Effect of Thickness Variation on Warp in High-Temperature Drying Plantation-Grown Loblolly Pine 2 by 4'S

Currently, an increasing proportion of southern pine dimension lumber comes from plantations; therefore, an increase in grade, value, and volume loss from warp is expected. One factor that has not been fully explored is the effect of lumber thickness variation on warp. The primary objective of this study was to increase quantitative understanding of the effects of thickness variation on crook, bow, and twist during high-temperature kiln-drying of plantation-grown loblolly pine to determine the importance of its control on the development of warp. Plantation-grown, 2 by 4 (nominal 50- by 100-mm) loblolly pine were kiln-dried at high temperature after surfacing them in such a way as to produce certain patterns of thickness variation. One group was not surfaced, i.e., left as mill run. All boards in a second group were surfaced to the same thickness. In a third group, the boards were divided into thirds, and each third surfaced to a different thickness. In this group, boards of the same thickness were stacked in vertical alignment to exaggerate the effect of the thickness variation. The fourth group differed from the third group in that the three thicknesses were randomly placed in the package. The extreme thickness variations did aggravate warp, especially twist. As a result of better sticker contact, thick boards warped less than did thin boards. However, even with perfect sticker contact, a substantial amount of warp developed, indicating that control of thickness variation can reduce but will not eliminate warp. Correlation of warp with board characteristics suggests that boards containing pith warp more than ones without pith, and boards sawn from near the center of the tree warp more than boards farther from the center of the tree

The numerical solution of linear multi-term fractional differential equations: Systems of equations

This is a PDF version of a preprint submitted to Elsevier. The definitive version was published in the Journal of computational and applied mathematics and is available at www.elsevier.comThis article discusses how the numerical approximation of a linear multi-term fractional differential equation can be calculated by the reduction of the problem to a system of ordinary and fractional differential equations each of order at most unity.This article was submitted to the RAE2008 for the University of Chester - Applied Mathematics

The detection and photometric redshift determination of distant galaxies using SIRTF's Infrared Array Camera

We investigate the ability of the Space Infrared Telescope Facility's Infrared Array Camera to detect distant (z ~ 3)galaxies and measure their photometric redshifts. Our analysis shows that changing the original long wavelength filter specifications provides significant improvements in performance in this and other areas.Comment: 28 pages incl 12 figures; to appear in June 1999 PASP. Fig.12 replaced with corrected versio

Positive autoregulation of the transcription factor Pax6 in response to increased levels of either of its major isoforms, Pax6 or Pax6(5a), in cultured cells

<p>Abstract</p> <p>Background</p> <p>Pax6 is a transcription factor essential for normal development of the eyes and nervous system. It has two major isoforms, Pax6 and Pax6(5a), and the ratios between their expression levels vary within narrow limits. We tested the effects of overexpressing either one or other isoform on endogenous Pax6 expression levels in Neuro2A and NIH3T3 cells.</p> <p>Results</p> <p>We found that both isoforms caused an up-regulation of endogenous Pax6 expression in cells with (Neuro2A) or without (NIH3T3) constitutive Pax6 expression. Western blots showed that cells stably transfected with constructs expressing either Pax6 or Pax6(5a) contained raised levels of both Pax6 and Pax6(5a). Quantitative RT-PCR confirmed an increase in levels of <it>Pax6(5a) </it>mRNA in cells containing Pax6-expressing constructs and an increase in levels of <it>Pax6 </it>mRNA in cells containing Pax6(5a)-expressing constructs. The fact that the introduction of constructs expressing only one isoform increased the cellular levels of not only that isoform but also the other indicates that activation of the endogenous <it>Pax6 </it>locus occurred. The ratio between the levels of the two isoforms was maintained close to physiological values. The overexpression of either isoform in neuroblastoma (Neuro2A) cell lines also promoted morphological change and an increase in β-III-tubulin expression, indicating an increase in neurogenesis.</p> <p>Conclusion</p> <p>Our results demonstrate that Pax6 can up-regulate production of Pax6 protein from an entire intact endogenous <it>Pax6 </it>locus in its genomic environment. This adds to previous studies showing that Pax6 can up-regulate reporter expression driven by isolated <it>Pax6 </it>regulatory elements. Furthermore, our results suggest that an important function of positive feedback might be to stabilise the relative levels of Pax6 and Pax6(5a).</p

Normal ventral telencephalic expression of Pax6 is required for normal development of thalamocortical axons in embryonic mice

<p>Abstract</p> <p>Background</p> <p>In addition to its well-known expression in dorsal telencephalic progenitor cells, where it regulates cell proliferation and identity, the transcription factor Pax6 is expressed in some ventral telencephalic cells, including many postmitotic neurons. Its functions in these cells are unknown.</p> <p>Results</p> <p>We generated a new floxed allele of <it>Pax6 </it>and tested the consequences of a highly specific ventral telencephalic depletion of Pax6. We used the <it>Six3</it>^{<it>A1A2</it>}-<it>Cre </it>allele that drives production of Cre recombinase in a specific region of Pax6-expression close to the internal capsule, through which thalamic axons navigate to cerebral cortex. Depletion in this region caused many thalamic axons to take aberrant routes, either failing to turn normally into ventral telencephalon to form the internal capsule or exiting the developing internal capsule ventrally. We tested whether these defects might have resulted from abnormalities of two structural features proposed to guide thalamic axons into and through the developing internal capsule. First, we looked for the early pioneer axons that project from the region of the future internal capsule to the thalamus and are thought to guide thalamocortical axons to the internal capsule: we found that they are present in conditional mutants. Second, we examined the development of the corridor of Islet1-expressing cells that guides thalamic axons through ventral telencephalon and found that it was broader and less dense than normal in conditional mutants. We also examined corticofugal axons that are thought to interact with ascending thalamocortical axons, resulting in each set providing guidance to the other, and found that some are misrouted to lateral telencephalon.</p> <p>Conclusion</p> <p>These findings indicate that ventral telencephalic Pax6 is important for formation of the Islet1-expressing corridor and the thalamic and cortical axons that grow through it. We suggest that Pax6 might affect thalamic axonal growth indirectly via its effect on the corridor.</p

Biologically-informed neural networks guide mechanistic modeling from sparse experimental data

Biologically-informed neural networks (BINNs), an extension of physics-informed neural networks [1], are introduced and used to discover the underlying dynamics of biological systems from sparse experimental data. In the present work, BINNs are trained in a supervised learning framework to approximate in vitro cell biology assay experiments while respecting a generalized form of the governing reaction-diffusion partial differential equation (PDE). By allowing the diffusion and reaction terms to be multilayer perceptrons (MLPs), the nonlinear forms of these terms can be learned while simultaneously converging to the solution of the governing PDE. Further, the trained MLPs are used to guide the selection of biologically interpretable mechanistic forms of the PDE terms which provides new insights into the biological and physical mechanisms that govern the dynamics of the observed system. The method is evaluated on sparse real-world data from wound healing assays with varying initial cell densities [2]

Propagation Effectiveness of the Surrogator for Northern Bobwhites in Southern Texas

Attempts to restore populations of northern bobwhites (Colinus virginianus) using pen-raised quail have been documented since the early 1900s. Low restoration success, based on low post-release survival rates and long distance dispersal from release sites, have proven the ineffectiveness of pen-raised quail in restoration of wild populations. The Surrogatort, a recent quail propagation tool using pen-raised quail, has been publicized as a method for increasing success rates in restoration of northern bobwhite populations by producing higher post-release survival and minimal dispersal. We tested the hypothesis that the Surrogatort is an effective means of supplementing populations of northern bobwhites in southern Texas. We raised 1,000 northern bobwhites in 2 Surrogators and conducted 2 trials in 2010 on a 990-ha ranch in Wilson County, Texas. Twenty northern bobwhites from each Surrogator were fitted with radio transmitters 12 hrs before release. We attempted to locate each bird daily for 3 weeks upon release from Surrogators followed by a reduced effort of 3 times per week until 100% mortality. Daily survival rates were low in Trial 1 (Surrogator A 1⁄4 0.87 and Surrogator B 1⁄4 0.96) and Trial 2 (Surrogator A 1⁄4 0.83 and Surrogator B 1⁄4 0.87). Mean distances traveled by post-released birds for Trial 1 were 401 and 1,416 m for Surrogators A and B, respectively. The Surrogator is not an effective means of restoring wild populations of northern bobwhites in southern Texas

Fecundity of Wild Northern Bobwhite Hens Under Hatchery Conditions

We describe egg production by 88 pairs of randomly selected, mature, wild-caught northern bobwhite (Colinus virginianus) hens housed under optimal conditions of food, water, climate, and a 17-hr photoperiod in a hatchery. We collected eggs daily using an 18-day period to differentiate between clutches. Hens continuously laid eggs until ceasing production. We evaluated number of eggs laid by each hen individually and hens collectively including total number, number/clutch, number/day, hatching success, and egg mass. Eighty-six hens produced 5,888 eggs. Number of eggs produced by individual hens ranged from 0 to 172 over ~ 200 days. Mean number of eggs laid/hen/day was 0.86. Clutch size ranged from 0 (n 1⁄4 2) to 12 (n 1⁄4 1). Mean number of eggs/clutch was 8.57. There was a strong correlation between clutch size and number of clutches. Some hens demonstrated continuous production of several large clutches. Hatching success of 5,793 eggs included for analysis was 61.6% (3,571 hatched, 2,222 failed to hatch). Hatched eggs had a greater mean mass compared to those that did not hatch

Learning differential equation models from stochastic agent-based model simulations

Agent-based models provide a flexible framework that is frequently used for modelling many biological systems, including cell migration, molecular dynamics, ecology, and epidemiology. Analysis of the model dynamics can be challenging due to their inherent stochasticity and heavy computational requirements. Common approaches to the analysis of agent-based models include extensive Monte Carlo simulation of the model or the derivation of coarse-grained differential equation models to predict the expected or averaged output from the agent-based model. Both of these approaches have limitations, however, as extensive computation of complex agent-based models may be infeasible, and coarse-grained differential equation models can fail to accurately describe model dynamics in certain parameter regimes. We propose that methods from the equation learning field provide a promising, novel, and unifying approach for agent-based model analysis. Equation learning is a recent field of research from data science that aims to infer differential equation models directly from data. We use this tutorial to review how methods from equation learning can be used to learn differential equation models from agent-based model simulations. We demonstrate that this framework is easy to use, requires few model simulations, and accurately predicts model dynamics in parameter regions where coarse-grained differential equation models fail to do so. We highlight these advantages through several case studies involving two agent-based models that are broadly applicable to biological phenomena: a birth-death-migration model commonly used to explore cell biology experiments and a susceptible-infected-recovered model of infectious disease spread