This paper offers new mathematical models to measure the most productive scale size (MPSS) of production systems with mixed structure networks (mixed of series and parallel). In the first property, we deal with a general multi-stage network which can be transformed, using dummy processes, into a series of parallel networks. In the second property, we consider a direct network combined with series and parallel structure. In this paper, we propose new models to measure the overall MPSS of the production systems and their internal processes. MPSS decomposition is discussed and examined. As a real-life application, this study measures the efficiency and MPSS of research and development (R&D) activities of Chinese provinces within an R&D value chain network.

In many real-world multi-robot tasks, high-quality solutions often require a team of robots to perform asynchronous actions under decentralized control. Multi-agent reinforcement learning methods have difficulty learning decentralized policies because the environment appearing to be non-stationary due to other agents also learning at the same time. In this paper, we address this challenge by proposing a macro-action-based decentralized multi-agent double deep recurrent Q-net (MacDec-MADDRQN) which creates a new double Q-updating rule to train each decentralized Q-net using a centralized Q-net for action selection.

Although definitions of technology exist to explain the patterns of technological innovations, there is no general definition that explain the role of technology for humans and other animal species in environment. The goal of this study is to suggest a new concept of technology with a systemic-purposeful perspective for technology analysis. Technology here is a complex system of artifact, made and_or used by living systems, that is composed of more than one entity or sub-system and a relationship that holds between each entity and at least one other entity in the system, selected considering practical, technical and_or economic characteristics to satisfy needs, achieve goals and_or solve problems of users for purposes of adaptation and_or survival in environment.

Today’s scientific research is an expensive enterprise funded largely by taxpayers’ and corporate groups’ monies. It is a critical part in the competition between nations, and all nations want to discover fields of research that promise to create future industries, and dominate these by building up scientific and technological expertise early. However, our understanding of the value chain going from science to technology is still in a relatively infant stage, and the conversion of scientific leadership into market dominance remains very much an alchemy rather than a science.

After a short review on the use of time in various branches of physics, I suggest to change the interpretation of time, from a duration to a cut. A reassessment of terminology is also required to avoid meaning traps.

Mobile manipulation robots have high potential to support rescue forces in disaster-response missions. Despite the difficulties imposed by real-world scenarios, robots are promising to perform mission tasks from a safe distance. In the CENTAURO project, we developed a disaster-response system which consists of the highly flexible Centauro robot and suitable control interfaces including an immersive tele-presence suit and support-operator controls on different levels of autonomy. In this article, we give an overview of the final CENTAURO system.

Durante la Guerra Fría con la Unión Soviética, Estados Unidos pudo compensar la superioridad de aquella en efectivos y equipos militares convencionales, e incluso en armas nucleares, gracias a la tecnología. Tanto en los cincuenta como en los ochenta, fue capaz de dar saltos de garrocha tecnológicos que le permitieron sacar ventaja militar a los soviéticos. Ahora, es Estados Unidos quien corre el riesgo de quedar rezagado frente a los saltos de garrocha tecnológicos que China estaría dando, algunos de ellos a sus expensas.

In glaring contrast to its indisputable century-old experimental success, the ultimate objects and meaning of quantum physics remain a matter of vigorous debate among physicists and philosophers of science. This article attempts to shed new light on the debate. It relies upon two comments by Albert Einstein on his general approach to physical theories. I draw their consequences for the definition of a physical theory’s ontology, and next for the ontology of quantum physics – i.e. what it may ultimately be about. The quantum ontology thus derived appears to be strictly limited to evolving experimental contexts and instantaneous measurement outcomes, which are to be understood, respectively, as mere potential measurement outcomes and actual ones.

The most challenging problem of modern physics is how to reconcile quantum theory and general relativity, namely, to find a consistent quantum theory in which gravity is quantized. This Progress Report focuses on such a tentative theory called the information-complete quantum theory (ICQT), in which (1) spacetime (gravity) as a physical quantum system plays a central role for formulating the theory, and (2) there are no any classical systems and concepts. Here universal spacetime-matter entanglement “glues” spacetime and matter (matter fermions and their gauge fields) as an indivisible trinity, encodes information-complete physical predictions of the world, and is as universal as universal gravitation.

We show how any dataset of any modality (time-series, images, sound…) can be approximated by a well-behaved (continuous, differentiable…) scalar function with a single real-valued parameter. Building upon elementary concepts from chaos theory, we adopt a pedagogical approach demonstrating how to adjust this parameter in order to achieve arbitrary precision fit to all samples of the data. Targeting an audience of data scientists with a taste for the curious and unusual, the results presented here expand on previous similar observations regarding expressiveness power and generalization of machine learning models.