Adaptive Finite Elements for Systems of PDEs: Software Concepts, Multi-level Techniques and Parallelization

In the recent past, the field of scientific computing has become of more and more importance for scientific as well as for industrial research, playing a comparable role as experiment and theory do. This success of computational methods in scientific and engineering research is next to the enormous improvement of computer hardware to a large extend due to contributions from applied mathematicians, who have developed algorithms which make real life applications feasible. Examples are adaptive methods, high order discretization, fast linear and non-linear solvers and multi-level methods. The application of these methods in a large class of problems demands for suitable and robust tools for a flexible and efficient implementation. In order to play a crucial role in scientific and engineering research, besides efficiency in the numerical solution, also efficiency in problem setup and interpretation of simulation results is of utmost importance. As modeling and computing comes closer together, efficient computational methods need to be applied to new sets of equations. The problems to be addressed by simulation methods become more and more complicated, ranging over different scales, interacting on different dimensions and combining different physics. Such problems need to be implemented in a short period of time, solved on complicated domains and visualized with respect to the demand of the user. %Only a modular abstract simulation environment will fulfill these requirements and allow to setup, solve and visualize real-world problems appropriately. In this work, the concepts and the design of the C++ finite element toolbox AMDiS (adaptive multidimensional simulations) are described. It is shown, how abstract data structures and modern software concepts can help to design user-friendly finite element software, which provides large flexibility in problem definition while on the other hand efficiently solves these problems. Also systems of coupled problems can be solved in an intuitive way. In order to demonstrate its possibilities, AMDiS has been applied to several non-standard problems. The most time-consuming part in most simulations is the solution of linear systems of equations. Multi-level methods use discretization hierarchies to solve these systems in a very efficient way. In AMDiS, such multi-level techniques are implemented in the context of adaptive finite elements. Several numerical results are given which compare this multigrid solver with classical iterative methods. Besides the development of more efficient algorithms also the growing hardware capabilities lead to an improvement of simulation possibilities. Modern computing clusters contain more and more processors and also personal computers today are often equipped with multi-core processors. In this work, a new parallelization approach has been developed which allows the parallelization of sequential code in a very easy way and reduces the communication overhead compared to classical parallelization concepts

Driving forces and barriers of Industry 4.0: Do multinational and small and medium-sized companies have equal opportunities?

The Fourth Industrial Revolution poses significant challenges to manufacturing companies from the technological, organizational and management points of view. This paper aims to explore how top executives interpret the concept of Industry 4.0, the driving forces for introducing new technologies and the main barriers to Industry 4.0. The authors applied a qualitative case study design involving 26 semi-structured interviews with leading members of firms, including chief digital officers and chief executive officers. Company websites and annual reports were also examined to increase the reliability and validity of the results. The authors found that management desire to increase control and enable real-time performance measurement is a significant driving force behind Industry 4.0, alongside production factors. Organizational resistance at both employee and middle management levels can significantly hinder the introduction of Industry 4.0 technologies, though these technologies can also transform management functions. Multinational enterprises have higher driving forces and lower barriers to industry 4.0 than small and medium-sized companies, but these smaller companies have good opportunities, too

Role of plants in anticancer drug discovery

Cancer is one of the major causes of death and the number of new cases, as well as the number of individuals living with cancer, is expanding continuously. Worldwide the alarming rise in mortality rate due to cancer has fuelled the pursuit for effective anticancer agents to combat this disease. Finding novel and efficient compounds of natural origin has been a major point of concern for research in the pharmaceutical sciences. Plants have been seen to possess the potential to be excellent lead structures and to serve as a basis of promising therapeutic agents for cancer treatment. Many successful anti-cancer drugs currently in use or their analogues are plant derived and many more are under clinical trials. This review aims to highlight the invaluable role that plants have played, and continue to play, in the discovery of anticancer agents.We acknowledge the University of Pretoria for Postdoctoral fellowship to J.K. and B.A.M.http://www.elsevier.com/locate/phytolhb2017ChemistryGenetic

Adaptive Finite Elements for Systems of PDEs: Software Concepts, Multi-level Techniques and Parallelization

In the recent past, the field of scientific computing has become of more and more importance for scientific as well as for industrial research, playing a comparable role as experiment and theory do. This success of computational methods in scientific and engineering research is next to the enormous improvement of computer hardware to a large extend due to contributions from applied mathematicians, who have developed algorithms which make real life applications feasible. Examples are adaptive methods, high order discretization, fast linear and non-linear solvers and multi-level methods. The application of these methods in a large class of problems demands for suitable and robust tools for a flexible and efficient implementation. In order to play a crucial role in scientific and engineering research, besides efficiency in the numerical solution, also efficiency in problem setup and interpretation of simulation results is of utmost importance. As modeling and computing comes closer together, efficient computational methods need to be applied to new sets of equations. The problems to be addressed by simulation methods become more and more complicated, ranging over different scales, interacting on different dimensions and combining different physics. Such problems need to be implemented in a short period of time, solved on complicated domains and visualized with respect to the demand of the user. %Only a modular abstract simulation environment will fulfill these requirements and allow to setup, solve and visualize real-world problems appropriately. In this work, the concepts and the design of the C++ finite element toolbox AMDiS (adaptive multidimensional simulations) are described. It is shown, how abstract data structures and modern software concepts can help to design user-friendly finite element software, which provides large flexibility in problem definition while on the other hand efficiently solves these problems. Also systems of coupled problems can be solved in an intuitive way. In order to demonstrate its possibilities, AMDiS has been applied to several non-standard problems. The most time-consuming part in most simulations is the solution of linear systems of equations. Multi-level methods use discretization hierarchies to solve these systems in a very efficient way. In AMDiS, such multi-level techniques are implemented in the context of adaptive finite elements. Several numerical results are given which compare this multigrid solver with classical iterative methods. Besides the development of more efficient algorithms also the growing hardware capabilities lead to an improvement of simulation possibilities. Modern computing clusters contain more and more processors and also personal computers today are often equipped with multi-core processors. In this work, a new parallelization approach has been developed which allows the parallelization of sequential code in a very easy way and reduces the communication overhead compared to classical parallelization concepts

Adaptive Finite Elements for Systems of PDEs: Software Concepts, Multi-level Techniques and Parallelization

In the recent past, the field of scientific computing has become of more and more importance for scientific as well as for industrial research, playing a comparable role as experiment and theory do. This success of computational methods in scientific and engineering research is next to the enormous improvement of computer hardware to a large extend due to contributions from applied mathematicians, who have developed algorithms which make real life applications feasible. Examples are adaptive methods, high order discretization, fast linear and non-linear solvers and multi-level methods. The application of these methods in a large class of problems demands for suitable and robust tools for a flexible and efficient implementation. In order to play a crucial role in scientific and engineering research, besides efficiency in the numerical solution, also efficiency in problem setup and interpretation of simulation results is of utmost importance. As modeling and computing comes closer together, efficient computational methods need to be applied to new sets of equations. The problems to be addressed by simulation methods become more and more complicated, ranging over different scales, interacting on different dimensions and combining different physics. Such problems need to be implemented in a short period of time, solved on complicated domains and visualized with respect to the demand of the user. %Only a modular abstract simulation environment will fulfill these requirements and allow to setup, solve and visualize real-world problems appropriately. In this work, the concepts and the design of the C++ finite element toolbox AMDiS (adaptive multidimensional simulations) are described. It is shown, how abstract data structures and modern software concepts can help to design user-friendly finite element software, which provides large flexibility in problem definition while on the other hand efficiently solves these problems. Also systems of coupled problems can be solved in an intuitive way. In order to demonstrate its possibilities, AMDiS has been applied to several non-standard problems. The most time-consuming part in most simulations is the solution of linear systems of equations. Multi-level methods use discretization hierarchies to solve these systems in a very efficient way. In AMDiS, such multi-level techniques are implemented in the context of adaptive finite elements. Several numerical results are given which compare this multigrid solver with classical iterative methods. Besides the development of more efficient algorithms also the growing hardware capabilities lead to an improvement of simulation possibilities. Modern computing clusters contain more and more processors and also personal computers today are often equipped with multi-core processors. In this work, a new parallelization approach has been developed which allows the parallelization of sequential code in a very easy way and reduces the communication overhead compared to classical parallelization concepts

Der Weg zu Industrie 4.0 in der Produktion. BMBF Zukunftsprojekt RobIN 4.0 – Robustheit durch Integration, Interaktion, Interpretation und Intelligenz

Unter dem Begriff „Industrie 4.0“ wird die vierte industrielle Revolution verstanden. Sie folgt auf die Industrialisierung, Mechanisierung und Automatisierung. Dabei steht jede Revolution auch für eine Verknüpfung zwischen verschiedenen Wissenschaftsdisziplinen. Gegen Ende des 18. Jahrhunderts führt das Zusammenführen von Mechanik und Thermodynamik zum Bau und anschließender kommerzieller Nutzung der Dampfmaschine zur ersten industriellen Re-volution. Als zweite Revolution kann die Verknüpfung zwischen der Mechanik und der Be-triebswirtschaftslehre sowie der Arbeitswissenschaft zum Beginn des 20. Jahrhunderts festgehalten werden. Ergebnis dieser Revolution ist die Teilung der Arbeit in kleine Einheiten sowie die dadurch ermöglichte Massenproduktion. Zu Beginn der 1970er Jahre wird zeitlich die dritte Revolution eingeordnet. Hierbei wird die Verbindung zwischen der Mechanik und der Elektronik bzw. Steuerung industriell umgesetzt. Durch die Entwicklung der ersten speicher-programmierbaren Steuerungen sowie Feldbussystemen, kann basierend auf den Sensor-, Ak-tor- sowie Steuerungs- und Kommunikationstechnologien die Automatisierung in die Indust-rie Einzug halten. Durch die bis heute anhaltende Steigerung der Komplexität von Produkti-onsprozessen wird zu Beginn des 21. Jahrhunderts die vierte industrielle Revolution ange-schoben. Ziel ist es, die Komplexität an Produkten zu bewältigen und Produktionsprozesse flexibel und handhabbar zu gestalten. Hierbei ist die Verknüpfung von fortschrittlichen Pro-duktionstechnologien mit Informations- und Kommunikationstechnologien (IKT) der Kernas-pekt der vierten Revolution. Um einerseits die anfallenden Informationen aus hochdynami-schen Prozessen zu erfassen und gleichzeitig eine Auswertung der Daten zu realisieren, gilt es, moderne IKT auf der Produktionsebene zu etablieren. Grundlage hierfür bildet die stark steigende Anzahl an sensorischen Elementen und Aktoren in Produktionsprozessen. Durch Industrie 4.0 rückt, im globalen und nationalen Wettbewerb von Wirtschaftsunterneh-men, die Digitalisierung der Produktion in den Fokus. Mit ihr sollen eine effizientere Nutzung von Ressourcen und eine Erhöhung der Produktivität für in Deutschland ansässige Produkti-onsunternehmen erzielbar sein. Um diesen Herausforderungen gerecht zu werden, müssen Produktionsprozesse hinsichtlich ihrer Qualität, Geschwindigkeit und Flexibilität optimiert werden. Zur Beantwortung der mit Industrie 4.0 verbundenen Fragestellungen im Bereich der Umformtechnik werden im Rahmen der Ausschreibung des BMBF „Intelligente Vernetzung in der Produktion – Ein Beitrag zum Zukunftsprojekt Industrie 4.0“ verschiedene Projekte auf der Produktionsebene gefördert. Das vorliegende Buch soll die gewonnenen Erkenntnisse aus dem Verbundprojekt „RobIN 4.0“ zusammenfassen und Chancen für die Umformtechnik durch Industrie 4.0 aufzeigen. Für die Durchführung des Projektes hat sich ein Konsortium aus Mitgliedern von universitären Forschungseinrichtungen, Schulungsbetrieben, Maschinen-herstellern, Werkzeugbauern, Ingenieurbüros und Anbietern von Prozessüberwachungstech-nik sowie Umformbetrieben im Verbundprojekt „RobIN 4.0“ zusammengefunden. Das Akro-nym „RobIN 4.0“ bildet sich aus den unterschiedlichen Forschungsschwerpunkten und soll die Robustheit von Produktionsprozessen durch die Integration von Sensoren und Aktoren, die Interaktion zwischen verschiedenen an der Produktion beteiligten Elementen, die Interpre-tation von anfallenden Informationen und die Intelligenz von Regelungssystemen erhöhen

A phase II study of cloretazine (VNP40101M), a novel sulfonylhydrazine alkylating agent, in patients with very high risk relapsed acute myeloid leukemia.

Cloretazine (VNP40101M) is a sulfonylhydrazine alkylating agent with significant anti-leukemia activity. A multicenter phase II study of cloretazine was conducted in patients with first relapse of acute myeloid leukemia (AML) following an initial complete remission (CR) of less than 12 months. Cloretazine was given as a single intravenous infusion at a dose of 600 mg/m(2). Fifty-three patients (median age 62 years (18-84), 41 of 44 (93%) evaluable with intermediate or high risk cytogenetics, 32 (60%) with initial CR durations < or =6 months) were treated on study. Two patients (4%) achieved a second CR. Five (9%) patients died within 30 days of receiving cloretazine therapy. Median overall survival (2.3 months) in the study cohort was directly comparable to that of 233 matched patients treated with other single agents. The study cloretazine regimen had minimal activity in a very high risk subset of patients with relapsed AML