A systematic approach in analyzing sustained oscillations in an NF-kB signal transduction pathway system

Oscillation phenomenon is very common in biological systems. It is crucial to study oscillatory behaviors to understand gene regulation functions. Model-based analysis in combination with experimental study provides a new and systematic way to investigate biological oscillations. The nuclear factor-kB (NF-kB) signaling is an important signaling pathway that is involved in a variety of cellular processes including immune response, inflammation, and apoptosis. Recent studies revealed damped oscillations of NF-kB activity both experimentally and computationally, etc. In this work, based on a differential equation model, bifurcation analysis was used to examine whether it was possible for this system to produce sustained oscillations (limit cycle oscillations) rather than damped oscillations. Both one- and two-parameter bifurcation analyses have been performed and it was found that certain conditions could possibly result in sustained oscillations of nuclear NF-kB activity. The parameter regimes corresponding to such oscillations were calculated with this method

Asymptotic properties of stochastic population dynamics

In this paper we stochastically perturb the classical Lotka{Volterra model x_ (t) = diag(x1(t); ; xn(t))[b + Ax(t)] into the stochastic dierential equation dx(t) = diag(x1(t); ; xn(t))[(b + Ax(t))dt + dw(t)]: The main aim is to study the asymptotic properties of the solution. It is known (see e.g. [3, 20]) if the noise is too large then the population may become extinct with probability one. Our main aim here is to nd out what happens if the noise is relatively small. In this paper we will establish some new asymptotic properties for the moments as well as for the sample paths of the solution. In particular, we will discuss the limit of the average in time of the sample paths

Noise suppresses or expresses exponential growth

In this paper we will show that noise can make a given system whose solutions grow exponentially become a new system whose solutions will grow at most polynomially. On the other hand, we will also show that noise can make a given system whose solutions are bounded become a new system whose solutions will grow exponentially. In other words, we reveal that the noise can suppress or expresses exponential growth

Population dynamical behavior of non-autonomous Lotka-Volterra competitive system with random perturbation

In this paper, we consider a non-autonomous stochastic Lotka-Volterra competitive system dxi(t) = xi(t)[(bi(t)¡ nPj=1aij (t)xj (t))dt+¾i(t)dBi(t)], where Bi(t) (i = 1; 2; ¢ ¢ ¢ ; n) are independent standard Brownian motions. Some dynamical properties are discussed and the su±cient conditions for the existence of global positive solutions, stochastic permanence, extinction as well as global attractivity are obtained. In addition, the limit of the average in time of the sample paths of solutions is estimated

Event Recognition Based on Deep Learning in Chinese Texts.

Event recognition is the most fundamental and critical task in event-based natural language processing systems. Existing event recognition methods based on rules and shallow neural networks have certain limitations. For example, extracting features using methods based on rules is difficult; methods based on shallow neural networks converge too quickly to a local minimum, resulting in low recognition precision. To address these problems, we propose the Chinese emergency event recognition model based on deep learning (CEERM). Firstly, we use a word segmentation system to segment sentences. According to event elements labeled in the CEC 2.0 corpus, we classify words into five categories: trigger words, participants, objects, time and location. Each word is vectorized according to the following six feature layers: part of speech, dependency grammar, length, location, distance between trigger word and core word and trigger word frequency. We obtain deep semantic features of words by training a feature vector set using a deep belief network (DBN), then analyze those features in order to identify trigger words by means of a back propagation neural network. Extensive testing shows that the CEERM achieves excellent recognition performance, with a maximum F-measure value of 85.17%. Moreover, we propose the dynamic-supervised DBN, which adds supervised fine-tuning to a restricted Boltzmann machine layer by monitoring its training performance. Test analysis reveals that the new DBN improves recognition performance and effectively controls the training time. Although the F-measure increases to 88.11%, the training time increases by only 25.35%

Sub-100-nm STIM imaging and PIXE quantification of rare earth elements in algae cells

10.1002/xrs.2480X-Ray Spectrometry424237-241XRSP

Status of end-of-life electronic product remanufacturing in China

Remanufacturing is an industrial process of returning used or worn-out products to an “as-new” functional state with an equal warranty to newly manufactured equivalents. In recent years, remanufacturing has become an emerging research area, a direction toward which China's economic development is tending as well. As the world's fastest-growing solid waste stream, the handling of end-of-life (EOL) electronic products has drawn global concern, and China is no exception. Although it is currently at a preliminary development stage, the remanufacturing of EOL electronic products is rapidly developing, supported by relevant policies. There is a critical need for properly structured management systems, especially when it comes to regulations and standards applicable to EOL electronic products—both at the stage of remanufacturing processes and end products. The status of EOL electronic product remanufacturing in China is reviewed from three perspectives: (1) policies, regulations, and standards; (2) research; and (3) industry. The scope for remanufactured electronic products hereby analyzed mainly covers the following products: cartridge; copier; and information technology (IT) servers. For these, there is an urgent development need of methods and/or tools enabling a standardized remanufacturability assessment. Consumers’ willingness to buy remanufactured products could also be promoted through the improvement and dissemination of knowledge and know-hows related to remanufacturing. The rapid advances in technology and products, and the falling prices of electronic products, could result in an adverse impact on remanufacturing