Sample Size Determination and Power Ryan, Thomas P., Jr; Ryan, Thomas P
Wiley series in probability and statistics,
2013, 2013-06-10, 2013-05-28
eBook
Odprti dostop
A comprehensive approach to sample size determination and power with applications for a variety of fields Sample Size Determination and Power features a modern introduction to the applicability of ...sample size determination and provides a variety of discussions on broad topics including epidemiology, microarrays, survival analysis and reliability, design of experiments, regression, and confidence intervals. The book distinctively merges applications from numerous fields such as statistics, biostatistics, the health sciences, and engineering in order to provide a complete introduction to the general statistical use of sample size determination. Advanced topics including multivariate analysis, clinical trials, and quality improvement are addressed, and in addition, the book provides considerable guidance on available software for sample size determination. Written by a well-known author who has extensively class-tested the material, Sample Size Determination and Power: * Highlights the applicability of sample size determination and provides extensive literature coverage * Presents a modern, general approach to relevant software to guide sample size determination including CATD (computer-aided trial design) * Addresses the use of sample size determination in grant proposals and provides up-to-date references for grant investigators An appealing reference book for scientific researchers in a variety of fields, such as statistics, biostatistics, the health sciences, mathematics, ecology, and geology, who use sampling and estimation methods in their work, Sample Size Determination and Power is also an ideal supplementary text for upper- level undergraduate and graduate-level courses in statistical sampling.
Strange or bad metallic transport, defined by incompatibility with the conventional quasiparticle picture, is a theme common to many strongly correlated materials, including high-temperature ...superconductors. The Hubbard model represents a minimal starting point for modeling strongly correlated systems. Here we demonstrate strange metallic transport in the doped two-dimensional Hubbard model using determinantal quantum Monte Carlo calculations. Over a wide range of doping, we observe resistivities exceeding the Mott-Ioffe-Regel limit with linear temperature dependence. The temperatures of our calculations extend to as low as 1/40 of the noninteracting bandwidth, placing our findings in the degenerate regime relevant to experimental observations of strange metallicity. Our results provide a foundation for connecting theories of strange metals to models of strongly correlated materials.
Domesticated maize evolved from wild teosinte under human influences in Mexico beginning around 9000 years before the present (yr B.P.), traversed Central America by ~7500 yr B.P., and spread into ...South America by ~6500 yr B.P. Landrace and archaeological maize genomes from South America suggest that the ancestral population to South American maize was brought out of the domestication center in Mexico and became isolated from the wild teosinte gene pool before traits of domesticated maize were fixed. Deeply structured lineages then evolved within South America out of this partially domesticated progenitor population. Genomic, linguistic, archaeological, and paleoecological data suggest that the southwestern Amazon was a secondary improvement center for partially domesticated maize. Multiple waves of human-mediated dispersal are responsible for the diversity and biogeography of modern South American maize.
Praise for the Second Edition "As a comprehensive statistics reference book for quality improvement, it certainly is one of the best books available." —Technometrics This new edition continues to ...provide the most current, proven statistical methods for quality control and quality improvement The use of quantitative methods offers numerous benefits in the fields of industry and business, both through identifying existing trouble spots and alerting management and technical personnel to potential problems. Statistical Methods for Quality Improvement, Third Edition guides readers through a broad range of tools and techniques that make it possible to quickly identify and resolve both current and potential trouble spots within almost any manufacturing or nonmanufacturing process. The book provides detailed coverage of the application of control charts, while also exploring critical topics such as regression, design of experiments, and Taguchi methods. In this new edition, the author continues to explain how to combine the many statistical methods explored in the book in order to optimize quality control and improvement. The book has been thoroughly revised and updated to reflect the latest research and practices in statistical methods and quality control, and new features include: Updated coverage of control charts, with newly added tools The latest research on the monitoring of linear profiles and other types of profiles Sections on generalized likelihood ratio charts and the effects of parameter estimation on the properties of CUSUM and EWMA procedures New discussions on design of experiments that include conditional effects and fraction of design space plots New material on Lean Six Sigma and Six Sigma programs and training Incorporating the latest software applications, the author has added coverage on how to use Minitab software to obtain probability limits for attribute charts. new exercises have been added throughout the book, allowing readers to put the latest statistical methods into practice. Updated references are also provided, shedding light on the current literature and providing resources for further study of the topic. Statistical Methods for Quality Improvement, Third Edition is an excellent book for courses on quality control and design of experiments at the upper-undergraduate and graduate levels. the book also serves as a valuable reference for practicing statisticians, engineers, and physical scientists interested in statistical quality improvement.
Autophagy is the primary cellular catabolic program activated in response to nutrient starvation. Initiation of autophagy, particularly by amino-acid withdrawal, requires the ULK kinases. Despite its ...pivotal role in autophagy initiation, little is known about the mechanisms by which ULK promotes autophagy. Here we describe a molecular mechanism linking ULK to the pro-autophagic lipid kinase VPS34. Following amino-acid starvation or mTOR inhibition, the activated ULK1 phosphorylates Beclin-1 on Ser 14, thereby enhancing the activity of the ATG14L-containing VPS34 complexes. The Beclin-1 Ser 14 phosphorylation by ULK is required for full autophagic induction in mammals and this requirement is conserved in Caenorhabditis elegans. Our study reveals a molecular link from ULK1 to activation of the autophagy-specific VPS34 complex and autophagy induction.
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Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Microstructural characterization and analysis is the foundation of microstructural science, connecting materials structure to composition, process history, and properties. Microstructural ...quantification traditionally involves a human deciding what to measure and then devising a method for doing so. However, recent advances in computer vision (CV) and machine learning (ML) offer new approaches for extracting information from microstructural images. This overview surveys CV methods for numerically encoding the visual information contained in a microstructural image using either feature-based representations or convolutional neural network (CNN) layers, which then provides input to supervised or unsupervised ML algorithms that find associations and trends in the high-dimensional image representation. CV/ML systems for microstructural characterization and analysis span the taxonomy of image analysis tasks, including image classification, semantic segmentation, object detection, and instance segmentation. These tools enable new approaches to microstructural analysis, including the development of new, rich visual metrics and the discovery of processing-microstructure-property relationships.
Molnupiravir, an antiviral medication widely used against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), acts by inducing mutations in the virus genome during replication. Most random ...mutations are likely to be deleterious to the virus and many will be lethal; thus, molnupiravir-induced elevated mutation rates reduce viral load
. However, if some patients treated with molnupiravir do not fully clear the SARS-CoV-2 infections, there could be the potential for onward transmission of molnupiravir-mutated viruses. Here we show that SARS-CoV-2 sequencing databases contain extensive evidence of molnupiravir mutagenesis. Using a systematic approach, we find that a specific class of long phylogenetic branches, distinguished by a high proportion of G-to-A and C-to-T mutations, are found almost exclusively in sequences from 2022, after the introduction of molnupiravir treatment, and in countries and age groups with widespread use of the drug. We identify a mutational spectrum, with preferred nucleotide contexts, from viruses in patients known to have been treated with molnupiravir and show that its signature matches that seen in these long branches, in some cases with onward transmission of molnupiravir-derived lineages. Finally, we analyse treatment records to confirm a direct association between these high G-to-A branches and the use of molnupiravir.
Developing fast, cost-effective assessments of wild animal abundance is an important goal for many researchers, and environmental DNA (eDNA) holds much promise for this purpose. However, the ...quantitative relationship between species abundance and the amount of DNA present in the environment is likely to vary substantially among taxa and with ecological context. Here, we report a strong quantitative relationship between eDNA concentration and the abundance of spawning sockeye salmon in a small stream in Alaska, USA, where we took temporally- and spatially-replicated samples during the spawning period. This high-resolution dataset suggests that (1) eDNA concentrations vary significantly day-to-day, and likely within hours, in the context of the dynamic biological event of a salmon spawning season; (2) eDNA, as detected by species-specific quantitative PCR probes, seems to be conserved over short distances (tens of meters) in running water, but degrade quickly over larger scales (ca. 1.5 km); and (3) factors other than the mere presence of live, individual fish — such as location within the stream, live/dead ratio, and water temperature — can affect the eDNA-biomass correlation in space or time. A multivariate model incorporating both biotic and abiotic variables accounted for over 75% of the eDNA variance observed, suggesting that where a system is well-characterized, it may be possible to predict species' abundance from eDNA surveys, although we underscore that species- and system-specific variables are likely to limit the generality of any given quantitative model. Nevertheless, these findings provide an important step toward quantitative applications of eDNA in conservation and management.
•We measured salmon DNA in water samples collected daily during the spawning season•This environmental DNA (eDNA) closely tracked the rise and fall of salmon numbers in the creek•Concentrations of eDNA changed over fine spatial and temporal scales•A statistical model including fish and environmental variables accounted for >75% of the variance in recovered salmon eDNA•Both dead and live fish shed DNA into the water, but model results suggest that the shedding rate is much greater after death
To survive starvation and other forms of stress, eukaryotic cells undergo a lysosomal process of cytoplasmic degradation known as autophagy. Autophagy has been implicated in a number of cellular and ...developmental processes, including cell-growth control and programmed cell death. However, direct evidence of a causal role for autophagy in these processes is lacking, resulting in part from the pleiotropic effects of signaling molecules such as TOR that regulate autophagy. Here, we circumvent this difficulty by directly manipulating autophagy rates in Drosophila through the autophagy-specific protein kinase Atg1.
We find that overexpression of Atg1 is sufficient to induce high levels of autophagy, the first such demonstration among wild-type Atg proteins. In contrast to findings in yeast, induction of autophagy by Atg1 is dependent on its kinase activity. We find that cells with high levels of Atg1-induced autophagy are rapidly eliminated, demonstrating that autophagy is capable of inducing cell death. However, this cell death is caspase dependent and displays DNA fragmentation, suggesting that autophagy represents an alternative induction of apoptosis, rather than a distinct form of cell death. In addition, we demonstrate that Atg1-induced autophagy strongly inhibits cell growth and that Atg1 mutant cells have a relative growth advantage under conditions of reduced TOR signaling. Finally, we show that Atg1 expression results in negative feedback on the activity of TOR itself.
Our results reveal a central role for Atg1 in mounting a coordinated autophagic response and demonstrate that autophagy has the capacity to induce cell death. Furthermore, this work identifies autophagy as a critical mechanism by which inhibition of TOR signaling leads to reduced cell growth.
The solution self-assembly of macromolecular amphiphiles offers an efficient, bottom-up strategy for producing well-defined nanocarriers, with applications ranging from drug delivery to nanoreactors. ...Typically, the generation of uniform nanocarrier architectures is controlled by processing methods that rely on cosolvent mixtures. These preparation strategies hinge on the assumption that macromolecular solution nanostructures are kinetically stable following transfer from an organic/aqueous cosolvent into aqueous solution. Herein we demonstrate that unequivocal step-change shifts in micelle populations occur over several weeks following transfer into a highly selective solvent. The unexpected micelle growth evolves through a distinct bimodal distribution separated by multiple fusion events and critically depends on solution agitation. Notably, these results underscore fundamental similarities between assembly processes in amphiphilic polymer, small molecule and protein systems. Moreover, the non-equilibrium micelle size increase can have a major impact on the assumed stability of solution assemblies, for which performance is dictated by nanocarrier size and structure.
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