Stretching Homopolymers

Force induced stretching of polymers is important in a variety of contexts. We have used theory and simulations to describe the response of homopolymers, with $N$ monomers, to force ($f$) in good and poor solvents. In good solvents and for {{sufficiently large}} $N$ we show, in accord with scaling predictions, that the mean extension along the $f$ axis $\sim f$ for small $f$, and $\sim f^{{2/3}}$ (the Pincus regime) for intermediate values of $f$. The theoretical predictions for \la Z\ra as a function of $f$ are in excellent agreement with simulations for N=100 and 1600. However, even with N=1600, the expected Pincus regime is not observed due to the the breakdown of the assumptions in the blob picture for finite $N$. {{We predict the Pincus scaling in a good solvent will be observed for $N\gtrsim 10^5$}}. The force-dependent structure factors for a polymer in a poor solvent show that there are a hierarchy of structures, depending on the nature of the solvent. For a weakly hydrophobic polymer, various structures (ideal conformations, self-avoiding chains, globules, and rods) emerge on distinct length scales as $f$ is varied. A strongly hydrophobic polymer remains globular as long as $f$ is less than a critical value $f_c$. Above $f_c$, an abrupt first order transition to a rod-like structure occurs. Our predictions can be tested using single molecule experiments.Comment: 24 pages, 7 figure

Depletion effects and loop formation in self-avoiding polymers

Langevin dynamics is employed to study the looping kinetics of self-avoiding polymers both in ideal and crowded solutions. A rich kinetics results from the competition of two crowding-induced effects: the depletion attraction and the enhanced viscous friction. For short chains, the enhanced friction slows down looping, while, for longer chains, the depletion attraction renders it more frequent and persistent. We discuss the possible relevance of the findings for chromatin looping in living cells.Comment: 4 pages, 3 figure

Mortality as a key driver of the spatial distribution of aboveground biomass in Amazonian forest: Results from a dynamic vegetation model

International audienceDynamic Vegetation Models (DVMs) simulate energy, water and carbon fluxes between the ecosystem and the atmosphere, between the vegetation and the soil, and between plant organs. They also estimate the potential biomass of a forest in equilibrium having grown under a given climate and atmospheric CO2 level. In this study, we evaluate the Above Ground Woody Biomass (AGWB) and the above ground woody Net Primary Productivity (NPPAGW) simulated by the DVM ORCHIDEE across Amazonian forests, by comparing the simulation results to a large set of ground measurements (220 sites for biomass, 104 sites for NPPAGW). We found that the NPPAGW is on average overestimated by 63%. We also found that the fraction of biomass that is lost through mortality is 85% too high. These model biases nearly compensate each other to give an average simulated AGWB close to the ground measurement average. Nevertheless, the simulated AGWB spatial distribution differs significantly from the observations. Then, we analyse the discrepancies in biomass with regards to discrepancies in NPPAGW and those in the rate of mortality. When we correct for the error in NPPAGW, the errors on the spatial variations in AGWB are exacerbated, showing clearly that a large part of the misrepresentation of biomass comes from a wrong modelling of mortality processes. Previous studies showed that Amazonian forests with high productivity have a higher mortality rate than forests with lower productivity. We introduce this relationship, which results in strongly improved modelling of biomass and of its spatial variations. We discuss the possibility of modifying the mortality modelling in ORCHIDEE, and the opportunity to improve forest productivity modelling through the integration of biomass measurements, in particular from remote sensing. © Author(s) 2010

Chemical constituents and antibacterial activity of essential oils in <i>Amomum longiligulare</i> from Vietnam

This paper reports the chemical constituents and the antibacterial activity of essential oils from the leaves, rhizomes, and fruits of Amomum longiligulare T.L. Wu (Zingiberaceae) obtained by microwave-assisted hydrodistillation. The essential oils were analyzed by gas chromatography–mass spectrometry techniques. The minimum inhibitory concentration (MIC) values were measured by the broth microdilution assay. The oil yields of leaves, rhizomes and fruits from A. longiligulare were 0.23%, 0.27% and 1.93% (v/w), respectively, calculated on a dry weight basis. The leaf essential oil comprised mainly α-humulene (28.4%), α-pinene (24.9%), β-caryophyllene (17.3%), humulene epoxide II (7.3%), and β-pinene (4.7%). The major compounds of the rhizome essential oil were β-caryophyllene (28.7%), bicyclogermacrene (17.1%), humulene epoxide II (10.5%), camphene (7.9%), and α-pinene (5.7%). Camphor (40.7%) and bornyl acetate (34.2%) were the main constituents of the fruit oil. The essential oils demonstrated antimicrobial activities against Staphylococcus aureus, Bacillus cereus, Escherichia coli, and Pseudomonas aeruginosa with the MIC values ranging from 200 to 400 μg/mL. In summary, the A. longiligulare essential oils are a source of promising antibacterial agents. This is the first report on the chemical composition and antibacterial activity of A. longiligulare essential oil obtained by microwave-assisted hydrodistillation

Generalizing DP-SGD with Shuffling and Batch Clipping

Classical differential private DP-SGD implements individual clipping with random subsampling, which forces a mini-batch SGD approach. We provide a general differential private algorithmic framework that goes beyond DP-SGD and allows any possible first order optimizers (e.g., classical SGD and momentum based SGD approaches) in combination with batch clipping, which clips an aggregate of computed gradients rather than summing clipped gradients (as is done in individual clipping). The framework also admits sampling techniques beyond random subsampling such as shuffling. Our DP analysis follows the $f$-DP approach and introduces a new proof technique which allows us to derive simple closed form expressions and to also analyse group privacy. In particular, for $E$ epochs work and groups of size $g$, we show a $\sqrt{g E}$ DP dependency for batch clipping with shuffling.Comment: Update disclaimer

Batch Clipping and Adaptive Layerwise Clipping for Differential Private Stochastic Gradient Descent

Each round in Differential Private Stochastic Gradient Descent (DPSGD) transmits a sum of clipped gradients obfuscated with Gaussian noise to a central server which uses this to update a global model which often represents a deep neural network. Since the clipped gradients are computed separately, which we call Individual Clipping (IC), deep neural networks like resnet-18 cannot use Batch Normalization Layers (BNL) which is a crucial component in deep neural networks for achieving a high accuracy. To utilize BNL, we introduce Batch Clipping (BC) where, instead of clipping single gradients as in the orginal DPSGD, we average and clip batches of gradients. Moreover, the model entries of different layers have different sensitivities to the added Gaussian noise. Therefore, Adaptive Layerwise Clipping methods (ALC), where each layer has its own adaptively finetuned clipping constant, have been introduced and studied, but so far without rigorous DP proofs. In this paper, we propose {\em a new ALC and provide rigorous DP proofs for both BC and ALC}. Experiments show that our modified DPSGD with BC and ALC for CIFAR-$10$ with resnet-$18$ converges while DPSGD with IC and ALC does not.Comment: 20 pages, 18 Figure

Роль страхования экспортных кредитов для развития российской экспортной торговли

Since the Russian Agency for Export Credit and Investment Insurance (EXIAR) was established in 2011, only a few scientists have bothered to substantiate of the Agency’s economic policy. The aim of the paper is to investigate the role of EXIAR economic policy in promoting the growth of Russia’s export trade. The current study conducts methods such as statistical, comparative and empirical analysis of panel data on the basis of econometric models. The results of the research suggest that export credit insurance can be useful for the development of Russian export trade, especially for exports to high-risk developing countries and to high-value-added Russian exporting enterprises, such as machinery, electrical and chemical-pharmaceutical industries. The authors suggest that Russia should raise the status of export credit insurance, increase the penetration rate of high-tech goods into key countries-importers, improve the foreign trade oppor tunities of exporting enterprises.С момента создания в 2011 г. Российского агентства по страхованию экспортных кредитов (ЭКСАР) лишь немногие ученые потрудились обосновать эффект экономической политики Агентства. Цель исследования - определить роль экономической политики ЭКСАР в содействии росту экспортной торговли России. В настоящем исследовании использованы методы статистического, сравнительного и эмпирического анализа панельных данных на базе эконометрических моделей. Результаты исследования показывают, что страхование экспортных кредитов может быть полезным для развития российской экспортной торговли, особенно для экспорта в развивающиеся страны с более высоким уровнем риска и для российских экспортирующих предприятий с более высокой добавленной стоимостью, таких как машиностроительные, электротехнические и химико-фармацевтические. Предлагается, что России следует повысить статус страхования экспортных кредитов, усилить степень проникновения в ключевые страны - импортеры продукции высокотехнологичных отраслей, улучшив внешнеторговые возможности экспортирующих предприятий