36 resultados para Pregulman, Mervin


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Back Row: coach H.O. Crisler, William Keenan, Paul White, William Pritula, Donald Boor, Philip Sharpe, Robert Oren, Robert Derleth, Philip Marcellus, John Greene, Otto Chady, Robert Shemky, John Karwales, William Kuyper, Albert Wistert, Peter Gritis, Frank Wardley, Walter Freihofer, asst. Coach Ernie McCoy

Middle Row: backfield coach Earl Martineau, Vincent Secontine, Clifford Wise, Donald Cady, Philip Mooney, Warren Yaap, Charles Kennedy, James Brieske, Elmer Madar, Charles Avery, Robert Vernier, George Kiesel, Robert Stenberg, Angelo Trogan, William Kohrbach, George Ceithaml, Robert Chappuis, line coach Clarence Munn

Front Row: asst coach Art Valpey, Mervin Pergament, Clifton Myll, Donald Lund, Rudy Smeja, Mervn Pregulman, Don Robinson, John VanSummern, Ralh Amstutz, Tom Kuzma, Robert Wiese, Robert Kolesar, Julius Franks, William Baldwin, Fred Bryan, ast. Coach William Barclay

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Top Row: Ralph Amstutz, Robert McFaddin, William MacDougall, Joseph Rogers, Robert Ingalls, Elmer Madar, George Ceithaml, Fred Dawley

3rd Row: John Harrigan, Charles Haslam, William Kuyper, Rudoph Smeja, Austin Miller, William Pritula, Harlin Fraumann, Jack Petoskey, Vincent Secontine, Robert Stenberg, David Nelson

2nd Row: Walter Freihofer, Harry Anderson, Harold Lockard, Robert Morrison, John Greene, William MacConnachie, Robert Shemky, Reuben Kelto, Angelo Trogan, James Brown, Don Robinson, Donald Boor

Front Row: George Hildebrandt, Tom Kuzma, Philip Sharpe, Ray Sowers, John Karwales, Paul White, John Laine, Julius Franks, Mervin Pregulman, Theodore Denise, Charles Kennedy, Ted Kennedy, Robert Kolesar

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Top Row: George Kiesel, Howard Wikel

4th Row: Alan Schwartz, Art Renner, William Rudolph, Ray Sturgess, Farnum Johnson, Fenwick Crane, George Kreager, Bob Oren, John Crandell, Fred Bryan, Lewis Wheeler

3rd Row: Donald Lund, Robert Rennebohm, Henry Olshanski, Fred Negus, Elroy Hirsch, Jim Aliber, James Brown, Walter Dreyer, William Daley, John Gallagher Robert Hanzlik

2nd Row: Ralph Ammtutz, Robert Kennedy, Clifton Myll, Earl Maves, James Holgate, Robert Wiese, Jack Trump, Hugh Mack, Joe Ponsetto, Bill Culligan, John Greene

Front Row: Dick Manning, Jim Brieske, Bob Stenberg, Mervin Pregulman, Bob Nussbaumer, Paul White, Jack Wink, Jack Petoskey, Rudy Smeja, Bob Fischer, Harold Watts, Clement Bauman

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Back Row: coach H.O. Crisler, William Keenan, Paul White, William Pritula, Donald Boor, Philip Sharpe, Robert Oren, Robert Derleth, Philip Marcellus, John Greene, Otto Chady, Robert Shemky, John Karwales, William Kuyper, Albert Wistert, Peter Gritis, Frank Wardley, Walter Freihofer, asst. Coach Ernie McCoy

Middle Row: backfield coach Earl Martineau, Vincent Secontine, Clifford Wise, Donald Cady, Philip Mooney, Warren Yaap, Charles Kennedy, James Brieske, Elmer Madar, Charles Avery, Robert Vernier, George Kiesel, Robert Stenberg, Angelo Trogan, William Rohrbach, George Ceithaml, Robert Chappuis, line coach Clarence Munn

Front Row: ass't coach Art Valpey, Mervin Pergament, Clifton Myll, Donald Lund, Rudy Smeja, Mervin Pregulman, Don Robinson, John VanSummern, Ralph Amstutz, Tom Kuzma, Robert Wiese, Robert Kolesar, Julius Franks, William Baldwin, Fred Bryan, ast. Coach William Barclay

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The common presupposition of Enterprise Systems (ES) is that they lead to significant efficiency gains. However, this is only the case for well-implemented ES that meet organisational requirements. The list of major ES implementation failures is as long as the list of success stories. We argue here that this arises from a more fundamental problem, the functionalist approach to ES development and provision. As long as vendors will continue to develop generic, difficult-to-adapt ES packages, this problem will prevail because organisations have a non-generic character. A solution to this problem can only consist in rethinking the way ES packages are provided. We propose a strict abstraction layer of ES functionalities and their representation as conceptual models. ES vendors must provide sufficient means for configuring these conceptual models. We discuss in this paper what generic situations can occur during process model configuration in order to understand process model configuration in depth.

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The purpose of this study was to explore associations between forms of social support and levels of psychological distress during pregnancy. Methods: A cross-sectional analysis of 2,743 pregnant women from south-east Queensland, Australia, was conducted utilising data collected between 2007-2011 as part of the Environments for Healthy Living (EFHL) project, Griffith University. Psychological distress was measured using the Kessler 6; social support was measured using the following four factors: living with a partner, living with parents or in-laws, self-perceived social network, and area satisfaction. Data were analysed using an ordered logistic regression model controlling for a range of socio-demographic factors. Results: There was an inverse association between self-perceived strength of social networks and levels of psychological distress (OR = 0.77; 95%CI: 0.70, 0.85) and between area satisfaction and levels of psychological distress (OR = 0.77; 95%CI: 0.69, 0.87). There was a direct association between living with parents or in-laws and levels of psychological distress (OR = 1.50; 95%CI: 1.16, 1.96). There was no statistically significant association between living with a partner and the level of psychological distress of the pregnant woman after accounting for household income. Conclusion: Living with parents or in-laws is a strong marker for psychological distress. Strategies aiming to build social support networks for women during pregnancy have the potential to provide a significant benefit. Policies promoting stable family relationships and networks through community development could also be effective in promoting the welfare of pregnant women.

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Introduction: Apathy, agitated behaviours, loneliness and depression are common consequences of dementia. This trial aims to evaluate the effect of a robotic animal on behavioural and psychological symptoms of dementia in people with dementia living in long-term aged care. Methods and analysis: A cluster-randomised controlled trial with three treatment groups: PARO (robotic animal), Plush-Toy (non-robotic PARO) or Usual Care (Control). The nursing home sites are Australian Government approved and accredited facilities of 60 or more beds. The sites are located in South-East Queensland, Australia. A sample of 380 adults with a diagnosis of dementia, aged 60 years or older living in one of the participating facilities will be recruited. The intervention consists of three individual 15 min non-facilitated sessions with PARO or Plush- Toy per week, for a period of 10 weeks. The primary outcomes of interest are improvement in agitation, mood states and engagement. Secondary outcomes include sleep duration, step count, change in psychotropic medication use, change in treatment costs, and staff and family perceptions of PARO or Plush-Toy. Video data will be analysed using Noldus XT Pocket Observer; descriptive statistics will be used for participants’ demographics and outcome measures; cluster and individual level analyses to test all hypotheses and Generalised Linear Models for cluster level and Generalised Estimation Equations and/or Multi-level Modeling for individual level data. Ethics and dissemination: The study participants or their proxy will provide written informed consent. The Griffith University Human Research Ethics Committee has approved the study (NRS/03/14/HREC). The results of the study will provide evidence of the efficacy of a robotic animal as a psychosocial treatment for the behavioural and psychological symptoms of dementia. Findings will be presented at local and international conference meetings and published in peer-reviewed journals.

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Although growth rate and age data are essential for leatherback management, estimates of these demographic parameters remain speculative due to the cryptic life history of this endangered species. Skeletochronological analysis of scleral ossicles obtained from 8 captive, known-age and 33 wild leatherbacks originating from the western North Atlantic was conducted to characterize the ossicles and the growth marks within them. Ages were accurately estimated for the known-age turtles, and their growth mark attributes were used to calibrate growth mark counts for the ossicles from wild specimens. Due to growth mark compaction and resorption, the number of marks visible at ossicle section tips was consistently and significantly greater than the number visible along the lateral edges, demonstrating that growth mark counts should be performed at the tips so that age is not underestimated. A correction factor protocol that incorporated the trajectory of early growth increments was used to estimate the number of missing marks in those ossicles exhibiting resorption, which was then added to the number of observed marks to obtain an age estimate for each turtle. A generalized smoothing spline model, von Bertalanffy growth curve, and size-at-age function were used to obtain estimates of age at maturity for leatherbacks in the western North Atlantic. Results of these analyses suggest that median age at maturation for leatherbacks in this part of the world may range from 24.5 to 29 yr. These age estimates are much greater than those proposed in previous studies and have significant implications for population management and recovery.