Tsung-Heng Tsai
Mar 31, 2020; 0:RA119.001792v1-mcp.RA119.001792
Research

A double Google header as Henry Burrell leads Scott Carey and Sean Bradley down the tech rabbit hole. Alphabet's most famous outlet has redesigned Gmail for desktop, but what does that mean for businesses and consumers. Will anyone notice?

Then what is Chat? Not Google Chat or Android Chat, mind - just Chat. Will the Google-led initiative really transform text messaging on Android or is it doomed to forever to be a fragmented mess?

Sean then talks us through the latest AMD processors to challenge Intel. Intel hasn't had the best of year's after Apple announced it is going solo. Is there a change afoot?

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In bottom-up mass spectrometry-based proteomics, relative protein quantification is often achieved with data-dependent acquisition (DDA), data-independent acquisition (DIA), or selected reaction monitoring (SRM). These workflows quantify proteins by summarizing the abundances of all the spectral features of the protein (e.g., precursor ions, transitions or fragments) in a single value per protein per run. When abundances of some features are inconsistent with the overall protein profile (for technological reasons such as interferences, or for biological reasons such as post-translational modifications), the protein-level summaries and the downstream conclusions are undermined. We propose a statistical approach that automatically detects spectral features with such inconsistent patterns. The detected features can be separately investigated, and if necessary removed from the dataset. We evaluated the proposed approach on a series of benchmark controlled mixtures and biological investigations with DDA, DIA and SRM data acquisitions. The results demonstrated that it can facilitate and complement manual curation of the data. Moreover, it can improve the estimation accuracy, sensitivity and specificity of detecting differentially abundant proteins, and reproducibility of conclusions across different data processing tools. The approach is implemented as an option in the open-source R-based software MSstats.

You can create create a Databricks table by using PROC SQL, but you cannot insert data into the table. PROC APPEND cannot create a new table or append data to an existing table.

Type 2 diabetes mellitus predicts outcome following acute myocardial infarction (AMI). Since underlying mechanics are incompletely understood, we investigated left ventricular (LV) and atrial (LA) pathophysiological changes and their prognostic implications using cardiovascular magnetic resonance (CMR). Consecutive patients (n=1147, n=265 diabetic; n=882 non-diabetic) underwent CMR 3 days after AMI. Analyses included LV ejection fraction (LVEF), global longitudinal, circumferential and radial strains (GLS, GCS and GRS), LA reservoir, conduit and booster pump strains, as well as infarct size, edema and microvascular obstruction. Predefined endpoints were major adverse cardiovascular events (MACE) within 12 months. Diabetic patients had impaired LA reservoir (19.8 vs. 21.2%, p<0.01) and conduit strains (7.6 vs. 9.0%, p<0.01) but not ventricular function or myocardial damage. They were at higher risk of MACE than non-diabetic patients (10.2% vs. 5.8%, p<0.01) with most MACE occurring in patients with LVEF≥35%. Whilst LVEF (p=0.045) and atrial reservoir strain (p=0.024) were independent predictors of MACE in non-diabetic patients, GLS was in diabetic patients (p=0.010). Considering patients with diabetes and LVEF≥35% (n=237), GLS and LA reservoir strain below median were significantly associated with MACE. In conclusion, in patients with diabetes, LA and LV longitudinal strain permit optimized risk assessment early after reperfused AMI with incremental prognostic value over and above LVEF.

Emerging film-makers will have the opportunity to produce a short film based on the theme ‘My Windrush Story – What Windrush Means to Me’ as part of the Windrush Caribbean Film Festival (WCFF), which will be held later this year as part of Black...

Giulio Marchesini
Aug 1, 2001; 50:1844-1850
Pathophysiology

OBJECTIVE

Type 2 diabetes develops for many years before diagnosis. We aimed to reveal early metabolic features characterizing liability to adult disease by examining genetic liability to adult type 2 diabetes in relation to metabolomic traits across early life.

Since the beginning, Inoreader was meant to be a power-user tool, pushing the boundaries of what RSS readers can do.…

Have you ever tried to convince somebody to start using an RSS reader, only to hear back from them something…

Feature screening is a powerful tool in processing high-dimensional data. When the sample size N and the number of features p are both large, the implementation of classic screening methods can be numerically challenging. In this paper, we propose a distributed screening framework for big data setup. In the spirit of 'divide-and-conquer', the proposed framework expresses a correlation measure as a function of several component parameters, each of which can be distributively estimated using a natural U-statistic from data segments. With the component estimates aggregated, we obtain a final correlation estimate that can be readily used for screening features. This framework enables distributed storage and parallel computing and thus is computationally attractive. Due to the unbiased distributive estimation of the component parameters, the final aggregated estimate achieves a high accuracy that is insensitive to the number of data segments m. Under mild conditions, we show that the aggregated correlation estimator is as efficient as the centralized estimator in terms of the probability convergence bound and the mean squared error rate; the corresponding screening procedure enjoys sure screening property for a wide range of correlation measures. The promising performances of the new method are supported by extensive numerical examples.

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.

The ability of intelligent agents to learn and remember multiple tasks sequentially is crucial to achieving artificial general intelligence. Many continual learning (CL) methods have been proposed to overcome catastrophic forgetting. Catastrophic forgetting notoriously impedes the sequential learning of neural networks as the data of previous tasks are unavailable. In this paper we focus on class incremental learning, a challenging CL scenario, in which classes of each task are disjoint and task identity is unknown during test. For this scenario, generative replay is an effective strategy which generates and replays pseudo data for previous tasks to alleviate catastrophic forgetting. However, it is not trivial to learn a generative model continually for relatively complex data. Based on recently proposed orthogonal weight modification (OWM) algorithm which can keep previously learned input-output mappings invariant approximately when learning new tasks, we propose to directly generate and replay feature. Empirical results on image and text datasets show our method can improve OWM consistently by a significant margin while conventional generative replay always results in a negative effect. Our method also beats a state-of-the-art generative replay method and is competitive with a strong baseline based on real data storage.

Uplift modeling is a predictive modeling technique that estimates the user-level incremental effect of a treatment using machine learning models. It is often used for targeting promotions and advertisements, as well as for the personalization of product offerings. In these applications, there are often hundreds of features available to build such models. Keeping all the features in a model can be costly and inefficient. Feature selection is an essential step in the modeling process for multiple reasons: improving the estimation accuracy by eliminating irrelevant features, accelerating model training and prediction speed, reducing the monitoring and maintenance workload for feature data pipeline, and providing better model interpretation and diagnostics capability. However, feature selection methods for uplift modeling have been rarely discussed in the literature. Although there are various feature selection methods for standard machine learning models, we will demonstrate that those methods are sub-optimal for solving the feature selection problem for uplift modeling. To address this problem, we introduce a set of feature selection methods designed specifically for uplift modeling, including both filter methods and embedded methods. To evaluate the effectiveness of the proposed feature selection methods, we use different uplift models and measure the accuracy of each model with a different number of selected features. We use both synthetic and real data to conduct these experiments. We also implemented the proposed filter methods in an open source Python package (CausalML).

Wanghuan Chu, Runze Li, Jingyuan Liu, Matthew Reimherr.

Source: The Annals of Applied Statistics, Volume 14, Number 1, 276--298.

Abstract:
Motivated by an empirical analysis of data from a genome-wide association study on obesity, measured by the body mass index (BMI), we propose a two-step gene-detection procedure for generalized varying coefficient mixed-effects models with ultrahigh dimensional covariates. The proposed procedure selects significant single nucleotide polymorphisms (SNPs) impacting the mean BMI trend, some of which have already been biologically proven to be “fat genes.” The method also discovers SNPs that significantly influence the age-dependent variability of BMI. The proposed procedure takes into account individual variations of genetic effects and can also be directly applied to longitudinal data with continuous, binary or count responses. We employ Monte Carlo simulation studies to assess the performance of the proposed method and further carry out causal inference for the selected SNPs.

Georg Lindgren.

Source: Statistical Science, Volume 34, Number 1, 100--128.

Abstract:
We describe and compare how methods based on the classical Rice’s formula for the expected number, and higher moments, of level crossings by a Gaussian process stand up to contemporary numerical methods to accurately deal with crossing related characteristics of the sample paths. We illustrate the relative merits in accuracy and computing time of the Rice moment methods and the exact numerical method, developed since the late 1990s, on three groups of distribution problems, the maximum over a finite interval and the waiting time to first crossing, the length of excursions over a level, and the joint period/amplitude of oscillations. We also treat the notoriously difficult problem of dependence between successive zero crossing distances. The exact solution has been known since at least 2000, but it has remained largely unnoticed outside the ocean science community. Extensive simulation studies illustrate the accuracy of the numerical methods. As a historical introduction an attempt is made to illustrate the relation between Rice’s original formulation and arguments and the exact numerical methods.

Nicole Bohme Carnegie.

Source: Statistical Science, Volume 34, Number 1, 90--93.

Abstract:
With a thorough exposition of the methods and results of the 2016 Atlantic Causal Inference Competition, Dorie et al. have set a new standard for reproducibility and comparability of evaluations of causal inference methods. In particular, the open-source R package aciccomp2016, which permits reproduction of all datasets used in the competition, will be an invaluable resource for evaluation of future methodological developments. Building upon results from Dorie et al., we examine whether a set of potential modifications to Bayesian Additive Regression Trees (BART)—multiple chains in model fitting, using the propensity score as a covariate, targeted maximum likelihood estimation (TMLE), and computing symmetric confidence intervals—have a stronger impact on bias, RMSE, and confidence interval coverage in combination than they do alone. We find that bias in the estimate of SATT is minimal, regardless of the BART formulation. For purposes of CI coverage, however, all proposed modifications are beneficial—alone and in combination—but use of TMLE is least beneficial for coverage and results in considerably wider confidence intervals.

The capacity to process information in conceptual form is a fundamental aspect of human cognition, yet little is known about how this type of information is encoded in the brain. Although the role of sensory and motor cortical areas has been a focus of recent debate, neuroimaging studies of concept representation consistently implicate a network of heteromodal areas that seem to support concept retrieval in general rather than knowledge related to any particular sensory-motor content. We used predictive machine learning on fMRI data to investigate the hypothesis that cortical areas in this "general semantic network" (GSN) encode multimodal information derived from basic sensory-motor processes, possibly functioning as convergence–divergence zones for distributed concept representation. An encoding model based on five conceptual attributes directly related to sensory-motor experience (sound, color, shape, manipulability, and visual motion) was used to predict brain activation patterns associated with individual lexical concepts in a semantic decision task. When the analysis was restricted to voxels in the GSN, the model was able to identify the activation patterns corresponding to individual concrete concepts significantly above chance. In contrast, a model based on five perceptual attributes of the word form performed at chance level. This pattern was reversed when the analysis was restricted to areas involved in the perceptual analysis of written word forms. These results indicate that heteromodal areas involved in semantic processing encode information about the relative importance of different sensory-motor attributes of concepts, possibly by storing particular combinations of sensory and motor features.

SIGNIFICANCE STATEMENT The present study used a predictive encoding model of word semantics to decode conceptual information from neural activity in heteromodal cortical areas. The model is based on five sensory-motor attributes of word meaning (color, shape, sound, visual motion, and manipulability) and encodes the relative importance of each attribute to the meaning of a word. This is the first demonstration that heteromodal areas involved in semantic processing can discriminate between different concepts based on sensory-motor information alone. This finding indicates that the brain represents concepts as multimodal combinations of sensory and motor representations.

It has been proposed that people can generate probabilistic predictions at multiple levels of representation during language comprehension. We used magnetoencephalography (MEG) and electroencephalography (EEG), in combination with representational similarity analysis, to seek neural evidence for the prediction of animacy features. In two studies, MEG and EEG activity was measured as human participants (both sexes) read three-sentence scenarios. Verbs in the final sentences constrained for either animate or inanimate semantic features of upcoming nouns, and the broader discourse context constrained for either a specific noun or for multiple nouns belonging to the same animacy category. We quantified the similarity between spatial patterns of brain activity following the verbs until just before the presentation of the nouns. The MEG and EEG datasets revealed converging evidence that the similarity between spatial patterns of neural activity following animate-constraining verbs was greater than following inanimate-constraining verbs. This effect could not be explained by lexical-semantic processing of the verbs themselves. We therefore suggest that it reflected the inherent difference in the semantic similarity structure of the predicted animate and inanimate nouns. Moreover, the effect was present regardless of whether a specific word could be predicted, providing strong evidence for the prediction of coarse-grained semantic features that goes beyond the prediction of individual words.

SIGNIFICANCE STATEMENT Language inputs unfold very quickly during real-time communication. By predicting ahead, we can give our brains a "head start," so that language comprehension is faster and more efficient. Although most contexts do not constrain strongly for a specific word, they do allow us to predict some upcoming information. For example, following the context of "they cautioned the...," we can predict that the next word will be animate rather than inanimate (we can caution a person, but not an object). Here, we used EEG and MEG techniques to show that the brain is able to use these contextual constraints to predict the animacy of upcoming words during sentence comprehension, and that these predictions are associated with specific spatial patterns of neural activity.

A collection of 14 restored wooden statues, including a two-ton William IV, will be shown at the Box Museum in England

LACO AT HOME Features Sheku Kanneh-Mason Interview and Performance & More  Broadway World

Apple's latest iOS 13.5 beta release includes a new Health app feature that allows iPhone and Apple Watch users to automatically send Medical ID information to first responders.

My “holiday season” begins and ends with SOLIDWORKS. For me, the “holidays” begin with the new SOLIDWORKS Rollout events, and end with SOLIDWORKS (now 3DEXPERIENCE) World. Yeah, there’s some cider, turkey, and twinkling lights in between, but for me, SOLIDWORKS

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In every new version of SOLIDWORKS there is always some new features that steal all of the attention. In this post i will highlight five favorable features in SOLIDWORKS that may not be as known, but still can help you

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THE Celtic Connections music festival last night lifted the curtain on next year’s line up – and revealed it will be kicking off the 700th celebrations of the Declaration of Arbroath.

Cornelia de Lange syndrome (CdLS) is a genetic syndrome with multisystem abnormalities. Infections are a significant cause of morbidity and mortality in affected patients and are typically attributed to anatomic abnormalities.

This study identified a high frequency of antibody immunodeficiency in CdLS subjects, indicating a critical need for screening and management of immunodeficiency in CdLS patients with a history of severe or recurrent infections. (Read the full article)

The incidence of Kawasaki disease is increasing in many countries. The only reported Australian incidence (3.4/100 000 <5 years) is almost 20 years old and the current Australian epidemiology and outcomes are unknown.

We analyzed 30 years’ total population hospitalization data from Western Australia. Kawasaki disease incidence increased markedly from 1979 to 2009 and is currently 9.34/100 000 <5 years. The epidemiology and cardiovascular outcomes are similar to other predominantly European-Caucasian populations. (Read the full article)

Celiac disease (CD) may develop at any age. Young children with CD are at particular risk for malabsorption and failure to thrive. HLA-DR3-DQ2 homozygotes are at the highest genetic risk and develop CD very early in life.

Most children with CD detected in screening by 4 years of age have no symptoms and normal growth. Symptoms are unrelated to HLA genotype. Autoantibody levels correlate higher with severity of mucosal lesions in symptomatic as compared to asymptomatic children. (Read the full article)

Encephalitis is a serious and disabling condition. There are infectious and immune-mediated causes of encephalitis, but many cases remain undiagnosed.

This large single-center study on childhood encephalitis provides insight into the relative frequency and clinicoradiologic phenotypes of infectious, autoantibody-associated, and unknown encephalitis. Risk factors for an abnormal outcome are also defined. (Read the full article)

Valor Collegiate Academies has been in the top 5 percent of Tennessee schools on growth and achievement every year since it started in 2014. But Tom visited Valor because of the well-regarded Valor Compass, a holistic human-development program.

Nilla Fischer, Fran Kirby and Shanice van de Sanden feature in UEFA's new Strong Is... mini-series.

Google Assistant Scheduled Actions lets you schedule actions in advance—so you can tell your coffee maker to start at 6 a.m. or your air conditioner to stop at 10 p.m.

Activities feature two special programs that explore 18th-century trades and pastimes that might have taken place at the property during the lifetime of the “Penman of the Revolution.”

“William Penn Day” plus readings and historical theater to be featured.

In addition to the film, this free outdoor, family-fun event includes activities, music and food.

YouTube's Video Watch Page gets a new design with larger thumbs and prominently visible comment box. YouTube music adds explore section and lyrics to the video.

To encourage Delawareans to support fall prevention strategies, Governor John Carney and Lieutenant Governor Bethany Hall-Long proclaimed the week of September 22-28, 2019 as Falls Prevention Awareness Week in Delaware. The National Council on Aging (NCOA) designates the first day of the fall season as National Falls Prevention Awareness Day, which is September 23 this year.

Further, the app will also have added features like the e-pass for movement during the restrictions imposed by the government to fight the pandemic.

The new Mercedes-Benz E-Class Elite is the range-topping model and gets a new engine, additional features and more.

The flagship Mahindra, Alturas G4, in its BS6 avatar is Rs 1 lakh expensive and still comes in two variants.

Electric Ambassador on The Grand Tour: DC Design e-Amby is being developed under a new brand called DC2. It is meant to be an all-electric car that draws inspiration from the iconic Ambassador.

The Mahindra XUV500 BS6 gets a minimal price hike and at present, the automatic's prices are yet to be revealed.

The BS6 Mahindra Scorpio drops the entry-level variant as well as is now available only with one diesel engine and 6-speed manual transmission combination.

The Skoda Superb facelift has a 2.0-litre petrol engine and Matrix LED headlights while its competitor will be the Toyota Camry hybrid.

The detailed list of equipment that the 2020 Datsun Redi-Go will offer once it is launched has been leaked online which has revealed that the Redi-Go will feature a new dash that offers an 8-inch touchscreen infotainment system.

The Hyundai Creta and the Kia Seltos are pretty identical underneath sharing the same underpinning. But, each has their USPs and drawbacks. We take look at the interior and feature offerings to see which is better.

Both the Go and Go+ in their BS6 avatars will still be the most affordable modern CVT cars in the market.