Effects of temperature, ammonium and glucose concentrations on yeast growth in a model wine system

In enology, alcoholic fermentation is a complex process involving several mechanisms. Slow and incomplete alcoholic fermentation is a chronic problem for the wine industry and factors leading to sluggish and stuck fermentations have been extensively studied and reviewed. The most studied cause of sluggish and stuck fermentation is the nitrogen content limitation. Nevertheless, other factors, such as temperature of fermentation and sugar concentration can affect the growth of yeasts. In this study we modelled the yeast growth‐cycle in wine model system as a function of temperature, sugar and ammonium concentrations; the individual effects and the interaction of these factors were analysed by means of a quadratic response surface methodology. Cell concentrations and weight loss were monitored in the whole wine fermentation process. The results of central composite design show that lower is the availability of nitrogen, higher is the cell growth rate; moreover, initial nitrogen concentration also influences survival time of Saccharomyces cerevisiae.     

An adaptive non‐conforming finite‐element method for Reissner–Mindlin plates

Adaptive algorithms are important tools for efficient finite‐element mesh design. In this paper, an error controlled adaptive mesh‐refining algorithm is proposed for a non‐conforming low‐order finite‐element method for the Reissner–Mindlin plate model. The algorithm is controlled by a reliable and efficient residual‐based a posteriori error estimate, which is robust with respect to the plate's thickness. Numerical evidence for this and the efficiency of the new algorithm is provided in the sense that non‐optimal convergence rates are optimally improved in our numerical experiments. Copyright © 2003 John Wiley & Sons, Ltd.     

Object Retrieval in the 1st Year of Life: Learning Effects of Task Exposure and Box Transparency.

Before 12 months of age, infants have difficulties coordinating and sequencing their movements to retrieve an object concealed in a box. This study examined (a) whether young infants can discover effective retrieval solutions and consolidate movement coordination earlier if exposed regularly to such a task and (b) whether different environments, indexed by box transparency, would impact the rate of learning and time of discovery of these solutions. Infants (N=12) were presented with an object retrieval task every week from 6 1/2 months of age until they were able to retrieve the toy from the box using coordinated two-handed patterns for 3 weeks. To reach that criterion, infants tested with an opaque box took 2 1/2 months and infants tested with a semitransparent box took 1 1/2 months. Both groups outperformed age-matched controls who received a one-time exposure to the task. Repeated exposure to the task and vision of the toy significantly enhanced this process of solution discovery. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Benefits of collecting local data on breast cancer and mammography practices in northwestern Pennsylvania

OBJECTIVES: A randomized trial was conducted to evaluate the effectiveness of a work-site health promotion program in reducing obesity and the prevalence of cigarette smoking. METHODS: Thirty-two work sites were randomized to treatment or no treatment for 2 years. Treatment consisted of health education classes combined with a payroll-based incentive system. Evaluation was based on cohort and cross-sectional surveys. RESULTS: Of 10,000 total employees in treatment work sites, 2041 and 270 participated in weight control and smoking cessation programs, respectively. Weight losses averaged 4.8 lbs, and 43% of smoking participants quit. Net 2-year reductions in smoking prevalence in treatment vs control work sites were 4.0% and 2.1% in cross-sectional and cohort surveys, respectively. No treatment effect was found for weight. Treatment effects for smoking prevalence and weight were both positively correlated with participation rates in the intervention programs (r = .45 for smoking and r = .55 for weight). CONCLUSIONS: This work-site health promotion program was effective in reducing smoking prevalence at a cost that is believed to make the investment worthwhile.     

Non-hierarchical logistic models and case-only designs for assessing susceptibility in population-based case-control studies

Mechanisms for the abnormal copper (Cu) accumulation in the liver of LEC rats were examined using primary cultured liver parenchymal cells prepared from mutant LEC rats and those from control LEA rats (original strain). The Cu and metallothionein (MT) mRNA levels in the liver of LEC rats were caused to decrease to the same levels as those of LEA rats by removing Cu in vivo selectively with tetrathiomolybdate. Cu was taken up by LEC rat cells to the same extent as LEA rat cells by exposure to low medium Cu and to a higher extent by exposure to high medium Cu, while the MT mRNA level in LEC rat cells increased dose-dependently at a much higher rate than that in LEA rats. MT mRNA levels in both cells were comparable by exposure to cadmium, zinc and dexamethasone. The results indicate that expression of MT mRNA is selectively enhanced by Cu in LEC cells despite the fact that uptake of Cu is comparable with normal cells.     

Producing content producers [computer animation]

Several off-the-shelf animation software packages provide extensive capabilities, obviating the need for studios to develop their own software, except for highly specialized effects and interfaces. These capabilities make it feasible for a university to educate students in animation production without years of software development. The author discusses The UTS School of Cinema-Television and The USC Computer Animation Laboratory in particular     

Reduced skin tumor development in cyclin D1-deficient mice highlights the oncogenic ras pathway in vivo

Cyclin D1 is part of a cell cycle control node consistently deregulated in most human cancers. However, studies with cyclin D1-null mice indicate that it is dispensable for normal mouse development as well as cell growth in culture. Here, we provide evidence that ras-mediated tumorigenesis depends on signaling pathways that act preferentially through cyclin D1. Cyclin D1 expression and the activity of its associated kinase are up-regulated in keratinocytes in response to oncogenic ras. Furthermore, cyclin D1 deficiency results in up to an 80% decrease in the development of squamous tumors generated through either grafting of retroviral ras-transduced keratinocytes, phorbol ester treatment of ras transgenic mice, or two-stage carcinogenesis.     

Network regression with predictive clustering trees

Network data describe entities represented by nodes, which may be connected with (related to) each other by edges. Many network datasets are characterized by a form of autocorrelation, where the value of a variable at a given node depends on the values of variables at the nodes it is connected with. This phenomenon is a direct violation of the assumption that data are independently and identically distributed. At the same time, it offers an unique opportunity to improve the performance of predictive models on network data, as inferences about one entity can be used to improve inferences about related entities. Regression inference in network data is a challenging task. While many approaches for network classification exist, there are very few approaches for network regression. In this paper, we propose a data mining algorithm, called NCLUS, that explicitly considers autocorrelation when building regression models from network data. The algorithm is based on the concept of predictive clustering trees (PCTs) that can be used for clustering, prediction and multi-target prediction, including multi-target regression and multi-target classification. We evaluate our approach on several real world problems of network regression, coming from the areas of social and spatial networks. Empirical results show that our algorithm performs better than PCTs learned by completely disregarding network information, as well as PCTs that are tailored for spatial data, but do not take autocorrelation into account, and a variety of other existing approaches.