Field Peas can be Included in the Phase 2 Diet for Nursery Pigs Without Adverse Effects on Pig Performance

Field peas are usually not included in diets for nursery pigs in the US. However, European and Canadian data suggest that field peas may be included in diets for nursery pigs without compromising pig performance (Stefanyshyn et al., 1999). So far, only little research has been conducted in the US to evaluate the effect of including field peas in diets for nursery pigs. Landblom and Poland (1996) reported decreased pig performance if 30 to 50% field peas were included in phase 1 diets for nursery pigs. However, working with extruded peas, they reported no detrimental effects of feeding 20% peas if the inclusion was restricted to the second phase of the nursery period. Due to the relatively low cost of field peas, any inclusion of field peas will result in a decrease in the overall diet cost. Therefore, the current experiment was conducted to determine if field peas might be included in the phase 2 diets for nursery pigs

The Effect of Including Field Peas in Diets for Growing-finishing Pigs

Individual pig weights were recorded at the beginning of the experiment and every two weeks thereafter. The amount of feed dumped in each feed was recorded on a daily basis and feed in the feeders was recorded each time the pigs were weighed. At slaughter, indvidual live wights, the dressed weights, fat depth, loin depth, and the lean meant percentage were measured for each pig. At the end of the experiment, feed disapearance for each pen was calculated for each period. Likewise, average daily weight gain and average gain to feed ratios were calculated for each pen

The Future of Using Antibiotics in Livestock Feeding

For more than 50 years, it has been recognized that livestock performance can be improved if antibiotics are included in the diets at sub-therapeutic levels. As a result, a relatively large number of feed antibiotics have been approved for livestock feeding, and it is common praxis all over the world to include one or more antibiotics in the diets for production animals. Typically, daily gain and feed utilization are improved by 5 to 10% by the inclusion of these antibiotic growth promoters

Emissions Savings in the Corn-Ethanol Life Cycle from Feeding Coproducts to Livestock

Environmental regulations on greenhouse gas (GHG) emissions from corn (Zea mays L.)-ethanol production require accurate assessment methods to determine emissions savings from coproducts that are fed to livestock. We investigated current use of coproducts in livestock diets and estimated the magnitude and variability in the GHG emissions credit for coproducts in the corn-ethanol life cycle. The coproduct GHG emissions credit varied by more than twofold, from 11.5 to 28.3 g CO2e per MJ of ethanol produced, depending on the fraction of coproducts used without drying, the proportion of coproduct used to feed beef cattle (Bos taurus) vs. dairy or swine (Sus scrofa), and the location of corn production. Regional variability in the GHG intensity of crop production and future livestock feeding trends will determine the magnitude of the coproduct GHG offset against GHG emissions elsewhere in the corn-ethanol life cycle. Expansion of annual U.S. corn-ethanol production to 57 billion liters by 2015, as mandated in current federal law, will require feeding of coproduct at inclusion levels near the biological limit to the entire U.S. feedlot cattle, dairy, and swine herds. Under this future scenario, the coproduct GHG offset will decrease by 8% from current levels due to expanded use by dairy and swine, which are less efficient in use of coproduct than beef feedlot cattle. Because the coproduct GHG credit represents 19 to 38% of total life cycle GHG emissions, accurate estimation of the coproduct credit is important for determining the net impact of corn-ethanol production on atmospheric warming and whether corn-ethanol producers meet state- and national-level GHG emissions regulations

Expedition 306 summary

The overall aim of the North Atlantic paleoceanography study of Integrated Ocean Drilling Program Expedition 306 is to place late Neogene–Quaternary climate proxies in the North Atlantic into a chronology based on a combination of geomagnetic paleointensity, stable isotope, and detrital layer stratigraphies, and in so doing generate integrated North Atlantic millennial-scale stratigraphies for the last few million years. To reach this aim, complete sedimentary sections were drilled by multiple advanced piston coring directly south of the central Atlantic “ice-rafted debris belt” and on the southern Gardar Drift. In addition to the North Atlantic paleoceanography study, a borehole observatory was successfully installed in a new ~180 m deep hole close to Ocean Drilling Program Site 642, consisting of a circulation obviation retrofit kit to seal the borehole from the overlying ocean, a thermistor string, and a data logger to document and monitor bottom water temperature variations through time

Elevated MACC1 expression in colorectal cancer is driven by chromosomal instability and is associated with molecular subtype and worse patient survival

Metastasis-Associated in Colon Cancer 1 (MACC1) is a strong prognostic biomarker inducing proliferation, migration, invasiveness, and metastasis of cancer cells. The context of MACC1 dysregulation in cancers is, however, still poorly understood. Here, we investigated whether chromosomal instability and somatic copy number alterations (SCNA) frequently occurring in CRC contribute to MACC1 dysregulation, with prognostic and predictive impacts. Using the Oncotrack and Charité CRC cohorts of CRC patients, we showed that elevated MACC1 mRNA expression was tightly dependent on increased MACC1 gene SCNA and was associated with metastasis and shorter metastasis free survival. Deep analysis of the COAD-READ TCGA cohort revealed elevated MACC1 expression due to SCNA for advanced tumors exhibiting high chromosomal instability (CIN), and predominantly classified as CMS2 and CMS4 transcriptomic subtypes. For that cohort, we validated that elevated MACC1 mRNA expression correlated with reduced disease-free and overall survival. In conclusion, this study gives insights into the context of MACC1 expression in CRC. Increased MACC1 expression is largely driven by CIN, SCNA gains, and molecular subtypes, potentially determining the molecular risk for metastasis that might serve as a basis for patient-tailored treatment decisions

IMRT beam angle optimization using electromagnetism-like algorithm

The selection of appropriate beam irradiation directions in radiotherapy – beam angle optimization (BAO) problem – is very impor- tant for the quality of the treatment, both for improving tumor irradia- tion and for better organs sparing. However, the BAO problem is still not solved satisfactorily and, most of the time, beam directions continue to be manually selected in clinical practice which requires many trial and error iterations between selecting beam angles and computing fluence patterns until a suitable treatment is achieved. The objective of this pa- per is to introduce a new approach for the resolution of the BAO problem, using an hybrid electromagnetism-like algorithm with descent search to tackle this highly non-convex optimization problem. Electromagnetism- like algorithms are derivative-free optimization methods with the ability to avoid local entrapment. Moreover, the hybrid electromagnetism-like algorithm with descent search has a high ability of producing descent directions. A set of retrospective treated cases of head-and-neck tumors at the Portuguese Institute of Oncology of Coimbra is used to discuss the benefits of the proposed algorithm for the optimization of the BAO problem.Fundação para a Ciência e a Tecnologia (FCT

A dynamical model of lipoprotein metabolism

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Forward K+ production in subthreshold pA collisions at 1.0 GeV

K+ meson production in pA (A = C, Cu, Au) collisions has been studied using the ANKE spectrometer at an internal target position of the COSY-Juelich accelerator. The complete momentum spectrum of kaons emitted at forward angles, theta < 12 degrees, has been measured for a beam energy of T(p)=1.0 GeV, far below the free NN threshold of 1.58 GeV. The spectrum does not follow a thermal distribution at low kaon momenta and the larger momenta reflect a high degree of collectivity in the target nucleus.Comment: 4 pages, 3 figure

Low Complexity Regularization of Linear Inverse Problems

Inverse problems and regularization theory is a central theme in contemporary signal processing, where the goal is to reconstruct an unknown signal from partial indirect, and possibly noisy, measurements of it. A now standard method for recovering the unknown signal is to solve a convex optimization problem that enforces some prior knowledge about its structure. This has proved efficient in many problems routinely encountered in imaging sciences, statistics and machine learning. This chapter delivers a review of recent advances in the field where the regularization prior promotes solutions conforming to some notion of simplicity/low-complexity. These priors encompass as popular examples sparsity and group sparsity (to capture the compressibility of natural signals and images), total variation and analysis sparsity (to promote piecewise regularity), and low-rank (as natural extension of sparsity to matrix-valued data). Our aim is to provide a unified treatment of all these regularizations under a single umbrella, namely the theory of partial smoothness. This framework is very general and accommodates all low-complexity regularizers just mentioned, as well as many others. Partial smoothness turns out to be the canonical way to encode low-dimensional models that can be linear spaces or more general smooth manifolds. This review is intended to serve as a one stop shop toward the understanding of the theoretical properties of the so-regularized solutions. It covers a large spectrum including: (i) recovery guarantees and stability to noise, both in terms of $\ell^2$-stability and model (manifold) identification; (ii) sensitivity analysis to perturbations of the parameters involved (in particular the observations), with applications to unbiased risk estimation ; (iii) convergence properties of the forward-backward proximal splitting scheme, that is particularly well suited to solve the corresponding large-scale regularized optimization problem