Asymptotically Optimal Approximation Algorithms for Coflow Scheduling

Many modern datacenter applications involve large-scale computations composed of multiple data flows that need to be completed over a shared set of distributed resources. Such a computation completes when all of its flows complete. A useful abstraction for modeling such scenarios is a {\em coflow}, which is a collection of flows (e.g., tasks, packets, data transmissions) that all share the same performance goal. In this paper, we present the first approximation algorithms for scheduling coflows over general network topologies with the objective of minimizing total weighted completion time. We consider two different models for coflows based on the nature of individual flows: circuits, and packets. We design constant-factor polynomial-time approximation algorithms for scheduling packet-based coflows with or without given flow paths, and circuit-based coflows with given flow paths. Furthermore, we give an $O(\log n/\log \log n)$-approximation polynomial time algorithm for scheduling circuit-based coflows where flow paths are not given (here $n$ is the number of network edges). We obtain our results by developing a general framework for coflow schedules, based on interval-indexed linear programs, which may extend to other coflow models and objective functions and may also yield improved approximation bounds for specific network scenarios. We also present an experimental evaluation of our approach for circuit-based coflows that show a performance improvement of at least 22% on average over competing heuristics.Comment: Fixed minor typo

Genome Mutational and Transcriptional Hotspots Are Traps for Duplicated Genes and Sources of Adaptations

[EN] Gene duplication generates new genetic material, which has been shown to lead to major innovations in unicellular and multicellular organisms. A whole-genome duplication occurred in the ancestor of Saccharomyces yeast species but 92% of duplicates returned to single-copy genes shortly after duplication. The persisting duplicated genes in Saccharomyces led to the origin of major metabolic innovations, which have been the source of the unique biotechnological capabilities in the Baker's yeast Saccharomyces cerevisiae. What factors have determined the fate of duplicated genes remains unknown. Here, we report the first demonstration that the local genome mutation and transcription rates determine the fate of duplicates. We show, for the first time, a preferential location of duplicated genes in the mutational and transcriptional hotspots of S. cerevisiae genome. The mechanism of duplication matters, with whole-genome duplicates exhibiting different preservation trends compared to small-scale duplicates. Genome mutational and transcriptional hotspots are rich in duplicates with large repetitive promoter elements. Saccharomyces cerevisiae shows more tolerance to deleterious mutations in duplicates with repetitive promoter elements, which in turn exhibit higher transcriptional plasticity against environmental perturbations. Our data demonstrate that the genome traps duplicates through the accelerated regulatory and functional divergence of their gene copies providing a source of novel adaptations in yeast.This study was supported by a grant (reference: FEDER-BFU2015-66073-P) from the Spanish Ministerio de Economia y Competitividad-FEDER and a grant (reference: ACOMP/2015/026) from the local government Conselleria de Educacion Investigacion, Cultura y Deporte, Generalitat Valenciana to M.A.F. 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MHC class I molecules and Antigen Presentation

Research in Dolan lab focuses primarily on the adaptive immune system and ways it can be better utilized to eliminate infected or transformed cells. Research focuses on the major histocompatibility (MHC) class I antigen presentation pathway, which plays an important role in alerting the immune system of the presence of intracellular pathogens. When infected, cells notify the immune system of a foreign body by degrading intracellular proteins and presenting the resultant peptides on MHC class I molecules at the cell surface. These peptide-MHC class I complexes are presented on the surface to allow for interaction with the T cell receptors expressed on cytotoxic T lymphocytes. If the T cell recognizes the peptide presented as foreign, they are able to react and kill the cell. In addition to foreign peptides, tumor cells can also present peptides that are tumor-specific and can be recognized by cytotoxic T cells. This process allows cells displaying peptides from infectious or neoplastic agents to be removed by T cells.In order to study antigen presentation, including DRiP presentation the lab has developed a model protein which contains a destabilization domain, followed by an antigenic peptide, and then a fluorescent protein. We can control protein stability by adding a small molecules which interacts with the destabilization domain and allows the protein to fold and function properly. We have so far created two constructs that contain different antigenic peptides which bind to different MHC class I molecules

On the Connection Between Flap Side-Edge Noise and Tip Vortex Dynamics

The goal of the present work is to investigate how the dynamics of the vortical flow about the flap side edge of an aircraft determine the acoustic radiation. A validated lattice- Boltzmann CFD solution of the unsteady flow about a detailed business jet configuration in approach conditions is used for the present analysis. Evidence of the connection between the noise generated by several segments of the inboard flap tip and the aerodynamic forces acting on the same segments is given, proving that the noise generation mechanism has a spatially coherent and acoustically compact character on the scale of the flap chord, and that the edge-scattering effects are of secondary importance. Subsequently, evidence of the connection between the kinematics of the tip vortex system and the aerodynamic force is provided. The kinematics of the dual vortex system are investigated via a core detection technique. Emphasis is placed on the mutual induction effects between the two main vortices rolling up from the pressure and suction sides of the flap edge. A simple heuristic formula that relates the far-field noise spectrum and the cross-spectrum of the unsteady vortical positions is developed

Environmental controls on ozone fluxes in a poplar plantation in Western Europe

Tropospheric O-3 is a strong oxidant that may affect vegetation and human health. Here we report on the O-3 fluxes from a poplar plantation in Belgium during one year. Surprisingly, the winter and autumn O-3 fluxes were of similar magnitude to ones observed during most of the peak vegetation development. Largest O-3 uptakes were recorded at the beginning of the growing season in correspondence to a minimum stomatal uptake. Wind speed was the most important control and explained 44% of the variability in the nighttime O-3 fluxes, suggesting that turbulent mixing and the mechanical destruction of O-3 played a substantial role in the O-3 fluxes. The stomatal O-3 uptake accounted for a seasonal average of 59% of the total O-3 uptake. Multiple regression and partial correlation analyses showed that net ecosystem exchange was not affected by the stomatal O-3 uptake. (C) 2013 The Authors. Published by Elsevier Ltd. All rights reserved

Interpenetrating network gelatin methacryloyl (GelMA) and pectin-g-PCL hydrogels with tunable properties for tissue engineering.

The design of new hydrogel-based biomaterials with tunable physical and biological properties is essential for the advancement of applications related to tissue engineering and regenerative medicine. For instance, interpenetrating polymer network (IPN) and semi-IPN hydrogels have been widely explored to engineer functional tissues due to their characteristic microstructural and mechanical properties. Here, we engineered IPN and semi-IPN hydrogels comprised of a tough pectin grafted polycaprolactone (pectin-g-PCL) component to provide mechanical stability, and a highly cytocompatible gelatin methacryloyl (GelMA) component to support cellular growth and proliferation. IPN hydrogels were formed by calcium ion (Ca2+)-crosslinking of pectin-g-PCL chains, followed by photocrosslinking of the GelMA precursor. Conversely, semi-IPN networks were formed by photocrosslinking of the pectin-g-PCL and GelMA mixture, in the absence of Ca2+ crosslinking. IPN and semi-IPN hydrogels synthesized with varying ratios of pectin-g-PCL to GelMA, with and without Ca2+-crosslinking, exhibited a broad range of mechanical properties. For semi-IPN hydrogels, the aggregation of microcrystalline cores led to formation of hydrogels with compressive moduli ranging from 3.1 to 10.4 kPa. For IPN hydrogels, the mechanistic optimization of pectin-g-PCL, GelMA, and Ca2+ concentrations resulted in hydrogels with comparatively higher compressive modulus, in the range of 39 kPa-5029 kPa. Our results also showed that IPN hydrogels were cytocompatible in vitro and could support the growth of three-dimensionally (3D) encapsulated MC3T3-E1 preosteoblasts in vitro. The simplicity, technical feasibility, low cost, tunable mechanical properties, and cytocompatibility of the engineered semi-IPN and IPN hydrogels highlight their potential for different tissue engineering and biomedical applications

Artificial intelligence in orthopaedic surgery

The use of artificial intelligence (AI) is rapidly growing across many domains, of which the medical field is no exception. AI is an umbrella term defining the practical application of algorithms to generate useful output, without the need of human cognition. Owing to the expanding volume of patient information collected, known as ‘big data’, AI is showing promise as a useful tool in healthcare research and across all aspects of patient care pathways. Practical applications in orthopaedic surgery include: diagnostics, such as fracture recognition and tumour detection; predictive models of clinical and patient-reported outcome measures, such as calculating mortality rates and length of hospital stay; and real-time rehabilitation monitoring and surgical training. However, clinicians should remain cognizant of AI’s limitations, as the development of robust reporting and validation frameworks is of paramount importance to prevent avoidable errors and biases. The aim of this review article is to provide a comprehensive understanding of AI and its subfields, as well as to delineate its existing clinical applications in trauma and orthopaedic surgery. Furthermore, this narrative review expands upon the limitations of AI and future direction