Characterization of transgene integration pattern in F4 hGH-transgenic common carp (Cyprinus carpio L.)

The integration pattern and adjacent host sequences of the inserted pMThGH-transgene in the F4 hGH-transgenic common carp were extensively studied. Here we show that each F4 transgenic fish contained about 200 copies of the pMThGH-transgene and the transgenes were integrated into the host genome generally with concatemers in a head-to-tail arrangement at 4-5 insertion sites. By using a method of plasmid rescue, four hundred copies of transgenes from two individuals of F4 transgenic fish, A and B, were recovered and clarified into 6 classes. All classes of recovered transgenes contained either complete or partial pMThGH sequences. The class I, which comprised 83% and 84.5% respectively of the recovered transgene copies from fish A and B, had maintained the original configuration, indicating that most transgenes were faithfully inherited during the four generations of reproduction. The other five classes were different from the original configuration in both molecular weight and restriction map, indicating that a few transgenes had undergone mutation, rearrangement or deletion during integration and germline transmission. In the five types of aberrant transgenes, three flanking sequences of the host genome were analyzed. These sequences were common carp beta-actin gene, common carp DNA sequences homologous to mouse phosphoglycerate kinase-1 and human epidermal keratin 14, respectively.

Off-axis sonar beam pattern of free-ranging finless porpoises measured by a stereo pulse event data logger

The off-axis sonar beam patterns of eight free-ranging finless porpoises were measured using attached data logger systems. The transmitted sound pressure level at each beam angle was calculated from the animal's body angle, the water surface echo level, and the swimming depth. The beam pattern of the off-axis signals between 45 and 115 (where 0 corresponds to the on-axis direction) was nearly constant. The sound pressure level of the off-axis signals reached 162 dB re 1 mPa peak-to-peak. The surface echo level received at the animal was over 140 dB, much higher than the auditory threshold level of small odontocetes. Finless porpoises are estimated to be able to receive the surface echoes of off-axis signals even at 50-m depth. Shallow water systems (less than 50-m depth) are the dominant habitat of both oceanic and freshwater populations of this species. Surface echoes may provide porpoises not only with diving depth information but also with information about surface direction and location of obstacles (including prey items) outside the on-axis sector of the sonar beam. 2005 Acoustical Society of America.

Heavy metal pollution in China: Origin, pattern and control

Goal, Scope and Background. Heavy metal is among one of the pollutants, which cause severe threats to humans and the environment in China. The aim of the present review is to make information on the source of heavy metal pollution, distribution of heavy metals in the environment, and measures of pollution control accessible internationally, which are mostly published in Chinese. Methods. Information from scientific journals, university journals and governmental releases are compiled focusing mainly on Cd, Cu, Pb and Zn. Partly Al, As, Cr, Fe, Hg, Mn and Ni are included also in part as well. Results and Discussion. In soil, the average contents of Cd, Cu, Pb and Zn are 0.097, 22.6, 26.0 and 74.2 mg/kg, respectively. In the water of. the Yangtze River Basin, the concentrations of Cd, Cu, Pb and Zn are 0.080, 7.91, 15.7 and 18.7 pg/L, respectively. In reference to human activities, the heavy metal pollution comes from three sources: industrial emission, wastewater and solid waste. The environment such as soil, water and air were polluted by heavy metals in some cases. The contents of Cd, Cu, Pb and Zn even reach 3.16, 99.3, 84.1 and 147 mg/kg, respectively, in the soils of a wastewater irrigation zone. These contaminants pollute drinking water and food, and threaten human health. Some diseases resulting from pollution of geological and environmental origin, were observed with long-term and non-reversible effects. Conclusions. In China, the geological background level of heavy metal is low, but with the activity of humans, soil, water, air, and plants are polluted by heavy metals in some cases and even affect human health through the food chain. Recommendations and Outlook. To remediate and improve environmental quality is a long strategy for the polluted area to keep humans and animals healthy. Phytoremediation would be an effective technique to remediate the heavy metal pollutions.

Whole-body amino acid pattern of F-4 human growth hormone gene-transgenic red common carp (Cyprinus carpio) fed diets with different protein levels

F-4 generation of human growth hormone (hGH) gene-transgenic red common carp, and the non-transgenic controls were fed for 8 weeks on purified diets with 20%, 30% or 40% protein. Analysis of whole-body amino acids showed that the proportions of lysine, leucine, phenylalanine, valine and alanine, as percentages of body protein, increased significantly, while those of arginine, glutamic acid and tyrosine decreased, with increases in dietary protein level in at least one strain of fish. Proportions of the other amino acids were unaffected by the diets. The proportions of lysine and arginine were significantly higher, while those of leucine and alanine were lower in the transgenics than in the controls in at least one diet group. Proportions of the other amino acids were unaffected by strain. The results suggest that the whole-body amino acid profile of transgenic carp, when expressed as proportions of body protein, was in general, similar to that of the non-transgenic controls. (C) 2000 Elsevier Science B.V. All rights reserved.

The spatial pattern of the small fish community in the Biandantang Lake - a small shallow lake along the middle reach of the Yangtze River, China

The spatial pattern of the small fish community was studied seasonally in 1996 in the Biandantang Lake. Based on plant cover, the lake was divided into five habitats, arranged in the order by plant structure complexity from complex to simple: Vallisneria spiralis habitat (V habitat), Vallisneria spiralis-Myriophyllum spicatum habitat (V-M habitat), Myriophyllum spicatum habitat (M habitat), Nelunbo nucefera habitat (N habitat), and no vegetation habitat (NV habitat). A modified popnet was used for quantitative sampling of small fishes. A total of 16 fish species were collected; Hypseleotris swinhonis, Ctenogobius giurinus, Pseudorasbora parva, Carassius auratus and Paracheilognathus imberis were the five numerically dominant species. In both summer and autumn, the total density of small fishes was about 10 ind m(-2). Generally, Ctenogobius giurinus, a sedatory, benthic fish, was distributed more or less evenly among the five habitats, while the other four species had lower densities in the N habitat and NV habitat, which had the simplest structures. The distribution of the small fish species showed seasonal variations. In winter, most species concentrated in the V habitat, which had the most complex structure. In spring, the fish had low densities in the N and NV habitat, and were more or less evenly distributed in the other habitats. In summer, the fish had a low density in the NV habitat, and were evenly distributed in the other habitats. In autumn, the fish had higher densities in the V-M and M habitats than in the others. Generally, spatial overlaps between the dominant species were higher in winter than in the other seasons. It was suggested that the variations in the importance of predation risk and resource competition in habitat choice determined the seasonal changes of spatial patterns in the small fishes in the Biandantang Lake.

Study on Closed-set Speaker Identification Based on Biomimetic Pattern Recognition

In this paper, a new classifier of speaker identification has been proposed, which is based on Biomimetic pattern recognition (BPR). Distinguished from traditional speaker recognition methods, such as DWT, HMM, GMM, SVM and so on, the proposed classifier is constructed by some finite sub-space which is reasonable covering of the points in high dimensional space according to distributing characteristic of speech feature points. It has been used in the system of speaker identification. Experiment results show that better effect could be obtained especially with lesser samples. Furthermore, the proposed classifier employs a much simpler modeling structure as compared to the GMM. In addition, the basic idea "cognition" of Biomimetic pattern recognition (BPR) results in no requirement of retraining the old system for enrolling new speakers.

An Automatic Classification Method of Metabolic Cycle Based on Biomimetic Pattern Recognition

Correct classification of different metabolic cycle stages to identification cell cycle is significant in both human development and clinical diagnostics. However, it has no perfect method has been reached in classification of metabolic cycle yet. This paper exploringly puts forward an automatic classification method of metabolic cycle based on Biomimetic pattern recognition (BPR). As to the three phases of yeast metabolic cycle, the correct classification rate reaches 90%, 100% and 100% respectively.

Coulomb blockade double-dot Aharonov-Bohm interferometer: Harmonic decomposition of the interference pattern

For the solid-state double-dot interferometer, the phase shifted interference pattern induced by the interplay of inter-dot Coulomb correlation and multiple reflections is analyzed by harmonic decomposition. Unexpected result is uncovered, and is discussed in connection with the which-path detection and electron loss. (C) 2009 Elsevier B.V. All rights reserved.

Biomimetic pattern recognition theory and its applications

Biomimetic pattern recogntion (BPR), which is based on "cognition" instead of "classification", is much closer to the function of human being. The basis of BPR is the Principle of homology-continuity (PHC), which means the difference between two samples of the same class must be gradually changed. The aim of BPR is to find an optimal covering in the feature space, which emphasizes the "similarity" among homologous group members, rather than "division" in traditional pattern recognition. Some applications of BPR are surveyed, in which the results of BPR are much better than the results of Support Vector Machine. A novel neuron model, Hyper sausage neuron (HSN), is shown as a kind of covering units in BPR. The mathematical description of HSN is given and the 2-dimensional discriminant boundary of HSN is shown. In two special cases, in which samples are distributed in a line segment and a circle, both the HSN networks and RBF networks are used for covering. The results show that HSN networks act better than RBF networks in generalization, especially for small sample set, which are consonant with the results of the applications of BPR. And a brief explanation of the HSN networks' advantages in covering general distributed samples is also given.

Geometrical learning, descriptive geometry, and biomimetic pattern recognition

Studies on learning problems from geometry perspective have attracted an ever increasing attention in machine learning, leaded by achievements on information geometry. This paper proposes a different geometrical learning from the perspective of high-dimensional descriptive geometry. Geometrical properties of high-dimensional structures underlying a set of samples are learned via successive projections from the higher dimension to the lower dimension until two-dimensional Euclidean plane, under guidance of the established properties and theorems in high-dimensional descriptive geometry. Specifically, we introduce a hyper sausage like geometry shape for learning samples and provides a geometrical learning algorithm for specifying the hyper sausage shapes, which is then applied to biomimetic pattern recognition. Experimental results are presented to show that the proposed approach outperforms three types of support vector machines with either a three degree polynomial kernel or a radial basis function kernel, especially in the cases of high-dimensional samples of a finite size. (c) 2005 Elsevier B.V. All rights reserved.

Manifold covering theory in biomimetic pattern recognition

We describe a new model which is based on the concept of cognizing theory. The method identifies subsets of the data which are embedded in arbitrary oriented lower dimensional space. We definite manifold covering in biomimetic pattern recognition, and study its property. Furthermore, we propose this manifold covering algorithm based on Biomimetic Pattern Recognition. At last, the experimental results for face recognition demonstrates that the correct rejection rate of the test samples excluded in the classes of training samples is very high and effective.

Weak antilocalization and beating pattern in an InGaAs/InAlAs quantum well

We have observed the weak antilocalization (WAL) and beating SdH oscillation through magnetotransport measurements performed on a heavily delta-doped In0.52Al0.48As/In0.53Ga0.47As/In0.5Al0.48As single quantum well in an applied magnetic field up to 13 T and a temperature at 1.5 K. Both effects are caused by the strong Rashba spin-orbit (SO) coupling due to high structure inversion asymmetry (SIA). The Rashba SO coupling constant alpha and zerotield spin splitting Delta(0) are estimated and the obtained values are consistent from different analysis for this sample. (c) 2007 Elsevier Ltd. All rights reserved.

Research on continuous speech recognition with small vocabulary based on biomimetic pattern recognition

Based on biomimetic pattern recognition theory, we proposed a novel speaker-independent continuous speech keyword-spotting algorithm. Without endpoint detection and division, we can get the minimum distance curve between continuous speech samples and every keyword-training net through the dynamic searching to the feature-extracted continuous speech. Then we can count the number of the keywords by investigating the vale-value and the numbers of the vales in the curve. Experiments of small vocabulary continuous speech with various speaking rate have got good recognition results and proved the validity of the algorithm.

Cognitive models in biomimetic pattern cognition

We describe a new model which is based on the concept of cognizing theory. The method identifies subsets of the data which are embedded in arbitrary oriented lower dimensional space. We definite k-mean covering, and study its property. Covering subsets of points are repeatedly sampled to construct trial geometry space of various dimensions. The sampling corresponding to the feature space having the best cognition ability between a mode near zero and the rest is selected and the data points are partitioned on the basis of the best cognition ability. The repeated sampling then continues recursively on each block of the data. We propose this algorithm based on cognition models. The experimental results for face recognition demonstrate that the correct rejection rate of the test samples excluded in the classes of training samples is very high and effective.