Shrimp (Penaeus monodon Fabricius) production in brackishwater ponds applied varying fertilizer combinations

Details are given of the production of Penaeus monodon in the Philippines reared in brackishwater earthen ponds applied with different fertilizer combinations, namely diammonium phosphate, urea and chicken manure. Results show that the shrimp showed higher yields in fertilized ponds, but increasing the concentration of fertilizers did not give a marked increase in yield - the excess fertilizer was wasted.

Thermal and crystallization behaviors of polyethylene blends synthesized by binary late transition metal catalysts combinations

A series of reactor blends of linear and branched polyethylenes have been prepared, in the presence of modified methylaluminoxane, using a combination of 2,6-bis[1(2,6-dimethyphenylimino) pyridyl]-cobalt(II) dichloride (1), known as an active catalyst for producing linear polyethylene, and [1,4-bis(2,6-diidopropylphenyl)] acenaphthene diimine nickel(II) dibromide (2), which is active for the production of branched polyethylene. The polymerizations were performed at various levels of catalyst feed ratio at 10 bar. The linear correlation between catalyst activity and concentration of catalyst 2 suggested that the catalysts performed independently from each other. The weight-average molecular weights ((M) over bar (w)), crystalline structures, and phase structures of the blends were investigated, using a combination of gel permeation chromatography, differential scanning calorimetry, wide-angle X-ray diffraction, and small angle X-ray scattering techniques. It was found that the polymerization activities and MWs and crystallization rate of the polymers took decreasing tendency with the increase of the catalyst 2 ratios, while melting temperatures (T-m), crystalline temperatures (T,), and crystalline degrees took decreasing tendency. Long period was distinctly influenced by the amorphous component concentration.

Notes on grasses (Poaceae) for the Flora of China, VI. New combinations in Stipeae and Anthoxantham

When Oryzopsis is confined to the type species, Chinese species are placed in Achnatherum and Piptatherum. This necessitates the following new combinations: Piptatherum grandispiculum, Piptatherum aequiglume var. ligulatum, Piptatherum tibeticum var. psilolepis.. Piptatherum. munroi var. parviflorum, Achnatherum henryi. and Achnatherum henryi var. acutum. Achnatherum henryi is lectotypified. The new name Piptatherum kuoi replaces the illegitimate name Piptatherum obtusum, and this species is lectotypified. Hierochloe potaninii is transferred to Anthoxanthum as A. potaninii, as Hierochloe is regarded as a synonym of Anthoxanthum. All the grass taxa (Poaceae) listed are endemic to China.

New taxa, names, and combinations in Saxifraga (Saxifragaceae) for the Flora of China

The following new species, new variety, new name, and four new combinations are published for the forthcoming account of Saxifraga L. in the Flora of China, Volume 8: S. epiphylla Gornall & H. Ohba, sp. nov., S. gemmigera Engler var. gemmuligera (Engler) J. T. Pan & Gornall, comb. nov., S. heterotricha Marquand & Airy-Shaw var. anadena (H. Smith) J. T. Pan & Gornall, comb. et stat, nov., S. hypericoides Franchet var. aurantiascens (Engler & Irmscher) J. T. Pan & Gornall, comb. nov., S. hypericoides var. rockii (Mattfeld) J. T. Pan & Gornall, comb. et stat. nov., S. sinomontana J. T. Pan & Gornall, nom. nov., and S. sinomontana var. amabilis H. Smith ex J. T. Pan, var. nov. In addition, the names S. mengtzeana Engler & Irmscher and S. mengtzeana var. cordatifolia Engler & Irmscher are lectotypified here.

Recognition by Linear Combinations of Models

Visual object recognition requires the matching of an image with a set of models stored in memory. In this paper we propose an approach to recognition in which a 3-D object is represented by the linear combination of 2-D images of the object. If M = {M1,...Mk} is the set of pictures representing a given object, and P is the 2-D image of an object to be recognized, then P is considered an instance of M if P = Eki=aiMi for some constants ai. We show that this approach handles correctly rigid 3-D transformations of objects with sharp as well as smooth boundaries, and can also handle non-rigid transformations. The paper is divided into two parts. In the first part we show that the variety of views depicting the same object under different transformations can often be expressed as the linear combinations of a small number of views. In the second part we suggest how this linear combinatino property may be used in the recognition process.

Localization and Positioning Using Combinations of Model Views

A method for localization and positioning in an indoor environment is presented. The method is based on representing the scene as a set of 2D views and predicting the appearances of novel views by linear combinations of the model views. The method is accurate under weak perspective projection. Analysis of this projection as well as experimental results demonstrate that in many cases it is sufficient to accurately describe the scene. When weak perspective approximation is invalid, an iterative solution to account for the perspective distortions can be employed. A simple algorithm for repositioning, the task of returning to a previously visited position defined by a single view, is derived from this method.

Physically-Based Combinations of Views: Representing Rigid and Nonrigid Motion

Nonrigid motion can be described as morphing or blending between extremal shapes, e.g., heart motion can be described as transitioning between the systole and diastole states. Using physically-based modeling techniques, shape similarity can be measured in terms of forces and strain. This provides a physically-based coordinate system in which motion is characterized in terms of physical similarity to a set of extremal shapes. Having such a low-dimensional characterization of nonrigid motion allows for the recognition and the comparison of different types of nonrigid motion.

Combinations of Deformable Shape Prototypes

We propose to investigate a model-based technique for encoding non-rigid object classes in terms of object prototypes. Objects from the same class can be parameterized by identifying shape and appearance invariants of the class to devise low-level representations. The approach presented here creates a flexible model for an object class from a set of prototypes. This model is then used to estimate the parameters of low-level representation of novel objects as combinations of the prototype parameters. Variations in the object shape are modeled as non-rigid deformations. Appearance variations are modeled as intensity variations. In the training phase, the system is presented with several example prototype images. These prototype images are registered to a reference image by a finite element-based technique called Active Blobs. The deformations of the finite element model to register a prototype image with the reference image provide the shape description or shape vector for the prototype. The shape vector for each prototype, is then used to warp the prototype image onto the reference image and obtain the corresponding texture vector. The prototype texture vectors, being warped onto the same reference image have a pixel by pixel correspondence with each other and hence are "shape normalized". Given sufficient number of prototypes that exhibit appropriate in-class variations, the shape and the texture vectors define a linear prototype subspace that spans the object class. Each prototype is a vector in this subspace. The matching phase involves the estimation of a set of combination parameters for synthesis of the novel object by combining the prototype shape and texture vectors. The strengths of this technique lie in the combined estimation of both shape and appearance parameters. This is in contrast with the previous approaches where shape and appearance parameters were estimated separately.