Inter-subband redundancy prediction using neural network for video coding

High performance video codec is mandatory for multimedia applications such as video-on-demand and video conferencing. Recent research has proposed numerous video coding techniques to meet the requirement in bandwidth, delay, loss and Quality-of-Service (QoS). In this paper, we present our investigations on inter-subband self-similarity within the wavelet-decomposed video frames using neural networks, and study the performance of applying the spatial network model to all video frames over time. The goal of our proposed method is to restore the highest perceptual quality for video transmitted over a highly congested network. Our contributions in this paper are: (1) A new coding model with neural network based, inter-subband redundancy (ISR) prediction for video coding using wavelet (2) The performance of 1D and 2D ISR prediction, including multiple levels of wavelet decompositions. Our result shows a short-term quality enhancement may be obtained using both 1D and 2D ISR prediction.

Prediction of carbon monoxide in fires by conditional moment closure

Carbon monoxide is the chief killer in fires. Dangerous levels of CO can occur when reacting combustion gases are quenched by heat transfer, or by mixing of the fire plume in a cooled under- or overventilated upper layer. In this paper, carbon monoxide predictions for enclosure fires are modeled by the conditional moment closure (CMC) method and are compared with laboratory data. The modeled fire situation is a buoyant, turbulent, diffusion flame burning under a hood. The fire plume entrains fresh air, and the postflame gases are cooled considerably under the hood by conduction and radiation, emulating conditions which occur in enclosure fires and lead to the freezing of CO burnout. Predictions of CO in the cooled layer are presented in the context of a complete computational fluid dynamics solution of velocity, temperature, and major species concentrations. A range of underhood equivalence ratios, from rich to lean, are investigated. The CMC method predicts CO in very good agreement with data. In particular, CMC is able to correctly predict CO concentrations in lean cooled gases, showing its capability in conditions where reaction rates change considerably.

Field assessment of thermal after-ripening time for dormancy release prediction in Lolium rigidum seeds

Dormancy release was studied in four populations of annual ryegrass (Lolium rigidum) seeds to determine whether loss of dormancy in the field can be predicted from temperature alone or whether seed water content (WC) must also be considered. Freshly matured seeds were after-ripened at the northern and southern extremes of the Western Australian cereal cropping region and at constant 37degreesC. Seed WC was allowed to fluctuate with prevailing humidity, but full hydration was avoided by excluding rainfall. Dormancy was measured regularly during after-ripening by germinating seeds with 12-hourly light or in darkness. Germination was lower in darkness than in light/dark and dormancy release was slower when germination was tested in darkness. Seeds were consistently drier, and dormancy release was slower, during after-ripening at 37degreesC than under field conditions. However, within each population, the rate of dormancy release in the field (north and south) in terms of thermal time was unaffected by after-ripening site. While low seed WC slowed dormancy release in seeds held at 37degreesC, dormancy release in seeds after-ripened under Western Australian field conditions was adequately described by thermal after-ripening time, without the need to account for changes in WC elicited by fluctuating environmental humidity.

Who chooses to inflation target?

In this article, we seek what are the factors behind a country`s decision to move to Inflation Targeting. We find that high past inflation, low debt levels and the absence of a nominal exchange rate anchor increase the probability that a country will end up opting for it. (C) 2007 Elsevier B.V. All rights reserved.

Computational methods for prediction of T-cell epitopes - a framework for modelling, testing, and applications

Computational models complement laboratory experimentation for efficient identification of MHC-binding peptides and T-cell epitopes. Methods for prediction of MHC-binding peptides include binding motifs, quantitative matrices, artificial neural networks, hidden Markov models, and molecular modelling. Models derived by these methods have been successfully used for prediction of T-cell epitopes in cancer, autoimmunity, infectious disease, and allergy. For maximum benefit, the use of computer models must be treated as experiments analogous to standard laboratory procedures and performed according to strict standards. This requires careful selection of data for model building, and adequate testing and validation. A range of web-based databases and MHC-binding prediction programs are available. Although some available prediction programs for particular MHC alleles have reasonable accuracy, there is no guarantee that all models produce good quality predictions. In this article, we present and discuss a framework for modelling, testing, and applications of computational methods used in predictions of T-cell epitopes. (C) 2004 Elsevier Inc. All rights reserved.

ANNA: A new prediction method for bioassessment programs

1. Cluster analysis of reference sites with similar biota is the initial step in creating River Invertebrate Prediction and Classification System (RIVPACS) and similar river bioassessment models such as Australian River Assessment System (AUSRIVAS). This paper describes and tests an alternative prediction method, Assessment by Nearest Neighbour Analysis (ANNA), based on the same philosophy as RIVPACS and AUSRIVAS but without the grouping step that some people view as artificial. 2. The steps in creating ANNA models are: (i) weighting the predictor variables using a multivariate approach analogous to principal axis correlations, (ii) calculating the weighted Euclidian distance from a test site to the reference sites based on the environmental predictors, (iii) predicting the faunal composition based on the nearest reference sites and (iv) calculating an observed/expected (O/E) analogous to RIVPACS/AUSRIVAS. 3. The paper compares AUSRIVAS and ANNA models on 17 datasets representing a variety of habitats and seasons. First, it examines each model's regressions for Observed versus Expected number of taxa, including the r(2), intercept and slope. Second, the two models' assessments of 79 test sites in New Zealand are compared. Third, the models are compared on test and presumed reference sites along a known trace metal gradient. Fourth, ANNA models are evaluated for western Australia, a geographically distinct region of Australia. The comparisons demonstrate that ANNA and AUSRIVAS are generally equivalent in performance, although ANNA turns out to be potentially more robust for the O versus E regressions and is potentially more accurate on the trace metal gradient sites. 4. The ANNA method is recommended for use in bioassessment of rivers, at least for corroborating the results of the well established AUSRIVAS- and RIVPACS-type models, if not to replace them.

THE ANTERIOR CINGULATE CORTEX IS A TARGET STRUCTURE FOR THE ANXIOLYTIC-LIKE EFFECTS OF BENZODIAZEPINES ASSESSED BY REPEATED EXPOSURE TO THE ELEVATED PLUS MAZE AND FOS IMMUNOREACTIVITY

Prior experience with the elevated plus maze (EPM) increases the avoidance of rodents to the open arms and impairs the anxiolytic-like effects of benzodiazepines on the traditional behaviors evaluated upon re-exposure to the maze, a phenomenon known as one-trial tolerance. Risk assessment behaviors are also sensitive to benzodiazepines. During re-exposure to the maze, these behaviors reinstate the information-processing initiated during the first experience, and the detection of danger generates stronger open-arm avoidance. The present study investigated whether the benzodiazepine midazolam alters risk assessment behaviors and Fos protein distribution associated with test and retest sessions in the EPM. Naive or maze-experienced Wistar rats received either saline or midazolam (0.5 mg/kg i.p.) and were subjected to the EPM. Midazolam caused the usual effects on exploratory behavior, increasing exploratory activity of naive rats in the open arms and producing no effects on these conventional measures in rats re-exposed to the maze. Risk assessment behaviors, however, were sensitive to the benzodiazepine during both sessions, indicating anxiolytic-like effects of the drug in both conditions. Fos immunohistochemistry showed that midazolam injections were associated with a distinct pattern of action when administered before the test or retest session, and the anterior cingulate cortex, area 1 (Cg1), was the only structure targeted by the benzodiazepine in both situations. Bilateral infusions of midazolam into the Cg1 replicated the behavioral effects of the drug injected systemically, suggesting that this area is critically involved in the anxiolytic-like effects of benzodiazepines, although the behavioral strategy adopted by the animals appears to depend on the previous knowledge of the threatening environment. (C) 2009 IBRO. Published by Elsevier Ltd. All rights reserved.

Occasion setting in Pavlovian ambiguous target discriminations

Rats were trained in a Pavlovian serial ambiguous target discrimination, in which a target cue was reinforced if it was preceded by one stimulus (P -> T+) but was not reinforced if it was preceded by another stimulus (N -> T-). Test performance indicated that stimulus control by these features was weaker than that acquired by features trained within separate serial feature positive (P -> T+, T-) and serial feature negative (N -> W-, W+) discriminations. The form of conditioned responding and the patterns of transfer observed suggested that the serial ambiguous target discrimination was solved by occasion setting. The data are discussed in terms of the use of retrospective coding strategies when solving Pavlovian serial conditional discriminations, and the acquisition of special properties by both feature and target stimuli. (C) 2008 Published by Elsevier B.V.

A comparison of lipid variables as predictors of cardiovascular disease in the Asia Pacific Region

PURPOSE: Many guidelines advocate measurement of total or low density lipoprotein cholesterol (LDL), high density lipoprotein cholesterol (HDL), and triglycerides (TG) to determine treatment recommendations for preventing coronary heart disease (CHD) and cardiovascular disease (CVD). This analysis is a comparison of lipid variables as predictors of cardiovascular disease. METHODS: Hazard ratios for coronary and cardiovascular deaths by fourths of total cholesterol (TC), LDL, HDL, TG, non-HDL, TC/HDL, and TG/HDL values, and for a one standard deviation change in these variables, were derived in an individual participant data meta-analysis of 32 cohort studies conducted in the Asia-Pacific region. The predictive value of each lipid variable was assessed using the likelihood ratio statistic. RESULTS: Adjusting for confounders and regression dilution, each lipid variable had a positive (negative for HDL) log-linear association with fatal CHD and CVD. Individuals in the highest fourth of each lipid variable had approximately twice the risk of CHD compared with those with lowest levels. TG and HDL were each better predictors of CHD and CVD risk compared with TC alone, with test statistics similar to TC/HDL and TG/HDL ratios. Calculated LDL was a relatively poor predictor. CONCLUSIONS: While LDL reduction remains the main target of intervention for lipid-lowering, these data support the potential use of TG or lipid ratios for CHD risk prediction. (c) 2005 Elsevier Inc. All rights reserved.

PREDBALB/c: a system for the prediction of peptide binding to H2(d) molecules, a haplotype of the BALB/c mouse

PREDBALB/c is a computational system that predicts peptides binding to the major histocompatibility complex-2 (H2(d)) of the BALB/c mouse, an important laboratory model organism. The predictions include the complete set of H2(d) class I ( H2-K-d, H2-L-d and H2-D-d) and class II (I-E-d and I-A(d)) molecules. The prediction system utilizes quantitative matrices, which were rigorously validated using experimentally determined binders and non-binders and also by in vivo studies using viral proteins. The prediction performance of PREDBALB/c is of very high accuracy. To our knowledge, this is the first online server for the prediction of peptides binding to a complete set of major histocompatibility complex molecules in a model organism (H2(d) haplotype). PREDBALB/c is available at http://antigen.i2r.a-star.edu.sg/predBalbc/.

Axial Young's modulus prediction of single-walled carbon nanotube arrays with diameters from nanometer to meter scales

Based on a self-similar array model, we systematically investigated the axial Young's modulus (Y-axis) of single-walled carbon nanotube (SWNT) arrays with diameters from nanometer to meter scales by an analytical approach. The results show that the Y-axis of SWNT arrays decreases dramatically with the increases of their hierarchy number (s) and is not sensitive to the specific size and constitution when s is the same, and the specific Young's modulus Y-axis(s) is independent of the packing configuration of SWNTs. Our calculations also show that the Y-axis of SWNT arrays with diameters of several micrometers is close to that of commercial high performance carbon fibers (CFs), but the Y-axis(s) of SWNT arrays is much better than that of high performance CFs. (C) 2005 American Institute of Physics.

Early Control of PTH and FGF23 in Normophosphatemic CKD Patients: A New Target in CKD-MBD Therapy?

Background and objectives: Levels of parathyroid hormone (PTH) and the phosphaturic hormone FGF23, a fibroblast growth factor (FGF) family member, increase early in chronic kidney disease (CKD) before the occurrence of hyperphosphatemia. This short-term 6-wk dose titration study evaluated the effect of two phosphate binders on PTH and FGF23 levels in patients with CKD stages 3 to 4. Design, setting, participants, and measurements: Patients were randomized to receive over a 6-wk period either calcium acetate (n = 19) or sevelamer hydrochloride (n = 21). Results: At baseline, patients presented with elevated fractional excretion of phosphate, serum PTH, and FGF23. During treatment with both phosphate binders there was a progressive decline in serum PTH and urinary phosphate, but no change in serum calcium or serum phosphate. Significant changes were observed for FGF23 only in sevelamer-treated patients. Conclusions: This study confirms the positive effects of early prescription of phosphate binders on PTH control. Prospective and long-term studies are necessary to confirm the effects of sevelamer on serum FGF23 and the benefits of this decrease on outcomes. Clin J Am Soc Nephrol 5: 286-291, 2010. doi: 10.2215/CJN.05420709

Intermittent target inhibition with dasatinib 100 mg once daily preserves efficacy and improves tolerability in imatinib-resistant and -intolerant chronic-phase chronic myeloid leukemia

Purpose Dasatinib is a BCR-ABL inhibitor, 325-fold more potent than imatinib against unmutated BCR-ABL in vitro. Phase II studies have demonstrated efficacy and safety with dasatinib 70 mg twice daily in chronic-phase (CP) chronic myelogenous leukemia (CML) after imatinib treatment failure. In phase I, responses occurred with once-daily administration despite only intermittent BCR-ABL inhibition. Once-daily treatment resulted in less toxicity, suggesting that toxicity results from continuous inhibition of unintended targets. Here, a dose-and schedule-optimization study is reported. Patients and Methods In this open-label phase III trial, 670 patients with imatinib-resistant or -intolerant CP-CML were randomly assigned 1: 1: 1: 1 between four dasatinib treatment groups: 100 mg once daily, 50 mg twice daily, 140 mg once daily, or 70 mg twice daily. Results With minimum follow-up of 6 months (median treatment duration, 8 months; range, = 1 to 15 months), marked and comparable hematologic (complete, 86% to 92%) and cytogenetic (major, 54% to 59%; complete, 41% to 45%) response rates were observed across the four groups. Time to and duration of cytogenetic response were similar, as was progression-free survival (8% to 11% of patients experienced disease progression or died). Compared with the approved 70-mg twice-daily regimen, dasatinib 100 mg once daily resulted in significantly lower rates of pleural effusion (all grades, 7% v 16%; P = .024) and grade 3 to 4 thrombocytopenia (22% v 37%; P = .004), and fewer patients required dose interruption (51% v 68%), reduction (30% v 55%), or discontinuation (16% v 23%). Conclusion Dasatinib 100 mg once daily retains the efficacy of 70 mg twice daily with less toxicity. Intermittent target inhibition with tyrosine kinase inhibitors may preserve efficacy and reduce adverse events.