A Study of Production and Marketing of Butterfat and Butter in South Dakota

Even a most superficial study of the South Dakota dairy industry indicated its economic importance to the state. Dairying, though not of major importance, utilizes a relatively huge physical production plant, spread out on most every farm. It includes processing and marketing facilities, of which the creamery and cream station are most important. In 1935, dairying constituted one of the state\u27s more stable industries, providing about 15.7 percent of the gross income of South Dakota farmers. It ranked second to wheat, which accounted for 18.7 percent of the total gross income. All cattle and calves, hogs, and cora are ranked below milk, accounting for 15.5, 11.4, and 10.2 percent of the total gross income, respectively

Approaches to Automated Morphological Classification of Galaxies

There is an obvious need for automated classification of galaxies, as the number of observed galaxies increases very fast. We examine several approaches to this problem, utilising {\em Artificial Neural Networks} (ANNs). We quote results from a recent study which show that ANNs can classsify galaxies morphologically as well as humans can.Comment: 8 pages, uu-encoded compressed postscript file (containing 2 figures

Potential effects of petroleum pollution and increasing water temperature on life-history traits in polar cod (Boreogadus saida)

Conference poste

Comparison of structure- and ligand-based scoring functions for deep generative models: a GPCR case study.

Deep generative models have shown the ability to devise both valid and novel chemistry, which could significantly accelerate the identification of bioactive compounds. Many current models, however, use molecular descriptors or ligand-based predictive methods to guide molecule generation towards a desirable property space. This restricts their application to relatively data-rich targets, neglecting those where little data is available to sufficiently train a predictor. Moreover, ligand-based approaches often bias molecule generation towards previously established chemical space, thereby limiting their ability to identify truly novel chemotypes. In this work, we assess the ability of using molecular docking via Glide-a structure-based approach-as a scoring function to guide the deep generative model REINVENT and compare model performance and behaviour to a ligand-based scoring function. Additionally, we modify the previously published MOSES benchmarking dataset to remove any induced bias towards non-protonatable groups. We also propose a new metric to measure dataset diversity, which is less confounded by the distribution of heavy atom count than the commonly used internal diversity metric. With respect to the main findings, we found that when optimizing the docking score against DRD2, the model improves predicted ligand affinity beyond that of known DRD2 active molecules. In addition, generated molecules occupy complementary chemical and physicochemical space compared to the ligand-based approach, and novel physicochemical space compared to known DRD2 active molecules. Furthermore, the structure-based approach learns to generate molecules that satisfy crucial residue interactions, which is information only available when taking protein structure into account. Overall, this work demonstrates the advantage of using molecular docking to guide de novo molecule generation over ligand-based predictors with respect to predicted affinity, novelty, and the ability to identify key interactions between ligand and protein target. Practically, this approach has applications in early hit generation campaigns to enrich a virtual library towards a particular target, and also in novelty-focused projects, where de novo molecule generation either has no prior ligand knowledge available or should not be biased by it

Comparison of structure- and ligand-based scoring functions for deep generative models: a GPCR case study.

Deep generative models have shown the ability to devise both valid and novel chemistry, which could significantly accelerate the identification of bioactive compounds. Many current models, however, use molecular descriptors or ligand-based predictive methods to guide molecule generation towards a desirable property space. This restricts their application to relatively data-rich targets, neglecting those where little data is available to sufficiently train a predictor. Moreover, ligand-based approaches often bias molecule generation towards previously established chemical space, thereby limiting their ability to identify truly novel chemotypes. In this work, we assess the ability of using molecular docking via Glide-a structure-based approach-as a scoring function to guide the deep generative model REINVENT and compare model performance and behaviour to a ligand-based scoring function. Additionally, we modify the previously published MOSES benchmarking dataset to remove any induced bias towards non-protonatable groups. We also propose a new metric to measure dataset diversity, which is less confounded by the distribution of heavy atom count than the commonly used internal diversity metric. With respect to the main findings, we found that when optimizing the docking score against DRD2, the model improves predicted ligand affinity beyond that of known DRD2 active molecules. In addition, generated molecules occupy complementary chemical and physicochemical space compared to the ligand-based approach, and novel physicochemical space compared to known DRD2 active molecules. Furthermore, the structure-based approach learns to generate molecules that satisfy crucial residue interactions, which is information only available when taking protein structure into account. Overall, this work demonstrates the advantage of using molecular docking to guide de novo molecule generation over ligand-based predictors with respect to predicted affinity, novelty, and the ability to identify key interactions between ligand and protein target. Practically, this approach has applications in early hit generation campaigns to enrich a virtual library towards a particular target, and also in novelty-focused projects, where de novo molecule generation either has no prior ligand knowledge available or should not be biased by it

Are We There Yet?: The Development of a Corpus Annotated for Social Acts in Multilingual Online Discourse

We present the AAWD and AACD corpora, a collection of discussions drawn from Wikipedia talk pages and small group IRC discussions in English, Russian and Mandarin. Our datasets are annotated with labels capturing two kinds of social acts: alignment moves and authority claims. We describe these social acts, describe our annotation process, highlight challenges we encountered and strategies we employed during annotation, and present some analyses of resulting data set which illustrate the utility of our corpus and identify interactions among social acts and between participant status and social acts and in online discourse

No observed developmental effects in early life stages of capelin (Mallotus villosus) exposed to a water-soluble fraction of crude oil during embryonic development

The rise in offshore oil and gas operations, maritime shipping, and tourism in northern latitudes enhances the risk of oil spills to sub-Arctic and Arctic coastal environments. Therefore, there is a need to understand the potential adverse effects of petroleum on key species in these areas. Here, we investigated the effects of oil exposure on the early life stages of capelin (Mallotus villosus), an ecologically and commercially important Barents Sea forage fish species that spawns along the coast of Northern Norway. Capelin embryos were exposed to five different concentrations (corresponding to 0.5–19 µg/L total PAHs) of water-soluble fraction (WSF) of crude oil from 6 days post fertilization (dpf) until hatch (25 dpf), and development of larvae in clean seawater was monitored until 52 dpf. None of the investigated endpoints (embryo development, larval length, heart rate, arrhythmia, and larval mortality) showed any effects. Our results suggest that the early life stages of capelin may be more robust to crude oil exposure than similar life stages of other fish species

Effects of acute exposure to dispersed oil and burned oil residue on long-term survival, growth, and reproductive development in polar cod (Boreogadus saida)

Accepted manuscript version, licensed CC BY-NC-ND 4.0. Published version available at https://doi.org/10.1016/j.marenvres.2018.09.005.The present study investigates the potential long-term physiological effects on maturing polar cod (Boreogadus saida), an Arctic key species, after an acute exposure (48 h) to environmentally realistic concentrations of either mechanically dispersed oil (MDO), chemically dispersed oil (CDO) or burned oil residues (BO) (N = 58–60 per treatment). Following exposure, fish were monitored in a common tank supplied with clean water for a seven-month period coinciding with the period of reproductive development. Females exposed to BO residues were more frequently found in an earlier phase of gonadal maturation compared to unexposed females while no effects of different oil spill response (OSR) actions were seen in the reproductive development of males. Mechanically and chemically dispersed oil induced a transient short-term reduction in growth in the first week post-exposure. Overall, no significant long-term effects of exposure were seen in growth or mortality. Ultimately, this study provides information for the assessment of population consequences of different OSR actions as part of a net environmental benefit analysis

Structure-based design of allosteric calpain-1 inhibitors populating a novel bioactivity space.

Dimeric calpains constitute a promising therapeutic target for many diseases such as cardiovascular, neurodegenerative and ischaemic disease. The discovery of selective calpain inhibitors, however, has been extremely challenging. Previously, allosteric inhibitors of calpains, such as PD150606, which included a specific α-mercaptoacrylic acid sub-structure, were reported to bind to the penta-EF hand calcium binding domain, PEF(S) of calpain. Although these are selective to calpains over other cysteine proteases, their mode of action has remained elusive due to their ability to inhibit the active site domain with and without the presence of PEF(S), with similar potency. These findings have led to the question of whether the inhibitory response can be attributed to an allosteric mode of action or alternatively to inhibition at the active site. In order to address this problem, we report a structure-based virtual screening protocol as a novel approach for the discovery of PEF(S) binders that populate a novel chemical space. We have identified compound 1, Vidupiprant, which is shown to bind to the PEF(S) domain by the TNS displacement method, and it exhibited specificity in its allosteric mode of inhibition. Compound 1 inhibited the full-length calpain-1 complex with a higher potency (IC50 = 7.5 μM) than the selective, cell-permeable non-peptide calpain inhibitor, PD150606 (IC50 = 19.3 μM), where the latter also inhibited the active site domain in the absence of PEF(S) (IC50 = 17.8 μM). Hence the method presented here has identified known compounds with a novel allosteric mechanism for the inhibition of calpain-1. We show for the first time that the inhibition of enzyme activity can be attributed to an allosteric mode of action, which may offer improved selectivity and a reduced side-effects profile

A Revised Parallel-Sequence Morphological Classification of Galaxies: Structure and Formation of S0 and Spheroidal Galaxies

We update van den Bergh's parallel sequence galaxy classification in which S0 galaxies form a sequence S0a-S0b-S0c that parallels the sequence Sa-Sb-Sc of spiral galaxies. The ratio B/T of bulge to total light defines the position of a galaxy in each sequence. Our classification makes one improvement. We extend the S0a-S0b-S0c sequence to spheroidal ("Sph'") galaxies that are positioned in parallel to irregular galaxies in a similarly extended Sa-Sb-Sc-Im sequence. This provides a natural "home" for spheroidals, which previously were omitted from galaxy classifications. To motivate our juxtaposition of Sph and irregular galaxies, we present photometry and bulge-disk decompositions of Virgo S0s, including late-type S0s that bridge the gap between S0b and Sph galaxies. NGC 4762 is a SB0bc with B/T = 0.13. NGC 4452 is a SB0c galaxy with an even tinier pseudobulge. VCC 2048 and NGC 4638 have properties of both S0cs and Sphs. We update the structural parameter correlations Sphs, irregulars, bulges, and disks. We show that spheroidals of increasing luminosity form a continuous sequence with the disks (but not bulges) of S0c-S0b-S0a galaxies. Remarkably, the Sph--S0-disk sequence is almost identical to that of irregular galaxies and spiral galaxy disks. We review published observations for galaxy transformation processes, particularly ram-pressure stripping of cold gas. We suggest that Sph galaxies are transformed, "red and dead" Scd--Im galaxies in the same way that many S0 galaxies are transformed, red and dead Sa-Sc spiral galaxiesComment: 43 pages, 40 postscript figures, 1 table; TeX, requires eplain.tex; accepted for publication in ApJS; for a version with full-resolution figures, see http://chandra.as.utexas.edu/~kormendy/parallel.pd