Toward better build volume packing in additive manufacturing: classification of existing problems and benchmarks

In many cases, the efficient operation of Additive Manufacturing (AM) technology relies on build volumes being packed effectively. Packing algorithms have been developed in response to this requirement. The configuration of AM build volumes is particularly challenging due to the multitude of irregular geometries encountered and the potential benefits of nesting parts. Currently proposed approaches to address this packing problem are routinely evaluated on data sets featuring shapes that are not representative of targeted manufacturing products. This study provides a useful classification of AM build volume packing problems and an overview of existing benchmarks for the analysis of such problems. Additionally, this paper discusses characteristics of future, more realistic, benchmarks with the intention of promoting research toward effective and efficient AM build volume packing being integrated into AM production planning methodologies

Toward better build volume packing in additive manufacturing: classification of existing problems and benchmarks

In many cases, the efficient operation of Additive Manufacturing (AM) technology relies on build volumes being packed effectively. Packing algorithms have been developed in response to this requirement. The configuration of AM build volumes is particularly challenging due to the multitude of irregular geometries encountered and the potential benefits of nesting parts. Currently proposed approaches to address this packing problem are routinely evaluated on data sets featuring shapes that are not representative of targeted manufacturing products. This study provides a useful classification of AM build volume packing problems and an overview of existing benchmarks for the analysis of such problems. Additionally, this paper discusses characteristics of future, more realistic, benchmarks with the intention of promoting research toward effective and efficient AM build volume packing being integrated into AM production planning methodologies

Accelerated Synthesis of Nanolayered MWW Zeolite by Interzeolite Transformation

Hierarchical zeolites can offer substantial benefits over bulk zeolites in catalysis. A drawback towards practical implementation is their lengthy synthesis, often requiring complex organic templates. This work describes an accelerated synthesis of nanolayered MWW zeolite based on the combination of interzeolite transformation (IZT) with a dual-templating strategy. FAU zeolite, hexamethyleneimine (HMI), and cetyltrimethylammonium bromide (CTAB) were respectively employed as Al source and primary zeolite, structure directing agent, and exfoliating agent. This approach allowed to reduce the synthesis of nanolayered MWW to 48 h, which is a considerable advance over the state of the art. Tracking structural, textural, morphological, and chemical properties during crystallization showed that 4-membered-ring (4MR) units derived from the FAU precursor are involved in the faster formation of MWW in comparison to a synthesis procedure from amorphous precursor. CTAB restricts the growth of the zeolite in the c-direction, resulting in nanolayered MWW. Moreover, we show that this approach can speed up the synthesis of nanolayered FER. The merits of nanolayered MWW zeolites are demonstrated in terms of improved catalytic performance in the Diels-Alder cycloaddition of 2,5-dimethylfuran and ethylene to p-xylene compared to bulk reference MWW sample.</p

4D Flow Patterns and Relative Pressure Distribution in a Left Ventricle Model by Shake-the-Box and Proper Orthogonal Decomposition Analysis

Purpose: Intraventricular blood flow dynamics are associated with cardiac function. Accurate, noninvasive, and easy assessments of hemodynamic quantities (such as velocity, vortex, and pressure) could be an important addition to the clinical diagnosis and treatment of heart diseases. However, the complex time-varying flow brings many challenges to the existing noninvasive image-based hemodynamic assessments. The development of reliable techniques and analysis tools is essential for the application of hemodynamic biomarkers in clinical practice. Methods: In this study, a time-resolved particle tracking method, Shake-the-Box, was applied to reconstruct the flow in a realistic left ventricle (LV) silicone model with biological valves. Based on the obtained velocity, 4D pressure field was calculated using a Poisson equation-based pressure solver. Furthermore, flow analysis by proper orthogonal decomposition (POD) of the 4D velocity field has been performed. Results: As a result of the Shake-the-Box algorithm, we have extracted: (i) particle positions, (ii) particle tracks, and finally, (iii) 4D velocity fields. From the latter, the temporal evolution of the 3D pressure field during the full cardiac cycle was obtained. The obtained maximal pressure difference extracted along the base-to-apex was about 2.7 mmHg, which is in good agreement with those reported in vivo. The POD analysis results showed a clear picture of different scale of vortices in the pulsatile LV flow, together with their time-varying information and corresponding kinetic energy content. To reconstruct 95% of the kinetic energy of the LV flow, only the first six POD modes would be required, leading to significant data reduction. Conclusions: This work demonstrated Shake-the-Box is a promising technique to accurately reconstruct the left ventricle flow field in vitro. The good spatial and temporal resolutions of the velocity measurements enabled a 4D reconstruction of the pressure field in the left ventricle. The application of POD analysis showed its potential in reducing the complexity of the high-resolution left ventricle flow measurements. For future work, image analysis, multi-modality flow assessments, and the development of new flow-derived biomarkers can benefit from fast and data-reducing POD analysis.</p

Weather, disease, and wheat breeding effects on Kansas wheat varietal yields, 1985 to 2011.

Wheat (Triticum aestivum L.) yields in Kansas have increased due to wheat breeding and improved agronomic practices, but are subject to climate and disease challenges. The objective of this research is to quantify the impact of weather, disease, and genetic improvement on wheat yields of varieties grown in 11 locations in Kansas from 1985 to 2011. Wheat variety yield data from Kansas performance tests were matched with comprehensive location-specific disease and weather data, including seasonal precipitation, monthly air temperature, air temperature and solar radiation around anthesis, and vapor pressure deficit (VPD). The results show that wheat breeding programs increased yield by 34 kg ha⁻¹ yr⁻¹. From 1985 through 2011, wheat breeding increased average wheat yields by 917 kg ha⁻¹, or 27% of total yield. Weather was found to have a large impact on wheat yields. Simulations demonstrated that a 1°C increase in projected mean temperature was associated with a decrease in wheat yields of 715 kg ha⁻¹, or 21%. Weather, diseases, and genetics all had significant impacts on wheat yields in 11 locations in Kansas during 1985 to 2011

An Inflationary Scenario in Intersecting Brane Models

We propose a new scenario for D-term inflation which appears quite straightforwardly in the open string sector of intersecting brane models. We take the inflaton to be a chiral field in a bifundamental representation of the hidden sector and we argue that a sufficiently flat potential can be brane engineered. This type of model generically predicts a near gaussian red spectrum with negligible tensor modes. We note that this model can very naturally generate a baryon asymmetry at the end of inflation via the recently proposed hidden sector baryogenesis mechanism. We also discuss the possibility that Majorana masses for the neutrinos can be simultaneously generated by the tachyon condensation which ends inflation. Our proposed scenario is viable for both high and low scale supersymmetry breaking.Comment: 30 pages, 2 figures; v2 references and comments adde

Multisite Comparison of MRI Defacing Software Across Multiple Cohorts

With improvements to both scan quality and facial recognition software, there is an increased risk of participants being identified by a 3D render of their structural neuroimaging scans, even when all other personal information has been removed. To prevent this, facial features should be removed before data are shared or openly released, but while there are several publicly available software algorithms to do this, there has been no comprehensive review of their accuracy within the general population. To address this, we tested multiple algorithms on 300 scans from three neuroscience research projects, funded in part by the Ontario Brain Institute, to cover a wide range of ages (3–85 years) and multiple patient cohorts. While skull stripping is more thorough at removing identifiable features, we focused mainly on defacing software, as skull stripping also removes potentially useful information, which may be required for future analyses. We tested six publicly available algorithms (afni_refacer, deepdefacer, mri_deface, mridefacer, pydeface, quickshear), with one skull stripper (FreeSurfer) included for comparison. Accuracy was measured through a pass/fail system with two criteria; one, that all facial features had been removed and two, that no brain tissue was removed in the process. A subset of defaced scans were also run through several preprocessing pipelines to ensure that none of the algorithms would alter the resulting outputs. We found that the success rates varied strongly between defacers, with afni_refacer (89%) and pydeface (83%) having the highest rates, overall. In both cases, the primary source of failure came from a single dataset that the defacer appeared to struggle with - the youngest cohort (3–20 years) for afni_refacer and the oldest (44–85 years) for pydeface, demonstrating that defacer performance not only depends on the data provided, but that this effect varies between algorithms. While there were some very minor differences between the preprocessing results for defaced and original scans, none of these were significant and were within the range of variation between using different NIfTI converters, or using raw DICOM files

In utero exposure to benzo[a]pyrene increases mutation burden in the soma and sperm of adult mice

Background: Mosaicism, the presence of genetically distinct cell populations within an organism, has emerged as an important contributor to disease. Mutational events occurring during embryonic development can cause mosaicism in any tissue, but the influence of environmental factors on levels of mosaicism is unclear. Objectives: We investigated whether in utero exposure to the widespread environmental mutagen benzo[a]pyrene (BaP) has an impact on the burden and distribution of mutations in adult mice. Methods: We used the Muta™Mouse transgenic rodent model to quantify and characterize mutations in the offspring of pregnant mice exposed to BaP during postconception days 7 through 16, covering the major period of organogenesis in mice. Next-generation DNA sequencing was then used to determine the spectrum of mutations induced in adult mice that were exposed to BaP during fetal development. Results: Mutation frequency was significantly increased in the bone marrow, liver, brain, and sperm of first filial generation (F1) males. Developing embryos accumulated more mutations and exhibited higher proportions of mosaicism than exposed adults, particularly in the brain. Decreased sperm count and motility revealed additional negative impacts on the reproductive function of F1 males. Conclusion: In utero exposure to environmental mutagens contributes to somatic and germline mosaicism, permanently affecting both the genetic health of the F1 and the population gene pool. Citation: Meier MJ, O’Brien JM, Beal MA, Allan B, Yauk CL, Marchetti F. 2017. In utero exposure to benzo[a]pyrene increases mutation burden in the soma and sperm of adult mice

Kinetic Monte Carlo Simulation of Strained Heteroepitaxial Growth with Intermixing

An efficient method for the simulation of strained heteroepitaxial growth with intermixing using kinetic Monte Carlo is presented. The model used is based on a solid-on-solid bond counting formulation in which elastic effects are incorporated using a ball and spring model. While idealized, this model nevertheless captures many aspects of heteroepitaxial growth, including nucleation, surface diffusion, and long range effects due elastic interaction. The algorithm combines a fast evaluation of the elastic displacement field with an efficient implementation of a rejection-reduced kinetic Monte Carlo based on using upper bounds for the rates. The former is achieved by using a multigrid method for global updates of the displacement field and an expanding box method for local updates. The simulations show the importance of intermixing on the growth of a strained film. Further the method is used to simulate the growth of self-assembled stacked quantum dots