The Service ORiented Computing EnviRonment (SORCER) targets service abstractions for transdisciplinary complexity with support for heterogeneous service-oriented (SO) computing. SORCER's models are expressed in a ...The Service ORiented Computing EnviRonment (SORCER) targets service abstractions for transdisciplinary complexity with support for heterogeneous service-oriented (SO) computing. SORCER's models are expressed in a top-down Var-oriented Modeling Language (VML) unified with programs in a bottoms-up Exertion-Oriented Language (EOL). In this paper the introduction to mogramming (modeling and programing), which uses both languages, is described. First, the emphasis is on modeling with service variables that allow for computational fidelity within VML. Then, seven types of service providers, both local and distributed, are described to form collaborative federations described in EOL. Finally, the unified hybrid of SO modeling and SO programming is presented. Fourteen simple mogramming examples illustrate the syntax and usage of both VML and EOL.展开更多
We aimed to develop and validate a clinical nomogram predicting bladder outlet obstruction(BOO)solely using routine clinical parameters in men with refractory nonneurogenic lower urinary tract symptoms(LUTS).A total o...We aimed to develop and validate a clinical nomogram predicting bladder outlet obstruction(BOO)solely using routine clinical parameters in men with refractory nonneurogenic lower urinary tract symptoms(LUTS).A total of 750 eligible patient ≥50 years of age who had previously not responded(International Prostate Symptom Score[IPSS]improvement<4 points)to at least three different kinds of LUTS medications(including a-blocker)for the last 6 months were evaluated as subcohorts for nomogram development(n=570)and for split-sample validation(n=180).BOO was defined as Abrams-Griffiths number^40,or 20-39.9 with a slope of linear passive urethral resistance ratio>2 cmH20 ml^-1 s^-1.A stepwise multivariable logistic regression analysis was conducted to determine the predictors of BOO,and^-coefficients of the final model were selected to create a clinical nomogram.The final multivariable logistic regression model showed that age,IPSS,maximum urinary flow rate,postvoid residual volume,total prostate volume,and transitional zone index were significant for predicting BOO;these candidates were used to develop the final nomogram.The discrimination performance of the nomogram was 88.3%(95%Cl:82.7%-93.0%,P<0.001),and the nomogram was reasonably we 11-fitted to the ideal line of the calibration plot.Independe nt split-sample validation revealed 80.9%(95%Cl:75.5%-84.4%,P<0.001)accuracy.The proposed BOO nomogram based solely on routine clinical parameters was accurate and validated properly.This nomogram may be useful in determining further treatment,primarily focused on prostatic surgery for BOO,without impeding the detection of possible BOO in men with LUTS that is refractory to empirical medications.展开更多
文摘The Service ORiented Computing EnviRonment (SORCER) targets service abstractions for transdisciplinary complexity with support for heterogeneous service-oriented (SO) computing. SORCER's models are expressed in a top-down Var-oriented Modeling Language (VML) unified with programs in a bottoms-up Exertion-Oriented Language (EOL). In this paper the introduction to mogramming (modeling and programing), which uses both languages, is described. First, the emphasis is on modeling with service variables that allow for computational fidelity within VML. Then, seven types of service providers, both local and distributed, are described to form collaborative federations described in EOL. Finally, the unified hybrid of SO modeling and SO programming is presented. Fourteen simple mogramming examples illustrate the syntax and usage of both VML and EOL.
文摘We aimed to develop and validate a clinical nomogram predicting bladder outlet obstruction(BOO)solely using routine clinical parameters in men with refractory nonneurogenic lower urinary tract symptoms(LUTS).A total of 750 eligible patient ≥50 years of age who had previously not responded(International Prostate Symptom Score[IPSS]improvement<4 points)to at least three different kinds of LUTS medications(including a-blocker)for the last 6 months were evaluated as subcohorts for nomogram development(n=570)and for split-sample validation(n=180).BOO was defined as Abrams-Griffiths number^40,or 20-39.9 with a slope of linear passive urethral resistance ratio>2 cmH20 ml^-1 s^-1.A stepwise multivariable logistic regression analysis was conducted to determine the predictors of BOO,and^-coefficients of the final model were selected to create a clinical nomogram.The final multivariable logistic regression model showed that age,IPSS,maximum urinary flow rate,postvoid residual volume,total prostate volume,and transitional zone index were significant for predicting BOO;these candidates were used to develop the final nomogram.The discrimination performance of the nomogram was 88.3%(95%Cl:82.7%-93.0%,P<0.001),and the nomogram was reasonably we 11-fitted to the ideal line of the calibration plot.Independe nt split-sample validation revealed 80.9%(95%Cl:75.5%-84.4%,P<0.001)accuracy.The proposed BOO nomogram based solely on routine clinical parameters was accurate and validated properly.This nomogram may be useful in determining further treatment,primarily focused on prostatic surgery for BOO,without impeding the detection of possible BOO in men with LUTS that is refractory to empirical medications.
