A path-oriented encoding evolutionary algorithm for network coding resource minimization

Network coding is an emerging telecommunication technique, where any intermediate node is allowed to recombine incoming data if necessary. This technique helps to increase the throughput, however, very likely at the cost of huge amount of computational overhead, due to the packet recombination performed (ie coding operations). Hence, it is of practical importance to reduce coding operations while retaining the benefits that network coding brings to us. In this paper, we propose a novel evolutionary algorithm (EA) to minimize the amount of coding operations involved. Different from the state-of-the-art EAs which all use binary encodings for the problem, our EA is based on path-oriented encoding. In this new encoding scheme, each chromosome is represented by a union of paths originating from the source and terminating at one of the receivers. Employing path-oriented encoding leads to a search space where all solutions are feasible, which fundamentally facilitates more efficient search of EAs. Based on the new encoding, we develop three basic operators, that is, initialization, crossover and mutation. In addition, we design a local search operator to improve the solution quality and hence the performance of our EA. The simulation results demonstrate that our EA significantly outperforms the state-of-the-art algorithms in terms of global exploration and computational time

A Small Peptide Modeled after the NRAGE Repeat Domain Inhibits XIAP-TAB1-TAK1 Signaling for NF-κB Activation and Apoptosis in P19 Cells

In normal growth and development, apoptosis is necessary to shape the central nervous system and to eliminate excess neurons which are not required for innervation. In some diseases, however, apoptosis can be either overactive as in some neurodegenerative disorders or severely attenuated as in the spread of certain cancers. Bone morphogenetic proteins (BMPs) transmit signals for regulating cell growth, differentiation, and apoptosis. Responding to BMP receptors stimulated from BMP ligands, neurotrophin receptor-mediated MAGE homolog (NRAGE) binds and functions with the XIAP-TAK1-TAB1 complex to activate p38MAPK and induces apoptosis in cortical neural progenitors. NRAGE contains a unique repeat domain that is only found in human, mouse, and rat homologs that we theorize is pivotal in its BMP MAPK role. Previously, we showed that deletion of the repeat domain inhibits apoptosis, p38MAPK phosphorylation, and caspase-3 cleavage in P19 neural progenitor cells. We also showed that the XIAP-TAB1-TAK1 complex is dependent on NRAGE for IKK-α/β phosphorylation and NF-κB activation. XIAP is a major inhibitor of caspases, the main executioners of apoptosis. Although it has been shown previously that NRAGE binds to the RING domain of XIAP, it has not been determined which NRAGE domain binds to XIAP. Here, we used fluorescence resonance energy transfer (FRET) to determine that there is a strong likelihood of a direct interaction between NRAGE and XIAP occurring at NRAGE's unique repeat domain which we also attribute to be the domain responsible for downstream signaling of NF-κB and activating IKK subunits. From these results, we designed a small peptide modeled after the NRAGE repeat domain which we have determined inhibits NF-κB activation and apoptosis in P19 cells. These intriguing results illustrate that the paradigm of the NRAGE repeat domain may hold promising therapeutic strategies in developing pharmaceutical solutions for combating harmful diseases involving excessive downstream BMP signaling, including apoptosis

Mapping and linking supply- and demand-side measures in climate-smart agriculture. A review

Climate change and food security are two of humanity’s greatest challenges and are highly interlinked. On the one hand, climate change puts pressure on food security. On the other hand, farming significantly contributes to anthropogenic greenhouse gas emissions. This calls for climate-smart agriculture—agriculture that helps to mitigate and adapt to climate change. Climate-smart agriculture measures are diverse and include emission reductions, sink enhancements, and fossil fuel offsets for mitigation. Adaptation measures include technological advancements, adaptive farming practices, and financial management. Here, we review the potentials and trade-offs of climate-smart agricultural measures by producers and consumers. Our two main findings are as follows: (1) The benefits of measures are often site-dependent and differ according to agricultural practices (e.g., fertilizer use), environmental conditions (e.g., carbon sequestration potential), or the production and consumption of specific products (e.g., rice and meat). (2) Climate-smart agricultural measures on the supply side are likely to be insufficient or ineffective if not accompanied by changes in consumer behavior, as climate-smart agriculture will affect the supply of agricultural commodities and require changes on the demand side in response. Such linkages between demand and supply require simultaneous policy and market incentives. It, therefore, requires interdisciplinary cooperation to meet the twin challenge of climate change and food security. The link to consumer behavior is often neglected in research but regarded as an essential component of climate-smart agriculture. We argue for not solely focusing research and implementation on one-sided measures but designing good, site-specific combinations of both demand- and supply-side measures to use the potential of agriculture more effectively to mitigate and adapt to climate change