Brooklyn, NY, United States
Brooklyn, NY, United States

Brooklyn College is a senior college of the City University of New York, located in Brooklyn, New York, United States.Established in 1930 by the New York City Board of Higher Education, the College had its beginnings as the Downtown Brooklyn branches of Hunter College and the City College of New York . With the merger of these branches, Brooklyn College became the first public coeducational liberal arts college in New York City. The 26-acre campus is known for its great beauty, and is often regarded as "the poor man's Harvard" because of its low tuition and reputation for academic excellence .The school was ranked as the most beautiful campus and in the top ten for value, diversity, and location by The Princeton Review in 2003 and in the top fifty for value in 2009. Wikipedia.

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Delamater A.R.,Brooklyn College
Learning and Behavior | Year: 2012

A significant problem in the study of Pavlovian conditioning is characterizing the nature of the representations of events that enter into learning. This issue has been explored extensively with regard to the question of what features of the unconditioned stimulus enter into learning, but considerably less work has been directed to the question of characterizing the nature of the conditioned stimulus. This article introduces a multilayered connectionist network approach to understanding how "perceptual" or "conceptual" representations of the conditioned stimulus might emerge from conditioning and participate in various learning phenomena. The model is applied to acquired equivalence/distinctiveness of cue effects, as well as a variety of conditional discrimination learning tasks (patterning, biconditional, ambiguous occasion setting, feature discriminations). In addition, studies that have examined what aspects of the unconditioned stimulus enter into learning are also reviewed. Ultimately, it is concluded that adopting a multilayered connectionist network perspective of Pavlovian learning provides us with a richer way in which to view basic learning processes, but a number of key theoretical problems remain to be solved, particularly as they relate to the integration of what we know about the nature of the representations of conditioned and unconditioned stimuli. © Psychonomic Society, Inc. 2011.

Quadri L.E.N.,Brooklyn College
Critical Reviews in Biochemistry and Molecular Biology | Year: 2014

Over a decade ago, the analysis of the complete sequence of the genome of the human pathogen Mycobacterium tuberculosis revealed an unexpectedly high number of open reading frames encoding proteins with homology to polyketide synthases (PKSs). PKSs form a large family of fascinating multifunctional enzymes best known for their involvement in the biosynthesis of hundreds of polyketide natural products with diverse biological activities. The surprising polyketide biosynthesis capacity of M. tuberculosis has been investigated since its initial inference from genome analysis. This investigation has been based on the genes found in M. tuberculosis or their orthologs found in other Mycobacterium species. Today, the majority of the PKS-encoding genes of M. tuberculosis have been linked to specific biosynthetic pathways required for the production of unique lipids or glycolipid conjugates that are critical for virulence and/or components of the extraordinarily complex mycobacterial cell envelope. This review provides a synopsis of the most relevant studies in the field and an overview of our current understanding of the involvement of PKSs and several other polyketide production pathway-associated proteins in critical biosynthetic pathways of M. tuberculosis and other mycobacteria. In addition, the most relevant studies on PKS-containing biosynthetic pathways leading to production of metabolites from mycobacteria other than M. tuberculosis are reviewed. © 2014 Informa Healthcare USA, Inc.

Agency: NSF | Branch: Continuing grant | Program: | Phase: ANIMAL BEHAVIOR | Award Amount: 261.00K | Year: 2015

The ability to locate the source of sounds enables animals to detect prey, avoid predators and communicate with others and is thus basic to survival in many species. While decades of behavioral, physiological and neuroanatomical research have revealed the physical cues and neural mechanisms that terrestrial animals use to localize sound, the mechanisms used by fish, the oldest living vertebrate group, remain a mystery. Collectively, these experiments will investigate the mechanisms of sound localization utilized by fish that likely formed the evolutionary foundation for more recent modes of vertebrate hearing and sound localization. Throughout the project, Drs. Sisneros and Forlano will train and mentor both graduate and undergraduate students and give annual public lectures regarding the supported research at the Friday Harbor Labs (FHL). As an integral part of this research program, Drs. Sisneros and Forlano will host GK-12 teachers every summer at FHL where they will participate in field and laboratory experiments. The researchers will also develop lesson plans, student projects and an educational website with the teachers at their home institutions.

The investigation will take an integrated behavioral, anatomical, and brain activational approach to determine whether fish are fundamentally similar to other studied vertebrates, and use binaural information (information from both ears) to localize sound, or are fundamentally different, and achieve robust localization on the basis of monaural (single-ear) information alone. The central hypothesis to be tested is that binaural integration is essential for sound source localization in midshipman. To test this hypothesis, the investigators will 1) determine which inner ear endorgans are required for sound localization behavior by testing animals in an established sound playback paradigm before and after systematic unilateral or bilateral removal of each endorgans otolith (saccule, lagena, utricle), 2) characterize the ipsilateral and contralateral projections of inner ear afferents from all three endorgans to known auditory processing regions in the hindbrain by bulk labeling each endorgan separately or in double or triple combination with different fluorescent-labeled dextran amine tracers, and 3) characterize the brain activation patterns resulting from controlled auditory directional stimulation in intact animals and in those that have undergone systematic endorgan removal, using c-Fos as a marker for neural activation. Duplicate digital files of all raw, processed and consolidated data will be stored locally and in the cloud by both researchers and will be made publically available within two years following publication.

Agency: NSF | Branch: Standard Grant | Program: | Phase: Chem Struct,Dynmcs&Mechansms B | Award Amount: 360.00K | Year: 2015

The Chemical Structure, Dynamics and Mechanisms program is supporting fundamental research by Professor Alexander Greer at the City University of New York, Brooklyn College. Professor Greer will develop techniques for accurately studying the chemistry of reactive oxygen species (ROS). ROS such as singlet oxygen and alkoxy radicals are of broad importance in mechanistic and synthetic chemistry and critical to understanding oxidative processes in biology. This research seeks to create modified polymer surfaces which will provide a matrix for spatially controlled generation and delivery of ROS. Newly synthesized polymers will be used to study controlled photooxidation chemistry in organic solutions, but also may have broader scientific impact in bacterial inactivation systems. The project will support training of research students to ground them in the necessary photoscientific methods. Professor Greer and his students will engage in outreach to local high schools and colleges, emphasizing the value of improving solar energy resources and water purification research. These talks will be presented in the context of the United Nations IYL2015 (International Year of Light and Light-Based Technologies).

With this award, new heterogeneous methods will be developed for the physical isolation of sensitizer and peroxide molecules to generate singlet oxygen and alkoxy radicals at polymer surfaces. The research will provide a method for conducting controlled oxidation chemistry that will facilitate a range of future studies on selective oxidation, chemical aging, flow and disinfection chemistry. One key feature of this heterogeneous chemistry will be the ability to break surface-bound peroxide bonds to regulate the alkoxy radicals formed. The research will be relevant to organic chemistry, and has potentially broader implications related to the oxidative degradation of materials.

Agency: NSF | Branch: Standard Grant | Program: | Phase: RSCH EXPER FOR UNDERGRAD SITES | Award Amount: 331.68K | Year: 2015

This project is supported under the Research Experiences for Undergraduates (REU) Sites program, which is an NSF-wide program although each Directorate administers its own REU Site competition. This program supports active research participation by undergraduate students in an effort to introduce them to scientific research so as to encourage their continued engagement in the nations scientific research and development enterprise. REU projects involve students in meaningful ways in ongoing research programs or in research projects designed especially for the purpose. The REU program is a major contributor to the NSFs goal of developing a diverse, internationally competitive, and globally-engaged science and engineering workforce. The Social, Behavioral and Economic (SBE) sciences Directorate awarded this REU Site grant to the Brooklyn College (BC) in the City University of New York (CUNY); it is a renewal of an ongoing REU Site at this location. The objective of the project is to immerse diverse students in innovative research in psychology and neuroscience. The REU Program aims to advance scientific discovery for the scientific and broader communities while promoting mentoring, learning, and professional development by: (1) increasing participation of students from underrepresented groups (primarily women, racial minorities, first-generation college students) in neuroscience research; (2) guiding students through the scientific process, from generation of research questions to communication of results; (3) immersing students in didactics that highlight the relevance and applied value of their laboratory work; (4) enhancing students competitiveness for graduate school and professional positions; and (5) boosting the research competence of local high school teachers with downstream positive learning effects for their students. This REU Program also enables faculty members to supervise talented individuals who might otherwise miss out on mentored laboratory and professional development experiences, and contributes to the training and advancement of the next generation of psychologists and neuroscientists.

The central (scientific) component of this REU Program is a semester-long laboratory immersion, under the supervision of Psychology Department faculty mentors, which results in a completed research project. REU students are exposed to a variety of behavioral, neuroscientific, and computational methods to execute their projects. High quality research and the integration of psychological theory with the design, execution, and interpretation of neuroscientific data are emphasized. Ten students are selected annually for mentored research projects, especially undergraduates at ethnic-minority serving, public two-year and four-year institutions in the New York metropolitan area. Students attend weekly didactics: a neuroscience seminar that dually focuses on neuroscience principles/research methods and professional issues; a journal club that familiarizes students with scientific literature in modern neuroscience through learning to select, read, and critically analyze original research papers; and a statistical methods seminar that emphasizes data analysis, statistical reasoning, and presenting research findings in academic contexts. Students also undergo intensive neuroethics training. As a capstone experience, students present a poster at the BC Science Research Day, where they compete for awards based on the quality of their work and ability to communicate their findings. In addition, the project has a RET (Research Experiences for Teachers) component, which provides local high school teachers with coursework in research methods, mentored laboratory experience, and professional development opportunities to enhance their neuroscience literacy and raise the level of science education in local high schools.

Agency: NSF | Branch: Standard Grant | Program: | Phase: IUSE | Award Amount: 529.97K | Year: 2015

Undergraduate research is a high-impact practice that increases retention, fosters academic performance and scientific literacy, increases motivation to study science, and raises STEM graduation rates. This project will test an innovative, cost-effective method, Peer-Assisted Team Research (PATR) that will involve more students in undergraduate research experiences earlier in college, improving their scientific reasoning abilities and STEM self-efficacy. Trained peer leaders will supervise student teams as they design and conduct increasingly complex research studies on interdisciplinary topics. PATR students will master scientific reasoning and seeing themselves as people who do science, becoming more motivated and taking more STEM courses.

PATR is an adaptable template useful in a variety of institutional settings: general education and introductory majors courses, STEM classes without labs, and co-curricular activities such as science clubs. Brooklyn College is collaborating with four other branches of City University of New York to evaluate the effectiveness of the PATR method in a variety of settings. The projects intellectual merit resides in the methods grounding in proven STEM pedagogy and current cognitive research. The projects broader impacts stem from enabling more students to participate in undergraduate research experiences, thus fostering a well-trained, diverse work-force. PATR is an adaptable, scalable and cost-effective method that prepares students for faculty-mentored research. The project will generate data using behavioral assessment and standardized test instruments to determine if students participating in PATR are developing the higher-level abstract reasoning abilities required to plan and carry out research, compared with control students.

Agency: NSF | Branch: Continuing grant | Program: | Phase: ROBUST INTELLIGENCE | Award Amount: 449.96K | Year: 2016

Environmental noise is one of the largest problem for users of voice technologies, such as hearing aids, mobile phones, and automatic speech recognition. Current approaches to source separation and speech enhancement typically attempt to modify the noisy signal in order to make it more like the original, leading to distortions in target speech and residual noise. In contrast, this project uses the innovative approach of driving a speech synthesizer using information extracted from the noisy signal to create a brand new, high quality, noise-free version of the original sentence. Improvements in noise suppression and speech quality from this approach are expected to have important broader impacts for both the 36 million Americans who are hearing impaired and the 200 million Americans who use smart phones. The project is also being incorporated into the curriculum in a diverse urban college and into established outreach programs to nearby high schools with the goal of encouraging members of under-represented groups to pursue careers in science and engineering.

This project aims to produce a high quality speech resynthesis system by modifying a concatenative speech synthesizer to use a unit-selection function based on a novel deep neural network (DNN) architecture. Preliminary results have shown this approach to work well for a small-vocabulary, speaker-dependent task, and the current project expands this to the large-vocabulary, speaker-dependent setting in three ways. First, it seeks to improve the intelligibility of the synthesized speech by utilizing perceptually motivated input features, more flexible training signals, and traditional speech enhancement. Second, it seeks to improve the systems scalability by training DNNs to embed noisy and clean speech into a joint low-dimensional space in which similarity can be efficiently computed. And third, it seeks to improve the quality of the synthesized speech by incorporating sequential models of speech units based on acoustic, phonetic, and linguistic compatibility. The use of speech synthesis models in speech enhancement is a departure from traditional approaches and has the potential to make a transformative impact on the quality of enhanced speech.

Agency: NSF | Branch: Standard Grant | Program: | Phase: SOFTWARE & HARDWARE FOUNDATION | Award Amount: 385.86K | Year: 2016

Search is one of the fundamental techniques used by many intelligent software systems. There is a big chasm between the languages that programmers use to describe problems and the encodings that are suitable for solvers to conduct search. This research aims to narrow the gap by designing and implementing algorithms for translating declarative specifications of combinatorial problems into efficient encodings. The intellectual merits are novel frameworks and algorithms for translating planning specifications into sophisticated and efficient tabled logic programs, and cutting-edge algorithms for compiling high-level constraints into SAT (satisfiability) encodings. The projects broader significance and importance are its potential to produce long-lasting, significant economic, educational, and social impact because of the ubiquity of combinatorial problems, and the resulting theory and prototypes that will form the technology which enables future systems to obtain high-quality solutions to a variety of combinatorial problems.

This research will focus on two types of combinatorial problems: AI planning and constraint satisfaction problems solved using SAT. Tabled logic programming has been shown to be a powerful and flexible modeling and solving language for planning problems. Nevertheless, it is an art, not a science, to develop efficient planning models in tabled logic programming. The algorithms designed by this research for translating planning specifications into efficient tabled logic programs will have the following capabilities: (1) convert factored representations of states into structural representations that exploit symmetries; (2) extract domain-dependent control knowledge, such as deterministic actions and partial orders; and (3) learn representation-specific heuristics. Global constraints are an important part of constraint programming. They not only allow easy modeling of many problems, but also enable use of powerful propagation algorithms. SAT encoding algorithms have been proposed for some of the global constraints. Nevertheless, there are no well-established algorithms for encoding global constraints into SAT; many other global constraints, such as graph constraints, have not received much attention despite their usefulness in practical applications. This research will produce algorithms for a comprehensive set of global constraints, and will develop a cutting-edge constraint-solving system based on these algorithms.

Agency: NSF | Branch: Standard Grant | Program: | Phase: ROBERT NOYCE SCHOLARSHIP PGM | Award Amount: 949.12K | Year: 2015

The goal of the research project is to describe the features of selective alternative teacher certification programs (ATCPs) that affect selective route mathematics teachers (SRMT) professional pathways and to make informed recommendations to decrease the current high teacher turnover. While selective ATCPs are intended to address issues of teacher staffing and quality by recruiting high achieving graduates of the nations most competitive colleges and career changers with impressive resumes, there is little understanding about the reasons for their mixed outcomes. Thus, the proposed project will utilize a multi-methodological longitudinal design that incorporates cultural-mathematical and sociological perspectives to 1) determine patterns of career trajectories of a representative sample of SRMTs and 2) examine how variations in the features of a selective ATCP affect SRMT retention. The results of the study will be useful to various stakeholders, including policymakers, district and school leaders, and directors of urban-specific teacher preparation programs by clarifying patterns in the career trajectories of SRMTs while also revealing how to retain them..

The study is framed by the literature on teacher turnover, alternative teacher certification programs, and teachers professional life cycles. It is guided also by two theoretical perspectives, namely a sociological careership perspective used to examine SRMTs career trajectories and a cultural-mathematical perspective that identifies the features of selective ATCPs that influence SMRT retention. The researchers will combine new survey and interview data with previously collected data on New York City Teaching Fellows (NYCTF) to produce findings that could inform the development of mathematics teacher preparation programs and interventions for an improved urban mathematics teaching force.

The project is supported by the ECR program that emphasizes fundamental STEM education research that generates foundational knowledge in the field. Investments are made in critical areas that are essential, broad and enduring: STEM learning and STEM learning environments, broadening participation in STEM, and STEM workforce development. ECR supports the accumulation of robust evidence to inform efforts to understand, build theory to explain, and suggest intervention and innovations to address persistent challenges in STEM interest, education, learning and participation.

Agency: NSF | Branch: Standard Grant | Program: | Phase: I-Corps | Award Amount: 50.00K | Year: 2016

The broader/commercial potential of this I-Corps project is that it provides a cost-effective, low-impact hybrid green approach for addressing stormwater runoff, one of the leading causes of impairment to our nations waters. These runoff problems are expected to be exacerbated, particularly in urban areas, as a result of the coupled impacts of future population growth-driven land use and cover changes and storm events associated with projected climate change. Recognition of these threats to our water resources, together with the increasing costs of conventional municipal water treatment, has led to interest in green infrastructure approaches for stormwater management. However, in their current design, many of these green infrastructure systems are passive: their effectiveness for intercepting water and removing pollutants is highly variable. The technology described here will provide stormwater engineers, developers, city managers, and homeowners with important design criteria that will maximize green infrastructure performance and functionality. The commercialization of this hybrid green technology is therefore key for making it widely accessible to potential end-users to address both present and future stormwater/water resource challenges.

This I-Corps project will assess the market potential and commercialization feasibility of a modular, hybrid stormwater management technology that augments green infrastructure both to maximize pollutant removal efficiency and allow for water storage. The modular hybrid green infrastructure (MHGI) is a sealed system with a specialized pipe and valve assembly that allows for both the control of water retention times as well as the location of the subsurface water table height, so that intercepted stormwater can be held within the soil matrix at a depth to maximize aerobic/anaerobic conditions that promote bioremediation via plant and microbial processing. Stormwater storage times can be controlled and the system can be made operational to adjust for changes in historical or projected runoff volumes. The intercepted water can also be stored within the system, pending removal by evapotranspiration, or for reuse purposes such as irrigation. Preliminary alpha testing of this technology demonstrated significant and consistent nitrogen and phosphorus removal efficiencies with 88% nitrate and 100% phosphate removal observed for urban runoff, 95% total nitrogen and 81% phosphate removal observed for septic effluent, and 50% nitrate, 71% ammonium, and 55% removal observed for agricultural runoff.

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