Critics said the bill would have allowed teachers to bring in alternative theories about climate change and evolution.

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.

Paul J. Birrell, Lorenz Wernisch, Brian D. M. Tom, Leonhard Held, Gareth O. Roberts, Richard G. Pebody, Daniela De Angelis.

Source: The Annals of Applied Statistics, Volume 14, Number 1, 74--93.

Abstract:
A prompt public health response to a new epidemic relies on the ability to monitor and predict its evolution in real time as data accumulate. The 2009 A/H1N1 outbreak in the UK revealed pandemic data as noisy, contaminated, potentially biased and originating from multiple sources. This seriously challenges the capacity for real-time monitoring. Here, we assess the feasibility of real-time inference based on such data by constructing an analytic tool combining an age-stratified SEIR transmission model with various observation models describing the data generation mechanisms. As batches of data become available, a sequential Monte Carlo (SMC) algorithm is developed to synthesise multiple imperfect data streams, iterate epidemic inferences and assess model adequacy amidst a rapidly evolving epidemic environment, substantially reducing computation time in comparison to standard MCMC, to ensure timely delivery of real-time epidemic assessments. In application to simulated data designed to mimic the 2009 A/H1N1 epidemic, SMC is shown to have additional benefits in terms of assessing predictive performance and coping with parameter nonidentifiability.

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.

The PFC, through its high degree of interconnectivity with cortical and subcortical brain areas, mediates cognitive and emotional processes in support of adaptive behaviors. This includes the formation of fear memories when the anticipation of threat demands learning about temporal or contextual cues, as in trace fear conditioning. In this variant of fear learning, the association of a cue and shock across an empty trace interval of several seconds requires sustained cue-elicited firing in the prelimbic cortex (PL). However, it is unknown how and when distinct PL afferents contribute to different associative components of memory. Among the prominent inputs to PL, the hippocampus shares with PL a role in both working memory and contextual processing. Here we tested the necessity of direct hippocampal input to the PL for the acquisition of trace-cued fear memory and the simultaneously acquired contextual fear association. Optogenetic silencing of ventral hippocampal (VH) terminals in the PL of adult male Long-Evans rats selectively during paired trials revealed that direct communication between the VH and PL during training is necessary for contextual fear memory, but not for trace-cued fear acquisition. The pattern of the contextual memory deficit and the disruption of local PL firing during optogenetic silencing of VH-PL suggest that the VH continuously updates the PL with the current contextual state of the animal, which, when disrupted during memory acquisition, is detrimental to the subsequent rapid retrieval of aversive contextual associations.

SIGNIFICANCE STATEMENT Learning to anticipate threat from available contextual and discrete cues is crucial for survival. The prelimbic cortex is required for forming fear memories when temporal or contextual complexity is involved, as in trace fear conditioning. However, the respective contribution of distinct prelimbic afferents to the temporal and contextual components of memory is not known. We report that direct input from the ventral hippocampus enables the formation of the contextual, but not trace-cued, fear memory necessary for the subsequent rapid expression of a fear response. This finding dissociates the contextual and working-memory contributions of prelimbic cortex to the formation of a fear memory and demonstrates the crucial role for hippocampal input in contextual fear learning.

International Kungfu superstar and renowned Hollywood film actor Jackie Chan has joined FAO in the fight against hunger. In a recent visit to Ethiopia, Chan met with beneficiaries of the ‘Purchase from Africans for Africa’ (PAA) project as well as a South-South Cooperation Programme where he discussed with Chinese experts how they exchange technical knowledge with Ethiopian farmers to help them [...]

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

Some farmers across the province are worried about getting their fuel in time for spring seeding. The Agricultural Producers Association of Saskatchewan says it has been fielding complaints this week about delays at the Co-op cardlock near Moose Jaw.

A St. John's cardiologist says public health restrictions put in place under the COVID-19 pandemic, while justified, may be harming cardiac patients whose procedures have been postponed indefinitely as well as heart patients who are avoiding hospitals.

Readers open up about their mental states.

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

Players from La Liga side Eibar have issued a joint statement expressing their concerns about returning to training and matches while the new coronavirus remains a threat.

One of the two grocery stores in La Loche, Sask., has shut temporarily after one of its employees tested positive for COVID-19, according to an executive at the North West Company. 

This collection of songs heard on Saskatoon Morning will be updated weekly.

Ten properties, including homes and businesses, have already been evacuated as the community braces against rising water levels.

The University of Alberta Pandas defeated the UNB Reds 10-2 in the U Sports women's curling final, while the Laurier Golden Hawks topped the Dalhousie Tigers 8-5 for the men's curling title in Portage la Prairie, Manitoba on Sunday.

Bank of Italy Working Papers by Eleonora Porreca and Alfonso Rosolia

Health care professionals are being punished for protecting themselves, and us.

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.

Denver Newsroom, May 7, 2020 / 03:48 pm (CNA).- For the first time in over a century, the annual May 13 celebrations at the Fatima shrine will take place without the physical presence of pilgrims, the bishop of Fatima confirmed this week.

Cardinal Antonio Marto said in a May 3 statement that the celebrations for the Feast of Our Lady of Fatima “will take place as was announced April 6, without the physical presence of pilgrims, in the name of prudence to avoid the risk of spreading the novel coronavirus.”

“As planned in conjunction with the civil authorities, the May 12 and 13 celebrations for this year cannot have the physical presence of the pilgrims and will be transmitted by broadcast and digital media,” he continued.

The cardinal explained that hosting “an unpredictable multitude of people” gathering at a time when the coronavirus pandemic is still a serious threat would go against the efforts of health authorities to gradually lift restrictions imposed to slow the spread of the virus.

“We therefore respect, in an attitude of collaboration with the competent civil authorities, the guidelines for these celebrations to be held with a symbolic presence of participants,” Marto said.

The clarification over the Fatima feast day came as the Portuguese government gradually begins to ease restrictions that had been put in place in response to the pandemic, prompting speculation over whether the May 13 celebrations would be able to take place as normal. The annual event typically draws hundreds of thousands from around the world to the shrine.

The Portuguese Bishops’ Conference had announced earlier this month that public Masses could tentatively resume the weekend of Pentecost, May 30-31, in accordance with guidelines to be established by the country’s health department and the Catholic Church.

Cardinal Marto stressed that the decision to suspend public religious celebrations was based in a sense of responsibility toward the public health, as a way of loving one’s neighbor.

“[A]s much as our hearts would like to be in Fatima celebrating together in the same place, as has been the case since 1917, prudence counsels us not to do so this time,” he said, adding that Catholics can look forward to an end to the pandemic and an opportunity to gather together joyfully in the future.

Fr. Carlos Cabecinhas, rector of the Shrine of Our Lady of Fatima, encouraged pilgrims who are unable to physically attend the events to make an interior pilgrimage, participating in the events of the Solemnity of Our Lady of Fatima through the internet or social media.

“This is a painful time: the shrine exists to welcome the pilgrims and we cannot do so, this is a cause for great sadness; but this decision is also an act of responsibility toward the pilgrims, protecting their health and welfare,” the priest said.

The shrine’s website offers four steps to guide people on this interior pilgrimage.

According to the website, “the celebrations of May 12 and 13 will maintain the usual schedule with recitation of the Rosary at 9:30 p.m. followed by the Candlelight Procession. On the 13th the Rosary will be prayed at 9:00 a.m. followed by the International Mass and the Farewell Procession.”

In March, 24 countries were consecrated to the Sacred Heart of Jesus and the Immaculate Heart of Mary at the Shrine of Our Lady of Fatima.

At that ceremony, Cardinal Marto recalled that Saints Francisco and Jacinto Marto, shepherd children to whom an angel, and then the Blessed Virgin Mary appeared in 1916 and 1917 at Fatima, both died amid the victims of the Spanish flu pandemic.

To date, Johns Hopkins University has reported 26,182 cases of novel coronavirus in Portugal, with 1089 deaths.

 

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

Author information

The post Top 5 Favorite Features in SOLIDWORKS 2020 appeared first on SOLIDWORKS Tech Blog.

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

Author information

The post Five Favorable Features of SOLIDWORKS appeared first on SOLIDWORKS Tech Blog.

The post Linear Static FEA Productivity with Simulation Professional appeared first on The SOLIDWORKS Blog.

A zeal for the Jezreel Valley overcomes fear and insecurity.

A man expresses thanks to God for good health after cancer by making a sacrifice to God and holding a feast for family and friends.

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.

A few days after a majority of Britons backed Brexit in June 2016, this newspaper reported that Nicola Sturgeon had been in talks with London Mayor Sadiq Khan and the Chief Minister of Gibraltar, Fabian Picardo.

Writers have been ransacking the Brainy Quotes website looking for inspiration for their coronavirus think pieces. But there is really only one that matters: “We have nothing to fear but fear itself”. Franklin D Roosevelt’s epigram is appropriate because it is as disingenuous as it is paradoxical.

SCOTLAND’S universities must play their part in adapting to the “new normal” amid warnings that institutions could be forced to merge in return for government support.

BORIS Johnson has said Britain needs the "same spirit of national endeavour" to defeat the coronavirus as Second World War veterans demonstrated to topple Adolf Hitler.

The appeals court put the brakes on a predominantly white community's racially tinged efforts to secede from a larger school system.

Analysts and business officials wonder if the education technology market faces the risk of a crash, similar to what occurred during the dot-com bust in the 1990s.

Framed prints of Steven Camley's cartoons are available by calling 0141 302 6210

If you have never given your gender much thought, count yourself lucky. If that tick in the box on almost every form requires no more effort than a flick of the wrist, be aware that for many people gender is not so straightforward.

Pediatric obesity is a prevalent public health issue that is associated with medical and physical consequences. Clinic-based interventions for pediatric obesity are effective, but they have limited reach and are costly.

This is the first examination of an empirically informed, scalable treatment of pediatric overweight and obesity delivered in YMCAs. The results indicate that a scalable, community-based pediatric obesity intervention can produce clinically meaningful changes in weight and quality of life. (Read the full article)

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 American Academy of Pediatrics (AAP) and other organizations have recommended critical congenital heart disease (CCHD) pulse oximetry screening. Small studies have revealed lower saturations at higher altitude, but this effect on CCHD screening is unknown. The AAP requested additional studies at altitude to help clarify the dilemma.

The AAP has endorsed higher-altitude studies of CCHD screening. This observational prospective study revealed a higher positive screen rate at moderate altitude than at sea level. These findings suggest that current national recommendations may result in increased screening failures at moderate altitude. (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)

Hypothermia treatment of neonatal encephalopathy reduces death and disability from 66% to 50%; additional neuroprotective therapies are needed. We previously found in animal models that adding 50% xenon to the breathing gas during cooling doubled neuroprotection.

This clinical feasibility study used 50% xenon for 3 to 18 hours in 14 cooled infants with cardiovascular, respiratory, and amplitude-integrated EEG monitoring. This depressed seizures, with no blood pressure reduction. Xenon is ready for randomized clinical trials in newborns. (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)