Real World Bayesian Optimization Using Robots to Clean Liquid Spills

Developing robots that can contribute to cleaning could have a significant impact on the lives of many. Cleaning wet liquid spills is a particularly challenging task for a robotic system, and has several high impact applications. This is a hard task to physically model due to the complex interactions between cleaning materials and the surface. As such, to the authors' knowledge there has been no prior work in this area. A new method for finding optimal control parameters for the cleaning of liquid spills is required by developing a robotic system which iteratively learns to clean through physical experimentation. The robot creates a liquid spill, cleans and assesses performance and uses Bayesian optimization to find the optimal control parameters for a given size of liquid spill. The automation process enabled the experiment to be repeated more than 400 times over 20 hours to find the optimal wiping control parameters for many different conditions. We then show that these solutions can be extrapolated for different spill conditions. The optimized control parameters showed reliable and accurate performances, which in some cases, outperformed humans at the same task.This work was supported by BEKO PLC and Symphony Kitchens. We are especially thankful for the valuable inputs from Dr Graham Anderson and Dr Natasha Conway

Identifying Ligand Binding Conformations of the β2-Adrenergic Receptor by Using Its Agonists as Computational Probes

Recently available G-protein coupled receptor (GPCR) structures and biophysical studies suggest that the difference between the effects of various agonists and antagonists cannot be explained by single structures alone, but rather that the conformational ensembles of the proteins need to be considered. Here we use an elastic network model-guided molecular dynamics simulation protocol to generate an ensemble of conformers of a prototypical GPCR, β2-adrenergic receptor (β2AR). The resulting conformers are clustered into groups based on the conformations of the ligand binding site, and distinct conformers from each group are assessed for their binding to known agonists of β2AR. We show that the select ligands bind preferentially to different predicted conformers of β2AR, and identify a role of β2AR extracellular region as an allosteric binding site for larger drugs such as salmeterol. Thus, drugs and ligands can be used as "computational probes" to systematically identify protein conformers with likely biological significance. © 2012 Isin et al

GARFIELD-AF model for prediction of stroke and major bleeding in atrial fibrillation: a Danish nationwide validation study.

OBJECTIVES: To externally validate the accuracy of the Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF) model against existing risk scores for stroke and major bleeding risk in patients with non-valvular AF in a population-based cohort. DESIGN: Retrospective cohort study. SETTING: Danish nationwide registries. PARTICIPANTS: 90 693 patients with newly diagnosed non-valvular AF were included between 2010 and 2016, with follow-up censored at 1 year. PRIMARY AND SECONDARY OUTCOME MEASURES: External validation was performed using discrimination and calibration plots. C-statistics were compared with CHA2DS2VASc score for ischaemic stroke/systemic embolism (SE) and HAS-BLED score for major bleeding/haemorrhagic stroke outcomes. RESULTS: Of the 90 693 included, 51 180 patients received oral anticoagulants (OAC). Overall median age (Q1, Q3) were 75 (66-83) years and 48 486 (53.5%) were male. At 1-year follow-up, a total of 2094 (2.3%) strokes/SE, 2642 (2.9%) major bleedings and 10 915 (12.0%) deaths occurred. The GARFIELD-AF model was well calibrated with the predicted risk for stroke/SE and major bleeding. The discriminatory value of GARFIELD-AF risk model was superior to CHA2DS2VASc for predicting stroke in the overall cohort (C-index: 0.71, 95% CI: 0.70 to 0.72 vs C-index: 0.67, 95% CI: 0.66 to 0.68, p<0.001) as well as in low-risk patients (C-index: 0.64, 95% CI: 0.59 to 0.69 vs C-index: 0.57, 95% CI: 0.53 to 0.61, p=0.007). The GARFIELD-AF model was comparable to HAS-BLED in predicting the risk of major bleeding in patients on OAC therapy (C-index: 0.64, 95% CI: 0.63 to 0.66 vs C-index: 0.64, 95% CI: 0.63 to 0.65, p=0.60). CONCLUSION: In a nationwide Danish cohort with non-valvular AF, the GARFIELD-AF model adequately predicted the risk of ischaemic stroke/SE and major bleeding. Our external validation confirms that the GARFIELD-AF model was superior to CHA2DS2VASc in predicting stroke/SE and comparable with HAS-BLED for predicting major bleeding

Nitrogen transfer from forage legumes to nine neighbouring plants in a multi-species grassland

Legumes play a crucial role in nitrogen supply to grass-legume mixtures for ruminant fodder. To quantify N transfer from legumes to neighbouring plants in multi-species grasslands we established a grass-legume-herb mixture on a loamy-sandy site in Denmark. White clover (Trifolium repens L.), red clover (Trifolium pratense L.) and lucerne (Medicago sativa L.) were leaf-labelled with 15N enriched urea during one growing season. N transfer to grasses (Lolium perenne L. and xfestulolium), white clover, red clover, lucerne, birdsfoot trefoil (Lotus corniculatus L.), chicory (Cichorium intybus L.), plantain (Plantago lanceolata L.), salad burnet (Sanguisorba minor L.)and caraway (Carum carvi L.) was assessed. Neighbouring plants contained greater amounts of N derived from white clover (4.8 gm-2) compared with red clover (2.2 gm-2) and lucerne (1.1 gm-2). Grasses having fibrous roots received greater amounts of N from legumes than dicotyledonous plants which generally have taproots. Slurry application mainly increased N transfer from legumes to grasses. During the growing season the three legumes transferred approximately 40 kg N ha-1 to neighbouring plants. Below-ground N transfer from legumes to neighbouring plants differed among nitrogen donors and nitrogen receivers and may depend on root characteristics and regrowth strategies of plant species in the multi-species grassland

Effects of Thyroxine Exposure on Osteogenesis in Mouse Calvarial Pre-Osteoblasts

The incidence of craniosynostosis is one in every 1,800-2500 births. The gene-environment model proposes that if a genetic predisposition is coupled with environmental exposures, the effects can be multiplicative resulting in severely abnormal phenotypes. At present, very little is known about the role of gene-environment interactions in modulating craniosynostosis phenotypes, but prior evidence suggests a role for endocrine factors. Here we provide a report of the effects of thyroid hormone exposure on murine calvaria cells. Murine derived calvaria cells were exposed to critical doses of pharmaceutical thyroxine and analyzed after 3 and 7 days of treatment. Endpoint assays were designed to determine the effects of the hormone exposure on markers of osteogenesis and included, proliferation assay, quantitative ALP activity assay, targeted qPCR for mRNA expression of Runx2, Alp, Ocn, and Twist1, genechip array for 28,853 targets, and targeted osteogenic microarray with qPCR confirmations. Exposure to thyroxine stimulated the cells to express ALP in a dose dependent manner. There were no patterns of difference observed for proliferation. Targeted RNA expression data confirmed expression increases for Alp and Ocn at 7 days in culture. The genechip array suggests substantive expression differences for 46 gene targets and the targeted osteogenesis microarray indicated 23 targets with substantive differences. 11 gene targets were chosen for qPCR confirmation because of their known association with bone or craniosynostosis (Col2a1, Dmp1, Fgf1, 2, Igf1, Mmp9, Phex, Tnf, Htra1, Por, and Dcn). We confirmed substantive increases in mRNA for Phex, FGF1, 2, Tnf, Dmp1, Htra1, Por, Igf1 and Mmp9, and substantive decreases for Dcn. It appears thyroid hormone may exert its effects through increasing osteogenesis. Targets isolated suggest a possible interaction for those gene products associated with calvarial suture growth and homeostasis as well as craniosynostosis. © 2013 Cray et al

Rapid global ocean-atmosphere response to Southern Ocean freshening during the last glacial.

Contrasting Greenland and Antarctic temperatures during the last glacial period (115,000 to 11,650 years ago) are thought to have been driven by imbalances in the rates of formation of North Atlantic and Antarctic Deep Water (the 'bipolar seesaw'). Here we exploit a bidecadally resolved 14C data set obtained from New Zealand kauri (Agathis australis) to undertake high-precision alignment of key climate data sets spanning iceberg-rafted debris event Heinrich 3 and Greenland Interstadial (GI) 5.1 in the North Atlantic (~30,400 to 28,400 years ago). We observe no divergence between the kauri and Atlantic marine sediment 14C data sets, implying limited changes in deep water formation. However, a Southern Ocean (Atlantic-sector) iceberg rafted debris event appears to have occurred synchronously with GI-5.1 warming and decreased precipitation over the western equatorial Pacific and Atlantic. An ensemble of transient meltwater simulations shows that Antarctic-sourced salinity anomalies can generate climate changes that are propagated globally via an atmospheric Rossby wave train.A challenge for testing mechanisms of past climate change is the precise correlation of palaeoclimate records. Here, through climate modelling and the alignment of terrestrial, ice and marine 14C and 10Be records, the authors show that Southern Ocean freshwater hosing can trigger global change

Cognitive impairment induced by delta9-tetrahydrocannabinol occurs through heteromers between cannabinoid CB1 and serotonin 5-HT2A receptors

Delta-9-tetrahydrocannabinol (THC), the main psychoactive compound of marijuana, induces numerous undesirable effects, including memory impairments, anxiety, and dependence. Conversely, THC also has potentially therapeutic effects, including analgesia, muscle relaxation, and neuroprotection. However, the mechanisms that dissociate these responses are still not known. Using mice lacking the serotonin receptor 5-HT2A, we revealed that the analgesic and amnesic effects of THC are independent of each other: while amnesia induced by THC disappears in the mutant mice, THC can still promote analgesia in these animals. In subsequent molecular studies, we showed that in specific brain regions involved in memory formation, the receptors for THC and the 5-HT2A receptors work together by physically interacting with each other. Experimentally interfering with this interaction prevented the memory deficits induced by THC, but not its analgesic properties. Our results highlight a novel mechanism by which the beneficial analgesic properties of THC can be dissociated from its cognitive side effects