Growth, yield and Fusarium wilt resistance of six FHIA tetraploid bananas (Musa spp.) grown in the Australian subtropics

Six tetraploid hybrids from Fundación Hondureña de Investigación Agrícola (FHIA) were evaluated in Australia over a five year period. They included three AAAA hybrids (FHIA-02, FHIA-17 and FHIA-23) and three AAAB hybrids (FHIA-01, FHIA-18 and SH-3640.10) and they were compared with industry standards, ‘Williams’ (AAA, Cavendish subgroup) and ‘Lady Finger’ (AAB, Pome subgroup). They were screened for their resistance to Fusarium wilt race 1 and subtropical race 4 caused by the pathogen Fusarium oxysporum f.sp. cubense and they were also grown for several cycles on farms not infested with Fusarium wilt to record their agronomic characteristics. The AAAB hybrids, all derived from female parent ‘Prata Anã’ (AAB, Pome subgroup) were the most resistant to both races of Fusarium wilt and were very productive in the subtropics. They were significantly more productive than ‘Lady Finger’, which was susceptible to both races of Fusarium wilt. The AAAA hybrids, with the exception of FHIA-02 which was very susceptible to Fusarium wilt and displayed the poorest agronomic traits of the six hybrids, produced bunch weights as good as Cavendish but were significantly slower to cycle. FHIA-17 and FHIA-23, both derived from the female parent ‘Highgate’ (AAA, Gros Michel subgroup), were also significantly more resistant to Fusarium wilt than ‘Gros Michel’, while FHIA-17 demonstrated a level of resistance similar to ‘Williams’ and FHIA-23 was intermediate between ‘Lady Finger’ and ‘Williams

Pseudo-Random Streams for Distributed and Parallel Stochastic Simulations on GP-GPU

International audienceRandom number generation is a key element of stochastic simulations. It has been widely studied for sequential applications purposes, enabling us to reliably use pseudo-random numbers in this case. Unfortunately, we cannot be so enthusiastic when dealing with parallel stochastic simulations. Many applications still neglect random stream parallelization, leading to potentially biased results. In particular parallel execution platforms, such as Graphics Processing Units (GPUs), add their constraints to those of Pseudo-Random Number Generators (PRNGs) used in parallel. This results in a situation where potential biases can be combined with performance drops when parallelization of random streams has not been carried out rigorously. Here, we propose criteria guiding the design of good GPU-enabled PRNGs. We enhance our comments with a study of the techniques aiming to parallelize random streams correctly, in the context of GPU-enabled stochastic simulations

Evolving AVX512 Parallel C Code Using GP

Using 512 bit Advanced Vector Extensions, previous development history and Intel documentation, BNF grammar based genetic improvement automatically ports RNAfold to AVX, giving up to a 1.77 fold speed up. The evolved code pull request is an accepted GI software maintenance update to bioinformatics package ViennaRNA

Processing of CP-Ti by high-pressure torsion and the effect of surface modification using a post-HPT laser treatment

Commercial purity titanium (CP-Ti) was processed by high-pressure torsion (HPT) with various numbers of turns (N = 1, 10 and 20). The hardness of the CP-Ti increased with an increasing number of HPT turns due to grain refinement. Tensile testing showed that the HPT-processed 10 turns sample had low ductility and high strength but the ductility may be improved through post-HPT short-term annealing at carefully selected temperatures. Some HPT-processed samples were laser surface-treated with different laser powers and scanning speeds. The surface roughness of the laser-textured samples increased with increasing laser power and led to a lower contact angle which signifies an increased hydrophilicity. After a holding time of 13 days, the samples underwent a hydrophilic-to-hydrophobic transformation as the contact angle increased to as much as 129 degree. It is concluded that laser surface texture processes are capable of controlling the hydrophilic / hydrophobic properties of ultra-fine grained CP-Ti

Bayesian Intent Prediction in Object Tracking Using Bridging Distributions.

In several application areas, such as human computer interaction, surveillance and defence, determining the intent of a tracked object enables systems to aid the user/operator and facilitate effective, possibly automated, decision making. In this paper, we propose a probabilistic inference approach that permits the prediction, well in advance, of the intended destination of a tracked object and its future trajectory. Within the framework introduced here, the observed partial track of the object is modeled as being part of a Markov bridge terminating at its destination, since the target path, albeit random, must end at the intended endpoint. This captures the underlying long term dependencies in the trajectory, as dictated by the object intent. By determining the likelihood of the partial track being drawn from a particular constructed bridge, the probability of each of a number of possible destinations is evaluated. These bridges can also be employed to produce refined estimates of the latent system state (e.g., object position, velocity, etc.), predict its future values (up until reaching the designated endpoint) and estimate the time of arrival. This is shown to lead to a low complexity Kalman-filter-based implementation of the inference routine, where any linear Gaussian motion model, including the destination reverting ones, can be applied. Free hand pointing gestures data collected in an instrumented vehicle and synthetic trajectories of a vessel heading toward multiple possible harbors are utilized to demonstrate the effectiveness of the proposed approach.The authors would like to thank Jaguar Land Rover and the UK Engineering and Physical Science Research Council (BTaRoT grant EP/K020153/1) for funding this research

Radiocarbon dating of methane and carbon dioxide evaded from a temperate peatland stream

Streams draining peatlands export large quantities of carbon in different chemical forms and are an important part of the carbon cycle. Radiocarbon (14C) analysis/dating provides unique information on the source and rate that carbon is cycled through ecosystems, as has recently been demonstrated at the air-water interface through analysis of carbon dioxide (CO2) lost from peatland streams by evasion (degassing). Peatland streams also have the potential to release large amounts of methane (CH4) and, though 14C analysis of CH4 emitted by ebullition (bubbling) has been previously reported, diffusive emissions have not. We describe methods that enable the 14C analysis of CH4 evaded from peatland streams. Using these methods, we investigated the 14C age and stable carbon isotope composition of both CH4 and CO2 evaded from a small peatland stream draining a temperate raised mire. Methane was aged between 1617-1987 years BP, and was much older than CO2 which had an age range of 303-521 years BP. Isotope mass balance modelling of the results indicated that the CO2 and CH4 evaded from the stream were derived from different source areas, with most evaded CO2 originating from younger layers located nearer the peat surface compared to CH4. The study demonstrates the insight that can be gained into peatland carbon cycling from a methodological development which enables dual isotope (14C and 13C) analysis of both CH4 and CO2 collected at the same time and in the same way

Targeting the EGFR in ovarian cancer with the tyrosine kinase inhibitor ZD1839 (“Iressa”).

The modulating effects of the orally active epidermal growth factor receptor-specific tyrosine kinase inhibitor ZD 1839 (‘Iressa’) on cell growth and signalling were evaluated in four ovarian cancer cell lines (PE01, PE04, SKOV-3, OVCAR-5) that express the epidermal growth factor receptor, and in A2780, which is epidermal growth factor receptor-negative. Transforming growth factor-α stimulated growth was completely inhibited by concentrations of ZD 1839 ⩾0.3 μM in the epidermal growth factor receptor-expressing cell lines, as were transforming growth factor-α stimulated phosphorylation of the epidermal growth factor receptor and downstream components of the MAP kinase and PI-3 kinase signalling cascades. Growth inhibition in the absence of added transforming growth factor-α was also observed which could be consistent with suppression of action of autocrine epidermal growth factor receptor-activating ligands by ZD 1839. In support of this, transforming growth factor-α, EGF and amphiregulin mRNAs were detected by RT–PCR in the epidermal growth factor receptor-expressing cell lines. ZD 1839 inhibited growth of the PE04 ovarian cancer xenograft at 200 mg kg(−1) day(−1). These data lend further support to the view that targeting the epidermal growth factor receptor in ovarian cancer could have therapeutic benefit. British Journal of Cancer (2002) 86, 456–462. DOI: 10.1038/sj/bjc/6600058 www.bjcancer.com © 2002 The Cancer Research Campaig