Many state politicians and advocates used U.S. Secretary of Education Betsy DeVos' recent feedback as an opportunity to attack their states' approach to the Every Student Succeeds Act.

The latest approvals mean 12 of the 17 state plans submitted so far for Every Student Succeeds Act implementation have been given the federal go-ahead.

That brings the number of states with approved plans to 44, plus the District of Columbia and Puerto Rico. Still awaiting the OK: California, Florida, Nebraska, North Carolina, Oklahoma, and Utah

[London] (at the Historic Gallery, 87 Pall Mall) : Pub.d by Mr Stone.

London (5 Haymarket) : Published ... by J. Hogarth, June 1 1849.

[London?], [between 1700 and 1799?]

[London?], [between 1700 and 1799?]

After an investigation found Illinois schools put children in "isolated timeout" for illegal reasons, a group of the state's federal lawmakers have asked U.S. Secretary of Education to ban seclusion in schools nationwide.

New York ; London : W.W. Norton, 2008.

Berkeley, California : Tabor Sarah Books, 1988.

Rockville, Maryland : National Institute on Drug Abuse, 1988.

Rockville, Maryland : National Institute on Drug Abuse, 1986.

Rockville, Maryland : National Institute on Drug Abuse, 1980.

[London] : [publisher not identified], [2019]

María F. Gil–Leyva, Ramsés H. Mena, Theodoros Nicoleris.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 1479--1507.

Abstract:
A new class of nonparametric prior distributions, termed Beta-Binomial stick-breaking process, is proposed. By allowing the underlying length random variables to be dependent through a Beta marginals Markov chain, an appealing discrete random probability measure arises. The chain’s dependence parameter controls the ordering of the stick-breaking weights, and thus tunes the model’s label-switching ability. Also, by tuning this parameter, the resulting class contains the Dirichlet process and the Geometric process priors as particular cases, which is of interest for MCMC implementations. Some properties of the model are discussed and a density estimation algorithm is proposed and tested with simulated datasets.

Danilo Covaes Nogarotto, Caio Lucidius Naberezny Azevedo, Jorge Luis Bazán.

Source: Brazilian Journal of Probability and Statistics, Volume 34, Number 2, 304--322.

Abstract:
The interest on the analysis of the zero–one augmented beta regression (ZOABR) model has been increasing over the last few years. In this work, we developed a Bayesian inference for the ZOABR model, providing some contributions, namely: we explored the use of Jeffreys-rule and independence Jeffreys prior for some of the parameters, performing a sensitivity study of prior choice, comparing the Bayesian estimates with the maximum likelihood ones and measuring the accuracy of the estimates under several scenarios of interest. The results indicate, in a general way, that: the Bayesian approach, under the Jeffreys-rule prior, was as accurate as the ML one. Also, different from other approaches, we use the predictive distribution of the response to implement Bayesian residuals. To further illustrate the advantages of our approach, we conduct an analysis of a real psychometric data set including a Bayesian residual analysis, where it is shown that misleading inference can be obtained when the data is transformed. That is, when the zeros and ones are transformed to suitable values and the usual beta regression model is considered, instead of the ZOABR model. Finally, future developments are discussed.

Fábio P. Lima, Francisco Cribari-Neto.

Source: Brazilian Journal of Probability and Statistics, Volume 34, Number 1, 18--34.

Abstract:
We address the issue of performing testing inference in small samples in the class of beta regression models. We consider the likelihood ratio test and its standard bootstrap version. We also consider two alternative resampling-based tests. One of them uses the bootstrap test statistic replicates to numerically estimate a Bartlett correction factor that can be applied to the likelihood ratio test statistic. By doing so, we avoid estimation of quantities located in the tail of the likelihood ratio test statistic null distribution. The second alternative resampling-based test uses a fast double bootstrap scheme in which a single second level bootstrapping resample is performed for each first level bootstrap replication. It delivers accurate testing inferences at a computational cost that is considerably smaller than that of a standard double bootstrapping scheme. The Monte Carlo results we provide show that the standard likelihood ratio test tends to be quite liberal in small samples. They also show that the bootstrap tests deliver accurate testing inferences even when the sample size is quite small. An empirical application is also presented and discussed.

Scott H. Holan, Robert Lund, Ginger Davis

Source: Statist. Surv., Volume 4, 232--274.

Abstract:
Autoregressive moving-average (ARMA) difference equations are ubiquitous models for short memory time series and have parsimoniously described many stationary series. Variants of ARMA models have been proposed to describe more exotic series features such as long memory autocovariances, periodic autocovariances, and count support set structures. This review paper enumerates, compares, and contrasts the common variants of ARMA models in today’s literature. After the basic properties of ARMA models are reviewed, we tour ARMA variants that describe seasonal features, long memory behavior, multivariate series, changing variances (stochastic volatility) and integer counts. A list of ARMA variant acronyms is provided.

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Zhonghua Liu, Ian Barnett, Xihong Lin.

Source: The Annals of Applied Statistics, Volume 14, Number 1, 433--451.

Abstract:
Principal component analysis (PCA) is a popular method for dimension reduction in unsupervised multivariate analysis. However, existing ad hoc uses of PCA in both multivariate regression (multiple outcomes) and multiple regression (multiple predictors) lack theoretical justification. The differences in the statistical properties of PCAs in these two regression settings are not well understood. In this paper we provide theoretical results on the power of PCA in genetic association testings in both multiple phenotype and SNP-set settings. The multiple phenotype setting refers to the case when one is interested in studying the association between a single SNP and multiple phenotypes as outcomes. The SNP-set setting refers to the case when one is interested in studying the association between multiple SNPs in a SNP set and a single phenotype as the outcome. We demonstrate analytically that the properties of the PC-based analysis in these two regression settings are substantially different. We show that the lower order PCs, that is, PCs with large eigenvalues, are generally preferred and lead to a higher power in the SNP-set setting, while the higher-order PCs, that is, PCs with small eigenvalues, are generally preferred in the multiple phenotype setting. We also investigate the power of three other popular statistical methods, the Wald test, the variance component test and the minimum $p$-value test, in both multiple phenotype and SNP-set settings. We use theoretical power, simulation studies, and two real data analyses to validate our findings.

Bryan D. Martin, Daniela Witten, Amy D. Willis.

Source: The Annals of Applied Statistics, Volume 14, Number 1, 94--115.

Abstract:
Using a sample from a population to estimate the proportion of the population with a certain category label is a broadly important problem. In the context of microbiome studies, this problem arises when researchers wish to use a sample from a population of microbes to estimate the population proportion of a particular taxon, known as the taxon’s relative abundance . In this paper, we propose a beta-binomial model for this task. Like existing models, our model allows for a taxon’s relative abundance to be associated with covariates of interest. However, unlike existing models, our proposal also allows for the overdispersion in the taxon’s counts to be associated with covariates of interest. We exploit this model in order to propose tests not only for differential relative abundance, but also for differential variability. The latter is particularly valuable in light of speculation that dysbiosis , the perturbation from a normal microbiome that can occur in certain disease conditions, may manifest as a loss of stability, or increase in variability, of the counts associated with each taxon. We demonstrate the performance of our proposed model using a simulation study and an application to soil microbial data.

Thomson (Family)

Karim Fifel
Jan 24, 2018; 38:784-786
Journal Club

Christian Gaser
Oct 8, 2003; 23:9240-9245
BehavioralSystemsCognitive

CJ Pike
Apr 1, 1993; 13:1676-1687
Articles

MN Shadlen
Feb 15, 1996; 16:1486-1510
Articles

M Niethammer
Apr 1, 1996; 16:2157-2163
Articles

Lennart Mucke
Jun 1, 2000; 20:4050-4058
Cellular

The Linux Foundation will host ToIP, a cross-industry effort to ensure more secure data handling over the Internet. This new foundation is an independent project enabling trustworthy exchange and verification of data between any two parties on the Internet. The ToIP Foundation will provide a robust common standard to instill confidence that data is coming from a trusted source.

Nicotine addiction, through smoking, is the principal cause of preventable mortality worldwide. Human genome-wide association studies have linked polymorphisms in the CHRNA5-CHRNA3-CHRNB4 gene cluster, coding for the α5, α3, and β4 nicotinic acetylcholine receptor (nAChR) subunits, to nicotine addiction. β4*nAChRs have been implicated in nicotine withdrawal, aversion, and reinforcement. Here we show that β4*nAChRs also are involved in non-nicotine-mediated responses that may predispose to addiction-related behaviors. β4 knock-out (KO) male mice show increased novelty-induced locomotor activity, lower baseline anxiety, and motivational deficits in operant conditioning for palatable food rewards and in reward-based Go/No-go tasks. To further explore reward deficits we used intracranial self-administration (ICSA) by directly injecting nicotine into the ventral tegmental area (VTA) in mice. We found that, at low nicotine doses, β4KO self-administer less than wild-type (WT) mice. Conversely, at high nicotine doses, this was reversed and β4KO self-administered more than WT mice, whereas β4-overexpressing mice avoided nicotine injections. Viral expression of β4 subunits in medial habenula (MHb), interpeduncular nucleus (IPN), and VTA of β4KO mice revealed dose- and region-dependent differences: β4*nAChRs in the VTA potentiated nicotine-mediated rewarding effects at all doses, whereas β4*nAChRs in the MHb-IPN pathway, limited VTA-ICSA at high nicotine doses. Together, our findings indicate that the lack of functional β4*nAChRs result in deficits in reward sensitivity including increased ICSA at high doses of nicotine that is restored by re-expression of β4*nAChRs in the MHb-IPN. These data indicate that β4 is a critical modulator of reward-related behaviors.

SIGNIFICANCE STATEMENT Human genetic studies have provided strong evidence for a relationship between variants in the CHRNA5-CHRNA3-CHRNB4 gene cluster and nicotine addiction. Yet, little is known about the role of β4 nicotinic acetylcholine receptor (nAChR) subunit encoded by this cluster. We investigated the implication of β4*nAChRs in anxiety-, food reward- and nicotine reward-related behaviors. Deletion of the β4 subunit gene resulted in an addiction-related phenotype characterized by low anxiety, high novelty-induced response, lack of sensitivity to palatable food rewards and increased intracranial nicotine self-administration at high doses. Lentiviral vector-induced re-expression of the β4 subunit into either the MHb or IPN restored a "stop" signal on nicotine self-administration. These results suggest that β4*nAChRs provide a promising novel drug target for smoking cessation.

Investment of cognitive effort is required in everyday life and has received ample attention in recent neurocognitive frameworks. The neural mechanism of effort investment is thought to be structured hierarchically, with dorsal anterior cingulate cortex (dACC) at the highest level, recruiting task-specific upstream areas. In the current fMRI study, we tested whether dACC is generally active when effort demand is high across tasks with different stimuli, and whether connectivity between dACC and task-specific areas is increased depending on the task requirements and effort level at hand. For that purpose, a perceptual detection task was administered that required male and female human participants to detect either a face or a house in a noisy image. Effort demand was manipulated by adding little (low effort) or much (high effort) noise to the images. Results showed a network of dACC, anterior insula (AI), and intraparietal sulcus (IPS) to be more active when effort demand was high, independent of the performed task (face or house detection). Importantly, effort demand modulated functional connectivity between dACC and face-responsive or house-responsive perceptual areas, depending on the task at hand. This shows that dACC, AI, and IPS constitute a general effort-responsive network and suggests that the neural implementation of cognitive effort involves dACC-initiated sensitization of task-relevant areas.

SIGNIFICANCE STATEMENT Although cognitive effort is generally perceived as aversive, its investment is inevitable when navigating an increasingly complex society. In this study, we demonstrate how the human brain tailors the implementation of effort to the requirements of the task at hand. We show increased effort-related activity in a network of brain areas consisting of dorsal anterior cingulate cortex (dACC), anterior insula, and intraparietal sulcus, independent of task specifics. Crucially, we also show that effort-induced functional connectivity between dACC and task-relevant areas tracks specific task demands. These results demonstrate how brain regions specialized to solve a task may be energized by dACC when effort demand is high.

Enjoy a low-cost, healthy diet from your very own vegetable garden and get the chance to make money by selling your own products. Start your own vegetable garden to grow, prepare and eat your own delicious fruits and vegetables with these tips: Do your research: When you begin your own vegetable garden you should understand the type of soil you work [...]

In the past 20 years, malnutrition in mothers and children has decreased by almost half. But despite this progress, child undernutrition is still the greatest nutrition-related health burden in the world. One of the biggest problems with child undernutrition is that it continues the cycle of stunting: stunted girls grow up to be stunted mothers, and stunted mothers are much [...]

What do cucumbers, mustard, almonds and alfalfa have in common? On the surface it appears to be very little. However, there is one thing they do share: They all owe their existence to the service of bees. There is more to the tiny striped helper than sweet honey and a painful sting. For millennia, it has carried out its service [...]

Four years into the 2030 Agenda, there is still a large gap in data to understand where the world stands in achieving its shared goals, the SDGs. To support [...]

The National Book Award winner's new book delves into matters of family grief and loss

A virus that spreads fear and stigma, as well as disease. It’s the story of HIV/AIDS as well as COVID-19. The former executive director of AIDS Thunder Bay reflects on the similarities he sees between HIV 35 years ago, and the coronavirus now.

A longstanding battle between an Alberta entrepreneur and a $50-million lottery winner is still raging after a new legal judgment, a securities investigation, allegations of harassment and even duelling ebooks.

With the business world -- and the world at large, for that matter -- changing at what feels like a moment's notice, businesses and brands have never been required to be as limber as in this current moment. Marketing leaders want hard evidence and objective facts for decision making. It wasn't long ago that multi-touch attribution was the prized child of the hype cycle among marketers.

11 startups to pitch at NEXT Canada's virtual Venture Reveal  BetaKit

Kiuna College hopes to play an active role in the emergence of the next generation of Indigenous filmmakers and creators.