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Royal Society Open Science Dec 2019The actin droplet machine is a computer model of a three-dimensional network of actin bundles developed in a droplet of a physiological solution, which implements...
The actin droplet machine is a computer model of a three-dimensional network of actin bundles developed in a droplet of a physiological solution, which implements mappings of sets of binary strings. The actin bundle network is conductive to travelling excitations, i.e. impulses. The machine is interfaced with an arbitrary selected set of electrodes through which stimuli, binary strings of length represented by impulses generated on the electrodes, are applied and responses are recorded. The responses are recorded in a form of impulses and then converted to binary strings. The machine's state is a binary string of length : if there is an impulse recorded on the th electrode, there is a '1' in the th position of the string, and '0' otherwise. We present a design of the machine and analyse its state transition graphs. We envisage that actin droplet machines could form an elementary processor of future massive parallel computers made from biopolymers.
PubMed: 31903204
DOI: 10.1098/rsos.191135 -
Advances in Neural Information... Nov 2022Training with backpropagation (BP) in standard deep learning consists of two main steps: a forward pass that maps a data point to its prediction, and a backward pass...
Training with backpropagation (BP) in standard deep learning consists of two main steps: a forward pass that maps a data point to its prediction, and a backward pass that propagates the error of this prediction back through the network. This process is highly effective when the goal is to minimize a specific objective function. However, it does not allow training on networks with cyclic or backward connections. This is an obstacle to reaching brain-like capabilities, as the highly complex heterarchical structure of the neural connections in the neocortex are potentially fundamental for its effectiveness. In this paper, we show how predictive coding (PC), a theory of information processing in the cortex, can be used to perform inference and learning on arbitrary graph topologies. We experimentally show how this formulation, called , can be used to flexibly perform different tasks with the same network by simply stimulating specific neurons. This enables the model to be queried on stimuli with different structures, such as partial images, images with labels, or images without labels. We conclude by investigating how the topology of the graph influences the final performance, and comparing against simple baselines trained with BP.
PubMed: 37090087
DOI: No ID Found -
Advanced Science (Weinheim,... Oct 2021With the rapid development of commercial flexible/wearable devices, flexible batteries have attracted great attention as optimal power sources. However, a combination of...
With the rapid development of commercial flexible/wearable devices, flexible batteries have attracted great attention as optimal power sources. However, a combination of high energy density and excellent arbitrary deformation ability is still a critical challenge to satisfy practical applications. Inspired by rigid and soft features of chemical molecular structures, novel bidirectional flexible snake-origami lithium-ion batteries (LIBs) with both high energy density and favorable flexibility are designed and fabricated. The flexible snake-origami battery consists of rigid and soft segments, where the former is designed as the energy unit and the latter served as the deformation unit. With the unique features from such design, the as-fabricated battery with calculating all the components exhibits a record-setting energy density of 357 Wh L (133 Wh kg ), compared with the cell-scale flexible LIBs achieved from both academic and industry. Additionally, a design principle is established to verify the validity of utilizing rigid-soft-coupled structure for enduring various deformations, and the intrinsic relationship between battery structure, energy density, and flexibility can be confirmed. The results suggest that the design principle and performance of bidirectional flexible snake-origami batteries will provide a new reliable strategy for achieving high energy flexible batteries for wearable devices.
PubMed: 34449128
DOI: 10.1002/advs.202101372 -
European Journal of Pediatrics Nov 2018Ensuring optimal nutrition is vital in critically ill children and enteral feeding is the main route of delivery in intensive care. Feeding intolerance is the most... (Review)
Review
Ensuring optimal nutrition is vital in critically ill children and enteral feeding is the main route of delivery in intensive care. Feeding intolerance is the most commonly cited reason amongst pediatric intensive care unit healthcare professionals for stopping or withholding enteral nutrition, yet the definition for this remains inconsistent, nebulous, and entirely arbitrary. Not only does this pose problems clinically, but research in this field frequently uses feeding intolerance as an endpoint and the heterogeneity in this definition makes the comparison of studies difficult and meta-analysis impossible. We reviewed the use of, and definitions of, the term feed intolerance in pediatric intensive care research papers in the last 20 years. Gastric residual volume remains the most common factor used to define feed intolerance, despite the lack of evidence for this. Healthcare professionals would benefit from further education to improve their awareness of the limitations of the markers to define feeding intolerance, and the international PICU community needs to agree a consistent definition of this phenomenon to improve consistency in both practice and research.Conclusion: This paper will provide a narrative review of the definitions of, evidence for, and markers of feeding intolerance in critically ill children. What is Known?: • Feeding intolerance is a commonly cited reason amongst pediatric intensive care unit healthcare professionals for stopping or withholding enteral nutrition. • There is no agreed definition for feeding intolerance in critically ill children. What is New?: • This paper provides an up to date review of the definitions of, evidence for, and markers of feeding intolerance in critically ill children. • Despite no evidence, gastric residual volume continues to drive clinical bedside decisions about enteral feeding and feeding tolerance.
Topics: Child; Critical Illness; Enteral Nutrition; Food Intolerance; Humans; Infant; Infant, Newborn; Intensive Care Units, Pediatric
PubMed: 30116972
DOI: 10.1007/s00431-018-3229-4 -
Journal of Medical Ethics Sep 1989The ethical problem of how to apportion limited resources amongst the needy has been forced on us by arbitrary limitation of health expenditure. Its solution would not...
The ethical problem of how to apportion limited resources amongst the needy has been forced on us by arbitrary limitation of health expenditure. Its solution would not be required if health expenditure were higher. Distribution of resources according to best value for money, assessed as Quality Adjusted Life Years (QALYs) per unit cost, has been suggested as a possible solution, but leads to absurd anomalies. In the calculation of QALYs the implied value of life is no more than the absence of suffering. The use of QALYs for the comparison of treatments that are symptomatic or life-saving therefore leads to serious undervaluation of life and treatments that prolong it. Moreover, distribution of resources by best value for money, however assessed, is inequitable since for a given degree of suffering those whose illnesses happen to be cheaper to treat will be treated in preference to those whose treatments are more expensive.
Topics: Economics; Health Care Rationing; Health Resources; Models, Statistical; Pain; Patient Selection; Quality of Life; Resource Allocation; Social Values; Stress, Psychological; United Kingdom; Value of Life
PubMed: 2795628
DOI: 10.1136/jme.15.3.143 -
Nature Communications Oct 2023Dispersion decomposes compound light into its monochromatic components, which is detrimental to broadband imaging but advantageous for spectroscopic applications....
Dispersion decomposes compound light into its monochromatic components, which is detrimental to broadband imaging but advantageous for spectroscopic applications. Metasurfaces provide a unique path to modulate the dispersion by adjusting structural parameters on a two-dimensional plane. However, conventional linear phase compensation does not adequately match the meta-unit's dispersion characteristics with required complex dispersion, hindering at-will dispersion engineering over a very wide bandwidth particularly. Here, we propose an asymptotic phase compensation strategy for ultra-broadband dispersion-controlled metalenses. Metasurfaces with extraordinarily high aspect ratio nanostructures have been fabricated for arbitrary dispersion control in ultra-broad bandwidth, and we experimentally demonstrate the single-layer achromatic metalenses in the visible to infrared spectrum (400 nm~1000 nm, NA = 0.164). Our proposed scheme provides a comprehensive theoretical framework for single-layer meta-optics, allowing for arbitrary dispersion manipulation without bandwidth restrictions. This development is expected to have significant applications in ultra-broadband imaging and chromatography detection, among others.
PubMed: 37863896
DOI: 10.1038/s41467-023-42268-5 -
Nanomaterials (Basel, Switzerland) Jun 2022Optical neural networks (ONN) have become the most promising solution to replacing electronic neural networks, which have the advantages of large bandwidth, low energy...
Optical neural networks (ONN) have become the most promising solution to replacing electronic neural networks, which have the advantages of large bandwidth, low energy consumption, strong parallel processing ability, and super high speed. Silicon-based micro-nano integrated photonic platforms have demonstrated good compatibility with complementary metal oxide semiconductor (CMOS) processing. Therefore, without completely changing the existing silicon-based fabrication technology, optoelectronic hybrid devices or all-optical devices of better performance can be achieved on such platforms. To meet the requirements of smaller size and higher integration for silicon photonic computing, the topology of a four-channel coarse wavelength division multiplexer (CWDM) and an optical scattering unit (OSU) are inversely designed and optimized by Lumerical software. Due to the random optical power splitting ratio and incoherency, the intensities of different input signals from CWDM can be weighted and summed directly by the subsequent OSU to accomplish arbitrary multiply-accumulate (MAC) operations, therefore supplying the core foundation for scattering ONN architecture.
PubMed: 35807971
DOI: 10.3390/nano12132136 -
ELife Nov 2022How dynamic interactions between nervous system regions in mammals performs online motor control remains an unsolved problem. In this paper, we show that feedback...
How dynamic interactions between nervous system regions in mammals performs online motor control remains an unsolved problem. In this paper, we show that feedback control is a simple, yet powerful way to understand the neural dynamics of sensorimotor control. We make our case using a minimal model comprising spinal cord, sensory and motor cortex, coupled by long connections that are plastic. It succeeds in learning how to perform reaching movements of a planar arm with 6 muscles in several directions from scratch. The model satisfies biological plausibility constraints, like neural implementation, transmission delays, local synaptic learning and continuous online learning. Using differential Hebbian plasticity the model can go from motor babbling to reaching arbitrary targets in less than 10 min of in silico time. Moreover, independently of the learning mechanism, properly configured feedback control has many emergent properties: neural populations in motor cortex show directional tuning and oscillatory dynamics, the spinal cord creates convergent force fields that add linearly, and movements are ataxic (as in a motor system without a cerebellum).
Topics: Animals; Feedback; Models, Neurological; Movement; Learning; Cerebellum; Mammals
PubMed: 36373657
DOI: 10.7554/eLife.77216 -
PloS One 2018Fluorescent reporters are commonly used to quantify activities or properties of both natural and engineered cells. Fluorescence is still typically reported only in...
Fluorescent reporters are commonly used to quantify activities or properties of both natural and engineered cells. Fluorescence is still typically reported only in arbitrary or normalized units, however, rather than in units defined using an independent calibrant, which is problematic for scientific reproducibility and even more so when it comes to effective engineering. In this paper, we report an interlaboratory study showing that simple, low-cost unit calibration protocols can remedy this situation, producing comparable units and dramatic improvements in precision over both arbitrary and normalized units. Participants at 92 institutions around the world measured fluorescence from E. coli transformed with three engineered test plasmids, plus positive and negative controls, using simple, low-cost unit calibration protocols designed for use with a plate reader and/or flow cytometer. In addition to providing comparable units, use of an independent calibrant allows quantitative use of positive and negative controls to identify likely instances of protocol failure. The use of independent calibrants thus allows order of magnitude improvements in precision, narrowing the 95% confidence interval of measurements in our study up to 600-fold compared to normalized units.
Topics: Calibration; Confidence Intervals; Escherichia coli; Flow Cytometry; Fluorescence
PubMed: 29928012
DOI: 10.1371/journal.pone.0199432 -
Journal of the American Statistical... 2021Methods for inferring average causal effects have traditionally relied on two key assumptions: (i) the intervention received by one unit cannot causally influence the...
Methods for inferring average causal effects have traditionally relied on two key assumptions: (i) the intervention received by one unit cannot causally influence the outcome of another; and (ii) units can be organized into nonoverlapping groups such that outcomes of units in separate groups are independent. In this article, we develop new statistical methods for causal inference based on a single realization of a network of connected units for which neither assumption (i) nor (ii) holds. The proposed approach allows both for arbitrary forms of interference, whereby the outcome of a unit may depend on interventions received by other units with whom a network path through connected units exists; and long range dependence, whereby outcomes for any two units likewise connected by a path in the network may be dependent. Under network versions of consistency and no unobserved confounding, inference is made tractable by an assumption that the networks outcome, treatment and covariate vectors are a single realization of a certain chain graph model. This assumption allows inferences about various network causal effects via the , a network generalization of Robins' well-known g-computation algorithm previously described for causal inference under assumptions (i) and (ii). Supplementary materials for this article are available online.
PubMed: 34366505
DOI: 10.1080/01621459.2020.1811098