Institution
Wilkes University
Education•Wilkes-Barre, Pennsylvania, United States•
About: Wilkes University is a education organization based out in Wilkes-Barre, Pennsylvania, United States. It is known for research contribution in the topics: Population & Pharmacy. The organization has 616 authors who have published 1032 publications receiving 21050 citations. The organization is also known as: Wilkes & Wilkes College.
Topics: Population, Pharmacy, Seed dispersal, Curriculum, Electron mobility
Papers published on a yearly basis
Papers
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Grinnell College1, Georgetown University2, Penn State Berks3, Muhlenberg College4, Corning Community College5, College of William & Mary6, Howard University7, Longwood University8, Minnesota State University Moorhead9, New Jersey City University10, Bemidji State University11, Worcester State University12, St. John's University13, University of the Fraser Valley14, Western Carolina University15, Saint Joseph's University16, Grand Valley State University17, Stevenson University18, Anoka-Ramsey Community College19, Montclair State University20, McLennan Community College21, University of the Cumberlands22, California State University San Marcos23, Mercyhurst University24, Washington & Jefferson College25, Siena College26, California Polytechnic State University27, City University of New York28, University of San Diego29, St. Edward's University30, University of Colorado Boulder31, Lock Haven University of Pennsylvania32, Loyola University Chicago33, Notre Dame College34, Moravian College35, Wilkes University36, University of Detroit Mercy37, William Woods University38, Vassar College39, North Carolina Central University40, Applied Science Private University41, Cardinal Stritch University42, Utah Valley University43, Eastern University (United States)44, University of Northern Colorado45, Oklahoma Christian University46, George Washington University47, University of Puerto Rico at Mayagüez48, Eastern Washington University49, Bennington College50, York College, City University of New York51, Mount Saint Mary College52, Columbia College (South Carolina)53, Widener University54, Illinois State University55, Towson University56, Gateway Community and Technical College57, Macalester College58, Saint Mary's College59, Bucknell University60, McDaniel College61, Webster University62, Linfield College63, California Lutheran University64, Agnes Scott College65, Simmons College66, University of Puerto Rico at Cayey67, Washburn University68, Ohio Northern University69, University of North Carolina at Pembroke70, Albion College71, Washington University in St. Louis72, Massasoit Community College73, Lane College74, Medgar Evers College75, North Carolina Agricultural and Technical State University76, Arcadia University77, Baruch College78, California State University, Monterey Bay79, University of Evansville80, Northern Michigan University81, Clark University82, Denison University83, Wartburg College84, Lewis & Clark College85, Kentucky Wesleyan College86, California State University, Stanislaus87, Grove City College88, University of Pittsburgh89, University of Alabama90
TL;DR: It is suggested that a dynamic of “formative frustration” is an important aspect for a successful CURE, because iterations can be performed quickly and are inexpensive in both time and money.
Abstract: A hallmark of the research experience is encountering difficulty and working through those challenges to achieve success. This ability is essential to being a successful scientist, but replicating such challenges in a teaching setting can be difficult. The Genomics Education Partnership (GEP) is a consortium of faculty who engage their students in a genomics Course-Based Undergraduate Research Experience (CURE). Students participate in genome annotation, generating gene models using multiple lines of experimental evidence. Our observations suggested that the students' learning experience is continuous and recursive, frequently beginning with frustration but eventually leading to success as they come up with defendable gene models. In order to explore our "formative frustration" hypothesis, we gathered data from faculty via a survey, and from students via both a general survey and a set of student focus groups. Upon analyzing these data, we found that all three datasets mentioned frustration and struggle, as well as learning and better understanding of the scientific process. Bioinformatics projects are particularly well suited to the process of iteration and refinement because iterations can be performed quickly and are inexpensive in both time and money. Based on these findings, we suggest that a dynamic of "formative frustration" is an important aspect for a successful CURE.
14 citations
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TL;DR: In this paper, a review article explores current research on aggression in institutionc ized elders and proposes a theoretical framework for use by caregivers, including the relationships of brain dysfunction, past beha...
Abstract: This review article explores current research on aggression in institutionc ized elders and proposes a theoretical framework for use by caregivers. The relationships of brain dysfunction, past beha...
14 citations
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TL;DR: The studies indicate that α1B-ARs are the major α1-AR subtype expressed in DU145, PC3, and all TRAMP cell lines, but most of the receptor is localized in intracellular compartments in a nonfunctional state, which can be rescued upon prolonged incubation with any ligand.
Abstract: The function and distribution of alpha1-adrenergic receptor (AR) subtypes in prostate cancer cells is well characterized. Previous studies have used RNA localization or low-avidity antibodies in tissue or cell lines to determine the alpha1-AR subtype and suggested that the alpha1A-AR is dominant. Two androgen-insensitive, human metastatic cancer cell lines DU145 and PC3 were used as well as the mouse TRAMP C1-C3 primary and clonal cell lines. The density of alpha1-ARs was determined by saturation binding and the distribution of the different alpha1-AR subtypes was examined by competition-binding experiments. In contrast to previous studies, the major alpha1-AR subtype in DU145, PC3 and all of the TRAMP cell lines is the alpha1B-AR. DU145 cells contained 100% of the alpha1B-AR subtype, whereas PC3 cells were composed of 21% alpha1 A-AR and 79% alpha1B-AR. TRAMP cell lines contained between 66% and 79% of the alpha1B-AR with minor fractions of the other two subtypes. Faster doubling time in the TRAMP cell lines correlated with decreasing alpha 1B-AR and increasing alpha1 A- and alpha1D-AR densities. Transfection with EGFP-tagged alpha1B-ARs revealed that localization was mainly intracellular, but the majority of the receptors translocated to the cell surface after extended preincubation (18 hr) with either agonist or antagonist. Localization was confirmed by ligand-binding studies and inositol phosphate assays where prolonged preincubation with either agonist and/or antagonist increased the density and function of alpha 1-ARs, suggesting that the native receptors were mostly intracellular and nonfunctional. Our studies indicate that alpha1B-ARs are the major alpha1-AR subtype expressed in DU145, PC3, and all TRAMP cell lines, but most of the receptor is localized in intracellular compartments in a nonfunctional state, which can be rescued upon prolonged incubation with any ligand.
14 citations
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TL;DR: This paper developed a spatial model where the candidates are valence-seeking, i.e., like the voters, the candidates prefer that the winning candidate possess qualities, such as integrity, diligence, and competence, that will enhance his job performance.
Abstract: Several recent spatial modeling studies incorporate valence issues—e.g., voters’ evaluations of the candidates’ competence, integrity, and charisma—that may give one of the candidates an electoral advantage that is independent of his policy positions. However to date all such models assume that while voters value positive valence characteristics, the candidates themselves do not. We develop a spatial model where the candidates are valence-seeking, i.e.—like the voters—the candidates prefer that the winning candidate possess qualities, such as integrity, diligence, and competence, that will enhance his job performance. We analyze a spatial model where the candidates value both the valence qualities and the policies of the winning candidate, and we show that the candidates’ optimal policy choices typically diverge as the valence differential between them increases, and in particular that the valence-disadvantaged candidate normally has incentives to become more extreme as the valence advantage of her opponent increases.
14 citations
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TL;DR: In this article, the authors highlight missing links in the aptitude and attitude of an engineer in combining technical knowledge with sound decision-making and effective entrepreneurship, and discuss the gaps in traditional college education, and their remedies through outcome-based curricula.
Abstract: The emerging facts from successful organizations, including universities, indicate that the real source of power in a knowledge-based economy is in combining technical prowess with entrepreneurship. This paper first highlights missing links in the aptitude and attitude of an engineer in combining technical knowledge with sound decision-making and effective entrepreneurship. Second, it discusses the gaps in traditional college education, and their remedies through outcome-based curricula. Third, it presents the distinction between leadership and management with reference to new models espoused in the theory of constraints (TOC). Fourth, it outlines the skills needed for the professional development of an individual to transform him or her from a traditional quantitative/verbal thinker to a future-oriented visionary by redirecting the whole-brain thinking. Finally, critical success factors in the development of an effective and efficient knowledge worker for the 21st century is enumerated.
14 citations
Authors
Showing all 619 results
Name | H-index | Papers | Citations |
---|---|---|---|
William I. Rose | 71 | 241 | 13418 |
Hsueh-Chia Chang | 62 | 327 | 12670 |
Douglas A. Burns | 45 | 139 | 7272 |
James Adams | 37 | 81 | 4653 |
Ann Kolanowski | 36 | 178 | 4333 |
Mihir Sen | 36 | 192 | 4245 |
Alexander Shekhtman | 35 | 120 | 3874 |
Ned Fetcher | 31 | 64 | 4011 |
Michael P. Kaschak | 30 | 73 | 5125 |
William Terzaghi | 30 | 70 | 4547 |
Thomas M. Walski | 30 | 136 | 4219 |
Samuel Merrill | 29 | 75 | 2621 |
Michael A. Steele | 27 | 74 | 2863 |
Gregory S. Harms | 27 | 47 | 3268 |
Michael R. Gionfriddo | 26 | 87 | 3074 |