A bill prohibiting anti-Semitism in Florida's public schools and universities is going to Republican Gov. Ron DeSantis.

Heiko Werner, Hajo Holzmann, Pierre Vandekerkhove.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 1816--1871.

Abstract:
We investigate a flexible two-component semiparametric mixture of regressions model, in which one of the conditional component distributions of the response given the covariate is unknown but assumed symmetric about a location parameter, while the other is specified up to a scale parameter. The location and scale parameters together with the proportion are allowed to depend nonparametrically on covariates. After settling identifiability, we provide local M-estimators for these parameters which converge in the sup-norm at the optimal rates over Hölder-smoothness classes. We also introduce an adaptive version of the estimators based on the Lepski-method. Sup-norm bounds show that the local M-estimator properly estimates the functions globally, and are the first step in the construction of useful inferential tools such as confidence bands. In our analysis we develop general results about rates of convergence in the sup-norm as well as adaptive estimation of local M-estimators which might be of some independent interest, and which can also be applied in various other settings. We investigate the finite-sample behaviour of our method in a simulation study, and give an illustration to a real data set from bioinformatics.

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).

This paper considers a Bayesian approach to graph-based semi-supervised learning. We show that if the graph parameters are suitably scaled, the graph-posteriors converge to a continuum limit as the size of the unlabeled data set grows. This consistency result has profound algorithmic implications: we prove that when consistency holds, carefully designed Markov chain Monte Carlo algorithms have a uniform spectral gap, independent of the number of unlabeled inputs. Numerical experiments illustrate and complement the theory.

Durba Bhattacharya, Sourabh Bhattacharya.

Source: Brazilian Journal of Probability and Statistics, Volume 34, Number 1, 71--89.

Abstract:
Present day bio-medical research is pointing towards the fact that cognizance of gene–environment interactions along with genetic interactions may help prevent or detain the onset of many complex diseases like cardiovascular disease, cancer, type2 diabetes, autism or asthma by adjustments to lifestyle. In this regard, we propose a Bayesian semiparametric model to detect not only the roles of genes and their interactions, but also the possible influence of environmental variables on the genes in case-control studies. Our model also accounts for the unknown number of genetic sub-populations via finite mixtures composed of Dirichlet processes. An effective parallel computing methodology, developed by us harnesses the power of parallel processing technology to increase the efficiencies of our conditionally independent Gibbs sampling and Transformation based MCMC (TMCMC) methods. Applications of our model and methods to simulation studies with biologically realistic genotype datasets and a real, case-control based genotype dataset on early onset of myocardial infarction (MI) have yielded quite interesting results beside providing some insights into the differential effect of gender on MI.

Didier Chauveau, David R. Hunter, Michael Levine.

Source: Statistics Surveys, Volume 9, 1--31.

Abstract:
The conditional independence assumption for nonparametric multivariate finite mixture models, a weaker form of the well-known conditional independence assumption for random effects models for longitudinal data, is the subject of an increasing number of theoretical and algorithmic developments in the statistical literature. After presenting a survey of this literature, including an in-depth discussion of the all-important identifiability results, this article describes and extends an algorithm for estimation of the parameters in these models. The algorithm works for any number of components in three or more dimensions. It possesses a descent property and can be easily adapted to situations where the data are grouped in blocks of conditionally independent variables. We discuss how to adapt this algorithm to various location-scale models that link component densities, and we even adapt it to a particular class of univariate mixture problems in which the components are assumed symmetric. We give a bandwidth selection procedure for our algorithm. Finally, we demonstrate the effectiveness of our algorithm using a simulation study and two psychometric datasets.

When the response mechanism is believed to be not missing at random (NMAR), a valid analysis requires stronger assumptions on the response mechanism than standard statistical methods would otherwise require. Semiparametric estimators have been developed under the model assumptions on the response mechanism. In this paper, a new statistical test is proposed to guarantee model identifiability without using any instrumental variable. Furthermore, we develop optimal semiparametric estimation for parameters such as the population mean. Specifically, we propose two semiparametric optimal estimators that do not require any model assumptions other than the response mechanism. Asymptotic properties of the proposed estimators are discussed. An extensive simulation study is presented to compare with some existing methods. We present an application of our method using Korean Labor and Income Panel Survey data.

Sparse estimation via penalized likelihood (PL) is now a popular approach to learn the associations among a large set of variables. This paper describes an R package called lslx that implements PL methods for semi-confirmatory structural equation modeling (SEM). In this semi-confirmatory approach, each model parameter can be specified as free/fixed for theory testing, or penalized for exploration. By incorporating either a L1 or minimax concave penalty, the sparsity pattern of the parameter matrix can be efficiently explored. Package lslx minimizes the PL criterion through a quasi-Newton method. The algorithm conducts line search and checks the first-order condition in each iteration to ensure the optimality of the obtained solution. A numerical comparison between competing packages shows that lslx can reliably find PL estimates with the least time. The current package also supports other advanced functionalities, including a two-stage method with auxiliary variables for missing data handling and a reparameterized multi-group SEM to explore population heterogeneity.

This paper is devoted to the R package JSM which performs joint statistical modeling of survival and longitudinal data. In biomedical studies it has been increasingly common to collect both baseline and longitudinal covariates along with a possibly censored survival time. Instead of analyzing the survival and longitudinal outcomes separately, joint modeling approaches have attracted substantive attention in the recent literature and have been shown to correct biases from separate modeling approaches and enhance information. Most existing approaches adopt a linear mixed effects model for the longitudinal component and the Cox proportional hazards model for the survival component. We extend the Cox model to a more general class of transformation models for the survival process, where the baseline hazard function is completely unspecified leading to semiparametric survival models. We also offer a non-parametric multiplicative random effects model for the longitudinal process in JSM in addition to the linear mixed effects model. In this paper, we present the joint modeling framework that is implemented in JSM, as well as the standard error estimation methods, and illustrate the package with two real data examples: a liver cirrhosis data and a Mayo Clinic primary biliary cirrhosis data.

The History of Pre-Modern Medicine seminar series returns this month. The 2017–18 series – organised by a group of historians of medicine based at London universities and hosted by the Wellcome Library – will conclude with four seminars. The series… Continue reading

Francesco Bravo, Juan Carlos Escanciano, Ingrid Van Keilegom.

Source: The Annals of Statistics, Volume 48, Number 1, 1--26.

Abstract:
In both parametric and certain nonparametric statistical models, the empirical likelihood ratio satisfies a nonparametric version of Wilks’ theorem. For many semiparametric models, however, the commonly used two-step (plug-in) empirical likelihood ratio is not asymptotically distribution-free, that is, its asymptotic distribution contains unknown quantities, and hence Wilks’ theorem breaks down. This article suggests a general approach to restore Wilks’ phenomenon in two-step semiparametric empirical likelihood inferences. The main insight consists in using as the moment function in the estimating equation the influence function of the plug-in sample moment. The proposed method is general; it leads to a chi-squared limiting distribution with known degrees of freedom; it is efficient; it does not require undersmoothing; and it is less sensitive to the first-step than alternative methods, which is particularly appealing for high-dimensional settings. Several examples and simulation studies illustrate the general applicability of the procedure and its excellent finite sample performance relative to competing methods.

Bo Zhou, Ramon van den Akker, Bas J. M. Werker.

Source: The Annals of Statistics, Volume 47, Number 5, 2601--2638.

Abstract:
We propose a new class of unit root tests that exploits invariance properties in the Locally Asymptotically Brownian Functional limit experiment associated to the unit root model. The invariance structures naturally suggest tests that are based on the ranks of the increments of the observations, their average and an assumed reference density for the innovations. The tests are semiparametric in the sense that they are valid, that is, have the correct (asymptotic) size, irrespective of the true innovation density. For a correctly specified reference density, our test is point-optimal and nearly efficient. For arbitrary reference densities, we establish a Chernoff–Savage-type result, that is, our test performs as well as commonly used tests under Gaussian innovations but has improved power under other, for example, fat-tailed or skewed, innovation distributions. To avoid nonparametric estimation, we propose a simplified version of our test that exhibits the same asymptotic properties, except for the Chernoff–Savage result that we are only able to demonstrate by means of simulations.

Anru Zhang, Lawrence D. Brown, T. Tony Cai.

Source: The Annals of Statistics, Volume 47, Number 5, 2538--2566.

Abstract:
We propose a general semi-supervised inference framework focused on the estimation of the population mean. As usual in semi-supervised settings, there exists an unlabeled sample of covariate vectors and a labeled sample consisting of covariate vectors along with real-valued responses (“labels”). Otherwise, the formulation is “assumption-lean” in that no major conditions are imposed on the statistical or functional form of the data. We consider both the ideal semi-supervised setting where infinitely many unlabeled samples are available, as well as the ordinary semi-supervised setting in which only a finite number of unlabeled samples is available. Estimators are proposed along with corresponding confidence intervals for the population mean. Theoretical analysis on both the asymptotic distribution and $ell_{2}$-risk for the proposed procedures are given. Surprisingly, the proposed estimators, based on a simple form of the least squares method, outperform the ordinary sample mean. The simple, transparent form of the estimator lends confidence to the perception that its asymptotic improvement over the ordinary sample mean also nearly holds even for moderate size samples. The method is further extended to a nonparametric setting, in which the oracle rate can be achieved asymptotically. The proposed estimators are further illustrated by simulation studies and a real data example involving estimation of the homeless population.

Joseph Antonelli, Maitreyi Mazumdar, David Bellinger, David Christiani, Robert Wright, Brent Coull.

Source: The Annals of Applied Statistics, Volume 14, Number 1, 257--275.

Abstract:
Humans are routinely exposed to mixtures of chemical and other environmental factors, making the quantification of health effects associated with environmental mixtures a critical goal for establishing environmental policy sufficiently protective of human health. The quantification of the effects of exposure to an environmental mixture poses several statistical challenges. It is often the case that exposure to multiple pollutants interact with each other to affect an outcome. Further, the exposure-response relationship between an outcome and some exposures, such as some metals, can exhibit complex, nonlinear forms, since some exposures can be beneficial and detrimental at different ranges of exposure. To estimate the health effects of complex mixtures, we propose a flexible Bayesian approach that allows exposures to interact with each other and have nonlinear relationships with the outcome. We induce sparsity using multivariate spike and slab priors to determine which exposures are associated with the outcome and which exposures interact with each other. The proposed approach is interpretable, as we can use the posterior probabilities of inclusion into the model to identify pollutants that interact with each other. We utilize our approach to study the impact of exposure to metals on child neurodevelopment in Bangladesh and find a nonlinear, interactive relationship between arsenic and manganese.

Bret Zeldow, Vincent Lo Re III, Jason Roy.

Source: The Annals of Applied Statistics, Volume 13, Number 3, 1989--2010.

Abstract:
Bayesian Additive Regression Trees (BART) is a flexible machine learning algorithm capable of capturing nonlinearities between an outcome and covariates and interactions among covariates. We extend BART to a semiparametric regression framework in which the conditional expectation of an outcome is a function of treatment, its effect modifiers, and confounders. The confounders are allowed to have unspecified functional form, while treatment and effect modifiers that are directly related to the research question are given a linear form. The result is a Bayesian semiparametric linear regression model where the posterior distribution of the parameters of the linear part can be interpreted as in parametric Bayesian regression. This is useful in situations where a subset of the variables are of substantive interest and the others are nuisance variables that we would like to control for. An example of this occurs in causal modeling with the structural mean model (SMM). Under certain causal assumptions, our method can be used as a Bayesian SMM. Our methods are demonstrated with simulation studies and an application to dataset involving adults with HIV/Hepatitis C coinfection who newly initiate antiretroviral therapy. The methods are available in an R package called semibart.

Tom Alberts, Firas Rassoul-Agha, Mackenzie Simper.

Source: Bernoulli, Volume 26, Number 3, 1927--1955.

Abstract:
We prove that given any fixed asymptotic velocity, the finite length O’Connell–Yor polymer has an infinite length limit satisfying the law of large numbers with this velocity. By a Markovian property of the quenched polymer this reduces to showing the existence of Busemann functions : almost sure limits of ratios of random point-to-point partition functions. The key ingredients are the Burke property of the O’Connell–Yor polymer and a comparison lemma for the ratios of partition functions. We also show the existence of infinite length limits in the Brownian last passage percolation model.

Richard A. Davis, Mikkel Slot Nielsen, Victor Rohde.

Source: Bernoulli, Volume 26, Number 2, 799--827.

Abstract:
In this paper, we introduce a model, the stochastic fractional delay differential equation (SFDDE), which is based on the linear stochastic delay differential equation and produces stationary processes with hyperbolically decaying autocovariance functions. The model departs from the usual way of incorporating this type of long-range dependence into a short-memory model as it is obtained by applying a fractional filter to the drift term rather than to the noise term. The advantages of this approach are that the corresponding long-range dependent solutions are semimartingales and the local behavior of the sample paths is unaffected by the degree of long memory. We prove existence and uniqueness of solutions to the SFDDEs and study their spectral densities and autocovariance functions. Moreover, we define a subclass of SFDDEs which we study in detail and relate to the well-known fractionally integrated CARMA processes. Finally, we consider the task of simulating from the defining SFDDEs.

Alexander Schnurr.

Source: Bernoulli, Volume 26, Number 1, 642--663.

Abstract:
We extend the class of semimartingales in a natural way. This allows us to incorporate processes having paths that leave the state space $mathbb{R}^{d}$. In particular, Markov processes related to sub-Markovian kernels, but also non-Markovian processes with path-dependent behavior. By carefully distinguishing between two killing states, we are able to introduce a fourth semimartingale characteristic which generalizes the fourth part of the Lévy quadruple. Using the probabilistic symbol, we analyze the close relationship between the generators of certain Markov processes with killing and their (now four) semimartingale characteristics.

Eric Beutner, Laurent Bordes, Laurent Doyen.

Source: Bernoulli, Volume 26, Number 1, 557--586.

Abstract:
Virtual age models are very useful to analyse recurrent events. Among the strengths of these models is their ability to account for treatment (or intervention) effects after an event occurrence. Despite their flexibility for modeling recurrent events, the number of applications is limited. This seems to be a result of the fact that in the semiparametric setting all the existing results assume the virtual age function that describes the treatment (or intervention) effects to be known. This shortcoming can be overcome by considering semiparametric virtual age models with parametrically specified virtual age functions. Yet, fitting such a model is a difficult task. Indeed, it has recently been shown that for these models the standard profile likelihood method fails to lead to consistent estimators. Here we show that consistent estimators can be constructed by smoothing the profile log-likelihood function appropriately. We show that our general result can be applied to most of the relevant virtual age models of the literature. Our approach shows that empirical process techniques may be a worthwhile alternative to martingale methods for studying asymptotic properties of these inference methods. A simulation study is provided to illustrate our consistency results together with an application to real data.

Abhishek Bishoyi, Xiaojing Wang, Dipak K. Dey.

Source: Bayesian Analysis, Volume 15, Number 1, 215--239.

Abstract:
Missing data often appear as a practical problem while applying classical models in the statistical analysis. In this paper, we consider a semiparametric regression model in the presence of missing covariates for nonparametric components under a Bayesian framework. As it is known that Gaussian processes are a popular tool in nonparametric regression because of their flexibility and the fact that much of the ensuing computation is parametric Gaussian computation. However, in the absence of covariates, the most frequently used covariance functions of a Gaussian process will not be well defined. We propose an imputation method to solve this issue and perform our analysis using Bayesian inference, where we specify the objective priors on the parameters of Gaussian process models. Several simulations are conducted to illustrate effectiveness of our proposed method and further, our method is exemplified via two real datasets, one through Langmuir equation, commonly used in pharmacokinetic models, and another through Auto-mpg data taken from the StatLib library.

Stefano Peluso, Siddhartha Chib, Antonietta Mira.

Source: Bayesian Analysis, Volume 14, Number 3, 727--751.

Abstract:
We develop a general Bayesian semiparametric change-point model in which separate groups of structural parameters (for example, location and dispersion parameters) can each follow a separate multiple change-point process, driven by time-dependent transition matrices among the latent regimes. The distribution of the observations within regimes is unknown and given by a Dirichlet process mixture prior. The properties of the proposed model are studied theoretically through the analysis of inter-arrival times and of the number of change-points in a given time interval. The prior-posterior analysis by Markov chain Monte Carlo techniques is developed on a forward-backward algorithm for sampling the various regime indicators. Analysis with simulated data under various scenarios and an application to short-term interest rates are used to show the generality and usefulness of the proposed model.

Sijia Xiang, Weixin Yao, Guangren Yang.

Source: Statistical Science, Volume 34, Number 3, 391--404.

Abstract:
Finite mixture models have offered a very important tool for exploring complex data structures in many scientific areas, such as economics, epidemiology and finance. Semiparametric mixture models, which were introduced into traditional finite mixture models in the past decade, have brought forth exciting developments in their methodologies, theories, and applications. In this article, we not only provide a selective overview of the newly-developed semiparametric mixture models, but also discuss their estimation methodologies, theoretical properties if applicable, and some open questions. Recent developments are also discussed.

This photo was taken from the Tunnel View at Yosemite National Park. The photo is of Bridalveil Fall consumed by smoke due to controlled burning on the Yosemite Valley floor.

Imagining America between the crisis and the cure.

OM Ukraine and experts in crisis management held a seminar for pastors serving on both sides of the conflict line in Eastern Ukraine.

THE SRU would be “very happy” to host the Scottish Cup semi-final between Heart of Midlothian and Hibernian at BT Murrayfield, the governing body’s Chief Operating Officer revealed yesterday.

Spanish co-hosts Inter FS and Barcelona will face off in the UEFA Futsal Cup semi-finals after being drawn together in the last four of this year's event in Zaragoza, while Győr face Sporting CP.

Team news, coaches' views, form guide and key stats as Germany meet Romania.

Spain take on France in a heavyweight semi-final – here's all you need to know.

CNA Staff, May 2, 2020 / 04:30 pm (CNA).- A man claiming to have killed the murdered Nigerian seminarian Michael Nnadi has given an interview in which he says he executed the aspiring priest because he would not stop announcing the Christian faith in captivity.

Mustapha Mohammed, who is currently in jail, gave a telephone interview to the Nigerian newspaper Daily Sun on Friday. He took responsibility for the murder, according to the Daily Sun, because Nnadi, 18 years old, “continued preaching the gospel of Jesus Christ” to his captors.

According to the newspaper, Mustapha praised Nnadi’s “outstanding bravery,” and that the seminarian “told him to his face to change his evil ways or perish.”

Nnadi was kidnapped by gunmen from Good Shepherd Seminary in Kaduna on January 8, along with three other students. The seminary, home to some 270 seminarians, is located just off the Abuja-Kaduna-Zaria Express Way. According to AFP, the area is “notorious for criminal gangs kidnapping travelers for ransom.”

Mustapha, 26, identified himself as the leader of a 45-member gang that preyed along the highway. He gave the interview from a jail in Abuja, Nigeria, where he is in police custody.

On the evening of the abduction, gunmen, disguised in military camouflage, broke through the fence surrounding the seminarians' living quarters and opened fire. They stole laptops and phones before kidnapping the four young men.

Ten days after the abduction, one of the four seminarians was found on the side of a road, alive but seriously injured. On Jan. 31, an official at Good Shepherd Seminary announced that another two seminarians had been released, but that Nnadi remained missing and was presumed still in captivity.

On Feb. 1, Bishop Matthew Hassan Kukah of the Diocese of Sokoto, Nigeria, announced that Nnadi had been killed.

“With a very heavy heart, I wish to inform you that our dear son, Michael was murdered by the bandits on a date we cannot confirm,” the bishop said, confirming that the rector of the seminary had identified Nnadi’s body.

The newspaper reported that from “the first day Nnadi was kidnapped alongside three of his other colleagues, he did not allow [Mustapha] to have peace,” because he insisted on announcing the gospel to him.

According to the newspaper, Mustapha “did not like the confidence displayed by the young man and decided to send him to an early grave.”

According to the Daily Sun, Mustapha targeted the seminary knowing it was a center for training priests, and that a gang member who lived nearby had helped conduct surveillance ahead of the attack. Mohammed believed that it would be a profitable target for theft and ransom.

Mohammed also said that the gang used Nnadi’s mobile telephone to issue their ransom demands, asking for more than $250,000, later reduced to $25,000, to secure the release of the three surviving students, Pius Kanwai, 19; Peter Umenukor, 23; and Stephen Amos, 23.

Nnadi’s murder is one of an series of attacks and killings on Christians in the country in recent months.

Archbishop Ignatius Kaigama of Abuja called on Nigerian President Muhammadu Buhari to address the violence and kidnappings in a homily March 1 at a Mass with the Catholic Bishops’ Conference of Nigeria.

“We need to have access to our leaders; president, vice president. We need to work together to eradicate poverty, killings, bad governance and all sorts of challenges facing us as a nation,” Kaigama said.

In an Ash Wednesday letter to Nigerian Catholics, Archbishop Augustine Obiora Akubeze of Benin City called for Catholics to wear black in solidarity with victims and pray, in response to “repeated” executions of Christians by Boko Haram and “incessant” kidnappings “linked to the same groups.”

Other Christian villages have been attacked, farms set ablaze, vehicles carrying Christians attacked, men and women have been killed and kidnapped, and women have been taken as sex slaves and tortured—a “pattern,” he said, of targeting Christians.

On Feb. 27, U.S Ambassador at Large for Religious Freedom Sam Brownback told CNA that the situation in Nigeria was deteriorating.

“There's a lot of people getting killed in Nigeria, and we're afraid it is going to spread a great deal in that region,” he told CNA. “It is one that's really popped up on my radar screens -- in the last couple of years, but particularly this past year.”

“I think we’ve got to prod the [Nigerian President Muhammadu] Buhari government more. They can do more,” he said. “They’re not bringing these people to justice that are killing religious adherents. They don’t seem to have the sense of urgency to act.”

Manchester City defeated Liverpool on penalties to set up a semi-final with Barcelona, victors at Atlético Madrid, while Porto beat Tottenham Hotspur and face Chelsea, who won at Real Madrid.

An executive order signed this week is meant to address concerns of anti-Semitism on college and university campuses. But the legal underpinnings of that order apply to elementary and secondary schools, too.

Azamat was living in the streets, but through the ministry of OM team members in Central Asia he moved into rehabilitation and then seminary.

The 2014 Delaware Arborist and Tree Care Seminar will be held on March 4 and 5 at Baywood Greens in Long Neck, Sussex County. Cost is $80 with lunch included. Register at delawaretrees.com.

The Fifth Annual Delaware Arborist and Tree Care Seminar will be held on March 3 and 4 from 8 a.m. to 4 p.m. each day at Hagley Museum & Soda House, 298 Buck Road, Wilmington, DE 19807. Sponsored by the Delaware Forest Service’s Urban and Community Forestry Program, the annual gathering offers classroom lectures, hands-on training, and on-site exhibits offering the latest knowledge and techniques for those interested in proper tree care and safety. This year's topics will include: crane safety for tree care workers, pesticide application, mature tree care and hazard risk assessment, new tree and shrub introductions, and how to use i-Tree to assess and manage urban forests. Cost is $90 with lunch included.

The 6th Annual Delaware Arborist and Tree Care Seminar will be November 2 and 3, 2016 from 7:30 a.m. to 3:30 p.m. at Delaware State University, 1200 N. DuPont Highway, Dover. Sponsored by the Delaware Forest Service Urban and Community Forestry Program, the seminar includes classroom lectures, hands-on training, and vendor exhibits offering the latest knowledge and best management practices on tree care, health, and tree worker safety. Continuing education credits for International Society of Arboriculture certification, Tree Care Industry Association and its Certified Tree Care Professional program, Delaware pesticide licensing, and Maryland Licensed Tree Expert certification will be offered. Major sponsors for the 2016 event include Delaware State University, Delmarva Power and Rainbow Scientific. Cost is $95 with lunch included both days.

The Delaware Forest Service's urban and community forestry program will hold its 7th Annual Delaware Arborist and Tree Care Seminar—a one and a half-day event on October 30 and 31, 2017 at the Delaware State Fairgrounds Exhibit Hall. Speakers include tree care experts, policymakers, and academic researchers who will incorporate classroom lectures, outdoor demonstrations, and vendor exhibits to cover tree pest and disease issues, tree care management, and best practices in worker safety and pesticide use. Attendees can earn continuing education credits toward International Society of Arboriculture and Maryland Licensed Tree Expert certifications, as well as Delaware pesticide credits. Cost is $95 for both days (meals and snacks included). To register, go to delawaretrees.com. For more information, email Kesha.Braunskill@state.de.us.

The Delaware Forest Service's Urban and Community Forestry Program will hold its 8th Annual Delaware Arborist and Tree Care Seminar on Wednesday, October 10, and Thursday, October 11, 2018 at the Delaware State Fair Exhibit Hall, 18500 S. DuPont Highway, Harrington. The event offers a wide range of topics for tree care workers as well as anyone who wants to ensure the health of their community trees. The event brings together a diverse blend of industry insiders, policymakers, tree care experts, and academic researchers who will incorporate classroom lectures, outdoor demonstrations and vendor exhibits to provide the latest updates on tree health issues and practical hands-on training. Attendees are eligible to earn continuing credits from the International Society of Arboriculture, Maryland Licensed Tree Expert, and Delaware pesticide certification.  The cost is $95 for two days with breakfast, lunch and snacks included each day. All major credit cards accepted. Attendees can sign up by clicking the “Online Registration” icon at http://delawaretrees.com

The Delaware Forest Service's urban and community forestry program will hold the 9th Annual Delaware Arborist and Tree Care Seminar on October 22 and 23, 2019 at the Delaware State Fairgrounds Exhibit Hall in Harrington. While targeted to tree care industry professionals, the event is open to the public and anyone who wants to create healthier communities through trees.  The cost is $100 for both days (includes lunch on the first day only and snacks). All major credit cards accepted. The agenda covers one full-day session on Oct. 22 and one half-day session on Oct. 23. Attendees can learn the latest developments in tree care through lectures by academic and industry experts, outdoor demos, and vendor exhibits featuring the latest equipment and technology. Learn more at http://delawaretrees.com

As per reports, in India, every year 10,000 children are being born with thalassemia which approximately accounts for 10% of the total world incidence of thalassemia-affected children and one in eight of thalassemia carriers live in India.

There is only one cure for Thalassemia major at present, which is a bone marrow transplant with a suitable donor.

The state government, however, is reluctant to close down its own string of IMFL (Indian made foreign liquor) outlets, which net an annual revenue of Rs 14,508 crore.

Persistent rain since morning delayed the toss and eventually the semifinal was called off without a ball being bowled, taking Indians into the summit clash and leaving England players in tears.

Differentiating good IP from mediocre or bad IP is getting more difficult, in part because it depends upon how and where it is used and in part, because even the best IP may work better in one system than another—even in chips developed by the same vendor.  

So, how do you measure IP quality and why it is so complicated?

The answer depends on who is asking. Most of the time, the definition of IP quality depends on your vantage point.  If you are an R&D manager, IP quality means something. If you are a global supply manager, IP quality means something else. If you are an SoC start-up, your measure of quality is quite different from that of an established fabless company. If you are designing IP in-house, then your considerations are very different than being a commercial IP vendor. If you are designing an automotive SoC, then we are in a totally different category. How about as an IP vendor? How do you articulate IP quality metrics to your customers?

This varies greatly by the type of IP, as well. When it comes to interface (hard) IP and controllers, if you are an R&D manager, your goal is to design IP that meets the IP specifications and PPA (power, performance, and area) targets. You need to validate your design via silicon test chips. This applies to all hard PHYs, which must be mapped to a particular foundry process. For controllers that are in RTL form—we called these soft IP—you have to synthesize them into a particular target library in a particular foundry process in order to realize them in a physical form suitable for SoC integration. Of course, your design will need to go through a series of design validation steps via simulation, design verification and passing the necessary DRC checks, etc. In addition, you want to see the test silicon in various process corners to ensure the IP is robust and will perform well under normal process variations in the production wafers.

For someone in IP procurement, the measure of quality will be based on the maturity of the IP. This involves the number of designs that have been taped out using this IP and the history of bug reports and subsequent fixes. You will be looking for quality of the documentation and the technical deliverables. You will also benchmark the supplier’s standard operating procedures for bug reporting and technical support, as well as meeting delivery performance in prior programs. This is in addition to the technical teams doing their technical diligence.

An in-house team that is likely to design IP for a particular SoC project will be using an established design flow and will have legacy knowledge of last generation’s IP. They may be required to design the IP with some reusability in mind for future programs. However, such reusability requirements will not need to be as stringent and as broad as those of commercial IP vendors because there are likely to be established metrics and procedures in place to follow as part of the design team’s standard operating procedures. Many times, new development based on a prior design that has been proven in use will be started, given this stable starting point. All of these criteria help the team achieve a quality outcome more easily.

Then, if designing for an automotive SoC, additional heavy lifting is required.  Aside from ensuring that the IP meets the specifications of the protocol standards and passes the compliance testing, you also must pay attention to meeting functional safety requirements. This means adherence to ISO 26262 requirements and subsequently achieving ASIL certification. Oftentimes, even for IP, you must perform some AEC-Q100-related tests that are relevant to IP, such as ESD, LU, and HTOL.

To read more, please visit: https://semiengineering.com/why-ip-quality-is-so-difficult-to-determine/

As a leading venture capitalist in the electronics technology, as well as CEO of Cadence, Lip-Bu Tan has unique insights into ongoing changes that will impact EDA providers and users. Tan shared some of those insights in a “fireside chat” with Ed Sperling, editor in chief of Semiconductor Engineering, at the Design Automation Conference (DAC 2015) on June 9.

Topics of this discussion included industry consolidation, the need for more talent and more startups, Internet of Things (IoT) opportunities and challenges, the shift from ICs to full product development, and the challenges of advanced nodes. Following are some excerpts from this conversation, held at the DAC Pavilion theater on the exhibit floor.

Ed Sperling (left) and Lip-Bu Tan (right) discuss trends in semiconductors and EDA

Q: As you look out over the semiconductor and EDA industries these days, what worries you most?

Tan: At the top of my list is all the consolidation that is going on. Secondly, chip design complexity is increasing substantially. Time-to-market pressure is growing and advanced nodes have challenges.

The other thing I worry about is that we need to have more startups. There’s a lot of innovation that needs to happen. And this industry needs more top talent. At Cadence, we have a program to recruit over 10% of new hires every year from college graduates. We need new blood and new ideas.

Q: EDA vendors were acquiring companies for many years, but now the startups are pretty much gone. Where does the next wave of innovation come from?

Tan: I’ve been an EDA CEO for the last seven years and I really enjoy it because so much innovation is needed. System providers have very big challenges and very different needs. You have to find the opportunities and go out and provide the solutions.

The opportunities are not just in basic tools. Massive parallelism is critical, and the power challenge is huge. Time to market is critical, and for the IoT companies, cost is going to be critical. If you want to take on some good engineering challenges, this is the most exciting time.

Q: You live two lives—you’re a CEO but you’re also an investor. Where are the investments going these days and where are we likely to see new startups?

Tan: Clearly everybody is chasing the IoT. There is a lot of opportunity in the cloud, in the data center. Also, I’m a big believer in video, so I back companies that are video related. A big area is automotive. ADAS [Advanced Driver Assistance Systems] is a tremendous opportunity.

These companies can help us understand how the industry is transforming, and then we can provide solutions, either in terms of IP, tools, or the PCB. Then we need to connect from the system level down to semiconductors. I think it’s a different way to design.

Q: What happens as we start moving from companies looking to design a semiconductor to system companies who are doing things from the perspective that we have this purpose for our software?

Tan: We are extending from EDA to what we call system design enablement, and we are becoming more application driven. The application at the system level will drive the silicon design. We need to help companies look at the whole system including the power envelope and signal integrity. You don’t want to be in a position where you design a chip all the way to fabrication and then find the power is too high.

We help the customers with hardware/software co-design and co-verification. We have a design suite and a verification suite that can provide customers with high-level abstractions, as well as verify IP blocks at the system level. Then we can break things down to the component level with system constraints in mind, and drive power-aware, system-aware design.

We are starting to move into vertical markets. For example, medical is a tremendous opportunity.

Q: How does this approach change what you provide to customers?

Tan: Every year I spend time meeting with customers. I think it is very important to understand what they are trying to design, and it is also important to know the customer’s customer requirements. We might say, “Wait a minute, for this design you may want to think about power or the library you’re using.” We help them understand what foundry they should use and what process they should use. They don’t view me as a vendor—they view me as a partner.

We also work very closely with our IP and foundry partners. We work as one team—the ultimate goal is customer success.

Q: Is everybody going to say, FinFETs are beautiful, we’re going to go down to 10nm or 7nm—or is it a smaller number of companies who will continue down that path?

Tan: Some of the analog/mixed-signal companies don’t need to go that far. We love those customers—we have close to 50% of that business. But we also have customers in the graphics or processor area who are really pushing the envelope, and need to be in 16nm, 14nm, or 10nm. We work very closely with those guys to make sure they can go into FinFETs.

We always want to work with the customer to make sure they have a first-time silicon success. If you have to do a re-spin, you miss the opportunity and it’s very costly.

Q: There’s a new market that is starting to explode—IoT. How real is that world to you? Everyone talks about large numbers, but is it showing up in terms of tools?

Tan: Everybody is talking about huge profits, but a lot of the time I think it is just connecting old devices that you have. Billions of units, absolutely yes, but if you look close enough the silicon percentage of that revenue is very tiny. A lot of the profit is on the service side. So you really need to look at the service killer app you are trying to provide.

What’s most important to us in the IoT market is the IP business. That’s why we bought Tensilica—it’s programmable, so you can find the killer app more quickly. The other challenges are time to market, low power, and low cost.

Q: Where is system design enablement going? Does it expand outside the traditional market for EDA?

Tan: It’s not just about tools. IP is now 11% of our revenue. At the PCB level, we acquired a company called Sigrity, and through that we are able to drive system analysis for power, signal integrity, and thermal. And then we look at some of the verticals and provide modeling all the way from the system level to the component level. We make sure that we provide a solution to the end customer, rather than something piecemeal.

Q: What do you think DAC will look like in five years?

Tan: It’s getting smaller. We need to see more startups and innovative IP solutions. I saw a few here this year, and that’s good. We need to encourage small startups.

Q: Where do we get the people to pull this off? I don’t see too many people coming into EDA.

Tan: I talk to a lot of university students, and I tell them that this small industry is a gold mine. A lot of innovation is needed. We need them to come in [to EDA] rather than join Google or Facebook. Those are great companies, but there is a lot of fundamental physical innovation we need.

Richard Goering

Related Blog Posts

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Everyone keeps talking about “the cloud” this and “the cloud” that these days—but you’re a semiconductor designer. Everyone keeps saying “the cloud” is revolutionizing all aspects of electronics design—but what does it mean for you? Cadence's own Tom Hackett discussed this in a presentation at the Cadence Theater during DAC 2019.

What people refer to as “the cloud” is commonly divided into three categories: Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and software as a Service (SaaS). With IaaS, you bring your own software—i.e. loading your owned or appropriately licensed tools onto cloud hardware that you rent by the minute. This service is available from providers like Google Cloud Platform, Amazon Web Service, and Microsoft Azure. In PaaS (also available from the major cloud providers), you create your own offering using capabilities and a software design environment provided by the cloud vendor that makes subsequent scaling and distribution really easy because the service was “born in the cloud”.  Lastly, there’s SaaS, where the cloud is used to access and manage functionality and data without requiring users to set up or manage any of the underlying infrastructure used to provide it.  SaaS companies like Workday and Salesforce deliver their value in this manner.  The Cadence Cloud portfolio makes use of both IaaS and SaaS, depending on the customers’ interest.  Cadence doesn’t have PaaS offerings because our customers don’t create their own EDA software from building blocks that Cadence provides.

All of these designations are great, but you’re a semiconductor designer. Presumably you use Workday or some similar software, or have in the past when you were an intern, but what about all of your tools? Those aren’t on the cloud.

Wait—actually, they are.

Using EDA tools in the cloud allows you to address complexity and data explosion issues you would have to simply struggle through before. Since you don’t have to worry about having the compute-power on-site, you can use way more power than you could before. You may be wary about this new generation of cloud-based tools, but don’t worry: the old rules of cloud computing no longer apply. Cloud capacity is far larger than it used to be, and it’s more secure. Updates to scheduling software means that resource competition isn’t as big of a deal anymore. Clouds today have nearly unlimited capacity—they’re so large that you don’t ever need to worry about running out of space.

The vast increase in raw compute available to designers through the cloud makes something like automotive functional safety verification, previously an extremely long verification task, doable in a reasonable time frame. With the cloud, it’s easy to scale the amount of compute you’re using to fit your task—whether it’s an automotive functional safety-related design or a small one.

Nowadays, the Cadence Cloud Portfolio brings you the best and brightest in cloud technology. No matter what your use case is, the Cadence Cloud Portfolio has a solution that works for you. You can even access the Palladium Cloud, allowing you to try out the benefits of an accelerator without having to buy one.

Cloud computing is the future of EDA. See the future here.

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