Forecasting with Big Data: A Review

Big Data is a revolutionary phenomenon which is one of the most frequently discussed topics in the modern age, and is expected to remain so in the foreseeable future. In this paper we present a comprehensive review on the use of Big Data for forecasting by identifying and reviewing the problems, potential, challenges and most importantly the related applications. Skills, hardware and software, algorithm architecture, statistical significance, the signal to noise ratio and the nature of Big Data itself are identified as the major challenges which are hindering the process of obtaining meaningful forecasts from Big Data. The review finds that at present, the fields of Economics, Energy and Population Dynamics have been the major exploiters of Big Data forecasting whilst Factor models, Bayesian models and Neural Networks are the most common tools adopted for forecasting with Big Data

More resistant tendons obtained from the association of Heteropterys aphrodisiaca and endurance training

<p>Abstract</p> <p>Background</p> <p>Popular Brazilian medicine uses <it>Heteropterys aphrodisiaca </it>infusion as a tonic or stimulant, for the treatment of nervous debility and breakdown and for muscle and bone weakness. This study investigated the effects of <it>Heteropterys aphrodisiaca </it>infusion on the tendon properties and extracellular matrix of rats under endurance training.</p> <p>Methods</p> <p>Wistar rats were grouped as follows: CS- control sedentary, HS- <it>H. aphrodisiaca </it>sedentary, CT-control trained, HT- <it>H. aphrodisiaca </it>trained. The training protocol consisted in running on a motorized treadmill, five times a week, with weekly increase in treadmill speed and duration. Control groups received water while the HS and HT groups received <it>H. aphrodisiaca </it>infusion, daily, by gavage for the 8 weeks of training. Achilles tendons were frozen for biochemical and biomechanical analysis or preserved in Karnovsky's fixative, then processed for histomorphological analysis with light microscopy.</p> <p>Results</p> <p>Biomechanical analysis showed significant increase in maximum load, maximum stress, modulus of elasticity and stiffness of the HT animals' tendons. The metalloproteinase-2 activity was reduced in the HT group. The compression region of HT animals' tendons had a stronger and more intense metachromasy, which suggests an increase in glycosaminoglycan concentration in this region of the tendon. The most intense birefringence was observed in both compression and tension regions of HT animals' tendons, which may indicate a higher organizational level of collagen bundles. The hydroxyproline content increased in the HT group.</p> <p>Conclusions</p> <p>The association of endurance training with <it>H. aphrodisiaca </it>resulted in more organized collagen bundles and more resistant tendons to support higher loads from intense muscle contraction. Despite the clear anabolic effects of <it>Heteropterys aphrodisiaca </it>and the endurance exercise association, no side effects were observed, such as those found for synthetic anabolic androgenic steroids.</p

Selection on Alleles Affecting Human Longevity and Late-Life Disease: The Example of Apolipoprotein E

It is often claimed that genes affecting health in old age, such as cardiovascular and Alzheimer diseases, are beyond the reach of natural selection. We show in a simulation study based on known genetic (apolipoprotein E) and non-genetic risk factors (gender, diet, smoking, alcohol, exercise) that, because there is a statistical distribution of ages at which these genes exert their influence on morbidity and mortality, the effects of selection are in fact non-negligible. A gradual increase with each generation of the ε2 and ε3 alleles of the gene at the expense of the ε4 allele was predicted from the model. The ε2 allele frequency was found to increase slightly more rapidly than that for ε3, although there was no statistically significant difference between the two. Our result may explain the recent evolutionary history of the epsilon 2, 3 and 4 alleles of the apolipoprotein E gene and has wider relevance for genes affecting human longevity

A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes(1). Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel(2)) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants