An effective way to accelerate rare events in molecular dynamics simulations is to apply a bias potential which destabilizes minima without biasing the transitions between stable states. This approach, called hyperdynamics, is limited by our ability to construct general bias potentials without having to understand the reaction mechanisms available to the system, a priori. Current bias potentials are typically constructed in terms of a metric which quantifies the distance that a trajectory deviates from the reactant state minimum. Such metrics include detection of negative curvatures of the potential, an energy increase, or deviations in bond lengths from the minimum. When one of these properties exceeds a critical value, the bias potentials are constructed to approach zero. A problem common to each of these schemes is that their effectiveness decreases rapidly with system size. We attribute this problem to a diminishing volume defined by the metrics around a reactant minimum as compared to the total volume of the reactant state basin. In this work, we mitigate the dimensionality scaling problem by constructing bias potentials that are based upon the distance to the boundary of the reactant basin. This distance is quantified in two ways: (i) by following the minimum mode direction to the reactant boundary and (ii) by training a machine learning algorithm to give an analytic expression for the boundary to which the distance can be calculated. Both of these ridge-based bias potentials are demonstrated to scale qualitatively better with dimensionality than the existing methods. We attribute this improvement to a greater filling fraction of the reactant state using the ridge-based bias potentials as compared to the standard potentials.
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http://dx.doi.org/10.1063/1.4937393 | DOI Listing |
J Med Internet Res
January 2025
School of Nursing, Anhui Medical University, Hefei, China.
Background: Body image issues are prevalent among individuals diagnosed with cancer, leading to detrimental effects on their physical and psychological recovery. eHealth has emerged as a promising approach for enhancing the body image of patients with cancer.
Objective: The purpose of this study was to evaluate the effectiveness of eHealth interventions on body image and other health outcomes (quality of life, physical symptoms, and emotional distress) among patients with cancer.
JMIR Res Protoc
January 2025
INSERM, Methods in Patient-Centered Outcomes and Health Research, SPHERE, F-44000, Nantes Université, University of Tours, Nantes, France.
Background: : With more than 60 million new cases around the world each year, traumatic brain injury (TBI) causes substantial mortality and morbidity. Managing TBI is a major human, social, and economic concern. In the last 20 years, there has been an increase in clinical trials in neurocritical care, leading mostly to negative results.
View Article and Find Full Text PDFPlast Reconstr Surg
December 2024
Department of Plastic Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, South Korea.
Background: Despite the recent steep rise in the use of prepectoral direct-to-implant (DTI) breast reconstruction, concerns remain regarding the potentially risk of complications, resulting in the selective application of the technique; however, the selection process was empirically based on the operator's decision. Using patient and operation-related factors, this study aimed to develop a nomogram for predicting postoperative complications following prepectoral DTI reconstruction.
Methods: Between August 2019 and March 2023, immediate prepectoral DTI was performed for all patients deemed suitable for one-stage implant-based reconstruction.
J Speech Lang Hear Res
January 2025
Department of Psychology, University of Western Ontario, London, Canada.
Purpose: Recent advances in artificial intelligence provide opportunities to capture and represent complex features of human language in a more automated manner, offering potential means of improving the efficiency of language assessment. This review article presents computerized approaches for the analysis of narrative language and identification of language disorders in children.
Method: We first describe the current barriers to clinicians' use of language sample analysis, narrative language sampling approaches, and the data processing stages that precede analysis.
J Clin Endocrinol Metab
January 2025
Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada.
Objective: To examine the evidence addressing the management of X-linked hypophosphatemia (XLH) in children to inform treatment recommendations.
Methods: We searched Embase, MEDLINE, Web of Science, and Cochrane Central up to May 2023. Eligible studies included RCTs and observational studies of individuals less than 18yrs with clinically or genetically confirmed XLH.
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