Online games: a novel approach to explore how partial information influences human random searches

Many natural processes rely on optimizing the success ratio of a search process. We use an experimental setup consisting of a simple online game in which players have to find a target hidden on a board, to investigate the how the rounds are influenced by the detection of cues. We focus on the search duration and the statistics of the trajectories traced on the board. The experimental data are explained by a family of random-walk-based models and probabilistic analytical approximations. If no initial information is given to the players, the search is optimized for cues that cover an intermediate spatial scale. In addition, initial information about the extension of the cues results, in general, in faster searches. Finally, strategies used by informed players turn into non-stationary processes in which the length of each displacement evolves to show a well-defined characteristic scale that is not found in non-informed searches.Comment: 17 pages, 10 figure

Searching the Físchlár-NEWS archive on a mobile device

The Físchlár-NEWS system provides web-based access to an archive of digitally recorded TV News broadcasts over several months, and has been operational for over a year. Users can browse keyframes, search teletext and have streamed video playback of segments of news broadcasts to their desktops. This paper reports on the development of mFíschlár-NEWS, a version of Físchlár-NEWS which operates on a mobile PDA over a wireless LAN connection. In the design and development of mFíschlár-NEWS we have realised that mobile access to a digital library of video materials is more than just the desktop system on a smaller screen, and the functionality and role that information retrieval techniques play in the mFíschlár-NEWS system are very different to what is present in the desktop system. The paper describes the design, interface, functionality and operational status of this mobile access to a video library

Risk taking in Extreme Sports: A phenomenological perspective

Participation in extreme sports is enjoying incredible growth while more traditional recreational activities such as golf are struggling to maintain numbers. Theoretical perspectives on extreme sports and extreme sport participants have assumed that participation is about risk-taking. However, these theory-driven methodologies may reflect judgments that do not necessarily relate to participants' lived experience. In this paper I review current risk-oriented perspectives on extreme sports and present research findings that question this assumed relationship between extreme sports and risk and thus reposition the experience in a hitherto unexplored manner. Risk taking is not the focus. Participants acknowledge that the potential outcome of a mismanaged mistake or accident could be death. However, accepting this potential outcome does not mean that they search for risk. Participants argue that many everyday life events (e.g., driving) are high-risk events. Participants undertake detailed preparation in order to minimise the possibility of negative outcomes because extreme sports trigger a range of positive experiential outcomes. The study is significant as it followed a hermeneutic phenomenological process which did not presuppose a risk-taking orientation. Hermeneutic phenomenology allows for a multitude of data sources including interviews (10 male and 5 female extreme sports participants, ages 30 to 72 years), auto-biographies, videos and other firsthand accounts. This process allowed this unexpected perspective to emerge more clearly

Behaviors of Adult \u3ci\u3eAgrilus Planipennis\u3c/i\u3e (Coleoptera: Buprestidae)

A 2-year study was conducted in Canada (2003) and the United States (2005) to better understand searching and mating behaviors of adult Agrilus planipennis Fairmaire. In both field and laboratory, adults spent more time resting and walking than feeding or flying. The sex ratio in the field was biased towards males, which tended to hover around trees, likely looking for mates. There was more leaf feeding damage within a tree higher in the canopy than in the lower canopy early in the season, but this difference disappeared over time. In choice experiments, males attempted to mate with individuals of both sexes, but they landed more frequently on females than on males. A series of sexual behaviors was observed in the laboratory, including: exposure of the ovipositor/genitalia, sporadic jumping by males, attempted mating, and mating. Sexual behaviors were absent among 1-3 day-old beetles, but were observed regularly in 10-12 day-old beetles. Females were seen exposing their ovipositor, suggestive of pheromone-calling behavior. No courtship was observed prior to mating. Hovering, searching, and landing behaviors suggest that beetles most likely rely on visual cues during mate finding, although host-plant volatiles and/or pheromones might also be involved

Target search on a dynamic DNA molecule

We study a protein-DNA target search model with explicit DNA dynamics applicable to in vitro experiments. We show that the DNA dynamics plays a crucial role for the effectiveness of protein "jumps" between sites distant along the DNA contour but close in 3D space. A strongly binding protein that searches by 1D sliding and jumping alone, explores the search space less redundantly when the DNA dynamics is fast on the timescale of protein jumps than in the opposite "frozen DNA" limit. We characterize the crossover between these limits using simulations and scaling theory. We also rationalize the slow exploration in the frozen limit as a subtle interplay between long jumps and long trapping times of the protein in "islands" within random DNA configurations in solution.Comment: manuscript and supplementary material combined into a single documen

Modeling transcription factor binding events to DNA using a random walker/jumper representation on a 1D/2D lattice with different affinity sites

Surviving in a diverse environment requires corresponding organism responses. At the cellular level, such adjustment relies on the transcription factors (TFs) which must rapidly find their target sequences amidst a vast amount of non-relevant sequences on DNA molecules. Whether these transcription factors locate their target sites through a 1D or 3D pathway is still a matter of speculation. It has been suggested that the optimum search time is when the protein equally shares its search time between 1D and 3D diffusions. In this paper, we study the above problem using a Monte Carlo simulation by considering a very simple physical model. A 1D strip, representing a DNA, with a number of low affinity sites, corresponding to non-target sites, and high affinity sites, corresponding to target sites, is considered and later extended to a 2D strip. We study the 1D and 3D exploration pathways, and combinations of the two modes by considering three different types of molecules: a walker that randomly walks along the strip with no dissociation; a jumper that represents dissociation and then re-association of a TF with the strip at later time at a distant site; and a hopper that is similar to the jumper but it dissociates and then re-associates at a faster rate than the jumper. We analyze the final probability distribution of molecules for each case and find that TFs can locate their targets fast enough even if they spend 15% of their search time diffusing freely in the solution. This indeed agrees with recent experimental results obtained by Elf et al. 2007 and is in contrast with theoretical expectation.Comment: 24 pages, 9 figure

Parameters identification of unknown delayed genetic regulatory networks by a switching particle swarm optimization algorithm

The official published version can be found at the link below.This paper presents a novel particle swarm optimization (PSO) algorithm based on Markov chains and competitive penalized method. Such an algorithm is developed to solve global optimization problems with applications in identifying unknown parameters of a class of genetic regulatory networks (GRNs). By using an evolutionary factor, a new switching PSO (SPSO) algorithm is first proposed and analyzed, where the velocity updating equation jumps from one mode to another according to a Markov chain, and acceleration coefficients are dependent on mode switching. Furthermore, a leader competitive penalized multi-learning approach (LCPMLA) is introduced to improve the global search ability and refine the convergent solutions. The LCPMLA can automatically choose search strategy using a learning and penalizing mechanism. The presented SPSO algorithm is compared with some well-known PSO algorithms in the experiments. It is shown that the SPSO algorithm has faster local convergence speed, higher accuracy and algorithm reliability, resulting in better balance between the global and local searching of the algorithm, and thus generating good performance. Finally, we utilize the presented SPSO algorithm to identify not only the unknown parameters but also the coupling topology and time-delay of a class of GRNs.This research was partially supported by the National Natural Science Foundation of PR China (Grant No. 60874113), the Research Fund for the Doctoral Program of Higher Education (Grant No. 200802550007), the Key Creative Project of Shanghai Education Community (Grant No. 09ZZ66), the Key Foundation Project of Shanghai (Grant No. 09JC1400700), the Engineering and Physical Sciences Research Council EPSRC of the UK under Grant No. GR/S27658/01, the International Science and Technology Cooperation Project of China under Grant No. 2009DFA32050, an International Joint Project sponsored by the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany