J-2X Test Articles Using FDM Process

This viewgraph presentation gives a brief history of the J-2X engine, along with detailed description of the material demonstrator and test articles that were created using Fused Deposition Modeling (FDM) process

DNA barcoding identifies cryptic animal tool materials

Funding: Biotechnology and Biological Sciences Research Council (BBSRC) (Grants BB/G023913/1 and BB/G023913/2 to C.R., and studentship to B.C.K.), the School of Biology at the University of St Andrews (studentships to M.P.S. and B.C.K.), and the Leverhulme Trust (Grant RPG-2015-273 to P.M.H.).Some animals fashion tools or constructions out of plant materials to aid foraging, reproduction, self-maintenance, or protection. Their choice of raw materials can affect the structure and properties of the resulting artifacts, with considerable fitness consequences. Documenting animals’ material preferences is challenging, however, as manufacture behavior is often difficult to observe directly, and materials may be processed so heavily that they lack identifying features. Here, we use DNA barcoding to identify, from just a few recovered tool specimens, the plant species New Caledonian crows (Corvus moneduloides) use for crafting elaborate hooked stick tools in one of our long-term study populations. The method succeeded where extensive fieldwork using an array of conventional approaches—including targeted observations, camera traps, radio-tracking, bird-mounted video cameras, and behavioral experiments with wild and temporarily captive subjects—had failed. We believe that DNA barcoding will prove useful for investigating many other tool and construction behaviors, helping to unlock significant research potential across a wide range of study systems.Publisher PDFPeer reviewe

A Scenario Based Methodology for the Selection of Non-Lethal Weapons

A paper submitted to Non-Lethal Defense III, Johns Hopkins Applied Physics Laboratory, Laurel, Maryland, by the Naval Postgraduate School's Non-Lethal Weapons System Engineering Study Team, February 1998.The allocation of finite resources to develop non-lethal weapons for deployment as effective military assets is a difficult task considering that there exists a myriad of potentially promising technologies. Each proposed weapon has operational, logistical, and developmental advantages and disadvantages,which often do not appear self-consistent. Attempts to invent a common figure-of-merit often fail because it is difficult to avoid subjective criteria and evaluation. Ideally, an objective, consistent weapons selection methodology is required. We have developed a scenario based requirements methodology that allows us to highlight inter-scenario commonalties among the weapons considered. We have evaluated some thirty different anti-personnel and anti-material weapons considering over a dozen scenario based requirements including such criteria as effective range, weather susceptibility, cost, logistics and training

JIT-Based cost analysis for dynamic program transformations

Tracing JIT compilation generates units of compilation that are easy to analyse and are known to execute frequently. The AJITPar project investigates whether the information in JIT traces can be used to dynamically transform programs for a specific parallel architecture. Hence a lightweight cost model is required for JIT traces. This paper presents the design and implementation of a system for extracting JIT trace information from the Pycket JIT compiler. We define three increasingly parametric cost models for Pycket traces. We determine the best weights for the cost model parameters using linear regression. We evaluate the effectiveness of the cost models for predicting the relative costs of transformed programs

Global application of an unoccupied aerial vehicle photogrammetry protocol for predicting aboveground biomass in non‐forest ecosystems

P. 1-15Non-forest ecosystems, dominated by shrubs, grasses and herbaceous plants, provide ecosystem services including carbon sequestration and forage for grazing, and are highly sensitive to climatic changes. Yet these ecosystems are poorly represented in remotely sensed biomass products and are undersampled by in situ monitoring. Current global change threats emphasize the need for new tools to capture biomass change in non-forest ecosystems at appropriate scales. Here we developed and deployed a new protocol for photogrammetric height using unoccupied aerial vehicle (UAV) images to test its capability for delivering standardized measurements of biomass across a globally distributed field experiment. We assessed whether canopy height inferred from UAV photogrammetry allows the prediction of aboveground biomass (AGB) across low-stature plant species by conducting 38 photogrammetric surveys over 741 harvested plots to sample 50 species. We found mean canopy height was strongly predictive of AGB across species, with a median adjusted R2 of 0.87 (ranging from 0.46 to 0.99) and median prediction error from leave-one-out cross-validation of 3.9%. Biomass per-unit-of-height was similar within but different among, plant functional types. We found that photogrammetric reconstructions of canopy height were sensitive to wind speed but not sun elevation during surveys. We demonstrated that our photogrammetric approach produced generalizable measurements across growth forms and environmental settings and yielded accuracies as good as those obtained from in situ approaches. We demonstrate that using a standardized approach for UAV photogrammetry can deliver accurate AGB estimates across a wide range of dynamic and heterogeneous ecosystems. Many academic and land management institutions have the technical capacity to deploy these approaches over extents of 1–10 ha−1. Photogrammetric approaches could provide much-needed information required to calibrate and validate the vegetation models and satellite-derived biomass products that are essential to understand vulnerable and understudied non-forested ecosystems around the globe.S

Minimizing Errors in RT-PCR Detection and Quantification of SARS-CoV-2 RNA for Wastewater Surveillance

Wastewater surveillance for pathogens using the reverse transcription-polymerase chain reaction (RT-PCR) is an effective, resource-efficient tool for gathering additional community-level public health information, including the incidence and/or prevalence and trends of coronavirus disease-19 (COVID-19). Surveillance of SARS-CoV-2 in wastewater may provide an early-warning signal of COVID-19 infections in a community. The capacity of the world’s environmental microbiology and virology laboratories for SARS-CoV-2 RNA characterization in wastewater is rapidly increasing. However, there are no standardized protocols nor harmonized quality assurance and quality control (QA/QC) procedures for SARS-CoV-2 wastewater surveillance. This paper is a technical review of factors that can lead to false-positive and -negative errors in the surveillance of SARS-CoV-2, culminating in recommendations and strategies that can be implemented to identify and mitigate these errors. Recommendations include, stringent QA/QC measures, representative sampling approaches, effective virus concentration and efficient RNA extraction, amplification inhibition assessment, inclusion of sample processing controls, and considerations for RT-PCR assay selection and data interpretation. Clear data interpretation guidelines (e.g., determination of positive and negative samples) are critical, particularly during a low incidence of SARS-CoV-2 in wastewater. Corrective and confirmatory actions must be in place for inconclusive and/or potentially significant results (e.g., initial onset or reemergence of COVID-19 in a community). It will also be prudent to perform inter-laboratory comparisons to ensure results are reliable and interpretable for ongoing and retrospective analyses. The strategies that are recommended in this review aim to improve SARS-CoV-2 characterization for wastewater surveillance applications. A silver lining of the COVID-19 pandemic is that the efficacy of wastewater surveillance was demonstrated during this global crisis. In the future, wastewater will play an important role in the surveillance of a range of other communicable diseases.Highlights: Harmonized QA/QC procedures for SARS-CoV-2 wastewater surveillance are lacking; Wastewater analysis protocols are not optimized for trace analysis of viruses; False-positive and -negative errors have consequences for public health responses; Inter-laboratory studies utilizing standardized reference materials and protocols are needed.info:eu-repo/semantics/publishedVersio

Advances in Molecular Quantum Chemistry Contained in the Q-Chem 4 Program Package

A summary of the technical advances that are incorporated in the fourth major release of the Q-Chem quantum chemistry program is provided, covering approximately the last seven years. These include developments in density functional theory methods and algorithms, nuclear magnetic resonance (NMR) property evaluation, coupled cluster and perturbation theories, methods for electronically excited and open-shell species, tools for treating extended environments, algorithms for walking on potential surfaces, analysis tools, energy and electron transfer modelling, parallel computing capabilities, and graphical user interfaces. In addition, a selection of example case studies that illustrate these capabilities is given. These include extensive benchmarks of the comparative accuracy of modern density functionals for bonded and non-bonded interactions, tests of attenuated second order Møller–Plesset (MP2) methods for intermolecular interactions, a variety of parallel performance benchmarks, and tests of the accuracy of implicit solvation models. Some specific chemical examples include calculations on the strongly correlated Cr2 dimer, exploring zeolite-catalysed ethane dehydrogenation, energy decomposition analysis of a charged ter-molecular complex arising from glycerol photoionisation, and natural transition orbitals for a Frenkel exciton state in a nine-unit model of a self-assembling nanotube

Software for the frontiers of quantum chemistry:An overview of developments in the Q-Chem 5 package

This article summarizes technical advances contained in the fifth major release of the Q-Chem quantum chemistry program package, covering developments since 2015. A comprehensive library of exchange–correlation functionals, along with a suite of correlated many-body methods, continues to be a hallmark of the Q-Chem software. The many-body methods include novel variants of both coupled-cluster and configuration-interaction approaches along with methods based on the algebraic diagrammatic construction and variational reduced density-matrix methods. Methods highlighted in Q-Chem 5 include a suite of tools for modeling core-level spectroscopy, methods for describing metastable resonances, methods for computing vibronic spectra, the nuclear–electronic orbital method, and several different energy decomposition analysis techniques. High-performance capabilities including multithreaded parallelism and support for calculations on graphics processing units are described. Q-Chem boasts a community of well over 100 active academic developers, and the continuing evolution of the software is supported by an “open teamware” model and an increasingly modular design

Report from the Annual Conference of the British Society of Echocardiography, November 2017, Edinburgh International Conference Centre, Edinburgh

No abstract available