827 research outputs found
Genetic Optimization Using Derivatives: The rgenoud Package for R
No full textgenoud is an R function that combines evolutionary algorithm methods with a derivative-based (quasi-Newton) method to solve difficult optimization problems. genoud may also be used for optimization problems for which derivatives do not exist. genoud solves problems that are nonlinear or perhaps even discontinuous in the parameters of the function to be optimized. When the function to be optimized (for example, a log-likelihood) is nonlinear in the model's parameters, the function will generally not be globally concave and may have irregularities such as saddlepoints or discontinuities. Optimization methods that rely on derivatives of the objective function may be unable to find any optimum at all. Multiple local optima may exist, so that there is no guarantee that a derivative-based method will converge to the global optimum. On the other hand, algorithms that do not use derivative information (such as pure genetic algorithms) are for many problems needlessly poor at local hill climbing. Most statistical problems are regular in a neighborhood of the solution. Therefore, for some portion of the search space, derivative information is useful. The function supports parallel processing on multiple CPUs on a single machine or a cluster of computers.
Multivariate and Propensity Score Matching Software with Automated Balance Optimization: The Matching package for R
No full textMatching is an R package which provides functions for multivariate and propensity score matching and for finding optimal covariate balance based on a genetic search algorithm. A variety of univariate and multivariate metrics to determine if balance actually has been obtained are provided. The underlying matching algorithm is written in C++, makes extensive use of system BLAS and scales efficiently with dataset size. The genetic algorithm which finds optimal balance is parallelized and can make use of multiple CPUs or a cluster of computers. A large number of options are provided which control exactly how the matching is conducted and how balance is evaluated.
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Homogeneous global mean temperature time series
No full textA multi-agency effort has been underway to create a homogeneous global baseline data set suitable for studying climate change. The joint release of the Global Historical Climatology Network (GHCN, Vose et al, 1992) version I in 1992 by the National Climatic Data Center/NOAA and the Carbon Dioxide Information Analysis Center/DOE gave the climate research community the largest monthly land surface global climate data set available to date with over 6,000 temperature stations, 39% of which have more than 50 years of data and 10% have more than 100 years of data (see Figure 1). Fifteen different global or regional data sets were merged to create GHCN version 1. Ten of these source data sets have temperature data but only two have been tested and adjusted for inhomogeneities in the station time series. The majority of the station temperature time series in GHCN have not been systematically examined for discontinuities
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The Global Climatology Network Precipitation data
No full textSeveral years ago, in response to growing concern about global climate change, the US National Climatic Data Center and the Carbon Dioxide Information Analysis Center undertook an effort to create a baseline global land surface climate data set called the Global Historical Climatology Network (GHCN, Vose et al., 1992). GHCN was created by merging several large existing climate data sets into one data base. Fifteen separate data sets went into the creation of the GHCN version 1.0. GHCN version 1.0 was released in 1992. It has 7,533 precipitation stations, but the number of stations varies with time. A slight majority (55%) have records in excess of 50 years, and a significant proportion (13%) have records in excess of 100 years. The longest period of record for any given station is 291 years (1697--1987 for Kew, United Kingdom)
A phase II multicenter study of troxacitabine in relapsed or refractory lymphoproliferative neoplasm or multiple myeloma
No full textOptions for patients with relapsed/refractory lymphoproliferative disorders and multiple myeloma are currently limited. Troxacitabine has shown promise in preclinical studies in a variety of malignancies; hence, the current study was conducted to evaluate the activity of troxacitabine in relapsed or refractory lymphoid malignancies. This was a phase II, open-label, multinational, multicenter study of patients with relapsed or refractory lymphoproliferative disorders or multiple myeloma. Thirty-four adults were enrolled in the study and received the study drug at either 5.4 mg/m2 (n=16) or 4.3 mg/m2 (n=18). The dose was decided in a phase I study, during which dose escalation was carried to reach a maximum tolerated dose with an acceptable toxicity profile. Two separate phase I studies were performed in Europe and the US. Troxacitabine was administered by intravenous infusion over 30 min daily for days 1-5 every 4 weeks. Treatment was continued to disease progression or until the subjects met criteria for withdrawal or unacceptable toxicities were evident as outlined in the protocol. Two patients had a partial response (PR) to treatment with troxacitabine to yield an overall response rate of 13%. There were no complete responses seen with the drug. Stable disease was achieved in 15 patients (44%). All patients had at least one treatment related adverse event, which led to six withdrawals from the study. Hematologic toxicity constituted the most common adverse events. Serious adverse effects were seen in 62% of patients. None of the 13 deaths were attributed directly to troxacitabine. As a single agent, troxacitabine has limited benefit in patients with advanced lymphoproliferative disorders or multiple myeloma. Future studies will be needed to address modified dosing according to emerging pharmacokinetic and pharmacodynamic data and combination therapy which may lead to improved clinical benefit for troxacitabine in hematologic malignancies
Gains of MYC locus and outcome in patients with diffuse large B-cell lymphoma treated with R-CHOP
No full textPeripheral T-cell lymphoma.
No full textPeripheral T-cell lymphomas (PTCLs) are a heterogeneous group of clinically aggressive diseases associated with poor outcome. Studies that focus specifically on PTCL are emerging, with the ultimate goal of improved understanding of disease biology and the development of more effective therapies. However, one of the difficulties in classifying and studying treatment options in clinical trials is the rarity of these subtypes. Various groups have developed lymphoma classifications over the years, including the World Health Organization, which updated its classification in 2008. This article briefly reviews the major lymphoma classification schema, highlights contributions made by the collaborative International PTCL Project, discusses prognostic issues and gene expression profiling, and outlines therapeutic approaches to PTCL. These include the standard chemotherapeutic regimens and other modalities incorporating antifolates, conjugates, histone deacetylase inhibitors, monoclonal antibodies, nucleoside analogs, proteasome inhibitors, and signaling inhibitors. As this review emphasizes, the problem has now evolved into an abundance of drugs and too few patients available to test them. Collaborative groups will aid in future efforts to find the best treatment strategies to improve the outcome for patients with PTCL
Gains of MYC locus and outcome in patients with diffuse large B-cell lymphoma treated with R-CHOP
No full textThe Twentieth Century Reanalysis Project
No full textThe Twentieth Century Reanalysis (20CR) project is an international effort to produce a comprehensive global atmospheric circulation dataset spanning the twentieth century, assimilating only surface pressure reports and using observed monthly sea-surface temperature and sea-ice distributions as boundary conditions. It is chiefly motivated by a need to provide an observational dataset with quantified uncertainties for validations of climate model simulations of the twentieth century on all time-scales, with emphasis on the statistics of daily weather. It uses an Ensemble Kalman Filter data assimilation method with background ‘first guess’ fields supplied by an ensemble of forecasts from a global numerical weather prediction model. This directly yields a global analysis every 6 hours as the most likely state of the atmosphere, and also an uncertainty estimate of that analysis.
The 20CR dataset provides the first estimates of global tropospheric variability, and of the dataset's time-varying quality, from 1871 to the present at 6-hourly temporal and 2° spatial resolutions. Intercomparisons with independent radiosonde data indicate that the reanalyses are generally of high quality. The quality in the extratropical Northern Hemisphere throughout the century is similar to that of current three-day operational NWP forecasts. Intercomparisons over the second half-century of these surface-based reanalyses with other reanalyses that also make use of upper-air and satellite data are equally encouraging.
It is anticipated that the 20CR dataset will be a valuable resource to the climate research community for both model validations and diagnostic studies. Some surprising results are already evident. For instance, the long-term trends of indices representing the North Atlantic Oscillation, the tropical Pacific Walker Circulation, and the Pacific–North American pattern are weak or non-existent over the full period of record. The long-term trends of zonally averaged precipitation minus evaporation also differ in character from those in climate model simulations of the twentieth century
annabellisa/PLANTPOPNET_genetics: PLANTPOPNET data and scripts v1.2
No full textDescription: R scripts for processing and analysing genetic and demographic data from Plantago lanceolata. Used in population genetics research by Annabel Smith and Yvonne Buckley, with the PLANTPOPNET network.
Author: Annabel Smith, except where indicated within the script.
Manuscript: Smith A.L., Hodkinson T.R., Villellas J., Catford J.A., Csergő A.M., Blomberg S.P., Crone E.E., Ehrlén J., Garcia M.B., Laine A.-L., Roach D.A., Salguero-Gómez R., Wardle G., Childs D.Z., Elderd B.D., Finn A., Munné-Bosch S., Baudraz M.E.A., Bódis J., Brearley F.Q., Bucharova A., Caruso C.M., Duncan R.P., Dwyer J.M., Gooden B., Groenteman R., Hamre L.N., Helm A., Kelly R., Laanisto L., Lonati M., Moore J.L., Morales M., Olsen S.L., Pärtel M., Petry W.K., Ramula S., Rasmussen P.U., Enri S.R., Roeder A., Roscher C., Saastamoinen M., Tack A.J.M., Töpper J.P., Vose G.E., Wandrag E.M., Wingler A. & Buckley Y.M. (2020). Global gene flow releases invasive plants from environmental constraints on genetic diversity. Proceedings of the National Academy of Sciences USA, www.pnas.org/cgi/doi/10.1073/pnas.1915848117
License: PLANTPOPNET genetics by Annabel Smith is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. Based on a work at https://github.com/annabellisa/PLANTPOPNET_genetics
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