Microscales of hydromagnetic channel flow

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/76904/1/AIAA-1994-695-101.pd

Modelling natural disturbances in forest ecosystems: a review

Natural disturbances play a key role in ecosystem dynamics and are important factors for sustainable forest ecosystem management. Quantitative models are frequently employed to tackle the complexities associated with disturbance processes. Here we review the wide variety of approaches to modelling natural disturbances in forest ecosystems, addressing the full spectrum of disturbance modelling from single events to integrated disturbance regimes. We applied a general, process-based framework founded in disturbance ecology to analyze modelling approaches for drought, wind, forest fires, insect pests and ungulate browsing. Modelling approaches were reviewed by disturbance agent and mechanism, and a set of general disturbance modelling concepts was deduced. We found that although the number of disturbance modelling approaches emerging over the last 15 years has increased strongly, statistical concepts for descriptive modelling are still largely prevalent over mechanistic concepts for explanatory and predictive applications. Yet, considering the increasing importance of disturbances for forest dynamics and ecosystem stewardship under anthropogenic climate change, the latter concepts are crucial tool for understanding and coping with change in forest ecosystems. Current challenges for disturbance modelling in forest ecosystems are thus (i) to overcome remaining limits in process understanding, (ii) to further a mechanistic foundation in disturbance modelling, (iii) to integrate multiple disturbance processes in dynamic ecosystem models for decision support in forest management, and (iv) to bring together scaling capabilities across several levels of organization with a representation of system complexity that captures the emergent behaviour of disturbance regimes. (C) 2010 Elsevier B.V. All rights reserved

Prognostic impact of progression to induction chemotherapy and prior paclitaxel therapy in patients with germ cell tumors receiving salvage high-dose chemotherapy in the last 10 years: A study of the European Society for Blood and Marrow Transplantation Solid Tumors Working Party

Little is known about the prognostic impact of prior paclitaxel therapy and response to induction chemotherapy defined as the regimen preceding high-dose chemotherapy (HDCT) for the salvage therapy of advanced germ cell tumors. Twenty European Society for Blood and Marrow Transplantation centers contributed data on patients treated between 2002 and 2012. Paclitaxel used in either prior lines of therapy or in induction-mobilization regimens was considered. Multivariable Cox analyses of prespecified factors were undertaken on PFS and overall survival (OS). As of October 2013, data for 324 patients had been contributed to this study. One hundred and ninety-two patients (59.3%) had received paclitaxel. Sixty-one patients (19%) had a progression to induction chemotherapy, 234 (72%) a response (29 (9%) missing or granulocyte colony-stimulating factor without chemotherapy). Both progression to induction chemotherapy and prior paclitaxel were significantly associated with shorter OS univariably (P<0.001 and P=0.032). On multivariable analysis from the model with fully available data (N=216) progression to induction was significantly prognostic for PFS and OS (P=0.003), but prior paclitaxel was not (P=0.674 and P=0.739). These results were confirmed after multiple imputation of missing data. Progression to induction chemotherapy could be demonstrated as an independent prognostic factor, in contrast to prior paclitaxel

An evaluation tool kit of air quality micro-sensing units.

Recent developments in sensory and communication technologies have made the development of portable air-quality (AQ) micro-sensing units (MSUs) feasible. These MSUs allow AQ measurements in many new applications, such as ambulatory exposure analyses and citizen science. Typically, the performance of these devices is assessed using the mean error or correlation coefficients with respect to a laboratory equipment. However, these criteria do not represent how such sensors perform outside of laboratory conditions in large-scale field applications, and do not cover all aspects of possible differences in performance between the sensor-based and standardized equipment, or changes in performance over time. This paper presents a comprehensive Sensor Evaluation Toolbox (SET) for evaluating AQ MSUs by a range of criteria, to better assess their performance in varied applications and environments. Within the SET are included four new schemes for evaluating sensors' capability to: locate pollution sources; represent the pollution level on a coarse scale; capture the high temporal variability of the observed pollutant and their reliability. Each of the evaluation criteria allows for assessing sensors' performance in a different way, together constituting a holistic evaluation of the suitability and usability of the sensors in a wide range of applications. Application of the SET on measurements acquired by 25 MSUs deployed in eight cities across Europe showed that the suggested schemes facilitates a comprehensive cross platform analysis that can be used to determine and compare the sensors' performance. The SET was implemented in R and the code is available on the first author's website.CITI-SENSE, initiated in October 2012, is a four year Collaborative Project partly funded by the EU FP7-ENV-2012 under grant agreement 308524

Comparison and combination of reduced-order modelling techniques in 3D parametrized heat transfer problems

Reduced Basis (RB) method has successfully been used in 2D to solve heat transfer parametrized problems. In this work, we present some 3D applications in the same field. We consider two problems, the steady Thermal Fin and the time dependent Graetz Flow, we compare two reduced order modelling techniques: RB and Proper Orthogonal Decomposition (POD), then we apply a combination of the two strategies in the time dependent case