Improvements to the use of the Trajectory-Adaptive Multilevel Sampling algorithm for the study of rare events

Abstract. The Trajectory-Adaptive Multilevel Sampling (TAMS) is a promising method to determine probabilities of noise-induced transition in multi-stable high-dimensional dynamical systems. In this paper, we focus on two improvements of the current algorithm related to (i) the choice of the target set and (ii) the formulation of the score function. In particular, we use confidence ellipsoids determined from linearised dynamics in the choice of the target set. Furthermore, we define a score function based on empirical transition paths computed at relatively high noise levels. The suggested new TAMS method is applied to two typical problems illustrating the benefits of the modifications.

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Improvements to the use of the Trajectory-Adaptive Multilevel Sampling algorithm for the study of rare events

10.5194/npg-2020-35 ◽

2020 ◽

Author(s):

Pascal Wang ◽

Daniele Castellana ◽

Henk Dijkstra

Keyword(s):

Dynamical Systems ◽

Score Function ◽

High Dimensional ◽

Noise Levels ◽

Sampling Algorithm ◽

High Noise ◽

Multilevel Sampling ◽

Current Algorithm ◽

Target Set ◽

Transition Paths

Abstract. The Trajectory-Adaptive Multilevel Sampling (TAMS) is a promising method to determine probabilities of noise induced transition in multi-stable high-dimensional dynamical systems. In this paper, we focus on two improvements of the current algorithm related to (i) the choice of the target set and (ii) the formulation of the score function. In particular, we use confidence ellipsoids determined from linearized dynamics in the choice of the target set. Furthermore, we define a score function based on empirical transition paths computed at relatively high noise levels. The suggested new TAMS method is applied to two typical problems illustrating the benefits of the modifications.

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The physical environment

10.1093/oso/9780198827238.003.0003 ◽

2018 ◽

Author(s):

Philip James

Keyword(s):

Physical Environment ◽

Urban Climate ◽

Urban Environments ◽

Artificial Light ◽

Noise Levels ◽

Light At Night ◽

High Noise ◽

P Elements ◽

Micro Organisms ◽

Diversity Of Life

Elements of the physical aspects of urban environments determine which micro-organisms, plants, and animals live in urban environments. In this chapter, climate, air, water, soil, noise, and light are discussed. Urban environments are affected by the climate of the region in which they are located, and in turn and create their own, distinctive urban climate. Air, water, and soil are all affected by urbanization. Pollution of these elements is common. High noise levels and artificial light at night (ALAN—a new phenomenon) are both strongly associated with urban environments. Details of both are discussed. The discussion in this chapter provides a foundation for further exploration of the diversity of life in urban environments and for later exploration of how organisms adapt to urban living, which will be discussed in Parts II and III.

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Improved Vancouver Raman Algorithm Based on Empirical Mode Decomposition for Denoising Biological Samples

Applied Spectroscopy ◽

10.1177/0003702819860121 ◽

2019 ◽

Vol 73 (12) ◽

pp. 1436-1450 ◽

Cited By ~ 1

Author(s):

Fabiola León-Bejarano ◽

Martin O. Méndez ◽

Miguel G. Ramírez-Elías ◽

Alfonso Alba

Keyword(s):

Empirical Mode Decomposition ◽

Raman Spectra ◽

Biological Samples ◽

Biological Material ◽

Noise Levels ◽

Synthetic Material ◽

High Noise ◽

Mode Decomposition ◽

Mean Filter ◽

The Mean

A novel method based on the Vancouver Raman algorithm (VRA) and empirical mode decomposition (EMD) for denoising Raman spectra of biological samples is presented. The VRA is one of the most used methods for denoising Raman spectroscopy and is composed of two main steps: signal filtering and polynomial fitting. However, the signal filtering step consists in a simple mean filter that could eliminate spectrum peaks with small intensities or merge relatively close spectrum peaks into one single peak. Thus, the result is often sensitive to the order of the mean filter, so the user must choose it carefully to obtain the expected result; this introduces subjectivity in the process. To overcome these disadvantages, we propose a new algorithm, namely the modified-VRA (mVRA) with the following improvements: (1) to replace the mean filter step by EMD as an adaptive parameter-free signal processing method; and (2) to automate the selection of polynomial degree. The denoising capabilities of VRA, EMD, and mVRA were compared in Raman spectra of artificial data based on Teflon material, synthetic material obtained from vitamin E and paracetamol, and biological material of human nails and mouse brain. The correlation coefficient (ρ) was used to compare the performance of the methods. For the artificial Raman spectra, the denoised signal obtained by mVRA ([Formula: see text]) outperforms VRA ([Formula: see text]) for moderate to high noise levels whereas mVRA outperformed EMD ([Formula: see text]) for high noise levels. On the other hand, when it comes to modeling the underlying fluorescence signal of the samples (i.e., the baseline trend), the proposed method mVRA showed consistent results ([Formula: see text]. For Raman spectra of synthetic material, good performance of the three methods ([Formula: see text] for VRA, [Formula: see text] for EMD, and [Formula: see text] for mVRA) was obtained. Finally, in the biological material, mVRA and VRA showed similar results ([Formula: see text] for VRA, [Formula: see text] for EMD, and [Formula: see text] for mVRA); however, mVRA retains valuable information corresponding to relevant Raman peaks with small amplitude. Thus, the application of EMD as a filter in the VRA method provides a good alternative for denoising biological Raman spectra, since the information of the Raman peaks is conserved and parameter tuning is not required. Simultaneously, EMD allows the baseline correction to be automated.

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Nonlinear reduction of high-dimensional dynamical systems via neural networks

Physical Review Letters ◽

10.1103/physrevlett.72.1822 ◽

1994 ◽

Vol 72 (12) ◽

pp. 1822-1825 ◽

Cited By ~ 17

Author(s):

Michael Kirby ◽

Rick Miranda

Keyword(s):

Neural Networks ◽

Dynamical Systems ◽

High Dimensional

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HIGH-DIMENSIONAL CHAOS IN DISSIPATIVE AND DRIVEN DYNAMICAL SYSTEMS

International Journal of Bifurcation and Chaos ◽

10.1142/s0218127409024517 ◽

2009 ◽

Vol 19 (09) ◽

pp. 2823-2869 ◽

Cited By ~ 23

Author(s):

Z. E. MUSIELAK ◽

D. E. MUSIELAK

Keyword(s):

Dynamical Systems ◽

Degrees Of Freedom ◽

Nonlinear Dynamical Systems ◽

High Dimensional ◽

Van Der Pol ◽

Nonlinear Dynamical ◽

Onset Of Chaos ◽

General Rules ◽

Van Der Pol Oscillators ◽

Control And Synchronization

Studies of nonlinear dynamical systems with many degrees of freedom show that the behavior of these systems is significantly different as compared with the behavior of systems with less than two degrees of freedom. These findings motivated us to carry out a survey of research focusing on the behavior of high-dimensional chaos, which include onset of chaos, routes to chaos and the persistence of chaos. This paper reports on various methods of generating and investigating nonlinear, dissipative and driven dynamical systems that exhibit high-dimensional chaos, and reviews recent results in this new field of research. We study high-dimensional Lorenz, Duffing, Rössler and Van der Pol oscillators, modified canonical Chua's circuits, and other dynamical systems and maps, and we formulate general rules of high-dimensional chaos. Basic techniques of chaos control and synchronization developed for high-dimensional dynamical systems are also reviewed.

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Noise Pollution in Onitsha Metropolis: Challenges and Solution

Open Access Research Journal of Engineering and Technology ◽

10.53022/oarjet.2021.1.2.0110 ◽

2021 ◽

Vol 1 (2) ◽

pp. 032-040

Author(s):

Chris Onyeka Ekweozor ◽

Johnbosco Emeka Umunnakwe ◽

Leo O Osuji ◽

Vincent C Weli

Keyword(s):

State Government ◽

Noise Level ◽

Control Point ◽

Noise Pollution ◽

Health Impact ◽

Dry Season ◽

Noise Levels ◽

Wet Season ◽

High Noise ◽

Anambra State

This study evaluated noise pollution in Onitsha metropolis, Anambra State, Nigeria in 2019. Noise levels were measured at forty sampling stations in the morning, afternoon and night within the study area for dry and wet seasons using modern noise level instruments. A control point was established at ldeani/Nnobi Junction with coordinates N 06o 05’.282’’ E 006o 55’.891’’ which was used as a reference point and for comparison with the sound levels recorded in designated locations. The results showed that the maximum noise level in the study area exceeded the Federal Ministry of Environment (FMEnv) limit by 7.8% in the dry season and by 13.11% in the wet season. Noise LAeq exceeded the NESREA LAeq limit by 29.89% in the dry season and by 33.44% in the wet season. The study indicated that the mean noise levels in the dry and wet seasons were within FMEnv limit of 90dB .It also showed that high noise levels were recorded around major junctions and market places within Onitsha, which are harmful to public health. The study further showed that transportation activities and trading activities at the market places are the main sources of high noise levels in the study area. Health impact assessment should be conducted in Onitsha metropolis for residents. State government should enforce compliance laws and regulate the activities of industries in the areas.

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The sound of potency: An observation study of nurses’ approach to sound in a pediatric intensive care unit

Clinical Nursing Studies ◽

10.5430/cns.v5n2p46 ◽

2017 ◽

Vol 5 (2) ◽

pp. 46

Author(s):

Emma Mellgren ◽

Janet Mattsson

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Pediatric Intensive Care Unit ◽

Pediatric Intensive Care ◽

Well Being ◽

High Tech ◽

Noise Levels ◽

Observation Study ◽

Care Environment ◽

High Noise

Objective: The objective of this study was to investigate the nurses’ approach to three sources of sound that contribute to high noise levels; alarms, doors that open and conversation.Methods: Methods used derived from a theoretical perspective based on interpretive phenomenology and caring culture. In the pediatric intensive care, the caregivers of the children work in a high-tech environment as they are surrounded by sound from several sources. How caregivers understand and acknowledge how these sounds negatively affect a child’s well-being depends on their individual knowledge and awareness of how children are affected by sound. In most cases, coming into an intensive care unit is a new experience for a child. This causes greater stress, both from the environment itself as well as from sound levels. The method was built on a phenomenological perspective and an interpretive non-participation, semi-structured observations were conducted in a pediatric intensive care unit (PICU) of one of Sweden’s metropolitan regions in the winter of 2014-2015.Results: The results show that noise is an overlooked phenomenon in the pediatric intensive care environment as it has given way to other priorities in the nurse’s work. It is also apparent that this depends on the department’s caring culture as it prioritizes other things, resulting in normalizing high levels of noise as a part of the pediatric intensive care environment.Conclusions: Noise levels are not a priority in the department’s caring culture. High noise levels are permitted unreflectedly and appears to be a token of potency and an accepted part of the health care environment.

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S254 – Bone Conduction Noise Exposure via Ventilators in the NICU

Otolaryngology ◽

10.1016/j.otohns.2008.05.430 ◽

2008 ◽

Vol 139 (2_suppl) ◽

pp. P160-P160

Author(s):

Angela P Black ◽

James D Sidman

Keyword(s):

Ambient Noise ◽

Noise Exposure ◽

Bone Conduction ◽

Sound Level ◽

Noise Levels ◽

High Noise ◽

Endotracheal Tubes ◽

Level Meter ◽

Hearing Damage ◽

Air Conduction

Objectives To demonstrate that neonatal ventilators produce high noise levels through bone conduction (BC) via endotracheal tubes, as well as air conduction (AC) from ambient noise. Methods A sound level meter was used to measure the noise levels 4 feet from the ventilator and in direct contact at the end of a balloon attached to the ETT to simulate the noise presented to the infant. 3 commonly used neonatal ventilators (Sensormedics 3100A, VIP Bird and Bunnell Jet) were examined. Results Noise levels were significantly higher (6 – 14 dB) at the end of the ETT than 4 ft from the ventilator for all ventilators studied. Conclusions Previous studies have shown high ambient noise levels in NICUs, but have failed to address the actual noise presented to the infant. ETT transmission of noise as a direct bone stimulus through the skull has been overlooked. This study has shown that high noise intensities are being presented not only as AC, but as BC to the infants though the ETT. This study demonstrates, therefore, that ear protection alone will not save these at-risk infants from hearing damage. More must be done to decrease noise exposure and develop quieter machines.

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