41 research outputs found
Dynamics of semiconductor lasers subject to delayed optical feedback: the short cavity regime,”
We give experimental and numerical evidence for a new dynamical regime in the operation of semiconductor lasers subject to delayed optical feedback occurring for short delay times. This short cavity regime is dominated by a striking dynamical phenomenon: regular pulse packages forming a robust low-frequency state with underlying fast, regular intensity pulsations. We demonstrate that these regular pulse packages correspond to trajectories moving on global orbits comprising several destabilized fixed points within the complicated phase space structure of this delay system. DOI: 10.1103/PhysRevLett.87.243901 PACS numbers: 42.65.Sf, 05.45.Jn, 42.55.Px Delayed feedback dominated systems are encountered extensively in the physical world and are of fundamental importance. They are found in models of diffusion and thermochemical reactions. In biology they occur in blood cell production, neural control, and drug delivery, and have applications in respiratory physiology In this paper, we present the first temporally resolved investigations of the dynamics of SLs operating in the short cavity regime (SCR). We demonstrate that this new dynamical regime is characterized by striking regular pulse packages (RPP) in the intensity dynamics of the system. Our numerical analysis demonstrates that RPP correspond to well-defined global orbits in phase space always along the same series of destabilized attractors and unstable saddle points. 243901-1 0031-9007Íž01Íž 87(24)Íž243901(4)$15.0
Dynamics of semiconductor lasers subject to delayed optical feedback: the short cavity regime,”
We give experimental and numerical evidence for a new dynamical regime in the operation of semiconductor lasers subject to delayed optical feedback occurring for short delay times. This short cavity regime is dominated by a striking dynamical phenomenon: regular pulse packages forming a robust low-frequency state with underlying fast, regular intensity pulsations. We demonstrate that these regular pulse packages correspond to trajectories moving on global orbits comprising several destabilized fixed points within the complicated phase space structure of this delay system. DOI: 10.1103/PhysRevLett.87.243901 PACS numbers: 42.65.Sf, 05.45.Jn, 42.55.Px Delayed feedback dominated systems are encountered extensively in the physical world and are of fundamental importance. They are found in models of diffusion and thermochemical reactions. In biology they occur in blood cell production, neural control, and drug delivery, and have applications in respiratory physiology In this paper, we present the first temporally resolved investigations of the dynamics of SLs operating in the short cavity regime (SCR). We demonstrate that this new dynamical regime is characterized by striking regular pulse packages (RPP) in the intensity dynamics of the system. Our numerical analysis demonstrates that RPP correspond to well-defined global orbits in phase space always along the same series of destabilized attractors and unstable saddle points. 243901-1 0031-9007Íž01Íž 87(24)Íž243901(4)$15.0
Ion irradiation triggers the formation of the precursors of complex organics in space - The case of formaldehyde and acetaldehyde
Context. Cosmic rays and solar energetic particles induce changes in the composition of compounds frozen onto dust grains in the interstellar medium (ISM), in comets, and on the surfaces of atmosphere-less small bodies in the outer Solar System. This induces the destruction of pristine compounds and triggers the formation of various species, including the precursors of complex organics.
Aims. We investigate the role of energetic ions in the formation of formaldehyde (H2CO) and acetaldehyde (CH3CHO), which are observed in the ISM and in comets, and which are thought to be the precursors of more complex compounds such as hexamethylenete-tramine (HMT), which is found in carbonaceous chondrites and in laboratory samples produced after the irradiation and warm-up of astrophysical ices.
Methods. We performed ion irradiation of water, methanol, and ammonia mixtures at 14–18 K. We bombarded frozen films with 40–200 keV H+ that simulate solar energetic particles and low-energy cosmic rays. Samples were analysed by infrared transmission spectroscopy.
Results. Among other molecules, we observe the formation of H2CO and CH3CHO, and we find that their abundance depends on the dose and on the stoichiometry of the mixtures. We find that the H2CO abundance reaches the highest value after a dose of 10 eV/16u and then it decreases as the dose increases.
Conclusions. The data suggest that surfaces exposed to high doses are depleted in H2CO. This explains why the amount of HMT in organic residues and that formed after irradiation of ices depends on the dose deposited in the ice. Because the H2CO abundance decreases at doses higher than 10 eV/16u, a lower quantity of H2CO is available to form HMT during the subsequent warm-up. The H2CO abundances caused by ion bombardment are insufficient to explain the ISM abundances, but ion bombardment can account for the abundance of CH3CHO towards the ISM and comets
Long-term outcome prediction by clinicopathological risk classification algorithms in node-negative breast cancer—comparison between Adjuvant!, St Gallen, and a novel risk algorithm used in the prospective randomized Node-Negative-Breast Cancer-3 (NNBC-3) trial
Background: Defining risk categories in breast cancer is of considerable clinical significance. We have developed a novel risk classification algorithm and compared its prognostic utility to the Web-based tool Adjuvant! and to the St Gallen risk classification. Patients and methods: After a median follow-up of 10 years, we retrospectively analyzed 410 consecutive node-negative breast cancer patients who had not received adjuvant systemic therapy. High risk was defined by any of the following criteria: (i) age 2 cm. All patients were also characterized using Adjuvant! and the St Gallen 2007 risk categories. We analyzed disease-free survival (DFS) and overall survival (OS). Results: The Node-Negative-Breast Cancer-3 (NNBC-3) algorithm enlarged the low-risk group to 37% as compared with Adjuvant! (17%) and St Gallen (18%), respectively. In multivariate analysis, both Adjuvant! [P = 0.027, hazard ratio (HR) 3.81, 96% confidence interval (CI) 1.16-12.47] and the NNBC-3 risk classification (P = 0.049, HR 1.95, 95% CI 1.00-3.81) significantly predicted OS, but only the NNBC-3 algorithm retained its prognostic significance in multivariate analysis for DFS (P < 0.0005). Conclusion: The novel NNBC-3 risk algorithm is the only clinicopathological risk classification algorithm significantly predicting DFS as well as O
Review and Recommendations for Experimentations in Earth Orbit and Beyond
The space environment is regularly used for experiments addressing
astrobiology research goals. The specific conditions prevailing in Earth orbit
and beyond, notably the radiative environment (photons and energetic
particles) and the possibility to conduct long-duration measurements, have
been the main motivations for developing experimental concepts to expose
chemical or biological samples to outer space, or to use the reentry of a
spacecraft on Earth to simulate the fall of a meteorite. This paper represents
an overview of past and current research in astrobiology conducted in Earth
orbit and beyond, with a special focus on ESA missions such as Biopan, STONE
(on Russian FOTON capsules) and EXPOSE facilities (outside the International
Space Station). The future of exposure platforms is discussed, notably how
they can be improved for better science return, and how to incorporate the use
of small satellites such as those built in cubesat format
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Missing steps in a staircase: a qualitative study of the perspectives of key stakeholders on the use of adaptive designs in confirmatory trials
Background
Despite the promising benefits of adaptive designs (ADs), their routine use, especially in confirmatory trials, is lagging behind the prominence given to them in the statistical literature. Much of the previous research to understand barriers and potential facilitators to the use of ADs has been driven from a pharmaceutical drug development perspective, with little focus on trials in the public sector. In this paper, we explore key stakeholders’ experiences, perceptions and views on barriers and facilitators to the use of ADs in publicly funded confirmatory trials.
Methods
Semi-structured, in-depth interviews of key stakeholders in clinical trials research (CTU directors, funding board and panel members, statisticians, regulators, chief investigators, data monitoring committee members and health economists) were conducted through telephone or face-to-face sessions, predominantly in the UK. We purposively selected participants sequentially to optimise maximum variation in views and experiences. We employed the framework approach to analyse the qualitative data.
Results
We interviewed 27 participants. We found some of the perceived barriers to be: lack of knowledge and experience coupled with paucity of case studies, lack of applied training, degree of reluctance to use ADs, lack of bridge funding and time to support design work, lack of statistical expertise, some anxiety about the impact of early trial stopping on researchers’ employment contracts, lack of understanding of acceptable scope of ADs and when ADs are appropriate, and statistical and practical complexities. Reluctance to use ADs seemed to be influenced by: therapeutic area, unfamiliarity, concerns about their robustness in decision-making and acceptability of findings to change practice, perceived complexities and proposed type of AD, among others.
Conclusions
There are still considerable multifaceted, individual and organisational obstacles to be addressed to improve uptake, and successful implementation of ADs when appropriate. Nevertheless, inferred positive change in attitudes and receptiveness towards the appropriate use of ADs by public funders are supportive and are a stepping stone for the future utilisation of ADs by researchers
Adaptive designs undertaken in clinical research: a review of registered clinical trials
Adaptive designs have the potential to improve efficiency in the evaluation of new medical treatments in comparison to traditional fixed sample size designs. However, they are still not widely used in practice in clinical research. Little research has been conducted to investigate what adaptive designs are being undertaken. This review highlights the current state of registered adaptive designs and their characteristics. The review looked at phase II, II/III and III trials registered on ClinicalTrials.gov from 29 February 2000 to 1 June 2014, supplemented with trials from the National Institute for Health Research register and known adaptive trials. A range of adaptive design search terms were applied to the trials extracted from each database. Characteristics of the adaptive designs were then recorded including funder, therapeutic area and type of adaptation. The results in the paper suggest that the use of adaptive designs has increased. They seem to be most often used in phase II trials and in oncology. In phase III trials, the most popular form of adaptation is the group sequential design. The review failed to capture all trials with adaptive designs, which suggests that the reporting of adaptive designs, such as in clinical trials registers, needs much improving. We recommend that clinical trial registers should contain sections dedicated to the type and scope of the adaptation and that the term 'adaptive design' should be included in the trial title or at least in the brief summary or design sections
Trench filling with a-Si using a PE-CVD process and back etch sequence
A trench filling process with amorphous silicon (a-Si) using a PE-CVD process has been developed, which allows to tune the filling behavior at the wafer surface. Appropriate void adjustment has been achieved by using a deposition and back etch sequence on the PE-CVD tool. This trench filling sequence allows to combine a bulk MEMS process (including deep trenches) with a subsequent surface MEMS processing on a flat wafer surface. The whole process is CMOS compatible allowing monolithical integration of bulk and surface MEMS structure on prefabricated CMOS wafers
Dynamics of semiconductor lasers subjects to delayed optical feedback: the short cavity regime
Process improvement through economically driven routing of instances
Purpose – Process improvement is a fundamental activity of the business process management (BPM) lifecycle. However, practitioners still lack concrete guidance and adequate objectives for process improvement. Moreover, improvement projects typically tie up considerable amounts of capital and are very risky. Thus, more guidance is needed on how to derive concrete recommendations for process improvement in a goal-oriented manner. The paper aims to discuss these issues. Design/methodology/approach – The authors propose a decision model that determines along which paths the instances of a process should be routed to maximize the value contribution of the process. To do so, the decision model requires a process model and a set of historical process instances as inputs. Findings – The decision model builds on the idea that only the parameters of the process, i.e., the values according to which it is decided on which path an instance traverses the process, can be modified, without altering the structure of the process. The decision model determines the parameter setting that maximizes the value contribution of the process, which is measured in terms of the expected cash flow of the process. When determining the optimal parameter setting, the decision model considers that different instances and paths have different cash flow effects. Practical implications – The authors prototypically implemented the decision model and report on the insights from a demonstration example that is based on the order verification process of an IT distributor. Originality/value – The decision model complements existing approaches to process improvement as it reveals additional improvement potential by focussing on the decision points in a process without altering the structure of the process. The decision model also enables identifying an optimal parameter setting, as a concrete recommendation for process improvement, in line with the principles of value-based BPM