Predicting hydrocarbon potential of an earth formation underlying water

International Nuclear Information System (INIS)

Damaison, G.J.; Kaplan, I.R.

1981-01-01

A method for the on-site collection and examination of small concentrations of a carbonaceous gas, e.g. methane, dissolved in a body of water overlying an earth formation to predict hydrocarbon potential of the earth formation under the body of water, the formation being a source of carbonaceous gas, comprises at a known geographic location sampling the water at a selected flow rate and at a selected depth; continuously vacuum separating the water into liquid and gas phases; separating a selected carbonaceous gas from interfering gas species in the presence of an air carrier vented to atmosphere at a known flow rate; and quantitatively oxidizing the selected gas and then cryogenically trapping an oxidant thereof in the presence of said air carrier to provide for an accurate isotopic examination. (author)

Chemical structure-based predictive model for methanogenic anaerobic biodegradation potential.

Science.gov (United States)

Meylan, William; Boethling, Robert; Aronson, Dallas; Howard, Philip; Tunkel, Jay

2007-09-01

Many screening-level models exist for predicting aerobic biodegradation potential from chemical structure, but anaerobic biodegradation generally has been ignored by modelers. We used a fragment contribution approach to develop a model for predicting biodegradation potential under methanogenic anaerobic conditions. The new model has 37 fragments (substructures) and classifies a substance as either fast or slow, relative to the potential to be biodegraded in the "serum bottle" anaerobic biodegradation screening test (Organization for Economic Cooperation and Development Guideline 311). The model correctly classified 90, 77, and 91% of the chemicals in the training set (n = 169) and two independent validation sets (n = 35 and 23), respectively. Accuracy of predictions of fast and slow degradation was equal for training-set chemicals, but fast-degradation predictions were less accurate than slow-degradation predictions for the validation sets. Analysis of the signs of the fragment coefficients for this and the other (aerobic) Biowin models suggests that in the context of simple group contribution models, the majority of positive and negative structural influences on ultimate degradation are the same for aerobic and methanogenic anaerobic biodegradation.

Modeling Seizure Self-Prediction: An E-Diary Study

Science.gov (United States)

Haut, Sheryl R.; Hall, Charles B.; Borkowski, Thomas; Tennen, Howard; Lipton, Richard B.

2013-01-01

Purpose A subset of patients with epilepsy successfully self-predicted seizures in a paper diary study. We conducted an e-diary study to ensure that prediction precedes seizures, and to characterize the prodromal features and time windows that underlie self-prediction. Methods Subjects 18 or older with LRE and ≥3 seizures/month maintained an e-diary, reporting AM/PM data daily, including mood, premonitory symptoms, and all seizures. Self-prediction was rated by, “How likely are you to experience a seizure [time frame]”? Five choices ranged from almost certain (>95% chance) to very unlikely. Relative odds of seizure (OR) within time frames was examined using Poisson models with log normal random effects to adjust for multiple observations. Key Findings Nineteen subjects reported 244 eligible seizures. OR for prediction choices within 6hrs was as high as 9.31 (1.92,45.23) for “almost certain”. Prediction was most robust within 6hrs of diary entry, and remained significant up to 12hrs. For 9 best predictors, average sensitivity was 50%. Older age contributed to successful self-prediction, and self-prediction appeared to be driven by mood and premonitory symptoms. In multivariate modeling of seizure occurrence, self-prediction (2.84; 1.68,4.81), favorable change in mood (0.82; 0.67,0.99) and number of premonitory symptoms (1,11; 1.00,1.24) were significant. Significance Some persons with epilepsy can self-predict seizures. In these individuals, the odds of a seizure following a positive prediction are high. Predictions were robust, not attributable to recall bias, and were related to self awareness of mood and premonitory features. The 6-hour prediction window is suitable for the development of pre-emptive therapy. PMID:24111898

Inter-decadal change in potential predictability of the East Asian summer monsoon

Science.gov (United States)

Li, Jiao; Ding, Ruiqiang; Wu, Zhiwei; Zhong, Quanjia; Li, Baosheng; Li, Jianping

2018-05-01

The significant inter-decadal change in potential predictability of the East Asian summer monsoon (EASM) has been investigated using the signal-to-noise ratio method. The relatively low potential predictability appears from the early 1950s through the late 1970s and during the early 2000s, whereas the potential predictability is relatively high from the early 1980s through the late 1990s. The inter-decadal change in potential predictability of the EASM can be attributed mainly to variations in the external signal of the EASM. The latter is mostly caused by the El Niño-Southern Oscillation (ENSO) inter-decadal variability. As a major external signal of the EASM, the ENSO inter-decadal variability experiences phase transitions from negative to positive phases in the late 1970s, and to negative phases in the late 1990s. Additionally, ENSO is generally strong (weak) during a positive (negative) phase of the ENSO inter-decadal variability. The strong ENSO is expected to have a greater influence on the EASM, and vice versa. As a result, the potential predictability of the EASM tends to be high (low) during a positive (negative) phase of the ENSO inter-decadal variability. Furthermore, a suite of Pacific Pacemaker experiments suggests that the ENSO inter-decadal variability may be a key pacemaker of the inter-decadal change in potential predictability of the EASM.

Potentiality Prediction of Electric Power Replacement Based on Power Market Development Strategy

Science.gov (United States)

Miao, Bo; Yang, Shuo; Liu, Qiang; Lin, Jingyi; Zhao, Le; Liu, Chang; Li, Bin

2017-05-01

The application of electric power replacement plays an important role in promoting the development of energy conservation and emission reduction in our country. To exploit the potentiality of regional electric power replacement, the regional GDP (gross domestic product) and energy consumption are taken as potentiality evaluation indicators. The principal component factors are extracted with PCA (principal component analysis), and the integral potentiality analysis is made to the potentiality of electric power replacement in the national various regions; a region is taken as a research object, and the potentiality of electric power replacement is defined and quantified. The analytical model for the potentiality of multi-scenario electric power replacement is developed, and prediction is made to the energy consumption with the grey prediction model. The relevant theoretical research is utilized to realize prediction analysis on the potentiality amount of multi-scenario electric power replacement.

E-waste Management and Refurbishment Prediction (EMARP) Model for Refurbishment Industries.

Science.gov (United States)

Resmi, N G; Fasila, K A

2017-10-01

This paper proposes a novel algorithm for establishing a standard methodology to manage and refurbish e-waste called E-waste Management And Refurbishment Prediction (EMARP), which can be adapted by refurbishing industries in order to improve their performance. Waste management, particularly, e-waste management is a serious issue nowadays. Computerization has been into waste management in different ways. Much of the computerization has happened in planning the waste collection, recycling and disposal process and also managing documents and reports related to waste management. This paper proposes a computerized model to make predictions for e-waste refurbishment. All possibilities for reusing the common components among the collected e-waste samples are predicted, thus minimizing the wastage. Simulation of the model has been done to analyse the accuracy in the predictions made by the system. The model can be scaled to accommodate the real-world scenario. Copyright © 2017 Elsevier Ltd. All rights reserved.

Predicting the Potential Market for Electric Vehicles

DEFF Research Database (Denmark)

Jensen, Anders Fjendbo; Cherchi, Elisabetta; Mabit, Stefan Lindhard

2017-01-01

diffusion models in marketing research use fairly simple demand models. In this paper we discuss the problem of predicting market shares for new products and suggest a method that combines advanced choice models with a diffusion model to take into account that new products often need time to gain......Forecasting the potential demand for electric vehicles is a challenging task. Because most studies for new technologies rely on stated preference (SP) data, market share predictions will reflect shares in the SP data and not in the real market. Moreover, typical disaggregate demand models...... are suitable to forecast demand in relatively stable markets, but show limitations in the case of innovations. When predicting the market for new products it is crucial to account for the role played by innovation and how it penetrates the new market over time through a diffusion process. However, typical...

Prediction of potential drug targets based on simple sequence properties

Directory of Open Access Journals (Sweden)

Lai Luhua

2007-09-01

Full Text Available Abstract Background During the past decades, research and development in drug discovery have attracted much attention and efforts. However, only 324 drug targets are known for clinical drugs up to now. Identifying potential drug targets is the first step in the process of modern drug discovery for developing novel therapeutic agents. Therefore, the identification and validation of new and effective drug targets are of great value for drug discovery in both academia and pharmaceutical industry. If a protein can be predicted in advance for its potential application as a drug target, the drug discovery process targeting this protein will be greatly speeded up. In the current study, based on the properties of known drug targets, we have developed a sequence-based drug target prediction method for fast identification of novel drug targets. Results Based on simple physicochemical properties extracted from protein sequences of known drug targets, several support vector machine models have been constructed in this study. The best model can distinguish currently known drug targets from non drug targets at an accuracy of 84%. Using this model, potential protein drug targets of human origin from Swiss-Prot were predicted, some of which have already attracted much attention as potential drug targets in pharmaceutical research. Conclusion We have developed a drug target prediction method based solely on protein sequence information without the knowledge of family/domain annotation, or the protein 3D structure. This method can be applied in novel drug target identification and validation, as well as genome scale drug target predictions.

Real-time eSports Match Result Prediction

OpenAIRE

Yang, Yifan; Qin, Tian; Lei, Yu-Heng

2016-01-01

In this paper, we try to predict the winning team of a match in the multiplayer eSports game Dota 2. To address the weaknesses of previous work, we consider more aspects of prior (pre-match) features from individual players' match history, as well as real-time (during-match) features at each minute as the match progresses. We use logistic regression, the proposed Attribute Sequence Model, and their combinations as the prediction models. In a dataset of 78362 matches where 20631 matches contai...

Prediction of potential compressive strength of Portland clinker from its mineralogy

DEFF Research Database (Denmark)

Svinning, K.; Høskuldsson, Agnar; Justnes, H.

2010-01-01

Based on a statistical model first applied for prediction of compressive strength up to 28 d from the microstructure of Portland cement, potential compressive strength of clinker has been predicted from its mineralogy. The prediction model was evaluated by partial least squares regression...

Predicting E-commerce Consumer Behaviour Using Sparse Session Data

OpenAIRE

Thorrud, Thorstein Kaldahl; Myklatun, Øyvind

2015-01-01

This thesis research consumer behavior in an e-commerce domain by using a data set of sparse session data collected from an anonymous European e-commerce site. The goal is to predict whether a consumer session results in a purchase, and if so, which items are purchased. The data is supplied by the ACM Recommender System Challenge, which is a yearly challenge held by the ACM Recommender System Conference. Classification is used for predicting whether or not a session made a purchase, as w...

Mechanism-Based Classification of PAH Mixtures to Predict Carcinogenic Potential.

Science.gov (United States)

Tilton, Susan C; Siddens, Lisbeth K; Krueger, Sharon K; Larkin, Andrew J; Löhr, Christiane V; Williams, David E; Baird, William M; Waters, Katrina M

2015-07-01

We have previously shown that relative potency factors and DNA adduct measurements are inadequate for predicting carcinogenicity of certain polycyclic aromatic hydrocarbons (PAHs) and PAH mixtures, particularly those that function through alternate pathways or exhibit greater promotional activity compared to benzo[a]pyrene (BaP). Therefore, we developed a pathway-based approach for classification of tumor outcome after dermal exposure to PAH/mixtures. FVB/N mice were exposed to dibenzo[def,p]chrysene (DBC), BaP, or environmental PAH mixtures (Mix 1-3) following a 2-stage initiation/promotion skin tumor protocol. Resulting tumor incidence could be categorized by carcinogenic potency as DBC > BaP = Mix2 = Mix3 > Mix1 = Control, based on statistical significance. Gene expression profiles measured in skin of mice collected 12 h post-initiation were compared with tumor outcome for identification of short-term bioactivity profiles. A Bayesian integration model was utilized to identify biological pathways predictive of PAH carcinogenic potential during initiation. Integration of probability matrices from four enriched pathways (P PAH mixtures. These data further provide a 'source-to-outcome' model that could be used to predict PAH interactions during tumorigenesis and provide an example of how mode-of-action-based risk assessment could be employed for environmental PAH mixtures. © The Author 2015. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Identification of informative features for predicting proinflammatory potentials of engine exhausts.

Science.gov (United States)

Wang, Chia-Chi; Lin, Ying-Chi; Lin, Yuan-Chung; Jhang, Syu-Ruei; Tung, Chun-Wei

2017-08-18

The immunotoxicity of engine exhausts is of high concern to human health due to the increasing prevalence of immune-related diseases. However, the evaluation of immunotoxicity of engine exhausts is currently based on expensive and time-consuming experiments. It is desirable to develop efficient methods for immunotoxicity assessment. To accelerate the development of safe alternative fuels, this study proposed a computational method for identifying informative features for predicting proinflammatory potentials of engine exhausts. A principal component regression (PCR) algorithm was applied to develop prediction models. The informative features were identified by a sequential backward feature elimination (SBFE) algorithm. A total of 19 informative chemical and biological features were successfully identified by SBFE algorithm. The informative features were utilized to develop a computational method named FS-CBM for predicting proinflammatory potentials of engine exhausts. FS-CBM model achieved a high performance with correlation coefficient values of 0.997 and 0.943 obtained from training and independent test sets, respectively. The FS-CBM model was developed for predicting proinflammatory potentials of engine exhausts with a large improvement on prediction performance compared with our previous CBM model. The proposed method could be further applied to construct models for bioactivities of mixtures.

Potential Predictability and Prediction Skill for Southern Peru Summertime Rainfall

Science.gov (United States)

WU, S.; Notaro, M.; Vavrus, S. J.; Mortensen, E.; Block, P. J.; Montgomery, R. J.; De Pierola, J. N.; Sanchez, C.

2016-12-01

The central Andes receive over 50% of annual climatological rainfall during the short period of January-March. This summertime rainfall exhibits strong interannual and decadal variability, including severe drought events that incur devastating societal impacts and cause agricultural communities and mining facilities to compete for limited water resources. An improved seasonal prediction skill of summertime rainfall would aid in water resource planning and allocation across the water-limited southern Peru. While various underlying mechanisms have been proposed by past studies for the drivers of interannual variability in summertime rainfall across southern Peru, such as the El Niño-Southern Oscillation (ENSO), Madden Julian Oscillation (MJO), and extratropical forcings, operational forecasts continue to be largely based on rudimentary ENSO-based indices, such as NINO3.4, justifying further exploration of predictive skill. In order to bridge this gap between the understanding of driving mechanisms and the operational forecast, we performed systematic studies on the predictability and prediction skill of southern Peru summertime rainfall by constructing statistical forecast models using best available weather station and reanalysis datasets. At first, by assuming the first two empirical orthogonal functions (EOFs) of summertime rainfall are predictable, the potential predictability skill was evaluated for southern Peru. Then, we constructed a simple regression model, based on the time series of tropical Pacific sea-surface temperatures (SSTs), and a more advanced Linear Inverse Model (LIM), based on the EOFs of tropical ocean SSTs and large-scale atmosphere variables from reanalysis. Our results show that the LIM model consistently outperforms the more rudimentary regression models on the forecast skill of domain averaged precipitation index and individual station indices. The improvement of forecast correlation skill ranges from 10% to over 200% for different

Predicting Potential Changes in Suitable Habitat and Distribution by 2100 for Tree Species of the Eastern United States

Science.gov (United States)

Louis R Iverson; Anantha M. Prasad; Mark W. Schwartz; Mark W. Schwartz

2005-01-01

We predict current distribution and abundance for tree species present in eastern North America, and subsequently estimate potential suitable habitat for those species under a changed climate with 2 x CO2. We used a series of statistical models (i.e., Regression Tree Analysis (RTA), Multivariate Adaptive Regression Splines (MARS), Bagging Trees (...

Morphology-based prediction of osteogenic differentiation potential of human mesenchymal stem cells.

Directory of Open Access Journals (Sweden)

Fumiko Matsuoka

Full Text Available Human bone marrow mesenchymal stem cells (hBMSCs are widely used cell source for clinical bone regeneration. Achieving the greatest therapeutic effect is dependent on the osteogenic differentiation potential of the stem cells to be implanted. However, there are still no practical methods to characterize such potential non-invasively or previously. Monitoring cellular morphology is a practical and non-invasive approach for evaluating osteogenic potential. Unfortunately, such image-based approaches had been historically qualitative and requiring experienced interpretation. By combining the non-invasive attributes of microscopy with the latest technology allowing higher throughput and quantitative imaging metrics, we studied the applicability of morphometric features to quantitatively predict cellular osteogenic potential. We applied computational machine learning, combining cell morphology features with their corresponding biochemical osteogenic assay results, to develop prediction model of osteogenic differentiation. Using a dataset of 9,990 images automatically acquired by BioStation CT during osteogenic differentiation culture of hBMSCs, 666 morphometric features were extracted as parameters. Two commonly used osteogenic markers, alkaline phosphatase (ALP activity and calcium deposition were measured experimentally, and used as the true biological differentiation status to validate the prediction accuracy. Using time-course morphological features throughout differentiation culture, the prediction results highly correlated with the experimentally defined differentiation marker values (R>0.89 for both marker predictions. The clinical applicability of our morphology-based prediction was further examined with two scenarios: one using only historical cell images and the other using both historical images together with the patient's own cell images to predict a new patient's cellular potential. The prediction accuracy was found to be greatly enhanced

Performance Prediction of Centrifugal Compressor for Drop-In Testing Using Low Global Warming Potential Alternative Refrigerants and Performance Test Codes

Directory of Open Access Journals (Sweden)

Joo Hoon Park

2017-12-01

Full Text Available As environmental regulations to stall global warming are strengthened around the world, studies using newly developed low global warming potential (GWP alternative refrigerants are increasing. In this study, substitute refrigerants, R-1234ze (E and R-1233zd (E, were used in the centrifugal compressor of an R-134a 2-stage centrifugal chiller with a fixed rotational speed. Performance predictions and thermodynamic analyses of the centrifugal compressor for drop-in testing were performed. A performance prediction method based on the existing ASME PTC-10 performance test code was proposed. The proposed method yielded the expected operating area and operating point of the centrifugal compressor with alternative refrigerants. The thermodynamic performance of the first and second stages of the centrifugal compressor was calculated as the polytropic state. To verify the suitability of the proposed method, the drop-in test results of the two alternative refrigerants were compared. The predicted operating range based on the permissible deviation of ASME PTC-10 confirmed that the temperature difference was very small at the same efficiency. Because the drop-in test of R-1234ze (E was performed within the expected operating range, the centrifugal compressor using R-1234ze (E is considered well predicted. However, the predictions of the operating point and operating range of R-1233zd (E were lower than those of the drop-in test. The proposed performance prediction method will assist in understanding thermodynamic performance at the expected operating point and operating area of a centrifugal compressor using alternative gases based on limited design and structure information.

Prediction markets and their potential role in biomedical research--a review.

Science.gov (United States)

Pfeiffer, Thomas; Almenberg, Johan

2010-01-01

Predictions markets are marketplaces for trading contracts with payoffs that depend on the outcome of future events. Popular examples are markets on the outcome of presidential elections, where contracts pay $1 if a specific candidate wins the election and $0 if someone else wins. Contract prices on prediction markets can be interpreted as forecasts regarding the outcome of future events. Further attractive properties include the potential to aggregate private information, to generate and disseminate a consensus among the market participants, and to offer incentives for the acquisition of information. It has been argued that these properties might be valuable in the context of scientific research. In this review, we give an overview of key properties of prediction markets and discuss potential benefits for science. To illustrate these benefits for biomedical research, we discuss an example application in the context of decision making in research on the genetics of diseases. Moreover, some potential practical problems of prediction market application in science are discussed, and solutions are outlined. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Predictions of soil-water potentials in the north-western Sonoran Desert

Energy Technology Data Exchange (ETDEWEB)

Young, D.R.; Nobel, P.S.

1986-03-01

A simple computer model was developed to predict soil-water potential at a Sonoran Desert site. The variability of precipitation there, coupled with the low water-holding capacity of the sandy soil, result in large temporal and spatial variations in soil-water potential. Predicted soil-water potentials for depths of 5, 10 and 20 cm were in close agreement with measured values as the soil dried after an application of water. Predicted values at a depth of 10 cm, the mean rooting depth of Agave deserti and other succulents common at the study site, also agreed with soil-water potentials measured in the field throughout 1 year. Both soil-water potential and evaporation from the soil surface were very sensitive to simulated changes in the hydraulic conductivity of the soil. The annual duration of soil moisture adequate for succulents was dependent on the rainfall as well as on the spacing and amount of individual rainfalls. The portion of annual precipitation evaporated from the soil surface varied from 73% in a dry year (77 mm precipitation) to 59% in a wet year (597 mm). Besides using the actual precipitation events, simulations were performed using the figures for total monthly precipitation. Based on the average number of rainfalls for a particular month, the rainfall was distributed throughout the month in the model. Predictions using both daily and monthly inputs were in close agreement, especially for the number of days during a year when the soil-water potential was sufficient for water absorption by the succulent plants (above -0.5 MPa).

Left ventricular filling pressure by septal and lateral E/e' equally predict cardiovascular events in the general population

DEFF Research Database (Denmark)

Wang, Joanna Nan; Biering-Sørensen, Tor; Jørgensen, Peter Godsk

2017-01-01

/e'lateral were equally strong predictors of cardiac events; in age- and sex-adjusted models they did not differ in AUC (septal: 0.8385, lateral: 0.8389; p = 0.94) or in continuous NRI (p = 0.84). Models using E/e'average did not improve AUC or NRI, and the intra-individual difference between sites had...... no predictive value (p = 0.79). E/e'septal was generally higher than E/e'lateral, thus age- and sex-specific normal values were reported for both sites for a population free of cardiac events during 10 years of follow-up. CONCLUSIONS: Septal and lateral E/e' are equally useful in predicting cardiac events...

Relativistic predictive quantum potential: the N-body case

International Nuclear Information System (INIS)

Garuccio, A.; Kyprianidis, A.; Vigier, J.P.

1984-01-01

It is generalized to a system of N scalar particles the casual description with action at a distance already given for two-particle systems in EPR type of experiments. The many body quantum potential is shown to satisfy the predictivity constraints established by Droz-Vincent for relativistic mechanics

The potential role of biomarkers in predicting gestational diabetes

Directory of Open Access Journals (Sweden)

Huguette S Brink

2016-08-01

Full Text Available Gestational diabetes (GD is a frequent complication during pregnancy and is associated with maternal and neonatal complications. It is suggested that a disturbing environment for the foetus, such as impaired glucose metabolism during intrauterine life, may result in enduring epigenetic changes leading to increased disease risk in adult life. Hence, early prediction of GD is vital. Current risk prediction models are based on maternal and clinical parameters, lacking a strong predictive value. Adipokines are mainly produced by adipocytes and suggested to be a link between obesity and its cardiovascular complications. Various adipokines, including adiponectin, leptin and TNFα, have shown to be dysregulated in GD. This review aims to outline biomarkers potentially associated with the pathophysiology of GD and discuss the role of integrating predictive biomarkers in current clinical risk prediction models, in order to enhance the identification of those at risk.

e+e- collisions at 500 GeV: The physics potential

International Nuclear Information System (INIS)

Zerwas, P.M.

1992-08-01

In this report the physics potential of e + e - colliders in the first phase up to a c.m. energy of √s=500 GeV is assessed. A luminosity of L=10 33 cm -2 sec -1 has been assumed in general, leading to an integrated luminosity of about ∫L=10 fb -1 per year. See hints under the relevant topics. (orig./HSI)

Specific IgE for Fag e 3 Predicts Oral Buckwheat Food Challenge Test Results and Anaphylaxis: A Pilot Study.

Science.gov (United States)

Yanagida, Noriyuki; Sato, Sakura; Maruyama, Nobuyuki; Takahashi, Kyohei; Nagakura, Ken-Ichi; Ogura, Kiyotake; Asaumi, Tomoyuki; Ebisawa, Motohiro

2018-01-01

Buckwheat (BW) is the source of a life-threatening allergen. Fag e 3-specific serum IgE (sIgE) is more useful than BW-sIgE for diagnosis; however, it is unknown whether Fag e 3-sIgE can predict oral food challenge (OFC) results and anaphylaxis. This study aimed to clarify the efficacy of Fag e 3-sIgE in predicting OFC results and anaphylaxis. We conducted a retrospective review of BW- and Fag e 3-sIgE data obtained using the ImmunoCAP® assay system and fluorescent enzyme-linked immunosorbent assay from children who underwent OFC using 3,072 mg of BW protein between July 2006 and March 2014 at Sagamihara National Hospital, Kanagawa, Japan. We analyzed 60 patients aged 1.9-13.4 years (median 6.0 years); 20 (33%) showed objective symptoms upon BW OFC. The patients without symptoms had significantly lower Fag e 3-sIgE than those with non-anaphylactic (p tested factor that significantly predicted positive OFC results (odds ratio 8.93, 95% confidence interval 3.10-25.73, p < 0.001) and OFC-induced anaphylaxis (2.67, 1.12-6.35, p = 0.027). We suggest that a threshold Fag e 3-sIgE level of 18.0 kUE/L has 95% probability of provoking a positive reaction to BW. Fag e 3-sIgE predicted OFC results and OFC-induced anaphylaxis. We further emphasize paying careful attention to the risk of BW OFC-induced anaphylaxis. © 2018 The Author(s) Published by S. Karger AG, Basel.

[Screen potential CYP450 2E1 inhibitors from Chinese herbal medicine based on support vector regression and molecular docking method].

Science.gov (United States)

Chen, Xi; Lu, Fang; Jiang, Lu-di; Cai, Yi-Lian; Li, Gong-Yu; Zhang, Yan-Ling

2016-07-01

Inhibition of cytochrome P450 (CYP450) enzymes is the most common reasons for drug interactions, so the study on early prediction of CYPs inhibitors can help to decrease the incidence of adverse reactions caused by drug interactions.CYP450 2E1(CYP2E1), as a key role in drug metabolism process, has broad spectrum of drug metabolism substrate. In this study, 32 CYP2E1 inhibitors were collected for the construction of support vector regression (SVR) model. The test set data were used to verify CYP2E1 quantitative models and obtain the optimal prediction model of CYP2E1 inhibitor. Meanwhile, one molecular docking program, CDOCKER, was utilized to analyze the interaction pattern between positive compounds and active pocket to establish the optimal screening model of CYP2E1 inhibitors.SVR model and molecular docking prediction model were combined to screen traditional Chinese medicine database (TCMD), which could improve the calculation efficiency and prediction accuracy. 6 376 traditional Chinese medicine (TCM) compounds predicted by SVR model were obtained, and in further verification by using molecular docking model, 247 TCM compounds with potential inhibitory activities against CYP2E1 were finally retained. Some of them have been verified by experiments. The results demonstrated that this study could provide guidance for the virtual screening of CYP450 inhibitors and the prediction of CYPs-mediated DDIs, and also provide references for clinical rational drug use. Copyright© by the Chinese Pharmaceutical Association.

Computational identification, characterization and validation of potential antigenic peptide vaccines from hrHPVs E6 proteins using immunoinformatics and computational systems biology approaches.

Directory of Open Access Journals (Sweden)

Abbas Khan

Full Text Available High-risk human papillomaviruses (hrHPVs are the most prevalent viruses in human diseases including cervical cancers. Expression of E6 protein has already been reported in cervical cancer cases, excluding normal tissues. Continuous expression of E6 protein is making it ideal to develop therapeutic vaccines against hrHPVs infection and cervical cancer. Therefore, we carried out a meta-analysis of multiple hrHPVs to predict the most potential prophylactic peptide vaccines. In this study, immunoinformatics approach was employed to predict antigenic epitopes of hrHPVs E6 proteins restricted to 12 Human HLAs to aid the development of peptide vaccines against hrHPVs. Conformational B-cell and CTL epitopes were predicted for hrHPVs E6 proteins using ElliPro and NetCTL. The potential of the predicted peptides were tested and validated by using systems biology approach considering experimental concentration. We also investigated the binding interactions of the antigenic CTL epitopes by using docking. The stability of the resulting peptide-MHC I complexes was further studied by molecular dynamics simulations. The simulation results highlighted the regions from 46-62 and 65-76 that could be the first choice for the development of prophylactic peptide vaccines against hrHPVs. To overcome the worldwide distribution, the predicted epitopes restricted to different HLAs could cover most of the vaccination and would help to explore the possibility of these epitopes for adaptive immunotherapy against HPVs infections.

Phenology prediction component of GypsES

Science.gov (United States)

Jesse A. Logan; Lukas P. Schaub; F. William Ravlin

1991-01-01

Prediction of phenology is an important component of most pest management programs, and considerable research effort has been expended toward development of predictive tools for gypsy moth phenology. Although phenological prediction is potentially valuable for timing of spray applications (e.g. Bt, or Gypcheck) and other management activities (e.g. placement and...

Predictive modeling in e-mental health: A common language framework

Directory of Open Access Journals (Sweden)

Dennis Becker

2018-06-01

Full Text Available Recent developments in mobile technology, sensor devices, and artificial intelligence have created new opportunities for mental health care research. Enabled by large datasets collected in e-mental health research and practice, clinical researchers and members of the data mining community increasingly join forces to build predictive models for health monitoring, treatment selection, and treatment personalization. This paper aims to bridge the historical and conceptual gaps between the distant research domains involved in this new collaborative research by providing a conceptual model of common research goals. We first provide a brief overview of the data mining field and methods used for predictive modeling. Next, we propose to characterize predictive modeling research in mental health care on three dimensions: 1 time, relative to treatment (i.e., from screening to post-treatment relapse monitoring, 2 types of available data (e.g., questionnaire data, ecological momentary assessments, smartphone sensor data, and 3 type of clinical decision (i.e., whether data are used for screening purposes, treatment selection or treatment personalization. Building on these three dimensions, we introduce a framework that identifies four model types that can be used to classify existing and future research and applications. To illustrate this, we use the framework to classify and discuss published predictive modeling mental health research. Finally, in the discussion, we reflect on the next steps that are required to drive forward this promising new interdisciplinary field.

Defensive motivation and attention in anticipation of different types of predictable and unpredictable threat: A startle and event-related potential investigation.

Science.gov (United States)

Nelson, Brady D; Hajcak, Greg

2017-08-01

Predictability is an important characteristic of threat that impacts defensive motivation and attentional engagement. Supporting research has primarily focused on actual threat (e.g., shocks), and it is unclear whether the predictability of less intense threat (e.g., unpleasant pictures) similarly affects motivation and attention. The present study utilized a within-subject design and examined defensive motivation (startle reflex and self-reported anxiety) and attention (probe N100 and P300) in anticipation of shocks and unpleasant pictures during a no, predictable, and unpredictable threat task. This study also examined the impact of predictability on the P300 to shocks and late positive potential (LPP) to unpleasant pictures. The startle reflex and self-reported anxiety were increased in anticipation of both types of threat relative to no threat. Furthermore, startle potentiation in anticipation of unpredictable threat was greater for shocks compared to unpleasant pictures, but there was no difference for predictable threat. The probe N100 was enhanced in anticipation of unpredictable threat relative to predictable threat and no threat, and the probe P300 was suppressed in anticipation of predictable and unpredictable threat relative to no threat. These effects did not differ between the shock and unpleasant picture trials. Finally, the P300 and early LPP component were increased in response to unpredictable relative to predictable shocks and unpleasant pictures, respectively. The present study suggests that the unpredictability of unpleasant pictures increases defensive motivation, but to a lesser degree relative to actual threat. Moreover, unpredictability enhances attentional engagement in anticipation of, and in reaction to, both types of threat. © 2017 Society for Psychophysiological Research.

Prediction of Addiction Potential on the Basis of Aggression and Assertiveness in University Students

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Mehrdad Hajihasani

2012-02-01

Full Text Available Introduction: The aim of present research was the prediction of addiction potential on the basis of aggression and assertiveness in Allameh Tabbatabaei girl students. Method: The research method was correlational design and population of research was girl students of Allameh Tabatabaei university. By available sampling 150 girls were selected and Ahvaz Aggression Questionnaire, Gambril & Rigy Assertiveness questionnaire and Zargari Addiction Potential Questionnaire administered among selected sample. Findings: the results of the Pearson correlation showed that the relationship between aggression, assertiveness, and addiction potential was significant. Also, the results of multivariate regression analysis showed that aggression, assertiveness and depression can predict the Addiction Potential. Conclusion: Addiction potential can be predicted by aggression and assertiveness.

In silico prediction of potential chemical reactions mediated by human enzymes.

Science.gov (United States)

Yu, Myeong-Sang; Lee, Hyang-Mi; Park, Aaron; Park, Chungoo; Ceong, Hyithaek; Rhee, Ki-Hyeong; Na, Dokyun

2018-06-13

Administered drugs are often converted into an ineffective or activated form by enzymes in our body. Conventional in silico prediction approaches focused on therapeutically important enzymes such as CYP450. However, there are more than thousands of different cellular enzymes that potentially convert administered drug into other forms. We developed an in silico model to predict which of human enzymes including metabolic enzymes as well as CYP450 family can catalyze a given chemical compound. The prediction is based on the chemical and physical similarity between known enzyme substrates and a query chemical compound. Our in silico model was developed using multiple linear regression and the model showed high performance (AUC = 0.896) despite of the large number of enzymes. When evaluated on a test dataset, it also showed significantly high performance (AUC = 0.746). Interestingly, evaluation with literature data showed that our model can be used to predict not only enzymatic reactions but also drug conversion and enzyme inhibition. Our model was able to predict enzymatic reactions of a query molecule with a high accuracy. This may foster to discover new metabolic routes and to accelerate the computational development of drug candidates by enabling the prediction of the potential conversion of administered drugs into active or inactive forms.

Prediction of Student Dropout in E-Learning Program Through the Use of Machine Learning Method

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Mingjie Tan

2015-02-01

Full Text Available The high rate of dropout is a serious problem in E-learning program. Thus it has received extensive concern from the education administrators and researchers. Predicting the potential dropout students is a workable solution to prevent dropout. Based on the analysis of related literature, this study selected student’s personal characteristic and academic performance as input attributions. Prediction models were developed using Artificial Neural Network (ANN, Decision Tree (DT and Bayesian Networks (BNs. A large sample of 62375 students was utilized in the procedures of model training and testing. The results of each model were presented in confusion matrix, and analyzed by calculating the rates of accuracy, precision, recall, and F-measure. The results suggested all of the three machine learning methods were effective in student dropout prediction, and DT presented a better performance. Finally, some suggestions were made for considerable future research.

e-Cow: an animal model that predicts herbage intake, milk yield and live weight change in dairy cows grazing temperate pastures, with and without supplementary feeding.

Science.gov (United States)

Baudracco, J; Lopez-Villalobos, N; Holmes, C W; Comeron, E A; Macdonald, K A; Barry, T N; Friggens, N C

2012-06-01

This animal simulation model, named e-Cow, represents a single dairy cow at grazing. The model integrates algorithms from three previously published models: a model that predicts herbage dry matter (DM) intake by grazing dairy cows, a mammary gland model that predicts potential milk yield and a body lipid model that predicts genetically driven live weight (LW) and body condition score (BCS). Both nutritional and genetic drives are accounted for in the prediction of energy intake and its partitioning. The main inputs are herbage allowance (HA; kg DM offered/cow per day), metabolisable energy and NDF concentrations in herbage and supplements, supplements offered (kg DM/cow per day), type of pasture (ryegrass or lucerne), days in milk, days pregnant, lactation number, BCS and LW at calving, breed or strain of cow and genetic merit, that is, potential yields of milk, fat and protein. Separate equations are used to predict herbage intake, depending on the cutting heights at which HA is expressed. The e-Cow model is written in Visual Basic programming language within Microsoft Excel®. The model predicts whole-lactation performance of dairy cows on a daily basis, and the main outputs are the daily and annual DM intake, milk yield and changes in BCS and LW. In the e-Cow model, neither herbage DM intake nor milk yield or LW change are needed as inputs; instead, they are predicted by the e-Cow model. The e-Cow model was validated against experimental data for Holstein-Friesian cows with both North American (NA) and New Zealand (NZ) genetics grazing ryegrass-based pastures, with or without supplementary feeding and for three complete lactations, divided into weekly periods. The model was able to predict animal performance with satisfactory accuracy, with concordance correlation coefficients of 0.81, 0.76 and 0.62 for herbage DM intake, milk yield and LW change, respectively. Simulations performed with the model showed that it is sensitive to genotype by feeding environment

Exploring the Potential of Predictive Analytics and Big Data in Emergency Care.

Science.gov (United States)

Janke, Alexander T; Overbeek, Daniel L; Kocher, Keith E; Levy, Phillip D

2016-02-01

Clinical research often focuses on resource-intensive causal inference, whereas the potential of predictive analytics with constantly increasing big data sources remains largely unexplored. Basic prediction, divorced from causal inference, is much easier with big data. Emergency care may benefit from this simpler application of big data. Historically, predictive analytics have played an important role in emergency care as simple heuristics for risk stratification. These tools generally follow a standard approach: parsimonious criteria, easy computability, and independent validation with distinct populations. Simplicity in a prediction tool is valuable, but technological advances make it no longer a necessity. Emergency care could benefit from clinical predictions built using data science tools with abundant potential input variables available in electronic medical records. Patients' risks could be stratified more precisely with large pools of data and lower resource requirements for comparing each clinical encounter to those that came before it, benefiting clinical decisionmaking and health systems operations. The largest value of predictive analytics comes early in the clinical encounter, in which diagnostic and prognostic uncertainty are high and resource-committing decisions need to be made. We propose an agenda for widening the application of predictive analytics in emergency care. Throughout, we express cautious optimism because there are myriad challenges related to database infrastructure, practitioner uptake, and patient acceptance. The quality of routinely compiled clinical data will remain an important limitation. Complementing big data sources with prospective data may be necessary if predictive analytics are to achieve their full potential to improve care quality in the emergency department. Copyright © 2015 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.

Personal contextual characteristics and cognitions: predicting child abuse potential and disciplinary style.

Science.gov (United States)

Rodriguez, Christina M

2010-02-01

According to Social Information Processing theory, parents' cognitive processes influence their decisions to engage in physical maltreatment, although cognitions occur in the context of other aspects of the parents' life. The present study investigated whether cognitive processes (external locus of control, inappropriate developmental expectations) predicted child abuse potential and overreactive disciplinary style beyond personal contextual factors characteristic of the parent (hostility, stress, and coping). 363 parents were recruited online. Results highlight the relative importance of the contextual characteristics (particularly stress, avoidant coping, and irritability) relative to cognitive processes in predicting abuse potential and overreactive discipline strategies, although an external locus of control also significantly contributed. Findings do not support that parents' developmental expectations uniquely predict elevated abuse risk. Results indicate stressed parents who utilize avoidance coping strategies are more likely to use overreactive discipline and report increased abuse potential. Findings are discussed with regard to implications for prevention/intervention efforts.

Invader Relative Impact Potential: a new metric to understand and predict the ecological impacts of existing, emerging and future invasive alien species

OpenAIRE

Dick, JTA; Laverty, C; Lennon, JJ; Barrios-O'Neill, D; Mensink, PJ; Britton, JR; Medoc, V; Boets, P; Alexander, ME; Taylor, NG; Dunn, AM; Hatcher, MJ; Rosewarne, PJ; Crookes, S; MacIsaac, HJ

2017-01-01

1. Predictions of the identities and ecological impacts of invasive alien species are critical for risk assessment, but presently we lack universal and standardized metrics that reliably predict the likelihood and degree of impact of such invaders (i.e. measurable changes in populations of affected species). This need is especially pressing for emerging and potential future invaders that have no invasion history. Such a metric would also ideally apply across diverse taxonomic and trophic gro...

Protein thermostability prediction within homologous families using temperature-dependent statistical potentials.

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Fabrizio Pucci

Full Text Available The ability to rationally modify targeted physical and biological features of a protein of interest holds promise in numerous academic and industrial applications and paves the way towards de novo protein design. In particular, bioprocesses that utilize the remarkable properties of enzymes would often benefit from mutants that remain active at temperatures that are either higher or lower than the physiological temperature, while maintaining the biological activity. Many in silico methods have been developed in recent years for predicting the thermodynamic stability of mutant proteins, but very few have focused on thermostability. To bridge this gap, we developed an algorithm for predicting the best descriptor of thermostability, namely the melting temperature Tm, from the protein's sequence and structure. Our method is applicable when the Tm of proteins homologous to the target protein are known. It is based on the design of several temperature-dependent statistical potentials, derived from datasets consisting of either mesostable or thermostable proteins. Linear combinations of these potentials have been shown to yield an estimation of the protein folding free energies at low and high temperatures, and the difference of these energies, a prediction of the melting temperature. This particular construction, that distinguishes between the interactions that contribute more than others to the stability at high temperatures and those that are more stabilizing at low T, gives better performances compared to the standard approach based on T-independent potentials which predict the thermal resistance from the thermodynamic stability. Our method has been tested on 45 proteins of known Tm that belong to 11 homologous families. The standard deviation between experimental and predicted Tm's is equal to 13.6°C in cross validation, and decreases to 8.3°C if the 6 worst predicted proteins are excluded. Possible extensions of our approach are discussed.

Scoring radiologic characteristics to predict proliferative potential in meningiomas

International Nuclear Information System (INIS)

Hashiba, Tetsuo; Hashimoto, Naoya; Maruno, Motohiko; Izumoto, Shuichi; Suzuki, Tsuyoshi; Kagawa, Naoki; Yoshimine, Toshiki

2006-01-01

We investigated the feasibility of using radiologic characteristics to predict the proliferative potential in meningiomas. Our statistical analysis revealed that the presence of peritumoral edema, an ambiguous brain-tumor border, and irregular tumor shape were significantly correlated with a higher MIB-1 staining index (SI) value. We developed the following scoring system for specific features in each tumor: peritumoral edema (tumor with edema=1, tumor without edema=0); brain-tumor border (tumor with any ambiguous border=1, tumor circumscribed by a distinct rim=0); and tumor shape (tumor with irregular shape=1, tumor with smooth shape=0). Using Spearman's correlation coefficient analysis, we found a significant correlation (P<0.005) between total score calculated for each patient and SI value. Our findings suggest that the proliferative potential of meningiomas can be predicted using a less invasive preoperative examination focusing on the presence of peritumoral edema, ambiguous brain-tumor border, and irregular tumor shape. (author)

Health Literacy and Global Cognitive Function Predict E-Mail but Not Internet Use in Heart Failure Patients

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Jared P. Schprechman

2013-01-01

Full Text Available Background. The internet offers a potential for improving patient knowledge, and e-mail may be used in patient communication with providers. However, barriers to internet and e-mail use, such as low health literacy and cognitive impairment, may prevent patients from using technological resources. Purpose. We investigated whether health literacy, heart failure knowledge, and cognitive function were related to internet and e-mail use in older adults with heart failure (HF. Methods. Older adults (N=119 with heart failure (69.84±9.09 years completed measures of health literacy, heart failure knowledge, cognitive functioning, and internet use in a cross-sectional study. Results. Internet and e-mail use were reported in 78.2% and 71.4% of this sample of patients with HF, respectively. Controlling for age and education, logistic regression analyses indicated that higher health literacy predicted e-mail (P<.05 but not internet use. Global cognitive function predicted e-mail (P<.05 but not internet use. Only 45% used the Internet to obtain information on HF and internet use was not associated with greater HF knowledge. Conclusions. The majority of HF patients use the internet and e-mail, but poor health literacy and cognitive impairment may prevent some patients from accessing these resources. Future studies that examine specific internet and email interventions to increase HF knowledge are needed.

Radiotracer technique to predict irritation potential of soap

International Nuclear Information System (INIS)

Castaneda, S.S.; Garcia, T.Y.; Santos, F.L.

1990-01-01

The application of a radiotracer technique using tritiated water to predict the irritation potentials of some soap products is demonstrated. Collagen films are treated with 0.5% and 1.0% soap solutions and tritiated water then incubated at 50 degrees centigrade for 24 hours. After incubation, the uptake of tritiated water by the collagen films was measured by liquid scintillation counting. (Auth.). 6 refs., 2 tabs

Molecular cloning, expression, IgE binding activities and in silico epitope prediction of Per a 9 allergens of the American cockroach

Science.gov (United States)

Yang, Haiwei; Chen, Hao; Jin, Min; Xie, Hua; He, Shaoheng; Wei, Ji-Fu

2016-01-01

Per a 9 is a major allergen of the American cockroach (CR), which has been recognized as an important cause of imunoglobulin E-mediated type I hypersensitivity worldwide. However, it is not neasy to obtain a substantial quantity of this allergen for use in functional studies. In the present study, the Per a 9 gene was cloned and expressed in Escherichia coli (E. coli) systems. It was found that 13/16 (81.3%) of the sera from patients with allergies caused by the American CR reacted to Per a 9, as assessed by enzyme-linked immunosorbent assay, confirming that Per a 9 is a major allergen of CR. The induction of the expression of CD63 and CCR3 in passively sensitized basophils (from sera of patients with allergies caused by the American CR) by approximately 4.2-fold indicated that recombinant Per a 9 was functionally active. Three immunoinformatics tools, including the DNASTAR Protean system, Bioinformatics Predicted Antigenic Peptides (BPAP) system and the BepiPred 1.0 server were used to predict the potential B cell epitopes, while Net-MHCIIpan-2.0 and NetMHCII-2.2 were used to predict the T cell epitopes of Per a 9. As a result, we predicted 11 peptides (23–28, 39–46, 58–64, 91–118, 131–136, 145–154, 159–165, 176–183, 290–299, 309–320 and 338–344) as potential B cell linear epitopes. In T cell prediction, the Per a 9 allergen was predicted to have 5 potential T cell epitope sequences, 119–127, 194–202, 210–218, 239–250 and 279–290. The findings of our study may prove to be useful in the development of peptide-based vaccines to combat CR-induced allergies. PMID:27840974

Inclusive (e,e'N), (e,e'NN), (e,e'π),... reactions in nuclei

International Nuclear Information System (INIS)

Gil, A.; Oset, E.

1997-01-01

We study the inclusive (e,e'N), (e,e'NN), (e,e'π), (e,e'πN) reactions in nuclei using a Monte Carlo simulation method to treat the multichannel problem of the final state. The input consists of reaction probabilities for the different steps evaluated using microscopical many body methods. We obtain a good agreement with experiment in some channels where there is data and make predictions for other channels which are presently under investigation in several electron laboratories. The comparison of the theoretical results with experiment for several kinematical conditions and diverse channels can serve to learn about different physical processes occurring in the reaction. The potential of this theoretical tool to make prospections for possible experiments, aiming at pinning down certain reaction probabilities, is also emphasized. (orig.)

The eTOX Data-Sharing Project to Advance in Silico Drug-Induced Toxicity Prediction

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Montserrat Cases

2014-11-01

Full Text Available The high-quality in vivo preclinical safety data produced by the pharmaceutical industry during drug development, which follows numerous strict guidelines, are mostly not available in the public domain. These safety data are sometimes published as a condensed summary for the few compounds that reach the market, but the majority of studies are never made public and are often difficult to access in an automated way, even sometimes within the owning company itself. It is evident from many academic and industrial examples, that useful data mining and model development requires large and representative data sets and careful curation of the collected data. In 2010, under the auspices of the Innovative Medicines Initiative, the eTOX project started with the objective of extracting and sharing preclinical study data from paper or pdf archives of toxicology departments of the 13 participating pharmaceutical companies and using such data for establishing a detailed, well-curated database, which could then serve as source for read-across approaches (early assessment of the potential toxicity of a drug candidate by comparison of similar structure and/or effects and training of predictive models. The paper describes the efforts undertaken to allow effective data sharing intellectual property (IP protection and set up of adequate controlled vocabularies and to establish the database (currently with over 4000 studies contributed by the pharma companies corresponding to more than 1400 compounds. In addition, the status of predictive models building and some specific features of the eTOX predictive system (eTOXsys are presented as decision support knowledge-based tools for drug development process at an early stage.

Predictive value of IgE/IgG4 antibody ratio in children with egg allergy

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Okamoto Shindou

2012-06-01

Full Text Available Abstract Background The aim of this study was to investigate the role of specific IgG4 antibodies to hen’s egg white and determine their utility as a marker for the outcome of oral challenge test in children sensitized to hen’s egg Methods The hen’s egg oral food challenge test was performed in 105 sensitized children without atopic dermatitis, and the titers of egg white-specific immunoglobulin G4 (IgG4 and immunoglobulin E (IgE antibodies were measured. To set the cut-off values of IgG4, IgE, and the IgE/IgG4 ratio for predicting positive results in oral challenges, receiver operating characteristic curves were plotted and the area under the curves (AUC were calculated. Results Sixty-four of 105 oral challenges with whole eggs were assessed as positive. The AUC for IgE, IgG4, and IgE/IgG4 for the prediction of positive results were 0.609, 0.724, and 0.847, respectively. Thus, the IgE/IgG4 ratio generated significantly higher specificity, sensitivity, positive predictive value (%, and negative predictive value (% than the individual IgE and IgG4. The negative predictive value of the IgE/IgG4 ratio was 90% at a value of 1. Conclusions We have demonstrated that the egg white-specific serum IgE/IgG4 ratio is important for predicting reactivity to egg during food challenges.

Random Forests (RFs) for Estimation, Uncertainty Prediction and Interpretation of Monthly Solar Potential

Science.gov (United States)

Assouline, Dan; Mohajeri, Nahid; Scartezzini, Jean-Louis

2017-04-01

Solar energy is clean, widely available, and arguably the most promising renewable energy resource. Taking full advantage of solar power, however, requires a deep understanding of its patterns and dependencies in space and time. The recent advances in Machine Learning brought powerful algorithms to estimate the spatio-temporal variations of solar irradiance (the power per unit area received from the Sun, W/m2), using local weather and terrain information. Such algorithms include Deep Learning (e.g. Artificial Neural Networks), or kernel methods (e.g. Support Vector Machines). However, most of these methods have some disadvantages, as they: (i) are complex to tune, (ii) are mainly used as a black box and offering no interpretation on the variables contributions, (iii) often do not provide uncertainty predictions (Assouline et al., 2016). To provide a reasonable solar mapping with good accuracy, these gaps would ideally need to be filled. We present here simple steps using one ensemble learning algorithm namely, Random Forests (Breiman, 2001) to (i) estimate monthly solar potential with good accuracy, (ii) provide information on the contribution of each feature in the estimation, and (iii) offer prediction intervals for each point estimate. We have selected Switzerland as an example. Using a Digital Elevation Model (DEM) along with monthly solar irradiance time series and weather data, we build monthly solar maps for Global Horizontal Irradiance (GHI), Diffuse Horizontal Irradiance (GHI), and Extraterrestrial Irradiance (EI). The weather data include monthly values for temperature, precipitation, sunshine duration, and cloud cover. In order to explain the impact of each feature on the solar irradiance of each point estimate, we extend the contribution method (Kuz'min et al., 2011) to a regression setting. Contribution maps for all features can then be computed for each solar map. This provides precious information on the spatial variation of the features impact all

An algorithm to discover gene signatures with predictive potential

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Hallett Robin M

2010-09-01

Full Text Available Abstract Background The advent of global gene expression profiling has generated unprecedented insight into our molecular understanding of cancer, including breast cancer. For example, human breast cancer patients display significant diversity in terms of their survival, recurrence, metastasis as well as response to treatment. These patient outcomes can be predicted by the transcriptional programs of their individual breast tumors. Predictive gene signatures allow us to correctly classify human breast tumors into various risk groups as well as to more accurately target therapy to ensure more durable cancer treatment. Results Here we present a novel algorithm to generate gene signatures with predictive potential. The method first classifies the expression intensity for each gene as determined by global gene expression profiling as low, average or high. The matrix containing the classified data for each gene is then used to score the expression of each gene based its individual ability to predict the patient characteristic of interest. Finally, all examined genes are ranked based on their predictive ability and the most highly ranked genes are included in the master gene signature, which is then ready for use as a predictor. This method was used to accurately predict the survival outcomes in a cohort of human breast cancer patients. Conclusions We confirmed the capacity of our algorithm to generate gene signatures with bona fide predictive ability. The simplicity of our algorithm will enable biological researchers to quickly generate valuable gene signatures without specialized software or extensive bioinformatics training.

Changes in event-related potential functional networks predict traumatic brain injury in piglets.

Science.gov (United States)

Atlan, Lorre S; Lan, Ingrid S; Smith, Colin; Margulies, Susan S

2018-06-01

Traumatic brain injury is a leading cause of cognitive and behavioral deficits in children in the US each year. None of the current diagnostic tools, such as quantitative cognitive and balance tests, have been validated to identify mild traumatic brain injury in infants, adults and animals. In this preliminary study, we report a novel, quantitative tool that has the potential to quickly and reliably diagnose traumatic brain injury and which can track the state of the brain during recovery across multiple ages and species. Using 32 scalp electrodes, we recorded involuntary auditory event-related potentials from 22 awake four-week-old piglets one day before and one, four, and seven days after two different injury types (diffuse and focal) or sham. From these recordings, we generated event-related potential functional networks and assessed whether the patterns of the observed changes in these networks could distinguish brain-injured piglets from non-injured. Piglet brains exhibited significant changes after injury, as evaluated by five network metrics. The injury prediction algorithm developed from our analysis of the changes in the event-related potentials functional networks ultimately produced a tool with 82% predictive accuracy. This novel approach is the first application of auditory event-related potential functional networks to the prediction of traumatic brain injury. The resulting tool is a robust, objective and predictive method that offers promise for detecting mild traumatic brain injury, in particular because collecting event-related potentials data is noninvasive and inexpensive. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Prediction of Potential Hit Song and Musical Genre Using Artificial Neural Networks

Science.gov (United States)

Monterola, Christopher; Abundo, Cheryl; Tugaff, Jeric; Venturina, Lorcel Ericka

Accurately quantifying the goodness of music based on the seemingly subjective taste of the public is a multi-million industry. Recording companies can make sound decisions on which songs or artists to prioritize if accurate forecasting is achieved. We extract 56 single-valued musical features (e.g. pitch and tempo) from 380 Original Pilipino Music (OPM) songs (190 are hit songs) released from 2004 to 2006. Based on an effect size criterion which measures a variable's discriminating power, the 20 highest ranked features are fed to a classifier tasked to predict hit songs. We show that regardless of musical genre, a trained feed-forward neural network (NN) can predict potential hit songs with an average accuracy of ΦNN = 81%. The accuracy is about +20% higher than those of standard classifiers such as linear discriminant analysis (LDA, ΦLDA = 61%) and classification and regression trees (CART, ΦCART = 57%). Both LDA and CART are above the proportional chance criterion (PCC, ΦPCC = 50%) but are slightly below the suggested acceptable classifier requirement of 1.25*ΦPCC = 63%. Utilizing a similar procedure, we demonstrate that different genres (ballad, alternative rock or rock) of OPM songs can be automatically classified with near perfect accuracy using LDA or NN but only around 77% using CART.

Predictability of painful stimulation modulates the somatosensory-evoked potential in the rat

NARCIS (Netherlands)

Schaap, M.W.H.; van Oostrom, H.; Doornenbal, A.; Baars, A.M.; Arndt, S.S.; Hellebrekers, L.J.

2013-01-01

Abstract Somatosensory-evoked potentials (SEPs) are used in humans and animals to increase knowledge about nociception and pain. Since the SEP in humans increases when noxious stimuli are administered unpredictably, predictability potentially influences the SEP in animals as well. To assess the

EEG potentials predict upcoming emergency brakings during simulated driving

Science.gov (United States)

Haufe, Stefan; Treder, Matthias S.; Gugler, Manfred F.; Sagebaum, Max; Curio, Gabriel; Blankertz, Benjamin

2011-10-01

Emergency braking assistance has the potential to prevent a large number of car crashes. State-of-the-art systems operate in two stages. Basic safety measures are adopted once external sensors indicate a potential upcoming crash. If further activity at the brake pedal is detected, the system automatically performs emergency braking. Here, we present the results of a driving simulator study indicating that the driver's intention to perform emergency braking can be detected based on muscle activation and cerebral activity prior to the behavioural response. Identical levels of predictive accuracy were attained using electroencephalography (EEG), which worked more quickly than electromyography (EMG), and using EMG, which worked more quickly than pedal dynamics. A simulated assistance system using EEG and EMG was found to detect emergency brakings 130 ms earlier than a system relying only on pedal responses. At 100 km h-1 driving speed, this amounts to reducing the braking distance by 3.66 m. This result motivates a neuroergonomic approach to driving assistance. Our EEG analysis yielded a characteristic event-related potential signature that comprised components related to the sensory registration of a critical traffic situation, mental evaluation of the sensory percept and motor preparation. While all these components should occur often during normal driving, we conjecture that it is their characteristic spatio-temporal superposition in emergency braking situations that leads to the considerable prediction performance we observed.

Maxent modelling for predicting the potential distribution of Thai Palms

DEFF Research Database (Denmark)

Tovaranonte, Jantrararuk; Barfod, Anders S.; Overgaard, Anne Blach

2011-01-01

on presence data. The aim was to identify potential hot spot areas, assess the determinants of palm distribution ranges, and provide a firmer knowledge base for future conservation actions. We focused on a relatively small number of climatic, environmental and spatial variables in order to avoid...... overprediction of species distribution ranges. The models with the best predictive power were found by calculating the area under the curve (AUC) of receiver-operating characteristic (ROC). Here, we provide examples of contrasting predicted species distribution ranges as well as a map of modeled palm diversity...

Validating computational predictions of night-time ventilation in Stanford's Y2E2 building

Science.gov (United States)

Chen, Chen; Lamberti, Giacomo; Gorle, Catherine

2017-11-01

Natural ventilation can significantly reduce building energy consumption, but robust design is a challenging task. We previously presented predictions of natural ventilation performance in Stanford's Y2E2 building using two models with different levels of fidelity, embedded in an uncertainty quantification framework to identify the dominant uncertain parameters and predict quantified confidence intervals. The results showed a slightly high cooling rate for the volume-averaged temperature, and the initial thermal mass temperature and window discharge coefficients were found to have an important influence on the results. To further investigate the potential role of these parameters on the observed discrepancies, the current study is performing additional measurements in the Y2E2 building. Wall temperatures are recorded throughout the nightflush using thermocouples; flow rates through windows are measured using hotwires; and spatial variability in the air temperature is explored. The measured wall temperatures are found the be within the range of our model assumptions, and the measured velocities agree reasonably well with our CFD predications. Considerable local variations in the indoor air temperature have been recorded, largely explaining the discrepancies in our earlier validation study. Future work will therefore focus on a local validation of the CFD results with the measurements. Center for Integrated Facility Engineering (CIFE).

Microwave enhancement of CISH for HER2 oncogene.

Science.gov (United States)

Leong, Anthony S Y; Haffajee, Zenobia; Clarke, Megan

2007-03-01

We describe a modification to the prescribed procedure for the Zymed Spot-Light HER2 chromogenic in situ hybridization kit (84-0146, Zymed Laboratories, San Francisco, CA) by substituting the heat pretreatment step with MW irradiation in citrate buffer 10 mmol/L at pH 6.0 at 98 degrees C for 10 minutes and repeating the procedure afterenzyme digestion with time and temperature controlled in the Mega T/ T oven (Milestone s.r.l., Sorisole, Italy). The subsequent procedure leading up to hybridized was as per manufacturer's instructions. Invasive breast carcinoma previously scored by immunohistochemistry for HER2, comprising 18 cases of 3+, 18 cases of 2+, and 12 cases of 1+, were examined by chromogenic in situ hybridization using this modified procedure, with a parallel set of cases examined by the prescribed Zymed method. The introduction of the "MW retrieval" steps resulted in consistently a greater number of hybridization signals in amplified tumor cells with benign epithelial cells and lymphocytes displaying 2 clear dots compared with the weaker and less consistent signals obtained with the standard procedure. MW exposed sections showed larger numbers of large and small clusters that often allowed identification of amplified tumors without having to count single dots with crisp staining and absence of background precipitation.

Label-free morphology-based prediction of multiple differentiation potentials of human mesenchymal stem cells for early evaluation of intact cells.

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Hiroto Sasaki

Full Text Available Precise quantification of cellular potential of stem cells, such as human bone marrow-derived mesenchymal stem cells (hBMSCs, is important for achieving stable and effective outcomes in clinical stem cell therapy. Here, we report a method for image-based prediction of the multiple differentiation potentials of hBMSCs. This method has four major advantages: (1 the cells used for potential prediction are fully intact, and therefore directly usable for clinical applications; (2 predictions of potentials are generated before differentiation cultures are initiated; (3 prediction of multiple potentials can be provided simultaneously for each sample; and (4 predictions of potentials yield quantitative values that correlate strongly with the experimental data. Our results show that the collapse of hBMSC differentiation potentials, triggered by in vitro expansion, can be quantitatively predicted far in advance by predicting multiple potentials, multi-lineage differentiation potentials (osteogenic, adipogenic, and chondrogenic and population doubling potential using morphological features apparent during the first 4 days of expansion culture. In order to understand how such morphological features can be effective for advance predictions, we measured gene-expression profiles of the same early undifferentiated cells. Both senescence-related genes (p16 and p21 and cytoskeleton-related genes (PTK2, CD146, and CD49 already correlated to the decrease of potentials at this stage. To objectively compare the performance of morphology and gene expression for such early prediction, we tested a range of models using various combinations of features. Such comparison of predictive performances revealed that morphological features performed better overall than gene-expression profiles, balancing the predictive accuracy with the effort required for model construction. This benchmark list of various prediction models not only identifies the best morphological feature

Potential Predictability of ZPD of Children’s Cognitive Development

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Parviz Birjandi

2011-05-01

Full Text Available Obtaining information on whether the child has the potential for growth is not an easy task. Research shows that using different matrix like Raven or different batteries in a static way cannot
be indicative of children further development. This study attempts to probe the potential predictability of children’s performance during Dynamic Assessment of their Future development.
41 children between ages 3 to 6 years old participated in this study. The data in pretest, ZPD, and posttest were converted into Rasch Measure. The results of different analysis indicate that relying on children’s actual performance cannot be an indicative factor of their development in the future.

E-learning in medical education: the potential environmental impact.

Science.gov (United States)

Walsh, Kieran

2018-03-01

Introduction There is a growing interest in the use of e-learning in medical education. However until recently there has been little interest in the potential environmental benefits of e-learning. This paper models various environmental outcomes that might emerge from the use of an e-learning resource (BMJ Learning) in CPD. Methods We modeled the use of e-learning as a component of CPD and evaluated the potential impact of this use on the learner's carbon footprint. We looked at a number of models - all from the perspective of a General Practitioner (GP). We assumed that all GPs completed 50 h or credits of CPD per year. Results High users of e-learning can reduce their carbon footprint - mainly by reducing their travel to face-to-face events (reducing printing also has a small beneficial effect). A high user of e-learning can reduce the carbon footprint that relates to their CPD by 18.5 kg. Discussion As global warming continues to pose a risk to human and environmental health, we feel that doctors have a duty to consider learning activities (such as e-learning) that are associated with a lower carbon footprint.

PREDICTIVE POTENTIAL FIELD-BASED COLLISION AVOIDANCE FOR MULTICOPTERS

Directory of Open Access Journals (Sweden)

M. Nieuwenhuisen

2013-08-01

Full Text Available Reliable obstacle avoidance is a key to navigating with UAVs in the close vicinity of static and dynamic obstacles. Wheel-based mobile robots are often equipped with 2D or 3D laser range finders that cover the 2D workspace sufficiently accurate and at a high rate. Micro UAV platforms operate in a 3D environment, but the restricted payload prohibits the use of fast state-of-the-art 3D sensors. Thus, perception of small obstacles is often only possible in the vicinity of the UAV and a fast collision avoidance system is necessary. We propose a reactive collision avoidance system based on artificial potential fields, that takes the special dynamics of UAVs into account by predicting the influence of obstacles on the estimated trajectory in the near future using a learned motion model. Experimental evaluation shows that the prediction leads to smoother trajectories and allows to navigate collision-free through passageways.

CLIC: Physics potential of a high-energy e+e- collider

CERN Multimedia

CERN. Geneva

2018-01-01

The Compact Linear Collider (CLIC) is a future electron-positron collider under study. It foresees e+e- collisions at centre-of-mass energies ranging from a few hundred GeV up to 3 TeV. The CLIC study is an international collaboration hosted by CERN. The lectures provide a broad overview of the CLIC project, covering the physics potential, the particle detectors and the accelerator. An overview of the CLIC physics opportunities is presented. These are best exploited in a staged construction and operation scenario of the collider. The detector technologies, fulfilling CLIC performance requirements and currently under study, are described. The accelerator design and performance, together with its major technologies, are presented in the light of ongoing component tests and large system tests. The status of the optimisation studies (e.g. for cost and power) of the CLIC complex for the proposed energy staging is included. One lecture is dedicated to the use of CLIC technologies in free electron lasers and other ...

Predicting Energy Consumption for Potential Effective Use in Hybrid Vehicle Powertrain Management Using Driver Prediction

Science.gov (United States)

Magnuson, Brian

A proof-of-concept software-in-the-loop study is performed to assess the accuracy of predicted net and charge-gaining energy consumption for potential effective use in optimizing powertrain management of hybrid vehicles. With promising results of improving fuel efficiency of a thermostatic control strategy for a series, plug-ing, hybrid-electric vehicle by 8.24%, the route and speed prediction machine learning algorithms are redesigned and implemented for real- world testing in a stand-alone C++ code-base to ingest map data, learn and predict driver habits, and store driver data for fast startup and shutdown of the controller or computer used to execute the compiled algorithm. Speed prediction is performed using a multi-layer, multi-input, multi- output neural network using feed-forward prediction and gradient descent through back- propagation training. Route prediction utilizes a Hidden Markov Model with a recurrent forward algorithm for prediction and multi-dimensional hash maps to store state and state distribution constraining associations between atomic road segments and end destinations. Predicted energy is calculated using the predicted time-series speed and elevation profile over the predicted route and the road-load equation. Testing of the code-base is performed over a known road network spanning 24x35 blocks on the south hill of Spokane, Washington. A large set of training routes are traversed once to add randomness to the route prediction algorithm, and a subset of the training routes, testing routes, are traversed to assess the accuracy of the net and charge-gaining predicted energy consumption. Each test route is traveled a random number of times with varying speed conditions from traffic and pedestrians to add randomness to speed prediction. Prediction data is stored and analyzed in a post process Matlab script. The aggregated results and analysis of all traversals of all test routes reflect the performance of the Driver Prediction algorithm. The

Output from Statistical Predictive Models as Input to eLearning Dashboards

Directory of Open Access Journals (Sweden)

Marlene A. Smith

2015-06-01

Full Text Available We describe how statistical predictive models might play an expanded role in educational analytics by giving students automated, real-time information about what their current performance means for eventual success in eLearning environments. We discuss how an online messaging system might tailor information to individual students using predictive analytics. The proposed system would be data-driven and quantitative; e.g., a message might furnish the probability that a student will successfully complete the certificate requirements of a massive open online course. Repeated messages would prod underperforming students and alert instructors to those in need of intervention. Administrators responsible for accreditation or outcomes assessment would have ready documentation of learning outcomes and actions taken to address unsatisfactory student performance. The article’s brief introduction to statistical predictive models sets the stage for a description of the messaging system. Resources and methods needed to develop and implement the system are discussed.

The use of repassivation potential in predicting the performance of high-level nuclear waste container materials

International Nuclear Information System (INIS)

Sridhar, N.; Dunn, D.; Cragnolino, G.

1995-01-01

Localized corrosion in aqueous environments forms an important bounding condition for the performance assessment of high-level waste (HLW) container materials. A predictive methodology using repassivation potential is examined in this paper. It is shown, based on long-term (continuing for over 11 months) testing of alloy 825, that repassivation potential of deep pits or crevices is a conservative and robust parameter for the prediction of localized corrosion. In contrast, initiation potentials measured by short-term tests are non-conservative and highly sensitive to several surface and environmental factors. Corrosion data from various field tests and plant equipment performance are analyzed in terms of the applicability of repassivation potential. The applicability of repassivation potential for predicting the occurrence of stress corrosion cracking (SCC) and intergranular corrosion in chloride containing environments is also examined

eTOXlab, an open source modeling framework for implementing predictive models in production environments.

Science.gov (United States)

Carrió, Pau; López, Oriol; Sanz, Ferran; Pastor, Manuel

2015-01-01

Computational models based in Quantitative-Structure Activity Relationship (QSAR) methodologies are widely used tools for predicting the biological properties of new compounds. In many instances, such models are used as a routine in the industry (e.g. food, cosmetic or pharmaceutical industry) for the early assessment of the biological properties of new compounds. However, most of the tools currently available for developing QSAR models are not well suited for supporting the whole QSAR model life cycle in production environments. We have developed eTOXlab; an open source modeling framework designed to be used at the core of a self-contained virtual machine that can be easily deployed in production environments, providing predictions as web services. eTOXlab consists on a collection of object-oriented Python modules with methods mapping common tasks of standard modeling workflows. This framework allows building and validating QSAR models as well as predicting the properties of new compounds using either a command line interface or a graphic user interface (GUI). Simple models can be easily generated by setting a few parameters, while more complex models can be implemented by overriding pieces of the original source code. eTOXlab benefits from the object-oriented capabilities of Python for providing high flexibility: any model implemented using eTOXlab inherits the features implemented in the parent model, like common tools and services or the automatic exposure of the models as prediction web services. The particular eTOXlab architecture as a self-contained, portable prediction engine allows building models with confidential information within corporate facilities, which can be safely exported and used for prediction without disclosing the structures of the training series. The software presented here provides full support to the specific needs of users that want to develop, use and maintain predictive models in corporate environments. The technologies used by e

A "Uses and Gratification Expectancy Model" to Predict Students' "Perceived e-Learning Experience"

Science.gov (United States)

Mondi, Makingu; Woods, Peter; Rafi, Ahmad

2008-01-01

This study investigates "how and why" students' "Uses and Gratification Expectancy" (UGE) for e-learning resources influences their "Perceived e-Learning Experience." A "Uses and Gratification Expectancy Model" (UGEM) framework is proposed to predict students' "Perceived e-Learning Experience," and…

Testing predictions of the quantum landscape multiverse 2: the exponential inflationary potential

International Nuclear Information System (INIS)

Valentino, Eleonora Di; Mersini-Houghton, Laura

2017-01-01

The 2015 Planck data release tightened the region of the allowed inflationary models. Inflationary models with convex potentials have now been ruled out since they produce a large tensor to scalar ratio. Meanwhile the same data offers interesting hints on possible deviations from the standard picture of CMB perturbations. Here we revisit the predictions of the theory of the origin of the universe from the landscape multiverse for the case of exponential inflation, for two reasons: firstly to check the status of the anomalies associated with this theory, in the light of the recent Planck data; secondly, to search for a counterexample whereby new physics modifications may bring convex inflationary potentials, thought to have been ruled out, back into the region of potentials allowed by data. Using the exponential inflation as an example of convex potentials, we find that the answer to both tests is positive: modifications to the perturbation spectrum and to the Newtonian potential of the universe originating from the quantum entanglement, bring the exponential potential, back within the allowed region of current data; and, the series of anomalies previously predicted in this theory, is still in good agreement with current data. Hence our finding for this convex potential comes at the price of allowing for additional thermal relic particles, equivalently dark radiation, in the early universe.

Testing predictions of the quantum landscape multiverse 2: the exponential inflationary potential

Energy Technology Data Exchange (ETDEWEB)

Valentino, Eleonora Di [Institut d' Astrophysique de Paris (UMR7095: CNRS and UPMC-Sorbonne Universities), F-75014, Paris (France); Mersini-Houghton, Laura, E-mail: valentin@iap.fr, E-mail: mersini@physics.unc.edu [Department of Physics and Astronomy, UNC-Chapel Hill, Chapel Hill, NC 27599 (United States)

2017-03-01

The 2015 Planck data release tightened the region of the allowed inflationary models. Inflationary models with convex potentials have now been ruled out since they produce a large tensor to scalar ratio. Meanwhile the same data offers interesting hints on possible deviations from the standard picture of CMB perturbations. Here we revisit the predictions of the theory of the origin of the universe from the landscape multiverse for the case of exponential inflation, for two reasons: firstly to check the status of the anomalies associated with this theory, in the light of the recent Planck data; secondly, to search for a counterexample whereby new physics modifications may bring convex inflationary potentials, thought to have been ruled out, back into the region of potentials allowed by data. Using the exponential inflation as an example of convex potentials, we find that the answer to both tests is positive: modifications to the perturbation spectrum and to the Newtonian potential of the universe originating from the quantum entanglement, bring the exponential potential, back within the allowed region of current data; and, the series of anomalies previously predicted in this theory, is still in good agreement with current data. Hence our finding for this convex potential comes at the price of allowing for additional thermal relic particles, equivalently dark radiation, in the early universe.

Potential decadal predictability and its sensitivity to sea ice albedo parameterization in a global coupled model

Energy Technology Data Exchange (ETDEWEB)

Koenigk, Torben; Caian, Mihaela; Doescher, Ralf; Wyser, Klaus [Swedish Meteorological and Hydrological Institute, Rossby Centre, Norrkoeping (Sweden); Koenig Beatty, Christof [Universite Catholique de Louvain, Louvain-la-Neuve (Belgium)

2012-06-15

Decadal prediction is one focus of the upcoming 5th IPCC Assessment report. To be able to interpret the results and to further improve the decadal predictions it is important to investigate the potential predictability in the participating climate models. This study analyzes the upper limit of climate predictability on decadal time scales and its dependency on sea ice albedo parameterization by performing two perfect ensemble experiments with the global coupled climate model EC-Earth. In the first experiment, the standard albedo formulation of EC-Earth is used, in the second experiment sea ice albedo is reduced. The potential prognostic predictability is analyzed for a set of oceanic and atmospheric parameters. The decadal predictability of the atmospheric circulation is small. The highest potential predictability was found in air temperature at 2 m height over the northern North Atlantic and the southern South Atlantic. Over land, only a few areas are significantly predictable. The predictability for continental size averages of air temperature is relatively good in all northern hemisphere regions. Sea ice thickness is highly predictable along the ice edges in the North Atlantic Arctic Sector. The meridional overturning circulation is highly predictable in both experiments and governs most of the decadal climate predictability in the northern hemisphere. The experiments using reduced sea ice albedo show some important differences like a generally higher predictability of atmospheric variables in the Arctic or higher predictability of air temperature in Europe. Furthermore, decadal variations are substantially smaller in the simulations with reduced ice albedo, which can be explained by reduced sea ice thickness in these simulations. (orig.)

Prediction of rodent carcinogenic potential of naturally occurring chemicals in the human diet using high-throughput QSAR predictive modeling

International Nuclear Information System (INIS)

Valerio, Luis G.; Arvidson, Kirk B.; Chanderbhan, Ronald F.; Contrera, Joseph F.

2007-01-01

Consistent with the U.S. Food and Drug Administration (FDA) Critical Path Initiative, predictive toxicology software programs employing quantitative structure-activity relationship (QSAR) models are currently under evaluation for regulatory risk assessment and scientific decision support for highly sensitive endpoints such as carcinogenicity, mutagenicity and reproductive toxicity. At the FDA's Center for Food Safety and Applied Nutrition's Office of Food Additive Safety and the Center for Drug Evaluation and Research's Informatics and Computational Safety Analysis Staff (ICSAS), the use of computational SAR tools for both qualitative and quantitative risk assessment applications are being developed and evaluated. One tool of current interest is MDL-QSAR predictive discriminant analysis modeling of rodent carcinogenicity, which has been previously evaluated for pharmaceutical applications by the FDA ICSAS. The study described in this paper aims to evaluate the utility of this software to estimate the carcinogenic potential of small, organic, naturally occurring chemicals found in the human diet. In addition, a group of 19 known synthetic dietary constituents that were positive in rodent carcinogenicity studies served as a control group. In the test group of naturally occurring chemicals, 101 were found to be suitable for predictive modeling using this software's discriminant analysis modeling approach. Predictions performed on these compounds were compared to published experimental evidence of each compound's carcinogenic potential. Experimental evidence included relevant toxicological studies such as rodent cancer bioassays, rodent anti-carcinogenicity studies, genotoxic studies, and the presence of chemical structural alerts. Statistical indices of predictive performance were calculated to assess the utility of the predictive modeling method. Results revealed good predictive performance using this software's rodent carcinogenicity module of over 1200 chemicals

Next-to-leading order prediction for the decay μ→e (e{sup +}e{sup −}) νν̄

Energy Technology Data Exchange (ETDEWEB)

Fael, M.; Greub, C. [Albert Einstein Center for Fundamental Physics,Institute for Theoretical Physics, University of Bern,CH-3012 Bern (Switzerland)

2017-01-19

We present the differential decay rates and the branching ratios of the muon decay with internal conversion, μ→e (e{sup +}e{sup −}) νν̄, in the Standard Model at next-to-leading order (NLO) in the on-shell scheme. This rare decay mode of the muon is among the main sources of background to the search for μ→eee decay. We found that in the phase space region where the neutrino energies are small, and the three-electron momenta have a similar signature as in the μ→eee decay, the NLO corrections decrease the leading-order prediction by about 10−20% depending on the applied cut.

Effect of foam on temperature prediction and heat recovery potential from biological wastewater treatment.

Science.gov (United States)

Corbala-Robles, L; Volcke, E I P; Samijn, A; Ronsse, F; Pieters, J G

2016-05-15

Heat is an important resource in wastewater treatment plants (WWTPs) which can be recovered. A prerequisite to determine the theoretical heat recovery potential is an accurate heat balance model for temperature prediction. The insulating effect of foam present on the basin surface and its influence on temperature prediction were assessed in this study. Experiments were carried out to characterize the foam layer and its insulating properties. A refined dynamic temperature prediction model, taking into account the effect of foam, was set up. Simulation studies for a WWTP treating highly concentrated (manure) wastewater revealed that the foam layer had a significant effect on temperature prediction (3.8 ± 0.7 K over the year) and thus on the theoretical heat recovery potential (30% reduction when foam is not considered). Seasonal effects on the individual heat losses and heat gains were assessed. Additionally, the effects of the critical basin temperature above which heat is recovered, foam thickness, surface evaporation rate reduction and the non-absorbed solar radiation on the theoretical heat recovery potential were evaluated. Copyright © 2016 Elsevier Ltd. All rights reserved.

Application of optical action potentials in human induced pluripotent stem cells-derived cardiomyocytes to predict drug-induced cardiac arrhythmias.

Science.gov (United States)

Lu, H R; Hortigon-Vinagre, M P; Zamora, V; Kopljar, I; De Bondt, A; Gallacher, D J; Smith, G

2017-09-01

Human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs) are emerging as new and human-relevant source in vitro model for cardiac safety assessment that allow us to investigate a set of 20 reference drugs for predicting cardiac arrhythmogenic liability using optical action potential (oAP) assay. Here, we describe our examination of the oAP measurement using a voltage sensitive dye (Di-4-ANEPPS) to predict adverse compound effects using hiPS-CMs and 20 cardioactive reference compounds. Fluorescence signals were digitized at 10kHz and the records subsequently analyzed off-line. Cells were exposed to 30min incubation to vehicle or compound (n=5/dose, 4 doses/compound) that were blinded to the investigating laboratory. Action potential parameters were measured, including rise time (T rise ) of the optical action potential duration (oAPD). Significant effects on oAPD were sensitively detected with 11 QT-prolonging drugs, while oAPD shortening was observed with I Ca -antagonists, I Kr -activator or ATP-sensitive K + channel (K ATP )-opener. Additionally, the assay detected varied effects induced by 6 different sodium channel blockers. The detection threshold for these drug effects was at or below the published values of free effective therapeutic plasma levels or effective concentrations by other studies. The results of this blinded study indicate that OAP is a sensitive method to accurately detect drug-induced effects (i.e., duration/QT-prolongation, shortening, beat rate, and incidence of early after depolarizations) in hiPS-CMs; therefore, this technique will potentially be useful in predicting drug-induced arrhythmogenic liabilities in early de-risking within the drug discovery phase. Copyright © 2017 Elsevier Inc. All rights reserved.

A highly accurate predictive-adaptive method for lithium-ion battery remaining discharge energy prediction in electric vehicle applications

International Nuclear Information System (INIS)

Liu, Guangming; Ouyang, Minggao; Lu, Languang; Li, Jianqiu; Hua, Jianfeng

2015-01-01

Highlights: • An energy prediction (EP) method is introduced for battery E RDE determination. • EP determines E RDE through coupled prediction of future states, parameters, and output. • The PAEP combines parameter adaptation and prediction to update model parameters. • The PAEP provides improved E RDE accuracy compared with DC and other EP methods. - Abstract: In order to estimate the remaining driving range (RDR) in electric vehicles, the remaining discharge energy (E RDE ) of the applied battery system needs to be precisely predicted. Strongly affected by the load profiles, the available E RDE varies largely in real-world applications and requires specific determination. However, the commonly-used direct calculation (DC) method might result in certain energy prediction errors by relating the E RDE directly to the current state of charge (SOC). To enhance the E RDE accuracy, this paper presents a battery energy prediction (EP) method based on the predictive control theory, in which a coupled prediction of future battery state variation, battery model parameter change, and voltage response, is implemented on the E RDE prediction horizon, and the E RDE is subsequently accumulated and real-timely optimized. Three EP approaches with different model parameter updating routes are introduced, and the predictive-adaptive energy prediction (PAEP) method combining the real-time parameter identification and the future parameter prediction offers the best potential. Based on a large-format lithium-ion battery, the performance of different E RDE calculation methods is compared under various dynamic profiles. Results imply that the EP methods provide much better accuracy than the traditional DC method, and the PAEP could reduce the E RDE error by more than 90% and guarantee the relative energy prediction error under 2%, proving as a proper choice in online E RDE prediction. The correlation of SOC estimation and E RDE calculation is then discussed to illustrate the

DNDO Report: Predicting Solar Modulation Potentials for Modeling Cosmic Background Radiation

Energy Technology Data Exchange (ETDEWEB)

Behne, Patrick Alan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-08-08

The modeling of the detectability of special nuclear material (SNM) at ports and border crossings requires accurate knowledge of the background radiation at those locations. Background radiation originates from two main sources, cosmic and terrestrial. Cosmic background is produced by high-energy galactic cosmic rays (GCR) entering the atmosphere and inducing a cascade of particles that eventually impact the earth’s surface. The solar modulation potential represents one of the primary inputs to modeling cosmic background radiation. Usosokin et al. formally define solar modulation potential as “the mean energy loss [per unit charge] of a cosmic ray particle inside the heliosphere…” Modulation potential, a function of elevation, location, and time, shares an inverse relationship with cosmic background radiation. As a result, radiation detector thresholds require adjustment to account for differing background levels, caused partly by differing solar modulations. Failure to do so can result in higher rates of false positives and failed detection of SNM for low and high levels of solar modulation potential, respectively. This study focuses on solar modulation’s time dependence, and seeks the best method to predict modulation for future dates using Python. To address the task of predicting future solar modulation, we utilize both non-linear least squares sinusoidal curve fitting and cubic spline interpolation. This material will be published in transactions of the ANS winter meeting of November, 2016.

Awareness of eSafety and Potential Online Dangers among Children and Teenagers

Science.gov (United States)

Zilka, Gila Cohen

2017-01-01

Aim/Purpose: Awareness of eSafety and potential online dangers for children and teenagers. Background: The study examined eSafety among children and teenagers from their own perspectives, through evaluations of their awareness level of eSafety and of potential online dangers. Methodology: This is a mixed-method study with both quantitative and…

Legal framework for e-research : realising the potential

CERN Document Server

2008-01-01

Legal Framework for e-Research: Realising the Potential provides an overview of key legal issues facing e-Research. Part One of this book considers the broader prospect and context of what e-Research will allow. Part Two looks more closely at the role law will play in the e-Research environment. Part Three focuses on the key issues of data exchange and data management highlighting important legal issues. Part Four reflects on the changing nature of Scholarly Communications while Part Five looks at the fundamental role of agreements for collaborative endeavour (contracts) in structuring collaboration and calls for greater consideration of way we can streamline the process. Part Six examines the role and operation of privacy law in an e-Research world while Part Seven posits a new approach to commercialisation that embraces the paradigm of open innovation. Part Eight looks at the international legal implications for e-Research and Part Nine considers the national survey we undertook on e-Research, collaborative...

Oxidation potential (E/sub h/) and pH control during experimentation

International Nuclear Information System (INIS)

Seitz, M.G.

1982-01-01

Purpose of this statement is to introduce the subject of oxidation potential, E/sub h/, and to discuss its control in experiments. After the concept of E/sub h/ is reviewed, the range of oxidation potentials expected to be associated with a repository for high level nuclear waste will be addressed. Finally, three laboratory methods of controlling E/sub h/ will be described, along with some perspective that has been derived from experience given for each method

[Prediction of potential geographic distribution of Lyme disease in Qinghai province with Maximum Entropy model].

Science.gov (United States)

Zhang, Lin; Hou, Xuexia; Liu, Huixin; Liu, Wei; Wan, Kanglin; Hao, Qin

2016-01-01

To predict the potential geographic distribution of Lyme disease in Qinghai by using Maximum Entropy model (MaxEnt). The sero-diagnosis data of Lyme disease in 6 counties (Huzhu, Zeku, Tongde, Datong, Qilian and Xunhua) and the environmental and anthropogenic data including altitude, human footprint, normalized difference vegetation index (NDVI) and temperature in Qinghai province since 1990 were collected. By using the data of Huzhu Zeku and Tongde, the prediction of potential distribution of Lyme disease in Qinghai was conducted with MaxEnt. The prediction results were compared with the human sero-prevalence of Lyme disease in Datong, Qilian and Xunhua counties in Qinghai. Three hot spots of Lyme disease were predicted in Qinghai, which were all in the east forest areas. Furthermore, the NDVI showed the most important role in the model prediction, followed by human footprint. Datong, Qilian and Xunhua counties were all in eastern Qinghai. Xunhua was in hot spot areaⅡ, Datong was close to the north of hot spot area Ⅲ, while Qilian with lowest sero-prevalence of Lyme disease was not in the hot spot areas. The data were well modeled in MaxEnt (Area Under Curve=0.980). The actual distribution of Lyme disease in Qinghai was in consistent with the results of the model prediction. MaxEnt could be used in predicting the potential distribution patterns of Lyme disease. The distribution of vegetation and the range and intensity of human activity might be related with Lyme disease distribution.

Development of a prediction model for the cost saving potentials in implementing the building energy efficiency rating certification

International Nuclear Information System (INIS)

Jeong, Jaewook; Hong, Taehoon; Ji, Changyoon; Kim, Jimin; Lee, Minhyun; Jeong, Kwangbok; Koo, Choongwan

2017-01-01

Highlights: • This study evaluates the building energy efficiency rating (BEER) certification. • Prediction model was developed for cost saving potentials by the BEER certification. • Prediction model was developed using LCC analysis, ROV, and Monte Carlo simulation. • Cost saving potential was predicted to be 2.78–3.77% of the construction cost. • Cost saving potential can be used for estimating the investment value of BEER. - Abstract: Building energy efficiency rating (BEER) certification is an energy performance certificates (EPCs) in South Korea. It is critical to examine the cost saving potentials of the BEER-certification in advance. This study aimed to develop a prediction model for the cost saving potentials in implementing the BEER-certification, in which the cost saving potentials included the energy cost savings of the BEER-certification and the relevant CO_2 emissions reduction as well as the additional construction cost for the BEER-certification. The prediction model was developed by using data mining, life cycle cost analysis, real option valuation, and Monte Carlo simulation. The database were established with 437 multi-family housing complexes (MFHCs), including 116 BEER-certified MFHCs and 321 non-certified MFHCs. The case study was conducted to validate the developed prediction model using 321 non-certified MFHCs, which considered 20-year life cycle. As a result, compared to the additional construction cost, the average cost saving potentials of the 1st-BEER-certified MFHCs in Groups 1, 2, and 3 were predicted to be 3.77%, 2.78%, and 2.87%, respectively. The cost saving potentials can be used as a guideline for the additional construction cost of the BEER-certification in the early design phase.

Two Years of ePrescription in Slovenia - Applications and Potentials.

Science.gov (United States)

Stanimirovic, Dalibor; Savic, Dusan

2018-01-01

ePrescription is one of the most successful eHealth solutions in Slovenia. Since its national roll-out in early 2016, the quality of its operations has been constantly improving, and the number of users has been growing ever since to reach today's 90% of all healthcare providers. ePrescription facilitates more transparent and safer prescribing of medications, an overview of possible medication interactions, and reduction of administrative and opportunity costs. This paper initially explores the current state of ePrescription in Slovenia and different aspects of its application. Based on the research findings, the paper finally outlines potentials of ePrescription, which could be transformed into tangible benefits with particular implications for healthcare system. The research is based on focus group methodology. Structured discussions were conducted with eminent experts currently in charge of ePrescription (and other eHealth solutions) development and implementation in Slovenia. Research results imply that certain application aspects are relatively easy to define and evaluate, while the overall potentials of ePrescription are difficult to determine in many cases, and relatively unexplored in terms of their implications and operational feasibility.

Potential for Drug Abuse: the Predictive Role of Parenting Styles, Stress and Type D Personality

Directory of Open Access Journals (Sweden)

mahin soheili

2015-06-01

Full Text Available Objective: This study was an attempt to predict potential for drug abuse on the basis of three predictors of parenting style, stress and type D personality. Method: In this descriptive-correlational study, 200 students (100 males and 100 females of Islamic Azad University of Karaj were selected by convenience sampling. For data collection, perceived parenting styles questionnaire, perceived stress scale, type D personality scale, and addiction potential scale were used. Results: The results showed that rejecting/neglecting parenting style and emotional warmth were positively and negatively correlated with addiction potential, respectively. Conclusion: The child-parent relationship and also the relationship between stress and type D personality can be considered as predictive factors in addiction potential.

Prediction of Potential Fishing Zones for Skipjack Tuna During the Northwest Monsoon Using Remotely Sensed Satellite Data

Directory of Open Access Journals (Sweden)

Mukti Zainuddin

2017-06-01

Full Text Available One of economically important fish in the Bay of Bone is Skipjack tuna which their distribution and migration are influenced by surrounding environment.  This study aims to investigate the relationship between skipjack tuna and their environments, and to predict potential fishing zones (PFZs for the fish in the Bone Bay-Flores Sea using satellite-based oceanography and catch data. Generalized additive models (GAMs were used to assess the relationship. A generalized linear model(GLM constructed from GAMs was used for prediction. Monthly mean sea surface temperature (SST and chlorophyll-a during the northwest monsoon (December-January together with catch data were used for the year 2012-2013. We used the GAMs to assess the effect of the environment variables on skipjack tuna CPUE (catch per unit effort. The best GLM was selected to predict skipjack tuna abundance.  Results indicated that the highest CPUEs (fish/trip occurred in areas where SST and chlorophyll-a ranged from 29.5°-31.5°C and 0.15 - 0.25 mg m-3, respectively. The PFZs for skipjack were closely related to the spatial distribution of the optimum oceanographic conditions and these mainly developed in three locations, northern area of Bone Bay in December, in the middle area of the bay (4°-5.5°S and 120.5°-121.5°E during January and moved to the Flores Sea in February. The movement of skipjack concentration was consistent with the fishery data.  This suggests that the dynamics of the optimum oceanographic signatures provided a good indicator for predicting feeding grounds as hotspot areas for skipjack tuna in Bone Bay-Flores Sea during northwest monsoon.   Keywords:  skipjack tuna, potential fishing zones, satellite based-oceanographic data, Northwest monsoon

A predictive model for e-commerce consumer expenditure in EC countries

OpenAIRE

Kovačić, Zlatko

2004-01-01

Describing and predicting consumer expenditure on a country or cross-national level has a long tradition in theoretical and applied economics and econometrics. This paper is a first attempt in describing aggregate eCommerce consumer expenditure among European Commission (EC) countries. After brief introduction of possible theoretical models which explain the variation in eCommerce consumer expenditure among observed countries, a list of important predictors has been discussed. The results gen...

Fire behavior potential in central Saskatchewan under predicted climate change : summary document

International Nuclear Information System (INIS)

Parisien, M.; Hirsch, K.; Todd, B.; Flannigan, M.; Kafka, V.; Flynn, N.

2005-01-01

This study assesses fire danger and fire behaviour potential in central Saskatchewan using simulated climate scenarios produced by the Canadian Regional Climate Model (CRCM), including scenario analysis of base, double and triple level carbon dioxide in the atmosphere and uses available forest fuels to develop an absolute measure of fire behaviour. For each of these climate scenarios, the CRCM-generated weather was used as input variables into the Canadian Forest Fire Behavior Prediction (FBP) System. Fire behavior potential was quantified using head fire intensity, a measure of the fire's energy output because it can be related to fire behavior characteristics, suppression effectiveness, and fire effects. The report discusses the implications of fire behavior potential changes for fire and forest management. Preliminary results suggest a large increase in area burned in the study area by the end of the twenty-first century. Some of the possible fire management activities for long-term prediction include: pre-positioning of resources, preparedness planning, prioritization of fire and forest management activities and fire threat evaluation. 16 refs., 1 tab, 7 figs

Fuzzy-logic based learning style prediction in e-learning using web ...

Indian Academy of Sciences (India)

tion, especially in web environments and proposes to use Fuzzy rules to handle the uncertainty in .... learning in safe and supportive environment ... working of the proposed Fuzzy-logic based learning style prediction in e-learning. Section 4.

Clinical responses to ERK inhibition in BRAFV600E-mutant colorectal cancer predicted using a computational model.

Science.gov (United States)

Kirouac, Daniel C; Schaefer, Gabriele; Chan, Jocelyn; Merchant, Mark; Orr, Christine; Huang, Shih-Min A; Moffat, John; Liu, Lichuan; Gadkar, Kapil; Ramanujan, Saroja

2017-01-01

Approximately 10% of colorectal cancers harbor BRAF V600E mutations, which constitutively activate the MAPK signaling pathway. We sought to determine whether ERK inhibitor (GDC-0994)-containing regimens may be of clinical benefit to these patients based on data from in vitro (cell line) and in vivo (cell- and patient-derived xenograft) studies of cetuximab (EGFR), vemurafenib (BRAF), cobimetinib (MEK), and GDC-0994 (ERK) combinations. Preclinical data was used to develop a mechanism-based computational model linking cell surface receptor (EGFR) activation, the MAPK signaling pathway, and tumor growth. Clinical predictions of anti-tumor activity were enabled by the use of tumor response data from three Phase 1 clinical trials testing combinations of EGFR, BRAF, and MEK inhibitors. Simulated responses to GDC-0994 monotherapy (overall response rate = 17%) accurately predicted results from a Phase 1 clinical trial regarding the number of responding patients (2/18) and the distribution of tumor size changes ("waterfall plot"). Prospective simulations were then used to evaluate potential drug combinations and predictive biomarkers for increasing responsiveness to MEK/ERK inhibitors in these patients.

Interannual Variability, Global Teleconnection, and Potential Predictability Associated with the Asian Summer Monsoon

Science.gov (United States)

Lau, K. M.; Kim, K. M.; Li, J. Y.

2001-01-01

In this Chapter, aspects of global teleconnections associated with the interannual variability of the Asian summer monsoon (ASM) are discussed. The basic differences in the basic dynamics of the South Asian Monsoon and the East Asian monsoon, and their implications on global linkages are discussed. Two teleconnection modes linking ASM variability to summertime precipitation over the continental North America were identified. These modes link regional circulation and precipitation anomalies over East Asia and continental North America, via coupled atmosphere-ocean variations over the North Pacific. The first mode has a large zonally symmetrical component and appears to be associated with subtropical jetstream variability and the second mode with Rossby wave dispersion. Both modes possess strong sea surface temperature (SST) expressions in the North Pacific. Results show that the two teleconnection modes may have its origin in intrinsic modes of sea surface temperature variability in the extratropical oceans, which are forced in part by atmospheric variability and in part by air-sea interaction. The potential predictability of the ASM associated with SST variability in different ocean basins is explored using a new canonical ensemble correlation prediction scheme. It is found that SST anomalies in tropical Pacific, i.e., El Nino, is the most dominant forcing for the ASM, especially over the maritime continent and eastern Australia. SST anomalies in the India Ocean may trump the influence from El Nino in western Australia and western maritime continent. Both El Nino, and North Pacific SSTs contribute to monsoon precipitation anomalies over Japan, southern Korea, northern and central China. By optimizing SST variability signals from the world ocean basins using CEC, the overall predictability of ASM can be substantially improved.

Space potential, temperature, and density profile measurements on RENTOR

International Nuclear Information System (INIS)

Schoch, P.M.

1983-05-01

Radial profiles of the space potential, electron temperature, and density have been measured on RENTOR with a heavy-ion-beam probe. The potential profile has been compared to predictions from a stochastic magnetic field fluctuation theory, using the measured temperature and density profiles. The comparison shows strong qualitative agreement in that the potential is positive and the order of T/sub e//e. There is some quantitative disagreement in that the measured radial electric fields are somewhat smaller than the theoretical predictions. To facilitate this comparison, a detailed analysis of the possible errors has been completed

Tyramine Hydrochloride Based Label-Free System for Operating Various DNA Logic Gates and a DNA Caliper for Base Number Measurements.

Science.gov (United States)

Fan, Daoqing; Zhu, Xiaoqing; Dong, Shaojun; Wang, Erkang

2017-07-05

DNA is believed to be a promising candidate for molecular logic computation, and the fluorogenic/colorimetric substrates of G-quadruplex DNAzyme (G4zyme) are broadly used as label-free output reporters of DNA logic circuits. Herein, for the first time, tyramine-HCl (a fluorogenic substrate of G4zyme) is applied to DNA logic computation and a series of label-free DNA-input logic gates, including elementary AND, OR, and INHIBIT logic gates, as well as a two to one encoder, are constructed. Furthermore, a DNA caliper that can measure the base number of target DNA as low as three bases is also fabricated. This DNA caliper can also perform concatenated AND-AND logic computation to fulfil the requirements of sophisticated logic computing. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

An evaluation of the potential of Sentinel 1 for improving flash flood predictions via soil moisture–data assimilation

Directory of Open Access Journals (Sweden)

L. Cenci

2017-11-01

Full Text Available The assimilation of satellite-derived soil moisture estimates (soil moisture–data assimilation, SM–DA into hydrological models has the potential to reduce the uncertainty of streamflow simulations. The improved capacity to monitor the closeness to saturation of small catchments, such as those characterizing the Mediterranean region, can be exploited to enhance flash flood predictions. When compared to other microwave sensors that have been exploited for SM–DA in recent years (e.g. the Advanced SCATterometer – ASCAT, characterized by low spatial/high temporal resolution, the Sentinel 1 (S1 mission provides an excellent opportunity to monitor systematically soil moisture (SM at high spatial resolution and moderate temporal resolution. The aim of this research was thus to evaluate the impact of S1-based SM–DA for enhancing flash flood predictions of a hydrological model (Continuum that is currently exploited for civil protection applications in Italy. The analysis was carried out in a representative Mediterranean catchment prone to flash floods, located in north-western Italy, during the time period October 2014–February 2015. It provided some important findings: (i revealing the potential provided by S1-based SM–DA for improving discharge predictions, especially for higher flows; (ii suggesting a more appropriate pre-processing technique to be applied to S1 data before the assimilation; and (iii highlighting that even though high spatial resolution does provide an important contribution in a SM–DA system, the temporal resolution has the most crucial role. S1-derived SM maps are still a relatively new product and, to our knowledge, this is the first work published in an international journal dealing with their assimilation within a hydrological model to improve continuous streamflow simulations and flash flood predictions. Even though the reported results were obtained by analysing a relatively short time period, and thus should be

An evaluation of the potential of Sentinel 1 for improving flash flood predictions via soil moisture-data assimilation

Science.gov (United States)

Cenci, Luca; Pulvirenti, Luca; Boni, Giorgio; Chini, Marco; Matgen, Patrick; Gabellani, Simone; Squicciarino, Giuseppe; Pierdicca, Nazzareno

2017-11-01

The assimilation of satellite-derived soil moisture estimates (soil moisture-data assimilation, SM-DA) into hydrological models has the potential to reduce the uncertainty of streamflow simulations. The improved capacity to monitor the closeness to saturation of small catchments, such as those characterizing the Mediterranean region, can be exploited to enhance flash flood predictions. When compared to other microwave sensors that have been exploited for SM-DA in recent years (e.g. the Advanced SCATterometer - ASCAT), characterized by low spatial/high temporal resolution, the Sentinel 1 (S1) mission provides an excellent opportunity to monitor systematically soil moisture (SM) at high spatial resolution and moderate temporal resolution. The aim of this research was thus to evaluate the impact of S1-based SM-DA for enhancing flash flood predictions of a hydrological model (Continuum) that is currently exploited for civil protection applications in Italy. The analysis was carried out in a representative Mediterranean catchment prone to flash floods, located in north-western Italy, during the time period October 2014-February 2015. It provided some important findings: (i) revealing the potential provided by S1-based SM-DA for improving discharge predictions, especially for higher flows; (ii) suggesting a more appropriate pre-processing technique to be applied to S1 data before the assimilation; and (iii) highlighting that even though high spatial resolution does provide an important contribution in a SM-DA system, the temporal resolution has the most crucial role. S1-derived SM maps are still a relatively new product and, to our knowledge, this is the first work published in an international journal dealing with their assimilation within a hydrological model to improve continuous streamflow simulations and flash flood predictions. Even though the reported results were obtained by analysing a relatively short time period, and thus should be supported by further

Predicting Child Abuse Potential: An Empirical Investigation of Two Theoretical Frameworks

Science.gov (United States)

Begle, Angela Moreland; Dumas, Jean E.; Hanson, Rochelle F.

2010-01-01

This study investigated two theoretical risk models predicting child maltreatment potential: (a) Belsky's (1993) developmental-ecological model and (b) the cumulative risk model in a sample of 610 caregivers (49% African American, 46% European American; 53% single) with a child between 3 and 6 years old. Results extend the literature by using a…

Prediction and identification of potential immunodominant epitopes in glycoproteins B, C, E, G, and I of herpes simplex virus type 2.

Science.gov (United States)

Pan, Mingjie; Wang, Xingsheng; Liao, Jianmin; Yin, Dengke; Li, Suqin; Pan, Ying; Wang, Yao; Xie, Guangyan; Zhang, Shumin; Li, Yuexi

2012-01-01

Twenty B candidate epitopes of glycoproteins B (gB2), C (gC2), E (gE2), G (gG2), and I (gI2) of herpes simplex virus type 2 (HSV-2) were predicted using DNAstar, Biosun, and Antheprot methods combined with the polynomial method. Subsequently, the biological functions of the peptides were tested via experiments in vitro. Among the 20 epitope peptides, 17 could react with the antisera to the corresponding parent proteins in the EIA tests. In particular, five peptides, namely, gB2(466-473) (EQDRKPRN), gC2(216-223) (GRTDRPSA), gE2(483-491) (DPPERPDSP), gG2(572-579) (EPPDDDDS), and gI2(286-295) (CRRRYRRPRG) had strong reaction with the antisera. All conjugates of the five peptides with the carrier protein BSA could stimulate mice into producing antibodies. The antisera to these peptides reacted strongly with the corresponding parent glycoproteins during the Western Blot tests, and the peptides reacted strongly with the antibodies against the parent glycoproteins during the EIA tests. The antisera against the five peptides could neutralize HSV-2 infection in vitro, which has not been reported until now. These results suggest that the immunodominant epitopes screened using software algorithms may be used for virus diagnosis and vaccine design against HSV-2.

Prediction and Identification of Potential Immunodominant Epitopes in Glycoproteins B, C, E, G, and I of Herpes Simplex Virus Type 2

Directory of Open Access Journals (Sweden)

Mingjie Pan

2012-01-01

Full Text Available Twenty B candidate epitopes of glycoproteins B (gB2, C (gC2, E (gE2, G (gG2, and I (gI2 of herpes simplex virus type 2 (HSV-2 were predicted using DNAstar, Biosun, and Antheprot methods combined with the polynomial method. Subsequently, the biological functions of the peptides were tested via experiments in vitro. Among the 20 epitope peptides, 17 could react with the antisera to the corresponding parent proteins in the EIA tests. In particular, five peptides, namely, gB2466–473 (EQDRKPRN, gC2216–223 (GRTDRPSA, gE2483–491 (DPPERPDSP, gG2572–579 (EPPDDDDS, and gI2286-295 (CRRRYRRPRG had strong reaction with the antisera. All conjugates of the five peptides with the carrier protein BSA could stimulate mice into producing antibodies. The antisera to these peptides reacted strongly with the corresponding parent glycoproteins during the Western Blot tests, and the peptides reacted strongly with the antibodies against the parent glycoproteins during the EIA tests. The antisera against the five peptides could neutralize HSV-2 infection in vitro, which has not been reported until now. These results suggest that the immunodominant epitopes screened using software algorithms may be used for virus diagnosis and vaccine design against HSV-2.

Accuracy of professional sports drafts in predicting career potential.

Science.gov (United States)

Koz, D; Fraser-Thomas, J; Baker, J

2012-08-01

The forecasting of talented players is a crucial aspect of building a successful sports franchise and professional sports invest significant resources in making player choices in sport drafts. The current study examined the relationship between career performance (i.e. games played) and draft round for the National Football League, National Hockey League, National Basketball League, and Major League Baseball for players drafted from 1980 to 1989 (n = 4874) against the assumption of a linear relationship between performance and draft round (i.e. that players with the most potential will be selected before players of lower potential). A two-step analysis revealed significant differences in games played across draft rounds (step 1) and a significant negative relationship between draft round and games played (step 2); however, the amount of variance accounted for was relatively low (less than 17%). Results highlight the challenges of accurately evaluating amateur talent. © 2011 John Wiley & Sons A/S.

Inflationary predictions of double-well, Coleman-Weinberg, and hilltop potentials with non-minimal coupling

Science.gov (United States)

Bostan, Nilay; Güleryüz, Ömer; Nefer Şenoğuz, Vedat

2018-05-01

We discuss how the non-minimal coupling ξphi2R between the inflaton and the Ricci scalar affects the predictions of single field inflation models where the inflaton has a non-zero vacuum expectation value (VEV) v after inflation. We show that, for inflaton values both above the VEV and below the VEV during inflation, under certain conditions the inflationary predictions become approximately the same as the predictions of the Starobinsky model. We then analyze inflation with double-well and Coleman-Weinberg potentials in detail, displaying the regions in the v-ξ plane for which the spectral index ns and the tensor-to-scalar ratio r values are compatible with the current observations. r is always larger than 0.002 in these regions. Finally, we consider the effect of ξ on small field inflation (hilltop) potentials.

Predicting continuance-findings from a longitudinal study of older adults using an eHealth newsletter.

Science.gov (United States)

Forquer, Heather A; Christensen, John L; Tan, Andy S L

2014-01-01

While eHealth technologies are promisingly efficient and widespread, theoretical frameworks capable of predicting long-term use, termed continuance, are lacking. Attempts to extend prominent information technology (IT) theories to the area of eHealth have been limited by small sample sizes, cross-sectional designs, self-reported as opposed to actual use measures, and a focus on technology adoption rather than continuance. To address these gaps in the literature, this analysis includes empirical evidence of actual use of an eHealth technology over the course of one year. This large (n = 4,570) longitudinal study focuses on older adults, a population with many health needs and among whom eHealth use may be particularly important. With three measurement points over the course of a year, this study examined the effects of utilitarian and hedonic beliefs on the continued use of an eHealth newsletter using constructs from IT adoption and continuance theories. Additional analyses compared the relative strength of intentions compared to earlier use in predicting later use. Usage intention was strongly predicted by both hedonic beliefs and utilitarian beliefs. In addition, utilitarian beliefs had both direct effects on intention and indirect effects, mediated by hedonic beliefs. While intention predicted subsequent use, earlier use was a significantly stronger predictor of use than intention. These findings make a theoretical contribution to an emerging literature by shedding light on the complex interplay of reasoned action and automaticity in the context of eHealth continuance.

Carcinoma epidermóide do pulmão: Polissomia e amplificação do cromossoma 7 e do gene EGRF com forma wild type nos exões 19 e 21

Directory of Open Access Journals (Sweden)

Patrícia Couceiro

2010-05-01

Full Text Available Resumo: Objectivo: O receptor do factor de crescimento epidérmico (EGFR está sobreexpresso na maioria dos carcinomas do pulmão de não pequenas células (CPNPC e é um dos principais alvos específicos dos inibidores da tirosina cinase (TKI utilizados para o tratamento do CPNPC avançado. Apesar disto, há um considerável número de factores biológicos que também estão associados à resposta dos EGFR-TKIs. Este estudo teve como principal objectivo a pesquisa de mutações somáticas e amplificação do EGFR em casos de carcinoma epidermóide do pulmão. Material e métodos: Secções representativas de carcinoma epidermóide foram seleccionadas de 54 casos em que o tecido estava fixado em formal e incluído em parafina, sendo depois submetidos à construção de TMA. A determinação da expressão proteica do EGFR foi feita por imunoistoquímica (IHQ (Zymed, laboratórios. A hibridização in situ de fluorescência (FISH foi realizada com a sonda EGFR LSI / CEP 7 (Vysis; Abbott Molecular, EUA. O ADN genómico foi extraído de 48 casos, amplificado por reacção em cadeia da polimerase (PCR para pesquisa de mutações nos exões 19 (deleções e 21 (mutações pontuais. Todos os casos expressaram positividade para a citoqueratina de alto peso molecular e foi observada negatividade para CK7, CD56 e cromogranina. Resultados: A sobreexpressão proteica do EGFR foi identificada em 49 casos, pela aplicação do score de Hirsh/ Cappuzzo (2005. A pesquisa de alterações génicas no cromossoma 7 e do gene EGFR foram analisadas por FISH e de acordo com o método de Cappuzzo (2005, foi identificada alta polissomia em 31 casos e amplificação em 7 casos. Por electroforese capilar, foram detectadas no exão 19 do EGFR: deleções em heterozigotia em 3 dos 48 casos estudados e o exão 21 apresentou-se sempre na sua forma wild-type, quando estudado por enzimas de restrição. Conclusões: A detecção de deleções e mutações pontuais no EGFR

Predicting Tropical Cyclone Destructive Potential by Integrated Kinetic Energy According to the Powell/Reinhold Scale

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — A method of predicting the destructive capacity of a tropical cyclone based on a new Wind Destructive Potential (WDP) and Storm Surge Destructive Potential (SDP)...

Statistical prediction of biomethane potentials based on the composition of lignocellulosic biomass

DEFF Research Database (Denmark)

Thomsen, Sune Tjalfe; Spliid, Henrik; Østergård, Hanne

2014-01-01

Mixture models are introduced as a new and stronger methodology for statistical prediction of biomethane potentials (BPM) from lignocellulosic biomass compared to the linear regression models previously used. A large dataset from literature combined with our own data were analysed using canonical...

Spike-threshold adaptation predicted by membrane potential dynamics in vivo.

Directory of Open Access Journals (Sweden)

Bertrand Fontaine

2014-04-01

Full Text Available Neurons encode information in sequences of spikes, which are triggered when their membrane potential crosses a threshold. In vivo, the spiking threshold displays large variability suggesting that threshold dynamics have a profound influence on how the combined input of a neuron is encoded in the spiking. Threshold variability could be explained by adaptation to the membrane potential. However, it could also be the case that most threshold variability reflects noise and processes other than threshold adaptation. Here, we investigated threshold variation in auditory neurons responses recorded in vivo in barn owls. We found that spike threshold is quantitatively predicted by a model in which the threshold adapts, tracking the membrane potential at a short timescale. As a result, in these neurons, slow voltage fluctuations do not contribute to spiking because they are filtered by threshold adaptation. More importantly, these neurons can only respond to input spikes arriving together on a millisecond timescale. These results demonstrate that fast adaptation to the membrane potential captures spike threshold variability in vivo.

A grand canonical genetic algorithm for the prediction of multi-component phase diagrams and testing of empirical potentials

International Nuclear Information System (INIS)

Tipton, William W; Hennig, Richard G

2013-01-01

We present an evolutionary algorithm which predicts stable atomic structures and phase diagrams by searching the energy landscape of empirical and ab initio Hamiltonians. Composition and geometrical degrees of freedom may be varied simultaneously. We show that this method utilizes information from favorable local structure at one composition to predict that at others, achieving far greater efficiency of phase diagram prediction than a method which relies on sampling compositions individually. We detail this and a number of other efficiency-improving techniques implemented in the genetic algorithm for structure prediction code that is now publicly available. We test the efficiency of the software by searching the ternary Zr–Cu–Al system using an empirical embedded-atom model potential. In addition to testing the algorithm, we also evaluate the accuracy of the potential itself. We find that the potential stabilizes several correct ternary phases, while a few of the predicted ground states are unphysical. Our results suggest that genetic algorithm searches can be used to improve the methodology of empirical potential design. (paper)

A grand canonical genetic algorithm for the prediction of multi-component phase diagrams and testing of empirical potentials.

Science.gov (United States)

Tipton, William W; Hennig, Richard G

2013-12-11

We present an evolutionary algorithm which predicts stable atomic structures and phase diagrams by searching the energy landscape of empirical and ab initio Hamiltonians. Composition and geometrical degrees of freedom may be varied simultaneously. We show that this method utilizes information from favorable local structure at one composition to predict that at others, achieving far greater efficiency of phase diagram prediction than a method which relies on sampling compositions individually. We detail this and a number of other efficiency-improving techniques implemented in the genetic algorithm for structure prediction code that is now publicly available. We test the efficiency of the software by searching the ternary Zr-Cu-Al system using an empirical embedded-atom model potential. In addition to testing the algorithm, we also evaluate the accuracy of the potential itself. We find that the potential stabilizes several correct ternary phases, while a few of the predicted ground states are unphysical. Our results suggest that genetic algorithm searches can be used to improve the methodology of empirical potential design.

Predicting wildfire ignitions, escapes, and large fire activity using Predictive Service’s 7-Day Fire Potential Outlook in the western USA

Science.gov (United States)

Karin L. Riley; Crystal Stonesifer; Haiganoush Preisler; Dave Calkin

2014-01-01

Can fire potential forecasts assist with pre-positioning of fire suppression resources, which could result in a cost savings to the United States government? Here, we present a preliminary assessment of the 7-Day Fire Potential Outlook forecasts made by the Predictive Services program. We utilized historical fire occurrence data and archived forecasts to assess how...

Integrated Computational Solution for Predicting Skin Sensitization Potential of Molecules.

Directory of Open Access Journals (Sweden)

Konda Leela Sarath Kumar

Full Text Available Skin sensitization forms a major toxicological endpoint for dermatology and cosmetic products. Recent ban on animal testing for cosmetics demands for alternative methods. We developed an integrated computational solution (SkinSense that offers a robust solution and addresses the limitations of existing computational tools i.e. high false positive rate and/or limited coverage.The key components of our solution include: QSAR models selected from a combinatorial set, similarity information and literature-derived sub-structure patterns of known skin protein reactive groups. Its prediction performance on a challenge set of molecules showed accuracy = 75.32%, CCR = 74.36%, sensitivity = 70.00% and specificity = 78.72%, which is better than several existing tools including VEGA (accuracy = 45.00% and CCR = 54.17% with 'High' reliability scoring, DEREK (accuracy = 72.73% and CCR = 71.44% and TOPKAT (accuracy = 60.00% and CCR = 61.67%. Although, TIMES-SS showed higher predictive power (accuracy = 90.00% and CCR = 92.86%, the coverage was very low (only 10 out of 77 molecules were predicted reliably.Owing to improved prediction performance and coverage, our solution can serve as a useful expert system towards Integrated Approaches to Testing and Assessment for skin sensitization. It would be invaluable to cosmetic/ dermatology industry for pre-screening their molecules, and reducing time, cost and animal testing.

Nucleon-nucleon interaction with quark exchanges and prediction to colour van der Waals potential

International Nuclear Information System (INIS)

Osman, A.

1985-11-01

The nucleon-nucleon interaction is considered by including the colour nucleon clusters. The nucleon-nucleon system is treated as a six-quark system. The obtained local potentials reduce the short-range repulsion. The resulted nucleon-nucleon potential by using a quark-quark potential well agrees with the central-force potentials. The phase shifts calculated by using these local potentials are in good agreement with those obtained from other methods. Introducing the quark-quark potential in the nucleon-nucleon interaction, leads to a colour van der Waals potential very strong compared with that predicted by experiments. (author)

Screening of transgenic proteins expressed in transgenic food crops for the presence of short amino acid sequences identical to potential, IgE – binding linear epitopes of allergens

Directory of Open Access Journals (Sweden)

Peijnenburg Ad ACM

2002-12-01

Full Text Available Abstract Background Transgenic proteins expressed by genetically modified food crops are evaluated for their potential allergenic properties prior to marketing, among others by identification of short identical amino acid sequences that occur both in the transgenic protein and allergenic proteins. A strategy is proposed, in which the positive outcomes of the sequence comparison with a minimal length of six amino acids are further screened for the presence of potential linear IgE-epitopes. This double track approach involves the use of literature data on IgE-epitopes and an antigenicity prediction algorithm. Results Thirty-three transgenic proteins have been screened for identities of at least six contiguous amino acids shared with allergenic proteins. Twenty-two transgenic proteins showed positive results of six- or seven-contiguous amino acids length. Only a limited number of identical stretches shared by transgenic proteins (papaya ringspot virus coat protein, acetolactate synthase GH50, and glyphosate oxidoreductase and allergenic proteins could be identified as (part of potential linear epitopes. Conclusion Many transgenic proteins have identical stretches of six or seven amino acids in common with allergenic proteins. Most identical stretches are likely to be false positives. As shown in this study, identical stretches can be further screened for relevance by comparison with linear IgE-binding epitopes described in literature. In the absence of literature data on epitopes, antigenicity prediction by computer aids to select potential antibody binding sites that will need verification of IgE binding by sera binding tests. Finally, the positive outcomes of this approach warrant further clinical testing for potential allergenicity.

miRNA signatures can predict acute liver failure in hepatitis E infected pregnant females

Directory of Open Access Journals (Sweden)

Nirupma Trehanpati

2017-04-01

Full Text Available Background: Acute viral hepatitis E (AVH-E can often result in acute liver failure (ALF during pregnancy. microRNAs serve as mediators in drug induced liver failure. We investigated their role as a biomarker in predicting ALF due to HEV (ALF-E. Methods: We performed next generation sequencing and subsequent validation studies in PBMCs of pregnant (P self limiting AVH-E, ALF due to HEV (ALF-E and compared with AVH-E in non-pregnant (NP females and healthy controls. Findings: Eleven microRNAs were significantly expressed in response to HEV infection; importantly, miR- 431, 654, 1468 and 4435, were distinctly expressed in pregnant self-limiting AVH-E and healthy females (p = 0.0005, but not in ALF-E. Sixteen exclusive microRNAs differentiated ALF-E from self limiting AVH-E in pregnant females. miR-450b which affects cellular proliferation and metabolic processes through RNF20 and SECB was predominanlty upregulated and correlated with poor outcome (ROC 0.958, p = 0.001. Interpretation: Our results reveal that a specific microRNA profile can predict fatality in ALF-E in pregnancy. These microRNAs could be exploited as prognostic biomarkers and help in the development of new therapeutic interventions. Keywords: Health sciences, Virology

Reduced model prediction of electron temperature profiles in microtearing-dominated National Spherical Torus eXperiment plasmas

Energy Technology Data Exchange (ETDEWEB)

Kaye, S. M., E-mail: skaye@pppl.gov; Guttenfelder, W.; Bell, R. E.; Gerhardt, S. P.; LeBlanc, B. P.; Maingi, R. [Princeton Plasma Physics Laboratory, Princeton University, Princeton, New Jersey 08543 (United States)

2014-08-15

A representative H-mode discharge from the National Spherical Torus eXperiment is studied in detail to utilize it as a basis for a time-evolving prediction of the electron temperature profile using an appropriate reduced transport model. The time evolution of characteristic plasma variables such as β{sub e}, ν{sub e}{sup ∗}, the MHD α parameter, and the gradient scale lengths of T{sub e}, T{sub i}, and n{sub e} were examined as a prelude to performing linear gyrokinetic calculations to determine the fastest growing micro instability at various times and locations throughout the discharge. The inferences from the parameter evolutions and the linear stability calculations were consistent. Early in the discharge, when β{sub e} and ν{sub e}{sup ∗} were relatively low, ballooning parity modes were dominant. As time progressed and both β{sub e} and ν{sub e}{sup ∗} increased, microtearing became the dominant low-k{sub θ} mode, especially in the outer half of the plasma. There are instances in time and radius, however, where other modes, at higher-k{sub θ}, may, in addition to microtearing, be important for driving electron transport. Given these results, the Rebut-Lallia-Watkins (RLW) electron thermal diffusivity model, which is based on microtearing-induced transport, was used to predict the time-evolving electron temperature across most of the profile. The results indicate that RLW does a good job of predicting T{sub e} for times and locations where microtearing was determined to be important, but not as well when microtearing was predicted to be stable or subdominant.

RXP-E: a connexin43-binding peptide that prevents action potential propagation block

DEFF Research Database (Denmark)

Lewandowski, Rebecca; Procida, Kristina; Vaidyanathan, Ravi

2008-01-01

. Separately, RXP-E was concatenated to a cytoplasmic transduction peptide (CTP) for cytoplasmic translocation (CTP-RXP-E). The effect of RXP-E on action potential propagation was assessed by high-resolution optical mapping in monolayers of neonatal rat ventricular myocytes, containing approximately 20......% of randomly distributed myofibroblasts. In contrast to control experiments, when heptanol (2 mmol/L) was added to the superfusate of monolayers loaded with CTP-RXP-E, action potential propagation was maintained, albeit at a slower velocity. Similarly, intracellular acidification (pH(i) 6.2) caused a loss...... of action potential propagation in control monolayers; however, propagation was maintained in CTP-RXP-E-treated cells, although at a slower rate. Patch-clamp experiments revealed that RXP-E did not prevent heptanol-induced block of sodium currents, nor did it alter voltage dependence or amplitude of Kir2...

Brain-behavioral adaptability predicts response to cognitive behavioral therapy for emotional disorders: A person-centered event-related potential study.

Science.gov (United States)

Stange, Jonathan P; MacNamara, Annmarie; Kennedy, Amy E; Hajcak, Greg; Phan, K Luan; Klumpp, Heide

2017-06-23

Single-trial-level analyses afford the ability to link neural indices of elaborative attention (such as the late positive potential [LPP], an event-related potential) with downstream markers of attentional processing (such as reaction time [RT]). This approach can provide useful information about individual differences in information processing, such as the ability to adapt behavior based on attentional demands ("brain-behavioral adaptability"). Anxiety and depression are associated with maladaptive information processing implicating aberrant cognition-emotion interactions, but whether brain-behavioral adaptability predicts response to psychotherapy is not known. We used a novel person-centered, trial-level analysis approach to link neural indices of stimulus processing to behavioral responses and to predict treatment outcome. Thirty-nine patients with anxiety and/or depression received 12 weeks of cognitive behavioral therapy (CBT). Prior to treatment, patients performed a speeded reaction-time task involving briefly-presented pairs of aversive and neutral pictures while electroencephalography was recorded. Multilevel modeling demonstrated that larger LPPs predicted slower responses on subsequent trials, suggesting that increased attention to the task-irrelevant nature of pictures interfered with reaction time on subsequent trials. Whereas using LPP and RT averages did not distinguish CBT responders from nonresponders, in trial-level analyses individuals who demonstrated greater ability to benefit behaviorally (i.e., faster RT) from smaller LPPs on the previous trial (greater brain-behavioral adaptability) were more likely to respond to treatment and showed greater improvements in depressive symptoms. These results highlight the utility of trial-level analyses to elucidate variability in within-subjects, brain-behavioral attentional coupling in the context of emotion processing, in predicting response to CBT for emotional disorders. Copyright © 2017 Elsevier Ltd

Assessment of structures and stabilities of defect clusters and surface energies predicted by nine interatomic potentials for UO{sub 2}

Energy Technology Data Exchange (ETDEWEB)

Taller, Stephen A. [School of Nuclear Engineering, Purdue University, West Lafayette, IN 47907 (United States); Bai, Xian-Ming, E-mail: xianming.bai@inl.gov [Fuels Modeling and Simulation Department, Idaho National Laboratory, Idaho Falls, ID 83415 (United States)

2013-11-15

The irradiation in nuclear reactors creates many point defects and defect clusters in uranium dioxide (UO{sub 2}) and their evolution severely degrades the thermal and mechanical properties of the nuclear fuels. Previously many empirical interatomic potentials have been developed for modeling defect production and evolution in UO{sub 2}. However, the properties of defect clusters and extended defects are usually not fitted into these potentials. In this work nine interatomic potentials for UO{sub 2} are examined by using molecular statics and molecular dynamics to assess their applicability in predicting the properties of various types of defect clusters in UO{sub 2}. The binding energies and structures for these defect clusters have been evaluated for each potential. In addition, the surface energies of voids of different radii and (1 1 0) flat surfaces predicted by these potentials are also evaluated. It is found that both good agreement and significant discrepancies exist for these potentials in predicting these properties. For oxygen interstitial clusters, these potentials predict significantly different defect cluster structures and stabilities; For defect clusters consisting of both uranium and oxygen defects, the prediction is in better agreement; The surface energies predicted by these potentials have significant discrepancies, and some of them are much higher than the experimentally measured values. The results from this work can provide insight on interpreting the outcome of atomistic modeling of defect production using these potentials and may provide guidelines for choosing appropriate potential models to study problems of interest in UO{sub 2}.

Nurses' Assessment of Rehabilitation Potential and Prediction of Functional Status at Discharge from Inpatient Rehabilitation

Science.gov (United States)

Myers, Jamie S.; Grigsby, Jim; Teel, Cynthia S.; Kramer, Andrew M.

2009-01-01

The goals of this study were to evaluate the accuracy of nurses' predictions of rehabilitation potential in older adults admitted to inpatient rehabilitation facilities and to ascertain whether the addition of a measure of executive cognitive function would enhance predictive accuracy. Secondary analysis was performed on prospective data collected…

Predicting abuse potential of stimulants and other dopaminergic drugs: overview and recommendations.

Science.gov (United States)

Huskinson, Sally L; Naylor, Jennifer E; Rowlett, James K; Freeman, Kevin B

2014-12-01

Examination of a drug's abuse potential at multiple levels of analysis (molecular/cellular action, whole-organism behavior, epidemiological data) is an essential component to regulating controlled substances under the Controlled Substances Act (CSA). We reviewed studies that examined several central nervous system (CNS) stimulants, focusing on those with primarily dopaminergic actions, in drug self-administration, drug discrimination, and physical dependence. For drug self-administration and drug discrimination, we distinguished between experiments conducted with rats and nonhuman primates (NHP) to highlight the common and unique attributes of each model in the assessment of abuse potential. Our review of drug self-administration studies suggests that this procedure is important in predicting abuse potential of dopaminergic compounds, but there were many false positives. We recommended that tests to determine how reinforcing a drug is relative to a known drug of abuse may be more predictive of abuse potential than tests that yield a binary, yes-or-no classification. Several false positives also occurred with drug discrimination. With this procedure, we recommended that future research follow a standard decision-tree approach that may require examining the drug being tested for abuse potential as the training stimulus. This approach would also allow several known drugs of abuse to be tested for substitution, and this may reduce false positives. Finally, we reviewed evidence of physical dependence with stimulants and discussed the feasibility of modeling these phenomena in nonhuman animals in a rational and practical fashion. This article is part of the Special Issue entitled 'CNS Stimulants'. Copyright © 2014 Elsevier Ltd. All rights reserved.

Analyzing power in pp scattering at low energies: the Paris potential predictions

International Nuclear Information System (INIS)

Cote, J.; Pires, P.; Tourreil, R. de; Lacombe, M.; Loiseau, B.; Vinh Mau, R.

1979-12-01

Predictions of the Paris potential for the analyzing power in pp scattering at low energies are compared with recent high precision measurements at 6.14MeV and earlier measurements at 10 and 16MeV. Phase shift values are also presented and discussed in view of previous analyses

Prediction of Reduction Potentials of Copper Proteins with Continuum Electrostatics and Density Functional Theory.

Science.gov (United States)

Fowler, Nicholas J; Blanford, Christopher F; Warwicker, Jim; de Visser, Sam P

2017-11-02

Blue copper proteins, such as azurin, show dramatic changes in Cu 2+ /Cu + reduction potential upon mutation over the full physiological range. Hence, they have important functions in electron transfer and oxidation chemistry and have applications in industrial biotechnology. The details of what determines these reduction potential changes upon mutation are still unclear. Moreover, it has been difficult to model and predict the reduction potential of azurin mutants and currently no unique procedure or workflow pattern exists. Furthermore, high-level computational methods can be accurate but are too time consuming for practical use. In this work, a novel approach for calculating reduction potentials of azurin mutants is shown, based on a combination of continuum electrostatics, density functional theory and empirical hydrophobicity factors. Our method accurately reproduces experimental reduction potential changes of 30 mutants with respect to wildtype within experimental error and highlights the factors contributing to the reduction potential change. Finally, reduction potentials are predicted for a series of 124 new mutants that have not yet been investigated experimentally. Several mutants are identified that are located well over 10 Å from the copper center that change the reduction potential by more than 85 mV. The work shows that secondary coordination sphere mutations mostly lead to long-range electrostatic changes and hence can be modeled accurately with continuum electrostatics. © 2017 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Diffusion of E centers in germanium predicted using GGA+U approach

KAUST Repository

Tahini, H. A.; Bracht, H.; Chroneos, Alexander; Grimes, R. W.; Schwingenschlö gl, Udo

2011-01-01

Density functional theory calculations (based on GGA+U approach) are used to investigate the formation and diffusion of donor-vacancy pairs (E centers) in germanium. We conclude that depending upon the Fermi energy,E centers that incorporate for phosphorous and arsenic can form in their neutral, singly negatively or doubly negatively charged states whereas with antimony only the neutral or doubly negatively charged states are predicted. The activation energies of diffusion are compared with recent experimental work and support the idea that smaller donor atoms exhibit higher diffusionactivation energies.

Diffusion of E centers in germanium predicted using GGA+U approach

KAUST Repository

Tahini, H. A.

2011-08-17

Density functional theory calculations (based on GGA+U approach) are used to investigate the formation and diffusion of donor-vacancy pairs (E centers) in germanium. We conclude that depending upon the Fermi energy,E centers that incorporate for phosphorous and arsenic can form in their neutral, singly negatively or doubly negatively charged states whereas with antimony only the neutral or doubly negatively charged states are predicted. The activation energies of diffusion are compared with recent experimental work and support the idea that smaller donor atoms exhibit higher diffusionactivation energies.

Characterization of the glass transition of water predicted by molecular dynamics simulations using nonpolarizable intermolecular potentials.

Science.gov (United States)

Kreck, Cara A; Mancera, Ricardo L

2014-02-20

Molecular dynamics simulations allow detailed study of the experimentally inaccessible liquid state of supercooled water below its homogeneous nucleation temperature and the characterization of the glass transition. Simple, nonpolarizable intermolecular potentials are commonly used in classical molecular dynamics simulations of water and aqueous systems due to their lower computational cost and their ability to reproduce a wide range of properties. Because the quality of these predictions varies between the potentials, the predicted glass transition of water is likely to be influenced by the choice of potential. We have thus conducted an extensive comparative investigation of various three-, four-, five-, and six-point water potentials in both the NPT and NVT ensembles. The T(g) predicted from NPT simulations is strongly correlated with the temperature of minimum density, whereas the maximum in the heat capacity plot corresponds to the minimum in the thermal expansion coefficient. In the NVT ensemble, these points are instead related to the maximum in the internal pressure and the minimum of its derivative, respectively. A detailed analysis of the hydrogen-bonding properties at the glass transition reveals that the extent of hydrogen-bonds lost upon the melting of the glassy state is related to the height of the heat capacity peak and varies between water potentials.

Chemical Utilisation of CO

Indian Academy of Sciences (India)

IAS Admin

Carbon Crisis – Need for Alternative Technologies. Carbon is a .... is determined by the extent of .... zymes, pH and other factors makes the enzymatic chemistry .... CH3OH using Al-based frustrated Lewis pairs and ammonia borane, J. Amer.

Predicting the potential distribution of the amphibian pathogen Batrachochytrium dendrobatidis in East and Southeast Asia.

Science.gov (United States)

Moriguchi, Sachiko; Tominaga, Atsushi; Irwin, Kelly J; Freake, Michael J; Suzuki, Kazutaka; Goka, Koichi

2015-04-08

Batrachochytrium dendrobatidis (Bd) is the pathogen responsible for chytridiomycosis, a disease that is associated with a worldwide amphibian population decline. In this study, we predicted the potential distribution of Bd in East and Southeast Asia based on limited occurrence data. Our goal was to design an effective survey area where efforts to detect the pathogen can be focused. We generated ecological niche models using the maximum-entropy approach, with alleviation of multicollinearity and spatial autocorrelation. We applied eigenvector-based spatial filters as independent variables, in addition to environmental variables, to resolve spatial autocorrelation, and compared the model's accuracy and the degree of spatial autocorrelation with those of a model estimated using only environmental variables. We were able to identify areas of high suitability for Bd with accuracy. Among the environmental variables, factors related to temperature and precipitation were more effective in predicting the potential distribution of Bd than factors related to land use and cover type. Our study successfully predicted the potential distribution of Bd in East and Southeast Asia. This information should now be used to prioritize survey areas and generate a surveillance program to detect the pathogen.

Exploring the Predictive Validity of the Susceptibility to Smoking Construct for Tobacco Cigarettes, Alternative Tobacco Products, and E-Cigarettes.

Science.gov (United States)

Cole, Adam G; Kennedy, Ryan David; Chaurasia, Ashok; Leatherdale, Scott T

2017-12-06

Within tobacco prevention programming, it is useful to identify youth that are at risk for experimenting with various tobacco products and e-cigarettes. The susceptibility to smoking construct is a simple method to identify never-smoking students that are less committed to remaining smoke-free. However, the predictive validity of this construct has not been tested within the Canadian context or for the use of other tobacco products and e-cigarettes. This study used a large, longitudinal sample of secondary school students that reported never using tobacco cigarettes and non-current use of alternative tobacco products or e-cigarettes at baseline in Ontario, Canada. The sensitivity, specificity, and positive and negative predictive values of the susceptibility construct for predicting tobacco cigarette, e-cigarette, cigarillo or little cigar, cigar, hookah, and smokeless tobacco use one and two years after baseline measurement were calculated. At baseline, 29.4% of the sample was susceptible to future tobacco product or e-cigarette use. The sensitivity of the construct ranged from 43.2% (smokeless tobacco) to 59.5% (tobacco cigarettes), the specificity ranged from 70.9% (smokeless tobacco) to 75.9% (tobacco cigarettes), and the positive predictive value ranged from 2.6% (smokeless tobacco) to 32.2% (tobacco cigarettes). Similar values were calculated for each measure of the susceptibility construct. A significant number of youth that did not currently use tobacco products or e-cigarettes at baseline reported using tobacco products and e-cigarettes over a two-year follow-up period. The predictive validity of the susceptibility construct was high and the construct can be used to predict other tobacco product and e-cigarette use among youth. This study presents the predictive validity of the susceptibility construct for the use of tobacco cigarettes among secondary school students in Ontario, Canada. It also presents a novel use of the susceptibility construct for

Impact of vegetation variability on potential predictability and skill of EC-Earth simulations

Energy Technology Data Exchange (ETDEWEB)

Weiss, Martina; Hurk, Bart van den; Haarsma, Reindert; Hazeleger, Wilco [Royal Netherlands Meteorological Institute (KNMI), De Bilt (Netherlands)

2012-12-15

Climate models often use a simplified and static representation of vegetation characteristics to determine fluxes of energy, momentum and water vapour between surface and lower atmosphere. In order to analyse the impact of short term variability in vegetation phenology, we use remotely-sensed leaf area index and albedo products to examine the role of vegetation in the coupled land-atmosphere system. Perfect model experiments are carried out to determine the impact of realistic temporal variability of vegetation on potential predictability of evaporation and temperature, as well as model skill of EC-Earth simulations. The length of the simulation period is hereby limited by the availability of satellite products to 2000-2010. While a realistic representation of vegetation positively influences the simulation of evaporation and its potential predictability, a positive impact on 2 m temperature is of smaller magnitude, regionally confined and more pronounced in climatically extreme years. (orig.)

Redox Potentials of Ligands and Complexes – a DFT Approach

African Journals Online (AJOL)

NICO

A review of the limited literature concerned with theoretical ways to predict experimentally measured redox potentials of ligands and ... electrode surface, over-potentials and high solvent resistance, ... A correlation coefficient of 0.969 in the linear relation with ... of E0' were performed in two steps, i.e. calculation of the free.

PINGU: PredIction of eNzyme catalytic residues usinG seqUence information.

Directory of Open Access Journals (Sweden)

Priyadarshini P Pai

Full Text Available Identification of catalytic residues can help unveil interesting attributes of enzyme function for various therapeutic and industrial applications. Based on their biochemical roles, the number of catalytic residues and sequence lengths of enzymes vary. This article describes a prediction approach (PINGU for such a scenario. It uses models trained using physicochemical properties and evolutionary information of 650 non-redundant enzymes (2136 catalytic residues in a support vector machines architecture. Independent testing on 200 non-redundant enzymes (683 catalytic residues in predefined prediction settings, i.e., with non-catalytic per catalytic residue ranging from 1 to 30, suggested that the prediction approach was highly sensitive and specific, i.e., 80% or above, over the incremental challenges. To learn more about the discriminatory power of PINGU in real scenarios, where the prediction challenge is variable and susceptible to high false positives, the best model from independent testing was used on 60 diverse enzymes. Results suggested that PINGU was able to identify most catalytic residues and non-catalytic residues properly with 80% or above accuracy, sensitivity and specificity. The effect of false positives on precision was addressed in this study by application of predicted ligand-binding residue information as a post-processing filter. An overall improvement of 20% in F-measure and 0.138 in Correlation Coefficient with 16% enhanced precision could be achieved. On account of its encouraging performance, PINGU is hoped to have eventual applications in boosting enzyme engineering and novel drug discovery.

The diagnostic value of specific IgE to Ara h 2 to predict peanut allergy in children is comparable to a validated and updated diagnostic prediction model.

Science.gov (United States)

Klemans, Rob J B; Otte, Dianne; Knol, Mirjam; Knol, Edward F; Meijer, Yolanda; Gmelig-Meyling, Frits H J; Bruijnzeel-Koomen, Carla A F M; Knulst, André C; Pasmans, Suzanne G M A

2013-01-01

A diagnostic prediction model for peanut allergy in children was recently published, using 6 predictors: sex, age, history, skin prick test, peanut specific immunoglobulin E (sIgE), and total IgE minus peanut sIgE. To validate this model and update it by adding allergic rhinitis, atopic dermatitis, and sIgE to peanut components Ara h 1, 2, 3, and 8 as candidate predictors. To develop a new model based only on sIgE to peanut components. Validation was performed by testing discrimination (diagnostic value) with an area under the receiver operating characteristic curve and calibration (agreement between predicted and observed frequencies of peanut allergy) with the Hosmer-Lemeshow test and a calibration plot. The performance of the (updated) models was similarly analyzed. Validation of the model in 100 patients showed good discrimination (88%) but poor calibration (P original model: sex, skin prick test, peanut sIgE, and total IgE minus sIgE. When building a model with sIgE to peanut components, Ara h 2 was the only predictor, with a discriminative ability of 90%. Cutoff values with 100% positive and negative predictive values could be calculated for both the updated model and sIgE to Ara h 2. In this way, the outcome of the food challenge could be predicted with 100% accuracy in 59% (updated model) and 50% (Ara h 2) of the patients. Discrimination of the validated model was good; however, calibration was poor. The discriminative ability of Ara h 2 was almost comparable to that of the updated model, containing 4 predictors. With both models, the need for peanut challenges could be reduced by at least 50%. Copyright © 2012 American Academy of Allergy, Asthma & Immunology. Published by Mosby, Inc. All rights reserved.

Probabilistic empirical prediction of seasonal climate: evaluation and potential applications

Science.gov (United States)

Dieppois, B.; Eden, J.; van Oldenborgh, G. J.

2017-12-01

Preparing for episodes with risks of anomalous weather a month to a year ahead is an important challenge for governments, non-governmental organisations, and private companies and is dependent on the availability of reliable forecasts. The majority of operational seasonal forecasts are made using process-based dynamical models, which are complex, computationally challenging and prone to biases. Empirical forecast approaches built on statistical models to represent physical processes offer an alternative to dynamical systems and can provide either a benchmark for comparison or independent supplementary forecasts. Here, we present a new evaluation of an established empirical system used to predict seasonal climate across the globe. Forecasts for surface air temperature, precipitation and sea level pressure are produced by the KNMI Probabilistic Empirical Prediction (K-PREP) system every month and disseminated via the KNMI Climate Explorer (climexp.knmi.nl). K-PREP is based on multiple linear regression and built on physical principles to the fullest extent with predictive information taken from the global CO2-equivalent concentration, large-scale modes of variability in the climate system and regional-scale information. K-PREP seasonal forecasts for the period 1981-2016 will be compared with corresponding dynamically generated forecasts produced by operational forecast systems. While there are many regions of the world where empirical forecast skill is extremely limited, several areas are identified where K-PREP offers comparable skill to dynamical systems. We discuss two key points in the future development and application of the K-PREP system: (a) the potential for K-PREP to provide a more useful basis for reference forecasts than those based on persistence or climatology, and (b) the added value of including K-PREP forecast information in multi-model forecast products, at least for known regions of good skill. We also discuss the potential development of

The Potential of Tropospheric Gradients for Regional Precipitation Prediction

Science.gov (United States)

Boisits, Janina; Möller, Gregor; Wittmann, Christoph; Weber, Robert

2017-04-01

Changes of temperature and humidity in the neutral atmosphere cause variations in tropospheric path delays and tropospheric gradients. By estimating zenith wet delays (ZWD) and gradients using a GNSS reference station network the obtained time series provide information about spatial and temporal variations of water vapour in the atmosphere. Thus, GNSS-based tropospheric parameters can contribute to the forecast of regional precipitation events. In a recently finalized master thesis at TU Wien the potential of tropospheric gradients for weather prediction was investigated. Therefore, ZWD and gradient time series at selected GNSS reference stations were compared to precipitation data over a period of six months (April to September 2014). The selected GNSS stations form two test areas within Austria. All required meteorological data was provided by the Central Institution for Meteorology and Geodynamics (ZAMG). Two characteristics in ZWD and gradient time series can be anticipated in case of an approaching weather front. First, an induced asymmetry in tropospheric delays results in both, an increased magnitude of the gradient and in gradients pointing towards the weather front. Second, an increase in ZWD reflects the increased water vapour concentration right before a precipitation event. To investigate these characteristics exemplary test events were processed. On the one hand, the sequence of the anticipated increase in ZWD at each GNSS station obtained by cross correlation of the time series indicates the direction of the approaching weather front. On the other hand, the corresponding peak in gradient time series allows the deduction of the direction of movement as well. To verify the results precipitation data from ZAMG was used. It can be deduced, that tropospheric gradients show high potential for predicting precipitation events. While ZWD time series rather indicate the orientation of the air mass boundary, gradients rather indicate the direction of movement

Towards prediction of heatwaves based on the complementary relationship between actual and potential evaporation - energy partitioning and hydrologic attributes

Science.gov (United States)

Or, D.; Aminzadeh, M.; Roderick, M. L.

2017-12-01

Prediction of extreme climate events such as heatwaves that are characterized by prolonged periods of high air temperatures (accompanied by low precipitation and high radiation) provides an opportunity to potentially mitigate the associated environmental, social and economic impacts. Vegetation may respond to these extreme conditions by reducing evaporative flux either due to soil water depletion or inability to meet the atmospheric evaporative demand (high canopy resistance). We implement a newly generalized Complementary Relationship (CR) for spatially heterogeneous land surfaces to predict the actual evaporation from drying landscapes covered by different vegetation types (i.e., grassland and forest). A strong correlation between air temperature and sensible heat flux anomalies identified from FLUXNET network data suggests that abrupt changes in sensible heat flux above climatological means can serve as indicators for predicting the onset of a heatwave. We thus capitalize on the inherent coupling between evaporative and sensible heat fluxes linked to moisture availability within the CR framework to predict rapid increase in regional sensible heat flux associated with soil drying (low precipitation) or with extreme evaporative demand (high radiation) while soil moisture is not limiting. The proposed approach evaluated using FLUXNET datasets provides an energy constraint framework based on the CR concept to obtain new insights into the onset of heatwaves and climate extremes such as regional droughts.

In silico and in vitro prediction of gastrointestinal absorption from potential drug eremantholide C.

Science.gov (United States)

Caldeira, Tamires G; Saúde-Guimarães, Dênia A; Dezani, André B; Serra, Cristina Helena Dos Reis; de Souza, Jacqueline

2017-11-01

Analysis of the biopharmaceutical properties of eremantholide C, sesquiterpene lactone with proven pharmacological activity and low toxicity, is required to evaluate its potential to become a drug. Preliminary analysis of the physicochemical characteristics of eremantholide C was performed in silico. Equilibrium solubility was evaluated using the shake-flask method, at 37.0 °C, 100 rpm during 72 h in biorelevant media. The permeability was analysed using parallel artificial membrane permeability assay, at 37.0 °C, 50 rpm for 5 h. The donor compartment was composed of an eremantholide C solution in intestinal fluid simulated without enzymes, while the acceptor compartment consisted of phosphate buffer. Physicochemical characteristics predicted in silico indicated that eremantholide C has a low solubility and high permeability. In-vitro data of eremantholide C showed low solubility, with values for the dose/solubility ratio (ml): 9448.82, 10 389.61 e 15 000.00 for buffers acetate (pH 4.5), intestinal fluid simulated without enzymes (pH 6.8) and phosphate (pH 7.4), respectively. Also, it showed high permeability, with effective permeability of 30.4 × 10 -6 cm/s, a higher result compared with propranolol hydrochloride (9.23 × 10 -6 cm/s). The high permeability combined with its solubility, pharmacological activity and low toxicity demonstrate the importance of eremantholide C as a potential drug candidate. © 2017 Royal Pharmaceutical Society.

Genome-Wide Locations of Potential Epimutations Associated with Environmentally Induced Epigenetic Transgenerational Inheritance of Disease Using a Sequential Machine Learning Prediction Approach.

Science.gov (United States)

Haque, M Muksitul; Holder, Lawrence B; Skinner, Michael K

2015-01-01

Environmentally induced epigenetic transgenerational inheritance of disease and phenotypic variation involves germline transmitted epimutations. The primary epimutations identified involve altered differential DNA methylation regions (DMRs). Different environmental toxicants have been shown to promote exposure (i.e., toxicant) specific signatures of germline epimutations. Analysis of genomic features associated with these epimutations identified low-density CpG regions (machine learning computational approach to predict all potential epimutations in the genome. A number of previously identified sperm epimutations were used as training sets. A novel machine learning approach using a sequential combination of Active Learning and Imbalance Class Learner analysis was developed. The transgenerational sperm epimutation analysis identified approximately 50K individual sites with a 1 kb mean size and 3,233 regions that had a minimum of three adjacent sites with a mean size of 3.5 kb. A select number of the most relevant genomic features were identified with the low density CpG deserts being a critical genomic feature of the features selected. A similar independent analysis with transgenerational somatic cell epimutation training sets identified a smaller number of 1,503 regions of genome-wide predicted sites and differences in genomic feature contributions. The predicted genome-wide germline (sperm) epimutations were found to be distinct from the predicted somatic cell epimutations. Validation of the genome-wide germline predicted sites used two recently identified transgenerational sperm epimutation signature sets from the pesticides dichlorodiphenyltrichloroethane (DDT) and methoxychlor (MXC) exposure lineage F3 generation. Analysis of this positive validation data set showed a 100% prediction accuracy for all the DDT-MXC sperm epimutations. Observations further elucidate the genomic features associated with transgenerational germline epimutations and identify a genome

B(E2) ↑ (01+ -> 21+) predictions for even–even nuclei in the differential equation model

International Nuclear Information System (INIS)

Nayak, R.C.; Pattnaik, S.

2015-01-01

We use the recently developed differential equation model (DEM) for the reduced electric quadrupole transition probability B(E2)↑ for the transition from the ground to the first 2 + state for predicting its values for a wide range of even–even nuclides almost throughout the nuclear landscape from Neon to Californium. This is made possible as the principal equation in the model, namely, the differential equation connecting the B(E2)↑ value of a given even–even nucleus with its derivatives with respect to the neutron and proton numbers, provides two different recursion relations, each connecting three different neighboring even–even nuclei from lower- to higher-mass numbers and vice versa. These relations are primarily responsible in extrapolating from known to unknown terrain of the B(E2)↑-landscape and thereby facilitate the predictions throughout. As a result, we have succeeded in predicting its hitherto unknown value for the adjacent 251 isotopes lying on either side of the known B(E2)↑ database. (author)

Do resting brain dynamics predict oddball evoked-potential?

Directory of Open Access Journals (Sweden)

Lee Tien-Wen

2011-11-01

Full Text Available Abstract Background The oddball paradigm is widely applied to the investigation of cognitive function in neuroscience and in neuropsychiatry. Whether cortical oscillation in the resting state can predict the elicited oddball event-related potential (ERP is still not clear. This study explored the relationship between resting electroencephalography (EEG and oddball ERPs. The regional powers of 18 electrodes across delta, theta, alpha and beta frequencies were correlated with the amplitude and latency of N1, P2, N2 and P3 components of oddball ERPs. A multivariate analysis based on partial least squares (PLS was applied to further examine the spatial pattern revealed by multiple correlations. Results Higher synchronization in the resting state, especially at the alpha spectrum, is associated with higher neural responsiveness and faster neural propagation, as indicated by the higher amplitude change of N1/N2 and shorter latency of P2. None of the resting quantitative EEG indices predict P3 latency and amplitude. The PLS analysis confirms that the resting cortical dynamics which explains N1/N2 amplitude and P2 latency does not show regional specificity, indicating a global property of the brain. Conclusions This study differs from previous approaches by relating dynamics in the resting state to neural responsiveness in the activation state. Our analyses suggest that the neural characteristics carried by resting brain dynamics modulate the earlier/automatic stage of target detection.

Recall of Point-of-Sale Marketing Predicts Cigar and E-Cigarette Use among Texas Youth.

Science.gov (United States)

Pasch, Keryn E; Nicksic, Nicole E; Opara, Samuel C; Jackson, Christian; Harrell, Melissa B; Perry, Cheryl L

2017-10-23

While research has documented associations between recall of point-of sale tobacco marketing and youth tobacco use, much of the research is cross-sectional and focused on cigarettes. The present longitudinal study examined recall of tobacco marketing at the point-of-sale and multiple types of tobacco use six months later. The Texas Adolescent Tobacco Advertising and Marketing Surveillance System (TATAMS) is a large-scale, representative study of 6th, 8th, and 10th graders in 79 middle and high schools in five counties in Texas. Weighted logistic regression examined associations between recall of tobacco advertisements and products on display at baseline and ever use, current use, and susceptibility to use for cigarette, e-cigarette, cigar, and smokeless products six months later. Students' recall of signs marketing e-cigarettes at baseline predicted ever e-cigarette use and increased susceptibility to use e-cigarettes at follow-up across all store types. Recall of e-cigarette displays only predicted susceptibility to use e-cigarettes at follow-up, across all store types. Both recall of signs marketing cigars and cigar product displays predicted current and ever cigar smoking and increased susceptibility to smoking cigars at follow-up, across all store types. Recall of cigarette and smokeless product marketing and displays was not associated with tobacco use measures. The point-of-sale environment continues to be an important influence on youth tobacco use. Restrictions on point-of-sale marketing, particularly around schools, are warranted. Cross-sectional studies have shown that exposure to point-of-sale cigarette marketing is associated with use of cigarettes among youth, though longitudinal evidence of the same is sparse and mixed. Cross-sectional studies have found that recall of cigars, smokeless product, and e-cigarette tobacco marketing at point-of-sale is associated with curiosity about tobacco use or intentions to use tobacco among youth, but limited

Molecular constraints on synaptic tagging and maintenance of long-term potentiation: a predictive model.

Science.gov (United States)

Smolen, Paul; Baxter, Douglas A; Byrne, John H

2012-01-01

Protein synthesis-dependent, late long-term potentiation (LTP) and depression (LTD) at glutamatergic hippocampal synapses are well characterized examples of long-term synaptic plasticity. Persistent increased activity of protein kinase M ζ (PKMζ) is thought essential for maintaining LTP. Additional spatial and temporal features that govern LTP and LTD induction are embodied in the synaptic tagging and capture (STC) and cross capture hypotheses. Only synapses that have been "tagged" by a stimulus sufficient for LTP and learning can "capture" PKMζ. A model was developed to simulate the dynamics of key molecules required for LTP and LTD. The model concisely represents relationships between tagging, capture, LTD, and LTP maintenance. The model successfully simulated LTP maintained by persistent synaptic PKMζ, STC, LTD, and cross capture, and makes testable predictions concerning the dynamics of PKMζ. The maintenance of LTP, and consequently of at least some forms of long-term memory, is predicted to require continual positive feedback in which PKMζ enhances its own synthesis only at potentiated synapses. This feedback underlies bistability in the activity of PKMζ. Second, cross capture requires the induction of LTD to induce dendritic PKMζ synthesis, although this may require tagging of a nearby synapse for LTP. The model also simulates the effects of PKMζ inhibition, and makes additional predictions for the dynamics of CaM kinases. Experiments testing the above predictions would significantly advance the understanding of memory maintenance.

Predicting Potential Fire Severity Using Vegetation, Topography and Surface Moisture Availability in a Eurasian Boreal Forest Landscape

Directory of Open Access Journals (Sweden)

Lei Fang

2018-03-01

Full Text Available Severity of wildfires is a critical component of the fire regime and plays an important role in determining forest ecosystem response to fire disturbance. Predicting spatial distribution of potential fire severity can be valuable in guiding fire and fuel management planning. Spatial controls on fire severity patterns have attracted growing interest, but few studies have attempted to predict potential fire severity in fire-prone Eurasian boreal forests. Furthermore, the influences of fire weather variation on spatial heterogeneity of fire severity remain poorly understood at fine scales. We assessed the relative importance and influence of pre-fire vegetation, topography, and surface moisture availability (SMA on fire severity in 21 lightning-ignited fires occurring in two different fire years (3 fires in 2000, 18 fires in 2010 of the Great Xing’an Mountains with an ensemble modeling approach of boosted regression tree (BRT. SMA was derived from 8-day moderate resolution imaging spectroradiometer (MODIS evapotranspiration products. We predicted the potential distribution of fire severity in two fire years and evaluated the prediction accuracies. BRT modeling revealed that vegetation, topography, and SMA explained more than 70% of variations in fire severity (mean 83.0% for 2000, mean 73.8% for 2010. Our analysis showed that evergreen coniferous forests were more likely to experience higher severity fires than the dominant deciduous larch forests of this region, and deciduous broadleaf forests and shrublands usually burned at a significantly lower fire severity. High-severity fires tended to occur in gentle and well-drained slopes at high altitudes, especially those with north-facing aspects. SMA exhibited notable and consistent negative association with severity. Predicted fire severity from our model exhibited strong agreement with the observed fire severity (mean r2 = 0.795 for 2000, 0.618 for 2010. Our results verified that spatial variation

Predictive microbiology in food packaging applications

Science.gov (United States)

Predictive microbiology including growth, inactivation, surface transfer (or cross-contamination), and survival, plays important roles in understanding microbial food safety. Growth models may involve the growth potential of a specified pathogen under different stresses, e.g., temperature, pH, wate...

Prediction of Thorough QT study results using action potential simulations based on ion channel screens.

Science.gov (United States)

Mirams, Gary R; Davies, Mark R; Brough, Stephen J; Bridgland-Taylor, Matthew H; Cui, Yi; Gavaghan, David J; Abi-Gerges, Najah

2014-01-01

Detection of drug-induced pro-arrhythmic risk is a primary concern for pharmaceutical companies and regulators. Increased risk is linked to prolongation of the QT interval on the body surface ECG. Recent studies have shown that multiple ion channel interactions can be required to predict changes in ventricular repolarisation and therefore QT intervals. In this study we attempt to predict the result of the human clinical Thorough QT (TQT) study, using multiple ion channel screening which is available early in drug development. Ion current reduction was measured, in the presence of marketed drugs which have had a TQT study, for channels encoded by hERG, CaV1.2, NaV1.5, KCNQ1/MinK, and Kv4.3/KChIP2.2. The screen was performed on two platforms - IonWorks Quattro (all 5 channels, 34 compounds), and IonWorks Barracuda (hERG & CaV1.2, 26 compounds). Concentration-effect curves were fitted to the resulting data, and used to calculate a percentage reduction in each current at a given concentration. Action potential simulations were then performed using the ten Tusscher and Panfilov (2006), Grandi et al. (2010) and O'Hara et al. (2011) human ventricular action potential models, pacing at 1Hz and running to steady state, for a range of concentrations. We compared simulated action potential duration predictions with the QT prolongation observed in the TQT studies. At the estimated concentrations, simulations tended to underestimate any observed QT prolongation. When considering a wider range of concentrations, and conventional patch clamp rather than screening data for hERG, prolongation of ≥5ms was predicted with up to 79% sensitivity and 100% specificity. This study provides a proof-of-principle for the prediction of human TQT study results using data available early in drug development. We highlight a number of areas that need refinement to improve the method's predictive power, but the results suggest that such approaches will provide a useful tool in cardiac safety

Intensity of the Internal Standard Response as the Basis for Reporting a Test Specimen as Negative or Inconclusive

Science.gov (United States)

2007-08-01

conclusive results in toxicology tests. Even under normal analytical conditions where the IS is poorly recovered, the substance may escape detection if it is...and en- zyme immunoassay of cannabis metabolites with gas chromatography/mass spectrometry analysis of 11-nor-Δ9-tetrahydrocannabinol-9- carboxylic

The human brain maintains contradictory and redundant auditory sensory predictions.

Directory of Open Access Journals (Sweden)

Marika Pieszek

Full Text Available Computational and experimental research has revealed that auditory sensory predictions are derived from regularities of the current environment by using internal generative models. However, so far, what has not been addressed is how the auditory system handles situations giving rise to redundant or even contradictory predictions derived from different sources of information. To this end, we measured error signals in the event-related brain potentials (ERPs in response to violations of auditory predictions. Sounds could be predicted on the basis of overall probability, i.e., one sound was presented frequently and another sound rarely. Furthermore, each sound was predicted by an informative visual cue. Participants' task was to use the cue and to discriminate the two sounds as fast as possible. Violations of the probability based prediction (i.e., a rare sound as well as violations of the visual-auditory prediction (i.e., an incongruent sound elicited error signals in the ERPs (Mismatch Negativity [MMN] and Incongruency Response [IR]. Particular error signals were observed even in case the overall probability and the visual symbol predicted different sounds. That is, the auditory system concurrently maintains and tests contradictory predictions. Moreover, if the same sound was predicted, we observed an additive error signal (scalp potential and primary current density equaling the sum of the specific error signals. Thus, the auditory system maintains and tolerates functionally independently represented redundant and contradictory predictions. We argue that the auditory system exploits all currently active regularities in order to optimally prepare for future events.

The predictive role of E/e' on ischemic stroke and atrial fibrillation in Japanese patients without atrial fibrillation.

Science.gov (United States)

Arai, Riku; Suzuki, Shinya; Semba, Hiroaki; Arita, Takuto; Yagi, Naoharu; Otsuka, Takayuki; Sagara, Koichi; Sasaki, Kenichi; Kano, Hiroto; Matsuno, Shunsuke; Kato, Yuko; Uejima, Tokuhisa; Oikawa, Yuji; Kunihara, Takashi; Yajima, Junji; Yamashita, Takeshi

2018-07-01

The predictive role of E/e' on ischemic stroke (IS) and atrial fibrillation (AF) in Japanese patients without AF are unclear. Shinken database includes all the new patients visiting the Cardiovascular Institute Hospital in Tokyo, Japan. E/e' has been routinely measured since 2007. Patients without AF for whom E/e' was measured at the initial visit between 2007 and 2014 (n=11 477, mean age 57.2 years old, men 59.5%) were divided into E/e' tertiles (11.00). During the mean follow-up period of 1.8 years, 58 IS and 140 new appearances of AF were observed. High E/e' tertile was associated with more prevalence of atherothrombotic risks. The cumulative incidence of IS events and new appearance of AF at 6 years in low, middle, and high E/e' tertiles were 0.5%, 1.4%, and 3.0%/year (log-rank test, pE/e' tertile was independently associated with IS (HR, 2.857, 95%CI 1.257-6.495, p=0.012). Although high E/e' tertile was independently associated with new appearance of AF when adjusted for coexistence of atherothrombotic risk factors (HR, 1.694, 95%CI, 1.097-2.616, p=0.017), the association was attenuated after adjustment for left atrial dimension. E/e' was significantly associated with incidence of IS and new appearance of AF in non-AF patients. Copyright © 2018 Japanese College of Cardiology. Published by Elsevier Ltd. All rights reserved.

e-Bitter: Bitterant Prediction by the Consensus Voting From the Machine-Learning Methods.

Science.gov (United States)

Zheng, Suqing; Jiang, Mengying; Zhao, Chengwei; Zhu, Rui; Hu, Zhicheng; Xu, Yong; Lin, Fu

2018-01-01

In-silico bitterant prediction received the considerable attention due to the expensive and laborious experimental-screening of the bitterant. In this work, we collect the fully experimental dataset containing 707 bitterants and 592 non-bitterants, which is distinct from the fully or partially hypothetical non-bitterant dataset used in the previous works. Based on this experimental dataset, we harness the consensus votes from the multiple machine-learning methods (e.g., deep learning etc.) combined with the molecular fingerprint to build the bitter/bitterless classification models with five-fold cross-validation, which are further inspected by the Y-randomization test and applicability domain analysis. One of the best consensus models affords the accuracy, precision, specificity, sensitivity, F1-score, and Matthews correlation coefficient (MCC) of 0.929, 0.918, 0.898, 0.954, 0.936, and 0.856 respectively on our test set. For the automatic prediction of bitterant, a graphic program "e-Bitter" is developed for the convenience of users via the simple mouse click. To our best knowledge, it is for the first time to adopt the consensus model for the bitterant prediction and develop the first free stand-alone software for the experimental food scientist.

e-Bitter: Bitterant Prediction by the Consensus Voting From the Machine-learning Methods

Science.gov (United States)

Zheng, Suqing; Jiang, Mengying; Zhao, Chengwei; Zhu, Rui; Hu, Zhicheng; Xu, Yong; Lin, Fu

2018-03-01

In-silico bitterant prediction received the considerable attention due to the expensive and laborious experimental-screening of the bitterant. In this work, we collect the fully experimental dataset containing 707 bitterants and 592 non-bitterants, which is distinct from the fully or partially hypothetical non-bitterant dataset used in the previous works. Based on this experimental dataset, we harness the consensus votes from the multiple machine-learning methods (e.g., deep learning etc.) combined with the molecular fingerprint to build the bitter/bitterless classification models with five-fold cross-validation, which are further inspected by the Y-randomization test and applicability domain analysis. One of the best consensus models affords the accuracy, precision, specificity, sensitivity, F1-score, and Matthews correlation coefficient (MCC) of 0.929, 0.918, 0.898, 0.954, 0.936, and 0.856 respectively on our test set. For the automatic prediction of bitterant, a graphic program “e-Bitter” is developed for the convenience of users via the simple mouse click. To our best knowledge, it is for the first time to adopt the consensus model for the bitterant prediction and develop the first free stand-alone software for the experimental food scientist.

Potential carcinogenicity predicted by computational toxicity evaluation of thiophosphate pesticides using QSTR/QSCarciAR model.

Science.gov (United States)

Petrescu, Alina-Maria; Ilia, Gheorghe

2017-07-01

This study presents in silico prediction of toxic activities and carcinogenicity, represented by the potential carcinogenicity DSSTox/DBS, based on vector regression with a new Kernel activity, and correlating the predicted toxicity values through a QSAR model, namely: QSTR/QSCarciAR (quantitative structure toxicity relationship/quantitative structure carcinogenicity-activity relationship) described by 2D, 3D descriptors and biological descriptors. The results showed a connection between carcinogenicity (compared to the structure of a compound) and toxicity, as a basis for future studies on this subject, but each prediction is based on structurally similar compounds and the reactivation of the substructures of these compounds.

[Predictive factors of anxiety disorders].

Science.gov (United States)

Domschke, K

2014-10-01

Anxiety disorders are among the most frequent mental disorders in Europe (12-month prevalence 14%) and impose a high socioeconomic burden. The pathogenesis of anxiety disorders is complex with an interaction of biological, environmental and psychosocial factors contributing to the overall disease risk (diathesis-stress model). In this article, risk factors for anxiety disorders will be presented on several levels, e.g. genetic factors, environmental factors, gene-environment interactions, epigenetic mechanisms, neuronal networks ("brain fear circuit"), psychophysiological factors (e.g. startle response and CO2 sensitivity) and dimensional/subclinical phenotypes of anxiety (e.g. anxiety sensitivity and behavioral inhibition), and critically discussed regarding their potential predictive value. The identification of factors predictive of anxiety disorders will possibly allow for effective preventive measures or early treatment interventions, respectively, and reduce the individual patient's suffering as well as the overall socioeconomic burden of anxiety disorders.

Peak-summer East Asian rainfall predictability and prediction part II: extratropical East Asia

Science.gov (United States)

Yim, So-Young; Wang, Bin; Xing, Wen

2016-07-01

The part II of the present study focuses on northern East Asia (NEA: 26°N-50°N, 100°-140°E), exploring the source and limit of the predictability of the peak summer (July-August) rainfall. Prediction of NEA peak summer rainfall is extremely challenging because of the exposure of the NEA to midlatitude influence. By examining four coupled climate models' multi-model ensemble (MME) hindcast during 1979-2010, we found that the domain-averaged MME temporal correlation coefficient (TCC) skill is only 0.13. It is unclear whether the dynamical models' poor skills are due to limited predictability of the peak-summer NEA rainfall. In the present study we attempted to address this issue by applying predictable mode analysis method using 35-year observations (1979-2013). Four empirical orthogonal modes of variability and associated major potential sources of variability are identified: (a) an equatorial western Pacific (EWP)-NEA teleconnection driven by EWP sea surface temperature (SST) anomalies, (b) a western Pacific subtropical high and Indo-Pacific dipole SST feedback mode, (c) a central Pacific-El Nino-Southern Oscillation mode, and (d) a Eurasian wave train pattern. Physically meaningful predictors for each principal component (PC) were selected based on analysis of the lead-lag correlations with the persistent and tendency fields of SST and sea-level pressure from March to June. A suite of physical-empirical (P-E) models is established to predict the four leading PCs. The peak summer rainfall anomaly pattern is then objectively predicted by using the predicted PCs and the corresponding observed spatial patterns. A 35-year cross-validated hindcast over the NEA yields a domain-averaged TCC skill of 0.36, which is significantly higher than the MME dynamical hindcast (0.13). The estimated maximum potential attainable TCC skill averaged over the entire domain is around 0.61, suggesting that the current dynamical prediction models may have large rooms to improve

Molecular constraints on synaptic tagging and maintenance of long-term potentiation: a predictive model.

Directory of Open Access Journals (Sweden)

Paul Smolen

Full Text Available Protein synthesis-dependent, late long-term potentiation (LTP and depression (LTD at glutamatergic hippocampal synapses are well characterized examples of long-term synaptic plasticity. Persistent increased activity of protein kinase M ζ (PKMζ is thought essential for maintaining LTP. Additional spatial and temporal features that govern LTP and LTD induction are embodied in the synaptic tagging and capture (STC and cross capture hypotheses. Only synapses that have been "tagged" by a stimulus sufficient for LTP and learning can "capture" PKMζ. A model was developed to simulate the dynamics of key molecules required for LTP and LTD. The model concisely represents relationships between tagging, capture, LTD, and LTP maintenance. The model successfully simulated LTP maintained by persistent synaptic PKMζ, STC, LTD, and cross capture, and makes testable predictions concerning the dynamics of PKMζ. The maintenance of LTP, and consequently of at least some forms of long-term memory, is predicted to require continual positive feedback in which PKMζ enhances its own synthesis only at potentiated synapses. This feedback underlies bistability in the activity of PKMζ. Second, cross capture requires the induction of LTD to induce dendritic PKMζ synthesis, although this may require tagging of a nearby synapse for LTP. The model also simulates the effects of PKMζ inhibition, and makes additional predictions for the dynamics of CaM kinases. Experiments testing the above predictions would significantly advance the understanding of memory maintenance.

Effect of NN correlations on predictions of nuclear transparencies for protons, knocked out in high Q2 (e,e'p) reactions

International Nuclear Information System (INIS)

Rinat, A.S.; Taragin, M.F.

1996-01-01

We study the transparency T of nuclei for nucleons knocked out in high-energy semi-inclusive (e,e'p) reactions, using an improved theoretical input, discussed by Nikolaev et al. We establish that neglect of NN correlations between the knocked-out and core nucleons reduces nuclear transparencies by ∼15 % for light, to ∼10% for heavy nuclei. About the same is predicted for transparencies, integrated over the transverse or longitudinal momentum of the outgoing proton. Hadron dynamics predicts a roughly constant T beyond Q 2 ∼2 GeV 2 , whereas for all targets the largest measured data point Q 2 =6.7 GeV 2 appears to lie above that plateau. Large error bars on those data points preclude a conclusion regarding the onset of colour transparency. (orig.)

A Review of Auditory Prediction and Its Potential Role in Tinnitus Perception.

Science.gov (United States)

Durai, Mithila; O'Keeffe, Mary G; Searchfield, Grant D

2018-06-01

The precise mechanisms underlying tinnitus perception and distress are still not fully understood. A recent proposition is that auditory prediction errors and related memory representations may play a role in driving tinnitus perception. It is of interest to further explore this. To obtain a comprehensive narrative synthesis of current research in relation to auditory prediction and its potential role in tinnitus perception and severity. A narrative review methodological framework was followed. The key words Prediction Auditory, Memory Prediction Auditory, Tinnitus AND Memory, Tinnitus AND Prediction in Article Title, Abstract, and Keywords were extensively searched on four databases: PubMed, Scopus, SpringerLink, and PsychINFO. All study types were selected from 2000-2016 (end of 2016) and had the following exclusion criteria applied: minimum age of participants article not available in English. Reference lists of articles were reviewed to identify any further relevant studies. Articles were short listed based on title relevance. After reading the abstracts and with consensus made between coauthors, a total of 114 studies were selected for charting data. The hierarchical predictive coding model based on the Bayesian brain hypothesis, attentional modulation and top-down feedback serves as the fundamental framework in current literature for how auditory prediction may occur. Predictions are integral to speech and music processing, as well as in sequential processing and identification of auditory objects during auditory streaming. Although deviant responses are observable from middle latency time ranges, the mismatch negativity (MMN) waveform is the most commonly studied electrophysiological index of auditory irregularity detection. However, limitations may apply when interpreting findings because of the debatable origin of the MMN and its restricted ability to model real-life, more complex auditory phenomenon. Cortical oscillatory band activity may act as

Application of GIS based data driven evidential belief function model to predict groundwater potential zonation

Science.gov (United States)

Nampak, Haleh; Pradhan, Biswajeet; Manap, Mohammad Abd

2014-05-01

The objective of this paper is to exploit potential application of an evidential belief function (EBF) model for spatial prediction of groundwater productivity at Langat basin area, Malaysia using geographic information system (GIS) technique. About 125 groundwater yield data were collected from well locations. Subsequently, the groundwater yield was divided into high (⩾11 m3/h) and low yields (divided into a testing dataset 70% (42 wells) for training the model and the remaining 30% (18 wells) was used for validation purpose. To perform cross validation, the frequency ratio (FR) approach was applied into remaining groundwater wells with low yield to show the spatial correlation between the low potential zones of groundwater productivity. A total of twelve groundwater conditioning factors that affect the storage of groundwater occurrences were derived from various data sources such as satellite based imagery, topographic maps and associated database. Those twelve groundwater conditioning factors are elevation, slope, curvature, stream power index (SPI), topographic wetness index (TWI), drainage density, lithology, lineament density, land use, normalized difference vegetation index (NDVI), soil and rainfall. Subsequently, the Dempster-Shafer theory of evidence model was applied to prepare the groundwater potential map. Finally, the result of groundwater potential map derived from belief map was validated using testing data. Furthermore, to compare the performance of the EBF result, logistic regression model was applied. The success-rate and prediction-rate curves were computed to estimate the efficiency of the employed EBF model compared to LR method. The validation results demonstrated that the success-rate for EBF and LR methods were 83% and 82% respectively. The area under the curve for prediction-rate of EBF and LR methods were calculated 78% and 72% respectively. The outputs achieved from the current research proved the efficiency of EBF in groundwater

Weight and height prediction of immobilized patients Estimativa de peso e altura de pacientes hospitalizados e imobilizados

Directory of Open Access Journals (Sweden)

Estela Iraci Rabito

2006-12-01

Full Text Available OBJECTIVE: To confirm the adequacy of the formula suggested in the literature and/or to develop appropriate equations for the Brazilian population of immobilized patients based on simple anthropometric measurements. METHODS: Hospitalized patients were submitted to anthropometry and methods to estimate weight and height of bedridden patients were developed by multiple linear regression. RESULTS: Three hundred sixty eight persons were evaluated at two hospital centers and five weight-predicting and two height-predicting equations were developed from the measurements obtained. Among the new equations developed, the simplest one for weight estimate was: Weight (kg = 0.5759 x (arm circumference, cm + 0.5263 x (abdominal circumference, cm + 1.2452 x (calf circumference, cm -4.8689 x (Sex, male = 1 and female = 2 -32.9241 (r = 0.94; and the one for height estimate was: Height (cm = 58.6940 - 2.9740 x (Sex -0.0736 x (age, years + 0.4958 x (arm length, cm + 1.1320 x (half- span, cm (r = 0.88. The estimates thus calculated did not differ significantly from actual measurements, with p = 0.94 and 0.89 and a mean error of 6.0 and 2.1% for weight and height, respectively. CONCLUSION: We suggest that these equations can be used to estimate the weight and height of bedridden patients when necessary or when these parameters cannot be measured with a scale and a stadiometer.OBJETIVO: Verificar a adequação das fórmulas sugeridas na literatura, e desenvolver equações preditivas de peso e altura para a população hospitalizada brasileira, a partir de medidas antropométricas usuais. MÉTODOS: Realizou-se antropometria e bioimpedância de pacientes hospitalizados. Por meio de regressão linear múltipla, desenvolveram-se fórmulas com o objetivo de prever o peso e a altura. Os resultados foram comparados com os obtidos de fórmulas da literatura e com as medidas reais. RESULTADOS: Foram avaliadas 368 pacientes e desenvolvidas equações preditivas do peso e da

Prediction of allergy from family history and cord blood IgE levels. A follow-up at the age of 5 years. Cord blood IgE. IV

DEFF Research Database (Denmark)

Hansen, L G; Halken, S; Høst, A

1993-01-01

was not influenced by cord blood IgE levels or atopic predisposition. Cord blood IgE levels had a low sensitivity as a predictor of atopic disease. A statistically significant correlation between serum levels of IgE at birth and at 5 years was however found (p ... with elevated cord blood IgE levels developed allergic disease before 5 years of age (p 63 kU/l (geometric mean + 1 SD) at the age of 5 years can be regarded as being an elevated level. A cord...... blood IgE level > or = 0.3 kU/l in combination with atopic predisposition was predictive of allergic disease, especially allergic bronchial asthma. With regard to allergic disease, the positive predictive value was 26%, the sensitivity 33% and the rate ratio for development of allergic disease 4...

Effects of various potential models for fourth SM family (Ψ4) quarkonia production at e''+ e''- colliders

International Nuclear Information System (INIS)

Ciftci, R.; Sultansoy, S.

2002-01-01

In the framework of democratic mass matrix (DMM) approach the lower limit on the fourth standard model (SM) family quarkonia mass is 640 GeV, so future e+e- colliders (TESLA, JLC/NLC and CLIC) with a good beam resolution will give opportunity to investigate properties of vector (ψ 4 ) quarkonia. We estimate ψ 4 production cross-sections by using various potential models (Coulomb, Martin, Cornell and Richardson). Signatures of the process e''+e''-→ψ 4 are discussed taking into account any decay modes of y4 quarkonia. Especially ψ 4 →and ψ 4 →γH channels will open new window for investigation of Higgs boson properties

Rabbit antibodies for hormone receptors and HER2 evaluation in breast cancer Anticorpos de coelho para avaliação de receptores hormonais e HER2 em câncer de mama

Directory of Open Access Journals (Sweden)

Rafael Malagoli Rocha

2009-01-01

Full Text Available BACKGROUND: Novel rabbit monoclonal antibodies (RabMab for estrogen (ER, progesterone (PR receptors and HER2 evaluation by immunohistochemistry have recently been commercially released. We compared the RabMab anti-ER, anti-PR and anti-HER2 to mouse monoclonal antibodies (Mab using tissue microarrays (TMA of breast carcinomas. METHODS: Two TMA containing breast carcinomas were built. Sections were immunostained using anti-ER and anti-PR, Mab and RabMab. The sections stained for ER and PR were evaluated considering positive those tumors in which more than 1% of the tumor cell nuclei stained moderate or strong. For HER2, the immunostained sections were evaluated using the ASCO/CAP guidelines for HER2. Chromogenic in situ hybridization (CISH was used as the gold standard for HER2 evaluation. CISH was evaluated using the Zymed HER2 CISH interpretation guidelines. RESULTS: RabMab against ER have similar staining patterns compared to the 6F11 (Mab, but stronger than 1D5 (Mab from three different suppliers. The RabMab against PR provide stronger and sharper immunohistochemical signals compared to Mab. The detection of HER2 protein overexpression was more prevalent with the polyclonal antibodies and RabMab than with the Mab. These were more specific than the RabMab, which were more sensitive when compared to CISH. CONCLUSION: The novel RabMab against ER and PR showed higher intensity of staining than the Mab. The RabMab against HER2 is more sensitive than Mab, however, Mab presented more specificity than RabMab when compared to CISH for HER2 evaluation of breast carcinomas.OBJETIVOS: Novos anticorpos monoclonais de coelho (RabMab para a avaliação imuno-histoquímica de receptores de estrógeno (RE, progesterona (RP e HER2 foram lançados comercialmente. Comparamos os RabMab anti-RE, anti-RP e anti-HER2 com os anticorpos monoclonais de camundongo (Mab utilizando tissue microarrays (TMA de carcinomas de mama. MÉTODOS: Foram construídos dois TMAs de

Geostatistical enhancement of european hydrological predictions

Science.gov (United States)

Pugliese, Alessio; Castellarin, Attilio; Parajka, Juraj; Arheimer, Berit; Bagli, Stefano; Mazzoli, Paolo; Montanari, Alberto; Blöschl, Günter

2016-04-01

Geostatistical Enhancement of European Hydrological Prediction (GEEHP) is a research experiment developed within the EU funded SWITCH-ON project, which proposes to conduct comparative experiments in a virtual laboratory in order to share water-related information and tackle changes in the hydrosphere for operational needs (http://www.water-switch-on.eu). The main objective of GEEHP deals with the prediction of streamflow indices and signatures in ungauged basins at different spatial scales. In particular, among several possible hydrological signatures we focus in our experiment on the prediction of flow-duration curves (FDCs) along the stream-network, which has attracted an increasing scientific attention in the last decades due to the large number of practical and technical applications of the curves (e.g. hydropower potential estimation, riverine habitat suitability and ecological assessments, etc.). We apply a geostatistical procedure based on Top-kriging, which has been recently shown to be particularly reliable and easy-to-use regionalization approach, employing two different type of streamflow data: pan-European E-HYPE simulations (http://hypeweb.smhi.se/europehype) and observed daily streamflow series collected in two pilot study regions, i.e. Tyrol (merging data from Austrian and Italian stream gauging networks) and Sweden. The merger of the two study regions results in a rather large area (~450000 km2) and might be considered as a proxy for a pan-European application of the approach. In a first phase, we implement a bidirectional validation, i.e. E-HYPE catchments are set as training sites to predict FDCs at the same sites where observed data are available, and vice-versa. Such a validation procedure reveals (1) the usability of the proposed approach for predicting the FDCs over the entire river network of interest using alternatively observed data and E-HYPE simulations and (2) the accuracy of E-HYPE-based predictions of FDCs in ungauged sites. In a

Can phylogeny predict chemical diversity and potential medicinal activity of plants? A case study of amaryllidaceae

Directory of Open Access Journals (Sweden)

Rønsted Nina

2012-09-01

Full Text Available Abstract Background During evolution, plants and other organisms have developed a diversity of chemical defences, leading to the evolution of various groups of specialized metabolites selected for their endogenous biological function. A correlation between phylogeny and biosynthetic pathways could offer a predictive approach enabling more efficient selection of plants for the development of traditional medicine and lead discovery. However, this relationship has rarely been rigorously tested and the potential predictive power is consequently unknown. Results We produced a phylogenetic hypothesis for the medicinally important plant subfamily Amaryllidoideae (Amaryllidaceae based on parsimony and Bayesian analysis of nuclear, plastid, and mitochondrial DNA sequences of over 100 species. We tested if alkaloid diversity and activity in bioassays related to the central nervous system are significantly correlated with phylogeny and found evidence for a significant phylogenetic signal in these traits, although the effect is not strong. Conclusions Several genera are non-monophyletic emphasizing the importance of using phylogeny for interpretation of character distribution. Alkaloid diversity and in vitro inhibition of acetylcholinesterase (AChE and binding to the serotonin reuptake transporter (SERT are significantly correlated with phylogeny. This has implications for the use of phylogenies to interpret chemical evolution and biosynthetic pathways, to select candidate taxa for lead discovery, and to make recommendations for policies regarding traditional use and conservation priorities.

REDOX AND REDUCTION POTENTIALS AS PARAMETERS TO PREDICT THE DEGRADATION PATHWAY OF CHLORINATED BENZENES IN ANAEROBIC ENVIRONMENTS

NARCIS (Netherlands)

DOLFING, J; HARRISON, BK

1993-01-01

The anaerobic degradation pathway of hexachlorobenzene starts with a series of reductive dehalogenation steps. In the present paper it was evaluated whether the dehalogenation pathway observed in microbial ecosystems could be predicted by the redox potential and/or the reduction potential (the

e-Bitter: Bitterant Prediction by the Consensus Voting From the Machine-Learning Methods

Directory of Open Access Journals (Sweden)

Suqing Zheng

2018-03-01

Full Text Available In-silico bitterant prediction received the considerable attention due to the expensive and laborious experimental-screening of the bitterant. In this work, we collect the fully experimental dataset containing 707 bitterants and 592 non-bitterants, which is distinct from the fully or partially hypothetical non-bitterant dataset used in the previous works. Based on this experimental dataset, we harness the consensus votes from the multiple machine-learning methods (e.g., deep learning etc. combined with the molecular fingerprint to build the bitter/bitterless classification models with five-fold cross-validation, which are further inspected by the Y-randomization test and applicability domain analysis. One of the best consensus models affords the accuracy, precision, specificity, sensitivity, F1-score, and Matthews correlation coefficient (MCC of 0.929, 0.918, 0.898, 0.954, 0.936, and 0.856 respectively on our test set. For the automatic prediction of bitterant, a graphic program “e-Bitter” is developed for the convenience of users via the simple mouse click. To our best knowledge, it is for the first time to adopt the consensus model for the bitterant prediction and develop the first free stand-alone software for the experimental food scientist.

The potential distribution of bioenergy crops in Europe under present and future climate

International Nuclear Information System (INIS)

Tuck, Gill; Glendining, Margaret J.; Smith, Pete; Wattenbach, Martin; House, Jo I.

2006-01-01

We have derived maps of the potential distribution of 26 promising bioenergy crops in Europe, based on simple rules for suitable climatic conditions and elevation. Crops suitable for temperate and Mediterranean climates were selected from four groups: oilseeds (e.g. oilseed rape, sunflower), starch crops (e.g. potatoes), cereals (e.g. barley) and solid biofuel crops (e.g. sorghum, Miscanthus). The impact of climate change under different scenarios and GCMs on the potential future distribution of these crops was determined, based on predicted future climatic conditions. Climate scenarios based on four IPCC SRES emission scenarios, A1FI, A2, B1 and B2, implemented by four global climate models, HadCM3, CSIRO2, PCM and CGCM2, were used. The potential distribution of temperate oilseeds, cereals, starch crops and solid biofuels is predicted to increase in northern Europe by the 2080s, due to increasing temperatures, and decrease in southern Europe (e.g. Spain, Portugal, southern France, Italy, and Greece) due to increased drought. Mediterranean oil and solid biofuel crops, currently restricted to southern Europe, are predicted to extend further north due to higher summer temperatures. Effects become more pronounced with time and are greatest under the A1FI scenario and for models predicting the greatest climate forcing. Different climate models produce different regional patterns. All models predict that bioenergy crop production in Spain is especially vulnerable to climate change, with many temperate crops predicted to decline dramatically by the 2080s. The choice of bioenergy crops in southern Europe will be severely reduced in future unless measures are taken to adapt to climate change. (author)

The steady performance prediction of propeller-rudder-bulb system based on potential iterative method

International Nuclear Information System (INIS)

Liu, Y B; Su, Y M; Ju, L; Huang, S L

2012-01-01

A new numerical method was developed for predicting the steady hydrodynamic performance of propeller-rudder-bulb system. In the calculation, the rudder and bulb was taken into account as a whole, the potential based surface panel method was applied both to propeller and rudder-bulb system. The interaction between propeller and rudder-bulb was taken into account by velocity potential iteration in which the influence of propeller rotation was considered by the average influence coefficient. In the influence coefficient computation, the singular value should be found and deleted. Numerical results showed that the method presented is effective for predicting the steady hydrodynamic performance of propeller-rudder system and propeller-rudder-bulb system. Comparing with the induced velocity iterative method, the method presented can save programming and calculation time. Changing dimensions, the principal parameter—bulb size that affect energy-saving effect was studied, the results show that the bulb on rudder have a optimal size at the design advance coefficient.

Predicting Risk-Mitigating Behaviors From Indecisiveness and Trait Anxiety

DEFF Research Database (Denmark)

Mcneill, Ilona M.; Dunlop, Patrick D.; Skinner, Timothy C.

2016-01-01

Past research suggests that indecisiveness and trait anxiety may both decrease the likelihood of performing risk-mitigating preparatory behaviors (e.g., preparing for natural hazards) and suggests two cognitive processes (perceived control and worrying) as potential mediators. However, no single...... control over wildfire-related outcomes. Trait anxiety did not uniquely predict preparedness or perceived control, but it did uniquely predict worry, with higher trait anxiety predicting more worrying. Also, worry trended toward uniquely predicting preparedness, albeit in an unpredicted positive direction...

An Empirical Evaluation Of The Potential Of Public E-Procurement To Reduce Corruption

Directory of Open Access Journals (Sweden)

Arjun Neupane

2014-06-01

Full Text Available One of the significant potential benefits of e-procurement technology is reducing opportunities for corruption in public procurement processes. The authors identified anti-corruption capabilities of e-procurement through an extensive literature review and a theoretical model representing the impact of three latent variables: monopoly of power, information asymmetry, and transparency and accountability upon the dependent variable, the intent-to-adopt e-procurement. This research was guided by the Principal-Agent theory and collected the perceptions of 46 government officers of the potential of public e-procurement to reduce corruption in public procurement processes. Results were analysed using the Partial Least Squares Structural Equation Modeling (PLS-SEM approach. The findings suggest that the intent-to-adopt e-procurement has a positive and significant relationship with the independent variables that might inform developing countries in strategies to combat corruption in public procurement.

Genome-Wide Locations of Potential Epimutations Associated with Environmentally Induced Epigenetic Transgenerational Inheritance of Disease Using a Sequential Machine Learning Prediction Approach.

Directory of Open Access Journals (Sweden)

M Muksitul Haque

Full Text Available Environmentally induced epigenetic transgenerational inheritance of disease and phenotypic variation involves germline transmitted epimutations. The primary epimutations identified involve altered differential DNA methylation regions (DMRs. Different environmental toxicants have been shown to promote exposure (i.e., toxicant specific signatures of germline epimutations. Analysis of genomic features associated with these epimutations identified low-density CpG regions (<3 CpG / 100bp termed CpG deserts and a number of unique DNA sequence motifs. The rat genome was annotated for these and additional relevant features. The objective of the current study was to use a machine learning computational approach to predict all potential epimutations in the genome. A number of previously identified sperm epimutations were used as training sets. A novel machine learning approach using a sequential combination of Active Learning and Imbalance Class Learner analysis was developed. The transgenerational sperm epimutation analysis identified approximately 50K individual sites with a 1 kb mean size and 3,233 regions that had a minimum of three adjacent sites with a mean size of 3.5 kb. A select number of the most relevant genomic features were identified with the low density CpG deserts being a critical genomic feature of the features selected. A similar independent analysis with transgenerational somatic cell epimutation training sets identified a smaller number of 1,503 regions of genome-wide predicted sites and differences in genomic feature contributions. The predicted genome-wide germline (sperm epimutations were found to be distinct from the predicted somatic cell epimutations. Validation of the genome-wide germline predicted sites used two recently identified transgenerational sperm epimutation signature sets from the pesticides dichlorodiphenyltrichloroethane (DDT and methoxychlor (MXC exposure lineage F3 generation. Analysis of this positive validation

On the interaction potential in low energy ion scattering

International Nuclear Information System (INIS)

Chini, T.K.; Ghose, D.

1989-01-01

The shadow cones for 998 eV Li + → Ag and 2 keV Na + → Cu are calculated by classical scattering theory using Thomas-Fermi-Moliere potential, universal potential of Ziegler et al. and the Born-Mayer potential. It is found that the Born-Mayer potential with the parameters calculated by Andersen and Sigmund also predicts well the shape of the shadow cones. (orig.)

Metagenomic Functional Potential Predicts Degradation Rates of a Model Organophosphorus Xenobiotic in Pesticide Contaminated Soils

Directory of Open Access Journals (Sweden)

Thomas C. Jeffries

2018-02-01

Full Text Available Chemical contamination of natural and agricultural habitats is an increasing global problem and a major threat to sustainability and human health. Organophosphorus (OP compounds are one major class of contaminant and can undergo microbial degradation, however, no studies have applied system-wide ecogenomic tools to investigate OP degradation or use metagenomics to understand the underlying mechanisms of biodegradation in situ and predict degradation potential. Thus, there is a lack of knowledge regarding the functional genes and genomic potential underpinning degradation and community responses to contamination. Here we address this knowledge gap by performing shotgun sequencing of community DNA from agricultural soils with a history of pesticide usage and profiling shifts in functional genes and microbial taxa abundance. Our results showed two distinct groups of soils defined by differing functional and taxonomic profiles. Degradation assays suggested that these groups corresponded to the organophosphorus degradation potential of soils, with the fastest degrading community being defined by increases in transport and nutrient cycling pathways and enzymes potentially involved in phosphorus metabolism. This was against a backdrop of taxonomic community shifts potentially related to contamination adaptation and reflecting the legacy of exposure. Overall our results highlight the value of using holistic system-wide metagenomic approaches as a tool to predict microbial degradation in the context of the ecology of contaminated habitats.

Oxidative potential of particulate matter 2.5 as predictive indicator of cellular stress

International Nuclear Information System (INIS)

Crobeddu, Bélinda; Aragao-Santiago, Leticia; Bui, Linh-Chi; Boland, Sonja; Baeza Squiban, Armelle

2017-01-01

Particulate air pollution being recognized to be responsible for short and long term health effects, regulations for particulate matter with an aerodynamic diameter less than 2.5 (PM 2.5 ) are more and more restrictive. PM 2.5 regulation is based on mass without taking into account PM 2.5 composition that drives toxicity. Measurement of the oxidative potential (OP) of PM could be an additional PM indicator that would encompass the PM components involved in oxidative stress, the main mechanism of PM toxicity. We compared different methods to evaluate the intrinsic oxidative potential of PM 2.5 sampled in Paris and their ability to reflect the oxidative and inflammatory response in bronchial epithelial cells used as relevant target organ cells. The dithiothreitol depletion assay, the antioxidant (ascorbic acid and glutathione) depletion assay (OP AO ), the plasmid scission assay and the dichlorofluorescein (DCFH) oxidation assay used to characterize the OP of PM 2.5 (10–100 μg/mL) provided positive results of different magnitude with all the PM 2.5 samples used with significant correlation with different metals such as Cu and Zn as well as total polyaromatic hydrocarbons and the soluble organic fraction. The OP AO assay showed the best correlation with the production of intracellular reactive oxygen species by NCI-H292 cell line assessed by DCFH oxidation and with the expression of anti-oxidant genes (superoxide dismutase 2, heme-oxygenase-1) as well as the proinflammatory response (Interleukin 6) when exposed from 1 to 10 μg/cm 2 . The OP AO assay appears as the most prone to predict the biological effect driven by PM 2.5 and related to oxidative stress. - Highlights: • 5 Acellular assays were used to compare the intrinsic oxidative potential (OP) of PM. • The amount of ROS generation in bronchial cells is particle dependent. • Particles induce the expression of anti-oxidant and proinflammatory genes. • Biological effects correlates with OP assay

Prediction of preservative sensitization potential using surface marker CD86 and/or CD54 expression on human cell line, THP-1.

Science.gov (United States)

Sakaguchi, Hitoshi; Miyazawa, Masaaki; Yoshida, Yukiko; Ito, Yuichi; Suzuki, Hiroyuki

2007-02-01

Preservatives are important components in many products, but have a history of purported allergy. Several assays [e.g., guinea pig maximization test (GPMT), local lymph node assay (LLNA)] are used to evaluate allergy potential of preservatives. We recently developed the human Cell Line Activation Test (h-CLAT), an in vitro skin sensitization test using human THP-1 cells. This test evaluates the augmentation of CD86 and CD54 expression, which are key events in the sensitization process, as an indicator of allergy following treatment with test chemical. Earlier, we found that a sub-toxic concentration was needed for the up-regulation of surface marker expression. In this study, we further evaluate the capability of h-CLAT to predict allergy potential using eight preservatives. Cytotoxicity was determined using propidium iodide with flow cytometry analysis and five doses that produce a 95, 85, 75, 65, and 50% cell viability were selected. If a material did not have any cytotoxicity at the highest technical dose (HTD), five doses are set using serial 1.3 dilutions of the HTD. The test materials used were six known allergic preservatives (e.g., methylchloroisothiazolinone/methylisothiazolinone, formaldehyde), and two non-allergic preservatives (methylparaben and 4-hydroxybenzoic acid). All allergic preservatives augmented CD86 and/or CD54 expression, indicating h-CLAT correctly identified the allergens. No augmentation was observed with the non-allergic preservatives; also correctly identified by h-CLAT. In addition, we report two threshold concentrations that may be used to categorize skin sensitization potency like the LLNA estimated concentration that yield a three-fold stimulation (EC3) value. These corresponding values are the estimated concentration which gives a relative fluorescence intensity (RFI) = 150 for CD86 and an RFI = 200 for CD54. These data suggest that h-CLAT, using THP-1 cells, may be able to predict the allergy potential of preservatives and

Application of a GIS-/remote sensing-based approach for predicting groundwater potential zones using a multi-criteria data mining methodology.

Science.gov (United States)

Mogaji, Kehinde Anthony; Lim, Hwee San

2017-07-01

This study integrates the application of Dempster-Shafer-driven evidential belief function (DS-EBF) methodology with remote sensing and geographic information system techniques to analyze surface and subsurface data sets for the spatial prediction of groundwater potential in Perak Province, Malaysia. The study used additional data obtained from the records of the groundwater yield rate of approximately 28 bore well locations. The processed surface and subsurface data produced sets of groundwater potential conditioning factors (GPCFs) from which multiple surface hydrologic and subsurface hydrogeologic parameter thematic maps were generated. The bore well location inventories were partitioned randomly into a ratio of 70% (19 wells) for model training to 30% (9 wells) for model testing. Application results of the DS-EBF relationship model algorithms of the surface- and subsurface-based GPCF thematic maps and the bore well locations produced two groundwater potential prediction (GPP) maps based on surface hydrologic and subsurface hydrogeologic characteristics which established that more than 60% of the study area falling within the moderate-high groundwater potential zones and less than 35% falling within the low potential zones. The estimated uncertainty values within the range of 0 to 17% for the predicted potential zones were quantified using the uncertainty algorithm of the model. The validation results of the GPP maps using relative operating characteristic curve method yielded 80 and 68% success rates and 89 and 53% prediction rates for the subsurface hydrogeologic factor (SUHF)- and surface hydrologic factor (SHF)-based GPP maps, respectively. The study results revealed that the SUHF-based GPP map accurately delineated groundwater potential zones better than the SHF-based GPP map. However, significant information on the low degree of uncertainty of the predicted potential zones established the suitability of the two GPP maps for future development of

Local and non-local potentials for deuteron elastic scattering

International Nuclear Information System (INIS)

Ramirez, J.A.

1976-01-01

The nucleon--nucleus local potential (central and spin--orbit) and the deuteron--nucleus nonlocal potential (central, spin--orbit, spin--radial tensor) are calculated by the folding-model (FM). Simple analytic expressions are obtained for the nucleon--nucleus potential by the use of Gaussians to represent the nucleon--nucleus potential and the charge and mass densities of the target. The analytic expressions give qualitative descriptions of phenomenological nucleon--nucleus interactions. A systematic target--mass dependence of realistic local FM deueron potentials is also included. Local-equivalent, energy-dependent, deuteron potentials are obtained from the nonlocal FM deuteron potentials and the energy dependence of the local potential parameters are presented. The local FM deuteron potential is tested for 60 Ni(d,d) 60 Ni at E/sub α/ = 15 MeV by comparing the predictions of the FM potentials with data in which all five polarization moments were measured. A qualitative fit to the data is obtained, but it overestimates the volume integral of the central potential by 7%. Energy-dependence effects are estimated by evaluating the local-equivalent potentials at E/sub α/ = 30 MeV and comparing the predictions to the E/sub α/ = 15 MeV potentials. The energy dependence of the central potential dominates the angular dependence of all five observables while the energy dependence of the spin--orbit and tensor potentials produces only scale changes (approx. 3%) in the vector and tensor analyzing powers. The scattering formalism for a spin-1 on a spin-0 target nucleus, and a description of the coupled--channels computer code DDUNC1 which treats the spin--radial tensor potential exactly, are included

Potential ecological risk assessment and prediction of soil heavy-metal pollution around coal gangue dump

Science.gov (United States)

Jiang, X.; Lu, W. X.; Zhao, H. Q.; Yang, Q. C.; Yang, Z. P.

2014-06-01

The aim of the present study is to evaluate the potential ecological risk and trend of soil heavy-metal pollution around a coal gangue dump in Jilin Province (Northeast China). The concentrations of Cd, Pb, Cu, Cr and Zn were monitored by inductively coupled plasma mass spectrometry (ICP-MS). The potential ecological risk index method developed by Hakanson (1980) was employed to assess the potential risk of heavy-metal pollution. The potential ecological risk in the order of ER(Cd) > ER(Pb) > ER(Cu) > ER(Cr) > ER(Zn) have been obtained, which showed that Cd was the most important factor leading to risk. Based on the Cd pollution history, the cumulative acceleration and cumulative rate of Cd were estimated, then the fixed number of years exceeding the standard prediction model was established, which was used to predict the pollution trend of Cd under the accelerated accumulation mode and the uniform mode. Pearson correlation analysis and correspondence analysis are employed to identify the sources of heavy metals and the relationship between sampling points and variables. These findings provided some useful insights for making appropriate management strategies to prevent or decrease heavy-metal pollution around a coal gangue dump in the Yangcaogou coal mine and other similar areas elsewhere.

In silico approach towards identification of potential inhibitors of Helicobacter pylori DapE.

Science.gov (United States)

Mandal, Rahul Shubhra; Das, Santasabuj

2015-01-01

Helicobacter pylori is a gastric mucosal pathogen and is associated with diseases like peptic ulcer and gastric cancer. To combat H. pylori infection, there is an urgent need for new class of antibiotics due to the emergence of drug-resistant strains. Enzymes involved in bacterial lysine biosynthetic pathways may be potential targets for antibacterial drug development, since lysine is an essential component of the bacterial peptidoglycan cell wall. No pathway exists for lysine biosynthesis in humans; hence, the inhibitors targeting bacterial enzymes may have selective toxicity. dapE-encoded N-succinyl-L,L-diaminopimelic acid desuccinylase (DapE) is a critical enzyme of this pathway and deletion of DapE gene is lethal to H. pylori, since the organism has no alternative pathway for lysine biosynthesis. In this study, we reported a 3D model structure of H. pylorie DapE, which consisted of a catalytic domain and a dimerization domain generated by MODELLER software. We also confirmed the stability of the modeled structure through 10 ns molecular dynamics simulation using GROMACS software. Next, to identify potential small molecule inhibitors of DapE, drug-like small molecule-screening library was generated. This was performed by Tanimoto-based similarity searching in the PubChem Database with DapE substrate L,L-SDAP as a query molecule, followed by fragment-based docking approach using GLIDE XP. This approach identified two potential substrate-competitive small molecule inhibitors of DapE. These new molecules may provide a starting point to search for novel therapeutics.

THE POTENTIAL OF THE EQUITY WORKING CAPITAL IN THE PREDICTION OF BANKRUPTCY

OpenAIRE

Daniel BRÎNDESCU – OLARIU

2014-01-01

The current study evaluates the potential of the equity working capital in predicting corporate bankruptcy. The population subjected to the analysis included all companies form Timis County (largest Romanian County) with yearly sales of over 10000 lei. The interest for the equity working capital was based on the recommendations of the literature, as well as on the availability of information concerning its values to all stakeholders. The event on which the research was focused was repr...

Evaluation of DNA variants associated with androgenetic alopecia and their potential to predict male pattern baldness.

Science.gov (United States)

Marcińska, Magdalena; Pośpiech, Ewelina; Abidi, Sarah; Andersen, Jeppe Dyrberg; van den Berge, Margreet; Carracedo, Ángel; Eduardoff, Mayra; Marczakiewicz-Lustig, Anna; Morling, Niels; Sijen, Titia; Skowron, Małgorzata; Söchtig, Jens; Syndercombe-Court, Denise; Weiler, Natalie; Schneider, Peter M; Ballard, David; Børsting, Claus; Parson, Walther; Phillips, Chris; Branicki, Wojciech

2015-01-01

Androgenetic alopecia, known in men as male pattern baldness (MPB), is a very conspicuous condition that is particularly frequent among European men and thus contributes markedly to variation in physical appearance traits amongst Europeans. Recent studies have revealed multiple genes and polymorphisms to be associated with susceptibility to MPB. In this study, 50 candidate SNPs for androgenetic alopecia were analyzed in order to verify their potential to predict MPB. Significant associations were confirmed for 29 SNPs from chromosomes X, 1, 5, 7, 18 and 20. A simple 5-SNP prediction model and an extended 20-SNP model were developed based on a discovery panel of 305 males from various European populations fitting one of two distinct phenotype categories. The first category consisted of men below 50 years of age with significant baldness and the second; men aged 50 years or older lacking baldness. The simple model comprised the five best predictors: rs5919324 near AR, rs1998076 in the 20p11 region, rs929626 in EBF1, rs12565727 in TARDBP and rs756853 in HDAC9. The extended prediction model added 15 SNPs from five genomic regions that improved overall prevalence-adjusted predictive accuracy measured by area under the receiver characteristic operating curve (AUC). Both models were evaluated for predictive accuracy using a test set of 300 males reflecting the general European population. Applying a 65% probability threshold, high prediction sensitivity of 87.1% but low specificity of 42.4% was obtained in men aged <50 years. In men aged ≥50, prediction sensitivity was slightly lower at 67.7% while specificity reached 90%. Overall, the AUC=0.761 calculated for men at or above 50 years of age indicates these SNPs offer considerable potential for the application of genetic tests to predict MPB patterns, adding a highly informative predictive system to the emerging field of forensic analysis of externally visible characteristics.

Evaluation of DNA variants associated with androgenetic alopecia and their potential to predict male pattern baldness.

Directory of Open Access Journals (Sweden)

Magdalena Marcińska

Full Text Available Androgenetic alopecia, known in men as male pattern baldness (MPB, is a very conspicuous condition that is particularly frequent among European men and thus contributes markedly to variation in physical appearance traits amongst Europeans. Recent studies have revealed multiple genes and polymorphisms to be associated with susceptibility to MPB. In this study, 50 candidate SNPs for androgenetic alopecia were analyzed in order to verify their potential to predict MPB. Significant associations were confirmed for 29 SNPs from chromosomes X, 1, 5, 7, 18 and 20. A simple 5-SNP prediction model and an extended 20-SNP model were developed based on a discovery panel of 305 males from various European populations fitting one of two distinct phenotype categories. The first category consisted of men below 50 years of age with significant baldness and the second; men aged 50 years or older lacking baldness. The simple model comprised the five best predictors: rs5919324 near AR, rs1998076 in the 20p11 region, rs929626 in EBF1, rs12565727 in TARDBP and rs756853 in HDAC9. The extended prediction model added 15 SNPs from five genomic regions that improved overall prevalence-adjusted predictive accuracy measured by area under the receiver characteristic operating curve (AUC. Both models were evaluated for predictive accuracy using a test set of 300 males reflecting the general European population. Applying a 65% probability threshold, high prediction sensitivity of 87.1% but low specificity of 42.4% was obtained in men aged <50 years. In men aged ≥50, prediction sensitivity was slightly lower at 67.7% while specificity reached 90%. Overall, the AUC=0.761 calculated for men at or above 50 years of age indicates these SNPs offer considerable potential for the application of genetic tests to predict MPB patterns, adding a highly informative predictive system to the emerging field of forensic analysis of externally visible characteristics.

Predictable patterns of the May-June rainfall anomaly over East Asia

Science.gov (United States)

Xing, Wen; Wang, Bin; Yim, So-Young; Ha, Kyung-Ja

2017-02-01

During early summer (May-June, MJ), East Asia (EA) subtropical front is a defining feature of Asian monsoon, which produces the most prominent precipitation band in the global subtropics. Here we show that dynamical prediction of early summer EA (20°N-45°N, 100°E-130°E) rainfall made by four coupled climate models' ensemble hindcast (1979-2010) yields only a moderate skill and cannot be used to estimate predictability. The present study uses an alternative, empirical orthogonal function (EOF)-based physical-empirical (P-E) model approach to predict rainfall anomaly pattern and estimate its potential predictability. The first three leading modes are physically meaningful and can be, respectively, attributed to (a) the interaction between the anomalous western North Pacific subtropical high and underlying Indo-Pacific warm ocean, (b) the forcing associated with North Pacific sea surface temperature (SST) anomaly, and (c) the development of equatorial central Pacific SST anomalies. A suite of P-E models is established to forecast the first three leading principal components. All predictors are 0 month ahead of May, so the prediction here is named as a 0 month lead prediction. The cross-validated hindcast results demonstrate that these modes may be predicted with significant temporal correlation skills (0.48-0.72). Using the predicted principal components and the corresponding EOF patterns, the total MJ rainfall anomaly was hindcasted for the period of 1979-2015. The time-mean pattern correlation coefficient (PCC) score reaches 0.38, which is significantly higher than dynamical models' multimodel ensemble skill (0.21). The estimated potential maximum attainable PCC is around 0.65, suggesting that the dynamical prediction models may have large rooms to improve. Limitations and future work are discussed.

Dropout Prediction in E-Learning Courses through the Combination of Machine Learning Techniques

Science.gov (United States)

Lykourentzou, Ioanna; Giannoukos, Ioannis; Nikolopoulos, Vassilis; Mpardis, George; Loumos, Vassili

2009-01-01

In this paper, a dropout prediction method for e-learning courses, based on three popular machine learning techniques and detailed student data, is proposed. The machine learning techniques used are feed-forward neural networks, support vector machines and probabilistic ensemble simplified fuzzy ARTMAP. Since a single technique may fail to…

Oxygen Dependent Biocatalytic Processes

DEFF Research Database (Denmark)

Pedersen, Asbjørn Toftgaard

Enzyme catalysts have the potential to improve both the process economics and the environ-mental profile of many oxidation reactions especially in the fine- and specialty-chemical industry, due to their exquisite ability to perform stereo-, regio- and chemo-selective oxida-tions at ambient...... to aldehydes and ketones, oxyfunctionalization of C-H bonds, and epoxidation of C-C double bonds. Although oxygen dependent biocatalysis offers many possibilities, there are numerous chal-lenges to be overcome before an enzyme can be implemented in an industrial process. These challenges requires the combined...... far below their potential maximum catalytic rate at industrially relevant oxygen concentrations. Detailed knowledge of the en-zyme kinetics are therefore required in order to determine the best operating conditions and design oxygen supply to minimize processing costs. This is enabled...

Potential Distribution Predicted for Rhynchophorus ferrugineus in China under Different Climate Warming Scenarios.

Directory of Open Access Journals (Sweden)

Xuezhen Ge

Full Text Available As the primary pest of palm trees, Rhynchophorus ferrugineus (Olivier (Coleoptera: Curculionidae has caused serious harm to palms since it first invaded China. The present study used CLIMEX 1.1 to predict the potential distribution of R. ferrugineus in China according to both current climate data (1981-2010 and future climate warming estimates based on simulated climate data for the 2020s (2011-2040 provided by the Tyndall Center for Climate Change Research (TYN SC 2.0. Additionally, the Ecoclimatic Index (EI values calculated for different climatic conditions (current and future, as simulated by the B2 scenario were compared. Areas with a suitable climate for R. ferrugineus distribution were located primarily in central China according to the current climate data, with the northern boundary of the distribution reaching to 40.1°N and including Tibet, north Sichuan, central Shaanxi, south Shanxi, and east Hebei. There was little difference in the potential distribution predicted by the four emission scenarios according to future climate warming estimates. The primary prediction under future climate warming models was that, compared with the current climate model, the number of highly favorable habitats would increase significantly and expand into northern China, whereas the number of both favorable and marginally favorable habitats would decrease. Contrast analysis of EI values suggested that climate change and the density of site distribution were the main effectors of the changes in EI values. These results will help to improve control measures, prevent the spread of this pest, and revise the targeted quarantine areas.

Can nutrient status of four woody plant species be predicted using field spectrometry?

NARCIS (Netherlands)

Ferwerda, J.G.; Skidmore, A.K.

2007-01-01

This paper demonstrates the potential of hyperspectral remote sensing to predict the chemical composition (i.e., nitrogen, phosphorous, calcium, potassium, sodium, and magnesium) of three tree species (i.e., willow, mopane and olive) and one shrub species (i.e., heather). Reflectance spectra,

Campylobacter fetus subspecies: Comparative genomics and prediction of potential virulence targets

DEFF Research Database (Denmark)

Ali, Amjad; Soares, Siomar C.; Santos, Anderson R.

2012-01-01

. The potential candidate factors identified for attenuation and/or subunit vaccine development against C. fetus subspecies contain: nucleoside diphosphate kinase (Ndk), type IV secretion systems (T4SS), outer membrane proteins (OMP), substrate binding proteins CjaA and CjaC, surface array proteins, sap gene......, and cytolethal distending toxin (CDT). Significantly, many of those genes were found in genomic regions with signals of horizontal gene transfer and, therefore, predicted as putative pathogenicity islands. We found CRISPR loci and dam genes in an island specific for C. fetus subsp. fetus, and T4SS and sap genes...

Predicting high risk of exacerbations in bronchiectasis: the E-FACED score

Directory of Open Access Journals (Sweden)

Martinez-Garcia MA

2017-01-01

Full Text Available Martinez-Garcia MA,1,2 Athanazio RA,3 Girón R,4 Máiz-Carro L,5 de la Rosa D,6 Olveira C,7 de Gracia J,2,8 Vendrell M,9 Prados-Sánchez C,10 Gramblicka G,11 Corso Pereira M,12 Lundgren FL,13 Fernandes De Figueiredo M,14 Arancibia F,15 Rached SZ3 1Pulmonary Service, Polytechnic and University La Fe Hospital, Valencia, Spain; 2CIBERes, CIBER de Enfermedades Respiratorias. Madrid. Spain; 3Pulmonary Division, Heart Institute (Incor, Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo; 4Pneumology Service, Hospital La Princesa, 5Pneumology Service, Hospital Ramón y Cajal, Madrid, 6Pneumology Unit, Hospital Plató, Barcelona, 7Pneumology, Málaga Regional University Hospital, Instituto de Biomedicina de Málaga (IBIMA, Málaga University, Spain; 8Pneumology Service, Hospital Vall d’Hebron, Barcelona, 9Bronchiectasis Group IDIBGI, Dr. Trueta University Hospital. UdG. Ciberes CB06/06/0030, 10Unidad de Fibrosis Quística y Bronquiectasias. Hospital Universitario La Paz. Madrid. Spain; 11Pneumology Service, Hospital del Tórax Dr A Cetrángolo, Buenos Aires, Argentina; 12Pneumology Service, Universidade Estadual de Campinas UNICAMP, Sao Paulo, 13Pneumology Service, Hospital Octávio de Freitas, Recife, 14Pneumology Service, Hospital de Messejana, Fortaleza, Brazil; 15Pneumology Service, Instituto Nacional del Tórax, Santiago de Chile, Chile Background: Although the FACED score has demonstrated a great prognostic capacity in bronchiectasis, it does not include the number or severity of exacerbations as a separate variable, which is important in the natural history of these patients.Objective: Construction and external validation of a new index, the E-FACED, to evaluate the predictive capacity of exacerbations and mortality.Methods: The new score was constructed on the basis of the complete cohort for the construction of the original FACED score, while the external validation was undertaken with six cohorts from three

Ab initio optical potentials applied to low-energy e-H2 and e-N2 collisions in the linear-algebraic approach

International Nuclear Information System (INIS)

Schneider, B.I.; Collins, L.A.

1983-01-01

We propose a method for constructing an effective optical potential through which correlation effects can be introduced into the electron-molecule scattering formulation. The optical potential is based on a nonperturbative, Feshbach projection-operator procedure and is evaluated on an L 2 basis. The optical potential is incorporated into the scattering equations by means of a separable expansion, and the resulting scattering equations are solved by a linear-algebraic method based on the integral-equation formulation. We report the results of scattering calculations, which include polarization effects, for low-energy e-H 2 and e-N 2 collisions. The agreement with other theoretical and with experimental results is quite good

Progastrin: a potential predictive marker of liver metastasis in colorectal cancer.

Science.gov (United States)

Westwood, David A; Patel, Oneel; Christophi, Christopher; Shulkes, Arthur; Baldwin, Graham S

2017-07-01

Staging of colorectal cancer often fails to discriminate outcomes of patients with morphologically similar tumours that exhibit different clinical behaviours. Data from several studies suggest that the gastrin family of growth factors potentiates colorectal cancer tumourigenesis. The aim of this study was to investigate whether progastrin expression may predict clinical outcome in colorectal cancer. Patients with colorectal adenocarcinoma of identical depth of invasion who had not received neoadjuvant therapy were included. The patients either had stage IIa disease with greater than 3-year disease-free survival without adjuvant therapy or stage IV disease with liver metastases on staging CT. Progastrin expression in tumour sections was scored with reference to the intensity and area of immunohistochemical staining. Progastrin expression by stage IV tumours was significantly greater than stage IIa tumours with mean progastrin immunopositivity scores of 2.1 ± 0.2 versus 0.5 ± 0.2, respectively (P colorectal cancer and supports its clinical relevance and potential use as a biomarker.

TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models

Science.gov (United States)

Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng

2016-05-01

Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com.

TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models.

Science.gov (United States)

Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng

2016-05-01

Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com .

Potential clinical and economic effects of homocyst(e)ine lowering.

Science.gov (United States)

Nallamothu, B K; Fendrick, A M; Rubenfire, M; Saint, S; Bandekar, R R; Omenn, G S

Elevated total homocyst(e)ine levels (>/=11 micromol/L) have been identified as a potential risk factor for coronary heart disease. However, the benefits expected from lowering homocyst(e)ine levels with folic acid and vitamin B(12) supplementation have yet to be demonstrated in clinical trials. We constructed a decision analytic model to estimate the clinical benefits and economic costs of 2 homocyst(e)ine-lowering strategies: (1) "treat all"-no screening, daily supplementation with folic acid (400 microg) and vitamin B(12) (cyanocobalamin; 500 microg) for all; (2) "screen and treat"-screening, followed by daily supplementation with folic acid and vitamin B(12) for individuals with elevated homocyst(e)ine levels. Simulated cohorts of 40-year-old men and 50-year-old women in the general population were evaluated. In the base-case analysis, we assumed that lowering elevated levels would reduce excess coronary heart disease risk by 40%; however, this assumption and others were evaluated across a broad range of potential values using sensitivity analysis. Primary outcomes were discounted costs per life-year saved. Although the treat-all strategy was slightly more effective overall, the screen and treat strategy resulted in a much lower cost per life-year saved ($13,600 in men and $27,500 in women) when compared with no intervention. Incremental cost-effectiveness ratios for the treat-all strategy compared with the screen and treat strategy were more than $500,000 per life-year saved in both cohorts. Sensitivity analysis showed that cost-effectiveness ratios for the screen and treat strategy remained less than $50,000 per life-year saved under several unfavorable scenarios, such as when effective homocyst(e)ine lowering was assumed to reduce the relative risk of coronary heart disease-related death by only 11% in men or 23% in women. Homocyst(e)ine lowering with folic acid and vitamin B(12) supplementation could result in substantial clinical benefits at reasonable

Psychophysiological prediction of choice: relevance to insight and drug addiction

Science.gov (United States)

Moeller, Scott J.; Hajcak, Greg; Parvaz, Muhammad A.; Dunning, Jonathan P.; Volkow, Nora D.

2012-01-01

An important goal of addiction research and treatment is to predict behavioural responses to drug-related stimuli. This goal is especially important for patients with impaired insight, which can interfere with therapeutic interventions and potentially invalidate self-report questionnaires. This research tested (i) whether event-related potentials, specifically the late positive potential, predict choice to view cocaine images in cocaine addiction; and (ii) whether such behaviour prediction differs by insight (operationalized in this study as self-awareness of image choice). Fifty-nine cocaine abusers and 32 healthy controls provided data for the following laboratory components that were completed in a fixed-sequence (to establish prediction): (i) event-related potential recordings while passively viewing pleasant, unpleasant, neutral and cocaine images, during which early (400–1000 ms) and late (1000–2000 ms) window late positive potentials were collected; (ii) self-reported arousal ratings for each picture; and (iii) two previously validated tasks: one to assess choice for viewing these same images, and the other to group cocaine abusers by insight. Results showed that pleasant-related late positive potentials and arousal ratings predicted pleasant choice (the choice to view pleasant pictures) in all subjects, validating the method. In the cocaine abusers, the predictive ability of the late positive potentials and arousal ratings depended on insight. Cocaine-related late positive potentials better predicted cocaine image choice in cocaine abusers with impaired insight. Another emotion-relevant event-related potential component (the early posterior negativity) did not show these results, indicating specificity of the late positive potential. In contrast, arousal ratings better predicted respective cocaine image choice (and actual cocaine use severity) in cocaine abusers with intact insight. Taken together, the late positive potential could serve as a biomarker

E-bike trials’ potential to promote sustained changes in car owners mobility habits

Science.gov (United States)

Moser, Corinne; Blumer, Yann; Lena Hille, Stefanie

2018-04-01

Modal shifts hold considerable potential to mitigate carbon emissions. Electric bikes (e-bikes) represent a promising energy- and carbon-efficient alternative to cars. However, as mobility behaviour is highly habitual, convincing people to switch from cars to e-bikes is challenging. One strategy to accomplish this is the disruption of existing habits—a key idea behind an annual e-bike promotion programme in Switzerland, in which car owners can try out an e-bike for free over a two-week period in exchange for their car keys. By means of a longitudinal survey, we measured the long-term effects of this trial on mobility-related habitual associations. After one year, participants’ habitual association with car use had weakened significantly. This finding was valid both for participants who bought an e-bike after the trial and those who did not. Our findings contrast the results of other studies who find that the effect of interventions to induce modal shifts wears off over time. We conclude that an e-bike trial has the potential to break mobility habits and motivate car owners to use more sustainable means of transport.

The potential of continuous, local atomic clock measurements for earthquake prediction and volcanology

Directory of Open Access Journals (Sweden)

Bondarescu Mihai

2015-01-01

Full Text Available Modern optical atomic clocks along with the optical fiber technology currently being developed can measure the geoid, which is the equipotential surface that extends the mean sea level on continents, to a precision that competes with existing technology. In this proceeding, we point out that atomic clocks have the potential to not only map the sea level surface on continents, but also look at variations of the geoid as a function of time with unprecedented timing resolution. The local time series of the geoid has a plethora of applications. These include potential improvement in the predictions of earthquakes and volcanoes, and closer monitoring of ground uplift in areas where hydraulic fracturing is performed.

Potential of the octanol-water partition coefficient (logP) to predict the dermal penetration behaviour of amphiphilic compounds in aqueous solutions.

Science.gov (United States)

Korinth, Gintautas; Wellner, Tanja; Schaller, Karl Heinz; Drexler, Hans

2012-11-23

Aqueous amphiphilic compounds may exhibit enhanced skin penetration compared with neat compounds. Conventional models do not predict this percutaneous penetration behaviour. We investigated the potential of the octanol-water partition coefficient (logP) to predict dermal fluxes for eight compounds applied neat and as 50% aqueous solutions in diffusion cell experiments using human skin. Data for seven other compounds were accessed from literature. In total, seven glycol ethers, three alcohols, two glycols, and three other chemicals were considered. Of these 15 compounds, 10 penetrated faster through the skin as aqueous solutions than as neat compounds. The other five compounds exhibited larger fluxes as neat applications. For 13 of the 15 compounds, a consistent relationship was identified between the percutaneous penetration behaviour and the logP. Compared with the neat applications, positive logP were associated with larger fluxes for eight of the diluted compounds, and negative logP were associated with smaller fluxes for five of the diluted compounds. Our study demonstrates that decreases or enhancements in dermal penetration upon aqueous dilution can be predicted for many compounds from the sign of logP (i.e., positive or negative). This approach may be suitable as a first approximation in risk assessments of dermal exposure. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Phylogenomic detection and functional prediction of genes potentially important for plant meiosis.

Science.gov (United States)

Zhang, Luoyan; Kong, Hongzhi; Ma, Hong; Yang, Ji

2018-02-15

Meiosis is a specialized type of cell division necessary for sexual reproduction in eukaryotes. A better understanding of the cytological procedures of meiosis has been achieved by comprehensive cytogenetic studies in plants, while the genetic mechanisms regulating meiotic progression remain incompletely understood. The increasing accumulation of complete genome sequences and large-scale gene expression datasets has provided a powerful resource for phylogenomic inference and unsupervised identification of genes involved in plant meiosis. By integrating sequence homology and expression data, 164, 131, 124 and 162 genes potentially important for meiosis were identified in the genomes of Arabidopsis thaliana, Oryza sativa, Selaginella moellendorffii and Pogonatum aloides, respectively. The predicted genes were assigned to 45 meiotic GO terms, and their functions were related to different processes occurring during meiosis in various organisms. Most of the predicted meiotic genes underwent lineage-specific duplication events during plant evolution, with about 30% of the predicted genes retaining only a single copy in higher plant genomes. The results of this study provided clues to design experiments for better functional characterization of meiotic genes in plants, promoting the phylogenomic approach to the evolutionary dynamics of the plant meiotic machineries. Copyright © 2017 Elsevier B.V. All rights reserved.

Prediction of e± elastic scattering cross-section ratio based on phenomenological two-photon exchange corrections

Science.gov (United States)

Qattan, I. A.

2017-06-01

I present a prediction of the e± elastic scattering cross-section ratio, Re+e-, as determined using a new parametrization of the two-photon exchange (TPE) corrections to electron-proton elastic scattering cross section σR. The extracted ratio is compared to several previous phenomenological extractions, TPE hadronic calculations, and direct measurements from the comparison of electron and positron scattering. The TPE corrections and the ratio Re+e- show a clear change of sign at low Q2, which is necessary to explain the high-Q2 form factors discrepancy while being consistent with the known Q2→0 limit. While my predictions are in generally good agreement with previous extractions, TPE hadronic calculations, and existing world data including the recent two measurements from the CLAS and VEPP-3 Novosibirsk experiments, they are larger than the new OLYMPUS measurements at larger Q2 values.

Methodology developed to make the Quebec indoor radon potential map

International Nuclear Information System (INIS)

Drolet, Jean-Philippe; Martel, Richard; Poulin, Patrick; Dessau, Jean-Claude

2014-01-01

This paper presents a relevant approach to predict the indoor radon potential based on the combination of the radiogeochemical data and the indoor radon measurements in the Quebec province territory (Canada). The Quebec ministry of health asked for such a map to identify the radon-prone areas to manage the risk for the population related to indoor radon exposure. Three radiogeochemical criteria including (1) equivalent uranium (eU) concentration from airborne surface gamma-ray surveys, (2) uranium concentration measurements in sediments, (3) bedrock and surficial geology were combined with 3082 basement radon concentration measurements to identify the radon-prone areas. It was shown that it is possible to determine thresholds for the three criteria that implied statistically significant different levels of radon potential using Kruskal–Wallis one way analyses of variance by ranks. The three discretized radiogeochemical datasets were combined into a total predicted radon potential that sampled 98% of the studied area. The combination process was also based on Kruskal–Wallis one way ANOVA. Four statistically significant different predicted radon potential levels were created: low, medium, high and very high. Respectively 10 and 13% of the dwellings exceed the Canadian radon guideline of 200 Bq/m 3 in low and medium predicted radon potentials. These proportions rise up to 22 and 45% respectively for high and very high predicted radon potentials. This predictive map of indoor radon potential based on the radiogeochemical data was validated using a map of confirmed radon exposure in homes based on the basement radon measurements. It was shown that the map of predicted radon potential based on the radiogeochemical data was reliable to identify radon-prone areas even in zones where no indoor radon measurement exists. - Highlights: • 5 radiogeochemical datasets were used to map the geogenic indoor radon potential. • An indoor radon potential was determined for each

Testing predictions of the quantum landscape multiverse 1: the Starobinsky inflationary potential

Science.gov (United States)

Di Valentino, Eleonora; Mersini-Houghton, Laura

2017-03-01

The 2015 Planck data release has placed tight constraints on the allowed class of inflationary models. The current data favors concave downwards inflationary potentials while offering interesting hints on possible deviations from the standard picture of CMB perturbations. We here test the predictions of the theory of the origin of the universe from the landscape multiverse, against the most recent Planck data, for the case of concave downwards inflationary potentials, such as the Starobinsky model of inflation. By considering the quantum entanglement correction of the multiverse, we can place a lower limit on the local `SUSY breaking' scale b > 1.2 × 107 GeV at 95% c.l. from Planck TT+lowTEB. We find that this limit is consistent with the range for b that allows the landscape multiverse to explain a serie of anomalies present in the current data.

The potential predictability of fire danger provided by ECMWF forecast

Science.gov (United States)

Di Giuseppe, Francesca

2017-04-01

The European Forest Fire Information System (EFFIS), is currently being developed in the framework of the Copernicus Emergency Management Services to monitor and forecast fire danger in Europe. The system provides timely information to civil protection authorities in 38 nations across Europe and mostly concentrates on flagging regions which might be at high danger of spontaneous ignition due to persistent drought. The daily predictions of fire danger conditions are based on the US Forest Service National Fire Danger Rating System (NFDRS), the Canadian forest service Fire Weather Index Rating System (FWI) and the Australian McArthur (MARK-5) rating systems. Weather forcings are provided in real time by the European Centre for Medium range Weather Forecasts (ECMWF) forecasting system. The global system's potential predictability is assessed using re-analysis fields as weather forcings. The Global Fire Emissions Database (GFED4) provides 11 years of observed burned areas from satellite measurements and is used as a validation dataset. The fire indices implemented are good predictors to highlight dangerous conditions. High values are correlated with observed fire and low values correspond to non observed events. A more quantitative skill evaluation was performed using the Extremal Dependency Index which is a skill score specifically designed for rare events. It revealed that the three indices were more skilful on a global scale than the random forecast to detect large fires. The performance peaks in the boreal forests, in the Mediterranean, the Amazon rain-forests and southeast Asia. The skill-scores were then aggregated at country level to reveal which nations could potentiallty benefit from the system information in aid of decision making and fire control support. Overall we found that fire danger modelling based on weather forecasts, can provide reasonable predictability over large parts of the global landmass.

Awareness of eSafety and Potential Online Dangers among Children and Teenagers

Directory of Open Access Journals (Sweden)

Gila Cohen Zilka

2017-09-01

Background\tThe study examined eSafety among children and teenagers from their own perspectives, through evaluations of their awareness level of eSafety and of potential online dangers. Methodology: This is a mixed-method study with both quantitative and qualitative elements. The study includes questionnaires and interviews. A total of 345 participants from Israel completed questionnaires; 90 children and teenagers were interviewed from among the participants. Contribution: The study examined the awareness of children and youths of safe online surfing. It also examined the degree of exposure of children and youths to positive and negative aspects of the Internet. This study illustrates the dual potential of Internet use within the context of eSafety, as seen through the eyes of children and teenagers. Characteristics of use of the Internet are liable to increase the danger to and the bullying of youths and by youths in the digital domain. It also demonstrates the promises of using the Internet for productive learning and leisure activities. Findings: Findings show that the children and teenagers who participated in the study reported a medium-high level of awareness. Issues that participants were concerned about included avoiding contact with strangers and cyberbullying, not necessarily by strangers, but also by friends. Recommendations for Practitioners\t: It is important to examine how children perceive online events for the purpose of examining their statements regarding eSafety and the way they view problematic or dangerous online events, as well as how they believe they can cope with them. Recommendation for Researchers: The study recommends incorporating in future studies individual case studies and allowing participants to express how they perceive complex online situations. Impact on Society: This study illustrates the dual potential, positive and negative aspects, of Internet use within the context of eSafety, as seen through the eyes of children and

Prediction of hospital mortality by changes in the estimated glomerular filtration rate (eGFR).

LENUS (Irish Health Repository)

Berzan, E

2015-03-01

Deterioration of physiological or laboratory variables may provide important prognostic information. We have studied whether a change in estimated glomerular filtration rate (eGFR) value calculated using the (Modification of Diet in Renal Disease (MDRD) formula) over the hospital admission, would have predictive value. An analysis was performed on all emergency medical hospital episodes (N = 61964) admitted between 1 January 2002 and 31 December 2011. A stepwise logistic regression model examined the relationship between mortality and change in renal function from admission to discharge. The fully adjusted Odds Ratios (OR) for 5 classes of GFR deterioration showed a stepwise increased risk of 30-day death with OR\\'s of 1.42 (95% CI: 1.20, 1.68), 1.59 (1.27, 1.99), 2.71 (2.24, 3.27), 5.56 (4.54, 6.81) and 11.9 (9.0, 15.6) respectively. The change in eGFR during a clinical episode, following an emergency medical admission, powerfully predicts the outcome.

The predictive value of ePAQ in the urodynamic diagnoses-A prospective cohort study.

Science.gov (United States)

McCooty, Shanteela; Nightingale, Peter; Latthe, Pallavi

2018-01-01

To assess whether the electronic Personal Assessment Questionnaire-Pelvic Floor (ePAQ-PF) had accuracy in predicting the urodynamic diagnoses of Detrusor Overactivity (DO) and/or Urodynamic Stress Incontinence (USI). Tertiary urogynaecology unit linked to an academic university teaching hospital. Consecutive women who presented with lower urinary tract symptoms (LUTS) and were booked to have urodynamic studies. Women completed an ePAQ-PF prior to having urodynamics (UDS) by clinicians who were blinded to the ePAQ-PF results while conducting this procedure. Receiver Operating Characteristics (ROC) curves were constructed for predictive accuracy of overactive bladder (OAB) score in DO and of stress urinary incontinence (SUI) score in USI. Prospective cohort study designed to meet the requirements of the standards for reporting of diagnostic accuracy (STARD). 390 women with a mean age of 54.2 (range 21-92) years were recruited. The majority (n = 294; 75%) were White Caucasian and had two children (n = 157; 40.3%). Of them, 67.2% (n = 262) had DO and USI was confirmed in 21.5% (n = 84). The area under the ROC curve for DO was 0.704 (95% confidence interval 0.650-0.759) and for USI it was 0.731 (95% confidence interval 0.652-0.778). The OAB and SUI scores on the ePAQ-PF demonstrated that they are fair predictors in diagnosing DO and USI. As the OAB and SUI score on ePAQ-PF increased so did the likelihood of DO (up to a score of 75) and USI on UDS. © 2017 Wiley Periodicals, Inc.

Genomic Prediction of Gene Bank Wheat Landraces

Directory of Open Access Journals (Sweden)

José Crossa

2016-07-01

Full Text Available This study examines genomic prediction within 8416 Mexican landrace accessions and 2403 Iranian landrace accessions stored in gene banks. The Mexican and Iranian collections were evaluated in separate field trials, including an optimum environment for several traits, and in two separate environments (drought, D and heat, H for the highly heritable traits, days to heading (DTH, and days to maturity (DTM. Analyses accounting and not accounting for population structure were performed. Genomic prediction models include genotype × environment interaction (G × E. Two alternative prediction strategies were studied: (1 random cross-validation of the data in 20% training (TRN and 80% testing (TST (TRN20-TST80 sets, and (2 two types of core sets, “diversity” and “prediction”, including 10% and 20%, respectively, of the total collections. Accounting for population structure decreased prediction accuracy by 15–20% as compared to prediction accuracy obtained when not accounting for population structure. Accounting for population structure gave prediction accuracies for traits evaluated in one environment for TRN20-TST80 that ranged from 0.407 to 0.677 for Mexican landraces, and from 0.166 to 0.662 for Iranian landraces. Prediction accuracy of the 20% diversity core set was similar to accuracies obtained for TRN20-TST80, ranging from 0.412 to 0.654 for Mexican landraces, and from 0.182 to 0.647 for Iranian landraces. The predictive core set gave similar prediction accuracy as the diversity core set for Mexican collections, but slightly lower for Iranian collections. Prediction accuracy when incorporating G × E for DTH and DTM for Mexican landraces for TRN20-TST80 was around 0.60, which is greater than without the G × E term. For Iranian landraces, accuracies were 0.55 for the G × E model with TRN20-TST80. Results show promising prediction accuracies for potential use in germplasm enhancement and rapid introgression of exotic germplasm

Making detailed predictions makes (some) predictions worse

Science.gov (United States)

Kelly, Theresa F.

In this paper, we investigate whether making detailed predictions about an event makes other predictions worse. Across 19 experiments, 10,895 participants, and 415,960 predictions about 724 professional sports games, we find that people who made detailed predictions about sporting events (e.g., how many hits each baseball team would get) made worse predictions about more general outcomes (e.g., which team would win). We rule out that this effect is caused by inattention or fatigue, thinking too hard, or a differential reliance on holistic information about the teams. Instead, we find that thinking about game-relevant details before predicting winning teams causes people to give less weight to predictive information, presumably because predicting details makes information that is relatively useless for predicting the winning team more readily accessible in memory and therefore incorporated into forecasts. Furthermore, we show that this differential use of information can be used to predict what kinds of games will and will not be susceptible to the negative effect of making detailed predictions.

Computer models versus reality: how well do in silico models currently predict the sensitization potential of a substance.

Science.gov (United States)

Teubner, Wera; Mehling, Anette; Schuster, Paul Xaver; Guth, Katharina; Worth, Andrew; Burton, Julien; van Ravenzwaay, Bennard; Landsiedel, Robert

2013-12-01

National legislations for the assessment of the skin sensitization potential of chemicals are increasingly based on the globally harmonized system (GHS). In this study, experimental data on 55 non-sensitizing and 45 sensitizing chemicals were evaluated according to GHS criteria and used to test the performance of computer (in silico) models for the prediction of skin sensitization. Statistic models (Vega, Case Ultra, TOPKAT), mechanistic models (Toxtree, OECD (Q)SAR toolbox, DEREK) or a hybrid model (TIMES-SS) were evaluated. Between three and nine of the substances evaluated were found in the individual training sets of various models. Mechanism based models performed better than statistical models and gave better predictivities depending on the stringency of the domain definition. Best performance was achieved by TIMES-SS, with a perfect prediction, whereby only 16% of the substances were within its reliability domain. Some models offer modules for potency; however predictions did not correlate well with the GHS sensitization subcategory derived from the experimental data. In conclusion, although mechanistic models can be used to a certain degree under well-defined conditions, at the present, the in silico models are not sufficiently accurate for broad application to predict skin sensitization potentials. Copyright © 2013 Elsevier Inc. All rights reserved.

A catchment-scale model to predict spatial and temporal burden of E. coli on pasture from grazing livestock.

Science.gov (United States)

Oliver, David M; Bartie, Phil J; Louise Heathwaite, A; Reaney, Sim M; Parnell, Jared A Q; Quilliam, Richard S

2018-03-01

Effective management of diffuse microbial water pollution from agriculture requires a fundamental understanding of how spatial patterns of microbial pollutants, e.g. E. coli, vary over time at the landscape scale. The aim of this study was to apply the Visualising Pathogen &Environmental Risk (ViPER) model, developed to predict E. coli burden on agricultural land, in a spatially distributed manner to two contrasting catchments in order to map and understand changes in E. coli burden contributed to land from grazing livestock. The model was applied to the River Ayr and Lunan Water catchments, with significant correlations observed between area of improved grassland and the maximum total E. coli per 1km 2 grid cell (Ayr: r=0.57; pE. coli burden between seasons in both catchments, with summer and autumn predicted to accrue higher E. coli contributions relative to spring and winter (PE. coli loading to land as driven by stocking density and livestock grazing regimes. Resulting risk maps therefore provide the underpinning evidence to inform spatially-targeted decision-making with respect to managing sources of E. coli in agricultural environments. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

QCD studies and discoveries with e{sup + }e{sup - } colliders and future perspectives

Energy Technology Data Exchange (ETDEWEB)

Lange, Jens Soeren, E-mail: soeren.lange@exp2.physik.uni-giessen.de [Justus-Liebig-Universitaet Giessen, II. Physikalisches Institut (Germany); Collaboration: Belle Collaboration

2013-03-15

Observations of new charmonium(-like) and bottomonium(-like) states (sometimes refered to as 'XYZ' states) at e{sup + }e{sup - } colliders have changed our picture of quarkonia systems as QCD bound states. Potential models with a linear confinement ansatz, which were able to predict many conventional states with an accuracy of {approx}1 MeV, absolutely fail in describing many of the new states. Symmetries play an important role e.g. in the determination of the quantum numbers (such as charge conjugation in the radiative decays) or in trying to explain surprising properties such as isospin violation.

Tablet computers and eBooks. Unlocking the potential for personal learning environments?

NARCIS (Netherlands)

Kalz, Marco

2012-01-01

Kalz, M. (2012, 9 May). Tablet computers and eBooks. Unlocking the potential for personal learning environments? Invited presentation during the annual conference of the European Association for Distance Learning (EADL), Noordwijkerhout, The Netherlands.

Testing predictions of the quantum landscape multiverse 1: the Starobinsky inflationary potential

International Nuclear Information System (INIS)

Valentino, Eleonora Di; Mersini-Houghton, Laura

2017-01-01

The 2015 Planck data release has placed tight constraints on the allowed class of inflationary models. The current data favors concave downwards inflationary potentials while offering interesting hints on possible deviations from the standard picture of CMB perturbations. We here test the predictions of the theory of the origin of the universe from the landscape multiverse, against the most recent Planck data, for the case of concave downwards inflationary potentials, such as the Starobinsky model of inflation. By considering the quantum entanglement correction of the multiverse, we can place a lower limit on the local 'SUSY breaking' scale b > 1.2 × 10 7 GeV at 95% c.l. from Planck TT+lowTEB. We find that this limit is consistent with the range for b that allows the landscape multiverse to explain a serie of anomalies present in the current data.

Testing predictions of the quantum landscape multiverse 1: the Starobinsky inflationary potential

Energy Technology Data Exchange (ETDEWEB)

Valentino, Eleonora Di [Institut d' Astrophysique de Paris (UMR7095: CNRS and UPMC-Sorbonne Universities), F-75014, Paris (France); Mersini-Houghton, Laura, E-mail: valentin@iap.fr, E-mail: mersini@physics.unc.edu [Department of Physics and Astronomy, UNC-Chapel Hill, NC 27599 (United States)

2017-03-01

The 2015 Planck data release has placed tight constraints on the allowed class of inflationary models. The current data favors concave downwards inflationary potentials while offering interesting hints on possible deviations from the standard picture of CMB perturbations. We here test the predictions of the theory of the origin of the universe from the landscape multiverse, against the most recent Planck data, for the case of concave downwards inflationary potentials, such as the Starobinsky model of inflation. By considering the quantum entanglement correction of the multiverse, we can place a lower limit on the local 'SUSY breaking' scale b > 1.2 × 10{sup 7} GeV at 95% c.l. from Planck TT+lowTEB. We find that this limit is consistent with the range for b that allows the landscape multiverse to explain a serie of anomalies present in the current data.

Positive Skin Test or Specific IgE to Penicillin Does Not Reliably Predict Penicillin Allergy

DEFF Research Database (Denmark)

Tannert, Line Kring; Mørtz, Charlotte G; Skov, Per Stahl

2017-01-01

INTRODUCTION: According to guidelines, patients are diagnosed with penicillin allergy if skin test (ST) result or specific IgE (s-IgE) to penicillin is positive. However, the true sensitivity and specificity of these tests are presently not known. OBJECTIVE: To investigate the clinical relevance...... of a positive ST result and positive s-IgE and to study the reproducibility of ST and s-IgE. METHODS: A sample of convenience of 25 patients with positive penicillin ST results, antipenicillin s-IgE results, or both was challenged with their culprit penicillin. Further 19 patients were not challenged......-IgE measured (T0), and then skin tested and had s-IgE measured 4 weeks later (T1). RESULTS: Only 9 (36%) of 25 were challenge positive. There was an increased probability of being penicillin allergic if both ST result and s-IgE were positive at T0. Positive ST result or positive s-IgE alone did not predict...

Toward automated e-cigarette surveillance: Spotting e-cigarette proponents on Twitter.

Science.gov (United States)

Kavuluru, Ramakanth; Sabbir, A K M

2016-06-01

Electronic cigarettes (e-cigarettes or e-cigs) are a popular emerging tobacco product. Because e-cigs do not generate toxic tobacco combustion products that result from smoking regular cigarettes, they are sometimes perceived and promoted as a less harmful alternative to smoking and also as means to quit smoking. However, the safety of e-cigs and their efficacy in supporting smoking cessation is yet to be determined. Importantly, the federal drug administration (FDA) currently does not regulate e-cigs and as such their manufacturing, marketing, and sale is not subject to the rules that apply to traditional cigarettes. A number of manufacturers, advocates, and e-cig users are actively promoting e-cigs on Twitter. We develop a high accuracy supervised predictive model to automatically identify e-cig "proponents" on Twitter and analyze the quantitative variation of their tweeting behavior along popular themes when compared with other Twitter users (or tweeters). Using a dataset of 1000 independently annotated Twitter profiles by two different annotators, we employed a variety of textual features from latest tweet content and tweeter profile biography to build predictive models to automatically identify proponent tweeters. We used a set of manually curated key phrases to analyze e-cig proponent tweets from a corpus of over one million e-cig tweets along well known e-cig themes and compared the results with those generated by regular tweeters. Our model identifies e-cig proponents with 97% precision, 86% recall, 91% F-score, and 96% overall accuracy, with tight 95% confidence intervals. We find that as opposed to regular tweeters that form over 90% of the dataset, e-cig proponents are a much smaller subset but tweet two to five times more than regular tweeters. Proponents also disproportionately (one to two orders of magnitude more) highlight e-cig flavors, their smoke-free and potential harm reduction aspects, and their claimed use in smoking cessation. Given FDA is

On the use and potential use of seasonal to decadal climate predictions for decision-making in Europe

Science.gov (United States)

Soares, Marta Bruno; Dessai, Suraje

2014-05-01

The need for climate information to help inform decision-making in sectors susceptible to climate events and impacts is widely recognised. In Europe, developments in the science and models underpinning the study of climate variability and change have led to an increased interest in seasonal to decadal climate predictions (S2DCP). While seasonal climate forecasts are now routinely produced operationally by a number of centres around the world, decadal climate predictions are still in its infancy restricted to the realm of research. Contrary to other regions of the world, where the use of these types of forecasts, particularly at seasonal timescales, has been pursued in recent years due to higher levels of predictability, little is known about the uptake and climate information needs of end-users regarding S2DCP in Europe. To fill this gap we conducted in-depth interviews with experts and decision-makers across a range of European sectors, a workshop with European climate services providers, and a systematic literature review on the use of S2DCP in Europe. This study is part of the EUropean Provision Of Regional Impact Assessment on a Seasonal-to-decadal timescale (EUPORIAS) project which aims to develop semi-operational prototypes of impact prediction systems in Europe on seasonal to decadal timescales. We found that the emerging landscape of users and potential users of S2DCP in Europe is complex and heterogeneous. Differences in S2DCP information needs across and within organisations and sectors are largely underpinned by factors such as the institutional and regulatory context of the organisations, the plethora of activities and decision-making processes involved, the level of expertise and capacity of the users, and the availability of resources within the organisations. In addition, although the use of S2DCP across Europe is still fairly limited, particular sectors such as agriculture, health, energy, water, (re)insurance, and transport are taking the lead on

The Role of Rad17 in DNA Damage Checkpoint Signaling and Initiation of Apoptosis in Mammary Cells

Science.gov (United States)

2005-07-01

Shen et al. 1998). Antibodies to β-catenin (Transduction lab ), GSK-3β (Santa Cruz), Smad3 I-20 (Santa Cruz), Smad3 (Zymed), phspho-Smad2 (Cell...van de Wetering, M., R. Cavallo, D. Dooijes, M. van Beest , J. van Es, J. Loureiro, A. Ypma, D. Hursh, T. Jones, A. Bejsovec, M. Peifer, M. Mortin

Elemental fingerprinting of mussel shells to predict population sources and redistribution potential in the Gulf of Maine.

Directory of Open Access Journals (Sweden)

Cascade J B Sorte

Full Text Available As the climate warms, species that cannot tolerate changing conditions will only persist if they undergo range shifts. Redistribution ability may be particularly variable for benthic marine species that disperse as pelagic larvae in ocean currents. The blue mussel, Mytilus edulis, has recently experienced a warming-related range contraction in the southeastern USA and may face limitations to northward range shifts within the Gulf of Maine where dominant coastal currents flow southward. Thus, blue mussels might be especially vulnerable to warming, and understanding dispersal patterns is crucial given the species' relatively long planktonic larval period (>1 month. To determine whether trace elemental "fingerprints" incorporated in mussel shells could be used to identify population sources (i.e. collection locations, we assessed the geographic variation in shell chemistry of blue mussels collected from seven populations between Cape Cod, Massachusetts and northern Maine. Across this ∼500 km of coastline, we were able to successfully predict population sources for over two-thirds of juvenile individuals, with almost 80% of juveniles classified within one site of their collection location and 97% correctly classified to region. These results indicate that significant differences in elemental signatures of mussel shells exist between open-coast sites separated by ∼50 km throughout the Gulf of Maine. Our findings suggest that elemental "fingerprinting" is a promising approach for predicting redistribution potential of the blue mussel, an ecologically and economically important species in the region.

Predictive Ability from ePortfolios of Student Achievement Associated with Professional Teaching Standards: An Exploratory Case Study

Science.gov (United States)

Payne, Phillip; Burrack, Frederick

2017-01-01

This exploratory case study, focused on a music teacher preparation program, examined the coursework ePortfolios of pre-service music teachers to determine if any parts of the ePortfolio process predicted teaching effectiveness in the classroom during the student teaching semester. Sixty-five undergraduate pre-service music teachers made up the…

Predicting hydrocarbon potential of an earth formation underlying a body of water

International Nuclear Information System (INIS)

Kaplan, I.R.; Demaison, G.J.

1983-01-01

A method for the on-site collection and examination of small concentrations of methane dissolved in water so as to predict hydrocarbon potential of an earth formation underlying a body of water, said formation being a source of said methane, comprises: (i) sampling the water; (ii) continuously vacuum separating said water into liquid and gas phases; (iii) quantitatively separating interfering gas species from methane; (iv) quantitatively oxidising said methane; (v) cryogenically trapping the resulting gaseous carbon dioxide and water vapor at a trapping station, and (vi) isotopically examining said trapped carbon dioxide and water vapour for carbon and deuterium distribution. (author)

Learning a Continuous-Time Streaming Video QoE Model.

Science.gov (United States)

Ghadiyaram, Deepti; Pan, Janice; Bovik, Alan C

2018-05-01

Over-the-top adaptive video streaming services are frequently impacted by fluctuating network conditions that can lead to rebuffering events (stalling events) and sudden bitrate changes. These events visually impact video consumers' quality of experience (QoE) and can lead to consumer churn. The development of models that can accurately predict viewers' instantaneous subjective QoE under such volatile network conditions could potentially enable the more efficient design of quality-control protocols for media-driven services, such as YouTube, Amazon, Netflix, and so on. However, most existing models only predict a single overall QoE score on a given video and are based on simple global video features, without accounting for relevant aspects of human perception and behavior. We have created a QoE evaluator, called the time-varying QoE Indexer, that accounts for interactions between stalling events, analyzes the spatial and temporal content of a video, predicts the perceptual video quality, models the state of the client-side data buffer, and consequently predicts continuous-time quality scores that agree quite well with human opinion scores. The new QoE predictor also embeds the impact of relevant human cognitive factors, such as memory and recency, and their complex interactions with the video content being viewed. We evaluated the proposed model on three different video databases and attained standout QoE prediction performance.

Ab initio calculation of intermolecular potentials for dimer Cl_2-Cl_2 and prediction of second virial coefficients

International Nuclear Information System (INIS)

Nguyen Thanh Duoc; Nguyen Thi Ai Nhung; Tran Duong; Pham Van Tat

2015-01-01

The results presented in this paper are the ab initio intermolecular potentials and the second virial coefficient, B_2 (T) of the dimer Cl_2-Cl_2. These ab initio potentials were proposed by the quantum chemical calculations at high level of theory CCSD(T) with basis sets of Dunning valence correlation-consistent aug-cc-pVmZ (m = 2, 3); these results were extrapolated to complete basis set limit aug-cc-pV23Z. The ab initio energies of complete basis set limit aug-cc-pV23Z resulted from the exponential extrapolation were used to construct the 5-site pair potential functions. The second virial coefficients for this dimer were predicted from those with four-dimensional integration. The second virial coefficients were also corrected to first-order quantum effects. The results turn out to be in good agreement with experimental data, if available, or with those from empirical correlation. The quality of ab initio 5-site potentials proved the reliability for prediction of molecular thermodynamic properties. (author)

Prediction of specific depressive symptom clusters in youth with epilepsy: The NDDI-E-Y versus Neuro-QOL SF.

Science.gov (United States)

Kellermann, Tanja S; Mueller, Martina; Carter, Emma G; Brooks, Byron; Smith, Gigi; Kopp, Olivia J; Wagner, Janelle L

2017-08-01

Proper assessment and early identification of depressive symptoms are essential to initiate treatment and minimize the risk for poor outcomes in youth with epilepsy (YWE). The current study examined the predictive utility of the Neurological Disorders Depression Inventory-Epilepsy for Youth (NDDI-E-Y) and the Neuro-QOL Depression Short Form (Neuro-QOL SF) in explaining variance in overall depressive symptoms and specific symptom clusters on the gold standard Children's Depression Inventory-2 (CDI-2). Cross-sectional study examining 99 YWE (female 68, mean age 14.7 years) during a routine epilepsy visit, who completed self-report measures of depressive symptoms, including the NDDI-E-Y, CDI-2, and the Neuro-QOL SF. Caregivers completed a measure of seizure severity. All sociodemographic and medical information was evaluated through electronic medical record review. After accounting for seizure and demographic variables, the NDDI-E-Y accounted for 45% of the variance in the CDI-2 Total score and the CDI-2 Ineffectiveness subscale. Furthermore, the NDDI-E-Y predicted CDI-2 Total scores and subscales similarly, with the exception of explaining significantly more variance in the CDI-2 Ineffectiveness subscale compared to the Negative Mood subscale. The NDDI-E-Y explained greater variance compared to Neuro-QOL SF across the Total (48% vs. 37%) and all CDI-2 subscale scores; however, the NDDI-E-Y emerged as a stronger predictor of only CDI-2 Ineffectiveness. Both the NDDI-E-Y and Neuro-QOL SF accounted for the lowest amount of variance in CDI-2 Negative Mood. Sensitivity was poor for the Neuro-QOL SF in predicting high versus low CDI-2 scores. The NDDI-E-Y has strong psychometrics and can be easily integrated into routine epilepsy care for quick, brief screening of depressive symptoms in YWE. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

Methodology developed to make the Quebec indoor radon potential map

Energy Technology Data Exchange (ETDEWEB)

Drolet, Jean-Philippe, E-mail: jean-philippe.drolet@ete.inrs.ca [Institut national de la recherche scientifique, Eau Terre Environnement Research Centre (ETE-INRS), 490 de la Couronne, G1K 9A9 Quebec (Canada); Martel, Richard [Institut national de la recherche scientifique, Eau Terre Environnement Research Centre (ETE-INRS), 490 de la Couronne, G1K 9A9 Quebec (Canada); Poulin, Patrick [Institut national de santé publique du Québec (INSPQ), 945 avenue Wolfe, G1V 5B3 Quebec (Canada); Dessau, Jean-Claude [Agence de la santé et des services sociaux des Laurentides, 1000 rue Labelle, J7Z 5 N6 Saint-Jérome (Canada)

2014-03-01

This paper presents a relevant approach to predict the indoor radon potential based on the combination of the radiogeochemical data and the indoor radon measurements in the Quebec province territory (Canada). The Quebec ministry of health asked for such a map to identify the radon-prone areas to manage the risk for the population related to indoor radon exposure. Three radiogeochemical criteria including (1) equivalent uranium (eU) concentration from airborne surface gamma-ray surveys, (2) uranium concentration measurements in sediments, (3) bedrock and surficial geology were combined with 3082 basement radon concentration measurements to identify the radon-prone areas. It was shown that it is possible to determine thresholds for the three criteria that implied statistically significant different levels of radon potential using Kruskal–Wallis one way analyses of variance by ranks. The three discretized radiogeochemical datasets were combined into a total predicted radon potential that sampled 98% of the studied area. The combination process was also based on Kruskal–Wallis one way ANOVA. Four statistically significant different predicted radon potential levels were created: low, medium, high and very high. Respectively 10 and 13% of the dwellings exceed the Canadian radon guideline of 200 Bq/m{sup 3} in low and medium predicted radon potentials. These proportions rise up to 22 and 45% respectively for high and very high predicted radon potentials. This predictive map of indoor radon potential based on the radiogeochemical data was validated using a map of confirmed radon exposure in homes based on the basement radon measurements. It was shown that the map of predicted radon potential based on the radiogeochemical data was reliable to identify radon-prone areas even in zones where no indoor radon measurement exists. - Highlights: • 5 radiogeochemical datasets were used to map the geogenic indoor radon potential. • An indoor radon potential was determined for

Carcinoma epidermóide do pulmão: Polissomia e amplificação do cromossoma 7 e do gene EGRF com forma wild type nos exões 19 e 21

Directory of Open Access Journals (Sweden)

Patrícia Couceiro

2010-05-01

Full Text Available Resumo: Objectivo: O receptor do factor de crescimento epidérmico (EGFR está sobreexpresso na maioria dos carcinomas do pulmão de não pequenas células (CPNPC e é um dos principais alvos específicos dos inibidores da tirosina cinase (TKI utilizados para o tratamento do CPNPC avançado. Apesar disto, há um considerável número de factores biológicos que também estão associados à resposta dos EGFR-TKIs. Este estudo teve como principal objectivo a pesquisa de mutações somáticas e amplificação do EGFR em casos de carcinoma epidermóide do pulmão. Material e métodos: Secções representativas de carcinoma epidermóide foram seleccionadas de 54 casos em que o tecido estava fixado em formal e incluído em parafina, sendo depois submetidos à construção de TMA. A determinação da expressão proteica do EGFR foi feita por imunoistoquímica (IHQ (Zymed, laboratórios. A hibridização in situ de fluorescência (FISH foi realizada com a sonda EGFR LSI / CEP 7 (Vysis; Abbott Molecular, EUA. O ADN genómico foi extraído de 48 casos, amplificado por reacção em cadeia da polimerase (PCR para pesquisa de mutações nos exões 19 (deleções e 21 (mutações pontuais. Todos os casos expressaram positividade para a citoqueratina de alto peso molecular e foi observada negatividade para CK7, CD56 e cromogranina. Resultados: A sobreexpressão proteica do EGFR foi identificada em 49 casos, pela aplicação do score de Hirsh/ Cappuzzo (2005. A pesquisa de alterações génicas no cromossoma 7 e do gene EGFR foram analisadas por FISH e de acordo com o método de Cappuzzo (2005, foi identificada alta polissomia em 31 casos e amplificação em 7 casos. Por electroforese capilar, foram detectadas no exão 19 do EGFR: deleções em heterozigotia em 3 dos 48 casos estudados e o exão 21 apresentou-se sempre na sua forma wild

Stress state and movement potential of the Kar-e-Bas fault zone, Fars, Iran

Science.gov (United States)

Sarkarinejad, Khalil; Zafarmand, Bahareh

2017-08-01

The Kar-e-Bas or Mengharak basement-inverted fault is comprised of six segments in the Zagros foreland folded belt of Iran. In the Fars region, this fault zone associated with the Kazerun, Sabz-Pushan and Sarvestan faults serves as a lateral transfer zone that accommodates the change in shortening direction from the western central to the eastern Zagros. This study evaluates the recent tectonic stress regime of the Kar-e-Bas fault zone based on inversion of earthquake focal mechanism data, and quantifies the fault movement potential of this zone based on the relationship between fault geometric characteristics and recent tectonic stress regimes. The trend and plunge of σ 1 and σ 3 are S25°W/04°-N31°E/05° and S65°E/04°-N60°W/10°, respectively, with a stress ratio of Φ = 0.83. These results are consistent with the collision direction of the Afro-Arabian continent and the Iranian microcontinent. The near horizontal plunge of maximum and minimum principle stresses and the value of stress ratio Φ indicate that the state of stress is nearly strike-slip dominated with little relative difference between the value of two principal stresses, σ 1 and σ 2. The obliquity of the maximum compressional stress into the fault trend reveals a typical stress partitioning of thrust and strike-slip motion in the Kar-e-Bas fault zone. Analysis of the movement potential of this fault zone shows that its northern segment has a higher potential of fault activity (0.99). The negligible difference between the fault-plane dips of the segments indicates that their strike is a controlling factor in the changes in movement potential.

Human Pluripotent Stem Cell-Based Assay Predicts Developmental Toxicity Potential of ToxCast Chemicals (ACT meeting)

Science.gov (United States)

Worldwide initiatives to screen for toxicity potential among the thousands of chemicals currently in use require inexpensive and high-throughput in vitro models to meet their goals. The devTOX quickPredict platform is an in vitro human pluripotent stem cell-based assay used to as...

SIEX design predictions for the PNC fuel pins in the HEDL P-E01 power-to-melt test

International Nuclear Information System (INIS)

1979-01-01

During the design phase of the HEDL P-E01 power-to-melt test, a series of design predictions were generated for the three PNC pins using the SIEX fuel pin modeling code. This document tabulates a series of selected PNC pin design predictions as requested by M. Shinohara during his visit to HEDL

Quinone 1 e ^– and 2 e ^– /2 H ⁺ Reduction Potentials: Identification and Analysis of Deviations from Systematic Scaling Relationships

Energy Technology Data Exchange (ETDEWEB)

Huynh, Mioy T.; Anson, Colin W.; Cavell, Andrew C.; Stahl, Shannon S.; Hammes-Schiffer, Sharon

2016-11-10

Quinones participate in diverse electron transfer and proton-coupled electron transfer processes in chemistry and biology. An experimental study of common quinones reveals a non-linear correlation between the 1 e^– and 2 e^–/2 H⁺ reduction potentials. This unexpected observation prompted a computational study of 128 different quinones, probing their 1 e^– reduction potentials, pKa values, and 2 e^–/2 H⁺ reduction potentials. The density functional theory calculations reveal an approximately linear correlation between these three properties and an effective Hammett constant associated with the quinone substituent(s). However, deviations from this linear scaling relationship are evident for quinones that feature halogen substituents, charged substituents, intramolecular hydrogen bonding in the hydroquinone, and/or sterically bulky substituents. These results, particularly the different substituent effects on the 1 e^– versus 2 e^– /2 H⁺ reduction potentials, have important implications for designing quinones with tailored redox properties.

CT volumetry can potentially predict the local stage for gastric cancer after chemotherapy

Science.gov (United States)

Wang, Zhi-Cong; Wang, Chen; Ding, Ying; Ji, Yuan; Zeng, Meng-Su; Rao, Sheng-Xiang

2017-01-01

PURPOSE We aimed to evaluate the value of CT tumor volumetry for predicting T and N stages of gastric cancer after chemotherapy, with pathologic results as the reference standard. METHODS This study retrospectively evaluated 42 patients diagnosed with gastric cancer, who underwent chemotherapy followed by surgery. Pre- and post-treatment CT tumor volumes (VT) were measured in portal venous phase and volume reduction ratios were calculated. Correlations between pre- and post-treatment VT, reduction ratio, and pathologic stages were analyzed. Receiver operator characteristic (ROC) analyses were also performed to assess diagnostic performance for prediction of downstaging to T0–2 stage and N0 stage. RESULTS Pretreatment VT, post-treatment VT, and VT reduction ratio were significantly correlated with T stage (rs=0.329, rs=0.546, rs= −0.422, respectively). Post-treatment VT and VT reduction ratio were significantly correlated with N stage (rs=0.442 and rs= −0.376, respectively). Pretreatment VT, post-treatment VT, and VT reduction ratio were significantly different between T0–2 and T3,4 stage tumors (P = 0.05, P volumetry, particularly post-treatment measurement of VT, is potentially valuable for predicting histopathologic T and N stages after chemotherapy in patients with gastric cancer. PMID:28703101

New approach to predict photoallergic potentials of chemicals based on murine local lymph node assay.

Science.gov (United States)

Maeda, Yosuke; Hirosaki, Haruka; Yamanaka, Hidenori; Takeyoshi, Masahiro

2018-05-23

Photoallergic dermatitis, caused by pharmaceuticals and other consumer products, is a very important issue in human health. However, S10 guidelines of the International Conference on Harmonization do not recommend the existing prediction methods for photoallergy because of their low predictability in human cases. We applied local lymph node assay (LLNA), a reliable, quantitative skin sensitization prediction test, to develop a new photoallergy prediction method. This method involves a three-step approach: (1) ultraviolet (UV) absorption analysis; (2) determination of no observed adverse effect level for skin phototoxicity based on LLNA; and (3) photoallergy evaluation based on LLNA. Photoallergic potential of chemicals was evaluated by comparing lymph node cell proliferation among groups treated with chemicals with minimal effect levels of skin sensitization and skin phototoxicity under UV irradiation (UV+) or non-UV irradiation (UV-). A case showing significant difference (P < .05) in lymph node cell proliferation rates between UV- and UV+ groups was considered positive for photoallergic reaction. After testing 13 chemicals, seven human photoallergens tested positive and the other six, with no evidence of causing photoallergic dermatitis or UV absorption, tested negative. Among these chemicals, both doxycycline hydrochloride and minocycline hydrochloride were tetracycline antibiotics with different photoallergic properties, and the new method clearly distinguished between the photoallergic properties of these chemicals. These findings suggested high predictability of our method; therefore, it is promising and effective in predicting human photoallergens. Copyright © 2018 John Wiley & Sons, Ltd.

Polysomy and amplification of chromosome 7 defined for EGFR gene in squamous cell carcinoma of the lung together with exons 19 and 21 wild type Carcinoma epidermóide do pulmão: Polissomia e amplificação do cromossoma 7 e do gene EGRF com forma wild type nos exões 19 e 21

Directory of Open Access Journals (Sweden)

Patrícia Couceiro

2010-06-01

factor de crescimento epidérmico (EGFR está sobreexpresso na maioria dos carcinomas do pulmão de não pequenas células (CPNPC e é um dos principais alvos específicos dos inibidores da tirosina cinase (TKI utilizados para o tratamento do CPNPC avançado. Apesar disto, há um considerável número de factores biológicos que também estão associados à resposta dos EGFR-TKIs. Este estudo teve como principal objectivo a pesquisa de mutações somáticas e amplificação do EGFR em casos de carcinoma epidermóide do pulmão. Material e métodos: Secções representativas de carcinoma epidermóide foram seleccionadas de 54 casos em que o tecido estava fixado em formal e incluído em parafina, sendo depois submetidos à construção de TMA. A determinação da expressão proteica do EGFR foi feita por imunoistoquímica (IHQ (Zymed, laboratórios. A hibridização in situ de fluorescência (FISH foi realizada com a sonda EGFR LSI / CEP 7 (Vysis; Abbott Molecular, EUA. O ADN genómico foi extraído de 48 casos, amplificado por reacção em cadeia da polimerase (PCR para pesquisa de mutações nos exões 19 (deleções e 21 (mutações pontuais. Todos os casos expressaram positividade para a citoqueratina de alto peso molecular e foi observada negatividade para CK7, CD56 e cromogranina. Resultados: A sobreexpressão proteica do EGFR foi identificada em 49 casos, pela aplicação do score de Hirsh/ Cappuzzo (2005. A pesquisa de alterações génicas no cromossoma 7 e do gene EGFR foram analisadas por FISH e de acordo com o método de Cappuzzo (2005, foi identificada alta polissomia em 31 casos e amplificação em 7 casos. Por electroforese capilar, foram detectadas no exão 19 do EGFR: deleções em heterozigotia em 3 dos 48 casos estudados e o exão 21 apresentou-se sempre na sua forma wild-type, quando estudado por enzimas de restrição. Conclusões: A detecção de deleções e mutações pontuais no EGFR mostrou ser um evento raro no carcinoma epidermóide do pulm

On the analysis of protein-protein interactions via knowledge-based potentials for the prediction of protein-protein docking

DEFF Research Database (Denmark)

Feliu, Elisenda; Aloy, Patrick; Oliva, Baldo

2011-01-01

Development of effective methods to screen binary interactions obtained by rigid-body protein-protein docking is key for structure prediction of complexes and for elucidating physicochemical principles of protein-protein binding. We have derived empirical knowledge-based potential functions for s...... and with independence of the partner. This information is encoded at the residue level and could be easily incorporated in the initial grid scoring for Fast Fourier Transform rigid-body docking methods.......Development of effective methods to screen binary interactions obtained by rigid-body protein-protein docking is key for structure prediction of complexes and for elucidating physicochemical principles of protein-protein binding. We have derived empirical knowledge-based potential functions...... for selecting rigid-body docking poses. These potentials include the energetic component that provides the residues with a particular secondary structure and surface accessibility. These scoring functions have been tested on a state-of-art benchmark dataset and on a decoy dataset of permanent interactions. Our...

Design and Synthesis of New Peptidomimetics as Potential Inhibitors of MurE.

Science.gov (United States)

Zivec, Matej; Turk, Samo; Blanot, Didier; Gobec, Stanislav

2011-03-01

With the continuing emergence and spread of multidrug-resistant bacteria, there is an urgent need for the development of new antimicrobial agents. One possible source of new antibacterial targets is the biosynthesis of the bacterial cell-wall peptidoglycan. The assembly of the peptide stem is carried out by four essential enzymes, known as the Mur ligases (MurC, D, E and F). We have designed and synthesised a focused library of compounds as potential inhibitors of UDP-N-acetylmuramoyl-L-alanyl-D-glutamate:L-lysine ligase (MurE) from Staphylococcus aureus. This was achieved using two approaches: (i) synthesis of transition-state analogues based on the methyleneamino core; and (ii) synthesis of MurE reaction product analogues. Two methyleneamino-based compounds are identified as initial hits for inhibitors of MurE.

Combined visual and motor evoked potentials predict multiple sclerosis disability after 20 years.

Science.gov (United States)

Schlaeger, Regina; Schindler, Christian; Grize, Leticia; Dellas, Sophie; Radue, Ernst W; Kappos, Ludwig; Fuhr, Peter

2014-09-01

The development of predictors of multiple sclerosis (MS) disability is difficult due to the complex interplay of pathophysiological and adaptive processes. The purpose of this study was to investigate whether combined evoked potential (EP)-measures allow prediction of MS disability after 20 years. We examined 28 patients with clinically definite MS according to Poser's criteria with Expanded Disability Status Scale (EDSS) scores, combined visual and motor EPs at entry (T0), 6 (T1), 12 (T2) and 24 (T3) months, and a cranial magnetic resonance imaging (MRI) scan at T0 and T2. EDSS testing was repeated at year 14 (T4) and year 20 (T5). Spearman rank correlation was used. We performed a multivariable regression analysis to examine predictive relationships of the sum of z-transformed EP latencies (s-EPT0) and other baseline variables with EDSST5. We found that s-EPT0 correlated with EDSST5 (rho=0.72, pdisability in MS. © The Author(s) 2014.

Predicting Internet/E-Commerce Use.

Science.gov (United States)

Sexton, Randall S.; Johnson, Richard A.; Hignite, Michael A.

2002-01-01

Describes a study that analyzed variables in order to identify accurate predictors of individuals' use of the Internet and e-commerce. Results of survey research and a neural network identifies gender, overall computer use, job-related use, and home access as important characteristics that should influence use of the Internet and e-commerce.…

Skill forecasting from ensemble predictions of wind power

DEFF Research Database (Denmark)

Pinson, Pierre; Nielsen, Henrik Aalborg; Madsen, Henrik

2009-01-01

Optimal management and trading of wind generation calls for the providing of uncertainty estimates along with the commonly provided short-term wind power point predictions. Alternative approaches for the use of probabilistic forecasting are introduced. More precisely, focus is given to prediction...... risk indices aiming to give a comprehensive signal on the expected level of forecast uncertainty. Ensemble predictions of wind generation are used as input. A proposal for the definition of prediction risk indices is given. Such skill forecasts are based on the spread of ensemble forecasts (i.e. a set...... of alternative scenarios for the coming period) for a single prediction horizon or over a took-ahead period. It is shown on the test case of a Danish offshore wind farm how these prediction risk indices may be related to several levels of forecast uncertainty (and potential energy imbalances). Wind power...

Predicting therapy success for treatment as usual and blended treatment in the domain of depression

NARCIS (Netherlands)

van Breda, Ward; Bremer, Vincent; Becker, Dennis; Hoogendoorn, Mark; Funk, Burkhardt; Ruwaard, Jeroen; Riper, Heleen

2017-01-01

In this paper, we explore the potential of predicting therapy success for patients in mental health care. Such predictions can eventually improve the process of matching effective therapy types to individuals. In the EU project E-COMPARED, a variety of information is gathered about patients

Basal and prism dislocation cores in magnesium: comparison of first-principles and embedded-atom-potential methods predictions

International Nuclear Information System (INIS)

Yasi, J A; Nogaret, T; Curtin, W A; Trinkle, D R; Qi, Y; Hector, L G Jr

2009-01-01

The core structures of screw and edge dislocations on the basal and prism planes in Mg, and the associated gamma surfaces, were studied using an ab initio method and the embedded-atom-method interatomic potentials developed by Sun et al and Liu et al. The ab initio calculations predict that the basal plane dislocations dissociate into partials split by 16.7 Å (edge) and 6.3 Å (screw), as compared with 14.3 Å and 12.7 Å (Sun and Liu edge), and 6.3 Å and 1.4 Å (Sun and Liu screw), with the Liu screw dislocation being metastable. In the prism plane, the screw and edge cores are compact and the edge core structures are all similar, while ab initio does not predict a stable prismatic screw in stress-free conditions. These results are qualitatively understood through an examination of the gamma surfaces for interplanar sliding on the basal and prism planes. The Peierls stresses at T = 0 K for basal slip are a few megapascals for the Sun potential, in agreement with experiments, but are ten times larger for the Liu potential. The Peierls stresses for prism slip are 10–40 MPa for both potentials. Overall, the dislocation core structures from ab initio are well represented by the Sun potential in all cases while the Liu potential shows some notable differences. These results suggest that the Sun potential is preferable for studying other dislocations in Mg, particularly the (c + a) dislocations, for which the core structures are much larger and not accessible by ab initio methods

Galectin-7 as a potential predictive marker of chemo-and/or radio-therapy resistance in oral squamous cell carcinoma

International Nuclear Information System (INIS)

Matsukawa, Sho; Morita, Kei-ichi; Negishi, Ayako; Harada, Hiroyuki; Nakajima, Yusuke; Shimamoto, Hiroaki; Tomioka, Hirofumi; Tanaka, Kae; Ono, Masaya; Yamada, Tesshi; Omura, Ken

2014-01-01

Treatment of advanced oral squamous cell carcinoma (OSCC) requires the integration of multimodal approaches. The aim of this study was to identify predictors of tumor sensitivity to preoperative radiotherapy/chemotherapy for OSCC in order to allow oncologists to determine optimum therapeutic strategies without the associated adverse effects. Here, the protein expression profiles of formalin-fixed paraffin-embedded (FFPE) tissue samples from 18 OSCC patients, termed learning cases, who received preoperative chemotherapy and/or radiotherapy followed by surgery were analyzed by quantitative proteomics and validated by immunohistochemistry in 68 test cases as well as in the 18 learning cases. We identified galectin-7 as a potential predictive marker of chemotherapy and/or radiotherapy resistance, and the sensitivity and specificity of the galectin-7 prediction score (G7PS) in predicting this resistance was of 96.0% and 39.5%, respectively, in the 68 test cases. The cumulative 5-year disease-specific survival rate was 75.2% in patients with resistant prediction using G7PS and 100% in patients with sensitive prediction. In vitro overexpression of galectin-7 significantly decreased cell viability in OSCC cell line. Therefore, our findings suggest that galectin-7 is a potential predictive marker of chemotherapy and/or radiotherapy resistance in patients with OSCC. Identification of proteins differentially expressed in OSSC samples from patients sensitive or resistant. The samples were processed by LC-MS and analyzed with 2DICAL

Improving the Accuracy of a Heliocentric Potential (HCP Prediction Model for the Aviation Radiation Dose

Directory of Open Access Journals (Sweden)

Junga Hwang

2016-12-01

Full Text Available The space radiation dose over air routes including polar routes should be carefully considered, especially when space weather shows sudden disturbances such as coronal mass ejections (CMEs, flares, and accompanying solar energetic particle events. We recently established a heliocentric potential (HCP prediction model for real-time operation of the CARI-6 and CARI-6M programs. Specifically, the HCP value is used as a critical input value in the CARI-6/6M programs, which estimate the aviation route dose based on the effective dose rate. The CARI-6/6M approach is the most widely used technique, and the programs can be obtained from the U.S. Federal Aviation Administration (FAA. However, HCP values are given at a one month delay on the FAA official webpage, which makes it difficult to obtain real-time information on the aviation route dose. In order to overcome this critical limitation regarding the time delay for space weather customers, we developed a HCP prediction model based on sunspot number variations (Hwang et al. 2015. In this paper, we focus on improvements to our HCP prediction model and update it with neutron monitoring data. We found that the most accurate method to derive the HCP value involves (1 real-time daily sunspot assessments, (2 predictions of the daily HCP by our prediction algorithm, and (3 calculations of the resultant daily effective dose rate. Additionally, we also derived the HCP prediction algorithm in this paper by using ground neutron counts. With the compensation stemming from the use of ground neutron count data, the newly developed HCP prediction model was improved.

Cyber-Management of People with Chronic Disease: A Potential Solution to eHealth Challenges

Science.gov (United States)

Laakso, E-Liisa; Armstrong, Kylie; Usher, Wayne

2012-01-01

The evolving eHealth agenda presents a range of potential opportunities for the management and prevention of chronic disease. This paper identifies issues and barriers to the uptake of eHealth and describes a strategy ("Healthy Outcomes for Australians"[C]-HOFA) for creating a central knowledge filter and cyber space method for tracking…

Predictive Models for Carcinogenicity and Mutagenicity ...

Science.gov (United States)

Mutagenicity and carcinogenicity are endpoints of major environmental and regulatory concern. These endpoints are also important targets for development of alternative methods for screening and prediction due to the large number of chemicals of potential concern and the tremendous cost (in time, money, animals) of rodent carcinogenicity bioassays. Both mutagenicity and carcinogenicity involve complex, cellular processes that are only partially understood. Advances in technologies and generation of new data will permit a much deeper understanding. In silico methods for predicting mutagenicity and rodent carcinogenicity based on chemical structural features, along with current mutagenicity and carcinogenicity data sets, have performed well for local prediction (i.e., within specific chemical classes), but are less successful for global prediction (i.e., for a broad range of chemicals). The predictivity of in silico methods can be improved by improving the quality of the data base and endpoints used for modelling. In particular, in vitro assays for clastogenicity need to be improved to reduce false positives (relative to rodent carcinogenicity) and to detect compounds that do not interact directly with DNA or have epigenetic activities. New assays emerging to complement or replace some of the standard assays include VitotoxTM, GreenScreenGC, and RadarScreen. The needs of industry and regulators to assess thousands of compounds necessitate the development of high-t

Structural insights into Cydia pomonella pheromone binding protein 2 mediated prediction of potentially active semiochemicals

Science.gov (United States)

Tian, Zhen; Liu, Jiyuan; Zhang, Yalin

2016-03-01

Given the advantages of behavioral disruption application in pest control and the damage of Cydia pomonella, due progresses have not been made in searching active semiochemicals for codling moth. In this research, 31 candidate semiochemicals were ranked for their binding potential to Cydia pomonella pheromone binding protein 2 (CpomPBP2) by simulated docking, and this sorted result was confirmed by competitive binding assay. This high predicting accuracy of virtual screening led to the construction of a rapid and viable method for semiochemicals searching. By reference to binding mode analyses, hydrogen bond and hydrophobic interaction were suggested to be two key factors in determining ligand affinity, so is the length of molecule chain. So it is concluded that semiochemicals of appropriate chain length with hydroxyl group or carbonyl group at one head tended to be favored by CpomPBP2. Residues involved in binding with each ligand were pointed out as well, which were verified by computational alanine scanning mutagenesis. Progress made in the present study helps establish an efficient method for predicting potentially active compounds and prepares for the application of high-throughput virtual screening in searching semiochemicals by taking insights into binding mode analyses.

The Impact Hazard in the Context of Other Natural Hazards and Predictive Science

Science.gov (United States)

Chapman, C. R.

1998-09-01

The hazard due to impact of asteroids and comets has been recognized as analogous, in some ways, to other infrequent but consequential natural hazards (e.g. floods and earthquakes). Yet, until recently, astronomers and space agencies have felt no need to do what their colleagues and analogous agencies must do in order the assess, quantify, and communicate predictions to those with a practical interest in the predictions (e.g. public officials who must assess the threats, prepare for mitigation, etc.). Recent heightened public interest in the impact hazard, combined with increasing numbers of "near misses" (certain to increase as Spaceguard is implemented) requires that astronomers accept the responsibility to place their predictions and assessments in terms that may be appropriately considered. I will report on preliminary results of a multi-year GSA/NCAR study of "Prediction in the Earth Sciences: Use and Misuse in Policy Making" in which I have represented the impact hazard, while others have treated earthquakes, floods, weather, global climate change, nuclear waste disposal, acid rain, etc. The impact hazard presents an end-member example of a natural hazard, helping those dealing with more prosaic issues to learn from an extreme. On the other hand, I bring to the astronomical community some lessons long adopted in other cases: the need to understand the policy purposes of impact predictions, the need to assess potential societal impacts, the requirements to very carefully assess prediction uncertainties, considerations of potential public uses of the predictions, awareness of ethical considerations (e.g. conflicts of interest) that affect predictions and acceptance of predictions, awareness of appropriate means for publicly communicating predictions, and considerations of the international context (especially for a hazard that knows no national boundaries).

Huellas digitales de cepas de Acinetobacter baumannii procedentes de pacientes hospitalizados en la Caja Petrolera de Salud de Obrajes, mediante el método de Pulsed Field Gel Electrophoresis (PFGE, La Paz, Bolivia. Marzo 2015

Directory of Open Access Journals (Sweden)

García-Rada Giovanni

2017-08-01

Full Text Available Acinetobacter baumannii, worldwide is considered an opportunistic microorganism, present in several cases of hospital-acquired infections. In the Caja Petrolera de Salud of Obrajes Hospital was made the isolation of four Acinetobacter baumannii strains. Identification was confirmed by biochemical tests. Then, the PFGE molecular technique was applied for the identification of genomic fingerprints using Apa I restriction en-zyme.

One-electron standard reduction potentials of nitroaromatic and cyclic nitramine explosives

International Nuclear Information System (INIS)

Uchimiya, Minori; Gorb, Leonid; Isayev, Olexandr; Qasim, Mohammad M.; Leszczynski, Jerzy

2010-01-01

Extensive studies have been conducted in the past decades to predict the environmental abiotic and biotic redox fate of nitroaromatic and nitramine explosives. However, surprisingly little information is available on one-electron standard reduction potentials (E o (R-NO 2 /R-NO 2 - )). The E o (R-NO 2 /R-NO 2 - ) is an essential thermodynamic parameter for predicting the rate and extent of reductive transformation for energetic residues. In this study, experimental (linear free energy relationships) and theoretical (ab initio calculation) approaches were employed to determine E o (R-NO 2 /R-NO 2 - ) for nitroaromatic, (caged) cyclic nitramine, and nitroimino explosives that are found in military installations or are emerging contaminants. The results indicate a close agreement between experimental and theoretical E o (R-NO 2 /R-NO 2 - ) and suggest a key trend: E o (R-NO 2 /R-NO 2 - ) value decreases from di- and tri-nitroaromatic (e.g., 2,4-dinitroanisole) to nitramine (e.g., RDX) to nitroimino compound (e.g., nitroguanidine). The observed trend in E o (R-NO 2 /R-NO 2 - ) agrees with reported rate trends for reductive degradation, suggesting a thermodynamic control on the reduction rate under anoxic/suboxic conditions. - Reduction of explosives becomes less thermodynamically favorable as the one-electron standard reduction potential decreases from di- and tri-nitroaromatic, nitramine, to nitroimino compounds.

Determination of the proton spectral function of 3He with the (e,e'p) reaction

International Nuclear Information System (INIS)

Jans, E.

1982-01-01

Cross sections of the 3 He(e,e'p) reaction have been measured with the 600 MeV linear accelerator at Saclay and the two-spectrometer set-up of the experimental hall HE1. The data cover the following region for the missing energy Esub(m) and the proton recoil momentum k: 0 3 He target are described in chapter IV. The experimental procedure, the data analysis, and the corrections which have been applied to the data, are discussed in chapter V. The results of the experiment are presented in chapter VI. The (e,e'p) reaction has proven its capabilities in obtaining detailed information on nuclear structure properties as nucleon momentum density distributions and separation energies, although corrections due to FSI and MEC have to be considered. In the case of 3 He, the results can be compared to predictions of various calculational techniques, using realistic NN-potentials and thus serve as a test for NN-potential models. (Auth.)

20170921 - An evaluation of selected (Q)SARs/expert systems for the Prediction of Skin Sensitization Potential (ASCCT)

Science.gov (United States)

Predictive testing to characterize substances for their skin sensitization potential has historically been based on animal models such as the Local Lymph Node Assay (LLNA) and the Guinea Pig Maximization Test (GPMT). In recent years, EU regulations have provided a strong incentiv...

The potential of eHealth in otorhinolaryngology-head and neck surgery: patients' perspectives.

Science.gov (United States)

Holderried, Martin; Ernst, C; Holderried, F; Rieger, M; Blumenstock, G; Tropitzsch, A

2017-07-01

The use of modern information and communication technologies (ICT) in daily life has significantly increased during the last several years. These essential online technologies have also found their way into the healthcare system. The use of modern ICT for health reasons can be summarized by the term 'eHealth'. Despite the potential importance of eHealth in the field of otorhinolaryngology (ORL), there is little understanding of patients' attitudes towards the deeper integration of these technologies into intersectoral care. The aim of this study was to gain a better understanding of patients' attitudes towards the use of modern ICT for intersectoral communication and information transfer in the field of ORL. Therefore, a structured interview was developed by an interdisciplinary team of otorhinolaryngologists, public health researchers, and information technology (IT) specialists. Overall, 211 ORL patients were interviewed at the Department of Otorhinolaryngology-Head and Neck Surgery, Tuebingen University Hospital, Germany, and 203 of these patients completed the interview. This study revealed ORL patients' perspectives on the potential of eHealth, especially for appointment scheduling, appointment reminders, and intersectoral communication of personal medical information. Furthermore, this study provides evidence that data security and the impacts of eHealth on the physician-patient relationship and on treatment quality warrant special attention in future research.

Can family history and cord blood IgE predict sensitization and allergic diseases up to adulthood?

DEFF Research Database (Denmark)

Borrits Pagh Nissen, Susanne; Fomsgaard Kjær, Henrik; Høst, Arne

2015-01-01

with high NPV and specificity, but low PPV and sensitivity. CONCLUSION: Although family history and elevated CB-IgE were significantly associated with primarily atopic disease until 26 yr, none of these were strong predictors for subsequent sensitization and allergic symptoms from childhood until early......BACKGROUND: Long-term studies of the predictive value of family history and cord blood IgE level until adulthood are few, and their conclusions have been contradictory. METHODS: Screening of total IgE in 1617 cord blood samples was performed in a Danish birth cohort. All infants with cord blood Ig...... used. RESULTS: A total of 455 infants were included, 188 with CB-IgE ≥0.5 kU/l and 267 with CB-IgE history and elevated CB-IgE were significantly associated to allergic disease until 26 yr. Concerning any allergic...

SWAT Model Prediction of Phosphorus Loading in a South Carolina Karst Watershed with a Downstream Embayment

Science.gov (United States)

Devendra M. Amatya; Manoj K. Jha; Thomas M. Williams; Amy E. Edwards; Daniel R.. Hitchcock

2013-01-01

The SWAT model was used to predict total phosphorus (TP) loadings for a 1555-ha karst watershed—Chapel Branch Creek (CBC)—which drains to a lake via a reservoir-like embayment (R-E). The model was first tested for monthly streamflow predictions from tributaries draining three potential source areas as well as the downstream R-E, followed by TP loadings using data...

Prediction of the acid generating potential of coal mining spoils

International Nuclear Information System (INIS)

Monterroso, C.; Macias, F.

1998-01-01

The sulfide oxidation impact on mined land reclamation makes it necessary for mine spoils to be classified according to their acidifying potential. In this paper predictions were made of the acid generating potential of sulfide-containing spoils from the Puentes lignite mine (Galicia, NW Spain), and the limits of sulfur contents allowable for their storage in aerobic conditions, were established. Using samples of fresh spoils, analyses were made of the content and speciation of sulfur, pH was measured after oxidation of the sample with H 2 O 2 (pH of oxidation = pH OX ), and titration of the oxidation extract with 0.1N NaOH to pH = 7 was carried out (Net Acid Production = NAP). The total sulfur content (S T ) varied between 3%, with pyritic-S being the most common form (> 80%). pH OX varied between 1.6 and 6.4 and NAP between 1.2 and 85.0 Kg-CaCO 3 t -1 . A high correlation was found between the NAP and the S T (r-0.98, p T > 0.15% cause high risks of mine-soil acidification, and create the need for large doses of CaCO 3 to be used on final surface of the mine dump. Use of fly ash, produced from the combustion of lignite, as an alternative to commercial lime is more effective in the control of acidity generated by spoils with high S T . 20 refs., 5 figs., 1 tab

Prediction of phospholipidosis-inducing potential of drugs by in vitro biochemical and physicochemical assays followed by multivariate analysis.

Science.gov (United States)

Kuroda, Yukihiro; Saito, Madoka

2010-03-01

An in vitro method to predict phospholipidosis-inducing potential of cationic amphiphilic drugs (CADs) was developed using biochemical and physicochemical assays. The following parameters were applied to principal component analysis, as well as physicochemical parameters: pK(a) and clogP; dissociation constant of CADs from phospholipid, inhibition of enzymatic phospholipid degradation, and metabolic stability of CADs. In the score plot, phospholipidosis-inducing drugs (amiodarone, propranolol, imipramine, chloroquine) were plotted locally forming the subspace for positive CADs; while non-inducing drugs (chlorpromazine, chloramphenicol, disopyramide, lidocaine) were placed scattering out of the subspace, allowing a clear discrimination between both classes of CADs. CADs that often produce false results by conventional physicochemical or cell-based assay methods were accurately determined by our method. Basic and lipophilic disopyramide could be accurately predicted as a nonphospholipidogenic drug. Moreover, chlorpromazine, which is often falsely predicted as a phospholipidosis-inducing drug by in vitro methods, could be accurately determined. Because this method uses the pharmacokinetic parameters pK(a), clogP, and metabolic stability, which are usually obtained in the early stages of drug development, the method newly requires only the two parameters, binding to phospholipid, and inhibition of lipid degradation enzyme. Therefore, this method provides a cost-effective approach to predict phospholipidosis-inducing potential of a drug. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

Appropriate experimental approaches for predicting abuse potential and addictive qualities in preclinical drug discovery.

Science.gov (United States)

Mead, Andy N

2014-11-01

Drug abuse is an increasing social and public health issue, putting the onus on drug developers and regulatory agencies to ensure that the abuse potential of novel drugs is adequately assessed prior to product launch. This review summarizes the core preclinical data that frequently contribute to building an understanding of abuse potential for a new molecular entity, in addition to highlighting models that can provide increased resolution regarding the level of risk. Second, an important distinction between abuse potential and addiction potential is drawn, with comments on how preclinical models can inform on each. While the currently adopted preclinical models possess strong predictive validity, there are areas for future refinement and research. These areas include a more refined use of self-administration models to assess relative reinforcement; and the need for open innovation in pursuing improvements. There is also the need for careful scientifically driven application of models rather than a standardization of methodologies, and the need to explore the opportunities that may exist for enhancing the value of physical dependence and withdrawal studies by focusing on withdrawal-induced drug seeking, rather than broad symptomology.

Reservoir characterization and performance predictions for the E.N. Woods lease

Energy Technology Data Exchange (ETDEWEB)

Aka-Milan, Francis A.

2000-07-07

The task of this work was to evaluate the past performance of the E.N. WOODS Unit and to forecast its future economic performance by taking into consideration the geology, petrophysics and production history of the reservoir. The Decline Curve Analysis feature of the Appraisal of Petroleum Properties including Taxation Systems (EDAPT) software along with the Production Management Systems (PMS) software were used to evaluate the original volume of hydrocarbon in place and estimate the reserve. The Black Oil Simulator (BOAST II) was then used to model the waterflooding operation and estimate the incremental oil production attributable to the water injection. BOAST II was also used to predict future performance of the reservoir.

Beliefs about the Potential Impacts of Exploiting Non-Timber Forest Products Predict Voluntary Participation in Monitoring

Science.gov (United States)

Dantas Brites, Alice; Morsello, Carla

2017-06-01

Harvesting and trading non-timber forest products is advocated as a win-win strategy for conservation and development, yet it can produce negative ecological and socioeconomic impacts. Hence, monitoring exploitation outcomes is essential, and participatory monitoring has been suggested to be the most suitable approach. Among possible approaches, participatory monitoring is preferred because it is likely to increase people's awareness and beliefs regarding impacts or potential impacts, thus inducing behavioral changes, although the evidence in this regard is contradictory. We therefore evaluated whether people's beliefs about the potential ecological and socioeconomic impacts of non-timber forest product exploitation increased their likelihood of volunteering to monitor. We studied a community of forest inhabitants in the Brazilian Amazon who harvested and traded a commercially important non-timber forest product. Two methods of data gathering were employed: (i) a survey of 166 adults (51 households) to evaluate people's beliefs and their stated intention to engage in four different monitoring tasks and (ii) four pilot monitoring tasks to evaluate who actually participated. Based on mixed-effects regressions, the results indicated that beliefs regarding both types of impacts could predict participation in certain tasks, although gender, age and schooling were occasionally stronger predictors. On average, people had stronger beliefs about potential socioeconomic impacts than about potential ecological impacts, with the former also predicting participation in ecological data gathering. This finding reinforces the importance of monitoring both types of impacts to help achieve the win-win outcomes originally proposed by non-timber forest product trade initiatives.

Development of an interatomic EAM type potential for Zr

International Nuclear Information System (INIS)

Pasianot, R.C.; Monti, A.M.

1996-01-01

In the present work are developed interatomic potentials of the embedded atom type (EAM) adequate for computer simulation of microstructural defects in the Zr lattice. It is observed that the less repulsive potential agrees better with the experimental data of the self-interstitial relaxation volume and predicts the basal crowdion as the stable configuration, the basal dumbbell having a formation energy slightly higher (0.01 eV). (author). 9 refs., 1 fig., 3 tabs

The property distance index PD predicts peptides that cross-react with IgE antibodies

Science.gov (United States)

Ivanciuc, Ovidiu; Midoro-Horiuti, Terumi; Schein, Catherine H.; Xie, Liping; Hillman, Gilbert R.; Goldblum, Randall M.; Braun, Werner

2009-01-01

Similarities in the sequence and structure of allergens can explain clinically observed cross-reactivities. Distinguishing sequences that bind IgE in patient sera can be used to identify potentially allergenic protein sequences and aid in the design of hypo-allergenic proteins. The property distance index PD, incorporated in our Structural Database of Allergenic Proteins (SDAP, http://fermi.utmb.edu/SDAP/), may identify potentially cross-reactive segments of proteins, based on their similarity to known IgE epitopes. We sought to obtain experimental validation of the PD index as a quantitative predictor of IgE cross-reactivity, by designing peptide variants with predetermined PD scores relative to three linear IgE epitopes of Jun a 1, the dominant allergen from mountain cedar pollen. For each of the three epitopes, 60 peptides were designed with increasing PD values (decreasing physicochemical similarity) to the starting sequence. The peptides synthesized on a derivatized cellulose membrane were probed with sera from patients who were allergic to Jun a 1, and the experimental data were interpreted with a PD classification method. Peptides with low PD values relative to a given epitope were more likely to bind IgE from the sera than were those with PD values larger than 6. Control sequences, with PD values between 18 and 20 to all the three epitopes, did not bind patient IgE, thus validating our procedure for identifying negative control peptides. The PD index is a statistically validated method to detect discrete regions of proteins that have a high probability of cross-reacting with IgE from allergic patients. PMID:18950868

entrepreneurial potential and success in business: a study on elements of convergence and explanation / O potencial empreendedor e o sucesso empresarial: um estudo sobre elementos de convergência e explicação

Directory of Open Access Journals (Sweden)

Gustavo Henrique Silva de Souza

2016-10-01

Full Text Available Purpose: The study aimed to verify whether there is a difference of entrepreneurial potential between successful entrepreneurs and entrepreneurs who have failed; and whether there are variables that may work as a means of prediction to the success or failure of an entrepreneur. Originality/gap/relevance/implications: It brings up an innovative approach to the entrepreneurship researches, which main content is in the empirical operationalization of success and failure on business for the testing of specific hypothesis and the identification of the antecedents and consequences of entrepreneurial potential. Key methodological aspects: The research was conducted on a descriptive and quantitative approach. We applied the scale of entrepreneurial potential in 246 entrepreneurs, which 100 correspond to the analysis criteria, operationally, as successful entrepreneurs (n = 50 and entrepreneurs who failed (n = 50. Data were analysed by statistics techniques of logistic regression and Student’s t test. Summary of key results: Results show that the successful entrepreneur has higher scores in entrepreneur potential scale than the entrepreneur who failed, in which the main convergence between entrepreneurial potential and business success is the setting business goals. In the investigated sample, the gender showed being a strong predictor of business success, indicating that men have 2.8 times greater chance of success in business than women. Key considerations/conclusions: In our opinion, the results found shed light on crucial elements to the explanation of business success and corroborate recent results brought by research on entrepreneurship and gender. Objetivo: O estudo teve por objetivo verificar (1 se há diferença de potencial empreendedor entre Empreendedores de Sucesso e Empreendedores que fracassaram; e (2 se há variáveis que podem ser consideradas preditoras do sucesso ou fracasso do empreendedor. Originalidade

Potential relationship between Hashimoto's thyroiditis and BRAF(V600E) mutation status in papillary thyroid cancer.

Science.gov (United States)

Zeng, Rui-Chao; Jin, Lang-Ping; Chen, En-Dong; Dong, Si-Yang; Cai, Ye-Feng; Huang, Guan-Li; Li, Quan; Jin, Chun; Zhang, Xiao-Hua; Wang, Ou-Chen

2016-04-01

The purpose of this study was to evaluate the potential relationship between Hashimoto's thyroiditis and BRAF(V600E) mutation status in patients with papillary thyroid carcinoma (PTC). A total of 619 patients with PTC who underwent total thyroidectomy with lymph node dissection were enrolled in this study. Univariable and multivariate analyses were used. Hashimoto's thyroiditis was present in 35.9% (222 of 619) of PTCs. Multivariate logistic regressions showed that BRAF(V600E) mutation, sex, extrathyroidal extension, and lymph node metastasis were independent factors for Hashimoto's thyroiditis. Female sex, more frequent extrathyroidal extension, and a higher incidence of lymph node metastasis were significantly associated with PTCs accompanied by BRAF(V600E) mutation without Hashimoto's thyroiditis compared with PTCs accompanied by BRAF(V600E) mutation with Hashimoto's thyroiditis. Hashimoto's thyroiditis was negatively associated with BRAF(V600E) mutation, extrathyroidal extension, and lymph node metastasis. In addition, Hashimoto's thyroiditis was related to less lymph node metastasis and extrathyroidal extension in PTCs with BRAF(V600E) mutation. Therefore, Hashimoto's thyroiditis is a potentially protective factor in PTC. © 2015 Wiley Periodicals, Inc. Head Neck 38: E1019-E1025, 2016. © 2015 Wiley Periodicals, Inc.

Economic Optimization of Spray Dryer Operation using Nonlinear Model Predictive Control

DEFF Research Database (Denmark)

Petersen, Lars Norbert; Poulsen, Niels Kjølstad; Niemann, Hans Henrik

2014-01-01

In this paper we investigate an economically optimizing Nonlinear Model Predictive Control (E-NMPC) for a spray drying process. By simulation we evaluate the economic potential of this E-NMPC compared to a conventional PID based control strategy. Spray drying is the preferred process to reduce...... the water content for many liquid foodstuffs and produces a free flowing powder. The main challenge in controlling the spray drying process is to meet the residual moisture specifications and avoid that the powder sticks to the chamber walls of the spray dryer. We present a model for a spray dryer that has...... been validated on experimental data from a pilot plant. We use this model for simulation as well as for prediction in the E-NMPC. The E-NMPC is designed with hard input constraints and soft output constraints. The open-loop optimal control problem in the E-NMPC is solved using the single...

Greenhouse crop residues: Energy potential and models for the prediction of their higher heating value

Energy Technology Data Exchange (ETDEWEB)

Callejon-Ferre, A.J.; Lopez-Martinez, J.A.; Manzano-Agugliaro, F. [Departamento de Ingenieria Rural, Universidad de Almeria, Ctra. Sacramento s/n, La Canada de San Urbano, 04120 Almeria (Spain); Velazquez-Marti, B. [Departamento de Ingenieria Rural y Agroalimentaria, Universidad Politecnica de Valencia, Camino de Vera s/n, 46022 Valencia (Spain)

2011-02-15

Almeria, in southeastern Spain, generates some 1,086,261 t year{sup -1} (fresh weight) of greenhouse crop (Cucurbita pepo L., Cucumis sativus L., Solanum melongena L., Solanum lycopersicum L., Phaseoulus vulgaris L., Capsicum annuum L., Citrillus vulgaris Schrad. and Cucumis melo L.) residues. The energy potential of this biomass is unclear. The aim of the present work was to accurately quantify this variable, differentiating between crop species while taking into consideration the area they each occupy. This, however, required the direct analysis of the higher heating value (HHV) of these residues, involving very expensive and therefore not commonly available equipment. Thus, a further aim was to develop models for predicting the HHV of these residues, taking into account variables measured by elemental and/or proximate analysis, thus providing an economically attractive alternative to direct analysis. All the analyses in this work involved the use of worldwide-recognised standards and methods. The total energy potential for these plant residues, as determined by direct analysis, was 1,003,497.49 MW h year{sup -1}. Twenty univariate and multivariate equations were developed to predict the HHV. The R{sup 2} and adjusted R{sup 2} values obtained for the univariate and multivariate models were 0.909 and 0.946 or above respectively. In all cases, the mean absolute percentage error varied between 0.344 and 2.533. These results show that any of these 20 equations could be used to accurately predict the HHV of crop residues. The residues produced by the Almeria greenhouse industry would appear to be an interesting source of renewable energy. (author)

Predicting evolutionary responses when genetic variance and selection covary with the environment: a large-scale Open Access Data approach

NARCIS (Netherlands)

Ramakers, J.J.C.; Culina, A.; Visser, M.E.; Gienapp, P.

2017-01-01

Additive genetic variance and selection are the key ingredients for evolution. In wild populations, however, predicting evolutionary trajectories is difficult, potentially by an unrecognised underlying environment dependency of both (additive) genetic variance and selection (i.e. G×E and S×E).

Seasonal forecasting of synoptic type variability: potential intraseasonal predictability relevant to the Cape south coast of South Africa

CSIR Research Space (South Africa)

Engelbrecht, CJ

2015-09-01

Full Text Available An ensemble of 12 sea-level pressure (SLP) simulations from the United Kingdom Meteorological Office (UKMO) Global Seasonal Forecast System 5 (GloSea5) is used to investigate the potential predictability of synoptic types within 14 austral spring...

Prediction model of potential hepatocarcinogenicity of rat hepatocarcinogens using a large-scale toxicogenomics database

International Nuclear Information System (INIS)

Uehara, Takeki; Minowa, Yohsuke; Morikawa, Yuji; Kondo, Chiaki; Maruyama, Toshiyuki; Kato, Ikuo; Nakatsu, Noriyuki; Igarashi, Yoshinobu; Ono, Atsushi; Hayashi, Hitomi; Mitsumori, Kunitoshi; Yamada, Hiroshi; Ohno, Yasuo; Urushidani, Tetsuro

2011-01-01

The present study was performed to develop a robust gene-based prediction model for early assessment of potential hepatocarcinogenicity of chemicals in rats by using our toxicogenomics database, TG-GATEs (Genomics-Assisted Toxicity Evaluation System developed by the Toxicogenomics Project in Japan). The positive training set consisted of high- or middle-dose groups that received 6 different non-genotoxic hepatocarcinogens during a 28-day period. The negative training set consisted of high- or middle-dose groups of 54 non-carcinogens. Support vector machine combined with wrapper-type gene selection algorithms was used for modeling. Consequently, our best classifier yielded prediction accuracies for hepatocarcinogenicity of 99% sensitivity and 97% specificity in the training data set, and false positive prediction was almost completely eliminated. Pathway analysis of feature genes revealed that the mitogen-activated protein kinase p38- and phosphatidylinositol-3-kinase-centered interactome and the v-myc myelocytomatosis viral oncogene homolog-centered interactome were the 2 most significant networks. The usefulness and robustness of our predictor were further confirmed in an independent validation data set obtained from the public database. Interestingly, similar positive predictions were obtained in several genotoxic hepatocarcinogens as well as non-genotoxic hepatocarcinogens. These results indicate that the expression profiles of our newly selected candidate biomarker genes might be common characteristics in the early stage of carcinogenesis for both genotoxic and non-genotoxic carcinogens in the rat liver. Our toxicogenomic model might be useful for the prospective screening of hepatocarcinogenicity of compounds and prioritization of compounds for carcinogenicity testing. - Highlights: →We developed a toxicogenomic model to predict hepatocarcinogenicity of chemicals. →The optimized model consisting of 9 probes had 99% sensitivity and 97% specificity. �

One-electron standard reduction potentials of nitroaromatic and cyclic nitramine explosives

Energy Technology Data Exchange (ETDEWEB)

Uchimiya, Minori, E-mail: sophie.uchimiya@ars.usda.go [Environmental Laboratory, U.S. Army Engineer Research and Development Center, Vicksburg, MS 39180 (United States); Gorb, Leonid [SpecPro Inc, 3909 Halls Ferry Road, Vicksburg, MS 39180 (United States); Isayev, Olexandr [Department of Chemistry, Case Western Reserve University, Cleveland, OH 44106 (United States); Qasim, Mohammad M. [Environmental Laboratory, U.S. Army Engineer Research and Development Center, Vicksburg, MS 39180 (United States); Leszczynski, Jerzy [Environmental Laboratory, U.S. Army Engineer Research and Development Center, Vicksburg, MS 39180 (United States); Interdisciplinary Center for Nanotoxicity, Jackson State University, Jackson, MS 39217 (United States)

2010-10-15

Extensive studies have been conducted in the past decades to predict the environmental abiotic and biotic redox fate of nitroaromatic and nitramine explosives. However, surprisingly little information is available on one-electron standard reduction potentials (E{sup o}(R-NO{sub 2}/R-NO{sub 2}{sup -})). The E{sup o}(R-NO{sub 2}/R-NO{sub 2}{sup -}) is an essential thermodynamic parameter for predicting the rate and extent of reductive transformation for energetic residues. In this study, experimental (linear free energy relationships) and theoretical (ab initio calculation) approaches were employed to determine E{sup o}(R-NO{sub 2}/R-NO{sub 2}{sup -}) for nitroaromatic, (caged) cyclic nitramine, and nitroimino explosives that are found in military installations or are emerging contaminants. The results indicate a close agreement between experimental and theoretical E{sup o}(R-NO{sub 2}/R-NO{sub 2}{sup -}) and suggest a key trend: E{sup o}(R-NO{sub 2}/R-NO{sub 2}{sup -}) value decreases from di- and tri-nitroaromatic (e.g., 2,4-dinitroanisole) to nitramine (e.g., RDX) to nitroimino compound (e.g., nitroguanidine). The observed trend in E{sup o}(R-NO{sub 2}/R-NO{sub 2}{sup -}) agrees with reported rate trends for reductive degradation, suggesting a thermodynamic control on the reduction rate under anoxic/suboxic conditions. - Reduction of explosives becomes less thermodynamically favorable as the one-electron standard reduction potential decreases from di- and tri-nitroaromatic, nitramine, to nitroimino compounds.

Comparing predicted estrogen concentrations with measurements in US waters

International Nuclear Information System (INIS)

Kostich, Mitch; Flick, Robert; Martinson, John

2013-01-01

The range of exposure rates to the steroidal estrogens estrone (E1), beta-estradiol (E2), estriol (E3), and ethinyl estradiol (EE2) in the aquatic environment was investigated by modeling estrogen introduction via municipal wastewater from sewage plants across the US. Model predictions were compared to published measured concentrations. Predictions were congruent with most of the measurements, but a few measurements of E2 and EE2 exceed those that would be expected from the model, despite very conservative model assumptions of no degradation or in-stream dilution. Although some extreme measurements for EE2 may reflect analytical artifacts, remaining data suggest concentrations of E2 and EE2 may reach twice the 99th percentile predicted from the model. The model and bulk of the measurement data both suggest that cumulative exposure rates to humans are consistently low relative to effect levels, but also suggest that fish exposures to E1, E2, and EE2 sometimes substantially exceed chronic no-effect levels. -- Highlights: •Conservatively modeled steroidal estrogen concentrations in ambient water. •Found reasonable agreement between model and published measurements. •Model and measurements agree that risks to humans are remote. •Model and measurements agree significant questions remain about risk to fish. •Need better understanding of temporal variations and their impact on fish. -- Our model and published measurements for estrogens suggest aquatic exposure rates for humans are below potential effect levels, but fish exposure sometimes exceeds published no-effect levels

Oral administration of drugs with hypersensitivity potential induces germinal center hyperplasia in secondary lymphoid organ/tissue in Brown Norway rats, and this histological lesion is a promising candidate as a predictive biomarker for drug hypersensitivity occurrence in humans

International Nuclear Information System (INIS)

Tamura, Akitoshi; Miyawaki, Izuru; Yamada, Toru; Kimura, Juki; Funabashi, Hitoshi

2013-01-01

It is important to evaluate the potential of drug hypersensitivity as well as other adverse effects during the preclinical stage of the drug development process, but validated methods are not available yet. In the present study we examined whether it would be possible to develop a new predictive model of drug hypersensitivity using Brown Norway (BN) rats. As representative drugs with hypersensitivity potential in humans, phenytoin (PHT), carbamazepine (CBZ), amoxicillin (AMX), and sulfamethoxazole (SMX) were orally administered to BN rats for 28 days to investigate their effects on these animals by examinations including observation of clinical signs, hematology, determination of serum IgE levels, histology, and flow cytometric analysis. Skin rashes were not observed in any animals treated with these drugs. Increases in the number of circulating inflammatory cells and serum IgE level did not necessarily occur in the animals treated with these drugs. However, histological examination revealed that germinal center hyperplasia was commonly induced in secondary lymphoid organs/tissues in the animals treated with these drugs. In cytometric analysis, changes in proportions of lymphocyte subsets were noted in the spleen of the animals treated with PHT or CBZ during the early period of administration. The results indicated that the potential of drug hypersensitivity was identified in BN rat by performing histological examination of secondary lymphoid organs/tissues. Data obtained herein suggested that drugs with hypersensitivity potential in humans gained immune reactivity in BN rat, and the germinal center hyperplasia induced by administration of these drugs may serve as a predictive biomarker for drug hypersensitivity occurrence. - Highlights: • We tested Brown Norway rats as a candidate model for predicting drug hypersensitivity. • The allergic drugs did not induce skin rash, whereas D-penicillamine did so in the rats. • Some of allergic drugs increased

Oral administration of drugs with hypersensitivity potential induces germinal center hyperplasia in secondary lymphoid organ/tissue in Brown Norway rats, and this histological lesion is a promising candidate as a predictive biomarker for drug hypersensitivity occurrence in humans

Energy Technology Data Exchange (ETDEWEB)

Tamura, Akitoshi, E-mail: akitoshi-tamura@ds-pharma.co.jp; Miyawaki, Izuru; Yamada, Toru; Kimura, Juki; Funabashi, Hitoshi

2013-08-15

It is important to evaluate the potential of drug hypersensitivity as well as other adverse effects during the preclinical stage of the drug development process, but validated methods are not available yet. In the present study we examined whether it would be possible to develop a new predictive model of drug hypersensitivity using Brown Norway (BN) rats. As representative drugs with hypersensitivity potential in humans, phenytoin (PHT), carbamazepine (CBZ), amoxicillin (AMX), and sulfamethoxazole (SMX) were orally administered to BN rats for 28 days to investigate their effects on these animals by examinations including observation of clinical signs, hematology, determination of serum IgE levels, histology, and flow cytometric analysis. Skin rashes were not observed in any animals treated with these drugs. Increases in the number of circulating inflammatory cells and serum IgE level did not necessarily occur in the animals treated with these drugs. However, histological examination revealed that germinal center hyperplasia was commonly induced in secondary lymphoid organs/tissues in the animals treated with these drugs. In cytometric analysis, changes in proportions of lymphocyte subsets were noted in the spleen of the animals treated with PHT or CBZ during the early period of administration. The results indicated that the potential of drug hypersensitivity was identified in BN rat by performing histological examination of secondary lymphoid organs/tissues. Data obtained herein suggested that drugs with hypersensitivity potential in humans gained immune reactivity in BN rat, and the germinal center hyperplasia induced by administration of these drugs may serve as a predictive biomarker for drug hypersensitivity occurrence. - Highlights: • We tested Brown Norway rats as a candidate model for predicting drug hypersensitivity. • The allergic drugs did not induce skin rash, whereas D-penicillamine did so in the rats. • Some of allergic drugs increased

Predictive value of neurological examination for early cortical responses to somatosensory evoked potentials in patients with postanoxic coma

NARCIS (Netherlands)

Bouwes, Aline; Binnekade, Jan M.; Verbaan, Bart W.; Zandbergen, Eveline G. J.; Koelman, Johannes H. T. M.; Weinstein, Henry C.; Hijdra, Albert; Horn, Janneke

2012-01-01

Bilateral absence of cortical N20 responses of median nerve somatosensory evoked potentials (SEP) predicts poor neurological outcome in postanoxic coma after cardiopulmonary resuscitation (CPR). Although SEP is easy to perform and available in most hospitals, it is worthwhile to know how

Predictive Power of Machine Learning for Optimizing Solar Water Heater Performance: The Potential Application of High-Throughput Screening

Directory of Open Access Journals (Sweden)

Hao Li

2017-01-01

Full Text Available Predicting the performance of solar water heater (SWH is challenging due to the complexity of the system. Fortunately, knowledge-based machine learning can provide a fast and precise prediction method for SWH performance. With the predictive power of machine learning models, we can further solve a more challenging question: how to cost-effectively design a high-performance SWH? Here, we summarize our recent studies and propose a general framework of SWH design using a machine learning-based high-throughput screening (HTS method. Design of water-in-glass evacuated tube solar water heater (WGET-SWH is selected as a case study to show the potential application of machine learning-based HTS to the design and optimization of solar energy systems.

Prediction of Active Site and Distal Residues in E. coli DNA Polymerase III alpha Polymerase Activity.

Science.gov (United States)

Parasuram, Ramya; Coulther, Timothy A; Hollander, Judith M; Keston-Smith, Elise; Ondrechen, Mary Jo; Beuning, Penny J

2018-02-20

The process of DNA replication is carried out with high efficiency and accuracy by DNA polymerases. The replicative polymerase in E. coli is DNA Pol III, which is a complex of 10 different subunits that coordinates simultaneous replication on the leading and lagging strands. The 1160-residue Pol III alpha subunit is responsible for the polymerase activity and copies DNA accurately, making one error per 10 5 nucleotide incorporations. The goal of this research is to determine the residues that contribute to the activity of the polymerase subunit. Homology modeling and the computational methods of THEMATICS and POOL were used to predict functionally important amino acid residues through their computed chemical properties. Site-directed mutagenesis and biochemical assays were used to validate these predictions. Primer extension, steady-state single-nucleotide incorporation kinetics, and thermal denaturation assays were performed to understand the contribution of these residues to the function of the polymerase. This work shows that the top 15 residues predicted by POOL, a set that includes the three previously known catalytic aspartate residues, seven remote residues, plus five previously unexplored first-layer residues, are important for function. Six previously unidentified residues, R362, D405, K553, Y686, E688, and H760, are each essential to Pol III activity; three additional residues, Y340, R390, and K758, play important roles in activity.

Localization and prediction of malignant potential in recurrent pheochromocytoma/paraganglioma (PCC/PGL) using 18F-FDG PET/CT.

Science.gov (United States)

Fikri, Ahmad Saad Fathinul; Kroiss, A; Ahmad, A Z F; Zanariah, H; Lau, W F E; Uprimny, C; Donnemiller, E; Kendler, D; Nordin, A J; Virgolini, I J

2014-06-01

To our knowledge, data are lacking on the role of 18F-FDG PET/CT in the localization and prediction of neuroendocrine tumors, in particular the pheochromocytoma/paraganglioma (PCC/PGL) group. To evaluate the role of 18F-FDG PET/CT in localizing and predicting the malignant potential of PCC/PGL. Twenty-three consecutive patients with a history of PCC/PGL, presenting with symptoms related to catecholamine excess, underwent 18F-FDG PET/CT. Final confirmation of the diagnosis was made using the composite references. PET/CT findings were analyzed on a per-lesion basis and a per-patient basis. Tumor SUVmax was analyzed to predict the dichotomization of patient endpoints for the local disease and metastatic groups. We investigated 23 patients (10 men, 13 women) with a mean age of 46.43 ± 3.70 years. Serum catecholamine levels were elevated in 82.60% of these patients. There were 136 sites (mean SUVmax: 16.39 ± 3.47) of validated disease recurrence. The overall sensitivities for diagnostic CT, FDG PET, and FDG PET/CT were 86.02%, 87.50%, and 98.59%, respectively. Based on the composite references, 39.10% of patients had local disease. There were significant differences in the SUVmax distribution between the local disease and metastatic groups; a significant correlation was noted when a SUVmax cut-off was set at 9.2 (Plocalization of recurrent tumors. Tumor SUVmax is a potentially useful predictor of malignant tumor potential. © The Foundation Acta Radiologica 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Biochemical methane potential prediction of plant biomasses: Comparing chemical composition versus near infrared methods and linear versus non-linear models.

Science.gov (United States)

Godin, Bruno; Mayer, Frédéric; Agneessens, Richard; Gerin, Patrick; Dardenne, Pierre; Delfosse, Philippe; Delcarte, Jérôme

2015-01-01

The reliability of different models to predict the biochemical methane potential (BMP) of various plant biomasses using a multispecies dataset was compared. The most reliable prediction models of the BMP were those based on the near infrared (NIR) spectrum compared to those based on the chemical composition. The NIR predictions of local (specific regression and non-linear) models were able to estimate quantitatively, rapidly, cheaply and easily the BMP. Such a model could be further used for biomethanation plant management and optimization. The predictions of non-linear models were more reliable compared to those of linear models. The presentation form (green-dried, silage-dried and silage-wet form) of biomasses to the NIR spectrometer did not influence the performances of the NIR prediction models. The accuracy of the BMP method should be improved to enhance further the BMP prediction models. Copyright © 2014 Elsevier Ltd. All rights reserved.

Centrality of positive and negative deployment memories predicts posttraumatic growth in danish veterans

DEFF Research Database (Denmark)

Staugaard, Søren Risløv; Johannessen, Kim Berg; Thomsen, Yvonne Duval

2015-01-01

OBJECTIVE: The purpose of the present study was to examine theoretically motivated predictors for the development of positive changes following potentially traumatic experiences (i.e., posttraumatic growth). Specifically, we wanted to examine the prediction that memories of highly negative......-sectional analyses of the data. RESULTS: The main findings were that the centrality of highly emotional memories from deployment predicted growth alongside openness to experience, combat exposure, and social support. Importantly, the centrality of both positive and negative memories predicted growth equally well...

gCUP: rapid GPU-based HIV-1 co-receptor usage prediction for next-generation sequencing.

Science.gov (United States)

Olejnik, Michael; Steuwer, Michel; Gorlatch, Sergei; Heider, Dominik

2014-11-15

Next-generation sequencing (NGS) has a large potential in HIV diagnostics, and genotypic prediction models have been developed and successfully tested in the recent years. However, albeit being highly accurate, these computational models lack computational efficiency to reach their full potential. In this study, we demonstrate the use of graphics processing units (GPUs) in combination with a computational prediction model for HIV tropism. Our new model named gCUP, parallelized and optimized for GPU, is highly accurate and can classify >175 000 sequences per second on an NVIDIA GeForce GTX 460. The computational efficiency of our new model is the next step to enable NGS technologies to reach clinical significance in HIV diagnostics. Moreover, our approach is not limited to HIV tropism prediction, but can also be easily adapted to other settings, e.g. drug resistance prediction. The source code can be downloaded at http://www.heiderlab.de d.heider@wz-straubing.de. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Can phylogeny predict chemical diversity and potential medicinal activity of plants? A case study of Amaryllidaceae

DEFF Research Database (Denmark)

Rønsted, Nina; Symonds, Matthew R. E.; Birkholm, Trine

2012-01-01

a predictive approach enabling more efficient selection of plants for the development of traditional medicine and lead discovery. However, this relationship has rarely been rigorously tested and the potential predictive power is consequently unknown. Results: We produced a phylogenetic hypothesis......Background: During evolution, plants and other organisms have developed a diversity of chemical defences, leading to the evolution of various groups of specialized metabolites selected for their endogenous biological function. A correlation between phylogeny and biosynthetic pathways could offer...... for the medicinally important plant subfamily Amaryllidoideae (Amaryllidaceae) based on parsimony and Bayesian analysis of nuclear, plastid, and mitochondrial DNA sequences of over 100 species. We tested if alkaloid diversity and activity in bioassays related to the central nervous system are significantly correlated...

WE-E-17A-02: Predictive Modeling of Outcome Following SABR for NSCLC Based On Radiomics of FDG-PET Images

Energy Technology Data Exchange (ETDEWEB)

Li, R; Aguilera, T; Shultz, D; Rubin, D; Diehn, M; Loo, B [Stanford University, Stanford, CA (United States)

2014-06-15

Purpose: This study aims to develop predictive models of patient outcome by extracting advanced imaging features (i.e., Radiomics) from FDG-PET images. Methods: We acquired pre-treatment PET scans for 51 stage I NSCLC patients treated with SABR. We calculated 139 quantitative features from each patient PET image, including 5 morphological features, 8 statistical features, 27 texture features, and 100 features from the intensity-volume histogram. Based on the imaging features, we aim to distinguish between 2 risk groups of patients: those with regional failure or distant metastasis versus those without. We investigated 3 pattern classification algorithms: linear discriminant analysis (LDA), naive Bayes (NB), and logistic regression (LR). To avoid the curse of dimensionality, we performed feature selection by first removing redundant features and then applying sequential forward selection using the wrapper approach. To evaluate the predictive performance, we performed 10-fold cross validation with 1000 random splits of the data and calculated the area under the ROC curve (AUC). Results: Feature selection identified 2 texture features (homogeneity and/or wavelet decompositions) for NB and LR, while for LDA SUVmax and one texture feature (correlation) were identified. All 3 classifiers achieved statistically significant improvements over conventional PET imaging metrics such as tumor volume (AUC = 0.668) and SUVmax (AUC = 0.737). Overall, NB achieved the best predictive performance (AUC = 0.806). This also compares favorably with MTV using the best threshold at an SUV of 11.6 (AUC = 0.746). At a sensitivity of 80%, NB achieved 69% specificity, while SUVmax and tumor volume only had 36% and 47% specificity. Conclusion: Through a systematic analysis of advanced PET imaging features, we are able to build models with improved predictive value over conventional imaging metrics. If validated in a large independent cohort, the proposed techniques could potentially aid in

WE-E-17A-02: Predictive Modeling of Outcome Following SABR for NSCLC Based On Radiomics of FDG-PET Images

International Nuclear Information System (INIS)

Li, R; Aguilera, T; Shultz, D; Rubin, D; Diehn, M; Loo, B

2014-01-01

Purpose: This study aims to develop predictive models of patient outcome by extracting advanced imaging features (i.e., Radiomics) from FDG-PET images. Methods: We acquired pre-treatment PET scans for 51 stage I NSCLC patients treated with SABR. We calculated 139 quantitative features from each patient PET image, including 5 morphological features, 8 statistical features, 27 texture features, and 100 features from the intensity-volume histogram. Based on the imaging features, we aim to distinguish between 2 risk groups of patients: those with regional failure or distant metastasis versus those without. We investigated 3 pattern classification algorithms: linear discriminant analysis (LDA), naive Bayes (NB), and logistic regression (LR). To avoid the curse of dimensionality, we performed feature selection by first removing redundant features and then applying sequential forward selection using the wrapper approach. To evaluate the predictive performance, we performed 10-fold cross validation with 1000 random splits of the data and calculated the area under the ROC curve (AUC). Results: Feature selection identified 2 texture features (homogeneity and/or wavelet decompositions) for NB and LR, while for LDA SUVmax and one texture feature (correlation) were identified. All 3 classifiers achieved statistically significant improvements over conventional PET imaging metrics such as tumor volume (AUC = 0.668) and SUVmax (AUC = 0.737). Overall, NB achieved the best predictive performance (AUC = 0.806). This also compares favorably with MTV using the best threshold at an SUV of 11.6 (AUC = 0.746). At a sensitivity of 80%, NB achieved 69% specificity, while SUVmax and tumor volume only had 36% and 47% specificity. Conclusion: Through a systematic analysis of advanced PET imaging features, we are able to build models with improved predictive value over conventional imaging metrics. If validated in a large independent cohort, the proposed techniques could potentially aid in

The 13Carbon footprint of B[e] supergiants

Science.gov (United States)

Liermann, A.; Kraus, M.; Schnurr, O.; Fernandes, M. Borges

2010-10-01

We report on the first detection of 13C enhancement in two B[e] supergiants (B[e]SGs) in the Large Magellanic Cloud. Stellar evolution models predict the surface abundance in 13C to strongly increase during main-sequence and post-main-sequence evolution of massive stars. However, direct identification of chemically processed material on the surface of B[e]SGs is hampered by their dense, disc-forming winds, hiding the stars. Recent theoretical computations predict the detectability of enhanced 13C via the molecular emission in 13CO arising in the circumstellar discs of B[e]SGs. To test this potential method and to unambiguously identify a post-main-sequence B[e] SG by its 13CO emission, we have obtained high-quality K-band spectra of two known B[e] SGs in the Large Magellanic Cloud, using the Very Large Telescope's Spectrograph for INtegral Field Observation in the Near-Infrared (VLT/SINFONI). Both stars clearly show the 13CO band emission, whose strength implies a strong enhancement of 13C, in agreement with theoretical predictions. This first ever direct confirmation of the evolved nature of B[e]SGs thus paves the way to the first identification of a Galactic B[e]SG. Based on observations collected with the ESO VLT Paranal Observatory under programme 384.D-1078(A). E-mail: liermann@mpifr-bonn.mpg.de (AL); kraus@sunstel.asu.cas.cz (MK); oschnurr@aip.de (OS); borges@on.br (MBF)

A GIS model predicting potential distributions of a lineage: a test case on hermit spiders (Nephilidae: Nephilengys).

Science.gov (United States)

Năpăruş, Magdalena; Kuntner, Matjaž

2012-01-01

Although numerous studies model species distributions, these models are almost exclusively on single species, while studies of evolutionary lineages are preferred as they by definition study closely related species with shared history and ecology. Hermit spiders, genus Nephilengys, represent an ecologically important but relatively species-poor lineage with a globally allopatric distribution. Here, we model Nephilengys global habitat suitability based on known localities and four ecological parameters. We geo-referenced 751 localities for the four most studied Nephilengys species: N. cruentata (Africa, New World), N. livida (Madagascar), N. malabarensis (S-SE Asia), and N. papuana (Australasia). For each locality we overlaid four ecological parameters: elevation, annual mean temperature, annual mean precipitation, and land cover. We used linear backward regression within ArcGIS to select two best fit parameters per species model, and ModelBuilder to map areas of high, moderate and low habitat suitability for each species within its directional distribution. For Nephilengys cruentata suitable habitats are mid elevation tropics within Africa (natural range), a large part of Brazil and the Guianas (area of synanthropic spread), and even North Africa, Mediterranean, and Arabia. Nephilengys livida is confined to its known range with suitable habitats being mid-elevation natural and cultivated lands. Nephilengys malabarensis, however, ranges across the Equator throughout Asia where the model predicts many areas of high ecological suitability in the wet tropics. Its directional distribution suggests the species may potentially spread eastwards to New Guinea where the suitable areas of N. malabarensis largely surpass those of the native N. papuana, a species that prefers dry forests of Australian (sub)tropics. Our model is a customizable GIS tool intended to predict current and future potential distributions of globally distributed terrestrial lineages. Its predictive

A GIS model predicting potential distributions of a lineage: a test case on hermit spiders (Nephilidae: Nephilengys.

Directory of Open Access Journals (Sweden)

Magdalena Năpăruş

Full Text Available BACKGROUND: Although numerous studies model species distributions, these models are almost exclusively on single species, while studies of evolutionary lineages are preferred as they by definition study closely related species with shared history and ecology. Hermit spiders, genus Nephilengys, represent an ecologically important but relatively species-poor lineage with a globally allopatric distribution. Here, we model Nephilengys global habitat suitability based on known localities and four ecological parameters. METHODOLOGY/PRINCIPAL FINDINGS: We geo-referenced 751 localities for the four most studied Nephilengys species: N. cruentata (Africa, New World, N. livida (Madagascar, N. malabarensis (S-SE Asia, and N. papuana (Australasia. For each locality we overlaid four ecological parameters: elevation, annual mean temperature, annual mean precipitation, and land cover. We used linear backward regression within ArcGIS to select two best fit parameters per species model, and ModelBuilder to map areas of high, moderate and low habitat suitability for each species within its directional distribution. For Nephilengys cruentata suitable habitats are mid elevation tropics within Africa (natural range, a large part of Brazil and the Guianas (area of synanthropic spread, and even North Africa, Mediterranean, and Arabia. Nephilengys livida is confined to its known range with suitable habitats being mid-elevation natural and cultivated lands. Nephilengys malabarensis, however, ranges across the Equator throughout Asia where the model predicts many areas of high ecological suitability in the wet tropics. Its directional distribution suggests the species may potentially spread eastwards to New Guinea where the suitable areas of N. malabarensis largely surpass those of the native N. papuana, a species that prefers dry forests of Australian (subtropics. CONCLUSIONS: Our model is a customizable GIS tool intended to predict current and future potential

A new measure-correlate-predict approach for resource assessment

Energy Technology Data Exchange (ETDEWEB)

Joensen, A; Landberg, L [Risoe National Lab., Dept. of Wind Energy and Atmospheric Physics, Roskilde (Denmark); Madsen, H [The Technical Univ. of Denmark, Dept. of Mathematical Modelling, Lyngby (Denmark)

1999-03-01

In order to find reasonable candidate site for wind farms, it is of great importance to be able to calculate the wind resource at potential sites. One way to solve this problem is to measure wind speed and direction at the site, and use these measurements to predict the resource. If the measurements at the potential site cover less than e.g. one year, which most likely will be the case, it is not possible to get a reliable estimate of the long-term resource, using this approach. If long-term measurements from e.g. some nearby meteorological station are available, however, then statistical methods can be used to find a relation between the measurements at the site and at the meteorological station. This relation can then be used to transform the long-term measurements to the potential site, and the resource can be calculated using the transformed measurements. Here, a varying-coefficient model, estimated using local regression, is applied in order to establish a relation between the measurements. The approach is evaluated using measurements from two sites, located approximately two kilometres apart, and the results show that the resource in this case can be predicted accurately, although this approach has serious shortcomings. (au)

A scientometric prediction of the discovery of the first potentially habitable planet with a mass similar to Earth.

Science.gov (United States)

Arbesman, Samuel; Laughlin, Gregory

2010-10-04

The search for a habitable extrasolar planet has long interested scientists, but only recently have the tools become available to search for such planets. In the past decades, the number of known extrasolar planets has ballooned into the hundreds, and with it, the expectation that the discovery of the first Earth-like extrasolar planet is not far off. Here, we develop a novel metric of habitability for discovered planets and use this to arrive at a prediction for when the first habitable planet will be discovered. Using a bootstrap analysis of currently discovered exoplanets, we predict the discovery of the first Earth-like planet to be announced in the first half of 2011, with the likeliest date being early May 2011. Our predictions, using only the properties of previously discovered exoplanets, accord well with external estimates for the discovery of the first potentially habitable extrasolar planet and highlight the the usefulness of predictive scientometric techniques to understand the pace of scientific discovery in many fields.

Adsorption of metal atoms at a buckled graphene grain boundary using model potentials

International Nuclear Information System (INIS)

Helgee, Edit E.; Isacsson, Andreas

2016-01-01

Two model potentials have been evaluated with regard to their ability to model adsorption of single metal atoms on a buckled graphene grain boundary. One of the potentials is a Lennard-Jones potential parametrized for gold and carbon, while the other is a bond-order potential parametrized for the interaction between carbon and platinum. Metals are expected to adsorb more strongly to grain boundaries than to pristine graphene due to their enhanced adsorption at point defects resembling those that constitute the grain boundary. Of the two potentials considered here, only the bond-order potential reproduces this behavior and predicts the energy of the adsorbate to be about 0.8 eV lower at the grain boundary than on pristine graphene. The Lennard-Jones potential predicts no significant difference in energy between adsorbates at the boundary and on pristine graphene. These results indicate that the Lennard-Jones potential is not suitable for studies of metal adsorption on defects in graphene, and that bond-order potentials are preferable

Plasma Levels of Soluble HLA-E and HLA-F at Diagnosis May Predict Overall Survival of Neuroblastoma Patients

Directory of Open Access Journals (Sweden)

Fabio Morandi

2013-01-01

Full Text Available The purpose of this study was to identify the plasma/serum biomarkers that are able to predict overall survival (OS of neuroblastoma (NB patients. Concentration of soluble (s biomarkers was evaluated in plasma (sHLA-E, sHLA-F, chromogranin, and B7H3 or serum (calprotectin samples from NB patients or healthy children. The levels of biomarkers that were significantly higher in NB patients were then analyzed considering localized or metastatic subsets. Finally, biomarkers that were significantly different in these two subsets were correlated with patient’s outcome. With the exception of B7H3, levels of all molecules were significantly higher in NB patients than those in controls. However, only chromogranin, sHLA-E, and sHLA-F levels were different between patients with metastatic and localized tumors. sHLA-E and -F levels correlated with each other but not chromogranin. Chromogranin levels correlated with different event-free survival (EFS, whereas sHLA-E and -F levels also correlated with different OS. Association with OS was also detected considering only patients with metastatic disease. In conclusion, low levels of sHLA-E and -F significantly associated with worse EFS/OS in the whole cohort of NB patients and in patients with metastatic NB. Thus, these molecules deserve to be tested in prospective studies to evaluate their predictive power for high-risk NB patients.

Investigating the potential use of environmental DNA (eDNA for genetic monitoring of marine mammals.

Directory of Open Access Journals (Sweden)

Andrew D Foote

Full Text Available The exploitation of non-invasive samples has been widely used in genetic monitoring of terrestrial species. In aquatic ecosystems, non-invasive samples such as feces, shed hair or skin, are less accessible. However, the use of environmental DNA (eDNA has recently been shown to be an effective tool for genetic monitoring of species presence in freshwater ecosystems. Detecting species in the marine environment using eDNA potentially offers a greater challenge due to the greater dilution, amount of mixing and salinity compared with most freshwater ecosystems. To determine the potential use of eDNA for genetic monitoring we used specific primers that amplify short mitochondrial DNA sequences to detect the presence of a marine mammal, the harbor porpoise, Phocoena phocoena, in a controlled environment and in natural marine locations. The reliability of the genetic detections was investigated by comparing with detections of harbor porpoise echolocation clicks by static acoustic monitoring devices. While we were able to consistently genetically detect the target species under controlled conditions, the results from natural locations were less consistent and detection by eDNA was less successful than acoustic detections. However, at one site we detected long-finned pilot whale, Globicephala melas, a species rarely sighted in the Baltic. Therefore, with optimization aimed towards processing larger volumes of seawater this method has the potential to compliment current visual and acoustic methods of species detection of marine mammals.

Potentials of mean force for protein structure prediction vindicated, formalized and generalized.

Directory of Open Access Journals (Sweden)

Thomas Hamelryck

Full Text Available Understanding protein structure is of crucial importance in science, medicine and biotechnology. For about two decades, knowledge-based potentials based on pairwise distances--so-called "potentials of mean force" (PMFs--have been center stage in the prediction and design of protein structure and the simulation of protein folding. However, the validity, scope and limitations of these potentials are still vigorously debated and disputed, and the optimal choice of the reference state--a necessary component of these potentials--is an unsolved problem. PMFs are loosely justified by analogy to the reversible work theorem in statistical physics, or by a statistical argument based on a likelihood function. Both justifications are insightful but leave many questions unanswered. Here, we show for the first time that PMFs can be seen as approximations to quantities that do have a rigorous probabilistic justification: they naturally arise when probability distributions over different features of proteins need to be combined. We call these quantities "reference ratio distributions" deriving from the application of the "reference ratio method." This new view is not only of theoretical relevance but leads to many insights that are of direct practical use: the reference state is uniquely defined and does not require external physical insights; the approach can be generalized beyond pairwise distances to arbitrary features of protein structure; and it becomes clear for which purposes the use of these quantities is justified. We illustrate these insights with two applications, involving the radius of gyration and hydrogen bonding. In the latter case, we also show how the reference ratio method can be iteratively applied to sculpt an energy funnel. Our results considerably increase the understanding and scope of energy functions derived from known biomolecular structures.

A predictive model of iron oxide nanoparticles flocculation tuning Z-potential in aqueous environment for biological application

Energy Technology Data Exchange (ETDEWEB)

Baldassarre, Francesca, E-mail: francesca.baldassarre@unisalento.it [University of Salento, Department of Cultural Heritage (Italy); Cacciola, Matteo, E-mail: matteo.cacciola@unirc.it [University “Mediterranea” of Reggio Calabria, DICEAM (Italy); Ciccarella, Giuseppe, E-mail: giuseppe.ciccarella@unisalento.it [University of Salento, Department of Innovation Engineering (Italy)

2015-09-15

Iron oxide nanoparticles are the most used magnetic nanoparticles in biomedical and biotechnological field because of their nontoxicity respect to the other metals. The investigation of iron oxide nanoparticles behaviour in aqueous environment is important for the biological applications in terms of polydispersity, mobility, cellular uptake and response to the external magnetic field. Iron oxide nanoparticles tend to agglomerate in aqueous solutions; thus, the stabilisation and aggregation could be modified tuning the colloids physical proprieties. Surfactants or polymers are often used to avoid agglomeration and increase nanoparticles stability. We have modelled and synthesised iron oxide nanoparticles through a co-precipitation method, in order to study the influence of surfactants and coatings on the aggregation state. Thus, we compared experimental results to simulation model data. The change of Z-potential and the clusters size were determined by Dynamic Light Scattering. We developed a suitable numerical model to predict the flocculation. The effects of Volume Mean Diameter and fractal dimension were explored in the model. We obtained the trend of these parameters tuning the Z-potential. These curves matched with the experimental results and confirmed the goodness of the model. Subsequently, we exploited the model to study the influence of nanoparticles aggregation and stability by Z-potential and external magnetic field. The highest Z-potential is reached up with a small external magnetic influence, a small aggregation and then a high suspension stability. Thus, we obtained a predictive model of Iron oxide nanoparticles flocculation that will be exploited for the nanoparticles engineering and experimental setup of bioassays.

A predictive model of iron oxide nanoparticles flocculation tuning Z-potential in aqueous environment for biological application

International Nuclear Information System (INIS)

Baldassarre, Francesca; Cacciola, Matteo; Ciccarella, Giuseppe

2015-01-01

Iron oxide nanoparticles are the most used magnetic nanoparticles in biomedical and biotechnological field because of their nontoxicity respect to the other metals. The investigation of iron oxide nanoparticles behaviour in aqueous environment is important for the biological applications in terms of polydispersity, mobility, cellular uptake and response to the external magnetic field. Iron oxide nanoparticles tend to agglomerate in aqueous solutions; thus, the stabilisation and aggregation could be modified tuning the colloids physical proprieties. Surfactants or polymers are often used to avoid agglomeration and increase nanoparticles stability. We have modelled and synthesised iron oxide nanoparticles through a co-precipitation method, in order to study the influence of surfactants and coatings on the aggregation state. Thus, we compared experimental results to simulation model data. The change of Z-potential and the clusters size were determined by Dynamic Light Scattering. We developed a suitable numerical model to predict the flocculation. The effects of Volume Mean Diameter and fractal dimension were explored in the model. We obtained the trend of these parameters tuning the Z-potential. These curves matched with the experimental results and confirmed the goodness of the model. Subsequently, we exploited the model to study the influence of nanoparticles aggregation and stability by Z-potential and external magnetic field. The highest Z-potential is reached up with a small external magnetic influence, a small aggregation and then a high suspension stability. Thus, we obtained a predictive model of Iron oxide nanoparticles flocculation that will be exploited for the nanoparticles engineering and experimental setup of bioassays

Identification of potential prognostic microRNA biomarkers for predicting survival in patients with hepatocellular carcinoma

Directory of Open Access Journals (Sweden)

Liao X

2018-04-01

Full Text Available Xiwen Liao,1 Guangzhi Zhu,1 Rui Huang,2 Chengkun Yang,1 Xiangkun Wang,1 Ketuan Huang,1 Tingdong Yu,1 Chuangye Han,1 Hao Su,1 Tao Peng1 1Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China; 2Department of Hematology, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China Background: The aim of the present study was to identify potential prognostic microRNA (miRNA biomarkers for hepatocellular carcinoma (HCC prognosis prediction based on a dataset from The Cancer Genome Atlas (TCGA. Materials and methods: A miRNA sequencing dataset and corresponding clinical parameters of HCC were obtained from TCGA. Genome-wide univariate Cox regression analysis was used to screen prognostic differentially expressed miRNAs (DEMs, and multivariable Cox regression analysis was used for prognostic signature construction. Comprehensive survival analysis was performed to evaluate the prognostic value of the prognostic signature. Results: Five miRNAs were regarded as prognostic DEMs and used for prognostic signature construction. The five-DEM prognostic signature performed well in prognosis prediction (adjusted P < 0.0001, adjusted hazard ratio = 2.249, 95% confidence interval =1.491–3.394, and time-dependent receiver–operating characteristic (ROC analysis showed an area under the curve (AUC of 0.765, 0.745, 0.725, and 0.687 for 1-, 2-, 3-, and 5-year HCC overall survival (OS prediction, respectively. Comprehensive survival analysis of the prognostic signature suggests that the risk score model could serve as an independent factor of HCC and perform better in prognosis prediction than other traditional clinical indicators. Functional assessment of the target genes of hsa-mir-139 and hsa-mir-5003 indicates that they were significantly enriched in multiple biological processes and pathways, including cell proliferation and cell migration

Probing Higgs self-coupling of a classically scale invariant model in e+e- → Zhh: Evaluation at physical point

Science.gov (United States)

Fujitani, Y.; Sumino, Y.

2018-04-01

A classically scale invariant extension of the standard model predicts large anomalous Higgs self-interactions. We compute missing contributions in previous studies for probing the Higgs triple coupling of a minimal model using the process e+e- → Zhh. Employing a proper order counting, we compute the total and differential cross sections at the leading order, which incorporate the one-loop corrections between zero external momenta and their physical values. Discovery/exclusion potential of a future e+e- collider for this model is estimated. We also find a unique feature in the momentum dependence of the Higgs triple vertex for this class of models.

Predicting Consumer Biomass, Size-Structure, Production, Catch Potential, Responses to Fishing and Associated Uncertainties in the World’s Marine Ecosystems

Science.gov (United States)

Jennings, Simon; Collingridge, Kate

2015-01-01

Existing estimates of fish and consumer biomass in the world’s oceans are disparate. This creates uncertainty about the roles of fish and other consumers in biogeochemical cycles and ecosystem processes, the extent of human and environmental impacts and fishery potential. We develop and use a size-based macroecological model to assess the effects of parameter uncertainty on predicted consumer biomass, production and distribution. Resulting uncertainty is large (e.g. median global biomass 4.9 billion tonnes for consumers weighing 1 g to 1000 kg; 50% uncertainty intervals of 2 to 10.4 billion tonnes; 90% uncertainty intervals of 0.3 to 26.1 billion tonnes) and driven primarily by uncertainty in trophic transfer efficiency and its relationship with predator-prey body mass ratios. Even the upper uncertainty intervals for global predictions of consumer biomass demonstrate the remarkable scarcity of marine consumers, with less than one part in 30 million by volume of the global oceans comprising tissue of macroscopic animals. Thus the apparently high densities of marine life seen in surface and coastal waters and frequently visited abundance hotspots will likely give many in society a false impression of the abundance of marine animals. Unexploited baseline biomass predictions from the simple macroecological model were used to calibrate a more complex size- and trait-based model to estimate fisheries yield and impacts. Yields are highly dependent on baseline biomass and fisheries selectivity. Predicted global sustainable fisheries yield increases ≈4 fold when smaller individuals (production estimates, which have yet to be achieved with complex models, and will therefore help to highlight priorities for future research and data collection. However, the focus on simple model structures and global processes means that non-phytoplankton primary production and several groups, structures and processes of ecological and conservation interest are not represented

Development and formative evaluation of the e-Health Implementation Toolkit (e-HIT

Directory of Open Access Journals (Sweden)

Mair Frances

2010-10-01

Full Text Available Abstract Background The use of Information and Communication Technology (ICT or e-Health is seen as essential for a modern, cost-effective health service. However, there are well documented problems with implementation of e-Health initiatives, despite the existence of a great deal of research into how best to implement e-Health (an example of the gap between research and practice. This paper reports on the development and formative evaluation of an e-Health Implementation Toolkit (e-HIT which aims to summarise and synthesise new and existing research on implementation of e-Health initiatives, and present it to senior managers in a user-friendly format. Results The content of the e-HIT was derived by combining data from a systematic review of reviews of barriers and facilitators to implementation of e-Health initiatives with qualitative data derived from interviews of "implementers", that is people who had been charged with implementing an e-Health initiative. These data were summarised, synthesised and combined with the constructs from the Normalisation Process Model. The software for the toolkit was developed by a commercial company (RocketScience. Formative evaluation was undertaken by obtaining user feedback. There are three components to the toolkit - a section on background and instructions for use aimed at novice users; the toolkit itself; and the report generated by completing the toolkit. It is available to download from http://www.ucl.ac.uk/pcph/research/ehealth/documents/e-HIT.xls Conclusions The e-HIT shows potential as a tool for enhancing future e-Health implementations. Further work is needed to make it fully web-enabled, and to determine its predictive potential for future implementations.

The size prediction of potential inclusions embedded in the sub-surface of fused silica by damage morphology

Directory of Open Access Journals (Sweden)

Gao Xiang

2017-04-01

Full Text Available A model for predicting the size ranges of different potential inclusions initiating damage on the surface of fused silica has been presented. This accounts for the heating of nanometric inclusions whose absorptivity is described based on Mie Theory. The depth profile of impurities has been measured by ICP-OES. By the measured temporal pulse profile on the surface of fused silica, the temperature and thermal stress has been calculated. Furthermore, considering the limit conditions of temperature and thermal stress strength for different damage morphologies, the size range of potential inclusions for fused silica is discussed.

Wave Energy Potential in the Eastern Mediterranean Levantine Basin. An Integrated 10-year Study

Science.gov (United States)

2014-01-01

SUBTITLE Wave energy potential in the Eastern Mediterranean Levantine Basin. An integrated 10-year study 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c... Cardone CV, Ewing JA, et al. The WAM model e a third generation ocean wave prediction model. J Phys Oceanogr 1988;18(12):1775e810. [70] Varinou M

Predicting word sense annotation agreement

DEFF Research Database (Denmark)

Martinez Alonso, Hector; Johannsen, Anders Trærup; Lopez de Lacalle, Oier

2015-01-01

High agreement is a common objective when annotating data for word senses. However, a number of factors make perfect agreement impossible, e.g. the limitations of the sense inventories, the difficulty of the examples or the interpretation preferences of the annotations. Estimating potential...... agreement is thus a relevant task to supplement the evaluation of sense annotations. In this article we propose two methods to predict agreement on word-annotation instances. We experiment with a continuous representation and a three-way discretization of observed agreement. In spite of the difficulty...

Prediction of egg freshness during storage using electronic nose.

Science.gov (United States)

Yimenu, Samuel M; Kim, J Y; Kim, B S

2017-10-01

The aim of the present study was to investigate the potential of a fast gas chromatography (GC) e-nose for freshness discrimination and for prediction of storage time as well as sensory and internal quality changes during storage of hen eggs. All samples were obtained from the same egg production farm and stored at 20 °C for 20 d. Egg sampling was conducted every 0, 3, 6, 9, 12, 16, and 20 d. During each sampling time, 4 egg cartons (each containing 10 eggs) were randomly selected: one carton for Haugh units, one carton for sensory evaluation and 2 cartons for the e-nose experiment. The e-nose study included 2 independent test sets; calibration (35 samples) and validation (28 samples). Every sampling time, 5 replicates were prepared from one egg carton for calibration samples and 4 replicates were prepared from the remaining egg carton for validation samples. Sensors (peaks) were selected prior to multivariate chemometric analysis; qualitative sensors for principal component analysis (PCA) and discriminant factor analysis (DFA) and quantitative sensors for partial least square (PLS) modeling. PCA and DFA confirmed the difference in volatile profiles of egg samples from 7 different storage times accounting for a total variance of 95.7% and 93.71%, respectively. Models for predicting storage time, Haugh units, odor score, and overall acceptability score from e-nose data were developed using calibration samples by PLS regression. The results showed that these quality indices were well predicted from the e- nose signals, with correlation coefficients of R2 = 0.9441, R2 = 0.9511, R2 = 0.9725, and R2 = 0.9530 and with training errors of 0.887, 1.24, 0.626, and 0.629, respectively. As a result of ANOVA, most of the PLS model results were not significantly (P > 0.05) different from the corresponding reference values. These results proved that the fast GC electronic nose has the potential to assess egg freshness and feasibility to predict multiple egg freshness indices

Predictive tests to evaluate oxidative potential of engineered nanomaterials

Science.gov (United States)

Ghiazza, Mara; Carella, Emanuele; Oliaro-Bosso, Simonetta; Corazzari, Ingrid; Viola, Franca; Fenoglio, Ivana

2013-04-01

Oxidative stress constitutes one of the principal injury mechanisms through which particulate toxicants (asbestos, crystalline silica, hard metals) and engineered nanomaterials can induce adverse health effects. ROS may be generated indirectly by activated cells and/or directly at the surface of the material. The occurrence of these processes depends upon the type of material. Many authors have recently demonstrated that metal oxides and carbon-based nanoparticles may influence (increasing or decreasing) the generation of oxygen radicals in a cell environment. Metal oxide, such as iron oxides, crystalline silica, and titanium dioxide are able to generate free radicals via different mechanisms causing an imbalance within oxidant species. The increase of ROS species may lead to inflammatory responses and in some cases to the development of cancer. On the other hand carbon-based nanomaterials, such as fullerene, carbon nanotubes, carbon black as well as cerium dioxide are able to scavenge the free radicals generated acting as antioxidant. The high numbers of new-engineered nanomaterials, which are introduced in the market, are exponentially increasing. Therefore the definition of toxicological strategies is urgently needed. The development of acellular screening tests will make possible the reduction of the number of in vitro and in vivo tests to be performed. An integrated protocol that may be used to predict the oxidant/antioxidant potential of engineered nanoparticles will be here presented.

Predictive tests to evaluate oxidative potential of engineered nanomaterials

International Nuclear Information System (INIS)

Ghiazza, Mara; Carella, Emanuele; Corazzari, Ingrid; Fenoglio, Ivana; Oliaro-Bosso, Simonetta; Viola, Franca

2013-01-01

Oxidative stress constitutes one of the principal injury mechanisms through which particulate toxicants (asbestos, crystalline silica, hard metals) and engineered nanomaterials can induce adverse health effects. ROS may be generated indirectly by activated cells and/or directly at the surface of the material. The occurrence of these processes depends upon the type of material. Many authors have recently demonstrated that metal oxides and carbon-based nanoparticles may influence (increasing or decreasing) the generation of oxygen radicals in a cell environment. Metal oxide, such as iron oxides, crystalline silica, and titanium dioxide are able to generate free radicals via different mechanisms causing an imbalance within oxidant species. The increase of ROS species may lead to inflammatory responses and in some cases to the development of cancer. On the other hand carbon-based nanomaterials, such as fullerene, carbon nanotubes, carbon black as well as cerium dioxide are able to scavenge the free radicals generated acting as antioxidant. The high numbers of new-engineered nanomaterials, which are introduced in the market, are exponentially increasing. Therefore the definition of toxicological strategies is urgently needed. The development of acellular screening tests will make possible the reduction of the number of in vitro and in vivo tests to be performed. An integrated protocol that may be used to predict the oxidant/antioxidant potential of engineered nanoparticles will be here presented.

CADRE-SS, an in Silico Tool for Predicting Skin Sensitization Potential Based on Modeling of Molecular Interactions.

Science.gov (United States)

Kostal, Jakub; Voutchkova-Kostal, Adelina

2016-01-19

Using computer models to accurately predict toxicity outcomes is considered to be a major challenge. However, state-of-the-art computational chemistry techniques can now be incorporated in predictive models, supported by advances in mechanistic toxicology and the exponential growth of computing resources witnessed over the past decade. The CADRE (Computer-Aided Discovery and REdesign) platform relies on quantum-mechanical modeling of molecular interactions that represent key biochemical triggers in toxicity pathways. Here, we present an external validation exercise for CADRE-SS, a variant developed to predict the skin sensitization potential of commercial chemicals. CADRE-SS is a hybrid model that evaluates skin permeability using Monte Carlo simulations, assigns reactive centers in a molecule and possible biotransformations via expert rules, and determines reactivity with skin proteins via quantum-mechanical modeling. The results were promising with an overall very good concordance of 93% between experimental and predicted values. Comparison to performance metrics yielded by other tools available for this endpoint suggests that CADRE-SS offers distinct advantages for first-round screenings of chemicals and could be used as an in silico alternative to animal tests where permissible by legislative programs.

Use of two-potential theory in electron-molecule scattering: Application to wide-angle e-H2 scattering at 40 eV

International Nuclear Information System (INIS)

Ritchie, B.

1984-01-01

A Green's-function approach is used to solve the Schroedinger equation in an effective potential (V 0 ), which is the sum of independent-atom static potentials. The equation for the Green's function is conveniently solved in momentum space (MS), where the MS ''potentials'' (Fourier transforms of the atom-centered potentials) have translational symmetry. The Green's function is then used to construct the solution to the Schroedinger equation for scattering in the potential V-V 0 (where V is the e-molecule static potential plus a local exchange potential) relative to scattering in V 0 . This solution is found in coordinate space using single-center expansions about the internuclear midpoint. These are more rapidly convergent for V-V 0 than for V or V 0 alone. The sum of the amplitudes for scattering in V 0 and in V-V 0 relative to V 0 then represents the amplitude for scattering from the molecule. This method is intended to combine the dynamical methods best suited for each type of potential (multicenter for V 0 and single center for V-V 0 ). It also exposes the shortcomings of the use of V 0 alone

THE EFFECTS OF CRACKING ON THE SURFACE POTENTIAL OF ICY GRAINS IN SATURN’S E-RING: LABORATORY STUDIES

Energy Technology Data Exchange (ETDEWEB)

Bu, Caixia; Bahr, David A.; Dukes, Catherine A.; Baragiola, Raúl A., E-mail: cb8nw@virginia.edu [Laboratory for Astrophysics and Surface Physics, Materials Science and Engineering, University of Virginia, Charlottesville, VA 22904 (United States)

2016-07-10

Within Saturn's E-ring, dust grains are coated by water vapor co-released with ice grains from the geyser-like eruptions of Enceladus. These ice-coated grains have intrinsic surface potential and interact synergistically with the ions and electrons of Saturn's magnetospheric plasmas. We perform laboratory experiments to investigate the effects of water-ice growth on the surface potential, using amorphous solid water (ASW) films. We estimate the growth of the surface potential to be ∼ 2.5 mV (Earth) yr{sup 1} and 112 mV yr{sup 1} for E-ring grains at ∼4.5 R {sub s} and 3.95 R {sub s} outside Enceladus’s plume, respectively. In addition, our measurements show that the linear relationship between the surface potential and the film thickness, as described in previous studies, has an upper limit, where the film spontaneously cracks above a porosity-dependent critical thickness. Heating of the cracked films with (and without) deposited charge shows that significant positive (and negative) surface potentials are retained at temperatures above 110 K, contrary to the minimal values (roughly zero) for thin, transparent ASW films. The significant surface potentials observed on micron-scale cracked ice films after thermal cycling, (5–20) V, are consistent with Cassini measurements, which indicate a negative charge of up to 5 V for E-ring dust particles at ∼5 R {sub s}. Therefore, the native grain surface potential resulting from water-vapor coating must be included in modeling studies of interactions between E-ring icy surfaces and Saturn's magnetospheric plasma.

Remote sensing for predicting potential habitats of Oncomelania hupensis in Hongze, Baima and Gaoyou lakes in Jiangsu province, China

Directory of Open Access Journals (Sweden)

Guo-Jing Yang

2006-11-01

Full Text Available Political and health sector reforms, along with demographic, environmental and socio-economic transformations in the face of global warming, could cause the re-emergence of schistosomiasis in areas where transmission has been successfully interrupted and its emergence in previously non-endemic areas in China. In the present study, we used geographic information systems and remote sensing techniques to predict potential habitats of Oncomelania hupensis, the intermediate host snail of Schistosoma japonicum. Focussing on the Hongze, Baima and Gaoyou lakes in Jiangsu province in eastern China, we developed a model using the normalized difference vegetation index, a tasseled-cap transformed wetness index, and flooding areas to predict snail habitats at a small scale. Data were extracted from two Landsat images, one taken during a typical dry year and the other obtained three years later during a flooding event. An area of approximately 163.6 km2 was predicted as potential O. hupensis habitats around the three lakes, which accounts for 4.3% of the estimated snail habitats in China. In turn, these predicted snail habitats are risk areas for transmission of schistosomiasis, and hence illustrate the scale of the possible impact of climate change and other ecological transformations. The generated risk map can be used by health policy makers to guide mitigation policies targetting the possible spread of O. hupensis, and with the aim of containing the transmission of S. japonicum.

Potential Predictability of the Sea-Surface Temperature Forced Equatorial East Africa Short Rains Interannual Variability in the 20th Century

Science.gov (United States)

Bahaga, T. K.; Gizaw, G.; Kucharski, F.; Diro, G. T.

2014-12-01

In this article, the predictability of the 20th century sea-surface temperature (SST) forced East African short rains variability is analyzed using observational data and ensembles of long atmospheric general circulation model (AGCM) simulations. To our knowledge, such an analysis for the whole 20th century using a series of AGCM ensemble simulations is carried out here for the first time. The physical mechanisms that govern the influence of SST on East African short rains in the model are also investigated. It is found that there is substantial skill in reproducing the East African short rains variability, given that the SSTs are known. Consistent with previous recent studies, it is found that the Indian Ocean and in particular the western pole of the Indian Ocean dipole (IOD) play a dominant role for the prediction skill, whereas SSTs outside the Indian Ocean play a minor role. The physical mechanism for the influence of the western Indian Ocean on East African rainfall in the model is consistent with previous findings and consists of a gill-type response to a warm (cold) anomaly that induces a westerly(easterly) low-level flow anomaly over equatorial Africa and leads to moisture flux convergence (divergence) over East Africa. On the other hand, a positive El Nino-Southern Oscillation (ENSO) anomaly leads to a spatially non-coherent reducing effect over parts of East Africa, but the relationship is not strong enough to provide any predictive skill in our model. The East African short rains prediction skill is also analyzed within a model-derived potential predictability framework and it is shown that the actual prediction skill is broadly consistent with the model potential prediction skill. Low-frequency variations of the prediction skill are mostly related to SSTs outside the Indian Ocean region and are likely due to an increased interference of ENSO with the Indian Ocean influence on East African short rains after the mid-1970s climate shift.

Improving the Prediction of Total Surgical Procedure Time Using Linear Regression Modeling

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Eric R. Edelman

2017-06-01

Full Text Available For efficient utilization of operating rooms (ORs, accurate schedules of assigned block time and sequences of patient cases need to be made. The quality of these planning tools is dependent on the accurate prediction of total procedure time (TPT per case. In this paper, we attempt to improve the accuracy of TPT predictions by using linear regression models based on estimated surgeon-controlled time (eSCT and other variables relevant to TPT. We extracted data from a Dutch benchmarking database of all surgeries performed in six academic hospitals in The Netherlands from 2012 till 2016. The final dataset consisted of 79,983 records, describing 199,772 h of total OR time. Potential predictors of TPT that were included in the subsequent analysis were eSCT, patient age, type of operation, American Society of Anesthesiologists (ASA physical status classification, and type of anesthesia used. First, we computed the predicted TPT based on a previously described fixed ratio model for each record, multiplying eSCT by 1.33. This number is based on the research performed by van Veen-Berkx et al., which showed that 33% of SCT is generally a good approximation of anesthesia-controlled time (ACT. We then systematically tested all possible linear regression models to predict TPT using eSCT in combination with the other available independent variables. In addition, all regression models were again tested without eSCT as a predictor to predict ACT separately (which leads to TPT by adding SCT. TPT was most accurately predicted using a linear regression model based on the independent variables eSCT, type of operation, ASA classification, and type of anesthesia. This model performed significantly better than the fixed ratio model and the method of predicting ACT separately. Making use of these more accurate predictions in planning and sequencing algorithms may enable an increase in utilization of ORs, leading to significant financial and productivity related

Improving the Prediction of Total Surgical Procedure Time Using Linear Regression Modeling.

Science.gov (United States)

Edelman, Eric R; van Kuijk, Sander M J; Hamaekers, Ankie E W; de Korte, Marcel J M; van Merode, Godefridus G; Buhre, Wolfgang F F A

2017-01-01

For efficient utilization of operating rooms (ORs), accurate schedules of assigned block time and sequences of patient cases need to be made. The quality of these planning tools is dependent on the accurate prediction of total procedure time (TPT) per case. In this paper, we attempt to improve the accuracy of TPT predictions by using linear regression models based on estimated surgeon-controlled time (eSCT) and other variables relevant to TPT. We extracted data from a Dutch benchmarking database of all surgeries performed in six academic hospitals in The Netherlands from 2012 till 2016. The final dataset consisted of 79,983 records, describing 199,772 h of total OR time. Potential predictors of TPT that were included in the subsequent analysis were eSCT, patient age, type of operation, American Society of Anesthesiologists (ASA) physical status classification, and type of anesthesia used. First, we computed the predicted TPT based on a previously described fixed ratio model for each record, multiplying eSCT by 1.33. This number is based on the research performed by van Veen-Berkx et al., which showed that 33% of SCT is generally a good approximation of anesthesia-controlled time (ACT). We then systematically tested all possible linear regression models to predict TPT using eSCT in combination with the other available independent variables. In addition, all regression models were again tested without eSCT as a predictor to predict ACT separately (which leads to TPT by adding SCT). TPT was most accurately predicted using a linear regression model based on the independent variables eSCT, type of operation, ASA classification, and type of anesthesia. This model performed significantly better than the fixed ratio model and the method of predicting ACT separately. Making use of these more accurate predictions in planning and sequencing algorithms may enable an increase in utilization of ORs, leading to significant financial and productivity related benefits.

Preliminary Screening a Potential AChE Inhibitor in Thai Golden Shower (Leguminosae mimosoideae Extracts

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Jakkaphun Nanuam

2013-07-01

Full Text Available Pesticides are used to control pests of agriculture products in many countries including Thailand. Since they can exert harmful effects not only on target pests but also on other useful organisms, alternative agents are investigated. We studied the capacity of the Thai golden shower (Leguminosae mimosoideae extracts (root and pod to inhibit acetyl cholinestarese (AChE in the golden apple snail (Pomacea canaliculata as a pest representative. The results showed that the percentage of AChE inhibition increased with increasing in exposure times. The inhibition expressed the same trend in both male and female apple snails. AChE inhibition was higher in extracts from root than from pod. Chromatography-Mass Spectrometer (GC-MS chromatograms demonstrated anthraquinone, an AChE inhibitor, in extracts of golden shower. Our data indicate that a potential AChE inhibitor tends to accumulate more in the root part than in the pod.

Transcriptome-wide identification of Rauvolfia serpentina microRNAs and prediction of their potential targets.

Science.gov (United States)

Prakash, Pravin; Rajakani, Raja; Gupta, Vikrant

2016-04-01

MicroRNAs (miRNAs) are small non-coding RNAs of ∼ 19-24 nucleotides (nt) in length and considered as potent regulators of gene expression at transcriptional and post-transcriptional levels. Here we report the identification and characterization of 15 conserved miRNAs belonging to 13 families from Rauvolfia serpentina through in silico analysis of available nucleotide dataset. The identified mature R. serpentina miRNAs (rse-miRNAs) ranged between 20 and 22nt in length, and the average minimal folding free energy index (MFEI) value of rse-miRNA precursor sequences was found to be -0.815 kcal/mol. Using the identified rse-miRNAs as query, their potential targets were predicted in R. serpentina and other plant species. Gene Ontology (GO) annotation showed that predicted targets of rse-miRNAs include transcription factors as well as genes involved in diverse biological processes such as primary and secondary metabolism, stress response, disease resistance, growth, and development. Few rse-miRNAs were predicted to target genes of pharmaceutically important secondary metabolic pathways such as alkaloids and anthocyanin biosynthesis. Phylogenetic analysis showed the evolutionary relationship of rse-miRNAs and their precursor sequences to homologous pre-miRNA sequences from other plant species. The findings under present study besides giving first hand information about R. serpentina miRNAs and their targets, also contributes towards the better understanding of miRNA-mediated gene regulatory processes in plants. Copyright © 2015 Elsevier Ltd. All rights reserved.

A scientometric prediction of the discovery of the first potentially habitable planet with a mass similar to Earth.

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Samuel Arbesman

Full Text Available BACKGROUND: The search for a habitable extrasolar planet has long interested scientists, but only recently have the tools become available to search for such planets. In the past decades, the number of known extrasolar planets has ballooned into the hundreds, and with it, the expectation that the discovery of the first Earth-like extrasolar planet is not far off. METHODOLOGY/PRINCIPAL FINDINGS: Here, we develop a novel metric of habitability for discovered planets and use this to arrive at a prediction for when the first habitable planet will be discovered. Using a bootstrap analysis of currently discovered exoplanets, we predict the discovery of the first Earth-like planet to be announced in the first half of 2011, with the likeliest date being early May 2011. CONCLUSIONS/SIGNIFICANCE: Our predictions, using only the properties of previously discovered exoplanets, accord well with external estimates for the discovery of the first potentially habitable extrasolar planet and highlight the the usefulness of predictive scientometric techniques to understand the pace of scientific discovery in many fields.

eShadow: A tool for comparing closely related sequences

Energy Technology Data Exchange (ETDEWEB)

Ovcharenko, Ivan; Boffelli, Dario; Loots, Gabriela G.

2004-01-15

Primate sequence comparisons are difficult to interpret due to the high degree of sequence similarity shared between such closely related species. Recently, a novel method, phylogenetic shadowing, has been pioneered for predicting functional elements in the human genome through the analysis of multiple primate sequence alignments. We have expanded this theoretical approach to create a computational tool, eShadow, for the identification of elements under selective pressure in multiple sequence alignments of closely related genomes, such as in comparisons of human to primate or mouse to rat DNA. This tool integrates two different statistical methods and allows for the dynamic visualization of the resulting conservation profile. eShadow also includes a versatile optimization module capable of training the underlying Hidden Markov Model to differentially predict functional sequences. This module grants the tool high flexibility in the analysis of multiple sequence alignments and in comparing sequences with different divergence rates. Here, we describe the eShadow comparative tool and its potential uses for analyzing both multiple nucleotide and protein alignments to predict putative functional elements. The eShadow tool is publicly available at http://eshadow.dcode.org/

Effects of momentum-dependent symmetry potential on heavy-ion collisions induced by neutron-rich nuclei

International Nuclear Information System (INIS)

Li Baoan; Das, Champak B.; Das Gupta, Subal; Gale, Charles

2004-01-01

Using an isospin- and momentum-dependent transport model we study effects of the momentum-dependent symmetry potential on heavy-ion collisions induced by neutron-rich nuclei. It is found that symmetry potentials with and without the momentum-dependence but corresponding to the same density-dependent symmetry energy E sym (ρ) lead to significantly different predictions on several E sym (ρ)-sensitive experimental observables especially for energetic nucleons. The momentum- and density-dependence of the symmetry potential have to be determined simultaneously in order to extract the E sym (ρ) accurately. The isospin asymmetry of midrapidity nucleons at high transverse momenta is particularly sensitive to the momentum-dependence of the symmetry potential. It is thus very useful for investigating accurately the equation of state of dense neutron-rich matter

Predicting steam generator crevice chemistry

International Nuclear Information System (INIS)

Burton, G.; Strati, G.

2006-01-01

'Full text:' Corrosion of steam cycle components produces insoluble material, mostly iron oxides, that are transported to the steam generator (SG) via the feedwater and deposited on internal surfaces such as the tubes, tube support plates and the tubesheet. The build up of these corrosion products over time can lead to regions of restricted flow with water chemistry that may be significantly different, and potentially more corrosive to SG tube material, than the bulk steam generator water chemistry. The aim of the present work is to predict SG crevice chemistry using experimentation and modelling as part of AECL's overall strategy for steam generator life management. Hideout-return experiments are performed under CANDU steam generator conditions to assess the accumulation of impurities in hideout, and return from, model crevices. The results are used to validate the ChemSolv model that predicts steam generator crevice impurity concentrations, and high temperature pH, based on process parameters (e.g., heat flux, primary side temperature) and blowdown water chemistry. The model has been incorporated into ChemAND, AECL's system health monitoring software for chemistry monitoring, analysis and diagnostics that has been installed at two domestic and one international CANDU station. ChemAND provides the station chemists with the only method to predict SG crevice chemistry. In one recent application, the software has been used to evaluate the crevice chemistry based on the elevated, but balanced, SG bulk water impurity concentrations present during reactor startup, in order to reduce hold times. The present paper will describe recent hideout-return experiments that are used for the validation of the ChemSolv model, station experience using the software, and improvements to predict the crevice electrochemical potential that will permit station staff to ensure that the SG tubes are in the 'safe operating zone' predicted by Lu (AECL). (author)

Immunoexpression of interleukin-6 in drug-induced gingival overgrowth patients

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P R Ganesh

2016-01-01

Full Text Available Background: To analyze the role of proinflammatory cytokines in drug-induced gingival enlargement in Indian population. Aim: To evaluate for the presence of interleukin-6 (IL-6 in drug-induced gingival enlargement and to compare it with healthy control in the absence of enlargement. Materials and Methods: Thirty-five patients selected for the study and divided into control group (10 and study group (25 consisting of phenytoin (10; cyclosporin (10 and nifedipine (5 induced gingival enlargement. Gingival overgrowth index of Seymour was used to assess overgrowth and allot groups. Under LA, incisional biopsy done, tissue sample fixed in 10% formalin and immunohistochemically evaluated for the presence of IL-6 using LAB-SA method, Labeled- Streptavidin-Biotin Method (LAB-SA kit from Zymed- 2nd generation LAB-SA detection system, Zymed Laboratories, CA. The results of immunohistochemistry were statistically analyzed using Kruskaal–Wallis and Mann–Whitney test. Results: The data obtained from immunohistochemistry assessment shows that drug-induced gingival overgrowth (DIGO samples express more IL-6 than control group and cyclosporin expresses more IL-6 followed by phenytoin and nifedipine. Conclusion: Increased IL-6 expression was noticed in all three DIGO groups in comparison with control group. Among the study group, cyclosporin expressed maximum IL-6 expression followed by phenytoin and nifedipine.

Predicting Multiple Functions of Sustainable Flood Retention Basins under Uncertainty via Multi-Instance Multi-Label Learning

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Qinli Yang

2015-03-01

Full Text Available The ambiguity of diverse functions of sustainable flood retention basins (SFRBs may lead to conflict and risk in water resources planning and management. How can someone provide an intuitive yet efficient strategy to uncover and distinguish the multiple potential functions of SFRBs under uncertainty? In this study, by exploiting both input and output uncertainties of SFRBs, the authors developed a new data-driven framework to automatically predict the multiple functions of SFRBs by using multi-instance multi-label (MIML learning. A total of 372 sustainable flood retention basins, characterized by 40 variables associated with confidence levels, were surveyed in Scotland, UK. A Gaussian model with Monte Carlo sampling was used to capture the variability of variables (i.e., input uncertainty, and the MIML-support vector machine (SVM algorithm was subsequently applied to predict the potential functions of SFRBs that have not yet been assessed, allowing for one basin belonging to different types (i.e., output uncertainty. Experiments demonstrated that the proposed approach enables effective automatic prediction of the potential functions of SFRBs (e.g., accuracy >93%. The findings suggest that the functional uncertainty of SFRBs under investigation can be better assessed in a more comprehensive and cost-effective way, and the proposed data-driven approach provides a promising method of doing so for water resources management.

The accuracy of new wheelchair users' predictions about their future wheelchair use.

Science.gov (United States)

Hoenig, Helen; Griffiths, Patricia; Ganesh, Shanti; Caves, Kevin; Harris, Frances

2012-06-01

This study examined the accuracy of new wheelchair user predictions about their future wheelchair use. This was a prospective cohort study of 84 community-dwelling veterans provided a new manual wheelchair. The association between predicted and actual wheelchair use was strong at 3 mos (ϕ coefficient = 0.56), with 90% of those who anticipated using the wheelchair at 3 mos still using it (i.e., positive predictive value = 0.96) and 60% of those who anticipated not using it indeed no longer using the wheelchair (i.e., negative predictive value = 0.60, overall accuracy = 0.92). Predictive accuracy diminished over time, with overall accuracy declining from 0.92 at 3 mos to 0.66 at 6 mos. At all time points, and for all types of use, patients better predicted use as opposed to disuse, with correspondingly higher positive than negative predictive values. Accuracy of prediction of use in specific indoor and outdoor locations varied according to location. This study demonstrates the importance of better understanding the potential mismatch between the anticipated and actual patterns of wheelchair use. The findings suggest that users can be relied upon to accurately predict their basic wheelchair-related needs in the short-term. Further exploration is needed to identify characteristics that will aid users and their providers in more accurately predicting mobility needs for the long-term.

Predictive Potential of Twenty-Two Biochemical Biomarkers for Coronary Artery Disease in Type 2 Diabetes Mellitus

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Edimar Cristiano Pereira

2015-01-01

Full Text Available We investigated the potential of a panel of 22 biomarkers to predict the presence of coronary artery disease (CAD in type 2 diabetes mellitus (DM2 patients. The study enrolled 96 DM2 patients with (n = 75 and without (n = 21 evidence of CAD. We assessed a biochemical profile that included 22 biomarkers: total cholesterol, LDL, HDL, LDL/HDL, triglycerides, glucose, glycated hemoglobin, fructosamine, homocysteine, cysteine, methionine, reduced glutathione, oxidized glutathione, reduced glutathione/oxidized glutathione, L-arginine, asymmetric dimethyl-L-arginine, symmetric dimethyl-L-arginine, asymmetric dimethyl-L-arginine/L-arginine, nitrate plus nitrite, S-nitrosothiols, nitrotyrosine, and n-acetyl-β-glucosaminidase. Prediction models were built using logistic regression models. We found that eight biomarkers (methionine, nitratate plus nitrite, n-acetyl-β-glucosaminidase, BMI, LDL, HDL, reduced glutathione, and L-arginine/asymmetric dimethyl-L-arginine along with gender and BMI were significantly associated with the odds of CAD in DM2. These preliminary findings support the notion that emerging biochemical markers might be used for CAD prediction in patients with DM2. Our findings warrant further investigation with large, well-designed studies.

The Role of Nicotine Dependence in E-Cigarettes' Potential for Smoking Reduction.

Science.gov (United States)

Selya, Arielle S; Dierker, Lisa; Rose, Jennifer S; Hedeker, Donald; Mermelstein, Robin J

2017-07-07

E-cigarettes (Electronic Nicotine Delivery Systems, or ENDS) are an increasingly popular tobacco product among youth. Some evidence suggests that e-cigarettes may be effective for harm reduction and smoking cessation, although these claims remain controversial. Little is known about how nicotine dependence may contribute to e-cigarettes' effectiveness in reducing or quitting conventional smoking. A cohort of young adults were surveyed over 4 years (approximately ages 19-23). Varying-coefficient models (VCMs) were used to examine the relationship between e-cigarette use and conventional smoking frequency, and how this relationship varies across users with different nicotine dependence levels. Lifetime, but not recent, e-cigarette use was associated with less frequent concurrent smoking of conventional cigarettes among those with high levels of nicotine dependence. However, nondependent e-cigarette users smoked conventional cigarettes slightly more frequently than those who had never used e-cigarettes. Nearly half of ever e-cigarette users reported using them to quit smoking at the last measurement wave. For those who used e-cigarettes in a cessation attempt, the frequency of e-cigarette use was not associated with reductions in future conventional smoking frequency. These findings offer possible support that e-cigarettes may act as a smoking reduction method among highly nicotine-dependent young adult cigarette smokers. However, the opposite was found in non-dependent smokers, suggesting that e-cigarette use should be discouraged among novice tobacco users. Additionally, although a substantial proportion of young adults used e-cigarettes to help them quit smoking, these self-initiated quit attempts with e-cigarettes were not associated with future smoking reduction or cessation. This study offers potential support for e-cigarettes as a smoking reduction tool among highly nicotine-dependent young adult conventional smokers, although the extent and nature of this

Propensity scores-potential outcomes framework to incorporate severity probabilities in the highway safety manual crash prediction algorithm.

Science.gov (United States)

Sasidharan, Lekshmi; Donnell, Eric T

2014-10-01

Accurate estimation of the expected number of crashes at different severity levels for entities with and without countermeasures plays a vital role in selecting countermeasures in the framework of the safety management process. The current practice is to use the American Association of State Highway and Transportation Officials' Highway Safety Manual crash prediction algorithms, which combine safety performance functions and crash modification factors, to estimate the effects of safety countermeasures on different highway and street facility types. Many of these crash prediction algorithms are based solely on crash frequency, or assume that severity outcomes are unchanged when planning for, or implementing, safety countermeasures. Failing to account for the uncertainty associated with crash severity outcomes, and assuming crash severity distributions remain unchanged in safety performance evaluations, limits the utility of the Highway Safety Manual crash prediction algorithms in assessing the effect of safety countermeasures on crash severity. This study demonstrates the application of a propensity scores-potential outcomes framework to estimate the probability distribution for the occurrence of different crash severity levels by accounting for the uncertainties associated with them. The probability of fatal and severe injury crash occurrence at lighted and unlighted intersections is estimated in this paper using data from Minnesota. The results show that the expected probability of occurrence of fatal and severe injury crashes at a lighted intersection was 1 in 35 crashes and the estimated risk ratio indicates that the respective probabilities at an unlighted intersection was 1.14 times higher compared to lighted intersections. The results from the potential outcomes-propensity scores framework are compared to results obtained from traditional binary logit models, without application of propensity scores matching. Traditional binary logit analysis suggests that

Predicting therapy success for treatment as usual and blended treatment in the domain of depression.

Science.gov (United States)

van Breda, Ward; Bremer, Vincent; Becker, Dennis; Hoogendoorn, Mark; Funk, Burkhardt; Ruwaard, Jeroen; Riper, Heleen

2018-06-01

In this paper, we explore the potential of predicting therapy success for patients in mental health care. Such predictions can eventually improve the process of matching effective therapy types to individuals. In the EU project E-COMPARED, a variety of information is gathered about patients suffering from depression. We use this data, where 276 patients received treatment as usual and 227 received blended treatment, to investigate to what extent we are able to predict therapy success. We utilize different encoding strategies for preprocessing, varying feature selection techniques, and different statistical procedures for this purpose. Significant predictive power is found with average AUC values up to 0.7628 for treatment as usual and 0.7765 for blended treatment. Adding daily assessment data for blended treatment does currently not add predictive accuracy. Cost effectiveness analysis is needed to determine the added potential for real-world applications.

Using the Personality Assessment Inventory Antisocial and Borderline Features Scales to Predict Behavior Change.

Science.gov (United States)

Penson, Brittany N; Ruchensky, Jared R; Morey, Leslie C; Edens, John F

2016-11-01

A substantial amount of research has examined the developmental trajectory of antisocial behavior and, in particular, the relationship between antisocial behavior and maladaptive personality traits. However, research typically has not controlled for previous behavior (e.g., past violence) when examining the utility of personality measures, such as self-report scales of antisocial and borderline traits, in predicting future behavior (e.g., subsequent violence). Examination of the potential interactive effects of measures of both antisocial and borderline traits also is relatively rare in longitudinal research predicting adverse outcomes. The current study utilizes a large sample of youthful offenders ( N = 1,354) from the Pathways to Desistance project to examine the separate effects of the Personality Assessment Inventory Antisocial Features (ANT) and Borderline Features (BOR) scales in predicting future offending behavior as well as trends in other negative outcomes (e.g., substance abuse, violence, employment difficulties) over a 1-year follow-up period. In addition, an ANT × BOR interaction term was created to explore the predictive effects of secondary psychopathy. ANT and BOR both explained unique variance in the prediction of various negative outcomes even after controlling for past indicators of those same behaviors during the preceding year.

Manipulating time and space: Collision prediction in peripersonal and extrapersonal space.

Science.gov (United States)

Iachini, Tina; Ruotolo, Francesco; Vinciguerra, Michela; Ruggiero, Gennaro

2017-09-01

Being able to predict potential collisions is a necessary survival prerequisite for all moving species. Temporal and spatial information is fundamental for this purpose. However, it is not clear yet if the peripersonal (i.e. near) and extrapersonal (i.e. far) distance between our body and the moving objects affects the way in which we can predict possible collisions. In order to assess this, we manipulated independently velocity and path of two balls moving one towards the other in such a way as to collide or not in peripersonal and extrapersonal space. In two experiments, participants had to judge if these balls were to collide or not. The results consistently showed a lower discrimination capacity and a more liberal tendency to predict collisions when the moving balls were in peripersonal space and their velocity was different rather than equal. This did not happen in extrapersonal space. Therefore, peripersonal space was particularly affected by temporal information. The possible link between the motor and anticipatory adaptive function of peripersonal space and collision prediction mechanisms is discussed. Copyright © 2017 Elsevier B.V. All rights reserved.

Applicability of effective fragment potential version 2 - Molecular dynamics (EFP2-MD) simulations for predicting excess properties of mixed solvents

Science.gov (United States)

Kuroki, Nahoko; Mori, Hirotoshi

2018-02-01

Effective fragment potential version 2 - molecular dynamics (EFP2-MD) simulations, where the EFP2 is a polarizable force field based on ab initio electronic structure calculations were applied to water-methanol binary mixture. Comparing EFP2s defined with (aug-)cc-pVXZ (X = D,T) basis sets, it was found that large sets are necessary to generate sufficiently accurate EFP2 for predicting mixture properties. It was shown that EFP2-MD could predict the excess molar volume. Since the computational cost of EFP2-MD are far less than ab initio MD, the results presented herein demonstrate that EFP2-MD is promising for predicting physicochemical properties of novel mixed solvents.

Comparison of four modeling tools for the prediction of potential distribution for non-indigenous weeds in the United States

Science.gov (United States)

Magarey, Roger; Newton, Leslie; Hong, Seung C.; Takeuchi, Yu; Christie, Dave; Jarnevich, Catherine S.; Kohl, Lisa; Damus, Martin; Higgins, Steven I.; Miller, Leah; Castro, Karen; West, Amanda; Hastings, John; Cook, Gericke; Kartesz, John; Koop, Anthony

2018-01-01

This study compares four models for predicting the potential distribution of non-indigenous weed species in the conterminous U.S. The comparison focused on evaluating modeling tools and protocols as currently used for weed risk assessment or for predicting the potential distribution of invasive weeds. We used six weed species (three highly invasive and three less invasive non-indigenous species) that have been established in the U.S. for more than 75 years. The experiment involved providing non-U. S. location data to users familiar with one of the four evaluated techniques, who then developed predictive models that were applied to the United States without knowing the identity of the species or its U.S. distribution. We compared a simple GIS climate matching technique known as Proto3, a simple climate matching tool CLIMEX Match Climates, the correlative model MaxEnt, and a process model known as the Thornley Transport Resistance (TTR) model. Two experienced users ran each modeling tool except TTR, which had one user. Models were trained with global species distribution data excluding any U.S. data, and then were evaluated using the current known U.S. distribution. The influence of weed species identity and modeling tool on prevalence and sensitivity effects was compared using a generalized linear mixed model. Each modeling tool itself had a low statistical significance, while weed species alone accounted for 69.1 and 48.5% of the variance for prevalence and sensitivity, respectively. These results suggest that simple modeling tools might perform as well as complex ones in the case of predicting potential distribution for a weed not yet present in the United States. Considerations of model accuracy should also be balanced with those of reproducibility and ease of use. More important than the choice of modeling tool is the construction of robust protocols and testing both new and experienced users under blind test conditions that approximate operational conditions.

Rare human papillomavirus 16 E6 variants reveal significant oncogenic potential

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Tommasino Massimo

2011-06-01

Full Text Available Abstract The aim of this study was to determine whether low prevalence human papillomavirus (HPV 16 E6 variants differ from high prevalence types in their functional abilities. We evaluated functions relevant to carcinogenesis for the rarely-detected European variants R8Q, R10G and R48W as compared to the commonly detected L83V. Human immortalized keratinocytes (NIKS stably transduced with the E6 variants were used in most functional assays. Low and high prevalence E6 variants displayed similar abilities in abrogation of growth arrest and inhibition of p53 elevation induced by actinomycin D. Differences were detected in the abilities to dysregulate stratification and differentiation of NIKS in organotypic raft cultures, modulate detachment induced apoptosis (anoikis and hyperactivate Wnt signaling. No distinctive phenotype could be assigned to include all rare variants. Like L83V, raft cultures derived from variants R10G and R48W similarly induced hyperplasia and aberrantly expressed keratin 5 in the suprabasal compartment with significantly lower expression of keratin 10. Unlike L83V, both variants, and particularly R48W, induced increased levels of anoikis upon suspension in semisolid medium. R8Q induced a unique phenotype characterized by thin organotypic raft cultures, low expression of keratin 10, and high expression of keratins 5 and 14 throughout all raft layers. Interestingly, in a reporter based assay R8Q exhibited a higher ability to augment TCF/β-catenin transcription. The data suggests that differences in E6 variant prevalence in cervical carcinoma may not be related to the carcinogenic potential of the E6 protein.

Characterization and validation of an in silico toxicology model to predict the mutagenic potential of drug impurities*

Energy Technology Data Exchange (ETDEWEB)

Valerio, Luis G., E-mail: luis.valerio@fda.hhs.gov [Science and Research Staff, Office of Pharmaceutical Science, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD 20993–0002 (United States); Cross, Kevin P. [Leadscope, Inc., 1393 Dublin Road, Columbus, OH, 43215–1084 (United States)

2012-05-01

Control and minimization of human exposure to potential genotoxic impurities found in drug substances and products is an important part of preclinical safety assessments of new drug products. The FDA's 2008 draft guidance on genotoxic and carcinogenic impurities in drug substances and products allows use of computational quantitative structure–activity relationships (QSAR) to identify structural alerts for known and expected impurities present at levels below qualified thresholds. This study provides the information necessary to establish the practical use of a new in silico toxicology model for predicting Salmonella t. mutagenicity (Ames assay outcome) of drug impurities and other chemicals. We describe the model's chemical content and toxicity fingerprint in terms of compound space, molecular and structural toxicophores, and have rigorously tested its predictive power using both cross-validation and external validation experiments, as well as case studies. Consistent with desired regulatory use, the model performs with high sensitivity (81%) and high negative predictivity (81%) based on external validation with 2368 compounds foreign to the model and having known mutagenicity. A database of drug impurities was created from proprietary FDA submissions and the public literature which found significant overlap between the structural features of drug impurities and training set chemicals in the QSAR model. Overall, the model's predictive performance was found to be acceptable for screening drug impurities for Salmonella mutagenicity. -- Highlights: ► We characterize a new in silico model to predict mutagenicity of drug impurities. ► The model predicts Salmonella mutagenicity and will be useful for safety assessment. ► We examine toxicity fingerprints and toxicophores of this Ames assay model. ► We compare these attributes to those found in drug impurities known to FDA/CDER. ► We validate the model and find it has a desired predictive

Characterization and validation of an in silico toxicology model to predict the mutagenic potential of drug impurities*

International Nuclear Information System (INIS)

Valerio, Luis G.; Cross, Kevin P.

2012-01-01

Control and minimization of human exposure to potential genotoxic impurities found in drug substances and products is an important part of preclinical safety assessments of new drug products. The FDA's 2008 draft guidance on genotoxic and carcinogenic impurities in drug substances and products allows use of computational quantitative structure–activity relationships (QSAR) to identify structural alerts for known and expected impurities present at levels below qualified thresholds. This study provides the information necessary to establish the practical use of a new in silico toxicology model for predicting Salmonella t. mutagenicity (Ames assay outcome) of drug impurities and other chemicals. We describe the model's chemical content and toxicity fingerprint in terms of compound space, molecular and structural toxicophores, and have rigorously tested its predictive power using both cross-validation and external validation experiments, as well as case studies. Consistent with desired regulatory use, the model performs with high sensitivity (81%) and high negative predictivity (81%) based on external validation with 2368 compounds foreign to the model and having known mutagenicity. A database of drug impurities was created from proprietary FDA submissions and the public literature which found significant overlap between the structural features of drug impurities and training set chemicals in the QSAR model. Overall, the model's predictive performance was found to be acceptable for screening drug impurities for Salmonella mutagenicity. -- Highlights: ► We characterize a new in silico model to predict mutagenicity of drug impurities. ► The model predicts Salmonella mutagenicity and will be useful for safety assessment. ► We examine toxicity fingerprints and toxicophores of this Ames assay model. ► We compare these attributes to those found in drug impurities known to FDA/CDER. ► We validate the model and find it has a desired predictive performance.

Predicting Seawater Intrusion in Coastal Groundwater Boreholes Using Self-Potential Data

Science.gov (United States)

Graham, M.; MacAllister, D. J.; Jackson, M.; Vinogradov, J.; Butler, A. P.

2017-12-01

Many coastal groundwater abstraction wells are under threat from seawater intrusion: this is exacerbated in summer by low water tables and increased abstraction. Existing hydrochemistry or geophysical techniques often fail to predict the timing of intrusion events. We investigate whether the presence and transport of seawater can influence self-potentials (SPs) measured within groundwater boreholes, with the aim of using SP monitoring to provide early warning of saline intrusion. SP data collection: SP data were collected from a coastal groundwater borehole and an inland borehole (> 60 km from the coast) in the Seaford Chalk of southern England. The SP gradient in the inland borehole was approximately 0.05 mV/m, while that in the coastal borehole varied from 0.16-0.26 mV/m throughout the monitoring period. Spectral analysis showed that semi-diurnal fluctuations in the SP gradient were several orders of magnitude higher at the coast than inland, indicating a strong influence from oceanic tides. A characteristic decrease in the gradient, or precursor, was observed in the coastal borehole several days prior to seawater intrusion. Modelling results: Hydrodynamic transport and geoelectric modelling suggest that observed pressure changes (associated with the streaming potential) are insufficient to explain either the magnitude of the coastal SP gradient or the semi-diurnal SP fluctuations. By contrast, a model of the exclusion-diffusion potential closely matches these observations and produces a precursor similar to that observed in the field. Sensitivity analysis suggests that both a sharp saline front and spatial variations in the exclusion efficiency arising from aquifer heterogeneities are necessary to explain the SP gradient observed in the coastal borehole. The presence of the precursor in the model depends also on the presence and depth of fractures near the base of the borehole. Conclusions: Our results indicate that SP monitoring, combined with hydrodynamic

Influence of surface conductivity on the apparent zeta potential of calcite.

Science.gov (United States)

Li, Shuai; Leroy, Philippe; Heberling, Frank; Devau, Nicolas; Jougnot, Damien; Chiaberge, Christophe

2016-04-15

Zeta potential is a physicochemical parameter of particular importance in describing the surface electrical properties of charged porous media. However, the zeta potential of calcite is still poorly known because of the difficulty to interpret streaming potential experiments. The Helmholtz-Smoluchowski (HS) equation is widely used to estimate the apparent zeta potential from these experiments. However, this equation neglects the influence of surface conductivity on streaming potential. We present streaming potential and electrical conductivity measurements on a calcite powder in contact with an aqueous NaCl electrolyte. Our streaming potential model corrects the apparent zeta potential of calcite by accounting for the influence of surface conductivity and flow regime. We show that the HS equation seriously underestimates the zeta potential of calcite, particularly when the electrolyte is diluted (ionic strength ⩽ 0.01 M) because of calcite surface conductivity. The basic Stern model successfully predicted the corrected zeta potential by assuming that the zeta potential is located at the outer Helmholtz plane, i.e. without considering a stagnant diffuse layer at the calcite-water interface. The surface conductivity of calcite crystals was inferred from electrical conductivity measurements and computed using our basic Stern model. Surface conductivity was also successfully predicted by our surface complexation model. Copyright © 2016 Elsevier Inc. All rights reserved.

Characterization, cloning and sequencing of a thermostable endo-(1, 3-1, 4) beta-glucanase-encoding gene from an alkalophilic Bacillus-brevis

CSIR Research Space (South Africa)

Louw, M

1993-01-01

Full Text Available - zyme that produced 1 ~tmol reducing sugar calculated as glucose per minute under the conditions of assay. Bacterial strains, growth media and vectors. The Escherichia coli host strain for the original cloning experiment... the gels were washed in phosphate buffer, pH 6.3 (Beguin 1983). The bands of enzyme activity were detected by staining the lichen- an/PAGE gel with Congo red. Restriction mapping and nucleotide sequencing. Restriction en...

Mutagenic Potential ofBos taurus Papillomavirus Type 1 E6 Recombinant Protein: First Description

Directory of Open Access Journals (Sweden)

Rodrigo Pinheiro Araldi

2015-01-01

Full Text Available Bovine papillomavirus (BPV is considered a useful model to study HPV oncogenic process. BPV interacts with the host chromatin, resulting in DNA damage, which is attributed to E5, E6, and E7 viral oncoproteins activity. However, the oncogenic mechanisms of BPV E6 oncoprotein per se remain unknown. This study aimed to evaluate the mutagenic potential of Bos taurus papillomavirus type 1 (BPV-1 E6 recombinant oncoprotein by the cytokinesis-block micronucleus assay (CBMNA and comet assay (CA. Peripheral blood samples of five calves were collected. Samples were subjected to molecular diagnosis, which did not reveal presence of BPV sequences. Samples were treated with 1 μg/mL of BPV-1 E6 oncoprotein and 50 μg/mL of cyclophosphamide (positive control. Negative controls were not submitted to any treatment. The samples were submitted to the CBMNA and CA. The results showed that BPV E6 oncoprotein induces clastogenesis per se, which is indicative of genomic instability. These results allowed better understanding the mechanism of cancer promotion associated with the BPV E6 oncoprotein and revealed that this oncoprotein can induce carcinogenesis per se. E6 recombinant oncoprotein has been suggested as a possible vaccine candidate. Results pointed out that BPV E6 recombinant oncoprotein modifications are required to use it as vaccine.

Genome-wide transcriptional profiling of Botrytis cinerea genes targeting plant cell walls during infections of different hosts

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Barbara eBlanco-Ulate

2014-09-01

Full Text Available Cell walls are barriers that impair colonization of host tissues, but also are important reservoirs of energy-rich sugars. Growing hyphae of necrotrophic fungal pathogens, such as Botrytis cinerea (Botrytis, henceforth, secrete enzymes that disassemble cell wall polysaccharides. In this work we describe the annotation of 275 putative secreted Carbohydrate-Active enZymes (CAZymes identified in the Botrytis B05.10 genome. Using RNAseq we determined which Botrytis CAZymes were expressed during infections of lettuce leaves, ripe tomato fruit, and grape berries. On the three hosts, Botrytis expressed a common group of 229 potentially secreted CAZymes, including 28 pectin backbone-modifying enzymes, 21 hemicellulose-modifying proteins, 18 enzymes that might target pectin and hemicellulose side-branches, and 16 enzymes predicted to degrade cellulose. The diversity of the Botrytis CAZymes may be partly responsible for its wide host range. Thirty-six candidate CAZymes with secretion signals were found exclusively when Botrytis interacted with ripe tomato fruit and grape berries. Pectin polysaccharides are notably abundant in grape and tomato cell walls, but lettuce leaf walls have less pectin and are richer in hemicelluloses and cellulose. The results of this study not only suggest that Botrytis targets similar wall polysaccharide networks on fruit and leaves, but also that it may selectively attack host wall polysaccharide substrates depending on the host tissue.

Computational prediction of protein-protein interactions in Leishmania predicted proteomes.

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Antonio M Rezende

Full Text Available The Trypanosomatids parasites Leishmania braziliensis, Leishmania major and Leishmania infantum are important human pathogens. Despite of years of study and genome availability, effective vaccine has not been developed yet, and the chemotherapy is highly toxic. Therefore, it is clear just interdisciplinary integrated studies will have success in trying to search new targets for developing of vaccines and drugs. An essential part of this rationale is related to protein-protein interaction network (PPI study which can provide a better understanding of complex protein interactions in biological system. Thus, we modeled PPIs for Trypanosomatids through computational methods using sequence comparison against public database of protein or domain interaction for interaction prediction (Interolog Mapping and developed a dedicated combined system score to address the predictions robustness. The confidence evaluation of network prediction approach was addressed using gold standard positive and negative datasets and the AUC value obtained was 0.94. As result, 39,420, 43,531 and 45,235 interactions were predicted for L. braziliensis, L. major and L. infantum respectively. For each predicted network the top 20 proteins were ranked by MCC topological index. In addition, information related with immunological potential, degree of protein sequence conservation among orthologs and degree of identity compared to proteins of potential parasite hosts was integrated. This information integration provides a better understanding and usefulness of the predicted networks that can be valuable to select new potential biological targets for drug and vaccine development. Network modularity which is a key when one is interested in destabilizing the PPIs for drug or vaccine purposes along with multiple alignments of the predicted PPIs were performed revealing patterns associated with protein turnover. In addition, around 50% of hypothetical protein present in the networks

Identification of thioaptamer ligand against E-selectin: potential application for inflamed vasculature targeting.

Directory of Open Access Journals (Sweden)

Aman P Mann

Full Text Available Active targeting of a drug carrier to a specific target site is crucial to provide a safe and efficient delivery of therapeutics and imaging contrast agents. E-selectin expression is induced on the endothelial cell surface of vessels in response to inflammatory stimuli but is absent in the normal vessels. Thus, E-selectin is an attractive molecular target, and high affinity ligands for E-selectin could be powerful tools for the delivery of therapeutics and/or imaging agents to inflamed vessels. In this study, we identified a thiophosphate modified aptamer (thioaptamer, TA against E-selectin (ESTA-1 by employing a two-step selection strategy: a recombinant protein-based TA binding selection from a combinatorial library followed by a cell-based TA binding selection using E-selectin expressing human microvascular endothelial cells. ESTA-1 selectively bound to E-selectin with nanomolar binding affinity (K(D = 47 nM while exhibiting minimal cross reactivity to P- and L-selectin. Furthermore, ESTA-1 binding to E-selectin on the endothelial cells markedly antagonized the adhesion (over 75% inhibition of sLe(x positive HL-60 cells at nanomolar concentration. ESTA-1 also bound specifically to the inflamed tumor-associated vasculature of human carcinomas derived from breast, ovarian, and skin but not to normal organs, and this binding was highly associated with the E-selectin expression level. Similarly, intravenously injected ESTA-1 demonstrated distinct binding to the tumor vasculature in a breast cancer xenograft model. Together, our data substantiates the discovery of a thioaptamer (ESTA-1 that binds to E-selectin with high affinity and specificity, thereby highlighting the potential application of ESTA-1 for E-selectin targeted delivery.

The Current and Future Use of Ridge Regression for Prediction in Quantitative Genetics

Directory of Open Access Journals (Sweden)

Ronald de Vlaming

2015-01-01

Full Text Available In recent years, there has been a considerable amount of research on the use of regularization methods for inference and prediction in quantitative genetics. Such research mostly focuses on selection of markers and shrinkage of their effects. In this review paper, the use of ridge regression for prediction in quantitative genetics using single-nucleotide polymorphism data is discussed. In particular, we consider (i the theoretical foundations of ridge regression, (ii its link to commonly used methods in animal breeding, (iii the computational feasibility, and (iv the scope for constructing prediction models with nonlinear effects (e.g., dominance and epistasis. Based on a simulation study we gauge the current and future potential of ridge regression for prediction of human traits using genome-wide SNP data. We conclude that, for outcomes with a relatively simple genetic architecture, given current sample sizes in most cohorts (i.e., N<10,000 the predictive accuracy of ridge regression is slightly higher than the classical genome-wide association study approach of repeated simple regression (i.e., one regression per SNP. However, both capture only a small proportion of the heritability. Nevertheless, we find evidence that for large-scale initiatives, such as biobanks, sample sizes can be achieved where ridge regression compared to the classical approach improves predictive accuracy substantially.

Prediction of the contact sensitizing potential of chemicals using analysis of gene expression changes in human THP-1 monocytes.

Science.gov (United States)

Arkusz, Joanna; Stępnik, Maciej; Sobala, Wojciech; Dastych, Jarosław

2010-11-10

The aim of this study was to find differentially regulated genes in THP-1 monocytic cells exposed to sensitizers and nonsensitizers and to investigate if such genes could be reliable markers for an in vitro predictive method for the identification of skin sensitizing chemicals. Changes in expression of 35 genes in the THP-1 cell line following treatment with chemicals of different sensitizing potential (from nonsensitizers to extreme sensitizers) were assessed using real-time PCR. Verification of 13 candidate genes by testing a large number of chemicals (an additional 22 sensitizers and 8 nonsensitizers) revealed that prediction of contact sensitization potential was possible based on evaluation of changes in three genes: IL8, HMOX1 and PAIMP1. In total, changes in expression of these genes allowed correct detection of sensitization potential of 21 out of 27 (78%) test sensitizers. The gene expression levels inside potency groups varied and did not allow estimation of sensitization potency of test chemicals. Results of this study indicate that evaluation of changes in expression of proposed biomarkers in THP-1 cells could be a valuable model for preliminary screening of chemicals to discriminate an appreciable majority of sensitizers from nonsensitizers. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

e-Science on Earthquake Disaster Mitigation by EUAsiaGrid

Science.gov (United States)

Yen, Eric; Lin, Simon; Chen, Hsin-Yen; Chao, Li; Huang, Bor-Shoh; Liang, Wen-Tzong

2010-05-01

Although earthquake is not predictable at this moment, with the aid of accurate seismic wave propagation analysis, we could simulate the potential hazards at all distances from possible fault sources by understanding the source rupture process during large earthquakes. With the integration of strong ground-motion sensor network, earthquake data center and seismic wave propagation analysis over gLite e-Science Infrastructure, we could explore much better knowledge on the impact and vulnerability of potential earthquake hazards. On the other hand, this application also demonstrated the e-Science way to investigate unknown earth structure. Regional integration of earthquake sensor networks could aid in fast event reporting and accurate event data collection. Federation of earthquake data center entails consolidation and sharing of seismology and geology knowledge. Capability building of seismic wave propagation analysis implies the predictability of potential hazard impacts. With gLite infrastructure and EUAsiaGrid collaboration framework, earth scientists from Taiwan, Vietnam, Philippine, Thailand are working together to alleviate potential seismic threats by making use of Grid technologies and also to support seismology researches by e-Science. A cross continental e-infrastructure, based on EGEE and EUAsiaGrid, is established for seismic wave forward simulation and risk estimation. Both the computing challenge on seismic wave analysis among 5 European and Asian partners, and the data challenge for data center federation had been exercised and verified. Seismogram-on-Demand service is also developed for the automatic generation of seismogram on any sensor point to a specific epicenter. To ease the access to all the services based on users workflow and retain the maximal flexibility, a Seismology Science Gateway integating data, computation, workflow, services and user communities would be implemented based on typical use cases. In the future, extension of the

Link prediction in multiplex online social networks

Science.gov (United States)

Jalili, Mahdi; Orouskhani, Yasin; Asgari, Milad; Alipourfard, Nazanin; Perc, Matjaž

2017-02-01

Online social networks play a major role in modern societies, and they have shaped the way social relationships evolve. Link prediction in social networks has many potential applications such as recommending new items to users, friendship suggestion and discovering spurious connections. Many real social networks evolve the connections in multiple layers (e.g. multiple social networking platforms). In this article, we study the link prediction problem in multiplex networks. As an example, we consider a multiplex network of Twitter (as a microblogging service) and Foursquare (as a location-based social network). We consider social networks of the same users in these two platforms and develop a meta-path-based algorithm for predicting the links. The connectivity information of the two layers is used to predict the links in Foursquare network. Three classical classifiers (naive Bayes, support vector machines (SVM) and K-nearest neighbour) are used for the classification task. Although the networks are not highly correlated in the layers, our experiments show that including the cross-layer information significantly improves the prediction performance. The SVM classifier results in the best performance with an average accuracy of 89%.

Development of a predictive methodology for identifying high radon exhalation potential areas

International Nuclear Information System (INIS)

Ielsch, G.

2001-01-01

Radon 222 is a radioactive natural gas originating from the decay of radium 226 which itself originates from the decay of uranium 23 8 naturally present in rocks and soil. Inhalation of radon gas and its decay products is a potential health risk for man. Radon can accumulate in confined environments such as buildings, and is responsible for one third of the total radiological exposure of the general public to radiation. The problem of how to manage this risk then arises. The main difficulty encountered is due to the large variability of exposure to radon across the country. A prediction needs to be made of areas with the highest density of buildings with high radon levels. Exposure to radon varies depending on the degree of confinement of the habitat, the lifestyle of the occupants and particularly emission of radon from the surface of the soil on which the building is built. The purpose of this thesis is to elaborate a methodology for determining areas presenting a high potential for radon exhalation at the surface of the soil. The methodology adopted is based on quantification of radon exhalation at the surface, starting from a precise characterization of the main local geological and pedological parameters that control the radon source and its transport to the ground/atmosphere interface. The methodology proposed is innovative in that it combines a cartographic analysis, parameters integrated into a Geographic Information system, and a simplified model for vertical transport of radon by diffusion through pores in the soil. This methodology has been validated on two typical areas, in different geological contexts, and gives forecasts that generally agree with field observations. This makes it possible to identify areas with a high exhalation potential within a range of a few square kilometers. (author)

QCD predictions for four-jet final states in e/sup +/e/sup -/ annihilation

Energy Technology Data Exchange (ETDEWEB)

Ali, A; Koerner, J G; Kunszt, Z; Pietarinen, E [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany, F.R.); Kramer, G; Schierholz, G; Willrodt, J [Hamburg Univ. (Germany, F.R.). 2. Inst. fuer Theoretische Physik

1980-05-01

We have calculated the four-jet production processes e/sup +/e/sup -/ ..-->.. q anti q gg and e/sup -/e/sup -/ ..-->.. q anti q q anti q to lowest order QCD perturbation theory. We find that (q anti q q anti q) production is small compared to the dominant process e/sup +/e/sup -/ ..-->.. q anti q gg which can in part be traced to the fact that the latter process is more singular as the 2- and 3-jet phase-space limits are approached. We present differential 4-jet acoplanarity distributions and compare them with non-perturbative acoplanarity distributions at maximum PETRA and PEP energies. Leading log cross-section formulae are derived for various cut-off procedures and are compared to the results of our numerical integrations. We also present results on associated heavy quark production in e/sup +/e/sup -/ annihilation.

A large complement of the predicted Arabidopsis ARM repeat proteins are members of the U-box E3 ubiquitin ligase family.

Science.gov (United States)

Mudgil, Yashwanti; Shiu, Shin-Han; Stone, Sophia L; Salt, Jennifer N; Goring, Daphne R

2004-01-01

The Arabidopsis genome was searched to identify predicted proteins containing armadillo (ARM) repeats, a motif known to mediate protein-protein interactions in a number of different animal proteins. Using domain database predictions and models generated in this study, 108 Arabidopsis proteins were identified that contained a minimum of two ARM repeats with the majority of proteins containing four to eight ARM repeats. Clustering analysis showed that the 108 predicted Arabidopsis ARM repeat proteins could be divided into multiple groups with wide differences in their domain compositions and organizations. Interestingly, 41 of the 108 Arabidopsis ARM repeat proteins contained a U-box, a motif present in a family of E3 ligases, and these proteins represented the largest class of Arabidopsis ARM repeat proteins. In 14 of these U-box/ARM repeat proteins, there was also a novel conserved domain identified in the N-terminal region. Based on the phylogenetic tree, representative U-box/ARM repeat proteins were selected for further study. RNA-blot analyses revealed that these U-box/ARM proteins are expressed in a variety of tissues in Arabidopsis. In addition, the selected U-box/ARM proteins were found to be functional E3 ubiquitin ligases. Thus, these U-box/ARM proteins represent a new family of E3 ligases in Arabidopsis.

Differential RISC association of endogenous human microRNAs predicts their inhibitory potential.

Science.gov (United States)

Flores, Omar; Kennedy, Edward M; Skalsky, Rebecca L; Cullen, Bryan R

2014-04-01

It has previously been assumed that the generally high stability of microRNAs (miRNAs) reflects their tight association with Argonaute (Ago) proteins, essential components of the RNA-induced silencing complex (RISC). However, recent data have suggested that the majority of mature miRNAs are not, in fact, Ago associated. Here, we demonstrate that endogenous human miRNAs vary widely, by >100-fold, in their level of RISC association and show that the level of Ago binding is a better indicator of inhibitory potential than is the total level of miRNA expression. While miRNAs of closely similar sequence showed comparable levels of RISC association in the same cell line, these varied between different cell types. Moreover, the level of RISC association could be modulated by overexpression of complementary target mRNAs. Together, these data indicate that the level of RISC association of a given endogenous miRNA is regulated by the available RNA targetome and predicts miRNA function.

Application of Volta potential mapping to determine metal surface defects

International Nuclear Information System (INIS)

Nazarov, A.; Thierry, D.

2007-01-01

As a rule, stress or fatigue cracks originate from various surface imperfections, such as pits, inclusions or locations showing a residual stress. It would be very helpful for material selection to be able to predict the likelihood of environment-assisted cracking or pitting corrosion. By using Scanning Kelvin Probe (the vibrating capacitor with a spatial resolution of 80 μm) the profiling of metal electron work function (Volta potential) in air is applied to the metal surfaces showing residual stress, MnS inclusions and wearing. The Volta potential is influenced by the energy of electrons at the Fermi level and drops generally across the metal/oxide/air interfaces. Inclusions (e.g. MnS) impair continuity of the passive film that locally decreases Volta potential. The stress applied gives rise to dislocations, microcracks and vacancies in the metal and the surface oxide. The defects decrease Volta and corrosion potentials; reduce the overvoltage for processes of passivity breakdown and anodic metal dissolution. These 'anodic' defects can be visualized in potential mapping that can help us to predict locations with higher risk of pitting corrosion or cracking

The relationship between maternal and neonatal umbilical cord plasma homocyst(e)ine suggests a potential role for maternal homocyst(e)ine in fetal metabolism.

Science.gov (United States)

Malinow, M R; Rajkovic, A; Duell, P B; Hess, D L; Upson, B M

1998-02-01

Data on fetal blood homocyst(e)ine concentrations are not available. We tested the hypothesis that homocyst(e)ine crosses the maternal/placental/fetal interphases and is sequestered by the fetus. The concentration of homocyst(e)ine was determined at parturition in peripheral venous plasma from 35 nulliparous healthy pregnant women and umbilical arterial and venous plasma from their conceptus. Findings demonstrated a descending concentration gradient of plasma homocyst(e)ine from maternal vein to umbilical vein and to umbilical artery; the decrease at each interphase approximated 1 micromol/L. The neonate weight and gestational age were inversely related to maternal homocyst(e)ine concentrations. The umbilical vein to umbilical artery homocyst(e)ine decrement suggests that uptake of homocyst(e)ine occurs in the fetus. The likely incorporation of homocyst(e)ine into the fetal metabolic cycle may implicate maternal homocyst(e)ine as having a potential nutritional role in the fetus. Further studies are required to explain the role of homocyst(e)ine in fetal metabolism and development.

Behavior of the E-E' Bonds (E, E' = S and Se) in Glutathione Disulfide and Derivatives Elucidated by Quantum Chemical Calculations with the Quantum Theory of Atoms-in-Molecules Approach.

Science.gov (United States)

Hayashi, Satoko; Tsubomoto, Yutaka; Nakanishi, Waro

2018-02-17

The nature of the E-E' bonds (E, E' = S and Se) in glutathione disulfide ( 1 ) and derivatives 2 - 3 , respectively, was elucidated by applying quantum theory of atoms-in-molecules (QTAIM) dual functional analysis (QTAIM-DFA), to clarify the basic contribution of E-E' in the biological redox process, such as the glutathione peroxidase process. Five most stable conformers a - e were obtained, after applying the Monte-Carlo method then structural optimizations. In QTAIM-DFA, total electron energy densities H b ( r c ) are plotted versus H b ( r c ) - V b ( r c )/2 at bond critical points (BCPs), where V b ( r c ) are potential energy densities at BCPs. Data from the fully optimized structures correspond to the static nature. Those containing perturbed structures around the fully optimized one in the plot represent the dynamic nature of interactions. The behavior of E-E' was examined carefully. Whereas E-E' in 1a - 3e were all predicted to have the weak covalent nature of the shared shell interactions, two different types of S-S were detected in 1 , depending on the conformational properties. Contributions from the intramolecular non-covalent interactions to stabilize the conformers were evaluated. An inverse relationship was observed between the stability of a conformer and the strength of E-E' in the conformer, of which reason was discussed.

Molecular structure and spectral properties of ethyl 3-quinolinecarboxylate (E3Q) and [Ag(E3Q)2(TCA)] complex (TCA = Trichloroacetate)

Science.gov (United States)

Soliman, Saied M.; Kassem, Taher S.; Badr, Ahmed M. A.; Abou Youssef, Morsy A.; Assem, Rania

2014-09-01

A new [Ag(E3Q)2(TCA)] complex; (E3Q = Ethyl 3-quinolinecarboxylate and TCA = Trichloroacetate) has been synthesized and characterized using elemental analysis, FTIR, NMR and mass spectroscopy. The molecular geometry and spectroscopic properties of the complex as well as the free ligand have been calculated using the hybrid B3LYP method. The calculations predicted a distorted tetrahedral arrangement around Ag(I) ion. The vibrational spectra of the studied compounds have been assigned using potential energy distribution (PED). TD-DFT method was used to predict the electronic absorption spectra. The most intense absorption band showed a bathochromic shift and lowering of intensity in case of the complex (233.7 nm, f = 0.5604) compared to E3Q (λmax = 228.0 nm, f = 0.9072). The calculated 1H NMR chemical shifts using GIAO method showed good correlations with the experimental data. The computed dipole moment, polarizability and HOMO-LUMO energy gap were used to predict the nonlinear optical (NLO) properties. It is found that Ag(I) enhances the NLO activity. The natural bond orbital (NBO) analyses were used to elucidate the intramolecular charge transfer interactions causing stabilization for the investigated systems.

The predictive role of E2-EPF ubiquitin carrier protein in esophageal squamous cell carcinoma.

Science.gov (United States)

Chen, Miao-Fen; Lee, Kuan-Der; Lu, Ming-Shian; Chen, Chih-Cheng; Hsieh, Ming-Ju; Liu, Yun-Hen; Lin, Paul-Yang; Chen, Wen-Cheng

2009-03-01

The ubiquitin proteasome pathway has been implicated in carcinogenesis. However, the role of E2-EPF ubiquitin carrier protein (UCP) in esophageal cancer remains relatively unstudied. In the study, we examined the mRNA level of circulating tumor cells from 60 esophageal cancer patients by membrane arrays consisting of a panel of potential markers including UCP, compared to 40 normal populations. The predictive capacity of UCP was also assessed by immunohistochemical staining of a retrospective series of 84 biopsied esophageal squamous cell carcinomas in relation to clinical outcome. In addition, we studied in vitro biological changes including tumor growth, metastatic capacity, and the sensitivity to irradiation and cisplatin, after experimental manipulation of UCP expression in esophageal cancer cells. By the data of 25-gene membrane array analysis, UCP was the only factor significantly associated with the extent of tumor burden in esophageal cancer patients. Our immunochemistry findings further indicate that UCP positivity was linked to poor response to neoadjuvant therapy and worse survival. In cell culture, inhibited UCP significantly decrease tumor growth and the capacity for metastasis. The epithelial-mesenchymal transition (EMT) induced by VHL/HIF-1alpha-TGF-beta1 pathway might be the underlying mechanism responsible to the more aggressive tumor growth in UCP-positive esophageal cancer. Our results suggest that UCP was significantly associated with poor prognosis of esophageal cancer and may be a new molecular target for therapeutic intervention for esophageal squamous cell carcinoma.

Towards a spectroscopically accurate set of potentials for heavy hydride laser cooling candidates: Effective core potential calculations of BaH

Energy Technology Data Exchange (ETDEWEB)

Moore, Keith; McLaughlin, Brendan M.; Lane, Ian C., E-mail: i.lane@qub.ac.uk [School of Chemistry and Chemical Engineering, Queen’s University Belfast, Stranmillis Road, Belfast BT9 5AG (United Kingdom)

2016-04-14

BaH (and its isotopomers) is an attractive molecular candidate for laser cooling to ultracold temperatures and a potential precursor for the production of ultracold gases of hydrogen and deuterium. The theoretical challenge is to simulate the laser cooling cycle as reliably as possible and this paper addresses the generation of a highly accurate ab initio {sup 2}Σ{sup +} potential for such studies. The performance of various basis sets within the multi-reference configuration-interaction (MRCI) approximation with the Davidson correction is tested and taken to the Complete Basis Set (CBS) limit. It is shown that the calculated molecular constants using a 46 electron effective core-potential and even-tempered augmented polarized core-valence basis sets (aug-pCVnZ-PP, n = 4 and 5) but only including three active electrons in the MRCI calculation are in excellent agreement with the available experimental values. The predicted dissociation energy D{sub e} for the X{sup 2}Σ{sup +} state (extrapolated to the CBS limit) is 16 895.12 cm{sup −1} (2.094 eV), which agrees within 0.1% of a revised experimental value of <16 910.6 cm{sup −1}, while the calculated r{sub e} is within 0.03 pm of the experimental result.

Radon soil gas measurements in a geological versatile region as basis to improve the prediction of areas with a high radon potential

International Nuclear Information System (INIS)

Kabrt, Franz; Rechberger, Fabian; Schuff, Michael; Seidel, Claudia; Baumgartner, Andreas; Friedmann, Harry; Maringer, Franz Josef

2014-01-01

With the aim to predict the radon potential by geological data, radon soil gas measurements were made in a selected region in Styria, Austria. This region is characterised by mean indoor radon potentials of 130-280 Bq m -3 and a high geological diversity. The distribution of the individual measuring sites was selected on the basis of geological aspects and the distribution of area settlements. In this work, the radon soil gas activity concentration and the soil permeability were measured at 100 sites, each with three single measurements. Furthermore, the local dose rate was determined and soil samples were taken at each site to determine the activity concentration of natural radionuclides. During two investigation periods, long-term soil gas radon measurements were made to study the time dependency of the radon activity concentration. All the results will be compared and investigated for correlation among each other to improve the prediction of areas with high radon potential. (authors)

Positive Skin Test or Specific IgE to Penicillin Does Not Reliably Predict Penicillin Allergy.

Science.gov (United States)

Tannert, Line Kring; Mortz, Charlotte Gotthard; Skov, Per Stahl; Bindslev-Jensen, Carsten

According to guidelines, patients are diagnosed with penicillin allergy if skin test (ST) result or specific IgE (s-IgE) to penicillin is positive. However, the true sensitivity and specificity of these tests are presently not known. To investigate the clinical relevance of a positive ST result and positive s-IgE and to study the reproducibility of ST and s-IgE. A sample of convenience of 25 patients with positive penicillin ST results, antipenicillin s-IgE results, or both was challenged with their culprit penicillin. Further 19 patients were not challenged, but deemed allergic on the basis of a recent anaphylactic reaction or delayed reactions to skin testing. Another sample of convenience of 18 patients, 17 overlapping with the 25 challenged, with initial skin testing and s-IgE (median, 25; range, 3-121), months earlier (T -1 ), was repeat skin tested and had s-IgE measured (T 0 ), and then skin tested and had s-IgE measured 4 weeks later (T 1 ). Only 9 (36%) of 25 were challenge positive. There was an increased probability of being penicillin allergic if both ST result and s-IgE were positive at T 0 . Positive ST result or positive s-IgE alone did not predict penicillin allergy. Among the 18 patients repeatedly tested, 46.2% (12 of 25) of positive ST results at T -1 were reproducibly positive at T 0 . For s-IgE, 54.2% (14 of 24) positive measurements were still positive at T 0 and 7 converted to positive at T 1 . The best predictor for a clinically significant (IgE-mediated) penicillin allergy is a combination of a positive case history with simultaneous positive ST result and s-IgE or a positive challenge result. Copyright © 2017 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Investigating the potential of e-Learning in healthcare postgraduate curricula: a structural equation model.

Science.gov (United States)

Katharaki, Maria; Daskalakis, Stelios; Mantas, John

2010-01-01

The objective of this paper is to assess the future adaptability of e-Learning platforms within postgraduate modules. An ongoing empirical assessment was conducted amongst postgraduate students, based on the Technology Acceptance Model (TAM). The current paper presents the outcomes from the second phase of a survey, involving fifty six participants. Data analysis was performed using a structural equation model, based on partial least squares. Results highlighted the very strong effect of perceived usefulness and perceived ease of use to attitude towards using e-Learning platforms. Consequently, attitude towards use proved to be a very strong predictor of behavioral intention. Perceived usefulness, on the contrary, did not prove to have an effect to behavioral intention. Implications on the potential of using e-Learning platforms are discussed along with limitations and future directions of the study.

Radiative K{sub e3} decays revisited

Energy Technology Data Exchange (ETDEWEB)

Gasser, J. [Universitaet Bern, Institut fuer Theoretische Physik, Bern (Switzerland); Kubis, B. [Universitaet Bern, Institut fuer Theoretische Physik, Bern (Switzerland); Universitaet Bonn, Helmholtz-Institut fuer Strahlen- und Kernphysik, Bonn (Germany); Paver, N. [Universita degli Studi di Trieste, Dipartimento di Fisica Teorica, Trieste (Italy); INFN-Trieste, Trieste (Italy); Verbeni, M. [Universidad de Granada, Departamento de Fisica Teorica y del Cosmos, Granada (Spain)

2005-03-01

Motivated by recent experimental results and ongoing measurements, we review the chiral perturbation theory prediction for K{sub L}{yields}{pi}{sup -+}e{sup {+-}}{nu}{sub e}{gamma} decays. Special emphasis is given to the stability of the inner bremsstrahlung-dominated relative branching ratio versus the K{sub e3} form factors, and on the separation of the structure-dependent amplitude in differential distributions over the phase space. For the structure-dependent terms, an assessment of the order p{sup 6} corrections is given, in particular, a full next-to-leading order calculation of the axial component is performed. The experimental analysis of the photon energy spectrum is discussed, and other potentially useful distributions are introduced. (orig.)

Final-state interactions and relativistic effects in the quasielastic (e,e') reaction

International Nuclear Information System (INIS)

Chinn, C.R.; Physics Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545); Picklesimer, A.; Van Orden, J.W.

1989-01-01

The longitudinal and transverse response functions for the inclusive quasielastic (e,e') reaction are analyzed in detail. A microscopic theoretical framework for the many-body reaction provides a clear conceptual (nonrelativistic) basis for treating final-state interactions and goes far beyond simple plane-wave or Hermitean potential models. The many-body physics of inelastic final-state channels as described by optical and multiple scattering theories is properly included by incorporating a full complex optical potential. Explicit nonrelativistic and relativistic momentum-space calculations quantitatively demonstrate the importance of such a treatment of final-state interactions for both the transverse and longitudinal response. Nonrelativistic calculations are performed using final-state interactions based on phenomenology, local density models, and microscopic multiple scattering theory. Relativistic calculations span a similar range of models and employ Dirac bound-state wave functions. The theoretical extension to relativistic dynamics is of course not clear, but is done in obvious parallel to elastic proton scattering. Extensive calculations are performed for 40 Ca at momentum transfers of 410, 550, and 700 MeV/c. A number of interesting physical effects are observed, including significant relativistic suppressions (especially for R L ), large off-shell and virtual pair effects, enhancement of the tails of the response by the final-state interactions, and large qualitative and even shape distinctions between the predictions of the various models of the final-state interactions. None of the models is found to be able to simultaneously predict the data for both response functions. This strongly suggests that additional physical mechanisms are of qualitative importance in inclusive quasielastic electron scattering

Back to basics with e-business

International Nuclear Information System (INIS)

Thomas, V.

2001-01-01

This article gives examples of the opportunities for traditional power companies offered by e-business in the areas of procurement, collaboration, supply chain management, cataloguing, and auctions. BP's interest in e-business-to-customer (B2C) and e-business-to-business (B2B), the anticipated increase in buying and selling over the web, and increased efficiency for businesses using e-business are discussed. The dramatic increase predicted for the US in online energy trading in a report published by Forrester Research of Cambridge Massachusetts, the development of a collaborative arrangement between 13 leading energy trading firms, and the struggle to gain on-line momentum are considered, along with the PA Consulting Group's criticism of the energy sector for not exploiting fully the potential of e-business and for concentrating on B2C where the gains lie in B2B and business-to-workforce areas

The prediction of airborne and structure-borne noise potential for a tire

Science.gov (United States)

Sakamoto, Nicholas Y.

Tire/pavement interaction noise is a major component of both exterior pass-by noise and vehicle interior noise. The current testing methods for ranking tires from loud to quiet require expensive equipment, multiple tires, and/or long experimental set-up and run times. If a laboratory based off-vehicle test could be used to identify the airborne and structure-borne potential of a tire from its dynamic characteristics, a relative ranking of a large group of tires could be performed at relatively modest expense. This would provide a smaller sample set of tires for follow-up testing and thus save expense for automobile OEMs. The focus of this research was identifying key noise features from a tire/pavement experiment. These results were compared against a stationary tire test in which the natural response of the tire to a forced input was measured. Since speed was identified as having some effect on the noise, an input function was also developed to allow the tires to be ranked at an appropriate speed. A relative noise model was used on a second sample set of tires to verify if the ranking could be used against interior vehicle measurements. While overall level analysis of the specified spectrum had mixed success, important noise generating features were identified, and the methods used could be improved to develop a standard off-vehicle test to predict a tire's noise potential.

The potential of predictive analytics to provide clinical decision support in depression treatment planning.

Science.gov (United States)

Kessler, Ronald C

2018-01-01

To review progress developing clinical decision support tools for personalized treatment of major depressive disorder (MDD). Over the years, a variety of individual indicators ranging from biomarkers to clinical observations and self-report scales have been used to predict various aspects of differential MDD treatment response. Most of this work focused on predicting remission either with antidepressant medications versus psychotherapy, some antidepressant medications versus others, some psychotherapies versus others, and combination therapies versus monotherapies. However, to date, none of the individual predictors in these studies has been strong enough to guide optimal treatment selection for most patients. Interest consequently turned to decision support tools made up of multiple predictors, but the development of such tools has been hampered by small study sample sizes. Design recommendations are made here for future studies to address this problem. Recommendations include using large prospective observational studies followed by pragmatic trials rather than smaller, expensive controlled treatment trials for preliminary development of decision support tools; basing these tools on comprehensive batteries of inexpensive self-report and clinical predictors (e.g., self-administered performance-based neurocognitive tests) versus expensive biomarkers; and reserving biomarker assessments for targeted studies of patients not well classified by inexpensive predictor batteries.

Climate and pH predict the potential range of the invasive apple snail (Pomacea insularum in the southeastern United States.

Directory of Open Access Journals (Sweden)

James E Byers

Full Text Available Predicting the potential range of invasive species is essential for risk assessment, monitoring, and management, and it can also inform us about a species' overall potential invasiveness. However, modeling the distribution of invasive species that have not reached their equilibrium distribution can be problematic for many predictive approaches. We apply the modeling approach of maximum entropy (MaxEnt that is effective with incomplete, presence-only datasets to predict the distribution of the invasive island apple snail, Pomacea insularum. This freshwater snail is native to South America and has been spreading in the USA over the last decade from its initial introductions in Texas and Florida. It has now been documented throughout eight southeastern states. The snail's extensive consumption of aquatic vegetation and ability to accumulate and transmit algal toxins through the food web heighten concerns about its spread. Our model shows that under current climate conditions the snail should remain mostly confined to the coastal plain of the southeastern USA where it is limited by minimum temperature in the coldest month and precipitation in the warmest quarter. Furthermore, low pH waters (pH <5.5 are detrimental to the snail's survival and persistence. Of particular note are low-pH blackwater swamps, especially Okefenokee Swamp in southern Georgia (with a pH below 4 in many areas, which are predicted to preclude the snail's establishment even though many of these areas are well matched climatically. Our results elucidate the factors that affect the regional distribution of P. insularum, while simultaneously presenting a spatial basis for the prediction of its future spread. Furthermore, the model for this species exemplifies that combining climatic and habitat variables is a powerful way to model distributions of invasive species.

Predicted and observed cooling tower plume rise and visible plume length at the John E. Amos power plant

Energy Technology Data Exchange (ETDEWEB)

Hanna, S R

1976-01-01

A one-dimensional numerical cloud growth model and several empirical models for plume rise and cloud growth are compared with twenty-seven sets of observations of cooling tower plumes from the 2900 MW John E. Amos power plant in West Virginia. The three natural draft cooling towers are 200 m apart. In a cross wind, the plumes begin to merge at a distance of about 500 m downwind. In calm conditions, with reduced entrainment, the plumes often do not merge until heights of 1000 m. The average plume rise, 750 m, is predicted well by the models, but day-to-day variations are simulated with a correlation coefficient of about 0.5. Model predictions of visible plume length agree, on the average, with observations for visible plumes of short to moderate length (less than about 1 km). The prediction of longer plumes is hampered by our lack of knowledge of plume spreading after the plumes level off. Cloud water concentrations predicted by the numerical model agree with those measured in natural cumulus clouds (about 0.1 to 1 g kg/sup -1/).

Modelling in vivo action potential propagation along a giant axon.

Science.gov (United States)

George, Stuart; Foster, Jamie M; Richardson, Giles

2015-01-01

A partial differential equation model for the three-dimensional current flow in an excitable, unmyelinated axon is considered. Where the axon radius is significantly below a critical value R(crit) (that depends upon intra- and extra-cellular conductivity and ion channel conductance) the resistance of the intracellular space is significantly higher than that of the extracellular space, such that the potential outside the axon is uniformly small whilst the intracellular potential is approximated by the transmembrane potential. In turn, since the current flow is predominantly axial, it can be shown that the transmembrane potential is approximated by a solution to the one-dimensional cable equation. It is noted that the radius of the squid giant axon, investigated by (Hodgkin and Huxley 1952e), lies close to R(crit). This motivates us to apply the three-dimensional model to the squid giant axon and compare the results thus found to those obtained using the cable equation. In the context of the in vitro experiments conducted in (Hodgkin and Huxley 1952e) we find only a small difference between the wave profiles determined using these two different approaches and little difference between the speeds of action potential propagation predicted. This suggests that the cable equation approximation is accurate in this scenario. However when applied to the it in vivo setting, in which the conductivity of the surrounding tissue is considerably lower than that of the axoplasm, there are marked differences in both wave profile and speed of action potential propagation calculated using the two approaches. In particular, the cable equation significantly over predicts the increase in the velocity of propagation as axon radius increases. The consequences of these results are discussed in terms of the evolutionary costs associated with increasing the speed of action potential propagation by increasing axon radius.

The experimental scavenging capacity and the degradation potential of the mixture of carotenoid and vitamin E, vitamin C

Science.gov (United States)

Tuyet, Nguyen Thi Ngoc; Khoa, Tran Anh; Quan, Vu Thi Hong; Chinh, Vuong Ngoc; Phung, Le Thi Kim

2017-09-01

The antioxidant capacity of Gac oil can be enhanced by the presence of these other active antioxidants such as vitamin E, vitamin C. Since many of these natural antioxidants are consumed together in foods, the potential for scavenging capacity is high in the human diet. The aim of this study was to determine what concentrations and combinations of antioxidants among Gac oil, vitamin E, vitamin C are capable of producing high scavenging capacity. The fact has resulted in detailed studies of antioxidation capacity of carotenoid of and vitamin. In addition, the antioxidant capacity and degradation potential of the combined mixture of carotenoid and vitamin E, vitamin C were discussed in view of their antioxidant properties as beneficial species in preventing various diseases.

Niche conservatism and the invasive potential of the wild boar.

Science.gov (United States)

Sales, Lilian Patrícia; Ribeiro, Bruno R; Hayward, Matt Warrington; Paglia, Adriano; Passamani, Marcelo; Loyola, Rafael

2017-09-01

Niche conservatism, i.e. the retention of a species' fundamental niche through evolutionary time, is cornerstone for biological invasion assessments. The fact that species tend to maintain their original climate niche allows predictive maps of invasion risk to anticipate potential invadable areas. Unravelling the mechanisms driving niche shifts can shed light on the management of invasive species. Here, we assessed niche shifts in one of the world's worst invasive species: the wild boar Sus scrofa. We also predicted potential invadable areas based on an ensemble of three ecological niche modelling methods, and evaluated the performance of models calibrated with native vs. pooled (native plus invaded) species records. By disentangling the drivers of change on the exotic wild boar population's niches, we found strong evidence for niche conservatism during biological invasion. Ecological niche models calibrated with both native and pooled range records predicted convergent areas. Also, observed niche shifts are mostly explained by niche unfilling, i.e. there are unoccupied areas in the exotic range where climate is analogous to the native range. Niche unfilling is expected as result of recent colonization and ongoing dispersal, and was potentially stronger for the Neotropics, where a recent wave of introductions for pig-farming and game-hunting has led to high wild boar population growth rates. The invasive potential of wild boar in the Neotropics is probably higher than in other regions, which has profound management implications if we are to prevent their invasion into species-rich areas, such as Amazonia, coupled with expansion of African swine fever and possibly great economic losses. Although the originally Eurasian-wide distribution suggests a pre-adaptation to a wide array of climates, the wild boar world-wide invasion does not exhibit evidence of niche evolution. The invasive potential of the wild boar therefore probably lies on the reproductive, dietary and

Predicting distribution of Aedes aegypti and Culex pipiens complex, potential vectors of Rift Valley fever virus in relation to disease epidemics in East Africa

Directory of Open Access Journals (Sweden)

Clement Nyamunura Mweya

2013-10-01

Full Text Available Background: The East African region has experienced several Rift Valley fever (RVF outbreaks since the 1930s. The objective of this study was to identify distributions of potential disease vectors in relation to disease epidemics. Understanding disease vector potential distributions is a major concern for disease transmission dynamics. Methods: Diverse ecological niche modelling techniques have been developed for this purpose: we present a maximum entropy (Maxent approach for estimating distributions of potential RVF vectors in un-sampled areas in East Africa. We modelled the distribution of two species of mosquitoes (Aedes aegypti and Culex pipiens complex responsible for potential maintenance and amplification of the virus, respectively. Predicted distributions of environmentally suitable areas in East Africa were based on the presence-only occurrence data derived from our entomological study in Ngorongoro District in northern Tanzania. Results: Our model predicted potential suitable areas with high success rates of 90.9% for A. aegypti and 91.6% for C. pipiens complex. Model performance was statistically significantly better than random for both species. Most suitable sites for the two vectors were predicted in central and northwestern Tanzania with previous disease epidemics. Other important risk areas include western Lake Victoria, northern parts of Lake Malawi, and the Rift Valley region of Kenya. Conclusion: Findings from this study show distributions of vectors had biological and epidemiological significance in relation to disease outbreak hotspots, and hence provide guidance for the selection of sampling areas for RVF vectors during inter-epidemic periods.

Predicting distribution of Aedes aegypti and Culex pipiens complex, potential vectors of Rift Valley fever virus in relation to disease epidemics in East Africa.

Science.gov (United States)

Mweya, Clement Nyamunura; Kimera, Sharadhuli Iddi; Kija, John Bukombe; Mboera, Leonard E G

2013-01-01

The East African region has experienced several Rift Valley fever (RVF) outbreaks since the 1930s. The objective of this study was to identify distributions of potential disease vectors in relation to disease epidemics. Understanding disease vector potential distributions is a major concern for disease transmission dynamics. DIVERSE ECOLOGICAL NICHE MODELLING TECHNIQUES HAVE BEEN DEVELOPED FOR THIS PURPOSE: we present a maximum entropy (Maxent) approach for estimating distributions of potential RVF vectors in un-sampled areas in East Africa. We modelled the distribution of two species of mosquitoes (Aedes aegypti and Culex pipiens complex) responsible for potential maintenance and amplification of the virus, respectively. Predicted distributions of environmentally suitable areas in East Africa were based on the presence-only occurrence data derived from our entomological study in Ngorongoro District in northern Tanzania. Our model predicted potential suitable areas with high success rates of 90.9% for A. aegypti and 91.6% for C. pipiens complex. Model performance was statistically significantly better than random for both species. Most suitable sites for the two vectors were predicted in central and northwestern Tanzania with previous disease epidemics. Other important risk areas include western Lake Victoria, northern parts of Lake Malawi, and the Rift Valley region of Kenya. Findings from this study show distributions of vectors had biological and epidemiological significance in relation to disease outbreak hotspots, and hence provide guidance for the selection of sampling areas for RVF vectors during inter-epidemic periods.

3α-breakup-induced dynamical polarization potential of 12C at E/A >= 10 MeV

International Nuclear Information System (INIS)

Kubono, S.; Sugitani, M.; Tanaka, M.H.; Morita, K.; Sakuragi, Y.; Kamimura, M.

1985-06-01

The important role of the 3α-breakup processes to the optical potential of 12 C at E/A >= 10 MeV has been shown by observing directly the excitation of the 7.65-MeV 0 2 + state which breaks into 3α clusters. The 3α-breakup processes also explain well the previously unknown reduction factor for the exit-channel real potential for the same state. (author)

The potential of large studies for building genetic risk prediction models

Science.gov (United States)

NCI scientists have developed a new paradigm to assess hereditary risk prediction in common diseases, such as prostate cancer. This genetic risk prediction concept is based on polygenic analysis—the study of a group of common DNA sequences, known as singl

Interpreting expression data with metabolic flux models: predicting Mycobacterium tuberculosis mycolic acid production.

Directory of Open Access Journals (Sweden)

Caroline Colijn

2009-08-01

Full Text Available Metabolism is central to cell physiology, and metabolic disturbances play a role in numerous disease states. Despite its importance, the ability to study metabolism at a global scale using genomic technologies is limited. In principle, complete genome sequences describe the range of metabolic reactions that are possible for an organism, but cannot quantitatively describe the behaviour of these reactions. We present a novel method for modeling metabolic states using whole cell measurements of gene expression. Our method, which we call E-Flux (as a combination of flux and expression, extends the technique of Flux Balance Analysis by modeling maximum flux constraints as a function of measured gene expression. In contrast to previous methods for metabolically interpreting gene expression data, E-Flux utilizes a model of the underlying metabolic network to directly predict changes in metabolic flux capacity. We applied E-Flux to Mycobacterium tuberculosis, the bacterium that causes tuberculosis (TB. Key components of mycobacterial cell walls are mycolic acids which are targets for several first-line TB drugs. We used E-Flux to predict the impact of 75 different drugs, drug combinations, and nutrient conditions on mycolic acid biosynthesis capacity in M. tuberculosis, using a public compendium of over 400 expression arrays. We tested our method using a model of mycolic acid biosynthesis as well as on a genome-scale model of M. tuberculosis metabolism. Our method correctly predicts seven of the eight known fatty acid inhibitors in this compendium and makes accurate predictions regarding the specificity of these compounds for fatty acid biosynthesis. Our method also predicts a number of additional potential modulators of TB mycolic acid biosynthesis. E-Flux thus provides a promising new approach for algorithmically predicting metabolic state from gene expression data.

The Dialogic Potential of ePortfolios: Formative Feedback and Communities of Learning within a Personal Learning Environment

Science.gov (United States)

Ehiyazaryan-White, Ester

2012-01-01

This paper reports on the findings of a study into the use of ePortfolios as personal learning environments (PLE) by a group of students pursuing Master's degrees in Education. The qualitative study explores the potential of the ePortfolio to support learners in engaging in formative peer and tutor feedback as well as in developing a learning…

Enhanced Prediction of Src Homology 2 (SH2) Domain Binding Potentials Using a Fluorescence Polarization-derived c-Met, c-Kit, ErbB, and Androgen Receptor Interactome*

Science.gov (United States)

Leung, Kin K.; Hause, Ronald J.; Barkinge, John L.; Ciaccio, Mark F.; Chuu, Chih-Pin; Jones, Richard B.

2014-01-01

Many human diseases are associated with aberrant regulation of phosphoprotein signaling networks. Src homology 2 (SH2) domains represent the major class of protein domains in metazoans that interact with proteins phosphorylated on the amino acid residue tyrosine. Although current SH2 domain prediction algorithms perform well at predicting the sequences of phosphorylated peptides that are likely to result in the highest possible interaction affinity in the context of random peptide library screens, these algorithms do poorly at predicting the interaction potential of SH2 domains with physiologically derived protein sequences. We employed a high throughput interaction assay system to empirically determine the affinity between 93 human SH2 domains and phosphopeptides abstracted from several receptor tyrosine kinases and signaling proteins. The resulting interaction experiments revealed over 1000 novel peptide-protein interactions and provided a glimpse into the common and specific interaction potentials of c-Met, c-Kit, GAB1, and the human androgen receptor. We used these data to build a permutation-based logistic regression classifier that performed considerably better than existing algorithms for predicting the interaction potential of several SH2 domains. PMID:24728074

Use of human papillomavirus DNA, E6/E7 mRNA, and p16 immunocytochemistry to detect and predict anal high-grade squamous intraepithelial lesions in HIV-positive and HIV-negative men who have sex with men.

Directory of Open Access Journals (Sweden)

Nittaya Phanuphak

Full Text Available Men who have sex with men (MSM are at high risk of having anal cancer. Anal high-grade squamous intraepithelial lesion (HSIL is the precursor of anal cancer. We explored the use of different biomarkers associated with human papillomavirus (HPV infection and HPV-mediated cell transformation to detect and predict HSIL among HIV-positive and HIV-negative MSM.A total of 123 HIV-positive and 123 HIV-negative MSM were enrolled and followed for 12 months. High-resolution anoscopy (HRA with biopsies were performed at every visit along with anal sample collection for cytology, high-risk HPV DNA genotyping, HPV E6/E7 mRNA, and p16 immunocytochemistry. Performance characteristics and area under the receiver operator characteristics curve were calculated for these biomarkers at baseline, and Cox regression compared the usefulness of these biomarkers in predicting incident HSIL. High-risk HPV DNA, E6/E7 mRNA, and p16 immunocytochemistry each identified 43-46% of MSM whose baseline test positivity would trigger HRA referral. E6/E7 mRNA had the highest sensitivity (64.7% and correctly classified the highest number of prevalent HSIL cases. With the exception of p16 immunochemistry, most tests showed significant increases in sensitivity but decreases specificity versus anal cytology, while the overall number of correctly classified cases was not significantly different. Baseline or persistent type 16 and/or 18 HPV DNA was the only test significantly predicting incident histologic HSIL within 12 months in models adjusted for HIV status and low-grade squamous intraepithelial lesions at baseline.Countries with a high HIV prevalence among MSM and limited HRA resources may consider using biomarkers to identify individuals at high risk of HSIL. E6/E7 mRNA had the highest sensitivity for prevalent HSIL detection regardless of HIV status, whereas type 16 and/or 18 HPV DNA performed best in predicting development of incident HSIL within 12 months.

Development of a generally applicable morphokinetic algorithm capable of predicting the implantation potential of embryos transferred on Day 3

Science.gov (United States)

Petersen, Bjørn Molt; Boel, Mikkel; Montag, Markus; Gardner, David K.

2016-01-01

STUDY QUESTION Can a generally applicable morphokinetic algorithm suitable for Day 3 transfers of time-lapse monitored embryos originating from different culture conditions and fertilization methods be developed for the purpose of supporting the embryologist's decision on which embryo to transfer back to the patient in assisted reproduction? SUMMARY ANSWER The algorithm presented here can be used independently of culture conditions and fertilization method and provides predictive power not surpassed by other published algorithms for ranking embryos according to their blastocyst formation potential. WHAT IS KNOWN ALREADY Generally applicable algorithms have so far been developed only for predicting blastocyst formation. A number of clinics have reported validated implantation prediction algorithms, which have been developed based on clinic-specific culture conditions and clinical environment. However, a generally applicable embryo evaluation algorithm based on actual implantation outcome has not yet been reported. STUDY DESIGN, SIZE, DURATION Retrospective evaluation of data extracted from a database of known implantation data (KID) originating from 3275 embryos transferred on Day 3 conducted in 24 clinics between 2009 and 2014. The data represented different culture conditions (reduced and ambient oxygen with various culture medium strategies) and fertilization methods (IVF, ICSI). The capability to predict blastocyst formation was evaluated on an independent set of morphokinetic data from 11 218 embryos which had been cultured to Day 5. PARTICIPANTS/MATERIALS, SETTING, METHODS The algorithm was developed by applying automated recursive partitioning to a large number of annotation types and derived equations, progressing to a five-fold cross-validation test of the complete data set and a validation test of different incubation conditions and fertilization methods. The results were expressed as receiver operating characteristics curves using the area under the

Predicting Spike Occurrence and Neuronal Responsiveness from LFPs in Primary Somatosensory Cortex

Science.gov (United States)

Storchi, Riccardo; Zippo, Antonio G.; Caramenti, Gian Carlo; Valente, Maurizio; Biella, Gabriele E. M.

2012-01-01

Local Field Potentials (LFPs) integrate multiple neuronal events like synaptic inputs and intracellular potentials. LFP spatiotemporal features are particularly relevant in view of their applications both in research (e.g. for understanding brain rhythms, inter-areal neural communication and neronal coding) and in the clinics (e.g. for improving invasive Brain-Machine Interface devices). However the relation between LFPs and spikes is complex and not fully understood. As spikes represent the fundamental currency of neuronal communication this gap in knowledge strongly limits our comprehension of neuronal phenomena underlying LFPs. We investigated the LFP-spike relation during tactile stimulation in primary somatosensory (S-I) cortex in the rat. First we quantified how reliably LFPs and spikes code for a stimulus occurrence. Then we used the information obtained from our analyses to design a predictive model for spike occurrence based on LFP inputs. The model was endowed with a flexible meta-structure whose exact form, both in parameters and structure, was estimated by using a multi-objective optimization strategy. Our method provided a set of nonlinear simple equations that maximized the match between models and true neurons in terms of spike timings and Peri Stimulus Time Histograms. We found that both LFPs and spikes can code for stimulus occurrence with millisecond precision, showing, however, high variability. Spike patterns were predicted significantly above chance for 75% of the neurons analysed. Crucially, the level of prediction accuracy depended on the reliability in coding for the stimulus occurrence. The best predictions were obtained when both spikes and LFPs were highly responsive to the stimuli. Spike reliability is known to depend on neuron intrinsic properties (i.e. on channel noise) and on spontaneous local network fluctuations. Our results suggest that the latter, measured through the LFP response variability, play a dominant role. PMID:22586452

EPRI MOV performance prediction program

International Nuclear Information System (INIS)

Hosler, J.F.; Damerell, P.S.; Eidson, M.G.; Estep, N.E.

1994-01-01

An overview of the EPRI Motor-Operated Valve (MOV) Performance Prediction Program is presented. The objectives of this Program are to better understand the factors affecting the performance of MOVs and to develop and validate methodologies to predict MOV performance. The Program involves valve analytical modeling, separate-effects testing to refine the models, and flow-loop and in-plant MOV testing to provide a basis for model validation. The ultimate product of the Program is an MOV Performance Prediction Methodology applicable to common gate, globe, and butterfly valves. The methodology predicts thrust and torque requirements at design-basis flow and differential pressure conditions, assesses the potential for gate valve internal damage, and provides test methods to quantify potential for gate valve internal damage, and provides test methods to quantify potential variations in actuator output thrust with loading condition. Key findings and their potential impact on MOV design and engineering application are summarized

Computational Redox Potential Predictions: Applications to Inorganic and Organic Aqueous Complexes, and Complexes Adsorbed to Mineral Surfaces

Directory of Open Access Journals (Sweden)

Krishnamoorthy Arumugam

2014-04-01

Full Text Available Applications of redox processes range over a number of scientific fields. This review article summarizes the theory behind the calculation of redox potentials in solution for species such as organic compounds, inorganic complexes, actinides, battery materials, and mineral surface-bound-species. Different computational approaches to predict and determine redox potentials of electron transitions are discussed along with their respective pros and cons for the prediction of redox potentials. Subsequently, recommendations are made for certain necessary computational settings required for accurate calculation of redox potentials. This article reviews the importance of computational parameters, such as basis sets, density functional theory (DFT functionals, and relativistic approaches and the role that physicochemical processes play on the shift of redox potentials, such as hydration or spin orbit coupling, and will aid in finding suitable combinations of approaches for different chemical and geochemical applications. Identifying cost-effective and credible computational approaches is essential to benchmark redox potential calculations against experiments. Once a good theoretical approach is found to model the chemistry and thermodynamics of the redox and electron transfer process, this knowledge can be incorporated into models of more complex reaction mechanisms that include diffusion in the solute, surface diffusion, and dehydration, to name a few. This knowledge is important to fully understand the nature of redox processes be it a geochemical process that dictates natural redox reactions or one that is being used for the optimization of a chemical process in industry. In addition, it will help identify materials that will be useful to design catalytic redox agents, to come up with materials to be used for batteries and photovoltaic processes, and to identify new and improved remediation strategies in environmental engineering, for example the

Effect of prediction on the self-organization of pedestrian counter flow

International Nuclear Information System (INIS)

Wang Ziyang; Zhao Hui; Ma Jian; Qin Yong; Jia Limin

2012-01-01

Pedestrians may predict the behavior of others and then adjust their movement accordingly to avoid potential conflicts in advance. Motivated by this fact, we propose a predictive control theory-based pedestrian counter flow model, which describes the predictive mechanism underlying pedestrian self-organization phenomena. In this model, a pedestrian will make in-advance-avoid behavior based on the estimation of future moving gain within a given predictive length to reduce potential conflicts. The future gain in the present model is affected by three factors, i.e. the predictive length, the smooth degree of entrance and the influential area of coming pedestrians. Simulation results of the model show that increasing predictive length has a remarkable effect on reducing conflicts, improving pedestrian velocity, smoothing pedestrian movement and stabilizing the self-organized lanes. When enlarging the influential area of coming pedestrians, pedestrians tend to aggregate to the formed self-organized lanes, which makes the lanes wider and the lane number reduced. Interestingly, moderate enlargement (of the influential area) will reduce conflicts significantly, while excessive enlargement will lead to an increase in conflicts. We also discuss the predictive effect toward the smooth degree of entrance. When there are some formed self-organized lanes in the system, the effect is significant, and it will make the lanes more regular and stable, while when the existing lanes are unstable, the effect has little impact on the system. (paper)

Predicting Social Anxiety Treatment Outcome Based on Therapeutic Email Conversations.

Science.gov (United States)

Hoogendoorn, Mark; Berger, Thomas; Schulz, Ava; Stolz, Timo; Szolovits, Peter

2017-09-01

Predicting therapeutic outcome in the mental health domain is of utmost importance to enable therapists to provide the most effective treatment to a patient. Using information from the writings of a patient can potentially be a valuable source of information, especially now that more and more treatments involve computer-based exercises or electronic conversations between patient and therapist. In this paper, we study predictive modeling using writings of patients under treatment for a social anxiety disorder. We extract a wealth of information from the text written by patients including their usage of words, the topics they talk about, the sentiment of the messages, and the style of writing. In addition, we study trends over time with respect to those measures. We then apply machine learning algorithms to generate the predictive models. Based on a dataset of 69 patients, we are able to show that we can predict therapy outcome with an area under the curve of 0.83 halfway through the therapy and with a precision of 0.78 when using the full data (i.e., the entire treatment period). Due to the limited number of participants, it is hard to generalize the results, but they do show great potential in this type of information.

Revising the predictions of inflation for the cosmic microwave background anisotropies.

Science.gov (United States)

Agulló, Iván; Navarro-Salas, José; Olmo, Gonzalo J; Parker, Leonard

2009-08-07

We point out that, if quantum field renormalization is taken into account and the counterterms are evaluated at the Hubble-radius crossing time or few e-foldings after it, the predictions of slow-roll inflation for both the scalar and the tensorial power spectrum change significantly. This leads to a change in the consistency condition that relates the tensor-to-scalar amplitude ratio with spectral indices. A reexamination of the potentials varphi;{2} and varphi;{4} shows that both are compatible with five-year WMAP data. Only when the counterterms are evaluated at much larger times beyond the end of inflation does one recover the standard predictions. The alternative predictions presented here may soon come within the range of measurement of near-future experiments.

Predictive Manufacturing: A Classification Strategy to Predict Product Failures

DEFF Research Database (Denmark)

Khan, Abdul Rauf; Schiøler, Henrik; Kulahci, Murat

2018-01-01

manufacturing analytics model that employs a big data approach to predicting product failures; third, we illustrate the issue of high dimensionality, along with statistically redundant information; and, finally, our proposed method will be compared against the well-known classification methods (SVM, K......-nearest neighbor, artificial neural networks). The results from real data show that our predictive manufacturing analytics approach, using genetic algorithms and Voronoi tessellations, is capable of predicting product failure with reasonable accuracy. The potential application of this method contributes...... to accurately predicting product failures, which would enable manufacturers to reduce production costs without compromising product quality....

Back to basics with e-business

Energy Technology Data Exchange (ETDEWEB)

Thomas, V.

2001-07-01

This article gives examples of the opportunities for traditional power companies offered by e-business in the areas of procurement, collaboration, supply chain management, cataloguing, and auctions. BP's interest in e-business-to-customer (B2C) and e-business-to-business (B2B), the anticipated increase in buying and selling over the web, and increased efficiency for businesses using e-business are discussed. The dramatic increase predicted for the US in online energy trading in a report published by Forrester Research of Cambridge Massachusetts, the development of a collaborative arrangement between 13 leading energy trading firms, and the struggle to gain on-line momentum are considered, along with the PA Consulting Group's criticism of the energy sector for not exploiting fully the potential of e-business and for concentrating on B2C where the gains lie in B2B and business-to-workforce areas.

Superfractionation as a potential hypoxic cell radiosensitizer: prediction of an optimum dose per fraction

International Nuclear Information System (INIS)

Dasu, Alexandru; Denekamp, Juliana

1999-01-01

Purpose: A dose 'window of opportunity' has been identified in an earlier modeling study if the inducible repair variant of the LQ model is adopted instead of the pure LQ model, and if all survival curve parameters are equally modified by the presence or absence of oxygen. In this paper we have extended the calculations to consider survival curve parameters from 15 sets of data obtained for cells tested at low doses using clonogenic assays. Methods and Materials: A simple computer model has been used to simulate the response of each cell line to various doses per fraction in multifraction schedules, with oxic and hypoxic cells receiving the same fractional dose. We have then used pairs of simulated survival curves to estimate the effective hypoxic protection (OER') as a function of the dose per fraction. Results: The resistance of hypoxic cells is reduced by using smaller doses per fraction than 2 Gy in all these fractionated clinical simulations, whether using a simple LQ model, or the more complex LQ/IR model. If there is no inducible repair, the optimum dose is infinitely low. If there is inducible repair, there is an optimum dose per fraction at which hypoxic protection is minimized. This is usually around 0.5 Gy. It depends on the dose needed to induce repair being higher in hypoxia than in oxygen. The OER' may even go below unity, i.e. hypoxic cells may be more sensitive than oxic cells. Conclusions: If oxic and hypoxic cells are repeatedly exposed to doses of the same magnitude, as occurs in clinical radiotherapy, the observed hypoxic protection varies with the fractional dose. The OER' is predicted to diminish at lower doses in all cell lines. The loss of hypoxic resistance with superfractionation is predicted to be proportional to the capacity of the cells to induce repair, i.e. their intrinsic radioresistance at a dose of 2 Gy

Pathological tremor prediction using surface EMG and acceleration: potential use in “ON-OFF” demand driven deep brain stimulator design

Science.gov (United States)

Basu, Ishita; Graupe, Daniel; Tuninetti, Daniela; Shukla, Pitamber; Slavin, Konstantin V.; Metman, Leo Verhagen; Corcos, Daniel M.

2013-01-01

Objective We present a proof of concept for a novel method of predicting the onset of pathological tremor using non-invasively measured surface electromyogram (sEMG) and acceleration from tremor-affected extremities of patients with Parkinson’s disease (PD) and Essential tremor (ET). Approach The tremor prediction algorithm uses a set of spectral (fourier and wavelet) and non-linear time series (entropy and recurrence rate) parameters extracted from the non-invasively recorded sEMG and acceleration signals. Main results The resulting algorithm is shown to successfully predict tremor onset for all 91 trials recorded in 4 PD patients and for all 91 trials recorded in 4 ET patients. The predictor achieves a 100% sensitivity for all trials considered, along with an overall accuracy of 85.7% for all ET trials and 80.2% for all PD trials. By using a Pearson’s chi-square test, the prediction results are shown to significantly differ from a random prediction outcome. Significance The tremor prediction algorithm can be potentially used for designing the next generation of non-invasive closed-loop predictive ON-OFF controllers for deep brain stimulation (DBS), used for suppressing pathological tremor in such patients. Such a system is based on alternating ON and OFF DBS periods, an incoming tremor being predicted during the time intervals when DBS is OFF, so as to turn DBS back ON. The prediction should be a few seconds before tremor re-appears so that the patient is tremor-free for the entire DBS ON-OFF cycle as well as the tremor-free DBS OFF interval should be maximized in order to minimize the current injected in the brain and battery usage. PMID:23658233

Pathological tremor prediction using surface electromyogram and acceleration: potential use in ‘ON-OFF’ demand driven deep brain stimulator design

Science.gov (United States)

Basu, Ishita; Graupe, Daniel; Tuninetti, Daniela; Shukla, Pitamber; Slavin, Konstantin V.; Verhagen Metman, Leo; Corcos, Daniel M.

2013-06-01

Objective. We present a proof of concept for a novel method of predicting the onset of pathological tremor using non-invasively measured surface electromyogram (sEMG) and acceleration from tremor-affected extremities of patients with Parkinson’s disease (PD) and essential tremor (ET). Approach. The tremor prediction algorithm uses a set of spectral (Fourier and wavelet) and nonlinear time series (entropy and recurrence rate) parameters extracted from the non-invasively recorded sEMG and acceleration signals. Main results. The resulting algorithm is shown to successfully predict tremor onset for all 91 trials recorded in 4 PD patients and for all 91 trials recorded in 4 ET patients. The predictor achieves a 100% sensitivity for all trials considered, along with an overall accuracy of 85.7% for all ET trials and 80.2% for all PD trials. By using a Pearson’s chi-square test, the prediction results are shown to significantly differ from a random prediction outcome. Significance. The tremor prediction algorithm can be potentially used for designing the next generation of non-invasive closed-loop predictive ON-OFF controllers for deep brain stimulation (DBS), used for suppressing pathological tremor in such patients. Such a system is based on alternating ON and OFF DBS periods, an incoming tremor being predicted during the time intervals when DBS is OFF, so as to turn DBS back ON. The prediction should be a few seconds before tremor re-appears so that the patient is tremor-free for the entire DBS ON-OFF cycle and the tremor-free DBS OFF interval should be maximized in order to minimize the current injected in the brain and battery usage.

{sigma}{sup t}ot{sub e}eyy at e{sup +}e{sup -} colliders

Energy Technology Data Exchange (ETDEWEB)

Godbole, R.M. [Indian Institute of Science, Centre for Theoretical Studies, Bangalore (India); Pancheri, G. [Istituto Nazionale di Fisica Nucleare, Laboratori Nazionali di Frascati, Rome (Italy)

2001-02-01

In this talk are briefly summarized different models for {sigma}{sup t}ot{sub 2}y (e{sup +}e{sup -} {yields}yy{yields} hadrons) and contrast model predictions with the data. It will be then discussed the capability of the future e{sup +}e{sup -} and yy colliders to distinguish between various models and end with an outlook for future work.

Investigating the CYP2E1 Potential Role in the Mechanisms Behind INH/LPS-Induced Hepatotoxicity

Directory of Open Access Journals (Sweden)

Hozeifa M. Hassan

2018-03-01

Full Text Available Tuberculosis (TB is one of the oldest infectious diseases that affected humankind and remains one of the world’s deadliest communicable diseases that could be considered as global emergency, but the discovery and development of isoniazid (INH in the 1950s paved the way to an effective single and/or combined first-line anti-TB therapy. However, administration of INH induces severe hepatic toxicity in some patients. Previously, we establish a rat model of INH hepatotoxicity utilizing the inflammatory stress theory, in which bacterial lipopolysaccharide (LPS potentially enhanced INH toxicity. These enhancing activities ranged between augmenting the inflammatory stress, oxidative stress, alteration of bile acid homeostasis, and CYP2E1 over-expression. Although pre-treatment with dexamethasone (DEX helped overcome both inflammatory and oxidative stress which ended-up in alleviation of LPS augmenting effects, but still minor toxicities were being detected, alongside with CYP2E1 over expression. This finding positively indicated the corner-stone role played by CYP2E1 in the pathogenesis of INH/LPS-induced liver damage. Therefore, we examined whether INH/LPS co-treatment with CYP2E1 inhibitor diallyl sulfide (DAS and DEX can protect against the INH/LPS-induced hepatotoxicity. Our results showed that pre-administration of both DAS and DEX caused significant reduction in serum TBA, TBil, and gamma-glutamyl transferase levels. Furthermore, the histopathological analysis showed that DAS and DEX could effectively reverse the liver lesions seen following INH/LPS treatment and protect against hepatic steatosis as indicated by absence of lipid accumulation. Pre-treatment with DAS alone could not completely block the CYP2E1 protein expression following INH/LPS treatment, as appeared in the immunoblotting and immunohistochemistry results. This is probably due to the fact that the combined enhancement activities of both INH and LPS on CYP2E1 protein expression

Shear viscosity of binary mixtures: The Gay-Berne potential

Science.gov (United States)

Khordad, R.

2012-05-01

The Gay-Berne (GB) potential model is an interesting and useful model to study the real systems. Using the potential model, we intend to examine the thermodynamical properties of some anisotropic binary mixtures in two different phases, liquid and gas. For this purpose, we apply the integral equation method and solve numerically the Percus-Yevick (PY) integral equation. Then, we obtain the expansion coefficients of correlation functions to calculate the thermodynamical properties. Finally, we compare our results with the available experimental data [e.g., HFC-125 + propane, R-125/143a, methanol + toluene, benzene + methanol, cyclohexane + ethanol, benzene + ethanol, carbon tetrachloride + ethyl acetate, and methanol + ethanol]. The results show that the GB potential model is capable for predicting the thermodynamical properties of binary mixtures with acceptable accuracy.

E-commerce of freshwater aquarium fishes: potential disseminator of exotic species in Brazil - doi: 10.4025/actascibiolsci.v32i3.3919 E-commerce of freshwater aquarium fishes: potential disseminator of exotic species in Brazil - doi: 10.4025/actascibiolsci.v32i3.3919

Directory of Open Access Journals (Sweden)

André Lincoln Barroso de Magalhães

2010-09-01

Full Text Available The availability of freshwater aquarium fish species for sale was surveyed from July 2005 to June 2006 in Brazilian electronic commerce and the Orkut website. São Paulo was the leading state regarding virtual shops, auctions on Arremate/Mercado Livre, and hobbyists on Orkut, with 52, 44 and 46%, respectively. The Southeast and South regions led the offer of pest species such as C. carpio, C. auratus and P. reticulate. Among the 207 species for sale, 14 species considered potential pests were identified, contrasting with only one page that warned about the dangers of aquarium dumping. The easy access to fish (especially the potential pest species through e-commerce and Orkut, together with the low total price (unitary value + shipping and handling ranging from US$ 17.67 to 30.39, and fast interstate delivery (two-four days on average confirm the widespread e-commerce accessibility and its high dispersal potential via postal services and home hobbyists trade. It is imperative to enforce the use of warnings or alert messages in e-commerce about the dangers of biological invasions.The availability of freshwater aquarium fish species for sale was surveyed from July 2005 to June 2006 in Brazilian electronic commerce and the Orkut website. São Paulo was the leading state regarding virtual shops, auctions on Arremate/Mercado Livre, and hobbyists on Orkut, with 52, 44 and 46%, respectively. The Southeast and South regions led the offer of pest species such as C. carpio, C. auratus and P. reticulate. Among the 207 species for sale, 14 species considered potential pests were identified, contrasting with only one page that warned about the dangers of aquarium dumping. The easy access to fish (especially the potential pest species through e-commerce and Orkut, together with the low total price (unitary value + shipping and handling ranging from US$ 17.67 to 30.39, and fast interstate delivery (two-four days on average confirm the widespread e

Bioremediation potential of crude oil spilled on soil

International Nuclear Information System (INIS)

McMillen, S.J.; Young, G.N.; Davis, P.S.; Cook, P.D.; Kerr, J.M.; Gray, N.R.; Requejo, A.G.

1995-01-01

Spills sometimes occur during routine operations associated with exploration and production (E and P) of crude oil. These spills at E and P sites typically are small, less than 1 acre (0.4 ha), and the spill may be in remote locations. As a result, bioremediation often represents a cost-effective alternative to other cleanup technologies. The goal of this study was to determine the potential for biodegrading a range of crude oil types and determining the effect of process variables such as soil texture and soil salinity. Crude oils evaluated ranged in American Petroleum institute (API) gravity from 14 degree to 45 degree. The extent of biodegradation was calculated from oxygen uptake data and the total extractable material (TEM) concentration. Based on the data collected, a simple model was developed for predicting the bioremediation potential of a range of crude oil types. Biodegradation rates were significantly lower in sandy soils. Soil salinities greater than approximately 40 mmhos/cm adversely impacted soil microbial activity and biodegradation rate

CircRNA-0004904, CircRNA-0001855, and PAPP-A: Potential Novel Biomarkers for the Prediction of Preeclampsia

Directory of Open Access Journals (Sweden)

Min Jiang

2018-05-01

Full Text Available Background/Aims: Circular RNAs (circRNAs are transcribed prevalently in the genome; however, their potential roles in multiple cardiovascular diseases, particularly preeclampsia (PE, are not yet well understood. This study investigated the expression profiles of circRNAs and explored circRNA-mediated pregnancy-associated plasma protein A (PAPP-A expression as a potential biomarker for PE before 20 weeks of pregnancy. Methods: A nested case-control two-phase screening/validation study was performed in pregnant women before 20 weeks of gestation (before clinical diagnosis at Guangzhou Women and Children’s Medical Center from 2012 to 2015. In the screening phase, circRNA expression profiles of blood cells were assessed using a human circRNA microarray, which was designed to detect simultaneously 5396 circRNAs, in 5 patients with PE and 5 age- and gestational week-matched controls. In the validation phase, 18 circRNAs in blood cells predicted by bioinformatics tools were validated by quantitative reverse transcription PCR in a cohort of 60 patients (PE and age-, gestational week-, and sample storage time-matched controls. Then, we examined the involvement of circRNAs in PE-related pathways via interactions with miRNAs by multiple bioinformatics approaches. Bioinformatics analysis predicted that hsa_circ_0004904 and hsa_circ_0001855 miRNA sponges directly target PAPP-A. PAPP-A was verified in the serum of the same cohort of patients using an enzyme-linked immunosorbent assay. Finally, we combined PAPP-A with circRNAs to create a novel preclinical diagnostic model for PE with logistic regression and evaluated the efficiency of this model with receiver operating curve analysis. Results: Volcano plot analysis using various parameters showed that circRNAs were differentially expressed among both groups (P < 0.01, fold change > 2. In the screening phase, we found that 2178 circRNAs were differentially expressed between the control and PE groups, in

BetaTPred: prediction of beta-TURNS in a protein using statistical algorithms.

Science.gov (United States)

Kaur, Harpreet; Raghava, G P S

2002-03-01

beta-turns play an important role from a structural and functional point of view. beta-turns are the most common type of non-repetitive structures in proteins and comprise on average, 25% of the residues. In the past numerous methods have been developed to predict beta-turns in a protein. Most of these prediction methods are based on statistical approaches. In order to utilize the full potential of these methods, there is a need to develop a web server. This paper describes a web server called BetaTPred, developed for predicting beta-TURNS in a protein from its amino acid sequence. BetaTPred allows the user to predict turns in a protein using existing statistical algorithms. It also allows to predict different types of beta-TURNS e.g. type I, I', II, II', VI, VIII and non-specific. This server assists the users in predicting the consensus beta-TURNS in a protein. The server is accessible from http://imtech.res.in/raghava/betatpred/