible and efficient, multi-phase magnetic-fluid simulation code that is fully three-dimensional and parallelized for high-performance computing. Hence, the code will enable realistic simulations relevant to the significant applications addressed. Specifically, in order to address the above-noted applications, the code will model and simulate flows with dynamic interfaces between the ferrofluid and other fluids. Moreover, the code will implement models of viscosity effects (magnetoviscosity) as well as driving forces that result from applied magnetic fields (magnetophoresis) in a flexible manner that simplifies adjustment and update of the models.
Agency: NSF | Branch: Standard Grant | Program: | Phase: IUSE | Award Amount: 300.00K | Year: 2016
This project will address the barriers that first-generation students experience in college. There is a critical need to expand the existing research to better understand how first-time, first-generation students will be enabled to enter and succeed as STEM majors. The project is unique in that it will integrate several interconnected, research-based, effective practices aimed at the specific needs of first-generation students in the sciences. Specifically the project will (1) convene a group of science professors who will work together to design and teach a science literacy course aimed at teaching not just what science is, but also why it matters to society; (2) create a group of peer mentors and mentoring activities aimed at fostering a supportive environment within which first-generation students can express their needs and have them be addressed; and (3) work with the campus advising office to select students to participate in the program and to provide additional support services such as extensive career counseling. Participants in each of these three groups will also meet with each other on a continual basis to monitor student success and the success of the different approaches taken.
The program that is envisioned has two specific objectives: (1) to increase science literacy of undeclared first-generation, first-year college students and (2) to encourage and enable students to select and successfully embark on STEM majors at the university. This project will develop a three-pronged approach that transforms and blends existing interventions into a sustained, integrative and organized structure to address the broad scope of needs of first-generation students. The first prong is a professional learning community (PLC) of faculty from a variety of science majors (biology, chemistry, math, physics, computer science, and earth and environmental science) and from English. The PLC will work together to create and teach a two-semester science literacy course for the selected first-generation students. This course will follow a broad topic in science such as global climate change or water availability and study it from the perspectives of the different scientific disciplines of the PLC faculty. Students will be guided in developing a research project on this topic. The second prong places selected first-generation students in student learning communities (SLC) where they take the same courses together. A goal of the SLC will be to create shared experiences and bonding between the students and faculty. The third prong focuses on advising and mentoring, and will be accomplished by employing professional advisors, peer mentors, and organizing advising sessions that will cover topics ranging from course and major selection to career opportunities. A framework will be established to allow constant interaction between all three of these components. Very important to the success of this project will be an assessment that will look at the success of each component individually and as a whole. A goal will be to figure out how to successfully increase first-generation students recruitment into the sciences and enhance their academic and professional success once they have chosen a science major. A well-qualified evaluator and statistical consultant will assess the project through the use of a comparison group.