Twelve-month observational study of children with cancer in 41 countries during the COVID-19 pandemic

Introduction Childhood cancer is a leading cause of death. It is unclear whether the COVID-19 pandemic has impacted childhood cancer mortality. In this study, we aimed to establish all-cause mortality rates for childhood cancers during the COVID-19 pandemic and determine the factors associated with mortality. Methods Prospective cohort study in 109 institutions in 41 countries. Inclusion criteria: children <18 years who were newly diagnosed with or undergoing active treatment for acute lymphoblastic leukaemia, non-Hodgkin's lymphoma, Hodgkin lymphoma, retinoblastoma, Wilms tumour, glioma, osteosarcoma, Ewing sarcoma, rhabdomyosarcoma, medulloblastoma and neuroblastoma. Of 2327 cases, 2118 patients were included in the study. The primary outcome measure was all-cause mortality at 30 days, 90 days and 12 months. Results All-cause mortality was 3.4% (n=71/2084) at 30-day follow-up, 5.7% (n=113/1969) at 90-day follow-up and 13.0% (n=206/1581) at 12-month follow-up. The median time from diagnosis to multidisciplinary team (MDT) plan was longest in low-income countries (7 days, IQR 3-11). Multivariable analysis revealed several factors associated with 12-month mortality, including low-income (OR 6.99 (95% CI 2.49 to 19.68); p<0.001), lower middle income (OR 3.32 (95% CI 1.96 to 5.61); p<0.001) and upper middle income (OR 3.49 (95% CI 2.02 to 6.03); p<0.001) country status and chemotherapy (OR 0.55 (95% CI 0.36 to 0.86); p=0.008) and immunotherapy (OR 0.27 (95% CI 0.08 to 0.91); p=0.035) within 30 days from MDT plan. Multivariable analysis revealed laboratory-confirmed SARS-CoV-2 infection (OR 5.33 (95% CI 1.19 to 23.84); p=0.029) was associated with 30-day mortality. Conclusions Children with cancer are more likely to die within 30 days if infected with SARS-CoV-2. However, timely treatment reduced odds of death. This report provides crucial information to balance the benefits of providing anticancer therapy against the risks of SARS-CoV-2 infection in children with cancer

Binding the Smart City Human-Digital System with Communicative Processes

This chapter will explore the dynamics of power underpinning ethical issues within smart cities via a new paradigm derived from Systems Theory. The smart city is an expression of technology as a socio-technical system. The vision of the smart city contains a deep fusion of many different technical systems into a single integrated “ambient intelligence”. ETICA Project, 2010, p. 102). Citizens of the smart city will not experience a succession of different technologies, but a single intelligent and responsive environment through which they move. Analysis of such an environment requires a framework which transcends traditional ontologically-based models in order to accommodate this deep fusion. This chapter will outline a framework based on Latour’s Actor-Network Theory and Luhmann’s treatment of society as an autopoetic system. We shall use this framework to map the influence of relevant factors on ethical issues, irrespective of their composition or type. For example, under this treatment, both human praxis and technical design can be viewed as comparable tools of domination. This chapter will provide a framework for the analysis of relations between any elements of the smart city, ranging from top-level urban management processes down to individual device operations. While we will illustrate the use of this schema through examination of ethical issues arising from power dynamics within the smart city, it is intended that this example will demonstrate the wider utility of the model in general

The impact of open source software on the strategic choices of firms developing proprietary software

Open source software (OSS) is now posing significant competition to proprietary or closed source software (CSS) in several software markets. In this paper, we characterize the response of a firm developing CSS to the presence of an OSS in its market. In particular, we look at the firm’s choice of resource investments to improve quality and the firm’s pricing decisions. We are primarly motivated by the following questions: Would a firm producing CSS produce higher-quality software when it faces competition from an OSS than when there is no OSS in its market? Would there be a change in the firm’s response if the CSS faced competition from another CSS in addition to competition from the OSS? We show that the firm produces lower-quality CSS when it faces competition from an OSS than when it does not. Also, the quality of the CSS decreases as the quality of the OSS increases. This result holds true even if we consider network effects. When we consider competition from another CSS, in addition to competition from the OSS, then the quality of the CSS could increase or decrease as the quality of the OSS increases. The change in quality depends on how closely substitutable the two CSS are. We also extend our base model to consider: i) competition for resources, ii) uncertainty in resources available to the OSS, and iii) uncertainty about the software development process

Newton-Raphson loadflow analysis

Abstract not availabl

Analysis of electronic micro-payment market

Despite the potential of micro-payment systems very few systems have been successful. Little is known about the reasons behind the successful few and the failures of the majority. Micro-payment markets exhibit two-sided network effects and the underlying dynamics of these markets are not very well understood. Based on a stylized model of a two-sided market, we find that a 'survival mass' of merchants and consumers is required for a micro-payment system to exist and a 'critical mass' for the acceptance levels to take off and remain stable. We also find the non-intuitive result that lowering the consumer-side adoption cost will actually reduce the chances for the micro-payment market to develop. Thus, subsidization alone cannot create a micro-payment market. Anecdotal evidence supports this finding. When subsidization is needed, the consumer side will normally be subsidized. The two-sided market structure makes comparative analysis complex and non-trivial, rendering the implementation of micro-payment systems very difficult as indicated by the mixed results of a number of initiatives worldwide

Sensitivity analysis of a deep drawing process for miniaturized products

Deep drawing is a widely used sheet metal forming technique, and its successful implementation has been a subject of research since many years. It has undergone many developments, one of the important ones being the application of numerical modeling techniques, like the finite element method (FEM) to simulate the process. Although deep drawing has been a subject of research for many years, there is still not much data available on deep drawing of miniature components, which find extensive application in electronics industry. The deep drawing process is affected by many material and process parameters, like the strain-hardening exponent, plastic strain ratio, friction and lubrication, blank holder force, presence of drawbeads, punch velocity, etc. This paper aims at identifying the important parameters that affect the deep drawing process and quantitatively studying g the effect of these parameters on the deep drawing operation for components of similar shape but different sizes. Thus, establishing a correlation between the size of a component and the effect of the parameters on the deep drawing of the component. The study consists of a plane strain analysis of bell shaped geometry. Taguchi's robust design technique [Quality Engineering Using Robust Design, Prentice-Hall, New Jersey, 1989, p. 145] has been used to design the experiments using the maximum thinning strain developed in the walls as the quality characteristic. Since carrying out actual experiments is both expensive and time consuming, computer modeling has been used to simulate the experiments. A FEM-based program, SHEET-S, developed by Wagoner and co-workers [Int. J. Meth. Eng. 30 (8) (1990) 1471] has been used for this purpose. (C) 200

Thermo-mechanical properties of unsaturated polyester toughened epoxysiliconized iron (III) oxide nanocomposites

241-245Novel siliconized iron (III) oxide nanoparticles reinforced unsaturated polyester (UP) toughened epoxy nanocomposites is prepared. The siliconized iron (III) oxide nanoparticles are improved thermal and mechanical properties of nanocomposites. Diglycidyl ether of bisphenol A (DGEBA) based epoxy resin is toughened with 5, 10 and 15% (by wt) of UP using benzoyl peroxide as radical initiator and 4, 4′ -diaminodiphenylmethane (DDM) as curing agent. UP toughened epoxy systems are reinforced with 1, 3, and 5% (by wt) of siliconized iron (III) oxide nanoparticles. The thermal and mechanical properties, and microstructures of nanocomposites are investigated. Data results from thermal and mechanical studies indicate that the insertion of siliconized iron (III) oxide nanoparticles into UP toughened epoxy system enhances the thermal and mechanical properties. Morphology of the hybrid system reveals homogenous distribution of nanoparticles

The Impact of Open Source Software on the Strategic Choices of Firms Developing Proprietary Software

Open source software (OSS) is now posing significant competition to proprietary or closed source software (CSS) in several software markets. In this paper, we characterize the response of a firm developing CSS (where the CSS is a revenue earner) to the presence of an OSS in its market. In particular, we look at the firm's choice of resource investments to improve quality and the firm's pricing decisions. We are primarily motivated by the following questions: Would a firm producing CSS produce higher-quality software when it faces competition from ail OSS than when there is no OSS in its market? Would there be a change in the firm's response if the CSS faced competition from another CSS in addition to competition from the OSS? We show that the firm produces lower-quality CSS when it faces competition from an OSS than when it does not. Also. the quality of the CSS decreases as the quality of the OSS increases. This result holds true even if we consider network effects. When we consider competition from another CSS, in addition to competition from the OSS, then the quality of the CSS could increase or decrease as the quality of the OSS increases. The change in quality depends on how closely substitutable the two CSS are. We also extend our base model to consider (1) competition for resources, (2) uncertainty in resources available to the OSS, and (3) uncertainty about the software development process

Model-Aware XGBoost Method Towards Optimum Performance of Flexible Distributed Raman Amplifier

Toward the next-generation ultra-long-haul optical network, an extremely gradient boosting (XGBoost)-aided machine learning (ML) model is proposed to maximize the flexibility and uniformity in the performance of distributed Raman amplifier (DRA). In order to achieve an accurate prediction of desired signal gain spectrum and bit error rate (BER), a novel decision-tree based system is employed against inconsistent dimensionality between pump frequency and power. The impact of various model evaluation techniques: mean squared error (MSE), coefficient of determination (R2), root mean square measured data ratio (RSR) and the Nash-Sutcliffe coefficient (NSE) are discussed in detail. It is shown that the proposed method can diagnose the fault within 2.3 ms with accuracy of 99.6% and has also the highest estimation and efficacy in comparison with other ML based tree models. The reported work transforms the successful implementation of XGBoost model to estimate the desired gain profile and BER of DRA in low-loss optical wavelength region (1260–1650 nm)