177 research outputs found
097. Meet the Professor: Dr. Ryan Tinetti
No full textConcordia Seminary Dean of Theological Research and Publication Dr. Kevin Golden takes some time to introduce new faculty member Dr. Ryan Tinetti, who recently joined the Seminary as assistant professor of Practical Theology.
Tinetti previously served as pastor at Trinity Lutheran Church in Arcadia, Mich. (2018-24); Beautiful Savior Lutheran Church in Spokane, Wash. (2014-18); and Faith Lutheran Church in Seaside, Calif. (2010-14). He was a guest lecturer at Lutheran Theological Seminary in Praetoria, South Africa (2024), and Concordia Theological Seminary, Fort Wayne, Ind. (2024), and he is the author of the book “Preaching by Heart” (Cascade Press). Tinetti earned a Doctor of Ministry (D.Min.) (2019) from Duke University in Durham, N.C., and a Master of Divinity (M.Div.) (2010) from Concordia Seminary. In 2005, Tinetti received a Bachelor of Arts from Michigan State University in East Lansing, Mich. Learn more about Tinetti.https://scholar.csl.edu/cjc/1098/thumbnail.jp
Narrative Intersections in an Author Museum: The Olive Schreiner House
No full textThe Olive Schreiner House in Cradock, South Africa, is an author museum that explores the contributions of an important writer, activist, and early feminist by facilitating new narratives. In the meeting of Schreiner’s texts and contemporary narratives of South African cultural history, this author museum writes a new discourse between literature and society, historic past and democratic present. These intersections result in a narrative project using a historic literary figure to emphasize the young South African democracy in which the museum is situated
Investigating the Role of DIS3L2 in Perlman Syndrome and Wilms Tumor
No full textThe general metadata -- e.g., title, author, abstract, subject headings, etc. -- is publicly available, but access to the submitted files is restricted to UT Southwestern campus access and/or authorized UT Southwestern users.Wilms tumor, while the most common pediatric kidney tumor, has a poorly understood etiology. Several recent studies have uncovered a role for loss of let-7 in its pathogenesis. One crucial mechanism through which let-7 expression is controlled is via the activity of the RNA-binding protein LIN28, which binds the precursor of let-7 and mediates the addition of a series of uridines to the 3′ end. This oligouridylation marks pre-let-7 for degradation by the exoribonuclease DIS3L2. Loss-of-function mutations in DIS3L2 lead to the Perlman congenital overgrowth syndrome, characterized by high neonatal mortality and, interestingly, a strong predisposition to Wilms tumor. Furthermore, DIS3L2 has been found to be deleted or mutated in some cases of sporadic Wilms tumor. The importance of let-7 in Wilms tumorigenesis and a purported role for DIS3L2 in the LIN28-let-7 pathway have led to speculation that aberrant let-7 expression underlies Wilms tumor susceptibility in DIS3L2-deficient contexts.
It is still unclear, though, how loss of DIS3L2 could lead to altered let-7 levels, as the uridylated pre-let-7 species that DIS3L2 degrades is believed to be a dead-end product that cannot be further processed by DICER into mature let-7. Thus far, regulation of mature let-7 levels by DIS3L2 has only been examined in a limited number of cell lines. To determine whether DIS3L2 regulation of let-7 differs in a broader set of cell types, we used genome-editing to knockout DIS3L2 in a wide-ranging panel of cell lines with differing levels of LIN28 expression. Consistent with prior reports, loss of DIS3L2 had no effect on mature let-7 expression in these cell lines.
However, it remained possible that the regulation of let-7 by DIS3L2 differed in cell populations relevant to Wilms tumor pathogenesis in vivo. Thus, to examine DIS3L2 function in these contexts, we used CRISPR-Cas9 to generate mouse lines harboring either Dis3l2-null alleles or mutations commonly observed in Perlman syndrome. Interestingly, Dis3l2 mutants recapitulated some aspects of Perlman syndrome, including neonatal mortality and genitourinary abnormalities, but not overgrowth or Wilms tumor. Moreover, the phenotype that results from the most common Perlman mutation is the same as that seen in the Dis3l2 loss-of-function mouse model, suggesting that the DIS3L2 mutations reported in Perlman syndrome are indeed loss-of-function.
Finally, we examined the molecular function of DIS3L2 in isolated primary nephron progenitor cells (NPCs), a likely cell of origin of Wilms tumors, from Dis3l2-null and wild-type embryos. Consistent with our findings in the cell lines, loss of DIS3L2 in NPCs does not affect let-7 expression or activity, yet leads to upregulation of Igf2, which is reported to be overexpressed in 70-80% of Wilms tumors. Therefore, Igf2 poses an attractive candidate for both overgrowth and oncogenesis associated with DIS3L2 loss
Jones Junior High School fifth grade students, Toledo, Ohio, 1964
No full textTerms associated with the photograph are: Jones Junior High School (Toledo, Ohio) | junior high schools | class portraits | 1964-1965 | fifth grade | students | Hartfield, Alphonso | Cook, Isaac Wayne | Hamilton, Deborah | Ryan, Gary | Bagsby, Sheila | Gaisser, Lynette | Hunter, Inez | Ulis, Ray | Kember, Gayle | Goodman, Roger | Moore, Melvin | Johnson, Ricky | Sutherland, Valerie | Richardson, William | Johnson, Betty | Binkley, Donald | Baker, Charles Robert | Bock, Myron | Curtis, Dona | Hart, Gary | Gillard, Bobby | Caro, Lydia | Davidson, Linda | McLennan, Helen | Echols, Sylvia | Morris, Paul | Bliss, Robert | Tuttle, Robert | Gartee, Karen | Carter, Rickie | teachers | Henry, William W
A Neuro-Symbolic Reinforcement Learning Architecture: Integrating Perception, Reasoning, and Control
No full textIn recent years, neuro-symbolic learning methods have demonstrated promise in tasks re- quiring a semantic understanding that can often be missed by traditional deep learning techniques. By integrating symbolic reasoning with deep learning, neuro-symbolic architec- tures aim to be both interpretable and flexible. This thesis aims to apply neuro-symbolic learning to the domain of reinforcement learning. First, a simulation environment for robotic manipulation tasks is presented. In this environment, an analysis of policy-gradient-based reinforcement learning algorithms is given. Then, by leveraging the performance of deep learning with the semantic reasoning and interpretability of symbolically defined program- ming, a novel neuro-symbolic learning method is proposed to generalize tasks and motion planning for robotics applications using natural language. This novel neuro-symbolic can be seen as an adaptation of the Neuro-Symbolic Concept Learner[1] developed by IBM Wat- son, in which images and natural language are first processed by convolutional and residual neural networks, respectively, and then parsed by a symbolically reasoned program. Where the architecture proposed in this paper differs is in its use of the Neuro-Symbolic Concept Learner for preprocessing of a given input task, to then inform a reinforcement learning agent of how to act in a given environment. Finally, the novel adaptation of the Neuro-Symbolic Concept Learner is introduced as a method of demonstrating generalizable behavior through symbolic preprocessing.Master of ScienceRobots are becoming more capable, but teaching them to perform complex tasks in changing environments remains a major challenge. Traditional learning systems, like deep learning, are powerful, but they are often seen as black-boxes. This project explores a new approach that combines the strengths of deep learning with symbolic reasoning, which allows robots to reason about their actions and goals in a more human-interpretable way. In this thesis, a simulated environment was built for training and testing a robotic arm on object manipula- tion tasks using. A reinforcement learning system was developed to allow the robot to learn through trial and error, improving its performance over time. To improve generalization and task understanding, a new hybrid model was proposed that combines deep learning with symbolic logic. Inspired by IBM's Neuro-Symbolic Concept Learner, this model uses visual and language inputs to guide the robot's behavior based on symbolic representations. Unlike the original Concept Learner, this version is adapted to help a reinforcement learning agent decide what to do in a specific situation based on these symbolic cues. This research shows that combining symbolic reasoning with modern learning techniques could make robots more flexible, explainable, and capable of handling a wider variety of real-world tasks
North American Monarch Butterfly Ecology and Conservation
No full textThis eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contac
The Financial Implications of Medical Education: An ROI Analysis of School Type, Specialty, and Training Location
No full textThe Financial Implications of Medical Education: An ROI Analysis of School Type, Specialty, and Training Location
Introduction
The financial burden of medical education profoundly influences career trajectories and long-term financial outcomes for physicians. This study examined the impact of medical school costs (comparing an in-state public and private medical school), specialty selection (focusing on Pediatrics, OB/GYN, and Orthopedic Surgery), and geographic factors on physicians\u27 financial returns. Further, this study considered loan repayment strategies and their effects on career return on investment (ROI), offering insights into financial decision-making for future medical graduates.
Methods Data on medical school costs, including tuition and cost of living (COA), were collected from information publicly published on schools’ websites. An annual tuition increase of 3.5% was assumed based on historic trends. Three payment scenarios were analyzed: 100% cash, 50/50 cash-loan split, and 100% loans. In forecasting costs, we assumed an 8% interest rate in line with current interest rates. Multiple repayment strategies were analyzed, starting with a 10% salary repayment and progressing to more aggressive plans aimed at repaying loans over 40, 23, or 15 years of practice. Physician salary data, retrieved from Medscape, informed ROI calculations, with consideration to varied tax rates and loan repayment schedules. ROI was compared across school types, specialties, and repayment strategies. ROI was defined as the total career income divided by the aggregate net loan payments.
Results Public in-state institutions, such as Wayne State University, yielded higher ROI compared to private schools, especially for lower-paying specialties like Pediatrics. Orthopedic surgeons experienced the highest ROI across repayment strategies, with aggressive 15-year repayment plans yielding ROIs of up to 2638%, compared to 524% for 40-year plans. Pediatrics showed limited ROI gains due to lower salaries, though repayment strategies significantly influenced financial outcomes.
Discussion
Loan repayment timelines emerged as a critical determinant of financial outcomes. While aggressive repayment reduced interest costs and improved ROI, it imposed greater financial strain early in physicians\u27 careers. Public medical schools offered better financial returns due to lower initial costs, particularly for specialties with modest to high compensation. Specialty choice was also an important consideration for ROI, although its impact was somewhat reduced due to the longer training required. Certain limitations may slightly temper these findings, including the exclusion of loan forgiveness programs, investment opportunities, and non-financial benefits of prestigious institutions.
Conclusion
The cost of medical education, specialty choice, and loan repayment strategies significantly affect physicians’ financial trajectories. Aggressive repayment strategies and studying at public institutions improve ROI, though personal factors and career goals should guide decision-making. Future research should incorporate broader financial variables and explore non-monetary factors shaping physicians’ career choices
Young People's Experiences of Receiving Individual Packages of Care in South Australia
No full textAuthor version made available here in accordance with Publisher copyright policy.The aim of this study was to explore the role that professional foster care – and specifically Individual Packages of Care (IPC) in South Australia – plays in providing an alternative care option for young people who are unable to live with their birth parents due to issues of abuse or neglect, but who also, due to behavioural concerns, are not well suited to a traditional foster care placement. Participants in the study were nine young people who had previously lived in an IPC placement. The findings highlight participants’ experiences of living in the context of an IPC placement, experiences that were at times challenging, but which also provided opportunities for growth and positive change that may not have been possible in a traditional foster care placement
One Hundred Years of Graduates Creighton University School of Law Class of 2005
No full textGraduates|Abboud, Frederick L., Jr.; Anderson, Jennifer; Antonini, Charles John, III; Appenzeller, Krista L.; Argotsinger, Todd J.; Armitage, Anne M.; Arora, Kavita Bajaj; Bailey, Ryan; Becker, Amy C.; Beller, Emily A.; Boeser, Joseph T.; Bowman, Timothy; Brack, Margaret K.; Braun, Lindsay G.; Brewer, Michael; Broder, Kelly; Brown, Richard L., III; Buge, Brian W. (Treasurer); Buhrfield, Daniel C.; Carroll, John F.; Carter, Justin F.; Cimino, Matt; Cizek, Sara S.; Cole, Patrick J.; Connelly, John A.; Craft, James; Cross, Jeremy J.; Daley, Jill; Daniels, Leanna C.; Dempsey, Alison; Eldredge, Trevor B.; Enriques, Gerald K.; Ferguson, Carrie; Fix, Jill; Flechler, Rebecca; Flynn, Erin M.; Funkhouser, Angela K.; Gadzikowski, Leah; Gang, Damien; Gass, Jonathan F.; Glass, Oliver J.; Going, Scott M.; Gore, John D.; Green, Katherine; Greenamyre, Julie A.; Greenfield, Kourtney A.; Grillot, Nicholas; Gruber-Gardner, Angela; Hacker, John D.; Haferbier, Jodie; Hamm, Brandon; Hansen, R. Christian; Harmon, Jared C.; Harp, Kristina; Haumont, Bradley; Hebenstreit, Julia; Heelan, Melissa C.; Hefflinger, Joe; Heine, John D.; Hengl, Ryan C.; Hermanson, Tessa P.; Herrboldt, Katrine M.; High, Justin; Hoarty, Daniel; Hoffman, Ryan; Holst, Luke Charles; Hopson, Diane Tomka; Huggins, Richard; Hunt, Joshua F.; Hunter, Jeri; Ingraham, Robert M.; Jacobs, Mark F.; Jacoby, Brandie; Jensen, Michael W.; Jones, Craig T.; Jones, Lisa Nicole (3L Representative); Judy, Brian; Kahla, Roxanne M.; Katz, Philip; Kaufman-McNamara, Suzanne D.; Keenan, Sara L.; Kennedy, Micki J.; King, William; Kinney, Brandon G.; Knipp, Joseph; Kunz, Aaron J.; Liberty, Robert L.; Lichti, Amber L.; Linman, Nissa; Lipes, Maegan; Lippincott, Emily; Luebbert, Kyla L.; Majeski, Penny; Meredith, Andrew S. (3L Representative); Meyer, Heather S.; Miller, Casey E.; Milligan, Amy; Mitchell, Alton Elie; Munyon, Matthew; Murvin, Daniel J.; Naglosky, Jeffrey S.; Nair, Nisha; Newland, Steven J.; O'Neill, David M.; Penning, Steven M.; Pepper, Patrick D.; Peters, Ryan V.; Peterson, Meghan M.; Petricevic, Bosko; Polzer, Natalie M.; Potts, Karen C.; Quinn, Kendra; Reece, Todd A.; Reed, Angela M.; Rupp, Kristine M.; Rush, Timothy J.; Schaefer, Kristina M.; Schanbacher, Kristena M.; Skolaut, Paul J.; Slavin, Dan; St. Clair, Jessica; Svee, Scott; Symonds, Casey J.; Talati, Umang Dilipkumar; Tarpley, Tim; Tate, Allen M.; Taylor, Jennifer J.; Teiken, Thomas L.; Tomich, Richard M.; Vaterlaus, John B.; Vermillion, Melissa A.; Walker, John M.; Walkingstick, Jennifer D.; Wayne, Justin T. (President); Wirth, Lucas A.; Witt, Stacy; Wolf, Kylie A.; Wolff, Lisa M.; Woodard, Aaron; Woods, Gregory A.; Wright, Damien J.; Yudelson, David A.; Ziolkowski, Nicholas A.; Downing, Jillana J. (not pictured); Hall, Megan (not pictured); Mueller, Jonathan (not pictured); Nickla, Jason (not pictured); Rohling, Anne (not pictured); Rosfjord, Christopher (not pictured); Ryan, Stacy (not pictured); Simpson, Edith (not pictured); Singer, Matthew (not pictured); Waltemath, Peter (not pictured)|39 x 30 in. (landscape
Blazer Game Day: The West Alabama Game, October 18, 1997
No full textPlayers 1997
Erik Gibson; Vaughn Clark; Keith Cooksey; Eric Doggett; VonfreH Mitchell; Mike Bowman; Jarmat Stevens; Antonio Speed; Tremaine Neal; Donnie Johnston; Wayne DeVane; Patrick Prewitt; Nathan Cronic; Jason Vaughan; James Lightfoot; Jerome Mills; Kevin Sams; Wendell Olden; Alberto Nurse; Carlos Hope; Brad Trout; Derek Dixon; Paul McCall; Austin Harmon; Reggie Cocker; Terrell Battle; Carlton Nelson; Jeff Glazer; Demeakey Williams; Marcus Ray; Dennis Fryzel; John Taylor; Jimbo SHubert; Mike Williams; Jesse Sutton; J.T. Fuller; Dominic June; Ryan Sulkowski; Chris Gaston; Hunter Taylor; Daniel Allen; Bill Epps; Jay Thompson; Kris Gingrow; Jason Ray; Brandon Jernigan; Arto Vartanian; John Gulyas; Craig Jefferson; Richard Freeman; Winston Williams; Terry Turner; David Fox; Rory Hogan; Josh Parker; Marc Lyles;Lighting Up the Red Zone -- Valdosta State continues to make dramatic improvement when crossing into the red zone. In its last two games, the offense is 10-10 (9 TDs and a field goal) inside the 20 and has now cashed points (15 TDs and 2 field goals) on 17 of 25 trips, a .680 percentage
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