Topotecan-vincristine-doxorubicin in stage 4 high risk neuroblastoma patients failing to achieve a complete metastatic response to rapid COJEC : a SIOPEN study

Purpose : Metastatic response to induction therapy for high-risk neuroblastoma is a prognostic factor. In the International Society of Paediatric Oncology Europe Neuroblastoma (SIOPEN) HR-NBL-1 protocol, only patients with metastatic complete response (CR) or partial response (PR) with <= three abnormal skeletal areas on iodine 123-metaiodobenzylguanidine ([I-123] mIBG) scintigraphy and no bone marrow disease proceed to high dose therapy (HDT). In this study, topotecan-vincristine-doxorubicin (TVD) was evaluated in patients failing to achieve these criteria, with the aim of improving the metastatic response rate. Materials and Methods : Patients with metastatic high-risk neuroblastoma who had not achieved the SIOPEN criteria for HDT after induction received two courses of topotecan 1.5 mg/m(2)/day for 5 days, followed by a 48-hour infusion of vincristine, 2 mg/m(2), and doxorubicin, 45 mg/m(2). Results : Sixty-three patients were eligible and evaluable. Following two courses of TVD, four (6.4%) patients had an overall CR, while 28 (44.4%) had a PR with a combined response rate of 50.8% (95% confidence interval [CI], 37.9 to 63.6). Of these, 23 patients achieved a metastatic CR or a PR with <= 3 mIBG skeletal areas and no bone marrow disease (36.5%; 95% CI, 24.7 to 49.6) and were eligible to receive HDT. Toxicity was mostly haematological, affecting 106 of the 126 courses (84.1%; 95% CI, 76.5 to 90.0), and dose reduction was necessary in six patients. Stomatitis was the second most common nonhematological toxicity, occurring in 20 patients (31.7%). Conclusion : TVD was effective in improving the response rate of high-risk neuroblastoma patients after induction with COJEC enabling them to proceed to HDT. However, the long-term benefits of TVD needs to be determined in randomized clinical trials

RF-MEMS switch actuation pulse optimization using Taguchi's method

Copyright @ 2011 Springer-VerlagReliability and longevity comprise two of the most important concerns when designing micro-electro-mechanical-systems (MEMS) switches. Forcing the switch to perform close to its operating limits underlies a trade-off between response bandwidth and fatigue life due to the impact force of the cantilever touching its corresponding contact point. This paper presents for first time an actuation pulse optimization technique based on Taguchi’s optimization method to optimize the shape of the actuation pulse of an ohmic RF-MEMS switch in order to achieve better control and switching conditions. Simulation results show significant reduction in impact velocity (which results in less than 5 times impact force than nominal step pulse conditions) and settling time maintaining good switching speed for the pull down phase and almost elimination of the high bouncing phenomena during the release phase of the switch

Optimization of the derivative expansion in the nonperturbative renormalization group

We study the optimization of nonperturbative renormalization group equations truncated both in fields and derivatives. On the example of the Ising model in three dimensions, we show that the Principle of Minimal Sensitivity can be unambiguously implemented at order $\partial^2$ of the derivative expansion. This approach allows us to select optimized cut-off functions and to improve the accuracy of the critical exponents $\nu$ and $\eta$. The convergence of the field expansion is also analyzed. We show in particular that its optimization does not coincide with optimization of the accuracy of the critical exponents.Comment: 13 pages, 9 PS figures, published versio

Distribution of pollutants from a new paper plant in southern Lake Champlain, Vermont and New York

From November of 1973 to May of 1974, 15 arrays of sediment traps were placed along 33 km of southern Lake Champlain to sample the distribution of effluent from a large paper plant located on the western shore which had commenced operation in 1971. In the arrays located near the effluent diffuser pipeline as much as 2.3 cm of sediment accumulated, whereas elsewhere in the lake less than 1 cm accumulated. In the area of accelerated accumulation, sediments contained high concentrations of several components used in or derived from paper manufacturing. Values for kaolinite, expressed as the ratio of kaolinite to chlorite, for example, were as high as 1.4, anatase (TiO 2 ) concentrations were as high as 0.8%, organic carbon 8.7%, and phosphorus 254 µg/g; all were more abundant than in sediments collected in traps to the south or north. In surficial bottom sediments collected near each array organic carbon and phosphorus were also higher (4.2% and 127 µg/g respectively) near the diffuser than elsewhere. Thus, the new plant after three years of production measurably affected the composition of suspended sediment and surficial bottom sediment despite the construction and use of extensive facilities to reduce the flow of pollutants to the lake.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46764/1/254_2006_Article_BF02380502.pd

An improved constraint satisfaction adaptive neural network for job-shop scheduling

Copyright @ Springer Science + Business Media, LLC 2009This paper presents an improved constraint satisfaction adaptive neural network for job-shop scheduling problems. The neural network is constructed based on the constraint conditions of a job-shop scheduling problem. Its structure and neuron connections can change adaptively according to the real-time constraint satisfaction situations that arise during the solving process. Several heuristics are also integrated within the neural network to enhance its convergence, accelerate its convergence, and improve the quality of the solutions produced. An experimental study based on a set of benchmark job-shop scheduling problems shows that the improved constraint satisfaction adaptive neural network outperforms the original constraint satisfaction adaptive neural network in terms of computational time and the quality of schedules it produces. The neural network approach is also experimentally validated to outperform three classical heuristic algorithms that are widely used as the basis of many state-of-the-art scheduling systems. Hence, it may also be used to construct advanced job-shop scheduling systems.This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/01 and in part by the National Nature Science Fundation of China under Grant 60821063 and National Basic Research Program of China under Grant 2009CB320601

Icebergs in the North Atlantic: Modelling circulation changes and glacio-marine deposition

In order to investigate meltwater events in the North Atlantic, a simple iceberg generation, drift, and melting routine was implemented in a high-resolution OGCM. Starting from the modelled last glacial state, every 25th day cylindrical model icebergs 300 meters high were released at 32 specific points along the coasts. Icebergs launched at the Barents Shelf margin spread a light meltwater lid over the Norwegian and Greenland Seas, shutting down the deep convection and the anti-clockwise circulation in this area. Due to the constraining ocean circulation, the icebergs produce a tongue of relatively cold and fresh water extending eastward from Hudson Strait that must develop at this location, regardless of iceberg origin. From the total amount of freshwater inferred by the icebergs, the thickness of the deposited IRD could be calculated in dependance of iceberg sediment concentration. In this way, typical extent and thickness of Heinrich layers could be reproduced, running the model for 250 years of steady state with constant iceberg meltwater inflow

Far-infrared absorption in parallel quantum wires with weak tunneling

We study collective and single-particle intersubband excitations in a system of quantum wires coupled via weak tunneling. For an isolated wire with parabolic confinement, the Kohn's theorem guarantees that the absorption spectrum represents a single sharp peak centered at the frequency given by the bare confining potential. We show that the effect of weak tunneling between two parabolic quantum wires is twofold: (i) additional peaks corresponding to single-particle excitations appear in the absorption spectrum, and (ii) the main absorption peak acquires a depolarization shift. We also show that the interplay between tunneling and weak perpendicular magnetic field drastically enhances the dispersion of single-particle excitations. The latter leads to a strong damping of the intersubband plasmon for magnetic fields exceeding a critical value.Comment: 18 pages + 6 postcript figure

Collecting Service-Based Maintainability Metrics from RESTful API Descriptions: Static Analysis and Threshold Derivation

While many maintainability metrics have been explicitly designed for service-based systems, tool-supported approaches to automatically collect these metrics are lacking. Especially in the context of microservices, decentralization and technological heterogeneity may pose challenges for static analysis. We therefore propose the modular and extensible RAMA approach (RESTful API Metric Analyzer) to calculate such metrics from machine-readable interface descriptions of RESTful services. We also provide prototypical tool support, the RAMA CLI, which currently parses the formats OpenAPI, RAML, and WADL and calculates 10 structural service-based metrics proposed in scientific literature. To make RAMA measurement results more actionable, we additionally designed a repeatable benchmark for quartile-based threshold ranges (green, yellow, orange, red). In an exemplary run, we derived thresholds for all RAMA CLI metrics from the interface descriptions of 1,737 publicly available RESTful APIs. Researchers and practitioners can use RAMA to evaluate the maintainability of RESTful services or to support the empirical evaluation of new service interface metrics.Comment: Accepted at CSE/QUDOS workshop (collocated with ECSA 2020

Empowerment or Engagement? Digital Health Technologies for Mental Healthcare

We argue that while digital health technologies (e.g. artificial intelligence, smartphones, and virtual reality) present significant opportunities for improving the delivery of healthcare, key concepts that are used to evaluate and understand their impact can obscure significant ethical issues related to patient engagement and experience. Specifically, we focus on the concept of empowerment and ask whether it is adequate for addressing some significant ethical concerns that relate to digital health technologies for mental healthcare. We frame these concerns using five key ethical principles for AI ethics (i.e. autonomy, beneficence, non-maleficence, justice, and explicability), which have their roots in the bioethical literature, in order to critically evaluate the role that digital health technologies will have in the future of digital healthcare