Over the past several years there has been considerable interest in computer search/match programs for qualitative analysis of powder diffraction patterns. This interest has been stimulated by the availability of modern minicomputers supported by relatively inexpensive mass storage devices capable of containing the entire JCPDS (l) data base on line. As the traditional search/match algorithms have been reviewed for possible implementation on the slower speed and restricted memory minicomputers being supplied with today's automated diffractometers, new ideas have emerged for such algorithms. One very extensive set of new algorithms has been developed by our group and these are contained in the SANDMAN search/match/identify program which was described at this conference last year (2). Experience has shown those algorithms to be extremely effective, particularly in handling eases where the presence of systematic errors in the data has precluded the correct analysis by other computerised search/match systems.

Last year at this conference we submitted a preliminary report on an X-ray powder diffraction round robin sponsored by the JCPDS-ICDD. This round robin was designed primarily to study the intensities of diffraction lines found by users in routine work. At that time only a portion of the data had been analyzed, and we reported initial findings on the α-Al2O3, and Zn0 /CaCO3 samples. These included studies on counting statistics, resolution, and the effect of software on intensity precision. Since that time, all the data from the round robin has been entered into Lotus 1-2-3 (*) spread-sheets and numerous additional tests have been carried out. This paper discusses some of the more interesting findings. A complete paper on all of the tests performed is in preparation for submission to the "Methods and Practices Manual" published by the JCPDS-ICDD.

Quantitative phase analysis by powder diffractometry requires accurate measurement of the integrated intensities of the diffracted, lines. When lines are isolated and on simple backgrounds, count integration techniques work very well. However, when one or more lines overlap the line of interest, or a complex background is present, profile fitting techniques are required in order to eliminate interferences.

Profile fitting involves choosing a mathematical model to represent the expected profile shapes. Experience has shown that the profile shapes obtained with a parafocusing powder diffractometer are not easily described and many models have been tried with varying degrees of success. Generally the more free parameters allowed In the model the ‘setter the fits, although, aesthetically one would like to keep the number of free parameters to a minimum.

The JCFDS-ICDD based in Swarthmore, PA maintains and distributes a database of powder diffraction data. This database is widely used throughout the world by x-ray analytical laboratories for crystalline phase identification. It is the charter of that organization to update, expand and upgrade the quality of data in the database. As this work is carried out, the database is made available on an annual basis at a fee Commensurate with the committee's operation as a self-sustaining, non-profit organization.

For many years the International Centre for Diffraction Data has sponsored round robins covering various aspects of X-ray powder Diffraction with the objective of illuminating and understanding current practices and problems associated with, the analysis of diffraction data. As computer analysis of diffraction data becomes ever more sophisticated, analytic capabilities are extended and the performance, not only of the instrumentation must be checked, but also that of the software which converts the measured data into useful results. In recent years, therefore, we have personally participated in a cell parameter round-robin, a d-spacing round-robin, a peak hunting round-robin, and, most recently, the present intensity round-robin and a line profile round-robin. Still others are in progress or being planned.

One of the areas of X-ray powder diffraction receiving considerable attention in recent years is quantitative analysis. This analysis depends on an accurate measurement of integrated diffraction line intensities. In order to study the accuracy of these measurements we have calculated integrated intensities from single crystal data for single substance powders and compared them to experimental data obtained in our laboratory.

Off-target movement of dicamba and 2,4-D may injure and reduce the yield of many fruit and vegetable crops, impacting specialty crop producers and herbicide applicators alike. Two field experiments were established, using plant growth regulator–resistant soybean herbicide technologies, to evaluate drift and carryover risks to horseradish production. The drift experiment was conducted in 2015 and 2016 to evaluate impact of dicamba and 2,4-D simulated drift on horseradish production with a mid-POST application in soybean. Simulated drift rates were 1/10,000X, 1/1,000X, and 1/100X, with 1/2X, 1X, and 2X of standard application rates. Injury and yield loss was greater following application of 2,4-D than with dicamba. Yield reductions were observed beginning at the 1/1,000X rate of 2,4-D, with complete crop loss occurring when rates exceed 1/2X. In comparison, dicamba only reduced yields when applied at the 1X and 2X rates. Only horseradish roots from plants treated with dicamba at the 2X rate had greater dicamba residue than the nontreated control, and the amount detected, 0.32 parts per billion (ppb), was lower than the EPA tolerance of 100 ppb in root crops. There was little to no harvestable tissue for 2,4-D residue analysis for plants treated with 2,4-D at rates above 1/2X. The carryover experiment was a 2-yr rotational evaluation conducted in 2014, 2015, and 2016 to assess dicamba carryover to horseradish following application to dicamba-resistant soybean the previous season. Observations taken at 4, 6, and 8 wk after planting indicated no significant horseradish injury, nor was height, stand, or root weight reduced. These results suggest that horseradish growers should have few concerns about injury from dicamba drift or carryover. While 2,4-D applicators may need to be cautious when making applications near horseradish fields, 2,4-D may be an effective tool for controlling volunteer horseradish in 2,4-D–resistant soybean.

OBJECTIVES/SPECIFIC AIMS: We sought to investigate the role of the host microbiome during severe, acute respiratory infection (ARI) to understand the drivers of both acute clinical pathogenesis. METHODS/STUDY POPULATION: Nasopharyngeal swabs comprised of mixed cell populations at the active site of infection were collected from 192 hospitalized pediatric patients with ARI. We combined comprehensive respiratory virus detection and virus genome sequencing with 16S rRNA gene sequencing to evaluate the microbial content of the airway during ARI. This data was coupled with 11 clinical parameters, which were compiled to create a clinical severity score. The microbiome profiles were assessed to determine if clinical severity of infection, and/or specific virus was associated with increased clinical severity. RESULTS/ANTICIPATED RESULTS: We identified 8 major microbiome profiles classified by dominant bacterial genus, Moraxella, Corynebacterium, Staphylococcus, Haemophilus, Streptococcus, Alloiococcus, Schlegelella, and Diverse. Increased clinical severity was significantly associated with microbiome profiles dominated by Haemophilus, Streptococcus, and Schlegelella, whereas Corynebacterium and Alloiococcus were more prevalent in children with less severe disease. Independent of the microbial community, more than 60% of patients with the highest clinical severity were infected with either respiratory syncytial virus or rhinovirus. DISCUSSION/SIGNIFICANCE OF IMPACT: Our results indicate that individually and in combination, both virus and microbial composition may drive clinical severity during acute respiratory viral infections. It is still unclear how the complex interplay between virus, bacterial community, and the host response influence long-term respiratory impacts, such as the development of asthma. Nonetheless, during ARIs therapeutic interventions such as antibiotics and probiotics may be warranted in a subset of patients that are identified to have both a virus and microbiome profile that is associated with increased pathogenesis to limit both acute and long-term phenotypes.

An internationally approved and globally used classification scheme for the diagnosis of CHD has long been sought. The International Paediatric and Congenital Cardiac Code (IPCCC), which was produced and has been maintained by the International Society for Nomenclature of Paediatric and Congenital Heart Disease (the International Nomenclature Society), is used widely, but has spawned many “short list” versions that differ in content depending on the user. Thus, efforts to have a uniform identification of patients with CHD using a single up-to-date and coordinated nomenclature system continue to be thwarted, even if a common nomenclature has been used as a basis for composing various “short lists”. In an attempt to solve this problem, the International Nomenclature Society has linked its efforts with those of the World Health Organization to obtain a globally accepted nomenclature tree for CHD within the 11th iteration of the International Classification of Diseases (ICD-11). The International Nomenclature Society has submitted a hierarchical nomenclature tree for CHD to the World Health Organization that is expected to serve increasingly as the “short list” for all communities interested in coding for congenital cardiology. This article reviews the history of the International Classification of Diseases and of the IPCCC, and outlines the process used in developing the ICD-11 congenital cardiac disease diagnostic list and the definitions for each term on the list. An overview of the content of the congenital heart anomaly section of the Foundation Component of ICD-11, published herein in its entirety, is also included. Future plans for the International Nomenclature Society include linking again with the World Health Organization to tackle procedural nomenclature as it relates to cardiac malformations. By doing so, the Society will continue its role in standardising nomenclature for CHD across the globe, thereby promoting research and better outcomes for fetuses, children, and adults with congenital heart anomalies.

With rapid and accelerated Arctic sea-ice loss, it is beneficial to update and baseline historical change on the regional scales from a consistent, intercalibrated, long-term time series of sea-ice data for understanding regional vulnerability and monitoring ice state for climate adaptation and risk mitigation. In this paper, monthly sea-ice extents (SIEs) derived from a passive microwave sea-ice concentration climate data record for the period of 1979–2015, are used to examine Arctic-wide and regional temporal variability of sea-ice cover and their decadal trends for 15 regions of the Arctic. Three unique types of SIE annual cycles are described. Regions of vulnerability within each of three types to further warming are identified. For the Arctic as a whole, the analysis has found significant changes in both annual SIE maximum and minimum, with −2.41 ± 0.56% per decade and −13.5 ± 2.93% per decade change relative to the 1979–2015 climate average, respectively. On the regional scale, the calculated trends for the annual SIE maximum range from +2.48 to −10.8% decade−1, while the trends for the annual SIE minimum range from 0 to up to −42% decade−1.

Observed and modeled sea-ice motions, combined via an optimal-interpolation assimilation method, are used to study two synoptic events in the Arctic. The first is a convergence event along the north Alaska coast in the Beaufort Sea during November 1992. Assimilation indicates stronger convergence than the stand-alone model, in agreement with Advanced Very High Resolution Radiometer-derived ice motions and Special Sensor Microwave/Imager-derived ice concentrations. The second event pertains to ice formation and advection in Fram Strait and the Barents and Greenland, Iceland and Norwegian Seas. Assimilation indicates export of thick, less saline ice out of the central Arctic into the East Greenland Sea. However, the model indicates little flow through Fram Strait, instead showing strong flow of thin, more saline first-year ice from the Barents Sea westward into the Greenland Sea. These results indicate that assimilation is a useful tool for investigating synoptic events in the Arctic and may be useful for both climate studies and operational analyses

Passive microwave sea-ice concentration fields provide some of the longest-running and most consistent records of changes in sea ice. Scatterometry-based sea-ice fields are more recently developed data products, but now they provide a record of ice conditions spanning several years. Resolution enhancement techniques applied to scatterometer fields provide much higher effective resolutions (~10 km) than are available from standard scatterometer and passive microwave fields (25–50 km). Here we examine ice-extent fields from both sources and find that there is general agreement between scatterometer data and passive microwave fields, though scatterometer estimates yield substantially lower ice extents during winter. Comparisons with ice-edge locations estimated from AVHRR imagery indicate that enhanced scatterometer data can sometimes provide an improved edge location, but there is substantial variation in the results, depending on the local conditions. A blended product, using both scatterometer and passive microwave data, could yield improved results.

The United States National Ice Center (NIC) provides weekly ice analyses of the Arctic and Antarctic using information from ice reconnaissance, ship reports and high-resolution satellite imagery. In cloud-covered areas and regions lacking imagery, the higher-resolution sources are augmented by ice concentrations derived from Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) passive-microwave imagery. However, the SSM/I-derived ice concentrations are limited by low resolution and uncertainties in thin-ice regions. Ongoing research at NIC is attempting to improve the utility of these SSM/I products for operational sea-ice analyses. The refinements of operational algorithms may also aid future scientific studies. Here we discuss an evaluation of the standard operational ice-concentration algorithm, Cal/Val, with a possible alternative, a modified NASA Team algorithm. The modified algorithm compares favorably with Cal/Val and is a substantial improvement over the standard NASA Team algorithm in thin-ice regions that are of particular interest to operational activities.

Data assimilation techniques are one method by which to improve the quality of model Simulations of Sea ice. The availability of daily gridded fields of Sea-ice motion makes this field one that can be readily assimilated. These fields are generally of higher resolution than forcing values Such as atmospheric wind which are used to drive the model, and on any given day may depict ice circulation that is dramatically different than what the model Solution represents. Typically, a blending method Such as optimal interpolation (OI) is used and corrections are applied to the initial modeled velocity field Such that the new Solution corresponds better with actual observations. However, care must be taken in Such a technique, as the corrections are not applied directly to the model physics, and the underlying physical assumptions in the ice dynamics may be violated. Previous Studies have Shown that improvements in the ice-motion Solution come at the cost of the quality of other modeled fields. The Strength parameterization in Sea-ice models controls the ice velocity in the model, and is obtained in part by comparison with observed motions. Here we investigate the Sensitivity of the Sea-ice model to variations in the Strength parameterization, and determine the effect of using data assimilation to impose observed velocities. We find that the alternation of the frictional loss parameter has limited effect on model performance. Rather, it is the assimilated data that overwhelm and degrade the Solution, bringing into question whether underlying physical assumptions in the model may be compromised.