GAOS: Spatial optimisation of crop and nature within agricultural fields

This paper proposes and demonstrates a spatial optimiser that allocates areas of inefficient machine manoeuvring to field margins thus improving the use of available space and supporting map-based Controlled Traffic Farming. A prototype web service (GAOS) allows farmers to optimise tracks within their fields and explore planning alternatives prior to downloading the plans to their RTK GPS-guided steering system. GAOS retrieves accurate data on field geometry from a geo-database. Via a web interface, the farmer sets options regarding operation properties, potential locations for field margins and headlands, etc. Next, an optimisation script that employs an open source geospatial library (osgeo.ogr) is called. The objective function considers costs involved with un-cropped areas, turning at headlands and subsidies received for field margins. Optimisation results are stored in a database and are available for (1) viewing via the web interface, (2) downloading to the GPS-guided steering system and (3) communication to third parties

Creating space for biodiversity by planning swath patterns and field marging using accurate geometry

Potential benefits of field margins or boundary strips include promotion of biodiversity and farm wildlife, maintaining landscape diversity, exploiting pest predators and parasites and enhancing crop pollinator populations. In this paper we propose and demonstrate a method to relocate areas of sub-efficient machine manoeuvring to boundary strips so as to optimise the use of available space. Accordingly, the boundary strips will have variable rather than fixed widths. The method is being tested in co-operation with seven farmers in the Hoeksche Waard within the province of Zuid Holland, The Netherlands. In a preliminary stage of the project, tests were performed to determine the required accuracy of field geometry. The results confirmed that additional data acquisition using accurate measuring devices is required. In response, a local contracting firm equipped a small all-terrain vehicle (quad) with an RTK-GPS receiver and set up a service for field measurement. Protocols were developed for requesting a field measurement and for the measurement procedure itself. Co-ordinate transformation to a metric system and brute force optimization of swath patterns are achieved using an open source geospatial library (osgeo.ogr) and Python scripting. The optimizer basically tests all orientations and relevant intermediate angles of input field boundaries and tries incremental positional shifts until the most efficient swath pattern is found. Inefficient swaths intersecting boundary areas are deleted to create space for field margins. The optimised pattern can be forwarded to an agricultural navigation system. At the time of the conference, the approach will have been tested on several farm fields

The effect of open lung ventilation on right ventricular and left ventricular function in lung-lavaged pigs

INTRODUCTION: Ventilation according to the open lung concept (OLC) consists of recruitment maneuvers, followed by low tidal volume and high positive end-expiratory pressure, aiming at minimizing atelectasis. The minimization of atelectasis reduces the right ventricular (RV) afterload, but the increased intrathoracic pressures used by OLC ventilation could increase the RV afterload. We hypothesize that when atelectasis is minimized by OLC ventilation, cardiac function is not affected despite the higher mean airway pressure. METHODS: After repeated lung lavage, each pig (n = 10) was conventionally ventilated and was ventilated according to OLC in a randomized cross-over setting. Conventional mechanical ventilation (CMV) consisted of volume-controlled ventilation with 5 cmH2O positive end-expiratory pressure and a tidal volume of 8-10 ml/kg. No recruitment maneuvers were performed. During OLC ventilation, recruitment maneuvers were applied until PaO2/FiO2 > 60 kPa. The peak inspiratory pressure was set to obtain a tidal volume of 6-8 ml/kg. The cardiac output (CO), th

GAOS: Spatial optimisation of crop and nature within agricultural fields

This paper proposes and demonstrates a spatial optimiser that allocates areas of inefficient machine manoeuvring to field margins thus improving the use of available space and supporting map-based Controlled Traffic Farming. A prototype web service (GAOS) allows farmers to optimise tracks within their fields and explore planning alternatives prior to downloading the plans to their RTK GPS-guided steering system. GAOS retrieves accurate data on field geometry from a geo-database. Via a web interface, the farmer sets options regarding operation properties, potential locations for field margins and headlands, etc. Next, an optimisation script that employs an open source geospatial library (osgeo.ogr) is called. The objective function considers costs involved with un-cropped areas, turning at headlands and subsidies received for field margins. Optimisation results are stored in a database and are available for (1) viewing via the web interface, (2) downloading to the GPS-guided steering system and (3) communication to third parties

Spatial optimisation of cropped swaths and field margins using GIS

This paper (1) proposes an elementary method for optimising the spatial configuration of cropped swaths within agricultural fields while creating space for field margins, and (2) assesses its feasibility with respect to input data requirements. The approach assumes straight, non-overlapping swaths and attempts to relocate areas of inefficient machine manoeuvring to boundary strips by minimising the costs of area loss and additional swaths minus any subsidy received for field boundaries. Optimisation involves an exhaustive search over a discrete set of swath orientations and positional shifts that are derived from measured field geometry. The method was implemented using an open source GIS library to facilitate spatial overlay operations and data input and output. Testing involved the stability of the optimal swathing pattern and economic evaluation of farming alternatives under changes in the cost values used in the objective function. The method requires accurate field geometry data, but for optimising the spatial configuration of swaths and margins, the cost values only need to be roughly known. However, economic evaluation of the option of compulsory buffer strips versus voluntary field margins requires accurate cost estimates. The method is being used to support regional plans concerning biodiversity and societal demands in the Hoeksche Waard (The Netherland

Creating space for biodiversity by planning swath patterns and field marging using accurate geometry

Potential benefits of field margins or boundary strips include promotion of biodiversity and farm wildlife, maintaining landscape diversity, exploiting pest predators and parasites and enhancing crop pollinator populations. In this paper we propose and demonstrate a method to relocate areas of sub-efficient machine manoeuvring to boundary strips so as to optimise the use of available space. Accordingly, the boundary strips will have variable rather than fixed widths. The method is being tested in co-operation with seven farmers in the Hoeksche Waard within the province of Zuid Holland, The Netherlands. In a preliminary stage of the project, tests were performed to determine the required accuracy of field geometry. The results confirmed that additional data acquisition using accurate measuring devices is required. In response, a local contracting firm equipped a small all-terrain vehicle (quad) with an RTK-GPS receiver and set up a service for field measurement. Protocols were developed for requesting a field measurement and for the measurement procedure itself. Co-ordinate transformation to a metric system and brute force optimization of swath patterns are achieved using an open source geospatial library (osgeo.ogr) and Python scripting. The optimizer basically tests all orientations and relevant intermediate angles of input field boundaries and tries incremental positional shifts until the most efficient swath pattern is found. Inefficient swaths intersecting boundary areas are deleted to create space for field margins. The optimised pattern can be forwarded to an agricultural navigation system. At the time of the conference, the approach will have been tested on several farm fields

Structural basis of DNA targeting by a transposon-encoded CRISPR–Cas system

Bacteria use adaptive immune systems encoded by CRISPR and Cas genes to maintain genomic integrity when challenged by pathogens and mobile genetic elements1,2,3. Type I CRISPR–Cas systems typically target foreign DNA for degradation via joint action of the ribonucleoprotein complex Cascade and the helicase–nuclease Cas34,5, but nuclease-deficient type I systems lacking Cas3 have been repurposed for RNA-guided transposition by bacterial Tn7-like transposons6,7. How CRISPR- and transposon-associated machineries collaborate during DNA targeting and insertion remains unknown. Here we describe structures of a TniQ–Cascade complex encoded by the Vibrio cholerae Tn6677 transposon using cryo-electron microscopy, revealing the mechanistic basis of this functional coupling. The cryo-electron microscopy maps enabled de novo modelling and refinement of the transposition protein TniQ, which binds to the Cascade complex as a dimer in a head-to-tail configuration, at the interface formed by Cas6 and Cas7 near the 3′ end of the CRISPR RNA (crRNA). The natural Cas8–Cas5 fusion protein binds the 5′ crRNA handle and contacts the TniQ dimer via a flexible insertion domain. A target DNA-bound structure reveals critical interactions necessary for protospacer-adjacent motif recognition and R-loop formation. This work lays the foundation for a structural understanding of how DNA targeting by TniQ–Cascade leads to downstream recruitment of additional transposase proteins, and will guide protein engineering efforts to leverage this system for programmable DNA insertions in genome-engineering applications.Part of this work was performed at the Simons Electron Microscopy Center and National Resource for Automated Molecular Microscopy located at the New York Structural Biology Center, supported by grants from the Simons Foundation (SF349247), NYSTAR and the NIH National Institute of General Medical Sciences (GM103310)