Protoplast Fusion of Koji-Mold Aspergillus spp. to Improve Kecap Production.

ABSTRACT Protoplast fusion of Aspergillus oryzae and A. niger for improving the enzyme productivity of desirable kojimolds for kecap (Indonesian soy sauce) was studied. Protoplasting of both mycellium aspergilli was obtained by treating them using Novozyme 234, at final concen tration 5 mg/ml and the time of exposure for three and two hours. Regenerated protoplasts of A. oryzae on complete medium (RCMMPA) was 1.46-3.74 % and on minimal medium (RMMPA) was 0.93-4.93%, whereas A. niger was 0.44-7.64 % and 0.17-6.25 %, respectively. Protoplast fusion was conducted in 30 % PEG 6000 (Polyethylene Glycol) containing 0.01 M CaC12 and 0.05 % glycine, and at pH 7.5. For selecting the suspected fusant Dinikonasol 12.5%, at the final concentration 200 ppm and Cycloheximide at the final concentration 100 ppm Was used as a marker. Results showed that hundred eighteen of suspected fusants were obtained and after screening found that seven as selected fusants. Based on the enzyme activities, finally, fusant number 77 was selected as a fusant with high proteolytic and glutaminase activities. Keywords: Protoplast fusion, Koji, Kecap, Aspergillus

Projective simulation for artificial intelligence

We propose a model of a learning agent whose interaction with the environment is governed by a simulation-based projection, which allows the agent to project itself into future situations before it takes real action. Projective simulation is based on a random walk through a network of clips, which are elementary patches of episodic memory. The network of clips changes dynamically, both due to new perceptual input and due to certain compositional principles of the simulation process. During simulation, the clips are screened for specific features which trigger factual action of the agent. The scheme is different from other, computational, notions of simulation, and it provides a new element in an embodied cognitive science approach to intelligent action and learning. Our model provides a natural route for generalization to quantum-mechanical operation and connects the fields of reinforcement learning and quantum computation.Comment: 22 pages, 18 figures. Close to published version, with footnotes retaine

Stochastic population growth in spatially heterogeneous environments

Classical ecological theory predicts that environmental stochasticity increases extinction risk by reducing the average per-capita growth rate of populations. To understand the interactive effects of environmental stochasticity, spatial heterogeneity, and dispersal on population growth, we study the following model for population abundances in $n$ patches: the conditional law of $X_{t+dt}$ given $X_t=x$ is such that when $dt$ is small the conditional mean of $X_{t+dt}^i-X_t^i$ is approximately $[x^i\mu_i+\sum_j(x^j D_{ji}-x^i D_{ij})]dt$, where $X_t^i$ and $\mu_i$ are the abundance and per capita growth rate in the $i$-th patch respectivly, and $D_{ij}$ is the dispersal rate from the $i$-th to the $j$-th patch, and the conditional covariance of $X_{t+dt}^i-X_t^i$ and $X_{t+dt}^j-X_t^j$ is approximately $x^i x^j \sigma_{ij}dt$. We show for such a spatially extended population that if $S_t=(X_t^1+...+X_t^n)$ is the total population abundance, then $Y_t=X_t/S_t$, the vector of patch proportions, converges in law to a random vector $Y_\infty$ as $t\to\infty$, and the stochastic growth rate $\lim_{t\to\infty}t^{-1}\log S_t$ equals the space-time average per-capita growth rate \sum_i\mu_i\E[Y_\infty^i] experienced by the population minus half of the space-time average temporal variation \E[\sum_{i,j}\sigma_{ij}Y_\infty^i Y_\infty^j] experienced by the population. We derive analytic results for the law of $Y_\infty$, find which choice of the dispersal mechanism $D$ produces an optimal stochastic growth rate for a freely dispersing population, and investigate the effect on the stochastic growth rate of constraints on dispersal rates. Our results provide fundamental insights into "ideal free" movement in the face of uncertainty, the persistence of coupled sink populations, the evolution of dispersal rates, and the single large or several small (SLOSS) debate in conservation biology.Comment: 47 pages, 4 figure

Rubber Impact on 3D Textile Composites

A low velocity impact study of aircraft tire rubber on 3D textile-reinforced composite plates was performed experimentally and numerically. In contrast to regular unidirectional composite laminates, no delaminations occur in such a 3D textile composite. Yarn decohesions, matrix cracks and yarn ruptures have been identified as the major damage mechanisms under impact load. An increase in the number of 3D warp yarns is proposed to improve the impact damage resistance. The characteristic of a rubber impact is the high amount of elastic energy stored in the impactor during impact, which was more than 90% of the initial kinetic energy. This large geometrical deformation of the rubber during impact leads to a less localised loading of the target structure and poses great challenges for the numerical modelling. A hyperelastic Mooney-Rivlin constitutive law was used in Abaqus/Explicit based on a step-by-step validation with static rubber compression tests and low velocity impact tests on aluminium plates. Simulation models of the textile weave were developed on the meso- and macro-scale. The final correlation between impact simulation results on 3D textile-reinforced composite plates and impact test data was promising, highlighting the potential of such numerical simulation tools

Prevalence of Symptomatic Heart Failure with Reduced and with Normal Ejection Fraction in an Elderly General Population-The CARLA Study

Background/Objectives: Chronic heart failure (CHF) is one of the most important public health concerns in the industrialized world having increasing incidence and prevalence. Although there are several studies describing the prevalence of heart failure with reduced ejection fraction (HFREF) and heart failure with normal ejection fraction (HFNEF) in selected populations, there are few data regarding the prevalence and the determinants of symptomatic heart failure in the general population. Methods: Cross-sectional data of a population-based German sample (1,779 subjects aged 45-83 years) were analyzed to determine the prevalence and determinants of chronic SHF and HFNEF defined according to the European Society of Cardiology using symptoms, echocardiography and serum NT-proBNP. Prevalence was age-standardized to the German population as of December 31st, 2005. Results: The overall age-standardized prevalence of symptomatic CHF was 7.7% (95%CI 6.0-9.8) for men and 9.0% (95%CI 7.0-11.5) for women. The prevalence of CHF strongly increased with age from 3.0% among 45-54- year-old subjects to 22.0% among 75-83- year-old subjects. Symptomatic HFREF could be shown in 48% (n = 78), symptomatic HFNEF in 52% (n = 85) of subjects with CHF. The age-standardized prevalence of HFREF was 3.8 % (95%CI 2.4-5.8) for women and 4.6 % (95%CI 3.6-6.3) for men. The age-standardized prevalence of HFNEF for women and men was 5.1 % (95%CI 3.8-7.0) and 3.0 % (95%CI 2.1-4.5), respectively. Persons with CHF were more likely to have hypertension (PR = 3.4; 95%CI 1.6-7.3) or to have had a previous myocardial infarction (PR = 2.5, 95%CI 1.8-3.5). Conclusion: The prevalence of symptomatic CHF appears high in this population compared with other studies. While more women were affected by HFNEF than men, more male subjects suffered from HFREF. The high prevalence of symptomatic CHF seems likely to be mainly due to the high prevalence of cardiovascular risk factors in this population