A framework for automatic semantic video annotation

The rapidly increasing quantity of publicly available videos has driven research into developing automatic tools for indexing, rating, searching and retrieval. Textual semantic representations, such as tagging, labelling and annotation, are often important factors in the process of indexing any video, because of their user-friendly way of representing the semantics appropriate for search and retrieval. Ideally, this annotation should be inspired by the human cognitive way of perceiving and of describing videos. The difference between the low-level visual contents and the corresponding human perception is referred to as the ‘semantic gap’. Tackling this gap is even harder in the case of unconstrained videos, mainly due to the lack of any previous information about the analyzed video on the one hand, and the huge amount of generic knowledge required on the other. This paper introduces a framework for the Automatic Semantic Annotation of unconstrained videos. The proposed framework utilizes two non-domain-specific layers: low-level visual similarity matching, and an annotation analysis that employs commonsense knowledgebases. Commonsense ontology is created by incorporating multiple-structured semantic relationships. Experiments and black-box tests are carried out on standard video databases for action recognition and video information retrieval. White-box tests examine the performance of the individual intermediate layers of the framework, and the evaluation of the results and the statistical analysis show that integrating visual similarity matching with commonsense semantic relationships provides an effective approach to automated video annotation

A stochastic evolutionary model for capturing human dynamics

The recent interest in human dynamics has led researchers to investigate the stochastic processes that explain human behaviour in various contexts. Here we propose a generative model to capture the dynamics of survival analysis, traditionally employed in clinical trials and reliability analysis in engineering. We derive a general solution for the model in the form of a product, and then a continuous approximation to the solution via the renewal equation describing age-structured population dynamics. This enables us to model a wide range of survival distributions, according to the choice of the mortality distribution. We provide empirical evidence for the validity of the model from a longitudinal data set of popular search engine queries over 114 months, showing that the survival function of these queries is closely matched by the solution for our model with power-law mortality

Cystic Fibrosis: A New Target for 4-Imidazo[2,1-b]thiazole-1,4-dihydropyridines

The pharmacology of the cystic fibrosis transmembrane conductance regulator (CFTR) Cl(-) channel has attracted significant interest in recent years with the aim to search for rational new therapies for diseases caused by CFTR malfunction. Mutations that abolish the function of CFTR cause the life-threatening genetic disease cystic fibrosis (CF). The most common cause of CF is the deletion of phenylalanine 508 (ΔF508) in the CFTR chloride channel. Felodipine, nifedipine, and other antihypertensive 1,4-dihydropyridines (1,4-DHPs) that block L-type Ca(2+) channels are also effective potentiators of CFTR gating, able to correct the defective activity of ΔF508 and other CFTR mutants ( Mol. Pharmacol. 2005 , 68 , 1736 ). For this purpose, we evaluated the ability of the previously and newly synthesized 4-imidazo[2,1-b]thiazoles-1,4-dihydropyridines without vascular activity and inotropic and/or chronotropic cardiac effects ( J. Med. Chem. 2008 , 51 , 1592 ) to enhance the activity of ΔF508-CFTR. Our studies indicate compounds 17, 18, 20, 21, 38, and 39 as 1,4-DHPs with an interesting profile of activity

Discovery of a novel class of negative allosteric modulator of the dopamine D2 receptor through fragmentation of a bitopic ligand

We recently demonstrated that SB269652 (1) engages one protomer of a dopamine D2 receptor (D2R) dimer in a bitopic mode to allosterically inhibit the binding of dopamine at the other protomer. Herein, we investigate structural deter- minants for allostery, focusing on modifications to three moieties within 1. We find that orthosteric “head” groups with small 7-substituents were important to maintain the limited negative cooperativity of analogues of 1, and replacement of the tetrahydroisoquinoline head group with other D2R “privileged structures” generated orthosteric antagonists. Additionally, replacement of the cyclohexylene linker with polymethylene chains conferred linker length dependency in allosteric pharmacology. We validated the importance of the indolic NH as a hydrogen bond donor moiety for maintaining allostery. Replacement of the indole ring with azaindole conferred a 30-fold increase in affinity while maintaining negative cooperativity. Combined, these results provide novel SAR insight for bitopic ligands that act as negative allosteric modulators of the D2R

The species diversity × fire severity relationship is hump-shaped in semiarid yellow pine and mixed conifer forests

The combination of direct human influences and the effects of climate change are resulting in altered ecological disturbance regimes, and this is especially the case for wildfires. Many regions that historically experienced low–moderate severity fire regimes are seeing increased area burned at high severity as a result of interactions between high fuel loads and climate warming with a number of negative ecological effects. While ecosystem impacts of altered fire regimes have been examined in the literature, little is known of the effects of changing fire regimes on forest understory plant diversity even though understory taxa comprise the vast majority of forest plant species and play vital roles in overall ecosystem function. We examined understory plant diversity across gradients of wildfire severity in eight large wildfires in yellow pine and mixed conifer temperate forests of the Sierra Nevada, California, USA. We found a generally unimodal hump-shaped relationship between local (alpha) plant diversity and fire severity. High-severity burning resulted in lower local diversity as well as some homogenization of the flora at the regional scale. Fire severity class, post-fire litter cover, and annual precipitation were the best predictors of understory species diversity. Our research suggests that increases in fire severity in systems historically characterized by low and moderate severity fire may lead to plant diversity losses. These findings indicate that global patterns of increasing fire size and severity may have important implications for biodiversity

How informative is a negative finding in a small pharmacogenetic study?

Many pharmacogenetic studies fail to yield any statistically significant associations. Such negative findings may be due to the absence of, or inadequate statistical power to test for, an effect at the genetic variants tested. In many instances, sample sizes are small, making it unclear how to interpret the absence of statistically significant findings. We demonstrate that the amount of information that can be drawn from a negative study is improved by incorporating statistical power and the added context of well-validated pharmacogenetic effects into the interpretation process. This approach permits clearer inferences to be made about the possible range of genetic effects that may be present in, or are likely absent from, small drug studies

Actionable, Pathogenic Incidental Findings in 1,000 Participants’ Exomes

The incorporation of genomics into medicine is stimulating interest on the return of incidental findings (IFs) from exome and genome sequencing. However, no large-scale study has yet estimated the number of expected actionable findings per individual; therefore, we classified actionable pathogenic single-nucleotide variants in 500 European- and 500 African-descent participants randomly selected from the National Heart, Lung, and Blood Institute Exome Sequencing Project. The 1,000 individuals were screened for variants in 114 genes selected by an expert panel for their association with medically actionable genetic conditions possibly undiagnosed in adults. Among the 1,000 participants, 585 instances of 239 unique variants were identified as disease causing in the Human Gene Mutation Database (HGMD). The primary literature supporting the variants’ pathogenicity was reviewed. Of the identified IFs, only 16 unique autosomal-dominant variants in 17 individuals were assessed to be pathogenic or likely pathogenic, and one participant had two pathogenic variants for an autosomal-recessive disease. Furthermore, one pathogenic and four likely pathogenic variants not listed as disease causing in HGMD were identified. These data can provide an estimate of the frequency (∼3.4% for European descent and ∼1.2% for African descent) of the high-penetrance actionable pathogenic or likely pathogenic variants in adults. The 23 participants with pathogenic or likely pathogenic variants were disproportionately of European (17) versus African (6) descent. The process of classifying these variants underscores the need for a more comprehensive and diverse centralized resource to provide curated information on pathogenicity for clinical use to minimize health disparities in genomic medicine