With the U.S. administration calling for the United States to adopt a more “merit-based” immigrant selection system, this conversation focused on what policymakers should consider in designing—and managing—immigrant selection systems in a time of intense labor-market and demographic change.

MPI and OECD experts discuss what policymakers should consider in designing and managing immigrant selection systems in a time of intense labor-market and demographic change.

Nearly 2 million college-educated immigrants in the United States, more than half coming with academic and professional credentials, are unable to fully utilize their professional skills and instead are stuck in low-skilled work or are unemployed. This report explores a range of programs and policies that are providing cutting-edge career navigation, relicensing, gap filling, and job search assistance to remedy this brain waste.

WASHINGTON — As host countries in Europe, North America and beyond prioritize getting refugees and other newly arrived migrants into work, another challenge has received less attention: Helping those who may never find jobs participate meaningfully in their new communities. Newcomers who are not in the workplace (particularly refugee women, migrants who are unskilled or illiterate and the elderly) are at high risk for social isolation.

OBJECTIVE

We conducted an open-label, phase I study using autologous umbilical cord blood (UCB) infusion to ameliorate type 1 diabetes (T1D). Having previously reported on the first 15 patients reaching 1 year of follow-up, herein we report on the complete cohort after 2 years of follow-up.

Every business begun before the Internet now faces the same challenge: How to transform to compete in a digital economy? This is the leadership challenge examined by BRITE founder and Columbia Business School faculty member David Rogers in his newest book, The Digital Transformation Playbook (April 5, 2016; Columbia Business School Publishing). In the book, […]

We all understand that digital media, data, and analytics are driving transformations in society and business. Most marketers are now armed with case studies of what can be done differently, but many are still challenged with how to truly develop new ideas and execute new strategies to grow their business. Mitch Joel, President of Mirum […]

The problem with this sign is that the best yard sale goodies were probably available “yesterday.” You’re down to the dregs today. Better to post a sign that is fuzzy with time and refers only to “today.” Hat tip to photographer Mary Ann Henningsen.

As a practicing sex therapist, I often see two partners legitimately trying to bridge a satisfaction gap between each other, but they can’t seem to get the moves just right. If left unchecked, this can lead to resentment and conflict; however, couples who figure out how to speak to each other sexually (both verbally and nonverbally) have the highest success in terms of finding something that works for both of them. Making an environment conducive to this sort of positive growth requires a little bit of effort and the ability to listen. Drawing on my clinical experience, here are my top tips for increasing sexual satisfaction:

What if you could repay loans through volunteering and mentorship instead of money? Activist Angie Murimirwa shares how a game-changing economic tool known as "social interest" is reinvigorating sub-Saharan communities once trapped in cycles of poverty. Join her as she explains how this approach to lending is creating opportunities for thousands of African women and girls -- and shows why this model can be replicated anywhere with lasting effects.

Sam Houston State has announced the addition of two transfer wide receivers, former Howard standout Jequez Ezzard and Harvard grad transfer Cody Chrest, for their final seasons of eligibility this year. The 5-foot-9, 190-pound Ezzard, from College Park, Georgia, gives the Southland Conference program one of the top big-play pass catchers in the FCS. The 6-foot, 190-pound Chrest, from Houston, broke out last season with 45 receptions and 706 receiving yards, Harvard's team highs.

City planning -- Remote sensing.

Biodiversity -- Climatic factors.

Leipzig : G. Thieme, 1890-1891.

Wien : A. Holder, 1890.

Berlin : J. Springer, 1893.

Jena : G. Fischer, 1902.

Berlin : A. Hirschwald, 1879.

Paris : V.A. Delahaye, 1880.

Wien : SafÏar, 1905.

London (46 Pall Mall) : Pub.d by R. Bowyer & M. Parkes, 1st Jan.y 1830.

England : London County Council, Public Assistance Department, 1935.

Halle (Saale) : Deutsche Akademie der Naturforscher Leopoldina - Nationale Akademie der Wissenschaften ; Stuttgart : Wissenschaftliche Verlagsgesellschaft, 2019.

Leith, 2019

Oregon State basketball player Destiny Slocum has opted to enter the transfer portal for her final season of eligibility. Slocum, a 5-foot-7 guard, averaged a team-best 14.9 points and had 4.7 assists a game this past season with the Beavers, who finished the season ranked No. 14 with a 23-9 record. In a statement released by the university on Thursday, Slocum thanked everyone who supported her in the decision.

The Tennessee Lady Vols have added forward-center Keyen Green as a graduate transfer from Liberty. Coach Kellie Harper announced Wednesday that Green has signed a scholarship for the upcoming season. The 6-foot-1 Green spent the past four seasons at Liberty and graduated in May 2019.

LEXINGTON, Ky. (AP) -- Sophomore guards Jazmine Massengill and Robyn Benton transferred to Kentucky from Southeastern Conference rivals Wednesday.

Maori Davenport, who drew national attention over an eligibility dispute during her senior year of high school, is transferring to Georgia after playing sparingly in her lone season at Rutgers. Lady Bulldogs coach Joni Taylor announced Davenport's decision Wednesday. The 6-foot-4 center from Troy, Alabama will have to sit out a season under NCAA transfer rules before she is eligible to join Georgia in 2021-22.

Baylor has signed a transfer point guard for the third year in a row, and this one can play multiple seasons with the Lady Bears. Jaden Owens is transferring from UCLA after signing a national letter of intent with Baylor, which had graduate transfers at point guard each of the past two seasons. The Texas native just completed her freshman season with the Bruins and has three seasons of eligibility remaining.

François Bachoc, José Betancourt, Reinhard Furrer, Thierry Klein.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 1962--2008.

Abstract:
The asymptotic analysis of covariance parameter estimation of Gaussian processes has been subject to intensive investigation. However, this asymptotic analysis is very scarce for non-Gaussian processes. In this paper, we study a class of non-Gaussian processes obtained by regular non-linear transformations of Gaussian processes. We provide the increasing-domain asymptotic properties of the (Gaussian) maximum likelihood and cross validation estimators of the covariance parameters of a non-Gaussian process of this class. We show that these estimators are consistent and asymptotically normal, although they are defined as if the process was Gaussian. They do not need to model or estimate the non-linear transformation. Our results can thus be interpreted as a robustness of (Gaussian) maximum likelihood and cross validation towards non-Gaussianity. Our proofs rely on two technical results that are of independent interest for the increasing-domain asymptotic literature of spatial processes. First, we show that, under mild assumptions, coefficients of inverses of large covariance matrices decay at an inverse polynomial rate as a function of the corresponding observation location distances. Second, we provide a general central limit theorem for quadratic forms obtained from transformed Gaussian processes. Finally, our asymptotic results are illustrated by numerical simulations.

Daniel R. Kowal, Antonio Canale.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 1744--1772.

Abstract:
We propose a simple yet powerful framework for modeling integer-valued data, such as counts, scores, and rounded data. The data-generating process is defined by Simultaneously Transforming and Rounding (STAR) a continuous-valued process, which produces a flexible family of integer-valued distributions capable of modeling zero-inflation, bounded or censored data, and over- or underdispersion. The transformation is modeled as unknown for greater distributional flexibility, while the rounding operation ensures a coherent integer-valued data-generating process. An efficient MCMC algorithm is developed for posterior inference and provides a mechanism for adaptation of successful Bayesian models and algorithms for continuous data to the integer-valued data setting. Using the STAR framework, we design a new Bayesian Additive Regression Tree model for integer-valued data, which demonstrates impressive predictive distribution accuracy for both synthetic data and a large healthcare utilization dataset. For interpretable regression-based inference, we develop a STAR additive model, which offers greater flexibility and scalability than existing integer-valued models. The STAR additive model is applied to study the recent decline in Amazon river dolphins.

Benjamin Colling, Ingrid Van Keilegom.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 769--800.

Abstract:
Consider the following semiparametric transformation model $Lambda_{ heta }(Y)=m(X)+varepsilon $, where $X$ is a $d$-dimensional covariate, $Y$ is a univariate response variable and $varepsilon $ is an error term with zero mean and independent of $X$. We assume that $m$ is an unknown regression function and that ${Lambda _{ heta }: heta inTheta }$ is a parametric family of strictly increasing functions. Our goal is to develop two new estimators of the transformation parameter $ heta $. The main idea of these two estimators is to minimize, with respect to $ heta $, the $L_{2}$-distance between the transformation $Lambda _{ heta }$ and one of its fully nonparametric estimators. We consider in particular the nonparametric estimator based on the least-absolute deviation loss constructed in Colling and Van Keilegom (2019). We establish the consistency and the asymptotic normality of the two proposed estimators of $ heta $. We also carry out a simulation study to illustrate and compare the performance of our new parametric estimators to that of the profile likelihood estimator constructed in Linton et al. (2008).

The wavelet scattering transform is an invariant and stable signal representation suitable for many signal processing and machine learning applications. We present the Kymatio software package, an easy-to-use, high-performance Python implementation of the scattering transform in 1D, 2D, and 3D that is compatible with modern deep learning frameworks, including PyTorch and TensorFlow/Keras. The transforms are implemented on both CPUs and GPUs, the latter offering a significant speedup over the former. The package also has a small memory footprint. Source code, documentation, and examples are available under a BSD license at https://www.kymat.io.

Datasets in sleep science present challenges for machine learning algorithms due to differences in recording setups across clinics. We investigate two deep transfer learning strategies for overcoming the channel mismatch problem for cases where two datasets do not contain exactly the same setup leading to degraded performance in single-EEG models. Specifically, we train a baseline model on multivariate polysomnography data and subsequently replace the first two layers to prepare the architecture for single-channel electroencephalography data. Using a fine-tuning strategy, our model yields similar performance to the baseline model (F1=0.682 and F1=0.694, respectively), and was significantly better than a comparable single-channel model. Our results are promising for researchers working with small databases who wish to use deep learning models pre-trained on larger databases.

Recent advancements in diagnostic learning and development of gesture-based human machine interfaces have driven surface electromyography (sEMG) towards significant importance. Analysis of hand gestures requires an accurate assessment of sEMG signals. The proposed work presents a novel sequential master-slave architecture consisting of deep neural networks (DNNs) for classification of signs from the Indian sign language using signals recorded from multiple sEMG channels. The performance of the master-slave network is augmented by leveraging additional synthetic feature data generated by long short term memory networks. Performance of the proposed network is compared to that of a conventional DNN prior to and after the addition of synthetic data. Up to 14% improvement is observed in the conventional DNN and up to 9% improvement in master-slave network on addition of synthetic data with an average accuracy value of 93.5% asserting the suitability of the proposed approach.

Edgar Dobriban, William Leeb, Amit Singer.

Source: The Annals of Statistics, Volume 48, Number 1, 491--513.

Abstract:
We consider the linearly transformed spiked model , where the observations $Y_{i}$ are noisy linear transforms of unobserved signals of interest $X_{i}$: egin{equation*}Y_{i}=A_{i}X_{i}+varepsilon_{i},end{equation*} for $i=1,ldots ,n$. The transform matrices $A_{i}$ are also observed. We model the unobserved signals (or regression coefficients) $X_{i}$ as vectors lying on an unknown low-dimensional space. Given only $Y_{i}$ and $A_{i}$ how should we predict or recover their values? The naive approach of performing regression for each observation separately is inaccurate due to the large noise level. Instead, we develop optimal methods for predicting $X_{i}$ by “borrowing strength” across the different samples. Our linear empirical Bayes methods scale to large datasets and rely on weak moment assumptions. We show that this model has wide-ranging applications in signal processing, deconvolution, cryo-electron microscopy, and missing data with noise. For missing data, we show in simulations that our methods are more robust to noise and to unequal sampling than well-known matrix completion methods.

Michael Jauch, Peter D. Hoff, David B. Dunson.

Source: Bernoulli, Volume 26, Number 2, 1560--1586.

Abstract:
Random orthogonal matrices play an important role in probability and statistics, arising in multivariate analysis, directional statistics, and models of physical systems, among other areas. Calculations involving random orthogonal matrices are complicated by their constrained support. Accordingly, we parametrize the Stiefel and Grassmann manifolds, represented as subsets of orthogonal matrices, in terms of Euclidean parameters using the Cayley transform. We derive the necessary Jacobian terms for change of variables formulas. Given a density defined on the Stiefel or Grassmann manifold, these allow us to specify the corresponding density for the Euclidean parameters, and vice versa. As an application, we present a Markov chain Monte Carlo approach to simulating from distributions on the Stiefel and Grassmann manifolds. Finally, we establish that the Euclidean parameters corresponding to a uniform orthogonal matrix can be approximated asymptotically by independent normals. This result contributes to the growing literature on normal approximations to the entries of random orthogonal matrices or transformations thereof.

Contact tracing is a big job, like trying to drain an ocean with a teaspoon. It involves finding people who have been exposed to the coronavirus and testing them to determine if they are infected or are carriers. Public health officials then can take necessary steps to prevent the virus' spread. It's a perfect fit for CRM, and Salesforce's core technology is coming to the forefront.

The enterprise IT environment is complex. Many systems, technologies and practices developed at various times coexist in the same world. With expectations for technological advancements at their peak, we're tasked with enabling these systems to work together harmoniously to support the continuous sharing of information. Systems and data must connect as if all information were native to each.

Did you know that cash transfer (CT) programmes in countries of the sub-Saharan Africa actually have a significant impact? In Malawi, these programmes helped families invest in agricultural equipment and livestock to produce their own food and reduce levels of negative coping strategies, like begging and school drop-outs. In Kenya, secondary school attendance rose by 9 percent and access to [...]

Cash transfer programmes – regular money payments to poor households - aim to reduce poverty, promote sustainable livelihoods and increase production in the developing world. During the past decade, an increasing number of governments in sub-Saharan Africa have launched cash transfer programmes that target the most vulnerable groups, including subsistence farmers, people with disabilities and HIV/AIDS, as well as families [...]

  We can’t really talk about the planet’s most pressing environmental problems without talking about food systems. And by food systems, we also mean the agriculture that it takes to support them: farming, fisheries, forestry and the value chains that provide food and fiber for our daily lives. 

Savage’s Cochran Frog (Centrolene savagei) looking from the edge of a leaf at cloud forest, 1640 masl, this species is endemic to Colombia.

The most commonly used method for production of recombinant adeno-associated virus (rAAVs) in research laboratories is by transient triple transfection of 293 cells with AAV cis and trans plasmids and an adenovirus helper plasmid. This protocol describes the processes required to prepare the transfected cell suspension for virus purification.