scholarly journals A simplified treatment of surfactant effects on cloud drop activation

2010 ◽  
Vol 3 (3) ◽  
pp. 1139-1159 ◽  
Author(s):  
T. Raatikainen ◽  
A. Laaksonen
Keyword(s):  
Large Scale ◽  
Computing Time ◽  
Active Species ◽  
Cloud Droplets ◽  
Cloud Models ◽  
Nested Iterations ◽  
Order Of Magnitude ◽  
Surface Active ◽  
Solution Surface ◽  
Surfactant Effects

Abstract. Dissolved surface active species, or surfactants, have a tendency to partition to solution surface and thereby decrease solution surface tension. Activating cloud droplets have large surface-to-volume ratios, and the amount of surfactant molecules in them is limited. Therefore, unlike with macroscopic solutions, partitioning to the surface can effectively deplete the droplet interior of surfactant molecules. Surfactant partitioning equilibrium for activating cloud droplets can be solved numerically from a group of equations. This can be a problem when surfactant effects are examined by using large-scale cloud models. Namely, computing time increases significantly due to the partitioning calculations done in the lowest levels of nested iterations. The purpose of this paper is to present analytical equations for surfactant partitioning equilibrium. Some simplifications are needed in deriving the equations, but the numerical errors caused by the simplifications are shown to be very minor. In addition, computing time is decreased roughly by an order of magnitude.

scholarly journals A simplified treatment of surfactant effects on cloud drop activation

2011 ◽  
Vol 4 (1) ◽  
pp. 107-116 ◽  
Author(s):  
T. Raatikainen ◽  
A. Laaksonen
Keyword(s):  
Surface Tension ◽  
Analytical Solutions ◽  
Linear Equations ◽  
Computing Time ◽  
Cloud Droplets ◽  
Cloud Models ◽  
Non Linear ◽  
Solution Surface ◽  
Surfactant Effects ◽  
Non Linear Equations

Abstract. Dissolved surface active species, or surfactants, have a tendency to partition to solution surface and thereby decrease solution surface tension. Activating cloud droplets have large surface-to-volume ratios, and the amount of surfactant molecules in them is limited. Therefore, unlike with macroscopic solutions, partitioning to the surface can effectively deplete the droplet interior of surfactant molecules. Surfactant partitioning equilibrium for activating cloud droplets has so far been solved numerically from a group of non-linear equations containing the Gibbs adsorption equation coupled with a surface tension model and an optional activity coefficient model. This can be a problem when surfactant effects are examined by using large-scale cloud models. Namely, computing time increases significantly due to the partitioning calculations done in the lowest levels of nested iterations. Our purpose is to reduce the group of non-linear equations to simple polynomial equations with well known analytical solutions. In order to do that, we describe surface tension lowering using the Szyskowski equation, and ignore all droplet solution non-idealities. It is assumed that there is only one surfactant exhibiting bulk-surface partitioning, but the number of non-surfactant solutes is unlimited. It is shown that the simplifications cause only minor errors to predicted bulk solution concentrations and cloud droplet activation. In addition, computing time is decreased at least by an order of magnitude when using the analytical solutions.

scholarly journals Nebula: ultra-efficient mapping-free structural variant genotyper

2021 ◽  
Author(s):  
Parsoa Khorsand ◽  
Fereydoun Hormozdiari
Keyword(s):  
Large Scale ◽  
Structural Variants ◽  
Sequencing Technologies ◽  
Generic Framework ◽  
Common Genetic Variants ◽  
Order Of Magnitude ◽  
Complex Events ◽  
Comparable Accuracy ◽  
Using Data ◽  
Computational Resources

Abstract Large scale catalogs of common genetic variants (including indels and structural variants) are being created using data from second and third generation whole-genome sequencing technologies. However, the genotyping of these variants in newly sequenced samples is a nontrivial task that requires extensive computational resources. Furthermore, current approaches are mostly limited to only specific types of variants and are generally prone to various errors and ambiguities when genotyping complex events. We are proposing an ultra-efficient approach for genotyping any type of structural variation that is not limited by the shortcomings and complexities of current mapping-based approaches. Our method Nebula utilizes the changes in the count of k-mers to predict the genotype of structural variants. We have shown that not only Nebula is an order of magnitude faster than mapping based approaches for genotyping structural variants, but also has comparable accuracy to state-of-the-art approaches. Furthermore, Nebula is a generic framework not limited to any specific type of event. Nebula is publicly available at https://github.com/Parsoa/Nebula.

scholarly journals Selective hydroboration of unsaturated bonds by an easily accessible heterotopic cobalt catalyst

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Chuhan Li ◽  
Shuo Song ◽  
Yuling Li ◽  
Chang Xu ◽  
Qiquan Luo ◽  
...  
Keyword(s):  
Base Metal ◽  
Large Scale ◽  
Metal Cluster ◽  
Active Species ◽  
Cobalt Catalysts ◽  
Metal Salts ◽  
One Pot ◽  
Practical Utilization ◽  
Earth Abundant

AbstractHomogeneous earth-abundant metal catalysis based on well-defined molecular complexes has achieved great advance in synthetic methodologies. However, sophisticated ligand, hazardous activator and multistep synthesis starting from base metal salts are generally required for the generation of active molecular catalysts, which may hinder their broad application in large scale organic synthesis. Therefore, the development of metal cluster catalysts formed in situ from simple earth-abundant metal salts is of importance for the practical utilization of base metal resource, yet it is still in its infancy. Herein, a mixture of catalytic amounts of cobalt (II) iodide and potassium tert-butoxide is discovered to be highly active for selective hydroboration of vinylarenes and dihydroboration of nitriles, affording a good yield of diversified hydroboration products that without isolation can readily undergo further one pot transformations. It should be highlighted that the alkoxide-pinacolborane combination acts as an efficient activation strategy to activate cobalt (II) iodide for the generation of metastable heterotopic cobalt catalysts in situ, which is proposed to be catalytically active species.

Efficient and High-Quality Seeded Graph Matching: Employing Higher-order Structural Information

2021 ◽  
Vol 15 (3) ◽  
pp. 1-31
Author(s):  
Haida Zhang ◽  
Zengfeng Huang ◽  
Xuemin Lin ◽  
Zhe Lin ◽  
Wenjie Zhang ◽  
...  
Keyword(s):  
Large Scale ◽  
Graph Matching ◽  
Structural Information ◽  
Experimental Studies ◽  
Higher Order ◽  
Personalized Pagerank ◽  
Matching Accuracy ◽  
Approximation Techniques ◽  
Order Of Magnitude ◽  
Matching Score

Driven by many real applications, we study the problem of seeded graph matching. Given two graphs and , and a small set of pre-matched node pairs where and , the problem is to identify a matching between and growing from , such that each pair in the matching corresponds to the same underlying entity. Recent studies on efficient and effective seeded graph matching have drawn a great deal of attention and many popular methods are largely based on exploring the similarity between local structures to identify matching pairs. While these recent techniques work provably well on random graphs, their accuracy is low over many real networks. In this work, we propose to utilize higher-order neighboring information to improve the matching accuracy and efficiency. As a result, a new framework of seeded graph matching is proposed, which employs Personalized PageRank (PPR) to quantify the matching score of each node pair. To further boost the matching accuracy, we propose a novel postponing strategy, which postpones the selection of pairs that have competitors with similar matching scores. We show that the postpone strategy indeed significantly improves the matching accuracy. To improve the scalability of matching large graphs, we also propose efficient approximation techniques based on algorithms for computing PPR heavy hitters. Our comprehensive experimental studies on large-scale real datasets demonstrate that, compared with state-of-the-art approaches, our framework not only increases the precision and recall both by a significant margin but also achieves speed-up up to more than one order of magnitude.

Approximate Solution of Nonclassically Damped Systems

1991 ◽  
Author(s):  
F. Ma ◽  
J. H. Hwang
Keyword(s):  
Approximate Solution ◽  
Large Scale ◽  
Computational Effort ◽  
Frequency Separation ◽  
Common Procedure ◽  
Damping Matrix ◽  
Complex Modes ◽  
Modal Coupling ◽  
Order Of Magnitude ◽  
Damped Systems

Abstract In analyzing a nonclassically damped linear system, one common procedure is to neglect those damping terms which are nonclassical, and retain the classical ones. This approach is termed the method of approximate decoupling. For large-scale systems, the computational effort at adopting approximate decoupling is at least an order of magnitude smaller than the method of complex modes. In this paper, the error introduced by approximate decoupling is evaluated. A tight error bound, which can be computed with relative ease, is given for this method of approximate solution. The role that modal coupling plays in the control of error is clarified. If the normalized damping matrix is strongly diagonally dominant, it is shown that adequate frequency separation is not necessary to ensure small errors.

A Fast and Scalable Heuristic for the Solution of Large-Scale Capacitated Vehicle Routing Problems

2021 ◽  
Author(s):  
Luca Accorsi ◽  
Daniele Vigo
Keyword(s):  
Vehicle Routing ◽  
Large Scale ◽  
Computing Time ◽  
Search Space ◽  
Iterated Local Search ◽  
Solution Quality ◽  
Routing Problem ◽  
Acceptance Criterion ◽  
Acceleration Techniques ◽  
Capacitated Vehicle

In this paper, we propose a fast and scalable, yet effective, metaheuristic called FILO to solve large-scale instances of the Capacitated Vehicle Routing Problem. Our approach consists of a main iterative part, based on the Iterated Local Search paradigm, which employs a carefully designed combination of existing acceleration techniques, as well as novel strategies to keep the optimization localized, controlled, and tailored to the current instance and solution. A Simulated Annealing-based neighbor acceptance criterion is used to obtain a continuous diversification, to ensure the exploration of different regions of the search space. Results on extensively studied benchmark instances from the literature, supported by a thorough analysis of the algorithm’s main components, show the effectiveness of the proposed design choices, making FILO highly competitive with existing state-of-the-art algorithms, both in terms of computing time and solution quality. Finally, guidelines for possible efficient implementations, algorithm source code, and a library of reusable components are open-sourced to allow reproduction of our results and promote further investigations.

scholarly journals Psychometric properties of the Adelaide Diagnostic Learning Inventory - Brief (ADLIB)

2019 ◽  
Author(s):  
Harry Minas
Keyword(s):  
Academic Performance ◽  
Learning Styles ◽  
University Students ◽  
Psychometric Properties ◽  
Factor Structure ◽  
Life Stress ◽  
Large Scale ◽  
Well Being ◽  
Factor Congruence ◽  
Order Of Magnitude

Abstract Objective: There has been increased attention in recent years to mental health, quality of life, stress and academic performance among university students, and the possible influence of learning styles. Brief reliable questionnaires are useful in large-scale multivariate research designs, such as the largely survey-based research on well-being and academic performance of university students. The objective of this study was to examine the psychometric properties of a briefer version of the 39-item Adelaide Diagnostic Learning Inventory. Results: In two survey samples - medical and physiotherapy students - a 21-item version Adelaide Diagnostic Learning Inventory - Brief (ADLIB) was shown to have the same factor structure as the parent instrument, and the factor structure of the brief instrument was found to generalise across students of medicine and physiotherapy. Sub-scale reliability estimations were in the order of magnitude of the parent instrument. Sub-scale inter-correlations, inter-factor congruence coefficients, and correlations between ADLIB sub-scale scores and several external measures provide support support for the construct and criterion validity of the instrument.

scholarly journals Best-first Enumeration Based on Bounding Conflicts, and its Application to Large-scale Hybrid Estimation (Extended Abstract)

2020 ◽  
Author(s):  
Eric Timmons ◽  
Brian C. Williams
Keyword(s):  
Large Scale ◽  
Search Space ◽  
Estimation Methods ◽  
Directed Search ◽  
Hybrid Estimation ◽  
Continuous State ◽  
Order Of Magnitude ◽  
State Models ◽  
The Cost ◽  
Belief States

State estimation methods based on hybrid discrete and continuous state models have emerged as a method of precisely computing belief states for real world systems, however they have difficulty scaling to systems with more than a handful of components. Classical, consistency based diagnosis methods scale to this level by combining best-first enumeration and conflict-directed search. While best-first methods have been developed for hybrid estimation, conflict-directed methods have thus far been elusive as conflicts summarize constraint violations, but probabilistic hybrid estimation is relatively unconstrained. In this paper we present an approach (A*BC) that unifies best-first enumeration and conflict-directed search in relatively unconstrained problems through the concept of "bounding" conflicts, an extension of conflicts that represent tighter bounds on the cost of regions of the search space. Experiments show that an A*BC powered state estimator produces estimates up to an order of magnitude faster than the current state of the art, particularly on large systems.

scholarly journals Observations on aerosol optical properties and scavenging during cloud events

2020 ◽  
Author(s):  
Antti Ruuskanen ◽  
Sami Romakkaniemi ◽  
Harri Kokkola ◽  
Antti Arola ◽  
Santtu Mikkonen ◽  
...  
Keyword(s):  
Large Scale ◽  
Aerosol Composition ◽  
Cloud Droplets ◽  
Inlet System ◽  
Scattering Coefficients ◽  
Stratus Clouds ◽  
Absorbing Material ◽  
Scattering Material ◽  
Cloud Scavenging ◽  
Increasing Temperature

Abstract. Long term statistics of atmospheric aerosol and especially cloud scavenging were studied at the Puijo measurement station in Kuopio, Finland, during October 2010–November 2014. Aerosol size distributions, scattering coefficients at three different wavelengths (450 nm, 550 nm, and 700 nm), and absorption coefficient at wavelength 637 nm were measured with a special inlet system to sample interstitial and total aerosol in clouds. On average, accumulation mode particle concentration was found to be temperature dependent with lowest average concentrations of 200 cm−3 around 0 °C increasing to more than 800 cm−3 for temperatures higher than 20 °C. From the in-cloud measurements, both scattering and absorbing material scavenging efficiencies were observed to have slightly increasing temperature dependence. At 0 °C the efficiencies of scattering and absorbing matter were 0.85 and 0.55 with slopes of 0.005 °C−1 and 0.003 °C−1, respectively. Additionally, scavenging efficiencies were studied as a function of the diameter at which half of the particles are activated into cloud droplets. This analysis indicated that the is a higher fraction of absorbing material, typically black carbon, in smaller sizes so that at least 20–30 % of interstitial particles within clouds consist of absorbing material. In addition, the PM1-inlet revealed that approximately 20 % of absorbing material was observed to reside in particles with ambient diameter larger than ~ 1 µm at relative humidity below 90 %. Similarly, 40 % of scattering material was seen to be in particles larger than 1 µm. Altogether, this dataset provides information on size dependent aerosol composition that can be applied in evaluating how well large-scale aerosol models reproduce aerosol composition, especially with respect to scavenging in stratus clouds.

Sign in / Sign up

Export Citation Format

Share Document