96 research outputs found
Co-transformation of gpD-UBHA and gpV-CD40 expression plasmids into lysogens yields bi-functional phage displaying both peptide fusions
No full text<p><b>Copyright information:</b></p><p>Taken from "A tractable method for simultaneous modifications to the head and tail of bacteriophage lambda and its application to enhancing phage-mediated gene delivery"</p><p></p><p>Nucleic Acids Research 2007;35(8):e59-e59.</p><p>Published online 28 Mar 2007</p><p>PMCID:PMC1885665.</p><p>© 2007 The Author(s)</p> The plasmid pTrc:gpD-UBHA and the plasmid pTrcRSF:gpV-CD40 were co-transformed into lambda lysogens. After lytic induction, phage were purified by CsCl density gradient centrifugation and analyzed. () Phage (5 × 10 p.f.u.) were loaded on a 12% polyacrylamide gel, subjected to SDS-PAGE and transferred to nitrocellulose. Immunoblot analysis was then performed using an anti-gpD rabbit polyclonal antiserum. This revealed full replacement of gpD with gpD-UBHA in phage produced from lysogens carrying the pTrc:gpD-UBHA plasmid. The molecular weight of gpD is ∼12 kDa and of gpD-UBHA is ∼16 kDa. () Phage (5 × 10 p.f.u.) were loaded on a 12% polyacrylamide gel, subjected to SDS-PAGE and transferred to nitrocellulose. Immunoblot analysis was then performed with an anti-gpV polyclonal antiserum. This revealed that the phage expressing the gpV-CD40 fusion protein contained roughly a 1:1 ratio of wild-type gpV and recombinant gpV-CD40. The projected molecular weights are ∼30 kDa for wild type gpV and ∼27 kDa for recombinant gpV-CD40 (Note that the recombinant gpV fusion protein is based on a truncated form of gpV, and is therefore smaller than its wild-type counterpart)
Monotone trends in the distribution of climate extremes
No full textThe generalized Pareto distribution (GPD) is often used in the statistical analysis of climate extremes. For a sample of independent and identically distributed observations, the parameters of the GPD can be estimated by the maximum likelihood (ML) method. In this paper, we drop the assumption of identically distributed random variables. We consider independent observations from GPD distributions having a common shape parameter but possibly an increasing trend in the scale parameter. Such a model, with increasing scale parameter, can be used to describe a trend in the observed extremes as time progresses. Estimating an increasing trend in a distribution parameter is common in the field of isotonic regression. We use ideas and tools from that area to compute ML estimates of the GPD parameters. In a simulation experiment, we show that the iterative convex minorant (ICM) algorithm is much faster than the projected gradient (PG) algorithm. We apply the approach to the daily maxima of the central England temperature (CET) data. A clear positive trend in the GPD scale parameter is found, leading to an increase in the 100-year return level from about 31º in the 1880s to 34º in 2015.</p
Conversion of Lap-Band (R) to gastric bypass for dilated gastric pouch.
No full textAn 18-year-old female who had undergone a laparoscopic
adjustable gastic banding developed several
episodes of gastric pouch dilatation (GPD), treated
conservatively. The last GPD (31 months after Lap-
Band® placement) involved the lesser curvature of
the stomach and was refractory to medical treatment.
Conversion to an open gastric bypass was
performed. Gastric bypass is an option in the case of
Lap-Band® failure
Extreme-value Neural Networks for Weather Forecasting
No full textDeep-learning models are commonly used in short-term precipitation forecasting. However, most deep-learning models are likely to produce blurry output problems. In order to get realistic and accurate results, AENN, a variant of Generative Adversarial Networks (GANs), has been developed. The AENN implements an additional temporal discriminator to achieve better performance on sequential-data prediction. In this thesis, we explore the use of AENN to do nowcasting for the Netherlands and surrounding area based on radar echo images. We add a self-attention module to extract long-term global and self dependencies better. In order to improve the model’s ability to predict high rain intensity, we also apply Generalized Pareto Distribution (GPD) to normalize the tail data. The proposed model is compared with PySTEPS, a state-of-the-art statistical nowcasting model, and the original AENN model without GPD normalization. The experimental results show that AENN outperforms PySTEPS in terms of instantaneous radar echo prediction in the extreme-rain period and high accumulation detection in four Dutch catchments. GPD normalization can enhance the model’s detection ability in heavy rain. However, all models still have limited overall ability on high accumulation detection and long-range prediction.Electrical Engineering | Circuits and System
Evolutionary engineering of a glycerol-3-phosphate dehydrogenase-negative, acetate-reducing Saccharomyces cerevisiae strain enables anaerobic growth at high glucose concentrations
No full textGlycerol production by Saccharomyces cerevisiae, which is required for redox-cofactor balancing in anaerobic cultures, causes yield reduction in industrial bioethanol production. Recently, glycerol formation in anaerobic S.?cerevisiae cultures was eliminated by expressing Escherichia coli (acetylating) acetaldehyde dehydrogenase (encoded by mhpF) and simultaneously deleting the GPD1 and GPD2 genes encoding glycerol-3-phosphate dehydrogenase, thus coupling NADH reoxidation to reduction of acetate to ethanol. Gpd– strains are, however, sensitive to high sugar concentrations, which complicates industrial implementation of this metabolic engineering concept. In this study, laboratory evolution was used to improve osmotolerance of a Gpd– mhpF-expressing S.?cerevisiae strain. Serial batch cultivation at increasing osmotic pressure enabled isolation of an evolved strain that grew anaerobically at 1?M glucose, at a specific growth rate of 0.12?h?1. The evolved strain produced glycerol at low concentrations (0.64?±?0.33?g?l?1). However, these glycerol concentrations were below 10% of those observed with a Gpd+ reference strain. Consequently, the ethanol yield on sugar increased from 79% of the theoretical maximum in the reference strain to 92% for the evolved strains. Genetic analysis indicated that osmotolerance under aerobic conditions required a single dominant chromosomal mutation, and one further mutation in the plasmid-borne mhpF gene for anaerobic growth.BT/BiotechnologyApplied Science
Principles of Macroeconomics 2e support material for OpenStax textbook: week 3, chapter 7 - OER project materials
No full textMissing weeks are exam review weeks. There is a discussion prompt but no recitation material for week 4 (exam review).ECON 204.Week 3 discussion: GPD growth (chapter 7). The material included here was developed to support the use of the OpenStax textbook Principles of Macroeconomics 2e. The material includes two components: (1) weekly discussion prompts that were developed for use on online discussion boards; and (2) weekly recitation worksheets and answer keys.Please see online textbook: https://openstax.org/details/books/principles-macroeconomics-2e.The materials were collected for the OER project funded by the Colorado OER Council Grant (AY 2021)
Issues in the GPD Formulation of DVCS
No full textThe kinematics used in computing deeply virtual Compton scattering makes a dramatic difference in terms of the widely used reduced operators that define generalized parton distributions. We analyze this difference at tree-level. © 2010 The Author(s)
Exclusive J/psi Process Tamed to Probe the Low-x Gluon
No full textWe address the question as to whether data for J/ψ mesons produced exclusively in the forward direction at the LHC can be used in global parton analyses (based on collinear factorization) to pin down the low-x gluon PDF. We show that it may be possible to overcome the problems that (i) the process is described by a skewed or Generalized Parton Distribution (GPD), (ii) it is very sensitive to the choice of factorization scale and (iii) there is bad LO, NLO,⋯ perturbative stability to the predictions. However, we start by briefly explaining how the alternative kT-factorization approach has been used to describe the process
A regional peaks-over-threshold model in a nonstationary climate
No full textRegional frequency analysis is often used to reduce the uncertainty in the estimation of distribution parameters and quantiles. In this paper a regional peaks-over-threshold model is introduced that can be used to analyze precipitation extremes in a changing climate. We use a temporally varying threshold, which is determined by quantile regression for each site separately. The marginal distributions of the excesses are described by generalized Pareto distributions (GPD). The parameters of these distributions may vary over time and their spatial variation is modeled by the index flood (IF) approach. We consider different models for the temporal dependence of the GPD parameters. Parameter estimation is based on the framework of composite likelihood. Composite likelihood ratio tests that account for spatial dependence are used to test the significance of temporal trends in the model parameters and to test the IF assumption. We apply the method to gridded, observed daily precipitation data from the Netherlands for the winter season. A general increase of the threshold is observed, especially along the west coast and northern parts of the country. Moreover, there is no indication that the ratio between the GPD scale parameter and the threshold has changed over time, which implies that the scale parameter increases by the same percentage as the threshold. These positive trends lead to an increase of rare extremes of on average 22% over the country during the observed period.Delft Institute of Applied MathematicsElectrical Engineering, Mathematics and Computer Scienc
全球暖化影響之下日降水與極端降水事件變化之探討
No full text[[abstract]]Weather and climate events can have serious and damaging effects on human society (such as flood, heavy precipitation, heat wave, etc.). In this study, the simulation of the variability and extremes of daily rainfall for the present and the future climate is investigated. This is done by the ECHAM4/OPYC3 GSDIO for the period 1960-1990 and the Special Report on Emission Scenarios (SRES) A2 (rapid CO2 increase) and B2 (moderate CO2 increase) forcing scenario for the period of 2070-2100. Moreover, observational rainfall data from the Global Precipitation Climatology Project (GPCP, 1996-2004) is considered. In general, analysis of model data revealed agreement with observations. For the future, the ECHAM4/OPYC3 simulates the variability of the daily rainfall predicts the most pronounced precipitation changes are found in high latitudes of the Northern Hemisphere for the winter. However for some continental areas, the change of mean precipitation and rainfall intensity is not coincident. A clear reduction in the probability of wet day, in particular, for the large areas in the northern mid-latitudes and subtropics. Despite this decrease the relative contribution of heavy precipitation has grown due to the corresponding increase of the scale parameter of the gamma distribution. This implies a more extreme climate with higher probabilities of droughts and heavy precipitation events. Furthermore, the variability of the 99.7th percentile also implies in the area of heavy precipitation, stronger heavy rainfall will happen in the future, vice versa. Extreme value theory based on GEV and GPD provides a much more complete analysis of the statistical distribution of extreme rainfall event. We have obtained statistically significant spatial models of the three parameters of GEV and GPD. N-years return level form GEV or GPD all show the relative changes in extreme precipitation is larger than change in total precipitation.
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