Though it has achieved success in some areas, the Trump administration’s many efforts to stiffen immigration enforcement in the U.S. interior and at the Southwest border are being consistently stymied by court injunctions, existing laws and settlements, state and local resistance, congressional pushback, and migration pressures that are beyond the government’s ability to swiftly address, as this article explores.

The high-stakes gambit taken by Turkish President Recep Tayyip Erdoğan to allow tens of thousands of asylum seekers and migrants free movement to the Greek border demonstrated the fragility of the EU-Turkey deal and the European Union's broader approach to outsource migration management to third countries. This article examines the causes for the tensions, the EU approach to external partnerships, and a hardening European attitude towards unwanted arrivals.

The ADA and the Wisconsin Dental Association are partnering up with other fluoridated water proponents to address February anti-fluoridation movements in three Wisconsin municipalities: Lake Delton, Berlin and Hayward.

As in several other states dependent on tax revenue from natural resources, Wyoming legislators are looking for ways to make millions of dollars in education budget cuts.

Governors' races in Kentucky and Mississippi took center stage, testing the political muscle of teacher activists and yielding possible policy implications for everything from public employee pensions to teacher pay.

Voters in three southern states will head to the polls for governors races that have shined a spotlight on educator activism, school funding, and teacher pay.

This year's November elections—a preview to next year's nationwide showdowns—cast their own spotlight on education, a dynamic that played out most prominently in the Kentucky governor's race, where teachers organized to unseat a combative incumbent who'd sparred with them.

An internationally known gifted-education center is scouting—and helping to develop—gifted students in after-school programs and pullout classes in one of Maryland’s most challenged school districts.

This book is a biography of Sandy and her great grand fathers life journey, through an inspirational spiritual connection, involving cellular memory and genetic DNA. It entails a story of forced assimilation on a culture, still not identified in the countries constitution. Survival, deception, manipulation and confusion regarding Colonisation. This is on a scale of mass deception from a democracy that claims, equality and equity to all. The letter of Patent making South Australia a Province in 1836, shows that Consciousness Raising is evolving through the resilience and visualisation of the' Original peoples' of this ancient land, seen through the eyes of Sandy.

Museums.

Pokémon Go (Game) -- Social aspects.

Londres : H. Bailliere, 1843-1847.

In a case implicating the use of schools as voting locations as well as free speech in education, the justices said Minnesota went too far.

Governors' races in Kentucky and Mississippi took center stage, testing the political muscle of teacher activists and yielding possible policy implications for everything from public employee pensions to teacher pay.

Voters in three southern states will head to the polls for governors races that have shined a spotlight on educator activism, school funding, and teacher pay.

This year's November elections—a preview to next year's nationwide showdowns—cast their own spotlight on education, a dynamic that played out most prominently in the Kentucky governor's race, where teachers organized to unseat a combative incumbent who'd sparred with them.

[Rome?]

Mario Teixeira Parente, Jonas Wallin, Barbara Wohlmuth.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 917--943.

Abstract:
In this article, we consider scenarios in which traditional estimates for the active subspace method based on probabilistic Poincaré inequalities are not valid due to unbounded Poincaré constants. Consequently, we propose a framework that allows to derive generalized estimates in the sense that it enables to control the trade-off between the size of the Poincaré constant and a weaker order of the final error bound. In particular, we investigate independently exponentially distributed random variables in dimension two or larger and give explicit expressions for corresponding Poincaré constants showing their dependence on the dimension of the problem. Finally, we suggest possibilities for future work that aim for extending the class of distributions applicable to the active subspace method as we regard this as an opportunity to enlarge its usability.

Parametrised state space models in the form of recurrent networks are often used in machine learning to learn from data streams exhibiting temporal dependencies. To break the black box nature of such models it is important to understand the dynamical features of the input-driving time series that are formed in the state space. We propose a framework for rigorous analysis of such state representations in vanishing memory state space models such as echo state networks (ESN). In particular, we consider the state space a temporal feature space and the readout mapping from the state space a kernel machine operating in that feature space. We show that: (1) The usual ESN strategy of randomly generating input-to-state, as well as state coupling leads to shallow memory time series representations, corresponding to cross-correlation operator with fast exponentially decaying coefficients; (2) Imposing symmetry on dynamic coupling yields a constrained dynamic kernel matching the input time series with straightforward exponentially decaying motifs or exponentially decaying motifs of the highest frequency; (3) Simple ring (cycle) high-dimensional reservoir topology specified only through two free parameters can implement deep memory dynamic kernels with a rich variety of matching motifs. We quantify richness of feature representations imposed by dynamic kernels and demonstrate that for dynamic kernel associated with cycle reservoir topology, the kernel richness undergoes a phase transition close to the edge of stability.

We consider the problem of clustering and completing a set of tensors with missing data that are drawn from a union of low-rank tensor spaces. In the clustering problem, given a partially sampled tensor data that is composed of a number of subtensors, each chosen from one of a certain number of unknown tensor spaces, we need to group the subtensors that belong to the same tensor space. We provide a geometrical analysis on the sampling pattern and subsequently derive the sampling rate that guarantees the correct clustering under some assumptions with high probability. Moreover, we investigate the fundamental conditions for finite/unique completability for the union of tensor spaces completion problem. Both deterministic and probabilistic conditions on the sampling pattern to ensure finite/unique completability are obtained. For both the clustering and completion problems, our tensor analysis provides significantly better bound than the bound given by the matrix analysis applied to any unfolding of the tensor data.

Nancy Heckman

Source: Statist. Surv., Volume 6, 113--141.

Abstract:
The popular cubic smoothing spline estimate of a regression function arises as the minimizer of the penalized sum of squares $sum_{j}(Y_{j}-mu(t_{j}))^{2}+lambda int_{a}^{b}[mu''(t)]^{2},dt$, where the data are $t_{j},Y_{j}$, $j=1,ldots,n$. The minimization is taken over an infinite-dimensional function space, the space of all functions with square integrable second derivatives. But the calculations can be carried out in a finite-dimensional space. The reduction from minimizing over an infinite dimensional space to minimizing over a finite dimensional space occurs for more general objective functions: the data may be related to the function $mu$ in another way, the sum of squares may be replaced by a more suitable expression, or the penalty, $int_{a}^{b}[mu''(t)]^{2},dt$, might take a different form. This paper reviews the Reproducing Kernel Hilbert Space structure that provides a finite-dimensional solution for a general minimization problem. Particular attention is paid to the construction and study of the Reproducing Kernel Hilbert Space corresponding to a penalty based on a linear differential operator. In this case, one can often calculate the minimizer explicitly, using Green’s functions.

Jianqing Fan, Dong Wang, Kaizheng Wang, Ziwei Zhu.

Source: The Annals of Statistics, Volume 47, Number 6, 3009--3031.

Abstract:
Principal component analysis (PCA) is fundamental to statistical machine learning. It extracts latent principal factors that contribute to the most variation of the data. When data are stored across multiple machines, however, communication cost can prohibit the computation of PCA in a central location and distributed algorithms for PCA are thus needed. This paper proposes and studies a distributed PCA algorithm: each node machine computes the top $K$ eigenvectors and transmits them to the central server; the central server then aggregates the information from all the node machines and conducts a PCA based on the aggregated information. We investigate the bias and variance for the resulting distributed estimator of the top $K$ eigenvectors. In particular, we show that for distributions with symmetric innovation, the empirical top eigenspaces are unbiased, and hence the distributed PCA is “unbiased.” We derive the rate of convergence for distributed PCA estimators, which depends explicitly on the effective rank of covariance, eigengap, and the number of machines. We show that when the number of machines is not unreasonably large, the distributed PCA performs as well as the whole sample PCA, even without full access of whole data. The theoretical results are verified by an extensive simulation study. We also extend our analysis to the heterogeneous case where the population covariance matrices are different across local machines but share similar top eigenstructures.

Yen-Chi Chen, Adrian Dobra.

Source: The Annals of Applied Statistics, Volume 14, Number 1, 409--432.

Abstract:
Activity spaces are fundamental to the assessment of individuals’ dynamic exposure to social and environmental risk factors associated with multiple spatial contexts that are visited during activities of daily living. In this paper we survey existing approaches for measuring the geometry, size and structure of activity spaces, based on GPS data, and explain their limitations. We propose addressing these shortcomings through a nonparametric approach called density ranking and also through three summary curves: the mass-volume curve, the Betti number curve and the persistence curve. We introduce a novel mixture model for human activity spaces and study its asymptotic properties. We prove that the kernel density estimator, which at the present time, is one of the most widespread methods for measuring activity spaces, is not a stable estimator of their structure. We illustrate the practical value of our methods with a simulation study and with a recently collected GPS dataset that comprises the locations visited by 10 individuals over a six months period.

Anton Thalmaier, James Thompson.

Source: Bernoulli, Volume 26, Number 3, 2202--2225.

Abstract:
In this article, we derive moment estimates, exponential integrability, concentration inequalities and exit times estimates for canonical diffusions firstly on sub-Riemannian limits of Riemannian foliations and secondly in the nonsmooth setting of $operatorname{RCD}^{*}(K,N)$ spaces. In each case, the necessary ingredients are Itô’s formula and a comparison theorem for the Laplacian, for which we refer to the recent literature. As an application, we derive pointwise Carmona-type estimates on eigenfunctions of Schrödinger operators.

Galatia Cleanthous, Athanasios G. Georgiadis, Gerard Kerkyacharian, Pencho Petrushev, Dominique Picard.

Source: Bernoulli, Volume 26, Number 3, 1832--1862.

Abstract:
We consider the problem of estimating the density of observations taking values in classical or nonclassical spaces such as manifolds and more general metric spaces. Our setting is quite general but also sufficiently rich in allowing the development of smooth functional calculus with well localized spectral kernels, Besov regularity spaces, and wavelet type systems. Kernel and both linear and nonlinear wavelet density estimators are introduced and studied. Convergence rates for these estimators are established and discussed.

Jing Lei.

Source: Bernoulli, Volume 26, Number 1, 767--798.

Abstract:
We provide upper bounds of the expected Wasserstein distance between a probability measure and its empirical version, generalizing recent results for finite dimensional Euclidean spaces and bounded functional spaces. Such a generalization can cover Euclidean spaces with large dimensionality, with the optimal dependence on the dimensionality. Our method also covers the important case of Gaussian processes in separable Hilbert spaces, with rate-optimal upper bounds for functional data distributions whose coordinates decay geometrically or polynomially. Moreover, our bounds of the expected value can be combined with mean-concentration results to yield improved exponential tail probability bounds for the Wasserstein error of empirical measures under Bernstein-type or log Sobolev-type conditions.

Two sites preserve around 50 footprints, a discovery that highlights the richness of prehistoric life on the island

These dairy products are no longer edible, but they're still valuable to researchers

Doctors and nurses are attaching smiling photos of themselves to the outside of their protective gear to maintain connections with patients

Traditionalist "two-spacers" can still disable the function

The new book 'The Rainbow Atlas' invites readers on a vivid journey across the globe

Why not use quarantine as an opportunity to have your homeschoolers master woodworking or engine repair?

Rice terraces in Longji,China.

The National Trust for Historic Preservation is looking for 1,000 places tied to women's history, and to share the stories of the figures behind them

The N.W.T. and Nunavut Workers’ Safety and Compensation Commission says it filed multiple charges in the Nunavut Court of Justice under the Nunavut Safety Act on May 1.

Seven people were displaced by a fire early Saturday on the north end of Saint John.

Police in Thunder Bay have arrested and charged a man from the northwestern Ontario city following an investigation into allegations of child luring.

Baltimore Orioles outfielder and first baseman Trey Mancini revealed Tuesday he is in the midst of six months of chemotherapy as he fights Stage III colon cancer.

Hope for a 2020 Grey Cup in Regina is slowly dwindling as the CFL hints at a season cancellation. 

Most of the animals at the B.C. Wildlife Park in Kamloops are unfazed by the absence of paying visitors since it closed in March over COVID-19 concerns. But Blue the turkey appears "bummed," staff say.

Learn how to easily delete a face from a solid or surface body when modeling in SOLIDWORKS. Our #TechTip this week is by Training Manager John Setzer. Video Transcript Hi and welcome to another GSC tech tip. Today we’re going

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A group of 10 students, including a translator, participate in a two months training programme in Panama. The Mission Extreme Outreach has its students work amongst Panamanians and indigenous tribes. Un grupo de 10 estudiantes,incluyendo la traductora, participan durante los dos meses de gira en Panamá. Una vez más Misión Extrema está en acción con los latinos y grupos indígenas.

ONCE a staple of drive-thrus and fast food restaurants, burgers have had something of an image overhaul in recent years.

Australia's central bank has predicted that the country is facing its biggest economic contraction on record.

OM EAST offers a special start to the new school term for hundreds of children in Bosnia-Herzegovina.

St Kilda