Broadening of hot-spot response spectrum of superconducting NbN nanowire single-photon detector with reduced nitrogen content

The spectral detection efficiency and the dark count rate of superconducting nanowire single-photon detectors (SNSPD) has been studied systematically on detectors made from thin NbN films with different chemical compositions. Reduction of the nitrogen content in the 4 nm thick NbN films results in a more than two orders of magnitude decrease of the dark count rates and in a red shift of the cut-off wavelength of the hot-spot SNSPD response. The observed phenomena are explained by an improvement of uniformity of NbN films that has been confirmed by a decrease of resistivity and an increase of the ratio of the measured critical current to the depairing current. The latter factor is considered as the most crucial for both the cut-off wavelength and the dark count rates of SNSPD. Based on our results we propose a set of criteria for material properties to optimize SNSPD in the infrared spectral region.Comment: 15 pages, 6 figure

Competition between \u3cem\u3eLolium perenne\u3c/em\u3e L. and \u3cem\u3eAgrostis capillaris\u3c/em\u3e L. Growing under Different Light Regimes as Response to Fertiliser Addition in a Degraded Pasture

At the field level plants can experience solar irradiance fluctuations caused by cloud cover or canopy shading. The majority of the research in this area has been done on forestry/pastoral systems using artificial structures so that the pasture has the desired light level (Peri et al. 2006). However, the effect of a change from high to low irradiance on the seasonal plant growth and production in a degraded pastoral system has not been previously studied, especially when fluctuating light regimes are involved. The aims of this study were to evaluate tillering dynamics of Lolium perenne L. (Lp) and Agrostis capillaris L. (Ac) in a degraded pasture under different intensities of fluctuating light regimes and also to evaluate the effect of fertiliser addition on plant growth under different levels of light

Brief history of serious games

Serious Games are now an established field of study. In this field most would attribute the rise of Serious Games to Clark C Abt’s creation of the term in 1970, or indeed Ben Sawyer’s popularization of it in 2002. However, considering the rich history of purposing non-digital games, itself preceded by discussions of purposing play that are traceable to the work of Plato, it can be said that Serious Games is a contemporary manifestation of centuries old theories and practices. In this chapter, we explore the pre-history of Serious Games, beginning with the suggested purpose, and purposing of play. Throughout this historical review we identify key in research and practice that are apparent in the contemporary Serious Games field

Creating and Capturing Artificial Emotions in Autonomous Robots and Software Agents

This paper presents ARTEMIS, a control system for autonomous robots or software agents. ARTEMIS is able to create and capture artificial emotions during interactions with its environment, and we describe the underlying mechanisms for this. The control system also realizes the capturing of knowledge about its past artificial emotions. A specific interpretation of a knowledge graph, called an Agent Knowledge Graph, represents these artificial emotions. For this, we devise a formalism which enriches the traditional factual knowledge in knowledge graphs with the representation of artificial emotions. As proof of concept, we realize a concrete software agent based on the ARTEMIS control system. This software agent acts as a user assistant and executes the user’s orders. The environment of this user assistant consists of autonomous service agents. The execution of user’s orders requires interaction with these autonomous service agents. These interactions lead to artificial emotions within the assistant. The first experiments show that it is possible to realize an autonomous agent with plausible artificial emotions with ARTEMIS and to record these artificial emotions in its Agent Knowledge Graph. In this way, autonomous agents based on ARTEMIS can capture essential knowledge that supports successful planning and decision making in complex dynamic environments and surpass emotionless agents