14,429 research outputs found
Interregional Analysis of Interstate Dairy Compacts
Livestock Production/Industries, Marketing,
Patterns of interdivision time correlations reveal hidden cell cycle factors
The time taken for cells to complete a round of cell division is a stochastic process controlled, in part, by intracellular factors. These factors can be inherited across cellular generations which gives rise to, often non-intuitive, correlation patterns in cell cycle timing between cells of different family relationships on lineage trees. Here, we formulate a framework of hidden inherited factors affecting the cell cycle that unifies known cell cycle control models and reveals three distinct interdivision time correlation patterns: aperiodic, alternator and oscillator. We use Bayesian inference with single-cell datasets of cell division in bacteria, mammalian and cancer cells, to identify the inheritance motifs that underlie these datasets. From our inference, we find that interdivision time correlation patterns do not identify a single cell cycle model but generally admit a broad posterior distribution of possible mechanisms. Despite this unidentifiability, we observe that the inferred patterns reveal interpretable inheritance dynamics and hidden rhythmicity of cell cycle factors. This reveals that cell cycle factors are commonly driven by circadian rhythms, but their period may differ in cancer. Our quantitative analysis thus reveals that correlation patterns are an emergent phenomenon that impact cell proliferation and these patterns may be altered in disease
An isogeometric finite element formulation for phase transitions on deforming surfaces
This paper presents a general theory and isogeometric finite element
implementation for studying mass conserving phase transitions on deforming
surfaces. The mathematical problem is governed by two coupled fourth-order
nonlinear partial differential equations (PDEs) that live on an evolving
two-dimensional manifold. For the phase transitions, the PDE is the
Cahn-Hilliard equation for curved surfaces, which can be derived from surface
mass balance in the framework of irreversible thermodynamics. For the surface
deformation, the PDE is the (vector-valued) Kirchhoff-Love thin shell equation.
Both PDEs can be efficiently discretized using -continuous interpolations
without derivative degrees-of-freedom (dofs). Structured NURBS and unstructured
spline spaces with pointwise -continuity are utilized for these
interpolations. The resulting finite element formulation is discretized in time
by the generalized- scheme with adaptive time-stepping, and it is fully
linearized within a monolithic Newton-Raphson approach. A curvilinear surface
parameterization is used throughout the formulation to admit general surface
shapes and deformations. The behavior of the coupled system is illustrated by
several numerical examples exhibiting phase transitions on deforming spheres,
tori and double-tori.Comment: fixed typos, extended literature review, added clarifying notes to
the text, added supplementary movie file
On the road again: assessing driving ability in patients with neurological conditions
Clinicians may not be aware of the specialised methods and adaptations that are used to help people with disabilities to drive a car. We describe a driving assessment process as carried out by one of the UK’s flagship assessment centres, including an overview of the available assessments, adaptations and relevant legislation to guide practitioners about how best to signpost and counsel their patients appropriately about driving
Ames collaborative study of cosmic-ray neutrons. 2: Low- and mid-latitude flights
Progress of the study of cosmic ray neutrons is described. Data obtained aboard flights from Hawaii at altitudes of 41,000 and 45,000 feet, and in the range of geomagnetic latitude 17 N less than or equal to lambda less than or equal to 21 N are reported. Preliminary estimates of neutron spectra are made
Variationally Mimetic Operator Networks
In recent years operator networks have emerged as promising deep learning
tools for approximating the solution to partial differential equations (PDEs).
These networks map input functions that describe material properties, forcing
functions and boundary data to the solution of a PDE. This work describes a new
architecture for operator networks that mimics the form of the numerical
solution obtained from an approximate variational or weak formulation of the
problem. The application of these ideas to a generic elliptic PDE leads to a
variationally mimetic operator network (VarMiON). Like the conventional Deep
Operator Network (DeepONet) the VarMiON is also composed of a sub-network that
constructs the basis functions for the output and another that constructs the
coefficients for these basis functions. However, in contrast to the DeepONet,
the architecture of these sub-networks in the VarMiON is precisely determined.
An analysis of the error in the VarMiON solution reveals that it contains
contributions from the error in the training data, the training error, the
quadrature error in sampling input and output functions, and a "covering error"
that measures the distance between the test input functions and the nearest
functions in the training dataset. It also depends on the stability constants
for the exact solution operator and its VarMiON approximation. The application
of the VarMiON to a canonical elliptic PDE and a nonlinear PDE reveals that for
approximately the same number of network parameters, on average the VarMiON
incurs smaller errors than a standard DeepONet and a recently proposed
multiple-input operator network (MIONet). Further, its performance is more
robust to variations in input functions, the techniques used to sample the
input and output functions, the techniques used to construct the basis
functions, and the number of input functions.Comment: 49 pages, 18 figures, 1 Appendi
Ames collaborative study of cosmic ray neutrons
The results of a collaborative study to define both the neutron flux and the spectrum more precisely and to develop a dosimetry package that can be flown quickly to altitude for solar flare events are described. Instrumentation and analysis techniques were used which were developed to measure accelerator-produced radiation. The instruments were flown in the Ames Research Center high altitude aircraft. Neutron instrumentation consisted of Bonner spheres with both active and passive detector elements, threshold detectors of both prompt-counter and activation-element types, a liquid scintillation spectrometer based on pulse-shape discrimination, and a moderated BF3 counter neutron monitor. In addition, charged particles were measured with a Reuter-Stokes ionization chamber system and dose equivalent with another instrument. Preliminary results from the first series of flights at 12.5 km (41,000 ft) are presented, including estimates of total neutron flux intensity and spectral shape and of the variation of intensity with altitude and geomagnetic latitude
Finite element and isogeometric stabilized methods for the advection-diffusion-reaction equation
We develop two new stabilized methods for the steady advection-diffusion-reaction equation, referred to as the Streamline GSC Method and the Directional GSC Method. Both are globally conservative and perform well in numerical studies utilizing linear, quadratic, cubic, and quartic Lagrange finite elements and maximally smooth B-spline elements. For the streamline GSC method we can prove coercivity, convergence, and optimal-order error estimates in a strong norm that are robust in the advective and reactive limits. The directional GSC method is designed to accurately resolve boundary layers for flows that impinge upon the boundary at an angle, a long-standing problem. The directional GSC method performs better than the streamline GSC method in the numerical studies, but it is not coercive. We conjecture it is inf-sup stable but we are unable to prove it at this time. However, calculations of the inf-sup constant support the conjecture. In the numerical studies, B-spline finite elements consistently perform better than Lagrange finite elements of the same order and number of unknowns.</p
Characterizing the transition from diffuse atomic to dense molecular clouds in the Magellanic clouds with [CII], [CI], and CO
We present and analyze deep Herschel/HIFI observations of the [CII] 158um,
[CI] 609um, and [CI] 370um lines towards 54 lines-of-sight (LOS) in the Large
and Small Magellanic clouds. These observations are used to determine the
physical conditions of the line--emitting gas, which we use to study the
transition from atomic to molecular gas and from C^+ to C^0 to CO in their low
metallicity environments. We trace gas with molecular fractions in the range
0.1<f(H2)<1, between those in the diffuse H2 gas detected by UV absorption
(f(H2)<0.2) and well shielded regions in which hydrogen is essentially
completely molecular. The C^0 and CO column densities are only measurable in
regions with molecular fractions f(H2)>0.45 in both the LMC and SMC. Ionized
carbon is the dominant gas-phase form of this element that is associated with
molecular gas, with C^0 and CO representing a small fraction, implying that
most (89% in the LMC and 77% in the SMC) of the molecular gas in our sample is
CO-dark H2. The mean X_CO conversion factors in our LMC and SMC sample are
larger than the value typically found in the Milky Way. When applying a
correction based on the filling factor of the CO emission, we find that the
values of X_CO in the LMC and SMC are closer to that in the Milky Way. The
observed [CII] intensity in our sample represents about 1% of the total
far-infrared intensity from the LOSs observed in both Magellanic Clouds.Comment: 32 pages, 21 figures, Accepted to Ap
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