Taylor Sheridan's new war movie gets major update, legendary director attached LPGA star Nelly Korda sizzles on the beach, Dems won't stop dancing & Gia Duddy whips up a bikini lunch Paige Spiranac provides an update on'Great Cans' saga, fan's still MIA but others have picked up the slack Ivanka Trump has the angry libs on high alert as she slides into an amazing dress, Waffle House chaos & MEAT! Donald Trump makes odd'hair' comment to Danica Patrick at TPUSA event Islamabad enters'red zone' lockdown ahead of expected US-Iran peace talks Holocaust survivor known as'Crossing Guard Diva' goes viral for glam style House Ethics Committee weighs action against Rep. Cherfilus-McCormick'Sinister' links suspected in mysterious deaths of scientists Welcome to the numerous new Screencaps readers - trust me, you have to give this column two weeks to understand what's going on If you are one of the hundreds of thousands of new Screencaps readers who found this column on Monday, welcome back. You're about to become hooked. Just go ahead and clear your daily schedule at 9 a.m. for America's Best Daily Column, as named by the readers who've been with me for years. In some cases, readers have been with me for over a decade. This column is their talk radio.

In this paper, we consider the problem of extraction of most informative features from time series that are regarded as observed values of stochastic processes satisfying the It{ô} stochastic differential equations with unknown random drift and diffusion coefficients. We do not attract any additional information and use only the information contained in the time series as it is. Therefore, as additional features, we use the parameters of statistically adjusted mixture-type models of the observed regularities of the behavior of the time series. Several algorithms of construction of these parameters are discussed. These algorithms are based on statistical reconstruction of the coefficients which, in turn, is based on statistical separation of normal mixtures. We obtain two types of parameters by the techniques of the uniform and non-uniform statistical reconstruction of the coefficients of the underlying It{ô} process. The reconstructed coefficients obtained by uniform techniques do not depend on the current value of the process, while the non-uniform techniques reconstruct the coefficients with the account of their dependence on the value of the process. Actually, the non-uniform techniques used in this paper represent a stochastic analog of the Taylor expansion for the time series. The efficiency of the obtained additional features is compared by using them in the autoregressive algorithms of prediction of time series. In order to obtain pure conclusion that is not affected by unwanted factors, say, related to a special choice of the architecture of the neural network prediction methods, we used only simple autoregressive algorithms. We show that the use of additional statistical features improves the prediction.

Reliability-based design optimization (RBDO) is traditionally formulated as a nested optimization and reliability problem. Although surrogate models are generally employed to improve efficiency, the approach remains computationally prohibitive in high-dimensional settings. This paper proposes a novel RBDO framework based on a stochastic simulator viewpoint, in which the deterministic limit-state function and the uncertainty in the model inputs are combined into a unified stochastic representation. Under this formulation, the system response conditioned on a given design is modeled directly through its output distribution, rather than through an explicit limit-state function. Stochastic emulators are constructed in the design space to approximate the conditional response distribution, enabling the semi-analytical evaluation of failure probabilities or associated quantiles without resorting to Monte Carlo simulation. Two classes of stochastic emulators are investigated, namely generalized lambda models and stochastic polynomial chaos expansions. Both approaches provide a deterministic mapping between design variables and reliability constraints, which breaks the classical double-loop structure of RBDO and allows the use of standard deterministic optimization algorithms. The performance of the proposed approach is evaluated on a set of benchmark problems with dimensionality ranging from low to very high, including a case with stochastic excitation. The results are compared against a Kriging-based approach formulated in the full input space. The proposed method yields substantial computational gains, particularly in high-dimensional settings. While its efficiency is comparable to Kriging for low-dimensional problems, it significantly outperforms Kriging as the dimensionality increases.

Despite being declared the third-hottest year on record, 2025 was a relatively quiet year for climate disasters in the US. No major hurricanes made landfall, while the total number of acres burned in wildfires last year--a way of measuring the intensity of wildfire season --fell below the 10-year average. But starting this week, the West is experiencing what looks to be a record-breaking heat wave, while forecasting models predict that a strong El Niño event is likely to emerge later this year. These two unrelated phenomena could set the stage for a long stretch of unpredictable and extreme weather reaching into next year, compounding the effects of a climate that's getting hotter and hotter thanks to human activity. Beginning this week and heading into next, a massive ridge of high-pressure air will bring record-breaking temperatures to the American West.

Like many of us, the bugs have been hunkered down waiting for spring to return. CDC/ James Gathany; William L. Nicholson, Ph.D. (left). Breakthroughs, discoveries, and DIY tips sent six days a week. With days to go until the official first day of spring, it was a tale of two winters in the continental United States. Colorado's mountains had record low snow levels, while Salt Lake City and Phoenix were among the cities who had their highest winter temperatures on record .

Forl = 2, i. e., for 3 - cycles, thisrelationship is X ikX kj= X ij. Figure 1: Averagematchingerrorunderthe LBCmodel ( left) and LACmodel ( right).