Nehman Lauder
Oct 1, 2005; 23:191-192
Case Studies

Joseph Largay
Jan 1, 2012; 30:25-26
Case Studies

Evan M. Benjamin
Jul 1, 2004; 22:137-138
Case Studies

Brian J. Welch
Oct 1, 2004; 22:198-200
Case Studies

Just days after South Korea loosened its social distancing guidelines, a new COVID-19 cluster of infections has sprung up in the capital city of Seoul tied to several nightclubs.

A federal judge on Friday declined to dismiss charges filed against Lori Loughlin and 13 others in a national college admissions case based in Massachusetts.

Huy A. Tran
Jul 1, 2004; 22:141-143
Case Studies

Arguments before North Carolina's supreme court centered on whether lawmakers overstepped by giving more authority to the state's elected superintendent and taking it away from the state school board.

Students engaged in a protest against a culture they saw as punitive; their principal suspended them. What did a court say?

The U.S. Supreme Court will hear arguments remotely in May, including on whether religious schools are exempt from employment discrimination claims brought by lay teachers.

The U.S. Supreme Court will arguments in Espinoza v. Montana Department of Revenue, a case that's been closely watched by both friends and opponent of private school vouchers and tax-credit scholarship programs.

School authorities in Utah have failed to report educator misconduct, possibly allowing teachers to offend again by moving to other schools, according to a new audit.

"We investigate the potential of using high-resolution seismic methods for rock characterization and for targeting of gold deposits at the St. Ives gold camp. The application of seismic methods in hard-rock environments is challenged by complex structures, intrinsically low signal-to-noise ratio, regolith distortions, and access restrictions. If these issues can be addressed, then the unparalleled resolving power of reflection seismic can be used for mineral exploration. Appropriate spatial sampling of the wavefield combined with a survey geometry design and rigorous data processing to incorporate high fold and long offsets are necessary for creation of high-quality seismic images. In the hard-rock environment of Western Australia, accurate static corrections and multiphase velocity analysis are essential processing steps. This is followed by a rigorous quality control following each processing step. In such a case, we show that the role of reflection seismic could be lifted from mere identification of first-order structures to refined lithological analyses. Five deep boreholes with sonic logs and core sample test data wer eused to calibrate 2D seismic images. Despite seismic images were produced with relatively robust scaling it was possible to achieve reasonably high seismic-log correlation across three of the tightly spaced boreholes using a single composite wavelet. Amplitude-versus-offset (AVO) analysis indicated that gold-bearing structures may be related to elevated AVO effect and increased reflectivity. Consequently, partial stack analysis and acoustic and elastic inversions were conducted. These results and impedance crossplots were then evaluated against known gold occurrences. While still in the preliminary stages, hard-rock seismic imaging, inversion, and the application of AVO techniques indicated significant potential for targeting mineral reserves" -- Summary.

"This document is intended to summarise the current state, understanding and the use of seismic reflection method for mineral exploration. Its primary objective is to provide a point of reference, based on actual case studies, for mineral explorers interested in the application of seismic methods to their project. It provides summary information (including the purpose of the survey, acquisition methods, geometry and cost, processing procedures and key findings) that are intended to provide the reader with an objective means of assessing the cost effectiveness of the technique with respect to exploration objectives. It is also aimed at exchange of information between DETCRC sponsors, affiliates and researchers. Finally we hope that this table will help in shaping future research efforts and direction within Project 3.1, regarding the application of seismic for mineral exploration.This is only initial work and it is hoped that it will evolve into a document or a catalogue that will be extensively used by the mineral industry to achieve their exploration objectives in more efficient and effective way" -- Executive summary.

Climatic changes.

Senses and sensation.

A $59 million investment in software developer Social Solutions aims to ease the flow of data among schools and social service providers.

Kansas' highest court has declared that the state finally is spending enough money on its public schools under a new education funding law but refused to end a lawsuit filed nearly a decade ago because it wants to monitor future funding by the legislature.

Cheltenham : printed for G.A. Williams, librarian, [1823]

London : Kenny & Co, [1895?]

London : printed for J. Callow, 1814.

[United Kingdom] : [Darcy Leigh], 2019.

We consider a setting where multiple players sequentially choose among a common set of actions (arms). Motivated by an application to cognitive radio networks, we assume that players incur a loss upon colliding, and that communication between players is not possible. Existing approaches assume that the system is stationary. Yet this assumption is often violated in practice, e.g., due to signal strength fluctuations. In this work, we design the first multi-player Bandit algorithm that provably works in arbitrarily changing environments, where the losses of the arms may even be chosen by an adversary. This resolves an open problem posed by Rosenski et al. (2016).

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.

Kushal K. Dey, Sourabh Bhattacharya.

Source: Brazilian Journal of Probability and Statistics, Volume 33, Number 2, 222--266.

Abstract:
Transformation based Markov Chain Monte Carlo (TMCMC) was proposed by Dutta and Bhattacharya ( Statistical Methodology 16 (2014) 100–116) as an efficient alternative to the Metropolis–Hastings algorithm, especially in high dimensions. The main advantage of this algorithm is that it simultaneously updates all components of a high dimensional parameter using appropriate move types defined by deterministic transformation of a single random variable. This results in reduction in time complexity at each step of the chain and enhances the acceptance rate. In this paper, we first provide a brief review of the optimal scaling theory for various existing MCMC approaches, comparing and contrasting them with the corresponding TMCMC approaches.The optimal scaling of the simplest form of TMCMC, namely additive TMCMC , has been studied extensively for the Gaussian proposal density in Dey and Bhattacharya (2017a). Here, we discuss diffusion-based optimal scaling behavior of additive TMCMC for non-Gaussian proposal densities—in particular, uniform, Student’s $t$ and Cauchy proposals. Although we could not formally prove our diffusion result for the Cauchy proposal, simulation based results lead us to conjecture that at least the recipe for obtaining general optimal scaling and optimal acceptance rate holds for the Cauchy case as well. We also consider diffusion based optimal scaling of TMCMC when the target density is discontinuous. Such non-regular situations have been studied in the case of Random Walk Metropolis Hastings (RWMH) algorithm by Neal and Roberts ( Methodology and Computing in Applied Probability 13 (2011) 583–601) using expected squared jumping distance (ESJD), but the diffusion theory based scaling has not been considered. We compare our diffusion based optimally scaled TMCMC approach with the ESJD based optimally scaled RWM with simulation studies involving several target distributions and proposal distributions including the challenging Cauchy proposal case, showing that additive TMCMC outperforms RWMH in almost all cases considered.

Beginning from a basic neural-network architecture, we test the potential benefits offered by a range of advanced techniques for machine learning, in particular deep learning, in the context of a typical classification problem encountered in the domain of high-energy physics, using a well-studied dataset: the 2014 Higgs ML Kaggle dataset. The advantages are evaluated in terms of both performance metrics and the time required to train and apply the resulting models. Techniques examined include domain-specific data-augmentation, learning rate and momentum scheduling, (advanced) ensembling in both model-space and weight-space, and alternative architectures and connection methods.

Following the investigation, we arrive at a model which achieves equal performance to the winning solution of the original Kaggle challenge, whilst being significantly quicker to train and apply, and being suitable for use with both GPU and CPU hardware setups. These reductions in timing and hardware requirements potentially allow the use of more powerful algorithms in HEP analyses, where models must be retrained frequently, sometimes at short notice, by small groups of researchers with limited hardware resources. Additionally, a new wrapper library for PyTorch called LUMINis presented, which incorporates all of the techniques studied.

This paper proposes a stochastic variant of the stable matching model from Rasulkhani and Chow [1] which allows microtransit operators to evaluate their operation policy and resource allocations. The proposed model takes into account the stochastic nature of users' travel utility perception, resulting in a probabilistic stable operation cost allocation outcome to design ticket price and ridership forecasting. We applied the model for the operation policy evaluation of a microtransit service in Luxembourg and its border area. The methodology for the model parameters estimation and calibration is developed. The results provide useful insights for the operator and the government to improve the ridership of the service.

Denis Talay, Milica Tomašević.

Source: Bernoulli, Volume 26, Number 2, 1323--1353.

Abstract:
In this paper, we analyze a stochastic interpretation of the one-dimensional parabolic–parabolic Keller–Segel system without cut-off. It involves an original type of McKean–Vlasov interaction kernel. At the particle level, each particle interacts with all the past of each other particle by means of a time integrated functional involving a singular kernel. At the mean-field level studied here, the McKean–Vlasov limit process interacts with all the past time marginals of its probability distribution in a similarly singular way. We prove that the parabolic–parabolic Keller–Segel system in the whole Euclidean space and the corresponding McKean–Vlasov stochastic differential equation are well-posed for any values of the parameters of the model.

Indian authorities used drones and fire engines to disinfect the pandemic-hit city of Ahmedabad on Saturday, as virus cases surged and police clashed with migrant workers protesting against a reinforced lockdown. The western city of 5.5 million people in Prime Minister Narendra Modi's home state has become a major concern for authorities as they battle an uptick in coronavirus deaths and cases across India.

The Justice Department announced Thursday that it is dropping its criminal case against President Trump's first national security adviser Michael Flynn. Flynn twice admitted in court he lied to the FBI about his conversations with Russia's U.S. ambassador, and then cooperated in Special Counsel Robert Mueller's investigation. It was an unusual move by the Justice Department, and CNN's legal and political analysts smelled a rat."Attorney General [William] Barr is already being accused of creating a special justice system just for President Trump's friends," and this will only feed that perception, CNN's Jake Tapper suggested. Political correspondent Sara Murray agreed, noting that the prosecutor in the case, Brandon Van Grack, withdrew right before the Justice Department submitted its filing, just like when Barr intervened to request a reduced sentence for Roger Stone.National security correspondent Jim Sciutto laid out several reason why the substance of Flynn's admitted lie was a big deal, and chief legal analyst Jeffrey Toobin was appalled. "It is one of the most incredible legal documents I have read, and certainly something that I never expected to see from the United States Department of Justice," Toobin said. "The idea that the Justice Department would invent an argument -- an argument that the judge in this case has already rejected -- and say that's a basis for dropping a case where a defendant admitted his guilt shows that this is a case where the fix was in."Barr told CBS News' Cathrine Herridge on Thursday that dropping Flynn's case actually "sends the message that there is one standard of justice in this country." Herridge told Barr he would take flak for this, asking: "When history looks back on this decision, how do you think it will be written?" Barr laughed: "Well, history's written by the winners. So it largely depends on who's writing the history." Watch below. More stories from theweek.com Outed CIA agent Valerie Plame is running for Congress, and her launch video looks like a spy movie trailer 7 scathing cartoons about America's rush to reopen Trump says he couldn't have exposed WWII vets to COVID-19 because the wind was blowing the wrong way

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