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In this paper, a large set of macroeconomic and financial predictors is used to forecast U.S. recession periods. We propose a sparse Bayesian variable selection in probit model for predicting U.S. recessions. The correlation prior is assigned for the binary vector to distinguish models with the same size, and the sparse prior is specified for the coefficient parameters for the purpose of predicting accurately using fewer parameters. In terms of the quadratic probability score and the log probability score, we demonstrate that the proposed method performs better than other three methods. [ABSTRACT FROM AUTHOR]

• Economics & carbon footprint of a piloted US flexible plastic packaging recycling. • Roof coverboard, pallets, pellets, and film are downstream market pathways. • Cleaning and pelletizing steps contributed the most to recycled product footprints. • Recycled products are environmentally & economically better than competitors. As demand for plastic increases, there is an urgent need to ramp up its collection and recycling rate. This study reports results of a pilot study in the United States to recycle flexible plastic packaging (FPP) from single stream curbside collection focusing on both the economic feasibility and carbon footprint. To explore the marketability of recycled FPP, four downstream market pathways were studied, including roof coverboard, plastic pellets, pallets, and film. Results indicated that (1) the cleaning and pelletizing process at reclaimers contributed the most to the total greenhouse gas (GHG) emissions of recycled FPP products, and (2) the GHG emissions of recycled FPP products in all four pathways are lower than the comparator products. Therefore, using a higher percentage of recycled FPP substituted in a product can result in greater GHG emission reductions. All the recycled FPP products also showed favorable economics compared to their direct competitors. [ABSTRACT FROM AUTHOR]

Abstract: Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae) is a key insect pest of cotton in the Henan cotton growing region of China. In this region, cotton is grown on small acreages in rich agricultural landscapes, contrary to cropping systems in the United States or Australia. Under such cropping regimes, naturally occurring refuges (with non-Bt plants) may be sufficient to prevent H. armigera resistance development to Bt toxins. In order to gain a timely understanding of the evolution of resistance of H. armigera to Bt toxin after continuous cultivation of Bt cotton for c. 10 years, we assessed the frequency of alleles conferring resistance to Cry1Ac toxin in field populations of H. armigera sampled from Xinxiang County in Henan province during 2007–2009. Screening F1 and F2 generations from isofemale lines, derived from female moths trapped in the field, were used with a discriminating dose of Cry1Ac diet to estimate the frequency of resistance alleles. Totals of 625, 516 and 488 isofemale lines were screened for the F1 generation in 2007, 2008 and 2009, respectively. Resistance gene frequency in Xinxiang fluctuated between 0.0000 and 0.0005, and it did not increase significantly from 2007 to 2009. Based on the relative average development rates (RADR) of H. armigera larvae in F1 tests, no substantial increase in Cry1Ac tolerance was found in the Xinxiang region over the 3-yr period. [Copyright &y& Elsevier]

ABT-450 (8), a potent hepatitis C (HCV) NS3/4A protease inhibitor, was approved as part of AbbVie's first generation HCV treatment for the United States in December 2014. A series of process optimizations were developed over six years to support the program starting with recycling of a previous protease inhibitor candidate through route development and final process. This discussion will focus on optimization of the final six steps starting from dipeptide 12 and amino acid 13 and highlights the use of a large scale ring closing metathesis (RCM), reactive crystallizations for isolation of intermediates, and detailed process understanding of the final sulfonamide coupling. The process provides ABT-450 (8) in 72% overall yield for the final 6 steps. Image 1 [ABSTRACT FROM AUTHOR]

The 21st Century Cures Act passed by the United States (US) Congress in December 2016 requires the US Food and Drug Administration (FDA) shall establish a program to evaluate the potential use of real-world evidence (RWE) which is generated from real-world data (RWD) to (i) support approval of new indication for a drug approved under section 505 (c) and (ii) satisfy post-approval study requirements. RWE offers the opportunities to develop robust evidence using high-quality data and sophisticated methods for producing causal-effect estimates regardless randomization is feasible. In this article, we have demonstrated that the assessment of treatment effect (RWE) based on RWD could be biased due to the potential selection and information biases of RWD. Although fit-for-purpose RWE may meet regulatory standards under certain assumptions, it is not the same as substantial evidence (current regulatory standard in support of approval of regulatory submission). In practice, it is then suggested that when there are gaps between fit-for-purpose RWE and substantial evidence, we should make efforts to fill these gaps based on a comprehensive evaluation of the treatment effect. We also review two RWE examples to show some potential use of RWE in clinical studies. [ABSTRACT FROM AUTHOR]