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 $C^1$-continuous interpolations without derivative degrees-of-freedom (dofs). Structured NURBS and unstructured spline spaces with pointwise $C^1$-continuity are utilized for these interpolations. The resulting finite element formulation is discretized in time by the generalized-$\alpha$ 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