Results 161 to 170 of about 25,080,125 (309)

Laparoscopic Colorectal Surgery in the Era of Robotics: Evolution, Eclipse, or Equilibrium?

Annals of Gastroenterological Surgery, EarlyView.
ABSTRACT Minimally invasive colorectal surgery has undergone a remarkable transformation over the past three decades. Laparoscopy, once viewed with skepticism, is now firmly established as a standard approach, supported by robust randomized trials demonstrating oncologic safety and improved recovery compared to open surgery.
Amanjeet Singh, Archit Gupta, Azhar Perwaiz, Adarsh Chaudhary   +3 more
wiley   +1 more source

Evaluation of Experienced Manipulation Characteristics in Robotic Surgery Using Log Data From the Hinotori Surgical System

Annals of Gastroenterological Surgery, EarlyView.
This study analyzed log data from the Japanese hinotori surgical robot to characterize manipulation performed by experienced surgeons in robotic surgery. Compared with less‐experienced surgeons, the experienced group demonstrated shorter task durations, reduced travel distances with the right instrument (Arm3), faster and more dynamically modulated ...
Masaki Saito, Shunsuke Hayakawa, Hiroyuki Sagawa, Tamiaki Kondo, Masanao Ohashi, Sunao Ito, Reo Sato, Hajime Ushigome, Kenta Saito, Ryo Ogawa, Hiroki Takahashi, Shuji Takiguchi   +11 more
wiley   +1 more source

Budget System Reform in Emerging Economies the Challenges And the Reform Agenda

, 2006
J. Diamond
semanticscholar   +1 more source

A multiscale Bayesian optimization framework for process and material codesign

AIChE Journal, EarlyView.
Abstract The simultaneous design of processes and enabling materials such as solvents, catalysts, and adsorbents is challenging because molecular‐ and process‐level decisions are strongly interdependent. Sequential approaches often yield suboptimal results since improvements in material properties may not translate into superior process performance. We
Michael Baldea
wiley   +1 more source

Historical-institutionalist perspectives on the development of the EU budget system

, 2006
R. Ackrill, A. Kay
semanticscholar   +1 more source

Trust‐region filter algorithms utilizing Hessian information for gray‐box optimization

AIChE Journal, EarlyView.
Abstract Optimizing industrial processes often involves gray‐box models that couple algebraic glass‐box equations with black‐box components lacking analytic derivatives. Such systems challenge derivative‐based solvers. The classical trust‐region filter (TRF) algorithm provides a robust framework but requires extensive parameter tuning and numerous ...
Gul Hameed, Tao Chen, Antonio del Rio Chanona, Lorenz T. Biegler, Michael Short   +4 more
wiley   +1 more source

A trust‐region funnel algorithm for gray‐box optimization

AIChE Journal, EarlyView.
Abstract Gray‐box optimization, where parts of optimization problems are represented by algebraic models while others are treated as black‐box models lacking analytic derivatives, remains a challenge. Trust‐region (TR) methods provide a robust framework for gray‐box problems through local reduced models (RMs) for black‐box components, but they are ...
Gul Hameed, Tao Chen, Antonio del Rio Chanona, Lorenz T. Biegler, Michael Short   +4 more
wiley   +1 more source

Paying for hospital care in seven central and Eastern European countries - a comparative analysis. [PDF]

Health Econ Rev
Dubas-Jakóbczyk K, Davidovics K, Dimova A, Habicht T, Hroboň P, Imre L, Kasekamp K, Minev M, Murauskienė L, Smatana M, Rethazi G, Szalayova A, Szetela A, Šlegerová L, Topór-Mądry R.   +14 more
europepmc   +1 more source

Sequential Monte Carlo with likelihood tempering and parallel implementation for uncertainty quantification

AIChE Journal, EarlyView.
Abstract Bayesian estimation enables uncertainty quantification, but analytical implementation is often intractable. As an approximate approach, the Markov Chain Monte Carlo (MCMC) method is widely used, though it entails a high computational cost due to frequent evaluations of the likelihood function.
Tatsuki Maruchi, Tomoyuki Yajima, Yoshiaki Kawajiri   +2 more
wiley   +1 more source

Graph‐based imitation and reinforcement learning for efficient Benders decomposition

AIChE Journal, EarlyView.
Abstract This work introduces an end‐to‐end graph‐based agent for accelerating the computational efficiency of Benders Decomposition. The agent's policy is parameterized by a graph neural network, which takes as input a bipartite graph representation of the master problem and proposes a candidate solution.
Bernard T. Agyeman, Zhe Li, Ilias Mitrai, Prodromos Daoutidis   +3 more
wiley   +1 more source