Pathways to Higher Education

Presents case studies from Ford's initiative to support efforts to transform universities abroad to enable poor, minority, and otherwise underrepresented students to obtain a university degree. Outlines selected best practices from grantees

Radiative corrections to leptonic decays using infinite-volume reconstruction

Lattice QCD calculations of leptonic decay constants have now reached sub-percent precision so that isospin-breaking corrections, including QED effects, must be included to fully exploit this precision in determining fundamental quantities, in particular the elements of the Cabibbo-Kobayashi-Maskawa (CKM) matrix, from experimental measurements. A number of collaborations have performed, or are performing, such computations. In this paper we develop a new theoretical framework, based on Infinite-Volume Reconstruction (IVR), for the computation of electromagnetic corrections to leptonic decay widths. In this method, the hadronic correlation functions are first processed theoretically in infinite volume, in such a way that the required matrix elements can be determined non-perturbatively from lattice QCD computations with finite-volume uncertainties which are exponentially small in the volume. The cancellation of infrared divergences in this framework is performed fully analytically. We also outline how this IVR treatment can be extended to determine the QED effects in semi-leptonic kaon decays with a similar degree of accuracy

Radiative corrections to leptonic decays using infinite-volume reconstruction

Lattice QCD calculations of leptonic decay constants have now reached sub-percent precision so that isospin-breaking corrections, including QED effects, must be included to fully exploit this precision in determining fundamental quantities, in particular the elements of the Cabibbo-Kobayashi-Maskawa (CKM) matrix, from experimental measurements. A number of collaborations have performed, or are performing, such computations. In this paper we develop a new theoretical framework, based on Infinite-Volume Reconstruction (IVR), for the computation of electromagnetic corrections to leptonic decay widths. In this method, the hadronic correlation functions are first processed theoretically in infinite volume, in such a way that the required matrix elements can be determined non-perturbatively from lattice QCD computations with finite-volume uncertainties which are exponentially small in the volume. The cancellation of infrared divergences in this framework is performed fully analytically. We also outline how this IVR treatment can be extended to determine the QED effects in semi-leptonic kaon decays with a similar degree of accuracy

Feeding a High Concentrate Diet Down-Regulates Expression of ACACA, LPL and SCD and Modifies Milk Composition in Lactating Goats.

High concentrate diets are fed to early and mid-lactation stages dairy ruminants to meet the energy demands for high milk production in modern milk industry. The present study evaluated the effects of a high concentrate diet on milk fat and milk composition, especially, cis-9, trans-11 CLA content in milk and gene expression of lactating goats. Eight mid-lactating goats with rumen fistula were randomly assigned into a high concentrate diet (HCD) group and low concentrate diet (LCD) group. High concentrate diet feeding significantly increased lipopolysaccharides (LPS) in plasma and decreased milk fat content, vaccenic acid (VA) and cis-9, trans-11 CLA in milk of the lactating goats. The mRNA expression levels of sterol regulatory element binding protein B 1c (SREBP1c), lipoprotein lipase (LPL), fatty acid synthetase (FASN) and acetyl-CoA carboxylase α (ACACA, ACCα) involving in lipid metabolism were analyzed, and ACACA and LPL all decreased in their expression level in the mammary glands of goats fed a high concentrate diet. DNA methylation rate of stearoyl-CoA desaturase (SCD) was elevated and decreased, and SCD mRNA and protein expression was reduced significantly in the mammary glands of goats fed a high concentrate diet. In conclusion, feeding a high concentrate diet to lactating goats decreases milk fat and reduced expression of SCD in the mammary gland, which finally induced cis-9, trans-11 CLA content in milk

Mixed Natural Gas Online Recognition Device Based on a Neural Network Algorithm Implemented by an FPGA

It is a daunting challenge to measure the concentration of each component in natural gas, because different components in mixed gas have cross-sensitivity for a single sensor. We have developed a mixed gas identification device based on a neural network algorithm, which can be used for the online detection of natural gas. The neural network technology is used to eliminate the cross-sensitivity of mixed gases to each sensor, in order to accurately recognize the concentrations of methane, ethane and propane, respectively. The neural network algorithm is implemented by a Field-Programmable Gate Array (FPGA) in the device, which has the advantages of small size and fast response. FPGAs take advantage of parallel computing and greatly speed up the computational process of neural networks. Within the range of 0−100% of methane, the test error for methane and heavy alkanes such as ethane and propane is less than 0.5%, and the response speed is several seconds

mRNA expression of genes involved in lipogenesis in mammary glands of lactating goats fed a high concentrate diet.

<p>The asterisk shows significant differences between the groups (<i>P</i><0.05).</p

Protein expression of SCD in the mammary glands of lactating goats.

<p>Representative blots of SCD in mammary glands of goats fed a low concentration diet (lanes 1, 2, 3, 4) and a high concentration diet (lanes 5, 6, 7, 8). The asterisk shows significant difference between the groups (<i>P</i><0.05).</p

Rumen, plasma and milk parameters.

<p>- means non-significant</p><p>* <i>P</i><0.05</p><p>** <i>P</i><0.01</p><p>Rumen, plasma and milk parameters.</p