Cotton tillage and planting guidelines

"Original author: David W. Albers, former State Extension Specialist-Cotton Support for the tillage research referenced in this publication is in part from the Missouri State Support Committee and Cotton Incorporated, using grower check-off dollars.""Tillage operations performed prior to planting cotton should make a firm, well-drained seedbed that will provide a warm environment for seed germination and vigorous seedling growth. Since cotton is a semi-tropical, perennial plant, it grows very slowly early in the growing season compared to other Missouri crops such as corn and soybeans. The slow, early growth nature of this crop requires a grower to provide a seedbed that will allow the young seedling to get off to the best start possible. With new equipment, especially planters and cultivators, developed to handle high-residue conditions, it is possible to plant cotton into stale beds or fields that have received minimal tillage. Clean-till approaches are still the predominant tillage system for cotton, but using fewer tillage operations is one way that cotton growers have found to reduce costs yet produce yields equal to those in conventional, clean-till systems."--First page.David L. Reinbott (Area Farm Management Specialist, Scott County), Gene Stevens (Extension Professor, Agronomy)Taken from the Extension website: Reviewed Sept. 201

Incorporation of SemiSpan SuperSonic Transport (S4T) Aeroservoelastic Models into SAREC-ASV Simulation

The Simulink-based Simulation Architecture for Evaluating Controls for Aerospace Vehicles (SAREC-ASV) was modified to incorporate linear models representing aeroservoelastic characteristics of the SemiSpan SuperSonic Transport (S4T) wind-tunnel model. The S4T planform is for a Technology Concept Aircraft (TCA) design from the 1990s. The model has three control surfaces and is instrumented with accelerometers and strain gauges. Control laws developed for wind-tunnel testing for Ride Quality Enhancement, Gust Load Alleviation, and Flutter Suppression System functions were implemented in the simulation. The simulation models open- and closed-loop response to turbulence and to control excitation. It provides time histories for closed-loop stable conditions above the open-loop flutter boundary. The simulation is useful for assessing the potential impact of closed-loop control rate and position saturation. It also provides a means to assess fidelity of system identification procedures by providing time histories for a known plant model, with and without unmeasured turbulence as a disturbance. Sets of linear models representing different Mach number and dynamic pressure conditions were implemented as MATLAB Linear Time Invariant (LTI) objects. Configuration changes were implemented by selecting which LTI object to use in a Simulink template block. A limited comparison of simulation versus wind-tunnel results is shown

Plenary Session I – Policy Track: Policies That Work

This session will discuss policy formation, implementation, and enforcement issues related to older driver safety. Policymakers Representative Khan and Senators Chandler and Jehlen will discuss the process of getting evidence-based laws enacted, while Middlesex D.A. Marian Ryan will describe enforcement issues and concerns. Moderator David Stevens will talk about advocating for socially just and evidence-based policies impacting older adults

Methodology capture: discriminating between the "best" and the rest of community practice

<p>Abstract</p> <p>Background</p> <p>The methodologies we use both enable and help define our research. However, as experimental complexity has increased the choice of appropriate methodologies has become an increasingly difficult task. This makes it difficult to keep track of available bioinformatics software, let alone the most suitable protocols in a specific research area. To remedy this we present an approach for capturing methodology from literature in order to identify and, thus, define best practice within a field.</p> <p>Results</p> <p>Our approach is to implement data extraction techniques on the full-text of scientific articles to obtain the set of experimental protocols used by an entire scientific discipline, molecular phylogenetics. Our methodology for identifying methodologies could in principle be applied to any scientific discipline, whether or not computer-based. We find a number of issues related to the nature of best practice, as opposed to community practice. We find that there is much heterogeneity in the use of molecular phylogenetic methods and software, some of which is related to poor specification of protocols. We also find that phylogenetic practice exhibits field-specific tendencies that have increased through time, despite the generic nature of the available software. We used the practice of highly published and widely collaborative researchers ("expert" researchers) to analyse the influence of authority on community practice. We find expert authors exhibit patterns of practice common to their field and therefore act as useful field-specific practice indicators.</p> <p>Conclusion</p> <p>We have identified a structured community of phylogenetic researchers performing analyses that are customary in their own local community and significantly different from those in other areas. Best practice information can help to bridge such subtle differences by increasing communication of protocols to a wider audience. We propose that the practice of expert authors from the field of evolutionary biology is the closest to contemporary best practice in phylogenetic experimental design. Capturing best practice is, however, a complex task and should also acknowledge the differences between fields such as the specific context of the analysis.</p

Assessing the Gene Content of the Megagenome: Sugar Pine (Pinus lambertiana).

Sugar pine (Pinus lambertiana Douglas) is within the subgenus Strobus with an estimated genome size of 31 Gbp. Transcriptomic resources are of particular interest in conifers due to the challenges presented in their megagenomes for gene identification. In this study, we present the first comprehensive survey of the P. lambertiana transcriptome through deep sequencing of a variety of tissue types to generate more than 2.5 billion short reads. Third generation, long reads generated through PacBio Iso-Seq have been included for the first time in conifers to combat the challenges associated with de novo transcriptome assembly. A technology comparison is provided here to contribute to the otherwise scarce comparisons of second and third generation transcriptome sequencing approaches in plant species. In addition, the transcriptome reference was essential for gene model identification and quality assessment in the parallel project responsible for sequencing and assembly of the entire genome. In this study, the transcriptomic data were also used to address questions surrounding lineage-specific Dicer-like proteins in conifers. These proteins play a role in the control of transposable element proliferation and the related genome expansion in conifers

Automated Syringe Filler

The automated syringe filling system is a bench-top device designed to remove human error when filling a syringe. The microcontroller powered system will hold multiple medicine types that will fill a single syringe with a user specified amount of one medicine to a precise degree and log this information against a remote database of patient information. Before the system can be accessed, the user’s credentials will be checked against the database of authorized users. Once verified a touch screen will be used to enter user input that will be logged to a remote database. The microcontroller will then control the actuators and servo to fill the syringe with the appropriate amount of medicine. The system will automate the process of filling a syringe and remove the element of human error from the syringe filling equation

Evaluation of an Australian indigenous housing programme: community level impact on crowding, infrastructure function and hygiene

Background and Aim: Housing programmes in indigenous Australian communities have focused largely on achieving good standards of infrastructure function. The impact of this approach was assessed on three potentially important housing-related influences on child health at the community level: (1) crowding, (2) the functional state of the house infrastructure and (3) the hygienic condition of the houses.\ud \ud Methods: A before-and-after study, including house infrastructure surveys and structured interviews with the main householder, was conducted in all homes of young children in 10 remote Australian indigenous communities.\ud \ud Results: Compared with baseline, follow-up surveys showed (1) a small non-significant decrease in the mean number of people per bedroom in the house on the night before the survey (3.4, 95% CI 3.1 to 3.6 at baseline vs 3.2, 95% CI 2.9 to 3.4 at follow-up; natural logarithm transformed t test, t=1.3, p=0.102); (2) a marginally significant overall improvement in infrastructure function scores (Kruskal–Wallis test, χ2=3.9, p=0.047); and (3) no clear overall improvement in hygiene (Kruskal–Wallis test, χ2=0.3, p=0.605).\ud \ud Conclusion: Housing programmes of this scale that focus on the provision of infrastructure alone appear unlikely to lead to more hygienic general living environments, at least in this study context. A broader ecological approach to housing programmes delivered in these communities is needed if potential health benefits are to be maximised. This ecological approach would require a balanced programme of improving access to health hardware, hygiene promotion and creating a broader enabling environment in communities.\u

The advantage of intergenic regions as genomic features for machine-learning-based host attribution of Salmonella Typhimurium from the USA

Salmonella enterica is a taxonomically diverse pathogen with over 2600 serovars associated with a wide variety of animal hosts including humans, other mammals, birds and reptiles. Some serovars are host-specific or host-restricted and cause disease in distinct host species, while others, such as serovar S. Typhimurium (STm), are generalists and have the potential to colonize a wide variety of species. However, even within generalist serovars such as STm it is becoming clear that pathovariants exist that differ in tropism and virulence. Identifying the genetic factors underlying host specificity is complex, but the availability of thousands of genome sequences and advances in machine learning have made it possible to build specific host prediction models to aid outbreak control and predict the human pathogenic potential of isolates from animals and other reservoirs. We have advanced this area by building host-association prediction models trained on a wide range of genomic features and compared them with predictions based on nearest-neighbour phylogeny. SNPs, protein variants (PVs), antimicrobial resistance (AMR) profiles and intergenic regions (IGRs) were extracted from 3883 high-quality STm assemblies collected from humans, swine, bovine and poultry in the USA, and used to construct Random Forest (RF) machine learning models. An additional 244 recent STm assemblies from farm animals were used as a test set for further validation. The models based on PVs and IGRs had the best performance in terms of predicting the host of origin of isolates and outperformed nearest-neighbour phylogenetic host prediction as well as models based on SNPs or AMR data. However, the models did not yield reliable predictions when tested with isolates that were phylogenetically distinct from the training set. The IGR and PV models were often able to differentiate human isolates in clusters where the majority of isolates were from a single animal source. Notably, IGRs were the feature with the best performance across multiple models which may be due to IGRs acting as both a representation of their flanking genes, equivalent to PVs, while also capturing genomic regulatory variation, such as altered promoter regions. The IGR and PV models predict that ~45 % of the human infections with STm in the USA originate from bovine, ~40 % from poultry and ~14.5 % from swine, although sequences of isolates from other sources were not used for training. In summary, the research demonstrates a significant gain in accuracy for models with IGRs and PVs as features compared to SNP-based and core genome phylogeny predictions when applied within the existing population structure. This article contains data hosted by Microreact