An effective approach for selection of terrain modelling method

This letter presents an effective approach for selection of appropriate terrain modeling methods in forming a digital elevation model (DEM). This approach achieves a balance between modeling accuracy and modeling speed. A terrain complexity index is defined to represent a terrain's complexity. A support vector machine (SVM) classifies terrain surfaces into either complex or moderate based on this index associated with the terrain elevation range. The classification result recommends a terrain modeling method for a given data set in accordance with its required modeling accuracy. Sample terrain data from the lunar surface are used in constructing an experimental data set. The results have shown that the terrain complexity index properly reflects the terrain complexity, and the SVM classifier derived from both the terrain complexity index and the terrain elevation range is more effective and generic than that designed from either the terrain complexity index or the terrain elevation range only. The statistical results have shown that the average classification accuracy of SVMs is about 84.3% ± 0.9% for terrain types (complex or moderate). For various ratios of complex and moderate terrain types in a selected data set, the DEM modeling speed increases up to 19.5% with given DEM accuracy.

High Resolution Melt (HRM) analysis is an efficient tool to genotype EMS mutants in complex crop genomes

Background: Targeted Induced Loci Lesions IN Genomes (TILLING) is increasingly being used to generate and identify mutations in target genes of crop genomes. TILLING populations of several thousand lines have been generated in a number of crop species including Brassica rapa. Genetic analysis of mutants identified by TILLING requires an efficient, high-throughput and cost effective genotyping method to track the mutations through numerous generations. High resolution melt (HRM) analysis has been used in a number of systems to identify single nucleotide polymorphisms (SNPs) and insertion/deletions (IN/DELs) enabling the genotyping of different types of samples. HRM is ideally suited to high-throughput genotyping of multiple TILLING mutants in complex crop genomes. To date it has been used to identify mutants and genotype single mutations. The aim of this study was to determine if HRM can facilitate downstream analysis of multiple mutant lines identified by TILLING in order to characterise allelic series of EMS induced mutations in target genes across a number of generations in complex crop genomes. Results: We demonstrate that HRM can be used to genotype allelic series of mutations in two genes, BraA.CAX1a and BraA.MET1.a in Brassica rapa. We analysed 12 mutations in BraA.CAX1.a and five in BraA.MET1.a over two generations including a back-cross to the wild-type. Using a commercially available HRM kit and the Lightscanner™ system we were able to detect mutations in heterozygous and homozygous states for both genes. Conclusions: Using HRM genotyping on TILLING derived mutants, it is possible to generate an allelic series of mutations within multiple target genes rapidly. Lines suitable for phenotypic analysis can be isolated approximately 8-9 months (3 generations) from receiving M3 seed of Brassica rapa from the RevGenUK TILLING service.

Complex-valued B-spline neural networks for modeling and inverting Hammerstein systems

Many communication signal processing applications involve modelling and inverting complex-valued (CV) Hammerstein systems. We develops a new CV B-spline neural network approach for efficient identification of the CV Hammerstein system and effective inversion of the estimated CV Hammerstein model. Specifically, the CV nonlinear static function in the Hammerstein system is represented using the tensor product from two univariate B-spline neural networks. An efficient alternating least squares estimation method is adopted for identifying the CV linear dynamic model’s coefficients and the CV B-spline neural network’s weights, which yields the closed-form solutions for both the linear dynamic model’s coefficients and the B-spline neural network’s weights, and this estimation process is guaranteed to converge very fast to a unique minimum solution. Furthermore, an accurate inversion of the CV Hammerstein system can readily be obtained using the estimated model. In particular, the inversion of the CV nonlinear static function in the Hammerstein system can be calculated effectively using a Gaussian-Newton algorithm, which naturally incorporates the efficient De Boor algorithm with both the B-spline curve and first order derivative recursions. The effectiveness of our approach is demonstrated using the application to equalisation of Hammerstein channels.

A unified approach to the recognition of complex actions from sequences of zone-crossings

We present a method for the recognition of complex actions. Our method combines automatic learning of simple actions and manual definition of complex actions in a single grammar. Contrary to the general trend in complex action recognition that consists in dividing recognition into two stages, our method performs recognition of simple and complex actions in a unified way. This is performed by encoding simple action HMMs within the stochastic grammar that models complex actions. This unified approach enables a more effective influence of the higher activity layers into the recognition of simple actions which leads to a substantial improvement in the classification of complex actions. We consider the recognition of complex actions based on person transits between areas in the scene. As input, our method receives crossings of tracks along a set of zones which are derived using unsupervised learning of the movement patterns of the objects in the scene. We evaluate our method on a large dataset showing normal, suspicious and threat behaviour on a parking lot. Experiments show an improvement of ~ 30% in the recognition of both high-level scenarios and their composing simple actions with respect to a two-stage approach. Experiments with synthetic noise simulating the most common tracking failures show that our method only experiences a limited decrease in performance when moderate amounts of noise are added.

Population ecology of the Asian house rat (Rattus tanezumi) in complex lowland agroecosystems in the Philippines

Context. Rattus tanezumi (the Asian house rat) is the principal rodent pest of rice and coconut crops in the Philippines. Little is known about the population and breeding ecology of R. tanezumi in complex agroecosystems; thus, current methods of rodent control may be inappropriate or poorly implemented. Aims. To investigate the habitat use, population dynamics and breeding biology of R. tanezumi in complex lowland agroecosystems of the Sierra Madre Biodiversity Corridor, Luzon, and to develop ecologically based rodent management (EBRM) strategies that will target specific habitats at specific times to improve cost-efficiency and minimise non-target risks. Methods. An 18-month trapping study was conducted in rice monoculture, rice adjacent to coconut, coconut groves, coconut-based agroforest and forest habitats. Trapped animals were measured, marked and assessed for breeding condition. Key results. Five species of rodent were captured across all habitats with R. tanezumi the major pest species in both the rice and coconut crops. The stage of the rice crop was a major factor influencing the habitat use and breeding biology of R. tanezumi. In rice fields, R. tanezumi abundance was highest during the tillering to ripening stages of the rice crop and lowest during the seedling stage, whereas in coconut groves abundance was highest from the seedling to tillering stage of nearby rice crops. Peaks in breeding activity occurred from the booting stage of the rice crop until just after harvest, but >10% of females were in breeding condition at each month of the year. Conclusions. In contrast with the practices applied by rice farmers in the study region, the most effective time for lethal management based on the breeding ecology of R. tanezumi is likely to be during the early stages of the rice crop, before the booting stage. Farmers generally apply control actions as individuals. We recommend coordinated community action. Continuous breeding throughout the year may necessitate two community campaigns per rice cropping season. To limit population growth, the most effective time to reduce nesting habitat is from the booting stage until harvest. Implications. By adopting EBRM strategies, we expect a reduction in costs associated with rodent control, as well as improved yield and reduced risk to non-target species.

Hydrophilic sulfonated bis-1,2,4-triazine ligands are highly effective reagents for separating actinides(iii) from lanthanides(iii) via selective formation of aqueous actinide complexes

We report the first examples of hydrophilic 6,6′-bis(1,2,4-triazin-3-yl)-2,2′-bipyridine (BTBP) and 2,9-bis(1,2,4-triazin-3-yl)-1,10-phenanthroline (BTPhen) ligands, and their applications as actinide(III) selective aqueous complexing agents. The combination of a hydrophobic diamide ligand in the organic phase and a hydrophilic tetrasulfonated bis-triazine ligand in the aqueous phase is able to separate Am(III) from Eu(III) by selective Am(III) complex formation across a range of nitric acid concentrations with very high selectivities, and without the use of buffers. In contrast, disulfonated bis-triazine ligands are unable to separate Am(III) from Eu(III) in this system. The greater ability of the tetrasulfonated ligands to retain Am(III) selectively in the aqueous phase than the corresponding disulfonated ligands appears to be due to the higher aqueous solubilities of the complexes of the tetrasulfonated ligands with Am(III). The selectivities for Am(III) complexation observed with hydrophilic tetrasulfonated bis-triazine ligands are in many cases far higher than those found with the polyaminocarboxylate ligands previously used as actinide-selective complexing agents, and are comparable to those found with the parent hydrophobic bis-triazine ligands. Thus we demonstrate a feasible alternative method to separate actinides from lanthanides than the widely studied approach of selective actinide extraction with hydrophobic bis-1,2,4-triazine ligands such as CyMe4-BTBP and CyMe4-BTPhen.

Are sulfurous soil amendments (S0, Fe(II)SO4, Fe(III)SO4) an effective tool in the restoration of heathland and acidic grassland after four decades of rock phosphate Fertilization?

This paper deals with the complex issue of reversing long-term improvements of fertility in soils derived from heathlands and acidic grasslands using sulfur-based amendments. The experiment was conducted on a former heathland and acid grassland in the U.K. that was heavily fertilized and limed with rock phosphate, chalk, and marl. The experimental work had three aims. First, to determine whether sulfurous soil amendments are able to lower pH to a level suitable for heathland and acidic grassland re-creation (approximately 3 pH units). Second, to determine what effect the soil amendments have on the available pool of some basic cations and some potentially toxic acidic cations that may affect the plant community. Third, to determine whether the addition of Fe to the soil system would sequester PO4− ions that might be liberated from rock phosphate by the experimental treatments. The application of S0 and Fe(II)SO4− to the soil was able to reduce pH. However, only the highest S0 treatment (2,000 kg/ha S) lowered pH sufficiently for heathland restoration purposes but effectively so. Where pH was lowered, basic cations were lost from the exchangeable pool and replaced by acidic cations. Where Fe was added to the soil, there was no evidence of PO4− sequestration from soil test data (Olsen P), but sequestration was apparent because of lower foliar P in the grass sward. The ability of the forb Rumex acetosella to apparently detoxify Al3+, prevalent in acidified soils, appeared to give it a competitive advantage over other less tolerant species. We would anticipate further changes in plant community structure through time, driven by Al3+ toxicity, leading to the competitive exclusion of less tolerant species. This, we suggest, is a key abiotic driver in the restoration of biotic (acidic plant) communities.