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It is generally believed that random search processes based on scale-free, Lévy stable jump length distributions (Lévy flights) optimize the search for sparse targets. Here we show that this popular search advantage is less universal than commonly assumed. We study the efficiency of a minimalist search model based on Lévy flights in the absence and presence of an external drift (underwater current, atmospheric wind, a preference of the walker owing to prior experience, or a general bias in an abstract search space) based on two different optimization criteria with respect to minimal search time and search reliability (cumulative arrival probability). Although Lévy flights turn out to be efficient search processes when the target is far from the starting point, or when relative to the starting point the target is upstream, we show that for close targets and for downstream target positioning regular Brownian motion turns out to be the advantageous search strategy. Contrary to claims that Lévy flights with a critical exponent α = 1 are optimal for the search of sparse targets in different settings, based on our optimization parameters the optimal α may range in the entire interval (1, 2) and especially include Brownian motion as the overall most efficient search strategy.

Real-time database searching allows for simpler and automated proteomics workflows as it eliminates technical bottlenecks in high-throughput experiments. Most importantly, it enables results-dependent acquisition (RDA), where search results can be used to guide data acquisition during acquisition. This is especially beneficial for glycoproteomics since the wide range of physicochemical properties of glycopeptides lead to a wide range of optimal acquisition parameters. We established here the GlycoPaSER prototype by extending the Parallel Search Engine in Real-time (PaSER) functionality for real-time glycopeptide identification from fragmentation spectra. Glycopeptide fragmentation spectra were decomposed into peptide and glycan moiety spectra using common N-glycan fragments. Each moiety was subsequently identified by a specialized algorithm running in real-time. GlycoPaSER can keep up with the rate of data acquisition for real-time analysis with similar performance to other glycoproteomics software and produces results that are in line with the literature reference data. The GlycoPaSER prototype presented here provides the first proof-of-concept for real-time glycopeptide identification that unlocks the future development of RDA technology to transcend data acquisition.

Previous research on haptic search using sandpaper with different roughness levels as a target and distractors showed that rough sandpaper among fine “pops out” and can be searched for in a shorter time than when the roles of the target and distractors are reversed. However, it is not clear whether the same search asymmetry occurs with differences in the shapes of tactile symbols on capsule paper. To explore this possibility, we conducted a haptic search experiment using circles with or without a dot on capsule paper as a target and distractors, which are often used as point symbols in tactile maps for the blind. Contrary to our expectations, haptic search asymmetry did not occur between these two tactile symbols. Regardless of target type, the search times increased in proportion to the number of items (distractors plus target), as participants tended to adopt serial search strategy in which they placed their index or middle finger on the tactile symbol to distinguish it every time they found a new one. The ratio of the search times for target-absent to target-present trials is precise alignment with the occurrence rate of repetitive search trials.

Organizations are frequently faced with high levels of complexity. While the importance of search for dealing with complex systems is widely acknowledged, how organizations should structure their search processes remains largely unexplored. This paper starts to address basic questions: How much of the entire system, and thus complexity, should be taken into consideration at any given time during a search process? Should a problem solver pursue an integrated search and be concerned with the whole system right from the start, or should a problem solver incrementally expand the “search domain,” i.e., the subset of system elements and interdependencies that are included in the search efforts? If the latter, how “chunky” should these steps be? Our analysis of a simulation model yields four insights: (1) expanding the search domain in smaller steps can yield a distinct advantage in final system performance, (2) following a completely incremental expansion pattern is not necessary as long as larger chunks are added early on in the process, (3) the value of chunky search is particularly high if highly influential system elements are considered first and highly dependent elements are added later, and (4) under time pressure, chunky search can lose its performance advantage over more integrated search processes. We discuss the implications of our findings for managing organizational search and complex systems more broadly.

Many organisms locate resources in environments in which sensory signals are rare, noisy, and lack directional information. Recent studies of search in such environments model search behavior using random walks (e.g., Lévy walks) that match empirical movement distributions. We extend this modeling approach to include searcher responses to noisy sensory data. We explore the consequences of incorporating such sensory measurements into search behavior using simulations of a visual-olfactory predator in search of prey. Our results show that including even a simple response to noisy sensory data can dominate other features of random search, resulting in lower mean search times and decreased risk of long intervals between target encounters. In particular, we show that a lack of signal is not a lack of information. Searchers that receive no signal can quickly abandon target-poor regions. On the other hand, receiving a strong signal leads a searcher to concentrate search effort near targets. These responses cause simulated searchers to exhibit an emergent area-restricted search behavior similar to that observed of many organisms in nature.

Accessing the Web from mobile handheld devices has become increasingly common. However, accomplishing that task remains challenging mainly due to the physical constraints of handheld devices and the static presentation of Web pages. Adapting the presentation of Web pages is, therefore, critical to enabling effective mobile Web browsing and information searching. Based on cognitive fit theory and information foraging theory, we propose a novel hybrid approach to adapting Web page presentation that integrates three types of adaptation techniques, namely tree-view, hierarchical text summarization, and colored keyword highlighting. By following the design science research framework, we implemented the proposed approach on handheld devices and empirically evaluated the effects of presentation adaptation on mobile Web browsing. The results show that presentation adaptation significantly improves user performance and perception of mobile Web browsing. We also discover that the positive impact of presentation adaptation is moderated by the complexity of an information search task. The findings have significant theoretical and practical implications for the design and implementation of mobile Web applications.

Cellular messenger RNA levels are achieved by the combinatorial complexity of factors controlling transcription, yet the small number of molecules involved in these pathways fluctuates stochastically. It has not yet been experimentally possible to observe the activity of single polymerases on an endogenous gene to elucidate how these events occur in vivo. Here, we describe a method of fluctuation analysis of fluorescently labeled RNA to measure dynamics of nascent RNA—including initiation, elongation, and termination—at an active yeast locus. We find no transcriptional memory between initiation events, and elongation speed can vary by threefold throughout the cell cycle. By measuring the abundance and intranuclear mobility of an upstream transcription factor, we observe that the gene firing rate is directly determined by trans-activating factor search times.

We show how to optimize the search for a hidden object, terrorist, or simply Hider, located at a point H according to a known or unknown distribution ν on a rooted network Q . We modify the traditional \"pathwise search\" approach to a more general notion of \"expanding search.\" When the Hider is restricted to the nodes of Q , an expanding search S consists of an ordering \\documentclass{aastex} \\usepackage{amsbsy} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{bm} \\usepackage{mathrsfs} \\usepackage{pifont} \\usepackage{stmaryrd} \\usepackage{textcomp} \\usepackage{portland,xspace} \\usepackage{amsmath,amsxtra} \\pagestyle{empty} \\DeclareMathSizes{10}{9}{7}{6} \\begin{document} $(a_{1},a_{2},\\ldots)$ \\end{document} of the arcs of a spanning subtree such that the root node is in a 1 and every arc a i is adjacent to a previous arc a j , j < i . If a k contains H , the search time T is \\documentclass{aastex} \\usepackage{amsbsy} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{bm} \\usepackage{mathrsfs} \\usepackage{pifont} \\usepackage{stmaryrd} \\usepackage{textcomp} \\usepackage{portland,xspace} \\usepackage{amsmath,amsxtra} \\pagestyle{empty} \\DeclareMathSizes{10}{9}{7}{6} \\begin{document} $\\lambda (a_{1}) +\\cdots +\\lambda (a_{k})$ \\end{document} , where λ is length measure on Q . For more general distributions ν , an expanding search S is described by the nested family of connected sets S ( t ) that specify the area of Q that has been covered by time t . S (0) is the root, \\documentclass{aastex} \\usepackage{amsbsy} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{bm} \\usepackage{mathrsfs} \\usepackage{pifont} \\usepackage{stmaryrd} \\usepackage{textcomp} \\usepackage{portland,xspace} \\usepackage{amsmath,amsxtra} \\pagestyle{empty} \\DeclareMathSizes{10}{9}{7}{6} \\begin{document} $\\lambda (S(t) ) =t$, and $T=\\min \\{ t: H \\in S(t)\\}$ \\end{document} . For a known Hider distribution ν on a tree Q , the expected time minimizing strategy \\documentclass{aastex} \\usepackage{amsbsy} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{bm} \\usepackage{mathrsfs} \\usepackage{pifont} \\usepackage{stmaryrd} \\usepackage{textcomp} \\usepackage{portland,xspace} \\usepackage{amsmath,amsxtra} \\pagestyle{empty} \\DeclareMathSizes{10}{9}{7}{6} \\begin{document} $\\bar{S}$ \\end{document} begins with the rooted subtree Q ′ maximizing the \"density\" ν ( Q ′)/ λ ( Q ′). (For arbitrary networks, we use this criterion on all spanning subtrees.) The search \\documentclass{aastex} \\usepackage{amsbsy} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{bm} \\usepackage{mathrsfs} \\usepackage{pifont} \\usepackage{stmaryrd} \\usepackage{textcomp} \\usepackage{portland,xspace} \\usepackage{amsmath,amsxtra} \\pagestyle{empty} \\DeclareMathSizes{10}{9}{7}{6} \\begin{document} $\\bar{S}$ \\end{document} can be interpreted as the optimal method of mining known coal seams, when the time to move miners or machines is negligible compared to digging time. When the Hider distribution is unknown, we consider the zero-sum search game where the Hider picks H , the Searcher S , and the payoff is T . For trees Q , the value is V = ( λ ( Q ) + D )/2, where D is a mean distance from root to leaf nodes. If Q is 2-arc connected, V = λ ( Q )/2. Applications and interpretations of the expanding search paradigm are given, particularly to multiple agent search.

Noise pollution from human traffic networks and industrial activity impacts vast areas of our planet. While anthropogenic noise effects on animal communication are well documented, we have very limited understanding of noise impact on more complex ecosystem processes, such as predator–prey interactions, albeit urgently needed to devise mitigation measures. Here, we show that traffic noise decreases the foraging efficiency of an acoustic predator, the greater mouse-eared bat (Myotis myotis). These bats feed on large, ground-running arthropods that they find by listening to their faint rustling sounds. We measured the bats' foraging performance on a continuous scale of acoustically simulated highway distances in a behavioural experiment, designed to rule out confounding factors such as general noise avoidance. Successful foraging bouts decreased and search time drastically increased with proximity to the highway. At 7.5 m to the road, search time was increased by a factor of five. From this increase, we predict a 25-fold decrease in surveyed ground area and thus in foraging efficiency for a wild bat. As most of the bats' prey are predators themselves, the noise impact on the bats' foraging performance will have complex effects on the food web and ultimately on the ecosystem stability. Similar scenarios apply to other ecologically important and highly protected acoustic predators, e.g. owls. Our study provides the empirical basis for quantitative predictions of anthropogenic noise impacts on ecosystem processes. It highlights that an understanding of the effects of noise emissions and other forms of ‘sensory pollution’ are crucially important for the assessment of environmental impact of human activities.