Planning Technologies for Interactive Storytelling

Since AI planning was first proposed for the task of narrative generation in interactive storytelling (IS), it has emerged as the dominant approach in this field. This chapter traces the use of planning technologies in this area, considers the core issues involved in the application of planning technologies in IS, and identifies some of the remaining challenges

Ultrafiltration of whey: membrane performance and modelling using a combined pore blocking-cake formation model

[EN] BACKGROUNDUltrafiltration has been considered as a green' technique to treat different industrial wastewaters, such as whey in the dairy industry. However, fouling is one of the major drawbacks in the industrial implementation of this process. Thus, in this work, the performance of ultrafiltration membranes was investigated in terms of permeate flux and protein rejection when treating different whey model solutions. Modelling of permeate flux was performed combining two main fouling mechanisms (complete pore blocking and cake formation) by a time-dependent pore blocking parameter. RESULTSResults demonstrated that high protein concentration and the presence of calcium salts in the feed solution favoured permeate flux decline. The combined model was appropriate to describe the main fouling mechanisms, with fitting accuracies higher than 0.960. Model parameters were correlated with both calcium and protein concentration and the developed model was successfully validated with an additional fouling test. CONCLUSIONAll the membranes tested were suitable for carrying out whey protein separation, with rejection indexes greater than 99%. The combined model and the statistical correlation of model parameters with calcium and protein concentrations were useful to predict permeate flux decline when the ultrafiltration of a new whey model solution was performed. (c) 2017 Society of Chemical IndustryThis work was supported by the Spanish Ministry of Science and Innovation (project CTM2010-20186).Corbatón Báguena, MJ.; Alvarez Blanco, S.; Vincent Vela, MC. (2018). Ultrafiltration of whey: membrane performance and modelling using a combined pore blocking-cake formation model. Journal of Chemical Technology & Biotechnology. 93(7):1891-1900. https://doi.org/10.1002/jctb.5446]S1891190093

Fouling mechanisms of ultrafiltration membranes fouled with whey model solutions

In this work, three ultrafiltration (UF) membranes with different molecular weight cut-offs (MWCOs) and made of different materials were fouled with several whey model solutions that consisted of bovine serum albumin (BSA) (1% w/w), BSA (1% w/w) and CaCl2 (0.06% w/w in calcium) and whey protein concentrate (WPC) with a total protein content of 45% w/w at three different concentrations (22.2, 33.3 and 44.4 g·L− 1). The influence of MWCO and membrane material on the fouling mechanism dominating the UF process was investigated. Experiments were performed using two flat-sheet organic membranes and a ceramic monotubular membrane whose MWCOs were 5, 30 and 15 kDa, respectively. Hermia's models adapted to crossflow UF, a combined model based on complete blocking and cake formation equations and a resistance-in-series model were fitted to permeate flux decline curves. The results demonstrated that permeate flux decline was accurately predicted by all the models studied. However, the models that fitted the best to permeate flux decline experimental data were the combined model and the resistance-in-series model. Therefore, complete blocking and cake formation were the predominant mechanisms for all the membranes and feed solutions tested.The authors of this work wish to gratefully acknowledge the financial support of the Spanish Ministry of Science and Innovation through the project CTM2010-20186.Corbatón Báguena, MJ.; Alvarez Blanco, S.; Vincent Vela, MC. (2015). Fouling mechanisms of ultrafiltration membranes fouled with whey model solutions. Desalination. 360:87-96. https://doi.org/10.1016/j.desal.2015.01.019S879636

Rare Copy Number Variants Observed in Hereditary Breast Cancer Cases Disrupt Genes in Estrogen Signaling and TP53 Tumor Suppression Network

Breast cancer is the most common cancer in women in developed countries, and the contribution of genetic susceptibility to breast cancer development has been well-recognized. However, a great proportion of these hereditary predisposing factors still remain unidentified. To examine the contribution of rare copy number variants (CNVs) in breast cancer predisposition, high-resolution genome-wide scans were performed on genomic DNA of 103 BRCA1, BRCA2, and PALB2 mutation negative familial breast cancer cases and 128 geographically matched healthy female controls; for replication an independent cohort of 75 similarly mutation negative young breast cancer patients was used. All observed rare variants were confirmed by independent methods. The studied breast cancer cases showed a consistent increase in the frequency of rare CNVs when compared to controls. Furthermore, the biological networks of the disrupted genes differed between the two groups. In familial cases the observed mutations disrupted genes, which were significantly overrepresented in cellular functions related to maintenance of genomic integrity, including DNA double-strand break repair (P = 0.0211). Biological network analysis in the two independent breast cancer cohorts showed that the disrupted genes were closely related to estrogen signaling and TP53 centered tumor suppressor network. These results suggest that rare CNVs represent an alternative source of genetic variation influencing hereditary risk for breast cancer

Early Infant Morbidity in the City of São Paulo, Brazil

BACKGROUND: Early infant morbidities may produce adverse outcomes in subsequent life. A low Apgar score is a convenient measure of early infant morbidity. We study determinants of early infant morbidity (sex, plurality, mode of delivery, prior losses, gestational age, prenatal care and birth weight, parity and maternal age, race, maternal education and community development) for the 1998-birth cohort, City of São Paulo, Brazil. METHODS: This study identified all deliveries that took place in the City of São Paulo during 1998. Information was extracted from 209,628 birth records. We used multivariate logistic regression to assess the effect of each independent variable on Apgar score less than seven at one minute and Apgar score less than seven at five minutes. RESULTS: Low birth weight, prematurity and community development were found to be strong predictors of morbidity. Maternal education showed strong negative correlation with both Apgar scores. The negative correlations between maternal schooling and Apgar scores were observed after prenatal care, parity and maternal age were included in the model. Unmeasured proximate factors may thus be the true source of disparity between educational groups. Children of very young adolescent mothers had lower Apgar scores at one minute (but not at five minutes) than those born to mothers 15 to 19. Parity one or higher was associated with decreased odds of low Apgar scores. Cesarean section and operative delivery were associated with higher odds of early infant morbidity. CONCLUSION: Education may allow mothers to have better care in the peripartum period. More educated mothers may be more likely to recognize certain morbidities through the pregnancy period and the monitoring of such morbidities yields better infant outcomes. Also, having less than seven prenatal care visits was found to predict early infant morbidity and one way to increase the use of such services is to focus on aspects of care that may lead to easier accessibility and continuity of prenatal care. Physicians should inform mothers about the risks associated with high number of children for a next infant and also about the risks for the infant associated with unnecessary cesarean sections. Special attention should be paid to adolescent mothers, since much of their increased risk is likely to be minimized by counseling

Estrogenic Plant Extracts Reverse Weight Gain and Fat Accumulation without Causing Mammary Gland or Uterine Proliferation

Long-term estrogen deficiency increases the risk of obesity, diabetes and metabolic syndrome in postmenopausal women. Menopausal hormone therapy containing estrogens might prevent these conditions, but its prolonged use increases the risk of breast cancer, as wells as endometrial cancer if used without progestins. Animal studies indicate that beneficial effects of estrogens in adipose tissue and adverse effects on mammary gland and uterus are mediated by estrogen receptor alpha (ERα). One strategy to improve the safety of estrogens to prevent/treat obesity, diabetes and metabolic syndrome is to develop estrogens that act as agonists in adipose tissue, but not in mammary gland and uterus. We considered plant extracts, which have been the source of many pharmaceuticals, as a source of tissue selective estrogens. Extracts from two plants, Glycyrrhiza uralensis (RG) and Pueraria montana var. lobata (RP) bound to ERα, activated ERα responsive reporters, and reversed weight gain and fat accumulation comparable to estradiol in ovariectomized obese mice maintained on a high fat diet. Unlike estradiol, RG and RP did not induce proliferative effects on mammary gland and uterus. Gene expression profiling demonstrated that RG and RP induced estradiol-like regulation of genes in abdominal fat, but not in mammary gland and uterus. The compounds in extracts from RG and RP might constitute a new class of tissue selective estrogens to reverse weight gain, fat accumulation and metabolic syndrome in postmenopausal women