Specific-to-General Learning for Temporal Events with Application to Learning Event Definitions from Video

We develop, analyze, and evaluate a novel, supervised, specific-to-general learner for a simple temporal logic and use the resulting algorithm to learn visual event definitions from video sequences. First, we introduce a simple, propositional, temporal, event-description language called AMA that is sufficiently expressive to represent many events yet sufficiently restrictive to support learning. We then give algorithms, along with lower and upper complexity bounds, for the subsumption and generalization problems for AMA formulas. We present a positive-examples--only specific-to-general learning method based on these algorithms. We also present a polynomial-time--computable ``syntactic'' subsumption test that implies semantic subsumption without being equivalent to it. A generalization algorithm based on syntactic subsumption can be used in place of semantic generalization to improve the asymptotic complexity of the resulting learning algorithm. Finally, we apply this algorithm to the task of learning relational event definitions from video and show that it yields definitions that are competitive with hand-coded ones

EDUCATIONAL PROGRAMS TO ADDRESS THE ECONOMIC ADJUSTMENTS FACING TOBACCO FARMERS AND RURAL COMMUNITIES

This paper discusses the context within which educational programs tailored to tobacco producers and related rural communities have developed. Discussion is expanded by examining current program approaches employed by various organizations. Many of these organizations have a manual stake in helping producers in tobacco communities develop their management capacity. A range of initiatives aimed at facilitating economic adjustment is compared, including the major issues addressed and expected outcomes. Many of the initiatives have made useful contributions; however, gaps and limitations remain. These are considered as future educational efforts and issues are discussed.educational programs, tobacco producers, Community/Rural/Urban Development,

Gut Dysbiosis and Neurobehavioral Alterations in Rats Exposed to Silver Nanoparticles

Due to their antimicrobial properties, silver nanoparticles (AgNPs) are being used in non-edible and edible consumer products. It is not clear though if exposure to these chemicals can exert toxic effects on the host and gut microbiome. Conflicting studies have been reported on whether AgNPs result in gut dysbiosis and other changes within the host. We sought to examine whether exposure of Sprague-Dawley male rats for two weeks to different shapes of AgNPs, cube (AgNC) and sphere (AgNS) affects gut microbiota, select behaviors, and induces histopathological changes in the gastrointestinal system and brain. In the elevated plus maze (EPM), AgNS-exposed rats showed greater number of entries into closed arms and center compared to controls and those exposed to AgNC. AgNS and AgNC treated groups had select reductions in gut microbiota relative to controls. Clostridium spp., Bacteroides uniformis, Christensenellaceae, and Coprococcus eutactus were decreased in AgNC exposed group, whereas, Oscillospira spp., Dehalobacterium spp., Peptococcaeceae, Corynebacterium spp., Aggregatibacter pneumotropica were reduced in AgNS exposed group. Bacterial reductions correlated with select behavioral changes measured in the EPM. No significant histopathological changes were evident in the gastrointestinal system or brain. Findings suggest short-term exposure to AgNS or AgNC can lead to behavioral and gut microbiome changes.Comment: 14 figures, 15 page

Clinical identification of feeding and swallowing disorders in 0-6 month old infants with Down syndrome

Feeding and swallowing disorders have been described in children with a variety of neurodevelopmental disabilities, including Down syndrome (DS). Abnormal feeding and swallowing can be associated with serious sequelae such as failure to thrive and respiratory complications, including aspiration pneumonia. Incidence of dysphagia in young infants with DS has not previously been reported. To assess the identification and incidence of feeding and swallowing problems in young infants with DS, a retrospective chart review of 174 infants, ages 0-6 months was conducted at a single specialty clinic. Fifty-seven percent (100/174) of infants had clinical concerns for feeding and swallowing disorders that warranted referral for Videofluroscopic Swallow Study (VFSS); 96/174 (55%) had some degree of oral and/or pharyngeal phase dysphagia and 69/174 (39%) had dysphagia severe enough to warrant recommendation for alteration of breast milk/formula consistency or nonoral feeds. Infants with certain comorbidities had significant risk for significant dysphagia, including those with functional airway/respiratory abnormalities (OR = 7.2). Infants with desaturation with feeds were at dramatically increased risk (OR = 15.8). All young infants with DS should be screened clinically for feeding and swallowing concerns. If concerns are identified, consideration should be given to further evaluation with VFSS for identification of dysphagia and additional feeding modifications

Extreme State Aggregation Beyond MDPs

We consider a Reinforcement Learning setup where an agent interacts with an environment in observation-reward-action cycles without any (esp.\ MDP) assumptions on the environment. State aggregation and more generally feature reinforcement learning is concerned with mapping histories/raw-states to reduced/aggregated states. The idea behind both is that the resulting reduced process (approximately) forms a small stationary finite-state MDP, which can then be efficiently solved or learnt. We considerably generalize existing aggregation results by showing that even if the reduced process is not an MDP, the (q-)value functions and (optimal) policies of an associated MDP with same state-space size solve the original problem, as long as the solution can approximately be represented as a function of the reduced states. This implies an upper bound on the required state space size that holds uniformly for all RL problems. It may also explain why RL algorithms designed for MDPs sometimes perform well beyond MDPs.Comment: 28 LaTeX pages. 8 Theorem

An iterative decision-making scheme for Markov decision processes and its application to self-adaptive systems

Software is often governed by and thus adapts to phenomena that occur at runtime. Unlike traditional decision problems, where a decision-making model is determined for reasoning, the adaptation logic of such software is concerned with empirical data and is subject to practical constraints. We present an Iterative Decision-Making Scheme (IDMS) that infers both point and interval estimates for the undetermined transition probabilities in a Markov Decision Process (MDP) based on sampled data, and iteratively computes a confidently optimal scheduler from a given finite subset of schedulers. The most important feature of IDMS is the flexibility for adjusting the criterion of confident optimality and the sample size within the iteration, leading to a tradeoff between accuracy, data usage and computational overhead. We apply IDMS to an existing self-adaptation framework Rainbow and conduct a case study using a Rainbow system to demonstrate the flexibility of IDMS

Retrospective Analysis of Factors Leading to Pediatric Tracheostomy Decannulation Failure. A Single-Institution Experience

RATIONALE: There is a lack of evidence regarding factors associated with failure of tracheostomy decannulation. OBJECTIVES: We aimed to identify characteristics of pediatric patients who fail a tracheostomy decannulation challenge Methods: A retrospective review was performed on all patients who had a decannulation challenge at a tertiary care center from June 2006 to October 2013. Tracheostomy decannulation failure was defined as reinsertion of the tracheostomy tube within 6 months of the challenge. Data on demographics, indications for tracheostomy, home mechanical ventilation, and comorbidities were collected. Data were also collected on specific airway endoscopic findings during the predecannulation bronchoscopy and airway surgical procedures before decannulation. We attempted to predict the decannulation outcome by analyzing associations. MEASUREMENTS AND MAIN RESULTS: 147 of 189 (77.8%) patients were successfully decannulated on the first attempt. Tracheostomy performed due to chronic respiratory failure decreased odds for decannulation failure (odds ratio = 0.34, 95% confidence interval = 0.15-0.77). Genetic abnormalities (45%) and feeding dysfunction (93%) were increased in the population of patients failing their first attempt. The presence of one comorbidity increased the odds of failure by 68% (odds ratio = 1.68, 95% confidence interval = 1.23-2.29). Decannulation pursuit based on parental expectation of success, rather than medically determined readiness, was associated with a higher chance of failure (P = 0.01). CONCLUSIONS: Our study highlights the role of genetic abnormalities, feeding dysfunction, and multiple comorbidities in patients who fail decannulation. Our findings also demonstrate that the outcome of decannulation may be predicted by the indication for tracheostomy. Patients who had tracheostomy placed for chronic respiratory support had a higher likelihood of success. Absence of a surgically treatable airway obstruction abnormality on the predecannulation bronchoscopy increased the chances of success

Genome-wide discovery and characterization of maize long non-coding RNAs

BACKGROUND: Long non-coding RNAs (lncRNAs) are transcripts that are 200 bp or longer, do not encode proteins, and potentially play important roles in eukaryotic gene regulation. However, the number, characteristics and expression inheritance pattern of lncRNAs in maize are still largely unknown. RESULTS: By exploiting available public EST databases, maize whole genome sequence annotation and RNA-seq datasets from 30 different experiments, we identified 20,163 putative lncRNAs. Of these lncRNAs, more than 90% are predicted to be the precursors of small RNAs, while 1,704 are considered to be high-confidence lncRNAs. High confidence lncRNAs have an average transcript length of 463 bp and genes encoding them contain fewer exons than annotated genes. By analyzing the expression pattern of these lncRNAs in 13 distinct tissues and 105 maize recombinant inbred lines, we show that more than 50% of the high confidence lncRNAs are expressed in a tissue-specific manner, a result that is supported by epigenetic marks. Intriguingly, the inheritance of lncRNA expression patterns in 105 recombinant inbred lines reveals apparent transgressive segregation, and maize lncRNAs are less affected by cis- than by trans- genetic factors. CONCLUSIONS: We integrate all available transcriptomic datasets to identify a comprehensive set of maize lncRNAs, provide a unique annotation resource of the maize genome and a genome-wide characterization of maize lncRNAs, and explore the genetic control of their expression using expression quantitative trait locus mapping

Recrystallization of water in a non-water-soluble polymer examined by Fourier transform infrared spectroscopy: poly(2-methoxyethylacrylate) with low water content.

Crystallization of water during heating, the so-called "recrystallization of water", in poly(2-methoxyethylacrylate) (PMEA) was investigated by temperature-variable Fourier transform infrared spectroscopy. Recrystallization in a polymer-water system is generally understood to be a phase transition from glassy water (condensed water) to crystalline water. However, infrared spectral changes of the PMEA-water system with low water content indicated that the formation of ice I h during heating occurred by a vapor deposition process rather than by a crystallization process