826 research outputs found

    Sonic hedgehog-expressing cells in the developing limb measure time by an intrinsic cell cycle clock

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    How time is measured is an enduring issue in developmental biology. Classical models of somitogenesis and limb development implicated intrinsic cell cycle clocks, but their existence remains controversial. Here we show that an intrinsic cell cycle clock in polarizing region cells of the chick limb bud times the duration of Sonic hedgehog (Shh) expression, which encodes the morphogen specifying digit pattern across the antero-posterior axis (thumb to little finger). Timing by this clock starts when polarizing region cells fall out of range of retinoic acid signalling. We found that timing of Shh transcription by the cell cycle clock can be reset, thus revealing an embryonic form of self-renewal. In contrast, antero-posterior positional values cannot be reset, suggesting that this may be an important constraint on digit regeneration. Our findings provide the first evidence for an intrinsic cell cycle timer controlling duration and patterning activity of a major embryonic signalling centre

    Coopetition in Temporary Contexts: Examining Swift Trust and Swift Distrust in Humanitarian Operations

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    Purpose ā€“ By drawing on commitment-trust theory, we examine the role of swift trust and distrust in supporting coopetition under conditions of uncertainty and interdependence in the setting of humanitarian disaster relief organisations. Design/methodology/approach ā€“ This paper presents findings from case studies of 18 international humanitarian relief organisations based on 48 interviews and the analysis of publicly available documents. Findings ā€“ We find that both swift trust and swift distrust support coopetition. As coopetition is simultaneous cooperation and competition, in this study we show how swift trust and swift distrust also occur simultaneously in coopetitive contexts. Research limitations/implications ā€“ Coopetition as a strategic choice is well-researched in the private sector, yet has received less attention in the nonprofit sector, particularly in contexts that are shaped by interdependence and uncertainty. We show the importance of swift trust and swift distrust in coopetitive relationships by drawing on commitment-trust theory. Practical implications ā€“ In focusing on a competitive environment in which cooperation is essential, we find limited choice of coopetitive partners. Humanitarian relief organisations must often simply work with whichever other organisations are available. We highlight how trust and distrust are not opposite ends of a spectrum and detail how both contribute to coopetitive relationships. Originality/value ā€“ Our findings contribute to commitment-trust theory by explaining the important role of distrust in forging coopetitive relationships. Furthermore, we contribute to prior work on coopetition by focusing on an uncertain and interdependent nonprofit environment

    Human optional stopping in a heteroscedastic world

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    When making decisions, animals must trade off the benefits of information harvesting against the opportunity cost of prolonged deliberation. Deciding when to stop accumulating information and commit to a choice is challenging in natural environments, where the reliability of decision-relevant information may itself vary unpredictably over time (variable variance or "heteroscedasticity"). We asked humans to perform a categorization task in which discrete, continuously valued samples (oriented gratings) arrived in series until the observer made a choice. Human behavior was best described by a model that adaptively weighted sensory signals by their inverse prediction error and integrated the resulting quantities with a linear urgency signal to a decision threshold. This model approximated the output of a Bayesian model that computed the full posterior probability of a correct response, and successfully predicted adaptive weighting of decision information in neural signals. Adaptive weighting of decision information may have evolved to promote optional stopping in heteroscedastic natural environments. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

    The Use of Technological Innovations in Promoting Effective Humanitarian Aid

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    The number and scale of natural and man-made disasters is increasing at an unprecedented rate, leading to devastating consequences for citizens, governments, and entire economies. In response, humanitarian supply chains (HSC) are used as a means of reducing suffering and saving lives. HSCs manage and deliver aid to those in need after a disasterstrikes and exist only for the period of the relief operation. With reduced budgetsthere is an impetusto investigate technological innovationsthat offer increased efficiencies and reduced costs. One such innovation is information and communications technology (ICT), which is currently under-utilized by HSCs. This paper investigates the benefits, barriers, and enablers of increased ICT adoption in HSCs and offers solutions most suited to their needs. The study develops a matrix that identifiesthe enablers and barriers of implementing innovative ICT and highlights associated managerial implications and suggested areas for future research

    The SSVEP-Based BCI Text Input System Using Entropy Encoding Algorithm

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    The so-called amyotrophic lateral sclerosis (ALS) or motor neuron disease (MND) is a neurodegenerative disease with various causes. It is characterized by muscle spasticity, rapidly progressive weakness due to muscle atrophy, and difficulty in speaking, swallowing, and breathing. The severe disabled always have a common problem that is about communication except physical malfunctions. The steady-state visually evoked potential based brain computer interfaces (BCI), which apply visual stimulus, are very suitable to play the role of communication interface for patients with neuromuscular impairments. In this study, the entropy encoding algorithm is proposed to encode the letters of multilevel selection interface for BCI text input systems. According to the appearance frequency of each letter, the entropy encoding algorithm is proposed to construct a variable-length tree for the letter arrangement of multilevel selection interface. Then, the Gaussian mixture models are applied to recognize electrical activity of the brain. According to the recognition results, the multilevel selection interface guides the subject to spell and type the words. The experimental results showed that the proposed approach outperforms the baseline system, which does not consider the appearance frequency of each letter. Hence, the proposed approach is able to ease text input interface for patients with neuromuscular impairments

    Computational meta'omics for microbial community studies

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    Complex microbial communities are an integral part of the Earth's ecosystem and of our bodies in health and disease. In the last two decades, culture-independent approaches have provided new insights into their structure and function, with the exponentially decreasing cost of high-throughput sequencing resulting in broadly available tools for microbial surveys. However, the field remains far from reaching a technological plateau, as both computational techniques and nucleotide sequencing platforms for microbial genomic and transcriptional content continue to improve. Current microbiome analyses are thus starting to adopt multiple and complementary meta'omic approaches, leading to unprecedented opportunities to comprehensively and accurately characterize microbial communities and their interactions with their environments and hosts. This diversity of available assays, analysis methods, and public data is in turn beginning to enable microbiome-based predictive and modeling tools. We thus review here the technological and computational meta'omics approaches that are already available, those that are under active development, their success in biological discovery, and several outstanding challenges
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