Properties and Wood Bonding Capacity of Nanoclay-Modified Urea and Melamine Formaldehyde Resins

Urea formaldehyde (UF) and melamine formaldehyde (MF) thermosetting resins were substituted with up to 6% nanoclay (organic modified Cloisite®30B and unmodified Nanofil® 116; Southern Clay Ltd, Austin, TX) and assessed for mixing and curing compatibility using X-ray diffraction, differential scanning calorimetry, wood lap-shear tests, and particleboard strength tests. Cloisite® 30B exfoliated fully in both resin types, whereas Nanofil® 116 showed increased spacing between platelets (intercalation) but not exfoliation. Nanoclays improved bonding strength of MF more than UF resin, and 2% nanoclay with a coupling agent in MF significantly enhanced particleboard bonding strength. Also, thickness swelling of particleboard in water decreased with up to 6% nanoclay. To decrease costs, MF resin could potentially be substituted by up to 6% nanoclay with no detrimental effect on properties

Improving Core Bond Strength of Particleboard Through Particle Size Redistribution

Novel particleboard furnish mixtures were formulated to improve the core-bonding and screw-holding of industrial particleboard without increasing resin content or board density. Single-layer (uniform vertical density with core furnish only) and conventional 3-layer particleboards were manufactured at two density levels from four novel mixes plus control (unscreened industrial core furnish). Board mean and core density, internal bond strength, edge screw withdrawal resistance, and moduli of rupture and elasticity were measured.The core of commercial furniture-grade particleboard appears to contain too many fine particulates and insufficient coarser particles. Uniform density profile single-layer boards containing novel mixes with higher-coarse (>2 mm) and lower-fines

Approximate and exact nodes of fermionic wavefunctions: coordinate transformations and topologies

A study of fermion nodes for spin-polarized states of a few-electron ions and molecules with $s,p,d$ one-particle orbitals is presented. We find exact nodes for some cases of two electron atomic and molecular states and also the first exact node for the three-electron atomic system in $^4S(p^3)$ state using appropriate coordinate maps and wavefunction symmetries. We analyze the cases of nodes for larger number of electrons in the Hartree-Fock approximation and for some cases we find transformations for projecting the high-dimensional node manifolds into 3D space. The node topologies and other properties are studied using these projections. We also propose a general coordinate transformation as an extension of Feynman-Cohen backflow coordinates to both simplify the nodal description and as a new variational freedom for quantum Monte Carlo trial wavefunctions.Comment: 7 pages, 7 figure

Can a single image processing algorithm work equally well across all phases of DCE-MRI?

Image segmentation and registration are said to be challenging when applied to dynamic contrast enhanced MRI sequences (DCE-MRI). The contrast agent causes rapid changes in intensity in the region of interest and elsewhere, which can lead to false positive predictions for segmentation tasks and confound the image registration similarity metric. While it is widely assumed that contrast changes increase the difficulty of these tasks, to our knowledge no work has quantified these effects. In this paper we examine the effect of training with different ratios of contrast enhanced (CE) data on two popular tasks: segmentation with nnU-Net and Mask R-CNN and registration using VoxelMorph and VTN. We experimented further by strategically using the available datasets through pretraining and fine tuning with different splits of data. We found that to create a generalisable model, pretraining with CE data and fine tuning with non-CE data gave the best result. This interesting find could be expanded to other deep learning based image processing tasks with DCE-MRI and provide significant improvements to the models performance

Neighborhoods of trees in circular orderings

In phylogenetics, a common strategy used to construct an evolutionary tree for a set of species X is to search in the space of all such trees for one that optimizes some given score function (such as the minimum evolution, parsimony or likelihood score). As this can be computationally intensive, it was recently proposed to restrict such searches to the set of all those trees that are compatible with some circular ordering of the set X. To inform the design of efficient algorithms to perform such searches, it is therefore of interest to find bounds for the number of trees compatible with a fixed ordering in the neighborhood of a tree that is determined by certain tree operations commonly used to search for trees: the nearest neighbor interchange (nni), the subtree prune and regraft (spr) and the tree bisection and reconnection (tbr) operations. We show that the size of such a neighborhood of a binary tree associated with the nni operation is independent of the tree’s topology, but that this is not the case for the spr and tbr operations. We also give tight upper and lower bounds for the size of the neighborhood of a binary tree for the spr and tbr operations and characterize those trees for which these bounds are attained

Manganese-Enhanced Magnetic Resonance Imaging in Takotsubo Syndrome

Acknowledgments The authors thank the Edinburgh Imaging Facility. Sources of Funding This work and T. Singh, S. Joshi, and Drs Dweck and Newby are supported by the British Heart Foundation (grants FS/17/19/32641, CS/17/1/32445, RG/16/10/32375, RE/18/5/34216, FS/ICRF/20/26002, and FS/SCRF/21/32010). T. Singh is supported by the Medical Research Council (grant MR/T029153/1). Dr Newby is the recipient of a Wellcome Trust Senior Investigator Award (WT103782AIA). Dr McCann is supported by an NIHR Research Professorship (08-2017-ST2-007). The Edinburgh Clinical Research Facilities and Edinburgh Imaging Facility are supported by the National Health Service Research Scotland through the National Health Service Lothian Health Board.Peer reviewe

The comparative clinical course of pregnant and non-pregnant women hospitalised with influenza A(H1N1)pdm09 infection

Introduction: The Influenza Clinical Information Network (FLU-CIN) was established to gather detailed clinical and epidemiological information about patients with laboratory confirmed A(H1N1)pdm09 infection in UK hospitals. This report focuses on the clinical course and outcomes of infection in pregnancy.Methods: A standardised data extraction form was used to obtain detailed clinical information from hospital case notes and electronic records, for patients with PCR-confirmed A(H1N1)pdm09 infection admitted to 13 sentinel hospitals in five clinical 'hubs' and a further 62 non-sentinel hospitals, between 11th May 2009 and 31st January 2010.Outcomes were compared for pregnant and non-pregnant women aged 15-44 years, using univariate and multivariable techniques.Results: Of the 395 women aged 15-44 years, 82 (21%) were pregnant; 73 (89%) in the second or third trimester. Pregnant women were significantly less likely to exhibit severe respiratory distress at initial assessment (OR?=?0.49 (95% CI: 0.30-0.82)), require supplemental oxygen on admission (OR?=?0.40 (95% CI: 0.20-0.80)), or have underlying co-morbidities (p-trend <0.001). However, they were equally likely to be admitted to high dependency (Level 2) or intensive care (Level 3) and/or to die, after adjustment for potential confounders (adj. OR?=?0.93 (95% CI: 0.46-1.92). Of 11 pregnant women needing Level 2/3 care, 10 required mechanical ventilation and three died.Conclusions: Since the expected prevalence of pregnancy in the source population was 6%, our data suggest that pregnancy greatly increased the likelihood of hospital admission with A(H1N1)pdm09. Pregnant women were less likely than non-pregnant women to have respiratory distress on admission, but severe outcomes were equally likely in both groups

Random tree growth by vertex splitting

We study a model of growing planar tree graphs where in each time step we separate the tree into two components by splitting a vertex and then connect the two pieces by inserting a new link between the daughter vertices. This model generalises the preferential attachment model and Ford's $\alpha$-model for phylogenetic trees. We develop a mean field theory for the vertex degree distribution, prove that the mean field theory is exact in some special cases and check that it agrees with numerical simulations in general. We calculate various correlation functions and show that the intrinsic Hausdorff dimension can vary from one to infinity, depending on the parameters of the model.Comment: 47 page