Speeding up Monte Carlo molecular simulation by a non-conservative early rejection scheme

Monte Carlo (MC) molecular simulation describes fluid systems with rich information, and it is capable of predicting many fluid properties of engineering interest. In general, it is more accurate and representative than equations of state. On the other hand, it requires much more computational effort and simulation time. For that purpose, several techniques have been developed in order to speed up MC molecular simulations while preserving their precision. In particular, early rejection schemes are capable of reducing computational cost by reaching the rejection decision for the undesired MC trials at an earlier stage in comparison to the conventional scheme. In a recent work, we have introduced a ‘conservative’ early rejection scheme as a method to accelerate MC simulations while producing exactly the same results as the conventional algorithm. In this paper, we introduce a ‘non-conservative’ early rejection scheme, which is much faster than the conservative scheme, yet it preserves the precision of the method. The proposed scheme is tested for systems of structureless Lennard-Jones particles in both canonical and NVT-Gibbs ensembles. Numerical experiments were conducted at several thermodynamic conditions for different number of particles. Results show that at certain thermodynamic conditions, the non-conservative method is capable of doubling the speed of the MC molecular simulations in both canonical and NVT-Gibbs ensembles.     

Dosimetric impact of statistical uncertainty on Monte Carlo dose calculation algorithm in volumetric modulated arc therapy using Monaco TPS for three different clinical cases

AimTo study the dosimetric impact of statistical uncertainty (SU) per plan on Monte Carlo (MC) calculation in Monaco? treatment planning system (TPS) during volumetric modulated arc therapy (VMAT) for three different clinical cases.BackgroundDuring MC calculation SU is an important factor to decide dose calculation accuracy and calculation time. It is necessary to evaluate optimal acceptance of SU for quality plan with reduced calculation time.Materials and methodsThree different clinical cases as the lung, larynx, and prostate treated using VMAT technique were chosen. Plans were generated with Monaco? V5.11 TPS with 2% statistical uncertainty. By keeping all other parameters constant, plans were recalculated by varying SU, 0.5%, 1%, 2%, 3%, 4%, and 5%. For plan evaluation, conformity index (CI), homogeneity index (HI), dose coverage to PTV, organ at risk (OAR) dose, normal tissue receiving dose ≥5 Gy and ≥10 Gy, integral dose (NTID), calculation time, gamma pass rate, calculation reproducibility and energy dependency were analyzed.ResultsCI and HI improve as SU increases from 0.5% to 5%. No significant dose difference was observed in dose coverage to PTV, OAR doses, normal tissue receiving dose ≥5 Gy and ≥10 Gy and NTID. Increase of SU showed decrease in calculation time, gamma pass rate and increase in PTV max dose. No dose difference was seen in calculation reproducibility and dependent on energy.ConclusionFor VMAT plans, SU can be accepted from 1% to 3% per plan with reduced calculation time without compromising plan quality and deliverability by accepting variations in point dose within the target.     

CORAL: Building up QSAR models for the chromosome aberration test

A high level of chromosomal aberrations in peripheral blood lymphocytes may be an early marker of cancer risk, but data on risk of specific cancers and types of chromosomal aberrations are limited. Consequently, the development of predictive models for chromosomal aberrations test is important task. Majority of models for chromosomal aberrations test are so-called knowledge-based rules system. The CORAL software (http://www.insilico.eu/coral, abbreviation of “CORrelation And Logic”) is an alternative for knowledge-based rules system. In contrast to knowledge-based rules system, the CORAL software gives possibility to estimate the influence upon the predictive potential of a model of different molecular alerts as well as different splits into the training set and validation set. This possibility is not available for the approaches based on the knowledge-based rules system. Quantitative Structure–Activity Relationships (QSAR) for chromosome aberration test are established for five random splits into the training, calibration, and validation sets. The QSAR approach is based on representation of the molecular structure by simplified molecular input-line entry system (SMILES) without data on physicochemical and/or biochemical parameters. In spite of this limitation, the statistical quality of these models is quite good.     

Direct seeding and outplantings in drylands of Argentinean Patagonia: estimated costs,and prospects for large‐scale restoration and rehabilitation

In large areas of the world that are deeply scarred by desertification and hampered by low capacity for natural regeneration, the scaling up of ecological restoration and rehabilitation can be achieved only if it is low in cost with high return on investment, and shows promise of providing long‐lasting social‐economic as well as ecological benefits. In the Monte Austral region of Patagonia Argentina, concerted efforts are underway to facilitate scaling up of ecological restoration and rehabilitation practices. Here, we evaluate financial costs and preliminary results of direct seeding as compared to outplanting of nursery‐grown seedlings of three native species (Atriplex lampa, Senecio subulatus var. subulatus, and Hyalis argentea var. latisquama) considered to be high‐priority dryland framework species. Comparative success is expressed in terms of plant survival and in monetary terms. The three candidate species showed low survival rates, ranging from 4.3 to 22.3%, after the first summer following direct seeding. In contrast, survival rates for planted seedlings of the same three taxa varied between 84 and 91%, after the first summer following reintroduction. However, cost of direct seeding varied between 1,693 and 1,772 US$ less per hectare, that is, 64% less than the cost of outplanting nursery seedlings. Therefore, in the search for ways to scale up ecological restoration and rehabilitation in drylands, direct seeding should receive more attention. We discuss the social and ecological perspectives and the way forward for direct seeding techniques in Patagonia. We also consider how costs could be reduced and effectiveness improved in large‐scale efforts.     

Physiological model using diffuse reflectance spectroscopy for nonmelanoma skin cancer diagnosis

Diffuse reflectance spectroscopy (DRS) is a noninvasive, fast, and low‐cost technology with potential to assist cancer diagnosis. The goal of this study was to test the capability of our physiological model, a computational Monte Carlo lookup table inverse model, for nonmelanoma skin cancer diagnosis. We applied this model on a clinical DRS dataset to extract scattering parameters, blood volume fraction, oxygen saturation and vessel radius. We found that the model was able to capture physiological information relevant to skin cancer. We used the extracted parameters to classify (basal cell carcinoma [BCC], squamous cell carcinoma [SCC]) vs actinic keratosis (AK) and (BCC, SCC, AK) vs normal. The area under the receiver operating characteristic curve achieved by the classifiers trained on the parameters extracted using the physiological model is comparable to that of classifiers trained on features extracted via Principal Component Analysis. Our findings suggest that DRS can reveal physiologic characteristics of skin and this physiologic model offers greater flexibility for diagnosing skin cancer than a pure statistical analysis. Physiological parameters extracted from diffuse reflectance spectra data for nonmelanoma skin cancer diagnosis.     

On the relative stabilities of the alkali cations 222 cryptates in the gas phase and in water-methanol solution

The relative stabilities of the alkali [M ⊂ 222]⁺ cryptates (M = Na, K, Rb and Cs) in the gas phase and in solution (80:20 v/v methanol:water mixture) at 298 K, are computed using a combination of ab initio quantum-chemical calculations (HF/6-31G and MP2/6-31+G*//HF/6-31+G*) and explicit-solvent Monte Carlo free-energy simulations. The results suggest that the relative stabilities of the cryptates in solution are due to a combination of steric effects (compression of large ions within the cryptand cavity), electronic effects (delocalization of the ionic charge onto the cryptand atoms) and solvent effects (dominantly the ionic dessolvation penalty). Thus, the relative stabilities in solution cannot be rationalized solely on the basis of a simple match or mismatch between the ionic radius and the cryptand cavity size as has been suggested previously. For example, although the [K ⊂ 222]⁺ cryptate is found to be the most stable in solution, in agreement with experimental data, it is the [Na ⊂ 222]⁺ cryptate that is the most stable in the gas phase. The present results provide further support to the notion that the solvent in which supramolecules are dissolved plays a key role in modulating molecular recognition processes. Figure Alkali cryptates [M ⊂ 222]+ (M = Na, K, Rb and Cs) relative stabilities in gas and methanol:water solution: solvent effects and molecular recognition

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Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Evolutionary constraints on polyembryony in parasitic wasps: a simulation model

Polyembryony involves the production of several genetically identical progeny from a single egg through clonal division. Although polyembryonic development allows highly efficient reproduction, especially in some parasitoid wasps, it is far less common than monoembryony (development of one embryo per egg). To understand what might constrain the evolutionary success of polyembryony in parasitoids, we developed Monte Carlo models that simulate the competition between polyembryonic females and their monoembryonic counterparts. We investigated which simulated life‐history traits of the females allow the monoembryonic mode of development to succeed. Published empirical studies were surveyed to explore whether these traits indeed differ between polyembryonic parasitoids and related monoembryonic species. The simulations predict an advantage to monoembryony in parasitoids whose reproduction is limited by host availability rather than by egg supply, and that parasitize small‐bodied hosts. Comparative data on the parasitoid families Encyrtidae and (to a lesser extent) Braconidae, but not the data from Platygastridae, circumstantially support these predictions. The model also predicts monoembryony to outcompete polyembryony when: 1) hosts vary considerably in quality, 2) polyembryonic development carries high physiological costs, and 3) monoembryonic females make optimal clutch size decisions upon attacking hosts. These multiple constraints may account for the rarity of polyembryony among parasitoid species.     

Quantifying personal exposure to air pollution from smartphone‐based location data

Personal exposure assessment is a challenging task that requires both measurements of the state of the environment as well as the individual's movements. In this paper, we show how location data collected by smartphone applications can be exploited to quantify the personal exposure of a large group of people to air pollution. A Bayesian approach that blends air quality monitoring data with individual location data is proposed to assess the individual exposure over time, under uncertainty of both the pollutant level and the individual location. A comparison with personal exposure obtained assuming fixed locations for the individuals is also provided. Location data collected by the Earthquake Network research project are employed to quantify the dynamic personal exposure to fine particulate matter of around 2500 people living in Santiago (Chile) over a 4‐month period. For around 30% of individuals, the personal exposure based on people movements emerges significantly different over the static exposure. On the basis of this result and thanks to a simulation study, we claim that even when the individual location is known with nonnegligible error, this helps to better assess personal exposure to air pollution. The approach is flexible and can be adopted to quantify the personal exposure based on any location‐aware smartphone application.     

MolMod – an open access database of force fields for molecular simulations of fluids

The MolMod database is presented, which is openly accessible at http://molmod.boltzmann-zuse.de and contains intermolecular force fields for over 150 pure fluids at present. It was developed and is maintained by the Boltzmann-Zuse Society for Computational Molecular Engineering (BZS). The set of molecular models in the MolMod database provides a coherent framework for molecular simulations of fluids. The molecular models in the MolMod database consist of Lennard-Jones interaction sites, point charges, and point dipoles and quadrupoles, which can be equivalently represented by multiple point charges. The force fields can be exported as input files for the simulation programmes ms2 and ls1 mardyn, GROMACS, and LAMMPS. To characterise the semantics associated with the numerical database content, a force field nomenclature is introduced that can also be used in other contexts in materials modelling at the atomistic and mesoscopic levels. The models of the pure substances that are included in the database were generally optimised such as to yield good representations of experimental data of the vapour–liquid equilibrium with a focus on the vapour pressure and the saturated liquid density. In many cases, the models also yield good predictions of caloric, transport, and interfacial properties of the pure fluids. For all models, references to the original works in which they were developed are provided. The models can be used straightforwardly for predictions of properties of fluid mixtures using established combination rules. Input errors are a major source of errors in simulations. The MolMod database contributes to reducing such errors.     

蒙特卡罗模拟多束光辐照下生物组织中的光吸收分布

用蒙特卡罗方法模拟了均匀分布光和高斯分布光在生物组织内的传播。通过比较单束以及多束均匀分布光和高斯分布光照射下组织内的光子能量分布规律,分析了不同光源和光斑大小对光吸收分布的影响。结果表明:与均匀光束比较,高斯光束辐照时,激光能量较为集中,但侧向传播范围较窄。在总功率相同的情况下,使用单束大功率宽光源与多束功率较小的小光斑光源均能明显地增大光的侧向传播距离,但使用多束功率较小的小光斑光辐照时生物组织中的最大光吸收率增大。多束组合光源光束间距对光吸收分布影响很大。