Anastomotic leak in ovarian cancer cytoreduction surgery: a systematic review and meta-analysis

Introduction: Anastomotic leaks (AL) following ovarian cytoreduction surgery could be detrimental, leading to significant delays in commencing adjuvant chemotherapy, prolonged hospital stays and increased morbidity. The aim of this study was to investigate risk factors associated with anastomotic leaks after ovarian cytoreduction surgery. Material and methods: The MEDLINE (via PubMed), Cochrane Library, EMBASE and Scopus bibliographical databases were searched. Original clinical studies investigating risk factors for AL in ovarian cytoreduction surgery were included. Results: Eighteen studies with non-overlapping populations reporting on patients undergoing cytoreduction surgery for ovarian cancer (n = 4622, including 344 cases complicated by AL) were included in our analysis. Patients undergoing ovarian cytoreduction surgery complicated by AL had a significantly higher rate of 30-day mortality but no difference in 60-day mortality. Multiple bowel resections were associated with an increased risk of postoperative AL, while no association was observed with body mass index (BMI), American Society of Anesthesiologists (ASA) score, age, smoking, operative approach (primary versus interval cytoreductive, stapled versus hand-sewn anastomoses and formation of diverting stoma), neoadjuvant chemotherapy and use of hyperthermic intraperitoneal chemotherapy (HIPEC). Discussion: Multiple bowel resections were the only clinical risk factor associated with increased risk for AL after bowel surgery in the ovarian cancer population. The increased 30-day mortality rate in patients undergoing ovarian cytoreduction complicated by AL highlights the need to minimize the number of bowel resections in this population. Further studies are required to clarify any association between neoadjuvant chemotherapy and decreased AL rates

Multi-sensor measurement of dynamic deflections and structural health monitoring of flexible and stiff bridges

We investigated the response of bridges of different types to controlled and to wind and traffic-induced excitations; the emphasis was on deflections,derived from recordings of geodetic sensors and accelerometers (output-only analysis). Our focus was to push the limits of the existing experimental techniques, in order to cover not only flexible, but also stiff structures, and to present independently validated results. Our study focused on a 700m long, thin-deck cable-stayed bridge, a stiff steel pedestrian bridge, a historic composite (masonry/steel) train bridge and a 30m long, gradually decaying, currently swaying pedestrian timber bridge. Our basic strategy was first to develop data measurement and processing techniques using controlled (supervised learning) experiments, and then, (1) use collocated, redundant and distributed geodetic sensors (GPS/GNSS and Robotic Total Stations, RTS), as well as accelerometers, in order to record bridge excitations, especially con-trolled excitations leading to free attenuating oscillations;(2) develop techniques to denoise recordings of various sensors based on structural/logical constraints and sensor fusion, compensating for the weaknesses inherent in each type of sensor), validate results and avoid pitfalls;(3) monitor the episodic and gradual decay of a pedestrian bridge, through repeated surveys under similar loading and environmental conditions and using similar instrumentation.The output of our studies is to confirm the potential of modern sensors to measure, under certain conditions, reliable mm-level dynamic deflections even of stiff structures (3-6Hz dominant frequencies) and to provide firm constraints for structural analysis, including evidence for changes of first modal frequencies produced by structural decay, even to identify dynamic effects such as foundations response to dynamic loading

Manifold learning for the emulation of spatial fields from computational models

Repeated evaluations of expensive computer models in applications such as design optimization and uncertainty quantification can be computationally infeasible. For partial differential equation (PDE) models, the outputs of interest are often spatial fields leading to high-dimensional output spaces. Although emulators can be used to find faithful and computationally inexpensive approximations of computer models, there are few methods for handling high-dimensional output spaces. For Gaussian process (GP) emulation, approximations of the correlation structure and/or dimensionality reduction are necessary. Linear dimensionality reduction will fail when the output space is not well approximated by a linear subspace of the ambient space in which it lies. Manifold learning can overcome the limitations of linear methods if an accurate inverse map is available. In this paper, we use kernel PCA and diffusion maps to construct GP emulators for very high-dimensional output spaces arising from PDE model simulations. For diffusion maps we develop a new inverse map approximation. Several examples are presented to demonstrate the accuracy of our approach

An integrated platform for intuitive mathematical programming modeling using LaTeX

This paper presents a novel prototype platform that uses the same LaTeX mark-up language, commonly used to typeset mathematical content, as an input language for modeling optimization problems of various classes. The platform converts the LaTeX model into a formal Algebraic Modeling Language (AML) representation based on Pyomo through a parsing engine written in Python and solves by either via NEOS server or locally installed solvers, using a friendly Graphical User Interface (GUI). The distinct advantages of our approach can be summarized in (i) simplification and speed-up of the model design and development process (ii) non-commercial character (iii) cross-platform support (iv) easier typo and logic error detection in the description of the models and (v) minimization of working knowledge of programming and AMLs to perform mathematical programming modeling. Overall, this is a presentation of a complete workable scheme on using LaTeX for mathematical programming modeling which assists in furthering our ability to reproduce and replicate scientific work

Catalytic Fast Pyrolysis of Kraft Lignin With Conventional, Mesoporous and Nanosized ZSM-5 Zeolite for the Production of Alkyl-Phenols and Aromatics

The valorization of lignin that derives as by product in various biomass conversion processes has become a major research and technological objective. The potential of the production of valuable mono-aromatics (BTX and others) and (alkyl)phenols by catalytic fast pyrolysis of lignin is investigated in this work by the use of ZSM-5 zeolites with different acidic and porosity characteristics. More specifically, conventional microporous ZSM-5 (Si/Al = 11.5, 25, 40), nano-sized (≤20 nm, by direct synthesis) and mesoporous (9 nm, by mild alkaline treatment) ZSM-5 zeolites were tested in the fast pyrolysis of a softwood kraft lignin at 400–600°C on a Py/GC-MS system and a fixed-bed reactor unit. The composition of lignin (FT-IR, 2D HSQC NMR) was correlated with the composition of the thermal (non-catalytic) pyrolysis oil, while the effect of pyrolysis temperature and catalyst-to-lignin (C/L) ratio, as well as of the Si/Al ratio, acidity, micro/mesoporosity and nano-size of ZSM-5, on bio-oil composition was thoroughly investigated. It was shown that the conventional microporous ZSM-5 zeolites are more selective toward mono-aromatics while the nano-sized and mesoporous ZSM-5 exhibited also high selectivity for (alkyl)phenols. However, the nano-sized ZSM-5 zeolite exhibited the lowest yield of organic bio-oil and highest production of water, coke and non-condensable gases compared to the conventional microporous and mesoporous ZSM-5 zeolites

The mechanical properties and the deformation microstructures of the C15 Laves phase Cr2Nb at high temperatures

Compression tests between 1250 and 1550 degrees C and 10(-5) and 5 x 10(-3) s(-1) and transmission electron microscopy have been employed to investigate the high temperature mechanical properties and the deformation mechanisms of the C15 Cr2Nb Laves phase. The stress-peaks in the compression curves during yielding were explained using a mechanism similar to strain aging combined with a low initial density of mobile dislocations. The primary deformation mechanism is slip by extended dislocations with Burgers vector 1/2 <110 >, whereas twinning is more frequent at 10(-4) s(-1). Schmid factor analysis indicated that twinning is more probable in grains oriented so as to have two co-planar twinning systems with high and comparable resolved shear stresses. Twinning produced very anisotropic microstructures. This may be due to synchroshear: a self-pinning mechanism which requires co-operative motion of zonal dislocations. (c) 2006 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved

On the commutability of homogenization and linearization in finite elasticity

We study non-convex elastic energy functionals associated to (spatially) periodic, frame indifferent energy densities with a single non-degenerate energy well at SO(n). Under the assumption that the energy density admits a quadratic Taylor expansion at identity, we prove that the Gamma-limits associated to homogenization and linearization commute. Moreover, we show that the homogenized energy density, which is determined by a multi-cell homogenization formula, has a quadratic Taylor expansion with a quadratic term that is given by the homogenization of the quadratic term associated to the linearization of the initial energy density

Techno-economic optimization of a process superstructure for lignin valorization

Lignin, the most abundant aromatic biopolymer on Earth, is often considered a biorefinery by-product, despite its potential to be valorized into high-added-value chemicals and fuels. In this work, an integrated superstructure-based optimization model was set up and optimized using mixed-integer non-linear programming for the conversion of technical lignin to three main biobased products: aromatic monomers, phenol-formaldehyde resins, and aromatic aldehydes/acids. Several alternative conversion pathways were simultaneously compared to assess the profitability of lignins-based processes by predicting the performance of technologies with different TRL. Upon employing key technologies such as hydrothermal liquefaction, dissolution in solvent, or high-temperature electrolysis, the technical lignins could have a market value of 200 €/t when the market price for aromatic monomers, resins, and vanillin is at least 2.0, 0.8, and 15.0 €/kg, respectively. When lower product selling prices were considered, the aromatic monomers and the resins were not profitable as target products

Onset of entanglement

We have developed a theory of polymer entanglement using an extended Cahn-Hilliard functional, with two extra terms. One is a nonlocal attractive term, operating over mesoscales, which is interpreted as giving rise to entanglement, and the other a local repulsive term indicative of excluded volume interactions. We show how such a functional can be derived using notions from gauge theory. We go beyond the Gaussian approximation, to the one-loop level, to show that the system exhibits a crossover to a state of entanglement as the average chain length between points of entanglement decreases. This crossover is marked by critical slowing down, as the effective diffusion constant goes to zero. We have also computed the tensile modulus of the system, and we find a corresponding crossover to a regime of high modulus.Comment: 18 pages, with 4 figure