Multicast Network Coding and Field Sizes

In an acyclic multicast network, it is well known that a linear network coding solution over GF($q$) exists when $q$ is sufficiently large. In particular, for each prime power $q$ no smaller than the number of receivers, a linear solution over GF($q$) can be efficiently constructed. In this work, we reveal that a linear solution over a given finite field does \emph{not} necessarily imply the existence of a linear solution over all larger finite fields. Specifically, we prove by construction that: (i) For every source dimension no smaller than 3, there is a multicast network linearly solvable over GF(7) but not over GF(8), and another multicast network linearly solvable over GF(16) but not over GF(17); (ii) There is a multicast network linearly solvable over GF(5) but not over such GF($q$) that $q > 5$ is a Mersenne prime plus 1, which can be extremely large; (iii) A multicast network linearly solvable over GF($q^{m_1}$) and over GF($q^{m_2}$) is \emph{not} necessarily linearly solvable over GF($q^{m_1+m_2}$); (iv) There exists a class of multicast networks with a set $T$ of receivers such that the minimum field size $q_{min}$ for a linear solution over GF($q_{min}$) is lower bounded by $\Theta(\sqrt{|T|})$, but not every larger field than GF($q_{min}$) suffices to yield a linear solution. The insight brought from this work is that not only the field size, but also the order of subgroups in the multiplicative group of a finite field affects the linear solvability of a multicast network

Phenomic selection in slash pine multi-temporally using UAV-multispectral imagery

Genomic selection (GS) is an option for plant domestication that offers high efficiency in improving genetics. However, GS is often not feasible for long-lived tree species with large and complex genomes. In this paper, we investigated UAV multispectral imagery in time series to evaluate genetic variation in tree growth and developed a new predictive approach that is independent of sequencing or pedigrees based on multispectral imagery plus vegetation indices (VIs) for slash pine. Results show that temporal factors have a strong influence on the h2 of tree growth traits. High genetic correlations were found in most months, and genetic gain also showed a slight influence on the time series. Using a consistent ranking of family breeding values, optimal slash pine families were selected, obtaining a promising and reliable predictive ability based on multispectral+VIs (MV) alone or on the combination of pedigree and MV. The highest predictive value, ranging from 0.52 to 0.56, was found in July. The methods described in this paper provide new approaches for phenotypic selection (PS) using high-throughput multispectral unmanned aerial vehicle (UAV) technology, which could potentially be used to reduce the generation time for conifer species and increase the genetic granularity independent of sequencing or pedigrees

Roles of Chronic Low-Grade Inflammation in the Development of Ectopic Fat Deposition

Pattern of fat distribution is a major determinant for metabolic homeostasis. As a depot of energy, the storage of triglycerides in adipose tissue contributes to the normal fat distribution. Decreased capacity of fat storage in adipose tissue may result in ectopic fat deposition in nonadipose tissues such as liver, pancreas, and kidney. As a critical biomarker of metabolic complications, chronic low-grade inflammation may have the ability to affect the process of lipid accumulation and further lead to the disorder of fat distribution. In this review, we have collected the evidence linking inflammation with ectopic fat deposition to get a better understanding of the underlying mechanism, which may provide us with novel therapeutic strategies for metabolic disorders

Inflammatory stress exacerbates ectopic lipid deposition in C57BL/6J mice

<p>Abstract</p> <p>Background</p> <p>Chronic systemic inflammation and abnormal free fatty acid metabolism are closely related to ectopic lipid deposition. In this study, we investigate if inflammation tissue-specifically disrupts lipogenesis and lipolysis in nonadipose tissues and adipose tissue, resulting in ectopic lipid deposition in C57BL/6J mice.</p> <p>Methods</p> <p>We used casein injection in C57BL/6J mice to induce a chronic systemic inflammatory stress in vivo. Serum was analyzed for free fatty acid and cytokines. Insulin sensitivities were evaluated by glucose and insulin tolerance tests. Liver, muscle, adipose tissues were taken for lipid analysis. Real-time polymerase chain reaction and western blotting were used to examine the gene and protein expression of molecules involved in adipogenesis and lipolysis in tissues.</p> <p>Results</p> <p>Casein injection elevated serum levels of IL-6 and SAA in mice, which are associated with increased lipid accumulation in liver and muscle, suggesting that chronic systemic inflammation induces ectopic lipid deposition in nonadipose tissues. The inflammatory stress upregulated mRNA and protein expression of sterol regulatory element binding protein 1, fatty acid synthase, and acetyl CoA carboxylase alpha, while inhibited these molecules expression in adipose. Interestingly, in the same experimental setting, inflammation increased triglyceride lipase and hormone-sensitive lipase expression in white adipose tissue. Inflammation also induced insulin resistance and increased serum free fatty acid levels in C57BL/6J mice.</p> <p>Conclusions</p> <p>Chronic systemic inflammation increased lipogenesis in nonadipose tissues and lipolysis in white adipose tissue, resulting in ectopic lipid deposition in nonadipose tissues. This disturbed free fatty acid homeostasis and caused insulin resistance in C57BL/6J mice.</p