The millions of customers, the short deadline: how the public service's digital revolution will start.

11 March 2020

This article provides an introduction to Fourier transform-based mass spectrometry (FTMS). The key performance characteristics of FTMS, mass accuracy and resolution, are presented in the view of how they impact the interpretation of measurements in proteomic applications. The theory and principles of operation of two types of mass analyzer, Fourier transform ion cyclotron resonance and Orbitrap, are described. Major benefits as well as limitations of FTMS technology are discussed in the context of practical sample analysis, and illustrated with examples included as figures in this text and in the accompanying slide set. Comparisons highlighting the performance differences between the two mass analyzers are made where deemed useful in assisting the user with choosing the most appropriate technology for his/her application. Recent developments of these high-performing mass spectrometers are mentioned to provide a future outlook.

11 March 2020

If your business key column is a name literal, like " business key "n, a syntax error occurs when that variable name does not follow standard SAS naming conventions.

In SAS Data Integration Studio, the columns that you select to include in the target table in a Business Rules transformation appear in the Selected columns area in a random order. Th

11 March 2020

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 […]

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.

City planning -- Remote sensing.

Biodiversity -- Climatic factors.

Paris : V.A. Delahaye, 1880.

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.

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.

  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. 

Artists from Michigan and around the world are painting 50 murals in Flint to refocus the city's image on art rather than the lead-tainted water crisis.

An Albanian man's heart is forever changed after suffering a heart attack and meeting Jesus in his recuperation.

A woman and her husband accept the Lord after hearing the gospel from an OM team visiting the island of Sante Marie.

Despite knowing very little about the Androy region, OMers Fara and Herimanina went willingly and have seen God at work.

The impact of baseball as an outreach tool is growing far beyond the first teams that began nine years ago in Érd.

Over an eight-day period, 18 Ride2Transform cyclists travelled 690 kilometers, participating in a personal journey with the Lord and praying for the country of Malawi.

Read about how a short term missions trip to a Muslim country changed a US pastor's life! Click to read more!

God not only rescued Kamil and Klaudia's marriage but also transformed their relationships with Him.

It's an unforgettable experience!” OM Mexico’s missions training impacts one participant’s life, who then returns to the training as a staff member.

A worker becomes friends with twin sisters and sees God transform both lives.

A remarkable story which came to a climax on February 23 this year when OM Ireland took possession of the deeds to Lacken House as their new headquarters and ministry centre.

One Irish family experienced the transforming love of God...one woman at a time.

Turning organic waste into bio-fuel and French-fry oil into bio-diesel; all these are innovative ways of building sustainable income for the church in Kaharlyk.

Lighthouse Ministries builds a kitchen to transform a community in Panama.

Crave pragmatic, honest, clear-eyed conversation about the realities of ed tech? Here's a reading list from Education Week, as presented at ISTE 2019.

Fewer than one-third of America's teachers say ed-tech innovations have changed their beliefs about what school should look like, according to a new Education Week survey.

An Albanian man's heart is forever changed after suffering a heart attack and meeting Jesus in his recuperation.

Participate in a chat about how multimedia tools are transforming teaching and learning in core academic subjects.

Two things are true as I sort through my reflections on transformative learning experiences: We need intensive, immersive opportunities for learning (such as a trip to Kenya) and we also need to build in mini-opportunities for transformative learning every day.

An Albanian man's heart is forever changed after suffering a heart attack and meeting Jesus in his recuperation.

An Albanian man's heart is forever changed after suffering a heart attack and meeting Jesus in his recuperation.

An Albanian man's heart is forever changed after suffering a heart attack and meeting Jesus in his recuperation.