The future of the small trader: Communist Party policy

https://stars.library.ucf.edu/prism/1627/thumbnail.jp

Lift Every Voice: Celebrating Black History Month

Enjoy an evening of performances from KSU percussion ensemble, Gospel Choir, Jazz I, Chamber Signers, and more! Join us (virtually) to celebrate Black History Month.https://digitalcommons.kennesaw.edu/musicprograms/2376/thumbnail.jp

Holiday Concert

Kennesaw State University School of Music presents: Holiday Concert.https://digitalcommons.kennesaw.edu/musicprograms/1575/thumbnail.jp

Learning to Decode the Surface Code with a Recurrent, Transformer-Based Neural Network

Quantum error-correction is a prerequisite for reliable quantum computation. Towards this goal, we present a recurrent, transformer-based neural network which learns to decode the surface code, the leading quantum error-correction code. Our decoder outperforms state-of-the-art algorithmic decoders on real-world data from Google's Sycamore quantum processor for distance 3 and 5 surface codes. On distances up to 11, the decoder maintains its advantage on simulated data with realistic noise including cross-talk, leakage, and analog readout signals, and sustains its accuracy far beyond the 25 cycles it was trained on. Our work illustrates the ability of machine learning to go beyond human-designed algorithms by learning from data directly, highlighting machine learning as a strong contender for decoding in quantum computers

Identification of CFTR variants in Latino patients with cystic fibrosis from the Dominican Republic and Puerto Rico

BackgroundIn cystic fibrosis (CF), the spectrum and frequency of CFTR variants differ by geography and race/ethnicity. CFTR variants in White patients are wellâ described compared with Latino patients. No studies of CFTR variants have been done in patients with CF in the Dominican Republic or Puerto Rico.MethodsCFTR was sequenced in 61 Dominican Republican patients and 21 Puerto Rican patients with CF and greater than â â â â 60â mmol/L sweat chloride. The spectrum of CFTR variants was identified and the proportion of patients with 0, 1, or 2 CFTR variants identified was determined. The functional effects of identified CFTR variants were investigated using clinical annotation databases and computational prediction tools.ResultsOur study found 10% of Dominican patients had two CFTR variants identified compared with 81% of Puerto Rican patients. No CFTR variants were identified in 69% of Dominican patients and 10% of Puerto Rican patients. In Dominican patients, there were 19 identified CFTR variants, accounting for 25 out of 122 disease alleles (20%). In Puerto Rican patients, there were 16 identified CFTR variants, accounting for 36 out of 42 disease alleles (86%) in Puerto Rican patients. Thirty CFTR variants were identified overall. The most frequent variants for Dominican patients were p.Phe508del and p.Ala559Thr and for Puerto Rican patients were p.Phe508del, p.Arg1066Cys, p.Arg334Trp, and p.I507del.ConclusionsIn this first description of the CFTR variants in patients with CF from the Dominican Republic and Puerto Rico, there was a low detection rate of two CFTR variants after full sequencing with the majority of patients from the Dominican Republic without identified variants.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153634/1/ppul24549.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153634/2/ppul24549_am.pd

FAIR Data Pipeline: provenance-driven data management for traceable scientific workflows

Modern epidemiological analyses to understand and combat the spread of disease depend critically on access to, and use of, data. Rapidly evolving data, such as data streams changing during a disease outbreak, are particularly challenging. Data management is further complicated by data being imprecisely identified when used. Public trust in policy decisions resulting from such analyses is easily damaged and is often low, with cynicism arising where claims of "following the science" are made without accompanying evidence. Tracing the provenance of such decisions back through open software to primary data would clarify this evidence, enhancing the transparency of the decision-making process. Here, we demonstrate a Findable, Accessible, Interoperable and Reusable (FAIR) data pipeline developed during the COVID-19 pandemic that allows easy annotation of data as they are consumed by analyses, while tracing the provenance of scientific outputs back through the analytical source code to data sources. Such a tool provides a mechanism for the public, and fellow scientists, to better assess the trust that should be placed in scientific evidence, while allowing scientists to support policy-makers in openly justifying their decisions. We believe that tools such as this should be promoted for use across all areas of policy-facing research

Early Loss of Xist RNA Expression and Inactive X Chromosome Associated Chromatin Modification in Developing Primordial Germ Cells

The inactive X chromosome characteristic of female somatic lineages is reactivated during development of the female germ cell lineage. In mouse, analysis of protein products of X-linked genes and/or transgenes located on the X chromosome has indicated that reactivation occurs after primordial germ cells reach the genital ridges.We present evidence that the epigenetic reprogramming of the inactive X-chromosome is initiated earlier than was previously thought, around the time that primordial germ cells (PGCs) migrate through the hindgut. Specifically, we find that Xist RNA expression, the primary signal for establishment of chromosome silencing, is extinguished in migrating PGCs. This is accompanied by displacement of Polycomb-group repressor proteins Eed and Suz(12), and loss of the inactive X associated histone modification, methylation of histone H3 lysine 27.We conclude that X reactivation in primordial germ cells occurs progressively, initiated by extinction of Xist RNA around the time that germ cells migrate through the hindgut to the genital ridges. The events that we observe are reminiscent of X reactivation of the paternal X chromosome in inner cell mass cells of mouse pre-implantation embryos and suggest a unified model in which execution of the pluripotency program represses Xist RNA thereby triggering progressive reversal of epigenetic silencing of the X chromosome

Crop Updates 2002 - Weeds

This session covers fifty eight papers from different authors: 1. INTRODUCTION Vanessa Stewart, DEPARTMENT OF AGRICULTURE INTEGRATED WEED MANAGEMENT IWM system studies / demonstration sites 2. Major outcomes from IWM demonstration sites, Alexandra Douglas Department of Agriculture 3. Integrated weed management: Katanning, Alexandra Douglas Department of Agriculture 4. Integrated weed management: Merredin, Vanessa Stewart Department of Agriculture 5. Long term resistance site: Get ryegrass numbers low and keep them low! Peter Newman and Glen Adams Department of Agriculture 6. Using pastures to manage ryegrass populations, Andrew Blake and Natalie Lauritsen Department of Agriculture Weed biology and competition 7. Understanding the weed seed bank life if important agricultural weeds, Sally Peltzer and Paul Matson Department of Agriculture 8. Consequence of radish competition on lupin nutrients in wheat-lupin rotation, Abul Hashem and Nerys Wilkins Department of Agriculture 9. Consequence of ryegrass competition on lupin nutrients in a wheat-lupin rotation, Abul Hashem and Nerys Wilkins Department of Agriculture 10. Brome grass too competitive for early sown wheat in a dry year at Mullewa, Peter Newman and Glenn Adam Department of Agriculture Crop establishment and weed management 11. Seeding rate, row spacing and herbicides for weed control, David Minkey Department of Agriculture 12. Effect of different seeding methods on wheat and ryegrass, Abul Hashem, Glen Riethmuller and Nerys Wilkins Department of Agriculture 13. Role of tillage implements and trifluralin on the effectiveness of the autumn tickle for stimulating annual ryegrass emergence, Tim Cusack1, Kathryn Steadman1 and Abul Hashem2,1Western Australia Herbicide Resistance Initiative, UWA; 2Department of Agriculture, 14. Timing of autumn tickle in important for non-wetting soils, Pippa Michael1, Peter Newman2 and Kathryn Steadman 2, 1Western Australia Herbicide Resistance Initiative, UWA, 2Department of Agriculture 15. Early investigation into weed seed burial by mouldboard plough, Sally Peltzer and Alex Douglas Department of Agriculture 16. Rolling post-emergent lupins to improve weed emergence and control on loamy sand, Paul Blackwell, Department of Agriculture and Dave Brindal, Strawberry via Mingenew IWM tools 17. Crop topping in 2001: How did we do? Peter Newman and Glenn Adam Department of Agriculture 18. Wickwipers work! Peter Newman and Glenn Adam Department of Agriculture 19. Wild radish and ryegrass seed collection at harvest: Chaff carts and other devices, Michael Walsh Western Australia Herbicide Resistance Initiative, UWA and Wayne Parker Department of Agriculture 20. Improving weed control in grazed pastures using legumes with low palatability, Clinton Revell, Giles Glasson Department of Agriculture, and Dean Thomas Faculty of Agriculture, University of Western Australia Adoption and modelling 21. Grower weed survey, Peter Newman and Glenn Adam Department of Agriculture 22. Agronomist survey, Peter Newman and Glenn Adam Department of Agriculture 23. Ryegrass RIM model stands the test of IWM field trial data, Alister Draper Western Australia Herbicide Resistance Initiative, UWA and Bill Roy, Western Australia Herbicide Resistance Initiative, UWA Agricultural Consulting and Research Services 24. Multi-species RIM: An update, Marta Monjardin1,2, David Pannell2 and Stephen Powles 1, 1Western Australia Herbicide Resistance Initiative, UWA, 2 ARE, University of Western Australia 25. RIM survey feedback, Robert Barrett-Lennard and Alister Draper Western Australia Herbicide Resistance Initiative, UWA 26. Effect of historic input and product prices on choice of ryegrass management strategies, Alister Draper1 and Martin Bent2, 1Western Australia Herbicide Resistance Initiative, UWA, 2Muresk Institute of Agriculture 27. Living with ryegrass – trading off weed control and economic performance, Martin Bent1 and Alister Draper2 , 1Muresk Institute of Agriculture, Curtin University, 2Western Australia Herbicide Resistance Initiative, UWA HERBICIDE RESISTANCE 28. Glyphosate resistance in WA and Australia: Where are we at? Paul Neve1, Art Diggle2, Patrick Smith3, Mechelle Owen1, Abul Hashem2, Christopher Preston4and Stephen Powles1,1Western Australian Herbicide Resistance Initiative, University of Western Australia, 2Department of Agriculture, 3CSIRO Sustainable Ecosystems, 4CRC for Australian Weed Management and Department of Applied and Molecular Ecology, Waite Campus, University of Adelaide 29. We need you weeds: A survey of knockdown resistance in the WA wheatbelt, Paul Neve1, Mechelle Owen1, Abul Hashem2 and Stephen Powles1 1Western Australian Herbicide Resistance Initiative, University of Western Australia, 2Department of Agriculture 30. A test for resistance testing, Mechelle Owen, Tracey Gillam, Rick Llewellyn and Steve Powles,Western Australia Herbicide Resistance Initiative, University of Western Australia 31. In field testing for herbicide resistance, a purpose built multi-treatment spray boom with results from 2001, Richard Quinlan, Elders Ltd 32. Advantages and limitations of a purpose built multi-treatment spray boom, Richard Quinlan, Elders Ltd 33. Group F resistant wild radish: What’s new? Aik Cheam, Siew Lee Department of Agriculture, and Mike Clarke Aventis Crop Science 34. Cross resistance of Brodal® resistant wild radish to Sniper®, Aik Cheam and Siew Lee, Department of Agriculture 35. Managing a biotype of wild radish with Group F and Group C resistance, Aik Cheam, Siew Lee, David Nicholson, Peter Newman Department of Agriculture and Mike Clarke, Aventis Crop Science HERBICIDE TOLERANCE 36. Herbicide tolerance of new wheat varieties, Harmohinder S. Dhammu, Terry Piper and David Nicholson, Agriculture Western Australia 37. Response of barley varieties to herbicides, Harmohinder S. Dhammu, Terry Piper, Department of Agriculture 38. Tolerance of barley to phenoxy herbicides, Harmohinder S. Dhammu, Terry Piper, Department of Agriculture and Chad Sayer, Nufarm Australia Limited 39. Response of Durum wheats to herbicides, Harmohinder S. Dhammu, Terry Piper, Department of Agriculture 40. Response of new field pea varieties to herbicides, Harmohinder S. Dhammu, Terry Piper and David Nicholson, Department of Agriculture 41. Herbicide tolerance of Desi chickpeas on marginal soil, Harmohinder S. Dhammu, Terry Piper and David Nicholson, Department of Agriculture 42. Herbicide tolerance of newer lupin varieties, Terry Piper, Harmohinder Dhammu and David Nicholson, Department of Agriculture 43. Herbicide tolerance of some annual pasture legumes, Clinton Revell and Ian Rose, Department of Agriculture 44. Herbicide tolerance of pasture legumes, Andrew Blake, Department of Agriculture HERBICIDES – NEW PRODUCTS/PRODUCT USES; USE 45. Knockdown herbicides do not reliably kill small grass weeds, Peter Newman and Glenn Adam, Department of Agriculture 46. ‘Hair Cutting’ wheat with Spray.Seed®: Does it work? Peter Newman and Glenn Adam, Department of Agriculture 47. ‘Haircutting’: Does the number one cut work? Robert Barrett-Lennard1 and Jerome Critch2,1WA Herbicide Resistance Initiative, University of WA, 2Student, University of WA 48. Hammer EC (Carfentrazone-ethyl): A mixing partner for glyphosate to enhance the control of difficult broadleaf weeds, Gordon R. Cumming, Crop Care Australasia 49. Marshmallow control in reduced tillage systems, Sam Taylor, Wesfarmers Landmark 50. Herbicide options for summer germinating marshmallow, Vanessa Stewart, Department of Agriculture 51. Dual Gold® safe in a dry year at Coorow, Peter Newman and Glenn Adam, Department of Agriculture 52. The effect of glyphosate, paraquat and diquat as a crop topping application on the germination of barley, John Moore and Roslyn Jettner, Department of Agriculture 53. Herbicide options for melon control, Vanessa Stewart, Department of Agriculture 54. Herbicide options for the control of Chloris truncate (windmill grass) Vanessa Stewart, Department of Agriculture 55. Allelopathic effects of crop, pasture and weed residues on subsequent crop and pasture establishment, Stuart Bee1, Lionel Martin1, Keith Devenish2 and Terry Piper2, 1Muresk Institute of Agriculture, Curtin University of Technology, Northam, Western Australia, 2Centre for Cropping Systems, Department of Agriculture WEED ISSUES 56. Role of Roundup ReadyÒ canola in the farming system, Art Diggle1, Patrick Smith2, Paul Neve3, Felicity Flugge4, Amir Abadi5 and Stephen Powles3, 1Department of Agriculture; 2CSIRO, Sustainable Ecosystems; 3Western Australian Herbicide Resistance Initiative; 4Centre for Legumes in Mediterranean Agriculture; 5Touchstone Consulting 57. ’Weeds for Feed’ and livestock enterprise structures: A feasibility study and farmer survey in the north-easern wheatbelt, Duncan Peter and Stuart McAlpine, Department of Agriculture and Liebe Group, Buntine 58. e-weed, Vanessa Stewart, Agriculture Western Australi