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Learning Semiparametric Regression with Missing Covariates Using Gaussian Process Models

Abhishek Bishoyi, Xiaojing Wang, Dipak K. Dey.

Source: Bayesian Analysis, Volume 15, Number 1, 215--239.

Abstract:
Missing data often appear as a practical problem while applying classical models in the statistical analysis. In this paper, we consider a semiparametric regression model in the presence of missing covariates for nonparametric components under a Bayesian framework. As it is known that Gaussian processes are a popular tool in nonparametric regression because of their flexibility and the fact that much of the ensuing computation is parametric Gaussian computation. However, in the absence of covariates, the most frequently used covariance functions of a Gaussian process will not be well defined. We propose an imputation method to solve this issue and perform our analysis using Bayesian inference, where we specify the objective priors on the parameters of Gaussian process models. Several simulations are conducted to illustrate effectiveness of our proposed method and further, our method is exemplified via two real datasets, one through Langmuir equation, commonly used in pharmacokinetic models, and another through Auto-mpg data taken from the StatLib library.




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Adaptive Bayesian Nonparametric Regression Using a Kernel Mixture of Polynomials with Application to Partial Linear Models

Fangzheng Xie, Yanxun Xu.

Source: Bayesian Analysis, Volume 15, Number 1, 159--186.

Abstract:
We propose a kernel mixture of polynomials prior for Bayesian nonparametric regression. The regression function is modeled by local averages of polynomials with kernel mixture weights. We obtain the minimax-optimal contraction rate of the full posterior distribution up to a logarithmic factor by estimating metric entropies of certain function classes. Under the assumption that the degree of the polynomials is larger than the unknown smoothness level of the true function, the posterior contraction behavior can adapt to this smoothness level provided an upper bound is known. We also provide a frequentist sieve maximum likelihood estimator with a near-optimal convergence rate. We further investigate the application of the kernel mixture of polynomials to partial linear models and obtain both the near-optimal rate of contraction for the nonparametric component and the Bernstein-von Mises limit (i.e., asymptotic normality) of the parametric component. The proposed method is illustrated with numerical examples and shows superior performance in terms of computational efficiency, accuracy, and uncertainty quantification compared to the local polynomial regression, DiceKriging, and the robust Gaussian stochastic process.




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Latent Nested Nonparametric Priors (with Discussion)

Federico Camerlenghi, David B. Dunson, Antonio Lijoi, Igor Prünster, Abel Rodríguez.

Source: Bayesian Analysis, Volume 14, Number 4, 1303--1356.

Abstract:
Discrete random structures are important tools in Bayesian nonparametrics and the resulting models have proven effective in density estimation, clustering, topic modeling and prediction, among others. In this paper, we consider nested processes and study the dependence structures they induce. Dependence ranges between homogeneity, corresponding to full exchangeability, and maximum heterogeneity, corresponding to (unconditional) independence across samples. The popular nested Dirichlet process is shown to degenerate to the fully exchangeable case when there are ties across samples at the observed or latent level. To overcome this drawback, inherent to nesting general discrete random measures, we introduce a novel class of latent nested processes. These are obtained by adding common and group-specific completely random measures and, then, normalizing to yield dependent random probability measures. We provide results on the partition distributions induced by latent nested processes, and develop a Markov Chain Monte Carlo sampler for Bayesian inferences. A test for distributional homogeneity across groups is obtained as a by-product. The results and their inferential implications are showcased on synthetic and real data.




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Beyond Whittle: Nonparametric Correction of a Parametric Likelihood with a Focus on Bayesian Time Series Analysis

Claudia Kirch, Matthew C. Edwards, Alexander Meier, Renate Meyer.

Source: Bayesian Analysis, Volume 14, Number 4, 1037--1073.

Abstract:
Nonparametric Bayesian inference has seen a rapid growth over the last decade but only few nonparametric Bayesian approaches to time series analysis have been developed. Most existing approaches use Whittle’s likelihood for Bayesian modelling of the spectral density as the main nonparametric characteristic of stationary time series. It is known that the loss of efficiency using Whittle’s likelihood can be substantial. On the other hand, parametric methods are more powerful than nonparametric methods if the observed time series is close to the considered model class but fail if the model is misspecified. Therefore, we suggest a nonparametric correction of a parametric likelihood that takes advantage of the efficiency of parametric models while mitigating sensitivities through a nonparametric amendment. We use a nonparametric Bernstein polynomial prior on the spectral density with weights induced by a Dirichlet process and prove posterior consistency for Gaussian stationary time series. Bayesian posterior computations are implemented via an MH-within-Gibbs sampler and the performance of the nonparametrically corrected likelihood for Gaussian time series is illustrated in a simulation study and in three astronomy applications, including estimating the spectral density of gravitational wave data from the Advanced Laser Interferometer Gravitational-wave Observatory (LIGO).




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Semiparametric Multivariate and Multiple Change-Point Modeling

Stefano Peluso, Siddhartha Chib, Antonietta Mira.

Source: Bayesian Analysis, Volume 14, Number 3, 727--751.

Abstract:
We develop a general Bayesian semiparametric change-point model in which separate groups of structural parameters (for example, location and dispersion parameters) can each follow a separate multiple change-point process, driven by time-dependent transition matrices among the latent regimes. The distribution of the observations within regimes is unknown and given by a Dirichlet process mixture prior. The properties of the proposed model are studied theoretically through the analysis of inter-arrival times and of the number of change-points in a given time interval. The prior-posterior analysis by Markov chain Monte Carlo techniques is developed on a forward-backward algorithm for sampling the various regime indicators. Analysis with simulated data under various scenarios and an application to short-term interest rates are used to show the generality and usefulness of the proposed model.




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A Bayesian Nonparametric Multiple Testing Procedure for Comparing Several Treatments Against a Control

Luis Gutiérrez, Andrés F. Barrientos, Jorge González, Daniel Taylor-Rodríguez.

Source: Bayesian Analysis, Volume 14, Number 2, 649--675.

Abstract:
We propose a Bayesian nonparametric strategy to test for differences between a control group and several treatment regimes. Most of the existing tests for this type of comparison are based on the differences between location parameters. In contrast, our approach identifies differences across the entire distribution, avoids strong modeling assumptions over the distributions for each treatment, and accounts for multiple testing through the prior distribution on the space of hypotheses. The proposal is compared to other commonly used hypothesis testing procedures under simulated scenarios. Two real applications are also analyzed with the proposed methodology.




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A Bayesian Nonparametric Spiked Process Prior for Dynamic Model Selection

Alberto Cassese, Weixuan Zhu, Michele Guindani, Marina Vannucci.

Source: Bayesian Analysis, Volume 14, Number 2, 553--572.

Abstract:
In many applications, investigators monitor processes that vary in space and time, with the goal of identifying temporally persistent and spatially localized departures from a baseline or “normal” behavior. In this manuscript, we consider the monitoring of pneumonia and influenza (P&I) mortality, to detect influenza outbreaks in the continental United States, and propose a Bayesian nonparametric model selection approach to take into account the spatio-temporal dependence of outbreaks. More specifically, we introduce a zero-inflated conditionally identically distributed species sampling prior which allows borrowing information across time and to assign data to clusters associated to either a null or an alternate process. Spatial dependences are accounted for by means of a Markov random field prior, which allows to inform the selection based on inferences conducted at nearby locations. We show how the proposed modeling framework performs in an application to the P&I mortality data and in a simulation study, and compare with common threshold methods for detecting outbreaks over time, with more recent Markov switching based models, and with spike-and-slab Bayesian nonparametric priors that do not take into account spatio-temporal dependence.




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Separable covariance arrays via the Tucker product, with applications to multivariate relational data

Peter D. Hoff

Source: Bayesian Anal., Volume 6, Number 2, 179--196.

Abstract:
Modern datasets are often in the form of matrices or arrays, potentially having correlations along each set of data indices. For example, data involving repeated measurements of several variables over time may exhibit temporal correlation as well as correlation among the variables. A possible model for matrix-valued data is the class of matrix normal distributions, which is parametrized by two covariance matrices, one for each index set of the data. In this article we discuss an extension of the matrix normal model to accommodate multidimensional data arrays, or tensors. We show how a particular array-matrix product can be used to generate the class of array normal distributions having separable covariance structure. We derive some properties of these covariance structures and the corresponding array normal distributions, and show how the array-matrix product can be used to define a semi-conjugate prior distribution and calculate the corresponding posterior distribution. We illustrate the methodology in an analysis of multivariate longitudinal network data which take the form of a four-way array.




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A Tale of Two Parasites: Statistical Modelling to Support Disease Control Programmes in Africa

Peter J. Diggle, Emanuele Giorgi, Julienne Atsame, Sylvie Ntsame Ella, Kisito Ogoussan, Katherine Gass.

Source: Statistical Science, Volume 35, Number 1, 42--50.

Abstract:
Vector-borne diseases have long presented major challenges to the health of rural communities in the wet tropical regions of the world, but especially in sub-Saharan Africa. In this paper, we describe the contribution that statistical modelling has made to the global elimination programme for one vector-borne disease, onchocerciasis. We explain why information on the spatial distribution of a second vector-borne disease, Loa loa, is needed before communities at high risk of onchocerciasis can be treated safely with mass distribution of ivermectin, an antifiarial medication. We show how a model-based geostatistical analysis of Loa loa prevalence survey data can be used to map the predictive probability that each location in the region of interest meets a WHO policy guideline for safe mass distribution of ivermectin and describe two applications: one is to data from Cameroon that assesses prevalence using traditional blood-smear microscopy; the other is to Africa-wide data that uses a low-cost questionnaire-based method. We describe how a recent technological development in image-based microscopy has resulted in a change of emphasis from prevalence alone to the bivariate spatial distribution of prevalence and the intensity of infection among infected individuals. We discuss how statistical modelling of the kind described here can contribute to health policy guidelines and decision-making in two ways. One is to ensure that, in a resource-limited setting, prevalence surveys are designed, and the resulting data analysed, as efficiently as possible. The other is to provide an honest quantification of the uncertainty attached to any binary decision by reporting predictive probabilities that a policy-defined condition for action is or is not met.




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Larry Brown’s Contributions to Parametric Inference, Decision Theory and Foundations: A Survey

James O. Berger, Anirban DasGupta.

Source: Statistical Science, Volume 34, Number 4, 621--634.

Abstract:
This article gives a panoramic survey of the general area of parametric statistical inference, decision theory and foundations of statistics for the period 1965–2010 through the lens of Larry Brown’s contributions to varied aspects of this massive area. The article goes over sufficiency, shrinkage estimation, admissibility, minimaxity, complete class theorems, estimated confidence, conditional confidence procedures, Edgeworth and higher order asymptotic expansions, variational Bayes, Stein’s SURE, differential inequalities, geometrization of convergence rates, asymptotic equivalence, aspects of empirical process theory, inference after model selection, unified frequentist and Bayesian testing, and Wald’s sequential theory. A reasonably comprehensive bibliography is provided.




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Models as Approximations II: A Model-Free Theory of Parametric Regression

Andreas Buja, Lawrence Brown, Arun Kumar Kuchibhotla, Richard Berk, Edward George, Linda Zhao.

Source: Statistical Science, Volume 34, Number 4, 545--565.

Abstract:
We develop a model-free theory of general types of parametric regression for i.i.d. observations. The theory replaces the parameters of parametric models with statistical functionals, to be called “regression functionals,” defined on large nonparametric classes of joint ${x extrm{-}y}$ distributions, without assuming a correct model. Parametric models are reduced to heuristics to suggest plausible objective functions. An example of a regression functional is the vector of slopes of linear equations fitted by OLS to largely arbitrary ${x extrm{-}y}$ distributions, without assuming a linear model (see Part I). More generally, regression functionals can be defined by minimizing objective functions, solving estimating equations, or with ad hoc constructions. In this framework, it is possible to achieve the following: (1) define a notion of “well-specification” for regression functionals that replaces the notion of correct specification of models, (2) propose a well-specification diagnostic for regression functionals based on reweighting distributions and data, (3) decompose sampling variability of regression functionals into two sources, one due to the conditional response distribution and another due to the regressor distribution interacting with misspecification, both of order $N^{-1/2}$, (4) exhibit plug-in/sandwich estimators of standard error as limit cases of ${x extrm{-}y}$ bootstrap estimators, and (5) provide theoretical heuristics to indicate that ${x extrm{-}y}$ bootstrap standard errors may generally be preferred over sandwich estimators.




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An Overview of Semiparametric Extensions of Finite Mixture Models

Sijia Xiang, Weixin Yao, Guangren Yang.

Source: Statistical Science, Volume 34, Number 3, 391--404.

Abstract:
Finite mixture models have offered a very important tool for exploring complex data structures in many scientific areas, such as economics, epidemiology and finance. Semiparametric mixture models, which were introduced into traditional finite mixture models in the past decade, have brought forth exciting developments in their methodologies, theories, and applications. In this article, we not only provide a selective overview of the newly-developed semiparametric mixture models, but also discuss their estimation methodologies, theoretical properties if applicable, and some open questions. Recent developments are also discussed.




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Gut Microbes and the Brain: Paradigm Shift in Neuroscience

Emeran A. Mayer
Nov 12, 2014; 34:15490-15496
Symposium




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Rassegna trimestrale BRI dicembre 2017: Un paradossale inasprimento ci riporta all'enigma del mercato obbligazionario

Italian translation of the BIS press release about the BIS Quarterly Review, December 2017




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Aprovechar el momento para lograr un crecimiento sostenido

Spanish translation of the BIS press release on the presentation of the Annual Economic Report 2018, 24 June 2018. Las autoridades pueden prolongar el actual repunte económico más allá del corto plazo aplicando reformas estructurales, reconstruyendo el espacio de las políticas monetaria y fiscal para afrontar futuras amenazas y fomentando una pronta implementación de las reformas reguladoras, sostiene el Banco de Pagos Internacionales (BPI) en su Informe Económico Anual. ...




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El Comité de Basilea finaliza sus principios sobre pruebas de tensión, analiza fórmulas para acabar con prácticas de arbitraje regulatorio, aprueba la lista anual de G-SIB y debate sobre el coeficiente de apalancamiento, los criptoacti

Spanish translation of press release - the Basel Committee on Banking Supervision is finalising stress-testing principles, reviews ways to stop regulatory arbitrage behaviour, agrees on annual G-SIB list, discusses leverage ratio, crypto-assets, market risk framework and implementation, 20 September 2018.




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Requisitos de divulgación para el Tercer Pilar - Macro actualizado

Spanish translation of "Pillar 3 disclosure requirements - updated framework", December 2018




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Comparative Transcriptomic Analyses of Developing Melanocortin Neurons Reveal New Regulators for the Anorexigenic Neuron Identity

Despite their opposing actions on food intake, POMC and NPY/AgRP neurons in the arcuate nucleus of the hypothalamus (ARH) are derived from the same progenitors that give rise to ARH neurons. However, the mechanism whereby common neuronal precursors subsequently adopt either the anorexigenic (POMC) or the orexigenic (NPY/AgRP) identity remains elusive. We hypothesize that POMC and NPY/AgRP cell fates are specified and maintained by distinct intrinsic factors. In search of them, we profiled the transcriptomes of developing POMC and NPY/AgRP neurons in mice. Moreover, cell-type-specific transcriptomic analyses revealed transcription regulators that are selectively enriched in either population, but whose developmental functions are unknown in these neurons. Among them, we found the expression of the PR domain-containing factor 12 (Prdm12) was enriched in POMC neurons but absent in NPY/AgRP neurons. To study the role of Prdm12 in vivo, we developed and characterized a floxed Prdm12 allele. Selective ablation of Prdm12 in embryonic POMC neurons led to significantly reduced Pomc expression as well as early-onset obesity in mice of either sex that recapitulates symptoms of human POMC deficiency. Interestingly, however, specific deletion of Prdm12 in adult POMC neurons showed that it is no longer required for Pomc expression or energy balance. Collectively, these findings establish a critical role for Prdm12 in the anorexigenic neuron identity and suggest that it acts developmentally to program body weight homeostasis. Finally, the combination of cell-type-specific genomic and genetic analyses provides a means to dissect cellular and functional diversity in the hypothalamus whose neurodevelopment remains poorly studied.

SIGNIFICANCE STATEMENT POMC and NPY/AgRP neurons are derived from the same hypothalamic progenitors but have opposing effects on food intake. We profiled the transcriptomes of genetically labeled POMC and NPY/AgRP neurons in the developing mouse hypothalamus to decipher the transcriptional codes behind the versus orexigenic neuron identity. Our analyses revealed 29 transcription regulators that are selectively enriched in one of the two populations. We generated new mouse genetic models to selective ablate one of POMC-neuron enriched transcription factors Prdm12 in developing and adult POMC neurons. Our studies establish a previously unrecognized role for Prdm12 in the anorexigenic neuron identity and suggest that it acts developmentally to program body weight homeostasis.




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Pattern Separation Underpins Expectation-Modulated Memory

Pattern separation and completion are fundamental hippocampal computations supporting memory encoding and retrieval. However, despite extensive exploration of these processes, it remains unclear whether and how top-down processes adaptively modulate the dynamics between these computations. Here we examine the role of expectation in shifting the hippocampus to perform pattern separation. In a behavioral task, 29 participants (7 males) learned a cue-object category contingency. Then, at encoding, one-third of the cues preceding the to-be-memorized objects, violated the studied rule. At test, participants performed a recognition task with old objects (targets) and a set of parametrically manipulated (very similar to dissimilar) foils for each object. Accuracy was found to be better for foils of high similarity to targets that were contextually unexpected at encoding compared with expected ones. Critically, there were no expectation-driven differences for targets and low similarity foils. To further explore these effects, we implemented a computational model of the hippocampus, performing the same task as the human participants. We used representational similarity analysis to examine how top-down expectation interacts with bottom-up perceptual input, in each layer. All subfields showed more dissimilar representations for unexpected items, with dentate gyrus (DG) and CA3 being more sensitive to expectation violation than CA1. Again, representational differences between expected and unexpected inputs were prominent for moderate to high levels of input similarity. This effect diminished when inputs from DG and CA3 into CA1 were lesioned. Overall, these novel findings strongly suggest that pattern separation in DG/CA3 underlies the effect that violation of expectation exerts on memory.

SIGNIFICANCE STATEMENT What makes some events more memorable than others is a key question in cognitive neuroscience. Violation of expectation often leads to better memory performance, but the neural mechanism underlying this benefit remains elusive. In a behavioral study, we found that memory accuracy is enhanced selectively for unexpected highly similar foils, suggesting expectation violation does not enhance memory indiscriminately, but specifically aids the disambiguation of overlapping inputs. This is further supported by our subsequent investigation using a hippocampal computational model, revealing increased representational dissimilarity for unexpected highly similar foils in DG and CA3. These convergent results provide the first evidence that pattern separation plays an explicit role in supporting memory for unexpected information.




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An Amygdalo-Parabrachial Pathway Regulates Pain Perception and Chronic Pain

The parabrachial (PB) complex mediates both ascending nociceptive signaling and descending pain modulatory information in the affective/emotional pain pathway. We have recently reported that chronic pain is associated with amplified activity of PB neurons in a rat model of neuropathic pain. Here we demonstrate that similar activity amplification occurs in mice, and that this is related to suppressed inhibition to lateral parabrachial (LPB) neurons from the CeA in animals of either sex. Animals with pain after chronic constriction injury of the infraorbital nerve (CCI-Pain) displayed higher spontaneous and evoked activity in PB neurons, and a dramatic increase in after-discharges, responses that far outlast the stimulus, compared with controls. LPB neurons in CCI-Pain animals showed a reduction in inhibitory, GABAergic inputs. We show that, in both rats and mice, LPB contains few GABAergic neurons, and that most of its GABAergic inputs arise from CeA. These CeA GABA neurons express dynorphin, somatostatin, and/or corticotropin releasing hormone. We find that the efficacy of this CeA-LPB pathway is suppressed in chronic pain. Further, optogenetically stimulating this pathway suppresses acute pain, and inhibiting it, in naive animals, evokes pain behaviors. These findings demonstrate that the CeA-LPB pathway is critically involved in pain regulation, and in the pathogenesis of chronic pain.

SIGNIFICANCE STATEMENT We describe a novel pathway, consisting of inhibition by dynorphin, somatostatin, and corticotropin-releasing hormone-expressing neurons in the CeA that project to the parabrachial nucleus. We show that this pathway regulates the activity of pain-related neurons in parabrachial nucleus, and that, in chronic pain, this inhibitory pathway is suppressed, and that this suppression is causally related to pain perception. We propose that this amygdalo-parabrachial pathway is a key regulator of both chronic and acute pain, and a novel target for pain relief.




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Impairment of Pattern Separation of Ambiguous Scenes by Single Units in the CA3 in the Absence of the Dentate Gyrus

Theoretical models and experimental evidence have suggested that connections from the dentate gyrus (DG) to CA3 play important roles in representing orthogonal information (i.e., pattern separation) in the hippocampus. However, the effects of eliminating the DG on neural firing patterns in the CA3 have rarely been tested in a goal-directed memory task that requires both the DG and CA3. In this study, selective lesions in the DG were made using colchicine in male Long–Evans rats, and single units from the CA3 were recorded as the rats performed visual scene memory tasks. The original scenes used in training were altered during testing by blurring to varying degrees or by using visual masks, resulting in maximal recruitment of the DG–CA3 circuits. Compared with controls, the performance of rats with DG lesions was particularly impaired when blurred scenes were used in the task. In addition, the firing rate modulation associated with visual scenes in these rats was significantly reduced in the single units recorded from the CA3 when ambiguous scenes were presented, largely because DG-deprived CA3 cells did not show stepwise, categorical rate changes across varying degrees of scene ambiguity compared with controls. These findings suggest that the DG plays key roles not only during the acquisition of scene memories but also during retrieval when modified visual scenes are processed in conjunction with the CA3 by making the CA3 network respond orthogonally to ambiguous scenes.

SIGNIFICANCE STATEMENT Despite the behavioral evidence supporting the role of the dentate gyrus in pattern separation in the hippocampus, the underlying neural mechanisms are largely unknown. By recording single units from the CA3 in DG-lesioned rats performing a visual scene memory task, we report that the scene-related modulation of neural firing was significantly reduced in the DG-lesion rats compared with controls, especially when the original scene stimuli were ambiguously altered. Our findings suggest that the dentate gyrus plays an essential role during memory retrieval and performs a critical computation to make categorical rate modulation occur in the CA3 between different scenes, especially when ambiguity is present in the environment.




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This Parasitic Worm Is Thriving in Nature, but May Affect Your Sushi Dinner

The worms are 283-times more abundant than they were in the 1970s, which might be a sign of healthy marine ecosystems




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Comment on Paramore go for a million-strong audience by Renata Diva

<span class="topsy_trackback_comment"><span class="topsy_twitter_username"><span class="topsy_trackback_content">Paramore go for a million-strong audience | RSS Feeds – IMC OnAir ...: Paramore recently re... http://bit.ly/dFBiD4 ParamoreForIndonesia</span></span>




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Comment on Paramore go for a million-strong audience by Fashion Style Trends

<span class="topsy_trackback_comment"><span class="topsy_twitter_username"><span class="topsy_trackback_content">Paramore go for a million-strong audience | RSS Feeds – IMC OnAir ...: Paramore recently re... http://bit.ly/dFBiD4 ParamoreForIndonesia</span></span>




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Enrichment of Fully Packaged Virions in Column-Purified Recombinant Adeno-Associated Virus (rAAV) Preparations by Iodixanol Gradient Centrifugation Followed by Anion-Exchange Column Chromatography

This rapid and efficient method to prepare highly purified recombinant adeno-associated viruses (rAAVs) is based on binding of negatively charged rAAV capsids to an anion-exchange resin that is pH dependent.




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Two-Step Bacterial Artificial Chromosome (BAC) Engineering: Preparation and Verification of the Recombinant Shuttle Vector

Plasmid DNA is prepared from the recombinant shuttle vector pLD53.SCAB/A-B created by cloning of the A and B homology arms for two-step bacterial artificial chromosome (BAC) engineering. To confirm that the A-box and B-box arms have been successfully incorporated into pLD53.SCAB, the pattern of enzyme digestion of the modified plasmid is compared with that of the unmodified pLD53.SCAB. Once the shuttle vector is shown to carry the proper sequences, it is ready for transfer into the BAC host.




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Two-Step Bacterial Artificial Chromosome (BAC) Engineering: Preparation of the A Homology Arm (A-Box) and B Homology Arm (B-Box)

The 700-bp A homology arm (A-box) and the 700-bp B homology arm (B-box) are amplified by polymerase chain reaction (PCR) using purified bacterial artificial chromosome (BAC) DNA as template for two-step BAC engineering. The resulting A-box PCR product contains an AscI site at its 5' end (the 5' primer incorporates an AscI site, and the 3' primer does not incorporate any restriction sites). The B-box PCR product contains an XmaI site at its 3' end (the 5' primer does not incorporate any restriction sites, and the 3' primer incorporates an XmaI site). The amplification products are then digested with the appropriate restriction endonucleases to render them suitable for cloning into the shuttle vector.




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Two-Step Bacterial Artificial Chromosome (BAC) Engineering: Preparation of Shuttle Vector DNA

In two-step bacterial artificial chromosome (BAC) engineering, a single plasmid is introduced into the BAC-carrying cell lines. The shuttle vector pLD53.SCAB (or pLD53.SCAEB) carries the recA gene and the R6K origin, which requires the protein to replicate. PIR2 cells, expressing , are typically used for the amplification of the vector and maintain about 15 copies/cell of the donor vector, which is relatively stable in this host.




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The Economic Stimulus/Relief-Debt Paradox

Long-term interest rates have remained low despite a surge in the issuance of sovereign debt to mitigate the economic impact of the pandemic.




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Retired goalkeeper Karina LeBlanc 'stronger' following separation from newborn daughter

Karina LeBlanc was returning home from her second hospital visit after giving birth to her first child, only this time she would have to spend 14 days in self-isolation after doctors feared she contracted COVID-19 during her stay.




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Why birthday parades are OK but garage sales are not during COVID-19

As part of the province's approach to curbing the COVID-19 pandemic, there are a number of rules in place that people have to follow. Kitchener and Waterloo bylaw officials offer some insight on what's allowed and what's not.



  • News/Canada/Kitchener-Waterloo

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2020 NHL draft: Teams to lean heavily on preparatory work from earlier in season

A normal draft year would see NHL scouts and executives spend the spring crisscrossing Europe and North America collecting information. The circumstances surrounding a 2020 draft and the COVID-19 pandemic, however, aren't anything resembling normal.



  • Sports/Hockey/NHL

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Two cases of COVID-19 at separate meat processing plants operated by Sofina Foods

Sofina Foods plants in Burlington and Mississauga have each had an employee test positive.



  • News/Canada/Hamilton

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The Economic Stimulus/Relief-Debt Paradox

Long-term interest rates have remained low despite a surge in the issuance of sovereign debt to mitigate the economic impact of the pandemic.




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America’s Parasite

Frankly, Trump doesn’t give a damn.




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OTC IRS BRL and MXN Liquidity Parameter Changes - Effective April 29, 2020

CME will be updating liquidity parameters for Interest Rate Swap contracts denominated in BRL and MXN. These changes only impact portfolios with larger BRL or MXN exposures. For MXN, the impact to liquidity add-on is approx. 5-10% for portfolios with aggregated DV01 above 100M+ DV01 in local currency. For BRL, the impact to liquidity add-on is 30%+ for portfolios with aggregated DV01 above 10M+ in local currency. Based on current exposures, CME Clearing expects that there will be no impact to existing portfolios at this time. These changes will be available for testing in our New Release environment April 29, 2020, with a production date of May 4, 2020.

Click here for the full text of the advisory

20-181




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BIZ-Quartalsbericht Dezember 2017: Straffungsparadox erinnert an das berühmte "Zinsrätsel"

German translation of the BIS press release about the BIS Quarterly Review, December 2017




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Queda mucho por hacer para detener el declive de Zimbabue

Un año después de la victoria en las elecciones de la Unión Nacional Africana de Zimbabue- Frente Patriótico (ZANU-PF, en sus siglas en inglés) y de la formación de un nuevo gobierno, la política y la economía de Zimbabue son cada vez más precarias. Las perspectivas inmediatas de una recuperación sostenida siguen siendo malas, empeoradas por el alarmante declive económico, los fracasos endémicos en materia de gobernanza y la tensión generada por la sucesión en el partido en el poder.




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Octodon degus (Molina 1782): A Model in Comparative Biology and Biomedicine

One major goal of integrative and comparative biology is to understand and explain the interaction between the performance and behavior of animals in their natural environment. The Caviomorph, Octodon degu, is a native rodent species from Chile, and represents a unique model to study physiological and behavioral traits, including cognitive and sensory abilities. Degus live in colonies and have a well-structured social organization, with a mostly diurnal–crepuscular circadian activity pattern. More notable is the fact that in captivity, they reproduce and live between 5 and 7 yr and show hallmarks of neurodegenerative diseases (including Alzheimer's disease), diabetes, and cancer.




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Paralysis provides platform to preach

Miraculous healing from sudden paralysis gives an OM worker opportunity to preach the gospel in a community.




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Finland's grassroots paradise

We visit the winners of the Best Club category in the 2011 UEFA Grassroots Day Awards.




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New Study Calls for More Research Into Early-Childhood Teacher Preparation

There's a new focus on getting more training to early-childhood educators, but there's a dearth of information about what constitutes a high-quality, teacher-preparation program.




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The Finnish Paradox

Pasi Sahlberg explores a central role play has inside and outside the school context as a foundation for positive child development.




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N.Y. Chief, SUNY Chancellor Team Up to Overhaul Teacher Preparation

Two high-powered N.Y. officials have put out a blueprint for overhauling teaching in the state, aiming for more-coherent policies for the profession.




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Europa aprueba 222 millones de euros para proyectos de medio ambiente y acción por el clima

Source: Retema - La Comisión Europea ha aprobado un conjunto de inversiones por valor de 222 millones de euros procedentes del presupuesto de la UE para facilitar la transición de Europa hacia un futuro más sostenible e hipocarbónico en el marco del programa LIFE de medio ambiente y acción por el clima. La financiación de la UE movilizará inversiones adicionales con las que se llegará a un total de 379 millones de euros destinados a 139 nuevos proyectos en 20 Estados miembros.




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Parental Separation and Pediatric Cancer: A Danish Cohort Study

Cancer in a child may affect the quality of the parents’ relationship, but few studies have examined a potential effect on parental divorce, and no studies have accounted for the proportion of couples that live outside formal marriages.

In this nationwide registry-based study with up to 20 years of follow-up, we included both married and cohabiting couples, reflecting modern family structures. We found that experiencing cancer in a child is not a risk factor for the parents separating. (Read the full article)




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Chlorhexidine Cleansing of the Umbilical Cord and Separation Time: A Cluster-Randomized Trial

Chlorhexidine cleansing of the cord can reduce mortality in high-risk settings. Time to separation may increase with topical applications of chlorhexidine; 1 previous community trial quantified this increase and did not measure whether caretakers perceived the delay.

Single and multiple cleansing of the umbilical cord increases time to separation by ~50%, or an average of 2 to 2.5 days. Caretakers were able to detect this difference and expressed dissatisfaction, while still accepting the intervention. (Read the full article)




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Current Status of Transition Preparation Among Youth With Special Needs in the United States

The importance of transition from pediatric to adult health care for youth with special health care needs has gained increasing attention over the past decade, but fewer than half of this population received needed transition preparation in 2005–2006.

This study reports on transition findings from the 2009–2010 National Survey of Children with Special Health Care Needs and finds no discernible improvements since 2005–2006. New clinical recommendations and care processes should help to accelerate transition improvements in the future. (Read the full article)




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Comparative Effectiveness of Acellular Versus Whole-Cell Pertussis Vaccines in Teenagers

The United States switched from whole-cell to acellular pertussis vaccines during the 1990s. Whether pertussis risk during a California outbreak differed between teenagers who previously received whole-cell or acellular pertussis vaccines early in life has not been reported.

We evaluated pertussis risk in 10 to 17 year olds at Kaiser Permanente Northern California during a recent pertussis outbreak. Those given whole-cell pertussis vaccines in childhood were more protected than those given acellular pertussis vaccines. (Read the full article)




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Comparative Effectiveness of Empiric Antibiotics for Community-Acquired Pneumonia

Broad-spectrum antibiotics are frequently used to empirically treat children hospitalized with community-acquired pneumonia despite recent national recommendations to use narrow-spectrum antibiotics.

Narrow-spectrum antibiotics are similar to broad-spectrum antibiotics for the treatment of children hospitalized with community-acquired pneumonia in terms of clinical outcomes and resource utilization. This study provides scientific evidence to support national consensus guidelines. (Read the full article)